diff --git a/.env b/.env
new file mode 100644
index 0000000000000000000000000000000000000000..78ea8fbe1604c33e3976865d8977ae0fd073292e
--- /dev/null
+++ b/.env
@@ -0,0 +1,8 @@
+OPENBLAS_NUM_THREADS = 1
+no_proxy = localhost, 127.0.0.1, ::1
+
+# You can change the location of the model, etc. by changing here
+weight_root = weights
+weight_uvr5_root = uvr5_weights
+index_root = logs
+rmvpe_root = assets/rmvpe
diff --git a/.gitattributes b/.gitattributes
index a6344aac8c09253b3b630fb776ae94478aa0275b..8f5dd3e8e3be92c6c0cf9d9a7b8c7fe681c90238 100644
--- a/.gitattributes
+++ b/.gitattributes
@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+stftpitchshift filter=lfs diff=lfs merge=lfs -text
diff --git a/.gitignore b/.gitignore
new file mode 100644
index 0000000000000000000000000000000000000000..1cc60801f6d12ad4d01ccb1786860d8583c780f6
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1,49 @@
+.DS_Store
+__pycache__
+/TEMP
+/DATASETS
+/RUNTIME
+*.pyd
+hubert_base.pt
+.venv
+alexforkINSTALL.bat
+Changelog_CN.md
+Changelog_EN.md
+Changelog_KO.md
+difdep.py
+EasierGUI.py
+envfilescheck.bat
+export_onnx.py
+.vscode/
+export_onnx_old.py
+ffmpeg.exe
+ffprobe.exe
+Fixes/Launch_Tensorboard.bat
+Fixes/LOCAL_CREPE_FIX.bat
+Fixes/local_fixes.py
+Fixes/tensor-launch.py
+gui.py
+infer-web — backup.py
+infer-webbackup.py
+install_easy_dependencies.py
+install_easyGUI.bat
+installstft.bat
+Launch_Tensorboard.bat
+listdepend.bat
+LOCAL_CREPE_FIX.bat
+local_fixes.py
+oldinfer.py
+onnx_inference_demo.py
+Praat.exe
+requirementsNEW.txt
+rmvpe.pt
+rmvpe.onnx
+run_easiergui.bat
+tensor-launch.py
+values1.json
+使用需遵守的协议-LICENSE.txt
+!logs/
+
+logs/*
+logs/mute/0_gt_wavs/mute40k.spec.pt
+!logs/mute/
\ No newline at end of file
diff --git a/Applio_(Mangio_RVC_Fork).ipynb b/Applio_(Mangio_RVC_Fork).ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..4440de685158080ff706ee4099b0b7188851ceda
--- /dev/null
+++ b/Applio_(Mangio_RVC_Fork).ipynb
@@ -0,0 +1,169 @@
+{
+  "cells": [
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "cellView": "form",
+        "id": "izLwNF_8T1TK"
+      },
+      "outputs": [],
+      "source": [
+        "#@title <font color='#06ae56'>**🍏 Applio (Mangio-RVC-Fork)**</font>\n",
+        "import time\n",
+        "import os\n",
+        "import subprocess\n",
+        "import shutil\n",
+        "import threading\n",
+        "import base64\n",
+        "import threading\n",
+        "import time\n",
+        "from IPython.display import HTML, clear_output\n",
+        "\n",
+        "nosv_name1 = base64.b64decode(('ZXh0ZXJuYWxj').encode('ascii')).decode('ascii')\n",
+        "nosv_name2 = base64.b64decode(('b2xhYmNvZGU=').encode('ascii')).decode('ascii')\n",
+        "guebui = base64.b64decode(('V2U=').encode('ascii')).decode('ascii')\n",
+        "guebui2 = base64.b64decode(('YlVJ').encode('ascii')).decode('ascii')\n",
+        "pbestm = base64.b64decode(('cm12cGU=').encode('ascii')).decode('ascii')\n",
+        "tryre = base64.b64decode(('UmV0cmlldmFs').encode('ascii')).decode('ascii')\n",
+        "\n",
+        "xdsame = '/content/'+ tryre +'-based-Voice-Conversion-' + guebui + guebui2 +'/'\n",
+        "\n",
+        "collapsible_section = \"\"\"\n",
+        "<br>\n",
+        "<br>\n",
+        "<details style=\"border: 1px solid #ddd; border-radius: 5px; padding: 10px; margin-bottom: 10px;\">\n",
+        "    <summary open style=\"font-weight: bold; cursor: pointer;\">🚀 Click to learn more about Applio</summary>\n",
+        "    <div style=\"margin-left: 20px;\">\n",
+        "        <ul>\n",
+        "            <li><a href=\"https://github.com/Mangio621/Mangio-RVC-Fork\" style=\"color: #06ae56;\">Mangio-RVC-Fork</a> - Source of inspiration and base for this improved code, special thanks to the developers.</li>\n",
+        "            <li><a href=\"https://github.com/Anjok07/ultimatevocalremovergui\" style=\"color: #06ae56;\">UltimateVocalRemover</a> - Used for voice and instrument separation.</li>\n",
+        "            <li>Vidal, Blaise & Aitron - Contributors to the Applio version.</li>\n",
+        "            <li>kalomaze - Creator of external scripts that help the functioning of Applio.</li>\n",
+        "        </ul>\n",
+        "        <p style=\"color: #fff;\">Join and contribute to the project on <a href=\"https://github.com/IAHispano/Applio-RVC-Fork\" style=\"color: #06ae56;\">our GitHub repository</a>.</p>\n",
+        "    </div>\n",
+        "</details>\n",
+        "<br>\n",
+        "<button style=\"font-weight: bold; cursor: pointer; background-color: #06ae56; color: white; border: 1px solid #fff; border-radius: 4px; padding: 10px 20px; text-decoration: none;\" onclick=\"window.open('https://discord.gg/IAHispano', '_blank')\">🍏 Join our support Discord server (IA Hispano)</button>\n",
+        "<br>\n",
+        "<br>\n",
+        "\"\"\"\n",
+        "#@markdown **Settings:**\n",
+        "ForceUpdateDependencies = True\n",
+        "ForceNoMountDrive = False\n",
+        "#@markdown Restore your backup from Google Drive.\n",
+        "LoadBackupDrive = False #@param{type:\"boolean\"}\n",
+        "#@markdown Make regular backups of your model's training.\n",
+        "AutoBackups = True #@param{type:\"boolean\"}\n",
+        "if not os.path.exists(xdsame):\n",
+        " current_path = os.getcwd()\n",
+        " shutil.rmtree('/content/')\n",
+        " os.makedirs('/content/', exist_ok=True)\n",
+        "\n",
+        " os.chdir(current_path)\n",
+        " !git clone https://github.com/IAHispano/$nosv_name1$nosv_name2 /content/$tryre-based-Voice-Conversion-$guebui$guebui2/utils\n",
+        " clear_output()\n",
+        "\n",
+        " os.chdir(xdsame)\n",
+        " from utils.dependency import *\n",
+        " from utils.clonerepo_experimental import *\n",
+        " os.chdir(\"..\")\n",
+        "\n",
+        "\n",
+        "\n",
+        " setup_environment(ForceUpdateDependencies, ForceNoMountDrive)\n",
+        " clone_repository(True)\n",
+        "\n",
+        " !wget https://huggingface.co/lj1995/VoiceConversion$guebui$guebui2/resolve/main/rmvpe.pt -P /content/Retrieval-based-Voice-Conversion-$guebui$guebui2/\n",
+        " clear_output()\n",
+        "\n",
+        "base_path = \"/content/Retrieval-based-Voice-Conversion-$guebui$guebui2/\"\n",
+        "clear_output()\n",
+        "\n",
+        "\n",
+        "\n",
+        "from utils import backups\n",
+        "\n",
+        "LOGS_FOLDER = xdsame + '/logs'\n",
+        "if not os.path.exists(LOGS_FOLDER):\n",
+        "    os.makedirs(LOGS_FOLDER)\n",
+        "    clear_output()\n",
+        "\n",
+        "WEIGHTS_FOLDER = xdsame + '/logs' + '/weights'\n",
+        "if not os.path.exists(WEIGHTS_FOLDER):\n",
+        "    os.makedirs(WEIGHTS_FOLDER)\n",
+        "    clear_output()\n",
+        "\n",
+        "others_FOLDER = xdsame + '/audio-others'\n",
+        "if not os.path.exists(others_FOLDER):\n",
+        "    os.makedirs(others_FOLDER)\n",
+        "    clear_output()\n",
+        "\n",
+        "audio_outputs_FOLDER = xdsame + '/audio-outputs'\n",
+        "if not os.path.exists(audio_outputs_FOLDER):\n",
+        "    os.makedirs(audio_outputs_FOLDER)\n",
+        "    clear_output()\n",
+        "\n",
+        "if LoadBackupDrive:\n",
+        "    backups.import_google_drive_backup()\n",
+        "    clear_output()\n",
+        "\n",
+        "#@markdown Choose the language in which you want the interface to be available.\n",
+        "i18n_path = xdsame + 'i18n.py'\n",
+        "i18n_new_path = xdsame + 'utils/i18n.py'\n",
+        "try:\n",
+        "    if os.path.exists(i18n_path) and os.path.exists(i18n_new_path):\n",
+        "        shutil.move(i18n_new_path, i18n_path)\n",
+        "\n",
+        "    SelectedLanguage = \"en_US\" #@param [\"es_ES\", \"en_US\", \"zh_CN\", \"ar_AR\", \"id_ID\", \"pt_PT\", \"ru_RU\", \"ur_UR\", \"tr_TR\", \"it_IT\", \"de_DE\"]\n",
+        "    new_language_line = '            language = \"' + SelectedLanguage + '\"\\n'\n",
+        "#@markdown <a href=\"https://discord.gg/iahispano\"><font>If you need more help, feel free to join our official Discord server!</font></a>\n",
+        "    with open(i18n_path, 'r') as file:\n",
+        "        lines = file.readlines()\n",
+        "\n",
+        "    with open(i18n_path, 'w') as file:\n",
+        "        for index, line in enumerate(lines):\n",
+        "            if index == 14:\n",
+        "                file.write(new_language_line)\n",
+        "            else:\n",
+        "                file.write(line)\n",
+        "\n",
+        "except FileNotFoundError:\n",
+        "    print(\"Translation couldn't be applied successfully. Please restart the environment and run the cell again.\")\n",
+        "\n",
+        "def start_web_server():\n",
+        "    %cd /content/$tryre-based-Voice-Conversion-$guebui$guebui2\n",
+        "    %load_ext tensorboard\n",
+        "    clear_output()\n",
+        "    %tensorboard --logdir /content/$tryre-based-Voice-Conversion-$guebui$guebui2/logs\n",
+        "    !mkdir -p /content/$tryre-based-Voice-Conversion-$guebui$guebui2/audios\n",
+        "    display(HTML(collapsible_section))\n",
+        "    !python3 infer-web.py --colab --pycmd python3\n",
+        "\n",
+        "if AutoBackups:\n",
+        "  web_server_thread = threading.Thread(target=start_web_server)\n",
+        "  web_server_thread.start()\n",
+        "  backups.backup_files()\n",
+        "\n",
+        "else:\n",
+        "  start_web_server()"
+      ]
+    }
+  ],
+  "metadata": {
+    "accelerator": "GPU",
+    "colab": {
+      "provenance": []
+    },
+    "kernelspec": {
+      "display_name": "Python 3",
+      "name": "python3"
+    },
+    "language_info": {
+      "name": "python"
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 0
+}
diff --git a/Dockerfile b/Dockerfile
new file mode 100644
index 0000000000000000000000000000000000000000..b81f131c79cc585012b28002f4916491e85f3a33
--- /dev/null
+++ b/Dockerfile
@@ -0,0 +1,29 @@
+# syntax=docker/dockerfile:1
+
+FROM python:3.10-bullseye
+
+EXPOSE 7865
+
+WORKDIR /app
+
+COPY . .
+
+RUN apt update && apt install -y -qq ffmpeg aria2 && apt clean
+
+RUN pip3 install --no-cache-dir -r requirements.txt
+
+RUN aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained_v2/D40k.pth -d assets/pretrained_v2/ -o D40k.pth
+RUN aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained_v2/G40k.pth -d assets/pretrained_v2/ -o G40k.pth
+RUN aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained_v2/f0D40k.pth -d assets/pretrained_v2/ -o f0D40k.pth
+RUN aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained_v2/f0G40k.pth -d assets/pretrained_v2/ -o f0G40k.pth
+
+RUN aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/uvr5_weights/HP2-人声vocals+非人声instrumentals.pth -d assets/uvr5_weights/ -o HP2-人声vocals+非人声instrumentals.pth
+RUN aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/uvr5_weights/HP5-主旋律人声vocals+其他instrumentals.pth -d assets/uvr5_weights/ -o HP5-主旋律人声vocals+其他instrumentals.pth
+
+RUN aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/hubert_base.pt -d assets/hubert -o hubert_base.pt
+
+RUN aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/rmvpe.pt -d assets/hubert -o rmvpe.pt
+
+VOLUME [ "/app/weights", "/app/opt" ]
+
+CMD ["python3", "infer-web.py"]
\ No newline at end of file
diff --git a/Fixes/local_fixes.py b/Fixes/local_fixes.py
new file mode 100644
index 0000000000000000000000000000000000000000..8a418076eee6f65fe06eb0f607061796b839c1ee
--- /dev/null
+++ b/Fixes/local_fixes.py
@@ -0,0 +1,136 @@
+import os
+import sys
+import time
+import shutil
+import requests
+import zipfile
+
+def insert_new_line(file_name, line_to_find, text_to_insert):
+    lines = []
+    with open(file_name, 'r', encoding='utf-8') as read_obj:
+        lines = read_obj.readlines()
+    already_exists = False
+    with open(file_name + '.tmp', 'w', encoding='utf-8') as write_obj:
+        for i in range(len(lines)):
+            write_obj.write(lines[i])
+            if lines[i].strip() == line_to_find:
+                # If next line exists and starts with sys.path.append, skip
+                if i+1 < len(lines) and lines[i+1].strip().startswith("sys.path.append"):
+                    print('It was already fixed! Skip adding a line...')
+                    already_exists = True
+                    break
+                else:
+                    write_obj.write(text_to_insert + '\n')
+    # If no existing sys.path.append line was found, replace the original file
+    if not already_exists:
+        os.replace(file_name + '.tmp', file_name)
+        return True
+    else:
+        # If existing line was found, delete temporary file
+        os.remove(file_name + '.tmp')
+        return False
+
+def replace_in_file(file_name, old_text, new_text):
+    with open(file_name, 'r', encoding='utf-8') as file:
+        file_contents = file.read()
+
+    if old_text in file_contents:
+        file_contents = file_contents.replace(old_text, new_text)
+        with open(file_name, 'w', encoding='utf-8') as file:
+            file.write(file_contents)
+            return True
+
+    return False
+
+if __name__ == "__main__":
+    current_path = os.getcwd()
+    file_name = os.path.join(current_path, "infer", "modules", "train", "extract", "extract_f0_print.py")
+    line_to_find = 'import numpy as np, logging'
+    text_to_insert = "sys.path.append(r'" + current_path + "')"
+    
+
+    success_1 = insert_new_line(file_name, line_to_find, text_to_insert)
+    if success_1:
+        print('The first operation was successful!')
+    else:
+        print('He skipped the first operation because it was already fixed!')
+
+    file_name = 'infer-web.py'
+    old_text = 'with gr.Blocks(theme=gr.themes.Soft()) as app:'
+    new_text = 'with gr.Blocks() as app:'
+
+    success_2 = replace_in_file(file_name, old_text, new_text)
+    if success_2:
+        print('The second operation was successful!')
+    else:
+        print('The second operation was omitted because it was already fixed!')
+
+    print('Local corrections successful! You should now be able to infer and train locally in Applio RVC Fork.')
+    
+    time.sleep(5)
+
+def find_torchcrepe_directory(directory):
+    """
+    Recursively searches for the topmost folder named 'torchcrepe' within a directory.
+    Returns the path of the directory found or None if none is found.
+    """
+    for root, dirs, files in os.walk(directory):
+        if 'torchcrepe' in dirs:
+            return os.path.join(root, 'torchcrepe')
+    return None
+
+def download_and_extract_torchcrepe():
+    url = 'https://github.com/maxrmorrison/torchcrepe/archive/refs/heads/master.zip'
+    temp_dir = 'temp_torchcrepe'
+    destination_dir = os.getcwd()
+
+    try:
+        torchcrepe_dir_path = os.path.join(destination_dir, 'torchcrepe')
+
+        if os.path.exists(torchcrepe_dir_path):
+            print("Skipping the torchcrepe download. The folder already exists.")
+            return
+
+        # Download the file
+        print("Starting torchcrepe download...")
+        response = requests.get(url)
+
+        # Raise an error if the GET request was unsuccessful
+        response.raise_for_status()
+        print("Download completed.")
+
+        # Save the downloaded file
+        zip_file_path = os.path.join(temp_dir, 'master.zip')
+        os.makedirs(temp_dir, exist_ok=True)
+        with open(zip_file_path, 'wb') as file:
+            file.write(response.content)
+        print(f"Zip file saved to {zip_file_path}")
+
+        # Extract the zip file
+        print("Extracting content...")
+        with zipfile.ZipFile(zip_file_path, 'r') as zip_file:
+            zip_file.extractall(temp_dir)
+        print("Extraction completed.")
+
+        # Locate the torchcrepe folder and move it to the destination directory
+        torchcrepe_dir = find_torchcrepe_directory(temp_dir)
+        if torchcrepe_dir:
+            shutil.move(torchcrepe_dir, destination_dir)
+            print(f"Moved the torchcrepe directory to {destination_dir}!")
+        else:
+            print("The torchcrepe directory could not be located.")
+
+    except Exception as e:
+        print("Torchcrepe not successfully downloaded", e)
+
+    # Clean up temporary directory
+    if os.path.exists(temp_dir):
+        shutil.rmtree(temp_dir)
+
+# Run the function
+download_and_extract_torchcrepe()
+
+temp_dir = 'temp_torchcrepe'
+
+if os.path.exists(temp_dir):
+    shutil.rmtree(temp_dir)
diff --git a/Fixes/tensor-launch.py b/Fixes/tensor-launch.py
new file mode 100644
index 0000000000000000000000000000000000000000..cd4ec997fb4b1338d7f29912987865899281b083
--- /dev/null
+++ b/Fixes/tensor-launch.py
@@ -0,0 +1,15 @@
+import threading
+import time
+from tensorboard import program
+import os
+
+log_path = "logs"
+
+if __name__ == "__main__":
+    tb = program.TensorBoard()
+    tb.configure(argv=[None, '--logdir', log_path])
+    url = tb.launch()
+    print(f'Tensorboard can be accessed at: {url}')
+
+    while True:
+        time.sleep(600)  # Keep the main thread running
\ No newline at end of file
diff --git a/LICENSE b/LICENSE
new file mode 100644
index 0000000000000000000000000000000000000000..c441961e22604dff6d32160a20972819efdd3872
--- /dev/null
+++ b/LICENSE
@@ -0,0 +1,59 @@
+MIT License
+
+Copyright (c) 2023 liujing04
+Copyright (c) 2023 源文雨
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
+
+The licenses for related libraries are as follows:
+
+ContentVec
+https://github.com/auspicious3000/contentvec/blob/main/LICENSE
+MIT License
+
+VITS
+https://github.com/jaywalnut310/vits/blob/main/LICENSE
+MIT License
+
+HIFIGAN
+https://github.com/jik876/hifi-gan/blob/master/LICENSE
+MIT License
+
+gradio
+https://github.com/gradio-app/gradio/blob/main/LICENSE
+Apache License 2.0
+
+ffmpeg
+https://github.com/FFmpeg/FFmpeg/blob/master/COPYING.LGPLv3
+https://github.com/BtbN/FFmpeg-Builds/releases/download/autobuild-2021-02-28-12-32/ffmpeg-n4.3.2-160-gfbb9368226-win64-lgpl-4.3.zip
+LPGLv3 License
+MIT License
+
+ultimatevocalremovergui
+https://github.com/Anjok07/ultimatevocalremovergui/blob/master/LICENSE
+https://github.com/yang123qwe/vocal_separation_by_uvr5
+MIT License
+
+audio-slicer
+https://github.com/openvpi/audio-slicer/blob/main/LICENSE
+MIT License
+
+PySimpleGUI
+https://github.com/PySimpleGUI/PySimpleGUI/blob/master/license.txt
+LPGLv3 License
\ No newline at end of file
diff --git a/LazyImport.py b/LazyImport.py
new file mode 100644
index 0000000000000000000000000000000000000000..5bdb05ddd5a546a43adba7274b4c3465bb77f2f5
--- /dev/null
+++ b/LazyImport.py
@@ -0,0 +1,13 @@
+from importlib.util import find_spec, LazyLoader, module_from_spec
+from sys import modules
+
+def lazyload(name):
+    if name in modules:
+        return modules[name]
+    else:
+        spec = find_spec(name)
+        loader = LazyLoader(spec.loader)
+        module = module_from_spec(spec)
+        modules[name] = module
+        loader.exec_module(module)
+        return module
\ No newline at end of file
diff --git a/MDX-Net_Colab.ipynb b/MDX-Net_Colab.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..a884caf08a9f7b9747346f5def57d24b7258f5b8
--- /dev/null
+++ b/MDX-Net_Colab.ipynb
@@ -0,0 +1,524 @@
+{
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "wX9xzLur4tus"
+      },
+      "source": [
+        "# MDX-Net Colab\n",
+        "<div style=\"display:flex; align-items:center; font-size: 16px;\">\n",
+        "  <img src=\"https://github.githubassets.com/pinned-octocat.svg\" alt=\"icon1\" style=\"margin-right:10px; height: 20px;\" width=\"1.5%\">\n",
+        "  <span>Trained models provided in this notebook are from <a href=\"https://github.com/Anjok07\">UVR-GUI</a>.</span>\n",
+        "</div>\n",
+        "<div style=\"display:flex; align-items:center; font-size: 16px;\">\n",
+        "  <img src=\"https://github.com/Anjok07/ultimatevocalremovergui/raw/master/gui_data/img/GUI-Icon.ico\" alt=\"icon2\" style=\"margin-right:10px; height: 20px;margin-top:10px\" width=\"1.5%\">\n",
+        "  <span>OFFICIAL UVR GITHUB PAGE: <a href=\"https://github.com/Anjok07/ultimatevocalremovergui\">here</a>.</span>\n",
+        "</div>\n",
+        "<div style=\"display:flex; align-items:center; font-size: 16px;\">\n",
+        "  <img src=\"https://avatars.githubusercontent.com/u/24620594\" alt=\"icon3\" style=\"margin-right:10px; height: 20px;\" width=\"1.5%\">\n",
+        "  <span>OFFICIAL CLI Version: <a href=\"https://github.com/tsurumeso/vocal-remover\">here</a>.</span>\n",
+        "</div>\n",
+        "<div style=\"display:flex; align-items:center; font-size: 16px;\">\n",
+        "  <img src=\"https://icons.getbootstrap.com/assets/icons/discord.svg\" alt=\"icon4\" style=\"margin-right:10px; height: 20px;\" width=\"1.5%\">\n",
+        "  <span>Join our <a href=\"https://cutt.ly/0TcDjmo\">Discord server</a>!</span>\n",
+        "</div>\n",
+        "<sup><br>Ultimate Vocal Remover (unofficial)</sup>\n",
+        "<sup><br>MDX-Net by <a href=\"https://github.com/kuielab\">kuielab</a> and adapted for Colaboratory by <a href=\"https://www.youtube.com/channel/UC0NiSV1jLMH-9E09wiDVFYw\">AudioHacker</a>.</sup>\n",
+        "\n",
+        "<sup><br>Your support means a lot to me. If you enjoy my work, please consider buying me a ko-fi:<br></sup>\n",
+        "[![ko-fi](https://ko-fi.com/img/githubbutton_sm.svg)](https://ko-fi.com/X8X6M8FR0)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "3J69RV7G8ocb",
+        "cellView": "form"
+      },
+      "outputs": [],
+      "source": [
+        "import json\n",
+        "import os\n",
+        "import os.path\n",
+        "import gc\n",
+        "import psutil\n",
+        "import requests\n",
+        "import subprocess\n",
+        "import glob\n",
+        "import time\n",
+        "import logging\n",
+        "import sys\n",
+        "from bs4 import BeautifulSoup\n",
+        "from google.colab import drive, files, output\n",
+        "from IPython.display import Audio, display\n",
+        "\n",
+        "if \"first_cell_ran\" in locals():\n",
+        "    print(\"You've ran this cell for this session. No need to run it again.\\nif you think something went wrong or you want to change mounting path, restart the runtime.\")\n",
+        "else:\n",
+        "    print('Setting up... please wait around 1-2 minute(s).')\n",
+        "\n",
+        "    branch = \"https://github.com/NaJeongMo/Colab-for-MDX_B\"\n",
+        "\n",
+        "    model_params = \"https://raw.githubusercontent.com/TRvlvr/application_data/main/mdx_model_data/model_data.json\"\n",
+        "    _Models = \"https://github.com/TRvlvr/model_repo/releases/download/all_public_uvr_models/\"\n",
+        "    # _models = \"https://pastebin.com/raw/jBzYB8vz\"\n",
+        "    _models = \"https://raw.githubusercontent.com/TRvlvr/application_data/main/filelists/download_checks.json\"\n",
+        "    stem_naming = \"https://pastebin.com/raw/mpH4hRcF\"\n",
+        "    arl_check_endpoint = 'https://dz.doubledouble.top/check' # param: arl?=<>\n",
+        "\n",
+        "    file_folder = \"Colab-for-MDX_B\"\n",
+        "\n",
+        "    model_ids = requests.get(_models).json()\n",
+        "    model_ids = model_ids[\"mdx_download_list\"].values()\n",
+        "\n",
+        "    model_params = requests.get(model_params).json()\n",
+        "    stem_naming = requests.get(stem_naming).json()\n",
+        "\n",
+        "    os.makedirs(\"tmp_models\", exist_ok=True)\n",
+        "\n",
+        "    # @markdown If you don't wish to mount google drive, uncheck this box.\n",
+        "    MountDrive = True  # @param{type:\"boolean\"}\n",
+        "    # @markdown The path for the drive to be mounted: Please be cautious when modifying this as it can cause issues if not done properly.\n",
+        "    mounting_path = \"/content/drive/MyDrive\"  # @param [\"snippets:\",\"/content/drive/MyDrive\",\"/content/drive/Shareddrives/<your shared drive name>\", \"/content/drive/Shareddrives/Shared Drive\"]{allow-input: true}\n",
+        "    # @markdown Force update and disregard local changes: discards all local modifications in your repository, effectively replacing all files with the versions from the original commit.\n",
+        "    force_update = False  # @param{type:\"boolean\"}\n",
+        "    # @markdown Auto Update (does not discard your changes)\n",
+        "    auto_update = True  # @param{type:\"boolean\"}\n",
+        "\n",
+        "\n",
+        "    reqs_apt = []  # !sudo apt-get install\n",
+        "    reqs_pip = [\"librosa>=0.6.3,<0.9\", \"onnxruntime_gpu\", \"deemix\", \"yt_dlp\"]  # pip3 install\n",
+        "\n",
+        "    class hide_opt:  # hide outputs\n",
+        "        def __enter__(self):\n",
+        "            self._original_stdout = sys.stdout\n",
+        "            sys.stdout = open(os.devnull, \"w\")\n",
+        "\n",
+        "        def __exit__(self, exc_type, exc_val, exc_tb):\n",
+        "            sys.stdout.close()\n",
+        "            sys.stdout = self._original_stdout\n",
+        "\n",
+        "    def get_size(bytes, suffix=\"B\"):  # read ram\n",
+        "        global svmem\n",
+        "        factor = 1024\n",
+        "        for unit in [\"\", \"K\", \"M\", \"G\", \"T\", \"P\"]:\n",
+        "            if bytes < factor:\n",
+        "                return f\"{bytes:.2f}{unit}{suffix}\"\n",
+        "            bytes /= factor\n",
+        "        svmem = psutil.virtual_memory()\n",
+        "\n",
+        "\n",
+        "    print('installing requirements...',end=' ')\n",
+        "    with hide_opt():\n",
+        "        for x in reqs_apt:\n",
+        "            subprocess.run([\"sudo\", \"apt-get\", \"install\", x])\n",
+        "        for x in reqs_pip:\n",
+        "            subprocess.run([\"python3\", \"-m\", \"pip\", \"install\", x])\n",
+        "    print('done')\n",
+        "\n",
+        "    def install_or_mount_drive():\n",
+        "        print(\n",
+        "            \"Please log in to your account by following the prompts in the pop-up tab.\\nThis step is necessary to install the files to your Google Drive.\\nIf you have any concerns about the safety of this notebook, you can choose not to mount your drive by unchecking the \\\"MountDrive\\\" checkbox.\"\n",
+        "        )\n",
+        "        drive.mount(\"/content/drive\", force_remount=True)\n",
+        "        os.chdir(mounting_path)\n",
+        "        # check if previous installation is done\n",
+        "        if os.path.exists(os.path.join(mounting_path, file_folder)):\n",
+        "            # update checking\n",
+        "            os.chdir(file_folder)\n",
+        "\n",
+        "            if force_update:\n",
+        "                print('Force updating...')\n",
+        "\n",
+        "                commands = [\n",
+        "                    [\"git\", \"pull\"],\n",
+        "                    [\"git\", \"checkout\", \"--\", \".\"],\n",
+        "                ]\n",
+        "\n",
+        "                for cmd in commands:\n",
+        "                    subprocess.run(cmd)\n",
+        "\n",
+        "            elif auto_update:\n",
+        "                print('Checking for updates...')\n",
+        "                commands = [\n",
+        "                    [\"git\", \"pull\"],\n",
+        "                ]\n",
+        "\n",
+        "                for cmd in commands:\n",
+        "                    subprocess.run(cmd)\n",
+        "        else:\n",
+        "            subprocess.run([\"git\", \"clone\", \"https://github.com/NaJeongMo/Colab-for-MDX_B.git\"])\n",
+        "            os.chdir(file_folder)\n",
+        "\n",
+        "    def use_uvr_without_saving():\n",
+        "        global mounting_path\n",
+        "        print(\"Notice: files won't be saved to personal drive.\")\n",
+        "        print(f\"Downloading {file_folder}...\", end=\" \")\n",
+        "        mounting_path = \"/content\"\n",
+        "        with hide_opt():\n",
+        "            os.chdir(mounting_path)\n",
+        "            subprocess.run([\"git\", \"clone\", \"https://github.com/NaJeongMo/Colab-for-MDX_B.git\"])\n",
+        "            os.chdir(file_folder)\n",
+        "\n",
+        "    if MountDrive:\n",
+        "        install_or_mount_drive()\n",
+        "    else:\n",
+        "        use_uvr_without_saving()\n",
+        "    print(\"done!\")\n",
+        "    if not os.path.exists(\"tracks\"):\n",
+        "        os.mkdir(\"tracks\")\n",
+        "\n",
+        "    print('Importing required libraries...',end=' ')\n",
+        "\n",
+        "    import os\n",
+        "    import mdx\n",
+        "    import librosa\n",
+        "    import torch\n",
+        "    import soundfile as sf\n",
+        "    import numpy as np\n",
+        "    import yt_dlp\n",
+        "\n",
+        "    from deezer import Deezer\n",
+        "    from deezer import TrackFormats\n",
+        "    import deemix\n",
+        "    from deemix.settings import load as loadSettings\n",
+        "    from deemix.downloader import Downloader\n",
+        "    from deemix import generateDownloadObject\n",
+        "\n",
+        "    logger = logging.getLogger(\"yt_dlp\")\n",
+        "    logger.setLevel(logging.ERROR)\n",
+        "\n",
+        "    def id_to_ptm(mkey):\n",
+        "        if mkey in model_ids:\n",
+        "            mpath = f\"/content/tmp_models/{mkey}\"\n",
+        "            if not os.path.exists(f'/content/tmp_models/{mkey}'):\n",
+        "                print('Downloading model...',end=' ')\n",
+        "                subprocess.run(\n",
+        "                    [\"wget\", _Models+mkey, \"-O\", mpath]\n",
+        "                )\n",
+        "                print(f'saved to {mpath}')\n",
+        "                # get_ipython().system(f'gdown {model_id} -O /content/tmp_models/{mkey}')\n",
+        "                return mpath\n",
+        "            else:\n",
+        "                return mpath\n",
+        "        else:\n",
+        "            mpath = f'models/{mkey}'\n",
+        "            return mpath\n",
+        "\n",
+        "    def prepare_mdx(custom_param=False, dim_f=None, dim_t=None, n_fft=None, stem_name=None, compensation=None):\n",
+        "        device = torch.device('cuda:0') if torch.cuda.is_available() else torch.device('cpu')\n",
+        "        if custom_param:\n",
+        "            assert not (dim_f is None or dim_t is None or n_fft is None or compensation is None), 'Custom parameter selected, but incomplete parameters are provided.'\n",
+        "            mdx_model = mdx.MDX_Model(\n",
+        "                device,\n",
+        "                dim_f = dim_f,\n",
+        "                dim_t = dim_t,\n",
+        "                n_fft = n_fft,\n",
+        "                stem_name=stem_name,\n",
+        "                compensation=compensation\n",
+        "            )\n",
+        "        else:\n",
+        "            model_hash = mdx.MDX.get_hash(onnx)\n",
+        "            if model_hash in model_params:\n",
+        "                mp = model_params.get(model_hash)\n",
+        "                mdx_model = mdx.MDX_Model(\n",
+        "                    device,\n",
+        "                    dim_f = mp[\"mdx_dim_f_set\"],\n",
+        "                    dim_t = 2**mp[\"mdx_dim_t_set\"],\n",
+        "                    n_fft = mp[\"mdx_n_fft_scale_set\"],\n",
+        "                    stem_name=mp[\"primary_stem\"],\n",
+        "                    compensation=compensation if not custom_param and compensation is not None else mp[\"compensate\"]\n",
+        "                )\n",
+        "        return mdx_model\n",
+        "\n",
+        "    def run_mdx(onnx, mdx_model,filename,diff=False,suffix=None,diff_suffix=None, denoise=False, m_threads=1):\n",
+        "        mdx_sess = mdx.MDX(onnx,mdx_model)\n",
+        "        print(f\"Processing: {filename}\")\n",
+        "        wave, sr = librosa.load(filename,mono=False, sr=44100)\n",
+        "        # normalizing input wave gives better output\n",
+        "        peak = max(np.max(wave), abs(np.min(wave)))\n",
+        "        wave /= peak\n",
+        "        if denoise:\n",
+        "            wave_processed = -(mdx_sess.process_wave(-wave, m_threads)) + (mdx_sess.process_wave(wave, m_threads))\n",
+        "            wave_processed *= 0.5\n",
+        "        else:\n",
+        "            wave_processed = mdx_sess.process_wave(wave, m_threads)\n",
+        "        # return to previous peak\n",
+        "        wave_processed *= peak\n",
+        "\n",
+        "        stem_name = mdx_model.stem_name if suffix is None else suffix # use suffix if provided\n",
+        "        save_path = f\"{os.path.basename(os.path.splitext(filename)[0])}_{stem_name}.wav\"\n",
+        "        save_path = os.path.join(\n",
+        "                'separated',\n",
+        "                save_path\n",
+        "            )\n",
+        "        sf.write(\n",
+        "            save_path,\n",
+        "            wave_processed.T,\n",
+        "            sr\n",
+        "        )\n",
+        "\n",
+        "        print(f'done, saved to: {save_path}')\n",
+        "\n",
+        "        if diff:\n",
+        "            diff_stem_name = stem_naming.get(stem_name) if diff_suffix is None else diff_suffix # use suffix if provided\n",
+        "            stem_name = f\"{stem_name}_diff\" if diff_stem_name is None else diff_stem_name\n",
+        "            save_path = f\"{os.path.basename(os.path.splitext(filename)[0])}_{stem_name}.wav\"\n",
+        "            save_path = os.path.join(\n",
+        "                    'separated',\n",
+        "                    save_path\n",
+        "                )\n",
+        "            sf.write(\n",
+        "                save_path,\n",
+        "                (-wave_processed.T*mdx_model.compensation)+wave.T,\n",
+        "                sr\n",
+        "            )\n",
+        "            print(f'invert done, saved to: {save_path}')\n",
+        "        del mdx_sess, wave_processed, wave\n",
+        "        gc.collect()\n",
+        "\n",
+        "    def is_valid_url(url):\n",
+        "        import re\n",
+        "        regex = re.compile(\n",
+        "            r'^https?://'\n",
+        "            r'(?:(?:[A-Z0-9](?:[A-Z0-9-]{0,61}[A-Z0-9])?\\.)+[A-Z]{2,6}\\.?|'\n",
+        "            r'localhost|'\n",
+        "            r'\\d{1,3}\\.\\d{1,3}\\.\\d{1,3}\\.\\d{1,3})'\n",
+        "            r'(?::\\d+)?'\n",
+        "            r'(?:/?|[/?]\\S+)$', re.IGNORECASE)\n",
+        "        return url is not None and regex.search(url)\n",
+        "\n",
+        "    def download_deezer(link, arl, fmt='FLAC'):\n",
+        "        match fmt:\n",
+        "            case 'FLAC':\n",
+        "                bitrate = TrackFormats.FLAC\n",
+        "            case 'MP3_320':\n",
+        "                bitrate = TrackFormats.MP3_320\n",
+        "            case 'MP3_128':\n",
+        "                bitrate = TrackFormats.MP3_128\n",
+        "            case _:\n",
+        "                bitrate = TrackFormats.MP3_128\n",
+        "\n",
+        "        dz = Deezer()\n",
+        "        settings = loadSettings('dz_config')\n",
+        "        settings['downloadLocation'] = './tracks'\n",
+        "        if not dz.login_via_arl(arl.strip()):\n",
+        "            raise Exception('Error while logging in with provided ARL.')\n",
+        "        downloadObject = generateDownloadObject(dz, link, bitrate)\n",
+        "        print(f'Downloading {downloadObject.type}: \"{downloadObject.title}\" by {downloadObject.artist}...',end=' ',flush=True)\n",
+        "        Downloader(dz, downloadObject, settings).start()\n",
+        "        print(f'done.')\n",
+        "\n",
+        "        path_to_audio = []\n",
+        "        for file in downloadObject.files:\n",
+        "            path_to_audio.append(file[\"path\"])\n",
+        "\n",
+        "        return path_to_audio\n",
+        "\n",
+        "    def download_link(url):\n",
+        "        ydl_opts = {\n",
+        "            'format': 'bestvideo+bestaudio/best',\n",
+        "            'outtmpl': '%(title)s.%(ext)s',\n",
+        "            'nocheckcertificate': True,\n",
+        "            'ignoreerrors': True,\n",
+        "            'no_warnings': True,\n",
+        "            'extractaudio': True,\n",
+        "        }\n",
+        "        with yt_dlp.YoutubeDL(ydl_opts) as ydl:\n",
+        "            result = ydl.extract_info(url, download=True)\n",
+        "            download_path = ydl.prepare_filename(result)\n",
+        "        return download_path\n",
+        "\n",
+        "    print('finished setting up!')\n",
+        "    first_cell_ran = True"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "4hd1TzEGCiRo",
+        "cellView": "form"
+      },
+      "outputs": [],
+      "source": [
+        "if 'first_cell_ran' in locals():\n",
+        "    os.chdir(mounting_path + '/' + file_folder + '/')\n",
+        "    #parameter markdowns-----------------\n",
+        "    #@markdown ### Input files\n",
+        "    #@markdown track filename: Upload your songs to the \"tracks\" folder. You may provide multiple links/files by spliting them with ;\n",
+        "    filename = \"https://deezer.com/album/281108671\" #@param {type:\"string\"}\n",
+        "    #@markdown onnx model (if you have your own model, upload it in models folder)\n",
+        "    onnx = \"UVR-MDX-NET-Inst_HQ_3.onnx\" #@param [\"Kim_Inst.onnx\", \"Kim_Vocal_1.onnx\", \"Kim_Vocal_2.onnx\", \"kuielab_a_bass.onnx\", \"kuielab_a_drums.onnx\", \"kuielab_a_other.onnx\", \"kuielab_a_vocals.onnx\", \"kuielab_b_bass.onnx\", \"kuielab_b_drums.onnx\", \"kuielab_b_other.onnx\", \"kuielab_b_vocals.onnx\", \"Reverb_HQ_By_FoxJoy.onnx\", \"UVR-MDX-NET-Inst_1.onnx\", \"UVR-MDX-NET-Inst_2.onnx\", \"UVR-MDX-NET-Inst_3.onnx\", \"UVR-MDX-NET-Inst_HQ_1.onnx\", \"UVR-MDX-NET-Inst_HQ_2.onnx\", \"UVR-MDX-NET-Inst_Main.onnx\", \"UVR_MDXNET_1_9703.onnx\", \"UVR_MDXNET_2_9682.onnx\", \"UVR_MDXNET_3_9662.onnx\", \"UVR_MDXNET_9482.onnx\", \"UVR_MDXNET_KARA.onnx\", \"UVR_MDXNET_KARA_2.onnx\", \"UVR_MDXNET_Main.onnx\", \"UVR-MDX-NET-Inst_HQ_3.onnx\", \"UVR-MDX-NET-Voc_FT.onnx\"]{allow-input: true}\n",
+        "    #@markdown process all: processes all tracks inside tracks/ folder instead. (filename will be ignored!)\n",
+        "    process_all = False  # @param{type:\"boolean\"}\n",
+        "\n",
+        "\n",
+        "    #@markdown ### Settings\n",
+        "    #@markdown invert: get difference between input and output (e.g get Instrumental out of Vocals)\n",
+        "    invert = True  # @param{type:\"boolean\"}\n",
+        "    #@markdown denoise: get rid of MDX noise. (This processes input track twice)\n",
+        "    denoise = True  # @param{type:\"boolean\"}\n",
+        "    #@markdown m_threads: like batch size, processes input wave in n threads. (beneficial for CPU)\n",
+        "    m_threads = 2 #@param {type:\"slider\", min:1, max:8, step:1}\n",
+        "\n",
+        "    #@markdown ### Custom model parameters (Only use this if you're using new/unofficial/custom models)\n",
+        "    #@markdown Use custom model parameters. (Default: unchecked, or auto)\n",
+        "    use_custom_parameter = False  # @param{type:\"boolean\"}\n",
+        "    #@markdown Output file suffix (usually the stem name e.g Vocals)\n",
+        "    suffix = \"Vocals_custom\" #@param [\"Vocals\", \"Drums\", \"Bass\", \"Other\"]{allow-input: true}\n",
+        "    suffix_invert = \"Instrumental_custom\" #@param [\"Instrumental\", \"Drumless\", \"Bassless\", \"Instruments\"]{allow-input: true}\n",
+        "    #@markdown Model parameters\n",
+        "    dim_f = 3072 #@param {type: \"integer\"}\n",
+        "    dim_t = 256 #@param {type: \"integer\"}\n",
+        "    n_fft = 6144 #@param {type: \"integer\"}\n",
+        "    #@markdown use custom compensation: only if you have your own compensation value for your model. this still apply even if you don't have use_custom_parameter checked (Default: unchecked, or auto)\n",
+        "    use_custom_compensation = False  # @param{type:\"boolean\"}\n",
+        "    compensation = 1.000 #@param {type: \"number\"}\n",
+        "\n",
+        "    #@markdown ### Extras\n",
+        "    #@markdown Deezer arl: paste your ARL here for deezer tracks directly!\n",
+        "    arl = \"\" #@param {type:\"string\"}\n",
+        "    #@markdown Track format: select track quality/format\n",
+        "    track_format = \"FLAC\" #@param [\"FLAC\",\"MP3_320\",\"MP3_128\"]\n",
+        "    #@markdown Print settings being used in the run\n",
+        "    print_settings = True  # @param{type:\"boolean\"}\n",
+        "\n",
+        "\n",
+        "\n",
+        "    onnx = id_to_ptm(onnx)\n",
+        "    compensation = compensation if use_custom_compensation or use_custom_parameter else None\n",
+        "    mdx_model = prepare_mdx(use_custom_parameter, dim_f, dim_t, n_fft, compensation=compensation)\n",
+        "\n",
+        "    filename_split = filename.split(';')\n",
+        "\n",
+        "    usable_files = []\n",
+        "\n",
+        "    if not process_all:\n",
+        "        for fn in filename_split:\n",
+        "            fn = fn.strip()\n",
+        "            if is_valid_url(fn):\n",
+        "                dm, ltype, lid = deemix.parseLink(fn)\n",
+        "                if ltype and lid:\n",
+        "                    usable_files += download_deezer(fn, arl, track_format)\n",
+        "                else:\n",
+        "                    print('downloading link...',end=' ')\n",
+        "                    usable_files+=[download_link(fn)]\n",
+        "                    print('done')\n",
+        "            else:\n",
+        "                usable_files.append(os.path.join('tracks',fn))\n",
+        "    else:\n",
+        "        for fn in glob.glob('tracks/*'):\n",
+        "            usable_files.append(fn)\n",
+        "    for filename in usable_files:\n",
+        "        suffix_naming = suffix if use_custom_parameter else None\n",
+        "        diff_suffix_naming = suffix_invert if use_custom_parameter else None\n",
+        "        run_mdx(onnx, mdx_model, filename, diff=invert,suffix=suffix_naming,diff_suffix=diff_suffix_naming,denoise=denoise)\n",
+        "\n",
+        "    if print_settings:\n",
+        "        print()\n",
+        "        print('[MDX-Net_Colab settings used]')\n",
+        "        print(f'Model used: {onnx}')\n",
+        "        print(f'Model MD5: {mdx.MDX.get_hash(onnx)}')\n",
+        "        print(f'Using de-noise: {denoise}')\n",
+        "        print(f'Model parameters:')\n",
+        "        print(f'    -dim_f: {mdx_model.dim_f}')\n",
+        "        print(f'    -dim_t: {mdx_model.dim_t}')\n",
+        "        print(f'    -n_fft: {mdx_model.n_fft}')\n",
+        "        print(f'    -compensation: {mdx_model.compensation}')\n",
+        "        print()\n",
+        "        print('[Input file]')\n",
+        "        print('filename(s): ')\n",
+        "        for filename in usable_files:\n",
+        "            print(f'    -{filename}')\n",
+        "\n",
+        "    del mdx_model"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "# Guide\n",
+        "\n",
+        "This tutorial guide will walk you through the steps to use the features of this Colab notebook.\n",
+        "\n",
+        "## Mount Drive\n",
+        "\n",
+        "To mount your Google Drive, follow these steps:\n",
+        "\n",
+        "1. Check the box next to \"MountDrive\" if you want to mount Google Drive.\n",
+        "2. Modify the \"mounting_path\" if you want to specify a different path for the drive to be mounted. **Note:** Be cautious when modifying this path as it can cause issues if not done properly.\n",
+        "3. Check the box next to \"Force update and disregard local changes\" if you want to discard all local modifications in your repository and replace the files with the versions from the original commit.\n",
+        "4. Check the box next to \"Auto Update\" if you want to automatically update without discarding your changes. Leave it unchecked if you want to manually update.\n",
+        "\n",
+        "## Input Files\n",
+        "\n",
+        "To upload your songs, follow these steps:\n",
+        "\n",
+        "1. Specify the \"track filename\" for your songs. You can provide multiple links or files by separating them with a semicolon (;).\n",
+        "2. Upload your songs to the \"tracks\" folder.\n",
+        "\n",
+        "## ONNX Model\n",
+        "\n",
+        "If you have your own ONNX model, follow these steps:\n",
+        "\n",
+        "1. Upload your model to the \"models\" folder.\n",
+        "2. Specify the \"onnx\" filename for your model.\n",
+        "\n",
+        "## Processing\n",
+        "\n",
+        "To process your tracks, follow these steps:\n",
+        "\n",
+        "1. If you want to process all tracks inside the \"tracks\" folder, check the box next to \"process_all\" and ignore the \"filename\" field.\n",
+        "2. Specify any additional settings you want:\n",
+        "   - Check the box next to \"invert\" to get the difference between input and output (e.g., get Instrumental out of Vocals).\n",
+        "   - Check the box next to \"denoise\" to get rid of MDX noise. This processes the input track twice.\n",
+        "   - Specify custom model parameters only if you're using new/unofficial/custom models. Use the \"use_custom_parameter\" checkbox to enable this feature.\n",
+        "   - Specify the output file suffix, which is usually the stem name (e.g., Vocals). Use the \"suffix\" field to specify the suffix for normal processing and the \"suffix_invert\" field for inverted processing.\n",
+        "\n",
+        "## Model Parameters\n",
+        "\n",
+        "Specify the following custom model parameters if applicable:\n",
+        "\n",
+        "- \"dim_f\": The value for the `dim_f` parameter.\n",
+        "- \"dim_t\": The value for the `dim_t` parameter.\n",
+        "- \"n_fft\": The value for the `n_fft` parameter.\n",
+        "- Check the box next to \"use_custom_compensation\" if you have your own compensation value for your model. Specify the compensation value in the \"compensation\" field.\n",
+        "\n",
+        "## Extras\n",
+        "\n",
+        "If you're working with Deezer tracks, paste your ARL (Authentication Request Library) in the \"arl\" field to directly access the tracks.\n",
+        "\n",
+        "Specify the \"Track format\" by selecting the desired quality/format for the track.\n",
+        "\n",
+        "To print the settings being used in the run, check the box next to \"print_settings\".\n",
+        "\n",
+        "That's it! You're now ready to use this Colab notebook. Enjoy!\n",
+        "\n",
+        "## For more detailed guide, proceed to this <a href=\"https://docs.google.com/document/d/17fjNvJzj8ZGSer7c7OFe_CNfUKbAxEh_OBv94ZdRG5c\">link</a>.\n",
+        "credits: (discord) deton24"
+      ],
+      "metadata": {
+        "id": "tMVwX5RhZSRP"
+      }
+    }
+  ],
+  "metadata": {
+    "accelerator": "GPU",
+    "colab": {
+      "gpuType": "T4",
+      "provenance": []
+    },
+    "kernelspec": {
+      "display_name": "Python 3",
+      "name": "python3"
+    },
+    "language_info": {
+      "name": "python"
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 0
+}
\ No newline at end of file
diff --git a/MDXNet.py b/MDXNet.py
new file mode 100644
index 0000000000000000000000000000000000000000..9b7eb43844ad0d4f9ce61287ccf9a8a4206d3853
--- /dev/null
+++ b/MDXNet.py
@@ -0,0 +1,272 @@
+import soundfile as sf
+import torch, pdb, os, warnings, librosa
+import numpy as np
+import onnxruntime as ort
+from tqdm import tqdm
+import torch
+
+dim_c = 4
+
+
+class Conv_TDF_net_trim:
+    def __init__(
+        self, device, model_name, target_name, L, dim_f, dim_t, n_fft, hop=1024
+    ):
+        super(Conv_TDF_net_trim, self).__init__()
+
+        self.dim_f = dim_f
+        self.dim_t = 2**dim_t
+        self.n_fft = n_fft
+        self.hop = hop
+        self.n_bins = self.n_fft // 2 + 1
+        self.chunk_size = hop * (self.dim_t - 1)
+        self.window = torch.hann_window(window_length=self.n_fft, periodic=True).to(
+            device
+        )
+        self.target_name = target_name
+        self.blender = "blender" in model_name
+
+        out_c = dim_c * 4 if target_name == "*" else dim_c
+        self.freq_pad = torch.zeros(
+            [1, out_c, self.n_bins - self.dim_f, self.dim_t]
+        ).to(device)
+
+        self.n = L // 2
+
+    def stft(self, x):
+        x = x.reshape([-1, self.chunk_size])
+        x = torch.stft(
+            x,
+            n_fft=self.n_fft,
+            hop_length=self.hop,
+            window=self.window,
+            center=True,
+            return_complex=True,
+        )
+        x = torch.view_as_real(x)
+        x = x.permute([0, 3, 1, 2])
+        x = x.reshape([-1, 2, 2, self.n_bins, self.dim_t]).reshape(
+            [-1, dim_c, self.n_bins, self.dim_t]
+        )
+        return x[:, :, : self.dim_f]
+
+    def istft(self, x, freq_pad=None):
+        freq_pad = (
+            self.freq_pad.repeat([x.shape[0], 1, 1, 1])
+            if freq_pad is None
+            else freq_pad
+        )
+        x = torch.cat([x, freq_pad], -2)
+        c = 4 * 2 if self.target_name == "*" else 2
+        x = x.reshape([-1, c, 2, self.n_bins, self.dim_t]).reshape(
+            [-1, 2, self.n_bins, self.dim_t]
+        )
+        x = x.permute([0, 2, 3, 1])
+        x = x.contiguous()
+        x = torch.view_as_complex(x)
+        x = torch.istft(
+            x, n_fft=self.n_fft, hop_length=self.hop, window=self.window, center=True
+        )
+        return x.reshape([-1, c, self.chunk_size])
+
+
+def get_models(device, dim_f, dim_t, n_fft):
+    return Conv_TDF_net_trim(
+        device=device,
+        model_name="Conv-TDF",
+        target_name="vocals",
+        L=11,
+        dim_f=dim_f,
+        dim_t=dim_t,
+        n_fft=n_fft,
+    )
+
+
+warnings.filterwarnings("ignore")
+cpu = torch.device("cpu")
+if torch.cuda.is_available():
+    device = torch.device("cuda:0")
+elif torch.backends.mps.is_available():
+    device = torch.device("mps")
+else:
+    device = torch.device("cpu")
+
+
+class Predictor:
+    def __init__(self, args):
+        self.args = args
+        self.model_ = get_models(
+            device=cpu, dim_f=args.dim_f, dim_t=args.dim_t, n_fft=args.n_fft
+        )
+        self.model = ort.InferenceSession(
+            os.path.join(args.onnx, self.model_.target_name + ".onnx"),
+            providers=["CUDAExecutionProvider", "CPUExecutionProvider"],
+        )
+        print("onnx load done")
+
+    def demix(self, mix):
+        samples = mix.shape[-1]
+        margin = self.args.margin
+        chunk_size = self.args.chunks * 44100
+        assert not margin == 0, "margin cannot be zero!"
+        if margin > chunk_size:
+            margin = chunk_size
+
+        segmented_mix = {}
+
+        if self.args.chunks == 0 or samples < chunk_size:
+            chunk_size = samples
+
+        counter = -1
+        for skip in range(0, samples, chunk_size):
+            counter += 1
+
+            s_margin = 0 if counter == 0 else margin
+            end = min(skip + chunk_size + margin, samples)
+
+            start = skip - s_margin
+
+            segmented_mix[skip] = mix[:, start:end].copy()
+            if end == samples:
+                break
+
+        sources = self.demix_base(segmented_mix, margin_size=margin)
+        """
+        mix:(2,big_sample)
+        segmented_mix:offset->(2,small_sample)
+        sources:(1,2,big_sample)
+        """
+        return sources
+
+    def demix_base(self, mixes, margin_size):
+        chunked_sources = []
+        progress_bar = tqdm(total=len(mixes))
+        progress_bar.set_description("Processing")
+        for mix in mixes:
+            cmix = mixes[mix]
+            sources = []
+            n_sample = cmix.shape[1]
+            model = self.model_
+            trim = model.n_fft // 2
+            gen_size = model.chunk_size - 2 * trim
+            pad = gen_size - n_sample % gen_size
+            mix_p = np.concatenate(
+                (np.zeros((2, trim)), cmix, np.zeros((2, pad)), np.zeros((2, trim))), 1
+            )
+            mix_waves = []
+            i = 0
+            while i < n_sample + pad:
+                waves = np.array(mix_p[:, i : i + model.chunk_size])
+                mix_waves.append(waves)
+                i += gen_size
+            mix_waves = torch.tensor(mix_waves, dtype=torch.float32).to(cpu)
+            with torch.no_grad():
+                _ort = self.model
+                spek = model.stft(mix_waves)
+                if self.args.denoise:
+                    spec_pred = (
+                        -_ort.run(None, {"input": -spek.cpu().numpy()})[0] * 0.5
+                        + _ort.run(None, {"input": spek.cpu().numpy()})[0] * 0.5
+                    )
+                    tar_waves = model.istft(torch.tensor(spec_pred))
+                else:
+                    tar_waves = model.istft(
+                        torch.tensor(_ort.run(None, {"input": spek.cpu().numpy()})[0])
+                    )
+                tar_signal = (
+                    tar_waves[:, :, trim:-trim]
+                    .transpose(0, 1)
+                    .reshape(2, -1)
+                    .numpy()[:, :-pad]
+                )
+
+                start = 0 if mix == 0 else margin_size
+                end = None if mix == list(mixes.keys())[::-1][0] else -margin_size
+                if margin_size == 0:
+                    end = None
+                sources.append(tar_signal[:, start:end])
+
+                progress_bar.update(1)
+
+            chunked_sources.append(sources)
+        _sources = np.concatenate(chunked_sources, axis=-1)
+        # del self.model
+        progress_bar.close()
+        return _sources
+
+    def prediction(self, m, vocal_root, others_root, format):
+        os.makedirs(vocal_root, exist_ok=True)
+        os.makedirs(others_root, exist_ok=True)
+        basename = os.path.basename(m)
+        mix, rate = librosa.load(m, mono=False, sr=44100)
+        if mix.ndim == 1:
+            mix = np.asfortranarray([mix, mix])
+        mix = mix.T
+        sources = self.demix(mix.T)
+        opt = sources[0].T
+        if format in ["wav", "flac"]:
+            sf.write(
+                "%s/%s_main_vocal.%s" % (vocal_root, basename, format), mix - opt, rate
+            )
+            sf.write("%s/%s_others.%s" % (others_root, basename, format), opt, rate)
+        else:
+            path_vocal = "%s/%s_main_vocal.wav" % (vocal_root, basename)
+            path_other = "%s/%s_others.wav" % (others_root, basename)
+            sf.write(path_vocal, mix - opt, rate)
+            sf.write(path_other, opt, rate)
+            if os.path.exists(path_vocal):
+                os.system(
+                    "ffmpeg -i %s -vn %s -q:a 2 -y"
+                    % (path_vocal, path_vocal[:-4] + ".%s" % format)
+                )
+            if os.path.exists(path_other):
+                os.system(
+                    "ffmpeg -i %s -vn %s -q:a 2 -y"
+                    % (path_other, path_other[:-4] + ".%s" % format)
+                )
+
+
+class MDXNetDereverb:
+    def __init__(self, chunks):
+        self.onnx = "uvr5_weights/onnx_dereverb_By_FoxJoy"
+        self.shifts = 10  #'Predict with randomised equivariant stabilisation'
+        self.mixing = "min_mag"  # ['default','min_mag','max_mag']
+        self.chunks = chunks
+        self.margin = 44100
+        self.dim_t = 9
+        self.dim_f = 3072
+        self.n_fft = 6144
+        self.denoise = True
+        self.pred = Predictor(self)
+
+    def _path_audio_(self, input, vocal_root, others_root, format):
+        self.pred.prediction(input, vocal_root, others_root, format)
+
+
+if __name__ == "__main__":
+    dereverb = MDXNetDereverb(15)
+    from time import time as ttime
+
+    t0 = ttime()
+    dereverb._path_audio_(
+        "雪雪伴奏对消HP5.wav",
+        "vocal",
+        "others",
+    )
+    t1 = ttime()
+    print(t1 - t0)
+
+
+"""
+
+runtime\python.exe MDXNet.py 
+
+6G:
+15/9:0.8G->6.8G
+14:0.8G->6.5G
+25:炸
+
+half15:0.7G->6.6G,22.69s
+fp32-15:0.7G->6.6G,20.85s
+
+"""
diff --git a/Makefile b/Makefile
new file mode 100644
index 0000000000000000000000000000000000000000..44de020e6feb7fcd58016d7c3c736681f533b597
--- /dev/null
+++ b/Makefile
@@ -0,0 +1,63 @@
+.PHONY:
+.ONESHELL:
+
+help: ## Show this help and exit
+	@grep -hE '^[A-Za-z0-9_ \-]*?:.*##.*$$' $(MAKEFILE_LIST) | sort | awk 'BEGIN {FS = ":.*?## "}; {printf "\033[36m%-30s\033[0m %s\n", $$1, $$2}'
+
+install: ## Install dependencies (Do everytime you start up a paperspace machine)
+	apt-get -y install build-essential python3-dev ffmpeg
+	pip install --upgrade setuptools wheel
+	pip install --upgrade pip
+	pip install faiss-gpu fairseq gradio ffmpeg ffmpeg-python praat-parselmouth pyworld numpy==1.23.5 numba==0.56.4 librosa==0.9.1
+	pip install -r requirements.txt
+	pip install --upgrade lxml
+	apt-get update
+	apt -y install -qq aria2
+
+basev1: ## Download version 1 pre-trained models (Do only once after cloning the fork)
+	mkdir -p pretrained uvr5_weights
+	git pull
+	aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/D32k.pth -d pretrained -o D32k.pth
+	aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/D40k.pth -d pretrained -o D40k.pth
+	aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/D48k.pth -d pretrained -o D48k.pth
+	aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/G32k.pth -d pretrained -o G32k.pth
+	aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/G40k.pth -d pretrained -o G40k.pth
+	aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/G48k.pth -d pretrained -o G48k.pth
+	aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/f0D32k.pth -d pretrained -o f0D32k.pth
+	aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/f0D40k.pth -d pretrained -o f0D40k.pth
+	aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/f0D48k.pth -d pretrained -o f0D48k.pth
+	aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/f0G32k.pth -d pretrained -o f0G32k.pth
+	aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/f0G40k.pth -d pretrained -o f0G40k.pth
+	aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/f0G48k.pth -d pretrained -o f0G48k.pth
+	aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/uvr5_weights/HP2-人声vocals+非人声instrumentals.pth -d uvr5_weights -o HP2-人声vocals+非人声instrumentals.pth
+	aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/uvr5_weights/HP5-主旋律人声vocals+其他instrumentals.pth -d uvr5_weights -o HP5-主旋律人声vocals+其他instrumentals.pth
+	aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/hubert_base.pt -d ./ -o hubert_base.pt
+
+basev2: ## Download version 2 pre-trained models (Do only once after cloning the fork)
+	mkdir -p pretrained_v2 uvr5_weights
+	git pull
+	aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained_v2/D32k.pth -d pretrained_v2 -o D32k.pth
+	aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained_v2/D40k.pth -d pretrained_v2 -o D40k.pth
+	aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained_v2/D48k.pth -d pretrained_v2 -o D48k.pth
+	aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained_v2/G32k.pth -d pretrained_v2 -o G32k.pth
+	aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained_v2/G40k.pth -d pretrained_v2 -o G40k.pth
+	aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained_v2/G48k.pth -d pretrained_v2 -o G48k.pth
+	aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained_v2/f0D32k.pth -d pretrained_v2 -o f0D32k.pth
+	aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained_v2/f0D40k.pth -d pretrained_v2 -o f0D40k.pth
+	aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained_v2/f0D48k.pth -d pretrained_v2 -o f0D48k.pth
+	aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained_v2/f0G32k.pth -d pretrained_v2 -o f0G32k.pth
+	aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained_v2/f0G40k.pth -d pretrained_v2 -o f0G40k.pth
+	aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained_v2/f0G48k.pth -d pretrained_v2 -o f0G48k.pth
+	aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/uvr5_weights/HP2-人声vocals+非人声instrumentals.pth -d uvr5_weights -o HP2-人声vocals+非人声instrumentals.pth
+	aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/uvr5_weights/HP5-主旋律人声vocals+其他instrumentals.pth -d uvr5_weights -o HP5-主旋律人声vocals+其他instrumentals.pth
+	aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/hubert_base.pt -d ./ -o hubert_base.pt
+
+run-ui: ## Run the python GUI
+	python infer-web.py --paperspace --pycmd python
+
+run-cli: ## Run the python CLI
+	python infer-web.py --pycmd python --is_cli
+
+tensorboard: ## Start the tensorboard (Run on separate terminal)
+	echo https://tensorboard-$$(hostname).clg07azjl.paperspacegradient.com
+	tensorboard --logdir logs --bind_all
\ No newline at end of file
diff --git a/README.md b/README.md
index 80c2a46cd201c6dac5f8241f922911ba58aef5ff..1ac591a16af74bf15be1fa41fb65d8dfa4bf69d2 100644
--- a/README.md
+++ b/README.md
@@ -1,12 +1,222 @@
----
-title: Random App
-emoji: 👀
-colorFrom: gray
-colorTo: pink
-sdk: gradio
-sdk_version: 3.43.2
-app_file: app.py
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# 🍏 Applio-RVC-Fork
+Applio is a user-friendly fork of Mangio-RVC-Fork/RVC, designed to provide an intuitive interface, especially for newcomers.
+
+## 📎 Links
+[![Discord](https://img.shields.io/badge/SUPPORT_DISCORD-37a779?style=for-the-badge)](https://discord.gg/IAHispano)
+[![Google Colab](https://img.shields.io/badge/GOOGLE_COLAB-37a779?style=for-the-badge)](https://colab.research.google.com/drive/157pUQep6txJOYModYFqvz_5OJajeh7Ii)
+
+## 📚 Table of Contents
+  1. [Improvements of Applio Over RVC](#-improvements-of-applio-over-rvc)
+  2. [Additional Features of This Repository](#️-additional-features-of-this-repository)
+  3. [Planned Features for Future Development](#️-planned-features-for-future-development)
+  4. [Installation](#-installation)
+  5. [Running the Web GUI (Inference & Train)](#-running-the-web-gui-inference--train)
+  6. [Running the CLI (Inference & Train)](#-running-the-cli-inference--train)
+  7. [Credits](#credits)
+  8. [Thanks to all RVC and Mangio contributors](#thanks-to-all-rvc-and-mangio-contributors)
+
+
+## 🎯 Improvements of Applio Over RVC
+### f0 Inference Algorithm Overhaul
+- Applio features a comprehensive overhaul of the f0 inference algorithm, including:
+  - Addition of the pyworld dio f0 method.
+  - Alternative method for calculating crepe f0.
+  - Introduction of the torchcrepe crepe-tiny model.
+  - Customizable crepe_hop_length for the crepe algorithm via both the web GUI and CLI.
+
+### f0 Crepe Pitch Extraction for Training
+- Works on paperspace machines but not local MacOS/Windows machines (Potential memory leak).
+
+### Paperspace Integration
+- Applio seamlessly integrates with Paperspace, providing the following features:
+  - Paperspace argument on infer-web.py (--paperspace) for sharing a Gradio link.
+  - A dedicated make file tailored for Paperspace users.
+
+### Access to Tensorboard
+- Applio grants easy access to Tensorboard via a Makefile and a Python script.
+
+### CLI Functionality
+- Applio introduces command-line interface (CLI) functionality, with the addition of the --is_cli flag in infer-web.py for CLI system usage.
+
+### f0 Hybrid Estimation Method
+- Applio offers a novel f0 hybrid estimation method by calculating nanmedian for a specified array of f0 methods, ensuring the best results from multiple methods (CLI exclusive).
+- This hybrid estimation method is also available for f0 feature extraction during training.
+
+### UI Changes
+#### Inference:
+- A complete interface redesign enhances user experience, with notable features such as:
+  - Audio recording directly from the interface.
+  - Convenient drop-down menus for audio and .index file selection.
+  - An advanced settings section with new features like autotune and formant shifting.
+
+#### Training:
+- Improved training features include:
+  - A total epoch slider now limited to 10,000.
+  - Increased save frequency limit to 100.
+  - Default recommended options for smoother setup.
+  - Better adaptation to high-resolution screens.
+  - A drop-down menu for dataset selection.
+  - Enhanced saving system options, including Save all files, Save G and D files, and Save model for inference.
+
+#### UVR:
+- Applio ensures compatibility with all VR/MDX models for an extended range of possibilities.
+
+#### TTS (Text-to-Speech, New):
+- Introducing a new Text-to-Speech (TTS) feature using RVC models.
+- Support for multiple languages and Edge-tts/Bark-tts.
+
+#### Resources (New):
+- Users can now upload models, backups, datasets, and audios from various storage services like Drive, Huggingface, Discord, and more.
+- Download audios from YouTube with the ability to automatically separate instrumental and vocals, offering advanced options and UVR support.
+
+#### Extra (New):
+- Combine instrumental and vocals with ease, including independent volume control for each track and the option to add effects like reverb, compressor, and noise gate.
+- Significant improvements in the processing interface, allowing tasks such as merging models, modifying information, obtaining information, or extracting models effortlessly.
+
+## ⚙️ Additional Features of This Repository
+
+In addition to the aforementioned improvements, this repository offers the following features:
+
+### Enhanced Tone Leakage Reduction
+- Implements tone leakage reduction by replacing source features with training-set features using top1 retrieval. This helps in achieving cleaner audio results.
+
+### Efficient Training
+- Provides a seamless and speedy training experience, even on relatively modest graphics cards. The system is optimized for efficient resource utilization.
+
+### Data Efficiency
+- Supports training with a small dataset, yielding commendable results, especially with audio clips of at least 10 minutes of low-noise speech.
+
+## 🛠️ Planned Features for Future Development
+As part of the ongoing development of this fork, the following features are planned to be added:
+
+- Incorporating an inference batcher script based on user feedback. This enhancement will allow for processing 30-second audio samples at a time, improving output quality and preventing memory errors during inference.
+- Implementing an automatic removal mechanism for old generations to optimize storage space usage. This feature ensures that the repository remains efficient and organized over time.
+- Streamlining the training process for Paperspace machines to further improve efficiency and resource utilization during training tasks.
+
+## Compatibility
+- AMD/Intel graphics cards acceleration supported.
+- Intel ARC graphics cards acceleration with IPEX supported.
+
+## ✨ Installation
+
+### Automatic installation (Windows):
+To quickly and effortlessly install Applio along with all the necessary models and configurations on Windows, you can use the [install_Applio.bat](https://github.com/IAHispano/Applio-RVC-Fork/releases) script available in the releases section.
+
+### Manual installation (Windows/MacOS):
+**Note for MacOS Users**: When using `faiss 1.7.2` under MacOS, you may encounter a Segmentation Fault: 11 error. To resolve this issue, install `faiss-cpu 1.7.0` using the following command if you're installing it manually with pip: 
+ ```bash
+pip install faiss-cpu==1.7.0
+```
+Additionally, you can install Swig on MacOS using brew:
+```bash
+brew install swig
+```
+
+Install requirements:
+*Using pip (Python 3.9.8 is stable with this fork)*
+```bash
+pip install -r requirements.txt
+```
+
+### Manual installation (Paperspace):
+```bash
+cd Applio-RVC-Fork
+make install # Do this everytime you start your paperspace machine
+```
+### You can also use pip to install them:
+```bash
+
+for Nvidia graphics cards
+  pip install -r requirements.txt
+
+for AMD/Intel graphics cards：
+  pip install -r requirements-dml.txt
+
+for Intel ARC graphics cards on Linux / WSL using Python 3.10: 
+  pip install -r requirements-ipex.txt
+
+```
+
+## 🪄 Running the Web GUI (Inference & Train) 
+*Use --paperspace or --colab if on cloud system.*
+```bash
+python infer-web.py --pycmd python --port 3000
+```
+
+## 💻 Running the CLI (Inference & Train) 
+```bash
+python infer-web.py --pycmd python --is_cli
+```
+
+```bash
+Mangio-RVC-Fork v2 CLI App!
+
+Welcome to the CLI version of RVC. Please read the documentation on https://github.com/Mangio621/Mangio-RVC-Fork (README.MD) to understand how to use this app.
+
+You are currently in 'HOME':
+    go home            : Takes you back to home with a navigation list.
+    go infer           : Takes you to inference command execution.
+
+    go pre-process     : Takes you to training step.1) pre-process command execution.
+    go extract-feature : Takes you to training step.2) extract-feature command execution.
+    go train           : Takes you to training step.3) being or continue training command execution.
+    go train-feature   : Takes you to the train feature index command execution.
+
+    go extract-model   : Takes you to the extract small model command execution.
+
+HOME:
+```
+
+Typing 'go infer' for example will take you to the infer page where you can then enter in your arguments that you wish to use for that specific page. For example typing 'go infer' will take you here:
+
+```bash
+HOME: go infer
+You are currently in 'INFER':
+    arg 1) model name with .pth in ./weights: mi-test.pth
+    arg 2) source audio path: myFolder\MySource.wav
+    arg 3) output file name to be placed in './audio-outputs': MyTest.wav
+    arg 4) feature index file path: logs/mi-test/added_IVF3042_Flat_nprobe_1.index
+    arg 5) speaker id: 0
+    arg 6) transposition: 0
+    arg 7) f0 method: harvest (pm, harvest, crepe, crepe-tiny)
+    arg 8) crepe hop length: 160
+    arg 9) harvest median filter radius: 3 (0-7)
+    arg 10) post resample rate: 0
+    arg 11) mix volume envelope: 1
+    arg 12) feature index ratio: 0.78 (0-1)
+    arg 13) Voiceless Consonant Protection (Less Artifact): 0.33 (Smaller number = more protection. 0.50 means Dont Use.)
+
+Example: mi-test.pth saudio/Sidney.wav myTest.wav logs/mi-test/added_index.index 0 -2 harvest 160 3 0 1 0.95 0.33
+
+INFER: <INSERT ARGUMENTS HERE OR COPY AND PASTE THE EXAMPLE>
+```
+## 🏆 Credits
+Applio owes its existence to the collaborative efforts of various repositories, including Mangio-RVC-Fork, and all the other credited contributors. Without their contributions, Applio would not have been possible. Therefore, we kindly request that if you appreciate the work we've accomplished, you consider exploring the projects mentioned in our credits.
+
+Our goal is not to supplant RVC or Mangio; rather, we aim to provide a contemporary and up-to-date alternative for the entire community.
+
++ [Retrieval-based-Voice-Conversion-WebUI](Retrieval-based-Voice-Conversion-WebUI)
++ [Mangio-RVC-Fork](https://github.com/Mangio621/Mangio-RVC-Fork)
++ [RVG_tts](https://github.com/Foxify52/RVG_tts)
++ [ContentVec](https://github.com/auspicious3000/contentvec/)
++ [VITS](https://github.com/jaywalnut310/vits)
++ [HIFIGAN](https://github.com/jik876/hifi-gan)
++ [Gradio](https://github.com/gradio-app/gradio)
++ [FFmpeg](https://github.com/FFmpeg/FFmpeg)
++ [Ultimate Vocal Remover](https://github.com/Anjok07/ultimatevocalremovergui)
++ [audio-slicer](https://github.com/openvpi/audio-slicer)
++ [Vocal pitch extraction:RMVPE](https://github.com/Dream-High/RMVPE)
+
+
+## 🙏 Thanks to all RVC, Mangio and Applio contributors
+<a href="https://github.com/liujing04/Retrieval-based-Voice-Conversion-WebUI/graphs/contributors" target="_blank">
+  <img src="https://contrib.rocks/image?repo=liujing04/Retrieval-based-Voice-Conversion-WebUI" />
+</a>
+
+<a href="https://github.com/Mangio621/Mangio-RVC-Fork/graphs/contributors" target="_blank">
+  <img src="https://contrib.rocks/image?repo=Mangio621/Mangio-RVC-Fork" />
+</a>
+
+<a href="https://github.com/IAHispano/Applio-RVC-Fork/graphs/contributors" target="_blank">
+  <img src="https://contrib.rocks/image?repo=IAHispano/Applio-RVC-Fork" />
+</a>
diff --git a/assets/hubert/.gitignore b/assets/hubert/.gitignore
new file mode 100644
index 0000000000000000000000000000000000000000..d6b7ef32c8478a48c3994dcadc86837f4371184d
--- /dev/null
+++ b/assets/hubert/.gitignore
@@ -0,0 +1,2 @@
+*
+!.gitignore
diff --git a/assets/pretrained/.gitignore b/assets/pretrained/.gitignore
new file mode 100644
index 0000000000000000000000000000000000000000..d6b7ef32c8478a48c3994dcadc86837f4371184d
--- /dev/null
+++ b/assets/pretrained/.gitignore
@@ -0,0 +1,2 @@
+*
+!.gitignore
diff --git a/assets/pretrained_v2/.gitignore b/assets/pretrained_v2/.gitignore
new file mode 100644
index 0000000000000000000000000000000000000000..d6b7ef32c8478a48c3994dcadc86837f4371184d
--- /dev/null
+++ b/assets/pretrained_v2/.gitignore
@@ -0,0 +1,2 @@
+*
+!.gitignore
diff --git a/assets/rmvpe/.gitignore b/assets/rmvpe/.gitignore
new file mode 100644
index 0000000000000000000000000000000000000000..d6b7ef32c8478a48c3994dcadc86837f4371184d
--- /dev/null
+++ b/assets/rmvpe/.gitignore
@@ -0,0 +1,2 @@
+*
+!.gitignore
diff --git a/assets/uvr5_weights/.gitignore b/assets/uvr5_weights/.gitignore
new file mode 100644
index 0000000000000000000000000000000000000000..d6b7ef32c8478a48c3994dcadc86837f4371184d
--- /dev/null
+++ b/assets/uvr5_weights/.gitignore
@@ -0,0 +1,2 @@
+*
+!.gitignore
diff --git a/assets/weights/.gitignore b/assets/weights/.gitignore
new file mode 100644
index 0000000000000000000000000000000000000000..d6b7ef32c8478a48c3994dcadc86837f4371184d
--- /dev/null
+++ b/assets/weights/.gitignore
@@ -0,0 +1,2 @@
+*
+!.gitignore
diff --git a/audioEffects.py b/audioEffects.py
new file mode 100644
index 0000000000000000000000000000000000000000..1830b19e1a5e3ec1f431388d8444ef3a2c9ed91f
--- /dev/null
+++ b/audioEffects.py
@@ -0,0 +1,37 @@
+from pedalboard import Pedalboard, Compressor, Reverb, NoiseGate
+from pedalboard.io import AudioFile
+import sys
+import os
+now_dir = os.getcwd()
+sys.path.append(now_dir)
+from i18n import I18nAuto
+i18n = I18nAuto()
+from pydub import AudioSegment
+import numpy as np
+import soundfile as sf
+from pydub.playback import play
+
+def process_audio(input_path, output_path, reverb_enabled, compressor_enabled, noise_gate_enabled, ):
+    print(reverb_enabled)
+    print(compressor_enabled)
+    print(noise_gate_enabled)
+    effects = []
+    if reverb_enabled:
+        effects.append(Reverb(room_size=0.01))
+    if compressor_enabled:
+        effects.append(Compressor(threshold_db=-10, ratio=25))
+    if noise_gate_enabled:
+        effects.append(NoiseGate(threshold_db=-16, ratio=1.5, release_ms=250))
+
+    board = Pedalboard(effects)
+
+    with AudioFile(input_path) as f:
+        with AudioFile(output_path, 'w', f.samplerate, f.num_channels) as o:
+            while f.tell() < f.frames:
+                chunk = f.read(f.samplerate)
+                effected = board(chunk, f.samplerate, reset=False)
+                o.write(effected)
+
+    result = i18n("Processed audio saved at: ") +  output_path
+    print(result)
+    return output_path
\ No newline at end of file
diff --git a/audios/.gitignore b/audios/.gitignore
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/colab_for_mdx.py b/colab_for_mdx.py
new file mode 100644
index 0000000000000000000000000000000000000000..274846d0b5395865a05fce0da86b96d26ac06999
--- /dev/null
+++ b/colab_for_mdx.py
@@ -0,0 +1,71 @@
+import json
+import os
+import gc
+import psutil
+import requests
+import subprocess
+import time
+import logging
+import sys
+import shutil
+now_dir = os.getcwd()
+sys.path.append(now_dir)
+first_cell_executed = False
+file_folder = "Colab-for-MDX_B"
+def first_cell_ran():
+    global first_cell_executed
+    if first_cell_executed:
+        #print("The 'first_cell_ran' function has already been executed.")
+        return
+
+    
+
+    first_cell_executed = True
+    os.makedirs("tmp_models", exist_ok=True)
+
+
+
+    class hide_opt:  # hide outputs
+        def __enter__(self):
+            self._original_stdout = sys.stdout
+            sys.stdout = open(os.devnull, "w")
+
+        def __exit__(self, exc_type, exc_val, exc_tb):
+            sys.stdout.close()
+            sys.stdout = self._original_stdout
+
+    def get_size(bytes, suffix="B"):  # read ram
+        global svmem
+        factor = 1024
+        for unit in ["", "K", "M", "G", "T", "P"]:
+            if bytes < factor:
+                return f"{bytes:.2f}{unit}{suffix}"
+            bytes /= factor
+        svmem = psutil.virtual_memory()
+
+
+    def use_uvr_without_saving():
+        print("Notice: files won't be saved to personal drive.")
+        print(f"Downloading {file_folder}...", end=" ")
+        with hide_opt():
+            #os.chdir(mounting_path)
+            items_to_move = ["demucs", "diffq","julius","model","separated","tracks","mdx.py","MDX-Net_Colab.ipynb"]
+            subprocess.run(["git", "clone", "https://github.com/NaJeongMo/Colab-for-MDX_B.git"])
+            for item_name in items_to_move:
+                item_path = os.path.join(file_folder, item_name)
+                if os.path.exists(item_path):
+                    if os.path.isfile(item_path):
+                        shutil.move(item_path, now_dir)
+                    elif os.path.isdir(item_path):
+                        shutil.move(item_path, now_dir)
+            try:
+                shutil.rmtree(file_folder)
+            except PermissionError:
+                print(f"No se pudo eliminar la carpeta {file_folder}. Puede estar relacionada con Git.")
+
+    
+    use_uvr_without_saving()
+    print("done!")
+    if not os.path.exists("tracks"):
+        os.mkdir("tracks")
+first_cell_ran()
\ No newline at end of file
diff --git a/configs/32k.json b/configs/32k.json
new file mode 100644
index 0000000000000000000000000000000000000000..bcae72223ec09dc199009d7cb5ed405a0c0981cf
--- /dev/null
+++ b/configs/32k.json
@@ -0,0 +1,50 @@
+{
+  "train": {
+    "log_interval": 200,
+    "seed": 1234,
+    "epochs": 20000,
+    "learning_rate": 1e-4,
+    "betas": [0.8, 0.99],
+    "eps": 1e-9,
+    "batch_size": 4,
+    "fp16_run": false,
+    "lr_decay": 0.999875,
+    "segment_size": 12800,
+    "init_lr_ratio": 1,
+    "warmup_epochs": 0,
+    "c_mel": 45,
+    "c_kl": 1.0
+  },
+  "data": {
+    "max_wav_value": 32768.0,
+    "sampling_rate": 32000,
+    "filter_length": 1024,
+    "hop_length": 320,
+    "win_length": 1024,
+    "n_mel_channels": 80,
+    "mel_fmin": 0.0,
+    "mel_fmax": null
+  },
+  "model": {
+    "inter_channels": 192,
+    "hidden_channels": 192,
+    "filter_channels": 768,
+    "n_heads": 2,
+    "n_layers": 6,
+    "kernel_size": 3,
+    "p_dropout": 0,
+    "resblock": "1",
+    "resblock_kernel_sizes": [3, 7, 11],
+    "resblock_dilation_sizes": [
+      [1, 3, 5],
+      [1, 3, 5],
+      [1, 3, 5]
+    ],
+    "upsample_rates": [10, 4, 2, 2, 2],
+    "upsample_initial_channel": 512,
+    "upsample_kernel_sizes": [16, 16, 4, 4, 4],
+    "use_spectral_norm": false,
+    "gin_channels": 256,
+    "spk_embed_dim": 109
+  }
+}
diff --git a/configs/32k_v2.json b/configs/32k_v2.json
new file mode 100644
index 0000000000000000000000000000000000000000..ad42f87b15e1ea68eff0a90db50fbc08d56c7aa9
--- /dev/null
+++ b/configs/32k_v2.json
@@ -0,0 +1,50 @@
+{
+  "train": {
+    "log_interval": 200,
+    "seed": 1234,
+    "epochs": 20000,
+    "learning_rate": 1e-4,
+    "betas": [0.8, 0.99],
+    "eps": 1e-9,
+    "batch_size": 4,
+    "fp16_run": true,
+    "lr_decay": 0.999875,
+    "segment_size": 12800,
+    "init_lr_ratio": 1,
+    "warmup_epochs": 0,
+    "c_mel": 45,
+    "c_kl": 1.0
+  },
+  "data": {
+    "max_wav_value": 32768.0,
+    "sampling_rate": 32000,
+    "filter_length": 1024,
+    "hop_length": 320,
+    "win_length": 1024,
+    "n_mel_channels": 80,
+    "mel_fmin": 0.0,
+    "mel_fmax": null
+  },
+  "model": {
+    "inter_channels": 192,
+    "hidden_channels": 192,
+    "filter_channels": 768,
+    "n_heads": 2,
+    "n_layers": 6,
+    "kernel_size": 3,
+    "p_dropout": 0,
+    "resblock": "1",
+    "resblock_kernel_sizes": [3, 7, 11],
+    "resblock_dilation_sizes": [
+      [1, 3, 5],
+      [1, 3, 5],
+      [1, 3, 5]
+    ],
+    "upsample_rates": [10, 8, 2, 2],
+    "upsample_initial_channel": 512,
+    "upsample_kernel_sizes": [20, 16, 4, 4],
+    "use_spectral_norm": false,
+    "gin_channels": 256,
+    "spk_embed_dim": 109
+  }
+}
diff --git a/configs/40k.json b/configs/40k.json
new file mode 100644
index 0000000000000000000000000000000000000000..28ff4d91f2618497fb39ad27872151bcb0d51761
--- /dev/null
+++ b/configs/40k.json
@@ -0,0 +1,50 @@
+{
+  "train": {
+    "log_interval": 200,
+    "seed": 1234,
+    "epochs": 20000,
+    "learning_rate": 1e-4,
+    "betas": [0.8, 0.99],
+    "eps": 1e-9,
+    "batch_size": 4,
+    "fp16_run": false,
+    "lr_decay": 0.999875,
+    "segment_size": 12800,
+    "init_lr_ratio": 1,
+    "warmup_epochs": 0,
+    "c_mel": 45,
+    "c_kl": 1.0
+  },
+  "data": {
+    "max_wav_value": 32768.0,
+    "sampling_rate": 40000,
+    "filter_length": 2048,
+    "hop_length": 400,
+    "win_length": 2048,
+    "n_mel_channels": 125,
+    "mel_fmin": 0.0,
+    "mel_fmax": null
+  },
+  "model": {
+    "inter_channels": 192,
+    "hidden_channels": 192,
+    "filter_channels": 768,
+    "n_heads": 2,
+    "n_layers": 6,
+    "kernel_size": 3,
+    "p_dropout": 0,
+    "resblock": "1",
+    "resblock_kernel_sizes": [3, 7, 11],
+    "resblock_dilation_sizes": [
+      [1, 3, 5],
+      [1, 3, 5],
+      [1, 3, 5]
+    ],
+    "upsample_rates": [10, 10, 2, 2],
+    "upsample_initial_channel": 512,
+    "upsample_kernel_sizes": [16, 16, 4, 4],
+    "use_spectral_norm": false,
+    "gin_channels": 256,
+    "spk_embed_dim": 109
+  }
+}
diff --git a/configs/48k.json b/configs/48k.json
new file mode 100644
index 0000000000000000000000000000000000000000..4d01946ed50ade92c1f85b548ab008a4cd617eb8
--- /dev/null
+++ b/configs/48k.json
@@ -0,0 +1,50 @@
+{
+  "train": {
+    "log_interval": 200,
+    "seed": 1234,
+    "epochs": 20000,
+    "learning_rate": 1e-4,
+    "betas": [0.8, 0.99],
+    "eps": 1e-9,
+    "batch_size": 4,
+    "fp16_run": false,
+    "lr_decay": 0.999875,
+    "segment_size": 11520,
+    "init_lr_ratio": 1,
+    "warmup_epochs": 0,
+    "c_mel": 45,
+    "c_kl": 1.0
+  },
+  "data": {
+    "max_wav_value": 32768.0,
+    "sampling_rate": 48000,
+    "filter_length": 2048,
+    "hop_length": 480,
+    "win_length": 2048,
+    "n_mel_channels": 128,
+    "mel_fmin": 0.0,
+    "mel_fmax": null
+  },
+  "model": {
+    "inter_channels": 192,
+    "hidden_channels": 192,
+    "filter_channels": 768,
+    "n_heads": 2,
+    "n_layers": 6,
+    "kernel_size": 3,
+    "p_dropout": 0,
+    "resblock": "1",
+    "resblock_kernel_sizes": [3, 7, 11],
+    "resblock_dilation_sizes": [
+      [1, 3, 5],
+      [1, 3, 5],
+      [1, 3, 5]
+    ],
+    "upsample_rates": [10, 6, 2, 2, 2],
+    "upsample_initial_channel": 512,
+    "upsample_kernel_sizes": [16, 16, 4, 4, 4],
+    "use_spectral_norm": false,
+    "gin_channels": 256,
+    "spk_embed_dim": 109
+  }
+}
diff --git a/configs/48k_v2.json b/configs/48k_v2.json
new file mode 100644
index 0000000000000000000000000000000000000000..50f06421912e2cd1f69768c35272981d75d86983
--- /dev/null
+++ b/configs/48k_v2.json
@@ -0,0 +1,50 @@
+{
+  "train": {
+    "log_interval": 200,
+    "seed": 1234,
+    "epochs": 20000,
+    "learning_rate": 1e-4,
+    "betas": [0.8, 0.99],
+    "eps": 1e-9,
+    "batch_size": 4,
+    "fp16_run": true,
+    "lr_decay": 0.999875,
+    "segment_size": 17280,
+    "init_lr_ratio": 1,
+    "warmup_epochs": 0,
+    "c_mel": 45,
+    "c_kl": 1.0
+  },
+  "data": {
+    "max_wav_value": 32768.0,
+    "sampling_rate": 48000,
+    "filter_length": 2048,
+    "hop_length": 480,
+    "win_length": 2048,
+    "n_mel_channels": 128,
+    "mel_fmin": 0.0,
+    "mel_fmax": null
+  },
+  "model": {
+    "inter_channels": 192,
+    "hidden_channels": 192,
+    "filter_channels": 768,
+    "n_heads": 2,
+    "n_layers": 6,
+    "kernel_size": 3,
+    "p_dropout": 0,
+    "resblock": "1",
+    "resblock_kernel_sizes": [3, 7, 11],
+    "resblock_dilation_sizes": [
+      [1, 3, 5],
+      [1, 3, 5],
+      [1, 3, 5]
+    ],
+    "upsample_rates": [12, 10, 2, 2],
+    "upsample_initial_channel": 512,
+    "upsample_kernel_sizes": [24, 20, 4, 4],
+    "use_spectral_norm": false,
+    "gin_channels": 256,
+    "spk_embed_dim": 109
+  }
+}
diff --git a/configs/config.json b/configs/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..8e9c17669bf8028653fbfa5c9eeac23ec76c1cc9
--- /dev/null
+++ b/configs/config.json
@@ -0,0 +1,15 @@
+{
+  "pth_path": "assets/weights/kikiV1.pth",
+  "index_path": "logs/kikiV1.index",
+  "sg_input_device": "VoiceMeeter Output (VB-Audio Vo (MME)",
+  "sg_output_device": "VoiceMeeter Aux Input (VB-Audio (MME)",
+  "threhold": -45.0,
+  "pitch": 12.0,
+  "index_rate": 0.0,
+  "rms_mix_rate": 0.0,
+  "block_time": 0.25,
+  "crossfade_length": 0.04,
+  "extra_time": 2.0,
+  "n_cpu": 6.0,
+  "f0method": "rmvpe"
+}
diff --git a/configs/config.py b/configs/config.py
new file mode 100644
index 0000000000000000000000000000000000000000..e3b0205a1f0d62f674b9c3de2c5ab7ee90464945
--- /dev/null
+++ b/configs/config.py
@@ -0,0 +1,265 @@
+import argparse
+import os
+import sys
+import json
+from multiprocessing import cpu_count
+
+import torch
+
+try:
+    import intel_extension_for_pytorch as ipex # pylint: disable=import-error, unused-import
+    if torch.xpu.is_available():
+        from infer.modules.ipex import ipex_init
+        ipex_init()
+except Exception:
+    pass
+
+import logging
+
+logger = logging.getLogger(__name__)
+
+
+version_config_list = [
+    "v1/32k.json",
+    "v1/40k.json",
+    "v1/48k.json",
+    "v2/48k.json",
+    "v2/32k.json",
+]
+
+
+def singleton_variable(func):
+    def wrapper(*args, **kwargs):
+        if not wrapper.instance:
+            wrapper.instance = func(*args, **kwargs)
+        return wrapper.instance
+
+    wrapper.instance = None
+    return wrapper
+
+
+@singleton_variable
+class Config:
+    def __init__(self):
+        self.device = "cuda:0"
+        self.is_half = True
+        self.n_cpu = 0
+        self.gpu_name = None
+        self.json_config = self.load_config_json()
+        self.gpu_mem = None
+        (
+            self.python_cmd,
+            self.listen_port,
+            self.iscolab,
+            self.noparallel,
+            self.noautoopen,
+            self.paperspace,
+            self.is_cli,
+            self.grtheme,
+            self.dml,
+        ) = self.arg_parse()
+        self.instead = ""
+        self.x_pad, self.x_query, self.x_center, self.x_max = self.device_config()
+
+    @staticmethod
+    def load_config_json() -> dict:
+        d = {}
+        for config_file in version_config_list:
+            with open(f"configs/{config_file}", "r") as f:
+                d[config_file] = json.load(f)
+        return d
+
+    @staticmethod
+    def arg_parse() -> tuple:
+        exe = sys.executable or "python"
+        parser = argparse.ArgumentParser()
+        parser.add_argument("--port", type=int, default=7865, help="Listen port")
+        parser.add_argument("--pycmd", type=str, default=exe, help="Python command")
+        parser.add_argument("--colab", action="store_true", help="Launch in colab")
+        parser.add_argument(
+            "--noparallel", action="store_true", help="Disable parallel processing"
+        )
+        parser.add_argument(
+            "--noautoopen",
+            action="store_true",
+            help="Do not open in browser automatically",
+        )
+        parser.add_argument(  
+            "--paperspace",
+            action="store_true",
+            help="Note that this argument just shares a gradio link for the web UI. Thus can be used on other non-local CLI systems.",
+        )
+        parser.add_argument(  
+            "--is_cli",
+            action="store_true",
+            help="Use the CLI instead of setting up a gradio UI. This flag will launch an RVC text interface where you can execute functions from infer-web.py!",
+        )
+
+        parser.add_argument(
+                    "-t",
+                    "--theme",
+            help    = "Theme for Gradio. Format - `JohnSmith9982/small_and_pretty` (no backticks)",
+            default = "JohnSmith9982/small_and_pretty",
+            type    = str
+        )
+
+        parser.add_argument(
+            "--dml",
+            action="store_true",
+            help="Use DirectML backend instead of CUDA."
+        )
+        
+        cmd_opts = parser.parse_args()
+
+        cmd_opts.port = cmd_opts.port if 0 <= cmd_opts.port <= 65535 else 7865
+
+        return (
+            cmd_opts.pycmd,
+            cmd_opts.port,
+            cmd_opts.colab,
+            cmd_opts.noparallel,
+            cmd_opts.noautoopen,
+            cmd_opts.paperspace,
+            cmd_opts.is_cli,
+            cmd_opts.theme,
+            cmd_opts.dml,
+        )
+
+    # has_mps is only available in nightly pytorch (for now) and MasOS 12.3+.
+    # check `getattr` and try it for compatibility
+    @staticmethod
+    def has_mps() -> bool:
+        if not torch.backends.mps.is_available():
+            return False
+        try:
+            torch.zeros(1).to(torch.device("mps"))
+            return True
+        except Exception:
+            return False
+        
+    @staticmethod
+    def has_xpu() -> bool:
+        if hasattr(torch, "xpu") and torch.xpu.is_available():
+            return True
+        else:
+            return False
+
+    def use_fp32_config(self):
+        for config_file in version_config_list:
+            self.json_config[config_file]["train"]["fp16_run"] = False
+
+    def device_config(self) -> tuple:
+        if torch.cuda.is_available():
+            if self.has_xpu():
+                self.device = self.instead = "xpu:0"
+                self.is_half = True
+            i_device = int(self.device.split(":")[-1])
+            self.gpu_name = torch.cuda.get_device_name(i_device)
+            if (
+                ("16" in self.gpu_name and "V100" not in self.gpu_name.upper())
+                or "P40" in self.gpu_name.upper()
+                or "P10" in self.gpu_name.upper()
+                or "1060" in self.gpu_name
+                or "1070" in self.gpu_name
+                or "1080" in self.gpu_name
+            ):
+                logger.info("Found GPU %s, force to fp32", self.gpu_name)
+                self.is_half = False
+                self.use_fp32_config()
+            else:
+                logger.info("Found GPU %s", self.gpu_name)
+            self.gpu_mem = int(
+                torch.cuda.get_device_properties(i_device).total_memory
+                / 1024
+                / 1024
+                / 1024
+                + 0.4
+            )
+            if self.gpu_mem <= 4:
+                with open("infer/modules/train/preprocess.py", "r") as f:
+                    strr = f.read().replace("3.7", "3.0")
+                with open("infer/modules/train/preprocess.py", "w") as f:
+                    f.write(strr)
+        elif self.has_mps():
+            logger.info("No supported Nvidia GPU found")
+            self.device = self.instead = "mps"
+            self.is_half = False
+            self.use_fp32_config()
+        else:
+            logger.info("No supported Nvidia GPU found")
+            self.device = self.instead = "cpu"
+            self.is_half = False
+            self.use_fp32_config()
+
+        if self.n_cpu == 0:
+            self.n_cpu = cpu_count()
+
+        if self.is_half:
+            # 6G显存配置
+            x_pad = 3
+            x_query = 10
+            x_center = 60
+            x_max = 65
+        else:
+            # 5G显存配置
+            x_pad = 1
+            x_query = 6
+            x_center = 38
+            x_max = 41
+
+        if self.gpu_mem is not None and self.gpu_mem <= 4:
+            x_pad = 1
+            x_query = 5
+            x_center = 30
+            x_max = 32
+        if self.dml:
+            logger.info("Use DirectML instead")
+            if (
+                os.path.exists(
+                    "runtime\Lib\site-packages\onnxruntime\capi\DirectML.dll"
+                )
+                == False
+            ):
+                try:
+                    os.rename(
+                        "runtime\Lib\site-packages\onnxruntime",
+                        "runtime\Lib\site-packages\onnxruntime-cuda",
+                    )
+                except:
+                    pass
+                try:
+                    os.rename(
+                        "runtime\Lib\site-packages\onnxruntime-dml",
+                        "runtime\Lib\site-packages\onnxruntime",
+                    )
+                except:
+                    pass
+            # if self.device != "cpu":
+            import torch_directml
+
+            self.device = torch_directml.device(torch_directml.default_device())
+            self.is_half = False
+        else:
+            if self.instead:
+                logger.info(f"Use {self.instead} instead")
+            if (
+                os.path.exists(
+                    "runtime\Lib\site-packages\onnxruntime\capi\onnxruntime_providers_cuda.dll"
+                )
+                == False
+            ):
+                try:
+                    os.rename(
+                        "runtime\Lib\site-packages\onnxruntime",
+                        "runtime\Lib\site-packages\onnxruntime-dml",
+                    )
+                except:
+                    pass
+                try:
+                    os.rename(
+                        "runtime\Lib\site-packages\onnxruntime-cuda",
+                        "runtime\Lib\site-packages\onnxruntime",
+                    )
+                except:
+                    pass
+        return x_pad, x_query, x_center, x_max
diff --git a/configs/v1/32k.json b/configs/v1/32k.json
new file mode 100644
index 0000000000000000000000000000000000000000..d5f16d691ed798f4c974b431167c36269b2ce7d2
--- /dev/null
+++ b/configs/v1/32k.json
@@ -0,0 +1,46 @@
+{
+  "train": {
+    "log_interval": 200,
+    "seed": 1234,
+    "epochs": 20000,
+    "learning_rate": 1e-4,
+    "betas": [0.8, 0.99],
+    "eps": 1e-9,
+    "batch_size": 4,
+    "fp16_run": true,
+    "lr_decay": 0.999875,
+    "segment_size": 12800,
+    "init_lr_ratio": 1,
+    "warmup_epochs": 0,
+    "c_mel": 45,
+    "c_kl": 1.0
+  },
+  "data": {
+    "max_wav_value": 32768.0,
+    "sampling_rate": 32000,
+    "filter_length": 1024,
+    "hop_length": 320,
+    "win_length": 1024,
+    "n_mel_channels": 80,
+    "mel_fmin": 0.0,
+    "mel_fmax": null
+  },
+  "model": {
+    "inter_channels": 192,
+    "hidden_channels": 192,
+    "filter_channels": 768,
+    "n_heads": 2,
+    "n_layers": 6,
+    "kernel_size": 3,
+    "p_dropout": 0,
+    "resblock": "1",
+    "resblock_kernel_sizes": [3,7,11],
+    "resblock_dilation_sizes": [[1,3,5], [1,3,5], [1,3,5]],
+    "upsample_rates": [10,4,2,2,2],
+    "upsample_initial_channel": 512,
+    "upsample_kernel_sizes": [16,16,4,4,4],
+    "use_spectral_norm": false,
+    "gin_channels": 256,
+    "spk_embed_dim": 109
+  }
+}
diff --git a/configs/v1/40k.json b/configs/v1/40k.json
new file mode 100644
index 0000000000000000000000000000000000000000..4ffc87b9e9725fcd59d81a68d41a61962213b777
--- /dev/null
+++ b/configs/v1/40k.json
@@ -0,0 +1,46 @@
+{
+  "train": {
+    "log_interval": 200,
+    "seed": 1234,
+    "epochs": 20000,
+    "learning_rate": 1e-4,
+    "betas": [0.8, 0.99],
+    "eps": 1e-9,
+    "batch_size": 4,
+    "fp16_run": true,
+    "lr_decay": 0.999875,
+    "segment_size": 12800,
+    "init_lr_ratio": 1,
+    "warmup_epochs": 0,
+    "c_mel": 45,
+    "c_kl": 1.0
+  },
+  "data": {
+    "max_wav_value": 32768.0,
+    "sampling_rate": 40000,
+    "filter_length": 2048,
+    "hop_length": 400,
+    "win_length": 2048,
+    "n_mel_channels": 125,
+    "mel_fmin": 0.0,
+    "mel_fmax": null
+  },
+  "model": {
+    "inter_channels": 192,
+    "hidden_channels": 192,
+    "filter_channels": 768,
+    "n_heads": 2,
+    "n_layers": 6,
+    "kernel_size": 3,
+    "p_dropout": 0,
+    "resblock": "1",
+    "resblock_kernel_sizes": [3,7,11],
+    "resblock_dilation_sizes": [[1,3,5], [1,3,5], [1,3,5]],
+    "upsample_rates": [10,10,2,2],
+    "upsample_initial_channel": 512,
+    "upsample_kernel_sizes": [16,16,4,4],
+    "use_spectral_norm": false,
+    "gin_channels": 256,
+    "spk_embed_dim": 109
+  }
+}
diff --git a/configs/v1/48k.json b/configs/v1/48k.json
new file mode 100644
index 0000000000000000000000000000000000000000..2d0e05beb794f6f61b769b48c7ae728bf59e6335
--- /dev/null
+++ b/configs/v1/48k.json
@@ -0,0 +1,46 @@
+{
+  "train": {
+    "log_interval": 200,
+    "seed": 1234,
+    "epochs": 20000,
+    "learning_rate": 1e-4,
+    "betas": [0.8, 0.99],
+    "eps": 1e-9,
+    "batch_size": 4,
+    "fp16_run": true,
+    "lr_decay": 0.999875,
+    "segment_size": 11520,
+    "init_lr_ratio": 1,
+    "warmup_epochs": 0,
+    "c_mel": 45,
+    "c_kl": 1.0
+  },
+  "data": {
+    "max_wav_value": 32768.0,
+    "sampling_rate": 48000,
+    "filter_length": 2048,
+    "hop_length": 480,
+    "win_length": 2048,
+    "n_mel_channels": 128,
+    "mel_fmin": 0.0,
+    "mel_fmax": null
+  },
+  "model": {
+    "inter_channels": 192,
+    "hidden_channels": 192,
+    "filter_channels": 768,
+    "n_heads": 2,
+    "n_layers": 6,
+    "kernel_size": 3,
+    "p_dropout": 0,
+    "resblock": "1",
+    "resblock_kernel_sizes": [3,7,11],
+    "resblock_dilation_sizes": [[1,3,5], [1,3,5], [1,3,5]],
+    "upsample_rates": [10,6,2,2,2],
+    "upsample_initial_channel": 512,
+    "upsample_kernel_sizes": [16,16,4,4,4],
+    "use_spectral_norm": false,
+    "gin_channels": 256,
+    "spk_embed_dim": 109
+  }
+}
diff --git a/configs/v2/32k.json b/configs/v2/32k.json
new file mode 100644
index 0000000000000000000000000000000000000000..70e534f4c641a5a2c8e5c1e172f61398ee97e6e0
--- /dev/null
+++ b/configs/v2/32k.json
@@ -0,0 +1,46 @@
+{
+  "train": {
+    "log_interval": 200,
+    "seed": 1234,
+    "epochs": 20000,
+    "learning_rate": 1e-4,
+    "betas": [0.8, 0.99],
+    "eps": 1e-9,
+    "batch_size": 4,
+    "fp16_run": true,
+    "lr_decay": 0.999875,
+    "segment_size": 12800,
+    "init_lr_ratio": 1,
+    "warmup_epochs": 0,
+    "c_mel": 45,
+    "c_kl": 1.0
+  },
+  "data": {
+    "max_wav_value": 32768.0,
+    "sampling_rate": 32000,
+    "filter_length": 1024,
+    "hop_length": 320,
+    "win_length": 1024,
+    "n_mel_channels": 80,
+    "mel_fmin": 0.0,
+    "mel_fmax": null
+  },
+  "model": {
+    "inter_channels": 192,
+    "hidden_channels": 192,
+    "filter_channels": 768,
+    "n_heads": 2,
+    "n_layers": 6,
+    "kernel_size": 3,
+    "p_dropout": 0,
+    "resblock": "1",
+    "resblock_kernel_sizes": [3,7,11],
+    "resblock_dilation_sizes": [[1,3,5], [1,3,5], [1,3,5]],
+    "upsample_rates": [10,8,2,2],
+    "upsample_initial_channel": 512,
+    "upsample_kernel_sizes": [20,16,4,4],
+    "use_spectral_norm": false,
+    "gin_channels": 256,
+    "spk_embed_dim": 109
+  }
+}
diff --git a/configs/v2/48k.json b/configs/v2/48k.json
new file mode 100644
index 0000000000000000000000000000000000000000..75f770cdacff3467e9e925ed2393b480881d0303
--- /dev/null
+++ b/configs/v2/48k.json
@@ -0,0 +1,46 @@
+{
+  "train": {
+    "log_interval": 200,
+    "seed": 1234,
+    "epochs": 20000,
+    "learning_rate": 1e-4,
+    "betas": [0.8, 0.99],
+    "eps": 1e-9,
+    "batch_size": 4,
+    "fp16_run": true,
+    "lr_decay": 0.999875,
+    "segment_size": 17280,
+    "init_lr_ratio": 1,
+    "warmup_epochs": 0,
+    "c_mel": 45,
+    "c_kl": 1.0
+  },
+  "data": {
+    "max_wav_value": 32768.0,
+    "sampling_rate": 48000,
+    "filter_length": 2048,
+    "hop_length": 480,
+    "win_length": 2048,
+    "n_mel_channels": 128,
+    "mel_fmin": 0.0,
+    "mel_fmax": null
+  },
+  "model": {
+    "inter_channels": 192,
+    "hidden_channels": 192,
+    "filter_channels": 768,
+    "n_heads": 2,
+    "n_layers": 6,
+    "kernel_size": 3,
+    "p_dropout": 0,
+    "resblock": "1",
+    "resblock_kernel_sizes": [3,7,11],
+    "resblock_dilation_sizes": [[1,3,5], [1,3,5], [1,3,5]],
+    "upsample_rates": [12,10,2,2],
+    "upsample_initial_channel": 512,
+    "upsample_kernel_sizes": [24,20,4,4],
+    "use_spectral_norm": false,
+    "gin_channels": 256,
+    "spk_embed_dim": 109
+  }
+}
diff --git a/csvdb/formanting.csv b/csvdb/formanting.csv
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/csvdb/stop.csv b/csvdb/stop.csv
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/demucs/__init__.py b/demucs/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..d4182e356427e1b05a79f8da641c70bb732514fa
--- /dev/null
+++ b/demucs/__init__.py
@@ -0,0 +1,7 @@
+# Copyright (c) Facebook, Inc. and its affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the license found in the
+# LICENSE file in the root directory of this source tree.
+
+__version__ = "2.0.3"
diff --git a/demucs/__main__.py b/demucs/__main__.py
new file mode 100644
index 0000000000000000000000000000000000000000..5148f20623bdaa827777558844796ded1876d7d0
--- /dev/null
+++ b/demucs/__main__.py
@@ -0,0 +1,317 @@
+# Copyright (c) Facebook, Inc. and its affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the license found in the
+# LICENSE file in the root directory of this source tree.
+
+import json
+import math
+import os
+import sys
+import time
+from dataclasses import dataclass, field
+
+import torch as th
+from torch import distributed, nn
+from torch.nn.parallel.distributed import DistributedDataParallel
+
+from .augment import FlipChannels, FlipSign, Remix, Scale, Shift
+from .compressed import get_compressed_datasets
+from .model import Demucs
+from .parser import get_name, get_parser
+from .raw import Rawset
+from .repitch import RepitchedWrapper
+from .pretrained import load_pretrained, SOURCES
+from .tasnet import ConvTasNet
+from .test import evaluate
+from .train import train_model, validate_model
+from .utils import (human_seconds, load_model, save_model, get_state,
+                    save_state, sizeof_fmt, get_quantizer)
+from .wav import get_wav_datasets, get_musdb_wav_datasets
+
+
+@dataclass
+class SavedState:
+    metrics: list = field(default_factory=list)
+    last_state: dict = None
+    best_state: dict = None
+    optimizer: dict = None
+
+
+def main():
+    parser = get_parser()
+    args = parser.parse_args()
+    name = get_name(parser, args)
+    print(f"Experiment {name}")
+
+    if args.musdb is None and args.rank == 0:
+        print(
+            "You must provide the path to the MusDB dataset with the --musdb flag. "
+            "To download the MusDB dataset, see https://sigsep.github.io/datasets/musdb.html.",
+            file=sys.stderr)
+        sys.exit(1)
+
+    eval_folder = args.evals / name
+    eval_folder.mkdir(exist_ok=True, parents=True)
+    args.logs.mkdir(exist_ok=True)
+    metrics_path = args.logs / f"{name}.json"
+    eval_folder.mkdir(exist_ok=True, parents=True)
+    args.checkpoints.mkdir(exist_ok=True, parents=True)
+    args.models.mkdir(exist_ok=True, parents=True)
+
+    if args.device is None:
+        device = "cpu"
+        if th.cuda.is_available():
+            device = "cuda"
+    else:
+        device = args.device
+
+    th.manual_seed(args.seed)
+    # Prevents too many threads to be started when running `museval` as it can be quite
+    # inefficient on NUMA architectures.
+    os.environ["OMP_NUM_THREADS"] = "1"
+    os.environ["MKL_NUM_THREADS"] = "1"
+
+    if args.world_size > 1:
+        if device != "cuda" and args.rank == 0:
+            print("Error: distributed training is only available with cuda device", file=sys.stderr)
+            sys.exit(1)
+        th.cuda.set_device(args.rank % th.cuda.device_count())
+        distributed.init_process_group(backend="nccl",
+                                       init_method="tcp://" + args.master,
+                                       rank=args.rank,
+                                       world_size=args.world_size)
+
+    checkpoint = args.checkpoints / f"{name}.th"
+    checkpoint_tmp = args.checkpoints / f"{name}.th.tmp"
+    if args.restart and checkpoint.exists() and args.rank == 0:
+        checkpoint.unlink()
+
+    if args.test or args.test_pretrained:
+        args.epochs = 1
+        args.repeat = 0
+        if args.test:
+            model = load_model(args.models / args.test)
+        else:
+            model = load_pretrained(args.test_pretrained)
+    elif args.tasnet:
+        model = ConvTasNet(audio_channels=args.audio_channels,
+                           samplerate=args.samplerate, X=args.X,
+                           segment_length=4 * args.samples,
+                           sources=SOURCES)
+    else:
+        model = Demucs(
+            audio_channels=args.audio_channels,
+            channels=args.channels,
+            context=args.context,
+            depth=args.depth,
+            glu=args.glu,
+            growth=args.growth,
+            kernel_size=args.kernel_size,
+            lstm_layers=args.lstm_layers,
+            rescale=args.rescale,
+            rewrite=args.rewrite,
+            stride=args.conv_stride,
+            resample=args.resample,
+            normalize=args.normalize,
+            samplerate=args.samplerate,
+            segment_length=4 * args.samples,
+            sources=SOURCES,
+        )
+    model.to(device)
+    if args.init:
+        model.load_state_dict(load_pretrained(args.init).state_dict())
+
+    if args.show:
+        print(model)
+        size = sizeof_fmt(4 * sum(p.numel() for p in model.parameters()))
+        print(f"Model size {size}")
+        return
+
+    try:
+        saved = th.load(checkpoint, map_location='cpu')
+    except IOError:
+        saved = SavedState()
+
+    optimizer = th.optim.Adam(model.parameters(), lr=args.lr)
+
+    quantizer = None
+    quantizer = get_quantizer(model, args, optimizer)
+
+    if saved.last_state is not None:
+        model.load_state_dict(saved.last_state, strict=False)
+    if saved.optimizer is not None:
+        optimizer.load_state_dict(saved.optimizer)
+
+    model_name = f"{name}.th"
+    if args.save_model:
+        if args.rank == 0:
+            model.to("cpu")
+            model.load_state_dict(saved.best_state)
+            save_model(model, quantizer, args, args.models / model_name)
+        return
+    elif args.save_state:
+        model_name = f"{args.save_state}.th"
+        if args.rank == 0:
+            model.to("cpu")
+            model.load_state_dict(saved.best_state)
+            state = get_state(model, quantizer)
+            save_state(state, args.models / model_name)
+        return
+
+    if args.rank == 0:
+        done = args.logs / f"{name}.done"
+        if done.exists():
+            done.unlink()
+
+    augment = [Shift(args.data_stride)]
+    if args.augment:
+        augment += [FlipSign(), FlipChannels(), Scale(),
+                    Remix(group_size=args.remix_group_size)]
+    augment = nn.Sequential(*augment).to(device)
+    print("Agumentation pipeline:", augment)
+
+    if args.mse:
+        criterion = nn.MSELoss()
+    else:
+        criterion = nn.L1Loss()
+
+    # Setting number of samples so that all convolution windows are full.
+    # Prevents hard to debug mistake with the prediction being shifted compared
+    # to the input mixture.
+    samples = model.valid_length(args.samples)
+    print(f"Number of training samples adjusted to {samples}")
+    samples = samples + args.data_stride
+    if args.repitch:
+        # We need a bit more audio samples, to account for potential
+        # tempo change.
+        samples = math.ceil(samples / (1 - 0.01 * args.max_tempo))
+
+    args.metadata.mkdir(exist_ok=True, parents=True)
+    if args.raw:
+        train_set = Rawset(args.raw / "train",
+                           samples=samples,
+                           channels=args.audio_channels,
+                           streams=range(1, len(model.sources) + 1),
+                           stride=args.data_stride)
+
+        valid_set = Rawset(args.raw / "valid", channels=args.audio_channels)
+    elif args.wav:
+        train_set, valid_set = get_wav_datasets(args, samples, model.sources)
+    elif args.is_wav:
+        train_set, valid_set = get_musdb_wav_datasets(args, samples, model.sources)
+    else:
+        train_set, valid_set = get_compressed_datasets(args, samples)
+
+    if args.repitch:
+        train_set = RepitchedWrapper(
+            train_set,
+            proba=args.repitch,
+            max_tempo=args.max_tempo)
+
+    best_loss = float("inf")
+    for epoch, metrics in enumerate(saved.metrics):
+        print(f"Epoch {epoch:03d}: "
+              f"train={metrics['train']:.8f} "
+              f"valid={metrics['valid']:.8f} "
+              f"best={metrics['best']:.4f} "
+              f"ms={metrics.get('true_model_size', 0):.2f}MB "
+              f"cms={metrics.get('compressed_model_size', 0):.2f}MB "
+              f"duration={human_seconds(metrics['duration'])}")
+        best_loss = metrics['best']
+
+    if args.world_size > 1:
+        dmodel = DistributedDataParallel(model,
+                                         device_ids=[th.cuda.current_device()],
+                                         output_device=th.cuda.current_device())
+    else:
+        dmodel = model
+
+    for epoch in range(len(saved.metrics), args.epochs):
+        begin = time.time()
+        model.train()
+        train_loss, model_size = train_model(
+            epoch, train_set, dmodel, criterion, optimizer, augment,
+            quantizer=quantizer,
+            batch_size=args.batch_size,
+            device=device,
+            repeat=args.repeat,
+            seed=args.seed,
+            diffq=args.diffq,
+            workers=args.workers,
+            world_size=args.world_size)
+        model.eval()
+        valid_loss = validate_model(
+            epoch, valid_set, model, criterion,
+            device=device,
+            rank=args.rank,
+            split=args.split_valid,
+            overlap=args.overlap,
+            world_size=args.world_size)
+
+        ms = 0
+        cms = 0
+        if quantizer and args.rank == 0:
+            ms = quantizer.true_model_size()
+            cms = quantizer.compressed_model_size(num_workers=min(40, args.world_size * 10))
+
+        duration = time.time() - begin
+        if valid_loss < best_loss and ms <= args.ms_target:
+            best_loss = valid_loss
+            saved.best_state = {
+                key: value.to("cpu").clone()
+                for key, value in model.state_dict().items()
+            }
+
+        saved.metrics.append({
+            "train": train_loss,
+            "valid": valid_loss,
+            "best": best_loss,
+            "duration": duration,
+            "model_size": model_size,
+            "true_model_size": ms,
+            "compressed_model_size": cms,
+        })
+        if args.rank == 0:
+            json.dump(saved.metrics, open(metrics_path, "w"))
+
+        saved.last_state = model.state_dict()
+        saved.optimizer = optimizer.state_dict()
+        if args.rank == 0 and not args.test:
+            th.save(saved, checkpoint_tmp)
+            checkpoint_tmp.rename(checkpoint)
+
+        print(f"Epoch {epoch:03d}: "
+              f"train={train_loss:.8f} valid={valid_loss:.8f} best={best_loss:.4f} ms={ms:.2f}MB "
+              f"cms={cms:.2f}MB "
+              f"duration={human_seconds(duration)}")
+
+    if args.world_size > 1:
+        distributed.barrier()
+
+    del dmodel
+    model.load_state_dict(saved.best_state)
+    if args.eval_cpu:
+        device = "cpu"
+        model.to(device)
+    model.eval()
+    evaluate(model, args.musdb, eval_folder,
+             is_wav=args.is_wav,
+             rank=args.rank,
+             world_size=args.world_size,
+             device=device,
+             save=args.save,
+             split=args.split_valid,
+             shifts=args.shifts,
+             overlap=args.overlap,
+             workers=args.eval_workers)
+    model.to("cpu")
+    if args.rank == 0:
+        if not (args.test or args.test_pretrained):
+            save_model(model, quantizer, args, args.models / model_name)
+        print("done")
+        done.write_text("done")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/demucs/audio.py b/demucs/audio.py
new file mode 100644
index 0000000000000000000000000000000000000000..b29f156e4afb5fbda32c35777022caeadf50d711
--- /dev/null
+++ b/demucs/audio.py
@@ -0,0 +1,172 @@
+# Copyright (c) Facebook, Inc. and its affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the license found in the
+# LICENSE file in the root directory of this source tree.
+import json
+import subprocess as sp
+from pathlib import Path
+
+import julius
+import numpy as np
+import torch
+
+from .utils import temp_filenames
+
+
+def _read_info(path):
+    stdout_data = sp.check_output([
+        'ffprobe', "-loglevel", "panic",
+        str(path), '-print_format', 'json', '-show_format', '-show_streams'
+    ])
+    return json.loads(stdout_data.decode('utf-8'))
+
+
+class AudioFile:
+    """
+    Allows to read audio from any format supported by ffmpeg, as well as resampling or
+    converting to mono on the fly. See :method:`read` for more details.
+    """
+    def __init__(self, path: Path):
+        self.path = Path(path)
+        self._info = None
+
+    def __repr__(self):
+        features = [("path", self.path)]
+        features.append(("samplerate", self.samplerate()))
+        features.append(("channels", self.channels()))
+        features.append(("streams", len(self)))
+        features_str = ", ".join(f"{name}={value}" for name, value in features)
+        return f"AudioFile({features_str})"
+
+    @property
+    def info(self):
+        if self._info is None:
+            self._info = _read_info(self.path)
+        return self._info
+
+    @property
+    def duration(self):
+        return float(self.info['format']['duration'])
+
+    @property
+    def _audio_streams(self):
+        return [
+            index for index, stream in enumerate(self.info["streams"])
+            if stream["codec_type"] == "audio"
+        ]
+
+    def __len__(self):
+        return len(self._audio_streams)
+
+    def channels(self, stream=0):
+        return int(self.info['streams'][self._audio_streams[stream]]['channels'])
+
+    def samplerate(self, stream=0):
+        return int(self.info['streams'][self._audio_streams[stream]]['sample_rate'])
+
+    def read(self,
+             seek_time=None,
+             duration=None,
+             streams=slice(None),
+             samplerate=None,
+             channels=None,
+             temp_folder=None):
+        """
+        Slightly more efficient implementation than stempeg,
+        in particular, this will extract all stems at once
+        rather than having to loop over one file multiple times
+        for each stream.
+
+        Args:
+            seek_time (float):  seek time in seconds or None if no seeking is needed.
+            duration (float): duration in seconds to extract or None to extract until the end.
+            streams (slice, int or list): streams to extract, can be a single int, a list or
+                a slice. If it is a slice or list, the output will be of size [S, C, T]
+                with S the number of streams, C the number of channels and T the number of samples.
+                If it is an int, the output will be [C, T].
+            samplerate (int): if provided, will resample on the fly. If None, no resampling will
+                be done. Original sampling rate can be obtained with :method:`samplerate`.
+            channels (int): if 1, will convert to mono. We do not rely on ffmpeg for that
+                as ffmpeg automatically scale by +3dB to conserve volume when playing on speakers.
+                See https://sound.stackexchange.com/a/42710.
+                Our definition of mono is simply the average of the two channels. Any other
+                value will be ignored.
+            temp_folder (str or Path or None): temporary folder to use for decoding.
+
+
+        """
+        streams = np.array(range(len(self)))[streams]
+        single = not isinstance(streams, np.ndarray)
+        if single:
+            streams = [streams]
+
+        if duration is None:
+            target_size = None
+            query_duration = None
+        else:
+            target_size = int((samplerate or self.samplerate()) * duration)
+            query_duration = float((target_size + 1) / (samplerate or self.samplerate()))
+
+        with temp_filenames(len(streams)) as filenames:
+            command = ['ffmpeg', '-y']
+            command += ['-loglevel', 'panic']
+            if seek_time:
+                command += ['-ss', str(seek_time)]
+            command += ['-i', str(self.path)]
+            for stream, filename in zip(streams, filenames):
+                command += ['-map', f'0:{self._audio_streams[stream]}']
+                if query_duration is not None:
+                    command += ['-t', str(query_duration)]
+                command += ['-threads', '1']
+                command += ['-f', 'f32le']
+                if samplerate is not None:
+                    command += ['-ar', str(samplerate)]
+                command += [filename]
+
+            sp.run(command, check=True)
+            wavs = []
+            for filename in filenames:
+                wav = np.fromfile(filename, dtype=np.float32)
+                wav = torch.from_numpy(wav)
+                wav = wav.view(-1, self.channels()).t()
+                if channels is not None:
+                    wav = convert_audio_channels(wav, channels)
+                if target_size is not None:
+                    wav = wav[..., :target_size]
+                wavs.append(wav)
+        wav = torch.stack(wavs, dim=0)
+        if single:
+            wav = wav[0]
+        return wav
+
+
+def convert_audio_channels(wav, channels=2):
+    """Convert audio to the given number of channels."""
+    *shape, src_channels, length = wav.shape
+    if src_channels == channels:
+        pass
+    elif channels == 1:
+        # Case 1:
+        # The caller asked 1-channel audio, but the stream have multiple
+        # channels, downmix all channels.
+        wav = wav.mean(dim=-2, keepdim=True)
+    elif src_channels == 1:
+        # Case 2:
+        # The caller asked for multiple channels, but the input file have
+        # one single channel, replicate the audio over all channels.
+        wav = wav.expand(*shape, channels, length)
+    elif src_channels >= channels:
+        # Case 3:
+        # The caller asked for multiple channels, and the input file have
+        # more channels than requested. In that case return the first channels.
+        wav = wav[..., :channels, :]
+    else:
+        # Case 4: What is a reasonable choice here?
+        raise ValueError('The audio file has less channels than requested but is not mono.')
+    return wav
+
+
+def convert_audio(wav, from_samplerate, to_samplerate, channels):
+    wav = convert_audio_channels(wav, channels)
+    return julius.resample_frac(wav, from_samplerate, to_samplerate)
diff --git a/demucs/augment.py b/demucs/augment.py
new file mode 100644
index 0000000000000000000000000000000000000000..bb36d3298d89470f306316322e7587187819c94b
--- /dev/null
+++ b/demucs/augment.py
@@ -0,0 +1,106 @@
+# Copyright (c) Facebook, Inc. and its affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the license found in the
+# LICENSE file in the root directory of this source tree.
+
+import random
+import torch as th
+from torch import nn
+
+
+class Shift(nn.Module):
+    """
+    Randomly shift audio in time by up to `shift` samples.
+    """
+    def __init__(self, shift=8192):
+        super().__init__()
+        self.shift = shift
+
+    def forward(self, wav):
+        batch, sources, channels, time = wav.size()
+        length = time - self.shift
+        if self.shift > 0:
+            if not self.training:
+                wav = wav[..., :length]
+            else:
+                offsets = th.randint(self.shift, [batch, sources, 1, 1], device=wav.device)
+                offsets = offsets.expand(-1, -1, channels, -1)
+                indexes = th.arange(length, device=wav.device)
+                wav = wav.gather(3, indexes + offsets)
+        return wav
+
+
+class FlipChannels(nn.Module):
+    """
+    Flip left-right channels.
+    """
+    def forward(self, wav):
+        batch, sources, channels, time = wav.size()
+        if self.training and wav.size(2) == 2:
+            left = th.randint(2, (batch, sources, 1, 1), device=wav.device)
+            left = left.expand(-1, -1, -1, time)
+            right = 1 - left
+            wav = th.cat([wav.gather(2, left), wav.gather(2, right)], dim=2)
+        return wav
+
+
+class FlipSign(nn.Module):
+    """
+    Random sign flip.
+    """
+    def forward(self, wav):
+        batch, sources, channels, time = wav.size()
+        if self.training:
+            signs = th.randint(2, (batch, sources, 1, 1), device=wav.device, dtype=th.float32)
+            wav = wav * (2 * signs - 1)
+        return wav
+
+
+class Remix(nn.Module):
+    """
+    Shuffle sources to make new mixes.
+    """
+    def __init__(self, group_size=4):
+        """
+        Shuffle sources within one batch.
+        Each batch is divided into groups of size `group_size` and shuffling is done within
+        each group separatly. This allow to keep the same probability distribution no matter
+        the number of GPUs. Without this grouping, using more GPUs would lead to a higher
+        probability of keeping two sources from the same track together which can impact
+        performance.
+        """
+        super().__init__()
+        self.group_size = group_size
+
+    def forward(self, wav):
+        batch, streams, channels, time = wav.size()
+        device = wav.device
+
+        if self.training:
+            group_size = self.group_size or batch
+            if batch % group_size != 0:
+                raise ValueError(f"Batch size {batch} must be divisible by group size {group_size}")
+            groups = batch // group_size
+            wav = wav.view(groups, group_size, streams, channels, time)
+            permutations = th.argsort(th.rand(groups, group_size, streams, 1, 1, device=device),
+                                      dim=1)
+            wav = wav.gather(1, permutations.expand(-1, -1, -1, channels, time))
+            wav = wav.view(batch, streams, channels, time)
+        return wav
+
+
+class Scale(nn.Module):
+    def __init__(self, proba=1., min=0.25, max=1.25):
+        super().__init__()
+        self.proba = proba
+        self.min = min
+        self.max = max
+
+    def forward(self, wav):
+        batch, streams, channels, time = wav.size()
+        device = wav.device
+        if self.training and random.random() < self.proba:
+            scales = th.empty(batch, streams, 1, 1, device=device).uniform_(self.min, self.max)
+            wav *= scales
+        return wav
diff --git a/demucs/compressed.py b/demucs/compressed.py
new file mode 100644
index 0000000000000000000000000000000000000000..eb8fbb75463ba71ca86729b22baebf24598ade57
--- /dev/null
+++ b/demucs/compressed.py
@@ -0,0 +1,115 @@
+# Copyright (c) Facebook, Inc. and its affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the license found in the
+# LICENSE file in the root directory of this source tree.
+
+import json
+from fractions import Fraction
+from concurrent import futures
+
+import musdb
+from torch import distributed
+
+from .audio import AudioFile
+
+
+def get_musdb_tracks(root, *args, **kwargs):
+    mus = musdb.DB(root, *args, **kwargs)
+    return {track.name: track.path for track in mus}
+
+
+class StemsSet:
+    def __init__(self, tracks, metadata, duration=None, stride=1,
+                 samplerate=44100, channels=2, streams=slice(None)):
+
+        self.metadata = []
+        for name, path in tracks.items():
+            meta = dict(metadata[name])
+            meta["path"] = path
+            meta["name"] = name
+            self.metadata.append(meta)
+            if duration is not None and meta["duration"] < duration:
+                raise ValueError(f"Track {name} duration is too small {meta['duration']}")
+        self.metadata.sort(key=lambda x: x["name"])
+        self.duration = duration
+        self.stride = stride
+        self.channels = channels
+        self.samplerate = samplerate
+        self.streams = streams
+
+    def __len__(self):
+        return sum(self._examples_count(m) for m in self.metadata)
+
+    def _examples_count(self, meta):
+        if self.duration is None:
+            return 1
+        else:
+            return int((meta["duration"] - self.duration) // self.stride + 1)
+
+    def track_metadata(self, index):
+        for meta in self.metadata:
+            examples = self._examples_count(meta)
+            if index >= examples:
+                index -= examples
+                continue
+            return meta
+
+    def __getitem__(self, index):
+        for meta in self.metadata:
+            examples = self._examples_count(meta)
+            if index >= examples:
+                index -= examples
+                continue
+            streams = AudioFile(meta["path"]).read(seek_time=index * self.stride,
+                                                   duration=self.duration,
+                                                   channels=self.channels,
+                                                   samplerate=self.samplerate,
+                                                   streams=self.streams)
+            return (streams - meta["mean"]) / meta["std"]
+
+
+def _get_track_metadata(path):
+    # use mono at 44kHz as reference. For any other settings data won't be perfectly
+    # normalized but it should be good enough.
+    audio = AudioFile(path)
+    mix = audio.read(streams=0, channels=1, samplerate=44100)
+    return {"duration": audio.duration, "std": mix.std().item(), "mean": mix.mean().item()}
+
+
+def _build_metadata(tracks, workers=10):
+    pendings = []
+    with futures.ProcessPoolExecutor(workers) as pool:
+        for name, path in tracks.items():
+            pendings.append((name, pool.submit(_get_track_metadata, path)))
+    return {name: p.result() for name, p in pendings}
+
+
+def _build_musdb_metadata(path, musdb, workers):
+    tracks = get_musdb_tracks(musdb)
+    metadata = _build_metadata(tracks, workers)
+    path.parent.mkdir(exist_ok=True, parents=True)
+    json.dump(metadata, open(path, "w"))
+
+
+def get_compressed_datasets(args, samples):
+    metadata_file = args.metadata / "musdb.json"
+    if not metadata_file.is_file() and args.rank == 0:
+        _build_musdb_metadata(metadata_file, args.musdb, args.workers)
+    if args.world_size > 1:
+        distributed.barrier()
+    metadata = json.load(open(metadata_file))
+    duration = Fraction(samples, args.samplerate)
+    stride = Fraction(args.data_stride, args.samplerate)
+    train_set = StemsSet(get_musdb_tracks(args.musdb, subsets=["train"], split="train"),
+                         metadata,
+                         duration=duration,
+                         stride=stride,
+                         streams=slice(1, None),
+                         samplerate=args.samplerate,
+                         channels=args.audio_channels)
+    valid_set = StemsSet(get_musdb_tracks(args.musdb, subsets=["train"], split="valid"),
+                         metadata,
+                         samplerate=args.samplerate,
+                         channels=args.audio_channels)
+    return train_set, valid_set
diff --git a/demucs/model.py b/demucs/model.py
new file mode 100644
index 0000000000000000000000000000000000000000..e9d932f4d014f7b95b394d2e24ed5edc379ded8d
--- /dev/null
+++ b/demucs/model.py
@@ -0,0 +1,202 @@
+# Copyright (c) Facebook, Inc. and its affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the license found in the
+# LICENSE file in the root directory of this source tree.
+
+import math
+
+import julius
+from torch import nn
+
+from .utils import capture_init, center_trim
+
+
+class BLSTM(nn.Module):
+    def __init__(self, dim, layers=1):
+        super().__init__()
+        self.lstm = nn.LSTM(bidirectional=True, num_layers=layers, hidden_size=dim, input_size=dim)
+        self.linear = nn.Linear(2 * dim, dim)
+
+    def forward(self, x):
+        x = x.permute(2, 0, 1)
+        x = self.lstm(x)[0]
+        x = self.linear(x)
+        x = x.permute(1, 2, 0)
+        return x
+
+
+def rescale_conv(conv, reference):
+    std = conv.weight.std().detach()
+    scale = (std / reference)**0.5
+    conv.weight.data /= scale
+    if conv.bias is not None:
+        conv.bias.data /= scale
+
+
+def rescale_module(module, reference):
+    for sub in module.modules():
+        if isinstance(sub, (nn.Conv1d, nn.ConvTranspose1d)):
+            rescale_conv(sub, reference)
+
+
+class Demucs(nn.Module):
+    @capture_init
+    def __init__(self,
+                 sources,
+                 audio_channels=2,
+                 channels=64,
+                 depth=6,
+                 rewrite=True,
+                 glu=True,
+                 rescale=0.1,
+                 resample=True,
+                 kernel_size=8,
+                 stride=4,
+                 growth=2.,
+                 lstm_layers=2,
+                 context=3,
+                 normalize=False,
+                 samplerate=44100,
+                 segment_length=4 * 10 * 44100):
+        """
+        Args:
+            sources (list[str]): list of source names
+            audio_channels (int): stereo or mono
+            channels (int): first convolution channels
+            depth (int): number of encoder/decoder layers
+            rewrite (bool): add 1x1 convolution to each encoder layer
+                and a convolution to each decoder layer.
+                For the decoder layer, `context` gives the kernel size.
+            glu (bool): use glu instead of ReLU
+            resample_input (bool): upsample x2 the input and downsample /2 the output.
+            rescale (int): rescale initial weights of convolutions
+                to get their standard deviation closer to `rescale`
+            kernel_size (int): kernel size for convolutions
+            stride (int): stride for convolutions
+            growth (float): multiply (resp divide) number of channels by that
+                for each layer of the encoder (resp decoder)
+            lstm_layers (int): number of lstm layers, 0 = no lstm
+            context (int): kernel size of the convolution in the
+                decoder before the transposed convolution. If > 1,
+                will provide some context from neighboring time
+                steps.
+            samplerate (int): stored as meta information for easing
+                future evaluations of the model.
+            segment_length (int): stored as meta information for easing
+                future evaluations of the model. Length of the segments on which
+                the model was trained.
+        """
+
+        super().__init__()
+        self.audio_channels = audio_channels
+        self.sources = sources
+        self.kernel_size = kernel_size
+        self.context = context
+        self.stride = stride
+        self.depth = depth
+        self.resample = resample
+        self.channels = channels
+        self.normalize = normalize
+        self.samplerate = samplerate
+        self.segment_length = segment_length
+
+        self.encoder = nn.ModuleList()
+        self.decoder = nn.ModuleList()
+
+        if glu:
+            activation = nn.GLU(dim=1)
+            ch_scale = 2
+        else:
+            activation = nn.ReLU()
+            ch_scale = 1
+        in_channels = audio_channels
+        for index in range(depth):
+            encode = []
+            encode += [nn.Conv1d(in_channels, channels, kernel_size, stride), nn.ReLU()]
+            if rewrite:
+                encode += [nn.Conv1d(channels, ch_scale * channels, 1), activation]
+            self.encoder.append(nn.Sequential(*encode))
+
+            decode = []
+            if index > 0:
+                out_channels = in_channels
+            else:
+                out_channels = len(self.sources) * audio_channels
+            if rewrite:
+                decode += [nn.Conv1d(channels, ch_scale * channels, context), activation]
+            decode += [nn.ConvTranspose1d(channels, out_channels, kernel_size, stride)]
+            if index > 0:
+                decode.append(nn.ReLU())
+            self.decoder.insert(0, nn.Sequential(*decode))
+            in_channels = channels
+            channels = int(growth * channels)
+
+        channels = in_channels
+
+        if lstm_layers:
+            self.lstm = BLSTM(channels, lstm_layers)
+        else:
+            self.lstm = None
+
+        if rescale:
+            rescale_module(self, reference=rescale)
+
+    def valid_length(self, length):
+        """
+        Return the nearest valid length to use with the model so that
+        there is no time steps left over in a convolutions, e.g. for all
+        layers, size of the input - kernel_size % stride = 0.
+
+        If the mixture has a valid length, the estimated sources
+        will have exactly the same length when context = 1. If context > 1,
+        the two signals can be center trimmed to match.
+
+        For training, extracts should have a valid length.For evaluation
+        on full tracks we recommend passing `pad = True` to :method:`forward`.
+        """
+        if self.resample:
+            length *= 2
+        for _ in range(self.depth):
+            length = math.ceil((length - self.kernel_size) / self.stride) + 1
+            length = max(1, length)
+            length += self.context - 1
+        for _ in range(self.depth):
+            length = (length - 1) * self.stride + self.kernel_size
+
+        if self.resample:
+            length = math.ceil(length / 2)
+        return int(length)
+
+    def forward(self, mix):
+        x = mix
+
+        if self.normalize:
+            mono = mix.mean(dim=1, keepdim=True)
+            mean = mono.mean(dim=-1, keepdim=True)
+            std = mono.std(dim=-1, keepdim=True)
+        else:
+            mean = 0
+            std = 1
+
+        x = (x - mean) / (1e-5 + std)
+
+        if self.resample:
+            x = julius.resample_frac(x, 1, 2)
+
+        saved = []
+        for encode in self.encoder:
+            x = encode(x)
+            saved.append(x)
+        if self.lstm:
+            x = self.lstm(x)
+        for decode in self.decoder:
+            skip = center_trim(saved.pop(-1), x)
+            x = x + skip
+            x = decode(x)
+
+        if self.resample:
+            x = julius.resample_frac(x, 2, 1)
+        x = x * std + mean
+        x = x.view(x.size(0), len(self.sources), self.audio_channels, x.size(-1))
+        return x
diff --git a/demucs/parser.py b/demucs/parser.py
new file mode 100644
index 0000000000000000000000000000000000000000..4e8a19cf976e3c6dfe411da64b8dce3e9a4548e0
--- /dev/null
+++ b/demucs/parser.py
@@ -0,0 +1,244 @@
+# Copyright (c) Facebook, Inc. and its affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the license found in the
+# LICENSE file in the root directory of this source tree.
+
+import argparse
+import os
+from pathlib import Path
+
+
+def get_parser():
+    parser = argparse.ArgumentParser("demucs", description="Train and evaluate Demucs.")
+    default_raw = None
+    default_musdb = None
+    if 'DEMUCS_RAW' in os.environ:
+        default_raw = Path(os.environ['DEMUCS_RAW'])
+    if 'DEMUCS_MUSDB' in os.environ:
+        default_musdb = Path(os.environ['DEMUCS_MUSDB'])
+    parser.add_argument(
+        "--raw",
+        type=Path,
+        default=default_raw,
+        help="Path to raw audio, can be faster, see python3 -m demucs.raw to extract.")
+    parser.add_argument("--no_raw", action="store_const", const=None, dest="raw")
+    parser.add_argument("-m",
+                        "--musdb",
+                        type=Path,
+                        default=default_musdb,
+                        help="Path to musdb root")
+    parser.add_argument("--is_wav", action="store_true",
+                        help="Indicate that the MusDB dataset is in wav format (i.e. MusDB-HQ).")
+    parser.add_argument("--metadata", type=Path, default=Path("metadata/"),
+                        help="Folder where metadata information is stored.")
+    parser.add_argument("--wav", type=Path,
+                        help="Path to a wav dataset. This should contain a 'train' and a 'valid' "
+                             "subfolder.")
+    parser.add_argument("--samplerate", type=int, default=44100)
+    parser.add_argument("--audio_channels", type=int, default=2)
+    parser.add_argument("--samples",
+                        default=44100 * 10,
+                        type=int,
+                        help="number of samples to feed in")
+    parser.add_argument("--data_stride",
+                        default=44100,
+                        type=int,
+                        help="Stride for chunks, shorter = longer epochs")
+    parser.add_argument("-w", "--workers", default=10, type=int, help="Loader workers")
+    parser.add_argument("--eval_workers", default=2, type=int, help="Final evaluation workers")
+    parser.add_argument("-d",
+                        "--device",
+                        help="Device to train on, default is cuda if available else cpu")
+    parser.add_argument("--eval_cpu", action="store_true", help="Eval on test will be run on cpu.")
+    parser.add_argument("--dummy", help="Dummy parameter, useful to create a new checkpoint file")
+    parser.add_argument("--test", help="Just run the test pipeline + one validation. "
+                                       "This should be a filename relative to the models/ folder.")
+    parser.add_argument("--test_pretrained", help="Just run the test pipeline + one validation, "
+                                                  "on a pretrained model. ")
+
+    parser.add_argument("--rank", default=0, type=int)
+    parser.add_argument("--world_size", default=1, type=int)
+    parser.add_argument("--master")
+
+    parser.add_argument("--checkpoints",
+                        type=Path,
+                        default=Path("checkpoints"),
+                        help="Folder where to store checkpoints etc")
+    parser.add_argument("--evals",
+                        type=Path,
+                        default=Path("evals"),
+                        help="Folder where to store evals and waveforms")
+    parser.add_argument("--save",
+                        action="store_true",
+                        help="Save estimated for the test set waveforms")
+    parser.add_argument("--logs",
+                        type=Path,
+                        default=Path("logs"),
+                        help="Folder where to store logs")
+    parser.add_argument("--models",
+                        type=Path,
+                        default=Path("models"),
+                        help="Folder where to store trained models")
+    parser.add_argument("-R",
+                        "--restart",
+                        action='store_true',
+                        help='Restart training, ignoring previous run')
+
+    parser.add_argument("--seed", type=int, default=42)
+    parser.add_argument("-e", "--epochs", type=int, default=180, help="Number of epochs")
+    parser.add_argument("-r",
+                        "--repeat",
+                        type=int,
+                        default=2,
+                        help="Repeat the train set, longer epochs")
+    parser.add_argument("-b", "--batch_size", type=int, default=64)
+    parser.add_argument("--lr", type=float, default=3e-4)
+    parser.add_argument("--mse", action="store_true", help="Use MSE instead of L1")
+    parser.add_argument("--init", help="Initialize from a pre-trained model.")
+
+    # Augmentation options
+    parser.add_argument("--no_augment",
+                        action="store_false",
+                        dest="augment",
+                        default=True,
+                        help="No basic data augmentation.")
+    parser.add_argument("--repitch", type=float, default=0.2,
+                        help="Probability to do tempo/pitch change")
+    parser.add_argument("--max_tempo", type=float, default=12,
+                        help="Maximum relative tempo change in %% when using repitch.")
+
+    parser.add_argument("--remix_group_size",
+                        type=int,
+                        default=4,
+                        help="Shuffle sources using group of this size. Useful to somewhat "
+                        "replicate multi-gpu training "
+                        "on less GPUs.")
+    parser.add_argument("--shifts",
+                        type=int,
+                        default=10,
+                        help="Number of random shifts used for the shift trick.")
+    parser.add_argument("--overlap",
+                        type=float,
+                        default=0.25,
+                        help="Overlap when --split_valid is passed.")
+
+    # See model.py for doc
+    parser.add_argument("--growth",
+                        type=float,
+                        default=2.,
+                        help="Number of channels between two layers will increase by this factor")
+    parser.add_argument("--depth",
+                        type=int,
+                        default=6,
+                        help="Number of layers for the encoder and decoder")
+    parser.add_argument("--lstm_layers", type=int, default=2, help="Number of layers for the LSTM")
+    parser.add_argument("--channels",
+                        type=int,
+                        default=64,
+                        help="Number of channels for the first encoder layer")
+    parser.add_argument("--kernel_size",
+                        type=int,
+                        default=8,
+                        help="Kernel size for the (transposed) convolutions")
+    parser.add_argument("--conv_stride",
+                        type=int,
+                        default=4,
+                        help="Stride for the (transposed) convolutions")
+    parser.add_argument("--context",
+                        type=int,
+                        default=3,
+                        help="Context size for the decoder convolutions "
+                        "before the transposed convolutions")
+    parser.add_argument("--rescale",
+                        type=float,
+                        default=0.1,
+                        help="Initial weight rescale reference")
+    parser.add_argument("--no_resample", action="store_false",
+                        default=True, dest="resample",
+                        help="No Resampling of the input/output x2")
+    parser.add_argument("--no_glu",
+                        action="store_false",
+                        default=True,
+                        dest="glu",
+                        help="Replace all GLUs by ReLUs")
+    parser.add_argument("--no_rewrite",
+                        action="store_false",
+                        default=True,
+                        dest="rewrite",
+                        help="No 1x1 rewrite convolutions")
+    parser.add_argument("--normalize", action="store_true")
+    parser.add_argument("--no_norm_wav", action="store_false", dest='norm_wav', default=True)
+
+    # Tasnet options
+    parser.add_argument("--tasnet", action="store_true")
+    parser.add_argument("--split_valid",
+                        action="store_true",
+                        help="Predict chunks by chunks for valid and test. Required for tasnet")
+    parser.add_argument("--X", type=int, default=8)
+
+    # Other options
+    parser.add_argument("--show",
+                        action="store_true",
+                        help="Show model architecture, size and exit")
+    parser.add_argument("--save_model", action="store_true",
+                        help="Skip traning, just save final model "
+                             "for the current checkpoint value.")
+    parser.add_argument("--save_state",
+                        help="Skip training, just save state "
+                             "for the current checkpoint value. You should "
+                             "provide a model name as argument.")
+
+    # Quantization options
+    parser.add_argument("--q-min-size", type=float, default=1,
+                        help="Only quantize layers over this size (in MB)")
+    parser.add_argument(
+        "--qat", type=int, help="If provided, use QAT training with that many bits.")
+
+    parser.add_argument("--diffq", type=float, default=0)
+    parser.add_argument(
+        "--ms-target", type=float, default=162,
+        help="Model size target in MB, when using DiffQ. Best model will be kept "
+             "only if it is smaller than this target.")
+
+    return parser
+
+
+def get_name(parser, args):
+    """
+    Return the name of an experiment given the args. Some parameters are ignored,
+    for instance --workers, as they do not impact the final result.
+    """
+    ignore_args = set([
+        "checkpoints",
+        "deterministic",
+        "eval",
+        "evals",
+        "eval_cpu",
+        "eval_workers",
+        "logs",
+        "master",
+        "rank",
+        "restart",
+        "save",
+        "save_model",
+        "save_state",
+        "show",
+        "workers",
+        "world_size",
+    ])
+    parts = []
+    name_args = dict(args.__dict__)
+    for name, value in name_args.items():
+        if name in ignore_args:
+            continue
+        if value != parser.get_default(name):
+            if isinstance(value, Path):
+                parts.append(f"{name}={value.name}")
+            else:
+                parts.append(f"{name}={value}")
+    if parts:
+        name = " ".join(parts)
+    else:
+        name = "default"
+    return name
diff --git a/demucs/pretrained.py b/demucs/pretrained.py
new file mode 100644
index 0000000000000000000000000000000000000000..6aac5db100cc7a9084af96d2cd083f0c8fac473c
--- /dev/null
+++ b/demucs/pretrained.py
@@ -0,0 +1,107 @@
+# Copyright (c) Facebook, Inc. and its affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the license found in the
+# LICENSE file in the root directory of this source tree.
+# author: adefossez
+
+import logging
+
+from diffq import DiffQuantizer
+import torch.hub
+
+from .model import Demucs
+from .tasnet import ConvTasNet
+from .utils import set_state
+
+logger = logging.getLogger(__name__)
+ROOT = "https://dl.fbaipublicfiles.com/demucs/v3.0/"
+
+PRETRAINED_MODELS = {
+    'demucs': 'e07c671f',
+    'demucs48_hq': '28a1282c',
+    'demucs_extra': '3646af93',
+    'demucs_quantized': '07afea75',
+    'tasnet': 'beb46fac',
+    'tasnet_extra': 'df3777b2',
+    'demucs_unittest': '09ebc15f',
+}
+
+SOURCES = ["drums", "bass", "other", "vocals"]
+
+
+def get_url(name):
+    sig = PRETRAINED_MODELS[name]
+    return ROOT + name + "-" + sig[:8] + ".th"
+
+
+def is_pretrained(name):
+    return name in PRETRAINED_MODELS
+
+
+def load_pretrained(name):
+    if name == "demucs":
+        return demucs(pretrained=True)
+    elif name == "demucs48_hq":
+        return demucs(pretrained=True, hq=True, channels=48)
+    elif name == "demucs_extra":
+        return demucs(pretrained=True, extra=True)
+    elif name == "demucs_quantized":
+        return demucs(pretrained=True, quantized=True)
+    elif name == "demucs_unittest":
+        return demucs_unittest(pretrained=True)
+    elif name == "tasnet":
+        return tasnet(pretrained=True)
+    elif name == "tasnet_extra":
+        return tasnet(pretrained=True, extra=True)
+    else:
+        raise ValueError(f"Invalid pretrained name {name}")
+
+
+def _load_state(name, model, quantizer=None):
+    url = get_url(name)
+    state = torch.hub.load_state_dict_from_url(url, map_location='cpu', check_hash=True)
+    set_state(model, quantizer, state)
+    if quantizer:
+        quantizer.detach()
+
+
+def demucs_unittest(pretrained=True):
+    model = Demucs(channels=4, sources=SOURCES)
+    if pretrained:
+        _load_state('demucs_unittest', model)
+    return model
+
+
+def demucs(pretrained=True, extra=False, quantized=False, hq=False, channels=64):
+    if not pretrained and (extra or quantized or hq):
+        raise ValueError("if extra or quantized is True, pretrained must be True.")
+    model = Demucs(sources=SOURCES, channels=channels)
+    if pretrained:
+        name = 'demucs'
+        if channels != 64:
+            name += str(channels)
+        quantizer = None
+        if sum([extra, quantized, hq]) > 1:
+            raise ValueError("Only one of extra, quantized, hq, can be True.")
+        if quantized:
+            quantizer = DiffQuantizer(model, group_size=8, min_size=1)
+            name += '_quantized'
+        if extra:
+            name += '_extra'
+        if hq:
+            name += '_hq'
+        _load_state(name, model, quantizer)
+    return model
+
+
+def tasnet(pretrained=True, extra=False):
+    if not pretrained and extra:
+        raise ValueError("if extra is True, pretrained must be True.")
+    model = ConvTasNet(X=10, sources=SOURCES)
+    if pretrained:
+        name = 'tasnet'
+        if extra:
+            name = 'tasnet_extra'
+        _load_state(name, model)
+    return model
diff --git a/demucs/raw.py b/demucs/raw.py
new file mode 100644
index 0000000000000000000000000000000000000000..d4941ad2d7ed858f490db441f5b46b12bd61ad78
--- /dev/null
+++ b/demucs/raw.py
@@ -0,0 +1,173 @@
+# Copyright (c) Facebook, Inc. and its affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the license found in the
+# LICENSE file in the root directory of this source tree.
+
+import argparse
+import os
+from collections import defaultdict, namedtuple
+from pathlib import Path
+
+import musdb
+import numpy as np
+import torch as th
+import tqdm
+from torch.utils.data import DataLoader
+
+from .audio import AudioFile
+
+ChunkInfo = namedtuple("ChunkInfo", ["file_index", "offset", "local_index"])
+
+
+class Rawset:
+    """
+    Dataset of raw, normalized, float32 audio files
+    """
+    def __init__(self, path, samples=None, stride=None, channels=2, streams=None):
+        self.path = Path(path)
+        self.channels = channels
+        self.samples = samples
+        if stride is None:
+            stride = samples if samples is not None else 0
+        self.stride = stride
+        entries = defaultdict(list)
+        for root, folders, files in os.walk(self.path, followlinks=True):
+            folders.sort()
+            files.sort()
+            for file in files:
+                if file.endswith(".raw"):
+                    path = Path(root) / file
+                    name, stream = path.stem.rsplit('.', 1)
+                    entries[(path.parent.relative_to(self.path), name)].append(int(stream))
+
+        self._entries = list(entries.keys())
+
+        sizes = []
+        self._lengths = []
+        ref_streams = sorted(entries[self._entries[0]])
+        assert ref_streams == list(range(len(ref_streams)))
+        if streams is None:
+            self.streams = ref_streams
+        else:
+            self.streams = streams
+        for entry in sorted(entries.keys()):
+            streams = entries[entry]
+            assert sorted(streams) == ref_streams
+            file = self._path(*entry)
+            length = file.stat().st_size // (4 * channels)
+            if samples is None:
+                sizes.append(1)
+            else:
+                if length < samples:
+                    self._entries.remove(entry)
+                    continue
+                sizes.append((length - samples) // stride + 1)
+            self._lengths.append(length)
+        if not sizes:
+            raise ValueError(f"Empty dataset {self.path}")
+        self._cumulative_sizes = np.cumsum(sizes)
+        self._sizes = sizes
+
+    def __len__(self):
+        return self._cumulative_sizes[-1]
+
+    @property
+    def total_length(self):
+        return sum(self._lengths)
+
+    def chunk_info(self, index):
+        file_index = np.searchsorted(self._cumulative_sizes, index, side='right')
+        if file_index == 0:
+            local_index = index
+        else:
+            local_index = index - self._cumulative_sizes[file_index - 1]
+        return ChunkInfo(offset=local_index * self.stride,
+                         file_index=file_index,
+                         local_index=local_index)
+
+    def _path(self, folder, name, stream=0):
+        return self.path / folder / (name + f'.{stream}.raw')
+
+    def __getitem__(self, index):
+        chunk = self.chunk_info(index)
+        entry = self._entries[chunk.file_index]
+
+        length = self.samples or self._lengths[chunk.file_index]
+        streams = []
+        to_read = length * self.channels * 4
+        for stream_index, stream in enumerate(self.streams):
+            offset = chunk.offset * 4 * self.channels
+            file = open(self._path(*entry, stream=stream), 'rb')
+            file.seek(offset)
+            content = file.read(to_read)
+            assert len(content) == to_read
+            content = np.frombuffer(content, dtype=np.float32)
+            content = content.copy()  # make writable
+            streams.append(th.from_numpy(content).view(length, self.channels).t())
+        return th.stack(streams, dim=0)
+
+    def name(self, index):
+        chunk = self.chunk_info(index)
+        folder, name = self._entries[chunk.file_index]
+        return folder / name
+
+
+class MusDBSet:
+    def __init__(self, mus, streams=slice(None), samplerate=44100, channels=2):
+        self.mus = mus
+        self.streams = streams
+        self.samplerate = samplerate
+        self.channels = channels
+
+    def __len__(self):
+        return len(self.mus.tracks)
+
+    def __getitem__(self, index):
+        track = self.mus.tracks[index]
+        return (track.name, AudioFile(track.path).read(channels=self.channels,
+                                                       seek_time=0,
+                                                       streams=self.streams,
+                                                       samplerate=self.samplerate))
+
+
+def build_raw(mus, destination, normalize, workers, samplerate, channels):
+    destination.mkdir(parents=True, exist_ok=True)
+    loader = DataLoader(MusDBSet(mus, channels=channels, samplerate=samplerate),
+                        batch_size=1,
+                        num_workers=workers,
+                        collate_fn=lambda x: x[0])
+    for name, streams in tqdm.tqdm(loader):
+        if normalize:
+            ref = streams[0].mean(dim=0)  # use mono mixture as reference
+            streams = (streams - ref.mean()) / ref.std()
+        for index, stream in enumerate(streams):
+            open(destination / (name + f'.{index}.raw'), "wb").write(stream.t().numpy().tobytes())
+
+
+def main():
+    parser = argparse.ArgumentParser('rawset')
+    parser.add_argument('--workers', type=int, default=10)
+    parser.add_argument('--samplerate', type=int, default=44100)
+    parser.add_argument('--channels', type=int, default=2)
+    parser.add_argument('musdb', type=Path)
+    parser.add_argument('destination', type=Path)
+
+    args = parser.parse_args()
+
+    build_raw(musdb.DB(root=args.musdb, subsets=["train"], split="train"),
+              args.destination / "train",
+              normalize=True,
+              channels=args.channels,
+              samplerate=args.samplerate,
+              workers=args.workers)
+    build_raw(musdb.DB(root=args.musdb, subsets=["train"], split="valid"),
+              args.destination / "valid",
+              normalize=True,
+              samplerate=args.samplerate,
+              channels=args.channels,
+              workers=args.workers)
+
+
+if __name__ == "__main__":
+    main()
diff --git a/demucs/repitch.py b/demucs/repitch.py
new file mode 100644
index 0000000000000000000000000000000000000000..8846ab2d951a024c95067f66a113968500442828
--- /dev/null
+++ b/demucs/repitch.py
@@ -0,0 +1,96 @@
+# Copyright (c) Facebook, Inc. and its affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the license found in the
+# LICENSE file in the root directory of this source tree.
+
+import io
+import random
+import subprocess as sp
+import tempfile
+
+import numpy as np
+import torch
+from scipy.io import wavfile
+
+
+def i16_pcm(wav):
+    if wav.dtype == np.int16:
+        return wav
+    return (wav * 2**15).clamp_(-2**15, 2**15 - 1).short()
+
+
+def f32_pcm(wav):
+    if wav.dtype == np.float:
+        return wav
+    return wav.float() / 2**15
+
+
+class RepitchedWrapper:
+    """
+    Wrap a dataset to apply online change of pitch / tempo.
+    """
+    def __init__(self, dataset, proba=0.2, max_pitch=2, max_tempo=12, tempo_std=5, vocals=[3]):
+        self.dataset = dataset
+        self.proba = proba
+        self.max_pitch = max_pitch
+        self.max_tempo = max_tempo
+        self.tempo_std = tempo_std
+        self.vocals = vocals
+
+    def __len__(self):
+        return len(self.dataset)
+
+    def __getitem__(self, index):
+        streams = self.dataset[index]
+        in_length = streams.shape[-1]
+        out_length = int((1 - 0.01 * self.max_tempo) * in_length)
+
+        if random.random() < self.proba:
+            delta_pitch = random.randint(-self.max_pitch, self.max_pitch)
+            delta_tempo = random.gauss(0, self.tempo_std)
+            delta_tempo = min(max(-self.max_tempo, delta_tempo), self.max_tempo)
+            outs = []
+            for idx, stream in enumerate(streams):
+                stream = repitch(
+                    stream,
+                    delta_pitch,
+                    delta_tempo,
+                    voice=idx in self.vocals)
+                outs.append(stream[:, :out_length])
+            streams = torch.stack(outs)
+        else:
+            streams = streams[..., :out_length]
+        return streams
+
+
+def repitch(wav, pitch, tempo, voice=False, quick=False, samplerate=44100):
+    """
+    tempo is a relative delta in percentage, so tempo=10 means tempo at 110%!
+    pitch is in semi tones.
+    Requires `soundstretch` to be installed, see
+    https://www.surina.net/soundtouch/soundstretch.html
+    """
+    outfile = tempfile.NamedTemporaryFile(suffix=".wav")
+    in_ = io.BytesIO()
+    wavfile.write(in_, samplerate, i16_pcm(wav).t().numpy())
+    command = [
+        "soundstretch",
+        "stdin",
+        outfile.name,
+        f"-pitch={pitch}",
+        f"-tempo={tempo:.6f}",
+    ]
+    if quick:
+        command += ["-quick"]
+    if voice:
+        command += ["-speech"]
+    try:
+        sp.run(command, capture_output=True, input=in_.getvalue(), check=True)
+    except sp.CalledProcessError as error:
+        raise RuntimeError(f"Could not change bpm because {error.stderr.decode('utf-8')}")
+    sr, wav = wavfile.read(outfile.name)
+    wav = wav.copy()
+    wav = f32_pcm(torch.from_numpy(wav).t())
+    assert sr == samplerate
+    return wav
diff --git a/demucs/separate.py b/demucs/separate.py
new file mode 100644
index 0000000000000000000000000000000000000000..3fc7af9e711978b3e21398aa6f1deb9ae87dd370
--- /dev/null
+++ b/demucs/separate.py
@@ -0,0 +1,185 @@
+# Copyright (c) Facebook, Inc. and its affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the license found in the
+# LICENSE file in the root directory of this source tree.
+
+import argparse
+import sys
+from pathlib import Path
+import subprocess
+
+import julius
+import torch as th
+import torchaudio as ta
+
+from .audio import AudioFile, convert_audio_channels
+from .pretrained import is_pretrained, load_pretrained
+from .utils import apply_model, load_model
+
+
+def load_track(track, device, audio_channels, samplerate):
+    errors = {}
+    wav = None
+
+    try:
+        wav = AudioFile(track).read(
+            streams=0,
+            samplerate=samplerate,
+            channels=audio_channels).to(device)
+    except FileNotFoundError:
+        errors['ffmpeg'] = 'Ffmpeg is not installed.'
+    except subprocess.CalledProcessError:
+        errors['ffmpeg'] = 'FFmpeg could not read the file.'
+
+    if wav is None:
+        try:
+            wav, sr = ta.load(str(track))
+        except RuntimeError as err:
+            errors['torchaudio'] = err.args[0]
+        else:
+            wav = convert_audio_channels(wav, audio_channels)
+            wav = wav.to(device)
+            wav = julius.resample_frac(wav, sr, samplerate)
+
+    if wav is None:
+        print(f"Could not load file {track}. "
+              "Maybe it is not a supported file format? ")
+        for backend, error in errors.items():
+            print(f"When trying to load using {backend}, got the following error: {error}")
+        sys.exit(1)
+    return wav
+
+
+def encode_mp3(wav, path, bitrate=320, samplerate=44100, channels=2, verbose=False):
+    try:
+        import lameenc
+    except ImportError:
+        print("Failed to call lame encoder. Maybe it is not installed? "
+              "On windows, run `python.exe -m pip install -U lameenc`, "
+              "on OSX/Linux, run `python3 -m pip install -U lameenc`, "
+              "then try again.", file=sys.stderr)
+        sys.exit(1)
+    encoder = lameenc.Encoder()
+    encoder.set_bit_rate(bitrate)
+    encoder.set_in_sample_rate(samplerate)
+    encoder.set_channels(channels)
+    encoder.set_quality(2)  # 2-highest, 7-fastest
+    if not verbose:
+        encoder.silence()
+    wav = wav.transpose(0, 1).numpy()
+    mp3_data = encoder.encode(wav.tobytes())
+    mp3_data += encoder.flush()
+    with open(path, "wb") as f:
+        f.write(mp3_data)
+
+
+def main():
+    parser = argparse.ArgumentParser("demucs.separate",
+                                     description="Separate the sources for the given tracks")
+    parser.add_argument("tracks", nargs='+', type=Path, default=[], help='Path to tracks')
+    parser.add_argument("-n",
+                        "--name",
+                        default="demucs_quantized",
+                        help="Model name. See README.md for the list of pretrained models. "
+                             "Default is demucs_quantized.")
+    parser.add_argument("-v", "--verbose", action="store_true")
+    parser.add_argument("-o",
+                        "--out",
+                        type=Path,
+                        default=Path("separated"),
+                        help="Folder where to put extracted tracks. A subfolder "
+                        "with the model name will be created.")
+    parser.add_argument("--models",
+                        type=Path,
+                        default=Path("models"),
+                        help="Path to trained models. "
+                        "Also used to store downloaded pretrained models")
+    parser.add_argument("-d",
+                        "--device",
+                        default="cuda" if th.cuda.is_available() else "cpu",
+                        help="Device to use, default is cuda if available else cpu")
+    parser.add_argument("--shifts",
+                        default=0,
+                        type=int,
+                        help="Number of random shifts for equivariant stabilization."
+                        "Increase separation time but improves quality for Demucs. 10 was used "
+                        "in the original paper.")
+    parser.add_argument("--overlap",
+                        default=0.25,
+                        type=float,
+                        help="Overlap between the splits.")
+    parser.add_argument("--no-split",
+                        action="store_false",
+                        dest="split",
+                        default=True,
+                        help="Doesn't split audio in chunks. This can use large amounts of memory.")
+    parser.add_argument("--float32",
+                        action="store_true",
+                        help="Convert the output wavefile to use pcm f32 format instead of s16. "
+                        "This should not make a difference if you just plan on listening to the "
+                        "audio but might be needed to compute exactly metrics like SDR etc.")
+    parser.add_argument("--int16",
+                        action="store_false",
+                        dest="float32",
+                        help="Opposite of --float32, here for compatibility.")
+    parser.add_argument("--mp3", action="store_true",
+                        help="Convert the output wavs to mp3.")
+    parser.add_argument("--mp3-bitrate",
+                        default=320,
+                        type=int,
+                        help="Bitrate of converted mp3.")
+
+    args = parser.parse_args()
+    name = args.name + ".th"
+    model_path = args.models / name
+    if model_path.is_file():
+        model = load_model(model_path)
+    else:
+        if is_pretrained(args.name):
+            model = load_pretrained(args.name)
+        else:
+            print(f"No pre-trained model {args.name}", file=sys.stderr)
+            sys.exit(1)
+    model.to(args.device)
+
+    out = args.out / args.name
+    out.mkdir(parents=True, exist_ok=True)
+    print(f"Separated tracks will be stored in {out.resolve()}")
+    for track in args.tracks:
+        if not track.exists():
+            print(
+                f"File {track} does not exist. If the path contains spaces, "
+                "please try again after surrounding the entire path with quotes \"\".",
+                file=sys.stderr)
+            continue
+        print(f"Separating track {track}")
+        wav = load_track(track, args.device, model.audio_channels, model.samplerate)
+
+        ref = wav.mean(0)
+        wav = (wav - ref.mean()) / ref.std()
+        sources = apply_model(model, wav, shifts=args.shifts, split=args.split,
+                              overlap=args.overlap, progress=True)
+        sources = sources * ref.std() + ref.mean()
+
+        track_folder = out / track.name.rsplit(".", 1)[0]
+        track_folder.mkdir(exist_ok=True)
+        for source, name in zip(sources, model.sources):
+            source = source / max(1.01 * source.abs().max(), 1)
+            if args.mp3 or not args.float32:
+                source = (source * 2**15).clamp_(-2**15, 2**15 - 1).short()
+            source = source.cpu()
+            stem = str(track_folder / name)
+            if args.mp3:
+                encode_mp3(source, stem + ".mp3",
+                           bitrate=args.mp3_bitrate,
+                           samplerate=model.samplerate,
+                           channels=model.audio_channels,
+                           verbose=args.verbose)
+            else:
+                wavname = str(track_folder / f"{name}.wav")
+                ta.save(wavname, source, sample_rate=model.samplerate)
+
+
+if __name__ == "__main__":
+    main()
diff --git a/demucs/tasnet.py b/demucs/tasnet.py
new file mode 100644
index 0000000000000000000000000000000000000000..ecc1257925ea8f4fbe389ddd6d73ce9fdf45f6d4
--- /dev/null
+++ b/demucs/tasnet.py
@@ -0,0 +1,452 @@
+# Copyright (c) Facebook, Inc. and its affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the license found in the
+# LICENSE file in the root directory of this source tree.
+#
+# Created on 2018/12
+# Author: Kaituo XU
+# Modified on 2019/11 by Alexandre Defossez, added support for multiple output channels
+# Here is the original license:
+# The MIT License (MIT)
+#
+# Copyright (c) 2018 Kaituo XU
+#
+# Permission is hereby granted, free of charge, to any person obtaining a copy
+# of this software and associated documentation files (the "Software"), to deal
+# in the Software without restriction, including without limitation the rights
+# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+# copies of the Software, and to permit persons to whom the Software is
+# furnished to do so, subject to the following conditions:
+#
+# The above copyright notice and this permission notice shall be included in all
+# copies or substantial portions of the Software.
+#
+# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+# SOFTWARE.
+
+import math
+
+import torch
+import torch.nn as nn
+import torch.nn.functional as F
+
+from .utils import capture_init
+
+EPS = 1e-8
+
+
+def overlap_and_add(signal, frame_step):
+    outer_dimensions = signal.size()[:-2]
+    frames, frame_length = signal.size()[-2:]
+
+    subframe_length = math.gcd(frame_length, frame_step)  # gcd=Greatest Common Divisor
+    subframe_step = frame_step // subframe_length
+    subframes_per_frame = frame_length // subframe_length
+    output_size = frame_step * (frames - 1) + frame_length
+    output_subframes = output_size // subframe_length
+
+    subframe_signal = signal.view(*outer_dimensions, -1, subframe_length)
+
+    frame = torch.arange(0, output_subframes,
+                         device=signal.device).unfold(0, subframes_per_frame, subframe_step)
+    frame = frame.long()  # signal may in GPU or CPU
+    frame = frame.contiguous().view(-1)
+
+    result = signal.new_zeros(*outer_dimensions, output_subframes, subframe_length)
+    result.index_add_(-2, frame, subframe_signal)
+    result = result.view(*outer_dimensions, -1)
+    return result
+
+
+class ConvTasNet(nn.Module):
+    @capture_init
+    def __init__(self,
+                 sources,
+                 N=256,
+                 L=20,
+                 B=256,
+                 H=512,
+                 P=3,
+                 X=8,
+                 R=4,
+                 audio_channels=2,
+                 norm_type="gLN",
+                 causal=False,
+                 mask_nonlinear='relu',
+                 samplerate=44100,
+                 segment_length=44100 * 2 * 4):
+        """
+        Args:
+            sources: list of sources
+            N: Number of filters in autoencoder
+            L: Length of the filters (in samples)
+            B: Number of channels in bottleneck 1 × 1-conv block
+            H: Number of channels in convolutional blocks
+            P: Kernel size in convolutional blocks
+            X: Number of convolutional blocks in each repeat
+            R: Number of repeats
+            norm_type: BN, gLN, cLN
+            causal: causal or non-causal
+            mask_nonlinear: use which non-linear function to generate mask
+        """
+        super(ConvTasNet, self).__init__()
+        # Hyper-parameter
+        self.sources = sources
+        self.C = len(sources)
+        self.N, self.L, self.B, self.H, self.P, self.X, self.R = N, L, B, H, P, X, R
+        self.norm_type = norm_type
+        self.causal = causal
+        self.mask_nonlinear = mask_nonlinear
+        self.audio_channels = audio_channels
+        self.samplerate = samplerate
+        self.segment_length = segment_length
+        # Components
+        self.encoder = Encoder(L, N, audio_channels)
+        self.separator = TemporalConvNet(
+            N, B, H, P, X, R, self.C, norm_type, causal, mask_nonlinear)
+        self.decoder = Decoder(N, L, audio_channels)
+        # init
+        for p in self.parameters():
+            if p.dim() > 1:
+                nn.init.xavier_normal_(p)
+
+    def valid_length(self, length):
+        return length
+
+    def forward(self, mixture):
+        """
+        Args:
+            mixture: [M, T], M is batch size, T is #samples
+        Returns:
+            est_source: [M, C, T]
+        """
+        mixture_w = self.encoder(mixture)
+        est_mask = self.separator(mixture_w)
+        est_source = self.decoder(mixture_w, est_mask)
+
+        # T changed after conv1d in encoder, fix it here
+        T_origin = mixture.size(-1)
+        T_conv = est_source.size(-1)
+        est_source = F.pad(est_source, (0, T_origin - T_conv))
+        return est_source
+
+
+class Encoder(nn.Module):
+    """Estimation of the nonnegative mixture weight by a 1-D conv layer.
+    """
+    def __init__(self, L, N, audio_channels):
+        super(Encoder, self).__init__()
+        # Hyper-parameter
+        self.L, self.N = L, N
+        # Components
+        # 50% overlap
+        self.conv1d_U = nn.Conv1d(audio_channels, N, kernel_size=L, stride=L // 2, bias=False)
+
+    def forward(self, mixture):
+        """
+        Args:
+            mixture: [M, T], M is batch size, T is #samples
+        Returns:
+            mixture_w: [M, N, K], where K = (T-L)/(L/2)+1 = 2T/L-1
+        """
+        mixture_w = F.relu(self.conv1d_U(mixture))  # [M, N, K]
+        return mixture_w
+
+
+class Decoder(nn.Module):
+    def __init__(self, N, L, audio_channels):
+        super(Decoder, self).__init__()
+        # Hyper-parameter
+        self.N, self.L = N, L
+        self.audio_channels = audio_channels
+        # Components
+        self.basis_signals = nn.Linear(N, audio_channels * L, bias=False)
+
+    def forward(self, mixture_w, est_mask):
+        """
+        Args:
+            mixture_w: [M, N, K]
+            est_mask: [M, C, N, K]
+        Returns:
+            est_source: [M, C, T]
+        """
+        # D = W * M
+        source_w = torch.unsqueeze(mixture_w, 1) * est_mask  # [M, C, N, K]
+        source_w = torch.transpose(source_w, 2, 3)  # [M, C, K, N]
+        # S = DV
+        est_source = self.basis_signals(source_w)  # [M, C, K, ac * L]
+        m, c, k, _ = est_source.size()
+        est_source = est_source.view(m, c, k, self.audio_channels, -1).transpose(2, 3).contiguous()
+        est_source = overlap_and_add(est_source, self.L // 2)  # M x C x ac x T
+        return est_source
+
+
+class TemporalConvNet(nn.Module):
+    def __init__(self, N, B, H, P, X, R, C, norm_type="gLN", causal=False, mask_nonlinear='relu'):
+        """
+        Args:
+            N: Number of filters in autoencoder
+            B: Number of channels in bottleneck 1 × 1-conv block
+            H: Number of channels in convolutional blocks
+            P: Kernel size in convolutional blocks
+            X: Number of convolutional blocks in each repeat
+            R: Number of repeats
+            C: Number of speakers
+            norm_type: BN, gLN, cLN
+            causal: causal or non-causal
+            mask_nonlinear: use which non-linear function to generate mask
+        """
+        super(TemporalConvNet, self).__init__()
+        # Hyper-parameter
+        self.C = C
+        self.mask_nonlinear = mask_nonlinear
+        # Components
+        # [M, N, K] -> [M, N, K]
+        layer_norm = ChannelwiseLayerNorm(N)
+        # [M, N, K] -> [M, B, K]
+        bottleneck_conv1x1 = nn.Conv1d(N, B, 1, bias=False)
+        # [M, B, K] -> [M, B, K]
+        repeats = []
+        for r in range(R):
+            blocks = []
+            for x in range(X):
+                dilation = 2**x
+                padding = (P - 1) * dilation if causal else (P - 1) * dilation // 2
+                blocks += [
+                    TemporalBlock(B,
+                                  H,
+                                  P,
+                                  stride=1,
+                                  padding=padding,
+                                  dilation=dilation,
+                                  norm_type=norm_type,
+                                  causal=causal)
+                ]
+            repeats += [nn.Sequential(*blocks)]
+        temporal_conv_net = nn.Sequential(*repeats)
+        # [M, B, K] -> [M, C*N, K]
+        mask_conv1x1 = nn.Conv1d(B, C * N, 1, bias=False)
+        # Put together
+        self.network = nn.Sequential(layer_norm, bottleneck_conv1x1, temporal_conv_net,
+                                     mask_conv1x1)
+
+    def forward(self, mixture_w):
+        """
+        Keep this API same with TasNet
+        Args:
+            mixture_w: [M, N, K], M is batch size
+        returns:
+            est_mask: [M, C, N, K]
+        """
+        M, N, K = mixture_w.size()
+        score = self.network(mixture_w)  # [M, N, K] -> [M, C*N, K]
+        score = score.view(M, self.C, N, K)  # [M, C*N, K] -> [M, C, N, K]
+        if self.mask_nonlinear == 'softmax':
+            est_mask = F.softmax(score, dim=1)
+        elif self.mask_nonlinear == 'relu':
+            est_mask = F.relu(score)
+        else:
+            raise ValueError("Unsupported mask non-linear function")
+        return est_mask
+
+
+class TemporalBlock(nn.Module):
+    def __init__(self,
+                 in_channels,
+                 out_channels,
+                 kernel_size,
+                 stride,
+                 padding,
+                 dilation,
+                 norm_type="gLN",
+                 causal=False):
+        super(TemporalBlock, self).__init__()
+        # [M, B, K] -> [M, H, K]
+        conv1x1 = nn.Conv1d(in_channels, out_channels, 1, bias=False)
+        prelu = nn.PReLU()
+        norm = chose_norm(norm_type, out_channels)
+        # [M, H, K] -> [M, B, K]
+        dsconv = DepthwiseSeparableConv(out_channels, in_channels, kernel_size, stride, padding,
+                                        dilation, norm_type, causal)
+        # Put together
+        self.net = nn.Sequential(conv1x1, prelu, norm, dsconv)
+
+    def forward(self, x):
+        """
+        Args:
+            x: [M, B, K]
+        Returns:
+            [M, B, K]
+        """
+        residual = x
+        out = self.net(x)
+        # TODO: when P = 3 here works fine, but when P = 2 maybe need to pad?
+        return out + residual  # look like w/o F.relu is better than w/ F.relu
+        # return F.relu(out + residual)
+
+
+class DepthwiseSeparableConv(nn.Module):
+    def __init__(self,
+                 in_channels,
+                 out_channels,
+                 kernel_size,
+                 stride,
+                 padding,
+                 dilation,
+                 norm_type="gLN",
+                 causal=False):
+        super(DepthwiseSeparableConv, self).__init__()
+        # Use `groups` option to implement depthwise convolution
+        # [M, H, K] -> [M, H, K]
+        depthwise_conv = nn.Conv1d(in_channels,
+                                   in_channels,
+                                   kernel_size,
+                                   stride=stride,
+                                   padding=padding,
+                                   dilation=dilation,
+                                   groups=in_channels,
+                                   bias=False)
+        if causal:
+            chomp = Chomp1d(padding)
+        prelu = nn.PReLU()
+        norm = chose_norm(norm_type, in_channels)
+        # [M, H, K] -> [M, B, K]
+        pointwise_conv = nn.Conv1d(in_channels, out_channels, 1, bias=False)
+        # Put together
+        if causal:
+            self.net = nn.Sequential(depthwise_conv, chomp, prelu, norm, pointwise_conv)
+        else:
+            self.net = nn.Sequential(depthwise_conv, prelu, norm, pointwise_conv)
+
+    def forward(self, x):
+        """
+        Args:
+            x: [M, H, K]
+        Returns:
+            result: [M, B, K]
+        """
+        return self.net(x)
+
+
+class Chomp1d(nn.Module):
+    """To ensure the output length is the same as the input.
+    """
+    def __init__(self, chomp_size):
+        super(Chomp1d, self).__init__()
+        self.chomp_size = chomp_size
+
+    def forward(self, x):
+        """
+        Args:
+            x: [M, H, Kpad]
+        Returns:
+            [M, H, K]
+        """
+        return x[:, :, :-self.chomp_size].contiguous()
+
+
+def chose_norm(norm_type, channel_size):
+    """The input of normlization will be (M, C, K), where M is batch size,
+       C is channel size and K is sequence length.
+    """
+    if norm_type == "gLN":
+        return GlobalLayerNorm(channel_size)
+    elif norm_type == "cLN":
+        return ChannelwiseLayerNorm(channel_size)
+    elif norm_type == "id":
+        return nn.Identity()
+    else:  # norm_type == "BN":
+        # Given input (M, C, K), nn.BatchNorm1d(C) will accumulate statics
+        # along M and K, so this BN usage is right.
+        return nn.BatchNorm1d(channel_size)
+
+
+# TODO: Use nn.LayerNorm to impl cLN to speed up
+class ChannelwiseLayerNorm(nn.Module):
+    """Channel-wise Layer Normalization (cLN)"""
+    def __init__(self, channel_size):
+        super(ChannelwiseLayerNorm, self).__init__()
+        self.gamma = nn.Parameter(torch.Tensor(1, channel_size, 1))  # [1, N, 1]
+        self.beta = nn.Parameter(torch.Tensor(1, channel_size, 1))  # [1, N, 1]
+        self.reset_parameters()
+
+    def reset_parameters(self):
+        self.gamma.data.fill_(1)
+        self.beta.data.zero_()
+
+    def forward(self, y):
+        """
+        Args:
+            y: [M, N, K], M is batch size, N is channel size, K is length
+        Returns:
+            cLN_y: [M, N, K]
+        """
+        mean = torch.mean(y, dim=1, keepdim=True)  # [M, 1, K]
+        var = torch.var(y, dim=1, keepdim=True, unbiased=False)  # [M, 1, K]
+        cLN_y = self.gamma * (y - mean) / torch.pow(var + EPS, 0.5) + self.beta
+        return cLN_y
+
+
+class GlobalLayerNorm(nn.Module):
+    """Global Layer Normalization (gLN)"""
+    def __init__(self, channel_size):
+        super(GlobalLayerNorm, self).__init__()
+        self.gamma = nn.Parameter(torch.Tensor(1, channel_size, 1))  # [1, N, 1]
+        self.beta = nn.Parameter(torch.Tensor(1, channel_size, 1))  # [1, N, 1]
+        self.reset_parameters()
+
+    def reset_parameters(self):
+        self.gamma.data.fill_(1)
+        self.beta.data.zero_()
+
+    def forward(self, y):
+        """
+        Args:
+            y: [M, N, K], M is batch size, N is channel size, K is length
+        Returns:
+            gLN_y: [M, N, K]
+        """
+        # TODO: in torch 1.0, torch.mean() support dim list
+        mean = y.mean(dim=1, keepdim=True).mean(dim=2, keepdim=True)  # [M, 1, 1]
+        var = (torch.pow(y - mean, 2)).mean(dim=1, keepdim=True).mean(dim=2, keepdim=True)
+        gLN_y = self.gamma * (y - mean) / torch.pow(var + EPS, 0.5) + self.beta
+        return gLN_y
+
+
+if __name__ == "__main__":
+    torch.manual_seed(123)
+    M, N, L, T = 2, 3, 4, 12
+    K = 2 * T // L - 1
+    B, H, P, X, R, C, norm_type, causal = 2, 3, 3, 3, 2, 2, "gLN", False
+    mixture = torch.randint(3, (M, T))
+    # test Encoder
+    encoder = Encoder(L, N)
+    encoder.conv1d_U.weight.data = torch.randint(2, encoder.conv1d_U.weight.size())
+    mixture_w = encoder(mixture)
+    print('mixture', mixture)
+    print('U', encoder.conv1d_U.weight)
+    print('mixture_w', mixture_w)
+    print('mixture_w size', mixture_w.size())
+
+    # test TemporalConvNet
+    separator = TemporalConvNet(N, B, H, P, X, R, C, norm_type=norm_type, causal=causal)
+    est_mask = separator(mixture_w)
+    print('est_mask', est_mask)
+
+    # test Decoder
+    decoder = Decoder(N, L)
+    est_mask = torch.randint(2, (B, K, C, N))
+    est_source = decoder(mixture_w, est_mask)
+    print('est_source', est_source)
+
+    # test Conv-TasNet
+    conv_tasnet = ConvTasNet(N, L, B, H, P, X, R, C, norm_type=norm_type)
+    est_source = conv_tasnet(mixture)
+    print('est_source', est_source)
+    print('est_source size', est_source.size())
diff --git a/demucs/test.py b/demucs/test.py
new file mode 100644
index 0000000000000000000000000000000000000000..4140914ddbff3543b4056ca0cb1b5e887434a40a
--- /dev/null
+++ b/demucs/test.py
@@ -0,0 +1,109 @@
+# Copyright (c) Facebook, Inc. and its affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the license found in the
+# LICENSE file in the root directory of this source tree.
+
+import gzip
+import sys
+from concurrent import futures
+
+import musdb
+import museval
+import torch as th
+import tqdm
+from scipy.io import wavfile
+from torch import distributed
+
+from .audio import convert_audio
+from .utils import apply_model
+
+
+def evaluate(model,
+             musdb_path,
+             eval_folder,
+             workers=2,
+             device="cpu",
+             rank=0,
+             save=False,
+             shifts=0,
+             split=False,
+             overlap=0.25,
+             is_wav=False,
+             world_size=1):
+    """
+    Evaluate model using museval. Run the model
+    on a single GPU, the bottleneck being the call to museval.
+    """
+
+    output_dir = eval_folder / "results"
+    output_dir.mkdir(exist_ok=True, parents=True)
+    json_folder = eval_folder / "results/test"
+    json_folder.mkdir(exist_ok=True, parents=True)
+
+    # we load tracks from the original musdb set
+    test_set = musdb.DB(musdb_path, subsets=["test"], is_wav=is_wav)
+    src_rate = 44100  # hardcoded for now...
+
+    for p in model.parameters():
+        p.requires_grad = False
+        p.grad = None
+
+    pendings = []
+    with futures.ProcessPoolExecutor(workers or 1) as pool:
+        for index in tqdm.tqdm(range(rank, len(test_set), world_size), file=sys.stdout):
+            track = test_set.tracks[index]
+
+            out = json_folder / f"{track.name}.json.gz"
+            if out.exists():
+                continue
+
+            mix = th.from_numpy(track.audio).t().float()
+            ref = mix.mean(dim=0)  # mono mixture
+            mix = (mix - ref.mean()) / ref.std()
+            mix = convert_audio(mix, src_rate, model.samplerate, model.audio_channels)
+            estimates = apply_model(model, mix.to(device),
+                                    shifts=shifts, split=split, overlap=overlap)
+            estimates = estimates * ref.std() + ref.mean()
+
+            estimates = estimates.transpose(1, 2)
+            references = th.stack(
+                [th.from_numpy(track.targets[name].audio).t() for name in model.sources])
+            references = convert_audio(references, src_rate,
+                                       model.samplerate, model.audio_channels)
+            references = references.transpose(1, 2).numpy()
+            estimates = estimates.cpu().numpy()
+            win = int(1. * model.samplerate)
+            hop = int(1. * model.samplerate)
+            if save:
+                folder = eval_folder / "wav/test" / track.name
+                folder.mkdir(exist_ok=True, parents=True)
+                for name, estimate in zip(model.sources, estimates):
+                    wavfile.write(str(folder / (name + ".wav")), 44100, estimate)
+
+            if workers:
+                pendings.append((track.name, pool.submit(
+                    museval.evaluate, references, estimates, win=win, hop=hop)))
+            else:
+                pendings.append((track.name, museval.evaluate(
+                    references, estimates, win=win, hop=hop)))
+            del references, mix, estimates, track
+
+        for track_name, pending in tqdm.tqdm(pendings, file=sys.stdout):
+            if workers:
+                pending = pending.result()
+            sdr, isr, sir, sar = pending
+            track_store = museval.TrackStore(win=44100, hop=44100, track_name=track_name)
+            for idx, target in enumerate(model.sources):
+                values = {
+                    "SDR": sdr[idx].tolist(),
+                    "SIR": sir[idx].tolist(),
+                    "ISR": isr[idx].tolist(),
+                    "SAR": sar[idx].tolist()
+                }
+
+                track_store.add_target(target_name=target, values=values)
+                json_path = json_folder / f"{track_name}.json.gz"
+                gzip.open(json_path, "w").write(track_store.json.encode('utf-8'))
+    if world_size > 1:
+        distributed.barrier()
diff --git a/demucs/train.py b/demucs/train.py
new file mode 100644
index 0000000000000000000000000000000000000000..6bd221279dc986a6df1a8d7b4d4444bb822a1cb3
--- /dev/null
+++ b/demucs/train.py
@@ -0,0 +1,127 @@
+# Copyright (c) Facebook, Inc. and its affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the license found in the
+# LICENSE file in the root directory of this source tree.
+
+import sys
+
+import tqdm
+from torch.utils.data import DataLoader
+from torch.utils.data.distributed import DistributedSampler
+
+from .utils import apply_model, average_metric, center_trim
+
+
+def train_model(epoch,
+                dataset,
+                model,
+                criterion,
+                optimizer,
+                augment,
+                quantizer=None,
+                diffq=0,
+                repeat=1,
+                device="cpu",
+                seed=None,
+                workers=4,
+                world_size=1,
+                batch_size=16):
+
+    if world_size > 1:
+        sampler = DistributedSampler(dataset)
+        sampler_epoch = epoch * repeat
+        if seed is not None:
+            sampler_epoch += seed * 1000
+        sampler.set_epoch(sampler_epoch)
+        batch_size //= world_size
+        loader = DataLoader(dataset, batch_size=batch_size, sampler=sampler, num_workers=workers)
+    else:
+        loader = DataLoader(dataset, batch_size=batch_size, num_workers=workers, shuffle=True)
+    current_loss = 0
+    model_size = 0
+    for repetition in range(repeat):
+        tq = tqdm.tqdm(loader,
+                       ncols=120,
+                       desc=f"[{epoch:03d}] train ({repetition + 1}/{repeat})",
+                       leave=False,
+                       file=sys.stdout,
+                       unit=" batch")
+        total_loss = 0
+        for idx, sources in enumerate(tq):
+            if len(sources) < batch_size:
+                # skip uncomplete batch for augment.Remix to work properly
+                continue
+            sources = sources.to(device)
+            sources = augment(sources)
+            mix = sources.sum(dim=1)
+
+            estimates = model(mix)
+            sources = center_trim(sources, estimates)
+            loss = criterion(estimates, sources)
+            model_size = 0
+            if quantizer is not None:
+                model_size = quantizer.model_size()
+
+            train_loss = loss + diffq * model_size
+            train_loss.backward()
+            grad_norm = 0
+            for p in model.parameters():
+                if p.grad is not None:
+                    grad_norm += p.grad.data.norm()**2
+            grad_norm = grad_norm**0.5
+            optimizer.step()
+            optimizer.zero_grad()
+
+            if quantizer is not None:
+                model_size = model_size.item()
+
+            total_loss += loss.item()
+            current_loss = total_loss / (1 + idx)
+            tq.set_postfix(loss=f"{current_loss:.4f}", ms=f"{model_size:.2f}",
+                           grad=f"{grad_norm:.5f}")
+
+            # free some space before next round
+            del sources, mix, estimates, loss, train_loss
+
+        if world_size > 1:
+            sampler.epoch += 1
+
+    if world_size > 1:
+        current_loss = average_metric(current_loss)
+    return current_loss, model_size
+
+
+def validate_model(epoch,
+                   dataset,
+                   model,
+                   criterion,
+                   device="cpu",
+                   rank=0,
+                   world_size=1,
+                   shifts=0,
+                   overlap=0.25,
+                   split=False):
+    indexes = range(rank, len(dataset), world_size)
+    tq = tqdm.tqdm(indexes,
+                   ncols=120,
+                   desc=f"[{epoch:03d}] valid",
+                   leave=False,
+                   file=sys.stdout,
+                   unit=" track")
+    current_loss = 0
+    for index in tq:
+        streams = dataset[index]
+        # first five minutes to avoid OOM on --upsample models
+        streams = streams[..., :15_000_000]
+        streams = streams.to(device)
+        sources = streams[1:]
+        mix = streams[0]
+        estimates = apply_model(model, mix, shifts=shifts, split=split, overlap=overlap)
+        loss = criterion(estimates, sources)
+        current_loss += loss.item() / len(indexes)
+        del estimates, streams, sources
+
+    if world_size > 1:
+        current_loss = average_metric(current_loss, len(indexes))
+    return current_loss
diff --git a/demucs/utils.py b/demucs/utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..4364184059b1afe3c8379c77793a8e76dccf9699
--- /dev/null
+++ b/demucs/utils.py
@@ -0,0 +1,323 @@
+# Copyright (c) Facebook, Inc. and its affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the license found in the
+# LICENSE file in the root directory of this source tree.
+
+import errno
+import functools
+import hashlib
+import inspect
+import io
+import os
+import random
+import socket
+import tempfile
+import warnings
+import zlib
+from contextlib import contextmanager
+
+from diffq import UniformQuantizer, DiffQuantizer
+import torch as th
+import tqdm
+from torch import distributed
+from torch.nn import functional as F
+
+
+def center_trim(tensor, reference):
+    """
+    Center trim `tensor` with respect to `reference`, along the last dimension.
+    `reference` can also be a number, representing the length to trim to.
+    If the size difference != 0 mod 2, the extra sample is removed on the right side.
+    """
+    if hasattr(reference, "size"):
+        reference = reference.size(-1)
+    delta = tensor.size(-1) - reference
+    if delta < 0:
+        raise ValueError("tensor must be larger than reference. " f"Delta is {delta}.")
+    if delta:
+        tensor = tensor[..., delta // 2:-(delta - delta // 2)]
+    return tensor
+
+
+def average_metric(metric, count=1.):
+    """
+    Average `metric` which should be a float across all hosts. `count` should be
+    the weight for this particular host (i.e. number of examples).
+    """
+    metric = th.tensor([count, count * metric], dtype=th.float32, device='cuda')
+    distributed.all_reduce(metric, op=distributed.ReduceOp.SUM)
+    return metric[1].item() / metric[0].item()
+
+
+def free_port(host='', low=20000, high=40000):
+    """
+    Return a port number that is most likely free.
+    This could suffer from a race condition although
+    it should be quite rare.
+    """
+    sock = socket.socket()
+    while True:
+        port = random.randint(low, high)
+        try:
+            sock.bind((host, port))
+        except OSError as error:
+            if error.errno == errno.EADDRINUSE:
+                continue
+            raise
+        return port
+
+
+def sizeof_fmt(num, suffix='B'):
+    """
+    Given `num` bytes, return human readable size.
+    Taken from https://stackoverflow.com/a/1094933
+    """
+    for unit in ['', 'Ki', 'Mi', 'Gi', 'Ti', 'Pi', 'Ei', 'Zi']:
+        if abs(num) < 1024.0:
+            return "%3.1f%s%s" % (num, unit, suffix)
+        num /= 1024.0
+    return "%.1f%s%s" % (num, 'Yi', suffix)
+
+
+def human_seconds(seconds, display='.2f'):
+    """
+    Given `seconds` seconds, return human readable duration.
+    """
+    value = seconds * 1e6
+    ratios = [1e3, 1e3, 60, 60, 24]
+    names = ['us', 'ms', 's', 'min', 'hrs', 'days']
+    last = names.pop(0)
+    for name, ratio in zip(names, ratios):
+        if value / ratio < 0.3:
+            break
+        value /= ratio
+        last = name
+    return f"{format(value, display)} {last}"
+
+
+class TensorChunk:
+    def __init__(self, tensor, offset=0, length=None):
+        total_length = tensor.shape[-1]
+        assert offset >= 0
+        assert offset < total_length
+
+        if length is None:
+            length = total_length - offset
+        else:
+            length = min(total_length - offset, length)
+
+        self.tensor = tensor
+        self.offset = offset
+        self.length = length
+        self.device = tensor.device
+
+    @property
+    def shape(self):
+        shape = list(self.tensor.shape)
+        shape[-1] = self.length
+        return shape
+
+    def padded(self, target_length):
+        delta = target_length - self.length
+        total_length = self.tensor.shape[-1]
+        assert delta >= 0
+
+        start = self.offset - delta // 2
+        end = start + target_length
+
+        correct_start = max(0, start)
+        correct_end = min(total_length, end)
+
+        pad_left = correct_start - start
+        pad_right = end - correct_end
+
+        out = F.pad(self.tensor[..., correct_start:correct_end], (pad_left, pad_right))
+        assert out.shape[-1] == target_length
+        return out
+
+
+def tensor_chunk(tensor_or_chunk):
+    if isinstance(tensor_or_chunk, TensorChunk):
+        return tensor_or_chunk
+    else:
+        assert isinstance(tensor_or_chunk, th.Tensor)
+        return TensorChunk(tensor_or_chunk)
+
+
+def apply_model(model, mix, shifts=None, split=False,
+                overlap=0.25, transition_power=1., progress=False):
+    """
+    Apply model to a given mixture.
+
+    Args:
+        shifts (int): if > 0, will shift in time `mix` by a random amount between 0 and 0.5 sec
+            and apply the oppositve shift to the output. This is repeated `shifts` time and
+            all predictions are averaged. This effectively makes the model time equivariant
+            and improves SDR by up to 0.2 points.
+        split (bool): if True, the input will be broken down in 8 seconds extracts
+            and predictions will be performed individually on each and concatenated.
+            Useful for model with large memory footprint like Tasnet.
+        progress (bool): if True, show a progress bar (requires split=True)
+    """
+    assert transition_power >= 1, "transition_power < 1 leads to weird behavior."
+    device = mix.device
+    channels, length = mix.shape
+    if split:
+        out = th.zeros(len(model.sources), channels, length, device=device)
+        sum_weight = th.zeros(length, device=device)
+        segment = model.segment_length
+        stride = int((1 - overlap) * segment)
+        offsets = range(0, length, stride)
+        scale = stride / model.samplerate
+        if progress:
+            offsets = tqdm.tqdm(offsets, unit_scale=scale, ncols=120, unit='seconds')
+        # We start from a triangle shaped weight, with maximal weight in the middle
+        # of the segment. Then we normalize and take to the power `transition_power`.
+        # Large values of transition power will lead to sharper transitions.
+        weight = th.cat([th.arange(1, segment // 2 + 1),
+                         th.arange(segment - segment // 2, 0, -1)]).to(device)
+        assert len(weight) == segment
+        # If the overlap < 50%, this will translate to linear transition when
+        # transition_power is 1.
+        weight = (weight / weight.max())**transition_power
+        for offset in offsets:
+            chunk = TensorChunk(mix, offset, segment)
+            chunk_out = apply_model(model, chunk, shifts=shifts)
+            chunk_length = chunk_out.shape[-1]
+            out[..., offset:offset + segment] += weight[:chunk_length] * chunk_out
+            sum_weight[offset:offset + segment] += weight[:chunk_length]
+            offset += segment
+        assert sum_weight.min() > 0
+        out /= sum_weight
+        return out
+    elif shifts:
+        max_shift = int(0.5 * model.samplerate)
+        mix = tensor_chunk(mix)
+        padded_mix = mix.padded(length + 2 * max_shift)
+        out = 0
+        for _ in range(shifts):
+            offset = random.randint(0, max_shift)
+            shifted = TensorChunk(padded_mix, offset, length + max_shift - offset)
+            shifted_out = apply_model(model, shifted)
+            out += shifted_out[..., max_shift - offset:]
+        out /= shifts
+        return out
+    else:
+        valid_length = model.valid_length(length)
+        mix = tensor_chunk(mix)
+        padded_mix = mix.padded(valid_length)
+        with th.no_grad():
+            out = model(padded_mix.unsqueeze(0))[0]
+        return center_trim(out, length)
+
+
+@contextmanager
+def temp_filenames(count, delete=True):
+    names = []
+    try:
+        for _ in range(count):
+            names.append(tempfile.NamedTemporaryFile(delete=False).name)
+        yield names
+    finally:
+        if delete:
+            for name in names:
+                os.unlink(name)
+
+
+def get_quantizer(model, args, optimizer=None):
+    quantizer = None
+    if args.diffq:
+        quantizer = DiffQuantizer(
+            model, min_size=args.q_min_size, group_size=8)
+        if optimizer is not None:
+            quantizer.setup_optimizer(optimizer)
+    elif args.qat:
+        quantizer = UniformQuantizer(
+                model, bits=args.qat, min_size=args.q_min_size)
+    return quantizer
+
+
+def load_model(path, strict=False):
+    with warnings.catch_warnings():
+        warnings.simplefilter("ignore")
+        load_from = path
+        package = th.load(load_from, 'cpu')
+
+    klass = package["klass"]
+    args = package["args"]
+    kwargs = package["kwargs"]
+
+    if strict:
+        model = klass(*args, **kwargs)
+    else:
+        sig = inspect.signature(klass)
+        for key in list(kwargs):
+            if key not in sig.parameters:
+                warnings.warn("Dropping inexistant parameter " + key)
+                del kwargs[key]
+        model = klass(*args, **kwargs)
+
+    state = package["state"]
+    training_args = package["training_args"]
+    quantizer = get_quantizer(model, training_args)
+
+    set_state(model, quantizer, state)
+    return model
+
+
+def get_state(model, quantizer):
+    if quantizer is None:
+        state = {k: p.data.to('cpu') for k, p in model.state_dict().items()}
+    else:
+        state = quantizer.get_quantized_state()
+        buf = io.BytesIO()
+        th.save(state, buf)
+        state = {'compressed': zlib.compress(buf.getvalue())}
+    return state
+
+
+def set_state(model, quantizer, state):
+    if quantizer is None:
+        model.load_state_dict(state)
+    else:
+        buf = io.BytesIO(zlib.decompress(state["compressed"]))
+        state = th.load(buf, "cpu")
+        quantizer.restore_quantized_state(state)
+
+    return state
+
+
+def save_state(state, path):
+    buf = io.BytesIO()
+    th.save(state, buf)
+    sig = hashlib.sha256(buf.getvalue()).hexdigest()[:8]
+
+    path = path.parent / (path.stem + "-" + sig + path.suffix)
+    path.write_bytes(buf.getvalue())
+
+
+def save_model(model, quantizer, training_args, path):
+    args, kwargs = model._init_args_kwargs
+    klass = model.__class__
+
+    state = get_state(model, quantizer)
+
+    save_to = path
+    package = {
+        'klass': klass,
+        'args': args,
+        'kwargs': kwargs,
+        'state': state,
+        'training_args': training_args,
+    }
+    th.save(package, save_to)
+
+
+def capture_init(init):
+    @functools.wraps(init)
+    def __init__(self, *args, **kwargs):
+        self._init_args_kwargs = (args, kwargs)
+        init(self, *args, **kwargs)
+
+    return __init__
diff --git a/demucs/wav.py b/demucs/wav.py
new file mode 100644
index 0000000000000000000000000000000000000000..a65c3b2ba5aacb1fcab3753f1f85ff7b8db7fc11
--- /dev/null
+++ b/demucs/wav.py
@@ -0,0 +1,174 @@
+# Copyright (c) Facebook, Inc. and its affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the license found in the
+# LICENSE file in the root directory of this source tree.
+
+from collections import OrderedDict
+import hashlib
+import math
+import json
+from pathlib import Path
+
+import julius
+import torch as th
+from torch import distributed
+import torchaudio as ta
+from torch.nn import functional as F
+
+from .audio import convert_audio_channels
+from .compressed import get_musdb_tracks
+
+MIXTURE = "mixture"
+EXT = ".wav"
+
+
+def _track_metadata(track, sources):
+    track_length = None
+    track_samplerate = None
+    for source in sources + [MIXTURE]:
+        file = track / f"{source}{EXT}"
+        info = ta.info(str(file))
+        length = info.num_frames
+        if track_length is None:
+            track_length = length
+            track_samplerate = info.sample_rate
+        elif track_length != length:
+            raise ValueError(
+                f"Invalid length for file {file}: "
+                f"expecting {track_length} but got {length}.")
+        elif info.sample_rate != track_samplerate:
+            raise ValueError(
+                f"Invalid sample rate for file {file}: "
+                f"expecting {track_samplerate} but got {info.sample_rate}.")
+        if source == MIXTURE:
+            wav, _ = ta.load(str(file))
+            wav = wav.mean(0)
+            mean = wav.mean().item()
+            std = wav.std().item()
+
+    return {"length": length, "mean": mean, "std": std, "samplerate": track_samplerate}
+
+
+def _build_metadata(path, sources):
+    meta = {}
+    path = Path(path)
+    for file in path.iterdir():
+        meta[file.name] = _track_metadata(file, sources)
+    return meta
+
+
+class Wavset:
+    def __init__(
+            self,
+            root, metadata, sources,
+            length=None, stride=None, normalize=True,
+            samplerate=44100, channels=2):
+        """
+        Waveset (or mp3 set for that matter). Can be used to train
+        with arbitrary sources. Each track should be one folder inside of `path`.
+        The folder should contain files named `{source}.{ext}`.
+        Files will be grouped according to `sources` (each source is a list of
+        filenames).
+
+        Sample rate and channels will be converted on the fly.
+
+        `length` is the sample size to extract (in samples, not duration).
+        `stride` is how many samples to move by between each example.
+        """
+        self.root = Path(root)
+        self.metadata = OrderedDict(metadata)
+        self.length = length
+        self.stride = stride or length
+        self.normalize = normalize
+        self.sources = sources
+        self.channels = channels
+        self.samplerate = samplerate
+        self.num_examples = []
+        for name, meta in self.metadata.items():
+            track_length = int(self.samplerate * meta['length'] / meta['samplerate'])
+            if length is None or track_length < length:
+                examples = 1
+            else:
+                examples = int(math.ceil((track_length - self.length) / self.stride) + 1)
+            self.num_examples.append(examples)
+
+    def __len__(self):
+        return sum(self.num_examples)
+
+    def get_file(self, name, source):
+        return self.root / name / f"{source}{EXT}"
+
+    def __getitem__(self, index):
+        for name, examples in zip(self.metadata, self.num_examples):
+            if index >= examples:
+                index -= examples
+                continue
+            meta = self.metadata[name]
+            num_frames = -1
+            offset = 0
+            if self.length is not None:
+                offset = int(math.ceil(
+                    meta['samplerate'] * self.stride * index / self.samplerate))
+                num_frames = int(math.ceil(
+                    meta['samplerate'] * self.length / self.samplerate))
+            wavs = []
+            for source in self.sources:
+                file = self.get_file(name, source)
+                wav, _ = ta.load(str(file), frame_offset=offset, num_frames=num_frames)
+                wav = convert_audio_channels(wav, self.channels)
+                wavs.append(wav)
+
+            example = th.stack(wavs)
+            example = julius.resample_frac(example, meta['samplerate'], self.samplerate)
+            if self.normalize:
+                example = (example - meta['mean']) / meta['std']
+            if self.length:
+                example = example[..., :self.length]
+                example = F.pad(example, (0, self.length - example.shape[-1]))
+            return example
+
+
+def get_wav_datasets(args, samples, sources):
+    sig = hashlib.sha1(str(args.wav).encode()).hexdigest()[:8]
+    metadata_file = args.metadata / (sig + ".json")
+    train_path = args.wav / "train"
+    valid_path = args.wav / "valid"
+    if not metadata_file.is_file() and args.rank == 0:
+        train = _build_metadata(train_path, sources)
+        valid = _build_metadata(valid_path, sources)
+        json.dump([train, valid], open(metadata_file, "w"))
+    if args.world_size > 1:
+        distributed.barrier()
+    train, valid = json.load(open(metadata_file))
+    train_set = Wavset(train_path, train, sources,
+                       length=samples, stride=args.data_stride,
+                       samplerate=args.samplerate, channels=args.audio_channels,
+                       normalize=args.norm_wav)
+    valid_set = Wavset(valid_path, valid, [MIXTURE] + sources,
+                       samplerate=args.samplerate, channels=args.audio_channels,
+                       normalize=args.norm_wav)
+    return train_set, valid_set
+
+
+def get_musdb_wav_datasets(args, samples, sources):
+    metadata_file = args.metadata / "musdb_wav.json"
+    root = args.musdb / "train"
+    if not metadata_file.is_file() and args.rank == 0:
+        metadata = _build_metadata(root, sources)
+        json.dump(metadata, open(metadata_file, "w"))
+    if args.world_size > 1:
+        distributed.barrier()
+    metadata = json.load(open(metadata_file))
+
+    train_tracks = get_musdb_tracks(args.musdb, is_wav=True, subsets=["train"], split="train")
+    metadata_train = {name: meta for name, meta in metadata.items() if name in train_tracks}
+    metadata_valid = {name: meta for name, meta in metadata.items() if name not in train_tracks}
+    train_set = Wavset(root, metadata_train, sources,
+                       length=samples, stride=args.data_stride,
+                       samplerate=args.samplerate, channels=args.audio_channels,
+                       normalize=args.norm_wav)
+    valid_set = Wavset(root, metadata_valid, [MIXTURE] + sources,
+                       samplerate=args.samplerate, channels=args.audio_channels,
+                       normalize=args.norm_wav)
+    return train_set, valid_set
diff --git a/diffq/__init__.py b/diffq/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..2b997ee4ed99a90cc43db7812383927e6fe1a3e8
--- /dev/null
+++ b/diffq/__init__.py
@@ -0,0 +1,18 @@
+# Copyright (c) Facebook, Inc. and its affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the license found in the
+# LICENSE file in the root directory of this source tree.
+
+# flake8: noqa
+"""
+This package implements different quantization strategies:
+
+- `diffq.uniform.UniformQuantizer`: classic uniform quantization over n bits.
+- `diffq.diffq.DiffQuantizer`: differentiable quantizer based on scaled noise injection.
+
+Also, do check `diffq.base.BaseQuantizer` for the common methods of all Quantizers.
+"""
+
+from .uniform import UniformQuantizer
+from .diffq import DiffQuantizer
diff --git a/diffq/base.py b/diffq/base.py
new file mode 100644
index 0000000000000000000000000000000000000000..9bd5276b51fbed3d4b898a45b93479ff19e62a7b
--- /dev/null
+++ b/diffq/base.py
@@ -0,0 +1,262 @@
+# Copyright (c) Facebook, Inc. and its affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the license found in the
+# LICENSE file in the root directory of this source tree.
+
+from dataclasses import dataclass
+from concurrent import futures
+from fnmatch import fnmatch
+from functools import partial
+import io
+import math
+from multiprocessing import cpu_count
+import typing as tp
+import zlib
+
+import torch
+
+
+class BaseQuantizer:
+    @dataclass
+    class _QuantizedParam:
+        name: str
+        param: torch.nn.Parameter
+        module: torch.nn.Module
+        # If a Parameter is used multiple times, `other` can be used
+        # to share state between the different Quantizers
+        other: tp.Optional[tp.Any]
+
+    def __init__(self, model: torch.nn.Module, min_size: float = 0.01, float16: bool = False,
+                 exclude: tp.Optional[tp.List[str]] = [], detect_bound: bool = True):
+        self.model = model
+        self.min_size = min_size
+        self.float16 = float16
+        self.exclude = exclude
+        self.detect_bound = detect_bound
+        self._quantized = False
+        self._pre_handle = self.model.register_forward_pre_hook(self._forward_pre_hook)
+        self._post_handle = self.model.register_forward_hook(self._forward_hook)
+
+        self._quantized_state = None
+        self._qparams = []
+        self._float16 = []
+        self._others = []
+        self._rnns = []
+
+        self._saved = []
+
+        self._find_params()
+
+    def _find_params(self):
+        min_params = self.min_size * 2**20 // 4
+        previous = {}
+        for module_name, module in self.model.named_modules():
+            if isinstance(module, torch.nn.RNNBase):
+                self._rnns.append(module)
+            for name, param in list(module.named_parameters(recurse=False)):
+                full_name = f"{module_name}.{name}"
+                matched = False
+                for pattern in self.exclude:
+                    if fnmatch(full_name, pattern) or fnmatch(name, pattern):
+                        matched = True
+                        break
+
+                if param.numel() <= min_params or matched:
+                    if id(param) in previous:
+                        continue
+                    if self.detect_bound:
+                        previous[id(param)] = None
+                    if self.float16:
+                        self._float16.append(param)
+                    else:
+                        self._others.append(param)
+                else:
+                    qparam = self._register_param(name, param, module, previous.get(id(param)))
+                    if self.detect_bound:
+                        previous[id(param)] = qparam
+                    self._qparams.append(qparam)
+
+    def _register_param(self, name, param, module, other):
+        return self.__class__._QuantizedParam(name, param, module, other)
+
+    def _forward_pre_hook(self, module, input):
+        if self.model.training:
+            self._quantized_state = None
+            if self._quantized:
+                self.unquantize()
+            if self._pre_forward_train():
+                self._fix_rnns()
+        else:
+            self.quantize()
+
+    def _forward_hook(self, module, input, output):
+        if self.model.training:
+            if self._post_forward_train():
+                self._fix_rnns(flatten=False)  # Hacky, next forward will flatten
+
+    def quantize(self, save=True):
+        """
+        Immediately apply quantization to the model parameters.
+        If `save` is True, save a copy of the unquantized parameters, that can be
+        restored with `unquantize()`.
+        """
+        if self._quantized:
+            return
+        if save:
+            self._saved = [qp.param.data.to('cpu', copy=True)
+                           for qp in self._qparams if qp.other is None]
+        self.restore_quantized_state(self.get_quantized_state())
+        self._quantized = True
+        self._fix_rnns()
+
+    def unquantize(self):
+        """
+        Revert a previous call to `quantize()`.
+        """
+        if not self._quantized:
+            raise RuntimeError("Can only be called on a quantized model.")
+        if not self._saved:
+            raise RuntimeError("Nothing to restore.")
+        for qparam in self._qparams:
+            if qparam.other is None:
+                qparam.param.data[:] = self._saved.pop(0)
+        assert len(self._saved) == 0
+        self._quantized = False
+        self._fix_rnns()
+
+    def _pre_forward_train(self) -> bool:
+        """
+        Called once before each forward for continuous quantization.
+        Should return  True if parameters were changed.
+        """
+        return False
+
+    def _post_forward_train(self) -> bool:
+        """
+        Called once after each forward (to restore state for instance).
+        Should return True if parameters were changed.
+        """
+        return False
+
+    def _fix_rnns(self, flatten=True):
+        """
+        To be called after quantization happened to fix RNNs.
+        """
+        for rnn in self._rnns:
+            rnn._flat_weights = [
+                (lambda wn: getattr(rnn, wn) if hasattr(rnn, wn) else None)(wn)
+                for wn in rnn._flat_weights_names]
+            if flatten:
+                rnn.flatten_parameters()
+
+    def get_quantized_state(self):
+        """
+        Returns sufficient quantized information to rebuild the model state.
+
+        ..Note::
+            To achieve maximum compression, you should compress this with
+            gzip or other, as quantized weights are not optimally coded!
+        """
+        if self._quantized_state is None:
+            self._quantized_state = self._get_quantized_state()
+        return self._quantized_state
+
+    def _get_quantized_state(self):
+        """
+        Actual implementation for `get_quantized_state`.
+        """
+        float16_params = []
+        for p in self._float16:
+            q = p.data.half()
+            float16_params.append(q)
+
+        return {
+            "quantized": [self._quantize_param(qparam) for qparam in self._qparams
+                          if qparam.other is None],
+            "float16": float16_params,
+            "others": [p.data.clone() for p in self._others],
+        }
+
+    def _quantize_param(self, qparam: _QuantizedParam) -> tp.Any:
+        """
+        To be overriden.
+        """
+        raise NotImplementedError()
+
+    def _unquantize_param(self, qparam: _QuantizedParam, quantized: tp.Any) -> torch.Tensor:
+        """
+        To be overriden.
+        """
+        raise NotImplementedError()
+
+    def restore_quantized_state(self, state) -> None:
+        """
+        Restore the state of the model from the quantized state.
+        """
+        for p, q in zip(self._float16, state["float16"]):
+            p.data[:] = q.to(p)
+
+        for p, q in zip(self._others, state["others"]):
+            p.data[:] = q
+
+        remaining = list(state["quantized"])
+        for qparam in self._qparams:
+            if qparam.other is not None:
+                # Only unquantize first appearance of nn.Parameter.
+                continue
+            quantized = remaining.pop(0)
+            qparam.param.data[:] = self._unquantize_param(qparam, quantized)
+        self._fix_rnns()
+
+    def detach(self) -> None:
+        """
+        Detach from the model, removes hooks and anything else.
+        """
+        self._pre_handle.remove()
+        self._post_handle.remove()
+
+    def model_size(self) -> torch.Tensor:
+        """
+        Returns an estimate of the quantized model size.
+        """
+        total = torch.tensor(0.)
+        for p in self._float16:
+            total += 16 * p.numel()
+        for p in self._others:
+            total += 32 * p.numel()
+        return total / 2**20 / 8  # bits to MegaBytes
+
+    def true_model_size(self) -> float:
+        """
+        Return the true quantized model size, in MB, without extra
+        compression.
+        """
+        return self.model_size().item()
+
+    def compressed_model_size(self, compress_level=-1, num_workers=8) -> float:
+        """
+        Return the compressed quantized model size, in MB.
+
+        Args:
+            compress_level (int): compression level used with zlib,
+                see `zlib.compress` for details.
+            num_workers (int): will split the final big byte representation in that
+                many chunks processed in parallels.
+        """
+        out = io.BytesIO()
+        torch.save(self.get_quantized_state(), out)
+        ms = _parallel_compress_len(out.getvalue(), compress_level, num_workers)
+        return ms / 2 ** 20
+
+
+def _compress_len(data, compress_level):
+    return len(zlib.compress(data, level=compress_level))
+
+
+def _parallel_compress_len(data, compress_level, num_workers):
+    num_workers = min(cpu_count(), num_workers)
+    chunk_size = int(math.ceil(len(data) / num_workers))
+    chunks = [data[offset:offset + chunk_size] for offset in range(0, len(data), chunk_size)]
+    with futures.ProcessPoolExecutor(num_workers) as pool:
+        return sum(pool.map(partial(_compress_len, compress_level=compress_level), chunks))
diff --git a/diffq/diffq.py b/diffq/diffq.py
new file mode 100644
index 0000000000000000000000000000000000000000..b475ec7f55227417b014c69b5cf55033182113e1
--- /dev/null
+++ b/diffq/diffq.py
@@ -0,0 +1,286 @@
+# Copyright (c) Facebook, Inc. and its affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the license found in the
+# LICENSE file in the root directory of this source tree.
+
+"""
+Differentiable quantizer based on scaled noise injection.
+"""
+from dataclasses import dataclass
+import math
+import typing as tp
+
+import torch
+
+from .base import BaseQuantizer
+from .uniform import uniform_quantize, uniform_unquantize
+from .utils import simple_repr
+
+
+class DiffQuantizer(BaseQuantizer):
+    @dataclass
+    class _QuantizedParam(BaseQuantizer._QuantizedParam):
+        logit: torch.nn.Parameter
+
+    def __init__(self, model: torch.nn.Module, min_size: float = 0.01, float16: bool = False,
+                 group_size: int = 1, min_bits: float = 2, max_bits: float = 15,
+                 param="bits", noise="gaussian",
+                 init_bits: float = 8, extra_bits: float = 0, suffix: str = "_diffq",
+                 exclude: tp.List[str] = [], detect_bound: bool = True):
+        """
+        Differentiable quantizer based on scaled noise injection.
+        For every parameter `p` in the model, this introduces a number of bits parameter
+        `b` with the same dimensions (when group_size = 1).
+        Before each forward, `p` is replaced by `p + U`
+        with U uniform iid noise with range [-d/2, d/2], with `d` the uniform quantization
+        step for `b` bits.
+        This noise approximates the quantization noise in a differentiable manner, both
+        with respect to the unquantized parameter `p` and the number of bits `b`.
+
+        At eveluation (as detected with `model.eval()`), the model is replaced
+        by its true quantized version, and restored when going back to training.
+
+        When doing actual quantization (for serialization, or evaluation),
+        the number of bits is rounded to the nearest integer, and needs to be stored along.
+        This will cost a few bits per dimension. To reduce this cost, one can use `group_size`,
+        which will use a single noise level for multiple weight entries.
+
+        You can use the `DiffQuantizer.model_size` method to get a differentiable estimate of the
+        model size in MB. You can then use this estimate as a penalty in your training loss.
+
+        Args:
+            model (torch.nn.Module): model to quantize
+            min_size (float): minimum size in MB of a parameter to be quantized.
+            float16 (bool): if a layer is smaller than min_size, should we still do float16?
+            group_size (int): weight entries are groupped together to reduce the number
+                of noise scales to store. This should divide the size of all parameters
+                bigger than min_size.
+            min_bits (float): minimal number of bits.
+            max_bits (float): maximal number of bits.
+            init_bits (float): initial number of bits.
+            extra_bits (float): extra bits to add for actual quantization (before roundoff).
+            suffix (str): suffix used for the name of the extra noise scale parameters.
+            exclude (list[str]): list of patterns used to match parameters to exclude.
+                For instance `['bias']` to exclude all bias terms.
+            detect_bound (bool): if True, will detect bound parameters and reuse
+                the same quantized tensor for both, as well as the same number of bits.
+
+        ..Warning::
+            You must call `model.training()` and `model.eval()` for `DiffQuantizer` work properly.
+
+        """
+        self.group_size = group_size
+        self.min_bits = min_bits
+        self.max_bits = max_bits
+        self.init_bits = init_bits
+        self.extra_bits = extra_bits
+        self.suffix = suffix
+        self.param = param
+        self.noise = noise
+        assert noise in ["gaussian", "uniform"]
+        self._optimizer_setup = False
+
+        self._min_noise = 1 / (2 ** self.max_bits - 1)
+        self._max_noise = 1 / (2 ** self.min_bits - 1)
+
+        assert group_size >= 0
+        assert min_bits < init_bits < max_bits, \
+               "init_bits must be between min_bits and max_bits excluded3"
+
+        for name, _ in model.named_parameters():
+            if name.endswith(suffix):
+                raise RuntimeError("The model already has some noise scales parameters, "
+                                   "maybe you used twice a DiffQuantizer on the same model?.")
+
+        super().__init__(model, min_size, float16, exclude, detect_bound)
+
+    def _get_bits(self, logit: torch.Tensor):
+        if self.param == "noise":
+            return torch.log2(1 + 1 / self._get_noise_scale(logit))
+        else:
+            t = torch.sigmoid(logit)
+            return self.max_bits * t + (1 - t) * self.min_bits
+
+    def _get_noise_scale(self, logit: torch.Tensor):
+        if self.param == "noise":
+            t = torch.sigmoid(logit)
+            return torch.exp(t * math.log(self._min_noise) + (1 - t) * math.log(self._max_noise))
+        else:
+            return 1 / (2 ** self._get_bits(logit) - 1)
+
+    def _register_param(self, name, param, module, other):
+        if other is not None:
+            return self.__class__._QuantizedParam(
+               name=name, param=param, module=module, logit=other.logit, other=other)
+        assert self.group_size == 0 or param.numel() % self.group_size == 0
+        # we want the initial number of bits to be init_bits.
+        if self.param == "noise":
+            noise_scale = 1 / (2 ** self.init_bits - 1)
+            t = (math.log(noise_scale) - math.log(self._max_noise)) / (
+                math.log(self._min_noise) - math.log(self._max_noise))
+        else:
+            t = (self.init_bits - self.min_bits) / (self.max_bits - self.min_bits)
+        assert 0 < t < 1
+        logit = torch.logit(torch.tensor(float(t)))
+        assert abs(self._get_bits(logit) - self.init_bits) < 1e-5
+        if self.group_size > 0:
+            nparam = param.numel() // self.group_size
+        else:
+            nparam = 1
+        logit = torch.nn.Parameter(
+            torch.full(
+                (nparam,),
+                logit,
+                device=param.device))
+        module.register_parameter(name + self.suffix, logit)
+        return self.__class__._QuantizedParam(
+           name=name, param=param, module=module, logit=logit, other=None)
+
+    def clear_optimizer(self, optimizer: torch.optim.Optimizer):
+        params = [qp.logit for qp in self._qparams]
+
+        for group in optimizer.param_groups:
+            new_params = []
+            for q in list(group["params"]):
+                matched = False
+                for p in params:
+                    if p is q:
+                        matched = True
+                if not matched:
+                    new_params.append(q)
+            group["params"][:] = new_params
+
+    def setup_optimizer(self, optimizer: torch.optim.Optimizer,
+                        lr: float = 1e-3, **kwargs):
+        """
+        Setup the optimizer to tune the number of bits. In particular, this will deactivate
+        weight decay for the bits parameters.
+
+        Args:
+            optimizer (torch.Optimizer): optimizer to use.
+            lr (float): specific learning rate for the bits parameters. 1e-3
+                is perfect for Adam.,w
+            kwargs (dict): overrides for other optimization parameters for the bits.
+        """
+        assert not self._optimizer_setup
+        self._optimizer_setup = True
+
+        params = [qp.logit for qp in self._qparams]
+
+        for group in optimizer.param_groups:
+            for q in list(group["params"]):
+                for p in params:
+                    if p is q:
+                        raise RuntimeError("You should create the optimizer "
+                                           "before the quantizer!")
+
+        group = {"params": params, "lr": lr, "weight_decay": 0}
+        group.update(kwargs)
+        optimizer.add_param_group(group)
+
+    def no_optimizer(self):
+        """
+        Call this if you do not want to use an optimizer.
+        """
+        self._optimizer_setup = True
+
+    def check_unused(self):
+        for qparam in self._qparams:
+            if qparam.other is not None:
+                continue
+            grad = qparam.param.grad
+            if grad is None or (grad == 0).all():
+                if qparam.logit.grad is not None:
+                    qparam.logit.grad.data.zero_()
+
+    def model_size(self, exact=False):
+        """
+        Differentiable estimate of the model size.
+        The size is returned in MB.
+
+        If `exact` is True, then the output is no longer differentiable but
+        reflect exactly an achievable size, even without compression,
+        i.e.same as returned by `naive_model_size()`.
+        """
+        total = super().model_size()
+        subtotal = 0
+        for qparam in self._qparams:
+            # only count the first appearance of a Parameter
+            if qparam.other is not None:
+                continue
+            bits = self.extra_bits + self._get_bits(qparam.logit)
+            if exact:
+                bits = bits.round().clamp(1, 15)
+            if self.group_size == 0:
+                group_size = qparam.param.numel()
+            else:
+                group_size = self.group_size
+            subtotal += group_size * bits.sum()
+            subtotal += 2 * 32  # param scale
+
+            # Number of bits to represent each number of bits
+            bits_bits = math.ceil(math.log2(1 + (bits.max().round().item() - self.min_bits)))
+            subtotal += 8  # 8 bits for bits_bits
+            subtotal += bits_bits * bits.numel()
+
+        subtotal /= 2 ** 20 * 8  # bits -> MegaBytes
+        return total + subtotal
+
+    def true_model_size(self):
+        """
+        Naive model size without zlib compression.
+        """
+        return self.model_size(exact=True).item()
+
+    def _pre_forward_train(self):
+        if not self._optimizer_setup:
+            raise RuntimeError("You must call `setup_optimizer()` on your optimizer "
+                               "before starting training.")
+        for qparam in self._qparams:
+            if qparam.other is not None:
+                noisy = qparam.other.module._parameters[qparam.other.name]
+            else:
+                bits = self._get_bits(qparam.logit)[:, None]
+                if self.group_size == 0:
+                    p_flat = qparam.param.view(-1)
+                else:
+                    p_flat = qparam.param.view(-1, self.group_size)
+                scale = p_flat.max() - p_flat.min()
+                unit = 1 / (2**bits - 1)
+                if self.noise == "uniform":
+                    noise_source = (torch.rand_like(p_flat) - 0.5)
+                elif self.noise == "gaussian":
+                    noise_source = torch.randn_like(p_flat) / 2
+                noise = scale * unit * noise_source
+                noisy = p_flat + noise
+            # We bypass the checks by PyTorch on parameters being leafs
+            qparam.module._parameters[qparam.name] = noisy.view_as(qparam.param)
+        return True
+
+    def _post_forward_train(self):
+        for qparam in self._qparams:
+            qparam.module._parameters[qparam.name] = qparam.param
+        return True
+
+    def _quantize_param(self, qparam: _QuantizedParam) -> tp.Any:
+        bits = self.extra_bits + self._get_bits(qparam.logit)
+        bits = bits.round().clamp(1, 15)[:, None].byte()
+        if self.group_size == 0:
+            p = qparam.param.data.view(-1)
+        else:
+            p = qparam.param.data.view(-1, self.group_size)
+        levels, scales = uniform_quantize(p, bits)
+        return levels, scales, bits
+
+    def _unquantize_param(self, qparam: _QuantizedParam, quantized: tp.Any) -> torch.Tensor:
+        levels, param_scale, bits = quantized
+        return uniform_unquantize(levels, param_scale, bits).view_as(qparam.param.data)
+
+    def detach(self):
+        super().detach()
+        for qparam in self._qparams:
+            delattr(qparam.module, qparam.name + self.suffix)
+
+    def __repr__(self):
+        return simple_repr(self)
diff --git a/diffq/uniform.py b/diffq/uniform.py
new file mode 100644
index 0000000000000000000000000000000000000000..f61e9129c04caaa33c66f726bf2433d51689cfa5
--- /dev/null
+++ b/diffq/uniform.py
@@ -0,0 +1,121 @@
+# Copyright (c) Facebook, Inc. and its affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the license found in the
+# LICENSE file in the root directory of this source tree.
+
+"""
+Classic uniform quantization over n bits.
+"""
+from typing import Tuple
+import torch
+
+from .base import BaseQuantizer
+from .utils import simple_repr
+
+
+def uniform_quantize(p: torch.Tensor, bits: torch.Tensor = torch.tensor(8.)):
+    """
+    Quantize the given weights over `bits` bits.
+
+    Returns:
+        - quantized levels
+        - (min, max) range.
+
+    """
+    assert (bits >= 1).all() and (bits <= 15).all()
+    num_levels = (2 ** bits.float()).long()
+    mn = p.min().item()
+    mx = p.max().item()
+    p = (p - mn) / (mx - mn)  # put p in [0, 1]
+    unit = 1 / (num_levels - 1)  # quantization unit
+    levels = (p / unit).round()
+    if (bits <= 8).all():
+        levels = levels.byte()
+    else:
+        levels = levels.short()
+    return levels, (mn, mx)
+
+
+def uniform_unquantize(levels: torch.Tensor, scales: Tuple[float, float],
+                       bits: torch.Tensor = torch.tensor(8.)):
+    """
+    Unquantize the weights from the levels and scale. Return a float32 tensor.
+    """
+    mn, mx = scales
+    num_levels = 2 ** bits.float()
+    unit = 1 / (num_levels - 1)
+    levels = levels.float()
+    p = levels * unit  # in [0, 1]
+    return p * (mx - mn) + mn
+
+
+class UniformQuantizer(BaseQuantizer):
+    def __init__(self, model: torch.nn.Module, bits: float = 8., min_size: float = 0.01,
+                 float16: bool = False, qat: bool = False, exclude=[], detect_bound=True):
+        """
+        Args:
+            model (torch.nn.Module): model to quantize
+            bits (float): number of bits to quantize over.
+            min_size (float): minimum size in MB of a parameter to be quantized.
+            float16 (bool): if a layer is smaller than min_size, should we still do float16?
+            qat (bool): perform quantized aware training.
+            exclude (list[str]): list of patterns used to match parameters to exclude.
+                For instance `['bias']` to exclude all bias terms.
+            detect_bound (bool): if True, will detect bound parameters and reuse
+                the same quantized tensor for both.
+        """
+        self.bits = float(bits)
+        self.qat = qat
+
+        super().__init__(model, min_size, float16, exclude, detect_bound)
+
+    def __repr__(self):
+        return simple_repr(self, )
+
+    def _pre_forward_train(self):
+        if self.qat:
+            for qparam in self._qparams:
+                if qparam.other is not None:
+                    new_param = qparam.other.module._parameters[qparam.other.name]
+                else:
+                    quantized = self._quantize_param(qparam)
+                    qvalue = self._unquantize_param(qparam, quantized)
+                    new_param = qparam.param + (qvalue - qparam.param).detach()
+                qparam.module._parameters[qparam.name] = new_param
+            return True
+        return False
+
+    def _post_forward_train(self):
+        if self.qat:
+            for qparam in self._qparams:
+                qparam.module._parameters[qparam.name] = qparam.param
+            return True
+        return False
+
+    def _quantize_param(self, qparam):
+        levels, scales = uniform_quantize(qparam.param.data, torch.tensor(self.bits))
+        return (levels, scales)
+
+    def _unquantize_param(self, qparam, quantized):
+        levels, scales = quantized
+        return uniform_unquantize(levels, scales, torch.tensor(self.bits))
+
+    def model_size(self):
+        """
+        Non differentiable model size in MB.
+        """
+        total = super().model_size()
+        subtotal = 0
+        for qparam in self._qparams:
+            if qparam.other is None:  # if parameter is bound, count only one copy.
+                subtotal += self.bits * qparam.param.numel() + 64  # 2 float for the overall scales
+        subtotal /= 2**20 * 8  # bits to MegaBytes
+        return total + subtotal
+
+    def true_model_size(self):
+        """
+        Return the true quantized model size, in MB, without extra
+        compression.
+        """
+        return self.model_size().item()
diff --git a/diffq/utils.py b/diffq/utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..be6ab5253c38564140bc202077292bb99f9f397b
--- /dev/null
+++ b/diffq/utils.py
@@ -0,0 +1,37 @@
+# Copyright (c) Facebook, Inc. and its affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the license found in the
+# LICENSE file in the root directory of this source tree.
+
+import inspect
+from typing import Optional, List
+
+
+def simple_repr(obj, attrs: Optional[List[str]] = None, overrides={}):
+    """
+    Return a simple representation string for `obj`.
+    If `attrs` is not None, it should be a list of attributes to include.
+    """
+    params = inspect.signature(obj.__class__).parameters
+    attrs_repr = []
+    if attrs is None:
+        attrs = params.keys()
+    for attr in attrs:
+        display = False
+        if attr in overrides:
+            value = overrides[attr]
+        elif hasattr(obj, attr):
+            value = getattr(obj, attr)
+        else:
+            continue
+        if attr in params:
+            param = params[attr]
+            if param.default is inspect._empty or value != param.default:
+                display = True
+        else:
+            display = True
+
+        if display:
+            attrs_repr.append(f"{attr}={value}")
+    return f"{obj.__class__.__name__}({','.join(attrs_repr)})"
diff --git a/easy_infer.py b/easy_infer.py
new file mode 100644
index 0000000000000000000000000000000000000000..81a70d3648c38120f908cdaf2ea3bd15af9dec26
--- /dev/null
+++ b/easy_infer.py
@@ -0,0 +1,1383 @@
+import subprocess
+import os
+import sys
+import errno
+import shutil
+import yt_dlp
+from mega import Mega
+import datetime
+import unicodedata
+import torch
+import glob
+import gradio as gr
+import gdown
+import zipfile
+import traceback
+import json
+import mdx
+from mdx_processing_script import get_model_list,id_to_ptm,prepare_mdx,run_mdx
+import requests
+import wget
+import ffmpeg
+import hashlib
+now_dir = os.getcwd()
+sys.path.append(now_dir)
+from unidecode import unidecode
+import re
+import time
+from lib.infer_pack.models_onnx import SynthesizerTrnMsNSFsidM
+from infer.modules.vc.pipeline import Pipeline
+VC = Pipeline
+from lib.infer_pack.models import (
+    SynthesizerTrnMs256NSFsid,
+    SynthesizerTrnMs256NSFsid_nono,
+    SynthesizerTrnMs768NSFsid,
+    SynthesizerTrnMs768NSFsid_nono,
+)
+from MDXNet import MDXNetDereverb
+from configs.config import Config
+from infer_uvr5 import _audio_pre_, _audio_pre_new
+from huggingface_hub import HfApi, list_models
+from huggingface_hub import login
+from i18n import I18nAuto
+i18n = I18nAuto()
+from bs4 import BeautifulSoup
+from sklearn.cluster import MiniBatchKMeans
+from dotenv import load_dotenv
+load_dotenv()
+config = Config()
+tmp = os.path.join(now_dir, "TEMP")
+shutil.rmtree(tmp, ignore_errors=True)
+os.environ["TEMP"] = tmp
+weight_root = os.getenv("weight_root")
+weight_uvr5_root = os.getenv("weight_uvr5_root")
+index_root = os.getenv("index_root")
+audio_root = "audios"
+names = []
+for name in os.listdir(weight_root):
+    if name.endswith(".pth"):
+        names.append(name)
+index_paths = []
+
+global indexes_list
+indexes_list = []
+
+audio_paths = []
+for root, dirs, files in os.walk(index_root, topdown=False):
+    for name in files:
+        if name.endswith(".index") and "trained" not in name:
+            index_paths.append("%s\\%s" % (root, name))
+
+for root, dirs, files in os.walk(audio_root, topdown=False):
+    for name in files:
+        audio_paths.append("%s/%s" % (root, name))
+
+uvr5_names = []
+for name in os.listdir(weight_uvr5_root):
+    if name.endswith(".pth") or "onnx" in name:
+        uvr5_names.append(name.replace(".pth", ""))
+
+def calculate_md5(file_path):
+    hash_md5 = hashlib.md5()
+    with open(file_path, "rb") as f:
+        for chunk in iter(lambda: f.read(4096), b""):
+            hash_md5.update(chunk)
+    return hash_md5.hexdigest()
+
+def format_title(title):
+     formatted_title = re.sub(r'[^\w\s-]', '', title)
+     formatted_title = formatted_title.replace(" ", "_")
+     return formatted_title
+
+def silentremove(filename):
+    try:
+        os.remove(filename)
+    except OSError as e: 
+        if e.errno != errno.ENOENT: 
+            raise 
+def get_md5(temp_folder):
+  for root, subfolders, files in os.walk(temp_folder):
+    for file in files:
+      if not file.startswith("G_") and not file.startswith("D_") and file.endswith(".pth") and not "_G_" in file and not "_D_" in file:
+        md5_hash = calculate_md5(os.path.join(root, file))
+        return md5_hash
+
+  return None
+
+def find_parent(search_dir, file_name):
+    for dirpath, dirnames, filenames in os.walk(search_dir):
+        if file_name in filenames:
+            return os.path.abspath(dirpath)
+    return None
+
+def find_folder_parent(search_dir, folder_name):
+    for dirpath, dirnames, filenames in os.walk(search_dir):
+        if folder_name in dirnames:
+            return os.path.abspath(dirpath)
+    return None
+
+
+
+def download_from_url(url):
+    parent_path = find_folder_parent(".", "pretrained_v2")
+    zips_path = os.path.join(parent_path, 'zips')
+    
+    if url != '':
+        print(i18n("Downloading the file: ") + f"{url}")
+        if "drive.google.com" in url:
+            if "file/d/" in url:
+                file_id = url.split("file/d/")[1].split("/")[0]
+            elif "id=" in url:
+                file_id = url.split("id=")[1].split("&")[0]
+            else:
+                return None
+            
+            if file_id:
+                os.chdir('./zips')
+                result = subprocess.run(["gdown", f"https://drive.google.com/uc?id={file_id}", "--fuzzy"], capture_output=True, text=True, encoding='utf-8')
+                if "Too many users have viewed or downloaded this file recently" in str(result.stderr):
+                    return "too much use"
+                if "Cannot retrieve the public link of the file." in str(result.stderr):
+                    return "private link"
+                print(result.stderr)
+                
+        elif "/blob/" in url:
+            os.chdir('./zips')
+            url = url.replace("blob", "resolve")
+            response = requests.get(url)
+            if response.status_code == 200:
+                file_name = url.split('/')[-1]
+                with open(os.path.join(zips_path, file_name), "wb") as newfile:
+                    newfile.write(response.content)
+            else:
+                    os.chdir(parent_path)
+        elif "mega.nz" in url:
+            if "#!" in url:
+                file_id = url.split("#!")[1].split("!")[0]
+            elif "file/" in url:
+                file_id = url.split("file/")[1].split("/")[0]
+            else:
+                return None
+            if file_id:
+                m = Mega()
+                m.download_url(url, zips_path)
+        elif "/tree/main" in url:
+           response = requests.get(url)
+           soup = BeautifulSoup(response.content, 'html.parser')
+           temp_url = ''
+           for link in soup.find_all('a', href=True):
+               if link['href'].endswith('.zip'):
+                  temp_url = link['href']
+                  break
+           if temp_url:
+              url = temp_url
+              url = url.replace("blob", "resolve")
+              if "huggingface.co" not in url:
+                 url = "https://huggingface.co" + url
+
+                 wget.download(url)
+           else:
+                 print("No .zip file found on the page.")
+        elif "cdn.discordapp.com" in url:
+            file = requests.get(url)
+            if file.status_code == 200:
+                name = url.split('/')
+                with open(os.path.join(zips_path, name[len(name)-1]), "wb") as newfile:
+                    newfile.write(file.content)
+            else:
+                return None
+        elif "pixeldrain.com" in url:
+            try:
+                file_id = url.split("pixeldrain.com/u/")[1]
+                os.chdir('./zips')
+                print(file_id)
+                response = requests.get(f"https://pixeldrain.com/api/file/{file_id}")
+                if response.status_code == 200:
+                    file_name = response.headers.get("Content-Disposition").split('filename=')[-1].strip('";')
+                    if not os.path.exists(zips_path):
+                        os.makedirs(zips_path)
+                    with open(os.path.join(zips_path, file_name), "wb") as newfile:
+                        newfile.write(response.content)
+                        os.chdir(parent_path)
+                        return "downloaded"
+                else:
+                    os.chdir(parent_path)
+                    return None
+            except Exception as e:
+                print(e)
+                os.chdir(parent_path)
+                return None
+        else:
+            os.chdir('./zips')
+            wget.download(url)
+            
+        os.chdir(parent_path)
+        print(i18n("Full download"))
+        return "downloaded"
+    else:
+        return None
+                
+class error_message(Exception):
+    def __init__(self, mensaje):
+        self.mensaje = mensaje
+        super().__init__(mensaje)
+
+def get_vc(sid, to_return_protect0, to_return_protect1):
+    global n_spk, tgt_sr, net_g, vc, cpt, version
+    if sid == "" or sid == []:
+        global hubert_model
+        if hubert_model is not None: 
+            print("clean_empty_cache")
+            del net_g, n_spk, vc, hubert_model, tgt_sr 
+            hubert_model = net_g = n_spk = vc = hubert_model = tgt_sr = None
+            if torch.cuda.is_available():
+                torch.cuda.empty_cache()
+            if_f0 = cpt.get("f0", 1)
+            version = cpt.get("version", "v1")
+            if version == "v1":
+                if if_f0 == 1:
+                    net_g = SynthesizerTrnMs256NSFsid(
+                        *cpt["config"], is_half=config.is_half
+                    )
+                else:
+                    net_g = SynthesizerTrnMs256NSFsid_nono(*cpt["config"])
+            elif version == "v2":
+                if if_f0 == 1:
+                    net_g = SynthesizerTrnMs768NSFsid(
+                        *cpt["config"], is_half=config.is_half
+                    )
+                else:
+                    net_g = SynthesizerTrnMs768NSFsid_nono(*cpt["config"])
+            del net_g, cpt
+            if torch.cuda.is_available():
+                torch.cuda.empty_cache()
+            cpt = None
+        return (
+            {"visible": False, "__type__": "update"},
+            {"visible": False, "__type__": "update"},
+            {"visible": False, "__type__": "update"},
+        )
+    person = "%s/%s" % (weight_root, sid)
+    print("loading %s" % person)
+    cpt = torch.load(person, map_location="cpu")
+    tgt_sr = cpt["config"][-1]
+    cpt["config"][-3] = cpt["weight"]["emb_g.weight"].shape[0]  
+    if_f0 = cpt.get("f0", 1)
+    if if_f0 == 0:
+        to_return_protect0 = to_return_protect1 = {
+            "visible": False,
+            "value": 0.5,
+            "__type__": "update",
+        }
+    else:
+        to_return_protect0 = {
+            "visible": True,
+            "value": to_return_protect0,
+            "__type__": "update",
+        }
+        to_return_protect1 = {
+            "visible": True,
+            "value": to_return_protect1,
+            "__type__": "update",
+        }
+    version = cpt.get("version", "v1")
+    if version == "v1":
+        if if_f0 == 1:
+            net_g = SynthesizerTrnMs256NSFsid(*cpt["config"], is_half=config.is_half)
+        else:
+            net_g = SynthesizerTrnMs256NSFsid_nono(*cpt["config"])
+    elif version == "v2":
+        if if_f0 == 1:
+            net_g = SynthesizerTrnMs768NSFsid(*cpt["config"], is_half=config.is_half)
+        else:
+            net_g = SynthesizerTrnMs768NSFsid_nono(*cpt["config"])
+    del net_g.enc_q
+    print(net_g.load_state_dict(cpt["weight"], strict=False))
+    net_g.eval().to(config.device)
+    if config.is_half:
+        net_g = net_g.half()
+    else:
+        net_g = net_g.float()
+    vc = VC(tgt_sr, config)
+    n_spk = cpt["config"][-3]
+    return (
+        {"visible": True, "maximum": n_spk, "__type__": "update"},
+        to_return_protect0,
+        to_return_protect1,
+    )
+        
+def load_downloaded_model(url):
+    parent_path = find_folder_parent(".", "pretrained_v2")
+    try:
+        infos = []
+        logs_folders = ['0_gt_wavs','1_16k_wavs','2a_f0','2b-f0nsf','3_feature256','3_feature768']
+        zips_path = os.path.join(parent_path, 'zips')
+        unzips_path = os.path.join(parent_path, 'unzips')
+        weights_path = os.path.join(parent_path, 'weights')
+        logs_dir = ""
+        
+        if os.path.exists(zips_path):
+            shutil.rmtree(zips_path)
+        if os.path.exists(unzips_path):
+            shutil.rmtree(unzips_path)
+
+        os.mkdir(zips_path)
+        os.mkdir(unzips_path)
+        
+        download_file = download_from_url(url)
+        if not download_file:
+            print(i18n("The file could not be downloaded."))
+            infos.append(i18n("The file could not be downloaded."))
+            yield "\n".join(infos)
+        elif download_file == "downloaded":
+            print(i18n("It has been downloaded successfully."))
+            infos.append(i18n("It has been downloaded successfully."))
+            yield "\n".join(infos)
+        elif download_file == "too much use":
+            raise Exception(i18n("Too many users have recently viewed or downloaded this file"))
+        elif download_file == "private link":
+            raise Exception(i18n("Cannot get file from this private link"))
+        
+        for filename in os.listdir(zips_path):
+            if filename.endswith(".zip"):
+                zipfile_path = os.path.join(zips_path,filename)
+                print(i18n("Proceeding with the extraction..."))
+                infos.append(i18n("Proceeding with the extraction..."))
+                shutil.unpack_archive(zipfile_path, unzips_path, 'zip')
+                model_name = os.path.basename(zipfile_path)
+                logs_dir = os.path.join(parent_path,'logs', os.path.normpath(str(model_name).replace(".zip","")))
+                yield "\n".join(infos)
+            else:
+                print(i18n("Unzip error."))
+                infos.append(i18n("Unzip error."))
+                yield "\n".join(infos)
+        
+        index_file = False
+        model_file = False
+        D_file = False
+        G_file = False
+        
+        for path, subdirs, files in os.walk(unzips_path):
+            for item in files:
+                item_path = os.path.join(path, item)
+                if not 'G_' in item and not 'D_' in item and item.endswith('.pth'):
+                    model_file = True
+                    model_name = item.replace(".pth","")
+                    logs_dir = os.path.join(parent_path,'logs', model_name)
+                    if os.path.exists(logs_dir):
+                        shutil.rmtree(logs_dir)
+                    os.mkdir(logs_dir)
+                    if not os.path.exists(weights_path):
+                        os.mkdir(weights_path)
+                    if os.path.exists(os.path.join(weights_path, item)):
+                        os.remove(os.path.join(weights_path, item))
+                    if os.path.exists(item_path):
+                        shutil.move(item_path, weights_path)
+        
+        if not model_file and not os.path.exists(logs_dir):
+            os.mkdir(logs_dir)
+        for path, subdirs, files in os.walk(unzips_path):
+            for item in files:
+                item_path = os.path.join(path, item)
+                if item.startswith('added_') and item.endswith('.index'):
+                    index_file = True
+                    if os.path.exists(item_path):
+                        if os.path.exists(os.path.join(logs_dir, item)):
+                            os.remove(os.path.join(logs_dir, item))
+                        shutil.move(item_path, logs_dir)
+                if item.startswith('total_fea.npy') or item.startswith('events.'):
+                    if os.path.exists(item_path):
+                        if os.path.exists(os.path.join(logs_dir, item)):
+                            os.remove(os.path.join(logs_dir, item))
+                        shutil.move(item_path, logs_dir)
+        
+                
+        result = ""
+        if model_file:
+            if index_file:
+                print(i18n("The model works for inference, and has the .index file."))
+                infos.append("\n" + i18n("The model works for inference, and has the .index file."))
+                yield "\n".join(infos)
+            else:
+                print(i18n("The model works for inference, but it doesn't have the .index file."))
+                infos.append("\n" + i18n("The model works for inference, but it doesn't have the .index file."))
+                yield "\n".join(infos)
+        
+        if not index_file and not model_file:
+            print(i18n("No relevant file was found to upload."))
+            infos.append(i18n("No relevant file was found to upload."))
+            yield "\n".join(infos)
+        
+        if os.path.exists(zips_path):
+            shutil.rmtree(zips_path)
+        if os.path.exists(unzips_path):
+            shutil.rmtree(unzips_path)
+        os.chdir(parent_path)    
+        return result
+    except Exception as e:
+        os.chdir(parent_path)
+        if "too much use" in str(e):
+            print(i18n("Too many users have recently viewed or downloaded this file"))
+            yield i18n("Too many users have recently viewed or downloaded this file")
+        elif "private link" in str(e):
+            print(i18n("Cannot get file from this private link"))
+            yield i18n("Cannot get file from this private link")
+        else:
+            print(e)
+            yield i18n("An error occurred downloading")
+    finally:
+        os.chdir(parent_path)
+      
+def load_dowloaded_dataset(url):
+    parent_path = find_folder_parent(".", "pretrained_v2")
+    infos = []
+    try:
+        zips_path = os.path.join(parent_path, 'zips')
+        unzips_path = os.path.join(parent_path, 'unzips')
+        datasets_path = os.path.join(parent_path, 'datasets')
+        audio_extenions =['wav', 'mp3', 'flac', 'ogg', 'opus',
+                'm4a', 'mp4', 'aac', 'alac', 'wma',
+                'aiff', 'webm', 'ac3']
+        
+        if os.path.exists(zips_path):
+            shutil.rmtree(zips_path)
+        if os.path.exists(unzips_path):
+            shutil.rmtree(unzips_path)
+            
+        if not os.path.exists(datasets_path):
+            os.mkdir(datasets_path)
+            
+        os.mkdir(zips_path)
+        os.mkdir(unzips_path)
+        
+        download_file = download_from_url(url)
+        
+        if not download_file:
+            print(i18n("An error occurred downloading"))
+            infos.append(i18n("An error occurred downloading"))
+            yield "\n".join(infos)
+            raise Exception(i18n("An error occurred downloading"))
+        elif download_file == "downloaded":
+            print(i18n("It has been downloaded successfully."))
+            infos.append(i18n("It has been downloaded successfully."))
+            yield "\n".join(infos)
+        elif download_file == "too much use":
+            raise Exception(i18n("Too many users have recently viewed or downloaded this file"))
+        elif download_file == "private link":
+            raise Exception(i18n("Cannot get file from this private link"))
+  
+        zip_path = os.listdir(zips_path)
+        foldername = ""
+        for file in zip_path:
+            if file.endswith('.zip'):
+                file_path = os.path.join(zips_path, file)
+                print("....")
+                foldername = file.replace(".zip","").replace(" ","").replace("-","_")
+                dataset_path = os.path.join(datasets_path, foldername)
+                print(i18n("Proceeding with the extraction..."))
+                infos.append(i18n("Proceeding with the extraction..."))
+                yield "\n".join(infos)
+                shutil.unpack_archive(file_path, unzips_path, 'zip')
+                if os.path.exists(dataset_path):
+                    shutil.rmtree(dataset_path)
+                    
+                os.mkdir(dataset_path)
+                
+                for root, subfolders, songs in os.walk(unzips_path):
+                    for song in songs:
+                        song_path = os.path.join(root, song)
+                        if song.endswith(tuple(audio_extenions)):
+                            formatted_song_name = format_title(os.path.splitext(song)[0])
+                            extension = os.path.splitext(song)[1]
+                            new_song_path = os.path.join(dataset_path, f"{formatted_song_name}{extension}")
+                            shutil.move(song_path, new_song_path)
+            else:
+                print(i18n("Unzip error."))
+                infos.append(i18n("Unzip error."))
+                yield "\n".join(infos)
+                
+                
+
+        if os.path.exists(zips_path):
+            shutil.rmtree(zips_path)
+        if os.path.exists(unzips_path):
+            shutil.rmtree(unzips_path)
+            
+        print(i18n("The Dataset has been loaded successfully."))
+        infos.append(i18n("The Dataset has been loaded successfully."))
+        yield "\n".join(infos)
+    except Exception as e:
+        os.chdir(parent_path)
+        if "too much use" in str(e):
+            print(i18n("Too many users have recently viewed or downloaded this file"))
+            yield i18n("Too many users have recently viewed or downloaded this file")   
+        elif "private link" in str(e):
+            print(i18n("Cannot get file from this private link"))
+            yield i18n("Cannot get file from this private link")
+        else:
+            print(e)
+            yield i18n("An error occurred downloading")
+    finally:
+        os.chdir(parent_path)
+
+def save_model(modelname, save_action):
+       
+    parent_path = find_folder_parent(".", "pretrained_v2")
+    zips_path = os.path.join(parent_path, 'zips')
+    dst = os.path.join(zips_path,modelname)
+    logs_path = os.path.join(parent_path, 'logs', modelname)
+    weights_path = os.path.join(parent_path, 'weights', f"{modelname}.pth")
+    save_folder = parent_path
+    infos = []    
+    
+    try:
+        if not os.path.exists(logs_path):
+            raise Exception("No model found.")
+        
+        if not 'content' in parent_path:
+            save_folder = os.path.join(parent_path, 'RVC_Backup')
+        else:
+            save_folder = '/content/drive/MyDrive/RVC_Backup'
+        
+        infos.append(i18n("Save model"))
+        yield "\n".join(infos)
+        
+        if not os.path.exists(save_folder):
+            os.mkdir(save_folder)
+        if not os.path.exists(os.path.join(save_folder, 'ManualTrainingBackup')):
+            os.mkdir(os.path.join(save_folder, 'ManualTrainingBackup'))
+        if not os.path.exists(os.path.join(save_folder, 'Finished')):
+            os.mkdir(os.path.join(save_folder, 'Finished'))
+
+        if os.path.exists(zips_path):
+            shutil.rmtree(zips_path)
+            
+        os.mkdir(zips_path)
+        added_file = glob.glob(os.path.join(logs_path, "added_*.index"))
+        d_file = glob.glob(os.path.join(logs_path, "D_*.pth"))
+        g_file = glob.glob(os.path.join(logs_path, "G_*.pth"))
+        
+        if save_action == i18n("Choose the method"):
+            raise Exception("No method choosen.")
+        
+        if save_action == i18n("Save all"):
+            print(i18n("Save all"))
+            save_folder = os.path.join(save_folder, 'ManualTrainingBackup')
+            shutil.copytree(logs_path, dst)
+        else:
+            if not os.path.exists(dst):
+                os.mkdir(dst)
+            
+        if save_action == i18n("Save D and G"):
+            print(i18n("Save D and G"))
+            save_folder = os.path.join(save_folder, 'ManualTrainingBackup')
+            if len(d_file) > 0:
+                shutil.copy(d_file[0], dst)
+            if len(g_file) > 0:
+                shutil.copy(g_file[0], dst)    
+                
+            if len(added_file) > 0:
+                shutil.copy(added_file[0], dst)
+            else:
+                infos.append(i18n("Saved without index..."))
+                
+        if save_action == i18n("Save voice"):
+            print(i18n("Save voice"))
+            save_folder = os.path.join(save_folder, 'Finished')
+            if len(added_file) > 0:
+                shutil.copy(added_file[0], dst)
+            else:
+                infos.append(i18n("Saved without index..."))
+        
+        yield "\n".join(infos)
+        if not os.path.exists(weights_path):
+            infos.append(i18n("Saved without inference model..."))
+        else:
+            shutil.copy(weights_path, dst)
+        
+        yield "\n".join(infos)
+        infos.append("\n" + i18n("This may take a few minutes, please wait..."))
+        yield "\n".join(infos)
+        
+        shutil.make_archive(os.path.join(zips_path,f"{modelname}"), 'zip', zips_path)
+        shutil.move(os.path.join(zips_path,f"{modelname}.zip"), os.path.join(save_folder, f'{modelname}.zip'))
+        
+        shutil.rmtree(zips_path)        
+        infos.append("\n" + i18n("Model saved successfully"))
+        yield "\n".join(infos)
+        
+    except Exception as e:
+        print(e)
+        if "No model found." in str(e):
+            infos.append(i18n("The model you want to save does not exist, be sure to enter the correct name."))
+        else:
+            infos.append(i18n("An error occurred saving the model"))
+            
+        yield "\n".join(infos)
+    
+def load_downloaded_backup(url):
+    parent_path = find_folder_parent(".", "pretrained_v2")
+    try:
+        infos = []
+        logs_folders = ['0_gt_wavs','1_16k_wavs','2a_f0','2b-f0nsf','3_feature256','3_feature768']
+        zips_path = os.path.join(parent_path, 'zips')
+        unzips_path = os.path.join(parent_path, 'unzips')
+        weights_path = os.path.join(parent_path, 'weights')
+        logs_dir = os.path.join(parent_path, 'logs')
+        
+        if os.path.exists(zips_path):
+            shutil.rmtree(zips_path)
+        if os.path.exists(unzips_path):
+            shutil.rmtree(unzips_path)
+
+        os.mkdir(zips_path)
+        os.mkdir(unzips_path)
+        
+        download_file = download_from_url(url)
+        if not download_file:
+            print(i18n("The file could not be downloaded."))
+            infos.append(i18n("The file could not be downloaded."))
+            yield "\n".join(infos)
+        elif download_file == "downloaded":
+            print(i18n("It has been downloaded successfully."))
+            infos.append(i18n("It has been downloaded successfully."))
+            yield "\n".join(infos)
+        elif download_file == "too much use":
+            raise Exception(i18n("Too many users have recently viewed or downloaded this file"))
+        elif download_file == "private link":
+            raise Exception(i18n("Cannot get file from this private link"))
+        
+        for filename in os.listdir(zips_path):
+            if filename.endswith(".zip"):
+                zipfile_path = os.path.join(zips_path,filename)
+                zip_dir_name = os.path.splitext(filename)[0]
+                unzip_dir = unzips_path
+                print(i18n("Proceeding with the extraction..."))
+                infos.append(i18n("Proceeding with the extraction..."))
+                shutil.unpack_archive(zipfile_path, unzip_dir, 'zip')
+                
+                if os.path.exists(os.path.join(unzip_dir, zip_dir_name)):
+                    shutil.move(os.path.join(unzip_dir, zip_dir_name), logs_dir)
+                else:
+                    new_folder_path = os.path.join(logs_dir, zip_dir_name)
+                    os.mkdir(new_folder_path)
+                    for item_name in os.listdir(unzip_dir):
+                        item_path = os.path.join(unzip_dir, item_name)
+                        if os.path.isfile(item_path):
+                            shutil.move(item_path, new_folder_path)
+                        elif os.path.isdir(item_path):
+                            shutil.move(item_path, new_folder_path)
+                    
+                yield "\n".join(infos)
+            else:
+                print(i18n("Unzip error."))
+                infos.append(i18n("Unzip error."))
+                yield "\n".join(infos)
+                
+        result = ""
+        
+        for filename in os.listdir(unzips_path):
+            if filename.endswith(".zip"):
+                silentremove(filename)
+        
+        if os.path.exists(zips_path):
+            shutil.rmtree(zips_path)
+        if os.path.exists(os.path.join(parent_path, 'unzips')):
+            shutil.rmtree(os.path.join(parent_path, 'unzips'))
+        print(i18n("The Backup has been uploaded successfully."))
+        infos.append("\n" + i18n("The Backup has been uploaded successfully."))
+        yield "\n".join(infos)
+        os.chdir(parent_path)    
+        return result
+    except Exception as e:
+        os.chdir(parent_path)
+        if "too much use" in str(e):
+            print(i18n("Too many users have recently viewed or downloaded this file"))
+            yield i18n("Too many users have recently viewed or downloaded this file")
+        elif "private link" in str(e):
+            print(i18n("Cannot get file from this private link"))
+            yield i18n("Cannot get file from this private link") 
+        else:
+            print(e)
+            yield i18n("An error occurred downloading")
+    finally:
+        os.chdir(parent_path)
+
+def save_to_wav(record_button):
+    if record_button is None:
+        pass
+    else:
+        path_to_file=record_button
+        new_name = datetime.datetime.now().strftime("%Y-%m-%d_%H-%M-%S")+'.wav'
+        new_path='./audios/'+new_name
+        shutil.move(path_to_file,new_path)
+        return new_name
+
+
+def change_choices2():
+    audio_paths=[]
+    for filename in os.listdir("./audios"):
+        if filename.endswith(('wav', 'mp3', 'flac', 'ogg', 'opus',
+                'm4a', 'mp4', 'aac', 'alac', 'wma',
+                'aiff', 'webm', 'ac3')):
+            audio_paths.append(os.path.join('./audios',filename).replace('\\', '/'))
+    return {"choices": sorted(audio_paths), "__type__": "update"}, {"__type__": "update"}
+
+
+
+
+
+def uvr(input_url, output_path, model_name, inp_root, save_root_vocal, paths, save_root_ins, agg, format0, architecture):
+    carpeta_a_eliminar = "yt_downloads"
+    if os.path.exists(carpeta_a_eliminar) and os.path.isdir(carpeta_a_eliminar):
+        for archivo in os.listdir(carpeta_a_eliminar):
+            ruta_archivo = os.path.join(carpeta_a_eliminar, archivo)
+            if os.path.isfile(ruta_archivo):
+                os.remove(ruta_archivo)
+            elif os.path.isdir(ruta_archivo):
+                shutil.rmtree(ruta_archivo) 
+      
+    
+
+    ydl_opts = {
+     'no-windows-filenames': True,
+     'restrict-filenames': True,
+     'extract_audio': True,
+     'format': 'bestaudio',
+     'quiet': True,
+     'no-warnings': True,
+     }
+    
+    try:
+        print(i18n("Downloading audio from the video..."))
+        with yt_dlp.YoutubeDL(ydl_opts) as ydl:
+         info_dict = ydl.extract_info(input_url, download=False)
+         formatted_title = format_title(info_dict.get('title', 'default_title'))
+         formatted_outtmpl = output_path + '/' + formatted_title + '.wav'
+         ydl_opts['outtmpl'] = formatted_outtmpl
+         ydl = yt_dlp.YoutubeDL(ydl_opts)
+         ydl.download([input_url])
+        print(i18n("Audio downloaded!"))
+    except Exception as error:
+        print(i18n("An error occurred:"), error)
+
+    actual_directory = os.path.dirname(__file__)
+    
+    vocal_directory = os.path.join(actual_directory, save_root_vocal)
+    instrumental_directory = os.path.join(actual_directory, save_root_ins)
+    
+    vocal_formatted = f"vocal_{formatted_title}.wav.reformatted.wav_10.wav"
+    instrumental_formatted = f"instrument_{formatted_title}.wav.reformatted.wav_10.wav"  
+    
+    vocal_audio_path = os.path.join(vocal_directory, vocal_formatted)
+    instrumental_audio_path = os.path.join(instrumental_directory, instrumental_formatted)
+    
+    vocal_formatted_mdx = f"{formatted_title}_vocal_.wav"
+    instrumental_formatted_mdx = f"{formatted_title}_instrument_.wav"
+    
+    vocal_audio_path_mdx = os.path.join(vocal_directory, vocal_formatted_mdx)
+    instrumental_audio_path_mdx = os.path.join(instrumental_directory, instrumental_formatted_mdx)
+
+    if architecture == "VR":
+       try:
+           print(i18n("Starting audio conversion... (This might take a moment)"))
+           inp_root, save_root_vocal, save_root_ins = [x.strip(" ").strip('"').strip("\n").strip('"').strip(" ") for x in [inp_root, save_root_vocal, save_root_ins]]
+           usable_files = [os.path.join(inp_root, file) 
+                          for file in os.listdir(inp_root) 
+                          if file.endswith(tuple(sup_audioext))]    
+           
+        
+           pre_fun = MDXNetDereverb(15) if model_name == "onnx_dereverb_By_FoxJoy" else (_audio_pre_ if "DeEcho" not in model_name else _audio_pre_new)(
+                       agg=int(agg),
+                       model_path=os.path.join(weight_uvr5_root, model_name + ".pth"),
+                       device=config.device,
+                       is_half=config.is_half,
+                   )
+                
+           try:
+              if paths != None:
+                paths = [path.name for path in paths]
+              else:
+                paths = usable_files
+                
+           except:
+                traceback.print_exc()
+                paths = usable_files
+           print(paths) 
+           for path in paths:
+               inp_path = os.path.join(inp_root, path)
+               need_reformat, done = 1, 0
+
+               try:
+                   info = ffmpeg.probe(inp_path, cmd="ffprobe")
+                   if info["streams"][0]["channels"] == 2 and info["streams"][0]["sample_rate"] == "44100":
+                       need_reformat = 0
+                       pre_fun._path_audio_(inp_path, save_root_ins, save_root_vocal, format0)
+                       done = 1
+               except:
+                   traceback.print_exc()
+
+               if need_reformat:
+                   tmp_path = f"{tmp}/{os.path.basename(inp_path)}.reformatted.wav"
+                   os.system(f"ffmpeg -i {inp_path} -vn -acodec pcm_s16le -ac 2 -ar 44100 {tmp_path} -y")
+                   inp_path = tmp_path
+
+               try:
+                   if not done:
+                       pre_fun._path_audio_(inp_path, save_root_ins, save_root_vocal, format0)
+                   print(f"{os.path.basename(inp_path)}->Success")
+               except:
+                   print(f"{os.path.basename(inp_path)}->{traceback.format_exc()}")
+       except:
+           traceback.print_exc()
+       finally:
+           try:
+               if model_name == "onnx_dereverb_By_FoxJoy":
+                   del pre_fun.pred.model
+                   del pre_fun.pred.model_
+               else:
+                   del pre_fun.model
+
+               del pre_fun
+               return i18n("Finished"), vocal_audio_path, instrumental_audio_path
+           except: traceback.print_exc()
+
+           if torch.cuda.is_available(): torch.cuda.empty_cache()
+
+    elif architecture == "MDX":
+       try:
+           print(i18n("Starting audio conversion... (This might take a moment)"))
+           inp_root, save_root_vocal, save_root_ins = [x.strip(" ").strip('"').strip("\n").strip('"').strip(" ") for x in [inp_root, save_root_vocal, save_root_ins]]
+        
+           usable_files = [os.path.join(inp_root, file) 
+                          for file in os.listdir(inp_root) 
+                          if file.endswith(tuple(sup_audioext))]    
+           try:
+              if paths != None:
+                paths = [path.name for path in paths]
+              else:
+                paths = usable_files
+                
+           except:
+                traceback.print_exc()
+                paths = usable_files
+           print(paths) 
+           invert=True
+           denoise=True
+           use_custom_parameter=True
+           dim_f=2048
+           dim_t=256
+           n_fft=7680
+           use_custom_compensation=True
+           compensation=1.025
+           suffix = "vocal_" #@param ["Vocals", "Drums", "Bass", "Other"]{allow-input: true}
+           suffix_invert = "instrument_" #@param ["Instrumental", "Drumless", "Bassless", "Instruments"]{allow-input: true}
+           print_settings = True  # @param{type:"boolean"}
+           onnx = id_to_ptm(model_name)
+           compensation = compensation if use_custom_compensation or use_custom_parameter else None
+           mdx_model = prepare_mdx(onnx,use_custom_parameter, dim_f, dim_t, n_fft, compensation=compensation)
+           
+       
+           for path in paths:
+               #inp_path = os.path.join(inp_root, path)
+               suffix_naming = suffix if use_custom_parameter else None
+               diff_suffix_naming = suffix_invert if use_custom_parameter else None
+               run_mdx(onnx, mdx_model, path, format0, diff=invert,suffix=suffix_naming,diff_suffix=diff_suffix_naming,denoise=denoise)
+    
+           if print_settings:
+               print()
+               print('[MDX-Net_Colab settings used]')
+               print(f'Model used: {onnx}')
+               print(f'Model MD5: {mdx.MDX.get_hash(onnx)}')
+               print(f'Model parameters:')
+               print(f'    -dim_f: {mdx_model.dim_f}')
+               print(f'    -dim_t: {mdx_model.dim_t}')
+               print(f'    -n_fft: {mdx_model.n_fft}')
+               print(f'    -compensation: {mdx_model.compensation}')
+               print()
+               print('[Input file]')
+               print('filename(s): ')
+               for filename in paths:
+                   print(f'    -{filename}')
+                   print(f"{os.path.basename(filename)}->Success")
+       except:
+           traceback.print_exc()
+       finally:
+           try:
+               del mdx_model
+               return i18n("Finished"), vocal_audio_path_mdx, instrumental_audio_path_mdx
+           except: traceback.print_exc()
+
+           print("clean_empty_cache")
+
+           if torch.cuda.is_available(): torch.cuda.empty_cache()
+sup_audioext = {'wav', 'mp3', 'flac', 'ogg', 'opus',
+                'm4a', 'mp4', 'aac', 'alac', 'wma',
+                'aiff', 'webm', 'ac3'}
+
+def load_downloaded_audio(url):
+    parent_path = find_folder_parent(".", "pretrained_v2")
+    try:
+        infos = []
+        audios_path = os.path.join(parent_path, 'audios')
+        zips_path = os.path.join(parent_path, 'zips')
+
+        if not os.path.exists(audios_path):
+            os.mkdir(audios_path)
+        
+        download_file = download_from_url(url)
+        if not download_file:
+            print(i18n("The file could not be downloaded."))
+            infos.append(i18n("The file could not be downloaded."))
+            yield "\n".join(infos)
+        elif download_file == "downloaded":
+            print(i18n("It has been downloaded successfully."))
+            infos.append(i18n("It has been downloaded successfully."))
+            yield "\n".join(infos)
+        elif download_file == "too much use":
+            raise Exception(i18n("Too many users have recently viewed or downloaded this file"))
+        elif download_file == "private link":
+            raise Exception(i18n("Cannot get file from this private link"))
+        
+        for filename in os.listdir(zips_path):
+            item_path = os.path.join(zips_path, filename)
+            if item_path.split('.')[-1] in sup_audioext:
+                if os.path.exists(item_path):
+                    shutil.move(item_path, audios_path)
+        
+        result = ""
+        print(i18n("Audio files have been moved to the 'audios' folder."))
+        infos.append(i18n("Audio files have been moved to the 'audios' folder."))
+        yield "\n".join(infos)
+            
+        os.chdir(parent_path)    
+        return result
+    except Exception as e:
+        os.chdir(parent_path)
+        if "too much use" in str(e):
+            print(i18n("Too many users have recently viewed or downloaded this file"))
+            yield i18n("Too many users have recently viewed or downloaded this file")
+        elif "private link" in str(e):
+            print(i18n("Cannot get file from this private link"))
+            yield i18n("Cannot get file from this private link")
+        else:
+            print(e)
+            yield i18n("An error occurred downloading")
+    finally:
+        os.chdir(parent_path)
+ 
+       
+class error_message(Exception):
+    def __init__(self, mensaje):
+        self.mensaje = mensaje
+        super().__init__(mensaje)
+
+def get_vc(sid, to_return_protect0, to_return_protect1):
+    global n_spk, tgt_sr, net_g, vc, cpt, version
+    if sid == "" or sid == []:
+        global hubert_model
+        if hubert_model is not None: 
+            print("clean_empty_cache")
+            del net_g, n_spk, vc, hubert_model, tgt_sr  
+            hubert_model = net_g = n_spk = vc = hubert_model = tgt_sr = None
+            if torch.cuda.is_available():
+                torch.cuda.empty_cache()
+            if_f0 = cpt.get("f0", 1)
+            version = cpt.get("version", "v1")
+            if version == "v1":
+                if if_f0 == 1:
+                    net_g = SynthesizerTrnMs256NSFsid(
+                        *cpt["config"], is_half=config.is_half
+                    )
+                else:
+                    net_g = SynthesizerTrnMs256NSFsid_nono(*cpt["config"])
+            elif version == "v2":
+                if if_f0 == 1:
+                    net_g = SynthesizerTrnMs768NSFsid(
+                        *cpt["config"], is_half=config.is_half
+                    )
+                else:
+                    net_g = SynthesizerTrnMs768NSFsid_nono(*cpt["config"])
+            del net_g, cpt
+            if torch.cuda.is_available():
+                torch.cuda.empty_cache()
+            cpt = None
+        return (
+            {"visible": False, "__type__": "update"},
+            {"visible": False, "__type__": "update"},
+            {"visible": False, "__type__": "update"},
+        )
+    person = "%s/%s" % (weight_root, sid)
+    print("loading %s" % person)
+    cpt = torch.load(person, map_location="cpu")
+    tgt_sr = cpt["config"][-1]
+    cpt["config"][-3] = cpt["weight"]["emb_g.weight"].shape[0]  
+    if_f0 = cpt.get("f0", 1)
+    if if_f0 == 0:
+        to_return_protect0 = to_return_protect1 = {
+            "visible": False,
+            "value": 0.5,
+            "__type__": "update",
+        }
+    else:
+        to_return_protect0 = {
+            "visible": True,
+            "value": to_return_protect0,
+            "__type__": "update",
+        }
+        to_return_protect1 = {
+            "visible": True,
+            "value": to_return_protect1,
+            "__type__": "update",
+        }
+    version = cpt.get("version", "v1")
+    if version == "v1":
+        if if_f0 == 1:
+            net_g = SynthesizerTrnMs256NSFsid(*cpt["config"], is_half=config.is_half)
+        else:
+            net_g = SynthesizerTrnMs256NSFsid_nono(*cpt["config"])
+    elif version == "v2":
+        if if_f0 == 1:
+            net_g = SynthesizerTrnMs768NSFsid(*cpt["config"], is_half=config.is_half)
+        else:
+            net_g = SynthesizerTrnMs768NSFsid_nono(*cpt["config"])
+    del net_g.enc_q
+    print(net_g.load_state_dict(cpt["weight"], strict=False))
+    net_g.eval().to(config.device)
+    if config.is_half:
+        net_g = net_g.half()
+    else:
+        net_g = net_g.float()
+    vc = VC(tgt_sr, config)
+    n_spk = cpt["config"][-3]
+    return (
+        {"visible": True, "maximum": n_spk, "__type__": "update"},
+        to_return_protect0,
+        to_return_protect1,
+    )    
+    
+def update_model_choices(select_value):
+    model_ids = get_model_list()
+    model_ids_list = list(model_ids)
+    if select_value == "VR":
+        return {"choices": uvr5_names, "__type__": "update"}
+    elif select_value == "MDX":
+        return {"choices": model_ids_list, "__type__": "update"}
+
+def download_model():
+    gr.Markdown(value="# " + i18n("Download Model"))
+    gr.Markdown(value=i18n("It is used to download your inference models."))
+    with gr.Row():
+        model_url=gr.Textbox(label=i18n("Url:"))
+    with gr.Row():
+        download_model_status_bar=gr.Textbox(label=i18n("Status:"))
+    with gr.Row():
+        download_button=gr.Button(i18n("Download"))
+        download_button.click(fn=load_downloaded_model, inputs=[model_url], outputs=[download_model_status_bar])
+
+def download_backup():
+    gr.Markdown(value="# " + i18n("Download Backup"))
+    gr.Markdown(value=i18n("It is used to download your training backups."))
+    with gr.Row():
+        model_url=gr.Textbox(label=i18n("Url:"))
+    with gr.Row():
+        download_model_status_bar=gr.Textbox(label=i18n("Status:"))
+    with gr.Row():
+        download_button=gr.Button(i18n("Download"))
+        download_button.click(fn=load_downloaded_backup, inputs=[model_url], outputs=[download_model_status_bar])
+
+def update_dataset_list(name):
+    new_datasets = []
+    for foldername in os.listdir("./datasets"):
+        if "." not in foldername:
+            new_datasets.append(os.path.join(find_folder_parent(".","pretrained"),"datasets",foldername))
+    return gr.Dropdown.update(choices=new_datasets)
+
+def download_dataset(trainset_dir4):
+    gr.Markdown(value="# " + i18n("Download Dataset"))
+    gr.Markdown(value=i18n("Download the dataset with the audios in a compatible format (.wav/.flac) to train your model."))
+    with gr.Row():
+        dataset_url=gr.Textbox(label=i18n("Url:"))
+    with gr.Row():
+        load_dataset_status_bar=gr.Textbox(label=i18n("Status:"))
+    with gr.Row():
+        load_dataset_button=gr.Button(i18n("Download"))
+        load_dataset_button.click(fn=load_dowloaded_dataset, inputs=[dataset_url], outputs=[load_dataset_status_bar])
+        load_dataset_status_bar.change(update_dataset_list, dataset_url, trainset_dir4)
+
+def download_audio():
+    gr.Markdown(value="# " + i18n("Download Audio"))
+    gr.Markdown(value=i18n("Download audios of any format for use in inference (recommended for mobile users)."))
+    with gr.Row():
+        audio_url=gr.Textbox(label=i18n("Url:"))
+    with gr.Row():
+        download_audio_status_bar=gr.Textbox(label=i18n("Status:"))
+    with gr.Row():
+        download_button2=gr.Button(i18n("Download"))
+        download_button2.click(fn=load_downloaded_audio, inputs=[audio_url], outputs=[download_audio_status_bar])
+
+def youtube_separator():
+        gr.Markdown(value="# " + i18n("Separate YouTube tracks"))
+        gr.Markdown(value=i18n("Download audio from a YouTube video and automatically separate the vocal and instrumental tracks"))
+        with gr.Row():
+            input_url = gr.inputs.Textbox(label=i18n("Enter the YouTube link:"))
+            output_path = gr.Textbox(
+                label=i18n("Enter the path of the audio folder to be processed (copy it from the address bar of the file manager):"),
+                value=os.path.abspath(os.getcwd()).replace('\\', '/') + "/yt_downloads",
+                visible=False,
+                )
+            advanced_settings_checkbox = gr.Checkbox(
+                value=False,
+                label=i18n("Advanced Settings"),
+                interactive=True,
+                )
+        with gr.Row(label = i18n("Advanced Settings"), visible=False, variant='compact') as advanced_settings:
+            with gr.Column(): 
+                model_select = gr.Radio(
+                    label=i18n("Model Architecture:"),
+                    choices=["VR", "MDX"],
+                    value="VR",
+                    interactive=True,
+                    )
+                model_choose = gr.Dropdown(label=i18n("Model: (Be aware that in some models the named vocal will be the instrumental)"),                          
+                    choices=uvr5_names,
+                    value="HP5_only_main_vocal"   
+                    )
+                with gr.Row():
+                    agg = gr.Slider(
+                        minimum=0,
+                        maximum=20,
+                        step=1,
+                        label=i18n("Vocal Extraction Aggressive"),
+                        value=10,
+                        interactive=True,
+                        )
+                with gr.Row():            
+                    opt_vocal_root = gr.Textbox(
+                        label=i18n("Specify the output folder for vocals:"), value="audios",
+                        )
+                opt_ins_root = gr.Textbox(
+                    label=i18n("Specify the output folder for accompaniment:"), value="audio-others",
+                    ) 
+                dir_wav_input = gr.Textbox(
+                    label=i18n("Enter the path of the audio folder to be processed:"),
+                    value=((os.getcwd()).replace('\\', '/') + "/yt_downloads"),
+                    visible=False,
+                    )
+                format0 = gr.Radio(
+                    label=i18n("Export file format"),
+                    choices=["wav", "flac", "mp3", "m4a"],
+                    value="wav",
+                    visible=False,
+                    interactive=True,
+                    )
+                wav_inputs = gr.File(
+                    file_count="multiple", label=i18n("You can also input audio files in batches. Choose one of the two options. Priority is given to reading from the folder."),
+                    visible=False,
+                    )
+            model_select.change(
+                fn=update_model_choices,
+                inputs=model_select,
+                outputs=model_choose,
+                )
+        with gr.Row():
+            vc_output4 = gr.Textbox(label=i18n("Status:"))
+            vc_output5 = gr.Audio(label=i18n("Vocal"), type='filepath')
+            vc_output6 = gr.Audio(label=i18n("Instrumental"), type='filepath')
+        with gr.Row():
+            but2 = gr.Button(i18n("Download and Separate"))
+            but2.click(
+                uvr,
+                    [
+                    input_url, 
+                    output_path,
+                    model_choose,
+                    dir_wav_input,
+                    opt_vocal_root,
+                    wav_inputs,
+                    opt_ins_root,
+                    agg,
+                    format0,
+                    model_select
+                    ],
+                    [vc_output4, vc_output5, vc_output6],
+                )
+        def toggle_advanced_settings(checkbox):
+            return {"visible": checkbox, "__type__": "update"}
+        
+        advanced_settings_checkbox.change(
+            fn=toggle_advanced_settings,
+            inputs=[advanced_settings_checkbox],
+            outputs=[advanced_settings]
+            )
+
+
+def get_bark_voice():
+    mensaje = """
+v2/en_speaker_0	English	Male
+v2/en_speaker_1	English	Male
+v2/en_speaker_2	English	Male
+v2/en_speaker_3	English	Male
+v2/en_speaker_4	English	Male
+v2/en_speaker_5	English	Male
+v2/en_speaker_6	English	Male
+v2/en_speaker_7	English	Male
+v2/en_speaker_8	English	Male
+v2/en_speaker_9	English	Female
+v2/zh_speaker_0	Chinese (Simplified)	Male
+v2/zh_speaker_1	Chinese (Simplified)	Male
+v2/zh_speaker_2	Chinese (Simplified)	Male
+v2/zh_speaker_3	Chinese (Simplified)	Male
+v2/zh_speaker_4	Chinese (Simplified)	Female
+v2/zh_speaker_5	Chinese (Simplified)	Male
+v2/zh_speaker_6	Chinese (Simplified)	Female
+v2/zh_speaker_7	Chinese (Simplified)	Female
+v2/zh_speaker_8	Chinese (Simplified)	Male
+v2/zh_speaker_9	Chinese (Simplified)	Female
+v2/fr_speaker_0	French	Male
+v2/fr_speaker_1	French	Female
+v2/fr_speaker_2	French	Female
+v2/fr_speaker_3	French	Male
+v2/fr_speaker_4	French	Male
+v2/fr_speaker_5	French	Female
+v2/fr_speaker_6	French	Male
+v2/fr_speaker_7	French	Male
+v2/fr_speaker_8	French	Male
+v2/fr_speaker_9	French	Male
+v2/de_speaker_0	German	Male
+v2/de_speaker_1	German	Male
+v2/de_speaker_2	German	Male
+v2/de_speaker_3	German	Female
+v2/de_speaker_4	German	Male
+v2/de_speaker_5	German	Male
+v2/de_speaker_6	German	Male
+v2/de_speaker_7	German	Male
+v2/de_speaker_8	German	Female
+v2/de_speaker_9	German	Male
+v2/hi_speaker_0	Hindi	Female
+v2/hi_speaker_1	Hindi	Female
+v2/hi_speaker_2	Hindi	Male
+v2/hi_speaker_3	Hindi	Female
+v2/hi_speaker_4	Hindi	Female
+v2/hi_speaker_5	Hindi	Male
+v2/hi_speaker_6	Hindi	Male
+v2/hi_speaker_7	Hindi	Male
+v2/hi_speaker_8	Hindi	Male
+v2/hi_speaker_9	Hindi	Female
+v2/it_speaker_0	Italian	Male
+v2/it_speaker_1	Italian	Male
+v2/it_speaker_2	Italian	Female
+v2/it_speaker_3	Italian	Male
+v2/it_speaker_4	Italian	Male
+v2/it_speaker_5	Italian	Male
+v2/it_speaker_6	Italian	Male
+v2/it_speaker_7	Italian	Female
+v2/it_speaker_8	Italian	Male
+v2/it_speaker_9	Italian	Female
+v2/ja_speaker_0	Japanese	Female
+v2/ja_speaker_1	Japanese	Female
+v2/ja_speaker_2	Japanese	Male
+v2/ja_speaker_3	Japanese	Female
+v2/ja_speaker_4	Japanese	Female
+v2/ja_speaker_5	Japanese	Female
+v2/ja_speaker_6	Japanese	Male
+v2/ja_speaker_7	Japanese	Female
+v2/ja_speaker_8	Japanese	Female
+v2/ja_speaker_9	Japanese	Female
+v2/ko_speaker_0	Korean	Female
+v2/ko_speaker_1	Korean	Male
+v2/ko_speaker_2	Korean	Male
+v2/ko_speaker_3	Korean	Male
+v2/ko_speaker_4	Korean	Male
+v2/ko_speaker_5	Korean	Male
+v2/ko_speaker_6	Korean	Male
+v2/ko_speaker_7	Korean	Male
+v2/ko_speaker_8	Korean	Male
+v2/ko_speaker_9	Korean	Male
+v2/pl_speaker_0	Polish	Male
+v2/pl_speaker_1	Polish	Male
+v2/pl_speaker_2	Polish	Male
+v2/pl_speaker_3	Polish	Male
+v2/pl_speaker_4	Polish	Female
+v2/pl_speaker_5	Polish	Male
+v2/pl_speaker_6	Polish	Female
+v2/pl_speaker_7	Polish	Male
+v2/pl_speaker_8	Polish	Male
+v2/pl_speaker_9	Polish	Female
+v2/pt_speaker_0	Portuguese	Male
+v2/pt_speaker_1	Portuguese	Male
+v2/pt_speaker_2	Portuguese	Male
+v2/pt_speaker_3	Portuguese	Male
+v2/pt_speaker_4	Portuguese	Male
+v2/pt_speaker_5	Portuguese	Male
+v2/pt_speaker_6	Portuguese	Male
+v2/pt_speaker_7	Portuguese	Male
+v2/pt_speaker_8	Portuguese	Male
+v2/pt_speaker_9	Portuguese	Male
+v2/ru_speaker_0	Russian	Male
+v2/ru_speaker_1	Russian	Male
+v2/ru_speaker_2	Russian	Male
+v2/ru_speaker_3	Russian	Male
+v2/ru_speaker_4	Russian	Male
+v2/ru_speaker_5	Russian	Female
+v2/ru_speaker_6	Russian	Female
+v2/ru_speaker_7	Russian	Male
+v2/ru_speaker_8	Russian	Male
+v2/ru_speaker_9	Russian	Female
+v2/es_speaker_0	Spanish	Male
+v2/es_speaker_1	Spanish	Male
+v2/es_speaker_2	Spanish	Male
+v2/es_speaker_3	Spanish	Male
+v2/es_speaker_4	Spanish	Male
+v2/es_speaker_5	Spanish	Male
+v2/es_speaker_6	Spanish	Male
+v2/es_speaker_7	Spanish	Male
+v2/es_speaker_8	Spanish	Female
+v2/es_speaker_9	Spanish	Female
+v2/tr_speaker_0	Turkish	Male
+v2/tr_speaker_1	Turkish	Male
+v2/tr_speaker_2	Turkish	Male
+v2/tr_speaker_3	Turkish	Male
+v2/tr_speaker_4	Turkish	Female
+v2/tr_speaker_5	Turkish	Female
+v2/tr_speaker_6	Turkish	Male
+v2/tr_speaker_7	Turkish	Male
+v2/tr_speaker_8	Turkish	Male
+v2/tr_speaker_9	Turkish	Male
+    """
+# Dividir el mensaje en líneas
+    lineas = mensaje.split("\n")
+    datos_deseados = []
+    for linea in lineas:
+        partes = linea.split("\t")
+        if len(partes) == 3:
+            clave, _, genero = partes  
+            datos_deseados.append(f"{clave}-{genero}")
+
+    return datos_deseados
+
+    
+def get_edge_voice():
+    completed_process = subprocess.run(['edge-tts',"-l"], capture_output=True, text=True)
+    lines = completed_process.stdout.strip().split("\n")
+    data = []
+    current_entry = {}
+    for line in lines:
+        if line.startswith("Name: "):
+            if current_entry:
+                data.append(current_entry)
+            current_entry = {"Name": line.split(": ")[1]}
+        elif line.startswith("Gender: "):
+            current_entry["Gender"] = line.split(": ")[1]
+    if current_entry:
+        data.append(current_entry)
+    tts_voice = []
+    for entry in data:
+        name = entry["Name"]
+        gender = entry["Gender"]
+        formatted_entry = f'{name}-{gender}'
+        tts_voice.append(formatted_entry)
+    return tts_voice
+
+
+#print(set_tts_voice)
diff --git a/environment_dml.yaml b/environment_dml.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..0fb3f222554eb01acce5313bf81cee4179edf0af
--- /dev/null
+++ b/environment_dml.yaml
@@ -0,0 +1,186 @@
+name: pydml
+channels:
+  - pytorch
+  - https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
+  - https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/
+  - https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/
+  - https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge/
+  - defaults
+  - https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/fastai/
+  - https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/pytorch/
+  - https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/bioconda/
+dependencies:
+  - abseil-cpp=20211102.0=hd77b12b_0
+  - absl-py=1.3.0=py310haa95532_0
+  - aiohttp=3.8.3=py310h2bbff1b_0
+  - aiosignal=1.2.0=pyhd3eb1b0_0
+  - async-timeout=4.0.2=py310haa95532_0
+  - attrs=22.1.0=py310haa95532_0
+  - blas=1.0=mkl
+  - blinker=1.4=py310haa95532_0
+  - bottleneck=1.3.5=py310h9128911_0
+  - brotli=1.0.9=h2bbff1b_7
+  - brotli-bin=1.0.9=h2bbff1b_7
+  - brotlipy=0.7.0=py310h2bbff1b_1002
+  - bzip2=1.0.8=he774522_0
+  - c-ares=1.19.0=h2bbff1b_0
+  - ca-certificates=2023.05.30=haa95532_0
+  - cachetools=4.2.2=pyhd3eb1b0_0
+  - certifi=2023.5.7=py310haa95532_0
+  - cffi=1.15.1=py310h2bbff1b_3
+  - charset-normalizer=2.0.4=pyhd3eb1b0_0
+  - click=8.0.4=py310haa95532_0
+  - colorama=0.4.6=py310haa95532_0
+  - contourpy=1.0.5=py310h59b6b97_0
+  - cryptography=39.0.1=py310h21b164f_0
+  - cycler=0.11.0=pyhd3eb1b0_0
+  - fonttools=4.25.0=pyhd3eb1b0_0
+  - freetype=2.12.1=ha860e81_0
+  - frozenlist=1.3.3=py310h2bbff1b_0
+  - giflib=5.2.1=h8cc25b3_3
+  - glib=2.69.1=h5dc1a3c_2
+  - google-auth=2.6.0=pyhd3eb1b0_0
+  - google-auth-oauthlib=0.4.4=pyhd3eb1b0_0
+  - grpc-cpp=1.48.2=hf108199_0
+  - grpcio=1.48.2=py310hf108199_0
+  - gst-plugins-base=1.18.5=h9e645db_0
+  - gstreamer=1.18.5=hd78058f_0
+  - icu=58.2=ha925a31_3
+  - idna=3.4=py310haa95532_0
+  - intel-openmp=2023.1.0=h59b6b97_46319
+  - jpeg=9e=h2bbff1b_1
+  - kiwisolver=1.4.4=py310hd77b12b_0
+  - krb5=1.19.4=h5b6d351_0
+  - lerc=3.0=hd77b12b_0
+  - libbrotlicommon=1.0.9=h2bbff1b_7
+  - libbrotlidec=1.0.9=h2bbff1b_7
+  - libbrotlienc=1.0.9=h2bbff1b_7
+  - libclang=14.0.6=default_hb5a9fac_1
+  - libclang13=14.0.6=default_h8e68704_1
+  - libdeflate=1.17=h2bbff1b_0
+  - libffi=3.4.4=hd77b12b_0
+  - libiconv=1.16=h2bbff1b_2
+  - libogg=1.3.5=h2bbff1b_1
+  - libpng=1.6.39=h8cc25b3_0
+  - libprotobuf=3.20.3=h23ce68f_0
+  - libtiff=4.5.0=h6c2663c_2
+  - libuv=1.44.2=h2bbff1b_0
+  - libvorbis=1.3.7=he774522_0
+  - libwebp=1.2.4=hbc33d0d_1
+  - libwebp-base=1.2.4=h2bbff1b_1
+  - libxml2=2.10.3=h0ad7f3c_0
+  - libxslt=1.1.37=h2bbff1b_0
+  - lz4-c=1.9.4=h2bbff1b_0
+  - markdown=3.4.1=py310haa95532_0
+  - markupsafe=2.1.1=py310h2bbff1b_0
+  - matplotlib=3.7.1=py310haa95532_1
+  - matplotlib-base=3.7.1=py310h4ed8f06_1
+  - mkl=2023.1.0=h8bd8f75_46356
+  - mkl-service=2.4.0=py310h2bbff1b_1
+  - mkl_fft=1.3.6=py310h4ed8f06_1
+  - mkl_random=1.2.2=py310h4ed8f06_1
+  - multidict=6.0.2=py310h2bbff1b_0
+  - munkres=1.1.4=py_0
+  - numexpr=2.8.4=py310h2cd9be0_1
+  - numpy=1.24.3=py310h055cbcc_1
+  - numpy-base=1.24.3=py310h65a83cf_1
+  - oauthlib=3.2.2=py310haa95532_0
+  - openssl=1.1.1t=h2bbff1b_0
+  - packaging=23.0=py310haa95532_0
+  - pandas=1.5.3=py310h4ed8f06_0
+  - pcre=8.45=hd77b12b_0
+  - pillow=9.4.0=py310hd77b12b_0
+  - pip=23.0.1=py310haa95532_0
+  - ply=3.11=py310haa95532_0
+  - protobuf=3.20.3=py310hd77b12b_0
+  - pyasn1=0.4.8=pyhd3eb1b0_0
+  - pyasn1-modules=0.2.8=py_0
+  - pycparser=2.21=pyhd3eb1b0_0
+  - pyjwt=2.4.0=py310haa95532_0
+  - pyopenssl=23.0.0=py310haa95532_0
+  - pyparsing=3.0.9=py310haa95532_0
+  - pyqt=5.15.7=py310hd77b12b_0
+  - pyqt5-sip=12.11.0=py310hd77b12b_0
+  - pysocks=1.7.1=py310haa95532_0
+  - python=3.10.11=h966fe2a_2
+  - python-dateutil=2.8.2=pyhd3eb1b0_0
+  - pytorch-mutex=1.0=cpu
+  - pytz=2022.7=py310haa95532_0
+  - pyyaml=6.0=py310h2bbff1b_1
+  - qt-main=5.15.2=he8e5bd7_8
+  - qt-webengine=5.15.9=hb9a9bb5_5
+  - qtwebkit=5.212=h2bbfb41_5
+  - re2=2022.04.01=hd77b12b_0
+  - requests=2.29.0=py310haa95532_0
+  - requests-oauthlib=1.3.0=py_0
+  - rsa=4.7.2=pyhd3eb1b0_1
+  - setuptools=67.8.0=py310haa95532_0
+  - sip=6.6.2=py310hd77b12b_0
+  - six=1.16.0=pyhd3eb1b0_1
+  - sqlite=3.41.2=h2bbff1b_0
+  - tbb=2021.8.0=h59b6b97_0
+  - tensorboard=2.10.0=py310haa95532_0
+  - tensorboard-data-server=0.6.1=py310haa95532_0
+  - tensorboard-plugin-wit=1.8.1=py310haa95532_0
+  - tk=8.6.12=h2bbff1b_0
+  - toml=0.10.2=pyhd3eb1b0_0
+  - tornado=6.2=py310h2bbff1b_0
+  - tqdm=4.65.0=py310h9909e9c_0
+  - typing_extensions=4.5.0=py310haa95532_0
+  - tzdata=2023c=h04d1e81_0
+  - urllib3=1.26.16=py310haa95532_0
+  - vc=14.2=h21ff451_1
+  - vs2015_runtime=14.27.29016=h5e58377_2
+  - werkzeug=2.2.3=py310haa95532_0
+  - wheel=0.38.4=py310haa95532_0
+  - win_inet_pton=1.1.0=py310haa95532_0
+  - xz=5.4.2=h8cc25b3_0
+  - yaml=0.2.5=he774522_0
+  - yarl=1.8.1=py310h2bbff1b_0
+  - zlib=1.2.13=h8cc25b3_0
+  - zstd=1.5.5=hd43e919_0
+  - pip:
+      - antlr4-python3-runtime==4.8
+      - appdirs==1.4.4
+      - audioread==3.0.0
+      - bitarray==2.7.4
+      - cython==0.29.35
+      - decorator==5.1.1
+      - fairseq==0.12.2
+      - faiss-cpu==1.7.4
+      - filelock==3.12.0
+      - hydra-core==1.0.7
+      - jinja2==3.1.2
+      - joblib==1.2.0
+      - lazy-loader==0.2
+      - librosa==0.10.0.post2
+      - llvmlite==0.40.0
+      - lxml==4.9.2
+      - mpmath==1.3.0
+      - msgpack==1.0.5
+      - networkx==3.1
+      - noisereduce==2.0.1
+      - numba==0.57.0
+      - omegaconf==2.0.6
+      - opencv-python==4.7.0.72
+      - pooch==1.6.0
+      - portalocker==2.7.0
+      - pysimplegui==4.60.5
+      - pywin32==306
+      - pyworld==0.3.3
+      - regex==2023.5.5
+      - sacrebleu==2.3.1
+      - scikit-learn==1.2.2
+      - scipy==1.10.1
+      - sounddevice==0.4.6
+      - soundfile==0.12.1
+      - soxr==0.3.5
+      - sympy==1.12
+      - tabulate==0.9.0
+      - threadpoolctl==3.1.0
+      - torch==2.0.0
+      - torch-directml==0.2.0.dev230426
+      - torchaudio==2.0.1
+      - torchvision==0.15.1
+      - wget==3.2
+prefix: D:\ProgramData\anaconda3_\envs\pydml
diff --git a/extract_locale.py b/extract_locale.py
new file mode 100644
index 0000000000000000000000000000000000000000..a4ff5ea3ddd7c612c640544099ab98a861b8fe35
--- /dev/null
+++ b/extract_locale.py
@@ -0,0 +1,34 @@
+import json
+import re
+
+# Define regular expression patterns
+pattern = r"""i18n\([\s\n\t]*(["'][^"']+["'])[\s\n\t]*\)"""
+
+# Initialize the dictionary to store key-value pairs
+data = {}
+
+
+def process(fn: str):
+    global data
+    with open(fn, "r", encoding="utf-8") as f:
+        contents = f.read()
+        matches = re.findall(pattern, contents)
+        for key in matches:
+            key = eval(key)
+            print("extract:", key)
+            data[key] = key
+
+
+print("processing infer-web.py")
+process("infer-web.py")
+
+print("processing gui_v0.py")
+process("gui_v0.py")
+
+print("processing gui_v1.py")
+process("gui_v1.py")
+
+# Save as a JSON file
+with open("./i18n/en_US.json", "w", encoding="utf-8") as f:
+    json.dump(data, f, ensure_ascii=False, indent=4)
+    f.write("\n")
diff --git a/formantshiftcfg/Put your formantshift presets here as a txt file b/formantshiftcfg/Put your formantshift presets here as a txt file
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/formantshiftcfg/f2m.txt b/formantshiftcfg/f2m.txt
new file mode 100644
index 0000000000000000000000000000000000000000..40356a80ce7dd7a893bca233a41306525193f2f0
--- /dev/null
+++ b/formantshiftcfg/f2m.txt
@@ -0,0 +1,2 @@
+1.0
+0.8
\ No newline at end of file
diff --git a/formantshiftcfg/m2f.txt b/formantshiftcfg/m2f.txt
new file mode 100644
index 0000000000000000000000000000000000000000..fa69b52dc8e29db4697401ef2766dd0b6c6f4b47
--- /dev/null
+++ b/formantshiftcfg/m2f.txt
@@ -0,0 +1,2 @@
+1.0
+1.2
\ No newline at end of file
diff --git a/formantshiftcfg/random.txt b/formantshiftcfg/random.txt
new file mode 100644
index 0000000000000000000000000000000000000000..427be5c80412098ecec082b3a06e867ddc9a7ba2
--- /dev/null
+++ b/formantshiftcfg/random.txt
@@ -0,0 +1,2 @@
+32.0
+9.8
\ No newline at end of file
diff --git a/get-pip.py b/get-pip.py
new file mode 100644
index 0000000000000000000000000000000000000000..cf68a2b3426decf01bde021a50c47a2115af303a
--- /dev/null
+++ b/get-pip.py
@@ -0,0 +1,32657 @@
+#!/usr/bin/env python
+#
+# Hi There!
+#
+# You may be wondering what this giant blob of binary data here is, you might
+# even be worried that we're up to something nefarious (good for you for being
+# paranoid!). This is a base85 encoding of a zip file, this zip file contains
+# an entire copy of pip (version 23.2.1).
+#
+# Pip is a thing that installs packages, pip itself is a package that someone
+# might want to install, especially if they're looking to run this get-pip.py
+# script. Pip has a lot of code to deal with the security of installing
+# packages, various edge cases on various platforms, and other such sort of
+# "tribal knowledge" that has been encoded in its code base. Because of this
+# we basically include an entire copy of pip inside this blob. We do this
+# because the alternatives are attempt to implement a "minipip" that probably
+# doesn't do things correctly and has weird edge cases, or compress pip itself
+# down into a single file.
+#
+# If you're wondering how this is created, it is generated using
+# `scripts/generate.py` in https://github.com/pypa/get-pip.
+
+import sys
+
+this_python = sys.version_info[:2]
+min_version = (3, 7)
+if this_python < min_version:
+    message_parts = [
+        "This script does not work on Python {}.{}".format(*this_python),
+        "The minimum supported Python version is {}.{}.".format(*min_version),
+        "Please use https://bootstrap.pypa.io/pip/{}.{}/get-pip.py instead.".format(*this_python),
+    ]
+    print("ERROR: " + " ".join(message_parts))
+    sys.exit(1)
+
+
+import os.path
+import pkgutil
+import shutil
+import tempfile
+import argparse
+import importlib
+from base64 import b85decode
+
+
+def include_setuptools(args):
+    """
+    Install setuptools only if absent and not excluded.
+    """
+    cli = not args.no_setuptools
+    env = not os.environ.get("PIP_NO_SETUPTOOLS")
+    absent = not importlib.util.find_spec("setuptools")
+    return cli and env and absent
+
+
+def include_wheel(args):
+    """
+    Install wheel only if absent and not excluded.
+    """
+    cli = not args.no_wheel
+    env = not os.environ.get("PIP_NO_WHEEL")
+    absent = not importlib.util.find_spec("wheel")
+    return cli and env and absent
+
+
+def determine_pip_install_arguments():
+    pre_parser = argparse.ArgumentParser()
+    pre_parser.add_argument("--no-setuptools", action="store_true")
+    pre_parser.add_argument("--no-wheel", action="store_true")
+    pre, args = pre_parser.parse_known_args()
+
+    args.append("pip")
+
+    if include_setuptools(pre):
+        args.append("setuptools")
+
+    if include_wheel(pre):
+        args.append("wheel")
+
+    return ["install", "--upgrade", "--force-reinstall"] + args
+
+
+def monkeypatch_for_cert(tmpdir):
+    """Patches `pip install` to provide default certificate with the lowest priority.
+
+    This ensures that the bundled certificates are used unless the user specifies a
+    custom cert via any of pip's option passing mechanisms (config, env-var, CLI).
+
+    A monkeypatch is the easiest way to achieve this, without messing too much with
+    the rest of pip's internals.
+    """
+    from pip._internal.commands.install import InstallCommand
+
+    # We want to be using the internal certificates.
+    cert_path = os.path.join(tmpdir, "cacert.pem")
+    with open(cert_path, "wb") as cert:
+        cert.write(pkgutil.get_data("pip._vendor.certifi", "cacert.pem"))
+
+    install_parse_args = InstallCommand.parse_args
+
+    def cert_parse_args(self, args):
+        if not self.parser.get_default_values().cert:
+            # There are no user provided cert -- force use of bundled cert
+            self.parser.defaults["cert"] = cert_path  # calculated above
+        return install_parse_args(self, args)
+
+    InstallCommand.parse_args = cert_parse_args
+
+
+def bootstrap(tmpdir):
+    monkeypatch_for_cert(tmpdir)
+
+    # Execute the included pip and use it to install the latest pip and
+    # setuptools from PyPI
+    from pip._internal.cli.main import main as pip_entry_point
+    args = determine_pip_install_arguments()
+    sys.exit(pip_entry_point(args))
+
+
+def main():
+    tmpdir = None
+    try:
+        # Create a temporary working directory
+        tmpdir = tempfile.mkdtemp()
+
+        # Unpack the zipfile into the temporary directory
+        pip_zip = os.path.join(tmpdir, "pip.zip")
+        with open(pip_zip, "wb") as fp:
+            fp.write(b85decode(DATA.replace(b"\n", b"")))
+
+        # Add the zipfile to sys.path so that we can import it
+        sys.path.insert(0, pip_zip)
+
+        # Run the bootstrap
+        bootstrap(tmpdir=tmpdir)
+    finally:
+        # Clean up our temporary working directory
+        if tmpdir:
+            shutil.rmtree(tmpdir, ignore_errors=True)
+
+
+DATA = b"""
+P)h>@6aWAK2ml*O_EvJ33*7hs003nH000jF003}la4%n9X>MtBUtcb8c|B0UO2j}6z0X&KUUXrd;wrc
+n6ubz6s0VM$QfAw<4YV^ulDhQoop$MlK*;0e<?$L01LzdVw?IP-tnf*qTlkJj!Mom=viw7qw3H>hK(>
+3ZJA0oQV`^+*aO7_tw^Cd$4zs{Pl#j>6{|X*AaQ6!2wJ?w>%d+2&1X4Rc!^r6h-hMtH_<n)`omXfA!z
+c)+2_nTCfpGRv1uvmTkcug)ShEPeC#tJ!y1a)P)ln~75Jc!yqZE1Gl6K?CR$<8F6kVP)a}pU*@~6k=y
+<MFxvzbFl3|p@5?5Ii7qF0_`NT{r7m1lM_B44a9>d5{IF3D`nKTt~p1QY-O00;mZO7>Q7_pjHy0RRA2
+0{{RI0001RX>c!JUu|J&ZeL$6aCu!)OK;mS48HqU5b43r;JP^vOMxACEp{6QLy+m1h%E`C9MAjpBNe-
+8r;{H19{ebpf{zJ27j)n8%0=-6Z#elILRo@w9oRWWbO{z8ujDS!QAC@3T%nJCf;1rX6ghzu#Z}<GSE4
+4EG}J&ngovyJ$%DCh>R@K&*?Hgj1WFD91+adaM4G`4Xs@*hA^t@nbDYdL)-aOjsW~3}QVVby(8=@7U$
+Fzj5Y{w!2hUUH`?e9j7WDA;>-1aos>7j{2$~BfyL8p@__Y98dsP#Bs7^<X<wp+-f{6%mc1~N!0T>lWF
+=e_gr;(4^?am?Cp93+7b-!?~nb}-$cPSR1zckA*zNp!)$;YjlZrfn&RWNM}=QA7*cb8A{(9@{5!vBfq
+rEMoeu5FvJZngI@N#4#(2v$WnMGCAVD?b9t8W^qDfcFBe5ZZF%dPAPaq#<aBs;+HiVj+9PK#6heH_-Q
+-kVzlI0rncJH8Q{ZFBFwrpI^^9n>>ikclG~yPvCg`JUGb_W2#PdCXxx}7!|T*xc9qdnTILbO-nAJaF2
+~0snMF<S>DU<%E01X4*yW9@|}F2;vY~;0|XQR000O88%p+8eg`F$&;kGeqy+!~6#xJLaA|NaUte%(a4
+m9mZf<3AUtcb8d3{vDZrd;nz56RT_b?l9y`mj3AXtV0MT+&(WJ!7$x<XKFy3uA!t|VtMivIgZJ5Ji5n
++}O2laG&&&kn<Ivc;_N2)LD*FI(_y<sdV43#Nct)d~Djbf-Z=u8IOJY7eM4${JnKJ`I8;rxdD0pnokZ
+%t1O(o{kB4L(#6WNXXLn@Ri9Miq52d?_ou0Rc)-Nw2hL1)Vnh{FFp1(!Y~Yi6Zr7%Cv?>|Xq_^eh*q`
+qYNbl$TgcX!{RW4b=Vw*pI`moV*K|DJ2bY*KQV<MvTF2m*rdGtEu%;pm-_&W{2D2Z_Z_^twpM1Z)o=+
+AqhUg-JPjL_gITiyC;k=D@`*;L!0=}(r1nNN>iviHGglIK{X_)>pN=IEr427|<0g`vfCSX-CrF6hnx-
+fU6^LzLVM{GttvQ!RX(K-@qvQ<9nZh3{TwCd*xxj~wep|+d4YrpRGd3uJ(;$x#MJ^wO(dX9-I(W~SOL
+|!j@ev4<Eyb3wu9PhFEUCh#7vF2;?78p&2>#PBd+t2O-3Y4TDlA%@&y9h}l?d7(gvc*a&O+atWdOv5|
+XtFg8N1I1Eg2~6T^Prn{|GZSIw2~Ql9c?>!a3=lwO6eT!TZzV{RAoH`=gPAEk0OKF^-L_LxAV)%Ld>V
+rC7Ea!84dqJ@cSb~%=6Dm=^V^deci#%k)qhs`k`mikNs;GRv|T<cNgr(f&zrAF^e3QMFK@rmRukK<~h
+DGnzmlr2lU<HA7<r6E*!Gq-55ghPB?mHgq@`sC)hvW;?&?lxAeg2z~=5)lly_z!5`Ee^4m$72}H*Uhu
+#huJ3^d6GO{;G9x1r>RB1+w&XWHK8?pSmvO+Mn5HP0Rg<yXP5hf5`O3iN%nTcXZlvCP~V}zj31%LM>&
+0e2!{O&s!2A%Oz`W5|6)QOoeMptG0vVbf-p%MA<(l*rGUr<W}1QY-O00;maO7>RG$G|nf0000U0RR9D
+0001RX>c!ac`kH$aAjmAj<HU~FbqZae#PBbp85|A3~X;eVm7U5EhTo8IEDN@P8ls7-*bu-NCRQBoJn^
+iQAVkDRLUzpPe}~%$w)4VGpq9sQ9OsArVq@gW&td8ktF(xhi|JBx9SfJ>&U%1)EvFVxRjSzi=C>J@cM
+k87yJyz4~-Qcqlg}hXv}1CF`fEox?~SG{pae%Dy$pBG>tnWs3{>FohpTZSG@fe-hAmws@4PFv7Mv`H@
+JnAXTbgKqwrl)IWaYE>+%OsO9KQH0000802@m7R+hDJp-}+<06hW#02u%P0B~t=FJEbHbY*gGVQep7U
+ukY>bYEXCaCvo+F;B!W42Adn3hP*|5~K?fa1xA6Cs^1JI)&D4jnX98E~x(=w{RdN$P(+xdH(X;aUMbE
+La7HDOJ;>ViJroJQOYSq=f31Z#UCgsvZ;PjisC7~V50}YW@1zhN!C_4fs|i^>lX7r-W?|$V(y(g0ZOD
+x-5bTWf^iasXM`rih^<v!W`vODRRPWL)$4oIy_Lw@%52^TY6ciWDVPL;9>?Sk#%z{jZl{Ri-7?Gn9_p
+NH(fR_VZQx#ZustU5xCHVj%1=)fT*F;XSi#wiQR~iuoy}(RFp&L9pfC#Zn^7Ax<k&)!ljMjX4O3A89S
+m#?Gl(S-mv1t5$e0@ASnWu?TZ>z>2yIKB7|@~y3-1&J5eC&FySna4hw0fjd92G^LTzc+Br>7Y7w1=({
+s_3<|LwzLQl3jT^=CKlyadUgD7M{+)3>-rRJjjOO9KQH0000802@m7Rtz49V_OUW00Srh02%-Q0B~t=
+FJEbHbY*gGVQepAb!lv5UuAA~E^v9(T1#`|xDmeVS714ZB@>eSIHgphB=gYhxH9p$W;~m0sZ?Bwghq@
+hk_(WwwJ!hnbT<GJASv%`Dwoy462V5JA74KJ*z>%XT~X$2UELO<u8zEFStohU_O)Pztjn}5>Wbx^D5}
+p)=7nt84rjpQ!t=bvqBu6SXjxf*{)}V#v6kjnleUMl*qKLJw7ma)>Zw|O-`<I|S?oo9WLaI7Jj0bG(*
+*BD&IQk37g?)l+Ec^(x7Q-g_%6+Eu3@x)k0Kj_pRU%)tGDY{|G2pPA!HXV7wN9#A$tcJh3tKUi=}1AK
+5}@x?izfD%tH35f>#U0v?-c6x#d+}i#X$=E%t?3;qCzPO{p3XDn-l0g8$MLf}@FhxjzhJPffk$LZTb=
+tRL0mAd`8KB>SS|Ny1Wz!%10Z<UfmdQGx29X`GcsEWtz-Ff;S(hF6ImoSS3#^%FkxHfaDO;NVa_bb|K
+}GCP23bBvC>P4l!(Z9X~Qr(M}5e1M{2V-3vl>e`}|vFvt@s535m*|M}OlVSM$)RrHcBrimd6?lFPUdh
+^8oI-}L;caqLRJjDa?_Dr07Ysf#%z>QWYbSDW3_SKrT&dAFG`Lt`@W9KJiJ}<Pen(?|l2qvtTpBDE3$
+PFaGv!_5r%NVV5wab92Q2!l!s&*fyMeK-hVh2zaA2!M6};_4#rzaz2Mp9n*;gyJW4x3cM{%XBOu>-Jm
+Eim0UQMILLA#<&5?}IiA5v%!>tEItSETqsiWmt%EBta_NRXj{H*Zo{ba+L0f#Cr>zURR@B*qHa1TLRl
+QIY3XdTuN;Q8cY|sQ{2jC4o$vPgD13HO~sl#?~l?=&A}cMFP(CNl(yMsR`-t2i}7DFz8rYgPveC_)gi
+?sXaiv@_U|jtx7a74!l@<;4JHe05F%Q2)SdHLgXxn>Gh!i1WT2K^_-Mqe1LMOvU4R{fH+QfQ%eQYa2d
++e#MFwQ*oaQwvhGC2wTnRW_zJ##J9Pw*x1bE%az6lfqS#7Kz)e-Rnn7GhG_W5G{(q)4xvM*<E{C*%%z
+|@dedK@>rJ>eb1rMlG<Q#PU6-U6LF}px>rLDy?OC^}{4osL<Xd-&gathY+6!(-G<KQY^Nf<0_?AJ2h%
+baI*&h>lt4f7K8F}Z|`B#E1o*9RQ|@+2V@Bv`<7P)h{}C>a!R4k{Eil{;q0l?<O`2W~qlt?@lZyUjHu
+vR&7*JrH75V}PZft@P>#-&mQ~4}M0|c2#<t7A2yM82G?A2D5@m!TT*N3NT=q;Asoc+MTS?=ih&;4fKH
+wB*C}hn3lz_KnbzR>OI;L{3Tudz_N!_rY+hTGzghD(#5kNVHprZaZYt##W$uR8%mb^&)N6ivKk8Fogh
+BMr8%*?0wS)XN@6p#nApa&Y-w9Ew#Zu@h&NSzS79U`3ykgq8X+X_$OD4A`np9UQ(OZ&?G>pd7)u100h
+6&Ehk$^P1yyq9_uwBi4bItZ;{YLK4idID%pU;f7}zm-6NU3Bg;MsQ)C_Xl%pd#APfelK6ZX)4Meva<t
+#WouD^v)6>rN3gu`&(XOy?+-ilBrvl6uD3dNNZ)`pUd=i?WZkc;yu4_~oaIcdwK6<&R*Ivfg2cB}&44
+buBuR0s5klsH#FHwVF%6r=l3b;v1Sm=o@?fr!Fer2uDL9L&_isoatz297jX@o{A}`XCC6WOfkP0%87K
+kvdJZNsFYvO_uCPfDQ#!T$k!x23L!YQl05fIp!Qum#J6eLAwB~uW~Tzhl*@BpO*0iZn3-W@i=nr-W|(
+11<!9_wC)@f6`9@{Twzk7R0$51^Jc}CuE!GAA9Xvvbt-);$WrHdL_|lAeLBQZ_CO#8e=M(+dKloNd^C
+?t#NN4$3mrXN;--92d@3I`3A83y^SY1a{JrSlpYTf<uyg@8?u9hn^MyFZ_gLeQ<UO`!eB)9Uqb|3x48
+z73iihbh>w{K!f#O~7gF*~{#IxcX?lmI`bj@X}m2N^O|Q*fI&p?b#N0ES?Pkc+y}Zj6*0Av01gLhWTd
+nOTbhdhE1BKPS3Fg`Z@s&2l@TrvgBPRJC~P2NN1QqdwS}`bs=5XEmp~mF78qqjMEpthH9w@9Bbi4O^<
+&W#%iuEa|8!D0@I9@+SrhW~?;jIcMk1?8@}gUVbulb{fRenF5C)Hq<sU(uBiQ1*0^E^hAIe0Dgo9vdT
+jSUSyEebQ=m&`3&lwsT_taZ=b~|iRqr6=hHb3s!ZBEizuku9O4FbAG`635jgeYT!aSk9!nV%5DV!m`y
+pgT+?87k+yw%=72vpWKHm%I43^$<JP-gMJvgke%q|fRx&y(^Qde)}^Hg2FdU5?0tMb)P*KglnUcUeIa
+sA=r#r1j^BZ`5=<A4T}Kb#V2XOX(h6NkuXuu<y{ln7@{>^fLi3aX)oB9={Aw5B1Eya}ud)zI$Kgq)lD
+w*#4Ftggw^aT0%+Vu2)HvSC$KTnIVg4EflgOXhv&oh3ZSz1L>6#^bnq(m1-OmeK*vFp=M92_79T`!l}
+{9`kKpLiSkSXPgGNTXzC<Mi#wGI%2)E8QZ6lns5f$h{oGgD6pb~sS%_2br2JS3y;ztwFeqDdX60Np7C
+{4H-5j|G&bD5*L40y&&58oUwE*8cHr4fVjoD1Jb{N5(5{*jSZY}Z%cvtO+)<AYufl$xy&c4Z?4)+A?0
+c+%a(ELlNY48bI{NVe$<pj-eZ4#3ki+j%$Ub>M!m$>YmKH1A`kiHiQ*43y-)7dhX|M$wzbh0!*8wWuO
+$+?!aMXV))oSMbZk=4=^~Bzkn$82y9L)OTJZ?WBo<WHOe5LjrV}0-gqo9*@{_X22Q$e1wfAO!OQu2Gq
+d0EkxC&m$VDOr%ZU)X{|-`&EC`&Pg%8Zn9OW0l#*U@lWj9krdH$|>qw*oo)B@x+ciJET=1kF<^8cqPG
+P!?R*vWNM|ELa#g+A5(FI=e?5HVwlmM86Sq%vDSn84<7Nu4Cy@v^93Go0~&XH@{(?4R;W-+{wnaSX4h
+dBLaWBKHJuX_r9tZX^)!C5M>y}CCk2Bg3Q180j_`3MbCnUAON=wR_Mw>=B(2!qdobEOu2v5=yT@shGM
+~r3jQ4Lc*S5nc8W7-2G(!r^M~cFZ6m}#W&xX`N#98l}tUwm`Ct`*ss)D%~d2{jaf3BD8RZT}pLU*I=(
+}#C|8y|~WONGYELk8FDK9$3V(nS{-09xll!z%G^#&nYYK%@=^l2j(@kWt-j^soOk{KTUk>+MW2)n^^6
+(IL-fyvERX*?qG*p`hD|5y$?@0$n)X&O2H<zEKt*HL*`y7(dgS2e<W6b`M8O4cy!}N&|O{PSEhrFs!?
+%zk_gXksUd-UHQ;gJuNg|85n^_?)!gYWND7#{zr7A;`8{Z%ssd|;b~QWY2#YaQqg_mY1@oiTQ7==&v-
+%=^`ShasOqSbjyd!TrLZ^WNp-d~!|4uMvq)WmMdkv>;^6Ex)SV+1jP-txm+iOw9lzzJAF$`cMda)C%T
+GVJkVYGtLqIROwK@kZ{Ay>IU@jDOX%0SdYm|x;oqbm2$vloyp_(hz1t7I43OljOG#o7wOvTf?rAeARa
+|#tj9{cl%Yb<zELjUf235p$gGdmob9D4eQtrpNi`bG(`#e=u35Pne6XC}{Xg~>U1ah!CbL`!H33}dzr
+htU}qX&Y?3r~m~9(#^Nq?X+Q|_9G!Gbecu}-EupvSfdppnjX=t2xj3q;=s^aZd#RHI3bE@&IndzQQe?
+i1`zO-;MmiOM@SbDofi_1tz~EAd#Gh=@ohyX!HEeD{|0MK8X+k#$FHr^$7_}l_w`+ZnbT?no-_f_d2^
+gF__@%r^IIH%GBQ!NI72pmqqVd1vE@1Pr*4|@_{B@EF0PV~*Do$#zj*ila-F<df4GJQmTtZLVA!4a=h
+Nn2OZ>feF<f3hVA_84=y+KZxXO+Gkz*ReDEu_Ovif+0mK(M&GF$CE_X^#<oYDeJIcRBC`g=;?*kt8Ah
+2!YfH*1&m`(}K*=8p%0{=V%6^cPXx&?$FBn<+|4biao99nbt-*K7Fy3cuq7ZbJS?J7{qg$RHFe{9lkS
+(e{ts6pOTgz5Hd}UL2c}*5&zHh+4ot{=ZO50|XQR000O88%p+8(ZR!S5DWkSy(j<x761SMaA|NaUukZ
+1WpZv|Y%gPBV`ybAaCzNYZI9c=5&nL^VynOiRmi;5aNJgain`7vcHx&GcHj?(1F;fU(%KZsaF-`5MgM
+!BnO%}gk-S`*rVT0>vbZm^^FGfkZ#J7flbgK~uVgNF>Y#FaF`LaUF7%-+Dl7KV>@&S?9zU2OZ+>URZm
+08I^H`XRZB-mZDJ|^~e)wBFx(RzKvAh|7nx7WpE4{G`@lqRnzbUOQa+zItGP;bDTa~9p6_;}JQPNqll
+{?c=cqexYp>wOMvQqd?a(Phwky}+65WS0HZFSa?+{nDh^+sm;N5$kqW|%M-jMb-&VrJWYFY;ULN#F04
+%D&c_;;kb)4@Ign6Q{aT8=KTs))4rLN4~GJJ9cF{|Jba5iQjiDJrX0$TIOnOF^e8sbtn^X)T$NFj-8@
+{iD(+L$w!^1W||6QX|+Kfkl2FcySN}PQI%LV?h@~meaT}{!YWRZ`NhSX?_PZK;&t-(w{Ko2ub;lU!un
+ZJX>5qe<=~GOsoIK!+!4%fY?Ln9d#;VG76M;4bMf#m^kaD;@PQA1r)*v2LSj&^GbPMkK6><66k7}t3G
+%k;6qC2p4udo4tT?R?rHN8dg)qrSbuz1WRSnNFs+5(4TFfe%EoKWbTh8VSp>k7KDv@TRHLsjAy~-W$1
+1NT<M<!PJ21bfzynZ&H$9wfD)jMTu1VvnIGHHz9m~16^3MtkQO>W?#JpWLXRdK6RW#F?EzNxpE#>lp)
+L@KQmY%OvdbHSvR#Q(wVAd@e}J8Z3r!je`je)Ck^oa=V6;$d%XlO!@K+b%*1V2d^Xy2w4ltjxNEf#-3
+%Z{ALUeFZ1U3)_(q;J7d`IZmt%WR2RXZX+EXcUxBd?R0*?FT5;q^X!cf+#1h3DP+kJ#Eet+Auqb=xQF
+Q9DDq=$BF)ebs7G3HsErkC)iV2`(78&*QQLjTPOCZkd?wy2ag;d-6k?}x1rJg}=7ORhL$$#ZPN^$zNj
+Tg>9AVKS|J*h^19BgTg-Si7jbyU#zk3OeHj<t-IMlm6rR`fViD`s2A{e2W^WtqKcbwxpdNNPD<2JGaJ
+L{q*c?;uRfj(f%X%UM5#|+HRmaIvN{DkDko}?lF&vu*Mx>X#w6z)PBwmsR4&u*u~na&oyv#<NKZYZrZ
+BZDJNy>6o7)N(dOcowdnwS-4$gvNc5Z?Za7Vbu|?4jtqNxFtz=&^dnjT11v;4IL1ID{P8VIaktI_HeD
+ph^a6s9Mm}XTh}^EIel%nssby5GkriNRV6AM)!D*Xygb1)d3!pB5HAL~sf^1LseG+ybyersu{iS!=M*
+kuF}3F4jbb^91EN5$b*Ak}P;HI_0()yqv%I|AL85vcWASBqD&-~0$E7x=R_5}LkN*5*=wa8h^Qz7UIU
+fvi%EVSL^kBCir+nM7d*!60Km<7sPqu|i+!T_ZXPIzO$7*Xs4&En>KIlwV0X?HObwzqXrbaTfl$l{<B
+KPH!1x#rjeblEt3Jv_m7FK3pz?PVcp#RW4_O%h2Lh5I_Y95Q{#ZleTww_&#H`+mdM0}y@Qf?0&q_ZH^
+2@;pY*hqXKT?7$NK?VO?g;lpz^n4=2<)~wxqpl#C0&$N?sQ;Fn7LH9mCoz_D<tfU5T82egZ~u`Pqa@{
+$8~bX_H4E|CTM2q}SU~OTx1B^y{<?OeT`wQqEWDW4kCu<ShsVn&-NTdR%}pn*FY8QdP;U@<D7<P|X%-
+!{OdR%f__C{?T!sLOgEE9I2@;~KV_=(-<5>}e1zjN>Bi_ss8)0_r(d{QhFWq$@a3>XM?j}$soOk6IBI
+&u#!le>AE~2k_cxYGN!FNPI=l!F}8{4xeyA%X@jh$HDXDyZ`<-I6shZfA>e12}YZck^uA^W39p#_)p2
+?1tXA~?YD!vm?bE50NhSCj^BGD}h;>RuQ2#i7i&_fqLqRTWi}nLKk*4+C{cI`FT+ETMNbO%(&2ZV})a
+A$64|l(d)5`Or`KCEg)Hd?>D=q(YqtM3teKWMm{m^@+;W!hw$?$yfP(7znro3iP!<JmY?<@gVuFra5k
+J7%xZsJ?~(%FSN)LTqYed-qv7;91LwihR)?bi*p0q`d@IbKr9aOcKhFab+Vi}3Dms`7t8!42!AoQV6^
+GmiSV?R7(o+OB&fm6`GT<l9tZ)T`N=#u?)W^?TvikxDb3eqkV}ZnURwZ#b`aI0$g>k!L^00BCW;vx+q
+NX+TzEJ+U|VJoPE$|UH24jzygsZkM7^8isYA9!ZY7WyC6|sYS73jlUte`zO3Aa%^$)d*#Z|nEMSSVQD
+}>o;@grJ5^0LOK=tx&yb%(S`XAOR9&=~f75q}ZKF-<~5a7#-pFZMQ;&TtGsIz)hE2gRavlZHtiLkZvY
+{ZwSV!k~w`La8T+vQ`*YDPlDZwC{UD=Zn-1a&Y^0ko|)NIqvml?~u<C=(JHEyVQ6DH^r6<#CSi}FA}~
+n>{qy;lD}oo_g+kf^F0msufq*K--n%A)TfOG-cds<|N9Wt{C3jrdGQS^DtTw`*s)69PYV+`VKuz?ioy
+k*jhrh$Xa2Iy{pQ=Fyl3ea31xSnpR<x~tJAQ?JC|O$Tdb%%d)`~=uH;7V;YMHsQi0BE)thj*=u8QGT+
+GLb->s%F+~5Fr=M|@FUGJj7EPZA#cIXKycEe0A9=P<3{}8VzrnB+QX`x)Je2|u-Qb7SFaxVx`#8w*J1
+?3mE?gP}g#VDb`lB4rk&&9(}DF1N9{N5@jA)J!i*ogX3G6MTP6My3*$(1bVg<Y$ADXY!?QrXS@m>6Qn
+!M<@5_Si=GPt~X7Kslz*{=cXBHm-h3x${9v=mfe)LP!=9;k=?-iw;ej0gk3T6$LlFQ7_SU{0H>s^A5X
+RmB11KbUVj#A&NVnbCr5iDb9=9evaaM%=xCes3hP=|4Q^Ujqt`09VfB&Qhe3F5AVAI-HESy7v%BPx6i
+L$CGVeKUA;`6J$?54s&BwuR;+;#PRW5^x1{c7xm^-ibAT-SjIplI?u)PTHiPyg{W)cffQhkmQ6|<!k@
+>=OrXGd}tA1a}6Ww-9cMttV?p{AAlI_b6x~JiL+-AL7nso0=65n;wTcxPwCEg;}^VA%A;aqSj&R;3?n
+$c0ZvFlx;`;?_X60p-s5Yv@=La!0Vlg7lsaAl+m^~pwj*M_>Vn$>pu@K3X0Djh9+SIsLaDjd@l=_sol
+#DA(LX;(&l94T@u&$%E?2W2XHVCECWWn9$hLc>O!&WNLBrg8u29`Jo7%R#nbcs<A}+;K=jh#E5Tm<z{
+ugnIqPEGv#q`duYAYFi_i5p8%tnuPur0VG#+s;}&<N~XrW5jtmJU8!9@Zf?G}MNNHxgSCeF3%5i0m9f
+9Z+nK4iEs0Cs%>~q;;hx;bqPP3bll?F3jeP|ga5#Al)jQ3x_KVI8q`TLdzllbIEagHuxU>s~JyP!>yR
+(CO7kVK@`0wzoO$a#7#)7?Z2S^$Vg-rb~G}mtJs_M<eO<1?0xy=9RyD?<OmKbR*=C(V`wLlW+G8o*rK
+AdSBrRisgkphdn#LlTInT0QNJ>#JrkmB3!{49w2^?@W>4O@Xw-K*(-ps(;%|1m^9fopm0d{)eQjvRPV
+r~Jt6SOhBZZ{nvUJ`3Uh3yHs$nK=`gHg#{t|7t9X)aIbjC#7x3p*|N?nxw$cSpgj43U}16A`8*Z>wH@
+*JIFIqUwr8gv07It?g!0&E*`rRiiI@qfLgyEvU*n3S<0rR<Ik~F`$pJBKVhnPs`Y<Qmv7Qi8^G_|id$
+73D@|`q>{Oc{i2pONRc`?tYpf4{_vWiNOMZXYsa^e0Yj~!AIh~K}y6eSo2|#uEhcCW-@|c1Fd2C0wmF
+F~CKcT-qpqrVVbJF0DTl(C`SoE2_aTcP#tr!~U0bTI+ZeW_@dBeEnnCt@+J2Z)Znf|DN9VPual~~t1!
+M7Ri90X)lJFnw6<x}p!MA;=mKWJ{XmB`gmz!o4d;TrVmG&#MdyEC0!GBCmT()n1Hh?#X4mVG+5a3Rcp
+XLa5h{R>b_0|XQR000O88%p+8N-^Lqfe-)y4>kY*9smFUaA|NaUukZ1WpZv|Y%gPPZf0p`b#h^JX>V>
+WaCyxe{cqbg_ILjkoQk3{=BVp#INS{Q?y|-01xu44>Bk1c&=iY~d66Z7l<oS0+~0ohJ(3bB$w^l1hck
+-SmdMBV{l(WH2!1Z|rMTV5q!LBW)=8e+@-@#Zrg*g}2ZQTk%~{3eTI5Am-0sJNBbFy?K49!vv7HoE#d
+9Wdwje-kDKf4iShP*D4X*lx|FT4>Vj+@>r)(#x6-zXbBX-C4u;?6q0EG38$n6SIy;6Y0g76B>mk4(a3
+Az+XULh7tiTpO>Y*)yXrCcqf05G>~x8f2|UvYz)r4dd%BIH<^2+0<B^ime<K@bFkfmoM?tjv}&k%~+E
+EGrgC#_g{{*>7sE1_*#v`w|Z}kB{^Hh@FT<HDag0z~m<5BX%Yf{66Qq5Bm~+UX+MZl8xAhO$o3yoKlo
+gEOOWcuOj|s!D*SYkV7DwF;8++DGNF3K7R}1__^3*>3LE8#LtQ(<>_cJ>^o;uiL5>%Da%wyb#Pq-!YY
+%>F8_Rbesb~o`tWj4om+=Dx4b%oC&1f-JJv!i>~fx~jpQ+4G=lG&^<Z$7>@=O1BqBEPBo?(_vlr}o1&
+~%ro(_Hyc?uhh5W)a|2P38`IUEdrzBqq-`Y!(I_<DMN{C*1S0>n<_B4A=^31vJ}T))9{gTeItQ;h4c<
+I{KN7gy60+_>dZfeZk4u;N(>+Vz5c0DZiJ0~ITlzG5oWRnXW(@@Sx!Oo&=7?vK~gt4Xi{Y5*S4^AYK~
+F8M+%#e!D6JG=Pl_-qo~X2ngC=~dTzRq-|ZEK*Kuu1`NqCxH?b*Y9Vagse76HfPg(D`b(A?R#K>v`N7
+8t=>TLx;(v%4Wr(ko=xqt_|x$fEd~3M&T<#@Cp26z1qDiY@o9Q>b$T+5FRo6eS3oUM9cem7<`>d!za#
+ecJDlfy#iIwGj?Yd{;<Jn6llbEN?6(@A3&IDE00)DNR1ucfY8l2cdYU)}jR2vYUwoL3+52RF!x>0`oJ
+v79`GqA_1rBFZ!PA1}g<L0@_zy=fgAl+KrhLib`USxa@vkvy96S0u{yQcff(Lq^+;QU_Q9Ts+3uK$*w
+~0)FZKOA<*vJKEA$J&CNb<cy^kN8$AWY~Vu)ZD8G>jxKvt$7(AEQnl1w&d1YE7$DmB>n=^9_R|c&Tw}
+!J2(Po}*xkJlnHU@+B}XE5NdWABr|e2plrk{(YdSPlbX2z}F!67#PzcAARBse$2-fogfN;l@*2+T3RE
+*(apucRs~@SFbeB8#J*qno}~p>v>CWpB>*8UFqna3py*>G3OE9kQN#it#3h%jq*QEQY}gJW3~T|pqR?
+MyyNd1~UIAhtmL&a0vw0XTQN&fKBb0qC69HSht~&H68MYZ0sWKB)2z(f^H$%fl(9YQN7%>IgkeG;pW`
+>?@)bP_VRO4;7>OH`^S&d_%B5>ua=--9NL;N;kEiX7^KpewYC=wGJBJ?5_Dn1C&9~zyS59l9v2_6jRd
+Z$6?j8KWhm+qMaAOpQ$>>mTsA%lM@LAdBB!{EQca8xfK^tw(w!pF_378?46MkeRG$1t&c!J{3%7`7ZB
+&<Op$KHqgy<38DqT1(M~joGZt>Unz|dO=v%<>;tQnA!ROdbh~HaDDx)UDdyU&8SOG(%6n^kye9CS!^K
+!DX=<5VSWi-2<<9aEWiRVF+h7HK={K?*i1@EkUp%0Vj3w}1Oc{E;Ds9K$Cszzogp!)z>g{x*t`*wJ~X
+TVyv{z;u@IgqI#*SN<P?5&*4oKd1tdfOtO2sgQ}BDRL2J43DfYC$MK;O6`zkV^1Tg0w3n)hglft8K3O
+EVBxGu^bVUNb_0NpOA*cPxuYs?u>)E>F11%XGcnE~3vNrGo!voxs^O+NrbWEBK4v49N32w77?UK}zsQ
+N=Oj;@NTptBVXdGzP>ANMJL_En|!d<2tJ)e>BHbtH?QdDg4rSbG0ccEY*;QgZdqqX$=uELywNT3G?QS
+i4v{IKlXh3K_Bd`B6{BuI8XwS8dX5KHOCz>wZd$gK_Y<2fWF^91lIL;;1NuSwAw$clQM(|3^{BI-Qlp
+a(|^+ZLf%J~^}t#C)nCvcJZX?`c>99=#1{$1v>hfYykwP37I#REE}G!+EpVb%5Gs$n6Jnict8pjrP$7
+fiXT(}r_<WAKaPLuO>NxOAb7HmmjWYGK!+O_43lXj19v<|SFn}8Du|w}4zVgs@kwSjV(}oRC(vBf_-d
+Gcgg)FJZF2L-tQd4c~#az0_pvfehRM2LC4Z5TQZVU;BuA$|WAvucW+m8doIVA?JDQmGdJwf1cRm41n?
+4_oz_6JRpXUM#w=%-yTg;a94D{;HxsscYJ3Ms06(_S!iyA)z#DXX^LJ01h<@0{y24y;z`(guDf`b7O0
+5r)VUG)7X%eansLNUgbn#A?|ixug#Ja5(#J-lVEjwzE@+6ko{Q^g=@f8x}$cU#o_1wr$|*6=`%Y5B<J
+|Vwr$SA_Y^3G}s|S=L3-=M@ot18TA8dU>=X%BL*$3H4hLr%2n>|3BEEAGA3F8a!tYyG<X!e;}Bo1zok
+Y>J90%X5}*^eSVmxdN8Ka+(NEfy7Caq3Q>G0)GuYLUBor4ta(uy>;)d7?$Uy-KM#<I?Rk3ndZZciCFk
+84_9|CgYb(!s3z=HDv!s23u)C6@9PpIZhv`0odh00%5_BF-(MX`qPpGLYY^`LgjFOMh0hC>l@>EZ*?@
+80tMA#jAP4hVasWjaQI_q)0GWH`0(`;rz<^v{s7mZj+!t&%N|Yp>wu7rkzye!E1tBUakx(ql&N<t%20
+<9^z{lyq!lOX_~vw3Nbd30Y&{+w`s9Vht{cf$4{>5*3@HZ7X%?BZeQdI7!pa;z7?k5PRs+W904N?}q4
+^&+9oE8L+@MirpRSMBc@KvyHQ%ClE*VHu)jt>sPpsxc>S2_VupjPf<e<A|7Ru+{c*t%#8PGd;UMr{vI
+{%rq+)rHd%*xFZsFv-fOSuYildT?wW&c*6OWnmuR9iz%=TtetwmKpWrRz)fr?5y60`;!%U=;H}i;HLY
+WA_AYM~19)rov<~9mCpgOMNgHu1QlRc$2>k?9^WLfEo)g`Ex7~gZ)l;jDYVfg&0+xP>fjh~cfPx}ui2
+!V|~l2Bj6Yi;ZsDLEzkM{7V@?!j3=&Kq^J<|mC8YX{#}YAfv&2p%VN!#NW9vIv9EQs{)NU@sL^i%YGX
+Ex}F+8AvuHuokiAU!dYpzUZ2JlF)Xh;5#`d4fRQ|uM{isvQOc~MVL2vGv4%ZOh$c~b}}mbP!eC1Jh!q
+9cEJ$Uc-dX+=nx$dF8u>c@^x`d#)Lq4HwnYfAG5z@aGV>XD;A^@Db&7Hfi&XiZ=kTQ8ET04MC}8Vl?3
+?Vpt-)#f3r&|wxD`U78^LybY@;S9hZI$JfP%a*;52{eegj(QI$k>k*SduZh@rzJuoH;8UYzSPC0ldP-
+Ky1q$-8HqYGG6gO{o<uMsD_XY-IWEcs_CL1ARIZ-{Tw@rGi*viA)9m^B*?RXUGEdV9%pVu1)Otid$M7
+Z&A4cU+8f)Zij^U5pSW7LQoqDhHhYSO~f1Ep}HLlZEO7@(^rKJorxKU_+u)y=?Kmv`hiF(DRiB!rU=<
+Q|stWj*@ko1Ak6i!sTx3?g1sG@db;Qt<Hqkns8su>f65g?7Q(B$Q>ta27WH(+kBH{^IjjTb+g;)yS@`
+8-PR-d2YSvd-H`fs4LNWcA>cAw_n}|}2(dxU2QX|45ya9f|B*qXZhvS#*lOFSw+=?QoYwVaG^a~_%Z#
+%X*2=B6VP*__f3I!xciq)xUQXJ;qKdReH8%~z0^zG}e$?xpysoar<C{rqWq;K0olh-K@>#E5s#h$m`+
+P6e&<56#J*L}p#SdN@ihRQdowu!Qn2^J>!bVs<fm?Ix7tTxF958Lxrj%3IAxJxWye4aH%~4W9R87NH&
+NOUWGvTGnp_&J}HM;b#URzztaoe+Rxx6V94}-UkS3>5Fz`KLDhwxt;5Izn@tj&%C{KLELN^TamrU={I
+Lw&ZHENEq2bJCNJ_LE5f@ZPMoCkt)4N#BRobzO=@iE7FQ0z2&bR5K^kNTEZW7RGbAU-Rm*p%$ly+t{@
+>DqZ5~yS=o)R?!WaCE%-NCE&@XVhi|P@%oZUgQ{B$`(3ghq5oSIS#w(yIZICp9be&4p=_&bx8iw|F6a
+xkWNS@RjhZ_KLd^kZ)6JTDkc$}F-I&l^^kN2V6sPU{aa0TPr$s^ZPRx@Cida3g012Oc8@`3e{hYkEu6
+2^SYOydTtrL5b*pIn@xBP_T-#xuV&4p{u*{Z5aHGcj27E-9q4GvqqF85{fx)kMW$jvugz5e0Hzy9SpN
+pRl;Sbt6obg3erECVw+q3Wx!`xbQ%Y_UqfmqGAW&egg5A^uD>mwNKx9`1O${#3UAd^Y{<$FFA-9X_GI
+hfmsk{{_ic<WlZb&(@Ahb<0!Z!n_fv+L86RytY>h#&FQsCgj-NF$bHQorYpJzO<ouNR6z=Htk>Xm*d0
+t7_|AR#Qxl#sEn6yc?c)%r;4M&kZ$;+##_^UyeYQOVKoz?G^zz@+XAOu>$w0--q)ZA`c_^Ky;>dU8OJ
+*6%^^XJ9f3wJW%YLlWhw^jbBuv?V-=&IW~e7z-HWu5@>`mn`nGrA%(uGcOs5gsR`O<%f3@Rj%A@yH&K
+#1V+TK?s04awJ6%eUsf+3-BSOpX#c>PWf2~nc$G7cF8*w_4l&|o0+C&{{@>P@;4$ezZQX;H%R*$?Bn9
+ii(>YiXtF(RSuQ`*YX5;1E)4(VDgZ`}Nmf$68C_55%~|O3!$p{#Cqg_n50fd7x@*iJ?6d=1b!@#H6Xw
+QSE!Lm^%|OZM$j)BPz-&QhfobO%{yAHPn790H6MTdUiHu?~83cxUEZTfUv1_;tWSEH#tFaCmMR4CR^F
+AABxYpQSK{D^*EPRAJB5G8%|vZzLF+c4iu<|``%jI&fMzEowll%;yl_@8|Q;Q+?5_)?H><x*<|hzZxT
+KHLHvPC&&-(}xKDDiu=BG$g}Ht;caJN%Ji>9fmQLmTOOy9$#nIu@8J)v<)An2fsb}{-z?A{6XeEfwYd
+5AjLOg&%`=%G0>w0|7{of8Kc2HO;MG7e;yU`bQIp4X94oX$eCiid?UwFJ+iX1%To^AESHYjSxQYEN3g
+vB)#o4OG16{4P_?l}}+%zal+H)SdoxnW9QUHMc9#|wT9hnc<{O|H2NIyhy}s??lRr1wIq_JWVh;*1@x
+o^bu2TW}UnK+$BXADpHmfc4VHZ|ZC@KWSC&tvd@>>6%Lx)m5~{q2jU?)&01MgQD%h31WM-kaw6rN^IR
+{d%xrI2WH+5-b8)>+?y!R!+bRJ@tq-_b|vTK(Q0<|X8sjnuzQ`<uC#5JWZYJRo~)e4m#j*m{@{pt>we
+0SV0XE9Q~UTGQ2!d+;pu>ObMP43+h!2c{|^KXUzfqXJ|d=Z**K2u|7my#@7n_}-^hnyF!&!(O9KQH00
+00802@m7R>_yM1-u&o0J&TM02=@R0B~t=FJEbHbY*gGVQepDcw=R7bZKvHb1ras-8|cJ<2IJ>{tAS>T
+P-CLdoq_)%DYaD)2&Xs(igAoPA27eX^Mm-#uTX`NV_#ERc-Az%+~(K{=@!BzGTk@0Kto7b&{7^SJIM5
+;Nalk;M@Vv^Cll6xhj)9Q=(Eb7UiPItN9|YO0f!~yKpZ3qob=uqQo+ft5k|N?=P>!+jm!@EY_mTMY3G
+wMJZ-Qz7%1$E*D8Q7Y_-3irZDP@`EHRWs!yHEi^yMSF#98=?j7h|H%(48I?G4E~Zk03#TxW0r@OUQ!z
+_YsSMn5A&*ow)d)hHcm&TXH4+LiPh*kgrHJK9X0gbr`O-h~Jn!g8V;kk!ESayuLdn8;R>}`$noP};G>
+^hm*1zU+n49^z3d@Dlwy^EgS{)JU2~4}p^HdocMT;=WMq&;WUQO2{=(Cbx$&JhP3JIrMUj1-B37)^2J
+pcCW?KdOwB8ke8I4hBKc`*{N69vED(Yl4{NW9PB%Mk-2lHbG3^TIFWUn{9f<-^*^8jlNpJc2K31uHLm
+dM44r2a2dXHESZC^Usm_!s9Chlf|+CU{zY~0JRK@yJ}@1Nfm{wU8CY6SUSLWShQJ_Ajd}n{;2mNRJaP
+Jeeeo?*KeCdeT@qerbqSr27CHTS%z^~hNk`3p^`6v(nT_@aHhNZ0hRH8c%VvTRo(rJe<HDyLM~+nGeI
+7bg*Y+H<j-aKnw|}UAPbi=2!=;TM^BEPh|4IP&GIxxmV0s(%b5rg72L^bI1M7eY@m(>;5HQFuf!C%jE
+PdnvMMt80E(B<Vo-ShejSegcJtX_%%8(g|H*@GGQ_QiyX0-2Nf?pfuL?O!J_NYQU@|daJRqPj5^>lyF
+2@K*y&2I9%^=5?HR$Q5{K3!&Nq)c}^#j5i;W6H@#EBvTW)VznM6ZVY4*!TLPK2Tdz{;}oO5*}6fy@}d
+AOkf#a*5K@f^i&){9YEbG=Dhpl6jUF(i@7;`r6w;XWoz5h9|W3diqntq5o5!WCKLdSF1EB2fz>cLoiL
+l?C#{MsN@h=J4!>P#Cfus6h&SPtVGt+2f1~%kYWmJj*KTHw(?1u>8>x55JpvH5?LVTOAX^R<DMuf!xC
+3V0rE=3wlgfyEH8j>5|o)aicQoBh0jzZfsH~EgqRYcm{wV|5cv#wIf+KtLuMqn0d`rg%@7O^+T~TjC=
+j@%R0@Q*^2H<sIP^lmc0kZomVktUb(={bek2=hqA(L-szCE(QCh{4poMXqurxGsd<1YnSCpt7o<X+|*
+<Fh9SUfC1%!sg%218Ij$n&ID2sN0Y9!z5iV*vnU2#^QR19*6yN|!M39|(^X!eY?_#A6VkN>>&4AYlY*
+QLO;84`b9zay+e)6!`1bH!EeBR!^Qb3_qh?3R^QNgP`U`CDYl+{`$23dIt=8ES_q)ckK~Az^&dxSY&{
+Uck>iBj(KdmIU^etbB%i*+M=|m8*1Vh>45v1_U%pGL@$N|somCTjLQYvY<XaFT+c_FcaVlfxZ5`|5={
+8BmM~AmBvTdeO9&i;224#NTz7bOpTsiuZ3mEMjTTLC#IFiAR*C8>EKyS75(>|D@`fY5E)F0R*Ji9wya
+u?s(Fw7GZyy}BMr<h&+pcfGWu;2A$*BDp+kc{&)3BY7ECyrZNArb?QH@NqjoDl$hLf7FHSe%&FUb;Uy
+tnHQE$sJZ6U$N1#C~sqL54t$3?I&$3YK{=^zCk&dH=eh=0QM0Hwb*AvA4%!)1346D{tuTSTOVofPsyO
+y@2VCo$W^2Y0y~EeZvjBR#Q9fNehopiY+W_tF@-JZmWOww$x<TE%mS7mX`dwt^M8G+OC9dZGS`SW?OI
+gRsEnzQjp<+*3i3!VZVWbe>oek$8BS_mI1C+d+b0=QIDPAW{o}E>CQf|!jw!D;jJa=duPwA6A9kQ%)8
+z&oGqAcX?(M>Ft*pvZjQyZ^R#9vc;&Sqc@Atq1to-@m>;SrNrF5}*G<XuM4YqMBNauePV>NswO}Drc^
+_uhA<}l6E8p~Rja};4lg$BZY<C)%?LU_@N4+hg_IkR1Jj{th=9~ZhZ=jy=`r9)qjrKqP{Xchf82%=cG
+e*j9GP$4s>wkX!`+t1(aWjOc2hFf)Z2y`$|LO(xu3^s|w3MFMKe6tlctS3ozn0rQZ^sK4P-FYHw3;)9
+0KME&Xge|Jl?=N<_jNvKU7H}g)ZV$Gb~TqkW$+JJ1|lR9emx6UuPXkv8Vo!0JeWv_&(nhZCG(8d;Ihy
+p5zH@~WM`ISw>-`T-G?*pHQB%$3uf!-pu=fYR^URB>!{!f`<KrtT2>Y0$?ftlzmXYw8A2NO6+NBE?di
+I#Iymx?5aX&~7pm^;0tMs$*MP0EU4Y*tN<oYB^?8y1B%|_cblG%ZM-95}cRkoem|#@(VIecITCcdfU*
+^jcZGUk~&fi$A!K+-}j=-lbVLh9VDT;>!-TGbU5Dk$fV>h<&$8Ptr>F)LTknDGSIx?}|I;7O(sE#?@U
+@K!$&b;Tq=-N$*;Gx)Xq;H_X54SD0HWnuOYTcdZk!Nk9yhyJQx#~VllekSyj1T)iW?h*}!INv3A~%BL
+%NWyU(rHsDi!r>q7Ppq-;QFlnCd^@T2DRnu**E|osZ=FxP{B?CgMh$Vz!2dyzXyYhXqBw|7FlWonF!-
+uN-54K=i*PFe<^053J_*2%Mj)a>SQIOWR^t4wZ7-zH*~fe5$(5SU}rHtj$w7L-;7}~k{+r&`v>CQ9Rx
+#uL%G>y<C)i_KJfa6XTAM@z@NBYZ*=&5m)v$aF^q75aOZ}?4beYU!h18hI(>0^b?Twf<eh)}&G_u?%X
+gj|tW(K61C*p*5*ycx)+2_G6L8@QKr>k?jBzf)do~S8W|))#iXSmx7Yx`DQ5CnhFX8FiynLBgSxmFJy
+(Q%(!+6NTKH-Qq(m5pEo2~^3Cm0EqJFYN*RC3%E7DuPemf;%XGI7Q2WI=LFXDG-6Rjp{^A(6uvCJdHI
+JMH1Dy_qgWBAm#6&z|!f)8lv*7U5FEKW!2=pAt*A+qOnR8IIpDjNG96R1y;qJIJ`fqyr2T1C@3$#L(|
+WmW(1q6(kjYv_n=7UKF@;e!HZGDejE;JQ44aJrFwbgA*$@5wWR^!b<VdBeAl%-9Zi%9RSDFY$4s~{Ya
+$Aog}#TvOvzjC^+RaX%n_%PagRgo2|po$g;GTV`sI%X54x{57QKQUE++o?-5kr?gwfVu0g1^)u3Y}I@
+t^{9%F7o*rb~hI@>8J=L>5uv-_mTGZbnh>M*BGeN<9PzqK{?t(Tz^;>mfK7^HPXwt_amwUCps*Veh05
+k~o+=gVo5(M)zu>v2S;a)v7nDs&_~PA*|qDjd>Eg~&@p=&+cp>*Mj~H^cTENXZexvJ@MJw<YG-)IFi&
+76i*&0s|FpnyKalBh~h;QA1!i_y}`2hy?6TW;Bpu3P7kCNIy~38B^B?cM_=z1?xFx?^#(KjKtj7{+yY
+KqN+d@U1(L}jI3CsgLfnwxwfx?!@lD^b((?#j@No{89$=4NN$0ZC92i9%*U`%>fH%qEwow~RWySpFo}
+WR#3PJ>r_g47WLVe(s8?V!2;z~5dl|+h`n!NN)I+o|vWL_b1yht<KI%V4$_Zenim2(1a9+s!B(D@1p)
+Zo+;Gv!>%D`}M@-5RODskz^nyPoDJK9@WKIFw6_^=tg+~XI%y1F_?pt>2)=%W-U^$3<~?x;rIdt7GWq
+@7IVMK?dCrC6gaJ$W=u<!Z4rKr{jI^EbJJ0BroRt0PelAy3>IOmFKrIq7G$M^~CYl<3j*B&`NC1ihzk
+&DWM{(7=9oqa8h(#*XP$F}SU8HZ1091Ud~&_RT<}3>-D}YQZ@??i=3BsDVvqppN5V=Qk4dpt{%aBh``
+8dBd839e?lpg_J4EN>s@Eq@-?-drh)0jXfFy=Y0mV!NL~FVE2J@+A_!nBp10ukQzvT?!(S3ifUC3U4S
+*c8t$R7bF_14ja6qUIrOF5Q9Vw}y5i_28+jjN+gUwJ(-TiO7SQ%7kAmJ+X@YNh*ex=$_6>a}?xYQ>v)
+V-|_fZTbYFQg`wphb)aZ1-tY!xsRZEe*71PB7F>J=gC;6Bn?Y^dELm|dLH?xPwc0_B#L7zqxpPCiArr
+e;Es*=@Lw<s2GpW8|h3j4N=dp2+$91l%aXWJD@0vqqq!zX`j;oge|-{tC`dw`dDYtr><*H8afu7+HT`
++V8tWGA%NK1}?&n<_m%gZ|Jl23PIy5{A{@(`W1bCBwMzV%oo;V-dI$(6su^k%%(<nd)!Iq+6vB1jXLF
+h(ZRJmgg`g-1RAN{VQ*acvYP5h46E#Jm}=CGBfBnwvH-x~#2QixNbCqo)s4sU12_or7&YXWt$<%texo
+g+06es)NLIB(stpDhD2VbH#8Z+vt`V0E1!zJk#}L4>Pbyfs*=YkLvqtCs;uGBhrn_9B603ta6!sx!g4
+_7szMNSbPB#XIkbT_S0T+M{W}L&j-oPFoxR?&Nf-%m`3~sKU-Tat&-F)k38e#1LHK6Qj-9X}kk@)eN>
+Vw_!TB8m36omA~5W5tB3C{~Dvl|mk?BR+bruM;lWs{|-K(|*E(U?_fy6%l?<E~3EMUT9*v3#^Y7HHy?
+jdj}<*=t&*_*aJ#cLh7OTU8`;^mSn|xrE!<h$EqW4-8O%0-(TGPq@>A_R~}@*-WJn<gS?wTlG9W1f~+
+A&eN6|YG{aNsQLcUT7R<(g{@$z!V}swhun5mK4+=0=Sz}WgFTXQw-{{Zi8Sc(+`=BSNc?5;P5Y|>M|#
+!%cp&eey^|o)KC;2Q3FxH?E3bi+%x(`0bkxn9z!|Kg**xEN^xABLW^~_7W4LQWv;?GX-Uj}g$J;;FEw
+IZh>SY#onKhSTnLH<X_nDJ#s<cd2KwR5gm=bL;7ITbApx(*_Mh|CHI*3L;R+jFx&UYC}9JM~CqYc-d9
+neFs_xh#=7OwDAhc@)76Bs0Q^Znp`-J5<LOjy=Sghn4s1ydf}$@NJZE~jxQKp;y$FJf8L$^?lMrAlM0
+f_xT4cpf7&hd~@q4qCa8Yyn`)5hbk5gaDYoz^p<~6JT|kvp>z_^?*Z#RM6bOrBOw}hDQUI;Vw`{tae%
+7cDS#x?szW2C2M_7!Rdkz-RTdzT)K}*>GPC097}Y88^Ik(D3EB+2hGuWDaBouKV;*1o|Egpkcx3Vj_y
+O$TCifr;uO7!QYhwQYUfl65MICx(>18;*(`}*hkzF|bLJG`S%9?|r1=9zizP!Lb^sAqSJi`$Bvtmbg!
+yA|3sj{naYzdaL;?n^vsIFzgwT^w?4B(+qZmtx<;Wynl#cp;_x#er;4@I501|u+w23A74k(9waf&tcc
+L2cXZQi}am7xQn#Pm{@&<Oz|lJ8IrnGSP0N(asGH_ljR4pwQn)-rRIqbre6h6|MA+A)Id2{g*?fW)-r
+#K#E^LarI6fV$opyPG9g9CK0$r8PtB2{T7u+2p_sCdFx&x>`kP;RZNDvyqd7c}hVh3kOdXMVzU-2d<-
+ZoeT?bP|Z;Z$HVxmW54%#mnN!5&5?SjshO!YM<P3(i1Fw3#-fefFRL(Y%G(O9F0euhWKU2ujTNb|vX$
+nq*UPVMD54sS5&~=EQKppeWHqAjHy-RrGCHT>npm8ftBJ%*g1q2(<<2-d(f8=uV#RxY*H~IERBebSOq
+5YUl#ZMOyRE8}f-SIDai)b-c?w$-7Bes}(P_8?qyEUHU)QL^AG#XbnG0pP2E*;grjd-1h@{{CnDGym%
+?((cp&noH?s_yrBCWl$lm{+5BMt=4VKw{5Xe|i^|Fdd2m4(_%TpPp$7(-jyh5-|<psq3!+D7`-7R+~%
+LiON88V6QgxG?|{;16MaN<*j0bj)gu#vqt7ruGE0d$CJ2ieeDB2MHn@1vXXy00gkJ7CD2%LAZ=4S59V
+;HZbhn-?^K+wrepJ2jH~2VvS_VCsbqQlodu6iJFq0#^)hibA19#*yNS;>`1h$qy*0l^twKr=H&Hs+T?
+wa{=?Ap^It?$j4d8Nd)7}|XtH+cy2?@XqSDj^>LVT!NS6mbLaa>6npEz#<T?;glUSACo$2p)%=8sc4$
+rY^XlRX#v8kUL>)GSkUyjAm1hKs{NmBvG0oZ)m<U3!yGATaT(_li;j?YyCM1z<i2?^`zXdK{cf)>w1m
+gXT+AuOUrau07DIJN+05yoJi#Id%#O)Y~W>u!z5FFJ`@D$Q}%u8{X6^1|hcw2&_bXEW?<<1G5HVuxNX
+al(u+8u8gdlAj3xC25FuL{;V()MjgdbIjS=+MSI(iX_Al{GnwbE9#r+i+NsxsT5%2T@`IT)isS?SDN%
+jLJwg3t7J;1SDHi^eIJ@NfKAv?r9a`RuX?F^$0RB3j0l|R{5r@|c_LoqF%T(A3b3NV%Hw0xb)vE7q;*
+xI$F0{%AG3aW`rW&Wv#Uw)>h$tet!vC0oHTQTj)rL;i#g+@2Oe`nvc11}-IZKmL>n6l+v-SHij7;)l$
+4pN?dg^kfLp#G3oOhU0fBDe%oF1?=wqb1sEI`qtY?(3661#Vj@3N1Q<G&!p*tRCH`5~XsME|Lp`WOLG
+3m4-dJ-*Bs8E0a<e#End`ASb7!0()qp{U0iF-i6oVsS=Q%d~<FI6a${Z2PB9OkmL2P=KDPf$#GBjSd3
+kk@=OJ}iFUY(X+0r=4uJ$GfVY3^lQ?tZk``nw&Z6>=`%0<0zB&+TrWhCa&H9F{x!rU4BGzp0o``lE`x
+eDu%WSlR#-j-PJXJ*r99AcIuT@+D-AHQBvnD^c^9nhgAkK(h?^p=&7M_=cM5-4a@f#^bmzU8#RTr#n=
+wwd?ni$1VNj;>{y!6Uw@IIS>29{$-wQrmKr%<yrk@TAxTj^6iF%h96jpKewULgMa#SvP)jtbxbm-26W
+Dew&653b$C6#Wnp{rA`RVg-PrsR5iWl$b(v~-;SI=Jwcqfo4;rYvpcW>zT#pK`KpIuDeOx|8yx{LPm?
+DfPKT6faAR;!pCE0;!QX-5J)2i*1C$OTlJ1HO2N;_o5B>IeBDT%xz&Letf*n6@h<B|-khg=8cOmccTo
+k(PIk@h|<ylq}uEAmd}YTZIpdJLxslX3Bl%(aj>>&0)IO0zU;o9g)=(rgIRh<zh)J23r7)OR{fsvaA$
+0qJGT)wEO@-=6H=ukIGkvj-fYgOV?YIYo3?&y#;Jgagab&YJ~<v);nLW8Dy-1{o42&k*C-`PzM<XO(}
+c~9&#;xcRAr&x{_QCqI?PTNmQN<hAsoNU+(m$?RV=~*S(0&d`b#4SvL3Wh#SYNo&a;hhB!VxYLK1Y=#
+FX;{{By2fb}26^3Z=eI?w$Bk@5NO|M15@9r{l%uy24L^dAm5JM^EXv+qO^XGEa@*eeV2Vn9FY!W>)$k
+FH0e4d}IPvzIU_(5|d*_;f+UDv-FEguoYL08lXNQ>67llC=b;Knq%kt}=-V49tSNN+C-H(gzDZ>9P#f
+v@6UFGKk^e+9H2r?r<7-OnGnUWFvL@-inoG3c>ieTr6!FN!3NXyqSDJXsHIR=s%w=#9Iw|sk$c*&{^(
+*XTDjU1mnlqbQxybc|h1`a_FWI4Awg=s(N&tsOXIDHGVm4x7lK<!QJ;LK^)rqAQ@RO4u+3ebnUD~Pf^
+?X8XVh9m-Zf7+_s`lb&-7(fm+rQ*Bq}JGi0OO2uz)tY*gMlhb6IU?>XLO_BJoSmaoYb8*~q1)@XfSSL
+C9L&$$$x97Ru#E1Vk#GD*;XRE4W^&I;qyk-cnf%7e(*$z0BOfA7CTMyK#>Bll)DpQiX|-D`i9<*+dYp
+E0KzRQ%F>In#xH^x1sHHkhtVJv7p5TqK6O^Ng;x>;jlAhWKY5ZmCV(bL$j6bgOUlg)R=3yNY2u<M<}*
+O#QZQfk}N%pu;KlmJ>R4wsE0S0YmU&^78ck>#Jb$m#fLe+tb&te+b^3z6JC1MKHOzcy~c#d)|*nXld(
+R;U3api({kK%4cyyWs%D;gJDqBaufi=F{pac`eW8Rf+k5T+)o!*iF0j?q8q9mAc0r%*@zeE65~5y?aJ
+(^tdVoi1JhlH7>EGvZ|qD=NI3ZGqh0!{LA|Rd7VS4YkxAWS@5xIfQdAWMLT-$r98wtSJW|PdFdQJQGE
+7c|nLy54Jlglg7hm26<f)0<+j@b=dVz0mTcQQ;3R}qNPFsVxU^;T*;$``ET1}@|PEf6SZXVO-t`-$no
+zqg7@!{p{M{U>5T6Fo9CBayeVC)cSca3pdZlQ4Nug9}<><WPTh9jzIdvpWsE5>WVYRkZb%GY!i*JDhw
+qn@VsPLsVwW7?~n$~2J_Fwg}v=u(&AowVL06(GaDqu_5(wOHSN1){&ZY#uw(`3evWJurR%OweA${Cxq
+f2%QnuYExV-QFmzjPl4I)P<#+7dfXmpT~tQ6msTN%+s9)9WKtw1xxfFc`L1KPus1*Q*e!niSz&rF;*?
+9x=4k&0^_mBI%>zDVa3|Mbiz1(!+enG?-LUTK=fRuF<t0TOD5);a-(8;l#awQ{<a{nL)gFWS%`$}!Mq
+$}p<A5WGixMqBQ&cWl!P)dAa}3th&-Gcn?~^Rf9~2$qEu;ggBC>O-h3=5()R4L6)QA(h_BHvNm1AJXA
+thX3Sph7I=>y|v%+N8J!YUf^#dpV!Q!GB_+f8jChorOvjW09=p9E7;Af3h%{m8JakF99{c==q8<tL%Y
+<OB4fMJkhfC&*hCt^1xVbxt%+zOz8JJfWbJI4yaz@VUBH!BLpa`>nY>QVBbaL{JY7-WY!y7{r>DM<L$
+tvHwz&nMc@-H`usU@j9c6a#qN718<DSBm=MII^iE5d>rxVH;o?v^U;=}dn7^1ue!Cw`id>;)dfn_&N1
+Rrbv^VJ>iXnm=RU8AQ*QoeG9X&}lj@jR)z$(POUvpX^wM0)sIMvZ&*9U(x|Ln-ea4C7gtIx$7xC5BIa
+`Qy46_)JX|&2&;GHz1>>Zxe08noa7$hjvjQ#KvuPSHbFI$z^roQMz_r2~>+}=%x74&rqSRQwfVCya_S
+$g%=&_4Qp;MA$Xw{q<oZ0$c2F-X-w<9-c8I0tg|jx%7|1X8Nqa`5g_7s|rQV%6{qiT~<njg>j)6Rmyt
+?aZnLX>M;y{%&&dHH_8_S^*jX9^=us7sD`#notfkewh~o-KXXIb3=XK=)mJzW|Wa+v;DL34CW&X|HOR
+hxba9#=B)n%P)h>@6aWAK2ml*O_EskVqo?Qq002}0000#L003}la4%nJZggdGZeeUMZDDC{E^v80kil
+xhFbsz8ehQJ(3Y~o!Yzu71oyK<At(4*>N+NJ<At@Vq`?)Et5J*Vk*T+9dnZZ`3JOa&J#Nd<E_VCR{CC
+B8P>v4cNQhtasYJ1-tE{6v-IUeB+zDmX&JiY^EYaP^Rn&xLBg_<m=D8JalPy|Zqp(|NSLeNf#O~IyU^
+~nlqloFf~1P2t%T_xM($h_N{k17%So~{(oqeV)(2StR*jI|A6B%7AA@5&r_<rtVakm`aOo}XS{{0(rc
+!^MMo;ZKzvrHcBcQmDslvT~_Yy_s|RlgNy6MG>?`@_o1&v~&MZO9KQH0000802@m7R%wcA+pq}$0Qnm
+L02%-Q0B~t=FJEbHbY*gGVQepOd2n)XYGq?|E^v9(S>JEmI1YZFze49eWDLwWEpWwU2gn|Fv0Yq%-d?
+aRun$2n(Ae^f8js|Y<fMb5|ND`YWJ~j-+kL#CKw_JuD2n{}QI-2%8^<L5>g1*xoa|=)k!d??jo!0bcb
+%x6)XD})rubeoZs<GVMckp6Y8$`)qz()AURt+c|LIYWcQY^7%f4Da3)N^7g`M7a^5kpP^ZJQz!DwZ~e
++OyAUMM%Nf2W>#C!61=PYaejq^n8ggaHpK@wpa#wu||U!Oxwtj&~i$Pw$M;W)WV~68DFDqd&p+e;#BP
+7qnjF-_ly}@RCS5o6Q>0vbD794x+Kv?b<ps*PBl(j8Vy!KeCP1-HNOk;Rd6a1e4&9ss#!z7;2V`tA>G
+-^W>{^V!vQuuw*TU6CRmV43y%+d;TQW{h{~Xt$Xfv^Fd)`MYFbgFtu1W;A`!)Ijp=Xa0z~A9%);lYV}
+D=by<JGigBq554AuyC?p>a7M%M<I4(QOZj<csCs3S96$|!Igp<dIVuP!y2LG&gqJB!=(Z-6$G2Wf#O|
+otD#ji712#4t3zWK*$Ow0#7fX4;P<tZ2tTnIo9rotomvqs<PaYnHk&75xG(Fd_8iud3Ub34KE0I^nfq
+MDJ^JvU$&GSzym++DV0|KgTRz)ORU3<8#F*!{bEh5}%>7L<+uWWQ-8MkCqJUT~F|*>S6`921}WPS(<O
+2WERw%T|h}8V%%u0Z-oRnremV)^EyxzOv`GH=2o|{H6gCsz4}HjbR7Xk04He2Gs-`*o(L_A_)YWLs^`
+QgTNvORm1?0EBy)lPRX8xAH&FG3wD{^>7i>dXtZi4w!A(7E;g_p<lcg5cx_%JeCN!=Vze^PJjk%jV^k
+KiMJ6408V@<-`{J_6$yX{8#vvlo;~OLkZy~`j$hhs3$P7JgZi9);gnE`nD+1G0Xe@WyIOLKZaU6BMgM
+Mf8@U%q9a&fYr5s10Z0&OH|z>L;zO20A|5&edYohloUBtnz4m@)G_SIbd_^6FGP=48kKIBTWd(HaQ6@
+h!<u31T=N_(}W7PrNO@#Qgor8Z9hY<9#o<!JTg~W$q7d2lWuvT(RQFgc1@Hj9tY7xdJQjm?zH_^npP&
+RgnZQZY<l>w1pS2%XBZ)QRo(s0Fd60Cbz}l+T~3FEeJApl{wb;9usbT6R!|>?YxDK&6{~yj<S?eYfIn
+=!a=Rt3O6t4+tPn4yo%_oSY1*kaHEf}2n|{wC;A1;z2+98yC1BhLJdU|ME?+>BCu5^z`7Brs<c{Cx#M
+ZK9M(U;mzw*6=gtFXFg3zwf}0Z{FPBO$;q%fjP%-insKg-HYlvYmqWfN35Qhx-71smr0T1hXFzjU~6f
+NSFq{X~=mJLWhOAamu6G@4JsF8fr0a_S<CDqC;K`1OkKs#@SvCI%Ho&Z&X73gG6V-K8{q2FUbz!~ICT
+i7K~3gA%y&fe}|Ja!}amDSnw`c}<=Y!ZFxt6>a1J|s;#$GPvRHo}Tuq=i`EHcq=EE-5{;J1#TQjawKi
+b;qBvLSy0ODpQIlo4REm%^*T1!+x^_#$AS-kBkN*oXY(F1uL=!3xV?OBQ^qPUSGbRQ^l;x*<uBix#w=
+4hT`EURFCC%hd-qE9rbTKL}WTI+5mNBdT>}}1gTIJ30km&aEqXdG5!`+avbZOL%c*Q4B(}Rny_M{nbm
+lJX=ei?D1U(^y~5)4d;`D$Pd9W{$~^}qYEc3l2Y{?*6R-hbbr>PsOWX&62%<ag^~gYYi=L4&=4Y+ZeQ
+-R{Kw#QrECM$HJev=l%a6MX27ZNA_L`_ii?#xqzhXP*db_&5ZltXT3(c7NUZu_U+Fb+6EQ4>$Y5ir5b
+Y=<8E+P2BNDTCHBbE>xfJM<<zj<@>=JoXtM@wwM(y*y&y}yQlbF_X9;~Jp!_08M2KTPGBR~S~;Sq6T4
+#N;x>%f7(or^Aagb=683RIpIy#k9Gi{A-$YT!~T{v*0H@PV5vgqQNK(DfFcD%b4Vz8gDh$be{13$hd_
+ZcNf4WD<!lu5H_4A!nm9W+B+0$2ZQf|4c~py2PhB}9XrS+Gz&B6<j66io*ddM_Rh1Vw0KYJj;N2)EF~
+a`4eM__7I-L`Ay7Hu>|nyzHgsF452+F}31DFJUZ&I_5xesppKmOtH^L@Yhf#Ti(*U%7e8OW+Ou!iqdq
+1Bf)f+WEi_yT1>JEqpxFhxhbOu4=U}DA@-bg>w2C_d*W#Y4_2fs9eW0*Vwh`^iF8}<ydY#8zqf5;Cz^
+qAq{X#|f;l<!McB-5?HiajK?^yBT{UspHPYrGinb@G_c97nwbI@+XM`6Xcj=d1PFr}cVWOa{JQsDe;N
+i`ZoXAjaHOzNrxh^Bg`F!kO6*Q!U^sq|xR;XGyiiH-L0ygxBA+3$&D<ls%LcRuWZz=sr^k)NTL>KSY?
+1vp#n1Fj+E$-|a3#h2v^F#)Wsv4kkD>4v?XsVi~cMeou4~f-|z}*t>4V*7kuMJVda`>^fq*Sa|48aus
+0N6Oi|bxJ1mD(#B)#CC=rU(>HJS=AmES#=&lcVIo;XFJQ&dp%61pS9w$q&VX?n?%0CVEz6nD=<j0+k;
+iw5QK~#0OTTe_nYXgz?Hu1PaI4jAapx{>q)G~9iUqHC+5HSnW*Zu7B(VtS=KjoI-;hqLO{M^66t_3+&
+Y43_b(3q~d7?cvNq_Hq=E@j-pu3>+-1)oX_vbN8;@Dy!A@>~zM&;)$ACScN75kDr{mpzWa&x7J5AxlI
+JHmXPMCpVbVXsW(>E`sjQgU~Lcd>za(+s_$yZr|^{72Az81pkaai$~RB~aAJ2C1}%pF;{hfL~J=JFpk
+7T%apygF4&bD)uvydZNx(lx6{xzz*TERCPDN4E-HF>SZS(b+Jix()Y({l@B`ax_HG7h7>`v4tERz3Ly
+?zI^!TOEdHsX$tOl)?*Jd-EnG6(r##^!8ijvg)#19GraHvAW?CNWi1s$#=hk#NLNPjuBtS9%DdPIVyN
+!b6D(px(iTxt122^?vv0BD)#<%Y@o{c9!0mqr(29(=Cp!i01(jCyvc=XxTrPCR0LZ%@`>ft$-60j*O9
+xEH*jxYiX(F9J5M(`-dPLXajP!F*O=JPCUMRzjV$gM=06aA%DyW`jot=!9wn-EZ#Nz;7-KkvwCB6~Ot
+$(ANSNI-rlr}LVs^3SQpsN|QtJ<n|(XQ62jDL(x_hp`_lrm7-?i>&0!+5Z4gO9KQH0000802@m7R(R!
+C9=Qqt0Oub703-ka0B~t=FJEbHbY*gGVQepRWo%|&Z*_EJVRU6=Ut?%xV{0yOd8JufkK4Eve)q3n9Sk
+BbJVFsH+QO)}n`S1vL9<Dancbir3<O!CY-VIp6{+zULH>Kc!;2)!nk2jRgDsIfhv$B?*w?brEKfDpV$
+Wy7z87tkX(>zP7j~)Im15&xKPp-I=TdIBqT2dbS?fA&REJ8cxK8!XzpA5}6^-1}m1$O{N^!+RM}=LoC
+-kufUcdRgIxg9Zv@Fw2$(QUxWO~Wo)>_CaEoT;@7ImE5^D37OF3s*zA}qe=jlwC9$WX^pWgil^dy1eD
+*)GmxrDVxH>`#qs>qn06)8?+N{YkE}wC0Z-)%-#GgV%T-k}oRF8?Y3MD(4R%pe#9b(fISPMRoVWFFp=
+u+2=_?uO09^yZX{BP66+^PDu?OV9Rxq^CE3ao$%^jG_u<BN`DD7-lVD%*o9EK5u29O^xKJ~dsvzCQpJ
+iBTR4-{4KF&oxbn;Iu*w@=Wn4{RsklDK<_>7oP~q=HePvgsfIu2<&g33e>LEV7dUNsi!`0)*A%f;uOR
+RQ8Ml*&F$!o)v2Ee_{Qo~Cjn?&z~N`Ptk4X2KJC#&Ub@%Z(HC^;NS^S!@4%|E6Ys7my{PH20{vK`Ov6
+7s!79xC1}S;OlRryj?<7b@!vxKeGylUy{jS#t6G`Z9U>%QaiG`PskE&-UkM`Ssb)tFvELXIKB3&t@}<
+0<g2S4+k-Ld~MdEB&pIpPm%?W!IoG;>?@6sLxh^m=#C#(45qSR=ReTz%E$?;$>yjLA=dN^v1c%pXkj)
+94(l#5#cG#6d-i?Qfh^)3f5^oaVs-!x*KJc7I8b5&4VhN)f&_I%^w?VsjS!8{NfN;%3&=8sG)Wdck#A
+(>&eMmE#g?g+iA^^+x1^wT3mQLto;ql_C;i|AVViY_p0MlY$h3qo)12uYXZ!(<MA6Vdb_Yc<Agx>d!a
+Xh;#~)$4Q2;=n4%d>+34t-8`EpWY<^o825nu`5;3TV)OAZ2*$eLHt6pc$}lnhqa^Hvw<f158TR(FR^@
+r}3zla!re5?$1Rg>><UjMs44w^x@<Bf;%&Y1wl3{4ahqPm9y5p0LY@x)hnv<&mkjMwCKafmSR+xUpI?
+EM%M=ILl@ARI@``X{d4n7pGg8Y&EHolx)P$h+HNRSE~E86nT6CSyP5It3TEa1lj0gXSYy@5o_p2^l{d
+Yun|*m6%Vrx2-@{_-ZqViBB%vcT~!eK2ZPn;T(a=n9{+qkH;zQifcaf|k0i?~sn5Y7A;_6e#H1R$re(
+v^{1^jrXwU!&+$rGSaS^%;fadUKomhJ{7)134kkqI+d_nLB(I}2YpXBLLA%Y}|qkzaMeEpSu$DVzUuf
+P1+d<~ubf+Gs=Ma7-$Dh}zu`=KTn*v{BS==VLhKz*X77@Dc+Vd!BuLlND=r+rLc3}`phCdPu3;Erf$8
+SH#Oz#`UCr=@2#S_~!nD8?VA1@#RA_I5nvEYRC+Z`i6c?BNL$!@tee!yx~Jy(+9@8{2RuZXzqRWxZEa
+OXv6-3B5H;rT3H$zhL2A?3?0#XeZXcaMeD&gGC@c!!%H}fFxviV<w2*rZ7B??;BSGk<SEx=;Qf_pvB^
+AB)yRbPs3A4!xjyBND2irx-(}RBsG*ctW{Kw0HiG0Ru0gmJ46JQR{5Ak)cuH*O@~yVCP=ZFA%q~b^y2
+NymT%;6;JPk-d<uAm(yOd&b8eVId}T^9p`R+oQ)QC0<{<8{Lt#%v6+1Lio5LeCbY~dM=fE~!F`r47;p
+V_ySAnsTdl$yNdmkRb1`e?btiM0`xo6!pBrb90?Y>qvb0V3c6ih&yT3<IUy>oO;DHNdA(R_*0V7{6UW
+oVN7NijMtddllXXkbNrXoThw(bH9X1N0{a#S?br)2(+$libc#%`;Jm%xTq@#0Sc;75msKJ;EX(9dk7l
+iSzf=GAUAG1F%YVA=&679yx`ns-q$%D_c%_b{`a7>ESAmF*E-}waR#bUO<PJ*qlH6v2T%W{rYRYZIDd
+gp`x#~#U{(#L^xX{^MidERJPQDy2{oBIn&gxh5^I%KOuFn?IhdhFq2~b=^HwjXz`hyn?9pY?`ZP)V_3
+h|Iz<CJKtvN6`Re>;1AcFBZjdOszP;I?j=QzH-4Y$Rb#FZ>E{_=I!%CPs@@V8yv=&p}l-M@^w04G2?7
+g4aa}ql)C^>b)vM^x*=9J#2!i+CgY(4=G67$<n#(Y5XXGbw<=w{n+Ub#Ks{(Qm>ef}SkuO(~i+_-$xR
+*%r<sIa4r$Y~B*78R@=G4TAnwdNQqeMFmY0}m->egnyK^lV1Q_1(5_u{Khc)>?dVso<X6q*WXw46MUI
+$psj!ja*Zfv56)(=?|`(3k63#nlSF^+@pR^x8(G^@>)X4SEQK@5CL}Aal6S1GE{{h<T2GE@`IGTDj2H
+UmpqqE8hg5}<Dq+VCO$Dui59Wh8O%yZ5JA^!Fn~H@hN=>iB<Cb&wqBdv*c00f`)r>$8oozbA{qNcVC}
+)pN>+m@$&zMx)XS{8VP0$+BsF`i0eHe*b8W;Oj+jX9irb)S1Yg3$zzB)D8_Ow!q7>C#(oehA;h-zFiN
+3dCM|W>lj^?%d?Kga%mQ*q^voV{>X3iEZ`R^#0LU{6!9MkHK=j)d#Vio23u9H*kmZk~Lc&P0Icd0{Qp
+*&NulWjQ8T2D^0dY(@2Uyk<hO}JcWQSQ*VG3CbI&EAkpHws*bDmsyDsEBp=IuL8f+<Nrx<xAftsw45{
+BDWQmr6i`GB;1UQNiX7X)%s#FMg(^V3-ptQ!8Z%Ki9%RE6z*nH6k5G!*s3cj<yK@?F5g*p+<Ye-8riL
+{bQAVaiM&?!ZOFuMw4V<;hwTpg(f7^G?J{)1+vUhFgQCEBXowEw2^oUnhhk6A-YvYiCtxN-K7sd?{;)
+0l7Q|LwG(e1VzG=77{Ec*gLHH<STjld`zB9Cg&Rz|#)DfQE9yWuE*@VQvRq%ho1eV3@l;-!AV2{Ms0x
+Nc==F8CqQ_!!;UQU25bYM%4WQy+NlnTNpGp%*BiAz7wUn7(XN162>_TH&GI*Xy~G<9IoMJa5(t;{5C7
++B2|q|3!24e{*Mj}nxJsFzG+8$_|;5%%|yu=}uzEE*g&|6X)(e_D?KgY7|x1Ig1wop2sFXM{6ricX<6
+msCKmrz~tXlA#M<B=ge<7X7Z|J{ov*^E}kx5R)qp&0DXC*J3YhVlNv0-xm4oNM@SZS`A4^Qgc>AHwVt
+|VrBv+DOMquK&xDsVoq355*}1u0(~56Bi*JYiX=vVec9m#jSbLu|9W-#K6&x{#m|??#jE$!k^_@0><r
+b-HVK_{D=;OMHKNvLR1+3vy`ld85^dl?&h$fUW7S)c1ud+zc%)3S23-G@JQM`8b(n{uZhG%)ptxHZwF
+bjzw>}*owmPfiVcY@*Cb|w;_31Q(I86iV?vLddrl&<(o^~Z)DO;Ca>E|u^@kYZxK|Lc$4=U-&lygX%3
+Kd>7zoFU@l$=x7d}~8sh|6B%`ua=%N5E?K7{+TFDwy5{US<CSFnTrxWnUtPQ9mAJxG-E_p}gL36o<w&
+4L*<vau9?IX=>fY?0-;80|XQR000O88%p+8=?eQ`WDEcRLM{LR9smFUaA|NaUukZ1WpZv|Y%h0cWo2w
+%Vs&Y3WMy(LaCzMtYmeNv@%#P?Mn+Hx(W!BeN4vlVXdJsRki>!Qq#ulfz>~PU%4sD<l<vF<^4~i%e2A
+o^y-VA)Kn2*hB00l(&v2+HieB}_QOKd^L))`G{JR;ex~!T5yFUt1OSbRZ6MNanf!FnG@$*>q;v||uW}
+7IAHk<0ywf(^A_HY0o^V-U+<HOOs_QL#<$8o6Y4Iv%Q9qyxNUJjz?H?>IFH<cVx_Np7Iw&8Wk-i}=@H
+VUSzx-7pFP1*LaLvhP-*9>t=gQ(z5+f)Uwt6xOk@DpJ4hVDc!0rMq%dWj{ixdYJhM>U!<{lg`xYJhy8
+HY+&D(*XVhMfeOymX?b5g&-znun~d1sA{38|Dlm%hx0<sEa5tdftP&X1`|TdvmC^UKvH%PLrxmaOAv2
+g-Hd}Tgb7t!g5I;bYHkg-Z{YWZrG(exd1-Omfr5$MjBLyYqajUUC%Vs`e(`u5xhSgvZD$FYnfo2+YH{
+Gjc?p@CSwhu|pYb0Ikf%%<4IO6*nCv&xK4d_vriA4=jIM*6Dp{EI0?ecrpx!=ZM=p=~zFOv5fl4uq-O
+#qR%!xyT=EQGB?o1Z7;7!i^gS>!iyy^P35YlnNy3VKJbx^R-4rw-kZ{huG5LE&3Xi?A#Z0sk8$4HY8Z
+4P5g0C$C52|qU*6tn2r&cv(?T;m%Wi*t$>d7f-Gxi}mE$G**b0c(4a744}5iN<{tzvEZGe0=rSJiGoV
+xtiWS_~;4-q7+xZ{QGyWUO#{Kw>QrL*;gpw*Fui<0Jtcgy~8N?Zf+jeD*i3aTyHj;QtVk?w9UZ5&@7F
+y+%j<Lgk62fZa{0>4TA^b^Vb4|aH<-C(R?@p+wdPQMLVn8_ExgGx)qE!%;3s41ibBd&rb{xznvh47KG
+hPk+J95A%k?$UVV~1HJj1j9xSJCh>F;iA=n#-R1?c2F>J_VJA!AC^~D<a=k0>aq%_$Gq1|vx=+n)d-`
+8q)!z{2h$HvsY>_(7lqoV;|T;;pW@KNoN8c=$J$q|;QJ@9z~q(FvHfdN<9oCwn81LI&ZC((=g%qDPY!
+L@{5@LCFYt4eC_>`It$n6|_CC?n2D`Q8Kx;>~T<QEvTErmP$VDvsB^;N=<Ew#hw<(itpLLTSgFNtUTM
+<S$YAgjE?B3izVhEM-kQ(5nuSA<DP?s4+faFQ`5^R+4os2rpH?L7D~lv?L>TFu}y>#G8_}O?}oF;)$j
+m5u0Qax$QuF%69AvikREW{NZAgM_dl?1#PJ<;rr*`v(G>OnAvRPnnt(*?XS|h%)2wh$)6zR*=!Xjo6S
+r%<TkF?<WR8b%%nx|fFA`Oqp|y*2*9bM(H-uctZl9}@CR<Mlo!Mds<IxlnW-Y*;jY(PFI0uWLWhHehy
+nE@h6@QfNkF1(lmTKD2o)Bjbi}5r86qrYT*~o85%VbA83tC&?|4<KN*8U`=UzD)q;FQ5&|R9?L{gFH%
+O-SX9zTJhGAQORS-J^him*o+?c6J<N<=oy3x+XBv+g!OK6}Gpi{iE&hm3vQ5>>RTvuJE;Djx>r@x&&_
+3j8!Gy3oR47Au>~!hxIx<aNWQt@VO=Uj%j*=*(}R=!fzj(lWeZDPTs(yd@BM60v1Yy(b}l2ay}RonaJ
+<<pt8=U2Y^YA&2@U4M<J=sP9IDb=5dbBVHQ2;S%gkydS8RG2C=@HNcp*x@xhsK*(ekAKhU63f<?v!VO
+ACx!Gn;o^oQ8GA%(CACdWWghPm}bEeWR4hc5Q|Gs;oBVd`?_Pjr9b1zMaiO3;eBLumW<ICu7+S`=p`|
+hSVu-*)UrJ~0nHnU77tBL`khlt#$paLC0I4ZDMVM}*66f4!jXt}t7H7&J09M#0*u!s)K{30%`R*S@_7
+6MAOKj&>jL@%mT?}pf?s`Wd7*lMxrvpUt{K-}y+ADbEl6&pp0pnF(JrV;DjLxzS+%cuR4WRiJ^^qx>A
+?1NoEf@Av}jC}Es?$=-u%~2E|8}YsaO9M;7;}|1^%#Qu~LH}FIA|Lty9)uH72Esq_A@=D30V-0b5>2s
+%2YZmh@<~4qIs&d#(tzU$9W_e^G!ghe#u3vSS(c=pj2&2CqVA%5i|c<cVuxUquOTcHv1zjy9&(^_L?b
+29gtJCOD^O4iOlChZAGUkq=-Wz4EGE9yc&>B<N}K-BpC=sQUO<~(9WRriV*~Y~f=-u%RUQD*KGO3uO1
+A9RW$eF24{-;mlQluHFDL4wr`ab_LctMJOeLxGgad(RmbN)Jv#Hs}zC{?07;M9^l;wkvRMLO?>Br1s5
+9|nhi|hz>2~;haQ{tGA4w9;T#u)i<?t==U8waY~&<E9^in8Vyj3XMQYA0@03jvm2tJy={-hgkfP1~c5
+d#<*XGp@4<mO2@5=+RZJX%?t-pn3&+?XaxfPifVh0U=_e&7-o-9JnoHzA(G;eyH}mz<?GR`XU6gg({{
+q77^ZP?gvvhES^N@+4`$D&-)(efe_;OpgvgN^S%L>3ykC|(;NR#Qm-8U5bay|862h!1ODjp@mhp&MlG
+cji{dhsmNpVCwo-IbH7};>W~ysqwB661{za$9YB<v7%1}geH?cfr0uc6OoOrgYN`Y(RkcZT<%hWf%G_
+bam&8l+i@6OKX*V?S@I!~ea1m%TWN=$Oo>Wv@QOiu#+FW3O7eQ<PMq1Xwz()*<ANx#fFC4|~^-X{iT!
+C@x<-ybLbD^Y<=%WK=lw^dW_v}=-pO_z6)vr`MByxe0Gj*U|2YXDz04wy|A*5=n%Dnzprn%*uD!>l8A
+DI%CBdU<GCYLQ-DDSTH7A1b(+?$p3|MoQ(%IlqX~xdhCUgoOIq{I}^ObbkPu^G2C@yg;*bN3%>cZo69
+!oaWK0-OaVVynb#wyJeGF21j!)cgCpcxG`Vo3&uZuJtz^y#Q&*0=CW9ogSv2=%i#eT(EU~3oe3qa^F|
+f`Y|DjKj}2Z1i!z_a*ZB9t$1X^Iv*n%>@BGX;Tl}D0b(a_)Kb@+2G&o;OlGaD-OGjl7suXfC>M=k+wN
+(?lWx#~m2cD(zi4N@Mr3`ZOfl%9P%T+>1SM&`*c53h3b?HRp9OUA42|m%YUT{1vs@9K6^jllY?jRycI
+J@pXEMa^8$!DMMW(A*lE_>!Aq~&=fi%YQ70X>TMWpx0C<K&^p6Y?Luv2AQ?*1C=fD`lT8Dp;(L{phA@
+uIJ{9hJ~WaA>(q2vPHJ5iuF2sqVJN}7ltPmp|HlZC^U~L-s=>+`O|>?Ox~P_Ba%bs4X8`@W1YEPXPVD
+zC5yg6$BIrzGb&yEK(SKx>-*jX1k0_p)sil_d6_Qt!Ryv<{9}iz)e!oK0I0*1XN9lF28}?4>a05}nzX
+u|f@7h_5qw<W+tEaQYVHMdFxp}lb)ZNvO@Bk!skm2(a^Z$xrWV_J4=sLnf)seTjH4H1w`wnBS0CM~ev
+MOSGq-8(-;&!KnyvkAYVlhFRiLl6&vEiU*h(N9b3Szlng;57vZanejg8B8zjX6P7wU2>3L#3}jVEN>s
+pE%7pitq%!p|<wv=dKq4R!JEI)#7cAg(yFmwPgs*|&uc;+Z-`7HwUt_N4mgOvoUzfmuW<!`fyy!ods1
+ZI{v{MS_NN2g<D|jJYmHhqLKRqS$GRDLs>H;ix3dF&-r~_5uTg=Gg$O5U_ecn;jS2D~I3`$T`i^pr3!
+#1a)_Jv-X+$Aez~r-DN(dtp9;3?V*})`6CM3r!u#r9bV^7H~gx=m0>;SzS)uvIiF|KC+xK-+FsdV+1@
+vG%S#5wy8~!QUsC(mtPWzN$iUD=-+IY7?KcBBjJ)T~;9Qi60sa&mlA$_N-V5uoD@YeyR^9UgB7t1=?R
+Yq<JH1|XyvI*(1Q?@0lO0yD)?)Y*VgL!?{l_S?#f9$8S5MN+Et5);@nk-8q0P&rC+vp~d&fE|HMit8`
+1#750DFPHqc1FD=R>x5Qhc&hiveJZ*EP7n6z29`*AC7AgBwWu&C!Yj*x-=yu7krPT|_?OSnEd;4_F6K
+urzQyrZ@PrUTUIou=^~x&g=N-jam%Fnf@MUn3sx?iK*|Ff@-ko^-5sHC-Dh2j6R0W7k(o8*N8M5K1|~
+i^OXy?DRTb7T96!dk)gihyPPC8{{&D=0|XQR000O88%p+8&UflGXaE2Jga7~l9RL6TaA|NaUukZ1WpZ
+v|Y%gPMX)j-2X>MtBUtcb8c_oZ74g(<!1bbewB1ImQe830hVx6%O_=@~KNNHzAlXHIE$Dnf2$tZ3?Vq
+zyq72YspJlE#ElU1k~Lo9eUDvZfW!FB7(Dd(Kh1MiP4G|_)&A#Qv1MRi^<4@e(A1M5Dz*IRj|A5cpJ1
+QY-O00;mZO7>Pjj$fq)2mk;S8UO$z0001RX>c!JX>N37a&BR4FJo+JFJX0bZ)0z5aBO9CX>V>WaCx0r
+O_SR;620qJVCln<WepSis6?r9B~!bu^=77Qr*crKNDKu@h$(^#fHTs+Pd7eDfTYHDbddz08|c^F58X(
+T<bycyis&QNq!rIhDndIgDsgISrnzVcZ<MBW&35GRLdvq`Eg5FZGG8P~vRLp_E2Ji()h(5Z_5YRsr7m
+i*m*PaYW>O1LE8=FVBjt^q)0dVv2S4$yxh%<hSWX{nwj>|8(o1sR;=Z(ASP3{zUhoDM!B}3^JU@Z9!W
+=^OJ4i+~D}tF>VR1UqW;dM6{V#UBf{mRLH#(=_#5CPeO}&Bx)5VVMX;<rlHBVfM=ENGkSS(;Pgqfuox
+&4LwE*iF45cmM3ca4@8@*qGv*$Ww9PQ;#|DFlu|RQKpkgxJHZ%F!RF<Q4f%G&kByGQ#(yLsX7b;kXi=
+tkA7g9g9Hyp4Til8bBa<c>hqm`{VO{@$3En9zNWCzDr0WG(-jXHg{IpL*qv>-O0xMt)7JhFxSDlO@c~
+_Kkq;O_9@xss;#+Bv(1~;c8~x8FgcwF{fbh_HZv;$nqkkXlM-MBLA&L~>bWIvtXg)iSgXnVX2;HVQVK
+aIiZP5ME^yW}F_YT82gK318iF#7BE_z9&VUu0?ZUZZkQ^y08hT=@KD0MV%PmM^JeZZ}e`6D%ZfzV)03
+Z3O;AF%6%ub*hMWQ8-VD6X6IlUP^8pevaGQlteu2aymiqo1@RDoGHM^?8tp;ib$kc*UG*<cNxLGff{&
+;`Qd48ijzySgoUhSZ`0?z#jdwu5115LHL<Y;ve;+;p!Crn-7ppo(G;T^nOv%;YdCwR-0Im?pPLHp)ha
+PeV4*!4upxS;k}i{=vjHLS^naF(QyGaK0;ylV;J{y2AK&X4FXfqXnVK@%izC2<8=SM8g4GW9VcJ;*0A
+L0XRsGq(2<Jz$wWeJLCV<IH?d#eOZ5&9m^)#0D_rKLl4x|R0<t3Bj)MLk%cFpDe(Atg?sBGlZ;S_qAq
+@VQ<h{8-@u{O7ovSg2V@=Nx+hoMH^%IRW%y|&awIOEnjPlGO973SD)LhrY53j<#{~7!+bhbx61-;X*f
+KP}rTU1*<IU(VBv#<4O5K^3B*FhlHpRtag0tCGt{Ctb$Y?#f+0&7UffODRJREavZf}R&y58CeHm=5=h
+xr_-jQnfemr41jKOP=F-hKL1{O9h&!+c1<+5)o0+_<2ks6}%q;Flt=?EnBQwHcWY7GD?8wq;;m>J%=G
+bVKDqWr2;a@cxHvC8C3hP_id3It2`B$aT+Ie<u)A0nsPQjXx)Bj<WWgKq6;%*(d8H+x)mShMmJKBr7s
+p+d~cp*JyfPlBdi_x}O#iGY|NlePZ_;Z)c2h>!FnOcRz31PS0-mrQZ;Ljkfy|rias&g*yTlheaEdwu~
+J36Z1BkbQ<8ha_Qn{&{7yJmgh0ji_uh^%XXjTbSxhFYA7#f5_@7FR*lMWu4I)Kk~0HTS&j}_mQXhYip
+uh56#k_wm-rjR;U@vq;SU-K|3W?)X^UgtkOctrB87}J#B>n`0Lm@Nk6FY{M%i}E3AR)6(yOt`0-Vfhv
+UUp~1xDA5O-^#Nz8S6&MV^nmIzmzX|Bjm*=%8j;1@*nzk|A<H`)2iaYq<ILHkq=*aG=+)WSzti8XoPJ
+Saeve;tCIIC)0$ug4v%KZ*e#_M0vw1rWBQzMVMR$SRO{0L6DPPm7hCE(X}d~f}X>saXL70UsJ7F1679
+G&h(c#vQ@!dGl}M@=$5*2=S?pu$N%vzQ;7c|;o~Q4FkY{}O8UKy*hkh+-$p`Ez+C5X{Co!kInr@NGr}
+nwhwqEYJO;ycTi=!2!Odm^J0VH_7j)I><~-a&;VyWU%yN6?`oFNAFrEC%Z0s5~^L$}CJBQ5*`&@Gg!=
+!)Z*t}~l+l6@zh`Pc4S>WH`P^d?(C&k{fQsCjVERjqtmjadAAGpeLDz<74lNCfHJ@w~PSk6IXhT4PP0
+s5&YD!B=bvK;z%N6Mj+@6ln}`B;ZV;xmX&f)P2fI<m@ks4M%*u$mZeK>0QV9Gt$fwYA63<Sni+HE{ft
+@OFEh8SH7|Zr!m&%nczYtiO#DD$!`(bVGw>l$(&%5?L(sh1CyZvhr5NMnqK@9%7cd5CJ?YzG#8x5ER;
+6(pkDP36$Eh9LjUV9=`$kBpWg;&=#C{qHw0J4<HVdEXK$Wk7`%AVMR>QJ7ydlHTl-3V3cp~uN5%Fhnc
+NZY<w;4s{<0MWQVQ>=uBN?w2f;c6Hxfvi7|z{*mIWUPefqL`OFow_o-1Dh*}=HCZ5OX?XAbeGJycO^v
+L>G!Cka?49;AJMF}?Kl}olPPSJP3jtu~-F>d!UDu~Drrs<6>^LgpVFH5uDJzWWv<EAc(JUd&ewSSD?g
+O&7A;dk2W%jVxlZSiOue&`P<P6AT2!a~LY<&y(S5i^{IdoFSOV{!lA2|HL~m>SUtdBW$a)X({&^>Jj8
+GVk-o<KEp~z;P)4wdGXU(Fa!??1<BVL3HHIu+sQ6=PabV_-t8Ea(hz<`HcsYk^BY|&1D;-v>y^5!7ot
+994L{BFdDM35$XLG2bU>A?bD5WrW~3Jx*wXsIZa`j#(GB0itA4x{^N$m?lZg1wCceE(eS0M;hoW3;YN
+nzV^X|uR__Mjg8DCTC0FR_Yr?T_ye436pya;+P)h>@6aWAK2ml*O_Evldu6ol7000&u001EX003}la4
+%nJZggdGZeeUMV{B<JVqtS-Ut@1=ZDDR?E^v9xT3c`9xD|f)uOKwoj$Jqc`Wn=2bDLRXvrdpWGcAIEp
+e5R7M;295isLT!zxO+&?v`g~`mk7GF|o+QbH7p>1i_`Sl3nTDPNXr55@GF>(N7~2kxTs5MXpk5gCH1<
+)GpH|XX_%3a;+0vEhKugQR$}l8b&%@t9n&uc_xgN^?QBX9_pXD5s_Sp=*wtr^sYX`%I!}gDWvs#`5^<
+5YUd(7Oxcx460u6;l-(+uPuX3TE1imD%9cfz$dNyosVwBLGL5wfjf%FcPn!wLXoEN0v`(rtmj+0~C{f
+kXXcuco%boy)E}V)vbdt-rygFEF{>rcZtlsA7DGW{#ra4Hu^#b0zohf_DVgX}quH{-3Np63XN%ldToy
+dXa6k3~$ys+RambOAZ9x*&O4-a<_Q}^@!;pWr)?&*<VKFx2h`StvPw|1WvKP~P)FWO6=<`2uKi`$#UC
+%(8_@(*`Ui|grVGQ@;@i=@|Gm;9xOOYL}+<;#sR+W3`gB{r$Hxr**p)>@yZ5DK0^NL$MbneVmv0?nl|
+>h0Yd`KokbFAJ5#*UGfEo>Fy;Z%`6MN@BycN+diwm%G|Kwley{Gm&q(-lxN+@Mp`&sSaKm{Y9pad5j>
+u^;@1kvobF-Ud7!>d^=^M3fV^HJTrPTWhwbYqW&u#Pp3~qgp9|k_PHhAp&KYqo5S*u$p^VXoS6d!Ou1
+PteLL1oqE{l}w2V~_8;cEjbG2Z86XUBgc_9*+zE(I*k-};lUZk-!yxAX(IEN)UXEXL3lpYnlj7FqM1l
+O$2UC`F8TN`tpik;+qG8&Csf~-7oJP^E-bLTUKg$(BmYy%}SC#@;?s*w=qKLvD13F!5lt&m0m@<Aj>j
+1DZ8YsMj=$~hlfnXF+i(09mS_W~r%p?p(TyDZ(sGht_cV+);1&kH@a$RNoitPxK}%^qlkL;~mOPj{mv
+h`sVxce_kVvw?gxt|4oU%-k9GbK2P@znrauUn(CRPkv>;5Hr69UBGpf&SqatcH>F+n22M(1pxP1dgk=
+h1tDrP`lq{$tQZ;PPdV;6k9EX(7pgMEtoqSx_ch&j>+`xwJ@-QB1!^TTHVEETu4kFu>LQ6rFjiI`mTQ
+)8l`Y@d2BkZzk7Cg+@Y2#yc5V1D5}C?fMj*v|er(X?8zqjkXK}Ww%Atq+NO;FBcbImmP1*unfZ=>Ak&
+TcDMN%<eLtwok(-hTkC%(wicHANEI#&y_#OtBDMrw1|GS9$vNdD3xSFzQ%W&>!en4$n~FB9BANM^_+&
+4De9njjym42i*5BJ8S0nE^^%=Vb#lfG!9cdo9Te@Si}YKhqhr<QM{VsB)gwfrwJruvi1g{UNJ>J}c?h
+*c>0>Afb2cXBY;V!AQ2314#T~rq*slAsfGWg&x`c9TPy38EIvjH`JgciF{5hZiPi`n{jz^%7RpLhcak
+s9+`hwXJ~8925;0EJ|nzdoDxw<8XX#;&}uGpKHs5R+<_74+l>aj^AAp#N-9H0U9<UIk*)V$&Rf#11yx
+Zr*eLCk)llxxWUN%8@+QR^RC$wjJhR0B{nL_sCsg_sraF>R-s!}~UgcX)htO1A>Uh$H>hr`MP0vTQzg
+9?PNe_KhRqeJwGqX?IvBJNH@ptUAWV^zmfkq)yE@%0yx02AJbbeN*SXQ?Z8mnec#>I~oE<d0Y#&vdV?
+=mX6+DbAJMbcV@VS=K?VO2Zl<xwI<%HYCXTs@*;H&67lKGjoNCm%Dly8BS$$)rVL4xrSRisV2YAhlgm
+n8fv8nJ(EywELDSIh=WBV#k~|?dtuG#bqa_(Dzg9iC3ZA^yCYPgr%Wo?L(KwgPurT)`z<|5};jzeBhF
+mD+LVuv*+*;A|jEjv_(+VSxh03!2qyPVIi7CCEvrmefFAzvx;)LCfQlNf?iDK4b4Qp%7mxIZsnSqPM6
+&+IW_uOms+o>&`?mK&8(tVEp)*kh#@kZW``OU3xjQhNcQ4jxlGAeF<(mzaIlr<w@Qy;wOqkX*q_|~sl
+s`2`}yKukNjqFad~@l%|F~+ET0~39tR2~viS)Xj)NY7uooshQXf6R5{|XjNuu{O^VD)UXLJNuN#LCQU
+_;hx1sw`hf$-m&@(0>}8IMmeHtF?)9XD%gnDZ}k_p`I?kZ+L_;FARv0+iGAea>tqBehm=JF$lM_fmi@
+R%M9|DNT`=<}yj9@YP5Zbc?ZWFz*qwHM(gF3sOwk-02jdZKQ~{KE-7aG$$l``5xSsLk=>b4^cou1zmp
+7Oj914vi+8BI#5F$EWe-M^M|L!V!rsu=L`P$bb0@9cXjjl2$f@8(kThuLiH+)a=8I66t+E~a-T|HY0Q
+Gt*aMed!LYVrNode#&~js{7s&~ysg+o^x~?D~A!Lb&V4GGcpkAagi)-?Oo+q^5Ft>;DP32>EmC^B%<=
+yq&Ia?xiBRyhHA@ndQwQ*zws%p&NOSyFE=>5HQ-ak}lsp7*Y;jnZN*cxTf+g2yBM;;y>cby$(7Y+YgB
+YWF=@?a~vxv<Uv$dKNH!qJeaT-%ftc~|od6VCzJZ*d3H-9Ie@8bgA=1cRucE1O#`+;z&=@!kA${<wVP
+7gx*q-NGZSVs{YRWRPHcdUmpsKe-G%G+uWYLIFkMV(uigSOUgPi&_>Igb~%(73HQPjXO91MFdY>FAVi
+deUA>V>NW$d5)ui51_Hl2Berfb#ubB;Fqj-+tsQmfqHS1p5%P$ni<h3A`rC93(77NQAAwAUl+wTD8aQ
+@RJ11)dJuc*{Zsow<|6t!UG|UR#kM4nzbF&G<5--F6645X^I_tsqFp6lkcu`>-KB~tdBeIV7Q-~;=uB
+1#s-@1AevMc9IF7rsUQ`Wl4oE+8ZgxaYS$XxBI1qsPn<(rHOmn0~S`4+v1^^_fSQPqeO*r?hN?0d`3e
+q`%JY{G%^Nzaj$j=_%IZ^&u7R~6LRyK6eS+_i`lKjFq)zC~R#BbYdSQ8=%!@1MgkoYLu+ru(2t;CR35
+Q2(euOoV$QGCQtNcLgBUz(v*9ae}4mu|NCi<03sA&mGlsG&og{zea}|Dw-bMvFhk4r&?v*&2k#au|Mv
+F8a`5uT@LOD!r!3}T!_07;Vl~GxePu@faBn~9KO%!)5i-sE;Ls-I?PUaG?uGkGY)R5D}3<pZ|JBT`17
+2WW=m7F?|}v+a~1cLV1w85-y&O`b}>$kNt)kFoKs&+PDwbN`c8bw=s$y>D24$0-&Fd~*FKT7pUEFu_g
+__X`!mvaNfG>^BI4Aip<!9xvC9K>s!SKA<kS@<Du5WaQW`Vp8is1k4)X$Lce+nLfy?G-drUpmSjPkkD
+ln&nnOw+*gNHMN3<vd)Xy*)B%H1}U7-%F~Ik})HHwsgm<EafR9j!-aWdCdP0q6SW^6BHSHt4B8?S_se
+SC)=Q{@>R5Ngh^On3%3?j485#N<z<(i`}6P`OBz?%0iM*V}Ee{$Uqa=Lh-w~ov^Yd@{K|@@ZZNs=d*G
+bvV<6@;tkwUsV@7}s&{cJ<2xP8flJOJMJYeozqo+|FkO?-P1Gq=)rsTn&i`i+mU(=P?rsm!pg&t`YCw
+Ft>+W2t{l+b<W8&nOh7!|c^gmEb0|XQR000O88%p+8O?S!EGavu}PIUkP9{>OVaA|NaUukZ1WpZv|Y%
+gPMX)j}KWN&bEX>V?GE^v9>J!^B@Mv~w8D`w%kBDqUq<Mrio#fws>D2nY`$5u&7_EI_(79@uvA`svLp
+k%Jg|NZ(kFA$VvDz3XaS6LE)nVy;Mo_<aDFp8pHy-X`TSLM3N%A!_jF;_QLxmnk}-sMuOb(IyfY@KVh
+)Rk6Qt(sEJ^&%^@?Nb&rJyO$6qyAWw%^y`()J<A6S=wmTEcL2)lb6#p&$qF92i+>2)@7llIxBAAecD(
++_gS-4=?p&{_0#oQ7xTWFr3L)2s;vU3jqXi#bFX!w)@fDiI#%m!Eq|*UUFa&!ExhJFo57rmMpp%nKce
+N;%W{*?i+<Bvr!~%=0mtgHgh{Cx^vvo;7Y#Jeb8m9+VNvFJc@MJ&M9g)a-4t;z0xb5PDa01P#&ylg)e
+1n!U<kL;tMU#o4ePDT6=1f6iNWL$MQX8WHkFP6%xb&dPGCk=HfzQ_cA6jknC7+a^|IBvte_M9%Cl*_X
+|mir&C8n`7}|U+Yx7s5-#7PFy6!Eias@*bv!*QbTEHOkfL1xbg%Jsv=H<oDXJ_Z97Z=H^(>G@$^^PWF
+e!oOUF(1ybTQyR@r1?hI49$#epw0ChkRtE4Yeba1IWB-YCxGvCngcWa0IN5E(|n{ZH^72D?g#{rlRMy
+zvWnN~>^8+!6DI7EfM?1go27a7Pn{I$D(GtXA)e(~OpC2dzmu|9WH<hLy87w&Gc8PE`>j^MTBlW2cJ|
+22SsHZs`Qr3EIXOOgb(;L}`g{bO+az^0OV$-^t@m9ZR^?phb-XC6RoW!Lq)k=k2HcPI^n@Qi&^s&U`n
+~CNwmp0OK-(s*a8~PWvxF@oeJ<(Y89nRjOH_!LX}#2TtrwT)@7}&lUL9Y&I=$H6X_eJ8(*@YSDW|}sy
+&iHk5a`ITcMRjdp=X1HNSh?XUatotNmXf9>xB1AqLCH@Chw%hqTFO+xp`IJ(3Tsj@ptNNS?Ebm!9U#C
+`1>5;g6NQbByEs&X$ZBUzj>gTM;*pJ>Udn;)C@`~GZO&gPez304E8>^Gjp@;c3RMEQE2e^xX0pPzR&>
+hwTM12tdHDqqCUWjkA4%gJ>vz)wn3z#_%{$r19%zN>pW`)!{M;!CNHal*9POO^wuJrw8nsbPH6vL0Y*
+o-v9CvV^}8F4aPEnd7V0&~#lj(jny7O6o1Qh)fW}j5JXRpfH!F~@4N37iOn~)CADN_2lD{vqysvKcw)
+R#={R=1jWbgYk@mC3`^QI$AHsZNlML1q`&4`2TYPbd@y)=+nMAwElLg;Zip9@k4@=M52F*f|hLWtQ?&
+u)`B=&hvEtUO%zdLlx3B<*->PZaJjSPLnaUEco@6$Q>57ctkcSyx#>A{)lr)D7<AJZ(@SIr9N*gcNn4
+p35GX0CrN_U_xp#*Z}e-_FIS3{M%9kyF<%Lfqj7lruR6H@t7N-VZsK*rpBRt%C)hQ)X@G2=)E0S{9oC
+>95w2gWgqAo*zX`Gy4wf}>h9O+G~4qAL|v}YMj*}L+Fa9LL&n}TE7EG4ltsQpLiu8T0LvH*N9sc~0gO
++gkIW-AEqAWbc+z0H={gaD0DwWSJ&Tq;`NL5#ByJi+xt;S(QC2#D?$7p_dX2IQl(-m%z&GW6k(cSb7C
+DKtQywvDwE|Y6LBM2!v9&;|%S|=Y)V|8VwzSqMJ{i|*J<Ar^Ox-UvC@ZkkY7~iEVn6^UKyEg`PM~J2S
+U^P#h9Hi$hDn00!Mp;j)X64fFYd*t+rOlG0yAI`5Iq7OF5J3NVVJFhLy#&2-48#>{%inV(HNXXA*k_~
+`EqRd5_W-shJORgjS%(Yaf`*;fOJONYCJB=F)U9=0a${S3k2kXF>}Nbv6*etf@P3Jz_^2>EQ3@70O<{
+ZBxymJ6exg(v3o3>l`TS<VBbGPIG=OHnwe+SBpC8jgrjMlfNnrw8!`j7p4h7tU|U&kG-7a5<QiOyXct
+t*8wAOEm!+z21Xw?8YZPn(T)H$GmM}1A8!zygjF*wRLm}@B8TdU3)CLGEfClF48rBMHsRq=;8w-tTHk
+f~>F?S4cH{>iw@9QjEGtdG58glo`U(Zf2teTDa<Db+Z!WBfo$^KlUq3x4^MSb$u)AO*ac^c2k^>(n^`
+YHr>4ZZgxqq8?mN_w@(1q*%V{(*mISmasoytmZ(I+<7x=qiq5<NqLF@zIz!g$k_X#()m_Ym7kT6F8^M
+QRF=kx7vS%e;!2_OK@oM&lnyLkrk$!n*^PJgQhd4{=qC9#MWHEh5&8SR2yyEFVaoku)FI`((TFU4Q%d
+Bu>=mzL8^PM*t#m$=?%sl%1u*ebBaBHg$j08y_tfo1Y%eFGLZJ7PUosz80Uh*6)2bLW)8-#$e|(OC96
+x=_ImyV)EE!}b^^G+1A@*s1;s=%GMf!_h0sTe6gc@V#a&jF1;r@t(kjEHuzp3s;A3e<Ci|u$9TH%q(*
+M|GFh79QY|<P+9)=cyGj?#I-FNOOqs<QPUOWYB#}wB=yaDye_Ng{xv!_a?<)iFBd<5zDnYbE&Z}!PbR
+IK-)Sps~Ops*`o%mmyniAW`&c0kI^4@2Cv(&_EE-U1u1#v-ul080-H`6;BabO`VQJd`caDpaTcb$NRJ
+_V~@4U&lWkzde3=`hz-?K!IlgvOr;L<**fU-(X3>Bc7yTc_IStdQr&0_I6g*z!EVBh?$o4VH?@wPXQC
+mFnneZJS#Uv(_+Z4{8hZn?m%7v6;Ob!H%)8<0I)IV^Q?jQ9KpnpDA-Ww>ZlD-=7nmqm9AxNMF|FdjxP
+TpI0plcdIxJVAP?PY(ZyyB_y>(oU@+p$i?r0Jvjdsrmw*~|*5a4&*(cbYl%ez>RO9BBIfA@FZ}fl}{=
+?0XfCTgNpFEaVJi$d=L)PX2T;oYGW*{|~l@*X_T^4iFho$=4@%h`=Z(oko>G}D)a|U&C{`&Iu$?+SbH
++?v{z5|bJ7)U<Q%{NH=WSSnxlm@~WAcW$;11&F_?OFp4mt{6H)a4KL(N%<;prUfIh^|BYMlGRoK{8~E
+9wxa-4V{MYU<wBFLi>c$D>951i)%FykP}cOL*^a8(<9ey4Pv`==o|ST#)~Z1{u3~-y+(`{_j#q86g2#
+in9d%Cya&AGvlQiLi8_x(nBqei<OBfdq)S!+ryW4ZXX=Nt=!17w-%?bG;COO}KDXtL|M2tW&JS6QQ$*
+6O*5rBHfn`0ndW$Ae0xj-9RUXKo0%dHV1gmHdvBQ<=rYVsx=RDgv{>`y){0r<?=m{<B9j4`uos!|Spo
+Jsf&MG>1fw==6%Ujs}=zQWEnVHJ7X@x#J_|qE>O9O&PhDbEe-{Nj-WV0nO*bL0^tR}-5UF0jXijl<gN
+6M|>I)LQ1is>_K$&L5hg9XO>ZCg^<C%gf`TWzsV)F}c|MSbmI9lHKCxOXc(`SYKz5ML8KO1z){=QTBq
+;mI97gtZHkf$33Yx<1rErp_(<*MG+A$##^+*Zy*TO5bOz%}N!U)fB_23nf65PJxbK=ogwJz9QPv1`Nw
+}BgSrIh^79;{6RWnC`-f-<w0TrmMEQ_Sd$@IFRU=D^(;U~*o@J!$jh{ikmmtLE-(s(_F_4^)w~=4qIM
+Sw!+}P$OQm=Tm<DxICoGZ%-Z@4P0g>p2<@skuKi@Cu5F6cw9PIe{mI1oWF&^^>V;&)LA!1%~FuwP;L;
+Z!qrY7lvKko6z6n~^fviQil@}3#V%NoIhYe}**5fQ+GLVnH5PCFJ3d&83qgL(+o{A@W=gKS7qXZY)Wn
+62^mbO^o<o;(lI;Z*h*2@MP@>FTj8xT|WhbHG;KgB_jOrC8fC*l5(V)1St=n1K%t#?!Gvuoy7JXvK7c
+p^VsH{Og4hO#vd*xNsEUHlzufUudoR7Z-2Ti3j!<UGbl=zCKDWbdcudY-8iWJ_yu_<a%TUp9r*l{aKz
+tzvOAyB^Vt@cCh#1+HfQuP<;aX7Uzf&2JPb;3|NIxb<m7xN1@bfQa;y0{EDbsSJ@q6@mBL82q{qyyMR
+w1sbXA-P@u#0WK-n_Nx;mBJ_0lbK<?3cyUx5P5;-yhwi)v0^EWNL;aPuN(|G`P@X_^s3Mw0VpgzE5ip
+PA$;RN-XQU-P;;?QtlbcwkzqA)n8g)GQQugf|EGmQ^h@+>VRN^*93roR5_h1Dt~fN5%er{lBNLyE8Sn
+GM(n6(}cslcyPZj|PBf<vLyIkRT$Zn<`B#sva$;N&G_B9cnoIw?NljLeY`pK_S{DahW`)I0(|GMgmEY
+N710VHWnAgsmRv@!Ud-)J~zecf~jPam;`CnhGKv9zJ8u`C375}9~@br-n$mQd-(Yl{%cYXA!^isVt8o
+m;?7PRH3qk-n2+<UxUCtT68;TzI<`ru&1W#m!XsqlkF&!u4*a1^VHqoANWsKHrM#6ZR<O7e3$<)kISI
+QF(p)m<$PHp_gdCGrvt@P%3{h{uC<Lyc^G`LvBeeMDpR_6I)D<4xFY_TmuG{*{Y+ITJ^uR`7EYs{T=d
+TY8=k|0EmZv!)<!Fj_I<n0@IRMkbgdo4~8?&HaPA*V~Vx9<7TMmX{RckcM(W7x}jid)wt1%3}EbHcTq
+=fVvW4|4O`#>K>b4%Y>?=CLi9{+UuC?WAvTHSI|A`XQ3#@`c3@5?GW9_Oiyl)lr5%5rnFR9WL=Z(ahP
+5lPGRPUF!Y3fhW}JYQX2o?Wz2<{edk2F7OLc5y&<u;;;l@_zAxCJt{WW&jiOGe_>oX*U@n%0G@r7y-M
+H?vwl;KfJbrX;9Lvjmr9HlcNhX#6AaaRfsna$`0cE5xxxOB+)~0DyPMkKk)B`E)9weHO*(BN{6U25Oy
+`Vym&g2P|p3iLngP<Kn&VaE1ZD$%q-}P4*Z=MuvWv;)|{prW(M@5IR;qEHMNe0OaUuy1*#FdDG5SU;(
+ZHc7@{}fvs6q!?K<aA@JPRX*6$Mfc2fCV3K=yAi@@X^q|+LIn+yPK0;^1$#-wS+cao*X(}<BqGAd3MC
+U~&x0ezh@&8bE0&tuRmUC&tC1SSh+>blnZ9Yfc~@J^WLI~caY{;;?ym@y_iC?AhJ5{02nqY7<G9Gb<J
+orD=sbvC8hi2Y0FMF!`ay12u5U-T`Ws1gHx_h&>~topkhQ8RN^zd7)$x$|sORp@cS(xrRfSyu@zKg>8
+|ZtyY`Llz{KIxe<0De)!d_NZ3Y8s~$?CgD%S!i_Lj2UoRuA8b(0Sz`Wq+BWF5_5npVP^lbsBA}D^d3y
+x;ezDATwLxkn`u!~5z*?MuAqY<Vm|<hPxQ=&dB?oWYnDH9?f5gqs`X9oa!HwgV9gWmt%snZa^eaf|?X
+W9t9^I}N5e(9yx>|CiQ<ijaMLQ_&3$Ad?ofuzf^W!A<&txOS>Vy?N+TD4!qwM)S(W$sTg`)8ldbDK9Q
+>we+6Cz}+j%S$nQ!7bfloVKO?ett<jufbhr!}pS$u*=t806lvKa6RLuoSEta*!el|CBkHf<sD-EV24Y
+B4)<##6&SEVZ!2{6cduUQYrLpRycrx7Q<ekDk)nPBoicm1v46NS-O|2HAbs^KMnA<O1El}W;r$yIm`j
+p#<R4tnysvo9H>>>yz+PWm*i(JmGsMSbmw0FU3gk@k^ispbZc4<@U&%GkEb8czr-~rAQ(i6ur-<-vb(
+}$Z7!JG%bgyWPcy2`vOn-JP`Zcbfd=MIJU?vR=@9G&q}!qYcNl;|?%@=5FXfz({H+=0yI9E?iDeBBH!
+jzh!?V?<pkOs;eZ}hMS_iv5WW`o&r<Mav+sNX;#YNPV*~S!B_?c5o4>stq;t__u2S!<?;J2i}Xjr|`X
+f83#q;h0aWX-tI%<Ah+wJx!2lZ_16df<4QA~REHF=!<fQ}N#w|IDx~6DWV}sspjk==wUW8#-aYoXJ4R
+Jjj`J&V38$eSt?_FTROrUqmnBZ{imbS;^3$!Eq4V=<=H)78Yw0b*%m}<^}@+oZyMci1YpuER7l=!C_z
+h-9Gv|aJHoZ?9eeX4W6{4n4maiMzn=ah|M%CFbj)WvIR*c#*hWd)u+7WWuaN^0=y|lb@)t);-MmQEC3
+PP17c^g&m{34cU29$i`#QmSQJafHB1KFh5@x1s_)c`$qqnN4-qK06~?8SWu>*H2!r-2h9Z~j?}0r!Qq
+Nl}E!4fHjuI1`;SmN<4Cu-P{U&ltGj1q>yZY+dzK~(qzl7O84=V%A%CD#abQJ6M>iOjQnkU*+Ti3_u2
+du3_E*St1(K?2-74R=Qildc@0gOVQy&oz+*n>h+AwK48B}K~FjW@b7_%j_t4i%yX)_rT=eE|dC@a-!a
+kmDY7u&LT*EIvz`UVHW!dJ7MU4$GacN5)&gO$`4rs3<Eq)Y(0wiTdz|>LdL87)iBM7}IIF7DQAttb06
+kWZhS#YW$m{QZNqyj=0!T_|f@7t<p5ypdPAvCh0bLN?v6P8=>wD!0#x~uD6d3a&#5l?Mv5bX<sfc_jG
+U+{WpEMbmy9Wsg=Q=oT4r4$p+bP=N!wd$J~=S(rEDv1mTv0E_JBCoywW(D#MC@8zU9n&D`nfRhpmaC4
+o_w!psqA&e&uLIxm~CQMPjn4J1IV20F$Q5fFs9niug`@mC|#aOS}`_`qpB@Ia11fB#li<5gCamA~z1D
+rsI*<s8R%Nj-^%F~%Rv#*OQbGYmJg*bQM(+JS`>0gUiayz7<a%sm~SYRd_4`L!j%K<eA@^LHT35MTZE
+x<69=-?sR3hJX9Xae&8uw(iI3H7k9~5^|15s!!r=L0OCA@YXcM!j2W0js5kuk4yywo9X?NAE!43Xm49
+=8JdAu;CdJlp=Urjgw&>&Yx9MyaG@Ml@qG(F9AUQWZSt?r`|WehPtn0gJ_2ph8;5ld)Thn%9a|mo<C*
+Cmu>BUhddXL!01~$4hF!8k%3;j_;i-SCWYjM$<@(N+jwFZ99GZ2xbs@W;^?~*6!R->F4eP;dMV0Thu_
+>s&zGYFEHh!7Bbz@8zqO(zGDLl|JM8ZQYktX=wyAB~(S-S$C{Tc5P4PH}t*TzxM!ZEX5rC11^#pl4bz
+A50E?x|(R71%~$wR(sK+o-E>J+wT7<p^%@#6wqm15NwmM%-~<<R}2!5jfgOBk{$Cmr7z~M|4IIRhfhO
+Zifvi84otlJ^XA3h5Q^uFxEBI8Xuf0hY-g8`4OFm8@Mg;*Sbw66rm3sR7nynqDcIx8J_W^O^RO1w|Iu
+*C&zf9V>^?*KEo6Jg)`0;H=e3<8_>GIxpJM7L6bS$>4~|Q(Q%Y_rAPeE96PhQ`6)R5T-dwjc>rfq1|^
+G9u#1c@-+}|9V@fzoSTgMe(u^z3F+T_#Z4jF?M!l#3%)p=m35o^U(ZIx1ufRnH?i&f9#!g8LMnACNLB
+u#fmEnCkST2jYZHg(40;Q`Abi_fDv)5<I+jowwj&Kv%+Y)%_POnN_bj~uO7zEpk+yxX5Dk+Oc@_@!<N
+aK-<g%bGI_|M)6<okH|Z^wm3D-|Ag6#75f?SjDu0Agq_ws;3P%;XZWS~nETYGX*Oe_kd<^zD>~mi*+k
+vI71}4LBUNKsm&ri=vE%Kv9Z=+D&HfwBZs7fd$q-*Ck=uDb;$+0bqH9h8pGh)hXKrIp*<KVCe&4HuVU
+DCj!djCE5G-NEzw+8-^H+A6)aAgsi2y1a{zC-v$fu8=fiLTK8!+uUn21-}wgWkKBoUAW0s_0_t_aWwf
+vufQNUn-KX1{PH3{mw%+A-D=9L=<aDqyARnLNFsr!3p?1iY3voExkscpjNBJl*{#ei0m%CveK<z4huz
+@So!fQPao;`MsS`X|UD52A}doRr41zS`hX3h)D>4Xp3<XiKgl5$ihPpLCzSSF{c?y5WP9_~}i3{q5)K
+&_}km~d~%Hr-_TJmK2?gPmkNKt?!Y3ny4lYmCl?uwV)aM*F^l`z$1O2?#vLnlVucY`cydeQXl>_t-ih
+vKIgWg+)2z&;Q*8J*9F)*u=U+5s8DHvroY+Um?Q_KYV8p6hZCY9nl`@;O%fic|FKE(_I`9rU5r!KmVq
++)V9F}uadQ1L&N`Fiw)*6=6M`$vIWc8W3gS3Wz`;XpLsR%%qjCw0Cn1V9>^U-FEH_pGBd{8;bxmruyp
+-Gx7mjH(eG2Lq=>{g0oNd51|j<`dW-=lVeu$BmR5KwC5v2?RT~AK?^%^on95e-0dkN{MJ4UobS}XH5<
+*A8IFaJ3NVslC$WDPQ3{$T0{+EjGoTW)SSPMIYPYiE|^~SVdcE>ga1kPqP?1%pj4f8+4Xdji}8fLxE>
+ZJ)$3&zoevv=TmsiGL6kq9=Oj)`y-!1$K$yW(3)pl{X)3mB6~{M;ioh#Xuh6-2P^+z+`1U=PBpXk#jH
+K*>E2Q0Cyv)MnTrhHZWePgNGtYcn;qF6){ic7lZV7K~awO<?+i-1^A3TH1j>I>ZDQjXj-m@65F?qn$Z
+=TWG(W2rW`i#yOMJJ)B@(<R?^>$H=~NazGxdmRbQ;3SY8L{)Px_wSDKceWuc@i+DEvoa>u(wgr*6Oz$
+#)GIZw9=Pf!E8jo7{BP?&%_d(2r_a*OWVwNI_c#!p%IB~tz<f5*rr#-nRgi&lQI&!-hn&Fj?@W}1P;I
+7w2bZm4aQtE?D?V~lsM7mOj%3n`^J^JPN4LGo{7mD&9sYN|Z<K~m8-gZ{h1NMHXl?2X*kM_x9vd06!S
+k0Lg^enhRFsscSy90c81?{d!R9`d<g9!F*%*PPuRC<93*rI#dV;+GA8oF^FLfFM`4oxtU81l<O2J4CQ
+;TYW5fD0|wa40`!h`je%`=te|6_IQWVM}q`HDe~kQcL7RB&TFY8NtH_F%Ar*u&%^~?V8@|9p?P`luZV
+Es<ML=dqbbVgF)$@c-sT-4mMLUgR`h&bKi#i54zHe+zJNK;jRhn_Ay!bxbvvYuO?0XJ?-Z)Vy+>n{df
+(Mm@d{Nz2BDwa?1bHR>&~AmKZ{RXfb;h?ypg*6AUqT7b>ZdyjG$0j8cX5!Z_<D3V|BVVZ&%{@3yU6r-
+ys#)cc9?5`uwA0^%h~9M45d*42SwEa-T6X>LJ@_;~m;t~5-MjCFKksf3BGZ>hYC)%RNi$((~ncxeG;$
+f03b;}<oc9ca7o(j=IfKx2FMMb`0w7g#d5F@Q6tob2-l%({2bClYe4tE`-7a!oPW_*lHpU%SC~aBF)f
+Rf=a(HeEw-hGpV-|0B2qcWFk;=PSJBD&|<dUhyuV6L43SZLX>*%LdJzO0E_;@Xi{5f_7LHUSA^hiLD`
+8sEO{=$~<$|mheL*fjDztiCk02`KFm&I^Nz$$tpM$`BNc(r3%5J#k$gUO}+`;VsKw{1yEMHy3q-Kt-%
++{k$cJ6HR5lB1I00|G`}e)^9;Neya$R!pj1KQGd^(0&8;zX`vMC$D(s>=@Fh0@AyJBV+{z>keGdNSh8
+<%tc<YR?;EV=G7@3K+5=JL5`{$obcnmDhz>aEJq0anF70!tkrlP>?v|ahO0}dk!g5`v3JjTvP^)mg-*
+Z($YT}7QvXLAkwZj=6m#?IWcW+mgcq}0yf%Pt<bG?^YP1VL4>D_1pbSy(AL@*h6BX>=}9crqcD!#%<-
+Z!no*(4)PKE<(qk9%aJ}n7UWjLu2_ep>d;N<HKYG_KeJd<||yk91CHII#zOl2t<zG&~3I-JA3X*j15E
+1>0D9ZBnk3;k|@0FnKGdZC3lbE)eCwcX=!ppGC}xEchHH0R(c{{h3JbVx`b!Tr(AS@Ajcr^@&mrsKmk
+c-OF9U%xid5;V}-c;!ee#HvAs!)afwqG$f_*3%+0v6m!EVcZ-Acg;@wWnJzm=h8O;v16|9u#?3IzL^d
+?0laClQNROz)&*%mP6r?I*W<NldZa&+NTvGs#csRPuiSI61FYsRo~B?Yl4Xz7OUgVQ>K8;vM^<$*gHA
+28$3<+gik$J(<J|N3370_S@^xctIcRVK_g*k6SoT#Le|8Fu~Qx08g)O-`+WWVFdgblVr~WYZ<42xsZO
+{e#NaJ#V|?UVglW-}{~jygMJ^_T_6{DB4x^DQi-0#q39xY*G?>Fy*9wKs-}s`Y2CDaNZ)eck6uU!m!=
+!=xUhP<`VO5uR<emLBjm5M68>GeUdQCZ!F+~<?kKzV3}|M8xW6e<{BJ^nH(lEOxA~+H4vY&p$nG?$p@
+*%8R$JzKZ0!7R3^KCFMhc<`2%=naBPh~$`@d(iO*m78$|d^WRBnb?fBP=<n-<F_is*rNPav$zWn)|zL
+tQ$E+(=ix?|427?XR*r~aUYG30Irl~kX<yojIot~rbgrhBsBsUAiqjB*NqfH3l`P9!U&&5B{42NP?}T
+^H60w;MECq;=z`2+%{iWQGVXPdUu>C$$Hc0n_t+rRdR^0<sj7M@CFXtaY7gn_&Wy&ifJ<rafZS@Q$88
+9k~ux==$vp@r6;%p>a^kb(!DU+hctPXkf7C=GKWsbDC+sj4=HA!N`>M`CnMU-v$|cUq!Dc-?W%?e%%*
+32(m#?uuW7XS;&H8n^a<=Hxuvsm*|Ty{8UZz-4X6t@Qn%X@$T0Vcqfx2Biv`X-#B;>=Ec&r-0ovudc{
+2EQeyX{eZg;VCi;HsPm*q2br0muQTHIY*3)a}-6Z9n;+=%vCwGye_b^NulKIn956%0c8DS^9x;=Q(tp
+Hq;mYfS;?CvAW*dNVxijQQl@V3H7u$jHJ&qsW4onMRG@YFqV_qcg8{vS|F0|XQR000O88%p+8B1cUvD
+**ri1_J;9Bme*aaA|NaUukZ1WpZv|Y%gPMX)j}MZEaz0WM5-%ZggdMbS`jtg;K#zgfI}j_bZw`L4th1
+CTmQL8V`Drc-d^43d3$=X~{6G@b|Wh6hY$7p`kNx9`C)hL|gIP8iJ0r`rxXnEfRm|6uptmKa+7-Nh6P
+dtn>@i*UB76@cn>z84wA70s|<?y3eey;awtQBICR97Hvef@x*6|N*dZ_*h0)0%e8D8M_0L@6(g(ap3R
+nVR|S+@2xSxr5jCL8nBUy;S8HIH`)b-6FpATFi>Hy>NL^c0(j7mxoT^8u8(5$gkPwHXyCCltsf_Y|?@
+bazAbT%1;nR7TlsoI-!ZeoFm9ncwe2f7^*iYQPz7(BS+|5D0dIh=&-BKB;^@8jFC_@_H`Z$XtJSS13J
+*xt6yLdi(ksU6fiR@1{S8_q17R`#sbS`8mA!grDO9KQH0000802@m7R%ULjxDo{b000XB02u%P0B~t=
+FJEbHbY*gGVQepBY-ulTVQFqIaCv=JZExc?4F2w4p}83542g^T8XyA>cQ>p+(K~cE>_br)icQ;E70Hm
+~q}j0lzK4>XG`-#ew9pGlkq;k|&hz|>Q#<L7LJosgwG7G{K_<B4V3i4Fmgjk<c7t_6Xj@B7=Uvw+)6H
+A!=aoO6mIvt!WPH{-yA$C!U?ZlxTjj%2d>;5ksk0<9sG+RzE;*c)wN|AZgRSju&=g&plwX|E_cV7>nQ
+D;ElbhAzu7cuDn&wTtbmeD-+K~+Zt3l5-#TZUHU)1o)IqTk%9)r>+!G;D$3GyssIN|7K#<lDy+{Uw_s
+*K!GRV}hCyAmI*FgBckFpU^J2@bYch(^I;(8nLdA3kCoPDes{A?u*_q>nJuC|}#r$&MPaJ+hlW`Di8J
+kDM>X*PaAFyo`yD=<{n^>g8TpCu|Edp@-RaG<C|37k=FSh4)0TqVA>Xpzg7hTEF2B0)Y(<L~b>~J!id
+#MB9=B3E3;LhcgUs$-&>iho({d*iyLBFuS6ZGONManxGE5qw(XwW)WOO$avWjhotx(hDgh;b&>^?K_(
+Ej7LvW`Lm2$}`kE6r90yq{drjurM;EVwwX3>OHFSM7GQ=y$tvJ)GBj98wIwyA}41Mh-qP6w7<4~jq47
+lAxl~F=weWFcZIp5n+H{xL3lV}01A?aeC030XSO>)wasG$Wb?p#c~N=)F@D=tLfezOMxl1p(Q@nq~FS
+*yu$x~B&Y3U9$F{69z&Q>e_|J`p1f8)uA5anlOK3t-^~pfL$&S#vSKHnC%KKk=Z-<l1Zq(icfWbs6@K
+HManU+mW-f?m3(AgDH-54@cg}y;TiUm<BQpn+5e)lb%8FGh6X$q-ShrV(MoxF$9dYwg=XQ6890#z`={
+2p?US*83gv6frF7+dRk{!Sn&@%uavIaqkbQ92<A(M2La*GFGUYJKTe|2Y>EHX&Nic_Vv^?*F1JlyRk3
+wd`6AlCvw>2&Vl**J^sExhGwEfE4l`H864+`5m*qr)=r7a|44W>+d(WkqDo}83@Kpn7&2csvITfu=#S
+0^>yi9IPgk}9LaXOXvBQZdO<2F+hu+AE46CD|c^{LxGaPxog!96|#u{&#MAy&UYIjl3rNVO3-c91XAA
+^+m(<^=b{yY*uhFR#S!Ad_P#A}mi`g$+`GP+m6Lc_d9r5!)3P1!r7}loDo6`SYa>?q?PiG%4~U#=4!<
+kqM%ReSQx<T323ZE@EXse$s3xNrClAQ;IED^`%l2p2ug|Dvd<U+u{sIY`dFWb?}8iA_PgDb;r%ebI5-
+twdEAtCVv%L9?dOg96wmos&0fwxPA+|hy`-)xvhoX*|F<I8ecxzc%f4&gYKYpHR)DKu9#kXImYKR)ap
+6k^{%PX4C2+4{fj9cnU&y5qxdv`h4g%MHpZ;+0S(KQ2dD62n}52$|9rm||3L2FeDQrr>r0dXc^WQ-xD
+JbVC+zNs8swE5c=}l4DGo3&&X8|1wdHnI{EA@!#sfy~_meJH&bQwR<*XDxgsO(Hqi=DVUh@>vs+bOLK
+UD8;Z<iv^FCdz3&oG@WU5S$su*q;EmOP6wuxlrM&$T&SGiyg=72{ZH^*1#y+~F*j4Q<D+$ZwdPvDL=+
+enb!J$?!XIa3yOXFC`zR#3Ip`Uth(U49Z*0vwKtItJS>88N!(+izz3L!syIwGky~mCz<R&P)h>@6aWA
+K2ml*O_Etc+9(rX4008n3001BW003}la4%nJZggdGZeeUMV{B<JZDDC{UvOb^b7gWaaCwbaZExE)5dQ
+98L8urkW3tu`7zP+~fh}vc0EHXm1^eI`0xeMv7l{-|Dv6QizweGBCCX8=8E7N%j>qHObI+ZkDEgIXE)
+EqVO+|A?N~uULg*K|q4G0Jo1z}H(L@i?O7^x{2q@hYPHH)HXHsf_8l_665C*AHFC3B{Sm7|`OO4h_28
+?@t=KXYvo@})6c3R)%Prfn)V>ognQq!|~6DG;UmmRCi_#Dm{@U?x+o5OiO$40NY9<rVkpd0j|*jQ)mV
++TF<OpGi^jL+9D0l_cc0DJX{IcUIE2GWt(eHRn>*)PR{uv$C!se7bkSy=Mi_;of)!&1+s!m3h&W8TOR
+3&iBDPtNlqSIeBnvc%{>t>pTn>=wuH}X|U8C4oN!9W?4q7D$B^4Y@=K;YFLIT&boj^35o2JcQM+{X0w
+8o<h5?RAj^*vp<B%e`~WLwc8j){Qp~gpu5<z^3qbI6uF2Ww3yUw@?1bwH>#<e9U#sbXt)suicX%`Mi}
+Uy+*}B~CqNG=*MUmY>2D47KKBtvtgShmGUB8+3crk1dw1(3UmE6-RI0$`N`*3^xMR2RM;M&62=1({9j
+};kJ2OTfM+ovvh5QUR;dcAjeD;v=R6HL*Hc+jI1*6^|#_7CNd*7Tma7-R<}+a?Z#&P*proF60KF^r?#
+{*>M&Ev-iw>mjP-UdTrs8nPHzlN;4C+yz9zR)imfRLooI5a-K?RKOlcCWx4V>0EK^hgA;VEwG~<`JQZ
+t>_*R+t<{e|zmR8V55ix{RJZV=jxSM&1e@A~go*^b9o2Kn4XZI@xMw#?@5mQ`XO#XUxrl>x7p$%(Jh^
+sd#tSA4FOOMsG<OhX3z7yj0es!kiU3>N((_EZg@xV9MeU-r@y9C^q~yT#><J>L6Q~zPxJd^+ZlLTaDY
+#;}k?NQbsv#iE3m&*KEuac`m@6r2@C<9&8K|VZx6#7m0u|VLX&r@wS>77NdUq%<p=$v1n!B{~$=ztN>
+Z2d1a1D;V*60r3bMZqbvM$^T{*;hw8(-}Na7NeP{^FwW=o>8Ds3X}+b7wP4Av6+>hH}DZ4Pd(m<Q)%>
+T%@CoXb=s<t~eUJK;C?Pe01WsMadCR;qPdH(dj2>cJWGmDrOT_LpU9KDFcoh>-IW$q%X8H*;WM+(g0p
+WM<@a82vAhcOU{ZAv>PdygY2kZ#7JZ-+v+VWEl_Qv$Jb;KIKcKyKh<BngBxjp9h_<o{Y#TKNHp;rq?i
+T<$HbaDu05;3cEX_%Nw`?Wjk_*49FUF%@a}SoRmq+~_8E#i*R^}kPIhhreulszNnzxDrJY;I&>CXki<
+ERx+Rm3t!)qp6v;JwGkU57*4E)2#<r3;u;nT(D;zr6!&v$;e=V|BI*brFSg~wzT1)%bOjGtIe1`CiPM
+{r%fZLIOXK1<7`gO$VWiLKPtD@H2HE-x;#tJ}@yV)I9KvB|D)f4jW;a`x%^I<i27@&ed9Rv94tj$E-N
+7Y`Du6B;5=njcepkb3e75InF;fa>*|R6FhaBIK#i7~lyD;-uCnhp>giTl}hS%V;RRO6J(_Ui(j;r`-v
+<7XDl!Y*oRq0DT>M;YcMgnv4Xe^L04r>`u)B6B*`8Jvj6oxn|HHNLkT?FTwl{26<9Qrp4SqLHguzqgh
+o#kEJ$+fengRFR>sQwwPw1-vJQYxA3#WuKQsKO-ER{ED*x)`(>k!<8<LS3}_5rGbsclc2{0Zu&6VM+U
+c+|kguKNNgNow?jJ22;9Kb0J}jW|qW*v4r;N@iwDbbm3%u)UKokg(Ahj<m@(k8qqQPtUBE$Y+;=$3NZ
+rxn@t-^KU)ySGQ1+Y!}s31}Ccw$|ATM=?taltfeCVcBX!fSo~YX8_d5?V;3;DUC7cQY6GiA6K;6R>RD
+zir<G3;+kXA+nTHF)@f2DEtugQBQ5Br%d~231{GboVBb3fRf=0pd$2S<{j?kj^aiW<>1Vr1%$Y<|MZJ
+7_BMjTtMvgZy_~lK=j`4tiJraoOEe$K7*mW#jNt}WQra|F*yX&Y$2}uQ*^-)382h4Uy93Mw=S~1LB1_
+`tU9h(pK2)ITV$^JdedNGitvLx}A3>|rMR2>?jh3O#YWcuUgWzToznb*=vws0lO9KQH0000802@m7R+
+NCe|H}*j06{7M02=@R0B~t=FJEbHbY*gGVQepBY-ulWVRCb2axQRr&06bk+_(|{?!SVNQCP~!O438WE
+G|LQyc#q}g5c7k*jos+#NFjtE9ykb&erh%-Wfh5QlcFv=!Xh{qX#)0&ht0JO_JnqR5Btu#YIax+Dq0G
+$<)v#Npf<+51r^0X~b^F+nsxa(R!qNmis~RW_&tIcdOV}b=}kMWZR1asYHt}8h%0C(4p&kCZ+kVjvXx
+GzP)IVIeEn^m6NxuWj$4*&&hi(;l-~**RT^atK(f!a-iI|v?;2F7gA9*$g&bOlaAV#5C8b^@n0Xx*Pl
+Os{2ZMq+AZG=unY>q&U)#;%)`gmeJ}bLC6t9M4qR4_OwVdssge$AU*d#v=$o8K)hlr!M00Y2@&&m+bA
+m2*Oug6d(z0ynft6);a&l5NR7&!xXG$Ia&YJFx=nquEvZ>QZ@vf~IFj5Dfv(*WK3pDzIbU2%{{&53xC
+s(Y$5TO4(3@2MR9`8ma7upbTe$BR|gne>VmZ@aTHYbm0zmqGYt4EJ6ugAxXoIfWYM9a+5c%7P6Iw851
+@nMjPTrff#zH3=cuDRNe^b5T<@E{A&V%2kPpd&4_(mFZNuO(6~9o1w5QvCVJVj$OY0peB94sfT(JzWg
+D=C#`EZ^ouk5hY0Ez(KR6<o{u5wtli9=j6}hTrgtLKvs;R(L$NzkxkMw5-yFmm0$p%YiUJkUals&f7C
+CuAYtSrM^NC<w*+SuWt^gU^cKEj+_Z=LSjfrYiuT)sS|KAKn}qywbNf8e6C~@#*EvZv#U;;ZL+<{w;h
+#c0I2`CX5TM{uU;qvHHW6DFj4YFcwlz60MS%xdoQz~vIPEa<OccfhoSw?P4N^Jy69g2v%W}es-HN1V=
+i9TKoSmN=ft+P?dgE5@l2&Jyo5<=~0L1PBB0_A-I1B`|-c0Osx6h)~{Gw{)BrrFtpk2q>I$e$hGt6St
+aLW%QHV&QBYFLYdWJaEorx7~5g*2hkr_KVh*uE6KWU{=X%>Ygl5`i$rjEZm|IJhEQl2#}kGJ>H_4bR+
+Y_rioIH@|4aHG1Kld$xKlj5<?G#ZAk+9a#TLlHzy4tsE9Eyl1oqd$7K1pR^+^jUPl}2asprCB~^_5{h
+J8b<T&I`V&c3zqQGNlR?rQvwZ0LJGk)e@pUVQo)NWY@E0U6+U5v<7-`vc!{Pr6rmh)l4MFXJFqUk251
+O(J`P&-_wSsuzx`-}*kUI<(zqMZsw>P)2EvFY9)oidvPGssZ1gII`rkW-2=LD!`*<4ycd?6u^BP%EG%
+^lJ@1s|YSu;rm?G;rxfLj<Hte=bo1B;*UiCmg63ZGcM1uD#i!L0Yhj1LbWpa}T^4dchi$(@Tt!Z7q{v
+2x}y}XVR;Qk8s{8k>bEeEvhlT?s1=(x;Sl|0YLh)<JvP75b(GEEKqiX1iKUzn`94KbBjrJTv1z@>}d5
+vi}z;n`NGC#ax~BuOvD)0JtV(ve%^Rzg!j<fCO29qx8S-r-X}EqnES`D&QjG=teBfR>o`D2YvtzQyA9
+k-TiUiI7vscy`aX^WDI11S)|%bie!YWtFc~usbE+8$;ZX-JM6UXVx0+lbyM`-cl$%9}$H1e5{77+v*<
+ZREaDKac#kO>4lneoP1cXm0`z0V-C<`K>dXSnkQ%IOZ@JUAk3v7PfLlA|311=8x!>C(Z1|TQ{2}ao04
+qOFO0(?E>fS)0WxqytXP<4P4u7L_@w(nV`AiSeM_7>?Q(!w&sEc&96!qzARYZRi38mLjQB6GE&beo$r
+Xc#Fif8PsZ?KA@rP?JIG2Yd74q>m1wNP<g%B#O2b3&ZPD(4n__gNxD#-R(#ElnVDUi>>|;9JAPNj5?M
+ZsYh*EO&2+6&^Xf;95eX`px?@Hwkn3$8H_?i^5ygUWRb2sk%m-s<r>LYiyf}RHy-%K>y*5MMU)X2)h3
+yfYlfCPG&P|Y2;!09-?2`#9y?kviek<&61s<LT;V}%&lp9&g^%b!;n*cDUrXbC(X+0Bw3foGJlYGuFA
+)SfQW#^B2`s)jr!zmZM!xdGESjh*{C2$<x_Q~h>#r*qr|v1|r?PIg-diLXfXsJ#LC_rWMi7cR-tj9)!
+>&{>d{C$vb6!E~I%GIrQM(-!{#aRb!p8xT0k(R9ZRcj)rReo*^Y*V@FTmf_aTKYghW1oK@YQib%LbcM
+>zRNyfpFe3XX{w0!ekd+G2>OuV8gmFX~Gu5mhB{{4aN}SakE}cDGsfcBax*5=BZgiBvDu+ai7>yC@^x
+e#6@6Dm&Uosh+&)Yde5u<nCdVTOsVcjsy(YNZI;ty!VcY*H#VTL_KNqS#jXx`Da15RFW_6eZ55jS_~a
+S>gfi&C)Kb$cE=7Z_iWR}W9cbVU1*qeZ@qH$roF>d$S|dmu2;hI=2eVE16m%O?x3s4gn|(%dKhlxXQh
+rzp&&ee_T6hKlYijes|I_AFe~dyun|924rYQjAG^NQ|+1HA7YQFG4akOr?!j^GNxIhObg-W-{3&5dzk
+f^EwP)|+j0jrJBaG>4<3b!-VE|2I002F`rn`YSj6MYS}ZCwULO0L*p-aebuJ@%{Dx>3E>A_FOHa%~Cb
+@5aaCfv$C&lqhY94h)fWXe}EAN<pAqkdOGR(cV;KBYN+7%?!_&$&y_oE@+eFlaWBpvI37;C0>?0C7;l
+oF}d1sgy{fEdA{Aks(`Ld;PCcaO=4K-F1^{Lj)1dGZ?K(u6NuZm)_S9(l=cLSb^-h2_}d_)xs{#mj1k
+W0r!b0{rTJ6BcddrbhfW=d$=)&afM&fcs&ykC@Yuz$OBY}9O5P#)g{h$i$=RRe8JaCuXVR>U5K%KyBz
+csazsJRZZ1Dz*H{K2`L@kzxc3Pb(Mw+f9g5}B6Y%T^naH)``U;-;x+oz3dxJ~Yz`Ih!?&H&vp3X$LBd
+{dY3eq4@(`uDW{Ev9g2Xc#dDmm4{1p4?0?0K_VSe9Th5;iI8z-w$5}$^VO2)EOu=<~x1%VG*b~3xhE>
+6O5T|im~v~X1#*E68IG`g;EWm=Z;m_$JxX91}ze0QbC%aC}$|=Bmj>oVpwlaG2zQ>I_fdHdI5p-Fksr
+jUOhPVSI05IGd5NP0k9Ym^ccT&<hF&>vVuawB|}}IeJT&MokAhZP=6{2N?J+=9nE}rsd+pc`Bwa1go(
+5B^D`*3D~fe`=*xIi2^ER$mFjZ^3|wIt5kVhGFK^n8$@zIgenJ+rMHOU1liMSPAv_bssH<HAqJ^yz$?
+IZQz<~DLgmw5ZsCl4k$=ZC~Ac%r}^k{GZzprVl#`XaCDC`1n0D|HJuMjlNh*h@rSj>Zj-6ycNtjO_-h
+oo;*%kf1DI=X(E0Ep~asrrH8S(AC%A_R+dP!~wVUDo2<@oO4D5O-N9GGUK6Ev;w`JL0JUujJ;|ZIt5T
+ytat|trors3$GHCc`N>)cT)l%#N&GH<=Z2W!woP%2!>$8FBv&9`M4GCEG|k0CHPni4v$fuK7N8_qGGf
+z#zwp@R<*sxD1>iWvrred6)G{bDp|@+yRkd^PbUdSbcol3)b&F&5jRGuEt?5i956m3wj1yZdGh~c5mt
+YrWiXCsGC&=}May;&#B`TmG5n#yJ*I&m`);ek-D|sfj3#s+9aG#P)cIrJKnLR)#2c`+|EY}`un{pbqh
+a`K;m&dmGh%JfV^9W(sosH%l9>(=Mj)87d64BpSiPXtWrVLV2)coHwhi$b^CUJ#;_X3q!N<}Z#@k^w2
+iX(<JEh>*5$zRri%flH=gn#~cb$?q8mQ1qR+_CZ_X@S9N8IkU)UQFL5pGO<8ku81X!nTi+8;dX&)+~!
+ykD&NrEsXu*r}RBDBrLX6jH3^E7zXNHpVEYffl)-b&Yyn#mT@hoDM3T&JkU6Gw`AijRiI}o--Mm6V^p
+T3EP`fUu%Zv0#N(W;Bnok5m25&s2J?YNqBlew|EF*0;=K$RC!Qz!g;Pe)Cnm$fRcQP!!uF~cRIp*DCw
+?6e;G8$Yy>w=_Fhzw70Ua%x2NP|Q|E}h&avrmNuCye0VKGmS6mEz2!N)J#(gN)1GDc1tvy6P{+<j}Z#
+x!)278tMDc%+<e*OOLrix$kHb6aH^iY<+RnyIrzK;;nosZxba=OQ#!f3yE8&zqYA%0*oo@G>`JEmEN0
+ss+)Slt0gAE|@)TDZJG=HGwLqK}8ab*N$uWqD?B*Ad6}hu6DeK%^ZuMk_mK@!N*E!Od(<AIWLlVIti@
+dS}0p4y5jzxu1_5Wg%6K3J(XxOk<ne0PS0S&i`LfO9KQH0000802@m7Rt+{9PwfH#0I&xD03rYY0B~t
+=FJEbHbY*gGVQepBY-ulWa&KpHWpi_1VqtP~E^v9ZRZWl6Fc7`xSB%UhU9u4$;!-IbSYX8k(C*%<Dsq
+!aYu2?R+o2T1e`g%$d&>oh98!Bc^E&f9^CFJ5HV&#r6;5kuqsr(bxN|Mk9z;02;ZpLQ!~||pq2W%O1U
+@-hwZ?YU+P>6IXvJj$4^1sG3ShOU)BHQCQk&F>;*i!x?+sep<Hr%u^NyPvEt{iC+U<LNQd0ABYWpZ8-
+ix0&wSDct=DVrKJ=H>KPfZW_!_D^Mh#w@cEtX639Ui$*#K!EvaAhkr_ce|Yt7*ML5i3MR+BhL?D)oLp
+VRVm<JW5oKd&Z)uueQ(sj_5*z2C{+u&8DY(vpYMq+wDkwZ;7I)#0qjxbKcXO@3;vRiw<B73#d@lRrn$
+IoEm_<tTVx6iS#v4O;jaZza9G^#3%4sD-7@Lx{cu0A{E+WL6!m2iY34v4#I*x=th>Hl{~`^p&{Z49^3
+(e3gC@&aMUHHEDDKNptK8Vv<Ck;?YJa@Dk9FsOsI;jhQp%06uS<cxLNcCq-naP(0K5lcSX!LJ$q@1wl
+JdY?Cmed?c>z)o2`-=#;n<5CWS&O+WJ1pUZ!sr-t&fz7pE7x?1{^=ai<P}4V3l*X`ad@S^tHQVXT*_&
+j<WpYM*3>jxYcC!tl<?X_tc*WrKFaR~;V-7_7)bql6~6SZGyduU`aOec`z%DQ+N!mu2qFF#`ry5HF@Y
+UcqyCwMxPrWbHd(orF6KFymcS+CXt=)T1AbVRmOlo(0kvwN5kpkW*8a++o~hn*cArb5&p_QN?Z8YSoE
+`&$jIDWYiAR2~pfB#6lf9W$1-}LlWWV$_qhIioXe4D1$L}iw?K~z59lRBLUzJ3flLg;5393f;Mz$V}0
+Qk@6a`d8kkdT|E+4F9DhXX@q79_AUhdev$W5kSD2+%jZB*se*8$LH8)Oh89x=;k)W(!1d=lUx-^j;xK
+9w^8R^`$t`j&NP(kfgv>ehWy^a0=P)h>@6aWAK2ml*O_EsNWs53qk000O`001BW003}la4%nJZggdGZ
+eeUMV{B<Ja%FK}V{dJ3VQyqDaCy~SZExH-lK$Smf~S0NJJ*&oGuU06ak|?X+dDDViG7ZDgT){a)Dqjx
+wOZ1OlAYec{P(LWk|HTlwv(B|;)KCO&DUbFUY;saj-u$auDVQAl670oPV3z+s|vQxBxiY<Ny)Jy>sY}
+X4i$C9u0`{KODXCqUMz06ww<V;sgP_}7k$ZD)^aS$nB+~?W*s*bvZlFmHJ4;n-7PB43sK#%qJFH(IxE
+;QyUz0a?2i9QR0VHYo;BH8l%m^1o9dureO2)s=*U`8?wQy%b=%>%3%}nk%eSK9?VjPfva)2Nlk5T3Qn
+$R&%i>ioxLh&b<?$klqQydwSJroTK$iJgOY<i8a<OUa9ozI(-qm#}4GFN;PGqI3t(y*h121*uU$e63x
+@Wg<aK*aj_HWnc>FL|^(?4Il|8d2>ul6f;DP*@|S4{`J&dL?L?VFM>RPRPKaVn~gw@?-5u*zYQk6X^m
+Q!EKKErn^A?~0lRmop7xl!H`nl<B2qWUh;D4ZWcBb2sXBs!HF9&lgo_1pYbailkA;^R}(q6}xWvgQ$D
+?LodqWOte%S8VGm)GZ0gj9QLO*qg{&X{?ruC_iL04r5hzgy0a%)q0S)Syp*xzI6f>QZCbt=R`S6V!y-
+1k1)<|X#_LhKti9u1+U&b6Xq^!gD!it$P~VDok9B(wB#?#<ln*)^>Qpxz^b?sLuaU3n|7q94dhP0o<+
+rNrnNeWb4XMBCdBgwFi<a+r)m^Ka-~cWE2W(g+ySB&O8ThtbFnGX3b)dc}v`Vpa3I?Og)+Jwst4q-On
+JQAr0)HE_W*XuPkOOMES{%-iOsz%99RmPL;|w0$WYbg6X*yr1pAN^uon>A2$ZOKjVTa)T2CE*z3<kN}
+q;=mFV2nXQw>-Zeh!#ys)zB5iMAe1{foV}V`L0O|(fWII3#Fixq+I*ewCHx<0D*U4)=V{y1H+{Epi^>
+&$!f+2(RO`S^6J6N*@6pztx0=S$JEw?_1^gQ^n~W3p`{#n{o%u<Hb;vE8hQ}*#8~_owCs|~mT6jLJD#
+S8i^Zbg8<yrR2L^(A^s<w%ES|!k#@;Ot+0lOuHv6Z@P7-}mWB_sCJz~RXQEh7WpKSTvihc9uP&L7)&4
+lEh^;<^hZSAyd19bGLW)l1|IKk{86D6ty+knMWMuL48fAi+wBOspG-R|uS#+AvEij?VP7gS0U+NO#<@
+nhB^$CuHWkT4IrFNYi{z@ia@W#7=y2nGb0o$3w<7#7BX=!(6sD?U$@9rjt;0*o5!@QH3~)<cUf$h;Lh
+u!RR~2d`|+jVS<x0Ag6P$R82p^FXq^Z^4Ln3`9<}b%n|r+lHFsdbM_r*h<6_cokpYT-{!sUR|cQmmkv
+8%Zu~(w<u`@s+cy~dU4=2MYRlgQV<)O4517D`@O<sz<lUH!eD&3!D<F?rOMQ6cd<N-hjHkI<Q+s*bZN
+Ro`#{o-TW9$Xn+;lW7!U32R%4IY41Qv@!n&hRpmJ6c{z&BQI0$ZG=SMF{ZaMASQZDlnkebFVCmK=tN{
+6`VC$KS}K3OVZNjGXMGFC!8t2c}WWjLs^4Im}$QPb8BqJWLpQ^ba;%0n13fbO3@+42pdSO%14UDqyk*
+A<JZT9F>D*q^dea!0}OfstUKX}4h>=!fh%^m@T;Q00&0Qx|6q;@Ty=+pe1I>1-fIZRW6eGO3zS`ZGGS
+!2o(TX*<1QH&)X@OF{oyj3r<PDh6gBkUVb0*e*CM2D!Defuewt0RLuv*$pC#G8UExD`lP-{Kz|y0X@t
+SXazvJg6ZM>-QM^TjP}fz{fUqRf9W?z=Qa2Q)x=jdP4S_>wXe`jfg!@E2qOdtqbiUr!c`c2A*|qFNn*
+XS6-HB{JCLJMvc9W#&?^Tcwr9px&|2G{Ah`HM;gC=InuC=9+kmmhl&FeryRMNZ$H#Y~+xBY&`o{{K9`
+E+e{um5Bkaqls-~Y$&*}cf`F(CAYLCb^wX3SF59NOoRBzO%Sd*t)cGd7m)kwC26!CMIS9BTv?-k2fVt
+P?v9Q0cj58{qF6AaUB&X%4Fs8*#$c5D!92Qh3#LRvsyEBOsLw24^T6T4~N9qihGzjvAmg=v9o~7!0GS
+(ym8~aAbW?gaNskMms>6@(M9S;Y+pWlm`}DoCEYe2ZX%t+Jm2)_%2|*lno7WbkdeK68-)&Bzj^6LDg7
+wr;QzPG74??%?B35@5JoE-)r#A!xn&5MRkb|aanfHkc5#0(NdI5Ci-9OGrU^;P`%Ce=?1IOuEACSw%^
+vUBZ+D1mHHj5wM~?|jhwBqQmZ+>CC<BT<VfHv_7+SHVA33j04JMgN9!I7w9`dchK|=2*+COv|HsBwnQ
+1`JVzYOZ2AT#Y1+WE}M<7ho!jyx^2Irzy>HL&f<4$PX2j<o0LxyJ3b*R9`$^<7g?Gn=r2N_=H<U%(HZ
+9rXZ#9fbRF9128L3l#cVbwlNknRNp{XEe-CGIEwFspDg`E<KqT-wh#IMN-&@<`(&ECRp-^a1!VNDcv9
+aCqRO(BUap*-~0@yaH?$tL}(?6XKyEg|J%F&-A+IdrSnR8Xvj_dt7DdA3T}%VH(z7po0C_)_tSFyaDy
+A5aOSp`?bW>Oy^{2U5qc;BRFW{j#A`1oM<3cjdhEOTJTRb^nxfxHZ^waMwwa4{5Hsc#chatn2uW+B?t
+oH!j^<B#e{;FOLzjP`IyQ@U}trBUgInZibHu3Tb9$xYG~cUR;aAD#(Ds7w%LO~zo~oI6v5((?PA6xyk
+hUNdkAYW(4OHbrMes7B1V8?r@hVOTuk8mX|q9kO;Zk%$9H8F#_$zYiJPlFR|qE`!BMU(;~x1zi<)B=U
+xG!1fXFZyn1lQtk_qux9}LEw17i4?)dt<%n~~E}7ApZQU;b`2He`omEJ_;;|4G2{Ah5g|wuW-?NMKQO
+slkLO*&~8iC-N6#uq+#%gJ+;%A1%s}Nvy1U1Y8KfF(-iM5+G`dfL`_ltqFyI1dN7s(-8`4Z|g^B#ww9
+3t97)=a@+x~65BWxot_MfP!@hPZf=qiN;d(e9cg5>E^AkW@d-ew<hJd(>!-~d*$g>`r}%_ZgG*@w5Ca
+jwy8Ze5{QCPJF3;23^LN*07dI(p;XYufJWck+Km6t5@+>`n|JOh!Fh0M2d;Tu{`1bt#GClqN^zC`5(a
+rh)q%_KE@kuA=FhiA!P1^QVn#r`SYn_p^HU^aYs_($g!*1w=7MV}k7nCS!F`LHzQi;#ns$5{sK&KboW
+Y0=<L1mGhC_&I#(Q&e(HW{gQ<f>vHfn*SYm7Zdk?J<F=R1IRT0;C`Fq8T1m;ASW%k0DiTEw-UorTdzu
+6ly-Cmf>Q}0swk|`9obElVWTeV$7KY>e5X^DwCpnpe76k4Q&~~#a<LqxWg-N-4xi8sf5rrl6!!pJEp_
+$$Yd+^!HbMdCLC9rNj;p;r3aA_`-Ie9tHm@k@Mw?g?wcYbC$DF6HcoT&l^*pY+W)!+Uy6Cz2FxLd!;X
+9iQ@Lkwh=B3qj~DOHu0DQXv=A~qlx%$m(JwRI^q8b0;N?urj1e+G_N)L(i#nIFsE>JdEa?Q}7#%LAg4
+K3!yIpA*?opH^EP52xci%?n3MN(g{tjxR$yS)LAW~7=1sd^h340T6I7;<epLnCB#Yil&`~XGnK!Gp>X
+5a$R&w_PYxAi?(UBV7zCnQ-x>sBK~qov4ci?n0zTMJ$Eu4#GDa?-}`2p5EcTg+PQ@DR7aJ;6+GP+KXb
+3mb6a4q>(j4;-3(li{}LmCNG?=&jnC)IU;}<|WUnzFDH7KEY%O*%$bCFfV67k`hq^%RsV$uObI((c2Q
+Gv?TJu9MjrayH^-WAC?HC_#V0%FnnrEVXMzmmgePT{>&wSwva;Fv9RqP;|n!TEGZFJ0ybZECbMaYd~7
+lO*!roN6ZaT!fV<-~4cLb}_(d69OjFtHiI<15WVuPDF-wBUB?oB%h@#E(7x@H>gR?j&Zjv<7_#Z{Z$G
+>W!*8OTH9z5RmhtvQFJs_Gnqei5Eb)KUR5#BMuQKJ(6m~;IM{vsD+NI@uW5WBrn!3^;%Knqx*@{eVK+
+IOLGM~;yPL}Nug8VuR}m{o+#vOEVLRCNj`@f{dcCc5}nGTUP>rGOR=r?uz}k=9h^mXqL1JFm%E$BMmH
+(nyyvUcbJ7wCeuM5eRiueGV6%8pQdoNI?i>oE7wf(Ai$Z7-VvJs5|~qV)i#59f}ktEKXZ};F~^VtpLt
+1LlG9R&I_=Hs2U)}R^(e|MnRm~gE*{7dO$%j#-wXMC{T9-Y-0FeWW%D8-(~s!$PDEr8w(Edl+(HM(|J
+d|k9x3Z5=uwkzWMfzo#TmfqaB28?lF9-ZzVW(36GMj^5T)U3TZ&%PC|#-_{=7jy-O1(-gSwUBLey?%q
+A6`WHMbWIq~nA*lO626jeHv05esV*;bm1Q;PP%SmG(zBxwzdTh}lMxC$_)Q2oZqQU@+;gk$ql%Kn0-2
+=q|rr+6Gp{$&syya={K*^}X5+uwr}6RVj1@=7V)I=26zjv?!>#A;9)lcjgX%vUF90a6k_uW#OI*>sd-
+EV;hem)Sq}=_6j;f(fHdCc7h08Tn+w-cRIioH3>e^Ep)KK9L5~Dl-71;l(;5S6~EaXjA?6_V#*oEIy3
+WW)(m-b5w<{pkCu0Lwnl}TyurEm6CPw+&JXuz-#eV?8uL}Hy$(-K)Aq^-)-l{I686y`ea}%p;0lUQ4y
+K%NmgfuY1+EzDK3wvEgUyKIbxU!97f>td#}XNtwz)OGJ*KYZMRH;&<=w$zS&S9g*XDefJNnMHG_Buc`
+>%w0rTJ!GN^45(Bjd-Lz`1W!vX!<Z{(W7#Qm`fOe<g|B!$D6qjJ9!#dU^6VA;@XToIZ}`-a5(HCmwZ3
+5gv027EvW?|}6(U1ydBZlT{?xszlwawBSMXirku@GZBC@QeK}p7%+-U#l5$PVB4SWN<*q@V0tNYm(9L
+$wAXo06=w_ary=moP@;m#h!T<6VTdII{$N=vb~@?_00h%?;j=OBkn3ZZ5=Kt4ek8wo^GahRqCsxbAy8
+Q%dxQ@b*@?8+_m5iQp&>cJHQa|hEA)ik0fY}-0Y7qJr((DYIyUzZ~ovg0Y{%MzuBkm#W<%uU4F*kZ^h
+y`{^WNh<l<g`d=|23bNrP!g+$A_E(*lxd*8lkd-6u9*O1H&F9uaK1u5PJo@%0EXJTJNIo;m?%V4yLnQ
+wbh9WO(Y_bhr0Cn=jDs)t%1ya{!;Or<y=x_iJ&fzEK0ETcPhI$sAE1Mj(z{ltrx_Q(SL^CLwgn13rXN
+_x9vMK?pJp`yJtM`+T*^q{bKDm1Y7D<GM@85_QNtGktAZC;&&KgE9Xe_t{{d^0gugJx)>lr$6TWS%Ds
+K0b~yN}Ts;!?AQH<AQ0I7kdZdtg=h)w-;9Kr**Rf4E8S>7tD4U*}^1T9AK?)9Fx)S07FJ*G8q?4yNqm
+KGWzXzaKepe<W%|2fQ&vTpQDa5viXc$J|UAYlE*KU#TU!ruadzpl)qmgdtW4XUnp}gmbXLy2B!OI!`$
+^dCyk3Kh!;SmXCT&W;)Gm3O*H*>;!_v~T+=66`j*2Hekg+U_Ou}7n}+iwx)`CHid}RV6Syr-W-0RT4I
+}EnZ%4?fI+30F3<f-2H@b9-9qi{T*k$^;$<%k4DW*2ZPBc0h_P1r$r)YwW>P#Cv8PFU~BUS`RU7cn{0
+i1flmpkE@*0!5cgwL12E%PWt($k@9k&ICBu%gg{tl;Qt*>;gmxQtt?_ms3}9I!pX78KzrBZ8}^E56h#
+nchSE8rC>y)bt3U(l8gpGN%p&Qpr0!e2~fX#`>s*xv)OxBENPY%!16PW?!@^rqc^I<|T~zKi->vE#F_
+U_gA;)_GX};jGzk>YfiU*0L>pA>FOh04RME;Sevt~o|XPBP3y=~PAuct68^t7gkK_6y34b|jn7yDE%~
+vT3WRbwk;AFkrNwR7bbw&XnS0sz{0fWyid}3VRNlKiD94I2YfpmpH4-Wu!eBRag&}Z)7+R1vq~_kCW2
+#)DM$$B+P&yOsPK2rOB|0DXs^MV#+`^})qbtG@szr37PCfDc7atVcb9hu4^kMfhpa#!;-DjTYZ*{M}-
+op$I%Q{x_3_tU#xW|3~cRv#`GnxK_B^Vm8GkYA4W1fJHMRcE^iOOH1|2{m3)%iu38hl>AE<{c#71(3y
+mqaX5-w8}tei#<vY3b;*iphb)zlLd&bH%7FFAcXM%cR$@kqx26jH6NSyJ@NnAAn=_oTuwdikzaAWiWn
+t=6W$6&vHhCxCc@!Ti3n5@jQGDxc)oO=b-;9b|z#~f`@vfyJ6<f21r)c^}V@ZXzsQ-F-_Ly+f?Rt!$D
+(Iuh=aenwC1hCh796ZGh%5RfMC_9-1w^<H(_SbT*|<hlqVc6DQcy#~J<~L-^tkuAV&d_WsC$o9%V}&c
+QTGJeSyhBDt)-z;b2dnG~_Pd8YRg?0j1{t-wkO5b5ffRS_LcIv3GTD2Y5v>&GouUqsfr2}q#2XDGnfd
+ixaV08$<)hD7Xvc#L+Rj7QAQ)D?F+Y^Bg7EU4HzwSN>N@&6u1tUl<PT<tY(-utlE`wJII@Q+*gMhEaq
+{h02v>OKeoln~RWL~UIT$igpP1x7?%1XQ#fZI_e9fwJ-O8B&(6MU}OCx0x;dP4YHVqvpw-;j*ua-o_;
+U&+!qV$NOaTdvv$n)vv_+<r4hAP)h>@6aWAK2ml*O_ExFPS;?LT0090I0012T003}la4%nJZggdGZee
+UMV{B<Jb8u;HZe?<FE^v9xSlezJHxPZ_uOMUumKtg0q)iYQb=o3v8liy=#0mUh2LiQANrWkKOLDEKmw
+)f!WiMJ=a+4NC^`O;qhBL$AoVkdv3Z*T{l(g)#6?~TPu);0VRw-es1)&xTE*I6S+0+!vS1g%pwIX&?f
+Q7{M$@!4{%p}v)Dm^6Uh2=_8kp$j?7wMEkt;SkfS}shQsZ~L3wf}N*_WJztVmEs<sp4NS3yz#gOP!`9
+adf81No9Kqj(2{oKb=atV$<m$Ns>%ZW5@+ehpiK*Voo!5oDh6+HYWy@zF}fMAfuP$Ovy-dA5FPoShJH
+=A=nDKS$?Xu(tSv-1kAbQX6Z!?-3t{{0~<?oOpMiEDmB{c4W*gow=A08?;c^$oM8&ja66s$YaQO2`fb
+IGp$p~>YF6i5V5z#etI7El$e%vJqt4!j&v|H?EvXJC0=+l7zW!s}Ygi7*>8jwGXH<yIkh~yekyFde*f
+0cNjw@0(hDe^V#wG|2T;bwxo!>k+)XarKq@0kW^vTm_LCxTJ>u~8b9tvFXS54=0e>TER$Me;xu?G>J8
+k?)qcEm=ydvqw;*(&(Tfd?G#@%k>j_4gcRa7Vri7nVc98!8M-I`rV}P3Enrahm#-esdLr?mlO5y4Kjy
+?~xw)rVE(<fIRMa?lJh%G$p;RjccCUrE`B1<<lTKMEU;sM*PBRB9-kNxg9Q=0t4$MZh4KTR+f<&n=6g
+ShRkSoV+xu%_*+Hn(h-4iiG?9?mbhHiNOQc*I97Gbw71l6QX(fV^9>0_5Mo7ciKYw6Wi7^0%ECqW_00
+LN<%->|j+>k(JA1Geh=Z1)XKL-vyQH^_P%;x#-Vh_GGglFs=R}n{dUv<ZK;Ly|g2^2mUc_9KNLF1^JG
+4{H472SFw=YEkYulH+jW*3}sb!nH35$+Wns54py}RQ<y%Qv^wcka|;Gd-BFFQ%wmbUbJogQI%E$<+0&
+z-aq#Rpv?Pb3HAqrp2+Lh^DoLul)jQ*DOusvPmAW)Lo6ju3|QCGcZ6gCSuyOCjQt;rv_(QfO?b5;aj-
+MvX57Vng~$W{fakX+xeLk(kLGGT~WT3Ohi&LKc((?TF+X#)=UYPP4NP$<?xzA%fp97*B7x8NHeSfPlN
+DSQ9|TNX<t`zeVX}IAIc2=O`gATLoSUZgT^;7=kw8Hzw0q9&vMDSs_C_Y!$@6SBjn=rAPNf%|o?lN7C
+O7zpt+>fvw-e&1<w2y%rcM+P{;&_vDO<B{XL#mvhzcJ%X-BrZ?PnR%OTkHqkWxba2t7FF&Z4z5hDPL_
+_AiI*isFxjrZ&hrhS={&{#$j_D?n0HRiy?FPz&(AbTM-CG?_c2hfYV5^O+t;Vpqf^eaA)XdN>HKs@u+
+!H^;r0%N~p*a(lg623zcU3jry1$Xg{_^DE!?i7Qpx6=5cQkhFOp+g)xh;)9S5yKyI&sof!KAN!F7>q&
+npakjW>?*;I1KH*|Na#0IcU!tB+4WUg}RV)%`%IcfCi=MnK8qlo6;^zqorc5nbKH}IpP58cwH=g6IRV
+}p(qT=taS6Is~xdG;KgNlfqEmz<m}D)FiPPmOF=zEb&{|k=cW*JgFps|*6a|yB4VN0Mo@WX%sP-q0cV
+}6xOK99HX7xu!u&wRnr=*Gj|79v0{W^gxS2U$l-ifApx9x&c2&v^MFB?pP5mI`^CEil)A^ivtKPW-fc
+$+k$-2|DA|+UTd}oM7#N1N_V<?13XDBvzB!vm@p{-VLnw|d0OP*t#m}aFm7*?Ajc9Q9aGxXh2SFqx9#
+tKV*VVjwvI`^7&S=c+4r7@rOGKvmF_###V(T&Y*ai{(PukRMa+*p0TjQbo@@5_M=m*$hVlh>!yS0CSB
+oWJ*z!RIHls~?^|6TRf(?fK<Blx6Q><Zk;hjNx(m?qIh;Y6q_$5VV(Qm(<$SZ6L{ASo^Y97U91ea6uU
+xn<cVb&_{kcyO<zqb7m@>Apj-0<rJ$zX}Y2*xloWM4{e|!6za&1|JyXa^Vc0Ep}7p())c)ZQbs092go
+pug=Wu(lJkmIg1A{0G03#3K^;ZKDbEi^ei|P-e1pk}D$$}ic*dd}WR6C^mYmrN{1*&|x3)0H<M9IY(%
+r>sTx<$DE_gBK#+1yAzy0pXix?5HY4AOHjan$(1KO86Fxxm~JJ4F=Kr6JG0Nn!JwxF=xH|Tf&(TFlzK
+{-hN0#Hi>1QY-O00;mZO7>R$dH_pU0001V0000X0001RX>c!JX>N37a&BR4FJo+JFLQKZbaiuIV{c?-
+b1rasJ&UmofG`Ze_FT~ups+GP8$<;pC~3-=|G$6*Hp`aPQbN@*g$_`J<)t2scH*1-GZ9*mYV(2AoVfb
+RM)?f`T!O8zsV`QJ?77H)jX><@T+@d7A8~*OP)h>@6aWAK2ml*O_Ezha)iII;001fv001HY003}la4%
+nJZggdGZeeUMV{dJ3VQyq|FJE72ZfSI1UoLQYombtD<1`R|&tEYL545K?@LXw;j=e*y1l&p-@UU8S-N
+b3EI(D#~_5$L6XU0xir_CPZ`jTcof1a<5(=<&US$<%94!Ks22_@7Xn3T|n21#|zRAG}8<q}ah+BgUgD
+RxO|bd54n^4tlnY|jG4YF@aukvxdFt|6;E_pRzy@J{4z1s@vHV=@VH=rY?1<+wpwmP?WCnC06Z#h`y5
+UX!H%^Pox%cahUY8gbGUq_r+u$+r!2)e3UStlg6I3T%sVrc0Me@)dlngoQ%*qaYCq%`Gt4wJNVbmr!w
+b>_Cdr(P2t$kRlt<t!rAhK?7@euh>qK)=`VX2eK$cI3g@^ZJq3v{V}Y!&=_vH@&;elYqIx}c}pKF4%!
+sl5UXYmV`48p3t=0{Iuu3W_eZY4Rl40*_}~yu3v^nrj*+XAaDiv>*pObuxleM6wh&J#KCQfL*-{mdm6
+{#!P>x#<lrt;1frV{&E=rMOv2<{%5CnP_Wrs3o>18mxrI5aWP~HGojyZyF@P(N|pVTr-Mv@y}8c)`l6
++~%##ti?R0RB>;@KjQ!o0z}wJkOs#T{ft#E|L#{)SH>$;PHKL*sNzR!y_f+QnO+%h_hbg>s?QqfHAOM
+#nGxSjK)PVa`)RnoPcuXy^5tYod3n=0_n9PPd|9d1cVR1)1b$}FHxc5GW^e07+zyH`9{H>xdw=eShDU
+53dgIB%Y#VMg+m<QKuw2Tser4aFj^6^YeZ7m*>Jp0<nbqbp8!JSiBMf5u$4Z|Mc{QJSHI%>1Og%>f{+
+WGfxvcpGJV&W@`~q&xuAkl<o=!r6R>{AnOb&JRaCJfeFbZrc>>2c6ujZ8;3^jr7_}<Jel|$2)fyj<5!
+je90s3dA=o2k9PFtXF;a=(;{v8>-$t{l9yqcZepcN<5Q>HTP8SvOWK7_B?YYAnTo!PPSN^y*c@R^pQu
++$+=X!2`I-z1J9BDLF5Q1DOl2LUOKJR{*Vh(^VKWJ1z*0AbbXmo9JfHew$7Tzo+(!tn<YCh&dV3R#5k
+*Z`-~tr?BbYd{sVvn$E#L~eh?_X#ve!m-YQ#IXx;(;9+9)g_Ko%~#`^=X+>&1D-Xn5CrN3ytjVk!i8s
+8LtBeOgUWp%T#VkV34GVi9uh$*-U5j5e+Dcf!==q*^G5c#irpj<4>LQFq!T9+-(SPy_tPjkaq|92lBD
+1z<c2eM-s=~%i*LYhd~e<yPR#7>hHeQ<SbsMF-30V_4WZ|~H-H@<#<<Ekl?{D!?}wbwmVeoM_kxyWa+
+Hk>{nyO^x6aXa`b6C4NEHRn_n|EO+Xl`evc2>gy`^oyb_aXzaIrVNVC;V+f58wmeZ1~QFz@>3C4hLNA
+rl6-ZKDSLKK$r+YekLY$P78Kmn8V84;M4q!=KNwAA(D=z*?u*xi$tTT{gti4->oulo*cTzDDkHsqrF*
+Ws0-d258<$xVB|dpSW4{n1k#9EW~MSU=a>K%1n0Pon0(@8=|~2vpJXP5Rwu5>D!Q09Ekiz^cSso@-I+
+J0|XQR000O88%p+8nG}$9g$MuuogDxG9{>OVaA|NaUukZ1WpZv|Y%gPPZEaz0WOFZLVPj}zE^v9x8Eb
+FjHuAfF1);?vQfn*Q;(!B;^B#)a-d%x38f<d+B^M~NMB8d*QAbkox<USXXNIIiJ)C6Q0<D2q7CG-1XP
+9DN3#pk<v%>t+{IfpDw4QCG*fUY<I+cnuyZhg?Y`8Le`dAm$*6n;(9p~(0q4dmAs*5^Kib``?rDfdcq
+EzvwD7iW+&G#%-ta~#Q`xseS#OqY?Boq66TIG(@g?T-NqI9Yo1xPtp4&}qAPd|K`v+Ms{Tzt5`p2Fmx
+GhXXLRBFKHgOozf*;P@~uPI!kS}C?$&mLQ@Kf(%^vsp<`w(8cxB&pIpPm*Xhn`LFH6uU^X9k)C~`;3+
+|2A?1Z==pu6YMyC^wt($)%TbUs#SS~pOO_#pct)Vt&DvT`EzQb;<%L|b>zz0-z2gQN*MOps$JhcD)ka
+t-{3-V-8il26(dZ7(L6_j~C3&5Ei8?7JHmpvwpFljt6wv12xoV6n`CdHmCHq8ACMx)oY!C1botZEjBG
+!%Ec6e!7vH~JVji3qq{{C-us?kyJ@9$x!Vr#%*+fu9<|6EJ16zT_@)0Qo&5x177AH}u;!4k>;-+;xE2
+VOmZKW}8iX}eK~w`x6wpSQIXTQu-s1<g8GLNl`4R?s_kyI2_8uWok@cySI6P_VtbyBnYyE3y`MuuZn=
+tCI5#OY=MtCfq~C%T2@<@7X1|VA<m1a-8i6PQ@KU*g_ChCulJ5t*05nt^)G^U=Q+AuL9ILnZyMF)20L
+vQhl(Q?L?7rwF=!X3#@5^s1Ld0WxWcnd5I~5VF3|bLl7IDEZvK0yJSR#g_dVTfne!%<f2*MEL0L@TvY
+I_tzD9>6ipqzoA)gjbw-y>MaG^pYx<=vr{G<=RVI&am6mtp4k$03H+GQ8C6@|f?6L0v2(VyjctUweDE
+1Rr>>DG%s2juK>HrY^;sD7<77|lz0BT~-0h_mHz$q3TG`$$$4(zG3bFpES(9TkEtJbnd(^S@&V`UBlD
+2BGIx!Okwk90OoMG?tVQDv_96$;W*rR$RCaS-(gORgJPnRBBP>J9q`hb-F{P^(OY59LKiQVhZK_T3$=
+LGg3$dq(=+4%zFHL*)ed4JQ`9RT0yI)m&l-$AiQm6v&47M^QkW!4bss(D981x$zohE!&mT#Ww>Tg+?n
+p@^)!mb2vG7T=Kco8B@;CSU54_mV}nazAYTctwFg9t>;Z{+<vpX>tr@(b$cXZC&8bwERU@QuhH7Bx=x
+`@-d=9KB8{OPx|^t~5GDlFmn1Eq!}9x$Ft`x{&-f#PH+x=b6?j$1>WAqYj#4C=lA1vOXtAqipX{`*6K
+eb*w4h}mp<-C6a&OOR6-7PdwyzkWQVXQIs0qFbB9AjsHkK$wmfFZR_?=rjY=rkpf}#E;1Pq2p!jnK1K
+V!4db-%GWlajU@Bam=H=o2Enmg1xyo|&M1vz<)89=V|)&Up?_ohVjb<Kus>Y)b_$;-8_x+Pd27m@nDm
+gqlxZMhtc96T+2gBA3m64b3<-ssFyYxiTgL+<s_IqkaVG%JRt8O;Kv=0AG<w>wW<#tH#K)FDX(^5Cb|
+kSzr=sDm|t#bXmVT+5j4Rdcs?)iM8?JH1N)9@IFT9yJXdW9fMC=e>J%}M(){a<(HZl7?CQYmFG@d7*J
+(Vhuz|dx^8pPtLDRY>^IeOte*%NvG?qo-&)uw&j&k_cpZe>0b}t~uu!-=y6&8KrqEl=$d|<(iQbICRz
+TW}41LZ-+Ez<=Bm@%@<LDWIhiG<aaEPtXMwE@uY}x5|{39Px=Sq-M-3>)aa49D9-&DpEeXZZ_C>VRt#
+J8P$K-hMi$4+iS1asrCVnW5JHr>-8c<Au@Y)_s~xMGf`X+$euObuopZUUJ9O@Vx3;Ug8t$WyUrnF~7#
+R2su|`M>HEAnf$IX3I2+rv2z#{X2N__j1S3Osy?{y~5*h?oU;2+_3dBsjHGhaI#v8ha%^6%|jK#C-{m
+w)6NiGLn;yoiEIZGP_kEBtX-EVwOMNKzye=vHy5s`(Dj9X!+xkBi#Hqy&}nJKB5fI7{S})cYfI&}c;H
+o!fC2xyr^ZA}{Y+JR!@kRNn%o>07&tYxYg^YG_7H|P0On^Duns?Xd<xE7GcmT|i$(5`$_j{w14h2@UQ
+Q3FQcVSu>Q5)CjOF#f<yt5n2IgupXKz(7XJeFJF8z~?Zn7m`8Waq6a}an5<=uGv;e(i+a!=gbbU}X$L
+3-!u@bU<(nl;@sLn$Qj;kg{Lb%zF(pwam1X!vZ0p*+c)__cM|yE{WXAowK%pOw@<uuufU-4QfX=1@#q
+I8NBd=0#_q34w{iixRgJrgtxM1F33`<~Act>do<z#Fh|qAAj}Xiv8u=zs_0VMbjJle#{H(QP&O4FN;U
+W3%n$M3Kx&qV&qTJ-xrVdQSWFsT^I0Om#IcpPw`<_cJw^TP+1Bjh^-1<5><<|tamB&+FU|edmsb3iz8
+nG2x0EgsZgO3PW~K=Qv<W0RGEMyjD<-whbom;bSHJJcX%g7H-P*BC#5WFq(^AYH~7zn`%c08cvA9zVW
+kDJQtkgw#JAdleZT3I%>zFJ(o~|U14#=ICAC7aZ~=lMc%wkBLiOx#4k}au_~F@QZm+G3G5ELv_a8WE_
+G1Iv=G15RU!m>qd&IOokcb4>NaMU%==im==Yp&1OgkOMD)hKnb(p|&tkVOD)BjXD*`3G>BQwa^Bh<-k
+*;!wChJeB>%2FI44AxNPDhNm9g=gBd7j3{VsUE21`T5~+h)op7LT=A<{%~INTH)8?9YCJ9$lY|}etpf
+tfJ6_lBnOKC1J`Y$46tVQ$5nT_sI*D%jWoXiP)h>@6aWAK2ml*O_Evr7<K9gI008y|0018V003}la4%
+nJZggdGZeeUMV{dJ3VQyq|FJowBV{0yOd9_tdYvV8wz57=Tfr1TQv*$wh5_&7Ukg~mmAQWZnXd_EnNp
+8u%-;uu}Z_{=UT@i>qGjBfL8zr)}#syHOX{2tl+L;!N4VF8PAP46YR~`Dn7tWUACeMTPAsZZ4+KNdX&
+}ptJp=7n^9+@z0%k^ObtcTaPAU^QWc>*2KPmue~=EtUl$Dix<{o~^`q_OCDkVgAT98sJmWS#+?-oz{y
+C*C0Q7|OxykOxfdET*Qc)Pz!a7{Xq-(@bH*#hE>$^RWt}37EGiWG%^5X2rFxx*(OWTIt2q&x?~((R9I
+f#9E{r9o$XaR}F@T-j*|_d5eq{S(XXKy@z!iVk9pgzl+<x!_{i_gih9Hm|KT&Di25gj6fP#;%BcA4ro
+yyPz#B^B4pO5=sX2eC(!`?xv|bPu%%6i1MlX@1J>X=oqJSu38VXV+>jEuYv?U*#nuP6E8xpF>MGohSp
+iZRATAjV&ZySjQ~3`i$%{GBKj@Mti7r4ABo-}+6<sSSLR{y&*ITkg&+ytfpniX$2)#%&-jwn(Wjte3l
+sZYYO`*GLj9K7ffmx+<l75L@7V8;Fwkv<-?KkDd1AQF+?xe%`T*AvyiX%u5+JwsjRjcx9hO~w25#vbL
+otL?`Uw5xVKA<@f>{F>8rs<!i?juKkmHagNk9?M(MICw-_FaIp>4xjthy5o7sPLQ8ypuEK<~`YDJ#8x
+xx9JUwdZyQXNua~fIX(Q;&kj@`mthNzSKkfnojIXS>GY&(r)hzUYXzo1kv~vN0|XQR000O88%p+8q@a
+j{<pcl#k`Dj?Bme*aaA|NaUukZ1WpZv|Y%gPPZEaz0WOFZLZ*6dFWprt8ZZ2?nrB~Z-<2Dd|_g4%Qqf
+51xcHOtS@B)eJ00Gj(u$=}A$50iEcG&1vl5#Gt|Gh&>vaa6Ux_XgB&YYPu!{LxDh$AjRyonA=KP7#YF
+WikgYaRs<#WHreppeb};ra;`>70CvS-8n(u9=XXbRuT4?XXZ%9=g80@|peU3hJz)AaFx3R~V(g$5e!L
+Wg<|?qas(C-Hk@$*{n?^k<1r%z{DyS-caepJlb?R7w5CFGrIkKay_13-QK_u48!Q0DFoPwC+hoqK<8q
+gN*0BHmbu)C6=$*BAC;o$x`OExz|L$my_(EtXkga?d<^9MWDK-9$Q}proC1fKhnd~(@Tne!I~`B1zYG
+a<iT-u&Z>PV_hDLX{D}EP0F86x_9v&*%wMUDOl>D$;e1Ah}ay4<z@8-98?8d`Bbo=o0=Z_xUehd@e2N
+Mea_xr<V#*cy(fk)SF;!ChD>)c_d@{?*|h<fSAdn06LN(EuSny73nK3Tum%d?6x*Yg@ddWpCvFgnL#Q
+;rECqr2&Jd^5NDrg=oZH5{pt{<0dC8l^RBa9StfO2@!))NCFVszOvTE+~f1e=Si1l2ww=LKR^XO1KS`
+G|{AuQ{c)c1r|z|g#s)FmQ@3nCUgtSrq!?Gn5~u@p@M!@PI9$%h}dTm5kVWKTh}jJ!>AVMs@%#6PgmF
+41%tFi&@{kWwJ)zYdZApGb1frm4TQ|8kk&-S<uXgq;NfBJK8{~wHx&45f~EE_D~u%kS>e>KTVC??!d*
+QlF)pxLsZVL>2GqKeG&p7#T7cRr@35}Q%A~8Z*@Ld{3VDw!w&8)Ex$vXaGj3iBPB-**IT*}Tesbjxi+
+_GyelQnSe`(J-3ubDYB-Q+@7#2{r77_PMJ`p2L1{h8D+Wt7)4ocNqfP6(XtKE`4?XPKH({O`nuxhLBp
+xsi*4MFllwtmbUwjna5LA1@%R`vh;M796l6m2+L(I}-}J=7OeCE>f*Vp}rK;L^oi>=7kEb-Gt<?W$a*
+`-nf;nrdjZpo3mI#j-o*`My-7`%b5`LIt4?2w9`ZjtV4un}b~Z9I%jM${{~n$Os-OB!YUdj*8);=h(V
+uD|NOBBTgMo|4tabw=~@1+Mn};rt_-dU|VtU2!wiq2<oq~`ai=>6w<-LcQtIU0xc)(LV;As8kVKc0=?
+SkV{OFMxf&WmD&KHx7P2Ox$A(4=8XlBzBHh}mGb%_!V;taSTk5{*Xr-f6!!rLnxAzum@2660f}PCl{r
+?ivox9F#eJZmSw3DgTuukAs>V$QM@u>`tVxG*i718We>FPTQxA7E1xy<-F8y+Pw`P8dM#4M_tC!wzD9
+%MB>$nG~iaQO!R)SYI5XO*R{d%SBDWslp)1kW&1fPA72$D_3#-Z0!%Aa%ZU($E6}H=E|w!G5N1qSR`%
+Xubuh){J>G;HPw4$0z+_Xa+Am)FUalxh$V+GJU&{)k1?x9?}aB+Q@H!wnsf0%IdmNPm9}l*&-DyJ&cf
+Pql0+JB&v@N^ZOVvtDUs^7ptI>+Kny8NnISKuU^VxSTS3}=2Rv;Jlq@eVbvvT<lhiLdX#hfg)>Q;q>b
+@(dOID!mneZC5fWn6qjvj;(8%300P|tke?=@LmBf9Oam~kn0Z>Z=1QY-O00;mZO7>P_Pr^AC3jhFDCI
+A2@0001RX>c!JX>N37a&BR4FJo_QZDDR?b1!3WZf0p`b#h^JX>V>WaCyBNU2ogE_1(XMQ&B_$WVPL+a
+eaX<O}k)O6C};ugBJ+0McZ0sQ6r@!Mv(u$a}G&Klw_yrMHis8C7$muo<lm@l|oi57n@C1Y$ln06v}>6
+^|F*=#g&?@rPwi1R%Id;XJ-A6B(J$ytM(<(uqz*neaJ2{RfX)btTIs~`9#B&SsBGyQE>_HqE((n%S7>
+bC3d@{NG<-UemsPts-&tFAf;Scl(XyW%j=Nc+@7AE-Q0{~iejB@YMG!w7R{e9_&e<`h4ktlS&`~*8(z
+f@ZoJNNuJqz}0E4f=7(@QJ;-q~e<W*LlNh#zQbX{e+ii|TX0#N5g6~o)ZD7#FpEIi5zKHG%sL1q<?MO
+~G3HJKn;F4^2VI|9H9dgsS+k?eRJ2b0NUl_yHM)-bN{&1WzpwLQ<H&wnOGvf)5=mE;T^xXHy5zB=}bC
+Iov^FO8ekOuw139Aacfk;1AiXUVF{?zxN2d?A^RF@QkRGgb0cw$6AO7&1J~fXo^EPe3j{p=1S!M{r<$
+jRYo`u`gVs++!>=&|a*vq~a-i$f_+f@<xK(Xz&!`-EhmQ3o$1$2Cgm$@)kc{%OmB>debq?P$Na=CXx!
+k*I5AsYX}#K2)oHJuGx3KS4?e1ou_QcSt=mKIb<}+Vlxo`X;B!)g^qF(6y+exgMUj293Ppd-R-etz2@
+LM2;8LDH!88u;5z=8?8@8_@*seXGH6E=E)j<L<FuAJ+g4SnX7An^tVqbsJC8k(%+?6nz$gykF~nN~rz
+FoUYZbC(T@Bc!;-Sbzl15dw<B%Kd!+RaaJq9d+6~KTODYLMm$oIsDs9I89!_tKL`I;4?;7qL9bXqGeL
+-;glfySLq6=Wt$fJ+Inz|#=8-Dk3@p-3VDUci$mc98g^k*pX{g;Kd@$Oaxw)*x}4BAU=6gpZ2YCA^gn
+nc^XtXeUxgo>ihN(>5tfUa(3KF3PLfEcZkMA}gu$Dr&NxzGRz1NFGc6-#UZOdk`6F%QtCazgAcj=1rB
+rzqeSH*y1-NKGgyC`yJ)~3m}W>RHrTbO@B_yq}sv)K22Ugh8!PDu)_#yfWX?EK8!}W{yI*S;;vc2*ep
+rYSi>k^@q8Vy>F?|-czV{*!`IPjM{p`?5&Q;%s9L*uq4OU0%xdn9E@2=+5%Ux*@c|kI!W>0$SGGJa=P
+qyJf2O?#kp)qOAKcbwG(^O16;!T2&Tno%UNC?=`*i;8@|t-=LfwS8Ph^%XvHWG2XBAW;ai66;ja<Z_l
+`)vS-g2g{jag1FQ4es;d~pTYaKMJ2lU$7%(Yr-MVVT{litnZmpx9Umz)Ix(IR!D%N7ciHU#lF|m|vq6
+R@PCiaN*Z#wW_7W0DYl)zn~=b*An(a_`fn*#v3W>(tjVib_m*<A?t!_MQC<zH8Z_A6nwc+x{p|>O5Ra
+5f&Q^ACR-?2IhP8`^^<E(tj*p`GsW+*ZZ=#aP$98U0(KJUPGenMdVo-hEgW{KZFA8;s1`yQ2+gwxN5$
+4c(!&@vs;`dx+8qNmo?9QhVV^kk);nmXOlUMqrre-Cv0CBh;{6@HgWl3wapuUNyY7f%%Rf>ezjBWKmf
+^(ww<^FgS#k+o#xCkbBB6xLi~b`ra5r@OJoPQ#AaH>L=SlLamW3XXT4fE}xz%Od3=i9EwH@z2B~|q$w
+*LuK;0`+cec})dDcGt25*#~_ZoiCe3-uv;97Y<<O78m>Od#5^@tSK##;KKz(s^iAlK~+sz`EMkbKj^6
+j#^M0hC0|n8%v>y<GbL174<0B%x}=dGk(O^JTf-@5kI_P7oa6HfdzkX4c#k%jt}N;bMG1=QzFN%er~K
+0*%vVw9ooRgtn=nurz9Qb8X>qJbY<7}pg6?#U$>LcR&oh^Om^7OP83rcut$7uK^7Y2&Tm{wM*T3m`~U
+dGytO9^O||WZ;DO59#@~!Bg~+M&+S8B)9xvRrk|H77_JL~`j(9M)InOwQz`M{4lwjat8u)ZD5#8RLT{
+p5t&E6giON&AHa&h^$j~6XUr`tJ<baVdgtVL<|+M_iI>Z#jUcj}L+wOymk`p5{-G4Vh&<2`Iwoi(g&w
+56NI6vnf<fO4iVN+mymy2fZgqbAis<vH+$`F5n}s0fFWNKafoS-|WzWQYL*y08z0jy!PI<Ohq^(s!;^
+531f`^t4ci&DBOtn_{SS&I`Zmj)2YQ?89s<i@IRWt|Ai{L7P<V^=`Bm!qC5}pw{DDOBMkaK~I4P6s#_
+x=(#<<=eGkk8nYd=-F>v*ZDA638k*O%P9uX@Ox;Y3&_4bbn$8I-!2EruR1UM&?BOG27L?h6(|f+{9_j
+hsTQz?REqsS&M?KqN{k(2Kw%K!s8sc2NKn8cD=Z7}JwRZEd%>&8MvJb>Nmg(!|4fS#R!9S%{=!!U^oN
+AO~3xd^3{`Kh2sJhCz3bdi3l6&svx8G5+ZDoIz+w?KTxZ_52(gKaS>_^lY_S`?OmgjkN7HZD&K$xlaV
+wq$TPr#&r3J(3`n#*?b(v52O6zY&+^svxRSv`_Tn3rN0>p%%<6=}`(hMiZsLW%okuI-%A5;|^Ju)XZ{
+kz8nx>N-UF8kLeOR77`AyM{n2oPt8fAq7y>3|}fLvb*2BTwrFDiNwL(!jSbEqX;<?t>KPBXU6UQg+H=
+U5h>g*^u7s!+uKNq$8h%?lQlHQoij#Nkubw9^>H#_*AC3Mh`mtgn9znpW27ed4}$6xFbFfcW*U!oyqV
+}ng?kMm)_8KPDRqM!y`$A{x0)l>SmDU7*BV9a4%CZ}mt8stAx8DQBhJ7`z0^8z=-Ic3>Lm(x{$uBaUB
+isUw`bUUZG60-=4&=`G_ny3nG917|BM6>{%h~*{3?C|>QN1Il=Oq=;d$tI8(@eGjqD!E{Co*Ehw#HW+
+z_^%VW;Dv3URO%psc6_;dcruW~44HswV;d^_ocUlrC;?7)aZbo3fMwVk@y-e8;!c&7OECRJf3hOa2Y}
+w$1D%S#eUCdA6Am9yn-&*F)HMl9YM&9S;DLD(VqBU(;(l5r=?#l9FtkuK$2YS?4*!OBAkf+IhqQx&r>
+uF_nk2#K~z=kO|P$?KP*q6Vs)FL<JXANmd{i@887}ssDV^o6!!><?YV_qScnKzQ?O1&;9kulV<nKJVV
+ku3BiIq&*yj}G#J)DgFs(J^;y(KdT44l10Ii1`k|YMTC)Zr*16bq%+}}K(cu)N=joMxIwZ$SwzroYHw
+|6fhMK!w{Lb)a3he3Gi*OoADxXJsQo{HB^QQKYq0^)2l<j3`XfIZ03?8Av&hT89^7dn~ck1Tfd0uk5h
+}k6&tO_qUyJvA5p|53Rw%Ni^UGJ6vjhl<y)L2ZN8fu0?lqO(*nFC)(g`L`fJ4Ouk1(?(Ye=PY5%`?IU
+H8QJD&(X+5(23uu>^(i(Rtqc}^n%!08uHfuAi@tCg9XPt4Dtu=LB!!n*Pfd;F*ca2JAfV6j<n4OHoZ6
+OU+AwD2G$yi#U8{3a_!M+d(}<@G`JXv_j=3Tk1_1RFu_Nr8ldJ6GWg8?ux0$H&906_!EJ$?awDh9j9u
+kC0cS`~zh%Knh$)#c=*|1rdq+2gbMpfkeK?8bf9&w?*oH{HfV`S@L%|+!neqzKVT~HuqqNsuaCZmt^u
+4Et+Yt1;rbQSh(=0D6)?JU7zB+v^F@tq9et%%M<=tyuwDtc0P)h>@6aWAK2ml*O_Ev&T4d9yy006%k0
+018V003}la4%nJZggdGZeeUMV{dJ3VQyq|FJxt6b!RScd7W8XZ``^Oe&1igstAq*Y=q=>aW+6|J7@tn
+=VH4ru0hZewaZ2lRg$u^F#O*;!;3^}cN3$2uqATl<IHfbvgih>3=#HED;`V5wH#H&^~$Z0R#vR#^V@D
+G`dxUH6PZ5fRik7_<X{G-H20X~U#uOu-!q4S>#*@pS&uEhg{5f|ki+ih{;(#OqB3i8Ej0Z8Z7@RitX+
+i@2QifNiTAZs4j@`6E3S-aL_mAqbH$IT23CDzs89LCl?M1g?=)cAJy5^9iV#F^xB_v?s+~@$x>{N(^%
+=tQkpWsIyN>mB;JR?H=U8UYz|gU8oEoNf+|c1*_8{09UTv5eH5^#aX1}?+xVXBxImsgXM(jq#Ok|3Sc
+<~fh#|^8QVSxd~;{B6QvhR3rPO*$ew7T@Z6!=761387&^DLdvReTQ6%$I|BT#;>X(h?}H?OIN0&pJ+N
+v0ANa-VnW)&-4jBGsle$(MGL_UD%-O73BRV@>TYHvm)^0kW0}wGSA-W4SA=tH9=0#l;A=rP>`|ZsJ=B
+@{v$jfFH`bOR#>uh)v5s69n+V%V>zCM*++)V3wIv=L@H-U4+@;X4~kTZGsAtHQ1ji;jtx!?49a_JFZl
+JaiOxMvBBdO7PYwTW@+=BGI6Lzp2+&!9k=D$j{+0Ybf_IZ1yf6f&9(X011NuuVdO(h-Ket-0iQ=7nf}
+rgWK+Gym2E`lkok&IW*uWFSKrZ^K9cx6vC<N7YF(X-Eu<-q~5>_FSlmPupJ+uOJA)vv>;{L+}X#gH6!
+0My{#aV4pz*M3k*>;=Z1};sQ537|E`&O}D1Ahl3Mv|<v2{A((2d!(cwUbYAGb*=`JBgemZ~}^w$YCW2
+H;G~5kST^$c*e`lqh}ie_I~HQyzzp%73=S$Vm*1}WE=*rDyHpu^Ho|gv;;b^ga*$no%GQ`VBhEslE5>
+>X91QQTDY`4dymdReFT6fe7?Q-I|v8r4@Sxs@|Y&9G9zo-1Cc%a8our5>~St~n)Jvm$!3IX_Ow*4EJ4
+cLJyGiXn$o<9eYkvym|sEYT`M113pc-ZHPb!uC*E#96!9IxjWA<W9)Yc6N#dLH0qFf9zQNO%7pmm_9G
+i{~)O({RI9Y=SZYOaa30}@54h6L_s}-wY^<J958prdkIuLO222#_6431Ot$FZ+lUI!sDBhK;2wB}gv>
+|RM}BS1uo4uHqt!4oMI9Is(idh&azp~jniSql}ZIYAW<#e`5pmjMvKj&+0Ls}hf+P2We>@!BHMCP@~v
+*?>LA{m@!?8+jj?iq>2<oKr7uT<1{=4r`l54qjB3EX$zm5wqt$P$sFc>lhSd8v+?wF>7wr!(e*^cD3w
+`U?0%J379(F?h>eyV_Vx>cnpmmugh?{{fn6(vfCPtgcJ^BG;)9w%9X<KPREtY%1S$~HQU)R&1Me?HjA
+9~jWLs4Bx;gkrPsO?Ay0O#+9bd0*(3Nc_&LVEnT+Or+XJu3sG<I3ClI1M>dKwqQ@9i<Ly^24nPF+`*_
+JJ6n>4j~%3P4YY!?Jeu;Tx)&BbqDzg++0;&ziLIYJwxjh>7A9{uW+X~4~1UW=^6a>>lGNN0?*Xxz5jc
+iOgYiDRY)Sf>i59pfT4f7I4FTDU-Hh!lhTH$`veQ^5)62lJijyx!E_y*-5_Y8kfExgRn%eqdXu1|+l<
+oxl|N@x#imMI#87^`p5YfEED*6-+2>uC?bEp)I-;(AuzrO*@X3gaOFx8O(B+tH1#uLkWZBU&$v?hxFq
+d1YN`PE)R4BbSJ<n-mI=YoHGlA$Py+pbRcfPt^Fo>S<-{AI(<65Ltq&4pb!b0A3$5+czt=D+_?o&a2X
+l~2VWfd6X48M*4qP1%cF!I>{s&9=JpAPe41};79F?T8o1>ait@;lJ!`9-zTZr|4=a~6G(U^-1v(wR`k
+8xTH2_A;`Bwk5!;bXCvI!K0SJo>WpPBMH`<}=-(0cy6zyBf>l=YWMp;xCUx_w`g-=V`G@81VALgvN|0
+<C5Fu*kRJswSlE^i-Tx#$B2ls2Fv<4z)XO)ZV1iwT(G2fX^n_I^vx`=jt65t@w=})`X%V9ma9Jbc`jd
+>l}!~pipKwucV!tqntT?bCP|PQ3djj>}V;5AcZ+gDTq1hdR`ovGSO=ThQsdtdC$3hsKLsuWOe5J$WaG
+wD1y|2CKH!ivD1uw!g0nK0%Tq+ofO6*J;Yj`Irdm>N0?0}3JddzM@Du-XC5e%J|8Vm{zr;Fcf{xlRf{
+fn34QO*fA`7#-(qUs?B9?Du|?k5Mh)E$hy97nK8#aS6dd*)B*Y#0)#r#$VMFYCC`T~f{C5<})|aP{1M
+EIJDYy*ve7WXrvnT@iGk=ak2TRj^!iyiSa6!-EVV7-hf$@R8z2~4iCC4HEuqJQd^lp!S6^aJRuEyS;y
+C#cD1_fSW#>LNw_fxwJO>lIXE@q#Z>cKtIWRl(PVc?j)*=aX(cAWKY+O-#CKR1yyWn`Dqy5ESI1u<-T
+WTTPpA}u%SgkK{N8w_di844e;EWm1*!bA(o0C~l2ag?JOMq^n+fs~CqDu~;G2Q7fAJ?p_^P#6F}2}Q-
+rnJ6-P^u-8f)zHA;sGELz%Zt-Y_@!!Qir&tX^Y6SG4ffHVV_rDV1mb`Pu(36~uOvpeXFlHek*Gk8V<9
+{m{3^CYI^H`2mfG8WKSu!k9tA0g*E9B_a-5~ii}g<~2!(`%VK7g4nZxUX;ne5J)k(}>@GJT+zRtK0od
+CV4WXGX-#>9VK{c(47b9+NCKGVP5eZ9QC0x%fR{lJcTpCmd1cX9XU^$(#I1ZQAQ{L`Sc|1HQ1!1PZ)X
+T7{~$6Nx_$@L=>FGq>Re%zBsd%m=UkNE!sP)h>@6aWAK2ml*O_EzczR>S%Q007q%001HY003}la4%nJ
+ZggdGZeeUMV{dJ3VQyq|FJy0bZftL1WG--drC3{U+cp$__pcy46q5m4+a87iK@|*0H()?96ie5aAYf_
+f*k(hMDoHt2fBg<AQW9-Btvv&YEuIT`zH_DczE;{2p|)Etw=>>7Dl^+?wI`~!HPZ%2SpUF81A%7S8YL
+p-EjM=75o%uNluHX*GLe^pN1k$Dp+c^tIm4I_98qS^o`71Ww_s`A+MSZ;WHo%IrP}YAtfKHg@VVg{_8
+{$DM_H0*Zg;d4z+_XOQ)Mi(jX`Y{^ar{B_wMeG`}-*oRfA^!)cLyMqU!!rt6BL3Ix27$B!nqdXoNR}O
+FV-RJ#srJpQwN>D_d&7HZ_7lUjVbQT$p^%O&L{yG>ryYalIr`={*ztE6|$R9b%%n1*#fbH}<?X3;Wv1
+M~(0C`3=HbTBY0B%!LqITf|t((crg!Eu&PjJy5!s&1R)w#*jDaSqjCf;Fj#vQ;VA!!Owg?_uo-~)QBD
+1qF>xOZ)TpjBJbLFf04|&UfG?)TvqS}%z`w=1*sm?6H`OUHypIdgYbvDds1ul2`wRw7XA8LRWi|2s$e
+RIBL<~W|6W-jMm4$w!gRUg2gm055KF>@QN%R01I~~t7~_uS;hv8Uh?a2yW{z&z@p9+(Kky2?Dkcdq(~
+@V_603qKEn&#21fY)(Tr26#MDiN?ouJBlIQ@^tAc*L!h%X_paHB1G2toBoUQdE{OCEv;RvzP3&!6Y{8
+BHslDC-QoM$zj-X~v$qeTi2j-gANeB71O}Q~OiT+{0DDhOnxNDVG@#n*~|jlE0ONo1l{rx9p0T<1_gn
+kPU?`FYzB%08B2EEfyDvjzPRsRw`OSeX-b9s5KM4-Is5==9205Qb8p}d!=ZtVFUU~VWZ0{_Pf%LbjQp
+NE(X;_t_EZ1n(1pC;(HJ`O8B02sfNa2*MR!hUw*q{@9TxT4%nUjnmFcLY<fTg@+Qm@PRqB|^c?OpUsd
+zv(aH+v1UtQoQRsB6uzP%yq3fhaY>uax$2v|=_3Xj21JlTJLc*%W8et2C_%+(K{)D^(Q5W;m&Wfc;k=
+Mw6n~xNZkQ(9YU`ocbq(t^`j)Z-+_lwwmMw<Mj*FDg!R!yDaKK7;8;CWJm{FZ)T)syEQ(NPKhx9NsIF
+Gr_aTp~7Q?C;5_8T>(XBRw=r63n>?Q}q((hAlq1N%{dh#G~&o=!>Df90hY25}`sM-|Gf?z8?rw+_JTB
+0{|HLqs0jYIa@zY<6+SVvcb9Kqnk})Y<*mkb%TS$4#-+PgD@j~YU9^OW7<97Sc(I3oUM?~tZTP84BIw
+8IdeRb^ZLW%WGr<#UZMS%r-%SAefkCR$d6HAoE4}x9c!~GuED9pJbZ?6<bGq2jvII{yHF2_MFVN#h)G
+VM=;=LX5Q;Jz7koPI6N+8PO4<?AoCq3<@O_*N{%l3~PKn7$isUI}oUWV2%Vl*k`O-^KFcRDq120<m^~
+Gi<SEQsq_Z8BG`}ppW9ThzR77D3sA1By(d>W>vJt3k)Wj!jL-Q0si2;M~y{;F^ZHfa~yZpN{Z3~4T<`
+%GU34=<x{2G_rM!OMDix7TQE96his4QTox8|_acLyC~U$c0wQb<yLx{Qlrdyi_Dl7erwPM-fm-y*SFn
+Vk$vXb~jkypQZ+Hvc;cx-GY?i0D7&E*cKkC{_%`UaXLDj;My&wSVn}4_~W}Rd=cOOnRXG9Zr19>hNYA
+hLk$gc{=uHIQ9Xa?=z(^=r8>_8j-!T`UP0E`n<hyglo;L!Y=kopKQb5F%a91+rVJH*-T`(ZpMB#}&|h
+mu{jzH;J@Woq{uvwS@#e`jDnIz<n=Niq{5MW2H#nOay!KXf-4bq&ZhP^=jGGC(fP2s37+v*o%qP4tOi
+=X!sNnJmm5&bOU|5_;jjr*mu0d8=+-#y6<l)DJc0>0VH`#XqvN-3w{F!MPYgLF1Lz%4T@M<L+4}6=kz
+Y^QVFP^gbeN&cLCN_<mR0a|9%DoJklX?D0ahVN-MG|1P(XxL__a9J80|XQR000O88%p+8pAhN|5(EGM
+WDEcRAOHXWaA|NaUukZ1WpZv|Y%gPPZEaz0WOFZOa%E+DWiD`etybNS<1`R|?_Xg>LP|xO<KwL&NNBl
+}kP!E<952f%a*}Cl*0GJp>D_YN|IXNs(<JSRJ(fPSwdeac<Czhi(bh41#MR#Fj%nizw+Ku`!f#ymFwo
+qi5$cdAKh)?fZ`>`o4f|Q3TSYD-Oi>Btz$z|_Mv5fRbS-HYTHzCnMa>baMt2=oZIZf)$EQTlan~aWwS
+Y<F_TA0R>)YFFBHDoE!G~gR0sb1}jHhcNy%Q1(^2%_RxY4yz)RlQS;A*vMVb3Z&>Rz@L_QqI1tm<CSv
+F6PKs21}z+kVe#t>tdT=wre4R(aTq6IdjN$lzYH?^yorhJF3bI;m~p6wE{g6U^`E-+ff(>8xZQGjcrp
+v<i3P87@WXQN!O}1(IXNk)N1tSk_Wnt*Cnk{`CF`Ad`V1f&qd?azyqffH-6<AAScjS(b(0x4knx0jVf
++QbNlN`NI!Bdy16)*$WFDD2HsXZO2^^&5c~#0+ZwxNs<6(4b{w+w1Gn5#0eNuf{3VX3$_?dhd(`%3PL
+LR!q^wa>I1tQ>heAjq&`#>Iq=Q{n`iLB?Owg|*`myYwH}R&yLB|;)5hDj8g%9eavzfSi&k)k++P>;Bs
+?D$XMud=2(E9**5YP6L1{sxN8rkAisFKSYKLr;88?P%;6i%Od+Ex%`}utbj-R+Kv%Qe8kU4@h<=p4s<
+vVI2?g%jrK2!d1p!_V8Oe$G;?sUj5_4sZO7^(OaJAexBm%5M+byTolj{;eQj%q=%8m_77kxHVY;DjN2
+PIQ39oNaxMYyH_tl9x%6y5Y;~n4W8tloxc`Lgj3~#5v{W4VMVdOTkb3_(D#?x}Hl=CrSeKup>uykh<o
+Q%r?{*Hmuc5X*Xbc4Zp}QAGeq9_W#6jOL<xrd<5+Z;l-F`Z<TyZK~LIHijdIrX1CN>pvXQeuJf!be6y
+-(b{zBde*lC$xr#@eSJfr?Ur~9gTz-r-fDgj>$4c*a+L^;!4oK~;ln49xDJx>X&V6qz{?J0@li@W9Js
+|j^B7qN$>|5AED;%#cT2cgPV5**AdLB&K>!^h#EeR7Am!;T)URD}|qrN)k!eI}yg`aKK4bs)Y>fYpEZ
+RYwXqsR6tjGWET6md7~a2pz(2RivxEi4aVDAAfTnMpqPC8>7#WWzbfL`y|z6K1+W`5N5Kpz~^q-n87o
+tOiz7MM=pJK0d8t$vM$8!Lm6*^H7bCEulS-Co)u~v_L5ERUIRk7uaMxl}Y(@WX;PYH1kSRBN>^))tt+
+>kvWsUne%wBaisgxoGwsHf}<T-(nZzL^1Hc!uk>H@>*bp$7toG`NkK3264xCn{NlZ(wwMPbzhv3(Dm&
+N7up6d5{2x$D0|XQR000O88%p+8zsURG;{pHxrv?B39smFUaA|NaUukZ1WpZv|Y%gPPZEaz0WOFZQVR
+L9MaCv=IQES^U5PtWs5Qc&cj@WaU3#DZ1ptO*5ed&r&?6a*^mOM#rSH}MPPO=@xX}i4G(%pT&`@Xx2X
+gh5jX}E2q*hgYGN?q4N)zi_w+Nd(RCAxDRHx|ffxaYEm(dJ$|44Ev~!n$ZMbfTk7C<jJyNee0Ho?Bpr
+Zd<O(Dd2KAeiULIcfG}+66_SR*=}#Q8QFcmyxi<|??v`bNK1WjbJUlM``hieyA8X#*j-`t-S+n8YdCE
+FgV73GOb7;e$%>{|Pc|bjMmS))cU_MKd*Z;5d}5H+;I6}6!kFSMFqTG9R7h?uxx&20vXk+dt|NlKIF7
+>;ZxI#<4+0Tg;hWS2m!#vx6R*)?ibgyGje`Fj)(NEGitK^(7E1CWTtil?5H1vk8~D`=11%_LNhKr@r%
+9>tz60*~UP3?;3K^GJ_#vP0(p&%0oWy6H(KUI%h7elWNAlT2ofAswkh!RpHo(TOv1d@v7<OlR7=TK^T
+FR1*0Eq=zrDSzZZnT1d1po8bv}l8$rE@@X@CfOxc$}TwthlT-YSXkQCTt*=#~)dXMvDS$zG#c33om>I
+d2Ah4_y)Y<y>$7q$rdgR$S#jjsX^02B3=iSY)y~=uk@e4F|D*|xmy++%F9She`=wUMV{%xF`d7gE(r}
+YY$$3B#*K`!+UUMZK4nYJ(^)Rls~}TGM$y*e{AbvOHJ<#;KUilTgOE5tvyP%7O1r^tk>qhcoxvCuS}e
+hpgEL=(G0UP1xZbE?^rM4iCNZCqqldeL7qW?S<Ay<algaTQzr*;MUH?$SAm#XeW>EtVmdzi}2=iv9E9
+R#mIWeE8b2yD9O=~QQJlSuN)&!|Nf(z%sG(Hb&V>^Jksl7^3W4{lZ!$Z+&wS>i>J5XbqvDwEd;da_6G
+dTe#pZ+4Kf|ul-nmoB-Cwg{|He@p5rAxLw8tuE1J4k}#fHZOutPT7gvQN_JA5cpJ1QY-O00;mZO7>QX
+!<0Pg0RRAO1ONaY0001RX>c!JX>N37a&BR4FJo_QZDDR?b1!IRY;Z1cd3964j+-zLz4H|#swyC5QO{9
+#FVRY^)LYtKq6j%*0JmVfW3yRQ_1`-N%tDm)#aM6N^PA_PB;A5G&IqyyvNf6<{1i=xHYz>ldLva8kZ;
+nuXatNjSuT}BQliN&jm*x%Vt&zWD^w8(`|<c5#X8|S%cKHrpd5be_s@sJJqo^F&^W1;z0rRr(iBC}r4
+iP`7i`P~B-5VmBH$Ir@uAjNsJQ}4O)%ND3`9dkXGMkZ=qraaz(+&6g3nXsQvhV8G+|Eor<1(Dpn752c
+j|ByDzF6VRAR9yw?1NTdpBjf1wj>`e4a<^=#;|46L6oq=~94uiA`oh^T}N7S3vVZUfgyK5ehfI%^IuF
+<yN+`5flpSTSXeppN{(7iunOH>~F|&16S#4P<rSKq=lMw8Z6-4k4<nF(&c$J3>v4Aq-%$5kt@;q<h{c
+2)5+_*8be!fMNr6s;pt}jI27<z75F;L!P+IE>qyO0HDj`TyHsh%;ja^1t5p1Gmd)KuD+xM_u>5Lm#f)
+RQ>C|tfud_bHe*@!Ryg98n>}t4befy-A31g6Fy4<v)KO^+IgBFEytT?b(?#2TN$^Z58FG*r}fH?c5rA
+k;cT@Zr5$D4s!G<Z`wJ||^{ct~^qG|58mCi?$SO9KQH0000802@m7Ryj`P6y5~@0J#zX03QGV0B~t=F
+JEbHbY*gGVQepBZ*6U1Ze(*WX>Md?crI{xl~`?S+&B>azQ01}Qn11GwO^NWp``5*C}~LA!m%tyv9-Ip
+*pe&BNtclS-qEYAwG*2CkX=bLqnT%3725S&DAe-(p0fRFCwPZ=uX-#bLDU}p!0kY!JyXXX=={kCcFfV
+aA_CvEBu8JUR5|+EE6N#ebM&3TkCkQYX<t-#gf(0gJ+5!DzOT3=LIRDK_l4|nef(iJbL4(ZB~S*pf$*
+YkspqP@hMPO(6NH5zKdYK|9cGPZI%f^}^{?PVe`XJ!;*|=kK>~Y2q-Xwgb@lZsN7vua&OTjVFLGL;vX
+BIe`rsLR0TfjOH~}e0Zd<GshsBOBi6OsgVomcBoVK5Y;37vKL6V?1gC@D)>N6i$lcP)8oAV`!RND>ew
+JoU?7Xf+7ZqNMY(|p!*q}u6aV7|1wpUvhHa|htH8VfC7+uIAW3npFr?Mv7tg0Pw_deTWzSnP?a`lC9G
+k@L-LUYflnUPjbC7q_5-oCX{qb!~T+m;hF|ucNZ|^!I`)Qt?6cgIcY0)&L5nPoDx*_+s|bs$#e!Rh6w
+)tGdNf+JJN3OJ~uStyc&>Ns^fFb0&Mh1nIaCorw{I?=Wq3q9LoQ1sxg35LpC%^Mmdg7o>u~A1Hi7;@y
+Fs-^4)7@gOy88Sc}c*S+9-<T6sCf7}J{W5EsCA>1^T%eWMLy35d;_vnH%vJS$=oGdhT<g<vk07|_fvs
+GY@_KWehbRso2P&(0Rmc2*{#NkU>7_V+9!{Yc-M$X#fgf;LQ2O36j$b`Pbx5SC5_BvG3z;c4Hm0)P{h
+{mX8YPlE>PJy=PAO!xZ_`<jOM7!)IY)h`yp(6%n+@2$+{Mxmb96^Y{O81Zr6t%4hDoDjKrVfxNErch)
+^bnbu_@GVJ_F^4tAzdn8v^>=a#p4Kt&E?`A3kI1SL!Cfbus|RxQ9TH#QK~&6%n<q26G1yz;}*H1U!Wv
+rKUb*3M|4AwARWIW&EGZHvM11tAg$4EP=nBCEy2)rPnhp11omKB2b624Uy&@i^A-9?pmcSV5rj=e9fN
+F#7*_^k1Y-2}=Iz$(fes$ob#%3Zgy>ch17Z}rAYcGMU~fX{YndU%5#XU~R*~d$mK-I;|C~YyKrtmv>h
+I06m^h18f&f0uHr>%!cWvoynZjVYpS4O)D+k>71WMWgnoI6&RtFE#8?QzYL@05LvG61t%d$;f_}Z}Dy
+jyQaoo&+&T^M1B$TP^2!ddVqR=Zt4d4#;GZU)*mRotJ`C}T&6Pg8F~W_saz(ig|WsD`h@n75g>-Yxh;
+H-eFCxlT{mZ#ZvbHk0|$OfjN2ZCGc5U<FPLt<X&+;BCPnUGyOYq;|ATUZ0<f(jZc9t8p$W<B_PS&1I=
+WD3q_#eMeb%srx<5cKp6NVs=ZK@-uFwQO3f7>~?6j#ne&Jh*U04M{zdJZ^{?W;jfnIs!UK^x4@Wu*<<
+DM_F`LcK^nQx0~qH)gn1b+XRT}sOnI`7iK9?0qt#4dojuR@i$7>s@DSQAOhHg}Tf$OJn4!N)^e!#~0#
+k^J=|rC<|M3AaU0ESm^bAOMM<^&zb)esHUDw5a(CsFf;2lrI^C2QSPea6d_MZb0$E8B5TaRt1uDrPD4
+<dAF^ED%~%w=L3aX(d@{O2U4=KaH6Rm#)S^di3p=Pbwh^8@B-pNf_~VAkPHyfIJU&GNf;tIOUTh8lu_
+HjpdfbqxJ<+||9yB3S4zlh@%;rpB4sb6UDlV3PmqnGUbem6=q~q+-m7!c$?%iV1<yKfLtW$mcY1>w?N
+jftm@-7NIsFrc%FLHZ}NVCe&u&(kpt|qU3_ZD5vU!9xIv&8`ua;#?pt!q_D5HC1+Su;$$(zFb`D|tMm
+-4&B{D_8aX#Mg+Uf7t^Q3){jkfnac$M%pg_`Ge4ONyCvBQMJfigBF^et8ov_J+C+7MPo~C08Okf!2zP
+T>hMCfz>9XZit^&3!20|XQR000O88%p+8<~jzZP6Pk|bPNChApigXaA|NaUukZ1WpZv|Y%gPPZEaz0W
+OFZRZgX&DV{|TXd8Jn0Z`(Eye)nH-P%%sb9ASGk;1yfa0Ue5FK)SsI0l`RTnGHp%B$dJ_`oHf;iIil^
+55@9goA=$Xk00+M+D;n>Qa6oI&E{Zq3%YY1Hx@w*#(%l&(GE6u>IfGtzpK+0?nLFb@IhF&88DsbO7@D
+X)~4)u^}>DVvgPIljg77~9(XSuL-i_*RxK)b>1{-Hj1HX<%CXN@t0_&iF>)|gXvNqp2;tEvF3U=ah^*
+S0+9RaB0xS)FVU=!MuIlJ?JN&%nVI6n9C8ruwdk_EI-oATySaWI7@tQjxp?`3Tcf_6%&%Li~3k_c5B?
+Td*v?bNqaTfzwS4;8Cx|e3PxxuA3G8IX_N9Hu6v(3g!01fP;7D}q(LpaMBQ@lmSip^$INp3B?SGL2-j
+l|^RXR+G={bgAeK1UF^BSNLA4CO!{fWzM>chm}IErMseGrI08B!IzCpHT4E!~I7%Xw!06rr_a=Xp}a{
+=(>7ApQM;qD*lt{F_?SH8>E9+48Ttmzk$c``kzuDQX=rWW}_juC=UhP{01Mj!rkZ$;Ezj^kH^_^a>x@
+Rly`F@b;V`2T^#euL-(0=zGg>7o&m<^u>X@wi%ZiHWw&2u37Os>JV6|YMAvia`*%lD!;xEPq<-d-(pG
+5g7HSPj(<>*HL3SBwK+DsOP^4ukk?tbATeRg8UQDGGKh8{V(OmRx-9B3}{BOpxdnHexd)M_YwF6U!#G
+OxjV}-*q`=P$3AyRrunSV!lapo9Cs3|ES8aH~f#^}Dwf7vc$7n2Z8uYv%#FlN||<97?(H1x~Q*+&`{P
+eG#exF?0q%Bqf7y|7eVEPOOimDYr?^h(YqP6U?TxhRPt!xD3>o((IzyyT#LriuA|V#psY@5l4L1o@LC
+#=eMdZ_(wmskW-V@rL*CZ7H{LBV;?sem#>;MuU+}_SyD0!=;`H^%$-!H1B6-O<OPbKMFsd0+C))fzYS
+3Ff(Q;(8}h^i>1dK_;i1F4~{qXEm*qD7T+eo_w;RAiMd}W`+<sy8iTGkD(#{qvSky4-2Bn*ViyIG`33
+JKxApt}X*UZ`dR!VWuOV(b-#7(M+b`tau49?kj2kW|I0<#o>2SNk#2dmH+BJTal{B~=4zutp((F?|`=
+R*izkXFx^P2g1kaIr{!gd<(IfS3Z9M(_)Rw!Caf-cyGIZBzdsfQUd4U|}YIeT5PCgLSDGMyxlILvWlh
+UMxR$$rcxVD=P3rk>+vPM41~7I$Z=de`>UB+e6h@k(rXbpot~<IghDVatVkG&9<xpS^p$kl5T+z#<Iw
+dp*+C_ODU!?E)2)<juSJ|2O&7oM%rjg`h-1ClqHrNkGN0g!2D-tjGF(c|4bHl#rP;5l<quE0DvPWkoK
+@7O1+6;T8Ucc8kOMYTTNA6~tng7@m%mG%3g^O7gypJI*3<*!%}jO9KQH0000802@m7R?9v%@LL=J00w
+aY03iSX0B~t=FJEbHbY*gGVQepBZ*6U1Ze(*WX>N0LVQg$JaCyx={cqdImB0J1m@)`Vp%T5j!1W5FTw
+I#C-SpDLh?DLWUV}?fBbghDR5+v^A;|sh_daIG8FDCpBxp}qY$S3%-n@C=@69;h?y9;GvaZYODCZx)s
+j4*JtDUUVrmDN&%6wDTZIc(>ue^~*>$=)Pk7k$FN(%kv;{Eyg+p~*{<fpS&=X3Fov}mQ`rp<nrmmAaY
+Rj!)3c(ZHrs!WR`ZnDdFQF0^8RaHlIo?V;9yE-qMgdnvV!ZTSz=O|0F>kfjSuca)W;}dVwA~y}Q?W&^
+b)kMRnZ(;gu(+@If(t0DCWVdgw0icP#wfvZ5)pnbfE7LhV67YE|Kel--x3X-W^ZPkHzfJ2h$=6BUmPx
+9Tx~dxeB5$sftdMEh?&e3csR>n+Hm!m=SF!{5?Csk(Z|ATn&!5Ad_<G7unRJ(^fjX<}s-BCNC5&4XDK
+?=;zCnsAOPw(gJqmVU>)nH`Y|>TQq;_jr-sE*vB38UzU{!^RatoTImegAhVgve?-uT900!L7zWt$f({
+(sWcY4$<ZHbBmcJBEUlW*>U|mFptUnisIjyijvNZxanV><_>85*-kY8OF5V<iHQG){j#ih|+Xxm(ny!
+EP`W#Vt@*{Nwa;TWYg||mJ?0s6BLHr4-2ifyR<|3&o5uUc=NNDtho6)FQnS5Ms7`)Mye*ct@9>b7BX4
+oUd(dmqS|aMc>#O!3ZD4)f_rRpmAM$;mC8@ttk@?&+37}Vj+3QoYl4D*6I16q5J0s8RPe)HT{SY}7dU
+eQq?oUBCin#YyUjsd-73wiur!%eZL@2egO~)I>~LlS?>qSY0(L0_>ARoq229elX#w2gE);}D3CK#?aw
+Y4eZ^cmczmu{`Hbu2eiwWp%QF=1*_xwOV=b!_s7I=a=V_nr2O_RttIx1*~MBMLIm?UMol}R!?Iy%aVR
+4GH2TF!)Hc{n>IsDmJ|$yn@w6=Cy~K(J4b=-on`@6TU~5T$I@TqDSUflpG+M5~Z`>V9;gb~1ylgWZjE
+=YKrEzzzNl&@S4#=$^j<fmU>HR(fA@IcQMTF#Z<kL#V2)Gbz$Ky9R!RW=uQzPNapZglcz)NM*PhAtU4
+m7JRTU<d<MBZm&`I!SpxzO43MaDP*elpd|L9sq{+rB88?^A%!J9@%2)giR3Eka7kZU1t^3KGRPI;Da^
+AGmzw>r#Gkw<`%zqK{4WT@i>`eXMH3?}YG*KB-(v>4Tu6ZHCR6ri{di}G!r4U-T-S&C{7G*fj(yTK?h
+v<<Ymu&2MoflE7VDW<{3u>mr99PR3W1N&Zoqab>N|wJEfLu`31_nh^#%2zKq=*q=nAaAlDh|Y+tm`gJ
+gARcv4p?ZTwMzy)Wu>|?-wA?g1Pe|&9HGCC}2b|!Rl5H8i3i;!~t|p#+_mF(za;gzW_H%_tmv5cCiZs
+!SSLhj~kq|Ma5zG2^bNqK49Ou_^nmiFa;(ArFe_N5m+x0!FaUiz`($jt&(63mI4IkGA~Jmka;H-i+oe
+U!WJFh`bGiPKCY#ziW_+>K-$^TO+{{pS-;GO??E%bAM6Sny<VJadl<yz;58b0H)##KGJ0ip1i9ya8!}
+P@fcZ-N35NdBi}FA3%_M-TTmhb;b6GWjv|W*cu$G^|1tCd{V)tZSp~}NyeWU4l-h-#JShTxMovtK`+R
+<PZcnq9xG}`l0-U@AM+-vhJ{=%Jeybwn$bvt|?t{v_(kmz`?aF^jlf-e(v{vOJlcWo+Q66yJz7K3b3c
+N}N5?_Pk(A@-nXeHevZXyE-e67Rsx%!p_I_k=u?;$)7R`suUt^B2$FJ$w4gFM68FyVF0jJr{}aLP{H|
+Rh6~KY0S0=3}PaBe{uFU`SY`jGv8p?YTe>0*c*su-;hfeW%Vt#YmGwDw_mO=|22T3GwX#CUnHn(znSF
+dNJ;{4v8)CrMZfSyGMRxaNDDG|!Ei$WdJ>C*uUaOk%60z9yHI}hZI?RDPfVgbCuk>GOHt&@xd5djdQ-
+Wnc8dbgRQM^E#bFA4NyM!pFm)Q_h_unlM*(o;qS>=<!9?|p2Zjr9Kq*vK=YU2F4Af|7Ju7YZ0@MI-nK
+AQuhSK~<J`1c7{x7OE8ryRk6=ggD2@ik$)$Gczzk0O<@;I63I2X01!GHZ#@E(hNO|NjWk{>7}BhOH|S
+3#vEuQJ?KO65xsO91F%T}wIh4PsgHhjhY&tT9z*_p{&z^!$Eo1!&FZmpI;ck5&!uwUR}Y8aHIsBUft-
+P@*uo01nCvv^ae@)k+pr19Z3s5+VN!r~}Ml2|h@ffoG?GDAWoQbf*`%Km)vyn?0FxU$;vW`0b`Rgy>|
+l5lfArDvSLhUoT22S8_FIm0edk@LYU3Y6e6I7_Nh>dm75ffZMzT6kb=iJx&2V1SjH}BL`>!6Z-wu?WG
+3%R6Nz+u6!(etib~>+}S@AR2nlYkRhA2hKZEIeLnVBVAqmmAZ&Hk)*x@1-pYpoG|dPFLQSo4{0X9P9N
+db9MF)na)=<s-D;c03mgFu2-=q8{k_3CUBH`v)4uiQLIR%Fx`lf^nhE66IwbU5&(k-<~rrO+3Py}yf=
+Ze{~7Sx!L)qBEWTGTRKArUT`YOw-Fah3anm-uol4TnCPch%e|nQHWS)0xKA%E^$e!3S8pK*1P|MD~L=
+Td($ehsIEbz9}H<0~^;SV9SIv^lQ9|kH{<qGiptmyXm+Gtl!&IiGxlp`9gMQGZV*Z>)(AVHK;d2vxm~
+2(<7oN901M14=0P~p(CJWzLUHE`2Ig1G56y;b1a-;e@q+*398OP?To|e4~`FE5+vVX?g44*!Ju#iyYq
+P;W7{k+l>vVL<DyLd&PMURgKj?2^_+Vde^SScDf&QB+kGQ3d-ru>3Z26Htj*{39a<bO;RS1;>|eDKOo
+}epWmuRj<0F?v`Bfe&nHcJ>4b-d0kytBR;e6xQRBfYxOT_uJcRzidH))pNWemS&;pq|pOQwc;$iitPP
+#Dz*K!9z5J#4iDk(!rjy??Ms0`usRU3cVVKC-h`A<1>BuH_>F>eUAHk4lzl{ot7~UP56V-hD^*Q9gxw
+i`b49QqcncNH%rV?p#u{RV0l-ZCo-S*r?E>p5|$Ok4bu2H|~Vr%`NC=59#*R0ZlFw@Nxzgl;|>oWIYy
+nU1Y}d?%|=CzseE|2EZ~Ef4g||nxrMd0dixB0)&zXm@!=CD-@!}%=P5~z%bL<!Ihf>cwFv5XIv<H@+~
+qE-mogl%LPVH2#}PsfdZ4mB5ycxPRc_yD-bZ#V{}HXX*w6XLZ(XUl}TO|0<~BGP_i+h9RE7fn+g!V%|
+DTq3-~vM2b{&{(P+o`!JU57f7t~)N19kLLr=l^xrRoa>f)$5xGNj@g#}TU;L=}FRxvM|KB)+{xNSUkV
+O<WQ={J2A29b>7+RaSjr%rRglU?Bx5_xEyPS`u<9KbORerysy$AQIrPsDSoc(I*mI|Y3!fjDgCNRcpr
+sy7|2u}n<{(nKHV0ZKhTI~RZW!yhAY!Rc-siDSugVc^2hzBQJK_5l+q3<t5>PNpx2l3WKBYk7<q!nkl
+wK_i`3C$m6W!(r#M|9N-z_Vu$@ul~9C`?J^2{(AO;DHlWgVErK70r3IRKPyF7O(iJEtSV=jU=`@~aee
+|v=<}VT6IJvAR5iG?ImSUFOTrtJV#P+4=*Wd#Jq4oQ6+XDPp&=5T9(4$3C<SLuce`a5t;gjdbxpQ(iS
+b}lD>6Q6JF{89UDiENF`5!laSwN<pWfx3scNFoVvS*J4ofYXYN6vZ3$$1QFJE&%cS6r#gZAC49)gj}2
+dvP*{zA)~Z3a{6r5D6|MYf-{5H973082}t@i2H#<up&RJY`TPW!o@*F%^RZ%n;Y~Nbj7xo!*YFVzme*
+_7IQTxF^7POp|WYj;iAkox2U$<CiNe0h3*0=c(5?(i5AKuhXvT_0p;Ox&k~o)IaD)5Lum3R}8yY6xA>
+H)Qjn1TndIl67aUQ*cnI=&<>D9=~Cgp;kc12K}M{LpC@9yZB9kCUXNax@hSAAe8VF%kGc_a>#n(iW_J
+Q+!%@0Q{dCmOqdG@z@DseF*{Ixzqi0Gi!Hm#4Iqj2;^S&ejlVf?=%4lq&SaihjKCdNPk-V%yew?e`It
+xg*VNCcKq^m=W-4ev`1K8`Pv?G`u>dK-!9zLd>7&{RXvv%l+HXumDK_6?eZj8s0e1jLT=F2PFEl?DBj
+CnTNcQ(}%{mPKVm_a!p2wlfj-hC(2XN~?$ZRXK&H66N4_@!6E8M!g^uL!nS|Lc`y3`y+#8VD$Fgfkv+
+{NT0EYj>-nW8cn=YNQ=kv?t0TT@AdbLN+qC^>SIU>FlnIsnMS}V1nq?@gRy}?{mE$*u(OpvPs3M%tN!
+hv)1Q&!{=tJT$VUkQr#<DoNvI;TyV=L7-H-2LMOfG)qpwh^F+MqvO~71t<as?VM?w6t%PPR=u>S=e-{
+mgcv<Qse3sW)yM<9oOvH!i2N7g*c1f$-vZ&J43`~1a|Ln*PhN|VJEz(+qc_br{YG4iPD!`fOD*n+5qj
+8lB$(l-OKcdx-IP!>J`7z=}C1%)!2QqqVXe;c}x~E;@Xlr*9(_k#bNfzlaIam+9xE?F2LmZ7Chd*NH*
+SPUP5kNR10*o~sj$S*KQ+yA53O{V#<;^}OG<84Sma_rVkl#PVEk7LN(_lI_Umm=&JMnDsP;7nwMmQQ8
+N<(?ty_oF!Sb^N($4#7e{RhuI>m7Ir@$i8kMVw%A@WYRWWHDCnNZvA8rYg?>G3zSiO&v6~IT55KP?Dj
+aNPijA5y}PQvgmqxFuGX=I2xok_YOg8S;|8P*e8AH97OCnWfTt9;#7Ah;F#*o8JnI5AP_OQjf-Fm2!8
+s*a3RXnnEORA)e0Ou+Z!_<z>sHA_#s2F+R4tq8G$kv!7ccFvdk(h<%ol}Sug$=%qW8A9~3`0OtfmZyK
+o2|Xi^RamreY`+#JG5RhH*mpFO=%I(jjll@uAO91}|+UyLkZ*2!I=Eoq?sAPCcwXFM{^ml8BzDRHSFx
+u~GbWKgi6Q<6I!`6$()2ui?c+rYq)031mVM>yUzsweM`*nni(lBq&u?{_`Ix;t8T8DL;FxB`>IdZs52
+uEw+Bhm^2Z!S^9)kFPR(0-NVq#{?}}XQ%uN#82=ul@gig_|su3%V{fu=(j2_L*OO;g454vp*a;fls@o
+g{t?HktHIE#%kFrkYqSq-P5fZg1kIdygyMnq83xdF;C69vQT(^ullwUyold4<loX>gFb8pyJA_vd0Qa
+nQ%(kzOM_V#2yD}Q9#3bL1@$<y$-+=)*9y7-fNR5)n6k4s4<=z`JyzfE0(3v52evQ=-(KA_Q0L$fghk
+d&EZYGItD75e4YG8=Fj?smKFvXP%bTZd=<vPs^5S=I$=z(8lcI*2JvkBw|;LwvD#t#EyY_!X(aSPXDk
+KLaKO$xx4yVj|=%;=c%L~!Og2@j-F-gE6j;HG~5Vh-K`_36!A`AdCisIJ_1uTPkPirW?oFny3o_>l_G
+M%$)`<k{Q^sXC%$SVv&)%4d|1*ze@2wkq!_qXro5rMGQ#q4aUiR#!E~F9sw&4n<KGNM|d!umAz4^rSB
+0LhEjr4swM;*VPJb4$e@I!kqZgY~-tM80A3lW1EQD@OJA*t(=5!&;uS(&(yw-W16)A<?zwU6w&tGLfd
+v6Af6AWS>+g9ebQ+~>p=c`(A6Z)FmTpo%dWw~SxQ;<`8PL4;VGT5B67ahQzo1hNd^EsVf-<+CT3^t=F
+Vfqvd8D=J+6L-;k$&^_&w$b?n)To=epX;*cUM!H)Sl`o!gi~O6+_1jhx`!Ue|ne9rW*m^1H~FNl%M(E
+IhHFB^%I^N_w^iLAft%4?yvKckLltVG=-hWrP?%_Aflf9}lm;2pyyi6=HX+8y$i0gWSjF&Xy=`8bkpI
+l8~+cfhTBOh|4Qa=naqZpzQ7@81o@n%&~4ux@yc&KBL!xo3fEG3M`m|^Eu`vmn|hG$vXG<Uk`_vta0#
+wybeC&w=av&?jVtNh`x+fyf(JaOhSLc6;GA&;z>p64t0xO(oh;&>hjPsSU31|ir=2-Ui%#wqwbTNw9Z
+p-ziIql^$g#4NssYxQ)HQ7K@;Y@h2?Omk+yW(dqn=7u3&J{W*Nv1JX~peCzJl5JEd<$=9}L7Hy30`qV
+q4u{ub!_TZ-k%C0IH}k9YA?@nbB$cX6}@X!-7ij52shr4kxA(Qn2JrPrQFu`~B%y!4RRbazDO`f0jQL
+o-J_PzWz}=OaV3tUjhgUy6KTx^c)VNxVBB4J;(_W*Ap~k0Xl-A00~iamEPqr22;g&xa)x6L_&89~NCw
+bPl<45TNti;ADA#zF+|sh8<cL7mQh$6Cf=|OFDH^Y;zO#Jr&EU;wX*hri%Xdo6t^>cki`%kAD2JYOck
+u#d4`7*~xg?8oygNqi|5gFqt)qePVAZ!T-Nuw`!Qa?z*7<Lk(WArm(ZS|2CNTGApgD`9~Ol>*g~(DDm
+CzyM|FG*|~3|ANGwH_(3Cn*fqi+p4$SSxXk9(PFQmfN*Zh=8(n3$J~U_#>&(VHf%d!DUhqBUv<5pcr&
+;<vR?#)>5rbr400bMy?&XeW2L=HGY=HdXN1=wa+qSsdAiuG&a?58(J(?bKanSZj%YCTuhPS#=7_tvng
+nYV#V7Q{o)5Z5!9#GB4)S8TqHzs2QB=LZ1%TzzG<82!ZIRO>)LmS9j0%w1;nnE!P5@0%{f*(_c(-$H<
+Rb4QXq3h~OCn7xEP|k%PlyfuJe(*8v=>Rl-1~`~*?B9L-Ol}!|EUf3M$jcA+#5#VyF-A!mfJJ);K2w2
+UMpRkQl|ZF!Q*FWL;nG-ht;!uE;W(<R|HiwxZX_ba+MavB0|p_+`u<;Sq@|Ycv5$N^XH;*STFOyBZ@1
+~3Abu)5<bv2759TpPX>w}qNDM8Nw78fL5jeAKAYc4zXa#k_8eJ<tzTWVvw{<2%iT#>A)j(vSP2ATQ`f
+|C4-9%$oo41}*A?#z^USrZXGq#NrQH{holQ$)XQ!Fi4t(>^L23YD?=@z=u<WyWY%}$-3oNPdIv`Y-!o
+b2|y^aL88P*ZhM%G<%Q1|Mc92HS7iVaJqr&AdqT1vsbU`!R=ZCmFd@R;#J7Q&{>RZUKC{jLS>|KW6A*
+4Q9113rbOOzpg0U>h2?nBWwD)vCnF_;S`cQ?qbMS;N0)PTcDwg(K5A@I(uzhs?b&6tSYGt@Oa{|wp;l
+xV9_xLDj9?Ak(qO272c1LV;uN8y~*(;cs_aQfj;o5FBe!>MN!@2P!<F|{Z0|qSORHR(2K(#zWd?3g?S
+S^9FvDp*xdlpq#vZdxFyS~7AE&BpKh$`lN^e#n@MZ?+QoknGA*a(^_zERr+CK+!l8r$*F>z^U7=H?0$
+<Fz;zMT|)d`85XxBSBD0+1AD&ezPrQsHLugnqu*k;K~yX)2EcjHK-wWxk%x0@%i-Gxpjf<d3L;}`MS#
+Pdx4PKnP}4(rQ&Dwo&g{g4>?J@iy#AI#?=6tTS)zm1@wjGcRChaU^>xJTOM_n!RfSiw6Sp|LmchlZOx
+DFPqA(ToE6W|nG-JgwROb(@c6_@DPx`$Yg#PT7{hX9GD5X@UNwPY&lL--Dbl3vb2#zlBENyT6fHPTcL
+tWHU3Vy<^_SfW$Zq;Qzs-&U588344J(j*BAj29$?S?x109TV;3}6nus-_@&e#XX=Q>=tpR!98Ni5RFA
+`CCZoupVO+<5)P~<<Z12!}lLGRM&B>&x-emK1_64(pFZ$FWBCy;R%9^##A#I9K;s5$almzSVm$%`K&6
+oa_PKEJ5{FpaO8-<r{NNYZbUR~*Zz!<bSAECM{z(Wrr=L75!M)1q2J*{(sY;>)7xSBcAj?R;U+zKbjp
+-0LX89I?>NNVyhn-g%iR)xS{*_(ghC>J-gL%xTp@Xn!}Y~+w02e=J_{yMMzbZ><hPo?gyoLuIj?@G%{
+JSc6#<;<fm*Dg9xaPp*h@-|(qat4^a9=^T{i!Gzc-c){shZ}NTwg~{Rr^LcIFEH`K6|D$34b%ZOH7X&
+BR$*?7?QOQfm2g&)mQmYjgzhl@lCR+6GZnChEti8C<kG)XtV-4y9UK-R--g2%f;ZJC@RVIBGd{qNr8I
+P*AYDed(F=Sc>Qo=X#&SK{OjF2o?B9W7E_%cg5@3Stn!&?kdZYFxH_3tCkiv9!8!INE1@cNR+f5iir-
+e%}7$ibtG;c_60mlZT<cL+%kq`FDISoHqFLIw#dUu|9=h2Tb^GDZ-<=b81b*cJ0tDGA!yX5_p=L0M7U
+CAHLe2ck9X<N6VovhLJ05a&-q#>iLi}}XdMd!BoTpL})d6VO1m6FT3fDn3kC;d5>0Ny`%^ZQdgx*(Ng
+0(&hsDJeGJsE7}1mdwZ$Hl(rT>V$4}&^aINR(e_AOz6<6ZQz+ZGMFe%O!<_dQTy~dUI^exa^ArhtCr%
+*T`d;XWjW_I5Aw+qE!8aam_3vws>2l?nyB!ef)q>SoypBAur*y~eD?a;pI@CNbf@vfOYkS}&E7Ig@tj
+#ZrZRmM!|Lv3+)CbBI_SmcI8nfl;hv*LLZ^GKJCne@MRpmfs!qBcut4Iz6lkpdNpU_v&}mG#NT7-aob
+MnO^w4y0rZ@0juwv4ep4gMIyfHJD=ynv7JRWFy-h(nW=9mY`$~jo2z!eduMq)lFNjTM7hz=v$77^v6$
+>snvr87DHLhcg%jSGr~8jp|mzBH3)v!bC3hN~=VYr2d-rzl6QuQ>!^ATuf^GVv6%Ejr}ks$y~#tQ_+b
+@ppa8FO5ae<eex&<ZUW*_Y7Wknu>1C{dmS_v5JjHR|9LN?^mbE!tkPtPB;A6jejaEVsc&qc0+<*Tdr=
+X%^f8&H@iF$7rVS@?4_406Feg0B&ExZWWPfp=O$<U;x8B9Uy0v?{|D|^H*5=3tw;c`+d|)4*4^MsE|_
+j9!tc!=Zt(~bfGGT7rmNA-hWD~U84MEe5&e-fbVcb)boLDEE_x&oRqD&8=x|Sr)!{ml${^5{(5y$zb<
+jOGS@ZV&sUCU&Rp2D(>43$=AL|KcT|j!sIi7eY-b3Pxca9G+_?GMU>jT8`L>g?k;Hao>@znRYwHpjN6
+!3K@aX7&QZ3odWrA4xuwhSd9Rk7X^uPWHXbCBtZ6g6sS!19K!nbEzse1j^m;SYcKuCs!>dCecVGQV+m
+{KWP8&DraBo_3hCaVjP86+8;v*E8{B2f=KDQ60nuKfQeY?v!K9T4?5*>xR`Q2}eA<z!x65_F6#ZoWA6
+>3xHEU{g)4V#0|UZW0%ITh{Qjumb?=@<S9^Vp&-wFe_A0xaoO(;-@-o(t_LPlg@2O@Q&dr2o#^DWI^n
+L10-#&qZmM4_cGLu+)mY$!f+8$2-2r#~p2gDt0Z>Z=1QY-O00;mZO7>PRIjbaK3;+PBFaQ7^0001RX>
+c!JX>N37a&BR4FJo_QZDDR?b1!UZb963ndF2{iZ`?NW-M@lR5kxwyh4$5e@=%|f3odAaOWMQ1Fcj{Jy
+USQBsifqO7WwZt!!MB%wYKBrUTz<}YjS2dobMTlAG%ib<g;v>6Rv;P?QX}L-N{z82hw(ZM}=g>Z2nH`
+fl0mB-**6KcRv2-{Y82HkBjqvzWMd_io9kG6SQx|ioE5rUy*lR&)bI9EAoN;F|cOCR^;Q*)$p~UvOm!
+@JKp8x4Qr}a<Q?5yQ)DF{dR|L=(1tc`!#A|%f3mWn2j-*lre^|9$u~832#2awhsy=PT(CdNO?x=drm{
+$Hnu^`M7VXfT>y0H`+0%ZIfL<}j;)mbP&o4fFh@r5%4b#k6U_<{xh*rcfIC7G2+PY>Nkf%j^%bV+SyS
+R*}g~-Y+{_Bw6>(yV>Vhs7fdRoz*T7;jeWPb-e3cenY`xV)-zGTe}7j1K3O&=u!GO1-Q88Qh-WhdBn6
+p~$j535X|MMM?Uu>Q6c*FZ)}fOc2l-3PrALsAw4LOXP{w-~aoYQ8SJ>s|C5jdI{}V-b3~9%|Zyh29F@
+v$7rfZU9T=+tAw2P6&LCNHJg2(S>|5{?3HDfg-S}sg$I|{eSa*{}xV`{hManrc>!>`b7LBN%ETCFw*Z
+CsXP$Uu0Ml#2_>5ry^OS5!tQ!O$(FOalKF`v@o~?9yIWq@WX(v|cIwg<sRn`m{pk~`8tz`<YMOoelmi
+L}JxVxH^!Ef#bi@wy8vFpc5x_m3ioel2$YI#*;gXC(WXSysjI7k^&JX~USk9udn!s*(%^(u7GtjTll*
+;#_1!Iz|LVQUI7jiBm(!Dx4Il-6*-ci`#m&29cs<pIKF{Ugt0Mi=6cxIe7orMXb8oU*LBP`(!1PSoei
+WqN{D_GmqLxu8X6$eABnN^ALO-ZO=qy~Jz;|(ejtl$)Au}1P9buPi2V6zpK6{r&?-!-jZB?PvC!#70K
+8@Sy^F)+0~NH_r&ESrS9=tR3CmnKkNIYJfN5?WQI*+{{ew;4HoMSg7?Hku(W=MZQSPUa&*>L3(*r){#
+DtejfQn(R;&8;V5sc#$4Bp8x=7bg28{7g|deZtYp!6^W9)rS3%UQOTan{xD~M==v5<_&)4g>feU_DG$
+KDwZ8AezNJpUx-cBc{8{|hbN=fVDuHj!e0Z)p>CIL<Atbzhpf&nazlYqir;_aIc1>$I7K6@;R4r-RUb
+!ww=9DyaeSbO+3wa2hJx5ljgJfcMZ`l_~WaIhje%I9ZL?=jh9WU^K?C{uAh+OQ6HZYcNIf}G|jJ{8^u
+Mh}SAO8zOQGp#To}CIPaWL~^U0JakR<|A2O2p(hnUkOI?HQ|>tw1?JT9ho7ZxS+`awdm<#9W>(o^2}*
+v_B@Hs5L2_L~*U~5~y8=Ln9~Kn|;f{VTyFzC&^YY_9w$%*pejK<7BQ&NmXeW6Vwb5dT5*788HWt)UcG
+Th(2fq$x}5yc})6H7?GD6@TH{)-3K~16iQ&v6;w_AUY$GUF{0)BZIuIOo|<I-6^Rn{1Qf~z3SPi=uB(
+C@Rv>uWignPEK>@{Kr`<*hn$V}8em`i7&}$x-j<)EH(M#&8ij@mw^hGc9SzdC|m(UfwHlXL_sZ+zpGq
+UTWZ)4-lV{fC$YtO`b@L93gsLc<@s_j&WP+xlR*cccx<qivGpO{8c%PW1lnmUN7De2W5i(t`*)P7ufM
+`uq#3vQc@WpBA2cwLoY2b~6#SH{`pnVF0rHK}_SuR&GP#iBXryMrdq{XQ2A>peQ^QFrdNgBq$695?$G
+{1e(QRbrUIMINPA^X9r7X9q<%Hpn;Xu+;GEZc~_VPy9as@6h{z*SELjJ#DU8rL!V3qq_~Fm&f$viz=7
+^6w&5C^rHDmtH?h5MVcnjI>vKYiv}dY`av|I9;_4s@}c00@ZXS=$?b~C|1&<&w#3k+3kF2R4*tVvd<h
+-xm9iV&^rN-#twqXR&cO=9F4~^qEZ|a54$AU}O=<GZOrpHxg@neY#!Gi#W^3NCDo;FdKE#Sw9FU@L>H
+R^@=DAp9Cqv2Q<gZS~;|;tZwAr)Gb?ItM8}sJAAg`e;D?smk>dln0m{d%Fl;Mq$0H_H$OlRZFw8`+Iq
+`{(jO2^~ErrtA>Oa>kaFn1Z&T2%IF5*dC#rB!7CC?2iq^~r!Qb*=@n$#SUUMd|8*(jPs^x%yO>R$?XV
+JX9^MW{}t=gn+m*hjUYt5ZEry5vIv>j1|+JIWFp}z(1>r8QEV~exO9b`PCLV3{tz0u9>!6$R28XR4<N
+hFoI%`N6+!dY<Ueb#te?JF08>etq>4n>ie9$1A`a0=s_-JctpUuUaGS>p!R&r(Lp6Ktf^*X%{CNdOk{
+h&;z8h=wJo1gJJc0Y(tM$74Tuc(!t$8u`yvR<-xZmK&b?ECrQ?`v?tGDu^DuQcy^K(H7FBzs<1sWw+C
+m;>T0!et%+(VZXn3<b#*)ca_HlyC9>J9+1<8@HFiSRLVKRd~n=%mw6!iCb*wDjHeOnbEEHkAU)^Z3r^
+4N`yhLKVp4ui=ny?Qel17C$=aq9Sg5euZ%$H*n{ukS4zh*jk^yGK9yYm$ei$qqns{1Hh)Mr^ZK<N#QQ
+`>DFVlB*vh(+qoizccyb2WeMkLl(yX48gFyVWb+m8u;@Dt}9j0U;-svK~hzAd!%6PngK8Rp@*^xd>{c
+4vynKyhj^+g6W?nmvEH}bsfFQb>0eM`s7vFwCls^_SjwGXl~h&J4p3GPU%blmhyi{Rvv3c7FBj?!d~l
+%uUX2!`1f(3qbX}$;an%=QE!$d!mZ00CBEX*XY=($y&b-KM#o`HKUcR7(p%h~G2`d7WfPK;(7r@ooj6
+60mpumcw`q61L+c|!f;ifkBP}|vzAQ%N&fY%Jo57mbEFKzZ-3l#;Nad;U8!;b@7gg`TPP-?0kP+!C|w
+{nm+<mFs?Jzy05>SVUeZoqJ<Zi<b()ri88FCE0(An;=zX($yG5w*<A$ho4{Xmg`1ijk`vAMTamei{lY
+s`m*+E+-G_{ErDR2r!oq2E?9?X=XxsmTwk$$gy`u9o_C3tK*zNyu_!G3SvHpWzhT|#gi!hIbJkfPA+y
+7$v#^KEcl9uNXbtn{l)Zkpk3+(mocnn^DCJYk6J@ZU)J0`KEwA8#t61hUVf9H9&+NB!Riro=pZh02CI
+;VikcqQ6*b}XsLMo~>FG4VJ~vPq+FdLR?X;&WvS(E12#t(1N`w4R)pewDcO?8n7W#=t4MJj7Pt-^(Rj
+}c83$5F$g8URW6#vDQco@S^@<JBH3rW%!GQ)`gYDUmot&^a<H2-1q-p9Nr)ZHkGB?k`pGi)5^;E@7Wk
+B`DLgR?wKK+uR8WDmKP)BnW9&>YMF&rR{JtbKTsy(Rbhf#^ZCDkzQVs+qwVxrNe>LG_3wXVcy)2nn?`
+K9tei5R{noy{Bf4vd|1Vs2}IvVW#3Z2)7nII{Njl#JNth!`cbXL6^60MQNh3ni@wLRi$d{j;dNPe<VZ
+RftIhIRwN-w{<-B%s$;2&A$JhKP80Gsa%VWpGLIMZB*>)7kw%h7%mIM$1s_y)Bu1PV-X0e<l}gpCjh8
+bc7=MTF37xmija9iF{OkAc8qhV4X8Jw8EHp@*P$`u4{R4KH2Pe1~c$t{#H$G)GFI6R`KoUdKAO+W^6t
+iK=iP7Q|bQG>WDQ9=k`c&y<qKjWV?IYyU<jUx2Pvtm_gM(;upWe9vo>JkRQJ{&*aB6@wJCb(T|E0;r<
+h2uG<CUFVKNv$N1mBMMUxWU}%t?hkU#S*Up<{sR>wr^x+aMHd!RcQLM(`a-v;e4K&`4fdxxZ8m;>!A(
+dIF9R9*s!}g#L+D&Ddx{BmriS1uy7=m8NRR2HvY+2)C?%L(<;f(FxhevLyr`*j8ZS0C2$yVstE6Y0Gt
+M3OF4|7M^7+=hYdT6Kc;QX2<D%2v#B500F$&v6ZJ+c+8_$kk=j)xm4f+b)7BP=yGj>mF;ZUlb{_XXOm
+<ef*4~+)Z3eBkmpCpFHaLIGIN<Ym%k!KShQ$eMNpjlM;x~lV<B$(=J>$a6+w5yi6bmyTkH4k5N?dM(4
+v_e#6<xAVv9hr8!iGXZXZ6+w``=C`IfET$*G1zCrz30Ur<W}1QY-O00;mZO7>P)uJbQq2LJ#;761Ss0
+001RX>c!JX>N37a&BR4FJo_QZDDR?b1!pcVRB<=E^v9RSX*z~HWYsMuOL(ukXBphu<ga03v_9^1<MU}
+vUP9`m9=S`t4ygRmBb7D-**l#k|-(d%M`$t$#ds-E)3t7h14W3wp%W?BW{1HU8Q+m|2ioDs@a3Sm$dZ
+1ANIK{SLrI}Oz6=@7JITP@|>+SFN7kF>PoJeWa~G4<!FjhmsBd|3I3#c#gyIChY~FDJ2!t{pJpe&pPu
+}2cKO?wpolR!=L$ZrN>oDgk>x9SnPzuPtP7czboH5{L+Krp3aGp|tCcGIlDXZs1THj_AQgQ|KT#lB75
+hCEYcJx&{(Oo>vM*hZIa8>`F<$ToE}r66n(9h{fHkY5cX^dvyuN`L%(J&wx0i3mWPW>cayp+631JT_R
+tCX$YEPvs<PgW6X}YGGdipKX*_v%=mFtX&J1z^cuMfAw3TEai<zmeqJp1+G`fP|+FnwRh&#6UBP0h>q
+X5mIsp>S!47s04fhf&XpT7}MF^=XzpSGB5p$u-N0N|%)$jrb;n)^tSR83N#;bjURntDGuDjJ2CW?%Dc
+xuH%{}v10HMbkC+lX<4tR3JyXZ!bOKbH8r4Kz}9j!8lkI9l9|uT6b|Lwti@S|lCvxUGHcA7QMuZ=V~*
+YTcnEdQyeNt+4*?g<ff1W9fVul!0SSUC2<$nNA*Y3=95D6Emx{^5s}w}ocvK45z))PU9z8E*u_cSbqH
+yV1JOST|Lb43fq~a1YP}~9gjjWgz2+$*Rz0MqetXRHD$mA8dECg%9i_7V1Z|GFoFvK;5@pQtYac5;>;
+M!S+bknnFXb02dj>=hd`|iBQWU^$25ll-!O;*V~B-ydNoJGGv86m(=iVcKY@1P!C+klfZlRL2!MV`Bt
+q@^kug<hM|B_ZqJQ#-e_tt_fCemM>UlQc1vl`yd!6BpU3tGZ)C<+hDK6KzPOCfJZHqR^Hua8FVWp0z7
+X99?k09psNY;We^VSV0KrH>fj!NYW^&WtkO#0cxlhO+<HGE7&kzS@zfv*KRaI9I5uXX?WvWN-K;|Bla
+AsM0U^DdIvm+t+uz&@t_p1p;)9`QLPVg5<1?KU^^z}X;$wk{x6G@#mi-*xs(uC0KbAWRxz42?#P;jKa
+;juwJ)7hV7ii`?h2jdZu@8;;o@mgVWQeXK@TSe7G@hO9ny@kk}a1loFJGn2_PVj+ct+bf=yNON7`;SZ
+Y!=2wmC1~9DuFgG2&Y7*o#jB5CK;(r=)Wxq3&MG;^EL{uGJ(h&4)174rD0S<MA=Vav4pD17_r^re8V2
+QXyMtw>`RJ(_54OFqxQOOglA5`7-<d;{4t9iAgRfSwPHlNU;SD3{&!mU&rMK@dyV4Ie3gxOa!XKs)!F
+#&Wx(me4fDXagWN1Y17TkN=TV}t0p-68#-uP3|lx93Yd7rin&zC0bWTLz_<m?4iVeQZIcRvm~6lrg}p
+jj);-XC-|U#tYFocS3s<0-=J|n8y9HI-x9ODp#mGH{Vpi`NF-`yEP!6;g+TsMe3ao})<Xo^66oVe<tF
+RA<0uCdmYl_eXf!ajw8Cg*Q-Ik?+`CjjoGy&*&47h1c;IR!bwtk2os32iQF};6=iwg_vWp{${yB_Baf
+uFV=f%_S?3Lv%;RDk^iRD1i=&+MSOMb>XFkORGV>;crL9)9)V+sZ`uHbCPK2#6N$eHoG+o6OA>`<ji5
+M%pr^WeK;D*sZk689vW25*jhU&FMqHwmZydM?MA&mN{LqI_P+zP%FStAct?7pwGMzf3Jz3wyqQEAy?|
+-#bRyWtq(3Q5v#R^^v*PiI7wWp+D^9yn#?45o>McZaIq=kdN_uZry49aKRRQcoeZD2jyM#fd?11i+e$
+cAtWTAh1W}2lf*=_}2sPp^oFq-gHkXMm2pw<Qin24g7r^!nBaY54=Qpp<&rjb>$#X?w%LH>>ATBJOeR
+zFC>{q2Z>w}xFHzO_OfTo_dK?;1L^Vc`0^P4HYqjw-~B3aI0(EXXX^Nyb8wn6_0S2j;fCKHhHF^T#a>
+K|+R@P6O(;aK)O3>}F)9zzuSdCiDxHJx6iwZ@qX+N#K_y|6>vwEkbk0>mxdz-fuYaqlV0PHMP;JS^Nc
+E$jWR5s3Z}`F)ZZ36FeFANm+r3`R9)B5w7JguHM|VMPKG%+$CkMPssvCcu#N&k&zZpX$*pgOyOm3-V+
+47WIF&J-i`D4azNYNWThy#piZk?A$2^ixoZ^Zb?w<{E2ngCIiPhAwP9%S|H>V`Tk`;SDq34PoL>Kwmj
+B>fT3i=b*;HSHd?w2CmnMobN@9=@gw%FIIy9A_)XN~=!1yhFeCW;j>LWcUXUM>B>ku0A`VoydahxrPi
+PZ8;=+-{k9O^tw9XM&8yd$nee9_{9wD%gPT{fP@7)=Kf`igSXTRAgo1)}d+zsMZaGc{$h55u$yE~jHK
+RI_XIq-icQ)A#|+HUe#0X*%Pz?3!%`bjeS4^T@31QY-O00;mZO7>P&AVkH%2LJ#Q82|tt0001RX>c!J
+X>N37a&BR4FJo_QZDDR?b1!pfZ+9+md5u_GZ{xNSe)q2+1QaU)ve0LvUZ5vUdKOKyi)6RwAqWIUq8)Z
++Nu{V{-J<{f%nV79lx4R@5KH9TIG1mRmWRGmnl;^iFWdcUr@8~{dfjt12qw+uZ@d}BVD|K}2RgU&vuK
+6lx>Gs(pyBDc5%!7JZsnkJcE=B*{yg@$_p#TqYk9LW(t6n!<*R7xP8B_`zH&687`1E$r=sF**UE}F@=
+sB=ASz^)E$9MqMb*gSnGd3@y2F9Dwd1}rujg0>&Gk3{Q!OTi*Z21y?{oI><?8DC;bDpMAT+PJ=8oe(p
+!g>^s*=wm9xrEmq03tA_}J)Dw69Wi?LoA9Nf;frILM)L;@*_hqU=W9k9xJj$Oy%@E<^>$zNNLaB!84;
+wpy*Kh7SXKc<J8kkyHDfZB`6ENs`bvQZU)>I(6V^E91|giFK`DonnVhLDXAtOVfy&nUIK~SP}2%7a$_
+Dm;`sV?EdCz4G!-c$y?11TsG`Q@EXiD@{36|J&XeggOfO082heQ-JU&mloi7h`@w2_&x)dOWOCnvS)~
+$xj1s;fU0y-RXEh2V797oZU6)o$I*4YMvGsd)2dCOtO^o4kQ5}eGC_F<tQIN6gU6RjM);rmVVYUnzqq
+oV@4zEz`HW@UUt-;O{R?3X+4Q~b!Z@q}7-zF3!4c^|3O~V>UE!ORVxR6%#F%!IcabYR~HQ6dYH`TK$K
+!i}*9=zPEZtT<V^Vl_+_o^CO@@CGgZ#NbTa>msj-mt(QA@QHc-;mSZ-Ezm;P8+)Dh$f+nH?CSp=QN>u
++ptfKfHGo`5U;WpjJs1Y%yG<3{2q!Vi-akmN7b5|oi_d$g*rltpl<I6B?fT%0PBO`s(LA1c9&QVDKTY
+p^Lqt{DlKa|Q%#FG#iyi@Y^|FLddu0XP|w{Ure*u?qqO<w!`MX!N3PP#PsaKWXuC&PD-nIQVGtO41GN
+L__X|x|QSti~QA>^JU4s9A7nLqOiGys4^U9b+l^Di9T(8UL<9y5IuJS4!ik2tl(Fx^F!unj!FaoHlqo
+;l84x$G?_!W18Q8g#*eAF*pV1s!t1wvQg9$5(}l)yW!R>!jMAQw(VQm6wjO}kGJD=eb(**34Ashd8A(
+aj0R%>Snt%zx$p5(-LHbL^PZT|7$EK}#A6_6butTBJ0|!xYJ<)PM@dE*e8l!9L6|$fW|~#`m&^-bbeZ
+l6MokLC`{f)9<ivAhbo+v3G^o@7L&>cLsexXa$})7SVwX^q=XjsYNbt^p^dFYKm!wC{1DDBEcs;fI%R
+ofTpWT;434`((Lcmgek<12=aI`m8AGDBcTLXAe2~4l0bVOaBKqXfetTfk0g&o?bveGf88VRpRzYOl82
+fzge9avXacI~q(+NDFCek%Ji5#=*QQqr5>eEy8{2xrzJpH2@UQqCQa!a&vY;W9=z0@#*qL%VtwyCF0_
+3{Q$vi~K?WRIXcW;@6w-{O}XbvA96NI<q341{D<?ffekN>+%BJwbjlS_(M>QrgmFTgpWt+ULCNn7^UX
+_)K62O8_c*h;xmiykIf(N<DSX=B2&a#s3SP6=Wn>m33}vpI1FB+hiON6+>&5sGh>=r#LA9IurEgo`9p
+U8`m5#wFu*Teed|rm$2@xd<<p&X(out2k~Ul10<K36;$SV+-)I&t(mYKNWS}6Cn(jT6{ydkckS0PFhH
+lkOuK)HZO$Rz<naI7+{#yjcmcZuYwLem^m$*`}zhT?XJ@|SUU?&pJ{r0@&_X@EYYv-0M^IQ_|SLADx=
+hev<;YG_>M>0N$6r90wqZ9?T6DW@cMXpRY5eSOV2hgPfu}_qN(G-B+`P}wKehLZ>8@&?qhop<^rWgVH
+dKP%ylRu%DoXf%;xN~LyciQyB$k$wX$^&i`$s-+u%8$VTm1ojOOVzrkYPg+sM&wb?KzR#I$wvcu~ZDm
+L^xzE`a;v)6AcCq>A{`<iV_BH%Mj-ZseMA{1=wjxW2>_4rL1#elpwZFZZ`gCYmvArte2uTv8TJb&E`E
++FD|@qu-3{)~qfugk`=BU-Hum+nQ@Z*cfO+T)1RJGstH8aU~iIpK?2`y6eY=J$GF*4Rm<ba7)yJ@i87
+C%}j{nSoo8`r8&~f3h`8CEidUDG<FeUPF+vt!JsuBXgW+IsaZG>%!ScS-)#dDO7@<89|KtUlSv8}_H_
+~<SG;*g6CjN`R9@81&(QwnZYG}GVbU3n2X{a59JapBaZF_s^0*Q^$MmDU$9N8t^Oxz@_MS86GL>?U_t
+xEpJe#eOvmDdiF<`N4QBS)J!`SC=Iz8=mk-BJy((>9$bf^>DcfCPp)kgBp9r1p;0?&qKJCB&%>>t?c_
+4Dzf1neYPkjmgQSJ)Tw|5poM>xKNCca!XboDcre?gdP}>k{WxaD$&sU<e4lT}@MFc;`QfXe^u=Ydps#
+ORf=;*Y@hZU<yI@WJPq*|955(OMzI{r`aV-f*!YMNzfuEd!pYm{+&GmOH^w?o48=)4G|<KmnO2tjERf
+W=c%MC-eU1mRS9-~ef9DFCmdZCeiN9_=qK~3a}mzvlW!Kza?vr!9LLGtJ!c(f^?y)H0|XQR000O88%p
++8i=lKQ<^%u$E)M_zBLDyZaA|NaUukZ1WpZv|Y%gPPZEaz0WOFZdZfS0FbYX04E^v9BS6gq}HWYsMuQ
+(7;#0DIq&qkG(tPjPyVL;XaLlDr6bYv5eNR6cIct!vF4ylVJQ*N6H32c$)e!g?DtZHo>lzO+5YPTqiu
+0YqW7RDmT_VO=LHfY;BcdCi5zxgb!TeKIotQkL`%C%v&$X<k(#~LR~+f!#kX(cmJ%72k7QQ??XDu+gi
+l4YeF7^<9Xky_a+gzQ;Z<e9E2q4J*VzJ0yMV(_0!jt8`sv~-NW$yce?a1=&yS#Z-RE-W`%yK5q?6Rxo
+&HOIl(hcEZ{A0Hm(SnxH&)~%lSlOhpiDg5C_W3-uLBg1?8kRDD4jWk%Ha<c)VdzO(FXPV4uGiX~bfF9
+ZE^isHI=A~4)p1%tE^0C78Vl}5S<eOE}W>aO^9<vvYuPs@5;uL7H!@Sj38|^T2oMg57DxJ%MkmBRP>F
++2BS4ZoWE<9AxK-y!L?a+M=XG<PX#W_(evQk(JUsUHym)m9cxt`1UY7?wUk|cZ%ywKtqEnBqa${M5v@
+mwM}4b4DTY3usnVSZ+VUzI*880B3U+_b`O;g7~3<Wxy*vGiOcK}YHKu-(=tx7P|Rx~69JsVCTO39NgW
+?Snjk62$@G8TS-4P#P+9A{S10TXUogRFr7q5Dp4ilA<G$0fRQyne~tvSvxoyQP*h3<~*NfjLGqUrLMP
+IHUu$zX)HNI+3KST@Q%{GgU7D2pWs91@f|S6uF%{X_%MchuskpfigGMK<T>wnmKMum1-EzbyH>dA<O2
+9(MvcYOS$1Yv4iv%sTa&CWPHsmATwGG!yEGXactIdCuOm%-EL9$H7osU$`uH?G_lY|QlP2ET3!Xiebv
+m^<Sa}Am|95*l<EbQwQTC(?$2&>Q8YVGKVsTzG1Nd`KcyHt6yEuW1@=CHQGF#TZ3}i((p9)x=EndAj{
+HHklC%lYm8}|6TkG7?*hn(8qZ1j>}w7PL1><bjy0Cmbjnkw`h(8Z{%b1X4niY0Gy={&xepB|h-W_WAc
+a`iTTeL!Pmjx#MZ5*3=YVPriT*U92Lqnmp9em&K;I+qTOxll6eF3)z;&HXhss~x@hS^r40<S7&tb^LK
+ng<eWk9;8!4<{hSaceU(<b_)GN(6iiWevWerU%w64J|(`Jd%Ok%CJFSjFr6P^aZz|N>*!QkO#>J6w2y
+Ir;HS?8{c7?i3$LGfv71P2<kn-f_AGnu)e|{EFB2hH+8MF!)MI`rp_v!^=%3`1I*^upT-6(RXF%>06+
+#ZTafJuI&=Agf=(i($t!XOT5WoBy>$rokBo4EG<`b}*<l1+dKHo#tjATzk;yKPsiRXz|qBuysjsfF+?
+$<qp)9!Pc{n;$f;V<5k<}-DsTmJxu--%lPd>4+LvHu^EBwcA2%ebgVA?f!*w8qY)Ao*K2G&g8b@)HPX
+388(3-e^dVvE-MPuc4cGtG)sCCY%{i#ZBV3G2hR}<jLyhqJA&^`H99l_3+vTyBx{>**$g|mOyl(s`h-
+T_b2gyjv_u9J(J4m3Lv6qhtR*57w{eK39W8V`&*lEHk`*v6Aj7j=HmcU8oO~#Q#7Bo#WbX%eUa`2cku
+oP4K=bVhH^y0e4~<Xxf&<;+QfyFc2M6wld0sHpLrvJhSpo7h97hP0Z>Z=1QY-O00;mZO7>ROJ13D&2L
+J#}82|tu0001RX>c!JX>N37a&BR4FJo_QZDDR?b1!#jWo2wGaCxm+ZExE)5dQ98!MP|Z1Gch#7zPAYG
+4u^6P;9{3Z6AVwV5GCng%(wka_as1-I0_mT5?(kGZ0%M`P`Auz3|A$U89X-N^dr@-ppip)wX-G+tx`n
+TN}M&x^ay#7Fg{2OQ;rX=yQh#@m<eHY27SzG_uLLtR0wIsJs;Aw#Way1yFCOWpb#J-N15Jp>C;bduCv
+6;0rJHZYS!h1N{MCT4`VhwR;nKmh3^gEiV;_x^2#hvQD_xqO=NZC+pLnZ{EE7^l1tLUrPvc>jp<{?~K
+uA3ZWY?!Xxs#R;ns|b7w?(52ll{0mqY$DN(p=zjRsStd;7p*^J@mLuefEu=MT7cX`hhY(#nB7F^r#=D
+;Jt%h_T|5jla)chZ)f4ybKwfLGEiS*^`ZDETk&M!4;Hyn|gsh)%|5e1D5`E1fonDcA#fNTA`!jDKCCX
+X+N&2^_7p;bCy}g4v8*8bL+p+c`4&(YIxs*J1~pFJ`k@sf4xB6$3OId(Pt8GdG{l{qJki88A$kax3@f
+DmVpp(5+$S2)B$JvVsQc3hGjV&1YUhz)I}*%W<m)Z7eoGQg*^EJx;IJU@UVOF{0Xw+R*^LM!KCBg2d@
+vBNYXn*KGCLJqQD=Y7I5Q9?XG7=g8T6oZ(JWH#mXzKn?*&yqD(bW0fxLHQPGZ*z2n+--aG0DjY>!xzt
+xsUn$|hx~s637ihD9e!*G`VZz=l%pNS-oOye$MTzUMsN9xD-a*B-U?33N=_Bhmhekv-IPW_JR|b#=qz
+|sV)K!ogwUbT!Lu-kiqBjy_&l{sR>?V5lEqghz46_ZCaxKBUVtJmQL99#yLL*BBj{$C0fO__&W!Ui#I
+yP&K`Zhr6Qm7t6LG&2rW%N0cebo={iKt+W{!(=jomo)p1zWvhzv(*iO&@B`F|*P*n;!vLKf=?ydYCUy
+T2|iJD-7h5E;Owx<{=Kpy*u=}y)eam3b+=na)q{e*&50zN%t01Q>63qGYN6%^;vQ<&0Zq*)smWw_v}t
+Gg&Mui$3jq{A%}R-=AMG4>Jn0(4qhDRwD>lO$1N+bHNTU!Fo$e$8Bo{i@I+|iW9Erqny}BR(rV>*s!J
+tc8sH5yKmYX06Ldcv9Co%acTBqWVmyA~Zi}9DF%&B4lhviTVRpF`YfX76L~d}e1|GFq-1y!0a`U2*o<
+c9BF;r^#oiK#GI2EmGy}~U`t`C!m2d6dJD@qbp%&nufJJZ6M^z&XQ3lphl{#Ms791FskT!%e7?wFWa_
+E`K>`FxllF7>;$+)yp%Faur8YjF53-CqdaD19f?5Pi8>Fx&j!luu;)4|S>93UHf*l>sc`@gx$;t34>)
+_+1@MWc{+(>qDnwIhFOPW}*CwJ9=GN7AlP+{E^iEl<?+TVYiU7i+bU!$70bkfb7IQL`i&Oblap<41?K
+A@MBU2{mlGP&77Zk=tm*=?NWt5E(fz)Tmnlti5h=RPF>OX%(S(yOqMJz=Q^GzvGz3^e4{hu4W{E;U%O
+yV9+oba%!IsoeRNccw&t-bi$VvBCPVx4fXBpLB9`4ebatp^r(po^Nbjo~l$4%(veA$ub;r}v)Tn+~dJ
+>FN1*)F$T!TMfT{b!wCQj8CF9=RfSJ_GQDR5BWL84z5CQomo)RV9xs$xZV62KvEV1a_?BV@2DK4Xwid
+K<=o9hxfH^2pY`3oN6N2K@JK|Jb4RXgAU|P#uqi{?efs+&A<_@LeZH!2E(ve&pW=<Y3ag8<2A954W-Q
+kf!J@k<u0w7yWU2*qPY1NZw8Z+|yIU-?TGuSVSsQyX%KqX%S{Pa>R5jm0|d2xRvNC6L}hw<(<aPL*Z%
+aU(YxJ){^@Xsi83?vZJ@?9=>~dkCHp^g<|lW4w|lyda9<o$GnB|wTB&>&ZlFtGhk(8Wyxi|)>&9!8b`
+egVgw+Q9e;Uz$jJSdF;;Bb&~*t^;bO%406hsy?qaDQ)9v`m=oZ!7+#Zvt_V*i@j!&nPRI>Trr}AuZow
+B<oR4#3pQrbB*eQw1bxRUifPJbYn7Pv@Ipit=JS3w>$)|IS37Y*If1o@*(kjICK8Cgy@D%p3Du{dYS{
+6UzyOKx2a!g1=nzokI<abC~j^-3`8$?jp>vc$AN8)+m&NQIjZ<zU~CMq5I|6Cx%Q#YJ|qmxSiURDL^&
+(zJYK=wLUuQ(Mglmo}dQ7gIia!cgiI!cs}&J(TS1Ys>DX_t~=uy20UeJrwRhhr^z+Qa4y>(*0)Gi=1W
+-cRmc_ew#@55_1?kY`BWgNme$Yayc$hPC~`sRI}ed`I~9Fii5F|aBJ!v5|1L|Dx5yy-i7W;!U>27er_
+508DJ)PZcj>u?n9HNi`VJiiRQ(qCH3eeYP%tr4;0i{I&#5&DA<qba`B*#Cy3!~eKvpZ*Fg3O5vFTk-K
+}Yewt135U2E$8zXSgPP)h>@6aWAK2ml*O_Eyt%4K6zY003G8001Wd003}la4%nJZggdGZeeUMWNCABa
+%p09bZKvHb1z?CX>MtBUtcb8d6iPlYQr!LzWXUecUTKu9-xQ8U_10Q=mt9mCsA5a$8Ke3p>IDWX*Q1-
+N)0*4^7o@pso6DfqEnWW4aioTtRf$niZ+n5J}b0GpyuQ_z)K+=U53}_g{p5c_`aMdK3vNs-bc_K5Y0s
+J)fcz$jOYH73m>%k#cs!Phv$|U8?-?wRbdT{K4Kn==C$Jqo%7%Or2;uoW0N3Vs}(#wC)3&t_{Cze!_c
+zzpdoI9$U-<E?CBeAf?ALR!vnlk6m($_B6l7-l4-T+^u<Gg;D@x~f1L1nzzejpR#CdL8Qkmg0><sBgw
+_T!&>@tJI-q!LTqVJRxUrSyYO>j6V;psyNQPHu<E;JRVc5j(ml1BIu3ol67asd)hQ+U^YQFh|IQe`)&
+BSNur1rZ^#T|KEi(ukky<?gmP)h>@6aWAK2ml*O_Ewaha2N*y006}V001KZ003}la4%nJZggdGZeeUM
+WNCABa%p09bZKvHb1!0Hb7d}Yd4*KlZrd;nefL)od6@$={(t}-mhJ-dVZ|`)-JmTx)+$S?L@({%kFsh
+f?t;!h087-lkUFs*ybBE2v_;VcH-Oi^s<mYb7EPtCqUXwE`-n%XyR;0TGv-I${Wfi00}sTgkg;ko(u}
+&3_b)nf(9Ou&*=xW+PxJA68ySuHNl&8=G?3+@C|ZLt!l4lsZ26L{Oqx^qR$8hKcb~t@#&%zTJe$qt0F
+#$Y(76CTT4l67g3dzN7y=BeJ7JDhF#&(|1mWx;BhkKa|1VO0scwur#eIgu4o(Ea7#SKVr*rH;k#sv~D
+~mNfSR5z=0ZLI4aEtZ>L+e7Imd#7Hosrhr-RO@2RXP@FTP>=|=Ih->IBD)75|4h>%gy2qO?0!tS^lk0
+9oB<Lq;BMS25B6qlulQHW+quIl*v%?9Hm1c!su)oR~YS%wQMQ!Bx$m(rnr4?c&&h0mT-Cb;F{ku9-wF
+MVzMGqvj=S4AEB8OIp-m3DC(e=_-U@|GLq?TQkVNH;oHLQBRn`u`<WQx=qZ%jY9ZL3OF}h;`8M%otxq
+YJ_!?dD(>t|zI1<;h#adm)Ix$V!Z~s1L9|5%_`@!-3;LT)~)YlN4c>BMy59B4gE78SDxoYTUS>?~ce*
+Gahmzz-=RqN;sPEMh5&Ya6_Pwiu!56Qj9%lefuzt`ShP)h>@6aWAK2ml*O_Er~{`FBeJ007wn001Ze0
+03}la4%nJZggdGZeeUMWNCABa%p09bZKvHb1!Lbb97;BY-MCFaCvP~%WA_g5WM><7M~JG^#M5)T1ugp
+QcCY;ZLQ;_vZQKdsQ<pQRX;+alcbp)&5Yd!*Mn!TDz=e=MWZxJ3|tS9ofTE15OD8Zi11V=1e^G>V-)S
+J0$WYL%47457pmIn7#59>eET|I-W%>IqQ;2Jz;iNi^<Ysn21Ve_N<?Ew@6p3OkH>QXX_aO9Nj{K}jRI
+(a7X|qDs*0KT)v<tfBw$?xONoGXgf!|g;G_sB5IcfEKLdw^vu$1IGu9;#O(4|cELRg*Xk71yNLnpc@>
+7~xxKON?)YZQIgOF*D@bGw3LJl;o)C8rLCZ<Ymlq3(*GU=)wfpda)XXymxv`x(nDe|~wFITBRaR~Ol)
+aEv~Kvzar`-fF*QaP=s{12S3zy1c-0~=kjI5RhRhT1u^!A(caca=$+yzKG0o+;o~iBFvre^5&U1QY-O
+00;mZO7>Pk7Wwes1^@tF82|tz0001RX>c!JX>N37a&BR4FJx(RbaH88b#!TOZgVelWNCABE^v9(SW$1
+>HVl5hUm>^{-~(K5eP}lX$bfC_hGJb>tR41H6t2$ZUDWt2Pm+@!g8cW9l4VP_@4B|@fCUH=TNFipBtK
+FX`&KH$YPs8qX1CfZxo76k;{QyzrKbiI-_($?mtZpXs%vXlIl)%6c_A7UXn37(I#E{zG}nITkM!b6b1
+jr?_RyH6O_k6_iA`sOY;?Zi8vO1bHn_q|^Ei-L(g5#EXzljF;zk=@*PLEHQA(<%ZKA2*ectl&itnJ<(
+xdVUUbweE+m}n5_h5L%4Iey3yFX+nF4Q{L-KJHt1U*=*x~2hD+z4}7Xat@f_PCA)tX32kwCmglDBpp3
+X5Xbn(eOPK#d@_`l{H6&FJ-67$c}Ug#P!*V;ZKqzzeB4)V`MbrOxxWo3`oARlCLg-p<v6Eg_LOnE!#@
+P%q8w-4M3&Y07<{VdT2E>l5M~$+5tMp4OAHebQc}#G-cY0CokB;2j4R3U(o&<cDy{Ww;D{>=Iw#OZii
+@Y<=fob@64-Ui<(X0Ehs`4QVsQX&F+6ci;+WteiWXd&@GhA75qgQTOH|oJiz%6k?!HdbWlY)vf;^P)m
+fZR<FYFlp`}aJGq#bk9+%5YD6a}9R6(o5b?ecEY+&@_9(yKv#o7br*E=XpZsfks2>l8$1^1!>c5?|9b
+`QAdql2(R6**yns8L}tC@e^!$Hbk8jKI3qhRfQ?24^xRw)h?oKt-KUKm@?_rR-1&4|Iazp?0Z912E$U
+E6}#0g_i8)O*KVrP=M#fI!0&)W6@UL3}-VKxyh;)jyM8;HW)d;6?|_*IZ+sRhSiLEO&&>D4+@_-&hB1
+e>QZAp(fAXE9FOP5!3Pm~2qsj*I5HN-*O2a7A`)$*`smR&SVj}Im)sV(FC;88|5R>wIo3C7E_u^PL!q
+fKtr&1s3sk;=l4AhajjQvCVoV;ZX8|!>x&|e-2eNc9vF{Os7Y*8iCr{Lh(GCif%0e@4I6{Hi`Lz^7$c
+QxD`C(8dYRQ2bnYBLT?6I^h&M-s}7_YTtH&R_8PD*wZaB|CFy=l){)E;Afe_Z@}@%+z=9Es^Z5fhbHW
+BHtP6N~i5=mJTxPXLsGnjwpFq*{e#CDmb~ms)}B%os32X^huA$EZqtQV-x3nm5863QHsDG}E32sa_qh
+lZbKwz@>cd5%1kWX+2A3pU8a<mz`3SzhSu{r(BB)`iww|YB6b`DFx^$B{&`=20XzEQ?gv3g;7t;3?sq
+$aE0g0SEJ3?cLAIDf)1=HDkvi9Xh$iVZ7oX5r;P1|whb>ha2TU<XK)ygG}5$ed?XTw9kB>bKbt9Y0aj
+cfwq8)Di7oEFtiwPhS*UJyRPWpAV|pQ%NBzTk-ibVk4jngW%|{s4w&LX$yx2XT_MJyiX--Gi<@Rvjh&
+==<mP_Z8^Xs4G)*P&H5I>(ek}iNdW}L6><2mQ>%odEwSR#?}Ykt7IxI(e>WM13Jplr0`-z$h=ODKY4i
+!1$wqfZsYkz(jar>`GA_|CUAh)MHUSsW_~H{<6wTv6Ycmw579kI9^$DOuxz&yL?;={(7n%MN#ECm7;`
+wz#{1Jr5f+xIEM?l+@{YJOgC5YLdAUycqd;V@m}^^203Qny&AG%dR9&bN&vyc)I6piVT2BsckR@8d<N
+Wu8y2R-FfI>u1DL>Jl+@lz4tW^{BOpHkzotD8Hd!}=`e{;T<+537ci6|aYShzw;)<`k~ln`g+u<ZJ<z
+k>Qg8B`jx{9fQ7;tSPYY*z>i(?fG~QpE{LWMJPWl1p{mk+oqCd~6)8X(YCMT-re;A$t`7lBYBi=`M)4
+o^o1~2aKjp7S~p1bIT(*+p_I&7Zz-0fuF>G4irJG2HQS-kEdipVqCeR7DXFwha5>UH&A0^LUu5PP{mR
+>EK3<9p~r20zkpJdAOG?LA^h1iXTqaXPnkp^wY^D^qa)4q`RrUmW)_U_J*=R@<ltO@U8Q<*VE8`mA0)
+9{E`v`eVn{&zggJA947>OWK~-<Lt9!K`?@h)i!k?{+JZnY?<tgAtlDI39>W#zVX_AoqcTuh&bOI`&hI
+kV@*NdvTT52=aQFl4@(70!^Ld?%H5>9C*CT@TDMc%@6OmQUiwNU>=)a+d}$s8`ef^Q8f}Yg&D~RMZ(z
+~+@{}_*<b3)f77uJZ$B6cW#*AXO$?ZTQcSPW#DdoQ9MqqXI5YXoeT%Aurgypb1V@{5^t)F710ghWuFx
+rd@Hk0O`ztafOdFn-XFqd?GP_;=#ne-)d2=8v=fw%pCUo<!TaY1lTOp%|C^xsfR0|XQR000O88%p+8!
+t3Ay<^cczj06AxBme*aaA|NaUukZ1WpZv|Y%gSKb98cPVs&(BZ*FrhcW7m0Y%XwlbyLBPoG=W%^A*;d
+K%)78ky@!$wWn28wUzdW3^7BrA)!gwE&cjB$-+Q)h7+;<Ui_Y&-q{f*HHqehjI>Tn*gfM#nTwc%(jL?
+}Sr?!~V~y%itH0D39H}V!4XR8aXHW~Nd~m8|q%~f&=xN1&ZaITp_`0jO#h{F&KW|M?)5oJ*IlkxULki
+vkj}%a1z!gvyz~2{cV}EU(q7O=wUwokPX&}-$c%jg|#$zK7fT}2pPNVmbiuY{gEoId?(Vb4GA2d1gWP
+%5TL=AgtQKZ6OgYqCPc`!DBA(DV*0ftWKFct#(4EJ#q&=S))>VjTiHqkDUV!bnSO6rrI)s%yz(v$8h`
+0(kSJGt{Wrbmm?Ll_7)Ym@CUlEw6FBk%w$SB%yz+_wZrVRnWUZ(REu7>xmD&uUeulVV4D;gy4wJWyM=
+aX9)tv*wY_6#FK(f1VHV)T1=P#X?)&*Cx_56NaIN(@zS~NH#Tq?GOIS*~Jc|eKnd@-)D`>&s0x&80d)
+S^}<U!o0!=Fvx<-ZZ(4b;ziOv6`gdm=%M_~LzsT~?VpUz&AnT+9&9)cic5TGh+bO@j^YPVP)9tLZY?Q
+Y;`FDoaT76A-19i_$E|N6)eLn5oH*4s+YZJR%`~y%+0|XQR000O88%p+8LqAK-AOHXW9smFU9{>OVaA
+|NaUukZ1WpZv|Y%ghUWMz0SUtei%X>?y-E^v8MQd08FOG&Lz$jmEAElNx-$;{7FNX}15<x)~o;sO9rO
+9KQH0000802@m7RwQoO3CR-x0C+$E03ZMW0B~t=FJEbHbY*gGVQepHZe(S6FJo_PY-M9~Z*nehdF4B4
+bK6LE-}x)L;PRT>fna-6*(6LcwG&xBDz-;u$-9+OR2T?oiWq?a2Mvhkx}4vhck~H>mS*Q;R8wQH(f#`
+MyN^Z`MYGF|6x*z<#jbC6jgq2Si*8dYv2BXJk^-K(M#wMp?tNL`oi<e^^R8)=oS#zF^ldKHe38r|fH*
+6+yQb}geqA=TGD8w}s*<f#D!Y|taNXAcuBq&-vXgBv@QZ3{^ISEzw`F~6el~Ve-&R$5lkBoq$-!7Ff9
+<8}X6v@uicPnzcvdU)w6~WZ-k;M5Pib}?O)&5OnpLo#-*tx_Y;WGoX9E5%|NHzbJ$-w2`d{xpzKLn*G
+^?uYrjq>YRhf7E^bXGE#^0ApkALVp9R85)5Im24%(k+)?007NPdg-LR`IV3JXD?QciyzmHOz`<iy0%l
+D|bnHFYBVQ=hgI3qX~vm%FO&E)eiV4kIzixms}EJ-lDEOoV9J!#^U1QJw5rzlr<0m&M~p{qwMxg3o=&
+MEIPb+Vl9ZLtW;8gM4H7Yo!^<NWY*@JROQXia`uA8E^ugSWzFcoQl$VHv+BIuUGT{F7WG|O*@LxNsbs
+ot+EjH}*Q=?8v>;iRl>{M^c4?_nM6$ex_3-Za%5AA~$KoOb)y(>Clj4FDRAFl6eQx)GN6n=~YqWWDn$
+<;FWSvy6;q^J_ZcN0!plPwV>C39nW&qTG9V*0<q;f)e&fBJIz)H-3JCbLaA+Zw8%`YGVvl%KpsOrjSe
+sU|j_cS(7(;8GHO+nO+puUw^AzKC0Lyfvp9Y`bm?|L?y6>=@oZPtM_z@b4RHgYTHK%phhScsGVu)2op
+t{FG5ZSR}rP5=|dUr#RtF9RagU@)cl{ONr%qlqB@eG4+(k!gipWZ^A{1+4$r)F6XsX=N*)DN#2(Gch|
+c&0r=k!c73xMDNK6;UB;NypyWg13eZA2v^&wec5g1Jar*}cR1y$lC>GTMsU#&%gDjOzn1XUJI=fj#1_
+bwSD8{G{n&Irp1%VX?PT4}&x{T)7#PtO<g4t`bgpEzj=>So)D)$fC>$FLlonFuj_A0LLrL{JI+KOw!w
+Eqw+#=X9@h5^L_&>vmJ`9-X|1@GEYt^?h&30wFA=#R@TGW=-Iu4LG>^t4a{EnnR6YJy>5n?dpRS7oDF
+hB`eaK}ny;sW%fVvK>{b~htsXi=2-IpoLBTB^*U1<{~H3F`pleO8r)d3S>ELWvtt&R~@=&I)yJ9{Hz<
+ViA3=@9Jh>M~m4AMp_N%ZzOf5g*Tk+%dh3sJP^{TlV7^$=)|Kqd;yAHm3fA;`24;uk{uYEL=g>>`<Fl
+b14}UO@Rl&r3n!th9(-yt@I&PoO01@)mNN*1x=m9o0@ZqZd3ioksvW$Y5J&^inl7+#?3b3Fk2)fq7vR
+T1BHo_;_{s=A%A_`BG1-j=1XMj*K=D*oGy%Mo$a@F~(M*%A3$Z~%Nq~Nbh>Nj^8!HTMx@z(mXxnXK0X
+w#b7`#+=yTx^@Af8O%hXPUQkkVFmwQ0s}!JdANHeI(veZYTJ^v#nKD;vaJttUuP*hh1WR1Cob<ttDUU
+~W;i-~rX@vhC%<37Ho~kS)^Sj##RNksDCmlo|G0<i_yS%Fd5D1O~wTTAL^0ycG`AT=C}YlEp{64_|z=
+Y+Pc70X$MA2Ah;}v{C{uK>L?G<z*t?IeDqT^D1x&YFFlE)2r$rs`5@E9y&O}GdPJ}mo3S&;XyuaivbG
+^{?R47<HV>3*?j|IRDfNpnykR6B{Q(9ti1(+g;*?MA)k=(KsNKNMj^S8;2k0E+LpB}taKj{@Uk-^Z4k
+^n6j`MIl!zbmt_OKJ2=J947h6qiwl5kxL`-<GHUzRdMipyNKM)$l@ct=z*k^4spgLKFy%e{kaT9`IjV
+6hKqmh5e27{k{sRsIqXAdLZImVi#c@!LD%;y>5V+PU6^h*D$^@QWeq>wlL?L2xTyAGMVgP>MCRZ%<{I
+n(CTYKtDx;)2`SAKGWGzJ@*r6=>H*OM#{$`K2lA(81x~)o6s4{x)~@Tb818{CDx|>P7PM7zFEgdESeu
+iPyo%BAoC<{0$VKsh@RXpVj1SZXkUtKzP|uK$x6o6fHxpk)cNztbfi3KZlG%=2;Iyg<NVN+`pAI<khG
+L^2-i0M__5U$+`i6ZV##_AXNsH7Jv8y=0ae)!IoAPm@fDq)gmx`hMWcza6MeVk%wpZbPCuzSgx}G@Z+
+8M-<K~0D0vSF(*OWy^&TmZfCcQ8xH*6vbsAf)wESJR4XPHQ1L{8jU?@h1uMa-KVzGhP>K@e;5V--0tY
+N!mc!pl#cH8XB35fja1swn+6^(G+oDjU2sy;wIgUA4c>JT}I&vl&#vO~_6Y-ItI&z*v%4?qBU%5C{~h
+%MS|y)JV!-sDE}41<O}=0$W4Qp`=JfM^2{`6jDx;p~7WFd(+u{n9HO*=GmL&GMe<(KdZu4B6QN12OQ>
+7TX>JJQxsT@6)EKtHWS<Q|A)xu5j#522)-G@NLs#{)W~$W7z^3hEu|kVfkT~JqI~@^3Q+%mlxsc=oEQ
+zg7&g)Dl{0DX`bqR<Hv{NgC_z@ee4G**kTI{uKcC}k;d~0^a;wiFfe8i02Ydzx(1;dj9HC#X|FtR#EE
+!o<uJ2eEYlEBLLjc8APdL}%P@ZxpX&<4iaoky)yrXE3N8yF9yAa{ZEyW5W*;KkXhwDAmZM2>QW&OLoB
+<Vs##HbEYXF=>pLftC%hnwYf%<C@CN=;OEW6}^7!2PAp2spUdM&v`pk0v26geU<%Q)hY{3&Yp$Q;dxi
+=W@)az9Lzb>3je!`o@NbN#PNdv&elJN1%RCfq?j>`{;J*=(5|e7!*JZ$MkkIlO>C4^cD`9t{^6#4I_s
+;Gct1bMk@zox4K8_A2tz;OH9GXh2ut7S5@G#erl1lY=c%IfZaF+s-3B968{a*z(|Xg{5of`u*Z)orSa
+?QzNXmX@riJSWtGrK)kC9`9;r-CQ2#*SAxaH*$G+t6zivW4s;4(ZG^;eMRRA~w(?iIDFtv#U8tkoZkn
+bVrpKUl<RigY&S^zVK{3HtaCyq^hk2G*tr)T$@wW$0u+a$6j%D4AHpDse0H#Z^smzb@q?(&rV^Fxt!I
+eBrRa3>kLP*yRfh0+^9-+-l**OEJV125kZNA1N%VI&`+|MvYe*@MO%&Lt_*q~BIN*P#)2A5cI*uyvG2
+muW`mlQRqX9~5xuR1ZmlLxRq5Q<Dm+#(h|n`U$gK4ebKkwiZu#rbhUs*s<rvr5UIU7Sx3f3c09q-uL6
+)*M`%g0NtPa=Wm6*|!kCf-%hvhAFdV5@Vz&Hdcnr(b7@DD`3I^7Kw@p@jc9NX9d$oxTFTBqe3!;0~m%
+QWSTS-W{;_J&NaqIj_02zgk~@YN&U-FF(n};Nh2)P@ncTuf)QX6>>xt~xg!w5$|o9tLn$ltqA1ll1oT
+2y6d{l^M7Y|>sDTKLN{vk1f2iL0sO-wiJ1Iw5QExKAFn~#9Hg|l%Pz2Lf^i;Tp{WFeWwt02E2suv;tr
+Z<QA@_?L%yBx~qr_IAJelGym>O7n^M@!wcq)SzOmbW}S<ciA(iK%75E<@|&O;Qe8`qS#zv0YL->pynH
+S(Y(YblF>N)QXd0y#J9jKGo`u*apL8;F=wGfvR#2yA9%QDDm=ge`5J$OB${Fru**w>i&bLL=xE)e+1_
+EAtRI`s1`8(cPoD@khQsS>5?0cVL`J{xQ+C0qPu%MS6`j!Uo7p<u+8C&!65~r3k`<z^A)_QPY13W*@S
+a(YV*Dv9An|mSL>tCfH)4gEqEu6e0lav8Jg*(Q%k!%m@B0Dai76M?Ylc3=(D*AsW6Ve`#cE2!il4^+f
+WO`%Rf|XozZTdoVUGs2{DLIt}Eh7^)CY70X+pTb-ECBeTHb8R>lBPi>kW<l{!_tUeLv2gpyzE+Y)3XF
+LWLMcRY|2CP6Pa=|evi2Ra~QJbW<-#~M{o5|M?_t!l8U>?H>tk6Dvc!P;3VuJp@yo2ERaUuL1dH%^n%
+Anyw#DT?gmqQkzb8{~^F1wR*$6*o|pV3-~x1Y{llZ(s9GgHc2RoX_e4b`shnaH}XEpJ>IVOpa(G!2^7
+5BE(Wo$XRgIa;|k4TTXW2;dYujNKckK1`*IC75fBEr&mN@r7IO!OCk~dv)zjw*eACBu4JI%Wm}{;Yqh
+AkTeD+U3HlRIzbGqWn>hCMtF+I<r~(0Oxo@Z5Q?h2FcVWf{5>ZuM$VU}>MF;y0}l6F(F$i*D-XwP(31
+B_nqbsc7xMyWs!>@u3R)zYbiaXM6RA7?p{2l5dyE~mp28OfIy^s4BII%VXncCDeFSBwk~-rh0oO9%^{
+KEs!5$2?en}2H))8%{uv<lUo%m?BXR2Ki7JWQ{H5an3AV-U7-)kel@oXSCa41|omJAwQ1%({D7uH<Re
+4`kwv7|$O<|#1YsS+nb-Ia6^1!6utOstQvaMw}p<RDYjCmr54h#&H+e4KG);aTJFlzE0d|DZzQ1D$)!
+)Jrtx@%YV=(#klzSeb_)uvl3@L5pQfh}C$=R=iw+E2Oh0T;h+%TcK8z!X!wm3~M%mLKGA37DrEj-7gn
+cFRo1u_SDv2{VPP|KZ=HA$CTBvw%YG70ouzOiX^mKa95U)kyF>0Y_{Wuz2KLHcb~O25NB|?;*=|@xHs
+0-pDHcHw&7ADo>D!C>7Y5}5DCXCtI^D(N%O#zyUc)a#JB{zP!JhIRD*fZ^7(VbQd4o)l-yh5?s?Oex(
+Q?Y{;6sCr~KbUtDhdGTK#C{a7%V0jY<$wQYzSM9^N%YFn_|gXdUPHu<#PSCn75fY<-j!>Z5|VV?(ACs
+H#JMY@h%P><<#fv26z7!PbMZF0ogkB;8o>JsyHVA;juE=eEzIL7Iu;`U9NidE^1S{OQ$COVDu+VtQZ!
+wt}!_rQ_1N%&C-%jW5l8h<DG=&c&bq?WG5Z|5SIVT=rrw%K1DCdRF=-+yoq;cGec0M$0dtc61w)lD&t
+M_AxwcO+CZ*8swuWDtWWTt{|sVu3gY@JsL8C#J5Eg0z+L~$`vCgp<X>W>^U<9%rzJzr-vAQIQ0Ul56v
++tuI}2yGO(z|fKOcKnCN=rD(?Q<D=3e&1{d0A+17+-1twcRT+PvKnJ5Hyqnl4$Ys~mog5TsB+KegN;G
+M%=B|ysqFMjW#P&S_`+j7FY4ZgENKb{N^g)KGeoH=dq*C-&2e2k37L%@&d*E6w?U55*)r)d{lcpSeCu
+B%N`e)@v;hy%xhISzebY5>$-82_Ds%x&`#7!I~TZ;)encO}F7YrD3Ah;WMuETn8(Zfi=RR3&mqn94PB
+0IQxuIAA%khhw*Y7*k#tQ>3`k@`=5#0DXI>{`Zl0jh!vMUPuJ66klQew`h8|%W^B5zI!bA2s^Cc{d&{
+!a@V(+MC7`s0$MawQ_<^+!lv=~cba4TZHX){^tUJOTM6yxz&RFNx?b8(C9Z4;=WefGb9;{w#Ujgt(+v
+*6$1wWRnyC%wSiLki8_l;cAYpzvTeob$6_E(ug2OGqda>T?vK-J6mzf(|_6rS=3G`oBsG@n)-ABa0iP
+8r>e7h7~3|0t7AM5D%-zzm7DIQJ)$o@<BmBrHkzT#-Lk8<4L<BU}RWjK*P#jrQ9bjya0&PTEb$wBKn>
+5h?C>XD~t_^RAefBNIC0y__4tkSw+;kKC<7ueh(qd-2Q?^ZW0F33cU3<f6Tmh_!FtFEKPW0d};%aX9R
+ysaC3mFDE6ZcezG$ma_jz<$HEQ!s43xj-d-25O<5E*m=i!OD&%Ut&kE#Sez22{^1aOWguLay4_zQOL!
+aTq8VW=<O!2R#-&eArbhx0W6i2lTTb<i(-8t@932aQf4X|)!vZ@7u^OGqJT2juI%<ie6V*ZowcG%DqJ
+hPk!xffUjEj#ZY|IY#{+NS%2Ll81a$p92WsYVHyJ8R2z})q<0HpgxyNvdVcBZP-Korv?0;_5Mt5nf8i
+nW$Lfv@q(j9f>|M*V68E&pE3q%P!hz1VUtT<A*dNUQ;!UCGP>@hTN9($b4rHYY@<hh7vJOLLc!XkuUg
+SehHE_AU7qjTzRP`Ilv?{oN@-{BA;GOg6cl~0sRG-iIf;f%9amK?gBBQ6DKjJAco=NdJU%*SV}il*~F
+`XtSn-eGj$C*Ejbe`*T|0t+lo3%u|FNti5p4!A)f^~Z0JrO-EBBS|-hq1K1}#x?PvhGOb}9yc~l_z}W
+raO%*jsloA5>Rr-D5E;mDz?Y;{sggO~Py=&#Th`;%^2-i(Ng*j+c@8Z^Z4|yu%nWTHT1_}7TFtRKIO#
+&uk=pQQ?hA#3w@9dxth~EiPNDvvu*P*yAK=V*;`bTjnWhPP`<~k5FzT$vvU>3vjI;Sd^VQjZett8)*F
+bC;Uu|DUe-vN&OWtqM_$}V#BzJ4R3QzJ4n6UYn>G4=a7bAFB%=5c7+z?7k7vBsA>#iStlCSucB~4g-v
+*vrQ7U;ZL=*7elBRu52Y!!c=u@+x_(f_s#mtZVKTO5yoqW`INB*VCPtkX7qlt3Nx`+T2hMC--TD1a7>
+8R2`~{{v7<0|XQR000O88%p+8Z2uE)ks|;A@sj`mB>(^baA|NaUukZ1WpZv|Y%ghUWMz0SaA9L>VP|D
+uW@&C@WpXZXdF?%GbK6Fe-}Ngd^rj3Z6xL2|>u$NB_Z(YJT<djQv9h@<uMdXEp@cOFFaT&-arwVrKju
+9Hh*Er4TUVz_#S$>n)6>(_)30evCX*kVeP7kG6Rq5oy<CaD5ihP@Je`TEUdi{en@lE0N7Z)Mw7rn^ey
+e|9@9SmXG@DL8sCwCY4>ryDc~zh5KU;aUZkw&>uXgZMsHdm@`QoH_^!>@BzdU{Z-Ap`bn_p%9QuZ_P6
+yTL-8#xotst*4CVb@npU2bNAUZ3uF`0l3~9v(5|UA4=Lcd}kJZN4j)Z_9IMpl&CZ)w+^xH_|xo%k$2l
+R-TVF1-fla+htidb+s%v)vvOs%dH&i`3{f(taabw+p?2?<7YSMwkz9Cin8Nh3iZ|{MO6a{fnvFQzm!B
+hgKu^u;OAS}^=jaUn^u;qtEY9>mz#}T&8Wd+pnO}M?XmCkrhn4xYxU-7{SGF(`uRf2&68>)anAhar@G
+tka1hCFXGhZ%PQ+gMvVp;Xk6Mk`v#NgkNI#sZxozNKmjbeFR&vwjK>by<0`}EV)HF)O`;mS*0$|;=+p
+;f~P2IQ6Mnic*PapBak=}@&i~mT|PL}QRqUe^*&LI1ep1s6Jqdk!(FrQ-A%5`TutH&?kscdDvlw*|Y%
+l2IM#qO%Vu$**C4`0x;k-nF>nz|1yZK`oAe+gFMNBPUXYUNheeX0ZPqr3oVq5A<c&p>v_cDVT(SPle<
+G<5j+`;(Jr#mRr1o;-i~^oQreJuk}c!gl+f{u*wrWSDM_Ok4Me>u{HC)h%`VvwgK$6}9X)&2qR$B&(J
+ea{0DsnQon0t>OOr8X-9SU;gys#ScH8o;<b$c?m*%?MvG^ZP!TPuzW7$`(D<aD>F`k-rw!Zc6D@A6tJ
+#EAr|7*#M>p4nV6tdF`Mp3+3hzyK7K*7luwX`?d0{*(b0w$8Gx7t&k7QrMKL`(`W9&iG8o>IkbgxI|5
+Y}9t%Uz8Aj3?6fO`G<$c*<AFa`AgBCnvI)6D+Q6}R?O!BzlR4~pom<XRNG6u85~^<WW-Z|1b?S^6n43
+`?|b<|zbTbGz!iZdw__oQpF!K>_n8<)#C9Iu*wc=n=0Kp2hg@kFwvlwSW!TUjPB&f8xA?<rBPzg*hoY
+v23<G5QA`zip#3M5G7%Jw_|u}Yj(%naUwvd?`3{OZ|5L<%WW{DhvMtw9%m(*HBJW=2M|adYzt&SL`4Y
+_p?<dIKbrP<Th;XcW!o6^K-D1f=I(Gqg!x%dwoy%JtY`*iSel6do*$u3eYbZAlzTMp+pD<&R&|9#$VG
+aCW~RAjj67&D^IEusUATYPW>fl&k8ekV$<^umQa`bn@}A09@@#+ZBQ$x6WFslTy+uGfk$v7y1ssKnsX
+y-~vl~unWA=fAJ#ex^$+f7P-Y4ihMHZm)B%kE}XsSBfmb(o0`OG8Pbn11}fYa>bHFf9&0MD9EX3=}17
+;bB!LBZBpRckt9dtoTn@u<L{K)eLaf?1_sUQgIGfqg=|KP^iL5+g_c5)Cp4P1!KXx`ZP(<`LrjaNc7~
+GdlUhCLT|E%5ze)JZ<+d$)n|_>^c&~cv59(tmG%~zbUW2RT39u$mHd|Z!#vGSy)i6nty;om1uKS)^C9
+z@e8Fq?ycTC+(>V|xWNvzRcus%{s1kP7l}3jrG}ciq&Pu2Sb{D+KMIbJZU<*O$unF%$?b6EN!zA}CF<
+XOwcKyYRw&9?DM`NoD%$jbO$UgyGRK__%#*c~<K0#E>i$<>zy5pv=U4ZR|M>dP)89?h;@uIC8x+7*z1
+-|qV9C@1l#1rEP=to#w*=Ke333qo+w!dx-5y4fCCnL&t&IZIf$a%`9Hs-RMQ6@M1qdu#2}eF`VCYIi$
+W<;*FW_{9?Ez;{xret3RDV(SF!Zw0C)AmQfdM`Fez&QX72-=r3J#CdT7q&sgCQ$G=|XOH8qiKQcuE2;
+wLsHKpN`m`X-N77a75J?h24pu=dUfZE25KDG)G;>zA`3f>Ls&VH@61$D^!$h1J4kcdnSNw<gN#+CidO
+XIc*dwZ2lS;;(1dm%aF7g{L_kK&5rn^6aat9r$91To>t)I+ElQdtSw7{@AI&8NR(4rDfMi;t05WoQGa
+N5q216U$0!iFczMz6H!Eb164tEu#1m;+ch9Q2Y_IML=z6zn_U%&A?`I9X1SYEb2!(J_01<wq&l^(wLE
+Y+E5dy*xgL#7oJJ~2W)u!sN6yL*t(04WCt^dB<k}suiJU}e!+3NFv%+Tv_DK{JX7a5$I4(NaQqYnTf^
+Yh$kWDa||J(H^y5E=->Dymp3uYw0CLwwKSbZX0UG$^MaHddlMFDtM$QG|Sd`qyVl#TAWWMe*X~h4{n0
+uYGk0j)L-7v+wavDZpjV4v&~W{LP@%QN*$X3DKgY0dgprlPM_ydU5B^0Muqe=Z{}aNg(ZHyRCZVc{`K
+#m|_uJu?-zzbGVue^3`Zs9wv$^LzE!7+u?#3ns&K(%u>1YAi-dyY2?X$4VqaRTVz9D98mLg+eN6%prF
+hP@5oqqixjl<MFT4F-h-g^AQtHtL2oTS7Fv)5?|nDS!r%D86kT};P2E3_%sHYqJ-f;>Izt@Olmsu^qF
+Oy-!#OR8AESH$gH4)~RBcH-F&#b1;ZO3k<recft7d2~vbC7C<OrAnwmoQ;Q#>+3;}T!+^DhW?%^qf#8
+$9dMHF&j{1NyDeE$L!56Ad?lgSQJr(dEUJ0G`9~P=lquxp=zvW>$6lVkW*|e7^vh4)X4dtWIA_>P{eV
+v@}DfX?^}D<os}`8OVK9ReF?I5irJ=P-hufqK_H2*Drfe8`oFq4Q4GS+)eJjBmEj|Eww*TRw5?x)|sc
+!Sa5%CQK*MN*~vFGPK%7{2a}*DY2=w^Gu0Umnu)>znTA2l#RvZ7qgDxBtU<~bTFU#_;TtpnHGXbOzv2
+7dw0Un|`39*AaprdEK;7u!?<{F&!i(6bjAkF31~W0i?j;=@lL$19&xTdfi8nlC(pntDBiUg+ajh71OT
+!u~83xM**nLcxchM{+tols!RD7X`Tu5|YgkIa!^b{wqC(q${M6eYcO7_r1cKQ&>$&ZuUtql(s&u3dMo
+9_MndlQ@uaR(fz7w$|Z`LES(a$A<r@KIc(nc@&)c`hsWhjq9GJMA;VUu##f>p*#%QURVc^idYXpK$KV
+2u`yg{!Fx)%!q4T2V5)h6o6(?KrSO#In7yown!=kL-R8{c-b~^3~3($oyZyTc!C3`F$=oHGBk-?50(o
+f0ET4>ic>C9+C+}O;_EC)7sQq+VSr^m*lC&ycYq_<P{-4WK){K|@zUBkY}Mfx8WR>wSAn$wXBn_-vj?
+5DyJ(u8EosNbfJ3tb^)pY4DPRaq0t_v%myoB0(`P=z37MAJG$x0)xWnwbp3rgEtmBzyAItzBS)F&>#A
+ya#h*`U@G3p}74=0X~l_L_*dLYQ93x^gZ4Qyym0gpw#r4b&p$^_HX#Fce}J8VLB#{S*!#Mzayc7Pq5w
+*`xTwhCtgtSNXSc}2xn|9bD9T~!pWY#U#5SbTPk{PPbA26^Li;znmg=+ah%8ggc1K&>rdT<tBxz?;!q
+V(v3KNh}2tk}GtN9)g=gvcJOGRE}iRX#XavX)zyDOgk-kCY}dTMaVPt#G46q8=|lJ?bV!{<zSYypu4^
+Hn%kkE2e&&1DYVP(M~AM{^s}^}wJmO|mc{!r*?tm-_0XtqTUd~!I%W+>W?RR6y*8k!e`2S*7q1#8NP=
+_IcJpG)+72U0YGufR@h3LO*dG)^AEQ9Vhg9t0I?f()z$bXzi?d89bB1lY&pQ*x;&2I*S{RN$8XVp+aB
+XXfQ^PR?HaiF^<*+O`&4HKHx|HUWOZ6(59;2MY+|lvla*Bj{oA5`Ib72ImAG&@*h>B+4yPmGg3q1Q&Y
+6cvm7#C18nb8rTNKuMfULG-fc0C@+7Krjbpe5f6^!WE=d|RU)z?&cgoCrAD438~(<Y80w7X(XI?EUaN
+p$S|!{Hu=1uITV*EHSzue!!lWRi`Ag4MIEPcwH3sq+^*_fsa#SRPw&|<Vhjt3~?htB8>6TW!cuOkl|r
+XY`Ic#anlR^ggZ(gYT>0BmH?$k&UF?7f)40sA|xGYO*LzRgc`ivNI2F}^=T!gm0(jQ>)M|*$6_u?&1f
+_^6_0{ddM0J9-B0LoCD*b#@HGJ`a)6<uhN4DYwYdUy#Y_#FRIQGx;W6BiYROZ^{wvv4ty=b}pC6zEk=
+iclZSOmrzoYe6l$4!Ge*hui#N6}|{CPVMG|0)S>Xv0o+)+0U!NV}UtTX#^>c4b1a7w=35q~vdwo7>z{
+*SY4%~GG0fUxCel`j%VEZm$f3P&yj6ir*yO|h!ZWrxm|SA0a@5i0GEpo4C6tQm%a%PJ3Rw{LeKDwJJN
+qX<^53?O<?EJ5HR^n3ISK{(z$cNaQKhthdrUr}CPc<|7v0Sib1)<1T3WoP}oa^tw)ux+74NXDzb;C}*
+R%f<c6g}6WBvvTI1m%E*;SC-<wGK1d6s@}^${|Z(j0Yvk;gO$aBPaJZ(r@$S>SpPQGa>h%u7t$LzU$>
+j0%Ouze78kXZimmKAj0i49c2{C5<J~`eboqDw_gcWCiBgNRXs<de8En=Gc2(9boVA(Hn$wuA)1VZA(x
+Ped2xSn^bwCQ4;2OMFg3F4f2_}N50cV1eLIkgWm<ux~l+pr;N6Hx%v);^S-|!(0kYYqoPtqNNHB=#LF
+R?`PlF6trT8)!!8zfeo)XQ?$?KgB1cFoo}4tBN+k(hzg@d*k}$9aoN2}tNsqB%o4bwU2cVMzoyva-s<
+6hqyJqXC%K3C(rNM5^&&QTzdLPI!`9km>*}j&+lCgoCVvBuEqU3!eL3Jql0|&H3A`ZX$8jD6bENN>xV
+#%+ot(Mu$T;$Qv)sHDAL&#ToIi?(jybdgMjnf#H{?2Gs<^`}N9%f=Rgn*-iH{0Jg!+B=x8~&Nt{S+V?
+UTDVx3#TcCHdx&_nR$Y>x2!u*US-q<K^+}Fq3F+RpR9>$0+E)QXjzwB`f;u0e3mG8=GgE;$fcZ>-}9G
+#vYCTZALo;?x(2q%d>w+%?vgyyY-g&-%qm>&L+CXyZ#&ec|i_`5^_Zj*Q!M)p~9K2!0{g5E~Qs~Xv#L
+^^`62BA1tYLF4FMs*EGsRsc0ySzv?LJ2X7h4H7^4ueAkh%Ew4?e@akP$-iq7Ehe2?=y{>$!fi*Em=Tq
+vp>HG46NK;QFT<|cv(1;X^4-Z!>2*3ALRXU4AZO^pR$K0FD8%DflL}s890M8f)hj<%%cZ8ll=K;k(1L
+h5Saf?h_Ng+Bwe-=g{+mBo9>{*y&%iW$T~L%&rh6VfS>XZCx$lJ;}!=e#~iOom<00}pCLa{obfk_*K^
+{r)gvOLC=&~>v>rFJ<P)aKnY6VaNABsG<{&cm0Z_)%bOs1|H>F%ijHXEv!Cch7-7hKfK$jjdKDMvP&f
+)IS@!%}S!`kMqDaaT!BNqiic*6|;#zTP}AaCq_L1!(^I=+<sn<>(RAvn9&gQdKS@foI9-Nn#Xj9gFIk
+UEFnC;uW^>KF-=q+H@>o=4csG!4kUUWfsrWU<rSMp*~rtD%Sk3E-P|t`u0LEuDD8h5zR)J(q>~Ep+fW
+a$@2A<u^>qibe9N-_dhmL{{c+%xd=MuGB}okd>5ML*nXxQfwYB_^#DW!^xr)!>r7I`RWgR9@$(R6=7v
+o^p?ZOJ5Ux^=vrSprl!aO4Rc+!U=xp6S;cQKvsBap8uKr~+i@!_Y&)Fw=(kMn?yyaiIN?2TTvRVBq#B
+Z%E+}i`9a?F(b_k3j5h|hD0ffN@K)Y&M%9w_^DkF`&^gDGdl;oGEp?<F$v-RhILdZBe2jt15#8oZKsv
+;tJFlB0tFACT3un->t8GAk#)#^QKNUQfVJyT4?BxNtm4l&(7+Wn3qF{#si665l)08_}!>W<`~ipmR6C
+Id++cz4846e1_ZpsLq+(Zn3>&H)4{%F?mEc-#0}X>6l~7N5u7KEs<f`nZmk7oCRhd~Yx=^gGJ4&|q@b
+1>#us9q}`8zNVs%K5K=fMjsB2ASjS@Cg~nc5UKIOQM8I(zvzXmR~WeA^pJkPqv8>KD|4o$8YxtrOaY4
+uBjoB*FB$=<_HWONR;tX9;qnR=N@uTyCBV_`b9J5Kvb@4+0jfv=CJOC;*z#Kdg$eeokS;IE`aCrob`F
+#3c?tZ~H#>l(!&n~bC=1_J=p~97!NMa$2vZ;w80agS%X)^;fz`#Tg%MPguBWUcV3lc{ZpD6QO&sNN_9
+G~P(;9zbjbc!nhy)7b{}8>-GgPEuXi|EeTf<0S_-7?S`=nT%;wD_iaeowsiI%BJkQ(VvwK5qO-D``Q_
+6ZL<8%9I%`p5QIB;h1AF87Qbj_NJq12j_7@JH#a9p?a!PirRL$}0sJI~4GztMBP&>gIvt<VuQclIV#m
+`)Nu31S`#`mB$zxZY|{8H!$EEFxk)dXcv)7nQr9~hw!YX`ga2?iBE^>l|3dMYm-kA+{%27q1!JnI4(_
+pcgEQOIGvLj+o}!60_?8UE%bdxvNhX^a_M(?#NtKERt7<M2ZvKHct8<*^k`6ge{P#SLCuc#J+QY#1!3
+lS2I=;{GR`<s0%%U1qzmWB0)f^!N@D~2AcTb(92$x?_Vnd4$FIwW0-2`jE<Sm>tqYCu3NkDzeUZv?E=
+ff^4K7PwY=lcIVWVP}7%xHFLjS3%e4|h_cSLFVJC8mD$|M#TK&ks&(H$;DFyIH5Y5>u~NsWYAE|kT<g
+CO~2?X2ii4mqR3r*6N<O-Cs!S2S#AOapT^18sA+f1<CN2&P`J!BBM$2yWuq&-ZhnA}C2*Ie>PLd;9CF
+TmffjfX}<C<V<s&VqB1ZTWm3knNY`F{p9Oh<!<WB2c0_`-+;J;ZO~yUD3imZ5OHWzo&oRbbWn#so;N6
+*s-A#ouHe86T}9-}o}1>pTC%2tG<)Xe1E^(<H*?1suY{B>7|^Xy&*VZzJ_wU+(xItimVxtLh#}R*K#Q
+fs>p)3aNzO|@JAA;@(Q5;GzTiN)?Q2(r3)qmA;M8Mryf3^Kj*Ve*F7W5tlnR|8K`ZBbZSIhs(w3k~CN
+Cp+jSs%zkh~)SmKXFrPG@V5T3y3g<CdDUF^eqOKThlRpQtMuf5QxkleTTzL;@<&Ev&^gQ0L;qM}0@Fb
+X*SV@`btitddnhN9_l4+b6JMB-7OP%T3aQCgRYglPLW*;W3COnPR^CAtWB!FtVO$>?Xt?otfOqoPN#P
+$$w>kUwt{v@-L>po6JIJ@k~?%ivc-f&BWw<U$$^~NtW4~7|bbjBE?iS0~M5~-1%wCsXHEaq6<8=`YZ(
+T>fY<=ECT%M{%Z@1;&OCX1Ep4=Y4TQa#E0#Nc~P#`i`QiVgJc?%tIRrgGw>)Zxa0#2b6<SnLEwXOim1
+UmWKDH+hFY!9=pkOd@@$9npGVx~zqUdxS>6N)6@b$ePr6J=gAT&?pUio3O*s8p2MXflsBAlR1()*^mU
+#2ksuLz=4SUbPaucdZfnA~iD^1a*aBP)qm&(#}7TNQYM3LET`98bOf(ZZ)1#<_|D?Zu!3?`n0ba|v*h
+;B;sn?(0FW^o4c00xX#BG9lqFPRk(QJ#RL7<wq~8!SU&K10@X5YkA&Kg7WH@m%<Sdizy{sJ$#7lO#mu
+4{8dgPDtk_`@nx&sjL@1A7t5G6-uebJ7sctQCGk0rOJ72C^!kf6ATS<hNp)vDYL^T#1Bq$Bt+YQ1j6;
+;!VMb5!-F(*Ma0zSoClRTO|#!zNXD<d>BLpM!h&%C+N=*3#B@5Qvh?EqpT2+%XLRY%Z$p+9EW#EH1Tc
+Bc(w|B8=&O*9N+XzZE|>wv$p&oClbacMvWw&3A@v^mRZEq(cE%%O#<{9y>T<ujx@Tj!$^_F4Cw{NaLi
+>cPzQ9yrZ|bx~7aRvqN_FQYjw25&Ugw7DnKI;D@!*eS38Yq~T8E>hqr_pOMKasdjrs;vV;A8AK+Ic=3
+=^xSGs>@;PNU?dn^ZChFb$pr?SES>6JHLf>In8h(E28oO|GGzf8|u7XC31VT%L|om95jJ<od<zPf?d#
+F#GnRxeOy?{FaLf&#{>FD_a_6W-jNc%A$hP;r_p78B_7*iBJa~BSCrNd9twaZ^@zJR3yI$Z8{6d&)|(
+DZiMNncWKEAQpd`tidnuCOU*BmWB>P(oj!RQ(2zbbB)<bA%}tgGR@ToNKO}i31aM6<%>fBS!K4<!-*N
+R-yVVx{pR-}2F1)`|6J@D1Fu%}Kk3YU7k2?CV54|Ytfw=z4FbgbHgk{@b8ENHB*5<*wY&8$pC2_V5fp
+;ssTj)-W_W|JkYI%j?)llvuc;ELb@S7ZU<~^Fb2qd)FYf+$MFv2LBJb6j!V6{^x6WA{{Ha2k!VrUSKC
+hXhI;e&Xjv;7BIq}_MuFu!O(=T4+b`valDbwQqCE)hRO&5qIwcGa%X@IjS12kXz5cUP6fx*AU9`0NV<
+evqq^qQ;_bYluhm4@62@XgQ85bPkLUmg230MnUP`?gzQclgGE3TX65koznpDL*^3Zwb?l!@UUh;_qN*
+YOg**hc$nHmc|BZ|E|j>Uz`ICpnLURa9i`V7w`<i0?@L}==)iRS7!jN!?h0eavxzD&Zw9IDH6@{<G*C
+qbuWGR#W;s~C(NuVH;Z5D`scJDMj1Km7Dc7)SnfXJ-r?iLRtrC9y5f=WRsgtx@sDH<f@x&=LewYVV=O
+-=LVf{?x3ABd-*Si3{*@#o5=WDwK=+7~qbSLCSUDt2c$`aJ+uQR%OizQ;!Wme3Jm<jX1*~*+D09Fu~J
+aSWQVf&J|VYMfJp?gKh#Q{KdI7)%P(6#fKzIx7ZWzAM4&BNG_&U&h1nzbTCxE<-ODTX8y)n)K$UanRY
+7fF`+x~7DpI~RTNI}IzoqNRTn1=8KsPSI5Ql16fP0>qIKgvpYnT9VBjgPdiWl@z{ghDnn2%{ESVQ*YE
+YI=H1*Zp!lsc+<TjUT`#@*QMm&CEYV}%buZg7c+R?ReUcAeP1g5C4gsOsY+>-JG_UDNJ$u1V$-;3Z20
+5Xl6i@A(>@TqX06J|@JyMA{zArcB<>+PI6D=^hH^#^MmdBp$>+W>bXU+?-M0!qJzZNu4cDDD8G@M0ff
+-=dQcd5Yb|NQLpF3q*+@Mn0Tn&!aML>$&ufglDf<0wFb52>CCzoC>e~XOswX^FeE*5UZBsu)Ui_W58Q
+p0B$He3u=iCQRbOq~cGp~4*TLl`VNJS?x>I8XeM;vdJMNOk<2e68k?8~GtzKj+k*53c-o!jVi0`u}vm
+FYSis;%(}aEhPn9NBDRagp&(DP!+^stnjWZYwFDs>>ZPY3dUBr%+4z<@kdwwhD$tBhv$h@S&O>J1;)_
+0jywpdt6z<KIq@|U2kT^YGBPb&zMg6pEHZHs0n;jTV0r>00G4!)sWo`zBq-x-n4NT~6z3y)nGe*BLQo
+!>{lHlku%Qb57|1lUp`C12!Dq_k`)*+|PJZRZnWu+@G84^*DDzFbhYhj3klD6;-+@`MK!Qzu?}WE&x@
+#<v!(<71ii2tbX@TKXR&naL;}3@p(L>ug{tb@)8Hb1!G!J1gbLm5sKX;0W39fXOMgm#F%aoP=Mhng{P
+WfkP-tlc|3>(mQ4-62BQczBZ94I{CbAsldlx^r+aaNx4_JPAt--8&~UFtX8?6&rqVh}FVi5$AHj7DF@
+DHGXrx>RN;{L-9nC%qWkC~+kpnhEX$2hR$tU72sN=F5w+s&hiVQb(naE|Vt@z+~}dAx&<)E)lN5Kw~=
+F5-lndT6T_~gcuEwvT`h(vKx%WLcFw1Zc7Ra;h%#FgioBEGbVG#*vMY=uyjIo66J_opwBAJXlPCHVOn
+)3HBxW&1h%QF$d*4o`Sz#prb<%zwNZleqrV7LAx$o?(8nkc{80&(eok=?n~ZLlNl{DAbl|YC`02-I5s
+1M;>4apY^W-L<xWER3CDTvzXLfH69M68lzv}PmMBGh-pDe;rM?T;-d1hLvgFqRBwk$Rc>mKxXOg2)<k
+;7VD<Tn>k$&=!yb=Z1X9!Gu|?$p5RXC0+7c9$J~CH#M>PDQHhh=y`dl?oMl&68$;iApAY$RVZUG4e3V
+9#U=OIJ=>n(2t6adb<yaiXP<pzhRYw@frj-)d>&F>-;BR(d!aLNfUMJX4-O!+Ss9sq2}suoZawGS%t)
+6X}>FUo3z*XG)>tA={Q0{n0adKsIUw9XRH{=t$APn78>S`J7*x1Im*U0Tf-@i8(Q%2YM%JU_e|_}=WV
+%?oalKwH{fY|#r#1Zc0&8aUN(erEkm5V-=Pl%AI=<`$H9j<UZI3(Er^tK{Dk(3XWCu@{by~zdrv*^Zc
+Qg1R~>&V4w^r2dM@z|Oo4o<E|EXvthA@5N^yKU-epfyJ_BZ>K2)AjtXO^VTlNboM&ew*^477?kvxaDh
+h!Tw$}jmC1LFJJGT}9q(iEzBD&-!3OkrnJW8d<R`vq?;Bwclt(1um)uuyezb~WtmibheicYDWQz@P|*
+iX&<nMO%pMi}`gW)o3#S>x6Lz(#l%7!($#lbBRuycebPf-_Te7Zv7nqRCY<-4PafASX{xmf5_zyaQkR
+WMt}I7VEe@p0${hQNnk4w1ki3@k6`el3Rc-oD&ETSNxs9M4`VeBXiY!H2E6{kYbD-VrJG)N<qd!E(`x
+vs8UGrXZ;HhntNem0;B<X;MrA)NLDR>ObAp<W=<2DydJKZmlwLsZxZWF`ihfx^`+1kR7dXj?(eyq+^J
+JR%Xa&me=wY<U(lW%<TAT)@D1y)1@SVt%*iI1Pd1FtUmD5GJ+vv+Ewx~0pKOGvHgW&YJoU!m4{@8%fV
+I@#$BuZ?>c+z+KvRw_dpG0BiK~5U{nhE8#1W*p)I0poO!!z;1hokqRco3r*eRxNm?X&@slNylyW2@q$
+llUao_-EAdXL1tUn#Zg03aJb>fwPg^O*C+`mg{)!cgKBmOq6!!m)=n{$B-Q9W@+NbZG&6L$<%;PKo|<
+8`?JNh9iU8-jJK!90TI>PbIv$%CR|}k(*ne4R?ADt^{K8CpogyEjby5=7aNP#1eu1EIVvQ@{<zu}lQ5
++YXyf*sy=tm=`t@X+JUy6&vR!FGC&_pXcYFfMIW`)dMI)wy`mj$yN<1p*=G#i0++`-Mhx`z!Z^6^CP}
+R1AIr#?osu!C2R6ShX)1qp)LVb8v#n|AbfvP^3PLTAyGlRfG@r~;8;LC3mjt}hZ_K9ve!CF#sI~C5IA
+@@_>xeGp=(CPJv@#RZhE6D1`ovG;OW(=<Q>y4{M^7&9pjM>mlJ%YxCH*{4Fn9DhqsbL;PtnmX^=&HrH
+7!JzOU826EK36qd9z1wpW(S7F-F4Fx#aY=N-_P&eH7%mVMr?Ns&1{ovm>^t#=CXg&3xC90@P+%;O5Ad
+K!)(F8q?!%P7ko1jHA<95XheXGmkS-_RM48`a^LD(D{E>ayFcj~KRUCiMk}Kx`BnACG3Bj=f=6a37n-
+O#RVT=xq-~A}b)>v9S12iH#(KLgUTD4(KX;|~60>k7$AL~{zLVm%jFL<>#8>m`HGN|wVAYgdtd8uKw?
+#X$_2h$w_R(@8-wgiXgQZU-vp^XCj^KfU!Fnl8zA<ph3$$arVt;BORjtIajm|I<n?2a%X(4iInTD!-0
+Uo(HL02MfhOhGb*9nKj-qzpUV4R7!9Pb2X*<o&v|5Yb1GGz7|)zMqrcpHi@RW*{4dM#lo1M7z{jOL*+
+=kVFkcO64;>Ti9Z{x?ud0|XQR000O88%p+8mqlXa?gan<oEZQB9smFUaA|NaUukZ1WpZv|Y%ghUWMz0
+Sb8mHWV`XzLaCz-mZExE)5dN-TL3kJ{7qYg`-dwEc7R-Rx6<M|~fg#HhZ4;qIfuz&;-|z0IH_A$yI7x
+>M69Pvf?~eES97(Y+m9|W(?N$`qK)BDn*mHX<xv2+K^H!#IC&fD0XtifR16-_{`jASQt|gDy+;Z*Sel
+M+1MJgk9btokd9A7EQI1vR<!Bo6gIhQ8R(jpgmYI!YhUKooaQNo9M@&N%-6gM^R0^Wy64^{x>K}*9r1
+|?P{FcvZR!FL=R;=auqHerw>2+(s}vsvxJc+2gA#=;~i(mhX-aS&XnLy<Q&7$C1*bUkS0(s7^_9x)Cq
+gI3T5==dq!a-gZbf9;5(FRic)knyin;-}I>64pw|We^0JOpPIz{-F*!<I{k_^HZr+$+bPwSI##K0}vW
+6H)A$=*M#0lb3FKrMx#q^54teS?l=Q8xt2%FBjk^m*x<P4ZwylfkAb{l)u}L?eN=Y7hh*Awh)e#9)=G
+!q<64Un%u1SMGOa?rAb1*eVzWUqwmyO&ZBVVWV5!b_;+BJk#^TVgSHCUTM#wYNL#_lZ?Q2HC_LOqrZ}
+c%G&%}m2Rq10`E;P@qJU(8J0F_7}eRp;*6VxUol^~m^%vendVdR}EnnKkgLcBe2V-kFC_#)&JnVnsv(
+(v*1_e(aLv61C>_B&i<)Z|cd0crR%>8$k8WmDKD*4V9Cna&IiR(1<cPFSrblZ`0y3Au3gBbMsKstGva
+-D(v(KVR*Hfr3;wF2ynh9w-3CD6=Y`!TJ$|Hm@uM&lBrgSfQ6etJRdbP+<5$4OK9nX1g{Em?(V7aU+X
+-<jZ<r2XB}QBiUq20^lQTl7vlgF=?XatCgG}UL~mdl$`=Z%YhD~K)WFd_eUtSskcI$3`qu%7#i+z;tD
+`nb&B{C{126h@jKQ$mG~0k&$ud!bCIOVP1OE5<-Y;+Bb^~0tp%|F{Djbi<CYR1$oI;)s%wPc%i5eSA>
+de{Y_HUSz9)~O2ni~R1NSD5g3Fvy7rH+pR6Hd042XF>!=Gt%V^j+q3zenv0;D|v8iUxN^aLaUHZZUjD
+XsyQbUIlAA-}`9K4AqS^9@VcpO*`0^~@Z~QUU@&cY@u~!C1EDFzd>D3bKJNb{x*3Eeo@X#9^f?N@NlO
+6yShc$a*5Fmf8qyZ0zvsEL?(K)%K=`K<En8DO54(QNJ?yU|^imuZBLf3!KqPFM=+u)aPK#AQ-fw<I@s
+x%Qr)hLxWc08E|k?w@=rv>#VwRFZo_s{>0M#V##`?`k$>Avf#GfqfeQ)W&f&W<!eHXpgZtyD#9Uyx|Q
+=!*Wvx8G{^jZ%=Y=AKIb;ePDHPS;LpMi4QoS+8|-kJiWhs+4^S6FwnCL+Cr?FzTkfsMNE~i0EQ*9Jds
+>zp_~6*GT9Gm_LJaUh+rzF%0P}zMdBw#43Q1e(+ng}h2O;yso#0#qCG6nP*3RMMt^4=1NIn7+`CSRj3
+8eXyj<WSK+0NOLR7d-ImaL)+s_P~mpyV?0!{e%KSw+bmq&#|vJRL@Gn$FYr&H@zGM<RX)-N=Nsd&X17
+zF~6%#fL+Z)`=TGpYFmNM(>D6H&SlGxkSQ}^+;@Ns;&7f;2<`lE$qlG`<~)GrR{8QNl#j5mClt}PZe6
+y-IH~!yH9NG790lL@XK;<wm{n=0Y0Ne#me4%Yu+G_*cM9je9A^Xq1$eAf!9jlR&3+sbc7_b0>Db9*$w
+)<x@^dpfn?e9xE0m<*WLNWpHp3ch!B*E*l85%ia<*uvS-{FSsxO5;Nx!BIyY@#^y&V|Gj6DMW<!IK$L
+1H&%>VRBv0!HPi7XnZqS@)tI2v$U?GSfk<T_T+uLfc8=t-wauW@%u+SAT7ej2)3Iz4or=Pu_myPM&UK
+h@gDrQ!D}H`uvfQoCnH=@F4~CVHWwQ$jCRt<C)-`%C2Q>n0<u;1_qp@BrL6d?^}$p({a{gV*+MZ`9d`
+RFbM)NN}Q$1B<@_P)h>@6aWAK2ml*O_Ev%-NU|;x000F%001KZ003}la4%nJZggdGZeeUMY;R*>bZKv
+Hb1z?CX>MtBUtcb8dCfa*bK5qW-}NhSbUQ2U%2b?W)5KHd&Pm+HyN=_Dlct@VhoU4%LQRo6g0!ve^uO
+=(0)QYz$#&YCyG)x%Ao$>Ue}&X?mF0z)mFc9&vP5?jFC^J~uF|>vnz;w7xL71=Y`^NY_C8Lsbf)H=S)
+MILv0ecHVICf(>%MrSCPiQTC{vloMV9x)`&FT`G*0^BW4TIXhu>VORT!zXkU2aGm)TS%I@FVeTuKY>;
+`Q6(cgN8`kAJ!7iwk<x_HJ1ycy*F30c-o}=aaKH?>}E`-#(SATux%d%)Von<aGOM*D5c{IFaeKeJd~1
+6j%_I=~U)X_1usd+I>-jbKyAFj?!*Nz@JYS#~-5CM?iJ-=Hx@4*5<N^mhrDy9xYW0e_zX71J2b$olhd
+bd!}xAP3b7px6v$*m+~gduXt6fLPo22auv^|=A}{tzPR4+^g5j=ijyRY#87;pr$HT=fZqx5#IZ`viOp
+36>94gQ?mu27aRFLZTPkzeSYn;1tvHhHYK=U*=m>;`%TA|*+AedT(5QU~uuf^M8$~IwD~f;-o#_1Z=;
+P_hE1>#N=mKAWjd4-rT@Ybk1P1M?0$N3Y*dqUcU(v-c7q8!+{c!SQ^yc`7qfe(F;azwqG_-><%`)+FD
+7sJj;@}Y;HkC8bj73%^Q{-NyB;B6ae<{Xbt%poa5PV!H%{GimJC&fAz*?zAv5?|APD&{<fL22!?9kh<
+*06sTmkC%Vs5Q!7SEeig-1)j#z&}sIgGYZ0`JJ+`t5XGhP~#HJS&K=WiVP^q)l|aKfYVe?6w)WgYoTR
+P0B;#-(mZ=g7@eP-*Rccke9Qsuf%qX#w4`@F#Oy7=Hd3)Dij_Vb4Cbm>lw-8<!D_vV2SCF>X<bS^IC%
+8z>32*eF$n&PD=y8lToh6l@mM9Q0Ph4u2<EpKO97a{vlMK<%+Zg<=^B{9h=5^-mi4?Ki!x71CS6Y>m^
+#peP5MAT+V!GGiq_=C7DecE)J&vV(SXG)-V-Ordx4C|M~Ni<mrB;6$V7adsj2W?-A$aMw=ynZkJw>+k
+OIbJutla>IbVQeV_HL&reZ0VS-uATOaW-Dl6VXPVx}2LF)3Cq6>>C5m~{;o=y2?G_QWd*L@5nG#~EUg
+vIkcrDFyloRFit4y@4E;8tj}H6rkuzjc4x(PXa`Y7V>tLsEI0o2iXdhQ6PLoo!;>{g}BOi8X|+Y7%;x
+JjrY;JlZ$spA78(XPLF>&KJ`4y=c5m2Cucu)Ag0N?_P#lO_320J3X&|l(ov$WWHer7(bK2TpFL`I1rk
+`Tv!o=cf~aBlKJ6AaDoMm-5vOxwp2*o8G@ua1a~Y>_A*J}<TG+Up>u^Qp9%lKRt&0G@tXlzz)Ugmvat
+S;Njo7WIPtGnr9-W>>9KtX7z#?B)exXd&Ed>l427o1vx4r~!Q*imk`rY7?V948vTovM<a($fVSzZA)W
+?Fd^v(R$jPz2xL3I&N45#(|jff+z#DIf?<?Ta=_bvZO0Qp)oMTx1{P#brZW6?we9NeJj(F!-hlDuVzG
+&U~-Ps=!z&<`O<lWVi8lU(ABRZ(bDpeE<Q<odnySJ%uw+soT!kU|*RU@>`EK;Q9>Np5$0=UaejrR5A6
+TcfR3IJrsrGj!6M9WdD~-S;HhRqe%>Vy36=htAEMi8F=d6R+*uEHVx+kknuLA1Q$SQ$5mzYgVPFj7Wj
+RUEhRe^<d;D$tcM#6zgY_2<|bZ?6N---Obd*%kYEw9Fo*72K5|t3)6B{+8@6?w6t9q?=5G5Cse6c;H_
+h_uvgcr7fThE_fyY3Ut>d53iQd=Ab1KIwPE8irBGEVWT*T8UNa7~L4~jDgqft8i^LQKpHW-=<xeQu3O
+q^xHlWY<vZF~NhR&QlPQ?W-QOgvc{qY)v-OY&CQ?0GaYnrvSF3%>T~(c`}#>~s9sN9VY2__L2BA!kE6
+1Ay`-HUP7Uz!}C8xCREb(<wz+tt34G|3NGRq^xBTur6p=QKnFqCF}p}i7Bv0{7(rE8w?ZzzZG@@xt-3
+$4disWgw0@fCgZi}5VUOkD+a<F$R{}|SPRY`$~?BA6f<ksgR%2#Y}DsO;|=^|x4p4BHJr*)m@KD<SVD
+uJH88sVrf#oiw}mqWB!jj@8P(RhTXVaW8^FCD%hAowg5NTYB3y(}mSM)V=r;7C_q&lr&0`>}yTP<U_)
+5#y5HYSGVU^pp{=#l?dS4Ya=(J}srg<P!dhBI>NDxMSn+iENR;L{t&|<U#<4h11d_{ew$Or1mH3pafH
+cTi|11~scOf!Ilfn%D{4jnTD`iv^P%%)``>skg;+EuO?UXVG5m|=fHW299C>C*6Ud+4quT!@zDg47gb
+RB+>}No0n>D$_RM>SG=aY#I`{UTe<vby!(n>QWI*Ll6xw_OmB#CM%9FU#Cz@ApJ46Bjz{TRq7oi`H!7
+CH8jR4mr;XQd^$V%c^{!01u+WsHoK8fBliV^b167v37eWa8l?s3kpUnuxkoEA4iJIEYx4|i7tHk0*-n
+yj3Qik%0=lGfs@s9FiG+O0IzlxE%ao*SrtAw{-cPI;yn`C$^S<qy?7et$@WSBFXw!2r0Ja`#8YDniK8
+c+PpaGaN3cC+@SgA`0z9l$z+Q_9QvJaGb33Ub0K{R5J1~4d5hXn?Jnmz2&+aN7k6}2rT3QhrAm-e!PA
+pzA_O7TJnM;hZpw}DqZ=UGwC!)kja*O#0K$u*}!uCpbaO82TPi1ZR99K~ZbOX9f(IC-HDxj*{F)ex?S
+%C!Y5HUE9d+L}yFV`+ms{4u(Y^KNkZ=BMKi7bow}3<dVkjlPzB5bz<rj;ZV&fXbg?$VMJfcgwyPihq<
+4-wf|j!pI&B)8td9p>=Nvp~4;bMxMi>Wxl%&l|by4Uggx*N+wedv&6%O*RdpAKoniokmYwAY5Q1+Oc`
+P9Lje70VZuL&JI+~eNKoz+AO=?|6dl$cj;zG+{*eCpawxiw#J)&mT2a)yY><RIAK>NCz`?WWC8zM+EP
+-6Ybn(M;3P`EEX)gV>k19)DPEt4uHKvOU<$qM>2_PNZs|$DV_XD<9$hb8a47}*s-cQt?L{5IID>Wi)L
+vc=S3q(eV5%ny<&wc-`epzK8!GEXD7aszU+7qYz)f3irZuy4rPq)#4>03OB1^tTPz5w14x16aGbJfi8
+_ba(ug&9yA0D)-~zP3G5wuzOFBFIDdzvk|+m-?W{I7dfO$lHP?_19`Ja7fsK3<()t$6D^tO>@Xi!3Oe
+5j763eyPk7uxNS#60m;zZG=k)OR8@8c?L*V*r^l3~4aK*)zlb<*EFz*Ci#D~bmM=SZ>JaE&5dI30nLT
+)~Pt5BJZX4h^eM7cYrfQ<WJV&Lb;RET(|E>U(&JrANwZXoJaCid8;sG6`hIK9K_;l51tJsXB4T(o?38
+@+q!zx1nLWab>%F`O$hxSADh*2N<LonCxYHQni76W9kkjWgq2KE0tdgvdM##yT+`?z#5irO&V%(S8ws
+Ee*C{8awQjWEckT=lB-2AHyaH#?u6LCA2~z#sCf^~i^~suUfQUD>O3;Jw6{22SUgA#=(lXr_vN3qKJX
+aF=>C@&IxkjO_+0V37MRq2^MI08iyL<lV8F;_fx(ja=x<8g7UV4m(m)t&IurdbO@n-B4Umid|r@fg@I
+obEk1R$JE^eXY)!Fot<<PA?4uIvVZdA(RZ|osTxf9-@V6ApFMtF6;b+1ts=xB(txvylZbL~KgQBF$Z*
+sWlE@{bFWjslDzMXyZwIyAcq}<c#o_qOj=ua2SKBk%jlHA?A-F;~-Km55zGX9_7wQ7NCnw!Ze+zI1*0
+LYSs&@B$y=>>&-TLVl|D#cDoKD3tD1ysjOf5z#f|&mt{z7`<fn(J)8{r|%YE6g0S^}N40M&x@(SQ%dX
+Ze>Tfkd(JfW5XeSs)0Gy;(>ApPNaK)j{wEGtf*Bl&@+po;EdVleFFXg*!F`)4Xxe-IU!GX`mr*Qwe>&
+d6@c`ckb4rO})5-_Pe#@eQF!0gb<LXuHpMB?7OW-=GdO=`yS7f)3CG1JZRWXFg+!|pym>lN)S7|^9W(
+STHD;(*r!>@y$EvG0ABp9Uo(TMGh{nqS{Bv(B%a5Jblrx+YAm&>?QR@bive&RU{y$6<BaVXQ2)$L?1(
+Gl3@SE<1^Q7lqv0kpH-o_}Ja{&rM%zgncv@FTY;PEg8_3?zEb6k^bZ1$0OR4#6+ntdYo0jFx`NV$=8S
+l+a?PKK~#^H9|tu<Bew5`kK>5b``k&gQ+4hww`o*lM1F~fT-FKV*dAw*p^Rj-&0nN{?ja=L$j+a<K!t
+?M1UZpHm>zQ01vx6>~;zcvA~hK#Lm9K5pm(BO(Y&y-qu&<3T>xo7W-23JFONTLliEzHam4caAUwS3Hh
+sO4_#1`rqTJfL@SWiRDS@M;mJNOk!p=v2+*ZFh)55p_x5z&lWOgT9lCJNUHix?Z=pBb_PqmxIG6muS#
+ks5ANA7tJ>|U&6MI3tUhVikISGOD<y|6I=qjv9G%U?R)WrI%FPz$CqsRTM+8*oFf9P9n;obYP(e=4+}
+J${mM8`6jshvS9~MGs<rPn60E?bUjcX9OgGw_#<&<v*;T`V*mG@DHo`orEx)cg=I_ZbKYy5~FdoOIL)
+DeS-Oi`L?r^u>IQCSu*Q@1BUN5x8<+M?Ix7_Mefl5?ny4DmJiKX5|_kcBp<i@_<g{7GK%#Z_*X(YlE5
+5%G&J%6&(CO0FAyZrrzA8(r&?O<yIjk_6Yl6hd}`TL8LpY7ZiQmkC9kdfEf6$VkY65VSR3z=%b6~6Xt
+#?`1^>AEs_JNTPJr5h3not627N>->nP)y#~o@b#X0N<=~g{?1;G+Q^e!qf!ed4sS8-5a3MNiH>J?j|m
+9AH@UL+D7(^-oZG@#)IdR#|JN-9!#h4Y;dZ^gQ~~0TJN16eD{3+6rR`RZvX((6*Y1;tkyt)QpMldrO-
+p|f+03f|EL)o#kUr1zwT0*8s>K?Otb$J^6iN(yMaC%Ki>Z`qr~5?eh+M`#>`!sAU0ZJ0Lo5HUQ=Lp*D
+!H5;&Nxqt>Y4BCgZi|S&dfARD$*E$3<p3*?YXi#++uLNh#jN#?nh<DX8TQC@7R}nB`^uolc$c>3OWQ%
+j5TIcUtYh!OY>8taIk}N3_w|bD!?p->bLw>Rr9fhF-Ie=k1_*tewpfKS=8uEz3AvcRl34Tv2#$bn99h
+eqM=J{g$C_3Q!K|EFIPt@lWvDT!W#XbFf!n_L^Lp#(nLA7QrSsx)yG6sQh?C^u{%%5dOui<bK7;Osuo
+A4JOtYTnxtIEr?>A%NtB!sN$wC>`wcTrP4$Rui*j8lTy>9u?=L==9Vn*!NPplhkzvQtn0gH&mJGtVfF
+eAE>oI}O}Jszez$+-umagb<4JFaA)aU2S*|u+M6wEJjymI8DtP(O&Cwv&A4A}+rkHg%VW!pFJwn^~ss
+4U7f~rlEs;;=#4fnd>^%i%pcEyg!cB7K&w<dg5Ll^mu0ffKXn$sVe0JH+!7zfrG<p8JGulLSzmdNZ1y
+x-1v)>>m;Z#OrPtqoq7z3tPOAmE`C2e^<k3*B<rxw_g&OmIJ^=~BD0ZHyTNffpj|Z%{xjxnP8};OPA0
+KGKzENdj)5RxX;GCT{O&RPnxX*MmbOb+NFwT5E6{>a|OR?6p60j-BZ{Bp_Y^T8#@@oWar!Nj{ivCo;V
+1?pBqeYPD2JoZHJ>m~)~-Lsyq)WlBlcXyl0j5NBJ*V;9og%dxmBBHsz1ey3(Ms&16x?Z{6_p_X(Xk^t
+hBM_?dbGK1IwegPe1<s(e>4k-4yjNqT_;2lR~ANcv~2Jg68dND2WFAZ^<ER}L<uW)!b)##@Y+v~?2vu
+${p^#zMx?gl`z$D)2RsA)>D0fr{s8(=F#u{W3Nc0$)=-Q^UgC$M+ll%v?za2+N~W~-}lC;TaXW)s?d3
+=>^VYyS3Ucq&&EJ={&1(&~QPH$U##*9!>m(}zgFp7Kx$Z2wWxcKK|a^?xrPQ@`F@KK}+#O9KQH00008
+02@m7R&}Hfv=Ipa0Mr)%03`qb0B~t=FJEbHbY*gGVQepKZ)0I}X>V?GFJEM7b98ldX>4;YaCy~OZExJ
+T5&pivf{;;Io61@Q1@4M1+~Sb<+MsCy)G3m}Fa)kd?K0MiI+F5w8zjH|p5cpL)^@Jww+4Y%B8S77;WN
+(+l_beqRdOp;YuI5Yv|tCp8l~=7tu!lDTg$D<m~4&ZO~Z`s>pEk?mPwK<7H90kPC&A0)Iqje$nW=}wa
+n~P-&AZPm==3=FDk|{sP=+&N@8BN%+kW%_FCjnvp;snHMDD4+6&c@J-oU6nKwqzE^lhq$?n{+t)gwLV
+!aWpk}${0hU^>mY?Y;bd*cMLNvXOc9>@S;`_3xW7}`;8cb4t=y?`~JMQLFqOjB-+Xz!&~E%}neMQIrR
+SE?0kbM!7n?QtzMnw{Lkk{ZUq(l`O{Fn28k+gaP0^=h@1cGqum#A?+YJHCQvD``wG%<7Ln{_xTTo>VI
+>w-R9>Kg-@2#DwvdcGBDjNI2QUj{KY0c)$jTF!bgNtB>mi!@r`C`%Y<F6lqcnkt=q*yi1n3Kc<3QNS6
+!oP>Rm7^o?6_rM1!-`^n;THoX<@ed)D!+?d6}YX)q#FnAkZm5ER0Xco0r`|-r`a*uHP*;fD!{9@d&*K
+t0KJzC|5^9aYF;ri9zuKsaV{Qc_R*Z<{;_=-KpScJi%e0p<u;qxIX*$P{9N4ryP(a4P#x5tj45hPv%&
+KY|P6&ZUUP@S=VwRp%_$&Fq3RdiI?-U<zYe6K1&`;|L^jEO$Fx2MDhM>}9VNPm3u?)CeR*UyUs-?j&W
++WWXf_iYQ)i@vRdF2?y_V!q)<Og-Q8&q^12+2ZfL&;-xLf*>F?yNp=KA^FygrA5*5y(o(1VzH=1J&C(
+_G<ATYQ77owAai5Lb-iXABrX&?PVnP9MPf0oH;})Dz&oUXpVvy+@6Ai28jciwN_VG4Eg!zO`bAK(MF2
+$Mkx|sL5$06il3o1SL4lNH<kzjw9^z2?{U?Y?Be}<zjD+iteJXtdOL`jdW_*&m!x-Yp^%h2r7B~R<N5
+ZD_?Uuazl2GWA^>_?ly_5AAEH^MyeUq3{%g(<fq~|8NxM<Y{9o$7(Z<E_#45p?grh|%Q+=l4;sgMr44
+um$Ck#}61xp=x9L;{z=<q~Q2TF_s|U~?^~WXDdJ9jZX3gz<K?Wz$z6S=m-6>K*aAf~EyGs?BH0kcc}2
+U#tA7rPvEB0pxl=XDfaF<Oi-P7t`6C!@wK2W&)H@qN$|*4rJB~s*a+Co5VwcJT-ZeJ=T=5B>#+Znkti
+%!7jn+$kWcd*O5-=%5uKk2Ul%APtxO*xnr(GQ5OxOjX<si#?mC99JZ8*qZOAQbT7Pm6c#~61WTnqjzO
+J-G9u6PS?bPco!4{5-o5{DwWi{4DI$bPlvYO`DF4QlS|clQA?g|xo2l9x6DzzEtfUUwu+*t=bVy+eTZ
+bO1>NPE_sc_5xh{E?W5s+sL8$tM(q0Kt49Lqo#4{6TI25$Rig-mPJ)H0J#149u>oh4K|JzXs`Rwp!e`
+Gx*|4a1jT{O{M~kpk!3i2@qC{6c@9Q6O`-@8u9nKM+%R8sRa?WbSofSrXL@BjLfR^3OrS*>~yBz|GQA
+m?L_}ocnQe^c3cvh`*Z&aR$?QVxt4R6GuY&q=^`<_VPCnAwUDa99>W<kvkD_3Hv>12>Q<=9H=8;rW2*
+CrRywx_nCtYW2YJ^{)IsKJW|WHeK9EUjVLlbmAS~NzqR}hyoBhKqC$Qn9`^)8Wp}JY7ft(7)8Z9$z#~
+SMIYZi5fwnZC8itH|!J7j=nipgj<FyqL;EzN1C%O};wmGr`NAnKTXlo5*GG`*roDyZgz?lQDc<35gO5
+0G!{0q8U*I@(L&UoL*Z_s_R&~tktiy%rS<|Y(A&mP_;^sl8I*<*QnUU}bDV3X8|h2UJyB9O%h&4-ua7
+-7J3?NB<|4PtYU)4u`K161iBOz@fUjPPg%2@$zWmYV0bm}ScZugOkunC**k<abB*Pw1JGdlIVNNy$iz
+w5MZr;=A83&$NT-^6SZpp{*E)L&Rg$DVZmHf8saXC|XriTHcF^X9h^KZg41Od}HW0eH4)8^5*63OzUs
+PjEu_Wo8P=#-v-OIZ{9+q=6hQT$p2qg>-toG&zSe8e+5NQiYDHt1i7lUFr8|va2@wo;jXs`lZKz56O+
+4-14E7Wfly^nw`x}{VGb_Rl`t{?t$47*^_Sms+3*c6xqjEs1IAl4G~tXK{&J<at3Rwl0^zq35BbjSn=
+{_HOOF*7(<<%HZS5?b9u4hEPt*d?a|d?fTh~zGkhKI)`)<J(k(zGBIK^rNu>Y(PfE48jIMW^d!NW>f!
+ZH)TX1D;;TrzF?!x|5Yr`OP2ToY>fB&;(kK^uccLh0iWWy9wid33onbj-&NJ6Z0SqGB{Gm(a~M^}ZLR
+zM3i+;Rn)}_r#g5WXvuERF6>AD&-O#Cr@pT9?bl<!pTnV@Ti$-rwsZND)ir0k0x8yUIYO+cEX0fhn?C
+O)8OfN`q^hAI%szt;CCV#vuEfz9^H6HI&`4O+%ad&^Gyt77JIWP+gwk`#U*yAW|7OndvZGxZLEWXh<~
+4o1mIpiV#I6`Qo8AlBH?{1g3`-}d3uSH%LzMfWLtQ@Qb#)=qIGB<K7IPMW^Y=i&?8MgQ-q>oGWwhpTg
+Q^OjyO0{?>x`X=?f%i379ikP-hgiFReiLfm1H2<3f$1k0m>IRca)P76MI&x6dauIVl5iK{{?d+*re>m
+a$Sf*N&$}B-C1#T!)B_SJX4M>19(XuqR+(*f}(uqv2v70Z?@ybgI8ht0W~&R4yI>B9r<}m-Bl08<t>t
+VnslfUlU^Yv(n|{gX^j{detbza0M}c2e!x$t}C|Z<@;+^6Zs#MzKh+h37URta1OZLlB#d3w{oMoKCa%
+Xtywueq@KQ8x)geaV^)pGdDpo$_fj0j`-M9L;2X>KH|rlzzi_314F|Y0xy#(FUxvBW^%2eIe%LixpE{
+k)Jxivk_PyARcn;Zg0_LD%{-H1><BM=NDE&w7nJS;V|AQ)jd;S$rO9KQH0000802@m7RzRbstI!Dm00
+15U03`qb0B~t=FJEbHbY*gGVQepKZ)0I}X>V?GFJE(cb7OCAW@%?GaCx;^U2oes7Jc`xAk>H0Gm5gE1
+@<987RYqdo$O?rplPSOC<>XD=$MTx3L+K9DEi;`T#}L~TTU{&vq78K7VjbNz2|<>a$Tv~utMG4$?|R@
+-CL#GS9%-1%v8CQ-72%KNM^FE)tXhZN>W)GQJ1_(#A7BZBUP!HUwm0U@IvOd*-EU%8?|1@lGB2iebl1
+9EVbc9VL$OJ$6(hg7llr=1!<9Q-~4j%&x`cei+|t7%;As8Hbz49LDr_>g(x3d@wzEXsF5~hF6y*@?)6
+F*Tz6Y#D_-7-v{uT*>`s_;&A+NTUCR=`A4ILKLQ<znKc>r?uf;~y_mc^kSJdpRwQ~a5EBo0rO-n3G)7
+fM)dBxr-BQ#Sb!?~9@&JS$al$kYTg2x}rC63X+a-!I>`J9fBizROglRBeJXY)DBWnLZ`CLX0WY#|^c*
+q@Wve~Ot_%&bH$jx;M305^QgjAC5h<8vHLvqIhr7HwACKo45Xj?$_YOZj-jyxnm;EY_@ozkt1t682#w
+v;barT4rj8T<Q%pH-xv5W`z>~VI`UxXOo#`o0TjC<5{Mf(%=LPh>YjQE0qDS-GYt_^DEd`<ZQ8JZ*I0
+`rAp}G_3!CP&MI)u(pWkr>~cwZ0L{VfJZHHQ4u07buxj_TM~vA<92Esyf}(7}GZ>4E$Jx#G?d89`S(3
+>lJ^$_e^6LEOtBcf;@)j=F!c03Pa=iDH^}C+V;P~|B{l(jh_wO(M=H=4!n@fmdF*l~31_y}<fczn9Si
+(a^F^E$Nq7baXQoT}5k*AFoLn3-dPG{`+uWX@IaXMl6iK6JuN<b?z{dooTVb=M4C|bxx&Fd}L)u~Ie&
+JAFkHnm(d#(Ad&L7cC7nX@Zd3ibgTYPRCqu}4=Tlf3Y77K~T|DV#e8FGP9j_V@wxf&l(;)*Xl~8d>Ct
+U+@VO0?DOIBSa&_z2!Q2(Fi01tGYk6#q0d;$!FD{&yh7+9Cm!{#Gv(*7YLrU0HKKu*bJf;EZB5x%UMh
+u&%k`^71EA&QCdExEqV-X92gRW%ov5J-)lbisi5^8&Y~JqHRcH)CG2O9r)8Ph{aQVw*ZG0Vf-ewyPU|
+5<_j5{Y(VQYaFKClvLskm}Y33rvVeK6_CR6BUjr}|~92(h!64e6UqocrlYYzQ6#i2&Jz-9|!HbRt7@D
+T*FaJxoLMr~IM)6|sk4<lMMXMG7PFT{#JNN5JVVIvKyldd2rrBaZ=x-_uJFuzzdNUH|_Hz*Gj5D>}*$
+Zu2PARIDVZc3lrgQQM06WlW%A#49SZP?Vlu@6RdiU@H(J9ScYBx1#(S~#5zmhKif|G3LPL!(o&L3ZeJ
+%?DQ*mJ&$Z2T5C6h(Kh?tU-E%k=y(q#w`+!&|PXc?<{wiA%yy5qVn49r>ofJq0lyDNzS}!7;GbJRg$y
+YRCGD4E<dtsv?VsBVZWR0&6eutCn&ErnoU94ZM98HGoQ~6AP`3o@uN7d0C|)E;`$aFN6xlUFXpS}P;w
+A79l}2v^bX_-KvAU{1qsyf8dzx*+!FPODO-3E+o;=&d;)uhHFQ5@2jrHZ(pY6Y?a1iqKe}q#sz2+%o~
+?^}$Opp7Ar9P>>ShTHnCOfxqi@Kk$xa_aR{WlRQ`)`ibUcJJ8nSyQJRseIA2`Pg!4F8g$}-Tm)ykW)Q
+|@<avwM6GdqA48SM0iDp{+8@M@rLQiM&)suyItHDB0b|<Aymj3aJ<kQyCajKbOd8&9iCjkD@kh))RX_
+AHN`@_ge*?+~K?3#;(KIB}OGe-}lS^ch7rwSV*hMVG4W<ERWf!?Q8<4bBUsQV9xZ#Ysdnp$$$eZMTPi
+j4$zwazw>Dq@B9Ofuq*xuM+~jvU};YMSml^ONlh5`UTigOL`u6T5Qcj73{i*)nxv9R`pdN+(s9<$&V0
+Ue#vDUKcI0}@D16<oAS;GX_TKwi=iZ4&k)_>7UnVXS1|6<@nLhB^1(SuEwcRmIQ_e8`u@hcZqRhkPo*
++S^W@V_yu+!ZsQN^8zgih_u1@+%zmJsf9GR~>LNlC8ll?g9CL+lII(J|aIx^Z~HGN~2JBJ#1FoHd>Sv
+HW&-C>_P^-@gmj4Mcw8L?;Y(>q?b*F!;z4a|x?BB@iQO?fZdK`$=dQT5J=$ZxJdq1pLlU0H7Qiya(S=
+clp%yA01g`X`ipq5o4crUB%5R+|gMbv5A?2E>-~F_UbN$hSR5)aUL0$u>mk5<J?2PnN75QP*Qe4$Ym`
+uqo`}OLuxIKi9UG<&^u1vl?s!+od^+Gl^d$aboK%Zc3(qFxsZi4TQ=R$sMuM>P7<KDscF=1CzLiWkF`
+Y1R@)9N$(DCSd31BM=PW!?OP6s&_|R(YPSvKW)q~81oejGK*~_!m0NXA#>bCX<DbZ#Q2V{5N$=-+V52
+w-bv2|t4qIO*GE2B-w{~f6H^$>J`x|b?!KJKq}5L1K7;mfGk^cfM?aEw*nvDIz+>JIpd-3GJdDf>hd%
+<j!dmz|xgjV=~;Kpx6ZofM~|t#HC_g?K?{?cs8j(fsAF`Ep@6(Xh3vp9KTUTHg(H-s@4?p8SxFcKf<#
+eTbSMsejNA{&s)b7xjBvLA!$Rz4z$;!4JdvwNC)*L(<>f=_$+6`(Z`1pH7|bXMqV~!q8_OP{)$1{;CN
+Fe-MaIUN58}YsUVLD_52=E(r}%PmE`Dcf<94;sIYL>_%1$If$~IyTt(`s1;~ubeFHK2BiDQ7_D2hpW2
+JterBg>*o_0u(D$XiQ0bGS-R<b(yI<d3e|mS6uusB+;YXD?POiHA^YY1_Ekwov-D6d<I?{on1HIf8-c
+$<;C<GgOJ);|WyOrHv_Kbf?d%l-3y2N_c(}O4wv?j3~-TVb)Cpe_mVVEZ%Dm(k9k6YVux_93Wd=oOA`
+60I>?PoM}S<&PoqLu^gDt(%Kg_WkXXUw|icuCa?f4d!n3~Ei;branl-A5Gmo&`SQeW5z@%}sw{Mtvkw
+$eBN%e;a*?`xQ+s!WHgqxWacKX9I<H6^{Gk&Eg<e)v_|W1@~`5a5UPyeN3<0XI+i6ZO3Tpu{lO;iP*u
+HWJ3m^05)Wo;H#}^_x+ap_Q6^#CZySHAglLR#13#UQ~7?WZ<bMJ$8QH;vA3$ud_zeU>7>#1Nudy8ClI
+m<p^lX~uXDEM+4XJkg@7+{eQ;U+`r+&I>0iFs;sMc(EF)J~I)Z;beeIv0+}g|glPgzNPNMxgq2Zwh7q
+Me0c^0@eFoNgNjs>2^>9`l-IL7`yoR;O2{{T=+0|XQR000O88%p+8sh&krfdl{m{0RU69{>OVaA|NaU
+ukZ1WpZv|Y%gqYV_|e@Z*FrhVqtS-E^v9BR@-jlHV}Q+R}AC_%dI2tVjl_^NYNnc#Rf&z3n#(0NCJVD
+Xq#)9R7uL02Ko0MQWwjc1T7i_iFlcrGiPoTn?h+zi&CamsoVsj+EDG65tg^#2h;gXm0XBrvtbW~kjo%
+gXtkk26mcS?<yx{l=KGWvRw!wxzI-K(WqHor=0t0yUlS{>$Xf|k6q(TG&3o}yXj`(J%WWf~ODO><DP_
+iWay$=$9$gegE>drwJ_^m@y%yXAcQ=z+a(Qw2d6Im*n$dY<H!clyq%2+W1nVdSgmB<AeY*PNdP14vM)
+m<SO;ssDsM54`SaKoPJR_@UnX5U=J)dU<OV?}(dv299t1%g?VYB5nUUG|5yMnz^^IXiG%^>3oawi-1U
+Fl>aB>rx>HgF~y(Alp}%{U<Zgkk9a&$unMB)j6|h0eSX)k35e{wOWA<^ccoU{}~>hL}?Y4u{0!Wn8KJ
+5dRVqgz@qIT^OI((UqO>={bIS4r8#eVK({+4#l-Cgl(Z3C(;#@OP*+@Y$W;4e|Qpx<h+(_!~ODwQ?)<
++=2o9}!mg;_DCtw7dBG9*EDpTT)uMY_7(jLDx8*~)jwOEiU!~Z(46!a;%Eaz|{9Oszf;-|GRE|%<o8A
+cnH3AvuRA_EM@*1plEjH$e$;^>0$tiZ1u<)wvP7P_d66wl;0qyDfKrTI}H=}PtW@=}=@HI<mdQ-b~TV
+tOqRM8HJ=If&hVBdf<NHCot4d<Ha1GX|@Y*kqsm6bU^4WL*!#~oxkKc}!zM(o3i_WD>V+j1ieo13Vm<
+an=>3;)JrE5mcc|Br_I_v6Pw#Re+m6u-0`@KL6Hyq(|xW!C65Xa&}vMK4i7q1(KF_vjTqJcOqh-63@O
+I{*^=ckC_ZuG^X+mtMBV=)~qCypwCGc9II*aYZ(!r`ql32N|AR4lkMXL92?59DoWnN@OASF2%|p)Wt^
+?-F{<qnp8qRv>A}}R<n&dS#gx_u<x014Wc?3QiyBe;1zD_UOT2W=Y>;7LQ=ZRe6t09ico^61?May%iR
+<}&f_=-rejF0KAgtzZCqHuaoC6kC%`;7Kh;o*K0>D&dk7(=4594y)t%D5EoAk;InW9{cFxfZaE{<*uC
+Hc1=ay%u2*D5E3mb*E&{sJ`2UQZ&96)%AiiTngrK$m>KIW7wL|nrHL=c!btaGkMK1^s+>GXzvrq1j<M
+xvpz(5m1%KLDdq`L;&Zql#>!HXIEU#&faeG;-XHtQr-*1&!uHj^emG8ybGmIs9ZhlJ8QjjZKg4z#hnV
+gV#;TW=OhZYdSXM42T`NQ3W_$n$mS&yJEI&t35(bFS)yperpBGQDIr@RfWw@cV}f>zhmO5f3UFp9!dV
+_W-<=rSKvg0piYDfi=I6%E$`$*tGChM-xoJmw-fmKTl?yYb6r-Ci)h34M*PjszbJ_=<SI{?M45fE&`1
+!MK~?R|Avf;w>NcX&mqYcLY#H7wU;n)QJpJ-%c5yxVHl6(*4hF$LP)h>@6aWAK2ml*O_Evl&QQ=_)00
+6iU001HY003}la4%nJZggdGZeeUMZDn*}WMOn+FJE72ZfSI1UoLQYwO8A2<2Dd|*H;YkQaM!w1dA4h(
+Jh)}oo%q2#Aw|XMG(leL`Q5SQ6MR2-LLNqNy(BgNp`pOi=`nsmvhL&ktl1a45YF${F5ofA`s59Y^u~q
+S?JavyC=QY!BWW*%(@oU19<c7ujwSY_+@hO;p*mn1RsSq5!}{B$chya%+@uJAZ6MFZgnl{I1w0E;dtB
+_QRui7I&J-Fql{c&3VwdPV4Ams=lJ{%BPg+GC_-c{lWHZDtV&*C=u1&>Ox5u6&zy72;F_0Gt^JGr3j(
+nm<~<Goe|xH%Drsbj$?!sRH>)+lTab&td5VQ42`h>uLCc+;a<rZ2QM9r5vTe;<Ik)Cs=B;V)^1w}!@g
+-{tlki=yG<?APL~fF7PllQoSW>cJ=_9W)wB83nfI%S9xonCoX*5q9IJj++k{gyW!@?1q`~*as1L^39Q
+Z+eOU?kugz-O4xyOnXfay|#CaHM{GNEFwyQ7PAG^clo~^>@AoUui@;h&<|p?kbqBO^$zW;?vV_BVbi#
+ooof6D3Vfq5}L;_%Z0{`TET*YTydpDmT`Pr1H*&T)CHQC@Wj@7>~cDWt0nXRh80tSEefhLnO;qk-+!A
+VSJ%_qUuPe$&XeoO?Cjmy><pt~AkDE7VXPy7Or(YxEa}OEcAzv|h?Qp%DE`1yhPy^nQm$O@3scufXzX
+*m-A2Q|b>vIs%C4D7^8<msYowB88RGF!$OS7%KeS<3`LhM%vAAS-eCBfpvUgUpM=aQrxn~1}O=at&je
+|23L1tgrQYub>W0gGf-uCi<`5w<y!;eRCyDRPglQ4Nt{9@hIHHOyV2fm&tB~=7}u%hAic{KJR08uxMs
+_ZroJDm!pj(zmIqi0|^x*v_KClnt%?6KzwwQwonM+o0UaC*8M%tGhZIZ4{($8E=ca(Kp>F)G}h8^N<V
+qF^Ilm}n5B1w-`D-7ySX)$<AV#cgaw{%%|I?(M{$+V$r3tfVhLch^o_s3u8Sn)9$^pS1Xgzr8`0M^=J
+{+T<k1=QnPVeMzP^_`2I=2i0Jk0J^(EA12z&8wI;g23vT*%FxMR-pC8=0X1*S9Dvq|?0bJE{6Y*z8yR
+OXq5$xu*x|HMicUt)uNPLUdM-(gLfPjFggxCU_ZK7i$)zSu^xBN8yU^QgZ&o`-NLCk(z#Of&`JB!GYE
+F(v9R(WYU~Pqf$j1vf@Oq<jrg+a6$t18eMb#qNDsamTj<&~pd#l8~%wnH$*hjvPIAx{BT@!OhJ<T0%?
+ECu{xnSE2pgI$9eR<L~PsLL3jP4fHJ&K0f`1O1MwMrS?e>i5nJ%|+!x4V-9InLSzWuuK{g+zUcdFPuT
+T_GJCd5b?5Wv3MdhU<3`_5!2uScE;(1c7iw@$B=NqCyj!w<Be6R)oTZ*dPu1n6NXCsg>*q8wl3U>FEt
+Zs}<W!ipn9-vDZb~OWi;sUr$|!w4+W|Cz#wLZj+djJfX`14@@ugYas2X;xO$TZ1C!1yW1az)-(p+M`O
+bvD}l5o6)X8?K)wHXY(TYPzR~+B`5%F9;~oauE*RHLv2v&U8>vcG;BA#btt5RE01dR|^+J3pVRo@2VH
+^EEaV=6q?rf}X$TmKeL4{kavFCJ+{}MkzIx3xM564mP`UCYM)m?u`v7ycCzu?&2tl4JVc1gBFs9?SW#
+C%BZ9-uD#6BWU>5~pSo-7;HrL?1KQupp&s)itMwek;LXI+?=v-~ABxGuV)E>7Tlr+#+lBbyuf!{MCDu
++<)m7?Qo;?JMh8|gB@I>O)uul+*pR$JNqd37f?$B1QY-O00;mZO7>PkZ6D*(0{{Rc3IG5f0001RX>c!
+JX>N37a&BR4FKuOXVPs)+VJ}~5b8l`gaCwbZTaTMM5Ps)ZSnNYV0#<!nMcN}p&8~Xcv{g5IUZN;+U<h
+u&c5Ra_Iy(RTj16oEBuBNB3p3--GvoPYxFHX}jiRZ6jO0pGq%cP6+3oF~nWEk$si<ycUJ0S#Rvz}-3J
+lGtp`Pcgp`xrz3ZNM%!YV10As^jSL^4Q42HT>0tmvVC81Ah=Yr2Pi^Rj(xEleXB-}kCHZz8f_sfoxF)
+A;?unc$wcd|1sF^VNL&`03$k@l5W?+9SAb$X8lHM3!}Fm@FZF(clz;zwDxj{|2QI#E-}$Ej5HuXJB_u
+gx8E04W|`LQNB|3N&LN}CKsw2%b#m$<AE%`Zc$ZKHPeGYr;15)(TS5T{vfykZsJuVr%`-?=2fUnPZS?
+T1+m2BPqD=-F9prwmmg0P<-9h9P*=pUyX1*-Nf|fzf$6@J>dM|HmIBvPCqI-_YnC&Id6v!}@T+DDbiB
+Z_xvKo$pu^L=zUh%Cpg1ij*Q~@(NKKcUvFgaOcCVsWwU^xbw$q{nGtq85&&wbuKeganEISA=;xd~NZB
+$6&zwGbKVJI-Q;>4+wQoMo+!bE{AX$pZKBc#9e!w#;}`>hdMiyGknS<gcUX*st>+{jXJ)1v#nk5zUA<
+R$HmiP+gp5WGNv($CM|zQ));BsFYT0?7~ts}l=5!QGyNv1e<_nPIwb4nZ+%nZ52C2_C&UkIgQY6Q&v0
+hH?z3h`PQLo-FK2i<%#_?FpMRIns{o8q9A*fMcI>eTJX+te_Zyb;rJKxW6Yp!gHiYe79r9pPJicRC8H
+j*A00Fu&6Jq$M}vQH4pl#vGX`-oecci<nbL|;Wg`%pQN+BXbQhmkjCcR!Y&;6gHl5MpVOam!UgtV>|l
+()C)AJ<s5a<7e`iRJ#Qh_;+U--n+G|Uwl)$qf7~NEO9&=aeSRKJ&$OJ9Mz;<9)gkDDyjne@=`R8BvY|
+Fwi2IrL>8@47!^X04povqD;HMGPzFFx$UjMwlcJV1kIjkp^Q0o|$RC`Ve>&~w7k(2hU*Z?kzDcEdF$)
+G>5%9XlVBJ(w*m%kk-Uok#-M1TXl32ae%8$PVrt4<m9h<5eH}xic-R8!}H_4eo>~Fl#vdVhxfiYF|qz
+&xn@TwNA1N2zHKQi8x+^!B$QB*279>8uE(oGeqEJ*}0!wqO~9SHbZT?FII1#f%P%L>@yh*66<t{mUvi
+zNa1FJFwN)~cZe}8TU(=R%-^QBX^U6V#!h7v_P5$ey3H6<Czy@F{A}<lVPQMNo)wNLt*!STP)h>@6aW
+AK2ml*O_Ez9u{x<s=006yW0015U003}la4%nJZggdGZeeUMZDn*}WMOn+FJfVHWiD`e)jVr++c=Wn{V
+Pz+O-0H{%w!+4dz$jyc@t;WyLtE$XQpmbJ_-^cnPZCNl2jCJHuu}F9{>pOA=`0guhumgNhHu{H2RGOl
+1-79wOCdkjuQT=HZn=WjjAfSR_5Vqn=R`+Pb>4_=PJ+4_cULxlWc8%7P7udlZE+NS|EQ*idB-Tqg9!2
+M7=MdkI=71M*{xNUQg)r;=j*Nqo;p7efsCKS3mHhlWfmlp5|$)mUWV6=66=hBvU2-e3mS0{&rTYQZ7>
+E{Hk-^>P1rNR<Gnn#TVPcw0m73Xqjq6niuaf8ghKZ=od*5Mjuob=Ve&P<+Vf#gr)lHHYwFcWp!ny_NI
+AusB2ZIWwJ_CX*-@}A7q-uZ_SH|uwUP*gRr)Bl3FmY@^S-k{-$D_>!EHRU~rhE>G(pe<#PWcKb#2t#h
+rhW0abxmq58N~L^x;EOubaKjAboP%Q7$fx~2J2dcCToRuLnls)^WEs*LbiU*}C8tF#JZpzX4bwq@$`(
+zCNSr%x}UcW+)qFHbK{o}FBrM6XU>o*Fj6Uhm4Z_47xhIN?M{<9hcDP4o?y`36|sqF%?q^igrWu7r3X
+E?z%-JrghU4@$&pm1GIR6j!QL;V?wCUPoz?T^pF@cZ4DpVYjH-SM+Nb$R??l20&6pNaJ)OGQ$No^tRk
+!=OtGvQXlJ54tE0L+a-kWQJwQB+#`%oS(x{mYK`wne;g$%U)E=|8a?{qyv*x-nWsmv<ceFFN8(uIi=S
+cnj*gyzSeMCSi?r743U5hr-}iI#<<Zeuw#v@|TiX&~OpFo>&$p$*x6lyPoGPK2)_37r)i3DTD2g(Wtt
+bNRaI{QiRf#{yN}XnPxj)Z=SR;e%m~sElqRb0b)_eK|3?i`qs8Z=_ET;bs%v5qi{3~TrDG;doYy;W|^
+@xgzJ4Y~FKQvGr+ph?2UFO^3OTZmr?`WB4pjv9+nyQwdz2gYY0P`^mt3pc6Slu%H!!W#L*-T)4dS3aM
+1VQkWM-ft_wA8{5H>Kgi`Xk#Wcv0s9)km2LP!g}-Jfr6!Pygad83-#B8WiokR28+Uz?`L^A3&@DMh#6
+7J;6#SFZUC%yMn>+4FS`m+y;<Vd!o$qdLmS~4lNW^fm5Rvo53`~vqF|~V`xaM3{SuS<tvS0mk!i8bh|
+T|yS+gNP5n7~n7deOc%`bhWme6Il6vh`Y=)#Z&+}3&R0Vzq>Cj}6q)ELOy97qB_8ZiBp#JNt1ZJDVl(
+W1>V<6^pxu}S3#`C!Vqk_QZbHo~KZ<VJX6uy}V&;bHe0dxf%cX@fuunRlA86)x}6hF~|&F6$4Km}sq^
+r`)P9)<`G%r|OsqQ_siG8J-@Z!;zmfivPjs%t(+g3agO3(#-o2k2sOt%@30ghmjuD8K-tj^j~ios^83
+ioXiQpFnfakoC?`Kh<jn>`tG|Y=pUxnWpjkZ!g91u?WI2Xv7pSK_b#h0`c+l{q#vsLnCtHUysEIUrom
+LU88)xmd6Zk2Jo7ugwwIc=*f)VFl(ULj;w;k)qI2iCgKsb9yeN4`%V>U(oy59X*KG&TQda8x&&=i^K&
+E1YgO`ZS2?@3qNARv*+$h@d2E#+nO`deqh$&lYJU=ZQb|D@xI<f5wimgKX;EXR3A2q98|^T4MBI^6XG
+juO;P1YUT7v*<;XqU7!O+Fz4hCV69A;cn=&0vw^n6DaG!n`Fu#HW-nON*=<+MO3Xb6d#&10}fXy2pOt
+9z2WX6;0npd3qK{6xaTq5K8vA@~n8P>l3W44uUJ>ACpsx4(yZh_%Wv!a#YJBB-uF<L0}7#?}4_j0iSh
+DKiUrp%^BZ2SMtK(L>dfg93~5U6#TG5GE?jZIaS=#9S_G)I$V*uj($J^iccarWv<DG|TZE)eL?mR1G~
+@N0OE{qjg~TYljkS42yoFwLF3=RRL5$?7ljq?yi(dS!U_$OawpSXD|_#tL`nnYp{tK!|$$#9`*!RU<r
+Cq@e?OH=+LfBdri2`07RF{#EU=iK=6?%FulTZkkcEuaEo1}r_5)?eg=`;Y_0?K@DDQnOHv>Lb74a~lz
+;`=!V=gs>|pUOtF{ID?8;zr<_-*NEd}9;=>Rs=5SXBYq~exo;TXf%ygPFP`JNFnRTK?5uWXN2!6$qlm
+U2go`dRRA9T0yOBmQmT)z9O=9Rfh!cZ6Wb^)^E`;7x`Co#9K5Ie)_Nvdf)7a^wNjGr*?~<D4L>$Ql$b
+U^{dXGPT6qPno3PQ;-gTn6p+Ja-P6>NwTFsK-H*wnIUU9qlp~QDMgiU%OytiWRzsNNWeyee*i21zm``
+ZI29Tz%o@z+j>V8!)jJ`OAc;<8l1(?@n|X%vSx)l+Wb!OoQqapvhNnqNOB+Ym32`0B5SZ4&tF`)<=$b
+C_G+7FCP(hObFbP%w-C$H)rFIdme@yP?Le)E^8l|7q<f;*2h4%2=>3ym0>#&ZBlNu9Xk<r0-;iU^lLz
+{l2{0&r}1$wL{&&$LNJL1h^uVIFDzDd!jRUjWlSnQcgm$;}60gxTgbM4~*_GWctgLJfrVa(M}M3a`G6
+*criU}nXD<(GK{ZZ@td#wOcZO$2fnG7+rYe^^*f-sxD7EH_VFue*8L@|@jQp-I$4W)`Ed-`vq9PKIUV
+fPjC8JoN|StwK?wMFcs;WYd(AO~{Gp!R%yujoJXjJ!Dyz70!7ls}`gf*JYsq5_QC-iC_i|?xEMgOJiY
+7Fr3yJd0KMZrkK~WOCYnpYgP9!FRG(Tf%%P5e#xBLgd63hyWse5bXC_yHGBMc4XR_iz{KBU;AHu@NQ%
+cvRc%%E_{q1w`pvJ$LrdmakG5?<E+3NNCS`J0;dSNZVI=|!DX=7I3vC5nXBuly7VIwSatT_}OFuxM+C
+(Qt*e#rGwWXf(IgW3qj4?Dj5X62uy%K|elIF#<5o4SBwE$Ufbif$}!-fS!HCA?76Vk6nYZCxRmm@IC`
+v8czKk*fq(n|vvS@t27V>0Pt1PTWO|75vMWjXOP7dl-KkH4BK$MEe=9Pq-Rt-ZeRJxuxUNW{x_HV4+D
+74N)FHVMp%wcvd2E~32IW$>ao$8~7z`xn}EOd3g(QES3lBO`jg8N$5Q$s^6t3uF`w3vidpfJ>8W<b_Y
+xseAm%dS}y5#xe85=YKLEgPpHm-qUEb)M6ju2(&HG@aZDY)3&EdsM*-h<$*>W5E+fKFkp2u)$?P05Pt
+svRyA<C<GKOSmRHaKj2Af|ytUaVF`yTkIPi7XpdCm>K<Lh?yvWf)uqu?(ZQ@_?69j9D@&wJ|B2#OI#2
+q}+kbvkmb6K~4HM|jxr{O*9OYzy4zKzrd=eY#$plyY`e4GbkjNS>-;5G~(!3|ii@4ximdVrGxpxQ>tS
+ePV>6Lc4Q^vF)SkYJ5Rc?wEHXqj#nItLt;toCMSqJIh6)E^@J-Dz$OvC85KnROJPX$o#ZXKWocyo*GS
+aMiw&&^dNer>{Fw_hqZWhO#Sj^c+?kRtmQm&03*#(wTS`#;JZWRUb`yV7ieRI1RC<ph15rPPox@RaR|
+vY;1F-EV-m~9gn6_6mF&tR?iw5;!KY?oW?+wC0#Kgc93m9$<1fl$m0<)#v`3qqx@i{LUDrQRZ5Z0=~J
+#l$=qLFU-WfrF))!O7=Jb81BASd?jf1rVC3scLf~!V1)X5mGQTuU1J5hbc@Jbb^qnjRvQ4(Y{A7K{&6
+Y)x>K!c?cqKM6#yHHvX~av6Xd~>Z%(v?+lq+UUvzauW2nq)G<Qai5>+Es^sRlPfmNEIflz$craM5A4I
+X$<M;CzoT3;x?DzZ-CO|NlAC67?U&lGZJZ{B3=|6z6_B{Hz8W*gdrm_Zq;lEoL8JAjRqJy_>L`64uD6
+b>)DXn*CnwRbi{1)RBaMuGnMj0`BwmIzq3R5{O})H`t8XD*1cJ13s-2h8rgzeDNX${v8F=U?PHO*y=V
+(mY&edmJay=*y{yWrNK<>d$a4*QaR4_-|)uyaN6riqWdc5PSywOXy#U<G;uTT@veGWlDeY&dq1VHhQN
+~%y<ubo7hKsms=@e<h6=2lBos&dxPJhw_dMTb%yhj%NLi3UEOaAF%#gB1IHi$Burut)1Mm*y5j68Nh5
+y&JUG94X75?e%>sNy<hHJ!3i!r(Yt+X2#4TU>dg0sK&aU$9i49q2v^8JRw8~B*PzhKg7ez>a5{iD_L6
+;ZcQ>(O{{VQ#R!<$!AFtfTEfJk({X;Oy1gi<1{GPTvIG1%3UN2`+xbAX|U$6dLyH_#nW1-gB9x5Y>SK
+!5nYm*T-<AjLI9W$pT|+=|~ABt}t(yWUXn06&U6k-&O6j?J`v|!|WY)Jf{933Uo2*<Tl-=gSlU~QCqt
+OgPTZLC!s3P`9nUDs~=6U7rZ(BuXm?!FHWBgYet*#Jq#Bga%OjMPhxNgN{b)x<<3?IJUE^7SZ>P_b=Z
+fbq+N5B!M8j^JLskn(w*E_;-cJ=_T8z65FW5&fqRzR7rG9(IV<DYv@^Dd5_0M7eGju6FdBe(z!#3NW)
+>5+LnONyPqZDj^7ih?4?qvOu8LeTzZi972OA%nm{%Kozu9@9{t+|u1{^#4(?-}3Bp02|gegev=l7>qY
+I%)WZHizpM?#fWn$ugk-Nb~X;hlHR0pqd>H=}9^N{h=l9O9d*`fdXHIRr&cEd7xCR}TqYjAELK5!($!
+xoL;VvMohCB*qZ`>zzUjw;RAP)4Yr^?T}Zh9Z)rjptTzU(0Cj-%$jIg@iwPiUI}h=kMe`YunjJ7+m(I
+;T?`_<i`uFD=y9-+l$?3S37QH@^%1LVY$DjgYk})nR398csrqrFM2K$y2dwFr@gwniRA5PUn+w6Hy!V
+T)FYgflP$7pcnZg3E2E2D5CVa`CcZsd+;h8Wkx6u+fON}=2V+HEr_{q3ud}<Qk8iNN^?1NhcG3ZTEKs
+XQj?$_b(gf7LI2wlFKRHoY4<{)e`3O5Y4j<S2u9Qp|vp{Pk*aj7asXm(1?+FID!y=xJ+@qGBLjANU=j
+C4t7H8Oq1ZS8Ab44De^{?_CJRy6F66Y{(X^vg{t3*~TZ#T@8}^FRMEJ$v>1^}s%=#ursI*8K{NfN?u5
+mGlmz*k<wrAc~yaQ{B}smA!y07|u(g{ChG<J6C*cN|$1F%lC$&=MIw&nrz!JPL{Qsr&!ip$A6OTeVaj
+fr0>3?fIdxd*9!x(DR>77+EOa+ur-2qd-EPEf|&i&E{AiFhW*4wVs2WIPV#7YBbh=iB(s%~smU&3j?<
+SGn}$H5Hq;y9B|FWvg2=B8e>mze8JyvKRD(4o+J-R=TjfFC{s1%0tJ5D(-=G28B$Y{!QX%V1Tr0MCIN
+hYCJ?5)?=fK0Yo`@CrAe1*X%J(|UcUhAq6r2XTnM62hFzE~JhiRqtX~b5cA(?xYaDaBE`hI#&eGie*b
+K+=<YTtG|C{;&nPCF<%4aGa=6DyP!kc*(Rk#8z9`elQ+-;eu<*P4x!Ur1I>Im2Ki;G*N0uug{KfiTHX
++8i$F1C&*@+Vf$KeE|U}I`OLfo=vhYo0Q^@U{k@V=W=nsh6*>1VO|~<c#MJ&A9r#k?X#mjnJHtAjzw^
+;5Al3cQi{=8oHh$!R_aiGO9P$wsn&^5y{V-Eni>Isx9xaD;h7ngEfXDuO!&A*HFM4dlM;hzjmExr=p4
+lLb=)%tDi_QQ=V-AArCWmH)k02eH3uItFn9szW>ia9%-e%xnXqVB!ur_#_MS5+h7U;$J{;4l$9e9k{!
+?lxOi$cM|3^^foX4xCH2yD3nn-iiGL<FLhDYL(M2;+bY@`?TULHtx4x~8w$YD3X`2~6M2khR^n$mHgD
+QcXh1Z`_G5S1Zd$HI&{=dj9r_x{^UkQ+LYlJAh_%jyGRugXy;**U%?ExCs07ocU&*~YIzSU#c&I;0>{
+6cp~ZW`C_nZ&b&WBpRa`DI6u1=k;*K2p^j}ycJ3ioU9cWyB#o5g!C{8b$o^O%AL*4acBz4z^5GH$Q>#
++N%t8tp1}s~yL%wCIS6_XJ9p0(x`%uy(*k~!RF7^8%5byS^6;T!Z~n!YN1wE?@lBRx1Ap*N#;nEvci?
+$UX45NWckEZ@cqi&V1DaDWUr`Zrfnb_cwN05@VDmYvtNGjyY(g4F*XB6|2R*}BSP<92IQEEaM{+T<$C
+Z<M#!kU49XfI$nQdfSq@mAP(}B9h-a*`p-iTLb5PQ;c;WFrroywe1PS9nCM?<@?etOF|w3$jMA?wf!u
+pgS|!NAUEWRALTwo^X0(#eV&I%=gn?&D?dXM+boy35d(kG)g6t&kq`CsagkU@-w`PbKR)T;5j=kcqQb
+XVav*GHc95;ckC@vflL%Lvi9Hn%K{vss!*Ymav%0*iEjIb@qhxnc>PD=BHdRr5+pgMQAk#nRHe3hzq|
+U_?dD<QOKkmH%SXV9cr;`;8E?EbDY@$Xs{XkCF-Vh4LA_mZkIJ@$@#tv)NMvwf!Iq<g3sq~nGRShN7Z
+H)Acblhee?zE>d9;8;vp+q7^?728l98LDsa<K9~EWt0kqbA3km|4MZVCAJDqT8k2Ucy$O-ri3=v=ol2
+|p0HP0T_5cz-s)3om2_0^ak*zUc>HZN6*CT!7lJG*NXJP5`!4k0(l1>cKg4O+wvc3mna*;ci|cR;=m#
++2Hn7fn&rr5@?T%ElG>c-@hRk`ob48d^H@3*G}HvX^v*brj5k?kSjFWcP_m<JJj(M*@y<5FOqfYaAGX
+WB%x9E1N^UeTeges&xR_oC)vINiIKA?nVy*r1%sBpFL)=+i{Nm?bV|#*1^+FbVCMnE&y;x>J|j_($wt
+|$~Yc5Ajdt_cU})tvlDaQf~H=a<^niKW=Fr}SeLC#S&Vj9v`betSG+Wu)Y6^qL!eCZx4(BRYg@C1;su
+}oIJ83Okkm%iVp)*mzz^wKD&iehr&N9kv->Eq0Mo+TVXqw@9dN6dp<lY642@+IY}Qd?(h>)et>Z&_O<
+1$7$p$4gQ;JWLv}r?j4@{muB(BAte6BL791jQ}tgxbHp{S{Km3U#b)rj*3J$qn`%|}IsAaTpAQ^&;E4
+6@J_rl$B5EVE4Ujs$R#ar$nVYQGiwijryXSqb&kA|27RdUEw}^vP}dnN_j2O<<EgHMeVdqWU>_=s{Jf
+kHo<-?*;zGIl0YRK-x!6y?#N^ChE{oteRGVCY{5dpT+m$lO|<wi@{wb=YVlkUH{%AXBLg1&H6VGbwzL
+H?<AhYaiiK?hlYYn6bOBVg1c1|whD=mr`_ar1adL*Q-<wQW@K>ChAsB)SK>WKi_K{7Tccne75d(coS(
+Jp!_L~ZKK!)FK8RUs2t-X=F7M7Y>&Dxg!A>&IyVo%r>On7B<-+>9%rWs?)0z;3-djcBpWLQ3UMbSt8{
+!P^TpMzaYfC8Cz}J@0*IAQAz$+{{gK+Qh>54a4NS7K~2K>uW?BLy7Qd&L$-Gt&tG`ta@V_ffEvIAEM=
+$lVAaxZilNs|)@>Ak&-hb3#Xt^8w|4eRQ&$9aCeE$*K)c2Vw$iEpA%JJWL;Vu0DCk_?<@vmur=xYBvX
+?Sj}zyBl-`499;>uxIWP6YsRqF18Ciatdxndu~)^ugg8OU(it0j0_%G94E{hxFZCh@P<7J4wgN3<%^n
+xrw6LgZ@;erGrMsu+DmbGCC~>MSPgqKlg##*1%saGO12%1SeIG385j@6mYRDYUJjB<U-U!)x6PiJ8+3
+S6t_7>P!PCnRiu0s+Sc#MPXSoD=UZ_p+%+?8}3W8rOJ;!sB?b{yoIp+VBb&=-eg1V=aOy%;n&?o(1y5
++X0wS2Z<G2Y%G5m0P+l8=&+Kn8tLgZAM4aMZm_Dq>K_pi#gZsh3yX+WIp1pV9l1>0iE`{@dl>%@_R{M
+$^kj=GpjPdP?o-#(|p(=vS#+SI2<D*$=N?zd3z+^7iylNxe3o-FbBF-c1Jw@Gm&S^Z+^ZdcW3Voo^~J
+`lcH9%<b0mvkmR#3Y{i*3ilCKOM;sOy)PtA@(wJK{l(X$<XO6(QE@DA09I@_4XW#;m^Ifzo84gNe%_{
+Sk}cD1tnAGt)c{QU-XEAYewtQP$2`>FE-LAbu2Z74H10^>(mKF@3yJyfJTtnys~=IJ^J&{gXIoun;pK
+dtbLbqT)ewi)%fKc5SgyBZ7~F*EBVheU`u<G1SYjAKbIlZ1)aWZLoZNr5O4i#_AAVFHX$kGsA#@=PJ7
+?WX*j(m0TXCuXNVmqrknqCR;JZgGeeN^vd+S&M_?T4qG<aM<Bf$)6b|5gk%~zhw;wwn@ODPZdy(du`?
+}~}(@VC3aU~hNrFgnbi*;D5~OT~9in-(1yZ6VMEv}C)XyCWUFJ^eGSy1W=WHIj|z5qj#Dz39m%mWQ~@
+jb$8u@bxr88S%x8v?Z2MjaN)+F!ez2E@qp$w}D2fAbTRl1KJ|>?QrXb)KL9)K%5gKor0Xc_Pzlz$7PV
+kn_FDz9>De;tM+^^-^{8RTF5HWw+}XsoVkur-$i)ayQg{Z=k^vFMuYyZap3Fw@cKo4f8WGMt0%<w_Ve
+j3aJ_N=g)?Bvw%(7tQ83w+<~w-z-EWRjZkoxxq&sr%J~6z5xKwfjqWJnfUBY^Km$`Zk7!p}n{PGJBf&
+urC;r{?oO9KQH0000802@m7R`n|;v<M3T04*i}04D$d0B~t=FJEbHbY*gGVQepLWprU=VRT_HaBF8@a
+%FRGb#h~6b1rasts2{I+sO6ZUolWnlv>E#?yCS7O*ZSo=sFv8(*|f@&=fh6r=~dU3~8+#<llSFnLA0z
+X|{Su$l=Vn-^XI#N!2sHFGZ8@xz^>5Ux;|IE0yNTtu=DD6Yb8uO6{JWMYk0Vzt}3dXZ^8*P0W7!Q8o>
+)dLi2tyXm<qHx0K>y;Ljqv(WvD-Ig65TCsQKp4T6S4mbVM;jyy0FmOB3<;4?kYpERY?r~QruH~RAt|z
+;I`s%SnigU&PGYG}^yzR9+{P(bS?&#2q#-Dj7)xK=RGp~`*6|2ftwxXh?qJ^b%ke;~Gz>p^%Wy?x!9t
+!(4W>&NyCJ;c*f2%kN!xM7TJ^|AD;{)dnNKLl<miJ{{_T^7Xp<Msb>Y>A}+-#ZyORVL5w<{XaK046uz
+39sRp}=EBBdZe8p9ZoQx^e(&p}VF$()kr@oyh3@G=u|EnaHL%8157=Yx7*}Et3VAn*o+@N|2*Hm|ZaV
+y@8dtU|33Q1~NUr`cvDh<9i9X<FzNDWQ&Gi7UQG;G-@#)ZrZJUk6h845&p&U;sPCmD|Y2PB;WD=XIje
+&GK->sT^ChTYRv)(S+Mrynn2>-H3RJQ1}Yw+*PW6>XI>qwoA#FPr8+w08z_s#;>NAKSMo{JKwSS&_9R
+NpoD>;KQ8SWa32GxZE!8o<ATS>ugl1)<CEJ%>bgJf+tkK0Iv+N}UFJw-q;S+`fo;$J(;F@n)0s0qxQD
+mAo+m#2tcA?-Cu(@KJW6$;7iW%*D=`7jhpULPAzxYEixwj8cg?k+B2#{b;cnO3(l-h%_#HDyQQZ@mv;
+{Bjn+5+5<$OuruAkIUD{{v7kknj>=Nuhs22zNQDgJ(;Bz{nmVfWQxL=`%$I3^qIk{EEFEc4+xv9~>zy
+hXz6b?LLV9ftIBbVAV`+=?#r0PpK;fc;GnVWXT@<Z5M_NZ$QBiVfFJ^L0{JFGyj58{Y<Zfd67U}&Py2
+M7uU0Lb~y;`>u#dPB%$O-!J9gQl_y$6xXXwDk6h?lsINDjYj80>1Ezr}bP5n=&3O(!-33r;XbW8_(e)
+OHc?o`Gz-mZQC;h5}Fyq5b92m24khLLf#<?LO^y`sqlar_184rS+;(vy#zYrZDq6b-fY?PuvQcz|<D9
+oxxBTD-k_!`q2kRf~oK&b4wT;a|xlRDSDvuZXT^JWlD4FMA~feW)tZvG7iS0<QZro)ivbeXgD0Wxa9h
+$#y(t~_oRk^mo`&LM@0K677#b4L*_6=+ONHie&X@RoxY?7^<dp)0A7=|sDhpD23cPi#HB9I6|Q5h7b)
+1#u}LH7=HEaG|}RjtQ+Xrs;_}N$}r-FlfW_)1U4_!~+jXQG=CmQ;JNe#WhRr*Hep`|Nlg_Rqf((K|CZ
+@XpJ4oh;-N~iOL`dR~}hNnpf^&IgSPh2M;V?a-XEIDk=$i97^R7!qKTFHt6@QO`;Av5K4$LA(%vrM4w
+)8Pmc~O6p+y8MEHx_pFX^P`})J{#d=CuK>cMb=a+SyCNNh6Upd}Z$!D*NaY>dX<gdJFmg)IK$MH+p_U
++oGoN59iJ+5u-I?5`iRWK<?s5T&2In+zG|I3zGVLWfst@uNCGqzly=tFg%J=@&2oSZqYb}zROEEnG|R
+_ur6r^_Gi)+d_=LWqZ^2=Rx72t{wGI-a*VQigdro8Jxb(BSV&)tmUTU3_-Te))beJr?ZHmT6XY`J1x-
+m*}qHai&Z&6;|BzWk&eUDy<Mr`r*@3FfGkaVwlu$z>cZCpe$x3^sa^kW?M6;&mtawuV;-|`ZoVcft>T
+Q|IxePYzH~z=v~X<pelzP$W1KfOS4eZc=Aqx7A=@m)9||ZY9zjmzdF~!n>tpNhaz=4uw-{?J*%7uY?O
+B47y)#<PM%G6oypr)R9Fm7TC8M{ka-QCmLa&|@6Zvli!ff+(dI}eXpRvOrNurpTFh^{^k-?!7hTYAcc
+x#jA)_)32DiS1#CALa*SW@?Jd-U@C<|8h1{w!(^{|I)?Cr|-2yUS`2|NesQo9!c+i>t)Xx^37otf6*C
+__}xfe$^7YY5AR^On^TJGUNZ0~jnz*og09AJvJc`d1W57KylUOyp@qwqfhFV}{zsS%^{dG}Vxw&XKVP
+&7@Pji49DKdNIjy1UYGXc9s_~&P<f1y=OcIj8WR9sMQqO<TBG<q3qUvHg&quj6kMCj$UOX{}=-_2*Id
+}sBw%e+)Z&uu0(CK$wU##Nng7#K=mR*OIe%B=98=?gA!YGdk*4wh7NFwWzybU0z{Vs_qdirTa(pgX`H
+l$rHg0=^mHr`)8USQ!=ycKz&e@VMos@TFBy0vU2&W$79EZi#~Q+EM>_kAl!ZP_gT)m?5Q6J4#`4S=;Q
+O-6mN{VC>ue-EgkpM<hz<l~Va}g&8icBFWrm$rml2R9-a+(&V))`}rl2y`77bN>ZqH2zzqGKg=-;qNT
+wl?@kp+foQS7@WNHV!3$#2d7fgPM}y5}`1RZq3LMsuJ!TO9Ni$AU|<`@}+*_X(#T6bJ`n@qJ=!%X@1T
+23tN$kHCOI8K<q{Sho6#N^PVuFC6Q5q4_$K(<g`C|Lw1rH}9^035O;LBN}s<ip2+p1llBJO#C+md%j*
+F8!(p_kmIP#Fb%oC&d8F}sWDC&pN9wfR_EZD%Y^(;suoUVi+3`flLBApSAWop)fo2jlmsJN*m9^>%&i
+_)bkQYWehr`A(__@_MEi4m&Q6XR;+<6^HBO{Q>4bN@t$AAsKbr-Gs#33`TSCeuKw7p;16Xuh7ey~DTP
++AIiDGkR)(d55TFllJ(~=!H(`5@`<#{yAHhX{o$Y0OA)x6Kl5=1_{+|Y*1I6vF(XVR^`e$)=sNHDJEE
+6nGa@cm+~N(ZAWCV!)qjc&M3PiYT&Jfr<6)gu_!ue?7wp*^6e4*JXh!rm$1^uZ4qB6_CP7u3)x83#i~
+0lIi`(t&=U&7^}K*P-6`GxNJ|q$7xfiVYptONB3(T;!aqlg0y<Q68rL*=JwSM`D>K(Istk)SeO%nwP4
+2NXVGIKJYR*Ll9(;YthzpF&Jg5ec4wJrUT&Y{vP4p-y_lZ&VxMjFxaGfL_?apZTt?JpYIaD(8D}IFhX
+mefwp434D&!Ffp%>8L-`~?a&il_q}swfnFwNee?Ole(>4L@dD;M^xn`m(Qa-RWGJxeI`H-`Y@m-B5m?
+jZxl5`I;TBA<cTfl_rZ`J-Q_A4oDTCPA}+DQ3mOaO|fo!MiZ6y(tdDcgaNvFADCoD|D+RW#S=g*zZa-
+pw{8tC9nF2iE)>Zqg+Fbw<;$D0;X!92?UsHgu5B_?U?mG|e^EC3ugsMMs!OqTH3D%_B%;=zFny=%HQi
+AlZ?n@O+o!RH|i1Ik>3-xRv?C5I}qo6_mgdinEw1Z3!8=ygPz&pLioXB8u>iH(0pX+#d*A1WOGqmJ-y
+*53QrX;zhO`DPTU3H~C&ZaofP9V}eLN&PlgIfsQ>?mt4UwQOvB9-OyO^o&aRnfn)R+3P|H)D<Q9x8wv
+HU=#3%*m72(mCn2JG1bPP}9gH<Y1rb1Rho(6O(zt;F30xvTu}1>snW4oi_7OE+w}0&E8WdSB+oS958I
+DTCR>0fJkPoQAlUWP8QX@#F&r2he9R&O++ifGNKCMGs4sbS`&6c~Tuhm=;{MF;Nmz?y!P)h>@6aWAK2
+ml*O_Evy0b3{%6003(M001li003}la4%nJZggdGZeeUMZDn*}WMOn+FKKOXZ*p{OX<{#5UukY>bYEXC
+aCu8B%Fk8Mi%-ccE-6;X%q_?-Dp7C&a*8sON=q{H^SII=3R3gR;PS3{Wtm0!dAX^1C0tzb@rgM(@$m|
+_3eif)8kKYul#moE#c}}vP)h>@6aWAK2ml*O_Ev$8*Y#Ng003GC001ih003}la4%nJZggdGZeeUMZDn
+*}WMOn+FKKOXZ*p{OX<{#5V{dJ6VRSBVd5u*~kJ~m7z57=TbXj?!3N3nDAVD|%N>L=;L(?9L!X8WGHM
+<lkkhHx@kpJE{lx%C84H{o8k>Z;-Z{7?|*ZYvj<UeaRbtj2iPQ2I#-%%QR<L;+zx^+WEzxBy@$F`!o;
+FE7Wo*Is6u~;;gW29HyzL`MEKiKZ&#}Is2-Yf{eR<^WS8E4XJRYtMfidqxX%`*(@AFvV3X0P!ox~?b)
+NAGS3%S-y|CB5}dMp*qRTCHI8B4a+?7|&vBd|1rb0B$0aQSo{K4U+c3(Y8QVbYe!v(T8)mk5qn`h4{E
+EW>Q4C<FqSJQcWrpMR800v_@&ii4Gi$-$&~4Ir+^$(xga@cUvF2dSv_i&P0+&gp9P2hWAmPk&Up7eGi
+!RTG4b<NvzkzuFXj6^?TEAjg@Jm(j7VqIgyqaak~y;Z9tzuKy4tjGY)~vcMj#C)+31XqsT`e9&p-Pip
+Dka2|R&!@*e2N4CnWOEYKvNHfi54=Lw#Wp*A}lL#jx6hisEMNJa1id1nU|C$VvW2DAG(%Gd{q;znAiQ
+kEgt0-)FViz&<N`c#QA_ID^pFCh(QV>s^QbFN?mW#0PqOV?ZJ5K!9e@^bk(w4MV#yWkZkZxmk$yHJ#S
+Noby}Us>O<_C?wLZ|mf6r>_0$6!!146Mr(OecH)rJqWJP?F`^5UYy^W0B8CzOeK4L`~9ysW8s2W1C?Q
+pPYD5{59Yv0&9UkyH>NR!)S7dKV|ZvDdh)x1V)>z>=%2H^(N+n{O!=Q|DUZE}o|?`%6fv0WH`X*Yy@H
+c^(_iV~Rz|l2$=f!!gL)8OHx@puG9ZG(J*_H~9Zh`jrllPpbV%Yo$T1iMQL}gKhRK>Wy@ngMdkfbBpk
+X)iv!*jnHOY9<cL3+%V$9h9Lg6)svaP7d`W00ke{*A~aI5UvFB+*&ZH;(8OM0&Mu(D30+z;nQ)jI0Jy
+o^~q?MyzfvAnUOEqFJi9m@A@{ms{e-nYm%)buAR5hQ~p4q&ee$|E<)4!M)ZMt?K(!(}2oIDgDqJ(Wm#
+V6f{YROTy66Ij-|JkEh_K5a0ZVqy%aQn#vnjr_Oy=9ibkoGzUgg>eVAW_AgnJ;Oj(igi^i=f%pA{{>J
+>0|XQR000O88%p+8BE&_;v<UzJ^&bELDgXcgaA|NaUukZ1WpZv|Y%gtPbYWy+bYU-PZE$aLbZlv2FJE
+M7b98eqaCya9ZExH*68`RALC7B>;nqrXFTiyHAI`0lLs29#dhQiC!;oo-^0JXcMdZd_8~*Q|8Hy4qY1
+avGz~w`{qR8RA&od)gx2iKt)Ld3+Ewtu$;z-&>`=^q(@WSwd8}8mH?S8e~Y+#3be3We|D{)kIs%B=_%
+I2;o!{Q?b|9(_eC2}KGv!ds7nH&4-CnGw3TM6&UsLnpU=Pi=54<B1R&MW)$Z}E96n!G=ja}DH@Bg;T5
++cf(knnHDH%kxkC4v3^3oRFQUMPsyM?w4`x(9x}t)o|v6>S|ueM^Sv>wOGO3jcR00OIZU;hbVm!odzk
+`pvF!M#<l&C^>2MKWCI!jsZ;Tg3(~;A$WP4|xU~3fBSf`gzczZ?;<~UaOEjE4(_0SL1_t^8R?ek1oxI
+(SX2R9Cjp=q53Wzw<jl2G18SZV@l<ETf!aiBHz$OcPkUrB|>fABWIHhLjS^Linnsf&>FGVIEOvm>hGN
+Nv?LU!)VB|M*l*>iBT-Tq_uC_!MU?B43S6TGm$GpEvw{NEBwvs~36hdYZ}B*m~hVSo{Bte+em<rUZ3s
+>)YuJP*Otf1j*L#ZeTUHSFf*h21wd#4sb?I3vE(BcgCtnT^`sZI+23&l5sCM=#W{zYlrZbaP{EE^TC0
+6j0odqibfAVo}8(cM&U9hpK+1StCTDS$r=reqI^&Nr;x2jbQ(k?K@N@(%bN+s0353Xy_=u2g+bNR>@K
+rS;NbcmJ5$hrfz=+<0ie3mm4`_OF+KssvRjt`*fY~K(KcZ25zBn3lXbDZP&Dcqbmj+B7cyygti(s8*W
+l(AIm`@N|u3pNt0zZ-0+_kRk<3TP?>t|Qr=acVAG3jCoYth57vQhcW}@3cuGRdWtGZFsx@0aMY|Jr@(
+;*ejaUZ^q~y4oomvLMcL8<S5<FYc{z)zjTHB~%kQMci^$s%1n^$^d{IOiSs*(04A75g0tQi<|TpDE@m
+Pw*$7Cg~9)D9SO#WLXD3*q>&T+uDbuoqQ_Y8d&&e{n-Oeo?RVF4b)%O&q<BR_sl3b@JvqNdgM!x403Q
+0ijd;Spm0kxJ#DIQZu|W`d$L{GJ10SKfjK~?Mdh|!17Z-suLBmyWX3nNceJF(Y86W?#;?kLe5D$!`A0
+z|05kQDavhF4Hg-%?S$EO4LV0m@~lFd$rwQrvNIfwDQ=jR(bXLC1qU9MgXenmi(~e&f#By=rS6F=Tm>
+b?Y&uGYm=5N7ARUD+_s9uO7?V;H)R`Av>xqR(WV|@`HhDVX66!O?#0O>Gsclod?K;)d9u-0cHc<R}l^
+~TNbVwr(GhM-gCqESQkRy`x)aQ6vhq1dNxgO42V8VVDJ7RKCRLnd3Z$}Z}cB(mr$W<ZYXlu%ozk6Qa-
+|{OUEqH%UyXZbdPa>pe3-{?l4g>tqA=dME3!(z~FS7KA19XSM1u!a}i0Jd0J&9*D?vvBRGpRiar6&7L
+5m`((%{(8aAD}>h0;ZU(FZ*9pO|TrU7m$29$9Uw?VHp|R#vzxW;y{i9FkgJd{=GE^*+YxNpUIoUC1<*
+K$_gErF1}Q#h6s<bLX81GhSAgz>zDH%2FpMx3G9MQ9yUzMO+3kh6Q{v+iL@r!a`M=_d-9S7g7N_16>u
+;#NqZ{yu-WZfTT~K4nS~PGb_!uxHhJ}ehL735L__$BA&y7$0HS1gIfpn5ay4FTA=!N=@c_KUHRf0ybN
+J8`Ol%g!anLBlpJY><M(#4G_ji@L1y|c;HE#e<7N?ipRwOBPFpfkr*BjN;(~*PMEPDU;^6dQV@+?~3o
+su{isX3nMKk;<+BlL%++vdi4T8nKPl{P}KfV%IY?&VN8ASo@Cwy*ckkU{5Yd);(t`-*bIi{5Dw8^tF5
+T=%^t3v1ne7n&6u#8-VE#PtAF6D%cwOM|VRQf5dq4REf5ls%W}Ja+pU=3ws+yy%hdLJhMe#BcHAkZg}
+%ZO<X5cT8)~-Wz5`3Sg%#Ya2Mi0i{?LSl{|W`HK#i8UIfwDQOu=OqArj0FnfBQ)V}~fZIVB=Mbm?RJK
+$?p!W+akjHlbOZqj$a0_%MsdUC>u=)SY>j5UGweedxofX?}Wj7r1#6I^^+KC5qvtVkHQP6!g|ImY9Lc
+b3A52)B2h|O5vsW0~X)QBAo6zupwvwE9vSjnO9$3X-{2EuP2C#L?T|1(p=ef5gzZCT0(NJ2_eeX(t)g
+Z@)r4Le)pz#eauLF^hwDXQ}X4?!7=QgL@@AChlyJyE;f_r&(T-(BzXyJ191794FBj#9_F$waOlIb{8W
+0W=Rb#3R6*r>W_rHnxh|!*xH69ob!&e6FW=1cO|U88`X$`&n(<@xA@*ty0zO0*|EE|9Oq4CNq=Gg4UV
+N&}1{yc_&+|FFlGkw9jD#9kVkw9CayVaAIEF^POf<2}==+dk+)oUCO|#uyv{va9`z-lQ^-1qyEV5m8J
+~Jg82A&$#{UySPZ*~xJS+(M8Z|lpq&BffWilq$eW!fgB4!~4LvcgNxCK%OHs87SXqpe5dni+<{McR;~
+XH2(BA==Q4)-LW}+l@^Nk7VofJTasHJvn?5sNN{})^cG(1x40pk!^d!5Kvj61ZPunrC?rr~EPO}tXz=
+Y@=b>eLr+D{&Qmfe74k4pPC3#=Xn}VE`RWb1h9Ng`RxSNDl;;&zDz=1{{k6<&oduLt6UY{`HxChXv<i
+2k5q8e@Wkb_ovkY|2TW70B2}+LEkyVd-sCtVFGRGx#7XC6{#&zkiU$|RfU$?f)8|N+W^eRIT!lAEnJP
+dr~asxT6@#pW7uPGa1M|g-A&UJo81eV(_>eeS6eD}kZchs0|`vKE#Fm&7jcrZ-$L%-T4lSl$>f~~<GL
+NvQw{+uVIKud^qNCHS024BbTJj%wqR1hYYK26+o><M$8(~mEN)4~uXFqN`1`+p|F=Ic6asDHMU$<37j
+R~o%pfzoSQda*=)2RB*M=FizcuVF#}8LA{hv_Mpr1q17?1_(8Z;C~7xrp>@)kEj-MzZ@C&QD3FIv$Qq
+RC~S=2w<JbnN5zSmG7u-bpBe_i6Ncl0qJ^=XW1qukceY5?NuuT_dThr-<%})`67CvlWpF1o3elB+O2H
+&afij$GyD@=-JXISd6Xw(@gvsSn#-yN4oQwJ7j%$oz}ejB)WO$XLB#?2q%VBf7D7r(J)d;1vE@sh`e}
+ILliwH-$We>R=h;A*S~d^{sFb+>~ipyKLAim0|XQR000O88%p+8Y)E<&7YP6W3mpIeDF6TfaA|NaUuk
+Z1WpZv|Y%gtPbYWy+bYU-PZE$aLbZlv2FJEPDc5^OpdA(U%Z`{Tee&1g)-5@YGSj|K8=0ZgpR7MTBP7
+oV#5kVkk$>Hu)Tn@__O5Ozh@BPjhUWOMbG7?mPWiEH-JNK*1xwefLMO$Uw+R|-IcoF_9%|V{ESGn@4|
+E9FZqp6PlM>|}pl|SJ^|IuBBZ+<a#VM-l+3{RV)v1j2gHSju$;;q+>^0wKFcgFd>_@Va3R;t{K5Bfi?
+t};ze_~K(*12RC=rk3f0u5#PRT4nc&IFzk7rR#Cu+vcoF^NY^kt1~b%RoTj9{3@;RDuyx@xB$^XczIA
+x_fX&C`R`z^F^86z+w+^7>cKR&I_t`>BH3J*PClNrE_<L)^kMBVb1rjTH#$>9qQB9<()rWZNY&7(9z_
+52kDHr!>CL}B-n{?t_J{YKpfb(u88#cG%KzC(8wC0h_S}o3_Gu1bSx4ccsS2BxHgML1(V2l_tewq<JV
+rO-x_2E3kazqpNf|axcbm;7*M$JAy?1G8?sdwlN_sl41t53g>aXGeKYhIs_%Vg3EO}%&BH;k;(fCs`l
+Xw@7(@&#)+f?F>DxHootdr!w(l}DzK=lPT*@(feDcwyQEzinlr=-Uu-ytza)aPKk7hTMNp|pD(uR~c`
+shksOtmrqU%5@Wvx7%&_D7+2&(ISt|I=SI<A5U7Gm8nGCHnoL|+d}x0aU$U30r$`PY!M}*ux*u3VO|L
+m%<YA<jAyIzf?rc&1QVpvIY1hrRdx~~PBjBa@i#J~C-QJ<ks(+Z4@|Vc4?HCYxPD7<=n2vRvgV}q%87
+$MsRv`5-Cig#NruTSr4<he9fdc+A?QVIJwnu|5}XD&HRHAdE00heg__PO<#28zRoDmJG$zL##ygqgX?
+l=kHw9BgZYl94I3;c})##!vJH6i^S^1WEcm#T559&bAs`9LHb<a}5B+eX4P4Ar63%-IMR?Y*7UBf|RK
+rBm%L<+S)JP;LyR!~2}R~1MV0;gr~CV`(fWZIv!YfFzf<<xq+ECF(w_4?F&+h>cryMV@#j5J|<nkG({
+1;_1s=w|eLdM#6SDb4}zHKq02X_~$RGca?qi*O70bqd}}M&65Mg6K=gZ6wv*NV$uRsUwrs)tE_0G5z_
+k#D{zMBxNS9Q<Y-}5FGMSd@y8pHTd)N`_B9km?|ID#fb+<nTsTE*|?I_3yxq}FmB-S+Gi5ZY>-qXae7
+5rSHNqUO9bXlwk?CZAK-D8X*UQnRrP+Mr;^Iyws|hyMj2{MN)h3YR@_(iQRvSq^W?dR15Lh6=9xv*p5
+7xoS<*s-At)OW62Vb?IS!r!=Z`&euT@SNA#cxhAIc?g31-DP2RKSGM4!m4oSWD^A<Eacz1Vj%xhJI#&
+bTOl38C#KcVM9@2rE!MvYU4pLq%P=uRmwHp44LsYQ4k^byYs9rh<BsEx9Qx>T4%Dzxvv3_fsMELd!-g
+M`dIV2><b>YW3ucYKX{QfJN(+^wLcsxj;@Y!y?PTe;FT(ds5|jG9xf$;9_(cynm*IF`baR{&pgncYI%
+%O*X@6s<&KAs1hM!HM$i_$V2E~_QKNVpWpr{RFj>|gO)L^g_F-Di!?ms$tPkO=9yh}vm8B~>@!I^>S&
+q#;Td#&>dWYAUV?|a6JF3bHPlEitr?pkSy8}#1${TQH}YL|uYb4Mf1>mh>s=p@R|GAnTXWopbj{qtIm
+qgI%`duye$cT`{6$#0@MzGia3>UCxw4$7p~ijVBG)L<C^&IKejb}7^h13kMZOc7e{(RU@fXPq6sAGaL
+~LK_bM4161DSNk^e7{90R<p6sla;DXlKg@Dn3U=Mwnc9HS$N{jRTaa1`){{8%<5jgWk!Bm0j0(Dgwl>
+V7-yM-U9HLq0L;68D{gkA5<lIZPZjpaY6O88wZf8o8<Xw$m%?qlIvQy1`k@f2V_1cU0W39v-s1s*vei
+(+ZX0R8gM!oTk9&>kqL^G>Hw=bNSn}uBz4v}OT6~>ES43(tA@%GEP<Pq{_GRJKDicvAqzdAMcHmw(!P
+(NUMN_1Axa5gn(MRtH(GgmNJh}zl;{_v!x^33lD(H^8e(bDn!=tAJp%j9@5wOB#m4<Hr4VbIY@F?x<R
+rapRuC5ZjQ;u*6OL5sqslHL274O@S%-o}5)E3T!^Xc}7=b%f?!5d;;t#IDXCx1P!^qBouw606ll~H$o
+!xn%iX;$XGpz#$O9!Fl!r)KZ78CjZ%eE28Ki0B~HZ@%2Ma{6Glf#p4R#Iixs*cBhHuYP6x@j8Q{ASji
+m@ZasPjgi8%z!U8+yMQDba@2yOml~#h;b;)^%%V!S3nC!znPfh8*#v}2+K?HiAI`xJ<k3E+OX;iHQQO
+5qNr`u<L;o*XG>!hsLUwDFd(F>>_TCOa$BO>f3Kl^&E<68!H2#hv;g{SJoO*r{&CC)Vc1~nIg5_|K{t
++zG$z0bLidAO0R~A*;dnj{2Bp1mk2F^aF@d&)k^PBwQI98!rlop?o`i=+zh2dmRL1SyBuA~e42Mos65
+@2d+6z3li2D)(<ks;9@4I2=F3YA(GnJima#o)mhM8+>q<1tJe}cZ}3#xwRwot4LYg4iqQA#75B`eK3Q
+0`{Sm~o|?L`z8;5U-2vJF9ZCD4?nT`n8ArFPUq+DYyIRZe6NO(;obKixHGIY_!uOyGA>bVPzHHJ%TIf
+>U#U<Z{@e$`*GVDZP=69#(npC%+&GXDb#4*ErmZGtZ9ILg2BQXB6NsdA^nbNBfFk#KG48F)s{ZVO2=3
+;ZWh~JoJ-s#IO*;gT=Jd31VInX59XskiLeBB&y$7Q22oZ=x>crDzGR5F22xu)tFXg%??q)Vtfa5k_SV
+U6QW=&FT+qc+0T-YpkMqkg?os1<)13~r;hAP|J+=r*t`izLqeGLgz6v$s+=7jx74QJs+l4JOCF56NXq
+(n<Z}imx5qa<A3#9Ld+m+e3Upx(^GDHaVVPiF%%=J&$k^j6AhKmVDG5D(P;~hI&l|2fXVCGeefnu`39
+QIG$LTYUzHC+ZR+?z+6PK-T=$ZqpLP)h>@6aWAK2ml*O_EvkzDE>PD002J#001BW003}la4%nJZggdG
+ZeeUMZEs{{Y;!MPUukY>bYEXCaCuWwQgT!%NKDR7OixuP$w(|wNY2kINzBYER>;jyNzEyS2o|Ll6r~o
+Y=9MS_ab`(oYOx-dl9Cb^08mQ<1QY-O00;mZO7>P2FrZI)0RRBr0{{Ra0001RX>c!JX>N37a&BR4FKu
+sRWo&aVV_|M&X=Gt^WiD`ewNkro!!Qio{S~Yx8*udjL7kzUiav&}MIi_=9SD&nK~jPSLH@mz<426R=u
+{0dZSu%Fo*QplaLRFUKvP@Ko!so?R+%k7pbyF#P_45*f|EWV$Z!cnpUtvn?4V3UZ=~j}tx*TAmDvsGS
+BjTP_fb*h1u)dU;PFugte<R4v+zxQE1HvSv<v~BO^8x!8EN>FG_|T_#C!=-tTLd(82doyF`$V7Bsd!>
+Qc?rk40r~O^`Nd=bAn|ZUWlM=3_?H!pUlV>SqZF{pTZ=QeO-!cYzUx?ibCW8byGq@tRO^RLJ#WS5^mK
+krhxl3yjz18#_1$1Pf(hg9`nRtO*J<o@1MoIy7Qsx=4Df6@6hK3AK8wXbar^G@{vP1n_5m?i*kk{_0-
+I4MQ2sDXw`%$u2<&CqJCxFHfTfBGCan;H^3g2%|G4wa|zR3tQjXiTN&q~COx;G2W_{Rr1KZjMDkD0i4
+crG8VnY}=?pT`UHm84A5cpJ1QY-O00;mZO7>PesT-E42LJ#Q8vp<z0001RX>c!JX>N37a&BR4FKusRW
+o&aVWNC6`V{~72a%?Ved9@i`Z`(HT-M@m<2F%(NqkS1L1Kw(^*-&8ZhQQ5$xt_{MRLn(|G?H@a1^Ms0
+BSngo?4&I+Kcv+0c;8=SqbMT3pZ`w2d;W|>Q8eMZrWT6)E$hmz1+%MGlqJ8KHB?A8DMY;^>d^4&nsoc
+i>X49^JW~mIrI?^sB}>R}jpB7h%Y>{B4Ksf)sYuA%3gDATn$ogNQ?elI34veqk_(opx1x-a0pOCBJf}
+$RT!>nD`>(2^wx3IpZTX)0pvz2lpPR{K1*|$DrqL>jCzF@2F3x{irEf2OO<$j{mM@p9W%_3M`Wz6WTr
+*EW^%)u^nw-D6OfQ!g=>={JHp}W=!%H?5(O>VrdUv;8p8ZMB{(W}#{aL#C_TBw-eheD__!TmqWF?i7o
+KkRl{vl)9eDPc>(f~G`%2`3uYo?|en9sG%*HVE|!3CRyun!FoWO)kyVRNnRdIj(sc9;{52P9})s=0Fy
+?1MgU>WWQba`uA{H@qP_eqoC2Y1uNOou30&#1RKVtDNka;Kjl5#@Jvpj43?L3uI2JS`l7>$Qp=0!Bi_
+MD~|>n77LQE;mF1w*GDC<q@q>ErW$FWY3z}uT(Z-Kb$D8{yD!8&*-}Z`Dv+KOwIFx*Wa^-I_i;1>=#H
+w8hLc+xc_3GS8BfAhX8?WJ^KB~FKP`x#|DR4?%>#q$n92u~JB2!0v2}+z!=<M7(RMGQJD_$?cCA!k@j
+WBdP>N0)gMFZxDi0~}N$X<DA(7?W6_~ZtEy5H>D@2=()~*K_`SeMwGq}*c)eDG6vjbWgfYiZ;iiOdqI
+e%V=?YNX!DS;-b3qnneN|7YkmWyt+&!k>OgCGG3N>&-&WAX!e{<&h*f)TZ))#nNV1&E2x6zgXj-&Vc@
+?Y{M4!AtO0S^?Vhn{RGzskjCoLL6&Hg^}&b&1-tYbdiC8%*r-L`ynF}9@5p8j_2LYob0t*Z$N%@tKl=
+_itXey)=}#VeD4Zy*B=b$itaEOqTU2115pnEaFwRLRV6En#C^dLlX?yU-C+kOcs_t*b~A}NCfFXzT3v
+Zr3Ya!e%?WL#Fwv0l4EO;a{0+fl;<{B0f#D%1Dd4)bQT>Is(vGQZo%goD9+0AYrdcTytWZvY(4m{Kp}
+20m>9qmZ<l|!EIoAc42LrZYc!MDpVeN!sro}*KMsX5gJ0(w@aR|ecV^c0{=`<(D2tJ9}3n*0^6QT=F=
+7OhlkVzxuZBRTa?ujrtWuP!X0!_LM@`kQ3i~Iuf37G`lc>7RBSR5vgh8^NRnnGU!Pt{Q&SFFI=h+lA=
+!-xTO(tINt*qq$*vLr<-04_*VH*HB3>&}O{)X`j=-0Zfx^lC)iKvg|B>)>7=5`h&)5us_O9yMIfjL2h
+xi7B1~(;hL7-{Nh-3^VgfvTRj-<_uxY1&ZUSr)ttR*MjB@m$+H6TViG>Lg6I*%QKk$53>Q;KcMQ@)z^
+w#(d;IqU$SeO9gJ6yiJn6Z(~yc1hfrD@FewIRVwQI9(f`h5Q*t$p7EwZ;$H7^q$8d6qXu7M8Nq<Tgw!
+b3c)gBRpE^Ok%*lAAgv}`b+Mk5lTjNmUn^p4h2{Dtv(=S(v9OmZJ;U-F_iogLvlI*&2&zMzOShiUxKf
+wg0`>9WKK6(&*IWl=XNBK(QFlz)wUicW<B584ERpfPj->^5_KgN_U|il3}qXbGI99b3=#!IgAe%k6mh
+33Z(1T;Z5LCs%b{0+F9-DIb|?>>0qe%m2m0_TAtqylVv=&l0FNc+(<8?kcs=rg%E{IuSx6!aR&ZqigM
+b2n?$qU)ElXC)VYOorX8#_lfyO`@IF^aN@<lfooeQLJybim3d>Sp=5u?3=EtA5B`Q=eUn>guHlBy4~v
+uc>3Kr1T@3{p`qb70SjALXXI&39A6h{z7W^B;Q1l|Qb+SV}7E5NUHyPZlQhedD^uevE1A?dqYWviSuu
+lQku*-OFCC(tuw_ydw*BggpE)|gN*IY#-G*6x(O8hZOf|&gS+6-D;ww*efA4MU61|~W+O+g}3{hR?o(
+x+D7Gq_4(9NluY)hf=B-fb;%(op>biqQbtS0w}0Ile^c77Z{w)0ewy&qZDBScNZTf@20sxHJ>lu#6WR
+@F6C;2iF91)6jbV9!&ZEy_YO{+{vgkw{!yA<n6_;Ghbr2Zd?wy=UGe(6DT%GdY2p1*~WY_)RF4UtYa@
+*kFshj!z}Qhp&+v@!->mKO0=+WP;I*<+(E>lTNi>}qwR)oWS-wqfId(6X3k>0TaQ$TzCq|uTV!qJJ=#
+^qO(iVF=7FhysvebQw-wq1q(61tgstI4(=Seg*}>l$9>X+V4ByR0GuQg)Q0ldWnb%qevq^BPiwErOuW
+Kj|kZ}XWDH2_|dVqv`r8!1o6F`n%!9StrVi7)l0Y}$%_v*ghJmAk!H%g91y<GRD*-phh#ElH2M1hl!#
+W((khKX<4_p*nA8gRXA!sD~Drn#KTIJBsye7w|lr1asu-8FKMl^{$lR0_8{xmbyod4#!4p@h&fwZl!%
+0;jAIkK-+{3(I)W_S~rXA5cpJ1QY-O00;mZO7>P_=#67&0{{Tn2><{l0001RX>c!JX>N37a&BR4FKus
+RWo&aVW^ZzBVRT<(Z*FvQZ)`4bd977TZ`?KzzVEM?vKK9)RgtRz7X^YE?WH;7(1T$Rv^48wO_2&odE*
+%V?;TPvQr<W~5FHlF;mkMRJbARH1OL=ZeGjthjrDMC%~#Z)(3kMB_tI#gN}%IzcMQtC>?{6=x;3`yMe
+`u;$+jB2RBlFSgf?0>LdmblwdgQ4mD-~v%nH9W81Wao52ovcZvV8_*xhc|DB&Dj8`}y0!Dw%ds&_yiW
+9%<fJz6*#3uF>Ggac_hh`!Dz*_=SYND%`kxI>WId7%`x6@ly`8s|<K?>L7mxMAAxJE?_zVkI!6)zf^u
+9kp9Ll7-aLb6!MA_#CQZxttb^ddc7oCGf_1dwWY>{xKR??ZnA<_4jc2Js#`DTpm|{Al>FRqeD;*eX&n
+%6YrO;Q-#?+i@Qqkm;bp+4w9VGq~d2vY0M-Te?nV>x%&?rAA`O#bM=>?JrR!e)D0HVq8z<(9$Sa=eIA
+NMKUhsM`oFtgVTaU;?JfnK%;$#q<!WTIiY@|P3*~UdnWWTa#XWlAy`7?Z*u&Ko%(96w2}2h@P-|}7@6
++U1?Cq4Em=EfWdh3xrzZB0eB|N|ESv5{Wk@3y5L;u2Xa$augSiUOSf--UXgR<^r)1g0^c42v<;Z?}H!
+4E=lnr}6<=!!?72CM_)61=b!e+_ecFQuLZmpeQ{ROHlpcb5KCumjr`S4fB13dv&+A3GehIZS={8ypTH
+#QALE=us{|57MH8_dr~S&?FVhkk<Lpc&2uq$n{G4f|YE&rX8dZSWTT!vru2s-wapmu12A-$ykPOOw?O
+fqHT)_JHKyH1y471_^qUF@yntJ@8JDyru{4YO9?fDr)8<bqJcBQS!fU5Kr3A%Yzz2^_Q{{ZmK6>n7Bq
+&0w7Y!<N5x`wz@doah+c>~mMgaGA`T-En(?B3nD%f-!!u*Q27Du7;cMstk$S*<Ge*?c?^O|g_7^HO<>
+SJAQk3y>nF<nfN|-rg%cm!5+6Rl@=rm49Z2#p2juVlNxf_%x!q04dqnsIRgX|?8mmGN6Ea^+L*<%5Ci
+EhSRBSiIW)b+J{6LVs`!AyqZXHeY2{V2C-p&nx)!kaf*BvmEbSkw_;qFYyUzP%!kZ*0bl)Wp5agqy|u
+`YuV>db{8K4^T@31QY-O00;mZO7>RYm#NLd0RR971ONaX0001RX>c!JX>N37a&BR4FKusRWo&aVX>Md
+?crI{xg;Py$qc9M?^D9Q)3rH!sN6OxNsiIYHtCi)#P~1AU<r&)M-**fl30tZn1f%i1Hy>|ok1-^MAvt
+HC>Sz*SQ520cL~t<8t9izI-{Qxv0C|*Be=sH_^h{vp2pB`a_!eRcZ?;7OG-NS>X&MwN4uHOm!3s`Dij
+hrga)C)}*u!5XC8!N3kL*H|EwabxP@nzr6zyzxR{X>vNp9VSqp@E7n>btSgx7k@T9<^b+vMJMK%6$Pf
+*VgNxcdzc!Q<3rerSl8%BsF_Ro5e7t%X#omhaL%RX?3v2AYE@I?JUP)j4K~yY?#B(UWc6g`}h5zB~^@
+{a3|2ly5-!SRfb7FL>-NfxJ=|L+C_8#=HS0ouC&nVIXX?T2E5qD_Bo#oTD6iI34b9nBpWo!Fz9;UgjP
+}U<e-YgE4vI@(2Xz-3dJACCE7j&(@7p&=`M1H|3*2s4mRh<5AjrLt1vdBBKmo#e1_7i@{8Lk<F|8^1r
+H|kcZ^Ii1;G=Th8)N1Tx)XY-hi?E~V<3Bki`^tU(>p^H#0y-+o+X5+%70z7NFM=5Uei5sBBRr<*wQvq
+aTDCdpBE-()JP;uBCy0|XQR000O88%p+87j9e000aO4F$w?xD*ylhaA|NaUukZ1WpZv|Y%gtZWMyn~F
+KKRbbYX04VRUJ4ZeMa`aBp&SE^v8;R&8(FHW2>qUvW^r*nlL*D4Mkf_6BqV1`KPFt)GHGV5F19nI>71
+vMUt%?>kbKEHQ2-Ac#dCpSyeR;hk!u4&XY?<qr5kE92l-*`@G-moA0B@k@)c#KofacAD$FIHIhS$u%q
+YY)8lP12cOxb~s*P&066Klt*rqJfL)!<AYH_FvfBvi(&%Jr9&f`$PIq+f3#p76Jj{^NB??HQE`Jk@}d
+;X+F^@1!n{Xsy<Gr36b(7!lDnc<S`>8(XVAi2VC;5G_2H$H$5oHz9}kfi*C61>tH_IR^p_Cj0bQf2OI
+#EC!l|Mn&X=XI6e6u`ucW(z?59wg2kT7gEA@B@jT|76<j>}nI!U2eMJ{TULY@4jV73OeGVsmYJ|`oBL
+7&C9@!dZ+@aeZtaJRXIf31??m}_tZgU|PW=5y$rnX=(W>|YvY8-hKsE`ohRU{98kf>VPsfKGUW6SD)K
+SV7Q;Hz8XTP_nYY2#?7sScE+w2-5`+t#nJeAdshyj6jJBP0-?5f^>?JY<UGzxd_x?sZ0gRaFTlN8OUc
+A$t?3^dxiacsO&0@z`3Oj@<27S;7p6a>#IC4INK4~v{|F^N`>XA;bjwp%2KoyF^&~?>`Bbf>?#dB)lA
+s$d5iFdT!tdBpoh1&Z^%=HUx^yXvYLKpg3G;)=owQSs2LYxGJF(heVP7;46Cu^HSg=`4O)^tEZLq#h)
+!t`cqF+@AYuY|thAnP)YRpO<PKB~G4KQ~hsHT=x9hb=ZFAkx1(&%pJO7^DzWL#9eKTe@r)FFpsPTCew
+$)ltaxp!D^t-$M5>jBQ@*UgXMrtaoVlEDHi0gDZO~b127((siBgFNMhs;WK(9}FhFWFVVWLO=d-JzpO
+T9S1>Yz3KL0)HNVd7fWn80rv~@vAe;ZleT#_nqci38_E&vI}zVt8)=fkCS?LOm=f6Qfqs-P+s(=$s@H
+pkF&HiFtA!q!da~*ZPB$xdWgl?yN65d=fSI8`FwcZRFiY-Au^LqGOu+)t*N-|PbOt#ch)S~Jj^!y^I}
+Ym^TnsQ3c~TfNcgXev>EJUEXh}u|MvFX`eyP8ke$C0B8-1Ne)zbBvNhDvoaoZ?jkiir*8XPOe%kck6f
+gm#3IHCNXsNYFpi`@}+Z3$o`#g1*lmCD6e!^EpL+v!DVH-TvEtLyNL-8cAjcNsnR(K$`r{*Ck0#=r)B
+{xd@4-aZiZQ1x1l4U(1*)U_2iSWpRrV`cRkb*|jFm0igel&$JXg#zZInAa}1ZQ|f`y55}^LGle<F09+
+a=OxM-D$QaL9My9B>nYfvw8n+E~5!PN$JYh+jMX}Fa85iO9KQH0000802@m7R>$3tSh^Sh08>!_02}}
+S0B~t=FJEbHbY*gGVQepLZ)9a`b1!UZZfh=ZdDT2?cigs>-}NiF)F$ENjA%=V(?s2A?K(>B*0FsoXS2
+Inm4b#C4I>UYAxKFRNB@2A15c78DQQk~R_$>(AaHSUao@OLv0B$n8!ftO-qv-gb_#ANTG<2*Wqol`R2
+SxFZC|WwRotvayEF}rG*4Yqmc@Cx7LAfSi>6*hxoE|_6iP`I=}xwZd$gN1Ok-XqI}!Z7|L?a)+4C1i&
+;S1N^<Ssd^sL(O!`H>U<)>GL(of%tH3H!uuf<B{@4Iy=`S+W3Thx^(`Iq<Ny9(N;JChwoWL>P&tf+tv
+&^hheqEu-v*NvPD1YptEO)}p;Y*CaF*5%gx{fnccSJ}~jy+3+={PNA~?IV{$E#0se^lN+XRiWk~<<_E
+Tt_!7C*vMSW+e~!rGD9F4Y!JUu>$31)RI)AWx%W=qv`CumQ`fmHEuw#yo4*Jp^XK&nHeY^Q+!WRJv4D
+jgiHwxBHDQMQgU`fVJH;a8gF`}Y1ZYv^@+O_vWhsHD8w2?zHb1YSSJm$9AUn$@ni;-MFJ$|Q+LA1*fM
+v1_7-45Odeh|4ZzWoQuBMR`O<6#L-k7Dhl97mz1!OL(xs2*7cv}KL*ggxu;d&`r0Cp{->!K_H;rV6M)
+={Tqx|1D$_xA0ZckhqB&R#q_esOdRSS7JqiYNOA@ifAx&%XRzKOH>z!aN<Awtf8XDt{6q#!sz0B|w{>
+WHo!=baJvoO&}xHC2|oHFOFkuP>9N$DFZ9r@T%nMT;{pVX&KR#C_Aar=>4)#5yK*}hOx^US3v;JkaB0
+ys#9%r4uq*T(F)--QN4)H1`9pY!#tpKQQ=6y2IvSvg{X-t=Y2kV*36g1m3&z(>a#TZehG3Fd2JE$K$Y
+Wq2rdBn+wq&%drCHiD2t!OIrQhX!ltb7@$J#u=!^ZwQ&@(>0Z1W=3YR94KZ-f-p_Zpcp?VTb6<jW%N9
+3WMp4Sa9Lt9A&+=8zFNEOYOa(;;eua^=U8fX<Q!62|2A=(HLDd@ctz$xuAI!g<cVZTh2WqmF4WOA0mz
+A@o&{=-PMj2t1sKj}A*Lm^r;;$j86n>7-ctC1ibt2Gdhl?49nMz8;Ji2Rw?QB}7Hs{l@tj3^R9Nx(9X
+E}FVqM@jnWBm#m7?ielQjRz_(E~IKx5INOKkxvn>0x>K%(WR7Yh6!krqOUyC_bCQu$O9`ba94~PL{e5
+n!aYk}fKy2j#9T8f{9g)%@(P5_<#~63b5|bBbyI^%1pWcsa!{Y5$!UK<zgKo?dO?7l!leL&92lvn^j>
+R0_c4W4tVD@>ss#v@c*S%?o>`Y-4nku_H1Wyq$EV4M`LZtNQr%8w$;m%HKK*nOrwBu|Zlj1@xZ5oLIZ
+l75iz<N~m4N$NCbZ?q78Bw|`x9p$$lt_5ov^B(FyrKM5oH+|_7=1%*o7=nvRq7}y+1{->q;KlVQ9!fw
+c^`!>nsfODQ)lyxWCT1!TKC&*>u@lz%C{$aifZ#<P4{oSX>sM(ud5P%u7W!f>@rgGq(LCHi|Ajb=ZQ~
+9E1LzFHy#r`;bP0c};bzNR$_K17f#wk_}3|MlD!(?Ye7O#z+7SRM;JWI0FV&>8Qk|iY85<*%2J984m;
+&4Qa}Ty6u{ZUf6cTXsQ*>j0dMAj4E+p^+3QS!TvLE(2V}|c37w^2j|J{ExJ-CK$s~~$D^AD`oV7VA@4
+W=ybS;{t2>Y^s=*e#V`##NF^aT6%Xz&lfF8UTQC)#R;_jfx%sY^?isdYzy~d0oB|d^D4#U%1Z_#~iir
+uDKLJuAPFvL?@!#VJ1umbz6mx2ZsH?)r`DM+3tI^RTRJj+=+3Jb;?J#hy|d?QLF`^)EX14Ch{F-0Agu
+@0L#y4>$Ad@Eal9lilmVLgVI6{{rlfyFt91qx6NhGnIDN9gXNYN+Q0`o(O>1gcjMy7LZ4IukY^eaMBU
+zfdCq8EJ)%mT1j}^wgRQXq9YLT*QCotp^nehX|=|jh>~<4cp(hmQY9aUNU~Wz*MXHihZZ9vQscaaS*|
+A5-{6};~X%w3pS#q1kVkZtYL-2C8*23X1Rmy`dxLuS@fYgjINkCpj(hQh67u<0&Rpqt5J&HnmKV(mOb
+6jpD*BUP4a9GORPx4QltR>SexKK&IZ7LEw9plpW_hVzZm<)=!uHxyLYcB)QFNIm1!gv=&w_t)1p}b){
+dXXpo>HU-T^rNlQaOi8+|WfcYf?@@Q~I`QIms#KXEiXuEZr+`VOQ5R=U)#NnUs8fYPWu_1EYJ$|=21f
++jr`t#mR8X@Sya3Gy&nAnz=SMq#*xv3x)ga?Z%JQR|wWX?P9MpeQ-wg89@29J`fI!5+xpji9^Hvr^Sl
+obY?_8tQBI;t5m2Y*kz=TjS!RR%*cc1Hr-gj!lq}on_sXIdST_og;cvVGPyXp!W&L_@kBfo%MKmgZT(
+H3UvwiXn-CtSaXApXKgv4kv~G1Wk8_QS`&nZu;zv1#ADo}$ELVe)LIA7p7h?q&ja(`aTB<~vYCU~+SA
+_7VKn@Ev;)2jD9tO-cesyg5KP3$)1N;&_+}ELnn_>&_4S)~N6()fA5F%EH^G01SEp!}iNi8(Lz8<S1M
+`-Gc0)sCSUBXWV$lO^b&VDs@IYY+V}e9IB^cYg#{`OKM{nCPvOR7p?VP5W$NP@K2?*|~s!8rNfJR;w3
+YW!RDuoXJ`TQ6c2p&a)5>msC0q3j@_|$}_Eo$iDPNgJ^L~`v7(cI9(j5#@F@g~f8c~gfyU|@1diOmhB
+03D(af-sFv;`nqj>Cwwfkb<d#&^&QOOw243=e|M|ioOMe>N5K1<|g8xMn#EC!ODGfut1(b7Q1^AOB67
+FvPmX-#adiq9W(_)Esx3ywM@n$nrRWbL!*9c6%!~)2s%(NExHo+##c+<09ECUSYfge+42+kUp)tB(T0
+VvxA3Or{Lne_4aJDsdx}3gcpP(#hCvCoq36X4aL?$;no<jn(fT@;8B@=O$&y-gjF^MM&$X(>_ZPB~jV
+N)s-5jVUHH0(DO~}JXk2pj42pQ^+00i_2&iH3gGtFk#L_cRnPpPhKfyY9l)|B+%0;64aWI)Fga0=g7>
+vl8clz>6JkqeX}XP5dmiDwN&A0|gl&X}YOUyBUA?CU1o5ubb7X%_sNY&GNXqpNs<8d#?Hl%#M*qmk`g
+W-b}an@%jhy^|#F6>b=3-*RR-atKBAR?IKOh2%`<CyG-pL^A7bXPGMNR%ICqyo*CJhK9@6T*l4)-|UO
+|O`!XwqMWhcisq&OT(k8C7`5_WZA5hmGc{7E@P!E<SP$b<Fb}2&GF)w@b8!A!d2wMQZrvUP4mxJA11R
+dVzl?yp7Pl(TnWysscGzP-nH-;<0yWWXbpUz<@SvctKj<D1<-X2CLU|+nkZm}0NJX}_&=KQ4*KrWZ=p
+z*`UI~DYL}Gq$dq^6B2@U_Cxz@I^?!fT?Gme>CO7<p85O31~F`e|G_?u&s2Qa|j6YZWE7}2%BJbYK>Z
+i)B@TA593+Mi^wfybOM(vBmkN&tTLPWRh;Oa0CQ@LohL%N*#omh%Fh$(&;5`LoZT=u9Q1-9hWS9_O1d
+UZr!gJ%iRBqZNskLuzTv$cy*izTzdf;sO(v0hAmJD)e^<JbC=tVCg+(<c-2-?c|r30abu4sATRt)!C0
+=uJMjQaby#dE-{^|Pg=iU8bC6sTpYmpFU=k?(S(P@juwQDR+aEv^$4leA}Hfp6>Z&Y9MMu^fX0xI0Co
+VXstsX~y}&2CDso&Sh2qZJM|fn$46jAUG9(r4#8(I8d#x~)QusL*&WIb<;M2#!rj02DN)Z?q1nQvh=f
+=WgKYu&=D^uNk=|&fBeVSoKbJ4AszzdsWL2BoSq73<tVoIRAL}c53s)!;bo%<IMy+yUwI^aZM2BR!`;
+Jkx1f{aiG6dBWX&!R;sE_e{Ep+gIbPQKO_ct!wT%&Mru{V|6&Mqep3_)Q_vG1kc#OunGhxoxNUfm&}j
+Z(jz`$cxwgw4YV#GdJcO*&-^G>YLIcwdXikqS4aNOeP2g!yZhLhs0Swc9t+N2x~T{W9HAU*$7yX7r?9
+(Qb7P+m9@yjoTcZlzo+olDCB8hZ}O%NnbWcl#WNl}%KOs3oNprU$Uw2ohX+N1(*fMSz_fRPhr13M2D3
+l{JftZ%sgE~WA$`^ef#d7v;8Jt8KrMZQfVZJ%3PuLpWc0d|_<!Lqo`l&%gf{cfuGyyz{EgIevPN8Cj?
+aQK0&v*dT3az3B*^b;iYpW$r}@!~hlmla9{BMfqF|wbqdYKev(dgi@|FPi`dS}k^f0ujIn+sjh^J=u^
+f=veAQNEE%*o{hBpS2m!z~ijLDVTn5<%CTnuCepwB)YjI3sWKll_@(-!PsZ8TsMUPfeoKJUKA8z5R4-
+kEcKON7$(+50o$oTVQSdCZb1h_(QM)!wisu-(lAgiJOgxp|_%rBIVTj%9nC8qaqCOpvm9KNbqK_$R+D
+hVxVe~B7??okngiYcisuVF_~;RIiw>&+?5|--Oj1U<3RhvGlMSA{;b-Zx-M&om9o(HA2~$q9U$80=Uk
+zHC&lZ{x`+@LP?vMkY9=BZx*9ksN8W<OY5XwAq@sW>b|F}ylEfI11#)4#-g}Vf$2%DDj%GRnokVF8L#
+C;n%1hX+H=1{cnD$&%59>Z3_XcWzuCGak9ZfU}dS&A4c66uyu>biXM+7jE>QTT*aBcw)bnw7x&&b0x@
+a%TA8L>86AEMCU8Z*LlG>p1<0ebcvf^J>-0Wo`9oEM<SH*Q<4(4kK^Ttk3JxU=EN(e1qlIG(ue;VXZJ
+p7C}r9)e)^S_dP7VnfOU(lI$IW#eH;mHN0A%0yyGfYX!)^{gdNJaGN|k}7h$weOdYFWJ{@e$<-`j^zT
+3Jm!^UpUU^*35<e#fZ0CsJ^G~|55v$^H!vD~tF+6`A5tCN8y(6Vy2vE2B_C`OUiZ%)%0I7*v`;9C@&;
+lIbjhk9V4)~mikw|S%@e`)hhT6s5jl@3f)12G=<!5fCwR*6UUWHvaX1q3(r}v*pD?h!bNY~AUR6ck?F
+;h>&I_1Xwb|3hfu)~W{W;x^&MYL}NF+4VPRl)vFdH_xA@>?vSxU0X<MtMId096Zd!@=Zx<NAQZu5(O=
+R*B9R+%x1G}@mi=P^^xeXDW4$23!VYSvq?wny+PRN-{Y4XwYqQ8rYX68J3!c?`#~EYcmOc`FEOq<@*+
+rLn)C@!h(d-_{Iooo3V^yS3kAk0}ep8aZy8PR80U>$ZB~fg)3ZHLm0(Q7srg0K9nn;$|}q_;<2{52Ln
++&abkAZoZ-2{U;m~L+2@`xwxbZsO^VcxFnS0wm?;u#4~U6^?txm+J#wf3m!(#f#>tVAa!W)xt)Y_4vD
+~oIBFW;t-Z)(|E`-FGnel{GqfmwcFQd>(g75%u}`V)HW|FdKR!p%3XyU+TywicSWJcUNB$AiD2d4T9C
+Vrd3Ys#H{y%U9ex1GN^D)pMeo37@<i<Z!QP)2a2^X`*=p&Ajo@qJ!FgEsf65k<(1S_nJ?B!cV&1wAMH
+cBY&hH&u1?Re!h_aEMZNo@XWGVRYc1&jh9ce(BwnejQ=#+xVD0B}OK?|_E6i2noK60XC&{gY0^KIK}F
+c4MKL<!l9Hao7d{*@Y^E#=+<#a{@!h?G0L>brL`F6dD=onY$g9qRXPoj?A&S-d$ASq@;Sv*p*h$y#zc
+Xg2>}CLaGKwB!yo!&;wFb^Rmk&dJN!+G`6mL4Q}pr-SpI!zV}33Gwg!v9K9Q*%WLU*GR6WLn?6BC>-w
+l*-}%y9o65#y5o5{22fJtg*4*MzOx|H_2xwumSA(KxY`klOxz6EEM)B@n@p4^OdkB*&Lmt9;E)Smapl
+u*MN)JK$PB~v70;k{B_4Qa}+?U^mmA`dEtR6(S;T{iW@oKS%e)^i715I}m?<mN(BSwU5R5&MFH!qlX>
+(1E;Cnx)-cc`CC*C)AD?l^4T{i&5YuC}2PB4GS}ZrG9TZhB+g4WFhYcTNz;h8{uMc~I8Kmvf+ty_7RC
+m40t!qmR+QWDd)K96w0V{B(tI>uswh{zr21Z0~;_?|pUpvw6_}O|!kzPfgq8-}}Xs91(lABS@KBItNj
+=qqw=OGR(Gn7gd~%>T78l{(xY1H+oh@0Nrh3S=X0%M0$y7MNP6u6H9A4QPy}tuF%Do3<qS|oCYJ4HsE
+@i8i^*wgg)2A(uoOH39tj{#NFSI@Y+nWKUkjTvv3Pj8k6{~z1)?%0zBqykl(h5*=oDHg`!6weMzFKt3
+5*=QtLx6R#%bXs9DUHNOh6MkI_@gBd85ba>Kz(!`BI@2*I0g1nvcFAvn&n_~1$Uc;tPdR3~Tq`(Nz;A
+$&P>k9}fk5mVhcAH>$p<~~{T`}T!y#PEzk{)LjT4ZD9@BzkQ<{<CYao;seFjo?0(^s*PJxZH=!I=pK)
+BbRa#Kw4CrNg9v%*CVmegD<DqvHH-8**zVz1-EvhhoF$&b?&P%q0&hogTZ~cK@W4~Yj*dv;cdD5F1Ph
+=qg@_GCs(JGp1RccWc=f1b6e(iD`R87d->RUn_!l)Fgpq6;A`8-1fm)*kR6{Y3tj$SGv9sFsAYYf-5Z
+~5b7$CNB+DM}f?eF7oIE}?4SzNbTPH6R?XR0Vyx12wI^;J{CI*MZ!Tmu>4dH<}XpDyd)AN!xt`$3Fg)
+)Ov>x<uo`1MlC@*$JKwjkR54@_)_d^K0w;EsG-0eYM7DZt}E@B739c84yhD9emn)E!uGUgIGP3^UZ;{
+k}U`I}0Ug6gW19y!@}bG)fA5Nm*^Gi$P8)+JDvcQ7{O}mMf&Fw<h;$FjvH$(e<2nRPLU*53jfqc5^<%
+W$So6^J7<ll9JVY!&iU(PePayy~19lsmm+A%+H?(uwPTSuCc6c&y~;Wj1!fZ5kPc3@xlyN8XIFtSMmL
+8sYH4A2?|x@vcVETgJjFaj|9-ioIesFuIeIJd=^0&d8+iokcmqCrsjq-!*A=FGWT=NTk{o{Sj_f6KA#
+=L(Upo~c=#9^;t6LgIO?a5MU({|e0CKdf$HKeOj;;Szvp}p8CFb1bCf7=myMKsi43e3b=yy)uR&ml8l
+Y@(5uLs%=RTp(%K5S?=2WIgdEiJDSaXd9oel2C+<j7kT7agDg`|7X=CdNG$#c9Dh4A_O0LunigPCZjn
+&q*Q%|Js{qg0_k+i}r}MgTZz_FLJDFoZQ8MYye+GL{Au711e178nZe@;fXC872C*1Q2|+ri*&VwO`)6
+#_Kgmj|ljY`KI6sOYo3a>}wN5TpMPs1k5vU4G*t@vGnouK^ncqpp{-xSV~}!kNCt3KR&~k9l`fbL9op
+iIqaLR%IR|=7CU0<OSv&p!(fp%uiv~k_oe<A(XCBlH-YSi3<kfL-~5_PFm+|=3xlN^FX6K^I=TT9JTH
+*ha%84ety)u}ZQ~ncsVRhTbGdG#v$Md(KRd(u&5YjnX7nB+XXx`lI)tfe<P4!nYHC!;<t1)oLb;u%FP
+NYd0CrqPjyFbTG2aM<H-LraZ_+nZ2wX9(DXzl1lkT|3gslmEAA*9?i4ksdRARsOK@twbK{6_==cSXg8
+ZWd~wnTF+Ydnd@J)+YTs@6nlsEF>W)shTqPhhl1#d?dft2@O?k(kgxv-)9**9xyCelDa|e6Wqx)x|}n
+t4deyf*3t;hUGBKr_iM_R_WA<_{l%u$M0_O;Xb|hch-HI#u&@+(tCI@lwu$J=a3wBvZKC5IrNakFE`;
+CeLpLtZ;s7$H=W8$8|@`NWiN4W|5Rsip7}T5-hJ~t`ttFYUrk*F%o2GS_7c6cLkM#Ogzj|v3t#AaW(z
+Y}-)*#&FpPyW$rj7l!eUeICB1@8pntO;RibAy{U!zjWayX>)o<Kn!7*I?5_g|cCLjTBJ{XCoYTk{T7P
+ikz#PG!kec-!--6)V{{mr&AYZ4NC9~^v<)PtjMyFeH$SrpGD$TZ%E1&u*v7o)MbSE=kz=~i$O`!C{Ch
+y>V7v&Kp2q>)ZFr}%j?dh+r(J*f7|<oL2Z73CB#YhL>a8A}HZ$x-70G$1d`E75ip${-we$(OiFcF)E?
+U;&JA=`#g?e?j|wfwSfkX2f7K&1d$?B6IA_BvMHU%;MOkY2nAjrG@zYoh(dUydi-_@PG7gr3KYa^bwQ
+$za)fO23Z@TH|rpfs@Z2<!;F96DIVv*8*=rO)cynoz2AB;+4(<EO9KQH0000802@m7RvR4h>TCf30OA
+4w03HAU0B~t=FJEbHbY*gGVQepLZ)9a`b1!paXk~3>E^v8eP))1bFc7@!S1f*)783i=TcCyVNO|yhrI
+1r8#cZT?B&tY8yZLzkzH3J*Nvey+GxF}tG)-f^<pT0P5(6@48&Jr>DTs%VSTIJEkQ1==v?p%O`~$*{5
+*3V)k5rC<PLKz{BZi3ENY~eZ$$@wZ1#C`2XITIf880&Os_R^~+>Y<!b82(hb)UMrQ*TG-*2_LVVH7G!
+Z7pvNwWd+?#%!Kn)^F?nb^UV#pW#<CsvN_%SwJ%$3RUO{9TlD++Y&~Zp+mvuw+^vUv%_XKy)vLjhkva
+E_#7R>h~gPeK3ES}2o9`0Ay4sOi%j4`AuG8A%{}BYkHI2gKr8>3i|}L4t#j=k+);a7Yi7{*9J6rWYp9
+!u7tzt64?+sk_aA0vI!tj`{QIgstbnE5u$M|6*xJqmTZ?*Nr_OGukFfj#-*c+9U4685y}GaHLB9By<O
+{l&t09#ux|gdnl`FcJCyT00m-!1&O9KQH0000802@m7R`}<9!Dt2m03#9r03-ka0B~t=FJEbHbY*gGV
+QepLZ)9a`b1!pcVRB<=Uvpz`aAhuVd9_$=Z`(Ey{_bDFsTg8oF1vLo1_bc1uGoMAK@l_^_Mr<@TB0pB
+5~-4u6K`05`<^2$>owbeVM3Ei<ni9`xnopS8|#_!(t2Y`w@`7RH2b~M`}WhEH)`Y5LoIyKE;P0*)t1-
+7I=R?cQ!#(6ag?3*uaxtPxKXQ`rw6HXV?m$Y2@=5@uS(ZaXF?mTGEu7EWvWFb`$v_Anp%{+GPx`rS2~
+vu?aAxo_3Js>z@BHOg3>K*AzbQV?4#tBa#>5Pjjf_SWcHd_nTyP)qVYva3{rStu^@*@%Qmg&_+I*}u(
+nKtA!)i=EEZWQoMSgq*sQq8Of4@L3x+32lJNgeIuo^PO5vqrzK~#-39pQ%FBkx2nQ|;MdZ+dcRAJsQ7
+ufMLqwtcZt~B1IDRg?D?BJ`kRQk>(YnBAZk>24;n=~vWxAEi;LCH$`!sKBgmphhO37wYVo1Uz6>+?s)
+{W8S+z4P|A+wR28ZnyF;*%m1n*H`T6_blo8DY-n;x4xq1RZxqGzDt?eew3MKVuzTX!$&De4*k$6`+?8
+$e8PTgRGIgz;_UT~3C)DvH<i?$IWMet>|XhTeO{w{SS5~ZD|<Xd2we#-r9{pkqUs<iT7ng(k}OviN*a
+6Q?8Y!}k9|#he85}ioT(kX$p^U4ty$w_Fy@?_IXg(}kSDx%^j(2e!9Ns>+DZ#Yl}Ab)C+#7s^E9Zg_J
+xP?WUyo(8|R^BkIfc7$jeSYxLY56K@JUmpqJnY!9H`|DX@hXeL9;Pl#{nz`WVZI0*TU3rSpEsp<N*1(
+eos3nS4%GL!yvP@;;o0h+*X}X>~QB2V>(n5%B2UWy@iPIXx}&6V-rbY%&*h4ZJ&v?)en?bdMY``hw61
+k$87?!=x75Qs!$4t!BTzeEWv9gR|>WWD*B1ECGVK8)gWSO93s6CMKQxaa5Z#)-6ZY^nHFtf1VXW>19{
+1>xo4(P6^PT!zKMz!0{1Y9(Q{@$6Z!P)Wc@OlEVAiC6Bm0fGNKhR>S<|EDb%$6e2@%j)2t4PYo)NC66
+<LH=o_yT&+>B_Y&n5D$co*q5U){YIyD%bpXFZ9J%^$c!`5hB}JFd6HOgN&lc!**QJe>zOkC1cW8bWoy
+|C0>tPX{1H0+PctFyE@uq$0woeI6-5|xD@@d-X;bgh{-y6akqvhp5B=0040lSYOQ6~>X-N%rql^TE}z
+IFzqo2NU16YnKNw7ImTlR-6D&}jx0q#I&foEmU;pi7Sc1u@o@aDTk^1rE`u!yU$xQqtn>w6d{E={Y()
+Ev%_lP-<?#S>mS$VD0mST~iT<%J}8&)f5^c$1yOtx>SBS6+SBge5t_pQlo{H=tD{$fa;+op0I-)rKLw
+$h!Vq_>my{x3TmR{1%5!%$WsG96)`a(S)?V7ubD$zrVffx%+D~xj$m8#&&)QtL>HHmZEN%N`Pa|C`(_
+<qzkTub3*HLIjdZ~K8CIga7e^NX@oXM+Ar!MTCcx^@s$F3kOeR(+CujJ`hfLNH<R}Z!{3vH-<TVGugj
+y6M-gjiX7Crjk(D>qAA!EgboJ_uS39?dFt~GPbki`OK*VY_VPNQ7Zg<q^6<vPurdD@wLnyJIKN&jO$h
+O%y{C!CY3*qK8|B@Pnk_Q#(IkGQd<QJa4>=&v(6tcDGsC%DCh#|EQ+uha>Tdn(O3ZLH@E5KJ(pHy=!R
+jxFmV5xQCOn?8vPmaK-D+j(dNx@$@p8uP>D>XPs`;PAPf4DJhWgRJq5YG)ec`$35@P<GybRmkivp2J3
+vMS~W7R~VJpa;GfjWfhl72w$Dj9i?>U632A_#+e810nk5hFxCOnI-Ld=lJf_7qq?KRHSX4J7&@Z|%_k
+%UkZ{x8)uVqWk)gU7V)LiQ;F34FgfIKPo}_C3>k0cg0MCP}nu^6+x7sSe{V{?qYW;|)VvH{#Txy32E%
++|{O<~9i8BI6=Nbo?sGF&)tH7z(}FH1mbvoE4s72#?d1Xs&!#Ar#lMqQKszJQ4s*BME0N*bBQ$795K1
+<<DmQ=^D+9B~Rwm#%=P6gu6VXilR_#kpgg$8$=PzOff>#A+)s_$y=iVEqKj2p}i(<3;D$+(jqGn0|l7
+Krz@q)fP4<)8qSTB2DYLD}~#|Ur<W}1QY-O00;mZO7>QYf~e-t0ssJW2LJ#k0001RX>c!JX>N37a&BR
+4FKusRWo&aVb7gF0V{~b6ZeMV6WoC0OaCvoAOK;mS48HqU5ZPfZ(0agt9TuPihCYs4um^T13PZ8!MvE
++IqTDq9ew1V<mYd{|*b*Nf`F&(sXFBkEEA=zT&Kl?8yY<p&p^BmnmsZ-clG>x=v$8V{Dk@v!I^nC@Xz
+z>~Js;xfZ8|K9qE><kexkxUgj_jn(V?!9mId%<u~@|4dtD1ly%HV?{05;Gx{(dP0*%gKkKVxPp)otHj
+A$5n48krTHF=>_D5jMPsXU~K4^>6Vc&aM6fya0fui3-ws=d%#Y!+AZbN;S4w__lJkfsKC7p6A}Y_*nJ
+xc&4(K5OH!a`>;84ym$xzcG5ScuFwe!JX0XJy%n!zCo@GrVydQR`klli%>m+H_(YKcdB;?DC!M&PpKg
+gN$w%zBiW!M*lm#8>tF~p)&zoGV+w3a__dLIqR4Qdo^OXxej_}mt|bLFIO`fYF~h@Gt7I($-hsTtK+R
+IQ;*^phZBW@UkVRt^1}vHpL;{l^+b6=fK;}wn>8tAE&^wkwd+g-2BTHBtqvm%r;*t?F|G>53(Ksh@d6
+55OrsgMh{ATpTFQfQe@Y8fpk_5Lr_9a|@iLc9}Y8H!I?i5ogPEHe;^<O?Li-X6~3MaZ*ll~0s$I)Q!T
++o1^Q4JRZe}tOw5Gj023#<DTeER(HGD^jw>!kPWlVorh*EE^K6qa)|^G<)w7sgNpaD-5P3BM_27#uQ4
+3Fx>R7$BM6)eKG4Tk*_5K0spTcoGE{W`SpCTpH7GQaAV-*9gmZOK;%M2p_x20MkvFQ=^(ISod)@Wq6F
+nS*k`7*Z30bLE~-&9**CnJSU$??qm{nh3TyDa;<Xi7C#2(>s4AcX>CxL)>J3lrF}vnT-0wlRo+p{?HN
+44`yv<YdFhWMQe<OYX8Y|X)9oq4*=Qd;X6L!<>_6*frpMekBb#lr_uTYsp{Fm3|4>T<1QY-O00;mZO7
+>P!1xIDS1ONaM4*&oq0001RX>c!JX>N37a&BR4FKusRWo&aVbYXI5WprO~d30!RZZ2?ny;n<b<2De!>
+sL&jLv27ypxO3fzy)&H0tJe0(B@_YT3VuPHWVq4R19^o|GhJmB8ifc&8a%XHZ{+W-#j9#+E@>+bxCPW
+1-`ANK7;Iz|B%k7@VWNVXs%LtXlf;rPO_FY%btZUjAb>?pZFOSndfKsqW!?nQ(39KuxN%gUMk0OQ`Ow
+dlT^~T*;MZ=eCC>(zKbG-XJH-sNBz=d-elSo#=ma2k}iL-q>Zh(lK+ZqY9vXLTyf_xK#RWaTYoWnpCo
+|KX0r*OpLEV^*C_6V1Ah@vTT=_`CH^!eaOkukIIpe1zhJZgiPFI;f)Nar#-elw5Wd#VbA?D2=Bkz9n4
+a)C8(fDkS>}}SF3aEm$8Zu}XJ?6UXLTDTvq?t@ev)qb8&OcA654aR!0DSB6T`@=NPM)se!B3NJtMe9x
+V!%NvCE(kC1xSD^jWqY<egCEs6B+R9|(3Nz8#&nkB^x8pNQu~JPu=`6i9i*i%5YnwxUX~yw6Dt*hGiK
+Bk3J{_%;08k8t$Vp=V!n%d2UQcc9QOaR+T7Igmy+7+~;w*%?NFxXmxfFw_}Lh2%T>5EHovZUqeW0jD<
+bGjFWLz^RhGs2F_4Lwl7D&0eKak-1XpVrDbv8cqUEjZ_$<?kN8fJ<2+VuB2x0fbog-;K&c^s+KIh5FF
+L01PV!MpPCL=wB9bm(#DT5D3fEMv}^(CoCkLrOn*(_i3)@<vcZ8BSeOn$p^k<wBWHd6_O^g*VXq)N;0
+-iRz*ev`gD(gun|eI%KR$lhvB=oN1?!$5yzplMO6aq{z)vaMrgY06;d&98I>@s`JQgW+{CtBT!Mq%<!
+JEkWvXQd7{n5p3bi0GH(Rs*^ld(k<bMD{uar|FlOv~p6{`Ll0PAm*vZ+`88Qvua0QXh#jcf+Et!`6Ez
+R`l#78CyZQ@QJC%6(88YFu6vUK}9I{T?6Y=YdaI%B`duVwKr_T{xMQ-D_(E$3e&lV<No$>H_;9N5eHG
+3KH?WKEl?yrh=s?FaTvSDOk^7C_~SL9@7~kRK+C2hCDH+VXrK;`<;G%-bJc{dKpY`rF6l82viYFEC1w
+~D<8bSmMaQZwnF#X$(Ow@1zXkD;&MDrp{y-*y`>ro`U7z|S0@tpWMgMXFV2El$*|*4!5K)I+Qg~^0;7
+}wN;PQ5h{lf1;wDb*I=UZ+g3lr8oi8c!t<DxBxp6zr!nGtK3&P3zgWS+}Hyjzh*&MyS!JJVVfOq9mT?
+#Z@+HR#ICS4{ZZ;cH0w2m5Uk@WZpTrzfH~fdsFzKOQe_Ft{6eI52wP;6U1SCjQk$NlYA9i2G0X@bm32
+5SDPNpo_?#sJ#kBQ>~CiScCbQ)BeiFOMIY0BPCi%Isn3&fHR|@g&2FN6{Wz%B*%GL8Jut3fu*%TTIYA
+`OdqH`7Up{Uy@7k$<ooM(hfq_ft<9pbUUA@b!^BC9XJ#h0fW5?lt3@txt3aT66IPP5%;Uko(*56A3h$
+jS^t@8<^epE|tg!me(;K6No`CjYHc?;map*tOg}_j=hq#27l2nL?p(K~@srn8pb(qeY%k<ZRK8KK3GO
+yRUT=E}KO9KQH0000802@m7R%rwAy#WOP01yrU0384T0B~t=FJEbHbY*gGVQepLZ)9a`b1!#jWo2wGa
+Cya7Ym3`P6#edBF(`$|t*uQ;1I2WAN$Caxp<Om1{jd))magq-WQ~{^d+nt8?>%?MdU>^5S_(B7<hhSI
+_uQ8pMbQ;ihAfrN3MuYaM1@$Wf`lw{Q5n5eIYE+TWUX*oxD|=5G)ix*sHB0FUhv_llxxC+bYdm9B-SK
+LRW6fJ6h$MouC#H&&}d=wTDW}$kvN?GqB1uTZygyqFK8m(DeFc-u~Jo%ZmG<*Nh+Crl1p~!<kHs0ALO
+#Dt4g>jWs%S>qsl2=HkxnCtt?djJ4g5i0W#jvXp|Kaf%((fNZ<p!uRA<2e1GnbQa(xziBklVWO`lUck
+Jc-G0?t?&o6&s=UXyo_4C>F-Hn~zes?~e@)3)|$+zd@abq6GUOL~XB0syyukV8V+@Dta)~fa+=j!OBD
+x_<V8qYV${i^u$Cdt9=RFw-o{svGdEpSRcUR?eB+xv@fHV!f8v=AvsRW40qOT}X1IpK(A!a6e+(=+j_
+E@{?yV!rC<nUTt(dWNW<F`=a|r`n}ZNLEl43vKFh9CRJB!I2;pj4bKpCs|9Et>W5qON3g8QoD|Mi`?_
+TfCur$i|9-3?kgi@H&O(&ZMm>GiQ4--v?jpQMyIcE5Vok2rO}%zj#v<l6GO;rMsbuz6A?{2{-23^dR`
+O)MZAFzDEQ8^tR?adamxmDaK%k$vlVr&e<tFUbCsQ)oGg`FZRT9mC)K`^Cupb>1-E2RUcP+w;wUB*qe
+XiSqK52A(B6Ts@)W&1=)y~nO?(Sj-_%1kUW|)vRVWun57K~c88(FA2{Ue~M=pe<Z`k4WHL}9h%@Kmrx
+hiFtM_~l6fQ5_UVWp&gzMYCMy~@O(i+2;TpNP+6-yJ*j$^%+hux|uDU_ScX>T)oR<F9R-FUh4)Mc+8e
+(*}p{df(<emaozCx4mA!BDXQ2jXgilt?=+AZxf5TOSvdu$y)-(s6d-^``85gpcz9WhIt5(iK}5Zcshg
+0ZYmz^$Vg7R6vcg*P^>l!a6#Iw2amn*80<pd6YzO2VSizs9hO=XQ+<CglZ``}trW&RPcLt^RM=T<*a0
+VqU}Q;KBX1BS?c}=Rt*88j*env?ACHXuGVZ|g3z`M(Tw{#J#}T5!<r97?Yl>fVZk}Ot%k_aNR=>Qs6h
+D0bDqMz<fgzE7Y8eo6DOJfH;a;1ZOs_WYF*(Fq<957CEXWwZ_Gr3S9(KV;S#0RS7;R?aEf3>ivI7!7#
+Sek^Ze;aiUOVY+o}Jkr4fsGtNjn!SUuFt4aadGhfEwv2_I2hHGE{%Hr|^a$-aB3ScNZ>+p=Htr9CwO$
+fqF}svb3R${l~p=@Sv9cLFzP&ls3xkXa4PpWt<v!8<zLqRD5k*^L~^$F7v1Qpe6Tsvi*}j5F5+us8Q>
+B?M8?isQ7Jh!Wc|wS5t?e_|?>K1cs(f1f8n;z++bNWw;io{6^}4X@`eTwZ;m~qzw`HI_GAPTdnf8*-<
+LHib@OAh^-`PuvBphuTm7!EU5|ksNw%@+a&`Y`c)unnhx8AQ>c#;jf^^3^VloYz$s{A9>oxk|4;WGnw
+3X;-@YIIHGbbdzA}6#2f>kH<MiQH;bqk6!1~`wyHVy^7efsO8hDO(k_cY;j{<rG4#KSL&=z{+KQEL48
+u^8_&rG5${t*13F)PB*8~p`PO9KQH0000802@m7Rt_J5N-_Wd05Sjo03iSX0B~t=FJEbHbY*gGVQepM
+WpsCMa%(SNUukY>bYEXCaCuWwQgY7ED@n}ED^@5dElSO)RLDy$DbFv;)&+7BOHxx5N=q_xGD|X3i}kp
+al$5vtP)h>@6aWAK2ml*O_Etk!O8<-%002Eu0012T003}la4%nJZggdGZeeUMZe?_LZ*prdVRdw9E^v
+9pJZp2?$dTXmD-gJ@mfWLZJKl|B)iJeR`LU`vvd;D<l~So-5EzPBffxn@Nanfx-><vpJs3!`cQ;{`We
+}L@>FIa(G?=F83G1(UcbPmJ`VDLQx-9ydx5-be*|AO>931hsFX~n#b=$LUU6d@D{cULa`Z?di{T~Zam
+pFHx6m69hLh!OKdR8SD&A^h9S1eic?qJvPtGcS&i=^yWg$or8!c1UQ7zMCD_6c7ntwN_`{~DO+MRt&;
+=|R2S@vcuAesKXH^j9wQmDmh@-I#B~3YIIGu+R4b)>zkOYQNt(fQGJV>Q%NYI>8Rs9p5I!s!Y_wXFnb
+-;JfI%qU^V<-|$L~Sr2X5bB^0k=ygM07Uf34-~u4_8~wE8+bwT*9b4BQ<p6vN>*@ig@KrvL*ck-c{UU
+i@m;EAnT?_boQfyiEe%Li^k-XU<yNYI!(2WBHx!z^@6>BTrWrmW)V39$N0qX$3Pw(HK8YbQ_dkdVjTY
+W2UFW^G#c&o`4or$b56E9ew1CP5hM|50tNxonwa(t$E?aX@(cUU()V_OTuwAn!dpF&(N^aYIG4ZZ!k1
+5pJ@tK^-IZTS@=oN`<s2a%9Z#IC7(`2g^4c<DT!$B?-yMRo<M18hOL?s(%8{kUE8gM)^)k}U1EW_jKM
+Tl0K=aPZd`|9pFV@+yCR{O;M0uU|ZeaW6qzfVl@{1865lR)uC(80LqBFkp6=fV9dl0+HG>dq?kE-q8^
+M%Jy%8+9(pIq^W=r2)+UdDhLBQWXB3dBs(?4+5}Wm8oDV&eksQuCM(bmdHaVzf$(0%)+7!@+ZyOH6Rc
+S;%mx+?_FBx(;QskMx&Ie?M^p7&;)<Uv%Whs)6q?z$tV>@#lF{NPyk)_1J|RzrrZI$!5O+-27G@a2#>
+i=<;P)k7$NHgbX^RKH6T!SCe8QdXfl=+3k<NOi>rGv55E}u$qAZ$buXGRm(FaAx4->?F-wn=&bJ!^8e
+NJ1AY(c5CntovJ<M7M^^`8HJJiC{?8+I;2-w0aC`q~kZgq%R*dPLE}ay|5Q4g47Tq%gQ;$@@(W_FN>q
+1^O0OMcovuM!I<mL?QB*<)iPjKV}azOSv@?zUcdI<`Qd>q&~*!-0lxQ(q?8ATMZYp^p(Wg!<CG&rafS
+j{Fg|Hx^oW@P65`qi)a4QGqmnz!~SeQp8&xATiyp!5ePUA%ruyV{Hk^1ATr+SoLWiGon9?Y6}`w^Nn*
+xF$fBR!LKLI(Q^c@z7?I%LU~;@|iOFqQK=aTt9X0jc%#yz2S|ek8lCr7g9*<kmv!cSF7cCVs2xDQ*tX
+)xF78k&I7zU3););g17Xlz-z(F9c8BH~FxDKbcTMWhlrq=fB8iui!^b}?%J=fuZ8o;i|ozq$}0|2}<T
+#!CT&FfC|Fq8nCK70RDrZ@hDRuvRtdnbMY7#R8c+fZ%SkcO~M0a*^(`G#%5EQCY}Oojty)Au`Z_~5|>
+n9gC90XH7}Qa}*GAE>DhRt;Z0c>3f|e}4M-kKaM6v3~eyRXuw0^l|mw(}#b0%$}6R!$<7l<LXKE@QIx
+T5&@xgw%gx({pj&`_u<deFEbXQn&)4k-*+;6|5;sEOUNzWQP+)xdL)sE!1$}WWVwTahmkK@C~OuNP>a
+9ST?dvIrRrvBG9(@ZxwfW8rE+-SDFyIh%!8;S0p$UXpN+k3>hH~N>)gy`?G?<0R2DAkj<+DryZvnLK0
+ixO|M~u>Hz&t$UYs1gc@CLNdJc2ap<mzsbLwzKpxl|<JnM#b<~!!C%Et6Z^i|z1ohi>>{QczT*RMyTA
+VP76ogSaQ@W%j}OZaDR&Rx0!YMG=Q)+?qd8r;Kaa&hp#ICG}<Jcrv|y_*5q&;|>(b0tiCxrE&=^LLdq
+@!QMUZ!ao02}vl%;wCZng@7sm%XRum6X5eF%c0LH;O#N-774;nxnbqy5`A1uvivmX2U8xJZHteh{y(<
+FC-VdC($t=EodnMGh2?o9?vQ*@VIVm16&J7tof?@;T~%Wk2oQyU`hgNm6R)HDhKKB`=7WInehqFPV-E
+-?R*bbtRSS#)q&){w32PNrOw7{2Up*_;)0_%Ia+b<u3b0DS2k_J}pMAIY1rH?~AjY#r-)Y@S6A+z4mB
+^*@n0Vu2R(wB}Y}Y5pH2wvu+Ss{<gI~~psDeOMxaZHf2QeV2D+FIHRX+=Goh|#gV<l#+OwSHxLD(lCD
+Ql|ay67YXlz4B{R$$na9-HV9mC=pqkg+nov+JN}jQqY~<5IC_?Dgeh`1ijP;36=MqFD~HBG!b>n(QMh
+hn}KHphp2XGz~^IX^d~UH<&a7unR<y{!o0dR3mEff+E`LCGTdcUI;GY$Dd!#=W#)^h9xF!U<lDeQ7t*
+6uy~d#)Kkx2;6T&}_#Z5N0a-NCab~K_%A3QjRFvQddXdiOA@4D8r}8+?r9wDZTB<1{C*WH2yaA1)6wX
+B|u<jn%A7tq`Yk3Y=EGGlyjX-OIQF{(yx`dh&)VyLn>$YeN^SYmrxdF2?W;WHdJv$G(ouvp9h$>B5IE
+Ug#tUkwliT;dqJ-#ZE7!aGKNAGf4bi5pXlm^b8_27zEL(fQM7s=m?W{}tO>DBJJ3(XVos%kME{hD;>4
+hRFq@ylrBy=1lH_aA@%<ooXrljpqsrl)+&&OoxEa?`?!*vR(es_1IcqFO|tf>}e|16#tjyMB*c^h#9v
+ql_Hk<_A<#W&wLVlDI{z4+10DZ*bz-xpx~Y4{}HCorEu=s{2fxpkVwIkwc9i4jIe9q%;9hk%PNTK!mU
+c?>1ALxj`NXi>%n~Ape?JPs!U$0C>Xtmwafeh?B4Y!C8zbC*?(LIs1jzEiEPjBHv`E76fQ1aSUu$v~q
+Ndd$bl)`wC;iDUJZJQP&wMn$Xa@MJu$l2^!=AK47oFZfiBMlgXJr>{1N&3K3qx!3J@F3FwYF#88C{`y
+Bil`-q1?!YMQ0=^Ukh7}KJiv*W|qjzYRbdsI1YstRIof$`?rA7asgG4@Nenvy$#+2|IS5A+)l7G1QwV
+`o59xI&|I9w4PcXxKj<O`cJbVyY?t`qO8pB=V09vvCUAP`M8XOTbVutW0}_T=cCr{czwIv%A0`h>BW#
+y@uHU25Sho#x_fi*LJa@M7<OX2MT%GEA#{8W~I5L!kL2ueBVpdSd}Hu)`%nAbHJ#OIw|bQITH&B2xG2
+JM``%YnfKuXl{=ipK74RDAXw(p+8vtrJja2K*g2<xTJY5A7f^Y}x_)oOew1RE(~Zf@!co0wk|Hq-Z!1
+OrA-s?IXRkulNrY^6GL`LOt&Txt#F&kkV%SkOBl8wW&^zi&Kr`k5GN<?%<z^&2=sHbI%*%4<s8zvTfe
+zFAP0>4`2!NEz705uticY0YT9~y-11Tvk8O_Io8IDp49>WC&CVS5Zi11qyPkBHsMHdvj?ilSll$3~$>
+&q#b04>qetT>?2bIJV=*q4b=^lq+EtMA`$`F+Z)Nw2{yz@CS;VZu|~L_ktguj|r@$c4>Hfna5Uu<JhA
+))$+e9>Fdh7}9p2Mi!+P_`3BzYb<#;MH6)YlnzMa>!hdWK_SrP_LQrjGNo7jbDqU((T=^psUn@G>07x
+qv?)EF@sqKkaH>cyYDgP#dGC}bb89*GAg;viZpe~i;6vlDDaR*j*ut!ei*P%)mlQ|QmCJ*X()$Jbi8}
+M0Qsy8x9K}}lOc)INWeoval~iEoRXnU=%Oc2VHb(m}CaC=Q@y$iUS4A_bdw63a4IFe1;=zfSD`|pqvK
++H$Sml?^Nk)yk56b4ZRHYrs;$01?Go29wsO0Cjuaj-jmm7T~WwjI@WmX7|5ZekBt=a=GYkA;)!CEFQt
+?N#=#Xh0NuHpi_$*iTDKmZ_Y$m0Urei^{a;yBrW<6wYZKnpTSw(__ebfuf30&^nlxd>X~$aw@BRy<wn
+SW)dw@DSjHz!6{&BDC&4_Qv+tZP^TnlWK5N+@qMoL0|Gf=EO=p4dLaosHtnrB^F3#7^2KAJTp*mjIyq
+1NcSf8$y|O%^c+FrWe`H%LH%*^GTJnS+C9%YS^rKSq;o6@J+P}&k6o2Z0B+x1hD%e{N2k-aC<9!pD-5
+k<T4^4j5tKx#+ncu_N2$R02HYI{^prS;(T&rTdF0&8Zg}Z|pFBO2?41UbNj*sZ;KNh5$6&Dyt!@VvWR
+aS%liQR#icd1xu({)>n<!Uy@Ldk6EM&pEeiqEYjye`p+VKM>blDW!RaICBhhDGc*h!pCq~wOam_3iZg
+NNnB7{BZRihvbRk~Q~$AdFl>@(-<KfThXV!}IWvvSrt9VlWk+Xgijh<5ctLTYCwXn_tVu%!!Owj__Lh
+bVr&K&gdw{b2Tri3Jm|8wiwg1qfV@>0Ye|-$1v}Z7^4IY0V+k1O|xkAfO)QwTBs4^6?3$SxqAja+1ly
+Lj7!2O8v#YE0?P_Xh$q{wSmpQv05XaX7w*yg2vt|FVu$>mW4mjs5LKwcW^4*3b(fH&Ni+-@qv+5=vOD
+x-8Z>1vDxw&dQ@qXu8`*dbOF#wlBrK}OMI|mDc3})lZ<YtM;K;sP2xG%*W-XF@VZV(8(ZU#kh%wC)l=
+$S}=5Rr#u{NM`A_)lIDKIjU>Ch@lWfHIn^uaPsi(FK`Cjf<n{S}fvMYurPeZicRdHlGZIfA-F_gAc^b
+(GYRNyY8pp<R#RVMTfLMpvs`g1c7OL&0{;%bszkg?{E*r;&8pabHCtiTz!v<M#D?f(Uzec3oHw`h`BX
+yeDe`*_b-o0|knYnSkXdz}oVT*`fpG5jKTbB!Vk7ko{}{wDq<>#LA){YIK?d<B-A{Ew5zY7yy&-CcL}
+rbmP3DO<D6O(rqXL3hl4r|EP2H770*mjRTx<KbRlPph|%-+z`-=0~s52(CZJf1nt*Z{I8P<u$R<vl06
+-lnC#L|eUFtmVku85i7U#O?5-#WqXIWy;Tu$5^|<66R`A@FBY7eEy<Bx*yQGQsuw`Hfd%FVF7O}BFpC
+X!s7QI2K-|F(9qHnhOl`gE}ZWJGjq^hyrj)#!Zv^t)0dXZRuv#0gVnOpG%bp>Kxuzu{@&E9SeuB@ho@
+$=-u$7^pvbUDhAqM#Hlp0M&RsCSr9N7pPYyysk%an}i}Rh5HTa%#bIyxg`H*s0|Lp<Y#0HFl!tx*ufA
+7s#7z7BB}P8@Ej0K=Kw>F{-hoi)1zQK0c6JF~8T|v(huyZ<EiavtPRz>JV_Fcb&f5BPBnEXn}#(nssK
+-nVfwd7{Oy%hUP#pJfkEnkS8)!tMU?vj;TuOSg02PSVPVd-+wXyb-f8oK6GGKWuf_vk;B|uLbTtGEpt
+3AAUfRodO%3-c!YE>IpQtk)V<GsKfEHlvHu3hM2DH=Gu;ypEk8!eW&I0ia-9r2tly@R?5XpjXH`p!oD
+?g5#j*g{%b`P!2wqEs=z$50ALL=4MF&p{ic5xvcrEgU2jC==aAkSiCl6dia=}%DlCsi18kRktR;FR4$
+gsv-%28oXg4TiTL{ZY2M&+A*cXV9FG31!+TE-8ax|p{f9Ui+c@-Py2uv^}s*%yV`VaPFBz!=9MfsUAk
+a19^+e37ivBT_De+3=wDO7@2$flsdC{+z~&D=~lRzLbE4Yx7b9<fe!E{Z@)D)U|sY_9}EjQ;F@w;+`X
+l#XbNh3;obL*6Sn|8~L2dygt9CvmO1y7RXyHuTzj^o#A$Ca<_yFk%NJV!wQvF9#g4uNQ5j35kSJz^O%
+q$DLgVf>wC~@u-Y5WFLCD(+E-xezkB!yJF@9*WPiIIyQoDE`5MlcrFsyx4FeP8{2b<wD|0YiH^{y$O6
+lg2x_F+1@gH%X6=IKVH@e)B^!VPhl`nZFnZr=q_Z<Ycs&pF*Yj28Z7gUFH;#$XanRlLN>-1*~01(wra
+-q+MNjf*3-uBFtHG=s~-TJgZA7oAyau@2ad_~onO)EHO%svE_P<>VYgDD|Sr{5ibi=Yx=??1YsLg8#f
+!C2@?;bt7=bzdN#rKhGhKOHrHk0pBHyc6|nq)LV!)C^*9!S0Y-&hjxt^J@$G1Zdn_gdg{e$YJB;n9-T
+0^FElh?om1N$*s8}KxN-y-5|))bh34}e{gbsh<(Rr=^jt>+w^=+-OBsa8hNYa#>|V|q51iOMe^;pm)A
+viArA5P7L?tW&w@S(dh4~s;1MDiV47!l7HD_naXaY}b}6Y24m`zlAW3-w^Vsp>LWb!e3Iha28koy6yo
+asE{UCB`8ver)7mkt<#~zF<g6Dj!#=4gEe+Sm>y_XPC4jr-|-d(Z3F!_q;By8BLx9g8nBwISi591*Uu
+gIa1=TCs8g^FCLtr1uyHNmD%5NQf*x;A;R^u1#?jde*TIy^|1sR1?m!fcd>@@Oh@PDd9rO)GC(r@<a%
+rUP`p<vg6a(3WF6{snu8**pbSN<hpZ$~|Vfz~sg~6hF)2-30b-)n+{a1x;ua^gza1>2%MWv)Nw}3I!3
+ox2@X)d7pQ-C(zqz%mml+B}zh4z4&;Ge~7d@-$bILo3xd<-Ze{axA7BHz5Qi8)z%-4@zVdD7Wd-`38b
+@P*s7lrYI}9u*f5>0n+g#OXl3u5b+>%zP_{hl?1a`G8x#~lsbI_eN(|Wod|6mU<+f=S#6&gCfeO_9H$
+wKZw2W1<G+0WsgK~`8gk2@4ZVS+I^~7<KaI-6}Gqu+ow>R_S<*L#foK_wunQ%kr$pBqux{Dz5ol8@s0
+J*WytwA_;bmhDaqVRjkn>G<ciT&s6q0uNVtX}y2IFQ{_8mcO<4jf&oN@iFkRfPbjO<3ZCTuED=%Ho79
+h$dS+Cv$(=Lg_v>4l6@Q4qrF_AZ}IWomWn`@rEhUZFCA-hl32UwY(15i7pqRIijQ#Arsih0po2HG#^d
+NfD~Ye_qy)`?~U^%J=z9d4rA{ed5vCe)q|;(8s8X0nWdNCWDHifv4VQg^)!m1mXR3h)&@fi_tdLIM?q
+Cs<DgGV;z5n#%Q(1k8azTS|HhOPVK~i=mU%>rmX*FB%E#ApWr4J%-<RkZX6_r*P+g|b@2xnEKy-MzoY
+tAI^5_z(^a_C({0~UMLthG_FAwRr4zY(7Gm`M<XRK$Aypk5DTJXCEQBO#ileFkd?+0Z>{1;`UK)K(-{
+@Te6nl9N{`cl6A8xa}U;{O9sO9KQH0000802@m7R!m7DT}}f40AUCK03HAU0B~t=FJEbHbY*gGVQepM
+WpsCMa%(SRVPj}zE^v9hRl$y=HW0n@6(w>AWEtObX=$Qlqn%AI*(kfWQ41L;2G1DVu}$~(-=}Qcn3>s
+;a!EKeG_HE}UcIs@%ksA`U;c!i_Y;Dcjl>z1=U!;Vin1(=f?jItLAzqKdWK#rk6*nM9i)}?X6A}Npk1
+T<#R&CqjrfQPE%(|s@W}*dE{iqJ2*cVFszF;8IRr4PCEEyv{P*19ui?eNNpjb$J0ai7viSFc&O0{i0p
+*tQ7doSr!#z1c;w%wnix<+dkwD$Wd7Q6Fe0bzN^{n-?X~S{@7LBBLZ==k@_1An<Zn4-7!WKm_;0VICA
++e2WDw{YRHg+}K`~;oW@=yR>7X4xsJRrH|?H1oanNi9H?zp5>D)I9Rzd}j37(<B;hc&)MYqfP%EVa3J
+|A$tDn}3fh0~(XxM>r!*k@}t*()R=fe!?_X^rX@<JTA_IdlDwDg&E;$0AqE?NqSaqfRiud7Ix+?fTQA
+_#DQH4$Gf+el}WfR0_70@;nyCGhfkkB1T{Ira4J<4y`(#Q<|A&CQf-q~AD&hC1%k8C(ejW~ohQ*xWEM
+C=0Iy+j2zUxogWe$Db4#`WS&KdO?*cQwL^!2AbeK9NNDycXXDfUVm$k)*;7>~fBz)Ue4&~TnzymmMqe
+;PztdNAE-4`aBq2_8`85Qnn1yd5I5W>n0i6#SWRkMvjotKCU%OJNIa7Uc<r;#$;Pl><cGiK^^&&<Dry
+LigH-qvyJtypX`jJ2a`ptE{;m^{!f)1Vi-Lt9NAsl6TVpU&J4?xxo>krADc!e8S2Q5rvKF_4FGB&iwd
+#w?u_{SIqJKj}1j;hMOcXdG_yNyAX}bfQ#2V7;3+OXGYCQaE3&N%w~zk2So5`}OZ}i%q*(I~MxI9<@-
+_^F}xDLj<gIm#N9Avro92iR)Q=-(5Vq<9-A9iTFg^mktp^W_}hF_~zk|0k>FfP*nkkrp$I_9X9d!JZ`
+6Qq=T3b)lP|frKEuqmkW(c6w%P8Hq;4s$m+=TBdH04`;D#epJ>fzc6D`%o`dUAe4P|MgMRg$SVQ0F(8
+$7ZfK?R#0xo@Cs*#0?O_aFnA$`%1GQTkp|3hb}9TsPOO6rP#08mQ<1QY-O00;mZO7>QwD<0_m1^@ui7
+XSbu0001RX>c!JX>N37a&BR4FK%UYcW-iQFJy0bZftL1WG--d-B@jJ+cpsXu3y2aC?IdDkOKQ;zy-E6
+U4nLL(6}40AP{JYwz){6M$$>VqW^t&q)1V=;xySlO+XO6@Q(NL+;d0Aar{=?HI<+xS@Mc0a>w<Wv{I}
+jQ;P7W<OS72sw|4*IO26Hq$aGUyvk}=L08PZti)=?o0WU4dCl~;Wy-w}Dq2cW6L<;BNcZ+kGf5W}OUc
+JpbJ5T$CG$;NvB<7&d7I_8tSN=eB>QW_lvY_SN>(YS;`rnF{N#L|AD@0cf1h8T{c)0#PfWF<Q3EZ!fx
+TdZtf+YAT+A0#dQB^)^RkOa?pH|Iok=FgRI&Sl8N0oXbEfZvyg3$4!wURzBBdCWwO(WpV|MSPFSZwF2
+i8`+xp7NB!2Q_L#u|_nv{*B@n5!I@=H}%gDFq&b(cT{3UfMT@gf^P@={P<4>Fvp<%almU70Z`G=1Nn&
+QSheAN?xot&5asUX;fu3SB29D3Tmoz#s6lgp`?Y*=|-=uLmLTzQEkOFyVp^KAY_uv92zr7=?C*J$@7N
+REYBxV6qRgAa?JKx>o)gh;T{P-O+A1n<kcGw%_}hTdKwY9wA|Voyd={b2{CK5k<QkP0%FuvTnO;1(XT
+4jtn@m*o){4e8j}1*s|_>oNXdJ)?e6AKH0E})x52q+n6ti>tfi89ye5%d7#g3NcL<uPfs1_(p+6-`%Q
+P}xx>CGaY&BEPPoZg*Tl*obhk^!yMG3w%J0dtLQIOfpfI35Z0U!tolmSKqgEYN=kVVWHimA1@!>rm!R
+f>(Sg4-OaN^CUXfUatYvfbVwpv>*sF}Nh~*P9yp*Y7k?5`Xzhk}qE;ab}^I^k35uok^%`(r+=SJsYW=
+og|RJQY7(bh0JKymE@(0)4-6)NI(X{j>u8Po~+M|m4GasESJbnx9kJEWmPgEZ+y+1oxl6oZ(<VSJHm{
+-qhLd4%wyg?BHIZ4Kmv9J=W-Ls4M6#ZBtIUJ@5$?<qoV^`2O7c<j$3FxTaq#;8qk(;G976<eVEa)f#$
+tZ?ijEuTH9b?tHT{Afr`zssm{V02L1!|%?9X;f~~x?-P7@(q7By|n0F+VV}&9`Cho?NgP{iaZ#}>v0R
+LZh!bC%liJd@9ZjsW6;dM%mJNA3aA%2P@hZ0MT*+5xmr%+i-^*UQnHMGN741A}0bIV?9GV;zc8v!}Gs
+e0!Q_;i8lpXpFaXj6vHpqg%P;<OpQf%lL&e9aXMQmx(&gHZzt2J=<+tNowYq}F{`K_tZ2uztjSv(|4s
+BQ@514iThv(z`ctfc4?=IDJ8WXQW|3L|S;P81ubW_yAo9hBHk{E`d#i+(Kidx6u1&6=>pscdB-z(P(G
+_io{tK6U;m&7^XWf7?}SsSRsu)PzJd7;zI7h;Ncm-E8c0PK^xtJ&o4|v{s}J`t@>^4v<oh;fMpwUI-g
+&7DuKp9s|u-lL5mxRq;0ma*o=4~VvtLq+;2g9IfP0OAJY{5GlU$~qw2_J;1rSq0Ir0%Ayk`<9tJZuHC
+Vi08YTj=f|*-cLfnU0$Bu5|L69XLpTW8wX=9~2mhmSQdrEq)FdTocr~T9hslqC8Q(_O7tJl{dW22Ne1
+s<?$+$knAVaVYvYj7M+9(LQ5WeQp9;Mnaj&^~bXhZ%m{u>=Xl&pPD0F3xbjYoen~@19%e-Fu1wJGJBL
+#MDUGoRaRKFb$3fdo|*UryC`yL=D3!&YGRXFCb#CCs#+;evHM8S-mE_y>!~aRL%TR12W8LJ;NT~QNYg
+GqZ?2MT~W2*T~Sf!`)+n(T}>OG;ZVYLo+tgRz^Y{$JnaX-e;k>y@wJHxPVv)$(kyq!F7NZs_fQ`eNAM
+U078g+UV6ibYocp2h;TZ3_qOrmpvad{!#QNwBii6(-9AS49w%A&Ff`g9mDl<n%Cdc8iD9Gd}fC9&@wU
+Yqa=7=<Ym?jiD=WrWHBEughGDoo3U9pnPkttl+O~8c&;(%}^gOA34L)6S{^iq+#wecUg&=1!AE}2Ca&
+{WxVh=IDvFcgT%XpHL~YeT!y!H=e4_SOHV;7#IE64Id;^5g9O(Xrnn9l=|_ulaFEw5&;-1weCmi+F+=
+2|M!+&p;&2?q(1$W=!|O9*SpokR4{{)qZ!k0{L~c@3@XO_XNB<b@yh6$~+DHOm(sTpK-y^Vv}Sw?a%s
+157#^V(3|I%S+=lTvcnwLk8p<?l7~9L9tf0<U^+twFxev)o7ra(3|>zq8N9xoXz+TJY)sG|Bb-sG2S{
+jiZRLOa39re1EQbt**S}yXC;nun!s|a^E4-e`SjO~kVJ&0oqs$eqdJcQxwdJfTJFk;*9-Bn}08mQ<1Q
+Y-O00;mZO7>Rus?7n{2><}r9RL6$0001RX>c!JX>N37a&BR4FK%UYcW-iQFKl6Yd0%&EWo2wGaCwzk-
+EZ4C5`Xt!L1-UV-jju7AARe^<<j&TT(>FG6bsY{1X`kOHnOB6r6$f||M#02QX(bGX_|*bw&wfeH$x@}
+g7^ISz`k66WYssJ*t@&Ck3kU3W=X<}B1zbatpoh>mX}*`EB@CC-Fz-}Ti2CpL>5FW$fRzPTvhwzaVJE
+Pw5ka1XEXeUZKM`y!{i>x?Wd#=c@uRXl-%wbL!4G+Bc7T<ZaN10&7PNhE0m#X#J<jDAv&55d@r&)fgi
+X!yoEQG?oi8e+fiMVhlstADJcGrD23upr6TqoOpn-2-N>rsMa1sfx?_Kq11<mN*%w)(^oZF9>tZeIIQ
+b^ZtWt5!(+9o<wQ<|XLicX)vMOcD3;8UP66`(ZR3@}K-dCA$oR>Er?yf%EC716$fB0|m>H5o6#BPPIt
+5Og2ONf&K7vjBWc*Yy<?AGE9c&X&3MK2@vhuBx@@F%7!Vq4MJtYse2l;Bb{kCl3ewa^+!I{6=E{mFdu
+64M|W@2)Q1T-|<(nBq_ZNnWW$H@s;zd}Ccp(p_6V=-F(R7F=ugLIs9bPpO~;&X+R=KQ%A_V<vJoQJEo
+zf62hth`~quWSv@i?#$WZ_oL_;4bULBqG?shIP=5Cs?Ardc2j;k!L|~z%Sbo-eEUA05&PXvYSw~Eato
+pWez7k9tf^R476+D#Cf$(~^pm9L^pV7oAnXn<ORVxP?GgLh>V}E3YPUNEp(Pe;7l_^n<N}l16k->XnC
+qPB7IgI{a3xq-HLQ<u^il#y26#l-v?38g@b9B+b_@{)TIL4u1;vCA_CDfs#x;A+O<eKkC-xSMR)S{>3
+Iie&_Mz_E&V;8FBGc&hu7bZvA9*sg5DyXk<{RMPWd^WOfLe6R1hIneuWwkbs-{Y-BJR0Ox>kOlgwJ`5
+brXT9bCeI*0!1XZWu=6t_9BP6??8)L)MDaE0?3e9lHxHy*f_LO`3;~UBR|>Zz_5KvOt~{knR=UU*YMF
+a^AXHYvCrpy8;vs2S2KonQOJkBQue&AMTP~#`wX}N@!C2r__G{TGK%?Gn*f!KN!a5~!ds9;1*MHvDAU
+|L*`&v(%ao+_)rj#!Raz)8*J8|f%QtHk&5BYs62r$`^l2Ir4FF1#AW4#hePXmI^6wxCBnHte(U6uUCK
+rn97}rT6fzF4j6s{q5P};y?<;M8YbPzrXrB@bC=dM;puo@zzdkuvk0EO|(*bpQs%pA5_v0u;529Cvv?
+p!b*ZR_Hr^T}C9f$-fONh?IT1wdF~5Xh?7I<XEeO-(G`6G?DCAF)yet|o?kIHCk-D^uQx&{sK@h8xI|
+rvDmDxyLQ%endih$w?ZSvtV;*gboN&WXXJYV(8N_xJYp@EvW7^E=tgyBAC0>_Q`s2z6FEE!cG}rb1?Q
+T-HG%ef%OF<L$Ce?7*|8e4}BTqjzRIEdV{)kHbJ@H)WXaZpo(07^5T&n0BSdJhwdIQ1!@zV(nd&hQrk
+xk6#<QoP1}|bz2bn%G2c^)Ts0Uh?X`4Z?=)?ysu-xULmSW%lqm$P3<foaGyyht2xR76@AaK(C+)!Ro$
+|B*<Z_ya9Sq!;_`Zk0fjrM4Bjse)=ympje}7uXIz4E=Vfs!a4UuyP$7yJg%?GW;xzUStKME{hR9j;j2
+@r_FtwDCE;1ssH;oH5PBKUIw)rC_5wk0Xb6sivTizMNMDRnJUnM(k7SPd5EZqUOK#p-HdUKZ@?<}FPH
+qXpb%?5%jDi15-y+?lxN2b?t>J*q_+k~Ruxq%8K`?4Pshu`DW{b?~?6Pa!@YW24uc4Og%R^blyk3YL;
+^9u45p<EUyNv>aVTeq(104hVwnWf_uC_K%@KosyAmYv);H1TTh6V-)FLhSqM&b3T8ej7-^(ut6#PSX=
+tl+j0MJLn0d33a;{8i-u~LwlJu#uAtAzAb1`&>y7{yfJ$&U&{SH|`aLXPSU?{c-{`7n8_^SaHT?-Jpk
+<!a17`tC#WzO^YBPz0idGhDSI_+mJ6p0(lr~uVttlbu1@CxUG;^qJ5XJPaYKshu_;>K<pPqp8CA(~uf
+}!ekE{MlgeJQqNlF#((l3jtHPN(5$bql?A=vk)Q;<zFx4JHCz?7iBc>hJ4foQ7K$>vZJDci_x)m8ZvF
+2|7sY4*lJ5N6bE92lX8-l_n;3TA9<GfvM5}ikJWEX#`VNS~cxh&wl5<9ao~%<<AXlSy-l-r}B1Kozz6
+A?X}r*aT@mUqms?*diX5|WSYtjz3}&FfmZ~uNcSRx(cvUmju44Vbc~ZgG|=!wo4U#QFXAa(;w8|;d>)
+E7Tu9#y;?X5kuK|$p;Oy^jmDVUdV($0-RHXRPG4VkNy09`w{v$lOFb7v*x)UEaMU~o9F5B?bpbf085~
+_NlqWr92PY*^=|E5ug;evXQqR9Ghaui;SNJtK~I>`0v##=>SSdEZ|z_lAWc9{EffHQMKhO_9Px-c56;
+o$;il(QE01vC4gL6v~Y!Uc-<X`F+=Ju$K86V4rtLtvc`$mpiSo|&*NMp7n2+x`5|oyQ3YgPV|3_aE^j
+v(;g9bn14a4>?`8dH12yKG7}Q5ifwiH2DVXewg{ag^-tY_krW{Hf6z%bV!AL+Hg4c+9TMKE_>JJOx`F
+&czaNG2kq`6b*ewjm4+oS7a_xQ7;U$vxZo`qF(^!H1!(n+iqon-c+J+Ie(CHNppm&bR<8ac(SI-g0?B
+_nxj(VHn>RO0K$~Xb!i8@4U}mHZR7*+=?6Iy({C<JwZB-Sd6Aq>eqCPPky1NHF)q3{;-35gG8`(Lv!c
+ELafxS@MS7y+h%jwaczv0;>%wa5D)USyU=l3h%cH8kHe9{FqK#J}!n;Nt2JGfO_JpuyCbqK6;Z#Bc7#
+DjwsIN(5Zvh;STdWjl+@5ry=ApC?3xl~YVc=J~9n#MziL?8w)e213_7_*@aPFIozf29<^h6`OtJc}v%
+>)~wPtSM2X?mqG_O#Bz_vIKd%BM6*Y*7V^X&Mij8dU@{M_ZUpaqskf{k;)jbUYsvIGQ{?;5qm&r#|bm
+Eb_Bn0c>2m<wL1nM8gEQS@ZO&so!Jkd-hB&VB>Qbe1$#UsQ3|}7xN3S;xbT9>1SVqSxz|E&{G4o_>FN
+5Wo2lNB+y^b-Op8{-CR-c^0QQ}EM#Z}F|DhLpZdnWG6UDh2{NFEhF`AgE{rHZosn#F^DDI8H4GS3)gS
+UtARqxSox||y7K689@t$IxB7NH6MJCA79Fbm1xpIu@1d15D-9-7|biYvMZiDN$dKTt~p1QY-O00;mZO
+7>Qttz_hi7XSdSNB{sJ0001RX>c!JX>N37a&BR4FK%UYcW-iQFLPycb7^mGE^vA6JpFUqwvxZ=ufU_{
+CQ>WYPTEXc&*)}c$H~*H6MJl@og1Hrfk;R~O_6*AX<5zWf4|)YKmsI{kDGh%r&Fi0h>yi$vENuG2!bn
+F+z6#)o-v*!Ow~n^mzB&`EY1@#h3~B5GQ$R*rmT>~p(;cymogq@qT1%=11rTpYoRI}yOgWC<dp@t5Nr
+M@^D-O-K`<K04FYFk!(|%Ql}wdwl6mv1;7L*fO19xom1p*Mny*%XihbP3ji`2oXvXHvuOj8uGA}pwS*
+>xs=BZv3Wga`Ls9p23F4I&l!h)Ad*tRV%kp^nCEb|S6HIX2uZ#-h~x&5!J^XTmF=V!mo-@Tbq(`mNTK
+VHeW(!bt_OaOiIQa@fuWjfyS0%7Wh%K|CLQ~h*<<jrECpKj|SH9y~HFlsuQj5JnoHevKAvLr7pYUX6r
+)NJa9-pDZK@mk<1mw9TZonhOVZaYnQQHhdq#iC!i5(9mGpmyDm>k-OAes%u(^!>$cbai=o@$1Fq*>6*
+ZK))T(-*0cPx~MsApMkUizD^rBSEYc17Rj~lp0aD9iadjp-w#1mWgS;FFlkFLCFU?GQ?ine0?)fY-yA
+^*#Lh&FCtTzX&70OMXx%?sJjH_8qgfmmjsY99g+DZ_woGBiMF6TqNsl52yv%@Hz-u9h5)irKcKAwEQ6
+iSSPOC^{kFw0OjmWCOsYKE+mDz)xeF49Rh8mp_^152vv2S4s`6>skkijv^_!Rm+H<wt}PQKww@mi*uF
+Gr&THa7yTQbsW1d{c0E&RK=CGB_dLP(6=<azM$9<ypFeFM*mP7U9tPq_IK+&j46+6;-L)KYRtJ7TeMI
+8&6^X@QqZ>=tV8lB!YvFaCijUPxE-nNHLkG{eWOv!yyQw$|FE~4N7?F>#7sdB?Jd)X32VUfkG~xs!`i
+N#E;0s8=mo%XtWM8@LSz98jVnAL*L9Q?+_U4g4)JWl<|#-BG6zr#KM=Qgds4NwA>vC+LY0k)rfbb^X_
+1;)Ny}*KcX{VWqB#AmS!cFN+fK%78$D*wj3UU%&JNxhwEHb;mGRqa4AzDn|&Myk{|_O_;@8&dAXYnix
+;3gx;a04e|;WZUeDjm-`$*$HotQ>at}MXBk~<Eus2m6=joIo2DooHNuZYLzU2>qEK&Jv4d3FK0&W4Ln
+lG7NpXCHovGI)%Cv06+#mUjpLRMkAJ9_@la(DCF*@U2t1MF0=iQqf^HJO?YdIrAXDPl3y`TWIC;W7Sq
+^z%^n$;tDh=P$ZlKt*Afdj~>fIu3xNK*|-k4qLucW+S1Q1bse=`YdnPLJ0;snK@dAJ@QiWMG7jn0KJP
+Xbh>4o(TUet0z8I;@>&6qvpHJyN^Dff*lRF|0@OnT1b7E1><j|c03uz(x~L=UFo1(-$Sje_4GDk(<Up
+aMsn*oMaEir1Nx+2k3jkT##o*vL%j(Snq~HLbioB>(UfMOM3`VDd;~9h6fdRPo@ScH$fLsz1d8FYC)5
+xkEnd?y|LT}69i})c9;D)977O1nxfl7#<rcYJ!C3tZ-{c3kLr_I%Xl_bdd1K%;Jak8src}3c^6l=6}j
+{@;Q;%-p*7Ce4fmAD3w*K()=7G23|T`y2?9u>QSAAuG*l1hOv9liYVmtRI_^XUBD@AK=+cW=+%-A2Ek
+Ue8Z|y*R%C;Tan?I{ga;0DM&eHU`{1Yz=;WKfibt(f9mSU^(s|B6|QSafdj)r$zC**n#`S&SV*b)tJL
+CuwH5{iz#~}tCTMoHr_x(p?T%D1RqvGtA=?tZ=jt&6{(DYU_+;-**v(KUq$nqh-RVE0Fw&mkw2&?l@B
+6{<#@sl{}T=;PqijSPZ|GS3ve+qWOF!!5|4$ZF`TB&y6Uk1**x?h9I!tGOY-bl%i3V%*Li|`fnMJO&P
+9ghtg3cwEW%Z26sA-hn#PlffwT}YM<89n0T&#2$erJiYhqZ6<idb4>nFKTh?eDBAPO1gN90~~+co=wD
+G-u&pU6^+oZexnX~VPK7&R%`ZxxzTpdH!feavN#0`^o!V5zc7p92_`!DHaqL$*a21%wYsQiQ+=f=_+)
+rB2B8*LDn|0kj7nsgni*n^q81i84509|Ob~egtr|s1c2?1}%=?_G#MAE_Ogl?6;v#s9Wsl@x&PnmN^y
+3o<vw&uj!+Hvv?PjKh1?`F!`jt15gyW-Mj8O_jejHY<vcib7fF&pzNDuH;)9{yFG#e3gN5P1{Jq+76w
+JMYsiW$2MYm9hy8Y7S`0BynDz`B2(WB#FoX!G(BbP*q_ixsHBX&&_pRM)yF2;e{+q}YghBXcF0-+>7P
+8*>X+k3Lg!0f^s9ojT2>OriS%Oi?aY7~7n;IkQfBzxRLHc_<_AkQA@;z~l9R>1SR%#16YaD>3s-J>Mi
+^#qpJpuDt=A&jDO^m2jE^1PQGczc}&4L)($5zyB3ubNfpmv|sLx-&f6cRWKmCrQVC-&P2F}_(OoIRbe
+r@QC((_a5yvKX85a1<E)lu2+u9oW~zhcOxTe^K=Ge~%=9b#Wx@bZ7=9@5@-hx#M_Wu3b9Q3Nf(|{%|L
+H$KeAYhSdGReRJq~=$9ET;pJ9l!Gv7CX2gb@ZQUK;cNMR*RBL}=!sU%`fd+xKs=vjCoPzPhUnf+eGKm
+Cm`e_J&|M+Rr%5EP-AGp!2-vHgr@E2&n^jCo0t--zQu5cH`MePG=Mm9i99>ASz(=HfQL!1DAMjg0$0e
+-YfBUj_Vb9i}m{tg20==byMoB8ECJq`9*7ZtdPiew0e?#a-MCn5DXf(DdnW(SjolR6NMi;n?ZmjcdE4
+_UA-9Vk{OIU15uui<trW8hK@!((95!NnkwUuuUm+kvOW73jVXGy@`d1NZ}5a+yM)q9EwZs&r>8GkC}i
+oT}XUqD3&GysnBGDc9zIL-K=7PhXqd8GJz;8U#>VDB!uWoH=lAZeLx#zn!v5ZUjJ^9fvRXs1cpPgW$m
+=@;crDcTAK>mGHZPp6*^;1+dV#GS}v`gvH2Jd)Dav_lYXi(5w%OXL{uG@a2o}IUE17h<}cMe6d)t7so
+H2A0EFvJpN_!-`TSd1Ct^85Kj<h#ufV$fam~3CP^yTSi_rOGOOxM)jX&7>9U)@bBMhv*fi`H6n&ToG<
+{Yg57>JMR*<<^$ti+>AS7e2c}g)1$|G_g#J(#GIx3w{EX_@b6R=>Q^^oOTW#VF-wGb2t)L9#ML7YI#*
+zg%6|1@O~Yilqvi}Nf_YmAzKu@#6c%sEX}K4n`BRG`ns?~gpKeYCUOfYDum^@cwn!!r;OiKB8tQfDA=
+GsM-XlmJ<sCJ9F^Wn)R?ye$Ek?1!VsbwoQ&OA3)FGdy#mEYvY$if-TEoL@($Z!o-~pRZ1DPg^C^&i;&
+gX$BEq&C|#Y_JWTzwh5Z<@6dYOe>&>58<x5M#6IHX(WfBPj6e2Po#9t&>T%=@zrv*66lzSppdx`m@xD
+gQ#=(>lV8H~_M`aZ~h@F}t4UNNqA!VF`__7O3u)V%9cM)UfhQo*^MxGEuCM`w~G%Q<W%vHll?|PygUx
+9kuoKW5XNJfm^_8KL0(#@ML)0|gRlU+3r^ymH_36Dq90s%70<?cjZGu`1rI_GLQryUrJvcD9$n0^{}X
+c17KPf{pny15B+W_gn+O1GCZPCy6ZLNWi$&32CsAu(G$89C%t1q`%M9A6oGP^VV4icp`xs29h_emB5E
+UDQHu0r%_<f>K&;@aNc~*|P?hH|J%U(_I#{_&^S<;-&<lH5)d|%~9LPJp6T62{pfD`QlFzSJMsz&=59
+h0xF@xYcoL$Zb0YpRmaK<km1MUANxa$iJno2JO<Pzq0Q+J4CY%H*<w0g1|J<LpHA3EfB@1eGE(J1T`h
+kOCJw23)^L+2aw&lbGxt*2h&xEI7}Ej3R-z5c#1wVQYEx;k^+4ejD7X_5?gYR!SIglFgGOp@PY>K*(C
+sY1`;jB?3c>B}?{_VDf;X14q3glEtMRedf}h|_<8^oo2!Jc@qS+5_ycriFTUBeA)6hW4zxGYK;Ho-&Y
+sd+6EM@z{KXu%ieFu%sZ9_3ooaG{z^vA|&t^|pbo~RpKQ6;9u?op#UY0MZ^CTRoTqL2e+HF4D5V;K$n
+RzAtBN%7GW3I|UT60Z**&>@fYln)<}-uk*1WwTt>l;VZ)c-PGArF5uKLl+C+NUg});b8cHBe%RvfKzo
+Q6TH?+Ur5p&u(?1Bb#@=j7&;ua_5)#DvI81QuqiMN{2a`fZqd@i=HPJA_k}^2orN|q^_tVk-*ztvnoN
+fV3v1^_=fbY(dW>MfrZJTd)~U^BHk6Md%+p5EKEw5$W1(6)I@&#G4<zVYgYUk305Yw>95l5P11F42hL
+HnbhfVgW9ak3^tA-8I7W|~$5cN2BnEN)?UfKh4c>UP)Z1@w(Ri|~4=J7*gp8I7F&X#fYXn5a&bCv3(v
+?zA#(qPcNB7tb(`@wQMIhghVPP#H^$=M@WH%EGhm)Q3n4i5Qd&Tn747)s8}U%!(GI-_sD!y{nZ)p}!2
+S;%;gKA83jNQ|TADU*THmoESum@x#{UNO6v_HiN22d-A69kb7I>Pe@Zr0oTF<%F)(zv$-uul&3HGHaN
+}-2h@r+(6|?Gx&dMu$gIpmR6qO*Q7_Qp~Kiu?*FG9(ylG`8#l#FroqsuA2@(kvwHd)%s@w(;Rm!xNuE
+AH1c1j5jquo<B~6gwn+8+A5n<f|0I@}JcCdRlB_S$*!nzqZtf1nIemFt6|H~|uy$i(82}Y8e?ml$cQ<
+IGl8`%~cQYMVb9I%(}Wj)P@D&i&_T&!>UNISBQ1;oz*dj}4hDtN5(AiUCPL+~+VwWj;XD9{NUaFt@Ng
+swOckJgpYP>LKFX^{#l15LrjRT==oT;MF?!O-KF5P@5YnEDn|N8^Zx$BT4+clR#-r&UD-7j=nQpOT%f
+jFW~-8%Fn+HLm$xfa4Eoe4BYNx50Z>z~VH#{WTR9Yn~;k&cNVmN=uW!8r8bZ2Fu*WEw9enpWfPM5FWu
+{;M%t4>Ka68$0*|gB49kdtxQwxIx@U-&shv)%{O339bjwd-3o)X70IwGqdJIgm-2&^0}wtPi&l9B&ZD
+kz!K|X4PH8Akxjh+E%}Y}v%(D)xHGdSL*G5oh239wYJ!LPCe=wmdU8rI03KisP_jn_CrrJE%YY1zg6$
+DdPWObmmt_WM@$lqWw${OrOg1k=IxGmp>-m1{CqAK3B0}LFn77vUYz)vqRK*v%WctWPsAXE;A@C=S?1
+%U_hB3{{apq2WJt8jn-$KWdMn!2POc);*<!~cR!-Tcs>{o)uy*OxDTVuxP@bC%|H@){0McyLT+0Mt_~
+usCRT2RKcUMpJ~3Uq9XVPA)-Gs125p^Gyz63bG7_8t`|CNr^3{DlxeaM6>pZ_0B9W6D@B>1px<bHlno
+U7$CuqGVZVxt^$ihOOAou>^OY!((x2~cl?gPT!PqHm%}SMPNdScS)_$AGb<BP2_c(TRN#VI+ks?C>&e
+<7vJDep;3jq97}CZR_ObWZ7mj4o&4`@}oMx6!D1B^1U*!%gSLjV47F8Y^;ee$d1)P8Rpi@Y+bJxHeu-
+l6p%?a8Njok`LHEB_khCGo8he3M`Ike!_M@FcvaC>_050o{nw<9dZjkI4tp+9En6a$9VU_ri?qJqw(D
+T*|f(t(G}fT$w1%qt6et7adeu8x9nQrYq*XF8A-l-0A!o~$s|L?fds>zb{nyCdLd4cDUPz|u%g>0)+k
+OR{LQsABMv0yez>(~IU4IXjn%t|5e>fvX-4NH%1Nr<c{Be+BS6sWAO+LNf^fE#;G^LgdmoTfR7Vk8jA
+g?&X09(9A2p9#dQA{v1C8XWt*>xM4Hr_rBYBjX4Ibu1ht*g#Z5Cd@g0#BlZ_$WV(+o-$043gtlTw(?}
+VcqG3=Ilnii(PxcPiqr2ceu|Cg;tFb~DRS>#2gW${n0N1%anK<B34{4dsI*xRo7(7WldW`XFN@^JI`6
+5$}Zc@QbXj2y`>{08CQJ!(iGO>-^z@mvKzRvCMPJbu1I!+;qQ2wrHv<&xrOmAz}-$d7XkLzz;&ahn%c
+)&-X-EWUfen>~;)=@7gs~Qaco<OZfSpRP78zLmV;=C<Gb_$%iK7KM`c)N){0G51%MZk+rk5sTTk%V37
+b`z&roBq^orowYdTxK?bMx_*uE$Mhc<aES%>x8Oz_&7l2V)WLdj-UBbD<IS|!0a*lF~*W;N_@mWe=9%
+vR}7c~)M)Qb{8`A~BWN}z^YBqm`ZV#O>6bJ@tTY<K6i4LfZ4=EJQ~N-E%*=Zcg`~?Xka8v>ihcCx{)+
+vMSK4&<HC_g{&c@LJVjCTH>f3R1_!w3=RPh!a??ZP&G(x9-U)b5#AOoX9UKDt5yMLX@pmO!S(V_Qxta
+<{Ivk^1WuEB(T&w`^SIXk4?oqXrOvin#13eb}-4?Ei&pw_@fzkRbO!GK?|7sJoF1_$gd#TeilCowM*d
+f7&MvJ@tu)arME_Uz;fv^)6%?HUCu;W07>(r{6Gb=ABN>b*BKH7XUqoua*+6ltQpJpa|Bo_*A>7JWUt
+YsmT)A3Yy_k`NOZExo!fgqYmfo$~i)tR=o;M72%yB4FnY2Yo!R1Q2E;GofEI!HcRg)t6P=zVbvNseaX
+0#9;cQ+H@3Cld90~>*94h{TO3un#IDoL)KVE?b}$ULGRl3YW?OjvtBRMJUbogYF_Lb>O`2{?L<onyf?
+H6*_%B0qlB<;;55A(j<JOo7rvrsA|__nAxe=e2`sgvpcW$@)R^`KBMa)pjjRtSuLp5b9j|dhu#(mH`u
+!|=FA_1L_q9Sco`)iwvP*2%31`Mvn8I{pU3zN>-)z#<3ir|<?}`1Eu+)WJ!S}HE^U2-eb1&EDaSi6g^
+mJWw<-I7!7CWkJ(usjGuUC}7bK_!A3s`B8?0M5}ilo?zl*%`;BGI|r&FyPQhJ5DLcZ^6g&CORle&8zz
+C#XiuChI~^Rz1;a#C1qxOa`NfmW@q=(W|Ccv#|%M>qB(U<8QMrZ2j*7blPATXo$YMfw76qYT;J}^vYu
+JgRl8xY+~Q{4?#(ppJPWTsm`KPIe;Jgj}LSpnC7uV4}Y$yw`tvup|Z#3y(!F2g666~Ds&=%nY9?bHKm
+)(n&==8z|u(`U64nNVNTmfP4haa3VV~$q3Jc^$Dz+)KOUJgCZrbt#}nst-R8X@oU!J_dqW3mP4Uz4f!
+o**hBbx$5Sq?i5+e!@ZC!<E|BZ+~Fd(q`H!JWBV2F~WPNdkE$A^eatZ4j0Gwuu9>bM$b`gDDrO=hdBu
+g!}6V|7iBBZT=td8{jtX86$2bcZ={g6}tdtr$}dQYQ{qc~yywVQ@6X-DVzZn_cT%R9%+tMUe*NYig4h
+Q|r7=6I*V8ak(EaIPIhTI8`R4SLF1TxIs>|h63f<tgjb#vwoOKMJn-_)P$^beVt}Z>rd#D=4HI5BqB{
+(gDgD?*StVX1vBkC=_c!{-zYZ8RxdYaLNGJlXOQ65H|&H6I!YD$4`mOQH*sTQS#-dJyY$&3pp++JKpF
+2OL^2ZDoK?`KK605-0_Rb3lj?>|bfA?Y&Nmx~i`Xu&$yv}NQNIbEfD?hW%v%iiZ~)#qQ1O1;gG4A;k|
+EyuLJN-}+ihVUT`4~EU*`uJJPSL4gX`9Pxnt5RIMYds#?3X?5yrdKZ?T%JNK+Ny-g^7@!+UC057;T~P
+Kk=%Cgsf3=Gbd^^d)%jPH~`=$BefjiFurS#Y(3B_N!Mi<Lyf3(Q{{CNmZZ%(26>)Fh||Jh3%9SS@LSa
+5={*`-7D+=0Z>Z=1QY-O00;mZO7>Q?wHpV)1pol)4*&oj0001RX>c!JX>N37a&BR4FK%UYcW-iQFLiW
+jY;!Jfd8JovZ`(Ey{_bCKa6cplY{N~OCNY`;U6L)ufNW?|3|LVZlytH=OQJ?naor;SeRrhZ?KErW4~|
+0W?w)&p9BY+=-R3e|f=qLzEnLaaj^S6#Pz$T{U=Z^=xy+}F2h1X+ryBn$&{#7~RfLJD1TTNTy}!P_Ut
+HdNxczN$_wKLjF}z2UtIS|qi_9$QOe9nM9Aa)I-B&7Z(QcGpU#cv_kZ-QFW(Y6feuWULBvBiN8mctK%
+o-3`1UL8hf4~YwgxbIcHG<M|Dak^z1rbFUL9itiSBj1zxU)qZTaXznrFEL<&(TqM^7`o2(Ybj2G6+sj
+U!ES#j?eMc+3f7}I1Y}E&!gxpoE=XGFG$m$2!%m-8#4aMbr!0KP|ZO`1WMX1p&=9jhJs(K!UYk=qDbh
+$DpDexbm>j5(HH`%%Xpb7c`OYC8pYZ$SOE`0OC;qghK<-7QW0TJ8DSMFgO%EVr6?KH52%5JLzTsHS!j
+$1Hca47rPVbBN+t<p%E}N)Ojsuy%LGX>JFsN0f+d5*-;fe;5qGi)iU(|@M4~b*Z|#a60Mne%QZ6k;rH
+<0~AtALCfoR)~5!rA^o<uR`taDVvj`cY#zsS6-mOW4uyIx`u+19R{8j1#)sy(-2O}9-*81z8{H9*XIc
+<X<GYE3MK%*O86pe;4vvrvED^6Rc(ESH8=Rb^53snS_TU4U3Bp?)}^Qe3Irhn|EmktsEY^-&{Ln&1h8
+Q-B+lV_YO&8Hq&-4Mzj;vou^1K2D@(vy$P8zLC3##zGm6PA<vSCllymMtZiYV0>&tm^A~Am2TA@z3uZ
+_$DU0_*or4<36P{Xi@q7E#*=ZC8upZZgm>f<r<fDFCgB58iQFy$r!rS%wNsc<PO=L$Po(MK=KAf`_4~
+WIn~xuj)nlNqPjCTWhrK~CoWron#PD%27*OMb7SiB?a4w7$wlIg>>hpR)j$rZ=+*0w*2UHKRvNm5J55
+GlfmSki&bm!!fG%_O<S%^*rO=Dpc)l;ywXhvR~KW<D3Yq<^CAr4wZgUiN~GYYDvgjRtvtsZE}hbyIw3
+r3<sk;pHuWTXaflKm%dX;i(7{p4}~w-oqE;w+A-5+UX`3PiYOozkeu+1bhY<fYF!T`4ZRmV8ykW?COw
+y=`3NPl@FMTEUolUk``Q^l(%Q_>BV}GRgN>?k%@szC&k&yHrdo5F7b@vV$sjuVyoNQ(pNpSh%FTfs@&
++(Xo^L!w$T7__eR$5iS!+6$joM`05Qmy3iInaVI1~kB`Gz*=SHYK+sN}g!cOXLc8-D=|`Xuu&%{cpt+
+%*U<`*{p>e%eFZf|pwPbm?2v<e6Hr|u!uxZUPxch~n2A~~JLB80-bq213YufbDwd2^ewEzC(p$~_{U(
+1PE6NAQ5uGIsL4%beRu)>=*(_z{Fo$`MHcR7YqB!0G)@l0fJ-1G|{Ivva*D&MABY$!#Ph_su&#?f)-y
+rw+92`H~_S6%!fsP?;TXM=vk_T)E$;#Q(_<CTZEV+!ml;qmi}#h2I@cHFVyHg4c-u(Jj-!(mf#PqMbi
+Yh%MpAmd#_N@VO;X1Ky|ZHlxfSh>@F#c!a1&G_?rN%is4%4!ohu`D;EThuBH3+<N^_5@4rM)bw(AulB
+t82jzp6ZKrs>|uf%(WZj)p4|7+!k#$n(!_65#2xwnKpB4+@vgD`Y-A7GJ)#Z4Wi}W^Px8wh*^<P4+mC
+0s=Z?}o7k!3@?hX77FRf_lp5laOC~D{Jo@}4IauYV3L=;w~f*f~0**1N{#9pz>Txm>FwWX~IVn|a~64
+{RUzKPWgw^6qpwi4+VqML$#GkU)8))KP`3ft!jG=PbSMM8U)I!PoYLj`}+CTc)Xvr=yEb%FEUSzGdid
+MI<|4x1@F>PXPY;JCT#t}gz#N%N#P{{m1;0|XQR000O88%p+8Ew6iDx&i<I{{{d69{>OVaA|NaUukZ1
+WpZv|Y%gwQba!uZYcF_hY;tg8E^v8$mEUjEFc8Pz^H*4wCZ$ql-Yb=tX=4bODv<{eLY|vkTZ3Z<+u2$
+n{&&vK@21d)EjizPeg1r}E~WHTDO(px?pSVxcD1pd$f{OQf%d{nqZ3MLl3*+>DRVeTedu2st3qiltb;
+z*Dl*hWg=B9{Mf|zOBGM(~U$^)C?(zQa!~3Uq8Oa;mEol>LSu-xR2djl*a4Mh<Ex5k)3H+<EKktmzP=
+u9xYmL2DtJ_TGz&Xt81-7#O+(!Oa)Oe|eJ*|)q_}*CV5J=;Y#eRN<bwcnH^=60f75JlZK0nux5&j8L9
+feY27Y-e8f+d@tD?5Py7-K2tT2#RKDoK(;3FkuZU!wfrR65&kba2&ngvM>Hd66X$L7uNT{d{3Hd66Qd
+j+CCGklFn}+^iQ(;zJ30!jYZyoTo7oJ`U7ABT|=e;y4{^;=IjB=fZlzKO+rdErka!D_E1AF$zIE2!*2
+*lvd>SEqO8;)}we+BbgN&ww+3>hO~Bf97^v{aXO<6U*bbLbhw(e&bTX%2n6dUDy$7&W_F{s>5n&ZvGA
+(_=P$4fZ%3SmHKD^?(8-d}r2^Y>8={>a-<k4^sLmeTxcCBgXWRwCY-AX}VBhF$^k_yHW8X)#IA9RI`c
+7&bb6r3hn#@8QBcUE?Iz^R{HnZzIi=IvYj`fK9iXn||Es5%5vbX24y@&=x2{!Eio8k@NacXZPJw)l@<
+lo?g(?7Ek3pnT6LG)<i8LQ3Iok@S$B8c-PHd6zZDP3oq?*B3YDT1grxou#+xSF?nan+=K|MRqXl+JZL
+S@(2taNk(nW=6Waml`yg6|bXid)NNsg2m|w33EHTiNQGQC1>mH-Np(ly)1-U(x#7jz9kShxN+q5C>0R
+A0DbtaxN&reak>|45%I#5u*_UIc?ERx7f?$B1QY-O00;mZO7>O&00002000000000a0001RX>c!JX>N
+37a&BR4FK=*Va$$67Z*FrhUtei%X>?y-E^v7R08mQ<1QY-O00;mZO7>P*l&{*B2LJ$;8UO$x0001RX>
+c!JX>N37a&BR4FK=*Va$$67Z*FrhV`yb#Yc6nktytTR+cpq=_g4^J1d#wmXcM3hF5H)F0|d>b$Od`YE
+(BVlZPmJ!q;}&j_TM|hn@CCaZju^EuqHWYhBId_^m4iULaVZ%vTPgDZb`v9))cJCOD6DpNAm;SF|k-K
+my1PNcP*EsYInP`*)6ubt%*E#@Ha7AuW41$O~n#&S>`e!?@9sxf1ouhKKC82f9y~ftrBv@U`wqoG*nl
+1X?6?xTb^pgfShvnPhWCYvqlQ5=F_ltPE>R(FSjM*PVgPu(foL2*Ut&}vaFokhnCmisDD|3cS%T2o3<
+%)wUjlmbPnkj3_$+|Hhj^G{?*GyG7hdu3-B5*H$8gFnNZUM%lw^e+j5W*5`3QVS&ulxnn?;#rWS0+WL
+B^(?JJqF=C<T*^O$J5p@LcYOV18_lNnjC3jbLvt@K;{bv}wtSOp*jMsk*Gf*NtV#EQiNxyU$KTT-TQv
+v+DO%2Z&oEM6=Yc}0aFe`+>g!i@kr8fY1>76d*fP^;PN;Q>EAR*Kx$-X(58(FM8MgN=LI6k=iY0nx!g
+Oo;0-k3x%X7Vk?TFrC&qF(&5&ZLiyATLJ1hftj0(P^?b0@06M9rsmvDp!iWK?<`90S$_D$1n|z8?CDR
+)2zt<ET;!w%--6J9iZK9UlbkakNM`C+CV=lqG0Q|&L@{~s+YHvGZL1qi2dH_V9Y_I%hms0zqe^6$oQ-
+T@b3jP3Qlhk{8jQYw(2Kl<>R977-q1=gwFn6a-%q4u6st3k>q;{y#PewhNitj}s0$*hTBuA}+f>K3(v
+lEyD7$qO8=m6_a|5)ZVCt%wE@k$J<j3LsnEse@AR8$FWsScJssc&R8P}-e2E<3%sDN%QMSZXViha#lC
+rR}2>UYjto)G9>JyU<jgbKn!doRdk+dP**1}gRh3P|4oEedQ<1pK+-?SVDK6}UiF7nbyn@&>pVEtL|u
+2UqzSG$oA9GpGm8#4=HSO$ZxZe+c_$-fItYCVSrao=My}OJd};&*5mytQGOOEB0+)6<N7!TFzFk)n41
+Ke0>cpxiK8a5PWDGwor-SrO-frTqETc_-#}YBy%Z94lILkVc}MX-)=+Qc&3Aj%Zh}Q((I891Ek#8LZC
+)UBB7~4a{1TN%!K-BJcPN21~b~E)-tUXW0O^?n`VYMA_Ku}==+i9t5{3buEd(0%!4uti!R};u#TzyRw
+%+^B6{GM0yWTnAm9bGxh>R&P20;;b5)pc#xhJKU=u{tm0Yk3qd$<!v)McD*IFmyWXf@n(8s|_<eL?Tx
+da*k7r5(I(L<02z9Y12(x6QSD5mO6#-|7;1*LT{%3w#rQa%^fMZp=^Q?N}dM?nd7TNks!Ps0%s+EG(}
+fSCd~jF6ZkQ=kBB5K7rCR3zv;(fyKrm7FeDz}JU(PL&ov4Q*qa(xQkW%|Xx<Pr;_K8Tn4`8E4NilPqz
+9lXgH|PwTX;$P<r)XYkrC)lxKqLPv^R4TmX>Gss)P#2Wn_PwzVBv42;Gqc83AILMR$)a+dQOjfx7Lm4
+!EUoasDc3eY6jD6@yW{tDJ?w(RH2JqDQb>CQ$_>e)_x0Aiy7m;l3qM1FXbM%ca=Hblb3i=z!SOu<LY>
+E~`Wjc}_r`?|1*;+jmc|y0);K^SK$C!W+yAs|yK`(R#S`+X}Qkd8EI}vo{J?97q0FsScSwb?b43E!k2
+HRYIc%tI6GCtd|;XGhwqOAK0Va=*~O=RuX^Jqe*o#KLggb_-$8C%BTp1G`!FRa(3Q~#?m9dhh$56!@i
+i*WB+o90%*B6Cf*7EKMGv&e8Ka-8)2H#CR&v0+XotpDqZ)|-N=a=HqNsx#Cf#adr%ID6X1>ey4Lo17Y
+K^n`*9E_`A5V|v~75?U*=%vLk+=L<t%kGg|F=|I;%80%o_1))G#O)7T`#~K?PKNA$kyk2`j-nT`$J>u
+j;g|F1h6!k37sTRSY)YrJ*w1nZ9DTbLJr8CoIJtw*_(2YQYrFsE?9Z&w1AhO6q^)nCwB)+FJJ0S<a-Z
+b)rx5PI;0M0)y{B~fYpn8WlLzrY4VrG~+$-NVmV>L&)?<J`vQ%1L2C?SqBQ?>E@{CRS;DYvK24a&Y_l
+*2#;9q!Cjhi&upME3-XW<8|h8BC-TnGJ;U5JY=|Vxs<yZv{WHDzL*8r~<>=zX5&rVIUrT8Q?H0RJ@yf
+n7NJgkO9H(gz@AhZhiubCQbpLh_+czH<b0ud*Ap6a(_bq16iH`*i#%NA>1$U1_kAXE4fWyZ(tOhO2)~
+InO#M5Rf|sADqGTbFqRbXT*RMQ8U|(9FYu$woH7~b9vn||sX7Gh<sOy*QuOf37t%aN_w0BQ!c4MYgjI
+i6%DtJWA>*-rhi-V17hnqP+4|>~KmGD*y14_=L19=gU%pCTEyMjdNM7K>^c^P7rz~xbk;g+!gk<~!d9
+2WJ3*iB782D$V`E#tq&sk<_H~%0zHOLG@y)oC_fZW6C!wg%Mf2ZNlS9pxI+Jygyxf<(-*{flm!r(bKi
+EnbySwiFI9H|xV;y+MJ0|XQR000O88%p+8<~*X@H3|R#SSA1fA^-pYaA|NaUukZ1WpZv|Y%gzcWpZJ3
+X>V?GFJ^LOWqM^UaCyxd+iu%9_T68>QBXv}%EHWGunz`2SZt?V6zF7%w$pjY1_CY7iKeosCFvw?kbmE
+Ec#%k1lHKhtutJgA)ZyW|-{@-Ba-m4U>zWm+;*DHXW~t`4w^eiNzH+(P3ce%i(84OQt1o$@Xw@*0l3%
+JqrQ{zBzEH(s;f;b%o0_HMZ6)E=72UD&<G#g}-&#D2)+zbG)WTqHt2WE;SyOV6wY2z5@%U`7s#?0^3f
+l0dDrjAOVR-}i=62pQA>k0W_mlbRA67L$B2baB$AW2!x|9A+%a?q&qfH5nG*Z#JrU>v#2rkA@?3kh@R
+kTMS*)PDis5X1tn37wja@O2ef;T(Xs4*mh{VOYg3MKXh$gra(UJ!UHLq`r!Id0BbSt%{y@z*sdCS4>`
+2WhyfW}Pm7`}NmXS0D5Duf}$0J!EAiz)bSJsPj8kx2z}8dqZX3vi7H+zR&HVU|S|wQ?SJXt%?b<cIK6
+VRNm^fIM*7@^JKAD6g8ES<gYA)Z<;NSd;3XNnqgpI4+o$yR|I6H7YooDEXb9%x@%az0emIflC5Cu3yY
+7pI%B-<cH97gSG=);tvOg+&YSwMA{)+Yc=?*v(!SkGCMI9DRNcwbCsdMyd9iW~1=wc2FIlJTF&O!|YF
+E88>JtDWPC)%+`E&1;_$D<6>%TWE-*mKv1G(tR2J*GwUs&_LmlmRZdS2*VB`_o5`@pbc&2*AgU^%(P%
+*wp<oIx5bgu-3-AJgtNa<)c3+(IYrb@$1<O!VI^7n&|$$<Vjzc7o1PYD11P?JEcy<DaC1ueL|BClC)1
+Pu3};gEqF;sH)ks9)&O0Ywg`Gf@xz%X~L=zC!FV-WryT~s5?fujZf;1g0u1FQlZ?5+KYyjaFF6aoC{S
+Rdmb8j$M<zfP-JAo2-{T(Y!1E`U=0l7Cz60?Ng&N02&Rdm-0f>sf#-SHJX$5eI3iObIeB2DVSp9r`OH
+{Llz@Ot_?A2%;dfNR(QuMI+^3Ek-T;AN4?zh0qqktxNLr;XC6TyWFLiq@uH1@fg*nB!fMhC8yi<lWRm
+Ghlo=~47%eF@oD9%H3Tiv5E5Ly&_a4be1sAzOv+zt@Ywq+E;q>~^~)sD%`w@Mv_1GfvpgqNE$h+`BGl
+>iynfwiLHJ6t(>Aksf-Pxw4k0Ki+;#KE3~fPUOcxWk=+NyVa`fU>q6kG{aC;Yy>)Fd(#^dWMfZ&cVU|
+R49qG$I(S}&b|(Q5*DBNxA;U$5v6B9Ej@{!wPAZ6+HKX8OW^6VJPW=$4=W&Lk4s3|=Yh9^od*cziv)*
+U-f?-J6aY0Zn3T(sflZcBDjdFo+a-GhkN#S2Abl*ij6wiC#nrT-jlW68eF7itJ!@l~;*|M=6KQz#m#R
+4mbF(xLfHPW_F(R8j4WC2BAVDD9Bv_Z@ru=^BdC`(Z$(T!`;%pj?W<)lHa-M%r(APh%Zcc_82DQ}r7;
+6Ze0r{jqBCE}ZXgw355KC?flF6!mJ}Q~weh$JFm23B58ho74d6~?yfbZtX@0*QG?l*B1r5a)4r1)QCZ
+OTwx8bY!&tj1<|)g4M!VH+|_So8tvRox(ad9teobhmZ=Lf$|PR8R;&B$~&jD;}h?sG*23B@|Rd54w)C
+QeTl5r@~~A<L5#BeEYTbqW7OIDM-5zl*k3Uy<NZ4O*_L54+}@EL4SY$7C+K^UX>@L1n^L<*$OO~2L2W
++&%?qU%d+7tA`Xn{WLO`=Y9oEvj?FTEK^R0t=%_nW={l|ygKlL@S-W-u7j$QRiEeW;)bg|zjFyLamoy
+I5m9y7@G;Zd(z{gsSRpaTB44>%zsCN~n5tiT?spe_kfI4hucErdFfkF#}c}7iv&sTVwd%i6ax+jqK=`
+HhR!0BX&&y=b&Y<Ze;&{=##<~3Cbh$9aB=?O2oNluqm_>`<B=OH{RxSlBnuZjEvOr6jT->a~hwk@Z?{
+GsO$<)C{cAP7SJ-WfawULLjNIs)JzWUB{oYNTmT`c@R%J8eF;BlfyHiPM~&j0aU0hB7FH3?lL~`QccR
+=eTv?#xLX~+vwaAjyP@h;7?KZC$E}Vasj16j3WU<aWdjuo`#IwL92N|K0-#?LLbf_Ft-O%)QW;k2IOu
+II5f3`##Pi$q<k|oa|KOFV13y=t@jK>oRZJ%u&(KDQ&RG{B9GdhGB}%wIPo-qBM}cnHl9rMY%pMR+@C
+zJG4s+KDBn?q<6J$Mwexg6C0iZMxAmM6zOK5_pxXes62H26yqk4ZQlH)wEcT&OH>gki$sLZl$ToV?hy
+;Dm6g{ukPyW{DXfY3c1a2AC158_W=el&6;V~FW8ycg?ocxmS+P!j9LQREHD#0j_cC+b38wJ*Xc8WDOl
+(Y`&&gkfb^!z6d*Kum9JTXrK=<O5|x=_<tx`DSv$z_IdD{H_O3J^!^7U)Le|M4WI#Cp=mUBZ3QT^qb-
+JFeIjSFicLDfR72+An^B>dGy`CW8<@<QvG;5L|&k_=a}~ZUv1NuN~r!jBdE<?}PM?<L}<YKy+<Q4}fs
+a?E8db!&=EU`$15<yyE23%MYMpU`Q*vn;!eUKm=7gs2{3#aT!J-OG>!t*y&f3p?ie4CBbg*;Po*ke4J
+^nueZ?!ahP0uG4sNP6X()cVF_N7_{mcHoJ2Q1ZJnlUwX6;;i#-h_nY->Wph_HulX?$YYgmdR_ZaCkoR
+YxLja<x)-k5p)=Q{r%%K6EO>iJ0ILbEU}=`n75zrlend;EXl`FNsyLI@t$Mj*D^p;)~!yuCOs?YEJ>N
+OFSH>GvK50zKuM)kyt-L|i_x$80a^=gR@Wl&t#;;?*!HjMh34WM|CCB~UGPI2>@k#J7EfkbEx+JvV?d
+C}b^)VW}`j>fCMu41nswGCCD6@bO(Lte8${d{oJvVs8T399@_jD=a1@6&a|9J7_y05@3x5y+7V>1>+L
+{!N@8P5{gkh_CT!m=%9@_$wZKkHT{b*x?bu@OQ<)&S}rTa#i37>phHd0AnVL~&%EdK#9;yY-FM_nT3m
+GKuhEaH3tOXM=>ti*QhDAJC0V`giO^#)EbCIA>cL8QGkwg#s{1L3e=)6T#DXeJ#CU#YlZO6<NATi|DN
+Hzg(Ys7O!Hd>lx%0Yp$HL$=%YeRwGarp!|E2}IW9p8Voh<v3t*E6*N)shybfl4JbtKJUJ?EGG<JZrDO
+=E-~uWNhZ9Jk)y?(4Aa?SJ3l2<umdJz@XmxF5VgfOoInk-z@%J?VcmBS|Zmgriea7ptR<Mu}(r%p~ri
+MvH@K{tbl)xn8^YEJiNVL!#zW=`bjPb;JQtsnJ~bYo6ZqyM|%mc`O(cI4l}y*mL#tIHUJXCb0M;yMay
+HXbCA8K0il8ilcuvwuQz!=Q!|<g#3k|TVr%hZtxpIFa8ZsO9KQH0000802@m7R*Rxwyv!W{0K{+r03!
+eZ0B~t=FJEbHbY*gGVQepNaAk5~bZKvHb1!gmWpH6~WiD`e-97z}+cuWJ&tJjyAc(!^Q8wM~-rg*HMc
+O3S07)98Nqaz1xUx;ps3S{SQ69%F`oG`%B1KY^XVRdD!x?R2OXMT@-sAfwGnq`@w7SV#ZB(u{h3VR2w
+eO0$Qro&!MP<6YEOUHtHknM$&d$}lYYp$pvOW~mm0H)kovu1%uIqidQ7f%ly{m8aM&<CZ-f7j;1-vgR
+)nUhdw{LX@V0Opmc&Tu_b$3xWI6_`7p68{}XJ^H(soPGK_0<&&Vt?+6o$ii}Hugd7zL{&7ba}RI>z#r
+oI5T<k6yVR*i%z%ss?>A!64p3Z-^hSx+@&d+Y<a7zP2FZqzP`zE*bG4$3um2IbyckMviL<Wt9+;ZuCP
+Mg0=Ue_pzFHJZ}ifCvjp5O1-Hvq|7%|W(g2HhLd>KSpjTkOun(Sk?NV^`hqZ2kX-&@*e4fJC>#lB(@7
+wb0++4q}%)Y_*dNZd6`0!O>c6qnH?w`D`0LhhY^TOkkXKh=z{P>mb@=f05FRC?+3loGj@|)MXJJjvXS
+2e&`N4<a{Z;N_wzT6ijEUWcieYZA)InGk6Evk+FAf(jGE&gony5I2A=kzeuc_-7h9lp$s_R%|6SGrr;
+Rsm&`;OdPo4G<C$z1+8@h5MvkUl+IfMYXL@^ec<%#`bs#-%m6>Tx;#1e~&*>jVs1|wy6(QS?8O6nLy#
+E@=&*P)qg()rp$jiE`yPovA%xy?#<i0y3%if!L{iIjD>hxB4F-~m>Hp_9m;59P&8RW7R|T(B-N>IV9W
+EaSs^F!pUbWV^7qU@O!khSrJ%s>#Q*JXjkev}(|eZ$h)4M4wJu>+(GK+9qg>FNq9ai?c!{V&ZWzH5k9
+H0FL%R{areAXf8`ywI<DcW5Mc~@rxI?OL2~Wqn><Y7v*JGM8KQ5cR6M=zqf=y`GbX{yTQyYI3#v&J24
+ZEp5xxP;C8f;|8d<Vas3>)vZuTU6xYvTtrt5mPswZkENJv&3p0M{(6PRc+8yrgH-C8>kua&~rhw$WR)
+MCs75R^0^Bf$;<EbeUiv#zw%TmjQcn1D0i%p%nA`7N%xFe5qD-El6HpYgjBd*yzUCcQbYIp9A@JNnIw
++G`Pz$$j~ytF8Rvf%sW~%;OgFrZwlXM1maM1*C7%z`kPwt#0Dc}g6wc8E1##XQ;)uRjH~$oL$23Mhz5
+pB6^%Qp2Bwx5gv)@1Xy;Dxk4qBcbKs=4&<Q%u)vaz<wJAEVihv7=Ft6)M^O_OB3eiz*0I%?i#+E09RR
+asyX&NBo?>zC`7|l%V02D@5bw|)+;IdDqc5ZV8`*dM9EJKGcGjF;J_YD`lE@43R9Cj5?oHhiIyy%w8s
+nO+ju23$>n!zkUn_!7n-K8_iet>sBMhL(UcF(XkpaB1JFN$pd2^SdlbiIRSi{7Hlu0TZ@dOStYvmgHQ
+qw5W-^&YVNpF(}4(RJ4~ggXM@(Vx*HD)!P-w&5F;brEV{FkD_QTeb08u#E2;5h8nnIQh8<MduWR<7P2
+o`cJ^bDeD#N(&KWMS0HCLi+Al_Sn6E8*rH6Z_5(>{qfDdM#kK(Tj=#v-hf!5twmRP&U30Kq;a#i0VD{
+v<%l_?BDD2o1s2d=o7XqVwm%N+(Zp6Fu0McBL2Yf5zj6m#%Bpob+j5Ky_BmQvf3EAmfmAZRqdTe$z;I
+`W}h}Pk_^BAn{C+oB1rF}B<cZe`bz{mV7V{GMDIf`Z)X6gnM<cR!3KAMh9X6A7{Qa;J`_u=cicsgcjP
+(S~rJK;8vZ`PYEk1W+y(HVm26xHwJU}9Su;TGJ$&Hrl#4w=;NMLK}!OO1PcUR;Pqzpyr_QS}xC{!je-
+Cw!m_#G(Q&?T&NAsPspuunY8Vr8g)du*+P5p%GZF{{&JZ6d4FNi}WY=G#i};D6#{P4#;OfuNkDVS{;F
+wN9m7kF-YO&N&sQtOW>3DZ(m-lz)0HQgz`!lj2}sVp!GjNt131ib$4OveY=*0fK>yo!%F)DWR_&{zP#
+6-Jh3H_?IQDIRQ-e|$Q>FfG*JEsE#=<gntpVf`#r5fu_Ii8eC(|gJ3blqTgMj}v*jgNh5616{zTj%Rj
++>57!`t%fkV~dx;8pwJ!rJsn@)LA5Bvc6{cwn*YnvCq3dDXWHNJL?CwvZ!K^-v4)@ldNPIpd1WnbaQ=
+maUUNpNbOjcgQ1fE%s8`|4YqI5>5O>tfxjn*#;l>K1U3w*|;Pnv{y-B{SLtIfm~LO@d)z;tH7Bx}Rtj
+qVZ=epVGbuXAPeB%$l-q=N^5MR${+=VqlV!zO9PJsU1y!0J9pXOA>Hqr45PY)a15KDUjI0W{XfEjZ4u
+*AWT6dfaTT?5(&f}a%kY$PwDoU{n#PXPucJF-vpEDU%BZq>WSZS4kV%JfIrEJA)RIkktuzvD_|J-qpr
+%Mzi$Mbz%V3~k1#sJ1Lo#|NZ5ke-2zX6f21)qur9DYM-~+YaU4N>8q%8q&umF<!5<mRt)6M<VPsi&{6
+a3fxY`LddD6~iIpu`im{{VshrF$p;7L;WVkdi^J!iC@!5)s~7Ro&*w!R|U!ylPE=SIStWndB$Ly_~lu
+3I$8X>J@`MN`E-rFI}#w)GxFhF}Ek8`93mq`lo?H@2ICXz<z)%Cn#AqMC*~!6|nPY4m0VQq%UL9ciWk
+P|q_TY-+Z(22KF(L6nhVnz4NRLbMXbRkEVm*3-#zLQHN_e#8SanTM;JjcL`cJ>J*!O#mbTz-;cz{}3X
+Kn&z0GmA61_4I6Mecu&N8<M`wv=9346GquWDS!L?2zVLQ*Hkl_u1`8WDnFUX3jG2*4AHhdVZ0~o_!vz
+JrSeFEr+BnjLNhq%wWt?c{eiR{y2lUI3&`q$vgH;brl)jN^*NLtt0&4gf3#x_PPsH+g5fs6`^rG4Q%c
+iZbS`19A@_241;($yE!s60OxNv5B1IiF|?GhBSj$ifx{rFAF0;C@LDqkO$Fw?rc#Yy$uQem8Zqd}Kvj
+-VoEEJ-sV21qLT7QS|bh6e6?s)-HtFG5O$O_w&Qu&|_v-a998;aS8}X*&-{G>f{faQpiJq7=)$ph)s+
+Ar$X%b&e?>^k_P;LN7!|TQ%+_WDjl8fhq;{O$I8v*reorTlAcSyaBZ@<|x{U8(r#-l8rmC3-eBc(#p5
+s;V2hR&%)UT>TVHiK7Zyfj94jdb6K18ixegMR*QI3`cS{+HM7$%R*+|^M4;pCi!r=72s{Li8|s4Eq0d
+42ZZ_g0=-~zg*x`c&WS3&9aDTQ6_vVG9Fypxg8yJ8GzZ0<8IK%0Bx&$^l_z4NfUP^D_i31<**Y!cffw
+ru+NA@g_h?WlaKcgpt?j#6CvF&#s?i1iT@YMH)z<@E!vPD_h62Xfk4^B6H;=_KWcXja#EIiVuV8eno-
+Q^9{4S?4L*8C+IRN06u(C8i)>+T1NVvD!?>u>&GR(-3<wZ^?Zfjy4FfejgfIayi~R7fNf!(pw-=%-AU
+3>L<nPQVJ9OlF>{1Or1dQ0O|57U$UeNbV^irAaB*x5Y+tknclB6GxJGvj7Ss&TO{J1=#Sz{&?oQW+Yf
+p&fp8{8E|5Aox`RIO{E<OMBsf`B2HzkDG-E4UubrLnb_{EbO2gR{RHIHO~Hk%W}Zzqi0pe~epQzx7AM
+?mOvw{tgn)8czO36aN9&D}R&xM=5r_bj95A9F-fdn`GE_~w>%w@T*vGe)Fa?y><sSLC2nLa~ae17@)W
+DZ{#WPvguv)_Yz>qBrNuz45r(sLt_Sw*+^<WLcKp}*n>yQ8;utD$4MY^W5c+z9*i7EDPpi3u;VrJ^sz
+SD2B$(fI?sqn(w?>tj~THL)W6WOA>HgR&WFr?tQMd{WtvG3er<Z$*`{%L}+fiw1=b|3)~?<?3|p3_KT
+NLOYL8V}#&s+VHUMHc*MLL8$FSld*xMiwh}%&Y{_^NhxmokSK$y%kZL6tjW20$mBaDd<g+V=#G)X5r^
+zV}4jJ8xwd@*n`LT9yM_Fuv3-hh>C=9SV6<?sxeqdFIi9UbRsAlo3+b=7wmqyM-ooMIfaXI{#s(zVZb
+e(J{wgSswv$h3UuSEi>}o=noTh7LJdW6YWBW;i;>Dhel%i;_Ms?)*>)qgXj3$*-B%tZa3o<qFt?WdET
++Sa>0F4=BhL3-&7&?j(&N937;_Q*9z^SSIULAA)3M%nisLA-gE9NJuMQZj1%9~Ex=~j(TGr%n1s=&c3
+Vd5ihbApq>9j@Boa?x<p#v5pExQFh;&LpuzgM^6J%9e<zh6DORH$!2%OHd9o2wRt69)|`^#$|HD`gqP
+>nuiUPae#3gyjFpYyR$=r{Bm>lAptZgabN3E7)E~pf-3*Ye2uxq{BL)X*fj0tQ`JM784F5E)(RTb&l(
+9(A0o6kZcU%?+<_d?V;N2iA?z<0i)Fy7CU_qmN%-J{`%W2Q}1xm@E=C<VW9~i7QTxU1|$Ql<xE$YVMd
+$}&=O$SE(0sLL3UYrrWZ(s{f_b_RMcv>7Lp@NL3&f_+*nr-J0YMBRzyLwY?848nvz`;Q6zxoYX%IQvs
+fm@z&_DEY}Bu#u->`)lJc^uD|WmF#K)Q{V&}23`p|F=$yiVB*54T`4SY`gi1MXIa|+P|K5q$o0I-e)5
+`&x!+EamvM#dGf9#uc@>Q?tk`c^BA42a2P%p>Bq!j13m#OZU?G#~O^gXPLH3x+r>e-$NxIidG&UwTm5
+obs$RjD##vcV~e?NFM*tS-nh%WumN*scZM9TiQ&g6o!Oid+j;mFcE{9^wxChGjt|Ei*g+@aOOsPNy-R
+~7>s~%8{JU{#C_kJ1zm^232;P)vA=xH1>|5RU4T)%-It7bYu_6}T%U0Zy7uJ70tcW2@HxAqdFLb{Xla
+UDH|!*BM$LdAUq%QWq2+X7tlvi`Gqe*`+|z(Iwr<<XY}O#Tp=bs<cx}B$aY14~2TSCT(n6rI8g_(1ON
+mfJ;R*JNUhi9U@QL_LrGf)XhT<B*W>KJ{!7nDWlG6Y-wHh55==)HL@6n@2$nZ3K656mRuJ4DP%LbOEo
+XS@<bIQ(xf~+sTE8!!H_l4NcEWl&GmHVU!;n&7bW9@$fTCTdds%w{IM&$2!Yl?f_S2y%Up$x!W7du2H
+DW)8hz#7#v=dzhMDIJXrS>NbBf5g2J9s5o~ZPkW%4$nFFC4_PZ1%jdZv<FgzVp9j%3QRN?YxFI!JER7
+k^q37QJf^;u*lLWQx(Z9Q#mA!mCyQ#sBwbwY`s1Zf`&3vdB(!)$8@<{mayJuu=;4A~2U-GYTQ0gJ4_$
+aW3T;JMo70&Vf3~Nj_oq)bmjs=Qd3yCXA3bF-{=jm0^X!fK```Yd+(8Rc4s+(oEyh4sl-jN-_^9M?0h
+Y74(8z$(*vXDKhQf&Kf70)~>muV1R?-{m$c?AqxJamrDxKig(_{Y;+za09bDV>RS2_;`tVT3OpXmZ^k
+qg%VCxw78lCV`xZOB%P{Nm~3nZg1);#oAHq|U%2Unu}Y8Deb}RU$}Lu><C?LvTEoFnAGa!mv-Wwl~FU
+p7+Z}T3Gb#Z4QcU1n?%`tU6KpE`e|iVn`^g9~ee320{j&FPg(qWYJrO?;(1K{%q!QOoTrvf}m0${Qc_
+LyC+Ydyn7-THyCvVug{}17Ty;fG4T-TcUG;8%+WGz9{^95ssz0=@ViCw&r+);Emi|=r@{237-Z6}CNm
+U0+c-QcZ5?J73I$;9TTg(<zaqz0nvlb%7u3&K&n1Yejg)p;FbQPI8HVv1|I-s2azqd&OEOFrz6n<J`A
+kW83+enC8eYN@G^kxi{D3=L!5O|mxUQWC6+brZ<XIh_xfL~j{pBSX4F@{$!sbRGt_NeKpu?VypvEhby
+$T+%p*SGhkYsdsz4~<X*wkwzOAwM^u(=pUVxYW!_T96$z^zS#wrzDh<j2778=Uc+29(e2h!g}KHukBQ
+w9-@OA%{wt9O((-L*lEBGgNvyBRW`wV$kPKb=9l55mgmeR(*nY;v`?M;!o+I3v}ZywmL_5V6n|XlTpr
+=sx((R?S?u3HcV>XtvjNMLbMA`6todqPTN^8Jv%0}tsb;o2t^D}N2MwHgQuuF&0P}ZJVW_BZhQ42S2D
+VEGISb6?QJ94Q7P`G-dWiAQxqs`&Y|)gN=F`9ywH?*#51*0m=0ev)09Owot(q=c^n+%85DupdZpn>)G
+2Q`Jf#@ci3|(E#?QH)V3ElK)6-o#fRq3*Bq{+8W>@g2)oHqN6(qX4y2F@y+ZB0mw9breWNBLl_5aY(T
+)NZpKMYOM9|Hix><rL>JiF2AAK2E;!~qc;M$@RGSsk#drFTf!oU~FSk_)}LM8{?{9@)&n#pp96cwvFj
+u2g$nH(2~%W3@o;$09K2A^|l-2*@y<@6<z!oQHGukhtR^m&ZI5&GwM4K!7Kn4e@Dbtg`-G1<&kN-YA^
+|VtnJ<SE!`paL%A5CB{tEG#GHf_C|LeIEu_u3TNpOF+ZuAl`81Qwr*Oi^$CWMOiNC#x*x$QOXn9Dyz`
+;P92!;WN5xJ(dZ_KPtC!oo&wf%;!N-IWoW~^=7RZ(}?Pv^)b8@hEJcj^h5bn+Nlzy;{C5_!vWl-9cs`
+wg~geS(xZuBv*k$nzINjqFQSFuz1G#kvz8Db(F{*?H6+LwzmTRk97p`0!Qx3FUY^e+*$DRdF4hK6s*Y
+gEd{u!E*HF+}`}yAiDa;)9KhamFw1AOU|&OYL-fMOp?rQIGS-kN@%czsoTRi3n5Ry^ElPmv(@`ADmS@
+6l;lw_V+><#cv}(q|<U2-oOHiO<v+DlfYHZ)VI2$B$3CkF{t7L+3p2Ls%?50E#VairW>~F2`Qkf4VH@
+NA%5^#Umb5JG0W5wquw0fyr5*szHMQ9fwYxecYEt^aR$`S-<yn0w@_B8>Wc*7nc3?s0`Z(_iPOeJU#W
+NacY`HkfX(`blVTj;>>UP`M_{b3g9h82($8G8g>Zke2f_Q)lG80q%*6Z@0fRkJtXZDFpnMR=u-E0DNZ
+wK^4#<di&2a9G0?b>o2M-Z2hCq~K@14+~{)~?2pFPBdh>1!yh6NaL<(ZR7XzTpwZzey=hNJ=ig3^PP#
+@Z>=im)0^i<8{$EpHA)H(X?;{X~k{ukjh}a~sw9T{`jO<+UrD86hcW93v~l3&@@58Ja{NS%6|qoZiAo
+U!Z`W;1Y#EWz*4`nyh3kKD;BWZ{mz;Eyhlw(9d0^fS)@Ge9jdgQYp4#Q<VBPuliFaw$jXnU8COOiTme
+h<suHhoiF(VH%s_`SUBtj>s+<k3FiwxuFjSblTI)PxJgZK^gvPku`^1av>2=?-7G%a6(aY0&cKoO#LW
+jRD5tFW^atjv`4|w8foifSUCh}pJX<mXm-At5aAd?)d8CfnxG}HEWf=jB1d~&^RxPjeI^P@JCyK1MZq
+w{??k0#zg-}7hUlmneicx}tP+*ix(1<6%U11BD^q{wf5s<@ES8|BcUR*{DcVT@G+L|<;nuaGXL$C$tC
+925r(k1=^1qSTI_W01q!m^(YxRhBEWb!c4;zadq>PSz#*Lr66_SkSY$u)0dVt};ZE^lwB9>k~-GX_8R
+QeVSjuykQ)I4!a}`YGidTFoR{iFRzySj%MqD-QG~6F-!4OiB$uF~L#yQ~1OWh4Ij=B~wJiwyhyX&u^s
+HSQM{E%4<2uj9i9i(|5%$eDjsUYqPKthV{2-#MpmKMHv1#<;%-YsNlN-5BJr^i8^*(w$y<J5eJ+L#U0
+uG4^%JC3BV)A`sNEg7PBo)&)x-!y2aY}DHyWt4lDpF`>u{cL=#q+azJD#m<NXB|8Yg?bY?<7x|=Lwp!
+b(qmYIHswDBlDzD4D3%AR_buOeEBQXU~1JG1pJEIG;z9@0kPMm1rsz478!?DuS3*01!E7bk*wc;RJgK
+Otw|lTlAH`;ZW$lgTLavKewuTH1e#3}VD`K*6O+$zg5Co7+n+(8Gv5l-k=uw~qrN$r&T8$Lr07KSdV#
+J!7#a@$_lM#uO6%qnw}nI6Y%7OO*5P33Y#w<GQ#b-cGFDdDy|5mJ>agkw}&XcpU<Hd8z?jOyIw#Qb=3
+q53EyckJjd=X&<zN3`k(aQC)GaXeAL?P!kEaU>I2#`YzGIo&XV)$C>-rk`BeO#rCkH)OjU)$YFb|#Rn
+uW>+Q(kSxO5e4yBx{C!OqON|^y7v9@l2LcBMC5hS5Gcf(5JSOo*dJ&A!OM<JqHK_Q(yWyq7YZ;dbUR!
++cmd3n!f6HbP~^oIr<=&U~`5^zllZ0ulcY%bMzzJko7KhdG*;r8NSJEVp5z3wu2*Dq3*ET`S<%_X59%
+eYMxqZ2Sj4ByP7imQr4fU<bsOCISj{+;jr@@%qUhv5dW(#xJqqhUqzNagz=yFhpv6Mii7#*Rweq2jzm
+^{FD^J^~*TR+kn8CQ*?+ifUj*g}??`)WHbxwNoivq@x~faDL!KaAl+tDQM#k82=$bn#h9TWN`XkYjly
+J!4PX)7BaX!dt?`VMMW%3qhVFeufMr14|@!=(qkKdE8(F%8h!8IzJ#ygDGrz`XMu+7f9mY4Z~qSrac6
+|bIx1DQ+T%TW51Kp4JI>_K?d?K|iwYNVMVjqMwb=uc!03+RX;(EBu)B&TmMygJ2Q~i#AVW{(Ts@Ohgh
+oXC6()4sdVh5-`JR16tfQtz$BN&Yb@n8pZ`eg)B=0gUoSN+sIs5UP7s(r^<<_ilcg~`@y~=O2qU3_LY
+jSt3Ua0EjNVH%!w>J595C=R*_ME$%5CNsQr&G$Jr0I-|rW_XKz`wC4Yv5%BkqhB<K+`BBI7nUb;W(_B
+G?$MaT@~H+euamUA2r7&f7BGsBg*xdM~@%>$LD|j-?73hVL#3i>o>_=HWra?(cj%Y?Yn07irnm4f7ld
+P+H}+5B+2@1>SkY3PS8$_qz)Dgg2}KUYJlKd6(z{&p*13zETTT1$i(6ywtI(wwHfw5fglV9Ou!oa>~D
+Wx{E82LoA@FDPhp`f1?HuLl{PyD8rDCQK{bl)t?q9NB>^ba6v>*(V(U>Mu188`%Ok}1vy{l?T^Ejf&=
+WPi!QD8C_uJ@Zp{Qejh4!#Te4R?Fn!zi<>fKj7EtGOyKlTy}k%1@UVq<P=x?()C;(VI+=e@9AaGJKuo
+C9U$@gO5dVl-FTFGUj?%QW#rA5&VxUtJspM9^YXPY26R)sp=VTk>S3<LeraUNuKoSOTu^Mk6$iqxC0Z
+6K72goxtZiUh}@`<*-W7665Y7$XG|m`)fo?zplee?+-zmBY9XWc^JRntd<b=qQm$mzC=)Tq(<|O8~N-
+25#jjX$jOj6(*z>s!x@I?jIR+4u35RGZ*Ysmw|L1^^71|>08ZICzyA=;{qpox@}7sWq`dp*I@AP=5Gh
+-ignw|KDn?h)50KxUvI&sW7tY%IH9Sl8j&%Ng4ulb=KFaMt=RJiH^dMx(D_7{x@rP>6_2BOIv?s>Fyf
+8&8Sv`eHwiI;=;$s9B-{|c*E~mT|VUUqqA^dCShJE(U1_Z6+#mLl2-m>vgR<`$#zR<?B*C=>1WH}h6b
+3ao3%T$JP^e!{NwMm%*5r7eMz_l7T3GfpwkOC~!q1Y}($_=kS^ExGs2`ft+hkmj!q2@P5v*g5$cQfNh
+i5XGk7yZ_`hrDt3moHbxIc+HaJ_GiSygSbE<P4t79>DVE?^`<a$Xl6g3U)QHEE4-jvWmVpGD1ABXva?
+2o5rmiMjC=n{jR#t`2vq7ASls5P}2uy1`^X-*qqPO#3N<#f%bdXOWjw%p0<%_0pI$jj#zY#5!`L{bZD
+B(CX@Gk5GZ^73QisqTm4C0`|lp8cYWdC7!;eh!kfc&1EwX(dtKcYZC!CjsK22QtL;aHJY9OOpkKGo!F
+0L3Gp;JzHu-PakzhahFYWvfP)h>@6aWAK2ml*O_ErD@0006200000001fg003}la4%nJZggdGZeeUMZ
+*XODVRUJ4ZgVeUb!lv5FJE72ZfSI1UoLQY0{~D<0|XQR000O88%p+8rH;n*fdv2nB@h4rF8}}laA|Na
+UukZ1WpZv|Y%gzcWpZJ3X>V?GFJg6RY-BHDb!lv5UvzR|V{2t{E^v9BS6gorITU`+udt><J3(O{&_1j
+pb+teXs;F4hmZzv1IWtaTI<W`a(<UJP`+mosYcc_rk=kVJbN$XWa$9QSSf-T|J6Fi%M23?Mx0~K;q1S
+7v*3GN7la<k1=JutqtUkOmJQGWvJ>226y$4rAa3M1{WAB6#hC6L$?BCK!t#~nGw*oiBH)Ed^&L)Aslx
+31i*k(YLY;`UQn-o$#G$OC@eT>wIFZ724>v&N#<X7SKMtrHH5nG|$7<1($)Hty%(_EU?J-lClD}(9#$
+%GIQhMhOiBx~WW{aKu*if=`lPA8MeKOMA5{dLO~2iYVSD^`^`cOn()F|BXY`Z|98Jlk-!7Ix08GgJ2B
+?+&`f2dw~A_y2xAVR#%jFat(un?R;Cgd|;@v0MHq*ds401T4g6BN}?Hau$@)={E5!N~=`tq;)_EMwti
+itzLcx0`b(7Sjf!NAaw4-yMU>62p55LM%LfogZ0~Y&$QBp5k51f#8Y5qQq}rxB7wV&r@<fZli7DKhgu
+gTiG&AF!fQ({c9|$0doT8v#%S{kVn&?q4C$#L(#HCL@W9Ny6h$7qmB^@~cXh^YghdDi(?+i8wuuTr=w
+gzz3>{t#LkC*lhhyaEk*gy%JLct(iyqY4II14m!ir-SZmmG2NbAc^Wg;Hxo`p;X2ISOsU+#}Y9DqFJ|
+9L%uH(ge;$Ww=I1i#{g!iiqf?OnKxMoP$NJuDz9>^S;(^)Y?@>FW9-y}Nn!=KbYO6iVPpx=pWrCYL+u
+ZXKjUF}EypyACGA!b?X4NZ}B_S}z!&7>%gu2l1fq#1B&C=aF~uMeSlVohBuBn}N7vIX`GMN6wv-HPh)
+pVrY0tE|%3gj;@q+k{9x;$eFi>d26WKbH|=pK<i~pS{WXxKKijIAe3rHhJg4QYOWCZtU!7V1O$2tdy3
+{QU7E&L6sw@Q>zYHXi6TjBwCUsE2A~;9?F=JnaXc?5DXnN4;4v<5i~!05OkijLq*GnP5=;+a3buQLhd
+DYwq3M#?enC^4V8T^K`Ky8Uod<4!!mQsxQyTK~c2+NFN-th>D=vL^#o_(^kO8&YqaTtUh+g&u_xFdI@
+KgY^LU2`;aUV#E+&-mBsMCNJg}Gl5ycpy|Cx!MKfOp<3I*HxzmoNW}i6^N{ky5(q%B3sA*A#eEQ-=K`
+MzL+gE|-{9{Vb@_McW_)lFwSIxQoK9*4Hza=XsN@;>&zwGZ}F`ilSF}j&VIg&YV6d#02DB`PIFd79;Y
+pH;>+71E9gPl7%2CPX?0&(*-?x%PBUDFM$MT(6~&eu^Ukx^1eEnGOB~osO<HEGc1dH$l^IQjCLI%3le
+s<V$v}`pKMr7;P6s-a!)&BJh<AE2h(^#6nmPBrO|66tVJbg5MOKkP?dfMAVR~X6?td=(T3q$l`e&fJ2
+!lzT9wB`&o@&AQ_pdokO{rCs5g+eaO{J2Z*`^ekyWHba5|Qw(Yl2v=+jUTef!?`bSVfvf&%UC+xI95A
+!`wzwZ;uwxd)(+N?fZLga~nX5`SP(*`Uw(G-VbgfeeFo>@-*-9L2?l!Z-e4Rx*-vo>r=1kL@eN%migS
+Lr&+~SZro2dP3Lp6$<Y2sB)_pe?_AqLyUZa$7lxxRBy@+j7z9M>Atga*nd%pXdut*LE&LbenyK0SWk3
+(c%&c2?-c)y=R8sWzKVXY16+tgIKTU|te#)K8Bp>0Lv2t^rB*)74M42`G`&iZ$oO>apF+6?<3~UTuRY
+X<KK>l+W>B=lbqFf$p_HCJHC;Tg?O>DkcmKoO!?|q6Hh>?jvyBH{!Y^dYPk$V?PPCcboOVA~MjibRP)
+h>@6aWAK2ml*O_EvuIe@k8h0052!001fg003}la4%nJZggdGZeeUMZ*XODVRUJ4ZgVeUb!lv5FKuOXV
+Ps)+VJ>iag_KQi+b|4<@A?&lcbE;h26h+*1jr8Ex{t$#V%yzNEGA}aOM)b)&A%Td#c8}Yoi4UM_>y`^
+swj#d7^IRx!VWb$8OUfD%#J$P8VBA?u0v4dgQLw9cYPy@q7Z^cYg_>1h1fbXf+gFud(_If#vZIQci4r
+tH|E~M@$B_PgSwX8J)io<8=vGbpgXrG9nfhxG@E#|MZI6x-sn9!qes-?B_n+7(54t?t5N`u@7f1;l`i
+*t+Hh<gdVk}badkQ{L-=}P@I}&qsutBtewf4H8-G%oy}3!VefvP6Z@r~78F^ps@Ul$6(YA`*Eb@ovpU
+E*i;|@Xyh1)qd$Z9#ze6JIv)iXRbY%=H71?n{@*5UwGz_}F_Tz!l`t0c?`KB7RFUBcu^?|9nvQj;G&3
+;2$!0u_*k+nZZ>|L#L0lE5zvljAgm9#6rmCn+`GubJJY@4VlJ(MBTcC5-Z(v|1OVQOxgZK3vqW8_b3;
+b!bPanYCK~aT8WzshI`;anV>A`g|~E?Tlzzi{lOaG>jqi@=^iE%ncZ+dyuf@wa7m9&zXpIXr+6~V9VQ
+WcK6UD4mI~0JaDTS{Wd@^_w3S~*>_yk#1~IUt?`~VG*CF?z(P+RVz041`lx`9+_TL|AeSZsc%??m;x+
+}D(|k--dFtgRm~p6z>ZF;8Wg2JQ&}J89{!~vS;|T7sT!<q+FQm8Tn4?+pf5^)7+*S+K{1Uv@_#i!C{C
+OUZljQN@n^0N~k7>2X{#hTt6{HqVnz^D}Y65;CQ<XJ$hV&xjdU5ee`~^@;0|XQR000O88%p+8fF~@<Y
+ytoP!UX^TGXMYpaA|NaUukZ1WpZv|Y%gzcWpZJ3X>V?GFJg6RY-BHOWprU=VRT_%Wn^h|VPb4$E^v8$
+R7-E$FbuxyR}kJ|HsE?Y^$;LCbn7064aK&*AzMtW)|LcGPMd!}N{ZZgZK{i2<VW)3qbQ1>=(*sY!yXk
+{?xj{R>b>k?r!6==+a5tk=dJAK@aq~@6a`~)GTM63j<KE96Bucl_JB%g+nA%V`W}1V4q87rILY43auh
+ebe;}#v^zoUGBieI)sXSW6$EFLSEvmyx_f{RG)oMcJUsJ-T9!>NyYn2RW{ZP)6sTka!xg+0tbnez#ZR
+;qIN%*#K@RiFEMa`<$><|y5YutjAt=U<Te)}l>&^jaIWukw+$ICDtC({aPGss`Mf035R)Aq<16S&K{!
+4`$|yc>~VlgBB*g{{pCo@(e4;hPKe*B}UsJlOyxnN@K0DI7Ktm@<9h1R<M**-5phYd>%$-Q)<s^;8}x
+Kq|Pqy@TuPj}40eztPW@^5F+uq7cteA_v-Jb8*lAt)EPwX1ivke2_|Pi%AP2@+u1#HS9;-QBcQr;)+N
+Y+rM_kimfpd;D06>!~Kv1L;B7bjc;MSgI}6x@B_b8$svU!2G$*L*wI_yJ~Yx9h_Pt6ea>J@-)%DYI3S
+K6a*k{2K6s?&)9Ss4fgi}WJ_G8h&LuGrxi#83*~wA*WAe}s(n07x(nl8%@QJ#(SpZV85)*G!ZMjIt?A
+%4yL-Mna&zUTjo^QOK#;RCUtL2oKO{|@@Pn$d_(^hR(M!h|*AHoXrNUEJa<uXIQL2Y)pJTHT41)QeGT
+f+jl0}O|k9$79OUYsMPArFbq_S9<I(_TRw3lTFFpN;)OQ#BT3bFZaZxm>Seuh>6OO9KQH0000802@m7
+Rx-2@E;0iE0G0><05Jdn0B~t=FJEbHbY*gGVQepNaAk5~bZKvHb1!0bX>4RKZDn*}WMOn+Uu<P(VPkn
+NaCwDQO^?$s5WVMDSVk))Qa6HYrEoy72ni4ZZU}kZc#<`n*pcl372>}$c5El5-Q8T$Oy}eI&6_c$^aD
+69xZ|V;1%^AR6&Z9dTheJm2IzTvBv#L+1tO$%MjmGGWb1-bS`>1ev~fP9m#R;n+7?A;^hhQ-)l4b}M)
+9FO%yJM6)K3!qUU|bC^-~(HMo{ijP&>%lPEsK}o8t5Yibdn482H`76kw)^vLN`pQ`Yfe2*-S5j5fP7^
+OyNB8Qp@l8;8Ww+f338mjj4hQC%vJ3=Oun;O5C`Jy;eFo}i5U9@yqj=z9$9G~=eXkEF}MQlb_yv(@}?
+sDp80LYfr#6~A9g1Fh5MSQNf_U`Ug?Soh%G2V2RQ;v+Ct6-6PSBdn83WW=RNN%jP#QIYGH{=E;Jp*(K
+TnQ%pF47m0I1kvUgA{DvKU$?c_lMn2WSzpy6qHkT$Vds6dtp`*fMyz!!BGID;CG0Qh?n;_V(dv5<(xH
+RWZq2%&^N-=u!nr2Oj(*e|%q!qd&v+n&@+aH=(khq10%a~!k(cDf)3vfgpzMP-K-?WtrWHH^;V-R`nv
+uH=8#!A9Wl&`%FgI~`SO3sbt=_wplW)(zrw+$G0Bnq!Um)hu-JcEZG9p3HY&tSuDaaw(!|w3v+Zd(QN
+CJpGIp7E^Hi7j}tkLUCOL6poBwS>+sMV!zJsqzP+=9R?9mmt5SBo@CJK~}WDLw}(EV2vvjABieS*cUO
+@Loov7I2vRwO91>tkkwRDZ{C+u<L0yf^H|?-t!*Fm8H8JeZtggj^|$tv443r_~C6%=eE4Z>1rs>`*qg
+*j`V{*pu&!9<O(Z`=Bt^Z3hiG~`Xz&@9$iA^Q&_jSn(fExqBNT=7}jdl$-YS)KRKQs*^RPtY_M;4d`U
+kUn7Hwr=a!X;{fbtETM~WuCnM!>H=P*#^WWku&m0m_yNmy{zeKaj`T-w3Vh02hU|Vd`(cR(2n&pxxqn
+Cr@Nt*aRcdAY-%We1AE#~O~|KpsCWidT;!Ie?LEUL4K?}~)WCgfat`7BOY7_bYQtKKf8|E`g(f~w*lP
+)h>@6aWAK2ml*O_Er%7#bxRN001)t001Wd003}la4%nJZggdGZeeUMZ*XODVRUJ4ZgVeUb!lv5FL!8V
+Wo#~Rd3{n%Yuqppz3W#DhJX!QK@X*{kRH;cv{0ImYbio&kG)D{NtMRkE~Wpy`q*{6m_`?AM)PLgycsn
+*>j|_S24x1OifIGuy&Zv$E_&hQy?3Onk(!lHryLi*&~(;wcXZx9VM}6f?Q=LIZYHI>8`(a`sL%1^qtq
+Jx60Z!Qk2(27N(UaMT};$sm{a)481&+xXfHx!lZ-L`%K;fnw9&)$nLi(pzGh!7gpnf((J;n3>|vLvh{
+GOH3y1FA+xIntcv93B0{KlgcZKZsKh#Umh$K5nQgq74o~=JFG7yfgJJ}7q`7q1&J-U8ub4*oLIX_r~@
+Wlj*$sh6O6w{4p2&Rx^r#-^M-2+6fg+83L;Vfr)M4G$_;3VyVEac`u^$?~uh4qux$BZNn_c5D4sDK;r
+C)~GKouB#STZVv9^L2lq0vJmfQo4*i=SMna47|hLG}P5C22w_*rePt_Rj4*aoQBQFGTk`9SH@h=(dqO
+>xuj3&x3?btq$&P|dR{|LcGOKZBb)h^Dx9ahST|7!)a7cn7d6Y)q#BXw8M|1hONR3jY*y~Iu-9wXC9E
+*V-z_?VyL?4qSK6cZ*4Nc1sWf(FTP`Ka@~0MFq$qpvGSic715X>ppR6)<X=I^5!~OwKO9KQH0000802
+@m7R@bMf$36l80Eq<v05AXm0B~t=FJEbHbY*gGVQepNaAk5~bZKvHb1!0bX>4RKcW7m0Y+q$$X>?&?Y
+-KKRd3{t(Z=5g?z57>;kRpM!wR*~7rSy=Gs+HO%%C)L20|PiQHnmN*tE&IK{$L3kXng^XJ#Xf{c_8{h
+8wXOitxzoyX{#-1jPAi52OotgdOtX!6_+F(4q~9}1y!vL9gc(1PgptDY5i<Z8P}tb^);`a{jE>_;D$?
+yW(VQ@tFShdT!0DX(D(v$bV6Ec$I_!#XlFb#Dusp}gzK2~t%XhR&v}c41P*B6>O_XN=)S~Q&Y0poGFA
+{mYHXkkeX&D_C>hqm@ls+=z^`y`57wDo+?J{L{lA#ROFcSXbH`aNjF&*0;{w59Kh)E{fOj8e6~Ft?kA
+1w8Wm&`rtq?vd>pb`){v17AkIKOqgaX$gJls9N<>mWC048-Pi71cgMx!hY+;!kIM0y|^uwxajHKUZrn
+CU3odo*(p7I$E#yl=ibJ@pfx+*<Uiula$nptOrAiKXWpU&2a*pf#3bn`gIZolrcGhJ`>EHrpj}3NmM=
+`T7z5XVCe4JFF%t7xXy|5*lsbcNpX!$Y*0xr+Zmsb8<1ig(9axFFeOm4|#eN`?IoVd}pBOr%>24H~}W
+Boty0KiZbjrkJj2>twZb7;w*x{DjeMMtMj7;Tr-#^hsJ2L-D-BjRhWD-;4Jxtg%T@1T8uVLr`a~bqzu
+#=lZ!h3lF~d%_<dyCQUqbQPd38EDw1seYS~GYyZG?tT=_StkbUGrVx1_hY!+P{8hfqxw$8NImWB_LK5
+3!yH1LIC3i20FO9KQH0000802@m7R!2;OAOQpb0Qd_404@Lk0B~t=FJEbHbY*gGVQepNaAk5~bZKvHb
+1!0bX>4RKcW7m0Y+r0;XJKP`E^v9ZR!xuFHW0n*SFkDyNQhQwuLhJun%!O&4bY;e%|ei+k<5l71(I6F
+Soptp_#uh3oo-N|K3EoKIGlO&9>;W?gw%wIVW50SsCyNvoEm*ddMQStPZOGmH$76N3-W2wRPcr+&Sj!
+gSyQe-;#%1<S}NSbL8@h&n1I)Q@z$PMQ>ID<dY-fpOx63DvToTuHea9)jU8rD9}fVmZsef;CE~oFq-a
+5{nY0aK^|oA)UdXZ0bt}fP;hl?@7(hUhYC)zPKtI~Gtgd-8LS5%cl625t?w6ourn7|LCycqX&^;+FpN
+q&SW<AY%N6=CvIk|gpe(kJFnx+pn`r=F|cgG?6=HN9w^o)XbpjyoSMr~R6lG{xhzG~x~{_0Ob(>wy#n
+DlEH@%)*miQPhb!iB!9!J5{H?<%rJT#Ec%aB!Id!x#=`1MYp_L#ycvJi-gGEGO^R+CJWY`0Kati2XDx
+Aa{2!Aol`)X+hLM9G{ot6l^hWre6Z@)RF2#mSUax=6&5Qd%gkVGO7MDtIzy3-g@>3N~E*ocB3Z}qEIs
+!n)c+_?+I>{=;&m4cg-UW<5YK4dIl|y!Rvpd;UaSDyb|&cpZ5WX$;`lPe%oA;p7zD0BxEB`#K{=5!{!
+QkT6y{-`O}EeP`CqB>_|CPW4V=yd{pQGU1neNkaZ4+75h;Q=$)mH7CV2W=zU7&h}R$FnY0objE50OPZ
+_AvG`VyNv4`YQ#CKQf@yZU-EH2>NLU?8$8_AKw8AjY}zV${6tC|>aUnw&Gm#g9;E`D#NqmbB(L&FK4W
+Q#6C&e~89xat7U+Jg|vT=hMbO6REkbLbvnRgj=9|086fRQyyb{}z;I3+sI%Pd`5|_i?BlC#UR|DC{_?
+r<2uJxGrYd!iAs)CiV@hg;m70hTM_gvYJ%8w}th=brU-^^QmdSU<1vg8F0b2#V9Lv6{WuSeu$M0Cnrs
+{>e6enCu(kuTR$`ASffkw3B$=FRoF`D_ZdQ#OFH(sjaVe%TT^%=X@qUDF2^WV@$2Rmp;<+5n-h*BO}Q
+O}rdO2(*_l0S%)gBqsi6#l=4Q448z2L@7*d=`W)m)_Q|`;gArSp#$--bcX%z8>-6eZF*v~_je%#XAZo
+eJ*Nu`D3gHO`(11*s#{fwzD|Et8eK-{0=$`%gpDxFUHfVnJ%lAw9%jlIXN+Jtaz_tjVa89Qu>hOaG5n
+%vt5LJ^ngH<!J+`*G-kltQL?<l|AbrYwDE@V4q4LE=VQVB<^Ne6DU<^I7H#-X{z}zydShk{DJiqw4Lk
+9L25dcMQmKSA`@EH`zV$a(H7_-|BLFkyh@pxm*pLE%D?ZP)h>@6aWAK2ml*O_EzED6nixQ001)p001l
+i003}la4%nJZggdGZeeUMZ*XODVRUJ4ZgVebZgX^DY-}%IUukY>bYEXCaCuWwQgX{LQpn9uDa}bORwz
+o%Ni0cCQ7Fk*$jmD)NzBQ~%u81&NKDR7OiwM=<5E&m;sO9rO9KQH0000802@m7R$jL1pbG*300IR705
+bpp0B~t=FJEbHbY*gGVQepNaAk5~bZKvHb1!Lbb97;BY%gVGX>?&?Y-L|;WoKbyc`k5yeN<hKoFEi^=
+T{JuO=cR`A7El1n)IQ`cAK=1O~W#BRkFyXfV1`A7w~JGnOze_?mhP+=N!zk><L<4j}(OT{G@<N?L1eC
+dx@GFi#0fxQ&~VkUmW<s6lSCX&Y;k|6eP<sB71|@Q-y6SbxRtHJ@umr?{rT6FtHt1IsFBH2hcT;31*}
+znA9F@$QGwTD#1XXm%1-8@Kv9sMcsq;_lgEDl`H1OmqMvUfU^*Nza;I(BPz$z!b@$>Ux8gD=gl&1TlY
+b?;WV?g^r-`lYzq?-zY#307N&|8{8Ne@7}LB5#*Ty#0nMTUTVy#98m>=y8d`-Xt{5g#UAc1l+j;wEf*
+1>p{8z5TU!*$h;cjAZz`|{rlRh9$Ve?ZWep*QbaGEA+m>HSjzPpG^hru==E=yNM%Ns4{MYZAeD+uOru
+r)9tEz}<EI5$4h$ItW`HIxY+?DlP<hH@G!c^fUe*|$d#ocbM|r$MhFF66=+1h8|DzOy*AU25f#ZXy>;
+_cTsI6;d~N$bJr5M`vA|pEhXegUj;7PY^CvMvnx6KeEsy<qeVf8s5uW?WY?|<D^!Nx{+<Qu)hH&4^-2
+zg`@sed~Bhe^3`rOf#%)4N#9)@t;4ZgTcp&c_8O1Z)j>Gyk_&73O|-_o=UN2vTwP^m^j-KPU8|7Yse2
+REySCcHkK{j4O9KQH0000802@m7Rt==d!N4E@08?uK04V?f0B~t=FJEbHbY*gGVQepNaAk5~bZKvHb1
+!Lbb97;BY%h0cWo2wGaCyx=YjfL1lHc_!Ch*-EOen~9vfdOo%AR8@S=Gjmv*b;76&C`MLlF@OAOI+ta
+XG*J`ZX^Al<nQxt7BCx5}4`f>F(+2*G!@)I@{KD)pTlAH7YOLE-Q+>yi{4aRP$|KEb&LT)+)MLYh6TY
+o|jp(Q+2ku$}Tl_+hkpG5Jl0!LB1hSi>fH}qRXqYb&oc6UT6UBo|K(_(-ryLK54JbSN`L@E2_&&z{LE
+l+N939wfWg-^Q~QPyWEb^?koZ~SyKXl_F&ai8#T{b{qPGJMs1s-%~m>{Km0<Mi)yL4k=|r^k!*C^;zX
+tGQ~t><@=iBhRTZsyyI5y=IaRB?fH$kGX!TS9Nr6N)_vm&t5>%SU2MRu?&!_bF{O>PL(#L-}dHmPYXW
+#LoN9B&cd_z<>Egu6Nvw5NU*OPqF@we}Eshg~;8vc0-NVsP7%f9<QZ>7^SeRIC6rP1>m*_IXj>rDT;1
+&V0%OM0AdYXkIE3C;QIB14E1p673Q4Meb1`$t}X3qPm$<+NN?2i&U8>m<F_<+5s$B_IS0PufM3*PW&4
+8U1{kUFl|jALO~|aH+dgzrnAmF1uzo?8TxBY@mLQcUf7L`64Uw-*j4L8|@>RgRnM0mqfo=Xrhtrcgl+
+<!-pqLQ#E7VifWMsy%5b!_Dj{Io4ka7uXWSH`?0<o-DS(H%R;I721NJ?%)iO!+s-lpsSHxz>CF$gT=^
+l6MXNVm1|24&qk;SvEs(Z>C7i<2FvC7MeR=ZuJbm@@`}FC_`J*R~&L5@E9z8vof&gOMS50vXymqnH8!
+HcIAm&d`(!ZYk{cH*>##du~i9gB8&dGGomcL{R;BMM&>U2ed)#$o_XZxXS@^;}^U3c3?FVnVLR@-i>b
+lJjhAWt(@>#SW1&^l|nyxYST2D>d$oCa%pv27YeaJ$LcE9OGprZ;)F&dZc(TQ#z_TawtW$rc@;gd?Y2
+l`i!v+ZG@sK)<vuwk@>Li*4r?G_0`{G|(o^!*`=>Wo$_b45l!<R<mG$>RyHVXGTMe=&Tn_)m5P34|tw
+M*0v;dv3W7!t~9e|k-}7~W|^Y8o~h_1{dxgEBHL=I+fLqtblS(DOUp~WoT+(bM&s5i)n?Z^ZgsJmsKc
++-v#Qi?O#IY<)WN|4ZW_8#$7c6PU?F@@&*GF;c$!WQ4jf9*Qj}rrBZ?}#nH<PE*UQIee|uToKx5K_7p
+^5WoU%^50Ls(v*RKH+M7q%^S+SkyRLwyvT(zKXX0Y>i0Pw#0>MQl&9?gn@Q#*vh6NFv%r3TS0Rm?lp5
+`^gz=r>h`E-$<Fg!XY9Lv35+8jeY7b)7x<!^3!j`!qsYn;tN%m3TtV!)roKc?4(|F_7a(eKy=P<8{If
+<H;mhYI+o*RxIyFlcYhtQ^(P9#4sC~g~1+P$1;P7&<o6gG_TSt*tsv;7?%N&jfjI=9@7SP$N_Dx^zH^
+&qM+k;1FNuAU8U-#s&!NB6#OYwrhtpMPitPACD}NaIcyOMhe`}cAKSMPzKUklVydE2-+--z4<Znfi0A
++`$KTs-b@*lUPNuTT-=w^+Irh^$P_#YlNrkC9pVYf<U6l&e1^ha~K1W@3#E+@D%=En3f=*r0M8L#p&7
+uj>zoUNq@ka&P`}xZ!#BALH?4nSm)=Q+#T&ryjTZ~>(dssc%8Cgl*TG^QJIwZu9jv_EoGmj?FP4Oh%V
+qE17?$D(M>EU-tqq8MGi6^!dOrWef*Em6wscUhRcpe#YM3Zol3sb&DE6ctBJ%|e%hugJ@(~5}*DLw@)
+;I<UQG?3a+tZ{slcLVq{Bn!T4b!~t~S-Z&d$N^}0y?8U0*$xPIvxjif^`-#@A6tAT<L_~}U|FG9i0JX
+Y-&9qH+e8h!9B6~sm=rT(&-SEI;FxAeGEj*C<nXjTe8E6a<Y8qO)eY#=i8==T(80Ko3`}+y8enw=%B_
+vj^q38-7Ejf=HI4dis>0v0$iZu9E7%~7m3XY)zGE9_n-3qNE+iaMLIRgLqLHB8o_a6Z*pn@gM(<T}*;
+Lz_X4e}#3dOPa_QHpOlJgqS@}FI2#nzMCV(+lt%z8t5Z$4r;;cXA!sSiz9D6UVM&A~`A?^0N*X;r2#9
+-aRsmS;2TDImjM6H|>RaS`lZPc)EzgG&qMo0U6dc$PJqlmMtbgiQV?`<9@q#d%9S)z`Ym%DQMP=&lto
+eNzFrJ)qfmszBd2H+iecd<gZW=p!>ZZ&?%Nu)~2U*6)Z-W~BL!wh`KX;mc0J($L1M234E0@+RKG);-^
+$DLC^a9b7D;7jn<@q7yL&m(URG9$D-t-Do?pqg4*^1p^OlP#6Qi8Ep=~P(EVQv#(Q9(VwP0y2^Vxg!8
+y?!@W+j<udl*O$@z$&}vzgchMh*^$1%J@{ngDMsW_CQ@2L81L=fi%pMdxY>p$~BEPVR7+k@T+JGCXWB
+&nuiSvoILEs(eZcp1|-~;IgFLZgGH&w~{4o4Ox*VaYe8K}1RYnjw3in4N>jcW6*WnCZcLQ@b3JAavX-
+X#JCKj-TlHt`C*K@ugLjjC1(?2>E1@!GnP2pv|X0;eIrMk|Y>G}vy0T1i&Jrn8Jcf?|Dn31>2q?NYWi
+90w+|Pn6$|h~&)3YrqKieri`0uqKo=)Zd#nG$7tTAqRRgq4f=L10oT)cfJO&^SVt1d~39ns3Cg1X)jZ
+<5>QTGAB;^8{z<(lnz78}JX-+VF7#E6uEo#|krqu1dKY`J0;+&X9f#d%qrM;RBV=x+7>y$%pBlmz3La
+~eunz74xw!Y*4Flf2em}ex0mAGp#GnU$aH%D~z-HASY<74bwv^9QM4JK{W4#9OK7clH-lFBhU<J^S=d
+fgOqMn9Uci+Cd3uaTkSOWq4jU(BQyPNUU<8cqE9(v$8cZ6HI+907E)aWs+@O%lbE2vRi*?=ObO4=7Ik
+Q`v_uG)e}qgT+zInog{YPU5!Z&7;y_Oe4x!5P%*@UW~7@yQ_*?$89KlE_=jA~lw9eSsNJG?<5>P(;Jq
+Ku09%B9xU61_j2pzds-}S$vO{;N~HdtU+PNWTuE7{yorBX_psE+~lBxBYO^FO%~Vh(Lc8-APRX%%5X$
+Cb^4hKdr}}oAOOV7XV1@1W(p-#f=Mg@7&p&AV9Cmefju-$loFcg&%ggX^+bXou`qA49Z54dd-_ccO9{
+js3>J`k1>`Ss*;$gv6V$z&8sKj^V$3t#jhKV5RMiHomz-QGUrUNMjeaU+<vXbp6EsEjO(EH33fo;%-L
+y<5`7yIW?u%Z0=JoV|>`>B{VK61|D8T4@X2$S>00<m6-pu&TX!;}vCX&7(ovkyVE3_nA1sDU{c1KDC7
+h=~W>Lo(KmjJjFwS`N0lU*?dXwOE|oK03(x@hB(5rHDufz8#*s3&Hy9Btpv4?CQb5=RofdYBf*Y)DHk
+DiE2ruF53^KQhH(IG7Q8`2MUEn3P(*IC-Hy|KmgIjo-g`@JF#QLEMUVk|^Bi2w|iRfx$Q%Pl%TLYFm=
+MI;B>K3<lLv;NV}3L}D}!oL&Bfb~;*Qpq`kc3|w#OZYMALVGL$ev7-Ud!Uq$mfJv3b4o5-b9|=@z4uM
+T+UnSuuI|@1ppcbeB^TfFV=0F!+XpR)Ib+)K5R*h_|3s^QchI<yLJL)gs_X59Z420gAAkqyi4eSB<W$
+X%U^2>DxEW)LO#HtpsqE&a3o6O1`-!4SE7|BO@t{QVTKvJS{lT$nsZB5KGs2F@`pcF=Ou$zEdii?%E8
+)Vv94sIDi3}zZ~#^VK`B7hc^ZlEg(x#>l+#4YLjb(Nz6#+WJPK9~q-!vaYRsZefkCu4_D&9lW78g%6n
+Bv$LgLut0|y1Jbm9bJMR+s+f<!BM@dv!gn%kMg$N>h|alUq1ZO*BoO0SUnYc(PoL{b8L}T1_wt+o1m<
+swr8y(I$Ttcbm*#d)l#=Oh-v%r-y)xjZ7Tsj_!~r2j8#h7PFhcWl<cT57L4e<@gv8BaU2peq2}{a{g9
+VSm<^bk6>0u8$U7|eMq^m^n*G!kcPa8!=enqvtIK=^hK05gRaBRl7sJ@eRcm%OGZWecmkq$<2qA2ueo
+SbjnIP}C^nF$eNt<qftDU=@w(K?1RN7JO)LQ+p9m6(w6h@mdL)nY$`y|JR6$YJA0%*^+W}$33#nQePE
+8LpmuO-K0dWa|F%ZB?djctMhU8TX>OU~uudpioh@tN;$a{Uc(7HH2I*rnOV$M6wsLp7&(vSzVHiI81^
+0~nQQ%o>Q_1&r#2O$=zCLVct{e~7lTGNf$Ze}RV+^|ksu^f5TMlZXWZTxHD3#DGQ3+i3?BhJPB^-i(5
+ussC(&?+Da6!!W$J&@lEgloaR@xILx5>2<R6PwJ|UdqAiCQNr+d4;bz#A|1i3!(<PPDM_Uf9n}Nr7SC
+;-n@#oLZ12DBvEV-SP*G@JI$WU7gMOa}gFc~{7=v<%Z!fXsVqPnX2-xM(R~;jobLFXy_mOfnc^{_lLC
+@<Ia@5HOS$tv8d3>l*SW`|n8J|j&TL{5dX+fYjZEL+~V|h61McJJ)38J?2_dBwS(U1VOK^bALlCd#<M
+Ug{L8w*pOVsIm)5mw-}u~KAs3Gpbxsc-B(A$w@E?SRV!Qa5*7W$Gk+D97d-*bMb9mhHjBt3eiwu(0wG
+_-8O^4!atehG1imHP`~eHJ9|jL~K796>Qy`26-dFqB{Z#oiwsg&^D*wWs3%6-BiDTFWQ2Ejbp8F6Gh{
+7IM@UobZd4kIh>1clX^!KZ8V}0Sv(@9yW;ePIz*Tcl0Q<Y!et5XD0oKWeV%;o-YNJsRk~Xw>YFWDn?Q
+j89=a@Z@KM;85m;p0QUQUjNP(GBkr?>18(=q0suGJr+UBhnUO^XCpk?Y)YiE3F2#g+=;7GoJj}v7q!D
+77uU;Hvbnp=W3=<;Khm7ONEKXYQBE<uZm`D>BpgeUn}XzXYdl)3c`wqWf#cKaAi)tsmWlfEI@G!{J~_
+S8Usklcg8%_OhEccT2G2^Gr<(y$VUWL8EvT|YiD&t2!}^}wjt23aueW$ybhW~XW=>0b8!?aWOc&VY-y
+WsZQdB4Xx&<mQP^ralZz8E3*<bhLzBg1{sR7REPvkzwe`TUIC|v;a`VwrG&DSg4eXaLnSk&YNzVfp)$
+2d?b^wMwk{^!8K85)s);zP-Rtp3AW9)#KJJ2HJ*EeLG~tJYKfbV(%rapG+V^VYJ_eeeiepCOaOmLs({
+k1J49#=j>;kWWypG*<_K<vsqH{)jGC#?jUtRdmjXtxTGrr9S*NSzd=WlhP>BNCRt*LcB{B$D2rNhJ&S
+FdqE~@H^mJygvKmUC4?CjOclNYBi(&sPEPoF<K`}t=j@vx0^5U#T(C#hm*o8Vxas;LTjWY)I{2E)eW?
+T5iE2SXlbMJH{gi2{Z99G!l^|HtI-#2Fy#&RFb+_|WJJYbj7OJLulghC}fvq(^_8e)K?zdREybh9A-(
+MD>btq@=6#VqNn7fa-IAl_KtT47v4y;hG-M=gG;pk6wL$?o9!AC`lp$s-Qx0v{YKp$j8~4DVhoUQ}xC
+iBRBI9I*Og)ZOUj3NAL!W7R;O2*r;n9*!<C8@{vi`xL|BA;V|6ljR}PVV-`Yv=8fki2-uSiLcGKA$=X
+t%02oK==z~!hW;y_qx9_M-!6jIBZ6b>V$hxY)*O&$v`v5%rZy9$*<LoIkjVFYF8{wT-zXB2j)>@}2pi
+Y@`PeCF<eI@DaZ-Awd*cYroNG};1Eyn`51ZKKe#|<JD|Frxp{waZfCx4#&`9FZhR}+`UvHcln&r8vTf
+qQYqeSC4;BY}RCz9^1#|98ryKb#2X2nHX<<uKGAEX%%(4FqwoY)r@S>51U*+pS^~%z0FPf+1Ouf+624
+RX%|D5F|^)i-pU=8j-Tz(6@@4D8lbNOTgk27!P9fb5_xs5&L|TM8D~fpK@Fvj(XgiT4|O9u}OlNQ0Nd
+OIDuTB`;WZ-2J8gA#6n%39K{%6%6XTjPB5^hb~-HE^}|?UweFOvkTHueGe!O!JRKJ1BJ89G8Z+48ld!
+oR3>w<+VUyG#08Px-u!TfY;62w0y7`0rqpo$O#Bw}gknayiO8kEPDNP*w+sc&hc!^5#?!*u%vfp;J!D
+cHk7dbz}$4T(`i|b9!4H=R)bzm14Wl*r9;ZNRo4EW#0&EEq8CUj_n;pf(>p^z(HD9IMk`*juv-dI0i4
+h3+f@>^UD)wZj*9nTPB&o@)j8~P2nB@|ttvL-N5nr*qTwW$nju2&ULowA<_>mW@DOsQ}9a1pFQvBxnt
+MKxzw+}m~@Aj;gZV}}V5_Ex}N*OzQ7v6(^<#iGiV<omR1n4ynNHAfdt#UL072Sw@~PP1(bj6PP|%eBI
+aAU=NrFt$xm<nzyc&FRuK4Bh|*)Hk3G?xIntFqaApH8B>Ic>vnoW)9{y#+f=cNh#;ppHZS-l|^1&8EO
+T~<ql?pF=c7!S*-$cqA?Flp+*J(IIs(<H>iBFLWjKEYU8UBzY9!D);lL@UKWA4-uA^S)Wa2?wm{qmQf
+QmO3dMzqYK2y;S*TtUF3SqnGgahDUn<94g(JJN-Ed^DfES;Io$$lQ(I_m10|8Gl7P+K)U7rl&M>#A?J
+<H;w&x;HRCL05vuG+IJ@MgfeJ;FB8KCN!_?@;%S=zH6t|8l?T_xkMF1@`Lr+jOvx3O1YUgXz`p@1x|?
+yu|>HIhl91T|uXKa5ikRm(E_Xu1o9n@ZHv!EK7#_Hh!Yh@;WQ>r3tEfw#W=Chz`{w8=37_h_r+*Dw{_
+Cx`mAiyw=Ann~`-V=C~9;shZ29J_r-yq$-jl8vT$hp`$yX0}erB9~$?6WomSLKv3Gz*rB2%W43yf35u
+vBJDcULmUJD>->W*01Ej{t%0xOIoEi*!IzNG$OIa8~VP6=ZCXR+7*9gHq@`0&o>OFCi^dhglLyxid-4
+h-xAQ_l#gUL=M!qCoKId*t-2J>-L%t$mHiT>l~BWUcOfndu?WR?&Pnp)&6D~$n8b~4WnjSfk4;!i%!0
+BX@%oBnfWm5Py#=L%<XzL1~QJ2{EW$I9>!SF<%huvSa5B&IZOq?tPz8BkS@KpKKh#Ww$S3%bIbVl(PV
+vbIi6q9_toVPdON^dnhYCc`t#uT(3u?UH@q0yutqk4|K739)G1aWHeP=}cb`4U^7>Zg@_EPsqyQO)5>
+Yc9t<Wy}~>n3QRra*m})`Jmad7ZOaZ3pLLSih}OZ7;uMjzQe@73dw@L_f=x+YCPwskoj#NoUcy15({$
+b^AkZkUJ$NwV#g*i8ymJI0!AL8VR1@Q@d8roV(P-tgU~@_IRWIpWu3KB5a&Zw7!GTzVtwd!~e7aOGg=
+u7mV9*~cn)A80*(ybF5C7(+$9mxDwDcjFM`+tGE6r+*yyu>O>Qefvic3^%_T<<<HyT?(n<}r)KY!o3B
+hR9d#4H_`LMcn6Evx4sLp^K?J1aI7mz>>HQ?X`bi+B&a&9#mBdg)d%S}*`!qo>XXUTw&qD%&&}Y<WpS
+VnO)U0RfQTY$AI%DVRet>dq%zo`C0RDbhQ!z+C9qfWxzeJMZ~&+w>Qn0JbSf*`+?L1jQYa+E<1`c2_4
+x(O5N#mrdpKtz^mdie^X=Hw(5R`*8$*N}CawtrRN>73IEI0?6mntR5>{Y4_Bv@XI9f3K4+B`%4B4dLx
+wsc7_)+F{Fe5^No5trNG89Cp7VdjCArs2C!DJmfx%Qay09m(Zi2yvg|^YOFlA5Wlt6&ALdNUih!ozHg
+MLAW@rZ!E`T$QmQZ*|H6*<pjTkx29zqO&^*k7JV5?vAOsqY(tMBb6%{y|vGY$sOZ?HS0_|U|1hafPv(
+3;d9qv2^+1QT`&qw8$24NUhTsxl2@r#d4fn7f3`3|&Se`LupeSF&Pbr*1>`pYPj-fi?#04$Tv@jDdL(
+RFsMT=Gk<{h)ny#?kjF2=nN)gCRS)`>)s8H-HetzF$T`T3(6vwR9EAH4g1|H&|ZA9$5dV^K_oP+7WKS
+(Lu$`SHz#7pNalEmd)r6yFtk!Xo{=&d>poEGS9&)?cP8tw?3GPlJQ2^uukZzpFYo@1cLzh6=uhMSOeS
+D)4}&PFAyNw13!mEUT!4E+g(ot&2J}HV0AJst{)Pouw5o^0-KL!I6TK?IQ`8uIQRe97+jlckD+yRxXe
+4>DT?w5HwG_cJCG2xe_R|t}n=258yI+aP4Kx1w=qsGg*LRa4jLDep*-Ksg>{D(sYfs|$^23ujYl^Y_T
+{u3y9wYl-^==Q**{gKjQIz`!!eW1@$#7~Pz__cjx+#^Tt@TETf$vmI^@V1ynFu@g@ovavkDXY-wVnH?
+T8Y8?V3BE`DHFl52*z*UO+JwC{vru9+km+Ls#xq*-5!U+h5CUieAxfrtI7L{E;Pivm;a1G#@Yz1v8lR
+G#qQ2RW3lq;*jrO{OxAUv@vVzR=lYABZdjp?w8NO*-koEyXGL;}yKvm!xajdz^(Wb~gU8n%#UoUhdc(
+>DMmI$&2p+X)JfAVJt;zA3*?Y<^z7^9Nv!SCyOotN+O=(l|`f)t0>Db`$fQb(V!L5QW@@Vi>Emk^HX&
+e3=Ww!VFKA$r*w>mJ+lrZmcXE=e7Kh7#2o9qa8*}m}D)?WdbXdO3VJht)6$q;S!T|JidVNFM->2V)d0
+bZdO)350W@QKU6cjB94YHv9#De&()lL+td5;RA_-py&AW}QrJqrn|<F-1M5LRM<RS$eup!vvOl*Pz(T
+PXb|ety1ym<3a8v6x2KF<i!;J!*ls0T_-Oj!j5IbnRf+-izE2KwL3o1pfer^b(NaldLTu=C;hVTx`^Q
+!2Y71E`}nH^kndmZLm?>vjDId>hhI2@g6>M$1I^9<17P02_hCQ*TK2Ih_D@#y+j~qny)5av5=;3*$FB
+Yz33l@`(7a+8%&GX#K>+<q_+T0BQL_gQ-O<H6qK`b$9~o!3F%8AM4_4Oseu#*v%Us^leN?B6w&v!>_{
+$|?>|bOxOcD+PUSmnkX>Z-gZ;1kV8lc`S(ze<*3sJg6+?ZCqz1EZSHk4kVe_#8$0Iycjhs!M=<<?;k%
+<Lzo%Am1FbFmD%$ZD=$@W2^DutNhRr^s51vSkA1lqr{H9I?Uuc;Z7j<3qC}$dHJ&SgfG4Hs_#wqwA(x
+ZWpZ0mU_PROJ4X4C?8+sGVmG?y0$G{h*Fhd=}7C)2v6mh<2c5t(49MGV^8Kxddq#aEsC@U<9N?$&ahc
+%yh`+}ceUCG^vTdiGDQ_*07oE%3aqcc_5$4H8XTArc%i6r^-k|#YIx)oKkiaK|6(MBAa~Z0yM#v?Ko+
+q;sL8vIPDux$T64z9Tnn6VSw#kGIK_~?tQ`N2x;yHzWP>nPZn9=FZYu{x{8W+45#=i{$z*XL53P4|Xv
+~+l(f5&(5p(G<U<!KKT$d0W{Icy$Q&yL@X_V9M5Di^6d(k5%)5ev@a2Wiw+XYqZ9DBDiC-T+51`-BX=
+wnKJs$aLc?&$jv5h0m?9Ul`vh@>o>F$o$6jGx|pgi<SH!0qpcEk@3D?ro2s-tk}=<2~n#$3FYt4EBv4
+o^DtNLyo(WN{m_FunLjXRXp(wdd!aXDhPPLkd&FdB}f*@2^SG!ah9Lw#9cwwqB**BruBy$(ZB!Yy?YL
+uWKmS}Ibp?@5(cB%(nWi$1}gyRG)XB{BKB%EIZ0#=cV&gG<h!Fvyomv}AUSw9ua-Ny5uqK!eV%vo?cz
+#zRK-H*%RSOOg`>~^aO6$EVsotCM$tPn15;OM>SZi~?qWHCDu?%4I~9Ao87OXn=3P|zPhtGP#~ACwun
+Me4^U;E3+-JXgb^5OqE{l_M+c8s-Ht&YP9sr7J?5})=j{T}<Ya;gsX8RDyKqf5RJ5yr?+;H4pX44d4?
+}gkS*>o5iZqHPwAVcsfnh|H-O}u>hSV4j_$LWHg_ut2O3+@IKCME%zSHpDc!FqSKkAuxY0hX|P)x(Dm
+)qknqgB!0+!R3FuTmBRIy2(nILt~8zOB=WKNHX%%Px<cO8CELw3}Jg8{<t;F(bWDe;j*t8xMP)`V*S`
+>pzjxJm}<PD=-YIR3cg3cyM$>RBzM69Fy$1tn2y}QyG@Bo8t71D8yGB1LHlcOCM|U}9MS2sv-3yae}D
+2a@~)%pF(8CUG;)ttfkhNPm&<79c(~`MGU~4`Ij+(J-<u~+5HBBkc>kV6*VU_+-z&Q446he8tHr;aeo
+T<v`wyYZzMJhQp*-~n)f<DWfZel@R6V3Tdby_wD2iWNJbq&@7UpZDy<EqDo_#Dv2>SBme_oxOou54M?
+z>)jrD>k{%A*ewCJQ#|(TNJBLs(KMJ#tI?-id_(>{%DS=7O&l^kZps%QC$%cY)ZuU#JV+=Or7>qP?c(
+U>kV=In+zHk9mh{xZC@#hUpD79W0UMvHj*n6FCTQEPtm%VjSCV?xiS;W1}?uknUIw6uLj`^Mu7~p=JC
+YRtrJ*YK_2r{q)oD?)K;gL>QNcv<jC7Sc7jcW&yO{k%3NCSM>iJNKT(~r4iMD+*Hj~M)yWp?`^ZIcYG
+O^4=<vX)kIV~;+M-ISgj(nc|?CwHj^8rKX4}}%k&$a1`rqi5%aw;f>kv2C*&<sZY+K9#=5av?C>9|`n
+_e3<g%(?Q<`BaFXKUFrSZJo_UJanU~3H0xwO^MFUighvVTZ+|GGw-UyZ({d$fMVoN3~pFzlf=RXRZl2
+rkZfU#d~A6_KLg53LDyc7xcd!`k05y8XYd3Z{i7g(5+wmk!{-i-%vZOOA~Ct!MqbS8jURc&z%`{~*<m
+$*dX1E=*?V__uv85$|Jf3WH|Mu;bR_m;bRGI=0_Nh8khj@z}#*SI53%_jTCJa_-oE3mZ)i{ufY70|XQ
+R000O88%p+8y}5(Hivs`vvI+nI9RL6TaA|NaUukZ1WpZv|Y%g+UaW7wAX>MtBUtcb8d97C4irhF5efL
+)=UKVWd_yZce5J(6M!v>PP4UJIS<!&Wv$s@@<X+r*eOR{9ku@kbehVeyps_N8rnqLQ{Eoqey&|0pf$@
+p|6)cMTiIqS8$5_=!;odnT4kf51Wx+0I<*owR#oGKF)`3TP=$QCN{X&eM(lls7insRADBd8uN7p4yOq
+fIV5ke1?U(5W>%)1C{6h=FMX6i-L4;fi3B0J$`l2@$b>PoEzaaDp{pBQ61a1e;})q86p3Ax{~>D_;Zh
+YC7GTkCH9PC<zSdncqM<gp(Yz%;f<zdJGAv&tM<@SwX2}SD>`avaA)%m>3sx>HYv_6!ze)chD1xN#K^
+!!hq;2;#3dBSY48bzsNsI!UT1fL(~p{ZrvkGjA$5iFyb}Q!lJ0bj#`pF-x4XDq2}9c`j!4(=1AOIy)n
+T%X4jc1vdQFfa`651v`z1^$~>95^PYTrJt4Vjr`X5J2Rz-66a8Lk=L;Kc?Q)I{^9$G#DD?a*jFL-FoL
+Kd6f`?E+=u!g*@(sVf=d+nR2hk-~@GWFv+X4SA0}gu@>cj+9e&7%t=gnmzK(tcGDvo3#xG2{VJAy$&&
+%f@9UYM5Dw3-iYHd|ls134)rCi#fnj(?gOZXp#6_f}m89N&28>z4+X^iC*Io=<5E00KAAcYE<$LK1rc
+;!{TiTB)a=EvzCZAnjBa*5isH7j|<hoqCZ%vCf^#j*N0(?HBxTcHApFgDF>jt(x~pldi=2z3xCm_lCE
+&_(?CPA7wd_<9%XsX|!qLYc6|L%!lb-aqNS8<Qusj$e(eU%nB9B>(7eIV)0Xdfx9WnazREmbNk|UJ5F
+aW++LE^Ta*jSFfVlO;uxN<#o`X@el@9Lh&<7#%|(r(!-Q>ev6qwlwMCoQi<pK{Min3Z%&6R0_(dq`H5
+-JE4$NNMKZ9mPc19Fz#5h|ed#<m|Cq4e)6@-DUlYIwn5oIf^)%UG($|JJa4P(6rs$Gm*1dY4xi`_bC+
+-+YxErn)!>_hgJL$i0dufEzH&FbqXl;Tcl=C>{IhZ=otVX)+_f4JSX!T;f!HI99U%U&u=%-FU79rhcJ
+;Ry%OrQ^ocXqNhJETNsf;=ASJZ0^*S20zgKcC*%zQL!BX&A5TzXwhE~{hvr;b*|hN<+|l(T+N07WLNC
+`ikJsH=!Rb$vugG)P)h>@6aWAK2ml*O_Ex^YvKb8$0081Z001EX003}la4%nJZggdGZeeUMa%FKZV{d
+MAbaHiLbZ>HVE^v9>8*7i_w(+}v1*>gpDd$rjNYTQD)3kRv<bX6eB$xKXuA|TrZR=JR6;axav)KRMnI
+S2WlI(SgrbTNcdzLsH4(B~XItYTl^7J+@cPu|tg*b?^;Y}_}wv{z|U8;r`#W&)|Hm_-HuGk%~bJ;4EN
+*Jx%w2`%%&ED<>%QL~*UexeSv1ZR3_#>1+R0okU&JO$?U`_XJdCTN>8okPY7BeLm>>%%uEI@H!yv&$t
+t4h`lteXjzi7Zcf16UiWL1fz~AOP{w(rLk!n(akV0jaeBSVeo<h^7%WYs*a3uzZ>EO<v^9kp=-1tA%P
+b7C~#pv^m%Yhm9QsFB@EQBUr0oc~K~FPkX-4n|)rgDz9){FUfM;Vwu9)ayuLEH=YGSFq;AEac70x?O@
+CHQ7Zeb7PD<F53D&>MpF3pWu7(*_GPZ%@7EOyjTZ~{t$@e3Ey!}gzANG7OwR?n;^a=0nXKaqM9y)k_`
+vI1;Dbf^H+nobq3((AX1y-&c#&t$z81`RIEPMEBF(qCL&CTAjZ1f4g3MrhvG^$!v{h$uVk#-^=XEXXs
+c8q0W1-?4g#MGA_~!WLHE;@~jo;49DsoU)GwDnCeg+gYK@=ADANVi@3_QgDlWkszjv8KrI!$wJG%?qE
+9<bnv$!(JZg}5fDk?8oBtAy9-KED%0&*_<mT&2z=Lj&IwBFXYeuIqW7u<hiXXp;I8THCtl$gFs?Pa2u
+PyQv9xsk<QnS}=Gun<WX*m?Uh)u4fEBfgw8~{sW!_97%(l2o@&*K>Xccg;H{-tY<T{T5u>UYrZk;?@M
+|YCP~Q;B1xi|tVGSxQvzJ4;c?Qvj&H?Lh0$y_%fyx?;8^o25kECGS0QeF$>3GQo`0%M`x>5lqsOQ9dP
+yW6V1ZhIT{r1Itb^~v_*oR*Twi~GvtB>DSx3JO7R1Ylp!Etc<tteVdXsP2L1V%XalMpD2X}~fwQQ^Kq
+o{)!jeTrzgJ(R0317@;xE4)Ymjj4}!D~1I!RAiXjb(}cXX$f**aPm59+q}DrECnUo*1*D5=|JnBn&h&
+461^sVlNAb6#;u@@Wh3@2jNCh?2+i}Mrgkv!lCp$vKNemX$d!!LtG%2pdj`!i;FqLL1<}Yzoq98Ufoe
+tJa@2U-+l9?^TLqsys&FX?O$o=FDbfP2y?F6?-x~f<+FX$RLc)O*c5z^|9@7CyDPEVtzJpF;q~=~|Gf
+U4YB%5_1f~kd706M+0*QXv;fk-71Y04x)|LfYLBO0rVO)ml_gC!o7Pd`p6txG_4jWK1ipR_<6B!i5U>
+(+t94+#(*1>YV4FXg&vnnOgsWtmJSFnN5LlE`MxngfI2O!7SFs^jsLb=Hvo_GPH*%1;6Q9?>2(p#Vzl
+9+D3hu0X4@qmLhJHouzR!w8@XLX~H9btgHS_YA8m*|}ZIVxBL<J$mx4AKNo$amzd?L1g*XjP6Oh2G2I
+I*ZY$FND$Xzh;*{9>-yMj>)0gqj9Jh+F8&v%oME_gJWuH38A>efU|V@0|=&MunistlOH{a^cp__`RoC
+P9s>_}1B!I3DWg=SmtwCO=ml{QbT;wm+`yh8DMJN=$PmQuWL|~<5n~KgpqB@sde+rEheUXka{1y0vRz
+w!M6<;8Iioaj(woIB7~pu_FtwL$0r0>zfr&d{ATx*bnnScrdBLh$z5~C)Kq8#|{l&NF<wmH&jex*hq9
+u}3c(9v(jN%^FFl%5C#I%tG7>>HI%U{N%;05gsv1FpbEeyRksoDJDaSj2y5FAiy-*#jWs|R}wXkX-ak
+Fu>3m#`ql`inPSM2ehkpR<5Y?{ySLHw9@T6i%)^LK;T7V~Br<7hSx=yrK(eFK{~YPA9&KLMCYf`a>_q
+5J;>g@^%lP@ZVnWySxC8$+7T)67`24s@ok9qF~EVV#PWFyJ&v+VZk=Wrz$LPb!Y$ude=ggNBg0OKzpL
+<4zy(37ASYS{*nZ$Cd!;82B4GES;|Y4??&j{AnSO}DXP2b-vvDUmxKwaVc9Vh;!+9W1CXzRw%I=aBiO
+1yrBbUP-<7f!L4;VhZuohjOHdBN5LHEd&KsR?f><THCki1Ll^G1(JVzgsmn~_m369362y_p={^DET%s
+^Xd*Wd|5;vNOiF!DyWkv9o+fkv>tH!eze@#+fp1zY*{7NR$#7vSB9oDWiYAOXii^Bs~x;J$OcVlQi1F
+^hsd$J_}*@}3wEAsAT(mH^d0$M}qBI69ViNPEDp0=tO6hGmiVAmVzdx3+}}G{jladO(s^B;7jUMtvN4
+ELes#=TKQAuXqL8k&)_^5TJ~<PH;9xH>X*7b2E%GBO;%FyzZp-j4+cVA^HV@FF3~t2*e-N-o!YKOk`~
+;670l)Wh4i+3%!&W{_Q-(H#8AVoq!ntBY#u$ek1q5GAWeF@39F&NU*;&Fgt6;@Wc;_(c<5XkWoEi$Z&
+nUP4;LFg``KLLSh@RSBPW&fbniVAk4%V+zSL*hMh7BV+5rkj627a@rd4u2q#IW)@SC8R*eZSiBp^U*p
+u~?pY8&HZl_Fnw%+`yl#Mg7X?J1pLi1MBH-Asf(d&#z0`Jr>;bmLMgl9uvvJH?Yyxz4G{2+p1T))dfb
+H=fpSR9cB01>7Y$A@4OY|<vi8{M1~qZz1V3vB9<S<Ro<bG9w`4p%TefzgzPL`flYSb2cf=8czKIQjxy
+0OOzzrK^c=(C=wpQ5OK@l{ZP!GfRnLyKt1x2}E5<>EK)Uu$aa;K$svpqoxb!0O&@b17a&~Tc+v}#}tq
+@w>wCEh`!0=ftfTF|M3TGJ91@7@`t-xXrk~QHFQo?;M4qe5+02^k&t@V*ic@btL&W&8&fuu>GoL<emv
+7Of;%BFSj_dTh|_JfJZY?i{Y3f+DYc&IE6)4@S9zQVQ|1bgwmEdBzA#!n<Se?G1x;BHiV<rut-ONp3j
+vrMK-#pB(!1vh5XuWEp$NuE`(y)8o5@J%T2Ud`3q|k_=czq@J?@@TyI{RGJJ$%_*Z+WfNGehN{-ZxQc
+s5cNK6I{Rfu|EohGQ`FiUVKu*shQpUL>Z?;u)nfEg%mUW+oHR*!|aSz<!=TQ8SX~DCIF3u#-B$GnFEr
+rn3_D0o+f=Q0i@~DM(moo9_~+6tLSdO{C`aklvnPvdyt5mZl~Hb?OZ9yrug(ImXy~Q^M-Htlr!8>ayy
+;_QM|UR^F52F%40xw{`2ZJf_*Yntts&@Rg>REXpC(N_o|P^++`eyXwF8!&XsO_DetH>*>mW?7>|1T)7
+V(iLQRE2G7GFW47rwak|EMA?2+~iu@L~0y$LZSDUDsezmC>Fp}B_7^^Y2Eq5#+EDW&(wx<B)q%PzNp^
+i{69o*ux%ja}9=AwjJWhWZryP!DLY2pI#!Na>Y+W}5Gy4&k=N#`wiBxn|}DKEG@fpLVFM|=9HogY#R9
+0SGB$6gv#Z}WXiz7m+-g3HA5t!yE43{Bs}Ca?g4*|B}(MFVf5KXrIA**KH$_j$SpE2^NprW}fnL)*H>
+(B3t3BfoHUdZV}+<UoVYh&D<zh#|Zt#|@yA{tkyPz=!}|4H*aHjJ=y+p2?e8CBt?jcK^u9keYQzFbn2
+uoY%=;ddzr*>GuNj_SDxz-e<SAYYk<%bDq}omy*`p^qkbfP^(Ph34GBy1VCGI$9=hAAq;kN#HUN0P_-
+ai>bb=C`@#qjL-4jOQ#$=OBo7hwnY3BY1=ySO1X%7f+V_246rijEbM8j3_vZ6A?2}JEq&A(KETXK9DE
+hq(RBO`sBTr3qN1o2NyjJY^ymAQS=z`m5?~lsx1NGV0FTY+AtHvl<gEt4Lh(F}JeZx!@T8dOC#p|PkM
+}JC4ZFEUOrk6?6vyePXs-x*`0x1Vzqm+Gte_<Q;rBx$FIo@yTt`+N09<#5EqnLw3ZmYOD&WGK_5<8I{
+K`|0E*N$RT;h3s<aH>4yw&ApU>e!3$%!Fytz!T;KHcQYB0HSdd2A@GG`cX$&A<EDNj@YLw_HoyJ8Y!3
+yd;Q_sJKTBgXg+poAnYnO|7=d!^hk~3-%4!iG<^)gMI1c1n(^WbEEVWN%Q>4N;R&9_C%I`#_IqAqJF?
+e`z)6GHdo}CBps{RS1#Q}<i-m($M$pIV{vc=2K^{tIvPi?8Q6IdiN)U<e<4&FGP8V(3uyG~w1WuQMip
+K;a#)<`hGU`0&MEEeBmvP>YqK)Q{DNPfoWK2Tg>0FPXQ@wsYf7a-o?Y_Cb3z<Ix^c`1UHg`HO-mnj-3
+;b||c(Q3TMsH3>Oswr`MghA!>?V+%tU4<Pk8&Ur>jL~n^*%jvi_H#&sUAn@&+CF)vi9}#;BvxZ3i<dJ
+MlTnAKsS{s=nTP=AOcTz28Q(YCG{0p|6Fy)Txg05ObZs6!r>hlgPQs}jyL&2H}h+OVZp|Ga2(2|ht9P
+0*&bVg@>9#sgkVVA&~b-#a1-Ce9|XF9$E!HeX}Vpbe^SDPkGL5{ZfMnar|1sSkXDc^jrtVm2`hciN~5
+(-j1CR(aKlDQYJ3pjD+4m@$atdP1`mWirryYEWuDAwtaJW4HnA%_F*6qle>Arfnb_@^JwS|!@=^;Jb%
+Of-;QOJ{7+|6VY9p`&#jI-HmPk)FpX{tn?PGj;X|&6~EYjV=n{EM(Jl)K(M|d@PImdM=1ddSv6LRC`!
+v^3cP63SE?P-t=3R8(1Vi*QNkQ}~#WFeJZ4-SsUDCj9k`hcXV484s`_6yIq^nek=dkP-PU);zWS5rQT
+9x#4*mL=wt;dSFjcft~!obhaR;+STNe61sR{Iv>3RCUP|)Uo4RAacA7I<3?1yW4Qyyop0AXQQj(?E;G
+=W-s9h&l2!h7X93xgTWStraM6GgX@>B0-tE8K6u-Mq&pa$d74GWs~cHtgPZaT>f1dS(7~0DQw0D(p1b
+FA#a?1Tj~Az{_3|y=hVHN7E+N|o3;%TWQT*YxhFJ##B-9fzy@2A#?qv;%wmCAMrcl+EnDwR{4^sRH8t
+Ei(=;W~BVTj3f^@m5BrUl|CRkN4o61L)ZP&?=40MRf>^s6DMcWLymzj!<r0uCYNAa3{@;$t)d0x4QJ=
+Ztkdb;N1~i*o(k<+=$cZ2n+TJ<cbL^kRV<7uem80~&o(n@mE^o<=<3CNDWNxZrfaB$ze}i%zxrscPu*
+&&%5TR9=kR!2j><{nG`NhvdmqfM310kDXfc^9(-Kuh;EUZfY;xmelPPJomLlM}KtF_0DWnj*8#6HWp5
+y3oe0fbr2GLJ;3MNUrKWu7E*9yLYYu$op0za8MS)QOX<rdiutDmbPYw{31?MXR}wD~+1m_qOBZ|5i2X
+*_iL;KbVD@U|fAe9-1;-7>RLz(*+`caQUpj7h;^^e$X~f8IrjCG4Ix)wWb|tfube?f&6JG3Mw{)RrJL
+?b5+Od}spH7Fpxbbuz{EH8>`!(oDTj%@ofZe$SVjun-MBYR8V1E#TAN>6fm5wk|)_DI>&*-IXe<gGpY
+HcHK=rSR;r8<7-I!`Cp6R%_MQpChqT#BZUl*df$ORJvS5%~NkkY$=<qL$@~z*u#x^8Vrqb)YjrH_9Lz
+0Zpgh)L@%IJt+t;TM6D+oJQ+`(d537clKUZzfwoR@G>hodCc@Eu`iTlkoz_I(kF@GrW{Opcr<tw!oX8
+^>(ybOcAtaWua`PdOjpjj%rn0239tCC`x1S@%`-9^M9ll;_?Kn>8E2u{^eZP1`PSJgwu$Wd`Op<Tacj
+hW9AuNB(wF_p0iV){3q)_YWW$h$a2%1IP_v74$yxQXC}~V&D#<^Sp#N7n`UH;#sm9cgRXQpR5dNqy4E
+%|~f?cmCE5q^p5fri$ru&@^pG+^+xtvIxCXl#?$7q@uz4*i9xy65(QaUNA3+}xB^|ciLx)t!r67n{Iu
+$q7-{utU)>2^tt>;=ooWlsE{_N*JaEPSkTV+E7<jPg@D-`yi32>Uch)u)qmnsF{iCxG*bx^}EjWa|WV
+QOZt`m*wq-BPRsztB~EuICB0IP)h>@6aWAK2ml*O_Ev7YiIQ9t007WM0012T003}la4%nJZggdGZeeU
+Ma%FKZa%FK}W@&6?E^v9>JZpE`#+BdsE9OwyW3Zth+v&E)OqD&3Bd6N+L$%bjU0H=8awsB(02BjA=5h
+Sr_dezc3}rdn?T1Aik(l>=&V9^qI-O45$ba-jE3akMDX}g}DVn@hMRhfqLhYouZtAuZWqoypW%{*lI&
+3BFyE5NeTc$Rp{9s=Cwk(Uwlsm24`q~a5bc>(zvX_eMx@`lKnVMuG;5qx-$x-&~k4Mk`>-g1=b1HgTZ
+TZWyye#v}Qu5mm#j@jXKgvqBc~`gmdfdUAZT6y2y4mZdE9xpQ`R%N4u*qz~YiWum&58=TLW^`+7G_z?
+>s3u1Rji@>u#{YD+8<Y{!*yceQQN|zgpd2@fcg_e2-U@gyslTWRH>4AyWC`ISvMAWr&M-|MX{ch>~8D
+!J#<wHW;eY~isqC{?&{QcMQMR(^FqmNUAGwk)Ado%sY5EOWxevKnD<?stt1pim&l!fP3%-xvdiEd0Nn
+tFfD_jt4=jjUd*W67Ms|G*P*q)9ull82!B_E3`n&Y;w|X!rs;hD<VByGIQoxwY_qe*Q7S}oSg#Yz;ur
+9HzuNxrLWl<L0R@@fdM%3j>wjdkbawBeJtBADqTAXaVO-<8L{|Nt@1x{Rp5cZ;4$qyhK%lG*eAQxX-O
+Cv6QPKA?6mH`W8nK%^ZQxc!7^>}D{F+q7oR(erXQb9Ar^XJ6Y=P>77sII+$me_<iu7!3+gwD^gcFt0O
+-{)E~vBxRk{^e2j<_J2pGDR%GR7pGid$Q@e<`?{<enBNNTTJKJ<ajoD_WI?^qgQ8<Udi8od8@vj?WMo
+@Y6{}ECtf0UVcD{}DcZV1n8Z!q7Pzo|)onpJ-Oyr?zz@Fq`0{VrPfy<*KmGp2QTFK51140rkua3$CaU
+}z$PL5-aYv#6$%qyDrjhM32L)8h4v?hgVpUufpahXeHc~vu9>6$BkBA3hYvn8zXPW|)WL=i^t)fOJuT
+PKv3JA@sRo<?|N&@wm|BjE2j>KuV5|17}{3d-ghp`?%eDsYtS{0}P(#g@QpK$dty!^+>A7K68z5VL#N
+BoW;e0TnI|GyvZKglk>p1u7vLwue7`Q+sFo3o=IvezeP$FE<VE=Z@HTT-TJI=6Z@Wi5AcfxJVU=oA=p
+AWGYOSR+4lZJzC}uWGIwRUpctD=?fI)%iR-o)Hk_w6s@&f{~R)^?uw3R&iNWdAl9eAgy=RHLYCBc2})
+lWVXo_@MNs>sH|&y1-d5N)Mjh(Dti#tO5SE`35pXtUm(ltTGT_Axb-Rp>;o@8ipG=%ruoyar}kA@U*=
+_|Uq=f?fMeub7gw1ASpg|hdi5kHE2+8%s8mqASU%$`&VD#LJ;Mb-+oVorDfXO^Qm#>CqMcwKG(Jd4X)
+7d!t>FcgC0T~Tk!2tblVu6m6Qt2r-p<PV1W2aHfK`hw%h;g6N6B(Mw{ITK7YL85DO6_Iav?73x^z__w
+o+xN)dzi?01UfmoGz^4agHVnD_gK>h-k0sO1d7v^)gd+-!7%s3pI7nbSCz{qt`_Mp)YTwYwTOt%!3k|
+d2eAe2QjpAFJU9Y*M|n$;TQ%vG=_Nz8+lM8@!i{i*tn71pUSvBA=3=Vg~M0%0<8#Fn73DI&<?<XBHj}
+}N9<knFiQZa%-1pGRjq-p>Je%+Uhj!i$Hr@h$QJmd51Hhw?Pau?$05)2Qbiht1L1_WjVxgaxNxiG|7n
+XEwb>JYkz!R>55N_H%^r=Z>%Qy?uxrG=1S0_cNkZ`FKnNFn{_w(sN6GsDz?hm$kUz&}8*^%eFSWhC@G
+SMYZi`llrwXQloj48E!dTzfZ9?02LGvLmoArZFg#2uss`HVmo%1O4_k!^PP9!xGd9bCirwLY**cP%}j
+kPw&AzD>SsZ!?O1uQtf_OJxcNsfkji{2&Lb)yMVzo$he^|T1J6Q$uaj9_|>bqkyWEqAup1B?fqExrkx
+;4zv_)NkZtSsbqg*baa>?Rx{ZJYgnW0m?TLEz`V;ZCF0Q=(yu2Y0So0_~=i0B?*H#qn5T&)FW*Zjk~!
+&<V^cBb<5q!Hj}uIb3Hrzi6PkBgJ|YtMt22BV0M6QRZ1Es38c!KU~aH^XzUkFtV8~o8$uuIPdm`e*Mr
+`?VA5B0H_+4gFl)M&Mu1z{v^8+1N&uwJSPLW^zV~GX;IsiZ5|>$axIX0ipKHJqf}{AoWfwLVjKhv4Y%
+*XNo(qjG{em2cuOmhn@d4<{ss|Hg;2vTj&Ls^fslvrlk7S0fV%~O#k7k2$peI6*aXVKYX;)lT;5%htC
+$O%&v$6cp05;(5CNmD)xQE7-E7o+;+~eWG<0SmH@a%;z){I2n9meGz@&vH_jpPUePz2V7Q3ninV9;RW
+1Trw6rXN2E_(w3pm)SIh0j~4TvHx^`IYoxW7XA*8TMtyW)6j&mw#A^B4GC?QFkhjsfuTLD4tFfBH<S9
+tuN`zxJO@ba{u_97;&!<4f~&nBGdr#S1DsZipTT=F)I}V!<oRQ#p6a7!BZ7o_!|QrTuy_UYprr@o;Sl
+PurK8{BfS$v4hE|6I+RX<lDYPQ?P*W59);HYboyeP}+>Sg$575k++#f$VYZs`5Zq`o!ikz}g?*ZXW7g
+{;lKUuZ{Cnd{BU5$&+vByO?&R}8OL>slS-jjf3o#nrtvUqrm{0TMR$AIBKP5+-U2R>%6^UxSJ@Gy1ge
+fL=`(2hKarx?fnOvDf!IY<Ae2B@{vY;$L>4HUB5w2foI;Tp$?96U&G^R@!RD&&CazbW2u;S>6a{eA2$
+F8dBF0-ry4lfEs=5~DP{rLEFwNQ$xMb*KyI;g(BS@gyHZl648&v6cP4ft9a(%Y~o}gHwwb&kWiaKPD_
+44XmS6xUnL4ui`@wTVa?`R;y$r{%cY|Yg8rC;c?zInP1!@I(jgw#@`-rNvGK`2r=M*%$%ObZvuzpaFf
+06${Y$zkkf1C%4{<e@pO&+jEoJ4jxcNcfxU^&YKU2H)R89}EbRPZG_tKHE=6RT(H3`%6LuYsI*9zLdk
+=1yAv(%z%yE_y;ecRa9RKy@5h$Hb+}1r<;vjle0XqV0g72klz-0oRV@zNj845?xb>0-#B+03CpV^|Um
+wD;zG&eviF=2N@b4EPaG-yt-Pa|h;PCsCP59;z&f!<cFQk*k|H&h&ndCxBuep=sYHX97Ui^{qhtv1+S
+3JQUk?r54PdX_n_DjWb&uiMHGg#xQQI^=A;of{CN?FZV>z@LKYg8ZNt;xmBJ^y9!yB{>e>H!D<!NX5J
+dZ=W-Sl^8mA_~^2f`*=*3`26R^%)CVEp`Sxdc0h7COhH&s?D&W7>pUvphhfG9pIM-(1_}jM=D$ux@&m
+5NVzgcwq{C!keM>1rXazKrxkA4#I*3b!>>Ms=mE41rsQfV*V)ehDA)!p$dBkRn8h*y+i<o;u`sb@v=1
+-JRK1L6F$R7i<=%45)I-K3tJo*BA$F&&Rwl3cGM*<1d6-JWEm>b1b&$pb;T;>(jslG%iaR9J|4H)_!P
+yhtOQK5T>5jPYu%AafXiXkvRTES@4&zW=Ph@d*z#X%IX9(D%Lp1nAZ2G4@<+?id1*w^|3_KGb?T;)5R
+95C1&62xK50g3yJLj!SUANIyb1hc;USuQ)24MY+Lc2u~FP^soH4Da0*N^0*#5!v-L=xfuo><eP727HA
+9S;%F?)OO%EZt@!pv<kUi!)n;^ZzUf?h&qI9>%w4LYDij#R52#jvAge&i`NvDG&9CW71#Ne2`&{G(`a
+DB*le$9V>$}xswRu$SHR1THNkubyr~wbT`Na?;Oc3#2n2TZ$URExr6agz$u{NS+o(xicAL7t+6d4^0O
+XPmy&xn64l{~2ROD*L6ag(x&9xvw5fhVP^yN_Nfl(Bv9mcKji3MOsA+#Xy>b5KGXL}J+!g>(S*yVSc#
+|8t&Zc`+dWvhm6mD9RW2RbZNel7){5lAR|Hp>_fir+uuxHFAopwSU^%;=jVId>-zGoz>uM}`pBhoOJ(
+ZDLo=;rVdM1K)p?3UZ4YW`Ss{9H)Qq@lrrnU@}%T$z0gY#oHNFYGT&-aQvMllcD0&8Aga(x$Jjl7aWX
+{9{&P>*IJ3Oo$3~jbA2u!f=|I7aYSrM5sbZT7f=f}dA$s-@y_Ff{`A=X+GCOcy>t{io?aL%IlhST==h
+*>g6>BU4D`DVeJ1npg0djfJx)X8GfvIkIk|_PFPWQs^#}s%wzvW-x#Zj(X!H68BoWWY#ZYI@)oIJ$Ie
+u{n_Hbj&DeXy#Bvm^{6(LgsPi}q=c>hc;p1dTt(Xpp#Ir}Vl6c}Jm;rCWABSI9-+arkWY<EKZzkoJyj
+-!q78G7WF5c8c~%pCC+voUwvL#^2{$4nQJBhKYK108J`szTC1{{kJD&25g7Q_na_ri(l-3%0Xam;tb9
+!EwgbYiYD?25m1fziL#km-Y-W)D1mceDIh`M&Rq?HKTo$jGzJb>5#X!Ax}7UPsg`Ku0(_`djecj@M71
+pqMdJa_ynJ8bw#f4adnfIMWB2a><WK+TYZ!%w2Sz_bU^!#gXIZy8}Oum0^`NVJ|h%I?Jz?ogZSMz9o3
+BOJ$!a0L5!~+Kf!Q^mrYFTY$|85u`F2A*5&WV$DaN0{P%rPqN=+!2PTmBWWL-m&jI<Dn7kMHa@m974-
+TXf9Q+DS(d~skEk4#%yTmCBfR5W>(K&b$$e8+c1tLS2W_;)}(%cITa~Q#o*bKwuK}SwQlfbrg1jxkAg
+L216f&3tB_=51XGJl^@t*+2=WP6Up(d9Ae3JIS`NW5VkoLT^hRJ#O^C1Nb2$$I*X!pgWG(Ht)J@X?#?
+({#ql+S}-fe?{h~p;b75X%;%Sxb$E($2<aMGnsf*jx#mW??7ObW${3$4Fi3T9Yx=G(T577*gQRL+6L2
+nb~hCmcqJF~HV3^8jrk4_4w&emKxK~@&-@(qoUlkyS{OWKexT5jb%gWwy=>VexZM;WGiW9(>$dG19cW
+>4TlbZiqkb=m706O!PMC`6Y+`uMWkej?aHsPHm(z(1EWtg2s}{Z(P*F+;T@+p*NT&NhanmWRfSQoGh&
+qlPN4qg$L&v{qyjhIZ)242chr#I<0Fq4=9AP$h@74)7-f4uhkIdzxS;R@@Js-9K$3hVglXoHbYuGT*O
+W0{})ZACGhI((zsU}ZdniFoLh+5Fo>ci+P2}XD~vTU?S9Fhy5<xEE!*7*_)m4XtV<A~JP@mP;#m|&2t
+OHR6B7n6{P_N24v<f&t=ByiQ-MpMz|GQZy%ZQ<_4sV!#D=t4?mu_lqeAYUM;Mn-SjywSr@01VgK0|d8
+~u$R!%aOZ0?9GEy^LAU5ac9@zQOH&8rPA%%}i9PY^_1V!vTyGlyr%*XxlK~zrt}1=kDi_zX+te%Ffgi
+dyv^Y4p0wL=!@qGC~L$|69aHxYqDcIc(9{=|7?>*ii+*k!n01*nd4d_M=%Z(LltGPLPcr82}xBEEXe?
+n(vj_PSk4(}tqbr+D(V!bKqULP+=^geZq`jf8@;blr3&zy^!r5u6AmDw<P{$3LGaYW7z+k|GTbbuffo
+3;QwyUjea%-{I&`U!6ybah1EA2@e<^4@l|AEE#hX#M#1Eo)A9<tx3$D_y+hkAfWcX=WI^z*}JoPX$<%
+(FT&2xA_)Bu6T0{@CG(l8?{pLupRvO_1Ne}SPWuDT}_Qq;$tTOAAOWAhJNpK=?*_F(hKyxR`+K9@tme
+6JQIM==bXZT!gp+5n#jA66K6N?E$9(LWs0Up!<=K)2yAQ2TE=)#;_YN7rM?jNUxahLptILMyk6)?Hkg
+VzSo!%H7!74U)hcE8IoJE@75Y3yeE2+Gt@OcRA+MWm>u0e{pD&VJ%`%?sss1vVPPx}?*v=zTaCBqL5W
+Dz`(es&;z4yh@8`+eE{<4hT5;X}jFg!0QlLlM$4d{iNA{Xy!g<cbMd#AHaXC{M0TNQ?{$h%>;E;_n*!
+84K$v(dhH!@H^PaPwmYCc0b9rQt2Q1ux@KN@RzEFuey${^}iSIXp@WK4r0jIbf+<k-%=&75H_gF>A7@
+k5h5P)95>|vRVRs%eDqn5pdTbh>9Q_E?haRz*gVXh0(Em!kjY1u>a(^w=a9nKj_Wr9dF&D>C4h01&@&
+Kee>^+ek=YE-Qk=3pedRI>~nz4zI&JH75qejkL4zB!IT200nr^?=rxycdGhcQE{#Al!h}tKsnQzM%~f
+0XO<K2C2S9KjAyynb`Q4KzPaZw_{gWpLFga)0T6C7Ki%uUqqa!HcO<{XcSi3~xUG^@#C;aQBQ*$252%
+g+&>3SnJcDIG;WD$@)wp-d0NQToBGsfru5GqD$K340<e?>J6Z2JnKWid>=rG{sF?p6k)cwpa_I`|mLm
+EGy({wO;&yb+NTJAaFj7@c{}T?mW5EySPSyugDDGz{?ymZUDBpWu<Oj_$mekR#MS)02RR_f>(1`%~@c
+s75YfC3|B3H~WHr`CtLs0$j8<XTMa7iqlEH%;^IOga`9H=O5#+SDb#uZ6?Em{2K~766=0c0r74(IT(Z
+v!6GD}TI@kNI>3oIJ2*fb0cu|0X}Ra8Pggm3?yY8bJOaeC0Jok`5vQ=H(5J#LIK<S8rh!6fT>28(l~-
+fy2fs9tV24qj77H<VG3Rfc{LmSAo`TzOE!lLWa~GE;FTo2A;!gY%51=O!8f@BLf+Y*cSclT#LfYQXSt
+NL0FkdD5l%5F+pSpn5hvm?b8vPhZ5RJlxjFWB)@exM)G!5bev|PQc$^QUQO9KQH0000802@m7Rx!*+x
+`!eF06c*J03ZMW0B~t=FJEbHbY*gGVQepQWpOWZWpQ6=ZgX^DY-}!YdDT5>liS9X-{)5#P`N~|NyKtu
+$2&2cwRLP%rPx}@O14&|f-pdng9ro|0Gts$HUE9z(RVjEBiE*OmsQe`=<e6o>vzA#gXHH+k!<?5?XR0
+|n^gU7C%P#aFZ)AVCl?|a#IC;*byC8^ekYQB-#~fOB@;G0Oou^aXAhFyaeq8d#%XA(Y2ELqrtiu&e^$
+1mI6G^0`+k_9c2`Y(-;U}*+i$nftNPjNg7NY&HLd=2)CGq_Q>*X4H2Y1{inGno?-J;8Uk;;4WZ_@S_8
+>+sn~r;&n=JXhJFb$)Fk?~SC|Ai781gE4K8c~cXvHdd(Two>Cpm{z@>=}kAi4@l-gNNjjDhZ(eO6qFu
+I`6yUsfMVoJqDThYw;HRbPLhpQjoO0K9=UhDFz{UYTd7nvQ!>HJirj?zMXITAXZ&i>n(|W!HC2RkqD9
+qUg$<IMwnBdV@94tIR(?p#^VJIr5j{Y8Jq8KlFcxEh;Yi{(~Ou4~M3$e*oZ6>(5Z|xP*Ni>@5N86a(y
+Ac7at3(Oo%hpLSQx(091DtK`T2r@j9)21<Oa1fhc-$MbHSpz9JJJ{^XBh&5~bs&ray#Z-*drEu0*SKo
+=LtjnoXwHIdze10fL@ub0nb#WkkrKbp~7Mt?WPB=w9B~u6p1cz-n!nauC>q{Y8uWWg0RM|yoPS-OycW
+^2vvHKgsiMH!&(T*99qc{w$YWswqyctflYMbtZs{aDM$Ex;wIIy(5yw$<_ZAFJQM4<{k2}&XAW<r7xf
+Kvs(5^gKDWp#8nIT$LQkl>+gI<rw$j}2pIrbim<Q&uwbgf9JOpWGv%mFh=9yPm@leaI8d5X!nRM}O*f
+K!11T2Vp(jm(yho7*JCDR~$OouLAl;J$MN%UCO8%6GhBwu?O6wDXGTlk*MdJU6$je(1-lb^lQHMt{E$
+LCm#3Rrr81`t>fg4Pi;AVpt%>~Bb?fiA6`J+!yZpN|Aqs-Z_6W9<R_O+E%5m9FX*F$H7pMR2S>;y(cR
+_IYC^7tJeC_c0w1R#iuT-SJY2wTRbteOG8{TU=Hj}6en;TO_+tm<<u*zR84QpYnwkRgGyHy{=-Mj5Vk
+j*>G+ljSy@5DRhqAR80S*Rc1ej98Fid$2##N=~0AJ6}P-GE9k}KII17iAuo-GREo<*@dJ3Fh|5+*OXg
+vHO#X&2HorN6Hbxkh6BC|gaJxX#lhh+4byh{BgdToAv2)j+o>u3*t+d4+|We%KMVGJ;(6hbe)>Hi%^E
+lZ}|FOOnzC(Tb}Qq&7>~NXiamx_0bA<m;vqI>H$>707~vO&)ke0=B)W?e>|T2;-gDBn7NmGZh6RHGW3
+XZdUpiv_98j)mv*(-kCZee~OVX)2d2h*IVFJt0WDVG<|2aSA^?4xd1^EwuvNAQ;v+qf{eW79n|`<@2p
+Bvh_mXk92eF+fC#e}`>!7T!K#cshgF-g$33j)M)oh}>$dGL%C=xBdUS?6PPh*5Lhwj~A}vt1<&`sS!^
+Ra6pkfr$1p6ItZ*77FDhdmV0HLP2nG*4UPK*prz@Xw{=`8I~jEDWcZRQsZ7|;$-PO~fGG-IsxGFg8|B
+R$uR;e?8T4h3uul_fpUnvpOc<oyMdtZZR?xx&g0b|c4uj)KPqkD=83@GGgMqDtzATS>F$TqCzzA-)Ds
+Jzj98TR#Aza~LYYBzB}@jv{NDXyH*&6D)zFA{-I`Z7f(M?23AYYk268ZHPJp3JCfI$c_Aj*vOc4LeyB
+Z8bpZ*hqTCowD0$amJ8eg*0@C%M;eZ`EiVTF%7hp)*ux12>x>Kg>nG?F*-<$(Ew}flsO5_cg$|qqoQA
+_5M3m?>lQq+691--;UmyvE$5&0MXJ44nb61(Wai-WhaPlM|HX72gaZ$mbu!Y9BKhAS#h0n4EP_OYDMF
+s)A_Q>z2%d7*wf?pQuL3uIKZvu$WNWfSwZDi_)1{fmHEf(HKYnhWbuU_zaU8CkV^j9F1)M_j7q$AtG9
+~L|d(^iQ9!2xP9IM_m{jZ0lx$7W1$VA+{Be|@%*;o)hOe>0GL+%<WSynOmH`Ra>rXt-AQPA!6&lUA~j
+V3zK_${O_DU6h=6$(kgnPaR=wL{`9&mkCSM8o}700jpM(phzbDhL3D}w1A?*F>%9j#n9z;@NV-Qs(t|
+BW8Zf*@%Y|?3Z0{Xb$!`Xmlj;yJlL!nE7$#XhtfJNCuumQea(G)=*~q_@swzHf*sqd^xQ}~Qp!=ZiXO
+ot;O}ynnhi*|2Gi6aVMJN-vr88M3xPmRc)XMCp&URy5<E4KyWs4ji3`@JZ?6FF;0tKlqc<Z3zCcOLVV
+Y9Ijm-s>5bUMwj`sKfq01KNVSQYae2;s=vbXShrTs4SA-pH;pe@I}(!b(_A=ZULX7}`;*?mZ!9)jWmW
+M1^e2mvj$LW%H1lN+OJEa?9wkqP?B+w%`u`PPCv#%82p!p<(1_Q<ux&LtBr3{{CZy)^Q<yJBj{Z}y%e
+>Lr(bTk|Qj%{g$gSpnYgK^?sF&p2Te0iTD!2^cpZAr%)#3ln^!QGgaid5EOqfEvr1l_<?knt*{4Ai5f
+@y6h5#p%ysXk_0CR_DQ%ZggZBX8q`-Y2-S&{-Rw0KsD+g<8m2bt^t*rx(iz$G=Q37Dd5o;bYdG>S&!2
+|_;J^lzt?^LdLTnDLvp{Z#%Em#JQLLF!1ni!qP@70`-390h|Ipfd0Epr}L6lG4zH`CY`TziNegX*RHv
+zc0^~klW6R?D8Ke_MP?MXbdD7A|To-oU@TpdAxHzUE7Yv-u4fNSC-Jg*v*4X{XzD5N2^h;H2jNA^HT;
+_-{;0B3t(LwrBj9k65ptQ06nzu))F0#_C^k!>?H6^X7EUDaS+NpS#@C8Bs}@8~!%W#{*qhiFoNglg)m
+TS42q&jU+0;b3U$UO4jGGZ-ofK#%^gii*hBLM<&7E7P5}f*Md;fffyDiYmb01PT1S@qi_Jw2UB|rSXz
+DumZt^U|z84%K}v)x#`9OX(1)|%pwuU0~MOx@QF5?E=IxX3eH5CG9-n9I!!w+y*<#zRXyDqj_S~J5D_
+LosY((f2U!+uMsgGiPee4<Oxg0JmT!0cL)agSJFqMb5KdT<>I0pK@(QLKs*85hV(JTOaBg&Z=o4s(H(
+7}nYJadd$sPb@^=8^=;p?bqBPnEan^8p#p0SC4&lq?Zk)5dVu-4!blt0;xh!}ag9ne1DP#|}+=*7t1c
+R)F=%C@QTe?W3tL!@XHIFt>DEM>_L%;FFP3~0r&0}O;gEOw$q6JwIn`ru(=XH9CMAJI*z|7!Zhy(<nX
+!TU3SevnG^11j8(;6F+Fs~XbcY}#^bd2}aKyV0YI%LWoWPCX<{(yql+N&X0A8k-8^As>?+4%;UAN){k
+TBX&>PiQ64DEwE`}H&r~qvM>UM7R3S^kwFK38bM8ox}j8wa^Ey8RO!+wwI$?;lAL^=Cn>94H@9iVipU
+~nM_(8r8I?lQ3(2}OeXvY<C$LlUEkH=W4b{i*(qLt5X;B$QT$|WjZSBjPZ-yUTD|b8*i+OnNUWBvrpr
++sM1mMZhnw;LHO^QmvjjDYc&fl^w`!lx8eqPlT;?6Q0Rn$~1DX0hH9&>aIhF<fGkb)L6K;5}1*{i|~>
+BdyOU7EES#B><CWVBBioWc2HCL5&R-rP#%<s43iHcsX@zZq`7(+4F~#fpNQBSn!ZhsjEx&gIIrbm`Vh
+Gdu=d)Z*f>of%@9rr&p<vaBbT1209pmo}!YB)Q1G#flygB=Y4bzYKoLiS-$Q=j*B*M(#_O<Ist)5EWj
+S>XuMNouFMiy}6}z(aVC>S5_Zy@#{O*Z}BT)vV=?>S=7X=KbBZ~aC1Zb-QLbEKi1FZ_Q2gJ1eB+%B+d
+TbH{F7MTgG`gN8$pg9FPct43pU(%>slG^30*oZwnpFpZ`tSU-Z7>ILv-JCn`$gmB#Mky<8nf<x(gv8)
+g*b!lTe3Nm)A_3NleGmN+rw+tOlXEJdIkAE!$oM8C_v`CJcNvf|P5Q7im4^FdwEnFbP3kJm<L;;KQ?*
+c%b5bQScm`Wk@?n0&Fwcjle4i-4G<k5N!03;srmdrBHq3m`>$HF=jryOhfe(w&9nIxcv43;q)!!0I4)
+z0%Q%KrXb%RBS*10*zu+3Q&lQI=0H}pdDNlP(zJdy5St;W|W%79Bu#+GPW5{#zLc}>VX8f(z38S<jWp
+cV3}78{KOau9qJQfe8nAH%b|kyjIMKR#MVuaXweoc1H3Xr6rYg^uiWi1)(+j?YiZ}q^GDg2I6MaPN2l
+;RSq4MT>|q#MYog&K12tRWElMkZqUq|(B+rvaB-?kOv@e<ocij{(Wt<Dy5|W!VC%Tx!pIgI}NEt1p>5
+o=TSpW)cj<Cc86>R9JdGmB4faIKo2gytJsPL+zaTIm{ZKt5p2-GLaiIos#nsi&^Swx#U&4JaCBg1j!7
+H<&5*V2_^Om$45vy!6R2IwXvGd6@w4SsQxQt#<GkK)!d1p7mqAv~evB}YPP-ppA5ZLzSeW%oZ4xQrjV
+{<>Rl`@T+Oln`=B=Lk!<)(HWP8)GD^sky?PTdySvSW6HXB=<)J&w&N1(}eui>>RqX>Yk5H^xViLz{xB
+E%b_K9ad#56r{OS8GDt=kM?bD3Ee*#&#TKU|Kx>di$!E)w16s%ce*tH9N4XwrI*>5>HO3v99hI|YH;q
+|cYjS^<(O4a}9@lF?zcCTJ3sIw=MFuVh*1Z+sD%RD2Ebj~n&~Umyo)I4bM+YEl>or+f+Fd_R$zI^-iK
+|h6j?|C(_lOQCaZFeVI)<CNP-xRInQwO5plO-0EHkIVk9tXZKX0<Znr6z9UHujNd@jo`zx+L+9@H_y1
+V(-Hn$QrX$4{9Gx<kDMU0(D+sbRsd%b`vPlgoD7k7(GlAYGToG5P5giG6yHwlpK4gjb?7>q7ftZP+;~
+{JQ|BG!yK($RI<qcmOlYvn*T6zMMnt?;CqK7%bUvLHU(22JC^f?V$G2z{wVJGI?lL2Muk1be&1w9Gqd
+<Zehn+Z_EQ)HZYz#Hw<PLpu^%%5Iot&cM)puAQ>ERl5R6=C9+XW(wMc-wMmIsC2!v?vvQACa8nd0E_^
+;07D!vU)0*yGngDFnGtzN@q;yS%TU<94v1#Ofm;JR4UI9jwlJZO7Q)iEVl|nIZQ2HlZ8vbvY7Si>1Y4
+Uk2yeTv)unk{&=9G!Xixf;Oza0gdm4^xA!Nnxw`Buo_&_diYAQ|aJP(mw!)Ri<)NAmSI%yS&h3oo_?<
+~5>NnHciiUHMKle2~1x>>CccA2|T@x6^LVO2ByB(Gh0)jgC5?8)H%dHS$n|qeDO|UyKK+3az`tZhu@N
+dpaNo5P`d85M`SLQ=`Z#o}cZNR+||tXzqsZhLRr|3vwr>H+%K;KZ+mTJb&?IC4HXl5oGKR)PXv8O!I^
+QXP>t8y0)}s%MclI1b}2vHe|rxw`C=a0}OgU;4sjegyD4^3)ar+JW#<*6rs#MYZC*OJSWFKb;E&hEXz
+vub>zM*V9lh4#;ySw?Xq5vLnVc!%$^K|6sdEfcAH$J9d=N|v8sWGCvV<7f1<*ESfAH}w4fnjNAKJY=z
+W8NfCMPT4Ptd0S{#&pL<u<6Bil9@f!m2t=uD#<+0Qp(GKk+CI_e*Fm&Z$>2^u(W)UVs(1{1_G{O|XRW
+p*h(-lmR^^Z9@N<>`6yoYoViH;^JHauLxs!)j1WqA-hs`0}S@ak=F{r(bN3qIPRK<0d&$#?5i4{z60Y
+h&u<9XKcz$AFFUk<9PjSOf9PDQfTM{Gb7-+-GQNg6-Ko?2T+ZQOnSOtr5AH)&Fwvsp!bTY3gczOm@!c
+?Wl)E5UFi&lgy^;FYgZ8iO1^9m$r&1t5{|+(#;0E+>LSr!Gn8&?p%L+cq8zqTe!;ai41$9gTw|Hi?&j
+$ZE=TUKlxqrQ@VV*UEj~%LTp21x!7P)iMU}`3535#KYKjqvT;>4642EAg@et$!l<7l=P&$XpF>qUq%w
+jvya+6vWVWD<KH(=MbGchterf7%*%D8qAuZn}x61&QNs>1*SSBP>F2^Y?A-=;D_F@3jOsbod(4EB3;E
+9JRam{5vRb#jZCSkd3sG+gvbrTIMIb#H?w8l)Nfk8mW@cdKaCejk56H~p~oJLicx`j#*b8edoRU9oFM
+Wg9A7E4_<~I+Q|E<{3)w&(NWsGi{XFo{V))Kfajs6foh)nKbD71`h2CCrlKa=u()ecnI78S;C4r!$Xv
++)V#CgMZd*RTv!jXk5LF}V;LePA(s_AB>4C6AQH=$mQ5h?iEAoP_d{PFDhu_wz6`jb)%^?<@Mq1(<Om
+1OZ~j1RxA|wN?UY-xaAc|H-cbzKeeA63oh_Dk9R&xRg;o@CQZyTx$R<rn=mueBw^8DLoZ3BWFmtK1a-
+*EsL*i4))vV&LHf>W)#!5i4if>$BNu^s+GTT?)d(oajydr45L%$yyAXs)V#jnsbEmIE%SyGZN#sS7te
+nHIPd|$H$-jVTz69;f~2>O|%ss)+rriRl{LSILwa>!iFcREsu;4WV62Z7mXC1@)?KlFzkjwKT3>+G6m
+=a8^mL<{I51vA^@ZaS(SuWdRGBUl3sh1P`Po@Wve7fZsypnvSUkmO>F4`L`Akbi=-^pN$a&nEpF#*48
+K&qJ2V0L4UNmmnNhB|1XUB#D*N6VO0_{($N!i7~jZK)>+T1cZ9y&S)sFSzJE}5S=Y<yGUe*{kcyl$-V
+X}Y<fBa=iY$T=K)K)R(!Np|Huwa+zXb_qyk8jthlngSq7RkD$fk+jw5kuq1>j<Zg>#@#_=!H%&;`-S)
+}s&IL5<Zsi;fbR`gX~181DyF$RvcVxRxaaHKX(lnGA(hV_lgGIAnmhtuddP8Gci((Pcu_0xBpq@64}x
+w!<IP|}X<%7}Y5w=1(5Yo|ki9DOoEi#4#-Y!1qJxG*<WD0u~$w#7K-o%EQYSL~0T!8m3F3<k7Gf9zE{
+6lyEDMmJc?A}$KPuR60~es0ZHNvcu@Q_Ci$camYAo>R5i{&Ob<9sJ5!LCe``LD}5A+)Ew)S(B5aiQE`
+*$Mh`mG;#;U3Elez=D?8&&<)Y$Ttr=y1Cc8y8wQjJ&`wt5GE*sRCg=>rBGP_=eadKO4NL~eAf#9TG#i
+I0!Wp)Oa&XZv+*F6Q999k;vf_Mo*D6j|XZmSNr}9wh=x+^&FObrK_XrOLCT|^CsN=8%QM_hjX<S71kc
+2d!Jh~wvwJ}p!`7!ny<7A0LH>}`8pW@)B2~bzrLFNNz{dD?(xtdEw;_}%50&(Bvo0M+`(FQa!<2Kt46
+Du5*kk5gy<{5Bg-bCEU=LNzPv%E$$EW`h6i4_>gN7mwbNiB_Fz7i#6!Hm2XAMF;_wP?CL{qlF&?;<l=
+p4$5$Z;0pbYBgaSM@myE87mdwwqli4|5izn5yS{|;xN|&4I}v1tr}*8aIztN^{P5?ZBXs5`(wh>5>f8
+wDZf)!ElKPltxInI2qH#V{^Il{b2GtMcFlC;<vBrXDFRW(ns!=bc2g!dmdu0LOsc-5Nx%K-(Kk+*4d!
+czp&>&-0G1wHl6%d=aG8v*!yXa**I$330pp<|ubjF;03Rfpea=}2B1A2SgT{{?8=w+1{BkWsp9)T0Mw
+=<2040AJ!Rk`XPi>}z8H>JpV*Pz}*G>A;A$W3o9=iMUkjB)gc+?2#+NA3600!(DW~E549=frl4->q6E
+=yiFsK_=LWFuJCj=?0h3!_on{t#*o<^e3j!&S5)=f)sd=gObPLPiYv%A$=Q%h)NI8C80*xoi&eFg5c-
+bB&nB`Iq|2u@k59spTg2a{);UQu$}rk$Zy%4=p0#HpvmKNH(%_0BPwdUyz67<oRVDL@8+)!AQc>Cs1s
++Ys}J*%N=o%Qy0t3L1p?P`z!41Cgr>et<BiJMkNc(MR(5!az}kE668$0WRy%$FN##m+yygR|Ndkn60h
+P|`3)l>8|K^{dU3f#N3iE^Kzm$rkPDbc7B${LZfq|9-X&|Cu#}vh?f;ia&Rm{wzsbqF0>e4pe|`>|$s
+@9Q*g~Jy{8OYD{3tObm!Wt3E39{N{hSQy?<<TTB|_DS>-HG&VWJF)dX=h%qy!J04wKiTvkYOOn~S4bd
+=K%R8#(LHTYADVQzx~EGSgc7SZ56~A=mi6I|jx*VA`l`O21F45hz{8CaGD9q`u18u~=%nj94S=mWI3O
+wt9U2MHykHQ6xV+W|N%1b9FHTCYm4WUA&^{v9ejt_8s2m8XiRN*49O=%jN2R0XmHQdLSgheNR{u7vDC
+KoBM1juIr8PV8{#$muwY1_r#w~3IlyOk+FyJV9eCBz<7wee;TQ01f4rX19iJ`?t9*^l;=G_D93YVAAa
+eJiPVZl4Mm;J_(@;s6phbNi9JlVr$Kdwp+!+%7Cw!7?oJUKC$1?R-)lDFH8=>`d^08;g03C7wssdCb0
+pDN?^DFY5S>hX?mEj6Q<g4z%ve+AM}uo4yX=(zMq`@{c*XP)GoHDtF;T$nCKLH;(9es2ja-2ki-^7R?
+n6(0FTI=g&~E4{%6z*7N5_>`WTOrp<SUFMPm}h{*gY@Jh^LlPH<F{%k4yxx7XvS!0PO|?P@BC~qC+gr
+xZN-h4!S_c$~aWIg^9A%*Ouur_K+AT=S*GCXU~4jx$iDxXd?70NxE@IbaaR&A^I9j$<5cWnujjA_xr>
+FF!y0win_t~!@jl!`#E}g+QD}R;dsniGIxb$&3<f{Patjhqy5Cbui(%Tw$0Ex+sQCP;qc={XV`opP`~
+bA8uo1v8Q%wwVNEGA;WP;Q=6hz4y3q}o59u0txd!#AAzoFZWh8`OBs(ed9H6|si+<q`#*PDh8nLpCCe
+@pSTOi~%SFcorUq6h_Z702qu)_Gg=^@?&%7(O(W+$yBY`**J<JXw)v*L<q)UZN9<?>qdL+{X=PAB-P=
+9X@bw`f?7qRXbPMMu}t=lY85xjQ$kjxxT8(dRR(1RCT9=nC1)1>)i{|H358_xp7#u0)HPf_r$>?P`8T
+1Rmvr{0YO(Bki&ak1-g6Z(pD6+<)#S(O8xg9S3shvbdx=3`lrdoxT>o(oKVUIrO_d+TZx@7kY&VHh~S
+^^>xGT=}s+}Is9)75%1sIGk*Ubk1rbME#R*NCpVC5ib8)iSP8Q~OlT5ACiMP2g`^B((|iPIYYk<(Jd9
+@9nN*;yxWN=f8IhA%VOHc7!=QZ)L3T;}Gtxk2y-B8MUqWtXEAP~WnQ(A0Mct^3=W!-s(~H|RR;vHuFt
+IQ?%o9A**B_cay;%jsILug_l<CUcR+z4m8Ra3CS0y_@L){{M)*q}`D2MBub6`A<(9&G>ZVGljU?^W6-
+2TrQPoxEM`xDJGe)-M9#z}qdg2c8604tmuSHB!U=f1L(s#U^Qcv7|#b9a;dH1xgx6}rg@Xw{0cD}HJA
+3{t0AtP)1~nYI=hVUr9-Jxn8_e?;aWK*{IYz(0z;%O;WdlF&yNlKf`4B{MlPDuT-{7zyTv|Ke3B4iFh
+JjDOx@dOlZMLbs2S^LKMqGwIn}SYuly>2K30s+ns)XkP5Yb3!2W4)DIXm%Tt`f4$j%EcYqE2V*S$9LE
+Izn-P#c%Ge+gA$DiwNO!_SL;lMv$|WZVY$aEhD(fsK%j`Z%fALrn9kw!LkyE;?-DHu!N10pIegCUW=j
+yJId5PF}&a#T3j*9P_wNDVn<lo$`Z*DW#5Pjo~iBz6d$(I4R7&2H1GIp<SY=D>OW5e^ETy)p+h@<x2<
+Pi~c>7`ugN5_kms8W_Jnk9MuSIOdf+3ZEkmy|9pmh?sts8lX5@U0bkVH`c#8E8aHUZf4)a&e9SUEqIZ
+x;!Nv(`CMDg0L@58XC%joee$p@>XCA&~*fm&xfAKWFgHJ=H?kdg6&fz-mZAZm@Xn?s>L{w6%FQPUdnO
+;Y-A!qIeyX~<i+`iJ@Q#N>QO5QjbV1?_o%NY5UCuFoL|tE1xvRw3vt&fmXTFNVGZzoTC5+r=M1F^7k^
+Gu5hT$d2JR0i0>~G|W&hRe(FE$Qvom_91hL<Fpy51!Sv-0A?8Wy#KlO6F=tc$T=Ih_jMza$)G{Xzh8o
+g`y@$Cu0HT-wPvbifySDZD2+?{5i`@~j6Uic2Ph9Wty%l5+}Oi{ET5Y2_k3PwB-9rNH|O(lV5OMD>vL
+|e+%Ve*On(JVSwbDFIx`EnjLm*6KvYy808@HSXzgBQ>*?3sNYN*Qi@ym6e~AXLzGZh7*>$45_}B;S6U
+Jo*}S!7utheD&2_dx;y__0ZrAcEf^U0vV3<iMyjVldkem8ynvrvh@G@4N}nmH+M+S*5lY3%T<Nh4RRK
+Eq37f*jzxeRy#z(C`fgUE#k{y?uYb+H>_@$Ja^{6UxOVZIimjId^{5Y=uA>x%)3wNRI95ZmpR|3_x%S
+6>Cz6-Q6|q_$F^#9OUesiOL?m8iB(vV27>Sk&@e;?8I|Fjdae;FD&wY$*o8y1(<NJ7wc{y|b6NJAJ6f
+c*=jn|4h`exqC7amg=oANvFj<;e>)IIVMn{j+jcPye@f3x(bHUdB9ddfI~`Sj?3`?~n=AE7YIbU!KlA
+QHkFyhk9GJLF3_w(_O3USfrwlh;B<`xTA%I#MxsUJW{*IsfqvmiR{j0wU27z`xwNM8`WwibCZ2n_D49
+lJeL?FP~q(kd(K~d5McYoaQDbIu$N4lrv!;Yp%k)%r#B3IkK~xe0F9f#&%=^FU)HLis`tgw~?Jk5{_K
+!&Vz)5WGVdBGKixN$acs5&;tR%tAL~yFQsc`2Q-Aos`;kFqB?W}(3NBI8nJS;Uv<F1)oWfNnR6ESc_+
+jD;d?Kjv7kS;UJ)hZEGblzo5+|wjPvIvwuvnsrZ2<uV-6~-D;z%E@}kC%G4U9yKrhaQ{h*8bbQX9-nb
+*-lrS_1Ul-uMd@}1DeCf9hGiMj&}x{Lth2tax7d)XyrRW&swTd{>2@0+8A=QBfL0|Yh#>(JGGMX$=h7
+d-sT@lGBD;{ulNQ0n>^sJ8F6b}aQocOTNM{3uob0GgzRlz*rwUhBPjq-~WpUU@p*1324w`wRJ^RsN!m
+;WDGY5PXA}G_5-@RK`L`C7N+Oi2R!`AAJ#s0@6q*kxo(o3KwABywDOMzsj86Jvho2HH2i~-AdjCWK6y
+$m9e4FCkncfP*rVyae<}t**9Y1?+w2SMZRunbR4+~CcP(d23`!Nlg4S2K9*_<&DGVFo7Bo*4+-kznw)
+vEBrY#=ck^nT$eQz7uhiAT@~PCluzK*4o>M^F$`T5{gU1^TtaS+e-t;J4uL<0m8xrMMuNjzrHV6xhpD
+@Je`smR&U;XQe!>03uIL~RVvXeYub9p?5C!V}D<2g_h@)NGtUBA8n!UjUtIc)HGQXi}YBYb~uMZP}o7
+7TASe(SG=9Zqk?r0#Z<x6I?k21DOwpy?4AFK8eQT^;@3P)h>@6aWAK2ml*O_EsmISv2_s003YT000~S
+003}la4%nJZggdGZeeUMa%FKZa%FK}b7gccaCxm)OOM+&5Wf3Yu)0)2U7<~Y9^5)8(DYDrkp+^VmqkF
+((%5EJCKZy}t!wzdXNIyQ>S24gSpmDS$(e6n-;76cS8C%}p*I_;HnX+SJC^C9fXqp)ER*&9t;xYa{#I
+tLmT~(M<(q3dpR*fj-K@SYWts8^P`Nf~DYAP(=&3CslWPg4#l3-z$o3za^GnK=lSQkS38j_HL?QnJuE
+Y*5X+EGq45n}MpZYNLS1Jcai6S-dh5qosI#Cpj;$QXG_wc2X26mv_l(P3T&7m}q2^ZLHjv$}SDBob%v
+Ppcp0e9oiV(#PNJekdASs|=tfx!>p7BhxV4r|8IsC1mi7K-(pWn0MZxvfgF204G+0u*+^R$3Qm>7%J2
+VL!fM@3ev%gq|ph{xE=EF)=Wd;?=B`BO8>IMgW1S>UY+e`9x+up~ZkSanc8x_7!!eF9vQ@ic*yGzB@#
+}yJ=7EKFxxxq06VF`F!BlE*&8xDq8PF++NcYqYPVXL$XY&ac0s7QB+{#gvm8i+L2(I=^a>3d`ad#xO>
+<y3$a_}g5(xsYLmT`J}|TyMS*$}xa}&VSj3|Avz98xnBo(QlhD`D%_Pi;L2`aeQqCvg1*2_0VnjRPsE
+{;-mMr@1;9G_Cj!dsU<M{fO9Wq@hcMRQ+ZL(koJg~<%(J*^G)U^KAkFqtg^zm};4>(VortJso?Jo;Za
+WC(EA#!FJ&7W1dQBtUgBG36mXPl<PX_j%H^>LR>Oa_b$aBLBQ17%;E>+P6|vcx$Y2bu#{U)<4=ldV8$
+G%>=Pq!}~f+)y<+KlbiIFq$oaZWrKI*on|cWkIdwgP^&*c)E|ZUqjCJ`Pl=R8cjWEp>ki{D>35e!Vrz
+XU$`mS;V;+KP{(Eb|AFI7y&C3X&|yARSHcWZE2IVXH|+m3Mw@sYz0-|J_9)$!xh?nr*@6ClXO7Xyzu!
+@;L@w?-rq|49ZFUp(+|SiwSmLui#(rQ0g2d-%?^(A(Y3_8h={(0f+z#H?4pKVE5vKdVcp-3p0OZVRwt
+}WrAWyqwf4qHri&{JV04OglYkWl=q}CR<q&DY;-`r5z>H?R#IkQq_P?rN9do^!`m{!I9luG+#_ktjY<
++$tF3A;Z$r^y}MwJaU-p%1nmP1~;b+I9`EEpC_=H|LzM_AOMf>^usic%3$WT7xY|Al|LwUCsMb_0onD
+P^RB%&8ofhI}eS9oEVxkJNPhMX*~>9F+NGm`}=v)$FJjR_UL$YSJz2ct(Mc5KC%cmb{f$X7&bK#fGC8
+1lP|e2c^k;#^x?>&3wTI;S}KkyPCAdZu8=DyLN`#45?>{dW|x5EMrmA`@h6Q*th80%yUr(EA<IGvg`4
+>##9*=L@=+Ed^M$*Rl*odkm8&XqdKu_=XQ?~tL?H#W@5m;k^Pxltg&0nt7A2&98^f23%5CuqA=mO>f7
+4*8YPSOOtjMIb6)b;#_0un}rv*01Xe8<~di6Se9gSs@QO_c|PTN+<UWxB^9ItSr0hLJ_tz%vyorT)R0
+i~(Q=EHZ~daI)=GK8SrYw-jqJ=X|N&sEa<0LR4lv<+DPxRu$~i>QnBt>Ic~wz=7}HX3%oQ*4QAAQxJu
+>8mI7PL1_V{X@?grqT1XKBDJ^d&xt-Xg^(v^lD$xbFH_$joDXFO9KQH0000802@m7Rv1kPWzrh}0A^q
+S03rYY0B~t=FJEbHbY*gGVQepQWpOWZWpQ71ZfS0FbYX04E^v9RJZp2~Hj>}{E3lkOnVLv+vRjq9^VQ
+sKE;G5Ex@?k~B$wOrxM)g*WX2T9B`IrkUjO&&2i^odPB!{rOC-=}H2RGOs(sh?qu3sr&Dgf}a8~hy)_
+faI?$=G*Y^&Ybwr}@>pVrknJB(GWeu_=8xs^FK$cOgOZzMM!PhHjQbfYhu(^7m@)OE40<x;$^HsezKm
+uzHTjBURZZ%6n>ufC}Uc=cU3R&7(%OYwt*pFbYDTAnfBuIjS9YM=wW&*X=Vq_%?|>Zhh^h7pIt$8Y++
+?PDG5c2ju$c5=+uRg-tU+*Ti!=J#QcQ2={67G*IOy8nL`gM1Ch_tpA<fMb1-ZbP<d_gyjSem}qc_Vsr
+^|1jTN?sj=yHFvs${+$DmTPD1o%sh~~-R+$9fXRIWPb84OYD(FR0Ae@adtVJ3-L)9*mZE9<eNk8cCkc
+tA=w(yv<p5vyV=v`Aq*3m>ysUb|809a;2FCvpp1-bo30&C&t9U=>q1{*gcqnSw+-rFKp@H?^<p-EmpW
+F9mXEn`Nys~po^Bl3x^TpZOSt++7A2xl}jr4R#&jfss0|4Di0Smhn&U^Kw8uHztx)f^=rn7}u{k!GrD
+{Am<+erR<eMu0LB>AeB#VEyiD?t$J`Xv4iNLJfQmI6VGcFXUoS`K1EjZ3jUQTGRs$e{&EfngsN!h_hh
+J$2bt_p%W;HzhFQ%}qu<-pTRM1E1sj8lEF~1WjWN8YlWMKS-J!P^ld<T-xlHwrWyE1&;s=>T#-MU7CL
+MsM-R17{2C7<EJM)oL<}HL3exvL6*rA@3MW-R9iWWi5^2y-hiL>TQRm-cRH%+)q{LqheUJ4p{f3Ukjx
+9)=F;e}t1QbL4R%Ee&ROegW`<`sXSDuo^m2CWi*87_4U-vhQK-Bu`rUBJ8ujJNyCZ!KI4=ZmCp}0Bvj
+C-vZLVRR2RWt-^BVc60vQFZ0Mq5Mc$kHSp%(z#;YveW0_!!<gJnforr2~bdCd!e@6OIFgQ$7J0{mG~|
+4hx^QR}33h7{TSa-w;kD~9y{Z-fNECHe425i|-B1xFHV7^oER{N0<czI*q2b*#qQ_Asu1VXijq^_c^Z
+dycJv%)(shzM1$Mph~cv0(!GNnwLufL?d9>6W(t`(Ukb5#YXsWKq)P?hRk?qWBR^_(P52=_6so<cc@2
+--e{IQ2bg5HbD@w|Al_~j4j^B&xZ4&~Dd_d08URSdxGt$5l0tOtFjQ-r$rcR+(U83X81(J8Km7RRH{Z
+N@N3&Jq-Hu~7TwYvs#pbR+3kB!^QJbvocNaq^H=q`kp}v60wtWe0RtgDOuDG8ZF1$t6_7M0R7tR=adR
+Yu$(MQ`xO_Vt#VTM-V6Gjs3Q(wXC6*S=3J}>2_28x!sdZ~m6<U+RwxCqmV#eUcUh~%rH!9fhGi3f!Gx
+YUGa-K<HUB^lF_nEe(0v67?_?G0-Bfo-xC?v#3g5^lQzK44fAUv^8`A)*hDuU<VodgEt(aU@;2<niuh
+KcK{U-Ep3uz7pv~;1lt;_8|7v?iOT83RH|JBDk&qNOKC%?Y=55MKbMw4!COU#cBnJZRDz#_DR#O0Qo^
+YJf1s*lbw&C{pDK(2l+(&1$>Q5@gp#<;xTb72Fn^?k6{!$h@q(kPBIe{nG^<DFl(W1L54Y@U@OkC2%#
+1UZL#LtCHJ$#os8mf7oR%HrW{a0(*$i>pvp@CwQZbXhOVy06u<gpL-hyEw$0V$>QC3+s~DmPm%4l^aM
+(@aLyMsMOi1lKB(~b*U~hN|U@CQRftKK!j04&~{9!#Z?jZ^uAB-Y0Cb(K-p%m`EYASGfMRVA%QHq$d>
+^?PeBZr}YMRYnLL$VdnDjO6s>eq|n0-s-?PN(kr!Pvq#(v9N>Kn2wGx&>rx_ob+1aSvL&0iO|`QSadv
+{9eF_$b|}!pOOfh6_uTBn=7(tB6v;!@*|M|jXDA@nTktsCr_`ylXjQ~pdIQmAMPp~t7uN?WF<4;{C;H
+KqrvH6kG8r?lb6ZDUrDrb*y0KXinrI_VMdF^HR>-tH~qmGn65MpJ89E!5$Z>0F1~a)y~&(fu~6=c3*N
+F{4-An5Dmh0+zk(IDyIv3%DsIBiZ6sAhZpAHxkBtN+1pEeyl*cHQN&OKuDE8eKs8u%gp|q|78m8l|WR
+`-TU~++}2MKOgvynbqtG?jggLYOv3fN0f{CAmWZZ{yC`My9dc+f0|5h6ZMyTzsGn6Gd(2>hcW;9gCQI
+Z%UP@`5LPD>rvA{433g4}peSTzz(JA?xnheNi9KAU|5BRX$2xf)`ZAc;9&0h<8p}=Vd`L9<37m4+9x7
+nW?9<UKR^S#rG}y$!1cQE(4<IOrT+xg)2YD1%Wyu95a<bm%rfEH;$pW1)EjW5JHwG;1pQ*Tad9DdByF
+9Tvj#cbQ?*m>zrKH89kxf42Lxg_EanOo_ls0RP&{Ehhg5wqQ2wl`jc_sXNRtYC^)sNgYB0VaLL3eN#M
+E9Vgif?{V1p{gW6IIggq>v7pT8|kNzmxPa}Pe^EvbmW1|?Va2ulm2N1LYr)P<f8ubIe@2$TK4g>0S1c
+7=Hln>|xz3>hs9s4`cK%m@GGkLMH$OY6k&$F`HZe@@9AXl_9{e7AmE+oxJJpL&zC@N<!q(hDX$utt4<
+@rvI82RP-(!ppU{$YW}v?)Ye-C@izjREcFwJIeHuQX3C4R^-W?1*h~mHvo$4*2bOTR~uEVmQ!vU0slM
+r);27v&aHqj$A!GxElJ1CI$6#DQgM(3t~Q60~nytP9;YqJv;nBMNoIR*tni!+pTI)y|p9GDt^-*DM`0
+De|gSb8Q4foz~zI*28@Sl*HqgRqlCO$jpqa53;yFkV>A0%`+?2|G${R<DJHfvyG37wlnR>7PL|qLDb@
+f^>At#z5W$)Yt%&Pf@jR;wqT0f~R6d2Hn_r06K*Ju~FsY#ur3fo`EZ?0WoaY=I2M<plPkrW1=rkLRIo
+~bMfvLwlCzl(;t|Y^lX@$XYqD`R>Rg(+FNgD*Em)P-e)GFyR>yaoTb$z=AQ8;lN1>vWOuy=seVU5Y>3
+l6a__NVT2Q4Iqa%Zoq#>t_TZ*Y>B(UD~1Wh89XGaS&P<cRY3SQUI&9y*vw+L%ZYZiNTdj6)JzuO=990
+<O|iNG78APC>MJ`QpgWuUudWb0x=`UlRK&8Co{{;ZAp!DFH3A?lsI{vlk%TfB<{2bR|w!zinMA>uW9B
+BxPe-Igo`HJG<l2g^GQ6UG2hxmY%uyX_{NWhQVj?<CE(NU_(9Q{xFp<O=lnuenZTKu><jU;B(+0YgFV
+}d)k`M6EHNX93$H__C=8<{NCMP6BD#ea^&i$PCHnEoE(Hb@aZY*k%$EamX@>^;w5bc=%pb;LxRqs?eK
+V%!OV<rh&bnwjOi$7V6e?*1p*@OQ_{Z5l(9qBZOu)&ei&QAEx3L~2s+F>Vz^LAm3G{PMFT`I9CN}vOy
+i=zTLc0w(T<N`-Yk&8}f*?{6j<mhP;umo{5Qi)uz&zya9O8Z-=V3k2=qx@wIs>Gw3gnj%-W=)Mg6%VB
+VJTm#T&02o91MdT2pkXrdNBJCA?ygq;11&zI|#g~gMI;Ea&_&H6L<g2%yL>DBJGm3c04eE6=7aLs~je
+0@$=e=!bk#`b3k!1<rUvoy$#K5nsRH?LMqR?M5}@+ETTzyv1z-CtgsRvbXLID<DMI$V>yPHt3L&iu3E
+24f02MP(M`G_LBt!e;=3Ox!xe`NpnMQ_Ra3r73~M`ioq&a|reP(HPSJ*HV`rwFPW2+=%#gRVq%nTWsy
+eA_{Jcd6n<WT+F>;2$1m9O+h?Zo2QC%QQ>TSG<x9%i!V~eJENQc_A{C<keCy8lw3o##{P?tG=bJ}|j1
+@DPivfGuS=jH_|C4wpb@XA2-mwCcb0mN`k5yJJP!x{*6=RH-d_22Ro;VmY};9H-M&K)1a-0|NNxnS@)
+tCCak6-Hpq31Z7?q`Wn*`DDyFD*v<6K;2^0o8kXDU=j5sWz|ZPcO6&V0gb-?{s-H8bLdem1ks|G10l2
+O3EWacT0B!Of4ww%VkDGpQj_4|u7Usu4T)Bw)*}3c(ja0u?Xi>sB-_L{ttjqWSoVDjaqvke-c&;|7Cq
+>XA#?HZ1T(J&wYb*Vg5S&sgdFmdeTPs3CQ+e;g5=X3W|OPMWrm0usz5VO_&N&2QHf4OVL6YiX9i9LxU
+^|%jC3BvB|h?=AIXF;eL`6SU3!$~JsC43yJJF^m}XH4&!Cr0od6eMRzU4KQe>{pBY2cb4+p);ZsMAQ%
+z@74$oT_j7h;|b_X7X*mji&;I^EC{yec5pJr=?YtsXV#yjJlxY7rkW(5c^hByvQDYf=KThoYrlSgC^8
+YhR6XULo&%>`_d--EZ97A|xq?rJNLwI9+~6TL!_CQD{^M;Att`E8P$2BJK}ln_3plp-V%%PrSx1ng7B
+7X3x<~vv2EqU2N{2nCMU76UxXuW3v<pYckc&PLN$mZ&F-elwowACVyq1z*wIQ@6{goCquFnFFQxD5U5
+_VrQLR!8zE|6)v%>pA9iW-PIh&%!J$7HoKgKjq5)$N8X6Wu849%3j0Ecsv_3R`!$~_?dqX~<7xae<%b
+o!FF%h9*Jtq~FzWgvtQb}92$=5|yvySLNzqFvAJd#ck@mJ)HE>OJWe)2=8S(S*Y$A1R*5kkZ9WJS1W@
++p5~!P#U>0w1Oh|13<5`pn?eq&(LqD`@;uzcdDum?}p8`vDZ?9^!*1LQ<|5n5otAWtH)NYLn8o>g5*v
+<&QS&(4DYBs3pdD`-b=2gHV*aQPB@qRzwt3$v8rTnFK)UZXBqZKlDUuu9-y=`gN4ZVTT&L3vNwDu$e5
+K0~A<8^}$uTg|N4m<#2&jNds73N;Sh1cwRJEsaw|r=hVDWF+b&o(7L>ci@!J*etYP_NC0C}xkIy=1lK
+;yoMwpru&rpT`vX5t7pdRc*?!AA%<+!6+ZS^MeXe&EH0SfhkNrWSI<v))tX4S}dgR2D8N+oanB6bf?O
+Tek3v?V>fYTqV!HxOcQD2DSuE0`6TGyojrl!Tkr89FZv5-3Bx?<N)LPv0}UNtnCy`5et^pkz|`SnOGA
+`6G;m_v(E+m}lYszy+UGqoZPRnT422+&$kbi_Ke1qTTR>M`G8-FNMYGYy+|3^)?U1y`fOUFxGMfjAbN
+GO_mDLP6qkDn+^MbKx_GE>F-*#fp<~8!=iqvsNpr+mRc|<|w+BZa<}^4C_ZaIa)EOL%`3}$9MH(xJ|%
+Rb&CL1sc}K&3`cS3M6t!q$8%e0$L`<wVLV4^Qm*gPfma@=nu`mu2X}fNv&avMU#>o<`VA^cir|hoPtF
+$TT@aUbQM+sQ#e#UiQx#`Zfz%v3>$WBcim$$Iws>;AbfZa;tQo}=%4&Nw&6Ma@SGp4#rHHMH;55^ph!
+~WKJ%?2ceCuG7c2s084r80s$&h}}rSE_!Da@s~m;Jg$lk7f@d*tspbYm-8VcELF<Tp25Q>unxry~W&Q
+aZVwn;RDu=mMOHDsthcI(3bY<5<kP?vrJ~dd+jUT=V>s;XH%cm;!)amjJk`C`*<zE9}=%dW{w_Jz<_<
+M?SHj$}Z8oCJzy)k1O}7YW--<mKUr1<nAndGF&Fh=}3;^pjEMlMnXe{<t)ycVEDkOzyR$LoF;e&F75_
+``Bd>r#N%hr^VQVbitLb?A}h7k7?xf+%f5(q4-4Mxex-)7m<dXF+dP(ZaX*UMYPKo!J#EEMMOE)uK?)
+H9P3>XohKTUP)H=oS>nQg}k{bc&alsFV4Hhx-c@)FNun2_G97B-H7Fk)=6P_-J`){vRX$5<kN}__g2`
+&o+BhZaR1Xm?^a!%N&VhyaZRc2teO2pSl_)(f7q9gDV3S>w`D(iJ$eneKxs>b<`S$1Y=-EjkkQIpWr4
+={>tWrmUyl-YO^q#?!9<!>83DyC1lNSv0}ubJXf6i}PHR%J;hi8);|Gl#qi^rD!Vrqe1C{1^^NekMj!
+1t7`Ng}<0>PF_3XkeX6<2#LUN2g#ulgoOcy7(5RYkeo7*Sb@n7Is$P`v*&?C7uSK0*-qdgMoQ1`W7=`
+y?jcZYQ4Du!@;wW+NdI=xEdE0Ppfoupcvb@cB#Q-Z7Ql~Rm5zI-nh;xTZi{9Ii~-o)R}i}*&IJ%dry)
+UodD%G6pgYzfb8{t88_!9dIU|o<Dfb6j@8782-#e)x%iqnY2WYVlMw*~N5C+!a0G1#n92qH=IMuW;i{
+RH{KGTGd>97!<pHNm_9qwPYJ=Vly&Q{RAvWCaW_@;%~H+Uu!1W0dbd&?YIUq4qyxvjk%Z`;x!NYMfkD
+c#h=lWC_U%&a(J2pPO5j}Z|c!m>?Tc@JHd^<hqq2Zih~Wzuh5W>iUDj)<#KA7groRS7*1k+!KeMg2@x
+6+p(6j~$t}Hnow5gz}@P)O$Utx;Ip<|5-ACLHPt$TWe9-+*f_uU{aD~=hu_sscA-(fXS=;HiA~$d76T
+-KKP>P{W3cf59YXjhWmL${$v=-x>_fTrHH)+V=?L$j~-MEUCo2X-)VL5{1h>&KGHIRXIJ#400dA~#A2
+r3aiN~O7^G^@n>DV6ZDi2G!rZpY&Efo4Po2w81EuX`O<b+Sq|uHyIgj?10WiiQ*}{S)0<Q$1GEz7DVm
+2$eu5vGnW^nXEK^_@Q*cPD*H=z%!(>UN@1gb8o<*wMAge<x2!Oi-PhmI1vIU<#Nn*-tDKksZ}nd8iI2
+LMven+|@^>G$=kb5L{AGRV4l9sPBujb_U113W!1Q*><x>%cV~xg0>;+!%`A+$;lVDyNLKgLr~Wv35W=
+I-HVCux5qrpla(yA+RT^xpW5SSsjR1*f=F39#a{^M&k~!kXWu)w%}FKnS#QIAin3?chzH1HRcX9+6+)
+7=S#eYfwtlYKl4h!4n1ad!FwygdEa2@rou%(c{a~E(?jNS91yDl^2C-8p3n1vWk+4;{L#a`9$tR$Co$
+VPXKuLzl0N`36TwF&71RQ|`Yr&v2wDH@xBvUsH<w&WQGky&jH)0FWdZkO*8u7+=+tgtVF%Vns}&Y#*K
+(y6b|pXXjU4r91wjySNO`eZ@kwoMjYDu-<RR}N4b9|dHcyiglq;Qnz?5^WZaTUfjvv|v26jacgb#=7w
+Z&slIVGTzX(JwI0#R)l<H-%MY+qxZZ>9>(8#}08uoDeqwrI}?c9c5@^8(CxCnXl)46iu18f7;_zP!8J
+A-7${*(>_gxD+APf<<wWil@HNjo|c+PJr8aPC8uAi@>x3-s5_2wsA~if;6A9i?s%gjE^7bJjZY86`p{
+8W;fLGPS(Xpijnm7iM$@V5+~ScnmvIYjevt|3I5POX5uZ`$wHVB91o@I+h0J<$4=_AJw4F*xD7)tP>m
+F$ROW$?^0;}wwZwQZ25sbGDr(Ew!CLJn(mo)brs~J4sNM9tKA0aR`4izfe!}Ylo+N)k4osK|(?_(t3j
+<^^oV2|Q+W&0m1W3a)TP1zy8&Pt5EjPu1YuRX@uEyLGO#Z%bYKR$DmC4L8v#ZatFE*clzUoeY%)UT?;
+(iET_uhLy+K6!HOjJh{a;AuMnd}w&eXl;hp6}jG1%I+sVZE&ne!8>?j-W3P$zX)!sURUTdD?Ca(Oilo
+yGX>Rlj(nicgPbal+ja}9yQXL;n~}7B8G8Z(*>vmAxy}@-@o}@eDTF+I&LtoET{u@h*&$3;2)cy;^u~
+Y$^aIf2&AG&buJAUmoEJn^f@2RjKg?>F{bebe#ir9!S<yg?h7j5jclrNK-SW|VX>O|?Je0iv|%Zpw#K
+^!7E?9t1egKDklHib$Wblig8GOKQkT{kQ36&cKk2!cE@xw8pZk}QlVjWD4a6H1<vxUje-tTb;Rko9$A
+zFuORLMK8hx8sy=c69a10;(ZA_6CBR@0fJ}#19C$Cdp`JEL`2!0vSF~5t73AC;w&7o82l_17bG{XUcR
+;=}Kqd2Tl6f5x+-cfKlpE!#@oz1$0InYeqsyINb<>RgHnd3|P%<YSgZ#kXnv<v6qQZFE;^BdNMQP<|Z
+(qBx=Nl-zziBKcs4|9a5Vfl9kK2se(b-7+d`vBc0x9R=1A+TJ4MtRKE#pqtYqT-x%66oLwq47&|N`;<
+<dj)v@CZx8yr_fwch#ukYP~{=XF=tOCRWIy3ra7c(B7YfU2Hy9zsgdX02j?z0Rm`wD^H<$@5nXF_`<H
+5x?fUl6QH@hTj3mB}>PA8=+xFSYte*>=Z>yMz0m;J0ad8&mcf^CrZv4`AN;1tXEvXT`UK4hjvhy(An+
+%#oN}Wx`6vK}cC3^*9bG68-N=&!)U+O!%K30N^yI^FJv8}$|_KMD;u1}*J=m@GkbLW?3K3T}d*M~)Xo
+1pOPh4`)!KZ9tt$6;E|i1G^lm^ul<F!{a<2LNu~4K<y<%G5<eSPR(ps2q&wRC<fQl(_J8(;IOAVRS)p
+)t9sDjn=?i=f_o`I<H7oxC7#XV;ueKPc%NxBQM}6`|6&Y*26#^>o8*I*t*9L06iOC;V%c)h=q>m%rq-
+K3xzv*qYS;4lvdpr{aw}U25{`|fS{M#wtc@YdIuWb*Wp2-02@TOwLTLj&vp$K&i?f6SGqcma<ULOx6Q
+d*8B14i?D0?n5WEq|`}YH0*7Sb3Eqa+`;(x&7!|Pd#eMfisP=nsIc%O*YMK65Kr{NRtLK$U=CP&#Uu@
+&Q8eHN%z&8YMr+-^LoB2yR>%Lp#Q!@r7?+!9738BR4~L?CACt<b&G45|*tm?8_O-jQkX)?UI(YlHOxw
+7amx0q`oGqHnlFzl@ah`ltNJSGVIty)^|d)tMNz`{W@EY)ClZz9wO23j?MFp#f4hdNS>S?)^H622U@b
+J*f(mn?anv@837)>YC5fpYB*d)hqkrkJ$%*YN+q9Owoo}VXAPV9-%q?cd3atWUUj#fo@Kz`4*U-zo-Y
+{U0AZA@$e=~>iC2c={9W=Prm4wC|*E9l}de4(Vk`_kJ!OQk#W~jLBFn6pI_S@9W@9%*g!;`CWmpm`j;
+fE?=l@V8R+|`Vy3reaLq-Mo@MgDKXry|Dlp3K@WCbDnt1r?B10Bbi|t}ES)c6ebN&w&pgiYjcbtQdGa
+L*&ckIEaFw-%IJXNCP*Cv`OZ<jNls@YJ-#kBC6N+Mm`L}vk)B*9!Wj1^8F6JB=jLd~WR`?Y3+ohzwYQ
+$U4V>*Eace};+^l1z@E(g~IS2T)4`1QY-O00;mZO7>O&00002000000000a0001RX>c!JX>N37a&BR4
+FLGsbZ)|mRX>V>XUtei%X>?y-E^v7R08mQ<1QY-O00;mZO7>Re8_TKx0000-0ssIY0001RX>c!JX>N3
+7a&BR4FLGsbZ)|mRX>V>XVqtS-E^v8`P(f<LFc7@!6?;s;%>xYSp{0jFX-jf6#whkW5tY5l?k1(buWV
+zt#A)e*4jO4@XQpOqKtF?P58#?Wtng^Pw|kEXJUh_@UV}Pntv9CbJ_i?8g=-Z#Vk^c|cOoDfd85W=xN
+h-uc8m?S`WIPHN8%604%L{s&>PdmRmiZOoMr~%WTO1-Hk&i^Jh^2oH^!9Siok;v+@g@bAg8@%g*EViE
+P9|DL0>1pL|R1mlJ-5_+Lu6i#PYq6bLhfhReT%~ePry3e6P2JyZfuq>9mNg6NDGiO%r_ojMWn}@nUHv
+dk569ecMGZh+{i5w?ob8b-|N|-!lBq%@<Hh0|XQR000O88%p+8000000ssI200000D*ylhaA|NaUukZ
+1WpZv|Y%g+Ub8l>QbZKvHFKlIJVPknOUtei%X>?y-E^v7R08mQ<1QY-O00;mZO7>O;&nGf68UO%5UH|
+|q0001RX>c!JX>N37a&BR4FLGsbZ)|mRX>V>XY-ML*V|g!fWpi(Ac4cxdaCxmfYmeJTlHc_!IvV&!0y
+GS6_x8gLPJ3|T7-wAK7>;xK;2kg&*%~pXNQF(#Sm*VBzj}1DpOh!T3D}K??5?h^cU4z&xm>=GC)rlAE
+zjbuR9!O;b=NKy?+#K__EkT<5_Kz1^-0u9oMgZ6`lGBwp~Svxn(k5EE*9`i4BhFbkq@$gnZJ*9FORYv
+;H7|Hk%_Kt&hURysFN&3finRLz!Rsw`%RX^2Ik!tebq>%M7I}Z*Y2CT9N>>$wB3*qB=~j1LH3WelA;j
+HsvCEWbeCKT`LUEIMqG)$fRPo=-DLu%0u~Rl@9PRs8Fx3{jxF99?a3QZOJz2*+}FJtfB<7#ZNy{Us-;
+*x0$LJR0E8>p7c9Q(Wl;?WLBrRJ<#M@LTnQvJ)2?psVV_4_QK&;VHkH`nW{!X&kQg3zM=4HS4ex;o2z
+x&cV=prRb3C8Uw?Yj)5b36)4HwP!Wzi_PSk%W;*AJrU?(bm{^QSti#lG*3uxQf&&0&fX`duaW#n=oLK
+;tp>Ap4=~nrTFNDC(Bq4d)Z$u3x<1sV{2e;wzX|08cjJ`&z-@KWfZ2;wK4zz8g;s;73qEsIvS4sN40~
+sVF}b_YP2$lX_pvUR@ZRxjZv7-`Z#HLO?{>10q>jlt4&5_?Lr}&A0d@HFOfC3HXX+;2Wui{{htC&GQD
+Ce16rc0i;@18yfJUM#k(&e_nUPOOh0N^IwHJeAo9~AN;BKZw;rwiO#UspgKRup{R<Xa325Ms_}$)$?D
+B{ICQN>YO`3Uwo`*3f7H~I`5yo5&BosF)0gxxHTkHQHxs@olytY5oYPgZQCU;BAI!Ax;oldAJ|aIn=A
+;I9U^s|GDm(S^RP-{z{5Sk2xfzff{2x3Za{JuXJa9lUwLwVA4>0ASXzD5l0|lE0l^AkR2RTD>vyhTQ0
+!2`X^dw_@vmH>`r8rq^FkqVmmT&s*p`PI$Kyx&?JDz}iySk}|b3PRJYIaH%k2O&4<&aO}HxHl!?8+e@
+`zAlg1{h~ej(vl(^JYdg7>>4OW-`htkRG1SPdV1AG~-+FTfn#fm0(0jM_};2o1YsQB<8+0I4VDpzAYA
+r7HHAd*xC%p@;yCU<#}5iWuC7W3s962{f?|&IQ|4?IkxjXh!b1Q_c3qp?iPy$*l3Y69u*7=kzwh@H@A
+^?vIM(Zzhzte9`?Nv=Kt<^TzwDZk|F$Cu>*eqNRyKRffqM_C(FcM9^D)M_gh3zfFh%#CZ}~@gW(ozp$
+rb_AB}8*2Y;-=PZor{LHU~f?NU=g-7tWq0R0=m1=8DFQ1RjzZ0x!C>&<|h!$6`&*8rvfAOIbap@<U0G
+BJfX7Qc1<&9QFj|I5Cc&>TAEeC94UN1tEJraL`^){1s8ElWEQ_5Ko-+Uvm~l-V}LHEPxY5Gw5#z)onm
+;9X8)tO9JRtGZL?wnUR#f>@q0I0HyPS6tvH<Eg=#;m(1BqG&78$U#F%st(SDz_RGkzzw3f2UCj7>O6p
+%_+|vCfQE)u^P&v|izZ41R3K6kuda{cw^5<0gK_GJ(;bK`aij-5D~GN}4JAlJf4-dv5TdrlO{`EDv*6
+X5=5SmfUe=8?-krQMhQ-nWi%g1rHv!(z5^}wcv8h$=XvQ{8zST55v4M^E(p8SF`-dIoZOevU*(-K-6G
+v!+A4`iXo4@R_=vyGIkJM7f6yjMg4luDm{t`S9XvD2}rj{GQ1TP-RZf<a)072d=M8GYp0ceg#tlQ)$B
+lKIb%$C`2AQ`J;aaxhNb;+T5fk4yx9qzi4yD{AJE1Zh5w=Y0CqMb4`1!fngi8{D_l3LJ!XZ_OWo==n%
+V>eF|g)|9SM(6B^-Q2{?Pha()r$xwQ@Au%?AVo2}{Pfvu2FETlOc{$|bzxW2PD1Ph<iV3J%BFw}(ZoS
+3Hz-<9jz~XI;D+k*U`P!_mcSCU3Se_g#QyczPXEStI>{CPV9h*mdI=Ffyq*G2a#$UhCd~0Z7_Z``Bj9
+_A_H5R+mX-dI>l8T07;=#J91VP0N*D?fAeNXg-_-jX#8_7NWaw@btgZIv8+^I^%#bK30Qs$lJhwDfve
+{eK>mV5fEfF8vVVn`%`niC8O|f}S>C^3$*S)tH)SVrAEIvpRT%#J@UI<t1tWn7v{@3RUl248{>`SeaZ
+azLUWa8$``(#+-P@(Hf9Hha7ugBAUUsTdCj&pE_)aTp}MkYcz;Z~MqcXz;VbPYT;h^2^yBM94SolVTO
+3Je+m?l(dORSp@SC8TR%sjv@`M5pSno!ALF#k0!XNAGX{dN)mh?CpyH(n0tt7`R?|Vw~kMpx{X`!H7E
+!G)bU0K&QT2E%E+KN6cY_^H;D+MEz~VkYH6`uyA?*i9b9c@GvFuG&#+hv~8pp$q8``lztHq!BttLfct
+mA#?UCh@bFQ{`D)6W0>z(AsGK_1s;RN;Hd#p>ECxnW^j$}(6hNIzzBW1ro1A1$VxbL?RbW50x7uJm63
+A0ASU2K%qzY8f65u&HR|N+0MuLMa2lOWx2a6-*7+tj?hch|06-M0fr0#`FD92><xWHrEbReKGdu(wom
+KkB9){=_ilG-UjWt0H~exxwPRYX|q&f?c!F@uhaGQa+s+5P<3mY8<Ec}1}xECI=cTX3H0OT`03PFzBS
+yx>unMJ*1UQWO{i(Xdd;bZ`(OVwPAr1^Ny01Z<{vxIM`BCqT(!cjode%ny*SRLR)}oL;5HW1D_#nS$g
+-MF6{PrO>mXHHz);nJqT?ukm-WEVY8!Yj28n5LK1CyBa#&*ecj4#bb^+z7o&NVWbq$)ZM5k4Uw+ekR<
+8KGDSYNdYXwJI!Mfb@dpQ%Q(Y~K7DGl*0@@9V<v|t|$$X6gB5<?-yW-5wPu*z*DV0<=TCGWwlvbsZP2
+W!LF$sUf2Q3*J;Cfl3-%t)HEV98`t)N0BlFf>NV}UN)2oQ?*)*Iqhb4i6=cwwu&t0eQOv>p;a(>8I6C
+^sQ8YhM_=BytA-Onw|d>Q^iU+9Kwl$7$C4qNDS}X*W?e=nTx*z@tqM-#WC(iW4f~3MQ<*2*nxWgXet3
+dA)G76w{heS)C|(M(AgP<^axZpz}^xc{$E?V#5OSBpgR+j}se$%KGsjQxOzd<x}?Ij5nt&G%*oLa;!P
+;&McrrrP1?S&#TJaAhNu0Nkg?Re(xB2T_=k+jAvi?FLq|q2ZWxH(;ZvzF+X6PtTH<vyw9je!^tjSm<9
+?Cj=#pT-`L`y%FD-sB$>T2AdhG$1j(5w+6r<x_M8y}6e2q=QCg?r!9&BLcn5r32dN?YZi4>S%?eSm9l
+8L{YVdc;2TEwg^rl~TgJjsqWvoXx80*jziU?}t2}WJMp$E4E13fB0rmgERkhAw>^c-8KxfaVE&d?Hvo
+Z|t^0HC16GG;+IO5a|z4|U(Q#NA`jf53{8U5wTBR)B=nERBBtjHN^{+sJg-DC|+zRLXmQ2L{47e1Rm@
+Tumu(|0PEfV65IdVtl8IuBpn20b!?;XTzw4%8NS*qQ<OA1`Ai>6$`iCGK5Kl&aoKE!^Red@pRg*n7P)
+E%O?}I8BNVKyj94bzzyi)6lGSC?X~r(XW+{WhS$&3HAZvS8cT8R#@=OLP?I7w9sJ_bR5(Jf<PTa0<R|
+m}9?a8gFA|;zst*U5yHixP(LMo$lsrP_O#F#Y)w$?KBro<L$QZG}e~=7R!!iCpA+R8Z4m`@Mb%FGZ({
+1&OV>=5A5q98x{o_w~!XgR>ngR$-P&L9>%990`iWHxqFoqAaT5)jcivkmD%Ll2eXcDf4tn>LmXMEelA
+z|j7_^td|9H@HnOFH@`{E>n5XJ+By66-jYVCF{W;<0GsZ~5u-r2SSxG#!X3*u?^1u)>$6OOp`+CpsmE
+t)r)2z)UA7EvT&6)nrz{x?}td=oKwc);(RqpDykAD24WbGi+nusg~?HT2s)m<<pH=vWxKCg6=v&y+0H
+Wm@qM*rMrWl6V8;<Nwm%_hU#>5qZ3fiiawG_*|}jm8BUHOoCIuahq}?aNnodQ8vG?JB83xk)|;be2=;
+Uw;0ArJ7NqTu>n1`|6ouIGBg9yMEC+v6SQW`c9A|k$?l@HTHh|hTgLvj^t&Yq8Tb@ZZ<}uWPqTLTTwc
+K=C=`j=Ywt*0SNyhMpLf|eKy+l5`1DwqEBA`si9NVoY2K@B$%oG|fjMV!OKsKF;iLbWdZ2QvcTae4l5
+jmCHJi*j0UqpRxe9lXUFDny5;t9;>4F$GaJc?OgHh9jqHXa2wk?JLEp8uDl@pKa1b`wMoYkG*agDSQj
+Xe1msj=3Nff_bT%2IJ(w5TO-`jEASFUo;$lz-+(<<u$mNf^#9rEU?xPhIaxh75x+JO|lqzC7vra9x1}
+^<uy9Esc?wPZM5};IQdatqakMraEmQ1q&3*$qO&V1KO{}9%WJEhx(#zqc|(#;p`2$8Y*nR`DhF`6KGA
+Z@R$`kDd2sR7tYy0p8bK6uK)VqQr#ESpy@21JRoQPT5~awMVG0YAxpDpJ^YyJ*##7yjtl*9%+!IV0`^
+KrAC8kbmu&@;7q;;|c^IpX#3I*XHT;TUx2!Zu9ROiCk$cDmZj(s(`9SGeHJAHNG3(`HW((HJ%q=cEiq
+bFe$MLKaY<|;<jAc*zpu{_Lbg%^I!d)pvP+lqJnDAU_C-c3;3k}o}q!(*&eCFZQfKe48;ioK#!ytDth
+(7EuF90pDdO@cpk+?X-D!}&KFhgA2$m3YhM!6UtED^WlST@^4T8je0t!`%c*+b_2KmS4vHxELjE5tRi
+YcQOZe`rLG-PlnP3J*u$b!OyKLATwuz+xXx<X)Ar%md!<o+$E5N<I7ldCacqndC)=ML28L)1`@<_mb!
+|=SS+?q2c1u#uYVrx)>p92EGj{|4IOi3nHQ9eOx+$NRwgcEqwg3GGf1a34j4PdB%1DoDDX%elWKCYPy
+qe%-8rjU8bF;7VR({pn&urHdwdR|d2zneHL5<;CwmMW9fUHMroM-noQ2rqRjxfgar-Bi0~~P91qa09g
+lw9oQIbs2Txn+OU=WEsA<SWp=`4Me2BsF|2^`UPYV8K6G;oU!br%*T1wz6|Krb8lfWaGavC{`u&N(b4
+rKNT)Ca!aLMu^h|7fPZ%MkwluoPcowciNo`r8Z|*dN<YA(;h&><WOefd21s&ZfoQQQWFPr|11D5yS_3
+#N#)r0TwZ4qOr1^;Em{H4IIA!ScL-t2&}g3@N`=vfn)3dp{$Nhpt_QL+N-?W>UB9N^cOzJ0DQ<|3Ski
+`c1v|QH2#j<fJB7HXQS*xTfXCR@u}~W+Mb}v1;Tj80fT=i8$Am-QVU{-NFo?0!l>XY$BTXMg1b5Cere
+d`iu$BYii^5n82=RD0Q!Y{{BiK}Je(hD(T|;Cnd(^FzvbBD??u(2ru+{sVv#3>UYSy7O3Lv<$`h@ij>
+S2qNAFt5SV$$sUt0&7Z(Snl=P5J2nV03o=WIvavJ2E~?lT1&f+E}U9kdt0Ap6FH8zMc9&DY~Ji1}e33
+-=G1V3GoufV7hWcrDX?%SCD&@Y<)a+>7{g)fHc6$zXJ+Kn>N|24R%x41EiS;n1_n=Seyw?<lF*rLNuR
+nChhcK(SN)|+XuNZgxI3POCCpGxQrDqP1o-@^xVNb_clTzewbtFc)Ee0t^#RVrZ7s~{z{?py7MkPm<x
+qKeKd-{kA*sLkW9xKLcHRVM*<RF8>E|#+7i-n=p$P48{mL`2#l{dn2ur<3+b1`S)T;KbUN?SC+@PB{~
+3)xfh2`JTYpINBdw=sB@_y7@%VDkI7KCR%ghN&v<zVj;{{7%u|m<v!I4!p^4LtfAhDB}Mh4dh^#mJxC
+BE-43e_$3bVv5hcW=bs{{1fmQ<k8*MSnKUEeymf;!rJQ8!S!A>0)Qjjm|~;A@)Ax-?lu6N96h;n4{%?
+v>3=x$?@;L3LMpaR5|8t{lMuqp25+1bz7Gm-ohPveO2Ss%ZIQq&Qq5^^Wg7V`hO~Ni|ay_b$u=HQK`c
+YNdvH-rZ2$R_i;t!3PTayi~kqa6ApQ3ZxGuLkiTGH-`)^>3rof7vc!G_D<>c&9AcnZH_dj!w$$-KeWF
+Uk1UAO#R(zUZe*Q<B82{FWA3KTE(>xTPcpsnrIcrnwnZRy++1Tj)Z}~sInGLRZ0E5?2&kf0z)nC6g>r
+W(m-?eJ&b+iehTChlCVRa|jOlsFztBoE-fgim}#;j9~@Cd$44LV|`c>KnR$h`)DponT?XH$<f-6~$(?
+jHeb0&$?;*}jF84O%;xzuHf|%jOPJj$KcZ+C9)2ZnT}o_7{6PPMykezZ^Z*2ccMQZ@{H1u^a0KZ;8{b
+t_=qe_C#AR2jpwL6qwrmoMuukNwQz5<VR409<O9^VlX0rzIzmVEO7WOfX7-<yMa`hcscf%(Hy~~ZG3F
+;BD}u6#~1>OCFtX^Zn2zW?+BstQY=)B6bB)m;@H84>Qc9c)<>ykqw+~alI`%*TjNC1POA4BCQS(H_LO
+VrXcxS0^?=POSK+fWhei9d!N*yGjt-q6zBNWPw`Mnf1<za!rxT-eV~0J?$MgDa&=QcU_W=!DbamAvCa
+_nUT>h-+>j;h@5aRl#m;;cuk?KX5c!~e+`ue_x$RMB230x3(D;Z=dI*>DbXEeBhAy?gq*^ib5vrveD3
+!WFB-?>@FsFb<o5X11J&8WJEKZqarZX`<^6P-*T9%>K<q(uxc`%SsEcMHVF1&t<XE0+g~zC3{Er#G24
+5|H0C$-p_@RqEPz`ap6LQer(?%(~4TIp3yv7{Lk?%}J3%F>+iO3N~G`20!xz4;J3H_Pp7<;safki|3L
+gvTk#`KQ#nB-(jj+4hT?RLu169OU#9B+J7ke8VgvurxKePFWNX+)kERkmSpJUsC<*8|B;(1VchE-^m>
+Ia5OykwndZO>FAA6{TCyDJ9?eh!O1+Vjm&ODnYLkfypJ7u1Eipy2Y`BxP(8z9wp#K21Ca7_m;NasQl7
+psVQ6D?&b?~ICYAF677bV9rkd$L<-jeS>FM&Fs%(dI}rmswS5tx_UP>paqgE|h6@%B)C{o}juoIm}~*
+`OoP`7{N=#!+Jl5aYNKxQ2)H=JIRpRw3-AZOUAo8=5Ax(udHjHMAB_KvH4REAtQoBy@%N)OS0O-!p!+
+LX?dx@H})pQA3{orp|OlJaadzTRbLlrpqb1QHih6&^~{D`@J*i^x>X9IUo!3*@&q|hsaJR5I2xygthA
+{vAX)#e~Z${Csho8e^N#8=|ZlL9Vmo4C$qYAeeJ8np;t83gg<k4;KFgUm)M+v)5*R9LL4O(`Y;L%(xI
+qI=<ai-Ts2$P2x?MEpM0?;7k^97CxnGVvBDVt#>fiEkS;eQ4rt9UI-m9Tt}Pf^1IO*TH$ps<@+a;^eE
+B@dxv?;JSHW|n`pUBPlwJvxTW3=>d%OrpbyeGH9xp|@2}w#9m&g2b#CH;sM>;Kf)CU!OxsGoA>#Wqp?
+ADpv?a2JCj6+@9YVroH6c%?7&We&UJYj(m=5t+MGsOzO69!%aTR@zz3HUu6(J@@m(G$EhA;nBL&+I|O
+6pH9`Ne9h0^nni>=7{9YRo5r^q1RmD@X9$fy!;J=)b~{!Fmqp8;rkvq(f=q-_(caRC13nBkGtCopXf+
+ldiKYsujXzq+~;*OGn;_xfnU7VW*H?(i*V9PjXMg7U4>3u9`WufCCWVxH^1<u8P`ZAJ~U&2MK_ISzcu
+54w4a(0!R4c?|DR9Jm><wBxCWiRAB|rq(L`Q{r}Mto30rfwp@K#|n|SrDEZUq%LG70~TsPSmguZlN&i
+n$85PO|q$MJw*1KZ&5ctR*<+wj4qn<n@Lgn(iwM;;O8!ho3@>F)!8cjjiJ2h>Mn(mr!3(_@OGreuli2
+hUdPP<ei#yJBHSfj%Ipu_ET6N(W5(h&_OV1y&GS{ROLm%j4)Y@zmV`k%i>cXMtWH?Lo66eXz&PhN<$!
+weH%#4h}fc(qs6}HwZ8teEMYE7{%{&FP!R?TsY@qL~~AnI`Q{OC~=MR3-hyysJl6@J!(dho~m8=3pFf
+QZxbm{)R~VzN2DCS&3$Yl=1m+;u-3&R@i*UU=>C?kY~Ln9^B8v<e-Fu<ywTrtN}{z+PmC|@U}eiR=JR
+)cwx;Vc2|?eKPpl|z=p}vK2yaa0Mu>7Auv*8f$4@Yb)Hq>=8liWQ-pNmKc|?1ru*Y+%25J;_J0@}fuL
+EA7`h_o2MZ=PxsB(XLb91bU_04=8;tz4_5<|qlTwv%Exy4=@nPpdUb!nAAJ7N52gI;tM2UOb>sOUg$@
++~&E!?4=zxX$T2#i=I1L{|3)6SZ$4gVhx*uX&x8^cw$C1GpFN)PY1}7zj$`8FTvFYg7i%-p-!m>2^Jc
+zR*9?ce+G*F7fQDz!DO`+0{VX{>*o_tq5W;Kp%@}JKbk@KNfw_4s!1Fh|6H6)ehU)2v^$EMt_9tQBoP
+bJQOYDX$5~HgI0FHO#NrZ<4j-Ut9UcYd<mK<MM=%ZG@hWpc7S=G4x(Zzxj$L-P0c>OC=a!yt|3cp%_9
+Sb*YQ4XL64>nVt{naBo3%nYd?3u!b~+b^tp*A9tYzuQK}O5^BEpKiRjcjI&;8X`l?D|mb(nz5{j!oT=
+G2G?{LjUi{@<YE)ixL3c-YRyuOJm{i>|<-JV<%MJuxRiR_Gyp;Z__PD>^)IcbYRt1tc!P)h>@6aWAK2
+ml*O_ErD@0006200000001ul003}la4%nJZggdGZeeUMa%FRGY;|;LZ*DJgWpi(Ac4cg7VlQ7`X>MtB
+Utcb8c>@4YO9KQH0000802@m7R>J@y-$(@j0Av&Z04o3h0B~t=FJEbHbY*gGVQepQWpi(Ab#!TOZZC3
+Wb8l>RWo&6;FJfVHWiD`e)mZIr+cp&aucshXV2}Y#4`3iefug|z1nH2b+YiH#8R;r!Ba;eAC3B0u`z}
+93QMThHn}cCNg4mSq*ExsxQfj2w5WVdfzawnZ38~4s6yJb<2Az`&4U*orkdsfHW`ff;CpUd(7QS%&o+
+OR2?^suqkHBjoi;h<J^bXw>s)LF(45S)7e;!uQ`7z60vo;uA3Av#y`v&zD-C*E~a=}?;mr9OH$2>h^b
+j)+`bqRO0+WzhqbK*b5RWObvW1YoD)X=J;W&A!^<L8{16;;AR&mL(DTpu!)@L>LML225ygM$nA_1YLq
+*gRuwt1s46ts#K$tNoTFA1JR`O*LE!ao>03%+awJ=vk!Uj&wP)w%CunT#n8>4(QFYx;PBeGD(se8qyd
+-w1qzFr1%Pzo)e{IPT)^1shW=pTHx|>Mt=UqT%RWde^^7f(8H~E$^1yrz2wCEv&(_#(%p>dDZ~QmY)=
+9i%uHGY2;<)MEQ#Ev-+wH=|5&Dl%Y8^YCuyD*Uj^gYZm`)5tF2n96!{<!JV}usm#)E}M7o$R%PbV2pl
+xyzG(Vq+JtvONxhK-AC`QVNYiYe%ysiX?`Na9Sp9~Pg=jkn8G-p2C^r8)k*X;kqUVCpV+<;z-I@AW6P
+H(fSRW^}yEI-|&YrK}l<z}<o7ivB=wnk-^XGg-Colv4UA57?+m{0QqJLX7ILxE$!h4EqwM-`&-!dHTO
+8{*84RA!9=;4U+dbf#smwBNd*&(0~joq2YBu}&_xLbNCsLxioseBXo9EM`-#X9Q(EuDh^1i~G@VWBXt
+^5qfRp_$nm*CS}StFkV4sz2t|yj8;)4S3+NGurZlCpdNJ?OL(g3pIoBFzOsX;V~G#9ALC(97$aJ7rOu
+IAo|ZD%FGX)UW40J?ULMm-B$su(<0F=sDizgC;azokyY*~ULr<QQsFfd(%sX-oriYmdOin<k`Qux%VG
+4U(wT7B}xxOS-$Vw6H@p{b^aRU;H7>1}vU|h>TGM$yyS7|O}tsQ_NMb~rPgyfO^VM$m{qV)d&<B2HRK
+)c0IPjstHMDc`E0PAUiDkR#LhB~Z({N}PgXS|N&@eYk7(0XfTrBj?Th(umUEACj8+q#}a-_}UVBW{1z
+qFxXt(d)=vWEV<R9%j-j)M_no!A-HwP=FUU#jYBr`Yw<LjU=cn_#6%=d0g+=jqG8ZJ<&#UpuWe^)q&L
+8pd&xa+#C%3WqN8F2}#rR2Fpmj6){#R5e=c3cZgLa!QjT|1%GSSG?*pVwo#MS%2=*e4i~&0S(BkwKZ^
+5FW}G~&S+z!B5#8X!apJ8k%&XO+D2gRs>!`%>iB>JxKoQK1Ia+FA4U8vKh9lnAR>Vb*W|U#*X@B}CrI
+1<rxxaO&tF=u?AVHGVxc!o6u%BWc&Nva!HZSzSHEXu!ki7?%uULW-Ee3oE^fBdsLqTxnsX!#nhT8MtC
+@`9So`#bHdV)4MX)eL(9q2N+C|i409(me1M9)uEia!|RzY?s~VP*WoDE92V+l}Y`q2xt)p-#r;qeL$&
+D5qo3qq+Ntv)lM%<H<SO(=Z&ILsD<sx{OlC++N?hg6;pcaeeYKv18av==4o%gz0oGYajamv|+stNI$<
+1G#3BF{GvVox|rB5{YwRW4u0-w;)KDVX4<>~dh=LOOBrK@_ZRl*_+Ll0HQ|x3tf2!uMDmK^vxA#BPfV
+{%KSA-q+*D~(7+!&muUIB8QBIPR8CRawG8*Csa5(TD=Oh`t>FD|kP)h>@6aWAK2ml*O_Evl4E<S4!00
+0?E001!n003}la4%nJZggdGZeeUMa%FRGY;|;LZ*DJgWpi(Ac4cg7VlQK1Ze(d>VRU74E^vA6Ty1aLM
+iTz6U$LbTSOQpHlcKnT?o>3FIv3+|i7#=kC=7$4#FfRG;<8-Ij%wt;-^}bgNy$#)v_<dyA+h#lc6N4V
+_L-TLi*+rUmX+e-qNpxLh59JBa<pv3nzh>+nwf4s{qf`|ee&$+$v=-@{3B+Mt8L7lHsTjvz2<Gqj$7V
+j^ODExW!)B{%F39XZfb0JQ^Dt$Ei&1T6y>_8lk|#LxoDC)TU=(iezIwcQkvynh-RIY#V<U6k*zt-u0&
+NVs41<WX&<F4-bh%}(E5-1=r3MWz%MYF@OKMN4BM5*BL+XuGPycx8qvh`@wk$0R+br#e7%|1jaYCgy#
+fE?ZI)+kc3drhRv}wnwee^&wB%Y3H4FYdll*&_(G>Fy(jS~7a$d@$EUHU0?K%7&Gi;G5|9MkfWhJb+X
+Y%!m^U}=z0Y3~4Zurj$ZlP^9i&iupu@p)UDU3>Sa?10frE?$d2KM+4G2lWtPR}vxXi2}qEj4_-V@sqf
+Ne&|xZMtd7bj8b>J8r!m!^h=rI_p9%%*@ItUaGYS1}}xyon#JYWkx>9s=R=M1nsoHYE_Gw$A8S0NV8R
+HJ1Ul;Elo*siu^J|nQzSsPu0iK2u+kXY-VgVx!~<{Y8$6SHccm^5h{}91O}7goe}xyaoO-J-)iad+>V
+RX$wf!{AbTCCXMW@PXmr3HUx^}TpeM_+ShVOSu8VfX+7)Lf+mmCaY>~6*WZSMp6(yrrNB@3v{Oag+dh
++AxvzIT@<L{4NoE|?tK6(Y5qHh>?O+NaYnyh4_1uDN(jo(JF;Ze?)ER!joO1dySj_q$#cQ6z7<+s)~o
+duFQS0@lf(J8RsY^t_cb7p*qSh8Sr0^?|WxM;d4Gby=*%_vL3pPfRF?U0_>T~{D@)jUyFwq%7Qv#A!|
+ZsQ#+O{SJ)!`n?$F*{`BHNFrP*CJhKmpmP^<x90U{B5coP|MeKNwOZWT#|afT``2rk-@c=NMhXyi%c8
+rm6_(q?B7lR?%ej!+rR;U?;869l+?fl^4?I~NdjI%(S@<lHt590!Ay5Z8`wiCH+5YWJfGQBgJw5+A=X
+?HQ8(1J1ys|T*WWz+b3jtJxp9RQ*yk;5TKqN9nP=eg{54IR8+TEPc~+)E-G**#*zU%!;D+pv_FDrUmc
+>OXd5gY628{R}ftKS1A({gG9V|~b-^`tR(Ba1GVPPYG2YZ$NY}MjxKMvfh{YC{pg9Yr>el(Ac`tMNFk
+VC^IYWE*eUE#K07p>iNO6bPZtl|FOxw?O#rl!NHngf_rN`SvjdjRuORQ6+iuRo8Br#o>O-5|G#1^R?*
+-m~x6O)wGl`F*t8qwk<Io2h1ft-s%IO8@uxznKY0h_U1nWSGvka5Q*m1KLl}hNXQi{W}0p4`_`Y0JJF
+YvBN)rm~c3QrLu~>ecPw^_H8nviKi>TAq}qqf<m)onZ>xk(T2;`A>cM^0H2fRo^!;;nZkiOM4~agx+)
+q`srUfcVHM}OWUYWHY{}cj3fRK-!hpwwAv{HfF<3`Z!~8PhQ`Q)Ug5$&BgRKSd2S^rIE;)d8(Omu&J{
+8KdC~5L{wLk=$)ezp+O+nbJQn3pnVc-qt18q@)8ELsp>#WJv`a(nw=?bp#YRk=(9fIv`XwRmu3kVUxA
+c$$T1`sDf(Gt1m-x8lODK^c5ryc%?ic^C~!-<y5h{BCTowt^ca;3{9Z-5yUj=X(~bda$XS0}1sa|!a^
+(6LdYin$jV9B1Nf(aaT_GH0~_t2CnWCdBZeDD{qMkkq3rCAAg^Nwk`QF_>?nSgf~o0XXSmk{Hb&?YR_
+`a>~@|8yMfy3_Pr!gx3vp!j+mj&nS7hjD0_8K#?2ai$Cl_Qy#j2+z1^GPg$fR;mGx&SD(6wE({*efq9
+H)+;Hvpy&2t@J)A?AAby+%n@!R#!gM{}R`DWqpE~1AkUul~>-3vT2|ZodgL{S^$|Hn5CR&}DjfVYr<j
+50^1s4XU!N(K-WI++&U~vHL96t7<Mz~ptfV!8}@9sMFXrY(9jaYO;PDfqN;~Nyy7tQ-glqi4WR1AOI(
+3#qT3T@LgG1-qe7?0Fuh(z3xP27lJ-*kI<ycP!Nc)a46@i<&L_S9h#Py`I2=*3Kctu|B4l@jf_5Tzp?
+M)5S%5H*W<k-NuEH|6K;QZK35>h8lc=kL(PL+r7&jC=a(q+yK(E%&@9n4aG6A`T5dVLlEI%TW())=}4
+)7@dj3dxR8U-(Q**{q8(?!<U%;YlTVAXc2pc170*V=$>I&Tj`+3;eD%g-tdOQjSd+A(eUN6i<CAoN3H
+9)rv3fe1o-YPJCEUZ-Sr*8c1@>cOlLLWzm#Jl{5FFJpYfiJ>1w*!W$D(z#QkQ?z(5b_Ub2MCGOaTJVO
+9>*4wo8sQMll>4?6_y98(`pxQ%r$O>dVOC@KiMJqDah*BH;KJTQ)40^?1QBbZ`xGbh`Q{59dOUtFf9E
+Rfm)!eXoa$ncFla7BUgKS5#y`aC*lJH~EE*AZEI8BRL=y_SPu7T2PgUe^~2qIV3Y<F`mQLlu(n@ZEXh
+-52-zA|xI4+Z{Xoz5(XKL6g1KGq7#bYj%FswZePdvZg+?YkR-xF_YmjK9iH~-g}CF7hP`wk_B{z;6-R
+bPRgp_=IU!KgUBN!cfd{>afKG+MxnO{tjn8nOGQb<NbM?X;R@K`4N<fTvUdp8ijYKOX!*OA3`0jTo01
+9_<hvL|<Pw890N8RRt^<^<ND09I;CNvMWg0YI$FM&MMpD|tN+UpV_(Ph}mBya(BFX37qAMZ1AjPJwH!
+Z>w2pS;@(XlB8jw;{;JRw*vs>7D$o4N!Gz>u!(@cV9&80pMd^qPaR&&8Dr9Muv@G_ZvZ0^Q@pP!oD!g
+aUi3enrchH0L!)7^W0lYR`u;HKt{#^fM&{rP5Qn+<ayciWfkf2S`QD4eq)AY7?~nU@>)Fc#4bSXwZjS
+b^@Vn3tk!*p>cge>AA)+rjkpt=8G{}W;2OBEpaQ|MoOkN)xdnxW4F7`D9^|*c<W~igSjEz>qlj~&|i>
+{2})Mu+tV`|;KB`U^0fC8b?(b={%*s|AbbqsMoI^yz`GwcVhvbjwNtNu?2(CS7r_PRQ}V92P?c4+Im!
+8ab1{zINc4F$G1ut{CGrO{ihY7f7<8Dkq4I7xC`bW7|DJkd8I)KYbzM5~ias5gVR&Ua5dtdCDbps}un
+W;)C;>Hird~;m-C!IU%G8cFF+}g7%9y&7{xnnnq<J%sN{pd4{sIv(!i*c&g)Qias3q#$30l)YoLilIG
+*<%6IXOCE-+c8K{WgNVdG$QJEejiK>{bo8T^B#-W%WJ{(&$ao+qLs%A)y!|1hd~@mk=xr#|q}h66nwi
+A~*9h8GW!hbXCo2)2*XWUAiLnZ2@1bC{##_8PqwDpW$j}|3qj}Wue+5+@6aXU`MU8|L|$4TwGVB$Z~o
+b)3I+wBt#fNoyPneu;=_DgV=;-Gj#|A>2kpp3#$xZh$5K$Bu!#BBogw1s=qGaCPHkMHH%eo#i@tN6hL
+-~cWa-{;I@Vy5e=(g;B@idlrpKld!7v+{5}Ph8yGj9B>fu@e<;Zn2C^MiW<Fct!NYcE{fI-~EHnLo*h
+%TPe*C1(ZPts<?<1<#^BN1M&E01@x|qbYn*p?Uu!<g1Qt=kU8bMjY8O=9EnakN}v*8m9XL^rwJ{Hm-+
+5bUA^Qro~Lve3;pwWR0zjGB2z;su=ts2{B48w}-RCec+vtA{%Q|loW?HqtU;Ja(?j`s%lq{X{xGCKWW
+OU1Uslv4J+lfZw50Os9lH4X(iLE+DVsUNbRHqt(^2H67E)2RkY(fKtcvEdej5SVdjZpv*Ekl|WI;FM^
+is%Qw<j=uwz$}L@Wl9GDTlgFG>W&{@Ss7c<kpui5-{T|^2jJ*8*<&?d~2M$}{D1+;m-W%o&UuX(cnTD
+IUyohEt^+l8A94kv8*b8r0^0KH?O=89(ovd(-MO{tk+k@5Iou1uW<U<QxHnXM@7vAKLsBHQE;QlIHKG
+m7!_4CxYR7m2d;D6<Um*oP3236p)No=1j*S({Vv9|#BVKpkBwV{g9jz#|Hb)i0+9uRV@hKkXXrJ3-tw
+WfWQYBsia<0SeO5|AK!3}r$(16tnCGw#h--h1-#GbIW2t8$H}=`rJ-A7@c8h}rE!^$PMZ2C?Lr#imD9
+IcNzn!hF%_XGtDY^w5W%Rbe*W*1_nxmOnG5>$zR26#u2VH<v=3(dy?3qsv%7(NtOWY`HY0XifG{#(vb
+xFMCfZ@lrrpZes?X+w4W}6Mz6d0o%DP_5&aX{2~txCvtFqLxfDSs36#Fi)FDWU|vVentqejDlCrh+K!
+x@?E^R7o2ec>N%fwnrPo@Lo3~9%QI_JGzWb4FL8pnz!vsu&4lQGws`z=snYur8^&Sm55bCLViM7F(Xa
+4gtqexh1for@)d_+_wA^`O=I=8%7QEeHZj(VlQ#-ju?cooR@u;HlKq&UIDfkPSUfLS)1puo{uisjax&
+~;X+(<bhNnaJEVFG~w^=0pLGlVv`8qH==tj=<S67GUNaB&$<kTlD}8vofF`TqiHSCWY{f%vQF%D%k+Y
+MmEj*W>IHx^vX`x%s}AkWg_fbX}j9JV4TpMHXu`1lAapfwq3Uwguo<R|LAexVXGa|0$HIUpa613;1{e
+&tk=kf)ue~#HnaFJ`HJ|qeUHwGmg#?#e3h_g%5d71@EJ48pfIhNd8B4AZKNC<YDHUIaR9;ud_%=W2_b
+_QRUx_AoI1eFeq*ZpB<~Kf6^d{geizAgDz7wk-^e@zAAi0-Y@#!n1)88b>??Hr`23FOS=o8RRV~<HXe
+2*LBxp%Hj#w14hrLo@bo2h~=KZ;!=vB0$I7)sJg~B+Rt%+LV6Ja@WHM_xo0h7miqq7_J|NX&qTE>bY?
+9*#{Te~0lPAmBb`CFiMrCSD$(<h78je410?<)=-na_mPk(E2a>pe*Q-rlDfxaz(hIv!>+JkNWG2zny9
+hu2+b!+TzJ(K0=%6SQ(>%v>}r&&Q$ec5GrW!mu#wE+Gan;!nD#(8bUVqnCSpX-Nz8UR!?F=*8u~90w-
+C@UvZycfcIVQH58`0UIO4sqo4AqqzZaDnQ7^0`nTxMfWkp{-DNv_19fFA0B{pvTpdYhw4dGg;Gec09)
+7Y%c2%%<5;&cz(vu)?*oBO6ILrOz+s>p+yX??9gZA0LJtLAfnUi}dk=dCk<eGyB?1s_>FQ8ioT%ZOnL
+hSRsHpZ3HeYa9@DC-6$WsAgj9Qfqhf8&C3jM&~I%_I8>wZZsdLY>Y>FR(6kvimk_&^@+dI?C355ET7{
+f-oWi1gqKIkQU_mv^KS*xsI<d#dZb<k%Cc_qX83?#doj!qZ>1vj_hZn1i=czbvcl%^Py>nSlee1{G0g
+?*=xZ!fv#J*h^irti;&To9gg+Kddm}${_?X_ysKg4c~zY#e*Zzac$;hx`*->=5G(EKRs~gl8S;bbZB>
+}sVJ9SZ-YNP;nm;h&#9c@H~3hRB<JS?xE>C-Gk<qAKNvOJ@pmuA9dh0~&R$W!Lr`vI;y0a5zdjG+jDa
+^KQDUF~sQF@|-Z7)m1x#qG^c0CwClGiQ=JmBfx)ag~K<Au30HR%xA89BE_0;PCbgIOAi|;yaWFu2yp8
+gtbk?@4{aE0HmQ^ONYjlSEqDa!Usm?q{3<&uCW+ooB|g{|mZd+CPcgTJMt|7ylfAY=0loqNL4yZ@TU$
+7jAjoaRRY-cS81Lr25|-+}s!&sm9s@#oFg{ufY70|XQR000O88%p+8Dt&gR=o<h4#cTioE&u=kaA|Na
+UukZ1WpZv|Y%g+Ub8l>QbZKvHFLGsbZ)|pDY-wUIW?^G=Z*qAqaCz-LYj5L5lHdI+dO66MN@Py5zyWt
+U==QRcnav>C$sqA=E^rKnl3EsHid5K?JzAgt`&CuHACxq=i~F<$l2~MSb#-^WtGZKfcU?cQW!Db;!_d
+@=i(0-}@7v|jb&b$3n(pqdZtpJEeYa)9VF!OR^(nt#@Ld1&{&o54>({TodHe29Q+oAPy&U9UZ~E?Uy#
+0ZzpKk}=SBr)_zlN@tzrL-7YW3%8hr`Gp@2V|dUGI0g(|5a}?%Jx6zkcAq?RmT8`j>*>w7)*=_+KkE#
+<IdOCKqxxyLwlY54>G<eX*;S_Z3dG=mBKi^DS=&p=bKGeW;px^}YRc41(D4WxcL>Z~FhB-vEZkdhUn1
+F`eFZ{T4?38(-lXOab|}YwIPwDqDCJL+ZKcng<U1seyctZ}zxkZ{dXyHLSin{Tc|Mhvh7m)pEmiuUGi
+vbvyKjDf@B5c|$K!-S~$kryUVKReS}z+1Cpi`CT`>>GthP?RqPQs%a|x^1AQ!_Wzj=)v6k*w=EE*fZn
+jk^2=XZvELzRzIuNcHeLHySXt;CeI-nBdlPup?TUX;E6vL_{_Hiz@8#P!^fJ|Xt8mjD{#Xg_PH@WZ_)
+xC+y4p8G$=ipz@7jP$EU<3H8&NcMd#~Yr3x6MJ`iS$=ZE2FJ#@!CN33sB{^?X<L+|qy{+xPNIa+W~&1
++M+j??D7u;;rR|mGHg9ZY82#R_&?;pudel!q%#%PZ?_e9i$X*Zus&Zx)7(85|Ii(mLPQa$gcK=x{C$u
+iDlPti1&T>P><{`F&)f&yMyIh)J;7c%AvY5^T)k4G&T-kQ;7{XoxY}D<E;(PyQB0;`4aR5;u`i<15~E
+F_WQO4NaY^sx3u3CpL<L53ihoAS_XMy{?z=$UYSLovPjl}gi!4RR{yf;d9^yIMdvF!1bs$k30}Qk)dQ
+-5@bw26Tm&zXH-c9RH6f)z@Uapl&bM6J*NSwCH433Jo(2gg14c}Nen4257jN5jry!(sL#}Y&HTAL{BC
+__8jXoRA5Pbo`2J|S_HLjHR74%oV_Vw<Jx+HWo5dP3DyXHdjSW^js+q?#3hga2J@Lac;NErAy)0~Y@z
+%)mRf-TL8U0htC*#HuDuI+~c==)oGmzSix$`YpW3K}Q{ooBDI$pz^dc!?Io4Q@RU<t>2Ihy#5sfeXLy
+I(MZ-Zmk404R@zzWLw-g9d6}n7;=XuG$Q<Txj;69Me2z)IVh!-+mf1S<la;$H4k!l&;_gn&aH>C%*{d
+x-mItQmsCPCU;Wt6N{IKfl>D~Mw$(i^9T7b{BK>SHQYj_r{FyPSZmg=mwM}9AB`txd2WY$i<ItHy*Dp
+B?s}Kl3*LQ8#8}xATlHb*4iE>9Y7Pi_Qz`h|71(4RAgD~y*4auvbC~j|oa^7{Vk^~cW^`G=}=50Wswf
+|i0fd5r5JABrE2Hl;tgGSD;pq-qIl{e6ML~`Z93?~7kaF3-LMl%y&h985z-u6Lr?{~N`{%+z5`EP>u>
+FtAV=?@n{_r<<$R^_^?n>{p|NvrcFvJY`rpPqxhWP_Nc)s!qDcq${=n=1u01|d>VNhpS_V=z`mjB3X;
+Vx$5`;F-4gIHYf!EFAInb{Z;D(@za)*>BC-Ziu<m8wd@J`Iv#5PrSC_x~xF%3LMmHg%5ryj7LKnVMZ^
+bmOz5^0i-SBQUKZZ!4TRG7kSemw61Lq^EXu^xR0J)Z7{3(>^#)fdi~d~M+<v682KLXMvf3j=AiU)mFc
+kW+cbw=SY?51P}XZn*tGy-&e)t%;t>2P!|yY)iW2foZ78-W00#B*rzx@V^#IJ0B!5o*)-~9UupJW@Dz
+z&NM!73Ui=pa~JS3B&q9^k?pG=Mpy%l#TV6rD~)Mr);nnT6RXbMY^EW-xA?m#xcI&O>1u5nd^i5t3tI
+SeszmY5`E$YFtYW@tRl0;845PP2g1td<EF&d!_Ix4h>Em}*|Ha)dt7@azf?+HSD@tkO6p8E(t~x0bfa
+C1>C81BuUZzya2TT#TD#j*}<=%w;5W6#d%|!G>6Hq}7n`#w;fMHjBM)XXdGGvfl^3MdINp8_BU568ji
+!5cyQ|Q;OgwA?D89C^f*S`p6OV)J$p0*3$l*lNdTG+Ri}|hDHoR$)Z*`!PkCsPw1uj&ZoBHM1dk=j3}
+%?{6`W3K2j+eW7ChvInb2p<}?jm>syDq;zqZ2Jzucv@4osD%n%HQuu5(|Gh1i5Xv*L(H0D@6;N}cqj8
+aGmUOUjVp~KcqbqA*6u-p`${+D5>Hf@o4+x&w4$PGroe1Hv!V=GY>9K^E146s^tT#9mnS_Htp>e@^A)
+B)l>vKRWS)g5?UMT)pk&3Sn19W3+=ePs2_$h>J!S$&bs5wW{VdgFj@a7<*K$bQU|(C}$I!i^Bo>^<7T
+W&80~NXm2k*LV{}#q$R@x*9%{=&cfBsqihU1WPO~J~BK|ptCc+G#N<wW!0~cG;S8no->MY!HV(QPsGj
+3+Znq#@TTb=@h1>0A8xbp2_9eRBP&DFWd4+GtNwn!%VzAl-}C2l7YLsecNt>g$u3F4$0uQ+SR>&mVIH
+x5ll+qOu|AepQb5eqJx}eQJmNq9<dKiz5%;}koQ)G;<Ou&iSU2RohJolY(+2Y^V8!Sp=S^&^I97<sI?
+lXwqirA)6f>2Y@B)o%pywk|x>hGgK(f>;!f3$IgKO64)NazO(SZh<PilGdiQNpafxwuF=ZYcihW?`1k
+Ph(*u!7jovAg<#jG@W_lxf+J73^!?bN0yDuX{1D<)-U^M$l?n*FC&&;>8H8=R4#TC&>MRVMMGWOKV#=
+ufOhge7$d)13`P=cfa!Gz$kTxwh>!)eUER*SlZTtj4%|kH25B-&n-BOFUHVtv2H%MQo9m@_k*>3;QN$
+iHgCa*tk6xSWGCC=L>GY4>-X$mKmRxDEu)N+u9}}u&Rx)ji~*c5snLU{7a&)hSP;f+5PzIzV$;=3YLz
+Gazs<s<dG;@J1J35(y|yYpryI(j`OpJ=m15&VDrh7p&i==pDM9d<8y{kD41XkCt^Bm@k586mf8qm?hP
+A74HR;X1$3#nWxUvp`(nJMx3=HhIYj$--@un*q(FGC&{HMqVk5wxNQXo|J2#Wx4;R9$004)D06CHNWf
+IUEctupL@nP#%|H<WnNxcP=Wh=61WEY^KvQax#C_yN0wM^16P8{hGk+j_+LK8A*NUG_?T*u8K=kvQLa
+5N2_WGqkRU0GzY6KtelMRS@<EcGp+CO|*sx!q7LS>j!X|MDEYG(Dn(+_MSH!l#!UDMxLBM&o~5iI$Wb
+4d^`7XicJB@KXdt?__G#9^R#_830CpiV;P{wiru%}W9w)yO6?cU_SHkQzV#|MP$ne4Lgjb%0;U6Bv^*
+S%gTmOrY0i?OttWD;Pr+)viIdT{p$ZlI#*)4Y%Hn^@1qb1l2zBabC$&|1#Pl`9HaCC8jifN0Zvx9A-X
+~BuEk@NFBpZpi4Cq%o%%7tHkxwQU!QPVW|M%a|*iTh^4~(Wsno*GpWiM7>_cmMz;-<6$cmWhAlk}jgc
+R-y$BAPw(hq_{y^Z6wMSquN2Urqp0HIN2hgaSZx4F?!1KM!Ls4gl-mA?H&T=H}G*IsV9TAqpL*S6@hL
+;($nYxKP1D5ZQ<lP;W5=pSJfB83_F#e6b_{&h$;%)hMfXs-Ot^%;zkFCCSo_@lm9X66PF$zaxN0;GtZ
+r+oQm=;sbFh9_wL~XT_&kLcE;?@)-W=8(9Yae#nhLQ!U<<n1<afzXA%bUj?oj{8qCO(i+uTw&(ahASI
+VdRD)G6$t9s4rN+n|`orj)#C9ShbulHTS8;R&v1SwvL0vjp?5cjKt0wKWj_Z<f=M%ro4Wj8bC)5c(Cs
+c}lP6PsU5P<L*jReF_?xE(5T5hACam_5HXj1d*k^E&G*Bd?#<A$i;F7p2T&!PIWUn8$pOIOFSmHUdm@
+R*BBwOW3$j`1YZe(tf@zOOk`MmE^V;G(VeOK!A*)zHG)z!XA2m$C&Wkz-x~^QZz+Cx$))Vz0KTdAJ2i
+$`%375`n8S-M&DpCD7$gAJlGldjJpK2}avH;^j^Cz||rYAr^XV&=^vF3-qd6a!J9-k;9vbyQ5vEjX!4
+$*Tp~~r2M;h<{qS`>+bhEqKPRhK}?|QgtTd?S2hVs2{0mQyP`oyscsad?<iCw=TJm!mK0N%ytssQLj!
+%cgT+*<V|^Ylx(8|9kW>_#ZV%jAHILOn1fT$WQ1^ZW7QLXUV}tbk677q{{*I!pkNC#N)l?~>MGzJ(=F
+Z&xby2>v?XB|VRQJTPw$oF?5q+Of3ZPR_E45W4p{tO$of^8)D3)2;8Lq$mVEfM8($gpyaw1*(ck{b52
+Zyn*DY?~iYL~5Hy|PqLs#_p)327}N$HE$7PzCJ6WdnO+iKoLd3TTu`+R8Ahfuv_sxZpZ6v}M2ut?%l#
+YDgub$Bt}FI(n2Fbt2DBhID1XjmkwhS!;q{CTWRq)E)E_wfadbZKbfC_|Xw3@OTkA;cJuO2|%RN<A|4
+~%|suq=xs@%ej-t2mLWEsB-bU%AIL*HBM3akKEAe5hh}8aSyF}GrXsrN6W2W1-)E`Y^ZE8@K>2jA_=T
+?Xm8_)H07Dz6-^$Rh5!>z>Sl&ojA~I&}72o+GOBHLUO5sGD9opaAdJL!3pNqkb-K)Symok+?q93CHLj
+fOCS7NF~wUR-M2%HSb9s@_KPyi`_TSZY$FE0Of?FFmsY?%&3DW(P;x>}_Kt^<tr5CHVGmc!D@A`NOm+
+g&BeXiuzBH5yn_B9BjJ1)dNXN8lv6MvAIvbl$k4AP5x3E4<&O<0&fm_z~8y`*_3*=;blq6qTQ{e3B4X
+_*h|@=&MwE!dD5Uo3l+{rZ+OyoLC-$g_msA$y|r5N&$@sTG0WhqH;)RQ&5QYa$~bCzWqyOfU4lc*n2>
+P4lpwSG&V5#CHyw1QDKRMa+S1vrw%-c4<NsRnPN;A)k%*9h^=(U$wBjs=#;6fcr8%A$pH4pkQY7<iJf
+JOg^y$C9*dPkLOpz}W>$HskzDU7&sfFb!`jVwp-B7$dn>&no!qEYp{VP#N~tky;;01>57n&#^(;5Ao=
+eQcO_7cqDu1j2E(Tf9SR*MDI~>Ur<_~}br5oir0YuMB>WFC=m^M4JBpv6#k}*iOtyY`?*)H!99WXDkc
+aP*vY$v^#e1d51Jz`Yjp!<#m%^2dIkP2J+0d8drkmzy!A&@rDff@iiimPO(&$E<OB9A#_kEvV@@TbMS
+&%x>(hD0gNO|9edxmrDNo}IM(iA1}BO)?|pL~1MgNZ8wHl?r|1b0WMF?$4+o)<ou86;WW2b~Le2ktIM
+hpsIab1bkl;tPf|7;3=4pceywKgs3%!w$Z$ao1SAcS$I)FsMAFXJI5giOStQiV^C9OPH~kwQerGozo6
+SBYF!&JS<g^VKEK4e7ue@K9AOehLypw+WN$H*feif#V5T6l%TL55=v2&E$<l#Cx9^#A1|w0<Q|ko&$R
+`E+m{XI=YPr*<vfEUT)QLuAO1j&0ju&bMvRzfc<YPQg1I3?i<bJwIeZQ%v>-<k+ex<3P(6#{mqF4}%{
+mHba>7BsvqF_Nl>RQE{KzBV>2Q6nM17c?CFW-Ob6}YH+VOc4LmA3&rr}Uu03kg8S${JqwWedG<CMyD}
+i!<;**%j_y1N@HJivZxGgv5Atha(o+lRy~gk03ydy8&?L(5s7cj3FI-^TMgp@`T^@-G=II+Pf*^HB}f
+ds^vZG?DC%FZiTdjwyh2esf7S_*d<w%?3Dy<ssR?5Rsm6)V4hH(I;jF+sT&v2glO?pHq1Q~#fGD(+&s
+1}Xpm%aoFVMn6d#VAAI^_at0g&CnWiPM4I4^l(@5;4bl=Oq>pT}L3~?}OaKiDnGI{j$uXEf+Hvthbep
+vYCcFLZf@t>e#X=;j=c)Q<X2!!Vr$3T>8zILJ^2^;e@2sK%EMn+n-Bx{!}N!NQy*bN<Q+ZM~Tj@^q82
+v!F-1t6WulSCDrw9HkfB)}1cH<EH4O%}SfU(%V)Yz)Z=6p{#8)OoaW%~Eg@b?ip5QAHAkd-Qt*|3p(+
+Mx;x~VplFIt3C(X+=-zT(zHRFCf?XIco|Z1^x=7ylD9&UR&#)R*33K=qfIWkiZrF8Omay^2t@OhJfy6
+23K^G1iz>U-u4-^Z|HK~nt#33~+=@D3<Lho-ct(ZDyiL*tKe~sNh^GW-AQx>k*|}4JmRcS*jINr9PMa
+p$ICV{@5JQ(|EFA5Wodn68t%^f9=b(-jET1sO@x<gLb#7|JB##&&d0^gFXiOcH(`xSwej?V1W-_wC`W
+(C$c09ezaW(guF3Pb(`bpE>GxmccT9gT+Sejd;h-wqP{q1fznA;7m<n;!T0}s3E6v&*$K)usoqYFsfy
+-Z)Z;A{kjd!4%)N{l=oLdJ8>5{9S$M*Ks2Q<k4}{I=`v*?wow<*9;i8KEK+oLnQA!@vBZuba?<rj#*-
+Uw%PBils?Y<p%1?QwNq)P{EgYt&4oEj!t7do)Xz)z~Y^5l%Sl-T7p%*UULfQ%K;52FnU#$dfjjVgFm)
+SSFNy8%_|j##p}`hMj1V9uo{2UcaLE4H_n*}gl)>-xhUA1eUF5-r6YqLwyYYM4hSQL1_o&T6$cryty{
+1b>!r*FVAyH3=jf#%qF8!wqG)WWw_`O7hC|#7J(4=>2ysRbRAwhZV)#%YQ|ycCd&x#BkE~ye2kYnFg;
+cIa4#*wLZp)zq$J)K3Agx|}st%7>Cr+q-*>e?r#~s9*^|+96|CaNWkcTKtRox%Vk;p$7NXH7cDF$iqE
+ZjO(&nuP}Lj<)UHr9q7v6;PhYGifBF;glU=}m>VEN;h>CQY}f8ip6B6teDEC&b)=(3EvRp_knHm;ozb
+a-l}g62yZ73lbF#6aqgr?CeIcU)TozkicWeI7^Pg89WYTN(nWV#qs4ZNt&lCIZm#K!KVOey@hdQd?AT
+t5$<16w}iw$3I|z7;g{ySDFFwP;ya`uy8&_@KT;3{rLEpI3IfRLphqeWYPh?>IAF^kB_7_k0CJhwR3J
+YyEIDU?1oY%@ME;Rv`eWC-QE|XV-Q(s)`h+eF<>;-kZa;X7Id%_RE(<;NTI2jmHS@sx0a+<<J?1R-6x
+P{~m<(wxgXwZMyU&_h>p^Bt8VtC^ZrnN(2dokuHZHjWv?s!`uO3Tv7f7pKp~k|seD;9_A<Gf3R?R9h@
++`MgoEg+FNYuz!qqUALbeN`lG%xcmRm&VxVeI-!yYk8<mN3B|4(uqk+Y&ugl9<t=G!>3y8AI2y&qs_Q
+U3Kc8|L1Kk2cBS^_ZLCAkU3v9C+khNy!rgrb%qM3==pqNQuWa6$-<QP$dNDhyZ+gp@2eaWB}Gi{)vaM
+qYJ$(&L3}cp0lcG>V?t)ht+EtkdfCaDsR)g+hp@7RBjjd&`Ih3FR#R5WJfO%2eANpj>tXOfl_Ju~>CO
+9?jr$BI_jBv5BFnV`#T4X|!t8mHh0Jy4TDqJkKzKF2!?jdg6-5p)!{eoP^d*FeBX*V-Q@7H3E|Y{ZW(
+EF+#>q}Cr|0^|u^FfJI(vd&uykZLKRINM>t;P@Kv*P?@u0WqBr!2yk+z7$Jyo}si$mg4HV<wn<#bQ*@
+&sO_H3`KEVunso{vcC%4|I-1nxIe1!W<&hNl2Q_^Ta=7J&s>8O}6ao0mFP_sWQ5P1kXp}`F7N$23M-a
+OtGU{jaZCi<`$PvL?WY>{Rhj6U%R@^$LByvfecgQ*;r=n=)^#WpjjbL31TwUh;*8cPN<47>kb$P6Urp
+1>E*yVO#+-Wefn>+sh+0po1BzqgKK7>b3$H_Z1^x_ACv$5`t7^x8T+Z*Q$-J2$J-sn9K0eAEe#t?@l&
+B~yqlLYM-`*Pa#`X7<SA<kKq5>E3c=zHnd~ygYA*-{So6!P{!-qg;~<0|v^7QN+Q{5YQCNgbKqR3EO-
+ZYKoxSU1A{epqj-1Mq)5w7&Z?eE0bZye4Rb!>u42_UDjdkNmTq|HRHw<{{PF1%IG&I#Bn}`?2Dsmg2Y
+Z6hdic_jWIYFTkq+oSZ-VmjI_Q=U^RqC4kckz=msTYy~p&b=)Qz00RTsS-Ci&Kd;icD{h>9zO9)BSq3
+UJHze3)(xdGh-z_9gmO2<rzrwu^A8+YmCLxG^AUX`_nT|WT>fLsplKsl1Qr-=q6%#R4_`BAul<|Gd*S
+D)elN=qf;ga3H-84L3jPj<?Y%B-qvWQC!Kyd-Sez}yOCnZGh_XG#y_yb$f_Kxv-}Q&DUY>~by5_VtEl
+q7TPvH88Oe1y&}uEXJ%Z{$0t)SDu5Qc*PsP&x8F={x-3KmARU-}dDX__>Oa~j}$ybd2y6&<Wjof3pNJ
+B20?%|$QRL+H_>6Cjx!E<GD%?<UtcV1W`3o<`P(s!wCJ!V=uSok~g4Q)l+J?ia1>5lv1RlGTiB{wCtV
+98DS66S%oxFSet%agL(@MZ_f*T%^>UU&9kC`m8l*-D)*$Cxw;Qurgj&xxzXsg-xuiQ3?rr+CBK1G3rd
+>I)e0GnSD!$>1;f9$x#$+gDtGk+a|>s3*GhJGvx%1aX<hQ8u!pw!EZCRN1bR(`c-iM75KW8k;<r=B_z
+DpX;C6Tg#5f;$V<zqU3D+z6G?J0sx5w_IP85RMirT=uCquxidWGsF;Xcj(I-#ypRW?=wbz|iC}#obyd
+}o5(s$zUyb+PG=~V3!dIPyIN`;nv)&fO2%-5v^a|0@2=!y)c_z9=ur6Sy!WfqOl*6N2PmXzjs&l5Tb;
+=MLQ_-<f<W0DtFCYz6ZDl?^yP;rVOit_a1Rem1EG^^6RMc5JEb-0MvgiJF<KvDBU8U<Ioc-KNwJyhCb
+QdHbh>?L==3282f2gFy)l&QKB2}XePHTdAWFmodwTPS+{`)hW94%v-P2!>4zJX9-p-fR*Az0*yritCd
+>skj~ElFjgvpB(DxafE{F_q-TOBKfgF#_cju;87)BeyNl_%eQkKNDEz7Se=00jOsRG(DeS40z}Lrmgz
+9&BB-0m<{|OGg1feD3|105B&jrw^^e77X=<P6I^CI`>MSoy&SO_z@mf1YSya+sNWYbP0E5qy}@s+Fj#
+^AXBX|@;!Ej>M34{_C)=)B%^lMbW3F>;ufE3Tm_zA{jg;FrBSJy5ggt=z3xlxPW*By2_VOkE-)eS;T~
+*ZGOWwZ3idiwd9J*b-6ff;GuI&G{=Vbut#fn#$(YZp0?#k(+XD-}{|1VHW0|XQR000O88%p+8Db-rPy
+aoUONfrPAHvj+taA|NaUukZ1WpZv|Y%g+Ub8l>QbZKvHFLGsbZ)|pDY-wUIW^Z+FWM5-pZe(d>VRU74
+E^v9}SWR!+Mi9O8S1go6q(C7M<kAYU(Zo$!qi7toZh^uOXo?(KTd%n6?ozf=^uPDbE<Yv5(WyugT_ml
+Bv-9!h&5S0K$!|_7=_Fa<v{30ssdgeWlsXb=nTxHo(uoWoWsWl|3SF0Z97Sg=Bg>m!%75uag|ztkY)f
+YMOk~<RDApAjJf+K6oI4@QtyWvIQ9&+S<MFwmduP(j`OlShR63a|Jh-Z*%K3tg&TGYH7`+iz*CwNRFo
+BFLb`XhjX`PX)n(q-Caw)7y!-a5iO@<0>2u{`+l*1t-U>4psX_*m+;g+b1h%I+)mf&YNHah`hScSMtc
+Out!<s3GMI}*BtkxtjydKfFWP91)Y(v{V!b_AJ{C=Ujg+KCD4P&&<nQf*W|5qE1UJDn_#PsILNc1RbI
+)$oc9i=)Y85=C-TY2!pumzmRAA)XwZOe;kh2f@baDie*=uk=?<@G}UxUBwPIzg_<E;casE<J+^J&fot
+q7q83RT%5t>bfpmGbH~ZkW-cx&R-39hw7I#stSd!PP*}+-PPSC$+Qe0w-KIBeXKQ?OPx2<U^m{mKo{L
+vFYJWd#Ll{NpWls0q_w%yQ;v`&nHPq7Ed3Cky4ZP}}TrQUgR55mO5edB7h;*{Jp*<TYh)7uqPdpLt0G
+dp1Du8*#^|M=u4*&~XTm^K!jK2jyfB{aktt;<WZ8_LiOC*#N-so!Y5}8V^jl*g4+v(}4I4YaHcxO7QV
+A-5sqNr$vbcpE&l_(5lC@nx0aK@!>*7_yHJE=%aURj57JDtphk^tX}If_-h3dMKYD&1A|));LT;_2%*
+XFsFTo(jGC6J~Oy1;<x5GqQ4=nUQ0c7vEnj#4ohbTa?@y@++lbUs?cVA~(A7z-)s0GXACwV*J^hMNyP
+fArc8q2@{8#O5nyWIs{)GqG~x4&rf@SKJ6hgsI&GrPZ-zN@0bTWF?)RtPGreT_C>a`_*`35u&-&Z@lX
+@g1}Iga(R_#KT8Cs%9{1q4UZ2mtWP2HKOhX(X>9t7%C7>-Ow8_DL%m|IO{=F$Xn|RV*aJ7!AW{Id-a?
+@G33HEN=a$+*!TSDag@BBgqb+ugX>+huam1%HySyOkI4N}G0n_C;LqqgxLg!dV3J4q_<pX$!XCdFx<P
+n)CJAuf_T>DEbQr~+Y8KJ{9<R4n>b%*7E1ivA-A8M53q(Y4UY;F~{efb_hxJ{rfIJI?!yOYUxUbz{<;
+V%$T$x8n?SZPKer75beGF^6O!jdh`k4F`iqf$H__ftA~RMipq{R#w%}#SUZkfeINxJm6sL^)ayjyVuu
+<|MOKB0m4DX{f}#)!!>Z(fOfAUTJ9ZE>=3o7VZE+4CFRHA7Q~^@SdRv7<C&jx6m8Ig{V?44=?6xm>zl
+PNEuUN~G?(I_&NvO6DxP#%o%=))(>>;B9=Un4XoeCDl@P?(;B|9<)hK8K$Gj@^Pq|H1m<;;+5dYAXd0
+N;vhhdAOosS+1lypbt3vNSC#Ch?_pz#<&4!+J?VsU}(;^EZ?)FDn!S|i4{Kg3Rt6zPHD*_T8d$3!pS3
+42fZAX-8g9}FQ+LyzQgKax@8r)9CnAJc=uaMm%;>#)MvcH9PKR7P(lC}X&@=@G#Ui?(!rOaK)%6C7j%
+VT1|RbIEl9Hc2)qHd>f7yXFOPsIcwJZP9l%&qAGTn_4*uju1|6xCXJ!hJ7&2GP1Tw0a(kctJogTK?Vc
+0>!wT_sxou6U!r-J<Owry>xP}D;p!U(POrz-($DO}$b<^tBQ;)SuyEh@74JXz9)qSLU6M?@BwA9%y!&
+=TE@@iIXnA|AzbyO52R-V6b+4CeIz%#%UtvogDrz@5MTyL9ASh(JQ8HVM9Eg+7aMWV=c~7Pf(8&Y!A7
+l<JgY3cCf!?vPUj6uJm;smvoNbT<ANzor1#kAgQR96vWX85F!4zQILZ>Zu9&A|f1Q4Cww(tr2OMsME?
+Yez7Xll_OrbN5ewF>`utSEHy@I+gHMv(MWF)f;26x0m=mjUoBh+)=Ku}P&R(48CD?HAJNB-iCrhXvdh
+=43VkB~Lyf9*++z0UIIBdx;;juitdXSs(LnH^-bDZl%2@Qqc7YWE`V!f1BAeshQt~_gOk#Z#N)*PHn@
+8)694B(7n4k4$PlVvsugb4`X_iE{r3?Y@sZ_BE){z{ihczQzuypho+nK-pY@3@?tg!6I0qSPW*i|FMW
+z~ytj{mx5?+F8O#sOSz7MGjnThQO9KQH0000802@m7R<*OmdWZ}F0AMBn051Rl0B~t=FJEbHbY*gGVQ
+epQWpi(Ab#!TOZZC3Wb8l>RWo&6;FK}{ic4=f~axQRromyLS<F*xk*RQ~6A0nkPo3_&zO_kQ!bsA5aj
+l1h?oAG!kNQ7k66u|(Ly~?lecMd=Tq$KYqepw1UIQKhO?`mTku{LF?){Qom8)<*Elg-0uW6e%9hgw%#
+5zZ$gfxp|IZ?5v!-(9`_{`&1dXMFTVuN(h#-6$(prAmG^#`<4B$eOVEAMe#KdsVFi;O(JSA7p_0sRA>
+z(RAc_sCAv?PpT@6&8%{!d{U)eWwkX=x=_}&++D6*W97QJ2`|F+Y$cs)VP4Cs(1mQ&OuUA`fY((s6Ys
+!`wrZ!UCR|##fF1gGSO5O$`rXz0{O0G|?|yunU%$C}dwc!u_0_v@WdqvA9$NTs{m;=zZ~7{mvyi_@v>
+U57%96T1c{e=9yNPVq)y7yD7wR1`qKG$nB^GDy+$G1esLFefD{uAw4e5JvWR5epX98gNBUL&z|13PC(
+JS%RkYT`T^Pq%PC9~%qbS+k@c~;85Xw^95U%@;x0m^g$G@X(8%trpix|Gf-myKQl>^8wAv=dSkfLk}D
+;gaFK-pnTO(;CC0$q)ukSW^;7TyKmh@D?^=@XMQP{41OEp88k=e<1%3(a5l}63@myif7$CAZ&?vqsoJ
+jK|^Akh%jcE#+`^`lGnh}HJFhurB)c_X5>%e0WS#10&%N@C?#bAumY<z&xT|vl!SD*K?sPSn3&0TRu*
+RUKaxmDt04VGSE>-&n~CC+nDgXjVzqCC!XpUE65{P-4dZExN3VB0K!<dd$UVuD$h8Inrk!dYOhJ0DL@
+jNj*ZUH=MJz$K$l=Rt2(e@am)hkH)^i)JihOlg5`#dI`a(eG9cQ^!O<t%Pafh(cgoiyMx{?Qvp3|iT$
+1Ee?D2p>iGC=2FIDb^h5?9wSvUWT68M@)%TB?LLX23@DaR%$)un?<5>TZ@_Kd7=G>q^o`t!#5>y|UF$
+z|1nb8d0N>tp#G-<0Tt^(u!Uc0VAPu%0B6}a^5b+MSD-=8s{zwOEw71)>gqh%1*P<X!Hi59;(1({AN5
+IeMk>J;9xX@<A|ILKoO9GHe3XTv%W6ve0iC-b><FHF%uu|eNl<fbILgW5D4YIZ06z(%8j`A+LxZYH+0
+Qsqw#qBPX&cFYUk4~G%MGSa;roocS@ATJnrk3whv7iZ4#+wK1<#{z=G-{;uTl7dQAqclqz7)=ZBED8f
+hV9hZ7Kw>fj9?XfrCJKf^7(ejxX&OoQwfLxecPB{1iisuE_z#9!OV1EWIBH>iZ{_R5iSF^g`RiOZtUl
+-=N-9mBF9eqmBsI>UsBj1&mPz2^<Aj@PAvGedxVJ@(PcIK3J<6cXhGU3*h)QdYrMYgv9vf5=aJ+nwJ<
+=z9ivCBD0S{r#N6&j3`fIgdOm;U3H$0fP8nKa##fVueU4LFYx$ML;%wd-=oF-PM0@-(9}H9}8a(Lkvh
+u&W?;l0<lL>#_=lm#v%<E8&Em3qln#7LZU1WM{!VYCcXg*r;(mRm~<XwDzNTqjac$ztWp8lBSOhhd`I
+TpTvWtfsegrqZmw>`U%&bb^M#;I-tdX2%e@P@yluQtA^zRP%>lt&%}8@_Fj5=JloTu7AkkQrC2ojhQ{
+^jEp+^PP<cQtGx}1c`i6-Ma1ah!(dWGq-`aZ+l1m_JMUW714hTtM1Zgkyt3zJ?uG3|o-hP524dcTrWI
+!t;hAG&jhA$MFLL*oc-Uv^;%J0x#lGPNe@yF9&jlzhKe2iM6(#Sn@$6?rJz1q@N%^!CYmWc3#IQ@z?V
+7ys#e*b_*|E|(V<mAL@CTQ2*k_Vw1vLgmD4qqYZ*6uy5E?*|~!0u4|AIPcO0>A}H@q=UXZNv?Fh&1qT
+fwBYu2T@ppoI&~pPEE<YL(Ec$n5%WWvwnd)nN;i2viFj1GnRUNH*`2q2czn~dA5AX4P{euQKEj?<`pT
+Fxf*dQeD=++dpr}YNQsUC{)>LZV6DG^s-eJ*-GkBjm+#(fh0Cz$RiqPZJ!M&kuxHLQ(-sp)-@V$cp^k
+Ze7D`KE|=-FaZ8rj^lNZoLng(xooH7Vt8RmeF{s+q1f)94r>?;IxV4{0Zt8=H51+C0?yGcygF1iTz2p
+>y~$a`DIobt!c>U7d5%lTC>yhUBwnxd;7BWHIsRZde@vxAXU1yp=k49PLisLtl6|J~<(dQ!FclIE^2V
+&;^VQ7TVGN?Cr$s6OeJ#H6>_kiapAqM9oA&MF+(BVT-w`X9OM}3YrC@x<kUIKT2$+c@8Nu*pT}a)OkM
+`?hpjwvZc0$+JUV#=xEF)N!8mukwYGK3HsN2+^MMDqQpf3=;wAGIN`hInL9Ylh8E}Zc=5|Hds88lRoA
+6+K&0XkJu&u8-FPNcw#`IsIN+)Osyc*%+KE!HQJa5y_pdA=biJWDNtUx9WJ@wtA`yZ4F_nRc&Q#X6gf
+1aK0|j{#O3PxgST03)Y|G1#9Et!<UOZk4xR*5_^^SgyIpW7*>gF=rlR2TeE)A8nFz*dYR8LPEZC#TQd
+4gmLp)F3(p%xdIZS9T+(22sdQ0#dWtBl~uknBZM2~bX<3RX>P*Cc;&^iTy-sq8<Jm0#pCGz07o^mO1R
+paXu%ZZHu_>%|5Q;JAl$U@?Iri`Ltr99Qau`DUoN=>5@&FPC3;X8hYZD|%LCSwF~C*Gu!fNLoQsuhs`
+K!Qfdt=ytW=Zskgsx;ad<G@iTX21PmH3JoNB&j}Q1CrLs|d;00LgI6DEfg#>EruMmwa#s%<58YPrTxH
+S}$2<>ueW-#R%c?IJoWpN`E+*Hk_vS&mT=%wS-(nn!3XdDD^EYnoUd5b%xEz4=@B3MkD)+=@RA4&Ra{
+p>F^_?p<;K(`W)Y(J2j*B?>(=UYmS6xrO48*1{$aCT<H8C?WnMR>nucNnjz3Z*h+pLA@y(URIkes?ph
+%_NWS$E7pbj0E^4>UaDVR{}H!S)b$p!bpOu;E)Iiyii;hDGeae9i<I66(a%ck@4^Ygvf#V!?AFr03+{
+>L7BpuPBajk($X#0&qS~x+W_3#UwN^yuj`nrc+(m(R|G2^pS*l<jPuOUnB**ZKKr#`;^17hB%jo9*<o
+22!eg#s2#lX7rCvvCrbWzY6W&l@m2QKNtC4ieAZn%8xBX8r$;Ba$-RMRjkKYwiJw<^i`kQLD*hn;G~n
+qtc21)mD*5={(Vdjk2`wgqQpexB9ewTC-lzPCa?T`8o`de2{$35Y2fS0}B?einzj3EZ=yx%&D*8BITo
+POqBb=k3aiM&c2b35?MVX5|cR)`@7ra5EEves+QwnHkWn3mHI}}Wp*Pg9(K|vw=!snfYq0qE3<J|31<
+JNV+yaw<)Jn7tiS96;0rd~8a=&5%JI^X<+y}IZIG4u$O9JKS_HvF#5f5Xt_-nNr8b5JDc{5Cx@bFN2k
+?W<irc+)fQu(O}04#SOfKbR>l2Wp-j0r<pveC{*p@%ey>*$dGydntz<WA-U{fG~>RohP$p`T^m0%yhA
+3J2$5#(`bKEqt87^UEEpe-!SL#kkyTI@pa59yi8H0-qMGF967C>`X>WP7!{SPenvuXcZq&0TtfFrQ%~
+6DaJv<DT7Mt)uJIzAgWpd}!*!EiMLs9{t#&u|%n3#Hu=O@e$r3DlVuJQ|gs#-op0wkb{}Q)`m_1xA&A
+2aadDEM&S(L~*G*!}<Rtj?YgwP}%XMHgz^r_Ob2YiL8zGygGiTGWF7+hXl1R_h+a=AtDDfagsGK^6}H
+BtT<H|D~B#5!D1rX7o&l2u3&3Ff|((ihTBSJP~0)?uwbw-Z9YqvTfE@o|X@d4l`g^c?>7B0du1LT@ho
+r;!tgxiYoI>ijpM;oqsUHaiJ<DifrCVH>sJj`uTqh@gpt?^FF`0_mrT6I;vA68LC8_~|^CN)?x(nL-&
+mOr~i*9B|s(Rc4$c<IprYLw9kGg)~hrdSh;X_~<xX#K%5J7@PC3OjgBWLJI#>vYSqaMP`tE7e^;2i^b
+s6^6@@$E_%zyWHs64=@U8kcn_HkDRr2p{e@(@=?(0hCE6|V(vlRpVCQR#Jv@?A$+=zgkoP-3xbY+w7p
+SxX=(E@(GNlyMi<&U5{ewP|>$U&xo@#&C+ng=Yzh{RTt83ppB-pUsf|y4XhRL<xjSj%G)Y>!=eSW6Zn
+<HdlB;x;0@FLY@1p7RKz0~!8P)h>@6aWAK2ml*O_ExMKo!sXG000~e001ul003}la4%nJZggdGZeeUM
+a%FRGY;|;LZ*DJgWpi(Ac4cg7VlQ%KaBp&SWpXZXdEHiBYveW*eV<=(aS6<@Q-{!(Vn|_|un;KQvMrR
+7E=FTt&!~|luOufOmi+fU^0yOD+O+hgCd_0c-E+?UlnZN0%8XK+d1<sGSysk+%DE7=^100Xst9M4+3%
+&^_xpSHKVXGzyX%kDWb>^)Zt1#3xDE*Ip-NV9de1sHHn!}Hx@RSK_%|4_9k{<2jz4sZooT$oTEBlKbS
+`t@c}pMoQ!Oo*tU;n0L3BBaTc@cOC8z0TwOVCLI7dIps>fbWi8jfK@W5|MQ>mp-)3sw&Z0PIn=)KY0?
+uREVL-ijBS(=$z`*e3qE0NuaJttGYZ=JVWlG=ZSs7XZESc0M%URttq0C1`B=@cBMpNFI2xkzX|TL@2t
+;F5Gmler6-5S~h~$x1QZBeqR$O+lYKolRUG$s3BEW95v1lu|Q29AtLr0Rnzz%1U^-1MGwJ2QvPEkS}1
+^F*7cvUk;6Jt#b0>j!6V$#qr#5vz`6?_9aK1mrDJw+`af_(ccCOe*g-eDx*V@`-9L_yIQE2els<da)0
+oone*UeWzD_Jc}XZ7Kq*$}Le|-lx<0h6d#G2GCw^s!pSJ>a>H?nSyv`QkEGkr%9MjLtbnw1%$@zI`^y
+*lNSeo+(VKsES^Bpn)$gJ_AFpE*#*XV1V0q&-tBiworXaEQhyU_SPgaV9PIEZecD{mFOp{vtzeOwJ)-
+S!m7)2yE#O@nVKvl2cd<4HTYhW%t5HLn~4w*y8TD(@q`xulD+<NL;b4a8t9i_TsfkKytc<0F}c#<H)i
+9))yPy_AzEx6S9Mp&hlc)P-3`H}Bv5n9!Mvwmn{q{FcJ6r`>ls_h&O1fTi0*LG)|rXm5{bms}PFTQt*
+{j4kCghgv{w77AsWj9CxmgbqxDo)D5Dqm9BKC1m$WBtD^xM8k187{`-7-j1v7xtaY}bfaB`qdD!4^iE
+{n*kg>F2Nuo?r5etZtu=OL7@S2lM8E5%<Y#+GZA+Cr>y6H=h(5O`;&!6-zq*<A*!4DspMHYP%JE59Oc
+};F;U<hVI}f*_CE3{SlAGeIb#J|SS{FI*>irrfvwQbCtcI6}moDHair!NHN)W~z-bD;M!nkX)3x+1$4
+3CfD6Zw-K<;yOH?bz=~f(`9{>K31sa4#YrtTxf+IaX@X26;C&Bu40;Nx0r$jo#s$*-g~pOvsSF(^T7_
+B}^tvs=rM;Lp-w`#%b=3^&c~Jj<qZ!xX4=>V~ce}la*xpO4m2&%X4^H$pTsMyj5nOb8P;@n_^kv63r-
+apqj8uG~#tzkD2;cI(n#%cO?4)P)h>@6aWAK2ml*O_Ev(dFx~6~002%E001)p003}la4%nJZggdGZee
+UMa%FRGY;|;LZ*DJgWpi(Ac4cg7VlQ%Kadl~OWo>0{baO6ndF5AaZ`(Ey{_bCKRli7>ETkU>3<f-`E1
+IpqPy}m-eFy@9mQFDnic&}_iEH@3??}lK<(H&cTwuTq7?w%ibH{sm?o_C%gqqh$dWSNvR8q6-hFx=co
+#+}fUT{<zcv)A<z^CoXCp44dxMX9v=!HI3s$_zH#rz{HF@}uEO7hGtrIMB=9u$`bm1H7Ocx%73pbZmZ
+3-+P?`zPKuTw#gQbkfO!Y22QA$7IfPW=LEA_(xUUG<6J~Xbgq5&2&~wGQqTl_Ybw;88_a+(0h(%6QEC
+y1*BvhH)$Gb6otE3t7<lAjbQpSc|c+-Wk2?C(w~L-AUE-lwNV|ggP^|yf<n_MY1hIrSmYxpte=Dk*6z
+;E0h@5$1HDq4C`elGguRgc4Cm)gcbc{<DLvWMG>ymSw~+I(sl%zx=wE78)u_y>zXC0M!K{tWaE);~4L
+5pCJ0KBrFx4o>U<zi5gCRgaw8HhCKSu^8zWQS(j!heR_~iBsc390_=F(4!N>%EKR2f6<344iijVA3+r
+ovUt0KQXBPbi9A>JQjlr<xhAi9+&pv3ja*7F8woG<cOW-%;0>aL-fEu3<WGJ3GKK2kMv<Q7$-%L~waS
+w{s_A2tHFZ?Oz6VBL-O+dhYo&7;`~tA&3X;&(01$7{xU05yyQ+snLW^U%MXtTf%S}Exo>!Fx23o(@};
+8IzM3Y$(f@I<X8<wvCpFEf;t-&vWt@qtGH(?4Hxe(;K#F{f&&>kZg4v{aFu-2_D3kC!}pq2i|k)F9%W
+ASY{GaA?<#p`{gG8=$)*}>rl_`Z@W%m3oEE%|;nx_FB#Gf1s0QJ;z=Lr$P_i4;j_!JCDue|$P*w^dST
+-e-bT5{(g}@+&dv2ChV>}$i^$pDwB$h3iyrv#6p+qL_oB`qQ<h`O1V)cr`OGQSL0_NA2T{S6QvODyk7
+Kjv`CE8#{{W{&x*b=+c33-CoVPt&;_LhCcL^KQuZo(iAqN`q#7a&lE4j{60bT->b<hEu8x1iXQd2>+4
+?O&c<P4)_q5;OTy@ebm0Hhpsy!4D9)2n6)huG8|VIK3scA%{=I=Uv&28(dH7Z7z?AqzFEA;~{C*jgN2
+3(z2|Lob9DPi9oP}vL5T)z@3J5uXPi61T!Sh->zkYW(A7XmI5f>s(YdvR4A}bIeG-mWrlF!=3zYNGDq
+bhF<}#aWrtPa3~Vc8Kmk!*^DK4|y{{UPyF`Y93%Wg3;<!LOx&B_-=B5R0$j6XZ*m?&as0xkUD3jCEpD
+l5i?*I*N5qsT;Hj=E8hS7{44k01((Y%te@7DQe)mX~x`g_-y^~H+VLO$N)gCKZ2$_Cr!P}7rTl`Yb=g
+(7A##6^ZBB<A<V(U8zzX*PNziiz$_w)}?ae;~s-?E9y6p#O&8aG%-ii=eyGdaQC2ys+o@NT=)gJ><~u
+`=!(Odw*0-Pd4u#L4DEGzU@9QW^!VKu~&z}+co%j`5kOjJL28MzjLVVASZkmc)WM)xSzPp&IVmM^n1b
+of!zHl9SHujSobg41<cNB&m>*5WG-CR&;|K$8~I0h)&_63Q^v<AHElBh#`X4%Ot~H)HV`(F-7zlgEu)
+u`rTsY_PqrufS0eWw@qOv>6lD0{puq1%MIG)r6B;M~08mQ<1QY-O00;mZO7>RL>tC;k4gdgpEdT&700
+01RX>c!JX>N37a&BR4FLGsbZ)|mRX>V>Xa%FRGY<6XAX<{#OWpi(Ac4cxdaCx;_e~;TX68+zwf^~4HU
+3j%=f#Lw;RG{6Yxu8KCY|<8oy@ghmXq#ABQbZ~nH^_ItH$zgQWO<wWWuVPkB!|P9H*aPrt3zEiMr_+M
+GgVdSnX(UxYPVD6&VQ}+Y}-@^VU9JP3itHwKVCmiuKxb~>Zg}KzgUT9Dl;qbN@@K6m)fYROpBFxBk}c
+ZTNiRAvQ(Ryl~k)bO5V#dubQY%v-^~`i&~=!?ZszlS(PeF3-yOg%Jd*lS2j{t#d}$(jbHRbs^zt$KV`
+EL*EHUeDlajtwb~S)CFR;aX+)~U^(+7Fv6YcFO`Dlc`Ddz;nUVR6Caw43nN<nRV3{aOv%U1wf8R@4T+
+x%MsjAH72WKXkZ0T#`SH8ASf8>W#i>q2TDVab=btCJvk^L#(wNUdQOY_=}ObTe^JNgd~v`LG?uYPI22
+0|WNtfiUQ7T}m(<lPo+;Lo9NtuIy+`@e3g_v(xl0+E5!YPX^@rmFvaA&rBZ7qXZMd?4zX+_W4<9U%Qk
+|6u8`F*xW|TIMQGja-Qn^G4egq1qh%+#l`N*-UMR0lDVQ9)qm=v(W+U+ro69$KNv+;-1Id<C{RORj4k
+a;C42f5q-cQvFDL!C(SE<wn#XXlLQB!WksrW7i^2rze}rr0uNUYGEX2F8|;+Skos{h0r_UW67#Aoju&
+csQA(N1oSvBKLIdx5d%U2*`6qjZTy8}IS1OYv)<g8sve>S=Z!SKX^;Br|(`*2)hoRRGKTs?u9Nz1W2y
+glbzwM_U(tGLSDnXd6A3=4$s?{>Ve@&v5!4?}3cR#3hW!1<emo@w?%M2DfGsW#I^E2a()j=oq(d?^oJ
+ZoDu8BKCx#=~vBYtmeL#~s&%jlk5$gpdc@K#y$|7>aYnjUr%0QFMC?fB#&S(k^wdVAr)Ew#72)oVx6W
+fGP<%k5v$=WQRu+sG1ER(FIxT<Ew{EkAQeP@_dM)xIV$nl*i-ogW>c5OL6e`aMAz|@!;EV;>cz3==*T
+;7$x!e!Q}K2XyWO|Ba;oW5Rbn1lb1s$O+XzEn|L~0b^?p|1S!J>(4I&yz^G+G56zxn9HWl-MKo1q$OM
+Q)DvxeXgZvi7(Ozcv2~f?cAy3%dE_N;U#l?4{<k?3<R>37ya6qRJ!I2wCybgY~UUXV50|IpUFb-4U2>
+VuW9PTpoXNFn>hC~SKxYH{No=zesbXa`Oza!v}+!jyz_as;vwu98rD$s8@Fa<hf*!k<1uaoQNZ+?08+
+w<$>+4CQMeK99msdOaE_o@L+4tDdk!Fo`bTJxTi2LXe@^Kx2}T|2SFXY+MXu|AroeLlCzcSK_2oD-@L
++NS%{G{>RBg*t$i_tis^RR>V|homo`z+z>xk<j3qr}P<Z<Eo7?`0&*qFgl4c|LL6>0(}M2#pYF8<~sf
+itp;L)6Uq;ntj%OkK_%13U$SYcW*m$tgFJt7NuKbmiG!d~TFj?*I^)q>R6cUKdc-1U!*4k>eyUK1TII
+QRl(PU~wvLZSEVP)Wu6X)!zaP>MHF@>~6h+q6(IKs=&5Yis1%h$092yq;zJm(g!qBK8!7YXdL-6uSrJ
+1wW6Q(MSD%;?^^m!t#=oGZv>?QS1TBJoI)BGsXQiRSFE%#-ZCNxT1L3QqGBn(OmGGQvVMY>}PU@=xf%
+ns?xRFKj&TJSLTwWVz|JdIDnNsfdv1v7e{m@4VSEjo*x8fGZ%tcjk8x84S2g?PYZz77bDaB+b#v#00b
+VWJaZ<c&!0tG3Ad5`+sbaNjVL3g|dE;JEgj))cz%#EV`$TOI0?51?r`@cHV!ZQ2R#h8B!m`69juaq1q
+PQ+8lQsF<tm7RD|OMTQsnztp+cOzA}C%A~|(K;-B!e(1d7pi=TT&2H4D^(XKPS0pq%&V(R87mb|eFc^
+dC|8Q(wwFIL=mG>N&lOtrDt@;m6Z`pvCUS6K+d`1!4j(PHQKf5RK58CQ1Eo^f@w#h3WbEn3kk8Q^zDy
+C0!jsML5qC;})Kp-BJ+4rpGk%){(&*talxgsLBdPd?`Jr$8~H9sOYeMHy*4i%HJlRH1ndYzF87^gJsK
+g-Fd(|LeC1LJF^N&ve~VV)46{|!FJRo{7q7`5><h{pWhA>1SEn3nhG`_Dic0MM{9MDyOL833>H;`=vO
+FJGcfNgJ>*P_PoemMW`qIc+GHigQkKuet3L-<;y}pm#XNG%V+&O<y4(1=tpcB<9saSyX8r5SDe%G>GQ
+*$R56H@sV)xMe`|;zwp@p=>GV0PFQNhN3!Lo<v+`7Yc0}gBZ&x{am7b#$4{p+mXyE_shK`CDHivBJ&#
+|fWqguirl*s_G5v3P*lNoYB720y0RbnQ{|yL`VyE8A^1F$MI}IhrIS*-r5@5H0o0mfXyJ|8@^PH~)^F
+i@OF|!<$o|;<#w`N%CjT(GkCHNZ{{|Cp$a37r<&|)rzT`;+lOU07+9rt1Hyu5rWhM96uv02H9ooZ=oT
+-!9#v`y&`)!!nVbO}{6=)&Elf?c*A->0)X=&In{RYQNC`F#FD5{Yr9>I11`+0asCj^S2O?;lGWbR0=6
+17>v0K@k~9L5N@<BKwNUY0x-A$u{^}RDEHfOaz&T=e;ayR1&3bv5IFC^SfS~C1TP&^<~uHU}Jh@b5nn
+dv!j;}T|NVlFE(^JEJp{(+Qt?r)EJU%YljSBU?d&HRCNVh(>p0^Gzxc{j5<NxZN*XS=-tnXf`;Z19K?
+fEyS<^L=icUMn_df4J)H<R0_FAK+5@=`g@o8Zm3tDFmPe5tGb|&wkV$wmk(&MzwAm;$e9ckR6?J`)_+
+9e#BMINN0A*<;9cxpyhH@zzSX#0DWj19kcnw=u_p(GO=lzBv$B3_Z{HuOK6oPAfAv<X3xrs3LZdc3?E
+n$X8+;{g&)J}~y^WI0)3t@#Pfe@U-7<~e%wgtf^h1{B;pj-)E!40lv;^vA<4|ZoXiewJYo7-LkYvke0
+M8pq!gRzH+tSF2F#3XKH;b4IyET)bU-OD4I-etgk+V;=N$O8$sUl)^XI*`N*7Nctch>yGXy%EUCsI*u
+lP5^I`X!riqsT{k1m*e{&$~Q754xG9#^9JO;o9HE3xgNY69Esi-dET2c*sL@CTFeJ8R&Tl+S-Q}oOOW
+9F2^n%tFQ9pJ#-vCusfVkeQ%8!x?Dtx$UD>%2z>#UT2Uc=GJk`t}VqZOoc`ju=XQDx@c`jkn8WG4LJy
+O|J?!bG7Lzg4cNA9*YL~g_b6p3}Cs)l6&pDOc$5xg7^LX&j0J@VQy+lUQ>H`H}ojwodMo?;xepQ9nHI
+<P=mzQ-XYWZKiNL2-_jI&DbE;DX)Ou@vwfqp~<w&XG2CuT(CiJE|RNbNiP&F!vD;>9M0m!Vy!TQ^e|5
+@#IoI6i1+^rSg?e6ERsARaFZOxM<=os!+Sb!k85FIF2jEfd_0)J9VtP$5iqL)=(K=4ou0E5%Oy1TuI3
+2D)PQH>UVI_4L=x5)ihkla)+4|13p(274U$qxqZM{$<PckzICI!`IWsH_pYRg+NMBXm8SqhxpQpIi_H
+TNBNi%>k;@Oukx$INsoEVf1s&MzFC3_3+GKk_*x|z+#wMS8;GGYI`v2bdU|xN86*O>`x|+yMj`wXw@k
+yX`k;RoW2u0CbtK98~YN=vzc9{BVgd_@o-Zm01NjwggAud;BZ_aI~{^$+;ME&q!Ed@J#X}BoRrlq?*v
+Lsu}#~S%LWg?(`EhtykljJtn^jR|(X|rSal8cvQXViRKiBcl(Lzgf~Z=(hOmVn<dc;k4cfk8WTvX}Xn
+8f6EVF|$RUvG`w7$a39~5;<A<yHK~)`Ya35yY=9GIeTM44hr6V(QKyD;T<6-=bSZWT}BD{cOo0(?d+2
+9mq_<q(oiWu1;|ta?$aQ;Qw8P#+E_7LtpF%Fs<tn>Squ#{6|DE@vY956hBl~yv?lQa?DV19_WV3!Ig}
+4SRH#wx7AH2K!ooHW!(8;}=?V~0a$f@72{jj3lY#W;Zr8buu623Gm3Z2#;|6bNfc$qzKP=9OS`kPWq`
+xmNo`^SLHgVzZ6Nuwe1|#$3s49(|49_q2qS{?*BPgsqEfyLHup*BC=IPT8<V!?#mbO}U2!A5(*y4Bg_
+h|kW@k0%ul~ko5el)$fXBI72o?#E*V$-YhMgnWb)Ovk+xdTDBn<%Rem-VquFKbm_Dy>_oFTZ~J?YDoO
+b?AIh03#<ASV|Q{^VqpinKIbcqSUy&V|TI~Ma56=SZA^@=sfs<fDU@2HyT?z_@{3s!iQW>Jql>ZTuxu
+{V5fsjOG>vBiI4@HtYZs&#%&eV-d4ovU60G(6r7~oxUjdw6U;$O$jQssJ|{PwL+zf3tF*{kdb1KxtWU
+pQjZp~Eua#gmwj}sXd_C|U*3d2gq>gmMM#G;K_Vk%_s1IZkb=yUKaHebKoZtkuR0sn1VB<l#A~9@e{_
+G4EK#taEV#g4_bzD0ta(ukq5o+%UzFk+D6G?BZu2jmnB!3jaug`e3Wmpo>Gg4YAbF@E);1X_de?SHu)
+SzJwT{#g{ae}LCtNQ2)tA&3zkx3W1e$=&MQ9ofZ_O3;-Yj6nx{oGaX_sr#R?ueXt*Y-@cUbg3<2W$J|
+SxUQ8zj<^&Ci~OOzOwC4@Z%~P>$;wwz&{=7w%R(7RO#+k2UkJkyCPTU{NVc|eluWonhW<jm%4i!lgwC
+mcW17-mUnlNueST&0C$ZET@~8vWp~@;UPNe#sLH`>hmHN+ZYqqD7qgBXC~H*xO_CJ-Jp>B29CowsszB
+?ggy{v2mfN;qz@T6o)myAaeEJ*Z1^Mje>FsjD-#0V?{@~v-{|it{0|XQR000O88%p+8000000ssI200
+0009{>OVaA|NaUukZ1WpZv|Y%g_mX>4;ZUtei%X>?y-E^v7R08mQ<1QY-O00;mZO7>RwCX#E|1pojS4
+FCWm0001RX>c!JX>N37a&BR4FLiWjY;!MPYGHC=V{cz{Wq5QhaCya6+fw635PjEIbeRY2iXu{ZB$cfQ
+TP)fb+a-%76i_gh#@6i08r6&pIA5RBBiq>QC7Y)Rsx0;NoYS}I=}xC}zN)fD>B`c~=+&ZVNIywKbEB8
+^Nf?popph?4;CX2wt)%%*Ul>W1Zpg0cT3eY@qiH5-#jnq*DO5#|wW@;$RW;I7qI?Xf#lTLlkY&w0-=T
+lp<9}pyS&3OG=}A_(HmX`sC7-47GF>ZaNzcLedGTPR)hm-p`{>NjtA+~k#Oi=(_r8G^RZgn0z;6^x%V
+iBMS!HX=bR~ZytCy1f0YV{Q;mYjUU}dwaNm&<*Y-J2kO6(N1Ggi;N0{A6V5yPR%WQ7PASsR_NGK9*x3
+aEubh^RFkaV+)osps`|y~Yy4@<CW#Q4&yJ>*dUP-b9+EvKFyp@<JLpThqb_1UvVEDw&(ILYRg0*>zE^
+2_a_~J!^!j*m?mM>$L|>IA}pXZ=N}^91>xz&XfQi<vLp};h5lD(Oi{?ceg1db*7sgogR}Qc5nij=e6z
+9E)B>`W0cFc52dVJ<!r-txl~KFVZe6J`EA*9l$7u6^l7PcHRoUH+^SczQrW_%Tru=))j()j=;G|NA1B
+&)R+c5b*2%tgPKQ})4rsFpk>h<XkeUNel=bE-Q-QLr_go`nj`5Ss8kVs7T$e~6yN3G7m8<VlcYsLDP~
+Xm%HmxWcnA)1a38-JQx>>S?fbBR~ZNR{*Do^aWW0>AHNW4PqYi-)|^u|p-z!wos$LHyFm_!s$X_AaT#
+)D`;op6fpj!)NddNICA2^vW_N^fX<PT}Z={)|ThpQ67eNi?0(IPv1k$uN!}i%0$8)gT_dr!(vujZ+%N
+mvIWvbWBXRfr_IkgIz{R{{o-kSv-u>8{a#R(-C8yj}r=M5+-TfzZ!-KO|Fv3cp8Cz0N7DHI#0k7T}Go
+c04rn^eZ&V%FT&xFsl4zC)+cNq^~aN&Bz}L9(#3c<h#)+RU|D!Jj9Mx<)gOlOrB8$KGJGGoU1Ojm9;>
+z1(e*{dBIXP6-%sQ5h~4OqM`?mjA6_QuZtHbCjeH7|cnVX!^JENo4kvbu9SHV~q85ciO$Ql)3V&Zsqa
+7d(qHqYTsfW$`%7NGEbUaTjIo)j&)w;A>fkMM=1s+c1oE|D&%}P;y?&6g6PCde7(6>xQ5V-1doxCvt3
+duB<k7T!V)ae1>j~#qqQPZWwS*t~p6%Kl>WSKvpy-C|;T5ft<2DXu3Zdiw&M5%Ienp~WM>G+JGfVUe_
+q^$q$-8<;nrn?V*eBA4~)!X}TE8QN?wLbRgcqYv8{dU8F@H-4pyQ^5~zizy%+}0!LF~Hw+l<6h+%da5
+qE&iJ$tugH`_k(cVRs8pL-wri5@Y^J8^1UmK09S*m0=|A8w(;*SMZIr^zspR|Rl?p<VB`WuOXEtat+F
+m(r-$W*tAcfQ1&GcKinh><s&QxVaAE6GHLc@4$HZ{C(e=Y7R9#-&Aa5NSV4XJWcCT^{_HlUVh+I;ghK
+pCL9AYl8#qRn+LDm8dcPZ9wyM^Q`8GaMFXqx);<V3!RWsTB>`~=uXdsN@i_*!b%$DqdXb2mn}LpXo8z
+ua%a@ky%+<mmF%%3YE!Cid-F`vA4gA=@b9#=vACs4+tE7=mDApKS@(-yXLwDO`Ec-QAlCJE*>W`TvZ!
+d;1cyg>#~j8(MiTDKJT3W(b17E${`+1Cz*5vs4?INtw4}pL~rPk6WU&7)R01Wd0*TT;MD_%kpx)XW2r
+#?`<`L6eA2~M!<>#!{Rymv&*U@e?lVNaEW<in`Gb3;h3<jv$j2>KbGH3@OH7o%VB#tY$R=Q{q9=BrUs
+pS-Zt_jZ40oiOn#mV#cp9Sz}&pKUGDBWy;l`}8nZqW@Z%sI+w%7G=U?yJ#?kH3PZ<ASntcnlk9^5w-O
+#krb<F*XUHuZcJ#{;=>urw4`v*`<0|XQR000O88%p+8N_aUx)&T$j_X7X`8vp<RaA|NaUukZ1WpZv|Y
+%g_mX>4;ZUu<t@E^v8mlEF^nFc60Ceu`1{l2oZB4qPhjN(&T(go*@Ou4&p#Q)?YNvK>%)`W@SGXz2P9
++wuJK%|DZ6+3jGR?!+g8)NLzN%h(+rghC7Z@GIP-fxWD)g@ZQWjtJX$%iq!Lw8flrUTmR5chn7MOeo>
+1Q7|u{BPG}&>}x5pp&iK})anG9#0+%086;(N$J&KQ35K`mo?<4JWf=)~y*6%QJs1LXr=IpO{`##>C23
+g4*pIUkK;k>fz`tECN9--=!S#cqmpgPHhzjo3H-8=ot%1kQ{WE)8zuY{(uHh$KT{Fg_32!kvg5?P{9*
+Y$NT3K=y;&lm)chz&&FlP5y%Yel~Ov)wfMB^C(Ou*tvI=&~xB$Zo~hY~v5uE09Vwx~^OSJ8~c;_t_FE
+MWNyHd<li^vj?di~=vg2`L{rg50R|B~p+JKJnC;T-6<htU-F_&E&;JJ4@IN4p7;_P~Y`n=7Hn1krNRP
+8(;MqtZ#5W3n?#WCZH9G_}fg*Y#{X)Y=w1{`Vz)BAT?(iB_5mbdenn#{y*IQhK5?7nN^e_N^s-^1ik2
+aB^0Gqwd7S57^|tx{+p_@N#oXAGq1gvy{wz&$rEm<`mbhY<1Q=MKTt~p1QY-O00;mZO7>O*azetF0ss
+Jk1^@sa0001RX>c!JX>N37a&BR4FLiWjY;!MRaByU4a&s<ld7V^EZ`&{oz3W#H?xn_38(R+pf~CMNJN
+35iR0IZN)3#RI5=6O4F8l4H{E_CP>$>G)$KoUT9-kORk$R{#Lv9L!twYP;Yl3I$3gf5%w6@TWp*2O{5
+O@P@h6qQ#cO5)q(-Q+aQn_g@dcBdb(zqcg@13L0gVlDdutBCoNl60Tc{$Ri11T?g9c`WVFPNUOlFXIE
+qQ|D$FW`yD>aH3xdt%REk$Iu8D}bb9Kg2=djFlM4ilrw9@^MZkZ9-mSS5c9uNVqHATH`zzp5J)Ss&u9
+WzaNTCpYJt$H693=BpU^qPi=!<IJbjT$dFC4DWwW3r8>DR$GoOYzFx~=hb=9Ey^G=IE<BeC<Tr^r!;{
+y6i!c@JeQn(88#YYwR3~dOH=K<q)0MiqsJ8%TuoYrU*cj8m3Lacfr(ImZ4<`7PezmsIISw=W-rK-574
+i$v<uC)uO}RI25400`I2q95fm+g@awyQ_n-mUxt)^!@B$G;plaMme9Pr^a9@{(;EPPc*y`#*l>vuPee
+hNgAQH-(qjW~o#>>EG!+l0t0L}pX#(F-D)yO=dRRKA4Gjs7&cyFNQ!%n4$3Jm?uhJ1Zs*N}U7a6AS(S
+Oof6tJDH6NE1_AS+v+a5Q1fjY9jcvDIrHo*u)j}SsjI{4C^Y9ibMT&{3SAK{Bg=v~$_<Sf?a2aUBKT5
+!Z+V%fmG*VNktw#R-CGQkPc^fws`TUM+uOTA)3a=Rc`?JSf0RG#e;4ubAjnYW9T%V#OX@K5)iA#GD6e
+2-#~xp(v$o%#@sAvY!0o43D2%n&hnv;u-OWD0J+%qk8}lSv98&UmSbAG(n&j9LBRpZ*BK~@^I+Kmz13
+X3n6|L28P)h>@6aWAK2ml*O_EzL$jcert003ME0012T003}la4%nJZggdGZeeUMb#!TLb1!3WZE#_9E
+^v8WRojl+HV}Q+R}8cdmH|iJW}60eu?14>rf^}{i**1u2m&oFjU-|zQY9(7LYjZ?kd%ChUrdUe%Q<sq
+7{~F}c4Y~+W)=!wmZ%MIIV@3Hc<ODfBpm2~D`|kq0$RarsdN(++*r-`opncP9LG__n^tKHLRA%))woq
+=T$$cPQI;_wvJCFwOI)GNT4w94<3&7!*w{kweb&BK#%*`Y^}}YjjlV`w<eZ`=tHFCpwk!WF$uh|r%(5
+w6E3kx`nam24OySM%uvbbfBA}nueOS2PkWprg0Js6E{$UIF`19>gZpSOBG(smkgGF?*(P%p@;gjyrf5
+U%sY%MIkt4FPsKKpN(F~PFbs)3fbX?8$aD4lj%5Xiffm=j|j%Wd}bdGqwR-fmaHYzTIJ;Ne}8mbk?Ns
+1hD5mo}u}%HjT>gBN#eVt@?N;Qc|NA<z~|C4@RsWg5Zdt2qOxt!>R>KCif~yM3CgX5RKKn-h|G+X*rM
+_3qsbX&~>66Gx`s-QB*wy}b+mp9IUXAZc*}WhZkd5~nS4(>k?v2v(hxmQylx{$csIlbCn#mzUlwh||=
+n69pg<Xgg9*50wITWc`3<p&2*iW3vrafL)CNG*Emtq64KNXL4d;kHjw{GA_B|UOCKKohU=<+hps_$IW
+WB*~QZ{FJ(a*R3=p|O3(hx?Kau-!)Cqu4F84QXgNLGae=O4!MZe-*`zF{sj=?s=^CBoLK$>tL1e<<!i
+jQVXJF=Ja09y!&+Fy-&jncCAgB`Z8uM2;bV8zLdoH-`XF!cgu#JTyIuf8zaGWa`6FoOZ>2*PQIB+R9j
+yVtXf`kxQiGn)vG#w~%$c=nEl52KAcp1UITp3@p;mPnJex$>r{~@d|_E>8Yu%=3D!U#u_>NWkq_UeFF
+_E*+P8GmzezhCL(H`s9@JPkt^x=dZ5u}$LXWsi<vs6THgm;9Ag=qIVI5yD6dI&N4WSmBZ&3!0>^EgH0
+}V3vg%4O(}>_elP7qLvfS)J>DY42ww$p|>akO)ATC-xawxC2<#MQ8!$Y(Vo!^qwXSCZepiG<sod+_HW
+-WUT7v$h?4t(>gNg#&M%XY_T=l!%wg)^{<65f7?#<AX_HJ=%Re3-x1T1{X~0k-)2D|5=nfx{vYxy(>=
+i@ylpqZN8V(1Xfl<VbF5cv-aF55uQ$Qm57Pnqn?o~LNifb(0lIe<SZ!rGuxj%9mut($J`;jvvN}N6+5
+9YpsxK=W3qv3&}0E8|bGj@8^);KvOG5L(AZgM1-SK$60;#~09dnC=d7s!8<mc;QtP)h>@6aWAK2ml*O
+_ExsEiLrAA0003M001cf003}la4%nJZggdGZeeUMb#!TLb1!3WZE#_9X<}(?X>@sCbYW+6E^v9ZSZ#0
+HHW2>qUvX1DOhO$cPTRCK;11g`3<ZX@*ouAe43&{+n~fw2B4x)2^51ty>V>qOw{^=0N2bV!ch5a{JUR
+%1UwO%Era7=OgRQKuVJq|+KK=3uUR}I~pJh=oEv`f^^bS6=m5N6}5R68msAR37=A&gT3(&htlq+aQe-
+lcN;bWzRELlE=&rOx{k)2tIDo!@M%w!!`EWKtcTo`La?pB8*z`svBy_V%)yjBP@Hbc0*eMnoYa-Pt_c
+Ca!loRJmzCQ@fal$zI7&G9oSS-}rSH|~Z7OOq;RdMWDy5u(v3k?JO4b-GT_0GOfwF&QIr9@aq^zlf6X
+?`-(QfdE&HGQNZsIT7VjCR!$?%%l$8(WxbBj`oZpj^jlHr|&`OdTOjWfsbXrgGO;^D$o-2n!{4mN`u}
+?D4XI6!D2HPooVV4f*}4XMHv>X3K3`Q88M$;ETYc3#Pc;I7pJtfF@fSa$1jU%ON&m|=)6ZpY(~w($g;
+Y$6YU!MGmPWlSBaJsqNIN;)eXxH3L=^X@v4?hrNXFRNVc_><D?Mz2@Og#2J=i%(J-CBxWbw9e#r9orz
+lenTMlcsLB;1=wo@R9R9ui=^9(7)uoABw703arwb}zRITD~*$Ura#oCsH_<t?i-b((rPgS+t?U8A3by
+N6@F2h`qD+~7aC5gA%>wKFzgq-%5#QidVNfn7gi4@Sv?>op}{F0OfJSlTEpizJBQgGLH>aK&LIWk%Ae
+c_BCZ)*yrerl7&(Oq+sZT4aE(WgHDmsYnP-_88qYC@>y-2*K@La(frV#2eG04L1d2p7SzntxAFjri;j
+1Nc<TEAh@qXC-R<FhV={c#B;?5p`BPXi~^=~37N>s?{zEN@Q3e?DTSUEZtB=qU3Row7OdRmqHJ!Snkv
+UOuo+`QZs|!BuezsZNlKWRZ&)8|EvSfw0n*lGm9rjZGm3U=)W!MaRp7GFznPr5lg?qg=ExY-O^Nb{LM
+ja&3aFjZyig97kvv77-=y4Bc96>s2o-`Aodk%(W!lt=tJoYOuiw3+6w+Kh!!EU!O`efnQ&}n$eC<g7W
+Y1K)#&vtGb)}|fXWQ*IwueG2>(yDtH)j>E6n&hYqhV(!_ayBpIeY4vc51ijcj@BL1`LIJ8;Hxdmskyg
+o41$A<*VRs>WSP+A!Zd(6?#!S58y?wg#OVWM^D0-JO;q?M}%{Jk8mE7%6TW1ULX$4Go|uo@{m*>5(gZ
+U(eowoX7W@?O!oEguOoA`+^o3nO3pJ1&9@en*q(LdX;-a-XnI&IkMs)ns0`C$zE_{d`?^~k+u@OV8yz
+Y7Pp;+srov`7VR<gMJadryr)l52&U>0|Gj?Qr+EG|a4Fg1PS8K!Xvcwjc1{CMi#wf1CP6DdQshgZH><
+l^&D<ba*9ByP@5sF`6FdZ~<H6$R*G81S+N@`G3T6$bwRYcgSaihgw^icFIZmJBkGwfj_$4BxY#zu$K?
+@Vx`U?;f}Z#(w(fbV+YLF3*Xpy!#IiFRrP?_qL4HT8t;g!%cRZ4$eIN!NV%>S>pT`)i{kDe2r7>|F&f
+E;*-uiD_ehuM!dnl25Vkd++0~M}Du5Zu+2rtr^X8gy6rQ9b9h0KDoQz`2b^Rs*l`(La#tAgIj;cyW4i
+&UC?qw6se}7OB~NEGY|S~FIf*~oi~*XcnFGJiAPX|(utSJHg)kn`$t<Ruz$w$4G*i{4KO!TN*&Iyd+Z
+2P6;H)d;CoRTkT2~U^(D5VpJJV5#Xta~;L@?zx3jp7>7?nF5xjgEP^%rhya>j9cyNHsj^Q)T>$cvCJg
+3u-DTO_{>E>H&K{hq~_|u2jHK3z++S<HxyzHrmoorysN(~#9i=o%*oF5OSd|0+}ZtSH5a+%^4#&!Wcq
+Gy5)TerRKA?ZG}r{Hh4!O^h6_KdLFIOKrF|J$t*G46zA3w|f2=^#C)+WS?|(XUtj`a*G-(^Rqjy!IjK
+K)t`*wnf_YV0Lf0BU<}P)~*~>G<(Y7+U=*3_7@v-rAJ&M`LKpXrd3U=ps$Pl!olC3;qD0X4@T#gA^*)
+GS2O?X_+UEeWkw%|uX-0}&W}d!gyFzEb_6}_g!^OGp%V^oGw1pLHUEBt_kN)B?R^H}Pjc%)yRD^uBhu
+SF`Ug-;0|XQR000O88%p+8Y!f}Mm;e9(@&Et;9{>OVaA|NaUukZ1WpZv|Y%g_mX>4;ZWMOn=bZKp6E^
+v8Wj=>IsFc3uV`xTR(AklsRi5&e6Qem}?(2}xB_<PGrJh-RH?Aw_&##~dz>N#Q#GgcR6fh6>v`zORR1
+}BWdNSN4?F@`8ibIPKd-6f)d@8xQ6TNjpYEPn39yI5`Pa)S`%gegVwhc2M18s`?bl*WcoMiX%P1>0R%
+b*oy5M|hV{{|Ie43N*VWg)_@5$0N1<-qHt9O9KQH0000802@m7R?xP^j!Xpr04ojv03rYY0B~t=FJEb
+HbY*gGVQepTbZKmJFJxtKa%E#-bZKvHE^v9RSKDqIHxPZ_uNZ6|Di!h?=%Y{tFk-hgkj6pcA}xYoLG6
+wtHWaxfxpD+U|K1sLFO)15El|HmBIkN$&J3OBd3FO^Q@0AiZ-fWAZ4_=%dk5YaCH0y<0kv3?1PZr@Ct
+)=mI}l6LdZ@9nSP3tUc14zx!HjGe>p_|Ingsiwy<WDmW($7bu<h>dM(=0v(6AAqX7GsL{QU!c?i-xJZ
+<>y?sMg4)D0ir9V~a*qUj=(8c4!^R^wt_-9gYh9aane9WeLJT)mlq=_J;tk;N8RH-5fkR%Dxf4+7Kqv
+ffidVvh4Qm{fE0ZH;?xZ@5*04{#??ppYDH$1?0)i90-7{Qo=cSFPqyDoli0UN%uLOXFz`q36er-tfW+
+gD&59Bbx_S27qb7(Xi6u01)qB8f4q7PZzH^LuRX49aFNxxg4Dt!_}HRzVvX~N<mb-H44k)LW<i1?#I>
+>ed4Rl^=q^`MAww`{g?L1Lf!fSLYCp=%hYEg<1^m**KI$YQ?0mSN0wu&>BPene3<6_sd~(rUo<-}tH2
+<9ypLD3qhU8~Mrn4@=coKh2gGp56UOLw<Ly0G&?%85b$3Uoh2(3d9;2Nx?P--7Ks}4j#3r`zK9rq-af
+{oBM<xetTR@8);m`MoNSJuJG*uafJuCux5Sy-&mzYS-TJdlV=hn6rYQUd4G69dHwT0IIbf%t!dHw)b>
+weysA*_kP07?YC*c?EZIBAM1g0{g&_Ak|Nt!iA|u&OE12ZbYkmexYVF5KTi9X7OlS4vQ_Vm01dPKGUp
+k*^6Cy+>z(S7D=>;?Oy5JCFvZ;5diGViFG9Z_mO>;X1CD^g)KHpRAJPgurl7SDQIevvv(^LzO`7clvr
+P)bO42jl5(DU?jq-DbNqs;p`N9EGb91{O*+rXu3BA1Gt%#iEKO=aiN{V$b&BV};Al2S1Y+vhZe=}f_H
+nQu*(B1r!O{{@Cr}pfabsFl(>d|CGTcrSoFnj1S6IA2^hHRnr9O6{M=ys(`&XzyOD}gL=a0iAtv!)Sv
+ubfvs?jMK?$;X458i>bp($}DX&3XN=|J&s&5p*A)Z-ZWAfzKj@`l#ZjFG|Gcf<A^+>qfl!S1<!G`)ai
+@h?u?o52{nFJ3m#aR0_^w>0>!cpd;>b;FOR+ZL{_DB-J4bMc&-IE4AfdpqS!+fbp-w9eR>gXlf~1l?|
+z6hCFdPQ9h~MNEfk6HuaB?U3INg27+43PQ!%`{<Q~`0YfqP1l5};{JhJx~g>nDasHUYj(0GMZ|hZZi=
+1)SvTHpslDu$ad_GwMPnII-fjVom^x!F6oFpvLkm#hVuib!^qH37a?!U*x+h~W{9KxxJcp+6dePl<df
+h1O=6XqY^h#R5=OOb+q#aH5{Q3M_>G1q~IONmWsB*NYJ4dslL*7>Ke29AyH9=irOmm4Fv6H+3D(bj37
+Wt7PwJN9C<$rX=`wQ}qlBf&O{4AOb(9r7BygOan@Vk-NpN}D33_fB1Ndh;}7%Dxlt3-%>Js<v+>9o~P
+Z2w`}eip>mVAh;4<q&2Kks}VAo)rUp{}H!wy#Hg+fng`n-i|EbpqI>?mO79Kw(-7k^Xu!i^qY2BP>k2
+jz7f|{p6g)BT|XaQg7xL7Dful9dGV)_dJKk#hwvpWry_ox?1XA@nhHQTnkBMKrlVF*-=C@237LYS^fc
+&AdtQfm8YW0GQBS&=ek7Zxe_eF-7-yCZrq2J5F}&7}-$DH4<-=@o;Tc2^vFfYB9je6-)9i0hO9KQH00
+00802@m7Rwj=1UF`z^0EP?z04V?f0B~t=FJEbHbY*gGVQepTbZKmJFJx(QWn*+-b#iQ9Xk~10WpZ;aa
+Cx;>O^>8D5WV-Wuox);4M92VsU=n$ZM4!zQF2JKm(>cnp%|P2o7kp1t5*N_R2eXa?w(bYgbQ|2pU+j#
+)LM1Se(8mLW}@qrw(OVQ3MF~F+tu{37kyR;X+fhb>r@4;$tt0tw8fy?+3E*fHsT0RvQ{bk(S811w{AJ
+gK9+_SuQ+Xme3{+-gzH<XgB7TWam}pRbK4YFQ7*R(j-}Vc<!-mDpk_<@1vf<x{hK%67n4v!4H{$#@uI
+a4E0Vl}Ju_A(?7O%0-tQPbQ53yb@(37+FY3%H++s>h!=D36JCK%)5bz95oaquMJMvak+(Mi%_P|8Vgm
+j{m*+yU`X7Y9zo}FpvHFv48M;5VnZ1h}f{!HHte*E;=iO8oB(pbK(F%#i2C1X+B5RW;F&X>pY<=y!bW
+wp{Bx3SmU)Itsk|1=a11mRYxR9z=*Au8`GaVu!Ql5Nm+_cLBc_gbR9%A?_?*{{m+0A{@JK~~!ooXMQ5
+fyI~`L#^;y^3!M}{~+&m&Sp4_JEgxYk*`vYLcKh~2D#%SnPYet_q*VM{6ybG*&j;C*c&8MSK2|#(B^v
+Zuz3oogyn}8VxtCK0*&A@S$>B0p-(Se+77+t0Sg4ql5{z3L^_`kkLS4gZ+d`9DY=m%(n&$AG{&OU-Z4
+|k!h~nS{Dhf*#zFg8Nl2Y`Aq+B6acThCqU2?R#BornMWqiM+hupFP{f~XGqlCwSxx{q#etVEc%*2LyX
++b4EOBre4A4RBtjBe-?Z?1Lh+pc?3XFvc3Gj$rt7OWGG0tq@;t?*WQE-gO2ivTt--RZXldz2%Y%w>+X
+0YjbU>}rbAK(A#tdJ#6z$8FLlvxWb673m=VZ5rCXNWAE-#ZwuQhH!dHIgSR75bRyRckQ4l9d^W+Sykd
+d*?c3!m<vyG#h6#T<pY=oaM$=blu=uZK{9~U!+W-4}B5_$m>ZBZN;Rbk4M-zH~`2gt&BZM49+d?(Gua
+Rl>BzI!rYgZ+~$vG;gY7h(NXz=$Yv|0sXMNlV5Q{`0sG<=)in{W&cH$GkfL(MR9S#67Ig!JhP$qqb7$
+_Jr)p4m7zCn6eKOg;3PmHzh7?OKF}&$<@K*gsNlqsf_F90^9p51~+nJdW3YjS&)_c504{;mK=St|fY`
+Un|>hxgrJj{T83eqbrpKtD0*GkuioZsMym07ahuCAVum;#BXhjhaa?&6<W5dIRz;{Oui7O$@PuOWArj
+&9&N-wpp&0pSeL&`%e`N>;cZwtTGA3qpqT!u3E+4(sUb6)ySNySYUF6G*}TR!o6%_xtm&5&IiZO9KQH
+0000802@m7RxA2Smkt8}07eJ^03QGV0B~t=FJEbHbY*gGVQepTbZKmJFJ)(EUu<b^Yc6nkomEY5+b|5
+h`&SU|p*HFmYkOLO4H$+F7*KRT+g(~@f?~^w8bvZBIa&JaN6H_GhooDZLo7?=6Z!Z^%T;Zx2je2yuB_
+-+ZtJ4TnicqME%h9_?HlQQ20v;qjpiz9O=?-^OlmJI?&Zo9oQ_@Z<D?g?=EaiFh0CCE!ZO-B<lK0vT)
+vjpH(Uw5?lF=G@MjyXF&Nh95;1mGSvcLjGi}&hnHg7EltvL_Tq(xj6FddOSj^{4Nxj6V{DM&!4D$_da
+dy<CPYg|_Q52P;0ydawz7mP$o3OY7=WPm;&-A=%0pmD4zZ$(3m=K3sG=!D#yyTw4nyW^DH+YaE=!8Il
+urio!f!DR#V&(zDF9bMpcFoLr=^F|PxPy8*XI41V*h08dhenkM@j%t+f~@iYaBDn<xDilrt&OLO(9&p
+Ga3x<lpP48)ok$N01m{r7suEUc56aACk&p7S!Z%jqBgd$c`03Y|$s?b<e3*R9r)O~n@dW>Reo{Dtct|
+tu$b6+L2bk?O_=FqNF~>K?ETJ-X#APLw2%EJv&!X@<ayMKpN#b}}PM3`n8&w!3bfn~IFb?<>J<59pQV
+*DIfctm|WxD&Gjnv8DmW{7W2TxfI9@0@dNpG0$;P-0LpYGS^)@X5@?q1<<qx-IfCRq|xAc0=~;vU0CD
+T&`WL2wEfw6GiLumluS9tEfe+!UzXOK^qI+)CrxyUtS}r6Qwzuh09ez1>plR8p6Lbfhu=d4GM!?!P}=
+XB3PcPody=k+yi+Oxj`bf5>By%MN5K-1|`W!rR5%J0_*kr_^sKXmso@=*yJ0q<uraPtJiO_{n8}v)Iq
+3Q6=^;n6kv?c68AuocNAo9u(3R2(d2$)-b$>f=EY0YGF#)NTuMpalRK56}gfYH?V?Ob{xy&-l3%2Rrq
+KG-OvP{MxB<A4fAAA%>f|C=_hoVjA$FR1xe%3^iR^j%J9V*x5)^6uxWvXa(mWz#XB(mmB9PP3xV_^a-
+*?wXsVFa+Xl+3^W@+-`2$c(0|XQR000O88%p+8#v9NV4gvrGkput$9{>OVaA|NaUukZ1WpZv|Y%g_mX
+>4;ZWo~0{WNB_^E^v8`l;3OHFc8Pz{Z}07i?t=DNgxzM_RuaJgRBi*_vDx$+j1i6NJf$g`R{j<9XDYy
+Oi%XR=YD;4wm8&ETgX+xa}$X6tx`Fw`1wuuPv&HTQmX^lQ!V5UI`c{xJA(J7#+cyo_1Ev%n-XtHvXkX
+z1jgz#g#{!5;0fD;5z^Z~@6Qh-AdM}@4}^|x`6u%Zn9K)>?c=hC#u*>xRu^0~#LcE1G@A|*pA~1*;fl
+zuF1WU08U)Lir`PX4Uw&-gmMDwnQLYZPsCcL|f*DZXBwnN&^Ce8in`4xIrGy4SQ1B91W7QUGV4bjFmc
+`&jrZE2IbdG%+gpj8_&p&{*UgvR_Rw|7qY!0l#d)J!hwmLz<Ek1zVbKtVAANV}atg14Gc@S?GBieCWY
+hH4UEzWR=oZ%EI@xejWT!s{sg!Repm7HNSKA9_?sl%wR0YZXb8Si#Sl;CEHjAh!Iqp<rBBj_jKj^?(}
+(t}BbwHyI)8g-(avr`{*2P<w3<X#OoU@5f0QI9x~kf;nZu8s9_J)O_`Hl53v+h*!Y*f1j-NoW#J)2nt
+JncT+{T<-;B<c<K71zg;3WH{6LK6KzegP5kWxBx@=70ry{{)_ZM!hlp3UX<ilRIlx#Bcq*GO>IJ&-1i
+a@W^y429g_97lsAAr!GA0V%8LIGhu|7B?5qd6Z-)kd0Z>Z=1QY-O00;mZO7>PfWM%2m1ONc|3jhEj00
+01RX>c!JX>N37a&BR4FLiWjY;!MVZgg^aaBpdDbaO6nd7W0@Z`(Eye%D`d&>ms~iu}}v2Izpa3)TW%8
+Z0T&Aq!Mmq9S$@DUg&MBgp^0?@0Mq>~-A?1XifK@4mbH?r7EZ#(Gj-T5nA25)}{3=E*gKSMBD%l}l=C
+I`XSt=?5B*KPu-l`qX=6v}luP(yKl%lm;};^0HNVCzM{h@bfV{j^^^xbiMFv+uIM9zkIsAPLkr{%f-9
+TH|K9ZUKE$-zg=9@8@fvfpA;x*79MMUege~cA*}-=fY%1WzZv`dBR2Vw7fMIx`$W}iK4$@{5N&IgvMS
+`GmzrH1SUsg_Mrke|W%?Y={*ij1pXT3;(vx0T@1~pM+E@xl#D!ZoDetYRhSE<CFtcN9BHVqFB$ceGSX
+$Bd(oTeZaA%vI-Ej-=oVWM)Aa-fAoYLvf2<u~(X_~&1+FQ}m2oT628kx2tezoe6fp>Wl9Nq)ZSXIJe#
+Vw{rIQ&)QBq|G-9Tx&IrDc`VTUm<1NisDl=LYElmaxjP+JaoJ&TrmlEW{iNX)@}D)~mjibhYvg(#^;>
+QdtU$5+$dHGodT$jPn5x=&<QPXTh){@Kf4(kd;+NU|=1&p{|i8(_N8Qodn1ZYkH7A((B9u++*4|hHD}
+hN_dGN%AtQs$M|U5LREmFPL_?(%5|ZLOJOzhh+$zFkSb***yB8K^@hWv^49b=p!cmPWdLYo+h??tq|I
+`yW$a8H(;e)~CJ~x3_R$3h#GrDp7B+<D=j*12Z!Wg;m9#crTF7v+)$Q&1@0TAge?5yObTpS?E$D^$OI
+9>rF=>wNN~?Omj+xU9mu9IzGTnmJLba@PLG|DVD`}iTZWwQgKlP6BRVxLQ;-sX;``(?+W)I3Y!<?7Lt
+Y7tF2A^4!(d^Z$*RP{utA#?@0J<AkJ&uK@K_kz06|!L0{h-|5g;CYmT5IMldb2VEl}I$EJqi)o`G!tT
+!-6{r@{*80QrW??gAT3d>cxh)t4+i>xK^SRI_%3Zv(s^qA-`fSoi8|QDOl$P5-gZm0lY~VU`+I8fNxm
+GhHCY|wKane2{Q&H7+#GD#BtcugwzXVjqdQAuVpb;TG&+)c^iPgq4YZR*`>5ylO$X8DTVc(TW=xMNBE
+dH$#DUOxejl#1N><mv7cy6gck*<-hH{t|G?VPqLY|(#lvmz3cI%)yg-N65=YB+^1xb=BOqs5E9+SMVZ
+p@a`383o!^Ux7mPK60Th_Q2x)MU1;9vyL(V9uhFnkB3(`oMdR{6>3;$$B?3xWkWpn*k*c?5K?R#R@um
+PEinwl84L_HGY;$r-Tg!F91UjpopPv8@{T#LGWlHmYnUYpCg-*T`_sZLgzyDP(jU1!+w74vrBzFyN)S
+jwK&);kd~Go#}VI9GKLqm50HP5y*~O9fUkI+b1zSJ1`iBd|jNi&_6pFwE6Y4`%2q6A4M*$JaO3hlxnQ
+BbjKjy-5hoL^!;5C*41SCOmSDGKeS**r~kcUc9%<Bn47(VDzNsj310MmBj&Bd=9m&bVs#$d4<Y(!6Uw
+GMYPOyCZG>2}|271`J8(EEuLC7<;2j<OOaJQu7v)Zjn9Y3rv4o4iG(%hI6OXJA-kDCKOSo4YenGdmZ<
+GBX$=^^*0|XQR000O88%p+8l?9u(>jwY;0u%rMApigXaA|NaUukZ1WpZv|Y%g_mX>4;ZW@&6?b9r-gW
+o<5Sd6iggkJ~m9{_bDFb3a6GwaRAOw7ms<xHe6C!4=tJvq1s`fj~)=&0U&QNou_=?#JIVq~83pTht$H
+OPU!D=jC~ZlAFd@&uYElzFf~_yfkk7mo?lE4=mS}+4NU#=VrAv8&(?a#e-L}VBMqc&W3Bg5;jVCv1w|
+lL@)D>Z$xz?=z`nb8$9Xcc8%1lUg{^kOWDs-L*(sM%6=7ESniEY*>BSMlzq_B=#-V*`B~I&WRvCh0-o
+B;3(ZUEcfB<$yoEjIO_TH53!7I$aopK*>GN7Xh-zv@Vi#6(m9<_fmz8FNX!N#L!sis6yp`4CIveTAUZ
+XY^an7CmQ_N<wO4O`ei}Eg7F<a~`p}&{#&o0>6zgS_6x|}h5zG81{wiT>0`k7~IelHk@(>vx(G{XE^F
+j3c{^b!x@6Eih#O2-;&O5t2eBD%A-70;Anx2^MxJJ)Um9%5@)0e%Eqm9(&B>@Eu`vZj1zjpClR!In!l
+-%9=M#he+-v>~S)_ueK3E6ouc0Uzdz=stZA`_^i9V_WQ=ZeU?C)>tMTFI)(~B0g`dxR<7NY{}jkEyBI
++nktBd*guwo#JC9D?CmM>fC}j>juLVIuR_cq9ZVreTPr;;V7u6{vb9!d&szAG?I}j{-R6=7Md5tkbTt
+3I5vAk`G0~NxYDUbMH743*QX^;;{vdlnL{O3%Vb$)0G1RtzgKJ?$P<QmrTw58om40nn&(8kCYQ<OCkv
+7Wx*uN0mu5uCFX(4y<Ka>^^rD#06djHy5V^3S`^81D>CyoTVhvTXU+@6qt*0J4A4Ke2>)o^exrR$IR)
+qh7nkG1>KNMnYVY|sqFf$G-4pUHNo?o-sewitS@?~8zkv)R87Adb43SGT-G;pBeP<OFqNJE!dHukW_p
+uG}R-TIlWp%RZ0zMui@~zr_8_=kx368E0hjOvyVmX>p6@WQ_sZP<f$_IK!$zglYIix57?iFWtcN2)>S
+$R&XyW<^&2|s2xKE(tV*Ft}D_kL}&=WCtX$2-NlY2$P7{Fc8{oWz>j0nlYZ5$7I%v31jZB;GIV;d+jB
+s64E_PhVAUEGY|ttJ;PC5v!MKOsE;>ewD(mAE0RkOyf?ATHH~{!)-(|>iI^LCbd9pS}5mXciVvs7(m8
+Zm9Ta(y4LptW;?LPhS&I0Ad>M1t5R(Vt@@mMmJLp_%GQ77-DP*tZnJgA|n)PZD_$!gWQb+X^w*iG$rx
+=eZ*#7diF0SKOb#cq1~v|JJfT@!r<2q2h5$#dwWK!-+2$f-^+<jh#PB4;}6087tuE5IM6$O8>yx8WB{
+2dyPBL*(Y=AwefE7LlWuBT*;k*~Lq8w6h9(`wM`HvhGIQju+17J<#V!bEy3M=yncbW86}eHxh*#$o-9
+yK82A`V6;Kr0(<Q<$N0($u_3~sHdGFc7yN<HhP9e-9+LqC5hV1O$O2d#t@<eUqqGOQ;v+9lS*z>250s
+=4EEmjZ_WRZQx1YfMR*J6m10NyJjvjxM7?iedzlp-Mu{Q(&1cf6Q45XS;omCMCl)<8aA|5C+Oc5lTP3
+W4YgOTO?txh<(Q(is+&-4j&9VH{4@0WRj&D{m|1t+34w75s;!ETJGGi3#cQfhcEy<p0i#)TvoyqY-Da
+Rse1>jxirMc#y&r!h`G%#Ws;M;U6$EvGB3A9+GmJRx#=EF2adGPE`JZj#wcw)VcceEz&>SBUNoMXNJo
+SI;E~PF%da__4D@y#Tf=IT@h|qX+B1uyFC>{D)woM??g09(@X%iGaHi=vuc%^ud-cFEM#?TjjCdxN6q
+C5I$%YB?7Tp%iBA((Wd#sI^W)JA9jD9zqt7JyO-bp@Z&$D7R^*S%~Cj)tVHtSd{R-JAA?KZptiGH&}9
+<OFj=`a=*Fa9d2wj%`^91cs!B|XGnk2KCfiRybX`R?BC3R}gu=MWuYdV?&Hfkvzq)??(@lTz`qQi5CR
+0tEx`@AChgtT-^hMlysPMb6ICeNd?g<5;Ivoni&>|qwLX^CXm~922*`(<QtaB7Y+H7`U>u2gI54E*it
+%3iorujtePMRx0O*97pBhmvq0L^$L>Bg>LbK+Xx_ypSUo)BfkzDKtQlHH0pD?Dur$Wf84L$|6n%q80B
+v&PDMBw~dPgc&|ocy>UvCr04o*%YY`u$k1=5gStg^<5~I#VOn4@u}OXn}QuS8Yi*{X_1Y)sXdv0z+i}
+j3C(_(v?@uY9C)Zdp$vzhA!qX*m<aI0OzWmYE&kGJcZ4Q7lz+y>;q*#{pzw?ir8wpp)%rL}JGv9usK7
+Kw_#0cx(sb%@mQ}lSob1AUf;y!0kSy0MytfER{qXMXr!(hw@ZPN{=__T5-odPAwm9Zoj((y+KYtnEgp
+Oz_%hS#y8GwDu)!iXug>?lTO}lp|G&y0VkT^F4W-;N3FkfM2#+aP!K}lS+ju2GSqMh}<gGo2&_1OS9(
+0hafW(aRXKI2dTd&+SCW%BkQv=qlFenS<O_IA&Q^ZiKCp#%?h+>1|r>NUWzgEK?H#Frh9d5Yi5sj11k
+kz`+I(OVpf@^9>%B$1@^?EEmtu;%_c&mkpU&5>A;KLC01wi_Hy<+an^@8;mwH_J&P2QzzFpS&yTBJ^Y
+wo{H)TMTGYMP)h>@6aWAK2ml*O_Ew|SPc2vh007Ja001BW003}la4%nJZggdGZeeUMb#!TLb1!CTY-M
+zLaAk8YaCwbVQES355Pr|EIPzqf3(QAh12-xP!woIlP^3mpHIODHNvG?t-_=@d=Yz{ja+mME`@Z8Sr9
+-KN|H%YMofw;PFO6n|Qc6f-O$zuY^$uj38S5d+GbPSHnao%$wHH=%#d0r|W2tnT8tXD8y*PS8K1X5r8
+i!v|IGK&#Ch!Q99rlWn=Xvjvp7ksGh4Z!xjIkvGJCu2D*}CY_E>`(<K?CwNzg0y5PgQy>XtxfVZ`F7s
+>?%w-CIT`azu%Tv$PDHEu^EtPF#VssT~WEKZ*I}$VEQr|e}oMNENIJtJ7|v(6YZv$XibX{vK0wP7jwJ
+W%Wn}UxBwl^Q_%-h7Qp=ztc_9qY8aGGh0m>q$mX~s39L%!3JHM2#%L$E!ip_$j5VA&q2y%c4wW3Z0w}
+!RhEuCx@vvmd9E9xzCkzsoFsb3%b)}>{_9BHe;vrW~kY7+s0|XQR000O88%p+86k2`I1qA>ADGUGr8~
+^|SaA|NaUukZ1WpZv|Y%g_mX>4;ZXKZO=V=i!ctybS}+cpq>_g`^P2Ur3W+Hw}8&5!|WniT<zWN6yH6
+oWxYlud*pHIhoEm;LQK{;;DYN`L{&gCkLQ-yM(leLUWFN?TB7#>0~t%&gI>1v_+HZXqt;be1bgMGjy4
+PO#Z*R<j1Sf|u3io@s+0H^yr8NHaM4^<e)47ymq)0sbXlnC-PR!3&}n1g{*FhHE7m@CKx^&>I)so07!
+)Ywtc8b5kkV;3LLHm}v{#4>M`@M&=`wS9b7+<}KBOD~ez(la@LgP}6vE56X}T95?cAv;^G1Up==BD3s
+hnLyct`?2bwZDU(m@HGwNTH$a6^Aeb>A_#G2NM6(J?2BlVaOuGHI+_=C5zU~kmgHX%1gNxJ~Rs)v^&v
+2c}n(7*{N{yR}V4a}0QM!dz)xBV6ad~HLXU-OjEw{VA#O&KeH`tw$iz@yvg(??K)fDw|d0aL>H_KwVt
+UlDs538bSj_cDUD~i==MT_#ZSgd)u*oPwB@NQk4o*b=<_s2dS_5k)FIplJF4#@+T$EzgdGinFdGk(qL
+;ql{E_M7pE!1<`=X>xJ9`F#Ctv%dOxvH5=a<@W04I>`>s82yDm7SBa`j4+kL^TT~5Q1rv|jLq+l6OzD
+-6)8?f+uY>vxQFLy5z`57(~vs*yJDS%^f!y3WpCM~)=KAaa~mJNQ_+XT>})z;PoIgLJtOHo<${)iL5f
+z`uC#`G2bmE<UOkrh9ut0(eUYKBk?(gZL`kc=|Hi&ZqGa~6Nusm`i*X6B{0CpD>3)l(h}aj%(A2GG$S
+q_q<}C)O@Yg^sRL5j`{cXL@azMrbHJ*OqLj-E6?C2IbNe7cda@9b?1(UR8zVXmGcTR!0ArT}pYD6u(1
+(L*lI-nuNJFT{wwn<ch2Rgt5!=xk%i1j#v%R7{sTKTsJrSF`QG<@4@2CBCa?P15O9r)H%y>_^jQy|2o
+mF@jjeWgPS#LpX-yXk1fuxnqGX_~KFW}kER1sa($93S1&<{!8D?a-D=;C7jjbBp%eSl4Q}dCjnZEO!N
+>xOdm=zBn}&WP}hdqqiF30?RSEmpqp773QzVNw^xOe2HepRq(Nr)u!4}z3IHmsOzIbJO_ySfZ9H+V1d
+8Kfco7bdrFS-5sx9>yByEbT@4jWN65L$ccdCmgO1)v%_>#1G@+*A97T0P1e_fT!Q)*+_SvH0wii@mPw
+gw^GR2O?+YZx{hDpPbS>Y@YB0?GhmjrJ-?3#A)KG*`7_2C9_%sQLBLl1y|eu8jkt;i`HRWOf2us8k%`
+woemzDO_4vbje{=RW>ChdE-*v!}4f<m7*V{or76`C}jGYISdScs!$Bh`NTOqdg1UqFYHnv63UtKRX4-
+>twY$DvHcMcvr6nZWxf5h3zFy2RRN96~*ZQa0F=?l}@ARK_=La_Q)J+sVnfa$_L8_l(j9B%*`4#lmm3
+UgZHE$D=&Hs&y+JAXAnQa;4-4%tRfh#{kU?gMDG;+3|tH1s+0Dh;`^HA&fV*f>#`7fFGGmtM9dI>#XJ
+_*k=zfhKlY8hzfqFpD-LrgdNnqfZgHc2$4}<d(7;~~ytNL=B^C&5AVurL9i2s<V+L3<>#$kd*<o)Tn1
+-VrH6fNz>aOo_?Bl|aeO5sVo@wFqti7l1_U&mU5-?2?yk6p{!-Sc#@JML(1TmZa3s6e~1QY-O00;mZO
+7>Q2YVO4#2LJ&66951m0001RX>c!JX>N37a&BR4FLiWjY;!MYVRL9@b1raswODO$+cpsX?q5NuA1VWm
+fVFEec*w9UP1|5=Qlwdj!7yZ6rffEnsFGA%qv(I%-I02;l&-@z0|_LGynF8Mx#N*CFO{}z$IUL2>q)9
+r&g`L-#g<9;>GsdJ7xDS)i}PPEuU^gAFS6kJaCtprFJxk8?9vL&*O{2H-=u-}>(WY9@ND8_m9mUtS->
+P1i^Qiy(05Zye+`P?NRxA$>}K_w0reocFqUT-$N3jpD?KK$vNAJKE=^KP)Pir~WLFh;W-^g!AOC#9;7
+4-2$@Q`rbx-K?BX*^3gspVJK#x|NDiIraWKW~#(UTwj3K&vFc3`Q}=rO^Pok;G`aaOUM!%Fz`@&GeSR
+9=EDYne%VV0&qIOl2FPS&6o@d!Y?EMy2fS!R{2PYvJ~TQUjb!CXd+dPJq=QKNrOYV4-D<XIq7`EPTur
+e6bNb-|=EAU`QIa--$wiQknpcwgP5@Fnr~pA)&bjthH>fipRi_3WnD_x!ZHS>6;TxUY@<bzPY@;h+m(
+*d(BQ+V0Qe;v*!T;yyCea!)l)+I1L`i4LoLQ51`ivQhjnl=oPVq@nXYPEA$?Yu2vxHywVzs$qqA^uMC
+0}v{DtIgIksfZY<*l5N4S~pPp!8fSbIaVFxUlyt}=*zIsJ?FWv#-MGbjI;Gh2Ry?=W4-IHJmb|e`$hA
+1kG<53U<XKb%|S&|<?`MQ$X#<0A~tSmD@upKN_B!cWAnizzfGrk3m7)!$L3bijzwn}Z-J<lp(CbbUtu
+n{SXf%wwKacD%A&b;(_lXDA9$%V1nB_lp9mrJni3Y;@#CqL1H!(Pj-pXVjlJa0svu?@(=m^HCt1%<Ix
+Ky6QR@UJy)5=F6*hQFQo1VVsA){JVbBY(<1e`y9~TKfz*S}1#jn9>0f4nWP=oj4dwOSd4BR^%p}_9wg
+id&BR5<P|W*xt2)7vpoj^#^rJd<^Xd96CW#1De3|>9f<R|7k~kM>(++|rk#uNiQ?A6+CQC00vDP<Dqw
+@2v%rxnpitE>^R92uBfx2_jKHUm*3CR8k1W@&f?X+lnFAHE0@MJUQ!Y~`Bnqg@gcHNm`h!SN4TB|83#
+f4-FTo+9j6?(w$l)D9rWA=xB^U}k2TP|j{9nh>RWD3Xr^`uq0U)PD#|AoYj2VO8I-ZSVqmxNY*Wha$*
+h?c^;r93_Z%Zf<U@fv~t*|l^N;3|#5c@u98%BC|Nw2(Nz&JN0C6|k7(WlIi#EHVJt3>YuAgO7%xF;C*
+D5{2$y4Rj$n!jwMcwf2Dhahk2Joa;`6;w5QXc+5KIZjknSfVYl6l%fzSeU8uFcU@SlYdIU{L27O<iLj
+0X`39<#2B1<N~hYzScB$_N*vUe*h!@Ug0ogC>(w{EkHc<9>_Z-I<-I66)d`tigXz{MZ%wOah<z(;*ua
+{x#j;}rm5<n0c;AqCOWe!6>75qqgB4~uUZKxX4x@dc-c6iLx8vcCV_lL-FAnqBslYA07PaA)M{PRXa7
+=`5`{fd<fOY}jI#at&*(!+Pfc%XQhAzUocuah&4?}{Z<V7P0Deb$32w2&AxnGZ6L&?JTNFr(yXY3Z5F
+?t-?3N%?g=q$rD_`RSF*fmd%WuF_RUxMkRXE3=JjrE}%Y)~WyzN1wQ#fNxsT2z$~8xfMIBRw5*ZC#ll
+fe)1v_!t3S9bLoeF!@{mj`+rPl=Z7yNDd28X@}Z=)R7s#%~{)d1k_0fj?F>csCKq7Jz!qg1L;IQm`SP
+3YSs8SZ%!otG<`U&KglHY2Cm-!>+I-kQ_*PtcMc~ZYM(x6CN$SOZzevrC9ZFwJ4cjIZE+TOU$3EkfHs
+$W^Uxj|jkuKHv}nLtF=&cadem&Tk;eA&o2o7^4t0;=i?5GFXLs$o@re2T3jDQh4`M{-9d96`!p6#j!+
+one`>Y>($ulFm{TmwX8@O+B!X<V1<cm(L@2wdj5z6Z)MmGav@$tBObQ~VR@?Z3gV<c+(+tZ_drwf#PA
+Ah}Lz&T+LMKBAZ4{*{52Ql*f_F$Y=&Hbv7+A$yJVGEDHrfKty4W4C&+n1-=gA!U^cEk*3_t&>?)8<&|
+Z#{e;)(ea~Wh#BgsZ^m>->FvyoR0^2wik~fmvScrDjRJ-WFfftV+CD2#?gi4($e9*vef)S1|}9xJZ_2
+4(#{$>vr@^1eC=M)kgVoH2aeThPZtyx4~8fN(CO&!4zc4!`vqM%s5JF0+iK<VWVK>=`>^fh%Omy{J*X
+<pQhtwTRncs}0A(u*Xp3Nsvj8?0>&s6Nu|KeOg7}UkchJe`CJQe<B%EX1HHp8WG722R1U3!st3O4Ohu
+R~8si1idr%_|8!+-j@cTX~hj`7R?v#(-=Xxm=&G%maC!F2K$P)h>@6aWAK2ml*O_Ey(_5u>63000{U0
+01oj003}la4%nJZggdGZeeUMb#!TLb1!LbYGq?|Uvp(+b#i5Na$#<BaBp&SE^v8`kx^^gFc8Pz^(k)d
+O9Gj2wzokG+sL5M*`rSPY83lCYn650Nluz?zq9LPZE0b`hC7|~|NrikB*|xJ(e=pCQ9U?>*qR8||Hdi
+?D6kqBw`_dqiQ@{$gYCvpE46KLP9U^2xEgi{HF*RR01dn281xi^-8o!ABtRcT4~%ob_-DW%9>&)ypd2
+C}U_lHAA;3NI5{#U!7$vR2G*KWQ!L0xF5>0qAiZlKJ1yt;7k{nN$gk8SQRC%!y6ZBKjS${9`d5^v*Zo
+mfNBt_DV@U{XcGuhr0`?da{Rgxr1oq9e7rBsd0tY3zSD4vKGOL%_;natyp0$CT3k4%gX_r}LF%T%<@s
+Hb~pVnf`)yGuxF!w2h=$J^r)@qxXX^2o=3g%eS5(-uBd*hjdYb~nt#uWMYu*A}b$0AhI_z*?tzeP#+y
+=RY=?6w05Q+u}OU%Ixm@m(49)T|)Y>PSaHWZ~wvAFm=$|UYC3HHL)JpIlKF)EAo-;?%c%lDL!pz@uZ^
+_<i!*$U-y0?qvtoWK2kY5FP8FtZ@r!R3s6e~1QY-O00;mZO7>Rya|@Jr4FCXeEdT%>0001RX>c!JX>N
+37a&BR4FLiWjY;!McZ)ay|Zf7oVdCeMYZ`(%lyMD!jhEXz==_WlKdO}s4lQ^kysU6t9`U;&vti+YI7m
+CzzNh?C(|9&&G4=yRvc6#mM6vQHTXJ=>UJ+qSQO;J{CQRJ2QTxD`Tl6pjxWnS2qthl?A`CaEVUhzE5M
+5*j};hxmaJyxqy@Dx`s%VNz^Uhzf7l@f{>2sfl5WML<+fuysGo04xfqSTXSYYXvCW|f_)b{lWzB;SqM
+8^roEFURb?$VJJk0v<m|RgKxjrjkX@v$5F)zIPij(x^6a6DRi~Pm3}x<zf{Be^ikPi#!}L_`K1BWB)~
+?Rjsj0Km?o5Eok$OTl!;{Le*JiMquAJ97r8S14OOl-716szyV9xd7WiHHp2r8J50o#e$=8ISfIq+TI7
+{oaHU^|fU8}@sVjW(xhg@?O5l53S29y^0<>7zpHDAeUtFDz*`2690EsPfI_nn2dcz$-H)rQ>FK(`e!B
+ep*#e$=3?3%ZyA1_beoLrw>oF_kBy-(on-Pu2eQLLp}*tH^8bt#fmmZK4#AW;>s1e-R>4m@7)ER05~o
+^Q%xA(TQuI1@m*^MwKK)PNLa5RFD7G6wd#EIx_+s!EHRzya%NSr%n@`gtKp&7uiuN)QBEW4KfzWpZhj
+ev}(QD_F5u)TLrec&t`}DZ&X~K<t`rR}$o9ZQ5ZRjZ(2>iB!p)uq8mMNCZ(JJ}(j?aza)!d(D+_RNam
+l%uiTrFk(kPuz68rnq;8S;b2mA3D!XPDMeM6IlC@v&>|c-U>7;Nk)Uo{HD;V?;!t9OEqKn<s@Sr6!?<
+FnXXihkd|+VqD}e`x+0&0_A5SL+(W<I8YI1x$ukTd6*;T6|kBjo|SSnSEmw);5%U90<{Pvqaz5LD|Dl
+eQe?w#Qs&y+cY8IelnpgH+MAV<L`UD4?y2F8f|iOC5wnX{0dVtt}9GjDhp)R(_D?mIS*Yo2p7Ae1363
+#=8@FU;%p1l}u9!dD~`=ND(^MJ~py`Fq<|t`i$0m_dztvskgM%ranntpuqSnltFu2Gpx6*j$*+K`l}F
+c)lZK2(<=%2Rw?2wX6^Tcp+0*P{pl{57;|WTQsaA#h0SeI2yZ)^&Z-~$+{A61Z?mT@UN!~ctQ|Wxoc#
+$lOjv$Z7IPAWZu*OrX!6>o6Q~#$ZO#H#1}sR@v17r2H}_m-l|~CzG>XS8BKtR0z1~Q4!no8SvO)F0#L
+vqjwF>_i)2ZYz?b0gm!re=(P4Uh_~Yd8r^(?}FtXq*0di%PB%wQ|64`R>-d^zX4y+xcsvF~JN?QQw>&
+=9$8@3@e_ZGhRwC$`VW}u2SJhj5snznZ?G+szA=3=Kv%RG&ax_TLp9Hz;Jm*C(!be?ER0f)qhkUNFVW
+De>G4y4XfR9y%eOZi!(4j+EDvRWYxvIH?MiZcBQNV3S|-UA^g;}#LXrq+7{T0^E2MzIqI@qO&L7&Q_@
+6*D%3%2QS$NsKKG)6xk#_%X}Gy~y%{%$_(8qy3D()M}|C1jl@CNiPngZ?`N&U$-b~(n*AKcr@S8{^5}
+LB{(<=<Zjf@AaI<9O7^`I{>{nd`PupVNsIf&a@uPheKC=(P()#Wc#qoX4%qcd=o8yx@eCc!j;$boaC4
+NHu^YkCBLAvlTaI}UdbbXytSCOgAwLNgSknC*W5Qzi1W%u4pA)B-mlv1)d~iDjjn>;ay^MKAt{G+YL~
+HNF?E)#rB@I2UByYeODyt)T%FER8ACzqlW<(J|TPScdvs&cojzgv`ZoUHxEE%LIB_)}jQzd5fD@~)7Q
+)f2jfcj{W18tcJf}=t1+mFL&nG+jXM7^7~v3}jmjk=aF?TC2aA+)9ImMw!{309-N255V>2Nra9flwB}
+zZU}muuFar#Q!Q}9?tA?k_LrodVs9MGptP}E0R`-saSLyb=A!~{phbvMd!yZkv5f&4TSE!Qx)liik6Y
+*@*@>i8HuUL_97ND6BAdSu|n5mlTMA+#3H}=nt14_%2B{8gEQ9jk^#jH?QVytqu5hhDQW&Cnt>K?ODv
+A(1k+Xr%0(=yP|KJ|(EN#dfOV}5s2)S~&)lmvun2_w`-*A;Qw@e*WoSI--%fwIxww3LHF34|%vRDfEU
+ahXIBsum;pns5p6o)4NEaRxSA)-V2@ZurUVvaTC;%u%_aq8?0kU;KBd4hmbhw1dW~z5<a8K<65K=6wW
+Lxshl(c%>LWY$DS?IKr(zr=-4}-H%pRW2Qy|R7Usn<h~gvix9<Qr855-si_^T#9^TqDW`at~cpjxo%x
+`6o=m!I>+zEy_<=18oJ%1=u@y;5ER+P9&IhKPwV+_>c9xCpoI`QQQdDIKBgRw#2=8DcGI7hZxIQD*0V
+rs7fvvRgp+C_#OqiIJOTMSt-Nv{8!`tv1<gb)+?KgpVmoIRc|s8`Ht31uhku!g2$VgU5?O$+_FOzP^F
+cL+(#54?8{EPMVHf9Je=2CF#G1V1-wsYYq|&Dn1%bjqNW3c2Gh3kXpFI;gXIA$Y0S!S{K(kCQ8Vx52t
+>o6^M&K>d+cW%LJMs=9DlT4+b030(Ppzv!c2%B2<L6$EwCQ3A>Aw*Ta@k9jcV9z%W$r(?8D$cOdre6>
+_>OPrn(6hYUdM_A`PNFaFIQ_NpCXz=r%i%WyLm#8kx81TUv)~v!QKMLX-_#K@FVE5^zid33giwC`T7%
+u`w=9?>eQwo=B<R!(7{^XG7gI)}1UXS?87f$uD<KkRD=s3hr);X}xQ6Dpu#DD&TQ24OPWjn4&MHR+mS
+<?nzM#3pHz}VjPtDvIwKu<kfB4#kKoS)MhJbdu*vKfEL_;Tgpm6p$aZ<nbm5Ak9n(NI_R|Iq$3_Yya~
+WDd2BHJ3eQ$zuaDAZwGj)+GY^-r+=qjr6UMffW-Pi_z`f=YTN3D=pw__z-Lk4plz%quve8{)y)E<FH4
+BY}wEctQWZN_9zSiDYOA|3@qs)-^nk{?qPjn?odW}+ciayP{!R~6bS4r8NqgQinvsPdMbXio?QFsSOu
+sKxsvLx;SYWg-TDK-#}kRhbttt*h`98Ci{EL4n{Mhwq6hXR3kIp<0sejJJRa&?zP(O%6Ve&U}$pzqPQ
+Dxv=JX=|r(<fodxLMKr`G6(|9h`zl#RO5e+fj2E<kN%FI{NCHlodsM_R;NPu*}DhobT+N_>v`R55_-K
+dn<<@AbCYke5R5@WZLk1KPr++OUgP|~J|?v#7|PI+q|e0Br7LhA+3s<&JWL$|JuYIrbA_`ewb5#%Ujf
+`EF$9MY4d#WC)s7_IP1VP&hNOo&nP|UWhKL10yZwo7y2zLE4pdkf`v+EH)4tU%pesjOp*vH$?NEw;*H
+AR;ZWM`)1V6@X7bSw%Hpq&5p4Flwl>_!xz&Y1gYtbg8pSn?Pv2oLX2AAfJjG_2dBOh9p<n?+^*Ev?CZ
+%<$U{XGFuG;db7^U2O?bL%y*?r3;nCpQ>E@HE|&!SpTv9+rRm<nlL{XV+(MPCgh6eoi;A;_Uq0g%*f&
+5M~B%#&GByJ(<7SRYPbQL0J@4V0GR!Y#~!zP-m6}CXxgO{fj!!APam!1xW@m5i25t&SV7Gt0WDkH`HL
+G1UY$u#40zC+R}4BZ?sy|UDL3Gr>WFd(IDs`Y>X6+m{|4%q*_4_hx<_m$EmnK&Y`#r`Vo2#8Eir-%8q
+!xb5<}Hcp0OZQ7)!gh#Xw;d%=hv!(MBt8kwL>OJDcsTVb?RIWKuBh0<KL<3zGMquDBOO;Ai#W&tV-q@
+KE+8QjwO9Yf5fSF57L`@K}(ae}vml*?T;B|59Ze$1~;uBcOsV8Q|jv6JKDCfx|eEhtDX_MmV~Lp{)66
+WkN~%ZAQQxIN<NyH~cV-`9ZgDM8Ubg<~)a=_3}YoH<(=JG0T*l=4TK8)^{1*IueO3#|6SM33%kY0Y%j
+Y;4#PyPy~VdCQ{G;h;g=FprK79!cSS*o3`ow^D*st8OAbONB=^ckBv4dpa+H4s$r$-hn1f#80-o%&~{
+k3q_D&^pqglnN%?D$3t2kOuC+YANpZ`2<k}CE8tyH6~26)AlhB6JxUm+jR3v(+l3e>o=2YL=JQE=jGs
+N(+#f^xLsw($-Nt~@=sw32N87);9iUzBhRiq&ZR0}q9JG(&=1vs5XU)CB|C%rYZryCa8tkopG2^Y1>S
+w$4T7$=PrbW47KMXl*fay5znRVE=LmFl>Us&o|$^DSd^LtTfW+TrK`o>Ak`mAW&<EaKwS+SzzjH*6Qn
+>w-JNj|&i{r|^njMcx9*S|Yo51`sKEPz5rZGg)XQ!ly!vOSoBvRM0*L;E|K9$flokC^ecenMsv<9JxA
+&vD9sqy_yZSv_ABe5nqE$=}~%Tq5+et?1<SOL<BO;3JAGOyuh+2?iF4d{N+!6_KX8S{{8jL{lm<z8m!
+9nt*-Abz{*N#{eqxdi}p;WmDAjNW=>v_VMxkn&k1<!24M%z1to4YnKNP&4Zulnm&tP#*Y32P)h>@6aW
+AK2ml*O_ExpAbZ9pl002i<000{R003}la4%nJZggdGZeeUMb#!TLb1!Xab7L-WdF?#?bK5qSzx%JiGB
+;;3OVb}|+O4+ACQY5LXVN5-xZCY{JuD?c7Hf)B3DUCa@&A7B0|3DfIqBYZZg%c68Hpl*hlhvvjR$9|b
+y?M7UKX{yt@CWQm+>1}RYhrjT*-Q!C}n;w6SZ`@X0~5mUR`CymHAoP5$jTAx9g-{nip!>)LCwS)k$ri
+x5{}0#1@$a*i<>p8?BQ{$-PBYu3&DV+dkA4OnvrNzprIgmu0R@^CHXP)gsB23`H&B<JW8*=VfsvRn24
+S?ONLY=T$P7vt)jK4sUHc%wRhBdjkHwD7GOze4Q0ZwLN>wzg{MJp3HKoe=&8xON!)5R{ZXpY+m!zx3Z
+8`QkS~n4A5+c(l6WgI#YVk+jX6lMUwNcbAWE9K5y1$FrwZ*{VmZ@zAs=XKh6^b80_%^*V#IXZ)A~{Rk
+Yr&tMX?#uj6G|UR$z!-DG+CHIM~*{S_K;p|TnduVs<UvwCaBRkE(OA#8NHj*|r}Do$mdz?)5y)$t;`m
+1&EF859GwN&&KQ?97k>F)LVlByZ=E$Y8O1S*}(|k)Bo+P)wZOa>snjluu8Ko2)8}l`QHpczHQbI^clq
+<5lu=S;ecYfKQFh*jVId70t^PFu582!`Yi}-v01mcXz<1ZjxLUH<nCIQ2>v{O_2hL+V;J@IEID9v6zY
+r+BvUU)s>VU@1vJyY7O*^QO3+W<lbf-r&(p*B<k8cLiY@r()?bO)helDmHldAW(p7n(PUP3;S|_8hpw
+IZD%kUtROTmA4|wRx{GKQ4x~XIut2!+kJFzSjymg^ha#h~QIBDu-jI@hE>@AR`oL|S%?kwyNZLMj4N%
+{h(8Rt~!ce%HRdP-J6ORcaX!1Xn~^Wzv75yv1C=g>h5j_;j&!QScZ{H$1%_!@=m0vj*BPLw<~oOl_E&
+hN0RM=tmN#w^qU16&ab^KrTNM%KWI)MUG;8u*zXjpXAyn6C5l64tht$^~&QaGc>-KM)7cK=`T&Q3+et
+*H=h$n4we=?qc+FnH9eI0Zm8;AO|Q;Bu6N`DDwC-cmPT=Q~2#Wtw2ib4=SLk3gMxE-`xw63i$Td+j?0
+R@ECXzb0Mo%{O4$Z(7tp)w=Z|dsvmHdKoh3rTmv|RtpFT4zbEd_L{W4}^c&kPCaC9mM$rS9S|p;T?JF
+19Nx{<Bl~ka1(0(N19j{o=DC$y_1$72dzXBVHpz0+^cf^#NfWb>Zh4hj9P1CfbDl72@Cxm&`TF$e@7R
+X|{MdExZHQaepfUUogA}O{SH-iyxW(NiCz=(@%A%5!N`;*8NOjI1;<dMbZZM~G$CPTBVIb=AnDdx)rE
+OjdUERqqSA4DC}XM{k1BLnf3crs}@r`sz2I2HaAaWFbE5RZj_6f&>Nd>8y@55b@I-&{<dTy~@Z4Y2Py
+S^-3?KZj=BR#EyWVH1>R;!C84<wGNftK?cjS0y$Xa6wax)6>77eK?N{y}%r|c*7vmpJ3}nlNJ+iKaf2
+Yi4w9M@<{xUfu-Ll;*u(X4Fqm#s;q33IDPZ>{Peqb=RcwwSyn0%AAlzweg4_W=k3M=MP)>8ruf5@{mq
+Dx1b$0L+6>SZ2_hs;?W#R6IX!*XSu3_X`f3L1nlv3an^96--CP`91}=`&KP!aq#h_p^&_v)Hp&~q(dq
+EEs-qVG5hrr~moHsR^&U<k{4uEHSOK?L+$Kq@*@%<My__ed9mfER7Gol~Qz)85JX9o}R(;a{w&AYevN
+W4cEOh{m@El72~5K4k~oeI#oqFJLhc%ok^=zVS+IHIrO(aZ?5tpH*tO%6Ix-hv+i{c_zA#2=JFm4Q`F
+a$!BRz31cr`jw<!)AOp4><v!)E}{P<V6Sl6x`zHy^fU-)i`nh*fmKNWKnq`iPM0w=+C<F2>4)uog^qq
+tI$$$#Upf-{3^hO~j!zsCa%>W{Gxa8!c7BDZyl>}I?#?ekS*74?7~SFS^*;d|pT@!OIV9;cu?1a#-kj
+K2<N^#?hye?D4OW5R4$ieXp}62eJ2^c^=5lYSYTgz`2ZXfk=qV@^l}OzbBB><sV3Hn`MUI|-DK<-4nE
+eYtC^P6?mzr78<wGc|5Tw6l9JCo=QOXS%Ch-HBq<W4v2E1%A8)P%gNDWBOC=w$$A*qvPxt5CtJVuIjv
+!an!GlI+kc~)v%H$t!*Bdi!f6XYpaF_28qAQ-o@!i2|oRi;w>Ck3<7hxqJ=_h;v)W17@eqFKEUYW0^U
+yFov{CSO2nCV30dp0a&ep7#tV572U<&b1!`(6IS%Q-QDVYWw*TkR{B+F?<<H(-&vtr&@a~;A=?O1ZrP
+njEYij#$rdukT~cM1;W+eZWPlqa#oqcCViXTAnU-?dVm1x!G@wHOT-nl7J}CXR*gb-3_x?h@rJyf`6e
+}FT$f5^u={rJahziw&|d@_E&YLii>nJP7;FMUR<%N|!rowuU>;!fKU!c)t~;8VX7VBry5NrsbTFKeft
+Xyns+{sCOsF=rb2K4DMf5~KXUVlUAlxeojRZ11QV;DOdTt5Ov4T*)1j_*ALEvN&pbHZdU3@L6ev+n0Q
+k)>9&l8xro(G121x$aexxNOU1^H!)&-8Ay%+OoxusALONMO4=G%C<VJ8sQp7a|OT)%iu>QmF?_6AU6>
+;;L9r32~}|xKUHC<TS#>CSNF;>XMI`i`gGk9IQZcHUYQG_uieoi^+HS5WjeNe)jeadI%n<1q`!&XGOp
+)4ir7_m?yx!+?Bx^4Bi%HV*_FijEfR<`MRk)>l<qB_hhP3&yqpUFfI}_5cMtCi*h5=$Z@U5miy*yeD>
+zu_vfw`#6Ezv8h&SC3-67YWrNP-Ed(Dm`t<+df&(9<4*o2DX{16B6LF{4a^Jd7LA$H}#7@GxUZ`tgZ#
+`I0Vg@OGBhgr)3_I*^lmu*qS_5>c3~891k6Qxl*aue+G6>+{kM}T-pjxVI?FSKVOyzg{Q`;Sl(k`A_S
+FpnFZV)AYESsu@;NShBx({e`5SR{1kq&mRECnXQ8-lyLw;{ag2x5Rq15Pezo((!9+h04qVgt+(<{fO_
+-(-|p&Dic1Ti$+fzx3?A7FVGtwJEFg)6htS>Hj~#MQ7q8{oTh3=B-O~fqk%uEjlotMW@YCD9V_(Sp%}
++wBuES{9ob&aK&+eDFaHKLqr_t6ac#LY<Cs;di&e`5I&^BubMuf2Y#2uKKo$%$NPWQaCjgAqQTf@zbN
+r@K_A$Q1}_$7^wB=}fbTgR`5TTu)!K`|>;uSsQeVZkUgE-#ow`W^=mJu8L%H5okU)sAfnq$0?6#Q16k
+bgqun7Dv3;aCpC_CPg<2FNJ!BFP{gL!X3AGjO>v!LHcBXEv(IY-W7{e_nmFiV!|O=8FA4!%HiJ;Mf0G
+S{DNYn0YSUM6*yHvwU46wk!*(b183OkV@Myt_$syto(NeQkxChaFP?=tw^}nUWUlZlL$#x&?^Z$pspW
+0($_t>s`o=#b6E&)Om<TU?>UkdjpQ6^dSUst%`lXc*;!=;t`Eb&C(+#3EM2;du_=@4s9rEJTYlj%%vc
+ow~g~MZ&roCZB$z7UID|)+hhe(O(y*6*|TRYnim)Qi?W<06$s4<5CG7)IJ!+C2$)H^xYVf)-}EAKU_T
+VKCto~y`sK-=o<99@ABP<uh2k?kzz7f_ITaU_^z&EA+9#_EufbbIB?nI^0oadyS3(|#tdd(A08Va*E7
+Jqu2?scbasK0qLP`iHb7Jo)I8qFZvMC76GbTl&5amBNswPB2o-zocN?Xlw#55BSNIgdH`S9GM7mJ{Rw
+Oe|o*po-i<M`1SWhNOO<_LR~7S-h{M_mdoPP2~I+rRJ*o-O))*h|H*8o(0dcc<^f)8j9M>DJ~=#YT#}
+EXl~QLKV5ZO6FUhhEG8uNJ6iFwiQ{53F5^TF*A5X7+OOVxnB#iK}0bVQgf&I;!4cqJi(x_Q97tH5wwA
+WsB-XqlVn6af~0Zh_=@p|wSn&hp*(8;B*!QfX$F=FL;<iwr=v#`!fcTAB}YYv6PYr5HPo(@5OUmEJpg
+kSe&+;)14pkrxfcu}q5=F301b^E1l2)SXLo=!;2AW<wbEG~m|@bMHxuhl(8QxlSw`QSzIyTf>+|^Q?_
+a$-eII`~`>#{Z-Pm*H3sP|*g#`TBDySbbnWti%$vH?ZsGu~d6F#a*XySuBy9TdthLjNvFj6i~-@b~v{
+xB}5T_fQRxZ&^!SK}kb9Um4qk-BxgzZvwtwr{qC8g&~S=5!MVm=#iGej{VGUF8{2&gKOXwSk95->qLn
+;tbwTR#S4jEV6l$hnT9D2X@L7oRS$#($vx(o$Pf0_A&|JLW6b(@u{552>b6{RQm}60|1DTx2cB_v)1e
+1$yB)9HOOsn5A8wfbK#!KbB-a=xLMM@CU!9S4Lvp#Gt4j~*tA%Ps7^3_P#VHu%AK+mcs^nZL!!>amO9
+wiIBO7srkq~!5TxruF)-|Waq!vXk`n;772liY$-!qG{cn-6;zozqewnA5mkPPr5k{NEn=t_|oO7^>LD
+5m%yn+Z)r1B;Mv9iMQNSvV^Us>0CR)UWQkv9vR3z*g35`+hA0;pDJn>oV(NLrd<H}WK?CqB4JQYS#Ll
+S4rF1c;iLmvy!pQ>;i4B8F~y02$~xj!ZjWC&j7};8d=ILc6=;=~HHU<=Aa3;m9Ad*7W_p)w(8mhn5Rj
+3tR*|BY=o#k==&ax{>>s$>zcgbRiPa)@4N2fO9t;gS%Zq%%{*C94CQepuh&Bo%0CY$YUTclZF!>Wb|#
+W71r0Rbh?v>S!#@z5T=7uSF~!7vznB==&Ht1tGTPz#Q(T`>Zdz<inyhq^`j{R9fPkxfvvilQ00_(oK#
+neo_o^86&ev8&O>+I6QRv>pa@ob$z=6Im8{pG8cgk%#vBvYv7#OmT^q$Deoli|61*0s6$MLJV#2-sd5
+%Xe!{LOT*O}DoPzhuJ#`>LncjN#<8EJp@=?h<bS|wl!5g1C~nMgm90~&zj$y5ohodHcaFDVTRW{Pq<b
+eK<V8V(k->60boZR5J}a`0%Ug@LS(+k^fZlL=fOSYf@jG%|gCCG&-~pJtwko~XYp?CcW3P6^xiye&D5
+^dpz@RKzc~SV*%B1EAWRR<c`<rn58So{bH?^lU;;hsPY`a`x(z4&f^+@KaXoSJSCeEwNH7sWLqAl<Pd
+1YuN;*7kaNBJJ>#Ec}#45qDh~Cwk=rEzs_cds##+J*kKHzM^@7rGb$1U{8HC(z-(n#kTq!$Ti~xNS>u
+5aN?#}(3<BfDkG6(gQHoq?aNz5JyrZ_+A$xe*MMh;>&iUs~Jlxr|*63{sAM1CkDZ5+WZud(b$_G@$L#
+Q}WGchb3JR5yEoGCHF*0DF7NZnt`JTLdHv=gI)W&xQw{ROnBuf-H-LlG=`20Z2;#eVRwV*p!3(iIj@S
+J;h_5t#Y6kdeNzcw<1IPsRjhBupNO57~;c6pD@>ie{zjTAG#rSjk@+3`{X?$)@2kvPIe&2dcKibPFSg
+!!WUsX7k$r72^CB0{H(}Erh8C=WP%K7OL@w(Q`-F@Q$`=BCh3@B3Aegb#5(VR8<5Tas?XxzMcKT(-7h
+nkPW2UyQHK&z3U_y0CnFxg)v?zkQr#W*`66zD#its{rSsM)!Okyewefcewaxb4_&C#5mXF=FyR_PI^g
+Q-B&+%!09S4+$K*Qr;!xAkn|MeA!pru1B;I0}zX5ik78W7}ybmHbtFY=4f+srg&uE&ncQ>Eg(KG@ALh
+s@ZAMY<aJhbrm?c@$|y!Sd(YO0)TLN&SgOA}1Zmr~mYJOf?U^;!)NK|3VFk^u4j``3nO3~%T!@#}dBA
++HY<39xYFg#23Xxo6xyO@DfO(R=IC?hK4i10<M9m~n<AL-L3uO(7UmTq}W;)fpB`(6)9;&%`w3A44iK
+IqoNiho+06B^A(*kkASBc9ofS^O>$YO%7^@=N=*|Y$S$c4{WNgGDTEV=<3$~NAQCle0b=@w%k2JJlLw
+}7l@M^;X2jDJILUa;dYn%4k6MRI&O4Ze<Bd1K#vtuy6C$1mhTV?d|o{v=mX3N7-ac?C>Rzu4%loUv=(
+0L{RGCV{D5m_d=OKxw9DH1gy`4oE7-fufXMpzT0@yhtOiwx&Z;Ea3VIw*37?~g>r*7*b7Bw60)fFPYX
+=)hIYZ-{Vsg)%h1ohCw9oC7`^v0~)UYN9k~nO+UsJZ?F+ieF9Ba1OOuD7f&>Jbz(`pFMmCPQUa=G};W
+cmoHCL^Ruu9B?i5zK+b>DJvuqaAf=Wyd0C0atBc@wieQp2ONLow^yMUVmmH<{@kvNMZ3yQ`V9gxGja*
+aGh`6Gc5#lbohGHtq|`B2BKpN-DH}~>s<mn(DCotJ!kJ6t3jy#hccQJqiZ%I73)2Qe;x(=zyO>h898#
+Xt2q!JVmHAZd9GVAVDt1Mlx|0`opu*OGKb(n)g?HBJ7A0tx1}~cLK*D=gnm%T*}bAo-Q@&uU%RdL?7H
+7wa|Tn;Nk;1a(Bkc2wLU}ixv39l(oSKI@UZv&o#}P|+?u+<T>|Vm?NVxL9*j<zI*YcYH8psX3ZbE)@{
+RS<K1bVV_|eu|YSYQ~lzdveN}ww#orJ1mX<EyAZs2Mw!>p`Xme?0?&>Y&wflrLuYCSH3ql&NALtzS1d
+Xj<Q{9OIN$SUwoB&Q}>!(bUE75ZmN1KJqvi$k<eTxXSR`|%85d^?uUUKwys$Pl7k1R4u)4j}$Qk6RpZ
+_E67ZYY`cSnSzdt`cyCwj=RQm&929|4!8aU!-#8r4W|#>M<|giPLHUb0-`5E-*8E+k5Z<BN3c&8cEDf
+YDJ`|~Q4u{t)Pfi0=y_2kSGW~Ak{`#vDeMaLq#efyM}_*jfx~cK7ZuC%SV{k>j**$+VU?o+Kdi&8R9t
+pI`(vYmFc^AtdNJnOSWj99qW8)7s>WPE5<xt8E5W?r6`fjImCWW7IT!orlq?(Jz8{DirVmnM*T31}8T
+P&C-dNwo04+gJeGwZt+uLE1-KgL%YlVl`^L#_%fhBg*ZtJaf@t7X_W_1&@xaa#Cc<P*ym|ln2OVCXyP
+Nd^+5H_TKGqZQ8mQ~qYEyW^Fu9SvAMHM<ZU&(oSRbZ~%WLHRyIyCqgy+B&K?#L$-qV-0cLNHsfZ0UkV
+F6!k~Mv>|Wg~p4s<A2T4R2G=)o!AtvNi0zcH^iGB0NWmyA|#oPopX`O!Tc7FK;MEMx{U?`<v;jw&zTx
+)%=FY<!nn5ls}^m6m59%*4aX{98XLGk;qAv@c5pMn(77(E0M3H&pKBek*tEEc9O&{FOREw~E!sp>d!U
+5>z&E1w4&(8MDgUA&<JW`q;l6qMh)k}o#hXd|q>MBbtq|tO*J&vgmS@1&lJDdJ->>j8MCd@mA{Y(_l1
+<p!N(LT{636W7lvk;LYYty#sf;;;sS{*|Kl&V|LAI}XK+9TF_74LW@<3jOP<vc86t-Z;^dus7a`RxOU
+svF1&iRfkL0gq+w#fMYcMShGe6hu+_gE`~UAc;2cn<uIq3P;Lyy-1(B}b7iT!{b7g&E#{_W})Gv9uQ{
+gq@bI!z)n8d5Xbd)!>1kd*P5W!+gCA-OH}01FNG0WP59zTJc6$%QXx9eb>Jj713SV`%mo`jWpmjTm#_
+JCL*L1l$V<v9$taAYw+}Eb-3QHlS6=im?_mrb$ER8<(DJ@6g;Pynm0<Ba(E_33}2fVL?vb-#4CmO`dW
+X#vvp(y^o4wSe(?Su>Saqj6AWl!-#xo?Z9#70IsYvJBz^ZbAYL8BJTUD8mMYkpkM(^I;%KV;bpN11w|
+v_>FZBu$Q*aP+iB%5BAaob2#3FuVAdSc5AI05BP-MZGf;tEFU1i$#SYgLqe19k*FR7|*vy`Y~2*G(%R
+Ty2!_HQzvPHv&;^SQJ=V#i@W{dD^G^V9clUc7$&<H2_?-n{ts^qZf468vXEsKf}NEXt-x!(H?6PAc~#
+emE^VZ%OgsUy%SPdv>$ZLC)^ePuS__DygpJ;6}dvBPbEwZpHI;JXHbT-@{A!LvnaFyzkb=QDqv>F+RV
+!ys>+|d^*VJ7*K8T1=6$3W$aY9`=j-e6i({iZY}&@dR~t{t;-5GqeS~+TVP#DU2lDBR}!_PKUv^bgU!
+G{x^~Otj>T7BiIXEI8ldpJbD>{5u0BEx_2qUhC8g>MPRi-OgcGS{a`N<ZpDsZW04&7nH&TPXB|p{W-s
+JIt-nV6f6>KX;u8Veya86nR6|g$xfD11Eo7(mD91cC#AE$J6oqBa;dKoqA6w8L4Hgg1I)@+XqGO9N9G
+hO-Y6hq^o9MRJJwVDfus8k?5dSHMcQT8~`@L;-4A#`6I!Ge#0>wR?sPfzISGkAI$gahMe@WiS}c(izT
+R_T@<n+~C9yV~QDI&1GUtt<4D+ceKPgp0`HmtkjOhd|K74L#lWZl@lZzNZ)yXF~^qJU)vFCR^wNErp+
+ar^39Vd<oVz=@*O^7H+m)XS*a2+%iqgk?HYK0EhynN8&_$CO#K`g3bsKWaf!@D!ve3c5tkZLCv0Ef<(
+%35<7o*$;Y)of80WTZQh);l|3K(3oicn>tH0(>4Ye)C&T(HUY2>P-TJmol}$CLk{g{dFb#ZCHREafZT
+vQ7l{0qi(Dp@}fV0|O-Rs#@voai|os8CrcxW2;Dtoi0%E=)~x{D3F>kB(e3N_N<5DmvCaA_TNNQ|{n?
+(a5+<4M6Skom67qQ=<P)%Pf`;VM~U_@*4H;NREc91mY>r$>7^<8p+?D_JLaIN(n90FehF=Uh>2++Tgv
+!*LLW=`9+i#Rvt${-URI2p@*XPlvBu53aif3S8`Z*A`IY@4f}U6G3@py(Ns%a6l7KyTs%F&zU>O@%u9
+;db}0>b%aW)7~G(Ex5D@r5WJ<HZTy$f@WGWl$c#Hij!EplCk=Qd{|pUwNa(*O8SG*nqy+d&;JV4!%Fn
+}6@t_L%-SkyVe?cGypD#y0qI3D?chXUxPM2|Nj3}hAGh{@sb=rGtp7wr+W9sbzq(5eS{txfxxFP!A-O
+~RCP)h>@6aWAK2ml*O_EtNz46t_r005~30012T003}la4%nJZggdGZeeUMb#!TLb1!XgWMyn~E^v9Rl
+TA*;Fc5|JKE=qZRth~pC6Is>LR2hZ6-AbtOcD#n6KsRX?XjKyBx#rR!VAyL_uiAnobykwwDJla)MTN;
+S{Y>;=%_;N80VZZ)%9dOP>)u6vaGh$fgk$Vcc?v@A%kbBwcKmW;A7~KF;;5n9K7Q2Bpp`I)b-NhoBC5
+`%OIRUf4B6js-Rw`s&ZtYl)c;^UHMjeP!9GH0ii143y0(@B7|_7yb}WMA?ISGpolFQaB<8dk`-QzL*X
+?HhJqJj<xtmIWNyb4^O0@JlJjdJc(I1N2iTFpF;6@Zx0(6~#=^a*&qYGZ{9$Udm99P5OmfQjvzkT!V-
+3Wf)rInUiqYq+<Xf~UZ36Cz^aXJSTcwHYv;mtDH|OJR`MBUWxAosF{WrJu-z@#(_f7c`H{~BYmkJql=
+v%6`r{9_9={a0Qmb8m2E>sPM;=fbId1=a%g=_1(KF>`O?8v`#y~YlW$BHcjj<znB_F#Uo$p27F0|XQR
+000O88%p+8!Az~A&;tMfJO}^)AOHXWaA|NaUukZ1WpZv|Y%g_mX>4;ZaA9L>VP|P>XD)DgeN|15+cpr
+r>sJh%!^((Fv<-Twfi1cSS|C8N36ec^v5{zLBy(3HRg&_q^XvOaeOPhQ_#oT-cr)|n&68?7V?9;9F1#
+^~OVqH?n7UTFp8i@+Dr;Kurw*$$uHN$V-KpaZz3;p-S~eTH>$?UEg>*g{u5_vs*^zZ=tmtI%B<lr&>$
+p&rV(T_^#1kk#xFszA+bhd0YwsqAkLR@{xiz+xjrzjnpD*4@x}I`OR~K8W4LNVuNfIh$i<4u?qGtbhT
+uZY|%a*eYr;?H@Dh^ycWn&U9>rVb)bea%87mK@@l6ypXn2XDluFP&=>0W8SAtA&=vZn3tv<LsY2)0_S
+;`iGSk5onez*H;HK_4Rg1V^p(NXn6<)yRX}4o6mJZbcH&cAd1cy~yN--fVryhD=2&&}z8@3fK&7l4HO
+K5I(JZG<Mr69iN3Yb1L2p{7}lG7L>b_6U$ilyEhN{ddkJJ?=5J`?`+Tc4{LPND~CE<JhG60n6rA19s8
+^tls5oV{+DbV=W{rTO-Jwa5fUgrP0Z}*T}Amt?{YdwFseaEJWW+l&KPZK4HCY%M#|Bx(Y%|pdPR3gcu
++6CtvRX^NoYfXkASHb%#Mi%KE9`@Y;Gr{dLA1w*Yb&ddU0nxR6hbtd|pq?Vz8{kWQdh`G)kwf>{6)pY
+q74^>tvDM1(wqPpC^XqkJ(p5WBaU-Pzb`jIE>--uRs5?j$?&^%NA`7Rb<Em`rE}B4a2dR@_9zy8jbC~
+@Q~@*BNivg>>nB1&&nSt1jqi=z*qDE)d!6)Lemh|g<kSY$J#-V8)%^nD^Qe)%Z2AM==~r&oEhO_5D6D
+~rcy<I{3#4osj7-?0GGDz2kS~D9G2mc2;M*jM~>RoeY*#5170yz$K_f;Nl2h&FkF%>%P{eg&5(xuw&K
+EaR2Q~KIE<`nL3@~Q?4f{etltc?=U{bX{c)COasxUBA^7V6^)16rEH(1+yS<!D)X9o74i=oo=efrh4!
+!I%`1D~UrQIuR+0!CZiQnjuv?X0d#48H6J!t<%pUC#wg(|htTiJ9637*-i0)7QY1i=<`+Q>{J3otXbG
+Oz<<yvnXN5i7`Guprkreo(}-Jh{+wws_@nIr>fPR@A;4jG=_Zsv^=JUvGKdJ=GAsGrcX?<+(uhKBxf7
+@Zq)!MlmoxcL&9?3RZ{vg+w`k41C4cRGyOw8yVMi)+qfnu72%XV~fK3IlbUJc&BjvK3&~^zS;gGw_kq
+R{wB5$ukor}Wq3q#*CJM%!WRAmP)h>@6aWAK2ml*O_Euc^VO#tK002`F001Wd003}la4%nJZggdGZee
+UMb#!TLb1!pcbailaZ*OdKUt)D>Y-BEQdCgaCZ`(Ey{_bCKQ&Gh3EMfcVH3fzu+X{3`(WKaiG*D>iWO
+I>8jil^&!~Xm3NJ*9ywGFy23xZhIy^!}j_ZGRUv~ggMb|%B4!v}XTqM8*(@4y`^sW#Ba-b(A1a9KI2l
+_-~Rg@4wlGMvqx!PQohx(2odi>|Jc>IhQpbtYIJ4$^Idz-e7tGWktA1h*9q(zK8zrYT4ZTcPq2bJ$A(
+?x5lCZ_GdNf?mFW=Vr-Apt7}TEGyx*7PKOFze|<tg9SmdOdErlE03MKxuh_+x-N5ABSf!PA3uJuXlw*
+ZJO4d=T_m&g>f-vtyX(u#w^!-aFK>Q@^A43H#~hWL&wzfSDDt29fZ06LyNY6%pPilgm(SpOOVQBp%Su
+-9DeyQGWr^k$#4!j6Uz%8C1+_)XF`8O+C<cFx*BIWoh7a3=lY%NV1<ruqGi9xDgP2&C2$j))5Gpntm&
+*WA;}}|&J@I!raa}uE+JvygJ5Q}P_kl)*2fB16vU{=dhdDx7nA|4)TheiRnNvIzW{JW88lw&D&|0xUI
+BZe%BOs`l3aQ8&fszk=k)DM+%F{%c&Hm=QTYn?BMW|JdrabaB?%JU5mce_6#z_KJcLDbf&ox?gM(Mwm
+>fZacnUR&_TiwOkT@vUNdo6S8<%KRwePHJYVHAC?I==urp=5#9r8{wtX4L@%oab;BXJ<avLeuS|L7*E
+{XoT~qS+1!QkwkDv=M%qKv5B>!G;gU5z8WUAU2<u23f!ZTe^H^b)R|+rYfrUTm?5Pzq~PCp;f1G7*ud
+Y(v@)_Sh4v@9c>n(L{R&<S<pbo>sHw{P_)F>-6TFMPkfl#ksURA9WxUt5q}oNbmqx1{6=4!B2U-m6Ic
+JD<lo946Ty#$?#Ruu;-!B3bUE?{Y<}zzlniQj#tvqPUf*?(}<**m)?7WpPPN?t;C3e`iZe_lBS~3z{p
+*neBfQ!{2A`enp9n(zb?5{`+ihLg8!P4U7snJVOI~}))l=rc2dd~^o@ez@){ysas{P-b!%oow@apN0!
+T6Py&Ld0s(BHWtVBRq#WH}&O$WS?k`(a4Nj?IJPOQB6|(vssP>aBZb0+my>CCGKp<$?if-7?)s^5}Q)
+5MVV?p#_Xz_XE*IQyCKzEX8$*>FxV)aQfD?4n=0gH1#3Ex6n+v!LeQwyx-JSdn5VjSRqe(~3y5F&3F_
+Ui1{36GbOV<3jv7c#lWbFSrrTzCay#HDRJEjrc5)iBN#JEw2_tr60IsQs_=y{5H=ya6#$n?$>06Is`Z
+3RC0ICr|BN|wZfqGNGwW%o!Xr6F!Tc~KtdM~U8L9aH=^?RNs0PUQKylKKGC9s51wr!?D$nO?EC<*ptf
+H<cKadQ(o0yinX-ECXuj}PxE##??%rcqo+x3kf!j52q;KP1$+cf!pFd@Q=NMnFG0Xee*3MnF$pFIGBc
+otUOXb5lcCFv=@^qKMW!_*0smSbjw<4N54e_`dyF4O$VLR6YYzT1p!CQ}seS<K^|m3NH4<YE7+zrs4t
+5avH(JGEq;ZrXjv+cY~r7gvOS5Y!(7iHrTk5R+n_B+9dG0rgc#{c1LUCn!4=0g?C4{)x1N{Dr)#Nnms
+g2*O&=Hl@uF421|*&gVJbo*c4Sk%P3VFFKN06`$W3}lyYr^IRYh?rS+&w*Jr(Rl75nYq0c?yXE~zfeE
+4<wIJ?ieth}?uD4~1lz&$z6>F<cIVGRuEeqzq?cBuY)woPTs{{TWCod++bjD2z;=D5dFS5JWD#gl7sY
+K#R*Ww4MBy<vDV+Ugxn3dmJ($9dm6n<T-Kmh)TQd|(7T<-*a;LiV+Mb+13qTc<We;(YjZ+3+|bvSB1p
+Nxe14$`YMzM{XdT?8HGvmf@l6{fuq90Q0snZQcA!6jQO03${6(IwWDzoW<eN;q>$N(qB$O+-y>*3jKs
+E>{NXVpGcSK<ol|k9o6b*$$Ug(d(j?sgS$^+NE-24SR@?#$`e5T3s6e~1QY-O00;mZO7>Rqjg%P23jh
+G{BLDy)0001RX>c!JX>N37a&BR4FLiWjY;!Mjbz*RGZ)0V1b1rasty=AG<F*<9?!SW5;SjrXv|{_PA(
+#i;OWF(8UJkiji@`HoTB2h%GU<|%eL>Oxeb4idlt@WQZru#zY)KEF_m>~3lly}<HLLX9om6)d=`OVmz
+wE9OpWBOOb1=FP)=suY?^*qDfJMwdolY2hZvXY+a{cDr<(q$Az5jMjw_d3S_u~z(D!!?NySl1{>8`$$
+wsyb1=Lcl#F0K!?)QVT`>XU+t`D8Y6@(=Qmua82N+T=zSyL`{heRBv330v@kh-sw)nZPYCDw$i5qJ*)
+5{G+?RLYgfv#GL7aP-{;%#zlNC1nJlExKg%8Bk|_P)?1gx=urkuEi0RQ=La4?T;9CC{&+c$+`UGUaUC
+3sy|hJG|4x>rP`Bc9J(<XD8juTe;|uUMI=^Bk4yvo#=&~t92|w9~hkB<K`%C_}+|l|Kx7Tm4FW8OP>!
+V;l_4)q9PCKDkX*9(SR6md|TWvaye{~#3Qpc+^nY_{aJy+!`b7$Fta$-p_U)tKtBg<B+$z)QBE!*>Zu
+`b-I=~o=qU9iy=a~APl&Di-r;v3E{S(dpxHG<cI@tA_?&CjB!^Mud~UOTy|^2?R87CZot(Y3r4<Xrk@
+CyIL_sK8L5u(jYN)7ylTm8uZQ9cd#bT2&A1Ug;BfzcJ`jaIH8mkT+cAEh&UdT9m<o-xPG2lh|3OQQso
+S?;45=X=g2wsH{krykOV$PMDLlP%>mHC|w%{c6IL0AD05<-bx`VBkIPegvdu5e6{EGI({;ZV@?SJvR5
+O~hTCbBzaeHp3~Ju&g{mz@q?Gnh@rN|rFK|s{RJUdx7BFxH7*O(}hI&GM+2(;2&=aUEYBQbrx?-;?tL
+N+_SgF++@H!kIl0?C39jR0AI7$*o6v?K%@T}?`_`KkX)kb2YfYb$t6uJ~|1^!D7D5~y1V>Y0sL5k<Ig
+LZ)F!y31mp<_T!)s(^lQ>E28w}q6f*l~k4nw+ueEpWnRo(tt3C{b!*QE8!UV}z5Zl&-mJnP3t)-x#PW
+s*b7x6RfcLEY5<AW%<uqs%e`*G?MaP8eNMix(gF$HkRI<vu2dG$;u?Ddqqn3XFlhQI0|0<zMN~HrI~l
+*Op616Z5VGz!wf&oApl7drFrOGvxLRD6$M;=k@;w0&(hFFF+tbeym8Jh_T@81x~Xh;`n0xnshj$OZM3
+eS`+dVfqI+DNfK8a=!~~wd*UCTEYVGX7gu7s8eike<!=a;ObC#XBQTQ$Ilr|z;ox%F>lvsd?hOhN~#K
+=Y>1JGE)q+6xJ-AbX3(r6Ve@fgGn5x_6KWsS0;9$D5(LMziH9!5mOeY}y<!^B^2xvWIFrZ}|A(7{N0Y
+ns5CT))OiFhUna;;VTwwZKco1$G=jRHGg8RWz`YAY=DH@vMQgx_bZ3HFhk}m{Ph+qca=?r7#BjNLRna
+1f>bSx6nVL@qzr_UcUbHE!=)9w!EpZ0cvMNm?7ighVCc5`*DOKK*CPg4ioHPp_R6}@B$GWp-?J`vXtm
+P6!~?YXh4wxlmjr6?FEPawOj>-dg;*9#NWp%XGd-%-B)}sh%c>e^*I;`1q!#@iP1VU|A25bjE`Z0Kuo
+q2YUb{SFuO(zZI?j4DCZ6`Q2msFS&~9+biMD0-cih5C-Dz9y58mNM?`*gn~h#KLbPB#(u9!XH1P?ci=
+qMOO{g(V8XQ6`BXHwhDga}pm)vr8>tS9+D?!Eq#K0^(cto4_O)zXMcW?oQw}UmKR4t?fHc7;X>(j^W!
+WZm&4L}cYLLsQ(1C*zfkBV#IQXRYssY-L*Wt+6;=LsM`XFuZngcefN<icVntMaV%!W81akxG<N4f;Sh
+fZ_QtL=tz9lAuhR;U|nSFY{QIt8du~03LyJ?TVIFFe@tzilivOXczJ*A~sjsKpFNt9wA^+lx!;UyBz&
+{etr~YqoaVsP6a4iosIaV5rCJ=*&K~ms4;pGK#K3Q%xZEA_}36NvanOCm=%OXI^(<akuD}i-x;j8Sm|
+Dhiq8_d!bw7E17m^cijZ7rfqf6P(!f)fH#gTe-cvZWYfN|ofEBv@fo%ltq#T?CpVZC_h_uyJr}wk23Q
+nCtE4{_AodBJ-XcK5#R;k93Fjk*rA<}&yI3vzhnnErD1ZOt5J){i)I=iH%xdF!HD+;~mV+55!iSQUFN
+FGWn9yHND=N3f_M@&#097}VE{F=v&D1tQ??Fqy(&+|DIEsn^+Mmv{ktGjB3M!9wYTLdTPD9u5LWJC0<
+q77DC*yD%LK*?(lljFUeM8AO>H^TSs5Fcc}g(lCY{GL;WqvB8s*x_8*AM?Sexjuu&E%v%jeBhwn<Gk*
+h7Zg1L48;NG;B3gGyakG2{d3yfiTZN8g|-I0<2zIWc0_+)L`nr!u5mD7|0G>}*@FvC;>?dcFL68;o(u
+LxsEZvximrP&g@JcC{{c-ShOr6MSA%d%RG3(k$<X=J?50r)6$-n~mllw149MK31V#r4)UXA2GbAtc;b
+A&Ur&s_S-Plscyg8IGE~g2_tUZZ9*ny!*5lh10pbt|dbLHWd*5;ujLR*r!d1TT%6nLW*q*bzIbw?;RW
+O1XQH&zdRW1OB4jP1Gr=FH{^6|@Pd7O^H*A1((Z*r%SOfhHZ(e7t>o{pl86O+oL_k>5x@#SQj53;0WK
+f@c@-*Sm>>!!EK7FYax{?anvFtRwU3KnIQNGMqQ!h=qGyOhC~d9!w1!)L3Bv=mN-0qlTZ%9TvPqaE2{
+Ld=^Dh_j7iz4AdFkj1xP3+U>mwh|(4AL4B8uu~shvon_owOfa-8cLa|;k}AnwcPlR{=y}sl6BusFLoN
+V(^AXgFNZL0xi<N|ssmojEFPw;}_W{TY+Gl}Tk+M0CdwdqD5SdJ?1|HqOqWb}NoJ;VP8xSH7J${{A!%
+-V8`6J8ztulY)*16y#f+(6XNF?`rQA%hi)k9jJy}pLTvmU2U)QRHWocHaF`s>hCAH#6|-hUi;;&)_m(
+yH)79zSteM?_oLQ&d%t5cG+nGt?&zT|af&w9Wi!Rp<2CC`$OkOe-Y}LW4U;Of{QF8~~B;8(Y)-!#cww
+JM8>358<VCz>YR=d@Bh5LFdJ+b33<K`#CnFke>;=NF>4zN(;bj^bPC|09k}NQY{dHgs!fzUnHk%SiLT
+z6#j;&RkFq#cG^3E?qyb3*y%CMXC1s8q=7B1H2D4H(!#>0qyf!H;IaEmLYl01yj)Xv4=(LCk`(3sJuG
+<Cb!6Y!ZaK$l<&hfksobg28wb90pbVtlO*10No;u_2uRvg*wQ%GyS@0-1-D8XP;4Wn!T=m53v*DnMhY
+NH)T(fw5;E)*DwyjZ-MbH03QWsas1-pm_Q<z6X7)ZdNJHHE`L2rL*PLrz#vzoj!&6ZSZsy@e8ohyeN>
+Cx;9czA?A^df$;<wjQ}+w(hM&sW<9kK&ytmw#Gau;r#|#OkGmi;>Aso~2i<)3Nt6h}ve4tip6({F=Gf
+w%G;E&fkW#|8D~UosnImKqfK==<qF8wv-BXJhEP8|Fa<}$i-4{F^p<&v}))K{5epEM39w3ADsC^dzOL
+8u+u4h#S#0LbnNlcp8YrY4L{Eo(EtU{o-@-Q@%JV;bh#&blk?&a9CFlkifwkKj=Yj3JL1iYRL<hp<nj
+;Zw=8+#<oAaD<xhicZ;huHq4}=&;BiQ#ssAQq=iVm|4;R|=^bbZKWl0;%E^LmwJC(+cVx!Y5&pme;gD
+(kSuF}gOn)q~{f)}qFS(UG00|C$9X?>4M;9I%dU1R6&ZKRVDj#as0uRdHkp-`;FP9W0f^%-s{4uW1e!
+F+#&??C(Rgq41DPV2Iej;FgfNZtLXUkp*Sf8YBV3P*Y*OAd?wLq~|;j1G~<K<Ma8v4mh>K3y{lFJrVc
+hMUBJ#f#)>NbJ>K`0swP#cAz=GWicsO9KQH0000802@m7R>e9LRN)B#02Uqq03QGV0B~t=FJEbHbY*g
+GVQepTbZKmJFLY&Xa9?C;axQRr#aZi*+qe<`?!SVk;BYc3t4-fs)Q8*d`jVhYHcj>}1@;1gmMELIvZ#
+{u?z%zpw|8bp>S4*-9&l~-A(6%5a2~&TapkU2+A^Vat!C2wkXC4`RAs`4N^Lf>-h`jZqz$**@Y9N2Q_
+4!rO09M*SG5%nwvub+*H;hHzOy{PO~T@i*L)+i+h7k3@D9Z1^&w%GGPenPCTgL%RXSl;jg_kARl=?hj
+rg9!r|)X`GIJ~%*`%2S)*5Kiy_J<ochcm6si^n6gz25tLd<5UjnHfv)JiwPzNBw)meqVGvTQz^W!FIA
+Pm81MI!f4D?dxJ0U4y=tQi~i!J48S_d&2%I>%uTqk};I#`oIcLB85rWRb3reEkq#-Rw~U@Eex|;ZW-4
+C_HQb+=2dlAIMWpA3>g87?3Oq$Nr!mG;Q7mUFJ4||tJmKzqxD`^#X{6~Q9?_rH_unEviHwdtC!iu`Ni
+|qG7`;J>=yT1A*w~r^R4itZ&!cIh|@CC;vWm*1WTw+7S8s5I&1BJ)B5rQi1Zq?0P=5+yjqCT>vPN~p0
+mZ*onLQ|LBhI!Kb(<hZZkXHO>6hkZaYK)LvEPCSGN@(RTalulMyoze@sM-T0T}EI;Qv>q^OGaODSvg*
+pOu6m<e&fXnDnrVFM^3*xrhbH0{Ar6uqJyhH%wF>cG}w%kQMpKrtgyG<pUxAZ?b#MpPx48jacsh@aEU
+Y}Fn_Dnuo$IHOp*fg=&#szSGZ{M4~D!g@+#nlOap86)~TUhRPaZksp^BzsX8GUrw>K%d=$G5AnnikGc
+m8+j*c;>?_IpkB*|@2y%m5g;mh+#gfx2AQEQBx9$}=A=5L0je_4;F++Pvr4(yYlz&QEUc{fhC-Qp`G=
+}ORuf6f3eM*H%Cc*{7t=~;VfVV8(go8~jB+NleGs5Jz@>}OlaTs15qr$?I95;cod{r1?2T4;vH;+6W^
+&bl@qASKb67aXWx<@+;B>Y(Kxh>JJ+}ZH7x5lEy?oligbk1p40@bE!dbK9^w0{iJV87~dD0T`d^XA(l
+rv5+A7zlK)2762^G9~+faO>;@Cnfo(6(&X<N0*TY2Ec)R1MhJk&s8!eGSfokjyK=;dS4DE63ICkh<u)
+-b&-Q_kGC`03K~D<U|Y_<jt<G00xZ~M%3VLz%OP5?u>Zyq;qSvT<@(go#Ch*>F42>Dt8P4OqgPFEdWo
+&6x&{qB9sPf-h1pJi!S+&(1#eUnSiQ<T~ePxOe-T(cuUNkMz7!yRrJ&$lkXdkr|?|TVTOd6(qrZ&o;Z
+)SB~H4O>ysD{wq)Qv%q|IZCd9`p<BaE-oH!Wwj>2$Ulm_`a8Mv;Oz5w1KQ6)#7IdeVV4QA<(bOOL}Pr
+!Y*ug&hT8lmJ-w-!1sUy}=0$bj%$UKxM(yjMH-4fZc-tB&^_K44RCPq0LgV%Qe|2`Y*NwX#R0GCWV%i
+;~?#xfD7SMUJp)Dw#{$85~+!VN`Y3x>1q!CivCrJ{^7bo4lrjWdR?i<hsHrxR+oTl8=Kl`x@HpfK*Bp
+Mqs7qc4Gf1uNi(Yk4Wa~RJZ>ckf*SPwsME|VWtteEDx<wWlgnM6w>l_1wjIF2S${($3(i&p_U-D9*c$
+1xwl{1cW7Wd_7trweWiAJh01de5N^#A4sw%Q32Ecl1+>~4;V2)`A~i`%0`>rZBQy_0hO7(|-MBgJq4C
+i!HWfHqWj+tM_R<~yO{1Z>YkO$p9o6j`P;ho9iWdWq9M~aYWdvCr&a|%l^E?-(O)5S`eC(|H=|tZ|rt
+W1PEH3?acp#16Sw?^MoHHt4S(b(=@RL6i*?yrveLcu(&Locc8OyHefb4q2AJ+%_9@-W?f!NN^+{o*jX
+?nM7dYNddWjVme$!yYMs7Kurhzi(@TgYh!Bf9jchfW>#JLbn3q-BNmWg=+~sflG*|2o6@NSkWg2X2Mp
+b3vrj?TX7(@P^63_%QeQ!5{se{0Vz6z>T~jDoQA8k#nf7%qYl1=3w9i!(bE>m`$Lo4Xu|YqxCqM!>*F
+`t;aWbt>4lfQr|#Xfx|vf;Lw5R&{*DQlWW;n1EZ?KGzhJhs$s^e<UdIQr_UPlqz0L^!3y3e;A$nW#?l
+y4s>^#mWBL1?G^iej8=iD`Ti|;PJzFUsmSxn)X7Lfd@o5pwI~2Gp769IQzlps+CY!G__N9puI(U8@Im
+2iUm^d-pg5TbXopO$tbbM$55dhe7S{(PS7*CR2b|%F30E@vEj016OtcknCGamxkDbeXfmrs52wj)0;e
+&jj0XwaF*gJ1JU8g-|aIR$smoM1;_#=ECST4@-tHaM3Il%e|T7kbPQsQp;$EkQLN;%dO}ytJqUR4hcO
+5A8V)29#Feqq{5QvUWwg+*d=12&%rhpPUr};s33xZ@XaEzT{i3c@D~Xx9#|$Kk;J4X_Yw|PACuY>K=L
+~29ei5l7K@$6Ot`Tq7@<;-nH6qw)hQF2Q_GZKZkR$FLK8~qABqzGxe*@?Iy#Ha<8H6GR>jSL#+x~mXI
+E5x*Z1BV1tzwfck~3O9elx!e7cgao2JXp#}Q$tHoC&o2;R#$%5^K<psBHuzR^WzkKofS$6UK{OvpJ%N
+L*1<(I#D`s?5P_IJPk!yo^2>OL!J0qC!v!cfqT4&nX^6T_+7uNK71mR+iWoowRhmp}XvbxCN{@VoPt?
+!VCfP#o@Pe(S{ExJwg3ZG?&Q3i36+b``6;Rv}eJ7bqS-p3L2%2)g+gTrm^>w5zFzGhS^#GrQg4XkGE#
+4~)S#Js3jS!xd!Gav(nrE~lCEA*O#<?|Li}s85avGGoibZD@FY3(??YWHEwg4ONf5Ie@Wh!Uq%&G#J_
+!JczpWG6wCQPhXZHGl}wRUT;MFGy(PM7*CoXWnrX*B3Z}+0|a)of7?iNwOfP#>F5mg&b+~P0Qq>p1t0
+KYI>0W>(rm$=4hZMt;i(q)gad^7=ZO6R6iI(nvW{D^=I{|IZsggA(RQplfx{O|2cr=YKJKC^(DsKXH&
+pKUEw()1R}6pr3kpthvZ{Rhq8tT>+Fj#pFo4C8!O_|yd;D)r|MQvs=Qa6H>Q%K;)}@AC*JWVbcQaO-t
+>yzq42<d;ildA}kuW*6hC|2{?)c6igAJpR03X;6Euhr#uwlaoMj6pqcJ*#W#RBT0c$m6MxPV$IYnZ_O
+O%!SGnkmR#V7THi<q`3a(%&f2BlME4R)2r-?t0oYRKxy*n~hTq?^r#2*0A3Fd1%b>3Hz36O9_3=8WI>
+&wZCk0LqYhXP5PK;etOgWU+B931yD-^1QY-O00;mZO7>PegReH;2><|fA^-p&0001RX>c!JX>N37a&B
+R4FLiWjY;!MlZg62^YiVw0E^vA6T5WUOwh{h*zXGMk30a+K%jv`&wQ|O7<cy|??Xlz;j};A#BXM_#cq
+9vel1^#*+q=5}_<oX-^n*K7&cr$bi^XDJp9K>H!FwZfX{69hiJTjeF|N|Jyb?N|1wk;I$xT%%!}4;ql
+EuoumfHW)>l#=zZ-yKH+i<m%x$v*IvZB|eDmTn*E8xc5)QJ&_FLE(w-%D-g>`i54S@7J_x`m$jqpVJf
+WjV8xm8{}K7Qg`LV{wxTTB{q@1&EZx$zbqUsZvcX!xQKjHvzdsvo@SDc>ebBS#td0?D+NR$(z@wa~eB
+)`EE4!;p1rN<H_6JShRcdjnt{%R}{KdBFUth%~0<`u_JGQcqPpDG!`aF!8amFqS<VA`u^?PH}B4lzwP
+V?i~0hv{ej@KnNizA64h<JxP8Xh9xKX!@)?a!GTuKLXk}&<&rXO7>DjWi;>Vd-)T=N+?wc~J(U=-GF^
+pevnWO20s3XiCdsF0Fwk#EUyEW^wU|+>w?RVwOZ#Vp5g7(bvKskx~9fHm>v1DnjlqgJ6Z@9h;Blh?O1
+DjfQ5INroh=8^5WQ@qz^;)KDpt~w_2r;(iR~QDSWE#jNtPm&}S2Ewm7=Fl%79K&!#dfQw5e+x*_>Ub@
+!qlpu1x`p^L3Ag%;2G?L9u-#HtPdeh6-kWob`CEWR&Jbxt?*Br!?3Kv;7JfQzkmEOusg{mg9$i@UBZj
+ZMGHPe*PA1TOIc*Zj{UVefIK4xrlwV>Yqyg4MTZSrcRE^1=R#(4c3>qEIm*=8_|Anu*IB8>i1-|-=U~
+VSr^z+fBR%TFCUub#Nu`Uj%o{IwN8B_ssurj;NJZoov>MGX=v6}?GsoR(4MUrlgfbTKoQW%;AQUKRYC
+K|Dz_NM)qKMR#YKvpM@Yy@^&Xbm#O<5$B5=(glrhN_TXaa+ac5>>{tqLsh98{qVESdJ9s3C`Aq1EiFm
+P<#OuQ;f<nIKE`<$@!jVEx5I(d~~u8#nofqdxULQn-OLFp9IT)XB9(^(Ku%!{!%-%N*+&B;Pi6dWNRI
+*4mA+(XxD@%e*$$;;dXcE_h<QAyGA3_1MAMRveoF$cJGZ|F!}~4Y}h!rnM81&6SNxJ(X3S9S+ZX`_4O
+jFM4Ulb2;h@>NAfpiMTO}rvNGvtgVSD6PV$3ZW2hYBB}CP1C2;)gCR6XO|3(Cef+>L1tTZ`TWd_J+*r
+L*AX!d=JiFFHJz1%;uAW?%D$i^vrEA!i?cYQ;t3NI)2qUmVk(Jk)RZwRuTW+#4)xE7jQM5R;X(4=CK7
+an4eZl@ctOEaHPs@XYgUDA2056Gzte(i;Q6(UlLl0#J-h{dV+aL)58jBJVZj53tUa*6&U4;byB0@~BO
+04RfE2|qE;KjC42OJB)g(gr0s&UJQ3i_sNS(GJgxFe>EPm`0=cgNq+Xhg#_|AjlQJ8fOyc~OiI|G^~Y
+f+sIi!eH)o35d)Hc*CvWuo#Lvto|N(Qk2l~LJS*g^-q3}PZ5?-3M5EbvY?&VC%@;Xn6a06Zqptt(U2t
+tyH*lKU<<AR^#Z-#YA_UYE~@E}wrW!j?kN%&5IdLnK$%w}iy%!~d|}q$nLVp)#AYFs4f?KmY&>>2hiI
+8OBh$>WERuO5>*9g;;DGT8(lWyJC3py12n6TI%N;8QO&VbZ!GLg1KJU3ky5_|S)KP1!E8fRDhl2>QaX
+~e!jg7cxp%$-(Ugb7XAabuT%~Yaj90H1}S~wWdAU;P8v<~gZ5F4-1kBG+{3uk!^V_*O2h<v44<*Vk=s
+6xZa7&puT<AjlQTIYAoYE%sd8dgE1$KRH|UqX<Nk4b-!9>KDJ>Cq?zsgtPBu30gzt;i!fKe!lk_sROF
+QWlM(A(V=!M+;0k#PEh3!y%O`+EaC}$9gRHMrh4fsEu$mhfi<@zJj*2;rjD0=(`Xxop&(1gT2zWXDpa
+zRn|sJNHeaiwZ#zGjMqe?5yhnz<0de4hls)c8*Vzjxh&dT6^&H3EMie)8dYYIEVxf^48iPJWqa)9pu~
+5dPWTM1)Q6@M3*f);q4(IgW$~rK91lr|XCb9WepSkh;s{R%>L;|gkjAzfEJqzr@JiQpaf!$UQW&ZpL&
+j(0FE!vUXk-gBc5fHVF$F()^@yey{@sVNq|F*&kKh{e1p^<#?7pm~m*8XXA^^=)Ta>O`{1jsDu*=5VL
+;nHl*dfBQiqpK*A{?*7N8VZ5Cw!oh@z>)b?-e6?DK|D^`VtJma(@ZlS!`kT?<}^&2<q*Bsn%L-3rs%a
+TKhQ^TTD;RL^0G#p~9$>nBvu~OILT$7$j=l%K_0q9m06qWbfwCzZ9C}w77ltAXdF=n@LVL50eQ_#nt4
+g{PJ#!b@xEmToquYet`@A&I|OxOc?Yb=)a+DLWe|W!W&K7dXNh~(!so6!F`2kMx%){{n5&VF?i(fPvZ
+f4LTYgSA}tX!90j#mKK}C*p4yF!&TWJcIwG0vJAxqC6t5Uv2!+u_E9TvV{ftL|rL)WLMMaPThnUFSRX
+q?DJqYj6y~b}uJjQ3A|24#8JKEit$5~Now8MmUIti(NFGQ1hmxJDJra0_`0qA4CSSFTBX#Y4{jfJr_;
+n;r%K-2(Z)9m-yX}Q5DR;sQ{V?hly8fp{Rs#0ZEr<mBK-oYW%l}P1MrdXMwzCpXZ-Q=>k)YG`(t_0J4
+f)jf))VS3nP46xM;f<~VuXrxA!*ROlKI7Cgd^&-;n+Vi6Jvn_)#D%h`#lRh=@a#_e6NW@5a6Uk&#tOU
+B^x;3mmOOsWUK*q10%|Y4NB{SQ&&n5wPn$c24J*a>m>t&u*$jGy`!Lg7Xm_8se{k3M59uI&ZTGOdLD*
+yOtBf0aw{Ik*Uc)yP!OdlzQz1<)zC#27du7(yCORZ={u(*lllS(#GZ1vW<N9yM#b5VnGj{iiZ->r)+b
+!>oeg;oF>}D#SUfOo1xxZ_B8XD?fEz*!{N)rTSht20?`bOivfy`%v4#+d^Knm!cbGkhDa}CgLW3{^zU
+WEtLD_DV^K!4Vj>^re{|3humUF0vs0J^xJ19>_Xb>jZDE$z*%>k-CHBTEM<U$65Z>U>Un;4yC=uZAb}
+*j3V}g9)MU)kyzKHQOJ2afX3@i!fHjs1NR-oC)Z^$6lR$_~G~vLa4}c@y&Q*!&fq8TCSkyg|wwx5|_z
+S=m#<TPxlShmzxY8LW@}BCC@PW@qY_=1P!Cp^JD9{k972x0Z<Imwh2j%|J=tcs=K%6=!Q#wv}@q09%U
+D-T#mb<zD#&?^t0dd7wA*|15ir?1QY-O00;mZO7>QMp^g_h0{{Tu1^@sX0001RX>c!JX>N37a&BR4FL
+iWjY;!Mla%^)haCv=I-*4PD41V`t!Kp7ca`Cm<9y$XlFkCkvK#>4lvta0ggW{uWZ937F<Qxve{`Zlxd
+_THie#l9b`0*q8Q8C+rd;|)GnN}fs<G#$h(OYYt>OuQ}-`G5U9WlhB^R$JyAJ_}>jk_Tla@rQtVcpVp
+&~ZL}xVe3Q_wZ{`6dUZ|3&u4gu0z}77E4|>!l8o8cL$u$Y<O%6;LmiR8U>CR&Iy&tET6|XdIz`UusGT
+CojMHG#F8Bs@TU6w`mwgOLtj>z1C#65k%UJn>mvjHodPJO((j7gGjb9-IYA^|b;e=?_a8sh0H1oCPIk
+sxctY6f4T63OWXH%0w}D<iPXxb?6mc_M=L*MApM^^HYi>;~tJ;y5D)!}UV9>OeKUI}nI05!JZCcHnKg
+qaKC6-)(^Y$eur?+@DC!e8?)yqYaCUK2Y$g?i}PmK<hnF^I?pIy}<;3TO!L@B|}F#MsVnRMD$3+UAEG
+(xK#kh6P81g8)T5Lgf#MfQ?UfKo*AH=lgx|EW}wK-LRz7%jDnL}np|^$R7N1jCD}m}MtulP{2;SJ&5|
+_*dJWLR3dBzJj0Hmi$JBf=PY+Wd(0vzx{CmfvIuUfZHMNL65N~Z{of_c+S9(D}<I~=aD(Zzv*CyNlRS
+V``cB{XYe>6i%cw`*B*tpmN9xM#2@@AxX6|qFW|{cX%i5B({{w4y(fQcjeMPQ<StYGsqWnAn*cc|gmI
+90XN8l4*qZ=@)v;q4H*;Im0WQ}$YyKOJ^7d-hX_?tyq`TSe72G*^Fm6M;kQAQ!2dSNbW9OOVx(C`KbK
+$mF^B00zuA1dNYcMQ3B2{O!Pr|nKs3W_Z5SRrp@q}{ek<;L;y3w^#*f2pEs)<WqvQ7g@Z=&C4I99+0B
+epTkzr3(RB4tr0g#@cZ9t>{wvBvXDIq${$M23uf%R6p$eRhQhV47rjcMad49f_IWzogrx5`+(@9E542
+SO3@R&7-`y)4zvWht`<2#TdDC0`uORXGus5FF0Q{KP30*4OY!kRpPZG%i6dAQ7m;Cd?EAI=99zAd3-y
+nqdc=*CVtIhar$zJvG^BIO9KQH0000802@m7R!z3%i5~?30Duhu03iSX0B~t=FJEbHbY*gGVQepTbZK
+mJFLr5ibai2DWo~vZaCwbaZExE)5dN-TaZ^7;9&EK6HZ&;a4ngJ?#j-YNQfxz4sI+vlxyqzKQg)4P|9
+y9)^<qa!8z6{89glbSJog+UH?=knD!p1swTfhT)wX>y*gje5`sclkN~1U6_BCyT!}681ZVGQ|C$$n)6
+tPz{FmK(bD|A<WEy*$^Hkf6TD0}t#^6K3$i|pplo7=^2+0ColMRt90`Rm2Y#ZC5h@pAD8c`%sfdQ-~^
+lL+X?#8Tx|Q{aqZak!arc(YpMpTr97U-sKM{U$$O|FjiVgU_95@ZVBY7AJ8uiK3{$5;D^$MPX%)D$rz
+GRNG_%v*)nXx_ai1iR1Wkjrk`FvgEAOrLdUQ221%Fgev^n;dLWizD^^*?{+OMtjVB43)hQl_~FTqzzI
+}RC<j|<Tq7!=6Q$8=gUZ>oJuu{lt}$xp{+l^a`Gj*Oq17qGgHYn>!1A8-DqM+tpB;|=np_Qvs?C+svF
+OIK8_NZ9+Uu}@opfuc_q90d49V^|)kogoasL@|%4}GLwXlP{2Vuo+t|v%7l;bT?fiv9UnZb4=NM&V#A
+jZ;}!V6{&XtzeQlNQqxl*Wmq%~wFsVnxtq^`3WTdAZ6esnCYt+je@--Syr&^Wj66%UcwMg@1bN|9c#q
+q~yf&Gek&`GALR(kB+cVku%UG_=5tfZx5!gwZbV^NIKfmR0Sx_LLiFABG1uUpgKTFt$2*%AbkEvO{*y
+^;nwNjTB@WEk}&L}BnWx4Gy9NLV8lh`*1B1(yWS}@QH|rUHRiJ1Pkj)}MpkYn6|gth=%S%>MYR*8Prb
+99A#JdMi|=k<%+6CtJmqRxKRSQ<-P1{D>}_<7Dmlq!N`%ODL0Hb?#+9@4c*12Y`=AGWD7kftWRhCych
+_P`k%+C91eh~IR?Iquy8r-h#?Lv{4&K}>jM1idd~nLJv}{p2TUB~Veeh-Jf{*v`<0F(r(IB62B%k25)
+e`LjGg=Tr?Ikh;goE80)%bovo#nx5>RMaU0jFUZT6!z3ToOuteB9G+ABRD18tXiD1>x+Or>jcucv`VP
+uHUn$E7n6(ff(sWK(M|j3K=@9A~w;4qG)!)1T`ojP@P{|w$o-=oyc_8tK|Eh9`<(Rus4;V$A*0W-HQ>
+IjFJ=(TcI%atR`jG#5CJ%kRu^0$&GNR`@qEs0-;kA${<G%*I74+=!sY)nu-9Tfr68?a}y?ZdZ<HkMDF
+;q6N7{IvmU22a%pP{VH{J4k6kU1D=Ts*x0u2Or^gF{)Td;$gEKvMPMmpOkk#P4v^SZYHWCkjKmq1IL&
+8Px;OSxU1D%2W@(m^Rwh24v&m+)-i$ewsx)<eeQ&<_@)Jg0wD5NIyImDix@u;Tws0Z&a0+Yw};Hzgn#
+~3R;3%ifoC3T-&OsYha!czD8`N#%oy&qfyHj>rKGIM0kg*+YRT;u{B8bX*cCe>gb4+(r%JX)1FwEPI8
+j{A^3WTgLDA<ba$&>LSfllEOKE&ok?8krY%x`GD8`Wkv?Z8)Q|tOICx?zCHdu%f|iGQ_g=9crCC6iIt
+w=nLF~KLT<)(}iC~p{8B^`<qXgo__Ro!g7pB+TYbqFSDdB3Xz8zOFZPvDiZus8q5DP@b>{3p3lF30z1
+}`gS!E{JyVu+$qG*Bs<&($_l{Q89t6{Y&S<RH!9g6Vl&iE=+0m=momqO%0FCbPGSW_8b~$?4yVJn`15
+ir?1QY-O00;mZO7>Rn5-6xk1^@uX5dZ)j0001RX>c!JX>N37a&BR4FLiWjY;!MnXk}$=E^v9BS8Z?GH
+W2>qU%{yuDglbx^rMFcXt#7L*0e?2wZMYFpe5R7E0F?8#dQt;_ucVD5@n}N7X*nd^6q%gJ@@dGB+2`(
+ZKX0~)rrz@DKuG0MYd9X;bKj;+-%5p!&psLyk@$XB}p=y@y6QJa=nIKvz3w!VGZSV(J-y)ni0R_%6%R
+0XsOang$-}*H@9wfEynaKAG)^ohTnLL(ZkAfTK&u07w{w}{=>{|Y<XKOZked0f;i<DipMKD!)qOkODd
+$`C9U~4wh*+5Ot~;j30fEIYsp#%hqwDjXonQ5J|P~n*~iOw?_a)oz4-mj)!SzuUOs<yNuHAQJSUH{*=
+&Z`K$=ejNX43&SN2)DuyGd)+*Yv_v4|`z%BlUkfQ09y&k=Xei8d-DXBQ5aYxtH2bZ_P}0zXih%dbY!(
+hx47hz-RAh=X>+NUP*6uUO^knG*&XDGRtE4P!==CDpvNzO<pDqN;*|+wbp~=@fv0e(*R%uI%Tc;@X^H
+I8t%NN+Z>dfT;_Jc~#`oUzeA!AcCP4HM9t4wf~LUxx?cRx><l50L{UG&KKe70F6T=>+OQ;-Yz^Cn*=w
+5*)3BV0SZ?Bdm60WPRE3!@)N2F8;-6h*X(Fhn(Pl`13RgJ__x5h9{l|wDO`<GOeV+jrYy@chj+PQ<(E
+Y%n-+?=<TW?D)SoY8Z}%x%mp-|?$HG(V6pmVUs$_Ta3;y?fx~uG^6ozsE#XUuUz!}6ulV=(l9GQ5j6e
+tV)9%0E>L`aYz*@-GA7w6%VRMrvjvyx1Uhrm;6%1z8>JXcJr2bh}GE1)3gmuA333MbQ~>9iqBMjknqc
+S|_51_tcgLbrf&nmkH!a-Lm3zOg#k0<^>dR$!nSvQ4vtOE4gc4z8VUYP;XNg|u`5Vx&<;(`0}u$!@#{
+mw4~!$AmiBa6NcQ*88oQNPE8-xgh61bl$I9Fq^J69Hiz{i8<3Q;CxJEKrSghOFj-fv|AQ~2AK7`0PT3
+u3MA|}66-W><9_{agFz}LVB6&agiaY(px9aVlW?6Z%>Ea3u-vtgZ7g@C;zEyG<Y){-K1ndzc!cak3%m
+j-Myo|EiwkUxV;R6+8DwC&GtBcb5@{dB_XK)R(Qr7;gVFtLdt%K5Q?v%rP^z<+YEJ%UJ0}OYq2XHNJ;
+Ve=%14gyB6-&d!y7j2ZmHHVo>XU`00wXd39zHdSgq6Xh!A4sk+1B23cgB8+0~V;A0`V*0oh_%F(}ZVV
+I{LjZu{%!2;xYH2dw=)K9OB3bMfVg`U`gnbJzTEl>@a~2_P<OFNJTwR&61p{Eoz8#k4Z{l&q3{bi%_U
+8~!I%)q#Ll1QZmt@dp%i%=09UxaMpOq}yN8!EI5oQdTUTT+$pL{$ZCKWA0gGW;a`($iz_OQGFc*FBq%
+b$V$=<hnwZjkFeR$=Pn8rJ2H%s1^EEgbj`ym?=1|=4c)<*aEnsQRzPVD)oi<(!U1!#?2P6866V=0j$~
+)iSU|SSdn-Go0GfJ7_*zKCkUvc^mIimyG;=dJP8<WmF@?h{<mU&d*gUXwG=##qoRgv`h5__X4%7F9w0
+Q_Wo(a+K*+&=Ue^J(-FlGmayG|nK$xRUd$bxI~T8ev2a4r|v9#ks!?wK*nlH(|FyC~kKr>GquK^)VDw
+yDL^8;4n>NU|&<_(xiIj@b9$beK4!0|TRdkg;xkXWX1mYdxJ82N+Sg+{|a&N#m>sj1_hgf;+56!NS|m
+j>91u=*ff)PLe=u^u}thVk_u1VkB6>9a_Wi9h(5NsCfuuHgwWwoWdARDAo<#plD0vHHE6<u2Eonnv@l
+5@}zi-Gg5J${bsKnJU5a`__@T!#q!g>)>1&LH5^*4f8?TBhv&r;@34p{G6xS&&TQQwu~sn+J?k9DIi*
+*a3%ulE1jhmgd>F*tYq`A<@lDqP<jBy=4xvlg85e)9Ty3UIncFnKUlZj28e2PR!J(&cT)rU3FU0WtC&
+#G$0V*^BVt>f+04S}~+L;Y31oV^G6+i?en!IK~Pq`5ld(OT@d+RJ3Rc+7JLxLx>8&Y#G`vsB)N;ygC<
+v<?$E>4MHTev_bS^lcCB#$lcK5ITY>wi#70|XQR000O88%p+8FRk9iF984mR00419RL6TaA|NaUukZ1
+WpZv|Y%g|Wb1z?CX>MtBUtcb8d390EP69y;zVA~s;UFZq(ZrKi1Bn+8Vz@44w!p~Dbm?@6`1IBVqe7U
+|B;Rk_0ZcwR&IAa-N3YaECIw!B3z#!yz|_L3B&VKJhRonF1d<F~H2ao}TMa-r1bdgEL$}2>LCfhzA(8
+nhgO44HLQB+<7#9;PI^WfePfC(7)TUk3<}-XVBc*I)FXWWv01*$6)rWBIw-Sz4{5v<7<?SiE9+}Vckz
+rMPIC5Kp4P#oNwa=Ccgl+@#ry2Ov*PpvQD_t++<-29q)hXwqYQ4lyM7fTyy<P_+i7VnUT&LJLd)u+C9
+AE&6clZd?hr9c#ANi7hB0Ekh9DepQJQIVxSBk9k!aC)W+KC9u_&+em;Qs<XH$}qnA8|{K1vWyvVh4(p
+^cOW?T#c$PP)h>@6aWAK2ml*O_E!B041lEs006%Y000{R003}la4%nJZggdGZeeUMc4KodVqtn=VR9~
+Td97F5j@vd6efL)o3WAjzTj{<Eb&)h^&;pADNVk1476dI(77<F+l9atp(0}g?sT*xMn-=whB@TykIXs
+-9MAay5iB$W&sP~IPtBTlD1MfumsXJlpihOLWP&Jb)a^E(RFT7?WnuLnlat%{SYlSpPB}~?@{Y~UKuk
+ZO2SjdHGBs<ZD+4A~o)9xCrGHy(7qhg;q%~VyfI={ZI)pA&Y9;j6mWOEA+nMn>@8^|Y9wbe@Y3*!ZW-
+`m!fzt@FYxzQ(HDa$`7`(Cwm{;SqX_Y(&Xit*#WyvcXoq?duK)nd6=AiP|YO^<W3=l0IYVoGaPaY{jJ
+kx2%5|H8g7rsL4wGIa(~7tBPvFFJC9T<Bhw3_{HtMF&;Q>a6q=CM$Wx4TycJ_(NN-N^6^FbtyCFLSxD
+cQE|C;MkFtlgyfwJvd708W0@6M#cio_pC2y>fJJxAaH{!%GQBr3yrjffy(H_O9YMD+ct{8Hn%h>_WE-
+t@w1Uy$VKG=MxXnsh^WzAC;j#dNa$}v<6#?d?0eR80^1Gc*cb))|cFG8QN(m6m=Ym0fP&J>%bD$mn0s
+D!u1Zdh##LGe5(<Ko=!ZAn(+q;rypYd?2){>Xzr6E?qbAl}XApB4;@gGi14`qx1EXVmV9#M>WlAku@$
+22ffNVZ3&t=EsO;5Hg2xeQirHsp4G<#dVRvpPkz{(5t``C%~k_qZsla>ol$n^uc6>@vg-a05m_s8Z}p
+d*t{J0(7!E-xx==rDKC<#|$(`okX|w;IofqIWo>11yC;j&n%lE)P>t1@5p<MoC`=GJLVg=xnoRilQYZ
+z*O&m>23Wbd3@+G*FjC}r1R<JI9jUQ77}>mMKmriC5mmK3ZSHl;$2{gK>is8BLbOEy$~gMNf)geoOcE
+_aTD>42WezpD>jZ|V0{aAM4bSmVWtsy(5X4}?7gBDLGdobB!H6ZcoKZ(pjP%qayA#Qnlz4)%1d^So^C
+&cUjm(kLMeaU!8yhUUO2mup|E3eqi^0w8iTDooUpRf^dfQB4heUi`uVE#0-Z+z{qhVj*-Hl`G=-FRGT
+)kfnt$I@WUyxGSLOi+c`18|U*YgM~p#4KWl{z5$*nfz-9CTeRef=6{*DTM87zyT%K7_YIUT7$j1|c(T
+1D$)B%*G$=4A2tB0Vln$b2@@n*VkV~<P{Fjo7qe#&p@l))deH;ph}f7gl|L^p6N7KOb%49AKtA$un+&
+@!1i8e4sD?{fwRD&bvo|}G$UbA0xS#hacUd)05r8|;*kDm>Iv<{L!HMH?GIr}kkAd&ytbq0%tN<borh
+t+o@Uhit~6>02*U==?d`*?E|^7BsW24LK*BWG!<0V7_<F^~Wb-FiTEF5-OimdUM)oja_}ne_S@IkN7R
+K+QPOtnteL%BD{)Dybf=l7_Ij_QcIpNsc<z)cHhZt~dyS{z+1`e=an1--a<di?QtUE}Peu=m2G%QOFo
+}E&1#3zcPxAMqNhJce6su32aq4VUbzQOMtY}u2mP#3rZ1U?S%vqkegTy~-M_-};e;vY~;0|XQR000O8
+8%p+8Q}91`vlRdU#6|!B7ytkOaA|NaUukZ1WpZv|Y%g|Wb1!FUbS`jt&0KqP+c=W{U!MZYOv+RuQE_H
+(AG*^{GLG}8olR1<cjl^Whk-~)!h|9<1Sv-~HQ)WZ8vqHuY$uhiI#ta?B7p|b=*O?S0n6<!%L|rd>$O
+bRBdLF8D%kO2V}IiJL@w>mT-a}Ap1^Zxo2&M-T>MrFRg6}7wq?a(2h^Eq@sm`=guUApGD~?fVHf2t5h
+LAlCwD<8(?aC%DiEI|LCuuy`y-D}vh9|q@r1oeRl$>lV}sK?&+<MJWg!z4Y^91UiPtiYMS3AV!z5y<b
+_qX(xWWnB$XJ9h|6w|+T<-EL5~`ZemVXjqq^H!^Zy%{(FLDKQjIy-Iv&8oFM+`pC%VP5;U1bycbtbl1
+A>L-i%dAXeT2$-B&peUM7kkY~rGNjd$2!qt>1QjM#<aw+$U>O^uOceKJj;p@CmiNtm(fq%8fH8hjYlJ
+31TaSyY|+@~z&^(YWjfTvycvx~C|e?jCPv7DwJ3g~XMPx_d@I5bMjO3)a}oZ0dUpQi-P`c&^wsJALXT
+Voz}lTmgl1OmeOSY2hM&x1>;Ze9i<SHwnD_ow{CG^y|HXgJa{Krys9(H*g|e+o>$m<7bJJk_12wU-$z
+p5^oQpQLZSd$jYI0t#VAu(hX_S;PN;gjrY?q5Ee2LjEQ^hnFiQq~wCDvP!7K+^npqL&NEaJIfe3_L+f
+UJJ~{QPy_qP-87e7br*efebi_v_#P{N#`CJZKGrpS)-Oxrj=j5@kCaH!HFzOU6uXK(;n8g@B1*9k3%{
+*fa5&Z$Zb9?tGPHvn9_1cz!ejLbov6^FGiwhasgB`NW}oL=F6_o5#<_KbXenBHuS!ZOSE*KGHn&FF(x
+Y*N?|@)BIwC9KtSB1qw*k#!eoGn;D6v83*iNr79RGK4{PlkOpoWIy~9Iy34J|WyGQl&v^to$W+F-Vrf
+>eB4bPBSGp<{UnauzXTN}YWH*WiR)$z2KM8hpGM^cC9kDFO-&gSa3V#Q7;g=ug*N?{Z>pS3>)*;{}$n
+uZx&QD2|MzL6d_-CI~h=jupR~uh#_#76JkJ<DeY?)=r+;lC<Jf#PIEf>KSg%JCUkzSN=FhQ?m;Wzc&F
+cq~5cGLrodGsKbxqTK?4@vLs<0#2ep`WX0Bep`pQ!NPiK~j%5MX@srY&=u#he~bQk8sr1qZNpnc{Vm|
+2W8%armzBJ0{8w%F_G?No~5WjY|nFvJEs^~S~9XL*l*B2+DkCKR;p-T^VzHxzuE4v<1=V7lS+YanjIg
+1|AbnDtrA6O2Et`~XpCOGIrAorzW(y=?4RMq+3BgLCkori%cKZ-z6R^LNB+G&eg485(c5ProrR3HqS$
+1yZO_2!g-fso*a15#AHLKAfKKreeq7HhCK*Y%gm%}XijGvF+-}PP`9QQ_x1vvANqi-e)dUSOQ3dA){<
+lxU@DolL_RWlUT`=s7mKptD=)Cf+Q}p4#@wg%&SEN%;%K+C?y>}Myk|zKUS{-RTSPQyNS%fkU0Wk2y$
+4O7xWXDaq4@f@1`sFATngZ|zq<jU^fX_%gpyQ;~?`9*T4ciJ1YsQVc0n?x|+$oeH0rO;NJi#a!s;H@V
+ujxVKF~}uNFh?UFp##97V1CPt>`fo(2jn$4EBG2M4QI=or_tuWYnO4uQ!-%@hYi<5@Pf!YM3y4rrCvl
+~NX(FAl$8lOC8=q&mTcy`Dq#)IMyU|GhFKnJLLek$lqyMqRY|lxAy}n>eY<>eJ#Nc0?tYv0sG%mHv!U
+_vG#be-p~OpAz=Q=s;HZg314f4PGPQWjZ|vNqXIgsKO|dYoLs&wz@Em~QHQRw}y$MwjgRU)Tqg$`(O_
+-(0VR4a{&fA&=WW`~o9k65UyBWBnX7skH1R7QaH#|>aBYp3Lqm&T-V$K@o>>-$E)*<X{h~L?w0(tENu
+l;DuRv?cN$_Py&Sm#-}Q$D&O?D33TQID-N>S;FEj}kS3IY)%nYpY~|Ma%SoBdxxlnK?NsuW3$DQ{IBx
+LN1~G1+hXNfaqKOsfhT5Ct^{c_QceB9P|$N0J%3+hwU;;WCR#)#l&Zc;0-;D*zSsh*=ihC+kI4SUQu^
+Q(X4X76#ztxVX>5f*Q<a*5W{#JOXR|Y);Rr*kq#^T<&ZK`it3B=(bGXsQ!01|xak=7NEL#|EL*YTr+?
+FG4Kr)m2t!1bJ3y<7h5?JH6kiK^Uc@5LYu=!%0*Sr!T$Z3?oc@OYr}bY~t${7O65|2b?_pI$noZ?_Xe
+{Sp_9@g7hzn8+|9CR~Mk<J(=q6rR3G7o&-0Fo{K>+e7cfJvF{J>`8juG-y$b8>}-)go2j;onB?sa|8;
+xZ9wt0|jbkJ>7Sa(stIHS8_vQ{~~w^440VZDm8ZCS<&CS22W_Xp>Wz%LHw-R-*9){3iHS=DgMt-{;AI
+Pvrc}WC@F6+ngd;qnD_;-~d2_Q8jKP*eql~P_yMZh=|Kly;MyZf-6~M`2k@q1P1Uea9R>4I#U=@_V);
++(LaOeWAp}~v>;^_5Cf<p_(I7BH31PdDuTeRD}v-HznxTrJk&a~@Z=f-Tj34JH)`_le>ls3`|jd&&VE
+6VL5>E&0|oAhOkvyfwnL0-AjJ*g2p#hSV`=vsYWh>Ak_?g(;EgzJkD3_Z6@dkW5NylAjL581$pHr>b0
+l>#hw%=%8r9hitv3aI6V4QET~l!bnxyYtrES%u_6zza$aQP)D)*YM(fD0#)a*^W2*H+2OVM~y<cDrcU
+^!~*gua+iiv~8cV<074{+WI)o;IhTlV9v-o|J+TK3(z;z<pr)L6E#=z^9Z_5wt|K<r2bvxjMk)vJ&H_
+O_mjuiCgv1B4;6RBnDAf&aw#ntqQt};;66ny!@3{rsDGsR1x;l%D?6v`yK!JQ~rnNm{P+Tb!oYBP3Z?
+>RozNkicnkSmA0VTh^SeX%e72rzk@{lQEM|o%0_c|plqY66%3+>Q;1^ydYA_4!d6n}4bU?6T6dqe7FB
+XQNZ!n8+%fpNGpYM+Pzrd0Iv1`)VNukO)o(_4eGm#}s{Pnr+izqR?6zymwVK<YW5f4?P+O859OL{W@e
+Iv6VhLa}!%zo#1*(BboE!wf!VkS5Co~ZUY+eHlh{m_t2!L(i$qhdMy*-x+C27p)%-1G_<_abbYzS&R%
+o+v1BKGkkVqZ#TeEdk$(@%(fY&ylse*8E9{WNR3F1~F+9<b+nmYS;ZY_#QlVuAwFz!79wTG^n!DEC!0
+acy^3z!Q_SS}xHTa#T3Ias5N<Fx4F!y%!8<;_f<Z>kR&a1V9fD{Xis07zl=IQK{tO?twd;=#_PVqgk>
+S70{_&Yg_Iq$>ApQoxpSM<ivGy36-OMHl!jnHYtUH4Iq#pYU0M}%d#b=BK0O9E6!g(KSsRmVs#sxXn>
+QGmH`J>n9{!m;WU=OyMy-2tWH0<akoiIIeru~tTt7(%d?%xi^CCBFcN`zHA2MXOHtxPs>+<g4_>rl5F
+}u>a*yVpv{9=9fWoPUaJD(@ub^tt-Zi8RL+OA_1FVMg3QZ_}hk150TP|;?S_4~3iPWJ!fpH1OU(*6s&
+P*w1(p-xp;|`&b!@3t5U!iw|%{5Uw@!V<@Yyl;UK$`0O3~d7Ft3!!WHDCa-A*UU4V0iH5cBYj`=(v0D
+g^Y<5mXVtHogF<?M-y$qakiD}XsHic2^7QU=EHHvG@=|d-QJLux}D|PcIilfijiO}?F?PZGK}Wk;-2p
+jy(;nr6V%Li6`4-!j>mUl{;@O3lMPSTq8YD%;W4(wm=-c2V1a1{PJ%&Wjkey@>{@s)PcKehhZLl{fx!
+Lrqiw!BeD1a4JxSfR`9{r}H*-JtLog7Bnp{dJ|BKSiXgHnHSj)Yzq2D)%D)p2(&L1UxIHWW}Ozm4P73
+^>d$R-1Qf<UNDQ-PIa4nsP1W%Q|E;8J@xf6NvOnn9gcCDEa+t)++R1z+J+DV?}Pb{*zegsHu3(-vcQQ
+(<q(8R&|6;Upi8A(H7T^Su**aLDL~>Y+k~pe$ykbEb2%fUlR{K=IW)+5arqljeS`62O9UlPjV1V_uoc
+Khx=Nr4)rXsfmfCK@RwP+(Qm~yM2@xXaqxOVuB3H6n1}&**LEmgxFNOn-L$ge*l4}6L$R9Uc|^@|6)q
+-;VA?3Fc5|p67Vv?V#MW7gX6!pdOG#8sfxB#FpIND%}nPhb#8S!-w6>bR_=&2ZrAd_R%IIDF59XcW=b
+i%06rI{UY)HRg=;1|Zq4E2r(u*kZ}DS_nO)~YFQ+EQvsfnCa-I&id_=p|{|+Uw_eD3mgP$hWxJ^Pj>u
+>rXvobq3tr14<TXD>AUCvq}rXXgQE6PP1*MkMI%3HS0P^Vtl0qolIv|VF!^-XjI(#?w^_nqdT5KbFdE
+LxQ&4Pz=|u`JiV2bPK1nLUK=?g(Tz8pNHqot%%`6X0bRT59&aOCcbQF+8xvSDW^17bRn8Ca5Yw)sx<=
+OCLVzW?jBP-PC@fZ5*1k{@u!iAI~mxKvSp<qN2gKy+EnI`MCFKM=$ImCKbSHrOy)AfVQep+DZOt;cj@
+}Mz{6Epx=g;Omr5cuDJHlF`>#q6k1|nr|IlZyJeB{=u;gLtvs9Pa^~qIyzIx>(8~dfc>4x=)8)V$XW&
+75O0yp5@2;rZ;=1$Xi}tz4d=et=l&Jl#e0(toZom_hE{K^%Cq~_yAjMTgCoY+j>jTX@P$HRwKL+@>&E
+hf<b(}{_D0eY0L|DHz>!?s2W~uO4(AOfl9?*8X18#YvEM3VpA{d<m3$(c6`9IBwF9?N(jFKa|Ci3bJx
+`r3fCqZAxXWihN^7#RKDRX5rY!QWl=3EoH1arj5Bp2@q3Xdo3?;T8N!e9iRvMx4L9T|Eb>T@8s<B-c%
+{Ojpts&{=)#k`$fFBM~d0c8j}wt`1s93RO58y%Jcmw_1vGL%~mCOIDpb-xa@3`!<VOtWIc^Z1(zXvKr
+M5x%c861NnSQLgA<*TB&X`1jUW{NHCk+4RJUB-!M_MH*!#p3D<&w(|^&Myl_Cb6qj6BXGb><S;4a%-c
+!;lV;lVl(~yio0Z*P1WSdkE9|hydrYxV-$8?_!YS-23x|wz_``<W=ClP(8_)4l?Lz}RTYYoV@#e6|or
+UAtm`<m#L(^QW#pfN0ld-N>LGb8`Z0q&^$HNm;nL{NbIze4Ub|T_Vk(83+Mi|Kr6P3#+H83z`&^Ku;K
+KGPCbuqF>tZLC)Q8toBkf|M_NrfUN@?g#4Ps^#Xb|q+V37uBUT<}i~30^dM))nFL<?*${)+)<G_TH#1
+p5vE0do0t|ysggno<AM#eh-yD$<jS0^Q&VVxB&81H;8+&!lsWbW%>b7XFS4<Q;rR|sMO_qmWVY^D37h
+!qenpQ(IbLH1z6a5GqHXgu;*-5Vi6ES9RT8>)q37)qf-{{3HO<E!o5M~Dbk^$6?2Z1!yJ-W<a0K|9MY
+_yzG7BeqYj<#13G|TowO$bqm2CVoZWKVzFyT!YK&2VIaR{dRH{Hff6BIa#9bd%N3Lrd_V2Sd%nY^#{$
+ZPnUc0THjKleJVa*$aL28%jV*;QC1^v&J4Ltv=<-;Evi%F|dZkbilBTy%pyqf7ns9TDv=6GZ7UEMr}9
+W&sto0R~LP)P}tB|cz{NydRbqC=(WtXyvlulh2icy-4a*4$zWz=Eqn`F$f=dB82VqU~1|WHy~{CEAj4
+(CYV=@?M<b5q4M)o*b$!p|mDtE>8vT!B@S<EG5n(;0hQm9m}YqU1(2-R<|+?+ptFi0ot~m<;0X()@or
+UMM4A8oN(jfj^;=9=EKqKsCUlQ0KmH)x~kmMG_Q`Yp3bhm_gswj&K}{K02^h}3~XEGxxT%m7d4DgoEm
+i(pWOT4!wJR?jUx~4F$d|MGcbpswLCc5-%GdS$8PoQ__+jcvY*oNTo*!v&dSvRzeBM3!DEkm4vi80Ui
+WK15SoT~I6%Z9V97q`?m%<vPg|Gg?s0U#i|X%J*Kb7PgS*)%2Z0t)*01B0>b>l(`_@-6D$beAkA8Uv2
+6OkQyAl6k0Hr;BJ>BLR)IrVy@UJRX-{zP#nk;l9?;$vZFv~bgMpp!3o+vbXVXKss%)nPco0L78O(Y!}
+xOw)9M7MJj#8b_=(Xx7pJ_{E9Wt)oFS{762*9Ou5iOsEc&^|FqT<e*n;!EY5g|wVgy*%6c*G#5<HHvN
+EN|3q7>GT2mR2pm0Fg<}ALEw!$B6#2HqRw2ZXLkv!y<LR&EqGa&6KxF;>J;Q!Cz$PB*#QaGH$gF+E6O
+E?r^;O8!<%H!Hkm3Y%}aL*al&+=P`kn-?cN-3cmWRLNN0H^o@TSh*LY%J2%TfYC+Fv{^$$9=A@Q^`9i
+FR5-DLSE>v4^1)>rJzt%O&ycwH{X0sFC}qjwawa@z(VSVak?7;n(B*8&698;w~&7qRTO#!Mn#LEwGE^
+H>?bPdkdQ6&0_`<zToBv&3_J7?U7~;5!%%OBq;GT$XF6sjmP|+JYgL2O|KxYfwFmmDV%;4GVtu=JV8C
+eMXMYj{p3Z|9bMoMLxLB2`sw+fuifSn+YI&ksl@yV{p1Vt8W<V7^w?~kU${P*u-sgv9P61GL=}y3>66
+GhT>El=W@=bcs`$WBQb}8XP^_!#B?fd$R;j2WFEKfyJM926x*Vx5!rEIz*o=7nyV``Nwa1`f9y`A@rE
+`x+$AN2*?QHetiJcy8^ctN8?AMWsheHS>%P}|(&mD8cUHdXQuml&*Slj_(b=GJ8*jKf<RRwQ7rzLlH@
+C(d6r*jMyUlu*gVC<#CtV^%2AV6UILNr&hy3`2E|Z3o23lZgT;%>Z=(R@;;Tjm%j0Gcmx1~J4cJ#JA?
+xAywmF=bj2QWbsKearQiJ1mm4_zWQ<Uv{bFky|q?zk>t=ZWmpbJuPfHBEoZ@uIr|$Wi5r?***x!lM@9
+YhU(dzzG_*wz5snl4@8gc-V`d;rVcAaVNsjjBKGCI)-0l;7a$RlQ0}+oBiB@hN#J{hzLKet0@!<_LK>
+~B6_L+3`p-;Mtv@zYj5>6Sd{ZvfN|SO4NxCa)&cyU$SIX&|4>J_(CS$ju+}$@kyI5z_AafD!M(RI-@3
+<Zz9>j*^fb?`;^Ikp0)V-5*9Gsy+?p#ihc9^?hx<s8nbOGwpMYKiu62U%Hz^a6PU#Uuz_XxWFexWBv3
+N@VISiZU(zF5e5J*C69yE_QJ3;0M|DZ}P))MPHK46pa=>GsvO9KQH0000802@m7R+Gz(-}?ms0DKex0
+3HAU0B~t=FJEbHbY*gGVQepUV{<QUWpZP6a%o{~E^v9xSlzGNG!%dDUttAJB+y1<;;Eu&a0LQsY|}RJ
+a(899$!X(}*qQCLw?h2y9NS51x9RO=OoF_$cFs9IAHVbA@TQf@kV1+L-?mI?P&4lLYPsEVu^pCD&o)X
+n#2i}OCH?LTuFaghY7Liy)pPQ$YipQ!%9gh|<-&l%S2^4l;K=mA`y(rFWYaKF&dIMr8&=oM68xl;R8t
+~4!)u*4To;3gUwB!9cn9~WM9Fnqvjc6JsV;NtZrv(bfF9Lo*dIU(ugGP-PSqoaJ%JiYac_!YSLl2PN~
+0<0SEFP-Fs3tt&l}izhv~Un|L$pTJgwi`a8c6X98~xN6ox7(4YdbS1+8>TPmL$eXW49KLk5bhhS=p>F
+fZI*N~vHCP>NKuqGo9RZ=i}!aaO0X0@>2ZwB#r$skVt*ms|~7`LO5I7<P+V3h?{7sGtFjyWV2^prEfe
+yoO{RZB@p!6I=RZPwVP*#~@gWMZk}y*`MeBO#`NqrB@v`1U*65Oar=ZN158{6#p!VHYy{F?;VbBadEd
+C4^dz`CCF{EP{|xuySv#aZ3CvLsDS;^J`ME-K?vG7sdIwpSVjP~CrcmrWe5U-U|CDe&0$FpMBWyw)Jt
+?|sLzh}7)Qqj!g7R2|02ysa*u_ai;X-g>6~|ifwC!FZOIe;L=z+NH}I}~Q2BTxI6Zz5rd?{y&yMep+V
+IWMO7h)`JY7aYHZ|L#Q(X19b>7SK{LbPhSu8$w985Al3WGWlw_1^JCd66phj^Y{;K36;9mHp9cmxB%M
+G5O}n`99(a@C2U$fRM#N&CEUoI-YO$&6in<-|J_c~oT&2#oZKrJo5r0gg+BEQ@1W?8}usGmPYjeZA)h
+{`8aaJ_&8CBfbZrL#56wnDP&j3x}w=x45rBbDRFE2pl|ehHWf=!}d3B{o1VqEEsi&L+SZ)1*}X1U9u@
+64JJ*je%i(i9m2XA(P_=ccLi3Bm<_#E5!r$WB_roP$q3WERB9_@tW$90UU36yKpDW&bybqSdh5F8Ja)
+lL`4;=e&{Exb$Pk~?*NHt-wkV{@jqK`@2x<C2ANzz06K0Q82VXOmu5NgUqTGj)rD#eAH4M@Pd?t&J$t
+83~qR!Ai$exe54bbZ4e^#`fDR7&#U0wG!+=Xg<X7e9!`g7OgCwicQMjEiAOIp;(SIfc;UB_04zeih<&
+gK;kKo{%HZK5l=_qel$xZKEx#JGzqizTJnl(I9cpBcjB<h6T4rKk_9cdCQ)vNY%$l%^at=4~1^8>=zp
+np*Oj9)X*pL0Jq<Z(=ahIhxZkz@>M8&NUD3xE-e+<=-Sp#{X~pNv47z(-zJGQdCTA0c#H##1qjqYd|D
+pQZr!(2e5fODH-!ufjFvmJ)~GbkU{&lWT3$oZ(#K&3i#_k327gNQ$wzX0%r$Ae8}=|!g7oP$GTzohI=
+WbV!HB?Am2V+AemwX-Udb)72LBD3f^ESt!a3zx)LX9MSgOege>9z5-4ZM1A)RUwZ?Hnc}X!~tglQ#v9
+@i0Io>keobF<_ma>k5_CvjA2aJN&9bQUo$oh+zCZ!Z#+RGlcw9w_fzRn+4(1ce<96_+5+B$LpMUjqI@
+nnmRZKbadc$gslJ&(AH9cpH;!#l79Lrrk6@>5Z^J=vn?L<Ta@wOAJ}F^4*R;VzspWjviZc~{|RscZ*4
+huS&3B1k=4&FwTYOod#twN6K!PKtS`>%f8Z?s5{%l_QpqEZG@~AA1X*ly<c?4JF=-_-BAZLbOnKtsQL
+hDS3ma$dR~t>Mv&~?q8mc)wQ@su|FSTCo9MBTq#P9<iWyZA1SCeq`<njN)+Q7l5;W~b?JuT{9IBToTi
+RD8?2Ats3xaochx(0MpBGJbP3o88txMmFWZ=sohU)s+xPHwC^;9fhJtk(EERHCL2QSbvvoaf*pz#-sY
+u&eacbn*$G1t0M4bKJkWxab#^spGmCxVgy?QT_%zkdN-@_DaxkgW<<830F{S8n{0|XQR000O88%p+8>
+_e6=WDWoT(JcS~9{>OVaA|NaUukZ1WpZv|Y%g|Wb1!psVs>S6b7^mGE^v9}T6=HX$PxcvpJGcRFnN&}
++3_W|5a*f;5}bkDT^swZEgY3zlPig5lFQpAB@0ErduR4RE+2N%I}}CHAb_QP%+Act<2SQP^OB2-WPH6
+&i}fVcU%9lO1e>e`&q=i}VV;=L52>uC<j1l~c|o%&xvI;IP4vn#EyE}+DkfkmtgAGWVV=s^?)4`G{(Y
+Aw2`jGHeKl3zlT?-&-A5&@HhLtLQOpa;Gp4E0xJtLInM(^<(JZ64FrTDCj{}XgifCPJBIG41Se5a3It
+d<TP1d)i;4zcZGWeF~IW3YmVlAg6r*{naP$OeRwy_MiOh`}!a9atUb>(~myj&D3uKD}Oa$d0?c=evwM
+e<GvF6_isYg6j)KWmb2HAy`NN1-GWyelTixxKV-&8iP-%#Wgi<}8X}RV24Xbf0HYEwV^3ST0xyf|O~-
+{6iQ#_x$U>d&{SRcNpl^f^7#Y#UToxRuxNTFb|tPCC-)<L{q1X@BJjdf{7GGd2r_#f5LkO!>|4DtKii
+${N#Z|lQ^SrOPBSnQMljLQm{~JLJa^l4-WB+X$d<PHiLqdJhH>_hQ)WhuJn|IuQ`)2;Ukf!Qf|DdqW5
+%DRi*n`+Am1gd|ZJ5$S#ulqhdK{)rKdU7q%jD!|N=GXp%&5rAq!%uvL2R#~E0hP&R_Y3nD8KklAZ;%X
+y}y)4W%;D9DwlnK=erp-SW4IbasiEtO2&4FzlV;X_LkefS!_EC+<Iy_xWkk?rykF_65yT+KPS8bup!&
+w#%zb<gvf&mZ+k)rNtG-KTk-6HAM%xFF!!1QjU>_z4(0C2Mg0qB&xe=m7!GVhd7%&jJ~ARte{n6=+X}
+#)(6=UMu5sq&5eilli0>MJ`Z#Q?wrtE+T0GaWUM{?9R7r1g&%`EUgGABD4lq@CrBK{_Z+smGXMAghQ{
+FgGme}X;Cwjso)?*AsNAwF$UK*(qt?l5WbMoq)$3TGukrW;V0-UVn8BgGFqYBAQuMS@E4vIzLwhA2!?
+G|dqH1bl+o^H_h3@eZz%^uu@A`mi@$#VZehHD>`*RIeDk0RCVkPsF|?^=aB;vpG8&;VVpP$=WUFKdCV
+ggcl$@WphB`PE%$z~&*2h4aQS$x33pQA(Y1x%eiTBJy=_K7UW!8ejPMGQ{Ju@mZ+rY-!Zy|WGsN^oKH
+k$w6Wi%BjDQ5DO;zpu9f`UjT7~H44OG}bg9TJWkfJ^%JYpd&^A1A=On`Ms$JiHv8i6d}8m7e{EmWmvD
+R>h5}iNETLTBRb1LKxR-UVpUULxr#wi>R;5<#^P&+Q5y1R|t_N3}X!6Nu?fSiC|C=xiSn=adOK*gJ2E
+`enHi3Q;LflYO`4_nf7!L3%=s=9Ty4VI+YW|D2yg}31&0->EnlRls7O8EjSvehdHNv{RhB3`+_rLS{z
+o$e2uJwL_I1dqah=pc*)5fW97IK(qhQ6d;N6@kRu4kuGauBBa-8ZcJC-qGuu9AOUB9D)07Q$5~gD=Jw
+vg8%rTJzvf&lvUn{M>2)Y80r}FU@<1T8>WEHK$#j|HHJA*{-`jU!Iz}^&ZKty;!;8L!#2K>W7;2J_N7
+<l?DuNM$7fM}fa)Pn%z#u}sL5mp`p3<~QuV4)SrSlptoN^5)0L<{Set?xR3x|INy2&zt6xC^?W4Rv8p
+?*`IlH+g!FfTi&ZZ`y3>&}o?c3>~}9Yvo%G%(vb4S%750+!sNl19DM-2TQ;`yA2aMlSp2Rm|-#khomO
+sv$*17KgImHQ7MN5ZGJ~;i0g$z4++>q0Xaa)gIiW91P@BKG)of#<<BobPGzjt(YZ+1QM2=Wh`e?iz-J
+oc463n*01{}adX%VI)XrOEVSq?Wwx8MCJ?Gs+#t_I~*dc06P^=>$NP^BleNECfDO17EJp}Napcg`UFh
+U9yiLrr_KkZ>nVU-yU*6OM)M6d%J{J}i_^WG{<ggR9>)TOB)X>;}Di6lM(twe!kZ=4`t0Dxo7E`Vi$H
+yvHtx$ohUU@#(R3J7SVqMdX@Ve|-08{VgmerW87y1KXb1t+$F?-9owu<?Lvjsgv+{GHS>(h*?yF|+w!
+cLFYqbKqc)UyGH|%KJFHxs1<ZaZuU=7#zoXK8VH)Xn_^oMF4%tY6Nl8iUMORs3&ORw@0!}LP9`1(Ujx
+l^*K2TUy_6~jhi<X3m=-34wX|)M(6_&a;*kNI-nZ_#D$%tc<Kd+p9kY-4~!qp`w7%=g>eX!=I6BZ;f_
+OvO|rCLU=*4P4*1@u;?w;+{#1BD(DjCdWtP_Ud<p+iFJNN?V5W^Gho^@l$=liWybI{TELAQ9v+|Scvt
+^*YA5(y38^a#lViJ(o<V?XqT(|@%0Q8)T8dKh@Z|?J~uMdEIF<N1-brecQMZEEm$Y}ki_6<!(yX((1t
+C_NTf8~8klWb2k!mJ>2A;|^#2mbkk_-C)W)GAWM!?oab=^q7+W?9K)s^TC3wg)wrHygG7a@3#G>k3u;
+2FKOH4Rt4bA*d4jv5Ycsf{``Yn*dXwP!&o{84f&v`YMZ>qCq=P!LTPuK|lloBlK=rOabYT8>~$bw%_2
+^TZXhn4M<^4F)KrAQUzR_Ifl6jQzE!677hi|1rOjJIGWx<+CyBZ@NW%(#A(HnoF`+9HC)uDc!K<umpX
+k}NCmEC`EQ0sNI~`@ya1CaK}`T&Ku>$cqAqPruZ#fR+bX2~Yt10~4Fv>aHYo@+W81moIr!Q`U1BqDHb
+Wn26T@;mamo$fMY2jjQ|Ip~Sj+><)QSkDImgc3m!#N^L-rb`)+=FTxY4vR^!~@X7-K#*bmTAcs9r0$b
+uHwu8{Bk?9OlKLYuO4$nv5{T>cCA4IJfBgf7`;4!6VMBSI)=KgF5sP2%#P)urD5^Nd#s`4Zcsn{!ANV
+q+}ZD<$9j?Cfm`y#5=2Voi9x+k;W(0^|-wP!>6*gNegS>3V@-=mn>VUD#(2}aachPmPVn9r7qOcMVGs
+G9FFxDoj>qo<DdrQEFA9ZjkFhXpj$RM%WuKI;gbz1F@+Lc!*mA9fk7L8O}>q5fymdPbc2EN<_4lb3KO
+9-b6K(&LJO8dHA7XR9#Q{pVMeqDFpLw1D=8+hJ?l^+<Q+u1J*f~mVqI(DJm7HI+-um?hk6AtQ_d}E^a
+*O2k}wRH_QG1_*p@<b??Gz|Dx)}bl}$LHwjtZG#6Q;zg1%#cJ#9kpHH99C-oC>$Ds5;jw1qCn8?6e}n
+}l?PSpn%`Yf@U`mWtbY>b0$IZu|hQF70m6hhQo|6yDr#qjc55!wN5S7(-AZ7X*-q={hXP#j4qCVr3)c
+c(3k&yt}74%4I#ZYbii$+HiRk9?iq&#1}`WC&y>Ur$J{a!M?3}^h(Hkc1w=GCdc!mvne?`Ssc$7&(9$
+Lk^9pZ(TkHAE#b&nLd7mEj$VfIaQ@h-FT<k~JoW37<D=*Ehfn>U3UYjkr=Cv9{B&`0wm5q3oLa^+0K@
+hDY+clkN_ia4XO~%ecL{jJHy@tq@yAZzo6}L|=Zlk*#n&&K)AKYIT=G>l1ECYXlP|*KhL}0rJfE3nSj
+&^wUx<A;^f(s;V9&=)dr;mDv-u!%cj_**7VFjy!0vJu^z)7i-@elpZ5cG5t`XYzsF20d)FOe4Qtc`%V
+p;+r`j`r1zBlu5gRNsi2WJoPtag~F<wyCis*P04a1V3JAd}Hsu>V<!%~1EeHh>{I{<q_o^Q!ne1K7oC
+jLKjKl(>+%GpvpG5N=pO0D)pprbTyD=c>eHmtC4=wmbj-6EN{{qo3+rT-tx?_z9AwRhwQtMH+NVQ`KV
+(d+RS&igBwgd%}vU7*paS6|W`SzR%kH987yu60R7+(iH0ztXx#uPAgqZjlY8Q<#L?b5!OVWL0;}*qo}
+*bCEGi9aAL3J?ADa6_l&mUThFmIsDA!ZU<+*>NU1T${#7BXj5Mxvms-_ej!9o_80gMY#7YkHR~qB}sn
+S8AH;#{RcyHFApp-VDS);wyhVW3Z83o6~?%VE+*q?CphA|q)o8DkuLbcCEolnJ3a5KXK!8Q=^z6NAoR
+8pISRDTV>5869g(iq(BoBC{4@M7lTVa+qTM`P~<OgrwxpE+dr@TBht&VpBvl25S_pq>r-WjnduqruQR
+t46IFvto}g&ndjH-s@R*KVZ8l|J&xUsmr2jm9#we^`Q7nR}LM>#Ay>ZD7m`&TSzXIW|TR?1Y~b)#{#)
+6zhjbI{`|wV`yitHqW#gAA57JTyq1-|+u00^GiDuD;J#Ub{SSu_nlHXI;ft$^oT|%V8WXf>YfN>O`fH
+sEH##B?0_F%!u$NJ(r`_SX+IvtrxE7RU<aNlfa2=A5-@W_r>@Aq+kC)`-6rX0a0YQm?9cX;xP)|R{^W
+zi5IB6+WAJ{E|)B!KGHq4JRnqL&)3%Dj_*M;cc086-FYD-7MShPyIVi0igaTKMql9)saM4U9BZPf?8)
+x}-GcSR6(Qio%0U^D*Fl$?%3Dm2@H7QNy7ooymu%v1$rRIr`j3B{dSUcD_lKUu`?fDNt-_s4rE)h%`=
+_Y3qnMRBCW#_i@8kLrhS4Y9D|cEa%>^LB*!zT33&-eTCp@QHo8C-R93O;2R+jRzYV{mzFyraR&O4AVy
+iI7zaDdmA~)t8+5%UdAe;YXsx78CX55+ORlm!PuqknmAANd+d4Vx0gM+n_uir2jsdVO>7!Vi@{JU&ON
+AC@Zd9=L>-N(Xi#TZxtt<h2YUZETib|XeVO+3!QTIlrgX;sFK9|1{GZj-Z&Azye|Id{8sG{Oew$N+$-
+e+lO9KQH0000802@m7Rz|znvV<4_02^5V03!eZ0B~t=FJEbHbY*gGVQepUV{<QdWpZ<AZ*F66Zgg^QY
+%Xwl%{*&w+&Gfo{VTXKa?^cj%bVE)_FzoUChH_S!Odm{<IF4$UPD$(Y&X|xu_H=$dV>7-t16NrDN*fs
+9*b)ru^wcxST9x;i%OE@o4hV7u2^1G?5Fb!HoN1E60&B6tlLIbbEdl8PBv|lBu7VLi<hjDH#efbvA0s
+$E4ArbQT2EG{zcbRl~|>_yixpU-N-F#_d5W=%=_69gWtRV{r**U{>`iN|9SKFZwq?#qTcI^m!fF()ti
+<#`KsdHT`L=X_pMN-)!*|S4xn$o+qE#KywZ2?x}EL)Zoe~EKi1G<aWp^D=<UQV%|s2rp<7y1B2@sc2I
+5$hFZBHzY_rY_9_z<H6r6_cd;K*p&*gRtR9~<+wQ7OxIW~CJG_r|-K!U1tD^wBE>Kjp(yne?&nEB@FH
+rwUxCgUG~21-9%<;88c%SvI$Qwp`K@;x=wPd1|D8F0tDyUVN25Jf0JL?a0VcW|0*+i;H5n#5Rjt6d`t
+u2hJ(nf;6A#^6{0^vt!^57)BU=51E!##!FC-sZR5K0Y`;%&8ywhPOD!Ocfix<sioEP}I%{^f5>e3RA`
+IbLfiVUv>pA;gWs7Z#SS6e@g#5)oo3Wci+AI?u`AwxAKm&>ml50cE8~@D;r6&XjKVk=OF%BLyRbeLFe
+e`D9eyY8C$Z;<gQT36+A;F<PAJB+L*#DzolohEUWV^&oU6^7hSt~Q?DhoBeB1<s&J{==4!!$TLfG3HL
+@MZHA5h03|`FH$=7TpWu*y)rU3u`z}v2=S=)4+!PMIgXV?W0lDCRg;+C_V{rJPTY0yhE0q_aALZi*K)
+U9nJq1anlb3H5xo*wdbUV$C)9@zFZ5NOl3yJW%WufmJ9s5t$F=U4100}7@jbks?iNt0y3tE}PgJJG<K
+n(&*Madr~#h#m{Ly)#!Jw*TTqoAtz60Gn5!DQ6*VVZu0-Bcdfdh?5dX2m~Vm$;lpj$fQTwB7!bhf;g<
+OCp42Sr*5dx>|V4Rme+e$b6$cR<BMIx*Wv@4@$@ET$&F~ACiB!l3#Wn*XI;%zk?(jpw{MBXAxHVmP3H
+H7srt7mU|E5IoFym7g)EsHioS=2>*S-I#HZ(QdH3lUz%4%xVSY+_(a_ZOMB+Vrih%w@zkwdI*)KopJL
+u=j2{bnBUJI}*WH4LVkJL!nW~hl7A%(Y^{go`pO!w?JZ|Pq1G~jl~-PbS{(G&j}#WzEKp%}tpt36XZZ
+;B1-f48HSD7UbNwtP$0fk0hbOs-R3XmBE|l|7RPX2Wr90mB3@u6vZPQ(xjxCav-Yok8`yJ_`mCS>$z%
+r~+oPtIJRbj)|fH4BbFB;wH0LleyBD^zwcKb7VD*H(Y9Fw&mP0yUJBN3Cw2{ypt+LvZMeCCCGv68^gR
+^`(+5+jj3n%5B>#GvdPgw0%bxTNv(EBF1a4E47E>o?EnlC30a&E<RA^&Y1^LO=S>ZbXTdun`nl|?lIT
+WMA3`Go((3|yqS&l$1YnJBUNQy;ei;~;zK7syo-9Vq0#1gn=fPd$Wb4SPt>uOSRv?vTy>Km9gwZ1q=7
+9wRvW<Uxrg}OFtKLxoyi~L<xBRVaU!%N|i#2;?T{1J+4jPU-{FGN>q5~R_3}jWbSvFI=S}&Mg7d-r7s
+fUGlp7t%FjUy6vLk|U{6#n;yztdI(41AzmuWB&DssnXKR~-%ciQ4f(tVMxKksyy9#L;Nb0{ARJ$od5U
+I%q!V_e|<h%!)#OXbsMnmSWI+jgH!ol&w(gISdWrqmY$iyX{)kQfC3ilnLhQgypWt2>2Pf-j~TwI@~z
+d(MEE$@Fd_azJ$6a;QTf@Ifq_L&%q3Pkd+SI2}@u6`Ri(kDG)rs5|<!)<tr_r+q*!<97K5I_wn)1!C_
+KlN9d_zQ4CkH_WF*!q!2cGjaNsZ>;-S#P1p#qhqv&5_}CH#-r38r!Kwji+88$?>I8Y>0&3eBMG9RbO;
+l3)b@G){4fZj>A|>zO4AESEv}pgK`Si6B%I9DbK^5D5KPF5RM!j=GMpkY^<em&s5?kLhKnF(1yQ<C1C
+`ZG&Sdfke;C~?P9X_4}$3@j!_ybd5;v$@3haTgE^k{+eM$r=DNisYjJnbYrk{D{>(le$A3Dnc&fF$VX
+uX4o^l%6VF%#Wg-JXsu4&OJ0#GtumX>;SHaq@{P1b=GnPvIc9Vbeh}C)Tg;;<|tUG`Mp^HY&bwzBu-Y
+7IRE~hQ)pDk-QHS?qHAag7RDAY*s5!d0SEv69*0OBvO{Ba*!rM1KraD~T!rq2k5^QnX{yLMW08<~3(s
+aO2YhqO?@xug&=Idj6`<UJjcfL2l+C#$S9-Jpfb4zz<VA`korzK#3?3k0q0sII|6l#w;2*Wt@t(S?ld
+H%|)Qd+bug9Q9hz`WiTiNh_G@?1I%9N`j(%t2akey<K)R+fJyL`?J`suE;Q(S?pwBV{BnRs0iN~syp^
+9qJO!#tP`VCv7tCcXw%%jaQF@U-tfpR$UWDgx9zGlaRc@d7;>374(eU^q%4so8vTG~<&GM~hD7(x7G?
+dE$wAh7rGBa}4@dlUCma{09d$ZO+`g&^jI(JhU+elI6Lb#fa@e3d6H-jS){{V~T3hX^Kd<v3{Fe<!#%
+{pfhL)QZJc@SPnvs<Xi`Nc5q4>Ji#;yfJj|p$p@h);17*$iB%NY4W)5Frr_PB?TTcF>)AYpZOK<1;A$
+1v<Teb2&m6uwr_@uls|Pd<GhAZ|<~pZz2>p^*!zmE@ZdASe5o#Go4~4dR_#mqgx*`YkF5(G{JXCGvaS
+k~JMoLg1NDD*WVxEzbYZS-3g}9|v;zrzI($Yqc@udP2WmfE+#kLCKy&co9w+_Q48R9p}V=Vpt<UP14=
+$y<rl=o!52Nc4`A6jlvcl>}%z2qPsTTydODF~g>exrODxpEPwkEP3A#wc{z<8&3y?r5m6ey^y@;{0d)
+9kcU|l!{wl5UGuqv^8<Em8$g^$u0zV7L)^U1oc26X^l*<4QLg+xA7l`H4$uqOFm&b2s1|@P@+{H44p{
+;V}n>=5Xu1s;;M-zH~F2$mXM=2;I{4nSZ#MLG$fJolp0z=!bpKDjvTxhPSVZCi7UO%@O9?P);9kz^Qp
+XGw|u{>cs;Vn0S9By4k)=vYHK~$H@};f120f2;)?o9)zM4B2b8eu*I2p6RGZG`3`iC=$Nx?$nY1;ft1
+EerZrB4J6<}|+ERK#~%Fx-lyED%R4sg+ko59TR)~o3ska&fUj>#KAZ8KX)u;N*NRXg{hABvrO?rHDM=
+*=JUxYIO6D`aMP-0!DS?xDUDjjS<vB)6BIlcz@6Wt<WG9c<an%nm|VD`2SsabU<nh<qqV@SLc)<?Tk6
+z2Im|lI3Md`!%?Sq_;J+o1?cu`pufb=GBDM+;2FUIJ7Is&e%SQmk@)ofdxQ{+!GUPf-tAAw_-5GM_Yi
+M());cxS<n6$cUR>$?Qz5P^J(aHm$-KWwuT}S|8`rSu#IBFw``Eb41hWfcFu)#1p9pyXP=SJ?oUNzxS
+YH(Vg@*1w2rPb|B1Z7U>+J*aK3d{Rp?UXQN{)G&@WvG>#ZSGGT%QeS{5-^{SM&o|HVE>&Q@zs6o!+^&
+oqj!k=AaQjx97N6fQ_+)q{F^cbZ|N_k&bGB4d0NDsv1HL88+U3xyL=V(r*Hy*Py*>`(Ki0d^8mpBZDf
+E8F;z?9gEDsQZGu4M%Z2Gcq_@<wIsqvv?`JCwv2vrQRnQBE*c?{4aF#xU2a^^m>zGvU*;k+TqE{<9v)
+w+v6+{%VlyGJ@-4710fcpY5sbh}SPLEaUcin|E?^-6FT>Q3~bM?xrvGpZO?XM?1Qt8eke*QABiOlzVi
+-A4vdAr~m?SWa~4mW~&~T43m9*OqMQ>?hr6`-tV+dyDUvE6uxiYY+;>6WVqh3avm1$soK37A^>;;#jW
+hx!M@c3TC4UEtEFG^fzuY0X#h_i;e*YCAyD5DDzLtV$Ic=Ib`y*vu5KR5s{4Gef;x|d9SP%`QgWSqwz
+V|<1PvlRBt(d-z#hPgqQ%33A&kuc5b;3tLhE7$&WwhKu2!+hF_7^h3q7@bjTsV4)CF#j?ZnQrd1!HJZ
+77S}WD{|XIJgGr;+AQ1KT60tW2=q+)V|qg@0Srkk_3N8@_;<#Uc)}a{A<;~>+y>>$_z;zc6MP5Q`kZF
+dXn%N=o1Ntmyd7@?dPZu_WHo`m6BE0Y7a^=a_My1x!)w`I~NMWy7Z?nG1?BAmJNDWGpe#G&i?sNSi(x
+~*<F8FY6~HGE-J4sLhUNi(krsUqksn=`u?Ve+#I7RoaT)BKjfU~<ab7ud>udv1y;YcwNoxsc2ej?5}#
+4THet)Zr+mJ3Cyn#*;}740x2`b&{iQ5JZ}M@wM87iLj?0vJ+v_kP5LsQY2v{7Ddpl8tjkOd4P#z#-+W
+4|>DH6rpgy^Q$WDva!Z6BJyT-0Ef?1s=qx9T@FDihpEc+!XxS6-<dTAZS1`}(P3K@hG{uwLH@jEC+-P
+GC<?fLJ=JMUtMJVBmN!o6;()2Tipc97jq_HnO|f*cv!k1z%&5iJ~&Q;m%E2;on3%s;^O9fyEAHh{cF8
+Y}+aHUh};TE2uPaV9LP2%&a)f>?{_{PGCMi9JJY<+TP;-59tOvcI2B_<sh91f>%%c2ZC>_J0B_XMw~|
+i53f8w%t<?LDO+lqzEQ$iKkiYa(;~d+X-Bom?0v_Z{erEV{6-hac>8HhMW!n(sevUtd7AVa4q9nK2bm
+nEpD+~Al|7>jR&pU59QETLnop=LIp|A;0%SHA&{c_*PraiM0_6;QeFYl$_0z9FD_U8|>g%)9)32cC*N
+a$J$}gz9`YBecLd)$QS#=6ePXE4tvD;CYL03tthX|*QKX-R*OOc0$AS5<!@6&}|17<+D1$#EXeCD>fE
+H{vk*-lq`SdV{b&TU%_(_csKe22nv>3M=28Yk#A<8>!p<7KdWPS_2zlR80i7s*2spGU>@V|MqvLzN(&
+Q-oMEzTLHZ=abB|pZ9zoVIaY{-w3chB5+K3nF0<))s@`$Zw#m@NMP|A&B5oUBHY-iY3}3CJ?V?e0)6R
+fP0HCpWlNIz$O&*N-AlruaI5!CDb#XU8EbGhG+@>^crV<+hAZa*Jf<YZb43&FBKFZ*V$&8NfN}-?P(3
+?r&@Trmerv6*>+Qu+4sXwBd#5x!ydI7=Q6kaoj@;_V1Uy5HCacAPoh`PgPFY`GG<se`HrpDY=pu!dP<
+Ne=n7pt+`&EDG36E`knDY_4F$6kUgyaqD&a=!0-5uINDICo>6ynHA=36*R-%;nOa+y)A;fb3)jWcs>n
+Fm}vq<b|Qh)VpdAp{=8WRCBx?W0d>kYkA3ad{&YSgX|@;^6n4q%Ak_xwO9k_K8ZEYqxm_QxX*&aRE1H
+b5Ny1+eFYgSv9ctZ6kKG<n&-NTcbylRK2tG%!Chc`Q_&XV&@tNYwxAbF2m$?E(bVJx1t4eC~knFH1WE
+ir{JxZV!h@N+!y?Cz)9)1AwQnYvC2I9>PxRmVa;2tp5*s~8d{g68Cje_M$SB|vB09G6}o==Gd$AdEb4
+S2>}wp~U$bZ-^6Ll|)`O;`hOQ_u0R}wn0j&jaR8Pk(X8um?WTd2Lip^aSI~YC<YT(bda!`ir=nzdyxV
+9c?`b$>vJ6`?bj2lME#b)-4`Sk#6E(pBa69K|sU*j;>*R($;fyH#%;~M1o`ucDV<}>N^ND6ejGH?0sM
+u8s*JUVH4)j;I9KcVxEsHQ{_lhD_@4A<A*Apd@HM9r5_nNBQbqRjaFF0Zr^^GFr(lpeo{Dav7KsY%q*
+n98HlVB2I`7vq~YuBFC1w>w1cpx7@EBjemWEJmSydq8^L*z*sKkyA8eyc9Ztyp<(4JDbIAe#2eG3B-S
+}6rzpmK}CxUJTjia`jT%SpdJpdg9n%QbjYPcVBSf;Ae^Tpo#-=C(a6t$c&yDEx{)!j(0V!)n)ogo`e!
+z4sE;MjkRF4LD}v`1J#4WUjq5Rb*<VG=5CiATl!)tN3>H@E)s6=V1j0lpzue4iZACD*rpIi%^@Q;@_^
+8(~bft!YALB!!$y@Jw9Nq@yYVj!Y3GJN2|K=<>`E3~67P7(VkkHJYL=SoO9O=tYQgDYV?#CJa&p%SGX
+B%(VpE37;<4D%8+K-q@EgU{C@hHKVNFJduX%(jv(TWxn)Eyw#6NMFilWjkDs`v{@INi<@(s-jWiF)v6
+sf{blxF4?+f0$Cq#jVh%)mOa8G1N2*Ef}SfR-TYyO2*KK+ULQYKE_Bi4`fxFFqF?ID`?(viatc~&*5I
+6h7&n9{O!P--L+WJl+4teoU#R*i8)3L5Gc;>=VFI{S9AIR154mKp|j`$|GTHt3x2j`%$o;k_tHP!X?f
+%;ya|wVE!k;=nj|^D6^%m*9Wy$9e|CC$0}Sm}XzosTR4H`2-S76NLaC0c(`V2A{9lu#eSn}LEpbe&Yd
++I~n^z=zh?JE71G%UvcyWs`uCh;*ztE24ae_{P==iAuwF9-p-0R>|9kb*g6hTQ=%D*u7@l&7c)3mt!<
+JEj&=yLh&DqLb6*d<HyWU#XC@$`XcXD81N^tw+DN?!7kSKL@gp!Had2CFcA8YHsr{a(xba5}5Oba0?d
+m#nzYp+xW-PW!LW*c`@xLZUG-{Y5{*V7~M%oD`F}X0j9QekZydvzHPL0DVzF*b`xfP$2A}KItS8Ra_?
+GYiXjx(tZ)u#G1C>ztTuYJ&DP6G(v0>q))AzE|je?5Qv@C__cA!dBwrvbbYCa`wRgZ?x36wUCT(d{tO
+$UpN}kopc%%L?rRAD4+018$iFdjkyHM}Ic+e;M>>dCCJuCmE?_E4;#pK7rsM8`Up`R*`#Hss$PudS%-
+aaXf56x_`so3ugf0-YWk_@?A~yxUe(;4yR@UOCYk2wF<sgCz(_cY}L1w|F9H<5~toXDe{C2Zwy4rpTD
+y%4RH{0?|f7t7?FZ5gZdr98s2GmC0XR0k_2k|;)TJVcWP3PID;=X+7g9Nh9v>7gB3697Y<_k`j3C)k(
+6<A)#4<sKYx%vW&{LNeE4bm2Yy!C+j6<fAo{}Pn`YK(;aXclxTKJN<(eaU{`*nB-r7ahE)_mN@D_t3m
+f!!M$Z`@k}it#c5LG9%tZ>8zQM$-3J2Ep#CuHF-cfyV`s?32R0)CHj}P3PuT#vOToBZ(yFhVR=J`o(A
+U{O!Z4yDqDUyq%qSQLwH41fXXJr&0#FifjgKkGAoKL5WyD5T1mEry9@T8@HR+K_>7HzksxTXjD1CI76
+2WcX0+QEg99F;<rbhs7I&vY<Cma4kuS>l`mzk}V!_#1E0(c`k-<H>Ed86QQH(|`gS&_;;-7d~BI|-D5
+fW(?S(?A&2BC&5!`lcvrz=bEdddaT-y>wN0bsB+4L^3oo2HiOtGD01dixHKMM+&<g=U@kUltm4dsCZw
+E!-tFX8=(T_y=B?B3+^CFWQJ!;7>0C?hA=yv0K~Y$@JADtAu^AJC<;qz@p0bveQfIxXi+<ji)Lf9q-|
+4t`EmS*M@!n;@vlYNe&b7dpstplr1lrAmNMi^H&!@Lf0DBu3GSN(40&YCpSSBu&x62Xg9L|90VOBvh~
+&`yzh}80F$=HFRwK}a1T3W7jh9S+xQfyg$zMr4S?(%#^%VEE?n#Zx`Ow|GV!e(K-U7ohn%#*IQSMZMp
+7*<2s^u}<O;9AD^|B)u(zU~>o1m3b$8FwSn<|6x!@cNbCp2(q{>`Mbm#FwZCV4rIl0^K@>IxEUZ2vZn
+c7qEo%QxGzR%X+*#68<V_=TK$A$&=#L?kI%SAdAyJ-h#DpO4!9o1Jo{`_0+ZBEbuFDipOyz}FO3lCGD
+BmMOjI>v=4lK3sMCu*LiX=2Ndkm=?Wq<?I`m#FZ|UnZKcxBrq59*p439}We=6Xn0jiMRwo(f4C^Clng
+ZJ!+b-hE#Shi3;>Q*Rf&OxS(I#Fu~g-Qnsuyul-%~H&kx8g;0{RM=Ne?cT27d>8&r#)E44ARCeA1OyP
+YmZ_Dv;gHT(|o&Hlo_>Ig#`7l=df^DUbrGT4LPs-n%>Z5sz1-zcs%n==Jfv|qp))@z$6TU!+E830}x?
+d<JgG^-l6e3d*r}=Qn@Y{j@Il}(~P)h>@6aWAK2ml*O_ExVfyZc@S003qa000*N003}la4%nWWo~3|a
+xY(BX>MtBUtcb8d97DXkJ~m7z3W#H&Y^bdXp<IcfB-o(*bN#W=%F9TAqcdzG?tj9M3to0>jwGneM3sN
+HkN~EQ3JcSI3FCoc{4*T7K@}+ZJOOuQy43h6I*=6C)JdqpccQW$rU+awgSq+8_`;Vju#D4!D?|iiQ2+
+6!kL<U#Ui@%WE-i|BzdDWyr{;hf_i6%on2)*U5E{d+yn(ng-~_fdAZRfB;58YrqO%oC0$!c4<&?iOV%
+lviLEuY=vwD3$vRCII9^!FvTf%(OIZe=t+8InjWfFQl*Q*H>DNnbHp6e@(pLIvcyxQ0B#*?U*)?$kff
+yBjs!ivObz)bkyb_hXCE&K{nnEKy)7kqd_Q#Og8F<46umMy~+)CXM9|s_K+fge1;^m#v8qcaM$wCoW6
+ov9QuGG;QD8mu#a@jc&0d^;}x*@S}>Tc1yl($mp2&N0rCzn^R|Ni~*-PNUdCEg$&;^V#EBiya*v|kHt
+%nkAt!z+}f9Ov8zib#P2B66fL-Bns_LvAAiI|@O=8A9dVIqD6Ss%e-JFaeYSTCBnuBJ!T<*0U7qLyDS
+xI7`F<-Z%);1c+SM2AyJ@j3@W95dgTPjgn2E&l>{IBtm4^cgj@(GMIYCjFc7dCEiy=I#$6+=AbWC!GQ
+GX<=~R{zg=Cu%P!yk0Tg@2q+l0+FNbGf*T|Zd;306zvehaHRHCiId8BZ)M3O7gEpogCu$<qppH|2gM-
+uA<gsM%^=@<>;iUVlW1O<S$Vd<dC%YaBU#-k1aPERS6m*g~ryza1pmp9ae>VcQa`_{d@xG0scx=os!`
+U27h^=wJ`e=jWk(~<M;qV2T4`04pCFH%(g_OR_TM#u+Vy-Wl?gCyfMz_j@M^h^5r*_TBMoNMWU3rn(W
+Ek?FUu=REyo$x2?%QeeJo2*08g1^fZQ#K!dp+)IePglX1?s96qcpI#*tTp!N^pSXvt^<~Q>Kv*Z32Ho
+A3^HPN0~fcb9rTZYdMlknt}F`l?G|JoIVu5k$O~|7jY5Z1UeqMfntUa_xW4ZFjanbd2NXmLyS^TI;ti
+3((Dw{#uQ=Ks^;7YuYI0N?{eU8h;!s0eFGpWpi_CH?TnIz09oZG_+&a>Pv0)#4z*xpdM*$!{4wraIC{
+fU_?6kB4PQe@zQo|93x$s!#z5|&1$0JWD(+K9!Y8#4#By_M5!?~d;bfVZ;22W$e)h#qT#|?>aGTVnxl
+XJ4<%8t?QLemYs*<cro2JltlJT>WIg>xK<gSL323iqu(x)1kA{SmAl3y<vlcre~b2d-8m3n<^SPOWRT
+^2<fKSc_+?<96hcExR0hW-lM3oAtRZV|NMUWMUX}6&Z-Z3>eKO`0v^^qaHDmO`t^yW`r=Aef{L&3B$9
+88PhlMdtFJZjg=v(VAPJ#&G60hgO#_D6Wmytbwv^96+0Lv!FbrkImR7v=ux>ThRG;F(<cVkjeV=~Kn8
+RyvkP=9&W>g-Z(zgIPsKur_YCLx8ncrq_uLxCO_cX-we;MYT$-S#9_C~u!Xxo(&%<Fr4i}o^C_t=e?Z
+tRDGMHf=R#f-RyLT6>vq$s*NHP$PpFX@~hH;-u`QKr%d_t319=2VJ#be%av08~A54OqIQOC0H@x7PD@
+wiLxweIC2mw811&0B*Fz7`TX&sLqT8;zk`%M$@-2b`H)x8`J-?=cf=AV13gyd>?cp4#PW1>j^Iov5`k
+zmd4Ml;<UBfA{=`hHEJYHqbj&qW1Z-7pKcNWrksc)Z`PV8_0=E#e~qB5~inuVQQZhq;W>_J^H*(Jk>-
+{CmKDnKYzbwnt?5v^6w1cU<OV$(dt1)t(oBSHx0S1%(qB!tEeBgS=#Q=!yD)3*v?7k!3Z?f#XJK|t#N
+*a$$SnS7mN*WhFPKVhisWn^^xx}b2_W}T`Q|_R-Uo{kC$|DnDyba;QOtn8be9WBs4RtmJQbI469x;%f
+hwb)EodhujUY!)gM;W!E*kQdb0<e3wC%znQO#Mm}}!zO{SZDE<8+_IHU1)G}Xp%&z@Z5jKFFF9~M@st
+Tg`o6#G~~n{slH24OAjP1jD#&JQ$}Ix4wX&ItYfT)dv{&KP+sbJ_sP6EUueGFSdI+1}Lp^y+h*fBykc
+O9KQH00008031s8R?_w4&jBF-0QH6d01^NI0B~t=FJE?LZe(wAFLP;lE^v9pJ^ORpHj}^mufQqOF_ll
+@C3f1o%ha7Zj??HqzfN|V_VRgXii9lI6shuITm9z#_uB_Rf=|hEZqAd5NMLud*j+3Z4+1a5QM_Cw!R<
+T~mNyi8uiw0WwfB1OwRkV1KiowSi3^#@B#on;7dtQDC0PV%8pM$ZQZbi_oUX)e;zpVDM`D&pDdL&%=5
+BH;M<R=b8?D5W@I^e$+#m{~Tj2^1N(FKNo6Uhx8qcx^H<1AD3pY(;FK~gP@MAAu$S89&EO8cuG8I-fm
+tt_KFa|>^#+Pmg^nhK=)tTZU$mVgLiA1JZ5_m{u1VCPx`^bmR4ueIY%0P4yM+)SCaGpXvklT@1#C|Zt
+UrCi)=F>1p=Of_<NPL=SkeFhkCnLmyy8LULh*XBi8qf%Ud#Z8CAwgj|OB8ITM3rL7!#rM8YZD+(vpk8
+QSV>rZ45Fh_|BzmWDTpwO!!Ulp3VLzm2UxH49jWgMa@}csFR4nb_9)JPW99>Ou`E@rveLO5hGHs}<e+
+Gfvs<ZEf;^-d*g@ciVi_k?XuY;JGx6zIT%Lct`f@lq7UN5CF**Nr{Neb67#v>0`(Px#jITbOf4&j`F*
+!WD`dyrV6o+TOi@%T0K8(ciZx@r}%S&-S0b=9Ri<9v&q>j&yPCkDapZy}<1LoQJl{gunj<101)j1WZh
+>edgk=*I=<meN;9=;!+jIVwl0jZDUt23ng@q8i<#l_*|YJBwh<ZvP`K2I*rFOPwR4?y^AeD-ky<s6?L
+pIzBdE~JU$U*SbuemXok!NP#r;b*AB1i2JP=NG?E#=m^J5}(dbJ{&{h`(xnl@cqd#7Y0>3IyoGlj>Lz
+<)5Bkm3F{o_U=0zFc@$qh9b+Pvc?kcGuEytQSec{qv#SZbj-alSs{;AU`0{up4kzPF6wAlS`6*Tt1q(
+RmL<TU=j+qV$y{a1k!S~OX#|268;rQ?bs9hp5S5$-BJ3E8H;Byv)U~ym*GcbyW1fIzbeF>J}LQBliEW
+oR*py@?okL+$A5O;QF2^hTN%<?Qxq~nNSfp!G;n#LhCE{ETDc2xQ-kGw37!&D~(;HN4HF_^NO#fg4TS
+4CE~TFP{1$8p>o_(-6%12Jg0Jn`dHCH=f4e(gB9{b>Mb_mB@3&UkO^H$T{~p#~t0&#9c{Aypn=R#0;{
+Nu^Nm;45Y`aGKamu!Yz=7r*ZT3E<4uB!g%ce|>!|4i3Z~Wbb!p?_>7c*8F#S*W#xGVeOB^+aZW-CIIx
+^j(|UOR?)3P5<uK68BuxwKKxcDMFzZch8KcIE|T$=(=+*)Q8H7Zv}q8z$x5eAR~bqfGfoeGyBz=bv0`
+@NKBmE6az}=#Y~^a|rjnD|nX`~P5ysK&u!Tp9m}Di}N0@a5kHZGnc@&^!ws4O1;euzx@G^8W(CNYkAD
+3h)b{y8=5BJ_344HrYdm;Xlt=bJA+*OKwM=JLBfOMAH1ym^ssDov_5kLMY_TLP}EAfUoEQP{E$Js7;<
+rrM@G?eJ$=Po#KlwUlvNCe_v4)puQ%1QCj$%bW-Bpvaa6;n3>92YtG=gS#1yHJ8PThLj}j2h{`L_(X4
+gyOZx&XQFX7Km8CS;JwGC?7q!%)~iZ=M4I!<0OfbD#{Cx&?}HoC2_5cnsQ=VKfK+D)(`tNTD}a$Z@Qh
+lWvb+l*k6Rf)Xu@PX`hrXrRQM26UMGD6Vs4uSy1j-97%8vBxl$69f)cy^j;&3Z<Msb10MSIfCu9z_H*
+bf&`A<skYGDVh1?JPYU0eD1A$5&N-J^~vZOv{&N*+SG>X0%J7`W7?hO1MC4j+XKshT4bu@8@>FyY2K`
+ojnq+c=f8u($8b57j9Rv%>QB{kb)n}cXDQ${xu2D>CjNVG8xs)#=(-mNUrfG)K3rGW{-ULI!Hh>?T?u
+W@)Ut)W30<eL#oqq3ZlLL5??i|*q)XuXb;Vp(>#$zxCjQ4{=gv7w9nHiQ@vqCx17gnJ(ceu|x*5;cO|
+LKF<Hu|_44i}=0(@=<2N5;`xt)>cE!I+y@^J;$g-qvaiDDmHCtdP~4Iq(-`A859aUg;>!)WqT@>xkih
+iln_P(k$gBn(>IlxLziqBM49!WT~Mi3!tA$<G@y(EN8(Lig_+7^%w!S~SSjYohaM+l075m4ifTiu`A8
++WTI17HhBdoI?G?hp7lV?*?Xlc@H_S0#5waZJoQYDyz{^rbj5@4yO{vx9s<h3WC%;hdxp~VaB^$KXD4
+8o;_%rpYY+GlTh5JF$?5ePq*!O=OC=3`!z#|p~&(}4$zX2dVv4_EE4c~BF!^JPqL>*T*p7gpdI3mMLK
+?s~riCu6QDGVq>UjTZN1QhfJ+{PLtk=N^LLn|8V6Wbb^0kt=Nz!WTpS|6tuukDSoD0u7kh$Z*7Nk_H4
+{&tB_ZPZyiUE~2s*SQ-=^FdH8jNo6>8?<2RqMFsvq!sMOPNuEa>nl`1bV;?&?^;(@_@7Q^rXf`;(0*u
+Pv~!z%QQ=cAgU3?<yKu8P#~`vE4Col+P%Hotx}|Kc0xgV2;v(n@9&KzyDUBH+rp7r36?fQ7iMnDg7mz
+}Up%iw^7snU-ulK|(h%h2UbPmp7_@3z|JH<(n1r&~9Hc`VUzZj_6-}B^D7(&+?q%^EmV=kKKV7UFFLS
+2m(YN5pH^h7*0s4C1|6hA~N8{No1|Hmi|15870G;K8!FJVv`BBj(Q5Z#_mN7q-twAgB;%&#S@e-i_H0
+RL-T7?@&-216LERT$Es%|7&LC6#5MUfatUku}vlA2cts-pyjG0x-C%bIhTAg%2D6v~mGqDo%@L--w&q
+IKwInqgLI|sk4z<8o_S2o=UA~SQUW&U9MU}&%_N<DcB!Swl$!(tHw-z42B)WnZQD{TQZezgjI<0^qSC
+IvFD~VU+qH0kW6b`jls<mD_M!J+1ab$#t?p4Bf}noG>C9E)sq%AUn63!jn0`Y{NENXHv1g{R2EZ2Tcv
+kttE+0zHL+CMc#t|v*Sm9Xdo-Y(JpN6XMwaAYtpU#wBe<_sO`|DA(k^E!z5tk%YMvVUig`@4;2=$K-A
+RH|;Mgn#cP}Y9@B&#m@_qZQ04^o=32(nQrT|O^RVC+cTEx*ETB9HnTQ>xmhEXCYPA&DyV^VLKESo>`A
+i>p?z!WTsr0CM5Z!+7%9oo6P2aFv0trfSr)NFRGUIO2dS{mnxr-mC;8zh&an{v}4t*o<`NH>$!rikk3
+@bi^+3t)DwUCT#saP^+7+5o75?KnlOaL^uY=uv<Xlu&~jXL6C60~I46!9;Q`*w2HDpy*v2Ryircnx{}
+6g|l#zI~0ym8kE->_7id~;vaaIG~YQs$AL@bC5Z9=B4s#g#h(QsRF>fNL^!@ob4UkoLK!8Ddg`S$bHR
+T!2v%QekmhR#?I2p_84u1BZ#-5r8BN>=r-0*!PHIqI)Itt?Sr^X2UG|Gf0pL#u39x?e!AGDtE&u1#yn
+O6OpSI(dPtzX!IM0-PAZlGeXi5|yB3>r3C)3W#CvJ2r*NFeI0OE%(QqpL{EhLM%(}5Z|zNH?CGKe_gc
+T@LsuZ?W6@Y98v&O`a={F%oYp)Z4_WZ_^sK5$kCw%PJ(t*`^*b1IV$fk(<PpS?H?CC%M-vWnm*Fq+V)
+`gucC=1(J+ZyTULenUg}D_GN@6afBolW=e?LvsClJWdVLd^KsSX{-t#W=-2*y*Qc$w@X~HBPV%8?-%^
+uj!?+iai?Bg^wn1zA@qWhxm>4L>h_1KeRQd>EOxm{q|)?q<=}H0oIhPSw-Ngzc*bA&u`#I&JSyQdI3=
+~gJAS@ctek8P9Y1-k`g;|iwdy}o&HqE!T*I~%H_x&qgdFi*ApdX^t~|b=gMk;!w#)1_6jIhNKGu-iML
+y3Kp@ZwTnZm^cdS5}XQl!`gNGFlfygpr>o?H}fgud*yHD*2xpajivrRJQ|hA9_r5ITzhVjx^sMHEW1P
+sgXn?<*+?WE0RDLeNLv)+mjuNkodl*3eqy&?cegS(V;tGnr_X;A`kcanwN?!rU(E6{Ix<;97E(@Kq&+
+2og{mA(Z^5tE-DkncTApG*d{mDZjSSIQnH=MQ9|fqi{*1iYiW9+B!PkMd00W7+^du`Kb-z&s^pN^I!D
+P29n5SqHG)=TVc}JyOUX3@=ouU-HaOk$?#M?ekZ%5AQQo^)MF2r;|FdSlW+b|JgGce<@KTCCbyErM|f
++JF<|;grCx#^iLcG{QoU;<)#NI0y#&cFO77TBn*3GZ`UqwL#ba0eqtP+77c09XaP_0H;I$76I(OQjma
+-x%ubM`g*sI~lXBz6E&~DUgK)^v5C*C}cmB-KSjxgm&r!;2x4ZaM_{vs9&-1Apz<cLzVj{1r)FngtcS
+2fY>?pa1Uiz8)>AB!hNAnxeTH0lC|IncdKV`V+3{Qf?!Sd#(OU#+@zXLnWm?v~wJd(V>){1|urKw3{o
+(400cY1lOgg~9PaA4!R`IK3n_geJ-F-6Z>n_2%_(nZ(mLD+8a}t76PdZKL(L2$Q8}gg~62ItYI03xgD
+XTI=S1J3X0P9F-lNB2;#D*SMS0_r*gH`SC+ab6UYH@I<lpRNEwmd-DbWy}vi$xvJ(Q(BJedP=iarQ=z
+@19#vhgcXrHm>IO}<{YdW&C}+5M2Y}k+Qf?HePBZf+f%bXkVuH;!SC<%Lz$Som^F=Ac9o$aEOO6H~%~
+f@ru&bx-?C=`jL3NU@VReJyPCH+es~H;%jTLrUPUDp|$a2gkx6LddE!OBY$!Y_}^}n4;0h`YQ(uiO}+
+i+ClSnm|f=?fSYWZR=Nvwx<~!40=T1{fGfCGPE($bZB^v?Zzu|5V%*#l0nN9zCbzJleYKVrs1L>YJlE
+%P>!$j+;kY7OD`RSFDr84sAy6p@8oOlXb*yMaT%(L7vVVsSid$$!bg7tY|Dx#mp-`?~_nz$JiE%NWtS
+`^IoXV`^grM1R|M*v9~okK)8#oTpOXAx_UZxf?GF(`?byey4ub6b|Te2zqf~Li2}-Ax)-y(-|ppWr=x
+FP(+95!i-*k+Tm|CoF|?Vg<-0Z<pz!#cg##RHSHb~G+B_WiJUKb8M(}&R!MuTr6FA%A9>L%XTIy9CU(
+WSnaciqDsI=Q{du=zfTf*JSZV9v3Zrk~Ks@*DM>9X6Zh}YR|F;HtGvDR)A3GOM)zM17JdR5z1iJMz5;
+KfTBwHu%=qH}2%#wKCtAOYE7!)r+3a*zKU0=T}9%H0F-R`Xwj4^VrW#y0r3GFv9`W6%+~tihhB>}_g(
+PD1+-;I5i353+^?`kxPS=E6{f{KqFZ^203^fwU&lCw87ohnIaWc%6L9x&ij%>N$+iT>mpGasdwEAx`|
+$+iybSOOVZ#z9!NQ7hBOhoTgdgdKuI&@DB5A{@hA_6GEh}Z$e4e??Zq~&flVf--Z&^@Y^x<T>Q)D5Wo
+rLXW>7O|0CC%%V*N~9MS&R=Zca1=JPxiKqV61<o#AX5I}jMbfbK^4K_rt_1^ahYIGxS^(+e5cdlRnj~
+fNI!l%&<t-Oc9mK`b6xRZb0Z$_g%j_!)QHjAVc_Exd9!tITwySRI5JY58_oe_0S*z00y4PK9`3o;wT)
+#);hzTph9CRmTGId${U8pNr0bF`SXDx<?D0oM!TRL&t1+Li!r-+2yhcSK#HceRBMS#8=F7=6puz{qQw
+LkELTZx7n|dKyGk+Ur|{f^RknO=x|aC|ByfU9&J&|Eevc%-FnfOb`jfh;o0`MvIOe2G_&FhBjAH*v{-
+q{C>;p;q=MIXKK0I{+g?{YfZ4KiEeW146*YgWw4+l`WivF4NIdhP12?7=@V&WDi>4yk`6yZ(O-#_P#b
+UdM<C+7{D2ZAZG4x}HczR}{J=PGLp(hrgm|hS+Yqzt^%$2M{Km+Ie<18qQJWH|suqd#e9x^u75TbL7`
+r2}OZCPFRSkY*rs%n(zkB^eWA8Tb4UL+N6|2K#-Sawh^>7b2!ZV5%_{mafl-j&n7w!>6c?u$@%Am6%x
+Ob_Y@-d+tE{4u8X%<xZ6i%NfQ7N_j9Bs`Z5{<9w(2;Rzs8ug>oUc#*D6m?XHHbi3xi=@eBk^4_5Z?)^
+^=OFlFh5Cm@S89PzYoA;nH+j@oPm*tM#g#ggn67vkQfr>iR66sQlK*gegwtY@Knw7dFCYLeEn91xeeo
+~8!8a>f)M40detff3wms;0c7E0R|U-Xwi*;KT~(+gbkxCo$1c0D2iL#HT_q0g+{Y8R=%e_@Y)7g8476
+wHpPNk;!wRydGYB#p$ymc3`~jkMERzS%4MTTIpR?=7p7J#aewyAa*o{^eDjlbzodJdhci1l#R!*N%-|
+=_n5uH0lbRd6`#QfozX{Y)N!91GAdE`6#h#yNOG#OACtZen69pkFcAP>}OSEuxfePQFnJY5=Ns1u01F
+m0BGS&Tj|70AJxVX9l#!d7P8;IM_iR&~^?TEfzQ<>?{AX9%IA5I$1_F_bb$>sn4NM{Hr?WVJ14YZ*mZ
+`rr+O)!pGvrzIB$NwsOf=&``-{~|L!7E<L3Jo1vhdRB*ut+Zka5Wqs4rLLR=P>@DLP{-=gK@R{zpI8=
+dYiMFAXVs0twL}bEfZ@bi(M-oy$7J8ug9ZRK9K+>x<7uE8Zs`fTQ58&^2SBHFCs(P3=QF&#dua1_K*z
+TUh#(Am#yr}Ku^wN6wNVIYcilPy4Aq8@Gg|BM8Op@J599+@%ak443|crK4KR0LKyxL!;W^*LAg;R+C>
+!9b4sE?sNE}J2lc%YKu}zIUNg<4G=;KN1U~EGhn<_&?JV_x1%oCJSfFMrc<FvqGusG2jvM6E;hzt49I
+;sOXHlNS>b(58i`$SDT%+eZ4s&4CO5vQiJ?W1V{d-@nI7$*kFditcPr_uk)tY7yO(ey-9tEK--ZQj^s
+4RGI5^y-Z{Xv<qMC;<=EoMXTM|5JiKz9&m^kB?>yqHGU$)$u`_kZNDjk2Uz|{a|S0fLfIlnrMi!2e_v
+BpbC`3eXaI2N4|WdJ$oh`z#u3?0JH|cXOqhyrZ@fJFG9q&ext1Sh^cebOTn!|cknQ<Bs+pmH9P(@cSD
+Sp>uDTRw|o@&_06^T@j$#Wc3?B^gwAi6$XoeX5;PK*g9b(omY`1E%$v)!0elwM;dM$CrFyK$hP-XW+7
+nnB)Esxa4O7Ak@g+{~+=N3MJgYi$Bi{`nk`q&~wG=|Q`5N0+N5xvHoycYAdeTaE|M8FAk-#5#7}B0mf
+^lT(xl27yQZxsCsM|j#m32@CZcSS_h!Y>uzrMaUeSTr<)-<1uM9_hj&%OrN!-nw}U()05I6S%ADn7Nw
+FE^JX#2%W>qtX(LMp8Bkomg!&Jq>~;9gGI?G+W=;&Yxi8g%6&NFn-3miI5y_NP%&YpHn`5PFKlS6G62
+at3ym)y2)+I9W*{Eh1JeeW6*}shE^TBQkEf|tqU_~tSjw#<!n%b*38z0XacR}n4KV<HDjEs$#Yox=m5
+|%0+{_@B5AV9%9g52ABk*QKiI1=JqAVc37(y2`so8cv!!v2lZgrgMBIKN(Qn}y>3mF9Hf=exnP$@%2@
+gUl@vLlGC2oKg>9ZihGlQyhHG9P|K}A)k#W}}Sw@i|?c)ASqg2SQIQ3q2xVeF}w>cL3IfRtyFkB!H>2
+FlrZ+dTOwm}!db5}hULG(G5GabB9<tvA)mYYGPpZqM|XtuB9Nw_A5AzoY~2but(uP<A;Z8m=K-kX4Kt
+bE(p^KpglhSi-bu#b8>z?2$CQg9sZLaK(7pKq|01twvJXf%1fH;SC*5kLNxN-?cD?MbW`_mMV)5x#PI
+GlQlL>n(;2d+gYsGFmYM6*bNw{l?&BeLSL8ldJuvb@chvb#iCFuI>+)kz2UJc4FvD;h~&eoG+Tv|G0N
+#3jBtumE8o(om3#L0m4-800;^2eUdBs0@CjFhQB`T?$9Yycjt;<EO_P0Zb*c-me2|v!X6~@z{Loby-y
+9;)$T;f1<=}Y);ZXvUtN^?aV?H|$xyQrWa9~7(7Q8orpQMi5_%zQTv+GP*21hfna3nTFsWq4(ggX0*d
+^g5yX=|ReyRLaW{YML2sbNIO&VW-3%V{t)(|Eln-xjn7d=t)~OVs$IM}7wDBSoRg000>JF0vln2qz^2
+H6iyAj{_?*Q&~4YNNH3L{f1nc0&7^4p$Y&kHPIA6ji0L|ul8Q#gKNe~B-6_I-1?83KF$fNB`V}}k*67
++A&acyeK@YV(qdp7#~AswnoBxBpiy%K+_2^V`mJkDBsZ)%a=Jmyp%AWi+k&4#E{MRP20qT@;GSdwC^?
+_ui&rF}o3n;hvdFtx$yxw_>?F4oLo`Zn3KL-Zgt>`8_1`p+?w!eKH<RGV!yq#5Be4emhz8Y$#`_fv2r
+=k8=CdS;q*^Hfg_g$FG&gRpgw<lAO?WnP#X#BNfFgpC)`g5ftBISD#M5R!5wsXGxfx)lDi=-$Du(l+B
+w%CM8GQVxj@wd8uH1hfsGheB^4IpnW;Y5xySE#ig?T!!_qvz{@Z=y%P-dt(W-%nh)Ua!x^*Bjz&je_h
+lc_558}W7lZi3iv($c89XJptOxV<ig_g0BPU4KCb_R2@s%fc0P$#hKU1MaWEw|5wvyt`Sh_TQCr4*Al
+@6}gART`pyEqsSFu43R8viYm_9=1WTU?L9ucTV}j*=jO&yq<qJ@(bS6FPe|$JMwfM?Rx{N};#5|&n~7
+2yv>yj#fcMwMGer%{F}7WyX9AY^KD3(~7;^@<@CMY8?9B~Vklqt1=u$P@4HqeDnjODj$1Y6IsS3wZza
+ybgy7r_9p}9CH1^s1mcyVz&aSksp$G@E6wPlyx_=@Qk^v@R`4zG?cYX^wyy>hzTss%QN!1!0c#X{Gqc
+8dl6ZE%YT{&_KIB5L$)ZHM`%l|qw_>oLrlDT!1`-L{b#Dx0=iYc>-9{GXxerwG$F%ob##p6j!C3Yh&>
+)i#W)GrHPV^AZirNDcP3GMcBDim|hxI^$TYO<~~&Yc0L_E4bGWqk=W{%TlLGw~DKhV@_dEMiW#`Q_-{
+v-dRAK04#h0e@z3La!XdR5fRhXb^#iTxS~KU24~8hCVU9AzEdd1d6Z@7MszLIJMu$Q{Fq4uzI4(5LwK
+}s@30g)a#7JL=#xETcoxcg8PXM<YO{*Evr*lBN!uZ5dOO7n7I5{xI73^xKM&86HaMp|rdCQKGxlO?lf
+#`24~}DbVXCh#!E?OnNJ2>Qn_)ov!~vg``EM=pnG&A9YY+O+B*rsjeLU-1eE-91T|-m2EmTO{S>g&0{
+kHXhzIy?}rtXY7J6t$e2|iBLFE*Rl4O;3*cAqO*Y|>H5oNBSXw1uWMbk)z(OM7(cf8BMQI0<eU!*O=;
+_;z~Uz%@3wZ6fN^-$Bz>acP!;gnBI1{xeC2S9oi-umn4EaeH06J+$wW!D4L_m(dIX8XIbCZE%HIj>K*
+zaUBCM`lFQHk+6p3m(AUql?F{uMr$TZ_oWx}@+&qh+FGRUwe4@-+Vx_WUfpy=O1pPyhz>c$&N3Shcs1
+`X3uE4_qTwm<1g%pBD7-p^Cg@EE(Foi%^3&yhrHAWEJ}s$H@xTym?#GuVjgn`KehZ9YQwRjGt7WiTA0
+jv49$>JQ$XN?0R8gPePlg7-xRSz~eRpdWE$Du&f?XF%DHH2GTWK{6$xtJOr<&uaETUqsx_f6Mlo9Pb<
+r^ujbX3e~9qi`W?A5>T>dBacU7pO@HS9B%cxM00m+8xwdZV#%wWYdD;iEA{s73Hf+^Eszjd=BwnmwcY
+6>gxEn-U7&5Q3BI^!DF1Ax&De_GnP!ccN!x=>}7?(2;pfXV-FX1E;w1vuBe-`#e`;f&$wSbj5f$GhWq
+)mxb<rm+s=8WZuL#99ETxGnd<GFnw9b{{Kg7H3Frg(EBwCDI=J37)CCFzf`R95pR;z(O=A4Rrst)x_-
+shDpTS^X9YC7Rf`wq(x~klshDQK@S5Ew(SBRASqyz->r;x*+Z2pe$u|}jo@jFwNmUFmqphdUut4-61=
+pKfV)4>qSVh+Vof$sSacrQ>%?(cBm?73P90}h%?d<8vL#Mo@%(|-vC-i%$f{-#sp{N%~1rgn7s_8gn@
+(#Kvc;+ZA6**mzR;(Wp$<JomzMe2a^PU6u`tCLSPGd>CM5>p2>u?BXKSH&ri~Zq9@dQ~_CJbvP;o$xX
+x_fQ8q}ipQQaQf!-WZG+CIHT&)B(Kjs)Ba8Y1X&#x6MxfiW37$X+QVq0=!v7(YYi(12D|y8cXGG0IYw
+P0)pq}sWhjdlw1_E*3bsC=%=OYp)b0rr<XcEDAI^{1CkYSAVPOB^<BEE=bgS{sGtHYDW|HuNyP&ZDY^
+~)D8>_3GpQ~a#&bQ3ON`V7=xWf$OZ_k=;|W8YMUH3cq9?u+3SH3>Z-2^{I!S$CN<=8^H^5=^7n_$zH9
+p@{!$95<h66;rArQ?BpWlA}hA;@3kctn)@D3!tK1%HW@PqhyBI&4D|Bxmhux2=Ss`e0oplD*)p=;sr+
+KFZ~uJi2TIzuOwZsN^p0|DIvQ82A|6F*~<L?iKkb(4U;2zVjX$6wGYp|yhBZn;ho<NF|@Paow<u;DF}
+81NUVtu*0AKx>WxX+&cPAVgCV{0%RERaRaUMj``hk-9@o`nIqx!4Q@-UqUv$^MX}F1BG}Y0n|-F`Na%
+9GD`YkiKx|r;$El9l0gN&a{KxxnaJI=C?SMVCEn90)AXG<j94rK?ZgLcUy=pIHnRwB=b1qe+VTwQ#A7
+?!K8P}cQh-5lUk}vip}kV`ExU&y+Nw8~-W}G&pjQ;v(2JoKLw}kgc+fDUYu^oGkSPI`KP%LdB3J7Nvl
+%cMWu{kD9+0MHEDb*_Tn3$4+;)4`pmkxp__mVot1O#GZA3*ocuj?U4XR_ua-EE}&z4FDoB7CFH%2%rC
+&`$Xf|5t6$x+~W2KG*+K${HNw~Eg}hdciZP)h>@6aWAK2ml;P_Ey1>u)w}&000`Y0RSKX003}la4%nW
+Wo~3|axZjwaA|I5UuAf7Wo~n6Z*FrgaCz;$X>%J#vMBl;zoG|<cmQM&BgyuR%^5nZbw=Su3XArf^LQC
+x6KIe<0@0Z6hA5hc@3+6)sw!(~5R~M5HY02i=&s7zva&L>aw#v?Ro!O!>8w}s*IBh(7PGdjR!!p3M3r
+1@R<pLMmbP5EYSvKB{H)eRowrqOem7UPWP7zPnk;X!DScCq%hj3rb(z;I_}TP&(`mk3PN&&HcGSz@b1
+!?d0pNSsT$wMWUbe2wi?S`>70rZ-4IZzq24nvEbeT8JFL`Z$SF2gx7AyGQJbF>C@}>Flec3|qmv7n{A
+e)D;^E$tH1C2%x9@l40^zb_vfqVR>ST4->Lm0LGt~w?^4>#+jE%NhfozLFFFB$#gCr_JfxTvd(aBW6r
+<d=Eb=BEzC<K}8Ld)e}e#1B=;r&V2T+H&Pr{adk0)P-4Wi}&ph`6@pv?5ii6#lro1dY+f7AM&;9KF)n
+zw1w(CW5mR+O#<rEY6Fk$&u7KIHii4K$T!ROSvhOXqaX8&V(!i2t9oA4#atJ{$u<uRX0`QZ)^1?!v)O
+qud)th&eDZdZPXN8Dwt_C3ZUPP>o;Ht9-5SfICs%C|J$zbSKyTiMk6$dSybT||T+QQ>FIQ2ypI}nvuJ
+f-}#a^{oWbHX_9J>ovRSS4NH<e*06m>gY74O`1%ClA>=4@Hy^|XRQ(8IYM&OC4P8SbWOTj#50QPmgrR
+k5y%nQrQ=Xk!Qqz0t6Q-X>I|F3-wU{3KsaPxGem%9>S~UKAInMeV)A(M(|~TKg2HQ0=v{vDMWhtTmr2
+ED>5@F{`-L`_~Ll|E|lqeg8UWp@wOPf#{j80kg}C@aL59PjAgb*cBReA1}+ii5`T+<!_t3w!J(2_t(#
+-Pyhb>>31)G{F@t*!h|2Ip9;W#JN-YwMk{N#q(4@zdL)SVdQ%r!j;$B4Vb1e+`0FyiYO>R!Si#9)Xgg
+!%X#==3Yu^-hI6$gl=UEB@Yh7Qxd}a4O(0`vs8N#9Hc?)z#(Fe7FFRB_y@%*R465tng^=q+G?ML*D9+
+Z~S|2=Qcbq`$MfPP*yzm&zLdf*Y%km`O{TzTccFB{tppp$EL;K)y1`iH!oo!cK9BJyD^e)<L}<Z4z#k
+8NwO);NU@vtQ>e^i{1qphZ)vp@bk6tT*Ma4o47C-3$e1nOe19^5v%RCS#Vn$yimqgJ~ZmA5Q1RtTK~(
+-0R)TfE;C~a9HAc!})Tt&fD^|T$b%s@AdQ7(=Y$@0Jw<5dQ<ddfqy9493CM|tbcf3Fk^!!Dj@H&y3BI
+G?Tcz&F3JL7u1nxus)gY?N<5Wd60`GS2}}u4U4n8&)mB9@hf1ec+0@VhYA|2Tfk;Ckpg-?`SY!<obm~
+8JH2c#Rf131qJtDN(^i8qC6M4B$b1*L!*>qY1v7Jtb4X_m>evY4-_HNeyYa>;@=>wSQMP9!xY8a;lH5
+|cng2Xd<#?vvJEnx$%k%fU1x`yw?vREAm0BNY-??1&#Fc~!veB=;;WKrK;O`M`U6R;V8&4$5L3A1u|U
+N+eovTaa)RnCeG2q=KMD4GTs03;rO6$QfMb}q{10(Zg0bcX(xiww>=>aLoOyo8!a1)n3#;i7*HJ-NxC
+MJ%lQ2NT^N8Au2P3(2@0KxySXZ(y&~JX`(g)D3$&?T<3(J(hyE6aSq9^ufKu4|VS#gMWu{8(b`RMchj
+}K6?9ygJ8Dc#rA>u-B)W3ocWs9pO!1?lbN?EoUa?=W{2z1u?KCnxtO-^rY#Z+1lVjYhGhdXMVkY~8Lr
+2fW{pR#wQzW9G(#WgH`#*`ZM`9l{~I2Ew&%AUjMD9@Em(C}RoV66A_sxPPVYAiy;wro!2(F!jh->=KC
+Sj&`cZS{v*>4VN^W4oTqDFA*o^N{!UBqNjj(U}xQU@X5UnOetE<(tTrDab+VJyn_VB?-k&NcN+AQZ&;
+ku_NKd40-wlNt|^Y3-C9cM!(f0L=uQDQyDBG65e4~g{Sthsd>^@`<|{(t?+x__r0kFZ-!@d?{bHO;7q
+yP};;MU=HPSsJ3F?p=;eU@r+!0l&G^2R~M;LeXTd1lUI+agjm65|4bKo6H@}g%g9l0ADH;h=8n8{Y6<
+fP<6cqrXPEq4MA2ZXVqDqug`%5QQ^@f16~TSFh@~lf4^r(o#^rKaGW7;bMywb?(t}p9l)Z(vp1uVZhM
+15>WAZUGwQ!SFq0|dfQq%)B2poyDY&^>J64at`G_2?l52>T$H#hFEQCs}g|7qp)+#LbDGF7e;8d^Xx>
+$KPM022k+d@!Btr~cO0Q>zv=7t4biS!NW1=18F1i0BYPmoD^Q(Y7pFiF570Uu9z<>6a1!Bf2ex`#Z_r
+eO{U_#KOgwGsI50ZQ1C*u4ee7xF@rQSUHX?cv~XFd`ku>WW}Ydf%l=eJ90$*_L9zq>B9_#fTA=f`>5s
+sdnM<U<@OmQLfqp<RZPUxOZ-x4Z~Z(JaxdtR|FToM6jQgZCm*-C%4f2hk_%dA2LiTtJI*ULfNQ<aF_5
+DnNlJ#3cr}mH2Z_OMCLcgS#|o)028rC@CtV?z)KvV!I|0To=pjN8`59lJkD~|RsiG8XmeS%=X#Tl`u-
+U&*xR5wa5$R8-Nlaff+3|j=bZ*2+;y_={p~%IR!4g3q1F&~DC<)W%tEM60g-&;l$^*5&&wHzG_a)kDz
+OD8w&ot8B@Dy}L2wMvY@$$il`IT>*jyl>%1H1_V8Yw;YTkH7;qf~X+;ojo>>STMvHk$iRr;}NVRxP9a
+y9`W$WJS1p+UXW1xO?f?f(|AUeFebtSgWg5Y#)656v-!AFKr@5^p(NXWVAl<2Dn;$(TmNlr)R6NqT9)
+v6^q9=R81|RdER`M=bGu)K$Ts`)^6P8{-cOIy>(HALF@aZHWrB+wgo#mw-GNZMP#i=82OjpIhV=41<&
+X!tzM!8L&uoRS8YnSpprzdt{J(M%!yLUBS83!;|C{a3M?NLWGiO!5VM?aH7P6)(P3%d8|Lr`lPY%<01
+0-<g3qmN_=4uW24k(Rx6~KNBfVC4b}X!jDX6!X``P6|Idmglo_O#G;8U}OiY}cytAS$0rxFMRZ>iVQ&
+7rvNGU&*TsQ6%A^gu`aP1c0284@Qv4*`@t(LI+Ga$2POF0DxN&HK(vC{t`_H#TE@@A${&5?J%lK9N4*
+#T_5$60Wz!z6A4d@WEJp?`*$5F&H|bQ`NK_F%!vGo+HhUWkTv&WcGG_vVyVbkYS$^Sr%nQ~kr^f1AE}
+`TsuOw-fO7g9i_GsgZqlkUhi$pC|+L7|(0rn-rbf+B&1<(`vP1-DpgJg3sa0AD+MZ`A~X$1e@#_y8Li
+!hq;j#dDBWmK*wB@3E4T_X7+KzJv6joRT-+!br55agb+`;uJI1CErHPl%o^>;Hu)5QeyY8HFZ-5DfOO
+QfBu63f8E2=PHoGiH`N+4S%**0|XNa2sI4$5s0o5KpM4WzG6l+iahlk&EO059nj`XYq;Bs68_gxg(dE
+2g={XhQkbaU2B)>m*wuO?M}_Qw(q<l>7zeg4HGOQ#9WaN#o*q;s>%Q`{={ko0z0<)5;&?VMZ&{S+8bk
+2wXk>)bXQ6Zv&T35VSIYipQ|Sj;C|_8ep2le{TnWaG7o9^*XBL8j!hD%<-ekTCUUGMOZrd$TzmVv`93
+?*P67cJI=BVnp1d?~8m9cP8EYS9q2VvBu~_`h`I4!#i(1(y3cqb6i}}HiSYaCl=XHP8_-;@|~RE*$Ge
+ahS<Y4;Oo)UzyO1?u+geZ+asW5bw%a~u<_EoU0Vk%8k~!E*U2S;c~!i}lQJ7VHoc=696Mevzzf)=Z_7
+1vx^_TKxdc`hj#?l?KpjNOds*{M{UiY3HwByx>I)i@;{hs<ANd_170t40QN~Ad6F{kpe7;BLyR68S>N
+Iy`fO_}SO}T7IbsHUoYrR>85m<<#itkg0cnr%7_?&`~bg2Mwe2+7^PK74VvP<ayqI}PaDI|!K2V?yEV
+DgY?#^;l-Ctq#XaKiu6v;k~sw>$`yd5b09bFHRJe$9H4W|-u_kRw@zcRWO;O=~llVmfUzfotBtv|dzb
+mSW**?BhnA%8C#$R%u7_g|8ByN?V>@F{TRKn9&oh0nbrVFjoZ@$(JdTDs@F&wH}42z?vg2CEOp)GKq*
+&SVU%7v7e^Ye#eM|(O#7W2ykoG%VEo!`A!VHOTpXCgctvE8Vw|ou{cK>GdJZ_YUgQ}83O6|C7xp_=oW
+!W5s4))#=Mw=bT`MFkD?tWr;mAevv&UCQO|aUM5VhxnT1XC?I6)ks9ph@be>kP2w*IL)=R$vJ=<}p$+
+iDb(W_jQtzCBzJN7dWFoLc+F$t#8T7V>qKz*8M>Ms1CvjhHyv$DIq7a^U#jiuezwZqL_oUSqI^*YP#K
+neZY@5FEg3YG+62|RFm0Tm1%yP{*4=ZH|r!bQCB8w*GkpU3tjiy_|2Hmh?n+EAlTOkC6KKn3r?>3vZy
+^Ez8rXQ+IttT0S{UoyiCe9CL$#_{C(EP?`Six;xqXh+#!>0vP3G;@k-AOG6*I9ZOb;>#LIs}HzaK!eV
+iDqaV-i*$aE>@fiqj~*P4wpR68nbgGvNDNdnU5!oDXmfZq$NtY`U2o3##PT~HAi7Yh<S7&F-(J9dc=S
+os8vke8Ogv`xn{*nxielT~5g@*9sq3OyR{#VU5!$B2GUoDK_C0WiXwmf!FPYn|fGgI_veC-iO~N*LE%
+AAm*ZXF|j=n&p!xvlYpah{u4|{tKa{%OV&N68>0FVP@sl6eg7OC1kQ-w^$7jhfR2OK|~Z0(fkKS)Q%9
+YSnER@$mtF=7;Oy5-`Em7ubecB)AuN>%}+w4;u01B%B82mx%4L%KcIh4idp=5)TfxVTa}M*jt0H-(zj
+zGvFmXSotNc&2*hje}~Q&}*-<E8{(u6W=pJbwz_0o`&Z7qMC0253_4T0X)RvD_w9e%T=+e_Q}NS=H`a
+VyW!Tw8JuS|PKCCsp0jl^nuNOBV{83Bft6{2?HG1c0rCX@GD%bXv1xROfP8`DnbpfIL|cgkVY^wwv_I
+Nw8C&lqX)@c*DacdH0_f8+pTVZNtWYYvKz$Rvgr<@GAyvE4H8om^YT97cXkA^7vm&3JE76;7QNA_Zns
+lj0zx5W}413cqz8VtF?vt8C=}WZg;`Yj?XktyZ>DyhaBgYq1_NQ`Ht@iA6X2Wt)OmIGmvkfu<ll2w77
+$E~`ClPgkO0*$`1PJ;xVR(sQgaDEk`HnnzXl||U12MU8L7f)=3#LC^G}5aC^L17gO@>s~Q&44&V2}>h
+VYM8uaK6`N@eZalx7UVn=E}8`1?ADB;mCqXE0pfBd?Jcax^beLN`BxF1IP;iCTfZR$<7YHOsD-ZHR1T
+5h*^$_)e#CFOz@`DWBO&N9{!Gw1}reE=J0YdtEP%7dL{8p#;$}KFkdSbF3yi+wYUPl2TooyS%1mOGk8
+?ou2qT-9)l15I>Z!Hj8#zAP6Q4WgdPUm$2#{jVtpDhVxIiQYX^s>UK(S36R%)WNLGwJK$zkgf~@5&%O
+5uGFu^o$fZf)pJRt$k)CrMm!e#)&kvi9cb9v}5)Kh#*>*Us_WZkYAkhd)Hc=_NTvNDmbF|4(0T>#d3C
+bK{tpH-_ti|lk(ZQ2G+t#kH=p>w*25~OdKgK&Sz>$2K3>}YiXf*-SGfC>%UBl})g6Vhug3N{sQkVIYK
+r6b!h;lYh}Ead(J(sqFg)?UxLXu0O?qn>rbQaAYKQO|SRQnmHtp6BqDDulXta-woC>1WS(ztSDh&wB|
+6u%MZsf^yQ*P1=V&zGt62O5fyb_bovx^~ga~4+Y?ZJp!v(#AL-O`LB3voGLfYhTk2IvtJGo*~J%4&ka
+538D}^3MxOM1H@aY|?DHPFPAG(gUp>!fN4?XJk)MD4)2qW*)5qU`|LPy#zkGvNtk*Q!L4dA<{mdN;%D
+2XI8`OR*+J`0WHAs-0kBoH(@f>q}za8JdB=8zMHtrydLd)_LJ8d0@LJvXbQj~H_G{7Q@6oM)3LZKU+#
+OMF^^!uNmJ%2WRe0ccN8#{+U=5uL6cyFTk_}GyX^XRh3-`2%Kekw1s{#by)Gvnpu-eFZFvj&V@>-1wo
+d;^C3;@Bt7lru*G{qp^TrsB;YEmboO$%w7zRrS`uBIxYvCr?;)%HPQZ$pNsAc(`qCg_&R%zcx;KQ@oL
+)$~Wmt`M=WT&R4R}!$tWIvnt&5Syi8zF1>F7!1SW7Ob6geotqzRT@<39mc=9ea(}F#iLW6%rH36I3=G
+tR9!~Q4e2Al`xwER@+e{E1ZHFdGJXFy#tQc99R^5MRy?s2NNm?qjB9n&cx2Rv4kzs!-IrYe`gXZ>VfA
+8TjiTo&zz_}D&$igtO8d|C``vLW@l`o`ou)Fa&5!~_RN~tu|{!+{r0tX<$_5--rH;w}%-XBV1<HP&XA
+KqbTHs@-_D)=F>6i{~pd|=%+ILzSyXuxbL)?@_O@N~gs$0}2rSz1W^=9ym8E3-To`PFGL&FBBzG_5xL
+c54Le(ck43(g-!AEQD^D>7B?%HG3MZNTA2lL*wp@R;I>?Pz2vYvCbxAOuEJgzRI?Md=1%+iWZ!zw3R5
+s7wCoToIH&$McfTm4Kcs>R21bGa5`kC=yMP_bOkp3uqXqc;0+v7@}er20jZmCOW+C`jzgGx+4n&H2yb
+KzM~4r`D4ve9!__gWQp_BCFD44Y%LUKJSUPb5D~Tc}*_pw{!pSY$paxsMt6Ip{dW9Y@n~D{LjMgyWbw
+M@&>m|;h^mnYPs4^G8W0k;u+F_B>5(@lL4+$T-HqT@ZQ9a;oDW4wbnT)rQy2j!y+vy3D)M3h=H6)ofv
+X5kA+x<~u+p$Ba=T8`G&H)=~05H~|Jxjh)H#ui!p>XlK?TJF8-%ed^|0(N`%hfpytYt%Jy<XjpV*TV&
+x>aXqi++5sV%Av3t(go>%I#3&VHya8woY3RU82$ZqLsr%98DrXw!m3jKrTiNpuZlND)GEGQ|T2RG?RZ
+;<!acVEHP3JGCU;Z6(i8%Not5qh@hP@v@=^bt{FQDlIx7`ERzkdxxY6fq_f?tY(9%Vbs0r-ru)|hgKv
+(mxwALN!D1VNcxIO=;iP#Gx&g5-8nAFhJ)9To_WZ!GD4yEFSf>MDgZ#w;L2~)gWHCKkR;M{M25;a5l?
+^qZ!y9QoeCMuq*;tWpju=_tjz)ba(7YBSPc)YQa1BQmDn!7Hb2l8ESdm=ZfD#KAzGq`CxG*1x?`Sk!F
+3MTXc3T&C^M%SKb<O+m(HKAjan{D4c);N+WBQ3rnZ1eUrqurH0p6JG#1q=uR{k?jLh~jvgqzkd9zd=}
+cu;n7kVX7FFmPf;wa{rgHrUXDD-o6(qwJ=ggD{q{l%Wj84#}ruMwRW=h$%+5n9U5s^I*W8B|1GUm!4m
+bcLJalE3*vnLfD1N^9mN{ho4^YMHa9;HTQB1ugcju@DW$W?J5k_BIAtIjT*B@%%P%q45(>`06!3YZj@
+ousv@>V?t!}<Ld3C=4Pho)4BYMoZn@;9!#89g>b5Ot^OfocFc^HIpbASlg-!gB1Z9JYGJCT)FPf4he9
+cjyjWZs2#SG6<bR#l$mjO<4fP=^b#G<SN2@o#I_jVh@E~b9k>1fbZ2wwE9pA@e0VhIeNQWHv3TQ-R;s
+t5gqPkmaZ5QY#X?;uOGBQo_?_^2X${NyP<@$8s%(P324TSC%wx+y@?1SiQQ-VSeI-RpLPJ8SD&(Kbev
+3vA=M$QxV`b?<Ud)&23+;q(3M*(?0QdsRG-=vHubW!%D8cZ*JDo<%oy7dm!HS6MUT@@48&t26>?qWaY
+y5k?1)17=j>DB1wZc^5{;A?kuWqVR|r6Hg;Qnsq)aws~!_q1QpyH$5VbitKU-3>xV?N?Bb+#zO$?+5j
+0x2y>JDKg8ZJ&={a*uc=I$rxaGGo0l{&u30P}XI)HlqKlnCrEi{0A1WQ`l$TOQ6*UGCuG<m_&5#{wq`
+K+CTYO7)=CSd!=z9c~y`Ma$n@vFMAu`Uk^JI(u87#&%_WTd^O?TO(m8GH$lRIK@XksXKjXU@$`i*X@7
+j6`zf06hgo^CUH0c>8%I8j*5KtYJavqKw|kmE2Y&X-?&fva*}o|bJR*R`5gNK~WSa>vq<ISo0t;{Cqd
+_K8w5cK_mjZ&hI;bzd&i2xlq|y-CAw%v6j<o`xztOA+K~+0FQk%QLmoVa_bxsjria2!5RTKJMTxpd(2
+?mM!(D2U9QDnxIOoCX<L5TbWqDS_0oX?Y09Ccm27Sy}>iU4?UDK^Q&;|;TW9(Mrl{Uh?DaeS=dk6L!}
+O)=Yx0-l9P!a7gA^|N+#<vQ}0w|M5kl5|A>MfF;sjMW8cRrIUMb!tr>4a^rZqu)HuZHDNK{r<P73m#R
+wSQxeU5#*4;++vQv1nCyeKWzD1SuZ4~~`(XU-5AbGBA+sM%=;zv-RqUK>_j`I(WamHMrEF>|SCCCx1w
+7(=HNb3eguKocO>z#`ng`7u|kEC7O$C1)3ebCu<FGJI?vGJptnb@Xg##vllhhoUq)w-qYx0BvGVt-Qo
+`tf8q3U_eFU2?l7te<V&E%8*{Wu7|`j64Iqm$x6|F|ec`1b*I;5xE3Yp2#vz*&JzTddGZ3O!{^((=wk
+^5CUTY50iu)5M3{?)UABXt_`GpD>|oDUJ#OoWQtt3I$522+28ZoThz+20d;sU6<o{)bz5}lYj)9JaCu
+-8oc+9V4Y6thPqh7PJ5q)N!==Ef**<TH=P_9bC@3v1%Q_f=Q5M%4c)xbUkEO_A;K`%5mnbOEw}4~8h#
+B5E6B}a~;~vX{fKD@IVtJ1ZqjErO(e$wOyzmFDulG1Dkmq-vJzC)bGkIwmW@5sV`G){=#6Jz?3^YLnb
+}nfPC&!2?&BOgx845b3pktZRNGV55#Db;y;$(*cH$q$FuEa;{7>pkvUFxR}H;(fuPRE8r<0x^~a*vk=
+2ZhmO>#NWQUB++v=-tD2>NmVnM_BhbeF1g*Or=UPZAuInI$zbS=CbAiW9P9=x43&|g5z<1gtdYie45i
+#@{HHH&>B(9eLB3TjOl_u#Llu>H<OV3@bhWNf5)Olhr^CqZ$?T(!=g)L6?IE1A%mefkIsOi8(+_$v~k
+3T?)cNBcX=3Fz`PIHGbk6FeE3nS9%omvi_Ql>I!>AoAPyoG*1eZK!+XLDq^_mdhtP(w{UuBLhyhO0f)
+A#JZh4zYFsb?KYIy3MZ$#-FS+wRJiLt#Y+HB}z0|8Ggj&2Oea`Q;xlOr00vh={*E2k|~qQL~!Q9GvO@
+RUYOG-2v)2yYt6_0#lQ&eBweqZxE60v5pZRN9Bz1|ZcA>=haJ+TZoTzT9me-gBOGz-P6nJ%OEuq7~VP
+Grh~ut3kL1pWh2${p>DGQ1eT4{T$<k<89WvsuXF~F>QYZu5BCu$vJq51gR3%M)P@p&gNA?cWTQ54bUA
+9`Mvvt2e{ww)1?uYOs(a_;kV(G@Jht^J><=P!v9ju`p{l*rPmS(401OvoK3_b>5u0*g`YQ@*}2y<Ov{
+qjB}}!`f22bAF{=);W_7kIfA#5O<FazVG|Hq81<HIgd%MTaMq>#e8U?8JXX5E68M~ZK58_rR@X}^A8@
+}J?S>Fy!0KK13;|T&qu$}?~P8*-+Hk!j=9g4y#&2diVu&v5v3VnRvG7reNu?!Ro-1*FR8qOQ`fhhLiu
+t2}XZAKRC^i18?Fo=I=5?nNe7;9jV_?6NmjoGtEytYaXDoZvSIm~C#1eh5OT%5tq3{%jWu>HGiCfL6I
+emXil-g!$MZr@P)w>DhB&;La(BOPRNp5iQa(a+&0(g~3Rj$4_e!NXr}xq!1%RkpDviG03JElo`r!F31
+M40htTHVET->PxY1&H~MX%BRpVZK+@%TLOLH$Hopar8`yNQc{j~W2|T#NH*j$nrdNZ&G(}J+B&AAK^m
+T+*USz$N3omGN4~gNw^xakxM<EYyo7hr8UUQ}=prLVdw(J(jS&btH)6_`2%9;^cESV#iA%>_ar&OI()
+5rIt$k;8xwbyLn^pO*O=$d=zDSbQ!<$7v-jg3zD;~p^=pHa7-GLo1&(X^{Lc^o-IBIiyIFOP8S$3b8c
+e$t!@F28pZ8)0nX*8v`-PUIgWv`*X*+a^>aczfulfX<G8%J+J`wf}y5$4daDK@rE|8FyJMyW)1(~>rR
+Fn69HCPk69F6{<~w?{+m%oYQGJJOMK65M1oSxqlLq2zlf?*VTn=|cD*VA|8>?{`>++rV}~#N0I9D*fn
+mO_`K?{sIZy+3JJxUqLURvR;Ir-_-*DEz|<rES`-LFP1axZi!w6CeYD)<vxWUV5xt|>$e(5c^QdUG~p
+o3yRp4SDxI98!!$)n3Pf@03>PNZPyWu-_X7EPy(~G}6Neq~JLQF5#f^nmvZRRiWUMC0Tj{xLN#G_6sN
+y`4O~RKQa2n)ym<Z#|n>L|NS|Dm>h3K-c)5&~O8Y<z_zu>IEY24vb-qs24O+s^=#AUIpBS%1Y3lZ*=@
+gRxd=Cc@NWC94C{6l@CY<kRYN=RLvbS5Vv6emZ8=NwyFC$nq(Y<82LLDPd6-8r=Wrq<pEw>Ua1@&@@K
+Pl2_!vvY#VQ0jK6dgv9Rgr{*adh8XHgsE{+dEphNl&f)3dK~m|o`Ok_y@HQV6Y$`nSBMg@#>MEdqDnF
+5^%y-kwzQq7lyZ(k&^~_hlnD*p%8M(yvA97Zi>IX*I>Xl!*yrEk6_M}DZr>Re%Y?^FYpuxYdG}$_!hZ
+0;7Fhd}4NaiA!O??{8lE8I2M>_rg1rA^L$vVRAm!0V4U;y~2M?0sJbkhu3N$xB4kPt3!=vq=8s5ijqq
+)BfAG?u&_9$f|EcCIz4EFo&>j6(-M9kDQDsL6=187>UO(2pjeE6(T%SsUn!}zF4AxitHrlm$;|49=gZ
+HrskYF?f}gZqdysJYoXS?s4-teQ<-Sb2f?UbO2dRv7Ed@V{8JTmiQghS8F9J_u509b?v4>#Ke;jgAEC
+_&VUefR`~*tFFBlG-YhVJe~IUy+B*ssW?YWpG{O`C~-ACPOq}>&C(iYFKov8v5aA*#<ssnYg!lWakHN
+1Z85#9(Fmp<wpi7V`xOiQ(wa8{=!yE>)n-rqrd7Ko_nYzTWM5Ybkct<Z%ks2F7cd(Df}%xOi!{2aB!0
+eWF;b*UqCl>)hzJ6eEwtF-a)`3a>S~m|Ew1>cuabPylkD~+C7*xw)#qQ_y{}(S9{lm4>n}X4Hf&+mZ>
+u(6_5~#L>9VRtHmjENy{5fd77i%NWIJS1dGz4RuXpPtr;2u7!4EqoRiLS<l}R;|Ct({n!#dCH<$19Zc
+Ndd-9c3w%iQVLeF?uB1FJ71&gGXQvz=pytnMj9DvCCudZoD5pG(aEcIavy_w=){q<#VK#TJ?oOlLaL8
+;8C$6QRB40#NykMb5JTU0RK7L@U82Dq8_7@V^%?HluI5nKvT8_aS-JZN)~B5ii2oiRKSmZqQZW8&#5Q
+~Y)B>Ma}S(;>V=!7d=(GaVK8sS7j$~~_`BzCra!!T_Vf48@lu0L1p0K6h;6UEsZ3l`j3z2*c~24O+YF
+zki~Mb2BG)@3&R$HK{E|~wR2{Sa?4(mfs%t{uXAR|h+>~J$exm68{!?5_^dBJiVZdpcZ?T#ui__o&_f
+R<*;OUI++jHI>idr-(1hapVz@CW<>x;$-Hv!1zw`<FbS4ty!3~L}D%@v%L?=y}@FfUNGe#)K<$S};S8
+JzjJwjRVcriXkt=VeZGtr_P4&H-%=EX(lPD7+%x!Hd*5r<1#-xfcw!2=<J@c-MwPV|LR(4`vAs^l60w
+an(TS0%yC5#e4>2z({&BMSSh`?jT|Fzq%SKwbN;&baD#eF1K8{?l4heLTkcZ(x`+Wf_~mJomyXUQFg*
+t7DQLoW{VzwoNZR<q7edxLyI;zCuWk(WpW9zskZWYMpd^W1WfY(9C*96>!~A*g}pBKk!P%^3-DL>_3$
+MkHWG+Y3bJ!BK8O?iA>!I%D!l2zfod_~ZIP_Q;6wPtSeWpWTyGrR9wo5Ewc(wN99^gJoAK?0uYESPx?
+D~D0xKIn<u(gqxk7i0&frHFBNkjd*w5Mrz^y)nzZ|^kX7m@1?%gWCL|oN=I49n577sn{am@4MXSJV7W
+ZCkS{8-HB4%|c<7xMIlEbiMCY-hRw54tcx`-_xM@XZdJ^^*+eH|w)u4yVK%>S%qo|H4c9CGL7g=$^6I
+V?6u4%efRvrtW-Ir?-OhN)o`~C;`wL<5qxPNe8fNKN?uU;*6r{b1xC{SpRN0S##F{Z<}igKE~by@?#i
+)PTH!(ASe$pJuK$w<66~`7+2URe!acPxLK^%Z2}Qa&p}xA=s`M}&4<j-&J$!Ls4l}yjkOfM(OdMC<wa
+LZN?c1f=415EjS-9e>AK%#v2c6uI?i&BJb0_#bkqnafEU-)d)LK21UudX;Jr)w0jJJ>n&jJ#eJO;T5q
+?W4b)>MHE29X*tYOGiVWufI>=i9xAZ+a%?cpBt*92A6GkD2K&e_~R%Bb3B^&)QGvD{9(VI1|loO?A(9
+{Jp&SwJ|ZULddE#%a1<4Oo?jJP~V<lS<KLesMa_<<!d*xUn2FIMa@S;=sGi$YO%fVmWUPB<#~TyRT*3
+qzMuywI;o)$hkI{i_TgvjtIUZX)atoA(%1*uv0_&5R@X7|DBjY<2}Bl$<}uE*=4!J?8T^oKrz-SfUOV
+;4O5JiJew6Y1yqx`rMP9r;?PfgBRqgkTM#hA)vR=BN=%+9@`1-h-WalQ#qyrW+T0PRW2BxiW^spgiVi
+geKVyK7&^lY(9IA5FK6*B^vy|Ah?@6;BJ-$jmUgoF8lCqWrT*JO;3|Yj%`@wz&jP>9O{yu`gR1Lll&Z
+=rYxFIdqcOHOKAHc6r_;X$HG^cv@b1!>=M*N*d|B@rk%)t8t=+4yv^o1ZE3@F{lV1&{Vr8DX(;Ac}2Z
+e~##a|uiwkLs1|U73?yDGf%{p6RC!FW{FBDLv8-_ckQsmWb=Xg9+Wt3Kf*4s8iL3LLE(rGH&{n$RrPu
+m!(C8U$U(H&8!a~#EqJ(Cm1%5@)?XtK}6iQ5v<seq2;_vwyjC_lD553&ANH2tkD_U)SX^&5Jt%hhBT*
+auXfx4hDdd})NS7m3K>WNm#-Q_S<Lh)ij=Q}daSOD+JPpbx+q)Hv2nUP3)Ijha=F61ZA1~+4#ylWxyk
+FsCO@djLwakxund*)u#85GQFk_Yoi*VKWh05C%`ySPUF2^I*60y?ZoNO)z1j7XJ<zN96=x7Kns;xjSp
+7T#Rve!VpvihdoFr1pt5kn@q9|fKFW;4O)cf)Eit&A~)dc_&N%Q+-Nukje_22i2s*9O1>D?9f4()*an
+T$Eft9?EGBWU8-wsFO67~?BO4A+0-y7Z?nza)Nz(wB+<66&P7Cb`p8%^cel-H1<aoIm|Ib}UcVi|5bY
+R?MfcQCFmXK`PDLl&)y)L1<F04H)jgrS<bQE@?JA)e<^`;nx!!z=_!qDfoT^>>-DoasTAnu{bv#AyhB
+^P~QMGyuP^^o%mffokB5yl~1v8`=Wmx_ML3*-9uVR;!H4jMA?v)Bk#f3oWJj`*}jB*T?rTDsgxQ2i3@
+p<$torw*_>ZC);)5=q|zVD(yiECMKM_8teBil0&t`3GdruFW&OYl0hq!SwA4)S%P^R;arVqT_y?C9Bb
+Sb0cizFV{3!7AGH7{_F}G>ol0eAMw%bBF1!2|_`725a1j2kIZVq#UY6xgE-tJe?r--BE-~-}_vMcZCk
+v}8x${;o6dV9#J&(%eXT4tTk&_}4mV(W|Khrsw4eB;!!bMK=0;pgUXxXQ$9DTO|qhZNX5Jf8uv>-iq$
+gS_%xTPOY4q#?27Q5lT_{#(U$uzoVq!|gMNXK-cYbco`td|(40dut_cJLB4uQGCn()^$zE1zZgs7#NS
+$=wc5rZC&D+eA8kc$I-xPd<U3;j(@nJwrFY@TuEy2Y&g=lj`Xj}r8kc?^NK@?6Wh=2y=#>G)bB%IU%z
+5nrf1JyK0TywZ`5^BbVK6(PR1Kf01Kd~)NA^Jdf2Xm%xfl)ORnR7u%|{qHQju_@O-KDVljDrQ7$jG@)
+m8`E;-#}%pVk(1lVIQX}0ws5I(s)AAA#gvw9_eUcqRN&;t<(XMJpHv2UxI2m4(t4!#;Qd(FX$Ns)4iq
+%sv;DTN7k^nEt_N5y^<Ss)|>`uKe_RzA*z9`6xC3>bA}<7L5*Cd6Q)dgP24)WcrjHKAU?rUHHi)gACF
+P-U=$Ih0h;n#_${wqoXX%Ekx)?77Wma~9e^@Gd?Ck`=2NCsU(vdUVfTd3_s=wIfDxQL@O#9#s;l$hN=
+YFcFlYm82&!@CPs<zf5T+>!N6foG;j9C`|_((*0r5L*)Uf5-~I5!WcqS?tIn2$uY#%R+=F~P{t2t??_
+6wCvygz%Xz*!6E4c)u+tohuI}7Z@TDT+<Fa>Pm|?OFdZG56F1-M18{}|y&pkt#x}dDYz)Pb|#9AL%L#
+KI@mz21x8MZ$9y}@_tT4UTTanU7tu2C<L3iMV3T(>YeCrxt827ObhVn#_SG4>LQ355s~+L#`Xb@z8|p
+EH;pJvbh953Nl&S_be5E)Xko4aDBlesj6RD<;9%HXW(Z15gL5Y<JAgq^^82tJYUjO1<R)P0lqT9r_6A
+QTB~5mbcPWa`NA7HWIz|5OAE`VUFmyJfy>-dxC7C{|2+;40K`dY%t>Unln~Tsyd#Uh}H8`4LkBRtWN(
+q&Nze3syV>JV4N+hnfg_(X3NdIkby@UHkX~4h&>ZazCDhO+)O^(YSGHkNNL4$vWE+mt7A^_fcI6a`BK
+>s19bElgTXC|x*&}{9;$N=hQa1&MxTa(Jm(-uz7kdIQF}~GqB}cSzauAVfz~s4AX9KqG_@;QF<6~#>I
+O(HWxf?MuWuIymb@MvlI_VcrvMf8(Bbg_h0cLi8R0V$;0K4!Hf+dtPT3%scVyHCqd*&HPe_#F$hd_ii
+m^!@!*^^HrPAj1=9-C1O1wj3gfU@7RLn!-m5sNcXWk<nC4HaL?~x@}p`y=wD(&aY%`_~y&kbK=2jo~A
+x!vJ7I{C`vz;V6Sp#sTxE>>t{mcQVpR+Tpb9k5vxfvUStp8w<VPtUWxJ?i0Uah|^`(PesJ_YIrI@~&a
+G3S#hJD{Me?e^*3{i?(h!+l&071VUFc8k|>`Spj$`4z|VnVg_F?tNJY(a~~>IZ3D8!>>O5g&U$5PyJ5
+D8!u+f<la<PiV~-Q@v9M~j9vs4ojY&y%YFnH=gnE&qZoZ=A(ybQ^Mu1B;iPL|QVI3#AX0zvag<#^Kaf
+KZMc^(j)`lOK5C!{qtfo%{Zj}0c^C8G!v6?Z?&!8#Q@bGs+)j=K;78wsZecfB`1bax@M!xxy;H?l55D
+^D{xKf<*1IRM^XZk>FJ&LmeLTj7q?G%v3@mBJB+YbjJeIPlI(?bjNd5YaK^9~tJ0J2vERbaF%j?lzZ_
+tzFu&2R_H>btcJtp6e?jd3ODFKVsNv_1}&;&mLAXW=}WdnCyHxKBIua6r}9y&$FSO|4}jlxP5JmFzf@
+BOxrvXi35(4%w}OX$tCh^y*XW$v+VKfmwbp~2z$X=WmGgW4(MzUH4>Pxe~{)dUIkKvax3s(a4Pb>&nI
+6giAYTB{gT5Jw+=j6T~%#pNRP~g$cS|zl$rH9l~(kK$UE_bOB9=Dc(I~RW+0C9V)l^!eI%zesfh5ls+
+4RPR$?Et?pP)QO&H*r((zeJRq0>=nzSt67G%I(Umz>Nq5P<bBYG-y1*LfLSRwx<z9B8_@=APK&;bFj&
+sJv+o{7p`aBPxgQ(2H{`ru{MVV69{3Jx7R&!ZTXzSLz3Z<i|ZW55CGa3wT*m1iIzer5~AgvJ=c*?LA6
+@Y!`g=<C$>jsN;QIS$qDz=7+4H#<r;qv=V8KoWZd6(R|ld_O)E8uf^hN<uINc7R3z3igSqH;y|UCAGl
+aVcbrWv~9TPw^67=w=u3gGhc)@lt!)mf76vFYSF)Ti9@NX7LMY+Q|`{F|0vXK9f1{iB=+1maSx}|CSm
+`_cz+djrt8i@#o(9Ck<K@iPQ!Eirno(jHwusb2rw3xiDzz}bwc)auj)l&130j1VuGoVF!9~Xg9V1sq$
+ietq}{I)=DVnaozFQ}_xsjpHD`{Fkl9#3@1Khj-vK-#OBT<=8U%h$!*WdK2QxA(3nIsyU#)R6T6nwkY
+ny8z(E*oYq{OGkW@Qt+sI1n{DMk%vAVBLdVESsCdz^KnP?utS7A_M24U(8*y!ExfTqQaq+CUTxRHiU2
+$38gU2aqmGJ}k4LzL8e)6rLLj>F9QCG#2h26WY>w=5erZF(n5HjHD`wq0zx<fT@l@W1EM4k5Q&XGe+O
+tR;(jGv7<TRvzX*4Sc?_0)wVwq1?k6v5(v9_Adzc{63!|%C~=tMN%HXHA^rR4nErfzj2ot-h?MY#<DK
+Ra&k~zNM#sMe7O(-`19-}PIv##W$I(;xtGnbTL`Qj|_0zE^nP~}IK}E_%`71G{-YggsMpIxoI!;$)Qy
+Fg(^<MP=q#=BdfjD)2d~kGle1}d@jkqKB@pe$iN!cG=ArZF4m`z0SOGl3N)+!M?cB0SH?)a^Djoo@%+
+*VX5X{INcJv17Tn`esj*qqayq(Q(P(jl?YE%IAAhGNwlALyB2EvtZbfaVzaQJ6bk%yXt<)i!0THdx=M
+IEBCDaLB(XSNir{W=)A#mf7R1vMGoO&n(09rdh?b-IVymd2$ZU@P6d?mWUl{TTFO**-j)Jz7${23UVp
+@a6d?f+QHsN;zlyv=iMS<-Wr8;VIoG_$c7Tk*O+D8IHou-fAU28uSl}rB1@Cl%?W+|h$D1jt_CeYvn}
+oAFqmR2N!DSb4_Z;WLH&tRD8R`m?(snyLF^k&{~N%r$9UC1hQ{W}cb7bC0G}*Soe|Ij4Uw3Ec{NEz;5
+gcUbZnz=JWyApA^Nyywure#aRtbx%V-R~RvH5@Y1lo|p*Xd_OYKdu9zgDzVlDx#N1(!zBkU!W2@-@wH
+5B4UfbQ5E4=ns=G7sOagNaIAee^DM1QA2Kn7<XR=n!<kW)(Ou;-%@5#u}S@(W%GTQ^}P!&M3O}IHOCn
+arQl5w+LB;azZDSnqF~Ylk6uW0Ik?)6uY+;Jr>{28J<4kK-6HR)uS&S9g~y4{O&4FW(i^o+f~MNoVWl
+g9StR@VcqP@#-PA0MKO~84yD=V=a9@PxB@-to(yDya8<C*;qkEy0T>*#8|td|dP0Ph!k%`il0&1NT}%
+mlRb?7bmo6}|2gdQ%jqM55$0LX1kQRn1{jB#|O36en`O4}k86d)s`5dln?a<xdwRBn}_bl-;mb+ojhZ
+5DFHo(7a_$*l$H8K+3MaB!-PJADBnm6bOher?!(Q*P2yLEcS=tPn!dCH;62Ja&rOaoGF#Sn{V0B8bs)
+L_0ui*iHrbCj+^d+{Jj@nGLG@{?fT?E^M{bErL}B2AbpG6l!(4Xk{8#Ab9B1iy8INP{!<@95|l_n7Jj
+KJbS73HH#?Lr79#(UXJ%>!UVTxE)j?bcED5T<exRv8Kl%??;E%+FCtq;g?|-@a3tW?aj=%T*D(bYHo+
+0FPG)IDHCiow>w0-H^e&odk>FCbZ>Tq-%@j3D+>cRm|l<LAAOd*vO!LhCeU2j*av=;CU-@G%+4+Bl?g
+QW?ew`-)xP2Rhpl~K$%h5371R_@DKIG$&m8d!5!Dwf7tqIPCFzMtZ^Sa0txm?{lCVfr1nU|#u}VXrY}
+Cm}JmLG)1mvkBf6?o@V71)7H<5PFflLD=t*VwvF+l2~a>a@*2_!~$VOQeD$-Gu>vpE_chWxa8*Ks)#i
+V=(cHBRx3!8^-IVXr`POx=Cy0i+kwNhb=A+?h77W(U8oUdQS=wvtxSEZ)e(ifn+ah-DAO^x`o8W9!Yu
+Yvj{R>oYfOnYBggp(&#SgdsS%G<(C7{F}<fG6&-MOe~Co2sG({6R8hnx55c9y*H-x(0^mT^oN7kfvdZ
+}iH@4VZ||<Jf9Pz0`5d<tEM3z|yvu96A+>QFDQ-V{OhAvUtu|Ir{u^_^f%AjUM`qDX2^jPsy44!^{gd
+{Th>wv77yxupuBc_uKa}sw71zfY`uNNG<A4P4Jznj~IGc%80wyw6>8t<>7wI^8Dt;oyHOor?OtTJ~^d
+0)e=Ghd(qqA5vRikk-iHc$;9Sq~xZOMA?9^=Ky6^9zGbQ+-8Xy4TtbM*Ig5BcQ8iyVWY90zVu)KiW*J
+1f+Q#o{#iM1K7zD*C6dzm&nr*mNqzV7Mc@WTZ1SnR3($bxfmoNaJ*>8H=L+-DgHQM-vnzWSiBTO(dg@
+Y{TlZwd9yCv+CS`7}b)Aa-kRe*@`SLySz1s@E$5h3G=xp6a1x9N#RW?UILIOV6Zwa&$pQ!4NRsnn!;i
+CWYND{g|^fb+Hc`BdcSrA8%(MHbDKTVf3e|4dgoy6a0d-tbmyw}fu;C&;(2~SD_GIi|6+i-n+NA&!Z|
+^_MnfICOc~i_=yF6A{YOsw6&~F0P}Ls!U?&ch*u9OP_dFsPX_ON_FfsSX)<D-LY~PJp{DENzkqet4r^
+3--G3=Nenx57e#0YB<_NRxBk|Kqtw=iObuiJImn)PG9AgehNMfpWi`6_40%ZrN*4aAco_%NjVN#^pH{
+}gLXxylhVnN{l&ucmg08*XCyudlXR7vP()(!40vsv_PbTvWGJm#_hP;)ZU-zThMl)?&`?D#do~f8)fR
+QIYKRIAi^q*a_GmLe;|WgaYO-HUnx*z#41wPKi^*dZDacCB>9;%bqt5>iB#`uepTAs23DLBpt<=C<@~
+4s<NRTunGqOupm=;Z|`V;7CK`DMli-2?9LWYBE%_J6StvpqWU4o4>kYs7Vv|Ne|%dVH}=>7D2dg)$G7
+4&U!Q#}W($-pxXoQjVYg7IkHT+m|91@E0mFH!K0S_q*Oig*(_;BHEu8HO9+x6kYRSWj8QGo@F;ctcb^
+$|H*rnGr#%Y{O!nX>!P2{lcZm}2<=5o8VK|}c<iGx-+A!Lk0StQ1ayGb6rCZACHzz^FSAW4enRM_&nG
+ve`tI)?nN5I$B|F`pfU7W|~`L;m~DRIDVkW7$cr@Tz;lg@uz4FKl5EF>Kl7#esdhg8@s2%l!@_ha+-3
+2pu7JFGTSrJLQSCh0<A*QW)Jma>~y`$D_S*;rNy+Y|LLNL&>8_l6-P-3Qv``6Ww(Bn(fgKU&Hdc)&{S
+26u;X*V;shkG;1YLv{K@PvOnLdSd`>x$Va=UJ#<GrS=nCE1*r*WX8ceoWvcA}dtp@MOXf7`W=hd`c_k
+LX)|4WL>X<+T?_w`5B#h~X^kvz3d3H|Gyyk@?fyS4U?R@6NtRmBRua^WSRICHQlar^_3I(_o{C{%d_9
+_NWO+{aTE<+vZ?8(Ul&`684%r{Xl9jw;$f?QFYX-7%@sP{|=I=O^wycn1U2!=^xBr|DWY_K$)UIza2j
+8rCQ3hPuka^0f?T2o$VJ8J=&9ZG~SRPGE82cun4P_}(OpHG+78L%y9!^OV4{dkSn#kBqXM-jCi3<exP
+aIeW1h3h7v&K&(r2{@a<Tc=*A6#{aZu*hg`U*th&JhyK-XwJTsjEgMIO>oACi^286@s!zRZjzJ?lD8R
+#FCB(fdtqTe1C)C4t(wl%Ot+WS@clk#IUHk1KKj;``A}vTCJ{|XR~vFnhKW2Yh~G@ip>*th_E~my7iw
+eho780PgrpFSDm$)!^3hvuk_}4?%fG~Z)UC_2z`{*%NItbum^0dzL>I<lq=@pB<X~xv3$!er`A*?iMJ
+u^9pgZLp?YCSE!-tRff{IP~LrHJzEXi1%7>1BB^jtvrRl<w|&sknxo=RG~gM-Ml3t!v0<06r343|+;s
+>|7eAjlY<7gE;s&NxsSXY8z*RqXR&fnwxI3Ktf{cC<h4Wrwh)Z!HD%bI-d<#<+Xhai@WwZ~5}Kb;*Bd
+8=<P8Td4F^WmN7qh`h;nf%%;(ndF{qy1;}W^btbO2T47VpWzYq?KtUQ*qz@+3V1k4mu^m7pM)48sHxP
++Elb4&lT0<Yi4h>+(L~25f&jHUE_Ij8Qbaa*LOe`hfIiqoV2N6ZEH*tha}r>SW$3*ssk>(LiSL}F3EB
+11IT%Cg)>*Z>Rj=cG0K-L0$apo78_fG09Aa#46d~O<0H1Ax;9=o5D0?B4q-1J~|9^uNrI7cZ`TOe5&W
+WPd^h@4R6{fUR6v76Je1IEk$3X67e;0k{S<xmom5H=F30maj3exTE&JmJJ)yaloItZgrQ}V&U+G+e2v
+g1^><i&j=%bWe~QxG_Y3OLj1Em_~MNK0I@Hv0|-WWt!98+)<L5iI(7C;&z&9B~F)eCZR*5FH~iN8G6q
+P84FZN=!R~*LpjX7U$?4(r|p1LR@72x4DO>)7vcuN7wyv)@Sc<RUf)5UgGtc@)MUhS~tgoXn%gB3$j2
+S-F?qxE)CsBZ$I-Z%{lqVyJe_saTd*ZyJo${I-1cf_QAp@DxH3ijcVjkjo8VMdOmYo*?1Us*`-2Pl;s
+cEfOp@%8;327;tb?QQ4G|vtR(7%u|4SUTcnnZ@1ko<_af6JZwH2E#CpcI3;?g&mgujjbVQXm5a$S)Z}
+D5~yE`~%;lw=^2S5e$2$tPA0a7Lt+-6B%KyMNluM#|+q<mu*3b9MAYEL0%CrOWR;TF^C#37`o%n~j2k
+P3BmK#{qw5<n1E)xYxn?8R3PAAV|UZPn;4_S!#-q7HV{KSjO6dW4e`ivcGmq;}JKIYcTOBu53f(+WhZ
+FOn437#eRZ;lUf!EC6%2YS`IT;YFnb<{7o+PDa62*QHUD+$~<SyM(d@PHPlsF08U|dvw>GXpoSyM4Te
+kN3zdOuV_c8A|~I?w|dJO-@VHT^pARL!FyXLvM2u?yLQB`(e17uf7|5sT)TeI178C}kA4f+4+6ZS>j(
+FTa<f>?qKQKxkv&`pPx1-XT6znSUZ2qzT{KBR6WblY6H<=xy%dTEXyYt-!Ca~u3(&=Y9;-VI(!R_kY<
+YfVjz^O%n$#CXzEUXScOfq?B=;|0?cAr<S2-NVm(ZR27|Icjz+!g3D*v@9tUKJc`ybZD!VF))j8L4-n
+v%xMO1XBEh-Afk+#`+IRp|Kd*p0e6gLN99kJB6@kyMuxyz1IeE@Z!xl<WbWW1(O9Dqmjxsx{!Sd2RkD
+3yUKktk)7D<Xl6e%YxHo1xzg_nTIMtL`e-%je(pn&>gq}^nzt-*g&Ti6v7qmJFMudC3$0OzzSR%{sx+
+PSFB38Rze?lAJxp-T5NE7=*C0>rKV5=jS1k~6^KC-1gh|XLQR}d;uw%#!y|(L;z*Vl#w%splNsR>$O&
+|tsDy>`Gnw#1b9jBCFt9C_O9|>0gJdN#TV7G{ZVS!~MNzqj9AZwoYs0>)O<+nsnwSWgVPTjJIIB)h#x
+ArSAOVGymmO(=NGLisnF9JVFZ{i=n<tPYYiNL8LMQgcfs<S-=~m`AX&%ydjCNnGbX3xpWGIe5x_>5bu
+Ov$(j`!pQio)99?K$lW#^I9_sC;sgtPH3VJ?~B+dM|rUTIBY&25Am(F1y-vo2adA`go5tpj=Ym!8HS*
+K+brPo<M6D>e1NY=B8nFbBsp-b&d>npu(`^xVi-z`cb9Jk`8kyDFNNdMFj{kAlzKr!qF||W<~duKrzT
+GhNDqooG5sdH=Kflb{LW<zIDg6I20$*LUMyUIUzrG*4Q00;~~$`VHX}yM_btJXXhLsmhR4FRvf*MoS!
+x|Joz*O1_J8L3IWNhgZ^iv(3H+&bXCmdcv@lxI-PdyvMyT_eu=MV9iEaI<g!?_Vzfwft^16^dvVmAiE
+DSO9anG`UnH)&QJ3N7jJTOE{+tbeMgsaw2q>XDwbG2z+%oc*Tf)7Fth^YA&!aiZ`C!)vy4L0U?(frt=
+r^RGeWSFuq;g}TzW?U@_fC`0DT@0anX1W@6O46F*dS>?w9A}D9A+?8j`??dX{Rgc@7&<;+~Dur;P2ev
+@7&<;+~Dur;Qvl;kk#+M6svh<b4ktCd{b)}62o-CJL6}r!&jJM67ehI$~>390Wn7yCwe*sc4RuGufnb
+kRFc2oB2`ML{miVEJO|M7EqITuxtH$3-7m#m@ygK?-5m*pV|x^I2k8%X1TY+PRB|&sPRu1Ezi+nK0+5
+MNaDDU`S}adDt=u6|o4QjMbu|S_U6(~;J4RU_w_HReVjp6~Kh!sU4|e*}*w}K$wl5RS{SJIcX>*8<;c
+vfEo$oX@6&tl<cvanL=HWBsa!$FD$KKfP2uJ*;$YjjNc0VwKKs^2D*3pV=<~*~BYh|ZwcN&iTk(+h*n
+?kRI4{pkUbWNpW(B45h^N?f9l}Iv)p9BDWLph*~7n1kT34PvUC5wJLO{v_y(p@P5C>fSql5kdu`m}6o
+OgLlmyK{P~MCfvlYa)8QF4vRkJ0j7OXxEvbll~|a2<$Y-GxgQ5`4@0qUO6(52HqlMT|9Oplj{99&%b~
+E^f0@hz4+<X519l#igH16;YCpTx?HU{?QnF%H7KXk+r+KRpTF#|BL0}TOlcf>162%a;CF`+`0G|gz(Q
+Nr|7Q`Xn{|PyJr#@H$4Y&=d*cW&J0U^qg&2L~`N12#2?x_`@MXB7*kkBsV=kRBYTQ1Ek!`_7|EW3#6X
+K^yZ+y>Q`O_@XkHFQ{W{v2FTO|5<>nc&HEz5+Q-D%afJj3LJ!_ps0W8wvz$XtfJZ)BmrU?qSRJqd=1h
+(Mh`^*w<K&d3&4;j)qkHI$-urwBYjkqAc6`E<P~(EMtjOK!;m>zgbYKp^_!A&T-GLBUK-|8Yw`*{JcZ
+^sr$?V0GDeB`sym(CZC4FzgWcXcU-;ZP+(?1>i?V>@5O@!`c-X7TyLcVIONg=?SUcj@cfL6AR<?1grV
+!H=E5-XfCpCf?2!e%oE;@Dg~|El<wiDyX7_zZ@J`tY~A&RR@#83oTa^f3oG@uxRPMUlscU(I9*<Ftyi
+k0)rqIm@V5bz-5;uVWuY>xYuMen!fpCT6kwx59a+Os(BbCNU=IdJ(0<6_bbk-RhwLqHYoVlqvw*mDQM
+REozG?j6;n!b(?Q6bAngEIl5Xhs6qCl;<fP{7eO>690gf252*37j_eu;j*3#`7Rd<S-3Kfx`=?W*|?y
+vx`LkJaY*q^N9XD9fEHb6t^Qk|z8D7<3%MT`~DX65Z>>roQD3e*Tm3_rEX#MR#Ck7XN2nfrb7*cin61
+=<#RDLUrd^bOHAJN%6nvq!=Z*l`fP~r9KvGekaPiqKdaxz25ZaA74Ly`rY)|tEXto-tYgP9%-*Pt2KI
+Q*z|wB-k}kygIDAuz*knY^KvPPBv^97D@&6)T7oo;dkx(gHrWZ8y&suK^2aAEoso+Em%OIP@F$#Hda&
+NeW!^<rZQ21XV^1&RJz7|5&v<0>dY-(fsuNs9_<Qs-b^R!4`1qJEj=X$eSlSlA1`Zn+p@6zJ92_=8R_
+|qRBtT=sTkPaXUel$<nRT4<wNmT@Z-fo<F1wcvLCjsz)$qw-bD|TwN!Hawb&LuKTXsXqH|}M2?oQwgW
+ouwumJ=Q}b%|yYw-ZidHU}J?wXi+Jo2w8oCS%6&$plBpGYO-zsWfCF51ZrT(Y~lHo=Ex*1n~=cy1QpQ
+jT9jY?_9_azSny}(PwQ;i-%*r<(g4m*oHmd@%r6_?1hosKe2cxyB8Pgez>6OWY@jE5B-(y5;|KH)=hF
+K>}3T_a{33JRiXwb+GwM9VtkHHXob}+czL$U;e;)i+}Loxz20^zgU7fdEZ$LbkF_ASiQ@g50=QvFg*e
+#2UUna0-M8{AU9d`8>wDRK1g%~|8*~$jtjwaShAvcvtTT1jPM!0~Z_RN-EC=nr=+rTp7cD74`q)GH`i
+gEL`MO+c(G4YEbmBEAF*MpRB#Z#p>%5|qt2qv9%rUSYO?o8Ar!p<sEK84Ils0PCBWNmLofUJr(_hoBl
+SyGL;~$Qr<KOB6plqg0F^9qR0`p)h6$8HKd@~GUXOUibSgxlp3qOF7z2zPdKanq`Ddv~*@A}k1(~CQO
+=N#3yMPB$eo(;Ps{AL@Y{@Y6_-ndgN_b#}j0|a7nb`3No<orf+?Lq%vB|zP}ik3R)*%|P6VD6CDRU6~
+eEqzkIuep~#lQ}$gKf8PMMvo8LHGt!xHm_jT=8nM|b+fy~Z`>YPq<z<>K~r$PL|i%>A^TmsL-;x<l@_
+|+wPD}GkagQ{;R#lUzpgbh2!$uU`|2mCf;aLlapY3Vw>@-RC(mpPz2x*F4VsOhm8nRmD?G`UzC8|G+#
+$-(_ar}r*`XF3Rj}d(u{9_5j>!UIZt;E+puFpXco;}5+7>S{KmM&1MS&A?dvYQ%rZ_j46QQ40Wbs#vx
+fHTPxPBc*ev;0+uJfxTlWY5SPBw%MnsUY6WDC>N0)qjwO&AnrmiiEw^20~RI$#~AhyiF1t;6EsBm7zy
+kp<OZB^fn~CVZ(?I`qc(O*}cFQQ`Vs7VJWOpXuR!cfA`7gX9FabZq%qJAna!-p4s$b56^od(C0Bm6;3
+OM<A%sk@I}cdEKta4h;@DsG3>@nK)huZD;s$B>|HfiSZZIz!9HUm&hNF)!X}T&hvFaMzq8tTX>s>118
+Ail|0>o87#o8kd%n<cs~$6)wJIQmu;#byID`H?0JGECkpq-yl=ML%n=Cn%Vj?T0tb`Zz=&6zRfv9H;w
+^sO#1_bQ(KrU9?V?L699`jd?-9QoeiAHjgY&*GdFrHISdDr{d_+_l2p~O6w}s3<y=Gf2iU(+`rrYrhb
+rPWI5!(L!y(rJl+u;{qJs6F%f0Xm~eE6p?9t1%q-tY6w9C2wWh`r_sBWQk=D~x(_+6>>1I6#dtMZe;B
+-zjij{a>Lz#uj>?k*<M1uu1UGF7@9}+^mfZ2v?u!R#4x&im*REWt2C;9H^R(AaYd}%ej$>n2-UN6U9_
+YhhMuTLfUP?&;Cb5?NY_u^g%%p#+8Mio6TEexBpL%Z}p+<B`o29WVHduVp(NaC=qS`!`aZJgi^z?moJ
+I=H+D$sk=uUiq2gz8wCc@pI)xPiVjRX<C3`_EMki(IQ82nqNQ6fI$2lcrNV$>}t68;K5#y4Rp%I_!x+
+f#eK%p-V=KL-$$~N7D_S`vYg~!=@HvKus9tL>eT6?dM@Tbjc#rHO;t`9NnC$bqAS8HH?Mj07Jl}(iJk
+2<`rD?~(89j`Yn@<AnVusGTQ&!;*D`lp+6*@BEZLCc?knn~?%Mog|zX_Apo<EaDHgg9QzL`de$q-3^*
+a|&QsSJz?2$Tmca{!bb<^z_={%E)dZv|k=)i*i{UpaQOGfhCWV9Z{tYR7OOv+v!T%)ahpqnf22EoAs+
+91(ov5$MBnP$w1|e^Mkk4B3docYEInGaP*s1je&{+Y)=|Sez+al|5S4_Z+Xy~Oi8vT#k*Yq;CSbaSq4
+KUJP4@#RVXIQGWH1udI=$|?c7o1K31a^om?SNqs75tfPk?X<W@UhMj@yn6#e;o4iU^4!|{j}(il>{O`
+k66B{YKNBgjUi;rQ?kNBw*FkRl^5bBtg}l%cMEEmqS=CB@q#0nKiy#LHl3B}%ya*!zxH!|^Tc?~}V9D
+m3a%q2sp$X^6@MQE=a0PEn_LTQPsYou!bKoSLL?b+d1oQeu659hY{7P`s=8{&;nDJhnl-yqvMB#IdhW
+)mF;Klv&KZcUMQQKEEaU5Vmx5c<hH`2ZVg)Vz1+7L7ul!w`*hOBFL84W$*-Hk<Ayh3cxP%9w{|QsxQ5
+*^E_z@u)Ec73ekMtTL-r9PY?SMqfMskm<UM)osZ;R{Cu0jS)XtrX3t=6wgocJ#S-<Qv=YV9RN~;9A2C
+%+8K28R2Vneef2&(bh}%y$O<P?Q^$++yZmOK~#b)^2U4V8@5@p<=M(#Q}=H?Z8^aOzHhkh5yz7K8r#C
+h@&!?2k95u;E!XS>E?d#|+gwr+Q|-((7&V?adVZck3UCQxT2`FU0RcFl?M3Am~*EjZTE87>r^_tC%JP
+N3`q@tNW_-SifXJ0q0ivE6~5ozOVurl>c~)e1G6<*%rJ0`Nw%Rsdnv&#QT$iFNn%#;@J&{J_m&Mze%1
+P&q@v+&ZA!u{)#CmsS!*HhAJw#uFZU@h^DkZgo)k-89gRIiKlj0VQ1mA3N-6sVt2sT{$WkN%Wt19r4b
+>Eq$SKL3dOKypDZDcY;%QONXT7Z{H>Vgx}I5F8F_;Ljf}ZEjHGg$qJ1Wcp7u{*pxD|i&T%)u_bKoyg)
+yQ(}FpcW~?Q~lM}rcsQ^mJ+qhb{NoxEyZ@lmcCRe?!kNYt}PH}r?xpDMmf!F4HLFydlVzkb3Up?HxS&
+n#1(@{KrQCM1p$p`K8Nk<=nX}FGPYTs@2{=VW&<J<1Ow-ceT_d8KO*eXyXc#^2&<1$q7AEaso$cA--N
+6EfX4#j=RaN(D@Nom9E^o9bvU6~G{y#f)YF6UPHWPUrz!aPyp#Pmg+pSnMN(Kl%`ZsV@it-pb8Wc}$2
+;@PGzJO=rtmkT(TLnbrvQRYk*Y~Ni0pMQ#OZ&REAaZ1seU|$)iySO0Hzr%wu<<use2AYfxJD7`a?QHM
+dfn?*xU`c9>0<~U1UGQjJua~97*O7KQm;eijY#QyNU}`hzd*c?svLbZhO~DeXa7_$6x;8s6mTMGjFx*
+B9((zeiWTLCAn$0#fi}e};c3%`>N_&T)I#_q$tX#PikC82RL$ugxP0pNLgAtf0rg}*izUL};mW9(4qS
+r&3Z002(#B?TbjGQi_Y~k5ZCdrhtDcb$@S3A(|w!R9&_2Vv_=q`)+@6-dNU&)4k<cP6Ti3eDHFMIR0T
+(g4L4!tRHJ<tl*9Nefw$NObg%lQEOrhta6*TstNrxB{;2}WO97YPJS8v-c69MAVSrILiiSDogLkaA4a
+xFL4pXRW0ds}Y46>maUk^wCGUH8<qdJyEI~`%IJA!xV`<)PWXUJ*UT+PA{4>l0uY%!hOZkXB8~E0sU&
+t(YHKJ$v^TMHR#8v>3AlMKq-0bpaH9dDW%?lylXV{+Y}#D)O<_>)kjF#Mblwb<ghe|i_0n}a_`1`3oZ
+Xv%?|p?XHUo|8E~MVk}e<b;*=c0JnMi-R>diGYyzekU3W`3wZew_Q;=x&Y{<7Iv;y!qKAzGI+PX%qZR
+_6U;4l}2@yVeGGl-GoC4h?#(rcNYt*QoD?h11@!b%#6S?!gGMMbK6$@plwcjEd_P7IC%Ri(y&8!tpEp
+cWh{s}^w^4a>onuOAyveWp1TYm}S6INc<Qu*}qt@wIXu!Z?L5jr6a&MZwYV?ACW=aNw8$p$>q1JP|u4
+x6{asN&*5lVwt36fE0|EhRB|rpas*ACzmh5d8wq9h2m;wZ1XOD6CzM`uFzkYj%qlPu~T|rpe{BwiGG{
+4v09qF4VKqonRl4FHa)e&t@4ezBAPpb224tW2xo!d_GDCUbq8n$13Z^aH1<n6Er`j0v1qM;Yj+--!Wq
+S<<cHOKfjVqS4CN77I!G>oc=#BUCyRP{+XO<TVF>>Gpeui3w=idTa=uTV28laisSQ%&(x#bF!%*mDLp
+usQr@C~ne5C3Z<QJd}fT;w>yh~77b}q=5Xdz2&aTmy5HYyB<HYu@GLDp#*uEg3r@Z;F5>02TeRRxoJS
+?B9!sN0XP*&^fJ?dg2XN46-m0bhnRe`7oU2j<II9m)spYxY_8Fn!?%^Xg4kIB4o;_kEzT3sE4_gGxfU
+m;F#8_r)PwSyRFpk;+xjg|v)Ccp<sPcop%AoHAV@=dg7`srzwY3+TPeJUbkTuOCont9I$QI_(b8xMiY
+7F*<qZipF%LkP<;o9>+cC+-E#{pJW4?oEg0RQqpU<6S!b<3t)k@$r=2gh5dTGaq{3@Cs~Ga$4Qo2!8E
+6ED8$m_Q2L5zRL2Vm;Hzr2hveDOYkNMqQ!SkkYS9;-obmzNOyaobu4y{ZZX~Ly<}RU!x|jU}?TX)#2t
+2RYi|(RYp@Z)l4JRaa@Ei@6tOfynJ~L~-3_#cp?vL8qejgt1A@obkU@WdEtT4_qkm2XZxkv?Q7MYSWW
+G<}RUAgL^d1b=s(}P?RJ8>Uo;XcA{<>G}rSPgh{u&+1ux@ss@JHaN?DIB5kmDLVbO~w2sDLF0+7g-0R
+_Hy|#LD4ot^Qvf8gBGQEiU<aE+Opk9kZqX-r-?Bj#dc}Zm7g*6o}nc*PDrx~7{OV~&PeZaO6nCq^s7)
+fKr?DAt{)IyJP~&o8}0`tW=`#MBxPki;k;-cO?qgRYaME#ti(`tQL{{|Cl2CCLwUumf*+wAa`11wgM)
+oBD^W!;FB?+5@D1JPldtzMSr2<@lRDu%UoQ4As4AEE>j9;6yqCS=-jO+fK1UrTXA7KC08Jnec-sY__w
+e^Tb3JQp<<F_I+Sp8*5;e9Nq<n4yoVnRNh-Wx37nxqb!8cu9wAMd}`7J<FHd?iYw9UbAq{ud3eLxFG>
+|(NldUR8Pm7QU;vR_Bl|H`T)w0|2&k_*<MLx~$zCrB~ZaU^G1+ykdRUtLVwHCmep+LBue4s@=^EH^ow
+2YdLjlVZM@`8wb~qo94voam;4&6&*$b9RRX)Nc#z9*c@ozFwfAYGvak2@RMb%b@XJR8@FVpz9gPDuO|
+ck=U&AHWwKz=#FZ{iG2xV{Hy1`8_t31b;tPR9N`LlyiC`1bzYv9c-*>mn_2`k2<3`#H8Igm*5Ml+kT{
+1JW!IQzbDUirbJv@L!Oh6?3w4`H87z1*mL~w<dqy^*3~;)JY!DmGX~4K-RN5<t*nY~kh5R;QzOaxI%;
+;;7NYV5=nLjxUJDf9i;Z5)}z<Yk8mnCQTWt*d1Qzg<EVK1b~zy*~?<dR47G`QjDp&%{e7txgXFb&GV)
+(1{t7_IC$yS|CkY`Cup8;HyuM@zuiOt&3|>?9Y$FSkk*iW;1dB5FQ#Rb$de%(_==x3ydJfl1sm#)ocq
+WI};mn>Sn1hkBFImvFx9*Jpig3DT}0t_RHkXKPukhTf<~**DokUh2VM_by%I4(2?;KDe9U7_kS0e-=i
+~xcy5@JwboyMw<wlk3AcXR?X4sm=7mhdaobHaYZ>npq3^|KH{bNj=AlH**Hj$i*ga{@$GaYis)!~H}M
+v-QPz#4^`p;{OJe)xRii%A6OnZd`A#;H!ul@x+pFl#1(Rwy>IXbQK{lZ*x<l``^!8r1S<}TSQ9umXPn
+)d)KE1FvmvRGV72G8J*d1xl+?f7Tn4~l{F+r48+mFs|)FKENZ`@z7w|IS5Xmakjk3NXt&~gW<!aj-9&
+6cwn&jnS|;~YA=+;B+!A(tIvbv#^;;O}wd!L{>Fum})(86}<HJ%%OZzzf6V4FjG5HkW$<^a`j69Yl^j
+R}-Xy^bf<}{K7eGV;oH0b=8HjjW`Ls5D46Ml&t<qw>`3*bAX1^siTflSuEq#m(==*-~HS$qLh8xws)K
+VJu_g>FV@TIswjr8BMH5dAA88dhItV1jy-xCZA;KrVcVwFZi!-Giol8<4NRhnay~fr1KLSi6YD=lm)q
+pq(AIet$^&+rjWMwgxjs2wlM=bG0mZtJgPb{+)}%DgFc4Say+hA-iVjsegCb=9?Ot?Ea?q`kGVQkJVn
+|V{$FE;b+{So}QK#CXUP15Q6?#6+ja$xEruloiT*N*Y<;<4(RtV?K@z6{%UTeZG!nvk|y(6{%y<nXSi
+>1U;GNMNJ9%AvIIN+`Rk0U){vUF4q;diwMjp;AP`HG@h#hi?~wVHAg_6{xJHM3{lJu#6^a~JBXGenDW
+&7$GWq=Si~+ivS*FX{(%O{x}+FT^J)ouK}eKCM&p_aZNsq7Yn@--D!>GWxXvFW127(c-p^Nj1oK{gZ1
+)lWu(6QE&cG-vIs`k52yUt;Jy_mfpVbq~aeuFiMyX2rj%_w1DHTIz0D4gD%$X6`9A5GxViQlpn!qZ)W
+_ntgmo^j(feq;!DFVyK6T+xNs!YU%q8Gs*4y?x&})*?U44cZNZh9&z<+{ha&syoPu`V+VS5}{J%7cr!
+YA39DiPt352mUm+>$MkNA~9E3do8bHW6%MGC1{I8Mh_wdYEzO&@RA=JrkLU%%akE)$MRND9=05X;A+h
+CJwlfcRxUAti4!IWr%1&-bV+-Yb5lPP4~rVuW+2g>54NKgF|JEv}6Kp+QUn%|7fGkD0bOATmK~0+5lK
+|Etf&%oVY+)kf(tmqBIA{=`KSYwafjD2neB-=M(8`v&hOO!B#9Id`YFyHEM^SU^Ja|3oeOvY@LvuK~V
+|p)i<Og?q8(4&o~vTn{B42kIaj4BdQ-gn%eG&i<$*gn>q4WeTD(o)yTG7qa6IWAhL-aj?q3PrHurjjh
+)=wW&h_?g8RdVmm?f3`Mn=ke|+gFg@8U7S4N~e+BXc6rAvjD6knn9%6~dPoDZh)e~ngtxVPg!H|woga
+KUTQ*IT=N?Sq0fmv4Y*2FIr^bsREBt^x0y!J!~{OWR#wyK450TiIVGN90ezh30CVv;>678u!7-R+H)e
+K5dl%2OTvtlHjn#Ow9O0Yryx@}ezt{!_e$Bcl`Jk7RDVE$k*aFWE~6L-m-BKV$V~tk$?L8Gwsryv!R4
+H_E73OwYn`EL7ZJ9t3B|)V@Dy9DxP_6-;Z^lsy=#+gsa*tWcq{j$GC_)o|pARfukvT#NcPfXqvwzi{s
+I;aGAAlFcbarXaI!=Okrez+()$h6AmOGdNFcvA#SMc;<|hbW6AZK+#X(l+pH}tup@S$=>7TL8LR)Fx*
+tlhIepG?a_+!fGr&3<CVQ6)P*J%8;m7V!f{(JuV|jc&5RZ#G{zJ9`<SAuRGYdjnyaylOb&^Q3JCM8y1
+2mD%k6wwo|;*=IlmkMnV70W-gxgyW0w}b$9!EmhNJ3!-HiO3dK=Q)h4sysQ@O~>-+}N(;mTxle1<Ffl
+qXkH!l_&>_hTrA7{+gqx^}f4+-AoGhN!@ea_VusN+akF8uTmUT79{Gf@Q48pAYzfa#4yUDVkvh*)mUJ
+r~7oWt=7xDCPo)ya|afe-z_<pIu;LYQV9>3=cj*|G>d;xRW81ti+dgx!-(S&KK@veEpI9N>u_oE>LyA
+(KRauDk)@B1`l!w6=Y7`RjI&|?w9jgtK$H7sonOenXw1VtK7q2=P@B|xfMutBQvBTnHeRAEO&|-5aFi
+VYFB1-P=lZ{LeLM8=u2pgLTsO&5Zm*1E=gM|McCJfq1Xxv!`qLV-$c4z-)UhR{=8GLa#ZE;2WkL|EHi
+Vmi9fI8vG(p-$m#`SvSTMP<?4KF#+E~F!FeM}=I+)TRf;i&si>xh?&>xG-Ly5>_ZS1sN(*qC-KrSKL&
+~jwD0%>WFxqZ%yAtvm6rihZBYDi}(w5VwbjX;1t)MN!BDF{B>YC81L=0;=)Dmx-Qh*(g0?vYhfnML}B
+!---{o$_CsLT=zWZs(HDwO@<cnZO$(H@smwN6n&X!q_CODT4e=qR8S>c{#Y(7E)J8eb4VY1}*`&+>J^
+$-&|Z=Sz|~^!^k00U34zzr#-P(6&f2befCTA0y8ZR_=)JJy|R>65fSV3YFf^Rcw;!lI|{Br#`!=}ZjW
+!m<%a_VFc`V#_cBznHfmnHYO3ik9(_<XX&7o#{K{9~`2{yfv8BwHs9Jd_@DZ{fZNm#^nMma9hYlwMvY
+`ui2t5f4o(whVQf#NfO=9rC$$)Mp@lGjP2T2l+e<n5FlTaYoA=DWi?L9nBHQ3#l6d(^@GL@qso$C-`{
+u2UL?w&FnKV$`LVxI)nkiUWx3B56kwzWxsLVq0wQ)1vTx<v<85_NZtSiwr1Bu8k4CQh=`b+z}!pC11C
+fj_f2rRYg7>(vor5<d+384`lDuXubr>~oubyQivE?SPOhzO%_yoQOR*#bjc-)UXWWHPBtWJG`nk*(C}
+{%c`P7X@LQzx79qkRwKJnq)tC4E%dcF^*1S%G=2hh&0Jj5GK`}*q_@UGwYd;1R^ON$^J>GJRP!3}uF*
+*y6bED5ar+?JBjn5d;0q&t25&*YG{)bk!Gva44O!Kni^{HXa;xJl{))^+9OrOr%KBh@UX-;sb$u{j9|
++e^W#5_LfigfGssO6qL*I?sJ`Sy&DftB65}<*De~7@5^R%k#qFGlI&#=n8!Xu>n^iw>RW=h7Lc;N=^N
+o2I_8Truqc`f|?OpK<l(q@s@%VLr$Ky!E)RrhAWy&8EItX?61Ciq&0F8Ec-lJZv*2{p%RMU>3iDqt{j
+gHj!!u|RQ|onYM);?G!{=Uey(Vly@LJxEfo>NiCTk|``Q30Cm!KhWw2zNifs+HKrH47QC(Av-C<zI_F
+<W!N}d0&;Ne=3sbev!n2QNF)pg9B*<Y48KI1Ct6K&Y1L{pYLEo#Vu6u&+bYn^swQ2?SV<2q8R@cI=Za
+VP2e474lA|(w%`S`N*4FwobMHhqYn)R^h39x>(+wAzNxP;dxN*~APOl}3MU7aJMFQr?Pk!KUdg95&=#
+<G|y+QqpYkV(bqn8>44%^M4F<u!d2LoWO@wi)JsPlX|2_X3G+SAokFE3!Dlz`QkU#G!)025@zgj`nmC
+Ub3LrA$!Ypn|du{w+qse;1X=KwazT9nVWN__uNP?{VdSv-*@SsH2o_5<eX*G{>G`+@VPB-bNS&lwUlL
+6bWQD9Q8Uo#NPJjp7vC@Y{7n(bD6qFOe}p%6;b^*VerjwpMI!alr#o+6^${tfJxeCs;O{A$6iXA4lYu
+qwID`*t^nM{T2{dkTk|eBGE+K*fVIw7$*lhKBokfgUIv7=Wut&nS+K#0S2dE&)5j;$)|fyATHAZOycX
+;du|u^Rg^SBp5p3L-yR(kKPKx<q7=6=bKY<V2DcUbnJJKl$QNwA%Yry5Vb6w?fwto?OJ;$uL=|QDpb?
+@3Ozm;^^fZTL7cMo&QN=8t9LFWmR6mJtVf<}ai#IXZ4(OncNw28(@L!3~}yy%DaKn6ZggzLVgM}1mWk
+Mi&%y~X&6!S?>mj=f4NIQwoN4A_=ufTz$P#WD}<?QVztOc2KD!>pq2()q33B%@jM+mA-L)n7T59h2&{
+U9wQ@p5QM!2DMLc+d=fbgGbl!r`bQBA}DR_b(x%PO7aIH^BdznjHLA18~=?-wB3kX<|Ls6kDlNeNsbw
+KS#SI56+2E%z3F%&m3wpqCD!-TCK%ZvkjJfRn?A9*@sSszw`?<%56Ci_l+fhjh5&rzRs-i-gEg#9VJ<
+Q7AQW>15D?y#bYBo7gaSc)wb!4<ra@D|(jvv|ZOQx&Er)N0XVmLDeE3~dCy_>@#{5W$ZNz!B0SjT#a2
+_t!aL9`TIo(RI8A@FcQ6Z_iNdV#aWiS=AHY$xTTSS!07IW@V^*EM^5CC5b(bZv^K*rG@tM;X_*hr*A?
+^f0j>|2#J%VLr0K(e<TWk0U72z0vw2>M{`ObjEW9y#TYdPs%vzSBIIUKE%hPPq)H-Ub>Y1rQAe*Bo@7
+4hu|Tkg_YFn8gyc@T`1StZYV>JbN9R*mR^M`R1E%wB11B?%%)~XW^(d4A%6#9-7j@;z@onPRimRgwef
+{DSH}6M#q-)RK4~O057y;s(f@8MggBaku*RcpRjsCquRB^jPi=0Db<;HigB62RCQr6<~HL>SlE!O*Qs
+d^3z=3d_L^G#u`n&#tW<e>rSLJtIzinR<iL(<F|;!1GH(GkA5Q>-_$mbbZ-t7<EfoU$zlW2_84ZwA#{
+$UFQ|ok~Ek=H#Lo8Q8L@A@H3w5tg1T!LaNCtjK%mMmD<(6Y}F+g+v^&jdR%M{p#l<&N@vl9GvW5>tn=
+-zQfVy6IWPU3ozZL_N3%`uhdL9qqdW6|ds{;x5S7T+N!aG76W@c&{ZN)tqFsPx>$WnpcaX!nM7E}`V}
+m3V2KB#f)>pO|=tZM7a@Bpn-Yr;rQBr!Pf5#K>r?!Ug>$ABSZ@(F+~q$@;2ykN3@DL-x$dZ&B>r9-pE
+`;;dygveZ)#dyiLFZ(5Zfi+}f?l&ieHdilz|Fi(0Ws;YZsp7fqtJ5cq~K7-e!3D)Vj?4usq2f62DGWL
+QQqn}{Q*%$6v&ypMU);#L{jpKY)sxAAd_ct2|NWUs)y}#$pxj#1Zq^IWsX5l5G%`YWI`7=+=BYau=V9
+XPK<#o$E>3vsR1rW`X9;)lzWBk?oAz!cAb4Q-a1M|X%q#pKIGofC=&)yFkV&-G0-g8sz4G3Gr%7^953
+s<mBlxce=_^*3up7dVhReG&3NFMYs?On|VvG$#N){FaOJLB~Nn}0)>M(z>*>>a`xqF0%J_kyTJ9I%LZ
+ME8(>_I^QCO0b0PS#Or>MZ{mdRi$Jd_s)Cl7n-{GYU$#xK=1ztP)h>@6aWAK2ml;P_EsMici}Ao007$
+o000&M003}la4%nWWo~3|axZpeZe(wAE_8TwJy1b%!ypX2^9p8quEyZR$%RwSeM5&}#iqfC0&e5qS2%
+5T(n_mcNf+y8yilx}f-xN^4N6J*BH!#CWmz-IN^(u3t(?s$gLfDUN*`s~Ql<}d6)G)3-Y7G}7Z8pDWx
+LoWcz{8SzSQ8a4fek<lQ9a;(21o?$+~-k9UMi=?d0QRj8@Q#6l`VXW%Rii)ANWDY;1GcIX&>0_}}DpC
+c2lWRwpuku2?E#4SnND4u`q=o99}mdpN@BS)FYju^MxPKcXL_Z3c%OtvT=seUsJ$s6k}!W=7lxy))7_
+Ef}9}ie>g<-4gHlj*rS;^Ax#zfD<<}77Aauzol)fM8UeIN)(tgoc9BYf3&U|IA;OteBF#WgJ#S2^LE8
+P`;AwOjz;z>?aj^p2T)4`1QY-O00;mZO7>O(bDXyj0RRBe0RR9b0001RX>c!Jc4cm4Z*nhVVPj}zV{d
+MBa&K%eUtei%X>?y-E^v8mk3nk!F%X6C^DBn+q6dR3^db~0+ET%mLVM^fgzOlD*~~H<YyJ1lc6Y&pr%
+c}a9&cuXpC8-r`HK&<;pQsd9n%;6rWGz1<pVy8x41Xba)b#?dU)?G#g^u~iemByPqM;wW9*UUOSJ$fi
+el6KHXM_1Kwmd333oA(9E>Fe@McbgJ|UU*iit<$AY7yEvUbQ`d^++uVc_U6nwr{NM6K#dKx=c(wrGuy
+SlsN|SyUSzdWW*}<T(o4lVWk5{X^1bsRtIST&l7x0RA^n7coskGOl%d%|MvSH0eIE?yUhF4hi?!ECUR
+BVCQ^vFucl9+UJpEs&#j{*0Wq&y_#6%*mT6+&moN3YzBW&O9KQH0000802@m7R?<DWkVFCi0AmFJ03Z
+MW0B~t=FJE?LZe(wAFJob2Xk}w>Zgg^QY%gD9ZDcNRd4*HUZrd;ryz47i`62<fk_PC-fDW#mJ^<GUY6
+r-TAf&ZSR3cT9N}7IsmoHgv(nc4FyR);qGt`Xi?=}yMPrQY-?4K2HPUZl=%#z$(zyCmP6|cyaDJ?}ZO
+J*Lt<rN4Gi?1~Z!;c))lB{}GonUcOTqg<ddZ`R)Wz%rcB*{_9j`X}Q=p%?)DiQz+eh#3Geu*e5%T`HY
+lxz!Dv);g1wzj#o&#ipw4FY$F<r`iZNAXsXf4Aqxb|LKL>zHbK)Mcbysb=U<k2@PgP*TH@XfQ)hgAiH
+1Ob9-nroh}59-+-by4c))y#Jg#$cc&CHZG%x#oj1j-4`Fv@+lFk>lhDpd1&8&p&GR2QpDy_%kniDGY7
+HHC{mWsiIatbVT~>iYJfTJr8sN(Z&2k<3JjcJP+S{cxwE73GurmpELvUc<2Yls=;R<wmY$61mseNmJk
+Iz!ME`|3gZ!8i+scTVc<JB@ZBfEiO_V}Mb(G0jYZ)$W4P*PP72X!Pe3lNXO|1}ZU#17VZuj4}#7JV)G
+eK9ph-p6UA86bwbPwZnjEl@hoSe}*JmW;?QKtf5SnWlbk#Fn=5EjL^(;&<RbT9D_4#Vgk37mwOc5Mq>
+W@I_oS)~~NXW#YWVn?W57E=a;#GnRl>3=&E0&$$oeiUKaIq@g<G_vpHlj{)n;Ks%I@qgqs4SW~mK~d+
+W;?_NP+3R<~AZRtbfb6943)N(qrPeBJO{riVP)f>@q?B6YC{2B>b1_f;08mQ<1QY-O00;mZO7>Qh=}f
+=>1pol46951s0001RX>c!Jc4cm4Z*nhVVPj}zV{dMBa&K%eVPs)&bY*fbaCx;@-EZ4A5P$byLD(237p
+~y8+e-jHWQqF$v_a6g=-vccI>$t0Q6s51?y&!Tccesp(Mk6(0YN14c)Yvc?~X^$*xl{*pReDG9Ij+}Q
+sRDZHt=LF*xTis-`QG;lzrw(%VIK{%$)FNkwT&2^`{I9BX$DR1-mSHx`)?q<K<)`4y9CvnNtb6`PfxO
+YNX8lz>i#PCzG9$2UdzQP9CAiq>2^%Re?4-<{2*yD9vj5kDJZyr5mf4#i=Zel6elQ5xOEHuKe(V-LAi
+Wxx885Y?80*>rY?TSDWN+bGi9;x4vtX(2{2TwMdQCQBUqLEJwx5vb#l|Z+ZGa5&Q0@CX-2;bFF*Z*S1
+C-yXO}ZhL0#7c`h<;L~)-S!0ctF*^2!=z5TYCF4*+;a&z^OUar@l*PHe9pNU<T!Hy+~D1=Fp$d1sXA>
+S?hmvv@!BMTUeC1CiyUTsv>o$-N6to?(98k9goe}EcH?4eRZ8<B=~;@cb=uLkq4xVqP!&sPse`%%Zm?
+pa|xqd*)N*3)_HBjA)-CG%c1YD8Bpn9-bx9jk%XjErKCYj8vT#ojkm;NJuKyKbWBcuXo5O+Ty=(fK44
+@g2u}P$ybDfPt0{h&(W$<^3w4vL#2~<VBAPo%cl->h{&EnYRSgn5B{B9IG>RaSnC|O$+UGI`!{&sD|-
+IMa;e-7zWX)2QWo;QXMcuWWkKYU4al3#w&m)1O{tEVV5~*IqGz8PL(btRw-I|1XciKq{;~uanLO9$vH
+&B`1|#^RpXMIA_KknMGqIFPW=IIK$dvhS3|&KFJZTd>i_eeCU{DrbQLxRrKI|qjR>=zSd%iX)L4xIQ>
+nrkxvfOr%0_*9v=a+Pr8RMtit14(J?NP+oJb!S5`bBDTF7{oVLI~69tb;zWmm}(iE8>bH_@*}<Eq3m3
+(+Wuvd9FHi|0u#>Lb}PhfF32UaCnpDZIa~B25M%B3*474Pw===51yLWA>is8qQ_iu%33={ReGov#thx
+dtwLvfTvKKibV2C(~!@rxb<bT$MSg;dCn+*s}cqBoP@Q_XZ&;CI+dj~)E}V8sh?q)H{t)v!a|x($ZE@
+eGBIcD$`g<mr}h-k7!z*Tfm$TynALD{pkNEQ7%0VUBxMuGL3;HMoKSZ4%YYY+k^lKAYUW27WT&n1@Kg
+%r>S*i7(2hn=tPM969%n1|Zu#5To*DZN>`);~_WThDbc36)^@iWKrQC8Pl@(I$0K5n&u~9t2uc%@RP&
+gZr6g*cL%@ZM9i!hB%SBE{V4r>7JO%)<$pYTN>VHF0NasyW$IU0wNM+^x5fQlNy_WZy|*nNer2lW6ld
+S0&3PH!?0j7FLq!h=j7Ne!^A5gS^8CKKh)7ixMs39({SdB>_P!W^laQIB-QnA%WaPw<GrZOah>#du(O
+DYX`qx^0n>2x*i`1X2(tPM0eq0R_$tTQY4Ev8^l-@W`f_EwDGs<u6#070l1zsvrkm_Y(+90jZ@w_3V}
+qI9%dIWDKoO1M)7)Ae9-yh`=JxUDcgGx5n;D@<kK?twWdrc*Eo+1o9(4=}t5AZu!P*=%+8_)EE^e8YJ
+<YD%>--pD{&(okrk1Z>vt<ju7q88@wX*`!TvxIcjm%+^t-`)4}3>4(RGc@wf-q`e}n`9k3o~S4_|WT^
+%5M2Hs>xr+VNXcP>ZUb&GIfHFw*%<cbcwu%efP960)en&x9W#?<T<_H<tr50HiHg6(gTrfiX9l0$Ki0
+IfRC2j<5tr^nt?1Jbq&n}<z!){JQETgOKi(OP_G=<r&e-^6Z2D-g^WuUitC9mrOCo^>5VV}IU=zu0zS
+gYV}-4=H#F;s4%+p6kB@UBV16V9muy@9kObf0Tf3=hunzxPP*74E~tm`Ym0?@}UofqkE<Db2l5BYfO*
+vy$^lc_{AC4TkP!pqMmmj#AE+H$$Q<PF^WzCRKQA*C6=R#&QQ|}dE7fL+m9DIdq=4O)jM`Kl=D+B!P+
+eN7f?$B1QY-O00;mZO7>O}NW;Nh0ssL21pojc0001RX>c!Jc4cm4Z*nhVVPj}zV{dMBa&K%eV_{=xWi
+D`eom5S4+b|5h`&SUnB?c0sE3iv|9{M#PKu{D*4!b3aO~+bf$&lnMUeW(P(uxzO9g4O(*pNv+K0cBj!
+2Id{*Z7B2cxS4{%1z-Hxc3vdy8QMX9;{4ZCag0$8bpKOJd-JEhvR96+RI#`oxn{c(gMd<$z>E>TwFwp
+0wLv3VAj7e^>Fhvh1^(>Wu>s>K)nebE&=w=Fc-D*ARP$sg+-A?PUHwuk4r3#Z6K4WmqrWQByE!1n)2Y
+vXasGnhnY#YQ52<0I0v`F;T>lg1|IPwihvGfgAMwjLzRzUiwzmzaIBCH;nDbM#}%^&YmFVor(o9)9>G
+qi8b^TpN?LT+k4EEX5i?Zi@#~CIWn2jFMOGxjQH*=iFNkrJrLV_wDYf*=<$*$bVaZ=t!{$Vh%5dF^O(
+f1tnec*4$9SN&KfioHcl5Q@Cyaz0TXkCkU)27O^u>wt>H8Voq^{_N!)F4V1i+V%wdOr|nX@wqaY}UVa
+L%DJ6_*<y`!&Z(SfX`nvgS0%{oXMEZvwxkns$M<XD6%_+K=dlu%=L6DQ!GBZ!Bg|$~`@aR7;(mO7wym
+j9^{!0!H2B1izu+m0UL--B`(Ox6(1&1o00fX_=J*Z(y~e{wz81FkY>apyHwsj2uW&rzpM!_h?1C)RfQ
+DMU&IyFq3@RKSbiXL2yX5Dft((Wk))G>l=~>DcLZWrBuSIrl*N3Osz6lBPb&>;?mWj8rVreRcy|x=qr
+7g!C>tTBHur|wVO9MJ%lbHpPyknjs;Lta{6ocJCgi2@I4y;08mQ<1QY-O00;mZO7>Q!HL1E!0RR9B0{
+{Rb0001RX>c!Jc4cm4Z*nhVVPj}zV{dMBa&K%eV{dJ6VRSBVd7Y9?Pr^VDhVT6qlW?X%j299QMlp~OL
+y&{FX4wvQq}^R-rwISv0g6;3M(ttKosVbUdD{*=PVb(&_f+Do4_l_^Lgu)U0rYzpS1@F<FfkmxOFBvC
+P&^@vE@F3_qZ3*Z@&Imvu?2SfX)j5Hw}S-qS+cL7=CY(k8We&+Rq!mk*o!BZ;KpJQ81JJ)X3w7+ziny
+_Xfk$6c2y#n2x0$r7Th#6Rl3l~xLiA>K(Iz<y%orZE8}a8Q6f}6ueGF5`U25GFrusGARe3-jjvHbhcz
+!@QSX5HUW?IDehH+I=xer^e(@$yNV7G%+;e)Ir%u_GdB&JFNX^9H-N}g2d_J8uv7aq$^M6JAm%du4Jk
+ls;%aGa9N6i1O?JP+Ro?$4-8bS54(t|eoIn;boXHT+4|J_Ws0pS{IN7m;b7Co2>TO!((Q8;-AP)h>@6
+aWAK2ml*O_EujONHORU001CB001Tc003}la4%nWWo~3|axY_HV`yb#Z*FvQZ)`7PZ*FvQZ)|L3axQRr
+y<2T_+c=W`u3v$pD`jd%q7^5bo%5AvE^(YH*JWl>v1fOyd>$1=LK4Rm$t6JB+O7TX*WCa}fNxfkt5wx
+ZBob%<{rYq_e8jFlz5m<%Lz41~yx5n?W-D*_lRRUmi<f_5mt_*Mk6|hDY;rU?QiDGx5zhplU&TC=$vW
+ZX8GBoV(U#9ogT-XxdEVq^%h^`SB28AOEKE0fnaJ%<up%!dkJ&meStU4ogr}_Jf3LWZBA}Vc4#%)G-)
+xd>V}6$0e2c=AXK`4X-!j?p$-2yUjPJrE4Jw(Wg6Wq9Y@NrU<V*RFi5gWTMX-DT5_uWaD+^gxk*rEy&
+%6i)zk*X{B9X}hf1gBB69^(asu_nbF7UyOU2|9t)_Rx6`*$#%9_u-Rmr0l=|ET9(n+N4&GQq?0lAW7V
+2OBOw(ldX#%)%XCE~k^pZ=bJVNXdgJ-xVM*zx00h{oCKqPJTMN`+j;h{mDN$f#3M^yD9v-{hhw~|BGM
+svm-yie?6f0>GJc>Z-2S`<!1T$^8MB4%Zr=k_08Lx->xsOVIBX~;^mCJTKoVbCox|uUM{OL@!`Me*@V
+Fd1ojCZ3l=imUL|1nOagmKzTr=71FXwfl7W5{!1CmYy<_>Beg1I4Uj63}Z-NO?@dYqy2OJD5xkXLc&t
+NsVoiPwk2|w0lxY>cSO<`Z|Hq0*Q-%XiUg@7@zm0%ajXiH-P_1ss3OAd0*n6Dn*zPy|1dAF~cudkc0Z
+<?<^+#xTbG!%l7a4+&qmU)_jobuHlJdzDt-r}((FV|tjnar8sAo{h@btblXmBx%zDP~{|SuO)S2hB%z
+FPBM{$mP<fC-@OOUC-2%^I!6e>+ef0!;Lt<DJytV>shIX2pP&sETcT;f*uh$y-!0`tMqxJ&Hfa3t2JF
+PoXB_z7E6zMCaYZl3G0_Ttl1ijvVOqf8)MKya%qRFlrQarAOZU)knm3ziy1hrSE#cK{9moTNbJ8!YC8
+`46*nxd$~4Q%ogbxQ#u}~GBK!qjDVs%w{_XQelw(wKFmX_K5w1DA=X>&HIDoclRPp~qt?>gw0L@^ElG
+c-kUb9`&>@WcVT|Py;kV&5T-mh7@XW>fZX(jOhS74?k>^)8MM;-@wVp#cw@YoAF{iNZ&TJKzc32=ffn
+|cQ@r2bxyYVRHo?QRvHz*O(VYX%>&3$lqAjAft6@QJO!iN-9`VhHh2=slD)uGoqL>$x=_{UW%3?SbNC
+1C|zma&h=CqS<eP)8G_oT+5if0sm9;PTA#Bv4rHq!YpRqPhRjxo@D;5CAqsPN&+9$^Ff_Jn0mVA-uKK
+qJ2~;---cb^+bd11<;f{ER7SK`85pQ;pW13d@Fu9WyAf^U#ubrB`7d927BIA!m%^fUpXHC)GEPcl-vi
+m*KOH$9QIHpKOqu7fX2Rt<$ji;iR_@Z1avlBo^wsMlp}0T)Q*i3c_IBaZJlt^ajQQX!XAFJVbk-dM#-
+28#K7`<iI>VA|zJ~a{9VM3Kb7iJ5NcqQJVlYfd(5>f($ui6YsNwFJp*fi1JXx#N<7Wo%Dk0}3e*mpV?
+DEX$qFSX%^xU8_c{qSnnLq6hUs=pSI3x1=SEJxjwAAVaI;6iL%JDto$XsipH*;T7ESg``FFkKMb*u(<
+ib`p%gzgwttCbefN3(h$0FnaXnKyMkl6F=0OhkoA;kO3TX<$Q1R`E&8sg;r<phH8gcMh9>Idz6NJ3Lo
+YZx?rFNtduJ_uW0neK8|v0%T$!(YDpw`s<xDms5OT|HJo}Wto><!U~KAF<(_1-@Dp?4?&k&WwZiw<kc
+MF4CBbG`8_?5X`1hF8WY{jnYueu^0p2J$F3obMG%Pf@T-rBLsWr+uVnJFmPz+Snw3{s%%29BsdqGdCi
+8K)J~#?L-p`33m<_wGxYBn=CLZ%zVi~1Zj~yO1c=W&E7DkSK*r~j$j6BZZi5gRZv%P?zhaM8*|M=k!I
+2gz|Fd0_=sA(riD}8AKs&eT|9oKa%)xTUoS%3emD1`?9L)<EINH$Sb5(&&rASp%1RpZJT%i(+Z2nese
+A9Bq>?>aS9AjDlmb;J&Og8_VRr0a<5_+y^mljRr4bkEt(@vI@<%#R|oP#?-LOB$SEL%(;By0g5JWWJO
+>syr!y{2O@z*o~q)gRm6Z__7J<%F(-e=pN{^CaN~TwxO`5>jSaXz5vX{<6~FpZDu<Fw+1n4eL{^<bXz
+|LcXG}aU%D-ry(FUWWARm6J7R_|;eCNA*8_@^3KEuLrCc5hlb=3<`6X}ykt6EF0*tFm$bLteC{FjNg2
+^7$44p!bZ~?L{eM(4(5PUy?MquLS9Vmwcd?Mh)EaHB%yMdxiE2OXB-Ey6zymPW8zUn(3=EB27C@9&9&
+6Y>^>~YJ{hS9>KFhlnRxvR;1W6P{XVK&mF$&g%yu`o6?vzR+;mhR+@NUN9Wk71dCbTz`#Ja4w6a;-Ip
+fX6faHbEo+*!3{wyCPlMh7Y`Pa|MS?E(2;XOF8G6nGZZkb~|_qqDuDx`>UPT#d&rtS;m0`WZ)8YI<Ly
+cYhu74_h`T)Tb)EiQdm>~p_b@QBCv-&^Xke1*%%FGpUegucY0(|fK2kt`pFJReqPqe&zs=2mHyadFVX
+~gf;xeGh9j0-IXkpc6%$u`cv$dIHuW`91d9ySQnjOi@Q4EqJK%tor~oSa31`ORO#{b#GU+2j165d=qB
+k2U5V}gW6C11;b^@rU0v&E;Pz4$>dfoYcV&G>?RTuC~SXqM2Va`QbI(4T_hg}TpvR8L;1C8o7X-ZECS
+h1)MU>5(-+RRi?M~~7cdJ2rxFFF~Ahld#-rDXe8kS#_>;sTJzd9%ieTL=QRDB}-c3*cWWVfmGY8nRIr
+Ajt_q1mJPd8R+`wPgS|G1ZfsLgWWsZ^15Kr@~LXEK9Aa6u}(dPmORK6LDGVNKH2dA|7R7kXxHa;LxEm
+zcD~&+@U={Cl|1jPBp|BF67(3OG!TJ!?L(Z##pXnK091JwY8u07s=ft|7AF8wPY{GOWF3HX^XvOx&)5
+w(IV#A4lmQA<JF4`7B7{<V1yQ9ETtS+mXhX+a;RjfrCaYJCzNor&0F;61F5Htc!qgR2sS^mN;Kw^;B2
+u2B%vaz+F<9q--c|gSiE>g1;$a19tZ1jzAye<7f@vuR49qd{Uvl<|v<q~iSdQb%K3o}tww1di;|e}zT
+r?q}ezHuHHAm?K^+h*sBV#q1gCmEVUFbkzX0jBu{vbBgCveTXcMp1`g&{|*<b$EWY6^t#^jxi0-F2p|
+Xf3sBVW<twY|uwy0Y+F*IsQ~6*duG5l&9p&)Jt#Bm6_S+tlz{8fxBtjPnwyaqNtu-DA|x-Y96+&T9cS
++^X$y-6@<2Gi*nbw9VQLE{9)2~Un{Lb<XE&9TuO!Bn+0}>)S75bHdz*MNpg%4z_c9VL78Bu<Pkl^V^}
+Ab#sY&uwLM5<4^-A}fFI(Q$^V|y;#TZ;Pf?eI`_2JxmkMR+?boB-13<Wp|EM(NjBM|{r$;bP?aP^EM~
+Cmvo5e;9`7JF2ZqHssnX=j1GciJ!6*OF5Yf!5W$+NuLY;FGZ2=Ygp^jOMzW2p|V;VI4;INuYrkH;eYi
+v*S)kZ|j`Hj!TZ20)k}mz*30Q44e~qOu5;k!0+W5LA@%kP<QgSB~yH56rp@=@fH-FRF8)usNU>h1&`R
+rCKZ*MM;i<)2Y#V0UiM%!1Y^zbgAW$yHJQKRe2UC2pGcD)WZkMRbN^<IxK4)tQ$0hGX7|_3hc^0)lu8
+|?3cjx0r))zy{+BcdROZ?hMxJ)c(nivJFI?nc>|R0x+|oikn>$0<29N1%a;0C&zfH&3UinHh-A$GdtE
+Jfi<WhxK(QMliEmvcK=#)PFsrp!RTcCl0v)|50@9;_y5==D%~bQ1sy-G<>Mu}!TipioB0yw#8$+*zTL
+v9dGt>QlF>>5Rg@~p|!-#M56iaLzaPz)J3ak9t#!%XUYTy}yArnO|c0|}Pv_A*33?l~YZW)HfcF&u3r
+)vqE+mdic4LTFiDPt+wjuo^1EeFLteBDVKk4F12G+k#lpv#>LF$22%)?8Yv`w^%f&0V#6AZ1RJjL|hH
+GXkQqn_~5@a>PDhgf~~^&e(g3QYx`HUA)1{tWLrZ2I9L-PU%$M$)@U$iUt5sAipicY*SZ@n%w8$do?4
+saN3TUaHJYwB4_`^kwDr-h}ViBPGm1?!qjYREjk-mZp2KKyR_Y>qPToMtkA;U(1K21)qZr!XOnXeen|
+bHO`)d{(Y0Ppc+siH9zS4W&og~5FC@E|xy4j$KZFch?tr=GA9=RHdoNgFuoGkFH6k6=zysHrp{imPN@
+b4C)wkL~(>^R>){f}X9w;7;1qT3T1At0^ADL0nN@3bK=ai)aoirsEZxIvsNr7clWh3SWn{@IUSIcNmR
+%YqEq&q;7K5a^;?Uih2Qde*-DtAF5Vt{YbpLQmjV(d79Df^Fe20wh)o40~wTg9UYTa{nbr)#E;PjfeH
+8O68tA%81kRZ>#I)OUtW?H}DIwkO?=q?1h}m`25MJ6}4v-iCNJ6?KJD0~khEe_~Y-vC4=`dJZR0sM^w
+}=Dtv0qG`><`!OR)L>)0&4N67(csjNw3ia#P?d^;9En5?%8uAdDAIp?X9hsWkjZ{_Aic-ikte^L-kDr
+5T$<{{4jp57gue}al+Wnum>@OkgS#u4LcpA@Dw<ZVqeCM$+eGK=4+GqlgM&8Y8EfHQu7Kkd^5_Hh=hp
+aTF8DXa<ryF;6iL+{o<iP9vzABUxQ7%p2_C#u?Er6Y19?xvAnUmHN0Is`}RMoW`1Bp6TkNZ=%wH|;S>
+XO!YySqork&|caySB8u^6HIaS<?{7*gfZkQ`@rl-?^|%4!+I<#{;$vNh!YCFD(${a>bN2d+w19R7AV3
+f1os~*FC5_+H-*CYNTU_$I_?+(b>z_>^t_uo7am)E7NvsJ=DKbkl0jA5Mcjv@h=b#Rw#rQsOFwSe>zq
+_y3pu6uIR3PPaBHlZY99ar@n61>qL~dv1&xuktEFaJ)KQ~ZEU>GOf^__TbT^hwcomV^B!TFQ60CqZUc
+g^>d^M{tGnlKW1HuV^Qpev<9Gl8PHsmYO9pi(!XiUztw61I85YbuMm&fDpxY`eTw$A(B-iG0rx2mq7X
+Mzbt~R5A44y*P9lg58^kdhvJb%gP$MzkgVX5Qg2s)0wXNJVAwR;-4ZND*C?eEi>UQaYqK){btu7Q_Y;
+d<Ya?LO=Mx+7Xn%k;$RPDE7qzh)RCcRb7l>Y)9XJn*7Lq%J36V|2&ea#FW%Hm-yC=?ODdco=p2-xOx_
++6RZ4Hp9Q7C8t=_PHsmQaIan2p9Alq+7^<pTkX!EIegX|t_JD0w>mhmpY8om4>B|SJY#D388tUGV9ez
+3Gi-MF88<!rSVg_6APueW)s7eU-16P8Sk-v7c#W1xw;%w5!IO+XVh0t4YGMwBT^t3LX;;(K>Z;qP;EB
+TYn0C%ooex#STy6uEYu5s`N5DV%s3A9AIs;OVDsUlw71ZL(7<LZO1=ln-xs==-BNPK|+ON6h>rQA``%
+QftH|dgX+U<%xHsX@F>BP0WW<Bt~d1uA*j~pVGB`YIVstzE_%!4}VM;*`yva>i$00;8FxD3~Fj?d;eY
+L$q2@p^7`(dMUb?BuYaYSG8eASGO-zFZ-yqR55H$Uq6=mPV59?818+0a+KlRJBUomk-#xN(Moo+8k7F
+MHr^)VwmSu4vxb0@J|`&o;B#Ls4v{m$~*kqZ=8nLdQ!Yx7imCk)7TeyfzrBsWJA@bD6Jr4w5q4ws@0$
+tntD^9r0P1f7|X65$Kl`4*hAMnVm^Uy?1)-ZPbA+7zc-J%H-Euss?6;J4OEh+ZueQal#rb+78FU0tI(
+Wa4@uZabdVdmkbaJ2Z2E2gRKGd|tG5>E{&7QVz~uh`P)h>@6aWAK2ml*O_Erdizg<ZN003$a001Wd00
+3}la4%nWWo~3|axY_HV`yb#Z*FvQZ)`7SX>4V8a$#_AWpXZXdA(OnZ{s!)z57=X&LKAHDCq*d1n?ovC
+cpy0cCiVt1-gYoOCyVGiWEpHj{kk%kg_d*v_MgyK5W+3@bS&en-5)x=Pw_Bzj{=f?rpnqYFURDdJnha
+!_CjXhzF+%@g$wMW^^&SNXAd9Ami!kQ%NSMN|C!2cdaaHy84jaj7F8SjR@4V6;Oq0TI+)NEE_6ch`&g
+;;rmAYlctgFXf!Ic^j_RctrxObvB5Vd+m_tKE`CrErne)3&v-nJf1evzighv((%H_GLW-&t$y}^!Rn%
+gwU=@f2y^-65TA8JABuk-8utG+tMORhiW<mmCU6T=^mO&))UKHATf_+F>^iD+=2v-$7Rs0@moS_I-SQ
+8KyFKm@?5_&d@Pw#*rLvU&V3=i5QT4&!CE&v^12)IE`Z<uFfki6-SztoWs2deWp-%zt4=Mw`dO4}`T5
+8(?7@JXIeg@(V3*E*`yyYTSaM>t~xUn`43aVp`@M)+Emc8yr<dG0PJQOY1WC_Vt4gNR$hHmQkl2Tf=W
+7tA<C@=Yo&!7GFNUTABU5l;H(@8M}LO6B0M#dpPD{OW2UIsOxG8w#p{i3*p#PaOgP(<@E`l~=E?0iyG
+-ufiJfq)hidoh8aKbqgk^tt?Zt8C<BU$B1x<koTR7d9P6lp!{f^@KI}tA9Ic;JKx2Ct*yBX5u0fu;rM
+kH(ZG}aPd6(Qk4BJ<hu8hRkP!-J##zC0T<vSy>5`8an@EwXtZSqxVlhcp!?qIQe@d!Eo-3n5o=-gKYK
+AhH?ey6f4uAMzmgkV9n4hW0$=EG^8Y5(+DbW1Ibu>LbivpVi{`luzG0b=O4#_Pku$*@M4DKHAx`^U>l
+gmyzMX`34(k<kYP)}Mz5DFP>NE)AtYEMS_0SXIR>b2ZJp%jq4UpGh#Ykx-}Dmu?&v2#LNr`}|sAqcqr
+aq}l9&aPRocEt!?8|`-(psPEII8Lf~i8KS4yRG4abI?$1EU1dol4rrtyYgTdD;m|r;A#o?xOomxl&Lt
+e1fiiWIv4NZ2z!=r@6%RX1uBIvazl6ap{k`%QUwzZ&)#TY&YssHwEp(`y0nGQT69foGV7MtAFk0sfDR
+>I(|ary<i%%oX!L~)wz*Qfk+4roR7}s}FbR`!ex~0u*YRF=jzZ_m*3}6sJF4eE`yOZV)TyJw2HFa4v;
+Q&x+{Gn}DiWWqq0!Ee-V18OQ4$YvTD0NOzqlsR`wv%Kh;Jl*be=`TiHx0tHHF-pY*<Xcef$k0xhw@YO
+(=M|WZAGVvMf7}?4#742GNW>kE4h_c~t3#O!v>xTr%iYPo`o%7dMAyiQhxhhScv*pF&if4p7XZAN0F$
+f#o@{ugQzBolZOpZHGQkgw&w9<Forbl6dH+zB@Yu<tPna^qMbG^_Vkhe2cp;pJJ)=vND-w{oj<0rFtW
+O22P4MMeBZ|fk?dla0p!b(=njJ8LVyF=);48FS}N&0<CL{fccZ1oE#*@6RjpUGjTKh`=BQ%rad_^;t#
+u>Mc)U&?2fS$%vzvhnLt~ZN5i}O`-kV}{OiNr$J09xe>oD@Br%#Ei67;FCdsWbwm&Y}sOlM-S|JetVR
+?wI7572zhp}(Ozz=}1|FJGmcExJL`xlmz#;3*^^K+lF&*#XY&Ea2^29`!`i`8)6Y;R4?x1WH#J6IhhC
+&jK|GT*qu#1%9yrvo6gW*Fx=CNE|aTiG%b&lCb%ANacf{Z-mSicO)1t)2ziPc43YG(s_ic<Zrge@Z+I
+FBS;KUO1=o{ID@zh<o&h#Oio^;{qbtFQzO>CR911w8;sN<%Ncg>Qj6JkS3(@$Th&o3ze2%e?p7pmip7
+6|MNcI?-jBMbLKnfT(K$42Yoo2!*DumZftefU83L`x#3L=$=5M$yk{>iFL9CRl_*0BWm@Jf-ZGA1Vz{
+}JV?Cs7nF(33pw@Kx21RS8v)R674BR|d9{l^-VI7z--|3m|d@u>8w`V{O!pEO}3^3wg3V2yjei+$*3h
+KcAIJEfAli)*CLpsRa{k!{a#>cVhoYrcweaZ4k`SE>?Tc`C&*!N$b9z_g1-s?<xgb`o7p!&KqtHUUsc
+=~^a_AgLN0|XQR000O88%p+8N_1|4?F9e;IuHN=CIA2caA|NaUv_0~WN&gWV_{=xWn*t{baHQOFKA_T
+a%ppPX=8IPaCwziTW{Mo6n^)wI8$KM_H6kQr^SrrA#0PRK+<-NgKj7aftIM43ngkK6~`^|-*-rnvgO<
+wKghc9T=;!F=Og#v;?ujo2Pcfvx1v}}cD2-VdaGwJ8I2F%Sh5(-h*TnP?X~u*!DlR{xuS#j3C%T28I?
+0QDoDJfgGo4QwOCdNsUaqu<_VGhS+k6`TB#Hn(2Ou1mYQ(|?rSP!Msz|n?L&b9>CSDWzdK{|WPEu`|J
+=6`63R7cwdU{7kE4_GIUGXJCVglp&|X0MA84P>+UK+O1^jtF4_d8OLQ|l(1(P%)siv}H9rUf&!w({--
+B}CpXP(iS{S&edij#<QvFdc~AW3y8^J>tq;8L+6{P;+VXh}(80%_;kS#1#Lc<4f7a+Tpwd#B5S(@wYB
+MW-<*O2HpQ(NkJVrZkH?V(~AHjn^t;47(ySXZck}QJ(fOkSYW+=i-`Q5Crx8=PC~ZH-xhU#<#cL9;%e
+hhmxXW6-%}-@AZ-*&&Yi3ge3o#N@ut-RM@KD&T*WN4opEI#SKen0$K<loQstYrGT?*3ghv9ZM@XFm<@
++Gl&g?YorXeQ4VOCOLz%{JCi~Mph4W@29~^`S;S^R&Dk-ce<di108!ZgcoW)G@H7K%fWF&5Iev>IIMJ
+e%#C*gw_Ij&xf$0Ha(@OjI_g+|tbR~zul!Y<qjJM|<7mv*Ryvrfv{!HVf6kbI4^S^1Y+(0=$hKb|4LC
+WF(DmuK$~&lOo?VdXI|6ADUTt$b+`sYPvH{S>>(S-Qpyh;F8_BC4V|fyKHaoHL}i54q4gUT^@029erv
+HOY0-Payi^ZUY=C3ch|EuL{@11B+E@hK4(E*M=LYSh{OFYfQkKgg)VFbZ5t?+c0wL)_shs5^*W{^4sL
+HZOPJyjgd)&7EJS*?Ew6Ejz0oNaWH$(>)jR(4s!3R?j|2|`i`vM8nQc$&f>uLwAm5ORf5b{bely+a@S
+H7jIr~raVeV7);29MHVtckFRqpi>wd{NECUxau;{V;9#l;*T|=)0rn5WzYhYdn-<qWPi5)goqn4fy&Q
+~3dyG}uT-|zIy-PhUcZ{4Q9I+)M?n^Tz`wQ!#wF}4Ldh()fY;MPS@lnd;2_v*}<)SMqzevj-do+rK6!
+*1Q{p|}4^s<bkyg^Ga$vfQ+Dqss-AOe7Cb97QZ=I*J^*z25a|i&$GR7DG&bgQp$!@@4V}Pn#g!dmX5z
+VD=ONeb_;JR%3nl0^!wJ!3|B7kQ|j-p!hQse$*z{ZVj|;6+$gCnc1De0$aM3n%xOlm+dVaYm(21(&r*
+Ed$r_AlHc3TEnN@ti^Ho1;Sz7weMm7)SdjP{L~flAym#xRRDN%;^l`v!-R#E~sQEOUgcECo+Kte}B{x
+M&aKZ$4q-4QqwIy+Kc!J5M;uiB%0uq6V8|~9ela1X~Xrq$2JnKXhW|Ghw$_2g+Gx42qPHaLnA6#Ax6A
+`Q77rGdp&gY+orUXo1JvsVodn)|4Y3l9=l5)(G4i#=GVmi#JUQu~H#6GD-Ecnov4|8>jf1ct~#5atKV
+sHPqH#Wp&ZWDJd&7Ov{jOl77h{|L-Sjw=$p<O)&n`p6)a4nLO>j+njE|sl^AN9JKj7ELD?3>HfTweEK
+-@Mx&jr%Y)@1~;zyo^WYf{zEIv9-SYiGqBvXPXaU-Glu1M)ziQliF41#zw*0HH&e}8f7SXyhHx7X^}q
+@#^zmt=;g)M*^^-ZRQ^_EyicDxR(`-uU1hGWc1Jwx+R5AQNn-mv)!7xgO-nSfBOkk=lC@1Uy)Bhw)oI
+7H5VM6bb7{JBAD*28o~xV^*z7x-5OFCbZb2h*W#*WX+s>$OhYxJ%%|I_FHle{iG#YtrtWsoqnNy`A&e
+H0vSx3oOUL6r(2&OFX$k2oR*P~IlfxrVUem~sK``OuV1k4>L@4I|T!7OY_%hW>WkHgg&IlRj3TQ6zdC
+xvUPj$ItXUh98QO9KQH0000802@m7Rvw9Gffxw@0Kppo03`qb0B~t=FJE?LZe(wAFJob2Xk}w>Zgg^Q
+Y%g<Va%o{~X?kTYaCyC0YmeKw75(mC!D>E?lxl<|GrK4T@P{;yHo!I;><*FwgMmRy^q3i$Qbo#+cai_
+zb4g03BztC4v^9d*Baw%f_i^syjQ#rY%|9>R$x^(o>U|^c*XBliHP`Ir^A|s`w~fr%PrT8Unw`zg+~S
+{PE|eA*?+c-fTuISfvsX3G*W%)3_Ix&zo4RTYTXHRayz2gvRrl))f%)IRm2x?ot(t1XYFTHCtx!ePF#
+mR=?*aQTd7m}nU#-waXWBGvZrVoZZqI9+`X16LEsflYH!?T=fGn>zH8<VDzu(+^{6*-x!r~O@`9q0sg
+S#)xz816DtPm@<SpImmC`4WrVzJyCq2pz8J!AMZ0_Q4!%M8ohs(6_RWq(9m=Tb&Vas&!;$9f1fJxM2-
+$BbID`b$JWSh3=5X%@?>*e@Ev3pQuf@{7n#Oz-oOYt4QYjpU{LO*FB4=Z_*Wigr^2Ta>Gmc|FpPP7#D
+V|4=F6w>Syi+r=8^iALkdBWjMjWtm?Fc{&8SvcODgM%V{v`kb-PYoQqLmZ)>XYFtAUOsbUa#CcgVdsV
+X*y)YU3EJiTA)D>&%f*Ubd%68JMfv?1lt>Ecw%~er~hM9^j#~>Qs#H3+7H=1z`psKxJ(~}+kQeumJBu
+qBgXGNbMgrgO)w`N``gGiabgM1<xZ0pxARyDTED*G#${{7D}0R{>@V;_FLd3()n)=(k-ai|0eBdLUJ3
+fQfMXPa|PvX$lDdpTDI7l6|v<PK2o^Kp->DfTk^O3H$koT~sE3TTxi*%=hYRAm?(Hf6ZGVmsJsf(3v*
+qkD3xa2C$D&YwYE!Rn@3mSV%!f;6k0KwWH)ky=Hr1HlVzZCJ?F3j0(pU@Ef{kRX)JMvDEl6BDd8-&#{
+@VaU`Sl#%2h9U2bVq-<U7tYtf;Ot6YdSjT)&)ovtM#@<y;F4eu)BaZ4s+)3DJIh9N(>r_~2W%SB83f}
+L9TXXox?*j*Fqt1n*>(MLsn*0c_=qsi3-)?HNcWN^Y$sB~HHdTY5)1u}LR8;Pd;Q81FWI-`MSwWw;XV
+Lf}2{<+0CJ9@C-yc%8MQpP%V`S2ZjgFHEYLXri1zuuWlB9=mPmZmHZMCdaxY$2Bwi+>{?c#&zVPxao3
+4xF<%}^kEa%}C88^S%qH^aT(W`|#aQ@zGUn+aLfHf+nAJ@XnJc+V~LfOpXyxzV?foc)W?CLP%ixf;u)
+D1t;VUf!RP>AI9Aj?!poPO`sSOQ#L-t|yA}E9ZeF+@r+mwm#x3?)_rR%T`zcZI0_*>|PiTk=k4|1%N&
+V7>Ep_z-i(-apG81_hNd^z$CYBEtw|Vb+B?*Z$P2hmrAPmb{XaQ{3=R2`p8^rC)kv=Fv(IXE64n%!TE
+PSolp@_R=k)L0dAu$EGSEks{mAgYbu;_+2k!)6>36i-V&37M(-sh2d<c~1VfZttt@2dXQW4ZHq@iLTI
+kSkgb~d~DljM|3m>Y4NbIQl^2U)R5hEq%{&^8VQSR^mG|hhG&*TQ4S?SArEonJrFAg>nUvp6#_K9rrw
+rQ$n0s{bRkmpf&k$><9;YtdZh7q2`MUl<ns9bHX=KTdJk+}khvlW#K0aRVNT8r6gmNS@2SOQlEEg&WY
+-(;c60eyRYdB^_b<%@=r`@7Qx{ya3-qxbq7rBs~S39j1B5^Jm0bVkCK53?Z-{_piWxB9)kcyZSkxxQW
+=_<__Y*>jsI3Dl{~x-Z)Zr0T-*3B7U-=;b+Wa34ls0dA-Ww;>QMY(OlwzkiD|0B*R6fs`ciso)5t^se
+y=a1vG6G50t-)NQ@Sb}(5*mbMiDcOl7Et;!9(h7>77Icuxm5!jbjL;J9_v4tw3Zlrc)kiQ?r?#UP<2B
+;g#@?z2P_m~WF>gS3_=pc%sPl&hGev)(8#+r<z$@|2_ZDGpVrbNqk*`tJAm@h!H@Q9FoYLO$nA(?jN{
+rR(V1SHON#0xz@8ymruCgtW_5!-Y@7627Jxk&G-_O6F^fl47T97oma-An2|j|4#0s8$?Xk?YDg7DX46
+l*5~<q*lX~gVg8bWH<zF0K}aLC=21QzLwXl6f5J3W)flvhTri9KH~aVxs-^c{UFw(XEueq``Aq9vP+6
+|pFG96Z`FaPNcc~oNxLW;tIC-g9uNR|P4!O>89()=Iw@mU01jov&7RES#BUaSnxe;7b*(esfsvdPw}&
+G7E~~3Lc2#o_<BvDK#0~Q))NNlZ-zA}y!aGE!fxn{GzpzsSxCImuMG2eFS(L9^^&pB7V|UxFpwsPv)Q
+^hP7aDqYnk{{EU<u%O^WG_R+P#vBheeM-LOZ#;KW9v=H>hAvb1K3dQCHUpEC_3F?4vFy2Pl1PUogk)E
+Ox`5WCYi0%BFo+%wF}sDXqrTGBMXPC0$>KKF?tlV4v|YqT7B+yI9<{gdQRV8AybVMap^WIgKx?Ep?D1
+uoai3tz<?z7%ijEL0#+|XPw*5)%EagZ6{xJ&a$Nj6M+aST=9IED^A<9pKZB;R5B?~Lq4~==C1QZx}gL
+&oQ0(9*|VvS24!lOmY;ujsY-K)s*(3nQMn-QdA|1?YpXoxJ6%uT4K7?)9-v6&T!s=dT<DO^XjTC0lEW
+a?C_$OBOV&O!+oTbA#hK62*+^y6+rIeD+fJg^ll0tAH8WT36UrYhXvduC%}au1lhWaI(Qw3;FTeA4Gz
+g?=@|cGH!1Za;>@QD)W?N`(Aieg=7>!pa%83u!N$sdQ6ZHGZO#0cmgq=Cr6Ku%Y)aKHw@0;xCn7NQTv
+@FM1+vX#p?CF&F^z!6U$S@I1M>+9$T1|tT@w06*ZSA|!&Z9?8<~)y!>c=tT`;!QdEuVt+(~tl7!nUId
+CjvI9vF+1}@KcfL&Ho26cKJk%4XE->Ye$xSvg;}d+)`tA>c+}6Pu5yeNsPsIP)WC>k}<#%Ur}$Pqg~S
++vvPgf_R`k1lAz4G)gzXqiRqz*(N%!fm7;rU*KnC#BMq{L?J}`td({Cy&8b)aHBRk@EeBEsD&LK#`~N
+R~{Wnlc0|XQR000O88%p+8oDoK1G64Vp1_J;9BLDyZaA|NaUv_0~WN&gWV_{=xWn*t{baHQOFL!cbaB
+yXEE^v8mkwI(1KoEuR`zsc6QP60GUIICYwos5#sE6KUyP24Q&2E^TK-*tmO`_REbDDkco1LAPNPd3oz
+80@&VC$-1!c)Nq_~AsZS5MFKg;2}ABJZq-MAX82)L=a<-ZHR^IRYheQz>1*VjZu9$jOy5R+*|8NMczz
+V!6HeTW6V^*|b&%>Wg#5cBr{Qg%BC!gSM%V=g))p^QLMV(|2bfI3I!4$)^XZJJkcBGWZ7+pas-~o>7P
+G?Gyua)JAz9SlupndNWad8#tE0h0CtqED^mg(|)VzOk&>2=;ei$U_7+a{j78E@a*Vel0oCRrA_Vjn)&
+e9#TC>&5G2=^z1?SctAfkNVUC5-I|d=%DJ?v^{r|XhwdLugV6Kwoax%ZJ{21{grhy2!Cfl&$A5cpJ1Q
+Y-O00;mZO7>Qb{)fJx0002;0000h0001RX>c!Jc4cm4Z*nhVVPj}zV{dMBa&K%eV_{=xWpgiIUukY>b
+YEXCaCvQwO$&lR6h-&*D<0!k!-O_Mi#{Q65!oV$7zTaj19gVyEb`yiWEer)bMLt~fc&_<M0;v*W9-0m
+uiY6RE`=nXFJQ-1K&H7jod`rQmNP1_>oGc%*g2{QIfa$gMU7E1i-oAzv@ok)ldA9(sI`V2yiYs`AxEo
+OJ6xM`nD9qrEUEuBPacgOA(YZhqZBORDkoQlApef~;H%4<cmhyM0|XQR000O88%p+8I6yd<Z3h4VmlO
+a1EdT%jaA|NaUv_0~WN&gWV_{=xWn*t{baHQOFJob2Xk~LRW@&6?Ut?ioXk{*Nd97GqZ{xTTfA^<gor
+lU>uac&{D_|f%ce4o)AR8A+?sgZ4gFs6oi))z_NGgtt`|zD1DT%U^+!d`~ERpknelr~EggyN0)7SUcq
+J~S=?6p`|_7R@#f}NlJ^#^vPMb2)yHcC!TCMTZwR^%WJyuT?xT2Ttn3-+Pmc?Iv!)3eD$Y#XI5tGKCZ
+vFcuxnUq>>nMLV4%^Mch3m`EQznP{v$?5h!as!vNFlP_YaLp}zRK>nu?wORdTGch^j?-;l_REur)%(S
+S;g4LsQ}$Z5vbfS(=?OgN&{%fIx8N2$-3e><=jqp%dDsO@ZkFzG&Xy1EVK$je3Mg4-Aa6BfssWkpw6K
+tr$S+a+oRwQuz^v2o1(=fcp6$4_%qr%n>A_aQFyfjsqZmnI!ZINPg<~Q~PEJ|#wLy!NNtfA|`{mv3w@
+FaomM-tFK0LDD{L9tX%UiY+b<IjHY9>n51x^*?wFX}789WPPjnlmIx`H&%=d5`rVfW6lnRIZ*G?0sO@
+6BI9&RYW{qw^18gOR~)Zk<|kf%Y423_})N3&Pxv8jMRLPk+03#jnomPl`!pS&6AvJ7)IVTF8wd0~!ra
+h&FU>3reDB!q1j(gj_S;Q9ApAC^RmJ;j+L4_}pUjT@*O;a2+hfcp~n(wK`E4!s#-*TV5}3Z<k-DA?wF
+}bQGQWOUb?nS*V>s^?$~QZ@JzKkYF5RD<s$ZS2TXSx%+Vc?R9;Azti>+N~K*EoJ*?J0eDf~3a9~L$7K
+Kqh0B@ZGAT?Dg~`%Bfqk{n50z@zs;8k2W^OOk-EkoetS9WTL+7?N)}_^1(1Eo>Y0f44P84P%8pbQ!Bg
+4rhG`5#VK<mRic9)Pwa7EC)RW&h$G4wnL(>zBblq`f5N@7MDluk8ZcYtb0cpnA_C6`V_o70T4xD1lO^
+%tjW1t?b-C{oN)UrenPwfHwmVYSLPAq^<ZRI06uxL&;#WM+qVBtxXYws9%M0O1?YH|TgMu)_Bdid)>Z
+2tQr(I!>?#+iFRCW#Kss1mbQrolT-d$65U#gP$tLdeTrZIuaT(iZXKjiFzIPiC3%dklPqdd94hBshAB
+GP?)g)<~4Pa%pGS`nV-e8kY4e0I(?`(slp?ohAp-M?sA3jXDekZ)^o8Zt_4Ehq{!r5aE(0^QrIj@dbI
+}Xa^AlcLZhKd?}sHSttZeI*St0mEu$ui<;9sg`|<2-B%)jYN4$=y&u}lJj9=VgCWkFr%ADWP29{7yfa
+#Cf2?JC{MC_0_2#B|aZ1wSFKl8fvM`SX+<dR4UlOyQ|60KSTwS^7}N7!-Upf22lIh^3P_)Zyloig2SQ
+0*b#XIeaB4!!2a(L|?w_d{QBszLDkaU>aS2KbED?v{^N3wDF3*9DFpSV|NMs`CLxd)4~3Rq>~>AA`}-
+SdJ44miRZMrZyIq=)ivxoHe3Z99V-(Jyj=ZL~>~C?1f}Tp-8;<QHlWJI@WrCqC=Bn9AXs5Nf^;WjiSb
+wJI33Qz++iddud;Cl)3JCOcF{E3BuFCb|^*K506JG!hU!fZ;z}TUc8<EG}L4AEtY^P`aS|OM={Cs?5K
+l=kvTOLKR^F_@|*_J*(|N#xe#kGHkm~osg#N9LCl@1afkKze58ZHtMASSs@lBba_t5QIv8-i*rPaX+;
+n;%?$St(|2+UKSY>Tv7N@6cVXJn9L-+O+`=>^qPu&<4rtni?Obh1p$G`Pr$S<Iy#f2<5H4Fmu!|C3-5
+aQvUc=}%!Km0mle__A)*I!>aZyIi^^t%#13<DhI?41)B#R~gSh}8!6QK-m_&N7N8?Y`cscIdmCDiVJ(
+PBor#6v(nVMsTpRtWug)lDNKnJ36{o9CTgJPvtTAVPZe#cvN9eo}<79efLMeA9c>J`WuS(#tDn@<u|=
+LiuIfo-0}rm?Jbx{Puy@Gcu50txXWN0Bo=?E0k#%6e>+j>i_9nNGvDAv!p~SR6m__jyq+0E0}k?l3?}
+K2fiL7(LNBxVsGetsxp->~rQa|*_Bc3b0A3A&;kZNM^~m4caJu2SZF$X(y0(+~!tIfyr9S$jmh~#`5O
+AK8A|I#I&+##QOk0-X`F9Y5HR$Q$nS%OA++fFM9Hl3uC|m@_wI5~ScPe5?L>Tq@!!|h>`sTyOgIPZSy
+8lPb{gjS5=y?#*3a`F2MkCs2NR-$&x2}~Kf1Na~uzXd68yIV@*FJlAPm{IcMVO#R6XRjLqd5Bj2LhLh
+Da}a1t@vxl8!o>1QRKkg&(4eYfceV>-F@Hm885*>X1EsNdYgAws0R2ZgaxMozJ?ck#y*>o+&|oG5na=
+iIHs=`ch~U`8t?z9pB~sdcX9detv>FjPR{=Thc|Y;?(UmYtLx0Fj8c|Sr$}&N?lPE<A#v|R(0}vs-!F
+)Ttq?$N0HDpE?r&3XxEmn~1^#N#Uw;F?@5+A~Ar1}1XdQfk^B?vyw2N%>u65^QXXbE3{RdD>0|XQR00
+0O88%p+8Uefd&!2tjO2?PKDE&u=kaA|NaUv_0~WN&gWV_{=xWn*t{baHQOFJob2Xk~LRa%E&`b6;a&V
+`ybAaCv=GO^e$w5WVYHOp}WZj@d5s64*n#ZE0aCr5~_2qsrrCs3I9@oX!6Gj%>$vAgNB)%zIC7KD>sX
+-#<QYK9j{q-@XRg?fDm;cnkM;Z{NYEKn9+4h~BBSS`XkSGUy_1zSiiN8p5!J_pLU2+}xLUN;SbBpsJd
+VyMR>%bZC8GsOd<NL}&oinvv;%Q+m7)*_PU}I-;w6C{2<!-f{4DxSTm3bi~ILP)ZrAV}u`AQ|v?8l+3
+qEft(r}u|<x!s<Mc-DL_=6q+vWMSf&^}^r@M*LmnxA@pZunC`G!NSSDbC%+$D~7I4(I!vgTsQo#7|%{
+yG^Q3KBNIXlNM+?8>7WE9IM6k6d+lU-!(3}&NDF*P^8R2=hC?fGjnLCcPf^DkL`+XJ2k7v%W-RLP#Tt
+zw#29kV>Y;xXcX>N;yq)<^o(&Kj+tt`1`s8bOzXFcx*_i3`qZwfcg##Q=>D1BBcTw6(ypXrd6MKG3Nz
+`j4zs3BM!43-Nx^FuG$|>^Gt{#gdwk6L+?i)Uy0m^*2oWh*wPaiw<3snI$rs<N#Xlt=KPQiNGP&z<yB
+Zi<yDt(rPO|j`{~sO9KQH0000802@m7R;UvV08#(|0A2t903QGV0B~t=FJE?LZe(wAFJonLbZKU3FJE
+72ZfSI1UoLQYODoFHRnSY$FG^L&%q_?-Dp5$z&nrpID=F4dD9=bOO6B5;k5A0WiH}#XRftxCNh;|mD1
+oJwVuA8ysYS(^`FUV9N=61o#(D;(dIsi7TmVo@0|XQR000O88%p+8FCeYqo&W#<{{R309{>OVaA|NaU
+v_0~WN&gWV`Xx5X=Z6JUteuuX>MO%E^v8Gj=>GXFbGBOp2G4emJ$z8sfTXR4I;}SDN<uwK-%?7+@vZO
+1pogBxYj~qBP}%&gE2Fe)mE%wd_kTHg#;uxqs6Z?l`N2jd;5L>X`toEUVn^mqh(vwb8kxL4@-#CG{!^
+g+>l&v-7uU$onjI!`RZ5-!6>wW^F|Y_^n=mbPGRL5ocF67PR7MptxBi|&RyrdfhWVi)?VL*4^T@31QY
+-O00;maO7>P-?UaibQUU;|K?DFE0001RX>c!Jc4cm4Z*nhVWpZ?BW@#^DVPj=-bS`jZZOpw{v!h6wE&
+9%{2s`Jc+jLKfd5~E>FbgD*Kn#MHYs?@(NPs}_>#w6d#E?5Ov#Pu8+_cyk3dh}X5cpc_n>O^nzbRe!N
+ZQReUjL_DHDOSlitPH$Y?}TX&we}n*mxcOPZxYU*#CS#3jObIr$=~6qW<3<z7N8r+I;(8e;oS1mdTU0
+2*6>S#s~_=P>RM0hJq=QWMG&;VI1_)1mc@iT(hLTwZ#=I1WPtJu_4e6LTq4WLm(Rl-6Y5+q&7sn!Ke+
+BZbD>3QyY}o(7|$=EsOj-2RI%^8;0D_;U>m6DZXLi4T)~hU=z?ACfLx(CVe{tvYaZwH%Ppp(G3&5&4&
+`?&od^ki4b^$!<z)(gy9CPGom&)x`~)gf-N(~*ak_Kd6(&e4Nh-DazoM^;<c27+C<<ewuwN`bVEkVgc
+ukCjxx~yS^nchS<%1oqG>6T!n2n6YK1gK5n_wy*$U0rQQ_E3*>mjcKTfjyU?hxDFg$hF_)0!RI%|j$X
+RxC)i+hbNWr#&=k;^sSDD9_gv1cyR9gb}*QH;9~Rr65NZ$64=;nnLSRD6m8dwA>9SsbDcP>30s0gF$0
+X8pGVnkAM$54LM&h<Q#hEH;rwm^cV5p$XzsyRajq30wdgC(sBQvRC8Mrb*G0pIP;7QqN*bRnp9Iltxc
+*3}Yugxos#j1?0I;D{$k7A`|HTtmm4^jzae8v=_(t6rv2Qh&rd4-6$Kcc5rU>HFy~dy#`C_@O~*{mWh
+SN!ZLrl%O@qo1ViLl!)94r;e?T0j_=q8+-yS#gh${*mx#RJ@M@P1!?VD(Dp=i=?OMEd``QtW6GO{K6R
++cXe$Mgy?3LY$)C-Rc+Noy!V7Nig2|i6^7g<|&+gR{U(_rUfuW>9sX*Op^6e2vHJcX?f)rr1I3@&4iZ
+t;h6sn2w|y+MfEUb?0volA*_qemBV74Aw*x*;b#RIXaRF6rrUW{T849aR;t`Y?)R(lX_(c>$lG?rI<M
+N9Gs3(}%i)OE<S5qilCL43o;~#|SxDB5sp1H75Gr-E-bV#Q5WhKIyCsIu)`}(wMIu7VoRkB*emYH8%;
+!XIqLjuVwy@k>q=Maecl$XS225^DP&0m2k=uiC}aZVhX9DR_$cpm~}}AM>f;IlPq713wWehTn0~SEQ}
+(z9u0AM)VT|LT%L`s3Hqh92yqrGu*P<+aqwH`%y2o*%o5ZKOanbnO=avcSe&g>vtG~4X=ZgUEAM$($j
+k_H5crNImOb#`C1H{4@tTSZ3M=TE+TV-eVo5t;hor}6cjd=+FzUpnnD%^c%+o%s_}yWKrVEl=u`ctWw
+i-#{;vsfOx9!kc*W92=yjgieQFs(Za)vWpWqyG1IWqQ<B-<5{i4aEXX{FoFWSZPnGvnAb93f>K?J&ug
+HLX+AM0jwB-iJ9I<SVn!RmE4^tV;Qsn(8COhN9COV|+`A+g>iqgd^wM^ZE21)NWFfPD0S#ION;B#_vz
+bdsZ=bEj+tjxl?_%gBTKacb-ry6Fc)5ig=8dn0MTnU1q=;tlVlGNnGrfvFx?cl2OX^L&Bf&^T{wTVHR
+p4wAJkNrf`FF5>zak6h6mXzd9Fd@uKcd{tajU`Omj4P1J=yZfMX?s3l(e_R;nKxF!HMlD03>A`1GVxq
+f3GecrT1KYjZT02cIr0yz4yGeDwo9RHDgZ(8%m)Bn44{Z?F~roH{+TR44dlk^|o{-Y}DqVK*{MG*euK
+iB^e{pUA?VVG|}&bME>B=Ik(`2WM@eW31-M~`h%7mxbeYx+|XJ=$c!-yvy#0b>RyVUj^{_$%;Dk_A<<
+7kpyqhDsK&OaOQREF(54wZL%*U<=<+0GHt}!IywH7`%bW1-${PGSmx#iA|7fFlLz}3KuX0s7}SpAClO
+h@iHZb{04l<coV(ONC74QFNg`27s8t`T|k|nH!uKiKo!zWf^I^36GY3hm$T9v3P3Zw;4&O7@EtOnh+b
+Gkj4q9UC{Wa2fv>o`0Pub8KEPKz$j4+Q{JgQe_7#EWdO@@`PFXf5k<Ya~WV!?#U7b1RiHCnSo`%4#-o
+e$@u^5Xdq6)9(6rXi?UlUc#GlDJYDS$}$z;ib!to0$fvH<#2LfNX7U*OqJe%?a2f}@G+0#_>bMfp@M_
+VR(+TRy++PVDnwl?0@S&LiHcNQ4=Wuyz1Wz76(W<EhQ;^8?X$<*)tpD!Q6C$giu5cQ$V!fO+HWz=6z6
+!Pz7fKASYbz;_>zZ;6w3F`oKtkGdtjA-=_8(5q1p5zSHqO_5>EG)6IdhxoCVe!6}^Vl@GOyMa$*xkDH
+PF!raV?P1-p5&Cs@MXnwm%1jZDXWq5UqS~qV1>1yj)q_>e3b<E*KPZo#B~}`*z0a&gJ6XFaf(VvfX1{
+z(ne{ff@&$1QEar_v0q%1DwWEPLQ!H0?;OaT}dk71Ti_c~gV(Km4mf22FMqS8m%Y(!zmtP+m@g0n4b~
+(;xyB9FEHnP8)JGpz@FA5tuQf=I!9Xy!B*zYWl>a%T7`BaP>8aEqV-i&&0?HD9^Yy(gC4}1BB(Bj-2w
+#Wn9cI!&zj0EaD`F1&@_$>E(b}jOPKD9TSE!iytS35c8`Fbwc0m-o>b|S1CG3p%Dr#3fFa^*bEkXCWS
+F)Bzun=k7<ik~70E$q@?M|?AQ^~Imo@|Ai%WtYeIN!d+4hx*rtjo%p@sT~VCTeExJ?~gm<NbE_|=z3F
+`GkbEpmg#C!6CNjz!_HyKtO#CmvfN^Ct8=g1<XXmOdkt+HKTfWVGbA*7$?d}7BDUlMYhVdAQ04VXOs%
+W$@S{QK7)sYOt$B*8)&?fHNW^X-+)x02V7UfXM&q64ZVmcHF2Fkg?!Gq)3;8r*YvCCjYXdR}2+7RGOJ
+8Vf;G&cnwv(JV*p%6!FVu%oT(q>#Rkm~=XZ9;HE&x8svBD#SE=Uk+huEsmPcjK&y<#FCJZ2P^uXh^ul
+s$aq`h`UrT$ihKTSwR9WUcXMonqi&eKwFy2W*xfyj2_YXazHLL_C<>HY-KZsLRS}pK>cO(SYT&a6zJO
++tpN^-^42EJd5;FXg(unkza)zTLt;vd7vCj;&G6`?vprQ%Sh7B7g(IE18UP$Of$nhtSYk=dh;p_4iQ3
++HGQGb%%7e+OGQRu@6zC5CQ<o5C+?7%_j`7|4Fr)zCQ)1Z`H}C&d&2RddfYiZwSq#=*z-!ix+Lwn=C?
+Avis<CTBv)P1BoE6eUcqMdCh$ZWWh$?CXcC5SrbteB9M)nBr4kv$kIFAKht6i(^d0f<6Amt@`l4<CK=
+M<VwAO;5Z?g69!!ZEg-w*%73I4qqK4AN|qkn{H3?m4fM5wP&8sHmHmJGfL2%uOu2(_SM3?TI-W|?q-H
+2}K+f&&2E_?IXR&@l#J55~b8BH57SCXF@(wn>vky8;ZS=?xlfD0&lz8<buqj)Fz{QuuFB8Ud$EHw3i_
+0Lqgaid-N%2sa42A>j=J2tcr$DGZhqr!O%c0{M$<5M~pT8ytV(HnEA~4IXY7Y&kKI%b+I-P8|NVM4lI
+ky!u3GHe=a`^%Y73-Dz|q|0WY<aa2{vw8RsT7$2~$8nx7c?Ysxuc%_-zC>kGH^Cl#&T1C|xVreI3R9H
+`d-UMgG1F;DQE;2;5of%kF_-ECA!wc>uQZ)`g3)Z53ZJ>fhTo=4ilbSOmSPJsisLZ-mE{&smc~kHo0{
+&#%Pw~PU9|E4Yf&ShCV0M`a@-5NQ!2NlLx7|-?7l7L3-!2cJnE&JD0hlMe+L<8d4Pf7tyZ~+{xVB%mG
+VXmVJF?4hqv2oM+D;Q6)2@YT0XdVrKh>>6ApEt!lfudN@`xjk!)~erUti_t1O<2A>Cq{B%=NDD1`;mx
+=0why7E*kSHBKF8Umr@$XwijE$cI-TL3X`HtIRZZsX1%6;&Q^O%lN2meb?BU){ukSs$Q~#>YEqc-2^|
+5v%{>blQ^w;nQ_MG$R9^;zvH?`fX7#`(cUm*xO9(HYD`g8L}t&9_tOJ9*TSm5d(wJu#T-)dh*WyDd_-
+>UF)P_8a}E_b84eQp7;Kg#l3XCt_4C{Z;S6|$KS6QCV0MYklh1Y!3#+D+ZXKU=S@TlF5#?=&Jd!%ZkN
+k3LE6luT6w=7Tc1#om9oAC<T`KsV-($Vh$E$oPd4N7F8-R^b)W)sxLZ$=9d7^Z1W7pz&6S-*Zu~8f$k
+dyh2K%9t;?+i2+-?X%%vEBl4;49PK%qAv$e1kUtf|)4)XbFLY*Z2Hp3SkXi5+w9M$c!0?iqz;RWld3)
+vj>JjEoL7_BTgEIv>JllsYVlvK_MnDErrSqeyF^gZsyS*7CpB)6?y9LEhY^DM<b6?Q$18R#C13C^wmN
+0FwtK3n43MJOF5sqQG%(KK+ajL02Ms0pMI2U9Fd2av_7v^zA0Y>n&tare$wYsM1t~}<i)z-TNn~=SFC
+{n4Vj+_<D*F*6-mld%1tEzr#AOtij1M#1s;WzM83l2L71)+Ny$_?*-Ab`Ww$TzXQ0;?g}>vthb5&UCd
+5h)9!5LkW3_D!ZAP!Yu}0PknRp$uHTjV{hh5xT`x9g`3cl}!RThs^kb{l<GCS)-!fgSFs^b3c&GqeHm
+B{b5)!&HFPxbl#d{eH`KYpV>zZKoP`fLDyNaA-1nzYF^N?yVfg<<mBPg8xZi2pCH<`)6{rz`mpR1t*4
+NfM^fFU2naApocmwn^f})Evi)jTeR&gDn;>24^5yk#y0tSo%9y4Y7Aw8B#A(F}4_bX?z2tn-~CJ^pc+
+V29Fm-3_g&c8?%6G%KQdash7nVpec@RaB%i;6Oo%3plQ6=wTW;8C(BWws8MPGY6_e$-Xz4*2p}1ZUGz
+Kn{4z?T;ezTwJ_F%RCmTHaOYvJSmS?Q~gjLh+4d*xFw-bKGE68!Qr*vWM55N-aPaW4OBG7FU{#+E|hi
+=ujKMP{$yCT-I;0%6T;sQWx1V2D-IpwD)1_0)RV*muxciZ3sf-dwX@)Ur#-VY*g%ub;5{v!4o-+iEB`
+TaQeVNkB1MFIa#0KbDdssZ7v&)_5%4c4j#v?-r$kZ!#i$1G%jwslvIrJ3F+u^&Ph`7VTcP7Q1Ap#dTQ
+>Ek>1m^q+@qlf>q1RV^7vw#SmKZP(@owsOLo-2S#0nEVlE1-(OLHoIV7c$G;mWr2^0H|md{lQ4^`OWM
+twtb17#X6vV@9=5s2lN7v9slN`68M{WD58YKGT;hz1t->b1_Avgh1ds9U+Vm-^ZQ-RC>UXC2PcxKPA5
+cLY9RfAb?aNhT}Tn%9cN4w{d!-*iQI~T)rID$x=N>A*P7SOEc3uJtXnCHnNXqX?sh2-;roh>tW=ud=u
+l0!X5@E{m!CtExgsz>tg~`ZTZ>98{b6JhyXL*S$R5U#zrfy{4h*yd8ebvo^Imk5ElL0u2y18cvO4WjN
+rB_&JRlF^Ny1E>ORyIRF1g!X!tG_}2`lw1D^MGf^o4w$s`7ESJ**UG(I-VhzcP=mLtAGMDm#j9WO7{@
+*cpy9z2+WBS&#X4Mcj@B#Na~dryZ=1_$}LVdOH{L{zj}Fa+OFV)o!&8(0~=X)i2j3Gm2Gw3{b6mXAlP
+t>cA`7TK|&hZQrc#tf&fX0c9-xdRTsb-tV07`s_V5OTn}Yi)gbkxfeEl4L)h2EU<3InGIAP%<FCETbY
+)~{@r>qFn~z>#Dvz{Q~9B;0~K5<d8%z(*yeRm(rLUm)(;UHTzFwY@0`?UI9Oyk4oL32Q=Cf#UYG{nUs
+ynDPR6h9orTjt@1({;1b#$DE!*`1;jIc&VD0Sg(EfDoC#yd_QHFO{h#APIQR9!vG$?L!Ju^LYKz8%4A
+FhaU(!8~IoF<Pe9j;>}+Qx4>JaUIb6K)1hnc35vN2NUJk)3oC*Q%ud2q3`1tu@B2&QD1{nU7g=RBCdp
+U?5PZMIQmGQa3s=g-fECrf^@k6e<{3{Zx>5>NZ`E5aSvVUt;F4yLZ>AHP#rjMz7etOW;wBWD&hsCl@O
+O=P^Zkr`34AMSZx8%lkuHt%fy}JV@zukB#ieU(e#*-dD6#ThEh`2zoCckF0$lugWpHpe#ircevj^9%%
+M34%_pPnMe)6Lwt^eU>??E(_&(kJDs)8iM87r^xq~mEX)3Y*>BeBB1$?y9r&hh;%0F`e{GZh7l(e(h4
+*92=+6=DFS;A~iWvZirkD+kFN!t^7b*ZWD^ROA^)f?8i;7(w)ge&FKu~`zxRGTjiY?w@GG0VG;2U(hi
+J1*bY)E_)0TO^Le}GyBM?p(WF9ZVr9WwxmKLCH=O&TtIg-R9%fFX+|fC49D77sL@EX!L2H?<HKB3<m@
+3#|zjLqF&M1U}#di%mRPtO!Z4A(;&W`s07e478V7{QkiVIQDC?P5mOax5h;bA&q;Z31D|RnLvdufE5*
+-?g3m5WB_imGyUM?-3n}M0c~9a;4d|^86o){HU&-+LKGQ%nO+>bKU!{qT%g~;eH=Zo81BQOz2G^toKc
+aMh6TW!`5nw*O%O-zrO?@zG6!IegN<!oet<AX4o)*Bv$%(TWI86S{NNqWG_i~UACX}HtYnre0qD)E2m
+_aR5si08rwDQ5xV2HK^J``T%MCOxd%GvuXc{Qfhp0I$PVFBJ_KNkkt%7}9gXG1wc={QK{S#+_f1`m5E
+^YpE6%YN4!329v%?F;`(ERz-P5X2h%23J1ARbTcO6FDvg58re*~hlhxS9brGp-k;h~Mj{6JmSxgobr4
+^T_c&!DBh@pOf`ypHe`<j@q2~PA9vIp5gsnbyBTxkH-YUwDpkTL2*&d;}yM3waUpkpKjxJeVGNjD-e9
+^%Pv2P#due@gy%D;BJoWb#dV+bIOJuzODjzvu9|1_B(pk&ac1zYT9psn+G!uh&fbwLuszPMhcNR+Z=^
+cN@VnNX6Tvs3_E0CxHX|<)eMD`rYp_$hC+GtkQ^S?0RQiOa?bg&~qCiagT<zj5QF529cbirj9o0}WlR
+Gs^S<J_3-OUU|MUSXXoksi=2@cil>GBhUM*zXYFJK2XoVZhF(xr{G!|(Ks!gp25u;XoS{6?+QKdO5PJ
+c%#&_?Wzbc*<>!F}kpLBLtbQcvG-7;YetPJ*rP34;b|8ePJ%%Y55Ef(DHKp?8$JxKSUF8iRy9G?=0L1
+fKSUg9B)~2KQT-DLOFYAc~sxII)GW}=O@zn{*vu$u!1kt1N7mO=cSNl2R<Z^t8&%*)U!OXbGa6usmHq
+7RQK&@pWIB0AD5b{u#U}`3~3MpybE+~W!nqU@)gyt=vXqjVU5vZd)Zn@3l}acr6`Yab~`h}mLKR75i0
+?@KO^m|?`O#D;o<q<?jx<i?DS-+9tp;byz;jz$9a!d;Men6Xpf-~JG_@BHq3SIVNLh<z6vu7g}}woxY
+Rh$8|BkZrD(iVvFO~9CuyeCPG}MqYXjDil{NXu_J`Xv-9%37kb|wL_pX2{RKQD#fRWuUuqkZ1yO*q~D
+IP(mXEUynVbwPT5>D-~zwG9W<UJV)@bh^nu>SbGV^CKg3kDG3tT*qhC>gX>3s>TN({F(nX8(du-gq=l
+5Cd`k5eS9?X#H&b8kGO;m=84mWB;FU7^Ru7pqO}hk*RQz=PA8dlapwP+)7@6OrlE*fH(qQlsg)J3B^&
+c!GZ-fqja%O1D%eMi_IAa0FN%B8GV_*X?Ouha5ez;47LdCl==-6)5L<q@ynkL;1`Ss@;szADZpD|Stk
+}ROIp-7yu_kKuR}Po2=?^F1Sski)rKvO>@-;n5kSI6_yWZ=`BzXZ^~*+2eA>Qw&M3bO2{Wyq1-enfPw
+1zRFiAo}#LxXjPyPTqKSh33KlG8lhlgc=`Y(RqQNJu<U&iww06Fj$`32DPvu)O9J<vq^Qw>A!p<nthp
+<ia~GOp*Ew`k(Dz(sD0;{PSW>(vK(@AMf4wkZBAQ+^lW#lJ;(DNBSG*md{-lC>KUh%nHhw6OEqQNXuK
+TaJDXfc;8#H&Z#!dtC0doHWdKb;%1a*bc;M%Vp$QeP)m}HDs)4v$jQYhuiL{V91DmSEPf}hR*`yv#wt
+!<%$|xxqAvXOjBiPoyY6I3f2UnLhfy@wUt*^L$rQWUAx^j$k_YW^}VlcrSEq#+fq!NjdWrS3XGPizFz
+5_DblAX#zGEi+lUVuiM-pcfM@6W;Vhw7$?>$6F3Mv(`$pmv<&a)zKj0tkh$BoAEWW~HEs?NwgI26L(~
+s-wtQHz`J`4e6uIAW`*rL}Ci9A)l-5X7MM#6((P;n=&w+WVp;z}vk@cE2DWp^+U@2<eA&|xx`6p>m*e
+y|seBXiv|p>&^4=&D^M=cy;jH70dKIG^m6FxOOlTNjWWjifz36(S><DKt^8+Sj6akfItqMh8~Zi!PIm
+eG~7ZwC^g{A2>vfpV!eKa!)B{=-A86dUp)Ap<s3=-Ns-O4HJYzHF;86-`eUlvW=%ao|-4YV+fI)!|5Q
+b2~Rll=plpF^C1_grjyL`y`qk%rgc|zGr8ORe%!iK=~)SpU$q&GbgzZZWOq}`l3fmmx9gd(w@@=hCY5
+_eLOrEZIZd3t17F*j5v1+GmK#M&YZJ|;qb~u;J>U0=z&tK)#2or?l{yavnjDIn<!w~VItIhWq#ISisf
+r6OK2hP6I!xQk>d?jR`0mNZ<xx|>lle{xpbu8?K??XcQgHla4?l&@89^@Z=#x0ks$tnwFQ5=h8@}1gb
+}(~~4+ZbfT$O#%`Li!6sW&ltZ7|TUJIuej!9c(6FrOPt^V_Wr@L90+3HVMb(G=pUN7G)Vct6^Mzw#{8
+JBm7Z*hb#dgwWag5{CENy=vZVLFQwpIOk0KxVyT-o)vw*LfN{|*KC5L6{GL#WXg}2ZyukRt!(RbZ>fU
+OPxd-TxiRKU!UMXR=hd6;T#k6L1<x&%O6#lI9x?64d$w+1k#k1NLc$rsAyz}yt4&-x7Y@5!Vq8NM!`<
+O)&!eWG-461W*g>v)++70IMS^G;Brl!kD~Au=?#|g=Y9pja`&|VaG+eKRQy%SBs&H~h#kT{yui!19=J
+4uf>v!Ygn=)=uV|9eVZMq<bRnFp}`Ec?kn`OqkB=E!Z)-LI5Yl0FxY;IkpnIkCQcSXnuIH7q2X`Ga!b
+|6W_Aw!S%)uYp~>3~-hZ@a630jqe%Xr}9~acTFt(-=n+vTVi2jyd8w!DSWXYLXU%(3WPiov`2m!|>j#
+y-OD4<BXF>_yH5#nj^&fHuhI%#TB4BWN}_t-_Apca4SpoYT}%du~DT7IjKW^xhvc=_Ui$wa(W&kJgoV
+%gl6OF>Yetm4>h@H%Pu+PdEXq%43nDzJNtfe)zU#l6$QVE{#oBYl^7)@c*j?m%-OSiyRLo4YnchcgM+
+n=rkz?f>OmI{$cVC1YvMQSzO@u|cZ(glS}UEnuW5(hv#i7241$8Y2h*<(a{$rF;Yl$o^MV+6emZk%ei
+iMUmHgP{#Y4+$5&Zb~X&Lr!(6Zl*`7JHOexhYKMSmH!54a1l!CnlE!I$U*5?g}p0>HCg!FhPHL<f-RV
+q}QYFKHQ)F1`>1e=#C@F{LoXVzdCXDo7R&N(67hWSI}JH}n;+PZ5jVg(iL%l0d&qD$#~Y7ve>{C}Z%N
+F$tGOuo#$H{z*`asRgVMqc%jaL{;GN;zyydg}0I6;%ix^N;Zof2U!kb#9z@e`D*bzr?}r~S>*lSpk?z
+fwCqL2^q*;&#iF`k{*Ti#?O&i}f(ALT;yUVF*ZR@25^6<7Novg1&JT}`)MPL^B7S+cj%AyP#t!CBv)m
+2}Y6g0i33<aocz&a-JdW|^jva|In3F!g(`t3gS6EM>*kwI4kwWhqIa#rR>d)A=7N!baQ<9t5b_;C@f^
+-hWWoJ3fjg^i9X*~259S*C*QQYOz9m&rGa*`+QI=f8Mp%r=vFVp4Nw^a5x#}His5@6{=aS0DFrytf7v
+l9eUyLDPVIIQR-kLQEHDAOcLDJC4&8~M0B?;DHZgK!+6!OaD!3e?>t&dU_7+mZtE)T}BY-j`W8aJrye
+l}pHD53Z#|X4je3;aZ?nKe1iBx1ib|NviIHfI8?sAa+-62aur~q*hJ>p_4<BV6N*+LTTgeMidv-)&^=
+VrRqagtTa!cuupwS#(fQ~uLu03mb7U(<{`JwIlJ0l)aF4@k4oh;0=Fr{Ik{Ek-iVaGTJ&xgUn0mN#Dh
+r9NflUWLDZ{O?dIaJLb8Ac+*q}yW4NVmk=<zyok)9y)`&-p^5X4L-s3{(A(s`;ntHs+&5%Xt(GPAr`(
+%@FYu}~kPAjzIs8ViLL}Z`{lAXKSIX~R!I~KKhc@TUkBKt1eUm6}gS&cera=Mz~Z0^caur1m{fuH%~o
+^7kyMH)L9g5&6{iy5#_<k_w(hK2BAuk?Gfw3vWQ?QC_IOAVnOauikbL!hba$=Ra=!;+u0OyR1<1?Gz{
+-wO0c=L*l^Z}A)%r)+&q*}CAz;<B>kGErnh!ed$RzC`wz`I-#zi>Goi)Qk!b2%juBvS7Fbp=_PmKXHR
+!aB%S2AHEwoUp7t|FrTXqL&4cZz^ghdvUKrKXN={=E@@{W>SeK<SBmr-)-}CZ7@;3bj7Eq)Zyr`=`{@
+fepu|m{tHX=+NRf1SSw-kN4=CpGac_9aZuAy!%ofm5S8+ehNiXkabasZgmdfC)U*EEK-b_q;R3D*eX7
+}&jt546>PeC!@OB4YWGiHjS3g)WaJmjoD@Clq&lkry=Z>)^wRg+!z&pJ1DU79l|{bIZ3A<Ghdjf*}4#
+S9xP*Lf{h`_c3qe%QC!r*`_W5A>NQbz*0**GbPm#00-5sAM8*k!ZFTXL3BM1B3d`ebQivdPFz0)5E^y
+1vC~6KsYHH<*x?>$?Pd9>b0jRMSC4cZX*1#3@-As+%{JfH_YOc)KH8xI6|$ue3&0+??7{1XvS!F3{S>
+z!fxGdOx)>l5U(Vv6i>938YJ{{umudKeWveYXth_-aXsQ9*=Sg)-gYQ89}f>!Wd`I{8u}HvIj%7{f}<
+)=@Vd~&ihU-{WDEAGnkcX<r|YMJ=jK6OPk!a2#K@Qx>6`=+QElHwkKw8~jia&k0^i!TbCk;#acI$+xi
+{w^)}fxj`Sz-@lipm|)rBDQ3idMIo+c$5Zl|jox_r=*esaFw=&~v8A%@rC?LgeKn61etBzT-S29%}Da
+r(d=dPgV^a!XbPxXpM-U&9HB@7Kq6owf04Jsp@+ScX@Q4==|~^9c$n>1{c=WpIqR)+*GVy7!(Hg@zG{
+Em_j19HCk>&O64>c$gGC$7|%;tczxwnwm;>(7ZiAvb8&Um+LW<(!$brCO;C$j(Y^d8V-#0b{DTZ>VnF
+6aLQaGGn0sKA|)=4cnDu0cS2x8-TU6N)FTGD4YIl&4jjCr_H7yxoJ^frvvYH$>r<-}o3h8fM{nPE`_3
+$$3BU!l$|`BR%t&*s5PT2houxl<DzL)#?i2ZTG3Ylyom`DoGL|KpNtj6+)NGx!Iz8_o{N&^srTX$peI
+Rpu?lbfz_RZfkGamkV68VGn&H6E8=9Rg!#1HXJT|cfL(L4(m<yquMYWwdE|6sX)((#vknJ+_y(pQEIp
+txkP@Iyc&Lt^p1rLXYSgjzyv7S~<8A(IXMb&@JZE*3vDTu5)qED5AcvKSBXX!)=t;Lsa5U7~%6m!lA{
+*Cp^5{k;_uoR>&mNiy-0B@2eZ$zmP_YY6ehoC(7Vp$+gQfGNTjCXBqSn}G3R%mzglN)026PY^I~z~OP
+ggqekT0|HF`WvGzgE)KzR_uV1*Wtb3W{IaR;Y(exOjq^S>)uRnNf(65w^Fzvqc8W&zBMSFPSiY+xuQ-
+zvxA^~hD0Yb-5NLrfQ!p%X+~$$40pfYEv{4g`C1-?im$u8#ZIFBUdTD=mWzg@I_Pdq+nu7}cJ_(hdyE
+U<fQS?bYecB;yEj$OiJ^Wbv$6lkFcBH3@hM08y*gb?B8Qwyl-vxC|cZb5i*@o+@{p@Vz+w*z5G20s!r
+}8Xc<oJ5JP<RxwzDkxVB<uobfFGK0yg9WncqG5ePnd`&!E`R`dM?h?9S9n^=1y+TsJY%gdld;1XGO82
+6f%(3txD9Rc!f#y`|;?hU?8z&ac1w4y$Vy+<O>Zc(<i5zEM6P)QSz9QTy5pt_3vvPG8|0lVEFFXLAzy
+|1TR?zr4i=g@7Sx5#)9gX*LVaQ^=Xfx+eGrslN4}_-BtTLzg3}UyX`0X;CQ-tq<8(e(${<IOm)a`Z_y
+B0JI7r`o&mVUKC1Hh{E>rtoLOeEjX~dyW2Y>FYd_E@$wkkXdddceSTPzkZcoA=iO5F?4fIP4&DZd5h-
+@J8xBGr5Ed(LD(M2Rm&&1UrLuG|!aID|g!(&yW==wQ2y$jHBd*m^+F+H|Ek|!=4EYjXH@ZF;?t3)P|Z
+GavRyqLC-ePQtHj?vrU;#l-5sQJb)tm^dCF~1(Ep&aE$S5Uh^R7#_s#%^v_b8-z%n&C{VD*<ui>ST-c
+4zuL*nZDk1vY}kpJy*hB?Ff2xs8#Q2*S(h!&zrTo@998|OPv*;`t=y7Hl&)up0?TvP22F~1k`OHuZDF
+Na3#+t@3O^a&roi;Pqy4{g?Mg+lAV=CMPsk}?YZe8^ORPaCM9&=SkvV2w(o$)=-DaJ6E+@*wVn_A%g6
+wX^M;uWAJdsFq&>zA^|)upf5F#vHiP>1?X7~rpM<l%b^FAP&j1qT8hr$}K3mYGd++g&sHuN3#r)5n=>
+yt+J`4MY%n}5q5SV6QnualwKnR#28I+-61jSJdqi_O7aEACg@dVkxZ*DSd$p%5-#ZCi21po{aFJKkFA
+d5kl_>vg;IzpCSAciJ4Zvin(w0sVT4UQ}UHc`4Hj{-<du>}YTbn&7k#FFG0k-vexC|N)^2CxY)i7NoH
+z%rI-TL5yzg0V5W<f4L!u(#w>bcu?kqs0S=zOq6i_~og4IRxQ&$$X_>`7i**1N5)sV3r_?XYm1hhOL?
+%#a-@*|I`sb9b#{lwO_`@@Enx=lH##M%x*7i^ckahenrIMQ7!e+R<AtFd4-<tYoO{Zv4k}KGubqBB{d
+JvY-Xd*B|g6;Ali#tA4owTh>s=cRXf4sZhSY?Or{3}37DDZ-b*Enf0fbrj;F>`vw*g-q9>#aEc^o0*&
+bhwf<5cANB}y({hiB${_Ohx&gDUWc71>6@}M8D@9$TJ;60Ti87VxG5Jo53?UbMgw!hJof4KAGLot!a)
+am?u#xL=aNYd8a^<>a*Nh;&=u&9y2_c60Qd;AgF`KT;2btL$CALnf29?YuSGP`<Pr?{p)(}rz(Z)Odl
+GxJ{9H;spSJIm1&wMSjbfP^P_5{WpqP${4f7EuPnb!$CnQUhXQg5mU_DxNtVXjBqsd6k{+wcUwWK#(P
+zTooL;i(Boe8fKad%B`8Oyc>4fJorZ|*{`r>l^63hVxpZxKFj)fZ5fspdF9@*&&c<WW&o+Dov!oK#MD
+_V)|ge~xQ%wF<L#kb^4KAT5V_-rD|j~&%E<fcy*T%#r{!yHtEReBK*yn-o+r#&$7c0`%9&4(nLm!==&
+3KW0W0(R)8IMQOE{JjSW*1+a6xY_F8L1uG9Rw6pG*ase{3$W?BRxb)rf*%PaSk|CWH*VP!nF1FW!#Ep
+z+{=BH3HRC$j4P9Q%@NmnV{&KNugByhqfyB2eb1x4;>Z{c-6w_r@2*FTGgMD-uf;or9rqGMZASd?xss
+3!C_+SLmKlCGCpfYH8ir#|W3<j%cIxF30`({M@Fj2@PSa;7<V+VtNgCHF~ey^0aSwlp*|m?t}*dc2he
+&>#JL8oxPLZb}2&294C5NGd+9g?&Dl~p>K1>Ti6;?%j-cc+*3kKL%CJO4sNf9G$IDgzgk2~owhe&<V}
++}^M}@o_W`7sj9#DX7?0@d^~r}@CDS|QRvMO!3-x5EyHj}H%Ew3BueRI}1`T^u!uf`h0cIRe6I77(lQ
+^sbxo4Tczdr7Kalx%=ruT|@)fn11gfRi@Ow(s%AJjU1If1R#FmNMec+W7P!-^8Eqt&U{lOL}poi&X*g
+@&Mp<KGsiR-Sy5n{Pr8$I~~tZ63GpnJk~}d=+%vH}rR4{<B{FZ<_J5=F%UA{IzankR=urCYO-YAY4E)
+eZd_<EkQG3xU_@MXt3n0kkpp|4rDGvz5;K^MMokpJO`LcfpO%LpAx*1QNcecc+rmZ%lDEbpD8nc1aRz
+ix^T($Tv9)iCENz^3ld*6HJ|}N#sV2kMN4i?6fGhb%!{WBL<30-;5~k2+W;kt5ld(K<*8X5H%rRuUjq
+0m3i46>m2SQKA`TsU7IWw$#uNaQ=PXuKF&-4r%zfD;z~?E%obh`)hdAy(vN@)F8%~_KI7!NvQk11Rn%
+L<V`|a<NPGGP{O$STFpyk6`psM!S_}(^p^B?i|dkAS`$&%SX{)u}n<$WdFsAiDpdydRg<LQrtn#M%w%
+#@|l2iR+%&pg7k4AP3flMC{P#Q2XmRQ){;HG7Lg)yWuH-OjRD=k97apW#9#TPj|!tigZIu<sVLgUQ+X
+noyMAtK^wyp`+t@-k1;Qu-9OLS+kW<IGo^h&DI{bHgm$(+nCl?$*v1n%Fcp`x$mg0RBS2n@gzrRjB`m
+vS9cw`VEGiDQJ}Q$W`b=o1-0(p`G~q+*?0G_LW^~C$#{lX6CUi~$*@24=K>P%inWi6LyOR-W56n$QK0
+9YQyo}Ss!j6Z$sGK&<tnO`(Ch3pMCib1ao%=a@Mdcs6bw(CB`ZC}1z~mXgY`~gZ(8F^1366xCW%Ju5m
+RWuTx)OGi(8*m93e(CSM$YWY*vt0<msanw>EM)if0^;wKKk^oLi}^#Q1PO%jA*(dbnf}ATc5QGaBl95
+$g1viHM^ag?c{CXuj^zCg`n;rpWq7AV}ufW9IGHWx%ifp^pKLo0Puw^$YW7?+f&IUYI|7U!bpE81PWB
+8auu-g70kL_xLNQdz#wsj<+o>c0tbJ(;+6=naj<n<ZzD}i~49Z{>n>O(Isw#>YcSC4VSJyL5BmSZ2@u
+F`bKjTwrJ9sHnI*Y&B=tOn-5<9u+8%U8Q`<3?$1t^?Ro{PZkMn?t%y28me$P5DvOHUJuYDBA$4U&cy%
+&cLl7O~Reka@NiwQCO3Zl@go+RELPa^;j~8AzHU_k<Czrw_{mC+UL1K?=dN?bEJmp)3ASdCTtx#e1;|
+IT=TdN4r2mm|0_O*54Kk-^Lp;&C!&hx$%Fh|*Uj2W0o#^!2X0h(;=6~j7EV#{&D?d~Rg?>gSC(PzBip
+O&H#{3C_T#M7@+5p`jCcdMk=$JMYsufxHo|Gsg!58AXys`#6gMESL;nyg5=?}+*R_`d|g|DDr*8k7Gx
+=C7d`pe`OPa2LMPFBV%e^QzsDydochSDI(M#6REwuD{MU4PIFvNVJ5JhVX)yNxI-I34j+{5D@?`f-k1
+t_?3$a^e;fikoc^d_{WF|e5uEj2Cr}lY_S0Yy-tx!O91{4FU1`gVo4n(h(&KF_{&E9im(WR1(Siyj?m
+W?QA>CRioDWO(xqYrLH{Kb3risDko*-CH(%^574%u$C)XkyGxMnSZ@&9170IkTG=GHXbMVosil$F&Th
+iG+u<Zu@G)UAt@2t;?p!{7)JVN?KA%G^H0R*FOlGqr3YP)>B^pBN8|L)R1#z6n-(!qY0{oV#`yyUL(E
+_X4lyR68wTyu)s3!GG9G@(;;Cdf*(Zi0b2?t&DewL^~fmKPSiRUW(YCXgbnQq6faS1N2FyPdaA7%JNh
+g3=<|aP1n2^|j=JdeLEV?ybPq7L7*bKYA=(#s0Ir`>JW$<P>gcjP?<W8!zN)G>dlKCf$vSlk}dQwhdz
+uMPS3wndybnQ&0febQcyxHlWerf*X@C3|#Hh$*uEc0b56oNNYTi4i^NAC^hElSx}H5fOfcDm-%#M+hc
+hg(ShIA{6p{<@-|y~c%Xx*MP?Oi*6vA{aCQzWVt4kh>b6PXtJ$&;;^LNm(i4p6(_^xB87$<<3rQs`92
+s@oa{2{F`rA;fRk2~^md!+=!MBp8Z24bp(CagmnsX1Q`Cx`lFh|H!;Dvjw5Hrt}Z|NZyPLX#2rnlL9f
+9T5rq}1KyW(<TslEUxR!y0QV=`cW26+ARf=kuHm<ZTnyOc$c@%|C0O3BpSm&ksw^&RHD&pJN2*@ABE-
+!87#RGD@r)AMqlFqcU&;xeL<c?8f(y^`gK+l3Q~w)m=Ye(4JC~S&I{}a|<~spDDORj@L*woV*xt!h5i
+{>v1*B*h#9lbY-uud+lgHSyYjSm>>lxX&=RNZNm~y`JyerYks_2rnA1GYP>Jb7Rz>-oFmQ3OmJq8?tx
+nOF&lP^XCh2{wSt}#Lf(QqZR38AIY~JUS!Ni0Lmw?F-V^Tmd?T2&jPpe6tB^t>f61kV(>h~!;Q6~j&P
+nxH{&>fqs<3nVEw7`R;od6leyNn;#`UV5S7F7#)~OYlpda+PI9gYIum~jDi5}z{M^$N0$E)rnyFRJ<-
+q?j{ff<}6*EvH7^=>T?X@~Q4DiOxtH=7GZRxHr?jRkFO5`R;KAIb)Q9{s^+9fP(Aw0&V2|1VGW0mXkZ
+(N8vT3L$U`p%@HDP?(@8nnV$jq8OY(aF{}Hlz{0kQ$guh8DBVDQc!?Q25^cqiwQhI78^D7N&*EiyObH
+mHWd0LY{SGWI`Rej@T)L!{E9k!V**Rbq+}rmak@bDG8417eR049u;0KomMmbr^m{95oGdH=r<dXr@GC
+(z2^I_eQfw)Cm5M+XL<brk=w)zXnpyg!Z-t4O#c>R}Vevvi08JtO+VlI$Ke>J8pBTa+%?LB~%z-=-u0
+YFcc07EY9tvRlkAUcC+$WT4rd(YEd)Y*cHw*9gaKyd%<S^(}6k+M)zB;|ag|w3~D%nRoVlM`6e0yOb&
+v6m9SnC{sla=^mq~tq}FL~_ZTly#Xd4qBB=e7%1{kUrA-&yvLtA_raW&c>p82XzQ>t4vu2SPls=e@k8
+sW@Am#nUaIB1pZRl>1;Em=jCvq&yRj1&iKGr?S-ixObmB<+KB|H|4WQkg)r)+)X<ItE{sii@U))Lbaf
+vaW^NJH8stHxv!?}WY^pDItl0PYWGA_-1Bwi<RWXr<uYUtQ@yc5BEZ&mCuA#VGzZ}#9DS6hy>*ctJ2D
+ZFPJfshm+QXguB$pKFuzCEa&a2rc0KkJdLuGeAq_q9amewatcliDXtc`dJU(kd@03Tqg#|Te+Q!QAZG
+SM6xVCOnlZ50=zdF(^A#LL@${k-rtPMb^$cbsc4G1YZKeu=!v^)$5h}%)<RISkaZOvoPAX`^vXsk)uC
+C5CKxACi#F|=5$J)jf6s%4!2Qp@<OQpOO+nG#9v21ecQvy0f<-s5_k<d{Y=MVS9kQQ;4Lp&vT`*6-Y8
+B#o{1J$=xp2)mWlevL(S=xGm=hhlg4$XCOJ#Mi`W59zGo_HJM570N|o`Sb`~V=}msTs1-h^WK=NoBO=
+ht=Q++%(GG`9ZR}81h`s^*<hjbPPt;|HC^DhMBJ{bio(+jqowO9)MJuT)ZL@2sdKSPExM(tsD^YGNee
+?pPtGG{4L7{ca5Y8~n$r7ch==m3HX9Nb`|8m1{rawLd!(R4!tklM8`9$w+M=DNXOWxEF@1OXJ{iQ5S@
+QxiMdDBnhl-*Ef4Vhdykd!Qoc)%z1k-!~a+!KhHi1?R9I7tTT}T)64EYJ)wYo96=QY5JaeWnPN5*zzq
+|60X+xy*hmEEL0xgY6&CCBm;s@`3-|8?;EcP9D+aQ-~W&yHgT2cXFi49zUn`(cd283Lg(lp!$yoj8GG
+IQbQ5Qp_S0fplCdA-$3$v0yPG1K5k;MKmVptGrRPAQ75;t#tto(yw0u5G)ck`ACoqU+5W=OHl=&c;8e
+r`uZIK%qtHR`<>r-IU~JTtCvy<_;PlNUi`x-`LZw*OOXG9q_3mls~iJZDp>ZCWg0Kt;+Mf3NMFzg!<W
+D+FlR(95KJO}37YK-G(WYj!3#s?+&JEB<vey<)%CaA(^t`<0+;_!fhId{KhY=t5q&=WryudF(0if(x3
+q$fdI>*fd;ZX-$>JYsA3>UFFK)f};z!RP&$bx<en=bZEb*-{RJru=UVVrQ6r%7`5!mD-144p<%0R1^D
+O&mX-3H%lIdQ+1;D!FI1}}aYa`C)R?mNqBkmPRfc1Ipdj49YvRK7n{RmVa6NzhpTaJ4QxX0K!6DVMB6
+V8!LMkMq%ISw&Rm4i7VGoz7POG#`7{?;@$gysOkO6m-o=CrwD~1k@Ya2SbvL1dyofQw663m*RJddhGN
+VPO%#fl&ciT1lV@e{Qy%eDcyPq$M|*p<kxF<i{|mNOL3lduMk-WBEKcJKquW9wV799sd&m@pDBaP_pA
+I~-n7(O%#8@s#TA*I=ES`AV?or|LE`R*pc__msM$W3Zr!O)w01pFLu>Ky-o8^Yr}d479M(9L#V&PmvU
+P6`&FNGWk={Hx9mBdjoGkWs;K)mVx*$n^UR_G<FsL69@~Ad~C*c77p&XI-=QVgg>L#!ZVdze1Le{>o>
+D{rApMy|Q3IjX#xE<exF_(=}!+v)Ds_*ZWruK+*@}`JSWw+`P@hUQ>?r5cL26X1RRGP`~)?(K}0Py=q
+eBQ1Hi`ycX{X<5h<Z4}O9spx_zC=4dpY2Jh{exDXh2lQa(QrH5*67h8*f@h=^02--ol3{<0Y{GTr9P5
+JG7Wn<OuagEVVB@8sRFR<hMjIJ&`W9Eh+~x%-0u`sf{xe9E{nhelux+}=|Jl~;c;Qo9<syilAXy#_#V
+CnxNWa?ZHd}6P1<aT?H?D>fvXPkPNIhxr#=zJ?$B`UZS@!=)4HL`m3vruhu@^G7?|>Ljw)vsSa~{K@O
+Zvqa7_21Q9?ZUnkXJ+c#4q*geUIlv8`G0)JBE!yk+nihj&LUydl2pgfaea0OhvG@;6}@T%+Wh==?We=
+6`X{Kfvd2=liL+FF{~948s(OBQOx648l+-PGK;G;TT0D;1K;~09K5@Dhwq{z8VoNLAwk5VXr7EVyPYw
+5euRMe8hkI%W;U8jW&6?fiY}>UV>SWEQl8$Fdn^^{0FlF4T%7-MHWblBLH>3D^a-A?qA?Iec75LWRb`
+?xkyrqS}+sHWiU(f3hcsPwH2^%p##CIGJgy&9Rl*@k*1b7WinY#4-g!omt?`e0@CN=Uc7()avX!bKO?
+nn_J;ZZTlRHoORtK*;==;h{Z9dDH|{>N;U@J*Xj8!FMiHes!klTTcC@%(C8ziSroLAde10g-cmMA5m$
+oq!e#y6fRa~@K>$Bpb_#-A(4{!b<f90te@8$Jhoi0nK_rR-G<3AHvil6Sm^7&JZzGV<WrsMta3xNKG(
+!pA&5$9tKt(X%<oZw!&hbiHS>nVb(Q|Lc;-O;H8^V$Gm*GbInR`Sp1KAA2I@7;D4=UT0Wsg?^J^&UR#
+%-t-)RW`)Co1>i$2Wkd#^I4vWOMidVXZld)$NcD3@@l1>J9I8i_!w5aDr(S^&p9U@_HI);>2=%aA)`l
+G$qbhUx1}D_%!l65QEB@3Yb(R7BsF4BH5Q48yBa_Sq?APEc?oAYe4RLxisjYLVeAJ{!I3>ZSG5KQTpp
+Cc_Go|`Vx4!=6Gm>d6ZeUK5HTp9IhQ-wX3v9dbC8IGR}^e6(JBgL$3DjCuG!s%qUCFgA5cH8Jd0~ic9
+J7-V6$BYiQSWXp!nXl3j9QW6#mmMfPH;YN9d1XQqY%iQhRYVqNT9fGg~%3d1~G$?1Q=Z{2;vha${vQJ
+dF!j=ubO;QI7Ae8Xp_US#ZYmB!aH<r1+VqIMX&%>=fVC$$fZcQ(Ur!L(4lFYkkpm4|;k})}o7C`%2U7
+2VN$*uvf?#N;E3O5uJ$Quu^=3Lo0V%7iP&cw|dseNT<<8-%Gc8Ix5#|R_riNz!7JwxuQ=Y7YWKw%t1Q
+_nPz&I>5vw_>CF>G2QtYrEA5sP^Z!TOdvvRcx8I_DK1DU}8Qyawhqp%#5+p0*bjV0h6b0eaUw-VoYwg
+;*-hboPs9NPhq6?YNe8QZver7M4Zcp+_I$-Z(bLdPlI1#ivUMCbfFBir+ID3LWKls5t#WvR0md=V&j?
+c>3ZGzM6%GdMA-}rE1M1*JG=-wq$KFS)I&!JHqPQ1H==Qkn5Mx$u7;+~GhT}|4X*iZCT-{pIiOFQ&vQ
+euAB-0XT2iiK4*CNT3J+F8v@Bu$Lun8P2VtUFzXVRLYkZ=jON{`J5Al7WQJw>Mb%ClvkDZN3&tKV1I@
+j)~!*+n*pvgoa6mK~Va`>M4o?Xvvr@J&J%{;uTSfcvG#<HYvRV%zCF8fH(&GSdotgaEZ|?P;Sk^Flb&
+{{{`r??tVi-Akjl?l(PUMH9$d^0^IHwMl~oPpDUQHj51-sG!PsEJs~XLWcp~3dR<|ArIy&1<W1vk@H_
+^^R8TRcx8f}hI-S7l&7=-U^ARB1%=~uVTzY{49P;Y`j>hUwRuPZLso6~*ef>U|_BPd@XqlIx?UEv&Ox
+|oi{Z2u4Wn8U^#V2#|(e?@@mz5==TltYwdAM{I^;<?&0P6PTVh9HEDWm$+vYL~AhGM}LeuQEl%lZ{|J
+{iG@l43ZYA5|M&jXdc4Q*}^gt3%l?`&7krUOylHm;Ni|#{GC`BY&mHK6c)#xDAa^X|H?0KBdN{nqEui
+N0n8Y#*6cvj)I)G1>&R`h<%y;`xD*M5Jj%f1&&@3<>s|Fx)yimTgdXYL#J|&+x3BZG418K57Jqmg0v7
+itrZxU32yy@-iaNQBzI0x2)^c71ocg`I^IPTQ3ra$ui5l`jBjyFua`o9mOG*<vGCH*yR5%7+98;$T?&
+zjK_BRGVI6B94twrt_bVQvNEbTZ>%fNty1!`G+^H?@BC?0VWOoe`sf(YHyE?gxP~Ne0{CpLM-I8OaxK
+A3a_0>dw9#)Dc3ew!(4fLr#ibMSZ)*$@-X7w2@`Hw7k&sqi<-Tl<A(F;mnliZ7_%IgpB;GpeX?|MDu>
+*+9oatPkBJ38#en}<2^W9B9X`HAC)><Jk{ZXaH5E(vBXRqI}Z7cwud){Jtd-F6knc=B+qY;>9o9-H)9
+R8Ft_n$>EJ-C%TvjA1!T%)@-rM0d?R<}~h@cES5B&vrekogcFg_r9VWlgadr+Zs#JYFO=p6ss;H$;^-
+>H&&nff^fZ9+NI)YHr3A;){d4nbhtOd!rFM=C8MfZNG<kZ-HYsACDQUqsyE|!fmWW*)HzLK;R!y)Z-<
+&)_HpmS7Tpt%6BeJn-8oz4wn@%u%_ngbt6GvOm%y@!xp^B<sWMoO^0D&Vp>$K`!lSnW89n2ce39=O<{
+NwQOz4C2?$$qC^jHS*tH|I33>Mt~ozU+O%sQL{3Tp38>z_#6DvoR}M>#1xuC#^!jah@0KUx<8D?8=q3
+3q{>jvh;KWm{G!n+t7m>w(s5cHqhqOuVnGJLOsDTz*k2gmg@6Q<+)fle6CQ%`5%%{a?WMe+yIHkDItQ
+DIh*4A)Ih%I;L2xDmo&o114~%a_>@0fJ-^NE3z;ik5&~H<9p79Qb673MV@$KXSL;$E*9jUABrzXFWm2
+UGSBp3a%Lh`eBihx5|@KgU$K%Z579X(b4D*87jC_e4E5bCm(Yk~0<sWeKh3Tew9meIEz*<>IBOjTiR^
+I9$Y}O#6-JYj{zZiqPb2vtz81WX-aSM|2cCzL=}w8mMRDiU**W<0O&I&@^I2%!(?wnKKs%o7sBmyk^8
+J{Ro%|wSdht}Vcd>iz<`I&Q{@pKFqSEppk?~}jM=_H*LQB|##_WsJQzaHSVC-frhIz{0X_U>aPu{e5-
+`(~xL{W$7sO^-5Qy<ZZ4g6Y+HG>%q*R&P<eXQrBkcm>QNa0N~;T<kX_OcffLpoc{W4(kby9o2VetUTo
+*RsIBJxZCpqi)Z;<#dh_w=(bR-|598@ycFCt9w50&qF+;u&7p-m7Xx@y|lYYw+!l(1?=1mdU06Ti)*f
+rey?m#vDcrXz1%7%+bQ6wg{?Ix8xC(gTFzqMLwZKGxtYpnchB90z^n`Fsik6%=p{d++{5%?eSPp&$CU
+SQg{}uAe5UJn(HXC<^x92OWQg4Lbv@kV`&k(F=krk=-K1{pmx!BA0?#sWWN;}Y^?N;Dtno1-BfDdHYv
+Isc^?X8hN^?Wr;d7X*52$3Z?hZ^hO%u}H1WN@6X4vtl(Ef{X&AqgrT>k!5!1lYX{vNXZxW)HD8$rP^M
+q@C6AqYh<3_)TanhS2OfH49bbEyo>TCFdN6jTIK7!;i;Vk-*JAi<7&9J4VAXfw-+&-2Z|uMhz_dmP&e
+=sAeifOSv-q>+owu6K<Mk@X14FJiWJ8*)?oiBV91U&FQ}1{slr1T$#N)&oawmVr15k{Tev0fP{ZVL<y
+kC~6d-9Ub0!_3{jy#2P-*o5^tY`<QJ6bea6B5u|$W(bo}|(&6D_t)TBZx}i-h2rhqQ{L;6W40L-r-!<
+K?Wd8hp6a}f0*(XW_q?f-%N?-F2>}+~0ZY(NnZmtH#&&wvr`KiJD-<}QhLs0k8+59GM10N#)C2o5kWu
+;(D+$d6fE^49kE&9FBX>*rZY0~R887xZhesu?22uK_^VPk}(1ukZTxQT{@KdMGJyaiHMI)Qmzh*)m}x
+^%>Txe|NU)s<1ccy2+QPcQPh3ojy-JfO2j*@>xiyM3Qi4hmoIEE1BkJMX#msYgnD>F<bVqvOqv!ZaV-
+Yf5j_{sneu(!1mmbWPZx74-OQBZ?Pt{G-<tQZ-{=s{70BMVw+K#iI70EYbA^*G);CF%mAx$HZLgcd9@
+n>m4Zc_O2L@eU6=<o}Sl8zo3oZ^Ev9j4Ebg-k??BsWM0ntfX32+I>xiR3#2NKo=~nCqTbJZ;>G=2kQx
+P#1%7_OrrqOna5~xvr;r|BbO}-2*;stJ6?t0fNG2P6P|ZD*(u!cg<-IKFs-tS-E}VpldkMor?s_fgS?
+{i~N-3i074Dqw5nPGnf}aT~k{gkqG|0Gd<v<+S!{dDB31nCM*I5+%{Voe+{oT2@HI&otGgS*qCp_K?$
+GjK6kfw;I)m`E!km7NJW8Hca58YUf>2j%e`O>^#M3|KQGe7Hb-;cMeUC4>7=reP6V0UP*Z^?bRvR6R0
+DZK^`t2mrimA*^Uyfx6n33J|Rk(rWny(P<ZS8JPnE-3u!2+WXcLoUfwiXLJ@Ld0c{FPNM<9ZI~p(6p3
+BaQu3FOW29GNX2pw@=(IZP&{I3+^YJB-I0p^X3zivxBp4p21%q~PPxN9>prpQr*uu=bn0ueYRkXHZ6B
+=*eOdV*;x^%*;x=fLnf@QdZ4j#*<uYfl@C82Nnm^%v&lLzeoDk-6jypN-nzNud8q%U7*+{M|Gv`OZg{
+u6JN4M&sP*c*z5s|xh%SP_ro;B*MV2sp+*Qj_r@pKSnVSZRO9<0&FTrTztx7;?Y1kI`*0|UMJM})kYn
+HmY_=4#w<68ZD{&JXh8acWanVfH$93fE5&AsTf`a7pN}TG@5Vb2^cs4WS1NXCKiBqe5n{!Q0zIpVswW
+$W^a2r)GKG^wj7Yq3!U(-E;5#%e<y{{yieIP8{zMqz<|Ga$e@jDE5?lDi<`Qm{1fc2F{1J=hXIIT@iR
+7rBO@b#t@Xt{cJ>GJxQ@3UuY<H+Vu`(cI_1I-+9yc0p%n9)1$Jc4(qcJ#Yc`M5zaW8vW$oJ0}T-*Q5v
+az;+cb<RuYIrclUnG8A_<|#_s%f$&Hd30};viM?jy5UY_riMZxV$>*M1|s~S00sB#It%yyuRect!wAn
+Xrj5a8FHJG@@uJC)|+!BiK?vrP3F*E{}ohShk?a{J`Grnj`?$f-YT;vTY${v@&}WAJ;W&m-<;-e24~k
+8cO3O+a=)?Z}sD5tC*ejN{!TqW&S-k`<AU_}rd%P{mdqJlJRvr#taDtGMa1gv~Se(X_a`NycM)NneKM
+?OusciZvbWsKQ**gp*HNqR-G%Hhj1|-y?h$n3TG6%q5O1Y9QD<b!e6cAF{+U^cR#T{#?TGlQr`v&&RF
+E^uvPBMp&2I_2<Ct&o}!);^ylnKXpGc3`OAt%^)a&QWUikRT8DvI1a&4lB7u##?TMzPn#_?kdC21zr`
+AC5frEntpO6ufDXfaQ)UFE9rRZM05k<;X3{N^f^m@C!nVQt3<c32gMt@p{DtKpNW^iF<il`~&qIEdb}
+JB2b4s>s+Zr0iTQCNs2(WE(aI>RK(*K}1I53uh+7d}^iap!;gJ2KeM0>U})f$oJn@=^6f&>bXzpX#LK
+t<!uf9rlc^45th!#+m%VlO<jcNM`O4>G79)t|~W0{fEmI(;5?Z@;)R+TR?WKr8io4PV&cOFm9$KTXg_
+!6zT7pUO!S7|RFEjMgV#3j%mrK<gWXDX@qc+$Q&f*6?pF7B^2q{&s*7O0V3QcAv)n3@4qWFFCpCixy7
+s#RK!h>Jap6XUSJn=3%fDCsa}?-lHEre!T>t_U3RKjcndNS&_Iv(W~3xXKOsSvj!Ja6Qc5hbE0EAQ<j
+W8{@T}hkIQ7=)bjO>GUJWxZI8rT3-0BoYe8^nWbBT43SpWCOe#OphsqSV^+3<9%eo<tp!KUt1YX=b&R
+F`VqpqGxIZ6stUDWsnO(FfZySIDnYMp*JFh;!;S&CV0@NCTBMvNiLsTaeWY&$OO(#n`zcil0M?r*eL<
+Qk%c*pHPS>viQSTy|XkIw0vS8E@T7r`df1Bh7wgptQrgDUMkSLoz2FR=aE5!mpBZA-Wk&AA2kO60d+1
+_q>*d=1MK2F=z1|G6hEN;XHnmf=+oozS%-uJ)Y}o)`Pw(51v&_V%7EUkBh8mu(tP;*3B>aGoYWt5xYL
+1(s&d11(CVfL)aIYVRJ}qlk{Y=pRFpubp5hT*O!oXKG#2aReT<;5572_ZPWEW;(Rz=4}BZ2|0fq_;px
+GTDinG*ZC^-#H(U7-Q@;1aATq-4Fu|m_7_|9>9m1V9`TD`<oHa;HbJMm{Hzk~%z#G**nd|~(?eMB29Z
+L?B-tHmn)Q_jkNSWhK<-(S~+rfL*^Fe!+uc!LH?=dBP>B<^NziBnFAB1$dypXhi^kjc~HytDp&5PHCa
+UWifopaOb+`3-pQ8R0Y(sUE|H2>7I=T3P<jbBH_SuUch;Y%4iUZeTwLi~z#WK8PCPMjDa+wIfyj9$>(
+5!flQa0Pp+@ZQw-_A$~KIg+{7?dV!Poagft6QcuRDlmMK2_)3*+g*U8DZme*5hs%u?u^K|5%;%AxhCO
+Ox)R~T^r&v51@lz>FHD#}q0@IVHUAC?|8T<}vGChQ-=iTzfgVN@wEtrWOdte-qZo=H3{E3BK{6CgFds
+H!te9176Y2nMa6tW6cq9o>@WB}Xj{s`o|0Km$QTn*65sLxDQCs$6g)Sfh2LqEyfK?<wBm7e@{w9=@;$
+V=j*y>Tpuksl<3R?a_=?Mqxr8K}dF!h%JHJuewfdj=RV@$xH=7lnw6Gj3q0ZBo61^_7ubmM@a9RkiQ+
+prk;YcRhB!*K&c_bV83$obM+E8D%bCc_<7`dHulk4FIx|8p?>)-$-Gn)Df~-0#$1e(3UNF~e(MqgL@x
+f^f|nGHTFd(I7_6f@!_Ozda-9=TrKVGx}a~2Kr40|7g0@`60i9*pA+WW8T(>!Vxv5%GuZNvvAR%i+$|
+Jyw9E1&@gF1!dHzs?u{oGsY2#v@eE2S*c(=qJJRUuN{RBZri*m;E+NefF|?PIXKW;Pa(8IWlwbC634P
+gk;YR}5_m}GlZeDF}5C-a6%H1g%Q@b8@J=!-i5yYtm)mK$gZe!-CA#Xo9ZQ_uUHpP>!ogU2n#5MP$G~
+HA6%pxVn@nIg}D_f5H=Xh%!@2WydcOsg7c&7tB?V^(D&*xYW{AITum}Ad@BFHR7-p(<tt+DLG+IdEa6
+d@DW#<R3N3L2!vzaEa46NlAzUqepU(a&}?5$F$%ugXO1TTRC+eIIZa_;kG1STB5&oPj5(jBbCVIrHy&
+DGrRt85&nK7XgKFf_*JRr98T2=vESEf03L4rlb>eh}r9n4`mhoQFA8!e8+t@<NPF!i<ruKBfZX;HUJx
+Q-W}vMs<OGVPJ{LT!1#gvbpr-h%VotDv6K4~f}zU&rA)96`OaCO-W5Gt))==JPm+0OxOwSCBzM;NM$)
+^OzXUL6Qr1H|*n!ZiNZ9n^sUc3g>&b!?xVECvrfoiUJ9$c|iz5qMzWDc3(nqqhEQOcs(kn0Ymh8}Ek5
+s8dGsF=eo1QT`NG0G-K&pN(X1n3Zn-{{`AAClLPYxQv<B`LcjvaFZPaNUt4^K(k6BvIsM>0|}HaSBVQ
+zQ=_FD_4&C}lOd8`;TC-uEDou9AP>nRd}2r|@iI%_Nyae+?HYPTxups}n=NQ>dVIq2t~UuZmd`>+#4B
+FD!Q-*LXRI1V?>o2ZBz3Gr4wD-}^W@Ood}9nTl0TNT=Z+10ru3mSFvZEZmnBer1aIU+v(lHR3;R{Noe
+=ju9(NVkAzZII}_}gRgXwCSZE~L1Q>h;so_!0f0zB!+i#Plt3~a2$iNFi_d&=L`=6ias)6!8vYMOd<d
+8%33?4zOl3AtLwtLYkbva@Q)F_}v5A53OR|C7x=xaTv3TlNfVpmfreJ_zh3n!|`(g2)7z6qJ71HyK*&
++y#rvY3s0c{)<v)MFljh4V;fB{?4o01(&0NRPH`$;y#gWq~Li3(su)7Juk?cK!n)7M&@9oCQvN7yE5k
+H3_U`^h=rCm%xZcRqyBw&C0O*oUw(92;g#4|a|}`w(gi+kW*1RvPo@`Hbj&BnJM24$Rk)fqAo8Ttiam
+^UMH{t(jMDy8h=Arq{-XDsvxMM}BpV<c!TZ68fEWq&WR(9r?vMQhZB-2O~$w5&vc#c{O<dON}D`?lbs
+sk{S9c&GXZM!9UFxz#^|-FuiV^5rh0xOaj(D!(_Lg^7wG_UdoPosY{8~`a;X?$X^ZtA3dG}bqn$-lce
+{OBYfi{-2T1-CMw_M40fq7j8DEq!U+GK9Ah7wM8L=1G`$sh@kh4uV&(j*TUyb`TGOz(e8=Z|715AQ3_
+(ccFH=)?h^%(97{|xm$n6T*4tB30FHs%E)G6+g02kvrHQzV1phZ`0G3;^bp&gn%?YyI{1fJ1Q<>^Ge9
+YY+uTIz^Dt&4UW<(Cu)7fY;<_mis$?cE^<7CFev-97Cf!P{Mx<l(KKh2ER@!LpdZ=WQwSW6u=nXB}fQ
+!iy1nqYhjsy*bQOi1RHHAF$}9gaus>f%?#gj``+{WUV)m{*&R69$KOPZl=H_9ro_=y_yh;+4dpeum2+
+T&S{^f`DoFu*EI#QgpLQ6tm^8PDb8eF=n=s2mhcXlCPB^WQ}UbH?m9<g{`OsgzMqT#l~v-GDZXQW$-D
+hIA+wZtVwab4QqPc^SqdRqYpl1|?qhg+=1frVk{cD*K**(m5lExKEJrVO(JQleLi0yU7S%gPa{R!Kkj
+gXMg-}vg3~4$|^4B$b7<9?%EBbpDcD<%MwLQ|yBqcXZJ$Em&#4VG)#|-Q)M!JWbcV^rMRc^~`i0<+IQ
+H(eYsV_lE(-tkJ&2ow?=`c`3J?J%OwL%DM9HZy*HKt1yhZZexn?1M2+Fh#3g-DH^9-s=`TqEX)yJnCS
+HzHmFy6~gm9>qI?O&`SZK{$&a5m~lAk;om7Tb+bkguxxkw`T-g(wI9sm9p3I?A|ci<nsD`5pQG7Nrpo
+yxlWwV-es^>)(%DXzZm2DjGQ9R|Ie}e-|yrn{Qid>e2?KcLQphHV>C&@G)XcjiP0-AGAKgO3<XmRM#I
+d9eV5ec@KY3<Mok8wn83i097zK;n-zg68WiYP%DO@{`imO=wl$uE8a|Le&px|2!Ufphip482O*Yl@mG
+;s(NGJn6IPBL6;1zB`p&kWIn=5ria4=}VPynRk3=AWnn=B5tSql~0-pNg`7TaXn<82s!Jr5KC=YbGl9
+3t7&Y{2H!?;xDN00=L?jlU~!KHfW(O(o9vSUK-dD>~Hdfh)`Pt6W=05RorDSN-gk_HW_)Qxm{{0pB3y
+_SJ4p{RZEX4I6(bcT-Nr!lIuc{L7sDy3iBxl|&<!=WhzI)gMGC(C@DCcb5qL?izo0iO|p2nAIySD$~z
+@E|ud-|54gDtCr@4T{)kF4P%yeymUTMS?)TJ^mHHR{)!x1Rp$nRW0l<rw{OjngE`K^8TbZk?X;9x?vX
+nzKO9D1IEw>%d7o?P4r@?aI0uHW?B|hG6&c?rJU#M3oAkk;8^rZ8EvU8&Zv#c?9{1|%4RwB+9Y@kQja
+;syuMu{){i0|MN6m<<m;XUk8TziQ{Nt@UnKz)+z}6y5O=gncXDny?`H9!Xo(g1%Z4SG;&_RV=%knK}<
+U_TLZgM!YbGGzdu^`jYu;iU2D0jAIeMU2AH%^zl=VXU6>y<Gj-Xj|!S;$#`Pi3mbB3+$0?@1<z=aSKT
+I@5()7%-h{W#@nKbOsN@@*0C_uIkdwx94T}`PuvNDqo+hpWpt01JQu}z$ioED9m6aifnA<?|RuAXIM$
+eN*h2iYcp6tHkFQy26`bV38cG-&D5;;*cA<UMCAWLFd!C!6Ps8z4j2j&gV`?<{@k2Id}@5hL6&aa+2+
+CaE1L)mJODv~E&;pFHbs+_n9(?RPOgto&=rpYLGF|Sjq%9lUAsP1@dTs_!H_iqa+E;)bL)0rud5(HFI
+K#sYxdg=;T>cMd;VLO`jJZUNj%Pez5lRFU9f-dQjgsAz6PoPPZscOE5>W=o`(z^pNzNYeNtKg9_jp-m
+>nf5PzhVZOcwjBl8G3eF`2<u3j2B4Wd2kMb6WK+t`7z1b17^k2+l1I5hB5yK3zoTa|Q^Q&8wduFW02|
+S1u2N8Xpx6dB%&W_+431!&9g3Crj)oM^etYd?~mHhiqPH&KeQV^09jBa@dUYISHE@cb^xA!7k=y=WtZ
+3E)zB6$$20aM^D+Zy)CmMzppb?+Ue2K*a&_ryXxW1K*mz(6SI^T%UWdbIUY**&;{ZZZM)(9m{ljd)K*
+W-YT&<<30k;f2#|e$EAMAMqv{j!9x<`5D|=-T_n5qrZxx@qnc3Sj*5dG3z44Q;B}<84Y8bU41cT=_GS
+_wazOQTA7tc*8TvPw)p+2t`nC4Ky(6KBf)As`(ybd*fKEKoUxDcYsB`Bl~W&0?D!_&%Y{b(6dYwk|R!
+I8_FbGk#JKI->$Lwf9ZBSSVRz9#pQX)2Rug8rnRMt)&C+w1Hn??hv%%>FZwnD$0soH#)d`?;S+f~OE?
+|6yghvJN)-{cQ~HV(7oUjmxrO_s^w<SbMLzNBU!r`1K3OhrH~vvb+<)&9$kJu-x*u`S)*>qOy&=xhkl
+A-&Z$O&dL3e750Y~G4BEKjCZkcW{M6kJoPccHeEqUK(>B&w8XI<56^xi7f^N5m3bL<YB$Dbm)IkU%3z
+*QDb1Ue&(jfEZ^v@ss7|`3P?5%jz_-TDvo0i>lF`}o+L!*!nqaCa|ACE7jWq4+$hpY7rxB$U?CH$hQ_
+<$n!|MepVa4@ie<CI8&M~UYJbj-lUk;1;L!umza}=&;{UU_CKrqBJu~%|N%0_L`V>`Lz1U+H9oA`u%A
+pUf%$H2VYBJSv<%D6x3da;L(sA6+UAi5Ui8f<ls?VDb}!A|F_!`_~ta8_tB65+8?#+*P;S+P5{DIbRX
+{{DiK(`)BN`X38}tYLojx|Y=x|K;Uvp5D5@_}l;afB#xPl1-m7KOWT2BgKCrclkfx*%uuA?YiFsBuX;
+`3DY!5qZCFUG(!>ujKKuTz{I)$rAQd3J}jys8z#Xpn2lP|5#FYVu?z&_MZV!40T2(gaI7)<#{`3<Kw=
+KgK=q2s0fkt9t`JObUhgY>7C2xR_||rkZ!IAt13FR)_*V+m@FstWZxucaU?;%Bt%sS|L^shb<p|T8CR
+hwon_2!jk%?{eV+F{SH4z&{$v604*IBPFEB>TOcmR+|e6yI4(hC#$S^A(ZCsv{w?s=fE9~af~pNndKu
+!!~gK=~9vms4z`6_Rw>EkngJkb@x#L6(9Ok{KV?cp8Qx9)GX&<@Q;O!%)M(cH!ph#P9D?e$bZl6T}(l
+1#ShlI@@GIeqLrs_)jt+&dG3%2~zFPk4UZ;VkLM*Xoa0!AWZmfLHz@?q3D;X^c1JjYw>RIpZUQwRZ+m
+{kn4V(ul{Fo?O${oL*I{yed#vFUH?eku;e0`NJOJg1%pYiLo;}$eHu04c@nF*F7B1YDv&!z3GbVO8WH
+!|^aUp5`kG!Q^<@{tKD(>6jOpBI#*a7~H^+U2p5&+V;ClG|RIh9WU20`+F<0XqwNo_efI5du>n$-E=6
+n9YH8>OTPxv&pdk<x@9C0h34;AzriqCR1ur>0DZk~Z0opaHWNS5IPaa)*)mzN4LTj4U^tvBwU_``|g1
+>aRL(SzZtrCQfOPvu!fAdkBaQ4u}fc34qO>LCxK(g@q;pG{*?_ciD+WkXnD*sM<o`gmDOT^|_tBs`jg
+m@*A2mh`?mW%z=4&k&BY8_rsdf8>z%SxEZ5=x=c2z+5z9Dn8WFVD5Jj9Kcp+-yd;Nu+UICQr_C^<3V`
+L<8;M~lD;j9doS?H?>uSc8dGMca?80~ke;suD<36Vx~EybbN4SF3Ke80de++>vrEF&;WD+i<CPhhiae
+h0XnSS`t$))OyAkt*=nltcK^$R@%oDz4Bi)6r9;`~SZ?i7C7}xmL+UQDS9u)WHa53ChHJy{f?8h1ZXc
+evEx{R)>-6i0<+hIU^1<JY;Y7M*Nxk{say4@D%;g)Z_de8HI9GNQCv#U%!aqo;-(eBhtXA)D<<Z_KT#
+MCZ5WL{o}u6K!Rz8IH>f@|kC4Ik&R=9p*hx>vueg-SSGq8m~Rm%v1vZYHh`*3XA55JVpOJQjX8<nqVr
+B!?Re6<z6<>}tRnQ1S`=n(po9e)(RY^J{6-vd>~P-;|XP1C97ew>QCF4RB?lG<dmOgLgKSxiG!66Uzc
+|v%%06h;JjBYM;2Eod{Vva(%U&#b2d5*Do5MSb~o<+_4X|S0QuIYiv=Kw-62GU_`!0rbG;^bd0Y1LpQ
+j#;>frA`yN_3r{5f=J<D(7e!6zab-LXn^4vnlDe8mkQMh!Gx|=&Lz-)Q$m;1pg@n}9j=qyBzXz1;PD6
+4O%Y4f}y=Z{gNSs*TZgtXK1<||HcW#3T|+!#BuTfeMJXPyGXxd!8u1@Fh;KBEFY;g<BeDjXWloOn7P_
+y@m-%D%wJ8Y6eF>3MfAzJ(+i+=`$xi{ZJ@$Pg87pK<aqjjZm(qj`EIkGk!7R4Z+sMWLG9Q|1eQ^5QLf
+>AU0v8Y`SvnUcwQCsU;{IYoT9U8@}yO%b0`30B8-IG&l^LpD1SB3|u*Z25zL%AWF4pK`8Ftq{5=n?yO
+1j!KnL8cEXi2Ft2kcllO5NW_DdADqp;d=9#y2B!LN@vS|b&JnGYnB*F<U;SL=j?gK=1;)m6Ahwohxbv
+J&#6dD;MHi?`;x?uW?Q5GXlDa=+Z}gs)(~fiArE$*9rh?T*N-JEy$%?Go=T;;z;vA9}ympR#k1m3<Ll
+;Qyk;~(T@?`JkSkTxLiDh_$)kbzwD65`_Bk3yD`5=!=MDNS%bLe(T;tY|-?U|MBK_Qc3k4Cky*p3ryr
+8kBjCNGJMc?!24wAl-@W?`4B*I5F`i)w^pbJ<+&aF4zhdnZ7ZY423^gt;~RxE|p<U$!QBQ*bf*bE^@c
+C*!KJ2|}{3uN}+s{^Hpm!@1wA`6X8S`K=$dXHW!2Q3}Nwgup)x!8WC}HRQ=i&<Tshpe43ofWkOvEBaK
+vO@PQ5j{gVw*d(NgKa0#@BuK=fn`j#F+seRh)*uPA<QAY*T5L5|Dh0b-<0R%+W!gLjZN=+eQXCBW<1q
+*T;{tey<v556kxxBW#8ybofD!<mffO!*fk7^y4e&|Vh5~yaNw7CO2MH7$41WDKYhi&9?D92hA*<|JlC
+CWOamHf!iR!i5(QrOFL4TU7uQst2A8r+|{!x)-lQ)x0&4KaKZ<u57qu3hAUf6GQQ71!iK8vmWxa{Yng
+M&l=lcR&4UFeS`UG#K$ohViF@76PW!3XZOl1JeN!LGg%p@-M(YX6}|l`Z#WfL4AbqIBHaJXh?Cj=0?)
+Ev&3xCgGs$$K5=Vd7&teg0&%kcI^wAXm|DUcp&$hwYuG_NnRmlQaYFOWk6i?gUCmT#k}2tEe4Nf7xN_
+K*kv~m8RTSVeDOkb7!>=eN{9Q)o!MZ@YGfC^b@{o*f)z=yYIzeD<6sIz&#x%%-`pHY5VEl$i=}oo{7y
+PJx!XlJ@rozFYPmeG%PBMWX=O@+aP^6s8?Xnf$L9$j^t#Jx_4$&jX@s<!YU3}nZP}YRNfdSpMqIRX`*
+rR09fM=+3e4eL*Kq${j`cz54vOZx`xADbmI0=}VmEKBWd0W!jKAl3({Co(&<6AtZ*<Jiy2<ffs7W|92
+Zd+2$IZMp|De*cgR5DC^!h~alv74rnf7vYX3uB_WYH{|fur2dnYw-^&BWNQYkTqAmeUul!K7T_FfYz|
+dWMXvO}jFFyuzc;yeY52qbAU@I&Fm@NcW_w8T_pu1(h%@sSVJZ!VyUdR|-v!dNM^2j+gJ9)WqfbM{LO
+mexrgI((hCK(2%_|@O<`+671l`Mf$e0She(>GCbfgFS<LSlPaWTNTtn2`t(GF6Jl8IdFG}#Z(nVnBj?
+ou9>3^#*u6<sTMniQ=Ry)$x%*6aW7?P#blG3m5Nq=8SJLf}%xm`jH1(oo6kQS_Sl`xFexl69yOlx2ka
+<>d7gZ;MI0^(-XibQDkyF?Znj<;q6MPW<IG=6iPyLoQf3c7FI{)?meDa$BVk-aZFX{ijV1z)P@%8_{i
++K3I?>u{s>rdngiick|JQUB3`g<R&)?DIjU5GX7j(_0zUo0s9*H5YQ|NqbC3*!BEXYxHR(lCMJD23BF
+LLwikn5M+m9ZPNHPYfu%WE-4d_-3I+11`TJC6<C@1x<e}{Y`=-0ak1iE?Y7q-h3}(7^EQL%>`=(CU|q
+~SXW+;w!$Zvt@)+qObXhBvv`}z+0qULywzo4u&*2j2%Mo?`Xc{qlEvTvih*WM25>#4LGSO1i0e6l8Y&
+I|65l$2ncq8hNTBvPeidJnU0)oCl@a{>AmOJK7ghQCvu?H;c;9m89LSwtgXVnV+7z?DpCmQ}k!UmVJ)
+Y5_bkPW2c|P#I^1l%MS0GETiRzb$MBr?&s^r=};!tWP%6zDN_4hP|v<Yv61;KIvsei%vlEELmE`U9ms
+pFaBfXrF$vbQgOSD&P1n$j6U2g?3-)UO57x3Nj1`jaK7?@t}ZU>O+2`Mj*=IjH|>g4&h*?^3_1!HXIa
+$<h>^O!#|k9)W#Z(aABO1YNIBe0CX+uQ33Nd`Z*jty3j~MW*x$#7ZLELV}3Vwu%gEiDz&*pK74ccXeK
+G{gBX2$!>1mrpGQ{643g0pT2$4z-5+)&pso-wrNacyH~|TYEFMY>hJoZpzj-_-n^5i6rm@MC)^6JZVB
+!Mvg}H|ydtJ;aPEF6=-V{kj<sqiH6uJcsFmorke<(R;f@twpw~B}jYb^tYXC3ogT0O0*cp-a{2okur9
+UrcGNDpaPE=<)Wse17Bevd)_;f!}m4+U#RA|#Tz19r$xRZKezv4K9kTpALj=)n%5XNyHJlRIUIO4$!1
+Qf7Hn`KR~5<%{PPy=(r-g^>h_7^@zkma$zp9@}g>kAeI4+p0XGW)9L)9rqzi+AV9kg8`>u`Ic3zCxc$
+iEL-b_>hK`5}(3(N6Aho?c`2kqV9SxRJbQQv@efzf}fc{d7}`gJs&%t%UHov^u9%|d8o2vZ|>NmYhM#
+q27OV7i++Rs$zE9ZdogleVCBuXdZpXqN9yHV{bOllIri6P&!aDsZzqmg{5@(wKC=@L;{0=*sDB;3IXw
+4NHHG(RqJ5h$Cr(tkIFE>q<}Q*`LCGi+@&P$K3X-#V%h&f$q~PhBi>gg|R&^#+-il1(XRm&gMSr<@&-
+nbb{3!J*qC<IT$J1@9tCcoLv+wK--LS;QFyoqf9GOGb_WA1!7lSl35hA(fJ;8(8P=yJJ@Z#VsJd~^_8
+wRKyF0Y&53C9sb_RA<|C535DhnM}>R(^7;bnLb3ouIyDZcy#z{8d;Qy`U2G((7b=gv6n^#^(CWb0b@*
+MDIGn#(Tj+UCR`>?>wX#;|G@y3>o{n+3E4ZMumBMq0p(8@x%DcnX6Jbe4M|nv)Lr}D~m$b4}0A>#MAj
+Mdvr9Om%*tskBJ=WUyR-;w`<v~|NV8m4bQJ~r^pJ+KfLo3*8lldUoiO>Tm0Be41d^W6w{kAMgbH~DH@
+1!;22<c)Ydq>z5r6-G3XaYfm7ti@@^zR#dS|844B}Gp(_lofD8J3@NN3D0AnvJdXqUQr4uyxxspVJ{?
+(i*0|+FwY09mzOCX?5v2xjT6E^*1mI0%H<C2>S`3lE51saTi7#*^CV#Avd>ee`w(VN}~z8O##>#=`JK
+{uo6>T4B%XLsdqB|<ht5r;P<)vW(jl*6yaq{|)&N~}DH8v)e*D5U+j_e<!jzNgE+KhKmdEBpeK07dh+
+`Dv!~%QD#X)Y%GdU(W{m{&fDEvw^-pogdET58H0RoGJS_()jb$c5HL4Zx63(jxAebR|0<^#J)T*)Wvl
+bS4YuXFvkUTI!;#~i)4iD7aOXBM-`-|T|Js!TOk3Bg?DTlxAg#$dO^Z|dHQW|zJw0FKK|+Q7@`;Rf!8
+-(dOZ{I3LTf$<MaC?epT==XzfWQ_l05Nm4W8cxFC8%mxuCFWc#C}3~uaq=iHU3T4dv++Se5no$=)4nw
+>>mTBB9e>VB{85wXvDkMFw~vkM`Z*)vW&Z37<-%99bhHe5lYMX!<?2D)AY`1vgPQ+>Ddf#c1qKEw@{Q
+nbxtZ{r*wbe9`-$X{D*+~?yHi;3QTi4p?aWVf%NJK;Mg6sB*;+bofB9^T!dR0qBK(snzaCr$V}ynIF%
+0s07D-XH1Qf38XkO%far)TLtDygUy))QO^6i!+Tr$Cvhg@dVmS6c_6r9+otvO=EBmUqk;&azehK)b(&
+7!{Oa5B;^)&UBw`3MUIv_zn)!sMGld+UukS~igWw2Pt|UYy}cGoUiVJ3^x@~#Q_<F-&3(YPvqm9l%R#
+q`!DT`fT&5kNclkwSZ4B)v9e$@3uI^5`=ZuwD^6PgtA!<jw64Jz|TwaMs{*Y+{BvxK?USlay<MT@5DO
+!t0C)yoox*xp#&9N#!aE7C);AW!xqDuwb)piU<jbHxd-dj*%$nPClgikjeTk`qBIqU*E)1biKWv`RYE
+m|n#(t0T#7d}%7LW_lGTze~L4xZOY4`RD93jd8?#itp{O$rJ;%Xt<74}UH0<Lh4^6SPmRiXYBz{#U#C
+ahmgoUHkwlA0f(0q==2%<R~CH>tmOOLDOh~0@<k?2UxOlx%F2dVL*O7teF62#B9z=1r4%_D-B$k8?zY
+`CmC2sBtW-%<zghU$!61Fb|m?gZxcv?79dSpY_`W303XoVl@WlL<(n?|dU`ao0UiZVa0RgyLRJz<Y^q
+f&kl+PCN+4CR2`2y>MidO8BELtJ1dz8j{ARcKaSi$WQwjOt3*rO%q7cnj#>MTV=^Wx8wT^yADZY9arU
+rNW1PCl3NS`O#K5Im6g<2cl93-}+r?t5qmy;>@s3~Nhr$ty8`hKAyl|N=Zo8JCThWjAS+F_-YRq~xzG
+4wqZ{K5pkde1u3B!4x-Fuy1nd={z#_Dc@P%Zh&tKj2xmKjrt{nQhJ+bx#`>=z`pQC-$xlmpB+wxT?c9
+(jF@w=DFy1UQ!&30i#L*?Va;JK;}Z7_NPg@W?UHJlS)Gs^LovbY)zxty>EfUu)1tLg3EB<lUIG$5Kos
+iw0aSe*sIB_j|#~=9OuJ)nJdY&0?5c7ti0D>=f0EA%WjWF#=Rsf^yL`ElO`<t79Q1C`jW>(z$dEo^c^
+cB#d3_Vvsd;E<R37Evk}RIqxaq|cm945Q64)*4sww9kE2Dg@2(DBvpUG|#5;6vtC2syP4>*@x9bI>jZ
+_HJ_3B=itMNE?oyg1Y6uyeL(a32M6TSE4%%=76@??|VW%&?A2b95*#aI2~3J4YL?=JRd_<_~Q7JkyR+
+*hVY9op(?lkh0j-JRd@MRa;H_|`lH{jGcIr)kcAvJ3{q24W9<WpPob-?LDe<&+z58I?4bw^w$kNF1qy
+xz95~R%2Poa9ZKD``jDhC@hCFkG(tSki<#h2CnN{50A$m$+e#z@3VzZ+OUK5PSy|!mDX@U7&Bt0z<N2
+Prt}^{@j=yUWkV;zPsbhlP#-}%;30V}claX@NEz>Kt3nwec~gPJ>M#E=1~GdsW2Ei!-Hy=a{aXzmkez
+6L!c6UwBRGD;joNNCEHtUG>q7P--^M_T$P<jrbmh+19k+kB4|tzClzS?6RzX1hv7cLfW$p3FHmb_W+Q
+v`V{ezNrY^?-BNn28PWQ^+tHVGvc8kj`dGS?5BmDF5kLbjV}wngQ{#T2b<uGD8tvU~N<A<DR<kK2%^f
+93z%T~>IwePtae3^Oatd|d%_K>Y+v|9ayuaP-d`{(ww4jNlZ4QWS|W1V!Wc$Agk9j^GSvH-a%BT!Z6)
+Q_vU~X#}Qzn|vb50Hx?6UE$_qnH>h?BUivHasU;@X4H$v0QLa1Y-YgJ*4ewVBnANnhA;x)gwB6uGMED
+S0ia5q|0mu|f)g5yYpkcS;#j;PXP$zZT)Nft^3DFC*v2AP4i;0Orz<DGfss$sme{6@kZef$`%EJb)UC
+(w)U6F|XHSmhEOhjXY$N{#xS-F-_0QSHZ=_@;F-U*Lv=K~Oe{F*LGV}-%VoLMf3bOz7u^x11j^8=+m7
+urD^2B1Zbp7u1G}bxWaY%Ft%(eQ-Bmt%*GjYqlAs%XYK%&5y46oV{5BfA9$$nk<{q_CH<w5^+eSdO!&
+_7+@pIjc4{Tpux>x$QVvwmcE89fxGJ&s4H$;eI{FHs+w(<54uuQu5tM8o7RT8>3kB7ypLdx*zVC}sS7
+6DrhuRu`;ZUoZP-3Z=<4rjFFDxa}MLjm~!^R8T#y2yZ-gelNqS5fv$4iPan={sTshy!AZeRe3F&op2v
+2RCWz^1jP<>{HAhMaEJ!4+Lu=wSID#@ja{*uB>$$f2eyA-k?Zpv_>*<Yr%c@wR|+!mTl1E#hR<<zeZT
+kegBRsnLY%1A+n31(wjTy^l6LFfR`d_N<f0YxJa&lk&K}Q%hgK%ja<&pt!HP((N$iggRa32irh>a~D|
+W^ty?9p$`F5nr>O~A%0cYiTvEi=VPcH=8J^ZigKc&F!eu;J;_7(r&PVDIdofLL+G>+*Dae1qfulMfo7
+~oj=*{$%~y3hwJC!hGDC`v1LEFG>-x@ff5J1_nG#nQV9`I|@v_?~|%PYN1r6S@9883Q)$=KaL%C-~Mz
+hB)i{csX^rO$bx3QzQMNE2z^KACX|0c@aD%aKKulpGSGTjJG|HnfK%C_Ocbcc(hKH=fjH^ij%sxj4Op
+_LoPQ^mc2^6wf!NvrH9x)Gu45-Rkn{WA~K7@{<&kNtSvZ2y3RX&-%xIFIjP=MT=8O{C<1!UqO+`@ba3
+UbqNe8Z;&RFzP36H5j~2|IvvbakW?|im`LLIyYUeW#Q&9rkWnz*_A@taxGOA7d0;999&&D$&&w1ja3%
+160SFK}~Bow_<vRuXjtGycu$Ju(elNZtTn|MNsVIs~QN4PjaPXb&~Z8FVg^`f78|BeYl;c9Jp<^Np6;
+FG@2M$D`qe(}Hm?F%~o@4p=ECk+0tcJKv<f3e07gO4;uP%wtB&`U5B!Qd!~!VL3qA52PY7Q7o4ugC=x
+U<!xW23^o?W)aznZdksxw0vCe%Sd1d3=DOVjWxocJ7q=1b>H|lESVx8Gl_1Ez@SB$*x;S~Pn`X#6*<{
+*mz(QhvI+E{6eu`?_G1K`A-#<ot-D)~lx^8Xbd&FaH>EqENwBF6QCmzvZCZIL0~Ug@pWpYvoPcX#^VP
+Lb=h*EZP7NxLKm6^{4s!pKCwvmkfj)PcoE-E$o;zvyp7DLLjqq#ZEiSC{B|XSDpPl?96Ce=&-J8Y_Z?
+5lsuDmsqv55E=1H#YRKHD<r>%y8dzOy^j#dr2ulIQ&$!}|nty34ui#vYidfIc(c!w;8Ge|qyXq5bK-A
+0ZF=XFsH=&3caDuH{7<Pi#rW;(WQ}dpkhIG<;qZorauJ6W-L}aJ8L6GlrMDlghG5D*rwhrJqfSi8OFN
+BKpBNmNje~Nb-bGXTPdA;<XGOR4Tc_TapHM{Y8H>`L2&{7~Wi4?^1BjbT_9%7uv{zJp`3>&sO<9$rSR
+^;nFGRrd!F%G3u>-qR;%rAtLl}4pQu)*gmFsrS&3aeJ0Z#!&BqlXIN_mjopPmkc8LQw=l(*46<#!v<4
+pTNu?i}ovqheNd|@fvRyZp>(=6<GD{9cw%<9DwR@@Jm45ha;F=;2oO+<s<8oSqXzYo)asFV6$vKW4s#
+8L^l!4rYcl#J8uTE$%34M2+R8}efeeVqPA-4Sj2Y+aiRriyN?QW3X_|2n1>|JNY7lyiE&Wrvi3jM6Gq
+ub`l`iIAEW|xs6A|G=6j%rI*v*UTaF=P3_rpw%oU8Z*=%cHNJeRxcvyaoKePtoj9(wUfJb@@PvA(@OG
+s%wLAQp+Or_LLkRwAd$uPoJLz?+mZVsdvnJE6Z7Uyjl3N_|-(WxBWoHQ)}H9jXywS!DY^E4zN>yK5(~
+D$taT*GOpesVv=RvLCbbDnu<zwI$ipBB{PJfk&Yo_=8}!}3F=a{$V;l$?aPy|reVL#kHE%{&1rqG(&o
+ucs7k*e^jRGRI}kmUz$|9b9xW^1x;z~q<4u#+d~&Nsu&jBObEB>Fw@XsbXOJ*Ekt%)7OW+%-=oXA>cH
+~fxrq2Z<>y~HQD^Msf#UH~H`+D9Umn_cy%JOfy#uVflrOTs>`^T-whxJ#W5vNLju_Q`jI84$%q169mK
+VQJ=zuw39a0aGmPzpyG3I+1582zzpAccX<BK67BC<Rp~Aa6s0o{$s;xzBvF8CroVg;zxT*nT$$_)sLE
+Yh_(G-!ynq9Pl}O>*Its3wz)lNN=9=)F!<{t~Bvix;r>%e4zn!f_(weI~s6FAf8`<9c7#4E{1}B6^sM
+`N28#vb4Ak?h1c@{CQ3Nauv=dP**qLr@e-R2aQ<7@Kv@FM-TnMkc;DYm6g9qPSNbr|Gx^?6!uw8Oyul
+Fm7s_P$VC;pN<It%ho@*lahtZh&(`Zc8ryWv3siKWh7c5}mCmFa_Rz(pt>hod>ENTf~nIN*!EWua-E%
+?;%DTp()0@BxohV+xYZWDNhuTJ)-$wEO8S}@!W26CEnXqS=f1EIQasoFETrE2B)q&-)<I45Y-reN6$V
+k<6d&V}R5T1Ab;p3J(O%2NHM<vjmsrd0(qtt+qzhqilJ<XBU5tRlF=80bq7{Ab2M&q`3)mR#)lA$sV2
+o~w6u(0W{S`aTTu@#%6rp$<plxiXs4a`nCM5VC$Ut|E@wwgIK_!1yQp$T3XK1xr5?&N#UpKj~iVCjxi
+WUr!V6(|MG1v&5S_wHGR-VD6Ft4|yR&I-@?rGeYtW8ODLi-|P5H9T!qk4a0ozwWiMY2rfQ})Fp5Mhxc
+6pAG^eX_YS)t#04^0X5wnRl%<EoU}~a;vzKwMcf+i=aK9@eZ$_t?m1Mto#w(bLL!a%<^JC~$S~d0+bR
+y|;ymM%QB`w9><+Eq(2<!zPN%mOZ4@BJUh-zM$P&li7D==|q=uBjU^1C|@FEoKVy0aNuG_ZHW2n&v@b
+Tih|;;<v01X*OkDoj7%T|@85@$fXHEAXvNSDKW#>8$ZH6z%P^)EnepEY9%h5*p5qJWTK66m`!t-o_fw
+p{TiM?l9S@_j`7Fov)WGay!Jw>*Z0$keCc7J?b)Xc4US=T~KXj6?A^gWF#J5)y%}pOXK*bzQWOdMq}q
+HDPyA-uSrQ5W$!@;m41i8=*{+_drJBt=?luHeO2pr2Sy*6>wLKjSs>AGgH*Db%~ghrmML##_mxkh1d(
+RLU4$lX@u;ygpQ@(!Ygg{&(J%dRX-z~UxaVybDxnoNOc$)-)jQU3jH_Sl#SbdTa*v7(yS0@2=}uFp*H
+;N4Wi(V}FgW%5$UrsNGl&c}3!{${$UkTfIqj0a9;Sn{$Ls$`-J3Nzifu`w@BE5>=YB2bq0Rb%c?KaSi
+8tm!2qXqE{Q3*Z%&N+)%u`i;`nzV=?3{=!g#<ek5!;uq?aQ6?Q-euH*_8S6dDl0NeSW<_vEL*!6e-^S
+e`AZwPMw*fiFGzOO5(UdI!<HQeYX-T^EZp3BfnFBgiqkuReso1zE}ey=A3M7@||0M&D!!EV?2f}8QEY
+$n|%We$1owoHpl1q_`?3#F4#9CVa&~DCq|-}wD|J4$uQ{GukRO7nA^-Y03*#zJReUK7=>Zxy}V@%hFK
+Us`E^Vao6_C+0inrt|1lD<uIfR_yx!^aR%$~*`_4LEYyRCBDGDyUzToh9Z|d7BS!-jo`4xj4WM+j|q2
+FmBdf?Q9w#Jij4mvQrYuD|9xkXk~?~{rIZ*aN!3x_YI6~L#{>wY2OyV1W9_2yJ6q{D!s^PI3Sm;KMjp
+YEEijjDi!w+FF_itvVB$Z(f7)XrYs+b`D|&s@hjSGYi&qqB=qFmPUj%}SSAd$PSEo&>K{t!ABHy^37X
+d%bo@9M7Z1H&OU_;#k9jciq6nhHH8r@ofh{qZ98ISgtmhiRzX~ngN@bq_h8Vh!nC|w6~~xwSGC#imrN
+lHQGqRa@XDk<DMZIzXML@t|*}ogSRnSiMFFIHr?P*R9Hi=mXU9ygCX^3fOn=c#NqOMGa^6SI0mZv@;Q
+kBn!Z!wr6PrF(sVcrix8MNc~2^we8K4TlJs(xdTwjCXyqd#jj9jod^0+t<J>y&4IoU!xrhtwBpA!^zV
+W7zt^IkZ*kQ=fODfAE{g_fC>c;LeL=L4;?fu>5rzvz0P=pG=8810b!d-@3SMfqR*6ThJY1ymVdJTk&-
+23+%<%rGxzF4Njb@o}_&YH_>oMoJ<WCLu7E5vQ<iF%roS5!~lQ@@s>LhBl}Dyy@ENZ!i|^5z}Jl%{8e
+>&(RFBPoY2?bs|(>qbQgBjqPi3cd_)LIN><;Af%5w6lu%f4k&Vwyb?-M_BZKSpThrf_WDH!}(9<$Fql
+j@w9IR<L^)T&b$~VaRP-19HSwWq7e+nX&grn4}Y45F=(#~e|j9gmwqwy8I$?UD5ueJMsOGcV@GX>(nm
+do<VT%FkpD&gyd*r#La3vUf7s}M1ke%rnajaHvaOGiFp?Yx19Wn9JC4ci{5aHx>0gwDN7N>CoWxVvao
+~-9^jZ*d^jcE-6TulDb>h)_i9e#~PbUWX{Np&?z>glwUf$B5Lvi$DAa%?!VaE^<{Ff!6NFD8I`tf^^w
+9cWy{(EyJPvv?Fba-hW`Jax+2a(|!?8h-{(c1*?D{dTP*1F?AMYmx^MKpGr`&}Eu;O-3pgaJN>&d1^W
+Yab&y6vW%n@3;7`9>v?&$M|A3Hw6xA2K(`h;~(Go+l_(a&PQqYH!C|8LVJy0h~bIFo%rxyz>p~M#Z{L
+kZ9zeN8$FmcnJt~G<g8JRztCs~rntK$FMGI{Rd#<4p7oMjRb@1;i7a4Ai$`P0p<@Z-dF-@gMC!-o8Wo
+Wy)ABf}ZKehq8W8ik+Slh6KhQX9OO~)JMQ8~b&>y$U4Ou*JThnCVDE)onMjA5H$spiU21Pni(V4}@gD
+Ax?VqyX+`C_0-wXtx$cm<}&(jLZnur^n0Jn@;gSMJR5;w^q&E(BBDRja%U@6B!Zy~%eX$o3v~%)#yj+
+TMfB11slK^OcXSldbB$-8$O*#u8^Z54C>3FRtY#HE9|wm@(=_fX&e0OWuFUO23X0aRvdk_k4=TsgiA<
+q$VljUJsYbd8<+pVqdMn(J_Zsndot`CX%(9b!nip9V<UpP#_>1=ymT-yVa#jLmhcbBsAjkm`hZVhhek
+>fd@WJF&VX$Xx<mgi|yo8maklcq*wkHRuf=rGwQl)bLWHN*35zX=Iid=@ltOONo?Nq9S}Hrh<NawDHl
+pg=Nms5?fa2$%;ZrzP*ybv_3aCzU(F1qPhsNY9VEgEgvrEAICw&2i7N({yBH~WQL3_+EWG!4swdJ^VF
+6ownOO|#8}vTE%9w33XLOYg6mi)b0=+4wfMGS8&pYIVv|z>K>6teT6QuJCepNw0HcIpaPZ3XM6YIqd6
+%_#~WOwoR$`08pyKS$p=5HqtMYJ=UC}4S{nSk&?Gtu?g#4X!=d>bQ&y}KM+*P?6)-nTz4@P|LHqglv1
+-mN%B_7-C^(4EoEy07j$K&|yAe14&b!gxW%!>aU|Rjg<1EYEaUY3Eplw-t-MvFul)p}S$-MI@AjowfN
+p8H1ZpYM}jMM|gY_udH}n@U}C%Fc1pEwf7Y;^M1hvFgP}dzR<o>_tNrkRg13O-yR$T4u`PsC&Zy7w26
++Yd~#IfGp<Vu-ot(>&En5`U%;_xFgA-li#c$fv{CUrv(7{#wn#pCWiBa{dD}O<?b7tU_V($gNcZiI=A
+>a|N)Q80WVec!a!$J_*4r0z-7xA##Cp|p(IKYuxQOn;+TV+_OnM5t6{p*fzpDEr7IB0VKr}yIOVv)1(
+6ola+_PE;EPn*4%RHgMtoFIG%s17V;y3>8saNTq7+W)lAYVdfn>#=?CrG>o6Mw4+y*)E;zmjoJUkR9;
+<eI4-$$&zMUB)|2ct4;AUT$~0;<5|L4F%lHfX-ioe!D@V0g)iDbtGtFRX&*)XNy|B1Z{RH@r|hN)uK}
+aN<8%2^K?3|8FA0`7v}>0`p!!Gj7M&+w{7`iV^=h;l}gI5w#+0v+qUdo;&^EgdBWh~Tzk`<>lP%th}m
+7b1A1x2CWAjR=+TF2ZeIoyZ?CF-Bch!pM6@HJH|u831b>~`RC>LwbG$P8D?cL~GN>`&)xq@OU*l8<u0
+kZaV?yxdS*?Op-=D6`ar@t+bQA2=XW^6ejKl%Ez##edlw!Q))CsU#Lu`bzU)PJpxLx?X(30Ec_B9Jwr
+IO^+{y=F~Zl8vo4OJ@wj+<&_mmGHPW5<9%8yS=<>-*N~6tFR4Dn<J2lc*fCeYO<AC4A&Q>UZ8$avj8p
+fjkA2I>TYmTj44-17NQ=)(p(TzukGOz22sKANuFhgm(N*PX!G2v5~_|`uy196Bq5j6#qaPDRuwBM`^n
+L=#P{A!N2os%%;?Ro_W-9Kb1%Ro0t0SEbMPy=8v`HPnGzGflc&DPeP8fs*E^#fK+-^Vta9gd<wp!PK%
+F@9rSZ43Pv8vl_);WnUF6s5$cGf*sI5*fW(fe?!9!RKNVbp9GaA4DxCN)>X#uG_|ffy;*U=qdCY(x@f
+e>x_ZT})+0swG(_T!{9}95wBl?7>qfjKWqftqqN7wU<i)o4;u6fZ>m>!j98vW%V*m4w#FXVUK<e$tdh
+L1mYvHdwt2@v=%TkYX~$wK0~qs%*g2!ANc5|?YtIz}&0f?Ud2@)oIPZr={X0KrS&7fHN_^8E|N|E5@U
+g;}4!Di+sL-oZh*1($pFgZT~c)%~XV&Zy`6^iTYAiuU!e%=k$AcPKmL{YPY!>E7W(+h5#_A4bi6_Yc<
+FiZG|_esLl`-1jcVEPSbtWk8sp?!I&=mCgGtSehSvx#bwTl%e!7L4L>1Z@SULX5>o)cE{H4f>6cR_u;
+2rM4|JYr{@99vhnpe4)}Ys?DTRg>IH1>5WT!rNjsy3(A)?|;{kz)MMW@J3v(B|^VN3EUvy{3?u&yEl)
+EjP!Vb0vvJg4Z=jU06@3XS+7?L0MSjWh~>1+h)jlsR^y8+z*Nd@9r-xL?uZ>N`S@!(4XtI~hvG^WqwE
+fkrnMhsTRsy2CP=M~^{g9$5Lse@)TyZIvNxjU3gG4eIRbejdyu*A|kW1Yq{H%ba5ncgEDXD=2ms_mD6
+ba&XATc0+5t5ISmim<b^#7kaTlgfRRwKbzz3At1XPdYGa7}F}=?nYxWYM{>21sM5p)@phhvMQ+<k#1=
+hM__ZjsmMvU(%XwH^UHg)7IxszOxruIm_%N*VZxW=IN%@8vj0$#03!d2N;|Q`wL-{KM6;eaDTd@B#VP
+ysaU2&SFpR_b;|c^p!ryWcwC3BAI!LJ~_&K~~5KTnM+pM2D&Bwt+o>OJnM!w{b!Y4sSg{L#p3~4q2^q
+6M?b<C0z+GUikV4qCdBK3EjX^V5)wQ&D5aj?ftdKfV8+PY|{3N(IqufcV8d!SIP{!u97c;O*L<z-ej8
+S<($o%YB{mFOc@3w<g&3w5VHbyzsrH{YbB80WQ`bn6a4BzMzg%scIv-BRd@MT#r3YPQ9}M4gHr6}0tr
+J8M}DliYOHa+t#LZ2uMpACdU81?YQO<7y~6WVz)MweWzR9y|D_JoOYFRFYGRUH9)PqenX!?uN<>DDp%
+mXy;nZ+P)M3n^fW5Y$#D~@ZTRO7^6O~_FuKXfpxz>*Ugf$?V7Hrel=k5zjxW+1`hu2CI1pmkC+Mi&`>
+7CXC5It&f$np4EFxNBswO?vh>iJ<VPIh&mCbu7AFvKNH`8HN_=>-pkJmB@B?NK!))YGcjVb|xAYTk2<
+1EE{;Kbi90z(yd?0H6nUgytqVUmr`I2%Se{!~Q_*ip-9&>VOdfautS(+WIA*heC6F%w!3O!Kw5SGTDW
+5B<(x8u<RPKV$x;k5qWf>YIH>fhj07ES1ORUc8{4<UD$%9&mKpobVqpW)TmIaf2?R_vJEp1<i%H2?S4
+0Q-x6W-j-);T8B1Uw?;J>Tkg-@FTwd30@s<R=&BvEQ^~;;<~T0i6#56{HuXT!r!q(xBK_=`v8Qi%m(w
+VoM^s#(T{Ko{1x8*72E<}@D?3s`%KZ@iDG*39pJQrgfNc1G?YQaKr&2u9CPjLdQ;_{(JpwzXxBxji%|
+freo@m+dHQbzCzUN#-p>`~(y{?bB<S2BE+2U1Y)L7;{q#KcS1M4S7uKn~(5Lkh24pKd;YS$ssq~X3;i
+SB{CVtz?RUxN4R69C8jA!RQoXxw5KAhQFq-%RBW8XAxuagPL^H@*YD+Nyr&ZuRX8q}k>vo%GkYgFFNN
+78$Ido|3{q*sX;?h80wNiz>!9($6h38YPzr40tnRu%Zqhc=wp)6+m`lvkE~=i8V_T|jAiIsSHegzlxA
+%sQAGWc0%d^F|1e!`M?tTVci4elVDYk0dpNbACSy+~2W|0sabaMR_)i5^NEdJuNcab%@q=3DL9g&>nC
+L{2XtYOOSVsJDcxDy_1g;<Vv^o(jxG#lhEA}xVqXc*J-r}46=t&?&Z~HPF{7lhnL+3D7lUC(<_{(!jg
+KWh3K$gk7TM<k5?<4Z@q4z3j*f#2?ek^Jt=+1bTdwR@3Eh@w*aBd#T^ivmJ(S?3hL5!CUZr_z)DBF^J
+Wq6?hDHo>^Uz0sy%tHqCeRsgp#4#gyP*%<OG8@1+)|qZrU>uDd4hFSiWQ%(aPjG@8yMEk-h3UX~0uI+
+0E>0Z>zg$jAp<63&uI(0?{HZr}tpcn(~}78pG+-g1&VwxQN^~GDV)!Ij_UO!+7567J89SHcSu~H``05
+Mlu{0-jr{5|K;?gr%YBEw9x+mZoduI{olgf|Gn$~8G!%pwf_={Ve;?_+X-NFWJ4V@bvumhMDl=5`Y>_
+X>0$P9Ov#Tl<DVy4AP1GC@`Df`gAnPVXvv_Dm&(WDg@}&X??bFfeHbTooRu77?fEZ|7$=Tv?F9k!$uZ
+t3Ekz!@HNyTYMh`s3KM9f9$9i`E7{iA@%yH-f9XEr~qp;YK7@-fq-w_@8n4Y28CyDZ}k(fNxon!WwNc
+{LoPVoPCNNjBk{tbzDHu4=3|6$zlpQAGHuUPMIs2mo*L}lP#vEILf%D^9C`RAxS9LAepP<d0oM`grcf
+pq^q_c!YwGvdD|P&GZn8tfP7krf?dVFQC!C0dKTo%9W-3ITzhfHf57+}+R!y<s={j@+~=zBV&c=*l~|
+o{;i%Z)_}Xqs!<#o_v{P=bLWBR(y&TCw(9QwLF8qnvj%r`|UJ5u;oR_;cbfQ@zyAf?7yj|Q_b1K&QU4
+b-i%}!D-{Ha;Y?7%8sH8ze|O)lKi-(c7#*@5>AvpUH!tItJmzi&<p#FW7sd=-Xb?xAY!lo1Sy!dUbIL
+QIyp(D#g;uvc$5(uvOpYLU+rkW*mI+eqYv&q1D1wDNUoxKIT+$fF-y6P+!yzHZJ3u@{wl`YOH$hpal4
+_`8qlFtUQcu*o>fVd!C8@_2BIa?v`_S{*`$3@kKV-zBy5x)rz5pgoW^JpKt}jRDxvfGd@&8JoYQ7>NM
+cUL_9(lML3J}kDx#oy~il>{|$tJ>%tRB(@nj}%QLsHzuWyPJ(JD24*P=SWoN#(Wm-={KL%_|GMGs1~C
+6{4OJr;`Y0x35v_lOp#JDr-DvF0Ze5p1v9fA5!&nmUVYsY^g3&c0Iq~4S3B{oZ8EHi8HIw)?*m4fE3E
+V%w$a{=d?bdZ`&5pjmw_5&fBOuQAkuir*oXG>^%i4fj{ToEj=xyj3wkrq2ChN!M^*tb2yY-E;R|AVwl
+vNh<pWNWv&&XJ3S&O;eEYwEdad`RJ*b`QE$<04f0b^p@y~0AR1^R0v92vWUJmj5v_bP-PrOT^zczRQq
+CLeG@J<xPDT8Efoh&t{o`AZ@#B&8$qryUO#a~uKWb6`-b;Ryo&NOc-}#^s5QXA6O_DT$!H1;ur)Fr>m
+ofV2m^H{g6Mt0n2~PY>_TiuTbqYIdKGVa+?B^z-pCpv{<C}uv2V~O8K{bz5Nb)ml2pxv&8GZC@cYHnK
+NRW>o%&($NAoMdk5r54rN${`Pj0c=!$BTDRhu~voKl_-%e{vy@n;nZF4t$P2*iV0Y+{dgX^cjxGkJUt
+f83e_<$5vVY7JjUxXd>;k|8uy`KOKy?@IPou4;&T0nrD1MMj-LA@9t~tU)J<v0QOameyBRxkPROnJ*j
+u3qXWloA0zO1oHRy(IDA31BW6)JqD>%!zs+Xz0k!!HsQvcXXC=Uoi2hGk0(@J_pH}iu99rmdJco1Acb
+6;7R=O_F(u$#`$lfoiu8*pEaf5BJ(AT=0m;264#hegcY0OXB8ITu3lA`Q2ItYH95p8~fqItcqdORezI
+$sBW)Xqt7CjRMZ_k>3nbp|@B5*l&yqHaA9N03OJd!M7g2+vvjsSM<W@ah145+HA!CJPK3&?x5g)>R4U
+fn+0+naPNY?4@UBe-ksMS0As~6|<@57;w7#1e;s*1G)Qs3tNhG7R>97U}s%5PpEtW$&R|-(qy@=4dKA
+RDnD_=({|2FC#L~>xP<vA+~9rDpPpRKv+)R0yk6aF!&=!PYmi7odcSd~&L)+6^?*McmBzqodIeF<e8O
+*xtWgHXjejvB--c(&!^UiVQ752XurnS${5R(!jY9pS?(Fev4*b;oORNT(v8^p(%+uV{u-*mN^+9Jy6$
+V1<j4Xt@SE}9jYYDh|XQ`|(Fd>yk?t$(rjs@-c>Xk6@hLkWMVp7FJ5@x!K_#$slar1ImvdBxp4xw2C?
+|8#*H!j-gyJfe0^}0fmdWG69$KRxGWU9GiIP66XKfojZ4q+IYPdCA>^1aZi-XjoFj<tH$dX)yhvNh`V
+UM#BjwpXvdq4`yL))}$DV!9Z59M;v-fJ21}pxD45v*zgnFmcpfA24`$xU{H>RLhhnZ`d(CQDmOCx2$V
+X0^Q5OYvhZUK_t>aLeiLzVF^e2#sO{fw8A*>`tqG?F%wWR#k562h=>ETx>xTQr8Vw!%`NKhA65Pl0L*
+NhyZ*j!pnn@;{>4jv1~I=s{X2-EaT28v3L%k0xki%sPsbJxr!V~IiSCfFZ`$-{x&Zqe)KSS1Pj$@Yr5
+}OUPUL=`p0)F!eP2gDtxPID#?X)M>L;&iCuv`Tu2T5pbe$f=>dP7AVe9oPh6Y7P`}TmS=s>`oeUYCjy
+!~bS>vtxWqX%~2=^>}1j|AWY<c<jo{9uavg5yu4bSHTGf}rfk3O@X)p^p{VU(etD2r;=p3D#xv9uD+#
+GqC?{h&fCr(Val_QGmC9hL~dgVg&X_i1|GBzYj6rujHRV%&54Au_RN3Uxo+~oz9x-4Sjg76?lc(>V9w
+$!W-R&`)-ZFGwS5G_XBeTxk6Xqrb4qjtU{S7!?qCFsg8OBP2h`Jz)jiF=2Q~=So;@3d_}i+c+v-=Z<`
+3t-5`ml2)J`*|L8L%RT4vPK)kI`;sqN$s*lL|Y3}=IWymk3md(qncQoQ*3sW3i^>=l7_|8QKY{6M1Ix
+pw$%Ah54I%f#Bm(Pm=pOZHdTw}V$ZCNt&81Z3)06P(D6`G`<BlF-3<_QqnB2heCyf@m0#`$6UQYP~IT
+dJ9}PZV(pLL=C|r<&>OR}iUEGO}O_3+6*UV{Iz!7=<FVs<Gx9jm@*T=5NCgdjt~y1;nt+$-(h0njb_3
+*t#=k4P$$<E37*7Z$Zp&HY|+NT!%6wUWQJ?<0F1-F4yYzDhf#ZG*83(m4Tpej_+=60VA(Wp6ErUha)y
+B6eMn<Zt2f@m-F)l9#Lb0RodPQ2GQ}hrvSBQWnl*~^q<xJxlMq5gBAo#AfmaKuq_fW;$R`)nrnu<NpI
+jCEh`?j#Gq18n=iZxyz*S!-%6N^S2^=TKrgyeY}OY#^VCsVb}H5vqKC+7fS`dIMreRKjK)I`r~>CLyH
+9mo<Vq$sOXqhZHUV8T(fv~6cab*}vBgwmCty@ou-lV{oF$FfI}!FieG0{Q(Muqwo?}tSm#)s`ONddxf
+@beft6cOHJ_}4OsQb=YEI49BN0iwcaxazyd`07%9{y(#bMCW8H9h_|zWnO>KLeMq&;28^kQ9xQ2c|$I
+iXBM@@K1Yx33lwy(8o>Xh(b(`(K8e}@&KTZ*yZQ|Qin?kweygllb4kGa2@m@CK+^0!0jv{h7UpYPI`{
+8#{8JNCO(O@JB}eAnzP>r`4xE~KOQM)eoV2U<l)}Dvk&Owc)73h02lla%k1}nv11f&N4>*8EIZnTRCd
+UwcR<{sXU8@KKTzrDW+I;mheMt7m+I%s(Fj_J-;gD~&EBP#9^8ceh%Cl|EcTBBaeuv^|L&;8v*w?W#Z
+Dgn7+wAGPpIND+ZW<u|BfnO9{X(-z~4uepRWS=iYmXa;ul#^KZ}A|SUm?`{t2{GG^ImO!%oqFxeNB_w
+;LtXM8_L1RDp_sz{VKNT*M9M=uw~RMygAHY*~%50ac<?P0`r~&TkHPcgINr?;e_$_Toxvm#Lb1u1{Q5
++HalaniKT8+{h|4*XY${cpm~_U1t|D@$tMeR<lvC0t(ax%2ve^)i@(wjn8h3Q8_Desdq@LBKom_?MVa
+gRB!eUFi__*Qdbp}JH{VL$PfJiB%gOQ&~$V@_QbK;xF~v%)9com#>j+(VHD3d2uW_3;ec$|i$?qTTQn
+RIUqgRw9w{P}hMi2R_eiC)K2htq)OtWzcB-bQ?X5pGo4rA!j;16)Le|OLQ4%>f+jHGkNX#cqz#dl&v?
+J#Jp3Zf`PWS0i<CiBbR15QJEukESQ+vvzNdkP(BH+%)Qu4_Y_wq!K6{sLk_NE0S7R!Xnh`Z$55pAEHb
+c)Mbhp2%z6$jK6PzD{~C5KWgsLlChXS1E~!TmN)YQBwhu=<Ytp2o#s)SMJmuQkY1XG5t36;&uc81m7Q
+4uDS(Mocp+*Nfuc@B0s6Mj4e*_<`N9fPN5HRW^9c#_fS$!zaf`o7l*BxhQ>}V@d>Ya4Q6^iVoybME(s
+w#kQ2KTM+Vb`1b0tWNGl}XlJc2Ia<+BShVa+z((nfurcIb0c#ea=B^ivrA!gni)5<}6L|uO*Q*1~4H?
+>pHa@-|iT_?!qoVsy_GT#K{Xu&{|J(}?VXuNN(Ng~%yBOg2nfmWLjy&^alz_3h&4(cScE<=@+g=m9zK
+!av3{Vq!;er5~0^_eHl|=dqd+!LnScP)Ysat6(dSRfV@P-)Q_RA8IlhJXqv*F&>^EkH^jWwOI^RE%7c
+;xO@nh%@LLU|5x-Wy~cm=Ss&34#I#$Tq90$bIa*p8RLNh240`SO&ZHInDx<6|BkoDHOHI5gdG@;mEkv
+AYu1h!ix*2KfK3PG<VLgV)<*YjU2?BSj6fEXFdhI4H()^A(>0{O5D**aiRes%MuAk$IbZ}J(8G6X<>o
+Er6`rb$6Epx6g6ufYA`xlC?x<?HybDB*~5;Y0EcXLk~v1JFj?q0uG}|6Pu4(ehLtPAS!eC(t3qgomKO
+&dvBbI!OxQ!ZgH^oR6!An~SeLWd<=s=}dTOf9-Ov*zAd%R09CgQvhtH0IzfQuvnMR6!8X_=(@J2Z3C3
+V{?zPd3Y;JJ-~8N}N78}?^MZ9bEv<o$JH@Y^gSj6{}0ed@$QS)MX*>w;!u?@%FuThI1&dtymPLwzP~+
+VRz_cd#47K3FHqrq8<m-goyGF=waO7VN+I5d}zE1iwTADv+g*Jl<{TZJCj#pE7aea(8((EW))<IxDl%
+4@2(Z3Mv{fm)iE`e2OgKGD@jv_Ob}tV$*Gcs(bOa*z$1au@1-CvY!P=nu3*kG3FULk#kg|el3<R1lA`
+a1GJ1oCZ_46%Y3u{i7fbMg^j>*|F{_X*=znqL3BL-JGzZQFoIw-L{bF2e?o|#7Db1R8+1%n;rPdo8a@
+gPnm(v&{0X3r;!l)ydI)&2^yktf>M-QqE0+(0KDw|+4MiN|S3840rpc1S2`9pi0_Sjpi;wfsLs9fArE
+i=blVnFc_Q%e9r`v~DYko+Eciv8XJPp#%2-?od_x0~37fFB8LaEObT6WOt!}K6Jn#*{0G^LMdDC8)j5
+cIE#BKC9?MYrJhj;@+C)sURB#-6$2rW{4lRzv&#Y0Q@&qV9peEJc1dpxH~2^t*!Ss6>EorHCT<yuE!K
+0TzR27Nfo|Ca=s!{fU5rjzY=Ugx?-B1n+Z134DJ>Y0pCOEj(iU{%&6#dcMYAT<suy9A*H3FRSp!Z(CN
+IIB4M5VMQA<=Co#Pwn)Ba#4GHP`B&IBqZDSvFt%xkSS*GR4?voTn{h&%Rh3vvFWCZpYq>CCH?;B3uNo
+d^hj`oG6|5{N8s7T7e)Md~XWC|)ltlx>01fy(ucRrgCmxz~v=&_Y4e`XKb47oRa4&Vsl54KDVQ%XMdy
+b8^KI+4o;Rm-eC+gRRm{|cfo$z8XJRiMr29C(!%zp{o_-0tmx(t8d*x^+T{3HuOV~gVJ_rBxYY_<%~-
+kF-Ya=9f}A{+J8{s#55d_DOC5Or~}a4CfIr3=sgN!r|cslaV5?v#n6SDY**Do0AJ6?Q0A!xB1sUJ4S>
+d|!isP=LHi=vJh;=;X<Ie4UHu84m(*3eV3Qej73jvB2>roAIm}nf(v8s6#-p?--x`BTK*a>kjKI>%YC
+W+Oo0xPMPtUN<HkjzP|8pgb@E<z00?4@RxV^E|r+1N$jUqU;9p%ePo$OxIKQ1vVPHIV#Go3DEcsA-gg
+`*KirkcUqt(mpR^t1_=tQAQ1+J|89(%~749T(=YG-0p&5;i2cs{VOya-jU&%6$kzDFn1NG%Z4L@ie_S
+w`(?4u(^4y|VVX;{M0L1m9U@#C<GMaM2lp~r2~&rt8-Sw<d0%_H3hI&41ws?|6hVvv{hZSUh*!DW6Lc
+PIZC+shh&;V856o1(w*<3~e;*UNk7navF;rx;n@A<`T&4OhPlli?(@YJW51!g=7(Eu;bTGfU||Y8aNC
+q7~o7Ad>gddK|mdS3W2Ccjbt#k<)kb7!EtH-_v<`Wj!>G=4PN@J;Ihx67ko^fS_i<AEtV3mlrByuh_r
+ZfQ5d5KeLAq#p|EsDh1%JIIGt}YjEDTfW7SV?a0TL{ufEa$B=^ZO@6sF{I~bx%Z_|$!ap=X5AU>}H9&
+!1`A}o0k?v59nBTlADmfg@qJ;%G!;;TYh2awo590v$GT`}O|KzpD?Uo^N0ZLHK?8LLaMt)XGe3M3x3%
+(R$*z@z^)FlNKuH&qAr-&5E61oAn*K<q}_<4b2KX_$9mG|2VsXYY?LzSXbm0X9o)p(g_R}|zbBGt=O_
+QJRG%Cg1x0G54U?d>u8PAy{Pi=++y-q)pSPzzFq6n;syd;3=QugX|%*<*eRhATJ(Eh&sp+#A5%Q&E?@
+s&~G8BPZSfF)VA~I|v7?g%@5&dJQf>6XBS{8@%eSmGq!Y7f|vJAbY<Hz$E7ZErn5pp?nhg%e8#8QHsg
+NT5Fzq#h<XN`$}kEq84|)Z-9P41^5%HeCG~gE9rph?1{S5!__3?$$nd!U_v2Ge{FyQKkI=0v;nF`UGL
+}?<06mlL|2edr4@{?z#x|bM$bt<x3mJ)#M|kG$@hfu!qv5tXB?*1kVR%ZpW?PZR71~2w!c0Si}xTo*8
+zn-pl}KFBMr$$!&gt0h0llVE9g$RheBEpV*MF@IIvhMePb8xHD#1HjkUK&_MiZjzQ}dlnU``wx5c^3`
+r~dSPNK;+Z=R`5a-xQ?VQAcl>(a)Zibr)gqGkV9*?@Z80KYT0#BwBQR2Dn#-tP)>gEoA-Q)v}8b_!;r
+>R1g7o8saO1Hb6@ORJDT1R31d7X^UOTifmwkA1}|$+ymnp7KXAv`p<i2aogdQ`@y-ph!D^8aEft2Mm9
+VcZ~97)Ls8>oa+vEZm=WU5BkLKfNO_6mr(-7{67Z-djI{^uJQ-e{5LN14Hp0M5`USS5PeeZsr;zFbNW
+zA#GjOeogVDS0%wO*;uz?Qj{F0X{wXr<KtyLpE0y@n+8srIa&$G3Pd4lhO*?|^ANNW=f<F2U`U98fe_
+_8$;)(M^QMs=wgAd??KgWSlcIX@_=om)atN)#};KZTvgt7zN4-X0WATTj~EcKXW$PRT0{?Tn7)|=#qn
+jCi9e~FCQfs7C9uW}ReAJD_|H^Bk+z2MvQxatd{>O-QXd;13dyRu*Bne;bPOvCAB?VFPqCwhPnne1==
+l>ZtXzk%JyK*HdY)#Qy0_~InNd__ACwp<V2!S1Ka{n=`Pf3n=4trqyza`#Q_SMC$+7xxL_aGyAUjhpj
+U!=8-g;jeuIbE}I}icCqQR1nx+MtT>)M8P+GWhOYTO6LlhSLF<fd&QoK!oI0%kZc%>U50Y$8dcgWT0E
+Z`)o0J;Edt+oF$q$Vy-PtXi@;vQ*3RX^9uzhiL0JYg^s477IE|^4DqC7V>4obm#9`Udp05*jF5jwOIJ
+ypNaUV4Sk;te0^R3)Cq{y=?aLMP;--bR0FEXt*;;BRzP|fO!g-}^s&zO8`9u1FmqI<fiETYiLx(rs&_
+9qG?PaDu*5$9H@v6dQehg*@2T#9R~6UKYTUX3<wsmB-a{8mnIzk=Sm+6t2_dg@eww|4*W18A@~VgAsI
+7^|?$a%0HXMZ)efvvWa)k-ku<pNGNy9bmh>EOB_$DWL~%^_(>hFJ0=I<AcZawN3$kmiKcuee|66c@@8
+8o+-VkV(oiR%(jc*>cio=>eSf=ch$Iz0}P>8?<e|&6E`Nu8tyUPF1UZTbZT3X;wqdb)n53QlqXx1myB
+xR3amBOdYXowO`8F@X0c7u<|}++zNYvDp(sqx5-k@rfjyd?cd0;MeVs0XL^v^4OphiZ`x4y}e2@u*2b
+!{^`QG!ao4aV%ee7_Yl-uVTbk>#yr}uc?Z0_aXTqw>#1jd706O=}qcxoea{@nu6@RV<fNr0xc|MGyCq
+PV5m*uetvnT0(!)I3R?x8<bSpJ37Cx};riB~%sLdR_8+2;6qc6gv79+BONl5vxZn>ekQmsU0i>=SebE
+y!(Zc`@h}1vi{o<ILr9Lr~boPcT)8j{)4mr^Z(IZ{=>{Z89WCD9V)`9{RS*w@_3N%Q_KJDYke2|^UEj
+xrR1MTJ}sg2=s)eCuv4m?jK#=7(o*6;kmG0#IdmK8&a-}QdW3&$C#mGXz#U``)`fnWPSnw8N<QL6_%l
+hKeByzQ13UUqE|S=<SRVYDq)$Fws?Qa7zIG%i;74PN`j{ylkwEz&?N2_FcLa36-xn<Y67PCgEqxrOci
+tC$nqvDmxFcXr{3Vv92bMM9Ur7Gh^d}iW4PbD_H!75Pkk7l&H-cgp9@-rIYup(g@2=S3iWlKWHUxal{
+`siUZG;}<t3Uk#9KK}%{b6p-TR)zdJhNGTcLjJ?`SHQ|`a>hmX_)T@4P?<2ZHP8^F1i9oBTf-b{NPma
+&f08<nsx^2UA{|17+kqAn;YtX$k~o_?>K<roz&LAH}>`s+#dk=H%H#S=;;|BuzYRtdW%^62e*i@)7MW
+vys`Rn(t@`+APpToLS^l)Z@%Wr4Mp*Ub_f!=W^*}uQV(o#1Ex<91YHa<HHMt?+am11d*9$|VO;SlY&A
+R@U$B0S?2xhNG!E>p<=!V76P~^S_{<eGr;AvigBPZ8!VBmHZ877uy#+DG2>%sEF&aL-S3^um-AB)7>W
+$3EJqB1T?lw@G>}zLz62qr5F5_2s19bw)uuAL2cVqhd7ANHKV=gauDdWiacIk;S_qBT@x8fLBKv%bUq
+nES17N_d8FxQ90pB3XJJ)3@`@i402RJ_Dj`2=f%HCjb^BYG||ypuG-jxz(%Y}&H}QQ`;-CYMBMKK$}{
+OJrW+>zX!fSW>nkV?3S=fOQr$lHbn%3h@5i9{jyj0e%qF8`jGddc6^cBy;nj(7C&whgO%6O*3%%OT8k
+!<~)Ne>nM3ipCXWS>cZE(vq@k(YC=7oZugcNuBUE&Y=iC~)M}n&nPS$KjYVkN;U5XzNsX5h$<EgV=<Y
+=>xuA6i-wRmg)8>&i%c?#+UGHc<fb4avWS^9t<a%|Hf}pee#N92VhtuTtC@Ek(A$8R`MK5WfHa}$Z%)
+Xd-iZ%bXR}Boht>!>^#A|FXlJHnBWbOK-`nuqd1KxRY1z_*a(S_d7?5WSqN8m^8iBx+0;pHdO@3>dt>
+QytziSxL;BL~U~gnqpJt1>gPa!F2rQ@0n^yX#N#h8B^Z)>^k+JE6<9lvcrk={pGh`v)+|7&X=Kp*vYS
+{t+*}G#|e`!THbUe=`4hg7!Zx3P&KCAb&iT`M0k0+hNVWyvldZ&Ikz~@jxVkA^S%Nhp3+-8vO|nNIxF
+TA1bwTpB;GeFWl!dj~0K9T=K*2`R6M94^HhUc1)TPhpZ8yKBpwn2jkFBD>3`DG2;V#b}T#W`I4O~{R+
+|WLm9b)6!kfJp^2m8Nqm6t5b}Q$bnX|0;v=Ay_<S{wk7dUnnST_0IAMN#cl*^2h|LdAmt)H9FA+`r^e
+u_s*qP$b-KBwa0i%Ad!jHBege;D~*Nin|e2d^_J@^?*;$%3+tbEOr<Jl*BLysZ0W;?vU5)NneikbmqG
+hk~6B!j;r=Jq?>G4q_+feGD$<+(%RhxUX44*iIBz=uSAQNS$wMb=M>c&*IFH|hTOkA1iN&#}|Lv;1TA
+z`wKnWA(s4k<L7+Sa>>*yKbEt$p~goGv9#cPC3`~>U=LSZcvhrEl>A2kSC8hp%=K5=Zc5-?W59otcIg
+=9NxM6lL=s-QevgO0$8+CilHr-VqU7p;aIXG*m`0vGEwuBbJ_fQLeFnmzWXxjWH`r2`LhyI+7m_{+Gs
+%2(4u-l)hLEd-GyF_o4l4{_@%9CgR_V&XK4Y>nQN-?5mXwBHsyu*jIDmBva50e3NG1#nLw*zN!cw?R%
+COsds1EatGF5SRFBY$j8i%+;QZzbm4A8Hm+4%eQwF|0`xxjKR|yE&s4nmQry5h8I^;!^%JS^?-S%+UC
+m2HH$tCWz-Lfs%bV+uWu1L2O`@43t0UWl$7ym?50c4frTJy7x-SLa8=x-2aNH@~kbdg^|F`2F}w<&^e
+4pn5a-bd7VLPQ|Ws7A=Ot8`aO8hTv`Wm*I#C&HVw?tp!!x9udI-xB4&^dM8XUY;CCz&sajM7mfqKoh~
+4;AwHA!1n_=k)>&(!P9^Dsw1=$LCwPJ>^#rdg_A48^Gi>_Y{W9)T$sbr#6;jt7*b1B@Rr#*yd)BTefg
+>AnGxIXC_Gl73Xhl?6f<ti{tS6|4~ZaI<@gBd*buiszL#bm6)>jAbitW%JXyFJdjH5Ii=uUHe5}*X1q
+Hko34&WW4{axYI-hF4Lr@{RlR$memf1(rCo>uv{aB@Q0JqR@wMA|0#qf8vg{a>uzE@hbe2_cM2C}W38
+{^I~b!`7KVd9JWbqDKW7CXlC#!9h<D$k^N1ghL5Et&IHTj9)+`FSkU&j<VVI+M|X4AtaW;vSB-DuH!N
+t8?OoLiIqzLgVk0Yo-(|r|!tsvQoJC3r-<Ys`cs4Ll>wbA)p@2TCdE<AZ1`o#*DBv#p|U&YG}gVNVIJ
+PStZsuNwB}i>^<E}xJU~EkmkV%$@vWkx};2Qths^=_SirYoS4~7KnX%TTe{SjX4V!BRk=u8i?@eINLi
+gCykem<61^MD2OI;sh;hqk{t6LFjh^dh8WEkAA9|L^g)IwZjP&c>(w{Bqd*HRnb9gVVT}8S>ce)0ibH
+i~LmtwS*EB3lZA6N#th@@jZ31;A3Vl7y;DWN%GH|2r2O%CCCJiM?|#9`}t1+Eabb8VM6RcnpNw`dZO)
+e^uMEMes)-yhifOutetB4qCDT>AizA&no0k;0G@v6o~(p1kGeDtE}sq?Sa-QdJQoY$yMm>e_lVobC&<
+ohHv17`R1mr+5nN_{BZcmxk#&c>y%+N<WcWnF^sFf(4S}a%-}D8mXkA7}j8P6&#C6m(OR$Q?X{s7zM4
+v$7#zNC>}i^<Th0$ef{3z&51TfEN-l~4Bl-=vh8d3ur8-pJ6Sm-g>N=nUujF6q9rN_axc48)dTc(xTv
+d#X2NobdVbr)G8NC_%VDplxyX>=2A%6>u`j(rzh~*@l4|G+324guz5K`p^!EG;s}kETkoP9Iv%V6T-j
+S=Q^ac_86o{-TuU*ULp9B-L)B22t;Xk<M_=x<WDEsym#`!-qg~9}iB0m;(|M<n<YPny$@VoQopH8(9p
+Cei1D0Z+<qQ+kP;Gdv+{A0UJ$44^(!;XI-KX0gG^r2HGKlTObr?bBQCq{nCKI#)EOdM4d5g)zwggDA9
+7&#7o>0dc7)6plP3Oa-|d!<JvpCDuUQ2Wr>$3ft81f8Tu1Tje;X9Cz~YI6T}jt)xl37mot;Z1}cZG0#
+@ls)k08^r!H+ffV-2OvoLy$SKB;^EVTuzqMlSnejIfWZ#mTGXE1`gkIV+fkx;D}-CTvFw}lX4J_aL*)
+$-QsL~%mI-PcQ5ehTAI2YQnBO$WF0-14%koyt2K-Hf{M}<S;MU)lVD6n-WcN#^-68xDh2QUH`^IRw#b
+&s-&Da$55CH*yPyuo2wV7{MbK6%jd_MEa?{W9X`&9k8w*Y)K)c?|4D30dB{wA8ae0}FEOJ7hBGD`aF!
+cpc<Mj^)?cFS?`ZcbAQ7qH#~M7flrSCO)vYqdtqs2ZijU>5f-;xySx{31R%h&%IKhdS}K+2(~J-=a35
+#vJBnAJ8!i$)|HmheUrnw=NYTPO9{GS&fDO<DX-0FC}4KPDToL0cd$>?lqL?8@K{W91R1ohDc5_`8{k
+)u~|q02FE8*cu0QBsQQadt`GYnvYo14@<}%?l+&=c$Yj^mK;T4P0Ha}Sw>?4S^E{NMWxa*zbY(<~-Ox
+l-ULN;yU&(3Ey{vHAr6%~d&_llM=k8Y0q#XkGBdxA&UUbcM7{}%*(jL)6?&u6bhRa=>TRsdEy{=|?9?
+gBsLx}6Xs$#ni6V=>VAnFry+JDLNZos6iesE0|o-?c@v@^`Jaaw^hR6pmJ%rL%)!CgVCbGsDEb`d)`X
+?nmLP~p;@k}*HueALK@(BA9vlZ)1MHj3vVx~x?`IA@$4=RVgeFn^=s<MN0?TJ<8m0>n$%viIi+4p!KW
+jSZ9J{u-0d2Scs!0_$fEj~HLOaJiln9eQK$Z2c<b`)M%Hw!ApN`Q%pHSuO9hOozz(>b-Ul&_>24*sJN
+A7$u&uo2SU35np3`G%N<Ldr5nn-BcxWX9BcysMwz-(JH)?zUAuzS2rrB(NG=?kc8v-G8s~xt>*19$bO
+cQwydaCxl?`24VE+T{prKsh~zRJObW8qz0={#bK8LFof<PuU>yPBzv$-td2{(N6M^wyss!lxHCv5>>#
+8=#46l+DR*-YNHc#^TlrN{OjH&SyAmHM~XJUHHvYHCIxRCvF#t38p7zCOUhj=fRHFhLq2vG)|px2r$d
+(lRuS3B03{%sFI8p?uFZ;CHG4dYpqFIsvn=m=QNG&d$LV3446gFMJ-OuJ+pTxiDQsQ$6`KAEC8E5ii8
+kda}9(R{`u)(+@mFM>J%%!evT8+zDa=}kI9k2496QBL$ay~z?M`a;#JGU?MdG5E^;t_##@?6ubI*6tq
+WB%mcBdF2p%MIvM*%2;S5akLxo)|T_>)x2){E#=$0aZ37^s<7*fCnu`SdV5v01)LCoR~$}P*xtT%%4|
+(dM1!F)Od9MH`&%j(YEdALaV0EPfKO|{>$yt2>7K6NM6*KP0LYZ1cm$5}<0DFkz|vWyp2q87yh!Ht+E
+D1a|B}(RjNNNg>4^EM(yy%}*5ScJ-KyJw0#07gKA)%!o@_B2BDk@U$O^H51Z!Kw)z$FPr<P{>TOCZP?
+(l3RSvM`tqBCY{B!G`J6;~2B2L<lN&MlC_Y7<`ebvP61>@3;EhaSla_70z^4<;et@bY|}U$|zRo+r8l
+(6bo1!MrNadFr)#BJZ8Uxl5WP8kprhS0Y8qo!}%&W(iWCw6ES@t9y^6Xy+#P^9I~tI0`J~jV<W?mBuz
+Va@m{CST2{<WxbibS_J-!`JWa`=)Y4e{f!s@yjVj2cCoZq9Y@I5$G7)O(lq`t4^Htz#CtT5vd^p*`3W
+*hem<xb9Z}Ued3+>@uRSS<IMf3$b{zJ^pPtr!0SZ2Ht>e#x@o}qP4QgfSak;&;ia+TVWOVej(7hr`kB
+?-0oCjeaMc!U}9fpp`$EpcC?u};02s1(-{~2W;pNjauX!N5S{FG8y`u~?=Y5f<)QeD87_(QSu<+1<k#
+gg$qES9uu#67*hvn-!#h%~KtR^7g0>cS!u!$qU7Ae(cM2bH=3p}t1+yZ5uSvTygf(rFAkr*ZMJ?ul-W
+n6Q(nNEG~J$Twr>jhzVTSBt%}Yd6ygDgY*$bnd0P;Qh(>-teMd84#ypp_<OK#=N2QS(O!*`a|8hCp`h
+xEwhx#>fE(|-}He7#;xV~LX;mq<hb<6gH2YF`6GRoqO3N9`_RTz>|V3EEZ5e%o+|Z*yveu5qT{<n&Q}
+29)fe2r1AmsbxNfUx6DG@MTG7O?*_y+!yE%jkuVQK5y&-#=%SIP9KbCBf(i)xsCzNp+Yg%a6Bpf>QK_
+)OA<T2B+(V5NcEuy%&!Jt#FEh9^U!}Q!`$Qy1?#x#4>70}9^K^lEWoZ$Yo5>dM%TwJ)GS4ghzBGO4FD
+HNnRISPA{ycf$mqdP70Pf`A;9QOun$_&MpQtR~HktzxIL-EbwA}-nMXe))DSSkS(<Sh~^vM3E)5bGzx
+b@Ec`abUh3z=A#dGJAfAsGuZSk4sIdd}FWIo-%K3*OD0DA#|g&O@{{6)#g|gg(XV$)P!DHlm}335e+e
+xAjIjz_nEmq_nn+_-!r=O)%L`5(p0w%t*Q_#3}F(daP?IAan6J3c?pU$pwaw-l-s^f)|wNj<7%??ZG;
+ORu3j}EQEcQtx`B$*UK2uHG%R0d485OgVc-TmLjQTOBxKl@pPCpXv0<9ufLoBb8gtfJdh`FZSYkM)25
+i?8?uN?T9{d}teFNUW0jnK*(!_WA?gH_3QOtFF-VJ>{p9`&}D;AH(7^%Er2VWmZ9DAjQLZ|xW1*+CC6
+ghXrPw{3{+N;N3F(|5nF)uL2krP$lx&puZ;H#n&?P*-D4xmW=aN-nJGeBulnCz9zm#4d}VsFZAzBvUa
+3oFgai6E70XM`NLj8p@ot<re{Z6koJ>N9TNP*jT_cXeMq{Qr{oUdxVZTd?3eUvb_Qw}m(74TKloL-Y$
+C1VRWS5MSS*GG|wvs%>uHHqjkX6-x_YCR%7_jxoo`Tn7P+1rwADqvS*vva%>Zkh;^WduzqwyJh)HajD
+D`REuK_=$MU&{-v9ut-Jbd;P<nWH|ioRMi7n_-9HC1(yc3m@eUoAWi8-o0NOjbx-go)z5ozGVw*n?lY
+AkSxJfVgl0vckkR+OeUhnnxJ`whf)9go>;wK5d+6e?tH;(MQYD4fD$nM%TZ<w}03sihu)N1wx=t1gdU
+L8Zd^h4`e8;wS6PFs4y0FjU8PWv@$U!@IK8xCj^$<i3^gij1BSR~tEw0ed($~#+3GK<PXA%?eaXi2&?
+CpLb@@;;MzaFBAQHkBv@AUdZ8$y~aTqZCy#aQ5leG=b!ZV)Rn)k=tg10<p%+@p_5{y{(K}g(gqbL%>_
+*#R4-ywYhc`@`94}^~tgZo9Fr_kqx8@6MnfCH^!faiI~GKn5!L>z|@Va#}jmJpfo)J^js1%wQ3OTyxo
+MjKc7>KJL1d?>-Ji;`qH1pIZFRQA?N>a@;0~g^j}}R#lO&&uN+3--~Lw3!gbS!9gO*Z1S*AlA|BN(|J
+m!S>{fp4{By16|D{*@UJm*vSNY3I&@}$!a=;@~g?@ykDfn0<+$l_vA4`Jp#}F1KKJ}o#mSZ{esqw>fe
+5XO_m+tiRqv3)a<(`K_EqJ7#sO;-1Aq4$9M-E<=LBHW*MRu%S?i?>eK04Isu@qWB2fac*%4Fc@0!Ql@
+esq$7AFGIr`gHc^M-Lj2A95`Fg^7=L%b_-w9Xi+W&hP$`i?Pe6M`HeyO3<%P5I>O~i*r}ty3zeN)+4p
+%^oNQWKIyDB?U;8QXsyH_y#j}Xqqh^CYzlWU6gN8i+TJy){Er8J*Wfx9=%PUSL-C8Mio7{_f;UE<)&k
++1`DT0mjm&+cQGe)@px1-M>5dD3sT@_mHlZC$g`d*VU*F%~xjo>|?(gs19`I-P_h+~Ft<)6wt6Edqyi
+i$WEMYCb<SS9;T|5>E63Lp6PUlSnNKPqnq?WuEPwuUmIp+IHO@@&gmOW*)!|0k&bv$F&ujN{=9!*8ka
+-uO^N8SOuoB>ODJBBX|&IoF+7hTFwsaqn+36H#mu+Y_d*0lF2FDu44M)dWh;{C<m-YyleJZGao^$g(p
+J!0@v-8`+s(`rDZ%1vvT9||~W7x+n!7iUAzh_4MWDiB{3*V8I2{U-A>21GeMdTLdIa2OaTQT14DYfK6
+6JBr9|_gchaSij=XTh>4^!m&yB%Fd>IFlUFLom7D9Xf@%?^0|s3#dI*(ueNq7@M)A*9UNR<zEA5qK!J
+D08KNRt>+F{+zJ22_z@HJAU#@ulP-<#J0DaD29TqNeb$trFG0<<peVqyY{W}7)^BeDmy!P0if;;^U_z
+FHZS2&ch;zTFH;+7ZG$<0Ix%%m9EIk-1ZIi^ymLSnG%WD-kzREkBUv?BJ*M*t+)yp7#ovT5dTH||>sz
+l_zibl3(D2)81^$oKZ<%xN!D<M5{De45?z{9<Bc@evTf%lnHkbO>Agysz-93yFS%ifSes@SHvGvgv`j
+*Pl!lzu524QU#(iKvA?78iI<z0Vv2kmCjBj{AWC#NYluZA)!P`Y6@jjNk)y7NYK^#RW`YB!{Twa29~$
+*!qxOyy0<`1<+TyT!e&T!?E*cU9*%{HUeFfO8HFk8H*?BJj%q{2vib*Mh&7tvqRIMpoik_;IK9F4yy^
+P?q*0pvACBeP&cA*@y$k&>_+KyxQak?bJA4rBK)Roh^Pe934GaJLxF2hA5FA8)35nUK*$?|Duw=)INS
+q$<LQ+TH0R?`t4xe6w!zJ@KkVt-HCzGRj8NrVg69oBqEPakX3@?)dkYMUSxZ)!<jTJ}3UjhEk9Em#o9
+%A%pvDn8`fCnJs@MoFm(<+FepL$X3Q<H-qDUcjJbg!xWI3z#%E{=lO_><H)dK#$%6%Un6=-(;ySCGi5
+2PCfFA(6d=#`dfAX_W(iaxJ%bK(*Y3TfQ|ZublF=Rr(t&{HG#wpXr-@rsrkPh5lnm03@G$27M$1m}BM
+SW1jAOGgCh*YTUy&9nzfYXq|rlybbu(u>Q%YfL{&k*Q5G%ohb0@LQ(x~j}&g5DCqt+aJ@eJF6YadGYB
+#DI>8I`c<MCES^J~v(skju{i9|5&7}l4#M9Dyo^v<2jn^Bp*<58B<xp6yugEaMavZ2Np3K5hQ3fsw1C
+uRYgRP|*p4z9r_ie4`-eibKdpN#r=(c#X1nJ^1Jum2XHN0Gw>I17iTd5(^A!Pw?+jyi;9DMPiT&#*BD
+#Gg;(bu;Zs4S&}!VHO;*I$Wf-I$ALJ_k_c2$z1>(YOku3bg#wYqj3Izr=HIPj@wTWc|t(qIE(qHnH`m
+s&k*SC!QF=nCfOB`*?K(8t3Y`!>k@SS6v2+8d;`KA9)bdxJi5znjkhOl($}>0Ey2Ev4ctaO?Y{S1nY6
+2zJK5l@RyOafyBIO7pjI<FAKZq#d`?fnv5C(_nWry3j=;B^e7lfR8&cnR7s#8B3>3!geQVkrR?LSz*e
+8$y&G^CJLWdlD8ZMfO}S%jcA;431|3hJ?RlCjJJRyyA#>mAS9Wu3Q{V1;f0Q-m^Gkiyb4f?#*ywD~_s
+92m&w`=azO1a_TD$@OD3yNb55NihwZQAX_9<d6CeAPq_9Pg71!f|RD{l(PkaUhN5cq|dVRICiuMm+(K
+!MFE`_iylq{lFM>h}3AK;#zeCk{5b_<R>^?3UjDyF3s0-q|Rg0(fI31h><|=J8Twb)J#?nz6l*GnqkA
+dX+mRt}5SQ5!Y13ThzR(fjBL;R2xe^OiZ@8oCcbQDiu3*Abg%+n&=GUD&}$?YxS**iq;fZTdTzrsMsh
+^^&s#-&Mrb+Li)MBVt5>7+j>9zV3xh1#coPRPN%^xhOH5r8@xCX2Cd;)2;7z+)bj<s0^7xXYNmsRGUs
+Iu#GK!1A*9uaqq4(Xlg7Eo+AVzJTRUxpV7ab<SREe_ajL=#`X&KG^6&BTxU>1ixeJ%M7{jJT`zpW$J?
+bU7+7hikyh&b>1@WxAV=+~p74<4kPIX5@Kz>vUbb4BwgJbXUVkYe%1UmtTpzZWHN&hQ=n)CioVfAkh|
+7*DZdgy;4_AeX#cT7w1qlN+gh=IV_C;CK>HjNZKkP!WpF@W&#BKdW}>>fy_)W?B(k0n2bgAjPwRqxnY
+>~ZL)Hv@)`Dv3QV#=&D_LVbi#kl!sR<cI3Oj@x*0oQV8rUX%C%(fg76*g)#v@Tau|{*+$qk@0?+oiOb
+2D)gl(1U<swJ=Q&zH{v4z-rveTNKXDWVw(qIzkfh%@Rx|q)BhZ?uQ&Sf4I3r*Zy>hig}*^<chT7BC)9
+Qq;Mn-9q5a*F0lypC???7eEED8ztypWB>l310FZwH3xQ)Q-m)uchU)XuscR+h9WvXKI)|R(>xC4ugbW
+E{C>HCV@`jURJ3pHH%@kB+K?9LOZt_}PsPuHY0E}04fh+{zEBvzZ%^+Z(}4qwk`MffZ~dj3@6vucJBL
+)=v23e`cTv&uPYh0$qY(te!r2zZ)~%I9ktv&nQ3XM{>l4&jGuiEcvb*rHPv&jFpSo3;98jMf^2B4mX`
+pbcsY+*&|SVE6v<z^?-$3WHej#^t0}Ft$PS8ozLGbi?xT8gm_CUkz4KH&OS=F?dzMWxCo435cb660dB
+?l9OG+GD$opr;RSXhbzy}48oI(aPqmIhaABmNJL`%56Eqs%V8l^{;eFirn_~s*4+CMDdYQ<K6*-<@)!
+`cwfl7r{K6pScjWeV<hFO@79Wzp?f;poqsB<!7eKGcS0uFW$k)IGkul}|4gSnIxqF}jYP#{C2d!0aU)
+InLAU@XBfD}>pjr0e?O^`cYzdtDLg`d|dOJfR0Qr6|0O3(rOpT~JLcVq`Fhr0dX_z}o$cBj5dOkiVt$
+PRIFX<eC1)i9524<3(EXFG-;qXm8#F08$i3-z6V1jy0GYZc*V2~aCkXg{$>z602UgYCmFX5hg6-}_9^
+AQ4QlakbrACu1&fMTIa<hVjT<I~l5T*aOJSu8<lwm%L*($W11ejkanyF|BatV{;-1S$VzbhwScD<rX2
+DUNs1GUAZ*d@)5*<ZoE!6k*mnI9|npfoz{Pi53A*+JC>2-Q%wlt0V75N)~?z_FANdX$2H~zCl$$3<AI
+Ak3t6xg0o(?(HqG!gdP~h@?%{aoO(#S!DAt57bKY14DYg~_s#H(u40vW`hv;Hp?Q;Q?6c*#;={&G?#G
+$%8XS8;Sp^MZ77eTw}mkbhb#xr@|vJPvFjDwjvWE3QN2Ef%@Uatqw%;9#%JE&xOLW4HMQJ$*zy58>c?
+7bH1jnZ%N*{#W{@b=#~Uff}mt;f3j0;bmC!}R6%_<tLJc6IuzeZLFv{IuT>>0}TiU<3nk5Jo5jK}Z<-
+Wri8XkG7CK_B{ZU_~;7|AI)#<2w4w7*7$&K@Y65}{<=SN4{UMhSews3jgVP>#I`$*qRA1Y?<d&tHO7u
+$7X7UGAHYu>`C#IA8Ri^5qIWd@NW5mB<$dtL=K}knKlD*D01vo7`Y@?O6CvBV!ydR7pXmByH-RHZ%6n
+%YWPD_|4`T}Q=-2`OQh|(*53qs0ulCEdeBEc?d8tSK_G^%qz9S*<MUF>PezGCDq<0?Nr-D6Pi2i6%bl
+u<M_U(Q2W-6sq=N;Xfh5zO$yfUn5Gv9Xjl2PTQuf3VvJ~^eUe)MQM?)Jqz$=qX*A2%-UPl;j|9Dg*3Y
+UKAZS*80Nlij%$_|Kb<{mtWzw%h03Ienw6;LyQ0?H}#{Y3}R$U-bsun{>c}^gB&~%a=T_bmVytNy_>`
+n)D@$`M`!I-bgMBqUV5?%BvUP%n6?aS7(`mYf<buVLrRXXJkn`st)L`JjEc#;jTcvN_E^P$ycP=LlA2
+sVEA@|`*pmIOJWeu)A$%cy2eA#>d2dLdInUlZVkvvu@Qnd+wuBDap;BSZ)+iphy<+g`#xmq+7sIY%lS
+Jr?V&4SF;Uu>Ly7Vs8PoB-S<aa<H#(`w)Tw9#14Qj0PM9PIOs53#$BP8>lH&z#G6Q^EkxYL>ynBLhTV
+O`czu$y+>fqC=mv<$#u0-K`<Vto`u?O_;;8ZneqqL!#b8t>u*ZUPunaIb;u!6ZtJ3p5_s_*TmSCX2;n
+d>H+^V{lK%e)ObU<$Z56lbBmLUW7Sdf}h)`ax^94{c~S+u~?!OJNL3>Ahg<WoSsqy%j6Qn7n&a5DbVE
+9c6PlGKt}LtP{4=T2&awW1K0eq!`a;)k0VNt(C|y-)fxI{iK^`Et=qHqhc8_i;!y`kN)aIgI;Z27J!%
+3B(_D*srTAtoqu^R_o$o(jw8nIUJds+YAz3K6{pg5S)e{gouA(rrV=P5J<)VSwWe657Q{;TQ&^P2tFf
++CQbj|Jw1c;v8{85i1!HBm(5(^Z6je8@ydH0+4R!eY$=wMscsxu6uled+U~F1&fk8BM-<r6j6-Fu0p1
+TzZt<8o50mIX~c*p{C;YtLf$#&t2b-z#?`jw2`L27`XR`!3;XP=@D9f*rd<!T9)&uMEgzu$v-a|Zv5>
+3((f*k`0mxQCK#7deJh-ifGVQd~g#`&f!_&Q5($pPy%tz^<wuUhljLOc&FxJ80UcI;2yAD>l4y8O2l~
+t@~Fn(9jm@N$9<ISQH+21U_}ztsvGpH_NmOp9LU1dZ(Xi0(Lxav_$@C>PIsdR>^7|bOb|HvR$7ZV?=B
+xt=ZY9dbURJZtIlVvwf2Q?JKKh_QhR^2u&38mYi7%B;-7^PEi}zBQ*`x>hQ#g;)RjAk`ZCmp7M|>SYI
+0a8Uv@iwUx(Ia?ck@`HWAjOj?uXPEFpd51aa%@JXmSGX=ZOH%r?I!)s7AHg)1N4<&I6IQ+D}^KyO7CC
+W5)CCthboc1q;SH@?Q*2^xqPh=w|H1RrbxAiWH+=P%ipV4i+vlgJUUlUVAf`xC>Vz91$QbwYWl7`WAu
+?=yYU|;Pp`_d}lWTOk2V0-UN1tBX4&69)x<yJX58xkA5^(TMSL1W}_jzS>VWpZi%ir>&GeDUWH;na6T
+aWGzXkIp|O5AFn!>;MQ@X{383Ha-S*k=zj9adSLp@x#o|Pxoq*FkQDN)7^hhoGzhn9YXb&K(tQCSw!>
+^*i^m6ee!zir*>&C{1oe@yDF*|W)+DFGsi{M%QdT6m8eXmPBI(dBAx2@4XocYxdICM9=QQ|nU@=R_48
+t^G$X1V&Rx4+tQ(IwMbjvfQ*=hQgqa}gX|#4#^u3lUf4_tHa`7x$ilC##cYl2>vm00Gc=>aO@SpDay#
+x5$UO%KONSMUHofn}5O5zkwg1`2T1`j526hP)jB7f%=Aa!(Sz&pc$j+(<`*&9Am1SI@#@HdW?$Z;qUA
+LWw}_Q{15M;+z<D_k6z3JN+h3fM=f{?N2Y5A9YQ-I>_$J4f*RNS;9Op~iIdwtOf~k{{d(qK>M_ooem8
+CnG*yEuVT$7(RI3PJp1#u;DM_i=Y1B3_7}&k8;X=D1S+hL~y%YnB;rzLJCG5=^O3b>+~=EP|VwZG>rg
+yS!C1ISg(~C+k31(X&RX}*fJ)l`Kk#nm+zSb>+8000sc^4$-CbKT0cq@?xG*wkz01;E4Hr!t>3q)oV0
+Q`+62C3MlLSDhZK=*x^2938T0Fm&0Us7bh+uvC~usm(%;KBxnmpP{k-t*9ZTDPoAD&TGoH_(`wWKnDT
+w+W3@A2gUx=~C`gdX_3u`kj*3~HP6Ix83lkvgYYZm{S$x^-DA0Z%4wE<f($#Eqd7|d<Nm^iqY2!tE{d
+ui9X;F$DbFGV(KrHYUse3nnz6J{TZZH4{=5a9Y@<Tua~-qa&i6q>+Qqf+Tgqpr5f-lTGP;7;BN+<U#4
+;LYnu&dHjfV(Rv-^)%3m#;}!GV9+|F_u%#6Wo#U;K@!}}T=x%yr|`wSwd+;r9(az^4cdbCb0%Vxm4<2
+nB$`~VyzLbycHYYV-eo+k_-H*~V7!=a1m4dy*`LvzP%q|dGM^SWH4Axrk_p3N${7H!l1F)}oLbx2vUC
+osqx_^_B#|CSeuy9G5~HM`bM%uH{CVdd8np~hot5*!U$I;S8oUtd$75?@8sS(xFz#s2XK}?+f}}9lBE
+g@{+9-n=E4S7)9C{B#Z^KBCZxvq8C;^~Xu4TY_c!w=`UTULM&UAYZHez0tSb?)zRo4+@S6n^Ax-zGj#
+-AbG3-8E=Lx!pYcf_|arMH!;J%L4_`Bg{GWdfg|>%+zx4k>QfBu(Z6#Ok`Zh_dly%~23flRI7QJ_gdD
+Z{leOX+hQY2~DO#uxO;_&7Z5yByP6f>q3|%Rb~#)+>hXzqgH$|Td3^gyf<24cE`Y^PwO;v5Yn7eRMAI
+$-J=i5x|%Q^Nh;l^=0Hc^7|;GVzmL@Am@b7GO2Bmq4?$9K|E_bX!@N{(5iXbg3uC%Gv(djuc<{Fn3Fj
+zKU(vlCfyn2Z#BXN><liA&_1T@;ls_(t_|_|ZQ}57k@zB?9*^Qe+L<Uuc{9Fk5dL^c+wC`6+U~Nk;SQ
+Ww=tlYir$I1oAt_bIbY-!g(0StKalfj%sy)o$d<@|=tF<)|AJKqacCZ>7qDo(mlXz$zsydv`PhuCW4T
+NQ67>QMbmzpOfy%>Ft))M@;1p9A=sDJ@U5>5np~&wg^60`UC<TcpeJ2G8IZ+M;RGWFT5J>11Kvw9wGe
+ewVah(h|)ywBQ~;+2bdWmJImWp=5emQ0dUzndbgGxiB+*p=r0=57a?AFX{3)L1Z33mwmteC&$r%x$I}
++!~Kl(<Jb@_OiK$W9WKWSxj$afJ${DAi3O5QXy!!=DGd<jeue!?`R9!4euaI=`_N;PxgR6h52%ij#U{
+HQC*DuQA0vp4k?#BLxA5hS_%n2lR_HG$vQ0+#+=5AiG#k<?O|LY|(V9uaH0RP+lm6V|aSJBRtH+t!uU
+B{+XU=G5q1gwmEcA;OQ#xB1gub9(KO>dS%KZeN4{@UxrYr}hJYXx`{{mqXix&7<Alx6_?ERkyN`colg
+4-<-_*?8#a{%vw`@Zv}@*nMnOk6B||1K={laU@=ELg&iOLw0~xyIW4(Z0w2+U}3}1jIi2G7tYop@kDf
+eT9Ee8jOVfdx6MR9Q2=2s2<fsfi!=~{rx)D2);bZ9Cz46m*)C8&=kIZ1OE%Hf$uSfoUU|#?#`~(**of
+Cm%B)~%OjdDhL-hOm}J)$gdrGXOU6d^wd+i>&w79*K+dA>Czx=1xPL{%^BzH&N~*E}?f3OK)3Ih5&Xw
+;yQl-|q#!KXMDZ+~lCInf!fc(Dn5$BwhDT1E&RSWlr(RMXAq=tG^`a9-QT;9H-_`waPcG$mgdlb1zgj
+-t$d%6R(dgiWyx(5NcAUJqNRQIbu`3n)ERCgI@HY=%UR!KHNyq4c;^qE4!V$#%&if?((0x$0*i*d({I
+}Jx0kiJZVEJLr3!<ZB^-0jhN6Qa|yW1m*J9lOk=<yDZ8t63FYdmn+R!>0~17pXKDvE!Tbt3fY)7$T<R
+4i`gVswMA5SYtD^GxK_aD<2szMs~$-4qW>pK;)HYaj>-0f>R~;=wPI}*EBkGQ(Nd^ndW^dxe9zj2~Lv
+Th3Q46e3d?Q$575vunLgyt?zAH<-&{WKd<%dcJ`8OR(}Fl&VJ`YoXn^fREs_sZ0IyRk=MmF$UWN?h;g
+HV3R-D+e0v5Ilv<jjm4bso3gP9#zlle24_0`d!a$Ix^L>eiUMyv?dq0l~*JL}bJdh!$P{tnbz#eXuPV
+jdje6=;be~WIcOy$d|Afh5g%nl_Lp0BL#eNvXKoRGOTpa(1hz2W)h8b^v@H{M`^v%n$mR1QmKE?ZnA{
+SfK7BC%L-@-!}d)@VrlGr8C=1-XCdsQSACv48i#A0%OaJm`<H2m<53?8GXlBmYU{AK&>yv;64!CXlbq
+Pt?b#>d;Itj=EXuHw&lfkrqYCBcwR=h`!hZBS*Bczs|{{32J|R*hGMb;Y5Lb`pJub<Jj+%hNwd?_RH0
+akGT2a>-BM2#K5EAX%A|s;>gn;7LnKyJYmT(LKHg!Ci1gPihq=iaOh~Fr^tWfpQ8?A#=kUU<Ubuo@B6
+pl<H9QcWtH_&7;=9Sr1SW61-Ore!q>#6XYBz<#yB;^nt!DKt1AAdorz0T=J7?1XOA)fkI#;L?AHp{<q
+v&NUjvaF4Xd|w(QXo|ZrUFMkyUeC4A7iC*x<RJ#M`ZXzLFO1n|Axsx_eL(m@Yb*Ah#Z~_cuvAfPud1y
+6$g?EFFK(#X?rFZ!0Z$eT8>^{I35Baz6woz+Xfs3zNMh9NoC&@u&zC(>js6ijcezK78rqf(IaQ)h)ME
+OzsMCH)|A98SGiUsLX3X9HnTjVRzD7pNI;B-!CtIUG->m=Ig?V&17!?NGpYFMBV_0`uoI);e{O3TLZb
+b$D=$~1V4u1EGWM9_O0zjM_dC>;W=;&#4E1Fr2<rDc|PR&&L_xxwi=k!ua=3P@%I#(GT5pFg)n63Eq8
+KwKKY(K3$TzNMz4W>zt8(3ut^mp4%5iIPD#9>0U-#_G}r_&RuDUHyvf=8hc7~0k@CrkP+UUn&qr~&Ci
+}EsCn<p9*GJ<&ilyiIn%~;HQmwt^M(<#SxO81Ij-2i*Y*_~6U$5+GMx*E3=+g^yOV?(Cf%kQ+;XpO|!
+iwofb9OMaE@!;Xc=c&`Y8PA3c)LksMAP>W=3wWk3DZVV;~O56=u!i1tmqr{ykJWT3Q^L}7vXsg@Vl<y
+`qh0@QP&hBsY4gP$f3y;t(W?Q=djjbRw<Lv03P(Yf6Lza1^E^e42EF^bV8x>PM%n3Gn0+Gw4_oe5#@)
+CGk29(d-BtYFGe|J%Ffsrb}MGa)^Y9B-~6>}ZfdqDg-ytc^eXRX<<juUA`jhsB46((>646k1NkKl^S6
+_v9PkY7oBBM>#C;5E;<}#iTh&N!=_zN@HdfmEtO^^n-(z!K#R@|d6fdz}(wW!7OOtd5P=~h)M@iY`Yj
+pBf7s>gJgXJ&WE`js*`%bH1vzcr@`C=BdQ`THU)by7aFH>IVC~y_Ev{V4-T~c)*M$enZ;FXyqmz{eF>
+qQ9gBKF48oK7`34O}5-$}M3Z`*S|`e#70(r`<ot4p6FIE0YrkiF7`=#p&!mGxfy2=hWga7w!t*+df4k
+?R9fbtu#-|ib4>6Wr>rEuDH(wBK|ToeK}tZR3*J!aK_f7*3E^l9>sM13(80nL3v&B{dJnTAdftr8L?v
+1R-yK_2VhCCLkZUMVBzda2do}k(6AfJbM7R#Sy!`+QkOI{PVWtEkcdHAr9{2L?o6G`FyaJsb(>QpZ-v
+Y`hs*h`1U_PdwS%1_Y<*Z+$+u-|tms`L$p#W9Q>H}(wr;XI>8a^g0EC%w%_^(Znf37W?=U0xj&QlrGd
+d8Ob!*Bgf7KKm<2o!4Z-b`FE4hc})&OGR?E3(|SvPKfmfAv?h|@VO`AWjw8O87Zh!<~qN&?9$?&A`jq
+dD*ES|T{oomuXQ+-ubFfo@cWa;=Ma7!z5bw^ZH6oo;V|)?!6|+CybRmPoZBD&HO**mB;n@baTgW{hWl
+#cse7LsUhpBq!E_fONOjFy4&pmP4&yRz<~W;d;hyVS{=(zOJ~LWnN)mUUeloV$1yvhy~HK>bRFYxmWU
+WUQZLUJwtpl)y+W?3xigd_7EjE9GO+l2KPV%#nv9Jo)72e{k;d`iOHzoKj^f|+d8%%T|UI$sm$w0rT*
+cKpV`mfJLEg>`Q`3EEK^eyh(Z*O6DR~yAOsQ=j_#Xal7JzCAaN3eFzlB)jECXMCw~cjvYQxwEL+3)R|
+b>9M;G|l<|*vo=&$?KQRLt}$-$nEl<3jojvw{kDRi`3;UBl@L)Ygc#gCw$nseev^&-DZ%^pg@AOGtjK
+a#`+dDMav#BoL#IdaDFM>Y8P75+Dj9t;Zp(62*QI6wGaOdNM{c+?=DDs}i+M?YL}kbjfZU$P_pNGZH8
+-`J5w%l?UfvWU_oYrfqt>FcR%(J$RB7C_rLS7oGc$xh{H>4|;bN#H$By>ox)4^maWwc12zD;K8rNK&p
+2x&eIU8)bI;X8Dq?JNrQodzT|U`=ymh`f=NhM!wl(0bhNx+{j=1(9>SY-Ft@)SA5Oi9EynkPow$|1+y
+6#P=C{Z{>%1r^?JhJ#UjPV7Tb|m^au}lR%`_Z@{$tDDaFSG_JSI2;zC@UWx)eG?G`gBOk_F*_d@KRH^
+slyI3`Wcg+>Gq0*Fhm1*9NSHq%~F;bCpKEMe}#_skjRQ_<GbXc#CyA~-}?!smG+ut9{`6NK-lIR!vOV
+9M<QH4K!Zp5K7l4RmasGSEr8i%-W8hAh`^hC9(QCD0<3p_WN=0d(V$heWI=;Cu@z!efZ1bJ2uMm2dZ|
+3lfrS*UFjSZM~*_o{pl}PEMl47f^&7me7aVH8|BUE+arf>O?XdMEDD)2RhA<mA%KO8p;wW;;iCB8KHW
+<hOsoCu!MROlY;j-XcNUd6t2x3$fo6CuXHJD+L`atiSSP}1>TAMuT2F0O@!16;%_I}f4mSLEL_JB?K)
+^qjsu5JLCgWYBJ2~7vZyM`qO>_T7jarA-n66o2^%-wpeOl0IfZmr)lr@a7OZHtlOO)Ab|rNN#vN+OEi
+Q-4xk+I0;+hR+JSJyOrVgG~XAYuB>me4i*>ayz%gUCmiA=Yd0zCz{P@pd}qI5%;k&-NT0<pChV!Wz>m
+V28>SgD_%W4vP892v|4J8jeDf#}FZxkEE{C5jOkTh4AFwf84y;VL$DmMg*a(kq<IbL?s)n<b<#x=bxY
+A>X|6d8et?BFM~rfCJ)c0`Z_;`tmBh2u&>NA%cqjk+Yumt$oYbXzF*RcgMmBaI|mzx^>H0Zcu~LiUHl
+Qr_XA^aO&nKe<~gB51m`U4=w>aBYMqNx<gn)?X%1I%sQ-aYZ|br4bbcoVw#YLcHf>il`S^tUM4M&t+s
+_@5R+s38TH_NzKBdvu#E`iNEY9#V3F=;st_rV$er^I5xIoU_tPsE2_l*M3V_1YDaz%6?zg3F0bKEGis
+IBIH}LLlLMC3qT=t4A0@a+g8_sMS$;yMmp>n&+kaGhZvoF)TqBUmW_sLnh`>$zby89D6@^jux&E?rn%
+X9Xi@ANzDQ8t08nsLxITQnxmfDkV8__VQ37^B=qzXCVZ_RrN5@IGRPHocjVGz7L7kOisk5hZt0M9IW+
+ltDE#WeC7TeRB=_aJ{?NoG;#Mtr~RJls1JLC+x~+cAuswH067+^PVw&C?kd5F@N-06TUqqK!3Na)#AY
+wa&#9yY4)7^r-548=BgA1_;_fH^xi3E>As0ar#td^8(1y8*UBEOs3!t=d9NW0kp3d!g8E*uY-#&G?8p
+(hm=zKm;QLCLBTl8uSjzQa-Zy9wYir!X41QX<4@@MfHLqD0uJ_Q+g#3JGxU?29AxAEhBd)qzOU=cCJS
+LvDmxIQZ)#$~1o0Wbs)wBad<;;1lfroHllIx=LFK?*YN)t4vVMDy_yxBs;uyOZD?fQB}6ZVFnIWgh9j
+Ox`}0s9Ig_*6x;W}B}y-r)Q``abWznK%9(#VeXLr6ZAegWlVR`aXl_2<k=OPrUH&6C&<^ICHsEmET+c
+9DDrlGYCP&z8l8~|6=O4J~m)QegBt}H;0?vZKuOS{jXR4FR|Y4`SkgX{@*^k<sb8fZx^z^T&Ri1_kJN
+YADVotf1+IfuNl-gQuh}F`oS9h;B_bggE#>qFoq%+_A4frkOwh3O8t<dz&^<ihD3b&!^!xtc;7i15+5
+{;pmxId>y|#~SXj@Ak4oal%LvbpL=*L?)5p?}K4Nwh6Yf0fXw3Uqpkh0d`<*=FF_Pk-gz%?NF#A+2?q
+l1}xNpa@W05`mbQ#7U0+)iH1_$)WWbNFPL=IQLJpME$QXe^R>}Y>DOa%||#=l~6f_*Hqv;R@lj_>8E<
+Avl6{a4!llkX~%|EfW>Y}F)>oj)~*EFCe)eX0&7w}ZmzTbsBBx|1gcT!-u|j`J?oo4Ek-PQccP>JL}H
+$e%vef$_Z^cdFM*V$@1p)#rDp&4hI)VNGe;1mD%@D&Oel>j*|wbdNK8-G`-pU&`1=fPA#8wf$s66!g7
+nmy7&eV2I)s&w_yHGn~IL?E6v$xv8wWXrF4x2K=IdByGU4QQf|8{NV%oJD(5mXCKht`Fwys`+)w==L7
+uN2lRJ7pMN9@j=tP;vv`*H@M@38@XOf^0S49Q;z^MdWnW|5yP4Y^v(E*)-fh{4%-NF|TX!1K247iaW^
+hHm&kE+Ln+SJCvWftURm(|w^I~V~%^gfkO^DcJf|9ZBV{D)+R(QP|L)oWs5Z~!<ya)+oV%N*HPnyo=0
+h7|{;VDQyj&FEND16@|mReU-Ydy9JH`@1%`yhQ`1v6L_-`R3;<={kT#qI@0+yi(*r;=->C0+0O?X)u?
+Tw!N$Sn!JUo;uoYS4%iCV@(jMZW51CR&Kn)Z?0%mS)?E=&_L*;-^h*((HwmDCKGEOoW45UGw8dFtDbO
+G<bg$s5F#-(&Z9>5%BJYXw$`FoDgwm?-D4FxHK>V|RsUQy88#wKN<jn2o!0Tho@?Jac|;?f<`{mc4^M
+8v<YaGx;g9nKWL#R{k$@oYl9QgS%R)$<yXR*j`NAu%@7wI)%SqUV2_@Z}P&i~^3e?mCPjI_RRe`C-Tg
+Payl#O2P_?TJF^44^~1M_-AsHnN|&y6;p{bcqce?Gq&mww)!yrAEN5VJ%Q*px~3c1k^GOm)9gZK5aad
+&3~Rz>WTNl~=zAIyZEj8xQMmd+RE`t)A1FSP}Q6Y#lK0eLC%!9PokeC1#y^Q*t@826APpNPqSaTwX)G
+C|T!J4wU``JL2WW?A^5|uc_PsaLE~oO6=|!H!O4CCbr7U3c9}+1-}qCn2=>qUfrFu<AD4gP8&zqIET4
+^R}@^Cjbv;(v*Y(KQ(!#0>x)pGNqIP}`A<c``8~cKKqtv~wDBNWI>8yFJVdQD8#vg=wh?+3&9C{If!S
+p!bo$zG6-u~xNMqgUDqJi;bm(jrH1es3&{Pag7$kS7%#`>29*++T&oGVW_dkWKT|#bE&NEKWXBShe^G
+y$~&kzunprpCzx<|mRijI580-_*wZjHG+ouDoYL(2eL+vi};F&-y6PH@K}T*##4c;28CAPDVZks#q&s
+xZ=Ba`p{af0Wm|Po2;dO<cI=c9v#c#F_M=Ykf9DMCX|520r~+rV-#IBw{YpG;ia|;Bk<<<c}Dx=aY+)
+%sbI8w6|<*bIu011>y8ghw<H|<Wfggwt)OA@RHqlu}jQhC>HERFm3PG*-J=+urs*3q*?n^O^BUuH|Fh
+R=d)cD!qYFJBwj9DF5v)Q`<+kUlmyb4jw?|ME;leM#2aOSQs%Hs#NcNV_iKgot{!-MQcU@<WCMAb!R9
+C}@ZRGH6GtfJL9D|`0q@4c7T;{RTvN45eUoCxsjcHxQLrPsy@HQHhLO@?S5)qN*Z^pmyuhP~i%5@OQt
+OI6%4dt6<oXOE0Yu{4t%|B<ex>FN!iKy!82RQ-`qD#13r{@@yipS*>l=sP5%4;nnHWjp6M_?!v)L{wY
+p+hMtW2aNIMp~LAU4?Rq#mC4znFC?$PCbw^GU)|1iW>)VeXGC;Uqe)4+*qnQ@2los00#bl*;r!kd*in
+sU!IRHtDAS1y}kT(oOJRN;e%#vdOV#o1;hn3Z5RlDIj<VF+uUa)AZnu1o3HMDgKSezb3WR!CB$#vu;W
+rWuu2$cz&##68Vuy+=(m#A00b8)l7@yMMi$a!+)ze4jsyvI};_ykE+GT`z%k6q+=2vzY-s3wH!K#>`u
+PPk6crl9SuMzb}ZE<=||f9qpAs_pXBRD;{x8<E&Tsq=_cuC=_XKRIq?58(oNDol5Tni)FTN_)z;)e92
+j<uHAPFpl^4=(2GCD?yF=Y3KAtb_ijZuoL^jjSad?&`W2v5H8W9PT4niOXC-72;6RB7)e;)4iQq>oLe
+>iwF(9+tPw=#FM*=^2LL(LjkK6Lubzvk?b8X(q!h`nO9<z5HQQq)`Fv?A`wH2_stCm7PTZ6yAL#GUvw
+pyjpo`RI+$fH&}QLSMq=wNk_mLG!7&>21>6EXg{!6u+Lpt-F>6?&K=}dQ}bdY`uxKuBFLaTT6Qde>cQ
+CQ`gqBX88$H@2;!AFRS4Bx=6D~5&??@k!7L1QyF`mtEUcoB(x6lOB3HGo7>sotqWioLc9JX7^RjA;lw
+?rK>S}N-E;<gn}%uez7qj?xM{&V%&w@S&KLVnq?=SzuS0VzGQD~O+89kI7tT-h^?`=GzmYJ}ot{HuHR
+yo%B<~{I^whP!uyv}j`~Fl`Z4931oyyk+eF5gzT1lsHyKf90Z&97&ASa<#80AWGMTbuIR3vP*;-x*9u
+)f!QovqmIQ5Pfs5+iQ`B<^t}n4jm>r?F%R@~KL)VBzz+6^rKbP%RDFT$-48Ud(IMLc!ERdgu;HFV7Pa
+94MjSS*TK9TdzJL3>__f?roE&T=ME<Y>OqRZW({0ZKhQ3PB--G5>G)J-z-0c8B+tO?jd?)T9=DE8S>c
+5H!vLWmMzqq^n`7Led_0qnKM;;#URtn&)c@1Hhm{?jy71W0Wfy1b2vXQ|HOQQo*rK@E6+Zd1cT701!C
+X+bBDyA@A|z(;#a%<&@O?a2uTnqMUW7JKsXBivSKODKhB%zfl6p{C?OG_R0)nBh_}Ptj!j8&R4?tXv0
+qm#9qE=&vIO}gOThH#S2&tCp(B%X2sRVP${dOxS2%XS59x^gQt)r}3Xx-VFv&k_Y3Ol${An3YkYj8Za
+zGsQ>6IYyug+^b+>sxt3glD9bS&e2Gzt%_CJ#Nu0zF{-u>JgN=jxx_KBa&)l(1flar>`zs!t}zV7Xjn
+mhbHno*5h^&|fEV!E3&(cpaVT-1>8yL?%$%A4RAEZjtvveQ%RMjx{-rby0O={#c!~|97!ZaT2?%;*Cz
+fYb)_C4<?BE)nn9ZqpyWU>g@o!pV}jik^bzBwu9T>Hksbh!>gP*NZt=ZxxI}3rS^cfe>sKga(Yf3>cs
+R(Xmac&4+XggV@6Xv@;<r95(-h*Mm<Xkm8ASTtaA##zXl8)RKR0#(^XG2BnJep_!o$A_-UWDWv@s^kA
++8pY5bt?w?#*i1wOrR*ees2=krECQ}}uU?1-;+a6GZ4`lR4TiO`bAdZ-t_wp%$0&>BI_#ed)Ys1#)~P
+1<^@GLaw6vxsP6V*;p5j9$zk((@`Zv^!b|42nuyU;Xg$9*U|t`%O#h(Hva(DUT%l0hwp5%Qt}(*$GsD
+w1@ZUJrrAqe6TNs&s@rZIy;^&=6ox!)`lefeZ{;?UQsC#7p35oj#Rw1DhrY~Yao9t-{GTh7~&^H=z4R
+HSgxTQ>V(yv+GQ9PLh!dla(-(({ZmQ&HE)@L8~d^?iAf0X;4;71F-o+tQkn9LIFm%1){a}pbFX|_2WV
+kYOqJW8{a@ggApD8jCw<R0CuzA_xHdwju&B@oEO)yuil>yt9K0N6>zdOIBgPw~6A^g>UQw~d(Dou;5Z
+zCws=>Ky_1s>P#$a>;q14)i^3L1#QQhatkC%6m!W?OAdjNaJ8UtW^e#oq(l8P;q$4s2?#PCIVEry|TB
+2U!G`zwhBaLL~?HJFC31a+h>?S>}_j`b;Uk465X5fnBJ9@O?ctJ=sixGq7M)_Fm_sR$sLj42#?b|fFx
+PiJjCHT0eeEOg^xeSNR+G!$gid{ubGB{6+d<A@l$M#wEzy65v%ymTCepRBmolw?g20l72hxzG$tR$jn
+$NJHb9MzA?iqmwb_aKS?cd7sP18jXvX<9YVCp~##cUYynA_wo+tU&0}t`+d8z1NROpKf%&JIP4ol{qm
+3>JNgI^J*r1=7{_r6#y|o&EImPlz(E|tP#i`<f+S!NME0rTmn#wR$GQ_s4twe%KhpTr$I0NZ$^<`=Q+
+&iahso!TZpkn4YmbO_=*Z(k?|{OOHoGI<`z!+N8x!&<c_pD^Bk^$oO~IqmV~+#z-_?{HaTtEAgJhp(L
+jpgf1or?C`{D`;e?)k(qbz0LbBE9T6WASc3Gnf6j~w?gqtM3}oA~Gyp~n)&KBfbd{}R9W@Ti#p>u>nw
+=6qEsPjD36*G*eeNMqE;6eVsH{rAem(NM71?2m|GHsBv*1Rf5@^H2gsRdg6*a%-RXEg1Rc2Zp|N>p8s
+lhn@aY+ghqNBdXi?>f0TXq;(Hj5RJ7Cd;@`>H>zCulWdW!{Xuf!%B_r*`IH~}*5SIT0<jPE2kfdAx=*
+3sbQ!!q?)2T2L1MYm+SGqkaa+Dx+Pux(JK-)MBft6C5wFMvX}GxI3}*6xCC~OL7HlTfcvTs$D!RxR+3
+A8cr^!OIk>DqJaR+Zk&trwJ=dyna1PiivPh!BEp96z7EH2sJ4b2|uQjGUICZ4n`47i!1=W6rC7@<nsW
+Rqao$PGWGk&31IKK(v5e*d}vI2jc4f~SiFizr&6m0#e-m=7qUr;JsH8)iUbbOp~B!`Y~Slfka+ZtvuB
+-KRkNQ30s2V9(Zwi(tp{vUOfO$TRAxvL7cUdq~=&xY_G!AwEXK3@Ri>nc!}V-PSmy&(EL-+-kC?NW#)
+mmBRtvu_K!M32c{AyCa3lfi7D+k6ECEb6etcSMeyf6u$X#Xlm6@4<Jq!^p4w2JMlGq?`S%T=Qn9tn*L
+CqFS5GrACKK`O&C2paBiNt1X+gj@Q9}z-JWd<AY*_vmmRb@Z$%;@O2lVjIB;0-1pKO^$Aib`%iAFR^7
+NFtaC*m_Ddvu2U39aS&jN6rlYokzo6n#xRca&wvg;`-Zv<T-qU>ei&N=F6EgsF&y3b_wY#RS^t*Ov1*
+LPq~Kvg8sng|M*yQbPeMg696gKG*E^&&QVDVM-w_kf#-5uPHoGv|ni@OTqa8+1yFUv<D~z~%%I4WnRh
+0S`OHZR2||1OeTY6LNBA_q?*!n%A6^a7ocM*_<ba^+eD`xYPOsY?s@scZ<zk{=NdjADfbZpA`@uSmBc
+pUURxISP@C`ut^dnzjW#^je}X>Q@O?5a32XsqZ`BkDa7}5HUd($SB}Xb_WGQKA%HB`v-<MZ=dtOpb>!
+&!WIpu^pgOU%<sGrowr@)#v!WogLF2~s``@%PGv|ab({Kk_UsOYc2$U{Y+iH1Aa5Yq31_LRpI_H@;`d
+UK-;}PHVnu^lSFwTz5Q`@i-8_itM$*QS78r9@>CPrg2uB}4Bm)g~UXE0vGYiH^ZsVowQ8@^M$@N{wpN
+L#hCUu!7@Rewy&>&3ty_+yWH+fB?ag285%jRE1MoP79J^3V2O)|y4-lLNCtlArEK=e~xTNsN;RqIJ_O
+w-d7BYX@fQV-+~4^MvIEByfPi8!}4ynp1|YyzflwY5W=)4%R<)M%}_KEiO&YQ~D696>_uWTV6$jjJ&h
+<0Rv=ZfWwKFSD1SyMp1S#PE^g~k-Uj{5<9J74R%BloGO^HGX?Y1<0jRw?+q;CWj!~5W-|`iIy(;**uG
+S1+1bzUNK?@1rrSc7RYfWLBw|8nW>74f8z=4*$zfkvBKuG621MnRewi+=gLz8O^xZLh$xTiV2_Zv<pc
+Nt<?+@Q`LU$Mf`J9h9)zO4nAU>4Ee$@j{2*n9;-6M>Ys9ZeflRL<}XSNOc5F*<V_um-#Zg0V0j^qWT2
+(NF^Ynzy=EZswX0=kM6uD8XWq|vzJQbS&24eEx{CZeXj>t3bG*UegHSxUE157_^CRt5jhv8vx6_FGm3
+|HP^g3WP8mBq$UkDQss|1d8IH6acl;tbO}Vw?G&tVU&Qe--sy0A4dT4Q<9N<$zf+lVqoV`dyEgkA491
+4cySP`UuOkC>S%t#Kg~mAa{SBEBU6oGM@&v&hj;-9e-&HKp(7n#VE<0Ze<S$sSXJ?nU``G`cKBJvM?u
+F?B0?N`3E;=aGx@kC99CDvk?G#Ay`Oi#@J<r5>?q#_^P{i?{d7$2oGU>OUIvl-J^o`>W$`H}^D|RNBS
+elkdfld^e<w?3m;X<&s`|fKmCm}Dy2(GXs&5<rFJ@KJKW0_cQ2TG%x}_dko~`+X4JT!g5V5{bd==Gv0
+X&~%=jPrltcj}xkU8=i@(M~k)a7Om56P;3`N9LA&MWB^l<$d^qF|NHF{)T-gX#kvI^5pb9PVT)RM+%j
+z24osVC_lsv`Zk%r{XH2co!EjPsN0U%W*rojXj<eY(7!%JCI_68O9;YU)VQ>=C}F^PY-E3_vP5Sb<pv
+p=)H*&D$VyzKeH8DtZ|Uybm}9h9ginKC!Q#T(##1D2A?qa;7&i)`0~<DWvTb4hgvWDU$MzR4A+BXRqr
+~%3-^j3c>RuBCImdFvsTJGbQ)ty8N%5fZa5UKt39U0P+-h`(Al84a^8GuJ<!mvF|0lz|GXMgLTBI&km
+93jd?%a2!yzo=#?>>82*tfk6iuw<`TD9D$WX34oojXL+Uvc8W+{3okd}|y^$AF+5Mnp>7D0h{hw)K}E
+3a={0lcU<e45&wJz88r6Asx=6zg#R2Xo)m^(NYEdC#xt%bBG)N953VL=gmt9PWq$1PB2V;nxqyq1$e|
+ZFiq<)_8e2Ab5DtD^=~P+O;dm>?1Aou&<z1Ah|0*W`;3X-V+KHf+u+u<=SZ6toRrWTM#W3I;uk0D&|=
+!JfEB-<tDh?Ojp^^&jm%Y0(fbTc|tZkIaOD~cyai=J*{GdaHRD8L28{k=;`}?5Lg>~ffD;#Vrjk~uW?
+mS&Vtkc5teK1Z4mZ&gDCAF%^nTi28N8xxv0(9z$x_HuPD#+ZtV#)+Jn{N#eqjwlXj!eCm>-_rne^-`k
+z8oM3%nN`f&{OS@y`NPKj|5+EYAp;NPGsS<J5-#j!p%Pp`Zm(DH)1r{%>#(7`Iw<-CLqGNzB`_TC#kf
+}hWJOF^yb<2XP^y|{%d#7#3K|14jlj+>V4XA!)bGm(!^Wt>j7J#`#<^UAtVE&6ybPU7PtDouJYS)jj{
+l>rr4{vedjRkeo=O)rZMgUB58%gm`ykui@)l(_JwR4HDoo?#DeylkOW13X25cMQW*P-Sj#MI2*9efpl
+=!80{uu*8wvlF`!5mGxH{WYXe1Xff-JxWbBa6%m?&wm|)Y8jTx^4a&_zJ&R0j%Cy)8d`~L`>Qh5}T~q
+I2i_CfR|JY0PkFvO2&c*4Ji+7m^4(?$LYUkF}N<g?`d-ri)e+Dmc79$6xha$v#&E#UKrXI74`_55X=<
+98|L)G?E5nUh|qB%d+#B_9EGntFH#?)GMv;KM2{rmGsk;s*ZHmJN_o-R`zID&ZPce6JR+SF)c3Z${5c
+}6A(mWn|yF@IRW1-ez@fCnXItBBWa+d`iBiE&>?DsVzclfi4(O6hRXJnaf7?7133k6Qz;K`iou!KoGZ
+!>jOD$Z9X`Y!md$;y3ViB*#gU>G~zfSzNkY1!X~|0-~!gd(gyGm3Y2X=pZVZoVkeeGB}Yh8%H=u630B
+ryUaaS*e~=Aa4#ZbPh{ELBNXtg9yV7nELr4UWT%Xf94YFBK~rxj!C!kFsm5@y^vr8Gq&=wr991Fz3{`
+#qvhSiQ<SSIQ0Va?F2^@k5aD!8OY6?fF4PRj}gb@f#z$gqM1V~aaLSf`L2?jgtN%wL~l<viP{6l2|+T
+jrSo*V%pzf;66-uY&)e!KsP+)>vDQtJk<BJy3kdDCYz;&%jmPr-Pnv9fpXc#^-{ma^^6-$Pa8J^*T;9
++mA1o!hC~-FHBQ?f>33laqTkjevJf?w%ye_uE7HTTuHg=ecWTA#a^dYA^ew<eoFbsl5dX#eW%9onKx|
+mt_kh{Sk`vj_5(|u98+%{M8WtKR{K>Ur^OPBmn*zRee7AA4XN`FQck;nNTA{iH9I(ty<m{w+fFDzlsA
+);?iuHz;UjRUGf-+UV~e|@5=evN2?eguA^-$N1-!2>>_pQ5nppT#dJ8378bO#Wqhi=qCElOt`c2ip4E
+Fx2t|PA&yhn%4YUTiWLs51oMv??Wn%AMn%HZ0CttMsQW@Q1xYO#JfJ5jrF?e<qNC%;J?&d?x@cT_B93
+5qxNGV?K-Z2u#6JPM>mU^VpeJN;+P42cf91@_9AUYLqJzbID@p!*RK4KG%2tE5tt7<eNq2UrZPG<@AJ
+w~$Td_Nr+5PJ0_!JDRT0)j}Ns`-!~q_i6h;x(bS5I@|LAfNGA>J#Xyp4&3Q`4MqkuIc56y5g<Jz$Kz_
+;1(Uzl=u?DB#tmnpgYzMuTn8M8-&3+<$A8&itx%a$$2WANBLm2BW?0Hm=joCV$`%wK(;*R?E}zFAXA?
+0QHs*3y6{z>O*QuLkm$j&!HO~qjh2lEM$e?JNtRZNFv1bkTxwvj9;KRM4RguqR4-;^*Ii5&PcD>m5xV
+~AG4`o3@)wi8U&OH(56UG3k2S%~Y9KKk;I7w<cAuJ?RU$%iYPzVP<+~)+T}^yJGQ#1X0`0K*fjdb00A
+cfKkOs`Zq=c-VKm(vrUnBE_D)c@xRJatMnB$E<xYRKidxOWA$;Q)wp<ZBZ5ZO_l#VNs2<^U71ftZ&Au
+%vnd5sLr#1+~t<MOAZ=8!x4L(6`HSnxfFRo`!U8_msuopeoKRU^jyJd+ORLTxqs&dg6wd^m86~=X;kA
+XKe$nV}HSw5IWK?@3usxJtEx<D5vI<90cp8_3o?c>k$bb?wu|W2x)NpkzqCg-<wucu8--&=ZPdTl=Dy
+zp1(5Bp_Kr^VTz?adx^4I<B?7<Dd<R*ctxj+F<Pu5c&8}8N5QDJZ2Ees&x-a|MJwjkurcrT0`9Z_ppU
+3s!uAa$MGKc~!b*9=_Ui`6dy104S!`*iPuDD*waucq#p|4hH$R<Efp7($M<&>;WWpY^i&Q)9#1BktKS
+M4x(gxPrGsQi*q-$QXdFdX=c+|0~7m{OW`Iq4yT>y}-j!!Xg;*qH3!_sGG*M7#q5ob9Je3Xan6{SEIo
+;<em{Zz(Mfiv><wPR#qp6DP45QVd!Zq%aKb<9ycMbN2lIYn1Hd!p^BR62^AN`h;+o2ZK~(!Vn7_K8^J
+w&99PTmz&knEXJW#j8<qf>qlrCC^T8jtzF@ycZdvPeDFeNNM1`?4<EUr4Ck%h`7<8;8%J8xFV52u=GL
+kWRWz9U8>C{iAX?}%JT`gph{ScCHN+{XQ=fBW*4|EY+pONt<+MY23+cUr=4$9q2hCxn&B-Jywnnz6eF
+<gDO}rB9~q_sbA8NiC}mrv)Ezdkbh*K&UKo$SvVB}Vj|;q$=T?qwQV4aBH^|Z7Ifwxl_|na@E8lqQ2n
+C0*0)KuyNqH^zR-oVL?O30sze(H&*mL@zTmJD?sZDmy<upzIoo>gH?bv@O_vY(iCI5D@&!bDezt9)VO
+$;G11SKIHBvEjKTogj$C;}n~4sYNKr9cdYsBfXK9WaqQ`r7dfvZsPbcrU{3EkMLRPAq%3fNwyE%zvlS
+Z=$aatf6mho(=eH$Y_@sjrNQZ3hwecXud<T41D7*a2E-skX_jvOMgf5@1U;@5N_~kPh8>eE_GyA;vti
+rcC%f%-+<a1+qV<8z2(tfb;RCX=@9xJmk#fxL6my`#`Z?0=sj3{pE9~V2=+s!OT7!-wfHCWWw4l<=wp
+C|hb_b)j$DuRp!F@u4UVaSuSTc4&dR$gqkiC)6sl^T>NawA>Z5VBJgoW?4mxi*2m#&`k@l0k_eswHrb
+gA;Ww<`!pplQfv@`Zr8<t@bM1zvXy-9q{e{Nql*N;?ATb=Ybm2+=Xr$4r?U#DGY=ku|OslVph{PMQ{y
+ldc}Z2Qx$cZv=0a~vBk#Fp#JsYp1vHPUUh*Td<asjfu>Ee<(G?1~5$-67>bpW~adB0g0{E+t?3O1e({
+OLlyA)sH6!VwjGmU&gHQ7gQXxBmv@5c2&>wU#aSY1y+*O>k$jAdO;1f9uCMdU9L+57Xm-UWr~dSnXz)
+^V8&-2<tecP_-jSeXF5@~s5wPwxWNfM3-aXJat-U7lj}9FJ6z^33Wl@zva~+kxw+LJF}EPeng-$-F<+
+g&g;v+c6N8UQ-Fb;U9HGm_WMAl=z%NfYY+f{_UxIVK+#aW0GD#L!PMh%H2?UkC*;E-Zg}%KScd`SGXB
+J<N%y~}kQeK>J%B%)tIA417*dUYME}I`R+uA<8yR(5GO$Yxb)8$Wm9DreLeF7g?<NC`}8?P_CKD;&%Q
+Lj-8{S8BNdAM$+UnIcruujHPh|fr}sKOW6A*YPHrcoG`x90ZLPfMH|wo^vl_7TsN#S+yAylUmVL{Lvj
+09eV*6!bK?kT^kZ(Y<^+fm@VMQ{$S#l%l(r5h-JF^x>BRp0@zwTv_G7&Jc4(Pi+a*&7_;Bz%Zr5$Yd`
+xi<ahexFVVi*^762+-v1!wX|0Z626>yJK^GBJrE#U*{%n!6u@9h`5bRdQm?C>h$+|e3744F>w$p6<tY
+=2%y73=U4(S|(4*XA0M+W=gpIdO7mj@ax<<WTihfWmx_uz_kzZsK=~Bxzac*>tD}BJ96Hj?am8%nScr
+a{6fJlZ0<KXA=bO)qDTVs`MsNmjVzcgI)yY2`1pLB{px!8}L;+K=CF%;WX$te;7K@!6d0)Z%)L`amvH
+r$D!FiyPH=KkUoi8tSK^MVNUuK0XNMx=Xj2g!b?sGUKxx8kPn=G<@7XL4+BD2U#}!1g&L<lfhty#4HU
+5CnH|l+CH7$vYuH?hbczQV6(<qkP9HeyHHQi$-X&3uA9y5d3f%z88?7_#>lpbFJ}SyV)}-+v<Bw3V*A
+>V0*<XhTi=f(Eg0*Thkla(-uE+imbUi#RUGtDdIwOD3JVqc4bpJYO=x%1V<~(^}2nhw{P!e^Xc`2X95
+0=L)<+J@NXRA?pc66L-0=>;=XI(-#Em5*T6q>i0YKS#r~29@ZnvR80PBqSHqyCt5(vq5n{wLm?wW+H{
+0%Ap4#AMoymfNke^@dku*~I00p(217VBiSUSa~e><;gXtN!x`NnyR#oCOnd$_jldSw?%d23HEHQ;nQ&
+E2#+upUw75McnOMPEEWFrY1VBv~ZWUh<&W%}+ZC;9Fi|a}sCp40mXF6`V-WG+g1b1lL5XzZGA7pa6Q(
++6`vi=!&j8Nf78}uq?y{ZSq>72)CsEIm@MXS}|b>LM-EDIduDmn`f@o^*R9LDx{#y0E_Czs^SDYM|#3
+Mxzf9~93LvttTrx=cjMLy+0E2jBr>13VOpS<Q-nkE0`M-ZqQ(_&ox_a3(pUD`Zv9z8^IwG*|74-RSkW
+&R`LhK@VG1G8%~FCOic`d9LEljZL17>QgD{M3FMTtoo1wcUBBQ-<jiEcK9fS8-M=1WTQm1>~bkEtoDf
+B4%O#_;~<Az;Yih2te;5+-Cz~2|)`-o!#+0j3U?{vZ>c@I&}_h=zPzhgi*)48p<{kb#m!QHrL*dCZb$
+R6Bm*Qdx^dkfibnP$6%%|FO1yfePZJG?;O>0X%FN&K5h#iI9Q<M?+h|6x>7y`zfgvjL^oe#Rb&`G{CT
+Ia#x4v^e(7Mlz=OPem2<B!0F=>7T99*UF&cp40u1@Lg&2&DgK#%~*aQ-+wTu&gWz5>1$<B*ZyMKBR|c
+5zMC93>YvingUyR?o$A|u&Rad2#VR0%!CB(y>~ne=G`kS4xqWDz#HT|H%SFt7N(?8<E<rB+RS4*#Y=H
+5W4Pf4~0UP9euDPaZGZB%^63Ognwf@oU?*)4;HOj1=C4Wi)eAJ(0^^kA&jAM`CbZTCgo<;8d^>#DQUD
+>pRcgKqZDwvQ&dxLY%l3?xzRa+x*Ze{?QiR_r>*9EgU4JQT>)O5rj2CxU8oproD;&RkSE9}lejfZ1TZ
+&6Tip)Qhh3n(}<fCtQ<TIskvpACqI(h?E=>K=;pM8c{VJzYk2WpZ`K`l-or3L)rmlr6#<TqEl$%v*tx
+)d~9q3FIZ}hR&JB3#7Wi)LM1o<dTxEzHWhYxLMsrb+pq(yfy~`7aJ+*sq4WpfS07#>|nOaC0qr@pv*S
+rirJDS+tm7r5;!H4@9~3Z)eVxPYFB)fwgi4QZ&`emwzNyxk(km2u&4IKu1EaP-z>ri{A#^@GjI7Gp?P
+9jMK)jDt*G!-Oz|cOfXy3H7u7pk?Xi1}LoZN=$wxFqsU%wugx0tl6?t=8EnB45vAhf?Uey%qDe=qZv|
+lKoWdaPRhsNk%qDhyhd<{Wa=%bhh9nbbC^46wfag>J%5|s)L&%~HK3Ez?QQ|Lq52@ulp-W<7A)trNxD
+Ow>DRXO%iU7-+<yE%EOCr4yN!xa3JL(mnDo@Uvxg@uge&4B@Af6|*sc=3e5BsnfALvi6*#)XcmV`l!<
+yx5NdbC%mg92_vl&oXi>7X`DZn`}mQ26X2wX41eoca^-VYp#?|x3-Mk7)Mer36MMkxA*K-ryFP{szsX
+x$n)@X7&iE-*?A49{V!+|ecRjon<(O+EcExj?~CZ+U9?2e&F_H-xcNbtf(U$zBanRvA&DY53ZdT&9(H
+-0bWe6+Z^gzueviY+_C~D@i-YOzt0;WWu3=k1@a=|a;@y+Hxge6-oy-<=Y`zaq-<&Xfmu}oV74n|BlT
+!OY!(IP6-Ffj;_8s51IlJiHzqYyE{M{|R6Y0sF5Vrlf3k+rZo)P#xA`#h(r#oXT+H0QMhQar2pgr25e
+&3=a_}vMR<vYo2TRHt9ON_njy<>^@+4nK7>%A^=)^QFr;l>4uMj@&G5<C?Dso>$~{oY>Z1pbZR+ua`U
+Z~Wfw_JCjTd#fr2y9T$o+rza2ciCV8P*9$yS&0j-G>=4i_(UHldmPUBB3k4bKO{$W_00#V>3ueLPZE@
+Um{eDTCAz|cgcFc==-3``J(wn+pwo#;4*dDXZm{}#G(3>#Q~f3gH#n0)&N!e356=toz@-is`q8=QKuA
+s1aZ;1}K|1_u4QuxWz@MGLK#fv&X^J^5pW01Sc~9$tvLP)pnAmF|eSCI)|G7joJ%xre1GEB@WHTN4TW
+_B2mSeAtpByboyDySVyqZ#ij3P>_Lx?U&6WQERR0pHEAl}j+n(+wSX=&2EFrFGqd&-!xc?{Qz&f`q2r
+sb199amCur}Ta9&_jN7<=~t289`lLi7<C0fniDfUpJZ`TUtNbDfC}h&40AgU(DuLt9)TMQ4GRB5W`4{
+AP@p12!cX3ySYy%10fuTP#F1k(uI8Y`6T<K(_O<q-_!Lmx+nSfuA>ja4#=CdfqhRsElqcOyN@+b_uT(
+xnzl=~IAPDYyagflOb7XqBfI@~@811TYWQBvfW6BH#G9s@zekis`ED!mWVgh`+g$E>lzb<kMDebJyT>
+-*Zdl3e9j`<?CuF<*7N&e;hP>k<iu#=-f5-#5?K}{q{KIaBL+oO>F4^Z&H!`Y2Qpo4Njv1ysW+?wtF$
+4cWUg&K*i$7bl&yBr*O1c=ol5{EmQ%RSf-}1iWUm=nlv5r}z4a#Ezq+B?<R8O~+P?dH=-5VrE7N8u9a
+C-7xw?e@KiJ~>ah!bjPGq)MN`FYcsxOa!hk4?BA+ICqA(ZYnI$Jn#QK~fIP9qM*IerWO97wXzg9@PDY
+aO}``P~&y0+Sw-0Z*RbOV96=tvDP4BUo6kY6cZ)q0*ghb!Ezhd=bYI?X&+djXjZ#tk}xBLA$sXAc_ra
+N<C%Q$yM}0U$x@2Og|gfgN*&<XCt~Bt1iSHbX~z`B5!r@_TFa7op&qtBE_#J>(b$~=LuRlEsl>4t`O&
+)vI;|Q&l~#_18&AfEB`S~(yev!)$YTxr?8B3}Dh+PZ{#4kSMfSzOr7nbq;|*6GD^fxB2(VfjS&_|RkL
+DUu@J%L`!d@GQcdtIRn2C9(ZWJkWr5FWi1%<vN!v)&-k>5$A&XxdQj7`(p3UV7VY{IJk89M}~SbB$22
++iG0%ag~h<4@Ljm}CnC8)3xPOE{<0nV~rq$j!x_&?6$n%EHGPksr@)CDMc8v5&!115<XQw2=?got+Mc
+;?`9cvo!MJ73YnC8v*cCLWIuvOHEIO7|V{b-7(f3-KhmJJ)=#34w*E?@Lo7*7qTHikT?1IRr3PZtBJ1
+wNfDH6N|Cnc9D~DD_@r@lyzw<e&r=B=S?K2Gt;LadlMp89u=yTTk-HYcPPbRXfFnSqO*a%sefp>L+^-
+`tLd&b`D9^rUs>p)1mqUg(3Yu^r`E@|1{y`);j|J?*U3^CUS?1#jKb5qERN?7*aR&<NTMj#hozlduoC
+%w05RNyjFgo`-z<}jKd~jgLRt|!&7%I+&Fx-QBsJ2nCS{VampQ6h_&TBDr;u$nv-OuEyeVodhOf4yJu
+(GErc^K8CnqKWKOSjSi?S2tJZh1mR)<UIZJm^K#8Ze@TKsesJ*lK&cLSoxXfLwSe&_hC-TtmyFse$F@
+;IH<xl1K6COWMR33$Zfc`9WNhT=uZj!;dl9h{H&W#76`SRp4aTc#+RHnRhv#J)h9hfAA74uuA4tYb0H
+bG&kFm9pYtFl(X&IOtUz=Fkfs+0}@t0aeSX#)3d5}7S9=1xt{0Cq+`7#8WZ@WF^ypb$#fW2FI;uRW-G
+nj1&GnG9@7BO_Xbey2_r7JF6!-Ra(R21;O20~(VK@#kTx(4)w(`)8lCAFmqnCWvDGO>SyNI5pif9Ci7
+7rhslugH8@Bl3fuf-wY*0TM+fS%{O|?Ng5vwRet7q!!;`f9<oiBP1HWJVub*qV^6>Inlcz0+Fq9crXx
+~<t1&v2O=f~Upj(cnOejn$j-(lPE(b#s>#n*4Ae;26~DOL9xmK3jKobcnF?r}TyMDjAOGsGLxe8OzLd
+4kcWAQ2aVo&i0i!JCW=ia<&1k3g?NvPI41vr&ja83k|_ET)kSSk(n8hk6`g)<YpSL7ZMH+KMmSgUDY}
+LH`Aj3M(g(DNi6*xvhF`#<P%i;@d96z%0P$$sSTuI2!W9>NFm5h8-WlU!C;i!3ug%Q9^?8K*apQr%!=
+Oyr49BVZ-tayRtw*$9{U7?x5QSS{+?~e$!`-#@;wuqzEw>katBKL>{ocNhUNL5hNbd%(>l2mf#Y~bcl
+#LHWP^v_gKhA;(H+|FzAe4Wf4y7S;rEz@56R!XbBowh(%a7C_w=V-jEvkvbnHD}7AD@a5|ABsqVXOZZ
+*X*rgpnV&n!`J6BR`KXFl?pAmT|1&1D#VKvBj7Asr^f;cY14v0mWAnpG;7iPb(dM2>-4&e@mCp6LyKO
+tL+IJDl6(;&?Koo41WUN7w*%aU||RwY6&?$+LbFlf+*7fDa{7W%bPs=C+_bj<t|_kGNqe#u^nnN42<P
+~{MGo=48QH~UD%aLee)h8a+iv?k1&tkAsq(nc<w8lhwj2*pLD~1^oYQZp7BSI2>j?7fAomJx1RAAhU1
+z5E?5?L?YtqHG+9H06*SvazV#ZeQ4&JaNj%#KY2!+vTr7k%+#b#oQ9%O#C|eWh1Ko;L18o+>i!^I82a
+5_-4i%Oh!b_uxeJGq>ZF|;*yCmc3gPLzzJ{%1MZ%-?Z5G)H&jCnZ31mBg^CCBRHn9uDNvQiw)d1W^CX
+YDdp*fkN9@qlI8^Qe_~OqOo&P3wccaDijiGq2MEmq%5v!v5C4bJyerYH^GJMM%Nfvk+XSrLOt*b;`M=
+#Np`Bon|t*-p_mvgefMm=f}-{w96F?kV1dm*X`S4z^R^;kJvv$>S-wzpOuMG*?!8|KCIxvu}-MRHXZ_
+p&hg=PT3wJQD_0y@B24;au1+K6FWiB|U4(CNN@y~r@=6PQK5FlhP_M^}lD#uA0guZOd@4w%9iRB~Vx0
+9?dpAHSE7Ou+=F1GnucGu=v|<adXN<I^`!>m57j6WpM;H}=b>2)Net<YjRww4f5JEsuqh6x*6B({X>2
+w}_gWG#`n`<)UxwFrJ^z(5JXQzu?i3Ofio;#<`HT%Q$z7$2ieQYLNd7RnP!z9srONT<*AJ`L{fl!2l3
+&b_i(Nv3;pYSNo0pT8B;R{70`O7fw#qqwX__>}k!#ptoi3W)`^n?;A<0>S2(}}36VO|<sPmkjgb>#y{
+`q{Te`P{~XaXd4sk@=%&LzyDO$$CDlPWouggU5f>4F4JG0Xx=v;?#kz5WIWwWFg@rQI!Fq-4=EHo`UQ
+j<zV28dhj=Z;Tspy{R}w~KjN7AgqOv3c!!oXwN+m=FbVeM&U!liYN<hyG|FOw3!{#`5S4=#9{BLwo%=
+_2?z&}&!O%R-g%&B%$OKm8K2!irlS9Y!_w#fC`-V?>W_Wbch|f7HbkEHt4b`E2;1`9sQ%zn4$y5hsgE
+#HP_GL<U0l3Pzq*(3bz?LR<<8%RWE&oO<<|-2Ma24s~7P%=pR4u9Bt?L-hWEGRo8!WZs+D3pdm(Q0y$
+<gJ&H|y#`*MUQ!EE6udiGxS!6(rS2gtCD&f`9J&+x1z@&*J{zCvPwxA;3Nh`z&u8G;Tp^%=JTjoh2fP
+rm_^K`E>-@u_SPlV8c@oqLV`>(4A?zO7b0UGh7M~-^EjrD_zGTEu}a&p3k^tK)}kcgTaVmY`#C>5M&_
+CqzFS(mKPV}%8j|aT(3!P8BpDB)brrT&y2ZPp+pIHnO@a7oSy+sn9?({=b?^8>QO*Mjz$OZiZ15sMer
+yE<=}D#EHJE&R~j@#j+uz2K%#I$uhu@Lt-H$NBa~+xwIuGbEg4T(ZNrPWt+mDv4of311`NH}BG@do`j
+$?YlXgV&1?d-+nDcxDZ)Y%<pDH~>+zo>XQzWUZ_J$Td&M>Il(4_`Im4(F^#qG{2As8E2Qc?2D{YsMd4
+NE}np+3!9FOWsHK*Ht=xcj+X6GA#ip_wlt18A-;Ft;vkahN!5u<56Pp<`{YzZF{l9@g1K_S^eh)3NN|
+v}~O2{p~A!_;1(x1QUO1oi97SP;7&T1db9U1Y#sX5*P)M1hgH;af~3he|`@q=Gor=w4u8V7{<ho@epJ
+mV?e-f*p<KKTCp9k#n|^G^~ih&a38428&KQ8U<Ci3f;%3>lbsx#6Fc=ddn?YS(Z{|r@_S{GjM&-83AF
+=QINzJJqG;y>WN$Gd<UQSre9PQ!Cy;MkilckQg+PC&lD#}bzK_Jvegsc<IGG?jHz0{OK>I_Si0qUA@=
+uh292(WjQZ4oAej?@@S2^7IdpNQDs>RE7)tO&u^Am_-Z&;l!j1v0t8v3_c;C2Pb{k6nq!ER^iYISBY+
+<OGUAB|QDKf6wJa;~nc2~KTV+ux4FZ;OfPD`|%LT+zd4oG81lZMyO&b=F_PiXZyKet;GK?lFO%dCtFk
+OyFmp^Y0!L_`B!)8N3L51dKG_IKFlzICv^oP?>$skH^)@ZCiniD=e0elF?WTy0Pi1m*G*pMD0KgM+QJ
+HqCKP`p)FTa0rN;tB2q6J(8nVx58)~R6*zq<oxVKHgD$^7eexukmM_oqJymZ3Fv_A6G<KZh>WK`lLDb
+RZ<-8vFBP$Bx3&xm(4(X;j7eZ@Z3v)pO$KAk}dc+Q~ydD9e1A~`)(zPgR!=YG0YAC{9bQ<K!Z68(~SJ
+w$SFPVM8UrZQ4B9uns@u(kc7&)I~7;rU2!e$A#BTOy(G--MZkvK%j7YXcJl!#6NW9kWG-$J`twJU{L2
+WQQU1iY;3pxFRHJs-!`)T1Qrs}pM@gDrB}u}~j`dRs>`lijvFpp^SURq%AXoTlR{TVb!l2om3N9N1Q>
+^DAD5J>TV=!UvEi&osi^AY(e2`T!yz(jCTBZzjmsMh2SC(Zji&5vruiYhwe!9f!h!tV<Q<pJ)EqakmR
+>C>cJ>YVEIUG<lt0MBI8VTJ(9f+hmTfqoxiAC_Yle_HD$cN?$<wwYqLf*D}o4!Kpo1+A}n7S7Mc0FtN
+>yT(X&yNA_sA6#Z~ao|4<vMY9ZW7|M5*>*45|)tL~C&}bWvm!8JlspEyNO{m2g2DhONAXqia3?qKX&N
+&&*ezCY24~SQ)f}VBx9K+nTh=;ER_wA!u>+w}r@OH7~Bw<!kb6);PEC-hR3NL<9pmUJs=soVeHBin~7
+lVdmQ?i%1a2URe7lCi`2fv3Gh1JPv<U&mXWrTIji5CHIy5sqv9zv!iWB8`JErxCeBlCodU|rZutl4T5
+*E^%(GJF&?W0I_RZbtoip9*_dmU2DCB;lJ2pBD)wtp|HVUJt!KyVm_Aogg=3Zy`~Wlg|$~-rYhqxqJH
+My(hMxWs4jUfVN9VklhX6v_zn^Pf;1HN?{}akp)p*kL5~A2eLBFhztbJGWaXCDl8$OrKul<Y5>TKDI7
+~>#g~H)j<paNK2yVod)g|O5}n|lAT=hz<|>Ptc&3J~70NlSj4L9kq?edLX)Fm3&WolUNXQrSM=PdiTn
+`mDS-$5-FE_EqEyOz>{LJ<O)7c`*{yF*MhBt4)ngLc$q?&&!1uJtzl`7CBB4S)?WlKo05lq<yyPwu4+
+aDG#M17|b1aOF(@G7;(9Jz*oFV;%H;+COcs<zyRB}vPL#!_kx<K?-1wv7{rn0K)i6Z%4N36xC~ba@aL
+auJ}0Isy+1$)Cpd<qETCwEbv;v#9_dog$-E^`a6PeiZ|MT$uw(pGPw+$k8%F|3UG&Pc$Y2xc;JfhT<Z
+gl1_d5^vVJ(6fYhzPUPr3r-B=ta%WFbPt!oZt}VZEq85`V+(0H6F~AvD*axLmrpWPCPL3+^7%SunB~t
+mk6z#=etKg`X#uI`=>E&8jT?rz3os9!7iD`ZUs%qw<0&Y(lMqSK!4qmNtQ!45o;6<Kg|Hts+KU?dsc=
+2!6`69CjBOrv3Fhal}L{TUSZ8#CbsqMcgicl1R5io?H-z3sRJAZwbD5Bm%k@=3~@^nXQ(5|nvkEVj(>
+=bx|ThO-)!f$S761^$$@OuhY^yc=zX)`#n*MT>@nS(o#b6+*tN%F*YAMiVf5zTjoJr3?`q4668;%}gt
+?_15^ZF3O3(@N3zq^=J-mdN{6^i5HX(;Z}PS8eCu(Oy_i;a$l&+OwKJB+^tnk*4^ANaIV-aCRTgoXWF
+15?UE>s{9us%?A_({2R2mqbT6tpv4_U0bju=!2s2t&n#|W@rRkkAAw@v-=M|)F@b-87Qc8*;Cs*ciRb
+?vnt#*_X7tGGJ0KlW9J0)pLx#}?Hu`z=U@!~UBqGvQ3)CP-;=6R?p0wi-Laq}vctp$7y1sI!Y}+evN4
+3K_%#9$i=O&%%o2U2ry1PcMoN<0_FZ%IZ&-UOR*4&nlWo1{H|B>d;fFJzy2kO3oqegRrR5F~p5Kj3TM
+symQ8?9=p?+-8szMf!yT)+CrPTGC%rlczx4sqUNwe?m{3?n-D0rgY{Sl8#nD1_Txh8^9I%*>q$G4F2A
+4E2m&KbC_e&-!{B9FSEFu2UL8tOQxHKr~1$u?Lu1_@n|IkKK}zwc4}v{xvJ|=^7Ld{T7>#aMTu0j6fI
+iqvHDWRL2jTLaV&Cn?e2af1E%6Z?~VHWL5s_Hxv8HVE^MqK3VF&IqM5uJeVLcf`UP6`vqbk0mC>>f;d
+Hj&@Pxqp~T)pg?`gQQ*V>J8B*xY5QMTlR^Gdfh&>uc$US1-8<gPpw3Tnyes-P@x>siqaIfn`=*~FI@?
+CUgGt&9{4x7<T(_La^i>`M{V!Xc;Mc=W|(7Rp~zpGH&evov}4}kf*zLf1v!U(!++--hi*ObY3PEU@#4
+LP*852WvzhY_}?0djn&AMJ%J@ZAVTZF~Kpg%<aiKC(WKt`3A+M%m!`gnW!`GbPDu1wKt*v(zSs<8Oe<
+ejHmptFa01?VQ5kz;(OXinkH@V@NbTZg+-MQ=NF@6SuGvfsb=f?8r->e|nMIU;N^=4<iSc&3^98#<xv
+Xg}V=Mw)&<y>NdTqwlQhY{k^rH-5Kz`t^MrIfN#+k|IA)AK}WA&Bjv}(PEYybAd}~DbP2JOa7(x)0C|
+$;bHd=t1&umrS;t}VG0=CsOK+wy#N7v03~fUZkv_%OX}u?2YDebF2pu#hZy8YNFSEThR)JX}$2|nAiS
+pKMY&%Q~<{l~^1D;<pZ(k56E?Ll7^6SBn_rm1w4bl)9c)u7ebbEg;fN#+kY2EGkp?<<-Fh8#~gN8YJI
+KmOyg4U8jWT;)vjOCr(vAF^mgr)ZN$+f}=D-kWrrSJ%@(v+kMR6*-QKM320(z~ajL@dHeSvskuta4{{
+`8hkS4$RX+cCgTqc|xF8e?C~RHSB2Qr|qDWX6?s`RQIOI`lS5Cw0^6e>wlc^mF@eb3qRSrzrW}UNQ%G
+|Nx~3_pcINDD2!}|4+cSSpA14!IEhdw{7s5tjO?ZCecBbWlMu7FXl9E1o*{eb7^U`F@%AT1y^GY}ma5
+w2u0D*tiuM^D>08KPgR~g-JBjY3K>RH$x~nN<Z&j&eN2i<BgR$?`y3?IWzTKCKcO}sD4L-?u7rEMiZ~
+7iSyK}k8J<+;ZLk!%1Z&rJ|0r9r7+s(4~yw`0Ldu<%t^PC$j-q3ZF{i;-z!CnRSN^id$r&@Rm+W$#^t
+Jj-jly6ZKtu5^TRL7Mq&#dFxTvA^HRV$g~Pex<L<nZJ^fe+I>j165;W9+$00M~!wLcfK~KLSW&$BM9O
+UuU(F)(`m6n1C-1R*dqiI|9Dm($DPZR~Uw^!?f82yHOCQok))|gFsmx&fyZGby{e(4IsvJhtqsI;<#%
+dN_dFfG?#kDc=EF&+UC`O$Tb{_2Y4xa1<HzsSlQs7dzC`npHBxkWJSV0*JGn8uO!w%2cz`juzlmt$Y8
+J1RPuxG*E#QyXPE9X4fdq|wHSGDNAiidc7O%e=tb79C3_~D^bRkoQbO$P(5D27Tm4Aa)zoQ7Jt$I>4g
+FPnIHB<Jsqt`lUO)~4V)xD;6BJxZJ4snJ_U-NGQX@QV`LL>itREh)kdslPKE(HUl&!SPz3IG`Pvdse%
+@VM|Bh#aUo-)}T^c5*;?~Ii!pxL%3fe@pHK}9d`ASrNbBxJnx_3S&3O=lUwoSr=cuOP>&WvJLvgY{#w
+qREXW;TE&-^VRO>!)<LgJD&21NE{fbuZL(gPwKj8nJZgHr2y`5qYe`p<iS8p=7qI`qijzof}4keYx+D
+WiL+*eW@fFDY**mn_H0XcNx-M7=|QLfskpjckh2#MRej+MUh>qszQo5J-^{aZM9M|m!kfEIJge-8-BO
+?E&p1OYPnWq)oM;2d!GFCT+^9|?_$uk^d`btBzH(XZ(K#6E^&<zxiYTb@Dx<b`Q{aoQ)_8tM7=lBJ7f
+=(6-MpHF?-(?@v!alu%N|#zVmUvb!ZV>Q+{RfvQZ?eZic_+JRLwqS7UcE&1=E1?<o21ZgI@`Ne%Dcc?
+I(e+9VOuy;iO$A=Kgwi;`3lUlg3p`U2B8Ck*cEM=Z!nV-EAaIF$e<_Z50*DT%D|6x+>i+w+_Ow&DWhA
+TBu&<5<57MqK@?>0{Feen_x6*En}}5Rj>wY_r~^>7zl=}GABDTd3)B&geWgesG@5C9)@#8OzL4KpVJ7
+O&6i3jk7&TV>$Mn0oz(e@n<;gHCuv;SstR3MNjE?gb4UkjCIJFzkgbTjdzcCe0a`k~Pf-&1uHq6&o5~
+?J9v<y@U+*9&)CBy540833L^e3KEsDX#j>sTO&|6i`gM$EvDKHML8-|r2DrpBd#oApT#H;CRlR~dm(=
+={St+gA_Fa#Ow@p!`ggm5JI7?^>n03PhWN@Gn0CAlthS<A7Z9Sm{0k7tlp3$S|d4@<&oc)svx>G*l}J
+QUF2OM+?Mz|IEf={5MteI>jzWhTkXqvqf)(HQpX{bQjz-E;fk@Ex0KHkU&6x(3wgRXZqg?C&@G`~Yg`
+%1a}PPUJ$y$!*n}yAs)l>!No{h0aw`>QrnmUfcOs%UK@x{`NRw6MXfnaXJ(y04>AN6rBwAy)6s}jY5W
+sKpoRVn3Q&a2iQ|PQuUMQ2Sl;%LhoN+tCI<!a;Oh7o`*o=)cQg3Xn1ih;z=vZ;kJhGK=RV%w86&vYDR
+jM)1ro)a`N#ajofF-!$fNkC}R#z1H|z$``q=^nWKWH6MDAS<S`$N)95O#PMFDQRf(7BAD9v^PPq6FfY
+s$0*JZLHn`FHAzlg1V?%Kb?tM6R*V}u1!1ipooB#KZ7vIUsmLRbi~C-%1BD+c#m+7@t8Z`qAK<reRZK
+j=NgW(yS4?VN8n&uyo})ZX5<L79D28~JXPL-!`PEw0>$)<bX6i+JxP$)b1FHr;ii^6!a(Zh&ZqQPiF!
++_gO3aV3oJF)9VU34+*OC{Eww-nN5Vv>0Q1hL4DL2)4_(C;Oz*?e-M5m#|ZG-_VB0sJ+YOhX^a&BT5k
+eCc;|5ko+5jrTrqpx=+d{warEN5@9)_TgIol+Q)VVi1|v&ze8CGq^|0+qby*DSzjEi80}Yf1$=8;Kf9
+|PX?;&k>T9G0OPx)2eEGupv}a#Kn?CL3g5C)ryWI!XdZ<;*cGD{K4>5%cHiCOeU^%1eUAH8%S4oCGvf
+NMb`N8L1&;}Wwq1(nz3t%!ah>sjDmQ)6l<7z}WNuL=-0okS3dBP&4vCXWaIZTmW5EFa87#M3n40cFHw
+YGpb9mM5+fV?Bik>F80N50f2PghcmSrO8}ds^BFd-UxURLSdo)i?XhcFB{3H00@+0&ooMvsSW<XTebn
+Ly~n86<echFrus%Z{?4L>aWQ8l?GhIR2u?IswmiE$~BrBH9<@Osc@0!;^G;ZH~}-pFuatmj;|Vi=ru;
+g<m`%tPb<hCcdL=-FuVtcK0i&Hy*_csYXW#@K<>ObX5{l;i6RKao~aG%BqTwP)Vx20sp@d>T)Q>N_~0
+m|4*i;h_FiK|SFZ~|E$8`0!#0d}yyL}c?gtzWKkiC(4QnLOBD5<G@d^`dOeO3qRqPdI3oJH@<?NP}3!
+LVqIQPCNJY)1xE!O4<VLCZMMF-2=G@!L$-|=zDE|y0+OFTl+fISA6wgsyndOHN*yz-NANM0wH3f<$Y<
+eW!X9-maN)g-5Dxm+-j6I_gW?hf4(0#CwYO}aDeEQYzQ1bC4ky6o+FU5Z@XK=K2Te437QGh5DRrBXR{
+56unFCc`C{hInyDJM}SlAv`Fjz$*uMM?_E_9GomV&ocvq{UXu=zL%0f5%JoNWowLWoP<JO%a?w_FQ%Y
+;ISmW=qq}~yMtqJV#$)0`9_<|{r4Ei>Lq>SLm7*&xk5Fy{?}bZr;s#yV%o1c&zzE+{Nyuy3lNo_hWf<
+|#acvoCjz%rYE7OSh)YKXtBDolY%25Tb<Z_Cz!aek^=mMO{jk$BCs{=td*UB~0FyTs}i|<Uq6+Zn`kA
+h{&)_O+qRWqJC?PppJ<}p#yk$j~9JK_}M<XZ`{LM3%mYWo;m7HvF@{6l8iu!vQkK#J$XtxSo!i2MOsW
+S>e0Uz<RYJOTC8@JhfGV%}v(L?7<DE<c%h7LqtqebPd7VQlbYi^~+0@k?)3&uHyQ;UqwsU{4;<6t%&~
+kELm-x`gEXB3yZe_35zT=Y0DTr|~U%NTQb%**Y8QteFCuDd#J0vuciVIpAp|`7ARJz0+Wv=>Z5EZO<1
+6MNE^qbPG8z1@7eIGbg>e@G4-J>p7eQZ@w$2TC^B&h-(aCjvBsweYp{gVbH&2&xA!gH$9%($=Slz+IK
+M)!d$GnCbd$BDn>|&Z(=!gl7VpxD4!fBMODSc9Z_g={9rs;^=4Tlq6{3M!kfW%&1d<}+QLkp5Y)cq1a
+$YGvs=)>DKgUTSf7nGPa>hatcMpHigq?Ken<(Xb1KOM!qVB5Ssk|6)LF*k13i{_#gYz}zW~z7pxmDZM
+xXC(Y|19Xfyr%1LOmz3=4l{aO+`6KyAKcP&(S!N_XC|BlAlIed^>(1$GuU`cdDlU^+9^)<GKH5@1y<i
+Jx_0C*>8I@ZT8`X|8BGKSZCL${;x6Xo8kDslK=f141&~eUtalNzvUaQiaspAX6bLwA^Yv#*2`B&?*F&
+FeL{*qy{|9J#OQ_yDFplGI9@c~33&<i77xXDVKy+?0Th_M5gD?}zDM9&S}6NHhQEml$@dj7@m3#t>!u
+;mj@WSgT}n=O4F%{ui*Q3}alEg(K{{eXb>HhTL6Kb+4tv)+Hn_TH2J`)5>^+bNO!p=B>4@(Fa1Ol(24
+_2rMd3YxxNQi{cJR5uzzwW!m~oeIh~DLhU4P+6sF1(xsBrnr9ptTASCzlC0)Lo8|N3f9JFu5Ug^G4Q$
+-#4u`%FJTszKuGXRx62wpjB?mq3KHI<!9a*Y5MzKU6lcXXqQR_~dS8ej3x0yTrb_mky9m7piPgDb_yY
+m&PRikDCA=?{Ym`OcNv0bqjaF=tM1%-_;?@Knd(zV;CE<y-2}*K!)_JcII~X{pLXWM^3FyT61$Rbrtw
+#7sKe)_`H~jNi6t>8Y*|2w3S9SD7pZe?R=bUzfZM)AB5h=s=vNr-+I4*UwOm6^?m`r@`iou{Q`dF4g1
+#n1^nF`_A|4NfsezE@!}jVFovqpK?!l2W;!H(sD0@gW-r5ypnKx^a(qQ>7E^0r1WIS+!2lg?z;w_g8A
+Dxt$xC@XBG<V!qB~2|yps)T-ZnjHxl5AV;p>aNXH?V-y5IP#DCRCCd3!tL2^`jQTjFPT7j+xr$}&mfw
+m2=X<9T*~Ov)vQ2|p3r-6fob{L+!Ho?2+h87VwqN)%@}$`Qt9QM=gw{9KJ@@mQ2x*_ro+N=|X686JFi
+=-396bodxU3?CY=?7|R72ymc7a(Nm4Sr5COM;H4fBY2<Rv3LMqOmptL*~EzSFuMAzF6TN<sOiG=INFW
+vc)x%^6?w1VHfyL*4&h$gJC<-2nw6}W^QT$IA0+nv+LX&w-;-4OLSoN+BxQ($4Drgdgos?xi6uC{F>>
+=*X$|<E5Nj5aX+1=6W|L(V<aRNsd~oXero_V1SIwTkn3Q=r0+oI1r;9?_2&+D<<3k{gvnvzM35x=CUG
+BZ7l(ZQ2o>xDa0y@m+ny<q0#gAqIPxlZoZ~2NJ(`s^P!BBi_JX%mwMaM@_z$I<E4Esz9gp9OxKAa;bf
+;CI_hX>Vj&;Xy{7XalNyoE+Y$z99VTkK{qs23{5p?zpL2!0%OZxNCQ)F%;nNm(A(@28|^G~Jfb*NU1z
+OFwUIcrVB!8?!5e!lalK;N|c->CrOytf;nPm6HTtUnQ&$C_=ms_Up;j1FBw5jkrb1`Yj<9`v~zy&$te
+qRwNUj<h#E?cdU~kYSuHflVWrfsOv8%2mYi_<yq*TJ9`NJ&jOMEcboe~B(iPn&rk$|F!arMAR!6?ag>
+4}6oU3yfe8Lh3H2C%%R8lS78$wEdf6+1Z&n%-?@oPl{}lPAHKf1C$+tTjz`gfi10pE6g9<ACIQS2O_k
+Zl12WU@K<-}fGB%_^`0HJ%53H{!%Wf0zP2kv<2oi{^wk{XKb;wV_M7YuP?hf~Cxq=vtB)l*_uPuX7D9
+wdINnLuxL2l*a;vz?h?y9Cs>zx;<1>g>VZ(8>LC2dqXb(K)kj?^KnevF5@4D@X0MesH?L-+A4iak{|Y
+dELKvy8N;`-LGBy&!CibyZDpSeE@&wb-(L$9d-W1%K$zMCFCKsa#pRrZwFQ6)3FVu?8l~SOnyUdDwqU
+%=ODa!7myIQAJS;&4{}pa)w)jd^^;@@Wrv<~O*fo!Za%-c&$!vZ#TlOK5Eh2BZ`Mfzt*X6&r%zfdD}4
+`^+x6YRQ8ItI$^JON-k2+GA#ZvrUP)8qp=VsTlWOTiJ!A2<^G@bZj5+1@`R;#ENp^v&$P2pw7Ph~sr^
+J6=49s?#3GZ^M&A@x+kXbgAqN3E!C1<QBvpLNYpkaw-B*R`(7LOf)K%3RTAvX`NQY2r@xb$ifB`P-0#
+f2Wc{C){zC>TzsAiOv;GXl(FwD*WZAtwm~XQq};ZSmGn3Hac#IaU!OlWGsBO>shQ{n<6SM;SnTPGwpN
+DYXbNE1^n?#;TjM{!yFcpIPss@jh1v7$)F_b6R0@pH|sT>S~YcbmrmkLd`p}tkU-r%YJzF?TzGUIHA>
+(!Kx<#gLRh$Oo~kUS`P&xe2F4byylYw8oHEbmR3fVl7ev-d*X|J`NWtW)#Hsg9v^MfP159Htq&A-avJ
+?XI%Y##f)D4AiFk*i4XYRAttrNYDqiwqD(Jop$0cOE#l7|;Bb}b;>E~q=1eX4dcYiZ=-QKkgin5J%ix
+#zSCdYTo_t&xs|8$YhvI&1$;0q;OkiakuCcmv*h3+Z-%?)e@7k(%GiFc6z0pF7=(D(F-c#l0vXgl~#2
+e8GrG5M}r#2=|3+eKTfxH}a1Jw^lHeM*$Psl?>2&$nyVqQ8^K_h=!>yA$m#LxsNm(=KC+?Rvc1_CWNb
+lHjf__}19nL+bY!jV&aFk~gh7+a(u3aF0i~JtgSw+xGAo+)E`tDq2*#13*3#mH89jtKXFT=NRv+Y5)h
+=6+fx$hc<uqI<*E|baBI9&1N&l9=73SVfZ_X3VdMie%71iIC|#H+b#v*dXgYtZ0M6Pm9z^}p(>~Df#L
+j)2dmo*sMThRKOL<8y2T&u5cts+f3!nj-{Q{;4sgEjy)>R9bH;65#sLvvFo>b~zs$W?v!iCWEqu?f@I
+Bwz<m9SzK^7uN<Zwq0A_xRR=+_@mciZlEd)t0%pE_SvuT^RmJOoK|jxocS{Bn^jjJ&~*psc0WZb|~zw
+^r$K_F@;kNIqIT*ELxezKNJnpLDvOMh5fvy9PMQ-EsR#plT|AU}C%GZFbFfsz+WiwRxYF7c!2o{l=lw
+n^JdkrPJOUQ=TXP5|HPf0HEk{^At{ZXUiTp;*1f3u}C0zWyor~!6m{6L&dkwOv%a#f=Kkv7yNjeO$U6
+@R(S`gDvC70I?H1zBV?_>rLpCWR+C+2B=zP;!Bh2%X~So1(fK#^7URcDzD@~7qw3pw1LEC+FnaC!r?d
+qg*ZLuIf8bfJcaR_}BhrT8nm0x6-(2eTPAUp5tV?zYe9Wk2x153MwaOr7hdU5>(`;bNlw1x}nxw`>iI
+X-)ng$N%wXLxl0xuP~Nbhs&GR1vo!;1X80x^RjLSgeepV^`sH`Qw#`2FHb1I@`c@<@7`@Y(2AuCh?lh
+H;zW?KR{#1HAd~ahQQvrPb1R$yAq<$wg*QA4bhxB$>LfM9)crKj%ilK^Lk{3D#O`OKES+pmz4Tj60(Q
+oIaF0kz`5|&U|HPt4upZ7CtwRq?jK`Rp5iDSnfT$vS5GaGl8dGbwkACjuTFg!UL}Ab#7@rH?9K?n&kz
+jxlF~cme)<^d8}M_+lhadGG))e@by{ErB^P2kTm6!5RvK$r2hV)t$1Q}#WRH|Mf8?%hzO<Tn=~-0uRD
+4vJ~Y<WMOk3|l5-lU#u(LLHDFFgba>bhHx4@;zf#)!pQ~1JKT1d95Wc?|jmc9!Iggt7T;q`oHwWDQ)N
+J-!q61+0Kwi4%RMF48Y&!p1aN-?Z#B{ypy**!-nuDIFdV3T3DiiNFg54Iztx@>-2<l7X0C@w=?(1seH
+8bYvgH^VsJ2g8T3OjM_qpKmrb3|V+rWq@*qF7LF#F27_+$-pe`&$Mym-p;;{B~!P(OI5w{OTDJa$}r#
+$8LU~Oeev%lPOg~=UuW;yO3rNmb=~ID4g3N5g^*-z(UZ|MML)P4zSckG-P(S=}z==$8bFQkVWF?ZW5)
+L2aVbf-)a!KU3J3G(6|9t;#9s%IHBKcJSB7;SWoA<xssF1w%mhJ|9*)#dU8#%eUwTOaKa?$t%3+`g5N
+WQ0ba_(5G}^pUgWmJks(8-649RuM^eb8CNBn6n5;VsYLM%fD8H8NguA(a9=N8DPfP~zHAM|@db!47lR
+rZ4g+od(F>@)!U|rj!4vq!xC|3VG*$ytCGR!|OXWVj6?OUug10cFB)0Aqv3OvW%#hPrp8Le)M@=%Q(=
+$~*orqj(R6yIt}u|Wo54X=@-*rJ%3+C2xLC*fb>lk!H$T=p$lG=|`oq*AGFS{I!eg49B8eV}JBQ*xhI
+S0;6WYqgmMqi!@90W3SP{7d%GHj-GpRC}~Ak)V5x3c@BP#^*PI+^OfyA~emVI?7LpE0nRGyPiS}d`1A
+#Cr_BaP#3Z#9*oPYDS94=@M<?f@7y#tOX1TS3?C%+SpG5mx+u0I{^BckuIAhKvdG*~-*Nfh-~P69_Af
+h2!_sG8pp@8W!}R!*iq-$vqTk@z-z@n3^cRXEX<~mr5R#y29KmrEMF<9^Xoe&yVh3~-LH@J|CH{zxCO
+e5ojuO~o_A7N%$L=Kli1QPl(Jk;%tGknC<mWTd;Nn12JDWcgK<T4Mct>Jn{An4Z4}u-j$4X58!Cjx}w
+DAXY<$qO#LVlXfVERZ@kRL`~PzQ-mKP?g@aTLWIS4jSfB1Z%w|HL8i_}HiTAj%#89YUtaCoq6~YEP)o
+P}+Ut-%g|z<^#{&e;@ynO=9Wx&RT_;{D8_vekT0-)AYkmqkcqBw(z@*6JO~k4{n{vo!gy8*E-LBYcz<
+QeY+>RC17<7l62O$zA0&c{X9CgB0(H<KK#bJi*E<~wxIn*(HZ!oq_bIbg6VvjW?%?Mv|M}{M}ygy@wM
+-Z^KILX@!nFb%kT^MetfN==+;+4_o3NYV0%VuqaLB#%Bry6=yiMDx4V|j$v}d6OC*0Ivd3#?OHuFk2R
+^=^llgYQZwr1?cm{qiBF^}uyyeI72LIi31C+}#;3N(=b&i8aI@PD=%v>&D$RrBUiFm(oQkFAH+bT6L+
+0iJ!Woncjm0~|b0VWIoDZc=Ju?VD58WohB9p*^EY2LBc237E&*+dqP*GQpG2qmO&#m!(Y6$n?~YD~G>
+RbI^jfJlf5QTHC@FVTrEA)KM01evjiKQD{E!xr$Qnr?VegOj<~S9%Mj!g*#-i~_|eFmAv?Wqi~1C~^w
+3;*R!<l&h|vZ3trz%h_|ylP)mJ1d|Xxn0*TMww^qukSRIy<nY85U>H}GN|cFiI#$$%kneuJdV0E=jhA
+kOjk{@|YL1j}uyv5=snn~{<d<hDyZ2?;m<iBPE4-1&{fW~Fh3^>nTLA_luFjj)z7}A7DZU8*T;>Y=to
+Xt(A;sv793QU_(3v|aB`kNjSX~1jtuSYG4LOdLdE@1Bz?ZTP_OC}Ch@1}M`PPN9S==${p|RaNtSI%Z8
+p%{vK<d>&5#yMo(jWolG2UZn8r2b}-i7Q`H#po@*Z!hAkyC=fNt~<j;$mfijOs~S6#^*j-Oa!JP;mrM
+J+o|MoT?4F=i3#-MKPp?zT$6I27Bg|yK-hkv)n@v7Ok2;4ES^bqNjT`X|z|7j0)js9BaZxug;A7=&VK
+@ZfjGekYiKl8!{3JJBv$wit;>vo)`0UDuDPZwN6UxK$LN!xNB)m4!9HRS>+`}3>ES;yYx?poiKO*+-W
+XqEN9)PQ<~R!7*$fhND)1@JXgN+A+|j7fWBiddbwO(<KCa|A<UZ;_L|wY$B`*Kot$1KYfk^?F?%~=CB
+^y@is0EJ3$IRbGpzA1$~%d7uk~*0^qu$hvB~}~_P>5`p8v`5-~8kc$9~uFM^NxF85E~>%tez7f};q9Q
+WS>c1WjQyN#PhqQ3OGw42d#7&Br6irw9`{N+J*8oR9v^A;*XuvWe7ZY{Bl?cJIg><I?^r;BkmFeuk1^
+#o>~&<XDM>j|S=8!J%Kq5`3KE?&Egnm3)RCWPhdQ6MqI5Fxl~YKNyLBg+I~k-4PO>i3$5Z^wX=DQ-^c
+LK5_f~`WgH<CGqJ5Jlezaqdx}550UOHKm2xj6c+rggG`Tnd^`R&vi&;TGY))taHDxMctL~pG-=uUhAe
+-cviup@?*1T(=!)wfqT7Rhg6A#t@6QYsOFOvNp}qS9?EZ*-g9IX<xF=XvDU!aJHvT#&)YsUmE+9s1y3
+yIKIop95_v1XiPV@QrIOnzk#@l@B?=NEwzHR)rO_zQgYryG$a9gUtF&dC|()hUou_bp-b9h_wsLaeeZ
+`pkwwqLHJ-NZ$=%2g`A1w9zYze%#~DJ9_En5%d6Hah<-_xv^Wj6DUy9L1*rm|AcN^W5JiyF$ygeq2W+
+$3iy4SM80VL-klYH#f^`=;}z@Gz4Uh@)?Wa81JZMb^z>Zn@DA-!kML4$cf<rH*U?8K9Uo(lM`X7k)qU
+Y{L>vXc?IE>*0^ZBW*E1m*W|JSSjpz2V4W6XnxOLGKAl)ZOSpVO_hch)zM{fJc)_1plJqU{CazBebbQ
+9pKu{6<i3G4hWRjY12Tp~ZfG6H_wq5Yfx#PTe;<Iyl>k#O@c>Uv~Z|vzovZTu2lm0=*Cn8G-fU_S)3v
+=sL8y}fBrihDXY&qFBF?Ti`o+Q+tdvsG+W3B64s3K!0OM*m%&PHvwlK}+sz;42dH*Nj=KKK03W`F{ps
+P=ccXLFIpR+Y6tdtbfX^6O0iRT)9P*X<{O5%`vSo`WmSGOx&gAt)K^V@|Nc<A$+1436D&+Wn*1LuBW7
+DIw!BLOZI0-`QwA6jV4dUm**Jp>!yS3xwX1ZFbm;09}%H<W_1rS#NacRdd4?MhsOAo|Zx#>5AwsGSCO
+Nh=OuT5PWmRr`cH{<jrZ(T_CC9x|XfST+cOaDY$XT%=G#sp4QA^cae3#t>dr2aNF=Hg{m718B;l(f?&
+a1LvzDo@}%q;^mt}@m!-wQ=edg6RuKxSdEmOCIMr2=Hz0!v;T~2+)#cSSkKsU;(d+yK=dF>3GGFF&QX
+6})DWaIyhQDq0odhAnP+m)<zwHvxp8lPGLvE0tuGJZ;<@8+Cb6B1h<30bI8K6hdeCd80`S4W}<e+bdP
+jdVEozKHBPM%i%&<<stKR({*pmbjk{fDvp|BL7OExiBN=lCw#zr#|7fngXqWJ)j^gPEg`fg<tUdlCpr
+FeLNyT<{kKxZUez%#pY~M)uIhKsh4$urK_O7D4jQ__*ZP;^&oWho|~9fMWUKuae@JId{ycppV%T2z;=
+)W9Bt^@X*~e9{Z<9vVlSW!ZRkH!Fk0eBb>#@LdW2X^f;3IDBBg}F&Xa|Q1NlV*oXQS_-D|?XB>DEf93
++k2Mva?!^`h$X7Irt;lEcyh7Zq3{pJ}>B}>d5LAC;Y+YD$MgGx2XKdIcoUsUc&;m=-iXFcV&oUrWe?j
+^XlnM{|S>@~4WJa@*|$G-PIoFQ;{!}EK0S>KYxw@*+WNo-E|Zxf8pm!@~%E4NHO0v;!CR-`Yv&Lf@ab
+RL|c%ocB-p8Rb;AQaxp`e~~dSX39vH*j%W)UV3j?y<0O<PC&yy$CvC?9f$LWcCMkY&yapSa79BfVVsM
+-HpP@#<`Ji3`xiAlrXzTfnK^B!D)@y?@#6%ZO(tY(y#dk;4c#p-;X2xJdezW%P-v(){)}AM1h6v<n=s
+#X{k{DjS4aY1`STkJ_`u4omJK1M{)`&&5&oNv~#~XjqvyRExo2OI(3VywTieT=zXS^sLjx5VQnTCP5#
+jXFj$ki_5gWn?Cm4&53{%RUYzbAnVfTQ;7dNJym9Qa^}gi_!h!SZxRbvohQFv12VBli3w%pZ19AnPh>
+(EezU>PEH^3nn51pt!Mwk(-2!|7EB2K#DF6n%dLT2hitQCRcHaBObleNZ#RQF}q+t{xc)l!v?SfwX%%
+KH9HVo+DA!J0<q?f&334ZSap74Z`&0`?Ospy^VOOqb*5vZ2&y%3k4!(%XD_ZMTYf$ti+IVOL2WXq)9t
+rOY{5!(8BoH_`zEg2D2IRJITfEW3;J-sSZizn>q~#4a%s-aN>7d9i}lXGEZKr_NVeWc8;A2OEsmz~e=
+kTsvjV{d)B<KVphemb(mpP@oSrPWsF<+gtoM5qJ~=%NCctvN*qZf_ot#<>CXE$fFX4i=CITz2=NjgS)
+u2>P?+J&MI#uRIBCOKGr7L&VmsH>9sz&Pb{X$m!*~Y8*rYK$!GVKA{x?Lq8X*Uz-Hd9#=G8j#+O{AaC
+CnItNN{akRB6hZP%}nZ~IAjN~{gUS$Xkqv36M=9avw_^Tcz{o5J3&&3+5)@?y?1v-p>+z_z#6n-%iZx
+r!?nTt{Yv=mG3jJUX{|-Br<pMpO?6obX(lkf!bx5*Rf9&2$Xl&&72%I(R0*J}%`IC)MY5azSqEU}v~M
+&YxQ{fKN}x_YA=Jt)t>3x59(EkqNy+PXFvbOg=1T{biYf7S2}}eVBj*z1m7oO*;~Dluo-FUUvKU&}Un
+m7_RwsBx2-l8EI)*voOfJQC?K%5nb;YQlD;40q|ZA`&g<OV5cd1g7Y_g@wxY;Gs3m%gfseFSdAd`P_g
+i<E!~jk%$;84m7rTBO;8313>>cB1ovPmbjd=9w=TZKLwQ#r@!};H!x`5A<BVX@@3gHCY1^SAt?E%7rr
+EZ3K-T!0s%H1$dZQTonpGADZxJha_ftPn_Y=aYfoN;ZaO>RUlJDQYh16mv*6~@t-y8_=o40)Oop9a_`
+n`FPqm*hWh*a|9`Fi&T7LxWUfnV0eNNxe07xN&FgyJc=SLGL|NdR^@_p8$<D`sg|C(J>+b85LtM$wFv
+g73-Q-f5TGF(wmxJjPYtBC@O9qPvf5e|wC;6<V6^Nxb#`#P^SA!^8V<hE6wuazsb<svA@XBAbpn@86f
+SdMy`bc=HIz<QypA>Hs8EOeTsUWHhSYs=Vsk8J8MF!W(15a;e+yy|blm2bsvgiSaVeUD9ZH^qfvIUG)
+tRu$rnF)zdDEXmf(tJO$fJO{0V$c=22z#NF3I?LF_`y`X+jUMIc$w!BJIpUOr7T>;{PLn3-wP-d8`LN
+KN~y2)%St%O>oRY6-+T=Lud^)d({W~(uHKi90gQg1eV+#g8|2$N4dYy0|-;p8cA+q|#SU)VIx@@{_-_
+t`I2{>bAgt$tDZ$6U|Lf#4pW$o_%NV1(Eq;J-QY0DAxRmr(Qn)ir#Bq5t9e{|HgxpP|nqPVt$Pv4hKF
+;23j=-yO{p%%OjD=pf^t`i<l>)iM8h;^HIO1d~TxCMG|Hi_B3yxG$W1dK*&mK#a*}hy2rOyDxtXKO_G
+tF7uJXW6+~@7Do5;9z`a}XDam3m5Y9cEPpvudUQ@4)sw}cuR?s<BaX)0{0QZs@u5|Me#U<gpXd=*{EG
+c;;zH&R#XRWp4SjO#U-U@ae<=C45ak63?_=jL>Tuj`2Z^$`q;E;oMdcejqiorGB=QmD(06ZORFUk>$L
+r81Zh#`4+Z6Sxv@?dIm~cl`_Z^yj&}O=QL7>|ALU6C$>wv#0<{5C+Ci1IIb_ln_(<VGRWBvWLEG;`c+
+o6!rhQYaskIK8=fOlAje6l3{7fmK0`wH81$NgIJ;(qOc_{?Mbl)M;+;98@vzin%Ne;&XeAIN|5Jb*tw
+kpJX)0DpWS|H<<J{`f%t_&ok8l-*snz=P@ylJTCt3ac16sA){Q*XwU|)K1UDxpB5N!ZXc4j%_$Iv9Iy
+cM^z19bR@C>zBP}jmbiBX#ZUm-{wfOs)vW>1S9GNcr3lN{8GKCO4t?auYl3(U=F0bC%u?Jq@b0eI+kP
+#)6nS}84@Tz<t`8;JhFoY7hPhhE-Lp0GPhJa~@!|)~6zTH=B(JO)<p>PmHrN*`-5c8DUPKG}UVDYebQ
+MynHVRA?JLzelBkaR^yYpb{jwD=Tg&h2t;?FS2149#J($y>=>Wm>_`W!ogIrByTdOSK}3BYL08dP)*%
+(+LA(}ww7jnW29D~VK;r11cTf758d*$!6YPiLKK!Vj6`YQ;KTN+&`OB&e^!05L)_GMLojwXA#2hWZ|i
+fE6YID2p=K2n7u?xj|2Ef`^Zu?C*+MAd+mx^O<NbYrvhb#4k!uw~0j7Z3%vvucB%6hy+3+(o~1LR3cH
+!9!|gSxp@z0jwG-WRF*Sl`{6ZG(PDuj+LNrphPzE}qcG<m@l=k0QHf&S@{B&%pvJs5Bug{tR@^K!EU%
+F5zhdyh24gE=_ZwrvVa0SyZ3JYci{vWb20$wmBbMY5Cq3*n+NLmySp60oix$uPWnLJpP7qw9E1r*Rt3
+$<G`~qRmlg6%z;w=TZ6&hn^EwnP)C?($ck~yOYEoq>$vW(v8V9u@&gdeOF=6?cZfqz;v^T+&DYI*&pH
+|J;IWk5RbN62GFW8%$YAAeah!=8L9@hokuxX@~xEu2%|Xki5iX78~nIWzNwOgAUIxZL?U(tR)6DuGi=
+w39#qslpVswij4Q&Ai>|I)q+*r$0Ph0d!nmz3KuIt(2nYhw8vf>a{vgx)3V(!sxhXk36l3VxJs&N3|K
+G;<u|byr4FQp2G|<8gyn{H+eUusW!Qq#}^o1+ea0~4up698LPPlEgGx0+-ANRaeh`A5rJ6<+%gdLfQT
+q=kJO)@=+Kac?cz6c2p^V)KZOvl+ez*@@GQ$t4%32OyM|?(Q#)C5JTdAHlVhNv<%j(6dK#r+_<4Va`1
+>hM{BRe;5xhKX>ZHOHR8Gb4vR7phz3c6HT?}tDUfm<>D<EL%cO%_kKei_a-Kf*6NwWAEZiHsELRAT6D
+xct47O$fB98f6`W>v){LZGaB54R@J!WbsBQMR7Fap!A-j5cS+o>Ge#!N-G=&Ur(!R3C#@wA?}mIq{7G
+@rjPSHq#rk0!ZG2_|y@+HkXUAfz5aWYx$)xQdzMAB*~7EkNMhg{L`Dy49++7B+T|xCG)4EcsdT;)0IL
+`DW<FEE9yfQedA{{7=l+8sYcjgX6EfMm+_p?Q15|WuEO}dUFG<!P*KyLR3N8n8J*N?=ir&R!nT-G?g$
+BYDF}JuA{1lI<~}M*k;va~=hT?ItL<0lX$Q4I<f}07?3nQmxes%Jw<!s$ej@4rD^T{E2Iv24IQu_+9s
+dcW{oxw^7S__pXC?@K=!zcGfYBoYnj;6Yg|nk~b_cYF{2h7##k}|_tYwO$1(!mOPG9CD1ihot;xiNY8
+0A47%O~jpJa>#t(g)s5;sfQ9e+6stFa0;fN6h(<=Q|3jiTG&k-ElZV96{Nm-8elGjfeJVdf?lH`6N8!
+17VZI5ot}3W9LJ7G(Cd8$Gy<MV%Xm{*sKSvy^Vi_wcj_?>=17J38WRiwEO+%koG`uz`uoXmca4f5Zq-
+)aKL{GX)V_fj#<4xf>~c8u1Al|m!=s+7t$Tt9z{FpOaJuDm`AYn=*;=HZ7t*Blgk8tFXqW?-Tah(9&y
+l<xJFzi?;x|+|8UvE=d%BJ)xf{G>@VYnzYo3wx@)fHx9ID8RwDoPIP$pR#&IDk-69`3UROzX^u&1Y$d
+|SdEsw#+?|oqy$UY%m;(heNnA?}?AQKipT{*^o(--q;i#e+$VCI!p?nnWDmM<~t<VeKNXB*5+n^vdBy
+Jly9bA4-S{AYK?c#md1(ITVmB5`PIo_9Ak;zR$u&Cb1lYGU<tc=t{k(#vP)Yz<s&HVQJw?tCu~s@LA>
+*j)CH?CqAED9#!U9{BXd{6q;3djDL@<Xd0Nm$n$Q26$YJ&a8OpwdYNEq7X==<&C(FKlH`$zxTxy7pYV
+5VSLqAoZo@gc38R2Q@wfaB*-VnyudlpaH^cJm5j_7+ZV2PBD6Osh+g_dF_o3eC4|k0fwG4J*m=a6XR(
+J(A~$Jk`Ya`+C{QYie$=K(>LO9%U2Dx9J=Mi!;C)`T{<+wfZOLCs9D|QGS3l=dpU;Q>*79j!{LRM7)3
+Drsl>7SENB<`H^@k(BtE;3?nkE^PCP{{3V4Nah5+^Ab#W4cL5t4yP1VMjl$Kj9CeZd_1q}dmhXzU0c<
+k_K>g=dHE*CC|}9|aot&%+bDX-%?El?HQ2Im4f#N(?!|2uSwnl_Zb4%JdTeVX{Nw8D%~T(|=*d8S*gv
+`6uRqesoliTp9M6=k!HDEIzVq=%=$Y{?uC@nYi7`!-whL{SXo#y*Rs}&+{WsmwqZ(vf@bnrGFcqkmAF
+RBfo_wELKs>HznBS#fU8VS}y2?uh*Yed#!-;{<BPh>ahJcn{}AyPrqa5!Cw@zyf58`Us*Wt#fE2Ff_d
+v7yHUjTb#{^S>DyRz|2KgzcQqOo)*W#*gdM|u5m5Mkqu+4Xp9p;2bw2&(VGbJx?~Y;tcIsKWsMln{$5
+VV~=q&8~%mVf$Ijr-|dkA9dxVQ9MF=q(qM`3EM{P=*luQcS!9{RN9z<(%-iVf$}6_$kJ-4XcYZDk5n6
+qU{ljo*~la=k>saB8qDRcq+!jma})ovlf*u9g$gcIHWHAj`C4iZ0+~cy*fu0<fdg%dJ7Mpf4U&1Bp+u
+>TXZ29->$5-n*#Vu0``&pCo)&%H&PxLRYF(ZQ~%;1*8kG1msvmMt5%6xL}D-H(E__eSzIJXcP{f=ivz
+pwUMvJs#r5ZH!KYf;DTlMW(Vs&;Lz$tbZ79rJ_m^MFzsn?IXsmPr?kR}H`uK!aZkTd+%=-A4iYs(Z3O
+VV^8yPSw-dk-4jf{qhqj!bK2dXc*rvv*ePjzw-Q+Vt%*(B->F$-WCT>zWYVjB8xnK<0U@y?+_XX;!QP
+v&-Dp*^>XckeF(5tUgw9qWnp1G{%Fw=+CIpWB8<+8i03QSWV32dL<?h{bC>;c~!Ze-hAh7u=(nl6*n=
+J6SU(m6iA%!pGRBD&6S$JowUjI(%vU+f8vt1j_-;L=J<)hu}tsJ&QvxSzwI8<ZZuUan2XKDk5zb9hK?
+OqayxTP7FI6tS0Z!|eCgJ3Y`;G`Byh6_MtbF`1|3v7-j*rOdcOb!x<f%2*Fu$G^3aDOWQY23;`Ylg|}
+mvQEhgjHgY$!0}-7qk^5{IGgAq9$iKbq3LopZrG!o1alZ5s7Ub2;}Kpn&j?oS4ksiqUI8YT>d^2(zGk
+?0eF}QY4x+=x^`B@!{G8i=uK_{KQs3oN(h{unF843Z#@$0^>5}AY88PrD4Tw@?J&Os)WZOnbFa_-t%H
+6FzZ#QL<B_vSp3#e#qY(pN?MjEgr)mxN$M~O0!fL||=((F)$iIIJd(kA&;A(=wkPw$0`$YeT8IVkrbD
+3;gcMn<v;U|hZvv00+!*n|7mb6p0CdO_EXiI+1Z-yeFtKmh`F&!OfnPY4a5@n%2jhm~F$NL2wtnnU!u
+a+_xp%g$Hpp?ufwI#<HRV<72!t50g$6MJdJ$!Qk;*_;%mH{Q4T#Fwf`02hmWEBINzo<aH1`r#?T@71u
+@9YNLcdk!wcd3AQ${K9*UFEb;#R9W-rpYQQ`S}1n{oLk`AGuyo{-nNz1c#nccici@6f}J%9Y(WTosI0
+O)=ZsoF<CPPv53gBnwFYgh84onZRc!BXuS?t!Kf7@$){7(DPVdL-beB|5rA8biF<VCrhOiJL$^7b(W_
+$uh?D_4bz_8UAhhu%?TufrS6d=N<x&M-p#Pl9Sv=sYeY<KMD)-Z&$&k9@{zPjSKQN5he@ihXtRgRCi5
+<>6koS2nrf@IV3+Q>3G(9xA~p_$rXseqWRhGh}QqZpqgR5O?iL7XcKbe6pI?uko#UwoEl&TN_fEY>a@
+?N6#qq5X4mEd$HKgAt=5xWOl?MC?)&-|LGds0_$=qxmY+@YO@Ph2xNV#zpP{ww_>N&wM*~;4Ls2CP5J
+hY$_rc9thh9M6JwIF7xR>EO5H~Z)x{w|I6a_qmYQ*i7Bf@zkJ*FM>O@fdwxSsKmO^v$|9PeDH4NebVp
+4%P4D<=XTStb(&!GP_7@cK)4HM@{S{`8n$(@9X4nT`Acy1?@=56I0OTN;)X}1Qj34@WOUe#$h)?^<QN
+4p6q;ubWC!-|#k$e9P;oPwf@e!zEm_xI4=dAm0^si<i9c27dT)QK?9c96vBH$gzk<`Izk4c*7!Do-EC
+G<0x^ON@>k)s6an9o5SjWx&Yq|YLU9O{STGavP>;%{dmN#y~Z(B&I+x(3n3(B%}}*rO*Ub1V6F`Z2oC
+uP&<#k01Lv4&4Ot3lTZ$S=mZ<ZiuUSXTfpANawx+mvuEwS1;Y0bO!vI`@>G3YTEU35Y6VclP~vE-E$P
+v>cTPOQv5PuL*U}$>^~6De}DGl<iPJc{R;%7-CyPDu2&ra0UKw`s~#~YmJgb3)fMVtb~pYmPx-07)`{
+0m6wxo2nouwI&C7i2lo&OMxmH??W?29nm)?AJ!0f6i2&Z>F2n$wwv)Jgge-TY#l^QyOi%0V&V3QgjhJ
+qNEQ`9$;pd@eh4frQ1ov+@M%qHh*rBie-b%1+I;rivNvv*ncd+bR)F>^GPJdGpbd}Ou@=grgC>Lmd)C
+j_y$lSWY>2`mlrCDa<!ORh#2yYqrPBSL<^vFT>I{CbYJY=3jab4cBuV_K|W1Yi{27_OVM?HioqI_c~n
+4xW0wzI%k=hXtm?;w5k6%X*Eh>8To{No!of=N9SinZg4~aSP`)L7aR09MxHO^XBSujg-+P!P~F%tx=;
+<djt~Jt^OnE2HJ`uH$_T>ypw{f0bTOEy=_76;6c75-T?6`NwvPN!qiAprv}pEsGB_=>?MQO!PBX`zlx
+%F=1bS6p+o`ejX1SqfM$c=s0ws1Ws-AAZw{zR0aJ}I#&EF<5N{u<&QX`7-rp7S^+>TAS@C;r1G*}oaq
+8ubeBs+5YEI#k3^y;*;u68qG0>@Z`%d!=&fm|VB-9%lb|HxpsN>EYbw`27-X0##Fbtc!2rlw%i#8nGd
+xw@IXg&Mg>?7mE5$0naQnR^-8cf6~1y8i$n|eM2?x>sz8I&!2D9EksgHSK0)j20p9M^Dyd_zEGsIO)C
+=a2#Lk7EYcjCmE9NS=ozL+zfi(DJQ;Cm=lEXI=P$trXV8birNqH5B&)%N<NjI)9US{vorbD{;HQkt$@
+!PS$#<>E|Jz0%+Y)Y-cV}N6Z;dwCTp&QrUQG@1NwGzd|dH;8YCK8|NtqKrcycN38X*1Iwx~-l{(vP<g
+6H^VP5kEk>lDbrQs|)|I5r_nHh7aPBlaxos{;a|mDsuU5F$n?ZvQfd-8Px<w2QJx<T_+CK$#xqujig;
+>@;(PU`e6RK>=T{kY>c#-5#2Q<%sJ=D#SM9UOhr0#y$oYC~$fD$&|u14gE3gt;5w1kH)@u^Zxj}Bt$e
+j#rc+A08wQr>MPhBMvnsG_L`(n-OpAz*5Cx_3(&+T@tUlhlV{oVP{h(N4H%lu_5Xma3=$obTFldb*st
+P7!j?lVsrs*;+{@eCVeeKeJ$wMLmTqHfyk8?StW2LWI5?SS~||rUQzI=u`R<tIyr#k|HTxX!t29mpZC
+rPUOW?KuB?91n=c}0VR%hUay4{FA121l=5os069>W<HiQ<Ja6%1B*E>1b<h~Gb{qTBFym0~CMMoZsk9
+i{x`FH}ft}x=?*~?H+8sdV*QP^AM%O%(HEV;`4Yq#=Cf|2FOk%d87U*}_AvZZQ!hV395zcmF1LjY2kY
+<Jhm|MNyO?q{M?jfpAmtu{M=*D$vWZS%P<FlEZbdg2_@#%>}y%}vQ`gXCh%Wjs|;RaZvs7y=}TUO^Il
+AigvMbNr{Ss<u2v@1_{L=W#6WR(sM(;X`E9-9@oKR#MDRKh2)EcBXzmWxld*m*TORu|26?pOO7YxDFk
+nxNP&eh>Y3>hfPU{Sc@6@Amr*SN*WhcTp)ELyv$I%^)O65Hvy36n!)~At;7WC<em>PGB@f?k4J|qs(y
+ZQ`l1c8s|qWsK}3U8MOEm%8<X(^pO+5KAQ9?{cBGCTw*l)h<7qaVE+JH`6u}Qk=cTaBlu6|hkVyD!V)
+>Un#lMgr<MPT{8f&D&W~c3{Br?#acGIrA8571sU4=pAAQjjJ5IB2#6HR_2>F@o^ART9&v7Wnd<Lth$&
+uyQ?`6NiFGW4%-?ucGA7Iga16U5%ZN;1DpoSd?{K?_<?b@|Xlx#oIbpdvxN&F-VbUhH+*C>!|`bd>`%
+%WSjRr(fsdU0IhOC)d<EB|5M+3WWxzq=XD?<32;O)N8hA7i#&oS%%l{JnT(I5Hn|7~G#p^E<%WPhoz$
+qOUmyv;4%<kLO_j6~Gd|04(zWSi8^B&Ukq`sksp}KpHcrQsUskr$Pj;Q0CkY3{qC%wS_BId`_$~SM#M
+bcW(F?9n+Ww?m1wIt(Pb19q9mbAr*yALGoQ7v(@9aU$5Al6IoMcVMN}bK|$}ir+SMe;YH8PTta5Xn09
+ZM(4cVz6p59S(`1&K+JQ0juwLEO70MH)s;7(B;LGgaLAUDlbF#FjDo^mPaZ`4!y126Zm;}7b(yYXZu#
+Gna=jEye@SN?ReFQIW3_*#$Pf{tK26S_lRjm@hDb2>m2-A1^Ce(-qFqo7ET@R6Wm*3vCI<+jGFi%SJm
+E@JCxp$E;TrL!W*iH%)LMG2a`)5xq#TC44W(PFoZYs``GL|sEyLpz4zshO-!?Xc#wBde-0TeTQD=tiF
+tKOc?g_pYYMJc9J4$9B?0&sMlu_hnVO%|IGU&)W%OWI{=)cR#w!eJpNyj2P1E^v?xt+&Qq;7yeSW=dX
+pFDQUZTy>srnvM^y3h5A7eR2xLJx?wfXU@d)=y=Xgk!ZcDHc=3+X=bQ<JmERcOk{N*fB}|*O=9;jX8G
+h9Y_#rgl(%5mb##MMo{OXhxg+Y)&)T^#q!vg|)o;&9sM0P2KcBz=ErogZX5DjWbH1Leif*RtcC}A@j0
+PT_X3}Q9EhK5PXf4m_xnu9|O^>93R7^5(0YZN$;HFz9SP5!yu7|kIg0gXMDv6^y?yfWE(L;j1&W4boQ
+MGFQU}kxc%dC*x?i(<TfmI}f*$>e}#z(?;t~>9w&F51l{!@p7{zHd?{sV`C{=}isC`}U#i4g=sBQ%EZ
+?gb_Znn4K|-rddq8bh(4GWNqw5J$E-%@1O|Q|g^zAM-%qBYQ!lzf$SZUW0y|4*7G3Lc|B5&Wj_<oKau
+PF^Nxtg8KZ4P7a;1BZEO4^F`9)2m;{A?iT)PHfHh}u7ZA&*6HD>aQKtIK#x^+0>Asa;*<T}9oX(TNc8
+Y}JEf<w<3>{aNTDBcl+59G4n2wwnUC?KQZxDcPN0uN*}iuu@I6GTJFN<!FXz{4|E4dh@h8l@{?9v<?X
+Mlmkv9Hr+yAsfY5q;l0`>b1P3_xD1<Ihcx_nbNbS_=%LOVVzLmI0z861i7bUK$Sg6iB;QFc12$w_5i1
+)rH!Qg86vDTx3dh8pKm%Ek@TcTC9$XLh>H=FYSEhXGqe70UeN4H(X1dLKu++b5$*pcrRJCesEbfMjZC
+?>B0Iy;_V!+Pa9+HQ;`K_qjd?k)c(#e7l$rjd^fMhvr%_!WWaga%U%eGAcm#3uu`BU2L3&MlCq3SB4e
+aSiRz#wWEK`cYC%MDfBjBCuTC3P4aFceWg^A$0KF}P&aTEh$|`(rZu6H(FV$?)7c}jZZ~Pqtk8J!q*F
+9@qmk@EU%^vZ#7$&bbyoRcmjiEzue|`F&*A;4QI7P+%|(S^!?m~vh|tNCo55F%QynY5ZckeCAUl3cZ9
+vA)rw}9-Kwl{MJ;XgOQ}<c!Dh%yWosRC>J$3rgKRu+>ES=))QWvU#VjGU$rhK*SWF7^Fj2fVGw-!XGr
+{Y_rA~BChalP$b+{4|!s#TJ*Hol<^p)nCoGF8U57cjq>wG2)~GfKl7p!69wiGWDt);1pLJ%L^xi>w7m
+fQ$t`d)v)D9wyI9*`D#MSDl{w$7Hx~$-qSrl9B)zxZ3~|1$BXkaBhth()7~GN-D)B%vk!J&x7oQZ5~^
+>P-4!!y#}5*hOp;UuAeFZydX=_(GXmtoNu??MzBO{iFw8sAeJwG+dB;Wta+F%<sW*7?NzvPx_&h!pFJ
+y(b8X#`(W;Bl0q&nr=lUD59><#9VGBNhe2wT>$3zu*0SA_)_&~T{Xn$-_KvP~@MRqUf#JnNjc;%{p@>
+6=nP1t-?Mx2Bi5-%~^ldQy}&CNoer+5ZYC`h+-aYFzsdw4kOk04X^EcDPQ+HV!>Fx@tqDX0ZLjD|{|A
+TXu7?tb2h38KC7th&DnjV5n4a3hTA4wlaytcjsiuW$Bj$<iV<{y7S%c%BV12Db!b`GO5R7t7B5**!sx
+ZxbTEtt~(;FJ13*xPMJ|8-dGLHZdn9^<TH^fM}1dyLoFc-ZTTb)>i-Mp`4THp~K#yif&uk0m<C8n=>h
+<Wt0rU>rzZ^i8Xj~o8iP=8ByOi%Z7QdBe;mo(6>z}A}_Qq<;%T;PA#xZ7A<MqWlO{&lW3f2Ph$rSkD)
+rbqYd}+&3{eQ`I4F#>x+pWn~CPq$FRwnd%F?{6z+O0PG=%-dn33Fm+8FRyOTi_nghSJ4(HZw+rbI`LP
+2GS_?}TG;)$jt!wp_okr>cZIP<W(XGDrN-Ik{8>4MHJxIFY|ub}~plMP?!S-qWJvjN>shFnCZB9rag7
+paQ~P^8)h$_rEDY*^)GF%5N?FOxwlh;})zQCB?%Ppi+j3#4YD2%etj+gVS;38o;6z)t|vc<tTLRqqKQ
+5^6mtvaHW;=gc$BO3XbhT5Ne)%L->wp;*EREH313-g}M?UdW?x0Q~wmhw}O#6Km`r;vnoF;2`X0IB5T
+2U<Rg05@m2|2S3<Or+0D<Gdszq_dgR1_S2$|V?r)|V3-|K6x0D!GWt`kM;tilpxU22MDb<(_RnYL9#w
+w$(G<Ny7A*Zb25$dH&_|mHi64i4>2X2xW7VTq1v^qA<X>rpeEMIG=I7$0iB%w<SsWkP>l`~kR6-vW9Q
+lX$@6;JXj&A2e2`u@{4T+D^K7{y;C?}4*2L2_rksT+F{}u;v^Wp!!<vSdN1a@F_A#_=n7|rWEE3cc~{
+8-e-5<i>h_Kz{p0fB%&V4(NE#Xx`3=l-`C=zu`L2LrvieJB090<~`iTRW9Iv9Q8&d>7p5h%0E;=)jVb
+kwm6jb+<Y-x`|6;YjZ(vX%LPbT%`E^Z6>Pe60Glg>RqZ~x7%n{TVBRkQkgy8MH{Wn6wPD<{2NJ&pLnG
+SnCEA}-EnLZc$p)l^+mizIg#-7$2!c?II{vLv$eR>NZ%e_Io1@n3E)QGnYb~GWoZK!xq`2cG?)3#Bzk
+GlO<pnilwF`#d*0sdv!7n|gwORGyxdt=nsXfpH%mDg^jc)zaQQcq4nKV1@qcJM@PA-D@ShnEh9YQ~-i
+-&wP&o1#woPKke`$)^9R^C{H1$&@zC&N=Q$?E*AIW>_AXG=??57nh`=}A``{1AQ-Sp>a&w@NO6KMQMd
+uHUpZuajm`I!p|r$;gI&dYY|a=b{6;282@T;%?J{ww3LTL>aM3c~P@z|mnC;G^{HP~!V217h?MwmY~J
+bNt3XJaFe->8EL~_)OkD3dqo-o9(cRAG!biMyQX7!`~SX`Y;|r{k`#^Wl9v+y9s*x=j-v<xQP>fG#>B
+&VdDY+zcU_&@Hf@1hC0<vwu2zufF81%!^@Dvkrq;14KOvFplkI~GKD4O3)9sFMGNf`<O6e0J8m3}L^)
+SdU?mBZmu8Y*Qv7mZ0^F);jJp9kDQIV&S(l-%)R99#MP9-(5qBFyBz3o*p2HHTe;uU)ewwNJF-m1zAF
+ublO&;$G?c>;cE-8&ivj_Sd@MqQclGSCG*M(723YjS?d4?}c*w&Cw5(s!x;OUJ<-nzXTRc%**zoi#i$
+RhDc&s}5=PJO=`F8uaO<;7m^2rJ^$OBh}8emeVNoGF&E-SIlD7fZM2#Rm{|(_(Z!i>>~ivf}ov9eOtJ
+D5Cnb$o>m!<hY#Tu<9>r+%3P@`Y*Pv{h|)H!-^boF1Pqm|MI_fyEHA`Co$kG)2-g}U%0xhyGP#s^2~p
+6^4p;b)6}<L*eQO@_0+|`sK+78e(bk1T-^Wt<s`qYyzQn-&!=1dKF;y=3VyJH|9`x`Z`Su;UE6o2`Df
+-fOAod89Zc;nj#k^^BSBMqR8NzSNKEz_xQ2W*<$td0wj-q-3+<SU`NWXYkJwFq=$anD3H#tcx;Pp)a{
+Rzo`(it=%ky8;zlvGmA7T9zJD}JXA^hyqL4kjS<958Yn|D0^NYP}Ual4<m7M&ciwH?ys@sSfjnd3BvG
+#z=A4)5z6u#q}aFMnfh#qg*yftTMKE&ilb^QC_n{&8fOq`ZLNW!O?jfU`F2@9i-g!$z4V^u0&yNQag9
+W_}6p<ZUt95|PdEvH!XQNno@I&!PJUH}dBtL0`|fYbQmNwlFxF49;_Cb6OUhktA@BK_#x|p3j~rX}S%
+sfckA>$7X4vk03`G@K;UxX<vXijJo3=XZ6VVGgD)(j)hzpejP=<z_-F%&9gl7*1D$q*e_q2Gn;dq{l|
+sZ<94PW7QP?1>0;gn9D*|XSGiUFExz=|T`z)y7>;)o$iVv1vGIp(x^lAr=%#?(Pq}U*hC25}=#_ivR}
+1y(y!+g*mY_xz?GH<LmDOawO0vFNcYh{R9JDQ<i06AEw{wbm59JiKie$Ah`q2p*WB*Z_!MQrRSkexu_
+WMWD-rH}FJ(PYvw+!s}{L&nD`lcat{`QcLwhp=NVt?Kj_(;<l(SFt_xZl6L&0n4q;2iUh1@oIzn?1?n
+ZO`KDjr;bl82gXo@W<^uzF!!<mB4<V&gVTo5@G*B_;teERVPOZh?z^IaSB!)I-^9+!YI{4#B8<>X|`U
+(Bd?Y|54Lf84&2EZu6SqSGrrNJ(h&8w172;sA_i!&O;xseXdtKe6H3%ZdbJ5YUr^OjFH<7E=~E`86k0
+QH&>r7U&SOXgMigTL3~Wu;CyB7&D|k;EJg33TvW&Ak7K0IKy@VF|O+Ud#B$*28`g)Us{xlUVnxC~Z8U
+SIOnv3L{#fs18cLif$!Js$X#$nh~N=?Bp0xgiJiqNg=>MJGC!|u);)AbUeX(I@zZRM?jvBXbkJ8};co
+3E)R!_@0_VSHPE5Q~3fm{Ozi(KJPSXp_Z3GM+WGNX}Wj0NAr3<2iK)^Ve1SzPa|he%Z)@PW6z;R|BR!
+X+=O`n%(ks0zA6>S7Ts)CKUNa<dq*Fyb!l$q^eGOX~Bb;PTg>ZYxOQZvfRUvx7XQhbs8Ol?Fdmv3$-p
+PfIa1)t(VBC$OWO5k1e1t596#E2sSR6s|AhCFem-Kf^a8AFOZims;^+Cy*0&}Tnj+CUI`r3cl5rctx;
+VZ+L$D&z|y6jqvnE~y~~7OD}9VGhAvTZn)+ybL=zZYsA*hqpnb1`Jl%!YJtnL`!5?H^wGC?J7{w}{p;
+sWb@rdoY(bZE%*QlSeBQ%67OhUN1R0`0IxOvO{2IeEuTTy5B+Ph#bFWtS;cLfh<A8tm%>Od8vgtc1EH
+3CU%dVUOV%GLP-Xb0>%KVi1_2Dh7N-ns_ddZ+7PRIWq*FX|g)Vdp#_IXTvKPQO^hx6w1Q%Np`8!e#&U
+hb4YF_PSV#6aK<q{_FqK9N|aR*Z+|PzoCPlFZM?mz`*cM&lr+`DI7*n82R~xo1G1%>7gfbj3~vA8dBo
+ZD@kAnk2#7{>4UrA^sh*9q=EiI5&h`Rp^wT1`qMOXP$ula3D_t6LVp@3bLKb$NgnI%=R9Vs{?!21q&O
+lyJDAuR*fDMg`}9v{2Ro$WgNnhQKoR;aVa5~(<=WZbj%SWpIOq{E`kK$eKAoB9LBf#FNLJ==J20jCNY
+Y@xjW|;ZvkRancOv`Yr`<Z?9{>VyAOsV}kHMqsH-T5x%{<d3PKsz<om*O(uxEQ>E8DKY9irx@=ef4X*
+t_G1cAsWkwfd!dqPdf`uLGkFNmVX7S%<{MSCzWYK|E(0_80Njubd4AbVoc08lpS;%kaLEHb;5y+jlp7
+LoVL%-6j8c#lXM4<R7mX_{W#5DE!a--4~_M^5gLMkHafP7L9eE)+;zW<q7rHjmsK=Ua=ve!k|@k<_j<
+Cu0zdJ!MOp1JE>ug`CwbgT3<cmd$zb0()570b+<}#;570uri<w1WLf!juQ2oD+^YOjo9cjT0H^PFys$
+7si@xZa$g3oJzl_&MZcdNg$u&?8vR4&`yVp3?d_;Mp%2yRM8DS?B2)F>Mi!*aaJ*LNLJrm1<L(YRD35
+dZ%Che!`Ud)j*7E>Fp^(E*l&8)9)ZL=2fgh{&C0AqTYyPGFIC@s)*Y^S<sQ&fp`!_|xQD$yb;y81k>j
+$@t~ek1%Y93Nbs^c8{j?!5za_f%Y=r^GFEGWU3FH3=5UI)%S)p#o-oW;tHw<+eegU|c;q_o|@hGB#fU
+%SAGR0?{H{D2ks}S!T6KSv35$-Wid)Y8Q);N%SSmE8T5&yY_~K!QpznP<;vcHHn|*cDMrX@}XN~(O##
+TDbhSKVy<f6cP_IET_qw+y(`se?!2t#`dFupX9oGFwH>=f(^E{o0U8F|rItCm809u%M*>=$?`g9sy3A
+8&*urRq2VVmP=Wy9AOdFjQQ?RER>xGvr=RDBJr+m@gmPWiOfng`gn$aaU39o4I!9wwIU|C1e`bSTn7j
+0b!o;Day&6{U#Kh}ZWKgyiju1WbYi|Dm7X%xV8;<W*BLE9#8S(l(ao8(?hHB>lrU%6TeB_)?KtQ*Vz#
+smL{xA$sx6HTLq@A(yTPko=rp{vdXNq|TaQRt4GgM<*_*B_9*-L`vs+&wdOx*U2FUZHL6^{(}V^?YC0
+@<SBBP*2-GoW71l&|TLvU()q#HFA*G=J%ul_-z35lfstW=4Lx>T5g&FJvDcp+OhmH+*Ti%e8(Gv1TG!
+1#UvC2kKKW8lR>?gCn<iO+LM9MDX%T{@{m~n)&RU2(?`|`VdF(h_yf82asQmVx@YcdWz(sCUsUp#bmu
+W)i#)#?z6*(!DiQ8rU$FxYa7JUrG76it@-XO-OvIa^w<u2B)SlHz+Vaj+m<~>K(_0mamFLD_rJ`RW!J
+l66W7$3jO^x}`Ms=FSUlUD7ykjKxkvG-L7{KLOm16KbEw42Zadk8rE(XV(@~|soQrX6BPM*A+7T?!8D
+?LmMA&~dLPR;Yknv?vH6b0uEB|1(t2gd0^xk%4jfReFzFai-AUKy~d3u3&7Dt%oO|L)BNNG4emD0bOR
+(h4#Q0kvZ`Cos*;?$D!AsK9Y>yxbj@KT>iBAQ5d9@Jse-lRMv;HL3iOp1RDeO)#janeva|rM+OctJad
+kjT&Y0+S`w7qli(-vMvD8Pn8t73pK!_OP>n9ov#%swqb<C89Cf>&_fLL=s!}_G{ZTl65Kv|2iv^VaQL
+`ifUAiK>zbz0J#PkoZDjHBItaNDpK|W8)GxJpNFa)uw^Arp*=N!w;CVrXUbbaT^WzTKR1ZcKq(<`6Sn
+Akxro9{U35{uu_iVI-fay=py<V1ATr|FPY%|wIg^)bEQhqj)ZD)!J_)1le#G(!<s)gOT<COxvc$0*N5
+S91Q3;HMXb1h5#|D&$?_mf~vYoAE7M^L!#(RYvc`JYYs|C@!rx%2<cMZPC$6h-0$1|jrb-HO5xgnb&p
+p@=<j10#Ex(LSaR-lHMG`&aaKy$GW{5WN?V!W%LAl&FQ|K6`LuQyZy^-(zPtaz&E69|ny5K|$~8(_p8
+6Vf;t%_R+`Q;{(I+S7ogDPUtpTh7)@ZErI?Blbt~(Z<FK*-cy1b@q*rqZd@&(_DIcke7Ap#cS?t+Z=<
+<j=YxCgQM!lRx932^?fw3isG)n+5%p~pp`0vB2+aYb_0^|DE#-eAYVS~Wxq<7OsAU@Knsp)`*Y9S)NS
+gxOkkwsdk^bJ|UIBKG`#nZ-LFgqC>E){r@2uI(>%*a6c}su13=!yCh0=#NG4T2HQ`T~zkDhFQ(l$w?+
+0km)8ve!5P55>UcpofT>XX>Np)u2!;1e?)UD3t-t2PV#m*_OhL>dd_FJLES`y>Au&Fc1{0(-QA57E=K
+{r)nUrxa$5qrOBrwq4SJbxm#b7Z6&1a|-V9WM4k%W&(a$9CfbFXrMjP=yg$E8z5p{gD+S(wrP$XyjO3
+mgjFLZFdt(nm~%8h!{u<>?z$YfV~?q~LHFttcFnM>;f{ypxXD8Q<rJK2cQ-ROE@7M5P;dqA`AZ%}ytp
+>ae5Hpw(~?xEJ=RNHJ|Ux|&d5<FLxw-H(1owI2T`8}Dc|bD8m`wS;s6duMAwt(WH0U<<r|~Mug+zQ_<
+Etb^Fuz}6ew)FVm@R^mlz9r6XyFe#OxWYt?YsVgzr__@}jZl&DEvp)(d?%lS&7X>GpjxWP%c}FL}kKx
+GHkagy!i&2luM4sP!=(Upa87srp`;{<85#_XLFvEAhr@2G9O&=r1&rw-ZMnC(d3<_0ftczdmH`fSD)z
+dOxU-BjEGsEoDo0xVLtE&G@KL6=Tp+a#?Hj-V$xGAdVB#kLm0Y4cif&<LS+KButVSXjA}B`obvPkqvJ
+ba54B(wtY_8nmDACBR7idtHOyH4)x36V%6?==<FXQOwK7HUybM0jR42OA_b*_s3==Ty_&HWUhxz7WH+
+MatPXtO(`q{0;^PC$Bbu<dSCRS1ovQoO{roB@;O2TE`f~Kb@`VHE1byN53w3%f?OJ#)czqbJmpT*_JU
+?$|?xj(AD_6+S`g40e7*zv+T0b`^Xdg<m%?08{9F{d<sx?ykrf<Wih@Kzf-O*=Gw&j!QaTPX%0x=&VF
+yg{{0cap1eH2Ie>jp1BWR~riWh$wAxkT!oY@t_NvMiX>1!+9{mrdSZXrMe@e2op5qYiERe^Subo_1=@
+s`~3_$V|-#x7*%54*c9co_{u$^=l!O%x=_!Yspg&MN*DWek!^^)a&y}fx8MW4DC*Z1IqB*H}et8-sOD
+F@3h*e{VgJ&W?_yq(Si;eR%z`v0hI_b8v#-fHy9~8>@+P#5Z*<S#Ss>XBEc?;Cn|t9CoRgHKTqPZcar
+w(1k1~Cir^fRt)30QIqUL;gVu+7IA*tMj<q8kMIJb$OlhW892};bk0a%au{TvR)FW)1c+y}T9Y2zlc>
+wOXiQP`6O&4XH)A@9}+9dy|Y=Vf+eo!s-uqGo2mo{6FcZWy2qdCfQKF4NxPaYQth(@M7p>g!=`Fmct%
+pIgwo*L8aK@{@&g*+`Nzz5|xTrX#k%4_DnZRt)LZ@WMHqRR&m5HpC5bE(Z9Do@3E&OrU*KH_rl@Dg;7
+XS58*ryO2X35*=*fXQMp)&xYd*R0y06p&CdcW;#{$AsNx4-&uYr`NU@9L5+O?krrB&NK6~>&@a(q-U6
+xs;!k*75%!x8~pizLZ|SlSx;<fdB?GzJhNMpYo$KB{J_H}`5e*%qMQWvc{HBr$%nAYu2WpNAIfVnKS!
+Wdr=dH(+#us#*EP-Iw7YP45#?jlloUCUBB8j`$Y2n$ObT22H;!<<42{J*Qa#5M=zPC;Hcrcr3(`WT3>
+Q=G8TTwl*>-^l;p^O`mG!!sOq`5GGa%8mCt+Ro#*v|{+y~?cnb`VDo>tnfB(7&!{CXm*|1mY(9n1bF)
+bLje{Ud6)E%F03#AuvEPzpv7nnYj%Lq6?r+KAUa`vKdF63BF~-KNsLJ87eMd)Yy{r^{e+AKHWle^9@0
+-$8fwMMnD?$a{h`j=kHv!@Y)UV~ratqwzh~mLPj<4@&mP8iZ`z?-$e%eRq6^;a=6Tw?skjGL2wgktX(
+93>tZ741;%tN3v)9b{}J8Um6Sc=;L;Fcj)=@1iNq0PD`VAgE@i!)<x|-r8>91QNuV1(}g;A9+6F4=F2
++)Sxab#$scIp&I*D5h8FIu5cqFs;m!(yPiW!s0%<?d!fe)gX8n;CemMsGH?(kPg}{G93wKrs{4H9z`<
+tzwS9}29N<IX4yt};67aG#mRJZK|YF(VFGd&Y!j%u806p>{SW!2y;`;_Xsc&N9l43IZW)}yQ?utsy>^
+5J(6kU9?MU_DwsB#=df4x}3BVyr<dy^wQuJ4}`5lG^id=gt|xB@GL{bO|E#Qro_TKlU1_W`5Nse02l}
+!?^18s(W1$<fPO;;y1w0Ss&?3&B&(bw+~FmIN4J?Ml0Xy7uzl~#R5UEf}%@KXwdtE2K+VH^DFbSLrcJ
+w*^B(y4>>OZp(AKfHc-Xu6Hn($Fds$pp+)kAEk=^$aj?``yv6y;Gmc79xM%Vtkqg0r@^m^ssnBO#uCG
+8KW1toHf^r}XvX4EroT{O(VGw&U5+~+QsGa+;KBTzU*Z&xt1^4%g+eH30ME@7d{S4H9Z>jI$nm{lLK}
+d|oP#oF*K=DuOW|Mbg4GQl?u5hpyrfpD*zri$p1NA1S;V;&g@rJpd!u2MWH!M$~-7B3A_cRHL?5-gxw
+qxg>Z;AKf+)dbTGJacW19s%y<U{`ou91&&S>hc~*!BSGZHl%5c=DyGh}dzPe4C6A@SbVeo_u$?Om?k~
+q`T&i-<h3V+b4TT@U{ie@Scsqqu(ldVz0%ZznP`U?!)g_+oF>5UnXk2mHdX_-v-wKUnbYNwszTzG~ak
+9^Nj1<u6Z7<e-5PGNU3Cr^gaM*hpumB2LP8%=N-E?xOzn`yCLouVZMp%N&m=YaQLqFM<1b|8*F(WRcp
+HeB=9ApuYXLj{oWxnbLu?-B7Za`?fwIMDhAW+%c{fg^vnXh5Axp*{_y_(&f5e2-TV7HZx8r)@9*!tJ>
+XZ#oX>JO<$9|xhUD21e|;LYh%~P|ph2l_pKCe|30k$$2|>#|zh7@-R$l`HzMk*=g%d;`Uvl=u9?B@cU
+KsO1UR$Qzpd|&2<b0kTQmh)NncI;Z=&o%qcaiV~lugMgx=O<|uf0#m*W(F&iAZYauER0U+i8jB0Kh^C
+4Ob;y;tN>_V%MsudZ(YyWUA7xnwLuN9^837pO3b2o4{^`5l_6l1PoOlkN8Lfl9j%yak#wT*TWzV=S)X
+gsP_dA?ZIBDC_@S=zauikCGRms$IP)g---!j38iE$-vokNde6h?TxU;p5%}CuyRjHvD35mqj)H+cpLM
+E&>|l}1Nt+7leiZ2q_FJvb^-IJ6A$`j^R=SUm5+Oo8!yN=CPn2^T>Z_-}^c-oiqVp{VN)ESNM;=m4>z
+sAWDD-;omkS{FRIW-i_CzcUF^Yzkiq(xq0V-7?QHZicq<GD8`;jd2fxT8uhBn(4fUebY9@&cvoINGV%
+S>cM-@=bI;?-w{>5D?(o}DR;MiODG)dqJD6Fiah6hvp31jdUe(|UQM89<+Tt`&A&ffe>pULr&>-S81b
+kWSp(?Fh}O8EDnbX`C`gN<%9f&#%$pe2HbRPiq7mzABDfs1D_GjgPLxq77>V*(5-A&C2(&&b9iIfw)6
+i;Xy+yNyjMg{_@zWOK(Kr0~))=>h`lDp4{tg2oG2J>CxBdqe=PA1%A<_oPJUAmL}}vDPwKiS6>cBI}r
+USVYXxH9zBO<({$}mR_vh1k+5-g^>cs$^d(?ULA)Z+t-qhJf0+1TJz&5{mFwYC`2ef=B$Bs0Iy$!;20
+?ezo%e(?ZQ@QF%J~JFicgmXT|jsDvhh2@&Wi&MSPd#&U+xu*`t3WYfaXLYb4=f#^b?+{s7}dt_78cdx
+*PvV6@5_b^NXJo2`$?`U@{<58DS1nG`gpWoFTNfxMC?<)@js0wJ|)TAGLFu`CJ_FtAvQz$SW)pn~t6y
+s;8p?Bz+fKyuA`+@(K(YKlK(7sL3It&-bK>XunCuQ{pa!p;n}VS#&i#&Zk2^2>fastra+gakuCXv4jO
+`c#S5?u5E*(`E!Do5>%>LsWC7aoQHPf+2~XoR^~H<!3{lhd^Oi6P}g)F^DD{O&Y0kneK3dfHHx2^-Fr
+MWkyt=+>Y@zh(2Hk<iERBQJdfCTW!;8Lga%MjQgj-T7_R5TG%XSC&G(w8oTXyC+P7CPXof2^=M{pQ2D
+KFRWh(k6ZcUEBkyufHOQ<&-{2)`ysHyxu9cUuV@XH9<hqQVm=3{cmTa;v>D(QZ%@)i3kPZ0*aL>i4B!
+UdQP(NP?D?}3_y#l~pWG#B4oliFt?SEhVPJFg7Q9eP2B^IG$htQ$FVLRws+v+ZXPuxP<>xNE#jns%fb
+o?&uBcMzoj(TVBJMitD%f;(-UCr{4ihG#2W!*00J`E-Ighy)tNogw&QBObrf&a<%(kC`kOs|>BdC67m
++5Qq5Qa^OGdboje8?Vkwz|8%W?N*#Za`6#^6Mr`}{CP*B^aU7xW&v+wF?<^5{Pi@>7-d^Ma@6<7Zc2T
+^28Pac;@@TirrJ+xGBNpw&vN*iU>lofUoRBwlgt48_Ma1s<wtb19Z<Ag4kBHo>a<{dK_*cAfBZtVI(b
+-$T;=P`CFBgjTBMG@bVTkXnba%{s*Yi@;UYoOVMf}~{9>3eVuy-aZrQfj&@;#06iz6@fTbW<)DTDl*S
+-PxpP2|ntlf5~AmHF%c3z@&E@8z4!hyRrMrtAOh4AAFN-<JO(^?~=nl0E#t$N)haFMmk=$M+eaqg(vV
+EYK%%ANWg$htgRl&iUfu^_n0?$`;n3Y>w-)(4=}r^ivg)y;5N`TOulr0bDtZ4(1_c)SUI}HHuh&L38j
+1YwMAvGFd_dkA(#~btlOIHQ12XbiEyJY6dIMycz+oWdn9ZKuQs(<;k3s;1jujd@0xQnn0a+UxVy<JBk
+Q$Rl*v)oq=B!dHyW-J*rRen6$Fsq2D>Ua>DQy_2U)5t6$Z2{4Dpsc7t3v1+Tc14!(NWJl}xjX+BP8V>
+<h>=&_Gsi0Kyy2Sg;kBtu)f!Jp6kA)RliZ)Cffn@@2Xk0SDtHMVxkfE?GFhLmCH@$l$%H6@KCPWIA>-
+KGT&n#CjQc=I2poG5V?WQ(SoBkP}}>czSXgW4*xb}xGT?hEJpuRhw%{=a{j#LpF!|H%U1DkeX_;>V^o
+m?Q~;fJvG}F$|-3H;@gKAryiMn8s1^Q-7&+hty3JC)h5zcYJ<FVmFNsy-lKagOFfH+qXs2=l)XfQT5w
+>P_l#KhI|41o;3mQhzP%5VIORf?)8;>&=r0AQEkE>{uL}od(bx7$J@U{!O*VjH=y3YHhfRA*ufpzQ67
+DptJBn;hR2b&(dfI&W4q>yWBT6Q@pkeI;&*T${X2>IpA0+=GYLor)7A-dYs&}^rYrm`>$P3h+q{r%>>
+K+SczZRG`Q<mq!9nUa{1au^cMn48&%(->AAM$A6%QeD%7O5x_qPqx{yeFDJNfn8S9HD1TKQq%$xL4?&
+o49Z!@-i(G>e&}>}$Kl97~}{7rr;!ffs-4UfY}3RExFrQn0tTAbfOwC_lV~?c~QfX8!rypXqVnx85Nq
+M<S%Na(lJIQR~U`Inuea2$`2*$R4H)%;PgWD+E6Z8+goC6{3e;8CG$S^T!+pCnyS*!)zOldC5uP5sUC
+cgu8UK?apOKxB_n3Xk}V2psnH9FQYB4^f?hVd0|hN&^a|Kgy4yl>rQ@G#EwHnUog_aQeL8|$>z)hfga
+Ik`EeYY(5+5)RJ(-7*LZqrS<pzY1}BJnIjSI-HTq>kJ->(#6_2(sahFr&d71#VeYLNXL5A+Ru%ty3m<
+T%{!4e}!5Hs%DS-C^~Ib3U}vseVBOI10o^tS6?Q`wWO34l3`pkatu?rPXx+T`k7p4C}oS2wZ1mY^KQE
+OniJRC56aYp@uJHJtbWr3?^}Sp5oAWS9)EvdF`D?H(C?udWMrf{@Omo#J&|+y)y9%{4F8#jOpZobAGE
+Al&e>r$kLY0$A5*dPxF`2jL)Ja`<4}@?%M(aNL+Rc2Pq8!r51wIT|Q!q$5w&nA2UXi33}Z><-&UIU5&
+F)$?0c--nA&+_wLwGXo!@Hc(_J5d3(fAos3mowzOUB75Ny1mnF^+D7aRYXQ%h5yO4m!NAKASvy1NA=O
+w3&m(HJ&f5m&T^v>FeVf)*PH2y{cM1Fn$Iq#^mRj!vkK4?d*Lvi;=yp9?^DPVx<>?g(V5Ns-HlkuYF8
+*LX{fkp%%q^02yt*akrghub8YO_1rT$UWC`DLaKcvV1jo<n2#`2CK<CWEXF1j%-;Cc1t1AAD+*zWi*3
+j9w2ZjHddx%ihpBiV9&61qg!uBrp=zzE&x*yHtj$#pV%1gA40#2DOo{@oqBvm8@Q_b|gp<VD~uosO0d
+UoCKo&_cM0Pe7hC8cmLic?zJ~C7A>xZV7wi1^9Ly2xT=$7exhjc_`;cvpV2#$?`5qh07Y_+Jk@r9G?b
+Toq6Tf7@BSja>AEV`taFRN8F7#DUVv0IeZHAN9`OI{;C@>^`Zq{FdOQrmcYyL8L@%5v2f!u5N0Qa9W$
+SG1aCZY?jrWMG{=O-FsTKv@c`bd**)Ak_wF6?{`E?Mi0AtW#5r?BxoYxGU<;SYdbmXXkz$O(e`GkOYg
+!Ewl+rHj1GNXcoD~hLgus&e73ie6pEt3ZVyY~?a9>=q$6Z{W*9K+S_(VRzkvS9&ddQS8P-gBLoku!aB
+kIV)P`Q!i*0_<ZPLFKUAZXT|tYae)=-~KLU)`IUCvi!#jmby7_2n#x)+EP-YGrVRZTaP;1JE<HW~K*w
+w3(8Hmb0LOV*PAx-ov`N^HQzq;1;eysEl*QH7gNA!Pj+HYs1Hrp1~JzIypk3Wc&ycEFSl1DnB=%W}#D
+%tmo<_tH*$zsq$qQr>J_dIE^pD*j~0D4IxWg(gdiAk~|kwRY$i7$k%E^f^Suf$F%EsGx$95scO2t(Fv
+x!=*84Tj+-+r0$25E5<LvS^L`HRTu1q8XWIAxXX=$}5}tJ*r=Dg0J{>b;%NG9S$yTBy%fG(Rqc7A*<a
+Tys{GX3=8^8K;@v$4*_=}ho+PHfRN&FK<`=2fPLEC<_;13S$7(`(xh7$-3p%ji$Ft$&yp`h&$j-dpMB
+RKwP0zII2|A0+CBX4I=`pth*YOkjx=$(hrZx@n%co?~9<Ig?Vp`EQ!*xrAFV!N&llU?j?ge`pQ+C8`P
+o<p-S!94+<?t*wbh5m}d?X{KAE{fszpfLn{8>$EIG(7Z{)ybaniNoF4gm_OugWtIyWOq2&2_;4BNgV9
+mN}Hm)%Es}%Ee59lpyJ;u>tIiyC*TK#yU14W@d_F6%9Ale>d_StLHxytfPL;t6!=bx@)rMR24>?!k_*
+-L&3V>|Efkxg`Jj3?dpo{&mY59<17Tx+WE+m#|G%PEuQ#~tG|vAZPwB@E-xjpkugq-v=4K#W7M8z!?N
+QZN2G;m$GVII7Ma?fgs^!NqXFH|`nh5=D;;zfz1q2jfim#Td*B0V#7$HwG^T7-2^LE@ZEmjOscLZ+Yh
+qiae+a`b`#H}<dn@%5t!Djm7hHneX!dI5ceM_Ln{LXhZ$)5zqm%hd`cK7R}f(Zh{$-JL2f^F27N%PN9
+UQozcBnGT4fW*0%$9w#6IXiUH!<}ZTYMO?krJnZ_rm%dhGLKcNV)-;K#r0N7UQETWOLIS|@)h%d9x*O
+Z**b$CW7oOxc$f)wJ30qL7$K&v_cC$O!GQKw(d^*M<di?U9{?Xl-M<Ky{}BJS<j8p#XTI&(%y_0sk&r
+g<@E6Dt-|zjTOg_spBB##|`(<I~rx=gM2MjaaF7k95;(pVyE`XD2yD*DZYUeodr_iUbC#N?Jds{D>i6
+z@U*Qbcpyaqlg9*YU!3ABu7#gqbrtd~uVWaXi$D(=~p$x)%>@Kn#G*&PZx&AKuWB_`pF_GTX<r63cU9
+Ax(FF|_Ke4gI&#*xA7GE4qou7l1SVkJA?K9>1SJ_IKBQVCP@2`$6p@7)jCuy&FA|7`!1Q4bw2Tfh0-c
+(C!C?!U*}P1Lh`IH|$BFT`Xc>($LY{6b0EO>OKoG*i9=pSjD$1sZa3|p>}B7uG&CxuRMBtJHgbhMYlh
+LF9E@Ksd(^?Z*H#;5_@2g`c(#-e(T*0grhHmzLGuqh><&%Z>#Ke>BQbTn7)Ue?{fByuPD5~b{Ow-F*d
+l~ggc7vRY(c`ezIVH`Ar9-zt3QsyL?-SZ+Ll)!5OLVCFvrd*ErejVqD129OHS0{@J{Rw@cxp324vW%C
+3j^u5^MU^fHSpbNdJ|3bo5$HrN9`aL-)jFHuJRE98~To^1X$qv8#Dys*4m^S{llfPS8up&LKVt#HGpc
+B0l@V_pa~w)%(zTCTH+@eQ?rudpR)Usd`)Ne9n~{{TXCeVsC=?J%K2nuE%u&8@jt%Ty?m?}(;Bz4(9~
+#MxPTg*vv!MUE8^#TCD?ySAW#su{CxLW*>_+XE4rC4Y6}w7Sv*eVh}QAf?3aWU72*Siqnl2<!Y)ZO4a
+M=;2{m8^D$B&ct;tr8W8>b>zvAu7M%Xn>by~$ITIfpjMZYqtw|Z%+(ppUGs*l4ERhC5j~iI+hs4Yyz2
+%zazesN+q<`N;zi~yc0P$urnSxXC8Lt+-(HDL7<YTRS|~U*i7`bU9|7FKttJZRUm`q@v6`IVQ6cnFe2
+m9i8d05UdsyxI0TrHni;OIt%BcZ_)yxoeu#`*S*?_2Za^%4=johCIroLn<4IW&GB8{HOVM=Ip_mYuXb
+TGm7<vnOM8N{bC$Cs<9`T!3-6_k4s;bUH_0Uc(T?=H9SdcWdN#HivDyThYfSYvg!lxg-3KL6m(Y@&Er
+C^5?mC~@QTh)24^v3%*O8>xfvG(R54*QO7u)eD~tc$}BZ5gD5C^(0i1GNldi)vLyr1YZMszy??~!_rm
+C4Li3Jf!8wpeC2u~_ApSvjcaBZraV-sZWleQw68^eg{N1xY3e#AfI=<?vgHOao_cJWB4a)orXIBRgK3
+uY`6l*>85oaO>G&d4-;Um?qj(17N5-kAwLJp{ae<03#)X2G<|OHBq^0^cZl5ttQrEsdCT8w7&X1ne-$
+ieM-!=dLSVtxarMAL2&ma2BwC%f-3*43?#KfCY|7D7ov2T_Nm&N$p_A>QA)*U_=jKxDja_CAxMITT7d
+EY+OD1!H7eT9qjvPMf6<@NK9VQ1S3&yR_GX7=TEu21ysh31iiJcp42w{JH9CuYi$kn5geXc-<)o4gY@
+DM+)h5KO1mN)IfypC}EA3<s%f4j<LKXcUFCM91-&)&P8Obu^)oMur%EfI=`c(6VEFzK9OaYjnDyPi|4
+`<@z1huhM!N*mDd9?1?_12HrUv9<&hs<Z}q$q|z}qUsiPFBZ*#Ec_JH77py^UW7~OQ?D2TI%ckB<#KU
+SakbHTV>H_Cy@Jvo>c;(j>QBYzOpNE<EyJsf5MSU4smAOV3dC>{YIiHG6Mo&HKj)~<o^OZ_VV4<k?=4
+0@YjIRsN-!ATmAJwp%GSJb2#A&qoPLS99bZ{<rM(WD^R1k8hJ+HJ_Q(OoLqK}E?O}s9r?i?RZbFQ^_S
+Q8(LOy$|F4#^`pShdjH4Z`xOF7OXm+y$Ske5=Cwo&mh($o@bu9nG(#SSGLXEFIzJA=6CFR>dZlAG|?k
+r*$KdV_uf-F+vW{;gt$WZj@&k0Nso<1#n(6<;0%+F3?<c<bu;k`>P7`?xDY*#ynf9+7>;Ki$RyHc}of
+D=c8CSaRK~7+~AvA)W){2R9U9^u{BNVco>a>B#mx3=ybU~kF?0?CPkr<5umta7~Ima9uBX7!-5Jph47
+TO6ZB8)qjvrx%+I8allWh5P#0fi;_unf-@EI3p7g6beqc-x0YeZ%k~qG}N&-h{65ZW1af;kv0pGrWNC
+^7W?k<3L0fwi4e3?dpzD<;NIhXF9m*ji8=x(_X@6s?qK4nY+x@QGKXxDnkd)OB8)^wZt+vMSHLWk_3{
+xo{CoOjM(V`lN5PW=UAioaA5(z`yy-w}WE?f<Yn1NAoUgoyqA_-&NA4{v?bu#LGT?*Xs7xgGs3%f|L>
+$951V_xuNq?3Ihi?>)o4oiRbmH^yYs@}t}~z=bywdo}%Ap>G7_Gsd(Lo`1raPJ6uPD`S$5Z^m>463MJ
+LWm(@i*7Lo&|0dVI#Ph!mMctUv`eTA1n>RHv1K%YGr2ph;fbSpYcTbaLa`E$K05F#?y8*xHsqF%V>Gq
+w0>$ywR36rwX3U>R>;ry}f*Wo5+u}yT~s9}us7z(f3;01dfhtsgh;=4H4g$PIDafA+HE3o?VAje=I{^
+tu*(=Ha93`Yg;Wk}7Db05mG`m%uGES?c%KAJD^enU7YM)A9}PQk|Fg!3h$@(UtBERArl_<q#s1zSzZg
+>a9tahwXe9x#xV0A>1VM;VL~<OAjGF>$;$5B+1I6Y{2vsTwg`E^ZE9?i}-%c9O=~-~I(m3XLmZko**9
+8TdHA7XEP@dhT9Ehv_8E*dn@`iPO!hayYW>P9@sn_kw9VDoYelRdvBg3m}5Fmz+xT3`!J-Tk9#Iss5R
+o5BzYb`v+WIN1sDeCmk~hY81G(+mbpQpZtW^x!jk4t9i_G<Pr;orPDoPxg%;8C-OS2CjsnE3fJULy5=
+@REfvG-mE%@whbd-Klf!XPS3ntW1yVdh&yz1Fr@LpDr^G^<7|E#x_L`|&d)ZD#XGU55fuybzij2$%>{
+IIGzGn}BJ@PLW5~T-nudm&UTw!i$YU?#&4dHPpteuKkZ)H5KD&b%?tu3_`>!x9?R-S{wA~4K|>$|a+5
+{KznKXXr{5Qi01M42A7=?8pH$*b){H<K-HPmj6Im+ZPgS|?>np!)*=gY`?HPYQcGQ*A>(ZU<1N9HI`K
+-qNS*ea-_N8mt@S%MXL>;5dy<$1T@|Nn>2S@Id-+JeQE`g}^tJ#HW#kN_fEDs6;<KP|Uo13oHP?9Wm~
+IT1d>llWBaQ12r{sNAJ?>_|T|&NIr76SH&R^Uvc_;Rg!&d?;9VG$AHwv0w++7hX)R23<69e#xa4Qr)q
+l=`p7ufydmAac8#p?#Y)AUrOlff^^)9`B7T29sMb8JSBK$*!)!=Qs0_1p0bDk^3Hf7|=tv9P2NGRNsF
+o0u!^ojJTE<HRb6a^)v1rrL?SWk`Nxt5s>U?@+%_`$SL=1P>Yvtr5G};v{=9Qlhtck_5YzPNCKK9nZL
+SiyH8pq|qk<^;&>WRT82Ia2as|T?0>J~EUsVevoNdi{n$l5;5<3U2HlIEn-g9$;h9`2x$oXsn1EO^V*
+h1r4!?6N5l;E9xQ9H8fC8Xklz%2AwEKjJgd@k<ZZXw(P%%Tz279?KeM4ey8!;<;3xGZ}L)DJTI%bTDP
+jV8;>+zM)2))fvosw!8={7n|{AxLe#?dpd#)g}%Ze3806^HpRo53bFSL;ME70t8==}=gMJL=OJ;h=}t
+v!Jh20=6%d1-xycHcae8tR0qKwBwjjd-4urvb48j4kNsCTmM54Cn4TcU@@`N4T)0AVY#JnAp%#hz_@-
+Bi`>0mnG#3pxe(Z^F2s^F`cfv9=*>!Ju8BA*|6bz@Fe5tpl@-X2f(ggx0tzUZ(V<ySd8fmdxVr9lVh(
+z^|+bPY8iEtR0yG@M>5B--B6xT;T&D@flgZdoGX5$8G5!omEvnbf-wEo*~sr4Ppc;q#(dx@R%$k$7mM
+HUD}C%u$HiI1YsVTzm1Kt?<FHe!lyAR)r8W31b*cQ6z+KJPN}IdZSe^gkvbW(JTZaaRUCd^a6VG5fs{
+EPrDaoxZ59u(R-pwvL6iJu2V6-JARX&JCGysZZ3(xOW-!rM8C&_(eEZW2;NNz5a=C5dV7jf`2ITEuN2
+>y+^<;`6~D_W(48^G;T{DGuzkEsg739=G`R<!;J5uT`JU=R$9wa|Ze33A)CmuEK1kzxFe`W$d~7ScQw
+4tzzpaQ9y_Mrw;k&W(+M^e-c6KkC-hnqZjO?->|5ASOW$e87lP#24%d=22mygOY&M~{dgYj_pR9uBfW
+4n(DruNQ-0IgskgBKvZ)V|D2<(XCg-uHJOb^4{FpbZ=0&#5h6L-fFxz?87vtSwp@e;Ks;(=qMX{n#8)
+-7L+N_aHG3d<j_9LLk=9#G|2L`w5eHCiv>`s0r_3VsfVQd#9Ygal4Jr?Nn~{XVGS^z_-}iM==|M=ie2
+1d`iW>XJWvgRE*a}zOKc(nTh7&@!hifcTyRBJ{ndS@do9&7<xsNrM$Etw~VOn(Srdz7xZavJM8dm)`j
+-3PAhi^h8t~nN4P_i<fmSbpID)|t2NN_hM)|7zglHg`%&l78o(9ovt4xJsfB@RTw+yURz+uQs+tX^YI
+0ZL5`1)y9ft_Z8T3P)e-!y$;8+3;xbq0ev^%X0Yz8JjcGm|7S@Jw}$`N{<+_+|`)Ae!6kCXb)Va_gIZ
+FZNdA{sBllOJWWZvb0;7X7)ly~ZTdQ%Q7Ck?^=T_HzjZ<1{jm_o5^lQwEs0#v*8P{-UJPOna-AW^xX2
+IQ{B*5NzFZv7$(?O0zHaX@0gNR22OVs`#Vh-?eE$4F}6APrOXW!MkI+uk;n40?9dqS!wPC%%Y%JY}tX
+@h-k^&j|pis;-;||dxI;A(w{=;wvpvF<KuL{=_Si1sJ{Yomy}blh~cZA$U7nBxD(FOoz~K`1C8G8K;k
+kfUEzfF<G$tDbe+QPrjjd_QSji|0M{L0*Y1%z!f%b-o$70}G~J$Fz7REuIx0zC!_!zSE&MzUwF^fFK5
+=E4yH(POgDc?Vjg9OzVeo_@+Z(S*CDQjf#Va<J%QeK+_<BS@;+{J$3l0!rhQ|&sZ(4)1SCTVuAfHNZX
+4<*N{JSEcMXd3`EUzI7D)|v^jnlD)w75SUZ1#!7YaWaeb^Tysn9Ks=F44?i=5KyGlodF#h2)Ox7=u`)
++p`hjT?&s<kzBFIU+fJ&xfb|#v2gjA;7V)!Fd3I`6I|ads6R|_E%f&U*J$ltfQs%zT%*zd6LrR0E5H1
+!3%z@oM0ZtJ_W7mkgc5EgTWK7asR8rIi@F0oX2JUCY4|b<_6sJc&23SUKfjK4C=>PVxW0tjQ+4|yzW)
+FM$%G=ldu<mlA%|DrA=A6t>fbE#*1o`J_6@aKB=&(X>q}PP6x?0XC~{+$Vhs6dbafo?*~_tH)#^|cAi
+`&SemtXdD0GL>v|aOj?ru!T<Zybc{FAnnId56lP2FB3u&-P^Ag}SGo#pv#i>3%j?jm7un_Qk^c$bK#h
+>^3TRZ})XWUHYJVYXTD%(&Q29`t(Yl#{fuOn=rBJv(I*0YI#%f#&f}-YI&5H+>9KYho|rUDA)0JY~=J
+v>q1&WRYu~oMe3yTMU6s8_flWyp33(W{?OUE4(zp#_^XM&(|mxS|OOvt&7n2pd)$(ny<;VzskcwzaqL
+=y7SHGLQJdT0_c!P7f(_I61NBK<axB{w=z@Omtfy%p@}Ki^g)k%A$d`$OMXP9dsfJ|m|9=$VX0ssJI~
+bxw;ODpU#~l4D2;Jbs2a@E+e~abPo0uU31yM@v@C*qjrb~sV`gpwyxex*!wX1*sGujwx6|eXF+{++P1
+W}Ml+BkCsdzQjUP&9xYr^Fol{4>js;JTm{AWF)t45%JKBe^O+4#9-A3RIrn-PiIpscQCX~3|ohqQbML
+*W=etx@zxF*?|Ydf>VUjf`8c<iN%;t>B7pAMI6=%Bal<Pn##TI%@EV3E6cxpkl@MFQ{3c2Dqt?kSH!N
+qB26?oE&ok(2Ch~^5oKlYMk{r5wL|l&e?VQNt)xCAz;zLCo37;WvbmXSRfUs_;#H<N?0jX=<f&rlIEv
+cU2%6{PqZ=4AHl!uB+7T&^{hySf2l=NJd=2*p<nMhEAmhL^?$J32buk3sUP?(iqj}e5d=X|C`@m3cw@
+y7_Gv3H9qrY@d(jBFhwGyE%!q*8dv)n|y=_SBal<`OxI2A)UOOD@T^hS}Lb?a#f@qJ(Men`~65rWm@E
+!%2z5{wuy7z}{r>Nu)D*BZzJG2+81nGPF4Y8+j>EK<E9PbXQIKK1K?KSAP2mHpeqc5Xz-xot~&bzHZ5
+c?Dz>Rn$PQTwm>U2aT}znx9{Zs};34+5)b>9z8+dGHL>Lp~1&wjc2~;A;TxWPev^%gvf{^Wd-5x~yv1
+LalMyM?p$-b71%;=8JE!4si4IE^O!_MB@H-)iQen>)>kc#V6m`?zZFDe=hh#`L6_g7@`|I^KQ}DNb8@
+O*Y(F^ni%~=WNQP^Ol=Y_UyDknz7E}Y#d78d&y!|3ll(O+E6j6kU)?H@PWkS8?j!lzL>{;ybsa6Nwh{
+GxcdImWn#6BKC;FcY{yFgDDGSjz_i^Cw*pFAxND^M4kUbp2wq--?kW65bjN)YlQbflB)z;Pa2*dc0%@
+x$Y)LZAv4^+POp6))@__2|!+v8BdH??;wvAb!I5<{LYxduRWA~fSS<6%~=Q$4`5#KMt=ycA+^n^L3h4
+@12VFn>s|_vn0huCqYa8g6KLXv+|D2V&BAof%;W4dkZEubbU8{_sl9mylT!QSx~Az=QV_Q{`}U1aH&1
+ytdsV<@`~3^n9)XPrHIcu;YWYBV4gKhH<#4&_)sZ4ZWVF8{91qGBrw-@(aP=EhvvY+;)NsJAtLOJ^>@
+9IZW2sSO?2BQbb?KI}E8*m*G@gy7lq}#_jSVUvryVRS|u}F%`*=ZMiS}3-~M)27;8H_r!$JNI#~+wo6
+gq;mo4S-2J701o$WR<KNuJkL`i#RyarD88`<<D#9-ld6jl64#?{^_I~n8j>Qa}Z)6k4kL!3(s7s!<=b
+QAvuV{Sk*LlU2Arwjtm<st2*stR=cV69k6@zUratR72G4!HGn$JrE<L0Yg%r%5Qu(L4om-}5fFr_s|8
+W97c?#s+ni)6!R=_3@Zi)p4;HhU@e<$%^pa`)r2OWi^3Q5@_BHOcmoJ}E&a4n)iN5<sNSvcg#A8Qli1
+6uLEA(v{Ro-Dla-TLm2*Sry~*i=Z5dxWdY$$Q=q|Ur5_|S-1e^WxRlQGJoOd@~9)K4~WHmS?bN<`-3g
+A>iL3maXAJ=0`)oM_O}w<Uf9pC=<2xh3=}#+tSrc+Rrim#zrEw|yNw3@A8djD?UFxjgFi3#!&XR<6a`
+@z1Vb=R!VpE!7!Ko~8j){X$+q{A$h$l;eOFGt2QcC9T_d6PG*?LN!#@b}5A5^q#(khI`bQe<C66ic-c
++M^`4GCBTW<T(wy)yU+ia5B2g0H0Zgdoe+jjY@8cbr}_>y-;6GZJ>-fpiE?~WJYd;STE?fE?T9ctPgk
+K(=H6W!hmw$HQMw#Dtq1M0m?#(S`8d!}I91mCw4;csg&?OlGw-(oq+`Rq$~FQ545UCn<UN4Bz$pNDJw
+$J^k(3j)8`2D6X;oNXJtep_(w>|1{9&jHN!ql+=yI~K9+@AV^%rte$e_s7Z~AAf&(;J<nN{po@K=JEH
+Z2jX||EBg9fmRUA)9@*u>$eCU+%%$uv3#OVXtelN`c%lW9D@<F~spTN)VmT1tUF~6<{0OJm<pCC>3La
+Tkj-0!2UkGX8@cMaw#>*N<gvvfSQ6^~-_ObJMvLSe0EFgUawNI(=6~jiG5Pb0>KeX)5-6Y7X=&xf~f9
+Q@dsq4lL1lrb$eq@0)k0Q0Gl2*vKi$B-wztH#Z4;b+66E^AnMz)&0H1hS*^L3Ihl4rRrnfYN?99awGI
+X1a0IjGo1ri<u(e#9ONa8CL%i0v~h%~2CdPjgDGeUUco-Gfpqgn>Ts)@Lv6O9n;$R=T3<+Ap${UXR<Q
+<pJ;%>LyWeRDN^g#RP?%b6IXF|8qIPeb4{pHu`7k;kS4HQY>&khy@D4ad`LsC14bV2?)Yy9Eb2vYY5^
+u2IBD^mqy?n<~9`DsCWqN;q487V&si+!Cq%Td|q{#ytPFN?{{o+V8cL&-V^$pF2LW8K{3ALD@y(m!h5
+KCQzRP%Zg2|y3L$sPU}9e-2=++)27nvj2FPAB8NSOpsrRtFZ6V@~klT|J>3its+q-y!`t2-^?XQQuO9
+wXKPTqQffHq0<Td@%BjfVBNMnjcR$TOopgmqQ13;CBh-0vv2TYfUI?$2Jq!R8wG`L*HjVnNk><QeN*l
+Of{jv1fKsBV>T(;pN|B*V_Em{s+@|dE@`v-|HSO|1wi={r=!SQ_uZ*<kT;o5cu6A{_Y8ZA0F`^j2~LT
+abuw34Pc|ySGc1>p&I1)rYD@e%w8r7J9Ktaq?h$j<6>*3(zU`5#}^jKWLDKGigQ=omCrXoiqEpwIfv_
+zAS{T1lSTv&V)iaYho7#z_aa?Vzas<Po}&#W<DxTaa2YR0JAOzT3<4-W^lq=;2kLk?dWfbY@oF5ijip
+W|23pW~M2?bw29qPDnqKBxiYrFzg*;>jIexq(Ks;+l$Pd>%LEAB|mWS)f>peiKkUc*n%$4yFIUkrzXT
+yZsm@O-~cuJ)7>#6j807k%UX?J>^@=)EVGDIGYhq~&lN}(7NSb^=_Z&!3<R!P@2L#>Tna2j7l<Fu>aj
+;O!DK(N%)g<yLQv~d34q{0t(DT`R_&aAcNRSI}LiN_=_?tmRS|D*9k+DUO=ohx65t{dB0N?({7UGTa(
+YQ_=`vpD%jpBEnry<tDqaG-_^21Npg%D7s#auaelL}#Ht5KkLaUu?pFLwht{E(v!f5BJ)ED?3gv4a98
+a%6h_ANp*`J1FE}z7D@rp$KB(F7dnJFp9mxy<U6dlz14+KOLI)?kGWoR7aM0ffv}f{I^;a(JVe01*tK
+PwAVk?ReK|1qu_4?ex%$iVY{R^Bc+_O$PxQnQ6jQwHS>UT8i)N{R8K=Io0dSV?O(AQ7*-F=ZWF4ND>-
+;q0)RRqdf$XXTb!8?*8D498{ytIqg>7U_(-_xMl5X4V*Zff^1(x*$f9Q)leA2K~N|y)0^N##q@_!Ef=
+X=&aT;bocd+rBzk5dSZQ5&r%Fa(FTy$gb142M4Lu-X_gj=m=-qwkT<$)2Ny_vU~<VsziZwtWL8-|&xb
+d(h|Z_3xMz_MWavzb6fCOOo*(tJ=r9hHrzBbpN$ySMk03eh)=$8wv5NF+<TFAKRPn!~F)BdM9G3J!QK
++F#MiMoxXiZ$ld64A1}D=lA9nP-t0cW_nj1d2h+BTx4WQZ-`1e_IKuF^V}>|o-@8Kb8@o?X5y|QR6WS
+%Z|CQYbKePMY<m2DbV@G4<4|=SAM~_coqs_nuGRa4C{1N%K;qBHVKkr@ZKia!~&LRJId)J?x_uJkTf7
+`oEN9Tc`VsE_m3n$TU&LU@|_5++e<xEV3Q2}TQCepIF4$f(=?S_J2wR{i<oa!UEDsLj+C2kp3xHmQ=O
+7q~dq48OLx*=wi!RuK7gDjqymZdGtRWPtBT<)Y-<dfqS8f`hFN#i&dBD|gt`Qh-oF87}X!2s_H@bfdU
+bdHe)ez_YJ!y?r!Cemg)*yrChNdrIlh5u@H?1h66j^c_GL2OYWE)Zttk^(=TPz0dQ07j3&*%R16jj_z
+;6n^QAE*&xJqNQFA9WWHz7GWpnW|&mnX=bbPrq>+RKBG?nH1SlIu2rAXhesSukQSpUNw6&JOb*95v>R
+dEJ)51&KPdi{x;Cq}-~T#y!}EtJ_dlHZ3H1K{T^~UAi#vX3EG1wP+UtEOiY8%{!f}d1D0nYgArP9RQH
+-QW6eVGVLLll>{Da}0Zqx6<8YH?CWeC}=kJES$LhPl%)J~V9x6g9=d30mDWaHH_w1*>*xAW%?f#KVG3
+Eh!&_YZkHckT%QWJjg#OKd|W<QMq2i3cRzZ9w+nt<fH=-;kJw_K3(HM1gi7-S2;QMs1Xxh~9o6#Ez6`
+yyGH;?Uga`8_VG@<3!RuOtS%U{M-4f$92a)GWozihhuMPQ7tve@TUsm(^(6~jVwmq{qiYanZln8oh)J
+au3BaLBs=*lY@&UL>3CZOYsZGKV@6MaC2j|oeJCg1YNkIOKjw>0u)H4&koWmZi0aT!DD*xLe1F0BNVM
+VLN4F`Wy`vm5uJgB#Zqskafc>B*Qa@z?a`mH>W%v0MruzMAvhdvB%6D%svVou8pQo{x54_jkZx4Cjls
+O{3_ig<U`Pk0`KU~0l7yj5D@pok|dzB0Dwc>a!^z^=FRAxWO2F~;+S+~?wr>Wu<c{X8Spv9ecnj&8qP
+nT)IVb)v7;b;JH(!f1<s0rJ<;o218&@(M<ZKJ@tjRXM++n8OBRhmQ1)8XLDk{2N37KMOv-iS3a;C5^T
+s?cyYj+%=VBt$kYNxdZc+08LmG<a>DXh)cr(P_j1;V_90jHMyr%NcIM-UVpSHhqRz3#Y+~f;vK-c~qq
+392^-dIZqqfpVg_)qFgbOLB+~me?$wnX_W>)N?qdv$g5)1EbMvyIl(Sd7pGQTuX;w)*Msh*$1a?cI|V
+DFaD6OdmhczIF>|$q8nY-W#Rp!hEpkkW9fDlDoo0jyq1WA;R-VodikeZu<;dkN-cL~_E~87B&9$GNx6
+5VISWnP?0->H9PMKhKx!+sO0I@wk2(*HLNRL3}`lNLKi6(+eDn_U->*-v)s=$67qQaZ??iK<wN<RwN3
+9Z4&d>a`Tn9n)>4h}M1UR-VBjuq9gFgiAdnGD^<5xE1UCsgex=bE~LK#g>4t>~18Ik8e!1a!1=$gbx$
+g>o?5{y_{iV>)`Qi%YF4Ork2KPz33Vyj7w~`U+qRhp-zaRJ_wtZXwE*x<I-xF$c4-Z}ZvI!JGV)2XS^
+|QuKW#i3VnImDlA(p(QAmfYf%hqdZG?jNDClAf}x-I(Y=Cs^nA3g%5qAn?4ovbH6BT&wNu^h&F9Mc4y
+#c+mSCD>ZiN!PYxrOYa2lcP|!ZEpuBz6t!!k$i8-&wZRH>I+Yv`~se5^b^_(DhbviXm2ZpC+PndvTmM
+0%WH~GKRz1fnZ*tRYB&R67Pm8s4ZeRIt21AQYJ(F%B@muQ3#i0<nP6ycE(ksdoE_daD-H#5vljuuM`$
+u${c%{j+_iAF9Y+kEr^WD<UO(-ZWF7c-{XcxVqcu8IJ`C}gU8GFVq`lW@;hDm^K_m@YVc_YfoO(sMmf
+{Oe*{0U{PJwNZoUWlih?7B0(HfcEe$TG_rtM+DJEMS1oij`G<d?g_O;WL&+}=|YyR<=ovvr82xbBYvn
+7(MScB;Xi>Q#K%@?hOw)du<udHS#xtfg3bj8U)NMTN(gmD1uQDSl{>cMfw8ed)l(<xd^EpTfT;N><lH
+o+Tq*Ka-iZ34+}JhG9N4%&XmWIglQBRs_2|I0Bx_9~mpqcWTIZ6i6Knu!aHq72=ICAeF*w9ve;6?|=$
+DyPVq71)z;P3T(p%q*ots{e{bY3aLv`OGZKo;?V65d44$X<WpZIYvm7|YhvP_pK)THB65QzA7^Df;4K
+fM!ubMMzQLk2YDg|_Ysw%@)Bc#}Xr<~drNSr(n(uZp-&x<kA$oHpf4raSHQ#Kg2Mobz%bY(`Gqf(7Y2
+dKIsD0w}q&o;@@JuPfFsFucX)WbXT`^W>1mO@eE}KVS9b#k`&-L#Rndv21<!4Y1}8O_rYl6+7P3LAaj
+A{`y)avwKj|LzQpKHNagV=P#gspD*5x1}g>!&mnxiWzXa=2NNbxCnf?^r61-frk~MOqS#b3Xz(S172%
+FfyYb_v$CfTxdiKDbxS**kP7#wkmUk%=Q_{?fK=T;E-^P0Ueb`&F{<Uc4fBhk%8;<)r_W#-0>;Ky6tD
+R+kOw;tgvM*2kuX{Ee>#T_C{~EGq(;xq@<p2Hy1|jT^AJ6=+Kl1kZNAzX-HB0|^_1Pcoy<UDol>dKQ+
+Xrs_?REW_kfRV1!BL9D(4DfA_y%NQ7(@t^*!|~loWRk~OI66X`sl`YzY2^Hdm#z=Zd}_BCU3i4a)+MK
+p1u1N!R{t=?;+${2xZ@82KNUWt;eW6M}{Rk>LiFA;%>Yerrvrd_^)@LcczZ*_;VLC#dl~8N4tv4zAgT
+?GuhU>QTc?}m0LFYo@Kj80RiqUa`0|w{H~XQ_myv}*}Lk%JtdffdqW%f_qEpcUTe*LS8J^|kck||&Z*
+Ay{-5C0Pp|mA*1Cw%ze>FS2t<YW{>3;~W#6p*^__l*3h*=KgcrBi>l@X^+oJuu!R!?`9;m`|9l}Dd`c
+|DZ(5gArq)%UqN>;iJmZ|_YG&<`x^OslIvtMCDEwcDcl@t#zX0eT_<qbE+QuQ_q{wS4pPVTo?|J2Upu
+M(&4iW3m{y0HLhoV(~NKWomuLA~!QXo%*>?_>IV)4H8Ld%u8x@`io(egXgF4g2i<0{+Px_SyRd{F68A
+Gf@TLSE>qqHudI<xPcCLe1wXG-VpB9*nXTm5ia(^DL$*6ScCw4I`FZ>OukR7>YzAHCLJV*2<;P<@+cA
+?VQqC%ji#R~f6#f6RV?fxw;pn9)?<$FfOEKYXt!~>1U^QfwjgN@^6DL-#L|6HtOP|5^>%xVr^1H%E|y
+y9+1RJi2EDrm-O&=j9%)bVYK;hjD!9^MyH5qVvOaW=83MmR`qlRJ^oq*cO@{yt3SRO!@FG^%SM?^+8o
+)x&TBRk?J01P5=go|gh0F6w-`nUuVXR2kq0RbT0^Ty#1s}EBJfX9Zwd7+NZv^51+~Bx=gG=|Or7R1vd
+}{=8v+D!pPTXSW*s$w4XOIWowS05MQAEDJlvwY>F(Iq7?gLY-jnoBM4rF&duuW>UuQl4(RXAk_RZLE&
+D;4!6=Fhrzl`nejKKQr~8zb|H21h{}fW5B6@8|ZheS{VkA1)~72GRMsk(;TP`!e+vQg&9E8U+wyW}=-
+uk9ZEcv7QdiJ#Bz{H$N&?mL!<R>nBk+)lp-dslB9Uh7;`eauKOTQZ!s&@+)$n?tB6Jk4wotD^wAD5=b
+xclYVKk&eo^-r9IWvDB#WzAJ)k~2J{oYS}cm4sPm|#ev^Xgb&;*50{w%$bjnl%I=bKu&H6X6xkw{e-?
+}w{hijUOSks>=9>Muweqyq^W^Q)Ad3H%1c?e4{IRsuSy#x}l`cYNkAJ&}%-&7S85}k#hoYs5WN<xndm
+WCMx-pADaUx+H$0Op>W4DHXHVTq48EKE7m6dxa68(zMUA)S^JchKsPIvdZRN6j*}qEMdONo5vub!<SK
+MpzZj_VQrVYZH@QtKBHMkK!eipHhgh>QQKf6;#?L%SZzYIho0+GlzKBfl$RKa1}f-MNM9Tl;^ct4J5A
+XBNdDO;}G#mt)`dfA$m2wY&cbVe~RFCEtLiqmHLpv^Kb+hLU%INJq4q(nk2@YP@z*>_fiXIH-fe()eV
+;FsvfN@;Yi^`%?<uBd_vcLxERn&2I$NqPkhfE+=k0l<(M1iq3ncXAQ*-hLZ;5h=K)KJSWZutkwbB|(E
+5=H#0z$cq<8`(Os(+e#Rg%);x|0<pz3^vj){cpNqG_u4UuIa6pmqyO7)E!Sj5?wAg=P3|0vx00K^36x
+)OPVAgZPdxS?b>gHNbvgWVl0g=QK{12b>UgFam>@w$Df+;yF+QP6Bxl3o=6=WNbBMH(H%jKA2A8^hyi
+tJXn(qT!Rx5#f2v*@M}0idJ8}))rK^F-ux8iUcK$8jwxgo)kJ?7baiI9-WDFFvfFZsfD3kUUGToo_8j
+-J6?3vHrt>{V9&mvUr72C-?tTD0xlk$$VHHx!%c)XashjRk<o#As1Ql<TFwuzqOSzUQ(^Sr$P&pD-nq
+Uiu;IB^0NjsfxxDtMcN01{JUdnL5aG5#&Yr=kbdlds%0co&FZ~nUeC?Jz+rG_*?{Yie&|~%;cHD3&v0
+>Uj$NySC|9@)E4{ZC7=KDdR0l`Ux0#O)45rP77n7}~-r*IsBQG5fp+lNGe@Td4TeJ6JIQZsz7@uJ>h^
+&6^;^EVo#c9fXJyQ)-{?nTU>;alomDZT4WA^SdPj_&CxD&LiusW(jC8wsi15E=S{G~bp?+u#KIm5Cm<
+SDWR?J2CZM*j`cw?eH7N_uj_jotsMYH(bv4r#1|oM{f%!Vh7gvTY5Sr_S_WtcGkn+Nvge|4gT8<)n(T
+JO#jpX3`d!IqIq^BgcDxOzGg}+@z+dM{j&z(o~g<-X8PEj^qfmwCJnX5a0vd@l_;3>ubq4xzd(9)(U%
+y}$M9~x^FE(D6S+Ss&2#bu?EXey>d$ug#iLrOO?qiUU+T}~X+xL$v0Wq!yp&&-{r#$ee`nd>uNwGwmc
+6g~qwEa$yzb0#M-F7oyT|a$SubdN!#DgGbvGs`hI&26r@MuXb`x4aTb#ptDB;63noE($at(>IC>Yo0X
+e9Qrenfpsh#DV0?&x7WIXvxO3;W8VWY|(h5Cd0{Io+b;keMX0juLF0T_)4m(&HHWv;DE_PZGYspKi84
+*x||xRxgPlYX>7b^o8Z0?C06Ma)a*d*IqrDg6HW#MgYO&-!s!c|D{cOOLI(3mrOubNXMP)+<#%kDd}-
+?7%y6DhG%5;0F^w=t75!dwO6!0773qF^oMC<;!R*WIR;sB&yj_=6@lFNxY)W~X-s5g`rwwL%K*1mYKF
+Z$4{L+JnD)ki1Q|i*MLv_yAxkxmhZ_gc{+%%V_L2J^4#WT1oPQ0&zcJqr2{Vu)Fq9xjihyyHqHu7F$r
+OT8`0io)Wyb;eR9SE@3CRB&eE&@HJ-X%O&fbY=PgCve{he*!j)VCYO+WX>L-x%4moSdR`%EOVYx(UHz
+eC?{Q3vhWHwxT?A)4*o;=3C?`im&MyP&)cPWBg#_brAkD3j!VZ`f_~pgje*4S?Z2?}Z`z&+S68_+5LP
+f2`&mm*ICO4n*#)<OsNLSY+Ve=E=IfAqHc=MPX?$eAYV#gQ`mjgLmVd68gU=3r>4uO#QP?&OeUCz|S%
+5Bcy%tef#^627JV{A0x30?fm|yNW3>@uRlj(;NQK0e5@Mycb5IJ>OBnx{9PXGYq$65Lg223PLDd|FYM
+z&S+L67aw7!vff6gNsR{qu#b9Pd=i(kh^eRPSb2xCdi5om!CyXD?vMDPLuP(=V9okBbST*xOAWS(ew(
+eS;*Tj?W+^0!oHmIf7DYJQOqx-N48Ky&GS>5+Ukh_YBh8~k_?+7-u7YLA4*T?lxxTm*8d2**&VouM7t
+&sQ}66cA4ymT44qrAjwX2T;Y!yEacFI1i6da@1;P>4<`cGK(NCIVSR@CHPojML*8mk4F)u7lE9r6M^-
+D<9H|1y@hGx<1{WNnf~(ssfaJLkPm4FK6oRxRYIX2z0#P+8WLMqlXrSzFh4^B_O#OUOgt&VCrQkB`jj
+nUKKY1B90pg@LuTtP+{0@s`ZC{b^3#snC%nF*ZcJxTemEiIwiAYqk1Gyk0*5XOgiQCibNoYEL&4+T;{
+2fTd&TtY8t=1&d{TyPJJ=-)=b%ubh0QxRuCn<9!Af~LOBfK(S5KuaKYsu^b-3H-!O>rp0#E@<VOi=2W
+~icqG5WRqVp77omSG&qyXJ+N9e(DQ8#=n6M6z%v3FkGbk?B`;h&cc7+{xYo!qX&T>%HlcQfN@kfC?9P
+y<BF6PR`#-ZW^v+|Krfwt$16aK`AIJjd<(Q`k+)ijl2!<(nsMrS-ihiKC346t;F;L9Mz@&-+6(>WWt^
+S#U6c3szt=U5HaOAGs2wA79&zK9leLrknE}3kQBB-^(ULn4{5>$Yiv!?sC%akC7Pk{-*t)-V1y$-}{L
+N$d{DYX&KKo!t!CHl->DW4UsRzh0}H+3#f&v3xyXdWLw~BhvLk$ccPo`by#f@;+a+kd-eQ{64padEh^
+^?q*~d>VrI`IWUxS?>1U%)U%Yc{&^fZM=V7=?B$%FH<w4>YL}mF^wCxQFT%Ts`XcY2dUyqX;V51kka9
+{{6@!8Ht_@tQ1#VZOvj<spK8LO8d70en@&eg%tJ;8y|IMGfIMrESFdm*qhyV(5-*mrje0PY#n<Agp6p
+=eyCTdeq(hYfdW;h*MI!TeaAyeKrvY<s1uuR_s5Q%Y;s6b76~%nu@%N$D9U&Le1TA5WYdkxS;@6hwYr
+N8Nv|+@SDCl6w)+5@%GG8fD73g>EDSc#PBeHBUZ^V+`ysl!BirwR~C?X3xnCRyUlA<?Wj|z-g1^E<Sh
+BMLS|n)nCQl5-nhU)W?#%U&4|vOpBFNbG=Lv2{ziJDvrJ5Q4&LPGhUv2<`}xyR+5+sPG|nrop1Ex0f-
+knl%be-vh6ETv1X<ho;X}o64RK2*qPg4wQp|aa5<fE=b&Zfka34hduic@L~{yA4OMnleL+JLi(}A!5~
+$|f8B&A~dcU5W1T-&kR)W-l^$PiL@ts>moyLqUS*fC~IzUUp&9YO~s80L^q3QunK=%eGLi5_bI9H+t6
+)i~;Z7FdMJH_KL@snSRWtMwW6om|6(Fd_-7i%t&?pYl8->>idFMGWe_x4-G(GQp`Oa4%Y^nd+a(fOO_
+e5>L7Z2S*64T3hB4DXtTIJwL1Kp3(s@DR|aMNH{Cx0B<$NDhhaplSC9ewXwo*`6@L$er+}Zy9{*^Aym
+=eRqAFx4#_vmfP7FGfM77m{`73+1;!N-FuFscUfoh_AcHXkbac{inBe71jaj@+UBL={olr^;bc$sWaz
+sniTWz21LAKa_x5Pomc2JQyt~YHN>1&~W!M`SW^c=;-KqX>osL*@2WQ#k1Dt8JXUW7OQ8iTQlxd!RcJ
+R_9{wL$&>gs(bwk&b<l}#_!H4)!p%YPR26qEjedcuoVIFeNXYRUT=<Gu$3=45!4;M#&aY*-31I1@CSW
+R^-g`OvfxF7DtWk6mhF+))tlt!QaaZTwldv;(v~V}WRY7B2m8?Bg=Nlga=0E(6%F<3G8KAF4pVTm}<r
+jP^qn=*K6p-MAzglxaqZlXLJ4dTAJe`Ia3lg`ImS*Z>E{DH0f6h5IXjZ_8Zc63BS6)ZNTy3_0!a%!~)
+y1OnA+&x>fL2MM?=Gco5FnGM}nXPaLX-G5e~zp-NAJ7*h-w_F*Fo=iqB^OGdRCFI6&rMGwXFU~gK#sZ
+%V{*fvdy0Xy$k-qWt;N>ZVK0J1fuh+`KA-!&aGA<Jt?M_^3j(PT236;|0Q^Cq6r#@oSKD;sr*Qi5vTv
+t7yMyGy|gE|}iI4@m2guo%o6YaMvJdOXoKWodP{>R2G4flU18?$`>Y8i&J2P+Z&KK%XW_>a){=d)i!p
+9ufxxQT3>6eV#Kgb)x!iS3U6dDc7Gx9tdQ4+_a!sD9&f6uR%fZFCTS+h>x*9&V`Z=Pwk--kS3ivWLp-
+i!d0uZ_dSUO)vB<_>fWW0`&A<AD`}Z@Y!y}`HPUZz3%Svne8d;?PMf>H(!yv{sR0q_{fpBA3VI*Y9i5
+oJWt+sobP_GEyitQ!1u37y34r6_`4)O+O_XN?C+KC_qxsH+peI(n>097gs9&@__N%K#{V4hYUQk1=EQ
+%q)EGF+Q(PCUCFjOCrt_V$*u2rXou>)9Vu5G@xD|Ew-nHqBw0+$_BG#gD!DKixqOIOX#QNdb$147eSp
+ViKfPEQ1uHsMQw!igl(>MW0t;Wh-3rywwz?H8Hq8H4@;9mhI-C6i(7}Mh+-d7gI4{X`SzTZ+lPHERm4
+q`eePrz7n-B27JH@$eNm+Fd9JR<TKRi*C5hliNfWXzmE`0AZ77k1B*tJWn+3gCfAIOZ7wFL^-aCa<EH
+X=i7xV&NfTBqAMNN1otcRMgr1F_~I7JJ<u;JiGN0IflctTF|WL>jStS?1W_Rj(@(3!tIjDq*hE0cs{R
+Jx<BKr#ofBgwL3+y9vG_Wfka?MexG>;u8Fr(4<wJ|C__!W*xMU#rsq{U-aN9k6ZO@Ex&BBm236;MT$4
+!EosKZ*;w>CJW<>+xbG%%D`7HEZMAYj9y-xJTR-gXK^#@eYv_eIW8`bo$e0ZlIv%B64wG8UxQ{PC_OH
+$i&37vr_yAWy{-&!O(W1-fq_~p3>i*8Txk*}gY(|VU#{h~_`Djt!ZGe^pWK;SY7!)JRF0InAme5UTRd
+oi{JBKmDW!`84|yQhwjfTYdoN{Gqf+=?73L=TrCx6s-=1LD97NInCcGv*XFU;FhE+{$htxGB<C>QG|p
+8Mb6M)LWCjddv|#^7y=zOWuVP7(Y;}4EwlP05$1dPT+z9zHr3GBUiE)F4c;QVfut>&;dy$@ziNaa0aD
+vVUYS){)nPn9#+c@aTdrfR&lblLwkhINz*;i!Kq)Y<*B@--r6gF*E$|tTH?dE?cHqr-Q5lNo!i@YcQ;
+nHp=KVk0%iQ?T1^U&l2&oAtrz{7HO5!1t3XGimys`lta|inFv}F3NLx|xtn7fwKZ+WJwW4W=2B<OXlu
+j63WMOczuq%HXjxH;s`0Hh1l!RbC_5^DvbR)93G*8rJffy%HsFaRMQlAzrJ9TN3+h7y(UKUoBW+BgDe
+Q2v+UMvdIK=Q;cVDpGOC--?vGi#u`u{6xq9(7=tBONqHqJk+`b7?q4QA?cR8<SfFgVL;6O9kBq{&nnV
+o+&X9Y{nx97z#(cba73JSV^*onf?2~;vq&}HT8Z@Q|{hZ6=BIR8s<pNikXqpSShxZ6i&h3f2c2$H3TQ
+5>(ELUhJ_O=ef650x{KqT9xb*kG3IvS+{M+7g2ZD_;%0=ds+`~v4E+kIhZGFOVRj0c>{@@7PdaD#VH^
+wGp?OTM)VS{LdZAiW+5W)lOEjF4{-Q0|MJn7yHh{<UQ1E^@NO*Y*S`OxU&u-`-KssMnkwXU=)nVg^y*
+z2``4n}qI^R<cbcN&K+H+n4AW~8BWl$EoFx0zcj?)@iWoush=6*gj1tA@u4?hheUuue}MaVW(q9=y23
+J25Iuma96KXN2g)3rP16VZAS#QS4;b#~tAp<Np&+&d4<E>%w$GJ570>X@<O(P&}&31Sx>fYjRdB!#GN
+zBY>Y(iTx2)Uu6;cin+8Y{Vk+03)H!3SdHB(Bf!Px8SG`OqxN2<^!h1q{<e{uU@LiMe_UEfVU$36ph)
+3U(c@!`i$>}N^PBPsG$E+H24!&{GXZe15W+!Y(L~;Np!<lBmxsKfg!uI`Suv5U>L&T&!ARL?vkjx1JK
+)qE&kHR{-xb6+4Zk>m8<xxDLMGLkM4FJneU)yqn3Lrl-yw%`lfmqwF9*X+js9b%DEfjQadBu(AnOy@~
+Z^wc0Tq-c^f?2TNBeANg;2Sa*}*I=;AvbM6rDs`nEU!@+%0wHT0qP1AH$z+<tCX0Y(1}$8QC$^f&Cy1
+$c)R<Tr_YjmZ<^Iy@8-3?TK{EuX?IS(HCZ!2T&nzs+V}=03V$WAqnKaJ}8P!$X*y0onONId<h&QTS5x
+mcjxY+Ke2-bG1!yPnPN3sJBtLw+`c1k=NGyQe0;tfgjf2*_!?9GB@XY2CB_~;b@@dDBn>~ZT>j+ah?C
+_GJ)T@&VO~8!0%k=zq-uNE#95qM~nci)~Rb>)iambV4xbKwO540Xh)K#^Gisvbm`c*_UV#n0$9q);=l
+$tUQ+nHg8q63`sp>YG_73xqkghGxk3|Pl)2%ip1|Qs=V}_}UL-qyDv9_MUT#5ocyg!o=&c-+q%VNj8`
+j%`yZiF>`e0w>WYmaqkWbpHtg7lv==2$FAl^Zlt{<FxOFtYs?u;4};P|<c0CeeLtYT&8-jDv|x2gzQ<
+RM$ehr&Dh$$y*)J81=u!PW=w5YTOYgt<kv7ainjb_07PXsr382vfaD5~>QuN|JQx9#W#pnnbfI1bthM
+73KEHWD#fO{JeJPD{l**$;@^*14`!~j9xC{=ZFd|p>wAO6yX`>4I#+f;NWRE-3f`JFIC)F#+lQ~i^{A
+7lNEC9Ks8_u>ubH-Z%%NKPCN>-D{&U|hCt%bY&r;mnEM63cJjibv4Z$PUzGE+)uxxl8*7kHz*Ppl<i1
+=9a$Rnsh*M%iaPp+4Uc$e4v=dmA;^rySy6~pIum-)IP{w6So>f<EhCm=`+n#c&N2_m`8)bPlaVZpp=c
+Dx)UyUmnP}!T6+Z?DeQhb%C3U-$74TU0e7*t&XFc*?qU-89)jc~qMV{%pHr*tp}`eh}?4Z*H~nOM1j6
+ye$C1xk0j@|LTLjSLKbf$qRC-GbdQT8uEZ&{v|OefJ=6r}1SEGkJ2MIZCl>c7Cq$r-%{wmp(|!y$~;n
+9t;EAQ!Vup#`fr{wr1keN1XxiQzOnV5o06i6Z+&F!nya3$c3GC5``JR0HASoPux(cw%8mL=)%Jf`RpF
+0^X(qT-i`CP?Hgok0%Vv8Viaf?#6lXS5xly>=;s;mS}Me(U1`EB`%XS8B<JH3HH++(X0;qTMKmad3fD
+-Z+qKbc`y)ZHb}CffT<7xwnm{cc4`^vi1r?t$tB2xL=FphdyA#`4w~W=h#2boRW7d{GJn9H72CULkpR
+ajH46Y0ivA(O%8875LlMIW8)N&&$MT6dBNP&+y%?+m@t@H&Fozn<jm`8M%v9`3gmmA}l2YOX-*8%Iz2
+)u*{5g(mWe>qp9?}cK)Kp%l_S=O8urKP|+9IMNW*c=51k}`xZ`|JQ(#5TvZOxJ}u<KFdRG&u+6QP_kq
+u0JDMMX!>BMn{Y5XpBpe$Mf0MSYd&(b+ceI1G*PRkE=c3Wy(PFlkLn0gT!zj8I2~pbjtRZttxXWA73l
+z($v}Z5zWdBDyulbOy?`$-4Zd%yu}P8XDCFaWl21_-w#H~9?fi(f)clEG7mLBWDj{l28XFBB~8n%HpR
+Ou30(1#Rgm?nf&6(Tk0gDfZ-s)L9xzGwys%+t^%U`?V0Ne17Tp(A#0<u}&67f3PMt{sJkK6VSSbs<Ns
+2qTeTN!OlU7wB@08R8bk7owY#$754*SLc&5q75t8zZWl<<%Y=L9Sn3*U{qk@!*;bL8bARsR8E+$-hIJ
+AC<{hmQZ*)W5`#e>d%qnTmaf4g^sMrHH+C1tCF-fS?UeVxNIYEZ$*X_TEgx(j5_gX*tQrU7Z2McCDlh
+5k|zGGQiN!^(N50K!k*M(1*U|Bz8yNFCGKXUVfJ%d!ishcV)P3?j+r}_x3Wu{8wNS{c2FKO^RhZ7{$=
+N9Ar<5KzlDZ2EF(5(!HP$&fZNb?+z8>U4a<Ao4&Wj!|zU+?dQJ!x2S7G{&)PheoJidMit-stu^lQ$XS
+kTeGaqgluG}Ss*pwNXJOSJ5f-EU3P?IX11#V};o&!cB(8DAN2Bum0kD9d5Y`u=3QmUf+wXx&-~&}|02
+0z1=4Vj(KKA`J|9r{7KfUIkFB$l!*ZlJ(1HXUGpXWe;ACe#vLBvK-qKLMz+M~c~BYE9zT~ryg5>7PYl
+(c<CtWH~;hmwef*6M(8QN^<0yD)@1WVJ1|l^BdOY%Osp*6Erv4wvT2Fu%%y0AGs<zU~sa96co>{gcd5
+3-aPqVFu8BKGVoM@k+Dyk*L~ZveB9!EPrLrn&`=*<$^hcE?nTn<#~GX;X#_?_!y;VJ&w0xn99}C&<>f
+3E5LCHE3;rj<FqhdMvJOfG)xvTj*Ud;ujQ4#3#Fe#Xul+=ZxR1tR7Obj|Es9{Z%_TNqw>F)_J?*t0z@
+f_pkN#W5fXuL0wPF~gm8%b)UPFr_E?3#eS>!e&3Dpcw~zyOmcLQ$>@B|o6MMEK#ebz>m%n9%lDBFd{<
+cvE(LG$^>0aQs%hzo&7~6BpIQdTcrtd88FI6zGJ<cQKenUv!oPL`zi+33d;yp|9t`UT>UA%J-z4^Wqu
+;+y0UCv`WaT~lRwc)))8-KSBLh-Jow<`<%t=u(xe{(_mTU2IMSg7G8RB)S)_=Nab)aCz(sH~y-Z&Lm5
+qcW^>`p;4MeeC~;sQf$E{JB06@J*md93#$mA(j&)Cc=cq^XKg<U-np-nr)PMdv@}rkd0dq8U4X8t_ON
+p5(Ox!EjnxFshRNpLfcPj4XK(ns%Gj=H+*~^ooYk!LUwGISLq7a-K>lCc6)&6V<4$e0HE_JxN_IJJ?W
+gr^S^4mI{#1}W@;QW1@uoTY|HBcTLF818Ld){Pa8z<%lkdX+3K$a+;^H|D!QZ*fDTW-WhsaDtR0?Kg(
+m|7x{Ai}PmBjEih0OOa<>j8)t_t(EZk#-$B$6(pM8KN&z=P|F{#-nulX<h5n#%Qg|vEXg4<H%)UA||;
+)vnn%pOFx&&p%)kRDb@py*X62dg=GFTnmMjWjy#@zzJw{FhzW#@DfoYs)%s+kc!@+7S#(d)Hn69O(Zi
+=lzKCzdh&o(VYSz1gBt<KnRM&F&sf~7{*}?K_H4iD4fC|9HU4S-Nr!3r<%^>E`)}@TeG+Dxff$&djdK
+}_LlAJov_}(Zk+Giu~htd!O&aUEr<7#pzX$hMthnXLf@s;U%+$rwnBY-5G3#5yUU`czb+Ue$^En~Y^T
+XyUA{Y|zSUH>SK1Xwq4!pAz9-<fXW?kyNY37c;@}&ICvTV3ZG4pOX>=mqRZTY%u-zzjmAJppp11p!F4
+}!lJ)%Q%k~&#Ma$nGvZZ<({KIoz8nBZT^Bj2h=k@J)45hTw_Nmn0Rn39VzUgg;`zXeIKHY`uyR>5edX
+NiCVDf*XsY5Ju(@}zyOljhjkFuhQ4Z;bTeCI4AtGVm|AY@K2<I2YBq_m1uQ_1L1VE~Yzmq>0tfM)QNM
+*}+DtzZ%Um(8nrR&(jsB@*H<zOota-tD<bjW;h^5lxYjii^kC(yRZ+Z5-ye}7ZyB^K_m2^S9sTBd}A0
+O^{w{p{3BJrrE>ID<Oqh&qT{O`4cyG`$%RbpipHx_EKmTw1-cLQ<yNZ?C@O5C7|px?fc?I@ltSIji4Q
+s&4qH-Ua*+feWZL0&m|cPgf*!8&o#QWu61V!~skDbvzTO0<on%<k2Ah8QkyazzoW&S%m82V4^MKUaj>
+vc5{ovZ6csG^SyU}s1&{z0SKqBGmPxQG3;wH~*@0@^_LvzG$4Z{zXQ-#qARNgZ^KA81%?kDT%pIADV5
+?@uqK?Cb!q*2WEgr+ogsV;C7C6B{$Hg0-h-)TnfPQe-I*Oy)Typd`bb>UZxQeMW3n;*o5BwUsXh{T>i
+W{RWjJ~Q%m2Wz0~hZY*dq!ABo2aGJKv5468b8x&HF}5m{qh~VLp6FmC#(5l_ODQM1IVR#O7Y4$#-ELz
+S;1r9dDCNLCL{?9V4R>vs$3tNV+AhlpzCq^w1of|o%qY%J*yqEQ&c2{eiPp%E8{$T=u)6GC4sK$(NXk
+#NUA-5EFf@3=YyFXTF?U*d@I-*=gI>tn;mEh^lS*Cj(pDn8rYbGZ_|gJk)*tTYITc&&bs}F73EHXAC4
+LY_w<Oi4`s(QeIIqODPG+w^m^t337n%^^vq9@f1h5Ko8w__Ks@px9v(Qs<$$l9RzpylXW(H4>M=~py;
+2NuiI1c9wfuxnKpVg@F2l%wRo+>Xv2qrPuZv3G->+Vc9>LZm+4F(}mHGi!o3qB4qfZ&p@sz^^cJwu1u
+su1ck;QQa!k_A2yll`-bn^RAPYNTh+6p>W5)sd}en^!}yJjDS~ET@f7b}e}I(4%<1KTj|ux$g7q)~#J
+%MCOQ@FGD(RAL8}GV9pC37I|dD$q}AHzYD6y(NF@(3rWV;DtU)sk|pT^%^br+E>p4(4&$YHT_3oMsYY
+990_T)D{p?M3s0i>e;L}NLfP?DJ*l0mZTsw{LNpjt~LXx5)5v91fq9PK{*TBizw6zJ`x$#PhXF966Vb
+;nns{+?2sFMO_*lR=>3!UF8<${`hG$NxZS6Xk$D}mV^7&BAydN>7-pjYhiWEaw7L)FZHTIyvbxz4Mc3
+Lfe^_ocqct!~v59n?tLHHxa_BGV)AOxZ7Ma<o(SVh{x69El@W0(cxrZtS3`(pwctu0stSqI{|rGe`8c
+pQG4am#(@W!m)h7od4u*MMhM`XbcR-I#&{S+)iwT`6f-^2fCvL#HMd3Or|%^D&|*kdYLuE9%%^|n~R?
+0gp7)Y!8NF54_tOqEkI?QBWGWi<Z+4p;vU~zJLoz=c_D&LK9BHm$*y{LK!<xKBTiSvVGmaN<oXVK91g
+t?U~+~eDSL&G#DjR%Cr52=JUB+Ia5x`YQ9fS9_O^X+$2e_XL3bs@z&rCd3LXUXa58}O3P)vPilq}F!r
+4eYu|djm^&TSZ6md3CPpHaBRf)K!s2;1X%aK)`AC(&-hvVy21C;M)w>({b8w1kp9~Lc#e+atf{FlXQf
+7twX6XFbux3`C)YZ>;2(!M=wxVw*P*8ha~{{2}#@ZE3B@MD`agrV@p);C0lU<kD9R}wIZ5a`C=ArQl$
+?SJs|20d!uOr?_dP9(A?>eIJnM;z~}KuNN1mhSu)-t*z{=a3GE-=K?nb8B#~qTKgnk)3Dngd2Ga*}sJ
+`;q=YrseLDR!(-^LjO_Q^`&$k;hTip+Z|99|B{A_nnD0Bc(A%^MjCL?bru&2F-H5kAI*i<lDe<>%ef&
+1-h~Jgt`wl?--^t(Gbi_NP%fHD0nZXz=vElP5d`(1HP46t8*3Mtrq|u+V^uiA`zL;dI!gP;?Y!d`$uH
+3@yR}WLh)$643R?R9VKzP?LT32qnTW=Uoa2LqZ%3{&WjbHKYta5bsQ8+Dw!rq6>*j`(FOuo_AjZT4{?
+Nv3u;lphL#<ASgb1TaEru^&3JK(~!HCZ+2tMKpFW5CygQ^x(|9=j|5I$ucR+dY;K4aYMFx6*aZL?@2^
+s$|5`-i|WsWaR^m2|nt;&wCyCHp$>RGOCrqq;b|sv#04)e4tjH*=;)j)2$=<yV+$y7u-5jES|Er3HHm
+AJWn~hzfcJNlYyTj+=I^Y(v7)ZJ#0C%eX!N<_mQdHl*z7SD)rud@xUym>62qI=>rB;3Fu=P7ik>ygJl
+hC_^O{PSmp0A3C3g(S`UlSn`4>_$B2ZT1l``hbY5|)W75;jgxV9}HXEx3apQ*nr_v|1h^dDSv;<*6R!
+7sk;Ll_}-oXY_{;CjM(V7_S-On5UeQ8fq(?LEzc~2`SkqXtsSC~F*D~mvjICAC9Azz7QC6>dOccpf*)
+NQ$yG0ZzAZw%bzaJ!j{n{-}@=Pd}jyKy4b@YaQsX2D~xY_JAAiYO(mL6?w6OnWiVtk9SA!57K`jE8?v
+HT8wh{^_q_q4*XjzdL##|ErIF3bwy}(noCl<b)q$DTcu~MBpTe;u|FfF_fS%lEeuNLUtcOjKnrrh{72
+0>6YlmVK*|1fP1*vI3<qn0_POE^G^KTfdZrZhT|4?cj4dsb75fQ9k||Fy-Bpw<rLpDRvEr~Ymm{qV;b
+Fq>=sz#-3faqvD+yW_$vp%eBWW+f;gVO-HxK&iF%9j+brZ4`@ekO+$7#I65EUIMe)$CQL&BOp50rc!J
+Y1B(H@I&<gHOb?R8V=Mxg(;r$)H!@f7@4^<?wuiFl<+DJmH4PhF~}T&`Sl>u2J|(Jl>WeDIT^t|DkwH
+3{Er^FA2v{6#EX#9-CeuOBWMz*n1$9|wKqlWu9kUqd3M?QYb&aWwbVJ>Ns(uI;-3-yNK+pTyA3%6+>`
+e{4eXANz>H7hUuC9t=PN^WRxkYYq?oIOr=ew{<S~l)wVNV6gpDG8bIcYb<^a<`Sfjw$iP*ecaSjC0))
+bNb)`FWeQ+Kf`?xcFrDTXCb+44^KBj;GSq?}0|F~rP3rdt*=LPjn9QN+)etSQ+O3Og@O+sfFp9E3U!&
+s_FG`w-T#lGuv8Jj}6cL<phbL1d<P>WVD|@EAI+Bt(D!J1|kQZ0_D+Le;m)MFUo>u)l9P?8kml@oPXQ
+(5*oHEJcK=?wnaF(M#6^a!%t~o?U<C*88(B<w%&N^fyQA?HNEl}bbo^(pY+v7z+_&X8sLwt#ts?9(Vy
+5cKGo(@%bcKmB{U<VnUY#vx31Rlh04fC13*L)){oO-q#tjM5RD44U@*nU`)=TaKW6Un9r%UQ&uaEZ3d
+R^^KTtbTzuuYrvU85CvBcOKT|phoPF8yCbu*6~gj>537etv^-WS`twA^Nd3wxIPPOzypV52M4KuyaEl
+Dwo#Ae7W-CeK2ecM>nh%`##3%4hwCNBWe$pVIW@9^m7RSrZmbT-$M&8i_k6Adu;mfBvf{*Q=lpch=8M
+m3uy|yLQlSoqFm>_pAmj^?`g2O0OIVoK9+=@iT#h<Hvc2?3>pt@=I99;q(VzzIS6avFT}zR%#)*0FZM
+TT#sfOJ%2~+lVueu0e7U5Y0$9NX*IC4{IMp?_Q?&0cCP@~^n@8$sa<|y5B<lLMJaT<%R#YL`FlRD{K7
+C?V=L;2hO<e%G<fe*S%L(4NkMXA%4=`mbfw2UrxP72M2Cw@s_r5Oc?bHJ+V5a$p1xlyxZ9E!B9<kiXV
+<AZGpORTb|UJEUVk`Jn=+*olXMK@-HA}Z7?0Oi#xw!uL!GJiz+iHOSWy_K35AC*&+Beg_KW2enNj>Nn
+ig^~+-dZd!V!ytU68*TtxX^4GL#UZ;a#a!Vtb&j17m9z2uT376Lz}Gg=R%^zEqyT;1O4e0?dv`HS_B_
+ZH@VMU}Qjgy-QV4~ROwsBUogWm;vd|M&AHJY>96sWjm)%XLyKCtx&K4u!zRDlK*%AQ3y51D#Y%d^U`0
+|<2N7)=qT#n=N>OBq$@(3HlO)FKz^k<_GBg}wee7!uCQ!kY206Z^O@A$ak;Ob<QR$r$H7pdyS2L`HVg
+u7g%#`5fiF$o=%kgiigG=*?ceI*d97Ip=Mt*+mk3ml&c*uGcSj8#qZxmqSCnr)2oEBUw+xjz-UUMzvu
+$%St+>tK)5l6AKc173$9FP95`4M1Ni)PwKQyhk1nYP^oVMn@eH<%$;P34E0+c5*3>vc;EUFSEl1m-`t
+&$10fPcD>Jb$p|o(<Xa%nOIRa?XmV^dSH`qjpLZTtrXW0w<zWnF-$yk#c2hCI0UgN_jDjl;3AwO+aOC
+4iaJ+&Blyu`@ihxc$l`5GqfCXlzL2=Y+ygxqMn6yu?JC6Wk`|^9gm>uGL9}3M`Ydd}3yl|CB$e&8Y<l
+Q-AANaowq4<9XLjCfjUqLATa|lI&2trcGhDHzy!blW>Nf^Z_976~KLg8)1r&)#=dy_VN=ZtB#7vqq~P
+8fIE2=8WT2)b8kN6B7ZgMSX8Hk=f{{S8uVr-J0Wt~-nO2{ww0MmxXVCPt9AyIH<_y~J;ZN&ZqZ<~?Eq
+OuNI(n@aAMkl8K_gMm9RLZH3AhsyU=q0~;7Q{tTpf%jKU@O?oW7v9#t{iEJ63wo=GVLM^{TT06AJ$j+
+|BZMmT7o@I@B9;Odm}z5NxxZwWH}nMjC-7-UPr$F>ljZz9eA<5p{uB7LqbJ}u;FGY!r(gLy0$+r-?1X
+zt=izY6+<OY?=dQN8Y|yUNGSJyWAv^aqtu}k*B)Dy+dYUJGs+e*pJHR@0hrXqsYd*DH`s&A%E$RnoVr
+d4#ADWsin0;sUR-QtRP~_1?o%jGI+im=s*J7Fii{CM4mi<~m`}aayKkIA(U(&JW%s#feKp&-GWvPXFx
+nbAC%vWUmmo15JdRjb<K(+}G;W*wfldZO>(!}_BzpXHfiP{}(-98ViQ5{;>(lq**csJB4Ucq>DTjE}-
+Q$m+C2^=iREqQ{TE)pxaOV`bys(B<K88Tgi=8TQlTHlUQJ)93LovpgOk>K!%NNxPOA@o1sf~vvLs$;p
+f^9KyV;BIsEUrF0E*)z%hXxjU2XtytB@rT&N($DeiAD;Uyto?M}4>1j-ARMG96h>i?geizbF_c0v82d
+DaeKB#z-+Bid=gQt&X&Xb^n~&edEE_ij-<i#HPn>=l!}gXIVwa+VkUggCfg{-)gSX@R+|j<#h7fz)f!
+?){=v%9b*uv1SDr2^&15^8%yDGwan=eJ*HHz@QLgH=4MaBP3pnFbsi;COvZ3P&-$I0!){H@ZpO|mgh7
+~C6<H`=)c<1M^xOpuEHmIf9(4TQgCO4UpCqAufbzSSchX6~n|+K%&+x1;Hqv%J#RZ&e?SI|MMb!GCWF
+V7G`b)GP9>J(sz=xk&Lvk@t89d<}Tq9`GEVVoi5;-P&_JcJC{er!R3#-X*K%pW@i|c#ERn(?I8^obB(
+d3ixbUf4i#h1fqezcsTwf5dFMim#5Vy#4++poI%88bOQ9iJMQJiVN?uQ(GX@34<52bz1>RzxxB_Paq<
+duvk~J_7Do-?l`_e(j9-+9x*4Yy>#!OkhTIA&1cD{jAIsD5&My@08PX!LBIgcEa#U$Cj!spZKwL<-?a
+TBSQ9Hc4<0}^k?a>ZqUzP}9Ue2d=q#h+)7_}4EtJ-L6@=y^+H0!?9q$6~xOJ{?jYp1HXpf=~U>lzO{f
+{)rdPr#zw9M}dg7DihIF5_}1w;rxOk3FlMPHdBBNoSTXwh)avn8^)GElb#y?DmC5;)8Mkm|6<0z|8p`
+t=z^ISnx(WZ8pm{dFo!T*Z87Yl;_%>KhZQKc7ud>mY#A!Zrq|dQUE)$%Ln^9(Y=LI;_WnL7Op>qQN)5
+c1sfgGDlut~XZLVU1k^3;VF?t<u$0>%NlhgIPijN%hT}%lYxVD|tH_LWx>UOnMSpa;Cu~4-Vvh?h6e$
+jhzTCSx#NAB=JxJ(Wf&hA|MK1S1qm^Hvi1t;qu?=nz@q5qnLYNf{0zEE%Ta4?CLFb#5y9H8()3p=Hiq
+bM5J%xSGt_VFXGN+AhQXAqZG9rmxyJ-}U=CPh+DL?6;fO(!$mR@h)Nw3}Br1W`~C!iy;QVY}jGa!8qU
+Zvy!R<$_F1@<(XGF6z<YZm%zZ@bmd;gVS@>SDSNOt$?vpfVV^pVEWb+zDg*_`eE7mzwy?I;FqRMBrna
+^xH0}KD{JLxa!EpQz_r;XJw8!sEd^8rZHa<og3o}G$x|=vA{0}|58nwwMbrOBc6Lra7hCmd&~(@<t7Y
+2wH)7etzkTb=)zxF(R+4&GAOPlErXc4X(S#AfmeglB-SAnYjjdrz#rDustZXs<q1`1(C+u%n`0~v?DT
+|J?wGt*%BKc;!9wo=4ytp}`XS_mWwF_QNC8})&NjkupsXG@8hm^x4n4LRb$c03Mn>mmj#34_kXi4sMK
+dQ1#XhFsT3ALCT&*w%4)XCtTb!XJXDnb|#T@1wxGb_3ohZ#%O;Dq4GT|}w;6n#JJRy#wAK)Y795ng{#
+W$cDleVuEB)RGLc_l3&RyQnjIc%Rk!9EY$Z9hL=`184ev!b9gSW3Df&K?Z!qeH5k31E6I2iJ830xoI=
+<;vy6x%_JlA5N0$$O2Z$GlEp{Qe;%?OMz)e)ZyV|+jnoaN5^0QM?PZ6#SaAyJ}F)aqWy(?n2iaElN%5
+ojT}b$s98Z?fUeM{t^#8hOk(+$I4%4gX93MM4$yW(ZzK2xb$!9V$kQ~lnjHoZLJyGt6wZ)Kg4~tgzE>
+V+WlhPaUEgANcDPq}0Da!a#ZY10uJQEz6mnD+f-X4W&27otM2tseLw@c$k11-G5Szin;W(xuK1k2<b&
+!Eb7~3hW=X``J;z->s^cpBOdAM#DeZb4Q=x+TZ)gLAa&Nsf{T}-8Wr;3g3k6F{41?cjpNfXeb!^}lmL
+vnN)i@JdNh>U(!{DUGmS{F9Rlf0hUj(o=K`Au-ect1zKcIcEw=^ttKXU$o%*PI#dd&D->if-%ADbfGI
+dA}t|e>LY1MQ_wbK0yS9KoH!CC;Dl7$?jQ#?;R#swC`*0wxn+{mKfeST8!^dYu}I0_98dx^Fn4U-fPN
+m@{P}uz36N=IDN}tLD>%Dwg=JM!Y@zuJ$?9X(Y-;$U&@r`@m|B0CGRXMwD&jf71rQ>@-EKx#(mqGled
+3gg6%kQ=cI1|nT`5_@7%*qpVPgxIm`Esl(z=fd&0lpwI_DUNquWCk-79-j^c_%1pg^iD+2SIo!zb~=&
+)`AYpaavtGgkpzortEm99SklT-<Ybz_+H3r4Dd;9?fxuHpGz#a95=V_bgcgF0)f>0;vB;!aSmk-y!cO
+1k*E0?iTK_pDBM(V?Vq3wNKa@s{r-raoj$C&QsZ&DkNIhVC+^fVOT2cW=LsgC)ycx$j&DElsi3VAaY3
+(H(yJsi0Zd)u!(n>wajQW?z=Nm)cQFbg`}>%T%HLLp@&k);s+wVgtOrN~VEvs^G1L<u<}2EBV`Y%ls%
+}4&RdsdL1C%vQ6e}lfj`ce`f~%4|<bneSAjC*o1=Z6%V!qHY^p=A)K(NkSAb+Kk#*Bc#NovvF9@;eq1
++fNXdFJPtTWvrg`Nq0ZmG{p9cAZ>VQQQjNukDj*J`~g9Q64Rl{nHQW5+};```8MfylFP*$=lak*;9L-
+uWAc^=_QbRP!^fW34fr{?;+hddACiRzlzc)m*pZUtvoqy|k<TC&i=M=~<7XVa(jwVbGyIGb+$41GX?V
+$KN3XPi0fc?_UXZ#C&8^7cZh_Cf9y1sW=ldk(f?X#HcfQlq{3eYVa7egO>?SQEJA;OB`GaO_@XXHsuq
+witrYO4gTsuF|=t7O;I)_u;J04AKYS7%B5@H5l_?EEe#9EX|wlUfP@mTy!&{fx2~S(!+f|KQFX=^rDc
+P-9Ez`x<lt{3AR#Nso6Pq(*9<yz=gO$E$Apui9*f{SQ7H-@p!2+Q%&r#o0BH2RCQ)g+v1N<kb<07D^?
+y)i8o=VG&%zI%}^<iWCH3WCCd%6rzdncy;xPkR>hH17S>Jz%F{<8g#A|r_AYml<IyVwskQ~>4yd|vy_
+t#5kr<nj44+^#@1D4rr`w^n7Up>{6U;I*(g`<qB9FOm+>uJv9HUV<FGhenCb={j_DgV#VP-8%<(h_%C
+MZO7I8KtV_Jb(l6FXPu=GmS2v*sC62@Q*7Y3PD6z>93LaSh1Rwdu?tH6973YWI6u@%8beH~FpA_A}N~
+<{T8~5@?}=vpkG|J;B-)cY9ysk)PCT5}#uF0N3-1?3{+a4W*pb>i^5!n>9IVu3Llm{0iTz&&NESh`s;
+;Vi1T~z#X&1D8$UKZ&0~vm&;Yh_CC8i+7ZsmM1WppO3%C2Gpr?SthOUi;2%^femcht92Cud5csnX^O~
+b~6xlFgwa8AlT@@I{ZmQ_Il9iR<S-jX#AGFPzbFS2;v+%<{T>)BRlQea_fP~<Dyso;0)Aud9-dl!Ivg
+=J*x1}In0~=_4+$VQ}rVVK=D$`_W;*u7?d&XT3XJmh*ulMkZIH1UAsWHu#MW+^h+qotQnr+@I#_cL{L
+&BXf9(OKIT(plhQh=8*bi(sup`MmE55`A}l_kd9pV3vOc8;gNp&h+AT*n2pIt#tUdfrn$2dwI;J5z*!
+Nw*Br)SpB<aRs4n9L2wER=Xh&_a1xNnpYfB7aG;RFYTo;p}^g4P&&Sy6BFiI(E+!zDdplE;pVDzO6jU
+?7?gQyNU(2VdUUgI3ONm<RyHadJn5(YmRA{a5YmC~7@h_IxV5m}xsFxIfrW4pIpG-Z(F)3%xPJ}a0i#
+EPuRq#1iAZ>2P)xaL-TonedfVv8G=OY5com*K!CxQTP}nzU9`mv0u64g42`oNJdZ=)Iv`<nS@6;R0<P
+Cf}Zx)J6f6XM|q(?yr&X(%>(ky7_H@+DvN>c2^EGDBmlv{LE-D;hAS#y#UF7G{{R!!VuIZWaU0;t8Jv
+Cr#GNWG*Po;os+*1|QFfQkBz&)ymK81CkjHIU@I8&dDCY#k&m`o>S4p0+J845X{N`8}_uZd@vuY1D8n
+^H2(I#<?Zzhmz2@RrSlZ&WmvV`vCI5Ze#r$fBvt}%-ILu^?e$*zj5IZ{${QHkk<Wg*8gGt&+m<I$LYV
+AUibk-{-^K#6-fSg-#_I22nfM<<VYYCNs%y4qd1L`hoUNsAv8+k5RG62_0u}W7ubj%hIhm<Id(K)gzy
+3Au#d9``jH3R;oBjL5C0TYW*@sdlKR-w$Hy3Ph8=0S`12$25wqEGAx?bqi1>jB_cM<PhvZjUgVE7~M?
+pv9$KlY29^f$yk19k0ANuwCV!i;zBs^w268xC?Kt783`+{NkBYaPO#CM>Ngbwrpo9L09%>L3N`Wzf+B
+ptuC)}<2FcoJ_p&vV6U%z#F(jsCL(3G`!YondqQ*I0jmE8p<6ZHIZ2#G8-gvSTH*+LDVq#4BrGOMX<X
+cm`zSt8*OwL0!om`sql)cM}EQl_yji;CZcz8xxK!Rxnm*yK&!x$b8=6E~0Yrs&NkVMGIg3!!h7qe0eS
+Z?n?o_zLtOYrF`@F`_)VNRR!gDrxG4eB;tM9_kpR#OAXP>EnVNYDO1}hzvX4)J)U*e2KI^}ELKYb#+K
++x%I(cX&Rj#<H6W~1*u&8Ij+KS3N+xS{&68Dq3O@5N2|?F$D!UoDhw?0YJ*alkS!X6IYJhJ8K`90Bqi
+WqRB}gRb5;R7c6z}bsr4;;z#mqWU058zjUw8rkqJqM3u7%Y2qu{d}C<D%gWaar3KL~n+&0e}(5le~1s
+geZ@D%#lft0!*uviN?LAt)e&W*j|vkkMKJNK6gTOru$?NrGP4NEOAKSL9(hloft@qkbUYPq%ld^@<n-
+{un=<DWgG-r~ZMW#P3n<GZ366-}CMNa6JAGKf@1E`G>pz(UycFA(VpPo!=uEOyeZA|3vN^DMr9Bf)Y3
+mV?XVB-nsK0BV**yP|eaKq8<9zAJ<aoL;UwBi(>~lKRVv%pN8i6Q<pyYH}nai=~2s#Kl-wJY>dc*yCa
+_>OZ+JXWB8|T9PVNISA0J`29EdL0w+J?%lOgRw}=0o(TDUg@=S(D!6u=Pr`b=7Kh<RXQzJS=G2r8JJU
+UK}KF1;Kc$wj61Id!V<ookM1c~RrY)Rg9;9Lti=Mt5jvbXD;VAB2(+d_ve3Gt&X$v+Oyz`q;Q#IJopM
+@$pSZ!yh@8~1pI^3PoV2-7^G+DDy--@b-v;1352miVVH3HaHT^G{w9@Z)RxJ1^<`enH?b{7lTNPmseF
+b&;K#4Mf<l*(()8t+vN{rqMM38i>DaDN>9*7oDw*%{1zjl|yyKZw<@{Z)VN?mVPE|%y$UyEoDMxH~P#
+l?WW%tu-m!rg7Klvu96$eiEj5}Ty2ZsR74NYERKjbig9oXM_H@7o~5cs<rS2W4Yx5#d>9>|&7-8N-At
+>+xeW<wj<8n%drwe-15YPtcU|XFLeHd~BAHxEL*j6C0lAzF5uNf707`amvRfuw@OX{1uBv^lk(hXTdx
+$)eubih|Rdr8uYH1J#j+}5%8?3twImjyfQ$_)iaX0KyEk@7vi4%sUu*c>Wd%qliW+g1>A6YSVHIc#5A
+~U+zKlwJvF+|<}#;|h<fx3HQTGXnyN#-x>S)wVYf;aSnZ8(Se*=f1GVQ0hDAfrgDAFzAfd)|zSGeqC&
+XZHk1H_@a~zSIS!m$p%6u2&SYgF?%DK3jbc?JsFyAf`j&m!jn?ZI=A-Ku*boubyfNz&a?5kx)XX=<Y*
+i^)smFI^G9Rk;*zKlg?vR=}|;=CiRN_Gk^DawSO@*bkYKIgmj<_voya9VV9@KB_1gkym^w>s=YNp`Z$
+FzBpz(l@|(h!lRBtDwgrju;fPmko_y8-CUk|joI|*a7~reH?c|ot4T44_2YOzSRqGz4$L!QpI;#<wPp
+~B_qPZC-%7Py>PXKnGAcO5n!yhN!{>Ki9-)X#hS{4|Xn5*4D*l1}D?h978Ts8glGeZ=^|1meF9l0^!l
+Mv&dPuO6t*MR{ic5?^Ul*Q`xrf)mG;TaTDXD1~a`BdED#7yllcVCZS)9j_ffcsLj6r!GH3XclVnY>&;
+_>JnBYok?_gj;urw|no!VZMfC-R5DEMcMCLko%=}o?2j2-%XgTViQXcj5a2OrdU^1KKO#_Q}Mj$FGP7
+DriYs`flakGrs|fe7X!H#$$)7lfUCAD(at5i1tvs6kQ#G{`R=dpY^Hg}>26SG$|<43k|pNnjyn5mcYA
+0V!I`+D@&<6p8e3sW2XgsYiEd+g$?oF(D*E{TT1sj0m((GV=6ckh1QF$p<tZZ>vl_RM!O9>5@Kk3Rp>
+9uUo=;NQb7c&jPcLt-R0LEq=e>y<m|v?T>u`B)a0+zDwL!AZx?Z1Z-2spj(^`|Z_q+L)DR7c0v5>F#3
+r*lBwM6FhUYNJ^Y24KtH!)NXzq0q1Zx2b$!eJvhKqsjQ<*f3w_K)qJ>K14h#9)9pbRx#^Zky&(i>pWk
+0zP44=&1bw(|59>TTmPoTLn5fpaZ=x?`6wHmmXWjoHOt@>XP-Q+-rMBiX8Qx$h_`FNfRs)f0ax#`oS>
+7w%h6eBw23D&5kig$~uggVMlvZF`EZ*nlQ*Qg?lOWZ|r^x;&Klu0(4K3b6Chi@+P2e|0VJWpH0}k9~5
+L@14GL9KqJuFa>F%4g6o{LSJRbYgi$?i<cjF;3*3y2{hjUn2fXEJ6Q{pvA7mC*=^rXGAGF3-I|6*S&9
+fWRA60Gs1NZwTW%I+m{@9MQ?;se2ACnjd&?7OFLLi!e5dy>a12lnA@cs=-!U%+rKP~!DpNdIDA8Ii>Y
+C?%agli}5JJ5=#qY{)+$7~t;fl|@WHO1oWkoqS-+OSY|oW3*Yqe&(?G!hPhf$W%=z@kHsAAvps3D_}i
+_jQ!+PaqIU4@?O|$Hd5?DjR<mgMA!J@k3FUN<Y&h^pOC_(4$Xse}WymMjscv{h5ybo=?&N3XegQovR<
+CCdkqLh{1me0{f%rgMZ`a4nJRAtYp=)3@<{RB*S$i`?^1Ytoo-S&_~U{|DiL+<*`Fc0RB2Nb}fY_xZ_
+1&u{Yl{UlD>oqKosX^#DIXMnZIPi$vT3PhBm^{rh%7Rpo^p7*$_nU%t0L`Bv1?xPyD=u(mnK7ocbS@m
+R61@ds}@$1ZqO<(#imd!unrs;Jf~iO0XJsuucv`9IcfKJqYt#Jl~D3Zb|@`j7-Tu=zk`<FCpFhAX<G`
+@2>AS3!pFOEkb=I}Yd?1g<nI=n1z2cG%BH))`pZzn!xw*)beWr2gr#A(MaU94Z_1@+xk%T0c1>%Oi*6
+?BMZU;5(K|ly(hZMOFHGjtHpi^=?T3L^ingHbeN1cr_0t<r0dbf^`u6&X~cBzk^Md4O6RM%*ig<@mWu
+ra?dW?8O@VhE&%TQk{ta-81(Bz3S-FCG6IfWBKq!1vKLZI^Gqgp%n+xf#YTxcWUAe9k1^aL*jEGK(t2
+hkXWrUr)frT=lc9`g7Bm}Gg0$cE=F$bx>}X)ZBzYlHN<1@nIo;pS3?p(k0jQqf)rgfVFWKDLvSg8TbR
+?-zb9q|Tg^d@y<aC`xt1zJ*<-*Ke&Ar{{-L=H%Q8f<mra}t!g^{I)+@HvvzmQ?bh)}+aFTIl^iB8I80
+OPhneT(eQP$go)o4S~zi7QVZ0aBmJ>{preEv0gg4P0H60RzT(y?K<PAVR(n&?7kSdta#*+C75%VsQ&9
+%%zIxQYiw|itqL5nx$Znq|Y)aMo*gTV0pr@IzJ$AU+#0;;MooXqdt4F1lHJ{=cPEJ^-;2NpqN=l$W}9
+QpG{RvZwvRE?LIzRKkPYgaqv1&gX&~V&r8UZ{(wvRIlnf#wUKSM%`8Albh>$<rSKA4`R`}7L5Ad^NMm
+k-rilHO!4&5?Tdv2HdOV#4&gDESxlR3<?wa)u;NY72A<RSb+52OS=6k$mT<TY!IVif&p)Em}e`-A~81
+#fc1gn1m_<ktzFkx6Pw4G%l{89`1Q4o(9t|5SijK?n$J-^hN?Q(Y<2FP8b(*`V04q?l5e!SG`82eip2
+CP8WlCj6KdNxf^uM&Z$NvsfJqQy5^EwAwrNfcS@(B_YT!IvWEHtBOY&z7<C7@P+!GE112#B%EqZ`v}v
+VajPl*iRW0$(b4_48l{)8XI<e00{ly@}qspqKPN<CoJ;VDIh_?TZSQW;<n38-%kQ$T4fMolJ13=HYKN
+8<1^q$@gjgA_X&UXYu#&3Ng453)%X)S6uhIG;p6oPn`$U`R#cR+Fq`r#Orncch!0Tjn6X-PV7ZN`+HF
+{J=RJ5~f-w`Vb4nA&3y$vj<SZ}uru6&gnNIZVkzbxV9}G$Dj|9Ff?A8E@Q2FG%${W^aNuY*1Mz<{C{3
+77^#jsJKJvQld1!t9ZS&p*z0EfO*NM%ctd5gmZ2fP?sFaD?(XBLImD{l-dFTDCHN}rJH31Ba-8-xn-7
+}M5^F+h|<@{ypnCU0k7A|s%25vRMtIgThy(q1@DI;<iC8Ot}TQ^2?Hi92_apIw&3!DY>ac4@R{BG5)f
+PM~i9=jk#RuE`aQMYJ0@VTC82JUfpzlZCGI7PxVK3Wg@FgI4AVCWs)THiCev@6)ITA~1r8kxBy_uf*h
+<V0^>nHEL}ex(F&4FNk}RhKD7&T8_S%0DU93iGRoqIWzl8$D#ldy5me~OkJyBo^WB89DcjZ+#-Ysr{L
+}1&kTypPP&-i?5p*i5%A$Ahrl~t6Vs|nn`itR6NgD!@85(?@|&6VY50yGze!C$JcscBZvB4M5BTpteC
+w}J@PD}N_o$F0D43)^5(pHG;xtM^1h&IOgxKLCLL=lMiSSdi0s=q0-0A3$4xor*5aiGtfR0w35IMjd{
+ORI3l5RVE`+2PfLJoZc2tQh@v(M1%;i88fC=enJ%eo{z;2``#cj*VtB_9U^;#akr9pvH3??&%Qc-#U<
+4yc;ZhX6tZAKg6r?Gog;BlOW$pbw|Mqt$4CR^l_HyDue54#;^3G|)%&>G0s&FZ}C-;Ojsg*!nFYc#At
+*ywMy*g}0K*pg=0I>}P?LWBVTyg2&vzA3&9Lar+(G?F>xacLD7YT-@RK-oN8Veyajv#C^oI)=GRe#;E
+y9ME8TR;`IPbe5szLub?Wjc)_xqqY21Vot3p5=t#$XMOW6Rm3sNT!FxHrzuEk(+0J(R(%=n$9^bwk)8
+KZFxE;>^p<fA>et@x$D!ME?F02ZP7YhGwR?&U`{vwRQnY98>s{r4Vi}1|KQKLbjXTl%w*r*3WU1W}Ve
+uc3Y=)pQ=b(l{%wxE9VH2&VrZ&m+EACEMhae}UZdUl(tFE#nv7+h^r+bETn^U7yvVy^R!;ogswyzhG!
+PL{G!djTbgbAK|0B6#X{&I6cxIfKMz4VNalj<eZ9-WVc1X<tuj5gKV@UU0%L@HEHN`X&`(BHVo1Zbn|
+<Pslg{A>C#WbvK{FSU!WRnWv$8bDud}S6mk&zEeF$WPXz&MYpH%R(i!ti1Az`D(V~$m<qh2TlVhCWLS
+_5lwJY8Z^A){!m4Z(EO<K$We?Z#Vvj4R;KDmtFem}#XK-5AGOwo@P#&k-8KxIcSVyDjUr%4WGQ=%d+h
+=-)7}>D(2(KOl7!pCeqX~}o?MK5;N!?JThDN~kPMXwff-m)$M$27IC-$l+%=0EOWyFQ$4V30G(=eU_S
+$(^|DHAd!(&eNV#+L8c2bj?@A^#c)2B-RV#wyJkV#%54;T;UOO5fNbc3Sl(GqX~xsIuIYu7hy<yK^0G
+w~hsvi|UNFmZHWKwY(!<3ROPw2=tnjI?U|z-MCAE@7~|#bj37`$}A{cZw)CD+QS<B4&VtGwb|CMabCY
+``NdW5-braeN$ToH7@%|)QR3}7MlWMiTFrPc@5;s^%;8;(k;FG}M~XsjQ8k4ZlV*+HxMHEt!bDv2iHN
+AfQ+eOo@@|~<<vqPML#f_$$LGE|goYt2`v%&YX~>Bfae_2xK`&WQ`mXCYfkkL$?3AQR7Qb?(I_i7CPY
+Zm^OOl8nf60=fo;v$ZxgPO!waL7WKf*rX_Zh2S;y(Sw?!OKEDOhfu&YN3EqueCfVCUJ?Xp94RFm6ou=
+e<-6hYw$EWR&pDVPs@7<SS=YDO~fGReOn=i{k!<rFtxO&QZ}6Fym|>3S@YI@Tz-xB}{I?9HiO3PYZ5m
+n1jgHIW^9u<PTNmI!gBzZo*r3?^+eUaptZrVG#oR-}5!Os=nx8ypGz5Dp%=ICYQ^kGPHj-+hO61mla7
+mXKvB;eHHYxgFX~{wj3kqbU@y&Ebf%S1d8k2j_tW97v*Zwe&P3aI%g^woDu{+Ir=%{hS)49%3o5o0iV
+&t2B;2fTP8r_6y8YY{$OUJq{EXy_qv{ALCQ2@XUMBmPN;^4L=sy91HTG55@0q~@F}ncpkQ~ljB7OAdt
+2AoIxF3sn&BX9Y83f$2eFGXt*S@#eVw{x5vCb(PagMEi{ba>szLyG#YK7#nVr75s`O~dejL}k&L?l8z
+p=%`t2X^zv`;6U%qOXD%BG60lo7*KvQzS91MEd&n@nWv6ZyCe)>UFTf~m5ar1<NAvzLY~Uxl_zE&qCj
+fraj?%0XfVw_GG8i==^2e@0a2>8kyRh45WhGq=Oiu6k{CNBAbF3zzmb)Xp7SL3@5Icrxyc#<pG)#<Y}
+w2bLLZa}|q~iwRwf!Zt?z#t1OjC$rt(cwwdaylVrfDVnCtQ1DJi=sWZ$W*!C%P8@(h1N$ODW_|tlaNn
+T{{r?i~`%m2ZC%Es&+x}7iio{`@rf?jiAP9#k5+gB)#4rMZU<}7`5=Ci(_!;mE(<4EK#YgiDLHsw0f5
+fjoP>}ja^3&*N9u7S+YZ3HwV}bZ+4v#;ADLby)@fVH!F7bbqaX)ULRPwvI^3n619@#(${%?%>1@J?&1
+FFUG0ZOrt$o8RGogB65Lx!3>U>@<wRPHD2w}wCPl|+vcH1a9;LfHWh_veel<F&x(kqV?gUd+&6CIQdx
+0VR@uHR%MXl@wm)-;j4CO*VK>6>$5pRbpfNADeXkG3YxmAMkI2zAsAE-@2ZE4*HJb?xOw?^c~0MoBIX
+y{bAPd-vNCG<^%p6&}TXt_qDJK{0sE`T;J-OycL&A;QNwSgG{^?TD}b&gQ+SBD9U?@Yq(<gRC?%ZDA!
+|Wk*}U*I>~!vtLtZ!dSxK2FnxFFc;{5kNZ71ZV{^{F9{`pusx^=2yq~}jsyHQoiukkBbz(kDFP6Q_j2
+n09WB7%<74W@i$5+jc)!cVe^Lk=6=MIG(Ro5r9m7O5!+dnB(0!)6n{8`^BX4H#uR#`E9Pep9E&$-K(=
+R1~7<3{JPg^tC1<vl~2k3l_)=pE-No@;1E=B{shL*7Wjm&ZDnW(7(^mWs@|6{s~I?-!nrTF{u!0Rc;E
+t^v(rA-ZsT+D!1uvR7ZmerGveO<rRgvtRw+pR4)xe2egW*Wv5kW@-N^ko<O*gx?qfA$H>WX)OH19L@j
+YKHuhM{@r{0A>`8J9#lybp(varNMtA8KMSu|dPKW}S7S$z-GkBLwES_1Pd|1n(MO(nkFD^|w9%jQ>gZ
+s*F>*8^?g1I24+4wQpHb-Oh}d|16g&=dnD}e6OLi1;vh-K-g5*b70{;k0d=wfY<Rb`;9wn5WY45@J_?
+jGjKm>L~*!?u}GyQWEXW~N(i$o47uIv+D533mHL(BL3{N)_<ML5DM_>EUf7nFNJ(`k&vpAXhJ-<4E=u
+fsD3M*bQ~Zq8p1l}LQ>+5^HKUPXBdYIi#h9;(m=R9z&VN7TaKwEY8i<9-)_KGXpVb<sYmfXNpD=z@WP
+J)nO(s0#cK;#{t+I?`->m7(UUZzDZlCwhQCjr2U(OX$gi@3Cuy1p6-VrN$!hntaRzX@!KSn=xxe{%Lm
+s{+_@yr&RTLBc_6+LJ7up(1?s2=L`uA3=d9XDq=I%H*X`|x;~afkzW{ZzFv1Xod%0N<5I8V10B8cn{@
+>p6Te(Nwc#<uFjOE8d)o0Zou%o5b+^}qo6~I7=lN=fPQ<bLbsUb7lywrWT8@<+333lHqdS3v`ZT)$S6
+UkGK1`fT;vTxvxhq0{2dji2sj9Ysa#<uGjPU~=TR6sH5LjoBUPmSbn#=~{Pe5bnnJuvVBD`-jDn;^rw
+G-B|TlBVYdz9wSTHvjWaB;FBln9IOUkRxB@BSrGk_tWmkD&6YW04GvDw6FkzO9~cbcA$*(Th&O!}^3j
+)?hO3tMsZkI;_<z9jN!qQtSPQL_kf|25s;vx|B4xVVFdfQ!#HQGhvaN1UE>6s5f*fDUg_yK@}RWl-hX
+k)X0ig`Md%FX!ycQB|tv&A@6xt%@d)_OXdaj;A2%NpIHRaK)Qp7TI#yQ8~x_lz^xMM&GWs}AwKH8Yfv
+ZrYF=o{dm{4bmQksmT;Q-DA1fVhqs*R%>tcuCiiBn(h*NpZ##xML5wrnCqL#Zm*{h+{gK$-%S4J9?Bg
+yqip|2C&tj~^1T!C6tLQD!Km1s8D=Crz4V>(X)KxifV<jSzZg3?GF@-Z*tDF-i;lRMK^X|Rm5LwmZ5_
+uIXsYnN^EC6qCgEk@?)>|p0+>EZ>l3L$mklPt~SS9vT<oK#8d|5z$9t1TVhnu#%bL%NB|#K0hGBKLTe
+*Nw5hFO{4RHT8Wf-4O$;N|*Zcn8omUfX#W(@Bil)R&WwPVvf;0YQE0Cq|83c8jiSMbeE6^l!y#*U1>B
+y<1whKHM$FPT+{UqbiNdB&v*eu2sHU9yQ#vw@74YOtd79W(peRl)Xw(+cHx<LW-I1GF*{-@nTvD$+aJ
+gGf6u`2K$No&=7KTN%pzYNU?7HzKPP-{kh8^cVZ^Z0ah`85Im7MLeP2Dma6F^^LQ3-|0rht&FiTVz>7
+6We4LtAmP@u+WK31~R3+%ig+)#84!QT~@%yRw7T`{AG__@Fog@^n0yq#f@f#5JKY)#mq1}#%JhGx;1z
+{78FmG`&wlJ{8<VQ45<270zj_D+-<*j^$ox=OE{Ba^9O;#3SH8F*wNt?3UYy+}sPb*Ief@jNUISPs|`
+eC%|!PtLls^ioAo(~)hn^e6g+Z}78{FkA=R3`1@wMjfcOQ+YlgBu;xz3lcQ9_Fa>YOlvtpHgf!_6cBq
+dJd3r3bKoJB<)KT!1N;sZpO;XNi>HlRXH>hA9+l!nQ6{*;L=**Af_!J5>M|A{@g$U?-A{%YqTNQ;yt@
+D#I=ys0HTAg|&1_pnDQB({eMTzLZElVoih^KZV|reB%7SMBWxK4F$Z)chH13fBIQNs<B59<EHeb_ms5
+7SjYL(<2Cu9Vkm}+dW;@;60nMpvX3`;>m%ax*-3OOhFU;_9Oi7uF9r!dp%Rdz_^HVb#y4h&84$}aD_^
+kx}saML`Ime`WM6Rva3&FtaMH@=&JjOKW?**`fMDBsSIbG<~6QQEcZ`THBx^+4*}yoeU>hQi+8PUHTc
+6Hc#8lcL6ddo=LeIr<~8<@aiwuLyWY@7W0>S=XK|-zH4f9Tgk8yjytE$spx!No*{4V;l26SA9-XfJ@Z
+z!5ZrmFDH{_I$Sy@F%x93>qbc8;{I*OIUUV2f1u5`|ND6yJ3pRH_}jVtKmXTtNPcuH`TJLWg_D1};(M
+4#pwQttLc$n?&^Q4>1cK4{jwLZ1KIUeQp==tZ5R}6AlW6Q`7;=YdhY%`!44dG{0rGalg`uAbn)K+h#y
+`G$@P`Rg_|NBPJ{s4D%Gal+bM)pQpY9*xBX5Ho<KH2AOj+;L8~)fk?*Q=djrx`A$kAC79qrsmd|Z#9N
+0H|6qW*O2kl}#_N&4s>O7Ua321AaSntkQR6MVXO(&&?MKtH}E;Zb&q@dH4T$$uy4Us81LqX%~X)~6HI
+9d!?1_Vmi}fVf&AVUTzY#qiM1e>7NAXTaQkP_Kco@AOGqn@6foud#tVUQx~G211Qjeu08Bwp<Fv|JMw
+O7ko~Xc$YhLn<IpVj$!O?D$`uNsWyY|*b>r&-&LmfW59O@=YMB4!1v4f%hibf%rn0D`|se`76d@Sc%C
+^+oS!p%;IhiQUGS>hffG}3EpgSrs=6CqM$0erJT9nq)`qRG2AHBwJL|kczyv-Xa_jbR>qc?ISzt0e2a
+UF$B(j*o<7woLcxvc~zhx&wM;Sy_-|CpmuXkEY$HtptY+_+_W9z)}Ge3u#YqV*2u7#ei-RUyO3QcB;7
+>N}1VcWppRg?bV@6Uz%o*5X@47fO&xRWSiry8?d_FW?l7o9dPv%J#99ovux3)-g5U~5Y5<AHq<aJq#V
+ZF!E5^bBw)ixG)_X{s<(`t^YnpcFhO`!3J<BkSI!|C(c#$NY<N_4C@iGaPPbJrruK{I>WDaFOlXKMZO
+AJe>WrQ1+8BhEgPc*pwbIi>6Qv-Gdmp$2FS7s6!|kqA?OCFdF)3LsLI(H;kxbv<@XdLwp}q=RG!1AAY
+%i?$eJX^B0Ne!;UEaxp@+H$leq55qkD$xYN$VejY!13XcrmM`-M@K>9Qd(jSfK{W)Q5XWhRtPYMskus
+y^Q_%Z#mM<e26n?%GPdsY0%U{cU=BPcma+9CW&WqwpALi#9+@5c|3Gx*3!9{P-*Ft$G{u}8$eG|Lm*L
+lSHwzJ)R4q%A!C-0r5C3>2Y)wns<gEELY4<-tDfhQ|LQlmSA)IA4PY_ceI@WL!ks)aA<r9|M0K7degr
+-wqZm_d~&(vkN{}+4k$Wh#k70K1D9PRHMHW^k~I;z!uH&TJU$3HNGl3XvwFcQT=Im;E#o0;7^s`E9_<
+$(H>cd_w#%Hu2(d^nk-TFocCbBQfTAnHqJpi^p@hsfb@R5hI}1WQY!9oeVc?LeBz{W$)xEXhpG>EL_?
+_8{(1|&Yio||^~GH$J*rpcv6c?Ntg9x=Zz+&&aM;cEmD87oo_pV(Lmg$^nt&Lm0d@A;oV2OinLs%D6L
+GhB?c|!)3Ans<D~gpVsY5qhySWlm!OIQZf51hOC2yP>qPpRFy^aM+$HYBo>x$M3%fo1{SU>~RIZMG)a
+8jY7IWM>mS@GMManGtfZ)cQ@uP^Gvxi)j}ytq{+%7kY^-e3|Y&ykvlKvs3m!wR$;`F`8C=X{RkYJMTf
+IT&t35DRbJxwLwWupSAOSNXkMZ9KTWUzhwXabYn4GSxUZdBZzQdY0#yR>lWa-cFPaqR;cwYS7v#Ujo|
+A`%VO*iE&~ezQzrN@pOf)o;9#X+4z*37aqPVt7D3zz~h%E*=jc#U*SqQHz(>fQW=9J-QDUd|D^}cQq}
+r7c`AOO0k6w6g0y)XhdYF|xU?gK;GFRS5))>hWpBc+bh@T^1An=+jS0ezPJ6h95DD8J%FO_ruG^TGo1
+ctD-TCzho3VBh1#j5*0wu*OF9c1pn7uRn;+F7!A)Z!><&KDQ=9zzqci`q(qs?E=2&mMScG+rB-MZ;k&
+#HT)Gb>4Iy=Hp<X;BwfhuQKf*wrvGloHdQ=0M<E<@b-2*YO*+pu9V8z|R|G`gtFR{pGzO&mWotfp6V`
+|FGdti8{*)(*dA#VV+NxN6Dv`oVf3%uuu5Tt?A<RcHWYa?u^COIt3Z$Sc9**QBGteMvBbzIRCgOK(p`
+zC{`tU<8nGdbC;^Cz6oYWu}{PNn&FUvD9`h3rzZI1vLUzi44(Sia;3|w2k%_^kzk|%Q%|*c7gd5FZpo
+kCizPz$o)SBTye(7G5hk*nZ>+XjD8V6khszKp^!#H|0VRCnXT^JJi>>t0qb8T`jO!dmh4DR%vZ%ZBR0
+BH8dNLTZm!{-;Szt^YyL0GH(sKfA&JmUTs-&zrnCrl}V{=vN^COsV`PQyfFUrlri8o}kE7{O;*&CMnW
+;2&{$P)f)0T$&3XC@V=-s7@UdPh<*R^;ryzjq3H|3Iw|*f3|;?$s8@v3vfEdEqwmD74Ws)?{x$qMlMv
+^z_a1ALb<X-g?6bLar0fW(_^_L%FlDC-S<!p}1X0DN)1ym)GXqHex*=(LhAQnNzv2Kb^f++`O9(RXfS
+Z>xI*wWR7_iDGZ8#);d1*mQBZAVY2_;=vu)oEYn!Pna0<(QSQx}6<wpzC$=qurYAe(KC8K~zjHCVEh$
+ym?$2eY8oqGm&GSd$eG8fr)&ctoks7Z*>KxNvm(UvrDYnYFSK9HKJM?ntn#2<a@~k=xXD1AXE~G0^)5
+G0C#gsNc&n}+Z3oD@@&o>5bR@7$CVXG5y$shGetkC}N7k(wnynKN*9<qZVsTtCDlMY|hvkvFUZ>89sn
+U1d?Fw{T4`YWFL{>ty+6h&h6(UwQk6h%T54a3l3SOo3Z3MTe11WLg0&$%G_F&V;+X1twp9jXY#0jT1S
+!3Fv83{If~@ubAJLE9h8waHO+h(7ie34RnssgEIi{83TeFU3DjkvmzW@k43#&;<LK5rx0<f!_fciF``
+N=~2xHsiT;%gRq^F?nDqLKjRtX@gtmk)W5L9Y%=+9StL8EBGhMYc&CZ`OW48Oz8dt?r?;<$g#MBXUJf
+o8e$$3Fj6_Kw@7j@F%FNc%6V^#|{#>rre=OG?7Q8R@9Dju@hiNVpc=8x{#vz?mB;IE}bw?)d7Tkr^NA
+esnQF%%{W)W=0{syM_%67{5D}?dY;!{)j;yA<^Uu0CdFOKcN=b#-ghriKrQ01vV))Xq&R`*Yj{8h1fJ
+&LPl71wyR-`obisC!jVYW=GO8=hG)u4y>tc=s?){~cVZmaAFjS8gce>%k3yAIahO+;9sfx53Wbd7Ncy
+QtwuQ#~YgV=#EA>6B37Ez5^$?y9(O$jPD#jmUox;>l=|r8NIf5QL*qPc2<nhbFr2Dn>2Z5k}F|N){K~
+uOeN5OG~`P3dPNBh&ZkoBZ^;6$buMx&*!|Ke!T6W{5b!grgs((0<CXh+z^@iJ5#{tu3zZ(8M73(T^Nk
+w<Ka#@~t!`#@=I7E9&Bq|bI_=j934x()xuKt5J^QX*7q*4jjIokCFkG=FF~W&|;&3gY)WHp(po>PDEd
+}8_Kd;*;$WWsZHtrCviJxl@2A_uN4(Dcm!vNS}On6IG%QztsJVZivZT^09%TrgRZ%psMe!CovC+El5<
+c~T0%}%Q{ZtD-}`|T$@@t<G)twrTeSN<XY1<?e75D1DP(Ef!cDV!n>d3*$g4$HRBv7a`k5MLUEKiMea
+Qz1>MkN^3{*!CFo&yF(ZVM(4I`J$g1vxP?|N{Ss3DgBt3ryt<}>?0hVeng%3=yX(6ljHaoSGGMa5x+7
+L%Ag~_#px$JAx9N9%8uITp*0vCeJ*<x+pmv5>9|9C0Qx9XhsP}1&JPdUwohyF(X)aavI%=AJn~@lXA$
+vV(#7zgi|{uiA>*1L{Z=bpr3f5x<+P-Jr9Su5j%5AEj%3H(_(DDNUz=0Hog%_fowNzU=kDb*#Wh906E
+$h4jKC+~v@yZA>9g|ja`-|1jxy#~ixt)1Ep&HOw5o+P-#$wCW(a)o(B;>o=|r=C_t5=Qv@<=`QfJBdY
+N7k$LeU)q<beV^Z*+qDQXSILhwJb4Ip@Dq$Vg?&udOkbb*T&sD)aAJp!f6R1^8Z0`mfZaX%+{aMqN2k
+FDFxjTH2U_PCJhl{X|gI6@$s7@U7&<`ZY_M9PT?o<7QSx$oqrO%Y(Y4#C8_isWj~gLvd`FC%}z!R9{Y
+eIA1qhOyZW0P6^nCEmw48@LJL5NLNBkjN^jiFijh^fv3;?1+VrDTPFgjg4_%`#M6=hW_&JxgBI`mvnE
+zF^}vJF2*LN`^v1l5AD@hKvd;>MJg5$J<x9Xd8({Qg(B$jZi>VjL8$&DVDB_OTvstEUJ#&!*we^K7YM
+6sVs5Ho=J*+xtK2Bw2<N=^aSIa260ul5+^{d>va8mq|4V1a*`F2{3DhUzf{o;cxd00<M<<~bxDT}!iJ
+MnZ@03lEB(3964iW@qQbnJ1B&gnWC-8{o@(Bye9e?7wW6??Xg-W(O>&+WY{;Ns@lt55)9HR?z#q^2jJ
+93~{*dI{gYuAVCLURYXo*<kj)vT#tn6#4~{-BO@&d`3ij-&$7g4Xh^xqeH^#r|j|Ir?s6FyM8Juw3w4
+tS+oe_fe=+&rwUYr?z@E<^d|hOs2MYBC<*}Zj>hn7V+IkadJO{I`t&$uQOTDD%{G+flHp5&=!l{8Jhs
+|m0Mog*N2<P}_gcwSAOyo3U#B(omVKO&WPV#;<8p?ef)%KALm5`gf~<%YNOPwp^cDtmua^toHOd7XeF
+DgO3CvQGx-P~EZ@t91oKP!;zN$(8Po8^!G!mkk*gI833r;>ACvH3T)rI2<|4lMKvCTbtl73Lz_?JR7y
+KlBEjEW48fu}A>%%$CTsDgODc5n+Xu&v)7GhbUuzp&yHAU92UJ=LA*!Xm<DVnk3-2A$Y&b9KT~Dm9fc
+987K%`-lt?)x%YA9%JaH({x$KE(R<f_s%Xfy>+V^<aoPl_Z^Ejst4A>sk#b9_B4fCPjF^tIK50_l)M#
+XfU!m16T%h(L2pAZoxNXd^>wfBdw5AMRyXqVf;Fv4ndPf&l0elb&L=B4)#a*JM|{@d3pTT~9RuDLv_V
+mG)ibW2eZk){B9!i+8@JIbL#|Z?k%p|XOs}!<St980hDk7jQ@qGtF6fp6&z)+<Z5S}=4Q!w?7|!>TTi
+-_k(JOHPTM$aC>BQHpZ<oD#p78k@bj*^<Ei1tKqXn*bsJ};95#{;LvD$Q#GGwH3$ipSh@v8YXfLA)Gv
+^0iqlaOWxguk!P-alPlTXB60fR<8tSn~UO?$Wkz<-)=}vF`j;M;t!q<JA<;u3ZRC*q9N|yD;%SXVA@u
+!IH?H)cgj@(v700n?IaLgTii3>d;Q`@RXAnHayLnoKGt0z3!Khd)@n>d^-!l@DKh<R?N7lCt&A&SmWP
+W>-qA~!3hld9j(<MK3esvlfITTk1e(2wD*~8BS}+-eWN~)?t|d7=59EE&y{^Yv+i}Y;eN)wMHW~_o<T
+zKGGdCrRX-1rtF!_!Mt(M1j_s9lhD=@EU2eud5QzTH`sWW8K{x07pT4gj{?~6N_G`nTe|D3f7!dt<)*
+p?C4)k>h1i%PIV-$rUC{3UwPVb+_pYqEctQ<xc)Q3mHALGL>HW>IZx)p{8ve~f`lpR0*B1um~2keQUq
+ZGK`gM<%&w3Ep2)4z*R2ZB1x7Rh63E5nZIEMf;m(SIYqY6p%!YJCZLoJ4<&K4ALD{FCSh+<kKJIQHp%
+``C&=<gwH&IUYLvJm6!X4f+`2!syYpwv$m5Io5<6YJz`-x>)qcFZ<u@a5W~^t88+>5=5%Aby;6Oa?64
+>b`(EL-!zPu;g9w~KNRSsGjupHF8s!rUlaG|@{7q2@Vm>;cMq!H9{l~W-xKxHqT2lS)u!V})T>)Q1L_
+xZqNAY=y??i~zq>NvS4;alE4%Nk82F={-q&B0%CfU|W*7@wn#L}Wx#C{bcr(kGA*`_;9h{xZ`&!=?VD
+uyGS!JwC;pbCxd(en`1{acLuJRbqB)F_%by2Jx74cxFS@_n@$@jDo_$Ll~U-w1#%93yAj$tJW0;l;ko
+=9w4?X`Gl&JQ(3i8J?Gn2eN5B@M;zYDZ;a-6+hRb=ho&F%pPs0U}9^U9OmK3DqMnb|iWZ6ZfJqXp!WO
+3QEWgN%9Uu>+4z+(4uy>@s4gFSp|Ll_d}Fz{qF2~khndh=T-VeM((2%|BTcAx9j!%V@&$nSA7dY|GMJ
+OK?g-36rxFlz+e)C4j*m|gGl73O|sC(qbz|wUas&#){a~jaa7O_4NmyTXeHFqsE{0nt3M4o=|?IAj=#
+*O9{s5(b==?!D?3Ev(}UjaF^Ec!+9RDD^Pm*`YY*=I;bZy${RojHhf>~`)?ND3L4kbkf`4v(Ord@xMf
+Y_cvU=nZmC}zO$`^gpJ&ckcwtA$($Rp;(*<V)%kEGUi`a{qu5o+mKO@3a+r|>70<@um_;?I&=-vrao4
+>d3mdJ2%Gl7z3iA&0=)(I|U#4lJs%@ec4+VV+sks|g>=`|20_wJNwXjzU`h7;OG^>|++R2OIGR()qVn
+1AM=n|7kTp^NT(DVS%6c#Ui|+T*dMBNbsISuO~-;r|t`4s5V2+Cl6ZLR$k~SR5NgD0fbz->nrtIY`LD
+S3F)&v^03Hqitipeo^YzuUlXgyUYB-GH(}D6U0>Hr?9-E1d*uFCsK|GyM9@;bM9zT>^`zZ;^H!|vqqj
+~Qbq=@#zPw~h72C+RbPLZh6|~NNN^VXu19p5pr|nZ2$+vztoBJC(%`ACN)$DSfV=lXP!4R?KZAcy``S
+B8%4Vlx>aufy9vo)%Kjww#nm{Xx_+GMK|&vWlqdA(v{r(PTH-rUB<t*!l?MYrz)@#faj=j+1E%n(mmC
+<6WF_HXuKWSE`XDq=w^_fpBlszYiWta_8J4%#nYvG`Ter|`^6Xxqe!^3+=_Xx|jzgC%?N3Oa=s^wfmn
+Y232j!12mWp~;FSI2TP~@s$z7u0!kz&+7h$h^;G~{<X1n38+u^rc6R*YRq}--Zv|<y9Qmko@YrMy1ie
+>9xG8q&a;>L%0Rd1^_z7%!^rh^Gh-S7<{Qi?AZ&Bwxq<Co>;3M@(Ae^h7nG=JQXitMv?L3ElLW$DDgL
+55j(1JH#J`s$^a4UopKf*3vshcBi|)CIi^(*eTBgCYISbZZ{usJ?siJc=8ql3j-eSb(lyPHEocq=Qx7
+f^TzT+!24L4_u7Y?*sQyb+gcaO6-G)HfhG$$Br1r}k>zHYyzchmXWk_(j~alrq^FZS5YfMYwum7Qufe
+5gQq^RQ?ucy1FVm3C}nzxIojPo43MBH)aVCvYL|<r6!#wX1}$Cn5C%J=<?T&)dr~g%#Sfw+9m7ZC2NJ
+dF@V-SNpdtC$4-77$v`*x0v4AY8K)SmX$&eNzXFQ7k^tNXxk=1YVCY62qhB`3Fn-0d-bPFWu(zCuE2x
+HC<^RY*EFB!s(wkiv*_*hP7Z^oUFWSzRPS=in|((j?WZ56)vFwaORs?<-Rdd^km7aby?e55rd6Z?5-!
+;V#lrVaF=YjH>)d1>udzMR3RZ#W?4muP$~LI@4WrO2B?Cd8N&2!;lr{*eMn9kG1?F&+YoK>}cPnx6<E
+J);=hq2R##9np2`1CBrQ+oJWOk+ksCkxLPUd+BWsG^hFoV(OcdNptta4XG7j%Auh6&uEJ+*{*onBSp?
+I^Z~KXPaC9S{hJ;nENsXml}=!Q0h~*jcoCh)zu8Y;5n8UjjB$H>1}cg2_Y)gx;ifa~_#2WKm)R#7Hyu
+m!WuPHnU4M@t-n+g5b@M5LH48OPjBGF_0#2r!xHp2g^vF@7J|A*lrS-CIBFwSlcN*kt6AY^c-Fj0@E7
+txuYGlI(w!iYEf%@O^;Vi67#|BIf(Y4or?)tRyL>sWRO%{8@HmbADqwV=@OvA6$FvF-aqj-N)mFHNQT
+7#^^{jt237K|ilQ@IoQx3N--(e<sFN<wnz6;TS;DB6NoK9PT5}m)a76POjsFd-g#24r>94N(Ggd<WjF
+m8q#-M|!eUjlcgzaRFK<J-}s>A7#bdI6V#1HW)1JZ}!#?Fl5@FS0bf0W#k18XEdCunqdOz~j!fw6WPl
+tf4WQ}!`djN+rUY9~gAKnD2{&PWe+b%;Kw68$Tu9x6Gyu#P19XGCcSR|k}Xj^QNYBczU{hY)-mACwLI
+Xv(F?M@Sv|prlU$GeHmiki*(B{V2bE293yc$AkYCR(kh$jXgVIxA0Z>r;P9aH&{vf{}on}{s~s%Zs>&
+6r_<I8+`ik)K^O@Qda=EPrY?yazU|E(%M!g#=jk;7O%}}$pN(4QVKrML3@5C8-@t29=gyd%2Ijs7B4s
+?q06fJ_mS2T&!Wj#+_s{pGuzY~vs+N?UDn-KwUf1};tanzro!%*g5Y3GOG5xusC=2zt(qoX&w1ZsIAb
+Y3T(VLhNP|w5})H`ZmW5v4NrJA}&Ax+Hd+u$he4VBkN73fK9E9kyK1!<k6*j$hj#NLv3N|u1>jk24ii
+ipV8gH^V<JbM_{W+r~A6X9*0u0o-(XRM!V%xw~;eTIG-M<;akMt!{JKt`Jn4i>IDcT$m2m=moyhl+^L
+#`bDc8607UO7dt7OHwV{e71v*w&y{rTMMog-33ml&bo-0C_(`91R)k<tU5+%B>qF4Bot4#&5_DHQ-<v
+wk^|qz{TAEu<xRi}<!>#Ja9xit?K8$WOV#7b=;P;Y>#cX-k4vv1EYaq}=F0A=wygAl2#vG^>v+%Fu2^
+vM4oGjhvrvqcBB@XZu&hgSxVu9_8|Pe<r%NiQTB)C+Rq3GjBA7Rq3{FToz;16gwh{st5_QLFtk$@%LR
+WKTc+1x!x;`%=DZVpfJz@6~eXDJauwIG%L_z1`YS`E~BUEnZ4#;CNxeSXL&#)ffnre9XkBe8Ycw1hRy
+RE?CNS$NeZ!^$wm5ZS3kRvm<^+DgtVg65Hr4a;`;(5z#yit&o+`c-;m6te0jQ;^Ev7oXIs0d8mB}1%4
+J=3#SvqJaOFdA=!d;C_?OG(7AHTtrEL?JrPDkjNOLRIG2`OVvpz*eOIsFokIVGrBL32U6&JnS{y<u(*
+z&w@=nV=>;=vxo5`jvr!TrtP%n=2FW1NkzH!46ra=qatL0`SR%JyGxFjF*i=_NlkS-%nRljyhUHL+?a
+r`GpFP{mt&sQ`}$qXWn=`j+A?==(Ozzy;>Q)*$r-=KX$1=Il>%9CygRgv6vlR$2nR<WrTLaUv%5#OB9
+exh11odA-QQ$DOvq}-#&n_SES)^;NkyY-x0U0%O>sBY^i-!arVz>#eTi>7x0vt=UeXB=SLqyseSYpvi
+OY|VEu(XjWI!*aBKM7WQs58gK}Z`rKby#k)4E^C(K8QU?K_zZ0$8qmTb={|%x%xCdwcr*M5unQuxZ~6
+p&*kTE4boR%g8;D&if`#ZsbJ{NvEb%($`GDzEuJCWb-Bdf0}!*Za1;CTlk(|(f2y%C8xe42}BS%>5eF
+b5JCbG^y?3cZM$vPcDt&p-|>B8xXLyg(2|AbnopWjZLW9CU}mlq?~iC~3nBG(mJ(ph`YmGL5@W5O2v(
+i#dd>txYDN|#+%u$F`vZ(Q45E|Sepp{B!8rvU_2+XU4(IrGIzE$TB4CXVq=&?C%P1sogGG|3y|c_$0M
+VewV7TzNq7h}WeD?IX(nghMu+*)oj%Wh=JfZhjE{p+^5^<6VJ(_rynRZUa9UF)WbuJ$1*bBmt7&vElJ
+tI=F6twN<q)~@Toa+ApSHk}zuJpUB{>YW^Pq-3G5(tXo6d0I6XojR|0>_X~TL|z1WNlV5LNZ|7g(ZOe
+Ecwx>O@d?%n5IrPZ$Ka(@p)b;2j|i#Nbg`P$J(?lQWmI?F<bvtzKzdN447*{wnl;k0kn*uel<8lfMiy
+(IU9g}aRwx!(rq{g$wA8%MFOQ<cFSF@ylJINE74omys|u!1>|U5FtAO;!D>LOdb)XICtK(GZ@H2nfNt
+uT`hhFG4*K(8of{QH*wY^yrM?jp=<o0(Kun;|nTheIc+$p|{tiz9tAT#clZ=0B0RwTIU3za*F_xQlkG
+*1HvMQ8hm1>e)Ltgv2LJgIkVYS&W=}s%rho!Br=R5b;K;x7Q)#fsn7Z`p-axNd7JumHp^fErwc1K@1r
+FQ2VMeg0uv2QaPE{>yNl0;BR&0(A<>KH@_#TSXFKlb@n_3tI(A)fbm#!aZZfW4|%u@HC#peIHMw~`%y
+HXoXf-O813pq+_*N$19KXeiK3dtb?LWz>%p>!Y?>Ns=I>Eo&UH<n8GU%Ix<2D@b23e$w%dduK)=U%*X
+ZHNQcpS0L^yQ^d2f)M>&uO@x0xrAV&!D3u~&y_|NH8L6?B1Ssm9hF#|9hm|E1MD!mZ7V#e;*6*(RBVv
+70ek1V}s1TY$FqB+jizP6cVlWi>R4!uEtzLlz6vtSgc(aCRz(FhD=2Ny_CNu}Qm8<~9e2Q4>rE4Swq#
+S4vMy)W1Y;LR{dfXr@j)Jx-db7#GQ-EhHEUqs_{Axx9D0b(YY6SwI6in-2Ah(WUTb`W-6*T~~<YwHmx
+qG2F_?2y_xS|(R0z3m=U0cg(!GQIlDL9$_tqkL*h&9Re7|)L^>v;Q<*3SQR#IpZ?g;@6Q5X*b#irFTI
+;rzUs#4!tbLm71Ugws=~nB+jpV>kw}b4H(6G0)&ay?T5?z2C1YS}u^S#PlOe2!}mCNK$i>*6RA`K(@=
+Rymz%1p=4a$eCr-N4L>N^g=v+Hxfm;#Yi4b9ASHhMUBq%Z@0dPwi&c*gE5NJ;wff+}sCHie8^od{5k9
+ko2(jw!r9_Wbf8It9PQ;b!50x$DNZveFS}8o4ya*aHL!CK3T+TZC7BHROZ(W>>EHO|AyXW)EsL<HXGa
+||K1lEq~IJfk*KEBrYi!<}HZYDurSH!dTi|lzk<gP#XjriyN2#V&Ce5>b=AieZ)X#GMqKs3x;>YptK{
+@f+sTm^nQ{RjP6jA2&lijWvf(+GuPIEi8yjj`KgABmHnrlgQ<2sz0>&3)x4E4DBs=rAt{P_F~^u?$qq
+*iE#b_#Cv-O`CNkPaht9BmyucBR~ZXApu8XGf>}Sm~H5|*!n6{fJfP{v|}*>oB=x1iLJ-{!!tVFs(B@
+7O<>q<AejK5g>9ZyK%-|nX9dG`H7E+CbU^0=zI6_iU_5cXTgv<s`+cWo4tfUAZyGli7v`nPrn};0U7t
+FkhErJloQeT`REA{F(2t5TC)IH7lgxeXhunh}$S!tyISI*rlMa(uGO7Qivkz@T`*P4Hq4Zr3B#(XRL!
+V8c0#;vV!}HOj=WKoGn-bWUV-Pq9mhzvj1o}bp|I?NHdo@?+$Duymwx)t1+R;wPmLS@^BN;01IFmWwu
+nNBK8wHu#=Yil})rqFw`~zC!{dX=`yZ!+yXsEr5nzfhvggJs!BX!z|hX}LrH1M?jIlGk?O*EV3EfePD
+P#^V*g;qek*ed>Dm0o;?HPhes*6qk6)E#fi46P^1!thQPLcTpW&v8F%SGJ4X5PrbqC3&z=<K#Z3R1#y
+)`2M7yZ<5w_$K-KP_2ZNX@8)@+DoHz*c^Ht#G+o0rDb$bT9KXGzXNpjZhn0WHE7RJateCV39VIO@@0*
+b<Fk5Yg1DPSbgy1L!`;TJ9*CTxM!_z+ZqlN1{h?cGQEy9h&(d4NrC+<YSmHu}8zE7{W)a>?Fb5CIjo7
+#}PH=)MVb$O&~m}r}0NZcVxp7aAMcd8vdU8~Of>`A3u<<N8%r;?|sul;+zU*&TVYENCfXjww8@9ydF3
+ex$O0C|$tWMX0r^)V_s|8;(dNW=^8IJPkE9Ljn-4e4<bog0B(*??+XxHufEwCr4)mmd@qdWghFVSc0z
+re5REDRJC0Oxp?T-0I;iQ;upXZWlc&fhqTtP$tQ3DG$S|^dptR9Z0-4zD7pWq#^l@cL)Q~WZ}`ghjKu
+~G)oP>mBKTTsdSmhM-jgC=lyGxABuLshu!G_byD0n=Hs5<ROK?S)ETLw)YM!rO<sI9W|Q9)H8ruaPYZ
+O&qZ&K%%T*7)s<}d++A=FzPl`wKaSauA#CqjKhx4+NF~KH(8US3Nr)j^7q}x|;%079lK>KX0hV#|*{{
+2+M&suc9oB+Iw!>OCr9lTB?q$Nf(3Bv}yJI``%8C+5!=BcTboJ&u-9qCirx3ZTSH9wxnM_)F(<uOTEc
+~>a%;1tMX!U%b|%n_=KcXdG8(*;6GD%z>cRPr@B>{a|+ty>Fg<d1UQsm}tNMp0ZAB{jb<b*qSXr@e~L
+g+wqsBGSe%Adb15<ogwsy|=dn4)d_Mp1cuC5wZ`WNFUc&?Su*!%jR}zZ-cx)RVhNTvJ&ct_nmhk*OB1
+Gw%utyGS>U0HABzbc|scwgWq4ARxEbHLK94xE0>ZYLbN%>ul#=QV<Wg1I}P$Yb+lc^^Y5CE&QHG3R0n
+s5DNVCvR~8c?7f~<_OdJ?0x10srDBhTbWtsexHN)IPRG|-YXP)uvE56_D9Uo<UQ{(g?a8|1vgrYi(Xk
+t=+bQ!hFAf0>)h3)5k%22Yxq$h;m`N&DxmN~tg=n-D&eRGgFgqUfOnh<B;t$^_P#ci4~Vbk;L)r=Nd@
+{iW<$51f_$Xjqp5ox4<@1A>`pk-gyI%6M6x6|xdokyVMGwyt~ZM+=G4ovV~SX0B|lU@)UxdKXX<MW=a
+1Q`YSwR=YG26k?{ZeDV@vo1RGa{bdi*Qt}O2#!i#p87NAyzD(XQdn>ywDf)-9y6w3*h_Wm)==8VPLGm
+4?y~#L*7h?Ay5<1ir<}R&_+ByMg2(naMhSK7HW~*#dF$o#c5ySZKi{?~{$J1WUGE>f^NsqTKt>f=+0y
+#6Ex40!sqz!I`U{tR<yXJF<VRO!5)A%f6iYKWi{Ugy5e!AM3_~)&U>PF_;P3RQi~<RG7LjgoR1U;ji!
+HLkHWo%>AQ4pJKto~WDPLWXe_~rJm04NN%7ID*T)p0Mz0JyOfOT>X;<Xe3MMQd2)Xz2*K!gPb$keYw#
+DWBaIe-A7!0Q<#!Z5(U%I%df5(vetQR#Zeb!`X*UYOYQVb(BoUCnw`zFAIzPEQuBfZU3Y>pMc$Gl}1Z
+h!`jU-h^*+F{N>{G{TGU-Q8NkFhP*v*!(d}Jp5b$T<`s_ak(`xGaLc^aGex*B@NYs;U1>L7i~XjZX`W
+$Tqp>R{y|dR@8@8Q5B=5Yi~j1gX{~x3c@+KWLx0skzaE2*qKyIpR#*H{%)ycT@5T!6o+#PFSMMYTLoe
+(3TNwE@NIik&`c2>k0x$TN@7g%UFLJ8l=W?phH$7D&)#s&lc7%uCUaYVe#LC8oSDxUEHklHtB%YcBal
+3t!%=GOjJm}ntU1*II2a+1EmPEh~cUd{cX<q1^dn?^5`kw7zuh~_6BpNwy@AIU}9*Q0hQL%2A>^v<9W
+Ct3VzM_}?Shpk_na*cP{Zk&tis?w&2tz@7OiJ$Bps7X)8vlIE?C|*{yui;NV-4jRQSXd{OdBF~hAfSv
+s=B)8iZhuPW{h#Q*KhWafBcKT(p!M&*l|e(Fs%L&s7IK(L^$}^of3+%eQ5;D_POh~^+b^;?@Dpb<I_8
+pohlRWqmDUUb_;4CS6R5^w;Sm<vVn4e6}=kWo+|KAsq2GdH-~23X}6DZ`#U17f9GcK=j|gEX3O$Fo(p
+JQCOCO}RCUQ<*9QoWfAACwmQ!>Zzq)m$a`Vo=3!kB%<L5@@1_^#vF<e#g?lM$S<zG(=aebe6@>NM}{^
+Z%`TGI)7w(k27nzUz3JGInnG-8eS?Iz4pU*@5I-pUv5r|0XPa{Z#Z!(^RaI5b;#d{IC5Ww_^+0LsH-x
+>v(YnG_2<21_@6l~MT%I4=eN5zhaK%YMfBKV0$y&STUXQsXpBVJPUnM;VHu5Pb9LTcc`{W!Ei${nU{K
+j7H}m??xj))tX?wgrqBYuKzE$wpO46i-2Yjs`$JU9|ctfa3^#t9k3wn#%|5DEAFl#HE3I<K-`;cmVNj
+J^`KY&S2({$;wTO36lel^TPb3*+Cw%Oo)TmLK{k;Do5~uwgNnvB>Ie*+Q?NUv8E7V1Hzsg73a~xTz*W
+rVA(*Fs8Rw%(<x%{hl+q;LsU@t-5k`Ja2mP0EJ_vu0^U}wJ_aAWHyZ+a4ejoftIB!Wh9-l<u1ke!C{c
+wGxZxV|~+TN>us}oe})=XFwN<UwcoBDJ!W_?uwf{(D+`t)QhmW0$gs_0^A%y~YS!h9Lq@s(!&a%r^by
+z5FlXk7O`onYt6vT>5LPZ65Byt3OteI|bu=NX%GVjMCb_MO~|L}!(K^42i;b^C>v{eKnb1MGhn=ba$_
+{}AVw`Ymg1Bt&g+F};|J_YZwKnWy)$O>M8IEAkqdY-D)M{lZcL2QBao>75~DBi)7h)&V!Umf3WDGq!U
+X=I+SRjyiIhec1QcJ?@uBGVCaGukofms3~+V4J0{R?V+yhaEF{c#0dX9&R@<KAl?1V8o|OD;sc0f5`g
+xXpZ}kK9NO&XVfVj$@i)x>cNhL>$be!jic$#1pcIY~EQ1gzO0NIWG>Nbzjp8JR|3ct{MuBlXm4Mj;bg
+K&|6oBvI>u3ZR!`f=nzoPdvVA**A{1Miz1KGx<fCobXia;yf26~MYs3c<uNV0-)sRHaI#jgaz5p<LGz
+yWWk=}mDB1A7LTzE3yD2z1i}N5OUi{(ysw@49DY)R!s~*sUlKa)2#|1ZDS?|AWHRx<`<|7x(}bpwqYh
+K3gaR@07f8EW40aHR-%?e=+Yrz`pree_v$q{#V#H9l2=}AJkgx9#}5K3o)xTcl|oer1(w;ov>z86aT?
+yK{SY?@D+G7^j|g$V6vV24*qQn+760`_gDD$>YprP17qI5x!@c8U!Csji|PWeLg~$T8E!nO-*zNaO2W
+L`gv5pK?Gw1SDSq=+RgPcW6QEz(Cm4I_o-s~?3JHEOg`-^_5u=aWT%SukL%sKyH;U>)batS3=9?<8Aw
+HPP>DjkTq94&$-mA26_E?{mg$lhH(n2dprdhIN+n0vv?6XM-dIurz;QsE0x+Prn=A-fbK%;?K1k0C6<
+sYEl*gH<ZpB`_z)%Q>8ARJtXCxk=E?;n4ug!G+z0`y^@aOMoz7YtialRK)AyEl_IzKDhE`?yl#JmTtZ
+>Ag|Usakg$<kocYe5}`ZY(x54t_nMGTK@u1PhwqmDej}!d{^a@dou5q^1eIgMAxmu%&Bf3_ZM|^ZqnY
+oHM>bBATc_LwLp3c{w_tn2z~A^OrHJ#K90)~2uuA(i1#P1{S@$iy6y+OLs=knOJOukkPJ&BplU=QE6$
+NPi;>LAcuDfpbOtbS-YjT9k$IC;EHO~=P6>b%V0w!Hz6T)pP<|7m{R!_98We_BJXy&knFDG|Z_{AwuY
+7Bl2AZ^69X<JIa^A}4D}LhSuPWX&V5lGT6d{2s<a+UnYhdPd6RrhKISg18TL9)tvw%KhDM-E`o8vW_1
+8}4^0bFX!uVkBUQ?jn_w|KWdf#L{4{R{7`8&YUBRSw<5co!<(zOBpWJ<Z3TWj_8K=6PKG74slP`WO6s
+XDEmm;uZT!eVw=eQ30=4s_RMU_Z4vHD8}F*V$=p|dOjJ}{PC}>3i@nWe|A-W!5~3+BbKKYj-12gd^;D
+Vffg=9AEX_W)S;<A%NBpYB#+>hq2dq0ex1f}j<BlIUdp96>)XA%UV6RNo3R*YxyRd%GdpXR5eO4@>VA
+CroQKgmeD?TcPbdfCPDs)D3_B;84ByX|5S=32O;>$Kj|XPB``%5|^8Mr7LDRX<%;QoTQJ#%UQNu#f56
+g?q)jrZojmH{nB3vV~?v*B8ESu_gIes>x-dD9de=?v>#yrYnD7x;LmDS~}L|L%d*Nco1#5qdd=Gaef1
+wpB-3l5^?><1%#3kAcxbA@z7sP$1eQ@A54KAj`X_w8xq_UbXF8I(7bkO8Jar2^NH*#=@BT}qz6JZ|G;
+Md{n3tUJ^j3QJR6<Ry#T%@;(=q+Wco*YR>QFzztCgK1=1c-)t^u}>zgw-itG*@qVu5toQFbb1!}`vse
+{xioq9=!xCFX6Z}C8yBW{v$^iXm*9mS+>&Z_{5q+p7nLjs+<K$5-(@+ZkK^*DQihoAzUj_Yt-B88H0v
+jDn6&Bi_K#s~PH8t2cOyPb_uXDg)0cvIX)mkl7(v<+!?1fFvoZ=*orH}OVWq{z@(`@H;FaACtQuWqs~
+X!m#~WRy-8#C!v~$+&Q*|t$=pI<_p_(qrXmV*7Hf(t;!L*@qxK7!fH~ro5-b=pC@3Pb28-kyP%pf|ha
+th6>r9;E{?wIMrkg!P}PP9dRHAwhGG1>QwjP_34b1pqKL%YP%M##GuyB?8#A?5LT;Prh~7W$#dSr%?j
+bSMM%p<>8jKQg;Mx(bY}U+PMgacdSWHKx@Oi4iQ5Dz%y?NRAH0ow+ISWBvN7F}3UsNqC<47vrpt*R7Q
+KGu@x*_tCtsaUwPzWZ`waRORuN=j4%AAnQ2TW`fa{TOFHr#^z>3ro8vNq(8;yEVlQ%=$bFtOubOw#&4
+kW{4F*t*85Hn>3hf|Ug}P?hmJ3s{Vq9`o^UvL<<a0X_GM|zLkZ6|JMAw1%YNPvk>Hp5uEy#M$Le9Z+m
+Is-GXHjJ+LKA%r0N^_c#-v<VAmzb-s>649{eJ*Hok;B&MuV>r$Yy`)EeZy4C``*xLn(t0mI);D~2?~B
+>U;Ex^cT_yy8%fkgChZB|W;iCE`xS%BKH}eO7$y^%_g%&IrNQu_d{}!rk~p#Av#En4WYRyG4A8L3l~7
+uf3bs^_@r`><)ngnzmZ^V9d<nP!V*pgF0#$X%a3ygW+GY`Z&DtR`4-S#`~!=tenRgWPI4SemwCMcg=}
+Kh#z%s!7Dftmu7+tKZEll=kLdRbvf(7<$Uw=g<eAUqL+KY6>cZOJRH$k50VG3$YdtxrzWy|#vM^S+(Q
+rl;03R#$_d#E&+kVwH0tt@4osKP>8Y1w!IA2A;+bJ;ustQ;o)U?{p<~>hPS*+=bRWy2lfu3FI2ZLE=|
+ZN`F|~VeC^<3f7cG^ByUuhzdw(a!NQ((!z@~B9{b`Z~$WC%;o8`M%_;1I4B2~XT_bZ9|!+Ae2Cx&5g9
+7ib>NIqgDO0U!jC)baHq)41#a0X*B^waj{HEaV(Gh%ZAz(4~_f`Bf)m95~^7OW9p{#vYb2K$^kA)wa=
+xbdy5g#nzX-1yc?kyiReZOR<$2`e-EsNrN8i0}yP*IJNkc(^slfFvWenO?17EV416mFod%>=bk(QYpw
+2QZ%^x8to#RdN+xJAo0Vw8NoKyHUyXutlW^=x*C(;YC-NDkRe>Yg^CV$AgtZ`t<J)#F;EXdC7T>}+^0
+TMkmda`Fq5{<x-Y^P8$od@(Ct!qQeyDuuN`>~h{d2>-goJ3CjT%lzy5v{*VDeENq{B&aIEIo&&Zn#BD
+gO!N&T>n`goD=dU4i>aKAAlC=Q!fs(e#EbN`ZS@{z+Jl!qU9GG381z3mpA!yV(8wEabzm&lT<`c!KfM
+~BDmAd6Ugo}>)U`pau~eeO)susvveICt-O7ZU!2j88r1P3Nf%2(DmUkHHaskCtGV=Bc{Sv-x6OmU(+O
+_@<9%x-`-vhm!r`c4O2q(;XQ~mcGAS<(?(ueiBEHRECE$o0*5Z7i>{k<sy@}PQ4oxiadqq4NegV73ew
+}uh{(RgJB5`bDSD6H7?n*M;7T3#wQ)sr#|jVcOYIQKiYe8*Cj^nWP+i4B=p43Nv+%1N*onF5^YwL*I-
+uJSC<pnSMnk1qe*DIqnji!*S%dwD+dCvN2ei&EZ>t*#?NwuD&69hS%i~afhgs1Wqu~%A@}&M9XkSl%c
+@Jn*P~`N)Pa_cmWL(q3FGNyv7t#BB=0$>1V?H?r!fm1<%LtI*PN^_k?TH8W2sWotP)2Lv;H|p7c&byo
+2!dcZ3Zety?8%+*baYT^xD{`<1?)K{qfc6)%ohMrv$#P)Wy~sI_l?WeTev>@t>V>ZBEWH;klK-w&}A`
+F>^sCTYYJWq=tiD9Js_)Ow<flgbi!>czaaEJY(W{@{PS{QfY|sBi}3v6fPxc^K#LO7C-EKG?)TdWr*l
+-m@?Q>Xsnhxx4=<>a9fXAIahzUx7PDTXpFLZ8xB-l_Li_n_HgB>$8w-}b<uBxD`(x)?Wjl^l+by&{ZF
+pR|H=+P-)Ud}w!@U?z4N1Hn)<}9fr&&>0`-FO^>MLonZbT0sraRJ<`op<i`SEYFs+2^--><og3=8#(|
+$r$%8?ZOP~&mM`06a_i-h3i{>~i3FdS&%tXX`WogOUO;Lj?!zR`i?qx?qQ-(E7|Im86le)7!5IB<bu=
+X<%9E<<<V9%Qq!B^G~D*UNHY>!pgqnMo%rd^0O5$C4};QnE%u==5B!QTH@$Vl)f`b5HP@vKhhIb9l24
+SgM0DlYaP}|L#VSbOy85uJy@JgQ?Mu&m4L>9*gYg%i$b75lh1pUXQ|i$IE@<cEO#Fk-!>v5|uB9G16I
+i7u?0lISLW;EPOV<KtmFvyrC*E*|OD<&EBu3I13few0Ns@V(j7Z?p#ktSo6hQ+b5Xs7xD2a)nm(OOhZ
+FW=09NSq2k107I7UGg)$N<GUWDLA*v$ZJfnDj2<dJ@!l^tfD*vLYL`r!3#=W|rh8FMHt0xw2)5q1B!_
+-m4Ik}FZxhF+tu6Djmcj2YJor)7Kzn`p<5~BLBQq+{`vWr_toAFm?jfooA9>)^o+#98LT4Sks(2#1S_
+a~q5l}1K;+4e=bi`4F=l>R%ozuH@_FVG@P?<;wjW`r_Mo?)N(l2!R4L}FYpZ}%rPo4R8iDh9bH1D==Y
+4m)&;-k8oVXj8I<rigQ_bVPR24JVc)GCSCf@HaiF4P(0N{ySr^m=qRrS%Ldv2MbHt(UVDLIekp8go4a
+qr`?i<5A9;oHRjLfoqnP((qEuNe>nFSlt}u460JcML*gibP&7uPIJ+_<j39BEq7e*eWs?ZWe40xF8mk
+2ugU@oniNG*C0tm&*hRSW4D#1a2OG0nM^X%tFNn4(MB|aeYgMz{&m`o=D!2)~*2RF_(`B*v!JuXEGCL
+30kgr&a{FC)Ov1X+Tq4WL%GWv8fZBz~n*E6YmIjjwIFD>mOIBNA}aG6ys8W%1861xa^iQxifc(6zj>w
+T#%N<$o_;#sWeVVc&8|{KbFwekK}Ap6y~Rd8M$i`$Nf;V?WEC|0OB{m<aS871@80g<aO)5nws|y$JTP
+{_&V0B3th<^n(bta{xX@A0pUO^X*mE7x~c#={uSR0a5IaEWJN}W`y*;)-`^EiE@6IblE5sk<6X31|7S
+Dwr<=HYmvG_Yq3M3Wqe$@j;eH7`!J$1e#i&Uj(xtj@qxqLB~|25;3#hm>G&%K*~hr6rYm!ep4iA6H6A
+o3zo)H*J7n_S;*Gpc4rU|Og@b)IxeWcPt@AU{GG;l)3+ABo<@%s@*z16v38*T@!{MC$$_Q!ZblD6qqS
+#l>#mlM5W7!w723*XE-6i+;4SEffm}FhoQ`h})O58nB3drke7YrTS!N5Gvhshb}$AV%BE$YI_NhVL^G
+sChHuQg?eA8PYrJBQ=DByjKOw2?3tXcTiU$*!1WR?my`ry)uDzuxQoO#bm9gZQog!g0BOj9|+2>(3=#
+{s;Fz?*9N`#jnRcnmL35sQCYcUjN10eg(RJd&?h2FG!X|F^a(vhFYn@8UbPiMgVOPWc>+f6+|flCFnI
+m#1Qh+j*%5#fW9;WihL_FmD`XNkRHPU`rw<|H9><gZ~cEld_L~Vf~bq!M$CW{0Jh=M*1NHyYq}{|V_R
+_&+k_M|7DR=`3S#W9Is;4K@|JE+$LlTdt)Tf~)4rk}C=t?|MhFNgfgpB~Y<|Ss*jR~zZWA#1R)A%LQY
+8hNPgcZCw($1%@V93G{ITDx+<no<_irb@G^hAbKF@kN`|{BmNJ+FmH&{By+|T;du3>K}G5|!1G@bbLH
+dNV7nq`lRz8Nn`{s09^(5^o?JHDzMB<bZZ#H@H+`f*b4?bnmOp7XWgW5v}MsNaKvAM{<tZ?6XqdcxJ}
+AbpWo6uxWx*sI<)R`LF3H1Gz_O^^wU=Dhp^WIb>Y=y87>GY&HMvnco)v05N|zJ<WEAwzaZKI2HO4Cgx
+Szd8`i{CBGf1ZUxSy)j;fgG}=DRaw&6&Vja*zRtBt$7ZuGsHK}Be6xJY9e1VSVZOvJ|3!{+`Zg^Bt?v
+tD`p<c7{8GW>ljQ#8Gz#i~t29KPTQz2N&t}nLq7uoJo^u_`^j=35O5!5sjf;g8EZv2&@$OEc0zWU$rB
+wV^B=p$~y=ppwFJY(M35-2T<4hM_<XM@ah=eWAdjE*$IF}G>-L;Co7-y|$D^rd-v(nirXCS(s6uQu~f
+L*X1T#0HRK2$=!SI@=ruaD5YaY^$W*$j5~aBQ(9;S5K4hLdNmbG8XX&+vw$Z~epu`GblR!FmKYBQ-)R
+)8FciTM+b6^zw2&zG;L_;3tvqIKF2dc9GwNVy{EZF2_fAKWOQxofdRQ=O^-%E0+08ojxGLIN+(UC(V_
+<avWJH<j#&u$w}si`!<<WhNky(N)1zAG}qxv3&qmp!9QgDv2$nYBKgt5yu#KF^N*$>U6NDYirvKRZn?
+G42tN?eyVYFca>+(B?S%YHAw+u{FC>mnl9rMwM#c!^1u7;tX_etb^c1ln)sC)IRTFvVO~`=Nomy)>A0
+tF(o-j*g?8GLAHrM%emw$!~^R9E*&+Dj-f=C&t>Ha`cgM9bZVBa-}l)4jskWd$K1L@qgU82C@#3@KG8
+aoeW+V{FATNfie6ghvvXL@Jd`0=?vRmT+Ga|+b9vfK~dn2VxyMXft7=plaL$~eYq{c$9Wj_+}8S_V71
+vflI-^YmQdS>&nMgmJe!BnBn!9HMFA++DOs6JjpRKt6UQ(jX@;H11!M`<OAs-XEh@=p$_XX_Q3QkmoB
+N*d+}ftv}?~k&{uQLe>!K#}L<Dph2T=dYRqOq(k-Sq)+_d9diCa|4I8`=vyV=aJy&i&Y&3LB^$PV77$
+ysV0v#L62aSy*FEWWxxt5yj9#(&Ucd0SAzN&S$`22%pfWw1`ddow)%5|&3jAuS{%n^jTilKW&fKy6Wh
+Y$J9V7X<m0$6L9@9^JK^e%a$K*MtHP#@0_n_~U@8<lCGIu+ca&PxRTPYCy+}XO~hwTJEnikp9UGH_i)
+9*OThH%%aVB2t|bB)NN`zFLp&u58u*Dvd!M}(ZWx>r2v+Jsq#OVISBBkpZ)S0>)OxpjrcTYb}C#w?(=
+E_Zr(9xmAZ<};_WM+SM<@7Nc*mruv$V9;-ex@ok&%Mn3-?8;K;TNYvmObMzw?u9vs)szwx(!E-Nz9Nu
+P8vPlY;@y3Zh&hg3R)Uyn$-xT}j@=8|n9{Wk-Kt^1ZJ)2>(|M$vmVSnfnD1e-x<BJvD)RKRy-VlJG_1
+}kUu_A$2kv%GmNs*9D(0ZTJ^S=ARiwuuJ^6ZfEo$Am7izG_PfrqyTDfh7k+H(|qQ^^Tlz!n`EU8n0Wg
+C{VhuDr(@%QU|P0SkZ(fDmX%O}R%O^WYs1l&J0;<<jCQ(oUI2W=NhHCZ=2B9RM4SAAwcxBCUoujR<no
+Zeum>lp0WKbIBi&YF42SJ-?;^{!CFT7*Ttmx!Ap-up`w#}s17cLqwcgAyU#TYtmk{(k3AuN`&GIyb;y
+FVu`J+#aZscophJwAP1%&*J0h?{ZAg_4U8NG5?d>{)S_I-12*liJ=UM5G=|v7>1E+7>xlza2jPvh6Z&
+8YK3HKJ+?AU8l{O(T|5a2H1RSh2ufFamXctswxmIH&2B$JHy6x;22}*=bCSty&BDnhhr34Nz>I3sI7z
+m~w_+ol)MoQZZ=ra(MaS!1nP2M9(LiWmT^mD!k_TOaeh+*rT438~%z77mTV76sWv}u2%8&^bR2)idGh
+rb>X9v1@UJ>QioW_7WLYDj!{k<7+w<Xyh-$<r<jZgVosl4_3a2yEIkJB5f7KcMG{n3p0?+{GD9ihKNF
+af`W{uIId5C;DP!35qe(9x@YBA7M?j{O;e3HT-ScL*jp2l_h%bLE$N2sHKOzmb07IM=)hH+Y`8LS<i1
+j+yTIv0Ayu)rPd}t%tE<)cR!&k8h&Z>DWZsxhLyE%O+=Mn6gnxc>*czaJCYX3g4$|-5ySz<`J<5mErs
+0c^W4?RZ2Jwol9PL;zIXaD})M+qfSq2_(7|;Y0^*X_R!Wb{gEQ5*L6?(JLkj1Va{rroaIyh^ezRG^3F
+vI?YHIs*m7s>1jvXEyItnoQf=jCgFN|bm~=JX=r8;v{~)>meeEVD&q17oN~34@;{r=3LB~TlkX^YY>w
+t6Z>*<bOz1wMbF1k}^Qj1*sml~!ZIwV5wQsCewcyNz2JkC$P7Iu$0zqCz=9quVkK8uLS?V8@FnLXWbt
+m8OydSBiB40h)0f$~nzM8f|x)_-&I6YjU$tG#5&aJjb|k_sF^WmghR<EsYD(htS0|A%1y&;QXq@#j{%
+zk9E*sQ&No^W!ifM$jyV;RwwlEQ6v9`YCj;7|JHVPOB_8RnH7mSBV^i@hfN}Tj>`kx8R@sCq{h=-Pxu
+rlQAGaKogt076}Ap5)6!!kmc41hk{NxAc3{HG6OYs<e&JjWY&QL0|^#`ZPR}%AQM|=6U@2Ln+iM$`s^
+?qES}i<_kd<84YIK7$@Df3i4)*W<ptPRR*+u-e7zwFB)@)}A1Fb704u&ix5}A&=7@-_43q88fu_j$oU
+uo~p*8fOiqNf8(w`3BplkLV|7dwG|8=6oD^_GWh3I=lCriJ~Mj+WQ!_C(4-u@ciliqhOeqxHDLmrad*
+Z%#Fda@(h-uF^j5@;=s=i^(#zM4H4o9X<QV>O@ugua?DN{u0Wn|sM19|=ScLB4GcKHj|7&0%Hgyyz{&
+x`Q~9UQ4YZ_+P=a_}&T;vN3i@qu}*1cF>IJmvIyuk=}pCZ43Hpw?#0`;+ENjpBv`k3w(Gq5p%$(*xq@
+*Om>zS33M~Oul&$@g3?FtkTyNy2?;lGd|}A58i#o$h&{Pa{9Se%`$+c>+KeF2bMOq5T@|_2%Mo{cERu
+d_zHJdjCGE{Y&9i9BHerZ)aOI3}l&N1os3>N`E0e>=E6ZVzDyPpvz)5>Dkp||XjS{-R{6fEBLx#NaR-
+UYU*WD8N7_A#|%o|g*=R%&^-4zRiMbah;Zd7Y@7YQa>L}IafiB6Zth8^u`h}}I5<xng1VMGy^4VvqT3
+F{#?;TMGo7^>zS<@K!eyvVn<tF?nnGB4t?58;uMWQ~TH@!C2&*tvL(I3MAH@MSnqjB~S~JvLfCPg%ED
+UX9OjF=UtaPFVJA@*$4&;K7Y10i96_NobNUn@r7p#||<ykwU2wZi?`TYgVGC;o`!_xDbM|f1t%~Paow
+>SLoQ7@u`61z|uN;ukBqv+$$Wb5r<wRkwEba&VgCtW)t%oAMENKCMOO_%ZIby_d0W~jaMu61GK|AI!o
+@)Vu@R3ehRqNM=wozER=ve2h%Uxr~P28-V_i=Ut<SU+znDa2+so}q%CehNWfO(LuSldcc3n(;830NXu
+@IjZI&{3L@v$XuGHq~_{b$E=0JsoQMtd>^P>6#`LrRAZO!%Lekp2v?`_@VXr%G02{~Pv`T;xmxr=io$
+R>f8_Ha--SeE_ZwgvsLqsq2lT63IL$xXOik$uQK*2jf;QkUm1HdG7xyovpfDD>gBC1%{kI1n$UGW+Z}
+EU62{o!NHoap4z1h>uK+qVABmq1z5u|4rUVe|;REw?#A2JGscy8mAvFsjW|OzeY@m#X<Yy6NzE*!79q
+jyO(vAw8#>ajovU>k@ofDo=d^*#vXl?e<A(-PF@z7z3Tg^Y}ThZhuA2MM#ja?K@Be!drd->e1?Rn;P6
+Wc+h)MkxreES^FlumM$W%sR*-or@~rixwhxdWhi5ijkUd&Igl4A3(2~sy3^&*7sWQ73<J>teZ7xI}c&
+kXb90%k`$kRL<X5LCW$h>p%^BjjAfuU3H=`bQR(E)1~?>S_5MT^ukgVeT|Pc_R3%_(xF!;A@Vr|jw1@
+mfIVC!s#EVAQl1?9$Q8I#-HHaaKC*bc<R7*)mCSnA;#EFYPrp5!)e_R(s{ct=Z{%30=6Ry6l*%H|$Rq
+`t+^r=2^mUWn<~M?^68QTRS6!?^>-Q;^-JR=^l$U@1t4t91TB!+SlcDDEd~Lt{Mg_w~VjC*Gh55agFL
+V+q*u`8F3t1B{0NJ&{}+txsv#P!0?nx{8NOmqmZ>>q$5J#8n#g!UlN<Qz5yftiUX)K3YHSFbzIFnC!G
+=26wB5Tr+C^M>gfQ(5PEvtN`-r6s9#Y>7(Ub2+^P=+`Z%$=wZBopv|^HFMi+n4c4qJt?#laV--|=c=t
++`8Ualg>5xx3Ol%9#BgHkYSkm&Jr{tH77zhFUMO|JwF{jadIzjVLfFtqRP^`jUdK~NNp6D)?T(Kd-uB
+>EXkTcc0{-`uk{RncM_Kv<6u85m<oQozsfEvBVG0r_(^Ee5z?VcR%GT5k1}O{y<LfECvoCV!M|GJ1>R
+DKM;n<bY)n=&!0cG$2)JzHzlpdt!~5GXm6>z!-44alHhT)`5%{118p(&4+6xi665P7_-T3l_1JrIpex
+MBHb3TvQPB40k#Rc)KcnSEbVy8Z}gEkyY%z>As;Z~W607E@ig?GGqirv?62|hqW*h^_MLIoN`2;!fiM
+XJWDGji9BO#}Vtxz+6JQ|B6u%vt;-C5s-G=*a_Tlb9%Ko^w5%&0<J|LOlPLoE)*+!Vx8Vvi6K+G$f>A
+qIM56!WO@nA_JhlGGxY8s+wdTZ)9a=H{FzD$gLC6?0fGz8si7qaUoV2PurAjn)~8sVT%Gh(eEf1#KOl
+V?}G-YLE{t<J${?aJ#1X(zO8nKw|*v%RG2chYRfH1?O9@6OSP8+j$hA&p(;u?_8)6XnBVPj%S2#F>$<
+`4CyG>dl=7`TCa@uOCy|vSOAyJqfhSRPQuip~lDYwv+jj{{Cxa^q<4o`x?zQT+IcMe_&xfeL?K|H6LG
+>g6$nyldf-MUy0hy=vJ;h56a{6vJs*S(1SMOdfy)NJ8?eD(<B({{T>TqLTQ1-_hIlTH%bG$KKsVIbYv
++!KL)keHJ(;XrO+Ltza3I(yoa6}=rN5HNA~*XF_TvX?x$oRKs8=EsE4Ec{nh{Ad`~f*gBSk<lmFo@z9
+Qpim;X2}hLaRVgI*pQB^aDt(U3(LeEl;@;5g0T7(*eSiVYH*+%mg)SFEV`(d&$Df$NGk%;rMBLQTnnK
+#~32D-0;-Y`O$=3Se~wp*3n<gWnb8R-no@b1-0HSZr-KI4G&FK`(~>lloN<TjHQoh$=UM!U9a7Aqn_1
+$bnLu<yQhSn)yf2T!OSIy`?GfVw2%X!P{XsDV+6W0R9<hp<Y3CU29VORk1-k2-${MN&Z#7r$WB(t)A}
+>pW8zFKerr<-gl`p;XLK`HBjAaV>)X@=me_o`X|*!_P*otd=NMX$U{{%*k8ZPI~vAbQZ*ot;9&C@-}e
+1?k_lg-kpzZ?rpLXZHJY7|=r$~iY%Yd1NF#2?rr;;3g!L=--GuJlP<(X{xqhd5*KECe;0977yZ(_6B>
+!v&f$vJJ>juv0yVRj5@{ZtMK~nRp$KrRH&cD<#y)q#|$4}7g1l2;=lAQ$I5zq1|<>_62#9fv1R`Tb(l
+*K-tkhqBJx|t-#A(TaYXt8)A;Ny-vL47AKPPMqb*H!QFfjb=`RzvnqUpVf>Gj?RjSJNptiWARjE`!TE
+dR6Lv3E25OF(wI-Ox~)((Tb<8W^X6fMZ?y@tE(Gc-DbxdVs5B+@i3X=qns=)o1Mc$uNIUSt)vsr4wMY
+EEL$hVyr_J&=*)b$-h<=C=sZr_@maV$)>taKwO1!6O!YQ|Cbr=HqL#Lq^+eM^<j$abSCi}MG!$IPUL6
+(g<vzREIQcRL(3~kOmW?8zQx~u1b-UD|q2o81MS>^cJ)qVoHP)sdOoMb4!FJjEw$m@p=(ut}=T4{EiT
+I4VL$xBLXeUIfG$E`VTjQ>v0TpRbfT-O{Os{bPUktu79kmKl{3%@7^Jy5!^<Vw&c-Kb3mW$7wU%q>Jl
+hVLjl(^re$^(YFdY76WBJ3YV++#%_zM1~K46PaOvsXm<Xz1nboqauD6%*24lw9)zic@b?z|5dMna~?+
+=k)6IsNg+n*R5oI#|ALf-MkRRW*&cu=;1Y_JPAv+HI!v_LR#zSaHD-U#xiQ5+Ks|<<SNc!cX^@;sg=J
+kMb3_Rrzxy)S)3qvv+P*zBfC5Fisa?xnTl@#74soZ@1RgVE03a~u(Z9yC|5oh4Veu3PK}5)#^~{-&+`
+u*(?2#r?;(1J8`uG<=4*W=*v!`-S$N%rG51M5`XfI5F_?wEM6<u_nD*~lfAH+`0BaY_x)INJh8+&AbD
+XR&Iqe82b_D8P%W>$J_mxaFN)_;;$vuL6-HZE?AdS4c&*(9;)goH<`&g<nAtqJHkR)7dE>JS*lf6d8t
+yihJab2>#GfaNT)K4302R9pY<cv0!Dr+}1csAIDTtB=Q#ojFHMbqR9+F>FF2d%7CJ$yhOzAAF<a=5L#
+l6}4PJv(0Epy(-c&kUC-Zwuv2QZQo5$GyhH9>YKpJ)ZKX<Be+ZhVPvrU5F>cmL`$tFdhxl?)|E~#HqO
+vAsW($`A9e?EPFZoratViN65X;ertsE`2-)!BpQXqFU*UWD%Moq<V+9-=k4%T>c=bO*vF9I_+8GWuxU
+7plACwP!p?KFe&^?fGD6HcQ^%=5UUQ|4dO;R2c8gAD-Jw<ntjNN0UuIG@Q9q58^47`r^8oF-$V^=`ew
+=&adFnzj+#MND;x2|1wFYuJ*3m8q%rhZQ?}$7VM6GxD+obvHqr(o)8+x~;J3r=`2$ov07g`wDl6V|fE
+W6|3gC{iD^UGqu=u)jREog3osUG>ubB7;xC~dP)5xirClHLV-6MSy*_Egv7h9<lwH99_avAWzz-;}3I
+={F5dDhV$jv|?#JSvu<RjY08)yCZa1zhoD`$g1!rQSW`a?N0K=@@B$yt<u#pGuDjfVw_)IEi{%TbIaQ
+f!?<`a&=aQKnJ~S&@$k0@820xG*q^z@zad~h2tAYQgS;{@ioq#_W?39TS&~9YhQLt_M-dhwNeuloJSB
+@wV2}bmgk%ZgJW%juHf1Ul6i-1NHs4HJfxP?YJ=WWZ8AE|nfY;aNHodYXFe*=j!LM?Q3;}c6^ra94<o
+H*@l>Ew5gQUTWuB&44%@U0U!}mA~Zn1K_FQSO~KeG>U!maqbM$aj=HG1QlyV<5j2#6RCipXnp%WSgHA
+Z-0@lcAsj%8-0(GPHF*JCvdQm@H~9@2~Qkb~Ngb`Xv6(J=TAjdjaYN{RQr|{LH-!@4P@p@H6*1FYB>C
+#k~Oag8mNo0@Mro#=Yv#b*sMVm8iIWR^_9Q73eDvW)7|!*I{|+aK24`pvLH>M{34*oyyx^7N)N(rcWP
+rz}RigEs{S=23s0ZKTE^I?eVVK@hj?TJ7{<9oR=tQaG?}3f6&-#fs=CqtHjf{{Ux+yVdXDKplF}yl^j
+(K>VrMZkD_y~STk*Q&oew9P+f3-Ib!|OI5q^{>(9B2Z+a#Cg9+Jk_sCUWymmQq!)E*VMr<~6-R^plnu
+LQ`!axWwFkKmuL^K0~g+re_a_(KP&&FZqjM1o2OD_iI>_?_OX;m8M;@%fqwkl~JBJi5%hLb*?UP?W|4
+ceID<NZF^$F5>gvu3A%o4WgdP)h>@6aWAK2ml;P_EyM7nV-r8006fT000{R003}la4%nWWo~3|axY_L
+a&&2CX)j}Ma%C=XdF@wSYuq>#efO^r(}#FqVkmv+5=bG0!UpzZC|S0!6jx(k&nS^4Bgr#yANIHJy^{P
+f&SXjQu-%0<rSa(F=<1$(&zV^)7D)ldiArQmm;5<ANpiarmesm!B`^c7HOex#116MpTuSbQR!r(5yy%
+J*oRG2xYNibn&ay%)2g=zjS>QRMZnSaCb~Z^8QPE4b2V-%2E>xx2hf9{eTd}uqmlsLG@TrWhS=c7UCN
+p4lYYMP&jB%S+Lc)sC|2FK&udl8@e!9)CZ$Gn3_KQ|<G`zmL{jneS6D3saumc0>lAV8G)|m@GPR|?Wl
+YsxM6x*GX9dlre*wC4q*0BSy16PhYjX08b3?7`}g%fJ)b477Y(1gMyS&ZKwh`Y~>&!;GX63E#%(ezmo
+t__)Ol@pR#T|<AD0EWl3$U}#aQri9wLtLd+XKskjz<CVqR9tupAQJ(KA{oG}rYLc+)W|3<EPwzM=1Ei
+Rj_$-KP+O@tT(Uhkf@7MpVJc2c=y__2C>rLlPL8NUE{MC4qbGQ}<LbU!g@Qd%Kv(M<pBu|M-C}}fa5Y
+za>u<^m30$=eWyR4Uq2R1fN2$S5mIo?ApG*=G;2Q3BE85Wa5f82L;NnRJu{p9OFw<MHhY%H>PCI8{2T
+DK9V`l;N8RM!9TahHLx*_CYC4Sx$SsA-gGc<oiUDrC4CS6l$#}q(GMa;3_DSaG^BivlXFz;IHW?1p|e
+SuMf<L*%-C{CKpb9fLg&#~hK<wEIm-DJmLGw9!eafwOa(M7PHcUqQMjrc}@A^-E7Vk<zwTMIL+{syH!
+BABv8T|o0&z{=Qiv!N;|w3JXdD2ett84$31aG@tWlRWfUtZa$6xCWaPq&&Xpv0Oz#OTC_@i$*kAz6Vu
+mlSP$YEVDZ;6xBt#7!`N1T%LrDa)+vxPEN{@0V*D%V3`aXBY#JIIA~<A<tJn^?t4Yh*pa-<iL?|{p{e
+997u*&Cw<HP3zj2B8&ov1;m2!`q=AjXXL;rn_F#+-|^m@mbAVu$Ztz%4(hSq+qV@%C3c*lRzG3FwwU+
+WmB6_mf+F=jwh|9GKeoIslT#|s=|hV<A!p6eJhp#S}2e2&Gd*SOOvykbY<``ry=6#r+0yJ9CD!p6pqB
+B<^3lj|C=qe<XLs?a$3o5BhU;jVdcPfT5g!9V=I>}UVm=N8{r6#f^#^ivdsVJ*&JpxS0@%==H`9u{8$
+Xq1==+kAugf#-uZ_pHL7N9)e*u)w3US=JbVqgapcviG3`ByH-8|IJBFioecCzYUrtj_A-#*dNwg%2%(
+;Us=_vf;uXKkw|;B=Vgg-B!splmk}rzp!ULORTFtk;*BuaUmrv%zV)gToWg=j`i7+L&2u_F#ALIf4n~
+#-{+p2Ri$3wINo9n)T?~mH=X(Axhz-pDS?j9vAI>HVjM2sp)A&ae?#xd=u0elQ-GE95>lzBIe_2w`mE
+7@T^N8h36aEWKy6hRhsYWC9Qgec}Rj|Xp^Sus6DIrmkdMk<uM-Gp~)Wl@4em#n1)Jl@bx>eD8yxy0>p
+x(%C<lw2VD;4GmOP6+KxJ&UG(w@x6ecrF6?{aB1SCfCT@&5u)O9KQH00008031s8R@+IJ*2x6`0KF0b
+03QGV0B~t=FJE?LZe(wAFJow7a%5$6FJE72ZfSI1UoLQY?N@DY;zkhu&aW6bUqEu)<f@adL|jD@l2|1
+WVQ3UZky-Ep+cUfF?m8Sg-GA?_-!RxTcUP%WrTPo(&dbg`GtYQ^a#H`mW$)G<K;OOU4ZI#)_J>!$!4c
+h)#tDp9OhL$IlE^LK--V<UlvwBuk@Nz#B8EBPAZfsqmTVSl3QPmx!B0Y>{aOTUu{B#U52ysaqM)f<D-
+erhaXXkmpDKm2Tgs^<Aw0yhkj>G!&*qdX3PeF<_SA|7Fxw_}Hzp7-3j}Tix+j_megTxB+?@SNrNSL}=
+bY!KWgcx15}HJt_$7$Q7`8CzErbN4%PpNo9R#~f17JLHyAlzmwL*uO=!S(M%qYZ)F5=Ke52y=|?)Yvv
+8AEsQ1drX(s5=-xU7)UB36#=TntEdEC}ijuvyz1CEe4Jb?t7!FJGAItx_x*2WTL-u$Ag~d!Od_4U3ln
+@#_rXm-yOljWb`ofdJcd`X%4Xgvkv3};sv@~3q&%Yny^r%sXt+P6$Tgvup+M%%RHy-6~iMi7t!{+Y8V
+Q>O!7sO9iSJ$7QltJVIvv#juzGGqL*ELZE*SAvEltWDiQuE#1eRDe!~{%`X&@Y+Hfh9Hmdhsv^{%wet
+vd({`1*6z{JCyV-NHO*WbvDlSX49#TxWBVwe_IO-PNoDvV^pG0aTv%vVGzs+Us4Q6$9-A<C4mP~uU2Y
+a|beWZ$G#dry(_7<rT_xIBurr?GuAsiZ0nb-?C2R~aQc*SM3Z#GIK<Cm|M{&b25`o8*G)OpqDmjLOu0
+?~OcnIIzL@Gl}mv8op1$(D$JO&sN2eWrLNTw)<!F&8p<ZEHm%cOQX>U=mJvZW&`k<Z8i0ghV2yXXR}s
+zvTca7eX+B?^(EzGP5qEA$$Z;}nGhjHc0)o%8!b5fSVE<pxV9`S`As8Ex{>lZjxnrr*6&MZ=xPoFGYa
+_9X(T4?h)A+71!tZy8l<Z9&lo)=Jx)K9HRIGt&9IB;ffY=rNlw$LA$z(=GMi4zN7W|@Udq{xVXTorDk
+&0C4S4fOnaHxSfODKm4wwRaB_ZWn{aT9sNEjw=#5)T)2R0=<PEy8|CJ0C~PrX#YR=WuCEqzteHIF0==
+gk=7>PabNvy$t=>V1x|wm8Sc><?39Q`fu($^c%(VZ&1BHheMS;@s9(YtLz`SmhenVug#HS)x{Oty860
+vku5k-R8b8XF+LjaE_!p#)=gx^H3<-Z0(WBFz;IlmDX;_u^W87!s)USVX#lAROfBt*(vkPxP0Ex@1>T
+17-7P>NGQc-;f{>zhuHW}DES?{tm0%|TVWiO<4-OO=Jqn9q1e1Z$?3GxEzZ3=aPKGg{`hXx^X`WI>nw
+=l4>MOa1Gp;ZSrhF(b^o6>|HWzZua2AQoXOBE1kBt}&;YL}(CL&eEY6*Kd*@$1je9$2vo38{hJ?9Ryc
+BBbB`H_iyCfZGnhS1zr7BOw^s?pWj`ono=u3T&s@OFbw}X}_1?JGtn)09-rRSTYQ;Cx)wDv414#(rZN
+E9W$(ld`_b~KR#jzeMPEHVGN;0qR*S=emB#~nVE5mOB>hcKajCwIEHi)UF@#Sn)cmHvTwdFdn?%~r+o
+1SUwjN5%uOQM>C|;=<I6lEARc^@gV(KD__M<d4%yk&XGrtMP_ak|g(cs*tX1fgeW+K`ZL$tQxt4O(L~
+2-#1N*DUqCOnQzKq2j+?>f5W(+_^kq217=~0srZlXz`yT4n0i&m%yCfdJ*TyXbqJ5@XL<Swr{ahjm!*
+A#g{V(7sKcvvVt-fu{oZZ&>gnzD>)Pjs0LWjH8R=@Rz8nq1%5kyUdxzV{Ep`k<n<LEp8}pFxWlWYO<9
+w&y=xb$nhk@yE%9|MkW*(d!y!6t$rNWOud=X@NHhiMnPDs|XfMoEs;WYj8Tu$#LdpTrYo{J)<x-X5t0
+8mQ<1QY-O00;maO7>QNb5|VwIRF4EdH?_)0001RX>c!Jc4cm4Z*nhVXkl_>WppoMX=gQNa%FKYaCw!T
+U5_P2lBVzTSA^7BEl3H3e@Aq0j|4RIl!gYj0F8QYP*IgMsVOR%tfCS7>(`#gqNZ0GM%v{f$vSzChkux
+xz4qGcet!46-~Mm==#xJ``F#8A$;Y33{?#YjN1uK1@xN^U#e08u^SkZqAMUm<9`FBl|LWPx?c;|Rcia
+8z?Jp1i`~Kz2XYubJfBgB?{qtvU9v-*nFYoVOz1g0}d)~i!`_U(_?%&+UC;xQ!_q&%5KixfU58rQZex
+uEJ|L1paUO#{K)7}5o?ES;5*YVHCpB^6lM>M>B`S6&pKYzS?_U7)z_T8_x_@5v3?2)#9`ZXT)!<+4$k
+Kf(Oc^=WkZ@&Hg?ZcNZx2L@K_4f4c_1)v&?_T6cK7M%h=JEc!pJSNsyngrh@yfRS<=NxEZC~EM{M+OG
+kK21&^zhC0=3)Et*Ec^ryt>98Q}y!xyT@mbzcOpzKi=JKuOGgD^GkH>58JN~KX1>Uz1kk{UfjRV=3^q
+>Y|mc3_~79&KL6vxi~H|?<)xory@=t^>o<3gKfZoDhkyS3o9(l^*U{7M&v&ox9%D3L{`}p``{(iD&+e
+b!y?TAOJ$t?V#A~mA_{U6rN=LrBI<kHG5Y0Qgf7tHs<L^BC?{|-{<CU$xU*10LYVmf9wSMQ>8~Pus`4
+b;}H#+_6_A*xE@$Dzy|II1*$4Fmn_pfaBhnV~LB^r!@{t{-jeRsG0{QB<upI_ca3-R9VU!Q#a&tH7=_
+4eWCf8GA|!>3O_{QT>`{vqBQGaY}8^~;v-fBY#-@WmFRdVKck&9Bk%Xy7lOJpK5e;}ai#^yITAU;mZf
+fBNL>&p-L<tL@V-o^Bs*Uw-)X>n9(7^Vx?_w=chW`sEj2ee(XceRX&Dc8ZzI-<stAnBwoF$sZqLCSTm
+Wd3OKubq@WnvAnONgD+ofKRo;UT`cqSyZf-H?OAM*pML%STEmwQum0wE<0Jo=&_8VV-*2xT-rR1#Jl=
+=xg!TQW)s0sEvA(xq^v~bF-A0KwJ$v<UFJlS5ijRMK|9v$5>C1<Q$J_0rhu3d->t8;M&+fI9{k_umvT
+fgd6|ekP|81Xq{-^&(r}Dd-X!xW1zYR9TzyEyq>Umh@v+rKg*D%nppWXlR?A3n{Cledt*<*C^%g2WwA
+LxJV!=GP0zkeBT{2xEOdGpinKltF6Uw(Q2?#0jVzxn0&NBQ8#_{if2|K$9adTiT!@BP!Zzu#+}C0?py
+zI|z|WAM@__3cZm=SyX;{d(y*+tK;p-jD00bB&|<fG02Ra360in*Kdynzui`ZR~@0%6r$Z?{0sr@9TS
+>Mjs!3{Eg4OiVsG2K6q#Jy}TE{z5B=g{j!hTNWcCR{_r;+_v|}%K^^}Mlgds#yozo5`VE`u$Dg17u>B
+BDO$QS0=INiF-rRij<j>>VumAexlaD|A?At#*`RePZPd@tQ>nC4){_WEb<9|7X!9sof!?Q;$E3E3@zj
+)LQxmMZ2haY|R$+urU`Cp&V_qJwy;QJrn{62c}eZC{M-qUZt{^HwDpMLT`zy0FrpFVjS?|kPb{Aal>#
+~we%K5wJ<<F@oxZo@+#xAE6AejJtG=Iz+`c&)4z@7wEbn@4;s*7CL<l~0uYcEcl=dDD*4<3p|8wz}fC
+SoiqniYIKn--a>s*AkyRd;BQJx-Esj&T-zhbMfXnZ(ASbw$9PA-Bxc3-HJEF)7#i@JN?*tJh;{}Znwr
+i#~J--@xXFU9<v?vm*2*58!he(<cz<zn(g)@=3%yY*}s)|dMnYRX)jl_TWh?vMBn0p?Y4IQ+7I6xJsB
+}+Z9fa|>rBSg?(8=)M^0X2xH~;>@yQ(Dd0UqQZzDc5XY{B?&yRS^7CW7pi^V9l(Vfb(u6a22n;1sS%s
+v?I&U)}0&x&_Nr%SKV8Z%NVv%fpjixuhgH>NgcgbAAbM!V;{iH}ET2KI2qI>!%I9HTfH-|T}Q@z=Ry5
+5+Z#N4G}fi^a%4@XsUdA%<`h(;NS&?cl)!V>>a57|_{bDfY9n&e4w*eJefYAzte=9&hO#E1WT3XUtcu
+Z^?FRtXo;}@_vTtIID&3?=hj}=#Fn^*>^t4Kw|XKt9Zf@t!*p*8E<wBOxoN2_I|US=U|YF(MRL4r=ku
+1IisN%-@&3p&s&UUTXdo@HzQ`hw#DF1jg7epyRqH5-^A2n4`HEo#pIP1GqTO8c|`Y5`nI3Z+F;<ZaA9
+nnabZRy47TvGc)s0FJBy8TQ)16!oIRS1hGPA(A9i$@M)U}S-5E&1h*~^hYX>$mSeCGsn1Xm;XRnTW_4
+lkdVS`RBULou!%$aQxjYmT)G5dbf?h)2q>KU`t_ULp=J6pV&?pJ#^Y`5;QZi~KkdqfvzbSq|yF~>5N6
+7w4?v-l8i>25G)?ua&ySl`&RIF4BEu<)7f)_xNMr`;N}x@wHM#`_C49m`IqX>GcrVjss}3mpvGi(jMD
+EL3BdM{(1qoz=eI#8|>~*{SjV#=ONsl~|+bpr+nfabAn5jjpnV>F;Fwg^lwuY%iWw4m>OEj(HQ#qS0=
+2Yn_<xj0dyTV$a1|4)*bI;FZVphNp<%4!T;{I?mw{cHXf)+g-8WIvaA~ole%YOzbk2C!U27pNuaIr7_
+8|f3Wj-E#9HoA1q!BWJJ5M=2yGNaT9MKO1O{kK<DB1(<etmvF;d3;gdKCc4K2(&B=n|Q6?7euBkQWq3
+yA5GddU}U||_wFU~aYnw2M<%mb6$82D}*nC_0Jh^G><F$G4mu6FAl{;aZHV)82SrLkHupy-y4*(Q&Uj
+l^TZ*j>vbc3CV-7@*@iSZ<tq$^F*ayoqjUx`YM1Q;+e*!Wtml_v}1cBeccy4`!Nxs-N8A`R7UasD``T
+Z*A1*Z{uYGaO~1>1J!BK`RF^HM%>}Rxp$gez9oJe-F;z%3FFzXeH`OueqHfcfMdm!jd((sLUg)>&j{B
+$=sE3TriJ)AVn)It5wv0j<DZQmKI>{XAQ`h9kE2^h)%oD?cyK@P1(V235MQ{9b?_|qN|-V;auUXMSJA
+O`WV?Oe!>{YF=~0hajTsSdO#B~jCBz>r6hjIF!u+c<XD=}xJWxz&jJ2j;@8FUd-HHJTaPYNQ@>;&%AF
+*y{biW*|V0CG+xEL&d#fu6QSj%<hzUYBVqDkg~NFErSor-xZmTa+P6Dwpvn=Xeq9|0o<5+jVB7yOfei
+D-gHp<QrEi&<^NoY<9xuwZoG@tqi(fTi1HJikr7BhiOYjOkYQ&tL`h6to+-By5@B#hT6oFM>~;x&c<4
+*b6Sgy724RW5++>aw;<y55$4S`{K829s-wyfzmfjXRumyE2iMYW3hYbLWbf)*I?kmE8r7*!)gzk9Q+~
+oaSvP)!4}gYmaT&ghSP3NH%m4E2l)EH8JIX5X5c**jhBhnjZTC^GT5h`4RA>Xfen0DVa3<9@fg~SI26
+7XPZ*0Atr4wbp_-O)#<~Rz#3(wU&EVY<pN+sJjV^RNMnt{FMgS^Dr#m}39z(DdKL8e2OjW19(HfvD47
+M<b(Fu3{)!&YvbT@Q+2~q-Zb|x94XcJ&DS-}=hEf{uy%II{T?qlMW0AP3ZuXY2M6aZ&zVK6kI0uNsR-
+m%2EsDp4m-8w`GVy|JJPREiFp1b&k0q+?%2e<_2u${UMB3L{gXa<}hbnk<paWJ7kJ{}zd0e>%N#9`7^
+Hf-2pwi~#l+8P52BVs^J*TCqbtMP=18*<?BNn%-ykZ>1M6|fq6*nN#%bK&X<E{S0Q?dj!kb%6xDU*La
+`lvGSSmWF}jAF4Blds~KaKw5Ra(tZO2+;nz(EEM^W9>C<qAV+BF^ta+RTNqJv5MaD(Z1^~W9AGNYFe4
+l}4>NE{*b1`+bXY^@I{1*T0hr6?D6HyPjD9DZh^cLMf_x#K75flBGIAfs!bTh#_RY6yUHD&cNuh&eJc
+Yg0G*fb_@DT@*K-7SZvb2S9^>)oe;F78rJAMD5gJ#P!Q6~Tkr?R<Zpx6pZuXz1#<jOG=XO5tJ#m(@J;
+UBPq1=3#t*;(CwdO{#=6Yv5S3FmB>=pfOL=byMuy0d{=wtD5UYbU;)ECBOs)-;wAbz*GM!R}7gi{VO1
+PhxOp#kkVSJh1c3k7rN(umYEC_?Sw>tIIvBvGH`wKepc>Hy}_>Q*Ne_eQ_+E4}&ABO^kBxSG(X6_CUN
+}%kN}kjLQ6}0AK--jUkaU$AaQxj7`9w5g&`?Zj1p>)zTi8xMcD&nO6i1-ftXYmjQ$}5{iST&OlT#sVo
+NJ<JfVpL;@T>7@dfe`z?HJtXnK%0~R-Y=m7sVf!5gdUF3z8#ipyoi%Qxx2&fy#GCXT#$%w~q=OJ)O$&
+C|Th<VUEu_2Q-;0b2Rlhryk?2h{;Wjfpqgm@-Cd=0;)ogLtkVUP(U?xqL*bPq7TqAS7CnSSm(!Qfd1W
+F#32EJ&KVIuN7fK8}DA`Egi55p9X1*3z6<DAyh*XvAHo=3(xG2Q<tOLrBlUAw^H-h5L@ix&Z_*-S~}B
+EmB^bu-P_Aa)2x|BeGXgv6IoPA)<@t!}$b|0UjKQACAB!@ge*}IQL2f4X;PY%rU!7v`ccj#_q+~&rXW
+9YgnXMdL>pcfKj#^xP%~w!v)Y+9UiU$csX-#IfljB!wfMkC)3h8M#<i8-R;MyXYS)8a7nxRd$L;5(BV
+Gj>3ThAnRs8!>Mk_w_MElXSs$`LMn3`RH4lMHdNsjgw;!Og(P^>)>cpfOdk<Dizr&apn0T_t9mAeJwK
+7YYAIIjq2}A1OE=|FhBe8U1s}c@GW>_8KcG+#i2ugq=wJ58Z#(?W<_V<J@0gE-MiVfh+bXN%=5MYdvt
+~RJ8vao1`F%T^!yG;Ixufu$Irhho$OJ@2L;srjYvy2%i2YBva_7AKOytQ=4bdZhMq;GH>6&Dh&De=Pz
+F2P_MVYf1Q@o^wQw@H?Vkya-D9JmI-(P@OCmrc8YVL6QIX=jnbvTh5yL$(u_YAO#2K;Y|UQX;@kmKo;
+FUx9qx#n1<kabZjI%3DtOl0JEBBStlLnI4nP0Rvh92hk)pb+QpUGa@@6kk&>?ONeHHF!X2az`&Ey-v)
+Lo`gQPcxSW&BnxHI=12CP-?qjP&>)!P1vV0mPGji_PZs3yW414y(F`aB7Q&>K<Ya?4MI~hUM4K-;I%m
+Z(;k?Dj#b<Is}Mz$NcBtAqWZOkeu8L34Pm*8XKN1<J*FuV=KK$E(|#L8}}u=ouySFZjJ^0(+^B$I@0*
+bjh9ukv`#2yj@g13ww<GF*H(?yX64kn@yj5J<ixOsvvhDALoX`{08gKwkn+LSM)N9=*}QCgFVG$boem
+ekUdaC)LkvH*iT9T`Vljc!7)wNI?G2-fGR6CJ$h^lk}wX7O+Bm!XNz83{}!(xG%`qZ=$P=wCi_dWUyo
+>83)$IN2jsO`GPbt3bU5b26ZKzfs5_AZsAaF3gNNB3dUX}py6xT?TrU^1JA(q!jBHf!~)UTNJ|R-w}M
+mKk^{^*A8(5Iwvh|#zz&(<DLF?n$y@hbp35gNH$Vr{lLC4R7$<!L!_wIPBlkrl_7UeRIFZo3K$a^L3i
+h$lhurIwe;}E}sm2<COK`X()9p;`Okh}PXC-h+AI?K@kakONYF5FPC}crlx{dU2BPFf;bC5(vceFj|k
+ZP>C<{@xNe27<KgAL+$cyD$OC6s-a4gdg<s6_I_4C0*$V-yN1%;RR628_@yyhC~raT7CX)iDDEa-@)R
+zzK4RjZ#a4B_9SONbB$$JB|ipCmX${<;ZryB}LxIc*q<r04I6bW?f>MQR2;)DV}tDGX(JjHq2m=LGGK
+0Gwn9&0c5XpO5R8uN)6H@Qi};7WR{{Kb}zep-!)2RHDMJd4n#h(9st^df9O0;@5H)wRtuz7alOv|f*U
+90-|)`02<E!1Grm(0UZmx(`3+nWZNTOheJx`l*=p>l=87+!CEOPv2_7>#!K?x$@k-4s7e1lZcFk|#lG
+1(Il!XT`Xb~KFBgY@b^qS1x*M<v4h|k0--vYvhJ1F&PH*iU1-8vNBD7oqAhhYgweMplf6kvnnfk4ci+
+`Zu+irK4Gyt#7STHummV8?0;7<QOc<D$ZMNv9F<aYIt@$4+I7zfw`^P>7>w``MlJzcDqD#}WYH*E<~J
+fDs>1)ivvog=`6^zMw0yt_JT~stB;)u_0@z4Ahc!k!YTE)6HtXaxOc00AL2bq?%SzN-I_iihCP6jeIu
+}wn>v>4+-a$?M~ubX9R$>aT-hL0tkhb8O&;QmGT`f(io|aBN?es8kJOjNZ?+4DkU7+#Z^~f80jBYi=Q
+l~ogQukkeWoR#1GE8xJ`6);Hb=xkK7jxTmlmt^8hLXGeO>zmYgi9Ta~P(`@@|F^qvxHGI@okvMiS4lH
+Y;#4L=D25^is&9srXhsRoPH<*Hg!CVzy`@2~?cJJ|iJ{!Au1<4~6`fg^&ujD~y{c@9QDciLD^hM5V#c
+roXAJ4-|0j4HYi&qANrZs3v%P8^Y`V3K4_O+07g04y9iD;~pj3mX<l?@6A@WPS-a83Zo>(BVr8<7*aE
+OdR#ZRwOMkR4s{BHP{m^XYNK=4@|rX+E3|_+!yiSo5tJ^5KVErg3lTuvj9woyS!#HNt0a{i78Iv%EFs
+xIhhfTYaZZBhFi!w@6-y+0ZoP2V8h{3Sf-dlVIu&UYwxU@pOZ9zY(X-#8?P`AdXY)!cA+|e0SX$1qfB
+Fn?#+Q<-6nfe!UN!jqdlyM_O!D>9jCbB5)`oYR458WSha$>6>Bg!3GE!DWQCdxrV>M%n`k$TUN|*U)4
+)5Vrg-|cJE6pvDRL(tTGDi+7KDoUEB<WB{c8$-)`e$+F257_ByhDTj?@j88oQd&!{$z7I(`zOsz9GK8
+2`q;Y;NJ**a+)uP$rPrZs3w;h4x@y?ABCWsO6lKRGWD&?H8nEO^&HGJ?dHpVP8rRirRJ$_S+y@lKZHQ
+pcEUuH?5@m?hp_o#AS3<(8UA0on}wzpALm2+3ws~x5LSU<kp{&q)u2@0XL+4crlDPQ)o&Y&CG!;0nDh
+|JlvdT&hMm-)3t)b#0s+X5Zkcghj^LsS%$|KS@S%20>GkBIV|)yVuq3KYBz96M*`A!OPdk{xVOc=pIR
+v1nR;w3668cAsQso-21>?2sMU}#?&WG1zC>o6qSlZIBLj|Q2Zw{tEFEJ2qsVsR$|`skeM>p3DTtJcL}
+c!_u%y7hB&jRy7e5IZLm6sVKx=R#R!avt_GayDxQTc|)4dt02p`AQuKE%j0_C0N?mb0ixH8_qNxed3R
+|`DS0h7ERj;bXO-wZ~;nVI-u1}-U-HX~mnWM#1oAaW2n4!K3r0+LCfWCTW#8r(r_0^R}-PcqUh3SaSJ
+S;xV!oCng5PLDe6Zg}$oh1W88EoR9T^fBz&YLy3e0%zUo6^|FVgxXxGCUK`F5e&wXPj+zd$;A(r_Vf=
+Vg6?uju>+&9mO9g)E$cWkWIUZgRy<~<#L(CSoiX>TN8qz1O$O#y+@YbUFTtP9tUJZ%_nX)xsuPIc7{H
+LN0mU`Ton2DZ3B^+gEWo5lYzBdHRFT^0F1XrV@RP+ih&Mp9Fs9XveP@T9<b@0zTDqgqY4D?6?ZRS3*r
+qW!BGP%a8@OaJ=AmxoG@Q%H;%Go4jhwmQlQ&dG1>5VSiA}c&uoyKlCR|eL#A0Jd9?+PXqR*ExWk3>EJ
+$f`$l}yXuQx-wkDDPPrIH(tBcH)Wm)PcmiI`INqg@YS8QplrI-$mMm>pP@&PQ4>oY+7^&yMkgnsBpQy
+sRIdzMI9$IRRkK63)L#pL8qDI?%MlkaymI#p*lDYHU$|4&+-$w-wtpIf`^L!p<5PY#Yfd4z(P?F>U3~
+(R=e~c{I85WRuHdI(a8n9<`;blseCou@XSHY1jj*-*uwITlz|kPP(SHOnlIl16Aa9T>F-zlA{<uW$+~
+>Gu?hqu)J|5)59wp@8G*gwDFz1Ep_#Xa2tw7_WCbaI$B*pqNgb!DrGqJ4r~S2E+n`<G5;SO~(;FMS%#
+_#=f(XhTD1iSRZ~em=xTF$aVsjXyPWX7A0NU#^yaX9wASTu*d^Y%+!8WPXd8;{^wS;-aw-dgEJge;@j
+})yHo{oFLfoUFH#i0y7HN0I46VRn*3m-dJvc6yV;e;<CoHsqEo}vg=;bft%25fe*Sa!miv5ZxEb!7*^
+2us5T8or$e^d*>1>=_fm#qzLFSW=g>1OqjTT8EL*#+?TkfL*Qw+aK=6wBHkb$%5Zj7gR+0bY{!dvcCj
+dL?(ETjRc`t)^3*hi1<|<DbWmV(}spPa7o`?03L@|X!@xsPkP!d)}C|~AX2Q!b#-Eb<wDRRRKP@ZnPA
+!tT+(qC1B!H1QO;r5#cGg7QGh5^g@)Aru<m88Sbw_kHr6mxyKuFu?zO6p#Ys#N7`-%tlBphto0JVhlK
+}aqFFKXErRg&9sLgujg=ncGzmRT*;#bWpy$SAXX!$lti%kXx=e}|vmfD>gq7S$e6L0(5d4Mm0<cJS}?
+@6MxB#Q`uj!w0p4#5n;s~G#SLMlpKsoVl62mo60;7CiNUC9s=Cbk;2`_?TB?kah3^UKPe`$t))55!sS
+Za=^>d`a!sJb+7F=czu5G|4I<KD<*f>1^=m2VE_AF&tg$H-W>Xla1;^vv^Ri`9=3yOX6jh2fw5KfOdu
+NdzwG|SryT+FS>@}-o};Uz?(Id)U}~iMDKafEg%>3aF8LQ`71cfu5y|FHVJCjjG6`GNhDBaXHNi?BYE
+12?zJ5<403B$GN{jpm)&`mEJ?*m(Yi2Vr56XhJ-%p=xYwcr;kepG_X@1p7DH1Vz)tO`aeB4x?g}bIqD
+(Dm?&uHUf$R%$1))QP#WULtT+)`_W_N$uI6mCak_jfBm_ipIsk^@Lxpfz2QxyUM4pU>y$ac|}pgfQFv
+t-mNs_^5KkGBTH_G34~3AbTBkCOo4408_UIW@z6t{b}7Uain7WCKLNnpHYo+^OUo1tr)Z6^ov0Ef8Bs
+ab!4}4o1=aWoPJKJNT@ytw`rEL|7}TAxqE$ET{HbaB2-AV_0AzTj>Y|M^#S-YLa25U39O=IQo=-ZJIh
+x5V$s#154h6Ng=sA^vS4Z;1)_D2Rrax`TxZ~RCKRY;qWYMCeW-*50I<4T2jz#D~iqh6%GYhV?ZSijp|
+D8#)Pypbg!+N6_YK@s>fnlNQ$g!0A{w72+KmT{iK75Z++KoPy4H4;aWHNk}i#Y%Hbk&5X_MN$pi~RRS
+^(S3y!$~YdS%80I;fsPa;g8c|HJ-b<+SYty%C&GyvhN8<;M;bx0I>db_3&2^TGNaVPOtbs&9Q?N;Jj(
+_=9fT*=U1FFy`&b6dksU=LlcW7j(`-^cvsXED#@X;Iq6ej~nEFh(O?NI*KG%Z`$A2o3;A4PHCC&mI_#
+*=mSjiXy%FMay`M?lq8-3*d)rlJVj2YQ9E}GBjcz!@zaI1hm62uD8SXX1&@CTrzaVjcOjQtW$Q_a8Vt
+FP;rBGnE>3Zd2E-PDP{!Jh^b%e%4*h!s=8P5r;69>Xh8>Ftbxy}M6v>|WyRM+4bb=&YR&Etv@|G{M)E
+&u@==tU=`XA+2D=q4L!q>B7AL6bB3rOCNFOR%!sbbZ>Jg2Bv(|wgE87iRQYaP`l>o(Bn}<P2m;0f@!Z
+m^pzzM@QcD0?kqYs&O_2@7bnO{_NuaQ=&f&p!5>Zh!VxQ{hDJ*C2CB6XAYI*M8gWD5`oAjNIC-}*HVf
+lIpd0Us~&XV^+rhzX9VgwYLRxG-O%n$tmi?`{dzt9F9703mHRa7jm-v2_LZ41Dp-gR0P}kI_%kRf;av
+Z1hm4X2nCD8U<+ZdfhL3K=-;eYp)g&h*5|<8q41Bj;(3QE((kRE~G+})gmWc)&BTbK*5Dex^*1l5F|_
+IlO<29q*e$_Oe}+f?|c#{L*QZSoc<7l=^`Z^bAHji*5(lu43Wi-MS-F<lLM=;8%9gnp(jl&ER&EM)kG
+Yr=Tc8_wTtf6vjgyxqos>9D`piAwr2AWmM%E&bcjo22*Cr*Ee!L>`T~<|SH6TPPyr?A*ey<z5vajGa^
+761gI+=x(l<Me$&6;@l5GD>{tSu<J42VLoDoaXy|C$qmDyct@>B*z@{)~{V_V&*KtpO)6AU!6{#Mbw)
+~OCpZ3alqxkRqIp%Lt=lr21}7RT5-mE@wzD3vBvz7hC-*#o-QLPA`Dh!s+36C1<$2Smgab}0>nNS@hh
+DnD)91%(`Rt1Ww%^MLNPnByWQtw=T6vI_^OUJ8bV+O?6Tyo&cV=gTbtdQ-CP#_G8*(7jgkH>u1$<uoi
+i`wg@;&>?qEgbX1kgnF?J(2&Jmxi50M*4EWua7lAbiz78}X#5iot8=ACXoV`#uN5VLLqJIWW~wRqdiw
+mU-2p$zva3?Fn4*~)zv0c>QX^=9kaMScqaKEArI0UF5cX*D8rQm^dmWjmoc0nEBa@<Z+?r&m4ixie43
+t`_r+H2eUZa~JG&&}FOaF`RwHyj_i_QvH0{3JJxm!ad6w|lSJSQQq0>Fax7$|ldBFaXt+V=}TpnL6Xg
+erjw`YvpfMv{R#jZYH&x{X6Ut8qmspsH}AC_#y=?T$71GwSZKj}dUGghlkzbkKV~9b8RbrX(IK*iiS>
+qQZmHALl|lG;<^#uu92$R&}qi$s4tmZ7JdOI3;P~LU}2Jep=TX4un0(hQZ>R$C-c!)gyKDvR`zsrCI$
+uJ%|a4te$Tf%p0>>9Vt)sJZ881{_t7QC)o7i_D{Vh3l(uljx+rq08+R=RY>}AJLqe~UbNBL)UJQXDz{
+lV>GH)BpnL6D`2c8D<%E6`2-T-2Qg)9aV4(#2W|apPwXsc!<t@##=?xP1p?j^n^%?C~AKv_pq?5fur)
+$&4G+To}pgu(2Jt&I~>vV?-%?qC$;u0`GvRiUWL$yD_-ZBY<5>=imqep@;6i#7rb?5_FEk*zP+x}9=!
+F>-n#?AVz34Hf}9=@Q-ElwQcbV12#hPZ@JWU+%aC+%yOJ)nEtW;#~`515Jcng!_KuC9kYQj)2Su-`=3
+Y&s@%$h9n!z2wg-y4TUttg#1ahRP&&p1`j3>@J5vhHe)1Y9)qj##c{`o^o~O7s-P|w?v!=uj6P2u57S
+IT{w)!syB~(QGU^tDmX*qI<n9ur9GT(Og!uU72RutdMNUEp2Kdg^B~_NYM;s{gj&{U0mdFbLX%dJyl&
+m8^6*2Rqe65Z@tFOo7XQ>tJ$j-2kZqH?HFbuRwY#UyrrciDU={d7A$n;0!qw_tQQ4QS;MM}65&`fICl
+Cg7Pxlbq?vBEHu(YGeuVY4vS6arJ+{fr%M{{eE>|jm}B)km|R;GyoCCTKLIg*>1U7k|(!_BPmutUeyF
+8UJBqN*e($P}r;A`yoc)^md%LE&&kf$6DmvXy#eDe57~_*8vd=UXbe*CH=RWvQWVELC@*@`&P(bu|h?
+tz@UQ3?^tg-E!#AJ#^>Xul}B{8%R*7vDB-{$iNnnvr=||$V7sts6d~n7FM^Skb@xW5-jZuJ~8~+Vk1D
+&TIrMzQmB%YJ;uqF9MZ>di-UxsfXdq8A-H@qMv?WxrtVb<2FElTTv;K=6ja#da*V8-XZ4|xRPb%nAON
+T&3&K2ORXmrvXS?7MFw1}z9@73Bm}yF~r}kU@B=BR}b5nCNPgmMKh1*oNcJZD~-Rq(BK$A4lrPM8V;P
+FTj{W{$ZMV>;U$oKIq;X$+Dh{dO#tD$?XWI-MOut{P`DUbjaj`y~uH>WD3G7<7~Ln~SEzni(@VKwG3K
+pojGxP*N%Kx`vVX#nbEcr6;@8mfl@tz~8`B|mRjp{Dx@DrqHoL|E;xGjdkL2&V$N=NSmt<xoRmdhJP7
+55cj^mjJSRK!vqA`~kh2{;Z*Ujgey3Y`RVTc-8#DO!+`p%TKa(pqV}VFr6<8z$Vygy!NZV@FgU=6)Lq
+3a|9O~jRAUsHcU$No#G;B#pa<P0`-w8EV+pZ!nJPbUTan!#G2NRQIj#rqlo~?2r}jO9BY%@IGJA{1~t
+rGLGIyv<+`bRWk8ki)L@BQs(j>2v}pkV!~jg}pr#!2i=7)w6Cy+6S$E3&6dJnML4Le>hC{_{W+niEE_
+J5QASfz-hsLQoA2j%V_c)#!apf3!UqwUr+L)~kg-k7`=!b-kCjtp1RaT$9eG-KgE_uk1v|uDUX1|}ZD
+d`{3y;j-W4D6;Br|Ajw-_lH3c3FKn9~vsD$YYXa6gmIlxem)pw97eR6}FyCgz>6HW#D1ooMf_(>W9dY
+Jnr4qXR)e>C%O=3zzVdi$2N4Y1%hp;2~(aY5oZ=%b6Ydh#t<+byj2BabWH(3Ry=DBk2!kQV;j2HigPP
+UZ%s|7rwXBuvGReOa<GD34KdkWNBdG!b+()5iIv!^$2Gs4$ASH5sJKS=h?qzCks6s0^ZpGItplVh8=*
+no4`u`*37M}965gw>Y?t#m)}W`S;nfy-=(L;df~^!lN&;lur1WMAOSs!rovDnZf?G0f0=#c(vCPG~xy
+!m2$at-QAt*ED*u8nK4)fp`%RtfJD0}pomdX6SZ8va9mF(|DX$d=;I!f0?7Jsuzf{{mVm(M35?^><9j
+Cw2(Zco0tseAPVz@8WG*cofOWKATDi3+iwuGHUiUuYUV&?p(Cc9$5|TfN%lJkFWNX7M6Gm?Ir2PpCHT
+NC`p3x~cM7xLZh*Je&&6(lzlsPX-SSA4Pa7E{{S;G6?EPlywH|dwkL*5Q$=JWMNb$%5n~YhH(DnIw!$
+I#lA4dMclAk+_MzWHF{?-OqblJfp8nk-pPGNw=&Q@7v&8@BuaT+q@jClCNabEhtWz9++1SE=Sei@0p<
+O$gOnnGoG{Fz>(cS{J<oSHb+66SGRohzZCG^<@l;ZaqWebr+q^*uiE#7En?qLVP~qlv1z@FX9@M=mx;
+!j}VkWub-G74bi6L;7g$%gvhKf8=VpwDe1h6v9d7lFJ3EZ?QtnnhKuBnsuoL-(pFi=P#smeZ9bM1M5Q
+uzW1Z=M|n4UOKe`L&KiwxW<tiLU+^&B@3jr))B=X{0>HSrzwb1x||%5ccOazX$uxi;~Q?sV#GMpcOY5
+#T=v(?eM6n`xx)2@)H*_IDtF5`J3)4^KN2f_#MURo{DOosX?qeJteJ8q4G5QK%$`H+%!>!+nZuIeNva
+1{eHEJz65x+odQGhO%IE8E5xKnsS*JRbAYTX(34c1<`;^Efs2|91y$Q^uA7~K-`;J=oC-8Rbnk+EH-c
+q8a?2qvSIxp$2SBh#N6)+;rlEW7q|MFat>_en@EH~D=ER>#h9I|t4?~K$onmPHliDVak`a;Ch1b!&j&
+7mdV;RL_ibpbm&lb~9?^6Kiso3fs{3a~nM-+8=L)9>=$^01EVdSwMEoApVP_*SvRqvyoYKc%N73xL3P
+GlO990RPwuEGsI>}q#<e+lQacCCvbvyuwJlB>_+<Q`697;)WT)P60<BTa4O*4>klBl$C8?@dvIKD=W<
+deh9hxNgn^I}h;{q(x8u16;CsQXo~*j*tkG=h2(GR~X0!en3VD>xu(WRpNzUsVq>HO1RNkLqe;JAtUJ
+|RNXA$ZM;zTI^_hAs!a`+lgM2pK_=C68hy>#_cvzRi(|-^y!NSUOY@os>No)8(bc_H4=sC6fs<%eX(~
+%bXj78p)gBuvWsm8Tl^3cDBPU~~ouPXj(&HQv9{ebXHcC;{N?B6!hAS}2vI;?ZpD^1CRy<JvfgqF}SN
+?|Xb@SReZwWdj=MZ922`hB4O(Vi|2DKLa8GxJPS``FZhCd7kSG(w52L}^2Q;S1UAS47yMy!!A*LB9km
+Y?*u$zzDy#XMGtxe-78B)Zq3ESMNsJo!XQ*i=HOLTRoC*&W5mZkfVs!#vp86$Zlzn=7u%|Dt=XU8ka?
+xcN!KuF8Vy?gdd%;iDGc30lP~3>0TNeU|WXZ>3y3LF!&T|BL5L#-IF{JfJQyCLnb8qA`=%W*uKG?7?G
+LZb(P?>b|Egv!Q#f1gha(V`PIB?zDK1R<b(qE1;2%g1YFw<)*tCRF2if5G`EufWAc8K=+h=#v%L5vL8
+Ba(J}27XURS2KiO|$Fbs9i0!Z2ey4Ot=*I`3s*4<=Q3Va#ANd~;~Ci5)3f;gF2=4E@%P0{bA-l(a2&D
+#b%(d5l1?jGFGq1Z+HMNr6+jqc&pLsP_O7#p=rGNak9{su1Tu#(l}O#0YMhFI}}6uWkTNLR~ebps|CJ
+GV-B<jqB3V)^Q~?Sf07+A3wMru#%2S3QgeqUps%DaQcHB3@wyb>>AZ?03%|S^d0l6uQ^uSwa};hInsu
+WdL9WRl>mR+LRH35ZugGmz(-N@B^4}D83z6o`vppI~1B$CrY}TM0cs`fPgangfyXg)1~pTf>yjx!^+`
+dlgNZx;%aoSm6C8f<b(1OKhVhVx)w~AVh%a}AP#l!;<9Ry5-}>@=!XVbZZB7V(Y<aNWQKgTkwdV^YLT
+^}VIHJ-9j#DrO2&ud@}ee`$kn$T{K$QQ?zJw@w|L<L<ecJ$o=^9IB-(%oMXEz>ClQI8GkTL@rkpX9BV
+RZb-D~$`HYEmR3%tQw#{egCz4C+D&*@blm2QEVSjM8%Uj+>jf2c;KU39Nt=vqA)-nBtodUcX@Gz2+yO
+cJvorKaj)R|R8FCO@32Yu%{hG(Be`a#A7O1(olP^0F^kK5q~uE$H5FH0(5Hv<yaACYbFyH^Twi=r6E_
+u~f80jZ$bi^L`eu&a=*|0TAwT;O6s`15q0kl?|R5NZu2TcH~3Os>Fw3jQS=!ZwwF4>a6gI-kzwPPs!!
+!TO1M&saOkJ*)IAL9^5#-T-13hf*5&A8b`1#K6wKSoX?>bgD2pYt--0-=9wnsQvK55b#<@1b!@X;84l
+c#2U<WGy_jryl?_MV$dM}N&NgW}$nY@)j#er6YksNY3{QN+og(O~6a|VDS9N)+KAdX>cCW$Z(OF}%t1
+yIzGe_Q%`=YCR)x&yglSfwQOqIIwKCv^80eHYvy(g!WHDXv_!#D?Os(|UzfdDRvn_8Z@nkg{c$dEx?X
+6cQL0OV0TMa=9srnaM;8)A=UvX^?8j_$QB=a+d<8=>&nqfyFq4*d>g9irM`GdBe-Q?+YOpVzU0OD_9W
+_ew_Bn`g0%z17ocl=q4AUb=!rt)R;4O)zIQoQ9?)FDxEny07HVI=a`2oO=u%bl0ZXpH8SZy0UBFEKAA
+9_+~9r=fkRcZI5;Qj29i<>)>*Q;XNNz(}n^n3(=sQE;FxKLDE7XU-E|w1qL(6ClOs)H|^f{Iy{qxK!T
+*C=P~2uvjUZQk<Vs92!Cq*Z+Ounh-wH5Xgq_)xaL=ViAQ0~7T7)BJB$0SOZ_i63SmvBqEdTa)C3R$ld
+6SP&4Ey|_N>oyBWC1TUJ_94n>Wx>aXsxm@uE0B96oF-_0{1G4B~Z_7!WySS_LUryOn!-jkrUA17YQrb
+xSM2uyNH}Ht7^Vkhl)k#XT{MQr5EbNPQ}I2HX^I36&z=N=dq@vN!D0kd9H`h1AKrG4u4QOMsrY=H(p(
+>dd=2KN)^K`v!m3v~mIu`;BVTrWW-yGNUb0ZUTcepgB5h+#vlNO1>xx*e?1KwOh)Y)U+teSQbZ$|8yG
+hqFq{#6o6bpb<LTV5EICXR+V;!?zQ%O7uldYMDt(zaAweXpy&)6Si3ROOQA?2S&YGH)WJd2zAnF`?iJ
+6n5v>NNJiBZSjBO{GET>be2ZB)qQ4LQ*5AO@|N@H(eAcmcJ&Jx<4JWJ+6!|Jqa!2pAW4j`6R<y8`gr)
+h+@DxupRnJ>^2Z;{A)3*-&=3hQ+Vw#sp<f-mZCBzEbv4==mJdwA|wa+##pQ+gwf9Uxz>d7zHtxdU$nF
+PaVqQaziZAQr--Wzf)BS{kyeo)-7!E03QpeR9SNbgz}_bytSpa_&hwPsNT_UR*LDHA$54*#q!0#-<k2
+qX|o_pK%l2>yQOPE>uY{Yc<)yV|k~OCG0K;#RKH+G4g_R5O=|;U>;56N?m4G_X?%am!eBkO)I0zo436
+f(!cT;jxBi07PS&`v>2vwD6jJ6%8<)HpnDxmdlgooGAbr`c^`;ZN`Q{#<Gmjj`nXfC9A4_MynPeYEfG
+2L-mi}CwI(a6&Kq{1>%g>CKm>uLThLsl_mB|N%8xEYuaJ+Swv)P*j_$Q0L)vEE%HkV{L$WXMuhOd=1*
+-6OBhMXFrzNbGk8RV^5Jk?J_05j%wNM=H3Tt@(K%8DtS`Ve;%X<NdIg|y5`fdOjnps}sG!(H0FjZH%)
+{S$*MJOkG*wyx^Bl7xfwsl@AW@jKglI_H>pbdy>!_$1b^^-h*(b2s&^mWY(IJl=~gIOJloYh-Wh3(gC
+_BZ0n6uNNTvZ5mg4COlJWe@0H8?}`VKUuvYn^-+4JGA9hbXeD}v;=l-StuX}B^VBwM=!d8(Ht}Hv*DW
+3@aul*0963e#ag|YR8|tVnP{3*3D@G0xHe6ZP5>$)DL1m*-Y&d@?iJ8O->ADU&(K*+=Y}1nze@P6unF
+(H^^81gN+58`wB_@~>uG1h^Ejub;3-otqsMAI1InQsDAF+n{@OIf-szR{Y{aYV%halaemf8FC0OXNU9
+bJ1=+Y=&Ht$lBnTHIoic+doZbO@Q#(;6<+`T#T((!YK_-2q(4Jky3!vV|JEec?(Lt(k2_ml{MvU(g2K
+DRFqb6MD+J0<IdoZGwUe&4{#5+L^DMV5yb3_>6fAVj!RS+ZM4XNjBl&Rmkt>g}~7>)o7ni2jlfnLTPm
+-b*#|Hy4}nna&YGvFW<IO@M|{C7!P#mqBlp?ZTH>;sqFXNYzTwuu<!)URm#{a+3Ngsi}J-1?b+>BmVW
+mw><jX)32j@-6SLE(EzCpB^8{m>7J=q<~EF=UPB;3La7o=(YS-9dHc|*AU4mFQEk836xQgrxC5#Hc!y
+eU88Ry0RTYj$l#8h4P<ZDRS|FtSt__^Yg(ua$o^EuH#lf6NjN)d80LSa}@E+X@e@-t0&4Z|>XT}v|yQ
+F>B{bx|GH_eL~J<&vZ(wBG1flInIe(&J~oVYwl#+%>aad=YTv`^GUyd^IA2ht?g&CYl~3|P!#fzz*Mu
+!BGni4<@AFlS|7lpL4Ks1^)3bNMrLuZ5FJ!!sYGEZr+ROoRQ9UjvcHj2S5&vy^oGK9H5x0}f9gUj601
+SMPo<=5H#)(H>4YOTQ+d`Ue`yBa=jTMGY{Il-CB5w&t1He&HQ-uN5Y%H8oD0GMzdaH%C4JuRjdguDCY
+`Sv_)?AT=Au+j%Pu?H=5Rr#m7k$}8(3=O_~OZf?uwhh*8%QMJ<xzKKJp;#<g9Hu&&c2;f9$7u{>~D5N
+)>vAw(ZgLlJ?-_%gNI2H=i^W_|ClB)Ku_l$2Y5Cw%xXVcNW4&Zj{c{MB#UgG6=x&ngJ^jZpYxlQni&H
+G-duaesex|A1O_wRIcuO;IwaK-B@y@a=ULmzcWpiV=^(u+3=D!P{pn)aMDT!y>Zc*cuEz65Z2>UVVHi
+fZK!NV$vmoaW_=pb-fuE992zyI)=cGnHS*k?~F4>&(%!2P_CVTT3OmS3-F(&Lv~cmw#nnk_t@;axxMu
+xz)Gp#=UAN5yli{bX9;58HQ&cc=(kBKr_GBgPOhHo-=hwVpknF6Tj9q4}3ok8iq0R{iwe3@=#oL)s?W
+po2OJTMbC}<eI3h#lG-mhn!E9e7wBGV3MR#xWO5Yg+i5(c9<VG5c*~(zqBI|f2ckG_A>8u`Ua>m!KD>
+_ZwMpxFSh&llp2BCx>=&A7BLE!d3!+}_f>#ob<TkzU#e3+lcHv8Q(TkVVdfd<Du>c@rYemNhnwnhjiy
+{}ml*xd^55?x%F29cMwJ~p-A<KIN-00G#%73Pa%EKVtc_8`M9^JxzzX@dzs+nV6{sG-<qc~9f<^jb)-
+6M6>Cdnn5RVfv)3h%sBfmt0(XGt1GknJXiYrp!-y=o$T5{2Q-bk+M-@;h^I^V5CAR+n7HRwXWRO(QSD
+I{d6Z^bbSb>q^@`c^LzsLc#&L?)`Fk%Qwu4Mg#^KUJY}2%OR|&*U}diEN|O|FF`<Cz3U;r90o>DO4*z
+Fr}5BhJRL6bz(jAvAvX*xSjVrAm42OXv$&~Rmy8cUcK9ttepScmojh{mj>ZcHBv+aTa@mrH&j(YS-oS
+A67rtb9o&V_@*sdN}cOQGQYuY29#SWp~E@QD|c0F{;WR#4XSAVJF;K~Z*Soh3{=YN$DDaJs*Sgx-K(*
+F}xEnsz9BT!31>$uw0-@qk9@^R$6L5zApc{+nwzKgAf!Yh!x$BUHEi(9%Fh~4Pzi7mfZgG+F43UOfbd
+OF3riUkyld4$vhrZU%lJBC*Rl3NZqwILPeJ%6WPpLAaBa<7_408M5ou8oz|VAv1ScF!_$AOI?=f(Hsb
++fa}SNE-@<hL?)HZP)utoK<sH?=|zRrU!<ozv(U{pjLkQ8INw>$pij9{rUxx9Pb{<d%Q>9_v$7!4k^%
+pQW)~D5D1>vIJ~GyrV=**^)Z&SuNfKIJZO<PiYx1)zZxehpXELKc>m>Md+q@DVv_8Q<=*=4@x;@?d1}
+b>#FkEyPvs`Ez<mS*SgVd*R?|PpT@x$sM^t7eYllrW&W{cdbNBWvncY+(C*Q|4O`HSt3xC{i7_oGO*L
+cY7o&La_On{`NT}I_c-KXLK3E5}*Gw#HRd~^78rmXvgYb-I@?sBo++nmEL`Gn~7p*U1cgkHf~pQr1y9
+>7H?oKw>s@~$i`dfS&LWmTAAt3H~1%xG<8mXkrl<cX}UO>ZVy*F10@$N4?-tFs_^bkO48-EaD^=M0=Y
+i^OUyU9UP2VnQCqhFx2E?;<w~MBHTZ4t<9S9;wigYHeHd9yWsKVQV~f+6M5Jr9Hf;6m`#~f8fCSO+S1
+EGyv<{k#}{!B*7!aXt#P14#R1Qas)VD_<krKF)WcQuH<PsG#vZbY1B*&M$5_bOR2O1FHB)o^ZW7$Btw
+hi%}`Nt4C+%?@-Q4?yxC5_1Iq(2@(SJ)sdM*IXipzHaK9m@`^8#L3#3?cGQ7FoCuDz{=Y**sa(=yg8K
+>5GdLmD!cK8IpXwt?V4HFN3IJ`ZETwLF>Cw}0#RKz!45nR*wNLNB)<uw`rtRV&h@>LJ-_+^7r!`1`3B
+_&Do{3eHJZff-kOqFY-mCCSG9>K`;p0nhNTNX5AJHPhVt}-Nj@)h6Ey}tV&U)1^P=KlatO9KQH00008
+031s8R(v6Y`a%N$0OJM#03iSX0B~t=FJE?LZe(wAFJow7a%5$6FJftDHE?ooVr6nJaCwzfU2oes5PbK
+qSi~<j;P~Pm0$eZX;bg^5jq?{I8%3TBT3XpeDbgUR1nRH9p+D2sLGSb=?d}X`XIE@CuRqiuJdLI_9>s
+%cI-ve|7XL%<)HWMUT5OqSR&Jygiei&9Nk<d&O)4euU6z%WnefI^rX*`m8EU$X6Lh4dmq0%93oEl@OQ
+s-yg%kBt_AV1UenTsbcKEbAWA`5*rn#|)cxG96&S_om8Gk-X*ub@`an#mRD{fQo<HtWhakaclky4a|T
+1N>xwlAC?I*E<;R<0|w*>dea5h0og`<3QWZLBQmmY~p+H#D#P*63sZuu93b6}Aqp6_%NtDf}yhJy2~b
+%7iA%xpW757~x6i{5NBPFHJ6sI)o~nqn)7Ivn}1p!>8$z#_XV!o>;R*H}h((WCrk9W~?2PaI_0Cx4k$
+u3_{YQ5E>fL@7;YMmdJ;*U)VZC=tH-6I_=2VA<ViZe9(_+?gFq4(KRVd!=8}cs}@{3%}MG#?H1nS1%z
+ny6>CLnrpj?qsSX%WOJ7Ed&$H!%qUkeziIOCmE}kDy3#XCA{0>aA++hWCLRVI3Uqd(uCW9pY3`Eo)jY
+o^;pnf=7Ob2O7!&yQR&7)*7ikIUkq4_eI&(cAcC}lob9L&6C^4a17l%;`_IeQ_MJGB0c@j3`pIc>!YW
+6T*#Y!nInBD?y3%}^P=+4l>`#n1<m1!?0u^lBw`2iy14bis0&ZwE`Cbvtz5Ly^#56-JN(K9mKhhsqe+
+p}uiGlujaG?>_W;celOY?|MYb6p{BH8cZMm<E7GUGzx1<>SkME&kGTj4Fe2+QD1KEAK%0yTobj!6>)^
+&x6m8sv2CTuwo>y681FM_$V?8IBcxo1vmE=KHETG1te;fM%YN-SMmA+X-)Aov=gPCD(bN4ZovbFa$HB
+PKXk<z_w^w=qwXSpFuE14+#VBaClDKhJtCnL`wCVOQni|cAe0W@iJE+y}p6l9|6cER@SCI7SN~5js1p
+WYhYw}72H^0GzPwyK2<IxtEp+|5Z{Tm)asjttS9lc#?QSzlb&|aFe>?^D3CY*Tl9*+`wQ;E&5IO5Q+<
+D166P)h>@6aWAK2ml;P_Esz{)OMi>001y2001Wd003}la4%nWWo~3|axY_OVRB?;bT4CQVRB??b98cP
+Vs&(BZ*DGddF@$kbJ|D}{?4!HOX})i0~j28H+EjCz{WO-4L)8f<x8bhLK<KaA+gdB!v6YudL%$d0>h=
+U>#JH<D#kNCPtSBe{W8Pz=h;70Z(KK9blbdWw7Lzd-?lG4&=%R}x#!dy3u^mvBwf>?3(poL1G@A6kd9
+;G@5yB5O3PH9PnIKvtH^>(Ik#NebfuD5c`3dL$D0bDydkL!Ovtx{3M_LfVzAP41N`YvJzxI;V7mAGaN
+P2Rsf0~~g+@%PGJVFHE}&|xD1T9)>e<;VKxB%SspdG;VcCE>A`t#JVTUKV@Lc7~!3@XD2ZeKt5Z#&nS
+Gt$Z$d?l;5q79Zd33)}W6zDw4^ugE;G6z}tv2+9puiidIX3p17T%03(<NWnG6>;e2t}rAA9+63Pdr-=
+7d$j`Z5)Spt%N@bmNvX@_32gw*eP8LSNJ&1{cPY!3yW{1CEP%e8PJr+g7Ml?SG<vKv=O@U0I#k4nuNq
+W>;5ME03&o<t}eAjh(&_0^QPkc!<$oHSiq(i<iH#La%DNw1nZO9BwY<VhVAhIfH>$Jw4#BaSs;cprw9
+bd(#K}+rrqyRt@S`3Yn@K5)q8jiSy&pg@Lz}|CsR<+CY;JQUA4f*0dUvoT-;zqt=_zC_8xfmSIu6l(e
+2VzyF)d)uXTFOi~en`L-+m8eY@Kz6Lp1HnwX85W#pBKhk%@Tu%s=NDV-oZ`UBh>V1tfLWAmGUn=K*1C
+^8Wu)5SqPbUb&Y&x<8%gT5v?B-c|#n)?#m0sB(k1<KmLMUdVq7wNPLA=CZpzy)0_zmh{hUpb!V7pd+A
+ibd~gSX()+Rx73I%Sx4~-^IwbA8NEN_e?6!bGf1KO-L=K632qqICOfmsRM5HUF<UwC=cZ56hZU*QYN2
+6+)=%GeQLm^9i!Jat~!l>8|}_zqf=Z@!q>MAqucyXBR=?W-@K^Z8kfy(uhXped(C#s=+yA5m@7mI#mx
+HZr!_YE7auxXRfe-kozduiO4U45Y477MrI^i7%A<QI9Sx3OR*%zKuj@R%Rc$n#)VmzsL-7|Gq_w_pcD
+JhJxuiZlwvRGzY!2e;-nVaRb=DHPN2>|ZbGe-5m;tKI*z_-#X$oYlp-3$P8Jvd}ZngW@H^ybHS2KDyo
+ksVjeS1l7saiQc(E{Cmr(rxax)`gJ&(79kt+pPjRQ1qZv(>!o-=%?G=JdQRhGZBLHOesZfpCTeD!rqY
+=ZbJ2{Da(PPIU|^bKvOs9|^@}=J%O!Eu<Kq%Z4_Eg;Pa;=R+ZH5(Byxs?C%6LSZ$^TFVA6G?ZsBs-Xe
+S!&v<!U8Ih3x%?TsRy>kVuGQNz0{MsFqqCkae@5mr2Od(Qo{#N9R}1{(4Cw|6Ih?+k&P>pJEUhs<`%(
+nqc^uOn&CHQL^zw5t289BmD~x42)(nM-tpw1av|$+$Cis~6SgGmx(b0T9FHgeWrtJBnqp9zG5ta&$a8
+~CCxrvLL=`ckCp)Q5OB-gsJnm92uE(pV!&!se~3FS@8aO%U(3_Hd%Lw7hKM-q0l;dV@1nNA>*CiWC?*
+hv8|P0VViZJG4Z;V8IlMYnKZ3)h}Kd#2}6=s6q&3WeneaEc2*T%`mgVkT$~!%{VL%n`ekm%>#&e}*J)
+FAb+#0zMpi9(IrA%yic=HiH<}K%l@+Ognk@{mr7u#X~v{ObdNVKp+AtBR&dygM)(H*<=uQsxk5T*yCE
+C2rjP1sNUSbxTvegyB)By^-u^~o4Tk~oQHMq(_o=QP$d4vJ<Q^BIBht>JqMdrwqqEKV`jP6uv7TzdUF
+?>b4O|%_l+E`FzM}EI$lGC2ACs2U1x#FK}Ul)MTd1<(i@9uKxA?E7w2!p3>j?Tg;shSngfX^Od)wjT4
+xIZ2cBmxD^=tB4oBa?lAF?LpT9sxPMmAyFQgP{Z%nSB-=q@PrlLp~ex`R@^W!J||L63|Oj_uju6V%~T
+BoUXFb*BhREcO*GvAHnG#Z$k^WX^a9d6--hpx}u3`=Yt{<Wp;{!1-8QXRr6*K!61aCq$^bc>t$HB#@2
+5d<_wFvrCqW~8)J-f$!$HKuIvCgMkSQQS0Sq*%*Gbv3tJ?LXe8G$tS^EkQ?7YZCv-r@>39l?D3cu_V6
+%Tu4%JMZ;w)k!Dh41V0z^i0k<iFdOwX#)&+8+hb?Xxtbya<8oE4RQ^f9%ol6bDXT(ljFp};gzL>lV}m
+KRrscr%oOnOdR2*Qql7JW%(jwpbpmRkuT<#cv$86u6$5MVdhH}M^31Nv{mkMM;;iHry&rCRNb9UBPk~
+2B)E%PuN&Wd6-vxnP^!7xjO3EJ42owW^+mg6S)$OhLYKt-_8mBmWPDnj|1<}DvUxDMGIu1phm6pu2#{
+K7`)I#gIr6S8bbGb&d_Lc1Zj;c-|AA0Td2-CJSKn+G(RIZC2oTfylU1#_dR3dWrOxx%hWUJOkq$a2!+
+$kxj)THi#n+UWeY{<?6!cjFt(rrfHQS8|UxtqAdL7ph%NYx0_PKpXeiU2Hqym|zAF58@s7oVZDrdLLI
+_Epo1BFG}6z1ZtzvAsR|QP^59g1b<GI@74*GO87k#8?u1_5AB4kS<R4jy|BWDg~LT}0y;7^%hcsQ5uK
+bhmf#hdys-J>$Db8|-jsGAY`C<<r^@Gej*rQ3Gw}W5B(p}GogfwGW5OjZTc8(f;Ob{RTC48n@`uio<8
+tPU#3NkZc&9jw%R3)4eiD~IbbgG>gUbIOm+O`Nxm>Rt%w_!m@;8_NEH3ZEfXeq*ueb${$-cqhWg@BZ_
+bRj@^$Q)J{<=wkEb453^WqCxo^gwyNU9l(u_k=qds?*F`ck=zH>vl_1BmnJBj-=Zf}zfRv)}<q@Gr=L
+#YkyJI21EEjM&Jh(_=wD7UknudZtz_9GW@f7>{Pox*VN8tq9oiMaVAxC%zszfc=krhw>A+&)@$1Sp7E
+-=w(l$F!@bT@kxe4G7@Tu`k>!FQZcdh?Vx)4TSi>ePO{?ygTKDaimpRoPAWUXtNXs$eOlp_{iW2d=-T
+|M>VV+d{e9L?h^^pD>@negimg{sfSe6=yodu@?RBUXX@%rHp-|I%N_1o#PG?uyuhdmEaOog;RgJ%JYu
+H953$}3(EHGZs%j&Mz^L2D3A;aH0Lo=C2*il<HSW4APJrln;zrX)GsQ=6>^ZWZBESZ1tm3jA7DOTBbU
+6W&lYwrv4e*sWS0|XQR000O897^_9G~vD>zytsQOAi15DF6TfaA|NaUv_0~WN&gWV`yP=WMy<OV`yP=
+b7gdAa&L8TaB^>AWpXZXdEHfQZ{kJ}{?4x$U33zt#D%LWHRMv2aF9bK2Jxa(6h+ozuVHn|F4|oua({h
+i{R-IRMe3(o{$P)1o|)&F+403i{ROwfyRi$C@nGmKhHyKX4*rHSz88%PSZ*my727aDI1FS!foZsx|1i
+!8zVCLCU_LQYfzKHg27L5!8hPkgFvBqN8-1o+?x_M9f~mnof0r8VlRZ6vWm0H-RePzD7X*fxRH@xplo
+%SoI!+L)sfe;z`xsMg4KxQW=w4m@fe^Ls4)i&Px%JgBr<$r~8l+4HQW(Y75z=hxRu3%z_eA}K8RHwpc
+5n$;p#dXd7MraU8Gn?Dv$Y~BwyK4SQqVFqFId<$#4-Y(2v9U&I)z6e3=k3gDiy}>WWd7Mnj#S(9b2`b
+YNvAz@7xtksK!d+jtZ)f%`94T=40@L`BZ2MM8n?N^tM!LWD8kjg}_K6e4_3(P=?=a?q{krTHuS*&9h~
+QZNOePiLv!#H}^KMg+<4}u^TFnbZR9inFhc_0=q@+@c{vm=nIY&tSLmAh7oTg0{X&_@$&n0wS>O=06+
+TkdEZ?=T%#{4jbE{UDH7Z5aRdWER*DD{W8nyJKb#M~V?_UUJQ*(^Z1tn@(j6`qFq+Px53~M!IUcMg{W
+;85^VxJUbO08V<`P>m>qIUj4iR!EQOSTB!njVUKVW+`7RUqGl4pu-_9?@O0)j_mAAhKaT#8M?7eh)xu
+YrXiq-n#8VmLcEeU<JaO4;8w4!!TR;rA{&5%H5_3l<nYVj)70xRk05w^AGHdf&&`&X;btbJ_i^(*;;9
+&~omAq5JKfOXZ@`2$kG{iT4a?Vb|=@nc!r!VVaB+;cZw6e8@Z<e@m36X0PNLb;=?JXk1V;ON^N#6%ih
+f9FmAlL^gE9I1XkTtS4q%7@X5aqv3O+b&hhUWVBDAnn%ER+VQYsYeVonhC9Ranws*kjpHshUYKC_PIA
+G`iNSHF?yv=ye}XFoO(E^2BV0VqmQz3<fZiNDx5^02?RdmDI7=R~#Z;Z+kEu$!mq_|}MCJ*-AD>RJ)>
+IpB6X6VcX=tx#Lp9o#-zXGOxFt;@$1B`Yr*|^2XDM&9IObFM*ef+wun#_^2@rg#B6{RdDd3kI=)NV&5
+%<5)hU83KD3ML5C&-SLf)qO9)_W=mq{sHG{MBMNi0n%dvVaPop78w$n!OY?krFAJ6WbXK=aAhw1$Z{_
+|3CIQvvTf3N`q_*tYbqxB-l$g)}wvbsoDO9;-^H4!`0LK@UUkbj|RKS3?(v5oX)z<h_jo;CWYrE*9&=
+E;;Y~olHuPRF?2@LmHW*bFRM7`PgnYICLpI#o8?@Olh7pceO0^DrFTE9)_l59Mucm6rqF|}a(TE_4wI
+ice#He?&H4uUwAk9H^Yp7<ijh7!WW^y4xg_Rbsb{s+fPZirvRXRM)z#Y&b*(7?I;G6XU|AaWr{bLa7|
+$>D-0i<TkV!n3n+^H|bRBJ)pFZm(Fpc=shMN7_df(a0NM-=9uE=T~l@zuxyh{j#{;cZ@ER6YHY$tI?n
+3dI1Hs)*MT~+I_brrnVdw8-sKJrT_hv@W>6!kRz1yD-^1QY-O00;maO7>O};>Tb>2mk;q6#xJv0001R
+X>c!Jc4cm4Z*nhVXkl_>WppoNXkl`5Wpr?IZ(?O~E^v9JSZ#CSI1>KOuTYT>3pe0|+1lDU=H-qdFheb
+Y6p)&m%jSr%Wl+V)K1oi({`!4dHrN4@%j{9LTd~w?bwAzxbZbsdj{n%_-j~6M4F}!cXxd|+hvV*V>>1
+gU$_bmT1RHC)l!`~J8wY|(!!F`KWE63BrR2TP20Q+WYa=WRgcZJxHS;0rRkj)iN?HlAb8#=CI1!q~A+
+twRLw+Qz@p&S!v|gu5`rOJ`8GPy_*6ss}*=4M=bzci^MZgvtr}6MAu1Qz2!Bs2EYTY_}dv?}>ilgEl>
+qHTokgQ=7VT8UHLFP#}R#wYJ3jb=R-o^@J7hK=5OBpS-T(c&Fg_hZvU2g0uR!(BN+TcGP#k3#q{B;QB
+00GiSE;QF0LO0YxFcXLN0hYgKn>b}YS4@jQn(TfcWf@n&X{>R69S1Vp&{C=b_)BhCq1R>$@|V#S8wvw
+g*cYLM#`Tx!B9cB152Y`Z5sVv_(3)8lQ1;1?X>JJX$58L!f6s)(KHW{>#|nGvwYInA8XNGH)wm`55$=
+Qz)?xI9MF^MPp7f4FP<R?Jshrvsf`dPx5RN_|{n$dV)QB*R8qfe)_H8ixI=-5*&geV))|pH?quKZOkV
+Po4ivVYu<T{BY6vHdcmEFK_D7ffNx?gdk^La2F%)XQL{lRS1n@(AOJYgMn*_q4+-K$||!Y;2Sm*Z*AL
+vV%ILQG&D19=B=2$ky?NTNu%j7;YGcZAo#z$joVelHMaU!bZ2#*rb(=7(Y!#cJvN#gPKg_e_RN#kRp7
+v_$S8JrAM_Ek%4As0!a}uwPmb;_5C!2&OpRmmyU5qd3+L_Bl3|L@zoxd-k@~I%~FmK5H>{HO0zvKh_(
+azmj}TDiuVE>M4qsD4ON=6V`?r)nqpbR$0C}b{WQ_2C))KFO%_vN>K>8%#f>P%9o-qBcx!1UFvuN6;q
+3htW*Z0S#L7x%m(98XE^^ho}5qTmz^0cvX8jc^W$|QBT=iMs@bA?&6|I8n*YA}+x72{@6MXPKlb}KZ;
+HkLWPcTV|EN~#l}g2rxB;7iFsH(j1wywgPUZCLcrxo=&E~VOlO8^X=eYOG`};51b|6AFpGy$dd|opm3
+L7XTwVa2}oA#b}IQn$K8;wW3I%|GnqgaWyQ%OJ4<joCXfHP%Cyz}0y*PRVUU!Dqc-y%aHJkzOox>Yg=
+`=zfvF+?<z$U^Hag&n%J+I+6~TFmG5!f6c_w$9_fYQB^HXQGMV?PjMq?^^E0LjN|CuE9Y!#YI}!R4aG
+;bNZqj@c*rgOVsNqwgYgHSPKQB>uC)--{}g42=XW|HdeqxgxIC_HGP|GnJ8>?<E|>Z{_2|!eQ-z?4m_
+hZ!=i+JVK_oL_hS{xKq$YYDU4!n4^*6aXSpS$M*3?3whjsuT=L9UXvcF0L#(1rZIOmAW8qedyC9!cut
+^uSMYV>4J)@%hwSQB8Q^n~jqyML2ecwE+y}~>RRJGz+sOJx{4$SLpbf1Nt)oOM3_c!Vjp;Xjgh^fJL!
+gcgL-*}X)_(Iq=6KYBQd$(fPmW+17PYi88{dCoU(neoqB}UtwU1QQAnn54cm~M!AMTFcsB)Z)Z8vUe7
+(0qYLh=Qj%W<egsDa~T&M9360LxpaK)+RF#9f0sYl56y<pa|n8H^O+?#1N*+C*$eFogsBO^>B;_nHD!
+O>@Kl8U6J6%GSu>OAY^kOos`QoP7Un)Z%P^MOw8>lqM)gBClU9v@d@q#pa^qZf+b8>zLX{1C4|V0+~|
+bn66XflZ+tBi1o2@d{S^yhYT-2SuwEYLB3|Cn49e8Po{vSY)pA;;Up{teu@sL?JSL!7H_K(`;ATnyMV
+m5`Zbad>xr48y?O7lx4M+!2!*r+oD8;N#&}S$XqU8W(<GD~l;aq0NNA^Oa_E0ea(5ty(E}+2Z<t&gY(
+^Aw=87WUZTHIJ8k?VG|byHH2*)+(ev534c%+5#D>;{A2XO1<tDUpq=n4S2Zx@~rB^C_PM)lV4jQ7}Fr
+#_-I6=f*&B4YzDut|1SCeO;)Qh-<`)`#Q#mK}odjNQRyZ4u88sF1s-12lmw9_2KdynOOIp?2*%RavC9
+U2sK;nn<o<4oLLBZ(l|1z)!p@lf)Aiv;*09jIPBj-y!>LIcEY7V<;=YmeTlxcSjYEb{<x0jmM>q)+2%
+N3Pu#VpG`8Q~Lf`FeRydkwer&sfqGWkOCwWO9kh+77nxDJ5%+O9LWdZ>X$p?Yg&4*7%Nuf+KIRj^06C
+CH7EnO~Rr0l+FB^$`NED+GtnRW+*(r&{&$#AisYK^f2Zad#8bK%WS-|g)Xkx{K|6286tAuih`o}vI^v
+(M3zcFUl&dm5ql27xugt~d8mJUE*0d}L9r>R0y&gA8|5L6(jHgdP)kdSO1IbM3v#>8^x-M>X&uenMdI
+TA&{3STv;PB+Xu$mJot}T?`p4-lvz9wTWq;o-RQa>4F{{r-}QQgj3i4@isq|#-zfWzH7aEyI*@dQ$JG
+ae5$q`i{c<U{ZirOc}*`EuBC}p6N#@Qp4=Q1U=A92&)%@s!TvK?|KARv-S4~b;V-%XMb7+BnKP89R3@
+3_hm@0<{+kd<dAQ*r)r(_#h0C^y-gJrHct#0HZi^RB|6Ms872jtwIDbtBx5@aM`ZHIIQ%e&S&zlD-IG
+>a-x`Sm<zYl`liNwC{PEhROO}iMo7hb6+54PEz;R!1s=XpiZ<}KhD)ISRG9+-Q&jzjw_q&F{gh(7^PO
+9KQH00008031s8RyngPfyo5`0F({@04V?f0B~t=FJE?LZe(wAFJow7a%5$6FJo_HX>Mn8bYXO5ZDC_*
+X>MgMaCwziVQ=C%5dF@t7_}d+y`{ObtCMb9^>mcdF1nUhK((q?6*7qf);cj~J9N2Uf6sP8NTIv8s1n4
+Ud7gPQ^PC<Y?*Gtb|7I|x+d;2C9QWz+_P+Nwy<vOUI;6>h)4djRkuym>m2eV<GWD;Jl0{0-DaKmVs!R
+vDumYA>e8r_&a!o2Fy9WdILvBsXmK;l2R^%dPR;b+IQ7@JD4*;eIrNerxIkP;W+1exS9>ui7TCQ=_!q
+QRim^vRn{sD-+<`H$Jq>-~VG~$Nq6;DDYJ(XK6W`$My$Q++xh3Jmyuk;|~T#JlO2oYMciXPT>q4F|+P
+$R`mGre{!rJ8dxDzz^N?3~uBpqS;Pc_K`J2N9N7p8TdX{4<q^bnTXkJV81xYRh$IDh_Xkk95loBBdLi
+bB$~sikTEKoNq<UbHj-lTDmo}sF}KUfsD&Q=vo2ZvwKclVBej+;@V(^-bbD4v=XsRO4AXuE`C&V=^T#
+{^qM59p)1d5F9mg`35ndpF2Fs001%13pp9t8sW3b(WE%*urO$)Or~AhVb%#&%xjPzlhm)ss*n(;7qJ9
+BMWJ@UkjI1=v?HYjt;I2RFeS$~#a&SACJh|wv2a{ocJf`dW5q0UIJDLo7kGI_sJv@#c?#KOzXv}#<u_
+JRI$s3AOKxPU|CfqV1O-TI-<uwRUCbVEHjxxtwpreRkM3(EHs-aZ*+~*6In$U9+Ddozx=|v0l4!Uorx
+<IMx+eXvJQJa46z=-8vB}y=c`?W{`eJz#JZMsy(I@7x@d{5tZI;SU{52qcX$1zsk`cQv(^*=@Au+>7P
++_*?JhX%}BtyHUwA}9x*j71w|EMABlgArRQjeCA~>~`<M?iF@RSDqIbi_)^(_NJ{?E0)ZdJ?>{MOfel
+C9Qf}p`GcuE*^!A(cJs$DHrO!ypMvLcC^w@eg9^okWSX$*!6Q(uJs1Z_@Nxw~TksgtQMG_+Z(2R&Xb9
+i@!CJX)#;CB^!q8(i!(uCR7@J8qhIsT|@MdI1#v?DeO^0~F@;L`L)@;Gen8CrAZ!FVN^OaDADfgg1K5
+UPTK&z-dI=b9x#)lfqxIt#G*>fp5Lv*>wAq(7ib%fk8sOU*W$yv(-jVGAF0C5&H1Algt3mox7TR#F`e
+;7$V$EY+a<DnX#BN2fVMk^*o;%_GCG~zk-MFce(L}T(6P{|pGjEIEiR;0oSzlXc)S7DWL<%zqOxCtrR
+9lmRX*NyW!yr6kteaT}u#MS(|unhNd=oFJ1F~=l?w#!4e>_WN1z&cl?+yl}yMxaeL%}Fl{fu?j9PK?`
+(dG&>d3-L8v6>$`D_MM90BxgxkM3H3}PM0?h60TRVYF=<~T8=<7y3GufwDw0MXm6w7Tf}~kQ=Bd9+V7
+UUF{Ym4dOYiF_NB6mmE)XOxdqZ{$g66$JuLqg%Oc_4Xcul%3a?qHf<a>8y(TRAD!QxFSvz6!KN6nObS
+m(=GMye7F4H!d?CcFaJf@RBX{ai73yjD#n&M@GOS*vTtBttOdg{2GqLeT=-M8<0aw;((Z|sM9T{NUO@
+>AWk4!Q=zi7t3^%UuTG_@cTMqB*y>e(h*F%~{5$)8nQGM1|X<<C>+g;P&36;YZPKuyX#*2E&r`_>8=A
+02tpj?xAmsTJc{v&HeP^1=Za=TZXu<!%(L}n;`jZXV0Wj-pK=i=DA&L+<a-m9d@x@%P$9hacbRdaPa&
+ke%`p?oZW2qrF+(B(jWE1+da_?t6bkiR%h_M&6?|YxAjX&lvg(&Z18MvQ|ZbPHa8HBQtssY>preh=4S
+Qanci*D`n?WmU~I+a_}<t(e|MtZT~KFZpt&t{zH?IDcF5PSL-0Jo;IVG#M&Ip1Rm8tS^EwgEnU;!LL*
+jM(4ahQSH+cuo0rIb<cK;~Z_2vMHmy3eUe+IB}0qB2FO9KQH00008031s8R<SU;UlIWT03HGW04)Fj0
+B~t=FJE?LZe(wAFJow7a%5$6FJo_HX>Mn8bYXO5ZDC_*X>Mg?X=8LQaCwE0O>4t242JLd6@pzh2)XRA
+5$GxHJ{Vie*2@^9sJ7CWI<~QumHhkJ&6?3tXii3Yl=q|dwgv8;G8<5>vz}r3xtOi0r&;y#{Pvi`vU8f
+UOx4GWGK2VC!LoNGr%EvFFn}`bt?UHJ_=H8zjWuvv+!q6VxS3DqCA?E>e+alCARP$S+KMfpk;g(H8jA
+B>Lk6U`Zf`YoE_wa?Uv2%r*4?00p9yxbn(YapF$AcrjK~Kg(<_Qb8A`<U$mYP7QBNK)db}A@kJl^4wW
+f0D=qrZLp(u*)6R1YP)|aWAaTAi@#q$RJN|U+78EoS=upcKH&8EZ6FijQB9V=^4!<PCiOMMSf&c}xd$
+kfv>P)h>@6aWAK2ml;P_Ev>a#sY5x002Y>001HY003}la4%nWWo~3|axY_OVRB?;bT4CYIW#$Na&KZ~
+axQRrl~mhq<2Dd|_g4(!7aMTYc-sQa23yo|<g5|jAlX>t$)M$tO)NzkB$Yt>^*ywFNxBZ&@=2P@;h8h
+TX*Mq(x{n`+6B-Ts@g$Auel+br(Fd{3Mw8}Srm2-1sfD7xSu;sTh4~?s5|ObR%3zBc$IzjcULx{=Us#
+zPTQWKM3mAx>uy>i*F-%2KYMBWyjdu98J7f1h0H&F-wLP;eJg;e0?Gb;zO4xw4t8mrUQ>)*m?(OX#fV
+dbQQBNsKLad{N9orXP*Ol~*_ExS+Z*0r8Kf^*a7WO;Mq}o_n&^3XfCvRw0`K{51`XP;yD=TajRLU(gI
+g|TW5WAzwl#~fgme<nN@DRe2(Cc4}MSfw{GOvQE)N7OzSbMgGJ8JkiS<r|bn9?I_wy0)Su9VD>Jdzn}
+$0Qu>g3WEuN(};$^gx6L2Jm}z?}#P*;qDi<4i@?pb&t0l5IbZnwS*7+(al{*Y=d+~3f-{B%;=&7=StT
+k^&WN$?ePIX6#9xWq7_r=I4@NP2#BR`!}-_gVotruGkxnNNpCWLzC$dOh8O*-kz}z`62Pd+3hgTp2f#
+Q^`d^XJyC05*^XI^RFq}`~G^N2bp&re8$$Z#fjCu*p7RhXy#t~7<e3Uqdc}e7x#5o`f10~n&g;cIC{T
+c0bAgI=~6)%i7XDl&MB=AIb)&J_DGJ3PG7b#~!??~pPjqlK_m6#n&-%s5I%DKNC41E@L==Uyyg#ND3f
+)wcknFD&DjIkZMH_nI9aSypSpSs<f>+Y{NU7|$_%SVUe$-{qKBF#o4x2B*d+X{Och%jtuV0cCGqW_dU
+ym9ofCn|>>amd5F&>QD5ZiUFUQu8shzxSlUGp;>{lwuVwbL@B4tRVFveq1Uq?<>!JcvJSXz4x5sTycV
+)-TrpFOvlUd^dTNK8jVZ|=W27E*1C*_b%AYx*~n?Rlvp~;Wy`V3+jRXWO^oK+AC4=rhFb0D6xTkxkZ~
+w{2~uA!l-hbv@tljzI-SR#Yp&rHiuxwV5vCAwUq2-sY^MGAyz9tefLHtmtUj1KgyuP0);@aA^DV?ugy
+#K#=3hQ;>^}>&*uEadz4b5j3~YUM((%yCr4|LBwFK;0O3S{qny&UWUws6mgx-{5^KT$ec-%r?HU0)rO
+9KQH00008031s8Rw38C7UKc{0Fwp)02}}S0B~t=FJE?LZe(wAFJow7a%5$6FJ*3ZZF4Sgd8JfsPunmM
+{+?fP;uA<)MR}2?N}EXA6g)ywHDMB;Qj=WU2-ogx2ZqFt-^Fgji$EG$zQlg)yL;~L@$K#H1)&h27GPH
+hk!;q6R@?&D2#vvtc3L&dm1?ZJQm(kJ(87k7cYKMxAQ<q*u9P0Ym`fN6F5MN_uej{p?zU&kHLpdlRO^
+FakAemZt=51P59;+sY3pKtfr;SDAP7pqjR7V%jm<2#I0%5g*0BBOtJ-*5jT?;yr8SORRWBB(X$z*cGQ
+gpc^*w6C1rTd2t<q2u&s&6A_ByX_F}<EeMVO5kgYR(YpeP%4NZ%nB?EIn_-sBM>M;+6c%Vk65nAF0e-
+fy!w_%vs+bpi|L#lQnPu6(l*k6;yW=V?B_-sLpjrZk_wNhL{>mf+!^L!Za!f+bNF6&bsl#%#i(u|Ms<
+I?ZR{nB^=@!q^`lx#OSVG;Gg3cH*$hbQXn)N51Vs7Neh+4(j`;VeI|%CojVg^bVb;_gHu{=X7WM^i1b
+z%cASTRIA%sE}dfbTRnZg2c2#<<O@I6$~elSQO=U{PAZf1IvE!%@060Hd2#hxCRe;%)e`?x(ry83@9R
+T`Ssu>vXCcpK>8zv1^6V|O41YH$ON{F~6!l7}>K_S;&Y+zl+zkj`l73;KgisIE5O<G^?rYT;P!iv&H9
+8M-_ABbxUMDfTjN+S)aJTh}oTeGu8XS8UXD*91(j=-JP~ifWXbWOolvJ;!(lwg>QkVny`h&`4eSTXa1
+C6%P(hMk31Tt!yPx-va?%4}jyOi2;^mYYmKko!ix~h(L#Ta?x$4__tMbvIStW|}=P<{1wAY@czfx}0O
+Z9s!|>eM@*0}asUj<m$B>iLR=^3kr^<_I)y=1Ul*Nj^(sAX250rml!WMJ*L*$@)#xNbS*t-efyTj!sX
+vZAzkINN@7efqqnEH&??ncEGWJJM7#&lcQ7L&0W|Q=?8xSP)h>@6aWAK2ml;P_Ey*v2=;CT005>B001
+BW003}la4%nWWo~3|axY_OVRB?;bT4IdV{meBVr6nJaCxOxZExC05dO}u7$wpPB;tddPP!zQ(-C44w_
+p$uRk^CN7JCe<nq9iPBu9V!&H4rNV%oIF7hrbg*_mga8T<Ua`U7|FgXcrv>$?8Lg}eT+`yNjCp4ZM{x
+<D8zKIeiZ(3KGa*RYgdd6F<ksyT#Yb83aFC%EC{d5<rc$Q3G(F_;Pr^7ql`kgbqR%jH_|kQpw8roU<>
+Rr-g3VI);%4;3<l5zICz;_+2XS*+EDu38wVcN@^Yy8444D%~CEBngbIuZA&dR4*81m2{;riqF<Ys=97
+mlLcVF)Mps+WUlxUE`TyLU?hw-W+6phKT(tLnPO^VS&9`RXc?PVO6&$Uat$F9pfKV(gC`;kFcJMK6~!
+-Q#N&-MtwluT*sKkzr7k#p@SmWMnlgn46sV}0(R!Bfkb?U>M4=IwhLyGHMafjpCNjwrfu1Dzl-(OZPU
+rUS7gU-oaOt#*+j7JvNCkCfZ2r{El?`lA(i=#q8>)zODk&%{jev_3c0t_J4+5k@Ur9zVLs)B!*GZEQ$
+QM3%)5qb{6gvJheCUkF9e?_KL%zf`ol^fYB)(iFoPen+#e~^V;sh{o$K6MY=-hdIZ~APr?|D<-olKxN
+976|2o$=J`KJ`0e7(I<g!-?wvOb`o-Etyp$Zz+xmaw&<)2o2+j&Pso#_G(HniD1EAklGv~Cq)6H5m{}
+1sE3IZ^R!+HDG9v+9)pmk39pKic1V3k-6fQ=zfBT-=rrN?HaRizIiVIzD7?pGg6<_!swUh?ZLI5{L$R
+&PcDr@a{;kypc$$#q)CXMu{*6oIyjF{qT!PuGIF&_Rv!gRig~XC3JPG=d`#9l(DUD{O<ct`~eY<3wpc
+$pc!jXnW%(Wp6E?KzX0=M4j$;6%vvXeXn#hPX*_v$k-U$Z&(ctR?s@-x>otO@q20;Gu6p<Wiz^%`vic
+>E`r41&S%-t9M2gEtvowk|KbezpDGsM`L1ykl?FYPB$7T7#>@y~^u*|7a~)h_kb^^gErrJqJ5fn$&k@
+H#F#QflE9Cwjyq+)>OqLU<{4z3W}W2EU{PG3P{@nndZsHYFW+&|H@_w0%l8_!u5iL1RB4rDcs(rtnAa
+7q*Y>M3dJK7#_l!JDrtLrk+V%d{SjddLBMHA2SHt95;tkTh<OmF{kcBq7u+5g9DnG$4Y>FVd?_%a#(w
+mgHhsO}Y@v5RZ+Ct-$_TnUS64s{zlD#Vwr4bd>G4h={BoE{_tB$m;|3FNFzS0f&%H0xIljQ5hM<V*$E
+vOG$g9!#If!FH?jXIXns=R1$CmSxH5@DdM-zBI9J?L=|6RW`V2y)LGt&PH5=s!#-Za$j*1kiK4GBg;z
+MHPMyXzx8+&)o+mE5VIB(LU8QRzCPquur6+`Ch^JN5jBeP>0}Wa^D_dNPAO`^Fp;QH9-Zfl}=BeAuUU
+pY|QbQ`RWcsaoR+pTnz8(4C;D?_b*ZP6OV^c;S}%{Y_hs7%-bHT{&1F*b+<D_L@{yuh6WOIFZk(8;V4
+J61@m7J3Oa!Ln&grQo|kCIFZa8!L^*LtL=y#lZXjz<CfEEmH07Yl<(fz#!#0GE#CC;{L%i`nc2Q=Z9b
+(J@9Ok=UsF~~TaZ14{E+1ACwuETQs1#-rayYxhyzjX3Ns(E5>4R0CNtN=M%Cr}k+*xV3XVG-567ocIU
+1K9Bi1XOE2rb)7TT5GMOzO8{-pI)oy_)*>Lue3r@_EI8M&*_H2%nw9{b;6%9~E;it6mXky&r}<lhJ0^
+c!&%3!>yc8=5k&Ab(w~ANRTfac7y7klV?88&#Eao*n%MP)h>@6aWAK2ml;P_Exp?*ZFY<0059L000~S
+003}la4%nWWo~3|axY_OVRB?;bT4IdV{>gTaCz;TZBOb*6vyB5DNgi_Ccr{@5H$M&5tS<fX)!n6H)JS
+NX|}XvTD)O5``!1PQnZw|11h-pMnXhp{{466%+v2Q93RKO;Ieho?n0;CY<0C3Ty}cRJ4nzTXO3Yo;m{
+N2lW8*xn$DPm>B7|c+q5i}cf=FuSeDPMq;1>uOjKU+XKpz&F2FIsi}65xmwT?xW*m#A)46Tx%rhO^#j
+j%K2>%NjL*Eh0a$Rud@iB}RzT@Vtm>{p&0&g|(;G}s9#d^Jl7P0a?G%O2L(z>8>my2gUUiPHv*q$&)b
+I%bc?&&#}0NgY27xYc*Ntjc}0k+Ts&w>8Jn>cpRe+-Rfjsz16ijpBX2iGyYpV+VqSU7XgnGJ%EO?PRJ
+f$)IY<3AjM*H4|XX)LH{ZjZ4$)M}55sk@5dP4@vh+{Ko{4Y#?#-t^}q%hd7Wj;V9o<-lB+QJFh=jnp+
+YL<<@M*ACkI(Y*j}Vm;manF|+7K*<+ZcMBY|0FHnY=1~W5IA?U_DYkk677mA4U7C-L!E0B?VA{U#1cQ
+(Npdt43C(a`nahSW@m|IzNKrMW44{m!8188&~;d?_>8{NU<1!^(WSc?O=bTX$i%S2=BmSDEGz?P%IeM
+@cL;uVd{cBegfq}E@z2i=yY!F5lC2J{>1pxu1vG*sw6sQsSS$^&SeuVPHmjEnM1j19D$IvC0^_n2w9%
+dS7-_`29YYYY?i%yFD`ZsL>zhHGTD*l7?g$A0qri<i6x^a4x+Y{$bP`6*1CJvje1#usf~M;MiDThHT1
+rHC?S|7GDQXykBh8fbrQIgY?@myYZC^7{rF6qI7IkSmr7MSuqlOOjsD>RxTRmmFs@hH$2k#|^`@pIi?
+o&y?vC)5i6ndo-A|q?&%MMz#0L+AFLLF6H(dS3{r-s(on&8*NOza}2VPx&1M0b~N}CPBOS|p_qk2+#9
+f;1zgF6GhY^~31l^r88TUs+=>ym;--w;ic&X)+!Sfs6mnCfZY6RnN!?21R+74v$*nAPE0bGU>Q*7Qiq
+x$_ZWXCpmE5XQw<@_+rEX{Bb{26f`+qB0P+nx@c4n;RTkIQUHFB$+NoC|#le*Q(tuA$|lUrTt#>kCH-
+59wssoRL$MpCyCxs9Z5I=SgmH=W#csoR*`#!|O2xs9c6oZPt7jguRfx*6nVNZkx_!>#T#L%W?e@He~g
+hM3m|c*<qhHpzTTReNd{{8uSb7pLF0Ebxshqdhi<JM6alH<h&q+VH;h?n2t=bGXgF(PrD$rbN|$m6IY
+#NAhxJ(B6|cvelHjO5`*7UbS3sL?vlfb<xi>ZT!8ILM}MxHZ-w;e$Q0hv5d~woI>kt#TT}};t(*^VW-
+s{B4u`3wECi_N3b&Qhxfg!R_8o{Yw*f{{GK1_7IWR9$3_-EI)^2~WW!Yk(=i>vx@u7D6IA#LZLqpv!o
+<+x_L|*Vivyv}rc`}&`y+RAnNvzd<tV7JnEf<oPkwEaTI+JG`ge`9+FDO3C`z-thFi*Sfm@}|!>#fcZ
+b@Y!+)}df?+9+C$wIi5A`9bInk<A{DY7tbrO86Ll_Cq{R+=n?TPd<IZl%dWxRoLc<5rq1gj*@HFm9#E
+Lb#P83*%Or>=n0OH@$$m=+eZqJW5$R^1%C!t|fUTwQsLPwqx0fyf)f;U;^BQ6<=xWBmH*_+_n(6U)27
+P84#kt5TGW&>|rM5lKp;>_>~H|Qp|ijM8LN0)XUaXs^v-%st(bl6t2UR9omrJ2-|BM8_(SJSmq9&1xe
+_g)U61Cqbx_dT(kQI1pn6m7zBSg@D79EXUPa2%io1PBX~8$-?dZ(ultYxz7YHi!Cz!w2p*N~8NqSW`<
+)Q{ld=5W2!8N~wfh0^{qehu$5-6DuY5p;-S56{l-0KmP?~Tr6u!6lyB7@KW6t1X_~$J79rs~Eup9zdT
++TrFyM4~EmNw8K^1ifT$=>m4L$Q#SH~0sbByZU0T2kKdtsj>+d}A|~mN?w0zvQ#~(z-12?7p0E(*r!a
+uWZP^p4~@fUx~w4;_#`718#c%hs0rvUrqcvFrJV+e9D9G1o)0m7d{}O9|7)%dszQ5zl!j)hBy`@qS)r
+g5uvsCKK@!F%q~Bb2yX)t{MzVE5`NvOarkxT2+nLDzWxJHO9KQH00008031s8Rwv=Ag<J&y0A3FO03r
+YY0B~t=FJE?LZe(wAFJow7a%5$6FJ*OOYH)CJZ(?O~E^v9RR)23AIS~DyPcceV33P-DtxmcoYITH=gq
+8q;MO9QqE3+8zb+M7{O-n!hJ?~EzHf?ivt4Lw(d2eRkjK_O=TK&*f@3udrLBHD@PJ47U7<E6=Gq$I-Q
+}WiFMp~?dWFd9cf|D?`QQt)vvX;^-3b59yWu|>8tbpY;f8wFqa!qPUwt@rpLvBsLwj4{FO(aFYtWeV6
+Rd1D!UqDP_rIYnQb7uL1=DV2j*cH=`YrBK1wWWHuLG8D1{{%&)d5bz>NE2skXu=KGPkfPN(pA!GF^{a
+$b<?=O3ei2&UuZ1Cl@=R1BSdJ)DjM(XTFEqjNE3>=W_ssTT58V8sHOdiz%FU0A_|x!%@@KX^bo=llZ)
+S#27aR!V!3lmkz61h7q#VjV=@hIhcg;*gGlL?ORka4IGTqd0C*q*E)6GUXzSL@x=`xI1u{(op&JGISl
+vtF0{hPQ6W0bS^t#o~yrqmyQkv?_y7*Detphd?^o~MQLubfVr36K$3lcJ>T|;~P03j0niZ-G-r^xVS6
+gI&CTl&=Z?nX0@I>QJ0)R{~=L+{}dwon?os9(Y)Hrr5u7+Gm1?GAy1;J!EM-T~3M>JR$fgNy#A?+ts?
+Dcy`F)S+=_;`O_;L1#ka*<?JL_F6<!&NGRfm{lU@5-&lyQBZQhEfb+hQhz{s4FU`ov}R8nWe&JNM-js
+j+3sFc!%)dpoG&1SpqC_;B$aK_S1r&x=)R-sf~BZ$6HOnqn)F8-MofMQQGzMpH)09un@}m;q$_2tGrj
+Ksd;YrJK0j-}Id2oqrdWCIq2BQN7l+7ct+v!^Lw2_nNDEbSM`tDxV7k)^)=cNE;@U7Z>dm?z#@Blr9Z
+Zm&!SqORI5Bc%EE;jcg0+x5Lw4hxsoS|vc2WqJ5e`&pm2SmmO&V)8&p@g5-`haiZ>4bDY~bJQK_r{G%
+fWEF1qo`KIfz0lu6CApu{-5<9PbtwV>Tsne|qoVkFI-zTCEm@%$Q_3fz_+oFrP4<(2Ps+eSs<G`*p*^
+WrNP%(@;sC?7PQAn0xg`E4OPDTR^0G`UvV>g@W~RhzHpH`uWVM^Bp?8d%lLp&SPPZum^%4!Zaqg#bPc
+(vhWiHGSm+vD0BaX(gJLExu>+`zGNF-I7Fs}Kh15VC7mFXvk&8w=a@n!R}owNjO7E{GKrW@ifoshFJe
+>^)82C5;gZAk*}a=&*-gmZV@$l?<%I|4CXzku0?Z!Fn^?k1%j%l%qjH!Vnj#6t-30C!V)$8J&!TP=!M
+F$a{==J(7kN^Sl_l^vnI>-5lnoo07!rfcxlN2pTv<XcWpq_J$(D2_kN4tO8YL(uZW;ZqG&EYh$z(JsN
+1nG+s8%a9(SpyTRsG1sJtwaW;V+#TYg~w2YY2tQF;4B3IcZh`lN9#a?+0dCZ&jO!<K;$mI=O!P9n>0*
+JpaCTgqY)7?aPal?0ZuXJtJkc@0-zVc<uMS|H1pz!&kwvb0@JM;(Oz$YgQ0Gh_vPs|6v8A`mu0uE1a+
+MW9lL|%=v`lbNdmFj@q|meKe!;0kB8Z%mY6TDQBuYyf3EXq2WJBt~%W8P=6Nql5W!lMEZ@|kN-97U!W
+}y{5|Q<GwEZ3v-V?QiXz6=dFPax@Ve*qx?X>HdvVxs)dH-P^|@5hYVG4Ijn&<^^n#A(LyV5QOv$BKa2
+asezE9StccY2doq4`@H|gPJa9zST{@pP;yl;xEi~HsvqWr#EhKkwh`{V_;M5dPWP@K6#1rJ2Y(W#>ny
+1HGSrARa1uy6JKSehm7M(rO^O9KQH00008031s8R%pw*%54|`0RA)p03ZMW0B~t=FJE?LZe(wAFJow7
+a%5$6FJ*OOYjS3CWpOTWd6k-Lj}=FfhQIf(NQo~-YM9EXtV@oyD*=X?)?i>8(8&7*HE=LT)AV6aH}<f
+<e&cxx?3K(&yGSngsmhFujLRFB%v-m<{jc1A_?NRM<?-2rhfkhAEcYKjeek#PFUH<Fxm8}g-<7Aw{m=
+WWi_7xh@OD@B*X75<fA23ZFY@<?51+2~Z!T^Q$MWWKzq`6AZ*t7tldn_HuJ$+kocY7<m)+&z<L+1v@5
+;?LXy*7QyPNAb7aw>3i|qbzb)7$t9}h==B;oSxaNOR%IqoiQc5ln;&r<y3QWr;Pef*qDy}v2nJ-A(J?
+`x9y=J31a-sNREXY6%3-(ByHzwF*_J9%)px;gG&f68rscYXWM`KFW~FOL5x&-Rx;ANL>1ost~hl$%3&
+_W9=h;p)r&Q&gAx*T;+FXQcM-xZ9QM!@HYbld<p1=fkJ+=HjXxcW?LC8~GH(O}V&w`=`S(=YKf7-M{<
+Ht4~*Nb31T-vpasc{wl-2Jb76j@2->6@|WG!?wGrI_UZNI{!LDPynnO1y55zG>++Fz*YAIq)FT*q{)L
+h9=#b=<?)PQ4&+n}L%kFrcZ%W*)UswA=@wB9_zq`1B|J3G3Cf-h_KbOnY#_{XSyWbSS?>l{4_E(a9pR
+&(Cl3;H1*EFm0dRIPO@7{g7JWUEYw*39<#b2Mkd{OQ_`KkQ<-ud~xCog{bKF6k{^K0sFqqP6<F-`Do$
+z2^Uu5Laj<4NGhhvyIenltX*KYM)k;wQL&boS!O!{^V-qo?QPUU_!!{KeUWmyhqAmuD}}pFMs4@NOy3
+ce}45Mws6c@^2!3mn1(NQj%|XHy8WM>uu{lrFyTE!OOSh{lzc4RP&qNJ}s(Tq>Fs~{QuJ7<>BgQ_nT9
+G7wGq8|E^peZcfXu$9>vPTHhbEn^b<+?`azSo4coFsyXQ5>K~V>g6BE?(f(bMesp;_98b&r!}SeAf4r
+A-hp2V9Q^%o}^747U`B(qS!zVxdA3^2TNfLg3fwFQ}?~aEL<>EDpjN!+$?|<Hu4;WJV=5^Z0o6Ap$50
+|;WM1W5z<aCb|;D?W&Ft(fBoA+0T%fru~AzEWC<<6adFT>rX=kJ*2ufKcb@2SRbzt@=wL$t3idT)(6L
+tB4;)w{Ypd%L?RKYX=a{NfyemVetQO=I~}`L5pi^5b^CU&gxux$|T<H~7c7S2+lNa$=0ra3}x1ExlO!
+7vK5(F(L5s8*@)i9=?3=xARvoetLHH;NIg`Kb$>(aej9H<%_eYPhOqh%l{>%`R?%BxO?{>KYaE4>^~p
+o`&=y$)`RyKM@%No<-eXD#g~iMm%D<~z58(U=QPlFU*@O(B$21D9-Tk@k5^C6e|UJFbiO+&rH-fh-;j
+?OPV3m`)6&*@T9?}Mk?+bF>uH&Xep;di@9Jq;h9$=h`8B%Z;<S`?IXy`V3%{W{w6xQ4KCQLpyBJ13wE
+Sz%$@4n#SCXEFl@Ak-nTG^cm{}$00z8t<eB|=A<zt4CktxHJ1jiXNV=^NBwkGKk&KOxq0`2sq^p;D(d
+;XqsOv}-IfUm`O@G$1PWywuMlj_QDQvxI6T2_R#anzGwt@*p>?#r5=lQhh&Ij}735iwNOTpIKn!fgn$
+F@(7*EX+zJ1$mOvWzp7nI1l>s%*t$3f-cXzR83L{HJAkF1^(r_F=QH2hRXy?XknRxRTwj&kBLPl7MYU
+%yuEWA6ecLla6QBIoO9P4cTz@~n;AX(7Zl*ItQ}G1a;>J&)&bUsi9JGahO~-GeWWI4<TJTtmO=rw@_D
+Jqo<$c#wXo8nj(nE{CpEf2Ukh0vy*RhC<rULakGc6Y5zPTh<`M3D#grD+pJY&fZY=p)J2Mujt{8UR2&
+Qz$?PbFf*m4?i66`F}(0q=b6dEQnk5I+zV?f|2Z>a;UFA_{fIwrVQxnW)(7|lSWIpGEi+$=r#;7?@Hn
+bBdPL%Kt->0#Y59oHM#cZV;T%h5HpmwzENm|Jrvbx29o6<;2a)H?V`JIv?EpN$7>ZeL~|3y&3Tb^hv*
+c6%wBwzwQastAE0bUbCn>DQWMK%2rUIdA11ro|q0AqCO~v<3fbbs9(#uuvrpIIJ#@m#=;ShsNz)YHR8
+s5H7SP?i9%6zQrPk_yI95x-D8B0v>>%s8WSFd~F4M){#X<hK$h1XT&}QQkgr<j?3j{m9nDXj&!F@Kr9
+NzG%W#0Xca`Alm#d&*IgF!L&wC?M8Q2$%hlx(0kBj?tPgW&VAH5Hc{k!h-96?arA>gt%u3kZ1dIaHC&
+>dw5Eu&%vErEpn_EHIF_lsp0Rr1hunAUTdpO*He>4E2v9Xpq$}NL#E9lm6)DdY8A%{pHt+s4>%!Lc+T
+(n#OBj3p|HrB+tL4akCm<<sq9gfX|C$RwcS{h)tPO=H8D2o+7fWAqSK*GbymREdeoqS;36KsONSaOCA
+kQks@1;yEMECPsh-Zg|f;zxYQEo-KzzVaCGs};;#XLyjp?7ImQ@dJAV4_ELIsn-?!Ta)xjA{D^XHBRQ
+S(P?l42nd6X>W7ATL1ys-ECrCZs1&?EG#jF2xRhVC^TnU6EL!5wD>jfwiHSf}8Lln|eK)p(*fmrpTUn
+8~K7<vmh_B!QBNzktl)3o<!$WfOggavA*k*nJ97+KaHd;nFc));y2-gSE5)Q>kKIlRtxFBMKADMMPF!
+h^C!7B`k1!JkRxTCSN73^@v`Z~B4i)4Hx|Fw$C{#;o^Ed#4FRCVZ%v5-^bzHwP}q*_}*x+6#e#N?Wry
+JMEyzEjK9l{;$fc)&nhHWeXcR-#f>w`{(;Tp9IcWr%;TGM8KK6)kt1q=9KbZ|aPYjIno6ql2xnh%8XW
+jkRe4eF}+eh@W*eUBLCsn>woR(5e97FdOEG@u+neOh8;1!vp3JZkj6mZ!5uOstgXnCfubH0_K&^*e2M
+Wf8o$F96lO+F^)A!4N|Un1~IpfTTH=Qg*bes;x52mCPqXh=9x`4;(k|Dp^bqbRS<zA0yh4aTLz`Xg_?
+d_){PO_L<<Cijurs<{0l8ZtB+<!enl$yd?(?o#P~|QtpuM0Q;o5KTsTDcs}z`wL-Z!r!9S+j8&X+yk5
+ymBtqDj$=xZpYqlylco8OvR^@ggMS3$<9Iv6qI4;{$t=7*iY-@(TYDE3K%Mb)Z@{IIzx7n#f)oPp@Eq
+E6TuK)7K>%MpG?UF>Wa3@rGJD2tml5TctdcI^q<glYvNJAwoRb1tb!2tk?%0Ne59KKm2@253eSv<S`F
+%pF;?la8!K##u$lA^CJt6=*;y#<Z?liBF@W;Y&+vf;v{j*9O+HlYCGakj|y&07g&<++e~iH`7|wGJLU
+7r$kdJ<e#SRW}WP|YMTP=j5!R%$O=kTriA|P6mo-U7ByIIwk(oinM1dPlfH=Oa9Bwq!U}IROK09-qKY
+cIqY<gw(~m&eS$hH=jVWCjnqzk|#|~J8*3Aam_7@bk<T6*P?0Yr&#)GG-1E4aDs_I*AdDS1?fY_n+A$
+IJfZXAO2olLQJz_ckers2VsO6DKE>w4WvL8WM4geFvx$PCVb=jhE%g)42g$-=~e0vL=SW8f);2v>m6+
+%lL?J`y3y@@^GJfg!Dfl|qcq$PpV*5&~9}@1Po;fQ^w%jsl|&7*JgeeJV<BG(1vzRh?u)kHWtT!834@
+d}P$iXX8)fCdrbCy=i%l&JUy%+g~^@GF$|tkPM<B^J!Qc)o0ovh&`ul@-t@YzzPpln}Zf&D8|ypxQsL
+T0K19g5pYz6WOAEIWZXi60d<rDbv$~s84;6J8Jntpl`0Dd3n#h+nR<}6=9XO`kunBDp9I4P^JLf-2kv
+ObG#Q*HV*?zf+2jzYraF?~$OcA30F2C1pqSTUMiXK3dNHyKTC6lmhJ{sGbDtYQ<^@z68{kWTcoj#D?m
+N6k+rfxuqoYo~7&M$K2x2z2XDSsdNLf@DR-5*O*sV~(iiV3;dnVQv_6ab{d0|hc{%}~Vqz1DWEVP;`5
+Jqda+7-n`8|NWwg{JzO=<i>A#Z&T$I46_@92b`FcAKj2$O=dQ0#SL?tsYPy&b26~Y*{gzrVn8lO(UCp
+kb=#KZ+loUVeuk6rAz={)s<!+)EgCWXbrQOeb@*R$k-X!WIY?02nln7i0K2%VFT0Za-_i8U4G3iZ^~q
+qh0mKK@p)0V$ZJ85m|$VclU=G!>c$K0Ndj9Kb&BmDB9K+h;%9`tAOZC#Hv~^|r=TheDxIJZ2}*{tZc1
+4pxH4IX7CSb`;e&mTS!9Huj7Sh0s1(gxYzu*9h9CfI8PhZZ@I;8NTlopdYv<ap^~{QHJ1lfq=*o;Fx)
+D=a@)^~786>Vq4k)Qa_WXcICpU^(t%I=03RYBmElx8lpTc$@o`PCwNalmg)b-%Y1Oe;I4<JzYuZ4%pK
+^m;9>4{PGWn3d4(5j41<cey}D1D&Hu1J`m;d*pWauJImjgc7u8D(%11j(pVg6gE$bX}}Th$+UpCLUTy
+y9hQ%st^RvsES50j0CBIekis>&mRX!8)sJLiPNZO3bR7Lf_0kZVidylm`f>^GMwc>*l@J_aXmeS7(BY
+154aimYTC4I89cN;CTR~ExIwy-4+!G<1+W_zizD_((5<K^V7-vgw%KW7JWVCr638&e*l|W8Hbt>%GyZ
+0=VhT2EPn7zT3&Uo!QAY3|O$AwwwsVj%S0~f^%*ja3x(iRKwow7QD!46H9_$2MW22>M9H!3mC_yqi(#
+LV|3!(zUs)7W*s@vNb_8kPlr|Rl63kx~9#Ux0`0pfx<5LL7xjh(l5>`|5$C@fG|l%aniBzt6rTe7cwN
+l1pnMO!j?#Zg5Aio&R7<fA_!z1ru34=sxnY}7VaIoz^UXsvds2r)FaOa?|3Ku!m4rd**)T&87{Y_eMr
+sCN70z?ZRT1_i0O^CvMFHu2WdRHi8yD1`(v5&~%!Y1BcB`3M>7XyHS+Pd890XxS8eab*ht!Xp4)6+_p
+EQGkXw%Utd*$jHd^PV$MTpcxv!g&Z|F0f^W#GBC!dP3De&1ij&)hZUBCvqcmUnp_-$EC2+BeN&q^#F+
+*enngiVEa-RzEuo-M6IA}SZC@b`Dp61-L4b$)EGVafyg1Czi1uN`0pxQs9p}-XOvWUDv;Y?ZpA4KX36
+4xQJ5m@<Ar;xg;@Ju2He!qcE?E6|kV6l)(7F$r{rPaqBp?$#fwr2hvOJJLD31^bKq;Do8Ach5<^i8V7
+cAXTRC1bUQbvtM&(x;TLN&V}?^b*bQ*}*?DEqCOuTdLWk5d%jBN?O?8Nt%Fo&$MnQ$1ukZWR0&iAn)#
+0Odh85h25PEQb*J!1aRQP)Lc1e`T`?6A%kZLV#!)ll7BzqYXl~10LE>;5;jb7)Et<y}Xd`0!t%u^?YD
+ZQNpo00^y2jA0R@!DByJ2Olejr<V}kWTsN<o0=lCu8-ievMXg$g2~=~D1%hl;r$GM8R?%Y^)#HyQ8rb
+e-%3?2vDFi8+lv$+VJzFcmjX_KQChH_gJSk)ZLA;8sIS81BMHCe5p)^%(<65KL$gn2h0RJI4Oif=Vji
+T`oAvdd^QIxJ{J6R7SpQ3mS%7aj4B`h#7Uy3I3gUn!c8gg4Snow&8&!YhpJXlUqGMc;s7$dDP;J1c-e
+i9W@ys`nTdDE~tgexmZGzxqby94Hx`mH92`UybA(>q((F1*@lU&YbRZZQ!&EJQ~7lYu#BnTPn4y%k=W
+_+StO#TS2CGGI2wI#$WY!eiwDe6jCj5gzye!i^+ZqqStg6A^RqjMgG8fG<yAXEq8brvFj(qu@eJ@n~*
+BxSRs!WN0n+^9U8hQfpzHBsjv$0-WuQtINYCCSGVI+1N0=&vYN`j(arT>~mljltnRarxPe4S5FQBSfC
+_ujeIZ=fF&~K7z6^!js_`mlrnjai{|NT4cdTC?un0ZSw;yu8rc}8oAlWV3f7)xFksw{!2!I9l}NrvES
+~626T>lbtfPWRv;%Z<I*H-Q>F7^ejCQj;JfulNwq1njnW&d9<pE)U@0#EUppSAWL2#5Kk)WFrfL7r1V
+H&`(D|aZcc<|7ZNZN7vz>&;}Y|McyMk<rIaXZz*Xid2(;m9?UFJPO%HBQueW-p`JnE5nuc~my!VV;_q
+iPD))^Wwv787V4>Vdf}+$U@;Wx|LZs))#C95e%e?<cyJ{8JVS}9Y`U8o_Mncu}{7!g@EMkgSIWtmue@
+`pFZG~Go04_%kq{*2qzr)#b~8z21~pxG&|Ec*%`<<>YgMx<6>|l715l#ZO&wg_EH`6N#M~F@6p2rJS8
+?yQJM(D6Y$Lhb%<38u%w;KIx_6a0^6BHl2u=(?=gahqsQBBMa_UfSVD}-VylDfGdlymz$b2T1h);6Dq
+0pmIE4>R6oaFuu;ijIQMeEh9DawbPtN~RG-|%FN2l=<flORW2o8nAW2UfNuZ9!S%-N{Qhw7GR9@vT5X
+;u9;W;_R@1f`i)X%SU#ybu>EU{vWCRh#o5Qg9qxCwC%CD9;mD64MMl(C^+Av43dA?Nu1}y=B%W2-ICv
+#M4HGg*RFYkClh*X#}#>oaERX6b8qGvGqDVAHwE@NAm7!?(ZR&{nZ&z=g=uQ01C>k;E1Ax<t+yl!5Kv
+u|LkPZ{0}fJ=x~OeE3<jfvTzTmSUh+ZXE#|~#%NE{n-JP$`ipwZFegd#6Y!z+7G!ckH!IWv$6aAN#!i
+gwP?{E5-Xb(Hj1nTH<Q^G~xwY*C+4d!f3T)%I!J6rv(8rXB2nBdY%hsDFMk+wCHoIr#NzzjACp%Lh%9
+_Av7us&@GS~=m7X&S8%P_a0I1OscVl(2)35I0_Wtb`0?CSQ9$WHYKjz5Z72sKu<wMViMls0uz&a*#Bi
+H(~!T$+<LTKFJ1&uVp1%O1r;YxL3>-1rw4i>fVuPvHrSb@Hy6Hb$;YY98j)ZM)C2ND%!1LFP8*3$r#2
+vJi+%*QT{sQZ++zGXt<LRfF4L?ksUhCJ1De)?~HgMKp^|^8}komK2Q%8nCKJ2R+!+14YB(Lh%I4x~^H
+xNo%{^;NdY8h+bX`@}kKM%9=ugVTJBM@fOnJq5mYaHp$2#Cy`45;RchFv1AIl;=wA7@zS?ugtBn3N}x
+2eWja|V0f61MFr@&u(8A1TCYE}$z#L_=$6GzL@kWprsI+)EEM1O0=w2D^6e-L+79M`EAOjga{I>Su^v
++tFBlVa(U$*5T*ojgC6#iGZAQm`IPJwjw0VBYpO@_&OX^|=mTi#+?p-revB?1qH6Q-D)CqbtGRh;m}v
+{m$MXVlmk=UD*Ps4@X1;oQ<%NRRp&WT<=Xa&yx$xHA#-lkx#ouxL`&Huk*)wRkUbup0HS()tG1BfGQl
+P)wHWgg47nBJCtC>r#8Jtl3C7z2Rg^IavylkIdU$CpO<~SU4KK2!aHzN>8S4o3}#sgw=Z4hW$L)a`ZE
+kCum_i9)1%7inmf`Pj2Y+c@#8}V^w>>ct1d#XalU$(hjan1vjDcVRz0$J4v$=;O0?g@l4obE01UGRJu
+j0Q4T(1QeF5Xt-at@T})f|+IJAdgSm1N-p=5<U{%#K-2v`>m2o48g^nH{c#F$WODZzSH8GNNn4pswcI
+P+&s9vL@zz^Hn^pApwkOa+yObtEiFh3;Fj~bpFuId*2u=CTrcOn_A!L!l9v+2p}F@zVdF&0Z37$HW|t
+}ZmG%WAX0Ya(GXsoy#dRTE+a7J_jq#cIx!%&w%zEvziT+3tYG(k+mH?a_;_v{5H@OV7uvH4_9mG7gHb
+Fe%{{S9k@ld4YAZY^A}9HH3Gyl!aY9ZwxyP6sPx}GVFeKkASJSY{;s(0T|*T*-GU&Ej;MtZeCE6q>Rj
+%Jizj<G6cE3Rt%#v`5{F@aF7=qW`q_`B~>uuFs<R<b8r<V-Ijf$D3aIUXf6o?S~MiXYY;TVLf89pKhQ
+f%7?pi&>;!iSui{P~*EN5#lDA9;*8{`2-W;=-X+hHsnG8f!T@FJVbA~^yh2aRfa?v$8#Dh7pj9Es)a)
+i`s*2!U5p?NAGVp9~X-kHF+yc{rdILQfRW?x>??Gp4e8vyoZ8#;uA+0)ML=*;dMlP5{DCqQxD{=x!pe
+K|#+=9AmMU0lC9`5#bA0|XQR000O897^_9oK{>vJ_7&%*#-arA^-pYaA|NaUv_0~WN&gWV`yP=WMy<O
+Wp!g~a&U5QVr6nJaCwzfU2ob-5Pj!YjKT{@goa*Ssl8FF8V6DozGQ={JfX!N!>a3Dw7X8^{`z~CkI)a
+Iwtj+{IcH|h%ucg;`J?{eel(@=C>~7H0rkhT_<>%DZ8n;;*fPzm+(<1H#U^Kxj!N@QDkZwcZYYDT+c<
+@ewDb~@cl^Z4?AVei$Y0<<{FJ@R#ExMq%Sy{kcxkl5U%NAQ{|Cf0H}+u9EDO&$t?NDGuc?F$T)P^nww
+_vXn|klxzXQd^@GeD4Q4(SuCG6Nfaen9|HriXcuDr1=*ZvO{qKU9yX)e{q%95@L6?*c9=C$7%ee567D
+7m)6)<LDhGLtife@0=qRGW%2p~-SC-GLrLcoI5)V=VBc$z@RoQ>AmX6RP%XOLx-ne!8SFJ5);dtl6TQ
+d9_wD19&Vm){aRy+69~2o|PJgLegU)G&G>!t9wf<;Saf=*g9C~ZMS#Ic4X|3vD6Yi)Q@TI0<evuYf_k
+oJt4anB{+AQlhk|KEwslE5Tem%tP!o5D#t~oI$%I7eHkr2&z1{{rjPU`N|I>0c)Ud{l!h1cJ21&|rzD
+8cl@;38C>#WnK@xukBI=LEqs3#WemGi82Wd*fSwa!bqhv9Pm*Xg*`7)W$(m|IfWj;w9#JnW(i^K&eO9
+Lfy_ChLmX#El6btq8fv=vW`F=s5XQ6%t0cJ*J)P#L}1_Y25b&|8uPY2!QeY$bLF+xN?K!E&B&2TPxIJ
+M?c4K|+637(oj7P!^ybDr0Pi`o{SXI*EY2dE4vVT=)LD=@BhcSYG>RFunW3BhqX%3TsO0W?Nxj79uPg
+1{hw^U>QFoci%Z8+=<%ZMjUZ?7kcA7)~yuTR%$*W<Gm*hp2@*;gp})$%(35Dvxd~i_(`R_?AM-ScvJT
+Cz4wf9uKb~>RXSNsW_N>eqtVEeaPD9}z*?8ta4v8yup0%fRuV^NwQ4z5MVqca($r`^_`~NaoS{~``x4
+hayMQ=0zCuwSF0|VEvBaOS-wVAGLC|l|;lt}<|D4?7B6=A2)=$t8wfg#{x1+u*ElNK32ikLcmVIS4T_
+NT5Lvr;RlM;GUiOug=9`NFXzH0mrP)h>@6aWAK2ml;P_Er^-^I_LH001$N001BW003}la4%nWWo~3|a
+xY_OVRB?;bT4IfV{~_Ba%FKYaCw!T?XD%om8So56<b21u_cT%J~AW1o*oHf=thHqDL^gHA5_4>9CcAe
+pDK))tDlJHS+N<Z-O`LDj!*5AJ0l}v#ai!r*GInn_CNmL?N1;4^GBcDKK|(a4?g+)gWI1z{`CF-ar;l
+MefzDqZ(n@>aQpP>@o$eWpTD@h|LWU^+vDroUtaz1#}_Z2&wu~$!%r_Czj^-V)zj^p7mp7w-`u{L*S!
+1I{_00BAKyIAZ~pn=?+-6t{rK>7d-dJz%|E#3y#AAiH?O~W{^P^{b=${RFJI4pKK=OWiGR!+-#&Zw<m
+cZ!Jv@K&@a^sEU%2Cc9P0Vgy4R1t%%Q%2bNkKvzrCd~`n<(Iy!_qUdoNzxo~>(N-=00Zet7!(!?(`l{
+Z}vFJUxE>)12mSUjOzF^OM`{FVCO;?e^K@i@!ZR{&4%<Z9d_f+nZOn&whFH{i~NT|G88z9>0Ei{`AXQ
+weOxD9&WE+efQ?)`Cxy%{qpLk+c(c&-ku)5eSGch=R&->J%9P_?_WL5@Bi@X+sE&ISs(rM^4mF`_0(@
+3o_=_}*YKY|`SSMh!|VB^w|{<k`S3Jn^Vv^dzj*v+e);3aZysL0ez-k<efx2J_WJu@SL(y{AfLyB+&+
+9YZ_n!f@%HdI|Gvil`@_@g`N=K6oAzjN$9HaXuYdFW&3gX1n?J5E{&qg}FSi$SH=g!4-~ES6@as&!y*
+<9<w%^aSpTEo-&WZj!#p?F;!|kWn58wUt;+=VidF}0AKl<WdKK=5G+k2n<_4cptJ$v@vCtv*akMr8O(
+(|u#|Gd-V4?j*3{Ps3y_4NGZn_uRG&l~*ZgJ<vm%lyWBfBNX-kG}ZpdioDP`r?xhKL7mo;iu1T@7+Fo
+@7Wh0z5nIM?>)PH_T{tBKK=ZIcW<}PA0GA+uf_aFi+o?=@8&Ikcr{n@+lM#LA78w7>VKWv`+7d$i*Ik
+=KmYr~+~#i{9;Zazp3ful<1hbTd-&qj%fB(-`ITQ6^pCg4?`|(&y?N*M^V8#$ohg0)VRz?Ue%;@9rqF
+-$?mM?L&5NGD{I?f#3qGG;|M2m<dFu~fyn6NY&h1aHUcXtF{^h;--6N-T{4SLv-ELogK0o=-{&)M}lR
+y7IDwVh2nm7L7%lE(d*L5QP{ilbQ-%PQ5{`HFoPudiqB_7{Bz53zy_2b{p+t06_{%uLZFSjqAKmPpu<
+$s+DXdaU1PxJ9Vn^(PBbDQ7%>E$<%FXn~+?fW-xe*DARKmYvmyAR*~^zNIV|IpL#f0*BR`u%@jW2fA2
+x8MElzu%5`YtC1iALaAfADykA>!UN}{ZXral#X2EqdrQn>x)P2@zH2!FKqos-#$FQ{dtS}dbnq6{cr!
+Y@AdoNq~FD_zrFoaeix<mY(C+f@_+o^%lXCmG{67NS&#I)`P*;*>3BCCrzh-}AE%;x@sEak{`EQ@`TQ
+?S*48t<xV?Hg&+qFu>y-WQ(>LGWzMt9-%`)}Svp+w3>n-->t1tfg*+=ic_wiSM{^;{Bo_+MEFTeQc(@
+(y7_TKzI=WwoNeE<9BPfO;ey#4#9PberhF>dkRpFaNJtIt3BUmvWeFYQ`i`R<1|f0z&RU0gHI<+HE8`
+1Gp}pMCH@zxwpqpFemuul>ziQ@P&KJGa!2WBxpk>zz4?bN*V(`grtrZsVO>&+pvkUs_4)s@CR3$NZ>V
+X<a%ubbio}d2L!3+~!ubnz?srWnNOs{4dve$0-8yKJ)ro=RZ=Ke@N@wV-1&6uj?M`@7FoUE&b~2JM*`
+CtS?-(#Qo3iv-61ax^;C~x2wlBpP{Y?$#a1D@p{yA96axu(>1SJw_SHU=Pxx6C&ypcgD^s?jIgerf6M
+$_^GIzybDCdn=Ncogg&PdK=1|wAsrG{}%&W?|*0vl>C0CYe#2Djnm9Di2Yc1B5y{%QQZQX5NxSnLK%3
+8?W&&)%vO=;^3<zQ*orz!JzKI!QQ{kRxm&XHX^=S|OJ{km>+buYfwc-(kBaN;2kw`Fa!lSs^c4sp$YU
+u*FgAiL3xb;)(C8;rGs^XFPAq-m_>zv{VutW~}aSG=>cNXWdlWmb{DtO<rJ_0nS})}EHmb5z82EzjB@
+79<@bBO`1LbE*d)SB63A=5<R}=9Z5o6|vd<bhA@ie>=u}BGx~xb<D?Ffhn77?#Eic^?f#J{h_ZLCnU8
+MRt}M`Yn9V|4$Yk&>(+Dntjzr0x#pdxhFhD#9rD`HHT}7@^V-G}r8TE>ZB8z0>Uk))Yc0+YrrzD^xd-
+!mYr%74oU)eeTFbN~eDJu(ShqbZ(_8yin8Z3MYs*thY(q}`bbxWV)v0iRk854%si{6S2V(t)6i&5yA-
+MBTgVT(Ntt~)c=Mt?WQLp)sXO3Bn<YrHqUWd7%i)!QWHXa61U#pgumY5@Sw2}gz2g9$sO_4>q*QrR^C
+l2i~ird|g37&Fo>V^Ku>sj6WgqkRRcget7uX&P}aL(WQ+UVLZG?@qIiUCfydoIlSa$Y-|*IwlHy>u+G
+Qsu5ExHz~6&)HpZwB!0lE+^8vR-mmX$vI?pT<-UrC+9w)aWcn^Lzhm~Ay10PuMgRY1L<AI<yu1xbliH
+>&hqxPmW<Ke^2{2~G1k+u#H`0y=VzX94r5gjt|K_Vy>@R-cB$GEVIC~s8Up=XjyM_1OF%=R0hZiM1&E
+G7+SmQ&xa&z7SB=j8A53U{I=_)QR-A`JeRU!;ol)jD-0_0e%$(bVf<?_9Yr^wy6@|{DE<IH+hzT<{58
+hH=Xz>I6cA<(6jKChI#J*qa>E|TpO_1-pZZVg5J@+~{bHvVa@iZteZnn;%a<OdY$uY{6*|rvA)GIV@R
+$-tZnx^Su(x}Dt3HR?6nOnn7!CEt4L$@V#Q@EYDQga}6G0YWPe{no8YRk&41(*WT5v_|!u49I><A7q3
+4pjR(*sL)Jaaq<m)D`z{J*H9oD{5ltkA(Of2oS0}5J#K06q~GhyS_^;R!(8TW-duQLYI`O`1fugIy~b
+#yz^vW&43>%kj2T2Fk&nZ+uxSL)F?MTP{Ia-Yh%~R3zfAV0iA|yCA1*>Q@ckQSz$Zdx~_GGW-ct6C<a
+Y~x@bKFYbr3O!rn1HYN}wIuM93rer0JVE@Q@XdpvI_bWGE!s#w~jfE4ET9x=|wZC7@;I*18@TxPW)#>
+I_Z;E==8IUtBfLDBPPq+0m2>~I@3#t7^-@6JgB*r1)3`b=xcDW@tKh66Zabms3FbGWXHU1&>{a^&aVk
+2oYL&>Na`PDb^Ruz4VZwI+euG~7Ptx^Yos0=?$<MgzE=fTpJ13IR)j-{zs|e6cVXqPTuuORXf~-_kP(
+F2-ufA9lK6IdW13b5iqKsQG&wlpGLl9sthYveBI#sh;SiQ<tIzhYxnXtFYGggM`z?fd$7L-P`-e6oUk
+eL-?`^kIkM7yry5oUhA<>@KavM<|-U15d67Ld|RuO639T=5!u$QRdQgt+(AGbY(Q4Kc)+!?=|U%W4Bv
+^CJ_SU`WGfs>P(*UoR7PVNvJ&G2pqp2_z2Lf~#pWqoiwAD6I5Z9IP!THNMeFD_j9odgl#I{X&!-cz#p
+%y&t9%dSLfBROQ!(Qhw!$O});8;m2)hOMW65J-I;F3btypN6qg)|wIS^g~^-m>(4~ESuZ1M?&5Nmbpm
+-e*#v!Le|>I5Ym9W;{xh1jI9$#b&<>4Cq7woGt@v&b>Qq)m(m>{_ESiNpiV>8@>WuA^UHR~O(-3=&8$
+qkINWS2+A&(S`?iVVSUC?mpXe0x43_y9056KEekr0@DzM5@0W1+74!LqQOp-JT_KylXO(^@Ho0lnF4O
+--_U<c2@Mc(Ry_A8f%qy1eQvs14B-=pX#|&0*9wk9*%uyuxiE*qJ$M?t@e@PH>ALD(wLpCnye$C%6Sb
+-tVacn~vm^n0n$}(qwgc6gIgz!9rcV^?={J@4Jy73{-RUIIwwQI`_mpKoCNnr$GERR{F0e6~O-Sg=g8
+MQdEFc4GTf(@Nu_a+}@Ruo=qM$Kk8<uhyCkScj)p}{Z(Gn+fZ_Jvr#7V=Go1Xw|S`1Y0C~)Zw;7-HP;
+9FE+U0ydiHDfFvYOGdv@6sn^8038E(i6Wwn2%{l!qdY7vp;7AH3$JO-7BdAB@&y$4s`$l@H=5~Qbws@
+Sdj6nh9<2615a>V^U+aFmr|$0lF$yIk%E)CM#mFQi$Yiy<8bb6dADrl*h2&aY|=g+KQ0D#VfonyEW}`
+|@e{5LKEANnmykoD8%z&XzadAx1HlW*0VJzY<_uOa?Rrp1kHr149@y+P*{(m0Rn+!nO!nUPv5moC8G*
+_YG#3--up)>`kW|1Pyc@jMTtave3nUx8hs`@;xz50W^LFeUyIzx0tFmZ_w5oxPZE^{MlqKZyIZHGP$9
+i6}9?pyRKmi8NHC0ee1svDm`9nD-l_0uTt$lF5(F|FP(g0J<Vb)Lgv;^`v0}NivUQNvJ>YZ3EEei6BI
+DrF?wY2l(!Mzo3zV>~@=~^eUs#cMYjnmI_OTap==ZV+|_kwHGx-HiQ({u1Z2Ny5ffs4{kkvCQeL(t$Y
+`<_ie!UVn3im(m_4AH%$3!1vBa}Wxv2Q9^}gD)~vLxotF>jCJ3Lm7LdfQ4se*OworON_4#p1K&l3mG~
+NhJrT`LiWyMjJ*N^Cpf$FigR-XE-YbLR3q9dmk^VBtnoQi9j1bbr0UFA2=O3$i2~=k`(&;_hI0j$ATG
+4MOw3tvRf|WN!<~`7j56c|)FmqrW%DeqiE&t`<^<b!<hF-QUjYoKHo*b{RY9QhDN*z&NMxod!!VRd!9
+#T%MU<!}#Ud45U3|M9ruqtOnAz&IR_uhwsDiU~WH=uun<UselrfhLh~3;fS6clez=}}<7hY<_f)j?Xj
+*kR>#*)l$yV2Ya$p!`BUnK;zV9&21r^3>1;C^jPi1C}^hy#niRR&PB_&YL!py&11Ar{uv7*L9Wj-q%j
+p48*Lm#rOlK>*fbO5hEL00+f;0B~>=gz-QWjWO~ku_FDvj>3t{eFafEwOz<Tjbn%Ez^S>`d}0b1;x-(
+BEr7EPE+IYv;S3gcAQ_MZ*H)vgY_m|c0$}#Ff2SnllEf=aKB#4Jbvi{wr0x=cBDq+X6c+gEu|qA8VfK
+OQTITsP@zXg%$t@xEPle@0I3-hAHsl~-Kpcg?-PbK}VKY!t*b##sSpS|lsc@P4@9^$JALPPTcq}u2!=
+>{wdF;^Dt#5(={f-l!WcNDHb+9RT70F0Kx<n`(#Xu;7J7XF(e(cN%a=Qy$z`_Q8oJw~I5&)wi{;h_01
+EX`Hy4H*v)>~4vV>2Z53dV6QU{;sMN$r6Or>J8C!K_W{ZGj?;wo~)WEIM84VqMg;&*FEX4m{OJMGO(3
+FcTTcV498>07S=dCmp|l9+|@o2LbvL+Z=*t2qbV3zEgq%W1IkmNvdf?%m{K~tvo7ft`e#jb#lUo5~^u
+n&}3BMDukoZfIz+Z34*mjRo~zcqEEnrqQ2z04W#h%K)a$>BNoF5==mo5!B2g?f~nlTK@W5|Pp4iOu1C
+@B(e=d2agx}kIcs6OxSjo8ShsTpj&_%&W?HCvMhcWz<(q~lROmv~reRpJ@<-Hhz}v5nA?h-YMysOSq`
+VWPgZJ$bshN5?2t(-2%(-b;?gUL&Ww{O_0_|{VbyZP#C;aYO^47&i3l|*F_a3IO-D3kqSVBA}h^`6LT
+o;DH)}j3eG6ikXboD*8L@?9k?2Hg#z2VCkD3D^3N^u|vk7BG5_=5kTVp>ZktsuN-HCf~Vzr{YTJ;m%Z
+M1aKYTS#pp0f_2_4mu%-;rr&ADeM<d?eFZv#Y#)WVao|~_6P<}H68fiFl>S*Ih0<G30e&i8qE_5*OCc
+R=nLY6;{rnbROmJwrRxgwGXf>f`z;usv@?)-95jI+-hao#ToYL24SISUZjzI0nAC;wj53F6o3`fKs*M
+}t>#kGU^pa4ZM|NM)nw$@OsDfwNK=u<Qt^JmGhiigDYBi$e(~w29AjPhFrQ5)hhDG9NKwX^3YEpLBqs
+N)T7K^{uWZ+${h#E}W80w%R!Gvd;)&v=E1_+XjHPjt&DdQ!g4Ut8{*|o$soeE1?S`4%!!UJZu3UoPh;
+I{_G%7mYi_Dv;;9sto}{gUA%2$&}JAvT@Ued*ekgLUewvV-NwhD~FsiKu0a6QpP|qL@@j_=?pCJ8aG=
+5JYzOochKH)u#cq%0hQPVcT4lQ}CcOi55FOrc$908z_*F6H*J3DsIjqtV5Mv6G$&M9nZX*CEz#&egvO
+MABM#vWaHuGKs1~zx&INcXX1c>izObyvjLb8)T|RrNW^IB#cD}-o$e`46<P;;sosZsJ7SAc*`@)W9nT
+(f2A!AKrulq+5wip2!RxOjP))<L^C@{Aw8N6gxmtUm9XHMf*Ma9X5?VmaC==YfDh5VJ^$XNSWRVaqHY
+Ic4@M2JXV~cmX!$pwSsrkgd0pNvCqyo(wx<e>D!m4Pj63Pbx8n~2!kPX?GKjX-z9YY43XG3gQ2s{}gl
+-d38nNg#}0g4mnq~i+e9pM5HfL>HcjB*Eymyrd-+!sGl0pf1L46OP@8h90)<4&9k&|OQ&1ug@z+ofjC
+AtIS}v2MRxZx-_pA+g+h(=&)VR9xS6RX5!N6}Tj=q4d^5Gnb-9X(0tU&|(?p1n6==oSxkNR1Y=ze*y*
+B`4XC0=l6u|))i?9%dkdAL|ch*b|kqPO}+dp78Lb?n**vB!k_L3Od)#@njKw_4xK9?>Bds_IQLL8PUq
+0YU{`cb44LiQ<ABCBuq11z_4S(JDNdntL#AqgglP!36tEJ*s4y-d8Ce+;DHAW%RKP5jE1XgyH5o1ecK
+g!3QG-iw!~x2I7CCtd3|NWFwi;>#b7Zaqq4(k0WhFBZWT51ck_HQ$(0X9px>M;^j7sH0_C+y&=hR7&_
+8{&;h`A;$da#JBUiLv?%rp3<%bQjXzMq^iRshBfPHWn1wuz@Z1S1@N^cI2zT*jJbSq?P9;Qlx{1@@=Z
+$dXv_Hg*ZG#tg15^mGM{O)R>Xb5rp#7xlDu$Y?IP5(yeN!JwowmN|B)>@c&88!2J~<r992`_Ey)DkX6
+wu9q1&0|sQE>do-M?<+(f)7V<OY`_R^nvXB#fL!5dm?k;&uH5axEwyp#XKpDtxuoGSu~1W_1Txf)IJY
+=T9K#`G;8$4s!fq{gMF*eL1>(VOXEW50l1q~`Gyrjq>W(=Nl`OVHNq`ewXIJbCZF!h1v-X$UWkb`KaV
+eY@xY#Ujb8P5S^W8MC5}fGBY9noe2!LS#wAx$_^a7683A0r-#Fu1QVecR^;6ZAvTiv*^U2ZRKmg;`3E
+u42cBwf}#YVhGaSH%nFwge1FA8Ame#f*$I?<sBEm?aZ{pBJEj%!8Ulf=*KEsJH`)1Z;zOLYyF2xQgpA
+SiNhj?;5}{dmv!l57UwK887yf!~<dn4L|N|lGUtim3}}S3W?zZ%t*`EUcF5+j+1pGM5g{A!_@?lY5=8
+jFNfw6b86yq18-~@#(69?cWu~sZrEu07UXWp#@F0bTzfFjdCKs(hiGok0dA_+j)WS2huCj;$&3`hv7r
+Iy#5g0Df-Xq}NkO&<Arg@+qF<%#O*4caZl`%a*@!FlDX8rUaPR7Yb;6Qmx0T$S;od9)5lE7tM!Mt~1d
+;ClSO$RT-oOc#WJ6Uk&JIE2I-aKetcMr_)}F`<=`tR64ofqCATl-xuB{83@moMsB2B3hCt#d=2wEK^G
+pWlnbW8wQS=B%|j}(m}L(GCV^NBJ4=r~yR?6&2-aytfX7Km0BC%8aqG#my5w_y=0j^ioGWJ)<W2&Zp;
+N44jn<M56>QozTabx=8}*&#fIOb;`dvs-uaS0WUiG%YY#*04BqYm3-tq;gHz9?pc;*r4D@ZZO9K=7{~
+u#&FQ$MJE50{p|+h_|kHaPkhH%_&811#*v)EWD?do9H;mP;!+<D>{pACJ1B4j{}Kel(*_L<h#7t}6ww
+tpGH0`BktM_wvX+M@$tE>ZM3$U!R0;^DaPFEAVnhuBYY#KB_vi{38LmIbkA#}8=0d9DG;%&LhS`WA%7
+UcIiqO?$YP(mv1p$JtO*tMCfnCpugSoJL!x#36(d!@!LbO<|X<pa1lb<YfD4sO!d<?R46T!GwWYnPii
+|B+IME->Fd+-VyFP)$P#297rzOqO&nXjH>J}m%blehtlm}daJjc`J8nEHL;XyB=mTULrR4t}lKK0viX
+Tyc*Pz_9?6GgcsFU9<v;zJzr6)Y5hQ3bJFFt2y0xQ%UpQ864#uxr6myS29dD1N3l~liJmPqw1jO$)jr
+AD<SG71$e+`M~#{Y;*!Q8{k6ViO;(3vn1vKiJ~-b?o3bOsLkoFgh0x~QktG&-aCkO^sET<zbu)Ck%w*
+ocKrdSW_eUJV1HwvXI6V9sNmF<l22M@QArv2q5vOT{3E!nAjXdpn2R71F8Chsn{*=2V0|$(fJxcgA-D
+PzaBom-vyTgSf?240S^qZ`!V)i%zn8@}djElcl&^DY-#1{3&6o^I5bA!Z_n70ERb(fu_$b2)m7eXJp<
+&;Y+YAXc^A@S(5d}Q`P>6H|g0lI)MrOlM=>XS_Rb0HnNn0kVa%vi_ye2^rnFw~>uI%&S9M@42BVD`|x
+?tBo?@m_?&S*s<2CyOgGmj|(i0IOAmhhBlmrhX?Iq9oxQrBU@i%nm*G+O=&Ku=m4~0f`aQ)&SgOz!Hr
+~jzBUrd*oUYQE4PMH9|xglv;@fGSIF_=`zf6x(F=?!tf_{=`_oxs|Gupfri!nAvNPP27>yHfJ_XuD^m
+*Gb^)YkBWY*kM|v}ifVjts0kjJd*JL8@Aui)Eq7NIUsBSQ~>r*luY9-p*SlV`~vX>d^=(y^ULT8ekT{
+sg7wjl#G=3muJ_=XZX=N@XajwzG^uACM{8+ify0so|acHuSNHj$?c&tIZ~41TSs=Pp^V5b|BGQV9wta
+uyN@zfk^?jcGNr7xfKbMo3Ic!W`(MaKf{nU~aV}WAD{2TcPxz5^0{-gWm}jK|Ll=Xo&(PBcM%bVZn(q
+L>8eQFH$Hg9V%}ZuYi6z_tmEY*$^J==m7U%tw>jx*RrS&!{>EOLMtSZ_p-+rJ8fksH_i#)iY>X8cC@k
+rzRrRm{mh{nB4l@}RUIC|@X!TnJa+*L!KXwS8Bw7UUL_&bW<?@Qt=Sv8#b*8UY)PYG)r)CZO@*=t+Mp
+5Rw$huqCGw^R;SEsDRBD>T7PJY<ZOsDWo#=9dv@9r!TqBY7++{3fL?SFxCjm@bhHcJ-{)uW8Ski)us-
+y%YoQ_5od4uL|r(Pah-<kJN*IhlRyq97#OBLH?(jAqb%^(2!saVWF%0iMBH<@17kld#PWG*9W<j!5yl
+E|hlL*z${eCV;L=s>*?D8yXmGCMdk?@B}ibrGdh(Idn=^XJ^vE$uXqo9UCfMOp$C6jcD(gJ^_nw)!)2
+``1QEy>QAE4gha3PUo&}Nrvt;#=@=+hjB{G6760h-;7HD;3ZM{fUL1fnnWRXR$xUMv0ets8#oLM0;D}
+lgJt8XhvsSNV?C8~1!Cl;k#RlJg}gc0-35)v?zyX55;>bGhZnsBp+YS3Y-zzZcN<h-ajhB$;{DWNHxr
+5TsB9D1W1KtnxOR*%a1~)w9*YN?P^nFp@33GGZUN;^CVDrj0Gfn1R&}KSLFX=Vsbc3Wy>LjeNgjgWhE
+54W2rh>;JVoQy1(R>f^7?FC*UFZGU8hWHMYZY=mUBIdQT0J0F1EoW3t~;#I3)aKL5vfA&;VOz>-eI+;
+oOxj#dH{U#{etUx&?1E6Ob(?X~40aCZ=+*PBUaQB=Yvy#Ov^pLdoTOxcc;SxVO`l!@B{jAO_+BjB2G0
+4xN<HE{*Klb{QK319jcEaK6ra!HeWaOX@H*5D!d1@-o~8=SXRFIwR#5Ax0k%G9b;IyxVM;BqZ)$?;^&
+5A!|kpDFaQ=p{bdJt7C!X#my&zlgVbz7_3@l&cI{jowq0nJ%6otf%lOW9+52sF^_M_Vv>7N<kN^^mCH
+DUc^FMq>!dl~7U-XQmjXXlvs#HrClE~|b+8ehX=Yds5kIj4SkQz@EaY2M%Fw4KK?j-3VBvnmB+gy(k}
+q>z66X;(E6jpOb8WKpI*@{Z1Q2A%x*J16yd$ND&*^@^KxwlJfVgbUBdTXDA9aS=L?(!>1TZnL1rst11
+A&9c8mVf9CRB-0%1(AhJrfkkRG1ek!E-fE$vG$UaRM8h$4iG*A-)&`3K6qqnNn5dg>u-HFS(iJ13)??
+nVG=Qn<RbD5^F$=<OzOV4iX*YXI}$ZYKw_V)I6NK_@&^ux64`}eJd@GWFL__p<|b@fRi&)T6ED_KD|s
+tL(933?XG@FFwS$E0UbmJBNrR0I0|kpdD5p<%fb|(i&`{@U;|){EWp{3#B*1_w95!%b!x~rCW2_?oU&
+U;_Js{Kpk$Wpp(Cw(h8m!@w}SUe+Jd)>Us5+(<B7mRBuORfjI$tIox`3%<PO;jV6$}(W?2>8fkUAT@!
+Lf(HAU1K2>@lArnA-@&a)9}m|7FphkY^!i46f93o631W^wi|?HZVbWLN9#t$Nhs=B}Xc#MU;m#|Hc(m
+cpz;xh&PfVr@9kISM<@T?Ye8z-BjnNOL+!3TtLZAkx5Xg1e>pV36BH4NFv-;g^#Ux6je8gGt3AQ<e*k
+m@`6Ds}zsDwukA;jK{}_i)i+g4=^)@=Zvht^Ii^v(^v@QW+8r#hsIGPVFKM&b+RbzNQ9M($@2r}g-$9
+tnfjzb4X)wbH8F+AQ8Q_n76x$}Ocazn3N>Y?rhtQgKz8ktcp$uKlLV7MM}*1GT@;h)Izeh?BN4KZgV+
+qM1m!?P3ANJ5aB5~zP*PAVK*33G7&$9h%a*$Hjv@h}dy6INF@Rt%Q)<<(#{4lJcmYI7%dn;xasvj~h~
+E(bopaa4R0?XFCF&NYTWMGI!BI9{QAho7@Kvl!3{2KEGZIx{Ie*!bw<}{VEsf?IJq_i2sQiF_IQ)3Oi
+Q?>H{^lUhL4pb<tQk0KX!H?X7|vZ7)9~(x!k~-l1RZGML-06D2+di{|G11qGmQ0G+3*#xCU~cFSH@(r
+ze*Mi0o@^pDqy}v%!F!hNfqoUb{?6aaz{nNiV}Zq5%oWJVN8)eIMmf<PZ7`1rw6qFPLMPibQ1Y9DRaQ
+tjJAL`z*nomcb~f~rs^`0MmjtqmN6^aCi@ZOBJ~o#yW;&5xf-f)(gr!X$zB(c_i^r$7*DvWhvb=N9$C
+x>tq%}3lW|D)n7ohgC`yHg21zuXzummz+*L8{G7it)nm!N-gxVV1^2^w=xY19TGepcOG&nuC94!!FjT
+TYou8e5_o>NiQd^O_*coU#-QecZbTh*^`nkB3b$HnY~L!+fPxY5=wjY&9J87iX4uAmZ{hE#=Wm7~FHg
+QHTf&A&p@*nWm16umhjZhh|hm|9J)(C)H7fOugo`qV6HPM{S75`vHpq*mjYHv89{u5}#Ldua@gSK|pw
+Gi!eMoO}+0Z%i<7OVe^9DM7KqKrSgC!U=1Wqk+_UFORXxkYH(v0&f5%QGjHuJ<GM*AS?6&(NC@>0v}d
+EP5?(OLLlcZktuYrX_wv>%L`$Knp?O8v|<J!bYlfg5U9<f)&p9_<|$bxr0osb1v11vbJqj`O7Ni?Y4n
+9`f<`(~#(lg@Y{hY~M3h)<5y4Vzp0)V9R_bi`x@jv%$SNd{D7!t@x?6x2pD<IbC`DB+kuB4Jmfdb#^5
+|PV+$&_P1vfbiW0mDH3=Ns1aTx<exhgAqYyj*e1t1e`Q<Un>LP6|GnJO>VOpAh0wN(%BCed`O;0;#=!
+8~H9jZE5I1}k-Ux%=E+7?QV(WeQ@PD3clLNx(0nY$g-EnrhXA!1&n;iq1Cq@{F5$g_#99CgKW=v<XNe
+)fv>3i4~`issnR-dI!Xhzyh)F8nS|+;FA=Uw?;wqKHDCvZNlN=Sc;wr@g3qrrC-+^D{#qV;g4FcAzjW
+NsWvMFdJA!w`s)JjiW$?cFO$VCd_?l6RSd!@WuNqeE24j(r)3{5XMit-(jbSqjBPb`!A!&WUgnr`RM%
+-AmUr?9uqmiKyF*cPlPv({nF=*Jsax`9?P0X?ICr^BAtxNvl1&v3-O3YMOM}2$v_T<NCGlIMWXU=o6t
+rC-Z+vXtZdc1>z;!-ity~nMIi!Ia@4#(lN~K!(!_HYWNXwmYLQMvd;EBYobKG0)AYc%T1(lbR5eGB}s
+pPfFlt6lz@M|gJfo2z9TC|H#r-+0F+%+=^KW#p*KXEY~6RW3g0>(=25mwfHfR#y61Bd;C`?m?+Hh;Tl
+Cc~qrL%L5|Uz!;Spbt>9$C7=5NK<c3g<+Tos{t`m?L(t{M5OQ9wKIj)EZES7yOl^`h=9GtZ6+h|=u0D
+XQ97{QN<w$7N$6tlqs;Nzr8Bh}S_Z9Pe6qo$^=*(cnd-#d;8v6QKWrYByO3;U-Gf3BrtdoLL2UIVL=e
+Rbjm&{Wz%B>PVHO-mwb{Wk7LTp44qK|)Kx^~L7GwQdUY+<Hx8Hy-Mo3Hv<=J558q86#1&j<~kq}3-TX
+#Y}anU@DFih9Ic1D(ke1C8#uC*?>E#oLiEM(uJ#xs%a5yO*s0Q3~(kO*5-WV~I+J^wKp%wVLgI1Lt+o
+yJ9{sH#>w?3q7qp-qw#L|HTiU*-ThD5{dLT{)9U7|WO4$#8^+w|CwAYUeh1(yX=;Z~H?tt~`lw0)`KE
+QR=m8XA)#nv7^P{jM4%Cim_S?W=#YsHYJJ&CB#Y9)&v1;EZdF}+E~6_K2s=~lcL9|%#lXk6(csz<~{h
+$`1V67HED=2MY9u`EQ>Ye#~x|Nv1PQPC>RAma%i)KA}#AuvB?7xb=d2J{D9#JcApkQW11&2(_@@#=gH
+eRP_?p-W7pk7<(MgB`q-(d#@X=vGhz)Zh4>Wp&vM$LIm)$*X9{T_sNZDsOf%7`3Q6#U1zeb<7RXo2#2
+K=QtAb|Z4{G-mtGVa2L)qDL4lmMlJ5{aHYto;df3&z!_e1??szOndp_5=@NdD;IFI~HYCX-{LpUm+q_
+O!A}cvu&2`#merl49)YIv%o6d15ICbaR9du6&1+pl%SciF9YUp6m;0%_M`CE4q~8yOVcAqDJC;C9a9O
+9#v+P8(h1XChO|xAm~*oc@hbp+p4xkuMs0e_=o6R&)7^pd&tP}M3Kw2%V~-o4To7s!-W{jcyLEz<ION
+=@ppJ%9-c^ZvUia6z7`Y!E5_D)yPT$4(*o{KW;$A2iw}VG4%-k7mkkpE$7{RAC3VAmCL*Q9hK12V@!G
+{St(ge6?jo1ZVh~F*tIarsV9&NTheh%LyzU0NnV3R1J+^39(iGDls#pVA(?Ni0%rM270Jxp2q`Pe?j1
+J8`EH7Ise@E;u7`1EH(U@9ygva0^#XFMGHJ69knn^0yAxZ!<pPDBX40Y)1GqET)xOOQ`lF~FO->Ptl=
+4g8iUv0GKGJSctO3)2UragBgrzj2>>Bwuib}>z*Y^d0;p-J}Gt*^QBsMKPpl9>`n=+<q)krIZ<6l_!q
+k1AzAB?k<@${kB0u*QH$IB89EXW|QdhLRb;f-`e@++d#~yFGfm5-anMd#JJ1gLcgL!`jecMQCRrs4^w
+NRe{xA=TXIN9LXMNL@1i7b?dubPSecQLv9+`cj>f9Tq1}kBzBlApK5k&lsUGir<Dg_XdOJ;Uu^iWOKR
+-#X_nitOuotnprGwcq;H|6vsVb24Wx@TlZosbeHxR~@CMUy?V6fK$fXkhG8NZ;Ty7J}vUD>|L0&LIt%
+({n`g$Qc(Dps&^pD7Ox$3W&lI6AH(1ym=`oqMC=F|fIiV(o=Mo+z^%Sl;jE&A1PDo23vT~m`h(3ZGLk
+&$y<4RmGmQwiz?(N6sbg?E({zyv5EuO>yW9GdFfH|pNZQOeBL4xCv&Nb!)cKf+6368g^eQGh_o@zOBy
+Oj|4O7o7>OT~kwt;AI0b_UHmXW}AUU%5Ajffc1)>A{S}3hVWtCoA=Rbhe+(I8auOF83+TBakvYmjjbt
+V<Z%#+C=qTLu5d<&V8mQu(=b4<N5p%sT~%}1$R64D5NiozvVt$7BG%v8s!7;oGJ<_ZA^+C$*?lq;#J#
+2l)`03P0}s(3(%4^sIL`=zM~DKiwKePeWc|!#BJ1qZR<^xO_jcZ#Cbc(Mv}Q5<5b!l%h`P_e!UY+~wS
+dF&W@~!vQIwV1Kt;Q*CJ(#QnY;_21jL$@WKgD?Im1M4Atwuz?Y&@PfsM)4Vfq-M`F356*u#z(*do&by
+7I2*Nm0NIuEU45Xkk784N})W0zue~A9hJi!yD_?s~EwyD?H1tErq=*-P|A?xx<hp&ql}9Vw;M1t3r3c
+z!1BpCYdp3#L!rB30hhqR&deKc+%a5&-fzn<LQt!;~G<Zyl_kSb<dDokE7W(AJTk4YaXo|lnDhZH;{A
+%E!1#+?T2W4a}718w?|vv>$*4dkvLywvs;MG1h0_2!HwB|fVvHd$de|8xfHd1c5Hlb_IbO4_u3jfoSF
+j{7``%yfi&ZCHB)h{h9l2m9c`0jZ3joBCE*@7bxV&}<FyNHT5L7AGn=%gg&BY$cFTUpc4u1;+&yLP3U
+C}_Z5K6myY&shc6m)zfOE9<1>o9I0cbqTJz}@)r!!39GCk0M2RxGGr&38SK<+_=Uc1aD;YlY_XR~i@=
+^(gf#trmvk|!1XxX{GOvJ1si31@vH2;r=<+gV<_)FulaE!l`_a%O7X9c4z1WW7rbZND6J5S@t%Y*rOT
+lblnDd8fWj)ULM4R8E>M+@oi=(NQ!jF*JO|>`G%~mSZV9;j|nDv_}7p^Vp;8bV)O1$c##0hGY-1!@j&
+GtKbrvHD}K`A}hl8;1#4h5C#%F>h_y<v5j>LW&|3|>G5tAG=;Ugr}-qAM|E~+Uo)H|QjY^jHZ9q{tw*
+ElYnR)gSemWJh=DaCPe8mZ{bSX(UW~P@=I|3pw0{buST5$Y5=5!d5BTc$a5o4v`$mlePfbnOFs3}a*}
+2_EQs=u8niy;?#<5!vXtv>Iadyc~VYibyjF?0^EKK%Y8bjm3D4GQ_I!r=UB0~+Uq=`Uyo<d37OK!*=s
+M&&A)rlo}=2oBH_vE=T{Kd^@89}wa{pX6$K~&ANzQ<~J>YDA5RR_13L~JMO>RVor0owr(*K3w0SmM;>
+{Rrn+!XV(No7&rzH?2prC++~evAfi;yW-&{qJHfeA2sTH-1!NS2Bsz>sF?V8Mnk~s{#F><AYbvG6mD;
+}yp~=&z^M|GL8`F^cC@swg#kF<WOVx1Sif;kob-H<G(h%tk-4`^&^m0kQTF(AYBH%6zP&+IhP8qPiS)
+$0huLH$zI2N<CI$x1m$tK&3+sfZRg5?oeXw1Z@gFujldhT!y!7a@e(j>0A?9&eB65jYgMm2R3}5TS&D
+qO^WvtYuIILu&-!_SYY&_3B&aT%sSLg8HMSqx;2M~aancB_9d;*-<c(oRROZ?{M`>6l`-Okcc({b&Jo
+2qs=Z3<*RR>QW`3sH;<^Iy0@wRYQH0--73uuKN)%762kfPA~~rWxQhO9CBRO(AFjUpRvnUs>)#x*PVq
+bx{z}A2Nw9-)-PmgCuCX^d{S#q}!Cn<?^R_`W(vaHQmRD*B1EM|H9ym2eJDT8x^Rf-K%ea0=`p$U~k2
+rYxd@io?;3cR-V+AN-<;u^0yxBsWEmW>~zIT47D4G16ZPBjr64e3j)j7AXzJ9nNvMXQ8Chh-_>;~6(E
+oCm13x!KuL7qv>%f%IN)H|3a%*MVytMr%o7NQVB8=zZJX$J8hYMJw(a_xY;6be`D6^${(|(9&JgkSu)
+f3WIPEyP01CO;h25$}2=H>4&=mo~whM5wiCu^M02PHcY9!jkutQZu1`&xq7I|mevmq2#rIEUPn9>~HT
+H6&k&4e9W9(7GD*OzEdu^eIhmKA(N<N0gF0~>OZ?e9cFL-c`(NMyTL;B--{lrC5Y$-?EA+yfOiy0%s8
+_KAsRGk6WN@|LDXmmI-qkD}+c>u{P)#mtJJ!9YUx>S64i@egq@_!6d+qeWVctr<;$9qM^bz&Q3m8(5m
+aO5CT&>OmPbn=(b#LvfSPA%ybCph}l+w%EnaR^3rBBzvgc1Ss1{AJ?UM9l=_wcSAfbY!}L!2!?@0=Vo
+OIp+nOZvz;5lFKoLSCtVV^(Xu{q4P30ZMEm+mI*PsuF}G%ui6qEHM?`P#^>`+QM~Y+H1v%9>6IqyrZI
+ZyZxiU>B?9mQ%Z@xtkeUOsAJqbqiD`~!;;qXL7Gt72>|BP<{0|pd}+A(sFZxDwSx4e>v)rKOL{2hHoI
++1bR5z9IFeUG%krB&9a$X)o&<Js2Tq90hV!@A8Xyzmjw$nYb>*F}*KXkVZaiNb9c<y8A9oIaC22871Y
+Ye1Coi>MB-fZUwz&4W<dNwE9CJSs4=hKATRIrXrqMg;1SI`D)noi$;;^1xnu{Ir&m!l7)QC0YB`R}|=
+_)`+3Be6Q(_hV@IqHkGQxK=`d_km6?GGm$@>U1R%`VOmHO%M#|k1@s6T-|jUz&C_lZGQbVGrI?G*<F9
+ZcoGIT~gewd>s`!;DltZkjU)n?Mc0eO;hFldN3b~@Nh-iGH=E?U3*$k~2d%?3U3WACi@$ua&TP5wvoG
+MigOfh|$!-qMS=`st{%cS9(2gsLt#IeJ^TjYbuJ0m-=?Yf*ctl#or;MEv4CB~U)mQnXlCX5e2hl>_9A
+<gglS5*NH!F{ajE)~iEi+DOK7((O7$P8ZbWj1Q`I$!&8s9*6&fKtAGA*-~)vuXFj973b;2!vxANxIEC
+cnH&KOAbpet#>^`ReHkNVqit{Jtj0n-)E}a!{HV+C)N%B98K=~7NNJQ{p}9hw#guZJMGHYd?5#PgDn^
+IiEGq$w_TZ2qhqZKfiyrXeT+^)W;e*}Y*Za5szQI2?wf<6VN7G47nvgY5Zx@=F3ibxSFv^S5lKzl{u0
+G`V_hs*9dh46bVcZHxmPzH3YHzd*)Z*~c6E+aAK7Ku#;BJ{9#$g^6n?E4PF8yxhd<p(_V#iRfglWO-9
+zmTlW+)$dapKgaR@Y?zK_!WxWFJgq1!OUUNH9F5|O|JnKL`$W_zg3V8Y5a60ef28Hp<7Av7|61k@1yS
+ONxfoqV?$m6D}tMuZB8M~U>NwkvhAuQRp~lxRqantlwhS*W%R@bx*C{KAh{aTRCG_kzUhW)268p?0B8
+wzxFby1BV%S@nm(30?sV4#oR5_$y-)88H?Wk&|Rs^bx6oZ5QfP8^lNwfUZnq_I-|I2{zIbffF`$_YF_
+>c{?l`V()1C)ku$NJAtpAca&*cK>Y<(nJ^CFvN%vW2I4gP@<$rXR$4|0S!DAq<FOB5iL}JFD|ONpon_
+HT<|2a|?Wr#%?@NTV^pQ-uBt0p3e(ZXJw6u~@j^B2zPT|mEr>e~ZhEXM7Dd9V7NhmVST9ba-&}m8K8C
+~9&iXdKMI%L|5w@Y=%M{4Hcbl=^pD&UpQr)NgiVO=4}ao-7Eo#HoixxHdw@k@?!w6?2tQb4z%&|((FL
+6{@Ki2j-HcJ&Pp@h}e3vBO|1L9~ucFd=Q1>~sPpoe)VUo>2&+7jQCqwrGR*Yi`g*R`FqRN%(^Z$-e5;
+s_j<yq;|q(Ggl~H3Rn4RVN~?b=@Y02m=8$Zm&+NGx5EUvg<V$NNZoPmu>xjxn4My>D9&`Xql}qKr-Yd
+uTL4J$t~iR(Aqq-~7y5cVjK$i-orv9b`A(K~u%DX!XS0O^biaw$FIgaFn3qJ1=!ov?ePM_3_U!*h_`e
+^)E4E#}lkK(vg$bUlM!z^|ndlsav;DARp=CiZebrn}G!)0BA4aVx`Pu>UwySsgApr%1;53mKS#8E?jg
+q|w2H`PZ;_N#!LiIV4dLFo|XC57W+AiMd%1n*>u>RIxHj_DENu8y)aU~Z%p-3E0s$9PN)Ns+|?|V*V%
+Y-oy_)1FqdiV(V8&qCZY8?6@eDp$$%f+V+Uk>1A#3No|vPZhV_^_|bf#0Y1bKe{jJYmacY-^;U$)Lgt
+Thj<n+-+biTbzTeZ@Ye{M=L^XuJ8JBz~WD~?~;IGaI~@9r=3yUe_c7>2}kSNO}Ok5o@!;E?J`Zgfym8
+vNwd$=C34}#SoV&9$|>Yi^urDg#sgH%wkz3|W7qH$-_kNXwjE(Lme3X1b+@<;5Z7#=V(3q4LUEd$Yx1
+_@90zI_@pNC4WsS$_yD&&Hj@W{R;^GOa&M_y=LOx@GnjPQep}7W{#Opv>zX!>!qC+9O)tnPzcF0~oth
+u{<7#9fnpl3ge)tOU0Z4<q=ZtQXDmWb*BF{XeZ+Sno)dWH9wH0}Nsn;1+cLgGtgE1PDkVHwW*SiAeAi
+uiPuDg%PNc?2SDmBOihsNC^yv5Otzn`DV<c6K-Q6&n^c8}0ta8zNiX7iwA86rD#1%n-S)7BqHWU}w~W
+hWdxc$Rm8ZTmB>rzNw^p1y6G*)`qtec$TDXwEAvHoGZ9C4U>U+BSYjVAn{Vj(YT@Q0-l=9R?|y_{)iV
+nB-N`+!zKu$(Hqbg@TMIntJ;gpcO05Feb?r@h$o?AccVV;VhjsPuQ?Ftz(h|s$mmr}6(8PXjF&@+Uhd
+JbsO>VI8XFyt-B}<O{^CA9H$6|Gk_wJ}J>w@)r7n%aqBoD2{@EUD15AC1E8fUS>IkObM3R*$##XAM12
+bB0I3D7m4u^)kOc9CH)wU~n@H~@LyPhpK>+zycNE=TuFE}`qpw3)XU%t7{_PLzED(c#F^RDG7;Oz=`S
+mU@@r$M}oC{p*ObH1XlX#+iEG{rpZL7Ds(I#DzcE_UC=JeA->C(SuqYJJKBVtLKN!`G{aT@z`<bZFVV
+rxkc)hzupgBNv*YA9s{V#DM@nC$+YdFIMq$60wGATqCiBL(kr2K&!@$*C4(ZhB@!oh4fw415s6o3<iy
+7^SFzPq27HpIZNrgJ?!r3JNifgEj8XQCr8t`a!+Zu7rH{B!fp_^@GV?{jeTLy;X~@M@vA=_Q2G+Td&x
+#m5+*_V^<C1_O-L1zVaHRn0R$jN_g?116We5g&{{D7LVbTv&Y5kbmD8wu^)|xH3b{tqnSpMTE&&_iV-
+UYJ1>HBa2}s#ty7~85bP#EZsNULxw|@K9+qdt2c=LzbtCw&6A5cpJ1QY-O00;maO7>PvfZ%^W0{{To1
+^@se0001RX>c!Jc4cm4Z*nhVXkl_>WppoPbz^jQaB^>AWpXZXd6iV#ZsSG_efL)o@rw;OZoEZ-Zi6i<
+D|XhXZ;)gJc{0WlWe;{VW6X>aXurN^e2Mqspsk)HlIM^-q}Xm>e`q**oXlxDiAVEvM8oMK{+r&3ZMWK
+#?U)u;ZlxBAVpA|lN0s?1l@fhpx0J)yZ=FLYT6&4d2Yz8?_H4<N<gaibe$L+IV$U#DRjp+%yfoV3)9#
+Hue1Mpi#vbjtW#PG?O><!UIhC-1Yu_N%&QmAu(%|FA-$8LTyibu*l!RDE2|KngTpT-zjrLY<YHw`Eb^
+m~cXeR6zT1vIGvZ7l;g`T{jW#e~7pZbS1N^Y#MO;D+{%;ZezUs2dSHKwLqXtG>Lcch09o`f!bF&6mB6
+tZlBsn!MB2~~Txl{;(rIA76}9V(?q)@;$uvfe0}13Z;EYsVxU?SswjE=r9<A?c|Q8XM3b)V(K`@Q2(l
+Y#l80p+7ihJ2CdiSn3EL>c=$q0oX;+4Jk~+o{{~l5?nehNa_Ra4%*`dglO~?YeXBS+HqN{9vBcyPm}E
+PVwF)ef2OA>Nuqi7e2-Wt4KL<*WRlfhNf4teE3|J=I0$B=B>oIUG@MK)*>k9VJjv#xG^Oz(p@^1Il1<
+{(G)ic>N|uXs)F(=r&k_eQuZjF7aS6)GK*@r=kjfoff5vzn3RDH{#0z80IZJF53H&1a=6}sl8NEI93&
+=&#dy*w-<9qaKC3Xkf_tSL2a+z-rOP}|9^xFVILVr;hK??X-mY^OhV{DIx#`zFBi-5iRFc{q34t~8G5
+Uo;J-g{^?fB26_q}^(j)>PEbcf!6cL|8TqF#JWMRh&INeB+34CmM$val+xh&|BxRZk5P)Qu7%ZA3SOB
+%#NNDq}qgJj{V-64WvHB&uZo6u<;zjo3dXXycdjf)ptd$)7g5qco<DvtyZptb4T+L*167xbAfAt-6(0
+jmN+`=b;q$PyL9^}&5h=xKRm9+8R~TVZ*kp=3y4$WYZUeAN~@jkOZ)-*t<Y-`1pNvfKD{sYkI5}AqKE
+Nd{R=vxR^Pn!cG7pPMa7r?KznJ=vahYC8>GC=o^IY_QbKQQvHdreOvqQEZ(9EVP)h>@6aWAK2ml;P_E
+s>7j3jX<0093`001EX003}la4%nWWo~3|axY_OVRB?;bT4OOGBYtUW^!e5E^v93oZD_*N0O!Q`4kBl1
+K0rV+IiTgF3bS3ORg5iWqTwU4bP21OH_$yNpzER71U2Z>-$n_H&AY%#}_ime;@J?v0}xF$p4d1e*eGn
+<>Nm;`L=xX<g3TuK6_lg{N}r_{&)E=uKncVlk)uab@}e@=C3#JuHKZdZeL!PoBQ&Y+kd}#^X4kQzkU1
+byPFqR54U&a#haV!cMs)7uKD8P<E>BL-8|gn&OcrM?fT8_FV}bF_EmZKooD9yZ?7NjUtIli{huCtbNl
+W-zux_Fd*?5CaQXiBZvOqn-SySO^~>_}d!P7^ue!S9S--r`t6o2pPrv%C)bl*@h~K^Zi}L8roAQ)v@5
+|Hc`|G>EUB8?&`RexF!`;o#zh;`B-hcK_`AaE(xw`w;^8L-5zuw)vEuWW+@S!~1mhay`yuN++Vg6aFH
+#a}uUERHB)n46QUzhvaR}X*B!2Vd?-~L)&T)iuI*Dr7G=i{>w59R9J%Rk)S<^H#~FK=GG=TE=BdztAl
+>WAyQxAz~{@Xz1=P`<go&q&LkuistYWj5dc`tzHc7rFVHn-|yb?yt+$effpI-M{{ArM_k$&pr&Ke0`h
+8ySjfY*Eji`cmM7B?mmAh?Th;HZ6BU^S+dukUOh1W?B*}r_*n-1zP!n9+<m<Bi{D*>-)8!<+`RL#ue0
+{~ArH(%{~og{KVO$$@2_9|`sOlE$hGBPo;?5O?|yh*9)0^``IkpepFaBb`Hz3hwOQ$Wn*Ezkx_SFcOz
+>sNtnRMfJ-pAr^MJoRe)`ov=Z;5TKKbU!^B)=g*H4~*`}o<j^7VI5%cJuBqo>cGeD%XOkDiwAe|Y-+c
+h4SwQOdLH>yJy!V*cJD|Hl%)$|K+2W+h)<KV03sxt~-2G245e0ls-zUSIv~I@|o>`X&}tuHquUy#N2&
+!#B6@{_1>l%Wn(%$8z(kyt{q4EPubdiS5Mt{$Y3Xl;8IEGDiR6i_5asTy*vBU*BX4p5^whZ(ilmU%$D
+%y}K-5-rhfO>0ch@-lf&Ld|vxfOZnkh{_<b_R~~=+r~f9Xd~%To|M|<-Ys<3TKj0Vt_G_Ty&3pF!WqI
+-X>h9_Vw)AlI^PB7Gf%zK~%;f&<yStYkKP#8H`}S>l{qNhpbsoItspa#}|5sVQ*iU})hkQ_%Ha>iCwh
+tfFo)6kGj*lN4A3j*Ne2_=Z59$}o^6`V_aGt!p20A`kGoJF4B`*Kd*VVrM;nVv0haW%7U;7-y(>QmA`
+;Rxi%QX!B59QOouWJA$zkTN8>bg%~djCrx@ps>P^)rsp*8hQ3&9U9Si>KZ{;7@OVeet@y4z7tIakQs@
+dU|m&ci^YzKYst@t4H7b^rt7!o<Du^<qyxFeE027PaoxfzWn^{!be|z^Z2J{PyX*?rn7GgtNrTj!$0M
+nuRdNBPkZ{)^Y4E8`sw5U^V4@v|Md82F8=hQZhO5f`#3M_82z&KZCv)V<)35O^J`!DwO-bJ$=}A7OSU
+t=uGN3mnC#vzd(GckTh_~qJRuKkc|u#)<FbrBkKS{2IdgNbTg%_Zaygc5xvXbyY3H`(pRr%|^;q(Jem
+e7%evFm}#tJUWv7MKrWk}`Rxn@5u*R6S9-gK^8#-BHhSPWj2v92eBJC4hmVPCeRWhP@eFE2_PT*xPTK
+B>o^NiBJ4-S@#Qnb}eMWyx?ZYp&s08S9d#)-~fA2k&en&)+hbtYP0WvznP5M`qiOEyG;%gf-)8y=6Ym
+w&gLsj;zJT^Xsu@NPAw~w@mC<^C`o;$a-a2Mmt!HmM1J3;oh^(OKxtNI3FAtS5~f{OrmE_rDslkIdj{
+>9`(F4bI7KYy0*)@9eLH-bK%}Ivvti+Wo5v5bURz#nT5@LEDej4x#uxk)-`*yWWXz%o_AhkvTH8PQ%A
+#qu$YmH7{kggZ<k~6{9c)NmZ~wmQnFq>KV~}Z%-}kUyK6QXc5nPMa&zT<8BLbB)hr)25gQm-Oh&UDdE
+HpD7JD`?JHu0BAuIFDLiWpxzGSd5{L1SY9AiJQ2~50>Gt*mRhjETPp~mp~wz>is5LP-jp}KiBYq;hyr
+L)yRpWK&Q>dp!*nLzeC(`(poUUfOLk!&#gmSu<uH16#zQrs$QkJ%hNM$^rs>yn)r3@O{QVR(5n+uA-j
+W-hK8Uc<0inygap&6{G_*_7-8yVvvj%6e@li?QPYc<YvB>1TfGTZ=XHd=QVyBo3D0%<{!H^Sat_ikb&
+D_9v@^5uZ$Db8wl!II|W7BObiT4c_@F`_FYNkIA!E{9%a!mCX@il7WPbVP~<AlVA03{B~ng_E<+O5>v
+v{8#}nP3>{|;0%Qdi9G}0%Y_L^aHsLUDIpTyB59@e9#=n75e6VmIKFLzmm6cm~`+nf_dHcwsWmArP93
+uc!+=VPq>Dhph$6l@rCeHG8z#+Jqacvtzz|H}rbpdGB_)#nlJFF-B5nGB;v2q9Al);q(MlLMX7MrL`y
+feOpPi8d16s!$^Em-7<&n&UF_%aTj4Z-PmMwovFUcF*k9WbrCJD+9fLT1H^d_F*SfHtgfTZOMtSzUJY
+%;aO?@!)=l`T6IJeZ?G@BLl|MD@Y#<;|YhG68u=$MtwQquCoD5rDJJ%U_1<mV4`~#G6v&gDi}F<9p2C
+LcMM@)eKf<2Tg486rIm@U_~RPWs%Lf~mR1Q;`P-<XhIqv?XQ{GCd1__THx}|VW?_eM55{m}X$+2eH-c
+d2&0ROH#Ib|5X24Z99xE1!JL0i%!p=74fgQ|`*$56Ne#=xAkZZ>idGlDZ0&CZt^HjEHV0iIFV2+ubO#
+bMAL&g-d(FmA;KDr$OVC-vQQ%1+l766>3*@#}9r8(G-Jv%rSylgx0<;wnSOID<3GlNo{xQR_*zm*U64
+kpKiI-uUQxt7=yD5|V_Y-e!qvJT-ZQ*m`cq^fnFd3_<q=b8l%0Bs06XKpDK+c{Q@k!4^y32hA=7yxYE
+H;$NA2aFmazwP=hK<R}`wk+n9wcdca&YSW_>|`VEa~%=0LPh!xgl;Pvz@8CZ;>E;$5Q!CzUomAi6Za3
+Kfh4T!0@XPoFThn$17C)A6!5X^@to@ZL!cVrq&FPmaKC}o%1iLS#+=3(E3HJAY6#ezax;G5B!h7Qs{w
+Fg_vw1&LTA=MY=U5-#0utva72zXhFv8+(3p&Hg?&{*ZK6$Ozq1QGfg!PlnJA$HV=QIC^`tDs*9w3Knq
+owNR7~z7)@U>kBnb|9a0fj%w&y%#ZR`S*0>$Hb2biBXvGef{AO~C{7+)mx2?@kty!9lmZF)5(eh7*O?
+1+WLA+mA+9*`L`#b;mu8$g^-FM`BG4Gf)+8#q0nO`&O+<w?{7A>uTdXsn@XS&1>MO8!P{2uz5}&8SD{
+01e=>4U>;aKoy3YiDA!ute7Rnc*t!4-MqM-SXLtx1)K0?zz(F$HJDZtuQHX>@SA~DFf2|dwZ*(di0YO
+>`(ko2G4?IvzbMSM;$guQnTml7AY(N3bPcf+aZNm2<ZqBMZyTb<MqtbXV@3<u#4f|jI-s%>c{c)f16f
+MPCmYtys%$y{{s3|84LW*gj2L!UAsZKbADDPTnpm+A#fgjnRLiphs364Z#f>L)LMv`tS?dG7lTTxZ*w
+PwH$ad@`987?T68gGM5B9Y#I%B2DKd^Id%ipq){FFIm7cm>Qu&`8#2#nAOVb-xrSsCyN(cYMR%q{ma(
+M=nJRuVpRQCR0i*UQ0<!n|vht+JU=+scAu{6MHI3YR?>XdlKw3RDNcl51jz<|!+{wt~|Q9GcsMJ1%&W
+3}DMH7arJ*5}RxoN-<p5Z2D-@g)I0*<=@18?EWyM!CuUo80&_81q1*Bq6TKO8z2NE%ops=uy`uI+<?$
+VLQuFcT#2w<bx)wyNwEuB_eP*MoE#g_L<l>{)E2@AW|Fv!;Xz^INIQm|4L&;NOeh!WPr2D{^2k^TQtQ
+gRVY<fe#bjs^ZOBeL3oF~MY`_`#O8g^GE+9m<B4m&Bu#r)$rUH0f?nqpQQLaJ<h%H=h!yJ)#4q2A9oo
+v+N2JjE&oSh*9&K+Z8jumo$u%v|i4n_vPs<DoI6BMcNm~QHKl9=FYBrtKp{3@vE71E3aJKT34?dvLu5
+6ceRH?n}nEoGPLE|@cPbcPeGbTLO~g%b$KpD+oASvJXJMmS({L5&8FAwSyza00!YD?h?n78nPETiohS
+ID|CFi#NF+ak&}wPSRF|0gZUF1l$Zv4poH55R%DkwR3ZxMh-#<>%^llR(2k;)LFE6FeV68jm-cnH>j+
+u%tRO>Yi*dw>dwn1Sbsv_$y&hff`??>oygTE?5!jw*zbX9Nj7lp17CxsHwbgg9O;5p!FG~;HjIM@l3S
+J&aM-f9u?zAdvMbbqOcYB7qIV)Rbf~gEjSR99P*+~u*uhM(vME`cE{=9nSr}Twc?+}yUYux%QSp3v<c
+<*^T-<k%9l$%dcp$TsrqiRxtg@r2iog^PgAHql)pnQpl$ms7A}}6@h9YI2<dTD2k4+kc_dXOJhH{1)3
+g`@SWy9H4UQEJQPD8#EV{x%8lDR?D4#&=r3OQ(!YxyV%zFg2Ghmf|wFn5>_q$kFRCpKI`b%T6-BfTNt
+4>+J8fPL9eu3=eLljhvlVUraTFG?>*1~-UB6$GtP&w<5|c*gyR%NzT%HW!i{PIw_cRVY4`uP=rZ!tEf
+1&wNOo7TC&0K8`yMtos1Iwn{W6BoM4CD-gS9NRXv*xWVWUfRENkz;4`D<wX_Nxr1Rlu9xsg+6_rTj|m
+bt@*<{8v_E836`0WCyVgKR-dNnzM1=9<1(2$XavIW_Ye+P%(q_yQR;86LMg$~4binR1lb?-BOho1?hn
+Xg>7cf#GWSHE-yz@}?J%Fs6kCR$r4PDj=uC2t2^E7iND<;R?55g#HwWA^xc~}Epc9F}KBiDnTjsqw^J
+8q0D#iAu%06uz#^ua(6Bj~tsZ!-5q_eb0Wj=L5~{8&|Rz^l5LO%tI9N}@0{X+}I{oC;@JAN+7I+l^Qx
+kv|c;7HoP4r?=pA3}}OBqpNIcOfVB5ZLEZVv+ACbAUr@}3$$rwH8V%xSD(Pr;N(S%Il8PITmS+P@F1K
+EDIM0X)w*bNzrjO9QBz*rr78JN$YJSs*0oKI7Xu=uv|YNzR5~1D7Yb40I&lCtnVna}0Bv~FvC2-ft|#
+s;CBokdnMVwpG_R8$;u;0JZ&R2<{aX&jC|6(yv<L=x#oF;LCa*D8$v5E85UC6CqwjJ^r79=}Sdr9wKm
+(09EJ!y2F!Shn9mH-kQ$w)b2dc=9t0O!Wbcx(Y&VEXQNP&mxIdo1HY%tNOt(og}3;}x`x*i!lwlqkw8
+yQ$ZjjvGMMgqR}W@3%9tKXgyf&)C{O~@Xw`L5ng3L0MqtgBQ6yI%n7!vT}ct;C`oVVNK`(5x%`Iq-gf
+J1SR3XyX9jz_XgJi1c0IZ*{6?vSB1sbgqyK(^P()!2mu2%R!8Y<Kz8R=AZ_#$@9(BNt5t3rB>3ZWQ+2
+t7y^`~wn;7|Uc_%C(wW}w=r$^474b&wP_ssFjm_=26i}sT3_PAn@T)=@K^EU4kIO>JqBhNj$P50i<|&
+vi&#z5((UjhJDgeu-bf{Xk8cP<#7{Z=UR|#iBgD*fygM~K5)G4z-6(~<6P?{}La5#NCRs;kP4znq|1l
+%EcxX50+A8}dq{DviG7g#DX1ye>Seur9BnGd0<4^e}N27ng=$-s~=0!EU3j10uyrfdXb7Fnzmu#fC=B
+@&MAej@~cYlW4neQFv(>;~d>bnUza3I^CI0iT9|ll|V+dswP0O)LVS1ldnSc4&T{g6|Hb`@%XyW*Zt{
+W5pBQ<E_&K7pOFJYw2dY8Ypy26`Hcuq1I)n8yL1F9#tf8CzCf!gY*QSjSDf=h5{0TW{C~MGeRFK9{hu
+FvYDsAV>){Nil+>yVMn8>n*tR$S`C!!cO#(g1pocSj}$S?d#$}?Fc404E|Q6fG57~T3aO_Zs>Cqgu4>
+Up0$I``3xRN;CspfNQ=L<3A{Wc_a6L44l*EGBlud{xJy;1gyJ_%rI54G}dxJI#Y)DlF{V;I=mlA|YR=
+So3vJgQ_Rn^%Pi20QOaiWYN#1^=0u@b@GlHP*(r!1E+N~tDbX9Q9N03HF|54h7wWz>L(J&Oq$oDPSkp
+cr4aHcCQcG&_VG0E&%jn}#7)D9;ctP8}L<bHZgQ+JrViXu1qmZIuyXru8uVGS(CSKEUY#86!}3INg9S
+cXW;}d2JYW&#2cbIFOAtB1BV^=}jIEaN_wZ58M$>Nap*ZPpUu(bCzl-r{Mq%gt%xJPlJ_IlCQ)yiY1#
+OHM7N(R<v`n>!2lh92AmVHQ1&|0-^1uq!eg~6_o-+LI=_t`@e7cC_<2b!(FWX5J_sC1x&(iQ<kt0l7%
+BIBwtn--*GtTDT`g3`s8Llix4~2UdSsBLE5rvN_{5y-~whpR7F<A!A2ELp@vFuBRIzxmFby0-~$$Qod
+mRL)C@`i6d}g}VjvT=sf)=3Znha2DP!?TMc0f&6Uy-l@ydvUh(Cr_ijcfpumob}8dfWvZ2e$a3VHTwt
+yj6P;q+FmXLW4{KP;jd7Ss>nSe4>Vol|y%O8KHQ>M!JMQ|+BNjeijOHW){hB`hXn)??N4Q1Xe(U4A%I
+RBlnmLtqWgp@iqD17AqOM+SLX`49;3Wku<x;%MzhUq%5TkhLbmRLN+T!LezkM}8KYhND7%anVEt+859
+wXCdUU(!m243|0<&PDu!!uMTCh(llpcr2JEfAEs+f7?G#rRvjfKwm-9gm4OhPPh-4hYASAxkVr_trdl
+y%9Ox+BB6c&_P&imEFm>`2RxW`tufi8%<^Z@&7}T<;9#v4Vvzmb>$mK@Cg#8!<2uM#w_wDe{izXRZoK
+KbIQilPwC?2;ageo7$c?VwIG1`i2R8pso!d&R1h-0#bP?KimW3f?#kHLWKo-~uT2b=`zInb~METIE{4
+MH1&No-(5PI({)B}_0gmTIsV<nhh&cJJy{6v=l(j4c6p!47@^iU-LS=u#AdsvlDWsS*%!%RoB_ggRg!
+g-mM@agZk4n3}lhr^&B50=TR%_r>yuDGCs}GeU(w0-lx4Vg65aM0OrijYWZ?zoSAVG6H^DW(dHrcgdf
+v1$f<|#)#kA8N=1Pm27)thV>x4z|cpw>za|7!yG6a!eD11eKRGJ%n%IRN1%$(TA*(2I5cO8Jj<udLK%
+i+C}c^6ezDesU_Y@Ozh&o1v1+#*%*+TKL-hn*bEsYpw4zy~-BxvMyBi3Z0;f(%rbAw|QU?wAKt)LA7X
+@5Z=uOwgXLz8c_XJor#WJ#40F2*VChzL(X#86pIE%Zh;HYL&Ekx|<*kMJ096}7GUh<TMG61rXD`$5OT
+8L_+`RoQWndZ#)1H{#mp1h(>nvV`a<*_o@T5Uc;IT^a_tfyFo$D!>A+SR6T!e+LB*_b6`cl)B)-)u`D
+_`uv}XACnt4y7t`S8^Uau_{=gj3wPM9D@Foz!rr|$|TD~n_)Wxy#w|ys9f1(VA&lZmQ1RkmNtaz26rk
+Zl$0Nn$C2n-q&vXF9qG!_X$2I^p%tl$;3>^!3RFEfDZK*)$)=quI50|wN%}MhPZy(GkS)Y>Ary{UZ4*
+JJ7-a95eYI+a(9|TkWLE?F5HhilL>Y0K`XNM*9CuTaXXA*Lp?G#Ypz2`k7B8^hrt2Z{b+v5^GIWI0O@
+6rAtAIn3FUK>vPdVd|46sL5tg6On#|C*RS;o%aP+kM5_CCPAXg8=V@!&BXFzV<+nV!rS{?^Qm%;*U*-
+7Yt~?aV<8N+jyGY0+g>$#MHWnLH$MQ5q99kjT-UXauNq->o!MHOO&WtY;aNP8-Ko;md9*d^@ppwYo})
+q)^`M)lw;}Z8b4L9}y_Y1Vc}pUCah~uM_RV4>gf#wQQzAiVP3yZV>rODYjbh0~{JFP$``?<iwSJw_*L
+73Pys|DfggT13seCek^MIfP)gVMPLlW{tohi-mJ)&%n8=S6f{3nV(vrQJIJ3_i%B%9ZN3DrJA~S9nrD
+^QQa}5q5C<5*@ar*~@yv+Lq>%hqrB-_r<l#-pL*Qp`iMh>IBw^b$Z#T0s>`;aq%Bq;I9S@{*ZBx&+e-
+AP?l|D9Lz_t$n!=?zT6@^`{r^`igq1pM^O&pjbS%0JYvg(O88&#{;NH&nH3bu|eNHr^u_|akktJwra(
+9%)4MLZ#rv|~0QN?gDuq%iAx){KVAF=#`wQjl>PO_~?OVj_V!&qo!rp9Ika<~uBbLO_ZF64GQr^ION1
+$J90L4>K>FX$1pu7fd>>9GIlj6J>McVQKC(&&Dhvgu08ZdZ#szUD8AOgAzj}V;ykFJ~Rg-)oGKDowU}
+stVsbcr(KO&7KlCf4M-+6>z4YZ&8QJ&v%AQq7%V|SPp-V#8V2{E@uyn7v!J2wblMYj;ChF(KP&pXeF8
+ELk^-u2!|WX;U|@KwZ77ycWrZkeih=a9Rl{h7yvEQi*D5NZrVxm`speso-+oQ{LUQr2E@}U-_(Y3Cby
+bKVw8y|+Y@joi8e;6p*)&EX6;N&uoT70-H>C(s_gV2_t@S^38;obr{56`gmrc!`dNySl!bGEaxRG5IY
+7_-gp}HxH@)DD<iR-j_t5BmG%x2Qr76iqB<=6;9XdSyfaCS%*o1jQ#7FBN5IMovjdooNb8bq5}7M*I4
+p@R=dIuQnn**mq9rinuct3<-0&58!wOl|O?PUIREEBUFTzi{jZQjHivKHgQr6=4v|6*~}-`l;-E+ABg
+q>$K3lC~wHNiN?(PuqScYt$pHfa6dAlaa!Bm^EW$anwhype_5gF8@z0_mxEZniUxWLTWxJgw2@|5pn)
+Vb#IxE>@He^5W>HNR3ZWu3C)G%TVajEMV^iRjLpjtHrjf;@$v8|-8~RQdJ+&&;ad2pztWB;);bpf(Ws
+5shdbV>JJS|JJa>KS;L$^hLdz@Lru0_&!Li}jpZBgnOCchLH$j2M~FMYF=$*Qc@Ag$J0pgAXmQfk!0s
+23DpkHHea3w=i2+<vug2;eoi20Pfh&AiwOI^#vLgUZCgS~zXvm10a=tTp&(RYPVn+Y3kn$zlpZY0;P0
+&0;j9eau!B%v73IZ9}mhL72dZ<5(Cd0f{VsnA8vii;A771g*qplBZ}B%?lwju04Pu>6wQQph#qWMKzg
+vZ)vufvFTM&36V#BSXETJ%|L~!wF+Ug?SZ%>)v;UOS_b|>6v{HtG}M$O0FlkG+3nPIj!+ZKd0CXW)X8
+xOdxKmHO&6)VS#(59u~3gEHVQNa{&~?%uWVRYW&$9<Vzr0b4lY|Q&8b=904%uK;hw*(Rff;5lDu;+zy
+>bW4v#NbQnwY&_7AF<j(<^>u#g}lBdxHntXaik^XRH-Fu-<tumP_&Y-2kOfwi1A_9^wOcD7PO5Weg#n
+jNHELdHmFO^`Bl*n&yKK5Y+G60%gsV%ugxmQkp~G`6fBb`&yEn{rLI7F*rSSfSDde$}XU57eh-m)k5>
+4wVx6jD#0+!rjcAs`X+HVr`cMTobWpLO}ruYV0<9&I%kMZC7it;%ZVZG|BFWPk29yN`W<BG&k64-f0y
+Z`3IM6Ou3<T4#-70XYK;7@y?TBQe7LfC%D?xU+u*3umf-pwl-tR?0GfJf!ONgL_(ytK_`2)S%Y+~!wT
+zRh(!CUq{^$pESOeMs;fnt-O4t0D5X%(RRSEeQ!?AW+I%TOvk4x_sdNW~u#pukDr}eoCcfK1ekhhR8e
+1b)Oa1o4XlSgp!h?$Af!Pd|jn&#B;%PH+u$$L@G28wW1Cc@Kx7i#LL#KtX%<>Ae<7`tNXoY(9{DooxY
+<t$;$%uEB-I4`y0DY$&dI6A7kj**PGVDbm`Mv12=hLa(?YaPUE0MhtnhNFAYQ++9Xl$12?2`jqm2L?i
+-MZ@B6cH6ErepGj9)Q9KJH^UA&+{M<n}*rzgsIkD-c5iYm^DjOlVcB|aGsXILhTjVExQ7oi|7nR@{o-
+d!#msT-!e}mI>J+{?29I)VsFZr^no?>NDB~$iPU2j%&<A)h4Ig3Imx%@Ev5~~5AE<hbq%^&G5Ol{3JN
+=TPq#B$8HAe~tZ*#0%X{d;egcwfTqx=7>@@Iv5{$+YCE#GfL}4nSVQ{?15JqseNz6`Q&kGF|e@d6TWQ
+p(ssV<a1+B)-pk6zdgMR1e+?fQ%kVK<~DNr0b!R*!g9lE*RIMpSeZ0eI;=AtC`$_*2e@l$a<`riP<5s
+t(~JI0e2dKkV`(C~<*Cl~bL$dpJ(f$EH(Hv+$B#AsG;{)1%v8rSKzd1rOWgS7x4A@+=-RB-YR#I2vUN
+nsxKwpuL`}<Yg8;Aec5W&;CP+5yFr~dCauZq#Irg$a|p5wpeo|syjs5ZcEP84y3@8KS;_Eb>RW%ro#X
+Wlz5OqcWmmwT|og$BXA*575Xj<havl751Cr69pjX&>S>pzIuuArm}qwTc=(R{nl0!|r!-{`b?n*7N>>
+Uj3ayzwSPaUBx|u@Q?QW7oOaUuw@uN1=k-D4y?HZaC(8sjOi^(!#HnT{J1`AA3$L++(+Qh3vvzPo4Mr
+~%Y#gEX0z*bFQ=(BB9H7;t^evRy;BgJM__zqmT(Wu>Q-SgB-o2>+_p$XDyA(b-2BCVunsZXr}xvaS<m
+T*ndkjQ<BY|_p1)WBx02c@@)MZyg#6=cUu*(M?oTL}$2ESPh(G&ft^u_7B~93gDD9=41wp0P6#^?(a)
+30Pl4A}R>8#l9BkTw83c)pkxN>IpFI1S_g`cR^#OE67$n$z_EaA60JORPxyr>*aJMjn!ih3d?GWp4?k
+Jh=^usH?>`QRD3EWq^i1XGQ7z;EjUcDHm0aZ*>MCT+wGS|PlrS!NVVN#g!InU*->hP&8)|>7#P1IfK!
+IocUsB@NqJFTs*_0z;Nl<JielPWJfg^nLS|t{kj&TerfK9c%U$Mr*wgG2what80Spe$77n}aXIGU?46
+4@#dMBljVp|*GR}I#xxRof@)l*2AZ$}lW@UV+UE?(>f^z_H6E)U;bJqZP&^%ykKvB7-GIy>1tR!H2ph
+m#DO70w8SIAv#h`pg+-xeH5BY4_mD?A(NA?6zm?QQ(>dO9Y*LSqxIp)5C5l@(2%|nsPNo8EcS`KTGec
+@-g6PUB`x+Mo(>X5~oKYJdR;^fJT7y1_Gf{brz_tvxW}wvLxx@7E6C<AI++w=kpF5$vh^x+m-@CNY13
+J2q~*Pqw7buS<82jM{)c^AQSSTg7CbsuSp_oTH%v!=O&cZNV0i|%d(6(N~}gbQQ;!j8^iL=X(XhZg`1
+1gA)C~w4)^Y}tmAr2&NgK-5tQR@l0!+deh^_8u=NzB`(0JKd1hXP8`zdF*lWMbJve2$OIZ}4J&vYW4*
+Q}YcT8qw&ytNGyRE>a#Te{qKUy_I1(>azlQh$AJQh2}Jbh)i0hVjS2)(Kt*=9v{o4GyXrEWt!N4Ht#k
+vkJz!Xf*%dEmvq$l-YrRIpi2t5Oj)Mj+I{;>qt>1~)V*AYkVlo>}Z9VFM6?+To$SN!mRjK#=0JQ~?)S
+wY%2RwQ7nfqs=ss5}w*IiMG$9%NjP&<k>$v1jt6Kg>E=rW2*~FeyesVtSY0PjNzR+TvbuCF_95^+!z)
+zS3pnkD+dlwSkJFHAPiYK-xO+~wyW(#q=QN$D&eQ6f;?hE^tF1v?KVzSgiJID0LlsgG<ooAL&&P)4wb
+udc&uK54Kh|XPn@VCV5N49)3j1KuwHC!q!`-GB|V;v=@w6Ao)V~n7ZC9LA_n^oESK*#`>B0Fdb?ukW(
+UV+-=FwP35HGvwBfqV^S|u3N9`9;7Kv`^TAp<PzHBVwR76Dxs<YVYHylj8he+tzTZ?->rYczYT>*;Ab
+V{$DI`R|}FNIySsSQKMCIQ*)U1fUJgJeMAApp|a(anRXfxsgbw`e|(FALG9r@bu2D<jy`M~&XhaQAST
+x}%MvHnO-3_KCyFmB>{%Pjea83npJ=+nzqQZ0YIX!@+GH;Bc5|`sS)?YXl(tuhFKH5MYr=YBD<wr0Ra
+n1@X`F9Yr)NqGLAWnLpX(hN)6Xv!4!4DZVVfD(3OL<+RiR<Dc~oc*ZWFHDKGh2cu!t59QFsTBzk4lE*
+%CWAWY7OO$y%t|GF`ud7g-f<<{S#w2qwj@gkwg@;np=Fza#GqogNbrvP;(zKjo7mQU{1ccqzUr&C+Y8
+O2g)@jSOJ(Zj7F}8EkYK**JC`?vM(pF!FXFa=AN<s?<5+gk!J`a0YaDZ}K3m7)dLsIOE^q8`V9IZBev
+8lvXf+hlyB?GIZPPKXl)p!I@q5yNO3A_SN#*AV1w|bPvVhL>6<WT^hQX5+B=7|v3+ONa#_=4Zsaq3*e
+r`?WH^I06)T+j5-gKAhL$zvyQ6{9bS=UC^_PsY!&rXnWK;@I%SIC$lxHv9X{g9*CB?sE@Vc*a$6rBW9
+GzE)Cdn@`N7DW#R_;o;3TEmnZO4Non1i%@b#=`}9~dB;3BroEC{LKj2l2<p^M3OH0iw_*YF^t6FmOOv
+3BeMDnV5;W_LB%%;svjx1G11~(Lni12$)4bYr!FmmT#d_IzRn#4aDK-88w?t#;)h<21af0YvnoR~Xvf
+D(&8dB!9^1s{vq<C5ttvos8fpG?>Ja*U+y?8{?Y>^Ifsi)$E9m?~BDkpV84LjwbnT?QK&)NGxIot1+L
+AyiKAPcadMbCsaDZ57ejt3x(tg?T=FaX?1fQPf=p-Y6A-HZ*S74u6Ttg$fxWv^<tn%hHbBfU<2pJ!D`
+6zzY)$rp(>E;?H}Pb-fTPplyO9U^uxT9ok1YnYFb7k-G|-8e4YEQU7M(DU7#wz8+a+B&2NKC8FPmd2d
+nsVz@s9)6R@As_Jsn5hyb?%6NPfmSQJA;1m@zjlJHM-C`<vlNo;sgqNTnctP;NlGw&v7tlhc6OL~G-w
+_~RV$<%d8$&e&T1Uh25ALuPFUM1h@H3jolSm;2fOUIv<%NbP&GU3q_q(es2xi3^JqVH9(&=95-`l!vy
+|&Lx}!E?-9{N^1D7|89OaWYSN9K8;4eP=k1wQpck%xKP)h>@6aWAK2ml;P_EskB%N;%g007?x001KZ0
+03}la4%nWWo~3|axY_OVRB?;bT4OOGBYtUaB^>AWpXZXd6iV(Z`w!@e&??kg%^+r4XIALUexN011TyP
+gh5rF&|;5a)%7mgT_<w?`umn2p_h`o)=&1#eBaD`GoEJi@<aW>!ziKgC>|u~fcoQU{Dt0#Z8n;;*fLG
+6+(<1H#U^Kxj!N@gDkZwcZYYDT+c<@ewDb~@_x!}l?AVei$Y0<<e8S#kV#hF*Wu;{%yfoV3)9#Gje}I
+@~#vbgMW#Kueb-ic&IhC-1YgZ%H)>A8PQ}4rvKS6OZyi1W%G!L<k=Iq!$aen9|HriXcuDr1=*ZvC@qK
+UBIXeQOh%95@L6?*c9X0_iMee567D7m)6)<LDhGLtife@0<<RGW%2p~-SC-GLrLcoI5)XDslg$z@RoQ
+>AmX6RP%XOLx-nAz9Lx9V(><)@;$utXeCX0X&u&YsVxU?Sjp1&q@tLA?dLY8XC~=)x9H@@Q2(_Y#l6g
++wGmQ9T_`hEVYCW^<$d50Bob^niQsCPsr{?3C^A7B=w$l3+?d&LNxk}HKH|B<+!L+2Mma%ucO81>2g6
+)@<?B!`8-M%k9UZL((qz_2PRqWlms!lvO@bBg@a%+n8%-ii29@PXz>`TAC4BuAWdmFol``!XucT5%W*
+WP*>XOcrh_g~%6yVIh<Qom7l{i{mIg}Z?1fbB(E20B>rkM|X)B%>W6oG&qe$Qv+10-_LuK@4-!C9%LG
+MTwq>b;;vz6E#Y~N4Q1<QH99V~s;?a&`R1PT33VFW4QLs@`&sEn~4>Ko@n=p+L6=C;?nx$eEc=@BhcS
+l)VQklg>`5otCWg*7F0v#qc%3lWwL0}OxBL;v=D@Am!&PlQ8JI~<845I=_AIFEfRMYffiPtbVpNrPu{
+@EjrKI%IR~ch;<-^)Y@@DKGoA=NR6U{cP_&W1K7hUDYa`tR~a@!MM?AWJ)-9v>$-2%Y3*PI2c%uf>tY
+uyR%xg9IK*D*Pkdcnh*Z)xC)o3)$YE;wa+dfj;*gy*2fFYwq6za3jCwkD-ksP4k<qVhv2W%TbxA?<KF
+r=v_!SOe(CP0@k)!5&mDsH+@NJ&Sxr}moL6r#DWNx&*!&+$9J+RV)%XWcO9KQH00008031s8R-YF=nH
+m!S0LeH203!eZ0B~t=FJE?LZe(wAFJow7a%5$6FKA_Aa%FdLa&KZ~axQRry<6{d+s4uUuD{|ce-Jq(S
+xKqe)Txt~k|~=LiPA`NJsyom0|G}96$mgmKs5W;_u1V$;6Q?kleVvC+L*xI-u~Wa_uyBr+W)At(fjd4
+U5?L3le>{RySzUCS?yW->fn{SUubom$MZN15_O(MTE#|PW&etkBv2pI_*v%$Z^A{88(pYK7dkAmT!mO
+VIB*okX<Wou_D(<RBwOiRWiwT@kjDDz&)s5!{{>05#M7HBFXAjUD$I3I=txaBOkkICkZVv|Z9sWZsLp
+v;ogN>*28q_?12s$%bxUiFy46PK&pHyu&$G11<7o+TI;Q)ES-T4ICv_7i^E_UvzFL7RRb=XBQ!KL7iV
+FoL@iY(e4e4r@YpqN+E7oA_2ervc6$Yuwbrc&R54j5!q|u+U9Q&796wfyFs7xb>LtGa+UmB;f_mhw6Q
+X6op-s@E7kmjbGCUJ<(mvN|5qg7zkik_K8t*HxQ<jyjpE;5i0NTok09pgQnO~%9%bvih4r&)?U1)Fw)
+g7}B=R<yATrZ*~qHFCFe(5ix3(n!TAlU+df_zMU^&^4S%O|>eGo|Q=t6tGr(8sC4o{&=s3lh5kY@b-2
+%x&QnF)<V;G3;PMBc)3bq5QbEFkQN&-4gy!B+w%|DF+3Yzj_*Gc_ZQ>)$>{D*U0mO)p}HB~-jB~eUJh
+^7&BxoD>$}ka9;dZaF)6c6$(4#{Ai2z-Nw|CvCq_j74D%W=m_%w3JZqRa)QFKt1&D~%<~P|e$<jH?i!
+HT6e^BvErCHHa>pX_<!25Qr3o5mJdvN-2&{MBZuqa5M5}4o)+b`l7NM9sbmiN?IW(rz*HN@WI)030q{
+>gX8CrW+1!;^h~)M)bV8&k=vgM(R~Emg5u#SjZtqtLl#M+%Z2r4j^?tQpvBvdXh5G-TJF<KdkyZup^H
+sM8XGVHeOF(7r3+k@mfrwvxKTvP7S43f&~?eAljyGHuc$#AaBOL6U69n%O*!{{`c~@6&l1%r&`I;PM}
+wK#dFX`9LjnLg~oTB6lG>!N;8we9+TeuPNYlVwaf%Qg-DNaijyYwcKS|%M0mGajF)h!zlw8*sd~4e?{
+<7)X8?rVu$0q>;CuOzy4eQ`$Ocgf5ZmT+4uB%9j8&YHvN;+*RN^8Wj2q)#)_Iif84&}YkwJp{RRJ~6+
+iv7wFpm`<+BV<NCXdSo=Ha(FNkcE6X+d!NDJOfl0zR<U66d^v@nPRBroV`mv!XSZB8il73&NsX*R>Iv
+>?TknM{fQ=hHcVK;dA*J7%DK+6ektoNAakiehnLW*?pcDlW+(+U69C$6voc?jL{s+XdxilP$Gc#wJ9D
+PRX&@f=kpDL$B8wxzH^WRrSqEhw+S)Llg%g!afcSOXnSb^f|^4vp7Pcm<L4(L7}}JcEC(X%tU`7U-gw
+!$z<YXoCJA8wptOKn>i~5wHB#v1uKedNrOYwJ)%HdD&)bO0>v7>&|fWqH1p*_(1ckU>O9p^57{q4%#>
+7>D!(A()vmxKa!tzN8r(3}l@3zMGhAY9>@ky7B;bVABADu;K8s{vO_>17e-4ro+5lyGfBILq&uSIaI&
+m5%Wkl!97{u6D-5U5r*%EKyW=>V1Mx`s(TB;ZMn3E3j<4KIP6C<`o@o}*sGaX8d9&Wu-OGs%%Mu7=mI
+rn5afCJSWL$!iUuL(;~0wlgsJygIb0HGA9v+=vJT|uG*$vlHe7Rv!kP;E6@oB9}dAGu>5tPPcLPPd7k
+u_YLJ$!=k(Fglr0oTe3TDY+;oRWOY3C2G?kd;(h$>^Fp)k-~_>MuJjv$&J{E%JoEL@rm#iC$@(qK(br
+o4B9t~bNoWN!}}G&ilC4?;fs1$FS10-YsXae8pJ5P+O`SRZ#n~19-uv1M=P+o!Jk0}$6I+d7z~sy!Xt
+G^XGiQ*I|-tvQ17TrFn1#qF$BEm7;1kOJy|axJ6Adm5|gRJXX{0@xy4}Yw1+lL@Ab7^H#@A(0qHQrV~
+)JcLT+A0K4J|$uoY7L(yRdL<7v!iWLw@^P=YY4B-mJ5d^EEz=pGA52J#p7;>vgF0F;r4R$xD(&iV}q{
+T8*_)JcE0L5;t0Ms1`{ilrb~W>jhcF$^S17@8q3z}BhlJqk*0;PxWto@Pyf3&9Jl)z6gKz~>l=jNl{f
+?2+0KcT3~2vT<^3nFrJ$v9+D$G(%Bas&d8o%c?e*X3qfg9-deUYJz={iPG3C)l-TxM=O!&Q7gR+OhML
++#{M>%sJvhF*H@o1`oYnJ%uOP4B9}(5UcFw#jc6ostY1N2)KIqIo>iGc+1hrEBvg|?nF`>e1l$>?s7W
+Exy_AEPabu#F;L74;>M4YjglG#HO6}W7roRiB(kx#Rs;wi?1xxKoTPTV#qba8r;WW?&Y0rVtREt+ntq
+L7DkX*{uaTaq6yN!M51j+;TA_g4ZK@>;M?ftz@zi>gMtb&Rt9}6Aqf|xAds_Hg`sYgR-TCNG+U~85F9
+8h2Ap(pfDYc51a{elWylOELQ9CibULJF{cL|84SfB>n|@NQH&0K*2nX4CtE4b;1`YN5zGJV_e?UU1k`
+m_vbR!?d(tdk>1qR+TSt3x^n=&8YhzYXWS}$VVvR7qNH*A%Ciw(u}BA4%O4MiY&BAnIfuD1kmi=S)-4
+!*wFf?Jfp7K<^hCSxL{duK7bk0j2)^VHb5C|V}Q(){!+$_BFOnPA#pcK04bb!_dd_cl~A|EzKs>@ZJS
++~5>v2|(#0E|Vkwovb+3vtm`rkx93n_7g7@*LLednA1Zr8z^C>Ad%K(7T4nKTV&@(g_$a)oW>kD#I24
+2MJ#J1hqK5^-@RYEE;c@~u+buGdkO63|_sm!;fE-8h!^d&M&pb-fpXj?SxT#S`PTDiZvq#_v1QLbExs
+)ME~VLia2b$@twJ{~t>(_d;<D2NW@qy%XR_j6r_!As82=?3{4;YSWiSfvd8;}{hy!)>&X8(2v#Y@11v
+(gC(P-<2vzs!(&%h3C{OYFBLL0igvVTV!x#TNU4Fw9Z{54sP!pfUi1qUPiU+Q=C$oyQ1HYvLLuE+Jqe
+hp~w-E&k0D0YBD=8+ulY=y2psBniTl?wTEg9TSx$M2@>*a?p~*5oLJawq2V@pLQPr1nq3A@BI+uL^L{
+q79t<)Bi=kYr?xqrah|Reat5#&w7-rUA@fXO5{;#B|9(#yGm5pJAWLP5KC{szZE-tN_t)d$tNYx!(h)
+dO*Ek0!`i!dgI(qa;d!h|x0AFvf{GUa?uwZih{a*T{Nw>d+&iC7@_!4-no{F9nTZLx7}eCuC5hgi#`*
+c!^%@zE=u*=b3w(tsw~K-CS=gJd0SDE<KrfT)iL$H(MWF!)Sl0Uf9%<gsuHOp@0X+ti~b%3{)3A#hVu
+09gx%+yV=DmR!B9_*GymGTxDq{o75h4kr{vvhR?><<r8>T;KcQYe$^45nv28@mW_4hmw3)p=9M%Rf}l
+kZGaZsTr8!ttWuqX9-2{Od1cQ;V#*1>5TvOjY>3j^5sr?s$dt~YV%V-CKf0RLhBUon_MW9tl_Xbs{9d
+Rg)^}4GTUlr%L5Rv$TAGK+Er4egSt_YPN{dtw@}PRAPJqIx&{JoP-#vx)Tx4uPS6IUb^n-(ggAh%tX-
+M2@WToz#1HP@f8J>^STXp>P^q3#KY9@z2shVzMo&+x0VG+H&?_xX|UOxUjykKIZAwQg4-(LAo&%C8qq
+bqs%&R<$R9eGP9A1Ctg!e8p1UL1Q%Z$y}j@BEeS;h(*Q_jf~dp8WW=zt(&HmjkPjD`1W#nljr&Jy$JT
+V}K;~_C`hnyWIwXH%o#WOf@P#SCbynCAA1S%}h;}(0^?2xl7)Xq`R4*I^t?Pc@(M6KMZdl-;M9?hZ8p
+I>t7c^eD=S=JAfi%)zk~(mzlo0emA=G`9)ei5tjckzWWG)K8((8N1q-i!z+62J2|hqyna7E-(A*-4xt
+z6nR<ML7K+Em4&~pj>i?)FNc<8A+}_YMxzim~>$>$T%Gi%=k4K8jM_Zd7MRDMK|57PhdsnV<{fx)_gT
+ry_{Zu1G=wDst7?SMsrn;ng*mG_21;j}FEi#tb|BMQ<f-a!FO7rqypW6Qyx~%~yPw)IjmHIE6d`YQsR
+vHU{d*1ft4Jn+G`|^w}AirstEw|BtiCm5uNE1PsJkS#h#XM?(3?~p0@iL}pwq4a!qha8V#+CqT<Nn(Y
+!n!cJh6^-9UZ?dXvk&YCwbfv=M-F4_4yMyMxz^UU@9lAxdc&5Ny|{j_$23oc=*<T&IW`tIe%CU`M%;^
+?6)pA~Ds#-jG|Q5j1u5eyB*Q;cPpjjqa@gDV4wY{2JCwG)?`}qWUvcfK-+pOGm1gO;NhXmay_32(K@>
+aOAE<ejMP!Tqg<qK>nZ~SnW=NBLkJeG5!$nr;;z)Jqx@QsKOgoN}E<yzWphcdo2qw)6_wfWBEbWdTM)
+gv;c(QXSX>45}UZ5k>`6v12z;@l2_Wq})6$W)fRExytGQHJG2OOth(cTBxDCUV{O^A+}+s@ExO0cTYF
+3&Uu1A{G9J7{^MIo<pm%y?FXifU(YI2S+V`x(6mkg@oNg$|l(h|tJ0ttJ}Sfi7RW9NlEAqn<iKUmYx0
+M||kfRXIh5d^+-I5y(e(N#j<KnR6#iim=y+^%*yOoesXyGi7V)eFR<Cq^3I6v$(KH&eSrabJ^w<*s?6
+vI-W0#&4^2Mm>w}{vxJWL93`}0O8TyX6gOxOQVx_Fk@l4TfTFSSfI_hG;AZ5-(@g8g#?cg6>k&@*Mm~
+mkpx;Iw)3+^~FC1e2R}OxtHR341-!~?f_R1!+zU}0zX2#omY1`|%pRT5L)fX&wva_$L_NZ0uwQH`o+;
+o;DiHvy3vqkCQLWfT}@+CUys-c7leF?+Si~u^ZGWN)WV)uni&_K9uxZwvW{sdI5BiEGf%p;Q^j>uyg7
+h08zG)Xn^bgpGK#Bpw1K?ZvR^~V$61Oj4xb)5bt8FzzmoHqHg$=1zK#i@NFh^?Nw(#xKjlxfcf9Ovd<
+lal?4iBdxqs?7vf_nUN$Wf>ZM4K*XZE!}eqOigQ<xB*E@%c$+8J1GjR*nl|G26T2Ngw>jqzR85%oXeW
+P4t$z2Ry~D0`tDb(fvzJj_WB%i-aMe{^=oC;)nEs;Nm2O!liYK}tq8T@D`1$idc%R`x-$$*0jDUMi<}
+A<Ul=wb#eFKkJ6KzY6C3I(n4@w7QS*>k?oi+a?{#6J8;zgf2p+jfCYyO~56K!|UAPLljH4*w;fHuX-I
+>r-jw88IZ0S0SOREJXjr73TP!iqFO~iKb^{9S=X38R428F$nn=yo7(@;<Q*ZwqaG!dO#%LO%#TFMPsO
+-&~CUAlDQX)C$rl)voDH}+dw;uX)IjQx@+*$mXf)$qpF81|c))E`4NL%n_5s3E9I_b6I*;+2#6yR5A#
+R6rBQqY9TS2V@ZX^okrZV=NY@rRP@k$5zgkBWng-<#SDk=<JcM0Ur5XmL{8yTh*;Ml99ra{idp(jng4
+Iy?^U>GtCv1*=VG|cl8ec^&Lw4XK6SI>S$-DQ*EPl`oqho$%!dks9$9Ls;Q(~01J-gd>Gwp+nkf`A?K
+15bKJVdvD)ZMgm|}|NukUk(m^qP=%2nJ7MQy)5B-xje*ArTfTG{XyS>zYr9uDWTXoX97tL<XeY5}gW(
+iK)B-pN~UmjkdqkfNsjk&^(fI2a{%^xSkB{?LQhRP?~{IAo>OQ)ry_uaDFx{D&9v)4;r*h4|~hnMN^F
+_AORcVeEGoU1lnE2ZD4`n@9${?W43t^p?pUW&fJcDkdn**Kk}W1;WaEd->ZQ6euU$lE&^RdS<8tR+jT
+4lqcRIGj}LwJou}8{Lo2@5ht(!r}i(Nhmf|yJ2qv9_fCdo}x9<CfyF@Mf+sLCZWchuCcy38}XNWQeL^
++71xTqv6uEch4v?JmmMIt4$5U5ET!IlaH&&*Bt01@)2)nGu$hJ_r<KL`W~BbhUgekAis+A)>YibGGYq
+U1c|*$#y7hp+zg7L;cf#&0+_%fv755z_7JwUkt6kqHcvE?TUVH&rYnb1PhC3~x)O4%C93ENUe|EZ++8
+ge)v#cWA_0?1z{bOy0=Jmkuwm?Pt@16m^mG;ZJzvHBlW;}K2F^ad}4|>xv>*qbS3^r4`A3nk!L;udC3
+A>|UGidi5x)=GqEOu%SSI6~N|6Ts4L2`RTpAO1rjr8ee)}@>ilnMQ8OdITHir;F2J;}^{Gq5L-S*nN9
+3?J^J!l<|=(LP`K-zUXe%^#=Jw;0d-54iZB|G4i>W^H%%+=bEdhOs-XA@&mX?@A4CiPL8My+osq#a8!
+vX~)Zj?B7sJ0|XQR000O897^_9>m=F$Aus>{#AE;f9smFUaA|NaUv_0~WN&gWV`yP=WMy<OYH4$3a%F
+KYaCw!SUymKfk>%g}QzRfPV8Ja-MMVA`V;7)g%0sU#X-NtL?~BkPn^t3*-JE9AUhb#g_?;|{7qAA{)k
+CW9<;|?B%##r(PDIvcpZ)rO<*TQEc=lcS_Sx4@zkBhteD&@3U;p>=pZxZ-i_gl-U#`pd4>y0gxx2b8U
+*EsJE;sMXpYH$n&F$?~et!G*!`;oRtH=9?^6K{H`tGs3%HMo>@u};xyPL<G?D_lazh2+ozq@`Y_ixJM
+uZ)?$|L*$n{i~~Y*Z<eBH}`k%^W($2`v-l<fy)o~5BvL957$?Z*RRXZA2s4XUh3+BvEF^mOa1a#e)IL
+`#nzfR#IOGR%kt#*wmj#z@5}S+_ty`9y?(u)<m>yp$A_DrKjdTn=KbgYoZpo4r>lp5D?i-a{^jB3ZTX
+_)9X^)F`|`ub$6xO6&gajmy1n`N;p*Wdv-alU`ntTofAjdays_VvkM|$StE;>6aQ*t`{T@Ci;;~%az5
+b{BhwT6M{`Jk9k9_sv?sYy6cl~(%@b>+uIsC(SKbCK=-{+l{KV08kKjhQ=@Zsm%n^)QS+nZO{cki#u)
+%)^}@819N_nG>J8+mcwNcrYIhu7@>u3X>bzjN)sUO&9gZ;F3upRRU}cv*6-e{=Q7{pV`FqvPj!(;v%i
+uExWso?rgz6#V^3UzeLZ4f{*Zeg2UH=7at%VO4&<E+5`szxi-`nIq(H%fCK*`7hu9__93t?$704pFDs
+5<hz%D{$2hyXFC5i*Kdz>^Y&dr@O8<jdbqlK{FpbM1N`af^RNFUdp!B-*|*PL{+YY~=Gn{dp1ycdzWM
+%nc~X9O^8DqquYdgZ$@B8VkI#Sj{>9TTOL=j9{b`Ds%wL=2|Cr)8Ipo{>oXOYMk5@Oh@AsqsIhXf+-r
+())^2^m<uXCASUEd_4%2jTWcOU=1*6{ZJ?k{@Y?DF>s{av|vQ||5`FU#K^ZW23*zJFNV9Odupdzqkr_
+2p%0mOr|>`?uR%f*0BSo0~T|^f$Nn_YarltNZtl{Pa&xvhU$$#}^idmGa|@{N_LVuRQ(k_y3PZ<+F<%
+_{9~Al~48N;r?y8`k96F<4=k2|Mghj0;JrV?-L`hZa<`bxXtHF3-BQ)Ik!hn;M;c}0NdmBt6%Q!Z}0!
+|QFH#st9Ms-*DT4y^}m0(zI&B;zxw$$F?;oHV<YG2=lguv7hnAG*$a*J^vAEi_~Q@TTz!<uc%NH&<Ma
+L@_uZG=ulX$Hi!c6LIldg@ST(=$)<1nU+pr_QYUZE5THd44@$mZTtC15)$D__qU#%LZTYvWY8e{Znf3
+WwSvuNeNej2R&Q~8a3aenwbzc>G~Va=ZBW8@_MW8b^{5x0~bef9R+?!TS!+u6U!FF)77w)WLueteha_
+Sdd|na}xO0PC~gKfk!hN&D&LpMQAv^^<RZ`u(#PFP}gA>c^MQzW?s0=TGu~Ib?i!FkN5&a`nJmCl>$x
+`v(~>)}dVP5uSYY?bDxLJo}$dvqz0S>GJ07<3Hzh-sl&(W1s)@^825@dH(c&{Pg|v-#>kxzx>TbDfPH
+a+iNuave@)&8qLgq@YOEeeB@uVU6z=38GKjcsF!i{d0G3>FT;AfjAq#bLvH;dKiFjs=9fOQXZ~tjnyt
+8W_kP)qaq!*D%M82pwfd!b&CBFv`EK!(yr<dnA9}YvZuo_Hcm6GJu-nR?=DkI(I9K<)w>a{uYhBtnxc
+$iAxz8MYRhr3zRGPe#qn_i|d66Id(vG}RHrXk^qggbSCZE1W(BwczPMWDZcV5OEJVQRAH_c7k<Mw*tc
+4&_Bj(T3$dXAg7A2gMw(P%~n&AiOT(_bsQ<%G5)*C7^<x$;3Y?mRB?Yb{0R>3PU?<kaR&TV+B`W8_+T
+%kDls{~?ZiX5-FB<n7daB=0LniE-ZV>KCSOJf9^WqtguTBcHS;DDtPd9$>_C=W(kO6fAznb4{LW@?4Y
+WnqA|XIrpnO(yv(E#iQl5vSC3NJr_L}Jr^^w=&|UL3!30MXpF}9xIQoPL-0+dX*8W?&`cV7GL2^ROpH
+{GYeqMto6*haW@C?AYmRGlH@Z9Bo$d+eZ0PCqbb113P?!xpoE|}sphwUH+%Rs>b+e#n&@<>6^bC3iJu
+5vcJu5vc*Q)fW^r-Zx^Z-T%JQ;WN9JkT4(K8n+myGU>?v3t^?v3t^?v3t^3wFA7y0NjW)1%it?#gvzX
+J<ptPR~xyPR~KlLC--?Fl}JkhESMm)YxyG9X)dna~?O&{FoOxMPM-R(q`U_fwLS|192^OgAJ~QEx;CK
+!?hB7#@rZq%(cip#q~9=*NX&xV`mHMn1KXVPHzHs<qejVOXl@p3wO4wws1~CE(2RQxbww#x$wE<8xPq
+b$L)-Zd8rAp{ME`mkXNWesDXR~`3Cay*EBpsB0k-k@w=6FGKb8E+4Gy<V|Nz&NLy%O#R7w;(fEDGxaJ
+H7wkww{yE9r~i<;#o3NV^$*RVj_KKSs9{JjiFjy4#hV;@G|R({7_vhz&Sy);nG`NGVWgmW+%X$~Bdg9
+Y?$*L}{5z&@loOsl|#ETz$yEO+kqk~5e?U_0eBavk!=aw(1PDt}>58JGED-1H?ESmFFygPZ=s2q%6^E
+R7o&ZEmK}1Q!IRoqH=zx7<JJA>_z5&ccritOP^yb<<zmQDHQBpWs%DT%d-`znbF*K?d8&FmDCy<rAIb
+M%u}yTg_!J?D52V!x?4I2>h1j&3I;Y@0u#jr6z-G<%}3+zJzW3M)Qk;#mYZ5gWRe!hG~-d2knNXaSea
+WZeUjPR_Mky!FHN#+=&P1Kz_)cjtzBesHY9hCTJ>6qhY2s$#Q{%adU&^E@4KvON><E3L1Cjx;buImZ-
+3t`1ykAE2DFlRYNk<tYv4u@?Ua-7#wS!56GQsM&`y@Jy<uqTCl{J-n4Fvk#m{w(L&+L0UL%fu`Wl=jO
+0wm0rtvZ(mEH6?dS6`;5)26O97L}_2&n4Z$ONVke#^c+!y&o`IpRqZ9Fm$nk8<!^^J#gz&Q`1OIV^XJ
+(WPDr{_Cvzi6u1HMoi#m-%8};Gpt$^sm^ndd@@glDrak)C6#irl(If0EH@88^^+??doZt_HLM<Ha`ZN
+{%BhGL9_8tlb7TNzQ!{;p3(6aj#K2evH=e!bD_WJjz@GnqT>-AkLY+r_wC;*yu|U0j%O6nb37vqEE{@
+)P{%Vu&9dQwctqARn~nw4N4mv%zsXDT1Kn|t80~E6j(hZUj}Bo;G#mE|Ysu#dc@s}~1XMErVsMPLh~{
+TZs$b;q2eeTHl3Pf}TES&y87os86AH&Bt)^Xr)rWReRx5|(#_+!0HqIKn#2Y`w0Xq&DV%PvhHar>**t
+Ie^VAj5g**d1*J3Vl`j^p)y-Y>ia<C+aUalo!e!vQ-E*m1zvsch(p8+F{MV>rNQHuRYEn0wtCyaZa@A
+duP66X)g7HLPxfUS>m2%_>d<O5F$s8Z@-A1kE+SYx9x@F9}ReU~+=VgM>DMhXzY-aLk79Zz7Pmz{cV=
+X1_7#+0X+}gzf#-;3WZL3ve0WGQeekOI$!U^n|Gecnt6u;4#2sfX4uj0UqPD4;hc-xZpCtWq`{7mjP1
+?AQ>>V0Ez(=11JVi44@b=wScJwOf62F_2eb_fu5C~U?pH`0Y(Ch1Q-c05@002NPv+5BN(-8=mAEe?{(
+|ROByCJ8+wA3fTRT&2{001B)~|3kpLqBM&SGnHs5ge+0bL`b?c3F11rRPMVISUkzDSwnLo|H)FcOD9f
+Hm5EJhF>rGvqg<vpc2g+#=*XB}R$*lH{EH8(RwR=L$gW9?c&pcp_gfMNi}0Ez(=F>2ZHNNfAej6(8$f
+n)&50FtnVZ0HFjgH2k2Vg-s7C{~~d7tE&7beci4?aoMEk{{>^BrA}Fv1UV0AX%{)xW{bh2^1?&Q+bdI
+6f01yK(YGfJ0p2XexN6itU$5?$qFPZkR+mQ1a?hCk6F!z9zd}I#R?QFP^_oF7|BcW13iIc1(Fp=66$3
+`PlAUE6f01yK(PWv*mO4Z0E!hT*0%lpNM4d3=m{h%kgPzm0?7&_D`u+##R?QFP^>_)0>ugxD^MgjZS~
+~q171>rWCfB?sBGv7BrA}tn5_yFD`u-=wklk^f{_YFDj2C?q|S5QChG=PDp-NgXG2dgQo%?CBNdEPFj
+Bz?l)g1E(!fXqBMpqSldsR@CHbN8O{W<&lZKvP1l6OVL^OzelP{BBX<(#*kp@N@7-=W3p2<t{13ke?1
+1k-))xZdJG#h$?kp@N@7-?Xnff1-nHuL}^E%v(2<R$rmo?xYcm4?}BV5EVO21XhfX<(#*5eQZ`^Z+9b
+j5ILP+FrMryd*!+6Rb3_(lA>Mj5ILPz(@llL@U{FEilr+2*fEHdVrDE_qt7ZNdqeltTeFFFk20bG%(V
+@NCP7cj5ILPzz8x&HuL}^4UDuizL@Zm238taA&AO`o?xVb5!ie-^aLXfj5ILPz(@llq7HKQ{W#YRUed
+uz2P++{bnHn7Bj{ocI^58?8WK>Gpo5yy6rU5GHN|6MSx^_oUFaq7k_P=~vW_y09gK7^(!odvBSe1La4
+j&>!AJ)q9gK7^(qpgNf|qo#(!ojxD;;~%!AJ)q9gK7^(!mH;KO1_0kq$;W80laHElcCVOFCHTV5NhVj
+y>sMq=OM?ZZ`A;BOQ!%Fw(&Y0$(=t03-d>9~Qi%gOv_eI#}u0lMY5Y80lc7gOLtKIvD9-q=S(TMmiYj
+V5Fb%#e$b~u+qT_K}kcL%Z8p{L>e6GRwFcTM9+=Lw~17CFw((D2P6HAhZek~gOv_eI#@x5%*JS(CTJ>
+6qv<q*X423Dj0`X`c3hYdL#`WoTQ>9rD+7Bnz{mh21B?tXGQh|HBLj>KFfzc%03!p8jIAT0qvyC_Wq_
+3dRtENDfRO=41{fJ&WPp(YMo<rPGtvW$3@|dl$f$LX3ojX9Wq_3dRtEM2y(D)qJ;BHTBLj>KFfzc%03
+!p83@|dl$mqu&7hW>J$^a_^tPJc4p=Lwo$cCO^WPp(YMg|xeU}S)i0Y(NG8KduUlb7TNdV-Y!RtENDf
+RO=41{fJ&1U0)Mq%_!2g9tT<P+B2+fRVAzb%U26KxIQuurjbG1B?tXGQh|LBNL2FFfzdi8c{Zlrqc|X
+y>13CnP6ptl?hfR_GE&Q2}ULunP6mskqJg77(s~3h8|#Kf|0p-Ne1}2Zb-%1&=ago><MZ{T2y+1kqJg
+77@1&Xf{_VECK#DuWP*{od5IakWP+6mRwh`P*pmrHh_SPwCm5MvWP*_iMkW}UU}S=k2}b7TC1&uF309
+C0v!N&UWP*_iMkW}UU<Cax8?FULCK#DuWP*_iM&{-vX7G{;R!}J#iefhO1S9a@Z0HF_CK#DuWP*_iMk
+W}UU}S=kInQ;2mrSrS!O8?H6MHhj$OI!3j7%^x!N>$7q%+b<9W+McG(of1&EX{rtSqpyz{<j&EHJXb$
+O0n^j4Uv+z{mn43ydr<vcL$sXS%_?ZVoS5U}b@o1y&aJ1Qj(KdV&%15)GxW!SovpzrpaE82$nyD64I4
+USbX}Szu*>l?7H7_GEz(LWXSU2}TweSzu&=kp)H;7+GLsfswU&i8;Jvft3YT7Fb!>lLbZ=7+GKh!8aR
+vf{_JA78qGzWPy<dM%Lyf=J1jQRu))UU}a%Xkd(8bCm2~^WPy<dMiv-ZU}S-j1x6MaS@T>sc*z1Q3#=
+@#valx$j4Uv+z{mn43ydr<vcL#=r$)-Dq53uiu%spDx+O2k55_l66Eu~k(R7+YGim6V80kc9+0eu2Ve
+~M1Y+hm+j_0^WPot;N)9LB-bb2~Hot{ol=UPq=r-#!c=n?eTyu>mb&vApELC>IP&@<>6^bC4ddRBT?u
+2tz#=~3xX=~3yid5L8>p5s<}HhMOCHhMOCHhMOCHhMOCHm=p^(dp6Y(dp6Yv3W_Fvm?jt^z8KP^z8KP
+^c?gY^c?gY^c-Ak&|}bJ&|}bJ&|~uw%Wyo$o%Edaob;UZob;UZob;UZob+5=YtduTW6@*LW6@)s>$X_
+8MbAY~u!0QP(YZRBR!7e2$XT5%T1VsTWYIcVw2mg-5h*)av~DLa$vF9<lSu0%(wwDm=B>h0%g%=)(Gu
+dBDffW-jd=+KhfeCPlX@#i4`!!-%Q*R>BKtUG(cvJ073pM80>@XNt$})2hz$&!1*|LxlASFX2v3e4Rc
++^;EaT*hf*Wy+j}x;NWCJH|a02*3j6}S9$>z*UCvKeZvnX$>42hy`=$a9#Xx!u_1)k~zlLqNAv@#=-3
+++l$YDR!i@N_1{iO9^Dr9uc>h$M|?a8v}1o4mv@IgW~2a6E?eS`gTbeN?bY1+MKdDwL+Y%N#dQ+*}#*
+LTVoE&DkazH+hM{qYRfB<Tnk=9Z=dJQZ4XsgG?11aKXg~T(_V+7XHEE2#yqHXTIASc^sUVk&G;mFC(V
+uB(MrGvo+lZ2|^5w69yN!m=g;-R@4#J9LG=*{WNa!lE8pCd%#eb4F};Um7V-ou+=L1pd%3*TBu=9Ln%
+Gt(n4CY5XluxuEq`3DFB5W!->EREhn&3g@CbeABICSET&;S4A*9a3f(r6$=yjR-#U0+&T}4c&P_Q##z
+j$dWPb-@M()*!o*g3?@VG+E;g~^}W0zO!%B61oH}N(v0s*Kqq@#lyd)%O-4la#&-tf@{$72veM}03)S
+tocgs7oOPuyx`rITv|7Jpnge`M0Kh+{jh}wn>h*ksG9n0G+~c&xHjoOKA`CtEe6hab(<19*2<Im0d-%
+Gn|p(D2>pxlTmkcBRiBm;?mIaN<`~Q!iAougPYUtB&IH$46$QP4Y{xog*XXgL)|j6(WY5-CEO0>V6=O
+cr(>_OlL$J!?mSuE5qTVPpXAA`s@4G&^H8=a@57sNM*A|Ing}Kt`#>;TVE?5_(R8Jgw|&T`LiYsz27X
+C>A)2^S!UT+l8#UxjYf8Yfcmz2{5NFa|$)6PDN4IldWSpG#0W*gZ8cn-Q+e${oF)ywiWuOq$HnPh?%Q
+jb74}OdeUf4AnH+f0n7Mz-Z0>?s20z{Y`mXW!PLm71jA{7zZ%*5x8-E&N|xhz}k{nn{3L18VrRbux7H
+FM+uXI6_+9S9^&1~bGJD7Yx(Wn75`sF@Krd7N=T#>v=qmW*@_>ZrljjeLvMT>t~HU@c@zI{+}^P3Dk-
+0BvT$ZlZASb<0h1;mYJH+fOAz=^LEb2kx9Cg1fw5y5d5fA;@QuW6Mc1X6cYKL?EvlzZoZAIC>^bnC(p
+tm~BN;tDv14B*IO?I~!&Q?2Cj{$Snb}+&_*WP)K%Y+~g$=5DhkKgu#W&I7JACyK~mr37G;B%V7-x7jv
+ZQ+P934p~ZI3dd@@g5=Z{3h({)0LQ>0EY(v~|MDE~moj4?9)L1u%l~w435w05^rlLM++~g(JW$Q3oNE
+L?qT!=>s5t@^SG}69KfKX5%jf}4mGn*>A2w@GbU*hDclll@!m8&8x<mnDvRz7`&);O|LklipcHHJKIR
+OZypcQ9axq((Z<wDTC3`VuN{yy<3C6NY^t7Iw@)RQZd&IRF;9U&8Q!ag?EQ3{`~eEbv~pNqtFE0l~uD
+=YDe}XxnTH^Nph}ByNn<s+0J1bnr^jrH~RaJV%fZh-23&q<3fCm{nX$A(vQG4}+`lrp<&EL+~g_4+Tl
+POc^9HKM2lF9g30lD~M7W7hXarZ3s(7U66ILqFt{snO|&u)5e9~Rk?E&T*%rb&yc^`C>+~gWSpFKoyk
+Uos3Cizl06c^xM!}N2xaZ5p>VAmN~IyWnj8rltHE}??fSl4k4oJj_JIf#P07i}8d8aGu5xJOvY-c4Ae
+TKt9-LwuIc0(;N4_p7X&N_qi4kBr*}v$UYid>(yFptb{{e1eeKR%o&k)(jYfWuV6-kBm)HyEoC8}XSk
+1~){kmL+wS;#4vwl$Wbh(xGX6M->ASdgBLK+RZ;ZYO?|QCt{yJv5hVvvlr=q8K#qLRQE~of!JFnIOY1
+CsRe>gDu2%!W5CdHE!|}!ygAaxKS8ZNyR$((1IH+WV-^OR8;4%JtY4sp4!!oQbY<`&N`-?n94pT+s-~
+FD-_s*Lb|9^WM?QG1&!WOrfkZ9@*ogtJ5;};^3OvR6Pn*#$@Fi`krRLvG*L&rvmL1DyQ+1Af#Deu;*3
+;FCA;jzyCr0&S&_Nx6q2712T<jyc!(;sif#5ozDeXu&4Fd(aRtCCK06?viVcRa2kltL9+$dTk~#sS2t
+^g4A~Z+@g*}ucaYr~skyVgP`ooED3X)O5`*~N`xAWZ;O<%b7tbBv2om4a@2Q1c!)@-Ea1HWmi>;mjY3
+N(Ck8g9DEsKy?bx>sV+z-T+dfN@PDXXHelj?!aQwYwFkK|vqsdMB^fRZ#_jEl6@6{hZ(AC4T-MLnDas
+%!H6e%v{j<4cRHUf<wpxEwqTrQcmee6a|0few_20yd<Uq6(UN+a8s}Y!Eov|OmtK+6;h*<Fflluu|tc
+DJMy0+z&Y4sT<Tr}3C0kkP35rUpba&_#1$xgaP;D8;tE*8x-AL-kab4Vz&BajIxS&D@*QwStRE!KjV<
+AdGLbI|5wMZJa4OfFauY)vDH@kp)i9-n8iO*ozi{eagWX#c(aA@0O{dP#LZz14y<oM;d{;~vi${X8EH
+(J;q3Wr5j@z-5L#3YV<0(&bFpX?YgRk!(0}Bhf`i_jCQ0&=4$pIB9Mql&oFPys9g4Syalh8|S?C7RKk
+}xkclmVD9Mb^!!@F+;G6ePgG@QrvARfREb@)8e~SMj)tFR1=-SHz=fBshz$1T0XC_W@3LccZG%Nd*@X
+g|T&ISKTWqC&w8%RXg4!n!pRDLbpTAu44oV1_)26!l_-?hZIn@U@BG<m1f-JB^28LCni*rCvr_WIfWF
+(_S3+L4+R61jU`&bw85~L6n~L=WX?B!se6shKNUw}MY=*3>Yn(k$iLNXb@3rGKALz?fD&!clp<eB<&n
+lsUQ!W}3{PrQN;ya_s0ohScZ|FDEyiGDuuqCN$s?7fGXpSu(zuRu(YVP=To#Mefl;F1@>}p2R4~k}%$
+CkGFgMbYrWTn>KLj&Ow3A+Q-+Yn<fS<8sRsMoI$Ka_laBb=!5F>>lILytm3?`0f(!@Xs#jyJ0v^&(jI
+!@G7Zj2yEu?2gU9mSR)C2d4k4#BEy7^l9wvzDPUw<+BU(?B*+<HAcs0-<d|^2eA)?+Sxeth+GjOa{a$
+ngV?l(y8E0a>ya>Dh{-9M%`-xPQE06Ns<exW;)rR^A`$(Ww9V4gb`FM6lD2|g)a(51kZN*&0Y7()02!
+06dad9aFGry+o33zO^Uu=hC&ud1g75)1z^a#)Tf&7^CI{S>U6P0L|1TVCzlyi#uO?RN*6(gMM4(4R6e
+;Bs@{wVb*N66o9pj=Ox>%qFI<K+b|o$n6WbM&YD4>;n~@4O6y8(Y3EzpW+z?&KhX7~BrS8?`6cGW8Y*
+WZHqQRL$2I_*0jE+&6Qo6*7B_G0aBacxqWQXv$c@*Wl7fuDA;ol6pRFQ2f8_cVUY8evW8@Sev@Z#Fm(
+qu_QR{-c#krk-F#!X%l3jYYD!{x-;pQHti#0?TLPb2k5Kanh>0%_vBrRsfoaEVvv{U$FlYLN=8EDk;C
+5~-{-4Yo%`KLztTSwPk=$ZBF-n0;u9V!tYRZ0|SfUY#<e!cPtA>!i?qXx}T&8k&7X09g+_9lYAnft-n
+V#9AZcTXc(zE4@Tf#ga3U%YsVck13Ke9aB<aFoAYa(2KljhxQMn3CYwk6;kaQcj4cl8shh+x?&kYG9=
+JTcg40eA*n`kiwKUyAc=mI|Ie+0?fY$8FM%Q+qH>in2&c3)5wQ^7ZHuK+J)omo;}mpV@PJI=nU5U@IC
+Zb)s$XY9sk3ntOV$Y`0x)!1S1CBghtd(23@yJ(FIkMH%ZL(fzC+!sQ>$L6(>0YDkd>#BgXd$)rc^W0F
+a^Yt`j{X?opr_dnlyIpI>+tA0ooE3a*M&MIv8e>ipAV<8c;rp)=bsfb)P%axFWD{FnP02_nW-LU=+dh
+RH{u4#mh*)lqs8`AQh_*NwTKyTQ_1$@`MNtg^Gnzciz;gd$lS5Cex=nZyh*utR98%nEBAjE{<8)(qXm
+WB#2BN>{!9{lG3yDyiVO~2?gu$J}MDNuH!uUDQ<zV$EK=5m*V3FaRVqa+dxe2nQ~dT6A#qA8r6b^`fO
+G4sqPXoqlkdSW5My1B{9YoxXL<9zQ%d$oSF>i))8@q7Zk;yh``9XEy=4@M`3ozO&kk#!0x#60aztx=U
+Hgei=-XeD|>#ado?Di#t!<>e~I-a08t_q=q09&tNVp?nRY0<tPlkmHml&JLSZ%ICNC)zs`%VV7oCI<a
+Uoja(ds^Mfh|~q80zpLaSpIAS#xa(fq3JLx>sL<SV*PNfj&6&RF(yL$!$?l>NGZ#N0OahTCxEf(OF7J
++R3Y_do3<GcF!u$BD!Q^jNB3SVd`iLk#&<!i^10c3KAhsIeQ`QHb3nob+3*H5QyhND!(Wy)~Tqam^Cz
+^L=a8qvnb{d@lO2w(&;U&D!caN)zrO)PMygrG#$!e6<l(QPDW}$$#L1%*P$diwZX2jA&yHdgS9g%LNs
+pj5^oBa6bNFpr($f0n#g)40KllK5-}ZlQ*c&LbV%U<EnMN$`+SI(pu<RnkfS6>E>wyZT&!W?3!<jiy|
+e_URcr)zfFF_!JN5~?bKR1cbdCoWsAt*v0|+O&LQskrlp>naOBCmXyidVtEG6;?6_`~c`tiE+g-+e8N
+nyYu$50wmx}41SfgB;xM3D&wR4I-s-pA25l3zAukQyS-scTU8>XJLCh^q=P5eZFY=hR^sbt{gBVuyC4
+WL`;Z+W`X<(OX2RIPoxbPFVh;DOJa#q3D@5*ajO<BNd99A<jZ~!%@PXw)X+z0_8r};ncmBs*}siOlYT
+aN>3@LDFvr%`{86*0=AARGIE(-dgx%ZHWrynjoUf@wqsFv3G83$;h}|6wB2PQC7WX7@Yd&+khhd#Acd
+Rg`HbJFdyTFTXOk~N0JM~;!`P~~uM&J=N*JWQP>M3ewYgP_>kRG9j#D?H?ln~Rk0CWzl({6ghy!7Fbc
+T*OCq-7}7EnM<yJ4#203m&AK4%<D-7CpR?37l9pKjTS<60n2lusBr6m#g17?I9UN>R=mIt~#lzR#mOb
++4u@l5&}x-!Y7<D`bHxqgmm2kYgEA7M5&unF_@S;*`DFWTS2SOWmu9Wk4&;m6JMj3or?$R=N>h)i^HY
+L<Br0QWVcc+`^?@rOIcWqf_^4L#mZ25lpH>R8D~)1X8I@N}vr{#Hrh^D#vx*j`EdFQKPu?UN`Dqi?T8
+@QCfR^lqui6w~3Y=Cr2r7Q3Q+$u`|&RPe#2&!76R%hn%|CLS323AM=+}Vb&!k?tGTaJfakb2Ms3dT><
+gVUt@pqNIDN$cN`nky?WPic2g)M9>Wiif~FE7lpmqsJJoEQm}4U-z$A<zlOpwJ>|=??9v8iYys7Dca_
+B57_@O$?iB_!daUqZcg0-V<yfqNx^lT_)K(fJQl^7SjgqYE^#QP|(=Ao$^0aLAPh?0S91c-k?!vd0KQ
+*wxAx+#`A@0UCdg?gp!9E2W-sZ|-vp@fu_2)qR9Pgg>IDxU`VRGh^F>sg1L<HAcwp#-`OvMr91l~H=1
+(>-0)HJWZ6V+>WWD60vkCA>p6babfAb6oV2r7SFS>AS=RI71An<1gBS=wj7&x{;a)CFHTJOUW<oXiSr
+0+s_E-6bInnl!1pDDWfiZ5)M+RYH`(5QP4u=9$KB=-Jm)UwlF(SnR*IDG%n|aT?~_e4YOtY&?%-Nlqk
+S<g`P%^TBej+MK38jMy|XQjx2NtnQ_VEV6=^LSi_+aBjLBu8k$^12T5$<F7rl;L(EHMN~|h{Q-=OfwI
+vxBy=3e+QsCm7vi-;{S{@9!Y`sj59MsOJo5VqyE_MNbk%qnN5y{G2R0*AOipsw!gDOW=l{H2mbSW|+i
+b_UDV%wog7oK4#LrwU(&ih3#Az@oc3p&Ryt7?|u@FDX?F@|AJLa)2P;|E;9G<Zl9Q}jGlwy@`yx>pm2
+=FJA3#?cVmq=<u>Gb=>8(-l~06KPzGAAXR!+i+!G>N&3RI9*yG+JqFykkYNH9dyqrx{tf#8OWBpayHV
+JrbP2S5BQoL7jjB2@gO^?IDPYQ8C)@8<*FsOD4C;!;y6CN#-nS8;QO_LQ<~nMU+P}HYg-{bNR(I2=Fr
+Lzi>s4_Ko=gRE2CT=avzY5x(mo05^>%yyo57?MO=u|J}0MZJhO4oz)W00N2;rsJ`8*4y$f1FC~8-Mid
+H)IxXDYp^0#=wpq8$%GA=mFXrs0UXVM%u>e|+DF>^^URdbG$Wu|@eYTkxI+%0WFn$n_^R$R7LOcW!$l
+}#15QBb&RWaPY=`28J$&yE8K?lbP5%JGX-YWDzjmpkVGu@onX_f3gM6`{eN<buE%lVJ+QRB^+&)R%B_
+!$ax)Ms%f2E<BZYbU4Jn%J)*&Q9~jyrU9kjmjI}GC++uLPaD*|2H8rN?kJu}NEVpm&bT2YH8BKYOXV-
+n5ltaK$%e92UxEp-9R~z;uLZ~M>e+M@U5RLbDAT|dysH4RYBC53vGAm;O5HgiQb@eLrtSBl@KPD>S4y
+*dpEMdVHB2@0fX-iS%R{KRUDaOl!t{{4RXtggH8|%1y@Z5#QTmMVuT*t1rC&tB)sqB(i>%5SvcB*>*}
+}DRR(gra<|Wj<7WSJ_FKpBdRh*X}TZ&gkg^jBW5J5&L=v6LCw2J7J)TW_Vhi@Jg)V&%#4F(p9cvQuzm
+l~)Jj(OmmXFe(0iukce4})As+s22Kza+sn_qf!(Dos2@f~y1|{=z;e@@q<Pqick8do0D&aeBRgiAY%z
+fkeM?@)GJ^V{S$Pz!iBe3Dl4t)`-x_n!+iUaEN??e?7Fm$_HQ?DDC!f?qlj+i}G)ryR{|Kqlg`>g7?r
+Xh$v+!RGnGXk$mN4@K?GMP9>Nr?Qq(4>Rw&RLkbgI#j?uMar&;PN?7y8yAVvJg`5-!<)RKnuUG{M4a)
+P@9cP8=Ubl)mFcPY&?%Je!yNC2X5j_<tv8`#eXZ0$Or9!Wee69Q4^FZBe4JnpGWz-AkVs)i^l0Qb7cL
+ZlA3(--jD-Tzp`5p1qvFjm^IQRRQfXRiM-bOXF;t&_c?IKCS)W$F1#H5p2jir(=ge|@M39Zic7OH;wH
+|kz(JN7|riGqV15!CG4*yIZ)tT$cYFI1?F%+Xauq^z4X2})Dr*l}S{_iE${ib|EKn=UFT?jju%?LdjS
+DyJbYp_&L~d~=qj<f*Q`N`P|mRO((0t*i{$bqttF6xgIOv>ULnRpmcZASNKE@?JG*QgK}+x`N$_2i3h
+w_!hO73@P1)YPQfTJEZz@^2wWC%+obrJkl<IQt&Tjm89&s->7>vj)nMCfT`?_vV>g*7hAsz>{WRQhgW
+%l-jmam+*8RF8^DzkKgT7Hv$WBN<_PFW0174lSvR1AcobNLP;iQ-6-zQV$1(IGH%<gvJNGelueMadC-
+Wl0tH4I?4ugxguE=Qty)0<5h9C634pM()yH)*tob#K!B<7~RS}pdhT$}vM<lRIr(E>|2R8fzb4A_U>I
+8|k*^-3yf!W(C*dv!^8;&{AK1-!e;hbf(@s)<m!pHvT>&LFI<A&E^}T{?jZ1W$iV-D_#u#}FqGbczMM
+?TTnQb_pIbP3)D>Xy|<|2@}(=+^DASj4xF8x+LRZwongUK@`PAWD9_T^6nC-DaqszhA>SIx`K04*{%}
+0Yv<oWb+1+L0Bo`aAVY%sR8+xkfCH(R({>792NDR9m9SR1fG(r-<=p;_x>rMqjiq`Nfk>5IKpkEkNST
+#eEkm_0t{Qw|pDwTwAV|Yu$hPZ^g1Xl-Ra{0%gWl&wknCvmj=tmQFl8w+QW>ncV3Qf*qa<x9Q=FTzT@
+Mq~y&CE2*oH{~JaVN9RUqh9bs$xyR5K`%XQvAFh97McIZyJSJFgeiy_Tspm6S>4hTd34E;Y7d3b3c>h
+iI<K_&7R*glXV0n)V8Xwz2DtLUpgwMpQu}7N;{ZdI=6C^hK{bQXI)CvN%+rr}^5u0Y}m_`|?-&ey8e7
+6kZ=v3MD=001Tdk8Nq|OqHXb6LN})hC+05VVf)D(!|2X)YB6;lM^+3!F!p<vbo=lfRfKdIOR@!o=DeT
+A&mt|9F&B|n=>=#x_ZxMuMP=V-Nf5H>=Ih$H;+Q%bfRHiuRwc9~ZR^lYW3DI*Ii&B@a~_83C#AjsfGP
+i?+lM-6rg<9VO;eftv2g<xm`XG$j8WNw)?x4CDZON>lvYHKTU|<P3v9$**asM^OSL0__gy=%WEHd}3D
+m^IcU?tL_v(kLX!$qgopvfzIo+v(Sd358qR2<<jDeUi08qYVDQ?jlAoo6A;w7T?s$o+Nyx#Ug>_af%h
+t{o&Z7Q^pdI@pEeIRaxDsc6_tG4q_9FahWAre>UPvWntWKiWau3R5cn+`!Jj~;qeoYEwSG1MaHMNKNq
+kl4n!;w9TXA<6M8mCcSV0;{+T^+)ErYsnxM0JbST!S1D!$A;8~)1FcHN;J!(seVT!SY;L}%vH3lBNEa
+*RfUK_+A=6XGF7H*zvxN@uk(K4CFp&IG9U6oiXNryDP+-6M6rO7A2R88s%RAhB@sgf7Q3rUQ2LD0L(W
+lQ1XXXO8qBVsUMVV6Nu}?oEGURl201aEbrV@$O2oKwsZuIqj|(qh3|GcewGj}3*eWV>(^Vy>%m<D~<q
+%kkAVRHOa}JXr-YjjM<0db09U>1|b5(lCr>oRnK2InR(?>bsfRnq#Wx-Ard5X*!;H<N$s(S^ip?3>z)
+%TF+;1ywnWaMLQml}!9D<P$AQk6!~aV^!O1CPyjDs``>xu=9QsQs%t@}<HH68EknZOWjkyw;VO)wqbH
+rerViG1W*BTPLX0y&5GsMoiUJ9j5FxqH)pL8<+MaE&mYmVJ%bCS2Blcu>>*E?6t>T=*m(PTv-{_r>cr
+pM;67Su=Pt-XL=CbAgd~1D{fM?IQ!?!lTq52_E&`olFoEML?Z02YQ{Y(ktZLbBYj<IRDAl72&`HFs0%
+7`+ja5GCFfgoQVORmo{H~9HFL?`s!d*-nu)pVRfEEr^5|?L)I&stIM0(+Qyyn0f3N^9$FA2`3Y>_9RT
+so9sP-H+yGpkwdD~PKpm7Z@xa01+>t0!BZMC`gEQY@;J&KW#2bJcoBVURQx~iv$FS@Ec0jgd+y5E0RP
+4y)zo06X=8jNlKbUFcB!09Q~rI)4El2L<yE6P<V12<+;D(iW_=p}l??=CnPa;%a_VW+AM>7tF&W)K2Z
+J&HOD4Yj61nXMS0y6pOgO5JNHZN>X~OkP-NNu8WS3#|%8(4k$oDm<u0TgNNJ>$S^7k-eYeCNFV`7Ov_
+g#lq67A?;+Nqsf#F*)A!(ghHk&IgI<#K~%kQnl<0~w@TfsD_AE1T2<dCzC*=fD8$nF2UR*BTkF-iI=%
+5)^hayXe2HbPb6j`{=X{({)AzxMp^^px0Q|5<L$Vj%Z>LUhlq4g=bk0c0NS&kFb@5g2d&SZh0{E)(e$
+~!W(PW(IalDTYg`_IWL%b)^AF99=``1pgE$3~!qxZd1G7>r(B}IBFjFA+-<8%^_O3%u6byYO+YH%r73
+W}sTh4$(mm%3L|?V)m%m>k=5f~ObdQmwk)>Z#IHn4PJD5h2bcH4?2DfQs{dHk>)hxCIBObhYpJNwrXt
+17LP4@N_LB2^M8}T$4udzw75E{A=Mi&h)-lYO)Nm)KvjX;2L5BqNqyGa(>8QvE3vWc3lv%v2&9O;uMg
+d^FVzGJ~hyCc)cTTLGDJ;4V6don>x_Vr70jYaVw6bhRS}r%IBn}$2o4FrF?dK_5M+>xcvM-UIl-5@qY
+kNO9KQH00008031s8R!US6?w>IL00O1}03ZMW0B~t=FJE?LZe(wAFJow7a%5$6FKTaSVPa--WpOTWd6
+k_}kL1RcrQh`{67Y)+XtWuTWRM|aA9#aITQjmGv?L7tWVE_VR;^pz+Ul0Q+Qt6&jX0;Y{DAQQyMiBF(
+Us&$#*O&0@*W=k<~RTRze^l{`0R_z=byFXi?5GMeEwzox66O>yTAG9H<xdIc({D|^!V4uw=dsZ+Pl{e
+m&f;)KfU{(k8j?*>_7kb<Iis&U%mYB?&<RC&Evz{50_W{cRu;(*Oz|w_VL4Gf93x0_lGy{etLMiy!-z
+0;h!9{|Na*bAKt%u`O^aq`}pqd`~Kt8Pw$@eLqG84t9MTxfA#e6^25XH%Xh!%i2w0aFQ3M-e)^@K>W2
+@P-?rafQmt!0#6SJ@PcGY=H<uUVci&%LJiLE+`uoFczmxXv?T4qw?|$xY^SAGR_h}!wT>kX(>2H^>9^
+d@+>G8+Qzg)V)50?+`E?@of;fHr`pWlDKRBs-?dwTiw%eZRaKRrBL-oN|)!#}#P-(P-t_w(h|%eR-Oh
+u4qqefWMMK3rbDef?kFJ@wcB`0n-N_rHvxpWnXjZ)d3f@bL8G`(Ll&AHMkZ^7+I2uJrPUhqn(;{oQ=^
+^LK9^U-cJ%{`l(Q?fZwz%lDU`#@PEG&MS2vLcV?$a=E|jhu78p{pI1Y|NA)i-yfdd_mNBfB>j4}=Occ
+6>2v+tmmh}yKAS&{7yhn`{^jzf&&JcQul(enUV`(TzP>!Z)nR|=*S`Ose!%`l|Iy3p^4-Jb=l2ia|NQ
+3TeuVzJmw*54n?HW}?KhY0i$7ofeS7g@`{J8F|Gxijzta6*`~3Mxk3as@OYrrjzpJO0Z$JFfh4%ye>3
+Grp*k7^5XP<xe&7X(*`)A*LaeV#t<^JW1%Xax{d-2U@?c2|{7niTTeeu<oUmu@bE?+-9{CbJU#r$U%`
+Tt(x@B1NteAln!>xU07AK$$9TmN&P-uGSLo7a~gUjF@|PxGsX$6isFmwk!+^vnO(9KLz?_OE)s{UzrG
+{r%<f`^(#RA3nbP<LR;2POrZIFuVOI=lp)$i~iLoA7AFwf9d7hzrE>G@O6Lr{qg&L==+;@@18!s#Jl$
+&#;^Wq>#x1$l&=4hZr60VeEW4D`Op5l9AE7JkDJPGK6>68`g-{9KR>*E^~<Hpd)cS|{llB@N0p3s@&4
+tHD&B{mU;WG9o<8}tmiqtx+t2U&BDwtd@~593`(^p?^1C;B@4x=$NB{ceAGi3+H(&nc__qDqi@$vNVn
+1H|rO*H8$K}6X{?|u+?Ov|`V_i%7^m6_9{4sxeN%(R8^pf%8`sw9{AM2-=2|sS1US|9lpI*xO<I+#G;
+K$pimlZ!wpI$0{?B`98wUqudbS+E&8N!w>EJ4}Ql_f}9x|RfOOY1*V+}?kNy0wc<khhM@0)6YaF3`93
+^JVC({q-68YJayG`s#Q+^ws|UGW6B{{xbA!<9N`wbv+sSwsAb@+q#|`^hN*o8}vm#{tfzCKmHB++W39
+wYvXv(cZ}bMzN728LEkZ64}Hfd9Oyen<v`!j=VyYxdq4gJefNI-Cg{8O<4@3c@7HgFzI%Uv6ZGBt`6u
+YRkMlv_z1PD8efM4u^Qo^+UC*5Gb3gx_@pFGa^Qo`S<M${0-1W~hejcwc__^z!7yR7y&!@gRR_R>vbH
+CmN`bs~3fxfYB3-pbJTcB^O+yZ@LaTe$stFu7gSdRtz#(FH!H`Zf;zOmjG=o{;4fxfYR7U&!6XMw)4U
+KZ#Z>t%tyu^txa8|z_#zOfz_=-c}HU!ZTSj}`j1u6KpLt<V1oeR1tSLtpgsuh17`H-o;h-d5-v>urU;
+=z3P@8|!a{zSiGQg}$*KEA)-^SfQ_V{T2H5e!L2Od)HT?Zy(2lzP;<K&^Ok1g}$+#EA)-^o30Qz7HGO
+c;aHLB3W;M$rt7J38*3_ECk%{D_Bvxg6et+bX-}QotYfSgkdBIhaSWhj8%ryJCEHkA2{74;UIL|KwIt
+wV8_OesC!2T$plkvNh_Z<wK+3l2B~ZE!h5;(uSQH6V+170gK<PTL2Ci)NItHM0fGB}1+gMo%XxYZnN?
+^-Y#a1Y-5(cGX^(EkC8_O?&FWXpu34qzgf=eLG7Nb6Zm~AYP1jcMlXMxgP2Zho@zX7F(bU^8-+XT>TD
+qN6e8>C4<&8A8QYqq<NaViZJE@%^~Q{X04r{GPf#sHkq=PVE>RCGX2j4eBXIiV^9bYgtoN}x`RT|5Ch
+p*jV3LUju8gg!`tJfXq`dP0*8_Jk%I@Ci*e=o4eNO~6lR_Q9VR`)vY%Vr-}h1d6evCLkz6XMs``3?LM
+t(?V&CPkF#l(=>oXP167nwE@xu5;e^WP}DRHU{M>Na}!|HG!39p(=-4_P167#HGRGXkecQNL~8m33nV
+pvM1@lAFo06i4g)GRZ79G})9wH+HSG=nQ`7DMGPUtZH33ac+XdLvR4{;3Q^9~vP2~VQH7#WDsc9htQ0
+*APK&Ymb4Ma7qY%r>gm7T$;Hdb~9quO1c;-PdvD}zyOKr4e$`=o=;7#N?#!Ki)GK~JUote319&~H=>j
+I)4I`>4|lM(z4L42;@~{@^&3?u&i{N=Hd$Flrwal)<Qd)mflae`SDCyZ+1oqjvqB0Y>fHkPb%eV{S7T
+wTJ!`g3__FGZ?jp4hp5AgF@+8*%^%5LuY}~rn5ll_ym=~sC|57%3##Kj|&7w?c+mG2BY>-mKluN4;>U
+rRUcr~q51%$4wVBKbxhK6Dm_#mVAL@_!(=e(P<?<=hw1~2Iy9AF)G;=L3`QOLixrGI^d~DAb&Ssr8H_
+sgM=Th1=&x8X>d>FDVAP?%TfwMfe0IoS)S(&!qYf1e7<GjH7KT!l0~mE^vcafBlMO~4<MVO`qYlkJ7<
+G(K$Qg_}#z*7~MjfgTFzQe_fKkVxvq0&gvp}i#ATa9C9t1|+RWM-GU2_XY-3OyG7<JcX07l)*xIkdkU
+AqGqbsvn%VAOpXlMP1Q7oB#+z)%WC-L=DjQTM^93`X6x!+=qDO*R;H_xBc1stpB<x~m+(sJr$LFzT-T
+1B|+B{{W-zDwvZ|^{Q)nGO7;@9Vesuz&Pm1s6L=?R3;3JN<JCY2Zqv<QGH+=0}BSm^*9+-ue!)5qx!&
+Yd`|<V<09X#P&&5p+Z9U3Rli-KbbR-9yF%%rFMptP%**WxrQ_?a+Z9U3{&BlP>DWJRS14We4HA@&{o|
+IPbZi&51f^rUxFsm9ItG-E4->ZprDOlNB`Do=P$(T0bW2dW>7Y=m@4hmWjtaVEDD}5rP^z!9GL-83tP
+G{cGzOql-*9CpJ#<<q9p7o)GL#-|3_$5!-?~BR*d1;+C>@_rZZ{|$pHOZ$C>;d4-Jo=Qb#*%#Rnw%i6
+by_vcQUFE=qxJ+#(Oy#RnuV9?POFR7)nn@^#Ofjm@zPvo{Z`PL+Qz=nu-nzrDIjzCMYdBD3p#hcblMe
+(J`P@D{6*PEua}nwSZ<QUA8d*rCJR$l&bh=C{<a`P^z+=p;To#L#fJghSKpj(5*nJ>a;-V*y(NsO7%5
+vfl^g+fzt6O&#gddjB+SYs;_zrl<K?Q0;T%0w?OG2;q7Ep%_^yrQGH+><78AH7{@pnRkJGSWK<s*Z|-
+DNAJ8#QrCIfHGO7>gTjmu5dP&8=IPD6hDu)$HwZX1Xs&ZJNRI|TAsrJGZN>vUkl#Z`%ZYz{(b6lZRo8
+t<l+8n{Ctj!UO%GwLTsH~y`qw@HqbOWQZ<`#^~+StITtZfU7%G$QTsH{y1jLQ1%9gMn-*`L6u+t^ShF
+zPnx>-|&dZPrUB4CtUU2F5q`VAQSXB?|_0mK6h|2>?dj)Q<wAZiC1Z7<DV^GeGIsKPE8hHVS3}qi&;M
+CNSzY3T6VMZUev*7<C)nr3s9>tvU;ojtZK<sM{!*35>dJ>VQD$*kL9x>bB_^P`c?DP&#&)35>dh4hp4
+Xhnc{rTj-!rI(C=|jJk~-W&)!oO%xb4X`;ZWsi=E1VPKpEjGD%Ws|k#nG?ie~q^Sg>CQT(6HI*R@jGD
+%0+zE`DG}&O(q{#-OCQUXNH4S=9VAQ192css<J{UEPk6#lQHH}YO6BsqA9Kfh)>@X7;HK{(ps7dt!Mo
+m@6fYPy{OkmVhbqpx2YLY?e*kL9xYEsdGQPbEzCNOFmAB-k2Y8qe6OkmVBc9;o_nnv$$0;481|G=n8-
+9IpD8lRLVFltgi5R96%DS=UwI)Y%-q!u6;HQmQ)!Kg`1KQL<6#s)^s+StITdD2-526WI<>8za&jGDF6
+fl>3|+yq9=<CD?^M$Os_!KhhF42+t!fWW9(>jjLORk&c(tilDOW>p~=HLK{rs9EIzM$OuTz^GY!5EwO
+&uYM;mYSyL%M$Oukz^Hlj+9oh+)-DA`&Dy2Fs9C!d7&VVwY6hd`@deQgM$Hjp07?fdXE16WpMz#FYHm
+6PlpcBsl#Wm1GZ<CWCkCU68pU8#QKuM;DryyjQANFCFsi6o3`P}ogTbh>YGB4d9s>mfItG-k(gCGa$A
+HqYq0C@ZscL#d>DWJJFsh7#nZc+sKB3HDRMAxjqsp#hK&dV=7*!6P7D~tdF@sTMYz8wJRmNs8gHdH{1
+~VA7XrjQVMH2-^EpF+bN*7HO7`3QL4@NDT7cgoWB%HyhWvts7j9LcxW-w|Q3wZ{kmch9hj9M0X3!rpR
+YzCv2MQ4H1vG!*$YEi*}QHy2{j9SK0pTVeQEcF?TTE<eJ!Kh^{^%;y>#zLOKs3l~BfYQ)Gp;QF}MlD*
+|VAK*i?Wt4_rWuTqhiL|*<YJn^C>fV#FiPg68H|!WX$GU@NSeVYS(0WjN}i+{jFPEn2BYLEn!za9ie@
+lMzM>h7lCfw8qvR}_!6;daW-v<Lq8W^mxo8HX<Sv@QDA{>tFiL)&8H|#lX9lC>;F-ZFS$JkJY8?=t!6
+=z}W-v;wo*9git!D<K<m;KiC>eWZFv?CHFv?aPFscrS&tR0zJ7AREJ7ARUJ7ARkJ7AOzJYbX^JYbY9J
+YbYOJOzxhi3W_4tEGTZvb7X2O1_o?M#;!hz$iIQ3K%78Ndcqe9VuXx%pL`dk~5=#Q8Ho_FiQ4@0!GQ+
+P{1hJ8wwaDH$wrV<W(qOl)MTBjFJ<ffKjpp6fjB-fC5IT;a|WgHT(-0rG|e2qtx&(VAM8htbkGK-WM=
+R-TMMYh5c4528Q7Zj8gZ$fKh7J7cffA`T|C&Szo{?_2vs06}re^ROljuQK4%JMn%<Gpj1T%MyZ`&z$k
+U^3mBzleF3A?tS?}cn)L;YQnS8*QEJ5(FiNfX0!FFxUcjhk)7q)D*|m1Xz|a9ksnK4*C^gy(7^Oyg0i
+)XZd#->{ZTvM~z^FF%^#Vqz6<@$8wc-mHrB-|aqtuEoV3b<%1&mTFzJO6`#TPJ2t@r{)sTE(qD7E4X7
+^PNx0i&8G8;ok2IWVee=D;X5>kAmAW_<yp)SEA0lzQ_8j8bpDfKlqr7cfe_`2t3%H($Ug_2vs0)dmU*
+7^P-?0i)EcFJP3K^#zRD2MP)prS5$JqxOM<0!FEwU%)7}^9vZIc76e)cGWr<rT%^aqtxFoVAQT!2cve
+?Iv6DfKmnuV04QM8ZkHyMs&K)mUA{~(YL^icjN0YI1fygcSimTm1{N?%rhx^Fl1E?xqvR1-z$keH7BE
+U4fd!0`M_>V?<N#Q}sD1oBw}4UV?=N7~K1yl<qtv}$z$kU^7cffQ`vr_r_kIDR)V*K8sAHDb^@@R^1B
+_BTe*vS8qL<t-Fis0b9b@(vFzQ(J5-44C7ATbm7mSieU;(4#5m>;e!?s)~9lO*5M#&PefKjppEMSx@0
+Sg!<2fzYGso}qXQR?q6V3a!V3mA2bEoT9v)QVrgD7E4jFiNfX1&liGdI^+{4P^nN)SF+xsQaYTE*Q`;
+Rt)I0r_#IX1B|+>KESBE>I00rt3JReSppU?N|t~HjFKf_0i)yqSimUt_ZKiq{rv@uQh$E|qtxGDz^MB
+`;{ryh;lF@U_rb~qjJn&X4W-&0z$iHY7BET<fCY?_17HE8<N#Q}C^-NYFiH-9<z&<*2f%VNYLf$CIT^
+L7;lG@W>H|7P!N7R?C!;nw0G5+cn;Zbk$*4^ZfaPS=CI`TBGHR0pU|FG5)38FRreTFrO~VSMnuZlh$0
+w9!g;K5k6-u@CS18rmuTZMBU!hcMze1_jeuYx4{R*Yy6UtJdRGUGC(kf#<l&WAVl&WAVl-j!wr83uFp
+>%8)>lI4JcClWebZi&v6-o~s6iUaRv+ET~?>Z=yj*l$s6-w_qD3p#3Wlc~zZbMlUl#Y)q>&d81&HD9Z
+)TU<rdNOKLvwl4pwW(RZo{ZYmtY1$?ZEDu9C!;ns>(`S}o0|3O$*4`u`t@Ygre^(`p>!;uHACrGKx>B
+5u{_ocrHg(8N*A3LN*A3LN*5giN=GHHHz?gS0Hvc~)*F;=(-?r#vE{5cC{;<_pj7vR+@Mr9eB7W^cYN
+HSRJVNGpj2f!L8)%?n4olgLRlv$9gX&Ng3?{bIF+jNzMhQQ)OlY|Ms4c6uP386HQLvcQJWg=>&d7-Fw
+Sx^YE$QZJsGvB(Y~IH+SF)YPeyHOw68OiYO-f2)y&OMI`*J-hSF8XfYMdRfYQ-uUkj9uU1}{*I_{BJ3
+zUv~B-R3@V;@@!l#YFDEl@i4v9&<y*tXUJrBw%o(mED$fl`&_0;MXt1xi(PU{qE~fl*l{1xBgAzk*Tf
+@2_B#`ui&wrT+d3MyY$hf>AeB5E!NI{R&2@d%uEFH&qZArDpvKMyWTyf>G+tuV9oq?<*LkM*9jzsRh1
+*QEGv&V3b<mD;RYf-$}1vlzQST7^R;03P!0XzJgKeiLYRkdg3b>bsHa8S1?LV@)eA_jrLOoqi&=9RKX
+~9%_|tCu6YHc)HSbQ)KtbjvS5_j=oO4o8@+;2YNJ;$N^SHCMyZWn!6>!SD;TA&c?F}?HLqZly5<#(Qj
+@%bQPZNcK<TQ3Lh0BHDj1~}cm<=>0<U0{THqCoQVYC-QEGu#FiI`(3Pz~~Ucsnotn3O#sV82+sA*JT1
+*4`-XMxgDK^2Tr8@+;2YNJ;$N?r2`MyYFF!6<djD;TA&c?F}?B(GqUn&cIXQj@%bQEHM`Flri~P%0Ru
+o_GbL)Dy2@lzQS7jG8AMW5&Rc4o0a-Uco3e$txJ8CV2&;)FiK9l$zufj8c=lf>E<p6d0whc?F}?HLqa
+QtkMRfW|cM=rM`LvqtsWgVAQNy2cy(zuV9oK?G=ntqrHMrYP44{YTkx0FiM^G3P!2XUco4}(JL6GHhK
+l4)JCshl-lSOj8c=lf>COcS1@WGA6Y6Gr6zd=qtqm?V3eBV6^tq>DKJW1^9n|(YhJ-9b<HanrLK7eqt
+qm?U{ulUgHh_5S1?Ll^9n|(YhJ;qGCqG)FiLIo3PzRj`J;kSWqkgqV3Zo|6^v4&y@F9{v{x`njrIyg7
+41@BRH<Xv2BXx9uV7SBeSlHw&8I6MrRIDef!4z#5UV@0uHcmV^L+$zpYINaUf=u+R4u;y7pz)*w=ZC|
+_;z2=YVrNPz}2Grd#~V?+VXwm)U3XIAGu*f?*hnDXTFcj7}41QEp^`e2sAIg?HQV#Tmf#WwVtj3mwM}
+c1e$dV<rU~sGrf;Mv+kL^0$%E`_Yr8;U6WVfOC9z;0?oQ_@(O^drQS!NIdpa)Z1pt+!yFZI1;kcgLr`
+q>H3Y_#3erbT&8x2}K(_j-f@IHmAV8TDL9Sq#GeNF^nNvNkpqX<$uE3d-J+9!HdhmS&nswjg6+}}PzK
+=k&?wq`WY3jrG5op%ElUGnpo%nPG)>c;wxVE}l0Jhch4zjIYr$F24bqcnvUZ;SYQaSnvG<)R&Z))225
+op%^&{qI%^}YTe-0JlX#8t0%Fs^!?0&>+g2Fg{}7%*2|E#O>rwE%S0)dJF0R|`;AT`gc;^_2(gs;@j~
+SG`VwyXtic-c`>IfLFaLLA>fU2;@DdA%J<#CAb25n>B-ajv2TDd(IiSf_n}cxB`3*7Px|ZjtRH|eU1g
+Vf_=^fxB`B@5&jDLh36Fb^PTTk@XvR;Ujabh*?t89eJA@B2=uM&S1`~wre6U;-<f^|1$}G!6&Uob=vQ
+#ix1J-+V)MP{NVC{{^Eu)yHs5`YJd4dYmm|<(^WEi0wCE#~MhZrJ<OL(EMpld{e*zqAy7eEi7Mt%vN3
+O-@+t3kgvH3o9BwK905gpMMo9{$Nw#DXK(GhO3`CfFSTWr1=9q|^M??y+y#pc`55pc2jesm;UY`!5K5
+f_{9NJqxS=3CMca<TcIbfjEtz9}6s7n|=&N6y9O+tLwqv8frJkaV&6PIW|GY|YgI4mMW{IM`e*;9zsL
+fP=01IMCeuDrjy#J2dZp6*TWYGBk??2))>RH$74>Hs4N<*o!`*$^-{}hdqKX`iLqM9P~~1h`#6}sts_
+k4IfxS_{FB~e?t1jruKhA{KcmJe?tDnCIdi10LCT<KtcjWAJMtML3scYGB7ro01`qlHn{*2QZP2z01{
+#_Hu(S&axgX-0TO~Rw%u7X;NU(>GdQ?Aeg+)ey>EbnyY~%naQ7|&4({F)z`@<?9UR=f-oe4$>m3~2z2
+3pW-Rm73+@Hg2pxJ8~9NfK@!NJ{Y5FFgS2EoDIYY-gVH)#e3cdtrtaQCVN2X}ooMm)y0d!2%VyVof=x
+O<&~gS*!$IJk$849#A-;GnVw5>hg@-D?>f+`X2;!QCqt9NfKf!NJ{Y5FFgS;=sY(s|g(3y>`IC-D?LN
+JiIQzL3te#0y8$59TE~VHn|-VA~QDG9TGA#Hu)VALNhk`8xm48`bgGD!H8eAV8myK=EcW>W>q+%GdB4
+k60$S4!&!mgpqvm1=^2}>5DD=ao4gPS`5ApgF-YLx@f^?u&5m0F2M^~hfrEzwm%zcpiA&(%QFUZ+@Ti
+J<0tb)rCx1ea#wKS)LXyTNYehno#wKq?LYBs+@PvdgjZNtZ327Re;u8|$G&bcYB;;xI5xom=P_~VPM2
+$_pjf6;zO~#FcOpQ&>jf7B*P1cQsRE<qB3JI|qo7@};xf+}790|c1oBSLJ$r_ss9SPAI+ubz}4&Gh!;
+NaaA4i3t)kr1!3-CgtG;N3M34&Gh!;Naag4-Ve-Ne>wt+uf@G9K3rKfP;6h0&wu|RR9j&T`l0Cycr2e
+8=K4-2~it;M5_QClwTtuY-78JQpmtTSvV5nHa2-U67n`SnK%*xH#WIA5)wE1h-&`iU|fBjPY%Y_*ZJg
+NADJ{#F`{#w9E_{4{K>(%`Z}K+jH|En$-z)MLqhaMTz#ES4u;Ga3E>-Y_5QO!v-h6`n!W!l(Cpo2g=X
+(ID>QqzS)o~<jgi3-*XMjUX!dnpq1h{Ug=VkZ6`H+rS7`RiU7=Z@1`)*(SFhy?&0fnDnnf$5am3YY`Q
+%_EujP}2k<71?gOR+JPYy=%RXsTv$*bVxU?hjxog9qhG`o|7eMEV)CkG=r;O^vL$U~42%n>pXBqVc$T
+m%Wx9FZJ@cZFu>;9a4)Ss^rQ$3{Fy$V!lq&k@OKc?p{D{+&~^>;(xC9U*@~LPkf(V2}{f5xTcOA*Cba
+IY@}<2w4geaymkOfP|oqkRc!;sUu_nNQmkPHT)B@Izs*Ygs_fKLq8#{Bh<i8i0g>#48sh~P9)6G>?@z
+4+1Ky}%~}P>><Hb-o)Fp*H^29jgQ0ub6Jk3;4fBNDj!?%uA-E%S_j*EdN8H9O&I!>Sp|*NLc1P%r_Jr
+_`xcSOY(Cq6xL9?&(1kJwA6Eyo8PSEVNGeNW0&IHX~DHAk%T};sIbumM;=ztuLxIG6(o|-3L=aYjm`8
+uB*jLFye<X|7syq_HGBR=wi5ota-7;2;^<axy8**Q5FlV|7TU`(E!0?nSC0?lGKLOnt^p(mtzgc|G#u
+^yogdqS>9A88taX3sk~IC;f^gOe)(9GqMU;Nav+00$?pIB-y{_k?_pQ13k<;3FolN^o#;MS+8pD+(N(
+Tv6cQ<cb0Zr%mr29GqNZ;NavM0|zJ97&th&#=yZze-9$-qmS$wfoAU;;Nax_862GSi5htyG40X=4o==
+}z`^M`;1rs@|A2$jq3a9|%1e-t`Vle{B*cF75!Ev|D1Sjh@JCF}N(Bcehoypp(|ytiG&?^P9Gt`*q<@
+5b2nq2YAtORU{zo6#Gy=`~wg(9yF*}+S9F$!lAp<04r?rBEv*TL9K^YVhVn9L;g@hcCkVPRO2qa`lNJ
+s*S*}1Ra;OyX6aBx=SD8fKOK81udkdRR!Ar7REXm-HCx#((ugR^!UB!Yze4GEDTeMIvG4$AV75DF6VJ
+S3!ogiH?!u^=JWLqaY{ACVq#aMmYbB!h&k5ed;CA#X%NHb@`Qdj|*S>Q_N?b!aa%S04wOwf`U>BxJit
+NC*k}E)pU_LOzRxjF6DgA|WKCkEk-iL4_P7#Ds)W4ia)gV%A?t2nq=~HWHFTLY9q$sF09nBOxm!WZFm
+w3kiiEB&3Ced>jdJA$>&e6daVbBOx#(6o8PB7!vdD<3RInh0v^+W`u@>JR%9HA$>%e!9m$Z5^_WOh!l
+c@v(ucx!Pz?!I5>N^0S9OAE#P4BE&&b}?-Jl(@h$-lmgi9CQ*-ey0S*@L65wF*E&&b}?-Jl(@h$-l7V
+i?^VDX*+4i@hT;9&832M3GSJ2+Upy1~KXwG0jxuS#%G&X|NaktklL;9&7O1qbDYNk|k4nPCzlMWT2ug
+M-Cu85}HL%iy34F$u9EQM{JH!Q!<H4i>LvaIknSgM-Cu5F9L8g9sN1J7<tC(nl7JK(kgH@<sYc)(A9f
+#UWv&k5r97^X}t7^KL!Ry!-6Xtkr~=k+5$EIU`};4uVF)z8xfuM7jGo&@AF3Ya|r5kq|Z#cKaZ0B<%J
+<+(;j>o{AA22OPBj2Z<wL{|_QZ`iS&^gLVWVbR_HuLh48#@sUr>_6Q+&B<vAF@JQGrgyfO1M+ng)edM
+kYXm%<)IB3@p(nrFsA;gcw;$U`gaM3ev5J1vLe0FGF90?E2e)0`CxQNRLA?YK#Mxfa#@ZjL0^^P2pKB
+BXOgG=?Rpt<^0(Cj#QaL{fjgpq{ZP)H*QyP*(A(ns`8!9n|@5J(b>2#Z9Luwx35Bw@!CGD*UYDTI>5;
+`I&=+Czm{lCXygxg>o=*BKnNhYHCgVGk9eNx~i~WRvs}oeLaX{b&Gi&^{}~lZ1U%$R`Q=tPoHV_E{mJ
+B<!<7L`m3Zg^ZF|pC1_j&8|#v&^{}~l!Sd&$SDc?tPoTZ_E{mRB<!<7R7u!pg{+dW&kA8BVV@P!O2R%
+X#Fd17R>&&}`>YUH607SF99%aa2bx`(;Go@E2rY@#)dCK#rUN**ng!tCY8HTlc6lMWB<%7+bV=Cdh3t
+~BrwidFp{SOG^pdd43-KkfdY=ae?fXK2N!aCu1e4HnmJ%XN!oDwLn1u3J5<*Nufh-9rCZR-@gcy@hBu
+he$Nhp&gA;=^Y%94;|684xO$|USDLzYSCSxE_DCZVSzC8U{zU1x|h3A@gaXA<_9A<!i3F+-wB=s8FUk
+tSi+88S`6t}}$1gk5JyH3_@U5Ni_EPt*Vh?L$MbN!W*mWRs|Vs0KJ_XBx6iqWZBK;9w1(9h&tW2;xmb
+u`>zzCZT5<B?O#=l4ueVPD0NqN{BcKJ*g-m<0SN~qJ)r>P=HNB%1QX?Lx?#EKYj=~Ct=4Of=<HE8$!}
+a_<=)+Itf2<2w5lLM-CzEB>c=Fq@9ExI)u2Bu)7a=Cw)ZM2ORW+h>&;^b^s#sB<ui0=1JHAh|rU;0}!
+bvVFw^$Pr}a@LhecU;X(*L3A+T5d=h?|5TZ}QzCmQ4gnfeuKM6lS2<a!`rvV}UB>eOr<e!9}_JaVF@Z
+)}vfD(S*4<b;)5Bxy}O8ALC2tf%y@&_p>;b;CJ1|{ruL=H;$sXqup2|xA+NhlGn7I4shNMxae9|eRkl
+(0h*X((ZbB;ruQ4oT#pgdLIyL<v9b2Z<=*$NeA@CG4U^CQ3X%-v=Cge!ven`22()aPavNKj7f=Gk(Cq
+=ZE}&gU?U-0SBKS^8*e(Kj#M={PjUU(5!D|5swmn_7Cz=!v0JIq=fyMNJt60F%gl{M|}2*k?~FulF~=
+~oS{?m^CN)3!RKcHfrHNv0Rji@y+l$<*n5enl(5qhSt((sCBjm|PD`Yvgq@a%O9?wIk(Uy7S|Ttd?6g
+E;O4w<M$ds_t5}7GsrzJvD!oEtRriA^Fh)oH*7Ll70b}b?}CG1E<a!S~Li0G8Cw-DJWVQ(SAQ^MXtq^
+E?vg@{iHdkc}D5_S?IKqc(uLxM`!%ZCV+u)hu&Dq$BKLR7*oIHahAJ#UCn347j<qY`$wAxI_ca6^(x*
+x`mKm9WDNSt_At=_G`ygdJ{3QwclV5T_FMvms9<^gNw}K$Wnc4T&mY9~vT6!ag))s)T)L2vrID(2%MU
+_MstGCG0~(u1eVVg<zGi?+eK)Vc!>`Rl>e6WUGW-UI<qSyS$LD5_WkZUM1}5LcU7aorQpvusaJ0D{**
+sz(ISckg*bWF(G6n>@`BlO4uWWn3b?22stZZM-YNm;{L3#Vno*m9JC_{Su0`x55iW$ZXcwrgxx-fTM2
+u6khjuDR*gWjK2;)drP=L+$dzWd4>DJpy*&tBX-aZQNL^`m`yh6u+3kbem3Do8YTJYnA9==zX7J=-v;
+PO#D@}1N3E?Zv{vV{TH2Z%LztZggLH<g!{|5mq&Hf)Gur&LB5W&)}-oq<2dk?SB>{_kR>`JK6?0K)yt
+iOd3#L|?^l90sG^yrm@D3)fg5wcjCy+#OQY4#c+jiuRZggBOFuMzTCnw>=mWNCI5A(5piq9q}crP*tQ
+OqOP^5kgs-y+%l7X-Z{Dh-GPZA0d~e*?ojymZo5qgk+YcWR`?zmZoTyglv|kD3*k9mZmJ0gmjjs?3IL
+gmX`cP!3@oQU|@!3KOitebM?8PdGo8FS$hIPTAKY)NNH(yLm{T6+53c?mS*o0f?Ap)R1%U}n%z){YH4
+;uA*-d?`-HHTrU#fLq_s5Vs3gR-G&`M;*V62CLSRd?(+P<!%}ysowlq7PklE6*XYk};%bvlLgUxOz#J
+04&c;wV<e-wgST7G`QBQ!rh;t`ttjK>+8{gB5Qn*Ef=8Jhi=#~GSk2{Sai5@u)?zmVY4?3hA?OCRx(q
+1o%bK(kkOfo8An0?l6C1)9CO3p9Im7ijicJ~`NKp7)c3?dEwuIoNKV_mhL|=6OFk*zEE`o=daK3xO`p
+E-xgyG`qYI>C)`-LZ(ZzgA1W9%?>W4x-?~_B*eP3n;#eo4%(fCV3%fh7Lr|>-C2lsX-ZH@$aZP=Ya!g
+Fk8B!&X0L8=&<-x-yEHqv5b)CM;6lPnvx5r}FU<}vWV|#xxDfKv?9M{UOS8`kF)z(NE9AU1`>YW3((I
+~2(o3^r3Q;f3jwxilG&`mc_R{Q_LfT8SV+wIE&5kMLy)-+f5ctxj=Vz@#vmdq!4%#t=%$H`z6hdE`T}
+()QX?7MN_NCcbgxr^AXAy#5nten_erfg*A^N4+BZTaiW{(iUUz#03NPlT|1R?&V*%5^Nmu7Dd0$`fGJ
+xG9Q_VyqGrrFzr447tb4?<v?y*)^QY4-LY2Bz8DgB+M<Zx4cCnteM+f@${cAPT10lY=anW={^nV458`
+NP}s1;2;jB*@1&Rm}V~x0%4l{El7lE^Yf#4p?UMUp!xafywI%GjZ~OsUkYMjntdtAg=zMsAQ-0Eg@R<
+5W)}*gVVYei$cAZlp&%Tl*@c31m}Wl-;$hnS{77MFc13}M_JJTFrrG0xh?r(?1~Our-4O_hX?8~-C8p
+UOftZ+PcLZ``nw<{_ifMK}AStHV`GBaHX6FO4Vw#-~2#aa<IUp^j+2??`m}bWU@?x4D3kZy9_7xy8rr
+B43$e3nd0WxEneFX@OY4#N$HKy5DfY_L3UjcGsntcTbj%oH4AUUSlSAgi4W)}gnW13wA2#;xY5g<LLx
+%-d!nC9+3@?)C2{|Jz2?*1b|rn%RT2$|+yKQd&RJNpQcY3_+5MW(qYju@Hdo;Y%3ntS31l4<U4BT1&Y
+yNxKB=I%DKWSV=~2$N~<QzK2LxlfHandUw<@?@HN&>49$ePq+fsaZYfj69j99&|>YOj8d!BTuHO2c3~
+8)6|2`$dhU6IA`R^G<BRa@?@Gi&KY?!O&#ZqJej7Bb4H#_Q^z?YPo}BkoRKHf)N#(plWFQWXXME=b(}
+NuWSaWI8F?~I9o~#QnWheJMxIPlhc_cnrm4f5ktfsC;mydCX{(=x4i2t<96C6-K0gl~n*Bg@aB%e#(Z
+Rv$N1}s+)z3r+2df{74i2irn~^8es-Ke%4ywbOktfrtADs>ks>7R+C)3p7&B&8!>hNad$+YT<0tc(>2
+OO-f7I3h72Ejq~YBTa=ntHVvc`{AC+KfDzrp|0eo=j6`HX~1_sWY3AC)28{1strS$B~gI)6{j%$dl<K
+Iu1BkU1Q+j_WV%$8%F%9Q}gC44-Rg=^5Ed+D-RBCzN+Bh=2Zy}Zobao;O12c4sKqR;Na#}2@Y;vmEhp
+!H3$xFo<VR>oyUwknYQ^Ff`gl{7&y3jRf2<?S0y;Oc~ydgo7W&XxOokNgPYeEI2fKCa4<YO;9z()frH
+`I1P+Gh3mgp37dWV1WJaD$3$Gn;P>(jr$dhT|ogW+wJ^31WGA+FGgM;Cn9~=zt{NP}?e!#(SwSa@+Y5
+@ns)dCKNs|6ekR{}T~Ud!NMcrAm2;k677hSxGUsGep<o=j6uGb2x?si&EdC)3oO%*c~z>P}|l$@CE)d
+B%v3Trg5KvS1`Ma%xt0G9yo>sXLjGC)3oO%*c~z>P}|l$uxB*GxB7bl3_CPWSaVw8F?~I{mP6ynWlba
+MxIPlzcM3Frm0_<ktfsCugu7kY3f&I<jFMkD>L$Bn);O)c`{A?%8Wdjrev6mJej8MWJaD$Q+F~WPo}9
+mnUN>c)Sb-8lWFQsX5`5<btg0OWSY8@8F?~I-N}qRnWpY!MxIPlcQPYSrYYwnBTuF&=OiOfrYYwnBTu
+F&=OiOfrYYwnBTuF&=OiOfrl}K}ktfr3*E2Y{yH>%$-L(o1?ygL5aCc>bgS+bx9Nb-p;Nb460|$3k6g
+arMe!#)q^#cy>t_^T-cWr=!>eXiC$u#w9GxB7bdbJsOGHv%R0S@loCBVVmy979>&TK}WOjC+TMxIPNT
+nXUd;duuK56=!bczAZe!Naoy4j!HhaPaUh0S+F%^5Ed%^$rdmUhm+bvNbaDWZL2R0tb&(dkZ*tcuxQa
+56>w$cz901!NWTMICyxL!NJ2<9vnQp1Av2v*E=|Pc)f#zhu1qeczAV#gLlstIC%GbfrEFiQ*iL^bqWs
+Ny(+=MyH_PRc=x=6gLlt6IC%HGgM)XkN^tP*N&pA%t^{yU-Q<isnWk=XMxIPlH#s9urm35pktfsCP0q
+-ZY3e3t<jFK;M`Yy5H1(G=@?>`Pjx+LPcJ+=k@?>`Pjx+LPc6Ev~@?`qRp^<!!==vZ}W>@bxBTr^m?>
+Hk*W>=>;BTr^mUpOOAW>;T0BTr^mUpOOAW>;T0BTr^mUpOOAW>;T0BTr^mUpOOAW>;T0BTr^mUpOOAX
+1{t)Gc@};XJ|hBJJ2jvB2Q*lKQ|*!W>-HqBTr^mc0@*=%&rb^MxM;B4sS-D%&rb^MxM;Ber`sd%&vZJ
+MxM;Ber`sd%&vZJMxM;Ber`sd%&vZJMxM;Ber`sd%&vZJMxM;Ber`sd%${7CCkOZB%ABCtl{rDPD|3Q
+o*Wm=suEQCcU57I?i>Jtw*^?`ChGtjh49%{?8Jb;(Gc>#EW@vW(%+TyTVTNY!2?d(HClqMjv<3?_dzU
+EC>|LTjvv-LC&92@8&7rC*(A<1vXl~M6pjm%qBTr^m4>}`HW>33+2b#rh<jL&GYiEIGubl;&y>=F8cF
+ix)?3zD0xM$b=$-zFNBcB}Hvupn3;GSLcCkOZJ3O_lxXIJ>i!9BaePY&+c6@GGX&#vc_gL`&8uh8u3U
+7^|4TcO#NS)ti`W`$<gYK3OkYK7)i6;+|xyJ&@G@0k^vy+c-Lc7<1HRy`w6X4jKHGV)~htm;LcOdnY^
+0?p081I?;K<jL&nwrAwY^bwy6ns*-=nhzftnpJhkliAgy&&ZS6)uYeIliAgy&&ZS6)uYeIliAgy&&ZS
+6)uYeIliAgy&&ZSMBi6HG#K)-^ksfeRUHgnYnOzSq$;gx0)yL1sliAhB&&ZS6)yL1sliAhB&&ZSMBR&
+o^>w6O9$?WR&XXMHBk?{>V@?>^(|1<Jrc6I+V@?>^(|1<Jrc6I+V@?`o*Xat&99~qig9|xMXE|4d)EA
+=HKPo|GZ4>)+!DnOphF7H7`p3E-qK}Md;e)GBj2X9^%;NZ>c0vwdDAR|v^m#-irPiDV)?F<h7?~ncuP
+)h>@6aWAK2ml;P_Ew<ob(cQ_007tq001HY003}la4%nWWo~3|axY_OVRB?;bT4XeXklV-a&KZ~axQRr
+l~i4C8aohu=U0rv3rJ*dXjQ4bQLDQUNND-eE~v^AGP|>2)oUZ$n`ry%?=c^tA4K<dpI~Or@tHGYH=CC
+~>J9EkQyP!@gK0XT-gwskLa)>|8%<hlnPygQq!x<$CTEh4O7mSRB_d-tlpz*1PNgF)y+q|5Kd~}9wqy
+$O7dTKqW$!YvV}#1G(lQfX8tw4c?u_040Wr;uJ;XE1!gEgRde8X#QNjkUU5%r*o?87jbw7M~4~mQB5y
+eVT5^5bK?AShWe(0ocw6}6yd1G6y{Wl^+6Jfv6T&j(gC0!E~dh&+mwci?j>>t)BxwgXA!KK17lQV^Xh
+Ok?zO+}f|WI31aKo28437!9CEbyhtWl@JvrE|0sRC~6iJ9&6NUDB8xl+rzGw&-SFt(D9G9?OiiV-k*b
+A?CJcr-ngDdK5xK1NyzYx5N_paP|{hhX}oix~J2Qj2$wTTEYkYnC313+Ynuo!Zhp&8C|sC+-Xiy?`gO
+29zQ^cMxU`pv}URt7nSOO0k!mXw0M{;7Zgt)>1&)M@pSQci&{91EarD$lI2cG5Th$Aw67r?1d~D1e*h
+xxjmD$JV^BXFEvADsrQs~0nC5Y^81<LqIHCD6na|QeM3ge0EDmN~GWo^g0+gkJlR0}Kl{>Wli19iIR5
+@+M6JyL7OKcPgT#;S<M>AALZ}$BHayImqWI@{a4n13m-NE+#HeIls=i9;3XHkdVbx|brH-!<TfDdH>>
+Y*~mcBp5Z52ceB*qb-q?#*@g?M;_xnIiJqM}z6z|9nK6jYeTjNl~^H_GKZ$vSEPX7JZ&Q#J#&85;5M1
++To2j;&3nY#(At;DYC89d_wm3nKWc3hs+UDuESxD{mz;-tUlIHD&=Lb_S{D{Wk26%&lu;*pG2+F$!ap
+Y8;l!`My7;whwuT`y3B^>0<Q&jqoCDF;?Y^HT8>rGrt42MHJT6k@VN@lP^%ri)V0qkAdZc%AnN0VR$D
+(y`~~}?(JK)Q{SF^KzHaufhg-ae9>IO|ANUBZzJBTL=<iC4lF$8t_S~LjUs+98pUqaRuU;ckLT@Uu`7
+e?$xNt&WHU0%qO9KQH00008031s8R;%8m)9Dld0Iz8P0384T0B~t=FJE?LZe(wAFJow7a%5$6FKTdOZ
+ghAqaCz-rZFAd3lK!q=F&BS0>5kT7W`MiI*`!X9C0kira!GRKTrL$0B0&jjiqHX|745Iz0YEgK=^oI^
+Wqo^ZE`$aLGd=zC^wSMUfuB7K|4~03y*fEnZ%z)6PA`tsPjAi+|D;CdKHGVwE^jk+R^~VPDqX6>VxFn
+IQg4gD<jZC1zTe%gSNSZhi&D*&dA6$6%+1-~>6f0Y@;Y}bUuK`PWpSUCs#vHxAk)o1&FX5F-e({-FIJ
+WNTHY6B`^5=X?~1Y;pOsl!XLEJ^*h-XJrDY@Q{?To9TdUo}J*B_<?pr4!IDKCoESKuMnOmvztjfyI*}
+Svluvpb)e!X^P?pAv*+=x<d)AEygmoIP1{7yYrPQzN&g?jf`-xjNl{mxa({JKob$Hr@mGRss|Eb0fR*
+!SwOSgTpOQe`&Jt4_RgM6J@*{0~Lx*54KLeDT-}tygnrPNQ|5m3LL|!&j&8)tjtxnyOdXDl45e@7CAL
+eC8Iv$!FQB%2ZmZ`(~`V9Xxg1C~~n;L>(7SeCyrsRhGN!&EB80vT`HJ?CXBFjl_v^vEEJVMt>L0`)1*
+uQ~FUYT{Oym<$llwgQatouUfIU&iC%b33P@&I9RFcOs%VIv0hG`1UFaxa&r0l?ER%WIQ^i0IXFK*IKB
+Mvy_@Si?XJ4`b&~SCdk4X}a#oe;s(y5eI{|Nx&JSO^6$d|^yg9l2&}e^ra(Q}maiNaS&eef>cW{1ra`
+^tu!MS?({`}q9#nHY}7g^T3xN&C4$>idN6M0uSPtLPC&6ibY`Ue-@$|<;<tK0N*=E6M7a)&6Dx)iy8{
+7o@j7OR`qUbkd$==UmLs8vx<)I*s&>^Ss^=sGDwd?ya{v;B!mw40Q!J}q4cF5L3teBneNFN>m_sGo|e
+Zl=CHaBCx@b@W`@NGtXJ!i|jmQAejQpGYdtc6JtJai{9X``nr3qSmC&8;6XEx?JBc9m3wPoVGhXe%x`
+Jm+4KqN|kv&yG=_~W&g3xRx@XFdfhB&>|U+!uALX1O<6j-RkO@Nsm$(6m&q%a(RtlwV7u<oC0?D~6y>
+AaV{uo%aM4)o{Q2HY8|l-TOZV*8TK%AQcU-2c-Dsk^!}KTr1&991GQTKa?@c=Moz-zW(tTS0JnoNfn(
+YT|J3?RS-1ajy%y;KW{}n%zemmPwF#T8EpIHAy_m^UEDTW|+0_h+FNo?Gk|MkN0wZr{;4g=<Q&Pm{t+
+?Djvr(h+0G%=JIQw%PyP5hwXU<~KFhY-Op0$_9}q=4z=u;|m)N&iU`x)T=t|8obJ&+;8d5{T)R$T9%L
+a3lgD2?QnSS%Nl-fH5$yWB*bDDkVaH3CO6=eI3gEuYLS?%l$~?K8t(gN6qv}XL<)}9~I<k4M9QAcP9u
+Z1{+FJ-KQ{}7#N9qIiwQmPjvy2X?r0<)%d&S{@))ABKH}8YQN%ZIL98q`sWsAvJpx>YzZj1F?_{xuYF
+%3oJ_w<uy0|sLzg<|Q|@bjITIym4bjV}4`-r_u<bE^Jz^D#_BG%@${nhS+Sefg>!>~=!J<){1cd0zia
+*Am=xWLKEc!9bPXIz_vh`<L02}RS02s{kOeNGj@s*5vv0e174}L}<*mcCdQC657`!kIn@fg4_D`p~=Y
+mi_-6V?wWzWI!S>0rI|;B7G9fZ-ZGabKFIfgCWq4d_M$YoOFxKYR#a)Gf%6@^&l+O(<EIRu~a<o%PL^
+;6d;+-?Hd4=rS-f%v;Du3t34>u%JJsKjBb|EuI4Y1O|h*JVqE!J|~xAEZAg%4Z4?MgU)d#Y0gMK2m|Z
+ufM~J)WOA1k03*9B-0<R6L^uXogNAf2i4ko{U@d_#@kt4(jF=x&hV?&~S<I`}ze=G`eA6~pMf6$VD6L
+RFI-kO1K~*f%F(AhXKVW6i{=V9`RGyRh8a#s-V2Q~(Mwa{Ju}CyOu}}DPB8fMKRAq^YR%>yetAPht+o
+M6Cff4O*A){{v0B}Mx__W-&z77$<5>pIm-})m6Bm#Eq*EKX5Q7VJZN+H%1<F6&!p~qPkBv|pVi#_PT=
+*t|}04*%s32cq*#7KZO0~XG;k0M&GeJ_nMKR)atfU)dg(PzQMPwUsyDCBBJEVvxg4dWR5gD9UJ!9ns2
+LmeuBfx}IsP|vUZ1R;mWhg}#cM!(j_He-Gg!p<f0BfuEzQuJB*Kp-Wduaqy*2=g=6jeOIv6(@Z#n=sZ
+4@N^!5sv0I}Fd2a)A%VrqLISd<Qn5H8jBR`<%xC-%L7BF`lUcut3?LgbWXK3a5wQ@=XdyY1ikkLWCD`
+>@-}B^_#Lpum%(udP?W=8lB(Uh?985!+9D$|Uj}#ge`zB}*h%JHfos23m*0K;UTDw_3Qumn?tiMsvK*
+S+77}#=<X&7aevld)LehaohM15A6kKQIwv3A0a*ZoMCj~R!+z?@|)jWEOch+brGwngk)8a#}j8bQ|5A
+<ZM7`6J(Z3CyGvL$K){z{Dhp*a)+j@c><A9SboGhDn2Su-l11xb<Vix<2DGKPe#VzRV!&%V(^p!As2f
+Mu66Wf5?2<D+Y1Sut6gzL~2et#BeFd{MhxOsMvoXgFo296lSHt!Y3;n7E+SUr;SWMLMP}kR`0B6=?TL
+L$V6JxqV7x58z=%$M8<0W9Iql7THi(3Be7?&<Okvt4Iz$1h$EP9ea*4(p>L5=?0D`YV_?)U#nAa!9S~
+g@Da=Hs7)F!v43a|(4lzQwo$z9cYGY(c`LX+bJg~?HlTky8NeL{MS!5#^#FOnQ&lVa#Qc~=gU0T%r;A
+8@)_Axegj=@S`6=r1wcVUt+W$DKg-OrImjd>}2N&J{Y{;+@nNfIC#YsDe)%t(($v_P+g$YLU3qT&6Qq
+(19!VSUr$$!OQdT*so%9v#SjBl5k6jjQz~v#en)t_&YbKr31T1|(z#rkkF4KjTY!tTG?svtk|kiER)M
+#=lAei4QR@vP5Ec%|fsJEl8g&Kc7l`9VnW1<cD0ceAqr!5uCBuBJpjELgq)XFcx&p%%=!43>cAFLG#I
+P-hD2eJo$Hfl2Cl*V-W0Gx74-R2Nn68S`-X1i$2;lR@O~O0i@{8#$=@Jp`M@Az>SEI6F6u1#0+8%!RV
+7@<XFZM#@~XSP*G+NawFe+F?eP`_0~t7q^fLs*{2cMz@U(lB*gev;~wV;xCl{dd_SOzFmagqh+FjhP|
+-y0BL)mmpY=bPjb_5Zul?X+d}Zzva*)c{fq_HnvtT}g(}L%b^N|o_;j_YrSZB99Td<G_5ol{*5J}AVs
+zzWJ?j8Yap?WMqXlr)EYsD60cYOG`16waLL5u9h%5H=QkfzXY)I3;!FoLV7rv{_6FoB4DtnQ=yh+Q24
+f8z6J0+@_JAl?ZwHX~$W>akQ!KsW=xW+?TeiOj#H?k8eN1ino|<_F7%%zD}}76<Axc5`Q8GIOkS6q&$
+o^iToovz7(T=^!)`k#4`=Cx9j5UfT!^$G&1LwK04w%_Y|vaDMOvsQ~W_P`yZaTh>$gTb<Mu;DJrJy#2
+&+nPNx?jEA)t+;VUGpF0Q@LCMCaKE|I|WspU+h!^F%fg2fYby)czT964v2w}>gZ|MY)%m9X3F-9Ghj6
+Cf@oXBFQea{&Ggp~kdewxp6#0nQlhL@jYzHBnJP}{<|7uKi!Qmge>ZJ9GR&U9mj$dvh=fR6+!!ZSm4U
+;8?<>KXjB{zB{%SfG)tSlfeK8VNOm=|GaD&QXu67|?~%SoD#*7(rRcYtoGo8YYGD=dgU#&?YgTAPoi~
+Vf{-;HOyDid|6N=^UM5VU&nx|Aq~e4BOLoT#C%YuhPZDBe-JzogwFsBSf(&|NB(jHo=56qd4X+Y1dzb
+UY9C`P2N^sp0Dx{B@FX6&<zc0q?&-8&Mh)y9`@-p*k#i>>e@cS1Oe161V1u!5Eb5Gbi~YEedXo8rn~t
+?KPeE^xc)tehg9nBq(2|WrA6s7|nA7-iXSak5u^PO`SekBjA~6B|7VISPu8<b8NJ(C$OWo%f^)VhmAI
+AO!mUK2G1m~bp#wSd26tj8@RItxPpyC7z2ScDVUzU#uBFhXMOA6^p*@Pfwwii3;kl%FRj@&aN&-&QCv
+wXmX=XC2zH?Vkzh!1ZQ$fLwxE;-5yr+FPqFPv2z_KAv7UJqBd{(1u<79ZLeUsUiQ{qgY#^B6PV_&4SV
+2{uARgwIh~_8DKS^lChAKI?O2fu>?-U<<r|L3rcVc+Q$$7JcLdQU;la{D9_TDGY+jYnZqGQfp8vG6DM
+ymK3O4;?K8z3xT>NFm8PvShg}e;9WL`Z-{R@f{%QW#N_|Ug$%%iSU;NBylK#!^p62}nENCXNkjK~Qin
+$U5@~KhbK}DjH^orKA}%pV8~gwGFa^+Fj9{=~!!m@(G%$zd1#*#v$r=ELh-DE(QJ5Ez*n;IXD|~1^KJ
+r3#V)-6K0y^LL?!w?AR9F&WM~yrm2^hq_5SF|K0D!j=BxJ1VMf35J2JZ!rFZKYz691I;{`VgNG8y?X2
+Vy`&lxffau(bd@GPZ?%EqEa4Ni1+i#5w}WtWmTfIT0Yr3ayy=5sW9}TA>`4XhA=tnXx~gl2O+BFCJEm
+jG@JhFOg4su<OGN!kR^F%uu025HbLg1ax3D5`i=W`y#ZoKooML^^K*giOBuo>d3D*Fd7X0lnS{khQde
+u#u_0FO&w~Li1P$|t6@3PJL6ksT@2GmG9i%WjQx6p^*>nw#cEEUSoaMCH}>_X!9;irZv-O0s2K<};w1
+6UW53*Bq_B<*J;T=MlNzKd8Xm!pTDS<^lK3j=K8X@BfsjCYVyrbhal*Ei)-ui6ZzfRmhoT8>4@+45On
+g6Mz7xD--!lXo`J)^IX0qSDpsyHfq;UiLM&LIh3dC&;yTrcE8|RGl{D~j^*!Qy$u3+@YsEoqLT!)#f0
+Yb9GXg_eq7f5MEIwM0O*C98?lmCBh(U%`|YXM-QHSL3+h>pO+nqkI8lnBU~2I57^uqKBNDyh~FE+HWX
+l`x|tQTU#C1Y0%iZCE=OgOU-z61x#>9iQI$L_XBXA*fjF>%cXCg85o(5p=@XOdC?q`0m2^BGEl17Iq{
+ek=RHc@{Mh>`XfgfKxqWfvQWj43|WUj;gI#hiV<RR>?NoH!1+}7rRKr9Pwtg<--bSA;X|XO=4={!;Dc
+>X;#X&EFj#%TJ`jr??iGQ1Bk&u0=0I85fPar(XSv$h*_kcVs!~6v_vtFDvcvABmIteJ`B>%Ei`G}C@8
+3?(j;DtQmq)M8&OfLh)W5XjFV9Xdr++#<`^Aks*X_{J>Dl{NuczlnZ>E>8&yOx%pS^kMuIeaiFTXwb_
+t3S?#go&Mw{EMK2bTxljCiNLKF=0vI?Y#kJ)Q1W*>bU`p8u#$i&fUC+5BmS_osDHr^{)XE#2aXU2~(;
+D!sd3W-r>;iGIvi^_83V@rq4cW!c<GnpU6k`|gdOtMy$#pz~kdT`$V!1-#^oVanX;=*ExJWtI7tn)i;
+@yL*Fy-N4hWQ|g&&2Zpzu_V19TWzXnErfOEKU4YAK(!KuF*`D1vo!jAR5RtFiH=)w|Psd!?_$|6p|I}
+SzID!51g=*ZSt{>}G_-tL4&1;~q*Na8-HrA?nLv8zh)?r$)XkLQr{F=_3#uJeCkf|m(&8uubt%?VA>;
+AiI-Ywj$tD4~^X3ajU<^`?YCV#`|Haaw~t?ovgp7&+;IWN{#t1c*dvglsLyI7_-jgc<2jdqviI-4}_0
+nTR43wPUB9ybU{S92GM)oi(L->Q6@Rv_y-%T~_HdA1E(1fzvBuSL<Mb;`7=%NN}Xb3e9D>V}(FAU|GB
+nwR2E+u;`tA_Bm3@f&s<hMPZSR<Fy|4rtoAW)oN!sT&tqXJ8l7vU&M;HlMVnLUf&BkE(JM)C8@4OLBe
+dzPQcM1Fg(zU!6DrrBycIrEx(~s`{ZIgmpMVcwsse4R~u8goid=Tp)cAwfO1~*3a$UK1~{fw8oYea84
+hmRR_Y`tjzY6`Xy`M-aWf5imHA0@@BXCwxFqAm>-%K61U!IDY!Fo@Ke!dXY0|yi019rRo+}l(MVd<zA
+w8;u)FkArta1*@#lHtnI_j8B)HX1)?;f$^SWh_(&Cqi+RSd=?7b{*@>#2|8!L;?nYz!)MNv9W&a(XhK
+MtW=@{Z;`+~$r{a`i`mq=&XP<tD8{)1^y@jo6#4?(%cDNBhTIIWVh#R_1EYli<dFp!NQhg}eCU*v>=7
+jZsIgo)3#h)^05p&7aJrvE10Hw%aZEhi1iI>+#*N$Zm#|F(@$<5a$XVoJa{j%>A(&5hXml)3Doypc>K
+}oq1hm>8C9k4;AO*s0{vM?vFwDTz%~R3W~W3J7g?$?cW3EI;NXut73g~JDsO>Iu!BiqF4@I>Iiepy`c
+sQws1Ii<}LDhle)tWi)E44FFX$JUWxwa^@biF9KkkhmM&-O<`w*E5aS57Ru4t_sp{CLeN#Oq?>H8M9b
+2eA^k5xCJeQ%3uJ+U)_+CN3QRnHqrlWwa>`h1OUF)&-9r8`@H)%@Vl?c!C=C+L5<BOk9E?8^4JJK?5G
+Ve*v>e`Xz?%qDl8<?tdLW4HfGfY?MU6VrJT)aLxzMMK;zUl1#H%GZnMEyux;)-G0ruv8Rhx5mM`NbAu
+yGy%&fMAdk!bj)t0l<sgF<kQxH}tJyqv=0x`UuC|H}x&eUgYH_HJy{F07O@)z;5*Gw_5%22b}D_MZbP
+`yx0C)716IpQRw>dA>&f0J%-nhT~wu6{q4W@(vJ_GBz-*ihwr|#<{O$U3k4{qu^-!bxM}D+=4uLEjsI
+W*I?4&4BD&`iUHh9<u76q0g|qe57hGW?v#DB*%NyfSQs;|M)grVGlb^Ry8=8QfQ0@*FHz|Dd{_y8_zd
+eWlH>QFB=}`~TgJ6mrA3Y@nvZa$PL?4f?wEt6~?A#O+mOGD0EZe7J`9MDv%YOw>O9KQH00008031s8R
+&z>e++Q640CJcC04V?f0B~t=FJE?LZe(wAFJow7a%5$6FKl6MXJU11XJK+_VQy`2WMynFaCz-r>6#ox
+cKxrXC<}W48<@(hrK@Diwj>w^TgzAi<3)D6q%K4at*&-=2_(z-6CjphFgwFK4C~CmVD^2R@9QVXnn%!
++I3p@f#;vFfJ8x%1Wp;Jy59lZ=DsE)t$y4Xvh`eKCc(%4aSifQU?*7`!aN~y4clI_``lA~*Pl^BA?2p
+zrhNt=)wZYl-;l`+TVz72*wSVx!sDCK_=M(+Wk>N^zb<duwYK?uhpA0t#qru(%_;2C9+Tp=n{nZQc{|
+EbOx2>(>Z}ok(qx~~I*>2Cl+YaA+;P@>EjxHZQaP;QoBgbyM>2Pg-?c$zV{HGmvd9hZzs&;k%Y6$=gt
+~1eQYhSHCK~J9Vt>}Mf1j#={PZBuP@KXfV-9%55-WwWzhO}PN@Ux_KQ^U_`xJCN@1!+w>d7i*^4ZlD-
+>1y~zG7>Vtmq;gV4ZloUcQpJ8fl2FMl1|7BzDin?0se}>WPq<}I3!>BI%!R&>J1Vl`N}uRNJuAd5tw}
+C+oTgRC%+~z8TW4pOh)os0+Xxr4q1d`fbSBR^!+~RgiP!Q8YX>wNYGBQzN3#c+|}sEWLoPQ{)F@qX!u
+hy+Zz3h^g-ayNgpi@e?eO7L4Qfmwr>0t=_Aze*90b`{)WI!4S!1}RiodLi>}e{Nf#uR-)nd&LC2Rgsw
+aAUAGuf>y`OZf*Vy<061ToA<I4mlojgcjJ$d7Y2&}Kx_+bK*Q9nXp9r^fYWPp01jvpn_kgt4<%pQRsC
+!OfI9zQ`k(f8e$@LXGWa^<pOw0p0U{}FV2F@=rW`ku^5-nhyJc>~Ty-e~QEywP_y@<!`y<c-$Z$Q!K<
+@&;^>H(-Oj0sA0t^t~A54S1Tofg0ou*dTAf)8q}*AaB41c>~Tw-hd7A25gWwV1v8?Pm?#$Y4QeYkT>9
+I@&@@#lQ+<5@&=lXya5~J4LBQl12)JTutDB{eULZcT;wfS_u>rc+NnFRQ8(`EY}6g5Q#V>0)Q#2#bpt
+l28=V-`jn>(y8*n!2M&H?}8?CcZH(DFi4cMS=zy@^#HmDn4X;3#>XQOVw26Y2As2i|B-T2B})Q!HUsT
+-(4-T207>IQ01H(-Oh0q4=(=pz$#qp?BVfDP(yq*FIqPg6G<XQFO&F-_fJDs=;$rf#4HbwiOF)Q#5Jb
+T{B!y4xppJJH>OUN6qD>o!z3E~Y`<fU~J?9(AL&59;QrZos*y8*nbwU3%)asBW}2s2d|Os2i;_Q8zfr
+gX&JVOz?$yR5t?8rMl5c4%LlVGO6x#>Q1*zEUFt_WK-Qd%fyN5ZlqH;Mq*GmV1v35Wj^XoEE7tj?x@?
+RVPa9;Ji`Q?%#peQ=Q2!qsvDi;qHc@ZZJ}-_h6(!4M%@^9ChAUiyFF4jOLe1<Y}9RWyDik6?slW`G<5
+^b<aYa0-A<?*Uzv-#(Mc}qcH?#@c}mKc-l-c)aE{cCPUfh((Mc}qMkhYJZVPn-o@1iYqPi{A&GNdjO!
+6cuJyN#|)$M}1(-V~z>gK3!me<Ww-9Ei;OQNzo)Ge6t;tVl*r*5BKH{fj4T^`kKF-$C8H_tHPscs&1J
+26b0sBQ;_iN)(?r711c4LDPc2~Txf3=?#nLv=eaOm--BJ5k+e?L~Dr6Y3@mxDD#|nWnU;Zl2f8Q{9#{
+CC2R|P091R%af)=>s)C{i|TffrbOdRs@p={Xq+ici7%XAd7vdtX;IzjY07l!wxlWZ8zx|{Y=#No;>!a
+8XG>H1RNXD@brY&{N8PyeKD=%Vb@RM#Cx!`H&(SaeoU5|iLfvS+7?s@?!^B^j5?@$&ni6o1G$qUH1|#
+KA-8`?m0M%`wZk}O+zVoSWZI}>FD=JOtM0J<P>*lF$UYe5Ub@L1p3w2vmcL8Zimg;7uDP5>;7u1a}^i
+g5L@w$O#GE8<cb@NoW8|tnn)J@3CdtJ8^>Mo$Jn`f8+_CeiF3=`ae*}QHZbr)cmq*s`r>rB)Qp3hd-o
+vylpW}|L=qlf*JWj0JK6((S>T!snY((b2pLfwL<F3zx&yWNx)!vt{gh6&)})09pO6Q1g}P`4Aq#7Uac
+qu1@iFaey0y3<v+g}TdPn53(2P|qUorsSz^pVZyZ#esy5wxPOrs$t@@!o=cr^U{>%sW2&zVFEal*UhR
+hLC<-p+hUkl(v%*(ZU=SUtO^rsSJ_!xaxALbLfuX(OxzeI?S#4s?`-1$Dks#9PUcwGT>y1kR5!1}#EI
+(m>2*6%-8||}SKX{Mr3>mV&2GvasJcsE9LP&k`Ya9<40CaYV2Y~i_Gy?DK;1mU#OFqMC#u_GnC#Frr9
+Z>O1$8^A>t=0)cc8i*q$x{J-Q}t4ZfMm_m}F<1VZuvO@~E4arYt>m^Xj?_NK<-L-7csbJ?|{)cA&ah)
+Xh=dV6WmUOn8O~;A~#Eg}MRfGfec!frK(jwk5|x-4@l&qi(>(SD2J%OAe2^aT^z3VUkYWKs}rsh^~u1
+v75IgC*A7?I;WEZ;fwp&k^?x`87635-jf4$aUkJ_Dot4)!^D!N<WaZ9FhT1%ZiM%#x*en`d4@@PUHAO
+GZp=rvLtoQXcRF=@OH*1@x5Y5wQMW~PqxBrqlz_cZw=NDOBv2G}Thf#~!=wP}M(g6wFmaNm^l6yPKTS
+DzuX|_irgT8v>4r%<bz8h{uzzX2ZcCcdqPl%jcc{~p<Zj<ag$b^4Hm}=>VdB&4worEgUbmCtKqrQYMR
+i*Y6Q5~H7u1c$d3IB#8z%Gjx-EtY>s1RZ>IS_1<EJc!iA8k-_OT_0N8L`&>vp5M_3=~Wwk|47iIrK}^
+SaBErgUPMIH7Kf>h?+9EU%kI-9U@3FmYm-0G?NxGTkuQ6%{5t)$Jrr+0toBa{n&kMtEMDvH-6eU+Lov
+lhSX5w@^1PO_}a>Thf&NR5x!+PI{WsLfyPHrG>iF)0FAOftI>%bdjYvFg;Ca@wx%e@l^{vubXF>Skjb
+$^HrE=!-U+ZC3{N_U>_Ud%d;g1aPhk-G4A3G6BpFY+LE(SUN@_*J6(0Nw&ZXO6N~ERQFnQ~Zk}P{hPr
+i{lH8F+9s0^s-A<^Rr@8?b|AI3Mbz^|l8{sE^ir7tA8tP`L?s8D~PBlylpzfAF!-U*=B|ERXJgVD?*N
+wij876>pscs8(SE}2`TXJ~R%`!}Q)D1X?>c;4*Ltks#F-&}>DO<X(o7`h1dpD&M>Mp?Rc4C-Vs2gzgs
+s+_ac?^^JznhY$y1f}D4ye2Is+(t+pc5~uTUVHno5{QCUNGuL>x#M+ykn_*{;Jyrb@M7r(hU=!#l9uS
+Cv{_Zi$dM{EjjeASwQNx7$#1<ZXR_5E}pspSJW;4lqgM!#ZVb0J41D&^&B_Cw{>wKy*-@0YQaf`i6u>
+m*13uU(Mc}VZ8^ilXK|pVuG>-^XsIyaQMb?HK)@cT8|d7q8))ILT3{I_>8cxT=SAIsOH18=i!TmrYp<
+K!2i}jLvZ!ueg$a+kEvnlIbvyC8E!1sM-Ig?^g}QgM>b6ifW-3#K3G4VN3w5K9OleA<>h@=tSg4z0m;
+lXG*Uh7Dbh0a{yQL3(B@4bN)$N43d4`Ek>UN^Kd4`FFx_Mi2D(cR)C5NZFS=0?U7j>s^giqg+W1;T!l
+LL1qb)yp>)a|o4Q2QlhW!sN137DcASH84XH;=gi`>?v5FgM^zbWi@+H&dbvB-2}k0UOK>I8%WM;7o57
+wj5ys*kEqJ*^V#)Jk8udGi52$k1$E!2M;vU5hj+?rvMww4cK6Azy@;zHkcc*!Q6m-FgN<n$J}}|C0WD
+UIDN_@x_wf20iwI2?wv>7tb+qB)NK*ntTSINwSnoPn|Jz@MRc=HpGv20%Mm8&ehG)VK~uR74n#SMj~B
+vQsGE2C6b9&ny7gX4vRJnvx_Nd<#oT3PZd|m5X6|&m1YKlvx>=&z!rUy;ZDDSn=yt%|>2`?&(akFjv@
+kc|Y@!>j4dw<HmzKFhounko(w);?iS8Xp-Md0`r&BlY@F^EBTA07+PES&L6W!^DPXWy)y1|S-UbKMLJ
+MGBVKwI5p{Z)QRMcs=|-Jsn}eu+hOv#8r*b)%2@scw$d%{r}{qq;3gN*;CdR5$P3Kqso(r`4?wFd++V
+8z;V2%v~{eIhotCAID#k(y||im87(6rJQ?`(i?O0{F3q{DS7*Gd@^^ashcdR$}g#?dts>CBD&M5o9CC
+XtZs{60@%YVa#%&(tojmfMcqzz!Sj-oJimnZo&~^O{E}8e-DK@len~~$yOX*-mIivPFIgPbU4UQ0%Th
+Wy@zu#Ia>9hU$s%!AU&3Q<%XXadFt=qpj!)*cY=Za6+`FQ_q$=tzBXgJDFLCm6GdF&T-bqQ8L*<uLqI
++Se+p-@gJxS@JzJz!5RC<z<w+Y@t-Ih1xa7qJNeo6Xk7Fg5`uFLgGVV_A#p4IKuFVU)-TzBt&iDeUf0
+o09=RMf3TvT)SRDh=e-m!xlk=ULq@>PvRuejF!$iG{i?s@utXDV<bxyP<Af)lDvNQHDvSy7N-E<@}P0
+y1f`CB`*zRonOMD?(_{g4pg^=x-F`^0IS<V-RQ)iZnXBY3tqowfnG_z>Mq~_lZv`4)jcQbW*t2>|171
+Yz{H}u9c;)+_qx-moAow$9(6l0Om^yCN^NzMOIFpFl%Bb9`&G=XI&rff$6|H6$WmI)d-W)~EmpU;t(5
+*mw<Swy5#78jrBBiAlex9#CKspLk5hW)t~7U6=AQe0oJFcHnfIZArLQk3&wiXh@5dpRp%UE{buSEcvy
+zm&`VtpON|s%M#vbgF^pm<BBq`^Aeo1*Y!COSPlcMhArId8OE9S14d(oM@ETVfy9$&(F$AZTkB~Nr)n
+A;+{OK)^12X)h#t(d!F?nP(rxgR{`LUWgexjA-8`X2bwSC@cBOKWr|Tj1#&R?J;7_o6d5OLMzm?$T_5
+FY`g&Jh!AgM+O$a+(Gh=1v*>RM#_r1E9%CymgvktzzdtB<ZYyM@{R?IU4l-0<S3o&#tAiblWD0`cSYT
+cPTlD_N}$<tl=#Auo*Bq03<R1<bz>acFX^`AD0ycFI(f$eZzHAU_!5ii_DbE_Fd^|*s=K1@-AUaR)s3
+Drm6!02FL7a*SoXj>IKIR|c}cp}%_}eQN!@7e<G5F^)SVn(LIbT-cSYU1le$Y@8OT%JtdqLaRd-2F>g
+H7j@=ogJdELC@UO~oQj(ZIf>Lw9Y)Ll{c?xb#u>ULq6Skja(3=@mj?N4=c3=<HN2h|NYo9YJa!!Y5gZ
+nVxv-MXrq485Z6in<q_y3sh3>Sh@x^Y^-W)XmuhZ&BTxs_t~^cA~m@)a}zSv8ZmZ)Sc{tr(>+ByQ1#h
+N!^w-rG>g#s@o%VTfA<xHmDnLj;)mGs+&XIK2^8HFtMm^9(6l8s@sWS5@^*;22-UeE9zbt>ISdvsNz5
+jy6ECS2Rm|H6bCw~>$VgJT6W}E4ln_|W}|LPUAGg}-O_1F@~sthSJb^Q)D1L~>IRxeb%S>EsBWP1Q{4
+`V13^7G3==dit?K4cw@<^Qsi~WEUr~2O-3vqA7S)};58h&!uy#{gsGD`*t3`G5&YohWDbo!Td|{3QUs
+-kCJk`xRd&;7^c@-v33==2CfkARsH|?i7@wKAvg`sYX>UOaao@JO=Doj|^J$J*zLfzh8ki(;H%i&WN>
+gE*(T6R<NRJTv+Zt2sf=m#p*T~YUfQ@20E1nB$>6To>46QI-74b-_|0@R0L0=Rg?#6sPG^SvM^F-($w
+k#NP`6?a$Mt){i&?uxr711t@9-@9keRq+hOQ*hhbO8<_*T7RW>`p(`)@ARm@u~{44*&EeX1}n9-;i%R
+>KiC}A25Ys^MsKh-SUXc2_0Nyw=i@LB^)@yJy)*qE9`BFNZLCQ+zQCIo&Yl{s)~;DUw|07Tt~VMC*RE
+CF4*Q$3-&6h7q3CQ_yJxtuB0newTf4s2m4At6{LpZ1v=MishbG2-2!E>`>8-De0o~d=wc5XC^V)rTZa
+HymxzlNNms`sRZ##VRf#bIvIJ$i3#|Mrt-+FBM*zp^0I$qmfyC|nY{2Fex@I0#5CzBIQqrn6Xr_peNH
+m1?W1Z_^E%?a9?Mq3lKJ&m>}=+ZR0G(kJlXlH_UDLPUy$k3V!TvMPC*(n7Zp`BK6gLbi@KqEBuY!8gs
+?ojY_Z~-QGI=Vp3a4;QSpr$zJPQz-B!|96`s7Vf|V+_<Rhtn|zYMR68>ldhb4yU6G)I^8VQ3hQF8&UQ
+YY(%MMJ2awHvmF{yDs9v-qEz$UFrrlR-H=f#C!waW2EqPFVNHVVRalE)S1GJbus>GV62bmNVI6|~Kw(
+{t?Y(;M<i4nrcGswTB_P<f3ZrrSslsR+f2J@R$8`#$aa^x38pjO^qjCIDVKNTomZ-(r>=I0^)K;BfYM
+HhIf~hqs4>$n^7HAMmt<F}HU}|Z$S_D(;vehP-T9mCNf~ghRqSs@e!pQZw`p*^j(ChIR3ZvI!|J8}cP
+q4pK7`+~Ur7(Iu{#s#i97{_R=zxOaFuLlIbWlNY6y5FwI;0@6b*`?O-KelQh$R*4O^PYSrn$QM=#La8
+9J0Fl(wh|~oXEOztA4DoIEE$l(OVQGjKYq(v;Ib5aR?pt$-h;QaK7qlB!?9i$FS6%Kt~i5$Iw+2dQ?G
+i2p#poV~W;A2!V?9CkhiGbX0GDr!W~pXM!D9SR6uEjqQYj;t-b9m)@!%k?sgoq_-(74xyu({k?+3RZ!
+n~yMn}32-Fw+gTjQ1*-_K`kLn>LV^H(<PYR<;>7Nxwm(t0T3Z!f4Ulc~y(!VN<-rLIxqxbf|DJ+hot;
+V9*xEsgORuiC@xGNTunsq$$>TwutH3KWa;xO9k3-G+F$6>V9mB7QUE{yR&UD`7M#d@l%Pu~eJj-#s@4
+uFXjg|+fifWp(QEATFWVo|B+R)L9CrN(_0Py09)T%|+-#IY=?t2qQFmQ|oWybe$VgKznFfN?OmHy{Ya
+qra=-+XN<VaP`d)Br;bRsD|eNiq(Y`cQ-(>yzudRpi#v7>Z%z(4^Z4Bpp6Rv#R>y&{0Bg~!Y%@&OYA=
+Z(lvH3K)T5O3m|=hoIJmTbr5#Ql{|UA1JxtV|8DZo?m+f5>SPjP9J)uo@E!9I;|<^;nTi;10&kGni18
+NiCYg{JZvz*R){`t~X9>6n7Tgx&9pEC~dJ=D^3tT*H>N?&YaPh>c>v$nIr3$F)cyaGZB~aJ#;{KCrps
+wS^Jt!4HUB`?0m#QF0;_YJor7{STc)OT?sSbi9-Y(`}Duf`3w~P6gDj`VX?PC6=QV5cGyO@8e7J?++F
+6Lh<h9HTzi}{zTAxPrwV*aIa2$Fcan187rLLD#WUn+=D$BX%wDk9YJV*aI)2z9)ef2k%y9dDxfMZBSo
+Hxd1H{kS}NzK7|T!Xi}D5Zwn<1RJVJi0%g}LJidvL=OO!fvO3JE&~-|Hee?_2vk0x)!?FsfQk?sNCZ9
+%R0P;S9`F&MBD@AtiRw3eAmm2aP?Hfo3RJ|_z_<MzsEDnBh#vzQ$JR_{4JK$Hgh$xGL_7{u28W4w0;t
+GwB8n#giZX8m@f1Ljw8Xfc1{g=yL}1D&4TK0uzW!N&aa>IV`y9YHEd2I>MH&bl(!|G~2N=iHH0;qpXp
+t5!;)?)9L>SUb0ON?7n7)?*iij{FuK*P3ZnRXUXdom>6SMRxK#}S;4ADS{k_LwK8bGlI@kOr#6gg*1$
+QuAfMEIgN0mczE@$t6+iiq$<Zv%`Y!eay$XduK%%P>Ggp-%9N9QJ1@<Vg!N{|-Q*PcWo+0g8x{IDZE;
+4yldLzXwpPyX4aS570QKw&9$HLZh@W_a6Wx=U#jWOv*+DD$g_&A_XJ*7?^wzDDV@2Ql%*HQ-HJE@j_`
+)7&|&bd2|uh>=yt@6~dRm1VbR2uK<c@jGD4g$`r#N4W&%M75WyS5ReM{4p<xx+I<g9Jiv|p8=(*>>gv
+E14TVNg6A4c=6cR-R2uC!OB>`%7;fIFOfB<+Ip!{{HK*gb<G#`utgiu-!M)^S~jR%bK5rAU3sTkpbhC
++<snFj|n6iQ?X-~MxeA|T^<&`@d++|=X$1{#OdG&XdELVn<>3!5|)+M}&nCT?gbl}FOSQ$R&f;K}jRK
+xI@2>lvVNSS?(VX93Ea2ys0JRET3VO-3N&!f2ldDlQdRb^HQQajiftW5uAMR2krw@k>DEPcXQ`F9Vf7
+!Z3@k03|;qw?H{l*2MT#pj0G}V;a48PrC1V<k*cj9j@)Kofxd0S?wRZFzO5I_C$YlWVq5_y+-yXtliE
+2XnC!7w!eRG+|Bi(o9kP9Cke*Y-rAXSy)*GY9Xz*srnfQZt*L(zA6y;{mxmiG{f*_bz4iV7zxO-c=ki
+%GjQzUp;R8o+o(y`@aCBjPaJsj;ygu9<j0Si2mp6owy}y1#x7}^TKjCDfyZZh0<=*D$!C-l{KN24G{v
+Y*LH~W)+?X9lg**n!A?cW<c89fy}9X%608$B2OB6>c0A$l=-DSA12CHiIbYV@n<wdnQejp)tjt?2FO*
+U@jH-$w65??&%M??)d*A4VTVA4i`=pGKcWpGRLrUq)X=Uq|0W-$vg>-$%b6UmD*xzJL6{`11I{@k8T>
+$B&GEHhy&c*!c1B6Y+FiyJyesw;a9k*zG5l<6k&I<%}z^a>grXTw;|oUOD3etDNx(RypGnsB*^f*sPp
+!1y;`ZRXLpT#Q9CkKKXzLCnaW|e7@tBzH$kkkbJ&_)bR65TH=Z2d*u?$9{GgFEqdh=ycPM7$8x-K35J
+h+&f_{<xdh8cJn9435m)Yi53qEHn`r$ZU}+A+X@F}eANg2FS1x@8$tay+L=H1iKKB!&1h%1k@`I=ni%
+~xN6R!mRpnUo#Khk0QiRb@PGNG{JgaT+MVZe_Q8laO*1#Gsa^g)vOgwZC1KsV_au2@U*-V$J3s#ZXZ*
+(;aeG)h6B%!Z@GwZ1}Sco@g!q-z-;euHDo6Tds@`D?(^?#54RtfPt9ji1&CaAI}ir!_3ciP4QU2h&j6
++=)v+ZF46MBYa$`6JXimXY|D8o;9AOfu(}pf^{g=LI5}B4={a&VCblkZDD=4B{!;w@k?I0-0++d|6RJ
+=YSOlpeW+Y++^BHcCoZ>|v#s9&m7%GL*uw4cf4bZl@cTfg+(y{)LP;!P8gPFJDbZ0aw>|<WAH}$1VD<
+|=5#SCTCq{LhI7okhPu`&p(AH-_sROk2IZ)~VZG8c>NzI<5-&Ts>B;9V)Es}0`VgYS^12oM7l74q$0V
+O$)?vw=tyS_VR0l}J=mbaNg5Ncy4g&-|&Gld}Z#!L!92#%Q)g0#HN6oRz8%@l%A9cBtaTHa;~VPbh3D
+FkVGn<)fod7CK&>3Ewd1nGF2DFkVFn<)foc$+B%X?U9{1nGF2DFo?wn<)fod7CK&X?dF|1ZjDjDFo?x
+n<)h8dC#N}gaDaIAqWLBlR^**WG00$u^fORg&-uzObQ{SKl_ptg3ur{DFmTGW>N@b&vBAMkb9iX6oQZ
+-W(q+n5Hp1!6Z2*YA?(hk5Ty1nQwTC0Z>A6$WV1O^2vT*JDFo?zn<)gLIA&4^Qg4_k1fe#}6oPcU6^0
+aoG`-Cff{+<z3PFerGld`|hM7WWHd0auQeT)Ugo(YNK%@|)zhI^iCW&<gB84Cw1~Y{)vAPwA6oM2MW(
+q;bikTFG5EU~igccRNNeV$oikTFGP!u$UaIe)x<@?<C4AxeL_iSD-I@*TQoyE=FwO;rC0#Hi>1QY-O0
+0;maO7>PsLtEjW7XSdXfB^s{0001RX>c!Jc4cm4Z*nhVXkl_>WppoWVQyz<a%E*}ZEs{{Y%Xwl?VW3z
++s1i@zwfVLrM9wLOCdml2esSQmK4Rc4yk0<J*Z_VEiAEKEw^0Cmb!H>#gP@;b(H#)*p83&x%DA-V#nu
+P*M8`?g8#w4q!{phh!+sv6jK7^kURMj>(OX{cL3aY_+T)&Z_vM3+3al|=se(Wtn~*6&RysZ*8Jgtt+V
+RCw*2AdpnujMRC*UT`-5TSbZ_JQx_`%&p?@g+>(l=5cz?}bUs>5(sU56*zrWQR_8#!VKe-1h$9nhs>s
+P}6b`DnV*;vP)ss}44{PW$Y-OABZM~>XpId=Prqn+a?4<9*JS*>iZRKou?!e-l*%HGO8e_td(bZ<+mo
+_Da~jMY9<Ta&iKSgkcCZFhdnIu3WSI+la$v0QJ&@}sQldMrP|`evOx$yzh{Db{x_mY-%aYyAxCn{D!0
+*18(YKVzG8WBEDOx*5yQGnw`M0_%kB;Lq8fv|{;1)=4{-Ut*mw`DNA#lV4%77t61*zS$;UW35>^uQQq
+L_ZzGe*7uui2iYNhi^<i=c@n(MWVXq7W7%QydrW5g{eCRF?C5;JTC*Mekjb(75$l5u;Kxj6=ff|V%sT
+lM8>v|RgsE)zK4tsCTC*$1WqbV@8>m?Qob|!>;|nIUWAG)DSutO+Yc*ECW_!&Vf5VP?to|le<G~wUjn
+(*QjefxPBJN`Ja4g41eDp&$8nJqfb;0CESYx(91|2sZ=+Tc@C9D(1BA4ynV{DVGM209g9=y?ynarxWF
+_s^?E&4yj*6lP}8}V4DFzi|kTMUz26ow&N3`hH65QcGsTp$cP3yR?uFw7vT>xP|73|B3NErusMSQLg`
+i(xa}Fqm!K@c#qDikI6r<5IN4)l3doEr%_K(TTOgyOYCa*x?1`uma=uO<c4bwj8z`j{1-}4F8wnF#Ni
+q9LDa=io=Krk{os|hm#zxPy8?kpyjaTu;p;nM>|GWio=i%^~2b`X*gWV<}mum!(kA23JwG1Ne-ind>l
+sW6o+f3a9E*k`zF#^4qFae4o7_~TP`7R7;=)sP^a+2*&GIpa&Z`4BsmO(PUVNu_1rmJi*pHvw1wp`PM
+j2nA*VQuUzSsG7=5QW3^~PN$SDp(PH`A=io=jo97Z|$IE+qG9EP0YFys`6A*VPDImKbf%faE<`(Yg5Y
+5XuOZY~ZN;D>?BB!{7<I1DW2;V^iX;xKy7=ZDcr863tY^ZDVJ!;D?#a~P*W8Gab2dy2!5^Z8-4&gX~G
+x(q*zp;{6@EX<dHoZ>L#TpUK@68tc_F2N6@>v`wH=sC}GI-3ut^WoZr!wgd9a~R;t$6>(_3miu4sW>e
+7VRSM>4x{gU92Wer9)|@#EO1zOivyjM;fK-pGH@8CwFC|qkV{w&=i_kfhZ&8`=dh4V6yk>k4nv-b!-5
+}%Z2d6FMR8d0!`U3x%O$ip3|QvlFm|s54ntm6Ka8Hs;4u15aTw1L^W_qdQ~7ZGoQ`3~d=Bg75`rIwT*
+h-cn-AyaFk0v1Ft9U~A4VtBa2S2$nzx2yQ$jv0<Pz9DBlBS`4rk}X!h8vV!*j@of#-aFc(S+z=ZpCq*
+7L(Sfy<aLAv~u;>wFv*{IDK}1wT9o4r9FSe2MW$#j2_EC9?hS0>0L)mrH<^bI&CdNw#kSiTNBZ^Eq81
+xrD%B<8ujIdQ;^RbKtP>oKB0wuz!n{59@Kbyj;Qz4wsor=y6zUzJx-?_D#fCSPlaK`TVeuOO(msGINP
+SI9!MyM&DD-TPyQ9T{edcc}|y|OBmyawK%NhhjsE{Ee>br60ou}d`^c=mhqe}&W9Nq7M8<$epr}4Y>p
+qs4$jaI>&=(I4o;O13mit@W#q%l<cICNwMiHA@x$2UG|%b0c-|Ugz%Jo%nYo1Cd<nr1&mot9oX-ynxk
+Mox7W}Z@{9%E^%QSBd_p5p55~ca!<>GL*AFfT7z2q1B!g3h$qH$R8!$K}m2#1B|bOMJ3KP+%q$R+eR4
+7rT=IA+e_T{~|rd%nbO;ILjU(VlRaUDfjX!-jKsQT?#MVRQVjz+t_7xDY>#){Etb3z@f;&0(l!a(LE$
+81fAB;UYNf#T;grular$va#<qL!Li}_1>p5-VYbTVaUsnOPIo8sLRV?!4E^8YMq~$!|Xa;SPl#GCG_6
+o5d5&fVPXF89Nyy)I1G9I?{Nt8C4~1l^f(N8?(>IdK3_t}C9oexuD4deb2`2EIACRGIDc3#AD(=jj$e
+@Gb9fH91X|DVIo+bpm(cUWdh1IF`7k<3aTs#0T%yGJ5+&xtCC-=7;xJ0g<A;Uy)(Y^$digL~PxW52UM
+_*sQ~7ZGoQ_?2%f?}0{&1P|*2>I>=P-X*kHdQJaR?k1=B*XthqF0ch#$`8aEX4{lw87$@6!qEUKWx|2
+plfN56ACuuuE*&I4t<#IdE9WB?JzaIbTBHFl1xbm(b&I5%VP=&(05{^)!B1$R*0-aQ1V$>|CM%4h!qR
+>v6acKdi^$?D@mBc>XZEmShfRf3JB#IjomU%z?v#A2vRhDCE87+0P#~<~@!Qa|waN+4-;*hjnrZt$Y}
+b7i`{|z+oYmi1T4~(U|XtA(yfKurOaj;IQzV4t-Cx4*VRR(+TTK==ou6a;jVctrzS$o#DBJRz9r7VW{
+(+KMZ-n=1X|-cS70KVLpfT)`8da!;s5Z2VUT?Ieu8kB?LbVdH(a(is0~K&RZ+Q50{opWc%R)IIK5cVh
+$V@*1d$B;&8m~CA$oEH;0XXPKV-+{T@dlepq-;C*%^lm&1B~*bELAFkeF8aG8EsFCW(P!|`)EcD|d>V
+aW4ee^}r!<TAcbS4b|Q$Kf(_31j>))Md^k%HuH9De_^+Q{=;X95!bCVJGG=JF$!5uxkv5_5AQ0IIQP~
+A(z2n$h$F@5IBqnQ2D;c0Xf%v3CQ_4jMgQ5j{|b9?{Ppb{CmxilN^ScYrcfQVYE(h7;=ikkZ0$Iop}B
+*JA;?a4_gjf4(H&oFkeELx2E-7B!R<dJPn5hKRj~|XU~_g9L~jIH~t<6J5`I}uwyxFIXv0H1>msYhap
+enhtbDWxkM2h7UoN6aTt9pkRJv@^KlrhXP8UG^VZloY5lO}@Gj(VA%3`sTtaw{!}{ULXy|fSSYJYq!)
+RRwhbI_jC!dXnEru5i!+NiAXnn4^h<I3-E+JqTPi=EySXky~<`~YNE-`Bi3$N4Z#S(gUSno9sA(n`jT
+Vto0wZoRfrgB*LERw)sv@YRwI`lD3JS@Z#TCdaTEdwub7_DdYI$e3o{0Md!av9Us^f;XTTC*EZA7<y1
+<*?=Of^isfJ`QL5VLc8Dei*H1w!DNXe%K5S>%GPy_+f#=LM#D!n%A1$IG122j^(iBu&EptUgMZOhanr
+vVZjeWURFOW<PwGWVLc8*&c)$)l^=G7*m&4t*i;M)b{MUviHC)^=}L@;i<q@$iXC45cv!%&5K9Oc7FJ
+t}XRWbw!P;TVVN*G*x7u0}t6myzhfP^sLdOn6E#3}eTEq<Pu)tw-l8eJm?1wontsk}=Hk8AVO`ScQ{g
+@7Y%zgH75q?-__Hg#<!*=#?Iv$Q^53{3d{jlY*sT?jO9-jH?!^XtJm=TwY!x$zT50@Pe#~5aZv6w~R7
+u606iw|228-d|MW=mw-VFANM#KQuHg?L!Nuqk#}XST$w<KZ&xupWj5JDiPSC!Q_A4w$vWmcvWU;Sy&{
+XmME24uje=drVh=9oC8^bnLL+V>*GudLKn9(GENDBJk|USPokbTMkEku+^LMy~Tmn^X4!b=i_kpN0AE
+PaJC-?=;qB~V`2#>ev5-2f?dsFn@d;@Px_E^3BeCTHZ&fFJWVcP1c#yKdy7MuwkB}6kX%CRZMxVFv$3
+|bB`k(5hNC{pjU|eRhYNX1ht@NCN~eY4B4!VxXH)HPEw;mKRCl)>wj4H@!*;fWojv?pI9%qp=>!hzy~
+UCJZMymd!)*Ah9kv)Y6~mCHTH`0%4wv{cT_G6Ovco0LmdKtwy!<cI32XcStkb+qH(6?p50rJo7Q?1u*
+z{Cl=5AOol@KsI<5WVxaQ2t!wA`>>DpBTS39Ti5CLcuNLt-&(F>Em$^-=Bzk!J6PwO--Sa>F`v)`Sm)
+W``2l9|$ee4Htr8y}1&TRDu_8QwhsqQ#mZ85|HhOnk#b(hoR1QX$i<>gu{?ac%`{H!7!`R+F^@fQ!%W
+!!q4odtQl^HwZ2QIh2hestj#_gF4GPR3&2k>%<7Rb>{<+443oTDQi&qma3NFHvfZ$NVc`vqSz|cc4GZ
+CLc^EeS4UU+@Y|pJ7wj4H<!-d#ktto3oq{Dg(4-4Nz%C^J8l(iD)N<iLiD@*8o4@pQR1Uno*rDMBjIc
+zy>Du<WK4-2t`z+tU7n$dMWKaAE%4&#xYi3_di`C;KR&1L#wz3<XZ79QsNVmWL%ykHzIF&^Fx9L`=@L
+h!>2$YJzh>Iy&gIG11>wH&q_HkHGAxda@Y{SZf`?Aa38?{H*u80r)p20~}}Ar2vzK<lX%fRAUbvED6*
+Er(6zFvyy3)|&7^B(%;oYpsZU7+sg}Ar3tbYdxpa^21OUDIeDJ!;nkhuoJ&b$GWi`wj4H<!;oh;dsvv
+ZCU6*XlEb)rO!b^DJC~UKb2=1b;ycZH9M*eIS0abq$x>^)z2&gw@Gj)AkV^=DxWtu*wdPBpk9n^xv54
+~}1V5}dU!o8W$FFhRupG7=-qjoy{IIYBJX+`S!+N;{wm6L+E-{zL_QTn^gdraY73NDoo@*}g(8|i*@c
+4#@@}7+~|GwUazg9VSp*!fF8~TH-%J4#WSXt|>RW|y=ihsGcHLUbDD#Jmyx6#`;Um5zBhta<eckobmF
+z9v9``<a`4=)WiA~~#b>&nHm{q@Q%o0m4u4KH<vz5d3n)NSA2iuyh4ulH4F{mO&=!CLeW)i_l4SK84Z
+!V~IHe`7cZyNP#A?e`)4sdBu#xv6&O?(W%j|CX&=53byM=ZV87?>*gd!oBDmJ$2;BU7bVUyZuz>?vtI
+9rw$)ERavcUM}wg5?VdLtm@}8F)$!0cN!1yvZc=r}YAvbO#%evO*2k)sRK2m<NUDvo+Dxj=vD!+it+C
+qXD%}gCXW(9)#0?Ttm7OIyRoXd{YrKmAiK)`)HtnQpyN~2#aSjGJS)D^8>?F%`Xo#J5Ql>F>lLybCL3
+WchIyA~|vPOr7*-ailhsN1WR_V|{yU8k@Hp!_fyZa^<hs!kDZmLQeZ8ufr8l7LMDrvlHsVZr_qo~6pL
+RCnsG3|Fqt21p6X&%$|lGb3_?~>MJ+V7FpV%qPM){eD3`}T~liz;h(3tcM?({3e=*YO9W@jCvHG+xJT
+r13iTlg8^fKpL;(JETQ*(5-_`)_R+1bf$V$rqOBYIZUH-)N`2z3e=cJXQx+Z8l9TaTXWFpy!0AOqm$B
+WGL6nij~|bNq_N|%?~jN*{CNB^Y5aJslE#n6pOD6n$DfkMkH?>p7S_?C-MgJ6H6^l2H>5jAQ;&YCM4L
+mTg=Mr!I!sbnMY}bYju0x9GpN!X^}D30AEr)YtQ{pyJ;klko_voqbuV`4-`+`@`Ups?IoAH1H1$zdhq
+Sv$3#({TcgIKyi)hi_9Vbbd0EdR;1ZiOrExLG564}Edn(eXleUhRYsJFi$EvkY3=_%5}8d|i0(<Fr@G
+-z+{CMl|b2J;@$)NycVtA9yaSVEgNa4$*fFi@+%B1zfPDrtXBw;^>LQ2pPK#!sfdC5@j<XU>qw&!)d4
+jh{__Pa40vJEZZe`yWUP%V^TUAs)BGGMaSK5sTaEK#+vHUNtPEMQ6ksw6Kgu@`q`7CWWIyXBcjG)v$^
+-?Z|m(VHGVJsSD7;DjGCWJ!tA+xU`Xfgs6@N9mxBksX9noho%alow<mceOO3?Hasx^VIjC}^r3}?G-+
+oxp+(mPHT)-t>Z~FSc0k?u8?@mqXkjHDbqG76Zuw1WcL|!hG^!*%05LkVXbc~OK~cwqO1=zDT^>~uuR
+v7SheOBxpCR&dYa1dzx&8$rKf4}+$WO0-g~;z7XD&B!1|;t8-#+{vWOjEy(ckdNVDX##w^v_)@8UQ2|
+9%Rpn`rzp<XS?03vxXnzY5t)$ge?eWbR%w(fAi=+{$d+PBi`;cCnh(xb9@CZl+qxRO^{)vb^W86ODxY
+Jmh43FG5Zn!mBSqP8RqdFuuuS_%viEAwL5-vqUd(46jYP&aBZ(*7yY)XC6YYnW<(TK`-+hO<068m%Fg
+=kxi)Khx#K>!}=QdnSLE2zy5Y!hsrO&oj0KJD{$vcsQeP#!8zXG*Wk|EP`UTnc?T+YKRXodI89buTym
+4&w08arZTW3$2N$+75Y75zba2CHCW`w2DlhKatItACRENu~nW*j~sEO)6hMK63f+0tF3b#&#46Z><RQ
+CzgM0KA+RY^Vp8gZ(l%tf6<q^6Ft7fl@a#~_A<HF1hO4lz;Jmr%pH@LLm^tJ6x9MPZN=`HU*vUxFJ@)
+$PE=#(n}dx*s4R`gf?REbQ!)5W})Oh=8uL8+CMwYg_q^I$Gk&R)(X70&rxN<!GbjPa%d?)l;Fat6T?6
+JR)6J*^bHadmds~QXLz50b*DY1`1)WtDHv-<Mbj#RS~%Y1i7yA9v;M(A*zZXz5-E&XapZbxUO;^b!>?
+4DegFds3xy1H+oWol3qts6{}(I-+&mFRL7Rygs2V@&b_xFh9!BaFxOQkq=jL62Vz)~hpoR0vBiv6@Sj
+kX4{>qq2m-D$BKR4AB-o9d2+DsSqPn0`v(wxt`a?}0LR7yuT<q#Epn7rM`4Kb)3LKG-A*$;sl?l6%4M
+{zjbNL(#y6)ZRb>P(O2v->p{A58E?2i2hiJw7K=N)OELsRu&+h0Ib<>0`52{HN|Na9xz!+Oy0YiR1ML
+&I+%s<VzX%6?sCH)w#6{JP3)(9uEe>nf{(A45oeUF9_B*dp_F>+CVuHE61q)TcGv$YWqL*CDE7lbZYB
+Dt}Q=J#lj*cYz%ue!9wAG$1|>F)XJ^V?O#fh^ihG{scsI-=(2M8XU#7E~>l%(M#P2A6m%@QIDTIeB@Y
+VwQ{<*aem#u<I2!iDeP%~c)Y*nuip~&rBd20f7sdRUi4S@JlNY<>p!@)Uv;u){N!)FyK(+f_k8%5M+d
+%tKdI`Ub%y;;f3W5cIv2Z}tN&Mso9wM~QSHL&xZSbaPaGZZ?6}eJ%4Y9ecfGUO-|7u}5BQyd%A!}R2i
+h&S6*50+bieO!cDh^VdcDrNKU6XE>UX>ATmJZOyX%`5x@Z02>Ym_w@M!Q@@Obb<a3lCh@MQ2*@O1D@@
+NDqY;Ag>e!Slfj!Ow#igO`GrgI9uAgV%!BgExXVgSUdWgLi^=gZF~>gAalagO7rbgI@-}3O)%w4SpSb
+7JMFj5queZ6?`3h6Z~d$b@YSL!=oRLu8kfUT_62u^yuiZ(G#N|k8Xs+b?eH?ou^NBS}m{LY1(+(#@iJ
+eZ`*j=#@kG@@iu8T-nQ}fShDf<UK?*08*iVv+=Amt-QHWUJgNJ83!W!+gKyQKCw)w-4n1jPS|0SIlW8
+@eC#_7Y2|ej$S}o{FGt+8APu1Ino~jpCv!1FKS6w|-FRr|Ls$N`u^;EqW|9Z0CHpai6thbHvuP5tmWB
+lvMdfOQPda~X&#=oAdw~g`llJ&MR{$8@)Hpbse*4xJTd&zp+7=JHSFUH?X)r;}>QuSi|y;Qvze=k+<#
+P6r-of!T+X?XnLK^cp76)K)P<jBM0Cr61u{M&~=ggk>peBb}z;X=WQIE&hiNyI1lB_3t8vL0pFK->o6
+W6=iUk!l0+v1kMFr4Ph!3SIT%@UV;hs*C+i%`p782fn*F3jbeFO9KQH00008031s8R$MqzrP>w%0F-|
+L044wc0B~t=FJE?LZe(wAFJow7a%5$6FKl6MXJ}<&a%FdIZ)9a`E^vA6o!OV%#(Blx=db8cNhl=}jY9
+8CCW*LMbj-yer7#QQPLl(X9Syt3Jx!7HL^+I-lV@wOwaeNiD>;cI@3AePGd?FTekb1fml%cqF7Tm<Qo
+7UyG|*G?BJr|Vjjsy$;m$=B`pN0!dShp_b7b&zFy5L>k6gJnoNfiPBfFR7|Lq2|o$2IqFl~&k?@Xq%#
+)Z-N>UMDK_AEFa{q==lc4o2_Y;SBl&}bfQd}FdZnvI?gqCfdZ8>dH41>3iy{})FaPmH(mC+}$EY;biL
+x7#>%^4R&47YC;wJ^R?;%()XMPd7FjdmD}DryaH1Ycw8c93CEy1&H3ms@jQEF;}lJRV3<Gs<!+@4OqX
+;L>)1;bF|^l)orG>5_Qb_?I%YzVQodycFNkOpSH`?wBH%4B5ivkRhzBk(=Oc_dh7$+$zSaMi1pn|<zK
+RH(u3ar73-v%%Ad2=>EPe}gtbmPx%(;mNRi5)u}+$)%nq=be&pRBGr5z>KVdTK`=_bwvm^N#Yn_hC-J
+i3O^;7v5tdn%8?((5Z<?vrwm1*DMv#FdONcf#pWnDbSJ}@2D@cC30Y3bn$>^PFsA$*bbk+%IVQ`55~{
+2uF>$uF_itdo~n>r{P(HD-0c${I8IH8x7A`Z{aOx_*PrOIqQZ>;u#DCj36@gB|o+OlA}CHj`N=@36kv
+P`}Gsv-x_DwN6jf@O>t;YCd3{bklM^Ol8)`N33xQvhWA&3QHS*%+7?g^m}*M8PZM(ckd3HvR0S1XVcK
+?u=Z>o+CA2ujcv<g?Wxjd9*+OhNtn$z+)mps#B6VAW{X^Ad%4UOxy%-h*$0u?xb_^gi)J=jSC-k37h*
+Q#rI?-QB{N%q*^Ib)W_tzs?0ja6TxR=AGuv~_UKeINpZ(>T4RuX?c5%#3*jWvqE#bO%A6pH5w!bv9O|
+p@EpPiqL_)Gh2;h23enGMx3yLe{f{#Y|+`>SEL#OU6A6xA}@U)pDT20lBV*(N@Fd1h;Uws6dL%#KyZ>
+^1k<2~(H!*@?a&vlCrmb_dMnyfpOL`ONlnne7|+?EGvb-)DQd%+Ak7gbijppY51ER~@q*vln8vEuY;2
+vl$ufFuSNcdwFKNXONEB^yBhu$87pBXZDJ+5edP)`xsaeW-p&-JD=^CO&{odwqrImuDj1p){QXQwbSI
+<dNxvpbt8`1j@k6%nC+NNKlSn1$umgCH9PCGi(<B0pY51E|8dNA%%)Ci;j<IQFUahqy~6Ay&t?QGlG*
+vsAj{oTW8$;jT0h6^qz}hz$85A-ozLzhKAW+sDtUIk&-M(Moxj#EpV^-C*^b#b4##ZA?D(gGYyFyu&s
+L~pWh<m-fNjqJ+eIz+%g46wuw7+r`?=W0vJVB@kQHo0US#PAR0Z3R6>LLRunjqjZIrSYw$Vox+fWz6H
+a>8v?dy;gY(p+$TMb$-^vV&a3%zm#YC+rAEn!>IXYW4v=-(5S4{gr?+MWTlJp-?80&UNE?R9}RF0-=M
+`)QzU!)u#CJKt*?K^u(~XhU8K+LiIzM$k6&+AD&##LV7(lvy8Wdk)$T+Vc;z6Oa@LZK$O=Z4I<FP8+f
+dNan3q2kmCENIQcQ2krTUIcQfM+E5Q%s%-(<Q0oS5qj+Qup)J9&cON$#v}wW|v>mi73T?>lQDof7fpX
+f(YqT?faL}Gl*a3pJumNp!vg!wsP!(uHR-g?z3vH-bXhT(?4OxLUWChxg7s|9DE6|3Vg*H?L+AyKZJc
+vYV1=^4mXhU8M+GxEPw9#6DHsma{p(@aZoP{>jYD2r7#3P&p4%#$ftAaM*=bScGY3Q`gR*zV4+M3lPM
+ot@jEEA7tpq=lut*joYy3=0A2a(Apc7Dk_Xw!rpAg8@n(AGF@4Yc!}cIiw0G|+~;YG`Ymww2W*W=sAw
+PCGx-HgekaSn}6QcGuip%O!s`g|-!^jZTV)N6>mHXrmMRt4D0aBSz5H#3M$~ZW=+`C?0{l5VRpL6_1#
+$)7Hcz=)}b%S!gE@BKbw^piL8YfSk4l+K`KYwhgCklxZ6|?fgvJ%xP;fZ6j!FGHoNLoeyozl0P$OYn-
++w(?;vXoVEtqMyp5G5!%W3AMmTyL7OJbLEAyQG-#VWh_nFh6*z4(Xrpfj?JTs@Oq*Sn4%#$fwT?%uKw
+A@!__c(#h1DZw@rcptk+q6PG)^0`i${`v%%Sb4t4G-N=b%j!c7U8V<i(t}6=>VYw2Ol_7+S!RKO0WFD
+$uqPk2q)>Iql@#Bm6>h(54A<(AGF@$n{#MU3xrH;Odd8K-<h|J7`;gw!EbF?z^HKv}wW|w9TMhemnxT
+R&V*kL6^2pJAZRckuQvLZ}}@Q9!Xvp#V;KPZJMxELAz-LZTMRS+UP`qHj)hm+K?4!qZ0+%kQHd769w8
+hz{Q{q@F>v61yz>Q&WE-p9<kxH3yepMc0_8R?N*Oe1=`I7+WZ=E(54An6|@1rrJOc8Sqj>a7t6FY@rW
+6;EjVqc_TN3Cfi@bKw<8jAMc+MQ=CmQZcaJOr?N*X$^NYbjn<i`>p$&pA25qwkk>zLF`I~Dr&^Fq}Zs
+fEz&@M0@F@m;HJfeZNCLXZ@ZL@g92-=!>Bp=%Kh)0seBmAs)%%=JJqVI?l`OJn~M5GN;D$ItwdZTS69
+Wi2dema7M9}2S}E6j$x$l?*G3bP?A%!aHm8}dRc{va#NhMZ+KRE61)v&@F7FdMSMY{&|;AupDWptZtm
+$cv>TXss|Ca+cXp6=p-uG8<|^%oc{sPTFUgorWXq{5EB_aLk_fT?e0C9cCjIUxwMZ%GQ_Jnnc@(+4*Z
+niextA#S(1|vo%|5N@sS$&T25*PhQN*&tzw`X~Mn;+J4oc4OA``j%c>lSV^=s;Rre@&1h>@X%`3W0=L
+%WuN^7hXloYyX`pRoYmL!k$Rdq)0@Z?`tqDg&vWcCavJTobVe6P^SI24FfObWkw%I0jBWN3~9kBsz%_
+{98p{;S+nnYW(O8da1BgrfN__^uQ5t^?rGTItuTS>Gvd)OhDm}qO(`&n5!vPR4<Fdfkt?TRPb8fI&rL
+RLJ{)}<pw8*M+I*~!Kleip8~&lWbAUF1{96|5Yw5{`iIi-jXD(O!hv^?VAcVYb;*NXS)XcF{gt$Lv-D
+ZFat`JG8BYBh`5fso7YgNwll8M!Ptpt=U+kNwo7f))+w>T@>(IRvSj!=rN?(7WN`H))W|y<nM;8*v1-
+7I3iMLvlGifn<lJcYe!a)j;z&szjb;HS(QXv<Fqwvw9OtvR%PwTsvbk?){dm{2s?uuv}wY=M5JB$$B<
+Uy5wu>)X+vIhJOaSjciNhGq;zQKJ8jJt_Ub%_)I{1Erww@_Xy<QXFZeN}EvKC@n|-chHqF;MM%o&qZ6
+(q^uuDf=r0pVYnuHP}?Q{n_J1HErX~Jr~-VbsSFZk0y8?9IU^^j=0%xg#Tcd(;v0Xx{CF0+FjAGpwKN
+6dDxL$28uu|uun7qRP%b_#7a`wrSPVYP<#3L<T@bfomfBc(^$Hqw!LI_)C2u-iyStVG&HLp#xxcSR-4
+X8k*6(|oP!F(hbKH)gwZWFcl(I~}p|7}83jU6sd>72Cot(ny<k<e)vDuvI;V1cob{jzC`d*B|7kBT((
+X-w$d<zy3gzj@0!1em1tSYu@jdpN>GS$ZkkYq@C_yXEW!RP4iWcMcU42ud~tC>|n2WIHEDy8fI7AXjd
+%J_R}rwY>phXX~I^uh20tLGL3frdOsthje{%T%ONXnv^6_xG)CLX&Kk(28SRR#9TDjwZT1fwv}wZJW5
+{}LhjdQ6qE5S>k@l*bcA_iLPQU(ujk<$2O<2XYLt25hW@n8Vw9R(bpp#X<m9;o%Ya;EcK-<P1b`7-6c
+Gj4!9nm=L;`Xo?3~gJ_A=7w-4X=YXP1u)k+E(Hbz|ZYrrz)!sZH?2`#3MGKUGY8aW-lJ8=^pkKLEBFs
+M6z*o(54AnRXpM{?d39Uw6*_@zE(1Av|eUwjZvnJJ_^`cqsg?<x?Y(!dag)3qI25mH;u6YbI_&<TgTN
+SX7LDG*DKT3yy8#ew2OPiU$x^A&5K7?kZC)ooeOPErY(nN@4k_7(54An6||kxuBy|9x|q|3T+L1FP)l
+^$kjvY|u5sFET<Nc2*Tp00-WoOp4%#$f>*%zLd|gykoVF&@E^ZUM*@H+MulUQ4N6LQ?seyKpt4C}+h|
+Gs}O;(SjPMg*0piL9Dj;luw@H_sBgLZ-ONX4ODoh5(ezj-8a!sR}QOqtD!a?Gar`XXlg`OLPmc*Km^K
+;l7MJhJ}Fv>_kBW!jJrYNV~(TjM3r=7;Z~J)f{uy?I2l;?K-zqm!k+073H{(rlTwnbF3Tqd*(idnKV=
+pwTWJ+C?tYHiNe2%_BC_ky=1oW3<!Pva;iJ%%=IWw}~BcWy6sJydSdkwIfD}cE$HY9t39VHnE$ABc_S
+A#%MQ_P3+ktstC131*olk4q2qr28Z3^5vp>%UOj@=rM-FteU!IMTl4A>bh6YkZM0ry@rco@M{GH5Q)(
+x=;<OpHl`k6;2Gkb0)E2qa7P-_GOM7jROKm@w+I}vzg`;-;s13E6n`<DKw&V}0``()PNB_Mwkn2e8Ry
+U=#@+AoQ)E1>uJKt*y18R$0Y70m0b)k0tKK9bRwr0(r#%n{amDfh=%6e@JTOw;h?M_PV1N1Ej`P6m^N
+e!uOBOx*I+E5Gd+7+jEb-cEXge2c<L#;No+r5<9?(M9O+V!J0RJSS8JRyNvH)=z+pOCDG+R0PL1--VH
+Qd`*-S#Cm-Pi>Q@k;^9}j@mV(cD~oPL2Vle$vSy$O+sRY+GYuf5w)w7kXTr({mjP31JP*_9qSY0t>DS
+gIM`}jxi*{*ugrq!Zew<BIBRT;wi@HftP$KA?amsbabq?ej>e<$)y6EiHH-g!bgCR5PN$>c)!-}VgV~
+MgIF_S{+r54L@?^X5;LeTlmD!EqY&01^MBPq;-MHV&!S+OUHfh|POt<2HC<mkQNTVPBA)2D&lksdCb(
+0>NJnrN8Q{&8VXGb2;<HO6_!GpUG9o@M2wX-MAUA!<5QE`J)Cy$*!d2w+3)T8GIkDnWyJAdNj`Nn2rF
+CGOsFzq(5>=BklRuyyA&#L}hZD!TxTy165)?968)%INNWYx}G?Pk^PT<vAm-dyc-mF`3$F0Dl(-S&i1
+*=3TI(&&~PzhyJ&g6@VwDUEK)LaFUZlC#AL3~;tOK_e`(<p~;M(a*{>#(sA41P!vEtx?b@``H==4YQw
+}KSAT{XR8!6(0;Z`(I;7{l8lb8R7s=lD^=2H`%0DMfSO8`G~P|6N*eEGTqP}EYmnAt+V7FpV%j0n+Dv
+<Zv<}mLpR_L1{(!U|)BcdOeySZhd?+!ANxKK>S`kcph%{cuACboE_+!#|9S@Vn>v)7TUdIvAcpYCMEv
+|!DNhfQo&onwy+aA;CG;Ir}(K*`onFb0pnMP-4yTvp*HRD};(CEBucbG;eWxLBXIwRYBK8}*c=Hu|65
+PSH1{3&UCJ~m0?^YLe-@%i|3()fJ*1!++oo&H>Ul%%MPKHb5NkrY+YrB=sDii+sb{p<uuQ4M`6^(28Z
+DxpXJ@T(+674*Av=`oU`0{Ya~DUzb&@AT%<*GQ7KN6>-&C28_rF6cAAPFi&QJ(5n7B#)m8KSNS<{C&D
+a&yo}!e~+Ydg!Jh6yL1@eAW1qnpAO@%NQ(;Sb>`A}lA;2-)an9BQ2`yQ{Be@x@q2WzPmm@Jgh%cEnzX
+2Z9>M-1NzzUU(*A}tX_P%G^l$0@BTbN?vi^=Veir>bY5Xj@bcsZM8vO%l{51L|Y5cMtkj5|Te<Urcqn
+*tO`%xWTDuW>0kILv|b3@@pWpuK?e+n-uqeX*<Tb&n`(WR-tea@3}LH%8YCMSbF_8PRP3LNkVT09#xe
+E$S7Dx*&gpMn<E(WVdHh9(Q4e|sHw`KS=wx05@+EQBtT3ACt?4)wPKP5!zfsFH6%j4Ekoe=8R9j^CmK
++=UiZ(xMNB50Ur!4z;@hO<vj5-_y{dLb`NH-h?lS3hC3eaSK{hNS6w}4Nd+|;ZehHL*ysc9z=d-{WC;
+<YCQvypIiR|k>4{e-Rffc<vl&>d#>Mm_P-!Y<kGcwb}|mgR!QjM61sQiRk$sA#dy@m|2+>?UNbm3?%j
+D4a#UPPO=5(+t+#tn--0U3^E!~<hAayN1b+J;P-TT)(#I!|<qgH_tCh(5L~<BEheebH5=PU;@qJ#XgA
+w29MN?Jf+!1-0DkqOP!_=s}UNV|5;~1jq+Q~0HuRx8eYjvT%4mB#Sm5k3DP~{1k^zaURuG}<`s4qa3c
+N|Rrofo0TwNb~v#izx|mB0c2d(v@STvsVBe*FrKd(`v)qOqJi(Ni1CxfALn#a_VoR8>x$ug;P515G&o
+B&HH^Fo#0+aRSArz{iUQP)EE#hz{-W{<~1+oz=sc^6bZu<*Dh@SnR(KRaS?qX&)!IbO?e5=<xoBP~&?
+P4bc8aP~*E4dZ1s-g|rIM#XeVm^Ac2fUP9gfPpENmC>a;D^bEajGCsIVNZ-)MG5j~gxHcT`|3HmlkA8
+7^N%tU<q5KqTOcjjIXHesr!vOz~RB0pd`v7u8(ThvNf&Cb&EUk&S@F!5^ym{E4_EV_xtZYL48B|#su7
+Z7B_OYv=6YcPCk{;wq*+db)fGRIJ)bLA)aw8XxmeNfj%|#od_&G#b7*5pvUqhAKla#zuNPp3$PLXyBX
+)s#Yj)sAi4x>lMbQj|)Ee4Jr@u!d;qe;hv@KZ>a(WHq*^eLpz!0;jX^rg|jtRVLErPFBA1S0hGy?Ck=
+;`!2Sbd>L@@}=9rS%DbT_u`4dLH!D9JW)_ThZ;{5s`@olNslJ=8{UB`%YsPZsxNIviz-00>c^1-CN=y
+wsIo5Hzrs(TO6p@;!cU>f!r;Ne&!Ec6;6K72LX9h<8p0nzm6f%WyNMsC4J~zS<FJ8l2B{in4Xv)K%Gz
+2zRgG)wt7_~<JXMw8prfVO*_UnvL;D=G_+Cxo^AII8XciGT`+o1fEsH+esfn=Jk4*?&K!}?Ccy~U;mm
+tO@B=Kd4EY*GmTI{Vzd=;X+fkAu?qV$QRy$&tLJBe>VjH*F}Z$gvRD4P@gcxy8b@-2w691QQ<5T#dCw
+k7(p-@pgG3sK&)Fca@Vl;<5zu=gRxw__4NfG7(>%MT&SUqwj!2wHrzB9ZP@zVsOwwvVC3zf&pqY@cTg
+OqCM^9$dN+F(*JT@|^3izjzXV!EA8c(K8#lQR<m<Cr+MjY&I^8##gt4W4C943}Y_@von*eVEe(iGa1(
+I2D8C<cs<xWbaOP`n%vxdMD}uM{<v^^IKFygcs2UVQ^DnFaFb;D?*_BUU^3kbri1Iloz4F@%+2;UxGo
+Q3lNz3W^z38v<DIvf-QF2p8Ey}DCcC5A=;>fEm8tZmcckBId68d;8$A^SJA>iwmC<Oh9n56ly!qAP_H
+Ho$+u`=kwc+Jpws|Q0PWW8-eE356V))(gd*Msr%i$~GtKn<m>){*Wo8kAvx5Br>cfxnW_rmwX55f<_k
+HQ~>ABUfWpN5}B<vz6WJ5Wml1QY-O00;maO7>PmV^x|58vp?Fiva*B0001RX>c!Jc4cm4Z*nhVXkl_>
+WppoWVQyz=b#7;2a%o|1ZEs{{Y%Xwl?VWFz9LHJ3-|JHhGGH5Qr>c7X3IxcKBPo$qMzUfEhGnE3OB1b
+TmfevoMVKQ8^Ct%a@o@-=;}9GI!6zid$H4*P@M34@mA{2P30>XwR96qTaX+c)o}QWBH@2=ywf$6g|N7
+3Y>YA7L$G01M!@Xy=?+!*g<Nar@-|X-23?|PUT+{z|FqrJ^kFO2(8^has<NZnF%5ZdJckt}}$>4PO*H
+;FUi{qWa?y+N!HG&h3=f?-b$?)zV{F6G-xG=mm*u5YAzdX^nI@+Z_i4%>j!Hs^@?%27jTW3#QK7VR!`
+@*TMv)dOhoq6s;<7DH(u}1i#x+fYB8jZ&qkDq!x5=azJ&8y9@R~f6%CTgo`)zePf)`^CS)ia42DBJcq
+r-!89Pdh#IY!7Fh9=f*eIY&*}o_G2UY}?N`ZQHi(XPw_Bt$M*}o78sEQIp!XoE|#1?IlM|e%teo8d&w
+R({G|)anz1gUvO$me%n>2-(++?=d^8E^>-ar*?vFooOyfV`-v!%Zm&5_+g82qv`r3o$5Cz5fzv@!!^=
++7<Qlo*v`wy&n~B=9;?QZDbnt~lO%Cf;A|@wi*ExXXG~9NE){3J<Om360^ZS#3zvuKSth(=<1be6l&K
+bAj#OXB|!aGi{$q3wa%1TDyp3}B%kM_Q!hW!Sy`bFoslHWFc%^8HI?PB_6=l40Szv6U~4A1mUNA4x^*
+PTv8BERLxK_b8H9JX^L?>KTRk>7Pj)am<&&X_u_-*;rE?+=_#WFmj)w06q*$Qi2SPMW>p6rY@g*?Y14
+>Qm8wG+iIe!&QS=d4pI&5Gx2`0YNMvhy?_(WPn&g5K9PR0YNMwh!q5}fFPC-#1ev7dV^R%5DNri1wkw
+zhy?_(Kp+kvhy?_(fFKqK#410C1p={zAQlM30)bdT5X<}^76`-wf;fO677)Y&f>=Tj3l4}$&Ie+W=Ri
+#I9EeGt12M^SAXXT}B+r4EI++78$#Wnkc@D%R&w-faIS@+>Vv^G!)*O8>k5QEj;le?T9We*Q{*IUfV(
+f?o!x2jch_NH)fLJgbu`Ch9*b#F;%y7hF$siUG#1erx$PZ%di2Xq<ivw|yj+lPs9EeHw0`U?Yaf?9g0
+F&#8g|{Qd(S$4&#DW3hRddA42XR4;*cZgY6U34MVqZtBRu9BQI^rThT%;q$Al7VrFptLa9kG8#%!wvA
+8L@&O=48a!5mzB2h9H&@#1ev7LJ)gr#DT9PhS7vXATA~&W<(PTfmkv?TyjR70b(+RULekJ#2FwiG9%6
+aae<DwWiw(2g4rMz3`Z=yLClFJI3V_qCa@#MAm%t?;q8by(L|XUv0{LD<ul@99I<~ifkC{8jCctk<~d
+>>h$(0;FC*5xdoYi?@+a&3qlxN*7(3!}qY0JY5tj<$rAHH+1!7egh$|mWWPrFj(S%*T=74Q6Am%vYqE
+<}^2x7qiF<v#nnXD@}BldR0!AgO+7)LB~gE(M-SbBoEsEincm`vduh)G^Ph%;7AWPq4jFCWC%5eL>0I
+|wV%5p$vmjw7z_I%19^_FpxD9kGBQE^{5RfFQ=vgn}T38L`L@V&9BdA`lmo5i1B{0YQv2Voo$67vP8&
+5>4<xTx3RE{;CO0s|WM2$_6pci2b7pjw4>RXaYN8QK}=xAg-f{Qddogr90w^XT(K1;tUW|CtewG28em
+lM4LeDV5uq@F$cuut|P`EUbW?Gt2J2%9dY0ZVn#Fp9r5xrVvZx`L=#13#KgJEzR<w~F}3yqu_n-ic>q
+-f#6?9D7{r`tqFfM{x_oW5))BALs)^-0;ss>H3jy&G95D~X85wa#G?9@Jv!aQ>zFFs>W-%{x;K{mmcE
+tV}ak-8df|xT|hcn_bLG0^@aWs+N5pUdNUFAVsomZSQKukt?4#f7&ItMC?am1=rM_k>E*dN6Hj+n80t
+)NvCr8?q5GGgy&!q*YwXo3UcO<2BGB#3#Fb-ZYzLm+nWQI$9AiUM){X5Ie-V*gbW5`kDk5K9PR2|+9o
+h$RFuj3yKUF<v#1-w{g)VhKSEGh&HAj8{!?KrA7MtFmf>TGzX;B_Otwbq*-j9mE_*EDCbO7{o<I6IER
+`fkDietn+omvP4ImAH+pD;)+KT86eJZ!~x3@XMlJijyNNl;5lNue9b|^W=_`mM-zCmjuTB(z!6t=`C1
+_$W<(Q9pR8L!5K||W&4@FWuVsLk<RT{PEQp<(zXq{syXGJcd_jz(iHd?)=6A#}nqYt!M-%x$EEyn{-X
+O-C{;cX`9kpKmWL<_MCV39THY0X!^BTmaZGj->L=&|mUJFMo5r`SlL{Y0IBnQN+`ie6T#JqLHivV%Ug
+4nsC>x|g6Eq&Dl=M`tc05KyYE_JdFgBZW!3|CDE2x3`;BbErng5iksgBUwv;SFNWWF6(9^;adCP70o^
+vzz`nw=VY;XHk$N77)auAV(}J0AlQjF^K&gu|ObRhfRM9nXFrbj2MHMl@S-|h<THB3(1HxK%5ax6bRy
+$T}SNPq^lTBtcN2m3dGnED+FTc4PtLc%m6WV#N|a3lHrJbL5v--EC|HJqRM8(>*a`B_8U6f+i@emDyi
+Iz*gu*mC?oa<F?7TQfmoIYVi-+e5Hm7jwPKFAIv^&wh>hVh95F8=W`Wpp*tzjka^o%h3pxbkuz(!qBo
+hL1SU?U7$YGpJ2*_apIV>QD1>~@R92Stn0&*Bf#DZanVKRX^96$~Ski!AuFis{E<S_oGqyTXkzu_Dp4
+hM+C0pxIiI2<4j<76U$91akN;dh4yki+;(oCC;V2|0{ktiy{Yco8wlYx3Qp<#Slth}gZyY7ob5Hxa}*
+BE}$Q%+=vHoFxRYgdmprL97sneP66o2*h}+37kwo5JN+Z=jt$sImv{CAYQ~=-4Z~Y@jeI1`SyjU*7+7
+qkeqMxHHASeu_3lE);V_*7sNOs_6IReCTb8D3Szu^4KJEdWrCRDh~c6M2x8ww6C4o37we!S#&0;|)oc
+DBR;vkO-dtS<h^ym>?dmn>zNsCtX}gIa#*SDq9I+|}#410CVKl)2u|gn*(S)}nE-0G7AjZ+eih`Kuh)
+K@ph)FKb5!>B}-8-b_aNKqiIgAZ)K@o8PIb27?3`2}LtQZ_#(TF&M!z&sQD{F|Io1q4=X}gIa#)cRt6
+W$Rqo~tV+B9{3Lv2QXV@`G3+5aWorsANK{6^JtoF%QHUhByPn8HSjgZ$3k87fraAeGTHcZ4F}mlkJFc
+M9fGg%3L%7lL_pI*EN|4Ac!|2nW+3+ogff97kCX~)3ye&{^2@eksri@;fNU#F`TPgx+BiNinypn6F8d
+K2uGX|5oheZ#shIiG{JJjJ>sx?Dc2m1+twV`KMRS7F^9b)V*GwHOeRW<h}F^!F<wQClZo|;h<WcfXBg
+s)h?vJ=!7{`)nQ*S!8pNh;4PyPnT{FP|vG<w@{90W#R}sU-YtRsLK+G}30)luWk_jG&Ga_P=3y6sARG
+o8u)*Lo%YYyulZbDqpB4S1`;cJK?hbx*8D+Y&gFtHJDbMS%*-c%j6_TjL7nZvmh*PX-Co5OO`IE?-9@
+`H(GuU*3&#=%7XmpSU0IxDa68sdP%VQIgd!@26#9mKUE-b6zTXX+RrW&{&>5pn)t0>4$~A55&(TXhRr
+GO>`EI$khAD=Fr-A|?(y*H_J9)3)ZY{wZ*#uArrB`GW}@5c@7&E7K6;U;@w7VMDxLGj$8$FwYQY1QV>
+KYj(RI_fo1k9Jgh1Sgr$yOMR)%o5RaqF(Da#*f${Nyi~UVD<(4bUE{5osLo4uHkfd(ni|BWZEcA4Per
+!-@eL*z?{fIAm|%d|JDA|i)YZX+UocVROLg{L4(Ix)L2TOAAl5$>NhW-^`&s%_T`@~0IF5J|wwd68cp
+*#Ic*z7#i0xM-Iafl>Vbiweu>L9i<!0r}VfaoRBOzWT4*MJ8jo|P?mP{;!!`KkpV8T7=HHYK2HHY<2f
+h#6ByZw~7bZxUXnb?RW#7pqQ8B5o&A69n%OXvL7AU16`5yTRL7_TA5AZAR};e?nGOjL8Kt{6is86f6N
+)vahkOlU1)|4aIn`4VDk?X@Ai-DSc#lQoD<+f4*9cEp^Qn+uw%W9)yq?A?B_BhJ6u51y*SYbN}YiA{F
+Im6@t*+g&D{b5?`cwB1AyV@K@0?V4nOSU?a91Y*3)geVQf*by^8ED?zDwrkiC3kHY<1hH665N9l2E7B
+2@T!bUGuQxkqrv|ZUyNMt!)e#poSLeIk&nmsm!O4g*h*vb4sLtCQi+HO}+Kkva4>gEQ+Zx3Br}TZ-R(
+{b0W8bxU(S+$_6&6ht_*z}dg4iALY!XXIVhKqs86=jF#0rvFLJ~_zVhKr%cl=S1#1fKNF-R;Si4`QVf
++Us<5=#b&B_gqaB<5rj&=LzsVgX6a2#H0062okQVTlDIv0#wcH=7WU#QxdDB0^&Nj9(&&NuDDy$#Wzo
+d5**+FFl)R+MOocp)HcclHrMK62~M~HHph5asD^!I3&*Ri8&;e-XvzF#Dv`Cd*byXaXazE&KOq36H7>
+9PC9`}jME9pAhGl&v4kX+RrSOIl2||z3ttlBbVB4Ou|Omih{Pg4i5Z?)<oCp4Jv?zuVowsc?5;oVV5#
+Jet{{o4;E6Ym#HD&-0Z9yVVg`vBD<=dZF<d!OOgbS-^~5X^*Pgf_65F-J?x>XSiE%o?Au-1jV-nY%nC
+*#6C9$t3W{?<qVg`w^Cx+>ScTQX~iEB?>42j!z-ygU9bx$YCC9zmv5?3{yfQ#4|>4dK*W~37pn6VQzi
+7P;2yW@mgCzr&c_QdN>Vw_H35*IXM=j(|fiHk`m$|P~^iPwU}GFdy}6jZM#Hf=X?J+Xu&_TCIrLK1s#
+hKcu_C~q@N2}xYco)ety;W3FNB=L%_C#J;OYkT+%5>xAZB&OD0B(}R@x<_7<*tD%ltbe%MurWw186<|
+=uvK&SpP&#DV^8e=irspVnB)>Y@ghhZBssBrh&74hwwp*|PCCKZ5EG{p91=6q35iGyXY71mcE;%hUON
+Fv47dL&m&7ajvh#YS6Dsk<?y=M)j@xb`i8)_h=k1BTx1A`)6Xz#!ndyXtB<8&ByuqG$A?XCkMSOW(k`
+p_>v?j4>yNM*mo*0uDuVRB=*1_?_n8ec46Bm+BU{72OiR*MCMdJ1H#6j|oo!fg&;<)W5k{IX2-syz@j
+2$Gggd~PDb}*g5B!=sWz2A1uPhz||G4{m%YbRDTov2PuypVJvd9%amrY5mzTa#G-aNn_mp4flJ4yF^B
+#J-*wlGr;ZhHrK-wu#4{*gu_EQ4(i(;uR%v({2;*wy#NS+SVl2Kipk0y-AGM6Ei$9Br)8c*w+)|oVXY
+g*Phse#JrrCN8&}~#4Wo|JpDz~drjiFZB1hRvyeACmQP}sPB7l=V5AcQlDMjGcB~hPNnRmO{OYk|kA+
+7Q9?sR#&fw+YXt2|`ezU*dzdjl4A2cR6`;*4baHlaEPa1=J!-Gj<IBHDx`@_+2bfYmD+?z!IK0NNz{r
+&x6|Hj}`mj{zO`=dw>NATeO?Q7%R#uIyYM%O2I`jg>!^rY!_JUEE@y*Ah#>(0iFSH}B0(LdBBG@fqsq
+CbSypB|4U`(Zc9q3Pp3O@C@!?C<UA1A3u<ZFlg*!ILMBy?B1>%%vBvY)jP=+vl!sojrB={Hd+&)8|fI
+-hScI_NB{bp1a&Q*?15Qg!U?}Ry;T_-4h}n9+_5Utg5uCVl_ysL98~@YBN?_X|)xr?X=pC)lORN#A-L
+Kc4M{Ys^$icY*?#lL<0~xSD8VpoGZ<+HCjhtyD$imbEO%$%DLJMU1hpBNdug&PMQ&x>GGr*V%bZ}W{g
+$(<ViEgDqW*AqpZ?3N;AwVeg32wXO*r}nt@j7DrL{eb5)w>n3}87jJBGq(u}s6tI|Bmg1IWqcn5P;n(
++>zDvi}|7%gzLUocwJ(T*Ff<!Fx?t?g*PXta)_{gTnTj`qt&>m}Op$B)PNg>c$EVeS>_Xipl=t>agW=
+GO76Msw?U%4lvKPaDmx;~As5b$rTbQ61*tWG>cdhhEammD&=HW-il~bTo5~wv?k01p-GiS7)o~Xy(#v
+wH(b{m(iDgkY+B*R>#rI71?sn#|fi3=i~8TGwgBC$FCdBJs&5H=AMt=Fq(Tle$!~~`S>lP={mY8Yu^s
+bXr_IAJFJ3OV@!QJETY*;Ir_Gqq*f_A-w8`-rM-M7tf1LT8TpQmJ-aCv-_eufy_ALTgojT@Z~S{l&*r
+pK=DnkjKK)L1N9Ui-lx^?ml@6_xXYYhZ-|VCedpA7#W;^B9yW!DyOpU*7r10pQ=D3V|@9LvBlCkbx9i
+p1<jc@OUN8d7%G3{M_^kyWCWABDX-!@18qLIR*Z<|)XW2Erti8#j8_w?ACLp6@R=UzR(XEgWfdFdr1x
+|h%I8_m6Z{=jJN?YwO?_jdk6qb0$I;criWhA=f4_V)BWV1}EXazfi=Ge$e4{hv<{Qs^Q~GkUrS?VHmp
+Or+2?nCtN-X<-fKN*j`-OGvNslOim^{Dxa3>GKdvyCi7?o?cZV_0!&*K>Mf<OEATcNzx^x-*%DuA>TH
+?^p8l>^KhmFdhF{5ygB&?B(>*Pm&oYBo=$IM^ij@Kf0wkdhPLVM6*3`V4Q(?b_ej&{!PI}BH2q;K{bs
+mS?#1+gME7d?V-nrV=~WWl>*-HObe|6|-Rsavk9Npxn*(_CrGFz?pB8icTjSBdSSWpQwM{3F9==7+Dy
+pkF-&j{h!}93iKTu<Rm9^U>{|m|bEYYcZ^za`^)*tZb)_wHw9g_72&vtMAH|o!*9YKwMOpSGk9aG}W_
+N*%;GCg|uUt|cQ`^S_xqY9&aD>~+yoPCc}U17&mIQto?y1<SpaAy0}^>sRPM;z_n(Xr)ygBt7dIz5uV
+NwTi5YwLTP<gmV^k8hKz>+8~qefV7?>t}u2_WUNPy1uR*jIWWb3+x7S2OVwr(KUnd=ylt(uCPm^L1#)
+o_hr|f?hi@U6?V<(o_&kds6bQ7?4L=E$Y+ju_CKWR`g-(HkowgYK=veE=6$m0(f3aDOo1Q&1*y8eo;l
+ec)97m}AbWJOUn5nQ*E8iE(j}nnfb5y_j$S8KSJyMu9nvMPO#xjOhu<eL;)yBw@Lx%diZdl2nh)Yqn*
+$}NWV)fWKTyJyeE0)WH64X1_>gXE?Glu*6zJ0vq7z}>lzjLjQZ-!!ozed$H7t&<t3$fSv}I6&ihGY#Z
+QO(zhmYwjYvZ5<o#ihXwHp;jCI5s}T^!N-@IOe^#St|RKOj{XM-Q;WpOUIeqbJPaf0C+8lcwOKKO<F>
+Q&Pd-AvJmoP;E2}+EXZc(jL*xuWf~*$MnZ^FKTC@=&5l;S8!x5=;1p1h*Vu0J#}VuCu)DuqP&_eNo_E
+?^wmx@j*-KlXYr9$^+}_Yg)Y;`WY8n@h)AW4hEg;%e@?0{OqrpXnj1)Ix1q>_9Q`$^+Oe7rDCSa;;~>
+j%^bJz=IU_$k{VP)SIa4%VZ;={SMo%h=$yDS#0;=q9NY#}ErtOhcb!B9@kG@K(u8hp*>`#pvB@SeQXH
+>7YAuT%EH%W|)2o25GNYz$^o&xl{v=?cax+uF-QQAPReERpKMuia}X}ls!Le_uwBT}`mn#=x_b|v&Mo
+SFMnMYe=4nYT&Q7b1Oln0}j7T^4<=nSGa3eZuJT!t^_&>MM~3>+eX^Y^2NJ9TLN`=#e?Ko$9KZbYkcf
+Xlp``?dkVO46C9C)sdmTied%&NO43bOWP89l25-+VpJ7f-E<X2ri6~_T@rOsMm+i^iD6OnWS;(jM16P
+BUGOau^{1%0&{SzJVqC!EQ#yUxiqNz0=x>b}g$wk7@#qaw^{JwdShLqjjf$dc<u6H%Y^3>J?~@o7MMh
+@&6B5IsX!vLLSLq9oT7E!cbf)MI_$jIS#-h)tGa9NmYM=|~-;Jsb2;G?!14rR#i>i8$L|qjP^+zN|Mb
+W?i8L4jKF#9J`U3dI(cv!C<%L-I4UOMyKg~rLomEq{d?%>(`lYvfUuM8#^$2)`FC!+pzYI`u4Y>)c42
+PcoeG92xUUpaVMcXT|S3*7CGZrthL2><fjozac{{;)qXf205D_GG+0-rpJQZ{P0koy-&LrhDDKtq<j7
+()Plst+Vlg#|<a<_lDQ|yW4x?gW+U&cd)&$bLx}gnO?IKgdRF-bZao!+wLD+9}c&72NNAZpL}8e&LIB
+F{_ft*{<Xp6<ndF_o<8&3r_Y`{|C!HTxVUxc`O8;cxca%z_pe>w8N7Vs=I{%*c5jcyd;15IJ9oc0eQo
+;X=~t$2PQN~VYx?%|o$0&NA5Pz&elY!T`qAvGvo~fxp1l{2!;{C3oxgHvyW4H`wpE>F8?nx^>nuCc>M
+Xm?vb9!c+11XnP4{({U1!;KmK|%A%ChO>^-K4<<Z0qCTUeb;O&n+2u&_(6CeE{!)dSL%6Mu(#lk_0Tz
+qQ^Xz3C+2q24CF<wW42-XXp1WZ<FRCB5T>;Gy0ly_=-qTJMwIb8_%dCo>sm+ey82pT+5RQZL<WalW0@
+OE+Aca3}TB_{SNyt+z+xAE(^5-X4vA9CO=xdo=!0&fT%~_GtX0eV047-X4vA9Ch1zdo=#hcMo)Jy*(Q
+LRN5WtH2!Yft#umzRNx)zH2$f?JJf0XQ<-<D)A*-C?@*`lPsQG$PUD{nzC+zQdN=wGb!+MKgx^U>z2N
+YhBG6R$ZD&xT@S8edgx_|)CP(;fCuUONx1EB?6@J@kob2$Mu0R}q+c0^-;kS*AQ{lIrI!T4!c7h{E_-
+$uua)jS@N+uP4+sT(4;rDE@;Wvq&9DWl{>hL>KHzE9{Cu1q$H^JtU!*3FEgx^$ED*PrM<OsiMXW*YV{
+H9J*;Wwq%sqmZn{N(VPPIW5$rkJ~o@S84x4Gh0w{>qQO!)~6|-8`*+j^O)~GvIZLz5f?bO9KQH00008
+031s8R_91_uy`i`03-AP04D$d0B~t=FJE?LZe(wAFJow7a%5$6FKl6MXL5COb7^62ZEs{{Y%Xwl?VW3
+v99MOQzt6Ae*hy?B*mPA-cTX!(5?MB&pbL?32#J%)NNVH>qZwspY)es;HMRvvw!zqp1Q=rOS938}b2V
+#;weq=|pD@29b#|S1pG(!jb=;@=ro$KTOSz_YUEbRL?0t59WP9sk>(ctAhgP2&Zl2%Te(2m2Yuo3CyA
+SQ075{5zxO-`P>+Ep5wSMu^*7k1e%=+eqjp4&rc85pv|NG2v_r%uu;l|R^y{*on)(5tB)_2#R8s`6$9
+%>z5|LAbzO8&o-L#@X)H}FsGL#>m;3v0C9(&@*}oH=&n<m&MwC*Qkz;?yIL9&a6PU0rJB|LOD(wXU{W
+_qOiKK7Ai4P}}b+$;-=!T8Wfj*0$~_`4w&Jo{~SK$%&HpHF-tJx0Kw~c5+*jwVixc+exbA&ndarR`Tb
+y<JR{5s<xAXlE0vBtsUSOH90?$RLcLW$=a!UO_RGy{*v}5HTlch)>=4U(YDsY`KoqKw5`9U$=cQVx+Z
+IX@*A40Mfpul*8b$TG`X+jZ)@jU`;*_%<W${NuWNFm<nL)wYWLvxwLhs{ogZjhYk%^G+8I>p8%j;JYx
+W~0Cv7GFSd#}z{)r}cl>Ad|-|DD;rm5QP@N-SpPV1XmFlrya&^FeB`K5LoS}?y-a(*2<QvJ2IajG`{j
+doI%`de*dbr^4Hs<!d(l&ntDXiuqqr9Puwaiu=1?RZ(q&uN!X+w*npY-l_Am?p3AL61JJ$?Dk{eL|B}
+ETbEmJWxBishuTtT}IDq$F2Rz7c^PjzoQqmaMUFqeNy|A+SZ@acG6SwOND&xUG!hVi?5cgSbHEX<Hn^
+N%eb+Vdd7{dE#rn<&$zL*W!#X*GH%HAj2nNlo^fMq%eW!eGj42c88>9hxFK7{4cRho$d++Kwu~DGIF@
+lku4UXX8Oyk_56ieATgDC9GH(1u)3{-nmT_YrmT^NijT=X888<ezj2p6P+}MX@+}PMOZm6blBNWTHv2
+h*ahVPih4Yi(eV{6N}A=fi*$d++K9?Q6K+?H{}p)KRa)|PQ&Ys<JHo5n3n_iD*=JL*k2o^fOAu`=!^j
+XOxj?PuIm$hey{Zb!!LXWWn{XWZD>GH%G0aYL?^ar+rJ_A!oe<M3)3w@=3HFm9iWyAvSeb{ID-%`$Gt
+mT_a>mT_b2dd7{dE#pRzV;Q$2<E}Pt;jULp=K4o6ZU-vC9W`&pJ%x<h&$t&X;|_vK9L5cKoQ&IH+>VU
+9+PI<4XvU2YP2+|dGwy(>#9`bHRN~0E9jGK><JMd>7%FiXw*!^nPOHbbr;u@DClf>^j*PoW<Mw0RK~P
+D988^JAo^d-Ex5Kz0*D`J#NG--4jhio_cg8&h<HnIp4wVSMyjrqL|BO2pC&$gWu@lR<A=g7Cc%teV_q
+-M-y^I?hk7e9m#Yu;8hbT^B*Wpn~wQ=JxEaS$;rg6hz>Yx&baYMF@8+&fTxE-hj=GsJY67o11cUPej%
+@_SM?kS)WKjZd8C6FhWaYK%%L`K;xDseDw?4uszt}agc8FzE21Zu5}8ylO(jl-ywaaSAn-Hb~7j2pq%
+Gj4@SGy`n9tK_a`+<vHJ!Hl~}R8no+4pibWZa-8q+l(6_)-vwu;^d@_8@re{<947DKjVg650#{B+?vx
+(36=OU?%6>lO%^AEpb~7|1S)YDcax|D`<~H0Za?F$?kd4iPr0iEJFbOF0`ze^jN5@q{Q9{4PzmH&MJ2
+-1u9hv$y#S|4RD!L?%D5p<zc`7l$3i8J;^Y(<_ne{<KgR7qC60_6vT58nf8%7_P#Zuckb|QVILsIsH{
+^NCxPutCBjc_%?v7&Ins+tb#|?RA8Fvul#u=QqKJLXbZojS)#NI$x$;45K*8-gC;$(oXk`OB=9mXA`I
+N2mBfjm}MNwskcm%3UuDR1L;WZVu^;%D3rRN~0E{fs*ZD#5<TLM1^m?j{+xA1ZMecM!(yg-U{~oOBc?
+y^MR}#YqR__A%~BXWVzSaXX5W)r`BN+5vSp3dOja%(!RAxSM3$L5$mvaXXAVNXG3jZb!zAttZ#V-Jo%
+MW!yOGDHkWbGVbc)B-DlODhaZ3(vfjHj9Yb;=(f{v#_eF-K~M>fdo1I|)-$^Rr%B@uQk)EuanFo#d!d
+pLvr0l3cL2s6z_`6KZW!Q#WZZD*u~tqxj9U$v(*333>3}fTnO%T`1DyT>oY~2^9mWlLRu|wvt=CoJVB
+B*#9nfp#BrJNm(*a>pV|A5a>w2?F9Mb`@lbJ0}cG<W!BWZd8&g`HP$P--hJ_X|r!nm76C4P+C%eb4I4
+%i$jnaAQJ(&aj+1Zq80;xO(Ys090-e#Y%EZtTP=PAcQp9m9=Ef@ItdR1#!XNf1;LgmF8%N~VBH9L604
+l{hl)CQ%9G22hD3;|^imj*PoG<DNrQGOvu=G1k?Qar>c?YUA#x1vr{D%+{=uSez^yHy-S0+;ZzcV_h8
+!aIp0_V_m&aiJx(Mp%R}3IF7CoA5>DEaU(k)E8})BZU-uXJeF}|C(|D?r55059x$cpfD2~aGoNw$p%R
+C2PoX#&BIEWm?ui#C{fryIjL{AlAmjEi?wQZH{TTP;yGpt$<JKPb*~+;6PzmG(S@P~@+z5WGjC<yblM
+ds?)(tFq_sY1jv1Q!Yc$^O@VAqqH4(Q0Zv2pO?Bz&=njN4J1bTDo|<Mt~~hFE~pRbRl-p6aGQq%b=fc
+aY*F<TzwXp6^*&IT?$SlUnj#ZQRw28zwcg8Mhzfb{Mx`#_cFhI*eNtC$-0SN~i?#%o=x)jN4({kjFA^
+zl=K?_ar~0Fe}E5+j6SL?LZ}Py2UnbM{&~6xYf!@?K!=B+5sJ?1Y1uq;|^lnGoNug7<Yrl?LZ|C<Hpv
+DVBAp0$he_SYRUV&8n>f3iLIOXkb){sY7b;IZZG3@WZc+#tXU-v<DNosvdN6wQJkE7#tnH9j5|Pa61x
+cA4(QiaGV{jmmvK9c+b`qpvvF%r-d%6pevEr|P|3U+cY_(XpK;Gh#*O1>U><ihD)A~#R<{HC829W<2X
+quCgBZ6X;|_sJda5|7Jz{r{aYJqbl{hl)CXE~Nycu_c8MhxQ36XI-x=I=}?&^#i>ZCGmILuv$O8ksFM
+8@4y?SR^|<o_WBzjnYTjT`dx+W{TMJ@f5=kn0(@qaAQ&GH$4oGj6C0@F4}L@k0u&Su<`m9Z-8{f(@B+
+WZZsz+)ZZOevEqxT_q0V_RF}jlO{6mDHyk-j~j9{?p8GJMK|tc#kjSnBUr}mXWZC2X54b?hBNLU#tnH
+^Gj0bef!x3X9EWjZALAG|{@|pRygQ8BX8{iAN3G(d1C{tK!0|KgDKPF3#@$t4z|kIqrWfE$!MGh6H{=
+O+l{hkPzXdo`FmC+G>3=NP%eWmGx5Ky{8Mni@Ay3S>9T|6k;$#5ht}aei8+VY5JBV@5YsRgLlluKW$B
+cXC+W~{1k|r7V%o}$IRN^phM^{M*<947D>|>mH+||bIXa|hOZ5X#B<Ayw|#;tr?yRn=8$h*V0gCyKjX
+ew#aw;c&L<VZ^7*1p|<n4V<$He}1UAzQu;xz>y+$d+$IuJr*N$d+$IHhmka<=c?!d`H324Tz2FjN^t{
+i<CG%fCC0&`8Kw;d>gXm+mJ2ahHUvZ<Oz-{!Jo8z8?x!!sj5wCx9~h0w;w49l5j(g#x2kHEE%_BIADV
+_rX0rYm@!qIaQl6^tQv7UjJq0fR~xruIAC?c?PJ`IHg3N!m-&4F2Xeg+;5dvMTh|*7==U83Y+cK^6SZ
+(syI1cX;|`K>N8?^}<92+x%q!z|Aa1XW+hN>Z8Fv8Vo^;0Ts7*SI8*;tjfR2nCTaRVjkjMItg2T8~ZB
+n}_qj5*$UU1_M(p2JQ+&H`i$hdJBb&T6<s;i%II}o=c<Mx~CiX?xmQ6-SaGH(1y%eWQe*6zM&+|jrf+
+_)VXw}WvzGVTzlq<S3pY-ilnE8b@%<90A^hjBYliK8~zWXA1<O4PbZ?KX?P9esOIe0x4?la3Knlderp
+nv^&ul`L3oGKg<4vvF%TR5b2r+>2t|ehIgu888Imo_KB2tBc#Ksl;dbO*JWjca4>B!xzUQCD_UIzwz!
+MC6F!SR<%j(&WXkyjeEh3d-56gtdNob88;4NQivON*@SWXA?_xdO1x^5D&f{{ktvM^oLAqDUEI;PdEX
+1w#T`k>%yx0B(xi4X#DqI0+>2t|euGLvkP^RP+|>y;j-vrm;!~OoKuWxf+cBubVcd?M5=S$j!?^uQlR
+=EzFX6@kT0JFd`Hgnfqj5*$UKHc@YX)>=++OS5Cr?VengM+fcK}i{GhN(%%WoW{#9`b`HUm~8ZuPxM?
+ea$7j=sI%zU{aA#z9KFdI24zWN~@{tLKzd`?eq9b|l<>%O;ylxP$ZpdXbVuH3MoFG8%U@?r7YQ-K4}T
+;dU&WoX6ES)yC~ZN}4oozh#p_22A;tCLM^|t2EhV-`1{J^zG=|(YGPbYfDLhUO<O$H%7RF__kkZ(vfg
+Gmb=4Sr=M`MZ)?{k`gZi~Me*(VTznH-O863bx0Lu*Cg-%JBvA>sb`_#=N8?@;<MyjeVjtstw9H}L*tp
+gw6lS|J>9g9s!7(N9#d!lIA$quZyp(>rqi;vwUU1*`n^MwX!aZ?N5+LCoA8-c&C4LEakhy?<zU=@dj)
+dE5wL5=nQa`bC;oHa?qHoJ{5`DWd-)?ZR`#i3hYz&k%>Dxg%N`g$63IR%b?AzKYoD1KM`F8Z}Df_lpC
+t!mOC9}~9=;Pb7(@^49m~7Iwz4GmZ7rPrLD;jq+?gcUK`K(Mj#sWfK)K8ZAt(m+#DwEY~COe97YiA`I
+cQo!rG43FhNynN=Y(4GDWPp#mLk->v=vA5YYbk***84`VW6flc4=CUO>#dpeYvFc`1yra+3qKlnH0}j
+AZfxAZVt2nOB_U9WmvIL`B|hJp3}M_szI+p8vAd&(+mUfM_~o0FSG((RM&pjgz2L?j<dbDyizXX1?&@
+AZ>^XeKjl-z3+8w?#&LD2=W2||u*t&^~+rhXU#*LkfW!${lT@NT4cQo$1)3_aT0kP|GP>G{B83L7fH3
+J6tf<m=%SECZxQ3K<p92vJCDhV=P%8_w9ijxlGhFs6MdG(Ec<k7gJao?TB?U!+T8Mh<jZqB$T-Bsda+
+(EiZf}oNh8MmKt2SFvOIH?_CH125J3vS%lcybwcgT@WnG;XN1GH!UWY24U$jEoz;V;VQqdW;)ek5!z6
++{8D_9LDWfHW?!0?y7b`?O395N8?@;<Az$#xFL^Y+<wK$YU765fN?`MjT@?I+)!&7HymaR<A%H-#tnH
+a#_jlof+|jGe>56*H0}jAZofY65DRd;7EU_)xUuU=^>I5g?n(D?JB+)@K5oAS??H^)k#ReWTdjE4_a2
+Qq8uwxwcaTxsAy!U$Ex>VP+||bI$hZS6z^P{30luN&$hiF&_Y@|T_!)PIk*;DtS4+Ez#$9dPc=nq3Of
+Yt088_syj2k<N#!dh6?<#Q=C##Jc8;{ct=s+com6O%&fL?vv)r{MLN_>iw)qUJSR!;hLl{ipIlf_9t<
+MvyCqcU!7`)J%T<6acw_FM8E;xoYx<Mu)&j?V-`o|JJrP)TF60Ua54kgrYp%_?bf$-Be29kWWRjXO~*
+Ctr%jUF;+p_aYg$A1Y~ZIN&_aDhZHrhhW?e<Mw0Rvt!(l>lt^MabH_nx;H=e{NNwkJU{%%`sVO_>)aD
+-+iT}`hub@?-6z&|Tj$r$w>GzSTf@uiJG-s*&DQSr+WO}D=7rYo@bWJG`*}D=*S5FU*Deg-eR{b2<n|
+`X`E9my<>J|`jn@5_p4>dQ`{dg0`qt(Ha<^N<9op~N;l`HO*;ec6t?l#lFN(*z^<Zm2|B&B2N4GY2xA
+WboLleh+6#vvZv3BW_IG_)%o!uDTzw^MMrDG4DSn2gvPd|3%%&{XUSC78$$m!J&o?1P1`jJOZw+^?i(
+g_gBPPbc}l*cc(+r?=~Of@Og)Kt?#?U-t(P?t@0xlp^N+AY+csrCxBZ>s%5T`|>_LLKPpu8e^~TbAOc
+6s^e4O4$nSoRmBIF1Dp;g*KG3728Md<CH*?6P#c(x<sDg#0)Qyr#KmyvOLGBdGQi?l2bFrM4si;j4_d
+?IW@0eBF}SbMw!SHotjZ511Vcku1VR7Ql9P9ic+5K)Qa-FyuYj{<@xSdQOfh(p(v%_w4~P2v_FyBvZm
+c5wXUY!E47}c{i)RYn)YW>ThX*Xm)byS_uO|+@m#dE?e3S)N}_2GNKKF9FQlf&@t0E5<9L_U^f(@rnj
+XhPQq$vjx6~*O>5}qhT^?wfyi>bvO_R52H_<eCk9Jc{g9~&tP2Qa}a}b)mHM?C+llNt}r)l!0?DjQH-
+jQAXdK{9Pc0KO<E9pJ@_4sS4>DS}1)b#7|H&WBD$KOg#zaD=lHG!g*<?$Vnn)ng1EVp}DY6283OS?HL
+HG!s=<!%0m)Wl1CxmRe9O1Bh0VV3)a_8zH;AB)Q?h4x;liQmG@gF<_s)Wnb2u6&OklbXmMx-wPxd#Q;
+yaGu{UwLFf#Jmlk25@FyJoRC@`Mqfs8Qc5BUnCmI&?jj02)E|(Vh@vZ_{RgRuD7rG*(^8`-WVC0bMp4
+LUKPWX3MNdZinAF78=*ejRQEDQLo{aWGQWICBCqw%usfjpxGL8?+_mPOBC*$~Msp)sszer8Ls~&$`iu
+!H!uTs-*tACT4{+O>yO@GY)U21tCeHoiH=7ET#FJqIgJjmnd$<vJYUt7e{m%BR;F%JZ>;pNvB7X<eKU
+VZI6kiOjG1!&@m;7)h~Vjc<3;5syMN$_v~2SjmA`trJe6r#Adq_zPq4+imF#H*izkv9nE10ooCgKR;|
+gXzf~UV<j>uD;yxKOyG9V28*KL>_=MwgXMXvLbIeq$jkdd_`WDCn1Vh<X?FTnz+GMWH3)7VG+Ts$iH(
+LqIgtR<cYijQCyl8dB*<>qJEEEg{a?T{|!;U%dSDxZ?pe_sJ~7gzud=dK;O`mrxO4q5ifgK9q>mYUiB
+UPc6tS39u&+D=pzxY`DK8xeTaEbusdLnM7-$X9)KQ+c+<n&fIJfMs)tJhcqHOo-?MN>B3||#?DJKKA|
+iR|fI1TKy6@nSz6eqL$g~QJiFo06a6(>#D1H{pO9#Y}h*v(|2ml<3c;|O;@Lz!_BC_B{BHsEiaiEPvy
+!LVF05%fw-iH|jYb4^u50?ehNW`1JYaxw9y!zqM02+yS_rpMeGZOLg@8e(pE<|ApIL_B0<`KcC!8a1|
+{>Q5ibR!W70GuCeBM}(@Ub-L~Nl)VjZ$J}fZPgJIkpm<+%pXG(#(=-`6Ntj)ES{0{wBPzagC-s%T=kz
+r6b};q&YKYPc(CCwpoxUW>eNdp6R@T~B_b8TMf){05sn3(6OjwxlK&Q(#=hTzM!A3#e+N<c+(2%6a2t
+;`B?N;MG9GM^6C{HUWIWoG7Yt;m2m6v~B$OHqx{z^?Qg$$q&*H%?-1(Fs4Em69?^BL2Sb+>Xpfq7HfD
+G#pnL^rbL&mcrl7+O5C~qOk6}oDO@)lf0qzq{rQQpGiF0zKSjVN!y8bsodwh`qm*a+ngZA7^b6Q%T_j
+VSlwgOotD5#>JaKguE6h;koK52X>ftq=D3NJNylj}G?tAd4t**BtEQwh;+MnsAixFOgHE2}da%EEQ=*
+nsAh_LZ*j~ujM{u5oN;H@;i`4lnGzUZ$cJPCVVZw3|T~(^0oXlWD#Y`*YbOiMU*LD%WpvzQKlT_w;_u
+tQ;t&JnkfN@l%xCxWD#Y`QGOn>h%)6UKL=SvnR1k`Ko(J^9OY*qizquB<?E0|lpT)pyO2ec9ln<QCq<
+Na4Ik{k2${?VQQnq>FC_?pchte{>ySm1ct;-G#!d)AAQ?Egjmtpk2;P$ixA!3DQOX!ctcm<eYR^CuZw
+0A63ypqEN%1*|;>C?U@}Y{r@UKhynG$u72L$$+5_7P~XIc;kDdMaUa=;(D2~ngXIHczx3M0iIdI2IOz
+f#1x6RAkYqMa#m2W<H%i1d?0ijs7uL>>@)hEpeUkskj1%Me9KoH*b-5q?0@HNw+L0D{vdoD@P3c+-wP
+3zgn>c#Gj^2}2;E8NCKo1ctot&Kpq0wZgmp;07KZq7g{_?z{<ATrQ+!2RC3d1(Lu+a{V@BN{MB7ckmD
+!T;kw1?4)aQu(kGmf+JhR^~9-19zEVV+&Z(qd0}Jt@Ri-6z_n+FyC=5J4>#_oJqet<Gu&O>T)Q|td{4
+21dx~n}#@gnEC)Y0I^64jccGlN6r7r%J)!nVtt?l!}?bVBGmk$3i(rfN(^`iLGhq2}HBPZWm9A>fE?v
++dH=hik>FKz9t@2)>JT-_G9`f&T9LBH3_UwO3AM~A~pt7|*w*4I}zhP#49AAZl;#?G+#f7doHJ+XFnx
+O@1X?3wJ-*~{50*=Mr->{fO=`)u~P?DN^H*%z`eX8)VLmVGJva`u(%tJ&AGuV>%LzL|Y1`*!x7?7P|P
++4r*VXFte(n7xtxDEo2tlkBJ2&$6FqZ)U&9ewqC$`*rr4?6=ul+3!Ysqi06Xj-DG`AAM}}@zEznH%2!
+{&yQXhy*T>h=u@MYMla{5?181F4;?%C$f*yVS<QdUB$0=c7<qW);iN?#9(lOXA`g!|Jo0d%MIIh`cp)
+~&!<mw0;9K+!O+d2jIV4<dossP^YfdyqHqxQELS%b@FrAK$$o9Z&JIgvE+XG0Z-=mDk_5jrA7bzpMX9
+17s)z64*5BQYc{y=2eO{m1Y@LOsRz>-n`5VGufsD!-mTk%DxM7+QqUw}%$3qbxQsKmSQ+Zfc5k^zQed
+*J+(4=^0t1L>!ffZ^C46MVv504jUT@CkQufS`_)8!#N(!{ws%fZ^C4=pAJU5{{kR+8j!iXcsQxb>216
+F2snVrbL0!*d8D-<qAM!Biu`rEr5)T5FzCY0AnL?NXi(PfS@2jIYY`f`WkY2${SMa=RQ$%#$x!nPZ*u
+4Sat&{VJ;aSev=m<9dPCkfT4ua!Cda(E+>`_YH|mqi5?*?+@H@tCBh}6yMy9HpSTHb&+AZ$Z^_v1pgh
+qhyd`71gNLL~bgReb2QLnhQ!os>gBnGj7#?8#C!i9-Lv(n~`h-pp9qJT)LMMps<4_5m;My_zCUPR9`v
+bFVA}5Fr#flZeLWmC4iWR~_05vFAh)l!gN(E47dUKtRfv^xZ#&bYC9huo36fFp+BR3o2=_Q)Z1wF~|3
+Yd=kYy_%r<Q+g$gwjhzN|AY#ij*StC>1G1?oldIisYkIq!iglsYogEk5Z9RBp`N?lF+$bq$F@|7byvw
++eJ!(=5~>ikhxu?Bw%hADG8U`MM{F@c9D`$xm~0rP;M6~36tAJN`mBek&+O(U8E#HZWk#DkK08`g5!3
+PlF+zaq$DtI7byvg+eJ!(;&zdekhoo>Bp_}VDG7($MM{F<c9AmGd!7M9DHXAbl*GdAB4q)?ts*7CaJx
+vEY73iDq%2stRirFfxK*Si7H$<O3lwe@DG7z!MM^^9R*|wG;Z~87NVrv`O!YOqZ$TTBi<HE{?V^H6Ht
+eE;NHy%Df=Dz<MFo*(l!^+JX4pjqN;2%C0;L#sQK7&NQbbXK(hIw&K=pXLsL)L+iVEGdqNpJ9ic(R5v
+I@JX(CwN<g=-G3>QB9&Uf(>w_4LkzVmIFG`|a6oB;ZA5qT7w^o5aYzBl{*TvhT>gg%;U&WZ#i}3oWwm
+$i5440_>ZatjWGX#0~bXAh(Xb6(>(Ca8m)k@%s;yui)PJA;Z1nU5$n_<twN+_RB5heT{`PZ7P^IeoAq
+tIWcdW#TCdKKl;F+3gnHS${>FQ^2RSb=GBC}5gT}EfxHnLLu^9chz&HpAl`@#G??-LaBv0ViFYG5Zf+
+;sjo1L=3)+p?m?snLMr^?O1?xs^V8I3JMr`251?om@V9y2WMr=U;lo?n*U<q`WJHl7WKc5M6m-^9NZQ
+><rNa;bTcf1NEQi5Rd0HWKa275{oN)6@x3clFWhKz8R`JjS1iY&p#7KF7+>i{TEuv^?kqEI59M6>}O6
+cwjyWRqMX+T4+AG>fZ_T%%cBb>te&;;JLpXcku;xkj_N4P}UGmsUB51j6pN7YRgZeF!0K)#PjRh^r=F
+qeomd`5Haqs>#>r5x3j>MLJPhkV5$cw*#B~;oJ^v_J?yju-PB3+JTM!aMccM^oMghu-PBZ?Z8HVcxh3
+B$TG@=n#wJF=8WEOZX7my!?|(T><!1wZS{sPb9=PW8;%Fb>J7&Qw|c{ot#hBKNIYzI*{)a-M7X;IG->
+RFP2dT4OAVBh=49AZUYqs6=#z#g+oYay51WS)epu!UX>@@v^My3J!13H$UEo~VF}lD@r2$Gp?CxYrLf
+}zm2Y8u<cPrY$dlmHtk%g3c#aAk75F!DwS#PJRE<xFc4S+@RQ7TptXedGRip6L}2e?h_Mdo2wnTUIr+
+rn2WstuHOaO*SoI2XjBjkFAvNaEimUQ7Vou5A=~hZKSRMcPrSR2Aew?voLARk>xks<B<99Hn}RlYp11
+HQlOKeOi%bSAfjEZ&rQ#zBRh~&icN)-FMXY?V`GodM_=#|J1RS)zguBlNhOYq~4@O>K&=K&?5DY)H_m
+dp+)K)sdphxfO;!dVqk9tugsor{PH%zw_-eI(>F67v*~-E$C(&S-wboirf=qDX4Ch6b<;QVBcthCp&z
+sB8^7$$u5Ts=X4^OO1+(v)my?@~-@KgM?EF?}(QN%@v}m?|Gg>rTzhC4*D@N=0ZI+GJ?;G5SZM1&h;G
+S!v_4_8G)LXxE8JEHA{l3YQSoGd+t?k<E{(cc1{6_aTcMu!h-*+(7#OVI!o?fH-`}aJUMDPA)dS*6%D
+*|eCfAc&8!sDg-P0{_$C=eH>X#ciRpzQx<6bQ^s4d7~00_rkF2RNfZkl3OHoKYYio1zDtQ6R2v(FD$+
+<LVY&;2b*2B}E%JhmL2j=mO^`0e_1&aE=nSk)jWrqeK~msJQ~3xGRfJaE=nULeUCtx4##y;2b2+Orc(
+I4w4BsHG|tjFJw132gy90$SVhlvWD3ZjyW4<LpaabFgwB-_L?o>Jl(?V3FlcDW>Yv*U9&5kd;cjrvFk
+{KPPq_7*@<2Aq4dNq?+mIcIRiDYmWwunidhwe%u9{Dgv{+;Q<0<Ct+)j(mm*qmMUGNx#T7|P31@dJ$h
+AmPY)IW!AG}~5EmD*cdTv+EsYojNbCZhx+@zvEH>v8+C0t>X*rW=&CRJlMiY!HnV55X7Yz$gJ3c00D#
+!GOM0ENvl2~XI_Qlu%R_Fj>ul-tI;<yvHc#jUa<VewLTyvR}PVj^*IyKqQgywrwYHKnZp<92U8O=+`N
+Fo?XQw1PooC8hchO=+`>Dl{6!uAk79HoI0LvXN3<gr>CFWeSmrlu8dG4=I%yXiA%1QlKeqcKJYLAf-w
+HF>$*nKup}`|I1aVf4OQ20(FJkM4qO!+3;QD93{?PHKmP^c$uDe%~JWb5_R>b;bI35p7y5Ue~k7<8os
+o2;>gjXA3lBT`0-;$BN8VuBJqgCNsCB4B5|QbBp#7?MB+k=NIW9(LX1Pf<52L{T{#q7m27xAPA}0)HV
+n~eFgPkUY9L8RE7;t@Nu|-?sMn~0Bwf8+!;@nuAwao?CvH$mfNBk|DWIeP#TuR_LO>g}8gr%zmuh&L4
+DoD~YIq$6;cQfDc+CdUY%bK?Wa3Pv7u+9Mo<T61*ClZCHWglYm@6Z0Dlegl+!$)YRT{315X$B%4cA79
+WrJ#}VJB2}!PPUyngGeF5hzr2!Lx@74RLJdn4q$Ru^D9Y023;>;1<Mk4uaUs6O9gV2D@0IK?s{i^Ki2
+_6<lz?W6eU*0uFo#|Djw0$d?z7P%^<tl*gq|xdnHo(f-Xv7_MMZP60Ije>?_-iY);5T-T!M;9P^b!6=
+-HEx0#<u8Ib5)SehVQ>leVD{)6R5p90Gpav!zz!4#+E%krHI!8SIgeom?ZeU;P{>B?>#8XkI&SEVHD&
+~T7^#uc-in-uieZhdIVlFtho9}VEH`Q4<LT>J+It$7#d)%H)brv2T#Z$zIb;}5U&tRI$EbK0NJ2+Qgc
+pP)l4~`IdTdE}C24z-HKb~-da)UShd}4P2(oFSVf;@matysB5)Vtgw9!H?W5hzn1fx>u+hTvVR#;X3z
+`^4J0qgS@qH#XMKd4un_1-p@cFD)HAb82;Er8`)SQ&0*q!tV&bNsI71!f&BP_#NSQgx^Ao@H@iqLYzQ
+9_~VyXkOCPE;kk|+$mj^qbtFMXOL(q#pzA&1xxNftZwk-#E_A&sJlA{B^|tU_??c!7!gGBEy51O`>jU
+U|XLzo!LDyTua~-*-(HoxYc=(Lw@Lb39XLN_>I-WtJJv`TO{*C_d$1e|X{*4ClT*vu0I>d7w=ig`%&v
+l%Cqenc~asG`a@m$CGH@d`g9p~R@6VG*=f1^)4*Kz)hM)6$7`L{a72RQ#mr+BX8{2Q&}xsLO1G>hjt&
+cD$vp6mPrKyMh&b^ZlVYhXB!<<?uqnM#`j!vUI&f#J+&je+6JJB@+i3Zv@-!<pKe1H*YdxjrzQsjWFM
+9DLRo7|z3TjDg`i7N^$0a2||f4h+W#9Fc~U3Tz?~DHYg6CQ>S}iCm;qU=ztmslX<(ky3$;hN{>FHj$5
+%3T)1)Dy0IONJ&ZsHj$H*3Tz@NDHYg6R#GakiL|6tU>j6Stss(KDzFVIIzNe{mkMlyiq21h=%oUiNKQ
+%xHX0Ca7uaY(xZRK`5|mPtCnYF$Kc~o0N&~G$hEnP#6)8%o?^L8HrN&We2e&(uMUGPHq!l@eO>+sD+c
+cMwlv1a5QbBV?mQtd*L@cBRn(OQcFSm5}$~3q5Y^D@JbCZezH-yJ+nwwV5e-UYlO>-$rks4?&adDgG#
+;;`F+iK=3ncCo#<n2C_IpQX5s?4DDh+2^GnN0QZOe)NvJcn|U@tMq#-Vv@olgU$7^v`6Xz-N9Y6NN+b
+E14(}nqSG}qL}fKOfG-bn3cj6BLkL;+R(L12>T9(rJOnSpxDWS?_glc+d$w5%9s8hP)h>@6aWAK2ml;
+P_EuwXtW6#p004H80RSWb003}la4%nWWo~3|axY_OVRB?;bT4dSZfA68VQFn|WMynFaCz-rYnvR$RsO
+DDG01>yu$AeayI=uXc5H(#L6W%&mXUTW4PNaoyCX+Jm<N)Oi(@;E<JiUy<VJu5LP9RY%NPDiehO7Jb>
+2Bs%GsyScGXPJZ2OC?*EQ93s;l3A_13A=FYWK%ZS0Nr&ThUk+S%IOKYQ!WaDQtwIeT!^{@1~1vbVo`b
+F|+W-`(5YpERzGcW!Two_;VHT`>Rq+GuiVcWbnL>eOS6*15(fb`Qpr@hc<qr~F*w;`rs!_5<_Z*}2Ax
+JKOZ9=DEh@(e0sYck24{=U>>oc>eNpo0qOU^X$dOM&seBhWV#+uJN$Zc&u^e=O6w38Hac@fAUed)nxd
+mW_aFa_-AH#pTVDF&ASZ$JiDrirAhb~*kw)k8R4(7_8G&!IK$gL*3TQPy%|r7@HZLWW8?V}>u13Fd5g
+7gG5pI6?=bvr)=!J|{}nb5d^+Em;n{$V^Q)|%HtYXg)}BxQd#rt*wSS+@Cu{zXteYO2&JWly`D*x(bu
+(b?zc$0WIm7>nwdc3%pV_qWu)fZQ-(l^)F~bLJINxN$@3Q9KV#8;X`E54JjCJ!bteXyN{~d<&e*TS(G
+H3n#JHxxI{dZYE{Gs?B8zvvmf3SX7H{WN&Z?R~9z`EhX`60V(llAl83}^6<*uCPT|1s;n#qgi7ZaDr^
+Hu@&JxBtWX;g8(U*me2vKVmpv3y18wY}O9{j`h!G`H(SKo2|h^&R}dUAAXu$mpv<ojM+L(*8a1seQ!1
+ohm7*rbRIIs<E=U2@zKA|uG*c=<{>8@MpTE4c)D!%4?U5*`lS1prE(&EHV=H71LDVR42U1?=ZPP1K>W
+Z95<l>O_<<KBe&7M|179%lqkTa9XkU={F`sFOA9z6g=sqBR-~sUiFG&2r=ZPP1K>P@6p7=5PfcVi(K>
+WZ1;z#!Z@uPh}{J;a^$9Mwb2VRW$(S1Ptz{?Rox(SFMctHG^oq+h!e?a_*HXwfB0rBIy0r7*{0^$cA5
+I^vO#E<p?@dFQtAN|Y|KbX82@uQbC#BV8^h@Z#Brnw;TD-}PwIpM@FDgMO7kB2cJel)K(@k@$dAbv^l
+OT@2L{IQ51?dORfQ57V9rQ%2Pl8Rp<eo678pMdy*2gHy51L6lo79@U9Z9x2JpN9CAiXV6y;_uIRpAD0
+*{en&p+Lv>B@JIx_kM<><o@Mbq@RGcbcmv+Y^as3;_QiM~mo4b@059nDp#4If9yBk=`)FTK@Jmh)h7<
+5UW<TJ4;N^H<68soWIl+(N1iX*#3-W#}!4HNk>GYs|L8k}T4R{|+TS)Mub-??;6AAwAjQBYP%N9RwOF
+;a%Eyai*tL=mcel781nhO%Y(&CqhUvhfTO-aG8wfF_Wk8a9Y{9306-Io;nlEp7LJzC;NxM?hYE%9reo
+>+n(cuA)RctOFhBYwb(C4S4bMEvZ^$8dTC;s<=fogRt!C5s<;L8k|JG2#at5I-KeM8uE&7fSr-rKIAI
+Mf|{vIX!?25<iAnOz{IQsQA&oq~Zr&5sN>T(<2Z+;7Ta|7PI&{rRw)~1>%?Xc2g5Su6sg=Ka#~SSv|3
+cA9xyzUm*Tid%H^_{#aHI`YERP5p6{*ekrM^YQ!JM;!mykvl;O->Z}#N>t}_CU#a-<5Eb0ptr+nG4u~
+IkImM6J35Xx<tG%}?5r1OEuTAQavN<KiFA=|XZ+A(=54f1slQ^lzawHKyr$|}xD?R>L#4n}sOT>@Wc0
+!0>srUh}W;Ul}^{hDY3u*jlUefAODt;~T$Fh2W7qog(d;AjdOKJRQU**l+4$JD{R48xm){4K9#IIER6
+7koH|0t^`7V!fwwz-SuB^5vLdEy70Nb#p8eo$LQ6u&_HfU80LOz|_ytF0c_Pfh%8m^JY?7DN2ND^2{8
+$G<GaUladvte(M)_&K#j+uW^*f2D|j#W#1CMErPG(h$Ga>QNGZtb@D2YvPYU{E0n&%V9+Pyr)|6H%=t
++*NVSZ{O(>I;{aDp{4t3?@xk2=tI@`OQ4_!GXMKrZTd^S)@kctqRTF;&J^q^bSIO#Oil0$ZZS}Z*jv#
+(8=V}uFswjR;b1CAlS{}c$Mw^!SrIWh?@yE*QS=Q$6ik#f7mg3J@aZW}(@v1UoRVAv*yy}V{ah0sqqb
+%7V<?(CNIe{lq{K{HASZ#}~)uSbTWmV=_9>20i8}O1<nKAr=dHmXv4Y8^+YisoY4~QRlp*;R273a*@<
+}Ra{W7O&aUQF?8t1_Q7;+Jam;I>qwDsyV$$2b>St0#5I2B}D!VD&7i9KV+MCB-ih|FUZJNW>pY@e9OX
+t#bTrR<eOnNxX9Wv53EFR!=PAm#iL%_$8}HN&J%HPo34X9FJdX^+*S}Qd>O&@yAm9kq&UhD$=I?4h#B
+OO{+&)jz6)-pE2TRlyQucyFyuJsa8)-{EcH(=hPBEZcCc7%v!~-Ez2wrzohsDt4C7&=%yg?OI8p1FIb
+j2amj|nAK;RRU$T18zNF&U*6K-pa#te$IJJ6GD}Huzmr+B!te#~RX<HTImlQwnx>iql#jo}FfuD%19?
+9dE6o0HQF9I*9_|g7EWc4K8++|5Ui~{0)hehK3SbMv`6Y)O!PsIC}wt`>Wl`MYgJ1m0Wmn{BR-(k@Te
+oS+@y<Oq^TN3X}f?u-urSETP&u=OBc31q1yOPrr>-$^U@32VU-vS=+KJbEjyDK61Ggh&IJ?qCHej%wx
+>+}Gx2=S*D{IQaHB;pqYzvT2t<@jR}zhv<%iC<ZxE!N&{tPd|LiC=PhB;uC@f26%#$?4H%bFO+)kJ9O
+>)^}KPc7BUJ)5oaMwxqpXE%Bp$K>S#33s(Hvq#lX*BPI1nPLDRJ2l!$?z!i!3r7!Mk_jV<VKk)~+&`m
+MoNAr?<yRn=ejHhH8zeN06i(gCp(C}5R%G_evob1_M{qL}>isE0A#jhp)idp;;@e5WDdMQc#u`GV&-m
+cc-mxv#DH7Yhpd%I{~FsWxnEPlc20l_a;@!N-#h@U;9b;SnP&-xPo$=ci1W^)2xuf5$!#1Fh+Hm8)-B
+Po7~_$9@^BE&CPJxe0~7W)7fe-`!GoPyO;XLC-8AMuv7dL-hP4(_6#G+$m!eSRyB;+L!*G+*$+T}kmP
+t)9dlzeN18&TmPZyOPxt>-?71>d~h03m!k37bE`EHQHDjKYQk?r}(AK-Blret>RC7ehY9#6h9v7N+^D
+b_+u&lYMtNGDt-*7WI2Ax>d|`qlH%7Ae`3Wi5dV@kciU`pmpxm@Ab#cMZf*6%wR)6UJ<B5g)i}7jrdC
+fR#V-**+9#^fCMo_Ev3dmJ2fWzLUADK&o}qXp+5oR;8h>i1M>@9~t3+EQrzh6AU0gR!i8eGZmc}2;>5
+<a-rKBFIQV;NAY5WrJE0cO+IX&8>9&H-Gw709x<^*0cn-k1jDvf_hNj>&yA>wBb%Moe(lEp6&f2`V^X
+kSq9qkTn)UlRNkBYr83Uz^PtOYkd+Ul9D-bGx|eg3oV7%I1u8eoG>LZ8oQ5@yDvvBN4yk^u$Wzk8^%Y
+BL37xnP<Gu9*TI!w^H+dYQc~3m*jo)Q<C@5PeG$c;C=16U36dY_?DE#AL-mKhEr~9SL^UgypQ$)?*m`
+#xm~Fk|B?j1l+zPS@Jr`*ftTcc?bfc4#jiZKo0#{zET@O9{_1V*o-~JFB7Vu?mjr*s9Dd*nJ-!8a!4A
+Jf{7Z89fu~94OzrRkKM@W;@I+1z+uCKT{0NI5@7-csyOQG9CUdT9PETs5M<9MFi$Ar+uO)tE!3Lo;r*
+>;sa(cAqb|X1GlHx}<X%xRyupzbLubR`NRs86u(v^Cc)x%cvF{~aX@z;C1M-zYIf(_ce-P9JpWc3J&U
+$S}x;$K$51}*U`EA=eN;@4*JYZbpl{F36=mS~fRUt6$2+S?TrzmoV9@9nl3@v~LC`d?u|{}myAt<{q_
+i+{xnHUM61O=fLUk7V^EF4!PhJwg_Lti4^y>XB-5YONk^GUu|6Z^f~CQWHN*>S3#MeLa4xo`CrAEC$4
+n_K7xkmqh%4D^C1Mt4G+}jYa&xOD6RIPec5Y;*Ui9z)K$A(h|R<_@#5ZpuCmz_)}Xw>?<s66&|BDr$G
+Et8vjWv*dQr>Z8d%=s|Wor*6K-3{1{I$t4B!V*IGT2#~-U;gGBtwte(VHPpoSEsk3?{k6$8w$?B1aKa
+%2CmS{^%{5i|&VXN&3k6%grc!n0N_*W&3AM;a?_$9?3iTEYOAB*@So!d>E&MA5Psfk}u{1rRD6{}!_r
+1+(R4Ztg&)e|S3GcobALOpC%r9Zw^C-odH_)pmJtw?G7k@j|Do!gaoKT;ZhV!<yZ^=OZ8NxZKW{F2in
+?d_&MzNI|3i*71WsK>6KhmS6w^|kn`M*P4RTay`Z#Vvk8@B>bh#xD^++OKAz9^iEve@ekGI6Z(Xk;b3
+1q#m|R;wgT~>Ct9$VmNC?{921&Qv8t)?n;V3RvN!_a91M!I0tvNd%If2uO)tEr5-7pQ#!aSIX!Di{IR
+k*wTgeGiQle=hmS6YV_5vkG=AWTtRD1VlK8brJ-BYcq#iBtONw84ek+#MqgDJ`;ujRZ(&~w&__Y-qw8
+UR4{xw$oN{c@=@y~dl-S%S~-$MH|ye|oU>G)RFwsvFjzE<#K9@2bhT@w6Kr5^NOX^UUl+ST$t+Amh{O
+Xqgil=qh<_?5@EswMbaEQ_Dr-y@PaC8tLq{#8%r#5mXML+cXpqnm1%=2TYdiRJXfI=3qw-x7!)&1=D5
+CE{OcrzdB7yX-!uPwI)K_$A`6n&MxU#Sc7<;+JZ3O2n^K{K_o;#1_A#_<@(K&8Z}QN%7ajf2^b)>D+E
+wr$<WaNqu~a5kI?M@rp9zZq?bGzmWK~m3kss{L3oQ7RlmAH^r<TE%9rQZ^g>y6iT#dEA^Z(;+KwZ#j4
+aJ9p6e@sVA}GZ?nB!c3<Kh-;xwRnpfQFNlpBc)r0nRHs>!Oex=m|_+)=}aZQOI)K>597AJmt10Fs)|J
+6(5UsuJyB;wa*b5@M_CB?s<#IHTSRTF<r{L`x*vAN6A_}M(C&+197_?PAJgUA=0)uTMPD-ple>d|`qk
+v4agm3mTd?#8OkDOf%A=5EvyZPlvOBYFIZYjd{PXIR*L#<O~smDN+V&0WM>@-r-w;!j+Z8LMF>6+b4Y
+BGveniXU)I{2JodZtk8a#h=ac`1!mYLHxkWrE^MIJ-`cQ^`QTXTRjr-FX`Z}HmgS>eo67i%Hv1-N|b0
+zeSS;G>Zz@sb+CE>S0kNsR+O2~PrR(2SQQ)A)#H~GzeN0KUy%3(#UCr36YWc8^#CuY_#>rrO2ogUiVd
+~ZQxpI6su8n#nBr&iaEt?7k<vMVui1weCE}M9zt-xBRIx!iz!l5tiBz0Z%IZl>{Aiyjol~%S>U7SU_@
+`HmsQ3pn;%D(5<1;KmsUC^=Qy<`3b>i3N@dHou85VR?4UZpivCUmHuSiypQt_jkn)qwtk3{^f*#WM(x
+Y#pP(CWc$S!_Dzx+;Dx@hhz!zzbIV67ego9?9cJ^EBVzl01Gb@k?1fLOK4L_-o>yUNs)^cV-8;`1q@r
+#}9nX6hH9#09ORXFA#s#6hH7ftEVRZB`N;d0WLnycpkqtt0xxmW0(~ue(3;L;&e{!=5ED^U)tPFZ1u$
+2+?5o+K>YRQ?ovOs9x0E%TEssq&dJ9UkN2hXTd|UQQae4%D$XhKex&nT+Pz)v`7J4%Q+s|(;C*FP=F~
+OXw7jn@)uYYkRDOm9-531uV%2!RuF8B2-e-EBUAX3b*G~oYzLxiudVg8xcBPyiCGSVd>Crm;v2uC@hd
+*%^|ElwTtP*V}swi`dW%2VX=!svM(^J>xJUWX%aW#IaHm9~4zt-r9MEsG??E)`I{Hd$)D{FJsMVXgcn
+{%a!zr&m!-V>YVdTTc&@dK~7b```AxZc{Wi67K<BDQw%Itz#&ucv_cfd|CTviR9AYT|eO)Wq+GSrdPw
+CVt<2P5kbk<q<!Kydd#o10>kmWyze3Vrt@d{nW(ohFKGTqb7deeNFuCpVd+P=x0X!ubw*fn0czrl)kv
+LHF{~hGumq0x-;A#-kOZ|4;qs@!%1Unyw%v*ois-G#|M+fc&9PhAC7m%JGUE?(fx`0y;+$ThWq>D;qB
+4Ku8t=6_IDg?X6)d>-J84HjmP)y?cAE&8&1Z%J5Ts-cSi@V-<zZDUEA4i<CDAlTkePU);FGN4BQ{geY
+&u_Gub!Y%!X#ieS!YexHR0`vje(5ytzGk{NRamr>?(nZL^y<H?Kc`{)Np8&!4}#dHu@fm8;J@d$qCAc
+<92n?s}&)os%2)o6YH@Wb<e?Me}(ypQ5dKv^7QB^JsgDcIMH}6z$HV-6`6eM|)GWKacjO=zyaWAA<|6
+?ZF)n29e$La1h!p54U(1`yLEJ8+ka0?IjP-2ba+V&qtT}8P4Xz%ls5)gL&A`aXx?ZGC#@re2kf&<$ON
+I%ujPZfB!N+&-r|mnV;x<KFVz1;ULPPhl42nZ0A9gezx-<$}PXXf++obw}L4Be79VbUfnf3)?(N%d92
+N_(;n+E>@kmZ8TQK_>oM$CJl1E}uX=1S!%m+$J$){ktli`OS;-jogvWRszveL>$FF;g$MK}ccpOi8jK
+^`-V?2(JdCbM(N!2gb_JCo2rFNPO^UKs#iX_ah(N4}VVu2RJ{OWW^7YXxAv(sUiUzd*Z3G<7x(_@%lk
+sW?N&UuX8k2Ak<27({hZ+eX1j}4FU`|(>I<M-pYJ;v|H?|97ami7Jk&U?)Mou%2GVo!U_?kzTZQ|yAr
+>`qwIzqFq5n0>wV{WYHTY-!D`zNe~>d(7_R^!+39oX6}AUDLlDpZA!FW8i=Kf`{yOW8V+&cRl99@WcB
+(kGU}VQ|zM0To{8XcFAKljLe5|*<&`0%n#*?r*{{I@9z^Hb7A=Ye&1s@jDhd(s>e(i)a;svOc(<{0oO
+fbqsaWtc+q1vip)>wA9&10G4P}NLyy@g2L88y<S`q?!2kA-{p-j^K{NU%9^;GZPd&yL)r}h-<g4n>Jj
+PempL>iy<(nSkPx)VX%mmW)WAVH^Fmd#J7@m^{CXAl{A-(;YHjK>wbc;X}N6%yQ>TBA&k@<P17hluv3
+TA!@-6qhktERv79Rf`xeLvG<!fYh8PXCfXdrvaI0$(Q31Vbxfn=pG*nm(Mn^y)X^^!(C-95B()letTn
+iDux(y+@e6DKzfCBG9fbKSUA-RtEI^B0M0>#6piIi4&Jc(DdLv0^P&z=kXN+O)LW+^CwBJm{0~jl>3C
+4P-tyFAj~c>nuot8kT0-@1o9R3Hw5w}_9}sVjr}cw{8e(}evcM`d({&c+_>K-`QzU8#0Lf^{o`Kt#0d
+r`0p#BH^wb)>MYs(x!*%;@!Yvo{0e1+tQPPSwc$aV+Xa+IS?-6cer8R8uKH)Z8T8IW85N^ZGX4f4O?!
+ui-1IbRO2J+c7(39tO;8{QP@HthG&!&eSK&K4y+4Ru#J9Us_dImK8P9fx&hXGB$RS5$Ob3n6ig+d>*G
+oZ=0TA@GdoaWxig?!eWCf`Yh9FsYq$#=3L$7Bv@@||?ZF$n{jd?z3B*(ho9orGv%G6yvIPDZpaX#<*k
+CnZ{#v;j@NlM}63Tr~MkQnY512H|hxZO!6^^0)D}rtx0h-5Gh*MC;qaOU$ggXyNbkpCZ%-+UgPfX@YH
+>Z9+dosEe{s@IMf2g6!dXpC#1ZPy#<kppCCf=;sMF(RGkq<Ns2gS-H`|7+xdP#ujE7XHIg^;{W+auM=
+#dYa_Tf2sOcVFtj%bHNkbz_Dh7C*xKm#EkaFf#6++oGb=zkn1{CsHNmyR&je*wgygsz?+|LANnGu#gq
+q;mn22`?weLQl?-6QZYa_Pz3GF<ZVw^cef`C6D)Uhm~9};R)$1$+45o$u~;=Xy?F|*2~73P;^R-1G%+
+^-XAL&Md+L8ujr1b&l1`&!4+`4*u(L-N}Mn#j6gPFZF}N``BFhfw##;cEX%uzkCS=LvJGR@z~W@Z8Fk
+Hb(YcLhX{oo%kN1_IV4_%W^AOdg$Rl2{o}{#=cLWjSWrzi%=`TaEE_DsErN7{UM=FxDe`n$vopJr9UF
+jrX%BGKPJ?YCNB09LhX74`cp#fdJNsj+!+~IdOsu7o)p4xKO)o~d&O-#B-FkaFtYz8)Y7EC9Oy829!5
+J0QTs~pH<O_@HvhOX)ZVq(Blv&*axUFAJl>c)MMF29jL_Ulns%7+mOD*Di;qmu+$tJ+IluzVou0wNa_
+HGNw{oTv`l7ij(N8l>u4rzh3{4t&qPf*EX!!*KO=w-9uMujMC(thvYVR8Yew|Pg+5kbkL8x7lcvueKB
+-q7<o;~~KR=af3^IL>kDnS=tCe*~%!BoCYs0pr%Ir|EsHafI@hfot;H}r0Et5<qJ-zC((-GIJFsQpV1
+Zu0wtn&A3~&C_r0qzb6|@B@O~vc%XvB-s5mE?n7Dmm^%++~;5@6WR`a_0+t1d+EwE&t7b7G_H+zZf}p
+CelQtX-}l;Ra%p#KwEej2#rnbrqsivZ@a|~iwE6i{=I5uU`<mOso!j?@w=I5WIQF3Z!RBOlb9aAhw7+
+?GxVIr2#`E25-nEzAaLq2Bzx>>EeA70Q2YcgN!|lzz-GlLD{K{x^-x}T<&9j5N+cLD^8ofLk?QISZZj
+HyA+oOr~vNt|H+&&mh|L<^n@6Pb%XtHtINF<|&jP@}?$A}uEV2oZd;>0KsBRh=7FnYp>2cr~>EHE0ty
+ztH2-Mq@pd)vIE%^TUge$Bhqyjjg_)Vwpz3(~v|&8yG6=gdpZyu!@;%DkP-tH``}%sa-sP|VxIyeiCl
+!Mp?v;~RcAWNw(-(6r%X!@!1a4YwL1HLPhU((s`nKf`o}eGJtYUNIzM7{kzmp#t;Vn}^&y(&hm+Ppf$
+}&2wlTI`e>;hsiuS<}oqPgn0nWYBx*UtYfoi%?dTk(JVc)%*^e2;?(~GP)h>@6aWAK2ml;P_Erp3qb=
+AQ004}10RSfe003}la4%nWWo~3|axY_OVRB?;bT4dSZfA6La%*XGXl-v~Wo#~RdF`F)mm9}*#lO#Afl
+x^#B@$g#jg<)#Q<N;y;-YYIV#o0W<Ul0E;b4LRCD9Y*B+lZj&dKI1){$b_vAimh7s;`d<eUNZf2FHYu
+eut#ebVn#SEB%qzgW7$H2PIHetmK4RpEu{<Zf$!ynk~0rP1EbWP0-E?csE1G&^~4L;uskXtqC{+!#$;
+<GcHl>8y2iymxDN^wj;?=xq9*ua0IHCp)9vt*u8|$*I=!lY{YW{L(1>H+8CYVSHz_dq4eWd8&1NZ<qc
+}oN8Sf-5O@E+q!oB%5&$hp4+}~=F+p<7cW2k%!StJ*5Otw{hvw?c-U$^(t7mFqnSXWcw$*idRBcZSKG
+OI)_Lu~s!uz|&DCdewWF;1Ddz}Xt3K<zTgR&BoFnAtdp=jY!m6LnRhb|6Ip?_fnO$(sH$TEf=e79}E;
+(vm#brnBTlINIZCmw<Q*mC~RY#Rpz2;P$tJj^^=I{0yXB_e~`%UK@@-h3YbKJbP&pBgus+BCnp))x7D
+co?>{1k3F2S`srEz}+7wf3+h=cV}pUT|KT-eq#3-g4BARc||^V8yZX(tOBYblyzZ^Sa{<f<3^l^V0mV
+cb!qR;-2%;{6bEgGsuT_KUed*rn%U+;z2GBtT=PtDnEgH&IsgJ{3WNX{FC~!qvqrNigVojlHYeq$dCI
+)=l;s?q@(wp1Lq??|FR?JpQ-s*9XTJf`D>1xe=g^5ItAtzWB!(NCiyKnf7^Mrb0+UOHRj_n|Im4Leu5
+9)aISQI><8~SZ<(v_Ixo(T@zLwfJLc7VWDfo66WRZ1wjM5{m5X8JjbYU&hGnA|mJAF_ZwyNYhGlgOD+
+Y!Y#IW$iuz(mA2*ZMbVSz9#8pN<b7#0Y_0%BMN!mxlCmNj6Q2<nAllB;2u-m*CiON?QXix_TO3_B2Q-
+VMtL+^}R|SbAev26DrJFwAkov0_+33`>Mz1u?7;h84uHtd3#jiQ%MC469f$%yYxFU|2#7Cv~{t0b$t1
+<%VN8UN;<VC=tjFt4Q524kZ$VVd0BmUpE{ol&HZC6a3aKlpx+#a>MlEYHk=~SXm4^U<`?22{9}h#c;y
+Fu=K{T*aQqmn+-z@<7`+~$8b^|!wJN&@WilpHY~j{tRRL(4Q{v=43oU_Y`6|LtQmN?jKFdXONe0!F)S
+Gv=48VPVpuXTj6(?yhH)q%A%+#iFb*YfHY_2ACB!f%lu*?%EFgv@#IS@ImI%WFVp#gRVdaZq0Wl1-;V
+_{@1XFa<-wpFZ2^A2-bZjp-j6(^<!mxrE*0eiZhMmf9xk_#rW7t2GP=VaAVqh4D5{iLgPBzS$qQe+gt
+9Qc~!!VR+G#kbkhS@O2Fm%Hh!`KbW5N_B%8<r5mIFw*z!zG~vF|nE(rh_bDm=4llD8a%o@wVC&U57C2
+V2$gBIiUo`Fm}Tj!_wOgV+{LG(Qz=0LkYDB7+(Dp9d^UQ7sGIhPB7ds#4v1F69~g15QecE4u|3Br|5{
+Rl`u?Eg%5^1wr|)0*rrd>`MY5OF)X|>EEpIT5W^x2h99yiI!31i#xQonFqD99n1SJD8`kQ;Fu~6Y!#p
+<}dBd7!)!{O#j+bwk^F5xTTa1|%D`mq1VwjN)dt(?+(J?TL-LOCy4%0UbLkWyw(I|!m2g5|Ujh><_!L
+Yy>Cb@`VX|rJmN+B_vtQm$?1Q=GU$1rxo2?N6k!mxxGP9TO8h~WfbIDr_(eZz?-hB=)QFqB9Th7*M0g
+n{A28^gF$qK+xLcrZ+sdewcyZQHQs;wK=66$8T(Vi;$`F}Pv1W^S0Vd;_~-4u)aFS|B$ZC>w?t=5$I_
+&xRRObfMgE;|*&eJ0(g&36g#KhIyS57{khj5)Np%oe~@ji$>kBgc#=Z4aeYyal=}pZWvF|DPK1nXio`
+@VeE$Co)S14_U;?5?uG@zu!0y4HANSB-*8fg8?GaisKpK2P{Kh<^PLiSiY}BJ_Mf7|oe~@j$I!6GaKj
+OFN-&mh2nL3s8<y2E9L5bp42wV*#tmz@Z#bGxiCWw+55ug6HP#ee+b-X5;1PGHL?{e%8rC>&*njy32g
+97@8{Tf%8^f`7N-$Q@2?mA*!m#kfaKxPw6f=ataL7)Hl2C$x>$8}-1jBv8u!D(Mc34|CH|*ax%)u}YB
+?4i1b9Yz^(>JWv3BxKBhHF{AQHvW6xQdRfv)A&CHeuKS0vE%fR?%TMEW9zy$%g&iaJ+rP-k}6;SYxcB
+i@*&-414ztZ-5)FA(SA>MZ0_>;1nIp4JURLo%7L;1;e4-Fvc(rCH(t_Lt)rIlvuB9xJeA-Y#3rVOy4l
+XFz%Fyc)#J2P@)z$%$uSMxO}5zijL)m^{4!B`9r=r%QtYR1Sgb;VfjV`eZ&5p5^(tj#;}4IR@E_#mv2
+aj;U+sJ6vA-z{f2R;1jew07?u#jc#1CaP6=KpL2@-WTnB~)#xTiCi<vEkosV-YQ*_u3`-c*efngj<a5
+^R8b;I5m#%`DqN^smT1H*ybaD!X>L=Z|~H@v2u5+xWeal@=^nAbO4;)d-Mo%6vh?;FMqYyP1GXQNAh4
+0E#K#M=#H4C79Tjll4Fg%YB=8(#Gk9S$Wz^$o|;utu+5eWwJ*a2=sU*EXy<AJNSTB`}7Cw;OIYl)xBn
+G?Wkw4C7D&Vpv3qVF58Ls$&?tVNVQWH!K=;!-9ihqFl70L<xok#xTkC?<vu?JFGb$#^$H!IBpnE(Mbk
+|L+v+=G2Cq5@Oo`@*=VN(&W3$Mi3Z&;#_-1MH%zat=7xC~4(NtUFwEQN(ypR&K6b}$*qrY}>4p`;Fzy
+@14QmWH90<dBF*C+6!wpM>Ved`}i7+gyW4PIDc(dGa9aD5A%QskV*v`<oAF%wvU%MIRY_JxpUyVay91
+S-+Lzgfp>>mv?DD1t#8m4fd4b~D!Va5h)FdD{<61Z(RK@|4gU=5pLyuq4cP&i>wST;}LlD1)ztC?YHd
+TXvx0-IrFG3<VpA~D1MjS~L-YMZ>Xk9XT}qdWUx49n^mX6$nr=odjDhM^f&2*dvUYMe}hgW(mJVczPE
+5;M%pBrt|+*<j5!N;sdIkiQ7Z+2>M03@eCXPBhGM!x+QZ4NHh&|7aMu4J(LYPBffU$FPJL#+d|;hT%S
+!5@J|F4C8(^RUN}PlL+I6aWo9uhJD?zgc!z|1a2F~ZkV&(a4l}QBpT*r5+!c9WGyqvKEHv)bHkJvFJ%
+(8QNsOvY|K8F3Szj~el?C8#uyIehH)t2?S^sNFvAUF3^PIr91Y`80<PZhcEdQ7sE%QV8^)nTC^sAs!)
+qE1*W!kW!p<i_<u`Ke8~fmB7%$%Nr!Y3doW&cVqG3+gaHwe5JCit$h9A0UI2sD`GKpxS;gShDn@PAge
+I(IvC=9P#G#u?xW=@|3!wlo4%o1W4M#B<fn9;5lC>n-l7)Hb1nS^4PVT@tCcw@7o;aK`4^!<JKvD<sY
+G2HC_YRzU6jdl%lFf6NMSU?QpXc%I+$xOm~DKp$r0%j5%H_XW-{4u<)nFPrz&m`>rYR-+k=@|B3ywR*
+17O}cv!N4$_q4WRk4LC!`!El&H2^>m53|9{&IMFb6!<-qq$lY)>7_K9fuuJINTb3CO$4g<{t`=&74);
+m;n_*5S;omjPpm3meHJnMTRlC~CqhSt(BblJ%^-1tHlqjJvFB-;u61A9NyXU)ecW#auj-hMVfAL1MeG
+;-dhH)n0-6!E44Re;z`R;NVCX)zchH)mL*3k?{6AjlgLnjEs&V9H!7{-|d#|_6YL)YvYItGS0ZkUlt1
+nL^bZa7T48pbem!_}i<4u%B-!~TmmRuB!7kqyx(!CJgg#~M1D3_EvRNDAY2wPq<S){MdtGz|+#VefV|
+ymo`ruI5c)m`O-TVd+cZAZs`95<34riHBhcUCG*w=FPB;hMk)$<l2pO!*H`}H~h^o2g8i6;o}V@>gXC
+?IfgkCbdh72<OZYRaAw#h!_I9K_X;}6pzyk_pu-f7wrRN06?8a~fE32baHJD-)stcW2|8?saWWh^g`+
+XUbu<l2n@PBLOe9+kO9qBH`$=F7D~MqMF{~hl{r8i=7#6W&SU?Qp{Uk(n3=4>10WmBPhVj}BjA7rk8+
+d{a?<XM;hT+-`fiNr>7#7|b77)XVgJDADy8Rkx$$k<f`~2_*-cLf=t%jX@<9LG3oNpw*1{y7f8(q8M-
+6w%Fi7*%z5W_H&fNoeK49h?m#uIdr_et<DT;hgf>65T4=$yMCmLCK4r?7t}5yJ!>&Lm_Y3VU~}VG1)c
+2~6R&$|M*RZn9~ZLt(tR8m90H+9X!cG>j=+N7Jy~PQtn1u_VJdl4#ZoKYYosce9#zGR&cHqzmXUg;&0
+G!=J)<>Bb7Ya4i&WzD)wp&kcye&b8f~M8baoUA$g60t$O~NpMzfcvJYH^1=y&!Z;Y_c;R(TB%*0nvuz
+U2W#s<)5eLKm&1#%B35;RkZHDpu9LBK!0=j0K)fB>Tqs?lZb<B)rH3o*ohMHjoF)Sd4Ic*Z_x~We|Bo
+T1s2F7q=cN%ss*ygxl|4ia|evaKH;q8WTCLth(1;Vg^81~-clF>7aF$~u+!#0Ts_Er;dyWv_g36fXct
+=6#<bk3#ObPRLcu!t7Jp(f}chNU-#MRhmK!7yx-z!(<QF^t`?Kp2(`3=4!|fiMi)Bm~4T-f38PyI~H7
+*VPTz(I!Ev7l!Q&opTXFVpukcVgFF#*bTSJ7cz7DB;a-ucp<a58|Gxgz8L0ot3eD`cf+__O)xObal?^
+k!_i>4jy?%J-iIF>?noLXLScB_LWxlON#JZaP`jG<PQ%_)bd1f_0!`6X-&_s4;dpoTSpkMOYKl(TY}g
+st@~wsy#4uh$ryz#$6dmpwRuIDqVwkgpj^l<oQ*;Vqn6rdVLJZ?6It4MT7#LR7F^oeAPQMz&FlRrBK%
+1*Ersx>iFkV6zq*DUB;ZWQ9;3agmgc8KWB@B~e^>V{>?B;%wnHtk7Eurh$ZGGG!JPwD=`9>WMN03Sgh
+8-4&!+}x>0XZxnhlMAH1;Y-*R6-yQ3&ddoIgI!9@lPd0+;+H@RD$G{hr_mG%^j<Hwv>?G91gXmL?{m9
+EhYS0)-Z?hBpqk7VeE$)9QIzzEEpWdYndU3u^+}94wDY!oqZsOVJrbT%t?p+{cz(PF7d;)aG1BH1dGG
+Gbhu=*VY}zMJ18MJth_mlbBR!X7{|jBa@aqYSThcL=MtF1c!xFbJtZ)QVLZ&>aF|?z5f5Vyhw532W*u
+F~T!Pg)TnmTo4r^}p&F2z$i?vX>gbd_|aV`<c593^d!(m1)ftPULT!OL18mDQE;fK9*2?;qY5r@Mxtu
+g#?v$;ea942$xAcuK=xP-$vALiu}B^<U3n%y#E$%jMjE72^6MWY-RtLHGzCA>K-8ssqc!;E~GkxNwPu
+-Fg|ufPwJ+}s+Dl6gA9^U_i}J5T4<bNn+%=6oY*TjT635y%e<$YIWsW=1Z7mo#HP%vjQlIn3yn5QxLx
+ZEG->V63GRki-7@@NxHWb8Tx~+db@_cr1Q61`a=bei-(xZGs=h?ZXT|yy{#6`(e&vy3O~)MAnu2VHSs
+zykEjO!*UKw$YDHB$Kf!}hdKQc91i1U9FoCdJWq%FCH(t`@iGqoc{&D%Im<Y3J`DRM0xjc^ki(4CbP9
+4f%ujGY4#WOooDcgi<G>u2ki)otxP-$5#SlNi!P{G+WS*{s!>s<{5)M<NaHV`$+Px**Q)&LEkV5%kyq
+u1c566&8gj!DL&0&roW^fqyOJEK|Ka4r-y`0W_k001C0sGb<hdImXaKD7~_QTQS62$nGFQ=<xRdZtd*
+4+0j=P+kIT_`_{In3!F_FvY_Sx<-iB{+R+91i=hrxU&$4%9E<ol7u&3yI-}1>`Veo=zeTGjfSgei(C@
+<%bD#A^b3p!#qD+(l0^8t;AuLA8y-x*gbg2{$a`R!<==^oLoXMIIJLt{c{QIhnvkM7#x<6!`}VFob_~
+g>tV+B5;&J&^bf;)82e$&;p+2r3_mOw9On4p#^>pXtRdDlm-MZb%+r<R64(#d@jD#$mqFd5ly5JAF)Y
+08FvhTd+nVyW!+3iMjNwqR1gBks6H73*muU3oknr{r3=HFTiHGXvknj(2U<^x$;mCJ@=f%S%u|&xZ@T
+^#(j&_N*jV0XI$6|*$%jr0=L=1LVdD~&kVShUeIV>0)#_=$tZ4Gl6#}eM#{J>bk+YU3P>8iJ_VLOc5B
+{)Bb6t^8N;V{n*m&6iv*x`~`qNIHoZ}TJVGLDZb#lsv9HyaOgVhQYr738q+<}fE7#vB%q!~U^^gdAqX
+!<=>r7!UimOGw0FJWVGchhZ$?9S>taTs@Z9jCeR?yF^JmT++5yOFYbKmnh-z$76|Cx3(ThZ{>6VuJ7%
+PUKsC<c3L-Y52wSMv(faRHM>2WwRXlkt-Z;tHF{-yFl&wXTC?eJyf@yv)tZf7nPq>U7I}6!osNgMMxV
+Gcn%$f3WpX-F2lwyZnC!M5+rPJWb9Qey8&CEgH;0{!4zlCk80}8<!6vPjC)1tm5A{9Nda^ah{v|E`>|
+}2?O%Icwnm+Hd^lz<;!~K1ILf3{jc1MpLJbr5H{MF0b{eEY#J=nf>{mOIaub$gJd+yAY?Q55}FJF23n
+JcZ+t;1{(^exfpEC%NDuL!Xi8d+53LRCdoE!3o_CJVJ)RND)+Q&c+(wOdrX3$<5NdkeK+RQn5c;Hu^`
+Dhs6<M#!bg3_j&jX@;M&P@AEITq?}~R4&zK2r7%kNgCi{b<&KmES4wD5X(VPHe;-c7f+f&R>c~n8D&+
+hQJP^^#p@@{IICin(hRgJRw)NYUaHbOtJG4JX0+8(m1eZnQkCX$l`K_h#yeT6(u{ZFR@pL|TjI|d&8_
+c*(cI!5F`8T1&l}Ax>lcjX*7S=;a|$}~=!q@DlYQM|=Ck6K^0?95I)2G$ZXLgDG`Ef?jONzyq|w|uP8
+!Xv;}b@6>o7NK+r2R6PVKmLnA^1D)?x0^j#~#&z^%jFogKFhb8B|oI?R39aqBQQWyh_<+>sr(j#EZ+>
+-ZJJ9=DEPHJV$;X`{Jy{F>3+I)2?~ZXKUAny#bxGpAi`g?j}@-%YD%_X>8ttG^fz3SPdeYZw%ad@n7b
+Q*`k?Z5z7<3*So%Xm<+!y_cSUCn=csUV8f7qI2(Qr`Ijm_Fj7S?Lon__w+R=8ung#_U&%Lt@qNiZx=f
+``svxX`vsrgPtU$<4*wfQ(r4dZNXEDKwJS6Q8Pnd^maLeZ^wYEN6zzInkG*+E<JJ4=*>}x(8Kd4$&%S
+F8|64}VXK%*K825o5dsCxv?F0Aj`E8>W*!y`Sy0_2o7|p$XzF;)>W3X*B_haz8M$5kr8vYLShoJaHVW
+96HQ#?K8gtkn@tVW7F4WI{{&|kC6pVHG!=o-vTdyBNJhJ|*Uw9axuBZV%(T+$aw(<PX@=niRV5$0&SB
+xy5O{6--4<K7(2KI^q_G=DlFO<xIf!S+c@i|Cra{XNpsB1~QM+}BTdQ~m)-X$|H^CD)Nf4CY|>NYkI=
+;-W&SpXnX*4lk1n(RY)1i&sd~MHJhoW%ej9ejAX5=lCIs?(OvZB)a$0t0cNN)E|&oe17-ns%JAVeL;G
+kOidQ{_6AlbSCjerUf=3uYqFrT*Ry&;y1vtTU8}cA*WW#Q_I&ys()IV9Ufb$j(lxqziPd|g>#q(yW%W
+Mk`r7rR)d!^OdV6`jL(+A<-Mn6Mli7EWZeA~a(6TQw-Mn7<uw?;8H?NmIaamB%&FiJ{&q9o@t#?4<pR
+H)=+Ij~x{#k6&we=2Y{IdY5YwI1*_-D~c*Va3r@y}MabZor?8vksc7Lgx^#y^WnI(8feH2&Ex{~bFH0
+~-G<)bH4F7|{4<-)Hmta6sdqC5WAT9BBNrNV}7d1C4(+E!D}#fyO_ZnCj%`Z!Nv9SLEkoJ-x2CW5;Jm
+<DY#ArU&EE*GbjY(j)HZO;UBO^t?a%2C2GIdT1VflT=+NJ-m<pgH&B5Jrs|=MQVmn3I*OGRaZ#QuA^_
+0s_UcY@zHmTs{KTIs~YvYq-M3zalc2Zu8l0p(f3K!wI%kt4{4mWyO3mij@~9!S4VE;=s!u-Xr<!bAu%
+nExO4O_iD_*ED(#0PW{(IOvL6|>pWUdW{+Lu<T0-yj6H>F%=(z8Zs-G1kzE5IS7medjNzLk_ar`e*^;
+Ju#hM$qDuNwKfqYp^cSB;+5M<0@^OQVPG(SI9tkUhj{6#s`*T^c=%kN%fbT^c=m=YL45zG{NhKO$8>2
+x;!}OC+YH4b0ij|Cq$IGJ^m7Pe{~P%)I~nPf5(`qJ#b!srrdXZ*O8NweThsA^kb2X;}j^F7v-2F|BGq
+ul!3Aby4Jj=6^-1zF=fm=YLJAu8LmzHzexoCFoqgLaM%Al8XIXQnhC^r}f}<67}UG-!%U_qh`}k(p<#
+(-;=8ABJm$c)K`lf`1~J9)rFC}ng0{1X<-B=%J`HvE&~$(nM7R|8I}3Jkeby+)&47~`g)N=oc|lCSz$
+C@Uo&dvVd%78BQdS3y%gao?P3Th6xAthWBOF<8ziPx^=YvGoy4>%dM3}mPGVXWJ)kJHRNBUn`<Q=&#I
+z=Q)X%?3Vp>w4>NK2H+P(DY&%Z^Y{)V;m>px2S7P2$*Z<DBrK^1+6L|qXL{&z{#29u8YJrc9)M0I|jR
+9zB{@()PVx8G6-tF%WM(AyihDs51RL6o#A?M}#?%-<zZ-+Y2b^oOLTHId(%|A<6g6aD><Nz@P&G^9Tv
+ReuGezkiR!w59>o^gfAcO?|5ArzB?2Wx6DWtV+8OGL7?}k(d@mPH+AJiJ8AN;)f*a>tu$6s?UsvDV}2
+EEG|yJshB@cnfmG$%3Cj9e)^dUt<$Zm<GowEqo?lAMmn&)I+|Ua?2L9F%Z{Z3-Gk9=dvADmboxYkkSF
+y)o*bN5OcCx5_io)A-b(+|wR_V$<Ad8q*MGJ>n`}>}JEQ6L-QoV}|1a+?9&h`uK84ft$_r;MJ-ayF#m
+i>*_s2JfyW9JdgYj(q(rA0CgX`1c<e(?gXH@o@JEPJ5_VD25c)Yzkn(0XT^tI`|(c(W2clU1(Z;WQAP
+n>z`?9<PD>e+MWKmFW=i<d4xf92}6>!11T=Y}_K?u=fzb$k5co!z^8ll|$z?A}ZFzc~NW{LAyN%)dJS
++WfWooAbBkZ_nSGe=z^>!Rrs+c<|1HcRzalqc_qaczo;s08mQ<1QY-O00;maO7>QuKO_ju1^@sA6#xJ
+u0001RX>c!Jc4cm4Z*nhVXkl_>WppoWVRUJ3F>rEkVr6nJaCx0rYjfJj68)}U(G|Wx7PAQA;3W5MEtV
+mnE=FF!*-E)wlq?2&%0j~(4bHN^eoyO-0oyE9$kKG5KK&Xo?Mh|;ht7Ln2O}B|oZe{Cqw}Hb{ErUkR;
+&t59|XBt-pkMn$We1aGNMcMw+sT0u0#1GbOee2;OR&hnhPU*qcr(YZCIIwK`4!c+J$%$fm#VoYC&d?Y
+3PrHiF|J*u(VvRL+N`)sxZQ%UMU?vz%X4Yoviy>ct*_WZWCMFrSde}T5Uk}V5sWUsMT!RFtJy?LERvr
+G3!P&7Lm|TVxC0esL*J6w?=%`sP-8vM3<g^q$?TRYq_Kof`^8TqN|O0P+_bwdD!6V1&ZY=k2lUxnjoY
+!kaybC8_w=R3qg@un4j?c3vJYzd@m#|<}yn7ktsu7IR8~?;FoGH7aLw$hjYZsVHu&9QI_PdqiY(92%*
+qd5eg0ZtMy$VeSnA37hxpGi)h7b(L<5SK07i=9ihI0`8fSwNJz+;o6C<CYBlVPEwxxjtW@<3`;T(37+
+8bT8wyY^ogo{0Q&2=YCmF_OA5a|Jz#szsiT0yALF-5?)<GQ>pi6%arr+G_DRoCb=+EwW+#OASe1R@X0
+VxWcSdz<CAYm9$X)iPzI1U4sy|MERi0=7dIGFxm@B4%4s5hBV-yKtzuDavtz_}iF$8>c)zH%qM28t_0
+mSRrkz9i=<Ucls1A(Pl7o(!TS^dBg11P6mTJ$O$7W%dPj)to$Z$ZB&`4FeV4$MFJEB=if(1%=Ag>8F<
+H9kl08bz!BbZymeBZ`A43hLRUP1}MP<@V;EYbU#o^*XdkEhE*@Sz&2a9-8`||O`GU?f|Wxb>Wwbm`0}
+Y()<R>`n9WKeEL4s6))1Xh=NAulS0Znu@1B)bcgRkv=U{On%vHRYDvEH8O_3_F1a>C|-Dp|;aqo|r)1
+A&n*O&BP`e0et7k%6`i7N57TF6k$EqD42i#9K+cn5SR4i;Lx;6=Wa*r_XNP@F&*6U!%%w+nf+^nya_d
+}p#)>Z67xhd-&GB7oe5{B(~zV`u!wk~}e=q9=^*>_`)=GlXwxxM!?m6dU#f4^0+XDC%NqKBN5>)(~A0
++A~h+R5`2wOx41>jgXM~TP{q{Y~lsj>>Q6fV_g4eoXvdp@q9M(*~jy>n6Gs_UyJ!#$MdzBuYEjUoB7%
+$J~Z)b7sh>Hz7GlC8z2Ra`9AcI#+@?X>0Z7U<2z-()2;X>uU#1Tk@-Gme6K<Z9P@qbAC2oUUuQ4hi}7
+`suTzQ-uc~?$se2fA#(Zbb`vvcq@?C7JxQlVjcb4!KRIm5hC+7RK!<V}l-z9u}7n8;~=KFN~e&{k^_x
+SzLWxnq5eCNz}emvhf^PQ*t;(V{abSdY>VLqqxCR}!jam?prd~R;`03`SGg8439<#V6=dBJ=a*?wT1!
+xuNbFs{dZz0R9(*(Js?UoYcxbF&8^d3=55>%Yq9KKHZFeEq&v;~&W;eI^`6#l08c$;J~7wi_H70{JL{
+4c1y%3zc5R3hhiG6(>Kf@o(xS=7AvoVXg44U_bd~$1em<HRqRIVn1S+oAsB!v6Wo2{ld4xTyNBbM|(B
+x^jp@P9Mo);{#H1;x3W9#mZtrT-7c|ze^ImSr;Ac%#~qw1t@sQ?NokS;WOeH}iP4Wu<4{PmnZy7&n^h
+wbENXP}8;w*b5;=dOHAc#6t&!{13K0;E8K}&RPp~sTJy>P6D0DCo{(t7<c#bpU=lBGCBSUiw-J9EORg
+HPofFt)WSvcg}zw&@-o453y%4g=CfVVvP9cOban@#RldS;)6-cl6qVdyKo)55HENbd#{_vGyC^wWv`?
+vS;>3-8z7{cD!q6?s_*F^{$D7<P@Av3@dD-0*XhEc1Z4xs45$$A!XjhDA=&{4dp$nEka3X2!dZs+qi~
+IuC(9&$KyhF5=Ht9d^&%H~#IGI@cvvEZ!nF)%~S?Px-08M!%HEwyk1ZOblcG*><n!h=>yb>T+HhBX>H
+x?Cl`#wD2CST^r@Dy5Wag`UTU~9?jhzEgr1rb&erXGS_AGzDKY5DqP692>nu@ECS`3B1S}BpgI0M;ca
+Im<!m;ZcHu}eN}(s#%j#~ZMKcs0<pWjrfx+iBNv!@S;VR2SfZ=}+(M|gnzf^nHZQi~u*s0O4iP_xV0q
+2(9U)5rv&OQ{H6$&tLCjWRUp%iaSZcK_)@}HY{@=X2*f{ApkxkQDL;(v!;NXB~<w9-;(X*P|0PQ6EWH
+ahL+)h{%xe*jQR0|XQR000O897^_9XAjAH2nYZGy%zugB>(^baA|NaUv_0~WN&gWV`yP=WMy<OZDC__
+Z*5_2aB^>AWpXZXd7W5kb0Rqs{m!q*Xn%nonxUZGw%fB4gE_h#Yl9bXPjomOgj@();i?i-5_Yq{eqX9
+CE*~rr6qJ-NUtUtB>fm7aht9g+&iiz6-tP8CT{^oMwEs;n$R3mqX#AiI`FbkpSr`iSRLzu}(k#{?1;V
+Pxo5%W2#<ls9?v^yvcQl$y8Pgva{wr97D$+Hh|ExJ(k_NH5SCI&)%{rm`QvX*4fuQS1J;~T$#(xm8k(
+Q>?O5f_((F31qIFFQ75bMY%8R$8v^o;Bd)sXK?YkV=67z)Ehq<mPcBZJ#`u48w@hF$468TVr;EZl=9b
+|;mHS=W3Css~Huc7+=Cx(5|I#cR|G0vfWcp`kP~ev;F~leUg*tnL=@uWTw`F+wZB`$S?Y=9a9cOW_Z7
+C?b*(;-I2?CweL3N4iqMeXK%A!x<-hwX_d9auTD5CB7oiJg@W6xL}s@%m(T%7V(l3F^i=nqi6ORPM*?
+IFUSXNET_sOrXr}8L^S<f$H2Q<Sn|*!n!;v|fR%A*vV45&U(<y&@S48KNXDSQTHFQ72lztyGBT1-Q*$
+0O4@J~_Y{)1zgnAn4U8YV+D$FxCR|-a`QS&mkRAUvsQdwBGAC)m@U<F1mxmsaKimdGnLE-6?ROHk?Ad
+mP1g>dv4l}dM#7Dmn%K@}PxOMjn_zYng*)aw7Fzgxp$t3UpE3R$EAv#5nclM3enFCBOli^wivI22rVh
+wbk`w9d{i&c{F5`ri4t-yMypHyBcju3E$KdHedJHKeQS;niT&ts%KmW+CQa?h0}q;u%zi8j-|$5-Ko>
+>pziR0|SF8J%}fXH2V?@a7qFdGGFeM!$3#(&R;-^fS!_?QKW5^o@0gDL3wUv7g~z^R<VHmT9pnx2#M%
+1Kng~H_tXrkdx6$*mCm%WEPB}jw%+i(`X{eh_lT}X7<uVK-G1ktd)`5*<Tf|EoMW+Z)_84QpfakwM`3
+j(^R;xFO18gDu8qNwv{!C06_n8eiy{@^8R#8ZRAZ^s8+QLQX}89c{`DpOi$0f1*PR~z)QJw<vYM$#PD
+_LFcMN(wsND)^joKJ!@PIJBQdp^TWs#gfTI=RVm~R&ICKN$2+y231Zq`Q*Z4Q6Z&oaRL0P}}C<}-H2e
+_5GN)TihXqmQ;`6YQYV!R#^5asY*I-PXbD%fRD6J<4FowIb$oDdJN50=}f-IboF5Y=|ES6s0Mp&jhH7
+?q%{+x^Pb=R_D|{OOn5^@_c2X7)A8xR)qXzCE`0RtT1jD2ZDDU6=6I4X94Sj<tOd?i#X<LFw5{x2d2u
+qAl6A_RJ!wp&g9@(EDbgYXhOP?X>k|GTC&Zgiw!9#w)A`4@E(yaHlX>hTdYYSpeWn+4ev-Hs-KLqi{v
+?0WB+HN{R-Hul&PI?5sr16LxiZ6OL!U(N~rpt3nE;v<B3r}+8cJvu-?8fkJ-Gv**s?R_GW7^TVrpw2D
+3HxW@|EAb8ogLvo%-Pu-xCe0QQ;LJ|}GNK;$rH``p_XcF1gpJK0|I?U30H*L)kjbph-Pvwg|f-bCauX
+8Y3H7k0#KM?2YG^X-V)j#9Svk7{-q?D)r*(GLeZX13#uEt}Z73|4O$#%#yEw_s~nz)qO$<W0688*C@c
+cJl5O;3xrWF<WbE1#~*ur9k9yVHmTu_Fivi%y#yk^|t2Q8MB>ju@&~MTbi-8nXSE(Z8iIw>25Py`~AK
+#Iba=T>#XLDmF_Za&BzY3b>3jxuoSQ^vvrTQO8K=5!<em`vax9|2BIhdz<SKqJ1SuBxG;>_dc9JGAA@
+!JN@&mJy$EpU;SR0-GH)p`*1%Y#<Io8-Gl6tEdw9C1<|WQZfqQfw5I1Dpe{svjZ5209+#qoi#H|jDad
+y|MZ-1S(T)O$n*K^X~-9s7{?v(b@@22$VMd`-I?*V(gk0tHFnzXlJiML_Nk5{EP?JjhCZ+s72b}D(3g
+x<a6I>)>POB(g^THB7(I1`}xrpZL%Oh1{FjSOZL`t&FDbtIE{{+I<$`Q=J2m#Y+0K-4B6vlDJHCw|(F
+WjQTmxYL~YI0m5!{pwB{H!8BXkiEHG7mXzj9N@_9O9oyt?*FoYY3sN2kyg(pr5td;-85*8>saTp(rNp
+iH?`<>1sNU6XC98Zo6dUJ(-k%DsK_rEaGsvRZa)1RD`LxiHaEp+ccCZXmnUf4i+-A=aCTbN1fFn#&KR
+mR7PSxZS3JCFaBRJLX)BFu@%;;g7`Dqi+UbdJ5{Xb2K{qxoVjfGoh$H%tMdQOux&j<n7UKRbJs*l(&!
+n6>=_*2H<%H#v6X^}#n`D?@E-Y`I!quZ@p*h1M1Zho$h}q;<7)-3VH|1=;sAN7a`J9fNHlO0pT5at*g
+WUMHYXHv0ifFOp-jsKj>_^H^fff2~g>YT3nx(37eqJ}Rr~_9!AYYA5tv?t~F1uTZyI6|H(zcGZTH>2q
+`VIB8LvnlV6*r~LTsufo+j-7$Km=1X!!a}RS88PzXkiN<;dy~(|97~z9+8x@UaNbBA<5Aib+HJ`+pZP
+`QCO58FS8F6ZssJ>`bWaGIwu1oX$R3w^A^wb9pfHvOAY9$(C>-bT;B`Eh2mGa7^t!hm6e?%(9h|M%M}
+z(;Q3x=bh5j+cNfXQT=2_)^$n<aQ4NR{kLkXs?6S7YtdFSA+EH^e|Aj>9e^5&U1QY-O00;maO7>Qnww
+sbV1pokp4gdfq0001RX>c!Jc4cm4Z*nhVXkl_>WppoXVq<7wa&u*LaB^>AWpXZXd97A!Z`w!{{m!qrB
+B}&h!a}S4lBkskfdnl91V&YqM%G}DVN^4NX2$8#U%zK;Fb|vTcD1NgVCLR)&pr2HUtN`d=&tuL7}0Rh
+?TuzVx*LwWf6@iptI8F5D^6oAmO`?ax+>%(3_YozB90l&rFi4o;3ilxZMdb7TOL@YDS&CSvPT$5VFk?
+Y`5TYbhHFw0*%D~jkGM4f+i)DM*NGGXvqDLOpL(No`UAi;Q93&hG-sBFwAiMI#ZXK;tj!joR+ehrI(=
+-l+JGoEZ&D|YY3ghZO}XLvjfYt#T_vp+iv;=AO#KEYL{ChAr-_J{TCC}sz|fLaG}+pflBvaPwZ(rHD|
+fH*d{c!|gNaru+9)Ay19XDDYS1|r3(fS_Ngip=$*9QwKsvXyRS5-5lIEc>87atTiOKMHrQyF;p@_EbD
+3KvVaJgEp*JiK$!)Q)JZjc{6aLF||O_D_{0yqyvz@_2D3~k(*SsnE4J0i0k5$Y?zr!~1HE^zN+yPm)a
+eQdV((RPRp2tYMv9e?z|#yQqOdP^~CsP~@b5*#uONyrp-g^J+|0Fmeq^dv1fC5A^y+yDY>>FdCI9M3)
+KjGpOhXFBbSyysikqCU7q)iWfq-oygH$VxM5w;&FHr{1*t2#?O)U^wue9sB;k8}(*0>W`<?p-E@z4Z8
+DTXG)X#bTXdxny5JEdx@QxWg_PiM}S-_D2d5oA~sp-&nT|}!8oK9d*di`z%gneF|^HQ`%5*9m0YIz!s
+Q_7Es2PvLd*To0=<KtEmRjMhx%r{*`Pn#Fk<q1j1tV?-WL&|`>|5GL3henXZqBEZ|h^b-MVgnYPE^xG
+n`!dP;YeqFE`Rvr4ngOlHG0u(n8hTz>U*JVsXQ5B#d2V({xKIZyMK-JM%8i?~l$qaNQa#pMx8A*+#1c
+ggx?^aXU#5_lB4;xil87yJo>kNS<4#H#2whl-=xHxJ)pDJF6j+%Y-d?U&LsBsFs<gZVk5<7JHCNr4q!
+<VDl!i6?a?9Px#bMeql3Vt5CICP5+j=<R<BtkVoYE0=v-nYlg>B0|P0Sev~r1Ib%wn&kmZS@u*j)>n}
+7?l4s%F$0S&&wR$s$J_7xG^u2!YK<wsm&3xvH^V5;oSNY{q{a!)L5jaK5s^pvXF+!m}<-R^dx4vr#Tr
+Z%Z+YZ~>qWZ1%tyQfb#M5|C*i^Z9WXOyT$zlS}80J?+_7}a&)hZ&D+7(cLE$xW&aMv%+%twTqYzAN4Z
+__w<zox<*H}!!db1TfACG1u{7Sw4~jx9?QI`PWg+?Ev?8TaULQ;2P8d2P?Sek$0Wgrf-w&MG1KUpBi-
+{p%;LD9fq$=aac^_NLSE^fX$od#sjA)FkAKWLYbixKH(iA^h9zrWKxgTx%qUCt#Y~2UBg7I%X+ko6VP
+O&EGMLcf(z7B8tcL@^o_jj;oGc;rUO!g2w`{ao>MQ$$>Wm&;=>WWB14N(Y-(L{)gx@50Cz0a3`@J<E5
+g|HA@H|BwBNsjTVe*Md1)uxLB<s^dYx=JYU+cy9vE)T|W2u<Q}0la`r`DJU09tO78^OkJyXA`)`|Wkl
+%0AemxF$Y5Tmi_UWYn*X`FzVg2RRIVtpg&+B!)!RX=Uyr}QcT`KEysgmW&$2$+Jxi{00ii4O!q~%mH5
++RoXhwYc_eD*k=dfmC_dymr|ehlwV{OkX%UvnqTZKCB->W5`~#wdRnMX_SGeA)i<3N4F!LA^6UDt`k|
+O9KQH00008031s8RzJEWEu8}Z08<D6044wc0B~t=FJE?LZe(wAFJow7a%5$6FKuFDb7yjIb#QQUZ(?O
+~E^v93Rqt=&I1v5LUold@fJ8Z9Z>8O>_9VyxrAtGUfU4?rLMCy*t+6B9X_fu!?}Z<Q04v>Dij>T}d7g
+PQc5ZI2FX|6QW1l8tZ{SA*>QAQLPx=k^rglTKHK(Z&E1{SqPbZv&rAPfsNXclf#2Ysjo_NiS<&F~Wc<
+i*H7|>Sjz%W+A3BZ2vH!gL?4e6BJ6>8vp?rh954%23nD-km%w6gd#nKs)G5L2Md&K?`i98YLjY#A@NV
+y5KE3T(A@RQDRxZMQq1xC(DkPf7|)tfi1!Zr*sZtHjgF8L`Y!U)?so!9w)N%qs;#u8i2wEg?fkPE%00
+wN_h1v@Y;4sY}29sCTQ-77!S%(@YEHnn));s0N*-SQ=)EQu5SrPFAPx9p&6np>v9vBEu75cS%7$M@%J
+uXoL8TPDEOird%Zup{&($v#|%|NB*29+@d}jam5XC3i72CF@h%|=E`znma@`j*GGMaWg^i&5gKaHZ+m
+h_T)<!MUCsn7)NOSRyX_g95P<5;mHA@^vNEuNqzjVhp*ciem*7}wLPBk6*XS5tK!`%$F_X09lv|$WvI
+z!Y>1jN>pU!90^PlOd7lu85_Iw8{`U5YzzGD)bObQUAD#Mg3kT?h)2cdV5h+cm@8PA@}?1$r-KZqh4P
+DAQZ&<kf{Z$9aT6wJe58Vy?LIOhk6OEIsB{2_4)%8iDSI5|v6yDR+}?X^fyCbVX69Bqy{j#@$tW0MvC
+tA|pn)wW)Q90k22k&@CFxpyNlJDAyv?t<mm-`#9B>2n7lrd}ml5FvahQcw@2)}~2)ZCwd{>>;+@?R46
+=olor!(L93XcZ&x8kN<ch-PCHS!AWW@#p-ir^b)0`b>*q+!xC&Qd&vGyS{a>ZRj3C~#NDX$R70|_e||
+l~1~64XT;(`Md-sH?RnAs?D5N_g^7!R!%fZ}x2&y!B{Aw;hKf`m7d%pn9o+_Z#viqsit)fQ#(pG`J=r
+vnbQ4iDmUcUmeFTz$a(Ze{ZKysIUsY2$n;g>z6R*NOG_(k-+=tST8rR2Ckart5HQ(7zpuHnU^Zn;dGx
+C_*3k!}V3b|x@=KQpxasXu7Y?O)_;#dnnDvN`VZdZYD0eM0*E<h^l>z}~H0T^8H?{oyFrvBG+zS@9g@
+Irp5j{M>cgohxC7AvkxP%;LH0IQ>`n4)b#EI%)r@>z}G720uYpZ`A$;P)h>@6aWAK2ml;P_EsrY=JHV
+v006gk0012T003}la4%nWWo~3|axY_OVRB?;bT4gUV{>zDE^vA6oNaTPxE9CX=Tm6vH|>nc#l{b~oqd
+s{PB*RdFt#(DzRF-MC)~x53plCw&i(H92mwBT5E#d)cQ=8SMEdK11nB&HB&*R7|B%z+my0Vhx;PtNO@
+`!jbba=X6lfbq4KjV8<l3|DEyu9QnLDS%^2yTu)3R;j*!Av-32DbivGl^R0t=L%=@YfxN9qxGK>~pd&
+|lHOH;qRMNz3KRu}mYdT*rq$y+_vz{{X|}#`So*=}{w~b23|p7W1bvJZ9^04X1ht$osPoq%|1mU_vNA
+CMUK{#!TyzG4-kUMCZIFXRZ@?)@&8H-h2PUM@S*$((wKuH<o?xSxcf2xWa%0F1c9;53Uo{ADYItW}e}
+#St~6(N{R0-f@ip}Ph{<`h-o;)qjSsW=Aj`1VmR}ExgL~Xx^ru>W=Sh&4%J~-9Z+xS$8GrK>XwYC4_8
+XQP=|U@o14|lwoE8IvP|mulo&pFWNH4xrlro=g-oIgA?Gfb4_o&Wp%&z`b3akfhZNF2ZpCMdEH;Vjk@
+rTxt{?8^BP;j;E_zLDxEo$v@>tjeo0`sv<%DJ*pzYxoFbEZWhR2A^C|UV*v9g<B0kq`%#q{^<+bKD@`
+a!;*jK?Qe(;uHe3oQ+~aR0a^Yx!tfU>IuU8BVZ<3kL(2!|~bgP~znDVstV6!LI)NVtO^4Ovw55n4FNC
+lkxQ8>~?fACO5a^o9oH&n2-sjaTBw~6g6_v#0xOFbfG2ZG%zgN=T-j!x7UXYwCCi(c%pEdO=`gtMGSa
+F9@kslL)&%k!}>yzO@n?S)`B>0&?L{E1<wvVeYv{}RyOyy2@kz_+$7x=hz#cs8*ae_il18xFnw;juGb
+`|t{*Vz<q4Ek+pU(Wv^2Fv$n6ADihjuO>T|_Tq;Yh#@Z2RihMvN5?)?BBo26ksSPr}hX25PEdza3_+z
+HFQ<hh?AH!4b<6}$$KGRh96M{v=n7hk&UxL5`sp_vy)EaC2KG$Fr{_eb#Rl2%i^6R5EYFSFWbs)k|P?
+lVz;LK?hAHob?N^JLg7T3|#CcV<LqMiyn~YO!;*`e~V(moaOtQfqByt=%t`F>CEoYZ|krm0Hu7HH}+q
+H^n>1I?P(9Un*nPI;GaS%v!h9T9;YtmRjpEYrRryJ!Y*}YOT+#^(EGLyY-p1KDX9sig%Fd%$nXWl`(6
+2skH&KHYl|=VAckSHBGdG%wX0GZcV6(WXzheD3i^YwOOgP8M8JkwPrGFW~nukSu;zm&6%}%skJ$?HZQ
+eCnKfE!jWTPr)Y^hsTS%;_p^6!Up76sF?+ho?q%Xw1=kahnz8*JINs}q~M^O^trz|VKO;STu6}4aKvI
+I#N)5+cCaKCBsb?Qpgz1MEO{U$Y-+wQ~tj@_UW-FaZ4@!e>6bq7E+8nUM#aX8R9smTL!d3SmJc{uu5;
+D@2$f5ZB}Gi}57?*e0H({~?9>}s1hb77c3&XC)Ul0%=LE;E_NMIH?A&ZbVrWa_dbsbege;N7Wp-+k9S
+`X6)pXE%e+06YIMA@u&G?qBB7)pCz6bKz>a3omu;wTp9Ko)j<Y`iuMlciz~$bc^@=*}1n)&MqmN-xK%
+Di<j#2XXpNy7l-@O+h$K3FfYDU*&gz^N%4M#U61#~#q#1+%HloosYS&HF_CBmD8rqooOmQ8#Jy(i;@n
+NvD6S&E7<xS314J&bVcPz0;lmL6FVf<NHa}?m(BX$JKlJ#a&ks634A@B?J^Ez1E1!fN8u@Jtk5JKj%D
+r!gAG#tlBzoo=BwxC&hdrRAY`wzNe7#<S3HFqhtszgYd+VyPL+zWg4XrSbwBKsHN)q#ohm3&LtI>V+Y
+V75q>ZNfv0>1*@Z6i!e{6>4@Eo$;_LYra$ZmB{7jy+Tn0*k7WVc<{_L-6qSO!<0)DHu||-lSq+65xws
+U<I;-%y5)TVhu;Ru#v0`MY$x_aFk0XLs2e?3`e<SG8E-11?5s}ILalF;V73(hN4^&8IE$vWGKodk>Mz
+pOopOd62!+*E+NxvxhR*!8jf<wWGKqjEyhqB<&w}Uj&ez4ILalHp(vL`hNE0EnO@HEnJAY`hN4_*Q@m
+%QTrwGoa!F)3$|clvGf^(y-=Q!UiGUk(vnIsn9kB?-u=a=8FMyXQhE)%ltF_avt;yq9bz5`Cvlo9zYq
+WGFa#o~R_3D7zXsb#)6ZVT-e~yEams;aNtIb<elYJ7#5VKEDh(7U)T7*8LtIwbhrya~b-^LmC`8KW=0
+nEUUEFk!g9O9G6F#O152!13o3_mg%f**+t!;egc;720E@FSBU_>s6a3_mg%f**+t!;egc;76?mKSe`)
+zY2Z|gP41RABhaZk4%Q(M<T=UBh;`^W|n@S$J=_4??oNi)`NWe8LF%6Z%M>QSy#$Di6o@3Y5e+5lshZ
+26YUf^(eQptoM`U41y1zaICi36uYW%|#XdAl$ixrQTRw2G+0<s<X^P6HLj}BKDnAt?$d^wC2L$=4sDP
+H*vK~<r<s(<9HCw4I?*j$-Dd(5ZPkTK<e#+hD^V5D#ke_mJ`TVqJ!&^J&(t1t4>Cu+;WqLEcWu2Jb?5
+DP@_v(xCk=qjGV}B*gM~+IAk3EzyAGsz`KK4n%eB_Mc^lr3ey->F~KwCHGeg@6-mi0TreB^LM`PkF&v
+&LJ_#qbUx9#kWy?Za=;m|E(mB}i)v(lkL@N08PPr1b=8eL<QoNE;M5NFs6yFPA1dN0cUL31OO`b;7$?
+WxVeI$Ga+zi)}S9R=wE|DJ@sWg5k|wp46(B^wLj$ltv`OfHklF7wbX~p9aPVn~LXL;iy8y^PA4KCPF5
+xw$&I^+@TjSq^K$xhWzS27&9D)nSRg2VW!_x3@Q20gHclOiANNMkyyiEiH&4sh%Y79FlNeRh&ClM44p
+FB+f3`UtaPSzo>^;$VS29;hS3U!(J<Bu=ef0VbSsHVVaS!q5bN?pE&l&)rghOw>s%NHI=n5yFlCV$!J
+)HFh~@PsYgHS7dUcfCW~c}aLA}gK%^pH(nb9cWguuNGpB2_R8jY&ba=&QW6lt_|rJaxRF-{RdTN3Ewy
+S91B>xcU|6Ny=^Uli^O`xQyJFIRyKs{K^x%2a~qnAX0WwzXCp(;83N@@sQ{mr*l`8%W0pBd3_R_J(WQ
+;+k;EkbGW#KZ-;a%Mh-WPSY>7hH*_I!?-4sAzYKlFs{jD2-hSsjB7F(!ZnEu<C;u{a7`k^xF(Y!T$9K
+!t_d|cT#I_Vm-ud6?W73p-k5H`<9&EqQ6WXYKH4FUt5)DeX;1Qf#{!T$oH_eKkZX{s%T|*xOmpRdv>C
+3C0HkyuJh1f_Lf9g`a1{=a@x?Dln=KL1VJnTCuEIqrET65iKpbjP-)9S11TI_1!t|`A<$zfz8$8o!5s
+Kj1CBEgDY~=-BcIDG~xJJanqyJe^$6OP`G3>Pud9Guxn{34o@=U|!N}decVv996_fVcfHN*8(h-WzW;
+er%ixT421we4dvaicT%#v)w(!KdN%2CULhyiJ(?I3c;RC?q3W)D6}o+6^~ugS1KCTg0@&N@SpxYht9G
+JXnk1?(4+_Q|$!){)aNHME17W!=9M7m1Ek>2MR9Ja!f1v0D_rTBEw88lOd*Us6T;Sp+m83zSxQ75dYu
+sH*{KIAJ7b!<MG`kC6C5E^~v0&J}+vzPGB(o3i_<s8v14OokE`peP7rg@fC8Y=dq5^_3o`F>KvD~@7v
+`2tZe7NCyp!c9{5bn(ch4C*vtMc*O>Sf)ARRE!}Xy{u*wAYu<}(V_(VDWl+?tG*pY8D*F1VGix5L_<r
+%<8kRoP`+p|eqIUQocU`eOL6k|w6fG}eu@x^2~SjZR>YnU;TbS*DKj3Kdx8AHvFb|f;y7!qrkF=R5t7
+!ny~44DiuhD3%LLncFvA(3ImkjW5ZNMx8XWU{}`Z1W-+_VzLv^7axL_VzLv^7axL_VzLv^7axL_VzN_
+;eFMv6Moe$?d_u;5Bz=R+jd><zx(l_D1ecC9dBz7{#S9~m3??9?uidoV@T=HR*^N4QQ<}8zUn43SmBn
+VU{dNa(aWnVJZ}{FDZRcI#3RzsR7J~xPwe=Mzi6lOU(hR46Mi;~u?_wt?`aVL32Tr+pxf!W((0WKQv@
+{15zy$3fO6K}2q-IiBcQbGjexSUzYYP7hWX_N(k`f<`s)pP(!9~l9CjG3$`Vio(<M2@FqFQjdg@T&yh
+Sinxf#la2BSj`l6Gp7-5_Zsg`{>0l195h(x?_BjmjV?R|6p=jW&=3f9okknx5-huSlL*kKA}$k-Th>N
++Nq(t{^Kz_=MlY?C2B1C&|iB`&*G*vZPafp1fFw@JS-W_#~6%@aZroUg4!>_4G2c7@sn^11v-M)MA}N
+tN33Aqgre%R73yZzP7r&e`5J*nqr;fZlgy#LJ^6tIjkr~FZMHt@>?lqp9X<0hCFSX1;c+;QqeT`gStf
+V^r!>;l4{Y6se`=K1P$wuW%^L@MshMd=x0sS6>Y~ic9$0Fs7mL+Td1QeovojnzW7k_lwDQn9(b#Cb*2
+0AJ$<d#>ZwZaz+0=QE4{6sp@H~N@sxd4=^uEj^mV2GDzva&%jv43A9%~@x}tCUJaN#=A1a=5pelm{Z<
+T?r3|{Sds@`&jsu%~}a)z!LJ3mkLPd`(Y*@3svOjl;LpRHF}Q@&xUih0njNE)WDn3-=c@EBpiL^?bo(
+aufp<iQCR21q_m*A1dZfy#oVL<(Z4`~!Sp1T|kVLHtw?gQx!oP)h>@6aWAK2ml;P_Er|0ik;;E005E!
+001EX003}la4%nWWo~3|axY_OVRB?;bT4vcb9HQVWNBk`E^v8mP{B$AF%Z4)S3K~dAia1{7Cg13ir^O
+MMMNYfligr86OycD|K6l)w^W?dFz?O0_eKZqkw$M^3)6cJ3A@+r`eXU9UOqiOZ?4h!WY`H?RYsp<b%k
+6P*o~gl%E*Mhh%hb%R)Zv!TWrVFvBS;cZZWZsJI$)8@j^X+6H-SY8wsD5<rjog=R%Mj<@vrN2Nl>K+{
+VEdyTA7|hm+Rrq^1AKcC=a@7}AOuvx_*`RHm0Rel>+FMNYEHH|qHnZ!v}U8JFy|QJF<Gv}KWI#0u9Aq
+NTr^RS7!@oV0NdRgC=rP)h>@6aWAK2ml;P_Euc&qVQ1&0000P001Tc003}la4%nWWo~3|axY_OVRB?;
+bT4yaV`yP=b7gdJa&KZ~axQRrwOIRa<2Dlh-G9ZPK>?@rx=z|0u-@CnIgXMTb?m^8>*j)-K+CjEgciM
+&l&t&L-$&|g$?5ih6_AI>nc;9A-^}Rbr2e5x=VmaX;h^t~rVd>W$Nk^w2<=JZgk~E~V=dOgXOjAA$w>
+rsr~VXDGMfA1h3f!2-iGObhqUA&_d=z~18KXFN*MSe6d=3eFI=h}*Q8by)`$lEh=+m4b{tFFZR87&g+
+loOUiD6C`vSpquXMcbY0g5vq{ZG!tRBU*k+s|7s7*-C{wbYzI%g13OWvlQlr%B40Zn+o^$TCdH|Z-s)
+M63ge$C*tixr|frl09v$h8(*dPmSOq)^fQKHMnZQcO2{{4lA^zRK=vEtD7tCY55Lncf@gt~BQqs8#q1
+%|FmyMdUG`G+&A!J|C6}iTTT4lm`D+EyZeYmLh+N`<iQoTyKNa$Ty=o4S9g8&<*#w#_{*jLJAMeL*a2
+h;KTyjnYCb(oATNyGEEerYX$Mv{2z!5?3=TV`>{gj?X&c>L}Ckfr6voF{&4rsFrGr`JxRDrr=0Ct6XZ
+8tlJKqA4V;62AP^UQMflNzQxx!3BwLUGTKZ!!yB*JG)Ehm}AHB(>H<~?s04-dBT{t+FB(^&#AQ-pO%n
+$ca90Kl~N&glcz01LHFnciCUk_#@XF8?p@q~JG-<!+^{rRvrq5Jvdemr&Ba4zSmiH$MqjGUQx1(90?O
+Cm{_kU@O)2e>zYf^tb4_QK(2k0Yy=#1J97{onGTRQ}rD7c99!Kag0Fufi6+YJu26cvid%DY<`J$O^CB
+qKh*SG5=Y@1yitJixos)OQm#+E>#d3(z_mbJLhL-op)!ycFu_AQ>+|&$QfOIBlw&&8Y_*Y3HLjJYr$(
+Kx2}W-O@@e%7LC}JFK5wCBG|?@z?f_qP(tR#yzK;+c3Lf9xkN@Ei&Gxn+r@;C`w<eRK)^giX&<4wR(j
+teLku;hAy!&&`<ICO9v_NlF2zQvWuwvXBntwXf=cqseaMqz?vUrQnd=JR04k)2>H65{62jfCO6IR4wl
+1s~IyY3V(#UOh%XVFBgGb@R0{Hb*;&Zp=v?58FIHoox^_X;bDggSuaM!|WmsV1-&{8~ezH?dN3E@f}!
+V*E37D`FG$>eUs7CelVJbLlizRl8Ga`|cR?tbXF)4_in`bhuyEnd8IozZxHbL&o=p*y>sIMdtl@CpQH
+o%7#_5N7T33;L<Z{oixTifkOr2LHy|?RYZl&u1m}PW%0ZB^x<6y|>6Z7Y$3d<STMrfzsf*O}k>AfXh`
+YdrJ&m@9vyT1g_==>-aLZAP%}_68M;rm<Vv=2<>KZ{8%#E6SzjoPnb^W-6#9n&2@`Vx|*l$OzYE<+U+
+<lAjSU8_JF*TxnuC*m6OkbIsk`6Ujvvx;~f(^#o$;7^8Y#79mr2Fi6aVEE*z9zj9BzlNMV3J$x4HZ#s
+)CECrnK^5M8hjq!-=}=n#croF*VUzqmNq4)_<>1IER{Y!Jkxg|Y18(*bFyLSzRR0uvUsn<g!5Ha*iKs
+H58`?O%@UX|x(4+?EAkykPd;@OR3U+u2Hwt$@;DY+{!zoc;d>Ggj(6ncS-&Uwds(EZVwW43>fimFW8p
+20h8I6~ukPilHe$q?&#sV5Z2UY@mLv`I}y_oBu*Y!J^?lGk+1Eb1!7+3FLdq-GKzE#A?249?io@`&Fu
+T@tj62wavOR-4UJBD)2q^P0x5s*Ni69Yz1twTD8zzhTMfZ-MCUen)e`HHVxVS$tqr~x7{LMjjzUCblu
+PBr-X#_0eJZBv-qCwE8;n@<;(Oy{yH!bVRcKZR?!IPib{&tl)aKwQr!_amhHF-&6G4x1rF4ITb$-wg=
++kDE8UQ->trN4XEr?Qv%nZG+pRPa>4}BlD(z>S<;LQGt-P7>7(ln_1=H7Snu1Q{TmvRev)ZaQVeR?o%
+DEnloU7B4uoL?H`Exg(Azm@ZOdswp$3wT@o4Mo3l{3Mh0FBVK+0K~J3zHEy;COz~X_>*{K$?B3r^jN=
+bb|E=ShI(KUt5^eO!34dLjCb*HW?4=#G$NiP0V6;@uV_ceA0zy1EGl_KWy7^S@{r-p>D;s!P+{3=B^u
+VrZ6+9n3#YP7Ola!7MNWzA5wyzMW}=+>f{wsco$*P4mbvsA|XOAcH2K|jFViw>}B&*ApU2xbI0Ub;zD
+<KOk57&6={jYN`d<p;fMO#dR2Qua!L*#S&vssY946|Bx1gtG>?axK0U^NY6Vpx<XetN<W^34!vMwF{}
+{`Cs+yvvjj(?kCE!V`Rt@G<3Sa6v3t#l{W2p|bubi3FpAAMg-NOi~xb0Ko@A{ddYC~koN-RybrD~eCC
+SPry)`eMtD>?9uN#u=ylWM(2ZC&z3v~C{t?+-r)Wj%jH-9*~k?*<I;=KEa#&?*_dRp6)<T)kKB*~ANF
+CtQz#!|q^K;X^-IvPhD0Zwy`E$07?Z)hni%H8ZoV`M9D(FA4#-=$1E1E<yD}>!{3<^^Q|zryi&ItLxW
+u{%wbh#xwWM$#bsS24rp6K}=_Dq8<EmZ|Ha$KC7f<Im0>!?FYE3uBvxl4a(F^7HKloBh}C8_keE`HXQ
+u!3?HhZs`mb+a@nIKF_hJRPbo1Swk$I{PHSFQqMN3%k3VmtGuWrCLLmM;Yz2~!gCYMKp0@12k_UN8*r
+s5?Jq7ShMtCpM=qV0co+Rem6@O}&w^^y-?`np#(*v`awOVn9CHybg5PF(Eq4KmlRk(-)_5J(9*w>B!0
+Z>Z=1QY-O00;maO7>PFa+w;D1pojk5C8xs0001RX>c!Jc4cm4Z*nhVXkl_>WppodVq<e>a&L8TaB^>A
+WpXZXd9_z<YwAc8{@!14pdVJjy0uI1_TF+A)TTAmsw7G&%M!+9)S)pWGn0z@>-U)?TBDI`KWyN_b<R1
+@d4K8UW%WlL=gA#V-|adB-=R)_*nOrGyq6c3G+uBTDlr!ci>WIkPD0a*{8z*=qe&t@xYD463#K$T6mi
+2tBNc^UZC-2<+(Z}wwg>*fW4Ypr<cv%OH24SH=#Z^Ao|elr5g{`|CK^B0N~-J!fN3OE{vImM43B8K$q
+<iKF=eq<8>m_ss&(shbA8<cL?wHZ+Hp*t<<;bI&D95wa!<N4F-lBR_*c{QA9x{pVd|YmBAzR;q$`4jh
+K!`q#w=u#arlc3{;^nEy4?AjMW_f6LK=&yVrpZfJ5!vKmNT=4<@dCaDTOQ{#Ur6}{fLwymPEfx1^K0n
+#B5`q(j<bv)-A);Qg4I&G?-AIYq&yBJmCuJN9i;cA%y!P<ca3QG_CBLUVMh~(Hi0xhR~w~d=~zD;sSK
+5+om5cbkl5YwH1gB_)0Zqto=y$$_mzD^oC-jOKl~al_B`_G$N5?unQyy{{bKzU8DSH$|==+mc|VrfR|
+p~ac?*oQ+x16uWiq355{lz;6*AxMS^oAv0TLh!0<}3#B5+V0A3ug+k-^A<M!S0o3;MY9S<Der^lg3Z5
+p+`vD=;W+a8T3-e~AMO(d7|ZHR3!tAe}>@eGhliAbVJn22@m`Ww=#VPG85f_-qLIppZ7h!`qlwfRyGW
+0}k|e<AW2(0dXyN~CGfS_#w+%JV3@K>5sX16>g|8+6+O6HDG>q`-&xqnH8uF_uy_s3WzptS@cIUf;A@
+*H^7Su3JPCA1|jqat04)4xh`5i<v^xG>h3XS2A6#l$;_2NTF@CE+{@XPnI&uD22#^PZeL6nS0q=i7jT
+ye455{rUXmSMm*j!yZ$h^ySx1!+y<RV|EcY{?LqJ|d~o^=l-b~6`059(o7>hQbq{!s_`X+z{uw-Zj`L
+gr_{TnF4=i`6gtjMj8}yux=e!nTNXVXKnpF5#+u3px^d^IngW1&j#kZ&Y`VgSLXSYhVKGJ<*5!}wp9S
+rv-zQ3n>OZoP#lJc3A3hMLFy$if5%1gW3ee>Kt3a^S>O6UQ7-x*9FQSxN$`oXuG>tNh#yGJQAsd~pat
+*(IY!Fb|5yMC`Erl&=%mn+v7$vozrjp0SX7e#z=5ynhw@;hCBuLo+!ZGmNF9gX;mf<R#91wl>ocvh#Y
+zi1#6p4088Q!K$+y}9G7??`zO28D4yOC7bx7Rx!7b{rhCpKznL6FkU8xvCr33xVQxZSd&lBa7{dN!XG
+X3VxQ<?Jz&h!j>6641Z)J8v`-bFvlk3$|mIMuJDHPe66K=*Vr(|t}3iL=mLMp_t5fBnBO$9(4;Jm^R4
++IG=30*x?|3t{?~wvRr<wvl;}+qU68q6Jm^|w8XJ|q90z&mJvbivZaj88pL&jmW$D^0F_~kv*)U0EZ<
+P;CYrE6exIeIEmQ0&HW4A%ZsYBX&intoCahT1pKr<l7Mk2E74cWqm<xT9grCrK0#R+!=RjgXv4lCRQA
+}N+(W)0HO$aJmwmM_GGDXgJO_73t9T<(R{zGQo~GUXw|ZBpDT+8#R_V5JFIuAnr<(fNV<c-M63#byzB
+6vp4B3OH3Jr^i;kaTY+;z&um*)FeJr{NzABSAE5b_=4!+-ubH2rTu-T@Tn#L^?)Co9ADRebhR8nY?~N
+={TO?%_O>Sk@dSUhK!K*3&@!K#H+jp5B$8`=We<Y-0b2gCneC6Yy>N|Uw%P5tX&&(Y(*L7-<;eImB5-
+`OoEOC7h5yy`9W4F>@$#%Kk*ddWiKS{Ze{%d&o;C`9+8S)_{{T=+0|XQR000O897^_9`;4eQRs{e6rw
+;%CApigXaA|NaUv_0~WN&gWV`yP=WMy<Ob82aGaB^>AWpXZXd9_w;Z`(Ey{_bCKNKnAW94~G$U~SN1j
+$aaYeuE^V2#P?UCCcV1kp@X6Re$}Cdbcg7%diOnVv+YeclX@!sLRXd2X4oA(*?|?!|}o%!|iN2{1eXD
+UbZg5*-=<Zwq=}zFcdxorXUhOSQwI?kX!I@t=B3{r<`eqmLvK^L$Rk4L;$*h1ML@7E063cE=5tynMX7
+eT;Z$S3z@zkF|35l);&pyrao+vl=0LRk%nuZpsSsR_OJu}_wRp4ibnGu48jmBW2?ZTipnSIXPFEI*OF
+~wEo57DKHv(#oXBsmV&PV@2(ADl)Sv~d61@{V&mW};*+vqX7?lD^DJT)>XAJBH5)p$(I7sR<mC>UR8V
+L7)6%z50@L7<UrI`Dej)_`R8L2|UyTux2RAHoWM>&<4%_`o6%tP>ud6X*(M8V#ysa>Vi!~|mJfxtu{e
+X8yaP=@=)_Y;*0SKw{0UwF$IyC5XAi8k?LHTMSC!Jrceu^O^K_8KLqGWCJ+ly-;O;}0anM4z#ZU_&8R
+G>F44GN3JdnL78&wF8621AG}+)?nd0+@LKgjk{RCjEP12kRdT<B?;FF295;tu{FF$#Nc*1n>r6B`pMK
+;jBOhxOA7|D8d%PBxSkCxSgozq(jNB!Y)T7>jhIa$ml6j^83|O<r<$-(WvM@4c@+j2`miHU6wB;Uh8+
+b2kH|iGRSiSIw`slzsRX?N762Ez3(t~a?_l?xR2NyQ`gXDDy<Qi7>!T6j-$E>bjqnKzka`jdA-ixZls
+2aG0b;M;_WRdY{dd=WfVGV)=N=d@M*nb#T((+)6cOlT&oC{lnmIaajsfO7J#R;3*(#<Db0hon)E?E=2
+RJ|yg~KC<;ep{>rLhkq;_Vox1#p<|*k)&*?c@;3V?0l}Rlb#)bzvpNrU2#Ef9*Z4zt^KNlYxHMM}b5e
+lYydoj~rOpf<F#5yG=A5;;v2gD&4IxN=0>U*Pgrc<!C%>wOU?CluB1KP`jB6XA_PlY{URum*IqS-L|4
+((1EK@un?SP`{q$G&b)S~SK4)|EkxvEx){>O2Km|t0Ukl?rE`gq<_C)K@of1{U8kZRLyxpRMoApm8W&
+3ivW1_dU!YzL;E?+dtSW+aQhLg(?Q#;)${{9N`IA(~lAock<InjB3E#$K`xE|)&ty+HMtf1|5K!u;s4
+iXrnz{y;owu*%U1iH=XeN&-alP{^55x>9ecT*4j&KB};x<|~_d*?2!pt0HSuo~uFh>*Tp{DI3>P{7md
+5R!RnAjqRf%UjiINeL}odYNi&O`LagTvn&Th`J#^j0=UD7IUynNK(IwtZq^o{KjM@Gn37JG|GZl$ade
+acOdI)J3-un59r_h8N6=erPsfr^}t@bV~i|Rqrj9jyoTpAU62P_3c$kP8}PG&Pdtpd$L?FM())454_t
+BUhb#Pjl^z<pA9Envqj;(SW3$AKU$$t`&2k|%Z#t<Q|c-=oY)!1*Zw0qGL?U!=*J@=J+zJXO&;Fj7ig
+K(hsSRD(#UX{P|4YNTzlmNsrjsYoYK)y(HEq7WwOQb|H|MO=pSSXX6apR>HkT+7Qq!pkh$$Y)+IQ+Kx
+(DAE{dNLT=gF-Q*5Kuy6oM9V=x*!<DoNM+<iE1`DPKfLc5fUc)N4)bC0ymN4XEDvZm;?&jk;dPq|0Y_
+EWZQ-!Cm^xOQCU-Wub}Y;=I{{JVqPcnhYG>Xtf+sJ!KZP!QdG3%%lQDbz9^s#AZg;E^aLI(Kw{Zf=*e
+6nW+m`QEO_(mmkrwEhNAO9KQH00008031s8R!S>wIo1yV0024w04M+e0B~t=FJE?LZe(wAFJow7a%5$
+6FLiEdc4cyNVQge&bY)|7Z*nehdDR>JciPDDcmEYz{H_PDpaY!b9MZei#^BJy*w5gXrb!+w(gLc5M75
+F$cfJ1Yo!QmLN?Kva<@H_lau<7dW_EYJXLfUXs{hDk?|LvI!$G$<8u!TM@V5ICDS<sbIVF=7Be%Z2v|
+Z|uu4ge~b8_STY&#Am53c>hd=4|_iu#-d#9{$61J5TWfEp(;g@J1aHh^8RC+2t?<`Zv00u5<^AF+U&b
+i-h1y$)U5q=D_Z9DemTo-cj@!sO2L<+$lH8Ze8@cY<PZDe5Dw%?_4Y1*F=ok#@7$0uowqgIqWcxkp$|
+?ipwP6SL$=x}F>O_B@31Re7xgBZS;g|B>9;&eFHnq(NYZ0SP>Ew+mLDD<H<J9sEZf59ht)yn;g!gMg)
+uJ@=`<L+&no#t8Qo!4`J@hU~nMnA9acvurNc2Tlcqy4H7|5BO`(vKKoX3SA4%i^mF>zveNMuSXAL$T%
+E@Tr-#Xu>4&(cWe`ohqlRF&IsjXgJXP^va*jG8Alr-eGkYB_P-&_hIw2Y#SbH-ZM5RmB8qi5E2+`|_Y
+dOUAYu(Ry(12Y%a1V)Eeq0<TEun**%b%}egJ}S&@HGRnKKe{wg{a%Pykr+ZZLU!`!FFFqxa<9#r^%oX
+!8CIz=9}X76dFQ+3SsC17SFoPu*Y#8wUb6z5DK4z__>^3<s0<xcmNKGU|=Tq<?!)F38=*{bbO67+&0y
+yNCO`+i}kT;W8Gp7@4VKa>C*TkX(DfNiY&>J6s<9J&2dX1|5s6=o14mn+&YVA`~=avpY(Lj^{4Lc>yJ
+5=o?}$i0cJ)vh{7y9Z=7Lbb(4L-#S=@Y1GNf764KA(E$;R0ljZ8fOOySJiksZJsu$F%?02#+pSi!(K>
+6k2zeO8NZChvqpJg*&*@2}QaQQttk7Y=3Kw|h+HgMHd*XPmVt<o59*1%cM_t+G3RMZgH(;E=h!Zgfj1
+9T;K(iV8EkK>kVi~}cadOh3At;UC$(nc7j+{l-%4;dOV(ZnMsVh)dV9l2fb;aVOx~Bhxefw-d@c?*4)
+RZ%$sh|u11stG7x#<bMoSc9f<2I1C$>ZM~ZwZSo<6l9r3m-NU>^4X@8Xbal)yb_eN$S**o8YS?q!D@Y
+rSFBCjqlBYQxRGhX2vYI#+f@YlSR=&X8@TSf>(+F2JR*d#sN5kIvG-T8PX-|+Yb1KIzcShu$YZ;xtU#
+{$4%WD;9YFDl?5G&u?*Onn(#Muvw%0$yvNZj=-lKQcHCTc$3<TFjE7EO*=7*K-HVYc7>Pi*p59nXFAN
+r~S7+@k=)<IsgAw3Kq}K(b=$t_KA*e0*H^$-FtN;Y6FVRKt0LLgzCNT{|S{8sULf1r<5!4|1fa-xpf{
+F)#L%|_Ot_q^jg89r1lB_`P9vq(Bh)0$%NMQ}+6K){2ZqRe)f=<hy!TUoLhUtZE!7yk_91S^o@tvUOh
+i*qwHVk17o#@y23&{^f=2UB07-PYhRps8AP3Jo}QGVKVJkD}Rk~QF~e*gd}`ICg_;)k2TXmImzGo8G>
+?~UKy4zB>TX|$VS^6lXI?ey~fq&L0lO?ur4gqa_}WDV0>Z)}HE=amm1Kc6=nA3yi|pDJ?c-nd%|UH#Z
+RJNx&4eyK&U?*^m8$iGg=55~7sM7z1T1K?kh(^hQmHO|jpzHYQC9a4E`yOy`*jaK_*yHeLcwR2ESE!4
+{#R7(r>DhKsS3-x^t>P!oDo`ZU+g?gQXdZC4Co#nv3kHCHv|A$nYa?lOPj#fdi;hpcki#6Ne8)h0?NM
+^Q6!}FKlow{_*cmou^;m|pActioS8j3Cv=s>(#(*S~+j5<W1h)@xe<-%fow)P;8Skn#q{Fsu+oaT@!K
+SFNE1F%ILANH;<y6=n9hA?B>2MKzwIs`UvylOWQ1QaVm&<lAl%a`-^SxczY^=0e4d6v;87MhJmA1Awa
+uV1`Yr@(nOTCW_2li)Mq=R`s$(ta0YI>o3yomLYx&YVR`1mg5^x)5=xlZ#Wpv+RIzF&w6tGNYJ+Cj?1
+N9k!(Au0!UY=Kx}#I*=m^*cxg4NJgH^I+-mPQwVv}$c0X&3+*IP`$InbeFCCLBu68PA4U933@Jg*F3v
+k5bNEnL_QR(vp7ewrCGusoOG+)$Sr82_T+hy?9v|kLMl(0<L|iW*|C-&11(Pwab4Ocx!4$GxS~6{8ax
+&$Ze*i?9su+;^_of%)?qHC^fEXGGh5`IM3c1OwqC_yQ{FVcQ>`g+*G|qrHITT~n=~QUZw3b_TMfr4Vy
+E10!52MpVfYc2a<j4XDd1Cahpaf7J2fM^_6dqL(Ug)vy2B{kREC_wK$kH;3nZu+s(PT=9W-!Xg=F~VP
+tWoEZb#f$9_aS+dP|TWfMbQInB?KkK3%cznfx>(zT7=B0`50AecB(0H5h6Ir4I+zY_+tVIS-j6?u~(b
+T>V$hDYw}!YM_eW%NkR;9WU*-3P<aLb0>$2(1zQHyG6hGm<4iOX(yY$%%y11qL@^|PP{jqH*%vHbW8D
+Rd{%Ur7fO&jHTZcNk)N^M%SQ%7eas`SxKdzycg(y(ML?NysO0+slHAg4Wc$p_-j3mfaU>t-MQ9^zYT$
+aPwTiJbj#wI585laU!(9nHEC8LRQ37f#BIQDyj6%<Cxm0D%^%wbQ|4N_Is7903oEYR<ws$*3#n;}^=j
+JTFCR}2jeh(1v#Wbq16p1{s$vxE)};`SRDC1(t!gES(e5@n3-0s&kgYE>l2`qE4GgFt^pyUa%WM=uE3
+o5g?|8*KWeMHhb6s2?_)NgD$q$-ZjJp`jLXy#Q+=MW#x#i8@=llTHJRJ*;kk)OH1C4`=!ow}n<0AH^2
+KzDg_+mAy!Kg?<Q@1?rG$TIh);ehA}wR}pKsmC+FVr1L#dA(3pNaEAcf+;+jL!Oc`-JViHaSsF0}T67
+GOpw&{^r=)NDJcx7#jq1_$wl2B6y#dXK6;06)#BLn05PTZ87$g0dV;{>$H=EyT)|X{>c1i|OU5#!I4&
++0K5KTT<vre{5>;M%9cn?`!1{vtbhcF~6Vpe6-$N&OUz&OwGLay5DlgmqT*(XS}ah@z$0L?l4!n}~W5
+(Pvme%=@lt}Asta3(;s^66g!rUZ?OhSaZ_5$2TeBF7Bypu=9B6b3JQH7%R^ebVodW)uGiPMx*u#Ib|G
+VGZV5Hg&a3JB?5Px8F|@=k{_R)}Gi}kt8bl_}a?H*GlC;#>^`pKlgjseE9ge*~I@UdJc#q#2o038!zf
+4bVD9OlH!>GxMa`AdkHuYsh+)PwQFCbLZ@VMdv)89=}yukiu?@^H`p1I>5nXs4KkLVP8P&}d0sF7-oP
+rg)qM5hRYRPkfxG=(C@IQ9%0SAa-_y$?QYxX7&&s0RdU5vuBMaQ^??M);!^pXc{Z4|&9z^UO$X@rLI0
+i%k$FL9nImdvVk3$@TCa+X7Y>egk@S?2zAzk)UtPG<<Xiq3dS$%;he)*6tf}o2CA~}O(MK;6mo(vMjE
+&KL~$qEPaGLf@m-Ls$&@<pgtC}GfE*^o`jq5$!kym992Um<db7xV8-kx)`4bhNxFc6kjB`GvVk(~A-Y
+l~*PS&7#Iu525v3nG=7=8-cF2o#XB2YoR}pG+$DQ9Dh7qO>Ssk;T0|Rq0#DmQZ>b8p94&b#3ixgd5=o
+EF0&-M*}xHal#|KJY{<5yp@4@}h{>p$_&9yyc5HEm_YrFQty()NYFw_KOC+b>jTurVgVD8K_wqzU?Uq
+QXK&^lKFuIx!CM5zpBFEFN9+#Wga5}`1Yl$p@Knhi@eGONiobYIuBpnaOW=Y<M)bTD^B<}fEZFD=WPz
+t%IgT<v5lbs##Z|2H&MXi}HHu6hBb*2z|`wwBa7(d(1cB;Eded0y+3GPmK&GZTZFAB0dgMe<X(#4Epo
+MU3i1^rB|=ecG{A{`AR2rJLsYQE!I)0>8-`|>|F56up~%tSPVjyIE1QZdYLvZB1TC;_-?8_cLjS}Ceb
+(T3q<DPDHrgC@v&TJ7(ZL!6?6kNYl`C;KRPvFYG@F&Gvm!$Ez;MKZRHLZ7TbK6V3FMGH}gAr#bWVkYj
+siW@UD5{E4UL*Acj;BvNtyrU-W8ZtJYuG6PX;;|a;mf_<pVc9E|7#{ir2Ip1j;k>ftcw@K>J`P&X@$M
+a8UwI2<-O!Z_XHTfxO=`&^b9l~{lcZyhE${6pCJK@V!#kwhbBdxBe=5+5bqYm~;zm(Jj@an_?I+dg2^
+UrnT!C850rjrtkNFF}(d}po<csGjJ)42ahHF)G&pWEMlFF+LUwy-JG;;P`OCJ5`)^NnG-|97!Z9n5V@
+l(C$!M;);X8h$*-cg_{9`ad#h+oksCdb^DUEn9K=e5DA@RH-;5+Z*AA{I}2`SMXqa(k6t*y{WB<G|a<
+OQE0Rmw0CAXD)@Jhe2yb!i{w1lq~QWTtX!6X)E38j?AujCw`|?Y;M=p7emn_M@Ammj_a5?i}htzC$m)
+4@EdM$7R#`tF?~v|Jonpx%so*Wh}EKqV#h8gZgE@cz4>z;ZB^g1wT-GA$Fzr)i(|uL^Ke<MxSs44$4^
+QBP{}l~uh@d3xj`(Fg>qUKL7Y@#v@D>H3le43@V*9xd~I@Ee<Jez^3AN+EqZ>ja6RTV>c^b%K!)-)3y
+RONzDfj?enD|4`PUTqt?B2f4zOu7OW<@=zSLEt7M11J_{CROg-P9(OPpwVh)~gg)N?|=tum$+#-71WQ
+1aeY0YSe|)i3y?<a9xMG+tK?O0a55FB7hcjTU^_9b~bU4q5@;@wT|d>|*M#hJerrCBsK$d(TSqlsrHp
+6+O{Po4#_ZE)T#NVj>zp^pcK}aJt1u{~BuSbKujMUISmm*$dm0HGxi*ibqzPvdK#_U0*z+poxfjSdAb
+BuJSq(`BiMS?H5s<?A3wz)3N?uywV}j<DIlx7m<mF8z!#4({VU0<&VtLF|zbgP>E~MFd}_7xStQz3^M
+qxN~IQS<^kOJvdalIwj5heD^HD|EtnPK*;gVfA#3Q#S~T)F>0(^^XvhHeN2#Pnk?|gQ-&-sgBvVgpi2
+s18S|fi>Uyoh&E+0x7gZhU3o@RX^!-z|_6{HSO&D!g5jn6a~D3)VYiju>~C0@NxkB(o_#?cw76!zF|S
+u~3%DK7(5f_2S5aVYU7@rly2sDzBYM=9s)UU2*>-*EB`&-(Chc*(7p`W;m=<&gH*I~s(;t1JA9s)8SL
+cu7ux-;u2QBDQ4&dN|`UXos;bgK{|YQpRa&i~j;pO9KQH00008031s8RszNx2vG<C068H503-ka0B~t
+=FJE?LZe(wAFJow7a%5$6FLiWgF*Y+YaB^>AWpXZXdF@&MZ{j!>|Gj_3yH=-#9ZCu9R&$-}==ud_+3n
+D((A%5qjUp2quxes9c1qdP{qOgl69OSgq22Ckb-J_?V88eA`|f9FZ?E`)^VX+M7p^)Nt!}Rc=U3MkKS
+BxZ-VXl3g$hh429Z%=MORO71mFjzRRI5Fk8C6bvt<3T&>+PiWZ@j}s~>U>TKQ(iLjD2fDguuM5b~kWF
+&+nDfCa+?6(avc4TV3ap(q&g5X_i^;o(Gs^6igL-8;DATI1X&9`KM!xQPZ*c*uMuJRWEcOv9AM^q3D}
+Ft>bd5~P<10&Rux%m@{H04{Kz)_&xn#t~@NoyBSiVhvOX6=q2O5Y&_yt0?pwBtz*Iob^HzEHxd12rTS
+aO;N2e0-~ZbAtekrM4J1NtRVu@!cU$4_t$rQIO~3apU!S?&$|6DACT6J70&WU9wUj#R0;$}twI)<ISP
+&dpIf&V-y_G_dFQIr|3cEYJN<5}*Ms);Eu6v4*=@gbad&lg3paPSH`l#Z9iYeg!o+0EA|t0J_7QTT(2
+_%Ln2<VF{R_HRqkwV<WA@0=%^nwzC>{e(P3JH2p;W=h>WeH(gMI+vL!e9zW}(2?F)Hs}L|OW`2A#mG*
+Wfz`iCFL;(FHwZZwnux+fu2p2Ioo}BK>@Zyp5*gH1?gth68Zd!;!KFTHVVnQ)q9;57h+Bd@4{Ybeakc
+s;W_ty8xx!iRbIyn1z~~X{ZKhoP_QI2YcMy*ujL52NC8(LO?T!+cOx9J3Bj`WLm>rzwI0!He;?z1_RR
+<vln)EckQPQ*qBLEJYiHT^`NbfmFGoa$ODht4E%+M3Ny-ZU89`Ec=j>$Ey`@nDUYl>d?7i7zLkNZ55F
+8Xp(536p9e#M6#xeZVwC)<T7))^i9j2MtJN%qwvv#^q<G*^fqylU|NB4%B+OT+zO&3W-WZIO8UmS*4T
+Kb!4;UbrTXy|(3i5UdYz}b3=EOOQC{Tw>9OwAFwNRe&o}<0UQn;Fte4*YW3k5fVV`3~!ZNKbc?#~dLN
+{1Q=4?~}P&O9t5nikPi9tYf~-10e>B&DYUUkrI*$OTiXogRg@1^nFUx|r*?Jr^_Ey=?Vc7yZt47fzws
+NLFNM%O_L;VaT`!Ldp!n;!jiVQC%X<HTeXsupj@xJi%fdNwq&!S{Pg22(R^z8(gAw>E52<Lby(&{+FX
+zxgqz#bwwbI>sHV(eiimVLRSSm4mf&rG{tbN)>FFbatb->i^T{yJ7dLinQ>7poV{;+g>T^~OOrTp6Pc
+?iRd9ASbLxrlx}UPdKSwMEszLJqHA{eTz@!+uk@2150l~JJ)chGDxtZv&xdqZ;vkb`>p*HTAN#E6&z-
+ojFx>F`X7YnxaxmzylR?KB9ha3wSdNqxRcwj>~EV%yQvG9LaZ^{fy@i(l%=vOmOgCN=1+<;B^G8V8gT
+808{?6K0?rLrvN3)@txOCowgZlW-NU7X&h`Q1$ras!0i1VQ$D4ua-4LOd@8%`YML$Y?B*#%>8}f?F$X
+1U4FWirII|OfOk5irA>k><g6LWyZ28f;_osTddI5b4y-dDrR!r6ZTYb>KFmpygh)UdZU^HMsxjY;ARF
+mA2TWLKq<L|O(d{uW9VAc0(GnFa%A{ECX8i!FEt01jHh!&i%QYK8fr|H-Cr{(gqufl-VCYvYmnB;?fu
+~^!LYe6tdJ>Tx!dI*((UVp`JeOrZ|HWp+3mJAzufJsHR!F~UMciDdh1<Ts#MpEmVw*OfR(};^RCd@Z?
+IgEzsMC^`0G_^`uqE<QR=TZF<^neoML~yNq7|dt2n<b0X2d)2i@fX)yiB0>ibUY^~Jpi%-4dpesQ%x&
+)*X?>Wk=dz;=yz__WsubW32DqoXypV)dPrFCJJDBzI>awlf?WPmSb(efz^{wDC!q`I9H3A@xi#<>mX7
+5`Pe7N;)=Xs!t9Mcu=2-2QkItHLI&|bU?ojVkrt0Lw&MwM4D09{Au;PLJuCS?HoGzBg)|9W-ANUQ)IR
+NTF|Ehji<}^@YmCL0_!z?#i8~x7uK4~l2b-MjQ9o(4xiDW`Md^)>l!r6G;m&{flM_hj8*42AFFhhd3~
+%BcP3U>g4H=*3s&d&*<iKdM?sni&NMJH;cM?bSwNKB-ZtASru2kn<<d2njfFRcNu&*3POYw)BE>80<H
+tF!>?<kNEWQ=Tp^JFth3ViNm!(5mWVSq$X8nx-ix44FN{2W^&a-rBY;1q>%|tytT*j+i<X3B#td>9fX
+HYpFkBjtq!3wWE$rmrbN$}S@PHu3V^CpgyTRP5pk>m2Hn;o}th1cGqyu@(@wa@2#n3OpxP%fS8<M#>o
+$sIj?(3_!oT=-V6xRz^DY4NCfq#zk_umw3<G-K%j{Ld@bXsNumuoF2Jeel*z8snV8VTrcScO4eIx|uV
+-2gG7EPOxixJ$v)yXpJ2;^6cJLqE4oTi;eQ`6r62+zut3}AY{FgnNE6ROQGXeLo}SfAhMIomb^Gf7ME
+Jdbty*6zcUx6-Rr*lxmC;FqPDN^x|eRJ|DUXqd-j#C2$-y)0G=4)hGb#0jqR!e@v=E-MjX!s$=eZ+SE
+|&U)ZaG>`iSCd-i3fG#b5!Q8ucR_!METvnn&weAnA+)%0RbtM-KzEO7cFEUS7p7iIBi!!8eB9zR<2uu
+e-moZ^mkCXp+;!NIY_grrRnIo4wHI?uygN&1<&WaPgMy3(=_Gtw(>Qq-f=DJ#&QA%amNQZbuv6>26D#
+!>#7B5H)Npd)n&Ge*sWS0|XQR000O897^_9|3CY<UjzUE{0aa7ApigXaA|NaUv_0~WN&gWV`yP=WMy<
+Ob#!JpaB^>AWpXZXd97A$Z{kJ}{?4x$C0`&VZpi7X<kFl<z$B<(BirZ{Rh6~aYgonJMZ4>y?yv8xZSW
+b0uBqxz@w`0q%roO5=jW#%c(5O*4$P(_+wpC9n7O0h;hos?&N&1d3a(^p#z_hz5mR6aGVwP{Q(_6Zh6
+rs|XBRr<Of!re(^r~`EtMb=&?hi3-l1AWWJ}SMWjSXN(M)iKuW~D7`GUZ(5VEpIk`hg0SQRDWaVa7V*
+0#V>8x7r24+gilHwbYu+=5}6f@fkCcvMmOO5>`Nk>FagRj!5Xs@@m00L+Pefdxy~l4WoS$WVh8uqgCK
+@VbALCS@y0WMNcFB&DE4qTi6%9TXymh;WcJW~zcmAv6#k|12ctXCh`vVN5xXu^q!&Q<<rqhL6q?W>g_
+lc%+<4>}HX#QWjzIj75|y3Pi!y*wm&`YGR1^H4&HygfG>-1Io~EYQIvc&;r-iU{|e1?1PZdCED=EX>L
+to4@no0;xyzg(>f_Z(`gKhm#`bu9{)f<Z1fG+2v!twMUy=3BLc?4w`uU?E&~`k&+u*Nc|#|7zQb5l8o
+fBb3W;Uglp!#7B?;FB5=Vf!?Twx=WB4$gO@n8{eliUl+xKDOdN72=&<m!c<!tD|V(Beh-?jjJN_P?)F
+;9uSmpDPlOrVl6)r6(0YW*3<tB_zC!-l+49CJh&ZWIvwM7G6;W|#`TF8jrlM$kK832>qN@Fp4V4sPGk
+bP=VQZy%RFvik6OfI)=6q&NZ}(<dxJ=t(Ms?8Adl+Jw%Bn0s|S7+hTrK3xp}mOfhEd%$+a|MG~OcRGm
+_8R%lmuq~XL`E-^X3DzDf+7PLz-b%4TUFwJt8hxr4rEwRCp9o(ojhmN|Xu~+&N0%Poc;=O-PN6)<FQ|
+^HU1eAw4D>Fkj?Pw*QrVtlFu4i+c{q2+_N>$CL@80Kv{tOTEsl67@J@j1*dcD97cM;a0q)_-`rIiUF-
+;&08Q!5V>?)cjJ-GY|j^MOPG>^*hGIe{_KCaieFryYAM2hz(TJE+8AEbsTM3}9@Qf$Mk?Ur}}HI~~`t
+qeclxyw3D^0fPyNa_C#$B&@8*fXftBIG2a4H3L34G&3mE;*d#I=Q?#dk-ije4Uf^k3i0v<`YWeGP;jP
+RMXJJS3CQMc~_O$9G>FO67c(7YLLyTh|J~NgX~@A*$HKmP>2KZIQ>gkzHZcO<>4J@r{1?V+p;~+_1dK
+x^>@|2XKXoc5YFwRj1~UmzI>?kH1HAVL$xRF(iw--;D4y@2YB3%i(}e>wrgCgD3_9QUG8B@dAA2&@8S
+A5yP@A&+@J1Y(CHkO*z;<&IJN_O6il7RFNf`vNhKS>6Bbh*QA4D%`%kVHjFv$dJb5<0%*Ovs*uzb4m^
+K@Kz+wNTB&i^}DVy_@z0mTk-QFH`-&W{X_@&LaPQIvDy>%%sE{+je$u;+Zb%p<aRY-?@)z*IiP)h>@6
+aWAK2ml;P_Ew(pokO_*008s=0015U003}la4%nWWo~3|axY_OVRB?;bT4*ga&u{KZZ2?nO^>lo#4r#<
+dw<2q)m>vjL30ukLQv3v1c)|rl1;KY+Z%b;2lw|xr$eHgnOD5=-n-9*6<NlX2=v2h3MuIf6Da33@pMK
+dt4t>@Gi)K8s47cAX}PBgnJ_G|j%04ClJU*9aDkGw)kKmamJyff%0XMd#^D%e(%{@7Hd~|~@DvLkQ!E
+z@yD^r~|HX$nM^0goymx-{c3pS%=sMiP--X+7<K5Tu`^U@M>(>0+gKj@;=Y!w7Ur<W}1QY-O00;maO7
+>O&00002000000000Z0001RX>c!Jc4cm4Z*nhVXkl_>WppoNY-ulFUukY>bYEXCaCrj&P)h>@6aWAK2
+ml;P_ExC1H<bAV0062C001Qb003}la4%nWWo~3|axY_OVRB?;bT4CUX)j}FVRB?;bY)|7E^v9RR^M;i
+HV}T-UvXej)E;c1DbN=I+OVzbRv=4*G<z7bK&B<iCPIlCN!c}m{O`LXC0UA{p#!D|TjCu*-p}vI7>mB
+-Mm7%iTbXac@dsf+*8;SGN*e*CR010Awib9@fDw&0j#R*Hg)~qICvqo>NYuG5WWBLb^vhRXHA*B&6ah
+Z3A>VQn6v66BcuacHh+*i<>-C}p_OdSY-YzfRy?=)vZVS1tOIhF<0^Y{&2lW9U0d8|CPn0j>w^8(|gj
+)Abpihm_JCqj-kgjuCqEE7JS_h@k6<CL^#8JdBKv5(savHa88g8uUzwN<BUfUfSbR4?nPfi%VR$>8{(
+z*qFZk*ILS5Z)o<6be#cEVVcWmzw3Ye{Qdg=k?CI^92d!G}(OW)-5u@LQihLeb^S2S&+S*krKdZhdgV
+-Y>kY<`u@uIs+*%?<EU@O4hRCDuK1u3WXoJvLcA=R=29ijG)b#5*wZ$p6ktF`TgMO9pc|7elG=({%?e
+9O%0rmrdS2L*Yt`hq>QY|R_Ln;bcxEoP|(-lm36cl0Bjs;E5VHLs(1Moq5La24IAM+_6RZ#doW+(d6W
+p+2Wku(qIHG8B<`%i@=^+OfUeT2#~I-c5gr4b4<UT<%di&^BoHKn$>fKJ`S&MuqHotq7Xsrf{%+-tD^
+WZ9!^pN5%z)L3vbkDKQr2R2Ps(m~4kA6bIQJkW#)~3^&DBMG@W(HwKIq&Sewfk1d=R&BDMayX@fEpXT
+#kLJTVD>8VWo9L8Mk~#k>ozxWow8WV2O=yoXlIrjXFSUMcFElWr#X2u*`n?{Chkcfs!^ZkOGrQ<kzVC
+5aJT&N?S1tRvBSi<<O5d4zE!M(l^wAVnPc9tvlA|nBDg~P9-Os%Que{;->^2Pqm*;*l$oeuA$nSXpG2
+uM5M@|&N^<XxU6SLdb{M<*+gl+z3<WGD~ytF{Hq~ceewK;!$M&n=DMnAZun#)R$Ea``cZ=YiS@npWo{
+kjNEFki4o6>heLrkoAk|a2Y$I}6N>Oyfs6T5-XT_&&gHwR)Twt{$bH{{!cahw$Rv;~vMS(SHu@;LlO9
+UH6+%xg=75s`MbKXa<;O7N#Z9hBWA3OQAm&^t;M?{{^CdRYdZyn0hiF{-cHsFPtosVpbc~NA&(Z_?CA
+BNp*pl2&old_L=@P3Qsf239HqrImwB_9N}AsJvQN&?KVjyRT75+>?=1W4gchp-UvEw0R%S+n_3t40l*
+vhPM4JIM5ovKR*Sx-Cm#x)Jv+-Yu71d!BfBjnf5lT_aUYh6mA$!(ih@hNx#69PXz<iUSq1lR480_8)8
++8-bPu`aCi0=EVsyVSX$V8~<;nExQ{ETMR(QmF_Jq+3Oh&@Xg%9<LFNF#75^(8nF$!<NO~TXg$BoqhV
+H*G$=?A`vN=?AU1p%OUs=*%;r;SZYX8bp7GZIsat>DGi_Z{3P-n4+<;>rJ=zI%h~XNE&jLGz`1$tca`
+^$=ULu?FaG&s8749c%#p{RA_f#KpgB0m?&OixlRNQpXtqC{Hm>3B^Vb8JRD9H;lb!_GtnB|f*|EfnR?
+jK@>v}+1s%v9kxL(hck+%0l~yujd7`7QdfmiioZAB(dWi=YzTUod4(m+KNQ!hTx@DPBsmjOI?3v5;gx
+gyzvdP)h>@6aWAK2ml;P_ErD@0006200000001Ze003}la4%nWWo~3|axY_OVRB?;bT4gXbYWy+bYU-
+FUukY>bYEXCaCrj&P)h>@6aWAK2ml;P_Et9qQrImK008(j001cf003}la4%nWWo~3|axY_OVRB?;bT4
+gXbYWy+bYU-SVQy!2VP|D?E^v9xTia6;+17vOuh<_x9H<YdqmH9e#aD%Z%8V!q;^@>=rju+)OQ$=hFK
+}?mD!E?-6j9`&2;T34c<F#T58XXA^*uD5rzCHC{*$wIcP^cz2@Ge>%+az;r`KM4t>0ezx7NO-w6wIO3
+Cm27kr~AJ1w}?2!*?i52bPc`;UMz&AVCpPSO{Vc$s)t@EZ>0w@QB(4k-jTwfp0i`q({beAx3P$a<eG-
+u_#p`R3|7L=)jIHyMY|SB9cSUMnWtPpFoi!D<ZBcDQOL{lA{~`_cOGO;E1HHLgBQv?V=F2Unv3THHc*
+t5rvC5AXk-?f>$N>dr20lxokKhh%#cN0L%I~EX!b>BOv!gTmmOpNv=SrA~GxR3|CUJ2eqE6KUIxtgF$
+q*({`TWQQ5br8V^;TEiWl432=-gp%W?Ns!I_3f!^~VWwPc24($qOBas2q##Sn^8&|VkjEHz9jH^*AI2
+TgF&?9|z+PI*opzt*S^sE%BavFm-IMo<DcPV5g!AEheM*Auq|50PhDfIRJ!<Bmx+m0fFB(Z)DbnbV*w
+}-+Wv2Iqv6}H0sKVTI&g&5u$*#NlB2_1m7?Y1N%5leur+rq3hxmJQ6pFKv^=v)Zf>OeavMzt+<jg2TZ
+a!3lL!;0ktoDzgEp^-%K#6eFZQy9CAaCPPv1kPm!jVB4qk~0G7C)ABmH^a+F7LcSwoPgqkC?H}+#>k0
+DL3DSKRRm)sBcVOdUxtf>7(bS?9WephK{hw&|0ZQbt59P*`Y~hskAS78!#}o)3jVPI^#}?~A+87U7*G
+P!83<)LB*2JKTvHu6@Pess>$BG7THVcdvOY;>MA;XiJmFY>4!(`xAj=^8OB*FB<IGbCv2Oe~5u6m6ZV
+rOpdz4atvbu8S35D2gV4)%TFxx~xKLl|*^7%lG?DLgn`j#-)o(*be-lQl0_n_kkRD(_myesgtky~6YF
+Sy`69gpn$Y-D8gQ0}pn6>7_lMDbn=0ohJ_Ija0W`>{F;iW0$MS$S0kuJRnbs%$Q*vC+zXk;VpIra$Hi
+WIzFl%;#K@%w(&{K$OM4Jx@(_P7uNC3{C~nm41W%w<a$OxTSz0aFMoKHN_nCO=pvL{}8?~+u9gT!40A
+)h-IZs3WO=;5SW)4?VuwI5Tw7O3|Lc|2foXe($cDn0?U_Ca>c<ifT}G0w!FOD4TtTQJ<7St^1}s`=6~
+g$JtB^X5Dv7d9X1e6Sw|zlU14Y`Qp+k(%C;OF+Dm`xyj=5B*Z+u@OYMo>S%JDJ1KGy-d_gt<;a0`UI4
+qUf4p2-xt88<mZdMMJmHJ$OWIu@*>Ia^7kWyu*WzgmG(J=M-E|>k3G4OIZa6-w6+LOo5)*fqU0egRPx
+T02M{A{4KI+M=Ja;TvuEl|h?HKmML>M{9i>@m!~*n`ethmF$-1oP0|E`{U}Bio4-lyZ<zg05BoR#>Wl
+d>3G-1ZC`iB8r%&$u%H^!<Ywdgo*CX274TpR2U?K*e-;m9tq$@AxK;t40r@`Gib5f=J!{H>}o8G8Q#u
+)5k-V5fmScnejsSnc%<pj*I!i?kXp_6rBFOn9y)a3aOKxD7|u1GtUq<GrE>4S1NL)W^TB<8cRqlE(jN
++$uBJ4xoVcHOka(DQlz5zYl6abUmUy0ck$9PSm3W<alUPZtCf+9267Lf46CV;E6KW!wSWj#uJ|#XUz9
+fE5UP<;Q`;z_1f#hIvC^?)QNscDRl2?=C$%*7-@>=qGa;kJ|;sg&8Pm%+P_sL%9@0rhjSWP@mjwROM-
+?OyI<<5VlM=-~TiUh@Bk??T|d4-T4?<9o0Fg}on@m~6D4~~s?6BDTG5m}Cd*!6_kx^7KbH>_#vrgh8e
+wPvi_){r%4&07oB9qX>OXx+1xtYz!I^}w369$JsA$JP_;srABoX}z*uTW_otYt?#dty%A^_pvGKgY_{
+sV@0iXYs30veYU<>KgX`bdSiXD{@7w{AT}5qiVep`Vpn71v5DAZ?Arf-Dn1lo*$U|T5?cgqE3s=nsti
+6{0o9+Oo0Wp$P`D08+-5W~GM<Cc@rMt_fde~0pJG3|1@>9wpIOfV`#j_+?v}a*?pf4FV`G3jpuP>}cL
+CsG8+X9mMjY^7fd@4<RET)pB^(G9LECxng>>MOC(_>Kk{jrKc|iZ&8(wW$pU|&q&-4ZDl`*2N8FR+6@
+km=Y-e{kVFIulYu1{*C`n)z_3~STItg&P~)aH%X+Fj#wafps{Oc$@cqB(`(nS4a*86MVUMIcEDcwrJ`
+c8Q4-Y?-J0SlpMQgEImwDz|{^v8HN|v>|O)8!YbrQ9+d0AkO#u7#71tCtgax({FDI{8RjXsD02rY4?6
+xU(^P)8SPGS=QAsm>f?+OktGaOO92uh#+}80u-|*(fVthW&%r#;_j`M5u9|PnHS?YM-uz&GG*vTduA3
+X?C-bxU#r%2m%4Y9o|7PFjz~<oQ(B|;w$mXc|(tKsUHs5THZ%%AZnp5TtbK1OV-ZE#*+vcn}XU>}o<{
+k5{xoF-qm&|4J0sMVvJ~AJhPt2$0GjqrsF-OfYbKIOXx8WXhX>$Us`B-hvLub8U+-g3yscnxU=%yt+@
+#X)WINM2Jd3e<Xt5{z%JQVmM!Geq7Wucfi85vK1++XiOrz_C83iMrty*+W>uA=SjH-@fIxZMTT7J<b0
+1NtZ|4?6U_A^j11QGegbg?S+&O2%DTF<y0Dsy$MtkJL9DJ*M9|u0L%2Mt}G1iKdgMn$NTtcUsRHFWW8
+@4~DkXOcSd05!@bO^t(bnfGv^jxHc`}37+)Vk<O~NtUc3SX=~a#kk6FXtBq<C+O#&mbN*?DWdsu}NIw
+mdEbzrEpp1woD)MeA=&M{<_UFNJ&<({NR9AtHRv=@kA{({mE6@e_>N8@*)M^RVBd#W#!0_FI7?eB^tv
+yoTaO`;FH|ZE_J=><;atNLA2XRM;y_gPAS?SW=JG5UM>jsJCa7fNa_$bS76Lo0`FMQkCzb@(qDIieie
+1=31{zE<VWv9{BAj1NtODVttR+vTWzm$L{65dPaKLZJ4T3gcYYfrSNFbiL6Z?vekp*=TlXjim8ZCD$D
+**K|P)8@1VZEOb!Y0oG`wSj<wS<V-M1$TgrFdVhxh%v3SqcUKjFvFGS!*?9}MciEkzLbC$e4$-08xQ3
+Hw#E7+emy=FzY(8~-;Cdi&%|%XXXA76`S?QoPW*0sF@7(;6km?tk3Wb%j6aG$jz5V%jX#S&kFUg6<8O
+<D2CWuB=d=%+T!%(;1*-~CVC3Q?mJ#v9M)b~$=d;w3IhTTenC;+^%`8>BLv)8r5}Gt8^x>dB1&PzeNX
+9a7(k0^yO_}5RP`!Q~(x!{dj3uD63)?MAj?rZa<E%>9KtW<SuJGHgjk7YIs4D-hs0MTKq-bUm><43tC
+Rt+@(5=tKm7<zSy)(vjntqLy;wXQMF9nS$j)~;s+bA<!adguXUf8nUY4=Y_3s-Ey8`o|C3Ufe=loVfT
+Zvne#aV(&yWg+4+gjZ1Eo?zvW!faEHxP-ir;dWh+c$6S+tiH-ENStt{mGgI7R?e<^Lm!}%wZ1{0)n{l
+>>95b{%va;B@tn?CMjxcJK8W=>{WgtK{Y_8K#5dNA7j*J(3pJn|WTCF`MHC6*kCh70X5_AIpiW76;@t
+IT;+#txlrf4{clwnS+BaZ5aUalr{>``ghZFin(@A4619=MY-W1@|usV4FfWNrdsek13Phs8|%Amdj%v
+<!{P9+Rb7jP*|C>-3b%ytQR;T`VWE#96xjqc6foo_t$r?wsktyyct-h3Rjw;#t`8<69!Ey!!u)9lt`Y
+}(m;jNP)-*eu<CjLp#v$k@DV3-XR@6Y^ecWZMnj4bcB~M_Z5eid?kxbl!VG&wFpP{AafTjtfG2Fk&-i
+z9-GXHhUT=0WV)7Ty9cMG1y<4ksWdzqU4y$w?;2a)c#Z2G@YvRt!K}jzhFd-4Tl_uDLJMRxX}l*bU@J
+7=saDJmF}KP#=5c1LM^*YX^}+%GE#@pr>%8+0WHc(hk_+s6zq(UC*Xf!rtXF1Nk8Q4VaV5GcGYqdR=M
+*~>)h8KK<0h|nftk2^}K^6?)r|GF3s9<ZYIwM&Niwz-DO0)Kof;sg0{nm)B6E|*T2sFx}f&~Mw7qJ{y
+P8rY8Sn~z-L9;=3p-^;pwsR`{+IMmEE_S>vP}a@_z0+`+C}${BLtILtZzjv%<n}54bz_&LRbee>*&c$
+{hcB96#>t2rP2|xlJ~?4K}W2GfL_Ju~<%N;e;-x*xr3gz-z=M?}Yvb9%yL~og*#nmA<Zjp@&-9JL8sf
+tmPbPX#>u&mNubB_0RNROS@^@bdI)mda$)jmyp^r-&sJP)OpMo<Ic2%Cq8+Z>c40CNUO!I7v%N-?qWO
+-#yzM7i+*~aGywnn7<G%REMuPDi17<@2*8!$BhBOKd0T<}ihZL)q*nrYA*DxR!x4^NPVAw#?mDn@=_A
+!VeFw<7;bULM%U-XOL!zK`gi?C!n}E%Y6-W|n^m(D1Ui`S2zO6(rtfWn;N`->sLa|UtNqB~Wdw<5WFz
+w5niEmYwUfr@Ry^%f>-?AuO*s>`7<Ld3-QQj8NP-}=`i$H6?_QF*T?RHJE*LJG4v8D3s%nhA`TinngY
+A;dyh}uuo0iq5Pb%?0LL>(dOC{f3VdX=c-M4ce&BvG#s^*T|fh<byl(?q>V)LTTIA?j_S&JuNwsPjZ!
+AnF~W-X-cHQST9TiKxp&y-(B!M14rqM?`&0)F(uJO4MgWeNNODM14urS44eH)Hg(3A?hko-x76=sPBm
+So~R#)`jM#XL{*6zCF;*4dWA%LNwkkd`$=?wL<dQ9h(w1;bc94lNpy@vuaf9EiB6E{B#B-l(d#5SMWQ
+!IbecqOlISfGogvZNBsxo?b0j)Xq6@{Rzis3kRZb0iVS52a_7)7ZB6b!p{nHYj!|k=rnXUgbyBPi+lv
+1<1;Mkv2xgO4&4qHSC@T&I2J|Vmp(pOX5s(qmBdQVogPhCBiXw9Z=0Lf~@_CetyEbLbtqSa<7)h@Q4)
+$X*Nzd%bmZ5zmIfo@xvp7w&Q)y86(Vp+84cL{kR-Q|61Q+Umf<%2@EL}58Z?{ZRRwKE&NtS9j3P^F)h
+UGmv(GdBX$jO&bBbB`Pn_$pVEqd81o?S2E)?cDQA-74gmKxc-)DY2jBS?Z75;-GK|^Af!~ZQJIy$iCC
+-qz?!uR~x2_VL8Un;i~WV{$O7M4-1egQa;kqYipzz%Uw;%TI<?Qq5}u_?yKH=`0)Pn3e?uz;smQ3v#R
+g+|KNs`X1vrTbwE?Z|4>*F2O&`@fe`(rL3aqd?=ONUihbQt#7vO!vm7h;(6k!i7<%Cy|5HY|G7QF7c#
+lE)cLsJr(oS=-Jt{eOGMPXCiW1rh<Xl(V(~1CNR(ZzmnRCNc*4B9XOga5UL!0eM6OREWHUKZ^b7j-Xh
+Nkk0@4s?;4x<kF8A6Tzb_50ov-Yndy6EmaXs_&MgL23vF9kw4j8O<M3E}`pe-D9zA`^yMAi!|;78}P2
+-R=wcPTpsNf_+t-c9IH@^iOZj2_i>_C+K$O9QJ!&{B#k*p)Cl3F4Ft~ditR~hic0qgm=FzNB%*#?0;G
+5`e#oqUA`TuqbDHR7*t&j7u@`1srfYBuK(pt+jr-S(?DJ5w~aTx)5>ofQvn~}0S_)dxLootP)h>@6aW
+AK2ml;P_Ewc%k4VM<000UB001BW003}la4%nWWo~3|axY_VY;SU5ZDB88UukY>bYEXCaCuFQF;Bxl42
+Adm6_yyfgj3rfHU=7s03ntjF`lf{X-zNZ%D&L%-*XkM#Psw&J%7G|Mh=tmc9-Ez66PHyctOpPCRolFw
+TD&v1odqbaWsO+9VMd*j0oOeoApP#hMpsN*Q*TRIdNu;T(&$ML^GU81snQHy<{g*6bB5MPNja2mP5~{
+aOAX+qlHeANu-MvlkwH}EL#4ru-jMA<|&rajB29)wpog&US3Zg3;L9=GjcA3A5vpUA;1I7=Kjv#&z$=
+OP)h>@6aWAK2ml;P_Eu8at%iyN007zv000~S003}la4%nWWo~3|axY_VY;SU5ZDB8AZgXiaaCx;>!II
+iI5WV{=R5b@fEz8*8B$Y{V0OQP%FpvVKCaLU}OJg@!8zXxqv4p?hmh8b8;#B4k9{}~!d);omwz(pHmL
+CM$B#L~<I8_Pd<c<oJ!h!T0x8EhB<(TyU^i#T%KvEU~m(U>+fJ`TTFk1#>%~I%EwryLhgh{f^;#~@40
+~`cZAjxpHoRBD?f<_7iiLw}jDkHgITrs}ENSX-~LVU|OO=Z_w0^E>9sr=^p8hCflzOfu)M!T8VT<g`f
+)(t^MG>1@&ni4D@lMRUdm(%ZmwXONme_s7<TccoVRuuPHF|183p~^yCoowk<`^F-82~a!1i5B~VNF@p
+kf7@HTph{4oV%Vsb`K<GFTHM=vXXBT_@f)+3SyP}Ql#u}7Eo>JIdQEA!&uKr{r`(ir_*LddeX~(YC7u
+MA%-8L2Wl#S=q)M*V4MWD63d5F!bX~^vbwyMHMDCu90v=op_)7pO6sb~zJ?-={?-Ld!L_>VHeFA}JSc
+yF387GWOMe)d~Vz}CaPK-BF#v?dU>zv4$0_YY_<ft^!iyH8g>;=uyDP+%7Vs;t-6+XdJ`*#PJ>ZrBO1
+mP%-MUa?@^V`=KTN9osv#X1R3MI94%MR_cjr#hJraM5BZ9wU|j9$lZ+ZTJ~#h%WYBaK?ST|dB`keRqV
+!G}-JLId}tunS{w<BFkuB#!5gvzJgu74`jm@i<(JU&8h)_GsvTd<k`2Q9sR>CG-2h?U2LI=?6nM!>E_
+v&GN237w<Cxt>b`{YNIKZcyeL`(svB72*$OeM8Gw`?IH+fb)aW}FTr#=f2;xhGRH%3CgmC6es~+qR>M
+=^l>z)O!`T_*wE-UQCaa(hyeZ3F2CF*o)-uQyStWo^c0Fio%0zm=!Aw(}_&m>qg1BRbN)JGe)+gDzm`
+5Dgn2NZV@#*CDZe@BE2A_@mTc-lBS4G$WZUvZL9T~j}D0*cO1p22r9)eN}0j~neUTF-0R~4XpRWV*yf
+a%pS`J0*-Ml|~N3tsS=yx=u?!E5q@*W?AS$qQbS7rZ7fcuijLey<l?r^yVi)8q!%X|jXsH2J}GnhfDO
+O^$G#CQG<Z-4jc7NPqBvSZHFYWg_Fr{jssdJ<R5d`{A^V^r|xmhg1D`#IY>>>@o21LDaUi2ahph$hKu
+_c#ahXwXNcPPzKAFL)-cvP)h>@6aWAK2ml;P_EuDTtY<t7004L^001KZ003}la4%nWWo~3|axY_VY;S
+U5ZDB8AZgXjLZ+B^KGcqo4d97M)bKAHP{_bCao<E36CB=3+oz_=PDl58+@0{eu_SH>omjhFf#S2BS1Q
+<uX-hc1z0wh6@qIK7LCL_M=KG<C>o?U=BWOJEq^Z0SC*>^JKdd*YzmghPVTXu4E{A$9^uHLX$<9WghC
+0G(iB2{9<lo0IVe7<;pwP33_5tD;>lgV7OT$ER8tIA8M4h~ki+^`8xRm|+u8C-uOb3ntZGah|1S66zQ
+z(f0Uwz#mmPjRY6zA4p3${!LDe%4`@%Sb2{r;j6c6Q|c8L>F_J$egYStA=@XQi8zEGD$}G%d<GtLg|B
+pgL0%PdoNRPXl3PCtXL{FJv}{O@K;OPfrBCFM+sL79LNRV+~hpVL>|b8pG2gGMr|+{&@aAJj59@|EKo
+(XW?aGjQWknRVm#8|7Cz!k=McS&=OWb%T>i3UE15H%Bm~8^&f|wd3(&!6Fb<-ck<S~U*K)}QPkF3GFd
+Trt>lj7?ca|a%k6eo-(~`*|C#<<lKZ_h3V{xi9Pa~LL*X*TOu`rC&SchStM6v=va&tLiQK@TP#lJ%a?
+!aV?i*zY+6~Ux40a9DNM(<$cEQfpW3nRA{3gW8QEae-xlq(0P@)Dk>Os_>ba2Y}q=1HZ3)=k2&l$w_E
+zJN6w0y?c-IB>ju6dDJw97f|D7jvPDJY`lYXbx+oT{wYxQ-QtU`J;lL7oVQ+su4Psi74htIf;pspNfn
+<Y%|C)2!mtU%j%j!6o#};9jLX|nL2&>66Q4eB*Dj3BA+Ia+`Rl(0hu4mRJ}Yt`QxjTKmGX+FQ3-i@lp
+zv>aj%~Kgs;l7^h||zQo!A*6Tvi)NAoYC-DQ@@W(i^CPOO1eB-*otc_t7KF8d(+Ye$hc#}F<ewZ2o{o
+-Wf?s)DT!l?I+poE6NVO;Gfbmw4O&}AF}6yy=T_j1TZ*lCtQs5Q;HHG^V=+hbPgJ2A2(RRhEdBE9tow
+M%B|MWcETyf^sa<NWRH@?H4$!`1cT%>W1i*nA?=&v7o(8p?`WM299BPnW=J)pMu{Fp}Xn2okKfj&~x5
+*&a60ohV)BMV-|;-!=seUT9pVS-|^=xvwO}mq=t#gUZFS$a9%Df$V7C@I=+a3ApJLYYZFM*#8wW9?0L
+0i!%`=Qi<iSor#u{jX@^{)LD;Bw{X&sDkBah97?>VJ3A&V@d1?UBBP4<Adr$<h=1crVbQSa?1WomsY>
+8-xdkYZg3~}YYgqJ8Yq*2thlR%SB31rW1Wlty&XB`S=P3=!VvCK#wY<UF-d$?XH(4S!z$92ot4dh1D%
+Hag))atP$|r>_0Tg`jD$dyK{na^();x!DEKG@10w@y-qcRm1BY<meMEMRY0n$4ww6^69inrccNV`-~1
++qTXvTP)vD_Iq3gftAXO%l~Cx@bf=hkus~NR(V4Z)ebY1%tbzqvO|iN3UMp-Q5Pk>(jft<$t~&z8D6#
+eEjd(_#gK}kT`ig7}88aao4#_*p>Bwo#Xwoh^%Kc&WEdc?>P6t?LY7MJ&bY39rXI|kbQu}=M;det<vD
+@Ty8cH9hVS$TZk$0$H+{9z2*f_oB$%8(yDCK$?JAA5Tr8SKqR+BErxW6a?Bmj%&<wM?KZ(J#A{h3kSc
+<a31B9)mkOsBoZ&@+nYF^EiCP<Gnb;el@&LxDuH8{0uv`mDDAVMTB^XBN&TLv)|C-1Zhcx@nDyl>|^+
++-epG>NQ3Q#(BC~P`qgH#V3b8axNmBy4tlVEksemG~?2*46~5D{$)uy;cV2o09{dKEc9@NUDA6Ih|Br
+DfPSL))Dg4)J-Y9?by>#N=_p=G#Xwon2e~;RI3`<e`EPCB=H67_>+*F=kmBF}GcjjbY64mP?`PzR~2M
+g0&c0QA!IZYPisyZG$t>Ew)}c88yM}QYsyB%YO^{iT$cdy5r+|u4yraz_TIj*W%A2q&?M?Dz0N5q<Pm
+4DOfG*k=Gp5O_fA#Cyi`LAt&9(Re38RQX!UM9jvN*_9BNkG(@NM-K)&uUXN|-mGIhaR*V9qLA^h#qDH
+T#Eps7CXjU1B)`}t}`rTopxhgr`GZxw1GCL7^!`f1()86uB+hUAlx4E^By>d;)mJ+s7jFN?NomIA#Rm
+bEsY#V_JVAUv(8&NhSKgvc0`q|KV91PtNkqMqeO<#s^UpGN9N$7bASu(I~2hGd6WSDqUf8_U2Wu3%7Y
+z+)$At_LU02ffb3#tYfQ&@@Ye8pB+M@C2krbjYq<u_(jxG_<HzW8bd-34vxAbaSIGsP$oD^(EV$_mGg
+0u~|LAy*dVkTY?PHeI91g!(8_sG#`vq3%Da?jggbG96o%Wm&>CbY&Z$<RVRQ^Dl`>fLqJC<w*?dJc&Q
+mP<1K7rj434Gy}K{;%`XW?1C^;uu?nA-VL_9cPVoai)_7w$~&*%;e`4r<V`BBY8Tg%E^>NjPxy0d&rq
+ExO)eK#i|cT9adFB5i!mW<LXJm3!%>g!+2#4SZ?7FiWlpEcvn4Cgi}B|CT@S$f50~#|7rg*R<hNqrQQ
+PF~VmANYL0HlGTX|MyUiax=F5c|chL?T1-(D^j?{{m{>puODi;Ig7H@gAM`+o0#T=Y5r<DyUd-R#@N`
+|H_m04vakG5<L02?4(C)4q9oe%<2$MDSz(<iP@HsrPAIU{X_3gp0pFlQtt_-DlAtNqVv1{hmmaFuhnL
+u_v0zo?bX3vL_y9(=$Q)aj_?sO{`uxE3+peW?C;C3haqRS^3;NeC!3o!~YgHJ<u0{y|{_=o807S@8%}
+b^|{H@?&BuXZ*h|c(92EM`vy0)oZrb!q}}Ew51^l$2*cwh51@yeNZaS8b_92ElbyUKHyQOlja}T-l{U
+{OUpF_klW0$*4sPm7sXfuUxT!P2_QY#*Q%Ab(iPgzX-O0BnVw;;fQgKhL4sPm5%ucXh{00}dP{DAoQ~
+9!OZMMI*iS>4-X4eByuoW(MdfFb~mqP7RXLqyIIP>2rv`PxKc3Sw-#;Pgr7@%s8>9c0(c>T1$TkinGC
+g1e?!C*5OvEXPlbln65_ap*>SDhTR4kw-sh}ZVJF0=#QIgjo(=LS`1kN6nlc^8V>kEY(aqdl{v{T@%Z
+bSmI%dwUL!%WWI%`K(=ZfLxvwn~i3DMpYjY`^H8^uIO9lQGF_f_D&lU6iO9&X@iIR8?N!=u-(!*=gyN
+AY&anbdEmu~9Me1pH$;jDRs=Co8Bc@Gl*H)6t~E|WL<&p<jL{>5)S*^djb|9a3p2!HE{jYB!=`xUK3L
+<Q@b(U!h}8JjP8LU}&Xtklwzm-QIr|H~*lXq9lENv7-|w-AYvUS0F^16z4yGXfhlt3Wy6?M6jc%DIU>
+AP#2+h;LVl_tSnx}e^dm66c9=0*PbA*QJRsz#=@OCxWVZAQ0L<F#Af^3LdIInQ^J6I4zrtFw9Jwq60D
+9G3(*1_QGftOHE>o^ex#W(^pd(!?ud02f4Xuqp$vlqW-!SSe%;=7%B#%#~orWfTq>%tTSew`0q{J;Bt
+GiVDnY)67`Nf6JwK(n*?n`e<QT7FG7Z{6ik=U!(<bte;k_wZezK%-6_?9PBxGX5!Pw?B9w7t*QPw54%
+NSob^iK&4W@J?fUT(6!w0X}6#~+nbucraFk7HqT|-lUEwk{=X9C+t&1c=Y_Ux#YE1P2vwAeDl5S){0#
+e?F|8rK?;RqEQ}I6zfLudw4$JD2Nfpz_+A-q~N+yLCohD$jWK_aZ#oF?l3^8kEhatI0=(9@0khCHlKW
+Prx43vs&#LnP%DWB32o5L04KFldBnm2HR4Rb^5%ZTA8qn`&eumcu28>hn&8=ToYx|!n*pdH~2+8d1N?
+w4EZ%YA38Y@GP=r$Xrf2kMJay9#1M)7i=G=xfY(?*BtyW4kM=<fo)^4-8MY*a6&kFnhB=SKwtw<1@Fz
+RcDKf-Be^tLL>_)7+-z;74iJ>GvwMXCaBq|a|k7LjQ<-VeT3FE)`|H)J~2!IY_f#;b|F)2VI7%WSjRP
+1g|L*(55ck8rG4UA(kWI22C|=4(9y|`T7!S?swK>lH;$dY%vK+qUMC4nbLRiop04)ozfem91QY-O00;
+maO7>RFgOr9w1ONd23;+Nk0001RX>c!Jc4cm4Z*nhVZ)|UJVQpbAX>MtBX<=+>b7d}Yd6ie&ZsRr(eb
+-k^*AKA+TWym93j{FGZJMGfitIzSn}@a#XlrD1OOXOet)jp0kh)Q_oMZz8k;LJd3(uTk7I3SITJyuv!
+XHX9dt?%RXW9y^;p&GUuVeV-@mILs+zM721i|+x4X(i;!k_oIcMp$uka2-=#PdRF3(Vp(x82)bNqV<}
+@47FhHc^yml|#&=;Z{{#USC1G`hh-uQcvzv6h$d!kW{?DgcFRGOeDsVgCtWrv1qJWu5KcrpMy|4CO}a
+pWRj}VuKO3%+S>$+u!RRDarBwYy3ZkGrCCv6+M@>V9q`yB#2y>Z!8hef(r!oaPUgQcVaE0ue<nPtS*j
+|NP<f3K&Cc1CF^1K3Q!e+j0I4>r0G<K2P%$GfENDD%L#4*Fw`(GbOWCb0H5#-D6Jq6!@Oh5~9i6qB?@
+EhzS}Ps;DQbIE60UB@<0)JWACFL>5L8=)l&7Fd4LdsBxW_1%F)bf@=iSj$`~ho#8}ed(p>G=Z_r{b6i
+}yd>fZBb*y)}?~!tZdea`dJY7I@xv9s|f_K%7+^_-`ZPlG`OKt@2A-U+=YJ{#Vp?>(HrPs5V9W>`1Zw
+q)Vg(x(r;%?mIA<(r>-|y9ex{T9kiRLv1zV)Rdo@D4VJ;FFd#p!EMW^Un$*++oMATWsj(V>4W!wvHDh
+~zt(0meMbErH!m~Y)-Lv2sS<;|J4%0yeY)ox4JqNlF2LBHZu+OU>o93eBg>bgyv9{uLvSE&&uS8|OX#
+J5gZ@7oaAR|_>Ggog?hOIIq&qDKgU>fp1vuCLr?Tb9)iy_pzCDIs4cQU)>ippa)>DAC;Aa7v+Kt%hBl
+=Prn~+#erE)S#=7lyq^g=L8gD8jZw(!nRv3EgdqAj)T%xA&Q8BYis<Ve{}*)dyz1w4|ld07+0le8wGk
+d02Qyuy&+JE1kU%rfGOa>`pNHvkN2qD(i35{&^;i+mbn)HwJkL1IN>LX<O{5(1UMQ<LC2RL?j`oZ}=R
+6%xYDdD0|qMGYv~jwTd2X))>g!M`GWczC=AQx^V0z@;;QZk#a#3=B_kgIPvW9>Wt=MG~4sOu^E8+1rw
++S+|%P>6rEyu<HA+a#U%&(Ac?9BHb8U3v3(7Wd*rPu^B^@?I0oHbQq9d68*`1=+$F@joZy<I$<yj!)Z
+u96HcfI-yRO_J{wNsaxjcuynQrM@bhpFjN8YYNp?W(TXL_2(ky3*TUcJwd?F5AUjA3Pr%pN?d#6jMx0
+;%xNZW{{<H4}hNl|~1m?+cvzI)STnSptmL`~*w6J4nC&7ao=ew4{{2%Yex0UeE&jxS?J+o`*4|1=DMK
+5-qJqbdb)fnJxvUB&0^o%T7Ct^W`W`qG+E6&CQ9aq2(?B$f5&&q<fbYgsrQXs(RZ@pM@&_pWPGx;~ap
+UPwojj9&ZCA^IOsO9KQH00008031s8R=Pbn$=n4103{dz0384T0B~t=FJE?LZe(wAFJo_PZ*pO6VJ~-
+SZZk42aCyyGZExE)5dQ98L8Ry`b&BAm`xGo69LH&0D0X1EON*fpWQmHn$)Z70vAtivqa;hztDAHKDg;
+J!ytn6gcRcD1n$Ycmk*83gPc(K#=*H-y%S40^=yG)N-b6R{EqZ@GiQI%^6cG={92<yZjI7yYI=81NAQ
+3hPgEuH(bc1#zUb`Hd;lN(qE<Uf&H9EhzkT28aGJUxm45st(jWu=tm@QYI$Ck62F7Ib^_~&7{m`rVZH
+va&eqy1<!`fV@}>~J+e@Q}@xGJ!mC*kYbiQj6L9an&Mg=CXrDT_3ZQ2|V(n2ozS9v`ox=B=N0f>0RnT
+I5UU$9^MM1jfG%jod`T-j4}hwQoi&>zpC1s(-@}|8;c2zIgRiN??s^jSR!|`_FeSOxhlCq-rW*MU@lr
+XaK!Odm$&N!!-0Wp!4gj-3^vMhywC+V9~QGYgn5ukP8N&hE$BXiGo6%@Eqam5Ik3#_1#FQ$Sx%>O=jQ
+X>-E`^9=64IN(4OO!&)L}-PsxbHQmsd0Gc<u(a5w?Mk<T44`)5Ivk9OwoZ1N92Gcvz)qp>_m7^m!kav
+}(gI~jLHWI6B@;2zs}IfIS&=}u*|@5h$qET@xIix2nio@|m$Ce`8Zx8gq^2gq?CB#xtT90f|K<ijw;F
+GfS{t#9=H=|l7uX%$)dNR?(5HuI}ddHvF0F4n7IR0L}aohp<7cd;DfYOd(EPO@+y>a-gw1l`oBOWBdS
+fi(6)!O~o-!qKxVcRpZY3;&}FwTiP+fTA`3#w^Cs`%6<@ZVH$#d&&w=&E_JJZe_}4Y4NQ^m_cO&pIU$
+)$MaijTDq3E3)^ED$2Un3U^a^b+U{rv^C@K~Kx8hJ$(?r)t-CYmb;w<YTLN&iSXepy?rvGf-oe?c=7p
+#$U8I7qOaJ$Rs}@}^x+-hGq8H*zTUZCKn&N(7cO;5(xkVzjiI~8-<9Y(KaSOH{?vv_Xh%i3^d#kh-2{
+qlT?9~+SbMl4J>Pz!(=2OakJlX&6h`qdSRs^Qg$Np}Rva}1H2#NJDd9+u{jzZ5g^m|(Ny?g3+94!h%o
+6sveb1m@g%{bNny|L~<V7DN!e*{6*^Y-AMc03)rl<8Ru)ALrDy*$1qAlozC>IE-PJP&gTpyw#7j%JxX
+BOAjtX-qHm<ul)!(n!m7>!shS+ls@vkQ*PgDl#1fl%WvD?Z%h{k5(BtwCpCP8>m5sJDIL4ZuB69VHUd
+^hxpgIy3)(=I7L<U7ZUo<v;mS@0`54)OWzIT0+GK8ZEmq^RM3v@W)|9<svg0rSKFKh(*9ow7uPG6sHw
+g!2aB{%YwwPf(!V!o79bJgl9_Ns6M<-em>WNVYd%FW6(NbA%tDL=g@E}L{SG&E1i4s{zNDnK3y)%WoI
+0H*aW<;+VJGY>MGl?|6Rj~gghuD`O9RAW7ZTWz@!XzC02dkAtV&&)2=BMp6H-#!8wb52mvHD++QHcCr
+Cb(R>^qHED)7(Ig`r}HcU_HCrlcB;3jAk+ck=Q+<cNEWMp2=yBEuP2@2P{lD2qE(MYw?k9RKwibjoYm
+3C=G$r@Xx>AzfmgY%nAT+qmE|qq0^Zw*N_))Y87Fle%+C&2-OVYSm;PLn0hMi4d-g!e!!heGK#fUp8B
+6^2fxn2Pc%KG@Q(gdRC>!o0ic_zBt)9J4S@Sag%wZmg}6tfG9#&zz<|P{DEcvTpIS%WJ+^cd*-0U$2#
+;uI4#V!j@mQ2wzt%l$Q}Ev;(xQ<DvRc`8zs1B%R1X{_m&NZ!#+JI%omKb@2g)hpttQ{QGOzTMM{~U)s
+%sL@nkUgW4<Li*my;XxYdci9IQ3D@)Kvtu^fBC+L|E+;O|P4wi8&6*P4*O%@L?EhUbiJvx^)Ro5SCx7
+-rSTotQTiRYx3Bk6!8Va6%rXYsa2TI7a1{=JYeM)~FGwv0fZ@y9=rDt2Uqe1b)cbe*sWS0|XQR000O8
+97^_9L#;>D?FIk<-Wvb_9{>OVaA|NaUv_0~WN&gWV{dG4a$#*@FL!BfbY*gFE^vA6SzB)!M-+bNSDXe
+ZhJ;YC(=>`iBpVZl)`kdh6F;q%-N9_L?4X%hV=Ak^y=N}F%q$l}5?6gFFYN4``{kQ6P=+?0FIjXu74R
+EPd@=PC_~<hclO-HCnkRKQ8=k|-t9I<CoIo4}B;lk6oDjI|wmZFH2PRQW>LtOJ?@EB538OQZ@w<Qth-
+Pz&U$;bfluuB27?TpY56E0VSM7Beqf9e~Wa3g*ysF-jALd7BK!2zhD$hpKh(pAaBLRyj3F(6W^sHJcm
+6Y~+rWm(Qj!UJoHVRh(P3qH95c{0N=O}5@7=_XCpCk}Q*V*N1`*-|qLBp)CJD}E0wZ0g1Iz6>MR_pf7
+X;1H;sP&+84to7st*=fmI=#^;u76SMo6hBB|FhhGlgYc$^uO*fbSRb>56946e{gkr3C;(NzHc<33}G|
+_LGDFOJ&pa~>n)>c5^9$Q-HVT-4V-V0bF8c35oYfUqjWLoU-!-p^IKP~5o0m0oEZ@|Tltdb-t(d)5}s
+G#B%WBAm&>|`6n+{D)TNSIzaXMb6Ha3?3>YEFSvr{z)=eg~q6vnh^ZxayT3?(B!J=_02zNzttTi9^c*
+W6B-K^M~P)1O@ekm7Q=%mXzom_08<1(c=p<3mXW#}eASx6WN3S^eXzK{(kBj5P~QIZvX4Hg8(6nkO;V
+oI{qDrt2~+>qk7FIFM~S@|5W&m0~IDI`=t5YzD(wG%&>0!7KJW=TVxf=M@VV}=gQeTMeMOT-1NT-#6%
+^p3Cvi-aHvjF<2M1NZZp9hI_e#5#kjd^9&Cyk3Z8tV&Eas)HY^oZ9d~M9LB?d+^dq5xjur8+=o-k^v9
+4n(9i2TQ@bh^W&7P)vGBNwF%F$x!rA3B^AB@{yn^|ZlKC)B$HCfprCHz^#Fx8R%2QwGop-+V`DN+P&8
+H-YxQWdX8V4PA*ll0ffYsF+Sx`Mk|jfA43dw^mKrF+)(1b9=gi7b^}@0=()_YwB;RU7ew<#l8+db)oS
+iasiv6~T#5AkWq0^{ng|gRGZ+raEDyAqWCFs$1#^){gdmHCk0#<R#pRDxDVl#o3j|T@@73;=8J78xc;
+O254yN$mq(Dn)Q{V}(seS7#f2{|wms-aCP)U(OO&hTp#*cgBJ5OI!{El{#y?*Q{HO6`R1{5_mdgqxkv
+TgHhMg0B!nkAwNquTOScc&^zMyw2Ad3~~zdGM^(xIJo4qLPhf$2dnN0Gp9Tf5lu`CG^yoow!hD?Vwmg
+UqMb5M*(bwmwaFO?)b#yXpZRzg;%E@zv`+8<M*wTQ8vC4t_6aSI)S`c`d?5F89Kbj<HFtf@`uZ1mnN7
+XU`y2PYIa;&rLbWKR#fW9geF`TJ=EmB=N$F^&N0yW^l8AVzXOk$oRTELhj{PQQAfk_qgo0_7dO@6(yS
+yHA>#Gj2cKlziQa6ivnPw(hm1;uohkvGAn84rHV7V*aPvgVRn3@L2iM72X^enE5U3=04yGG%@dT6xPb
+Y!ngKvqE{44cE_s%uRQXE=+t8oQ!ch6eB{P2&&;Y2q_|tCQ8Jb0UX&xgyx5bfO-$276?0?j>SOZlffT
+#lBV0u`5U`77@#6YYHu9ICopJE6rN-sR20P<LCg0v|PdhQhp@qOx{w^^<av3kU-!fAaTs)70Cokf&z?
+{w3TK_gV#-ySTsV~f*3rE{vudYFP!yFLGyO4W1=R?Osfg!ya?%9y(TsYx!nY}gjEA<-uYrDL>4KuaNI
+5o##lw3IzLtlx12jGLk0Cz8%UNy;9hO=#hS1zOPV_@(IwFC_Xp<{?5sw0A1n6IdHkbw=AQ4EBFk8Ocw
+vh|WyY=(qbz?ri`P3+&%xu^PrmX3w0%GZ(<l8@%u~_MN-zhvBRHxR?5|m_+kKSKg*>G-lBgCr;%eg2z
+n6d?1Zvc{jhBzvu|7E!$GQEC+MYc;n^R#!;6k0|2_Yc~9m+jV0mL|HR@cBjjuP^eP%q{G0H805*$(qA
+<$nvypAf1XIDPdfXnreLZGq{>;N%c%4uG-mvPQ@1e`x!`(B@o-L?rUdvwF6`WbH<(Xf;)-R8kO?_~V#
+(cQ`;Z8W7IWgUTc{La=7E4EggghTmM70AWO4k@7u%9(fo9QCa_mQ~{heIsZ#Xe)9Hr|Du^#LD%KFh5=
+Xjdadt^t}3DpcvExUDGd*Xxzjs6yX<&>bO)pB(@SsE8C-RH`0#1aZ+C{nZtr5nY?5%Om01ry-&^Io4N
+U<fmg;6HL)%Z(3^`iPiTW!`O{$m*o<@S0BkgDs9?9JKa7BZ!=GJNcHmjJwz-lWI+miSXP)h>@6aWAK2
+ml;P_E!DIPZ3Q3002t>001Tc003}la4%nWWo~3|axY_VY;SU5ZDB8TWpi|MFJE72ZfSI1UoLQYQ&w=!
+FQ_caOwTA$@XF6iEXhdBQ}9SED#=N$R4_6yG}cpa3U*O2)^*NFEG<q|$jMAj%_~mTQ7BGLRq*k2cJ&K
+(RY=RsN!8;508mQ<1QY-O00;maO7>QiMV_qh0ssIP3jhEo0001RX>c!Jc4cm4Z*nhVZ)|UJVQpbAbY*
+jNb1z|Tb7^06Wpi{caCxm(U2mH(6n*DcT&WL9qzpmBI<-<C^1<3{G?kK6UA0NbO`OIn!5KEq`1i9-0#
+3%jmBv$I&bi!s&pC)Q7}9N)ke4-wFEmDcjbgY(36F3F=Z@R6VK5s(@53-cDZ>zv1&$f+0>c=B@z9^ld
+{~hP+ZNeuX~KbJ%vvRM18Gb+$Be`N#$5a!BFWt#5?eXQwo%N;0Wv^~*Didfi2%)b7GWL4>5jy`^8>ao
+j^^}H9$6OSOPcbKib3F7wqWNc@&-<llN;j1vaCgf7|Y9u&f16eI#-qj;#%UB7?MA1+YCo5aSHqE3>Xr
+lWw2P|#p@O1PXe~4X|#lA3`i{mXd-4vNc=Ls2m1UIFSxDM7<1T>C;}QsnIviB09gSMPiS{wjTmeb{6=
+WX1a6n0?G`VA@S>7z&K85<gik2<f2AmD^K6UT<q|qwy?V!(D%NyLEjGh3N=9@SpDw3-s$6%e$|*q9&H
+)E?EWI}4(gS@i*7ux>zkfZY>^yH<!tFuOAAapZ>xa|peeXG&R^_M~Vd{?xxZ4cBnfm^uAe=W7p8O!Ve
+=HciX2u|R@C&@xjKAyO_>+0RpnPnm44?Yt5Esq($J_C|?CF!qR%iaaAY4j<=KG-x4e+&mm57&47w~V6
+<E1e58%`LZF|!-$2jiRDxzalHza5@)X&|>E3e9zzf$WN=wAYCS@+)HQ0i9`JgZ+pPzRokSgW~Nyp;HZ
+Pp{UXuI?uo!il;oH6O~Pl6D{BE??|+SA1B(Ymsk<BM0@qpD)>>Ny?RL%;W*J=y_EYA%0zqh5-R*jqP=
+?Q6h%+8S1*~uA0^tWPxOAPTB5!GnrKzOGSRMMpm#;2UB^K9%1pbCfdi^T?K%cls7kf#7<l3zv34B;b5
+!Npbqrim8En_7NVfV?dq=bt-X4wb4pr;dp2H{i)4P69Fia?esT`qbJ#SomTZLhaHaHC7`WjkcD8EL-u
+$4C~|Fk>SA5cpJ1QY-O00;maO7>P3YWLnZ2><}LDF6U20001RX>c!Jc4cm4Z*nhVZ)|UJVQpbAbY*jN
+b1z|Tb7^#McWG`jGGBCMb963ndDU83bK5u)e%G%+*$<?$9F`7y4y#<X9!KM7D?TdnOdcE;3!)&4Ym(p
++kdK<mf8Pc`QX~jc)Htc#(L+KD-Hq<APk=f^=QMdugNHRo|DrMGYaF8wIOQREMWexR?4n=i@6q^&^AK
++sL1EyNm=OmtLeR(A`SfZ&MXMkrZf}*+2n7@cQ9@IW<~$AJhuO7*ZpjOuU4Kq-l8{u9ZQ_7)!gx-63(
+x0R$c=Ci_jvkx(nIi(#6FEVhzNs4PCk7J_?%<^u}5Bfl5jMW-%rz&ri$?pC9ix<V>B|!8Px@8d*%wd5
+%nK)>P!3(_?Pg7gVetX=Ki`-2Pvonzk<Ydam)fvpM!W@=ywKR-O|tED@Pzoa8$w3bt~l4tFvD}PQ5>7
+pKgCY`{><HKV8nQ;Nj-e_4#x@pIu#KY#SbgEa##u#u4fDdVYu*t8OD4W9Q!KpY)_*OR_=&oEba2N$Jb
+0%}BWFE2G6n*sP?WQ)#K)FV>!wTv({=V{dsJbVXyb<q*PMP>iJfHr)_A7vZKjUed_JoTn&YrClp4{i@
+FINk|?rJbg|BPWI7Utew;N3G|Tq{{_P;B5JJevsB4ilQ5)KGXNDSiplkH7<xE;U=Ff#2~OWZe}3&Z0d
+TI;!305znM@fdQ@d<^z}K4LOt%+dhE~aTCz&HjX7y&L+06Ar%E(f)M@HZk&8)e^F@6x6xA`?sL(REa@
+OT~pQK{#-ELakctX9P5z;*`F6f8EJ$Q0irFa$IuV?N=45oTA#NpPT$1o4Vi5i%g#98y9`7EM(tEn!wc
+(^D9GY)v=eGUi??wDo9QEXaLzd|8gIAvDyQa$bjgVY`aJ^gkOM+PN`GEod?jBAsnn5~%s>-PTk(m%X*
+EW}FiE-K|pvy3`cf%QN&ab0RG1hSviXZ#Xq1d=5rwTYD?Uk!&epgrAD17Nat(lx<6=q|0umViUDr=IM
+XR25MVA4QYxaTyCMFGeSy4RvGMF3^)lq0Ua=fI9e<*dgq;F=$D}tp^(g&Sh$V>k|lj+I@B_8Rd2Pem|
+Oj7Mz(pP1MV8JUMm%9OsJ`4MW*_1IAr8{wd$gLLRs*#TYnX-r&98_u|<k%Ge$OXX%Q2m_lfq-I#t8AN
+sy|l9t<9yugY;Fr8GoT7w}ZiD8{z%!p}={8zz}jr6EA{M+29Zftsq?_#ien4-XRW_mr?Jssicnhq}bC
+)|?7vwft7EnDFi98Qq_|yrP77MSWD6?4WGta(R|z%+Te^u29(3n|Fav_M{WY9X!yt5&uFDpeUYeIIEh
+y6|%P@DsUEBWezBzVG8WCDu`vQwi}e8&cHa`Hi!<yT7B#wy6nXLxFxlL-C%pX%*IIhC%XyZAbx8&AM6
+u0wM4LybRBBR1hii&=;u4ln5;L1;U72*mZoa8R~iT{)QP(m=1a^me0x{vWkS<0gYoz-0{tw<yf$cC9J
+O+`ueL8AweCCEu{;^J%bpy!@*fW-<H4kTkF&P@FIpCdlM(1Q`uRhZ=Dv7Z(Ny?r6QLlMj;oF~#t2lkB
+x)MeOtG%EXq;|Tyz9rbI}zn~gL|o@cosUg=Y$sqjNdyoNoboXwk5IXmp~Ao9m(?uxigIt{yL8X*w|1P
+zftnE)Qdb;)&Ik&p?IhU+zb@V5begE0}+!3e1_Tg2E*}y$<-(Vh2CU%(LCkEw?8aUg;VTvFOf>+WGUg
+BH1?iwxFM&OTC-~P=udNsU=a={#rF^>aO5e3H00G}vM96J)}jN`z^`ltXRl5>4JMO|g3-1vIxtnz{sf
+pln3=xT>wtsEOG11OQIb^z7lI>VcHdYTwm$oAWx=pjk?&9)N($?@9>vhpe2GKT;K5^Z;@;;b$1h!SmE
+&IVG~W2s`L~0at!pnb_nRx;bOj|2xnC-NQ1=4|#`^)vTyY*gaL_@_51^=aXDwYV9OPFE*}X#jo~|>@+
+M$07Z+28R5UMh{rOci>dLarJ18j3|i2HTp#lhbPQ@Z#!WKpGPe>YU8s*J1F@|PNlxu%!uxcb-wN3W5S
+iAH6h8R>%TkwFejm1SWD8Yse5Nw60hnk0=UlcVDwGjaCVLGYJOH-xf2nvBPjqoc|3v8e0Ap@T*v2aN^
+8k%Nwpzfo~-I7L?5uWgAdMJc$ym8`j13=`6Yzca!<Qu??_bcc(Xjl{-RET&M%$?G$dSoTD3V71T~0$R
+mAri0$S^SqN{W5BVm`)<_AFdEeu#;pwFafRWluKTvRDO5!WfOCKO1srTnNyE&1hoK)91G8{(zJL3Kd?
+(^Z#nOGPiBjf6!(NhFp1$F7tGJZW?h9ne>~fQ>Uhk+ss-bH<e2R}8pYI1>UIsq_zQ)fX%F4PpZEPYEb
+JiqgvZ543{cI9-h@MjlLayiMV5c0K8^z>S%Hr+ufQKa4@DQoCgPv*n*dSooE<ouaZkpQl7`;^w3;hG?
+n1$Y<ACJUi1)4+o6A3_eL(t*q=%<Q|>M2YFt_U{sX;geFw_k#E$Ml#5i7TcoX_iU_pKf9<a!ZT$81vw
+Xh)fjk0z7QECXqo}{9MA8p~%Fe7Kk7+v9W^|h9)fOUG;V~`!R;C;$AR7dVrCfsO+d3c!+M`xI^M4;uI
+|iqA|)|TvW$}Zc|1lo|f^Vk^fDc(qV;!Wf)3zY5aqDebu6L&iX(^*;=h3;6qYujG!J5N8_W?7_I@j#v
+IX2s(z`Gm9RB<R|N$+yPD4s+a%(rBAO002RGSsK{%YU84bxL#O^`urlO?l?w_z!xvRL$D;t?#tTn?v*
+VNR+X%Mp3mv>?<dwpAb=}@8w7!1*`Zuu;)-xHLm#Sg7ws#6bj*It7+SNM^Lej}7e48JlI@UmN<c<xjO
+F<S0eS>e-Uk{B;Ql8ly&5kaJ(B}FmiYtcRk*ytM0z_nvc{hePG==?%k-P?Gg^w=VXoet5l*So|nq{S@
+XNv?!W9-r)fE#<E0GYSc}7)r9_dnQ&Ys~L_Fg=Ui#wcK%z!h1;xi!I^4C!&coB&pjm+V!L?CE?(InN|
+NkA!B%z-hpygz*MAa@zM)c$n!+6@;r2UiY(6)KZx`^OLbH62LS(HP)h>@6aWAK2ml;P_EuwfBWdOZ00
+31Q001oj003}la4%nWWo~3|axY_VY;SU5ZDB8TWpi|MFKKRRbZKF1X>(;?bY*jNE^v9>S>JElHV}T-U
+vYCDEDx&ICfyza7+98OSc>%rnsj+63W1jCm@7?cB$dSf{f?AmQL<<|U4soHiXsv3j&~pLJ|3APIG4p*
+vD>AA*HRF(Bm#aT%5b`d<L56<QuyWS6`VXf=cLpWILoQfGyzR1{C;_U@%HKh7L3z0Vyi+b1A48ag_0{
+M1v7?f1NFo;{(MfX?usyh7QV3Jqu^BQC^Bk&8Uc=uX1bF3mqxuHCSNA-20umgA*Y3bOE+_&lvJK}NU8
+EFO^MLV$a^MEjvKKnqbOP3C{h$uHF6BSV1zS_x)!rv68N*!CR?zF3{A}Cz0PtewB#5Ueko|igrQ0ho@
+ql2%@$H+HkcZfv^0$C#-h}MtWZ<Yf|HzPvvm|n+zr&7%hJHq!kJdTY$m8u?F9Z3MN!U))^LgbS(M`j>
+d9&3aQV5#I&KZ7OcP_)@g#v!`xTf5Aq^0~xzWVw&*=g;+<YuzP5EL{fo;bTXo8EbAzxC2xcO|QQuK%_
+^H!P)*LggNHpUDk>Xp0~eS5nRj3@01t-n+75bFz6Sb4~`K2-iS&h;GeBDmBTg9lsUub05Mc0(^^$>%V
+ma9^1mPxe|ve-huh%9{20Kx@~kq%qS>AW|Zy9WOgcJxMm|c8q6a4z=Ue0_sr<IA0H0z{b)p(8J!#ja~
+2`jJ-|U{rDdY{+79_mK>+V<6Ls7$clJ8kt&K+k`d19wYOwF?n&`~QZSd<;{-Ta&E^EY&rZQ&et<p|WX
+5TBXR<=c97~&t+peKs3D<Pu6`eMgA}r?mow%v!%R!Ia<)MGi%(AAYcqGioo3g_O?3H2<;9j*qJzRk(U
+rDNk^X8qnSd|=^Wd1}Uhd6HAk+-q~d&q%8YWDCnK3p!)2RgWVdkDo=X8-a>a6=&{Vr;<n27O0hNfpHk
+%3bHsx8AdqW8-m4bxle?)Rjm$Qp|jvhN8A?Dty`t;?tEx+XE<_l}5Up#Nw!G<c#z8m^pX?t-f~0NMm%
+`*7bmYJ2uay&SK%`(IH6`$YM)pQ?F(oolCVlmm-%dELeslbc5@9;O$`Z4+INe$A1uBQrEaOrF=SsRsx
+>4AwsF>;fk8`st>!S59Z7m#b%|UA!hMd=nP5bTHaVI<1UTZkUm&v-dpGAbzq6>Fwd@UPL3bXAqQr|#a
+|`iF{dKltd-_Slo?UCIzzV&Hf_gy)I+MDUVOIy#v5P8pA$I1ouIwvL3`f<{By?)_N?o}|7iYx+WmO>w
+fG%><NY|<y&pYL{z=F`?NRT{+7a~m<$%w-S?aMX{1{$gf1YCZ@W2dqEVpQC(=2at)y;mWCoNO(^*h%t
+ZxXhd^b)g&f4}SYwOlN8-U@dnt3Jwp^2~*;yP${7H#f=Gc*p&fJ=Dj{hFH5-%LakWt^aRc<wDm<7j*4
+jmyAaHddyLKFtw%F?Drr%{l(eBd0y201AI4yky~ce<))+Hi-LCxBzPNnCX0?@NG)8`;k(oUD*gLXt3o
+lKx-nUx7UT=HqH&LltC;JSyzcj=n-_<qzBNwq=K(b%tEUDqOM+Kd3V1lo5viF({?9QlHRMt$nj5~YzR
+9vT-BRh!r#Y8++M}2&l#o>Qc!ITON+q&8+tBP&vF~I;_ElbNi~AK(7sHUvsv^R{;QRr>SgGM)Y~qJBh
+GRJn#Ztdnd3D<itPK#@M&8lPmLl>Nd~&{4XV&NK<Z)+xRmNL$c0A^~JZQkXTzZ~ui4Nqoi?~BNLlSLe
+Y;UU_M}WkP<)Oej$>}po&yIKo#S2C61|JM}32!|j4hbK~FrCN;nZ|Q*SQW|AgL)X);1Z6RyugN+*k-A
+q;r<g{$97=LG(~Xc;I_(UsND^h1P1reKB^LaPu6;n$(!+i*vSKT=*ddwa#6QFph}@(!Ia+dXus!(ZN@
+;W+>HO|o_TI15PBckt?D+d^I#HTnP!>2WMvslr!dYk`?s7d8&`#8e?jm522e`_1QY-O00;maO7>RR7i
+?(j0RR9>2LJ#m0001RX>c!Jc4cm4Z*nhVZ)|UJVQpbAbY*jNb1!LgVRUqPUvy=2bS`jttyRHl<1i4t>
+njF&s12#vZEl4e+O*4dS=vGjr6-{#<BdR;j3l@C?<>i6A~%gUZE7$`*1R`wW;Ejyn5(MM{NLKbA0?Sx
+GYP+$wgMYC|M7F0!PVj#re|}(YJ(v75~aZj7)1DcJHNSG+(5wvW`viO(iTi(NTF2;wdB^KvCtjlZarr
+nTQV+5Ym{Y78gA7qm(%m!a$z;H@=>#@LOp>?XOXK%Z_$Bj%Z2H!t7f@ox}1Q<O0Xr;=VrTBE;KHg2p?
+PCJb&t!cS^b)A!LOGa6=ijwn<DlOD_nxN29H^97^geCgAXxX526jO9@#DW(?ehy$?6(V|HYL&HM2=q0
+Vh$P!ydP|2PcHwi+E@f8q@@$Bf$My2fOq)V=A}?3LSfpN%9UK7e8<PKLC+*XO>{SYw;Kk7fR1!bDCw=
+;yWW<rxb0Y!4mTJJnxGio3&^u`AR%l6(k4)pksr%h&yjW92J6y!yik;%gp?cSM~dWo<F{iTiKqM>O^|
+`^Fmkw%aFltlr@)k`~(c!&%WD4bkJW10ekbV3^5q=&+R0B^k?7JhE2Dv_&+32fnj*3~uJ%-d1TN-=*0
+Ee=yUIo~ZARCh_gQOF{@QfKtgyq!eZ|IHlD8z$iU!)8;p>72W_)O9KQH00008031s8RzS!y@qhsU05=
+2x03!eZ0B~t=FJE?LZe(wAFJo_PZ*pO6VJ~!Lb98erb#!TLb1rasol;v*gD@0+=T|iN!jegxdowXn+0
+15iGs4Sa4C&x7nv|BbMdjbyauL|(H1>gTzRT(PnsbIco|l5`QiUEk!z#rLEwE4&N_2TKnY!rCpP}iwM
+{ywmQ4#@@Fh&vpJubcZ%AcczP;jk8@C-$qDfm>BY!S(FE>w$TnBg6WT19xv`brSCTdu99mZfZexwI@R
+qF73!0-OcG#%cAVD+}opLxPCJN|lZTnlz|60#qRw3Pb_JE-TLd)94;ksXN{5#W6lE8P32lpT@`agQ9C
+qxCX4D`d_2pP)UHsd!%t5zePY!aRlL3Pgn)%-4#j|^FnFAem}P^1|$g4k-DhJPHVWTXCH4o9p245aP|
+f`wD$%$9m@y_!}JgN!ln$vA2Nnb*$9T7!>pbBRNg^{W0?nSe$AbiQHn+8v?-+v?41bCUhU_Nx43<I3K
+wfXn9uAt-Oiram5gx~>K)a{V3|i1`9W0LUz0{W8XtY+mhCpZ%NqkdIg#}RP)h>@6aWAK2ml;P_ExU-2
+ayf~004as001fg003}la4%nWWo~3|axY_VY;SU5ZDB8TWpi|MFL!BfbY*gFUvy=2bS`jt<yUQQ+At9Q
+o?l_H4<s9nfT}O5gtS6g%hVSMQdRpDx#3cxItjI%QZ((q@9dC}Kq<7NRi)(vICtl}d!9R=;S1@+<0%j
+BMw0xDBPvHUB4?CK22;|kH+F5(9-NTfoerak0Kx(fA^|lb0LXc-)4d#Yi61bqjUXJyToN%AhR@@WBvB
+wG2uWrN2iF~{_J%Zw(8GN&zK$3OVHlE6j|_rOX{Q~=-hH<H0@pP%rqUZ3@Z`Z*lAhLdIgfc^_o_{4R<
+=C}A_+XqOm2dx6SJ7t)M_B74D`xD6T>h(Muo`U6#_GZVI3Jd=6CJgta{1`4Qb|IeeX7_mNpuKPZXjaA
+~OXrzoyf?Q6^TJyLy!DSV~S>I&;%n(%2LA8Qdo54XqByH?mK@lEywR4olYBw|xq-6GtLuFz`4))J}XK
+crWr}n}bYv<UUfC0J_Q|<W4k6tqgl17nQ$_v;cDdkWgl7xUL^_r0!s?-7Qr$*<WiX(pnr^GoI)DVq%Z
+kV@4&03~eE?UBx7jBeQ~>SF9STaCk@p4!Ux~cp@t0G9W7os?en<@V^APq)8#7zP=z<h@KH^044eJNbf
++pRHuWf*H;D2`qci_JwLy?d5zD7txFMR`R8UA$EV#(=XiC9T$B4K#w%$TVq=>whSBZ2lv74tb|~$3zj
+u1(d}L0kycpej!;$ZUz;0t~o5#L^sWm_9*p~}~U|cVCy_{~TVRstOx7m_BD>W+08m_2wDRNiH;>GFH*
+l_wZUom}NHZ1UAdzdN=YsBFRyu;M`fe_bDtTz^`zCgVan|qtmzW0e(YGZ-7&Qd<%%W@^&gr&6UJ`+oN
+s%@R7`Hi=*RYz+!*E2OccFna1bRAc(8PS7$T5fYl*GmTP_j4?RHDqj_+se|tI7&;m<UH#+KMp*}9Hi#
+mrTk8muUFG7Y;{hquASP_g^Vrw`_CN1zg6uDFX<t0{vT8?j_`;mtgS+`e_SoQ{r)DkGy<QvZbU<HUD9
+fis_Ux%e6CwfE23Ty=3h`t0|XQR000O897^_9fJPXFUI73AMFIc-9{>OVaA|NaUv_0~WN&gWWNCABY-
+wUIUtei%X>?y-E^v8;QNeD)FbuutD=cxKoz{wV(lk}#GR8C{1QTVuR-tuEwl=9;v%%lbEoI_1Ut+&JK
+R+iU2yOz%TyAU`!-0$7u|w2IjbP@Q6Pa?);LUu9CU;Q~O`-@sjMXPd^rvY;p)E~@w#6LS0q+ssPP}&(
+5?An#CWIGvu(@U<m?TJ`Wu9d+y8}C^N<ysBa;KFb!g4X2uabGlM+R+kn5|da&En~OyWS)nC_H8A#t}p
+1%2JFgm8RcFt&B)hn8J7x-iHrkrLs!5Ej*i+E3=y)Gi*8=-e2a&3M3j~DaCX;mj$`{A`Qc&)uF0h#Z8
+5zuy2P&e={d?6vGG_(q*k<uuj$!H@(!^z*Vz1=!Qc*IOrnB0`@)XwOAFmK$tno{rK$fnufLEe@PjkW?
+Z`LtEUR3JHko;d83uHs8r`heq?%CH!P8tJ?5pU)itK6KafJ5=a(g}7xI1e3s6e~1QY-O00;maO7>QvC
+dD{LD*ym1p#T6K0001RX>c!Jc4cm4Z*nhWX>)XJX<{#9Z*6d4bS`jt?S1Qd8#j{Ze?0}38ZVm;)wb-J
+T(raNII=v^j$?T(Imxb~VOs2_*io~a>5F8JH{Z9fv9EWY<kST~186i!JDcz9oNx8RCfPutP*tcK3g~@
+t@bEy)ia5=0jzm+>4?f3V_V)Mo#c{D(m+8%-7QyjIJb8Th^Z@?(OnjT>(OR5GKc%Y>n!QYCNnRzfs0&
+dq67hOnFN$287xVf)DiiUdX!1C!Q}_)&B&CR8yu2>c>!vQ?+fA7y%OtN6)_IbMm#4=kug*`x`duxeJQ
+l}iuP)x4e)aa^?9Dm;2<`UfWw8{~>Ab0%GMP?Ax?B|{G{3Hjtf`YJf8X1azZaGIR3_?EwXXK|>T-RwC
+*V*0SY><3yIHcT#VP%AQkF$|B*ea0mC?;IIudyS=-(wJb%XX|B3>1F0%Oe)W(bcenCmpn=f&mYEAdD1
+w7);i;~Z#_-<+N)B-D2vfxb-Z^(v`gsOzXo_@^;Fu9J5)J%ndXo&qD27BF{`P+z23a)Aw_O3dLi^)lx
+^onAL-R;M}86WYixmD%LD$mi+J>!_@djTQ0{zOU$eJ8V;C^ponPzK`)!leeFLD$<-jRI4nl<zxD60n5
+^B1uB5AWdie0?f}HkO;OW)rt}E_<myA2Jy}KdB9E2{6Uz6eT0DW~W1L(KVt7#$=L^O8u^@DiRHHqD6D
+M;XH>gHO8Zz)ct$<i{l+WPFSn<MWLd*m%Rbi6jqhLs@Z8*{`U}8;~%gF%vJ(KiIhbJy!o@mOvNq%lXG
+-&R{Dgna2ee+UI;_Hix*Zi@U7S!ges7hzgntJgyEW9j{JzqyvbzhY6H#gh*TixCyaaty`TK(AH6-6zc
+BGO68<iNF5Wi9c1GsZE_C2*5ci@FA$U7J6>TV~~I=KT1tP12C`{EQ!3!hU`6%}XibdL;FWJ<c)%c}eR
+v$OJEwGP;L#ziMjWv;N#dPV1zsiz3r&GKGa$^HSnZ+uP2gtV-Gr^pyn#G;tE$fo1?LoK_+#QSXX5sMx
+%?AB!{>vj`VuE%GFZD-gG;DUm_g1)f&LG7<ODS^}FkFyB>K+$aUdKcoE9n!v}wqNr*^#`ncwFle6+@!
+!j%70OS1^(Sl$-(WIV!;v^R_)^#nhGQ`_+k^nj0DY4c*HPBuWjq3LY0-tbBfj>^+ZU|?uzxq_StjAES
+gt@j2E)Gw;lt6N@Sooe<x=Dh%c!0$pt0^4(l1O48!38lq!u=P3vYlgtKe`fo|uhg6GVJ05YpaW0-W7q
+InrVmn*m?D#sYry!MT7Yr)S@l(Q2jTvTG`QwxMGSlu2DQb(*<)E3_;`u*F2MR_|9J^k*vnjzO^$xr<B
+5s?)@VHK=86Oa;4xaZ!Jkk=fe%*J@z{%ttC?`S(FO*`;7dHJfb{G(=`gX{1_n<+H@Dh7UoVLmL!PkHU
+A*f<~tOw5);w$ZIAX>wsFHg?9(@5R!dJVHFaZ8|}q5TVd*ZYQ?5wqAZ8u%n|@}O=VY7JX6#vB(mZdK!
+Z7%MRmfo^|`z~dS{k_9CjcC-$q%(9}RPWdVQ~To2GGIAp%p@mvPRTj&WK>@22-4a<iz6tI44O1+2g~*
+a6K{G@HQ^ARAYRH!qIGr-x7e0Bakq7{nK!hQAM=wz?Vx<LJ>NB4d~)^*k)fn@7lpN9BBmUH4_r1MX=I
+X-uL<C3<;fI(vChi#WGUj8x$-T8qrxOX?rzA!(ps7#c2LmdxvAfl8%JmQhOK(S-Xz>@b#}4v(%{fSO3
+qP<02Z)#L#Bp#d7OY@2>*)7Q0)r&R^6(Ej0PUwr=fNJMu<8Ux4j6s95ySoTSI2SJ{=UIUu*rb7BJi;g
+9&7f~+2fa!4s+K@R)5r%g{JQLt?+$C#-3Cl9N&eCd;#15EMk)^Y>h?WHmbAJ93r8uJqk%GtyEJ|??;U
++jTAOzRo3^@SGB&v!WpeJIsC;;)$=2Mh{<>^RpM<WhEZh&n0+MpvkQEf-@{METY@jVg)@d=E(DnY78m
+bXx?z}XVb3YO3kX2d?&{iC7<>dI9Qm!x=s9Az;5G8l=;M6Vz9n>ljN@_?_+HE5TmI1G)}7ZABiO?dwG
++1r=T#jCRm5!KLeMTBOzCjzaIRL}|;5TiPqr>F^Yalc4s3j-jg0<<8^7Eu|^P+y^cRRRM*C5kM%PBKw
+I%aVl$`=Cr8piuMU&?JwNcbqy1yDP@uEs`96M;9>Cf`?+8)>V?t$0##24;ns)b&s=Ki@2z>q^cZnT5_
+%5Q6Gfp9_4W`y!>l;^@*|QlFYy|1QCbjd!N>eVE8USH~_B~ET86C_pv*ntt@;RIz4_B8y#5pz?Y<tk3
+iyNd7Z>DK)@-01ONk{9Y~(Ku->W%b8MEvz-3O$Im*(%0f@Lj^+$`TpWNV{C)F%kC4nOG$RvH$@%hhCw
+C+>%B~dIi>vPR==_`*#65fR3{{H^qhl~ym#wv>-;xC6kJjCz?<pGqiwGN{=CL*$iN8PCes{(<%$w83{
+OUtw#R>A5MmzTB=M>`;holGR4l^xvxzR!lJvW7o|!w{Y903nU|r+*)!Jql0%{Oat@$?>!ElTMBT8XHj
+$a&2T7dfVR!P-C{H-nQ)DCS^Kb<La-)Lu~j^1Tfn;!4wHauK*0aCmtAnx?b!4U>wei*=<sXH%Se8wnP
+BIXrvj9WPhjzeh3x_7u1u_4?m~GqFP<;<eChn1Nbp7GSsN?82n)Hi(VrWVZl`LF{){BMZjlb9L+&ms=
+Foz*9;k-7_6k2M`_jomBkr^-VFe&KpYU^d6UyxcW7SWsOSWRCjDIFffR7;2AR9oKMMw|^C&N1TC=gkH
+<>1g#K3~r`5T~(u80o^6u)797XnFA3?fNM!Eb|deDdaEdiMI_^z7BMmk5Y{cyscvZ%^NxJRh_oD7{F>
+DXT!OOlUeN48agI<WHb8pJnwcXbb`!7`g&kcAKon;tt6|$&bkK=765if(#8<dB@bq2985Zz`TNP@q@V
+8d8B5g7Bc}Gx$IS~Tt$a!U(Oh%tjM!9=;{P`5~CU?%L;Ovq7aGr)j85cfCehp4j?3jMLFv^(hVLfH^`
+zilejx)53QSPKWX;G_uqft_3?4R^3ovN4<6MFMHa$D@~Apkw&0cxv<DBdfi)L;+Zb$S2aTk~kDhG*QC
+wGlJ=|A++ob?P$UwCkfnR^<TkRd^cAyva1K&y<#6?o&L+Ko;6$`fdLDg;iKm={rhDML=$1++4=mC%QB
+u1lA$1^gK2crKL*gq(@;H)r!2y3JN(1#5yAz)8gfFFxNKr1(>wLIwA3ku@(Bm=#ApOBqt@^~=n1n<_)
+%{c`?*tc4Nvw_wSGbG>+B>vESOYE-t1_j||8)W_YnYh8+53IA9>OgCm)XB2R>J*UTMO~4pkkObj)Lx*
+J2AF~uR8OY?yW|fa-rh&$P33Ntz{7Aljnf%44VzUAqz+`uZmxrJjEY_yiF^oQ_OY1}V=`2^k@-|61`u
+}w9n6;C7%ag-nG{v{VtV!$@gD*{eGi|;l<%8h9@nPppVK>_TSU?V&Ik7&lOGa^*Uv7#)}E+zu~6S3EG
+MwSG%GkomD+8+A-D((oeJ821z=+oMMMHshN=6((`aE~ZrAWvencog;yfc@FOATdUnqV=r0iDg-B$2b!
+vft=;7-?FS{6Cki2>p@7!hVOFxDU{NdGd05F%$!0jL8C8~K?;rGY1oXy9pY3ml`FV+S&l)WCVEF(UG;
+WROCbf_1@6DACM}fS<*2$`Oe&o(%Oz1otD;569p{YEgnoi_p}H@4zoF?kfY7YJ!<ROoGw4Ko3TSfrs{
+@;73z>6wGs$kC8V85C9}1N%AhO>IzzqNRIRXZGW$!!L~RR1tzTkUxZ?XEvF#u$*@!s7D-`bK4}_IhH5
+ObqPWH2x>?CbK*BOY!Lu>~5ymldWI9`Sl6!+#AviKAW?5!g6DN{T*tSeESeSQ-lr{tC4EL}g+BLXBp<
+MW=nw9CQmB@6iCk$;lFj>Z<j@M^%LN9fXU6<^DCO$54QGfxM=;z&>q9+sof*Iq_AR*YM;|}7FUJ=n7b
+_RHwI_DrIA*y6GvQWhO1qf(s)G%nC2lr|I^vS^IZFcA`>gX259lj>8qGyS*G(wliQv3i2^hcktI}?R@
+nC2CRb&tnw4+Cq)2uXGF{RJ)31lboMLWNw$eTX1<3{(812Y5jJ!C>SenmsyJt+1Xo6_A;2DEMje4t!U
+P8Hpt@bdqDONY%~az(nrTEE5sNq2RybWU2-2v!&&%No%&lJltSKmJ0MiGH^k`GKR+JAu&Q@4i0ME79s
+UUJC21)l)#!7i%2fCPIN%cy4-{r;zChLNFZg*X)Tzc`f)_g15#UZ8$SA?g*4;H4&Yr`PrLq^+g^M^@V
+n!*fV@efT&5tE<X2){G(a+RDVY`+c2^=xZxbzPNS_241Wh|>v#4eXsG9jaeJ67Uz?@lwId33$RfwN3G
+$GqikO~1?a*#TtwTaP&x=DhuZUusBhqS$GDTi6%!--ab_zR|@16oZEKXG-cE*P)DcwNfluVEC&fo$2e
+HHZ=rmPnEEqNx1Q5&8BlauiPh$g%3~w__b;Eq9Xq+FJcd4Vjx!qouO<_Qk)as~3cIC5zQip1^I3ZaCN
+dB>apsLr5w5{^=gqr2Q>j@qF18Re-=z_zI{kzf!H(BC4XgE(7Cth^3}eOv;wi>2TEVt}3V#3+N8@0$u
+D*-qj9*@|Qg$VrYL2>_!HeJ)S+*s_o*{V>|t$q1qXwqzA$D`$PDo)9alXVn8fF^>{vPW?2Etz*Xs1Jq
+9dS(sF`h3Jeg685zKswiHNHV?Y?)z<eCanPl_Q?C*4f3Kc97P-tLu)*I0wn{AN|H}v(<!H`3eEjJ9*u
+8Wj!Hj7hx|L{XLyK#PAAb}m+y<z+!8N;b9l{FV*>5^C*M(Ct(hp*SK*F#dcZ5gRo9=N6B*|H9uh~ZDs
+T{QIf`xnB)>S>H+ZAhJhFT`lO+foXc(ZW@v!(;Ve&#nS$Yj3$+$l%}%Tpil8o#>B>Rharv5&TB|HY>7
+>H_9Lsx}NE>RRvEoRgHit5Mz20eWR2Uo{x2ZJMmC)9Vgo@^-VtF{R{Pozp2?gtGV_$*`Ac(ZTT<0I6^
+0Z>hpkdbpjqrKtYbq%;2WNXe_%SOTmjJdrQp;HIT(%r1uhd-D4zp&xw8z-ZF_YPUvVzg_y(KVd-KpTy
+TAOC|*#C3glX{8SNqXOS4MGX&l_W&C_={!gj2VWCnqVFVn=87~qdsWA}gl^S>yrfWQ&s3JK3j6So-%b
+hYzrnnn2yD#YOU?D@(0$;HUch)5{DrnEJa#38TFsbnpVG}%a77(mwa?#abv^@XLmyq;CY(!|Fo1L)%o
+QFY8}?rOWKb~Dh*1!`g5>KnE)twb<D<eXHrU7xHPfQep1AmCr$s*#<+^+M5gg_|L%!e@gj<92e}GqG5
+`uC}l!kYe<a?pWeT&e(%$ARhGke)xxYwj=_-gL3)Pkx58iupdIm9Z9eQF?V1|DDnHBN=PS{UEC&l`Zw
+)$#z_rBP8H@KVvnVghw1C&_*ZA&Oy6F-_?&Z4&5D<vuJvWp0#DLpS|-jW_<%9EJepknP(2JT4}Q20uR
+a+K3|W}MVxMA!6J<2NpeWND#NBoPPM0Ydbs(YB9Id&Ue;Ll4ism!gro-Scx-OcUcYo6o0>i^6ZK;J36
+vDV@QzQzPM~6?YbkMCz5e8GtS{w|lWD#|ohykgm0WunXG3`A+fnHw0ll@$XFu7nr3jg2`2TiNu;PcP_
+@J0JgJtXD$g9+LhU&A@D0UbDy0K*;>jlo@et_aq$)sevfOkbR(Zq8nR#)OyKWu!Oi(O5O|02H_4WRKG
+PlxC?GMU%COLb)l)UC396l$Tf)O*u<AIWNR1it*1)TH^Wy>jlnngDxcQ6EMzgEpN&j09C|={20{XcO`
+&;GHvNZbx|7W^i%2IqfexP0y@j+UAk<Rl)Ji5XVP6Tb|>@%aV8pE5LMa{9?AWUEUjuT{aFiy4*m<)(9
+kg>Qg;|+EU3yOieVZyc1+XC9&@gI5H4iGbR)o*C)lpx86GXmb$bnubpehn_mQyzDi^C{b@2Gfr%#dMb
+LdZ5ZUn;<P`yeuUfoh1^8j&L(K$AtkvLz2Q}&K4K8UcmDMn=<4BVQA1dNG>+~6ZPK`B>TRSB}1)V2j0
+V7<cAPb6HaJ#~Oa8;dQD?3Wx==?xXfsXaQA&Y1RT@k$N)P#T6=E_Z#9*3#8!r>J52R**Ic>Q5OCQpqf
+HU_vk!oK8dARC?X!K44bn8;CI_O2C5`x^kL;wl1C3LrrjExpMLeVLC0!X;l}iz|ljU8RDN@Eoz2N6fS
+3W4$w|(T$i1I&wz0~9NK~RJk8@N%TM6wu3mih#dE1`Dgjm#o%xeg)?X&HG+7i|`ha%IB1WxyXkcF#e(
+JMDtmjZ5Rt>C{XXnSKr{sHM>7^{kppiYmuv}O%Kq1gA+dwR*GSHsTH{}m?PShDhe#-~)c={d@!oOvO5
+C>}c0n*E~qH1R!Il4Rj>AaOhxn0=Z?6C(MzW;^tr0@Ts{ACz&xmy5_#u`#L_sQD8&;{7R*%DEk50lpU
+2~l7`#|H)hy{TW>w^tIa1w$lm7gNVylEARmV!L>fYlloFS1wR+y$pRxZF)E<w@|K=MRb>fJq1QC(^+L
+DV=(Oo%Di^!UL_$+Ms8!`pviCZ;=WxqTo2x{J$eS-t&9!uw1^yu_rDC3nCO^cqnqw0BL3|nN9nv(qTU
+)fVi_l&{y{6vzVfbL#S}T<Zj5P(In+d4mBn?IEafrxp|@W@Yc@bM*u$V*4*B;ldg$LlNsaai3{587=l
+^P9(+@e4m^enu^x>(6>4mFc%FWywX7r+LoSHy64E=xk^vK?|bM2{(zf?HX)qmQ7yN|Kb(`UO)8%R*xs
+E3#1CV~NM>S=AT%?g@qKj{!{Zngz)7j_Tw4C~{uA4_bEk^HC_4fn+hti>tvJ1lVnl>Slt@!(7GkI{1V
+Pa>&jp%cjC!6_A5bN0y>yBmS}P3koFU6F9~1n)=)o{q)urPwt&HwO~6N9!QMRlo1Gi?oB6ZsXu?WQKK
+CcoC)fH__@N5)d6&-|)^ZKwIfGXjwSwh~<&SWd>z3Yk&}UXq;Dc*mi3F#JRv863f-)_CcMKQ4V!748z
+b(-VcYi_CSA#0zy6;a+^>d7_ia7ZJT>yu%zsw7I_OC#*m%yT!lapZ%KLLsTwB0M6dqlEw)*e)3V8PnT
+Ms#?@lYK(c{C*zWp@yM<u@^jk(R3vNp756ZGyhV;4Gx(W0?+k6F{qul@~Cw2=-&_=orUN-da*6|6-;o
+|(53s2wbE+XT@-3?f@Rl+ur!4sodd&*O<5M_5P!*s)B}VNB#v6^sN`CSE7A2p<>dYZNtjrqK$ld(|XW
+2b^Rsgo?`|ZZf?4WrFOZt#pe5w3)6N4ZFCvkm6#t1q`*=2!nH<8-Z|>jZmT-><XW9+ycyMIUIvq=<)B
+EGZMVb8f_dpE79D(Rw^>E^_#J(V10{cx}BiQ4XU<0829um5rD?v5}PFhs79b}U~*=CAXaOEy~PV%1jb
+xg4#5Qiv@3X*Cih0V0yA=Sn@~oZtO_n=Xuw*RoYmpXQ;5x@nzK;gHLjZLES*tiXJ%wwbfqX@%LB)P&$
+`kvA{e52h$rbd3qe5Jx>}xIg-KuoOO8=0S<gyvd`QdVKcGyrH8j9d=7<%JOysmd@M+GMCq-z<@5{7KD
+n+J>6LfKsC2X6h(5qNsVnG)NlMkSwNem2(hi;a^t=2{|bZyEhv`OhGA7HMf;d+gFnp_J>KD%gH&fgC4
+IT2+s6x{4PP|xvLi-wTrHd7K=EcTN**l@37e$4Mw5P_&r=AfzrnhtXO^8GJYZM%IDW%tn<h6k}pqKeA
+o5Gj{9GC`o}gKE;Z<?@$g%`QIaQ3nXD1U${T0SMY$NfNHelGEra@m^b@FCif)moUba^?V-}gH+T*Y3*
+d=A(#D1PZEjV4N}-kQPcFJK=%Q7aFSI)EiI7%Hf~k3;>v;Mnp6`V?u#%tJjbM!(b*<0R&#2ij@1<0`g
+{i$CQfVg@i&SLRezU(5an$w;K``Wr6wO1jq^jzz|lxfuuK}9l+;~|s9LDA6<9i4z~poRLpyG|t#Sw(^
+p5O8lhp*(CSjI^F8Ml8BEqt1No5BznDuNUo(Ry_{ZFoUJ8~eCud)g9@cm;DEs~k(R2%AFg7=5NjC7pd
+kyf6+?{JerKNC+HU<nqjh%F4!?*~d%!7RhmzL@2u3ebn10;%D#vVU5G%5r<D^l;@#BN?|FAPQ*c%?rS
+|0rm?uCN2^Vw`Rp^?W5=LRdU}V#s>k}OOQzB@Ekj%ABP0O%kOx{XkKx2v7)Oiyl6@lAo<kF0ssjKBk<
+B&*+no0+9<lKHF-?<!JZGGHJvTeOgj5VF00kwKG*j?|0&9EiXk79!usV^Q!SjZz$S$;ePWP0JB;QpqP
+n>R(_Ix2z|SOS_V0f&Cu@os*5E;~zP4t#im(#D+A_ZlGqjQ$-3gMUDYEZ0fnHAWqOH32P96{S)h|jhV
+5L0ab}mG4dbU_luU&+0-7$R0=6<{8nD-%k;+z)c%TmMZQr7gyPWB_J4uyarI2-ROe3LATyTsgzjY!Qe
+K@8H;;1w(!@y0?9eI&Io>G}q6p&WK@+QhQfq(ae~n%|vTuL@*UwSijUuuB|MY`lt866qndcxaKtq+1G
++2?<k|PIK8+mUpX3e>|-M1K0oe@-+jO)|($09^(@=-!ZzrcQR6;m5llM2y97@Q%%a6V0VguIOT<Ra+x
+PJXVGktOtHaKRz2WZ9^MN0aw49FzyF|PoLt%IfW(U}7U=n1H#bvx;xKU?K=dd}K2O!2UKxg~wSA$I4a
+C0#;k22McEX>g{g523N5@7mWj<>O-QAdIn-!e`TsmL$iEOe%F7&K~s5FV6qieroI&^<uynp{*-LZw+K
+p}_*IBFaO&x++E@ZHi?Qa$>^XP<uh#nVS3D8Cr(?TfFX*)3noJ2wXoMl$O_j(yos1S@of>F>wz&mZug
+Psdbnic5L5Uaj%o;MW`yaASA~){Ra$RZUv6vP|<?QLZrAf#-3+EYpT}M6G1}9QLGb>jjskFsXE|kP^1
+~+tyqyfr^{uay{J*U=KFa=o%TQdV@ZwzD<++F<<c^Kc8ZeFn-*MmT^ZLQ{UtW`ZH#-=Xo1%Gn0}fUIJ
+9&kxg7cbZ`Lsw*t8@p5eCMBEeim%pMX2;H3A#E#xT2y^6}|Au|A#87z-g;5D{l7tVq}D;H#Y{|@`<oL
+eAt4<fv&+U)REdUJ3lRKB@R@xBpCd;{gp?z-M8;^$>@(_~TEW+w1d>t1Jabp27L1K((6rZOz@WNCg|a
+V{$^n(K@TsPI}3%4|7+>1-ek-)Sm%n~#Wt8cv56cv2w;KPbr(`?4!}tBCU){9IW5NZ*Q6O#nZj3uh}l
+-hc%|yrUasHwAETu^gEoPe45rT2x`g!7deysS+{Z=nWmzE)zV>bou(t$+u(i>g4;2vG~i$zg>l!(^Ks
+!l6Xs+N=mAfFeZH{#Cdv?M|i6^BIt0}@qD|S=0jn?I=rY;m+G~527y8>mhe;TTzaQ6;4mH?xwF<1Rpg
+Y{X<Z_QoAX=pjt%lNx|f3x+D--VP@hSSYQA6Putj_<Zm<+M9*PGo+#TvTq+FLpVP}eVDCKgx<0dTscX
+{PDqrd%DLUVQg!kRDizC6Of;SxWN1^<h7`>JnXT#pm+{+F(oGo8vaYqp^69^i~gUQ~k#Mdn6(S7eLWd
+>W)<u^x#(P9|T9BEC$oCTpAhcodoQtsIY1T)+u~O8!J^k4v_0@KA81idAEENST#}0~ePkYu37>osA5v
+Oq=Vw7H~wE{3G5u#0aHxc=%R2v@(I@kyz$`pG@Ij7F9}8zz6j{zC65YTeRSS)he*O%qXeO^3e$dO}2H
+z)*a$e$$9xiab7p{a=rzl*p3k^uzr2zGX6QG{gLx{iVwI&sbb_m=M`JY2BU(N2b$MX8dCTALn`_#DUz
+aG1~FG{hiJ1TOK@X4bx$?7vD(j|8^+?q$?uy~Frsy<4MLw{-ek-l^W+`##A2KZta|z~$94a1Bm9+xLH
+F4`!O9Gh&n0sx+gijUCq=SZe({*4lFUO}=72F7-?X6039(gog{<*LA!>K|q$~Y$0D63Q<<77~b6zF!r
+db+o<V@8sziPIRf9u&kzS=eJg=xybRUCXt#sM!2l&KbUw&~Cv`QOlVhdjVs3ct>av&5o=u*2(?54U)-
+A-g>4&TR)x_>tyLhwbL$9j$d|SBF%aLF@kH)|gcD1Z&E=&KeL}XPJ;I!7XUp(YQ@}#Zo(gWeW^l>@hR
+1;TQJ8^fi*emzSq6&XkKaXB&b(A0UJ2?HATlx_5iK^TlOhUMuG0acsj$xj3gZU<<b;%H5Gjr*ANZO4m
+ufx3NuYHT{z2XixLGzmn2K?yzUzobO~I<UDO;-(KBr!C?$L6JS$9BRp{n7Bkm3u%5FgGhrdOa*^I6>#
+baxLEymwr|oE`z>G-ag0Fc@R^*W7(%VwuBFN^9Vv~addr{HGPLE=vXS9M;j76~}EPx{RCi7`y+_Q3};
+_4YjsWo#TwS(C^)MdNfD({I@3e!>Dq=5T|=7-kE9fhzF3vR7(8Er?V+(dExoKWKYJQvwv=8Sl{g#~io
+w!;F$ery<9lD%*2ey-58`#o{Cyi6t!Nw)Eb8}y=Ov5cF3EQ)9<B$^HZz2TeB^vH%M*yx4n6}+VffS1h
+ZfgX6Iwp7IlnWYzwp*Wqx1G-Cwl3D7|@0hM-GB@n><W7#z%fCh4b%M0+KwD7KM6GRBA1=HWnrycL=ow
+kL6M6ba&!><puLVs&flUsUw(dX8)g7XEENILxB%)#_y)}B&q9~!gQ0v%)`XSklCp%<2BwI)FwlbCTc!
+DJs^7cRBKN(;l(x!HT2Qim3jW9_PXne*_o`ep3(*=U?^rH~vI;1u`BZ9|jWP2zoSDDa2u5sTN-(Za|z
+O|^-6=(Me{D$?%RkK|2wg8_;9#B=Aea?vs-6kUF935&|F`4*yp?VTtj$OA8!&6I+m-{aiCgp$){eE<7
+SSH-ev$vZW*D%R3vGS>Mi>7^}swMUDgL|(t>s*$+;}pAP#$8aT>+~A)1_M2N>?-SpMaKLAGeU_~jioo
+dWD86Ip$uJ@AYJI<s7$R1b{UnoBollSZLoQ(R~2umetjWBaC<q9uSjR#ja7`$p7up9IwzUwO3-Rm<a9
+EFH-%lDE9)`!-Yei^9;HPQrqyU(rf2TF%Ok*BHJage__mj2vA5<{r-^c4{ZH*`ZD(k8SSK~|MM&ta(M
++HB>n)e7l3M=0V`Uz))#%i67k<b3zT0sOVIc%)1;S?IF(HQBs?4J6MQo?DT@2XKuWF^J8SXlHt72^|r
+e>{u-`sT{oqSn&(oE94SP+lwuid0Jp4XVVry-_&$05>r+W|;7-Fz5A72x416zieY?@~cTY94M+tZWRj
+&0!yamLrpF*Cy!_z;SQEJa&ChZtlzrL@HAoQt$Z+T$w#{?+QuW%#xm*oV;y}_Sr?6bDam>S`C_JmCkN
+6tl70WNAC1QTwb=G@s;gMI|dnSG2O^V)}WMby)4D^JLJ^N+Ryh`84Z^eHD{(eQl?w=N|nQyu?W~t9gW
+-0UX|3>Z^t4?OcW9gD2x%+f-h)Qb&oyaoTs|+*A$QP@h+dX7!J>#x0Rmfm(Z3~B^LB`_d9u`hAXh>O~
+e*7G?Fq_Onz>_F~;3`5%6|_dH*+Ivc<CDaZ0R3^#~7Z6E!{0y6Javl&bCAj`*`yv1E<Cu7YgV?x;;Bx
+C4A#ELTyPR+xP$fC%ijo;{}*Yf!a7h1d4h?%6k)zqWhpZDL)$uYlk#uLQH*Dd;-K#zO1AnmUu$D~=`;
+{K%x>EgD08p})>Pt^C1DV&1Rn5Z0x9o@}JNx_woua6R-+*)giuz(Xx`bxvv&2YuGbh~asmz8uW}(^cx
+ZTFFU$K;^OQipq);-b%%`n2dwf&4n2Q-<(t>jyH7%zxU^D6h3AO4eJxOV8YG4xU{uEec1FSYZNj@Qtb
+n%L%qBx>5?RckzJIQ6*o6n?#cH;>f61dD&d!oH<T?R-IvC)Lh1t!?w&qBd3AC6;`HQ=`<ma&=-_YDEB
+yEI!57o3hrg3AzcOEFWejS)_InAyTFCN^Sd~>WNEd4OP6QcmWE#Gr7Yp#MBkCpu{Z_Uk@t{Os#DFVFN
+@wxa%b&4W=UAWR#uw?R&<vN2JOrp;3ysPo#y7gj;q*<CmAd;;?)9(f?T>UHxI8INw>V*89iPk7$wUsM
+BpAHOU){0D{qV%M0#Wg0uyi_bOgURFOsbm|-gwQY#L`k?t!|LSYp`HAE=-}9(?#n2ZI#@_R&Td6hE%T
+*D-$)k257v+C0ldAw=W-2osuM)y3>a40*~a2j#(bt^MGPeWU<;Ek7hO4%Xa#0d%Q%m;xp7Oj-hqtQuE
+MPf;Sipo|#AXO<OLHk>a&Wj#A!!z|7j#@ON+)wGoJh<`hGTo%`-0B8I&FN;9Ip?K4j2biXHFP=Iu%4O
+H9+!rD969O_<NRE4N)PH1@IT?vYAG33W1y3o$1|JdNiORRy}nj6Hww$BAhbnlzMaMX~GZ%9&ZYRGXK{
+OeP%?)mEvJN#y`-{0+j`Tuvr{|&h_hxh%vnI67>IL~)s)o;Or?eyP?_PuoX(A-tth-iS8ZG-Zr%}P^k
+tA-z{wW${Pf3^1C_o~G|d*!C_yUD@fCZ1bu|2ufSE1Uj@^I(SsO7Mf)8O2?q^!&eNjS{5aZjt_f!Z@e
+l&Wne+>xPS)-*9-rI<0liDJYR=npKjEZmXrM_rY(UH<?a++4r34FUM!EzQq^UzJ7Lbaq{MsbK~^zufa
+dR{v+OHpT7GNW6rBjMn{hx;g5V)>&x)r=y&Fk$M4SGJnsdDw^sjf|H%mcH}-&^pY;#_L+I~w`s(?~_x
+-&tjb1-oIm4a)`E<j8@h8@NNJyv3l+c~_@9pdtn2(`2qW@L9p)G^M+5Co@!2g~mznICS?-H?0Zx&!@q
+r6t(SJWCVe*YD{O+lYgZ2cGdg?1=0+n&xi6BSIS{KWIR8tXU;OPBYhES%<;xZ$4c(bvIJ2WtIT7{H<^
+vb#hg;MTU7;*WoCxV4U=@s*FXWGZ>}jm{IugbZDWtYTgpOS;D}+&G-PqqmZ8R2zm)<pSmPCj1t7G;NP
+}IBTLVCghB!WEkF<6n8gx%onQTAbur9Sm0%gA-*CV+k2aByp>B~rEYMNTgLQac5kO0i*424F0=h8T-4
+QN*v5Le=@6lAGZyu=;J0L`R}uvyJUQHHish$f3hbC}v{K?L9$?z5;w?B>o}(_JcetT~r>1Zh2fx&1G)
+wSJC3F!4q0*flrQVz}e?!s8W#hYx0A%^O+#lE4OTFR@L4X>^v}j$-iY#;m-`odME7W&##87A-iwc0)f
+=X3;_fnQ>5t$}O<}|TW$KP1?U%}da>HOQA(uGDE@j*EN_Ig|ye`$=w8~?jp;vwx|<Podb_M4z3Ur7d1
+`1q>Ze18RcuNLu`;C3GKmJUAhuS88U!{qi-%%oiZ!o~^2+t9|pEjQIF%q+vc6}Rp9QHvOlom)6=Zr|?
+NhnBY>@xj<-^N9Gzl!3OJ2ir^+^|w)Zn}7JGMGz6f5f4R`^jd|y!DG+z-i3fl2yuHP>$xM*Kb3s*L})
+Usbah?eZa8nD)Mf_nw$2E-jg;>0a&%R|_DW0rH++D}cDWT2$g`9r$WF3?@NaLSr;`;vT^zeR{yS)0>$
+~*a)D8&k6<aTc$2cqO-Q<7}$U%$V-$F<2c=y8yL!*q20MPXcp*WY`8trM|n=k1_B970fUUaoK_AT5!5
+p?FveG%OyE;c)Iazz{4(vl;#JIi~`-Bvx7ohnpzd}5D@(5<}=vDr%3-EP7a!`wbxog7|2u9Wfn?Q!Ms
+8j=0Mzk0fz-6Ti<95^ZR>nG90fg=ohMV1?s;GecvPW&t_L=Q&&nk;S&R7|x<-c}rlleQf4=b>NKwQiO
+~(+y*3(}Y3zYMKm$b)OB+y}H>2(BjWMXt}5<4_`;0{G{I~DGAU`10K&?0^+%OO9=yzqN(a)xhd`i9in
+nGiBaAl@1ejeZV&L5#|&$9=MlYAyyLvi7*~vhF+LmyZtc5VK>GcTGmosz6cd#vKC@w<2Ctlf!l93?`{
+I~hFpj=A@7}lD_V$@beyge6X$dZ|@=bcEx9YeN2BoU{!7e$t9bNUL2xo!+g{gRFB+jDeU@E<6PS=G~%
+l^V}{Hvs3@xWsff>%_0dF`m0k|Nq{V&B$jme%X`{&D$w8C5vIb`&cF$c%O*#H)O^=<vEv>sf;Te*sWS
+0|XQR000O897^_9$~So0vM>Mu@yP%H9{>OVaA|NaUv_0~WN&gWWNCABY-wUIWMOn+VqtS-E^vA6eQS5
+y$g$ve{R+fBJ|Go}o_BJztL#;5&0L@B*V>-U+@ttV5ZRP40s#&HN@BA2zi&PI{QxP?WH#AdoMbEl-PP
+UI)%EJ?>c`p9;ZZhk7G-^PoNfB$(I4^6!Q+F+*|TQ7ZOg0cJ{vt7XJ35w`4>m<pFd<Du0{5C+g~?z_P
+$y6cSS3*Z<|fMDEhLgr%>~~5ZTKY&(2=IKb!XVeOA<q?Ae>wAKtzA^Y<U#ynBx?q1?fvM~~i~z0JP-!
+#7#ET32Ev>YjnXmxF_4+pMzLY`N(-t(eWQOw;z+rY@nwVpf&CXp5>lIFKJMi%xv=mHLHc=AHRf_u{^<
+%1ia;y6CR0pH*{p1xQdo8(nkVbmjfJ=&#j_ZmYljtz7e8va?gw$LD2-ZJpiE#To}R$y(7hn|3ZbS#sX
+20H`YezHg!N7jNXpThVq<OMSf({j8f`1AZpi_jR{f<6E)#3zs@;+oqKjSE4Uq9tu@+^h&;%WUtOXoIX
+GOa60?;#mlqTr?1W?*$@AIcJ^`>emKbD&&#v#PM`f}SYa$%-}GgrTV5A!CuXhqc~iDDvy*IIz#ta0b=
+#~(+ixcsm#K@Dm;sH<<gladx1w0g#6809CfQvJlW%@Ld;gbr@Lja@=MVU?9UmMV%w|PZ0p*-z=Q&PET
+V8H(I`T=D{~4&|McwsKLM+^mcKdmvOqQQrUA?H6%|KQA(_5gR{3G-U2~D)nB}s8pnBAB3ZZu<5%%JOM
+KfZnQ?!$YHVkn=lw+jGxBu72{se=X&p1pbX>h$&VXi1>472s7BJ$U}&{Rb-d9tw@}7q8!cIDPr@>|Gw
+Ej{M!(vp4Ua=k(YA{Qm6yhqLFoKR58{{hROKJv)03<@`=V&G-L)`VOj%x$zgTzkM@1`|$(zaY|h*0fW
+%9gLzeST{e4$6f$Zqe-iV4d`xX2E5LtGvyPYqQ&F}m)@#6Ch8XLJ!x(@WF4r#Wn`~jtK<9v4h$ZlrvM
+&4CY}AQrDVwv);PV1Xltoo`0vgFmB!+q}rpN_>@0DFvH|+}OW1BU#$d*l;3Fu$uPyI9s9NV4Z2mm2}|
+1bA7jv?~;O4PvhVD-bdZ-M)X13jF1C5m=vEYGk&)?Z5;P5@%xBNEFVkyZ9xR`PH&7-lbabb87Sj>CS(
+zYKJ}SS+aH6PmF^_fHp#tZ=3jd##6KdV36frC3qPV-i<>9cV5-wsJ{j8ToYs{JA!xI(BGZzdqMBKElB
+8M_7)~1=xnM7MrRcQI#73Eb#o}cnYK}>IJ<V>$TuhP<&Oq6Kjwxz+GVt;B;oq(j|H(S>#_ppiqWJHtM
+(Qa!ynW(v12(o(?aM3DrD#4OBh>nDc4_B3N8qozP6C2oAV*?<|~*Bn5Y4k~Jh8sUHjyiLnw_#eAC)I#
+8l?Pc1U)H|xG>;GG_%7`p=w$bhDf$biNU)4%Cp3<Y8g*0n@g3%G6CQgqYo#geAJTZ?(QEX5)r4;AK+2
+>`@J(6EK2V+8u4-9Wqjb=eto+?7=YlAyUE)`4uSg)z3Z#6n6E)8o!FjOR`OF!&dAGhkP!4$-7b9V<!k
+Y7jWLE{#hbq(&NLP~nG}8aQ?kO5nH?B>**0!1{II6=Y_Aq9nsO_E|z1E>ahl6>*+OZ&<g2Z${A?<#MT
+_=ptm}g23+%JfGXj$&0jXLFuAUCfRLKZS0j4??07dX#OXqSdGGtP9n{YJ<-8mcM6b>SZ)dWbPG$@=e>
+cXV5o74VCGMMxA3$rMYWhYR6f+X|HR_9767a1DJ-fffFIGDB&V>!JkEX)SuFsez$u`2^BY_vcOt(P&}
+jja+W@U-bv`R9R84`CUy6AFd;nIQ1&a#5EbGlZuA*M7x@;t-S5yA*TwIn#{q+0GP2F!`W?T5xcVk2_C
+>LN@*^suYs;qBdm0y>jV1P;jE4{&z*|Mwz@)VjFQQwwrQ=`T`wXh8xKSBO!O#yNoUi(QQw=C-gDXV(C
+Q+_pr$}=oKBH`gw0(8lGQKmwa3+5OgMK~X@9j-`?jPg8yi+s7wpx^YzwCrXGsVG6Q*tZcBl7I=aphoR
+f56o?g6uG)@Q7}=R5WL@ADn1U1*}ZP32H&C%K_+{R4?vICfEFTr7i9@`X$rbUcUQtx*(&%r4htW!c)J
+o9#0=?*^=mMo_BRs~&qJ-v#FH{YKPKVeTq?s@j|nFs9B3LT_-G(X^eNZC^rxn*nE)nXQz1>*58G-UEj
+cX>*GB<PAcp&n&n0lGn`9{gdfYG!O`6G4NM@F=1-Lq(sJ<F;52r;p1O6+D)o46MMTLLthjhS@a%PMWv
+!D*2aDA|2NM@hptTg3mgt75GU5Lxg)hH*gRraI<)0J0dx+1REDOxGJ3X;$Q`Ef_9a7MbktYk>zME&tV
+;s@S-LJ}}qO;iCVK+Pz^2u3*yMK-=4y8ir!K;`2Be)3x(y^-32hx9nY1i9ui?V&?*OpyPoL-jKMp0p;
+^3Q*v?Hf7Pnh`>Y=?RBy4vc-nVT|zN6)5kdED0qpUyP~aesX%KAGm|XAJEV_IR_UT;)JFo0P_rl5$iS
+VTi9f%o#I2}KzHpUXHq&>jgYV}B>m0-nk<EH02~705S#K&d0=1n^OhUt8Tcy7S45A}>iPRBS%%ES&q9
+F6kQZBV;!70pUL3}}Y5J&|Lp}>05t-|OeP)|jY!`50<RBw$e4**_v$`B-LcalY&jftgYBLEi(yAS+QX
+|C=M-@x#-E`@^-PIMA{Bg=vkU@z8@01(yqH(J%OoUWUNCRXefaxv&$i=uWkuV5MCUtmtLH#tGO=npu=
+f`>#8hqClxMz*^E<EA5m1YriBurpxskhiI9jRq|x{E_J9#Tv>0F@QKKr(z0Fx7o!-ew1HafEfWm=Ne`
+!)>SdL=#0cB6rN#W*6CqI@Y+JRB9In*H4alKg`Jk4EiE5APaZw|L~0KCTkx0KQ>ZtqOJFx<l8^O>sm3
+vC?Pk>IEkjmOFN)S<dIbM+D~E%dCowXk2a(ZkfF(4j4cA9tzN}$@o0VwGxs4ve1T+ZHs!#>ik3_8Ha_
+P5gA^YFaW=d>)5(k4rRCr=2)9n4az+IbUSKtB553RXHgL@G;F|dT?G~!?rV;uxJlJW^*j&%b?cP()D1
+CgZAx!P2HxgJ6mJX{mUybyJ#$4pqJk3J?frhH_whod{zF0(CR-70|fRXuyfNk2EaLgfk=!7NTPAbZ2N
+qz45)uu^^QEas2n?Dv^%#u&MUE|0x^1#jEtwp`H0K}Oq%Fc20(=!@$TvP_QMjFni@@kNwt!$NL@l94^
+53+)W-%=Q5;dYD@vp_RQ-C2n<(p~#LtK(_<J*sn7wZ($%g*_re!2}RcA94C4x!5E^ar+8v3>;X$DGS|
+q5wyS+#eg%p|SUb@uNwpmf#~P23we%H|T^XnCmzshLD&}$R#;9x-X?;Mi^m0?rWtnQLsGUkL%N9n}iV
+m0!>uBUaubXVuw1S0|Es1EH$YsU-8n}d5D6jf8Z8voa#>EBthd`XcD{c?{=mEhG6ZvG2q616=VpOwH{
+K-+Ckn1YSy{hI;*uKnv_^MFbQa56oop2}O6r}qeY(uHX^#Od^+QRWl7mB^K;@#3+@{1B@|9JkH>$n*(
+Vk2$R%G$qOT|8`C${ns{mfu<miqsm^l8JW4QhUh6uYtceP?(ehSGIsKMz4?b?7H7%2c)iQ#563Y!qQq
+xT@qGR+4H{ArJ#)|hF|r9_kMYZ-7j1GpgPQjv;H+SlwHi{NZEBbKu?>oN^zjwa}828sTOBkMb(N)VKg
+<lQ70uhV6vPOx-GSLP&<-AD$oZ|kWhsu4Vt%>@h1U=e!V?=d-Ua3UjyIROYa<1q-^?t2Ikk~W_MT)EC
+d}0#Fz@5=~1V!foJb;P37xR{-n!BPr7lA9s$=@a_vW{gZ>34lcJ0wtE|At2tV9ul$SM-Kq=R3V@=zWb
+^`y0ruTF^1sycTm(NW@4bWqyw6${$tE0fh0{nS}((prD+?Kelf_p9k^z<*k%I*q#;~bgKq7hx4_a40K
+;#M#;sZRECQ#zYYrvcAwDC!K$NOM0|74rzwcim>Mo9vM){pgteXQ9O(xAqlhkaA(F;Dml$+7cqyxU3Q
+vGwT`8${ItqXb(6R$2D3fyjM$2p~(#*t1LG*EcetCQ6FPZ+7UkN1P^*cq#*~x>uW?f8SsWaxSNhDh#m
+*tce7<sD=IMiZ~03?2)$zg*IRKAh2GX9Pe$DBCS7jP6*h9WH>8>ppH=1*sGM%r#7stc-GmN>1#kzJ2*
+{pX_)<m_4P#eS?-?O35?r)#%$!)v&=FpWPGS$m#8rcvHrUXR2$$F+!=A;M0+~sWxN0!2rR~f4rYc$uJ
+dk7h3rD4>UpOP3DBAh8-hISy6u&ad8jz(XK7~cL>IZoTND?xIlEX=<*0HfYoRPMQlgL;^pVR3f;pS<$
+6p#_M=c-V+ai{gml++6f0#T$_oLp_J^F6>pig>vt*gNbt)5vW!d@B{uh!Hv&7Y`f`6BJ0~Lb3w5T6X8
+*M&Z38jkA(U-4$C>{8pQ;XR$;P2703jeiBjS9TBno6XP7D9};^2>JM~bGv`2V)mi%Ea#Mn((wD&E7Xr
+i8L_Oc?Kt6k1?*&B@qUV-;+}O@d-P}>+-KAh+Eg0Yt0?aIcBlMjT7@T?TUREr7g9i!_AA7w+4Ni1+Xr
+cTJNN$=+kT2EI4Hb5ADPLUZ09P<Y^@bzzM4&+eC8O-1f3@`N-8JpPnkD9|^PA#Ic-q6|7Pau!?kCP9D
+(SA4fdOd-72~NMT_hM!b@E|Rt3EF=n^PYsq(=s&S#Bk@<$3{~=;lD3>|8F*lDDaLAPmUb##Mj11*Czk
+K29C4B9$QP*NUf<W;lL-%;XE}=?F$4>aIjdkWr9*TXv1*w4?e;ueRFr4FxJ!HFI*bd73$WTa;I#3;YE
+1N!<5s(aBHz{xJrfmK^SwEk%K68ahL_Zhg6fZUcC12ljx<(cS>jp*`7>Cg=7H7F*R6i`k~Fx*+Vw>U_
+rm#`NjmRP>l8IVoHL$dD@)DMu<1D7z5ts{QQycQ0vTDCTiDq1e%LdR|N~<YKS}M}a)*Ga>2EumtbWjn
+C&RfL^N-hLjj#ps@~&^EAU?Q~;*K?2Ns>u8M7E_FPaY)RtR~IswetH87Aw$eHqa+jf~I^NB;T<J3@;P
+Cq<^NQAHzK`+}dt_0*=19K-g1C9;gM>PJC>g*$F^(Mx>t}NYBPq?;DG{NHT`(C(FHPD5m!ndgrFRZnq
+U=)tJ?gIUiK6_E0);SiXJi@CP+Hw}MR||hM7VMvCxdAXT09OkOf-dFSd{4UL><VMYtj0+_MkT-sENJs
+dX5mDEO+<E3Pl7=sk610H!C0yEBx8<tVsW><<3?1_isEYHBn`KlS~VWfu@hMv^fI@r=E(*SXP?@FQ#a
+iN>q(#3hFdw^2q-Z9r?%nLO*gR+x1ZXAUDXbsW;?mFOPi&X3Nb0RxSHLdc?l>REjJY?X;n8SQ&vL_^c
+?ucDvnhMwNV0O^D}bUQE6aYA)hlkt?I*s><894Q}M*_tVUNb9vQMK*Hm`I?i1`!#j!9=X9xb$YQJNBe
+GN((J9PVNg$L75<BG9SjL0>-G!p9W$y<79Y6Koe%e(0M6)~7rH){Y$FJj{0qVJ*m@y8#f>^@pG3&GZ8
+O%b#hb(M1IdO=kAyxCM7<wMn!GzR8*1lqVdI7YU}a0Hx#J$$5|3h$>N_e;>M{4I<mg4mmJ;6YOEBUEn
+@1HKk}V68j3rD04Qe6-V!gSe&m^hDk#dF+h8>vt*dTQpob>Xp{LkNL}j(xHp)A#_AThPC3eEPs1v1}k
+OV4xa#2uAdBr*9NrrR-L&jc)!GBPm?GVwX0?HRd3&Ivs{+<sOe<qPr8q&=XmAKf(ke7bmiP1asJ<JPe
+dlws3+Z@hBT>(glLBa&OobB)+brODUL0K=Gcy&S+a)Qk%o*4CqW5#HNA}=+hcQ%0|=+t2l6HW$AKw<k
+G2u!KB^^eXU%v@bhnWGOP^{2mSQBRE}N-|sKl12um-+cTp;S87b8Zoa)Hq+k4AZtqZ}cm5M9trIr^{}
+G0JF3jM=rARV51(L-j2COjkAU0yQ*Tpm<Jyc!53xvcN4DEXiKjyFwXfN>w0_Es_cvaHs+eT4D&vAPQr
+S%o}BFI4|uHDGy-sfcYpA+^IT2Td|U0JoljS6uERfQZ6W!OF_mRaWK5^DZ@USt;SvMrHMSKi8}ny2KP
+hVO{et^Z<92w+2_RbmzL6wb;>BD{cn9Vn^yTHo`EWLPg7J2k36I5IRb0xD@2Sqp@;S{Q=UV)#UghKps
+)_z#Q08(Khg2`7h!;kH7>PN&Q27OvctItFiG42O+^|3SXUw0KUh4_0dq{1Hb+CAjvmZ`kZq9Ep!Osef
+{e|dYU0ygP1jkKJZVbN{_-n~-re)jt8<buDKqI0(eZcay1tg2q*<~Hoh!4_=xp#%siL}ST98K=_PaE_
+Q+qSv=8y5W5^b?hoVvE~gD|=1<+it+ArcCYh2gL!i}4`L0i9GTD9WX}gx(yP^(3kCTES7%?CickSQKW
+;+xb>p$Hhh7T^FC{7Z*ujT;z){zQRKC*O!0fU+^FN_VqXF+iLN(jB6eS_x0yrVB{~ylPPuvbZKpe@uK
+5T>Gfsy>g77!5lX2RLkgZc2Cm{<OxG3|xw0y2w%jg-M)4$j_5AA{@c2MCgCi1D1Q#eB9g~A1-d>W}lw
+*ZtcW}judoWz)Wsk@IhYq=Ov=DC{GFTN>1PU;yhwxTzHVOksHWUH3Y$|lw6CLI!xo>y7Hn*n}8DxgLf
+m);yPw<-Gx2{|mQy@dvaH5gAs&%MdX)wyYr`DPLGETsJ(w%5c-|M*EUf}m5;)~L6Z+Y`|G0uK8MVEiE
+6tl~3z7jR&KpJt0@w7!^UXLyT^#DiEx4h`)Wf=*-e$qYZ$U@-0PGmbqyNPQyNmlQvIh+{6BA-L#;)e-
+|Y2=`GOtS}sVChZE22}hPZ1D4v(E?l@5?*i|mpqM#S#d5<)j++VS37;Y%t1-On6(KqL|BC#aenf>00g
+C`82LDYGRsXxavI^WAZoWq?WWGykI})p!S#!4I;oW9k|!n=Gw&QBr{jodXYA8y7MqGs?|yW@=yTl<KH
+$CMa5qPJn251aE=zCf;<hL&Izoq7V)6=L!%*ab#alo10i7n3$EVHb$f0#>tI;cWPFY$)=R5_Sn%r5@f
+q5r%BT2CA;*YZr0uSjGK(t3R;2*AqsIt$dUwo+~vhQjc2#4}pPn@OR)d!hc<(Idg&II-Vm;tGPJbxnf
+Nt|TKfqwCcaq|$lxqVEXSZ?<|to%s_lsy&sVd}AEm06GmSC89mYgwqwOBSFY4}(en<tgTN*hOoH>*!+
+Z3_dlSK86qUaM$y`S<mS3DJBEV9Uh>Hi+eyuH(Gl>51O%NEdUh2X)kk{on<7<h$jWRSu93I=24nM?~u
+61FWD20?%fK+MmHMob{T4aTXZhb^ZcZvbHXjV-ooaiemG_SI6VNk$qqb%W}bA9cJCoudz*8NWf^j@D8
+oqQOESI)&OH*dPeY&BsjlB|lwHB(z@`-X)XKk!DUeVv&jhOv;gZLa*^2U0S{gO=gv>S-KWEHwI*wAzL
+G2Bp(fV#$mhT+&4uWdLZiteyE0sEv(m3TjqQH7r+-kj41=Z1URV8glD#@Oq#$U#esJ2drIN~Cb4N)bY
+>{(0S!!`4m+*TRIy-24mhcBQKhVy0R*IAUImj4*l(3!4o*1kHRYZ3I`b&Jc6G!f@}SRbdpZSE-OaCns
+Xtjdl|dYG-(Ds^8;b&L8+j4I$S0Bk(Tz8uF>i!kL<hM;bPJRS-1gnICM1wC5vv5W;*!z()&;K&Qzbtf
+g$xwxo?K0f(0pCFh{Btot2nhqCsP&vus6M~OAEh3{OMzK+k6K>p2o!oZweroO`qeu7HeBq2!d=>*~Lk
+HjP9iXx(DXI~5p+>hn(P<<L1=9(~EvQ<E7t3XNMzzi`zlMF1(}|W76n6-Q%ciJ8V6t7wulNA*jo9+wD
+9~+y+qfAbcQ6}2Kc^#g+r)-}6!a$h>S(9a-YGpexy3?F1xst`c~uVADJVYj1dekm@R!bN6^*?A2hQsM
+ktzJ;s;%yzJEJU3c2R+oqgR@*@>hZ$C~>b`biu6h%ta|f6NdDIbA?Z(kEC^B(nUUqOp@>n`Rqq6%P46
+eMh3{jXv;0&KfjA=%kETZG%dYT6z+Ko6}q$g=*jChAI^?>Q{wdP3yy)gMk%Y6ElTliEpdzOgKTUn^wK
+6ytr#ED6?CK49Wo|}d(v5l1X=wy=|RnauqmVLOq6R%wY|dzB^|jJt+Uf;Hiv_8sSOs>0PO;jw|HQKWw
+&;zvNQjN3Z`@<CABZo(<GKBxLBaqQroQesE!XZJ2g)yC*EWxr$(J0GA$ZJk~88z#MZbXB2=c^q&WkVE
+}qc|p1ia|`_bM@olZiQGSek#H4n;6_bjnGy?{0Z7(eO=kd>?g<5o6ydXS5Yk+Hd?{wD1vN<D!FZzya#
+H|s<QBHCG=X_6tO8!yNfr>F1o8Jf5piJ^$~R?NGloYd`h)^6&-oWvw#Iv;ZgRBiH^ZQc$u6X3AXYpMO
+e)9kc1CM0<&u$l*r_M|XB5N@;JWZ^h^QCql``v7XA2lJJyog(&1!<##ni8ixHMN_L?1=rmoQDZ05q`-
+o`OfxbQHslZ1;PKrQCIdtSC6nV1N$A?#aQh%FG?igEF4jWpSjPEbkx@R!T?9luXOlA!-6M%i6ux>(ti
+bVADb~jK2aIfZlwFx#hZ!A|PnxDCn!CXmdVp#+^fFn|$;r3g&M_Sh{M#fG>OIaD4Ox%tP0uDLE_Pms+
+DUQr<sZI@)}~+@PR?<n4AwkkVgpITWSu9()YQOW=I}!#7p#L@cG|K3Py6lGX@2eYR*?wp>o3>Rs~1hU
+N}aMu6v>ZJJ_-qXV8c27_`oIoC+5pDzCjG=O_d2Pm2dz|XjA^Dxf@x`ma(C&Zl@}pFe2u~t44C69uem
+hB;l!PJHS)S46xU#KNRb0Y(&9mobq{2Y$0My=t5SOYV<lhL|8r}HwAkV^_G069gUq*>U08Si-+6UmpO
+_|dK*-6OwI&t-=dH4offtunN)V0iPgH_j+M<|V3nN=N}Fb9C~$R}VcN2kU%8svZkIBgwmMnbXmD}_5}
+WKYN1WpLawPd22c2id91$uLTVOOf*hY&wmx1gW+=w8En)OdYI5~M+OjppOOhUl&PlP<4sMFAt<wFDFW
+vjB(6?2N5rI&H(WzgdKPxqHqpD0lj3lA5V)>)!Dnzv3K;?qkx<YIm}m7kxqTs^=&<FLI>sSTBQuPnlJ
+oqdL?_yz;kuKdIkj+`T0C)#0Jm`O<jmcuA2Mxu;e3p^Xh?^u*2-MooW(F&PJdbZ$2TBgw%@<`ew`ALp
+Mv#TUNPT&a_mgflo$RztbI8|W!GL)er65i=QX;GX8E73!{F@Y$Sk~kjg;$g@J^t+S2FojQg7KyvLYu9
+Qc6f6eP4(D`t4H96XedIe1R=SQRuB&%Z@U%Ie?70zJj-8Xt9uH0CtUg$WQ1bN#L~D78Tzm~iqx=(HN^
+9or*JK&fpXfEsX+`98juVqrT9H+hU!rNjq*^yMaetkeE%dFBC@Cyo*wV^i7<k#)QQa3eBstM90}^Ia_
+mu0CbYY|u5(-joYFKz2KBLq4=0tx+nE?21gxeBBcIfV^BQ!?=XIC3KTsEF&FKP!Co|aKU&_Y2*m+Mfc
+@8~EHNm1p$bImD76p#z1X?jjos^F=k{qmNDV8g*dIOofv@la8HUKsZg=W~H(<V5;<DsfxXy|cGb+NV~
+Eg~{N`cWF7%$nI_&2TASkYnCJ)6GvLU+IM(a>)2!U7Npp2J>SJQC8lE)Mc$KR7z1BGc%pXZ6U>OV;_V
+H6XM^4@NwF>^C(fnsAuys3Wm}NX!{NR$;Ulx}SyVQZgwMY2$-n7|Z+dxv*~K8w0nSH#1&sMN;C_#CG3
+__m+h5{yG>2g2X+)1a4QWP0<$d>jq21<Y4}Q_iH#(5n;YP=p2m1KJA6*!guZ(~D{v}dJ<>of|6M#E_F
+<m#>Z^IHK7AGJd?aR^4*{)qX_@AAJTpTc!h?D=sg*f01u~+0Lc|+7{vvhG>R=5aYdPZ7qWw{hkmQ=E2
+6$vPhCs<qA9nrL}w1y57E*Hy^hTT-_3gc;I)EF%}Ki~@oKv$wkKN{#TBWpQNvXO7byWn+E*-G76Huw%
+scef{}Te7J<%Kuu+6v)(vP?NF1hv{P7eE_rQt>G!lLgq;@mqW%PI@1~c2nJ`HHNps~{y6O&x1an;%VA
+L*Zd|A<8>ar;?T%E97=?R<tA>L!cRc_?Y1@%tn84Mj{YleeN6vY^{?HtaPD~j8(5Z|2h|>YTA`jMJsI
+=viFl>gBahUU~%Gn*=A){=Yyg63j(Tk_~#l?}#FfZh^+k0h$C$y3Q-E`@ltB?J+G#FswGEltif_iqE#
+*Ca=X+V0<Fdb=*gqQ|UILE1M;^ADzg>%A;kMl4x-NXXJ2Ol1@2g{rz4aO`_%;UXd(jPZrHy~#B@s~Oi
+rHmKK{&bRk=AXW&WL<tE|HCQdU%4=GB9mB&l1-c+eQ_M{cE3KE?`k#q^*{f(cgoS|T;(oH!Yw<b5aM~
+4qH0W@SB}q&bFAD}_I)-LiLbPT!eeO>K-+ZQ_)>%$)c+!k*k^PpH6^ye>2SSYcYl*jO=tVkK8dIEU7{
+fdJ?*6nRECl$hN@3@#@T^!x3(%bKi-zxZ7%JbLwD_(y4I#W>ixZ(#$D+}9`3Wj%FF`!gJk4QD-XD!sa
+Yu&LTAi=OYf$=2Vuq>g60ikSK}E>Odv^hWL>mFMN&8IM0bO%GpOnWyG7%C-TignuaBQT1&alSz3s1?d
+fK#CPeDf(Eqc?Rq8^L~fvU%x405VYwi6Kb1M%j4RtK&kx$XBkZngWQl{ty*%4J#~>cAC&Q@1TY@W7Qe
+gLp4$q7JB+ODk-L@Ow>)wu*ZxOn)XWc)BgXa*Yr;YU1MJ?SFiCgtvphaFmurn;l9oisp=@Yz;J-bd4?
+_7zcw86A1vOFnuNP4cuXc1t(<gMuOs-pjJk`<ngV@c`fod!om$R(oM2@lHGcXp;PG+YwtDZNUW{gh!0
+4O$RJE^#9Qw+UQ5usAN+IJ*7APvfi8Vn#vX^dblKFwF79CrtxlQ)Da8F;kX8<(z%yg@$FN=X(pLP{^E
+i7g^Z{V>{9cMB=FZ1~_>tnjq{}{k-S<oo4b#P}IUA%qMyHh`tmpw}mGrq2jjgB^q%w#Fdl{7N(9Uwz%
+?OH@4iz8G|Lm*2RfbhmBxJm?0)%IgWGZY2&LP4+JXYMVr$l^o;@;dyegv#?v6+iS44T&|&-wDR=V!r3
+xnIJQNOq|`9G&!8xj5+raMZaeziTm^pT~026F@K3*7vpA{3RgA8H~Q~+0ZnJ&$@Y0bE?99bWsEp-$#n
+4ZjWa^i$hTt^6odf*OWqR-dxpXr;_wqZOH74>Ha3K^Tj9(nM!fLo={mg7bL|?TEvEXOZ(~ibYG213=z
+37RUv80!X9LKpXer%uX2!aDxrrsw&yG|DeQ?fMSb#o&T@;!X!jy@Oyy_W3utnMwvtgI1aD_oJI;UZ2D
+yuja``#7z45DY7zJN)8Ip^9N!zD!m_1lbG)r6H#Z(=Wn>CK-G7-Ban~O2&MBJ9l?e^l$KDpeIbJtf&3
+4y<)aQ1Ih;Xnu#bSE#b4MI605qptNC62b9ea9MTWLZ%X(U^gRM_HBTnyBZWF~-U#8sHw6Agh^-wQW;W
+q^iMeP&0Lq*J@SC@xgWF(nFMCJkGv-@#CvA(9Y{crEZk%RCc1jm20(sgRD!Z8wkK)LFf(q!}sV;^<Sb
+*gfPnU+)(R1`A}cHiTj%nG)Eob3~5SuYNpmch5W}n5^FMaoLv69$6O~bi<h8N9o<0(1X{1H6cCRj1`l
+4VCru_=x%1&9FLh3`5w9VKH&BdEggfw!tDndsl1ol9)M0FY($c|apveIylUn4(;DLR7lI&>*XNu%0Og
+K5IW8^^<wRC3a$w6lY{+R5k`(R3K_Hue=8U@BOhU3N_T0}v5Y$|WY^q8&?<yewteMBhBRAvG6hS+$Vk
+VxX)7`q#4jYT)D_`7mys+0?4<av>PvRH&LO%RwYvpWvVtoxlA6{PkkYq;PH7)u=q3BeSTf5nX;FK>e^
+>-+z-U%>Lq?8xE}v2p)Nb2$9}sObOqqN3vw`9Z*lCW<4PoSmsw>?1GngD#V72LF3dWVCEbInW2AnDH6
+1nD>un_K50X5zUEM(O>JlUSwMS(TDepb-Lr|o?{5lR*SD=2uAhUk09P{T1wBEB|u!DWsNack@KQ-L{*
+HU*1MIrZzLNSPp`$jPL$^k$i$aNBcO2Oxi5My0e@2YgI{;q=}1g#JwIeAMl5vuK+QuUDsA^+LhA41KE
+%g1hB56dX{ad-k-IFFvE<S8=_9_+map6*mz%us=u-4|oW|G5Ka_w}P#!TW#@NZ|8?TjMG6Ofig&xEDN
+Xm;|?!Qw+ULr+{Y;^tLlYr_;@=J{f+Oxbv#d^tizqQTgisNOLU?lH@2WjODbVWwJYDPPe+yg|RTy^8X
+|K`+i$e0rw(k9u?L=&k9gNY7f84Pg!WgJ?E9~fQM3PX5U_<_adle@BeMIV>|E`<RKfIU>dD1PeV0)-z
+Yp`{+{M6a^D12osSMcrZiFZG-=s=z=hH*9E{z0q_x7#s#h-<{Nq$Xl91zjH^t9xH`bnPJN7{vsl9zet
+SVT(jzK%C+2q{uf~La;J#m;HOU$0r1wa+<OW9XOMMC4upWx&HP$oM>e?LHxk9Gr|EB}144$d43--{;^
+jiZG5z9Tn253aPZ<hRi#uZUGY*M4iAV7qG}Xc_78#$ps8!#%`CVJAuj6;MzEdHy?j4=k6;{z&iE}T5<
+j0ig-BjS<KlprIuK6sONjq4erClt3D&|;phGGr49+~N@V$JNzz4}2XvqGK*wt<|^s<;#t+66MrBKyao
+0DYGk(aTN-3TpR;GE2qcitJnhqe6!+F6bu!r7K#4i<ngY@0MIz-3BBIrW#lAL*r?7T6N8Yc+m>u9>j8
+4&P%$8t1S>xQBAZQ74Tx~_U_{19%YpoFU$xqN6~dnOP3wopzF8f-dtR?2m*85LFx1RkC-w3wC16aknv
+y_h^;0-F?_kCD`AUTI!w4I&uEva5}aeb-a2{zoP9u?YD(loo`J15^%obiA`a0cos|92hh#J@4AFtJLr
+gX9aQcCl5;*&AN9-}*X6uozqJ4|8SaD2#o@tk6y)$N<KF&-=<g-b|XopUruhqG1T;AmnhPlb!p33wGh
+jx)e6}3i7)mD=DiUq6av5x7+w|LuU_r(;M6=gh$-wH6urGeCkAV#>-g*~1jB%j+I{}{>e?a==~;m7t2
+#0om|f$K-k!~G=NN>&rOQUm9rNUpcTdzu#a-S*H+<)z^rQY(kS<lTSDjAc#aZh}vqCho}gpQR&&sAFI
+!P()od!-;YCCan99+9Ff)JGOT>R$zOT=yt`qWxiJMy$*E8_$BViwwMgx)`ss@aC=CbTQ9^vRzmg2zK{
+&bQIc(hGfZqYm^!tMG^+E!9$FO+^-*9BPIWoTzYY^QR`*$&a3x6^QH1!n&uZLIj8huDQEqOZe|4)`2V
+os3M%d8a3|6vcHnK@WyCk#`L-#rGE(!e^?vfD58h5J<NFZ<Ah&%b*C6KpmN%4JrPd!-KBsy$FHJcvOF
+9Cn#*iX}6>ZyBT(pJj!5{PhfZyhX3b2qZp04w!QNwmorxY-R1%?Ak&k)|#f97!b58h0x20ChkWzRI&h
+MpyQGO4>mq^^&M>E;VN4GFC`eNRR+N4=U0<<*L3qi~ZL+kM>L4_jGkLR6GCt_+xl|i9S2Y6)ZaFo7tj
+KbOrxI^Aa%&rf5xjH796^y96Oq#ueG~Hy_m8YX(6UfYdRxZbi<W!==qC(Ek!NMvfQ^1_l7eA4A(n=&5
+tGG7X7zx`I_Ytz`BYY49<9j&)6FdhOmvMa*G&j4pI+UxouhKd|=~7e`fjBhby?7H<1oF&GQ-7WBR(n2
+TN1(k$>%M_wN-N=B!nIsg5y^&|KE3zID@p)RqWrT}dfOVNW_y|LaH?bpx9;!!>ZcPz2xqra+kK}*2h!
+-%YRY%jVahAr!b8(*|GcJfEKC4BU!jQ%}m%?tnj_*XoXHYh}F25Ihm48^;8(jJItZ~j{QT-Y=+4#ENg
+Y|}j8)Yvb_*`NILiMnmYlU<_vd%!Mq1xE8p_UO4);ZeH$<<-2Y8a{2jpkl!^6F)8MY?y2ubRm*7jv_&
+3*2(Wgzy8bl<h{0d+!}g+Rn9S^5iIGU{mHkYMNcm7G@4o&)>513(r{80tnAz5UYN+uf6RFz_~JRNX^d
+DKFy1&uA;%$Y>F8OT=S{Rzq7#7SMZASQfvM~^HJ|>JJ%PXG#fE*<d{blyZeF&0<)3TP(;cvxMBjWnuX
+d$sx9zU%RdItc4Ba)U&)K|LZxzZlH*+(U7oq)3DH$f&?SmL0!8yO7R3hir30=S_h%J;t{;@&y>)o*{0
+TBozS~a&qC&Ots?m46$a}Q97An4fcFm_{9*!>(scapsFHW8Pk8dGffChp>000&Sb_vHdbD=9d!z|$Z2
+{`E>MY0>jcj7oC)^mu+}%(U)NfqKGI3wSL&VMwR<aVH%~ftYBQL|>7fVSKDvJ|BT`){dEPP4KFo8bQG
+NP<ELfymt!4u?Sv)cEj6OOwqitnHD_fP9*+9Dd^@3UFwh9d~}OY>U+9WVoPvhQxqoK8jbh3xCd71yU2
+~+lJUjWepkc)M190nvOR^_Q?JvC?E#K$1-xWN{iTYXiMf;}SZ*BJuP9|##Eq>fk&WJ%H{04-q;~AUl2
+BPS)-e?HbLT(6Q4&qj`cR|T<mczU$<zy0A_sRPz`O8M(E;N%qnjRQ{A0xb@MJM6Pl9cQvFm(ACQjZIb
+mmf88C+I~BMQG8>EJ=41L??DyDT#B>~d393(E+h{rnQ6K!Hf_m|;2RcRjVmKGDNMK5)6RhU*afTGgIP
+*q(CBi`*O{<;dmWG@};{;W8TX<TkqV$Y&<<|M|piL1M@Ors~-)2(Dzg9y}E5Evy=3F)k;)71Hg(ofW3
+dDlmvc9jcxEFGdy})G#mO5(*2_tOnH=;&v9s8gqX2pY3yCUKDLC4vS;j=;{C>+^Kwl-k9jIobPLWRO~
+N|v_yP8=NF)(#r+Xqd%08!7aiF4ca0(>pyO!fl($b;RTTB4&5mTEcE0$yuC}`m6$V4YN1maEZ_?oqO}
+d#x7i;kW@k2pbf=**2R{Yb~ZY32*8`~`}ISC=9tWv8XG#r2oG&Rd&tzG3DVMG)we3B<cbl0o_(Z8eMc
+(naIlxF;<7zfc}cu6OgN&_)$jCLwmFe{8q;#A;tKxYF;77JB5sXxm4VdqSzl)sw$rF$cVJC&0Holey#
+*ADUIPDysl8A__ld;{pc6<}IjiJC&0QbL&}JUO$wL+wVA3X<hUq7sLW$lpuco07-g-ZCCkUtJ1{y;1G
++UAbt(-3gf$l`l+@(n?8OnKMXfsy_2g92g087~~x4Y?$iK&I2R4)CF<W5%XP1dtd+3YA430uy>bI_iH
+SN*z21`gK7m4OR#%K)fMVdL8LSl-8Jz@;4Bzt&TX<0htRC-5_mKM-b~kx9oPfi(XK34sC1h-oxF|p=4
+0Shqta@6L?l{=+E#il6gKFg9(^{((MgMu=9;$*#d<<P1U+Alg9-ukgwv(sb~MJ%H8L<l-|e!tR*)2mi
+{D@YsitsS{hwp~I8Vum=~Tuy+mA8*zh$+dCWIRg{YcW2oRJ-CEw&Z2&uT+J9ftjIn?2|byeq&4?V=fD
+2y%tW%NBPl<*nuLVc&&nYa^(nU_K6Op{^<M47-HlLvhX2wG1}V^}G!yRMz2>uLId`0z@&T*)#jOq7K(
+PzV&;n9-9|nbB+iE__jq$J6@i;e|UHUD&ke=MQEL3Fd-0ONvCu$J#4e!V58!Ou6kp#W<vc54-yuvS>b
+RbaCaqio7D<~ZcZ|8kme+pZ!tRiE#AR--Bc<wr251oS}p9;kh<6Mo6g?@|EO11;vGvxh7YDE>MuOOlx
+p6_r)>d`R)FjO4Nyx11QY-O00;maO7>PNk{{Xe6aWBXQ2+oO0001RX>c!Jc4cm4Z*nhWX>)XJX<{#FZ
+e(S6E^vA6Tzik(xV8U(J_T>mK=Q6fd2GArbvqYGv$Nd+ve{rVX>XARwk*-Mc4SGVq;cGf``!CHhonS3
+>~S`^7u&@OK}MFy!}H>Kk<>$R{>8b7@;J%XGf`Ko^WW2xvxjF7#f!Yyt7N^Yg#Th9o;`W`mH11Ng?sT
+P{4ps4w0N0BGAm^)s$5hXDPHfZO`eH2`KsE5N{VmuI*Y?9!86=QB|;39RVrE5RgPb4CFNFT6~THVrFe
+Pu;_}s-%b@yDi7<=BiyvOyTwnd^?adF@Z|EV~oh92MSC!a=<t9y*_Gg-}*C4_E%u9P$Zt5yYn_u;^P<
+bTF=6xl%#VSeVS*7-~Gl6TR@-3)QG9;!5)9!{JoXHQ7EGluu4=<I<)l7(oqEO*_8_q<QgTOnfT0n8V-
+R|dyz@2fMz&`yZDJu|l$%BAv=5>^Bi?Fhd{O@jVUjHd9ljwO}ZN3AaQmLlmTK=P!Wi=J_`gK^AyIjTJ
+uho=s8C<nWi%^wvDwcJU#`C<88G$Jwooqd?_Ju4bW_;qH9sQq4F^>~8d?OVIeXa5j`?E7*Kg4@s<q)i
+8^^%|Y^LZ9-<$OLlJNxGH+vjgz-psFFeRKKWXzXpOswiiV9~b)~339dO8?R}1efj+5_tZ{5K8sS2C0>
+WoZMc?KP^b@nzWh-})kI6~!Gj0<_hyrnLN`{jP_l%ImC(IH_Y?_r6`HHbGL>SNR2wMo>#M1w#tg~~CU
+~@<8HI0_tler4442+{bKPvN$~pd3-$`(a1v=*u=jiY%4zK?<|Ba_1#BwF(c$rl5xnIh3H6^)Ryvj3aN
+OH-d>k4g?FilE{2?9dOD$F7ooHY$*kZQOkFf;H$inrG<MZRLP7>Ph!t)Qlu3Wbc4RU%_eGqqb`P7)VH
+QjRK3jj0}tqD8m|7!$0Z{{g2X>ux*J{5kBvDp}Wxt%E;lTSOa}gsI46mFCeDGOIT9KZq))0xGWdQ_QS
+zt%qVA_U-U3m}F)85H8${Znz)*>Oq(dNhW;OLvL#I(Q{Z&mkNp7{i*4DNp=T8#H3<*nZTayXW~)miAQ
+3H4nHZ(q?~W`oCO6W>29O4Oy`(aB$@FB>tcQA`FxXus@_Z1ZJOPFUIwwe%jz@*sXK2X!cvq;cH1TQp?
+C{&X_V!j6f~^U3Os<0C@2b)4zHd~sW07-3W76WbJl|bJG%v^VDd<<EbU#zqBo@$0f3PN2xeaZbT!twf
+2jxrw`M(nWTV@86sD>F4hn;L32v4UnD?HHTb$R`1rdF~EFQklS1QGQC!>9#a)iu<cruPD18F5VKE>!-
+VuIWb-Wt#I!yD~&Mtc*N9m@hEJSWqsB22gK7Fx$M<$!7Vv#i(>kj)~CUkcNS#gt@~RAIydZOo<U%;K`
+O4KpRHT4gf^XuynHj-iJcL7TKK+Qv;M4V@mray0ag*p(yXUZb_K_8=sTNPD{U@cgI?LJA=c%?8VvK)a
+YCFX}X`WGl+W0ya{S!&@w-_+`~z{{n*PcCp~l1}#-e_mvKZWN8DBcItMpIhlQF4mN21wUAb%a_%e5nw
+|kSxT7gLkPr7g`^-CF%-pv2S-&mQ?Kb2GG~L;;_px9%;<UBq6&+g3+DN?&@8s!He}mS?r5=dC<+a$>C
+B>L%Tw+?dVkPN0@@^&UigGD2XQ25oLo{J3(w416RB_CI8q=j@jCci3zI5E;h@4CCMD_*Ud1_?buxdEK
+5l+3J#$@q_<afztE-j_Zh*eX5uU%%?x&&$6CRs_i-El79T~`mmHS%TbvO7v=UYzEr8*qeL1A-;IWcfN
+8SdgCfB4|ep^ENP<H~)@DBE>ccW6U}O&u?c$3#&u*v`g##LBv=-;1}DDWn6<Rc&cMeXkv)8ESwz9UHY
+QAHV_a+lNDq=CvoDRj+^UJE4n1df0x9tn0A<9bZXzs#B(v@Kz+9O-aK10Q7xg4*cf1;gQ*N5uTT(&4!
+drWu<`dItG7!aOwP-?wFYhEtIH!`EWg}vw{d9{RTIn6sx093ByJ*^+<{`ArEFPhyrHmUo0N=<4#5W_D
+xI|bM5E9!m;+HbBIg|$=H`8c{64DOx9_|eIdck&D8b^0bMHA0mhqx6g^-Y0l*e*zp89c+AZ-RFQ}OQo
+#OY-CVR|9$ikm*>?_m^}S=A?_z=6S$;oInl!i8o^n2A^6A?785#ASWRFzVD@s5;AxdfD6_wjQ=0qGmk
+^ov@U`ryNfJbtTnsLeTJ9vyeb1a2x!@CT<!n;Zy#_1DY%wvoGCGf<7?aT!S-RF*qYlh?(GJm!zpcnop
+ypd&-WJ;^35khs=;?x0N1nsHiIo9(cOc4lvUEGz4O15tOh%PNE|)MolxX%E#xzZj&HSzfpD1=9i=&j0
+C5Z1jO%#=ZQ&ohY|BI&Sq#xl1SCyH>eusO#(%Rqv(OvBn6rZzwEx$<q!Z`)@$E;RNBPQH)=L<jJifXO
+7l{>!7K&AWwOpXkvlS9u)zSqOD@<@BkL8W;#TfC1TaN}k1+5&b4ZLy6;e^ejs9s6HpGm;P=762TEvvI
+v;G=op|{%PYOLd-$}%y!cfyvA^Ixm~{MP=`7>odDxL~m;%VMKK7$oZhG$8MA>ZPwjC3mo<#7oi4Im3d
+%$d=(P>8#!GH*gCSwvz5f8!mi?aBYkTbvld$kBO{U*8w6EmX6kK4g;}X)GHCL+2Vj3rBV=OMuM*k54k
+!kdM6bN^(1aI<$yOO0ceY1eY|5LUQ<b8F+SOm*I^>Qv&k}N@gSzE%kx!CX~Q#*pJn-ZRqeg^ZUAY;F&
+-i|Z!fw<lQ9V0p1>)PA1a#c?=UoVf`q+x!oBYlpE~+TxRB_E`1GJI!z$Wn+FI>3G(Yj25h`MkEnNrO+
+nDa%D%uL~^D-cH41Ua$%&(v?_Q4WRX@2^4+D^om!VAJOaw6d#YB6GoXmd_<X#_*H&6U1I3>&8B6u)}o
+Wfg0y&{jJRO644D=1|r(ok@0=-}2G~3@G{oOQr_MO$J^c4+*Rj_SSv#$xV_B7|ba!I#y}Dt}|Y)&|07
+H4>+M%SeHI!1?QSRtyb(cTtRT#Njfx@KtWF|3z~d$oek_ti{*@_erMWKHfhoq#1#8VnzFq$GPDvhCI@
+pdipCzp)><>&A#cPQJQr16uw&qw9|s`DKsWQ+L#hXMkOQ4sJCU!3$Y^ih#3TbKi-oS$QQ?HG&L@JBN-
+Yjpo7-Ke*5vvBrvuy52zWC$uz7v;`f@sG2H?k<{jX~nTCpCs3L2w#1Uk{taSyf=JrIs$EZ@7&fKc~Y(
+SyPDV4e(Le4$5cXVXLRS7b{F%PVpZtfqBFUI_7t*dQr_-b5k2+DWku_sC+|$~yoMyoe~3@L#%CI4B-E
+Wx>{_Jq40Fxb`ccB&!Ry(I!xb9stb?-^vBkFVMHPuIpHY>M7oZ%1wEyXD5Rvc^dGzof?k1;GYe^pD0=
+enq<LFA%F4P9+S~lov2X1*o8@ls;Al@c5v%GG3K!d^o^dI4(mXhQ%)ntMRxiBI^cW*Fu%r=|F7|+9rC
+~uU>h+W2K7myWVkHzl$tjJbwmKN$hKIvBHH61ZiotV=Rh4*hXBc%HMj}#`l-}?I(?5g`<IoNGvlKE1h
+crfAqgS-kwbOxG&PYXQSBHb6^Z{CEJYovkP_H7-wVN>SlekyYfZvC1xt@`F?p_vh9wyzl-AN9mZ0Sb$
+JW?-)zIp&ap{RkKO04jy3-DZ3$LWI9~tw#DGTCJUMnd1z;cZ$)LTXp(@#mNK(@B0T~Pm7R5u-ysQEf#
+6b~3xcMjeI;osP-T9wd)(p`t}r6fr-gzFMnQXWmQhYO|JG9${0>xg0^T09}}Qy~KfrT&Eom0-c5f`G+
+hNk8T=hcb0zRzpam$(j<Y4<N?uzS2nOx|-Hm{Ozn#4zDT?#J3on=Wu^x4COW&w#hwqd7Z{bph1N|5>G
+RV-*ehKup`TZ%z*n+3*rcxeHA<#A@UdO1b-e&2c{}&D*{N`%BpPZ0jIeQg0P}ZP`19=^#2S?6pk0~>}
+N5>71`SYVavRxsxz$in!*B-9TGnw-;}m6Vb`Q};T>EbSG3MGFb*!gZfq{oQVyZ_V~#eA{*1xKFwkf>_
+q4-!YN_}3th#7Y3!R-@2)zl*T}q07H;<FGUT`scD+4_An_iP(BR}XSu9P<6v)_F^?5dyN*E<gCf|a6|
+dfSDeneZ5bw#&WZk_WL>d6e^hsnRrm+HYj-K3>|}KA3&mzq#+VY1xBD?T>ybz-0zi1l-?FJ-}Jk2TD|
+Wc;|a$$}ms8V`aK&E5ynB-i%;v>q@-U4*UMFcCawf>X3po*xDrz-m*1sLiI7c?WmI@N^ZxTbcfR0b_2
+Dol$5@O4D;Uw?1q^qE*CNpKWW9#1gvo$)wF53-D~1Tu6RrPV?QDhHX&vQ?9VX59N>3s0sUYEY1lI!f*
+$kkhodkTFB7<x8yjVG!BRkW5Kt$USS&Q_H`SJQX^k@B-^sxzh%lAkDCf!U-3hti<P|x23#2t-S%0y?G
+=a5gx#-;+d}Kc%>|l)0^Q3@7`$wzaPVk{$v|V+JrXTNl*LKlte{VQR#RZI1yTc%uOk-o!ttSI3sEcuA
+qXrR#(LOu97XgOK_pD!PaCVITsOQjhSahA%$E~AA_)|<Hm00v1lHP(#;~(a2fI_&nKaa&fr)22I7p^r
+@$Cj>#7#=A)w(Bd$7hl_}0Y5Z_E*n1Am^x$?dfQcRz+d`Gbt~&%*Q!rmtM0Wm8^KPPxSws!wzVS0f;2
+;a1{-pU1^EjPOBST5JCo`7)nNRh4Th>E&7kgj!wwe1oW21Pl<JFb5m(9axqr0ga433lDHnCt)*S4rDj
+g3wt>W(V?rz+0S3de~`I8*7bA7_9M}MKhp2K=F6;Dr$0X0=Wea+&Y)e3Wvr!`G+zRUW{6}3viI|M>Hv
+({<8S*f5?3#!`W`Ry^wW2?-3EcQ-jiKMhm9~594WQT177_+xDqXT=bR=&#BmbP))0xj+B<jo;%mnNO0
+HhI0qw5^pw+?ej$06EuZ1PG@s@;8(B;Fq5SGO+L>48N2OawfTHpoH0;*YYNg?IZ(Y=mNAKY4b{&-0J*
+nwyLveM(1I`eU->NiG&M}^m&1-V+&~F$DyL_qDvLhSwM3xifiq(5hqRaU1@~DrR;h%WsT`vL0t2$8A}
+MKzsvw_J416Is-=@=N}FoXZY>#eeO!Jh^!`{*22MMV>8!XoL->e3kYmP2QtZ}d+$ACD0;imRzPzz<{%
+}vQRnwl^XxCg_VG>@n_HjJNr-L^m2|hFao-Ip0l?ka7%G?@1PKS%P8%+(8x{Fzpftc61!ffAaJMSM`U
+s)`ue&;O~6LWZlM}@yIu==v=QPfUlvmug?l9W6*##Fbbv16R;De*z?VzhWPJk;-oheYY>24t^t3#gHZ
+<1U8vY}(3FS|971>ZR~0j-G0nOh!&<T9G!TV108!?c7NAg3GMlAtK?+$iMrh!aOzICcPSEm-KIXblZg
+r4cFcCM3P<QWIS{N5%UzlbV{HVW|N#F=D_LtS82CEVHS}M(l$8Ui!#?%WT$PWwnnm}9uF<UT%!Q(LYK
+9(7rrg!whqVJnNn`ND*9)5!x%nemD5=|vlmH!dI6z6>{b@iX?@tlXTgVFN1(iu`b-y54Ch;^{o_@Vk$
+dTuXjjGPNe}ZO0-sJnb!9Vph<C%=uXyMEst5>ae`pYvX&&8{$v-I>`u)@Yd^S?L=6B~$N6Kg+#Y0cVV
+P^Gq^d;uN15;Nyhxpgk<^fG?gY5X}TZ2QARlaHW?!gNK<E4i2en=XHK&^!t1>C;(Ez;ALB~u=F2>8&E
+i4OgS?Og0{ARav5OnStv4xexyKfJ7|fFQoS5MZYsYJ3<dv)LVYq)}rV`^$hGNT!8dWI6(`(FNc)R3S6
+sePYr?eypg>)EZfh0V4(*03VtF&6<^Uu49zlCQqf=YXDTW!Es#)E9ZYf)%5{QlEokS;YsoK06EVX!Vv
+Z)BfFN$3c&@TLx+;YqnJ*}kWqUS^A6>57?3{_KH*`Q;u>R30UM!ESO)~d$`J&IU4cv6xGIEERflQgh@
+b~!OOPE9v}H<n8;avlCi18WHn&O1xN&4ahklyC;-qwr+4`uQG84^tp~k6Nqkk%({$-h{shgbOGi@4d$
+~e|zHW^XJ=IewAzYZO{mb{0%ANVxIHsdoE<a6}NY*tdv#geM6C)j0`VStUXb$Dh=-GD?Wp0r5QuFd!(
+NK)Ht({wT(tC_>NWp~%LJ<r@fv)ffJ+qXGOHr8b_0P21y<OG0j^A?!?>JNRu#`y@4|AmDx$cuG@fCCY
+dcB>A(B?Y^A*j-o{SB*>VXctX5ndhYq{%T0Bj~P(a$z(Yte|BhW$1wHR!Zomr1~^q<m?OQ|VOE0f&pw
+7{85uh}PAX3r=Dx}buj#XmoajNvb?l*d9*0F`mlE~IjKH0#slrj-K{BEmR_L^J0MPesW{)2e!vk8Fx|
+39@mh^$C#|j~GA<M^4fBW@UPri1xoQJCF>9zCWBi1eZyJ<kOyEXjf@4Fc3^sO!ze%e$+x4%EtFmQpBz
+I%VxX~OG1Tx8_8!~RT?t$GiA8<XgrpL^oVhSYJ{`JRpM;1~Ea6}&GG2yD-(RPYC0k-K>CsC)o(J}&;-
+Nq-;j_*hHtz~QR9!9L(gR}gaVZm4CZXqlva=G?=W`<e0)4EaNY(_#Mj9o#1;aB7rGdY(^uI^EFOCyQ?
+B(UhRM-IjT*Klb%^_4mxIYA`6L_*!v;ZJkyLy?X4BZsA|JgS9TC$%A^Ep)5zuE~coz>*z%%O`&Z^$dW
+n82D*+ew8xN)F~4?fb-=|;>M^yLbbNiNqKz@?h@|LKT<`%Zta5eAxsPr|!2sxdX|Ah>+=4ivm&9lKfk
+QwM%?tYS9NIYFp>rsylC7jqJ$)5CagN6H^G{ptwcr9nXpcnNmg~VYIaQO<sJ(&XdmOlXRGj!1P)h>@6
+aWAK2ml;P_EyH=5KS#J000-u0018V003}la4%nWWo~3|axY|Qb98KJVlQlOV_|e}a&s<ldF_2`ciTpm
+;CKBBL>e!^gn}*QG2QGa8MotfJSUxaY^NuC6gLGDAcYnQFaRi-Y3IN1eN~~VPyi`Ay^}p>aT1FJt8Tq
++-FMwO2~Iye4d!K<7t2YoZ5F40z&A%HM<>CPa<i-Q<#iK8Pe#G{qqFl<_~+B$Z+VgIf|toZ@=XlIzRl
+-ZQD<q;ltFWy1<!ZQby);2%SCgSR9WzKxh>M9$>AM*$f_WL_KK#;XWOQPZ_6sn)>+XYte069eEaOl)9
++qBjhi=3kQ8a~<ooYly?FNLA6|X`;w8R>az{t`dQ(<Su>2+894)GH9pq&o@BX}NvijNgs>na;vQVE_<
+#GuFRbR_mecF_D{$`Uj*Xl);9W~W%aumQLubS&BOK_f!vN!W=(*)1x{nM%{t4R=?1e+>Zu9HbnlrX^C
+tTHR7+x2=k)gXeTHsDE_Usn0-h({BvdSB&r1FxS_i!g=q^SoR`Z&jgaTdn?4=EXRG51XW_Gy1eG+Rx`
+WxFT7@H}&ZpUXQ7do#*FmwuO>EZ_5U&7g;?|Ht=b-%~$EP++;;o^;G@l)vM<(vNW%<dGie{-wGGJ4*s
+0fne%!aG})VG+Ux+bAJ&TuI#M@d0!s5d4t{v?EqxlvOaNvjGXQQ*7@-zS*4X;?9L7Bk*2zsaP2siFUu
+R8%FjW1&%J;GU^sKl|R(VRTN+p1|(vv?==GR#|-Bd6yRkIrhup72jHmz4l4Gq?tRo+Y&`6}b-UuF%K{
+Rd3Mlp6Alofd9d!T4duaC4016~dUp{7nJBY8v9ptb)(atMbjx3#urqHT3@%uB)a^s;fa@r)n4mcJK%2
+{s!M>>EF1NIrO{hEYoBEZ~QV2@_Nb$na@_)(Gl)4SoI6F-C}_LExn7TJb>xw=;)irFTZ*EVv2vDXq6F
+8!z@Kr`1k0iyN^Z}(PeVFcy#*5*B_0-(b1D{9=~|`^p#uoPe0Wk&aZK98u)Yp|3~qMBlz=g;TTIk8y$
+V~>aX8Uk%~P1?$z|w|9<||h7lqfKD=($tGCGp7Hdwl>fxK{x*2`BUP04eJ^lLe58u9;KKt&gr$0jF@V
+aR>_2l8h&2E#&WwoRa;n7i=Eodr})rxRTp&pI8#%+4>U0Gx!rYpzC$489j&9*86s1%r$0;&|;6y;qJ%
+yvKvgB<ARo0uw103VVyZtY3%3aBpZi=bQ(0X9oj1bY%Z4psmfOJFk$v)fo~^($W>cv#&4J3Z0Jg)c7x
+Yf|X9`6>rYg`W(R#4*E0&(~SGZ7x2JAC0J}rmgsJAEkPX{hV%+`AxEfDdXY`;5e(5QH9G!;e1urSvZ1
+XM|0S2b>PsL$U}FW*?$~xP2gU4WpxuI74j=!QnT$6rZT9@wdQFb$LH}I=<g~6u+D6q;4)NMShrPiF^D
+#)-L?RJNAL)cREx5B8Pl8d0LuI@+ZN3>_`b;UDxZ(y;2Er0@NLOx8C(O;5Y}=cGgk)$;bAhH!(MEl$$
+V7@vuvJhkuEkto$PAr3~%uu45dCS?W|mG>u~_v8ZdC)Y;m5c&ULw6r2#^~niZ4cu$G#LZaA72YD~;qC
+MvJ%Z5EuIef-%UKjUe_t%2KSnjtZne*EY>s<YJs_vp{#V6hpa5CYU^T`$Kn$a>T+IEV%~Z#7|79YlFC
+FDqQs)o!E^XuVxE`DT^5lT{l~qPhe=UCxpj46_ED50)itG91beFP_0{2S31w7kLGng=@#Uc9GpN>f?6
+MZ?Wo4w!`&~!j-fPv?ttFd1#D4c9ayAo=rLwTQ?#lE}_EfPN^A)4mbKOfR$=$ul9-~_MS7hG|-c#hIW
++*5i!V-*@`L_3nE<rEe!23=>CgL62bZ+1DGzhKosF+G#UpkXaRqn)JfA+kqjN?u*x>8WS&j=jXRzANZ
+Hsf8Nsaio5@yn)(eFu8~V-_T>|ByCGnvs?H6zcAGHaNsIJw}8RCce;$!#4zq>Ea6@{eDQC3koLlLAy4
+2fQGNyO|Gm#%|T*y_N`k&Yw{zs@WU;*i6-+*Yt0z*<2Z!k?i-Q5ZK#6)%6m?Li-BznrVj^cTc={;tZ*
+ehGQ~X21ffT?byaTvEa8O-6t3u2)h4g!I)m1;Na%vPl==SZ4LaV2n)yqXXVa0sx5Uch~v+Iv{zc4tC`
+>xJ!V$0h?GS&HOqht_xHx0jeXgKu!dz2cU2daxtJS$uh}{x*<|YZM3pdaF;jNOkcM}fvNxlVk%0czte
+C~Livi@f-M4a5BG6Ouz~0$YS9#thsKj)o*{&!9qkq<B@oih?iNMyWR}A})%<!S<L(Zaz!^;m9c1bb^2
+DkHaTx|>Pk0v(KEg%7byACftYJFM3lNj1vV)kuT!b>e=EheDhR-volY?*zC`-~2545G&A|x@iN$_W3i
+5jU_WqCtrzAkIj`Q|9U2(yN{g^AwvZQLSbjTc2JT0zC*g*3uX&=g_`(ByiP&GSW`)qT(qz<dh~4cdSH
+^!X`trCfvD5BRG9o)Ry<x(Zj>GMVqftE)a>Ib)6Lp-A(vAz<kdv8`Q;81sDh{8{XsU|fxON*WHV<v)M
+5e^6XNx@fRjHPe7-APd!6juHv=nyDu>ZoUT+-oSFK>#+grE~AkH9t9}1vi2EN32g(QMn&+CEv(+Q#<2
+m}#sab3QK@rbDX@_%D~?7+tIrmurWTEmwa!5}f;lBch$$d4Gwe9;^-80l0SK2L_9#_Sl9VWQpwrc2I8
+oqOic;d!9}qdsskq)D8OEM~N<i}hY*nG5GicQ(M_!@dh%4asBuzj5FZ?$$wj&Om%g~1G*?vlKDRzMXW
+ZH3^+`@Xz387OzVpUlU`x-iM*$OvM8AxJLHfA5=Y`tlA(P+O&W9by?A?!4u!N8)g6OaK$oub^O7<53`
+cac*-Og<*4r`WM>i)h=*i*088VAgAr`evHKl0+k8I%p=j3+*z@LD8rVScoTBuDcHFWXEeU%Rss(wY+C
+JPJ;i$Jp{8uI4V%k`qo@mOyJf*a+mCEG&0a+<o23~hTCa_p2SqltT%0~5N<u0AFeLcrma`o^~TH`JI!
+ixML%<W{Z5&0qN!;MF+jT=Rg{5SB-@IAalS?)XRyp~VGX1bS%Kgs$Qnq5L9l_f+HA-$cnjJavQf>4aC
+@6}tX3cwVgr(we#h*Fb+;KA#a2XWfXW~Z-p)w0v#J24GYMOwX^~R;#x^~<%U3IejZ_Uq3JpjVP<o+B>
+5vbB%u_EwEGGfxE@$0TK|>nVLn;z1`d!&PYX?IXsVIC-ig-IprF5%th7L*d*kleMZ_q&m+H0F3yLVnI
+vEpAoir+EjAtKe*{y-RMsV5OlEMp=p#I*I8(Q1NZ0Xwovc7R1CPVB}%nIPeqlF2=^Ug0`i+nh``j;ey
+$3Uz8U59Ec})MN-8mAJ%OuMI%1x=Cd%!ajPpK5AfQ!(`g5l}f_!ysV|3msLjkIHM6N%6=^R3*Zlm*Qn
+MfTu=B*D}|5@GrulNz~fDoEi&Z%Xe4SS-bEJ~l_kx;$c<@?u=IG;QE725TE|VSUPeuf-`moLx^)q}st
+nGY*HboUUucjq@ctULvdGjWrLd{xc<az|^yosCAw{)pqlVQ}%cvfar9DzDj)Ww)+E_=FfN3y{G-R+w1
+zB0FLn1P9ku^ZIy4DG2uw&ifvC+w~o&keE@#@=%b;d5JKH-JY232NM1MW(~8`Lxb(PqFb0`wvRuBCYj
+e2MK6sgEq7{tEb2x0Xpn5~Y}-?b{~e5thr|BuIqXIS?B~a9hX0FZpI<(YRJk)1-?{jf><KG?Y3}t^pn
+dQXqN-Z^pWR?Vdn}i`o|#1f?I1kNA?6d}U5#11%t`n*4l~H@hGLOlsLLl^BW8mN5&F7KxPY5yWwY99!
+R+L%GfrRceU`mU2kaxwq7L$Jz(rzJStQ3EJ$^nOjSK{D3>$t<27+IL$!sj6&eI0b2%<u{@~Q;PL>CO$
+J^bU?8-?zBn9YANjSsg0fXwC!ul>4lwt}O@pctNmd99kXzNqy{$+r!&7?zkwZ-M@~RIjSl+gK+0#Em@
+-GVj+u)i{n^KdIX<jVKmK+>3JW_*k$D*epXYoKNfUpt;UHc*uJ?N-mkC=vbjsA8ZeRFbekUCV)t7M~v
+-XcIRAt>a_Y-G#EFta)AKTBkS{_qSzeOmsTY*z=zIGp2ga4b`M+|ra|HFd|d1jjH7$A4-C;W1kb4Y2-
+YA<RJsswokiu?%=Va)lFGLfiez6-LMtJU^U|j=FTgHXevxBz%Kn3CJ~_tZR%H$SRQU7a)T5@@`mD{5@
+WkcW82nL6EE(;kemyc@Z9<>D!y}K|Rs<4e}$2&)5Xg<_T@gK0{exAtHCY?dclEU^uB+|B37}Fq*YJ?a
+69cjsaJepf~}5b-b*~?Zy=Hx&+3lgEKz1=e?}*CC)WUJQ$^7v`?=Qsqn+)>Dg;y_z%PV(`W#^oIphvY
+DX5bd+oKiD0zzI6<ZK9z@w4J7H~wmaK)N#3;5UwKy4Ao79K1-$~*oJ_({APxq%X0-*=}%L0$$|vOKIc
+8-TU3X$oQ=vF+)$!0B&DZ|HyaZwGinYz2_V=)iD!*?PK)3QQTUrRbrqrg_V7J)k8}r44S1B9|not#WU
+dn?uFIa5UP}nGJE$({={P1w~%Zy^UXnu@ps*OmusBK6yPF5g)rn3dXZS-kH|}{rJ`TMXZ!MS_~tv4p5
+8nku7zXROp9_!knX?m`Gr+SYPpND^`}v#vvMm%Fum@JPL9qte%e4JX%Xp)2;f5pB9<Cs$`dZu*T46vp
+~=Iy4$crQ=xDVb+hR*^pDDRg8=Z+h5|=a6UKZ9<-nC|4nvZ@wGq!GPL4GBP&UON9oB2s+mI!_0vOy5F
+yf}4oC+qIL>z-|OxkKQeMbiMJqMCbd=&ZIPs*rtOF9lBn^eajore)ks`W1<ocP?Ec;a&sN}LzQfFk*<
+Q9U1$*8-Q~xesnLM3VdAvwC=;FI~cpRyBg^1<;Ab5p+SB3?)0C&F~VW)+q~oVeo*8VI%xzpYAwiQ#KY
+Ar3&?{KI@&Bdr7tw1HYlk%y#4iC;KlJJm!-1u~Ep7LRrxfZ!LOigAn_!hGJ+=FC;WA3C>R`)*y&XF?U
+3Y07lx4i3G6yKX}5%l~vm&_745Tptd1-dHK!b^G`n;vxVcYUwyjAs9_1w&|)aVBl8!|n!PykD_Y;+w@
+Y2xroE(V!dN)utG-U4N67it>8HL3CDdZ2w7~OI8{KJZqUuXR4nOhihJlg21K~{Gr^^_m21-N+M}1?Hf
+VS>r_Kl0C76Yvg8B^aD*ly4gprW8DkXi>{VbQ@o@dH%`)Re9n`++P66mF`1q&;Jr;YY0Uw}v;PI-4OR
+++*G{F1DAq7KrO|mDbcnP{J)6=5m!KMeB>x@(Befik+j-c0Fb2G|ig+Eg?b<HW_cqO~j0<T>_;+n?)4
+;v-DjZIbL`%4SS-U5SLQe-aqS<NL}6N;QImHSm5cf{m2msBvQzTM;RU37`@e6xBk%jU4+IGCh1xn-N^
+I-nd)nY>KIhx5`OoPbu=2Ju>?jTxDPCN6Q}=XN$H(oWVe22H;$Lzzz@))xXv1hsfyYu%$jI4ijy?8O*
+J$>;?$Iu-Lb0ml{s!VsQ8d|Jfv}sp~_SM^#w;_^f)hbHe_3|S(f=;1vzk-9Tp|;lF>)qtihNhCd~K|q
+vK6qwZ+~RWf??g@uN|QTX2(A*U6?gjEf$w^2J2}wZ_5c!8!i<0Ka}b3f*oPvoS$y<JA?~5w5Pr=rJwt
+@b^<Gpxv^Atv4mQ<aqkiIQYIbG2R;#x?Px|xHd`SSiyu`)RQaIPkf~v#3)t5n2-%$T`_|S>h1ix+pe{
+;a}~d!#&HiWUy<tM9G{7d&lWYS?%_Np559XKi&fJkU~SpLss|PFO>fIO?8FIq>5wodlB@kBLHF_^s$y
+?DwxTA5Q6~$c2lXf%D}ZC<O<5%0Msa&iM?umt0T*rPk5Z_r*j6xMUQugRRYt)V!8yz?OfXU*5{#9kMe
+-yf8ek_V-L_(PLcxJ}c%&Y;9l+9Jov=#RD`pj!Hn+K*uj+Q@lzD1OXxovIZji01mb{|e4U14jPRFf0*
+`q;vgTe6e8c(GO+;ghCY;?XEP*5?35U0vDio+DAEhu(S>D9h@7iFA`qncdd&PMP!ztF)rucz&=!}>I>
+lnS)#=?Xq4dpg8r?19%eIft{D<SrZp;lNX35AG6R1!TXt(Q_C3Z7Hth?Qs3mHM~(!2)9NK#@cW&?pr^
+?g_FVgmAy$taATfzr&n#Hn$7@n(J}7S3n4o2vFpvnQv3X-43T2c#W2ME=u~T^Q7Uk0dMDJQ$-mmKU1?
+J*<DFwTRh+$Ps>HL$B@C2*MoCsadZa3C{hJb9YkNXrriw=V^Vbo5cjPTw%C)1bX%*5AKt*f_W`}ms`J
+ckuH7_NT@^yMRuBJ+&t@)F8PP7i)lINj#WJkl3Qz{q~@#6Utby!9II;T}$8Buo_g;WPW{`K2asMbbQJ
+4aN4XB6NH;&WMX7v@QUR7{02(O#=5wj)^Q90nWFkry&S@GH{Fh_)lMwa>kH4l|Ho{^5r=u*EHp)*&Yu
+TzSzt@5yHjXz^v>oud!j=p=ZqBh5Lo5CmDCXcz@d(01M%xJYFqdp+1shhl;ZRFBSHax|n*^>Hx!w*ya
+$>Ph{dj^9)f$ZT_q{ijv$6(ro6m6=pbU|Sm^1%7Qwf-8SX`_lAOab;1DQHf~RLOYfGl8q2A6RdzE;-N
+HdhhpKGd4DA`#&|2~!}b^YbbYi}ftP}@STOMOC0j3E`wO<rgUf0&uD|$-^H)f5rnK@d?CA<Hz`L?aYp
+afW3FP_mbx*~5yI!N6$gC&toVLX7VX9S;0@Go>Jv6>pl)Urm%ST=Q*>=jbFZc`_W}o6i?Ic#E9xH-+l
+r=%y5!?cZ!8Dw_=ou_N`$xbXy59hd4*IMp{q_?dfPJ<hha0xc@IPOE|J{ALA=V4)0IR~RG+DJsfTsWt
+gqN@>b|8qYb2%EY*cNQX#K=N|M=>Sps5J6Oz;0lUbk6FXd0xv+i~+p^J27)?@T~uC7)5`eKUoTNl)an
+?YvG0eI__Z~$+jkQjCTHqm?a0T6_oOY1I^pX?<lL#_C{?WK1@e{y67*&9?Qp=?Is$5DuAb=qY=oQ3sN
+EPI+8GUCPv}4j=JQI47vw%59vU98RF)4SwOm<sicRplk`4}B)vZiN#B=wq}?(@bXlZ=R1rOotbf_gj+
+b(qR9nO8lI}wpkEzl0Q(J>c)mmLSjMDd0`F5cD$$c-WKcE*UKsfH`hz<vUE3vLKt-3b|qm~I)rJ?UY*
+4H49dKEv7&=&@J58JP}Z^;Vx@GeMA{Y^dP{WhjlQ5#S`d5g3gP(F1_`4GNzF<zHER2*qhyWA_4&^o-2
+SW?~x$&Cu{gz3g8-^DZJ19K?4pY+Wj%XKF%eAfYH&SR(WK@zIJmV*<WLI-pep94BMJo!VUW)ReU>5V^
+F(6&Jt$CfwSCejJpqRcU1iJdQN-6AA)E;5P>1Cb|7#o}ksfgaNj=(GOpBz(k>3RRgn3~D-)#-aQ=gx`
+~y3DyrCYG_ieSD4fgz3@q1?M_wvOO-9NH+(FSgHDulT?{>F4HkIlfiLFQm>(rCZpQl9driMIOoOuE_`
+1p#$3d18Ezj5MEX|W9gO)ew&rGva;Fb2T+*KG5X8j6|fvg|5P&x5P+XyEDk+XOL4`i%WQYmv*T5eI^B
++(8thQMI;SGMA-FQ+mRU?VA>{uFRH39GDF0xa>3W^Zu%+w&t+9BE*sRm0hjpzA+TS~kqf_T}U_`tteb
+@b2u3%fBDL{%~~sHk3E#@Fs*e;ahp}F}(N!s{K^J+Yx;DX!PX~w$g!zr*3R`cml_Q2QO@RM-f8o>D?!
+t-hJx!?lTJ-^bAJJ>E?pB_~#}6`H^vbN=bF>#C1^Nb9@cmpiyz|y36qR^_LMecKpTbk47%g{(LE%v9S
+LPr{BETrl0wt$Wbb%&C}w$93^90qnQh3j!YZ%mw~JyO7b=%E?g~+zIW||YfZecED%QwcZoFAq2m{B3v
+&J<I+MAZ;>p`$TDi*+Uj98f{pHc=AOG!teKdYJ`P0Rh{}G=&nEv$B+tb%Nksv|%4=3NFUJ@h)hp3q{q
+qR!LN4pE_a`GNpf~Ewr&4=w_g?w>B$*kOxEjzDV3Nhvrk{Kxc>%3@F8G+PBN4gu3;y@8?g-RuK@QT}o
+DM1JUTx=`q5>Z=i18@ha5<svrXfMw3s~n`q?FMlWW*|Pcm+rmK7U3g2Whl^<bzBNb-W#LpX@2B8B}JU
+tGPttaRUaS6O&%{Wy%a2qfy+*`lk!wE+G1o`6o&2y5wRnd_s_!DNW%Hcx%uT|`r;cO|Ne<t_*3)CXQ8
+8e@>XIEu5A#htoh|*N3b2VIds-dN=vHQ?z$QTL+@eGh-c9%S<li0=s*xYc<|u-4O%fkhmO?Fe>58PhD
+DKN#ZCtpx0V0rzcccGN+JsmDZDPpvy34&6@74`lR8l~C(7Xhw6bVCSi>Gx1s`3kGMr`-G?$NFW4{n;c
+41re{gTs5@>{)>{W)wce5_4{yx&=ds#_VVHl1jiK*-U{PPie7X4ST++boQn-?)|p5I76Z9)ABP451=w
+hWrQ5bv7t%)JTtlWm&RB1fMtgCPZ0~+#47RhHh_3$yQc3r1Fv&mVoG4ZlPyMeXYBLqikhA<a$+`ry$L
+e6%*Fmq{^}G6XtlQPYce3EwrdssVk8;Qo5w}005>YTfy9f6Uy66X00^|MJ-JUF+DXDkTso6C|`B_7x?
+FE<T~g^1VQ&gGFC@3koDP0X22+b5?e54{Nt~^!hq#O<HLl-c0I*ugHc?ZJ$h$vr25@;Mpk9nxE{$an~
++-4Gp;FL#!M(d@<=i78pW_tGG1OWNkmh}z2utkPgE#EIURHsfp{ye=saxcsM9NBhPY?&Vuoo*76HH3_
+-tmz1H=ZT9_AvQuAM!)x0`mzHS68=zlllRDyio1Ld~ZA^Au@DZ>G3ujYqCsHpxFV<&@P#HyfE<Y?h?c
+>yjf2JYX>HhYny>KoPJE#g^J-j5US=#y6)apn5krPL-fNegU(36PfJ6$kO)7rxVOkr_$}sh+pLF-M&+
+a7!<JuR6sIhKtehuO^rE`FOeqL3X*9eUTlHb12ICL1ZrN`&>m~MY5)VmN$1sR2hL02gL%Q(EHQl^`G7
+FAU7_+R^^HWmISPet$1tJ`5Hyp-^#&S>ZDF%_syJR*^7>5yJE%M@jx&#EXXge<b6Osft6#}zC`||tgQ
+GQQ_RU;GI)@*pAYuU-%4<+F3Jk$Hl+?<kZSM#)#f^aGp09yx0CZSu+`Ise2qn;gAj)HdN)lF+_?^v|r
+H%&lB{fnzf|0CF6xNdzONkLR5Z67DZ7l`QOVq%&&l<MG@=miwp#}ueY)$sn&Kc&0&*wWSimd*sIJ3so
+PVW*RI)^M>1`3c;f((H{uS^ilcF<nImnPsRz-ADDIl~*SqK1WSDx1w(h;v=`<-7Y1bO6p}+vdu=LxHE
+<u#E)76a0lYT%GJ#_%KB~>MkcRLyLWupco|`v=*>EE~@6lqqJ%|NR~EA6VL6u6Uc_o7I$c^iDT_@{kG
+0Vj-fILglDuGpp&gi7qCunUIZQIz+R7LuQ#)u4P;6>4Pp1^mZJ?7a_E$^w|rr~c1$F3JC5`WJ&KC4b|
+!utQqI8ud^(Br?W)$cb=-xp>5P@@(?sx<ruJ!ul!2qXEMv=0ptj}3_RTcPe@g%G+1odN_-y*wCvTH#j
+Tb+>JuF<e3h!WiAD_RSChPRGPeyOo$-J!JOuzgo{b=;l%(mJPnq!D^r*C`npM8Z1;@M&m(778<q^uyF
+>eF6IOZw6a#!O+^?S(RO*`W-$Dd(V4=uA3$JFC*>6m8y|dYd;CaG(?BSjlp{*>0+A2`XMznWiU|me6x
+(&dgG4AC=Q)s?MP}XeuN*#ppmwl(`|AG0v);*GPx;4F#mjm2C>(gsxpEOSBAVa8z?RgP<dspj5zH!H+
+9lo0bGwSs|_6sC6mD(Q-pcl8AhD2w>lV4i`P>WXI_jnv}>XNORQPbD9RZCSr~6PKYC-2SO4#n?##3jG
+}v?hl=!_&5W(1neN8Gmu5~^%3(SsjX<!TeJzq*uws)<&z2S2CnhRnJ8D9;`3NPStYkQJQUEQkWcjqub
+>dYA`Fy)dIu=$V!zy(!?a_EGA<t{xobrFBNfSG2Etw~+hA*o+^T1A;{EzyHDZBT&dGb4%q=Z-7Dix*u
+@abMSl^8FE12OYESxovKZSWa1UiIGsUM1Or=pfH^xy}#)=rE6LBlk4V-~{kVt`=U?&=m$c<KhCo-*-Z
+Ls1ISrfuLLpgsL;jQG|V*EhGvj(805j8yt!^ag^i{rxab3PYU(d6}}C-vO`ZF{Qa;hSo(%@RK(c-`oJ
+3RU4zCclF)aNnMo|L&AoZ~SacdvSvaAB7`w#3t#Z551wwLpn#!fE4XR^GHHkziZ(553dw$4aqu8^N>J
+qn-llijihA|XjAkD<{F~R;0BYdw*HlS?_)6n3jP@I1q*Q664u1)V+xLjtgR_K*=IXJm5&&^V&XD6Wn9
+sj*?CPWCAX0l&8Ach8$WPzdzNC6b8&`a-n598sp(9V1$512p^;|OSV22aEhTan%0Y8At0)_M>BnUA5O
+pqIkt3IiRAbOQaZ^hiJ~rTKs!n2eZbsCAg^9|k_X3Xj^)dMEd;zQ1plO0<85B;v()vEM`^lS+Jb&=F~
+THts>v_sGI^c)(4sCWm2qcX;7f%F)VXPET%27!pv0WgSdT_iB#5D+=%tX6)V3C-y48RF)dVVDz8n4cZ
+~&u-iCi{Lmy=lY)J^&R<LlD~U0HE{`#jSDj<jy2|aD7pLoNU4p8@>U>KwfBf;s;MMnEeNU>#L|v{SNy
+Q8Fy|p?A83FK6Jq6Iis&Ch5H3D@-gQM_q41BmNQC&eE00Ik8Rmty*p8f@$Xy$ap+AORhGH~~5XhnwGS
+FDZI)=2lk-h`=C?=dT$sLaC~nBTa`R&=S%w#b_u>f#T-%5I-vczX5lX;SZ=VHZ}b6FE_IO1B7}0*kr7
+1iN(-ej16W(d88qTPthI(;eq^npcz|SY1rYuKAIV2`PI|$5#P@7GHaa_c(@zhu%2o=oobdbGf(0x(6N
+IT)-$unDmUH8%mffd%Tx)=FfT{LnSzRtlDL=&j$5U9h$~t<6FAC2<kGlb{P2ekX*@C_A_)(E^lRxR_-
+#p_-FWdj#Tk96HhB<{mN0e1*8mr?b3!`R%s95>r5Y)?lYpv+<DI}(1mTvV`_T4{9rt710fi0T4q2Uh9
+G6%UsA%ai0lXY9zYKFSB~mem@tjfto6xCol8$8m4FF-fPE8t5yv2Pc!_Af>gh5*-J>48Mb+Z>jZV4Yd
+qyWCR8WRx5OLnCRad_JOI7=IfP@kwR26rltYpJ5CA5uUdCsWx3^t_uwfn7`822XE+$wvZwOm89u^yfV
+qZdX<Twm$E0;&<*rw;U}76xX5<sykS+;eaCJz5S|=;Ay*3&mlw05&#D48N%RXc9`H#vD7T5x&3w9nPT
+Zc&^=W2CZ+f_C#5$2XQ*4Fw74wf=?cO(!T`VXzQ<?Kx>oz^rx#(mucTaLj6se$Hz50?wNMY%SapQvLa
+(t?;?2rCd2BL$=hK#a)rj5fb<W%8zq<PBO`1Ugq%T>1s!yxR6TA)YxsE*V9epg<=?+}{oxnU<=;Pl{n
+6<2-_wmq{@6*cRlqj&nZh0C9bUT9Tu-j19}4n>K>tuQhs6vY1U;}lF`UL^x1pS5C-8)F8WDy@L?=+)-
+Ua0#zOU#`LeNzXIPJ?dI7qK{?sX({PpW`n&~N6%#(6@=Sfu}LqQelD5gsNd2kaiv?G?o7-YauOZvd81
+1X#;n`tl)0Z*D=?zr{N?0i)0W#(5w`&BEJuwlmf7JfldHekR4>=u~x6(jBg37aem<3I#fpo6{9+_EkF
+@{ov^SNSvW89ebBUTq|k}7cz64!co5u-J}p4JmzBC0dZrJo?7W|$*jh|POfa(nYNNgMcy~jnw~P1V9j
+p0-OW%ikn0jOx{EPOlI3@=T}d$Ds?W8`J|80|=Zwxu)S$oMS)0UrNy)%HMPCMw>)?(eU^snY+Yx)G$Z
+cC73gS(|L2jgytkI2o3q44&Qn_7TvxTPS(?jOHvi5~VgIP{gM-IK&swF4CZ6pcKArcQvhKu)sW50;90
+bboDtDDGLZHEApv7F4_RLyIfX7`ni6pLa^jrM3qi^4#DzTupDxG4N`jy7EA^9XDNLGA6(RNKlja*isP
+yYZmm19ENi6LPbZpW82k-pf(F=SGUYjKKKxyNdl@Vgag++nTU-n>Z+g@b6Rj`Tq#d&+irCDJ<{Z5Z;g
+n`E)R6oA~W9oTa08$rnQ*I?0M}%)samov(?UN^R;Axig$Eo6FhzfqMcFGpBQH`jAHxDEIYzhdnG;TNO
+)`GJ}^Kwfa)_BOVeZGu3&n+XE;Pp{t?h`s}Md@s_0@AZOi`TY|O5)4ss{l4V{HYfTzeqh6_7v&~dC|I
+?)5_n1IN%q|AdHqDnM_2JttS<+cRbm9^sQJm+*OQ?8{Z0Kf)*Ju!t%OL`RhL<$7_cPG%6cgi#Pr#?w_
+e&?eQu5Z+4PutcvSQq!r?&xz*JCd7u3PY=b^gq9G$crR8^E(7TR^pROVLK{e(->3cSz^QP9k(OXN_dl
+Z*$WeKp$nG7u{qs?{Wi3_<WVjGt6r*BiET}4(ZAP$wCGaxwl0Q&t-PPZa=<H!p*{^p7zEFePINXJmYo
+<Uq%~z>{JvHU9~WFYWhYQTcl0W@ze4c8J>MPKy{<pn@w3Yc3pYbQ%zDxQ0<|FK1Nwj<_fdAmAk@NhrP
+y+x_J&f{vMnQ4KX!aA?Olwj}?TZ2Tc9hURb=?t^yUc3SE?Ao$#~DXa0D(tg<DYosmvl?M-@yO~01~#k
+GMbfPIP9ajM#6>po*j_qdod#Rn+-Xn?6O>{B%qwF7l~<0#^)pdgd2jPGYrLh~$8vCE!4JP50KukO1S&
++B?O2QGp#k$*zpx^z#sX&1(w!h5f!Uav>Ldg>ef^nk$OLOrY6uYLPXHe46Y_uCukW&%D3Nw<C{bQCvz
+hz8TF!dP0$@QiYx66*GDoex#X-)!$FfNX+vJM_CSJo0Rj(UA|tIaWuu302VZdOOEZ5TIK9%#??tVqSL
+2;HpP#-Y$z)Ni+uz@a8tuU&0zty4Aq&Kpb^H#ZKo|{uzJo0B44dzwuny#!Gq!EQ_xRvCHe8T-cfe6(B
+;_MePAvr}2`4eAq+dO8oo4npJI;z76xSJ8$EL(h6)i?T)GKyCTMN2yS9e%v9ekK|jAoKO8_*M!!?(PZ
+YV3((wYw^Vsa`JL)9AzC*{;78$JjDY|AVWD@=M5yHD3V+a{!l-JJ9^WGx}s)XofrT$#*>cKM@ZzzgBl
+M7MMQhrzEP38z;WBuKKVVOO<F&o_?Pj)=&?!q^`UZV$32wmy17zii9yEVp~gqmvfCn$8_(|sF5pxb_5
+-n<Up0=5no-G8G*3#<=Tn)WPa?<^@Cpn39OUJF^T4%hHFxqAm-pQio;5qV?;C@L_;rqC8X>XLyvp|1Y
+xfks-KI<>`24_JKzEcz~EXO=qChPSj(_*LFbrpT}o<x8!(6LIi0-K3hJjbqF=y}Q1s9#C>Jn=`fP>zO
+2a-5OW0=mnzgXgY_gIGzxg+Xf(Kobn1_+<~%RlsqhcQ+MybV_;-bs<*QmL*9y}<&vUrVDg~cx{V21?1
+6PhJDtX+oH6DQDg6nSpbHQ&PaEkieWT<M0y?RH*J;_KR%g4)uKmr^FPH%`l87%dwhrs%az!I7a)VKBc
+=Emn5D{0t`OBZqLsMb7FJkW<+>F)ld;_<t-aWlymy+9o26nHf_Xk|ybMP?C$F=}F9Uw^iEYX2^LB}xo
+|L0sNhlvZ`C^v!n)|MnZ!*n8HS>E?pZM#ia2L@cVjO>xPD?y0@F>}6CA{SjsveTQE@=ocP3MBAil&8v
+E6@ck$Bbauup%Z91U2X@{{QT+j;FC`t#Yav^IZUfZHSF2armq3$%84{Xqo}!w^UrV}qboVBk~=?b@Ta
+fhlXMuxzT4z+SuG#(^(+tXWu`Rm6!F&+8)V2+ho*E%es$r7+cP?4T8I8hTXZ>3l|Omuw~|WBwC>TdFY
+AIDU8PS^mOfBkr+aD0W6s=fp2fzim>gEycX3X?;?^RJ`b5bGtr@dx^j>~vD;|d8kff<?@@egDJ#+9lO
+`Yfqor;atC}x8OCGTK~tIdwnpKkH)x>WHNxTBJ$V?0RdYO7Z+aYG)R_8hyjqshe>Y1O8n!_>McOXaOc
+E6|ORnNyp}>gjApl<E@y=~#2ya+h*di)m0Ab;{G#?#gQyt2wY~n{_j5pl)HLfH@F3m6Jc(crypf@NwN
+5J;@YwIhOy!v3ni7JtcZrs<LUD=9-30I<lb{$W~=*P_*ueZ!f5li*ov4=w762&6h^Ph4)7~9?KzkM<w
+3}^K^m`5BBvG@}u7Wb)1v6qs4k>#8YN!1;80Nm5F&dy0~YSQXv3cxj|2!(}pFGsS80FW2@}vK8)pa%x
+dP8u+33x*3G#NvLQ$b>ugK4h3M1@mjOI#-?ul$x=luAM&i<=Kq}9N3K$Ro@n0FhRgYP*Bi<R8r?zaUy
++IYHN|)DX73%F~Ls>fi#;qQBY~h4X7Gf}V(wwd_rXSW-?wX^tQAibh*BQw6!rsU^u+9mv;c?i;E)g%~
+#}-wPAWa32s(L@R=-ZfW_nJf|CU}3)YJqgkL7s!K$It^0z@IuJ!Pj#YwAqiQuL*Nh&P<y7$3_QrONA(
+Pc;`K?@jR*Vpk$4KkWGGTUTWx%ZI_Mf5{s7lFSscVK43~@t-W>khgv_gIMakK@#sC$!*-bq=f+t@jl1
+Tj;f*oa1Z&tnvn!SGS2p6N)Oh`7wu5w5m<9~(s<I7+E2yY<fjeeX2)&qr64&Q~dfYVGdebn2B|w-%v0
+V<%BU2EtSZ8Gb%+BXJd65Q2NeU_M<JJlfA^iYZl1`}0-oaY3MCv=sTU|2xbHLY*D{I&jT}J<QHZnHl*
+A%CrTuW*&d{6t;l^W0074)ITFc@SR-Mv*CW5I2BbwwkGYO)#YE*(&?nHID&$C-LzmBb^j<`<{5!-}Yx
+4usGLpnEz&mUyBA^i2oZnC%ZFsY%>5iC+C0r-Fx8#9Pw-&FO5hK%%i%0}=m8&}?zNl>-ltnSfe?<POF
+Z0+nk7^pFZ{uHV>L6P?vx=%{xgI}h3UER-OZ1giP6$e!Eb=_Cd0?mNm`s@JmZ3vCp;qnXzT=a>sEGmy
+Him}4e?2C<UBw>)!OFl|e{wjzoVsk*lp5AcTCE3w%GRE<f?wO#6_`$fd9wn7;6Z+5j4$w#TlPJ2m!YS
+1dLu##0C8+AHlZ@`=agy<K%$E=BT$3~9adT=J96AKykjX;*QtCCU0-W-J<G@x+|EV$7c)HapJcA^Xgv
+i4}69Xo}eWBKzR^>8ed)LQvWZPhUaB~JNjYDw~KT+Yt+^&wf#(NvKrAZd4^r&RbZS{J>-oa#?UrV|^}
+PMMq>&2-RoheI9*q=}gEMg2$3jJZGwQ3ZS8>p(8@1~zw%*2qbd!NQM&$!wdiK+W5i45uyw^RSHO9(t;
+Yfm~hTQX>7L;27)jd2NEF<j{kSDfSbb^1eV<(O9ghf*wZ8gP^v>3b;C5+ky;{*>*ySOH=@{v7pK@ub6
+@_*sKjSV?U-UY)ZFGY|M;QuEwB;*rw2<rBPWQ@m8i=O19k2Ip*D)TnTceS7si*tl?zuJpD*H2?lzrS}
+L!sFjrRwf<ozyj_|p<qHQ*!6=eR{-x0!`DO!}LZ7}apuZ*>54T_jcx~!X1iCkohk0t#H|95)r%&wL@+
+WA!S1D#E)Ir}$*Vi7{uzq$&yMGY<2XbTRZr%E<3H?lf?ChQ&;OjXg4@S-a5H0#}JxN<VTC&#u%8p@HI
+KAs&MJ@1vN$@4o=a(>_Hd@ZdIdBA)FM8~{&69a%JA5JLx*CaBwq|pALEId@nCi*AA1Pc<y0TF2n@)6<
+y`ZDr)j@OaNd7QKlI69>$&@W^nhR0fjjM2w5yPaT!t=W4cXw%{z=EipKpkaAR-Kpra^5ElSBIT|00P`
+Z5RiI;~Z7u5x1WtpND}bF5R^JE7p64;yqVc&K5Y!triqHNN<>EKtL#alGhfI%LM{>tF6Gc`}x%ndNIE
+MAUcV*h9OiOu5L8T@(GpU)X?L=itrx0t72*tZf_ya}f*~4<I!t`#yJ|a_2wanys)`sp8&pJX@*Ba}0_
+@BUD!z+C@>FiJV4~lqG*jRHn%^5x{mtJ_f<+1F_aJbF~JPiX`ARHqE1q*jf54N2oSEP)wVvE-wiDv({
+JryzSm;|Uzt1fddZ^29ztUJja^Myr;D2^%TTvHZSbw^Es6WNZlqaxixT1B0pl&jgTn;lj61~cYN9@G=
+uPo}5A=~p&LoIT@vOP)t$*E03tgIZ6BG-i(;ho|O7R^qLi*0%z-qi2v=PS^B=0VwOM!ZODu>oIewd>5
++BA*r#xD~*;o#sqr@WC|1tza>o@Q+kN;_%NEPo)eUii?$m&2uvc;0FzP)OQ<{gUkk)&XROQeWe<fq#^
+;$ZvsFs0qS6zaGJG$}+;1xE3=4ZYvNyetEZ`IN8nDo{8(cW)v8nQ#0v^`$R~(LzDll^MLJt55d}}?3e
+O?S_=n+B~bt(OxG^xmH_S=1B(2U^+md7m6M7wwo--Dc4P|TtSwv125<t?fAn$iY&p9mMd9Io%vlcq@d
+Rrk;l;pv-rfcV~*gR7^<&|+CwdS-DLSMSZYjlpRCy%}D2ypttsD@c^5uye}0u^F~0c!Yq>kOW`~Z0*2
+ezWO&B*#=F8$Q}eX1OP{U73n}NrG<t*LD>&wU!KValAf9>pHdoBqYD^88t=n-YP=uE?e-|>74z6K%kv
+1?VpXAWwo`xfe*jQR0|XQR000O897^_9c&0UHY!Cnd+c^LL9{>OVaA|NaUv_0~WN&gWWNCABY-wUIZD
+DR{W@U49E^v9x8)<XfHuk%I1rl$Dq$@FvGqby+#>r$IXX|NvjO`vfw#!f?B(bIll^`u^rayk)djLrAk
+fX$HrpioA5x~Q{FF-qNv^!#vh?8tKW@RxQ{Tts5b_P4_KrGjJGMg97J@DAxw=eca@ZU>zwl3x(V;5pt
+tiqhL_oB?=ut-Ga!>S9;*@vTp!;_0czql`0n8obi^yKpV=s!PRo}OReOPDu!`t<4GAPuEtIbY^n@~i+
+HSTW};O=Q8ulueVAOO|9TWHG$TlS!#|865szCU;>9Ygi#@5Jpnz;|g3oWH1%h-@|$-7Mv|}F-iGC`m}
+GdSc)9Rvqe}$bMrM7vl*aZz6xoca&DgFS`G%&Tr8N+^s9HUU7Ab|?<2lM?DTLX7R#_OlcqA}z+|om5m
+_@7iR_N&MF6wsgTWvO!ZZy6w$HAd<1kC6To%sFV1UT+9A0ZI{TVMl&^tE>vT(tJz#9PjLw3!kB2C4L$
+854z)XQZU0Vlp;ho>I~!NKW=4{y&d4ui9|mzRg<Cjd0(gfMW=b*|yF+P%)4A-+ELaKZ8M;mPIUyWqpo
+$zf~yj=%fHeY1a^d4F7I@bC{$FJyn<p9{na@OoEr6cvg$PNq|yqwGNJWm=#H6lI<%gtbuoA`df}h6Nw
+86=xaeF+f3K3no+4%5-f(0{H@k5;bTla-*Vq{=Z27Uiy2?_kGwskp#*Bn{YPCMTt5NYG$o`>Hm|74Ae
+W8sI0-+|1Q5jJqdm~Jij<PMUH_c_#ih45)YDWDz3(RAf<>D+Q`inlizq$c;f+s4=CQ-mTFJRBrT9=*p
+c5aQ;{1Jpz*aV_<{(4uLTf_3?f+Ja+$7i?p>HCqLd7@2PR|^iCWD;@m2@}Rst}Pf<a(F4>6yz0I*JqA
+aEs5r(iCj<ohQg;~H5r-#j0|<Rk>_Ip71ll0}$B0JoYjUWR$NAUI=o2^8QH2q*^zh<uHBDGE6QZ^3iF
+cN;{;r<MC)e?HoTA5J9xb<Ouo<O_O1^FU-U0LBolV%PJ$CMa+$-~>=y72t1hzU0g1L@+ufl6{6;Xbze
+Y$qUz0B=4yI*;zSBlZd@NJJPQ!1|#<YD)G0;)b}VC7}82W>>!~Nekg9(h<*HMaQgVsSPrm4q-9Z~hkQ
+Wem$gn!(Hr-3mz)nsu5wEk!O_L};eUtp@b2hbJ$yL%VX%=q*5lPpH7ggQu(@0>FT&^+=i-cd{!%P)Iu
+82qT)!{nycz%{=UH5%vYNxjYOLm`wL1WEy~coI4XF|u9%!SBbG<=h7MeZIL>E9Sn$T%VnWi+QR?FW+k
+`c5aEo#A3+VS>IBr)hcx+cZ=2>2)2XvBUi(Gg^vtrF0LSPVhHVRp;bqI}YUL`!LFd~yvoUT5M0VvOQn
+0aF9~+L@C~joe)v_qx>L$H-Yr!8H-A-n_dzgx;x9B?X(bITMA^tA}<(*;}Mlh7`uJc2Wtr!wvrFZ44$
+w7GP{;p`CEoM<E#Hqm23B8ra5%mk=N#@Nf_qat_faxvK!8UiaG-P>nPqToh1V$W;RV$?`xgl5u8Rl`7
+lOboRI)A6e0HgEYIzuK<W&TTGJ=a;+JYwql=b@=sa}giP-9Ify1mOaT*A@EiP6P6&usoT*5a;KaDmj#
+ZeUh0Fc-VJbJpv2)5a^ujv9tmBl(!5cT0R$mNr(T(6nLl(E>if;+exM>_JdGljFDQB*uVIVBP;hA(0P
+*XpqEM`wEf7-PekOkyDLl#(iB$sJYwD-mjBqfky>NQGNGv+$5vGd&Nncg5$t+M=^%Gz{1thLj_u^mvH
+TL@H;)-KmiYzr~s>2j=!to8tE#1zp~yLB1RMAEPTzM(?8)0TVEIRCLvJ6fcWI$Sj@aTgzhqFkonzz~o
+6J0R3`&PoZJLcqs*aZQJJQ)_RO@-Xko4-W7>B?u8D@}QSSQ~ge=)XYp8L(M>4ZK@OHKxsS}r?#Hz`v$
+`~Q|qV{(=#z3M{~v#%rQ|Oy4KQp2qqh?B&LG)@uPk@!~`zq3vtK$R_j?^CsZM!98rxExEf8O_U3Xf$}
+~oIM1>@X1nP_40K`<ymO!D%(1F)=C17&=_T=dO;l-t&WIzhxHSUId`pk=BIez{;77?ffl@q?mXU{8W&
+!s5yh~syEUM$ib*caSwEPELbIcAuHPgR9+1_YCaftzIIa;VHrmbsds%Jr;VOh6*w(pTWlqy-B2K?T8(
+0<+eBTF6s=2NtSU_>4JWgw?ErOTu&&u5B=&NPtN^1|%G*>y=!p#kj4(72y0#I-=hR+}wgw%ySOT0+81
+b;V)(z5(^?qcnOK`a33%SkfBmG3xp|rhRh|O3S^mA9w`^T)^EHz_$a_bYdOG$nPdq1rAcU^GzS4#7E{
+~Gz{2G82gn4)3M;Q${99ldRuh4Yyn_lVCLCeXJiH^JSs;4FXLx}OC67XYHBiVTB~*Mi5DdO#0>DmE;{
+{ZDi!fz8&qY3p<~+K^27>LJHMISG<|J8^mN9q69d~Tl0(NBB)^*D|7gCJVumU~Z)qhd@qPfWTFY|I!H
+mE};RNxsP>pGdR>l;Qr0xW=^<xV9<OB|GnT2w&}{urv%rbZt$u!qU&mIInK1gpEn&IYO>fxN>KKV6SB
+J5Ao=^uuU<oG)Y8EESV59equ0Xy<MAXM1(%VM`xZAVFTCCsf&A-CX<}=6qG9Qr!95XqC-zMTpJOErEP
+C<H7HixdhMqbre$-Z~H1Vd@apX{h+!cu?^OQsjXP_b=0%Tqrb6!_VINqSljb{mWR`##qS3-4SS6h3#~
++@%cve68B&t|sQ4*mv$oqz(K0WywgxpQYU{<LDC(1Xm&#9?k<$!zHla10*r%ohG7o2qa110t{(ooXmW
++n&8Y1H`4tX1P#K130%)#sOA`106LJNXU9}B)%;&DcRd0ewL4Y94>K1XspR6=T|6G$Z=AdWrLU)pWyJ
+h_9t`uftHY<9c)?<d?DL0Sc1okDI=mECCo)*@AZjM-bJifb`_I4?I!)?X;8WO?60PnF`e&_Quip1Cy9
+L-l^4a&i2A_3cgF7%{<RSSOC3G^fs|okD#%gh$}e4VaGt@)&NAZyXwz(sBqpXn$I-XRs5fK+3VWEOqG
+%svBYlr;<%$xvE-|4BK4px5Ijt<=Tu_tK?mcREKB#THBNs8Fe#fLOli3=W0twCpt22cZwS-`-<&#{ph
+ytgZ77L$nTe6ACkS&<h^)ZJ?_26W73XS>EY9reQZtWscsi_0Dvos$1lb=H~q1N7}ukmeaiL;mc0BESp
+rgj{RNDvw5G!q;K7aeI415r%*2Q7s>!S;`+ueag$&Qz!Ee8^jOF!4CN(W;1E-n+dYdo_`7*X!vIn9ft
+yaCRt>TLnEZYg23YL8Zf0gu52DI5fCNjwRjNkViQ(SOt_cAPsvYBKq-is+0;UryC@=Hf8p6ZP{b^q6)
+j!*@Mk{?h9g(GN2$bQU{`;jcx)YwepC<Og-(eZeO6syB}W)u|rau^bSFOxz!VTosDnD;;`!xua&)Rhe
+!a`e58+Al9eT&9o-IJ*voS?7&okjq3ilAuIMn6hXNsY3)if-F@1_*4&B2W*mI?u5PDk?Ih_-eV@yP|m
+SEhV*@h-EtHyy;Tj)Nf_OlNfoenrx(wEPO@06<aacS)*+bVFk+_{7AuaX*eE~|Qy;VdF*DbSMjok;YR
+?(fRusbQg~;u5a1<$F{dCt~uAi!NUp4vZR0w*9mzI#@_~Q8_%<-j<XjE`)bf&04LpBkGX|PIefo;*Dw
+38OfatWCck2Urpv-OM72_`1b)I2onDp+n(pz48EnWUPS2r{wORJups!)#qpI-cOMV6o!7mIh$37}{7j
+X-sCBz<V!ArY`S9bcEO-%otQ9qG1hz^v+O@`mEuRdelrc_)@c5g2};->UNMh+|U9<w^f7*7A)|Nw#6Q
+EXt^1BMfZNNISW~hxyYn@z%dm_s^^Y#;T7El&=;y|tPpp|ejweKqeNOnD=z^9#!nFU09kdQ2#8xp#`Q
+9N^ohO-!-A@&ktYw_7};UJ{PGLKlMF?^x^xsy1Ssmt^tWwGCWvpU^`?hFzOJ2bf!M0{LUr3~Q~%4j*J
+0&A8_oBar{NliPen+2h^2%%0K@ZbJ9ldyj{*PDWA_|5n;SgVM)p;a2AEFNt!eZn5A$g5(zS+e^lcsQ_
+uuO<d_>{3LmG`)A*)@H|Ft3OoX+mH3t3jQQpVo3Kucdw$?~YM<QN`ESM4Z-!f@IF8gCzhe%i(9rMXht
+h?(S}<7ApB?*j29;{HY>X==2ECG`iO%%&KnE`#A+2)uyFxIgn5i36_*qE22M9E10rs55IChLD$8h7sL
+{c)OFSBf>^!y1(lEYb~taMW4naAMG>$E%bi+u+po;UzqhMrSDSrc(s36@h{De7#!w2O-E^RYvoraA3$
+xWoICpbG7ak{6Xeo4-dhz}*Hfde+Y9-<-;Q_`?(A5aHG`Szg@7$qa0ne0d0Y?|9pIYiR*L|{O+l%;m`
+gE;xhgnHv&@cm-p0F82HlRXB+^_Yt#uJF>CqQ0b?e@7r=v&Q>=X^w;zn|>F=*fGea+mLL$=pxPQ(f3X
+_Oh6Y{yDmo1p_I4OuXxNyhpx*$xT;jBuU6@%$y`SgL*r>?TERK}{5T4B7(O%Z#nb!%uZXsJ33~A{#z>
+_Srg4z;k*UhKE*Tbu;RYQ`4&N`64J8g-h;kx)0|#UZaVpZ}s9`Zb+89(c8!i1t2Ph)&lz!n_lg2<P%>
+ki?vn8cBR{MpGx7oNp|Xj;MI79g?a<Nce90dZv%XzxXs#4(yqq)h24ik^?Zf&C}3l1LR2Fj8_^4d)g)
+2!rM~BCUC`E2Qg7*0;`-X@iz&D^$H7MkxT&qbI_w*!uZ;tIrI|G$pWg<>kK^wm*m@^#8!y&Ctp3vFat
+(GPn>+Aw=b2Rh{9XJXTPUvfWXc9>nvoG-LU_F)xyH^}47Gr@X+z}%VG-L*I&iaT8qV5cRYSdpyPqNP4
+l^23uSdGRpjS>CdE3L&UMb#myH?$}hvK!;AIsz$dCyiU3odS^D>_SgFgxihiL0s>5|wxK+Z=V1ug>#3
+zwUvAT^09G6JVz(7F@Y?-5Tk(iR#?KRTmJkE~wf=G=G{z8`6=6WV*<74@7sUZ$*8CU5#mrV-p_Xy+y~
+@)BJkg`QcDqlC;1b9e;m{p=*^3;20>n4Ii)CIt4XogjCs@;)Cj9C92gmw7^lDYYmbrct%wQ?7P;dk_b
+vKFE{W~or*W$t+5Bj*oDA(*^JXoRP5NPC>?`{3RzQF;|NPFK-DJn`-f$>RiH3nZdB%Y!8l!y^^YRR&s
+*~A4GNzK2s>=W9sI44v|BZVYL+ZZZ3OgosBX}ypO`ga;E$GwXnlR%bQ6nJ5;grn9enKYV>m`5FRp%lC
+U4LS*mN{q1q9-9;^vO)zIpZJ`r305p112=`%u<uXtv+*+MdF4SN{i4O9KQH00008031s8R+l0`L<R={
+0KyXh03HAU0B~t=FJE?LZe(wAFJx(RbZlv2FKuCRYh`kCE^v9BSbJ~WHWL3|pMr4^NJ?bE>0NQfq8p%
+1H?4tSW5kYeKx}MjiMz{0B2|*Iy?4ES_M72DtCw4#3ujj%e>0pnXY!n!zC0y`EV<Y%NNcvI-{DI1JbF
+&v%I2W>Zf{8PHYMMjz5eDDzWzn7xu6GfNx$$W2iSXFFrisVj3j2y$i>0zr68AbYaXa#<eh9qNezcJcw
+mZ9I8PYG?^+|_ZKoKknJ~!fk}>lB{OxLexysF>Ayky)?T7W%$MYXQU48g?iHm@XPEJmu3#v45+X4?fm
+Wg|=q(Dxjrs^wGn$)~d^0cC2*U}v$CEIcVf^tDFRu|;kv+r`t2@YOM!xrS+ZT#b(-)5HQi2i}<pj{#B
+26VcsSVpwdn`#4$YFV}wgZ;KD$sHrDw@ic55^i$xi+o`BOl3g^5XUH>DgY=OrYKlN6WtbjU<W7uv9xA
+bE|=tC&x<_)ql(yAEvzsZ5v*WZa|05I9oV<z+bvUQ3EDJD(qf-S5w9Dm43RoKDHfjep<8S!YQUs*6m6
+BPN$wOS0SImryNx+COnX3Uconv}*xZ93GN<jvxxwQ=WsNc5p=&sUR{TG#y!IQQ>iRm0HXB-1n+;i#&o
+NkrsYWpq-@?ZA>f`14hxO*-hpVgA$2A}nv-0tZB`QvmoAOn1lf!rV^5)@X`uj~hUb=~Yzd4yKo}_UaM
+Gzfi!}X@(a44-3nJyv%AHF3*f^M1%ZKx<%BC~-ZQUW1}5a|f;12VTtkax7wEb1-D&u6#jx%ehNiT#;7
+W;WhBI??`A#dKR4w8E`@$1tyva%_eiV!A|;JJKV04(?~7OxD*)o$r)v8=a&eL7Mhu(##|d4^}8Dsx?{
+N)2hWlOyu1cRv6D2lLddT_FNN(gohB~%n>o4euO<X7?q$^-cj2J7v;DC`u(?)IbJT~1*vF#S5oqrk;8
+&KLfDf-)`$Ex=8q>J=%z>VW`KP*gMBt+_dOuSkne|x<qYI_;t>3120N7L&7ZRyf}u1_HNbk&2T3)>0I
+xoTizx)6tq-wTFavYz0s24ZV~p$&5Q%2hHp6&;s)x0oJ(^yuhN!~ND#Q@&MUir0<l_~B?e1VJ?qb`DV
+)3ghHj4e$a%FFlUpsaPus09LhZMSD1>bUD;l;>jrGS+0rMr`Rknu<1JsdIp)E)xx(<QWpzFwTZz8zo~
+REjB;XB}+prJmyK36#SXb9oSkKCYC4<c(YLRmcZH?y2GwE~^E3p=0vG@=Tu=(I4{}VMi&a5<&rB%1mu
+lawr)Cq-=ubv25bovH4)zYlxwe9}C2c9j%sdU!T`aW!=q6uWjIR+z9&0CLI}juRDR@c_a~2y=^tw=EI
+Ak$0fC?H{G;6(x;RexQq)(0baTeLvbwyD&hW6l>}waK%>lx38j3%)hTAJ*rlJN2#Gg<t2wxO5)PUti8
+J1k#Eoq~!rc{PNpY5&?pec3)CY%w%M&QEnXRH3mdDIiz|7Tp`-9)l>^GG5bjFNMX}IO!VJ57@t{U&M3
+iInJb<mYTLa2LLR{{T~1jCDdB21TkqZIfoo7=>Ca6sZOZ$|~)(NE_;pI=>$n<8j(Y^M_%9Qa28zwzEp
+yehbbT^}`@Z42#}monjED|_089uAE4Lg)6+h9tuBntqXx`|g>G-ZM1ON4dXpY-Zh-VilvHF7(4yzxY}
+VT*EQ+HnbWQ(;&pFrNv>@eTCK8NdX0k(`sTSPZWiYZcjBeKm(mG__eDT*5ZBt4tF+31I$?qnB_x)(Dk
+NIF%-0B=<+Eg?nEv~`(^h@f#S3HFAj-gr+(Ai!&_+d^I_O0PShIX)rAx|))e~$sN9yN_U&YH7CK2EyS
+;91MhNH~W>&K&X+kPa$oxjX#nIsesq+!npehU`#U3U=0Cn2?r6irhd((`<V==Ma5HQcn$9kXIFU{j2B
+n+$jaJMp#K3b}ScMhGy`$-M(E_3W#k`Ay=w|;~p`{sU%>23FSLEud|5l@0353iwD?4@X^WIwIm{qX7i
+)duJO)xWPGs3t`VN?A2tjUpC?79cqeFuw40qh#XxN^D12(b{P89F}V-*l5x@4`j!N6t4v@G7W)WGMuw
+;_=a5U{ZB;hGHwAkIjuc|1&mMKj09s-Cz<O-7uaETQ1DKl!$fAs%)huv3@1gK@s*Tc+osQThP;Lm5#$
+~yZPejda9l?RdSZI_=X!5QR{+>!!5TwW_Qy~2y{a|S=X?^_kPZwGjG`?L+n&(B9i8S!S193DB<Bom@D
+{)e<9Yn2hqeNT(!$`t3fmQWtfYqGB_B*ab1I(T4-TeY+9o#{1#2hV)Y6?;Ve)93(so;8<X|@MV!GF!4
+aTVG|4>T<1QY-O00;maO7>Pj*<B)aB>(_<n*abG0001RX>c!Jc4cm4Z*nhWX>)XJX<{#JWprU=VRT_G
+aCz-LYj@kmvETVCP^mru9g>z9C%sjx+bTAl=){(NB;{2_g&|@kp#lL0041x5|NEVpePb6OrR1LW_FSD
+dmVn*a+1c57?aX337(X2c^D@nftG!^=T#o+>pA5DK+rf)+d0%B$*G&+;7zWdw-Dz-o&4PFL&2?D>C*@
+^xmsBixRj!IOX|l4IK&KPNg4c&HW=AKpN%Nrzk|GUWygfQSKK$aF)3?Vb_z>C+wzjqo7t5S2SkX}Dpu
+7wk0RM(H34lw2%d(PVEtC08a>eT4-RxaG84ONV%Vk+Lb&%wFurN9-5_lNxPIgAY?qnDLGsXXW`fNJcB
+~+%9>2QLB4=$^65ybK3s##Smj)QE0AcIwr0X0~hXAP^8ydDh13w%1Sc{jF5vRw99u(}51Vtf-{W;v5R
+{!y2O{5>zPu7Jey&x#EO9MnXDd70Hso?Xm7%-Is@F#_anSyjWYaV*--%f&KjWRH`k0+5GqM?p=$#m)V
+a)uW(c9~$~y^jaj<4FHnevI1tdtXLynuNplU=vgK6Cce0jZ`l1PxMEFA&&0$h0wdWT-`DeNSj7>p&GY
+9w@wc<%lf$=1@$qahz*(~@*q76vK>OG9EQ;eISpeOKK!|ys)U{gpH(6an+gVkWRn(@+aBmR64=msT5b
+>u~R<TrbKvo9}-WylA4fsV_T;|!lSqr&o*kaiPO$kFJX#jk9R{=X1oR+aXt$|%(F>nja1>{wdPkbYPQ
+&enTUKQCtS^6!f;5sC}DQ=4LuFzvj$``A}1*^Qn92U1po~7$4r-3H<iXquD-j$$k2g}t3OeZ*acgS}o
+(zQ%iz}j&PTMl;1esC7bVZ%`nzWe&i`0(h}+jw^L;_b`Bqc5$8?~Z4$X2-{~my$cea~x(?aKRI-YFI_
+w?<fGE*BE;RxR>gI0~y8+Nl=A^YQ-*Dg<K#AGzq>cm+W$t=l8)~2J+zo*5^7Yu2>4qVNF3M1Z6R2$gs
+hu&p*TI*Ib|g6b4}K@2(l_&~Ee*1&}X*K>YgfXhsbVzmIq0DZHr|?NdNL3V$pD{`2FHzl1}(HT=`pBf
+$34=ezN%!`bVXC(tZX6dwyFLLwi*Ho||6NAL2aL17q<27&z(o~#xi4(_qlOIFXTjCjM-@N0H|S5|3_E
+x#%kY`g>+hkqQbKqOcCw=oGr4}{m*oE0^LX$;~|cc1^(^AHO*){XupvxAl|a1&-A6R6)y*tL0?q~mXn
+U*q3zFX}R94XZss-c{vomNG))m`k%-(d*5@@z=m^L@)zLN3Rwh?V(zD(HPG^`wv@_HwoxA_&;9={g>=
+uteVqz!$lmUSoN>uKiIsH?d1}Q=6apF`m6Wc;<38SK7hh5l3cBt$r<ZL@_=@Eqdh&};3J#9E)XBRO|l
+^N&!?aNKhOQ2;yD7G-6jpwi{wC(sHWpDi0CJ*SuMv7CnC_I1BAkUhUTVX7Ms;ucsRXAZB$$?U5naqAi
+NkbB*8Y?-rf0p51bt^nKH2S4T($sgcim@IiIi4QY?!rFg>yYt&MAKG){uUVxF&3hEEspp56j7ISYid0
+j5e`-l2^GMi%}84FO7omJt|(L-em+W(~Z@CyGCUaZnrhKHr%P;?F)eHk!HZJ^?}+dtwYmG0eOfpMt;O
+p_iXy+FD4fCtNoi+g!Kq;js1R&p)+W--Bb2&5fNieg&3MDBJ2;8FTz3FyTPUgV(Qh%bGRO(0n#oEn!J
+mWY|~!_u6jhc&~J*|Gg%>|Gl1q|Gl0tOn>(M>G1*hRkp=gg<(i8+K=_q{eAdPv=yEGee3*_;npu9{1(
+D*;Sd_3r<JnHKzfx^@?vt>0FihiT!idWIUD<A=<bAjiZQ@%TvbJ2P>x=)-08LJ>80t})obeOrKs%of_
+)T0w@;B@z{wAXy8CvJ+?H7yBq=!=G~EEb&Kjqf<mlYp<0b=Jzk5jFE!w2fCGEOP9MNPw0Cfqwv!UlEK
+X@lNwTYQzH4DB)CyYC7N+Sl)5FL}dthr9B1ROz>HaLuORl=b$Q;D}`xUTVi1lDXe&}gl7UM1H^zPey_
+Bbh7WF0ytyUxIj;Hzf10okA*QOIFbOlw2YT-x^&)a&oahfxk}bn1?c=8+Koh0uk3RRvZ_IKgHD$@AoX
+B2K3M^5YC<>^8{5+tChnSuadlG1A2;m(G5Ny$dM^xB0TCs%wqzQeNjgSj<_JQO>}k+Z2Qg8*GF%^I|2
+?qDhoEW5t@U*%nAb&9Cwl|k!nbXA;)G}f+ca0Gf96!jkfNH@5K?{T=b9HEF;bk=g2|Ga1~pWx8NraI8
+$9_6|58p_OK3`>K+vnDH_;3VmASYB2O-ps=-JBpfAIC0uPfoF2w;7K9{@4@ODYJBKr8knVd}`=k<ioB
+O(Apt1XX6O;UETx{5%b(R>4F7o@NxFu^CN(1@-bNE)uJKyvrjBDuRElDnHDsl}H-a{6nLoNkEZbYmn9
+Au5pk^w%Q!>4r#t`e-Dln=QA1^1FT81KGoEby&b=+Z};aQ!lu|2dE{NU<n4-pqT)yBbmCVK6RL=d-~G
+{Fp^<$iRu4JMw)KONYg$>+HRw17`Ot>jU>l*FQRSPvE7NPM|uqW@JXJ7gIEVYt&$vlKNYyFrSX-sB69
+E=qWa!-RJYUaZ0DQ?zQj|R;CI>z=!UwZq1qFCyW&!vSQOoiRXZpRmh~Q=w9xl0)5afq51rsPzzG%2xW
+W;d235+c$bJI)O1)k4$#HVk@ou~;<FVc)CysEf2Q$Vt)Uc+(evi29gr%c03f7e4)hRH#U>WYyP*8-R?
+F9QhjNJvzaH0*&ron#CUhaZrxL8BUtXa`Sd=Z9VDXYJx#$QwG-4x&bx5dhRtnx#-;>QD7!B4*sQ`Cje
+V3F`x?-@!8&V8DN?pSc0+>)yu%&$xEBk>q;XM|@tbS8*05PpZgqDKJijb;GM8mya(s=Q%EAmT{E*tvl
+1a9370+$yKD$EGav+Jdl){D~esx*paW#PS399ug>m!_mO`Z(vGE%J-SkhYl^%6c1l2FpOD(N0qhJU`o
+TmEOYP|>qf2$$wj_3q~9R8+xT;8zlDV{eWyD-)>`Fh5jKE0G)s#6pkA^$2(7u;i>B7-IW1W)h=nxkhN
+0MvCgq4hei~!8nflsH%{EgXoT-Gfty)=B(d_`%!0tJv1F6$%5>Tkm`N~wQ99BKKC}F+9O)qMUQli5{9
+t1D|w*xMS#{s}~(=6+~XV32L?j}o$%uUMb>RHNepDo$4#{Z0WKuA2>&eGjK4B~^+)8i>AKiJei6He&l
+PSBvJq9G`>WuDAgv^Cxu1zYjfaF5=TRZhR40@bmH!N&prZHj;qBys;<kTgw2o$!~DbO5lgLO^;u9|r?
+m!k33H4o+ugz}Jbpxshi(j5!=g4mk0`k)cc7&TOV4g>>|Ga%#LX!^L(Sw(r1ZZ2+t%R=a7KUWZ=SMSM
+Gg-@XXvx_GM{opnNQM7`5*-o2igBs8(X@Z9Y6?9J@x^h7daWW?9;{WnL4FW$a1LFh2M9Y^m7;3JSXhb
+Jfe6u7*=;Uj$b>hSgK<lt2+G!~xy{b2mJWc<&a@gFDWpXdk}rY%tV0f;{pvA_o-X^f4K(<z$+AMcaju
+Y(!Ke9z<VPBTot09j6F^SGTzImp9kE+Y;vEpQ~Ws}+nUghvv{S7VrMvgD`X3l;y!?Ea=edIcNuqJ$9%
+Fp6_&X`;NYR-nyG)Ca{l$(Pqjv0AVS<TvyRC!qmnew|?E2j+=jMuQL<sZezR=2U=^3di9j2oBOT!}%t
+7#ty?6VCp6Gs%3OrqQdi2f(r&K!>oY`>-|72;G|w%L@>&T-e_}D#jt!$C9$QX3j<`FNjMx@68cF!22(
+Y764*<vGf-Z$t7LvJ4UvfRmtJ*De#)tdHe5@Lg;XqONzKG!tK=kQPPOup&|koXl6gr{vTDk4N&zyK4k
+rQHJoAKG0^lk%Nzr7W-nlhHn9{1~XbYH6Np-ctT&g;V=(IoulE%SPu$r!)j;K5SO6G}~%#t(N5`TwjK
+Mk%ju%7t4ah}~UvDx^*sw*h3IS=Sd0E=X~gr$CpES|vT0P$dSm#uipkZ7csgdWnmONt9keERm~+aN9H
+G(mo-!iS*@6(pqyp<$pfS>+9?)`5;3##xayaU9hwzZ?+>_A$~n3dD59Ujiuq%RLF<`0a;cjL?qhogr8
+SQ2{##VYC9nmm+(?pMz=3?jh3`4?~2xYeAu@$*JP5WFO}Fs)nU8JX4(1Bo<Lq(AFRAHzG-@CgEWOEOl
+2Nfn~)!qxXoZ-9jwPzMz0PYhou61jLT^>;wWy8euz)GWnx&j_Z39>XB&Qf+DHY4@DfOh{i*=0r;P><Z
+7i5hMI-E@3E)B1m;4VxkuaQD7&l>x!J)OE2d;K{#>xE;wmAyFn(-?z4_}2b&NpHp-=u}VTwBHVGe>i5
+Un+}ElA!v1~K6XO(QOjjsCT#zl)j)rWRmiD-&AE@;+>c7_m?moNgd^fRJ2|N4BzPs(YIW0J^<A8lK(_
+j56f{Fj;6X`ZlV3=Tbw4b=HtGk_NZ6Ys<=!HeGXU_cf8QT6?iT&(O8_y{?!N!}uczPi}=$vZ#5(I2=k
+xqdiyCFSt@m-=>_9rZKU^daMmA-gI9q%hNj_L+nX=K%To8*zn+AoP!-2V`gFYL7>#;>+F&*Lt7}w^GJ
+2>GW25OO9bTh%#Ub(i~XTE6O7OGV7wsg4Ue8%7l&HBp;pd2EcQRMHxJ(*2MxD{nX^l_g(`oiGE2qd!8
+XUx(m~6rTmmQGM`Wp+FGm3i9_x`YNo<XopT-U#wU=DlCOrN;!i>kC!%GG7!DhU<a$XmN2+K2|&PSZg%
+7;DIb1`O|)s~`Yttkv_9A@ezCbJ9keYGhE7L$qQrlQu67VS8KiQ@vcc-DvMW5?6-K#xZjhhBZMJzDFY
+q*iVY-z{}OIqrNF$+WRn?s5qT@+yD{uxAlT;IPxtX=Ngtd0%8F_voXxX|vRAFEeth?Dm(-$viJ>W|}0
+ryJ;glVxrtMx2C$NuVAiDVS}*2{I+L@$pfIyLOJ~SR=&|2YCHJuniVu1ARd(*@X)Hx1;9|GaEFK*n1-
+RFPaS%UOiar7;AcdDh<nuUoUU6vZ3c6DZwt(LteJS6XLA+IJ-ZW>CyJmx#6)_YCE=diIT)Cs7xM8ruu
+iMj8T5?ju+ZO=dI`o>6pp|_CSt051m67I0j110!b&KY+Q!>eQk+C0a)3nf(?l={fp&-1=@NRbngn#fD
+)qRZ1YX>SCjVg_z-OO-E`!@l6n0RmN}1kc0fAMZV4T~I06zm#a+_p%a*^wq5&*sC%j6zYJR^GxooyLG
+t}Wa()D5Oi{~~35?Tmr#b30MMf_@RDY&2Gl6hE&c=fw=%Y~luS2g4Sv0O}@N#^Pwur)IyS;u%W}$pV^
+Ef!SEp-aSIpN{@<Ut&Q*_B(DL@a?e1DK7<&$&V}mM0wN5BX1c`k+BG7KE$Qgy`f;nmmDMdnRY?xz0eW
+N=TEWJAEzyK_u+D74M5i<LcY84WSucuvjC@5M%Xv1}MeKeMdXs;YSrG{l=E~lFJY>Q_pIT6j_uJVYUI
+F!3SHinm{1@${kuP8u75V!6h4(|D|KfqJHIP&;{kqoBbS^>~n7xi2YRulrZi`3qP}{W<(IqYmO3Wt}0
+mY|JZ|;)ns<tJ-i7AgwdklpF#$93MF&!Mwx!)7G_q4G%EW;J~f`Q$Um6Q=dLDu&eZxz9=_j~B7$o~9P
+`~7=7a(w?DhrcdU9pi*X_Y`2v%M!g7@PR8D^Zk1g7trk-x}o1t*V$FU@C|_$uO<rA3^-{d--<rQgi65
+aeWWubhuB2CH0Sm;o{f?kPD?z21_3$0wxia_HKdV~h8tio4ywI-vCN5))|-Mu2@{)`>!4qvdyE!>ftE
+L$%XW>mwCms_1nF^TFg?gML&Tvyk*%GiL=TaYWc<LK`7}k$iP_PkB`lF0BZb9B$3G%4uwRi0+QNiVG;
+xB|Xo5{5kG$bz5?p?EbKV!DAdoOo1+^R8txX8d>D|!8PH<9dyTFPFZf~Fx7y@e(s**g9f~=-CyG<VAA
+)6D5B7dYx#jsFQs59Ila+WnIo}s~yg66`C9|aNW^AXQZ9}ZoXb$gg~;vTw5bNuXff-RSkkgG~!8lHn~
+sr&VZf_H8+WaJCywdedVm^J?Lz<HUgER681o)sw0(pO~_$-?*V4vvowkG^aTzvL(AW?)-}e{AKYj$m}
+bePo=?I98b=u#<(MU8i2>(O!4IX@G~uY<{D?C85kvkx+E0%iN(d20|Q&6;sog1U##vTghX83WsMqK0{
+Id2y%lgD1gFIXFL4a3c=~w!z18O&YQ=-xK&FphFksRPv&BQ{Aiz0bBeq={Qk|1SIk!oo7eJea>O&WfK
++s+#$Q@|W-eMg<7LA&>!2*iCfEU(UJ>(RACH3Tps9y!GH@u3)CUmIPe;B-U0Qlc^4m~EdQJbvl(6gqN
+dzl@#u0o<k@UM9Qh0I2<vH+ZTP9YJkD~t46R-mBmUb1VI{PwP$5ymo{#xDIp0)7GOiUf}$kYH>J&Bb|
+9N9>YZJ$oLOe(_BqS-?i&0Y$V!oEQ`$>l?Pdvv*@8;)QG+59`nJw@YBTNwrTBOI+B<<VNU^?siiOO`z
+WSl7|)c409mGr^Q{x=~0ct*sjd#{m^YJM(P!eCS<zOvvq6l%9CS=IiocbH?Nr!(JP--g`z?yP4Fw*v~
+lHyzxb{UXb$7F73!(hABY{7&a-I3A&&h06wQPC^D}3X`vB1Ey@7R9<+zQmFa6>MJ#!eV*219*mm&!_u
+mKgH6}1CD~0KdtVp0uk+wTb!Y&gSM^i~$BQy$x0^oc;vP?di3(EsF?RyJ`dpuuQ+);FKFYlXauP}iyB
+$&IT0vXAd*umBig2t3C#M@$E{OsHY#ZPrY*}}O#i7GjQCp>wMf-9nFi}9^=ee1R+7-85&AK&!~uJ!(F
+i6LxKoS$MzOudhg9}32J(3x|D$jIBV^hsBElujD#@?;_g-%Sp?80vGK>2Ad#fa@Kzt@au!>n!x&#Ll+
+LUOg|UM%G$zE>T7loB(G!=Y_UW<ai<@|6GR~Sx!;gM&78`I@9=pWB;n5W%8+KRaHRLXUX7?r9H0n(H1
+2c`WV4~f`)(SW$LwtC0ol~xAh%fb0Od&&fGkHQg30-nH48B7`%V8Ap18ZhA^e-!J`GyxF>x>oFyeP;n
+avCzA{Sw)m>oRoCLWCf?!qivzS$Z^_KIpVq?l?nkRVV*4!H>d8mfzHn_{+`hE#oY`n-m02FE(WfL|Du
+0h1bDB{e<O70DH^pR>rD4H59vE1`P6(9Z}=4NL@GE4L!=R$^nLTO4VrtX%HrP<SAev>RR7Bp}=c3bcG
+gYj2N{+5*~-W)z-Kv{k(ovc-rcO1arv?z`(Loj`iyUk1!j6R=O@fg}l&d>yY?raT&p?5=)rm@h{l-e!
+!h55)$N%QAnI5%?OkIY{PMF1VE*Ob<L3L@fZK*c0f<tB%%yX95uo-%K-j7PwjXFz_P&k2$n1hkWw&sy
+a)=fNlY7MWyS;2WJcE}l?sITgAgx#=w8DM+pg?N>uEQ9!(v@GI7gcF#jLl$Di-1B#Tq)<qWL#DTVjFC
+KqSG_x|@c>t~h&ogzD(*fS_0C;G<0}ekYQP76#!NtJFOV2cACgz`?)B*kPzbR*#OM;k69pZQ*uL|X3P
+AI~#PUlifqrl_M?DXK}!RY~2j~pGm!AhZUd5>v-6TGK29DMiHZ1y_#wo_L)@s_V=Umm>p!QWIq44un4
+opKWT_tf;AtYQ+OB<wqKL0{Ea7D|0pKf10`l~|J3MYnQ@2P0U{;I2xRs3Gkd7lI=lOn{TkuR#<PY0h}
+<BCO<?EBV$fyAw4F`bE(~nnrI9PG5XAJ8oZ9^!FdrPof_u@ZaIn-^+4cq@BM*`1iA&@gEPye>;!FFY#
+o2{!~63{^j=}io?mFfJEA%7n}*J50X0%&-J$0@Z_5}Zw`)s=ooPF^X_Q6^ZXAV<y_l@k~Q7@?U%Eo+3
+~^YTLcrP`~ue?dQuN@TbS1Yb65vQFR}3t@z=8-PE_$H{)D(mz#xkZlQxvecdf^@sI`N~Aun$VN8-Iu^
+oK_;XWz>~B7&`=o;fcR3<MPWQVa6(g3z;BL;f!2H!0tUGQnUe&cF;)YOabiYd@q^+?z)lUXc0a?A;8I
+K6>$kMw{Pbj3seWsREB<J%;-0VwL5o{?j*_7?R!UW+F&Y(-zT>OL-Ap46c7SC~=)r9kb##1EZSMm7K=
+O4@aj5-^bq`ygsCrZY^@#)Waq0+KD4rbaT}ugP6NzWO6_U=eS_~T@0>jZIR9{skr$Kx;Puz*GX_^9M^
+dX1dM5wW7#SQV|h6-_q{?}@BYV^go#o`Uqx3eEcwlAy|%@L-^=vkPxv2lHSn%*7Fpqwwe?s|f}Tc-9O
+I;6u>d0LwMK#Ol+&4vXl*qTH9hODGV8)fk+4-6D%qli;C?Tja(Yo;(u8ke1Zj~ETts;#DCS7YRP+l>A
+gF^bGnx+|>he5CZi3M~XCtDgC^qx-$5R#&1NNUH;N3@AlK~-WSz26_Sh|Xr%YZw6f!AQ9%sn`^7W!xJ
+#C+0_y0s;u-*ybISi!2KDJ$7eDPy<8#}?UqE}^=GL&fhAIpcQzj!=u3B-xuO!z9?q$#RuH-p%CD3$4}
+(YRH;U@Mi#aY(WjEdl!mLrmr#VI)*ta8@9K0GX`nNNP2WY$qF!c!J?&{IX!3)Wq8JuxF1sJfWxg_aYn
+#H&R)Pq+{Olgw!1Mt*0vj&e2VJ8+H~5GbWNyU&F2)EM%fM?IaNReVkyv$VhDePukMnf3kuJ|D5-WTxq
+>z9S>`UeCY7K3vIOUs%>taQary<KLd6h@)Ch>U01H=Ku82un+}=brF84M3n(N!wZ;UIPrO_c>Y%GJP$
+S#@&T%%K*SHHx7p?-;fiLST-z;+Xe7)F<AKa$PdzR9B%Ne*qRlDhaWA#QgxtxV{qCSx?Q?AMMqmRZ`-
+hTF!3n{zQp8!i4Nh%QJJY^6&eI)@^ASH4A(8*g#_VH<S5*3JMSYu((^Mzk(h)tvFbA6_hM->*&PSBp$
+-W7>B?xzX>VG$?aprW$Wg@g)^UDzg(aLA9*ptgr4hnRIjtjV)rR1kSJPdmDTmT9%s#;PCgh1kZ2Kc)g
+)7x$yTC_-X5YQ?_{ZVSdwX8sHD`Cr`ehBMP!6Z;ZrOs)M0N(L;{^6;u;HIyT8~HYs6}r!9{_%D$yA(%
+e1L`(UJZ)X3UCYsId$8#)j0tjUvAab>4EKY*0myhbX?>C{6cRLtH5&p-QPhls~o3fLaTWj$-K<Q@E$k
+vk0(T>R3ax}&lIZPM->La{&?9@mnmm+lJHlp`R{YmAlcpsM^KBU=q>%Cp{aQ)kE&_IH+d&3m)?cg(7f
+JM=vIN=E!BOP*hgGVYiS(Dre}Lx=k9sgqsG9{6P;!O`8LDCnL9FGG58vER-<5MBF)zIAsh!R;2+-O{o
+J#l4cCQ_?ueN4%|}AC=!>UIU@&tQ_pt1=(6{(V$Matd(sIlwnmdk}(s0OSZqKSHVRhIs#J9%;1nKq``
+W!R`6B>KK_JKFrp3y63oBo5a(9zjrF~+Et#8&<u-*#O;zXfTWguT^|OUO41tuFG0@RIUyesO1nv(qM*
+Bt?>w*ezIZn$@<^1B?k^kQ2RQ$hfN)e-g!>vBD$T*+$M!L@On{!7H;ZIu_{kEpeIzvWF6nVbx!?2_Ld
+}D*9rA&YuMOfFeGDgAAA3F`b4eW^Y%rP1K6SBy@nXSMTu8DZdRPZCu(dwjZH+6f*)J*ZfF*i|sYFGBi
+j2>NOP*sHwyxZ)-*|+#39R`tt%PXn6EQOx>8V@W=*?V*eubZpAR@7M1;eng4Yui%8ze=^D6oB_O95-2
+@`{o>;8DJg#k0?WN*fpd)x@!;ha0}_Ib;Ij<5BK>jC2Irei)GJ@3QIIrKq0I1;I28_>8x@W@j-ov$eg
+~q*G&7X#0pVuM9rx~!|sc+yrk@<phqyYDQR$+rkcMzr6ZB5sYm>yx3xI&W5sRT$~4pLzQAlhUOtV%Rt
+(kJ*HiHVZo1JP^Et%Fb7gnDjw5NZ`tqKFy<n>GOTR%u8Rx(JQq2#I4m|HIlPXzog!h623Uwj)T7H*oj
+FDk5SS(~Zqyg-KYfJ`_Z5#abjyN4htPD&X40tmW1vLRodH}-V6{HtTCYZCjG0Uzcl;RdZbWGm(h!4Yc
+6rYy%t;S~il&H4JeryRxL6UvrE69;}1}L718@eX^ku8*Q4k_PuxMDul!eg$X+@C4`aD_n#{i-V%vnqg
+5<W;<W1tUH=w{L&VsGAl&2zDzMI@#gm8f&H+16$?y=F;ky-2s_?g!_@U0i-HIgx?e74w|(YTk{n?*H4
+q0rFffhg89R0mybkUfidGwSc1Vdmd3hwhb+{`tNLRWng;4y-x2Re^37|$_Rd}?3NnM!2uxUYoN(^)z3
+_Y@e(-^wK+10MA3Ut^nfHijxc8*qL#>ASj2`ruUOzvI{GI%IOGjj8JHW4o&sP;DOn^&}=Og+IL)OT1K
+p@v5EAX;qu>9ssAl(5BZ`HV9ba@&75{x?h>)|w#2%fmrlUg6ra5~uPzk5Ao8Gx<gY~?06^wEwxszqd-
+wKjrnVBs+cN~h}nfhLw&qlVYd@mB67qne7HC>R>?VMwfXp*!#8Bx=u__~ITT1NI?0{@zMYllG~JYTL|
+mrtv^i>oK!2SXA6`)4uw~pD>_Oom9?%g`{}N+1@#J8)DYJH*v!^p|u|=bV~YcJ+HpoXT$_$IML3p^j|
+k(yQ*SlUVSgGH(wtsG?2AE^k<TgzxLMmiHba<Boh(;jf(p$x{2#p<a&Au<d4_U{Rvh9oJe2K)KyBGGP
+bW$(~4d5YF6$Cw${X`MUlPT<!Idmpw5K%)G7dJ_3-?ASnC9>gLPlHVw2n)r=qY`PW33!D<~+y*d*++q
+t}T)olo3VQf;3Om>Qrpm!z&i+S_R@>Px9wH#jKTIb@H_9or~pOy`Q_i?q#~CS|G3HWf)}#x!pdRd+P4
+ONpuV*HhBI&z}cY=+#q=OQQkWUV(Pgib{3_C5xM&6})_a8$z9LoL77q&kBlG1Ab>WTB6_F@n>AU7$0~
+yjVZch3h_S+!&a3v^|x*dr?GUP5XZc^)8p|Bp(s*Dah!@z`dFz#o;0c`tT7QNb~?6FhK9D>EkS%1H~#
+O}!o*6sYP1oMI_1r|OJ0kHXFrEVhLGs<(ItWvWFbzLPxOxDN&nWDC>HADKK66ZhL^=P2k+kTul%@04W
+iUuKi8X9fALAZZAI_hkht18!#(xgBNMvLWY?c1(r;7i>z>x#D{FBOrHS-JS1D2ptQsYRjI#L$fTOG7<
+`jM35l1luO@43b@t~++!+<sB54zH>T3J^QSQYzB$o@zdf%#}?h^Fk&4<bT2XEjz>G!<IU;$P=xe(9IB
+BkZ{6xc|vJdOTQEc&PZSkb~Q-xHTH}di<5hT4biL?X*J7sJ@<>cSdqh8RFPdF%o`#2?;=nNs^{f^_Zg
+u71{_pt6s>X??=LhBnZ48Y(1&B(2S)Az2J-6H9?ZiVktHr7<(r&iVsP_DDpex{fQ>)vt_J-0PY6M6aG
+n<@=>L*=(?rmr^dLG!m^t9mz*q{iSH%XYHFnm>!FH;eR`^1YzLbZj?kwF@mk3n<$T$CpwszkrPw17el
+wsyA)nwEK7&Tj6ICBf23nzVv>N(XG3Bj2yAwab+Y!lB#$0jZN2W8kUk+(mJr<TcA3u^`s~H7{Man+#W
+cF^D5?%MQ5A)}uVu@>z(Ff|F`v!E?bgJ<CxNYG~i*MEFeWI^NRu7Fh(6kFktC~-MF_WsDi(e+b2&1%p
+T8YtQ0nyhNBkwVQ?AESKSG}rTx3MoV-0U(nuWZNC^*#E`AHN`0el3Acg8FQ%_Eqkk<!@XL@Vhr!SDTZ
+|(o^ncSGoPp`gS#;MS%ugJ`shp4`62G_wuuL^l32^OXi2d7)x2&u5|MhR$+#W$GKg5+|8fIj-$4L6mY
+w0qr?e3_-nZo2=OH^&-MELtLrzw%DMwzRwQl!+M7JlPee@tf9SRw+YTinM(wOjqf(o6wOB@}QEmy=<*
+H(FQqQxD*mVTr77w5Hr+wiW+-j81weN<E{8&>RoB6c@<4XmybgQQ#&&K}Ic>8cyyZuo&iL5`fpEz(Wh
+<&jlQ^I#<LRb#8dmNJFcgel;%|iSklO2=+okW>XI*wvJr>?v^Ka{l&Lg|HnDHTH0#@oczpLpvT@7I~p
+r{Mk^n0~rR>{d-;o5m9`k-+4Oz=h+$Heu`vlNh*1#5-9Bf59*G#=qh==4L-bn?ZLg0n~p<h<O=kAub6
+FqoU+DrD`8Te<Ie*hN0HbSjGt2dQsm!LWwo~7m%zq;PFRUD`r4ZT{|vwbp8iWO9KQH00008031s8R-L
+`ofUpYy07NPP03ZMW0B~t=FJE?LZe(wAFJx(RbZlv2FLGsbZ*_8GWpgfYd97M|kK4Er|KFd2jd8Gi^{
+Ts<>$NbtZ7*q31W1!ZHYv~=hC*Ak&8#d5qP)A#;l6ukh7XZ?c)fQuf~+mh3}=S(_>t6@U3`1N)<r7w?
+VKIz&BdSb$!I(pvzJAAtmJlAv*_iNeRp~F`~v>_6Z^N!`H|i5FS3k*?5$jjT#1y`1*><0{dBB%Mb2)D
+O?}TR!Cn`KJms~7XYfT-jKh3+UCGs<F5uU;5@Ij%8fD!G!QQ@k`Rd)xtGIrs8P8Mp^8LGyAKtw9^zr?
+N8+-_KqfJ%pS(0oH^`R0;!sNazsv6`=FhwMptVP8$H5!?Ll~iI~+h4M<-?C!61<UQvLfLQS?e<X1%>G
+nIH&P!<;eLFTrT#Y3D#ccle@Inla`ozAElM=q45Lg-vgYfZNRzTEN>SCv8QY3Fp@+$eD=}j)@%w0mI)
+c}(t+FxDy`^VSlH`03_D@Hn5pe?5yCN41K4Z471g~LT?sp<*xe%#HkuKv(u@6EOhiWZoj)?xB&PT|Xi
+Vb*H=CV$bNQrDSW2nwG$~7eTksEr<q@o#{0X_F87|LPM?*vn@)cF>pgWnZ01rBu(ia|Jh7eCCI5-w!M
+5MJM3#(^lB<Qi5cE_uC+zZ5c$LPtf@8O{++Dr3_HjZLOgCrBN@#Zh20@PKX8*qMr=z>n4iQYEV9nJ_M
+}vS$p{@ci)X*)#Y3jiLn5D?!|B0}+nTw&01}N%`Bz@yttJ@x2?FvyVVMr$w57wi<tCD}g@LArrTmQ6<
+fY-&nDsDXmB*^F}R?w-S&%Iq+2nfy>#b4r@x<$GujLbzp+nJDy3C*}%ftj#nvzcwS{<&*m46|MgTfQ{
+!P+#g=mi-1<)eg}^t*6dF=?cEXiE_Bc}JU|PQJb%b#s=G2)^^wlgYv5^ltKp<i*XS|VE_2MRIWxgpQX
+S1JCT10<N0mC7yK`_d9BO+5nbV16XqhnoG=&PP7sf#3)RiuASO>hU|V3_>T$TLqOJyA#vHsnR^NTovQ
+hG81&i65Zb^IHJ~%2Az?Cmx`zDm!ymp3b>z9ccbQ*G)b-dBi1rE7jZj5K&jwnB7;<btp(y#~KS<D}wx
+}g<8I*#OcVnmzcq&$c>dVHo0F-ri?4L>CTFuO-wU8y<?iblYClSrvbdc3R<kbKzkf+06K(cthJ2fH$4
+Vk)L+6u6FT^(GjrstV5Hi7`jKhcN<e5T00&t8IFy<EqU7saz7<|YR)_Tt{lgg)BMy2%<$`2}ERu?(VF
+=|#wdYxOGzFlR)EZYuc2J-_q6X-5hniKe=I{UpIPtbC$ZN9lGc;8Rv+j8gx~O2G<G>OKD?~e7=H#T;f
+J#IYGcUjx07<C=4fYUjawP$~9GfD^F)E>t?`b7Y6v!ad$Qhb1ZtA0P3Auwai#sqbF$tN3JX_t#;(+Gx
+8h`81L1DSLHv*f|1A)wHxgRKpChWWzp%Um@qgDHR3kW&eaUm1T!M5$&tXT0(XOdq&UH9r%Pm7L1+|x-
+CUEXbHdQ3q|w6<~sc6+psNLBKyI8$gt+68tt==##E6_kVk&Irgsm2Kdi>x>qCM|quOVOg@VWob;kA%u
+mIf*8FPP5W0(9*#_W07YD8yatwi3{{}26_(p*@`c~=iC@@mWm$ru;-QAE4U}mGUWz7hd0bDRAj98+{*
+u-c9YtY_IY)wrHe2;}U!;euQ)%^6kfXnZgIU3K83zCI8sM-dg1M4Jk0lArOej9&Y$0sh-h1RwLZXxjg
+6l?ko_;x~x=GazNH$?$r+^BO5wUKtjUcQ;z8JffNvrXU0cyi0f{p)pIj5Zs7BT7+6>K<ghlbr(gW=rn
+E?~Fe3CJXrJgZPb$s|g@m`G)zVic$`(`i4QYdLCH9I_Oqf!4C)u;w{y&7~b(f{Ry^KTJ*_H%;Wzlo+B
+OmLvsYRYFRFhstS47=yx)meJ*`Sy;cq_2I&AiL+A&i9c9Zi}squ!u&gHxeaP-Ep`hJ5AFnvFbv#goCG
+(rJXMB5#-MU-SQBR<xxfC{B{elkZ<!c)6m>hXu2^|U5R_fWE+}b5b?g%u2<;Z~J_FA{xgCj*3(_pH@m
+a9pXrW1eHNDn;Y9%eWZ59#=O0}A_Vxwu8y}|;V+!56Sm(A=OtUhVfn#?uQlZu;o1_q)JCT<A~J6x|+f
+_GU~+>12YbV7?}j5h3d*I0R>ZBVKt6FL%u*c{jjh&<IjjUukwg{D2JUPp_KZlk!%1uHYiSKPRT24WmH
+`Yyw>lJ!884q$;W75W?*P+;OhH<IhUfKr}D!T!=$1dsiI;gMS4aPoD7OiomS<_th%=PtUei?je?3ro2
+SMq#Uv38LvuPOAzM#AQ)Nm(vc}Q3_}>mbf$QDH;2V(Z6A|8+yk=+q2$yf}kK`*_>U)F0}il8-37GG|?
+~>eqdjb_?yHby8hBOAPHKi?rw`pcWnHB+4ZXZtYLxDAQ-H$VIJIWAln)KwjWwxf(U6uyu;ETH&;gliE
+;4xzp`v0=<w$mNZKtfE_wV_mV~WUxTie}vC@%iN2AWMt6_9}yaJo<Txx3Q8k?sfa5ZOG89=UUcEx_r;
+9F!U8-ZiMe?J{rS_qX-YQSh9oHN3*u(1V%i+IhQ<D-UHVUNWDHiO6j^^y7g9TtAa6+vT9L&V1<ax!g$
+It?Lkw$LX1@FX7eS)Gb;0$-cjs6o`i*u4y0gg$@3dC@ctk&MJ&gWp5Ybpil-z+ur^s`=9QBoWHoH+2A
+G1xI?l7>i`#+R?NZS4-@j&?x{YcT>sJ5CTV2g#r<;)2&gg|3r;L`%VVy>UaWrHM|SC^tYZ}L4vM~*c&
+8%RaHe#QE_7FG^q_*^=QbY?~vkDtPa~~LMz8M9NeAG**6vZn`oP6L4=xP;S+A}lY3uOw@;IM0#lx|Lo
+lc2rz=MLRGxyw77e427n?TXy)*qM!BZdX7>$q%4=7LK#xpUrEaDfaz?=6vEE|m+&yx^tuXlzsH-K`Kw
+F~4}E}k!+41=FI^-~gEXZLkGy-VFOXyJqO^U}5U&IX@S3N+S}>@Os~p__KfmD^tqmW6KOuOK*X!yeHt
+E{ihsS7TSqQz+Nw^gz30#;&G|%jJ||o1`NQx!;Qv&&D;hs6==}A<>;zk0ox1?*9)R;x{bzQx>mN!=GB
+eAF15~b-R5*lW05!$+Lxx80~(3CSp9;iu65v>!@@_;|)ac@XWjm3rD|<M$XnTsB4eNp2t7Tps!cOSCJ
+=LKqgo0;;-F@w5J4kosBx4Gw(MHv*7L=j2!tcBchhih6MTiZD%duL40G3&BR-(y-V-(<8^aQ)ys=qnr
+47YzojDe0p!*9KRl)eR7drwDyhiGB;$_A^T&++SnIcC1pPKyR086MVA03#I4R7om53}PH9FyGm*wi{N
+in4vrb~B=r+K_swD%`J|6=AeQ<>Yi&d!1&+Pk#(wiuilCcUX}?=a9aeGBj3z=y>4uD*M<Z!hNTsjYkU
+A`sxN<u>*?!q33U;G96`YcRerjJiyPn8*{0^&OGzQJI7L7P3uDJi{KyI?;{0lYWmooYqym-UELe={fF
+qfV=no0uJS|^WIW4`H$WSp*dT65hGYiH|fdEs`*T)#RM@hX|(%QHyD1ndJAR4o38Tw5D%OYFh9vDpK`
+vUGaY@AAH+9+UiJ;^tf>nof7Z_Sw?EP}KEm#xCAIoRdf4xei3=KfLoNOn{rrfw)7w#rAxr4)#>?RZlu
+nxKm?vg3VtaiTZf-){mA!e-j}Au6Ep+euO1~wuEw@#-dn7-G;LS4F>E}ls{JWyKRrIo*Vzx)>cZ!<(W
+b^hP!D>t6wR#t+bfJj3W{HyK0=Xe~Z%CXOoh~xx-GUITb!#}bH+1bw9&<20X&0EdNi2H3ko)g%wBj|0
+)Gz}72T)4`1QY-O00;maO7>QZn{?EU6#xLXMgRaF0001RX>c!Jc4cm4Z*nhWX>)XJX<{#PV{&P5baO6
+nd96I{a@$6d|M?VSYE=MY60+<hmsN$%$~INuo-C;>IqN;!#{$72ITi?Dfq^KxuI^Fp-sAq>liZtJch3
+Nr0YFO522R-^Fw@i1-`&&50ULfdWMMKF@$!Tfaxwe~pY#rT2kdo{ZZol5N#?%x*z;${FNW~f59~J)2U
+~U>d=aS+!_Gy><DAc#Oqg78cD0qOBxcviLT-YLv$Ld#=YbUP3~qSF0$4AWnV1zafnUpv^EHnp!n)?1o
+ljnmFRsVFyq7G9=j`?6#m&3PtM@mT@2>G7jO#73WX(jv#5zqf$zE+G&nK5X{WD6IOW05OGs(-ljF)%0
+%!*J}zqZv7Db`$p|0>djh<Lfizln4bFOr^m>4(WW4J4}pz@8RjIbd@xc_^nmRzw}(#4~`S=Vd%kiY(-
+LIdvhBDEe(7MO40Uan@zZvjE66U`q}_@9_=5mf3cIRJ`Nx6Yy9KdaQk^DLgD>FpIbXkw$@BB-whvL_E
+FY@txP}A-#Yvqmpnw3_Pc2?sOUlYd)RAsOg*W+3EZ9o9Wxri^<ve`UWOAj??@3m-}_Z0FxY8JnA3&&-
+$#~{iy%`=4|*=ALtFN45B3FqyCoX{a;@8eh%`SuV>Mg!TdNM^@}V%$-@<22l;R<!Ys)_goZ%qlOSLFc
+gKCU4q~z3x%|ys>}8KtpeA#mjgVUl9sJYpu{2A7?0J%%X5mU8lZp(m`S8<^@Dg`9>L2ECE4L}!Zbbaz
+dH?8T51>C84w-_y*pi3`X&Q-8$#f3%&2Y(#|DzBYiE{3<;SlixDa$2_%_H~tf_77a#CwDaJLdDNOx%G
+$EO~A{9ut27k#l~>BNpM`qkfQ2;=AOQXMI+P(-8MP>Mw#Q=eQ;I^U)5lN9NK;752caqmslgf#*J`k4R
+k*iUS6l32&KLlzK0676wrS_5gk$u@)lBK_^Ab*+$3}JcA)1$)E|yqTbo$-Sy4%d~z|Kz8ix~Wt@}?ka
+B0vzaKpDze@@7=9iDphJW@yf9HN=pX6u%JMWi2IbQGj^}ET{&Gcsc_Uiofh5!JD2RrOq+Yo^2lkOe5>
+ttR;+^aP6&{a320v=e11uNBojX?IN({%t!G<8l$`2dn1WXrpc&pxYN<i*U*9Cw(9KrH#mPq&-@_~e5^
+BH{zkoq;*WtAOx(A>BiFQN*E_yPnrWE$j8>d;xm(k0O!W&}z57^%Nd}rUQRO%<5Msm3cS-CA#G-2ia#
+E&IlZEDpG=7&%pU%ki$D%_0E_N)&s@`>l6kZ6?t|v6Y&uYVf~}I$P|zBGys{SH(!W(eFK1qLGXe(Lhf
+4t9yvb&OtXyu+%~HO3~TuYHeTZoA{t~eM`*5Nt>Snmma&9q17=VZm}i0kO_weZbij^1YhF!fb256YIF
+aTv3zdFzc|yTl+&Rn{S|W!XGPj9bjRFT{K4~I^EC2q5%T?>AG$G?)DNSiYwf|SnQxcgZnv?ZpL57Z=x
+hNlTvhfBi$Z-S+8Yn#Y%7_PG2*3rPDgFZXmlZjvClm5XZ`zh@<U{LWuNOvOiP$yi)LRhc%uQwpOz*DW
+SE6#t)IbPILWpA+AQfgj0AW|^m^0FP<&3LmI0}qcwe>vZp;%~BpZnGdYR**hHTqOUw_%EUy%vctaQ9k
+=@)e&2@iJG#P`js75eqq;x;c*)1C84hlw!buk?6hYKA6v^Q2^EfXq%62vVwPb|9Q5ZW<@+YL!&=n7|A
+5*2-i2n0N3&BWdOnYhdroX9|qMw>_HY{FwXjI4+R2*NDxBLeicT^Y)0XT{qlfKq_R|K!EzW3Q77^@=a
+PZ#=4>XAg)zIjyq<jU8@mLAY0!wdN$!)xq7hG%T--Yza^8CWCAbS5)aI_hYX1dbrcL-ZGIv2H0tge3;
+9R;cx&r5e|98i044f*y!8m;bXqsW6tJ&=J8uLUxjU`Mow-if<w%KbS+upOi1(?^wUqx3St`OOb$Z466
+42ecL2_ng}II!K85^*y+O;S=aLp;Ht>4zARy3Vo?Kq!(5kI*#sdV&IyX2EhDoPhZOr3Z|xoz7!WgILi
+7LuPH-yKF07G;|R|zz*sia@SE&2y#ltBaS`6QuK0-FNug<wQ@bW!=UQzA|=ZR-Ll@q8gKt5iQqsCFf3
+8jB5=d{msYI2-ay)ttuaUgG|;YV(+6>!85Dpa*M`rU?P5j;!4SSactXLRw|6;6VA|e@Tz``C*klTNkw
+w}bY!Gsh0+)ih``jaWJ$T|Y7!&do@~O+~ah72!HMyjl4u7aJAs_PA7(A2foCP9MnJuEl4s*vMX=}blN
+Et4hF$-}&Rk6%IHSk(4y^?Xo)}2G~I$(cGvRmzl(Z~F?ipeoDh&i9Dxcpqi#XU+Jc(2@V!O;OQ3SF=L
+azQWr2%MLHO(0M`uQDJ}CbzDmO^TzqK}$J%`PYayD!xT_L>DC+@b;e1<9VqSv^@-|yMmho_8w!z46-$
+jAuBgY0{{IDGVf%Q?_%N(tn^zurUb#T<EGjI&I%FDr`p+fm_2Y1609a@Uux{Z)R$KX0rgJ7Ano$mL}g
+dGpg^2Lb+_Ks04=>erGmFviEvfQgiI2UdKiMCPpQNz{PrL|;|N48fi|g#RMHFg6*$5|t>d%HGBzL3WF
+k<$(vhIGZ&LQM6m-XHKU?Cg(1d6VwxbpyyMxLI9*=Q>OX-r5&OIrr8mO?chF1t>yfBu;>IS=61@SF~h
+Q9_`0JObGviUOOv@eF~sfg1;`nBw1T?%wMIbka))03m4&1U0^cvwVhf6kBo6ViFggOAX&Cq;gwH*s_j
+@pvg$9nz10a)7j2`s?JYfS}V)vgMJ!ABI@u38EwP`$tlwN9!P5b&3aiN$td+Q~`&r4T^)M5Q2Ncpm9$
+oallUJbM}JBf#wu^4hQ?Ck{iCETs|)r@W{3udV#6hG!~Q^w)`nQF-0C8y=a*{!wZrPnFk<KafcCE2lv
+y~qCXrzZ`hIM{&r41e*Q1}3Fo>qO!`oBtOVP8M5yRCmiu|sfrMv-a!3jbfs=+M%8LktyczN6sp+Vnns
+x<#&74oMvxnmrEUmTX3}ehw7}R$h2Ul}g|DknR|4+~Q@Yi4Zd*NXzv6g9VWYvg9IN30zRh`vXcr?R^T
+E~vfq(>)}O)V&0ZCBBRrkUYgV`QVAP{OA$fSw(I1<VW3P%3_HK*QM#en1|BRhA5^ECzFQB3~7ieenJ&
+=2YIqZB{T$)a;_K>)CL1(bs(-lx#t@;@KK8swfBOiggC<c%7B#>e8{Z@|QLobvp$M>N?{OV>1^bdHp9
+4ZlSb$<yVu7H<NcA+o&*CxVyVS{5F1fJ-NJih!lI#Py}cdoKP&vorxTM!$ScfnsDtMNp|eIhZ!&cP4&
+PUWKM3n18h)M*tH*ED8#D3GRMjV))p}UNUI2Kf9+|Hd_9Ugt;-U$JrJ9Ou5-?Z)PHww+m+SYR{ftz^L
+Aj<onM&Aicv{{fM*><SVE=15rss{0UNT{mv7&WFK)(f*yZ~hV^Sx>Vt|A&I`e2)$bW_L7H6?u5et3^R
+WDF@f*EX$tsp#{aWsX=8jnvfM=2nqhp5Xe8-oSq?BMwM_dYv~V57xy#SjM!*DCZ;4wpQJ1)^w6yBk78
+%i~-~h%yHTJP04RI6QVF#CDqic*4%=+V%is9HEy{F(MwY|NEc+Vr~^c2L`zF)0@c!dwqH}xj8*&=i{5
+3@jG_?>*>2Ib`3;*|MYnL=dq{4ZbdT6EC2Vu_rkk=dwSl4<`B4N&)%GQinel-(7w?+0Jgb+kQkuPwg$
+M0J~_j4s=ENf4T@oCj~G4Xz9}ISRRsVY&e&Yckw~f{05prOKwd})W47qeVvYw*LAHgB8K6Q?k4zsMR1
+%~ZXB7LHi|7|I%7B%hS-Pp6>mJ?Qe?(&LP|4E|$0ux_;Qr8FEpiGdU|S%mAsvxKguZO;iq5^{Dv)Ldg
+j}3+fI!%&`Zk?D)q(P^lLoc0>(Fq=#MC&7nPf?<tTY5X5s*C(7V6M}#{_bbAuGWur<lT<q;p$gbr=a%
+?sJA8PR?jz71|onltt@mco9Xrr#!-hS#cu9ovcQpl?#?e&Q7LxrO^iIv`0&W3<X)4TFM~t0IDoyX+F_
+WHAtWokx6`sAr%$2^l{?-{XOg_xfNWgUx_4|F#wH$-O4mv#sMgBFrZTIfP|(E5f~jKIcFw-O(vuS^El
+(cI#~2Nu|%$3x0XC~@&*LjS}lUD>RXw=6MzmG)Frg{vB39lXcX1Z9_Divpqu$Ehzd2M9gI095#7VgD{
+B+>c9b4b+^EKSZF8mhi3iN2O=MyN78bb#0A;SgTq<lB)7y;j2H#3!WBqC&nIyh#zVr*s)YX1$Ms(Ii8
+{8>@G|SJwn?;Xf(<52sbWbD>c9967s2ELwty4O$RWa8?nh9Zf5O*)Dq!8$6gu~@@ItXeU+Z}>?3#C5%
+AJI%-l{+2|GL6e<70^I*fkYo5`;PbV+2?Npi46c2EFHp?T`*u3TRk~7X^=AI$hz!Etqe6`X6RPxU=Dx
+c2)7*BNx^FULz-`J0}U0|{LpJsWHDeBb2a&A*s-OKCG`m4o`D!BXmxa0T7Ua^v2p%W%|tt!^Hl9h|Jd
+nU%S>A<SXEip^Sn+giS9}dXaX|PZp=0IjT<UKSuegZ;idApRL6|lj_O#GfTS(uL)Veb1FX(E*#khDr(
+n4R*9zf9*^}qmuPNZu9dWK2J75R|1JkdI4%?>>q$$NplW?UN%i}u%p^!QkyuN(@?)7;3=JaMf9ba9({
+?%!p%wX2l1l4^gLGQ5*5Kp?{AAh;Ve_RMI+!hGW`*`x>=T10Z_35Z?9CS-rA61P*K5%VNuQ#gh+UOI&
+g-;3wWOE6)txfGo-3)DlYM`?l<X4g6&I6PL;v7={4n0PL$qiYrB<QIj_9d`tBDIZR5gQ^&G6^>3kPxZ
+^=|-u*Zcb44rd2kv)bdg85W;J7Ei&ThUo;w>@@4niAT>KGGWK5L*8BRMbC}b~7MNN6ur;_dS|AP>%>#
+<l)0v1NGoxqaE*_L06;h1pA4u1`*E(SOloZ#YEZNKtAy>r&k=lr7#9UxT`@|8i-G{HV0~;u8T?JS>0*
+=PzV8jOjRK&sYb6iS<9aaLb`NCj8Ib$Ce@KT2`BrE)0<T7^^m>m*;7mUyN8l<lrTG8_&k?Pz_?S27tV
+Ax01Eldc8oOZ?43f=+M8g@_pW26Kx&AK_C6~MStWDzA<)H-1@PGwq;V43qcX6@8~iZmvLJ4ZfF%JE9E
+p^PC}bBQH<CCn({OQ19C69eZ*xK#60KbBR?pr*HRzU`}19r=iKy4tg4KXm!C;v~ZALZ>0SrIo8tGaIw
+I>C;r+>syhg$ZG<LH`Gi|9TYo_C|+1@6LHa&*gr;EOWK$HV2`k$xpksKv)qq*xzCNJp)#KJvFRY5*Zz
+Wr>AtTiM2-RVZy}q8jvcgX{3}pKAZ?{I`oInw$gF_Yp`KK$&#ddL55sBKW&=+C@C~z_>M%r8zS$dwZO
+skv{@=fKfm)2sRhpE1Y-ZJkV;APfpWEqY>o^h{5$$wGf0|+BH9Jlr&GHvkzZ{cHohJ|w<X|*qb;KzE8
+TM{X@jWQl$Iq?s2j8^iT*Gs8^NIr|mqIFh-qsr%UmUYDscIJO%tKo}*s9mnG^!3uDp0CeU_mmneU<0$
+MudhEA4(9N3Z`=GmM&;)R72#hKE!4v8j*!;Y_spMy&7c{I%$7){#;|<%AZ@Avmun&?raNXYmR|+F#l3
+eDWTDcTN1t<ZJTY$<|jxRVMA>m8?(2{4=qS#o?f>OTb`-3)G@~nv2wem?X`(-hbrpGB&AsLFlTO&4rM
+aLM9iylA+KSc&=#0SC8u<Fq&fuE2QOIPofWc-3ow8yGEV1I^K3iB_9f~?9uBSgVIUbm8n6v_Ai4nZup
+kVJ469TN&gZj0eQ2|xDzPeI+m&X8@18pEf(!_cD;hc3tX<~S{gIC<KvX=?oycuFLzTrA7HAIls0h`}r
+&Kc^u?4kv;t#iF+i?AQ@Z;j7W~>5?$HO;BTh^)EszAlfbpW$V4!UFkuXP})NMU`}<kM5PMzm@xo;jbg
+PuNvV9Xjn3f121~yi2vUdRWTKHr52fUuH>>y2sS%j_#(ZTMA;U{j{SbLy=(KO8QMjBpXCwSyLIC@E-`
+q{`f$w9MP6JEf(nhU8gh(XlE2@w22tLR6(rX*v_z{VdXjn*V^4q1*%(|sOktDZG2<u)(X;=QKT-vb)U
+80?DNx|ZB?Do^sH)!NAvcrs!03maGKS-oh7UeCt6-+lYiw?b|xJiuJ>d7*>Jgvx~|uDx(!n7)fIa6ms
+EF2SMFMKot)y16N`p`Xh`}ODuvX9ZNeKcs?Ie(_-VicV$rbbBZRJRMjrW@$bP0DuyI`psH%ecsM<G%o
+!3?VOdtN0?Xoi=XGM6+C3VZ*;iu?+j-R3*=~l@S?op%v-YQ!w>fDNW-qCPRpN9Kk5QVw;3Ss4y>SX`v
+gmC-u`yt@aVl;hw1XTF(`^LuyodR5re(~HMT^`R*bypRphe5V>5HIuVZCCZyZ$yl*VNF_xIX1Mq5I|X
+!E+)FT?E#@MXf9}rblD^EqH2*?1=$>9ZFH8wEKj0BVk<{@8!S0f=^4a54IuOS(-Qph7F)>gc=>+|fcP
+fEP81EqnmQM`jKpkOE-<RTzxA`~SPj3+gdDD!LaP3@k^a2iZGiH8eC~F7Bs9z=fR47|oZ5h$_p03j%X
+0v!UhyzjO*IN*GjZMJDVnHtgc;4VSwNyID6O#Y)oD^s(f_KLMIvOUR};2KsGYvf7BGV?vjp>7$DMhr*
+?EqiUsg>NM)%MO=HzP|;E8ILu-B*>pL8>SfR;$$7e`j}O7}%sn+=h<z>l?wl`<Z|1E9)pK0Wo-L}}(b
+z!^PNJ3#5UL9JW%Sw@LM(DR!_DpP%SO6SmUkNs0goqf^=62LYDs*zCrZTQ*%r$hkZL;^pvU0?~>R8qN
+8nQ+-nB8}DrldF}J13CX#>y;w+sP+G$a4ilrnze8Wuoq>haU4pH$Vydh(WrCPJrSFNVpd^x*I!z-h4S
+OEa;U8o({&L^kw%@`vAe8e67oh#PRR}%0{Kt%DZcqVGN{3Nuvd|Clf_-%C;wh)7<`K~&<D(x>S0mO#&
+btN4v`ZE<hqpr%}=M{X_wz>PW?YnO9KQH00008031s8R)k7<66(AF004dg02=@R0B~t=FJE?LZe(wAF
+Jx(RbZlv2FLX09E@gOS?7e$@RMoXOe&&(nBusJ!NFcl;28#wYGN7bGU=Sw6N^o#whKNagU>v8^VmJrz
+N+9uMEQiBbd#_sUExl6et=9HiY~^JICk*DHqKL1wphin|k3(xHAsI->`K`6inMne+x4+--^Zow*`SBs
+=vCrCT@4fcgYp=EUUTZ3Df1I;$9A||;P2;$Ioc_<n{m=gx{N+q}C5L-C^T=iUOiPYjc3a^7wFPVHzJF
+icUEeFX=dK4H_`X<h_q_#m(gOweKTxpf7H`4#zQ5|;YqGPm3Jo0F9z3$H&AxM5@^59eb6Pvx-wX58Vs
+tN^)=KxxX)nROIZ!<92*Lh*+K(wc+kh`I?(^t=>;3lx5MQ#c9yiA=F{N?l?7!WeOzY&#rV*wrj_ZJzp
+X+HcCtU3C*JV%vpUoVX#+m4Q^3EMK5z%JuGy(lwjRc6Wse9^1|5oRkxViXnr-|$KegiQhCT?FQ$31(R
+<0k$Snm;X=hW8EB^A6KLhQCI<cY_G`@gEr#!nRt6!xTWRuBlsfmv|S)-95u-`!(=)VmKU>>$*k<<5t~
+(8BIFQEYrnsk!$MK*4+co)K+LScN<pX5;)g2b@#6RJ^)S^bQ%!82QGoT@gKMF|Nr;@=HGJlRO2Zt&v8
+4NrY_(duPg3;xt`}Fci3(BXp$`)>hIOGfCe%mfPCX&e}$ndAI{Z3cmi{?7I3U&6r@F59=0t9KiYyOEs
+yJRacV`s;|QCZ&2jBfy(H^DE2(dINuO6IOX|atHegBbj5JF6_xx`t>6pzZNv+`h4lP{P?-35BMXp)Ed
+6uzdqbWxyB2L(kNouB(m&|G+Ty9d`d{J|FQE`9#9ksQl3Ngs1X88Ppr=iTSyWgP&I-P(-sqa_nyVx9P
+kfYt%Dm>8~cora*u_>CS1<ig<>SybLK6rm|630EGxLI2NfTqcZ3zg-k6nDbeT5nP669Ab&pzr9w0V{B
+P(Bx(RHJ0PNY8NZfFi(NARUE5!6-6!XL@@1{%5eSrXPyI;>fhs=4#H5e`dAT+7scJJLOC#Q`zkLj;>*
+ja2p>>N>SpuC;#)Tq@gY=8?Q%q%y~2}`z^l*<MLOkS%Q4w~s>t0POoL)80r;80a@h^pNW>Xx#Ysy=XO
+O$Hf@u=`@0UN}SiN4-YuFe+w&vY2M5ne1k%OIpzqiBZVP`LBTCF-_Uq2)ORcfIR(v+&M_-(2|s)x*uN
+Rabj)o17k30DYksR^iV>x2j)`t=1OYk1KVEuK@W+V>;ITIWbHqud!?`?t77ad#n-=U@&{-CdP6)$Mw}
++I+!lG>LcgC{lvGJc8pYD}g5_`2va31v=~b;ImK5<AJZ>i&z$a&>!GNASZNtfEzsQSC{KlBm&=0e3k1
+QkZuaQ6Q0-X0EwIsFBpQ-GZdwii-3L~%Ns{5>1>hSk6Ro)Wr*$rtWk~HVpO-DH;Xp7TGw3(*Yx$5?+5
+@VLbb*>PHTWC?Ni{qHGwto7|ir&c{V7)5pfX@Lz!CM61^4U<%C&E?{V`MNeG&d8Q@zke5;BQIKnTh#e
+(X-58&Sw_AclB>Kyf*@3yDO%~t2Tb$+iekeTb^!eWM%9RofJ&pjBfwgJn*px~XKt}RmgiUw2*<Q^j@G
+;ySy7!Yl0YjeWvVb?-0RLW7S+-h}J@pXU1mOchJDyvu4P(xv`A#(N*F(|Jl*vK(@*K8Q!VQ)-;XSFMC
+k>A$*Z24G&M8-(9`}}NAHj0ej!?=O0FCdpj3OsBlzIQ3W_)ldUg5z--S~lPgS<^(jb3kaq`OBFQn#^#
+Q2QaZ$XgUkh(b*+5{T1%m96OBnrcO+35t?uoRcE_^eBNM>_F?d>+5y*YAcgiJ3_&)XYI7B^37eFx%f!
+nuPdVhNtaSE?X(d(NQikI=AyD1@&IBa6yQQok7d)$dDBs%;Y?~OG+Ks6RWM*enGCPht-Tjgk;hgRSKE
+S8a71-Oy#T>a$6EnTqN01HBJC2uB^^117zF!lwfb`l&UM!=eDuIa!N=#rP6tU76D2=C9WepY9AS1m#5
+UPH^5@Kh8h<S67)ldvR*&N6Rrr(L2xr~iIuW6N);m|1n@&wl$MAq~LGqu_HS<9QD^J9*D00GuWX~2GQ
+81sP{fWpH*IHzfi*~r;kG4_9O&5*pv+<_$o_Zxr<E((W!3P}7OmV1veSKvDggINIC8)}0WE}i3qP$<=
+5!}=@Ki7olitAtL%18eKov{q~3YAWGoC_&wg06z9x_z>7e$+I9?+fCrlVCpVPos7VQ1jKe@m<k4NQnt
+SjPs;8NyoOG|HNZe57}fOqLA3e(+HRz$U(2&Y^_;Czsg}10p8We!a4ZWy*#%#3UFHE91j1g+D}Zm|P#
+3k6at1n3;;`!ySh!uAjU^;0HW7fe-EW`8+8xC@=Rut-+3Rox92an2O*0|ZIRIE*YJunV*~S+w?>3~DD
+X@JsAj$I}@n_huwZ#eSVr}**EGZ9p&L7l_g7fmJe$@NPq(bU9%6hh!vhF@bEQC|{TPS&ewbarjr(N71
+)&Q6nrPD`hSExsv7cS$0`-Ht*EpW{gIWbinALKpkXCrm#Albac&<HHO2N|-}Dqe2k)xOvf?DHx<XbWs
+aoa`<hr=w5=rfqNFX&dtDeNdb5!}-GA4Eb<A7BCud-)P_#lf3B-oS@3j=_T1Ax0)dbg6AOk=wwyCtd-
+|;YOgp>*qe?Y&fAR-P$6?|NxJl<@!>P$gUCA~wMsgC^|L#HgS@>Rf!yo`+ypJit!VrbXAhX1JuK2gU0
+W+Vr%G2q7J1%Oukb`9P@avo`Z;{n@j%sD%yQHW6$}c2$Fs53-_1y>JyUAshbK=J^OFc*+TTS8?jrOys
+2sNG3asJ$WDWBPbDSD_RWfk|6r)2+U#f1KQVd#C^-4o*6lV+-8_=;@o)x;eR-Q9ev<3^}X~C&-#9Fz`
+!)~x9`>-|iKCo0S@Nv8_yv7_KiN*av_=e(?-3Y1c7zaB^v;c!mrvggxeX7VSyH5a2Ji9f7_s=0wW@hz
+Cd~vjgw|Bz5R<YgKqHBgM2b!;TI3l6rND?jw)0P5zR)%FP#?e!$zUk~(o40jj!})B{)^I*c%vj)TtNS
+``R!>8=9?X_c*~VhFN`E-ijRUA9ohv%y^9K1q>;jIlVpLQ?<pR-t2J<YUJb&)iyRS*YOdvUT<Gr?IJK
+j>f^uKbFEJM6BS^AQ?@$$eLKmxqrVgK2Uxr62!y|e0*8L}+BNIaM`7-hLE@N6<mfU@ZD72g0K4s`&nJ
+U(SR-kG-_XIE&khP8j6YCnx?UqXNZPB0i&fYhL{((5NCWM5j52MeM9){!C&;sJGiq%H{53B;g!8VDWF
+Y3$3*lc!2WLHo+^;)38*53_*{j-(@E`whl_;SBO^E^%nsTH`TLghMCK>Ea78g%9A1+8XwlYgJy3m}^7
+r(%GUz?<UkPm1-R>hc9;eatyvSznf4(M-wP8PkiH7wM`{%C5-v><+zT~(q;)`&Y(FgUdQ{`BCK?ZvE~
+XS|Nf5C2j<s^OSRot2Y+A<eD(RfY-T1>qu9$Hg5<YizXFmwvvD*@<}=ZlYckjgwt&YDM12YL35TZCpL
+9e($~ixUGGOw^WgbXx<v@Aj*mKaQj!67rfRJpY=z~S^3DB!#p8kA{{pK<>Ab7}`&BjnpFs!(EJD57PB
+~Gb;nNsM217UZUCxDe<h100h;yXaGwL`UkGa29Qiu+`%8?|_iWuo+TpJcZ{{wT<ERt*+PWmMHr*;6GR
+#Pw+Qi>ZKiOtn(X&V!nyw!{kq4IC<fcCZN9C_`0C2d=b2J2IFE@G1v-AE5!2q*h&Si}SV4H^foU6T)5
+|ySJ;h#4du^u8IP!)*!7yQ;`r*szWo#Amy=dO-&JMBPwZaTKr~U<$9Y=n@<%`+1YHAQ9ukIlhKgqKx-
+AWdz+8dU4fK435`#?0vkW^;+8L;YP5WnHPv!7dBv+C5v11a!kIWZuGVdWd>?!2GGuan_V=)|%dq71WM
+h}1rsqTR14>7%9oHc=iuN8Uzr@`yj%Ldt3yxs61Tj_gD?Hf|Nn-ib(=BB-EbJZ@D}~yZ@oM>MB}Xj}C
+`+wsjx#$@w15*wso4crf{jtWM#^AMI{_|TEweh)rcZ~DV^qkL`p&an2ja0pYL9D;S<02m*O;LYQ#?!M
+0kg}BA3;+;WaV@MoU+4w>MwEIg{HUk2^xmac=nTmRA+n*7SKK*<mT9m2vBbeY2v3~ljVjhx>zx4^q{+
+M$mOI3MV|_Ltxh?ype|cZ+`b-$cY(0C3&e64&ghUl0+Z7zIRcZSR$&(x)q;{Rzt-6$M&omkp@qE`P$%
+YtmbkY|f6wr+$L141>vJh&gZyF^=1jw!ZNgso-%`}vP~Xp0iy3M~LcVLwg_@NHt>x0&pldmw^bqh9wz
+Lr&LOef~?V6HmX<D+S@q5$?Tc}<9yy!HvDCeRU9fcMh7517gX;Cw^2<mkV>vdF&QoRlpHOEH>jX{K*B
+GU?lJ;_O4)R6i**MHyVmrIccIVqoASO_C=GFyBj#|1R3n}0sd2ggOL8U^DNOs7GXU4s)@BBV)I1Z~wN
+X|K)!#>n<E(;~<M-1P#C)HgsNz_5<e4b_8qu9tN}A(ia6laT;64u|B*s^~thU;!81ai<^W^4x03pRo^
+@T;u7^mii2}WhZ_KT0QKxGOW?gMT^n?l_m$RK4mt3W6oh8(t_hxR7V}h_9NbS+73)sY-YK+Kt5z`Jl6
+o?YvWhJfog!T1B72a)SO6Dt)YUl1)O?b{&Gt5m+7iC18qLu*&<p2rCGTSvftQvZVhDE_;!sWQXOR<m2
++G}X#>(vOk+Et4%%!ii;YGVdr;6(`<z{MQyT~FgtFI<SKlsbYd!~7wS5`O`wqu7F12wW^(y08a!Y|v%
+M*dRLqwdM$gLkEN9-QPZbHFgYb@8{0mN-X(^Ahen1fpGY_6M9N(JUO-f7b|Yg$n=G?Wmvlv8#+?}j0H
+D|keCF1LQPk%ubz<4eKcGXANH3T<8xIk&2}74nYbTkj~e^&Y|v1#!&QEcuXW=9^-j%uM1;JyrTjX4bk
+<ezmXp&%EVRyxA?E#wXN(MkwYabGRUf^!Jrfg#C+}<#_WoZD3%N<(zz4bG(C{_!(z1HHw|;clrVP@|k
+gQTyxA0k2ZKT$J=VcH)<=R;Ts2P@Opu+{cugv2kJXYW_;tEk3WVg!Dzn=P1dBGT{cvC1qJW8-+2b6)p
+HY)Q`Ie?;KpW{Xr02x)bAkkIo*6+hOR1q03=j7)s+hx)Rk%r=xX8wn3&{qIC#(D;B79bRY(;n$(R1(h
+{Qez%6Pp&&G#DGj9|_3fKzP)lSHXVINt=Bv2g+pnX7PIJ~#oVz}WwS=aLG3?MNz=t;E_*ja7j#alW}}
+VX)J2Y(?*BIbp85A-pJ)FGW*w{b-hrhz~oX;>1?&EfBx)k-$};GgU%TW-EvEkRv>ZGqnSxayGM0NDkH
+bqtvWrSWUmSCYP<c2_<Ac&~l`g2(fx3sRU|Q+{WG-57oJ<66T-NUKRrJQ>nIu?>z-Zg1%6DB^XjkS$P
+V?lpRI;a#YkRc$C37`#%8LP`*}HrUa~!1!Wrvwm;|!g3)tfcRtD}DR)rvd1$#ZzbaJ};0N(%18cM14#
+ZWe`eAYzFW2XCVlHS7W7(+jDd~J)8cHZKY*Z;9WWNnm1jn)7-V%52y325d#pVry5&873x`ovvHV*=<-
+!1&MKDW2bX2WHG`Y!cTkyp#|6?b<$qt)GwraY+8O@D%d3?Ok4%(6hvQen&Aak}VpcGQ{GgtNY1_`x3_
+!LMD9maddw|GkXkuH0lb%`?>}iarI&er0{XTHh7JMGj|GcikOweK#jg*^e`e<Cyc0>oV2mUa4Dcj%TP
+*e25kuijSa)$Jw#otVW&g{`D(?=m{VDPmsKoU=4VZR^!7c2v?chiK31x-Tm=GA6sz~uH`}Mtul0vI2A
+fab0@Z#pm{fIpmeyqLE#NuK@)Xu>{Xn6>TQ~ceS+P?v-_42a`xZ(NNdoNxY!R7YN@S2Z7l-P-7DE+O?
+rwwehQSh$5Dxk<fAdBNGD4qyLfGhlq+6UBIQe06LtZ0GDMzbAipU;)sa85U`Mjo^GP4e*N3};w9FsIE
+g#X6a_$f%HceOM;*@Rs`IKBwWeaMU@pj_FT+%mpVO8_6s>hWo)XnR8XCG>mQ9$wX*i@x5Eu?bBUZ;7m
+q>8l8sCYuD=l$%pb6CTw{+`7)m-Kx<!!;Tr`2<{49itv?KA#2x;<G8upQT%DPvX=SPusr%w6~rGg`1@
+-5p*1a=BhN+bWUmROt)CWI^aG6bQLy;xoqlSjn+fg%M~ZJlB$!^<$m@b<59mveHX^J&CkLf(syy$dcr
+sAyZ4SY^j+~>icrh;;jVIRiJO-|gKvk)-lV^-1(nJTn&hdg!DQTPT@asys%_8|cJm(G)Y+(O#g@x(?F
+auVY?n8;4-w&@z}JpR)%_19q9zP<mwj*|+<6iVeB-t8)O5?Rg$dAt{5Xg+yzG^gNZ#i<VdCb3OTd1Fh
+ajln2bXeSt75Ve>YydF;tRS-5;{SNo$#uJPvG^*4!mxEAFsQQ;`P8=Xvc4RGC{ZSDY|WMqg&`O-JXlk
+?KiK&?WaGaWjEDr4Odu|Fk1huRGtZFri2)NyQyCZpTvg>n-a!)sTFoep}L&v#}&0LxMT;)nU>c?>u^|
+Yn6(>pa@s*>vl)$k{dQbaujsFF99hYpKAjTCK5aIVP0M>6*A68fEs|~UNW`Q?cUAKRO$WzXxri@lW<M
+kC5(Z!1(`dJ7c~7AJVvLg^s6dujs<h6F2i<R>)^9l?9{k5z^?_vYj_S7KW(nJro9gHHG+b_IkAh-lqs
+6`o9>n$}l_%l7d=T(g1Q>gaL%n{aA64XQguU}1TP;ZZQEF?g^U%<RrLJ0e9tR1{kT4Q${SRv85>Bb;7
+w5vnC+wXAh9>6B6ZT$*nOgw%5Wt#^%-`lD%#4|&_v5s#XM%TV0!)JL{-WmIjtP;=-TgJysd>-lg;@xc
+CTAZ=hM$Zcw11GGAQ|ojp7!}!CiZt1$g4z2jkVsQ)L4TiFPNj1B<FyWol#+1AC5sk=w3WzlK7&<*4Q+
+7QZv+Bc(tSGk4jZ{&mjx6<wKMlxg;^<FQznqk>0atrnLb?%Dc{^Ywc=R!?&{})505_AJ(0PJSgC$32H
+Qk8y-!^Hhj(gJ}Ozy*bm?W0?H&by-cNBfol9^%e!OGkzJQir9@G)<xq298k7{CxE;$>V9Z;n)M6<0p`
+aOOgaq5OLf;5;_e%xpVo*SMOItj%VNRB0(cHWXblEe#i*0yPA@0H)Gz~VcFy^R-($IFFLskQbmi2b^7
+F$m<FY>+3sP~8#b#XowjHOydL<z#-O5D@vwz&JN(QX6DeH114%26ba-8_h65;CS#gPHFFbxeFZ^6f-i
+J42fsU#>zG=NlG3ZXIQa#JjpvA`uO7e<-q{(wW8qMb<7O5e=3+5NR$+XjK3T$#ZiwX|`O7_KFF07HP7
+~IMH4%^5xQKZ?HSgdxK}=7TiC|!(AmcLz$Qk7FB!<s~CxO#!9f|sFf9<Y^<ps)bhQK<37Lh&5bLa*;E
+Iwinf7zn(CliLK#LcnZ)bmxy71TY*a;>RP?53ze(h8`Uka;ZRs%b;(4sqo~p$=xJ{i;l~_5{vKau*|G
+k}R$evDtlOP8Q@j8X-#<L$9FybJ}c2HYE*CyK8h-~^S*RzO+Iv-K3JWa=4*r|`&aUFrjy~s4RSLb`nE
+NW+~`y`$=aU3tH=B3%eEGEyzWtXacd><EhR)86x%mz~Jr^bW?le$*MCp)?r)$pp5;v~YIG#&|ac+ni2
+VVWT;EQUHn9mk;>P>9=^S`h*|z)TKRPqhOY5ng1nrEINWe!xBw^&df>pK;OeL~sNf>(tF{9)-nSc!FR
+Ad)=uoS1I)!vgQ)PP80&O4j|f4kI=Lqs;fwys+CgGIG*-6<)?5Ymsw5HN_i8{Npqlv8xfJ?_(GrrrA@
+e$6lqG;iMR!bfun#;$BwH%!AWDo)i$r*Zp0~0@ahebTU>Ejt?y8!PQbtL+eiV*@I?!N$vIk)UeD%%bR
+cGDnxzX=J-Pm*COxz`HUke>xPk@jmg~{nQrw*|o!k|+Q4Wx_#3%*o$i_p|rbBDTwz#aE%xf*Kv@H2f9
+`}ABQ~cxRFVmFzlR787qbpEGf3+av_!-X6NL4G6`r`5YNDg!&kU3N`xT1He!0UG$4}$eq8LmI6RCS(t
+v7{;&7`rt)B{?RZ(?$BLw4i0j*~{4{P6Wd;pFKMWb~d4dJpnJR?o&5XZ!zewMyP}~e_bYUD=inLhpqE
+L+-TCou-lkXJ=$`fR$z0TXGEVfy75M>;^c-b)!n%zUxSv91W1pU-GJ;(s^nDso<ZM}AIGOYrh)1nx1(
+NqvQ}BNX+YQ>k(s%AaD@vjCJ>G%ZK=AK=yk7(f~>*@@_w)&?V%pYULx6~Q7{*y$qI9J2Ce8xcJ|9u=9
+r2Yer!XNdZOMOXWzQ3)Hw^izQD#UE{^?(l#G0o7&oy808pMYRjOjE;7OSizfH~e8-RfU+~mRCJY~tI0
+fZkX*MqJxmd!D8eT!X#x$@(aVdj|RXs=ar5X{cT+LGo7Tir{I8I)E~sf$d@vwDrH1{ZqNGTZYq;CW|6
+vRyb?+$VQ_4K*++Wi~0t$2cI9$!(MGwR4p|mN^^vq0Cm<6nTi3JNp49KIVCoIO=&`%y|LlE-9n6EFb4
+Jy<i{f!->ShLd$S36F2-4n($<Ec!5?;;%*KKiXV@-Xbvk))rkFjk3NUZSFv-%EP22rrpW_l=}*|G#eX
+#>HJ{PSDaq3kmrQNzM;KGvqkm0JZE|VBVqEuBXRn#LfJ2QxzTOWka81eV03?X_v4XoeZs#e`3E8*r#I
+@>&GTE<c@Iks+&jfW^K#Sx~#J#o#b<{+Bx`zeu(b>9gyqaDs&)rZejr0SAhdouDv{VJT#j2(Qs$*!iL
+&ty^-C&M)16fueSsJoHL}sv`qXa=avR^mO2GH<o0X1`MR&s^sd$?UMos5gh4WRsiu4h(?fuNF|K*bM`
+dq-%vs?p*6MEt<Z-h@ho*O-E4AG?L=6w7dE&Q@T%=FH?03fq&3OE*Bv_yn)d!|<pnDm|^zWmrlpmIAU
+VN$AlAp>v>GQ9u4;GH$D7u#DNmc2fL<gDQ{Rnwf0G^8l>25Ftp9PQ%5iPt^~Lj^Z{6u87iRm}t30`Wx
+=)N$=xA(kRS7l~!)zuMQR=zoS7v=CU(<ij&F#|A^N3qMkCFEY9(<(wW%v3HBs(l#hA;4t58dW1?krQq
+kVg;-l2EiMXHZVPAg%RH~f_R#&Z!!{uS(-VNAIf8>p6E<!8jNgjS^u;jPT=scVaMZ3goLIH&O3qV9cG
+5#va!)&fLTrER$KK{Ont5rw88n#FaR&6bwOhDP^*+JUGfJw^iX=s8hCQ$8RgiP#lEi#E?z~pfPXwU?0
+ok^z|pz9|3*cJHf(T_twjkEN99AI9vL-VmmaFe-ZaHUySLMmH8!{WfK0Q>r21{$HzEVItOL3`k7q(^%
+O?UKlS1JVTcXoju`;jVs4S&CsLL&rg1nq=rpH3rzC6c~F3IwXEfjY1WYD&85r5^9EU5UL?}n#2|_YwI
+z{r)KEtpUulYFx1<)!2X_|DtO5JXft^AZYVDbmG!cM-XT(<3kJMdOk+<M(V{8)?8@XW!|5w<#(~D>2K
+HfNPo(1-PswZ-$PsCT59~~^D}MoW+*ffsE*zxcabPhG2j}%W=E8I1K1{*m-O^Y4N6_NJmV8K&PRRR2x
+aX{U&(U78i@_tvNu>hj@G&HB_~1l_%cYg<TZKk~oh_k++PiVy?PrxmB%=7>1QrMNrc%p$7VY4<xXAw^
+3NnU*?29`MD4xBJP^_lfNXTR_V?xlxRBR?ljtmdmfk``19PV5V7mqgkPTW(OeFt2b?Q=uic9uvdrF0L
+w5}=s}F7azr_bHWEGnI-Ho@MN%JCJTs^<JjBPXIXRNgTop2!HK#R3E5kV0vdqfM`+nF;qDAB%baZTn*
+XD6@&Ja-G41y^AdQS)Q#8KU3e`$1=rebdHKb7%eK*N5~IYllXRQbNw=#{!0o3$OtS-s>gIM@>2BT07v
+rHxerGPe(>h9Png>8}MPmnk+-Zfk*0coBG1JOLTGRTkSwJW3X`M!2blI_m9#5o}H+GgoCLpR6SKjgT2
+d;DkUOkP6lyIFxE=2&af&r!z*D3>ud)V^C;M((!0_OtGam<S<8J=WZ-mNT8D9iDvVGCIE^9n>f4IwA)
+0s|;fCtfZm){A4=DN9NiE%=%i8t#HQ`VS^Zj%PcL%N6~mc;+86QTkQ%oAp%&NBaVQt@Du3^dTgNAKLs
+19&8V_3r!PExJD6?6JFtm|AAX4n`KrYH1*&ZV<W^{%f*E<%NMVfS(bR2%&bCahY1bcgb;d*6vYHmOn%
+cIi^6@xr=(@}L|sDYH<a$8ebiQW7lOr}p^s)E^f-;#e)-P>pn1q|nn$!k`(q8H#wR#QOyMnvKOnQ)#M
+@<-Bf86h4p6B)nWYP%aRAU8<sv|A_lQ5m7vs9K<ZQgRUwaL@+TD%$<JVE@w9MuG$&@KZo{^1j;zm|n*
+hkCZ9ir9I9ygEZNUh2Up%b)v+{Fn^&*BM$f*QSFO6G})pv4zB44uyQ-e+h4LTC$CxFvlM2zszol2TdH
+0&hVMAM@$s3`YG3xg`s#0lHRvL68r0(B~V5ezxOhGZ&v4%m|#K&-tm(6Xcd0{A}We@QXvk!bY)H)1dw
+jI#PUMpn*1x>|r+^S_9qX<61hkXdG`S0G(S)>%>*IihiZshKqa~tjZi^1FvkDsFd4jD*~p44wRI?!=p
+*Z=>Q1u`H`!2s}=Q{PA6@P3gI_!AmNr|*t)AEUtEd1QmCSqzkp<y7KF<#$O-%UQQ<PXhqccjYf@->BA
+H8@wadrW{TXLCdRMKxdR#Eq+dMvYgp$kRKT;D=f%rYaIcyCIHZ_~JTdglSqvBFB8IxJ{-9z1Uq%>(X6
+u`dt1Q6+av=ev5C!_$;eAKhf-328mHE1x6X}piNK9w4)Qo}1#l$we1E%wwbGy*xgm3_?NBt&HSxM--I
+?Pzyek30_2L>#?9K6iE9>2Ud9<#Qv~=LEA?fR<!E^2AhJE>2s7#%4|>9$de?S&r~kQMO<r%@OJQ5|=O
+FqL3D4*Cdnr^(332O|Z{3+Q(X^@az#%61&)|a94_9QV$$m;Nn(kpuj;@7Zuu-)rIyj{1tV2eSQ*p*SY
+&0uX~hxnI<J*cp7a}+=;NeYt>GU+E&rEO3B8@${O5K`%Bfb<c6#v*79kSOI^!5W+P6&n%?5pIAi>UAG
+YJxK(@NnYI(<Do5TL|I8=D4O)cZ~cNO2=e2>dotB-ND!X94E6mP$}5`-jEDo%kmBG!a&0?t~gE_pOJy
+y#J|JiAc2O@K<7tA50=C@9nvifnLgUaYzkY6qHGZ#UFyoLH!)53fSLQ3W4W;oFR-Ds=0ui{geEok{|-
+HkRD8_IsVum2&AEv^B(n0N$Cr3WpNzp9$)6ko>o5d6+IA=3y8?3VXsto987fY~rYZPL%i5HujXBtX3p
+&#9dUYNB%UtR&{@(!zXGv4-LEua=wCnQ{uG=O}D^<f%Z+d06xXW;lehaYrU<|4qctAE-B1keyeBMvOw
+3u6c6b85r>sUh5RaIn!y#t>Ixp9XE?^GYi#nsfanAqv*hywqSg8Lb=QPvtqb4rd%HRUYAio&<)pU)CT
+zt*p51yc$L+^H#+Oy_65qAzhp6@9E+`N)3TUmp3#_1Jar+QXbU=ALG|17$p7^5%+!M&x*4VT)cHHBgX
+Y8*M3^YSA@55dE=yE{At5<3dPShUE*B+eC@(jR3R&Ke^?^VCTLynGPjvj}my}OcZkgwF!YBLPU->yRA
+6u!2@cTM{O52X0~LGISTQ;S^OGPddG97lHda&>hff9o<$EX-xQ2Mqi?mr~h%?CZavjnS~mIJmfxz4S4
+FMGBl<WO@p02fe%C{Z2>3rOQ@hw^dr|^@AQf5wtFOKKBQlfTRL1d+~CVqZu%+M~BODgJz|SSJGD~W%)
+{(HJ+``S2pp=Jf%8cskSyQwV6lK4zX(`>g>toRkB{ch57^(g?PnrK2`vI+gNMU{)T2xJ||zn$+bLJna
+l%n)g`9O8zAR+bQNJHYSez(JaaZnX>yKM71h#Hds!Q-mz>Rq0v*TwYCWz|gu~DG(TQ`s9_YmD_E+hep
+zBe(cGI<kuKVcvK3v%m-~*OL`F{%6lI@5^x{CFlhe=(Z&z6AsHfQ_GkS=Dap<Qs7?_6^MO_6S}R-I?W
+W5V7X$1!C)BebXJdKj<alW?tdz9}@lgyyz+rR9u#0HHW#cLZ+2wr3zcyr8pIPOMlj2z#4_gALO;T-_C
+r%EG~>L*?)q%xF$nZ&yOkLLN}6eoz3pw8Bv3GIW2D!`L*a|I^e8YFmif9HQ2ShzcQWZS2cT)V`WQ<r2
+RmGmCh=%y@BHQ501iix6tV^O#|T=VPy?o~^N6sb^E{7x3Ij&!|1co`ly-B6MskJl4wRu99ZRtyaAw)X
+n|M0jx_%6O`Z}#$M`_*a}=Dpt^oHk|peI4=>`6>UEEmBJgwAGA?#q67dzo5qBGiM-pP9LM)9?c3*@N-
+(z3#dgBu}iGDc|5X<DmYB3*lTp{!hpKKJasKz2Z7C3LUG}dy)NX9jN>a*BRKG_U=?8m9+f|yF^L8x9Y
+O{tYPnP*A)a*Nf--jK?^3bP~}I?PNR<~fAH6G#S(i(pm>O*hcP{X)|<^zeP5X&OC9ph(lh2BB#*J**I
+#vhd+K<Po3%vhlL;Ze+Gr>U$J`Y$MnevClFLI;;|Ycr9r1LQ@1c!%-ujfJZYn$!vjW2d1cmKfWj`ggy
+nSDmNFj5{n@sowN0pyJYGJF1#IG7inKg+1^DwheJUK|2w3#QWu~kj-7(nUSi5(q*$np8>AsB^Ml`{3?
+p5o(JS|9QW~Cu*$iyZLr?`nxB-h4ntH8x)<hbyqw{Jsq%cu_?iA5vH@<|93y;~MIa|}4K>bUHCtZ99d
+m_s`?Cjl!cr}%kX;l3Z8qXV##*X8$ZU$sN3-t%0km^_j7ETX{Yb4SuRwQc%)XmXTmaN|H_XmYi=octL
+Zrl=T>%-l3EY+jZttEsTJe;=c*Ql}3caPx-%4Xh`TvZa3-8i`88MO+1(;@UWD!Z|ovFok44VoGy(2#G
+d<yKHq96D8zyM@=F`!J6<>Y1WLgUk^-jfXUzd!L5fmw0?&kc1vq0ET~M>?ndH)(AgDYe{J8M4K;hudw
+YPrQat!7Q<b`#Qoxfa^eATI&y62=kQG@M?-4}*@nld_%35$;MvFJ>J6zXv!BrlsnB#!S~6RKXscC2$j
+P{<$Lo(udMk-Ks(H6H$wDr@h%D3!D519*$DYviOMQdbZ<Sm5*n2o9j;WOoAnbiomCl`Ht}QE}=S}Il&
+}byyMoo0n4eD-6X{o}kYWBcHoIFE^bu!zBc7xgx&(cw1MksYQ9tnVgmC)n(d2zoIdSZ|VwB0zYgo9Lb
+jSA6e0bfoL80PYNwAuN1zTiXcsCodKCLf;I_$3Nqags3vrCbB0SDRgEz*bhK+L<5HhC&piAR3%kgMF%
+Z2sCb?K7PHi^Z}F}-A11&PvWc^FO=C@q3Qm9;`*j-sI1`JfrnCBLkRIL?xGGyH+P|FH9!W7R{-<Ag+w
+4wIkF7i-|kCJ&9TJ;)Ma)Q3>AnPMtXCBn6DG0rx_Fn;kCv6ajUR*asM;%(LhT~v^)dT<*`Aa387<~$8
+H1#dF{yF4*3|@`=`Oy86)9w=$Z3shh%nW2KDM~L-=64OhUO=-)A4j6KZrstCW5j&933yeRyJl(lwfbL
+Xpks2q9jrQsbYw)#LZF)3|WoT&!&0M*N|km(P`KO1FfO2wQTN#t(!;h^VNg%%~npQ4&B3i7l}Pm@GqW
+X_!+i-loy;Rf*$tDb>Oi$4g1<olK2c{rlkfj%VFmE6?G?3^`&B9hd%IMBmW?1Tn}5a5MqcpT~hhb$H$
+-7QKKJ6Rp9k<2lcp;9e9@f8H$S1`8@{mGE1Hzr(<<(nMc$;1pd+^&q}`-X;~sC+jm(ut1-ZZef2%??K
+Xqv`Wz$(l&ph?Z!On0aU|OQp3W;DIf_EjCtoI*@~~M6tC4Et<n`Ll@cExEY@+W(OcLP7i0fiK0ty^`m
+Ra>J#>82T`El(!vt|s0;8n%dv0dCSL&V~p>5Q&n+mnvzaY|5^{6;D9m=vCK!D27@y)y9*T`WiI6h4uz
+Iux^>c(WdDB~kH&<3Qg5N>oB4HB<18gvQCUhBS?Wby$NKVac&yYYcN`ZmsXlvb(g8s=VLTGB#+f38)Z
+e3mLib7ouYyXYgC)0I+m?>P=b_Q1<D0gODGdLF9v>cSTfQdQ$gs-<t?Nvg-cDtB@3m$|s~#V+n1_}c}
+4ufm@N(ns8cXSB$j6PGW4O@6c>;Gb;XiRbIp=F~Y2n5HHeXL+4&+ggFG{Ti#LpPjFY3csxYEB|z;M>3
+Ux);rL-ezY&h4?U$1hRjU46c6ZgxJOZws~;ISMq5H+dJ+|wHWhX#EWOo)31F67{R^0*#Hli~ieqJ#E!
+xUOiz5=<hY=j2`$o|f<3>dHjl^eF14Flq>`;umFwyT}jo(7d!rnHuS=nSo!)cSP`7`^7=I|!_i!Z*op
+DSEIeqUu1i{5?>Gj7c_ZLzy<k$S_APJ-8i9HsG)wp8k^sZN?c6Vrwr<MRXSoX3e_omI=*1x=<y)Hq%C
+Q`5FIQCI<&v$d{!Yv^z1QMJH?f~JUA9Nzx*c~o@Tggq8#+xjs@%`Q*)iER8HEVz{&B*z}x)`ccHYHo^
+1A3}Gn!$=j73Ci<8*$C<hnt~jAqY4+~ypRs57jUp7Kl>q*m(|~a$QBs@{X+o)w8M))D+s6%>9);{#q>
+0r#GHmD>67eRx1}N4_{g4SvzUiT1(*bgwropBg2gko{FENBt*^yz)yW9+4WRiiJPy}>B|WQ8;x*iqgP
+$!&!?zd6edE?=H7v=QWDhSZh-b^^$E~;FYe9Hf=N5b1(!y~IobS}NBu@(l+mXkEwm<?`BB%cqeWB6FN
+bDfTpv7xo`rW*m6UVCS1Hhbouz>vvojKJO<^teoFq=&rhr3<4&9pwCNGF}M$-C(KP>(p?r{(R_SyyNr
+KrRt8eC*&GxK4;b%Hn`Z(2xy4Uk1=&`+JY6(n%=b^RYvYXxP2bGkC`QG@wx?O-HMLU_hGOnud=ks<pf
+bAevLvFS?Dx=JC1mzy)d4P>@#vBz{~T=$A&}GLXwU_%VJM^Jb{-1j&S!)Io_;1;fsq+Gw|tt)f5$jvk
+DhFd*fqQT9qd?IYmQJ~Ye`DcM&HZ4{b*geALA%8}wyjLTE^WuwL}pz<IBWTO_N=KyUXw0g9>!$diu$%
+mT^ZU($Zg94LofFv5B;e``@9`+gf4<5S_x0@ceDr;>e%bD;fj+ut~zX8hkQ0hxxZ_R0H7n)j7UD;CxB
+c(m|0yhlJPcW=O#YsT(-S%Qd>I}c+()%V}w6)9xgX~IS&pa?C;y|*_tqn8aBfrQw39y+KI}_`^QtQ#9
+wP7A79fgk5+?{d@FV}Zk0YhC(ZH2nEF67BlyB|e=y0Xv~UT6<1vjEZUwd!@XO0nFGd)eQSPOE3wN2oH
+rjIIMqER(D*XY;xqM865=ar7MvFPyx802|5kuA8KD>Ow0UiSzP8o8sl;7G*7O$Shq{J&d9%{>zft*v~
+@fHvMR3O4#4kLIWW;kUt6r!j!MzYelEVwx#1>Q0h-G+`v+60?_B|K|B-e=A8?zLX#i6q5uXx`!+g{qq
+l|7R0fIraR&p2gxYuJIr(yOgl8|4TQD7Y5<=KPs&qnI7f6kgk!o3>R39fE_Ealw)m8_*YAKEk?W3NuH
+D)376)K=<I66&22p7m<ggld%9D)n2JLllUvyk68m+rQmF1R})3NT(Gt=?X%E?H==Rc!7VknD;x`cjHa
+P@lbZN&dtwTMDkg4>A1%j)-~?SotVnwrrXHE&TR{Mx!=W?a?%vQx*TX1uH%Y)4bY8$q{YFp;Zi(9gQ<
+rG(JsEXi`CApPtLheu=qQ6-!RoajSf9Cx^S9A3<7FE}emk#L}qX1?Iy|?AA0)pc8))!yC@0&PGb%SzN
+#Nq56Ye963>1JovJ2=*!DPUm}Aq;Tlh?n@3B&@!>=v&{)i*Fevy<ez+gCg@xASd(^H~@Dd<+AK=pvC8
+Q1>G{S12V~7kNuxd!G|Ieyby^_KqCFvyb>Z7<Efi6)|@%yE7z*-Um>Z4dSNT@E!mu^=d-KW2eg}2cjm
+i{_);~vb#+VQ}7rTXa0!vOwrI0Z1D0JJ@bj~y9IKXe!efcj`e&$tLOy3|Jx!`sz3ls#+*0H}}RX6S2Z
+{1vr&*khD*)Oc$kWSE~xhshaIeH0s7IvvR}q2y_-6V}G<18KYGeOlwBQp1~4MBJ<saip37l^6k)0IvN
+O0+rPCi=))V*1=>uCd;iv(^eld;p?zIMxR!v?us_crxrVV#p!-!4hz!Z!ya*hkNpjo4d!u`I0-&}l|B
+isB~Pl>YC0mKpZ7w!^UJ@$NXaJ;d3^#dTLYTgCYXRHG7~1RS#8Y1g}goszw#HHg>CGqk%kD+W~1w`+_
+KuoDm7i)oE$a=4+1ov!mR`$9Yw7bT>_$7UK`xVx7Vl5UQ>j_`z?xc00mCaW|z-Qp8i+6QUFKswWT_`V
+>K3;(8Mud$9qzc+EF<hzi2zw7~gYXUV9&x3$h78Y!~PfK|Zho+y3H7O$#hJi+leah*#oU%kJ34FQD~x
+hqhSRl&fr7)AA@TsV!`I^k%f>Tgw6{KR~KHWly#r<>^pWVjjv!8<Xt%d0LEeQMMXSiR?f^!Lzn*HTwf
+vILRD&$TW9Bb)rx#)C160qtb(PUM}d$2nNHzQ$gBnY@wQ9hcW9>BG=MDt{J0%vDG86Co7Q;zU|W?wb@
+IC&<DeE1UVl|3{WhUyiTOeQmdw<$1{EGiDpQ3^gu}`ARWUbVZm%Og+d}eu(OHj#0S+;AY%iPan+yUD;
+>9LO5hArR*1&6hb=~AYS|3^twevDrN0&FZ*%pxN&1^he-re#Mf#gbe=FDD&P3?#j#BI<O!yoVfLy$go
+RBsJ&@InDL=n_<iSK8-BSUEJ*L&$5j9md~WOHv?4S6s3v)`b*ma~*x+H)H<8bdaDJ|_W^tA=*mWDXav
+st_;R@wuiUJ5%@lS2pz;JloiR=+ByeD6^ppbS9g10X4UpC`jv*coJpHSrXZSjd<U=2s`e>z#4if*Ixq
+kLS6cyT#68!Iva<@P8<f}7`e2Z+={d1(k1kOPRNBj-lD@Vkgx+sLu(ploPURlQ;0iu>O%+z<W6Jc2u;
+nXJ<>1)agItL$=2sg<gAQS{cIe^+J`!fQCXeajLPam)2J+!!M+$lbId(zDe_~0t9BXKw2!o-JCmb&QI
+em3%BT3bcsM_QM7%r!d3i?v#k`EMcQQzyb403ZbjeBHWb&z8^dJ+Oen4|1#ty7F#m2sd9DGV$n(H|3d
+{fE;;TkS~tyVraZoRcu_m_{~Ozvkv6FHzwM%~KaPN%)m7p+p9p+5E&DY{luydb>1|JI->yqv$)vy83J
+F`QiyP_&{)+MKEc`lWWGsZgEN_5;&<lFR`O%M0Z9(2=8)`g<CNH9DF)QOvV86txtIjRGMBd6s4)iNUk
+WM;H=={SZyIE*RGsnT}o7j`678TZzvH>H7Ohy#AEjf%2;dk2K;AD7t*9IbhhEwRhzft5dSool5OfmKM
+_n`nUkz*^O>m8o*FsP#;XHWagVdP2G4J`gj!{wAn#31K_;P=MOx$9a7My-FF9kJ9sBtD%FIuWv!rQ02
+(uh@m8yIpzgF>It$CGsTL;$@QHQkVFE;3kR$(}JWQo%9R-2sQ5b#n2`KtJJC|jM1K@;`v@NKBQ{c6oP
+4KwYZT~s?-plni(954CHlL2iMQC9eG@%Zq>S*Y=7|>=H;#rmtQ6GO_sXBq45no&3+1XcjGn;u%(@HYL
+zrxEr?FP)ora+RCp}nW$!=xmNlByF@T8X<u%t1U=M-_JmVO6V+#$Rl8pKJgcG}fQo2Dh~%Rrg7iGYH{
+6X^nr;>h64;06L#A06GT&Itf6RM+Lb1Q*Y;_D_g16DAj-*xTS~8!VaKj0N+JCa@dD6dX&XJhIz+uj@F
+%Qe>*VLHyTng<R5z`nTksmL5?Z<JHFx?#=jY_l!wK1A9pqrPnziGHOX6#zB(dm1@E-I9vN_fCh3wBW9
+t5fov2!0KRn<X^twc$Jj|n>4%_b6?cd{-$^k2s>Fg7lR^!mLu+w*ttE)+9%Fq)!@6gw*vJD3$q3Lg^j
+SckE68iOMN%d>MqPZ4O{~n)-q0l}%W*pEGLa2>WprM0@;FHf=yYr1%3yg?Sf9NyQ5uPc5w*Z0H$6iS0
+6KzS4M0+caw|Ftfxu8~a*IngfpTJAl>P88swiUe{w7h#Ra2OC2{n6`T_pUUKbV&ySuR`KMtd`HuI&L=
+(sY%aiyRpfTb~u&xqkz4@#0Azs20vS%d-lbvz4$No5S~Wr*797WMLExiWf-Gyfg`fjws_07G=2bsMNM
+2R@~%=mb5qB>;Sd(!35W2TXG>KdlW=e+6MR}8(?h1}M(j`bk`ZfR>sIQd7xUod{*^k}rzHKp#srY!Y}
+x=uX~m}rq<#!K+wPl_a<<iG<4el#Qy{^YjHreYCsQ8zOMGGX%SOOHbnvP6vDN5;Ug>CeHtViU0=$PG$
+9=k;<n1#X4>>yzt-W53q{-!dT5YRK<Fb@;3p`BWvRYi1!HZ){`L*h7I%yqog*|<ZE#w&VVcik0zqX{}
+3!y28PW~`wv(SWL?=X~;6*$xqJ&2GPNcEGAX7!U2I#XT$-Pa1?MlMKinT#FLWro{Pcnjsoa5k^K&Zv`
+or-f^{b4r7Jr-Re$2iJlusNA)jDnOMiZ$qV=@75gyDXAB+@#pb$m7W~97GH-)rf4F)0}mznp}V$b;%Z
+<;Pctu#@T4MpmXb#sc{B~WwNYjzU3K?w<+hYrFLB-yn$WUB-z|5-x>$4fJNq_1<~XjNK@>zbJPW0XBe
+3lBhNaeq_=7EF*2d6rDJ|HuBAyjqsG&!z969STSTlj~G;ajmYo0$<H^(&O6lER-9|bI~c&41NNLF~{F
+R7C_1L_mcLa<icX44kReHLL`0DYgR&$YZ$6y3CDWp#TLPs;b`lbzquL%u5eQKnRaPWG*mv<UFux+%cw
+-RK7WD1%Yx)DtbZfYXKR2yf_)2Pq_}xDxdYG2zhsmvKce!ewB(dj+lpRbr)Pl(=o;zlg2*5^PDgql1J
+{uNq*q|Em}e7)}=UKpRf6;zyuXVSobA&wgal&yEHyHA;P_vlI`H*59V~((%iZiMvF1^5m!BVZOHwF9{
+1SN@}?qrw>2i*_AxEiHAEgcMmz-xj4S#Vjm*MM`(tc*!AYrTCLacq*B`&KC?KEH=Hv|t`~6qPb^W(c)
+vQY2$b$kGyEPO>w1k`p~luE-Dm{J*A#h3kUKA+CshUpl#t)lY9OOrYlY!ZtwvW4ao7T52<#<1hgTWD*
+2gw#qzj7VO*{n;Z@Hk@Tp#<vYq;GnqXSZJN9BZwaoQ`G8(>Jw=^tw3lX()|GEMA8vu-jDJBo|TIjN(#
+bHr+uBZB&%8M*sVj5?0ps4VYK(o!wA^)$=kwI$1WX{3jJM>B{%8HgSqS5nVQxws1e{c)}FNwQ?RLAU8
+=xGh~4Z*qV#+&OrRcM=s6O?JR2QZaZFbb@G6-6z-!ALu=SdwrGofR10f#p>vJtqpido_qGyBJ%$YThH
+!88+Z<lV69kg%})(s8%$1x8{Y#dUsD~G3keYSmrkpiSDl2+;X8<F(2*c1M$4P5CNbNuz2|2i{|@HfD`
+5U<;Ts1!W`I0AL69}*(j{ghq-61E?+t$cqIxi-k2dS|eYCh>xXjuD_R-Ka;rFp?7GsdS<0X@DTTIGlq
+cC*rWOheyaw1zzVGw~K!n3HtC6h&~+8X~}FrWP=8j7IS_DKTkeQ$8@E$#_su@#)*Dm+;#B3k%UzOiHd
+%=SApC=aDF!C;GzQ0B$K{5<{A5c4xR7_N99yC92QsSR@#59=+H=h6Dq<vNdoNjj4G(Njmeet5vBf9#G
+r=e^XfX854)XG$&rDR<Oy&NEUT8#xG8tAoYAOQB*E_ep1By+x@XbUQVCR5dAAk(dYAeW(xWY-e=iH~5
+(DF%9!E70AbQ%N_Hyf8b);cq~<)4-foLE~dZYhP#+9N@b>K1#A|)e}jwZ!8gH{IWXvAx|oeXO>oXssg
+jxCNtqM(kc%k+KA{7)ESjfrLmf;%dRNagjU9m}B|knf6nSVuOFE~!m+pHP>q73O*$4hd_tJC2+)IH{p
+~$8Y7;KS^=V+CbTH#4$(DD+4alFv^)3$CDDCiiELd<l@&1R?DR(E<ZaF_9KS$IhyU(_alCRmy$w2x@6
+jD2+<1|2q1Gm@$AL#iH>1DVCg#8+@L!-l@A&p!ffKYkP&M{Z##bb+_7g?@hCC1$h8(PX>hfA%_#KW`G
+pDAm^I?YjN0F6HIU0VM|nHXuV^*)}sg0|X4L7wDw!4ED#DjB~xBjU9O@d8RiTqeMM2M^{rbeC&+?3g|
+K$&K7>5se#t9cy(U5+@$2FOY@5oHz`Z4&c02P{1jm7lNHGb8u1FbtpG|zW`9Vnu*v5z(#|=Iw9_niPE
+p@&KA%Pbbe<d*K*w4j<_67P?=p5TkmvG47%&j{dK#3vwSwQm$H#!|@nb|AEbjZM;!5iKL7?e$ieo4W(
+vnE489F!RvCumy-v1L2Ja(R%WP4r~n!e_cyh7+pyqiH!qXtl%4!I4Tjdj|={Pz3%aDGcu@g%dhE?-;6
+``GS%G<DvWu2%`;P6<uugiVV^kKkrene7p2nUAUajH##C$2RNF17aaqaCPtkDyPqICS-TRJJ6~U>6B4
+fV-RVp%Ubxz+()Dg3~~pCZQ~~LW|s1>8N;2NF-Aj<w$v)@F)dJX;<=<=cG~5LJrjBc=5L_Zpp=`aE+-
+KX99W^aPbte!0z*t-_u*-e0*)<tJH?K`iuGw6=f$AA8+j)wl66y9>DxF&+2tufwqd_66qlx9BvNRa|D
+tFZTbC4DK>?R?8K-Cd;z%-cJkW?o0yeK-s#JA5-_uV~!VE2hE?6-@giV~iby0DlIdU|y#XTS#jFbnhm
+EyQ^DMvljdlZL+{P}>g+^$yH@W&ATO;44^v8RquNgI!(7~x%@bNqVs(7Q~jusfUUEQ%WgsIk-N?%M&=
+Q5Ois$?Q8vlJgF`l^%J67!O!+1uVHr@U2zQSV38oGacpjZ8<Yk!SZ&`0&BS%75{DPO=%71vcx)CY*?*
+T*c<8xxGf`8A-vFJ_>#0N%1O%-J*u#ENzOC`b`$XYExanY^c)Ck)<LIbNz(}Q3IrWbpt(s<0JG>|S7Z
+gba0Oci&GM)j+N^Xfuivm*Hdt`CnT6VgE#E^mx56&`U=^lim@2x%i_)z<T!YYrAw8gEv(SV~kfC-ltH
+GHir8V%@xTT?>Pp#_0$S+Z)3Z|-VXNMra%aN1IR@2<^Lep>IWp1`;+hSR`0B9Wh5lztD<<7RX`QZg7j
+7o!{e&AD!B`Yog{o~)$-1Z>tw_^k=ZFsGduE6jF)L}p!bgfOdmW#O!^;(v=zr~WRW^Ap{wk%0ci%)Y_
+b%CvfAD)GN()0*poA0JmSCni8_=Qj*j4b*{86K<3Q#16oyRebwc-mGIR9=l1xx26fppio8D5sx_!Htl
+cw~lCP-;lmA_9!VcE@4l5T#ysi&7-04x}2MZJtJHV`#Wdg@*vwfTG;c3a8SY5P`i}PzJ3Gw34;;F|80
+S@O|n`#;x1L_S#%vVY1+aqw_TS8_TI+Kt)o?8%WXN+7NW_Qe7j;{QAd1KZ^tu1)2-y`@SJ{_7c`)vs;
++k#ib}60bp^R0L9;QWTtu3cjEwsPo&}LBPN6RjOl!D>@L$iPp5{IU(n$!ZWZ8GeWc{v=b+kL9!jsLG2
+q03Hj46({08fmlmH#<YkW&rN7-KgATl^6R(79}JWUVp+<HAPF(DSj~#5vt^^8i@?lQCMfT#_Ya(^`T(
+m_-4okcrSmTXx&c2A7!e7eM|Im#ic%S)SyQ>9ulwB1`;TFndL<VnI$xAgAENIe3_+X0$9yzalGs6>?6
+74jdxZ89)Lrx|0a3r)TO&p#Dh)8jlP#4#u>YW9>;t2FfwVGiy~&2ZK%lkrw-RR8^^d!L({;3(WYjwv^
+;N-G<(6u^_4}iSG%a+wtMvQ(Wwh0oobCi46?TV${g{05;{#zOPLe*W25Mit9bxMc(W`GQidi7WwAy{}
+pd`J;b5gJ|W_Q+4MUGnrquqrv>(US;yXs{M`*D%*+1$Tr&1Wd@MWPnkw6@<M~Ga_cmOHCI9z*L*onN!
+gP)<Nq5mt9*t(d25fqi2J`PRE<n7TWZ@XlW9vrxr~*9eEY;TmTT_7(@khBZ<_E(50btkWu)7hH5wGEQ
+!7(eUhpTw%ZG|@U`3fBq?{`GDE-K`kBGQ<~^Qauv<;bN8H;(bN*hgU8`qgvtd28Kuy?>NHvxv5$ceiB
+7ttL5Ul6us(=1$(yj5j;n-jF}HG{?+h`k5C2ah4AE6~aLQHBq=)jSy}<3vDi++NEZI+9PJm4@2w09I%
+<v<MZTi(c=B4Vo-p#a$1E=eUl|Tc-V=T=V?-oJpU@N=-=EmpM8$OC;@cy2e^F)W<$S{k<^tMPc@h?3h
+QUncRy0DP`?-wk`IIDDWR9?+C|qkx-z=HMb}s9iUIoAp<lp7dmZ1OfOqJ{BG&bKYA$xageO9GT`*3B(
+oYf@eo!}zARWpjRr}cD-vTeZvccFFGeS6G^hUL-c_58KIPNCJ(yYEg@f-hhX#7S!Hq?;#jb`-_25%HX
+57MDN=O2Zp``~HoXd@C~m?9B|_rZ0`lV8KN>6p;;SQf`Ebo40OG2&p!ZUhvzJ%p}SH+IfNN2`N}E^)M
+KPB~gtDxqzV!`Ym2wED%PE=~?3*?_iNh{8m--9*pbM9JMm;oV5dSPb2)4j#J5&8ocIaI<=Y{FM-%j~z
+@sTVuaVJ)2_xO>S2BjNBXhaq5#frowZ>`J|f_MMy;d7p#kOKnSlM#Mny#7-P4SPZU0)Pt?ITbe|~tG(
+Qs^ldxs6Sq9oGhNEQ$+B`x_G>ByqLUs{C!tysBvD_psZ#W+i7d4z;E#^0zUoV6{<df|o535!LbFP-gE
+Ho0)zlypm_G>;_e|zlN)N?`X33%RWnR~r7x#3|GI#)%_M&5>0-ZcO-*Fg|7b%^H>LPOUo9bzd$tP+~a
+@P5D0G!O6J7n-ieyQDi>&D|h0U4i!%Lepei?B0$1a2fS&ID{k2BkVckVXfDYIkq)~d{-$>Rl_*$!o+W
+Ed<9l_p<XQd8tuZ<aYG>zOMnm<2nAUMow4?iQ_YH`GuA86@!}G4#sbzUEXQDY<wEF1(6$>66|{!7T+k
+2R>wF*ckzW-ySNE&>88?jLKjemfma+yvsnn}r21;rB4eu%)(2i{%<OGcWDKrfv9jtUugHCdP=%o0ahm
+8uw-b(sPO$BWg>b<$BS!lx6Vg2LiqeNK0p&+ps9Xs?h!p0AaghM#QJ<N57;Rq#8X(h2mCs9XlUEIGVq
+{k2KFcS5Qdfj3h2VJ7D0LbptU7}{`Wv5)C5L(QA27lXPNK^1<TlAif&9J6?qB^NYHgvd;<yj4%s8aH!
+n`SnAqAXU!Cu%R5n)izv(I@H}@`?JAe4=P{>!i>tPo7b$jh;czs5|8lezmG}Q`hvf%~$D~?cI1>nlR|
+@QOHq-dlbpV^g$ZM=B1@5PN-daX}XgXCM2DtI)^$*(XWsU%@w8}X)zr9C>U($S(2~FKIlAycRV~64@x
+5&&fh29qbE^6`Ag^-eQ5CBNOFbzs!CNtko2n>^Cd`k;%Jb=`z|ECtEjx)Sf1`(mCQcOyQ<-W;a$}<I8
+rqd*f7L2Dn{o5NPU(-FvoDuDs1X7&nnDCo>hcym}gbP0jy`ru__60iDMP@r|wvV?eNB$smqzs<w_Xm=
+=fFSSoHvi2^c0#D~38&C7A@_boVOa9lalQ_o|ryzm)*2%UVJhnYVaL=mW}y^Aj4Sv78~^Rk_2ws}TMF
+=v|cr8Xr2gc?@}1*?T)ie~8Xi$rc)8YKU{yaP~<0RuR`3zEwl{!tkx4DK#ve(I**=1k_N+Dr~mySoQR
+khGUh^8Y#yrB!uo*<vv4RRmm}>P-bN}4fngrtLp8Bl48-Xkpxib+F~kp#pmBt3+d!8)h?YWA{Kl%5uZ
+N9y>w9e#WQYdm;=hCi+*uOXICmoK7iv82#z5L^x=jyoDKbe8$FqNUtJv^kK3KbTT$GGJ02tTw*tKf>A
+V-s+C_x8$k5=PC5$#{nwp4D8al!3D!7F`Q3m8WfNvVP41KB*Y1IR$;i=mRm<j<gOOw*fvq`yvURKxWk
+5)i_0LzJw(@}$_T6_z;;UeUJmJgty<n;a#rBGzkgX(Ub6i;6uXCy6*51wE;{k&x8aeR?m%<LYYA>5_w
+ODI*mM%(@P#WkfoR85t9p%52WSt<Q@{BoJpK`lOB&j16wliEhmRkY`!SC!j1(`b}<rO~KMs8;R1h-&f
+yltkocg%51fGw5hVX_YF?@LMfgNDXL;h@;i;HmW&}m#s%*b!Wd(an=QO>R^K9$K*;iZ<C8F-RR=J2Y+
+wE-`IK=Hx>Q@@b@%)lc)8g6*IVY>SI57!PphEvjwjVu`S~jen_KzUXPZ?oi?_uarqo=Thx1T6U)P{dj
+%0dh6$GjZ3|=U;(`mQ4OI`?wU@s##IEh!uUne0?;mQ{K5?;KyWar&SqhAu`Nh8$rETg9|Hx|X85m-<E
+*iwVWdA?3T7SJiX|)Dl7>wNhk4?9QNz-jMm~O&ewB0;vl+8Q<CAfJrSZ|e*faaS$I3Lo-AHcez{dV-5
+?6={eEWm!tHS9NNky>vHhhHX_Px2byj(&Se=+}LNK^*je4&))Mhr1xhJUwIrGXn>)`TLTgEXaN<-j}l
+9LOYQSBT0|GSNjI-x4&j#AUfxO_>Qo5tU~UFx+k+jeuc_z3b64cx((JkKNOmNLD4KKE$5U2=ulWfIfQ
+K+bPFpP%;J!+r(suS%EnR&*LNeC!k(t$qmUlto0+v*ccI4L8O5kFaw0?cLAGvnO?=`T!dvVbLWdJWC_
+_ObIw`yb*<Iymcg-ql5eti&#ax<5F(PH=ZVFYgcSvxH7l#D5_^;u?Egr`l^co9M3<@xhid2gnwI(~Kg
+Zx4TrFLj+3-V;XjclZjJ|hr?VI$F}k|D7zu1?~eHVkjKfj4JJXbbc3&=zkD32pHuuQxn#lei2+Tet>8
+Tf8+qw8a4mZ83kfG}3ZzFtkPNzlQ|1_{or<7LW0IP=mzv(zsfAvw4;@3Y3Pypcb+38R0DG>rDM?Dx5{
+^mSiA{vSc8O(qtfuS;;^aMae)GQ<H%##!(;(a${A=efid8Ad91huQB^QjN-~zSBBASFrKa>?fbQ)@q}
+^aFt!{<vS=1>hd&;SkkDrs$>Pw^NEXD^Dv{U-ArL+=7|7zlU?7W7yP!NaJe0*J7lpED=LRWvfcxf97U
+XM=VmR$JGPa_rP!`nn>dJoI`(9`|hnCjye-g?<6CN9x3T2T&p)62*=%FmGD!3$+#Q`If#fhYO_9=$40
+MqPAtT)RLnz}KTMRPKi1v2E&SQbZzNTuPiEMC@KsPXpCVp-Hq9ums}NAmv|%VKa${7bPclKf%BvN+oJ
+jj=3ln=~wz#b3zmK5|Jci!U$eu`C`yyRGozSQel`V!3w@iDThQRTg@YeK1kC)HaZ%c5xsJODd3srImy
+lRl9d+APdBwmEt1ZLVE_iSU*u0CRA^K>;v5N90k(jKFL2MbivKewoSYds-Ug$oF2R){E}{7?foPA#3E
+`iub%JwhTs*6VZkdbhItiD2CrC{3SL2-o(x`b$Ov3P%^w!H!avl!+MWzt@#my@l?q%z==>K2uE2_-eR
+X^&#1Q*x{;<Fmi}ms9kBu9^=5&+H!1*%+>7oa&c(|Wfyy>S&`|54-8%C&Mfh(|N-Ll$vQQ!&$9TK=Aj
+MGrekET^9DNltEz7LLVaiad<(&>X{)<QC~7J`{I*7ydbO`2K+WhDQf31*=OH27!1ERZ0&%~d$@n}b;(
+Vg99H7S)5nEWF<w%wjGHzDt8yBnNmr^A-wbk#1=QbL`B;u`F;v{XdCiaiT97%K|6rWGsupz+%Z*7C0#
+l24=Y8_m{@9z&y!V7Vr069LwSdXOrD~aV!fgWq2%$w%=VE%Yp>kH^s6TB8V@JWf9B&2eB-udU`C2JAU
+_nCzgfYF3Pyau&^$TWkC(Pgk)!4x-^yrN+U9{@PWOe;&ex8l`5&3Dvb)zMjSm#NY_PMfQ^pE9z2UWDC
+!HKx>HDu3?XDX`;F@EMFA|r3R+#^o4DVrF7Ee=i~9@wxwg8vZSeOr{Cxs{AHcViZ@pS&2j0wZL}KYCI
+#<X^<5~N!Q)>3)r$KkXnLYLehcUwOr+Wb6mxB=fKTbkm2wOj?0nSg?<uQ2>rUPJT$=3KK&?{6u7^4eK
+<nO4<`JxYnz1Eo*{dQ(s+^n`y46=)UJF~@nGyZaBJN|NJoA|o0_o%S9x#&>*2Comjt^+1JdY1N;8IC{
+FMArMF{)2RSeFlB~TjO>)GJszOe+jhu;-3N)LU@e8pv`YyOts3KYIzgwB;&7uetHlSN+kQbT=vKy=to
+b{R$&cTNB>)XCUnN|p9!U3*B$)DWH<kAqCE8*iRhY)F|6?nale|5{=go!6!+@!hYUSlul5n1ppS|Rf@
+Tl<$uZrfv>y_RH7Vf<YTES(148erFc^Iv_Ny{oH`|a$QT&}zX^-*Sdvwsdq^e)+(WHL1XA7W;$5jm~f
+WIT)cc4`_9!<9G9P06jQqi>7$4YP*g~hVu?>l|r4O$obnf(}@lBrZC(T@!rm*}wXy*jS=Y#%d0J`5UM
+8Qx$Lrv}Y__VK$^dGwrK;PZP})3eFwzc;~b7M`^Ue>qBeT_Y514Af7ahL4<lIoFz2ka9P#Tv<~c)#yh
+KSl15_3Lj}z;$+g><mXS2dyP-a<8f`G%hB#UjT^_+(b|$6k$#4{gqIS=y~|tF5?*13>8JZ>^5}au<h5
+en)|!>oQLoR>o|&R=BY!dchbqL$&-3DVZ5_|<fyy-2+IstNv%XSE$C#I8)*)=5a*cB+=;~GS2D?QnR9
+(5H1!?~=PRuL43~xE5Q}LEj%DJ8~NonjO`n6>Y1{#?3w95$4o%FZ&v9pJDPgJ34CQe36?|`wZHv3ELA
+gUs^@P0g%>TIq1y0Mv_n%7$OpL3=e(!+<2k*GO~!|8mQWW!%~aYS6Playf6eZ*iOdDZGWm8Exrf-Ilo
+!PJG+U}2@Y=?-~S2@jLCt??Y<-}qORQ#Y+DeT?HGQfBM_#ooIBL{)A7<9lF$QPIKFLem@-6~h$67mnm
+0i~@n8C}=(qWe^a7h8Z8-6m*~%M@(<s-rX{-?D4&~m)TQ6%tu*jcFWAlO6$;g6O#lJ-T(F3=bT|cFza
+@|-|z4Ly$9CpefD#$z1Lp*arRz&LMFCqyH`f7SKn9RJwIxL`i^$$o*Q+q`i@%{-IJm!)OYNjbKeqmkN
+S>1Htr!&e^%eu;QfZEtv<?o1>QSFy^8k$ddH3tz9chO$3L3sT$$+(0D)8RGI!oA<sK(huYsS`gJdN&1
+<BJCaLba|vNTq12zTI!cZJPggE^7?2hj@J9}w&^(;0;}T*hth%PFL|BT}V!ico?EFar%hlOi4aP&5FX
+>Km6zO?6UF_1Mxxn%erFh3<~MTqGb}R|dwG1p5zcjs20Kbfy%cvM*!*O&iqHWm8;9K`9ZHsm=h`Pp;{
+Kd$1P=cYE2|VUf+O(>lA5I4QZMuN{}vm>XZ|tG};u0=9CF<pCt;bZh*}ea1Vd2d=q6|5|nO1gV#Dys-
+-pz)}?Te@TIB{JA->Tr+_(pzKONx7{r6JA1a|g2Coja-p65aY{+Mdpu`YX(KZAr8Nwb%drNVc5FMl{{
+;8hN$zij$3aE96M|+L!62@Q_&f$0%_l^c+%nsC9@q}R2EyLr-ps&?37V48eeGITt-B*M;u0A|1krG)h
+B|?3;zi~@v&R!b`|M{x3)P@)y1-FKDBL=>oo!;-=e8*Q_R3@m+)o;<oUH7)#-GTOiQ@rHl)5`g-IO4{
+<UwB311Hp^VwCxjEnv3~Lx~|mP)#Rsd4O*2EQEC!7}t2+TZh}jB71=ai31;en{)YuUGNy3uq*G?(}<n
+;fh2`C;;sbeh-FmMB>J(EI6Bzw>$EqzrZ-{-R7y(4iaM!1ZY40|P)ii$I<6=I8>-IpqVcYVs_%U&w0d
+Keb!4)n-!Cr0GoG~#Qlk4_N=roo`!1>p#BIVo3QlpSLPVw8SKejqg}N$Qk3^g^ektEjlNA}Eh}LjLw1
+(Sj(_B$OQ1+gh8djZpsKJz+lA7u?*U8=5ZrkW&spNfeDMll`-I$t+UX9!9C=_}%bf}F|`_=M2qbZ6=C
+hlyf*wuSwdFtz?plG%oKWVKVpB0L)QeTflsJJVKQf@TBTB^g+Aec5KZO5eVOmDqKB840G*gBR~+uGG1
++=MF?+?G_7A@61YZuZ6qdjs#*6S&pN$FN}ri+6D)Z?~?3hPnuIZA7iH-X5@hGNtSeDm!ZrbnWigc_L#
+~$Adc5I)%#d`cIrAkc-!T{!_z=an6~8N>W|5&N;`*=Uj5mY1m`lFCUILXlv)3^YLyo52DGo`D5`Fe-5
+uOA4`^gh>=y(mwoBa*z1_}mzjg?*VLPXm??naNbWJ4wj_y{xXeM0<Gx|lxaO=9dj(2tF>$ugIGaIAdJ
+-FH9i6xo{-nD1>aGe5sA|3xTlDJO*As3eV2~`MWKYRj$4zcu=kz+4xod9F%&;okD1sXadJzOUB$NHA$
+mw;W*`9LWu*ZyxA(*=xS%lV%K(dIrnXhvW^`t>>Qo^j?&Nr~@IZY@kGgcKx*g~msgi!Td7lnDDZCVtg
+Wb8NXG0VC)rjbP}mNCd8G8iAl{3zh?C`KhhQFqz~NsBhB6i(WxQn-1od<PKK0Yw$+u>!~<=5ywtJ?2_
+0Ih5_OUF+&NgIY}ep?*ohrTdlzD3?Xh6!Dr>Nl-hbU6oXaYYrSqr?k%srPjXfR@81W*xJedI(LUHLAC
+(-B}j@VLGE~;J28&yBOQ7|e0p%+AieqoMzg^f%|1(37ps{k%NbWx$QhH^lU%z;R<>oAD$M(-Nu8org#
+juxyyKKwA;|`u>8<Ry*SOanMpdS<^<QPF!-!c#r&tvC@`$5cBis6vb4lG;YJ37mcJu->YUedsS|D;<J
+<e#4{na#ZQ2*!0#i{<|%2hz;?EfXb{W$1`%6|6~@>$3v?l}vY#B~TgQu+e?=<hm+9bcYXI<cXC<{Dz|
+eVXz_AMIuS;<iAakP<^ldD6ua%f-0zByKN0S5=}f-9p?$1>|EZ%=Jm3^glnL9BVXQuy>b?gwv|g812}
+S$@2`&E^4^gxp{<P7xNLgt~;m>c6($wRvhVJ@8a6?&{X)Gkas5%=k64n$wx|eo)BTl<;8PmPWgvY{yW
+e_-w;=wtO&B}UFKu`_SpT}B?Y;C+nIxi3H$9aR@q{sz+ARLG=e0fZxk-v5N|&6o0f^urIy)m*loU~aR
+*Zu^*U}_5nRxo+<e?x`ejPv)t9~?G!YUWCg+M1`m)F5t-wMs^s9<OyOwofL<uQzyRk}Nwp=+7yhndmz
+F7J6Swd4R?UFD@gP*=^7M4V}n=eK1IDP32*tnxFn}~HX^9g<l-+pSY!FhF`v@|M;gTuwbLWiBU{b|Bs
+$8hC<h_PB<x(=&nz7^&ZD96DElv2}|E)g4OeQdeJ7y2?RRjgWZ;`CcPn0*GQ7Kb|&1V0cPXngc{<%lm
+tTK(N=I3_OVK2^<KUy751G6qqyW51o0QyIpXH36dAJ<%UJHKH!jkG%(ltGN$tpu=N|2yxmQYSM|YC=h
+ACJ}uXW!u<Ig56(NWH2}qbi^ye}?BjlziUpYG`p$AyhwVwOh>a4|=JuC&u;Q4>-4xZg!T4427bGf(uP
+?jGvm#a#vPO4v(xsBGi^Fwog}}c3psJdn%C7@TzA0}1Udf7!tXyaBBc%EDh}FvNn%WYbp_wFEDJ01<P
+qS5JNv<zM39(LpNEqx+=iMNxNTPW5qiY`(?Y8xNNHUC+O4s1q%tkD;jC6hIMTL+cPHiU|z0^$qg>!M_
+UwY&&8VBcg%`U{3<$aGR$4hY`TClMmchK#zcagFmQKkI$yTro4Op^UH7+#?hA#7hpuIOo_2G_NJF&1K
+vTwiIjz2{uf=zYu#Jm}gj&2CUGK0ofQ%*aJ@a}N#vs7G1zh)`=p`A4oeVGE61aa=B0&)wn*JxvrFT%I
+q<Li2?8wa-!??tQpT=(^Afod6h!>#$hSO}|Y8{j43cj6QZ96#VV<aeqgS`fcsQs+#sVtBO*U>%lZOIi
+2XSzE!J6i(A1?M|`B*3l<lwzi+2&XR{5`o+)nJSl_++ZP8s*QuW(z_mB7}ts+(z3{70F6@jj}K;wC9J
+J$@I?`Osf*7oBam7&H@tdbbSwb*Yh2)>lPo@!3M>t!RABujRj(luT1(h%`(vgbAzr$wSdhb<d7nMpT_
+vVmT<X@u8J;&wCHCt3LD#8)3vNR`yPo_Yd}deN8HoiOsHDdN7ch>up`&a_HFIj##+f<t>p%Lu?<zKvr
+#Bzkt}7IFW#bm|ty=BSCbyg%e-akWWYW5ix*nqAx<668t_o$5*snJRUKklLlY?D`N~iV_<VG(DLLDtt
+@JyHH40glOfmp-`c?3kA2JaN8Kiogss{&EIGX8NB4Cis4IKfv-3dLjrLP%AK!J-*BCL4@&GSIw_thmU
+Q&F+km!0t#T1cL}jK+ysuiW1rGKg*OWll)WFCoI=i1BtvY4OTeUaQIJtvjaUri;b<P;Ab5Y>*DakWt&
+Y3xDr<U=9&2BW-OCLU<?z#XodR=6Ejr5AgOVT+wcYk@g)X;CIM&vkdn$vtl?@^x;h;8L*`m&MY<CVLF
++Syy`-tr--($Ny-kY3+Z>BExdXY{t0c%RX8`?#vtm_kB|$NK0?C9KR!kCiB={V1UgUI~@8NXXtsLK=P
+P<07GHUJ1o{B{a50LW3_$=$uJgVw)pmQ(dkf+DWoBW0<<nH9%;9a?gq2kt=FfhVx0<W!Jd;*Ca;OmFr
+xcl%s>4s0gF#Qj?{Gcf}Gsp|N+OaYgN&2eYV-+y=)4?WJWMU7fJP>C`y<ecT<P*NGzhm(V}$Sqfim#Z
+tI91kd?4Ca$uFzAWe6u+!Ab!9%Uz(cDX(bM4hc?2GgZq1mtgzA9H08kA@+Rp5GC$Qq5K3JOst$qx3@;
+$ohP%^_ZfOY<hbbZMpUK}Ri**y*UE!L~-T$|kv@8!6_^r6+75&(fHb*}6atE4TT$Kd6Z2$R(_*x+40L
+$9B<UYgBBW<$C$17@9_Ri<}c=3mSa`wAt!t*ye}JaCH%tm@X)b>{Uf#kv(!oSNjceAb<U9ohX#Iwp(c
+GdLI>~f6YHxf?h`Pm3;+P=gTpSah%tz>>rsFbf+QWqsTebKkb}K6+9(1w;eCk%16A)Dk(HI!lWRhh+;
+L2o~t40TY?wLOkbKMq?}k@uel9<)WZAJb7<bkVEM}^B%H{p5{Jwv>0C|o-1KE*@Db-tMLSZ{D)>L-Rq
+&?PC-jTeO53d1MnFA9QmxC0Lv;FW+UWk6j5b^O-&gHPQ75z<;daZW{vj3OvO}dklqv<cLIp;ARDZ^G1
+QL?WT32;_Cb{o*?S|=l$UTwlv&jX=cqq)FnnRx-`r*)#4*TqN^=DnR6sjwQAYoeno$n!QCnJShs<Y~i
+6n06wNnzx1{j`v-5ucMyN4CKFqxDA|N15wA*J0OZ$Y<`(Aa=Q&aZL}FuZTaqvNw$&T<^t?4z}q`#`o>
+#9Q(LyXINF7apww+$!QLzIeg@t5PJu)PV6#io#qhNh;Xss8#yO5C51YEss*r<_Fafos*ey^8&@q&L$H
+!Nm7G_`$ZF2(X;5n&RS`Q*7lk?U(k{|%RaEV}i1B*vVf*(}+wYt#jVOX@ziL~%J?x7wh`lOxPIDdR*m
+aR}>TEBhiJ2e98yI?o$cpcdqjimF5ML<d0HVe}5uYh!MR{UcUPhyjK`yfajxR9zp2d4M$%yy#jwp`yx
+mGk7FRUEzh5Se$Z>(B+t@K1CVcuxGV9VYU0L&eGbnYI>(lTpH<mEeJDd0G6Z=ft{y>g*;)Hfw1a*n~S
+O-XV4bGt#D{BKB00cG8=Mnx2)Nd~)^bk<4N*~MDe%nHj1^w~*`5g$lzE|%q(%FsG6^mhf&g%C>Z7AYy
+|HVx8}rITXYcSvjOJ!Ohlp9Dq`T+q{-3wkzjfdO35Rd7L26BqOZ7Z3|z4X$|Q*j2n12dIa8*Ztfbm)C
+vd?Uxnbk+RQiZ&ql>CFimfsr^1N13~$K5^z9IQH-6TFCj$?;O`V?N*hw7ABxn%I^`*>io8||>y3OAR)
+{F97RBTi0;6YZ#gwY3)Lh_;C4H@QelhgM>!dTn43uhw86<rz%&yXB!VH!U!5k^QCteNGPGN?KYUE2or
+I&>{Sb9#F;nI`B94<X9%%0Mpg*jSUBh0bV>czm&#Fv<)rNSvzDiCIzv{0CdQo1mcr8HqqlO_vuhBQ%_
+v!!vuoF|PEW~MY$nAy@mVdhD_g;^+FCrq297v?f4K$v$*JWod9H7qzuXXuT;h7T#ycfty-*V5<0x)#=
+h!ivu`(!0Wny|dDr!ulYre;3wAVcjgOPr&++ux^HRov?0!)gi1xlkhTOt%P;4u%fe)<_jxix|AlY&;l
+tXswiV=U%EwjV7@3t2rDMzQmC*VgSD5iLdr<j2rIrvNddx&!Ijjw2-Z`Aeqj|_hQAZmT0y_C)(QHBwL
+#D?tU~qLo5G6aG3oEZidA=Mv#>(xh4j!O1!d@dkX*te2-Xr|?Fy@1Sc75B6;^Bul+uOO0P8ei4S_XYS
+VLjGMOX*J8X>IVu!aija9Dc@D=z$&t`XL;um%XL3D(A3SYu&5Bdl?-ewVADoQSt0!Xp{h4}^6ZtUHBu
+2CUnJbvCRo2<tppH;P1p=Qh*rWSi;oH~I-3)d9)U%3PszR%`SdtGMLJE;KebDK59kF5yPMY{ex`xGWi
+N9FaFfR>3?HF3mI2mqNR`YeJyWFII^cB&QT)^ovtmF69W9u13E^#pRUj5^VHKR$PwCE<KHY(-fDzvWv
+m!H$!oGO?C+}`ps5cHp?!fjedoS%b#VJu|_|e;!+~Jn2dhQ6qkJ2CD!P7r{XeOc8N3kl_)L=!evRKaY
+U&?{pcK-de3+Ug`j-Bqlf1274dA1PkShA+Nse$uMKgZp)#T|1G&@aca6XB+O5%V(uNfM=&Ew;GN?PjU
+DI``Y4{E$EAQzd-MvO#;P}EW7C0j0i|n=KKJIT^KZVt<(Uk}Kn@YtM_Gc+d=iNR`nzE+pK=f|;CiUj$
+p|!ZYvVNx+f{%6ijM3PK5K;riWN7UD+n=!Ys*-}nMElsglVj&G8NT))8ihM{YTKW%f8?T3W%c^&D-Ru
+aRBEd0cZwNs@ERYYm6G|M2&72I>UUz*-nKc*g;fjk_>f$8BmH+N{dXKyKJId_@=L>boW{Mb6*^ay>yY
+nm<E14!V}pM66O{a_^AMQUp6W^ME@`Qb@AZ!F^u|kb)9rpW%Lg-7zemv0wW`L)@r|$Jyv{o4>{C4CFS
+V~@8^D|Jbku0AfsW(8zI%B{nU>snNCkVt#MYBpO0Vm?(vOKClc3+BHU8xRYbI#QCu-JA@S$YOC;B*c`
+#ScB#P@p=r#kh76`?ea-9C;zJ_z-+C)9d53{^T1+@pbSxpx}hlkqXZeu7;DZxg&q@B+bR&=9-sgfsS@
+6J$zcN@SiQ^Awr2WY&^dM`j(F4P-Wu*+^z%g%+RInQyIcgIXFKMC%B;5`?~i?^(LJ>HDhJ14D1SOuga
+)p7t&gDh@Slg>6`4#hsCjN*#nW)j`LLXP;`MeAm8-eCt1>k{<h}pjWMv^KzYpp-$GnA?gHy*FQn_T?D
+5H)=cp2cc^@#uj5BidZ$I{z3i1Va8trG)zyy_Qq)4ZSIG5V;V4j3o&D(RI1QBbtMMhcdD<p2;s}xnW)
+RFH$R;QxaJ(t%rYDtkPcnna3?{QHnO(^YB9o>#>jKH7$;&z&nL0AHWNMq&ja){L((h)1R|)pM=~Xuqd
+<ko>x)ATp>%rTtS>3hJcXf60%Eg7C3RDHvnTiQqmQ=aA>=&^pJNz!1fIjski6zrA8e3i~bjTlc({#q<
+waO-aF^GDnBnn%d9sZU{Sv}YkZj5G4YEy^P+osX@8H*p2(W6BbgXxZm?V?#~WU|(#cb!>uF3^{xX=R{
+sxAoMbeSyA7y1B-xB0qThV6BOd7;9AZu0oyiLEu_m=Fv}hL>y7-P<*Sco2xq42Ol*1%I5%VWVgpiGdJ
+QB5e3BYO-!ZH0dEJ28}Z|w&X>-19hT;Z-BpD;m%n?8tJ)#yZ8tk4e_Nk8+cna`QqPXH{)IHfeq%du+K
+3<bwcA1HM*O(jZwILx@w3N#LY@=|#GU5j5tWV=$2I!WPs9Z5xIG}(R~r5d=aJ?U=$O8G5i0JnRl;#WX
+KPOs+58+AwD#*=ljk{;K6Xx=NAC7pT$3}MNeA~#%*2=yE`wbiO;nuDq+_m*v1IWTuaQZ|R&;kI9iswu
+rOkH6cGhw8G4~hJwU3KK!(J=mNTWAjnwi3<AD`*&PKD`Oam2CW1XM9IsSs)&s)b*3v^u-YDo*|`^Fim
+t%!o>9RH>@58B7q@tkyRrHoc0icI(A0Ac{h2SsgVLTsP7bs@8Z`zZ!d#T$jQwR7})58njk>igf=#ayd
+fpGmS@z;$9cZZ;urDxT<}tjn!6tGWI7-eqPb%eQiZd5V_tWTq6}%+t4cRlUy<Ub%kq1=F~Q#gvR(!o&
+Jv9+Eo7OCV`AuC+?(B_B7;ba}Cl{&k3!HwW(h5Mc}e?cE8-<8FQ;00~ofp<pyTgf=`dHh6aEq@ddI`E
+T5p@y)U9rH6=Duz-sB!C)EN(*lk??#!-J{W*mBaW&Re@{E}p1EtffvrmK|7sK;b2HIArcDsAFA$-W}{
+)pkNTwAdknJ9#jAc0~!b{#)9Kn`y9?AoQ>a&H2gvlk5lKu?dOrPw`$V-luuqv&H)i^?lPkvf+q9cCwr
+z+-9RG;K!9D$<=MFvQ3Qah_JSC$*6Q#T@BDjUdC;MY04Wa_D^=NNIEtp7fV!Aay7~PFs^kwXKv8g+pS
+6pV$8tY5gUPv(Ja{pCCdv6{Gii(3UN2iP<-^Vj}D*B;mJn`df*l$Cb}o^WelF;+?wb9qdA_rvaFBMqk
+FNNw6{bZzTJ=~??NDs#w~ML^uf9OFI=BwImR%XKaG+m+v|v`@52t^yN^@bo(4(y{6hn~A0sL$xt$b2T
+2j(9w0lk+Gl~O)vLeWj>_L&!g(67tUB-JXY4jkoVUZY1ej)Ez&T{&=4|-wc<NnyS6SwLH(*W~~j7%p5
+nSq3iyRYj^*iZUxf&N)eWpAv_f3nT@R=XRUNyP$c8P}IB7b}oRD9Du*n46sCj7_*SqXyT0Q6|z0#U4s
+(FpX)t?{C=+j`Kb%10Cmm?Oiw44uKdDhO?vmBHdo>5wE**6@8eVd&lh^@OkapdDL#^R4W^;I|}__bA-
+fnC#AW=#dU$H<eJOWs{#j~QEs!C8|jD30&S*LDPps%4!4)%((xtlr%L_sF8#E!NeL=yRQh@)c4eubLN
+}~Lll6ChBkgPEzFc;9?Qy@S(28AT#`l*rU2hmvq?hjVO5Gi;|9etUYMSdz<Q$!?1E{F#D=y0d?vjqnd
+l-prx*ESM3JN=$n#+8@N|D-a6AM5%o~x?YeEmcZDz2bz&F@T?uVSN~v26HBoMsp;e#7ZEaz&6>nf#kS
+cB0yQOZt^i0xJEy!c+E`8=-%6`77E2U6)cSddequeI4KTuKM18P2%VfpM3|<J0A<7G|MZ-(QnClADds
+vd5wJ_F<t#3>;~*5y|h9;2Yi21^6qTTYkE=I=VC`|4K_V4O29Q4OS_6MA*s@ulk&wCr4K<Th3~o80Bw
+oBbS<tF>+~>&C3zA1BICMNlo=?X{=TYYmoFb4;5x&*4ab(QeNcNok3t*I*aAlj)bypvK0@Idc;PWoBq
+B2Pvt@%(DCQvjUH$xUZpCyGiWLy4v{GNTkYwbV4z8^sB5=w1_Sg<p*7GDjiu>+yEE~;i-PR-zFP~mlp
+7gV0-e?BxXLZT$TlL$klBEwMna#$yDv)Q``@Ts*G>S6r)!+4$*icbX7JCvJDWoZqs93Rg;LlpdVz@xW
+eSNMbMGllK-Q*Ppnhr76%k`^Bsw3f8QGqa1lKEDUrNow(Q048&QBaM@Dg?F3sld@y2BKVyicVIVj}mW
+>Q+Oh>s{-8OTjeYR??i4zME%-xI4$=M=*Jm4=9MP4)ifo#+g#VNS;8-ghzP0CuYD0~hGj^fi_~kdQ)j
+HkrXA~J@1x%q5wXv4iAuT(s^|nVKF+P6&sl+-m4H*ZaFgEZO${f@C<;km7LR;HqCN_qwn4caXCym?zq
+GDd;GP1H(E<-(Lv!#*k)M9``HO^>4%!zxt?43%DW9ev?&{=>)sL<@P23c*53D&Fthte1OWpy`FlU9FG
+*;(iPK!(;-ns}*em~+|m|%p8vN-xRCIuA@SkomY+W8nNt>l;XB;o`fyIDumgz_NMgjJV#7n&mf!&NIs
+39ChUhst#*Tw1Tj7-T2HX$0!V-TJjgxK)P<fnbDoJS^YU^!K3dqc8iQInr@BUHcTugK(EI2g@Scxj;T
+fzpab!m%bm$_&W&y9-6JdKeywoEN8GwIQ#C_Y(*0CZ<aI2clWAyV7&y&UjMC><!COaEJM?RvWcMVRuN
+Ke>w{I2>_RICUKPT;$U3i(Wpw>TF#EP^G=l4WKLlx=WTM(6XA225Yh}c_)YR<h9dS0d)=dqvq5{c=RS
+7*q$*!v8R7LfpXqiWhU+POAP+F0ooygdoTv0j#ky|SOTcGb&1T=nG{JuL-?tx_1CYRYRL1>sl^k}s>I
+^b*IIKl-np?Q>VMF>88v?tkaa+x}wiWN*O;x<p;A^H$z&vU#Z!q{%g^_v?hnxMU_v~8*9+y9QG(3t2R
+r!>#%r8v|wOr-_F+(h#|fn&+&9^w;8h_qD1?}_-uOJ!vadkF!TKqO2widpgvt#hTlDdJ9#pzNToG_t;
+Hsh4t!7&)#Ky7Y?5DS9fwG)-8i&c8b46lGa$DW}M9@KR3k%o0z^e_zt3ati%YRXN26NLDD41Whk5@zB
+&on!UuEmW|D6xkid=%IVJ;M8nZGY48^`e3&9tS-fcQCmM#ONU?CEN$Th`VmD|9rRs?ot;2GHiHTr$>0
+2yTCY^BVq}_H8R;>^=a*0Y<9n!5n7aeG#vG8&ovxV?@?XnK8&gDMT6TDXG4%BbQ`Sm|-R<<+PecSn0b
+N{Q>fcV12mKqSZT)dJ7M4>TJ)__<^j3iyO2@M(-6%86c+C1Zwn0Yu-_`0gd<<*N#8Z<JzG$5Mi{u?zQ
+o`Zx?G$0CnHO{TFJ|kHnA@tca=|OzCz0f)3tp(B9Tnl1z4ILFoMAp!u^VZM-XK3g+jlG-!Grcq;e)Or
+VqeIq>DD)<(CA!zEjB7n*T=RXCZp0=X9dU7rj*fjoM+buc!I}|ip5pw?nh_mO3FTik5pAnRM7mwQR3q
+xzR*m@2HdG`2qq%Ct-EFHzeBMhn;^SVb5%0YU)rbYZsv0p#QH^L;R3k<ysu4#hsu6EeR3r9RR3r8hYC
+42=E5}np@l%CRZX_#5eC`V|)NNfk;>8QlnB=7#@h>fvBYuuU^>2A8N8Bc~G)(^$<%nBU<%r-!FXf0S|
+2@hPFI<Ik#C@vvjh<f05noZ1BTBzhIU;V*^C(B$eDP|PBQC#8IpSDZ$Hs`OQjR!W%hal`32mtz@yE}w
+4Y;$a9dV@4&(c@bj>uIl8?P`~JK{2E*|<??+4#1lc0^gm{fcHp%V$DmPHDogYerNH=;}2iegVB3ms}G
+YTxpFp?OJL^RFnj^q973(%Kk9bh!_6ir5f>xi_KLdBB!fYjVRhF7kW)ESB?1K#owwLQ6zUI)re|<Uss
+K|OHd>5sX)iAs716XY7u9tYCE=jsYOJ%Hq;`H5NZ(-pl!8?oxRi|UibUeBDSWdqiwy2O6mPZ#fW8Btr
+)TR2oVA$9WrBhlysmdeqAx*f+od?GcHq%Xo?rQHx$i?KmC5qh-ioZM$L#1Uc7>4#5;Zl2CZmD#K^BT&
+4|I9+tQ4Pe41-U?A0RiD``fAmP4T#Q7A)HH6uc4snCoV@8_i%5w6gTSl$xTCe4VqZ$j2c>vGMAk6vu4
+88K#4TbdCCQJ0lkY+Z{|a|jiRLTv{ul5ZR)jl%76&4_xr!A6{0bFe1!XOC`7XzhR{Kwnl-*Xj_vg|5U
+;&5G8J+YXpm+6Oc(Avj4e>_ZcaB5)9FCBMt>|Ivo+y}q*kV86YtUHw@t4QuyW+q<e}-sfUYZAkS^5CU
+b)U88LLQ`SwL<_4EJC@qyH9Ma$!gwg>%)40dpSvr)hPI_E>T%WoV#75%ADdK#r(71>VmwW78)Y}eh?U
+JSHY|MWTw5@89GMi3>?!%pH$(a4Unk^qN#67IXm5uj3rR;2Z&YIMOL$&L$JRfY@h2KLmDdGBi!bx|~J
+jZ=VoM@>SD`pw4T4i2Hvx3B7TF2Kkw@sFwO=~f??b+<wrcdSF!%p)t=k(+5?o#!_rYj2;%BLU&%FQQ(
+$6V8oO9Kd*YNT;8&2w~y`yHp=Asba71>J+)I7vEZG>(9Dbi@bh_C$+obKITjMOzWwmAuFa0^Aj?b7W|
+lQ!}SJOMkj@N(wGA!gavKuAPo=imRjm+bCtrd6vFdLl7N=9|L~E@ngbIGJfXar?A3_E-ub~u<Rq-DA!
+J!1=;j&Ut&1KuZRzdv!8Q(qqp^R?Tq-m>IWa2&e^>pUYlTVa2)rw`ImQ(j<f$VYeu!}Nd4!I>Y%X05t
+UP2haKO*PZOPB|E0=}IFyq1R(r#3HPfkda@+H6V~JxnVegBoKcZ;|J56tcjA!kgjTe@5l=r6lID;c9-
+G7o_d>uNzierGfq>E(C@_hf9BEJ8ma(gf~b{>yaH@NG|u-`DtW$yY0u4BqFRxKH6JZsZa@*UDrQl*#v
+D%LKfT8p~vTsmpNa*e$E+)MEb#TsC|u+$*EYr$t8<a#~jig0DhE_HFMYq`I&rCvVrDt5V#<?>N>gb7D
+?mJ~Q8B`q~qQ<2nlN{Vw%pxDD6Bu=2&x<<|k)R&15NJ%>5`?hzS8uuG=!*Vp-p)bRUA>&znX%QD!?B0
+dVcp&Aw#{?-gv(!&dEiNCsS8#FHrd@7b%g(Lrh<hodNAH!t>blH5l^e-|rE=j`cFxuVTOr_->UA%fiE
+wpa>-sQkuiY=#XNJ2&L}l4N{X>-%u}ssnkxuAEafhUdJ7IRduAVv#a{24GX_rB(%MJJj*Ij6bA&*a7y
+Tkktr>eoH{s_`(dUw~#vMSBhKr{FQW!#n+8DMMYsM4Aok<4D7YRc6nOMYvGIsqKeFFR+~<+hXj??wy5
+!TN4tmy)Hum}THAw@W(;U&;UJ7=SbU*j1u(A};8|J&$$9-Bb>rEby$0giV$|524MZxPsH1a~h3b+AO(
+IDN=N_{Nc)Y$u`~im2FByWme=;A8~}dVIwFo`q^+%VS8yLRnI2jvfI9FBh+O?+5>G7#@)7|(x)`_+9W
+j2oOvDNo#km#hOpQsNs~NyK>Y!3Ux~CgP~*pO^WFCAbG6bgoJZW0Et0k!b%sZZ;<tApuV;mqoU3hzGu
+$OK<q-0(gyHO9<00-`Q7cWjB#1Cx(yzUUJsJ`EQYd7p82%O?DP0pSG|6D+yg0>5os_c^B$p=Q94J_t>
+oY3_TMh2R-7CJ;$<p#Qo-(<OJm9xX@k^7s%;f5A&L@Sqtc}=Lp`DoJ)KR1Jt*-y<`hE3>`t6;P#=B+9
+=d|^Xq&hB5oUb<2G^yA`sZlA|Iw9@bP2$k`Orp+QS927!Owvwtb|Um6{q1Lk)EK9COo9y3rYSmm3f8D
+-l#Wm<rY4MRl&qaFU*S{#RmDUf;~xFmGD<N@P6Ib;C+BLFG{WRGuyB-tT&Fiy1itR<?7Urz;u$8V`5A
+79#v|RENQn@>RpV5ABPwgcE-8(+X?ObdCUG_;(3MoTW_s7sX_{X48^k3s*EBn=($5^EXgKzbs5G^DY(
+*;$uH-W5Vcz^0OmIpnu9ehaE5FVuE(MZ)sK+IMk~r7woPG*Rb~AAw9-8on^-#6g?>*d!cb?m#vBz;mP
++0Btzv#<%6F$W{5=?htQ}$cv!cuZcQp^(@D!LVlMb$>!qA5A%d9E>AHV?v92-s}QK#@x~4bB=-!ztr;
+wlCHi&sw#vYPXMTce3CjopkYQ^?RUg<U`1PnSb$NYVHSIIAzg*Ah`Pr_bE2wDtZNlJe*wkTwISOb)kG
+6qy6k1q;u)&DSpR?oEp9R9pi=K+wY`oix#CcNzcRQI9D$N)R)GBnaDL@vb=blNlD8aRpK6Unrr**bWX
+3slI|es0Z;PM<LONw&z=5+Yd?FP;}WF??anDew}FI2vzul0nYeCA@Q-|#uCfv=##I$v<<;)?@~Fo5!!
+^+%K9y<u*OqJb+biV>?4gEL7sREv$z+m)Z9JJcm_Gof53}6>Q_Jj8CGpx4SNn>@VIgZemwdCT<ULJ!X
+ZOJ7uB%Jl^KnZh8QNlZ$0nbWJ|$()$zl%>nmp!IqcHljO2+(<b<-v&s{d}1V{ViFw|I2nGbljEOe4*w
+be>zpl{+bqPxQW%vb!{KuJ@gk;^1ISlt#Ig^2WKITPeTZqOo0v3kGo~CAKBDxRVlB4?>knu8-sR=~*4
+BJ(nvEmQ3Tg=VHp?!tS}4vgTd+rq+N|X&5eQZMvA!!8{jJ`Y0DuhQ05cL~{rAX3E&_l+PrM?n%nUj!~
+kM{|z@&c1yvIfhp2^bxkZn(_zYYjxNg??CyoH@QujMbwN1IX_WS#RP)6Zl^s0A<_>UG3pD}qRbD>Qv0
+@BS(_Fj7pi*Ck(^IZPj<1WWeh9Ex-2N4h$Ro=Fe}YLgvMflYk!8VLj4T5PCS$OfhQVe!ITd8lV6z~f2
+Ac&-Xs}tZvXDF$VgOoz0q9Z;K#L12#MzOG9r#VKZz|hoizo7bz|~gQdFNLgP_ZPaqBtnQe%kT1-WKAj
+!c|orUDrCVt5~9~DAvZ?&*IyIudN++^-h==Z?B&*H+@d^n^+zRI~exf6xU8Qz_sPqi2zknvn1l|XJ^*
+nlcBWc6Vd7Fa<7%vl6B@ezbB|urs;UDCc7JBrd(fXg;|s;*=}E{>bDY`b-GELXL;EB`~+n)PqU3Vvzs
+n;o#Kdkk&?b-_mgnx=SI9haL7kusahE3Sr{nlrjVS86(6Z=-{8orBHdFWK98KE6JHafQ_~<ny1Ymu%t
+B4BPpb4lq(?c3tvC6lrb!P^QHNo;4mnWPO~B3KPB-P?yV$>;;z|nYu+NqRQL`d&Tl6cpy=K6^+5zoPt
+O>9UY+q^X=h&@r?9q(*-s(T*+oe7}-;LQrwraBN9&_B@0e6fYir6>ixUC&ll)2TX{xetAER3|o1`c2P
+&nB8p*@N4oRG@%i6X>s2OTiY1Z$$ygvhs$eUBBY!d16RVhrKwxZEuIG$?Ct}8N^cRzgCW2W`=b2m2F@
+99-c*By#E$T<NwB^y;j4nAqXM3nIMs1F2NFlbp+25yiM>CfkdFaPQ!W-3?>*$kW4U-ppc-1U>(8J1lt
+KF^whB71R(_N34(*kP7qEIM=+1TO0bUL1%gU~g9OJ3>Iih*DJ;Qwf*Ayv1XhBT1ospCjo@{HT?C&Hd_
+z!6aEU<IL&JI!3?>*)FpXdyft6ql!Ji49B={RaCBadGI)e7sYnXvx3_$|HJc2t2$_XAMc$(lfg1rRC2
+pR~c;sg~vwM6q#g2wAKmzA@#uZev%!^Bdyo7iJVO)ULElgF>}I};nz&vaQF_3`QW<9uNfBoQ3fQyEb|
++(4|KJT#gupuZw=pU$SS3G5~|+RHwSjbw?;EYg|ICb4)H!zQy>;SxuGW7uN)8$<DnM3_wFZ!j}ZUh<#
+8<FZ`&W5Ru?a389;FqSN^V=P)RW0{38vrzi;>DMaUCb0sxq=nmL3S}dA)g^_@LUQpAMUxY@kf4a%@g$
+HvPstbdd<rM$T}a_`$PYMXkbMF4YEW5NC@m|6gqs>KgW@&0$oQ%_s(7jRs5q#3tNF_LEcfKC=BwtZ=7
+V%HC_Ov*WhyZc2G};ePa|v*qR7iFjnc^!6gIg|qfp-ONrZF0SDX}qoA-N$pheD4%|}gJO;1fnjgJp-V
+-_zSQzV!plb*qbBzg?6ET@MhB@NBY9J*X&l1$YeO%Q8YU|BrhA}V)M!4i*s@&a1{tSOd4o9Y;CUuZ9~
+p+nCTX(ZV5MMXvzT607lW>^=9`m@Zp+B2+jn2da3rF@V+(nXp`3+W&YinknTAU@(E4ok_f*{zuwB8>^
+w9ATT5ZMPOFZfTaxe2elj%`V%L3i5?Rid``?Y>10^2#;_G1AlfawW_JaJ!Wcg5$t9*gg7dZ{zQIxMH8
+$R3(ORYEj1(0F6<M%?9q971q;+RukrEK`uPXw+O_Wx*s+s7sPi>lx^}zvy5R0TuJ76FhTeugefx#<A2
+2X<(2Ze(ZyGW*eAvwq!$*u9H9B&PactBr<4n=xV`9w{CdS1l+?tp)X>#(EsVUQ@r>4!AdE2bnbLOVc%
+b33)(~`9?J12Kh-s1d%!rQGyHv5vL%a-5qr#n}yEM_qUR`aqPTe7uafd#d{n0Rdg@rISS#6py1QVT%+
+SOuThh^H2lyFs*8s|aThbaZ6x6~0cS_LM?@-eF|l6p~7l*u++R&?YAnPezLnt@%$S`4&#49U)w9qA<~
+fjVwDLLkvQ)7=+}o2$_c563GT?GKE`~NOQ3Wn@yAyku5_=L|Fns&Oip*Mcc_I8DOB_3_<l0kwQ~i@Xr
+xG85A#v-Jyg-t7<P=ot%D-Xq`C}Gecl2=V_qa>>_>mL*5pMT;W$pe|er5a*9L9Ctgq~r@EM2i^MxZE~
+0d0+(8$xvx=M`y%45=C^v}o@<e!<vJ8>4T240!+EA8|sgM;07D_UI0lit-AW?eYfCV0$yvsAA)so5=I
+D&Izxo;J?SewO+6*xhX<_J1l*7wbx`p%~qHo+VDqO=wgtp>`Wkm4>->Q_!Zk4%|bwWegB#a<=aGM{0;
+!dI8qx5cZxV<??zO1)S;K5_{ch*Cpa`gia}OFF_mbf`F~<<=SnnJwbqOk)Z)zFpMle5DkxR0=2q;HRe
+Lo!+S5S$|6fg;#E8t>riJcjN~y&HSDDjqv1GC~6AnE}`&NF#<put+gDrEjFd7rZ@a|;GZs1wXkIZ^Pv
+hy$#1ARwH7bOe;A9rVtp4-ZWaY&xjh#s{*Z!81UI&xZgV~YHicr;Wm9B}$}_FWdhc{b{YpBE6)Be^TA
+Wp+n(2`Ni+(lz-@`A>bIKIuouQ<zrrXpGQKkigA3}v3%@%!*L5z4U&A8$6_89I}KUa?*LdZObI$JE>Z
+O!lt_o|<(PZy(IjLp>)i!S5ea4&hCCF($KJ#vpzNbfl!ra|;hg~G)u-c>B*IGN4L0uSay^DddNDU0dI
+#A@G*7fm8WHknw`2_myI+#5~o8n~0$1@2@*73~ujOsqSZ$z=8*^Y||&c0HMeWMa3qfy^7=e%{1-lNn4
+VMmH}um{=b&E6<sT|0o?YF?K8^^A6-gCiHg9BNJZ~O=KpCwqX_hH2PoAmMUbwDivZ_82uTj<eHDH63K
+=cOw;_Oy;2TC#2;g0#r&gy$`qj%D}ApV8)+>PrMZ-TZ&B)|c@Abzi|8ZLPHvXk7(sKWm@$DX2Z=O7^X
+++gWcA0thRT%r`ZIr@Ag$SK_QNwGoYFx+!|3E00XjA+JUlHqfC|-sDr35N+4JaOY+2zldUO<m1u&hC3
+?2Oi=-7WAJci5uLOp+%`(6GQM>TV$ztUFznul2B^{2VYKkxXfz5aZz@=uLx_@6HR{{_$Gb(;O(%>kOG
+zpH(kae$`j&*v)tnmFKJ{rffg@z<69yx+Y2u9{?p?&j}TOK%h1EnUP77_4N~YDa0=U3Zr|*SOYJth;C
+ZhCknX-(T*3;K7F;e&o@|{`&Y68=u^?`KhO$+4Agj&%f|rfBXB3FTMQAt6N{&_WB!dzV-Gy+jmq}?X2
+GQ?(RK%_r3T2{trGpaPZJahd=(uC!Zeq?C9smzWDO1<6nRC?TM4$eJ|Dg;6C-wA5Yhw`RQ!k&*$nJ&i
+`_u@!}=^FE32Az3^~V3lsm-^#4!i|8HLyYTN&RMfpRQaR)^r_9DAhvET1y$4xxyxM7`_{T?s-dN2D1F
+Z-Xp?Du-vaXXJ{-|A(DBA<40dSaKtM2os+mX?#BS+F$4mSM{&$cOv%B8zqM{9MZdTYP?2fpxL)NR#6v
+W)#_?7ua%^Sdt40?S;ZkewUMBNt9y7Ld*DqWoc|WOA#xLE!P<F_?ML2RkEst24cQ<mE5(uq^qAFjl{~
+z%BbMN!%LD&%4t*;I&gGyS_zG_XfT$X4BdN%(30{Jip6L+mYtog(*-OmEL>Vx*lZkzF9(wd@NEG*2PY
+^qoIKWi-A`Vl$Ri(lew!_PF@Ee%<6L>nIw8ZBk!P@2tp!#?PQD>8!=Aq&+hQGK=wBoPSjEaY!sX;yG7
+Yu@LqVY>-(Xp0Szxzi%+JFj@$`IH;Fm>(WXQ-jWE4`MObU-xV=BBMUSX`3j7&q8wO}!Y7SUP1KKN!4P
+1M9udCnk{F{4tB2?g^F3n&We$dDzF5N<h5RcE-}Zm}-U$zRx(f04yz^YUhkGZx{s$d*YI=j0Q)If4{5
+K$Cxg-PT$F=A8zWT^nKWOmAh@zCf9s+Ju`tS6Cp{n2MOZLaNTl22xGs(fdH9*7C&Hp#=r`HfuqiAv+^
+KGtXkZjJ~G2T4=FRRpr<W3kotVhJq|Zp}LMdM9kIYZ#6?jo>nsFi=2llGgLh0WrfsG<kaNarL-0=rko
+8_!^oA&aNrQ)hk>vaWn1QFkYip>zJ+)wuc*~DmS*SJEJcMG3oM3=EE`cUaHze=I&^+c{!mN)l7VW(7J
+SvjbI6GT=2#2z7hCdeo{XC1Ww9>K$<Gi4L-k0pZo1uGV59mWPH&!6Ye<j1tlgxGH7G01*=CdfG_U04b
+eHDXvcWG!whXJ6^VMbNRcC@$B}^-2r_v?2SMRi%h0U~xD);s`*o%PH^l1}r8hv@X1N#j$WGL8!Q<|mR
+3LXRd3?$m}@(PwBQN(VE&gF61E{9h5%(~Ey$}KX4T9%N+$;mQU78lx<54v(b^NFPtrpdr}oD8Z0m0?9
+8EVe8zur6nPmDbeP)2<AyxZ&IE?|*O-I6Np?^i5M!VpBHuo2h$#+dpGpT4X-yFr{J79E%w<8~sty>{P
+1M<+G{JLdR4zyC`RIVV)&jmB+I)bBb)UZ4oyQDa;fC`Cv3-wK3F}Y-v4jY-)%3v0|$43vV!8(Lba2mH
+k5pUD<!ijaT;19C~H{f?>`5_qOmK9%1s(Sa`Fk&2+|%ymCG-kGisd-RS222V3}08`Io>znA~>Mibj%y
+mI`{OjpkT<7sWD5A*36SB`(<?B@PQTKG?&(^PhuUiOyZu1jz7>*r;!Y!UAD1y`omk$Yu&I_Am#qHGqm
+U9amG|4O|qzp{V(@+;#p`02LG?ek|$?8j%?_D_Dx#HPK~+`nZxMZI(7dV6#GmGOV(y({~dynki-)_-P
+VTe@mIWxXGJWNL}uyEVB525VU28P@9apM6UIzI{sFHQt~4@7B=VBS!AJ5~=4(W4*K~77VD9Gi=#u>~?
+zdp25(lSDw|dEi48jW{WxjB1ws`abmdW6@#%~v}qYRwh0B+6zatDEOLDFGIlMCE-K1dn6IQTt)MA!Hd
+ix2B%sWMDD|&^DNv80A%|zDLRTMhO)AK==UFDu*k)43VuXFlcM3-9t>V4VH_4u7%Nf7iW|>xymXm3T$
+<DB{1xP0a!xDQTqNTAixJ;wbfLsvlFABY$l&Ejalw)PeL^I~&qs;EinCdWgH%i3I|14+#p3{~WTG&nS
+jVZ`4D#)|M*sOVSC@V`6?slt{1}3pNR?3RT5@}e$kI5@2vM7n&YMwgDoJf6jW?mj+E(SEG(y(KRD2Nm
+qtfVosCdFo@|9FZ$MuecMo-eAIrNkwsMJLCL=m&h_EE$Dj%L;p6*yZghKQePZ4FzLp){(OyBQJ$e5j7
+g=n`p^cV!6ycM=lR5)iWrhTn=le=gTvQO!Kk@mO_Lh{A}0`^c3i9+uJw3DAqFHzHp(%nryWcQDLwj2p
+^0%lM8Zy7kdx8g1p`<wd#nui9;#{hs&j@I)3XDpHHY~<mKGal8EU1%#^~M{Fnke<#$($))CDPi_&S{C
+KwCWPPOGt&!<6ZCi_5yka>k>wjzaOgl4BHSHhACc9A7BKA$F>7<w}1_I4+NRQGJejgCoXY!u3MvN;L%
+_EavZgn6cD2h=v$yV_}<{X~0U_v|y;i#N{>q}_NEl^opEYGiJrnkqtVc=7JLUgb6|8}sRSn)R7|lr@j
+&%uK5&-~N7SRDy!(SV5BnkPDC<q8iGx*e+w0m$fN*7E2+!$u}`3i3(Kk3}I2}JC$-0iLorC2CG`VEJF
+kI%}tXsIUWh0qe42g;=#IHE+MGpcJ@=7{<H#*JYdhrawFMd6_uO6KqiB-zE?<toCS*%x~eYcDk`4kg8
+!En*({5v<xoCFqOFsS-J?hkIHa+0zKI1H#8LCD8KPx>BzR`3MXtn$Wv-Lu0@e5nUhhN*l}wsuLY}=S8
+;Om#XJygIp88DU3k8z`>jVpSzgg6FlgWsQ3p1=1PdTTdY`w}WHN%>NDNPznk$o~JXUVmY;M26q1uSVa
+A-4f)JB)?MwXa~8)_QmTpXYzcGY{8@E2c){<q>pwSbS^OT<+Y=-{%j+?LW`|{~z!ZE~tK~`;J)k9mio
+*Uh-8;tnFj32ChuQ2{|Z^!Mb|@lh@sKirG#v+bez@y!@_J;=<G`=>{oo*dKC@0&wr6xQ|fYqm}m<<vm
+%6GgWa<QOq<Y{h3PMd5ZgD#>7`_>?6mX603r%zY@Mg!FiQpu2%dVihrq+&ISVPy!fl~zEQzvvy$I4iu
+*PNzYi7vPZj^*0J$vGGW+*FL2W*=zoE_N-;UaU%hUG9OxeHfk8S_6c>j^l|8*Wvp8wZbA%w;UK3d&o6
+3FvbFJIk9aen$M+1&V)Y_59zxVX#Kw6a8)TPS?hrlXq-Z6v$ul5Cn3bL&-xk5<grDExsZPdwR!oqSSy
+a#q{vuiPkXQ>X)(a&+!d14}=ed-UeZ!yi8K<?-{34O=P4#QGIve%#L{7E53v7)vmkU^qcIK`4QNAebP
+KfDts*nb;`;iQojmae`w6M+iP9I7qOcU@yTgf=Yt730@`GLhuB^gG%`I1my%J1U7;^f_Vhf2$BgB2}}
+fo2@C}7v`yo*V0sTC&=D|#hO;JCOCS*(A=pdsI>Baw^#mmZc?6jRvk9gVBof3Dj3pROFqj~OpeI3Bf<
+S`CpD0a&V+03(lEd#J^L2tP1osh?5)=~5CYVN$NHCfph@kO|N#J{>@#Vkrgba%QL*F&*a$IrMnEGtdM
+6+=JX!c@2Gz+D;>u-!^TzOvbmF*?%*}wE?TA07py)FOW8on+6|2+Tt^K1Led|Eud%A>|N(a1HN0Q~qI
+@twi%-tOM%4?khLDo~#x3WO7{hZ=t!ij`+Lg&%Be8_;$%O4{Ch)N($leoyc`xBB`2AqD+^{Lw1EV4QH
+8j&ve(8JQTQttS(6uPyR4#VdS(sH;kHM?D=O6Y*=wguhP1N-$qDkcmnfO(y1K$(okwXvB_?>{i^f=(n
+U5cjWtEEADt+^kN`y_sTZh54Pccybbr-Hr&0L)!RL&4R=Eu?%}Ptqfa-Hd-8k@lgK=wY<3%M(J<W4sl
+Lz4(y%SMrgvR|hGqLTy%*ZZzkkzv@Wb>T)bw8Y9EI05y@&o?BhF8&@9XIuH$JHE55BBnw|V6s%H(;jN
+now+$ZP!>GGqvwIB_CNOG{%pIXTR3x62h;QbPYF?7;^gWY0YF4142^H&|t5CHwT#PuZnQmzes=Q3R$J
+T%Jl3+I#kw1Ty`erArTp*8}`?V@Y7+(xrFai2$eh{>B4*e?58cp?4j<oTj++zH}+xr33r-?-%drni+1
+FIn5ihg#XezYjvk6GT*JdFFl}ZK>Vz%M)|!M;rAcN$~v$|d2f{caeqW3-YNY?^2bAAiskg>_q=)$e*g
+XhyJd%Zk^Wc6Uw)_jId>hvM^(51zs3XSzoNHu@E7>6Zd|j!asN4_f%i*OXU9{3#ym=&-u>R**LBdN`w
+tKaStuXfk^frN<+MB=!8NnGi)A-=PTYThLaaq`=^CGXc-Uw;fOv2C;K1g-FYFg#0pxxvdMt0C=wdB_@
+c(erwEYc@2TCeM_ye3@oW7%>QFtRfm2b_X4P1DO@<$Sq?2Yh3U&j&ITcj^=3sm^HTzO<~*4VqU__%M$
+IAVd`Uf@fhDPgjpY6CP%IPZAl+JIsLUcxj4z61dTdV<~@d>*9m`mgc%@ZrN*Qc@C2Nl9UM+;K-U9$&w
+HJ$vrC=h&;SzAAY9lTSWjCr_UA@OdGYZC<2y`{K3$)Wn|(|HNO*+QEu<oZgYOsDKqy6=m(<ym*H@oj7
+4p@sB^Jzebkgzn+}M`Gu?%`%X@uK7B`4;_&CmOkb36`()0yrt_7~fjeeRPiMt^(~hmvk=`5YkbW`e|E
+#ZnkqIvT6JslT_vS$Xy*cw$fL#I9FaZka<#Iw9nM65VdBv%J|Nbm2ER2PRhqI`tC>9+Z&En(ZMcGZ6G
+KHn4rm~qcXR<kS=CGBS6WGFq3t4V%E?c~KF|%5&LVm1Rv4U;1k7Li@5yf6vX=ILtX0~=w47;x&nmuAQ
+vA0%@VgFSU&mLYipKW`vknO(bR(5dHA{M%xv%xz#8@8LXal1Gh@g8SmKjduo2b{%x%-O9+Ih*noXGH|
+lzu|1w_na*_&e{A^oUK~5iaDK5wqe5t_P_%Vu!kOch&}q~qwI+%o?uTs^^~aJ7himlZQZ(6$g;QJew!
+Vxevz#{!`aqa&fb0ZUAAxEKK8)}AFxA*4zZ6v{+Jy-dX#<f#TV@K$s_FWPn>=I_1A(gYHDg&-RU3Lx9
+2&lt*vGC_4R^R@c0a+{vw$%e_|RPb=vKTZ#qz8??esQz^`FZd>EU>r?BPxcJ?6Oz_#+2*vI^kDo<Hgi
+r<&whg1A0il0dFXHxuy6n`1-%+^r+M=Ac_D1Ify|A^wB@QOcx;+rV`Z4}=|@z+uOXDR+pihqdWAEEeP
+Qv7czehtMxP4Ulp#UDC=`Zt<F71A_*y^Z?ubu_nsmipUjYJ?wkX8g!7#=n@t_=(#Y|6v2;wJ$M#&MSU
+bir<&w(*S1uEfhbA;!|3+ITU|6#a~15AEWqxr}$MA|09Zj(knjoYsu7<3u&;jz8%G<`Pl)IKeaR%;)Z
+J&zlGw@rucVI{0AuhYZU)uulTGJOJ>(mo9#nmrZ8%@BiRAs{8|>zc<0*~A6Cftl)D(e{ZYm@yv+DZdl
+^6Ul~;TN#UDxW6Dj_DiocBFucP>zDgG-Ie>=tBL-8rk4aX?{Ns3?Vi9eW9xRp}Kp%m_>6rQ3Kc2NpnQ
+wp`6Is0iCXLVCJJ9j&0^&2=l{}N{x4slQX>nZ+C6n`AWpGxr;Q2ZqnzntPfMDd@d_^(p@ofQ87#Xm;z
+-Cpr^N(pqM_}5eXJ`{fd#UD)ZZ=v`zDE{pfe=Ws-n&R)E_(#3sH-FOQ$J;3;W_<McXz`tZCEgg?KcsK
+p0TVsG(c=^1<6~nJV#bY&j!nNQbl|}LArmL|Q&WhICvW<XCrfN>de|TYm^jg(_$MUAm=nfP^5&T6apR
+-Y2O~iL{(bu>{_#ns=!EE)*cgfryoL-83%ez~3CV<{1ofG4eeiYZLx#vHg!JuW=r<AZDgA_m_;Cs8y}
+EP{CVvVLsstF2PVvV@BXUea`t@D9beH`Fjv;*wgk-!Y{q$~KyL7oVN(2ZK0s0saKPDEw(eUrurPr+rY
+Kb=@2a2CQE;?yaLV`IVy$2HL9(>((*9Ha#_Dn<$@J|vCrQf4jfOHfC{A0{X@d*h@=A_=u0+9c}8%6r#
+lVTIhNwG;2Zs^fX2>|~=p*JNmIsF)sg<5LqV-Y|pKau`0V-gi{k~tws5Fv6<%b)O1j~!+L3JH`(j|mg
+Hbm>9?JpSn;{nJfD&6L3;^1ori1c5?NkAIBbPd~a-xH%y<iAs4wZ$U(_2?~3R8xtLUv#;JSd|Y}`dQ!
+Yu!7@qZuK1YY<70+uHSH%U9w@8$SkH=2e0t>2pmzQmP3Jhm5GW=kj3Y*B@{b-hB0Qp<ukM<7@{Aczyg
+Yn(OiYu1diwb2$;M6rej~{mlaAEmW1I3%k3o>h#*RJ#CiusUBX&(-P5vk!VlY#O&YdQw$0Ut260b4lo
+xc3U1$B;0il%am_wq*ivBI0&M@7UK<C}ZS{6p!-5+lZ&M~rFV?Ug<iO?>p27TzqO`IFSboAb)z27Sr6
+<1~<{{A0#*#jQZAW4RJGuElun%HtGuJU4afR52b|X_@F5dpxu37FM2PW)E6p*sH6}?8S#yvQc|!OhIx
+k?o-ZEzmdlb%gDU{{`=V@k37O2d+af`apOj|dGls5R(R!=SHyVm%{Si^V}*ZIKEocN@y3fZR@k*`7yI
+zT55?Hv#5Z5DZ@&44oj7rVx!rDd>eMOr)0xv^Z1D5XKeLM$FR~5woV`Tvhc0-@*`YZ2GKxAnYM1L5P)
+E0%I=XwPqkEcl=C870d^?-M_p;mhVYY!EV=wWO)PL7{#itH2Ihf*8XS;qd#UDxWO%y+Y;?JV^w^RJPD
+gI*=|7D85kK#A=bN?Bq{AZl<|LQoUhav-d^ynczfpr(FsXc=G4;?xbnx=agdh`hH(dWkAL7h6?Kz!D{
+Z)pGi1N#r{9HbxAk=}ds={Im7h3y>FduZ6uFxIp0jiEz(wIAA<0(9!w@rIs#`iBnf&_47A#lc_*y>X~
+c7Z^%$23^ysV~^nLZXDV{r)%HN&o6M0Uf)CO-{Zz!9dzyCFf^!lw*XB*-=TPVwev&z*9QA^p|=kG+P7
+;LM(wLl|Lc8wk}pN+Meme<SkJBl`-Kf18iwm)DE}M7!a~Br`h*GkdeVb$v3>f;U;K*ojE%)2p05IJE&
+6M`!XP|0T=bULhluUjJQ2ijMLByFkGeI)-wXVdT>m?s-}A`>_+l$Yx8A*bqfh}jPC1}myLKd5gic~AD
+WQUdB!$?{p_cd`_4q3323}=&lq<SNu)pE)#~)9le&?;zr%!+P<BvanPkqlf|NQ4aPm=jnU0vO2nwOq9
+cI?<od-m*cX*8O!v17*$RcH!U(!tgil*4Z+Kh!lk=4%EF7|@SQlvSszj2k>_)~s<O=^^{|pMLu3Jv5K
+zJ9g~g-+%u-r~Z_G^2sMypyFSB^%bZ2H-|sbz^R}8LXxB!qV?;KKKkgdRaI5R<HwJWU~)ZSE6;UI-f9
+C}P_OM3fL+~Mge^S15O(q6#Ssk+4Y)vl@NdAsJC*kVYJ<a(#;8%F1^_?8OW^<Bd++f#-gtu(e*E><Ul
+(|vJb99T_uY5=;K76Z(4j*j9OBRz0q!R#&f_n=^wNrL+qSKsA)DFZa7->NER0>ZZe22stAQJ~8HHVU-
+E|R8r}MU(Z@w927aSWK8;W#)EB<HCp5-)_+0d_FzY$c1>wfs*2VPlO=_%&}2M+MhKKo4IN%bRehyD2R
+<NWi_KNs(yNd+472$OiO?#!7p4a9dBC{5{?Uw+{~{q)n>fBfSgZ+!dhw_j0S=Mj$RyqDVB2*P0<;{I0
+rX*`9zJOKPv01YajPE-K?Djlj_g_g9aKsbAV>f8g~?ttHee|2^BTB^ss#1o~UVdu`B0)Ozw(W6I29en
+-u*Ww*GqD@d67Uto@hXtT*pgv%t-q3as=l%EJ7x<$Nsr_@*!=+1?xc5Wv7s$O4{?vwV{w?^QJ9my#Hz
+fFf^ytw8z{ddK|G@_z@VDN2i&LF*8Z(PFjPgf)?Ay0b0C3;CcduwGM~)m3cF+JB0DeO|K^+0N*M8*Oa
++LFNA96l?ALm2g#qGqL52@sQ>U*3&carm;&z(C=ZKdaL!GHVq?HfWuLPpRSejUk6)Q6w}_@c~FuAm2X
+0o-9n-GBMzmjYl%nWMacFZcko0B@8(>iEf1oX38`x#=U$jR!a%wV(5dy+p$<&Tk|d2E4<0-#0m5cZ~D
+K#>Pi~3;rbQJplYwQ0qd4-_uUe4!|#IUvfV22<I{Xpz;R|R0kv9=lo`(A^%g(&oy$Mb%^uu?Ve8)SA~
+CleLZ-2ZA3&wU*d&Q&_MNY87;sCd;}a@qXXrRGDjVOZ@~YMyEJDL2u&vZZ~a`RVf@FO-$J;KAsR*y-x
+MB^@y|KTdC1#xo48v1sn6i5{0IM2f5ZVT>qO;qlq>22d<EW6=|CF?pMmeuE>sik0#C}<oKGSe5{UmNd
+@9orb&&JO4`dp`sVxlN$$99G-;O`Y;tl=#_a8y^unz4EvZXaT!0T=C7s?<0=ob(Va>n~fJwa_0G<?B%
+Jkek#8eaS-znbR^!NYCgfByV=PW?<X01YarbhK6{t<iDe!UcZljmP*?cP8+MZy(3+FE9xtZu^e&>ECi
+b<v8a_py4y6JrmE2RonAExjjQB4cIQX=bPS^+cZhs{cYh-^}KfY@Zo()o|giD@JUNL!1v(mmUO7JfY-
+rCU+sUDKeKc!-(-*Ce=WL2(12%74d*iz8j`=_JdtpU`^>97g9fEN4}nY~ncAOZQXitB_v^B3rDs)Z`1
+kGG*TetR$D^OWtUl0w(I2RFf%brRl?LEXa*tO&kjbB4K9)bdG>Sh-G(1K$;K?BQIh$yhL3m92My5e+&
+!9nV&yY#O_E5Q3b3O<(Q286)p!UC4B=ccw_>;UB{7-Fd9mYdwb1EGwEuaDYL0h~9{2?c|u8QV=`;(DB
+M>IS|G;FlV_!ph#e4d+VkT_2}DYs|Hq=e6#+B0ZS+cRiT+cRWR=vyM0`j+^kouPlBah3-_g9<I_XswN
+?wBXrR9LZn4a}5969Y+4_GNNHg6#u#Q2ma|VG7afO!>sR#2Cw#<ptR@c!?H{o{ej#+t1@XI(a`U$R^^
+hwpT_rVM~oQJm&Pciz#noECU^!kV9cY^0yp%v>bMMk=x;G*!1HEFB!6vXB!7u$_%EVi3(@fQLj}C<bj
+?)>n;N2XG1bXvwLL3ijDg!*#~<=S<^M5b#tcARsDSngyn!2VS80LlhrGwU267X975X+j+gFd~Zx9VzS
+B~K?-f8475DhKc^Iu3NZCD)5*De~*%X4D5V_^(0&Wz<Q`)&NoPY((jyvG<rlrctI_>;UB{7?9-1Kz+3
+CU64YXb-?!trN(2@9{DEU(g8tuP(oZze6;<PBgr_f@q+&fc6X;o>XXfNTFdpXviJU@6IL~vSRtlOtYW
+?4`k99uQA4mcU$Lw$PDyh7)JoMY}vw}fBt!naghq%b#kS4a`ECte(<juyvi|(zrBiRptkS|(eQVrJwq
+mKwBN!Xv);lVEF8!0%Qx|R@}jwmXt;}LSWPsnAR6$r9AnHq+`9Y${=^G{|B0_lLCalt-Nj#c;RQj@)z
+G2Rg1FM5SNP7-QM{69c#CKd?U`tROj6tP6C{%!wT|Nt6q@+GM8i6wVGYqxMtro&BJRZ!GAY_?jPZ)Qb
+@>ncRsJ^`jRSxK@GCDb_t4Oijw{h}@nR$Yy6R#6?%Ei>!!eq_rL^alz1s6;g@#8I8vaatv~E!}cjm}6
+;1OdC>Yoz{9{XPOzwfilpYEu0>VG#(nKC6IKR^FH;EMK$Hn4K#N<o7+fBjmWz(kvBImc@4`E=LcJYx*
+B=L)4gw|K5N{sI1|`?$C`)B}I^*=NPr3u76l)5(`CS>mDLN_1SQPVhh`y}I%$+B4D6ikxZd>5g(*zkY
+oc$xc3S;6R?9p3a|o>M4$Xxu~d!+iW(zcI{fxuD|%=3n6zf7HW+a;ElckvI=7%j7Kpaz=QUD;AuN={D
+tNlo0fRmvpU9jNNLaOsV)2({%^niww}g1(^UL#y6L8oSy@^6nVFexlB1#?o_z92K6&zFo|2NnD=I4Z{
+rBI`@4N3lfe+^Qz!x;2FF-$`(t$Y)Xn;HgAEGZr9=lwz{G(@p|2h8N<|R#Ij3x3I1ML|y>EUHbK>t_g
+Ut`CPbtWYxtpfiLuWz7v|A?(yx4uAan3Er0wrm-vHo@_J>#etnF~Ym=zAN|vxC2+zk;+$UeSkjj9_Be
+1*P$-Z9?+&md!~BuZqLuQXwUn%J&tkUBUi&bk&%)2J@n8+VjTo|D{YyVl$79}M&7SqKR#&CAWmazfeY
+|J+wca^ph8Pp0N^P#ZOGOS9-GhKE;CX8ERQkJKR>@BhHtxfA^-gS*Z8@ge?Cn0ebws^4?g%HFD)%SyJ
+5oyzIyfQpKrVEHlCN4C(51Xm4cT*1KI`X1a6?CB`sKkKtBw=M<0#0g7pZ@BjJWI66y}LwDJ)7=f6Z5{
+nqs#M5ea;L}6j!SAY7`pDqE<w6rt<XwxbUH{N(7U%GUus0Z{J>e`M<2k-^{>Y6X+1~Abc&_>W6TDEue
++1_&x%%9nBTz^B`0{;^)ZCtf#)yHV32?+`O&O7fE^#B@x|M>Ca`HUGeggfd0G^hX?)Oj!FVi;e8?|~;
+w@DOP8<}Hk=5T0bopF=`IM!x#$tM_0I@q6$GZvwzeSZ{_K@WPt2-EJ4{Hzp>An@lD?WXKRv5Aa8vmUO
+hnTWZ@-P4E%q0r(2?7<H$vZxBxS+;+9!F9iNX_u7#oNA{&MEJb^M=bd*14JaS18&dlaG-PCC@WjMK!C
+RX*Zx;BYtWoB$18=kg$RD_4YzqFtSR3sCZ2)Zo=|Tn*?w2T?(%|4=6V>~ZyLRo8nEcHr;A-(lzTV>>w
+Oj$1F9IK`TTWvO>?#)Rf$EzRzX={dAB8ej<EZP2kfSJ5$p4pLewqL6Z+{bg;NSoLcM%U|P30t!Y@0)U
+<eh~3PI9}O$=^M$_WO+(zhV3X`A_X}9p2I2U;-D^H`*-msTfNvUc6YyR%+{_e}k+6f2(|mc7S$?Isu=
+c4j_}g$3w6qUDOfk1N}MCi<63wn|@b`y9a-7UiIc-Z{7xOpbI>Nws7~|cXN_iqM!DDfSU@4133d(ga`
+bCIS~N3gRaLPe;jL!Px$!w{8rpO_^ac8D(_OzpvuM8=s<Zx22tNF<_X{_^tG+5=?nZ(H|iJy-*v$E;3
+bqf+R%g8%>UcVy&3-A{0|w?vX5;^3rwuB&z?P-Kk&c<g1^1XT?K>#FM-$bjy?dmtKUaxT>IF+fV;rod
+;Uv(&pPlW`XJDuuJ=QJK-Qr@@}>i2``T--@rNINSn#vjh5?{kU7N?a3Gd(;_4@(I%x8Rkeg75QJ@|X~
+i{4`x@3GC5>ICq_6HkcvpbOza8}J2hL3V-`6?Yn+KK(oS{WAQ43$-u7|I~k%s`IZa(W0(-s^9NWH*iB
+esNdvJXOKnsmVj?ipar;79=}J<ToHfo^&fREb)`DN_#WdQyyLqZ0K5fr_wL<7?xGCPUcv9cAMJqnaq}
+ODyTIRj{gdQ`XZ;5>pzp-^1@aGkfc^-5C(0OePLw_BL0#WPJ>VTOAF>v5jOG;Ly9UwxN8>K=2k%~q&)
+ed6Z&?I?b=?Bx3>v}f#7CECj37~6p<nIs2jh+hYE7>FHv{s(zK1_V1rRTx&Sl5arHw3rUmCY`>2b!!)
+ygK>{$SHrF*S<G{vcD+B7LuXOBA#6kHEiJF}ZAN6w_BR0~AxQn7tKqoMIL$CYMbO%;x8I4D5G2*xwVN
+fFHZUSP|=e1p5fiwU{sB9bZ&ht_QaDAg^E=`-W4WpJ1_ArqFmlmSjG*VPo4F#@yYQ7oQ^SFB&*s@(t&
+4pUB_XuojGO3O84CKKnz?Klw@EawQx<YfnEvzfm-|yPeu}1LPTvIe#X3TSIc`6v?HdG(LZl#<saM2F4
+kNVFZ0?ym5Nr3Hdu2)<W@}&#0{Beteem17|oNw@c*z;}!DnMKXL7<=No<Jzd>vqOPASWByA7XG!KBCb
+{`062>=Ed~d{eE_`3XnmE>C|53;J!Jn?`TW@d3>D8-OXWVz+eg9v3R~{clk?$J;Ib>ISin?!c$wO3Fu
+0E!Z>aOl48ii=YEP)slgd`*+kc&*<0TMt#33u>99`}ua5I~My0l|mBD!N><E{h8yPg#^p@J8qTzBSV@
+L=g0Eiciy%neM9UU;XZHbyYh00N)Am1MDO8I&2YiHGEn4DfkVaQ64{f0WSo`1H2PCZQwh|$pd4%Qu~M
+jC<ZN}c%e@a-y_aNyYQnylOX1S-xObfmp%4r6z>C8_S&gSr7kWiC#&&;Xg_}LL-jcipb6~P@&DT&SvV
+qH<S{42a)4RKBat4*qPS_=;VAAK%pZv7N8m%i89ANbznCYRz@||Ann`|cdi*>Lj6Zx}^ab|k^(loS2Z
+nqwa`Hj@IG#8b#XW(y34Z(_inRgb0Y3tx0@ewfu<JYG*6l(2u;Uc(7nPTn_ld{51Ai80_}0sY-Y0U2$
+mb%D7~ejySK!BwR^!KZF^mRSA225HW6KRu{SdSd|0f<Rt&YE=FDO+pd}8i^Xg>Dr$zzeHPG8&y@MC&4
+e)MCQsTSkMYB-%}pW>v<DO0AT$M*wmgU@kB0p5n3D)0s5gx5?ixgutG?7K*$l=|ZCiehb$3E-Xa?ZdA
+aG-y!Kuwldc#AC1M1M()I1q$-(z?xo-;eEiFkPihv0%HQUF(QU94atrkFFl<v`XKmm=LPJ$di&L};OZ
+DK#((oDU*KK9ijdPpZam;e<i&xn0GkjPSFHW=UJr=2+Q;#uyW`^Vhfg+o^ytiK)25|E77_2mKgV;UFQ
+5U=yXWQ$+z@yb@~TT>x$T)Td;u~6d<0nG@SLRcG(d^h(ZFuw`5&@1c<|sN(*Jz|d;oC)Vmr_Tx(Bp4d
+-NZXx1UcHI05q0Rk8f~yf~Qv&NMcLlMRdY0Y&g5wcCx317BY(|3Q2PIfTz2kF&&Mcc9aiFrz(hE*BUJ
+u)2}dhoLd7F|PbX|DpY{W5;IBm@y+A*bw}2^dpF?gL#AK2WSC(gx^qr-!2<`K_)K6k8!+qN&OEWd&rO
+>MWaTIDg+%SPMj$89`r73AM`(X0rUVbqV0Ih>BQl^k>iK=kxW$M$AZN3SlQ3D51WEK2XeZgG2$zd#q+
+uJ>R4DXHW-VyCZ$GB9oZW>`SHFB{8)B@AEyrOismnA|Ed1#g7(wX(?9ZkU*uhZP3Pz5N5+g9BjP*sDb
+NLhuEh9&HfN6RkGwa#Z{*J-62)AAfFI`!dLXj$#gfQpM-D_Hm+^l*&(qqqYc~kbF?8tA;;gK!ZL%y!`
+u6QB^1u@&Oc1$?Aoc;xaR&W^xs9Mlb(@TWI_bLI#9Ke>|Fv%2x(ms@hy!8kfy)3}B0nqg_~Va@=e}I7
+x%$`yc08C{N!4TC^UuHFPxMFI<bNCkmWaG@a&ofBzoHNQ`t=iZhdu}}l7I(-9CE-9WGBuQ6cqF(UJjF
+wgcrLJ^Is{ZY64mj?JM*0^0orwL5{vlmo5>E1@JYp%jfX|&^_S8V2(&|CR_C#(ep{FYbM3#$ED~i8&@
+h#f*e2UfNuwSBbN&vL@ph;2IM0iN5B|BFW^4(1+;+PhR#Gk-+1GViPF_!6hi*TjT@Iad-m+~Am+w6qY
+u4%_l~q|*)r0xV@J`qAnzC8L%0rn6X*-fOI*2fC6?A~bQNuj_R%Kv&xjEt`k+4K<YDunbAT;$@7`Tt%
+#aIQivk)1IbQh7z*OM3(=$x_1#O>izj_WUJ|_WtR9adpbOYw926;t{7if*=hECqIXU~FP*tTdN?U1e!
+`u|e>2z=lbD^^6NPoFMw#n6q&IR%*FuWVbik9Gq43tqzW20l1sFTf?y2k;m$4&<NKu3a0<6a2MppMU<
+V$$>)8K=)ystE#HNf5(Xyqorv6<kuFwYtryn9+0mq>9@<4b4`Z(hiY8(?k$chy|Wwt?(X^fr07w7{gq
+$v-fqHW`$_h&$>n|{e!Oqy%$cvvnKS1r(orYo&!7L?f&~jM(mP9+E<H(g6fa)9SbR^{)S5eYZt|>Ivo
+^l^>Z@Wr0~>~MCYjzBe?RcF&6_tP&-y*paftZuEaVWeG5B>E#UN?_jLw7d$-ka@SX8w(xF6Sor{Ti|{
+!AcK&}BXT9gUgbpYA5NCbaD$|5$<zMq7}zASR0U1v8IFW8k%4{KO1@Nyi%KCdd)`8ob}JbN#%?q~fS=
+m>r9q5I-V*MXZ2WMW$G33iS(ED`Il=9sG}WUm2P#e4H~BgH1gftpl+*VlTvgi2D$CS`>G}hk;LpenW4
+eAcldzxa!4zqK^3T+4s?$4)O?y*+4&x6Kqg02le%5?-%|S{5|-3@HOG<BHma!ZM3KZF-HgL2ga{!*RB
+HRh7JQA4sDqoSu@-f@g#hA`0a=r5IdFUv=?op9gIX45nZNEohtl6%n<>uhOq>{RQJVqZmtr3e|h$KpB
+oRm8uTN(AoLb6Im{mjY$?i$p<d+Jp*@10h@qaz7ww-7#vi-~T@OCRSa#~vNzfE}8e{pdH|IoFKHXl-|
+C~PXp~%~RS%~{r2lsE>xKa3O!F(L(ZTMUm59rhQzTh)#c|8B)`e6KnIZ3Dsb`tHw9wAOZ-O$Tq`-jEf
+4?T^3qaM%#SP`BHHXHdQ+>1CHwtLH#Ef?L3GPKUp#D;W8HDibLGe>Yuo!D_BzONzGkrEObiq)R50$UB
+NY%Ko5`fJxoSg#l>2VnKJni5tw#$Q-_t(GLqQSF44*J{VEOc3j?T_3wLL9Dt~N2*&B?q0f-CiS5IvCC
+(glq~k$>_O*_(gXAvWkao#KStNVt05G4aQ0)*TZ{fxPq^laUZ+WAQfX|b#|P+)9U_zIuUx5^uDMrSBT
+E(?jE<0$B@(9(l4-0V-AC6HN+nVzT|bC=6Wv`NB~9!iUlQAIGNsxch6z#^DJ(vrJR$v_>I&LU5<5_4i
+$0Zz-RO(y&a0{OezB8eHho)mey>XuRjL<Pf4aCj99OR*wGoFb&LQ!gOk-6;(4kCRUnKT5z3_x(vE5dK
+-7EV@chdDK^trdV5|k++n&2sVQxD4|=@Q>z*Y^9Q7Igk4^s+?X9*NbHAM0E2d_|Y-V>|3xEv1TmK6_F
+9*>uI#j~N1=dOx|pIyEmv%Ot^%=~Q3oB{&R8c(@y#=~wVkSnPNiKkoHvRn_8|;c!l2R>7czfrSM{VYg
+}j(jq&YotIOX8E##epIurUF3v4$on2gLXNC*g3{aXT6lNCX=jMdV(sN3~`Nc(UQ>BgE)cZ~Sgalqz+C
+MDz=ef$-wCH_wXE-Oje`$W%pxEE^O=(WQ{?tlNuhi1~0r>?vy>r6ne~kb6ezEB!btENcKu$qI0seQJW
+`>iC1{C+rDQ%k2KR+=WTd25Ab2AIVIZZv@_A)nLXuR#^Tjy;r>ML)1{-Nn_-Zr48mztQGn3R;<v3*7c
+eSq_HglJx0PLv;$%j6~U7Ws($wcJE$p(HAG)jV~O`i|N_Ypk`<(zG60v9?Ovpl#Q7X@|8RwYH&gAy@C
+G@6`Xx;6?}IVI$ipFiMTF#$;oWvCLRyd|;d~8kw!kd(BdFygAuiWxi$ZHTRo`%zD-zth=n1mTY-elJ&
+5aX7#jkt-jVUYrOTG^@;VZ)to)Yrn8Og0E@5;JJ%j>Z?w1B@7W*QKidD{Bs+ypx$~y;rQ`69Jd>C5=l
+NRxA@A#sb{Dv7T+KV|mHQ+77k#*e!|54sly8$;$)=p4)KF#BQ14eqs$<l7>MC`Ux<fsneyo0>{;1xdw
+bc@}N3>pAk@kYNP1~m()M|#*P$PYz)roCo@3NEZEB2H<#Xe}Cws$%IbdEZ=^2Yog-iklWJ5x`3^KaY&
+uYo_*pXAT+xA{<@cq!{TxslvjepsF*Z<jxke~|yEJgQ_VmC6idq4KHnt)i=sslC;S>Spz?Y8`EEXh&$
+Lo@!(m`9^<Zyz!|q!Mc^DvF@xto56OnZ&<E9)_&QZZ?CX7*#B$4Z+~bXwc9!&$8!b}Wkxz<oQPAK-@t
+F;xA8l8Gv1P`obh(NJ<%(jKf!Z}W>50r{8?Vfr|@~aim&Ex@wfR-zK?&-&+zNqH@wqcL%*&6oWI)tyM
+NdhN=59Ge7oFS?j&c+CGvmEqvR>_4EYQBw~C@9DgBfQ%3)=_x`inEwc1hZuRW!W3!Ml_`UZW0vD(;a9
+A~mKm~ZCC`Hk)oPZFDHG$3QuRq3u|DmhBNQb@J*S4I+T_9+LHPn0Lsb?V<#Ka?686Pg^F9a<h*7kV@F
+Rj7u3gWgPUqbKS)`ZRr)enjtV^fUfqv@koE8_d6&2h0=1XE#~DBQ8s}a;ze&%qq8@wkBEYtdFcOtm|1
+PHk<vMxwhoAaTYk6oLx?RZu3MM$u!=B=kOw4#>@F=K9Nu6)A=iWIbYAW@*PB>Z}@Lq%?-PQ+_~;6?sE
+4n_d~a)SMJU778B<k^E99NkNBPaZhn@Z?-%<6{2~5Gf2?2WzwFQUU-eh|YyA!WX5x<>{%)e~C;mCmx2
+IS)mw2VV41R4aH<Me)vh2%A@`G}k9F_;kljKw-UFo6ZDiz8PN^SLa^-i_9YO6_VvYMk7tIw#F>SA@Zx
+<P$c-J>2+@6hhi9@aV&Klj&WY4?V@gnEaTg|>!vhCU0O34I%?qdR&By}Ld^U!s4l-({p2U5y^bXk$5z
+)<L70+0txhjxr~i>q&CIFmJUUurjP?tyiq&)<3Mn)(Pt_)`r<E%!aTE_7;1O?Pq7$E%qIDlKm$;-R@=
+kP8P{(rE}1^o44jBPv$)ZT_^JyB(d-CU3@?B!cFd<-1$Vs>xtjq!O|`QdzKYbxnJ!@l6j}LDD;G$r#C
+iQ8gr;`Bh3kB8>_&YVQsY}d%NA&8SN~0ZsdO;9`EQw;IW5plKg@4d$m33v6Rp}(n(8=D&sX{ow457WN
+bBlFzTCsG?UB$<_xpK3bV0nIa|lixu!qZU*K=YcvMQ#5IU_;8ix`>%|gvXtwJ(6@m45X=SD|kgYlhF&
+rC5NH8V-Wm77z{_f6=rKeO#jvg_Lq5e0hM{p=w&C!XrUAE#%}<-7R@{48(m=DB6=2)BaxXPLX#{o1YN
+HS})x61-Mk7q7b~&5G_HQ(qn<e<{~h?opVMqC7$RVx#hWXf?@HBVE^hJzalNpP@fwWSHH}V$!m+&4p%
+T>nYNswOJF^oaM7|YysOwe6HG0+N~Vbv78Q0n)3|F_;0;Oy;I&MA8U-(BEGZb?($diN5mJk_1p9o`Xh
+R#9@d}HC+n~1uj}vX2ldl>O{0-<kFl7f>#X^`S<|X(HLx05%<4h1HPWiE##xot3)ailG;5Z1%sOSAwZ
+5^=Sy`-*_+uh_fxXP8u?_4~_B%VlZe};PTiLQ5vMrn2&)VbcO8W)UYMRr>DRKHcBb*9nyz`thha~gwf
+`eL;RQBQh_yCg2r%7|2=HGFNXgJwjNK{<o-tD#YLf(B|uGiNq@kWs>*7h6vxB7ScEq(4M`45szKIZrG
+`}k#kxnJRr_h0g7`AbOtu#k0za0dTVo}tWFmXMvOqu#7OsAj3B)l}__c5|qv-ioMk#(3A9ZoOw6A>L1
+7AF-Ql$6ihLAY$u|@4W34^09mcZ{)Ui(_E@=XLP-rzH*jwMm4l7ZG@Jq?>6_59sHMh*!;viMtZ8)8e+
+X@t+Gy9w~<boZ7;CbI`2E#d<@^n-{Y0;OYR(ZiM!GL!L3I;(#-ptcen4*Q%v-wL(wGhc=-jnp>ms2s?
+1c5D{IuZ$x5f`|D(^+m(kem*Q<;*#_PsrW4CduiAB00A9+fFQlgY814-LfDC?C?$`)^jx7R!19q~T*&
+U)v(T7Con7QeCI%x~p~1O-!sR_o;#h+w0Jn1sF8|G<|T))4f|lPly!WaEw!&o);=N-DKbsZ=RDl%2{c
+r6JkgRJBAMqP|SFcawTZm9z$0bFG7xr&Vb4v_;w$@-L2RbxGDbg!1rU2{k0Kb*x-hZcbi7D<-oLvlwU
+Xi25B^3QJ|3SqAIIda_<Dj}@>IR>lUBJ{rzO63>lel`*cH#pba^Y$>Z^ud#J(J=?^#keu!yYkG(sVMp
+2L>=Zjomh~LTZY{g6-N0^W-(ufxH~tBywj=G<!A`ML?ap?F-Hl|tmz`%9*d=zEJ&>e*xINOYAbb3cUD
+vtYY3`&r8BRB+r_;;HbIP1U?h*H>`?)K5wY<7s1Csh%XiOWE<Tvvyk9+OBB(H;);-z|>y$r9Lm**7_F
+PC`(y&>LkZ=_e@RgZ74m22f%xmK=~Yvq@e{|8V@0|XQR000O897^_9oCtaWPCfwu0LlUY9{>OVaA|Na
+Uv_0~WN&gWWNCABY-wUIbT%|CVRCIQWq4)my$yU+SD8P4?wy(B&P)P%nY{4UnFMGj1JnXZNNQ_tLSGW
+7?UJO`t-DJCRVRSj6j0JyGXY<QrfP?zqQN!LTFuN_rEQ`eZ6(0E8=BQEP;1py5@_9o&=v}mOxrNO?{m
+(*nVZQ3Q0xBxzt3;;VYqMSJm)#j+j*Yz`r*4DVJ60y8NX<hv1gh1Q`zPJ6p68E&Yw<W-PT{`JuBVz%e
+-1|!$#M=_kHG*_tk&OwYL7#pZ?4y*P4&J?%VunSHq`WH{DU=`qXFc`S`V|skV6<jAy@n=KlA_It%pQ&
+^NyAzR0f~?$7Y+F82jof9UUUALG|u?$`PC+wSxH`*++Cp7%Qi-@>)ZztcU&uXP1u{Jl~jp8uJ@uWnfD
+rE=oy@^?2gc26jY9iREe8vWgAme1_+v^nfqRMai;cO`}RFHMk$zoC1Xu_XGB#jea{5=6zHiPg2}ne@x
+#=Lxs0@*iY&1KsSES#B+^yKzl5BuF!{o03q>3Ypbjf=51lFOdu{UX)m`JazhOH+_7|CR`W(L=p&5-OU
+rzxEQOu_P%@SH`O!toks;s_6=O0lP087@$XuZjFrsCfA^x`6kMz2_;kJ3-YXLFI-;&@8m|8|DV=)leH
+-svi+fHJ(1zWG>xM+>KEB~INJumyS}_IJ1C!EKOihXZH~y}Z*o$d03#7?v#L3b|${DNeHLZSm?17&L$
+4o4se_xF2;(U>AF@C3Sm4a0YYiI03FA<#RHg?$bUEh(lOCEpggoy<Q?NSi$0tAbGdU<DSei}UgF)4Uq
+tsIQ3HwE9_Xbz4&U<r;bmjWCAP7QAUXnF8+brr!T@ABXS_udq&cdHSVl>widk@hC!S&qCFfKeViTk~&
+S1p99RQ^(iDr2b|mj~ukI+Jh47&SSpFY8N|$I)?J0dTUr(vC9=rt#j>5UBi@O7sEZHdsdv!)KXkajqu
+|CDtzpW$--*sy4K8U^IX121(VJkG_l&U6!k5rL~S#!brP#}xsKg755GLs7s;#hMe1Cgx7~wZ1(VO@N2
+9fC<m-x|vJRJ7eKJ3#{K<KaiYKq0z5K~MCI`mznAwwSQluyEamY`8Vz%kYwfIK)*IYz?c3m-*L2%bFc
+d=_X?swC@tJrlf?(e1hT)I!eeac^3clrZvt$C+AM~S8;+;0U<9|PRHG<J9`elAxX;JZ>E1N=M%@9=Xm
+ykjm=&U>p%*1YE|nW`M3>j{m%MCZKIyGDt=Ci6u4_JY27OhS3;ZFHSS*V8*k^G>&ouElemi`_=odvGO
+sJqCJB2d#nsVWKh78nir2bSL`jd5OkEYoa;PUZ?eApf#1VRx6X>KL(oT`A|pvT)XjZH@$Ne=c#yypX*
++{yO-YO7U#L}&c)w>7cAv3rCIc#ba?Cm334w({!P#WGxWg%y+{h?F*P!1Vv)0u^>ZdEblxO~-Zq&+$M
+G{qqdNyonV~_G1J7BZ6Q=A?4Rq~J=-Nl1Ykv=2`xtcXAE9dux<)WAUexkTS0UrRBWJbecQ@XGGH*uNH
+vxy`z@-BETOI^%fy>E{Y*x3dNnwSr0lsQx%l2rx^4LOk$Lij)Gyeg3+Pz7=P3mg=bUwTKs(gtRKB2O}
+6Q@4E!|5{pdiSPd<KG^OMvL(6@P3(nn|-tHb~ZcjcGh+8r)7MrP+0YD#`;yWua$5jo(v|p^glLF-Ex4
+j!aOrO^8@JMsc1BZ-W?}cpgZMZ@0GVvo@96j7Br@ib4D#C;S8BrRtDLh3weB8lS3W%hw+a1e!^txH`Y
+OZH;VGM^*_N(t(12;>Nxkk<!#2g9Ed~<VNcG~1E)MilW)k&ph@a~!YuV0)2<nf7NVJS>|v~%aIbhL%I
+njGyhi*vF3H<?o%16i4U0r;shkZ+`v=q=9>)<Q&%mFOt#-j5;*Bcm_ZHPJ1vYN?y;QHoqFx5x?7sKd_
+<Nl%^_(v*jW5>;zNE0~Ctx=SPb&8bv!MAnk5J#o9BN5LG&;_sVc<D^T55{jW>u1tEM^l5Cj83ONqpdV
+ZZPt}fbUk~12YLes5&2RYBS<av>fMyZf7*So<Q4TOncnO2jKizWFjBNc>p~4_fhfPHyY!?ALDosUCs{
+kwi|8snYD}i&m^;mkw5h9bh6f_uf49{DW{LXS*=Aru6v{-1E#bPJSPXGCtERwZ*Pr7cao0A>*p#P;B5
+TB$mykzbP%lNnm>{Dt4%u=C#i?aP)?bgHnIn}()*L3yDLSyU7Ef7b{Rhteyd@te~`p#CH9H$_~E@-8`
+hL4R%<JhoG*K_GiJ}oN>81ach#(1M_Nk3)p37u_CamzOi}aprK))>mC74`mRu8_%O%lPiD%<CLq0>ES
+bCO1*Glk3k!-E3k==%Ow<WS$O0TbaHB&}TLI$edySc5v!p^9BI&b?A(4rzu-LZ8v+H*O3SDC851zD(7
+%Gu!|lhR+olzz3*e_Pdix3m$j;(xr1Jgp3ex})OVXgAS!!TD${l}+v9{&RvCiOO3Ix!#b=YL{Qd(!Aa
+^C2JL>zm7R${*ilsmwVp+E~jJ~k!G{n6{)?yE5J{ctRn--oio`y-`xb;^hI^ljUS~O0RC%JdVi-NT^;
+B#A>B>tvu^yx(<w-2O^^=q@5XP^`}eyX*g7|U&GeqqnUT)&|2;la;i2pPpIh#f<!NxH%zvfj{I&GCOu
+heHIDaWWx$el^pFC`oec0jJ)sXo-v}wlo^(OJYUgSBm4!$3*0n)2ay@q?V$wu4<VH@y{+j7@A{ynf(o
+~V0M>DW|tHtMtgSC4dm{*{iOZ`$w=E53aEyM3p0yCShi*nY>jzje0eXTkG!7CAm$4!)XW3jWDSG1WdE
+6P|<3K1=@KL9_$#17T$&Cdl1!%^!Rf{@@WOYae@Hf7f}t8aZ3@i>?^lpL4i6tn=KrGy$GDbWDTwC%~}
+)-m8FhqS<#u_W6zs0_GwYYgd>r!^vP}pYqL&!9UP70dI;0Gg%}a@3%ES_ALC^^C<IzNeUboFEfXic>-
+l0N4bOWXQ>`(3Cg^XsYXPs_=~PTmtNnSf?nRgfL?8vq1V@)m#5d*1J4DIPnUqR44h58jI(IlqbAqk0f
+`m8y3G|h0o(`hK7jI6=Br+u0=V!SBq<|s9Pc;deIH||l@F^C7rry8>}BK+409jhU%Nzq!sK#(%gagA%
+1Ik9=b%<j&UiVQyqxbREGI4SpN4YI);vGn7ht5>+kjmnvAsE&L!~D{n*$l_a3&)<<#+~6wvg;)?Zl^c
+#Q0nJdq;?6x&ta=l!ua7pi8#(Tczw)qGf(MJKQF>b)12(Mez%liShn}gA?({B;GyG@u0fMEt!ER_*sD
+ayp{qklLPRla!}?6QD1`3>%1p3Fp$$Z^J$8+>^xqomhk&D<dL44jkU{oc6?rKqv!1z=2c}9Yh1dgbLO
+Ba(}Os*{RG}`b@`6u0rmjo`73i-`yiEv`yUgHQCDT28XQ^60=6_Y?48eo-Y=+asAvDWbQWGJvDSIy_i
+f#MqzieiTX$D)m#r(Q9HJ?eTgc0EcnFtUwK8R-7iDIJ){U2$75Wy+<aNt)1SlSCmf0DyQ%!j9y;|V0E
+<+7dTEfN8ammtf$!z^VK5HNP{!Il`7M1Om6#K>scR$tFouIxeQFa!}+jGDX0A0@v?ChNRPbkZQcP&e@
+0u@@ie~0|kF;;W|_gA654WK2#r+Vh0epFss0{BY-pJ0#I1@Ld7y2#nBnHF|98L+4fDvRXgNt6TMt#D%
+!JKQX1k5Hct`PCQjjmnGI!CTm&u?G$sY|Pa1wBO>Zj!tJ0;)Me^{?@|Ui&3}T;49aYbTvYD;a}w?0h7
+;HEi+*k$VVXE={2*$LgXVJbJ;A<3Jh*z0g}h7^T0RYfVz1Iw`cKOV`4>gpNX{fTeAYk!LMx4MU`3iZ&
+2P)h8lsMhKywz%R_rxM0qGLy-P;kx{J{sqCug?(;uUpPMJ0KAwNs+>_|ilVYh^CI~CUGBY)VzRyi%mh
+xXGgvD0jOMWhaNpnDm1suJ>T%J5a^Nxo`pQ$_}-k5!FSrLi#KM)rjCc--zzcaG|1@U(YwT7)RA4{<7$
+%lnR!)VCy*$<t)1k$k|(qq=~nl$PqI!#<l_KB~iy+4p_pc8cID4DIk>R$$03>=D8FchJelMwfjOI!|c
+`CT!P^0obTNa+wh}=xmJv{{(grG_O7Y7$+d3Br}B9&+$y{E|o<#_osONJ)ZX^v8SjkqU}D}G4kDvns<
+CDthN*H>0PIsHS$Hg8?X}%#Jgs^yC<Xe9o4SUV-D=J<jWvB=+C26PTac-)DNP)BYQ}AeiL{Up>BlZqq
+tv!`+agQ%KYd%gG_^8u0~)JkLYFO;(ni;gESwRltwQzho{L#n!6^Y(Q(MeeKX1$FnzP58Su`Tc6N}yD
+rR>0tmzva&Q$i4Tj%+Wu*G^^;_&f9&na!CAuaJNKD~~cH(~nBN$GVw6SX^J8_w29cqa><zlSz<xpLTc
+1FKn`&Kl>r)pvHoCtbkQ@TLdVHvcq7t2G_|D16Bi@KN2p3tFv^K^J5&6Yp;U-9L*oo7RYSv=ek#1N<^
+gz9arGtD_3+oHLz0<pnM4E-r7o2|mZhd={W|CfGN!<;2H-(A(|;-lrJY?Go)bXu8UoYHsY(d2ut<8F*
+9MzFY~s@-AfcV-=`Vd5~<uB>9Ftj4sbVtoKWB7*#^1h*rAo0l!|%-m^F$+SaT<?_K5yZxhh|kRL*JA`
+^Ck=TB85y?5Odc@?&hYzFyhWH$&7+3%sbYMA8GSuQuKjE3KQ)xuB74*VNnc{7BqAsBjItHrTIw>b?N!
+shTiE!lxE@(eu=TlOFe4)CiKbUrBKXTr~npC#yA%pyF$B;;-AlWN#$$+@q^JhiT!PoQh(47zq!YnOj<
+QEQi_oWM86s87}r>eb)1<OBj^qM!C>`n$Z`z{7+ya5#T7Ie7L~7Ez?!B}1QNVXDW_$5@b;w@Qs9gZ@e
+QS$I3+t0uo!v_m=L?SfBcMLd0xL6;Wuw#38pq8)j4xy;)W!PBkP<Mi8~8#sY)#|6CV+r~6G%Tpu!Wx+
+>EJNQA!)o;|M67oT~jm-!gLOQoajpS**q^R4>z@0h_=wEM=0jE+t1Ewr|u^3(dUc9Haa~#f|nSteFF@
+JRcGQ(*;p&d80FMnSiAs;mdc?T<I@t8s9(MGhdzebw647F)DwLN~;Nd2f1<jMxyNbPFZ-Q^L=SC=nvp
+nPp;TiY1xCVe~)o|b6sywox)uvH=-#t}N_)P3yP<Rdjw>_dL11Gqm5o!>31O}&tLD(g)v+H2gC?2G<D
+P44sN1SnrJ@;qaMuY9e#rBBN<U{XAT$fri5MP9%<3wawdeEXe%S>#0?FVfT@4Sjn_D+_*A(?-A~Io&s
+=%js3z7VU%2#qos>55dm)k=MDMHMW2@R2F@sXCWt7aew-cNT<VW$FIjG{Bmi~891)d<VT<he1}5+hXg
+#92wsaTK;^ywcy$IEeJ>7g%4e+aceL+%eUHj4LUo%MS0=D?Xvd?bIk0mqCNndHY${CPNn^Jx4fX@~E6
+lJt_?1iBXTooT|G;_(@9aQUzy{uBD}WJ)+vhag`ZV0gW;zg~@UrG}-?y5_MVj6cy{(^Dk5YNaS9<~9O
+n|);^)9fo!-@_5>HP&;Jczq0)7_;5kEaEG`kuza{dp5&fGv2xF2fvXmTe<hfIkF#QvteLvwBO)idZA)
+TU%Bjd_AXR8(FUT&RJ-GNDhP?=5wBW{5?(Y7O9cP<;<1%Uiu~A{wjP=vd2_k*Ylk*ogd66Ts**~k@DY
+({N67#w>k5aGh5SH?J)8=8w$3Z#dT=uM4EZx_(}Y>Qf#+pZov6fz=O<{1D*xA>Uri&m8X7Q!1*PSr!X
+#0T3nt%v~?6ml3gCr?Q;42alN2=%ms{5_|!sYt`0a&;{6<r2TYTB^3mVAinTK{{B!WI1u@RRHYM=u*{
+mIOd{McxJVMVzuP*4sF!B)3_kcg;kg?rcS>UHKw<CK=&vd@hxFD4$X*y?>eMdOFRppV#lB}(RfH`o`!
+Qr0AwM*`88m8C}^>i=l-7<uFDyH71MTh}UnsWL3O6~m+(%vTJ_7B7E8`JmU{Q@Zm>9Z%KuS8619V>71
+SXx`lAzv#k54Ucze6`gF+xUSb4R`692{L)~T~4RHron3h{|$K5NAw!-p#GYz$k&q3cwD#kUC}=N9`*^
+k)lPbw!N+05_zV1*2>I4^>_ac<<0|7mxkPQE==<U0u_8TUU^Q$^Z;VIC{@#U{;71Z`|MooA9+Y@o;Ax
+o8+A|sBz6l!1c4aoJ=`yjx8N?fE^Y(iJcOz{lejdbGy=ZsQp0xi&;`X7Cr`eMiXaMY2z_Z`rw*%jD0G
+F-=uM+8QM%?=_p2PUTA1Y#T@y!69_ez2eI?j*q=U9xTzkdPmoAA4OevAea`@McXUgs}qb#mKTA#6nTz
+U8d+9=yxMyF!UQ;;*<pOfg`cjqEimawCnuVp<sO{EK<zDP+f9WG(gp#qFd^15RIc1$2zwOZ9g02VQjL
+*#pz@y;93d_N)l^Jtzx2_Pm1f8U?*W(A!8CV$4nrFZk_+8}aT<$O4!1`tpc~0ewfx$;TkyT`qh1<A(f
+5*Zp-ZKglcFl86O7eJNkWf4+IdQ#Eq`Jffc(7JZYMA=rSO#Pho~z9``Ho#4eAz@7Suh+aQqJT`=hVh&
+1shn98-cy=vUOTo*cKh70t#vV8@p>L3QSSFEg;j6w;5@}x7(*AZX@k;RTS19ArDD}Th<SX&NPKK{+$_
+On4Zyw4k4cOspRgSIh^Gd8|<(RcENcs)jnk8j~#_TB#|IT9H_kGaxYb6@(G0F~)r#1c3%R?LUNM(9cD
+fuu3_+B9SXI7<`mL3OwKat1j%Vm|yyy|N4&ab`uInqP`b5cKmAwK6aCf{F5wDg)-5#ruP=vVD#(jVfz
+#Hh`Dgq4>DzBpg#27lgD8t}~*X{fAJluz#!q$|L+0N-th=WPWn=)uosWf3qf!sS=KzI43*K#T8p<M|b
+)>zB}vP*rO+?A%_oBLTMre?YRWmn^Jy;f-q8vwvZ$J>;*hln^sW_Vwk687dbe%_5}{u~@C0S^Eo+#$B
+K`DU!9-R*&{O755h3k%a}yt`PKawUjbKK4(>`8g4Ex7<nA+aHUlZTP3TVp10w7#UA*XpdspVWF2@&bt
+PY;a=se&ve9CCPSW~A%$onG`;jDn@pg{%`YO<te5+?PS}Kqc=U8VS$%WD881wOTkOj(LpxLY-@{{a_<
+_j6FkVW4@e7}ql4)Mlaa4YZkfn9lu`g`7i9un@PgD&tdcfRPet&^#*Dh5l3aSFP@<IK#?yC=)l^9H$6
+BO8<0N1amUNV$c_bT2A{rU3QtS;vm`4Z!zsQQS9OjgXxx*l(gfqKF&ccsvN*C10#SQeNPB_m~31c9GX
+*_&%_W>ZPS=nV4o6G0F(qn<4n2wifFP!^l%9Szk~j`wQ0R)g5KP%`dT!D$@22Km68VlRHGTwpz$e9~_
+rY8h2ju*s(?5TEN&+?Mgh>byv{9&#yvXuIIMbEtvxX7pHjNa(y7azwfR{bmw-n?+AQe_%&AQFN>V#F&
+*kBH9rko7ctVA%R&~(z3{6H?_XqlV&h%>xh3{YZ7<y)iL*1DZsh_`#`}88UfzxPjC}AQbkHeT*XPNsR
+=Gh9lg`<C-K|y7yE5oqy%f_s>NBkT67VWzjX~0-2<gbg*veQB-ZsNO;dIK2(aC6^sJ&=|92J;YF4~qb
+;lg8~nYd49jd{3l$XCOaGRt*K%1Wn|HNsxhqCLnhla%$lwZ06at$AAFK1HMrad3}zKLQ<CyYW*4E=$`
+CrhZErZ?6%j=(v#Iq}1OK0Q|j0EjI)*^Y9Kor<659emyGn;-)XFqupr#`qq@A%@qA&KD3Y2k2n|pJs+
+>)@z8;ZenEUWd$e-)zklVBJSa167IKpulN;jmq8nJv>lRkjHw`}1sn737lX`DVDQ5v&3d=}^9Z&11yF
+J}jcl&}5<=!5WbC(r-NV#1}nN!m>zpuk1DJLmbs!H$u9r+esT&<FnJ}j3MKVsQ`Lpt(acm3W^E6C%IM
+!OdSj+^e`XIPPz+K$RRw#wQ#rzSZ6P={NxpHweKYZZL60nYZ+6|H1r-6)&V7vP=yLG|eN)XG*@IXhfM
+Wr{ZM$St^kCRM&Y1$B4?b+7_|YKJli|F3QQbT!JR@^1&M58yY9x==l;fX@olh48XVwuju3jn~Ph)u~U
+zWj$!#puHQ?>bV*+x!}EM?IP-Hd{AxkrTY08lUu9P3e>4mn*LCgH0>eC<VfE;(b@ylzpueu$@8?fLMa
+_^<OBC=G)n`%8CN}Z`zp|m@Tvsu2>(jlqrRMWWVb8h=+XeXEC5~Bq0L+^rLM1&Iy=O8%g-jxDV`e}ce
+!9Pg@!(%21jU2_bSn+JpwywlV<dH$)c^ZHmN&`q#3QlOUg?t)7jy3E64`0#=9kdhmx#@52g6XR;=5vu
+-eg9DM<M`Wo3Ouny~$|>dk?pxc<1hu(dBq4X<AA9@&<JZ#HqCPxl#Wc*ufyeVWSsUKiy3gh!3!FL$>N
+n(QHJGroH+y0gwQx{TVWPodpc5LXmTW4UA-_LFURx;#R%Rkt-Y@R`+U6UmRkJKcYMQ|o^gV;Z?3@?WW
+38s|8R_QA!=$_)8X4!u8)G$s>`;bn$i%U2_>W~-4rr13^YJM|#aQN2cxm+IV}#L}tWTS13kh`DRrC#S
+KbAK-f?Xxb^Ktlyf<YEPO{JU;|IhD|n4pGDANF44g%?hl~dB-$oPv+k?oevPj>1RwNA$n$;to~&Nb+J
+$`06`&>R-enc{`M4iWSHoTD!e;J)ybY(|IaNGUpTl|!OK*lxbz&@9I}ALUrIhu9kYTDvALXS!AHe!oM
+ZKTwza4e(qi)2Hp%pBA2(XAJWZ(0b7qr%Z4pcvaMKmBdow9ZPNt4xcVl-MSe3OG+@6J^t6X&OkxdCK<
+jqTF!*hC+f#vY$Ayc@#(I|=;TaXYG|`!Uk}fyI2IME=Si#6mtZ>mD|<T-ZZSBZ*`ySF|&GKzqdn-;lm
+bR^HAiCjLFrhqlrR9t=~wIa`fL`wLo`LycskOqx$UjrUQiVZY=mw&H!EL_gL|{!ylNJhs}a$5zx|M=}
+}jf9UO#OPi~v*E56sW*-a0$15rHes}CWe9msPEvFUfg8?T~MyQ|v>ob`no^G(U6iasN`Ksp%zdXL3$_
+A{ynOsj7*Nb-cNQsC&(SAt*-3Q~(`_0srdwP*xf6x1MlGszE<BytI4^KB}4(MqR^X;H?)R#*AXS1m9C
+=LDz?k`BZABU$WUslia4Cu=JSQ-naJ{0E5@ZQhD=kbo_MkqRd6U*T~PZl2o&kU`Ysljd$J_-2YadEzg
+KFvw(x52;WJ`L;~e44%PJ?3#55Z&1f7IvE1Vwx|j@UfW>26S8~osRcz1Kut^zQ7z77VB$B6dz;)ULEl
+Q@CU@W(_Tfg#L6dlGX=c(_`u+IoMzIE0{426myZjaYpHgLvF<_}(o{Cw!QsG1POoa19*)N^(Rh|oW{$
+4ABYYG#naXpZJi;}r#S+LtY=(GYRq*1mzPjq1U0imM7Uiruv~GHMDPm_G|HS>uq|ZMeA9sER?blMo<&
+Pkq>63Yk97dc-cxF&+rt22*{7#b?bB4aQ4?UnhP5SXm(6Pmk*MWTG$C4aV+S_>^hv#+8pN=2*K8tv<(
+U3o1l)d9Nz@Yp|Ggv!~s}a0Pw6Dz>jJH7&mqUl=IP(5C;C%98^e5hIHB9lL(=ziun#)Z2272B7rDT)8
+pth|e9~p7MLMb_5AG@V3HA~&$Z(2V(&FVW6%$v5$3tu<?wcgS@B&EMWgH>i>_rcGvU2PVAG^MAsp7Uy
+Hh$+Q`rer==52Ps`bc}x=>@9r=_}0s6@J(*xrni0)bRIBG4`q=rromUNat(ZzqU#Ja=mo9x@8Em!apc
+j<p?*f{A0~XL-~Y|A@}mP%a_i)I0EzsV7~g3=T*M@YewfSJFMzf~pbydJgP_e!(8dbdcptcb)CSs6th
+gZ0whQ`pqzb<+ppi3~H5S9CAsTymjO_>!&#ds%h>jkjA?WP|9qyE@tzB$%*<IkZ5AjuS+RGgu5_4oUK
+IVAt<?*zG&zG!AqA|c+kHoTQet$dBA{qD7@#8ehvebCt|0q#Yx^)h#0goCzfKy4o7JtW^Olh49_@tLK
+Zb9%rO7P7hmM8hj!}oo%a%KbhLOL&IB-KzK|M+vB!rR8_Dvez-$7k|=;TTOIOQ4BoP%X7dX~k3GA}Ot
+Uy@yj@?r=|kxx*@1`(2WwmGo<>c7E)EpN)^_Us!7b56zr+Huw+IUA`mpaE)&KK>t~7j@u2nLQh7ikBa
+jnJ48M|;=bTaD<69$Kh9GCzIeu}T9szO@1@{(7WnNTe&4@&^dn>CZQJu_?#i2?M(m&&y^ElXhw!cn@5
+)Tpk@6(XcJ8+X)GU?vBbfOdN*0jW*6P8zqR)bXM}i00Au9U<;>SAk=ud{=Cr05jrNDO>M%snt?$(pI+
+NsTwMf*DqcKNFoc9{B~Dj*Y;5@fE3@%S13I``cwEqGVJ8uwEll!XPz&sV^MLx+Y+R=~f2?-pp5az^Oe
+e)w-gD5DbfXYkLpSbIk_Sq(gYHo7yi{wC0Qc`!ETK=7e*Hp{e*nbJLgdkS<|4gR`WO1}b}U~>Z==wGK
+Kjl8k#p$@_yao~|R;1~Gkt6QGLcfxOdR%^#TY1#;_1*wZPABE51pghCd{2k;EP`}wQ<;m(TS)t`&4qp
+eKKdh~nc>1ESpO0wQTDMr2k!Ze;1b#EccVwko^fzyW{878^BKoLXk8F~a)@Io;;-fyy11#_n$yc2VTK
+xC`jX`9G^!DsV4{LvRt8>&weePd2k9Jl6L&-jQ_LiUI&o24N68tJ=mni9TGP<f~m-HR*v{s?5BR|#|V
+WnkRtZ^-H?*dGx<QT~V{i&|i?%2Gg_&F?z{3pUclVrkx_j&FE2pP;qo7i`e{EsXiuk_?g0h+f|&*z|I
+hKk+V{Mt$V2}Zj8T%RxM*=JK5*8=u`z@KwV!X7_JeTI_gtBl8)=HF3YIn|43ybrdr1bVd$zu^Nnhxfs
+^UjTU7rsP21{ToLs!Dr(Cj%aje@BK?h;eYkCO9I9x-J-4h6YT#G^78(H1C}t_`vA4m)P`C=ueR~NE$F
+QWdRqX!Rhrg~+QD;Io_$w8Xwr~p35fndXTo{0)Q`>QLz_pJaaj9r4mTqfTLXRcYVAO=W*2e*zYjJbmu
+y~s?k*4X9Xjxo1ljq~3~o~!CFlZth(hWYr@o|S8*8LKFPd*cI!SX;_<T5Ah0i5xzMO;mas;3JB7$F-#
+Ud2LY%tJ&^<3VzhJ{a(SZ=O}F6C3vMev_^FmMfPhmV^9g$ZYp+~=?`@v~W$8y`YF9pK|Pez$S7*u;AB
+z(e2fz(e@cd>mrG;91pvOL+4qX4XI^J?%)-1)AEZO-0@Xz=`_zy@RZj$~$=t@jT0uNVZ7ke*>962c7J
+m&JZW&jO+%F{KxqiPVqGEBRND|lo#`3={smqJpQdb_N^xqu{U&t)+_qu?0zfgqof|{$eNL9Cp=Strww
+@8LBCXdt8CgZ+K`t@ZGW{JIP1^U-?a$5`cJ@te5OAGI{gIqiTqiTw;IbtSvz2mwIcA$fpW7^X4n0jMs
+rZ^3;8*_s?fG>H?iVM$Q<><yC8EJf2GXnaSWA1eO@GYhftPBle=H#$K-B*ew^H0dOqr6npfDZ<$2BkC
+ztS$WA%sMy#6to<8TR?T>zPFK>ZuQ=Q`A%VzPhMU_W7ieU}(t-J!=6XKS9D;P)A0AMf!yxUZ(DVjRYq
+${HJpuTS}BN|Nu0_xSWMga7vY)vP_2`o%9KN62QsMq_3dZly8L9xt^GTG~2%dm7*LbidcqdBqqItv}%
+Njxt*q_0yhSMm7cMXrARJz#+e+l*bFAy{SW6wA(FU1TWsw7Rpw499`!g9lF0^v?_1rt_7fj*9ux&*%`
+=xZ4+X(9@xg0^I2fy8Y$3@xTt$9IzBEv(XSHg1PC96@cF!Y)Mh8!VB00=HnH7Vh_>&V0v_W&LUC87hB
+IQb7yI76HBz_EJ31d}=)M8>A+$lR{VbqDwrJiJ;qubOXi+b|KMJ}WdpkLjs2w8sy6&=G@|&Eo_vMq{$
+B&PXuQ4&no?7tds{B|S@t-2zJQ6>~d-h_qo93Q$U5pmeT%In-M4BPrS?KZZ<t&hl`aO<(+h`6EzAGkQ
+^(emWgDpA^n?<oW*_fpZgrD&Y-jlDf8+p=@m#)9k){7t0<3B?@F6JRhh;3vZ2fmpX!-4$%Ufk0dww&g
+xru8~?GK<iBrq}Ysn7DDgWIWza5MTb*0QVt5lZ;#~2BUbD`}#$xHSp;Q3D=Jo@G*EEzy6>=_$&8hvG!
+I6_4$kzQyz-J>ax`c^#RQRf19(#oSY*Cq79!Mk0p+~pElsOmQ9Yk$77MjDK!M2#)`ry<89EhQKRiaF^
+`+$dmn%2@Vq&J-lAOV4XkD;+F4CwK1*>Ade)Xn=0@JnPI_^3dBob(u*D^1+GxDt1Y}_N8rDSdc62Ul8
+eA#nW1R4ac_Tw})h33t#<5(T4}6}{SaKw>zZDy|IuHK84gOy+nLMK=bEsmWSXYqwU*!?<`?ww$`lDYp
+<%Uimo;!{<k>)SO`T-~V1%!iDLL7suckI>(Y<vcdfi7M2LPyP5v?mcP7NNCOwDpbeh>3}{6Z(8&YU>E
+59WYaI?E=hofVlxM6@}(R+E!W@_R-kP3tgzY59K80zs%QibwdVROpQdf{Sd4sF`vhWxS0vwdW^DgIXJ
+ItaDFDo;Jk4$F&tW#WsENg-p132DGz2Gep}<qInqnOA2nIH9wi%O^;y0K&6iOI-ovr)E{aCG2f;rYXW
+oeNe<L@)6>XEA{jN=YCwf%cGL+LfGuq5bht{&vVVWyU{&o!uLjMCpACV(8r)@ZD4o26raP(l(Xmok<X
+w)P%MceRPBbP?+K$;pk^7dR7IeWqqj6P$gemq{!M<FL@2aAD6&qgyVqA_oZIcT2RGt%g?&I3#N-1XVO
+^&=+M?SQ|w5qeDX14)nd^eX&|ee2vM12q*9H)7wR6KW}yNqzh$(e_scmxrxQS7lTMO*GEo0j&bpf@Tx
+rM$yh}5;0c>`RqD;ih-8mU6<@=b)IpSke{E359ycT!xOF;AMVolpeEo$`uoNQ&_DUoyg2gL^P*`IFYb
+45Azu7q-j(s9|INRE7fIm7pmWQg#``BHuDev&=^akQ>SU|PPTm6A`!(N-Y~Bn$-cu1-I@)}c{GMhx?a
+X$h^UD<x__-r^$H#Q0YyFv@KwC+D`kMt#d|r$X`5#6dA5D@YZL%C$s?8bu$~=9JR-*N;@pz6-z;pIgc
+%J*h72$cq6nL&lfagD60?*Y7YoxyX)hVp;rrg`^r?`D}p%}At&t^5&uS%;<&Y?MHwskb#Zr0`r>1~P;
+jw%Z{1h4WsvF@vZ;GiwDvoE~GVU2ZG6C4hY;sS}Cq4^(E!L?pj5dj@~taVZVe(@3Nr&ktMM3k}eqckT
+f#ljAIXS2+dd5mm+^{^==q?CwxC9YT0`>AhOv9MK22@6-ikD`7)k8)sU)tBU1gC?8Dy`QDq=djG?*I4
+6MsZTm9)oz``(ih;JGLN@SrB+-EP>yvT>0UHvyJTHy{W})6;eDkAyqy=@yJG^rE+f7bN8J{sHN|>qd<
+U)s-y2yC;TtsI>jAzi@t$z?;vR8J6X9>Q3cUZD;z`NM=h_nP+P8pJ!~Jq}PSxm~iuBVs-l?HG;G-LGf
+2Y@g`yE=J>H_6II~u+;eHV?fx`CGs_}_+Wr$%po)-;a)LXF-jar7Pn-od|u-h^YSbu#WoyqW1Tc!RDS
+Z(KVyy6boo-EY(A?oU8>vRhr3pnD>}3;vepm@L-vE(6}=Ly(St7<lIL_6abugx~3g-|2_V<?k$f4qEp
+fnbvCMc#1y2WAVkixgAky3@UxQ%=lQ>H*vL+e_&yYX&jyU2%6>W^$W(tyqn4ErVVlHte9P!3fE5o*9d
+&sE5`Rjtma$Svi7pMuJwNjzL8mKBtDj$YWxoEwTITSzOCVWUdI`>isr_PwddKPqEyySb0M4)%5<zBxv
+0_TQtLwgobph2DzEe}DK9QwYhJ@jTR>CyJT>V39t+OWVtl2gJlscp3p6ilaC*R6pavU4ESO1g1Y-Jn#
+KaW8DV4AvNi1T$NsTnvSmdW3nlG$I>MK~FANMq7<VM@x#gt`=<XqyR{t2}4>(=mj*rCbevf8>wq6ct1
+@H(w~%s8yivvx>g?PWK3PvcTqvxycgAmRNX_)hD-R~{r^iPA2V2q!hNQldGAG=`-{XnbNgDhH!0$saP
+qAF_;|q_u|!SyOZ)-W`=nqh;`imdlZ$Tjj{eGp1m)%^W_>gg-Q}ydv@_tzTaY|7E%6znCWaFJg=;%X8
+>j(T)QDz&BBk^Rx~-ZvA6?eZM?KeYYg2?^pkt`ffu#|NYW+?w4Y9{^%9f`C&tyKbD}*ZkpfuAoYLsmJ
+)uqNxh|zvBF`K;u$hoJ!Mh~pQoeD?k%Brv_{5mhF^<V-m9g3eHQ$nIk2Hw(yB5kbsf!F^Umolp|lNX2
+Rul(dOvHVF=Nlzu@buPjYezTV*F|S!gPO!H><Y<_P3-Dc?hpXz$*nf{ct<C%Qc4%c}vP3mH2w4e*vB;
+vw8ZOhTnR(1fx02#?uT+eB3rg0d5Kl(6c?w-_eCSe#%1qWW<Nw(sgL3y0WNFDV`r7Ryc*aZP&`4I8GA
+l2WkT^X)Le}ZOpglh(4J%=-6iHd^7A@1^hw(G&Q2HA!4ZCNjF~)68716Uq;W@kk5xae14C%29EL!^L-
+H%KHq!$G!`-XQeIh%0pAHeZw4&h-!$d?&BXZLdnNdy&3hpZ-!*?Td?)rJ)fHDnTuH3E!>+CQNP>K!9K
+VHid+)o6w<QhtnZspP*0_5bADeo_vELkMu4dupYgzan8XE_H*Ll=%1MoSSGP-O-(*9C^i#BfDAT<tAy
+Y!&iW^G}I7tDC@=tCJS@TrD%&l29Lg!i>*vr<#-9(-Hbu<6<LfZLqM8fgth^BmULMSaS4mgcVdmlC&C
+;rphM&HRAA4nko?*>hsC<G;TvVn<_N70rQZ{z6iL_Y27d&9YS5TrHIrX)(cT(C_PL>@q0&-0P2sbx{8
+ZyW+w7bs1`8$YkqBySu|9*;-fTvB3Ha7TM6U`q>S|Ec_pc^Sn#c@JUn3%5`|QN>?puSi-_Iwm|Jj^Yt
+t|Q-e=BT7MjR4F6^-xL&}eHrtDQ<ZF4aSHlHQ`DZrZc|_Zz<%_7hNyDG!wQxF&Mmg`S(6fdlsg&*u&P
+I!fKg64Oeh!|A*4BY<KL*SnJp1$gzxnOR8}ahtg?!L_Q-TFP_B=N`M(0mybbgTf9OGaQjLV8+Tvpb^$
+x7%7WyPz>ibC^_QWZPNOM#?Jk{8#zQ7$iDTpQx#Mbh@LaA-2q7l{_uqwF=0q5Xa=J)l7TuNP%Zl9NJ>
+&L4xEd?10G9K9IbS@2iN$xKa7X8Z+mB4mV(%g8BBM%Ei-<Qtld_}`i=BMn9wxmNi1<{7u%zvpzcHlDA
+0G?_8#R`8kdb4Ol!Z77j_iI<;+2Ko8JJ3@XoCXk=qsgrHZKal)b4YtNUx@`TI)h6Y=&T22@!Fr>Rp+0
+H{AwM?A$9BliZ4C`vep1G5O$wKt+aNm|0Jjseqe5mnAv=Ctt864YKbT-^iuHAA??ekPCnv8nAt%joa<
+ch-mXqf9NlsQ7<m8W<oK&9G<wR|2_%dtaw&Wb-#5#p7d26y<JpGgBdtZKK_|%oi#rI~#<l-ZmT-={PE
+_?~>%IY||SdsFV$;Ecag>F}jvf<KXgY1fEhhnlpemvQbb>Kf@UJu!lEZgO6$vsoZ$f>daf67RSK}MEZ
+v~`znO_q^EXALr9uqD!&$+kpFATvMEY>8stU+QcDZDdwU>&_WnpA<fUvq!9-ckUPC<;r!mZg0*Kntvk
+huUcXqzh_I5#_wk>F^%6lmsqb8b7HxF@I|%hf3iGd{7G#S>BI-)=DhRyl+cqpv{Ui@0Q8>v0fNw>dfY
+1uVtp1~kLUwv@Q6MDKL6K~c>ZsE98B_42i@^PR(TmylzT`k_kP5-H1_7q6a5cYT6TQ7R7cVes>2AuN#
+b(FW4D#Rt=r<2(lc})pwFb?aT%H%^jw}MTz(Och_;YLhC%ynGh?=>kdK=QANxw^SFhEhEMYzBC)9)1E
+$jZrkb<~20WNh0T+%Ori;ja8dQ&z-;`0e<4WU0JciAxcO$%9=*2Oc(7wmzftW@IjN+^xjp1aH{i8MDE
+$~!+Q%Bv-OZ&1T-#A#(gsqs`2tM%bmHXm^zjkPY8cprAzDyeZdV3zHX8fhJnHHG%H>n(NSnbx4VsSh%
+RMQA<qjeuE&D`ei$Mg93VurSSMCOnGinj+%G)xQ+;Al)=4@{ri0Y=tD&gRK6on7hos9Tw@<;hP)w#|C
+&*7Olmqtd~}C{}TGGm|1OunSInfzptaq#EJ_fVK2LY3ytNMJ*Cy*u*CcF%l;s7`&>3GHPSkmKBW6K?-
+TY_AH{W8TN6B9*QX}db-TtdnvY_=A*KiVx(+FAt4lJ>x49Jm=F6Ao-%B%M{QJ`X^6!71e`rUH{OdCC?
+<*Sr>f`w5H}LNs1OKu#{@oeJKP8#f?!FBF2FLk_c1`D>HO9XWY5cpvz`yG?{w*8lpV}1TAK*;MKYTOt
+FFnS;`GouV&gx3t57T&92_7o*4^86XAFq&yFKIkHGKq)4<*AAFy%Z1s9R8iZ0{)%Ljq&e^3;)Z%|0({
+(&mZG42HIkqMOwA`55PH-)o#y(@Ba6pXRR`>as2|_h<oN~{_TfNtUXU3*G^*XS84aV@Sgf}$nUmFv$?
+-rF7dfE9ERP(*ONOM@ZC*oIcP1HG-HVu>1f|0n%l(J_&`3+;hyr*z8_XRd-1&?Ke=F3^S5UvX>nL8{2
+IBuv@eAfZ2;V%<+K)@HPM`Wr<IlZ)6F$qw71ucBwk*ZMeue5W5r&Jm=Ec<NZdbC%<wsuv(g2~`zg@o<
+Sbux7xf?4Q~$AT-5x$ZC-A;jqxm$Zr2!o&Jz@si?eI%N5-S=8E=m$`Zzw3)S1<9stoB(T-_w27)EBJS
+ebvLaQvXds$$E+jiq-IW#7N$1HQZ^r>ORC;D+{Hpl_Ym-AEUjj93BZc^8Oh3I`KXp^?4h7ydLh;Nm+L
+C>8Q^4RIq@6ljWhlRf4k+eii3Os)^@!Tjd%W&lxW-NtAaAwpN#gUx4-m+bxYQ<Ge;5_`8MiI37cuiTf
+K&oR0|JM!!U|sa@$=|Izc6{@zKDe!6zOa0yt(@>zoNS%N&dOdKudNKn4X@Ge8ke>uJLr^AkAOs#h>n_
+_zR89AnReoIX6o|iAJcZ<yLpWfY|#kPHRp?8(`|F`sRD`Yy69=)A(WqNd<L62^{LOuHU73fiuCdW;2a
+!k)x`g<oq`sv#B!X;oC%a7NiCQT3G^BDCgzI>D6ovugm<Da+uiSLIM@*)=3b*V1{zV9X4uu_9A{hJii
+rPs_cUApfwx^&X?{^?SK)|aSgZI~Zz*m}|>6W67%P3TgSSJNeLoGz_5=#tl{OD5JtYY{hqHpB0BR{Nn
+xwD-gwKCegMyhxKL8ef7QuA+2S$!hyBWHv}TWD+{$Zt`sD)O4sbUWe=~K;Ku4>yVA>Q1fMUXxoLqvh6
+Yno%{DI)VWVyi0Rx8%a!Te-4`b6+|#d39-}7t-loa@wm7+`=PUialOX+c?Rw!7u#Dx$>)kd@Z{qV9^)
+9}Ali}SYz0>xW_P#b*@4T03!#*a*^lpg7^e)+;ckR-p^)BUo)Vo%bwpXIohPmzkckA8Tae7xIWgGM^Y
+h0$^d^@^x6RtE*B&JW<T%WdBE~QIZT$lL%^KZv=$$m*)66I2!!*5U2rDLy7-s78Oc8ey<TjFGyp0D)x
+PJ;B)wd;jTz%rH}uS;7rU5L+P)TQ|HO@?=*OY!q|Nr%SA8mtq?8aB7A9z8Fy?(QTt(v9ny52<15H?5N
+qvz`YJuV#^;tTu5OmiT@c)zlwd@Ss#fabk$E7b~Ut0WZ>3;p(2#TO#&Eolkqg^;7?ALv<`poUlgduf-
+FxPk3hh&GC$_hoC)FxlMu$(zz1ru8-M}71C(2H>sTal;kUtKY56JN7w{Ux_{=n>q*}k3_mL(zufuHLg
+#4hvvZEb`vW#14UJ<}ZnmUL52|f-Yox%YbJ3lAZ&J#)gpbwr=<{2>*NXYA*3FhxG)B~b^lnQ<1h(ajo
+AypXeW#-7y)CQXs|UQ(nQRPY_m~YZ&43A8(j((tJz%a~V+~leZ^I@fG}m0&nvXP}%vbqbuXA=5{y6IN
+iR-y-i}cThzLK887LlIPyb0K@qI&SJ?rJr12zokBt2u&Jw6;;tv)z#Pn@GFvYMMjVTiV>i8ufIvj(r{
+KXO(7h`qOvse64@-QN%m6*ODyyCqc7i&85<K-u2Ub)$5a_Qft%f3_b6#$rf5qwqBDBw`A-0YBE84<r>
+$w@cu?dXUtAqFLPP>fXtpGJA66$K)NfHk5gy=FOd&hOg@%hMn1|(K6F}LMn2O1R`T&>*7Ux}N8GrS(Z
+(J=OM8>65pK8mp0;!r)I>h4ZCSmA_|RgYx6TI{G`@%EP$32UPS);{HQOgkrL=b2$nS;VcOv-SmSZJ;i
+IobQ8IuvJmr+h8jkhJ}Z=n5*H^Y{W%T!!hM!UTU^?Drjr}B85PkY>=+;fP}Db`(!dPQ$#rG$fvaA0ag
+w)(<vTt#~aj}~u69ZBYl^6ZdUlM(;T)qLKTp$-QUtaC}Ye?e#+aJ^uXJRb#as~53G_jFcUl}2+8LgRA
+|HXUFAn&({%U(5<0&YQu<V+*aQZv*OE0NNHoPkBGE_O7U9b;(jZQ(mGI<-beIFKCARlX<iy3vlN1e&t
+DR;}&Neyllw;FF{+H8JAv9OM9oq&qvtY()lcnqfdUn`q^&)@9oI%CjS+AA7!IIE`Yw#ocHsltbVe8v_
+}z_E!ZEve<XCOoX&?q8nR!{y%pX0C}f-C(KIuI@=|+zET7Io&-EPVbJ;UPG<TNPP<|OQL-LP%Pr+G!H
+bdAtC%I;r{O4-1U!M1BF|Vp@zgP!E&$cAKSJvSM$N_9@DW&D((3%btZvUMT8#DOk88K#%Xf450TLVu$
+fxow(c<PC%))h=8Lk<5cLw~jml~P*@Icl0hhVD!tLrs^Ep}7Vb`q#HEB|~b{BpI@f%TQAy8M@0LL&*j
+iO0>RXZ_6Wlzl*=~-`)G&_<31Vwac)ZqYvc62Ex{pe34v%4z&%YiE_2h;|o6|qy3|{0<ja(itzJR_cr
+0aiMJt-^_JqkRBto%I?OlJ;pNk@I_T}&skh!dHH^Q};Zwu$emu>)ekcL%t-#%HyS2c|_GWBE9a_)^`e
+eTE#^NH$KeG)qO?^xFGH8!zU+$hD?SZ#{UcirUOK~MU_k00-2XA@b+CX$C)o(m4{CS=hS4u}|T!Yb_@
+HssGD~v;~7=N^5@%X=aM&RFdh4_C1_@4r9*;CYk=ELoiS>rGHIWgcB;M(E8_|Y~#47rQVXIa0cSxUdp
+o7C2k3BRXP%39xgF<SfZ6m=H;E!w(HM{NCnmzfn+Al80^&Nxw6I<0?v9kG-B^K@P!t6evCOIx3m9H2c
+!8nV<KDOTT+g?TBvDBk{oWDWRV>n){rT+cgIo&{Q-e?cDad9`$iv0{IEOy){YPo7_+<86Z<P_;)5Iwk
+7}?Ll2xua=U&Rx+WBRV+5Is1o-yF3gZ7jpi>H(h!_VE3M&TfhsGD@Mq9cLfc?x;v7(~B)&IDvGscY1L
+ZeODBn7<{P_Oq?+noT94+psE-!Ukgbkzle!n!c+Rd<Aw1?E=SF2kNz}7}hEKEKl?V(2NcHWr{ztKeJv
+#8<Y^5pqkiTg`s-d~zz=r1LB)c3PQf^T0P+kdzGy=ZMVi_P<*c7x!pL7Muj)hjN`VknEs$(6)jvgCVz
+d>}!eX&jwu<LE@^m*{k&b%~dw(_YYNw<PGa26)ET`w=#=-n1W_%}{UZ&!ak1KB~7~kF6|LkEIFfk!T+
+&y$*g0Vm_@7i!8A^<e<#aXlFI|p=n<Y+Is@<bsu^T>hd=14y}7!gt`;W2j;3xmz&2|?_%xFxs&G?lAe
+B!=J09t?>SK1N;Htb`z-C-`^EQH$M+DPyr0#0Tw+)UWZ-vEB7RRrqnBpIXhiEA2SFcwjv(!)5ntCU<#
+&kzf8&~<MC&faxze(S_GV}|v%*8vFUM_<ZG_JyfnA~VS!lhHRdU#A?g#BZ=z`tYiFU>*<&0!4-q}HGG
+++Hgbmt4QurXFCtF;O?g+E)hXRG!MnEtV75uJBQ{SUl8@Ev#`G|CCeioJoaX}a?DqwiNe9($+x=+nk}
+SpJsvNW9Ng#AFUFHPN~<M(2EoMo}+XGfZpDeluOHF<WY4k<kMst@=8%sGK|EgMQ8g4t=y%IJ>tbUf24
+x^~41x)=lRNzU>rqX7|9ibD6|iw0+aLtrlz1f~;{r&EZL~Ho4ERHkn`zB>Sq5I}@*^Cf)7OaLjvGoP9
+>mlh?2%-tQ{$KCpsTwBJsqNt_oM0j(|=X!Wp0t4!2~_J;keMyqAXN^6-ZXQWr7*SoM|wAR{njk;y3HP
+}@qu?D-;8Jh!5bYmLb8c`ODquUj&=?2~A0cLZ8HQhR$2v;cq-R=Us&uVm=Y7bV?o<GZJbv)A)9Q?Wz9
+LQmjLEwDTbi@4L*Tp&v@*ygs(e9zOXm^s$!J!2#GQ5oi=xog4$1TC36Sy9v`=sCrlN30<TtfRK@pG4L
+Z_rsveU~lwYD2ldc^}IC-Rl#}ol37pwSC5DFB)23egU!*F<C<In36)vl38~Ta3df2r6h6w56yAin8dn
+k@uM??q06-wrm^<dOfy3c@cC8K4B8Wx_FoD;mIS=%95vuV`{?b5{XaF0&Mp&cI`_a&8p5-K_J;=C*EB
+fUad7lAvJSmYXK{-?b_iZM+6UT0o#ybpY=Aq6=OcKA{}ZM)3O;GH7&2Z;d1zi^KfYC(#opq5(_(aQdO
+fyoGLg>xt?Bs0W#~9!pkqfI9lv3qW7}ou_*<eQ?T-Ukv`3DSj$e$Uqi-@Dn{+xh8R+;~10AoqB05g)$
+E3Z}w0)60H4^KoH^9sohdHq?vD3yH`!0$-VdtKT?xZn(vFBH2XeEp7_m+Q3?4Ndeiv7xI-&ER*#+4k~
+H`@A5ai#~&6_4#f?z~S*5_^!7PxB<~CG9=W(<5FRqH{K;-1o7!w7@*N%!_ypv2l?svm$-Z^Dfj?HI4p
++;68k@`KYzm-QOx(`wPaJk9KNjR(Sb6{5#0XIg>rKE?*5=C0l=)<QU=mT_bPj0ryA>#Yd8(742@MAw!
+&P?3NrWy%}uc-g*=EADcWbNOjivq3@+fW5(~M#`r=!p>q$`RU@7nTkS7snw?QKrue(Gv)+vScswfNbT
+9np&Lqa?xYGN5!_l4O6K1ijR(gIQOYCt#d&2WNXtbv>Yw}sg%i4U^gtBOFJDpDjeBU;!&1uob7vlE*r
+oA$~`7EsSPRH|>X<|QdZSSq|^ONG^_&o6X4!+NqwofQyXXfRq@6h_)XAJbY2XaUI9XiM_h5jR56U|c?
+27OmB)?eAsu*E%}ZK1gXd1iLFB^vF4Zt-+`QiXmIoNB;P&6CfP0**Z@ot?$hCR$J9!Sxh)MrW$n@H~R
++u*vRehTM=0ZC|8r88KNs4YWrB&1+bwZt-8FbNke$lfbDGv1ow?gZ5!40E|>TQ=TCXCzZqTb2wsO1{y
+;mI9|XZ{G9XH7ALdO85<EbU7Ww8)9E<yU2mYz>{DE?k5Eioj<$~c2E^-;p^MS(Lxyt*FR?#f_^DxP7w
+GI<_zB<(>7K5Kq=Te?q=yC2LE6{-A;yZY*Y@$CIOo>X*uJZ@pO_E6#PQ*&_SX|<rl8#p>wCj4N)`LJ7
+8&4Bzb-S4F5`G;d&6#(#on+}*$5rK6%s2Rs-gJTR6uR{5PbR*@Bxma?H}C80?&&xuN~91a&rvj_KoOv
+^59hcY@Vu<Xh$I9=Ya=}Z_=JJb7;K&xEdk7q<58h%c*~58QIrzZci#`&y8ZTC8a0D93d6=#V7e$up<L
+wWP=@^C3yBzKh|LE3=}rTW#qK+Tok^a2-2Sfo#_mRpe)XAuz?=#ruC!LUsaWtva4*6l|IAx{+*tmrHF
+krjXIEU|1`sXujdWzavf;&PwA{3_3n8gB_@LpfM!Q=Pi^Nu*qa*op{P^j9AuE@w-ktWBvc50cNouZsk
+e#rwZO^(GzST`mG9G3Y+-?Ne(phb=xamKox1^}7iIk@CAMc<o47heTbvy_jhMDhVntLY{MHEZg7CaM-
+LUtXAzn?ie`VFH;75Y~)PO~ci_EOsVWu;8=saG>g!6R?ciNjL3-}Mqtefg~(qxT0YuDPpFUimM=BF`4
+Wy|I*&hx^4i+ztAv_}^|gSFvn>gXGE&V?-EM3<G$4&eMcl89e)jy%<AF0KKCJskku>J2=~(BztY4VEi
+x_QZ3KChxb{^ZV$|(YXCc&(T?=2DtB?6!v+87?<FCg--iDo$;78vX<s%!QY|zW)$18e^w*Cu+0z2YSR
+j`truurh+V7;`8aFzlHRnibn54S=vsA)Co1+Vru8p+J;A#S;=SbZRX5BLXLMYE{k$4DRayj2b5q1VxV
+Iu7#c2CvWki+)F0)f&ZNe{4iZ+4PqA3yh4CO39d!x8oIy>kLLnli+<EJ$`H}H9HBewy+p<|zadivN+M
+<4qA_&F1SjdUK<x4u<Pwy-cq$jnj5W7p4iRa5M~u|n{W_DZIGD&Muo<ayLiekbj>3tt*Edd-yMc@=HA
+UQePK)%Dsr{9OA&I<H%&^WuwQe_JZ|Pxe^-YjHhGYvbkB&jx`5okvABsjh+@E=d#n@H&C_&A(5)FC@u
+>&=2M?o^z$|sZ9G4lU*%?PkDT;@U01-&%mw@Judo{PueH$Yh*l+ir`b9W;ELAABrCHQy(INHGXcx>on
+IuJ1dpqx6pib%Yu38mP(7X$_W{%f_!*!e_PA;nGLw7cV684BxNPq)gs7YVFmnvii^=6W4p=QjF$4S7q
+)_QgZ8V@Wq9RD(v7_tdK-EyD#qEsgCk}Ze-5*;pXm8<8%g{1P`gUDahm~lp$3~|>@L9G$YSx!AlhJ}<
+LhX{N2aS0??3bNk9!1<>1>d!&~w1W&1h{D+nclh>cH-+Rrm(xMmozeWwv^B$i@QJrVU%R)11rgYQ)j7
+p@jPI9PkrKE(XD$gR@yX!FSxiYI-k|->T)e8uCA*<)?j;eX^C)c@yZ2`0H@nyV0IY@jSkd>Qd(jMl?G
+!3Oc?E+MGoUI0`xbJ$_->jYXjA%b+X8Q-2&5e$S=OgnNe0EMvYMiuIL_W|K0qU5nFpYj#)6)0`1{{CC
+lvOUI%U(ssQUofOBwKJ)WJNtdl`Yqh<3)~=JtKb*<JCx0Xb-vLaDD_U)=oAA{0+j)NbIv3*1&t=fqIx
+D<jqdi}jjZ^^U1?c1I<;&nAvf6ssfa70Kk8Xucf&Yp2(-wm6c0cw?bZ0Ve_hxduKMS0PZ6dbZMgAM$w
+pT3cr?Z^yUcRi~D&?%KEML~zpv3^NgGXs^+0KfBk;f7Lo_s)kx>L4|*dUu9X=$HHWA|0szL!I`Lo=;^
+u+F*wUK3u+&0-xo#TI%@@d?<T!Rd4!QI01I{*%kX3RT2r?FU@_3VgJ?54!q?Gu7}(q)FB0Fdv>R`tp2
+$_fyo3zO_S!?oMWh=?o=RVx>f1qNh!=wVs>~AL4wpXTUTo^kv##Jpu0uL5J_#VmAGL+M_~`Z=~5v^!O
+&p7-LCumKft6I^S18JI=uS4O)ErD&+43<nTD;k<OA6ZE(E)|J=||%=-y>-v!An#o{|r$IbX<%B%-|;Z
+r`2yMyDN1iYJUF+1TIm*)eMbcU}hf<Hv<!U@zJG!Kb=;<7^v#UAH8J}e#LF?xvhINy<#2;Z0wOZI9}m
+Ua%#G}cXWvr;kzR!jB~nlskR*L;>g>y#YpeY6G>?-5&3fAo=|6xN+(Q6oLL?#pIps4v`U5qpWz+E#Zt
+JA6U#>x_1;RK~|>JOwiJ*(4TmSP*CDv&I(4d)0mxSWqtWxnX61QNY_^`^X+D3-L&mjpcqeL!7DD2f3y
+Fj}KYJd7VDQ1KYKG+WWRjyQjU*tlIrKQ?@71g1V&nstfU>c_e+fzLX~XRWGia@S}L664zS%NKgE@wx@
+~xfe$4a%1bhomt-g}DOMis>D-m>tL{!0`}FtW`ck@>qtFGI-D#rFrxNdK@uPkP|M>Z$;=CU4*Tdi=?3
+T-3{%i(~$09BSed5zmTTW>{2fBVwJ1;cR*g$}>-ml{KHT=Gg-y`_#z^@IzZkhG=;79U;c5*MpfqHu<o
+|*Ca5gNZA!Fw-cK;Jvwv*?A6)wHLub~Z52XJLkY?qmH$iC~Zn>wD1aZ6w({f84pN#(nLL{sh6a(Vq5-
+ueu8G8YJsVW#OR?MY6ph%F*|IO+4>ul=nB9Lhy^|ocSYeT+bQW_0PfvABEkcGc|H(Z9;Z$3GX|Ed`D&
+0cp;~A=ACBVHaQfN7$3I+MjM@9_13Wx*vwKoujo<Sx62fpW_cR(#QCz5(#yT2dV1K$KoQdHd=Iv2tJs
+TY-_@*<#waOm^IOgmvQ1=1vj{Kbbt66PMMG(w^97FnB+`2&q)5G`5!&xtVTHyzxq-t@JD+P7C;%P=X8
+~VVEo9Yy6+eS3-PtHL?uKqs-Dw^H{P<<RM%&>}>Mf;rr0;~YS;T^k=Rp@bcXq{tQjG_A0mdruxBGKi{
+fu=df8U34T_&1O#fqFh)@aVH;(JN2lvyFww+{Iz4du-<(2vTTiiXBADBU4Cn@7Z`lfLi8x4ZD|80g~G
+-V;5hnhQ1Y{Lc4w(Ake`WIk@Uqe9!$Sg{`HD8qX?+os_2@~)xjt`N<`D8RETm9^$U-mXp+wwT(0J5t5
+j8pgOUc8-T0pO5>Vp3Qbv*p(#q{T>GWPbjf=rTxD}Y+gh21f7V(p$jdDN4C1e9_6nfuJGe|nC9>V`JO
+R*mxfh3ucVvi?o@&gZTSA`Hiqz03Q|9c9y=3`)c(BvmGWS|7PmjAwMP#4Yx|W6d#xXtfqGH=PJ1P8ot
+E87Fi-IK!NJ?F8OVz^gYPLYG+o$-O;0g?h7Ro$eG<==e=mh;O_aX(CE0_Ii9IqsXQ`h9K4>(B$2cMS{
+$2|2*LRR_YNfLW$?l+i^Hcr4s*V<bzkShY50%vb*p!ECmrX186!Pok45#q3%&JAd!oj$4@QM8<1S7NF
+9H>K^x7)&cD4wshu<qLtPpD>AxCzfMnZ-H2XxF+Y#<vRh5y%F9+65mE{?uoYM(-Qhl_K__r!xh%@|ZC
+jF=G~w8TEX1$OnI_Q20q%p(S(0nK#c;U&`0iQU80<9>Oh&`(|0=vbHxxKO1L%T>WD9n`8(u`2K79K2v
+`O*=lpe&efx{U{W-{?*rmY;2!;a7~VE~i$#22V|*?HmA4~B$owNImpUiLQ2vfs`NZF!Pf_;WiOPNyW$
+%cUy-_Q>F+tf=_)j6SFDD@rBvaI<PW?FrmhBz9-$!4kgDah3O6NksKMpKP(fS6!_qS2rcEH$fragcip
+$20<_@X&TUv^&X>7OUg0u9a4_)b2h=>N(I{mzW~nOM=UWg)L*%gd1Noa|^F()y9kp)AB_h$WOziN=5U
+zCBduLXF=`glzNvun(jd&LWKSBNFwWH65e=v#IDrec_G}t$Xj%=(OI_+Cls8PwYoa;eCJ})cawJt<^8
+_bC@{o>hSK5cC9bYB4|f&hd?{!MwV&2k<}#Xmm_$~kax94$8wF1{r1Up{9`1#GoFsGBVBt^PU~w4=t%
+u7Mmiq13px(iV|4t3{m-N0HOD6RLvlM3P$QYNpDx)D$WAiv@An;<%4TeXE@r`IY=+GcvXd41nqBn4!u
+RN2!)->EM~Cw&XkfG*8=Xem;RxmBi@F5?!;3mAupNwv^_}$nal3v#Q=<Ol34Y&R<y)u=Q~B8%v^QRjB
+<f|P?bqXI+iDkmFjLtB4)@W^!)=O#yEzeDLwi1M!vRO7Gv1O^{R}rg-tsf*dxp%l(HUHjIZ7A5-sJv^
+lgCSSxP$|p7gPsX`w!|nqxYasBHUNR;eHFAdHP2ar~gn~`s?HB8gEa19f<Ey$II3E3tFA;GSu1Ep{=t
+q&~ejvy(im+^L(GctbXepIwyAd(S5Qs^7gieI!JFmi@G2XezE(@>L`qR_s|;h{T<x*_rdQcf2~>09+9
+Gn_vTM@PAbLbbUrG{#Ww(ZGhoAK?e1F>i=!xpqJAw(N3h4oM-uLTt?$(>&L4V48%N8r3%?_o@xA-QrJ
+UyR=TuD|XE=}8r7QpD(xD_)M0+z)EF;c!@AOmu1o;Svm%>4r74<Q8n&O<5h;iVnJ>uR&=l0lm-Ku!})
+Zam|lAm+}aTC=|voXA_qu7byv+^Xq_KnVEru7B<-JYbtLo(z>EAJ5KL2#tOl)!deUG*t}hogLaYOj=+
+D&9${fv?cJq*xxBFW!}JDfQb_zSophVx{r6;VKi^48{N}m&W$!EE;;hcH^f8VtV-8_&J%!zakf`F$sK
+>a&hK8)6T4<zIqye4OX@CzHZthiuTL0hy2yHUUzF1@G6t+>uJBO%EfAvbCJUL=c@dY8g`b7b44m6eEt
+(3CtFJAxUc2wB1?yI;1kzCXW?%S&ou=rQ6JhjYxr?f!HJD5aQt!jukd3BZe@Wc(%~GwCa{qD(sesPFl
+8p{8@H~`^DCD)w{w7eUQ<R$SqwTpuZBH&N)2KwQC}%3c7`cG(=<stCpOdL;xTci2fEoVcrMQK9MHZQ<
+&|P-X^)%x&BQx*y?{ggLB~-)l6gMfh**oKl?npnPjk2}Nyf29I&Z66moY<Z?jiZ2JiGPp<*|H5T@dmX
+>mQ(b9OYX3)1vQHpgljR?N>nG@7Mb0bUio)IQ~7cxPLw3e$oeud94fkJ3NU0AJWQck;U2P1lOy<F^-o
+#YKg^7x4bIGwUUI-_=sX%A?815=SJyc0^_k?n!3ulIqg1*U7XjcjRTraDS7Sy)AX2W>r@^vl(SGPM~6
+p!r)6m>#c_`;l9B^-?(8%=|FvnuXtLFJ<WOERALCx|T5stc(u@qg|C>u~bm8h&fkV^u`&8<$W95x4{C
+w~kOXz%B(#arTyf8m`SLJK0G?mX)72imvsZXGC2Fsx5B*Qm7&uZlP4BuDw5kCI9p5OcVm{&7w$ac27+
+Krz}^3OEVh0DO6m<({fhnbM6{cPg<=S3f)alD1UueSsyJh#N2C&$C4P*0|?$In<<`##cP+V8pL8t9uN
+giNRDJWhW;wIjk;IJDKq&;6j7ocfpd<C*WvkxzD<Md;j8e)cD9`oCJqrXQTtE^uB$Pr1F*_$}xlbngU
+g2<aG&r_h*>AL(dcx}opO1^>zCX&ji;pFsBE?&+*u=~^CMfwTpDZL9OXDrx)7<|MY5c)n2<XZ`ZC4s4
+9e-3hZH{y!ncefb>krmMu>v66F%(q-avifMlF3!q8m8EbgJWc9@RFPz?ADi6o%qs`Ybi@t_FLs?B)S&
+F7Jw)CVx<=AS!I%f4B()!xrn|LPi7xpYs`x-w_rOYb)=~-<29LI2-RUhZS;`1QGi!?Y*1~|7*31{*;+
+Y7LNLo%IpsYVdfb-x1orI^%6kgsb>c_C;~BdxGScP%3OgJ-K6xm~;eFs{d>)R8?FR@)_I_h*hRZ-X43
+v8ui!?v}O=tCaaKHnZ=@oznJ>eRAf=T<}#!3?#;UvqLZC2|u3NzF#P;ozAx1oI!mkh~XvCKhSST^BmG
+Rl3DlHre(IK@cG}4&{wBrwNgCxrfFKJOPV(BhY?;w@WWtRyVoObI`t(s+AJx&FP`!ap^e{;df8xWSHR
+9P-nOI8i(cqhiMsVmEJEq%JEf~anv>MOaqXcFJHGeju>jg){(XU#meLU{D_~IC1xQz^rLkK?8b8uhN(
+zS+T-4X0r?FdEMC-Sh^8E8l&GV*l8ya(`b4%B2XEW2eoxcM=Z$r5a8b2Gr&#wW8I~V;*@H2@WE=y%k)
+#AA_iPc6B%U%HeM?u?Nuxsu4>@dwqrExYtw<|M7;49Z!k@s7$C*HN?k)_D1x0}>v(%J$lbAcqvqBT@D
+q^JJz4<qe9DQAS9SK_`-`sh0Y??r1bm{LRM@f$VS`MBe8ZH&yv=LKekZUpZMW}ooqA`A632Xqb(Xv^0
+#(Ahy&9`jaTYR>l{$-L$_(pZUZZ^^C=z}|8{NV9E2G{+i#6ZuJ%nvI*yZCs2mbsD|-zMTr6f5+`FwcF
+IT)45BEiv<-$;AWhsGG1=796Ww-V!8b6&TC?R8kIeAk;)eRwH$VfEx>)}GiKi2#LW}nb$ms{W85eHby
+V!nGjYC*NdM4#6TcblH<gtsiE&f;xHyCMo;+cD{!P37I3nIZHx`34@f<G!i)irM|AKv;&1xpjM=;F81
+-|Pp-V`C5OZ}ylu)9Ic?$SORb@=uYaPn8A1*o5z<fJ>9`hU{`-izk(ws)#{nBdo)yeaa1<Y_)>j_~I<
+Zi+lk&u?hYPpgqmdVZRT=O3$)UG)6pSlgbce&lbm@`8ZG%z>jWu}^Lydh>GwXsrnG@%*ikO4zDoyI7l
+)q>UHpaLy!vW311%RMwuEq7t6n@i7zWB+Y-x*ZlTG^Hk|vV!iGA>ENV!s-+X>sScO8vsj6D@;uej3vz
+7yx@$1;Jk{~@*YkLPW;d1f!90Er`)Q@1JY30?;yU)Bm+FwG2(r}6(w4a-R@{sC3fo&<h8T<D99`b=F5
+_Koyzo6-Cy$FgueF^LKR=DmQU4t6cY(U~1K(FrelGC+{2*V$?s$~eq1f0e8Us>b>&RY^P8P$zZ9@KRl
+=H@Pw3o>&P-yBc{S@rrDcG()=*RY}SdHzs4O?Ddxy3&~yVEW8mc9;~x&dj3hMhlVjYG0?$%PF6OuDDO
+LmJ!a{Go_l7a~s~@=*FAd?Va81D|~rtg#;U`IJcs`75+Dg64~PX8r?g75TvaFUaD(Hvi23Ptqzr?szf
+w-v39os!CsrMg6prIG5?GD6<u1(|$nfQMPeUPKxJf{7XUF4HkB|2e=b{uhX8Nv`;wA14f!Hpe51K13G
+R1o%kN0fVoMlk0Oh;)Rdpfzf+r|VYB{v=E^-;v)-?I(Ry&&L)s~2t(S2<Cfn8@Wa4U*R^H!0bDt$K7W
+i_0)-2j5n&e`cl;c5L5^!kv{uk}bOlOwT{7;%6&FkvmbDnS1>iXtDbmwoR++{RxsEO#7VD3-@e2oSs`
+n6!YcpI>o&zZ{h&>5SR+FbY{6Dz#Npg*5uY#C%NgZM-6cS=g}mBHW3$NH}@Z3gXA^AYIQ+otT5Q_X*h
+&j;U(j~gW%N1Q_csPBq=2s-a`v!;I|5^Mjp%*S2A-v%u|BQeJ}$R;Mxzq{a*e+&6(%zCLwZF1WgpKC!
+dGv}*Y$mjKg2ee1v2LVe(d(j15gS~Ei7Bc7kAzKxswP})dU5i*t#`960WB1RxkML-5Aoe)G8V^px^(1
+RtL+b?~hxbz3e!R1~S+=e}o`P>%XEZ*Zifd?wNV9dus!vk<cwkoJ3Hp9=mX>$cDw;>q+%dm#F1<f6U%
+c;_zv^TB{WXni?ezW{?fo^Y?&R+a8XvdO`vUEK!Kyp>`vr|B{ttWa9v@Y8u8*%hlgnI^K<*)^L*SsvA
+bNlV5_`!Gs13x{5~9`id`pmHog{kBiJ&DaCO|I<u`L7GwBfYj(%NLyR!dMuYYE!+fM_eAsJ)Ru)k)$F
+5y*gHe$TVk-kHf{f_l#R{dfMzCwul@*LS_^UGMv@_hRS!8OHk=#CyD-SwBs_pJ}|Gxp;wmKdXMZjqhg
+}?`JLkoP0m09%mii&oSQ5Sv*g^FRDMD!1qPQ`=Z6f)yDZH_0#yiwnV+3U$S_HeE*sH<?(#~8RPwD7Sk
+@JaqVa8cf=7spEcm~*~Ko&AFY)zd=C6%xt-6py0zT5c<-^;Drj?H|45bDL79J8m0=q;yr(UW?fieTtg
+^Kwt)N}2WnCrxc@`d5Yb48Ky_h4;qzSZT@gykQ%bM?Ki+P5ScGMVjL&ncqD;7&SvlcY!Z(=d`0{xFkC
+yxM!E;8_qu^ho`H#qEqdd8r~i2umD8PZACVfk{qI7s|Dz`K3MbJv`8ly7GO?}_tAk1AU@l=CjZch+Nh
+#<Dz;)*|WTjU#mO2<T+i<p0CZ|HDrcKUps&^~QUSX|&x@=UgbpId^7imOST(yTw|L+oXGU@QkylT+=N
+U$>$czyaQUgJm=O4g{MWp)7Ol1?#JVtb1lXh(LCmyW9*+C_xFdx=iD74e9o=HIhP%A&i!bdb8c+=<DY
+Xe%F1)@CY*C;tl8t9bJ6v9K96_Kk;itH&Ggc)=(^SV;pP*o58G?%cDsbVjyw}>jF#>a_0wqocOBO18p
+XeC)l`lL+xwQq)Y&`mdq4KO?ro7d>|4-|CslZ-)OdEs(xZLg5Sy_!yY@+cqBv=fZ`&Yqrn%EK;s0|;`
+sBC+k>wsY$~6fu%f!l;^w)^;!e|##qc@swKNMNcXje3a%SE66=Uk(FJKa0eh2QYOa5p-X-xTfC>A&<A
+ZNv>bo6FJe&bXm@QZCqgji38$D(!dg*EeMkU%P2P-WO|$-btDI#>w>Sy7!wy1=A)=o$`Q1%q2W#{#E)
+DZXERu`1WE%KRrg@3DPDx%k)unXBfUdd|vifWsgdIV7F2JHxX^z@pq{&+(@0<IhP)c%@>XFb9Iv^qCE
+1}UzHyg?N1+yXqRnXqGZ7hw!KRCeB7ET?>J~{B=1br-PVRkpQ;sT;{;<M1HajB&v2-!25?jQh}b@<ov
+x<JTEM4VvpGC{yyqJ2U%TG8XZYiY-)t;>l$zUF%&ojpA6X-=7uSjF!2USzf@#hzpUKpN#|#@cSAmj&@
+-YURcFAn+1wPlh=)dW3{Lo@)r5?Y-k~Me=bEgjc7Mwv{s9Rbi>U(gGbS4OIX_1g|J8LYW<P_v3=7n)-
+S%bI8vpL+)LQU#)4iSH8Cz+{bwz3Xwx>!%aJYK?-wh7eJ@Ggh;TD0RPoN52WdommCH;lP)UN(DEC2?)
+3W~=2L#=wG}lBESox7{h_4N;<S(z(UmFG?7jC9pt^t=dv`R{GtcT#}UA<vq{FUTdy<8+AD-$9`Crw#^
+(rf1B;{UU?5-wBSsr%E>)%_9Oir|9M`y=92dzgm1YuT&LQSQ6cen9KG3pcfFHF);lR;y>Z5T+<GUd^)
+}a<>%P{>_0}7>-o4-_Ag4#JcLUe$no;W=?uYB$Y^-;Ac)c4+F0kJ7qt?4RUadD{JehOjydu{-FpcpwA
+%CJ@+F5s@-@s*}fqk(~Ki1EUIt%+14)kB&Q!)d;Yu+(&B54cPKL3O$N#k6`!HGNrC#a8PpGi?Tkrc*>
+h7}Hl6Vpyd;zZJga6;DcSd{J2lm^$53*pAc>8I)2HUu1?UGiCLobQCPy^ua}%Z2i71Ma+31l-90?qu<
+v@Sc@Jr0dU5oxEk?8$BfjPQd)RDXr;@A&EU-BZlUk#JX|)4$v-Ii}w~>ES6kOUH<<5;sQ++)!<!6D&V
+*Arn5W9=bc|#%(!j&`vbIRE4+iYwJ6htdQQ|qJ4M%GY^MJi^}5XK=Apf?mLz@8R?NS=m2yBiU}v`*{x
+n$UFJe9Gu#Y<I;LlNx<F5g|;r)Z01J<`AS>=`*^9^ggqU`bm@{ZP;RKeK7Q>D#Pw)<xo&k9RU#c`ZNZ
+(zL{$KjYYN7_hDd8VT>CrkR%6?vlkYCizK^%7_``*Ml&I<d;N<N*32ov%5im$*Uasav+CcH}P9Z0?#<
+%C=$r{r~aj`f1}lGtc$@VRcrX7!IFl%=@}CUY_eOjhyT8qt5l0#y!`qf;zyoJ*b0nRR@jsU&nvyFDEN
+oN%xh1mgjz2^tu11h;ckS9C_|D*F;w2xzAV;?&W`0u_AcxKVg*rZA2UY{?~9Uit*3=So`8P=Dm%(4{$
+sRc-?THewZ-(PotloMf8)ViHy7R!Z16E`5&7is`eTC<|@Jqu*(6=7T()1lnl5zE=%50fq6gd8V$2=8S
+Ot{zzocB#toN<!Woy?=H-P#-Q}6IKWjP^+F|MX8unddqOv(`bSiu1Oij#PVYG3t(T3#L0E@$D>qEejx
+>oWnubfYu*LlCT#Fff>^`^?gS<SiRqkduw+lVti3;&<Y7QyH6Ouy1w(XMH4eG}ydJU<;i3wbx_{yW~6
+8*{Z!OWrbNk_d9{oHzF+xD@{xYr2p7lzVh5aICyvow47_)$f@?oHJr?22hr5RiGckS79;RoPj-k4)O}
+W@wfXOb&kvWlo3(4)*@|dWPP(PVJ7Qi&og$)Nc|HL^(pU-Q(x8vP2fCJ822vD7=xUv9r)Z+;)olXEBA
+a~g0~lVC+%p~L2kg_r{95`*8)+(bz{6G$Tjch15eDd@{C(9ylb&O^m~=|GTK-=()$tQiEKT{oa6mF<`
+)#k+nlL*rcIG-6KCeAHdm<pDrTDjm(Can^^VjV?%4;Kz8~jjhGut0t{vyI-aa(91^CSI5;n)NpMG|}?
+C>$G-KYF=v)s2Ce!^vvU(!n$<Gd5Fc^kY!zct%8h`*2}X>cvpM&|shQD^YdA{D!UdGtWX2ak!-yuqR<
+-oUQeTWc9#7Uc(V#+0JYI`Giao`g7tF)svO<>TBe$GPdzvgJ8hh;uSm$-HvBJAtFj?-vbISB4tT!ykq
+B_)iTuGj||=XBhSeu5J~3KEv=|x$h%I+gO(OZKs8@^>!HdEUeS|k=mb|BHF+DFD9+}-N&5c(fV5zr%K
+L2Q+6)Y$I7++h2GFfp6E(Fh%>S~gK;;+w<<FszjiqE`c1!X$t4~A$!nk!2JPy8wy>2nKWp!%+#|qKli
+sua>}?h=Y0o6!MbmfmA<8ba4RP7T<CLkv`;~No{<Mgkd4cms_wjy<elwo)*KV@i>lv!a(l@&ECT(e1y
+L4z_rU-VTJlBW&Y8U>FU~k<x94cZwtXQ=A<M<fPA=?=1q(0##{ug7+T$`)Fk2x^z&rEEp{2^s6j45!B
+XJ|jhG$+ro1!D`kflo{0#R=+mJjclQPMYmGCQ972rNV#SGcfK3?}VzgrZn<nx~Ae>Ou_&BkeV~?PATi
+S&{hj^*?4c>wQZ%o@gk9SSC$C6><Y(Kf4Q^&0ep0U50UyN`R?M`%ooe&dr+QbI3~>XG5e`6NPS3t!`(
+x<lZ1+`nS#BHdG-w{yVY^|g$TVxFUG_;o9Tuf+$7)wZB%as@A@<R%^|OYzYY<ObrJRx3f~J8{uzKjai
+qF-<q+==-+ndJ)>vCOv_jfJO+2w66sn4O{~KkmO1r**m44Da?Ji9lTnCzAyHDFvfVN*jKU-6-k#X(k$
+k_M5{k%kp`}Aq&9fOnyEMgbGW#C)jw2a?DyG!4;NjTH+%r;oQ8Mw+iT%(@zp>FE(9yu32<6_0ch=kuU
+toKxl=$1N{<ZFU*JY{M;nqliWB?j&O$~mPA^5Q>aO#f)Oj<zqBur13bY%4kctoWuw;K>e)#aUaVt>K4
+jDj(OBpIWD-+>bq#+ISVtIq=3^7Mp*^c?I`40|zI{`{uE>$C3`9AI86NppPlo8?_ks!n}BIK5bz&*SK
+*k@!_Sz==-oH@6F|SIp@qZ@!o8-g)uGe0<5bmv$t^m`%o6+Tf86Rn-dBZnRpQ^-sHIBDvKW1_<sMAK9
+o)I_F>Ft*IK-jz|%3-2>FsB$Ud}Rcp3Yu)uIP$m2c<sQ)WKjPC8eej6I($b{)0k3<}7$&C<7Yj+~!Ev
+w8bxXkB%9zPBvF`|`E=?vvo_*`D;BOc0OvB#0{V)<q2~hb&@EWx2u)=`$e=Ti2adu}hxWz!BT9q8YA#
+(IkJ+EN!9f-eX3cM<7=i_Op*^%fjy;%2GZRil4B_b}S=&S-3AVP6&9yU4fL0Ry*jUeYj(vj3a<=19(?
+Hyma4^Vf#MQrmmTHj3H_BE8Cfa@%GOs>mp2+f!>&~lkH+ZNPJ(D0C+3@qu1a$z^`_%w~Y0nT{vM<t3z
+`<?>5FU0pl>+d>b^7|7#-b!dPC$QotHHHRtm)jCvmzuOZr=g)p?tN|yh%vSev1zhI*9HbK_DUFmCmb2
+MW<5q8Mb@oh!_wBaB;L9=oq=^FE#OgH?UBk6_gZ=0R}H)wn9UiQVkxY+1R##D*&M>hM2wr#o4dC1r&k
+oTnS#G*M&9|gDUH_rk2#_C=$1-t^<WE{jHYrLCr5YJf?eOF*CjFVAfi5$x$IhMd@^x#|8$-XzOxxP27
+Igoj?eaFF1F?Wp-XGq5Kn_?|JLK^`yPuU=2K(nnpo1}q}b<KLj50x+G!f`>P)^CGlnM1*IjYF*;=0zK
+okIpNYrfXwiYWjG~yBis|B{9N=e0)D3+23BHzdi|93CAYR^ZbZkYD9k-Mt|vU`j#Y^{q-e|vY{W(Z$_
+=3Q}vhU9O)0ZSNXe7)8DoW^*8$bRWNmq=)o0ionH3agMJ@EzvOd@M)f-qQ$Wh<^mR!z``(*q_!6jZX8
+#`-7mW813f|7q_}iz(qC>u2XN={B7-La)1_~cXjc3`&c-$skitUH<3HR5sq|xJBlQgownk-}Y*Nx}@_
+xD%2xxdQ(H}+QyeAuhzcxq$~k`z8LCYynWg)#7uc|<rq;-XdQfPB?C%1<nM{UL8W=H5G%XY~f!%a)hL
+d9RCWI<!=?4blhp?R5{d)0ev9+hT}v-!_Av9B<t6PE(WqOpm4G?60976KC{Fod4C3VL+U_<@rv%pCPj
+}u5}HW{#hoy9Uo7Xj*T+Lo^<ev;2D1fxpIZ#(>9>+hMn2Mzwg-fQkN#;(9h{F1nsY{7+Q$4m-1-W1QE
+<PVl6XvC;fa`MxadPtMcw?R<(+)klKkp%=%OI3U4iQ_pON^p<8A>>Sg%sdVS7Nce*b5LFT;Y_#Pcrdb
+8*l>mOs!9^7>#)K*JBJ;TnoAWn1_m@%R;ZsrWgj~8i_X($ty#^>J2T$y&uO>;dCS*N6*x=_ZZ(<0(a$
+7{@Q#rWoo4av9)GJX$r<?OFqGx9=cMtt%V>0_T}$L}W8dGLtxYZxO>$n|;3@YgWr;!?Kx*A7dWcSAa4
+sQt9j?fZfM?i5?=PRP{s``gO9OtjsJweium9C&Sym}|K<cCOS9?iV-BiySZI9@-K3F#j&h1u}2&;pM{
+nFz86<Wg^%$1MOdl=Lz@*zO*x21b3_x-tAV+yKM((Jof4qoW+dQNB@D(4|A@67_)As&QivsH2ukFtGr
+zKlTk+(3RwzhXAsM$tXtk)VSTbyyxhQK-9II@IoGsjj*i1S66@7~L0+7KK`-+qT%mVmXwC}SDt1^zJ!
+3gBkHX2pP#g2oQU8>dD>ma>9d${u;wTw>ob<0Bi3w}BNSoYn4BOFhWkoExGAh5^CL`tx=R3imMT}p{*
+p4Ip%yi0JOVWNCWA<iCTUdD?66psJX<tk_(LwvxsQyOU<i2M95cBt>1ewQ&u@Ub02>S|ia^^RsDL6PC
+k@IT2Uvv?Mqxe4APdFws<6v@cZ$Mkb8PFBRhYre^T%>WS!tcryl$n{6N9~_Uie7bnq-?|G9x~dOb}#p
+dE?bW9+rBKku8FAMqYb$-P(Q-&D2AN6!Dj5K0_>^GWy<$7KUo}n0{e^iT#Q}66SQ{;&%Oxw<YT@Z$Cg
+(@ZFPW$2e7bf>9cEw9nC%i7X9-)?iQ<<$8v2bN4Y?ALLQ`_3FPRlpxxyEb1<jQwM&OE|88@x{B6q00<
+`lD?4_M}7skKzQTWF`R-ung7Ull|e3kJzV)F^3?FZ<`X&1EBkvbkf&mUV$nV-638Q1M{eO2iiQQw0zh
+Is)?zpcsp=hFRJJ$=JU|EAUFO%PRcs+GMt<^B-kzu_z;4V;q)83^xA@*Ubtwh3>Fv`ufSoFEv}NcnMH
+O+S77T_fWnFg|dK`)%t4+Mg7<zNppji=z*RsA3$S9>}$>N0m<2^|+`P{GY1T^N!qAqRG2U*Fvp+nL||
+l$s&qYST35)JJ1!DNwcM0m?ihlZ3*-h%bh(Nzc1sR0{(v^K@?p|yU+yNyjq)>!|`s46LWZ%{{z8xCeO
+aom`ev}4|7zz7Hjp4-{xw;e~#~ani`j1lRm7jgPPPsyZW^HKH893vhU;>xx$h)o9*-`cI5JGZA?hJQ<
+MH{X|u^Iy^H=9HDt*6q~GVWmO1+h^vy9fqVIU4j=W2>q^h>EJ95c4t`OC8?S>9zg(X9NBaBN?uXAEYd
+$N|?+W%pwsM8MKP>A|&t+}0d>0IyTEA&+^W4(Vte_OmSw~4~EGvPa$=YVT{pu4mSiMH=h{8qB}7AePP
+_#R0Uo2Q%)6}99FFKxo4oy5#=AB=yIHyo-ew9EW?W5yuc(^9<KjrP7gsC0fFOUmqpTGOF4!>&auOYtg
+yuMFQ8M#@Z>ZMQTXvYTbrq!{{#4BzKbraBlxnTfOaqh0_oYObx3{nF=Vy~W;I9x+baP^jqCa#8Z^h~0
+|0kHWD)dyRWb`oLcbTHQBI_yg<ol3tw6;5Cb=Z^+?2Az&Bx&rOxb<$Ym>v`gN1k=QJ-pP$D#%THYIA9
+NXK^N9)m@V<AtqvG`WNpBmozzcx(dUAzd(Z}b;@PUfgwHf@EYs3#TK@*#4n_w%~g8|0%v53t9r{Zr+A
+IxZeE85Th;&U?hp5(RM*XThxR*pSltkv}YKNpMt8Q(84@tlgoO`oCaMKV@y_t(>L#x0U@K{wb=Tpgs}
+4&%*r8h%WsACGOK?k@+-UjY6!E)qfVB$Ga-|LA$Wb#}y$KS(`Lp2ipudhjPkJcIa8+1}x^VK_|zoSHB
+n+egYb$@Wp$HwkkqlJhB3en~p!^L^B1pMkTZ`y9UaX+_8B^94K$xP-j>2@v=24*!Gnt?iON`f&vkZfh
+=+c|HQ*AsN%G|1$c&H&r_Gh5tBx#;z3f{eQ_`Hr>m(Q^$^j|JtN{%D~G88K=@5UqzSI-;dw<*Qob3)R
+i@84XkJXwpIQI4GjJV_QUZV)In?BzMZPAZPEvBte)TCf4UQu9^ZHUSrxZ^w4ap0N21N%9hR<6<NlTNl
+=)01WBx8RuV(4@W-YJ_8M^~==X4p@SosCoee=+MZ#HngSPvGSl`#u~Vx}IPWj@c+gIAc(MS5_C`8*x-
+HlGXh;B@o(b9!*9`CNwio6mh^!He)LeV-%z^k`=%`P}0MpNn@_g~C31(Rv-ynkMW4-j8!n{5VbeJ<0v
+R_aC<>5>b8=_QVPq8ztTM`_x$RWJb%U9_hC}I^H@M)c3b;obRU$#4~R7IVD>&P6^|CGOq~a%|o<vVL9
+5LZ8#_6q!elmiWhn$sOs?h%iwvb|NZVc75nobzR}*9G;-}Z`f!ONqn$(dpHsG!w3U|hJf!OU4t3;M*T
+jv|A-yc;YVbr6wDI3QV7<}s#rWTEGUi1%enH)T_)HzSj`N;#YBJ{ZHS%+iDa|>3GpNe*`(a~FmByU@6
+W`M0-EO+?i^iOcb`C8(r}$enr*xm)n9~nXXQ#1Nk?U0Y!PxjnpJbiVKfyX(8nsUIW31D~#++`8Sf`w*
+b;^iZr<c#GI$s@Uono!gD1S%kgKGEsu#bq}!fTQ9GUBSr7@1Fp<oUnLh%d4EEc%Z2SB<1MfbIL$27I_
+resz}l5Sr3F8!aPwH%HxfMZnwDBp&yW?-Sw#?LX7Crgk~6yhJbcD!jWJx$hIB?)x6&ec#*fh41@*o)+
+W2PmI3rd+fst-}jkkPj8~uRfhGQB1CYSVSmW-&z}g#R#0%gaQUBpFuHs+-($uTl6nif=zhhn>~O(v74
+5Xkn34?@A{^WMG<Zjz7w%^|D)W;m!#iXg8qzPTcA3|V|1a~qK=!6gM7xhEk2gu)HvcDj5c24*70UjTF
+)bUWNSd#glqZa}#h=N2igKj2-^^9{cG>?lJ9wu!QU5*ZmuRi4kg+Fa?y?hafG1~cVa7ts1FRP(iOsA-
+yv|3xJ<sM39@nVn>M3Ciw<&nn%NU{)7;h_FpKugt(`<)v=(e5>6_tKC+BWbY^8sM~uD&?K?|dx(#@Or
+Iq+hBD|KE)G!yTU{8X)tX;2QkQp`YcN&^ExxJ0at<%#(6~jQ=h3=LPQ7f6Y7qj9D@H!!U3E!Xf3iJ43
+EnoUa$>QOhgp{3^hjaX$1-*k<HXWW4*(1SN0o1bmmMn52Hl;q`Yw#)|up`(5|b*2jjmv&D&Bv@>-LTk
+H2*WDbH8Kg-q6c8!W-4SN4vsO{9rFr0M!4;(lAEz+aos{d{jyjEficga|iqJ*-$%8M-g)T1!Y8*RGY!
+WnGFdgD6L7M^`G|3I%W?6E%z6`AuP411Lg&M5lo3TX9v&xXdG$CojW=Qt0;Pi5sH<<I=0AxF^GY58Zx
+64NezG#{k-%yXSNHORA!oa-kR`t6+y{CHPO+V|Q-6`LiRPm0;z@W;3J8^<{9UEtn2B=fRrzP<{TE0FP
+I_h9c5hZqZ-ch}6jc;q6n<g7K(-MzIV_k))~&#n-uA?&FD`dt+Ps{#X7k7M1a+bj>RJnR~Fomd8X8`u
+K=+?wkSSw)b#gg2}i(x&yeHOB`z#;;<6r^}oHzfv(T3pt*jqOEO7>K@|c49KSGqI=&ZA{~5frMqVGl8
+Q1d)hR@YD@l}WWWQqQiOzUs-_9}6256r}ROVhR(igfWFPVF>NF8cyI@EyoOAD_1U~&RzC+2Z4%2S8BA
+KzRr>K_!RcC=HL&reWoeG}zr8@-abjxc^1ixYdywpz&t`C3m&zE!nhe^KAKFhO)%*tXVth`P!<%-n~X
+wtfb_d!|3zPG7MZdqrw3{x5w)`FxdYSx&}-ET1SA(?-zpIgu`71%Gt)VcH089}dmE#X2<aIN(WGO@#c
+%y9ms&ur5Iyd}ne~<?R?tGkv)y(U&_};>W$GT*W+B8?|hSLmlXE-+)M^tkTS!)__lqrfk7ICyo|F#!2
+;@a20dxFUmcV;not=I(+xpP}_?6g{=Xc8;{1*7FyJo*G*nhm-gd!JJy5k5cap*g_k&B*K!WnthNKCnm
+FO!*4)nj9@Oi6ygAnsFG`kfn{Z+a>I_<wd``w9U)^-5Jb8aRebXIX_ANGy%?>!VpiHBdG|2fZ^=c<rw
+k1iGjV#ChX=BZ@SKAkzb;{Us<CiOs_}z%{kamnmyVM=m_%;Bs;_H8CjdwRYMCu^+m;?P)Yx?j~EpG6X
+ls7e;TUOtKS>I~s8Qzp2Qn}yGV810!hHRg%```E)^Y{t(aeQBk@2*{<elWYEooh4jYDasg#c{x{IS-U
+;&Q``x5n6idHcLzUFD8Ze5$y!unxU(`hj#v9&33E%yKsKCM4{sSeX_i)CO=_uqy2i%vmLqi>DXJCkL$
+UDLGqrAw*dO#K4p!UG=#ZmZvP-mFD^c)=!NvPi;*X=&zdNCkXH_e+U8nho=`vM-jBJvwT#wABS&yK@S
+QRLJ@jKVV$kMmjsuo>`b#-{I{sUFz<;9tAZYwk#Mxcyex)6-X_YY<MSU`D<Kod4bD01a@{PUiM*FoFi
+{gD2{g8d{oK{z&czh0Ez21@znCG<e?r-X>*<Q`s+)g-72ah-<Q502!UVM{rC2Wd@bV}VsPf6)s@JGC_
+OVItv@nZ2EVrcF=*5rzN5<q{wT74aTSQ11|=j!||_TlQo9!F2fjMee!x38{n0^cibT9Wg7yX=!a4wNq
+tvV3P;MEMk!x5)A=>q!wM&Gsbcqw%&1Pg+ljO-puq(nLwAQ^?$SHqle!+N<mZsRz{Jg!hR(<LAQR{@4
+Us5-SGmL;FK*v`=w;dvNh>-}uHiM#rBD^Ps)bmn~lU12X1W8}Q?6SZ5z#k^?&PP4H>ufQ?Jbs$;CfQE
+R`~-C7PDUs^M#I0rP!{KoN{w4XGS@Fi`!+$#CiA`|}PFSrJ}^0BRKW6o{-twbGpFJvJ;rAOgY`T>3?P
+W2jjH17b6R*^=d&dO)=Tj|Hm-0#h@enwRN3<DoCeAwgOuM@t&vrUZO9)V};6`uH;EkknyR$B#Q^E<Q~
+?|FH9bM8ucml=C()z22Ts`k@;UqIVy@7Fh(^m_8%3$LZja}yPNYOFo5asNR3ebBGdGFM2vwBaEA;+^1
+e@Cv1?MVIoO%5=Xb_kW`Ml}QF2TOOuk^u6Gkk#FOg&cS{@3fh&8HQ#5kAJ}VAd+F{RMZ-YrN-k1ouC(
+ndO%=2LY1<9=JTHBq?RD#E>zbwD(Rj>N{Kh;z_)nOd*_ZP3$ngCOWKBs6@%_>fS~v-`FvlHP?sw;v95
+tT3u*stpV2=5z!aIO@H458cFW|CWNcpm)Nej!c{iFkmH!gu3^SJ9GQB3?>9w!bqqYd&iGaFn>zJ$5`J
+LpNjcBS`WdrIr&4Ru3|w=!VFn-0g=PCCH;0^bGQ#eSZFvH{eg+-5<YxOc<8R!7I#t55G!`iRp@wNbjN
+W*M(T^L^#B<g>EYyTPwiOn<d~1^AM6j4?YEJmS2LT-q<cf3euyWEDlUq4S_Dc^@~*UWc+Bd5Wi@yhlH
+K#uKB=ZOePL9cy^dtvS~(1+PVWh|sgjhizY4#d`ZQs*MWpFyz4+!KV#EMuXg)#=91mut}Z&9LAzSzX3
+7y<Xg0F7IBgWtPtvb`A4BA&AZ#vOJm%tMc7%87k(!qSKuJvc*>f<nEbo;ydRdg{^L(d-U40Es0xL;XW
+%ame|zH8{aR;+wwU+UJZH=Cn>h9bYtFn!u)muPepuRFV&2OP*w8NW1@NtQ@QREf#`jGIkJ&uD;_!eq-
+wk;;ty*)<ZXRwttN||nz}SuhPpNnKf52(xM+i*3`fw7;1i&wZ#JwM6rFP`*`Ic6HJ9*DIjH@B{PL6R;
+2F99*|2bMcWvsvq+65)KPlFGqymg$h*bEv++n`=+vhUrGLTy)}?4He9J?~lf{79>3{GXA!));jYRo!>
+6mnffZ1>InbGtvnc=)^IUmHJcEdjb0#a;9J90sxJ`dr2QIQ}ls)uPLDU7A@1+4EnGJ^x@yL!~6|>Y2U
+zD;<)G6nR{O8C6=Op=O>)!hT%|~;_*h?u#CztNO}mI`N<wx_Mo(5%hLUskPGFV^Q@#Lopw<~I`YEtP#
+ci&ed?;7z`kaTBEJ8_ah1!NK34qw>~UqY&F4LMre7Rmrw&>Yy`F~Kha4ID#$=fjGkFWooBbBMH~$Ts<
+-<n&q<B$pPf%_B>bSD)G5dNrs;^%}^!2k(+E*X?vJTDV9T@NS`lfN+g!i++3t<sO0jtj3sZtjB9`^ZZ
+eD8VwWHHwuFT(DI<)jU{#a8FUzNem{H`F0><u#{)w%f(xmNent51vS^U#9yEXbfR1<D)TGr6w9$EXuE
+9y}UcmbaTzhupVb7lXo4P4={hCIyVX?3jad1z4l`IfAii<loaqkXfR{<gQm$?yPYyes~+sa+7-NUb<m
+;dzb@4rgJzuP==%>Hb6@(R%7x1NcJAx18Nbau#|r`LAEk`8`53FO9BmKtrkOK2K@_s=wMLtg*P#zW*=
+1hp+1P)n@lA_2zAd}V>!TgliR;66lcrt7k1$@%R=drr>|`pw+*BFs&Qj4=>Sos-dh~3lt;x(Ua8lika
+ZEPGS-(?wF-93PQRST${+g-E&yw$%Z;s`I5jmd5v!~&FNry+-wM@55yB4VjIBnRqe0dzZ7WB*e)mZT^
+)E!Hif1i;@vHZO-Z4bVvavk#inRyhcb6d(Y_I#*n{qb;4MQcP(#aQ>sr;MCSW*#V>lgv9hGor7*8+}c
+qAEwb4<N2~LQ}^2TlHw7?kEJeiS7h$YZ(ux(ZKC{xtulX#)LR11t=KQreWphA$G)VEkxeYVP`<-xJ*E
+jS-b3}Js`;zDnz83?j-B(r?IqePDj0B{yuWym{x`;4>6aRKH$284115~M!#Qi1Gh~xpGVgK3ypN=c&7
+>8HndBwY-ETs^1TFXRES!qD_oDpLOVs=izWYC)f2{bqN^fSBa<7p)(@mbiw8eb~^I8U)%JJU&41My_>
+(b*yYWmhqxy)H%=)ewz?P$~8Mm}ISbvnTh%`<3hOjuKoYy&;)2i*)z6Afm5RMJt#IU)>ffPF9Zw&01@
+N}p5lm~H>1Ugt&nVS7W}D$upLGH+lD@T;b-m~@ylQ1S!xtN4i?Y|%vbbgbP!Duj1L=Q@Qlh28g5Nb#5
+KgK+J=Om7H0XTWvBSbcBIc%RDuVb^UD>y-1N>8}{34^g&UVVb~m_IxO8Ul*?}Azh#?Uo5-70mfpI@5Q
+M1(RnhL8T9((#VQXypGnhR?+dlvGFA7}*6=Fugf^^cHRv4kR&{EU=dWiBFWN-TNNvs?&klq(Apb?(w9
+&6C-gW1iIMruQpJA74QNMrFr_SzPP5s{8r+i`gysOX1oedgapc(nIadsCN`LoNXCv73k>SC;X&F;1J=
+_Ly%a(s4&%Wjdfe|U_ON5f<)WoKJG?|LF_3klni-+8tr9;pvqTj>GKWe(3;nfF;NCjE!}?$tGU=M#Lu
+(3dwE|6M{GyhYssN}DPE?rl?N>uCNwESH=#;s+J-yxFev&Z@B5p$F%DfOBs<<f{8M+A{{fB>4pLE24-
+ty&lWx@|PLqab_MG8dCRjybr8)(AKddm+MHLlm7!a?>#76lOlrD>CoO7JWd17<?QI3&b%|C|L^1RDt}
+Fp#$5KJee>486KZ?-9d*aTy;_6u?XlPgYp~vtV?2LCjdAPQ#>0OaXN+Bzv124J_OA}+$FaMk$JL5)F+
+M-~*tO8`2m3Q)kulz7S~!OCn7m-1^JgZE&iQdt<qI9N7B8I`y%v><XKNU5Eq-T|=biO~pJFYxhS#EmY
+Y{uAP=;}@lkNVu3#`d>tjD#+np}2)HTkhIR?_I&Pq8L?#G07nj2_>$G1lg_7;AF|v~`rf=!N4<_^6K^
+LYpb?glX)a14@Ri=f1Pbob!kFVc&)tEnS&BpCI3qTSfPh_@>HJiRy0o<O0sy<~#KTQ4*>UC25y1b}(o
+o&**iLIrVJJ1-4n{UY0g?Hs7&z(tcOQ*H{@RiuQe9AMy-`cAfmn{H`ub`hoo61)DNJEAlU<-+j8zKD^
+*?qn0`N&bpTNNoX?(e~;oUs{OV;G@h>4rcG*n0BuadUkBsUgO6fPzdq|EpDAw<9#0s#)TWS!LI3>!=a
+h_A<{o0q^E1|5UoY1EFBlhd)0GSMXNl_1ascb%U1-fd5Wv1TjydL`f9B@ee6h@rS41A>n{|alo2OztX
+g6ESZe24Rs>-s4^R~sG;F!{VotCU{411J4wQhZTw(>{r?)i>BbPi|DnFR11_{JQz(*OT`)7N5rzy4S{
+pU?l!w4aHcM^wd>=bW>AK|>cpo4C>Q&yxAw0@gxb2z;C!XN0Niilr|LSTb63q~0{g$9!H}-dBEA;EB7
+H4r3B{pB#DjcQy0GCx{}=nsMMb;CT$=*oyj}$NMRGU$b5B;yoy3oN9}-$=k&oYfWhP+warnPRS>~#53
+<q?YvK3BfK@+MHl15Kvp@B0erKI_cwN6kK3422{e{^KiZ={VwZldGGEkBB#bkC953@e^4*W*yL9*Oxi
+^zCTC1muE_+f|E5Fr%4s2k*;157&g5(|SdFVSq?lBn)GS-^B{v36UPlxpj%dK6(X-dcNt*5~YKIc4W+
+N)CUx^t4aNyc*mZrYv^i>3U(OT`(ixpZGU`09CT?`8O^05_M&ko&=o@}>PM1_kq}(#{O~x9T|OKC*u^
+e9Qy%2=6{4+U}%&6>X!Bxdn#oYL{^*G7f|q6T4`u9BQ<6Q6~WU5M*1S<(86QVsrbg;OPR1${xX%ta2g
+C9GS}ve$hIbU!00^<VP1`f3OVWlf*1%*bl|}Mtl6e=QOFSe`i?wpakQU9<ttCgWmM!c6AmgJKJOHEMC
+**X9)1)JrD05qTw^kh_(22^u6y=y{ka89he84l5=j1>*D=+s4>1PG)DwOJG7GNFNW<gM$LbmJ4SQ<cF
+zBJ#QdYnMb1Ax#{8|A{~W7#0{s|g(9TfQ_ohGCF7JE%#@$aGV_}Ix{$3_yp7t=`Od;p2_GO0el=5|T&
+%qfU*ilyEkv=S$zE>b$O8D(n@aqHoxW{Eqt23dZ=cnpjcF^V-fKABal(<HFFzYslS5MAvU8ZFp;GQd+
+tYSpSJN1b6pE28CV>4{dRNH~&^HmwFY4>|-KVpw~_dXSB3r-{bS<n^M0V!Ij*`za#C_Epw2S4o`%hQm
+*q^!<!znr?o2wtYx<Yg=dFQbhvS2P&D+vL5bteZlcU6En(D(`+Quaf0nU=^DgkDwq1uX1)E)HZog@hX
+{y&l>6BzH^}}#bemU;W4t@Gp%EJjDZ+D#_1^gG}0x)Xc^!eT4z5f$CRhWM3`0Gryt%vg?xhMHRB0IkN
+brIDc4mND8JG}Czn_xtvI>F+7$w=3r*8XzV^a@k4}`n|39P?(uP;_-W!rKa}aa%Uhx#~Mu<Pr`EkRx;
+-_&gK4I93Q;*afVN+kWOzN6m%G`FDcPsT|;9s`kyqgL*E#0kh8Us%<@LT4#n~nZ{KA_$+X2*^DN4Iy~
+t#RImah|lIoww1>dM(b|JbiDcXZo7X4(1D!x$S`uc;C2sO(*l-?8Unc11bi{{QY6uc;-wQFUN*iW{M_
+l#y3RTw7>qY8Wa6z88esdc&?!zr3khdxmYUjyT<S*sELp#dn}N5-cxsKk@AIWLyGbT+L|K$lw2>T$a^
+5EuP96Qx?W4EC!Mw{|LVttmh4S1pZ6xoSn%?BO_DdPmmRrhcK0efu|vND&r3PDRCD+lr;hRXcn=KT(T
+~0GQhuIY>QS*@XA$Q{eS_>AX`d_0rHNVFBHAFomkyjAPq$>|T#lvZCGFXCi;U&#BYqGce(9I?vKyR$z
+X!O~F<%UIq-ntdeD8Qx3^}y)107kAv1?Wo1J;W@S)!Qh*z%1yuLro|)a(ZwDC?=IVczq_%-um>w`jeq
++}}>cYt;C;zb`sSy-an2?$5{mVs6782V<Vm4qw56@_^ju4pC^6ehT2-(Y{T_ON^`E0lag9{sq3KmkjO
+@CH-F$Ug~b&Mmcx9UP3z0a=a&PU6^mwbJW$KUj9tIIB-5xbSwJj9oj#3V2v>k`jqAwd^7Xh-Nx^Dzbv
+gR_{NSnZ^$bAarjN21<MqJzrHBCoNaVDU6nhB^XK0IH^z{B7yUW#E*WLsLc4FG&i?88s($c2HS;fTt*
+E)JIDZ-ACtWl<f0-yDUiJ%{@$DPNx5@IGjM0iVD{8Kk@h7nk-bb+(-y3F38j(S{hHzqEo^Pud;N(X=t
+Ht8l`T4E?2HtDoGR7ObXm<HBmGjOMZ;|ElBg&~VlV{gx)>M|e0`=H;iqyp?wWiz}M?0s~2aNt7{U}s~
+b@rYD9XjcZ_8T(kTtx2536`$87l|cOw+p(r#E924oxZ*4%-bs5wri;O(f#15>rC5j`c8>!nhte*sQCS
+pIMYvoezA__8sItVT=Zn9jk?`E7WzVExHlSdVn>3QwFYyn?hnhYl-syRo_r@P`$W<b#?1fHKh&5U*Tk
+lAfNv4Mi)-ZF&W8L5`nC=2%G{r{w@p{^W-_l4!TxlE7M@t>cVkcU-efP%+sJ%Porcd2^EE~Li`0XEy7
+6p?HmZ`g`q0)w%@TZZlzs4?QF`<i-vYncCv7}=Z`-^`<qY3+tscCX_o?X5hcWXvZ40SW-wIl~ld%%ct
+GRp5hvyzpeoB(2%iMv6o^v_c*opd^t`)(W^9JocAEw>x=ZSY@oW~KLhDaTR{Y{>gqx>-*Yfke}@5lZg
+OUD^#!rB8FiO&UP7klMcv`JpirK0PBlcBa_>K-j^`Fyq4d9Tg&Xim#7iH_}M_BH>cq?3<neV2J34Jp5
+)@$PG9?N;}-<XP@EVhU!Yi9(JeYfYYv>F!KuI&{No{cz{~&Mo$uyLXpr8FjkDi0htd#B~Q<?6BDCbh|
++p`xJlL^m(y_bg{_>S=lHf^`{BK-w4{>n2Y~ci3XfM{zlO7#w_Lk*MYGxm%}I;Yn66J(#K+JyePa&o)
+4KL=fkC#3-3}_8g0|&K#K#fG+8g{pA33zVH^RyBmlZQL(@yZ57d>**vQU`TFk|Xzs^Oq#dY*$(=M6ax
+ya3PBDIe4J!o(~XfWlx0$Hx6xOCWB&zNzYiwcUD0|q=FQZa6psYd^%JO~-szn}4EW!~3Cep{lv>r7+3
+-fzk|WRJ|@)RXFrODxOtk`{g+@BV=Qf5Q5A&Q91em~3mU#n@|k4~V&NPS|^O)U|&R<JuD+S3jTp;i5a
+_*jq@OHJdxIXl60XKgu;j`TdZ6YcZz*&|T8NKVr@)cqVSG+%5_TXT}vJ-RE3xpDnxx@GZsKbm+x2jK!
+U@g>WMM?rQL?YMCxp5l&vi?<ZOL$W-#qX6uu&@1V!}VQ6kM#|?c@KeSriTlOp3ReOn8V%zI(wco0j0R
+L)<L$A=reS#6+;`Q29ZY|S6m=kAfqwbSG&HWa};N}^)PU$2nj~M#-&hPw4p8d4hZ2tC-K!0r&uIZw_n
+elzA!1GMsmkU}n&(#UJ5j2PEDSZYGx6684$wR%eMLySX4;)d?Tnn4QS5)KK<S`h}BTrnMCilQHZN%@D
+Wo6&IW5JmEze_!<!sY034Pad57+14JjcY>0czPqovoK;j1>6%RpF@7m92>{8Do5TKa&FXb1k%4t+vWN
+<)4$VR1NeRc^f1Ky1y-9+joUsl?pSf`WSKQ#UQ)&uN)X+k-3^1-+vJh@txliqb0S^p+h+ExQu;Qhj5A
+96gt~Y~t4Grt_VM0J%RFGW3-3I9J8sQ(N6VF_UjuRDm!OSVko}HWNW-&yPko^L!x&?|8|MY>Zp`}hv0
+!_V^?$1F`wG*Ic&Qmu7n1IK8M3JPoBB#Q$8B~)UeEMJ`iRB0D;|CRMZ<_=TnTxV{Z2FFZ`$yFdRS#hS
+QX(L?^N#jK>7TwFxn<hx?So4mCexUZo~g?Q0gEe=49kwh;a^%?{5*-tp>60QE-?0t;oCSrZgY@91^9R
+jy1{hl}{0yr4Gs}PQ<0(c(yuSR6Pxvy7C8lFgLNM<VidS+VvpL7{k6K!?!|Hxhq!wKm<3(iCw!;=5@y
+W*(iOmx`RhUZBtT3H`_4lmRVKZe~qY1y~0xyL?QL6yqCF>zV|;+dexio%=%RmfVUf^?6=D-Hyz)$ZdB
+#IglB%YrKtX1PFDF<vaMMM7~9_lJXAg(HklXp%`?gmk$jB3=1g(vDN+AVlk|JI4?DlF4}Hip#gcI#b9
+lif%6xo2HKF;yUDlx|*>1j7bT{2|*U&$s-+RD!G~*e(UUy4MW-HFYAmhL?w~PEuxiu8p70yeW;kzO(o
+O9NNHZss2Z4rnYKfI@Ch<Oon6Gh=EYvzG%%s(J92d5=cpY_qkQt*$@Ca65OY-@5vTS;i^!+6Xc{j#mB
+)uM|q_Q#1rQ_mi$TQAhI4m3F=|8wZzfa06)Qg;^A3ouuSZ;eCo0<FifE^&le)&aYg(@LCQY8CZMPq>Q
+vtn1rZ=5&tqQ7roYn_=H9#YboQ-az}5U-*1%K*krAI=FRjj^(-kJYe$N<Hz@krQ4qR+Zgu^(tqH$BYW
+bEu_tbQbM&6r$vYa%m-~V;D)D6VZxu}T(0?lp`yxYBJp~@3YLgz^ouD`P$!E5W-WP8fIbEtYseRGSoa
+^7$gHOs_hNAlm+!tx0n{AkN&3*A&L|yKS-4nr!MBuy!aB2F!!g(*A*>3(s)mC9dxv%4!zDbq)E}r@QL
++p*0Q%L`_4om`FYL<B_&Al;cWN#ci9kDkW8diPMz44&2H_DB@Q8OUz)j###xXl{I=bJcow3lP-jS$v_
+`-8A~Eoy%pkJuk;6T|ysNkn^BqrL8g@cv+X+#`hdSK{R!X&BifBQ!qiKnCE&eNu)xiBbC`D{7x)zXte
+WpX4Wke@n2nmdo7jb}wjaeQBR-RiCw`J@UL_Ox<VSQ2T}Qapa!K8Bq4)e9jzD^0T>bcD*rn-y{u$W1_
+|Kaf!8OZg|G<6OXWe;8}H8*-{;fzN7b8WZbet11bk>clr19A;z-XCv&s{|M2|Ves$hg#ffg-i|q%F{g
+8LB(ze__%C`Il&3<5Of}%l>p<Ykz92xuQb@{wvXbS4yf;P6HOfB;Q12=1chh4)VIle#jD<ASB<J@;$j
+QQPn%%ltdyYu{(G0&C8Jp04*Y#5oRfk)+-XD0c91cgU;Ma=c5G3NU1SHp8{G3L72nCmO!%=OrBLTzQ3
+>)Bz&SO3<ye+c_ir1=<s$v#UDx>NOFg<ba#ilKRw3+@<@@__WwApffy_TrKH8tM|t?Th?&(Jc8i+TZ4
+D%t7ez$Fe8gWW!#QcB9k1)hXZ$QdIm2w!I8<sZPVYwD7xs;kzun%L>2y3g6}8U2gbYCEs0wcbA0UeUa
+~`;@#BnyK=s}6z?t#zgxg}bMbC&_}%CE?kc>yD*Ud5?>>)rpAWw)<h%KJH$VLDO1`@m@2(BMbMxIIyj
+v80H@)A8Q!-9GRtYa_1iXL;q^D;6OtzVTcM0Kl6Zy`8caHEoC*NIxcUOepCGg#Byqg_<r^Ou4Sp85-i
+q@L{zP^$4l6Tmr)-|`2_h#(;_XDA}71Ezg*$P}JzPOwpc#}S~Lpx*suRbQc$ML)d`>Fa_&D(1}&$oL2
+hG*`R>SyC<H`G?W9ef@7tA0oi9^!wW9(*Zaw6iwed(dq2mIUt~N7_mB9vErg#=WcBobT}do^4i^1^2M
+68_R;v@c&oKf=~1R*UN(bz}UDlw;1-Nl=T+IiGz^sx*bAqa4?P{{!{)ZA0TX?XZQoXIA{mGU<@^WpQ7
+0+l)mVx(f99lab4$TD812+oz#nqgJ<y^H05?{uFvq1cAvAx`RL<$(wgA*{T}==XheA;&IJ{ppuT{4oi
+N6{)aG1MHdFpa%oma2p8k=vO>y6idOS;*d+3$>^-Z0SN9<)n#=e=drlWl;Xpu`yJVBY<_F3k%5QEpzh
+W6-vzn(CB_2CCO&J|Z4z`A-N3v@UC_{Z{GDt%AMI@I5FKD|Zy)~}c^yk@NKlW3Q+j~Vav2WUt6VWj)a
+apuWy8Sb;^RQwBhh8ppyj?rJkI@$2wp5!*<Hn$-cR?4{3mZiJ9(6?!;T0LJJyawx8ZrtrHvPR#RWVn~
+omSCOmR$x5mW{~H+x@+{^?jJ_>i9<K+7^C7?IsQWrK9Bxmep_{cZ!0hGt!eykq!r0|6TOaJr9&#$mJY
+eJWa)E#9eAr3P_M<P*Ah{$e9hM-Pj=m!r9<PDS+s^Styo+)94ZnU^xzHB4tuPgLB`R%Uk}z8w9Aa2M7
+t)>ozxYJZkwk2sh_RBN7|Nm+l20Kradp@(rVPblexO?9{ufg<J*(`hIU>tejmnv&sr7Bl<hV%=H++vp
+a@zIzQAwm>1Sa%xS!A8SI>W7UDWv<|3glk4L+M=%?9l5-X7;&2|Dx&b-xzEPx-7jSw@d%*ITq>(}O$l
+zj^J~hxU;Mu3b9RWRwAp7CnM*N2Utz=Cv{x$l?cwRV>Jd-cqzAS|_nplRAv|ZEI%BdjZDZar{TT*SJe
+ajl4_fwc6Y&Zs%iZ<HZGC5z!uX?zDmMe7($X;7ZYdo>wu1*1k2GwtdVv7JuA0dJ{nh!+T=!1@^?^3+#
+!-7uXYvFR&*T|2Ox<;!m(A7GG#j{2F{%G~ZM5j^YV<r_yZ1&fuL2<)=;H2bMriqrcr(-ctH#jd8i=Tf
+9!8@>TKM-EYN?>Gb^3vGJ&QzrZ{Nq}LgO@?`p;X;YpmX|9kq<%hBMD?=d}=V~*~KKeiL?z7p514cQNI
+#Pa52&tG&CSN=%zIv3Mw2^03#w}O5PF`teZp3FXh6j#~jz^SX_+_w<|Cg!eYn}_c?$6qye4R6WwV6t0
+W89Q~OS|DL?{2q)ujZN2WJzze{95tB(L8&EUT=e~FRa(&97S?GZIVv(CU)eS_cna*!h7<$W8*1|o+Ir
+l8QY6G%&(yRyXm(||B_o6BRosS2=B3!9-%)G+AZXnN4{t;V9Nirv1dGP>V{WL6$d?_9mKc0(9SC(?Wl
+O~<S`iM9c>)+Oy${|F}McpMEh|?)06S+*ohPLpS%&{z6<@bzkTEM$1(PukBAu_0bdEn)cD|dapxu)IJ
+`vBlMS)*6i}}_MU2EC9(B(aNzeF=dZcE?8pOVxktx#FqyO^MYl3dg_WY8W2ijTY;Wy2=ztMheX57edj
+KzCmwRf><uL|vf=k~X~Y2sEmj-tyZ>U(H6k|XM6uBgwdJgcrMA^mV&H>uymar#NgJ+&?0EAoWb5&3(W
+koF`Jj(z#ko<u(5TV#ALd8fM|e5cDCZZ*bz@BUCY=GI8Nn&=Xm))g~;#z-E;5#K2{?XD-IJ?2E(xj>Y
+3OcnK)^ZuJLmmHWAW45FT8Kbr%SLI4$Jll>dgp8xx@p+XGwfRPwAH2R(>95>RU~Ffw{&^_7?Cp`<3cH
+k#&2!`CFYJ=G&*1UwSc_C!EBVO$c-mxT)DgY~k}q`(E(_7FwCT`(@Zop$h4mko_JrE#lRXdcrfuII%q
+a)u=$l=Q-ygjJo|p0z)_#&EW4aaQg9mg12cEasp1%=me>6dysK)+20-2Tb43O`gx~9@L{pDQn7;|?+?
+%EByuqQzT2`~Cp|8_9cHhH4%e>z+EpT=`@D#kNW_~my^-q${6PrgRpmpfAJtrhrP1N<$=vu}b3G9Li%
+ftJRL;3CZN9Ol4r1uQcDq8$54jGbdM?HqoIGHjpsbUz(byf*2Nx!<_gmVvf2CU%dJD<b+k*NWdbPtR~
+@WS+L+M9fpoZ`((qs_)483I8$lX^!VlZ}4uWsq(hJ5D$$wcQ$38G_fz73ywNEVHuj&Y~<GFJr{k$?8+
+uEW{&8BJe5OO*K*UiPd@4mxA*8Cb?-SUPG1avIeE_&C-XOK$kygbd{}uAdAoF{eRa8WyF=v=n!8#{e+
+_bv?Y;XBYc<~-n)ynojd`c4#n9ZB!Ml+@9hSbs8Fe#xk0?~GG&{-%K$G)pJiBe$&^(vdTF<l2zWTmRi
+%3uQCd<6)k@RhByo>SU+D>{##kCcTzYkauMkc%nE5eEJGGXPgh`H}SBkzqi*fht;nP=Re$y~nWQMtQm
+XS1bO+3M|xfHBIaH8DQ_Gs@02I)1H5LwbSl=9+Jcs82f)VU1dI%O_j&Mc899?!VPqK$;i8UX%WqkjeU
+1V9$cK5GTGF(O>=^(|^zOR~%oie(_hdZMPhx?8}^{Ef|lP(=;37F>_y@!+E)C!PM4sb40Lzs(s5)w#;
+i03|uLK9=vB<+=bNp=Y?S{ZMCNffA4Y4`}@7h{yUVYd@rbP%j7<W%<7<wZp|4SxJ>vhE|puA<DfsC4d
+V#>BB5)>GaZ%pT6#)oJGNAF)_tG33sGNlimDk6o}pywA23eO-kGiaQzvY32YX6zjuq1WU{9u~uK<k<f
+X438M17K$e&EFfl^c|0_i6E7cTg{}?;j|>0_Bfr$rT-Y=MJ`J(C*dZ^=P&OEH{AXL2I)6@}TfG*9=Iz
+jq*%U{4n@n+5j;2%uMWM`p>-0dYL`N3$<jYv|G`#>YDc#6xY!%4{%}Mv;(ti&enlTC(yRRyEG_DzKFK
+iXK07Di#bk@riyyncNC{K=UN)|!^e*^zKkaQ{;x`qKK+kZXM#RsZ}M)c#-f*SK3V(wi}x{S;NJYfx`~
+YSF6u*nitBQtE&7Mwl-i=&o2GebGtBlbHQMV<126XM+*bNb%e=0D>)@r1Ew`W2OPaMy(%9BI+I-+$E!
+Jc{eSFqgymr9c;{r|5Y>t8NT1q^pL`nZTO9}bgS^c3lmMv#YwATWwy0oFWw8gqRL3odX$F?MkD%p<IU
+kI;vQ2AgsrI5GGVqC0@sS)2>%<rhzJ5BeS_vSyB_KFs-(wV6Egw)0T>5S6vWF<+x3Hac6@6eUexl^;;
+eLKST^SyRa7?=ZIGMzq^whHD`t<o}`A5OqN$9nFtgLj=F>epCQZu!6*(O|Y6*{;l8zg&#8J0%hAqOE5
+BN88Np$Tl;9C#SG42p7t!+kvBjUtHTYaGCDcan{h5utO6k7=P1Y;Lv{JSIx=dKQeyY-h$Ra;8HE{==s
+(9rlnfa;2>ypvzFlupndWm$wnJ@01q8uJWM5i&(IvLY>V}MMt#PIpv=Q^q)Yu%L6`7-5q`H|-2G^G(C
+ysfIi+&RbIlWD(AHk3@Dq-K1@o0%Olg#^DNzqHmk?-?_px7ISl1NGu51hHT$vAf>6c3XM%qdrZ<D@;(
+0??Ir3^s)SUG=cE9otH{CS{h+v7#m>E$Xu_`_J&6KmHV8dyH7mEW1$o;lEoQ>8`@Tc;*U^5R4){n6~8
+2QKhr%*mLkWmWW{-!V90#zR`JY_SL*=JgAFS1;%XjBJ|S8Aue6k2C8QXi7fXaV}I93$A@m#vr5(n;zu
++G56N$U&gk7;yGo)jWGL?0W;740A_OmFZ$4$usS#fR=Uh*9|5a|JR4wT2dt)xRVJ+ZQJ=7~8TUc4V7C
+1p*AfM@te7w>jnAwj+)S7){}eDw2MogS`uKA*^k}H<deog10lV?ea%t;mz$;*tI%AoKh`B>b0Kch;v|
+$(T=U~2PF~6rZ<`heJ4=!g+tI6JgHP^@T^P}KN-gh$K841hh$dhT#16IIrgeLmdRQ_YyWG~~+nz`#+P
+fIz(y~`pBc^<z)SfY$pR@lm%w%aWk6(-z!jof7t-s#LCo#BMsU$+i@)mXAC`T=u}kGY)>lUI+<V{O2i
+aKGMw_mhu)ygvDp<h?iaEF*dEXZ&5|U!L>#Fh6uTaA0Sg<iEms@8iOG?^`aE_a1yCdA^3HV&}D=6wy!
+8-y`$dXPGe_N9DDD^r>)OdtsEfMYQ4n&By1pzYt#D47i4@n&jtB8o4!I$r6Q(@$iqoss7&nTUbW?iP7
+IL=|`vdu9rRoSmYY~pXc6thH?OtGvN0Irsiy^dZVYL`FuFu5%yNq4a14^nCrb$<j<Wi!g=DW{?55(xq
+rjFMK)2$w))WqbB?=hLvsrQp*H5wV4RCC`g@t*(T6)xm8V}2-{l+m)~95uGh6yTB#6SQco~<jzUle-_
+dEh#pkaPdEA1DQ4FdSg$;8b`gUm<I+~lV&)mJfA(f)~I^PZ_w>hf@Q4`DqroH&EQzwdF2ditJhrJRT|
+jPc<rQhs_F6Tlnttp1CoAcQuF?{CM#ci^RhnJ)8m&6fC(={9qzUo;$QqwNOgN0=@IJoa0L=6<ND9Mm#
+4tOMgnlyQ+q>TNi$>>eWDy^447QSXYSK3fEtBPZ~j@amb;?~QS}4w2?4SSs3j{ID6P%gEo#c-_(SnIr
+tneL=gF0pM7HUH8-9Xd&9-o(?4Hevg&0wse0J{TMSuJ$*JS{}#sUYyL*Pu6q7gz^nkjZ(;n65uDJ$um
+AI0##VIIDBa3@lxeoAIz<NV-XQbbX%(g%30(L7?2!x862_D>?<g6!#+RuV&&be=%j1>5$HFxt)r05j*
+0ki-;F<3{cy7{c6-|K0?ci7D$BBdU&xdwJ>Qf~>iHKvA6|t}W>*?|182vT$$>JEDGUCKj7Cwdc&;K>t
+{;!Po8IQ3lDt3_>?<Z4)W60n7TNTI1(V_=Cv-DznO>J>A{@d_>iZM^x(}J%#m>vr4`gHMmM(4*mX^r#
+koFJr5|6s(J*FLRc9z^Fqf*hE3mqqxuo)2~3N<Yq(*>{#<9?ZG82Yd2OYrGL($>Kh4)yUV&drsy;`?<
+22ba$g%C;3a@-)81Wwlw(-9l=Y{Is!M&;f27r{7J4f=BTHB^9%k^TNV1g%kY7DRr-a*wwF7D{`&9NN7
+|;If_*VQX5_hlTCJU1$?`oV18GBZ@5&H4jh4(>(ipA_<>2>^V85nGpBTSg%d9Oka$40`G99I<di_<D*
+QAagd_tMN*wv7FC-tiNYt%D!*!fzSe5SunyAf-6j+X9zkMyaUK1eo)D?Ul`U_UbArE<KDj)`|pfs92v
+$UyQx&wC|7_d7&qrCr)OHdRiVAaXhrENS!&<Gq<fJXXo)9w~$Dmd|-fsP6#mo!I+!QO|hplo9RB@c`L
+74>CG+s$HPzw-~a&icgyDZc}Gqef9HY_nfqD%B4(4{~5x9`eojix{^Roz>~YQNp-Yy=lm#}hR>R8xBs
+uwzO364@vi%?Qbv57bH4Jg%3qf;{k!gWE%_ULZa*i|_J=y;eK>VCmqy?!?fLqTs&8B?wp(Vj`%|Oc>f
+w-tC3(!qet&3w|0q<o#L76BJtbz2H|m86N5ZL3+6{D6GLP00p>mG}@yz_9n>59jodTS;JzLm%3-~d%{
+q(RQ_Xa~%86v|;JzP>q-GO`>`?jC#1U&Ra@!r#WM67t(C#^Og_Z8zhHYbQXnHQFP)~kSz)b+=!bBgmI
+t$y_{p|)(mt>r0|2gEM#v~uQl0KclG&-rdSKO1n%BL6>D+2Y7aqhC&`Hc{%8OB*sJUYBZd5=Nz(t)94
+0swLGkcLMbm)Fm)K5%a;+81%eU%aFSHQY}Z0rBu5}{{OWxrhmnlJiu$ap{wjN?pX>9Uzt7gF&E(Kp0z
+4J-kxVwe!M*v6<>3Y#UlM-e`>V%Wn+#>(%<GWi6e|PW0QWcDyLt$v7Y%xU-Z$mPsBcaNGqVv(PmLB&p
+P@rGFEc8wrXB^qR8p6*lLLvqzwbF0H@;>U2x^;@@_%aSvE=5$<Xw<k_IhY<nOoUyWLurqgE8plertxg
+uhC|d77pBYdLo<VRjArtx4h8J#jYS?uNWxo5HbF&t=>wyOuMXF{3sMkF00c5@nsu;Oo@y_}QG(W--P1
+9VfrXidP;B=fqAGmzsDNz9$Rw^EDAPmGpE(rwf`&8fvpQRnF*>epI!~z`s|-6`TC#M*m;b{W4>elJ_Y
+13)cv6OSZ_hz49+=|7R&ZQe|kGXizjL-F-LCZJA#KbV%60dJp}Q&0N;kr>MA@0_Rb9kEgqT@)xzo_2K
+Z|3*QIF@;}&Z-n%hQt320(IM;h++_`x0UvX~oY8Qhy7{LEirC6uwdKYEDMRuL{E3-V)MOUp|1UbJGe^
+xk1o~RjT)|o%6`F%v6#3yBpNST|5wCl~NvTyUZ!B>4C`PZh(fiLL(5M+pb_|9*Ao31SgR4^ad3b$PoX
+@Ld0zyE8LZ6Fg)(<IM$jb?L8Ua`z!_+?CzJmk5$YYP71yt;sQULod6!dmsu)BQ=H0r~MfOOooCxACMV
+=9=~AHi$H~agBAdn|+*i3BS}$%6NRLU9&x&0WCP+O<W<K5MNAOi9FwDp#2)~vOMSWhgA;f^_YJ*=6%|
+wD_(e;#TdWR#Z+6z^1#H;`%o`dzvh|G`q8{a0e#o|!tEUXAXM}K+M&L1E8`{GlwKsTyr(2n%bm@$gy&
+uO-Nmy>KThG9cMyGy$Mb|5#{=~7G{&*pB4%?eL(4@;<euSo#-S_5Sk|LXg@jYx&_ek=X-nxFqGXO{o6
+EK@3K=>9@Im}t`J#-y<Gv034=iV{bDg;tN+e#c(<ELhT~@lg55G<P{PnPmQQ&7=cgZ*+HupO`Z&&M^9
+>kctEJmC>j3M8Mlh?nXr=$Yo>BP61H^z?ja(rt!1-O<iS>&b;8MMF&y!2>}Ma`!~iOXuQCGWFB%b82q
+u$^eUm;rdy^eI1W58$y6e2rc5FgX9gUu=q(`1q2|ST7SF<U0e$_ueDYh}$Nf5=Tw^Bt0N*%JLDo^X}_
+vy)HN=;0wn@7$;!=;!MvTuMXFBN~RerWZ$^HAORT*)B^fq1>YRUn9ed57~@H%51aXnN5^US+S5EMRSb
+cB#K94N#}%ulXsKzY+;t)OV7xrWZ2z`o(9?<H1byszuJs%IR~P;ltZB|=?w}frXo$>L9Gjk+yf}Dl87
+p1Ld|J$xGuI}%KeT4~9*h^=4OpXg#uq^QJUcy*b9j#+&*}vAoA(Yf=ZXWerzYyBTHD*16GzI^81q%h#
+=Qv65zvNic^+$%>$=DrB#09WvE~l&<u<XUau?($TfrjtK)R&04S|HFO2-XZbJkxWR>?fAc-QO@-pvl)
+$)~rn{0-+qyFSFaG+VL`oMh~*;j&G3!~O?6dINLD@csR-kII3yQR;}sS$p~d-bKGD`p102d2hG;aAe*
+*uRlss^VY$~_A<{j){Q=*n-kR7`M=-DQAd8-l#9Wq>{=>#Z`*X}3ferNFUI2MJ$`BRB$<C#!|x&f{&M
+D>q;+n_VaQSbtEHcvcqh*|!ZV+~rNgfJe!zGU%Uq;lwv^^O@1&d*7~X^PM5|+Nv08q=q^a_4tHYO{f%
+61>QcKO0;=KD3mOKzI4&DyA)}v|Ey_GN@3CBoYjsGtj1KaWKzm5EDZtB){$eg)=-z(tjpX|uJlrbd|#
+Ae1DG~YiW?*v6v4d8VHZKAavDSy%5j5$AyoV`V!50(~#r%uZ>Y?*kU$2j|hg=}lDVT1Ancy4^Bt%F^b
+iIcK~S%!R~Sw=VPBVzkWj`jPXEX#QN$6pJ_!P)$zlH0H5T56&j@T#X=P~Ov#%b3=sJq3dpf7KDxSrVu
+CUdC@a6w$`IC)M5g9DK{do@h$YgLk8iyAou6LK#Pmejy@G*+kn=rZY<v&yN#}*&k(`J(OE5L-W>vMji
+*xbPP1@$3|@Ka=^6<dx@~6Ze^|}&--H68-N+(1z?={cqd`>dzG)aIYH$MZUHY$UcMG%xlkUPWeF-i%$
+FYu+gyx^(+PMozJauTy+jmV#+<zPpA;_^4`MFPL{a39)BQ{1m5$67$J}t#IoN#kU5{+<ZA}#M`y%GM6
+rX?DZht;Ef16`6_o^)pyjh!+IsA+T99=h=dx7*LUd63_7jtS}tsk~CpVO+E-4$z`zAp*dTz>v#kNuDB
+*dL3XkEU$F8GSf;O>!&i(YDSrTz%NNRTM~{7R<SVvIXe0>Nj~zzm4GSnzKaJ_cUikhn8G7U`=ul$~Y<
+dCiY#9|5u=YK2N~^quPWz^4pA$vlQidr|y%yHsyO!#k<Mm3{e;W?3lOdidD6{12*+sglCS4@mrox?fI
+%Lb5VuVOJl56sjay-ywB1yDyR?Yy7WlyzPy)nuK>@wYwF9nA@E%?_H~kKYX;i#Oh1yFsb#uJcYls?Oi
+vz~_Z;BykVteM6-jlS%#CrMf?*uS&M`9A!Lu0K!Z-!jeHhz-RRq~)GTQt{qVT^g{iOAvZ~Bq;M=^$@;
+P3MDUT(i$v-zyd<7kY*X^bIROP038@1f2DV~yUmKi59csQ-H3GuACfHOHVG<D#A=u&(;o`!rjteY$na
+yZ9bxWQ=^<AmcMUe7}D9S14DzI%Uf{{I<sKqiq%ET_fzRrCRdfA3+xvY0d)$*dr-8FNrhEF@Ko_FgNh
+Ujd_*NL>u7aoWO^G7Vk`wcy#;j_oQt@a$UKWTv0c@wcWPr^4%dVv2GgeJInrQkY^+BoZkWr(C(p5)b*
+iV)@N*DJKC7B%ClSAX`o(y*^E|)HlfvlcCJTXykp`R-v+JShkEI2(p!HHc>e)^x1J2m<vwdg-2to9O+
+OP0?aPdDyH*wK=J!QL42lKP_CojvvA2n5HO5|G>;}GPJPGdaXq@I*IQAXwe#XCtIr9+xRW3g$?|l-*@
+M(D$WA&YW)!N0_;OD@rJmD0Z1Cyzf!nu<w(p;<6onC02$^pl6hf(GXexFR#gIzeE{*oYq#A`zqtz_=Z
+{KuPfdw0kjd;T>jUvqZlVaBa%{G<K>buWP#y1!HO%mqz*%<{PK9tFLl-nf)`P{8+k{;2Yx$h}1SuBbd
+H&4zEK=X^L1ibr$Jel<bqv#6t?9!SOzOEzpkQ$>BBMa2-a<WY{}UD#w_>C2#<Yef<DfuQv=ZkR>WyhB
+EwNJ}5!Y(DQ5BlTvXp57$$!B>7@MZL57M%o`RzlqRp`>A7i<>7wtT-50-Ezm#cw~CS^OYb4V-u9xtvE
+TYYJLH^J&ha|>G-%DaiwZ<qm1c8p1k5J({Oct)@mSjJ=c^9~aZUwy+6%r4INL3&F3H!xgEYAAJY{Xk?
+Eq~#m8klmj%Nni8HAkNacE-w@=U;b&LzCx^;2JKvuv##YEAS9HYNHmcZx#V2)&K(@66G>T{qY6ZpI&Z
+-!e0{4PaPCUf}tOi(BxQygGi#WxxxrcY>B!fj$rA=l!8Q9=O|&Hav_ecC%+UZF=5@%>EDSbhjOJusm~
+NMT=&yaDWyrWy}m~%U8QJr?d1$tv+duNVO#Z$3V|`elTy*TzotFN39<FvFcZ7^MwSlxC3;#2|P<P_O)
+H+0CU!@Wqc3x`=y(e9UtvcN{#mcytmz~Xd-o8HZ9JvUyFA*rvD)~KkvVC7lG~$qD<}0m+$6T!}f`rgB
+7};HmbqvbwBI9gT2YQmEN4cTg4<xu47z1em@O3^K6&*dU*a3{-2p_@ejEy{@2M{{}FKe<Nv`e7TlgdS
+rcwMX)F6@>|5YnV8!&&`1&=wKd{{Hf5EQs^&NbF7wzr`u67#u+GiV$uPuNb_mvIsBRr#FXb0>{QFh?6
+j@%m!n6+RI=6Dzrct2oQN?wKXGjoeYz-^HMACAX_Ct>0-;K})yH#DcKcLlrYpTf3GIK6GaiE!BW9q^;
+z30B@8zhv$G_bY$9ofEt}e-61fO{B?qOL_Zpn?YL!@cs<WyoEOx?k1jDR^NX(FlhB}PZZs~D{S7S|D1
+RNvT{`)${pAdYMaYD70kIg^~bryC*oK6g<ul@|1(The=?YK0wz!6_u3K_2lGDwi{r0^+H!FwKG;oLqW
+Rck^Zn&Fh@1!WhURtN-?=3hXY<XC)+PQ)qL6V+_hGM<ZUJAq=Eu3rB}@OPg1w*f&avBCO&G6q=p}ch=
+p}1U-+#E-lIbKYZ}_>45#6BttR{I0^X>Sq+3l^mJ)`w5z_ovHfuFEyW^AqZr2kM+w!GW7_#dMDgKte4
+qUxLA6YcU0<G!}}-oYAm-dwlawmNBxqpYCSck_(hjKSBaW!Ejl`16RnY2b4(KNt2m@AC&xXCd|w-({m
+L*Zl$X!TFngvJb3PMkqnlcVbLutadlcr8nw_rvgVT7RX4z4dMvpBI3t_9n`^!3=_uLnD_cu!m(;U69M
+Nr!BAl%+U`vjRj($8=M<h#`ndCXfig9Ihn|l22Y_3A9z_3~*Ya8G+vRUO6VA67zyE1gTQ2$gH_}>ii8
+rKAKT8ya-?-`Db|*jvISSrsFYvtoWR`ay<-MD)*d0LovoIg>itkuc7`LeM)_7642XK^kDXc^KhB~gBX
+YLM&6ene^e$>0}rrUP+;r)!8?%4fSoJb9c_`2rR4{foRUD?|FxrE7X@PKygiGj%?Sa8$K-S5rQ{p1e=
+PhaELhC@|XT2w#1NvfZ15&d+^a`FBF{4T%wj@@i?A>Lm}z7_S^&XwmwMY2BVAMGZOYH@YjhC)@`>*hW
+mvxaEz(Du=5_|VTnZIdF_@cEtLH6$JBr+ueWXZ+IlORTnv;G3bMQ;CoZv2W~mU9!ZT{8i_}366>bR+;
+;9gN<>@v2PsM+l~ZLNEwlP|5ZyQUOPS!UKeO#yxwjdjn_OM0+{EKsS)jhPJB^oI@B!NO_uGhA89u$+-
+@G)1^tlw#ieMGY!~ljyPzjR!`?vqke##7S~Dxk8#}k;pnf*y{mlq^5o#yBX!}(3V&Ts&OfPD-$EFu1U
+H!R1FBr4t#%Owhxx|KRc>XnM5%U+L=bweLq^GUC$Gx6+O{!1sDU2Zle779aY0wLnn`6+6W14|$Xv?G*
+^P+IgiFx1uav0aH1g@RFZDGNZ2wHI@l2(k&C7M=*=klVY6<HCqB1_Q<)K#<szwsQV6<MGaKa{lM_n;M
+72CewrC|Z$K*O#F7;}P;9pcSXl{_H4P@$FHxBI{GpihcJz0$MSnb>HPlpcPkwR!kT}D^44<;(CKtFn%
+QaiA5_0@w*1Jg7Pk5Rf}(wJx?3-VuC?0rr5&tVh!j8*YMf<BWQ)WerWH%wvArDEujA?5$m_-*H}N`4D
+p1#6L`oGT5-l=tH^#URAd{W6E`_45*-z-$3kQ1#Cofu6I=U2RX^+tjiwWy0G}6XVSJvd#m48;=R?^X>
+xcNS@LAa|g|Huw0XO(=4d%)D?+{{h-*TI`cbew??72|ehoE<^d{Ms*cwdl!ae@BSKsKYz`-(*2eIai2
+`SvByAT{Qcs4*vnX^?gNGuxzX6Qjq7cXEs<dk@CQInd^b`P}J)B5f0TM5+g4<G2DYJvcyH*LdOY7DMw
+W8&Zd`VPi+G!{TrTrpX*j2TRM`gVZ+^%xZ2g)Fw;2=OX;y3S4;?FoTSr^CjD8I{TtS+!UM6riABc8K2
+IWboN5)P!_Qce?A*(<5-flrpiI9aR0!PUU3wA_^s@Y+_x}a&*~?(gdi^@q3`vptxL**bN1xxoOSW`ir
+T#*mATnl@t!;;^~-OGj$HDXo<%c@>BF)Id}SZ@TBjxb0NZm-7bgm^j`@3=+taml36s7vA?BSdq28GE<
+78q-ZeX3RatJIJ-o``~&p5R1a_?i?FKo{j%eJ837itsFw||CunHOJp;f2_7Tcka#%%x)5$jQ8on%H&O
+;jpgywZ~06wb43r#ye|DTXGgSUS;OPdvPmZ3p#4X_}_-HKgf87Mtkwn&MJLyE#Q-KSn0>v$DYTPKK!k
+SdlQFEY)-VrvIqR_h);X3%mI|{Yx@J_m66<Kxpz(h&GlTNGj~vBhUTn*jO&#-Ag3}Ow5WGuoodtmKlZ
+)^Agb#7|Goia02c&QM1^rn#0}Rl6$fzvMMS`*vSffkMqt31LBX`pHq<grOS4S0<%_ggX=#gLwqPzPTA
+7++QsGi*Sz)F8&$;*9H#1MLzTe;P`~Uuz-^1~|&t1+v_uS>(ckg-kvK<qljpNyAc;<Y$*b_Pe&q{eu7
+nD;MTR9Zx$h%-$&_mx1{Yt#^+r$-(*|y{QCGG!y(NFPNnSI(gwDf8})ed;_VPPk6`p*WJbI#n)gfo!M
+4F66hmaSZTna7!f=X`2y1sk_F1if@+#i*Cbf29{6jb41N*GsxqFI|nrpqJu*Q7;D@(~I9fp_fslm*JQ
+BIdo0y#bv!!A4KQFweZ06;rO@ZT>c=ZZg8DQ-_5ug=lP8A9A?47Z__K{`&k%QyjmjGvsdVMHRJ2qD7!
+p|kngk1_xQnYXg$Q9$r)megzuS*a}r%+_*p?Hv-8`}_ucjn((c<J&(=Hnp=()&aoffb)lQq@ru2sP?B
+h`PE@u?t`cU6$=kvF*xR+ec1B8sC-G9Xk4GnAXtUwIU&wz#JG@dDhb%@6=4hwKi+sQX<K%?%(9RsxI5
+NgjpJWcyl#C=WY&f=ahfVU{nrvohsWr0_&2|wKDrLny1RL@y-y6pfrh#PR@{kEL?zq=9re|6}u^^a#@
+Hm3grhyHo}Pxue&zwWfV{*$Esqgl$Se^vj{jp@Jf^G$I-YV4za6KBZbdUM6E9-i?0@``u~WL(70H*Hf
+9TPF5V$9=BQU7UN`wqit?I5TJ~=pOA!-OoJ@jHrb$XQ02sJ%&$v1V^B~%bCv`*5EU7nJzFVdtq3h59l
+|d1&jf3zFt`x($tx#f3+U+dKrFa%ntn?%k9G>Vm$C0C^iRe_WtnDMc_FuS3JD<dGEh@ct`Aa$wyr?zJ
+EppKZm{<>%XiW+GMgh7-l06)4l@Utycd+VbE4Cr!7mJ2jy0Z``xxM?nr^Y=&@#O@IAUVImR~JZez|qF
+P4h$PQ5*-kE4CxW4a34Wd5yY5I@^|&P3=3<6wM_>m1ME8q+Z2(DB1?y_gM};AI@@2Xv3lI5bYd{lfJ*
+5uGQ@_X&V-eT-3hD0|!+;1QJVZ}RHt;m&JwD<?1P%NGDI=RRg=L)ezim~0pEQ(eQFdeFu6mTZvzo_ki
+g?q9a#i6@f(Y7eu_GVx8@Whg5L?op}}-!!#6A#5y<&>m)JOSqc$FhhHjR3F^K8qd=Ws!(NOLZ<y7lM%
++jPMO<8;Qp#o<`3({_qjvhU9#$KcbWf6-YAmy=UDeW*S<b}<2~12*NHv1#U5)U56Qa`<SB!4FnSoTxV
+IbEJ=t(yo(>UhKNsT#<cs5sfr|THYa3~=wR1<rKHV4w&)qB4?8jCDVNM?rHh1_wVr0(!U}i#p0PSbx*
+$w~vcXQIl>k79A6Lwhj(B^)_^+;%ozd*aY4DIe`Xm`h9T>2e9(>aKr=?r~Dgg65*ID((!2+w!i2kA!k
+UyXgUrrnooHl2z7Gv61bq#ED%@qBYUAKh^T_jDBd^sYa`ZMU!R{$HWJt&|YAz8%lLMLQVb*Vg?ET{;s
+T`!9YzF7V=gz7F-`zK`LJ`mcL8VE@$$_aEf@I$Z(X{SNO9yFjMkgU;^;_Por)t-R+i%4zPkhOM{4Z={
+}G!Zq%2PbgogV}F2tgDq{J{H3dY<u5<7&A1+aGxkj$A$xs%K3~W8m+s6i#lib@m`BL@v+Y^xVO<EkV+
+EhT>=A-{vZsnYlf*ZhaxZm*$H>pozS;5q>UD>8fjm5(18^SN=sAzziVc9#p8p|T@Lsfmf%nlvODyN2N
+-Ysl@ogCHTd*zIqwQWyv-D4lXS}in?cA@%91dLA_DPwh17vZg8=|I*->hGNv~b_}nI1trt=UT8Ua?0)
+<xsTGg8px)<x*Hw0)BtwmWSZ$cuBcudI-4_JerpKdR{?|^7=bE_!;E*g@+A1kM@5;mqGm7+#BhAKj<2
+5jHK?v|3-LtnO*T4w83q<wtL|{<UF2}ke#88(?*T+B7QRka(U=vp4wF49$T2FTwR+c^MreNtqxeV4(r
+(`Fh=>q5BE!JcYYJZ`wh}=fVATkdPbVG>9^zQS6*uvgl8jhnR%QLekSSl@`~^^5FXR<@d(^|ewuM}oi
+1cAzK86EI5R!k@oy{VL3_Y`G46ur@mmkDdTbBp`M4qYJj$wreEtqP8wxU`8^$SeiSxQk9OQ{-UDreUy
+>U+@h>yD1)`cB9KaFjM@Q40@cgkL0H@x{4j2Vices^t<`vi+V3*P&;!8^^i7_oO#GUgZUB6q<r1KiQZ
+5p6ZQDB?cgQ)j=h`z7a`0=9pUsp2g3$LF9QfoIv?d+=QlZ7nS4qq3n~%5e;UWd-HK_sWv)Ot@Ph&GBf
+v1ODS7?R&88{L!!t`E2Ch+bGMzpe-@qlH@aJXAbiGaKJhK-T?9#;r@in{KNRC#U86TUya{+`YbfA8o7
+vF8U=j~&N+>QIuo`??4{C^8HZZ%JTVB@2kjuP#vTs$VF4CPZd66*s*pIvC!%LZV^p@KcT`X4i+w13FF
+rTPR$|zm5N9@o4Tm^*o)g-E`am2E&uwn*1>R3P&l4(rR_ya9=6!JAO?+=r_wV9+x}n|S)&owxn_m)VN
+Q6T8l!k__d@cs$KaJmBz;iHcOT(HAfyOJPKE@q5&WGpDAuQJ%pjbaP=={#3-B-4P`&%^U=fT87^~u)x
+?e$TNkIvTl>@`BT8`?vw=Os1$d^x{foQovK$79^a$NXE72yQ<_<Kyqu@iDZ2Pdr~XFelKHwGJ#>72-P
+Xjk6nfL@0RXBhE#Mu@}z2#k5`$BF1QFU(+rE_x;B)V-cNWb1%*n{0n2p&(=3ScD(1y8;>22_-V(EZPc
++?G{{!z>;C@YzK1W4!`ernozSu)Vk|brhYcF4OByl+=zF@hIs5c1b#x<RIc@yAD1M<g8;s{AmH(4t(Z
+|*|J{BGM<&DRphdtO<ciGx##+gFClp|tXD))8}<JLg+409Mm50<(K_?Eusz;oXl+52~Fb;Ft)jYXrY#
+aNV&Jt05i*WY+dgZf3C;=X9E>ESvIrWXPHzR`YH>oPvY`mc^r?`?XFI^Y!;f8J}{p&h5zd9WRBW7TKa
+%B~IK{ND0L&gT{HvQ3XyWxrTaE8g|7-H5q2?Y^JeRQqW>e;IB48t(Dg%+DfDVORKfzR&1};(5ea*BkC
+>#^)m&hOsLRXOyAWUKZbGUw7te6Mc$2bM@<LF%DPHT-AnSE@!U#HFh?!j?dLSfM;*udEfYL8@yv2LwU
+j)k*8~nkf%fA^6W%;AdD)HHk_+G9U75`??ctLBK;KK-+Hi~@0aGY^7KICm6{38eII@~6EpNOxZ#`tz9
+&hHwt?b%qo9gM4xw)7jADqp?2z2MZEyMYcATP|@f&_TCt5x`K7WBfJ08V%3;gCB=W<z#F;{%>+};=uI
+UmZ;s=n@ffkyTlT@CzE-@}hKtigRFS8*Ivk$H%J108hFV)kmB2S1<rqQ0}o%DIqUWy>)<-_R#k$TbE&
+@2X?lFkBl57hct{2Ipas_vv$DzdnqIamugZ-ryo0j=}I7d+d+S?{nXSR%^>H^djbxac&(tDm=qx(AO#
+ATtKYTTfhzX)2r!fEXIBe=l$HzvAlj>>$2ECs2b}6_DvJ^i@h<ipOJIpW5Er-^IN53dn<k5JqN}#CAi
+m?j$NAA49_UTHJ`=R=MIWz3hMPu$`3y06}BQ7`9*)+u;!j-#!Ei%eu#4mT{f-?p)qsBD?iY8)KIU3!Q
+cMAVK2I48hN-UEyTmHx@T5}JWFA5|JPOf=)2N3;v2mu_K9!#P>+xA!@UD>Z=s-yA3-+UZwtR)?D(<RI
+~C={I*PVkhZ`E+5N%M%<FlW>C)MHHW1EOwoB8_jMZMyoen)1w)-ZUXOL{(Zezfa1iaGnl{)KjuMWoS=
+r*UzgYy(Zr--$A+dQyx<viWy!Jy+ht*rnP2rR%snK7Ce>1l$)e(r_q?adh9xf5W<2P!<MgGq>ZrVGCn
+1^vQ$w!r1A67w$V9b@L>6)|^+^j(e~#_1>^<GR_nGbO;DjJh<&M+UDYTH@ij0fUrfvEmztfx9$`Ww##
+GAX>WK(1GhRR#x*c5n-C7;NVK=?rTF=N@6kL0?U)l<8;7>&#8M{Ue&|<d&l(>#r|gNC`MbT)9-w*7Vo
+tr!pEW$Z?qfySi)*SM!8_@9o}dTM5RgkZ2fsD03St3%?foJen9q3+7(b%zJic#~D?KMnfczx*uwvvN-
++~oa;<t_rp7DzKcFBVEDQ5JXE<pAEAh!pW-J;}hR)**H_AK>bhtA@dxHx+|o)LKl_`2$8rh<D_KfI2A
+s|5Fd?sflG37=ybPddlR+WpUKJd}u-qUHhcPT+f1$AWQ=8|yvpr7h2v8;Wfi#w6eDb@qRcSBQ5OZ_!t
+6jifNx*85<8z-XUhnnS7i^WvY4?Y|CVJ`qm=+KkKW7Ek+~AnwP}nuj&+fcMVT{P_v*X6N8pZiMFo?)R
+0g6VD~I8#&ufoX>*a_@f(s^CZt`aa(87q=P(>_mKwPe-5sLXCz|5pIr%W%?9A!3`fx)#>M9pk!R;#)9
+(CRvaF|luKieD)idEye3!*<oKNi+HuyCjEh|>*SkMnG>fh*&-$+3l#&tAZLql~OK36ujUa8cwem8-e$
+)hBB7=%4_#rPBEZw!RL58Puh{I!N^+?(Qus|{~f`LXHv?Z+OVm|hh;JN*5vp{@PXLLGi=M#rdv&;p?A
+;kOfhkM^1qTIvBZE=+rLRR>$>FlE-$D~H_`S{z{yo$tFK^sq0R5#?7L+GbK}*jBiIBYApQ8^B+TnjTh
+vt}rYF;wSqp3@x5;N7${i?hH$VAD)w;*VR;?g7GohkLc&uRQvm|86a0hYvBKgcS&;pTM9z^>aw2Jkqu
+DQe(T`@dN#vP2^rAZKR2{$Ti)S?&De}wMelbv&{ax$=$?B@s_Q^!;e8Tb_Xj?Et~d_&Qd&*0Tx~TOzh
+jDmFfA12P#o{0l$C|Pw$Om$yg%dU?82a13PY2;fY;Q?VN-z4f!`A$_D~1V4ii$tZiamQI%-N-8;Emw?
+6k07J=qM0@4V18S+|D$7Eu@)GIMI!bj)kU9bw6s*9muq@jb6`{{pzCUTj^7baB0oU2M3cYEa4Wk>93H
+fot2y!H>-ezj<?cH2N3qJw9^7<V)UN<I_hT`RJ`Do_J!(NWS?2JLn;3$;gv;KET~$#(g<#6oi{LMeqU
+7no)hf9XY&s@Q*`(w?;G1V1BlMe)O=<d}~%Ew^Dq^*DY+B;;pm|sPpo*;kSWdN)q4uB1}mWdvGfSb9~
+ZDl79$X62j;34dVN}mPS#J(SEBz3AXt_J3pti3pnesBm`}g^=K=Cd_77-un&3w!bK?hhzm*^aC?A%2Z
+7&$#e>`TN)Wg$3&FirG0a)C?O5mw{jN`hkJ2GvHqZ%*cSM@fG6Llf2l;>S&_|q7!fZZ}&L>K!nl658v
+RCP(raOt!-LG^6w?}vy<0*}*g*vx1_9-mD*t&UyY>%FvZ3Fb4!K4>Y(u<z-(tM6ja9Q;?flGM5>ZLE^
+-@<zNm+`YT;T@{F1q%yk$wC8Ku}%TrtYbhk)*%3OkKbN}d$Q@h6#Y^?3rd*{b$tT^of*oY&X%qNom8N
+leryroW$Vz^#;>HL8uC$rxB;=Tq&i+=i0fx?`unjJ)u$NR7zo@GXoTWb;a9V&I!^KXL_fO2XPC!^w2{
+2O^#(axft)Qt&K4kN80%m|9s7B(>3YR)sW0o8;^SXZJ%RIEvJPcKnL&qKwm4S8<py0=plnM4TX@)|LN
+>)I8_Lv^(obt>Xu$O0*;RqxUE(;h3dVzBOgWFX1^6weKKpD`X+y(c?Q_Y_*ow4kqpyVN*{gC-aJH-UN
+*~-Wfxfku@A;YVLp!H*K0Ykx<KMJvo>%xc*>rA!Yd?%Oa_lPbZq8mU=W}7sZ~F0E*z3lpF6SDEusS|w
+p9g$uKt_y5``=WEIfu3tV$U>j4k?biR(bOG6}RvHabNshxCi{TreqoU`9GU)DIdyF13D1z2G`4@j`JE
+h?^VCRGsPF$Q=HOiKp1Oho1m12WGkU?-_|x8&n;8J;JyvHGq?{T_ZD#9n!D>gefhpqjrBM9%*yc!=6l
+8DD8YRHiX5dK#MRqiOf(=3;`8rYLC(5B+>cg28=tHA{n%2aV+zW(0s00h*9Ik2m1~32NtJ7Z($R*z5?
+Is_###)J`NO);pp63WNA*m<G#u*dH!ky>dT$ooo9SVk$Rb?((i)Fe5j)^nf7YXSM1;b8%a!K7i3;{pE
+XM%j#46C4Zyw6mZony3j<#?w<!dwGlqz=++%s}-4fid$dzDu(>FxUdNa)R%^yW)?^BI6TJLRRfodsPX
+zdFUo*9dayp+A89@%~_$%em`e9(s?)?BDQx>-7K@fbU?RvEU(FnQ;hyqyH?7YwYto2H^MRpD}-Mj~ik
+H_oul#_9^Jjz&&Y53AnH2?qLDm++7du(}xr?!w?4j#7gcL8n6v8?kmJ}CDjjcw+;a~pDE{0Ty2-G-u1
+Toyl7W;rLG6NiZVa9R_sq+tY_0}{MglSV_IlEomYx;JPdR|d&NhHd7@?!>5yK5Zr0Pd2ckG9tZl?aZ+
+7(^&`}MH^WO7iT-P{<#Ltfy27Ftyfpz!7__r%tSqo!8arQFq;fb~Y%F3QFhE0A?%md*W=t1ziwA+}6G
+F*H{mxueCUhcql)I(o#DU4l>!EtK_Tbc46KeKr-?kRT@x`i39qTUd9L5%yN0*}FX?`^z_`yUrTp6hxT
+uU_ej^HQ$!Y+`Q*wxN=jubxeO4ZnSq^}ZSJCtS{>;_uz`4iEJJ=ODuHyK&Gxo|*QWhi3)OtKpn7?hAP
+q+%Jc+;E^rZj`yMbaL#Bo;5aYb>xm7B_d<6)cfZ_8x`&ZF<L;@ddnmd4bN8(srF$oG59aPcs(VN74&(
+YO-{ZQ_)wsjucn)J=&j@%HjXwwDh2GHqN}-*W`-pHq@Nn^mt1w(E*KnP9xGEo4e&Yo{Ki6=fjqsZw_<
+6gA3u}a5g5c-TGXnaefye{TsVyTtz`L)=6X>#xbSB(7k(<AZTPV2&ySRmso5976aW|B~7sh*dF3C*jf
+AM?Unb7~@o@q0o|HVB`c^rlBZ!iGY9V6(yWjubD0)FA(7w5$WhQm81zFVu|3qu3ooomMhKRmA*aGPMR
+gI;|)h`n~ekB99{@^ogPQ{$Cvz*F%%mAnoCmd+x~MV;~8q}J?R?r##|EhdVO7{bOAeigz_p3L6GJ_z6
+G!&`(6%<e4eB=ET!>BFw7@i1MJNEgE*Zyw$x!UM0X{d=;jw+TCMcqY?cr?Fx$b}?5T#O-@HPapg~+As
+w5>T_k@qwu~?Zo%X>*Tv1B+zMUX^yKDH-AbVz2sgWM6J=q;z4P$f6uw`b599mFL3`upqVVuuvtRQSI;
+ch*?lt>$d>6$rYCPY^2Itlx+%MUj@8dAuN}6nZcZ-g_i?&abdm694s)N20_hi$|@jyRb`3U^rUA}T9{
+FcLS1^m?WN<78hgnGR=zorhqW%yXE86xkKa34<VhpzLT@_CE<$w$!GkoQmYY;6hk=B!8Oh(1cor9BrI
+59{%#_$++^#*#kJe_IrvPkbOAz9Y-`1K)+lRTC6e(aVLOOh@HE+_(d6>U}H2m&Nxq7ALeoJ6+#pc%Bf
+v3k>o#u$A%9w~RFQJdZZpybN%kaKLByvsQdpz{=Rl@f+F7XT(`j)lHp4I;f#xONoxH#QmJpXq^n7jiu
+mb(&_i2-|+_C-}CihEHiyK<BqfUWJ6tJ0Z#i@cl$p*GZt@-UnbUG__`A0tD;oo3uMOcK5<PquD`Ju=N
+-cO=;z3NU0nC0&F%>G0>bx#HXL4+Q$HJY2;=p=5sI?R*qI$Vwz^@BJiiL#!Mk5|XKx(0Rt_y~4f<-%0
+{kv4cyzWd_~rtoa)iElr<CTb<k8aZRqI->Gb9f1H6+GI>l5K!;2h3r#J8?IhGUhu=-@;jxbLYbt>bl3
+H-|$RrL~A#2IJ?T<`)+}x<WBtjq~Z0(gJvu3tlbz`x;vIBwjfFiG%p~URBZ}ewhX0<;Jj;E4+3M$8;l
+a*<#g0Sa^@v3h@%d@gC0?ggCwnJyQ6&NF+lqkYP5smBvIYV=?T|RPY<rTuJnXd|hOfBYYr_P){F4zJb
+dJS&^R&e!U_7B;=t4-;DW2*~WvcaX|YhzDxb!hjWABo!MlcIh|6*ci*#alG18vg3^4cAAeUYseYgp{|
+<Xw4*U|}_o<F;EkzkYCM^33xX;1;t$<>Cs>3{k-%Kd?3>aVLLRvW>!+2fP5Z7>}6t0T-O!%RB+_H<!c
+MV6`10WA`K=x$#^@6zlAnrt<2|!Qc9?K|~!nTHY{$w3~s}cdSP5@p@yi1aMDt;4ijx<hDCWm*fB7Z-%
+TwT-M1L<O!)<D{Po}bz&)*A)tPo4jNf8DYDi*+aSzp?I27WVtx79kPteJGDuf6jUY-#ifNmCP&F6)X=
+di`L5rTCv_>dMIaK;NL>=J=YuR5azu?lXqyJt#k2gMbdkfOTFmzXG3Zqv`>Y$oYtar8SZ7@0`&4K=p`
+KV5)bJ{f=>KFCz#L3=1R-v(6{zq9@!W5g!%OajAwc5zS5Aone>JIYgvn>%WxlZ%tsFBtblap5Ap|uzM
+420bcgZdKzEog%oFHit4||khvjC0a_a?po2^t1ow=xUPMWe|9oCbX26hSUquxio2N|Qnl+Jt)1Kd-4a
+YMs4J<yqqU2+InTKY5NRnVa-Kc+EKQTVe7_2ApQbeRv+Et`qoE%fJW4ngA$z$1oT@`FA<!;_^BfjrGr
+luI6<yMi&smn^&3N}EsRhzlNm6?u?X>ms(Y&GI4ENGLy$dF9P;KVDG|r2-9x-;U5X6IX<8PwXGIC2;`
+g0rMX2!L}h!{FVpP>I!*6osEY)w?<yFu6aQ?@bA(9;X1QRyPH8crSUwKc{$5=Fy?>Q7Hc-91?_e#@GB
+*qZvp+|IPQW+i;9bIk86@EWP0F#0ovpWaQEP0d@B6?42gP8dFkEDYgGxPiRCZbg=^SwO;`(rH9$U5hV
+k$$$?42i;#s5FZJgza_DD-{k2Rn(6?Un{qja6~`6Sl$!<jh4E9Y&o7p#01nHW1F!@={AKgWQ7@JQTu+
+GWih!$F&^bj~Fy6=m(%l~?a&D-G8+RF%gXhgNy9L5RbzovOk!4PS-#u%6(DGy>etdciw~BGw9UZ3o?X
+*!J+OZ7t?(q}ygs7Od|q!s3`s4eR2L^-{W9Je=<My~KnK4Qr&I-e1Vs6Yd9k8Lx~6zrY}NCHH-yi&s<
+F%8}PLlp-};J5}mBuZ8)>Fd6o|8iUuW_MPF^1%9dyU>rOCnWlAG1JC`NK55#&ycItOa2xU|+AqT4{oo
+t$EcfGOd8PMXhuQJt#-_uhDJ97bd;XfouQv#zr+RgD=MDG-iZHb|;8PZ8-0{H;WX1CXkK9PsFp<XI8>
+IndvHJ%8c-HOPH}J=C-|IJ$0op(*olCg+M&Tf@aq!Mo-p;t=1uTEuH(wF^=4aD)ZTL-Fb9LYR=I;CEL
+q3adpexyqEBKo3c3Wd@nf*U_#m&@ldK*z2(T9kZ6Mci|0ircTFA{B@CTJI;1Bk{Ey^ZK>qKk>HAX-Lr
+JJEeaj}g5<^mn4m&4S)dw18+P(Nv-{OoGlO`Vi4gMBgD=P4psB&vZcph;|{`m*{Y!<B6sc%_Vvt(M?3
+(BD#<0QKGd(>xnkc5Hy5nB+*esQ;B91olkTr(Z`8yBKir@&xzI&{fX$GL|bMGY9Ja(bQIA<qUl6!MDH
+WIoaj2D&l7!z=;uT)67{9>=}0t^=vboi3Z?SsOLVl!-M^?iGb*llfIF5~d4J)aM*c@930n1x!s*2^N~
+7_TJ`&+dUKRfSlN;wRFaP;E?!Sd-xY0d)!7;%{Pq>7zH{nu^|60O6G9QF}32)cnD#FbPAJxRKCESegM
+U6i@?vDMByUQ1R+&#T;!hVFKH1S6rch~D^!k&baH2kL%mT_hfmZhGi!I_%y*&6>`4KC2&qT}xRzE9&{
+s^R~T#(#wduhxWLtHDoca2a7*U}w*2{L3}?MGfAfNq?)xf4j#29gTmb#{UD2f0YLB)8K=e_(wGOs0N?
+V;2I6C)!;e}zM#?9MGd~J316?le`+v0p{eg0Y&hXwKf_PB*Ow^5L4=bu{%M2*2p19VNO&#bPK38>{Eu
+q<>oxwtUkTimu#s?xOrNlUa4F$1!sUc-B79I2|03a5QeP+C_3cU6OX}~Wdw9c1clk!2bnkzXPP*$mjc
+`lC1t;C*S#i=m|62%mm--^yP0D-9-9MagFT&GLx$`eN<*u(X!d(bg5e_F@PdGyIuMxNd;kX+2{&+g!)
+-r!J?)|5>zbw&&U#sE2y~e$M9jtNJ&qc!Ro8YhQ-?aUcwtZ{+18x7Lt^fX~1#Uxl=FD`H-JB`a2RI|s
+oRJH(z+}%b<vQK%j!eM0Dt2UB>`sT7GqX%~hbx|I&T!=0qzmxPm0;#fvnk!8@||bNa?I?{-0=Vv7dUJ
+~1_8C1?GBqI!y(-Zt)^VdEUP(_W9f?-F<8y>q}+x~bFSH8W+UJ}IvU1_!x`%g_anfeGyHD9LxjsOFxy
+NZFW&cw7WJnWRLVYm;KxM$yoviouzpO`-{JTJ9%!r;4YW7V@SZRR26`v_7GNBRv;b}*z`qy#`oOOr{J
+LX2h%_7++ywUv;CCnd(&lD4OzFAi9wdL-+;j~_CH7!xj^YAyewK7*X}S5}VX!+)4oik%R-wt3$^Ft$E
+!J7iaC5P|K`Y>1hy~O`y7S@^>VgQ`5NVm_EK^~w!;q10l^%wS+<beXjmwsXb-{Fl_{85ey2T-M-oq{Z
+M!i*kA%0U_Fr3BaC<IMpTI>b6rVMkQ+3GOlnF?e+&Dn;(5JelVQITByZzxh)Mt(tYQ%b{h3NsxBo7qu
+lv+`m}8xzOUl2cRT-OE+274Eok##sMly{7svAxq28vsw&ThwK)t6=_Z-iI7_PwEnl>;T9q-&tx^tGH3
+pkQnlflEN9p9(P++%-}U;xL1?VM#a2@uG!2W@;;=x^G2d)6WI-^QPw8)Rn2Rh9SNU8*xz^(wCU;$Zy>
+aNq^!OM2-P*e&+h#Upx-@&WKQnacVsOJ5`7=%POcv@!Rrlc|qD6g4g?_~_+HB9TSqfYPG>pQ0#O9jpb
+{AjJmLdE){}`LiR7?@cDb51P*fO$<wX6-X`FRDr-c3rM4OurNK)zhkO*2{Zt;Koyg?0m!kJ(-TwNX_X
+UCmhIm)2crBury&axA5dFR@M&&y#*$jZpSCsfP=7y}a1pyHF-QbB+r<2)m{s#{hEdtY^;4gWNq_u#D%
+ek;9u^f9W*Tm49R5T`vqLb=#~F+!)nf-W1Qf5!@JUOunY%)naXYJ!|~Bk-q<q`~O^j?~-+fX{grSbsV
+g{T-&p3JKFdX>s;Jj=T2PPT2uXjz6t6Y-}TbAN4+Mjt9;tLxnkG;LAG;k+TN^j{kYc08}$=fxo*_{UH
+c2yu=+;ujjkK@8~R2lYlM0;_x?ftSQD6O;{Q+k|Ic0F%*qN`F8uWr*jkvI+tcZf>%D$1;X48Lbit2n@
+WX&z%VW6)Kcc}aG<c;3KdQm2G<d7d9dFZMIZq+mnVgr&V|JFo@|lg9;jb^t<T_w1Hs3Y|#;-}X{0y_*
+&RES}_xWz)K6f1ai@?)~7DTyI!v#SriLOWz^9Pkl?(-Hah;L~#;eM28$vK+WCmQ#mJO82~jnDH-e|h=
+ucgI`yx$_ApT))@d9e-_^=x21KN2FNh!A$g5Etu#ZP`BQsb3IWXqQ2zk=i=9v;v#KDeErD{=Z6C5hwh
+!peK6q|!m)&tC{8lDrx2Y+{BNbSbICoAi8-+XCgzrGBx?!Dx`^mva=(}O+(+@Dp7Iv+G~taT$Fr2qKg
+j(}lIsBZe?k7YdWt!cU~gv~#VhT5QJ!T)Yls?t5VU~kL868q1x+JbMzn^g;Uf7H-9ps=61fxILbQr#4
+bh84qka<91RArjKD_<(Ve{bL3RJeFKG2R#%mH@}@X6yYxvW3@FMfX=KMP#a;m*eW-Q%*q89&!0-2wdP
+y#6YFF5G26s9f-w&+}pd7poh;{{Jof@*$sg_&=9x%U$Bgzs<h@D5hWre>?EW=I$ma2Y3Aq_?!HYhmE_
+=a*H4Nx8oOsO9sgCujL2h+qr8NxLvRHzltwhY><n_r2p&qMO*_WwL}K|t^8wpP99c3h2W31Scb_2-+7
+J5)Hpwkn*ltqBpjd-sTY(g4>VKAbu8<Wy@|ZyWriF%uH)}6VJ5hmcuk!Jbuu4f{MY!o=2&Xey%o9UKa
+<TREev#NsX3gN75>k4bH|kAv$|>hp=$xS<wIEHfF)GO<6hq@3EonAnU*_WZN9~G3a=QOd8{SZ98+Mi$
+0Vl2^XDM?;k1m&W=`R=$7724a}?dj=GtR&bMrG~eq7wg+RSEGJkIQxYRWA%Ys00ux_gs*ygDrxYlFKC
+Q*Mem!(qv{LfUwFP`HHHiKYToDi?R04l^g3^319E39<2`F%CX^V+snA@^dX2#UKq0ic-zCJd4$Y%qN;
+1+4+0{Ap`zkxWuNgR5lhg6h--yxIY`h64)5Pi7XzT+LPF5K>u?YuKNpD|E~AD{x1$n??!+3HS*^kVv)
+<A@;Con<1cpk)BVjq8Q1WiR{wweDp|Dn-uv!<;K9-*OP4+L@bX7itbBCU>c<{mv-XK~Pd>H&=?!HYH$
+C(0bI<>yd~?MMFTV8hD_dTD?e(qO-gtBSj<?=^=iQy}RqlF!_Xi(-^l{amPxkKHf8f)DhpG=B`RwyAj
+(&OU_=&Gho~k+h^_kjlzWuK5?78z7zW?FJi<f@-`SLHn{#JkG_dou;daZ#eIuB2;X5M-qU%%!pTDJ0U
+9S|7Qrfs|6_8}cQb_xwMbneo%TlbrKg!hc-)w@sMev$nL3>-9g$jwnhZy7dxMD$3bDLo_8oHZ-kGCL<
+X&zfH_$7XjF&Yf3OJpc9?cicHMt!e+e7A(B`p8s_I|I_LJm-QbrDt7dkvE$<6$4^L@m^dkEa&k)Ql&R
+CE-+G(Sf7AZ|N9h0mh#pXJ{{7v{tp`+`f4aZ<=j;Jp^Zj@7tNqhAlIH-<KT^d(@F!gn1-Qunx3f(7cE
+^7=zs`JXT@<(J3*(>SJyX)r8XBje2^yND@lVtE7ij!TH2(34W0}R8#S&u@nbl-P8lD3G$tf{#3%A365
+~F{7;%Ifo4E-(EOpeXHA|u^L&md2ONGFqMHql(71w<W0i-;~DdLPjhMAs56C%TnrCDDCE4-!2>^eE92
+L~DrF60IY8f#^k|mx<Ol$ayDW7pf;3M6@GO$-f)n-b4oxH4;rCI-O`XQ3uf?q9sIE5G^MvE75ksl|-w
+E9wd5{XbsUiq8Eumf6S>rQ3KH^qDe&4h!znoAzDgw1<|!c%ZQc}-9mIb(MqCKL=O@@O0<qB(~*2Scm4
+*#kwlF|lZa*$Eh4&t=(9v$B)XmGL8A3CJr6-s3axBnzLllI`^PkMCQHpOWMgd>mSS?CU#6*;p+Bd1K{
+z`C2x}F0<ept<lMv#o9>Ay2Mrb^=zp>_YHqm5*_YfP<Vm2PqA77ZuVhU%m6mtQal;L2B`E%K5vv{R~I
+E5x#F~+m;8@MLo$~nV#8Jh*)8-WLZc>+G%A9xkoX+a-&I?Q?LW*f-~{PPh(8m`Wmo{D28f}SS|_lXnx
+WoGs(mf2*PaP>A!gv)?8#l_?m7k5iu-Yq!8OzHCXQ;5&slko%NLWV+4ga0!*&IT9I6`vEp@c33O<Ke8
+E;49)gvEXA@T?9X?n;TR4+cd5+J*S&U7el&-8xP3J!<$(;m&3&8RAcxImB7V3oXF>RzUqMfg=`k*Yvy
+yYllZ&_^sA7Mxu|D86C(K+a<0W{IyM&<(m%&I|0FJvzD1oc5b2v;<VHE1@r68veBOeoa*25tF)vB=g3
+Fn&x(Ru;p``ro?lDYMmL#G=?uo1)=rj}lFLse9lm2?clYS!o8B~{I`h)ref44v?dGNoTsnrV7#QBgZd
+_Ekn*`S|3kn1GE^Z86&EXXge96swdfzP8m{ZsiodLj5~FWK*IX)XE(xh}b#uv~YkBrMm8stC*V&ZC6o
+`eO}Yxt3SgT0UpQb&;@K&#5OY?f6-Mz;f+MPgu^i`x9<KIGC`s(=`y5cE90-<-AWMVQI%2MOfOc8VLs
+yjth{_M{y+)mUg7m3AZJjMmU&oHeqS^T0mH}^Cc|pXiEa*b68xZgr(i}3c{g;*AkX?)MbPXgv$wcCcK
+5Pv?HED&j)E2y`B7}-Et*iX}4TOShdq8ENzpH5|#t28p6^pxsI^3d%hST#~0$NC)|fH3lz8?K|SFig#
+8KMOgNaZoX0W{9!fZza5Uja!nDC4iwczE8*v#4#}JMq97{Nf@Myx*36CY5MtB_IY{Jscv4HS+!bOB95
+H2As+j%MBNrYDf%5j*u))JmdxQy^L!sUc-BfN#M>{+)HzK3w;7#gQh2T)1=I>HADdl0T6>`6F@>X#Sc
+i{#%-b|^vAUl8^utS4+B>?8e&pC92!@^4PqNVtVepKwdUX@px5E+FhrxP)+PnLec#Ao&vxB)o#c2N5n
+K+=lQL!fmDg2nS335pFN_M>s_4i*N_2uQt>_NPQ6QB;_R>D)mD+Ov+E#AoWAIv(yjaE>b^)yGs2K?k4
+k3xVy|h;hSXs3HOlsC)`u!pKyfCKjB_7|Ac$X{I{k4fp9S4euTpb4<H;xco5+@!h;D<Cp?63HsPBI7Z
+HvkTuOK-;kATsAzV&)7~$=NqX}0L9!dBpVI$!>!ZC#F3C9xFx1;_>mN(%svb+h8mE}!%oGfp`@v^)Lk
+C)|5c!Df%!U?jx2`9?(COk=&H{m2%-h`87c@v&0%bV~tS>A+iljR*u{gbTkgmYy63FpfE6J8|qPgtP=
+ND^UB!jaUTy$Pq0zYpO8!oGw{2sbCZg0Mf~GQxp`w-62@TuHbs;e&)j2-gtqM7W-CZ^HWaRKExt2uI8
+O5RN5mB%DKdI$?zdRM~_*2^SIeCR|F`hwxg$zJ$vOHz&NEa0uZlDKFs~DG%X`QXV-#3n6(3`xEviY#{
+7IIFhh0VI$$@gp&w|5KbdJjBo*Ag$8&fGJV1;Wcq~5Wcq}+$n*(U%Jc~zl<5<$k?9kzm+8}hQQv|16A
+mWqOE{cxbHY)CLkPza9!5BgutEdM0?D6niR4dsh2%%LO!6bVUGg&sTqXGtJ}UVUu9NWz*UR`cz|?o7_
+=JNA`w|W(JdAJ@VTHcjij(mPPnYotXUp(3z$}vC375+7gxAXOGyzyH!xP>v!xOHO;RjLvWq87MGCbjW
+8J-5H`cC9eIGC_9oboUI2}enPBjsQE6P_+H4M?*kj-&iboIv@Pm<Et*341P}{1Xl#yq&O#-ig!sECA!
+SGI+`N(l~l^&7gPMO!Cj9k*1m6?9F^uf$@0_yt0^usNkPX;l(Tp17AB)@t!}M_~QF7URL63C0szbfWq
+6z-A4SfDIGh#Biq>=qH{TQ(2RtG!W9y=uuRIonZnEbh;(u(elFoGl5;NQFPr8HOrS9lPso!;a+n~7$d
+`%Y=Tkfjg|m}?4$)$gV;;#lpX7E>{so^|l#YY2gXGVla>!HlVIpj$c)1iVpQng+Ef^AQQ06jGANoL<$
+1p~EK|7>T>U&QHpT8KR&SzwBdyH81JtUL+k5=D%GP$*f)7C&(gN#$>H?p{u$5{0}DvPH-R`t*3@#9&7
+iVFe9u_=TtJpFi89t*b;iN_5B`DNwlC93hQkR!zMy{mxxC#n7gJpL#(eH)*TNmj$#c>2j|`q^CGI5j-
+hKh)m@70&@2qw>f4i2hO^4w~PIQ?ZR>$*+*(B$Xf5SIpmN)jx;NFFDK0%;mpTO)r<HC-rOQ`5U9ApUd
+S*P~S6ixqpJHzbsy!@v1y?d3jA$-($16bySQxlZNd8@ok(7&Q;2Oq0p_~<Z-zts`+y8d9vHod=zoLIP
+rWQ--)qZx#Aoy=QuTA!g_72T5j1~?s!%1Jf6>qYCi2;Z_aul?2IO=dd%VSPEhN44$t=lwO!b`b=d?p{
+X(vXDc9-2!P9ltpLCvYr(6Z3Z;5B|d^@p2<L{vM;haCTYVw(@!8SK+*YL~Z@h7S{gXeP`)F>%Wu3I^Z
+e#FT^^e0&3gyuxQf*eH+n?srzMVc1YbIx+i<K>j7>e)o{P9`k+lUTLAi1}5gd}b=Q>4ZgpGD<BM(LXr
+ji~hmsZ{_@4`v(Vaf6jU$a+jnjSJAGW{g`Vzh~+xTrEq4q_Alz$C{^FC^~N=x)Y}-Eu@ZV2qt-w1ypG
+fKyD_TVLQgSjy%TzJmZQ*9tXdAP`Mh3!XFjD|Nt7cYSAyDZgj^}AoI<Vy7dfnM=?b~Vx%59axAMxS@^
+s3X2V)0kiHY<_tMx~uKT$1DnZC0>w7S(dGd<6o&nKIkyy;Y4G1ry9kR!!S4-;MTCEDc}w{((J|11hG=
+OgWEKCe&5bX|T^)%s)B^rIr3(Q5u(`MQ^@;Oj2`B(+}`e8;<BJAV$0QTd9RENg~{f2&J=MLD~-(^wa|
+M9<?MKSixaBK{~%IVGw5MfmY5KM_9FrT*J_{ZDoapWq^o(AzY(@MF~S5aB1d_*;4Uac<#b)#tnjAEPP
+nDQbR9R1WU(lQjO5HRU+UC4Y9VpQ&y*&ZQpMc`b?8@ONKV!giHP`WNFxIZrJ0BIo7hygutK@En42-AP
+{l<bRZ~f$%ZHk%V6*Y$RMpIEnBhgwqIrO1OaVXM{@#R})@Acr)QL!aJnAgg+o$N%#cegM?+d*AU)E_#
+)x=WQO|)Tt%>6vu@%~{!bDPCoEU;wrkdPjN~s3l;t{})NvB|%kf_t;e}E^gx{3;)2s`YlE18%M>Xq$Y
+sp{s*X4vCl={%D8*V3mS&!>9>xfn4ze%P?c%=+aSk}{e!mkt7_Z9dBnVx1HCz$+~5x%Hdw+ttLxh_+$
+S;veb|7Qrt5#CRDI^h=yXA|B-xQOthgi8s(CG|=8L#a=~TV;L-e=hY!_@LAmVfkFIBU~x-L-;UZx$Y|
+0W%d08J|y);_$#R&!e2;z5dK8!gYY(~55l{oJ_yUrEQ<&~EA>J6C8-a>r=&gzuaf#8TqE^C_-&~V!Uv
+>22%nbvAbecrKT_b6GXI3Xl=&z8kxY;DC)ZJ<$X~Tsp!z4*LF33@+Bei_)>WsIzqE&t>)>*oJe&OGb3
+?9k_Lcf1e`!%5*Uja+dMWv@CcKvLbA-zYzf5>LVfh@dBK!v7qlDifEY}_7I%^&ImrD6H>$dgeFV`LAy
+1rcZ*Y_7#KBwe5u3Q%mCV#oVhg?^e>+s>^{|ezK!g5?7?FOV>K^*zZ=cZhzmK#P*C;!=m<+{3DhtKXW
+=gBC2jh#Xf`O9@%X_p}F7D~zgF~VyJ%l8>+w;-p@%gJ9pr{y}hTu0wd{?fulu5-(8;;P8Mh_GCDzJ>5
+n@?T6?+DS+|3c0Q<*U{@J{1U?TgynmKTvwN02<Zn1EG=lH9f7nv2qynogr(hqv{MKt|16n5!pkLpN>A
+Dy#F2j<;pv3$B`nv`M-a{?{|5-mb@*X~i^%^z!qTol+L4x$|9Z)vu-ve#oNyuG?S$p~gS11Db}Cim|G
+3l_VL5KCBfN&Nv|EvOE%oI8Fkxw@Anhvj0|mZY>PKS-6HNYc94YNyq+Lun`O9%{6ydcpKZGBW{0VO$o
+K3h~VvU_m5&6sab!k`Aj&LdY%W<)^lb~sIwwC<wCtObWAB49Po=doj@Kc1PosP8YIZFPw6P9)}($1!i
+{4)vH6W&Q!KS<!+go6ohk@_UOUFwtYUa3#QAItn}?2M+9{|uQwn#VswIGg<6m-!?7uGAOd=Lv5i`~+c
+Xmn7|&s>pwx)DK~~AD6VF87TEb{_`b&jU7%s`7b3b?PjE%kAASgC4{9NjkNm-CjUh;KN>r$aPq&Ca1>
+!HVQE(-?Xcp=e<opR_cK^x@~34J)y~R5IGg;_2}?UIY1dUm{%M4zoe?b~u~PDXTFOWGF2d5zO4?;@Cx
+6<0kW~@RCw!E!wEL?g{59cv!Yc^thX}lpa4_N5q&^8(NPQBPc2RMJ3kZvO+4<`8QoP5S)bW$R>FRjML
+|?$pcf)4&`5>@Gecu##wwhmobJYG<;9RvlBrbNtc^dih)#r!6b2R?;>##dNhg!b`E_TW9e4c;&Kf`6d
+#nnC6WqwD@->0km#rjLSst++=Y*Et_^HJ%1?#7jmSf??o<3_PglcDNa%<Ill^(5A9GS&A|F;8Yv$6*3
+H?Rqn5w*j*o&Q<HB#Dyvr^T2u36N`1AS?V~(Oy3O`y5V$HUNe0sZqnd%H#|#&EvkG1&sNLXOy5nr^Dj
+{IC$K}!zrcm6J_Vkyk!QYI55;_o$t8cHobugphWg$hvDV)`ex}CXtj-fiY<I)6T;xZbt=1cX^VD&oz*
+e>V1TJvNpTK4fwrOy&8@8*@U4aWV{&QXUIk@~zT<De`u?}TX(-Z54S*pBZy(df6PZsqvW;g7tKN4rV;
+Vc*aHn;klMg4}<w^#>p$|u%oob6JqTRQFD#rl)0zm3|hE6!Ha7weqaYWiZG&7{^}u?}ca$01@J)S}8G
+);XN{6WF5G2VsXkTkW^S`q?a1Ut+y0M{OTDntn&F`$!jIx1OWQFV@F$)P5_Mc7$-KcrM4Xeu#A+XL}U
+ugL!IyB-XK<>5JLoJQr-!_>1=Dj`P&|mq)t^NO{D%uvM);VqM5te+0Iw<!Pn<!x`T0)*lp5eYL7Mm$#
+2x6+1Y8n;R}r<&o<uvd55Ews?tUixlhBHdP+6PHj``k6j~=SjTa;AAz0u5!kNgU#x4})$$PQ%66CdV*
+NmJkXUk%>m#oIvo-!!7m4J0f)mf-^*>ilPqrWT=c=o_>+{e~&+URn!wYx!@N+f#nXA#qJYK(@xY%uE;
+LzyXLH&UfXY=Pvwu;@KCk`4{*i`IrD^IcRU#Nx`b^--z`H0$4c-^?e)!j9}VqJf(DxX+?cgiEy3$Q=2
+Yp}x&TiwEEtMUk(r`9il?P~uppY$<L#f5I^t5>aGs+i06&**dK$2l|)Z9MnAW9-4FdT-$KOr~FUyzt(
+$Gj?C<nIXpcncJ=o^7^3q!K_EGv>BF5bLakFt}w6eJu3YRWlWcK?QZHZ3Ex?by2reCEt%S_<3E1?a8_
+QG{Y2hN=WRH^WxEb!_Sls1N$|5jcE9V;{(>J*<%C6_TR&3_v}>)`cJH6v{GF@;VMF_R=*HaEy}o+R)b
+a1{KIRPxJ<_*aANyLxf{@P3jR%(g?04XU`+E4DU$A?1_m|>vBET5()v?qK``$C%dg6r_W_;XywAU}Q+
+P-rr`IR^S==ty?X{*I#W9Q~e-){Hp@>iyA-Y~A&kk=;MQ8V*IiEqWVi^eaPmme$%$>|DRLuORMfX6?c
+cJF7S#@Cv<Z2oeD|L}KhKYz2*(dO357SDIOko#qX|KV>j_xFe1ZklAZMBEkJ@#`edUW2~s_d}1Qj3?&
+odA{x0@yo;e>f7a8<3p_NQQO7=HyK~@OtOVu`Rvf@o^S8JJ?rtl!!{jX_`CVVl#}zG++^62a^<~`Ug*
+Ah!o)M4Y*C-xe_TG;B{?a))tf*66gVv~Xw->?cMSdfiT1bFcZ_<JeIE4s13TtDH{W#a&4Ae^KhR$5P7
+lx8J=GAl`j%xwe4f->3f|pmo@+S&!A(!Dubb7z>eFU@ub&3Y37j0a^T4KW#w6c^Z^Qm?7p?wHSLx{R5
+WC~zmcoyYZw}h=<=3Zdt;`7%!soTE`8DtTm9djQ-Sb$FDKC8ed5>?)pL+gPJ_}?VfAGTPi=|!f`7qCS
+dcNm-vAgf+Qy-^q{X@rF%YF~PczOTG=lZrUoAdcQ5017hRIFG0*G~;8E`0V8#!kPsV|Zcd;#F-&?$5b
+p>yncXKCK@+W@2{p=Z{}qxvJZ#zzf-tJw|VR;)j?;Z|wd=H~rG&>@PQUpS$qkIf+n%GXMDY-rIg^_0q
+J}t+$o1tZh9FpH_eP#lpOi&vl&m=Khlf>yM3yY5Qj4CkN-O4XpiQ#Vy83Uypp@O8&fwH+}nxFW)An|C
+ASes;4)9e(z1DsSn=UarUmu4;Id?8{PZUab+=2d+GN?H+!qBuIkh8rd0lZ`nA!@k6Z3GbhCH29a?l{d
++p0!ZM==?!{$%A<JkiPW4@l0m)ENEPXniZGc|Bm_cdRf55MpH<A>)Biw}LdPuMs^)Ju;aI`I3_<NHr0
+K2VuGW#b)|*Om+q=r(7}LVw0$I`$af&N}Vo^a~YBy8QUnADiB&{qc0WpWe+HSW>$6=IGwr-&=X|#rFE
+l%SRGtHw<n$d+My99mkEI42vkresVz0mmj|J%R81#oF1>eJhSAFR}M}2zT7bW$@*z)Uhuv4vU1n+y~k
+S~doQ$S#}7WPsQ&Ee+>eJGYCh%Isuk-$URS<%Ligag7hCw0mjCAP54+{h)^Xpwv^?Wh|L^v$sk3}>Q?
+#vi>jM=lZtpU5;8TU(^Czr4JFd^XE7o=28U5ORQ2%Ii|BEw!YMr~g`>17C_N-s&XMbfugV+6iVz*cdd
+-dsk-?Zobe+)awjPpPKCVhL|?9!wD->ltV_2HBy{!`w#_27}6e@yScc)LgYF$o?+_e^a6BKt7x>&k@U
+jU{`A9qRMy+4?SdcdlC!b=T4M#RqJ2KPuX=<D23{kJYt`=xa8fJu)LVe_`#D-+ejk%EtWkd6Ne%`>5{
+LUMHuY9RBI_hOu4RESOe)YvFe{rOcYwF5}H_&(HL|dd4!eZs6cDukr_X^#3)sRaocav9}$4{Fe?dY-&
+F;8`tYHuPxl!&vVa&E#Log`dH$|N9@OaYM=UH(ySI6+HC%O+qPd@J|1OX`F{NQeQSEnd~9S?t6yJVX$
+ZQx=+LQAhjyLp65VFnsaKZH{N|T=%Rc$;ncI{5d5oC!-6*~;;s4d;WS=p2oF29H<-UVne<uH#{UfdO!
+?*r6Z`Xu_Rn@a<>dRlAHEhpIuTQPY^;^IGF}5r2_7O{Wj=wzQ%jAi5$LD<5x#Ja|MPtU#K3eg`f`rrh
+r=EMVkd+Rv6?1yVN00bl^4w|53~s(_$b)~pP!!bjmC1h&U30#Bo5)@Xel0yV4jX<g{H;Gr=S`1&di%4
+rBkb@0G<Lz-bjKsDI=4Um@*B_eeJv=d;^7yDo*Omj@im)Iol>qH{<*qDS6qf`5XzHJC0%;y#K*l~8WD
+B##E<L;XXTx1R{rGV`ky>L*mOF%?3S+nUu?GDKl-gN13vW#ez4%lTTUd`CBODf;ven2`#nE#=jktA@S
+XI1`a^eJ*m0n<G3yAsx6Q_H3(xHPsb|0Y_?%O1yLp*^{Bn5Ch`D8F`von`O1M0*@1^ZOFK^K*(6TzgU
+f$}aG-IGL+_!YjzRrD~yZOgG$ChsG|MsYuge#xtdM&Hku6TXD;QKYnADDKhR~$X|;K_3Xx0|vru6}pj
+zQEa^?RvNmuQ2|BbwlQV^mNa*mwiXZ|NQCm&&_+L>&|Bv-@a*IKb!yHdq%I{xjpdx^27lNdtMs&^gC}
+|dvWf7&Ix@7><^6Iy7F4VkS}MvegB%EQCCCujjjJG>f7oEy)Eqy=|Zku+7|ut3p;k_|Df-<Q#?eC74I
+7teL1hb_lPe}&sp2=yU%<wCfmMhU;fJ2+af+ca6%Vx?W?f|9_|*{<E84ZZ?=Ei^MhXdn!WkS`B%rCnB
+cSi6Wxgqmrwq-f63I{%gd+t8#F4^b6L<g?_CT0v%#xXamK8xLq5xzn{;|dIxYsAw#*9gRjMmbdmS8R4
+>&%u?}lf-UjLfu>k}Cf?|9y{`pM4<OpkXz^Zt%Pzo5>&JB6jq4&1(JSoIS7!b@qVzWC&$UZ*V0Zhmlk
+x9^*+$~te2Z=Zks;Z=o;9d`~{XZ^7Mn=6KVI4ZnqdGX8LPV$AB%$Qy4N<Vv|ckGuT-<53YJL1=z5ykO
+~V>f?SJpS9OUDg$RUi0IppLl)o?8EQovdlBDpGbVpsxRO8^q5B+RjJGWoc57p-;v$hM_DtzoVM@wZG+
+EV3(Pf5{vhP|TaRs9pLl6w(sx%*%(*ASyVr((C)bOKVgDuX-Z^~g&GXJgJ+pVjq^GMF^?v%dXB{73*}
+dkwj<cg`XTJE<vY)+wzfk(wi@R=%KCthV`wK>ftv{UCr>=SM!gl$qEq9*oy*x8+=*Gud*R&cmeR#XAt
+ACB_@$R&n7W6%~tgviF$*{mTj`vv+_i5hUp0(Yckc&;?(m_#rz&Oa$hbf*dnBo<{lxD$9*DRFjyt^}<
+z7O-z4`v=d(agg)j(PefGf%%em}hef^J-qmyjm<~UM*KJuT~pavsN#&X8t=_v(}$7@76WUJK!hg9q6U
+#1A`TPn?8!ZZLH$c_EyEGU4h~gT&nm6mnpvOcPPFghZWxrKPY}3d~|*tyX*WqVLyWJrgiY-^6$Y|*#i
+nQj%vk99$yR3(O<mSC+mjcno9q!xZ?-X$++bQ&=jKaiKChORbKfBUzS?Ccmt=?9sl4o()SfkzleFA)9
+Q<FaGLk%Tbz3L*vaYLUsNJ3Nq+2oj(bh~K*VqOkkchEe9ZlCOWworo}WMA__s&)5uXE`2JiS3X=S%(4
+s!n)vkq|_)3ci6uj@E9COm(byDu{x;qEVme8%a!hd5<b4}8x3zZm)j$MxqpEg87(D95YEeaZd1{>*8~
+g{O{jzQ2t=&hf<aoL2t!$O-O#ZNOJN-s~fs8b>)!a{5TXDIR|ME1Z@kcdy~@(Kb$NY&$tE`Pt_*=eIk
+R)3R@$=F~W|PPj+*|C;l^vzXJGvz440zVJT7<A*15T3NG-(=^?eoYp+jsh0G>sj>c9PTA4#I5qT%_=f
+vm$>G#!e2LRC-4C4BjOzQXT#i()<3ATKC<z-9T{TO$c9%Un`st5KH{AZwozYM9+n3r~H$6HsCE%9%yV
+IjrEwEc&nqi7Qd;e>%&h9=jdei**JKkA(d-RFtZhgG#p#120%Hg=H-qz?}FF!Hv)PS7m`i?(cuI-r{e
+QSqPaa9laM@PoY-8%JhLiE~!Z~WP>EF*fZPfqFc-<pU|PIU5=XO=!PEhqZV9k0x(8fuEpJfL_V{>&Ub
+s`H`O-uW&sI<sx!+T{g#(L?%ue0GdwO7yYY>jHoM+7SI~w;o$--W(qN@!0ThJYUR@-Z|=nmxG?XGy0}
+Ei5_)#<U}97^|jN}cI8E<KlS-+AFpB2UnRWtd)v-4qQ~8SrTe~_S<y*x56A1*-4;D>=Ga%qeVZ5E>4D
+$w>hO;{qSMxFc_4dsbadvATh0}-{OBjw{;@c~dth|+&P%&v&!<J-H{<mS&0d)qojvpQ5#L@)jDBuT$R
+Dw5#zsFrEzx+YV{Y`F>BoF4RvV))oVogVLLY1Nphq^J{p@mj^v)Uktb1l<M&EW}#6e?$HG0U&#iQQaI
+V*Z((fN>9m!wBW{bFm^X~}KTE4PL1^q-Uwz3P11!>6ChiyrmC=JpX&GolmpalgFub!zndJykQlc_@kW
+5E=bm58d0*Tk@jUZh30U?Qfc*yPVqbLficK==6>;PyGD4IeJRUueV0$OpgwD@$|XgammrciwFNW^ml7
+?ZvL$P*ngk}A=*OXK8Lu5JeI%H;yi(Y;eHP`zALDKzj+(@8*d@)kBYvxfLnKX3srY5U}H@VQ?9{mv*D
+2?Rzt3-(3+8Lw%uarZs&n)G{ZdBWXUyW8XWnC`~tJpU@kIe6!If&h|d%&Ki>xYvn<w3gUM<z6+pmDh=
+aSKSmv7hYQpgoP_k_Kc@RUe>Drlb3sL+!U<{ki*M#Ld_4xdBLk2{_T_6ovTo~2eV$I68<q5Ajg=SkZo
+@Yd1wElLp!{Or1@=Q4h?T$>yy~PSyw}_K^D1g&HztGWG0J@yvK$kZNHw8+=1UkiCcny3<4+Ed|HZ!pY
+tU<HGu7S_Ni~Vs8tOt}{F5n(ilDW?Hj(n@bmY-|LHd!-s&9>|E=`6olW`}_vnUj&9X*T3%84Bdy<9PL
+DxbvuUzmk4DeH+kpE=4~+^FLShA5&Cd&Tt6MqU3>ZULHtcfYL_^K(9UeLVf9hclK;^x(OU}Emkwsv0Q
+tTeCB0a9OC#GgDJ}aIqK1`&~EFOZn5?=Tj%zWku~+sSuZg)2xzh8Tk$j`8Qz(W+*K6MzRE9z7=7jx<~
+z*%_#k&SjR`&cy0$fwuld+mw7OP}SE@@gg8w{=BOB|I-C?r1IRCw5UCNQ?m%=onKbb$#u3dRur|(QNu
+L`bV425<SZA$9cK2eRAPmiuW@H8Qw3#>(&6s`~7xd-GiH#dJCGRD}AiFJLvrghRp{j<#~!~(Y)!p(D`
+r?O-j%y|Wl;+}t<UOH4Ys!S%_GuMQtYf)w9O35?l<%=zzSQl!2UDS4HXv9riUx)m_J5hWE;dWaIa2KU
+>^TT;Ov{9J>els+FXxsHHI2C|jL6rOXy-^DL_gn>Hom+cVRyV%?zk2<<<oR#9%I|JGU;pZroH9CP<Tv
+Xc${D*gaeaplsrFY7euVsEZ<#U0ZnoKHOoc{RJR`}LkEdnXXV@)xeAZ0)oShMqJaNdN8Oi2cv&n9r;T
+STgkI9zTw;)rl>mFuKTUWIC9v7RMfW~urc<<}$Fc;x$v_2Gm&nW_T%i~kh{<{^v*M@K_!VTV7B~+chm
+P~l!cjM+BP?p>-xNl@+Mi%rTRT9T0r*@kj8-rmEYTVHAsJk1l(lu^w@jPyw#tj`WYTVH7ydK<woo?I|
+-T$y#IG#qZn_Ci3!*E#PwuI!y&8i~Z!%fG4QSNS>pV7@NmGg^pcjMubz-<etu&)hu$9Ve<_K>*S{Q2`
+U({Wxuc#=-UwK+1niR?0io7-)iU%0DVst6Z3Nhk8b-9$JehJ(i6w@9QLH$%tmIH?S|31R`b1v}liSyC
+yuxs)|Gy}@(pr#4gFgt=S+qzR+EzLYKh`M|#ep3zRDfimEY=@(FdEjpHjd~J4HMz=_Af|>N1j#W)o-K
+1IM-@e+gv@WL?ojG&n;NpndMfl&DGo4sj1iBsatU^aYAV>(?(*88i2Wu-!lm~0i6uhIb?F|hLF78HG_
+n|D(|8&)TRl56yTNSvy48`=dZdBzG<a$%>nePFgHdZ?J2zaI$GwQvVk=536n`8ayduv%AX7mpSx6_M`
+C@4oZOY)zA_}+tyyMaUS2+_A!4nTW3(e{uUK=YA<oY)t5qn-XDh%<;4Aa5QQ`->`Qk@rEVL_t`jelB4
+<z<oQOe(jkaaNmXBcd6|R_igCDFH6#M8Sn2>D|s$3GPVMKnZOh2C<u>sWta_bp3f4dtJUG0t-h9*g)y
+=vGkSdOJN^^>o(E7Ry=z@=|H>bEdXk(0#B(UoK%#L(dop7b$nWt<^F2%V=&K&6@*L$|>ju!)Co=f-p3
+*(dund=oGAxHO41>J-as4~<8Z{d73BTMAMDMQW`4jq^3gy*}hZm(R%d6W&&^i1bqBzgO{q#g92A%r1X
+e3_h1kmdQXSg!B-|m9@sqvikgWCiq1Aq9vNZ}xi-j`(T)JUGHQW!gu;>=SosE5H^ze1i;h(C<Ve>~Rp
+gYI>GSR-y<fox^KOY1(ok+A73DH!dtPm2<G5bM5dTN&V&(u7}YUbmh3I68%~TKLsaK72s#W|VJj*cA}
+&DVMMV8j-6S@__c`+O`e#!oOuBdPifwpp8yFcGjd>|14vppJUAPL*X9{d<Jp7R=KtBZvSBH1NengxEi
+>xcft4a`g*-SyqH0c9Y+N4<>hzpA+<hX%%`?M{n_G_Z!<Fn2l2LCO>HXz%Gc;WlFKCGCIcSlf;-|-(b
+PW;2ER!3dr;t5NH>~?b=S-4O33prNEhVK-i0>&?s_qTe;ockRQ2Y6`u-|69tS^Utm8*eZWKmao@F0He
+gD|WL+f7$ewSVRTQGk$A8PsRhs+%i_eh&#zYLXUEGq~;eQ&k*A+Dovm1pzgzz=>~iDzOH;XKbk9?v+#
+1z`R(X|Fv8kG*rwwmlfb-0QA`nqL?z`W4zL@#(M0<96_i`^{OWharz;?mX@T|3USj3*r&X({Yz&#_#Z
+K|J|9+At>k7F7+My0{<Z{<=hwASp@YDZ8S24!~b#kBVK_Tf2P2gOmX^m)c7ZX-$O3`VH*Du_`k}9za3
+;7!|SAwtsgxHZYCN*bTH8Yyl)iGlI74I`19}nJye2c&WvDbP*zp%Bd>gHcZaTTclW3~y3}U#@P|Aw^@
+o99375s$zB0j0JWCI$X&i$-4!<KiedzjU&?r8((A_K3I|^>&c^U_~OwTqU(*S6TeHv+tmj^2>bqMJEB
+cU%CU-<XpGKzX~FYgE4)0^5zU0l#lVQV9udjAmewVkKu%<DdIs}#>QHLpV<J#Uvj?-mUP9UD$p`^u;B
+GAYMekfQ@UyV{YS)xKjA<OhCHA2r>!GLscn0>9}LW*z9eyXg1a+A8+FFQzJN#uSAWQP>M`&!#$Ykf#1
+^1-=K9oqFh_@t;0TVMpL6`~0T*k`pE<lXOMxBlg`u4}+AZ{Sup~4+)KoQD@#DjUiBfnm6){OPU3`fM3
+~1vj4!bp?Jowhq7GZ^4xg~%Kt@8`OgNovE0pBPoVGc_jjqQvpkawxc^;Kvi-q~t^Jw!mJBUVeuCd`*p
+-MXbmsI8^5vx@8SopQru?HIKY`RA^n&_^-v{75`qzQ~`z*<@<p%L>EK=_pJ`uv>dfVv}J}#~MjM~22V
+|{U{&qv>e_i6BB9}9}(b3N&|8I7eCcxeE4|7Q69pj^OL2nO#G{_v`(z&l6ns9N#tLiY@!mx<y#o4ou@
+I{v;MKGW%z1a4*3P0w7!QP|sv+K4_xw4CT0L=O<HA$pN$^E5%b5FJ1?j_7SfXA@mabOq5eqT7k?BYKS
+J1){$bU2YciZlVQ5Gl`}WonaDmF42dGZX)^)(Q2X>iF&3B8bGuQ(Y{276CF=9m1r)}`-pBL`WDfBM2`
+}!C0b9kd4`}NL?elgBAQAxo9KL^ONl;CbQ94}h<;AAmgrAJ|0LQnQ&0oZNTQ>NCK632Y9o3d(d9(f5q
++NMJ48PxdXcCvl}|^akwnLuopl$lP%4kUL`R$4{SWHKnH?!OnOs;9Z_Ub|#?E@Cm>seCR(pP~Io4szj
+T0*ytgjci$2*sF#^<Mtqv%<T=VV;{Y1Hp1aKnYDB$Fe18ta2R1Vfk5jD4w$!!-GnZ-T{Yp2n($T$v&;
+ezzH8w_9de<=JHU&Lo%v!%oc4EX?I+wBg}q(-`{|T~p0@1tMuy=P|J`*I^k|>@cV1PqSp2W3x>*wpkg
+=#h3_8O|vkb3F9T0?2a+GI0rS&YnsX8fKVwG>#SU}NOVjQTf$;<^X+C5a02GcMP47ov4u99+3FZ=u|b
+r4Tk$mfemxdf)6A;)F?hy=>ru3I6oN3snS>Hy&QgmD%xnZAj1ZfjX;#m#oiHXjaZJL%0ev%bbMYyFnF
+fWXb7iteI8HX_<<I3RN+~dBOk<Oj6o(D|#Y2dcxP)mjN%1`TXi=U?W*aXeYlb;CztHM{IuL?sQ?4lK_
+)He+;+mR`>x<yX&hip0wmZyusg^u*jGgBI?pV5q^Ax+31dH7f2T_<6H8#a67Sb}u6lItTuyQ~wOu5Ke
+#zMs)bG2u(BX^2*p2Z5mS$~Z0Qf^Nv&NKL)R$R~7+n~6fuD4#1XYvhH#$YZr2kSBRrbmL=G*^4z9%C~
+-Zgd)7fHK;gYj#{0?N-lZlf`aUGYEaUXEG>YEMJWcXf_SP^Fm_nuh%wv$V;wlIm`Yf1;tOWq}%WyjCo
+p3jVS_My{w~y{bDjRZ9LXdO`D5hT~ULWa#Fqp6@do_UK62sZvad|!dYBeastkyJ)rmsgrej4Jy#~Xvu
+W+bSTj=!ELL8t*wbFAYB`nRy;@Ei5vk?00TE~Yu17+?DU<TcbN96SIgH@)f``iqh=9Kk{Rtv$Mc^_|8
+4DGMw_&!B-;cG}>^%RR=W_0rXfEPT)7bqU@ph2JlF8d0^c8F?>Lw;OiLo`vebShTc)y!#ED8HJcFjw6
+G^zP&@57>a3wExN3bC-IzsO6nF|Qyj8yAnMCYuEp&8D%fI_Hs%sC~vZLX9r8XQSAo3bV4zHai+`Im>Z
+Up`)PCfwCT;zDDG5qU>i<pva)`C-Txn0R0QUPd1B!@)y!%PRbIswza6W&PwrbzXohN)#r&`jP1X}P@Q
+$8fnPXEL)ugv#qjTuMQ8Z;EWaUN-Cu_K3m(jQPWS&y*I%7qrqf&=bp5mGG|(k+3G?;!b@6}giddJ`*1
+Ij2g}ba5uJz-esVjQNjn_^8)Bf5kskrg*k-yRT<MniY`JaEWp54S%W)uAVNv_zxitt~){F}UlzoE(N-
+!9t!maFN5J%xYM2T%TI<^FeH|G(D@&GmnIHBoe)ZjZ=k;YpFUxOj1A!q3x2VjF40t3?}X{zPiLyM)tn
+2*2x@W6v0x;J@gaphlwG{$}_XqHjR>PdC+W3Sr-Ds@rsXli`hbZ{&BAz2JB3&SM5P^VsZT*P90{I(+n
+G%@xM_-z{R+QNP`M>3<Kshpr36*MI51M*Gt58a-dH(et<vHwK#E)r|em_5bGuz3jnBIu;D{1kgC3+mm
+!G6X*v(3xMte`T@`jKn<-K3!bcFB|r^G0~iYjS_3o^C>jAq0j)$jO~)3rfwlxRtu145K=tilYy-3gs3
+*=D2ZIPeBY_%#CIO8ES^_i*s38R6qm59guqP@A#l4KqC<lS2qP$_ky(~<)GXrC}fU|+#2lSu;_d?6kO
+@|I>vd-*L-j%TyirHg(Hw<6Hg1aL%DJ9*}wmDrn3iOJSr90Szv8N#Z_HY<$VY<C=>rk_<tPf+AfYbWp
+9#kc)h|?Ojf^a#|TJ#_AzuNl}u&S!H|FsXASeDpuBdhCiMol@E1CD^80!gB#Vb%py5OO+-1D3;axP|3
+4ytiAJnuqx?V>w`&qFG^SVm6Rj;*@BaR1Q?s`u~1wpN&VtsoVGbpYMC_s^!bxd%bJD?|O&zuC?}ATfd
++1AkQwU5Xpe&aNnn!em@LwJo>Ywn@)$hyAW1h1Ns0a_29cFQCevap8Xl6dGzF&n^9VLPrbf`o;(wBtj
+XcSJ;w^+)r)6}R)`Y7xxf$V%`-WUYei1TeSj2GTm$~1rXNph^y3+CzynM~`AR>XE*{iL=mXdUa^%Zrc
+WK8p>j0h+7o}AW(CM)Ru)iuqVgS!(h&ELN&OrHuK(wcg)hY(UFKegV?1P1P0{2UUc}8c9DLF)^hX-UH
+!u?9X6S&U<4%6A*BSM@(eL+Kc=4gc|2W+WTnmmT_xA4ccV!%6xqn+VAlP5|mAI`J-#%k6P&@bGt96>s
+dXx2xe2e`J51gj$;N5DG)d2rex+)u>hx*E`PG|yf<rj<Bh<&%7WA;y&SH=dz+(i9Y-^H=PIUXeUY4sr
+op4gBILAxZ&D#_`O|@h0nd9hxzlpNso`6CfYcSj`p(y#q|1C`1Q9#}uA{hJKu?_p4(n_d26AtCjj1rB
+wrN&?-dnbRF_V$<2U1vvgQJ8+@C_nXJ#CKLLy9Lr>A3Wf9~6J`?^<K8|VTXLVTmEI(m(RI5zXq5BIwl
+Q&AMc!BMXGdY%#&KOhWa_EQYq{*^^e2mp9SMco6W18ciLYxP*|BL-nA;SL+y+M1nmodJhy`WcMAKKTZ
+gk+xGJKkhj$$Fs|PFV6P_=X%SSD}6_&dqBL<r&$)?u4GNL9g&Ua;**>b|IFbUau6|>sZYvmGvLftZ6(
+;4EB^xRfT>4u1C4Z44zS3p?PFdf8YnQ`0kNOz2CBd@^$ETQVrPTQIqh<RrYR*1#E-svRt0A2|LU~z3>
+l_`S35e&rP`p_#Ch?>_7Ys+AH+?4f+%G(?*`{5vADyS8B&iKE*uS6!x~6_6T`zrhLb09&ZW}i+X&v2$
+2A2+e&*lriHzw`yGc9@?g49+W9u>Kl*>0-d@;twu64$&g<ivxdeV0^+W=u119be;w4`1gj`7PPM#5WR
+I7Sh?<dPHo?%%bg5IJ1R)`|NZ&5DnUB2%TsoCD;nS@cA`8~ZKY=9mkVYh%5K#x)(-lAXJ4L?NreW3h^
+X8(ZoN1CcX;2t&n$sXN*`0dg8NZO<OtD-$RA0B&ke{0>V`=8{!Iz1JDVQ9zmL#KQJXW+V;*KQ}>5<U{
+*)J-SdN<Y`_-s>RW!Gj-l!UVv%D4+BN^>v&n@{kbU!~cYRh4xLS+^leIM?iPjQS=weB_4x*H#pV6r&5
+St#e|!DPU(EvPNQGR_i54vdcUDwL4Ur{+ckenc^=nFzSaFf_!;m4ziK;6zcyB@I?J;UqqLwZ+Dn|9-}
+fvxRxA3R@*As}f6!sl548Vdn&*$~_v4!5N4>oL9PQzl7Ji=fp<Tc#(35-t{%aKE%lB*m!>UP7q^YQy`
+aM>Q{fXt_4}ap>K~b9D&q9QwTq$5f`0uh`&_B5Ll(g$(rgBMnMQZLs6Aso3=+1GO@4evKqG_TM&<?m;
+RG4B-8qaglk^#@4-9$G{@l_4D4CN{tXks<XH`L(Ik7<cFX-bdE0XdF&G}1&0?iV%ERJ#>U=;5x3nc6W
+^Qe#bcp?&Kun$nvRC-i8diD_==-=-S;)d^F$hbG3OT+;0t{9ue*(4CsNUz^|-dzU7{ao_S6O(Xz%-K~
+kPrtzlmdo-~G*Rl6%N-iaU=RtSzeVUS|=l#52A*_I3qF-YFs^~X`wa{RHF{TQ@x4^I64E|70X)8@EMS
+q61LBHX;s;ws0vpp~L8(?t<O&sENXH7H-hn%`-q8iuX-kO+;YtdDMKaMgv0RIj;EDvfT7We(SfquZE?
+wYUwCiKvho>T(11byy3HQ|Z-$-Oj;cgIYLeKgTli#8SY)s!Ex_0xo%&k^mf2P_Q$J*+QK6Xk%8fg1D~
+{XGc%4u9%5ScBe;)ye>eahwQZJyDuZFyxN%RS)An>bHezD(-L}s)+`pK^GwXS=CU=^SG82hJFTpWq><
+i4@tw=uNdElvtIZuKri4W11187jnI_8Nd_D;+N9orVccQ^+>HMAc?|uE`&Eyz{t7KA9R2t>^z%v71DO
+0bP51$pMrh(uz@RAbiSm(fomGGp(Yic+Vl?`FQx%|<<tLzD0E?c|L^`0?WKDby|0t$Fo()dj<e0AX!Q
+>uKevfEjfTbu`J%f4&{$>(l9Gt~|Ij&XD23=#I_s?kJTa-)u2jmWDS*|Jn7X)~h20!$o4il0{&k@bC0
+{o)?i~gxY%S#%@#~4#J-~*`7mQ4Acbn{%PsW_t;FbMa{)<91Hi(b>j48Yj68vN2&lcyd1ifeP4hWG{k
+F-_N(O2But<2My$=yoVF+0JpT6tExdK1&n%@aM%2^f%kh(Nr8Faw#9gC4kYOHyQ9rK+koW@-L2cw4Z2
+G@*A2s#rSW%rs50B22B*Ro{iwY!PlmuH#HS!mTrOm;XdC>>4j^)Oa1`jO}-}{&Upr49w6TxO-B5;%nA
+99abLt2eCMzm#&N#qM96nl`8>#ZJ;@1^oN&GK`NvLp&Uv5jrSaOw3B#R`?_ZG~zIT)i`SJaj>M{T6Zo
+&W7)Igm>Y7xT5V;K?vxd@je)O3tz0^2Sx-$<>&m*75otQ?T|82W5H?*y*h#&_7^I&EBF@B!p+0^lm@)
+T60iY{u4epXW;3>bbApZLQ}%Q_=4h#Pu5`SGZqxh5Hp(xL<XJ`@i30((ij*;lB9__bv6@=XaR>O#1It
+DqWuYY=BL;&=a{4zTRa8&V4(4MZ-(i)?Iks_R_WIX<U0;x-R({<r`eO_L8RBGtZckaP980`;%;PgCBD
+#PrihHey}E7Dyk=S>C#0E9z0k)_Sj=0E-p^YoH<h$sLh7|Z6Y~2S!88piOrigi;|KO@!4meiQj(vO*o
+gZY^pFWs(95zytv2KL^OSG_UwJ?a-Td~V{1|~d-mM9EO1utso5v@T*Tw|aP5wZv%tmm?Ag4o+_z`X9(
+Ap@pxp7#Sy>aKp3k0J<^C;@<-5-7+56n9i60YFqhBvz`91q$V)nh~yspuoPs05gUZegRJZD0g1$zDZ^
+`wic{GL7g-qmkhRP`Tb`}#H7m-2;udq^7Yk-nOJKOM%^1wL2wFRFQdPtBeStb^CT4SymS1!^Xteq1-)
+y8F%!tM}{!3o+~;_wxLOcbwJN0IPZZ>)#)2He}B}lvu{@a<9pLwX2U_KwVew-Iv}fZ;vX=jQijE_m$N
+^SNo!%|HHIL_f*&Hvz4gw`=tDJ<o4<s^_b<+zo%ALOZ8awKdY$JAG7=(rgHtUs$bFO{1AbAqBH4_MNN
+y61r=^KU#LI}m+XeD*@W(>u8=inIafU2E93>p(k3)yH{?dhO_5tj>bZwg*RQ4L-MV!Xp`oE-#E22%>8
+GE*OvjUwl0;5Uj#$5bz0&bdKmAmkIB}v@&#n9^73QASqD_q`iD#_O$c-`E#e(f;x5rGJDi%OQG25kFu
+>G3|Xu`w=-<^-xh(8v*c4CZ_zr@VjePZOuk=tX2bjt;dm>4o`sFWKb<ou=Ww~rYaAr{EA?Hfk2zRk;7
+{{kt`T)bE$lomfD#QYX5q(`F`Qn)#@xJow4G;-#qdOxv`{8T?(efPX=+qR-pr%u9Rv50>C`U!u3e-Ru
+Utom-)uwi1<s8M3{=+WZIC!ZAa#}5({CQJ}dJ@u5BJbAL1K7G3KAM@tT6Dc!&Mefu6#2fSbh{Y2Iie(
+c6#7k5C#j5FkV#~tbBHtD)UR^j=Y)ZC@cVB#1l%-7+UfZO2V5bya-<865mlWOKm!j{7QarI&ihz%$c=
+(_c!wyRkk390I6k|?GF|I<2vENFuaN$C+bm>yDV#Nya$}6vkl`B_@)vH$vyWK7_GBT8Wi;9ZGh7B8(F
+Wb6xt2pp>ky!M-6dS6fc;}sW#O~d@#ooPp#s2;K#m66iEDjz#D8BsiOL6u@xj68H6i1F6QF?Le)G2Z9
+>}hfACn>6`s>H>M7nQCsnY=NAhY4{Ll*S!{_RY|nTVU+B!GO*3cF|9E6=UQuF-J}l$#R9*AlHeH<$lA
+TiaUYd3iuY__XGYA;Ex9W1mGvgX5x9^uLgbr@JoRI5%7<@;I{+5AMhUs{tVzR2Yxp2cLIMu@XLY!74V
+M%{}k}g0{?;wzIQu}Z~oBrF&JlNU>sjA#J+5dw{OD;KWZjqc~>F7946%PX+oY}A!OA$AuqV#-wFIyz(
+)X+)F1evz(-wGaloGg{O5tc2Ka@*-vRuOfPcaT-%bC1x)s4nQe)uX41D;XDg;B)e7lhSf&T>Xp9cObz
+~2b`k6rM^Z6ZwE4V!I=n5h%YwujgU&9B0YLN<F`$gWl)hdnFgwADhccwNYKr9$pM?1FCweh=Ue0sdIv
+Cjfsr@Y8|+2Jp85|2^QN%@v1$e**YbwfGO9hKEr@9BOzDHDsWMU8vy*YN%=^#SdMjI5$j+3)7^yxI&7
+b)=BZpep!ouFYx)zF<;;h2mUzV&jNlT@K*vq6Zq?azZ3ZTfPV=1-?-qrJA2?R;NJ`UmcVZZ{0D&FANb
++Gp9cJ8z|RE!cHkd$!M{93=*jg~K)?Y10si_iQ$sp>wQbX?RlC8pPyGjk1P2EOh6MQf`UggI_G;h0ZJ
+WV^TN^b52IDdQ55^yXff1cLu)yHKX6N&e(13v<zNmg+fWPkm|A+@zpl#b$EuGJUL;d_i`~w05fKR%*J
+kY6A|A<ROhJ=O~Y0$l%cSm&TqSw%-RZDa0!Nf=XAtAxOArbfAagQgSqkxyQK)VRw`}z|(ASB}6JMOqg
+f39e3)5;7YgKO)Lxa-b4?s&MLD$q$4XlW*XKp>y`^ZA{3-2bqXv>_eY0`Mbz{X-uK2^km?(VP|B<9YY
+pe`(UB$$dlE0-uMfg!-FbRv?1iz~=!2LxV#?LI;MnxU2x4x9_Ox9}pTCGB7kSbkJX$-{ma8=N-H{4-t
+C(0jde3*CP6|fV2Np{ayQnqKiWZhJ-36R0~G`gZ_xXu6`sT1a&kYH0X{y?m&Us=Mg<_itzIuhz1_P^S
+=%nq)520_IW_lhE08LvkVLg3`H*wYN438-}o?sZ*PD92i=-BwD?AZMuY|rbW&-2cS!^XbQ=)h-9Wqf5
+$6N;RdAqx?emCU-X4u_(zIqlppYbnhWJ8}E<N|}+1>I`V>kEPgYht60Cc%qw}604&m$rR_z&%KTcd_O
+@Mk~-YYz^*)P6(&iwx~^tErJ6p9lCtU5(GA8T|tV^Sh<lZ9^jhLVf!{*MxAbUr#|E&3c9UqaTA^9<%;
+H^%(biJ`~U=`0~fP{-FLqC}Qxy?!D_gcBvm-6YSr+&SMdBc?zxbSjv(G)lF@_6$m6s{+xJjK|Q(NSk5
+MV>%?<ck5i0zZus!wDju01J-9aZ$V%uh65|Gn<mmxo{i1=Q=+*h6XDMO|__?6Zq!@Knj~NmGUw-*zv1
+-*Sv1ZL0k&==k($mvbtnkJgZ>V_i%{SjvvBD=MSz;C9jUvPfyLRmoAAb0uiVcn*JuHqMJt~eLKQ6xc<
+{R<tx8I5%zCWvCgY)Oli(h~JRjjxu#X4N?|HZ}6dbh+t*OLdbV4xd^fo={4x)(9fWr}8Uz33{piD9x-
+Op^!13VBGZlP55KSGnM0K;%ZPwG}_$2>c$v_XB<i@W%ju8t|V3{u<!F4*cD~zckMMH%|F)obtalPBFg
+g)Vz6f^-9w{>O)k`J==PFd-K@u=H}+jJ)5`e*uvws+x`kYyQh^`+qUi7dN=cE+Tm7QH*eXxeS4H`=F!
+5tlXoX^U#pH@-uK_^-3$e8yY<$;-q*6Nm-j6<d;QgU!)*5I=<V*_#0xkbZolo;=AL(V^uER2{pQ9E8#
+d|Cv}yAOH#P5g|1It}^M<!ai@O?Wjaqp#-QTz&>;H?V=?+}o()#AcjXS}<TDHB{?LIsO%Kf-T`<?E)v
+wiDM-rk+~n?$tVu~VluojSGbr1-lJiSOFAY^lG&wV<gGeYuF|=FC@m`BZZ$!}9#VUJHGFi01%Csv_pA
+`q}G9TnXdk`zDv%P+a<)(*Jb&Bd^|)UVaYpt`;p?uv3|N6k@x^jT`fvZFmOt6I6cEi$`kl_$;Hx|E%Q
+ZthdRv3OW<}mBS;|-@JD1+Q%^NY&m=O?APCY_uWa1Jx9-+IdcN=@VRs6&SGAA{LrC8>)w0sy%#i1>(s
+YzUvDQ*p3Zvsxl{JTjr1R7&4Ky$cJ12nbD!+1+pdmMn>@#i8ROdn34h=F*=L`<h<UW!zJ0qqdGe&hcq
+%{r^iwWS$-{>aOU%C|pMwX9arVo~%F0vV^~gsbee~Ln9Xl2b7%+h66j4t6j2Vx~Zsw$ga=qD^`S-2PX
+Z(B~KW%XL<jIpCs;;j7S?Hf=zFzw8L4WUq4e~6cyL<NR*^cyqE=B+Q@4qiMZ{93HpDZpeR&<{@aYBCm
+_1ChjtW56Tzh9Lj4q^n}KMtI=>(;HCw`tR+c?j7CE?&HNsMTr>T)upH7~*Qu#!n)5y8G_CA6mL}>EjP
+R_#pevGcYjFi}l_p{XhQrqeLvTqIK)m-O-23PoF+5OG-*=`+48Kee(0qKUZ`@K8kk!T~SdXzxd({bxo
+d(jF?A3=-j#QzyH1(diM+Jto-@spXCof{P5!^pM0|U*s)`W(bi8a2R{D=d+QDwmJ|0z=|?=pwrVr!H!
+^uJGG$_9(r@r#{B7jAyciiY*JjAPHoM+u{v-6i{r20-AjekFi6!J==gysqe(J};g9nuijvP6nu1O<p0
+yeDRfddCrrfpCjgp?a?hd3X6@PVSAGKBq0%Hg-)jJHhngzH~$zlP6Y!w=pF{TD7=kQj!P{`>g&w4)v~
+lm5MX_sT6>wn)faB4$=L%>Ji5cJJP;GHEX@EmgKsUS6*LCJ*!h)Hm7*WklLGekW!0K`DJdl(O4yDZSs
+3veOPJyOc;d{Cz2NPDpwF!i58{mHVzqxeNW<wryL{rcImfh~byRUs4{52hz(vXTOpk%7V1>Z_56wuf9
+^5f3wfo-=vp%Kwd~U`=2sS{Z`7rPo?zxNXkC@r0lsz%7;q9!!9X1f`@i*N!jX6DVHCTvZkhH^|eXAL_
+d6eZ6^IjHe_MsKVm1e1M16TUr9N*T*`n?(EsECGU)Mvln;W3DW6Gsp+?G>{Zd-C)ox8(7yTD6UZgHBd
++4EuT0s|<kO#=&cf61m>Je$Ij}P`c`<ybO-cbMPcQI#E1PulK4}YQaFyLb;`-9fr;GsM8##*k^A9p~?
+Hd`<MJ=C@6$Cx1v|4;qLcqEzY%EZuf_A6yUy`pXye9*?JXViPzg#l?7Oe2m+`3QIjf&LHrOy{9rnUuZ
+u>O5Fr3lHp+(rf#T(+^*~qHWu@-64nNv@`ma`uL!(UrE2%|9sAIfq3*Yu4&Y9*eH4UQp#ZPFc3Txosr
+j*zDIubO7#Eq(@zrP%w?H87}?;XKAF_V$1lJ9BKL1zBQxfP$XBQN%9p45DIy;KTFQ~fq#RZuWhi<0+-
+c9ynZAZS@7C>^KB?U{-JUyd)omIcch8mRhn$yn>(;Fm{P_~nPd%y22lbwMU6&7o7wS6o=<uHPGHZ5Un
+KrYZd@a7e;(_VOQ&Nt0@(^}d$|0aB=yMl)CJ#<~?n0jgpV}5asU>)5QLOt`q=og-->OxsTK&fu&vE{D
+@}T{4JTPQId*HRf1L=p~lO?Z=m$`HL%FNmQWGZ-A10I;7;6I-L58<HW(W5#KhCP!9!=CAry1s{ge_P5
+9<N^I}-VFOMRn>f0AN}z6O8;SN%NY;R<_tazUdRK-gDdG4>8GFEu+U!?Jkv+!fQJn5kTOH3KmM$gk>7
+xaN+};Zq1!WkQpgvV?3p|m_DmiOd!|qF+M=qtSeJg<8OImIS+$uw7`ZMV_1TEQ3)7|rz2xh2d&`2S`^
+fAB@Gz^NJYRKMe)hA@Lj-sja}qqb*mH=}p8XH#KFMdVK0X^hsXcgTy`^5ir07R{zpQ)r?yV4`EFt~$i
+-gn}^1ztK;Dz@%)*5jcpK-ip%)s=ft(V+5zn5GG9`eD113YY9IaQuJd+NHJ%_;CX88Y!P?AaM(wBJ@g
+{qz@x{`c<PyB%d=WZEm~CT*nM;Dx@Q{+{z1`b~~i9NU<-E%K3@!NZ36y=BqdJ~9tH)V1e-!zZnn>@Sy
+193T_p0_5Te0dm3kK>5PV$K_X_l_?%vV~j4&7~@Lx!{00Y2R+M4H|ZiIO{AOlK)MZ?(8s&R#~gpjBlZ
+97#QyRv@K6jM*3SbEum##Pc}R8gu+qsx5_x!PfP5|%Jj4Xb`QryF9+>Epdb`9J-QTHS|LHS0hB1y{b~
+qd|H#b)@E;6#KOs-}pzyA8GEPE|V?pWMYZe0i-U<+@6heD@4(<i0O>@U|$?=O?BzVf9he)7dh{_+Lz@
+GN*(1Rmyr2d26)#@`Oq?|(=?bV2Dq^m++-dG^_7WnNyM;^%t!FnA$u<^DJ1&Lur%33%879+W+U2l^z#
+p6&2StEc<QSFC>WU*KUmcz7N>{2h9<Fgj2XN}uHK5@WpaP5u6#^c(u$r%#`Dq=ED$CMMSMP?wLZ@$&1
+hHS)-gSLHj)0_66^K5~oGo?myd=X56ztDHRi6MD3KqQ6`kr}Mz1VhoJWLy*^;RO9al;`iwu${geGieb
+Zsg-n?;<$cmhd!!A_pFdym;HqEOk_jPgs_q=CzVz9yg4!5^_WTd0J=aNBjekf#Wgiq2L^;Up>}(Z#F_
+u}nbg7&*YgR1}SL5SqGGU@mT0j3f>=``N<7cjv?qNSAB_-{E@09J^x0ewS5i%nqLvmb>kB^r#X3UVwm
+Mv3u{pFWmD!;>6s6JjuH^&D0D#k*LM>!v0qCM}+oGEL5#(X1fR;@i7F~&-#Jtx5yu0{XWty`NS)_K&R
+zjNo#Jz`>Fri>py{u}sFC5P11R5^6$P&s162>FkH{6oI{^2_q2mtIozaDGpE$pgm%juQqSoWqa@`cvv
+5$3nKT>xDr1Q5NaHAm2})bt%S}rN<bwXZoa96GBP;HRoS_`}SQL8XCHg`U72Gfq8%T4I4J(!G<NC$%K
+Ri37e3-e)!>sRgCb?JMSocAnl};GBWhakO%pr?s1;OxQ?=*J<z6=Jwpzz_MBbEp7(58%Q$e=^(arTUc
+FvgxpJji2VvVzTb4GPO^zBhO15s@T6XBrK_a$Rw2%(khHEAdMy|^XGj+<So4$4Lnz3^0-~BK?>oEq$=
+iGS#a?`&i$S*$FC@-8pe*p5n?)8V{<Yc*I$&w#etXLrzEn0N`@y8#RlO|14{f>F1(k1dhyC9#WjeOMQ
+g=-KThpG1*qiHK#kKjC#_ZTBlcI2g=1onUWihXpW>pw(>?b@wY>)~gfdFD6L`PgHRsZ5(Tc<9)%qntf
+^wvq$K3}bD_;Dhv%eq+s-a|1%!18s!%P}kl$X1mTkIDZy5xc)}lqW(jdQWh>;_%ZD?BqT)6ojX^_fjp
+4@0Rsle@bGYTpE4j1MkWu&yq9w^#@Ez)(n&}iB5$s`#h8la;Y<G6rcIk3>({S;k#mSYLO*qrnYzUFX5
+J%RTyvf|bEdN2fPet$=jSK8bm^kxz~{uN%SU~>W!Q!RsYmn&)GPX9%FbBd5bDU?>)yXm^n>qZJ$m$Lg
++5$Ddw%P!w-gWTAFdn1J`@j8QBiWpkReL9($muw{p@S@IsYczv;+Dd-e+t|{b8(4JD?5FCRi_hFlhe`
+^(^u9^z?(=Q+Ms!RVnm6pGMb9KihSUe~f-*=6sR#K(-RG1>Y)G_5gWH=$q03j#2Dm1IJiTq#tFU(*M8
+y`s=cwpg@g*g@uI*kA01Ps)TQQ5@Y0C(7qG*o)h}M$Mx>tsQ8WX5B)#vaXGJPZ-k_U@}|u~PgN{2dGc
+iCTVd;Je50?Sej9p7JD^=sCe#zkfIitZ9^&7umolO}IG%%Fo;*Rn+3;FK*QMW8S6y}3RkukS`JxWd7M
+^?VISHSo#%b3?+Kfyb`WgBnCh8C8M9id}e63x(mTQc5lgV_WwAa#a#Q*5;CFH^Ii}mrr{-zJY*sbOX)
+G3a&^{nYD`Y9VDhTy&q^`5%KKBo;O^JV@U@Au2-ch!ITh`M8JU0w*e#{R?;PsmqZc}3~BYrh+r<)};4
+bzXA}AnnHf2;$l`{{iiae%JXg#-8QWOO8S0!&vX9|Ddnqc;w0l`*!2Tjq=r3Usd{S*f2BsHrD1DH}RS
+}W9%QmXJ)y%x&0@!*V6AgF1p4ruCdM4WWsE>+Z8_fVtMjLdZ}CVo#e%!9r0=AAJq5X(N9`nUrPTmelI
+cRUsvPBSo1XY?<gDIqa2JqIm(Q_h<gd#gCZ}a9c}y(KXX<3UDtn%xzyEU!uX!?53ji|$4uQKeD~dVmE
+UC_&|azUq@Q*GeN6uoX;<{Su7AQ$)UN-K2acVLU+Dj+2ON($cCwE-=Vaeg4#xT}<-lwDeEM4YG0Z8{z
+6N;yvuRiKQ+KbX=U38qS6{^E#<~UjnLJY0p+~<VMyQ0WIIcGTlWAwVUFh#1{7+`K!S^2ilpjw@8wQu{
+vuD?cM)Eh`*|RHz@U7Az{`!-ln-gkIDE=g<)v4d5U7Hh@{2BBwa6+j=%?aI{u#posb;1@-=<9?FoKWg
+eBfR`~J7)0*65sD><jf7lRboZ1_aW~_zEEer$ZPJX)Ljp}Qes=4h<z;>^FyMeqlY2h4}{O>YuJ44j4?
+MqD^RPatozGqDQ6v(GU!u%kBw`=+*5e)Z7HAlP|8n#P_$f)2J(7e!-freVs1ALHeF4BhM4m_{Ou|DrE
+lSv4kA8JMQr;NVqpG;f!`l%g?QuagyZ@?8P`I&&)3JfmizIKQtta+O5a_o{qL^Q{{8UbX=t<BbwAyB*
+Th&qcgFm`A^!-UdjNj(O;*f3Q|>o%pNsn|TodP7>?h}>Ec@ZQ_Ig{;PcK@uDC(t`UK&Lj7&~$P!10lO
+onsMwHDg)EDSXDinZ{IJ+AriD5BEE{rp^5wuE}$c?ON?~4uCo66wDW%GUoT3=dxYK(d-jr&cnFLHF3Y
+}@ss*~ANR`ESJk(4aalTBM;}!CuJ1n7edmFF!tv|OiGwn0@hG*9x!k!1IQEQ`5vTQi(-BAYeP84K0at
+zG{t)*W`vQJ)xlXp=n1cCh6yn@buJ2(`{)~Z13&)==D<`WpFs=u4P2Omq`ERH7eNXPUDSa&0_u9C}Lw
+)2P756&1PdNGmg<5K~&v6{{{VDV2&3npqzuSms2^m`#%nwj&iCoX+I-+a)+<WEz@nd!L(a*U@!@WN4F
+;O2oy`}pHqkYCdu6w0*_uokiQ;~CjB5jtw9((TWX}R$G%W0rKj;f=NzRo?<hn)IYXP-{Bk9ktm%9Sfe
+xzfS5spo`D+;8KWD)$$-CcN<#>oxZbPya0CbkNdozrNQ-o8W$@Yx|5V=FFKhWx;|4Pr2^Bk_N7uurHX
+nzRta-eCK{2_nEjJN`2%W6ZbY2JNK97j??qYi{cawN*~KE?S0p6zwTae-92E+f5&saYQKwnMO@S5+PI
+;QTo>p53il?|9+$KIdE*DEwg$WCW4}F@%bzjX(xpqIR<B+?inhr4KI3!pO<LFogde5FseME4S8-i6*S
+WU6*15kxo8bNk_X=&%fwg_W<m#ijck8PEw5_L~etHW0|5L{P0Otjq+p$mRd)OD}DnFO+|0_)G6L5XH$
+hp3r?qU<%XL`Z8Pqx5G1C!E6wEG0|p^KN>zcD|f9Wv&3-Dh##yJJ6HYtQJw&O)`v!o9jBpkcmquhAv_
+&i}Ff7hZTF>b2Ki8^ygL#^a>Jm{%L`4U!J_1^p49F>(L4;OR>?QJ+4#=vux0pE35_xpSvH_uO-n*$*$
+i_@eTA^t&AU=>Mq;><{W9+jiY^`tIn*^32gsVH0)qagu-SUfI>!=a|BE4zB64k2$}BE!M83*WC*<WJ6
+iJvm#7Z9sgLKJ@)A(eVlPgA6LyE&F1SJ|53lmXn)kGQAd1zebu@v_on0G;^gzsKd<I@q{;9FhOeZ2*f
+&2`9+V%ZOq81!`>S^W41G+UGf2MvZ>#*~_#r8;5dZY=-~S;$KfgKTWB&a4Q^$@S`<}&OkrO9QRO`UYm
+oHaq7slL&eNM>!H{NYzf7Bh5nOG;veFWXQYW&x^bLWw;do>T_SkHYK?kyqCl4Hh<QG8!%t+}pjjB(s}
+w-VL!z2~d{z#sk3wh@1v=3XM#je~=O)%q)Gm^N*i>Ua7BV~@np0b>o>&<BhYHIpVyngCsnM~uWDc5}{
+utvOW-_7(a*DK<9tUGDL4jeg|Fk&?3D{u;*R+Wi9dyP=21J0b?eSoJgd^BL5&7W4BnLjTFewNeXXjh}
+Tewqt*DEtfjTwRG-l&^}!E5hw%t1>%tw_67YmeJ1JLzJ2?P;`;U|l>IMTwk#?oC1sQ`=cb%V!-NSFWT
+#G@<RgzfqG&VL{fzw~mZRPn{(|o%zW(~_DMFtsTu)N|kN#)z;>Ay~KCa1g%%{)c-olelKB@MYX%{TZ#
+6B?Aco{EqPla(icvyV{ZP&J6cMZ#RO@iam^y$-;Z{WMC#=0Wq#l9xr^vMSf9LT)EwpIIV2fjx6|N7`K
+V&HY_*2y(%)~K~&`bMrf8GDL<ux-^o+cCyp>Js@iVsP4?u`fv)sAJsY;QG_1O`DAO1pjE;wftYt8Yuk
+?eIMmqR8&O$JA=MhD)jY}KbrVk6OTWbX<yg!Z&yq;Eo{CO+GW4JWxm#Lc3pqFTZ<?3T=)Ey8~EL>`HF
+O6JZy2LXVAxhwQJX|Pfbm|03Y>TMn=XzGcz+U^E-KYd1q0_)SR3gbsuFKq@|?=+wJyk`T6-up2iqPIm
+4zub;aj?+KwGNxX$_u>ZpMJoueIcZcKeGz#L@67y5fpzKE|^9aU9rGVocJI?Wi)h-VC&qA!a$rO%ldp
+MHd}rrUd$#m9nUFx#T78FM1nSTO30J_p|P!|#US^T-?Nn`lR*)%bl!+17NqVyYe+j&shPIDh2)m2(Bo
+RV<h*tpr`%Yvr7rv{V1tZub0O732JfIoPUmdL5jLbMD2tALo6Xclu!7$ry$)73rqmV&WWz@!}i*o~G(
+>P2c>Yujz0dfpa$YALYa`$an{J%d-Pjyv2Bru^wYh#=4wu<gH$+>foFs2y{?>qeqWc``q+l?1ze7DRQ
+H&pPElHc4yqqc?0K8^P&f<Hbxwl(t&<iwQ7}$2l<W&_thv%>Py{Nylh92iu>n{tBtwI><0E9#s%fKxF
+^T=2aK_lY2Ez(@^r-k)t{V0{XI^#f6kCUb&tNDdP-RiA3j|5Dg88M`PI%;`TC;4>iy3(2@lKn-^?QZ1
+_OWFwrwg_Gv3Fc-)783dC;G_(!#$vmb>ad%Nz1H-brFz94Fa6$0N=YSU3GL#{LDa`1I4HoAt0SxK~7;
+IA(J_iMX6+bL`%=Yu9DCO!FJ%`FkJ>H)j@C$wrw*&fJvuHPJ|z%^vEsC!WBj@yiwJis!GH1iweYlLL7
+Anw#L)D|p4T*BS_mMfXlTd99(dq*<N2c9XNDS)IDpNVvN(+#4lEhzR^UPz=Xk!D6U*1lPg%cM$$&daJ
+?N-}H0vH08hz=<DRS0sgDI;2NW-9wBCk=^{={5fe~boR}n{QS%fLBc`Iv09D2!e2{w~cjH&=aX$n@qb
+34SX0ot~D3qTAYNB`suBv+kYT^^tW)?&6WG2dt6S26Sjyoeoy!wmjZ{l9mWwafL9FLOI)$hS);NPjhy
+q-D-iUj;M4tHnZ*;rMM=|R!hrT$T>bi7NwT}2m_Eedv1_bh@Z;j$lQsPa=#<0KajXN!kWZx{TXpst@1
+tx<jm{+^&pvS+O56LK*D6wVN$o_l5l(*dFb;EnW`kD_g;vz|C7Z3cf+u1KSwpniq{Z>kuN`p1ES>z5f
+PK8=5eU$-~w>&rl;kE2lE^m;Umi|`CL9>r7YQ9PbUT_*R&4T>7{^-Y*O$vi81dVJi}DgD}a?P6(fj-E
+1Z>iD=R6Z*9u`RJg|KJCr%Goq%9kD4@fN_4;WbE4zh`}V)}=Dtz!@zImVPMTvz1ykbtwVyeCO7Hk_vC
+)&G;yX`{8#jGw{M48koySd`+&e0Ma+g_M+nXmxO^J(%j-N5gwKY^_Hus$|eP+D+Sf{hLR@bQQp;ihHn
+DNo$W=@ZrF~@n0JJX}5%|t8F<HM%M&5D~8Js~>2_Mz+JfeAq6=lzC6&x)R8p2UCqwU3Gqo-%9d#OUem
+%`@Zt$MGw5{o2PwO^T0hZ}z^_i1(FS>Fa$NO?|y<nPazk8~uihy3X^z>Hlsj!w80fq9nB}wKBCTwK`R
+#xu==aywWUbVQJxMk!jX6TUt_@J*_CMB&{s1BCRS-q<f^B(=F+K>0#-S>DF{xdQ!SQy(qmTy)3;Vy((
+Q~cx0F}EE#?oVHuGb)(l%lQieUFD5E5!ETbZ$Dnn#?WSTQAnSPmJnUR^+Oj~ABraiMLvm~=Dvm&!9Q)
+GE$nX@ceepz8zky+L(TUJt*J*z0IB&#f|BC9G31E<66usHl2VU9?L)nRiaIqZ%iM~S1%QQ@d^h-{B+b
+G9YhFFPzdGTWMM%TCI+XBTCcWS3=EWLIU29FH7xjwQ!0CoCs2N2r5d#{=-nnv;-Y%Sp^h%1O?#=QwhT
+b4qebbINkcb1HHwbE<OOb3JptaxJ+&xqi7pxg~j}d1ZO!c@=q;c~yDUc_QCE-y`2M-<<E2Z^`$`_sb8
+;56chF7wXX1a)6TD(%iD#^4yBt%G|2l>RgfMp68M0nP<-P%CqG8<k|Bac}01}dDmNWWPWVEH9sNWmY<
+lPl%Je$&v)b(<rn9d<d^1`<(KDI<X7fb<%<IM0*?aE0&{^^fu+Ewz^@>vAgmy~AhIB~z*>+{U@J&0NG
+eD!uopNAiVBJgN(xE~$_mO0DhetKstT$LM4@}3N1<n-xzMZ7Qs`6YR~S?nRv2DL1u}`%(4T~~#I)ozM
+_O@OX<B(&Wm<Kbd%9=3SGrGnP<nWJY<fa^VtR7ABfU7iG`&2%GQB$8J;O7@E5j!vC?h;0HX|V;F(Wy{
+kx`scno*unnNgkLp6QwCmFbfilo_5Go0*WAn3<gE$Slq*%`DHX%&g9I&+^Rj%JRty$_mel%}U5h%u3F
+3WEE$XW|e1EW>sgoJ3Jj;4j)I5Bis?|NN^-Nk`X)?J4zkpj!H+h!#&$G+bi2AJ19FmJ2pEZJ25*s+mT
+(IU7B5<U71~-?VjVA<CWu+6O<F46AP_Kgho&wN}&stIn_>0@PQVD=f>tH<R<1O=Q?tWA>VSywmR1xQu
+TsFgYv@jV)GL667!NF+hWMI95SuWbB8p&Aju#|F%}X`g!CMcTq&ehnO~jn4taS&RzZ+cEM$}j`8Xh(Q
+plweGI57IydaAp$RV~cp)j#9xzJHqTv%FIURYUJP1$&uL?VE@-P7)6_pt}r!|k#51bd=A+3v6x+e_``
+_DXxT-95!K#Vf@pB`764B{n4?B{3yA#gS41{i#s8;{m;~Kxe|BFIMPE67-}9I#LGxsDf^IKrbxNiLk=
+RLTjO|Fsaa9SX5Y2SXNk3SVcO_phJDE(8F%FTkL-JFngrkYPZ>wFnunvm)Ohf74|B-NbyK9r&v<_Qo>
+RqQ>-brl%y1UN>NHlN?A%pN>z$T^++|RT2lQ|!%`ztt*N%uq*QxqQ7U~`1$>uC^ML2Fr1`;f{onUnR`
+{tT_^2Xys4{q`svME)k!yx;^2-g&jm)*?+H#X}?YTv{CGa>E@HRX^nrkKHC|i_^KddGZ1dxbctW0%>&
+kstAg%uaUic4U@B0UVY5ee(C!ai)UkR)XzMX-_**hv{Ir6T+P%c%9=^e3hN2T)4`1QY-O00;maO7>P<
+Wdj+L%m4rYrU3vO0001RX>c!Jc4cm4Z*nhWX>)XJX<{#QHZ(3}cxB|hd3Y36);L_fB~2EpSsKD7tpo%
+j8YV7@4Vog|QY{@p0c8{v4MtSdOsHlV5fdvtljhnE&Ww(;>bSh4vv02iP{;yVSOY2sP>iBbO#uePECf
+>DIp<b)!s5*P{QmuTNO#p;&%O8Dv)yxU7v8&8unB@-hd;v*germm%NPFpzfSn;KYBxd;otpsURh-c?!
+0o&;zyTyN=l!4r1ZfjJVg&a`Q%fI=b?u^rJ*N1k3Q+~&7AFd;;BUsUz?tul4-W_#@U6-j{ds;*!Z9F(
+aU3x!1uYNx5n1f_nTv1r0=z3Pr~=f!@nK-1(g-YR#EzEX8E6+-#?@8yB;lCjO~3F?6drWu;@ogf+hXr
+L-DjW;VL23nt~64@K2t$Y8rgF_>@=#^Vup04*U>$zXg|-Ch@0lT46r(%j1>eUzfgL@F;wFtworE53gB
+-Gqd4)twqRB?F+G0SONfK+bqJ!|GF}L|5=1;>v!i~t313yf$u9%ngHS0?H88u2*Sc^OBX$;JSYghT;8
+T|Gkl%7uv|X;zm^vhe3HOtY%q3Wxwu^QwI#eDjS<Ewq`~*JOUmV6Te`Hg2)n{Lfw>Xp!1o=OEBEk{r=
+Z{*L}r1nh4A_%<)(f2O#J`zU$`msM38+Fh|G2sMhY?tBQrd5`El7P2r_g0A;%)fIa}mNMP@dn1lhI?I
+In?dL543n&5)zP%xpR0%k*gbCklclyP-_f2We4xp&WI$rdb3{93TkmaUBfz+OGv+N8OGc-_fU?`poIm
+r~N<n`Tk?j=ZAwY?DNmq=j@S*K1Z5;%8~h*PC24vy6%zH;~wVt7a*I=&dTgm&cPsS3Pz`$6E`&nSd;e
+B5bU;54p%Fqn1fNdU6R)l5PkatMol0K3j6ZT>CG}zGIM2CC$ss`zq-ZqKwWP?8FFM*rf04+N17|$E!`
+ut<Irz@ki~*g$JGENz?wZ9zY25xIbQ}N59ewnq990YN4OgD(x8a=^BS$W$1r3DWnhffoV}WFBF<7_uG
+W1ee+U+}NzqN`pjg<DMERUQr<#4NjhcvKz-p^9Et~8XZ202<+v#KVntKFHC)+8rX6*>I-hx9N4Un{AF
+M}~-ERa9B$OvSemu=m#AH!5`1oB{K+qFLp<o!aYKrFh$P`|CW-?t|4etoPiz&?g~)BZ3V%kRQQS3qwt
+J{a8{sW5UFCu<R3s?m<02PmL-nSCHtA-&N4=O5HP*30Sv2($$-H8c$7Z=>nRskZr#%UPY!=VY_bAgd4
+1Ahn#~G?CCzI`0U3`4RLYiR=7AvDYyWl0%L{_LW|Ytwn!9^S2kq@gcOVeK!8$7C#>rZ*gNvU(hE*qjy
+B-XBmawPfLf3>l{^(T`c9<l$64(&meK>Y28-H4%3qTISX-herA4vZ3(dZvIA@>JU%T4*kS1b>3(T}G=
+Bl0D#xL@cO#-^=fEVKir#ZAV$(wH^>mn*=%nP?1cNe3T911JK$h9QoF*(YUXCou^ce2zkHg-s7Aq=XI
+yd81(4PUsy8?la&dFSi+i0G4-2_}4d}Z*;TC|g}gTn_ychS3^$(s+dOPl{l$L2%Bb8s(Y;>P=+A8fpn
+u<-z}P`&P;PN^O3HG~@W$gGaf<Pp{Kn60o^vLCpgk5xTBUhT3fDQcH}*<`gVY56rWOD~>@18h<};)WX
+{@SF~?m%_KSel4`Rp&xDS?*j}~)Qh@hJhqiT8@IO1_8ac^2|i_v+G!0r+UsngVZ0>U?qk)g88_>FvN3
+jCpC&x_VH>qTE@=MmG24=(>6&2}+Mp3sU1puy^TV+56=|$do8ZCJ7TqqZ+hL`4YsU%QFCYm!WCrAH9#
+DnFE;&*Hgkgn;lLhQT8|cCsjoOb4+>4!>72l(Bwicp<7VVTs2@ADFl%UC~VJHJ-Z?{-69blKeonpl;_
+@H)E`e$Orb(G#BR*a+cPD*bOD~3{fomkNy9@e)*dxram$Kdf>cnUJja4*5PGxXMKxbHuPu(fGViX6sc
+urag;MH9eJ#v|^v2fXJMN5K1O$d$9#Z1YB_SIABVyyr0I6UzCPaz;|l5!u_LIArf3$~i+h)?-MPptTc
+)q7SMbhc76163A|QVfchHGN7I}lp(Mi4R?D?5E7j=!AoKIODu4X3hV&<<OO)2Z^sZT+m(^B+5-iEsu=
+En^8&o<AICU?=F4nJri^5LmdsXV&cg-d`?8L&VPgG=uFKK4JD~^QU2Q4EyOv*L@~&`eKioH;=j_dCGT
+bigs|ohVx+G3JB93qn$UD%FQ=Pb^>C501DZ{Ldh~JwLzX9XRAl1jVvyX#-kg)0A)(ELn^PphJ5uMqoT
+dCO<(5&_c-qJNtr#$_xAc~6Ah&SGd;U2Hy!nq%X;;@#>phC`GBm@hAu`bqrT8z2yX1HfU!4Cg#gd{--
+J!8)DY|TUyzz4(a*Gx14j5XXhX(o+t(N>&8TJ9dp`xr<-?baURsn_w;a~+tvT?_J5iKiZcRB^)-zkz)
+c`nw!?rb>=108Z$5Xodx_tO<!6uzguZdJ|wD;!D1)F3QXm@H1P0kMS_g4ImnD)-N3;8a2akzj{<K3(3
+)FD>6eOY(NTf_WB}0q-w!T&w7-94fn*OIB!%8fZO4)0KRU?Y0~z#Bh>B>Zbx|_eG7a69v%^dV)dEV?W
+Ky$=Dsb5_bQLeMK=SNc^#(Gu*=?>(tCk|{7*NIR2gd5b_~I0@6QNEGkaje!RA;xS!UhH=2WksWWXnGR
+u%R~8qAzr(`D0M8HeE4Ic2rM2^C5|LXM<DL)z=q?%d|}040F)Du81&P6ZV~Se^nLwb^iQIfDJAzjW3x
+Ht=crBc-@!IB3>OXjJJA8V=Tnm$m@Tc(u9>mOYIpeH!45W0v6_$m?hE`q@w)h&-hK^D7{oartLSri+B
+2dtjg3%_-?IsC0z`C$GzJkJXTLd?{^m5>+M%#3!zs;VcHKpH-}OU8Rhb*gkFjAX>v=Q1=Tvf-u8rxV5
+A4I-wnM_@I&+upN?FM{Ku1kTpR;sVa>c-mMk&i*xQhkRGlMvIdl^R^Y~sF3%9x^~Wv;U}wQWrq~D#+j
+yO?pbpf~0$5zFx0=P%u=pqrn<leE#lF08$}n+VDyBPldI~I=6*9(zj+z<A2h#p^7W*P&FcZZiS7%%%`
+lp?U1M~(v3~9qhu)m7cTdxXDC|12!@j~z0Ni0N=-o@;AOKO7^!GjWqY4oBw`iGs=rKebZ_KK^NVZ9A~
+X(s}N4Lt!30faa%nsYw~a~L+Ri;yC&gLUSKY1o^%&Q=Tq{0cVc1!S|HQ%+7a=RZ)F;Cm&23@b8vW#Q=
+Cxm`pzUrQ#sdF$12y16z9QS_<9Km@OXAr$B3DnRIZ^ki|}Zdt9ii|h6vANm#S-kf${wAhJA&@ULBG|y
+rY^fAHcVyiw#Vjm*N&kP`t`v=smRxbEK*~2jQs_8gIC`}@DzWp%vGxZHfWX%e+b;B$0sHeiii|`<;$6
+#8cC7@RpOOfmEu6L}s(IU*!2EnWW$&0#=+4>5Eo^KGZRBT*kJt#1ETb2$j%S%_pvb+=}MK)?=Z)536-
+3I#r>W7g6Znkl5aQL)g<X7H=ByLt#caYV=NY=;BBc<96bZtDfin@>Ce)9{Eg?Evv@DBu_s1qA_9U3T(
+D63}4AotHI&V%Jp0L5VuKh&Od(RB1fTq(}GDWm~zjiC{|X5+fXBB+fEPP2EbE56_ju;9tG;85dAs_{F
+s#`pTxNWV-Cq#5~0$AB2*YoB$SbM~^$#PwE^|4*T~u_`m4?JA`C_=7ngA3(-NLgi?BsulSdXcZr7YaO
+(~RsnZA;YXqnT?iAi0cS^BI9iA&814pG+UV>-Adk<<ydpF)0Nl+Jz4xScpA{z$I(pJVZ~%b^K88I$cn
+T-*Cb_6ij=r>zSU|K4kgYIk_ZjYI4<l=M3lnmx18S2IVCO+&jLxzapZ;5b8FI&-U{r$CCVD>y@3PSpw
+AI8@dM-+V*Fbc>Ga0$z1}jl7-D;v!XTJDSJy3{UZ7@4PP;-MYhuOhsy2XYx33k^9FtI@t%7c+bpbzJz
+@I8MgFjA7MwWoo>?zr5);$m@h1?m5?H@#*IC_@9}ni^MeM~z{Gtl!khHBGMA53Vw0;a*Zc7gZ7&d-Jn
+au08v6PDpGk2<zfY)vzc-wIonI8-yXK#%*@tM8(PlB*9Q-FO^X~ffpc*6ZzXN?fUVYo&#pj!u_1C)lR
+@RGEi;V3?;7(U8VhPLcCejj!oUdqfLR{)~?N|)<=WN?#Fc`t<y3V3v}YV-kXGv4M?cwA%R+m+6T&X5A
+^B`0S36Z4W<2XQ^>6qKwlfNt4M~{4fx0EKo_biqfW_0Kzeh;hFr@IeJ5)JpazR;5qiI3Z>=&wR%>7%S
+a2VF4GAH;%xda#s_VEuFbif?b_OH)8NrC`nSHmZZ*+l}6Q4`Bwqbl?E|&rvYNMggzyjt(eg-l{<}9rh
+@Nq4!{Lc`ImLS_j8sQwI$-A|2pmj1(nm>lQxNV|Y(hpk*=rt-R_mkd(+SW}p7eQ7741dl|7LboYPCi6
+?ZK!q~UnIkQ7o-3Q{`hK`9$P|h;`0bHRz8_y^0n?85=?qT9waDk?fBKC9V)5X7w`njmmhJWu5@7=unP
+531{B;IdR7Y;AjK<i$!u*kPJd*O%qpwsX@*nwx=&<T1Z4;-YecT?_#5z%kW*VMVLlL8$L~P@k@E_i$_
+SYixL73>ORvOY{j?wCQrk|<YNr;gp}{JZvDO!4Sb*uctlx;wTKd9xSzQh-J0Q&jKsTd3A+armsC;ijK
+mntMYp2E~7V?jv4OfBW{A}z`l)YE^9K~+H!9Cj99;AdI?ECYI28V8yvpU3eBX22IyQR_;_`G+yy;!aD
+AaPYYDXEi^sy!qC7(12xVvvWt#oiXBUcVlM6{No&ZG=w{fD6!zxUNM@^`SsnZ;jVV!CDTiwF3ybxUMd
+%#+M6{HHx6Y%xv}dI49>xg-2FzZX=-Bi(y{!K|A7ld=6})y+O7=&vDBQFvH7X4wN67;~(2Q{xoy^q_)
+%egINa(#C2(dK<=Yab<wD5JixUF7OQ6|?JT9$dID;#HDEL%%uNXMHf4*ru2x*vl+_4`i%o*Epv}b%O6
+^~0_roo&cC{{F#my7pCRy}%0lGhYJsBKA9&OO=AOv24fW9*wo(z2Yx`2e>{Od^=#BK4`K~jtnyRXS}9
+K9K^us;%;D{m(rn6Cdx>&e6+Bc;;5Nj!p(qz}}(1CV$qk%*fW%>`smjN1&Njt7TZggU+_nB(X7S%i&)
+xonzTg$8cj0g8OEPA+QPfI@V{@dGHLjW0x`cKBxy7YSuXX90e1kBpjwnW;Q;yqTF?H5@7IGEySH83u`
+w!4_Gq%?8Tll#T5mD=<elXa@QbBq+d}po~8%+XAdH7<K<%wt&K3E!T89)Xzr;n7vkhylGyL4YmZ-vj#
+}z>RC|o3t=B8HCSOijDS&%tp|*z(EHFHZ7JeYkIWK;vZ?cOU`-T<)>TNe{TwP<u!OM(L2Brw4Im202&
+#8~=`AoxJ4WJj%ku9bJFNQCAL-vjIctyHaZIi`3q)X>Tob!B8XVx#GVX$Hu;K9x(d;@pBRg&g`gA|=x
+_BQ4)ULtL3{q=c+L1dis&RXw#-FeTu9JIx27<7y^acQDDuL6ue1f>)2T&_(TOXJ@Viy4v`|&K?hc(&I
++#+ZWyG<82lxB#~ckD6D#14(I(|KRGpVD#%D6lp)umwVA0v#=6P^+oikw4coDCNu1C1@dE0Dqxe(4+H
+%k%xg1I1Y?JA$zMF@uShE5NXwElj9B1?!2m(<MjiLDfSc!QxD8R0inJ$2~>d`{Xl^E1tt%MeK$t};Rj
+@p4R{jdgWWYAg%gjqYc>c-MXi8aw`x6CLX#7Dlc%pl_85c75m0$R;+0OsD;bGbG4c`8m2yI@ATN9?pe
+1NWz<XxtAnaND7dD0ZKx_e^QMh{bBWSpo)+%?LlGRRY>AV?0KwWZq7i#s(C(BVu1kD>%;Hox*{=xdSw
+rSM>ot)K*vT-&D-pYiA<Q+R;0}Rskb(19nnUmNceEKOaOM^?dp~Mz8LN0CcmGR9QyAClKX2P5Tm=JRo
+7NH$s70g28T|@*1k}9_k$-=h5$e8ssE#^r~iX5HUR-T7_g&f*5pa!ByR|reAQ+tGza#%qIE68948LVL
+RVHet>7S#3HCqc3X;&s4eAI;iEXa%{ihs%cA(es8;wkk7MxEvt|$_<1DHg@dKWbXTf&SBK!xq)cG_&}
+tfEua=@g7!C&tfRT+8H#7_-S;H)IFc4(L3Rr5CyN2I3t3ko3WlfU$ehd)#Mj}4fG+OBaC_)#?fB>f6L
+>2rPWD!izG#}i(I_ml_cBS;f)(ly>kL9qpyN!?+qi53+3#FIR-dyMO(3nax!DN{zR{;(=kk{V?2~}_x
+6eAJXQYuLrYlK4HZxOClE}z|HlKxZ_@G!Z53<ct(gtKo%KgEj<xYRNU700Tq9G~ZJ?Rsted}ktg5D<a
+$H&k#$3S4;gEP8V`(yz$H(|L`V)a3w-;3oeO|~RsUWpGr76xr?a#myP_f!q?{j4V7)k+up(Yg)8@E%*
+1DzREWJ1upb(t+S^^|5aQ9c{j>(|QU%dXM?V>8GK2#OSARRntKg^_$%V*glZOyz_gF{b=lc9H?@Z7F%
+X;>)V^NdGb603njg)rAnF*VEzH49yAh~5!}OzaVeq9iP&evLSe$w6BGUvAhtH{3S33njW<9Mb!LV~&i
+WMQAC$9>GqLeJ&7~g;u!h+19@IrHv;zbq3q4$u2(VK`ht3As=ZGu|5n1j-tiaU?T_qzQNeQyroW0sNc
+cSbtDuF>ou+{bJaC3d$Wf*G-H$n0(1U&<fY<6gOoacKQO5Af69~*QlN4b3Dv@*&svx009nR!7Ws6!bB
+lq}dwg}~oft*mY{w0wgEiQI(jcZu9i;@^0b+}r!e?ipIo$ONqGY$UtKKI6<jp$7${i!v8#S0eoF(=+n
+L@Q+Nh%|r`dv59JDk1|#+Y9_AH<p7O0OR@;+7o+9J_s$F01~&pb>~|$_=mGE`T#42-P(d9@P^f)c?z5
+q>*vfEh#SMZ2C?F=cMot~DrB$~}xn;^A?XF%}QxVo(25i`g2uc1Zq+Eq;hpAG`!^Ah{_o@`%j51Y<(@
+4Tlr5KO<7=`6xm`f+|)GBl>5!W3k_BMu4Ve(fY$%MD1AlW;FOi=gNHHqu&vObOsa6zDG`6#Yt`&f<Pp
+1BuIH85iiaUEoc>uSVx+sD+zg>ssIQry;zNQ|Sv%Jn51lSY~cL~<nkBj~EGSErqes~7!qrmLHq@f~E2
+`upI78Q+eYYbQI+_N!e6$R=}(1vE65kfmJ7*(+8396P&vCO_FLk)wW>94&OA#a<?b)^OMC!M*>MldK7
+I@bnKSQ~T$3t_|H}8nGE#O3?m}J20CL=<pPp%+t^!+9(h=LAWi2n)*nYg`Eg*B+Ofmzr9U3L~k&}65v
+P*@cc5vedQjUMYPw8d$_4zHr(f$Nu+cEmrKL*qhwgpl83Q{C=OoE*`e+K8oA1EGI4eS?7r~<wlo`$Ea
+yMamlt`67o{s>(2#tnnedqO#cj<bblx|{a`C|!uA4;1ZySc%g=#4(TeO8JD7ydJY^KRD1F(1?1O2R-%
+Uc)Om&qW(V$k#1t1Pfq`vbV;PaE$0n$c{wJ<fx7;#6N5gh>W62WpVfeDQ$~o=F0Dc$!J>1@{|hJVBa(
+3*<4+An-&-Ti#0)a18#OgN3X)2<(qEWyi1t5^jQmz+hiA6}>MJOK%7;Cw@=TKLVAn*q=8{$?&6{z~`+
+7B?8nNpSaFi?1#3FgGe+S4QdHP!cN%2de+7DESIYnqI&Q&EVNrkoAWSy2QCtbqy$7?9p4oH@odr*4>P
+pyWh92ABYg*2b}tHu&z*ypr=2MCJ!4mkoC53!w!;^lX3@46A&m%Euh`3GXLQsej)qdQmO5E|Y&4$Zdx
+1<nFvTLUud^O^wb$B|DJb#*GzoR08i`c9&*>}!;srXoo>G>Z60#awWzZwMw$f8Tqeif;F<5A!V(*Gm+
+Vex>P{!_siEpp9h!uZBmIx4rl5<YPUWb>gr(r7{FJxzIPdfuOJq}6zYV-_dZ!3KK#5}3p=YZZ;#YbV)
+954!ReP|4s4|dD8#yAiS1Vl~gsg8mSbdb^u&;eo})YJAnMBKP?AIubKY9NseXfMccDydi)b`|SXZ0zY
+w&=(eXEyC^4JN0Z=pxvyFsPBgVb{e@OZkG%89#mgoI4U2KSg@PV(}L;4wW`y|C}D#q17w^tPW=X+$Tn
+tbo|oBQs1b#mRy^WO{~74HOCOMny5#7jH*UuL+@T&FEyFCzj~l=leBXkoI3?K#dDW>8i59^U8Vd}4h|
+#2^g3dRL4h;1)Iz`kS=DA|(4kQ&=Gcqz6Si=x)s~cg*Gf?dSJgOd~<EDnZ1RZV^Jow{kavyp?paPsf@
+TTi|0OzA}5h#n3y7LguZuKz0X#kuD5zg~MyD!6OQTzaIhN0Y|PW@MZ1o!Gb;EuQqxTyNyyPW_&4?|6}
+83gg5UWmtE4&t~@PreR4usl{?N;@z(UQq|pXT@Z1dNzVSK`z<@{5+pPuSISTn*uq$%<MJoJ{Lfq1dlF
+#q=x=7*wWfWOIiS#83I7|kITqjd~X-+53<97nsXpj+^{bfgbJ7;n4KBy`Xgi<QCH=p38CwwGy7?uO#>
+d!--iR=$Z>6WO+@>;2vgC~GGgzTvxYAxZG8&%{x1oz-%!LEEbR!C9p*CJW!nJd8~WHd(AJNVm&{R`){
+#bhNABfD49&P)zyk8OAt#C3b5PgHNYE<4h+T${9r5R!h~A$Dm|Y-oTM5vccah#~*M{LJatzpYM{lwSP
+&-pK^2I2#pw8NHI~&<XD#0m%_mYkKQg#Tb+?7IYg7o$Rr$r3^iD(K;#uPr}Y6+(Y6Rwn_GvbqTx`_Zt
+^+gw3e1M?ib(>LOPSOkcAi{@Fgcf0W!~H-LZyHEFz25`xx{M>jLbujKmK@0ef_W_fJ|hbNt$Kr9yFq)
+MT`PC!LG}eKqn&7{c5Beq${K1~9X?wts-zx$FzD9vuq_z)$r~*~Y&0OU&wE4+BU>^WVo1?9%!B9X?Tw
+mtGe2U=Mt-?eF8UaHt%6#Ch`m{Lya-RAX{I&H<u!a_YL*VK&v!zV?E3tEDeA&B*cR3Es0Dpr%~1y`#B
+$N@izH7V?)5;}Eg&}DcOEr*(bwZ+N3rmFbO_a+xD^GjEnF2Ky$W!qgshFGKgNZ4!2L1E$8HvK<JKU`1
+gAl8YVm<Oi|R|499ht;{n<~NCGfQS2P8=3&`!?N{vdEq5(j#V9BS}u(+C$rt?<_zC<kU|+`6n^gTDne
+MLoG7YR`=LTY{`m4l;i}9=L-{EEyl6C81rJ56mxM6t=7wBr|_=Wd?pC*NFI=VNs%Un?aIzrhp6jS7Ii
+XwO3~7E;DnXnP~^rMa)~!Qamj(zqm*IZC$jWhrC5V8iUnX3KH4VB$1g8WS2RECv^+<Mu5cvD7ha1X$>
+e2$95E3+{oyMp=uI7L|RJh7&nlL6}!0fB35igyNtJa*(~iU7s|W0Szyb~1O=F7pxm?~2vQa-{CIpR!G
+jo*qwYe1p|dAcq8-O0jNGfl@bft7heWi3#8B1O_L56cx@`eU$~%3`W42d!nfB0>2-3`w2YRs8;i#g*Y
+OdvNhpyLtB%*@v(I<whS5AO}*I}_y+EZd&ZPin?hs4C%k7%d0zu36l_l$^Sz_?&Io=bz;FM4`qz{~JV
+CS{P~0F3!<HRRIT`p0`jUi_Ha`gP8U2$WGfEunteGW4Q2Z)-!A{6BdpxZaoHuQ<3eMN$u+^F{8<(1%O
+ybrxkXd^(l>lDOe;N@;RKK_-e9Sg8wGyN@-HHQ>&B32pMlm$pXz-^Dn4b)a4$LSiil@P$WEHzfeq+Rk
+uEVp8~^lA?B76o=Yv4SlLDJO*-wkJX`^y<0np!bJ-{wI1U}t@)SfyN^v?oqG56WThE((<mhWr^E`CQ0
+`zTN6s5H5E7M;HsUc-BQl3t1nuL+NLp9+(~{^RbPv?+M$0PzHUqcbZFmN_^AYn5FcnQ6IokX9?rm5$3
+{r~KDJ!RjM6MlZ;v;0ROF}0b9cYzJj`~(u<K}`34D;V<%P5Q=h^|k@x%#sgnax2Mez=`a<sj{NTCb7y
+O%S~FWpd;Sv|icd$Y@pvl!w~|_M!RWV>$}bkPOd6mj|O5x7<Pt9uuQ=R9o{Uo<Sy|A%C#;Vp`&`;YVq
+>A@$*fY%97+LDe8XHW)%(1tV8;2vcsRgH1PCPWmV}#av4KZZnB#C->*<4YDSj+Wx59^g}8#3ijIo&E9
+96@0}(bAWc1x)hLPU1R!H}OF*r*7NbTl8{0xLJnVB7`=M@Qs%h%gYeBSX=%Zh%yA4wx8LYjYnn23?po
+7!~{kC=~Lsf3p7T-u4f^}-8i}}_#1nMhH!fXrSj02j{fgsO7i-D4&*$?A3E*dYWMHvYp<-$GEN5+QAe
+KyBnZFnyn=&Jy9dK|!!uOz7tW(azlcH2=?;=aL%OWfNbN#EB;;@;6$hc4=Zee)qX8v)_}zRVon>ny^0
+Tyxa`N|9etg{PmP6mM5(RD1qHi!xMu3yQDj-mNX#D_GZCr(6N;Jde+;(Qr3ZbB`p${Zcg<qOE|LyS3^
+wh+>~{H#1O#Kmd%ow_l5UFl}2Q$b!@AeZ!mrY$_C}o=oAiE3qpQ`a%Xyk!c7+xl--!0g8M@3YSdV`^6
+<was&V|_hIj-0Q9nS0Xn|1Z%}^-M#tU-NvKVLCIRxn8F5oE*QtJPQEr01Z-kMo#ng6RE{I8~kkmjrjN
+V^+Inh3>4rKiETUv+_+Hd=D078iZ+O=(ch&{@l^B=gM+c1a}Wmgs6i_SofBcQk|_MC%yu3Y4BZ$_7%^
+u3TK+iJ>lF?1+&czvoBi^>_HmYjoX6`EfAFYA~03I;`qFV#Vl`P!>PXx^_<rz!(2f>m*7|2s(#)?@sR
+HX|#3y7=PN@Ns5rylB8Ix(174M2_Z36fMT0u_ZuSG<_1`bISS=bXGYLMa~~@CK{O!D5LFuoSu&lfamR
+xnPu^yP<sYrHL4yllW1NZn`nBzY1-993X@^S%%vCt$4`Oc1|yE24Mn_gEAYkAA44kq%TI9ykS7DB#tO
+$LKm!JR=tEhj3NpSBazgUwkg`MTfX}sjgUQ_1!hKZO67IkqTh>GN7Q`jF{CFifdZeEifaauUH<4YgWu
+S#*(|L3nIR_;}bT5Cjii@nUqClzyMUoqQnG~jkj#M(2X3-~sv+t<ml>xjRPY^v9gTUG6q4jMc5Wk_&m
+VTAYDl!Rxh+`4<88u(kY9RcMQ&^ojZYO9Q8(sKTk-3(ae-APn96yD`es-a{!SOsi@xAHzzQDT$S=KSv
+d@eEEYu?Ah+jCHkufXX$xnJ62@6!zYX)~_uTzFBZ?sJh9g_qlQCuUT<kN)u7Qf9cH#5(0$5Lloq6k~I
+rGZ1+^BM@2Y!FZd#XE*tUY^Af1O=c444l8pDvpNdd=RtN%X0f-6#qbH_Getj;1Cbexg^>afZR@=^iE2
+5rY8%Y|{Dw4E&>8f$iO-?QkrkZ7XZ1Iv9N7i2;-~oJwJ5`op9V8QLj5RUYcQJ8HWGon)k^s@LebJET0
+<aHO?~bfJpH`_M!XW9w0}R&o%c5I$=hkTAA)2y!_Ezc)Yfk8$s~M)rDe12!J<N%((#xuK4AMehzxM2=
+`W|e2UGSGdKcCMmv`Yv)*(sC;}*KVqZrI2PtFMtk_)pM-u5WooV|HNm)#&oXF8b#W2-JrW)}EbmS)t-
+YK_Y~bZLhE6|05GV8I3#@TDZSq#;eW`9Q{od6U^8?@deR%0``BbJ#B1K4S%EV1`Qb_^d6R47#1-@OiV
+8$@t)X{G2jg^$H+_11_!r;rbsI2_2q&FtdfW2FYlSgI@Z-RoqBUp(Geb@;H1i?HfmOp=~4sg)L9twa;
+cZ{BV?oy!TnmA6?D;xekEV<Y&A5Y@eTeT5nD`v3iwuah;9Nz1sPplC5@@VsyoF;6HAAf(h<AMze{w_s
+td?Y^8LG^+>60x^r_sJkr=@#r7oD%w0&uiaO-Vpju!gp}4M5?VA1UO64&rYqwaj2fK=;D$|W7<rX!Tp
+<J!TQj}q8mp$~nAN3T}*8Hql-R+9Kh1EBFog72#%WrSU7sC-^2>G!!RH{W^1<BUXGWBSWdgPqC+bV82
+nXH#UL!pPD5h>Nsi`3X0Wu_YIuS|h1Ct}}2)vhElJRESOqd@@H8M+aA>96PcVYRdTtWn(1-e1qcw^8(
+VvcEpcESUx+MO_p(98Fv5kk~%m4henSXT`7`n)Rc_VH1iw_THI>J+O5n=)YAq!u=1lU;ltCis2VY=cr
+5STew*DP8Gw;c}}7M_w&?%L*O#d{hy$cO{<v#U<}mnfFdiYh|?_M?JeShA_Md+^pB(>$!3uZDk6qccx
+U~gnCk*ie0e!ym`8I3@u+hLs3fpc(IvkO&Bd>l@Nw*iB8Edsg$)hlFcQj$_(%F8A!jfWf{wPrmka*Jo
+7(>pRQ?n?D9*kdew%tkcFw`*42zbNO;#Q>C3vUapKB4s=y8O<r~}CEwd2vJWJ;T$6wA!s)}EiChURwU
+X9%E$hJw-Q=haTva#wVwOS50ck5vCoV|Rax9?ER+X^@)seTq`ksKZyI_lx}-Yy*$in<2}42rY#e546f
+?h^>S{u1C9yHi+V^8Y!a9@keYblGcgx=UnvuFzrRP>qr8)LT2edrry%JwBi=(YdQ9%W_AmDCN%IU&+W
+vzhI`C9<kF+&5I7^dQH(`3XjFL-jS7wOAm6&+V~oHB-5DdfxTra=72-!SrmWBTauD#Zi(FjU9$z%y=}
+l3xjOu``S?!!udO9kdP&)@KPpV2sE>m9PgJD*YV%r6Z>21|@@+%Va)!0q`e(MN2<_h%##{2PEj_B1cZ
+kxpX(S7na#`6bLzUlk4U+W&;Tjm#uGN4_2F&xRD``NSnD9s*>&T=6x14vTDnsD0tPyVmv$6L_9H>bJ~
+Biul>4<ZlIhX0*7Ddw3iKoxYGBl#pUCo{tb<y?V=8js^=!*r)vW^Hd_-hLlEU6tuFMPwL~e3-P76Hjn
+7`vtAX0o+&B*|N8VPDux8?fWTZA*L)R;%hikoED*@fLs<rMIbl-DxKWF1L~A>LMV&;8?@KQ323o9hm)
+2eM+-dULm9DEp&}6}$cz*?^<e>)b`DJlP@$o~iC=PL29!!IpOIl5U<StZQG!=-jfIXMb^!8zkCvxnS_
+V~R2b7UA+ol~IF9?8p#z~O0i!$SA=ZgEreur(!Bf&n(rwt!qT|PD@z%+Im*pZSJP*=EwkVCQz&<mik@
+ZQyVphXr6q`QA)?9!y$VX*2}t9q*ua;x5np~35KMfOPf+8Ff6YkzhJvQ`_0OI&j7=ZO;((q;Pkw?zM(
+={ZLy!>v3x`Q>)OJQ;4baR-+Dh!88}$lNkHS_mpib0Is0J_NG>I}{&lg|GP}BqO?z#D@Z`HsB+}&_02
+-L5r3n{wg$fT%&D=1e23i9LBtZzT5?GE2%Q`zox!MzB_29M9nJ5{AK7evE47O8!xfbK0wKQKRYY2y}`
+)bzZZjWAy$0R520RAMN~*ykH#Wj^!tsddj})_vT(atiLqudom-2gth!=v&2l%!J8t1=pn^GD)z3xUCb
+4aDQLS9mBuCNZz)=q+#7%>(HD~S6?-I5RdH4umB}S82F{U5?-etZ&ZGIP<-^0!C&LsK{PcT7PzX+i8)
+`&lG0-Rz+CORT?N@7JlIYShP6*4{e#fpE^!*sFYPxLTbtf(ZpWS&^@Bp&;B-V2<&^FguVWy&uSD~7=X
+9TWywQb4VDqN@w~nk!zJ&2u8b{NCnCI7#A$FH@Ihh?@mqTId`k{4%R{Pp6M{#&C=J#Lc-l)AM2x;tQi
+DVITugoNu4Rc&5EU&`6(<I<{c6e8}ccJq#L&&j_$9$l+D=btd}uR~!~ANR|#Cgk_UO->A>g^PhbaHdc
+@G<qlD<6yNPHN9V59x}Ko60a%-C)Ju5uSnu;1s}7(|jiC1B&B-hg!^?o(OYK|o#R|Wj55*~}Y4BK#!N
+YW@0}pa63v>Gb36oEg5+5=FSPXc&2%uDMsw9=gzt&edC-c!@Q5jO6ARxOLNL<*gef+oy;mZEdMhVdkd
+vV0yEJqhKOVn{}Hq1bSzY?E|{Wg95BRJdYj(jS@PK6CIau=+fv^fa}1aSIdFVR{)EIvOJIq4&W9jmvm
+f0Uz1g^d>XNwJ~^64pOurv8pFp+vb~?OZBWtO8MGeaOt(hvioAmv9~AM5Vv!eprC`z;P9dEaa!4ry09
+Jo^dHopug6z5o(jO>ST@yl~5H!8*qw`izFW5ZkI?~m)^&1=CAm2<uWN6@D!`ncSi5ri>@#WaY`T3izH
+IRvBVu_;nc76K!DwnKo0H6$IJ;8D~@&pA&B1V!KH8%M{d%sk(=U^99v`KlPJ-#5^oLt{;QDn`@*eCze
+0}hdLE)fT4@`;U{k}WBg7UZxlr7ETc<t}C<%PIDJ`k62%hbJc3Wp}!E_)vE1iLk796(|nh&M$R&9P(9
+X3`b^FZ@dN&T`z@}8H(ndbpT74#8~{&qLwdPmEMrZL-KE@Zab*d1<q)`2u^G#<}X2Y|YCoC>n)=rqtS
+@>W}I^_76|+w~90b{q|33y2r64n`fUgFpP0SaI$g%A{2w^a+YH*CtlzNU)9VuuUp$u|x0@8c^)>#zK;
+bhrh>b0K8q&<~L{oXLezelGj*$b$P=Agt2J1R)j%B5&z%u=75S4@*`_u9X{ZIK2+~uLnnchR&F5QF_%
+mdH=UP@+M!mp;r{F|sJg=rK~El5Sm|TCO*fwEAV$f3fcWh(0PoM0A1y=BNB9B7hCrh}17*SAQ3G?)bZ
+9ga=F=F4n}vo_p_P3L5go|S^@g0ZIH+}^+z)t!vj@0@i2EVn60D>}5v#JWO~A*6u`hX|RT)&}i6=%^e
+2$bt?*~JcDcJ|j%nt(FT;b2^@MU#CjkM4}^3!6Cg={MZ4z^80ni#4wy|)14Ap?(X&^6fBN!>V=5%6gb
+xv9|lY|^`__CKc~N6mw+7y|BPtbR~t-4g3S%EPHmFmsVfePs4A@cjoL;WW2M3s<imOIkC!hb`jqCt1*
+3z;+&YQTwwS2y%S_eW|+)j7HN(6A0A%#~7$bV9xI#o{W<gZeMW~!m5nquzGr7O`4XNS9HUiC2jN&KQK
+|oPp2}C+8=g+kOxSE#egaEQn4&6=XYvnK$)d>E>;TGFCn6&WDuhUty&BZvvTs18WYjZDCIdRFVr8IH)
+f>8+AXyCU9l4uq#=i66xoa<saR5TZww8AuNBtosfwM_W1G<H4l;Ah%<m;K&xo<#LuM87VCW6aH~9K!;
+#I}hrxLFUz9M0b%7=N%Bajl6JpAQe3kO=Pm_@$PASBQN(b~Y^cg9JsrsgN6GIkJ;_9XTE#LxtZlS3Lb
+Z7|%X$RyC3rtUU~L7>$jnzk7yGrCG{rnG~&t=U=Z(ihuB@M444NSqM%X%HkcSggq3I3u!mv|vi?HMC{
+HLo}_7+Vw%Zn63(Z)g*77a*NtIM)}_QEWT=E)=%OOg9)9zHGHM+g+`tF9Bf(-z^6qoz(q*br@)I<zYz
+xEi_EP=KuhprK7Po4_5}`ugbaNkA`eX45|sA1{6=k~%tsPlcyha8_;Tlxj9B=Z>EDecCW-<odhd;BMD
+q2U%xniKH006P*V~%>*Qz(53{S!H*{C8I?)mSKIkS)lNGcNy_cTbElC*R<(4U(u7JliDv>vZnLa&&S?
+_78pNAH<N01pGtqP9D#*K6O~uvFAOIfddbkATq^$l~9+cne_z7;z^?h#0NQGoZf)SoG*DCrI>$JL_$(
+3r<p}K9!6n!(n*T_zt(UZ%0Y)pA9x_Q~x8rB=MI^&UG&Faf*H))EC$wL|(T0(B)Zsb}UkugL3p4mlU0
+m1j}FNi!4YBMi$tMzxk6Ko!b96MiiW1V;_yI3i#5l&^K~4Its&45mDFJ^C~SE@@s5^jLV(GUVN{F9DR
+EQcSbGa&ZuLK#Z`_H(m_tKfZdG5ul@sG%VXgh<P-}jBtWT3DlJAebn2}u{dSEn^X__(7CadAaJN1|eD
+@xUPkgu9=dE2nM9KmVRDF9iXfHvRy?=VN7cwdG!MY~7qB`^eyDg1eQ*o(LZOLZ0*?nv~x1xtj08z*~i
++VF2%rAJ9d}H$kD8}wigS1>Z>Muc88nVkG6)o|xx|}9Fanx>n<TAy>DA!zALn0qKvy$Zz;&~-OUQ*85
+7mWV4gd%6}7!}N_m)dO>rC(V;*BW2SVZA@RS`}AWKaaG==R90lj+3P)*OzmXyipUt*m+}ns8PQaar2H
+*Fb}Uv(R`2EIc&KTnu$*H=xGwZ^@mmfc`s_isKtr?pcGWiXo=}B`_2~bFI&d_WitY7DQtqL#|PNq1$B
+wDCXe<G#p`y)qY_V_1Y{m0t5wx#H^A7dSMaD$U$PzzE!utD&-zs!{D?E;9kuxc6r6@=KBCP?1<@etSV
+dQvpaZeDQE_Nv>v8uxUOs`9eoS?lqw<95<I`sFjlp~98o>|UozWQ{ZJsM(8%ms0l07CLL$J^fd9N0P#
+?`Tt&m+(3?g@=;a9nj>;M3y1{w+b^p(nHZhMwqtwflT%V1uLcT)d<eO6nh~-RDAs(aFNo;P}MMWBGP{
+V<LV9;5Bt%I#15Oudc7Y&ZA)*-ySh{3t|&Htp(7$e~@)zR58T`gFqM?VnqdJ(u>E@Elg&50GRrF*kN8
+SzcEL$?FiV8qbWx1a+Jo(4edN?q^NL|8!>wB5YS+~+i=f*lkdMH0(bBBfMn|)XC`i?#5+c!qc~C)ZPJ
+y1-mC4A`_p`Ri!wdpkDeF!G1a)-`I+OCNxAbZ%6ReJT=8Am;_X`Q&e{!a-ZTmTDoe2kY##=)c7(n~jU
++cC^no0`?TYn1&_J2f8L(}kJa&h@JoYBgel(Zcl@V$zT@j5Y#SSXX@G3h7O$@3Uh+k<{b|*#=Rt<o+$
+Zcu9NU>A5MecXX(bX=Xbn8(O12RWZ3wfhvbi;tdRi^jvM;8xljtA#-&J*x4Dq9D{uld6MJ~D@yQQt&Y
+fHg|F8Or3`?^~2>#CHdX?@AVL^YUS^!M`_3T4R%JA4*OOrWV?Ec$=3UM_1+CVWHh1oj40^p9Hdwhc?2
+zm4A&xLr9e|>eqJA^1n`3QjOiA;T!qTHu9lu<U`wtLkni@gXsofT{EJqCZ5@lL@Q?(iz627C6M(Y=yr
+e_rDyT%0+BTrck$tB&Ns_APs@)p%)T+e7yE#)E=k>KXw4LH-ln-w6=A=_T?Z^`(>Zj}Y4sM^#flJ2*?
+JG4q1H*)skP)7Bse}q+~;M!PaCBwD)LK^$s%679F6VJoaeC>jm+>=_ysH+jE+^m5`;FRUub}t6!7lA{
+a=etA_PL4VQc>p1viV~v+&jKcotZTg&*{7LJ9zr@NEX3(iYewj;FftOwSo{JVp;`5y!*$fc}7uuNnsW
+(5q)1&$#8HZQ?rL3|FxfsgTRQZvm31f5AS+{PMGi8qW-ZB5QoZMoz1&u#`-v0;pYhK!3vQA)s-ssThV
+l6HAoIP@+LU1e>{4L#UlNr1TH9_>k_Z!6A*Rqf8sXEDeRV&Qd##&^VZfr@zF4pC}mis*QuPS|}E`s_B
+j#n7ps?E`tB$-$H)6Q}>H#VI904&nmQjfcFiKI*}jdQt;~dx;DcivvQY(8=q}NP0KwOzGhtbn%(y`D$
+SFsl4vKnJMjvoyjg81$hpv;21;0Ebwwx9zFE%Rq-qbwegYDfqX6Azl;JfMb>yk{3le3Uj5eR8UmwWq@
+b2sbTKqlZqWA0z-ups#ZydTb6FMxC!of?AgJ-63__oF2^I0nC9t~D=X)Jd6c*@z2ovxIl=?}D#OR4gN
+%+xsW530FBXuixChrUS}qUH&q0on}o%3usz(2^g;W?06BB_{MKv67sD7&fX6=#%cCXEi?Z>Dbvc$jrr
+r@)#0V?ek4k9<7g?i5g_>)^_r=Sr-1fiN9hq+CTX-4j%aNHF#GMu;StBdYlG?>wFQxf(5iN7LGnWZxf
+$r$0_7rdDGjJfie@xLkY*?&=z1h_1R985ZFv-pPT~9Y4D)zxrr{QyTD^DHf9su0g{Mq#+8z={*)ja5c
+KX<u9G7J&~Se(AbKHWjt;=fU(iaT-i-HxL>=QnrU-hQVej2c_eIvxp#Zn%^LDjQX(3zUvdlOb2Hs_5$
+};`6_bLAseATnolb_m}!6?u~Sv3(mH_Ex%-TcZsUf|I|edLkGWG;`yk90ujG{!#l8y*t``<101i{TNJ
+p`;t`k0D)6Z-E4If{*=TU~lY@iF#)#l-%*eyC@2kqtd57=n@(v3{e&u%5fO@R9}vYZb5x{2Yx|?k*!n
+#2`ZPG>IRWqrg9Q%CjJ#V<b!yVvLhR-xndLQ4|FXTWweOO2TtSH{sA)oT3(}c;6>_6AGi(ohra?MoZh
+2h5Q*VF^lO@S)Q9A#Y}wF={9<f+JW<JE=^xPDY|Vyy1C`wlsY5_^Yoj=;O_-+6a2gSto~(6lBw-2Um*
+4$5A^n+PnCtulBYt5hEQ{>YCMWe-7NS8DEL=YAy>Ed9auMGg+AABe@(h{3t>JI;_}eP}wwS*?$=^!&+
+d}@fg1_BGZ;W;#B}hEsHNJy>{cpbE9NGj(-<-~w@2G*aN{ma-C>}%Ak;pHHLY?V{`UuTQTH6L#45*~J
+;;VRQ09B8#qLPI=X9S~4y;C299j*+ARxG%8y`4&b^;RL&4@;!>uIg`G{0#l)8w{hbP;JgD?hkE=NIow
+MffD|MmgnkUp=;29qudQ#rsd^Fw^C|ijVH78uaB5(yziIP!W9^eyIo5|*5y9%%fuS<6TM_QXG-i~)6b
+EDHRCSy6t7wAZ4@j1NV8hlsy#q}FKAVt9xQ~e7T3)M-Dq<$YDRP|N7*w#o6rc+W=i_vx>~(NTvzDYz(
+YN^EgehRqIP5}IT|F1>-;W#DwcrVgTz&Q*Y4D>VKWAU*65LFoOC%~5MwGy!+eTvR>O*l9X>DZ6lWIiB
+$>6K_dXfAGUD6cp{jB86;9^yI=K&iM>3Y--exA+(TsZ0T{LXJwhlcvw;S#cUM3nsw)@yF5nuRoZGU_=
+*YRPxNT3ltG5aU+75~vze%s+O(;xMK`Tb-ueN&GysTl8Cf=QZm36WxS&5#vgt8>cU&q_~Ra^El&N7<D
+sKr2Jh-`I3~wi<ilHDljJS7deS=_HtNwjZc=H2o-EDEYnH_-%DK_<fl0`#VV%sKxn;rvD7SwAFMSLkO
+=pWIlMm9~p6U)FV`6>SFlP`(JJV>Qsi^;ibdr&tcnJ{nVL=PRLDCbe7d{KL+U+xSICy_rSx{j0=3({H
+&E7@UbrL;&^R;jL4bV|7#R*D^Ln;aGX8KNxH9c?AIspnp-jaAyMFT&4Esa6JI8&Js$ibR=mM;YbiI4a
+yw18!FHMMykHtvG}W)^c;6#?drC{R2k~yZyyTEo$7@bY9{^5nxOcon8&>mSW+d7809r1gmjB6f;C&vw
+zy1<(+iyaSpjT7g3$kx;*yCmXot@~@ghl@qEXmAY(2`{T0%Og|{l*>SNmDWDO-Nen4}YnMe0E%E7=83
+*Xk3FMc7jg|&*(@++v#qt?i^l92z=ns&k!xy{9X^7{5~Ey<S`yACcjO1hGnzF=JjBdTuu`jlwva|Ylm
+qi^0C@jUQgmK7uZ{Wuu@=FzCd>vlZz`hq7CBpK-C!aCig>W_NFNP>G~L#+Bu~3R1UhC$TrCFRXY<j>>
+^(`x%~Jnvcx+M?GxgcisxgWUD|7C7-;7tRIE6Ow(C1=+K|VP)LOWLh6xVxoDHR`Q-8XTaA`i-0M4NfS
+y4qI-lX-%0qpk%+vvL0`EOx|JMqH3kD8&2Ce+jh(~0S%S}aKS4i-mlc>g4MF#`ShDUNzo=27TpBD8Sq
+O;oe+x`m%N<L*-2z0UdkjA9EYbvv+tj?V5lE1gr8O~-@-Hxdx9zKO^E<UJM*`riZDJCL<i-qR^(b;|5
+xZ6QTXT-xpuY!|A}c@shV5Qd@sh1`TgQjl)m!<1k1l;L>4`x`hOmj@3_cWOU;7>MCpw3HV%>&9j;P89
+kk@}v`>tnDyw<o)VJzTE)Kx#S8zlkKCkgEgsArL#CMM;Tz$(tSd8*7CDwU`k8BLbFtUe&xS2b5IH@n#
+r#b$c|q@h}T$SKZaZTDK`E*p#rM<oqy*BJ46;9;Qlz?&7Et8RK;U}#?y>yryn64QHJu@!+btQsZ&dUo
+LE3%MC8zxz@Fni+Yg;LucE^H2mTi{oVwn-j9B`cZOEAZ`Xc8+E;`FY|Lb1on@jy>dgC6;kFVv6jKlgR
+Jo7ld#~NWhuCUSV%pez#w1!rj$E{@4*Fde|fsJfuBz+UUd7GE|VRQA9)!RFa;)ZF4km8G!+TiIrA*Fu
+WWPF?Mt1K;m&GZgdP;2MO(c3%X@sW+CTUol&gXffaO6Egi1&`=K&jH+DXjBUpc{U38D+1BQ_CniNc^P
+6b!@FIK{+LEE^}Zexdc>uNtb9HeGxuohEm}$4M3QYEMcnBGaLrOlj?Ur$mpyb{*#$snr}P0h`BGq;n7
+iRTnYx|c4^~y`No>@*^GN%8!UtEc3aC>u4P`NY^(YTY?S8?c+>2k%Q2zi+%QW2g|AcmsUoQF@i0ms+m
+7MrwwpIPg3|&1jPqtlC6JYjCym3id<3};dRq1yc?v|f$>)@j(<oVN#hJdj(pl)$`yH{2C*^vM{B(tdn
+1m6^|ffor*@%AVwWkIjAEEXmr>B~eP5NCNuOBKc?k7!bBz6Fvl`aqz0=LLjBqis`&vnZ3C^T!tmX0P}
+z?1O8(cr$u3Hkq%dsGYWu1D`?b4|?MPtdmVJYtK`_Xqui*#pMROw}&o3sGBDlTjcU?jO`bnmr+nkFFA
+)*U-$`<ZQN6cpFB+Q@kE$nB8L4t?$YzHslNoilyd^F(o=Wf&j4uG|1+U@j0XWc6FtInp%*sw$rI?+^j
+i%LgWk_1rc2`V<C6DysIkvk3!Y>5RcQWm|9I*CX_>{abAGu#BISgy5+F>>b94YPUv?ET$$z|n0KCcp8
+1)$vdDaa;oRhrgLe>8Ti0_7>oy55qpMZ}MfU2T|ws#$BAppe>I25}KcNRhMI}?iU6BOS76lWyw88i(1
+=c)KkzdUph2c~fh4Vys>4?w3n3_mk21?EdV4$SYOeSz7b$AS4)@_rlI*!Nxo)B7~xg?F(}uMwST(H_7
+HE~5|F@Ce8|Dw1Xqo_Sa<`UYsxf^&lD&<ky)wNVh5ODouhA*Y6tWHeBiclY2`lc8`n7KT#XarX4{B;J
+kSiKn!)e<oks)N|<7k@<~a)agIr%2um29>0Epo9rdODI#UyqV3PLO|gb<?T|8XUnn=SysVY3u(5iQHf
+KE|&}<h5YBp;B1EPhuAtbVbjEd@&qS|^sQjno1t1~h@7_7}^xX^c(U#grdM^Z18-FtaRxCx!MQHi)7f
+qjHTa>aq6S{}S_0;DUvKV!T0Q5CtI_J5p$_N#lD%jII~Y4&|AmeUSPaEC?v#7gmu5+1$ND%eudwHmeX
+V9{Zi+z-wQ!tLsmRzX>OI~&~EJ`Gmle(3cNf2R;Q$G<S2rM1!$<w)vzOK6~WBRcAO8<a6dJ#?R`kHC2
+MAyC8$t2m5jN}|u8U!Gv@r>Kp=UqG|X(5z7xD>2O2H_c1l5a%tTuZOSIES$J`i0%tb&vB$WR5+Hx?{>
+L(+;pK?bZkZo-Y%VUFu=~K&pIukadJ^Tr-}7)G_4F&{Uo&DMAI7O2#EIm)(~MGXVl@PacXzwswVTtCN
+8+}z}#ziwJ^x7YUUO^^*(sHv*^v4#1coX{TT4BLuOfW_=GY-ecEZkg#^NP(;Chur~eVjFgn=QxzPUiA
+yg{*81rV3dwHtrwS<xkcQTfzGP^^EFCP$0zMYOMu(GWQ_Cup=jBTzIF1c@Et{LOEiJ$dP&H5aTnnSfu
+fDJ|O7^Nv^;&RW1HpKRB*#@%Jq^<jKSFHk`26}eAzH<F|EYjVTps1p@Yfm3<fO-6$1kj4n?y{X%4NWp
+R(=RIdrL>6E1@9P!_S4?F?Rt73GXK1wCu!r~A=FFP_R%>bRMOSUEy{w6VlelEI5HSD2HQcPEuW#y_S+
+s(be&Oo0Nt4aGxS;ShJ?BL&5tjctN-(z1Q`x)8+2>iniCGd>N*~5y)1Dd!RPUd2G*l9Y0&#QU6AmxIK
+2j)FfY2TAmVRHTttu)u3m8^UM}F|7ZD^b7%;587Yy{zThKDCa{f5u|8T#+ckrz2OKumy$cu|^7uZh=9
+Q%r!@5G8Gde|#gR15refkJJ|Zj{IAc7eP{;<pPd?t8ny!o+O=mFDdNOSBiD7Tqp@0;N_4Z;=drwYGdW
+MQ^qh_q|$Rao?*2dK*KzrrtN&5c=LMa3gOwl%rh(Pk6JygmCrB@%709zgS?%Zd^0-Vu60U6AM`Tzlm7
+W{7Y~0$wpFexqAg(?Y&pPjI+k^9|*E0Nj=;twF~wj+oKGUSiZBcXqLUBC1~3t7c~aQ><JXr0daKERYk
+H>w#{(1OEytS6W^6=YHOSPO3>CA%-I%TO`Kg=-ZbwCFJuzHu?;UEj$klHA2*(hV{8INAkwz5v+R^V+_
+X9sl?&K|H=$XD(G`$*zZR=Ae^dic!$0=1MidEt7UmT3LKaGP1BO@PDFZ=uz#C9dsl$7!YD-Uk6A#|#6
+R)8jcLgJZGx35oXJO94AZT|P!K~&&aoPtD2ieH6=!0A6{b1>kVyXNKp{+3bYXJz6RByx7P+O2eU4~;)
+x406x40ya4@VLYik>j?vZ7}KD>;C|jIU_?ZYHP1~4yfG3ow&RdYm96fR4UYS+H3Nabglo+1Ri{mW3<;
+;lwpylo$WO)v4T5`7r4~Vd*p~MG9v?cKIEybU#pE);QH@SFvoRT^4p035T(D?^@rZzk5mwWYrI7D=wS
+1S5&?riNb;_TqK!KXC5x=bVQWvbKqssq(`bwoIKwAa5A(6DQ2oY-@XSEJM{V)|1hHFTrSW#hF=|hbas
+~Z*OFjPH3FxDEOAF~RO`yZ1)#}Nxf8K0{aY{~)GBjr|+r{t3dP<<*77{DIremQQt~I{Q>`IG1<bA>*y
+uJ^LvaQ<22eE7Kc`>{dN{a8Ig^k||v7{FtxLk9|db65<+UYEvExx-qu-;<+3y6Q)1IhWNSI8av)z6ca
+q+nK!9C69E#zNK@P+M;e)WniPdHf|AUTn&M;^N}9Yw@s4t#RTV#And=IHhucd7Ex~oj5vQz(VjpP~L?
+<v$!-H%SY~n9dM@$>gB_C3;eZ0efZMguMPe>LoNEx&G;a(ZUFp24fx<y;GqRSs1kf@_|b+RouTHovb0
+PgHs>OFBypi0-D>#nZ3&|C1R!K=5L#-bjJH*>0ukWtd@+nhytl2u@Ebi5DI<orx~Pp7c;u*+tW9|mE&
+no;0M#vcHqr1`bR?LbDYJWAAQg5d3qoYNGj8{!W&IUAv`^1?F7yCac=@kfsGdS+AN10rT!$~K{z~_Z%
+F!EMI0-XQ)FRh(JG5fzpariLz`F#3wvmVQ<Y08vy}LkATT|f7d~V8fA&0o(sf_gUXXzr7&<N<wski~E
+j_Gt!8bvdSzM2TaDH=1K;=ANd7ZLTrD8s6)F16a#Z+eFMh_la~TYc}*1|sC5qm9{p0(*!l&y$O4B-Ya
+4Z$))BvfxXk=fkw(Cd0@vBDvbsrub%$ZN=+q4PaN5Z^Dz;u?BQbQGJE`c?4N!Fq;0a)rJwMF&yfV(KF
+cdU9C@A1o`pyd24)=oo`#jiX~9Cyc-$!vZ0y{T80ijX^gLH?13btphqzp^p+%CN-=z65-~<)k8jPA$+
+=P$I@9>AC#2@{lDKK7ukwk7Mw2oa@Hmy#bu_<iQQlS$_XOE#eWCgO${t<vwn*Z%79bdF@mD1Hh2<l(q
+Q<zmq^+PwI>>0n-vlU>bN15xeLr~&O*QGCJcIRGX0Qqx5|G{O{P;_N?USldPHXpN1HM=M8XngKv-?Rm
+H;NT62xMcgz$;Cq%Kq^>lDf^1YzG3-yDk3c!VX`hFT0<=;)L>0yZ|(i2Ms89h7T%*l_`mOwga+J3spL
+?N}f~(`opz->fDTVMnRony>)nnE~tuiZjLWYFk1MD4;9a}$z-)R+{S8d>8L~xzM{FGfH+dQ3h(KwlfB
+L2kAGk%tLmOrfY7!tp!H5{1_xaxR@{INwPok6V#V`TjAd5RrLtR6(6o~6wCj$tMcK~oK+%=}JA^-oW~
+-MYevJa<N1(#;9-dF4acIhLu>x;gl5XCjq?0pgz}OnwK@`xh$wp()t1TTGi25yf|6mfvyXmWgOpD=eg
+^_i}M+TzZJRF)CCvR*u$2ekj{0@*8SJ6{(-ZP&l55l;*o;HlWgOZiuWzWn@QAYbJ$HZG+<DXaQo7_+L
+2E2ztshAyd)Z0?@EI=5^6d1M{+P#Yf0W+c1H=tET#2xQ=1s<U-7*o*ugeE?hh8OCM?%QQPpD(N459fl
+0?_-DkSx3sAS!fZ%d#rR|Ay(i4sBCO+x0Qu3#3A+%!Sq4ZMfI%x*`WYk=|Cu8)Qa!grscjTl-y|%lrP
+11Q>TfWDlGU$H}O2Q6|o-g;a0aBu@JOsRC{Zo&7xY_)}k-Ca5}uuRVCoHde*vXz#3b8PB7IsIZr)n3t
+f_WGq#k~q7Q=k={R7{P|;qE<XQihLH5KfDeKT4&BwMEvU(K%a`w_M{RH{%D{lQE(gVCm-EFvAe@MT$a
+bgS5TmW|)H0G^i3tI8M`5zj_?Iy7K;!6#F+n145*>dcE&?|WF2Hc!Vda;x@<Ub<hLPE%gdl8a;ElKSJ
+oV=DC`Mp~dmw8J&VqS~~VfaC@uI@p^91e(SEzWa=`a!lm_7}7Y0B(MIDQ>oK+@wp4pd}MIS3gZC+23%
+VS;<4hUxosJpj^1YGl`WKBdM20SDZJuMajpXs#@c3iT8!5y2ii1&ud=1ZsnZpoAn@Ku`5wO<S32|(r<
+#Lk{fD~7XSgYX)insxRt_t-?zdrsHY)%T0E_GMepx#0bVZ@pF`nBzv{AhoyMn>Pa#KbSU^OBLhrYVGX
+V104}S&A+ub9HzE4=4{(Zw8TY-Go0rdJ`wQ)|QHPR!-^~WT<*t7GAkez*||1aRjPRNQ~a~_ZO_2Js9w
+Zvmq^j4kx4p&IjE%SOK0PZvI@a5(Qy6dR#_3jd~w_|cqmuetyyuB7ZL?Rj5m5F9!czZ$4LFA3Ug(vUS
+CyyX+e34M#XpnUT=z5>2OOK#^=1Y(TzMMCM**joE20e7a&!enPD(|EK$(Q-HN{4GudDGsjNjUD^17gP
+HzkoVVRoi_Yr$rgy!=GpU2y*cLKGveUwKX+~(Y{J;z<z=JSO0>SP{E|E;SCq{7906?LQ6~B{O0L%#(9
+xU7QhRJLBl-@>Mg}+-_1p|0nlRn%B!Y7P;XOEyc{TdKPXM7Uu)W@HQx*)+0L&s&&0c#KsVnid%KsWX?
+v=nKIsmdD3<;bL5Ays?b9;yLI1)lfqzIr(T1RpHEwsVNSB$l5=f#|e78n-ikq6WG2f857P9xV=~g50L
+p|ZWtAm%bIR#i342&JfUlZe(qUEpIX>8ZRs3qKLDE9EdXOI5(J6Qi8V!ChPG2PcoYx;zA_orVA*@_X}
+12Lj|0MGfyt=bth#I!%V=l>ASec5>K>>diPXy)g_^;PD%aJbRZC!V_mrA7>GE#m>*7z*oS8b)p>V!82
+}fcfw@NAv%}Ff`ZZcr5p8JeJ$oln~mh-ipU^ze2IxYx~4<Z%D>%vD;`b$jAqA>j?$)qwre-cM%!$2A$
+=PuY)q)24y@-++%`8)lkr<;IB|LN^0w9yu7RM@#=Ynwu&YsJUZT(4@It2Fybyh_u0?{tbGO69!7V`_q
+|{>VEcIuk*jIBWy&?0+zYnlJHVD$L(G<J#yk5m7bBiG_}6&iQRo!MWX7TUD}Za)k(|7sO4^80e!!^4x
+m%3U=kFx(!>raR^Og?`h?}+mRe0XnI?y6q8g>p@KTi=r_u)b33whA_oyk0y{D)>x`Bmok=Vtm2^Lvf?
+t(ZaQW3XrFQ0-hK{$wes(L8iq5-ZU8lLF2^63l?}aTYV+d=x#*Rul?0-)HF?Y@Tj0gU$bpWD$d`&0up
+pgS##sXFg8cj6r%|r7j)#%LYInlngM$Jl1aGfpT+V$1!w^joPz?W5F-8p}CJR(zjzP#cVsE{)yB8yF&
+6BtYJM5Ew90zpoGhbW9df@tq0>BU|{na-dyYp;gXhmYbsa!#dUXd0;8r-BDs*&X~Q0h$Da>__U3bOOI
+mYVC%mEGmQd-3!V9Wnxd0=it-v&?3^t;=6T`c!B@Aj8BUe}{+lQ{MvH9`XZX1R9KeBqS+W9CKfhnf@@
+AU8#_i4s>?jnlkPDXmv8RC%@YUc_uTn7zRU5zl!G8&70dHC}<YK;~6NSmCsUEb5Bdtf4P0?O-X0`wH4
+(U&_wNd`p{N}bNyj`7H`r}54rGpPGSBB*;259$UDW#xSPo%O!VS=mzb&eN5?%scg&@j&hqEA#!SI>^R
+6W>Ne5HHql$Kcgp2`&Lii&~2K*SP6x0?=(ZV*__Ov8MLj1k`X`BmL_7iucZaTRtCdoB4B$c57>55TAz
+SzdhZ*neZq;YrckSw#%h1nA$hwcab`Er&qX{|8}oW&wS)f;vD(-|B32u3zVL^2{`1rL6O?7%Y_WpE7e
+G{p%z9gPtQ*e}TvFM&M?wXNB?Mlc2^uz4ZlJ2OdR%Xq_IsbBFBQey!fIlOwvKlg_}-v1XAIFkRKr8GV
+W*$t(b-joTPh)!#xfuNEF}hL2l1-edNf(WqfcfZ;O{Izi7JfHK5s^7UqP|SK8nA7wFVCqy3qa=om)me
+8w7YfK6^Rk@9&#m=AA^L*(c(m*>%?>;$G>Nue>>#^Tja6&C>c!#?^8zO-7WP1k2RE)uOoYB`bc9Lr@<
+8saA!Gcyx_Hl8@pTpxF{%)*@&$>nIe7$7#bDCHCPzJX$CH{<8nIM4a|4$co#*ucJ8atxhEaKJ6D)&DP
+%UponIfCS#8BNZ43iB(raP^iy*$Rg*(h;oCfJz}StyF{d3^VD5&{b!_h2pdgQ@zVS|96M!hyqu&3)!>
+?f;|E!OfSO*5m=i`NZCbS$-4A#cd>IK2tS0cd5h~Ad@Xj2emKG9}?wjyG1cFIqvGIA*lvn5uB=4;NSf
+Pa3z1PZM2APWmm@1i(cVuXcj`^MR#;DAm<|9YOs3we-umv2D<qi>uo;735oh0n#x1o&KnW`c9eL$4A6
+)?bmza+icsfHmTKnqCQ%!KFV3pB}nKN?OCo(v%xRZmDdA<@!V%_z5vK4+>1l;ThjcWPB@<iFe8(vEnB
+D2I7jpTr~wq>ecuSG!!oapRxkBC4K`t6H)a+){0mwiSO<pcBHMGfX8YuZCPmEFX18FYj$Xl()FSsDEZ
+c0B^$LQGZDY1Uzxw4=q=wS)*$vXkicN<6GI*|#ycL_y%sZ=!SDW1@p=vn?cTH{5!(F}6);1)ABs0K!i
+?-j=?vq!1DK)iw0E@VB3|uCf!xpv59FQ~o4_l26bU}Zz(y-Om!(_<pOch9@R==!lX(lySkHOhRP0;+V
+2R=7W;pA~u`hU%HHMd&AxJ9{LEQ8HKlZ)^AgXHr{|pQ;vN)iixaFvrBrYggC|WZz=p7vr6_m;ngh5b*
+X}IH3E)dWIuaxy{eZ8{fm6i2;Wo~VtCTOT=n^`YudtI6`e6J8U?*IEe=iHfLGvD@G{=YYP{eI8Beb0W
+*=iq<VB<XuKHLP3T4i;s3hkJbW^zRhK81H<v>B$y)j}mvrI^B`U`jovt^S=DfQw$Z>87e=!!@Uhrr?}
+=qLq;E;pvQa?@^P&l?dg;VJY#_S{MhJ%$iEEkT=n#l$bLM(cM{5pqq6hY`--!5y36gb`n|DmRh(D#eG
+r%(nx(J!>@ZRu1>Pgzs@5I7ruzv+d@V|tx&Q(zS|&)Rt<q1Hn#=g=Kn7^JUmeh%feB$Goe(C$l+FAUo
+9vxo4>jOi52`a5d`97=U47&yUw2R9UVohi%qDxUJw>Nq1LWT`UD@feIOcJ$*`E734a9)$ety+Q-Z~WV
+SLuoP8mC`rkm5C=`nCC#eixrl>389L>Y=NhPhA;@s^>QHci>Rj84eYjy9j*ll8^HkxpD)@Wa?`jaHtY
+ra|`LEN4v+NTG$zf>O_)sAxS!njVewB7!1`AdeQmz>e8c1)y=n<tL_-$MxZ*OuW0Q8f$I7)jzG1u9Rg
+L2P!$Ygj~c-jL8!vY5RhqSu*Ou=q{SV_TvO?JoxbcR`r`YcB-~w|$)^L!9FwY*tN+01CQg$$9l@pv<t
+ZI8sd`aNs);HlRlPbzn4{rSguUt%;ZGWlNmWBQCe_^>lWI1dCOn}|6NYMVjW0jS?8b1)*O%Y!uVOfj^
+>br5wQvllh3>w;DZ;NamenM6juGpHWz`4f8|JFQ4<ExfD9jwp%Jl#uSwRa$+fqCgF(_*{n{C8IsYq5$
+i?HYM!ikzBMhV?wS<PcJ4vu9NL4Ctv|9yCj#~j~BUlxiFF>*|+;lsMdwEDQ|`?mIhs^C;6x~WLfX=qB
++ki`iw7|&Mmscaqasj?|P)eS>be5xRHo9_XqN|G)&t!?X!OhqvVRCp?>8M~*2?a--&rr)bGnD{miI#s
+P3ohnenXEHGD@}N^a!)G&@bT;#{H#!wAmb%fYe(^ytl|Q-!$WoSa%+=bR7<fL8QLhM4_44IT099-rgN
+?yE6mqI64+l1@*C0L>zNQeh5a%_Ry?3~lc@V1RP}}C9zqqXJ0IH4*c29AN{V8CI(F>$10A@M?FcQzFG
+o4NCK&q&Rrnh6;PkR1)kg9qhQdL5mes&we8`--8s%kg+F?2ck@inQlpARS)kO!(tP@$^K<$nSBr%+X5
+4|9BszRcGRQ)RA*Y5L`&8>i|fj#Kprlwm?EgQ?QbZbjcZpj5s6p?mtHFU$2tsS><Usy^G%9ZJ=tEb@<
+{R6V%^CpfK($(2y5?xdDJ@V3-7O4V*AOxP~@v9=If#is8sbV93I*mU7SC$y@C46Vva(W<O&v?@9e>I$
+ujPG&xqr?t{qkO!@5q1P-Z?UnA(s<>-yt3n^==?<zYqa9S$&VgM*Rb?=!s$!U-c%Z6iv|XbqDLsrA?T
+xNs?ugRhJu{$Jwy_xySSmlUY7vF2y2S%m#Us1m9B$%bdl`3vfl$%M235GKc^s~)wS-OX_^b%JYqZ8ut
+0wxe7fd<Um8<4gA*{mO5LN-*L0Fy9a0sh!H4MV)q~_NktafUy0Acl*rX7UU22DE%tGhMrAgr);Y7b$x
+NaF=zHCLlTSm7d<nXU+Tgs`Hk6ms=1v=Ew(y5Xy$yMnJ0uouD0AyOOY2=tIfd-N)y=_GNZR|!q;lPjW
+E(b*2JHM-HO(wlG##y#nAqgSQVS9bm`^r{6Ey=o3cubNKLtBef2Y7#}Sic_Jh^1UZKU$K<2K}9Hv5`C
+1*is$W;iaS78wPLQ79}@jx)E3~J+8M=apBIW%+S)6kSji8(;2yEgyszsKt8~!yYM0ngDflds`_y8!Ga
+#<INhb7oqO-qzgU9FQDn+4#pC*22QT)=vHm+8l<Oui2<r~&xU4wzWNt%VA@H2#%i~3#K!SvDVK>Fyl7
+9YLV?+WVp+`T~2h>qgZ_SN{beT{gKK8so%Q{$RpmX5+iVy`BYKI<7xUu}^ew9<Xk5%L4itFbi3=SK<p
+vQ&Ce8zhydz9|uB9@TBsm^}w=^tv>gfzyy&x^jfqXBTl?utQeqxOq}Y;Ts?kt5|-FaEBx}ZshsF(45=
+lhc)H|$eXrT=VS+VPWC<@i&E#6?Dy1UbC~D@(M@K0#H>cYD^#E_$DDBfEP(m(Rzaz2fB%m?2}+TrU|9
+PhUI%A4P@Sbm6wr<)?4+exIs$z--bhm-=HG^0YAaY;B}m8U6Fc%3N3eUvXCn}W!YV<RdIW9Lv*_$mfx
+)-Y^~}li=2_ec`Q=%tUUdz<=t={1-p8)63Yfp{H%76;0m%<WtZ?Av^=qKveb4oA{T0sELRz9<#a`qa=
+#O!lHi&K?VG~i>Iu&1z#IE#H%%-Y^i5z6!`E}I{&0Y%eo>eCYA7L*dSNa`&o!zf`3w%BC3ca;841t>7
+mmkG8tTbV2m0cr_5wgzEyuh>O$Li_DRdhuk=8`_bF5~PY^j!2Dyh$Zw9TchtCZb=?9pEv=rvxvbz8h*
+p<?yAiVAD0C*3WjBs3<DkpN;k07qlWMx7<)kACe9UhnUN=nU6Z)n_Adi(XQs;O2mz~;odaANNCNOG+6
+9K#b;8a^PI|@iKzun$dWOYdGBKu;V~&O%u1h<##Htlgemy~K}#dPzLj{O5jxM^`8t9r66RE&ibH|XAu
+hHhRDS#}MJdUOJa>`ay|45|Nbbr+oqE5Iz9FqCiKh=@#FVaz)H;VtM#EHu7Z)R@4nfj$>QE#BQ;G30j
+niNLZUiCq9E^tFQAF$jdV@0N7B@~!*Kd0MRXQ&}^ES4XhtzAZ8|i>$(-vCfhbK)ELxrk)s!>&16N>ld
+eo)m3bwye*_qEU$pjc;Vl}x&13V*4=A!n<fGsIeH(V41@m*_EB3%+$m?;&1G!+Dv$R9yKwlG4>$oxZ#
+UxV^D7^imp$(tV-UN~=$+P;vo-UGrVZr27b|mfpneA*a5!lx`Cde(|(q(k3uewM$U@KC1lyY6mlIJXY
+$ut7Ot|z4Y)-ohzqgQk9q9J*YRgWYYa!dU%%2bz{k-2fg(0eF@jdl1Xp)c=YhhimOk_q#d9KZ8k<iZ{
+Al)&7|Mr|8#<7QW`30N?d`MQIbUqIzlDQm!=Qf7#vksn1Nlqfm}NEx?0Q=Kl#R8D8hsO_97lx#D-!3W
+;ry2WQx0)m>!OU@`b*d4Zda7&hNY%iSO#vM&hwQvPJ?TG3XEATX6!tW%a(S3rB^giO}#SVq2ZNi74_k
+5i5q$K5CZQMEITrkDR-})07uk15vyZS2l+mU!+Aog4Fs=JJ?+l!CKIc4>G@2&RU1Ryo%>sn0KGPirGk
+LKX`>Vju8?zBUw6Yky=fqHk9J8pyrxtH5%T>2Ush8@OEb0kHrZ?ondj+<v$vC4%Kh2hS`fG!+1zZqL?
+578+<DQ1f^ELGY(CT${$&1@6fxW1u!+1wTJ^?_V9|axXmE?!~Z>;Pote42WKe6g_Fs+7RV-j+1CW~+9
+3KBC-iXofm7F6s*htsycwdiR8EP)=$RCMe$U>8)|8s!goR=YM)~@(!_GnFEn-ihDp6A$Kh#NIs0hNWD
+{p~xNX^HaTw%%~4B!7?z(R;3Mj3j07m9~CyS&Azn_>`WOz9yeLWbO+e+T9Y0==^Wsi+ovZomV3G;QdR
+C({)~x8;=ms7Lca+23>v76%K5aO+Ls3IY#(Bl=lNqoTm3|F1oMOxH)*HGd}hV-7IUPuzjM-_%FnQ197
+e)Aq?hzYRMHPDSI>=)U?8+z79ndTJY8u)>@rPG3PfO<#+mb0>BwU7cgSjZ^C^tbMrEj=#Y|!r7vQLY5
+T|uAf(m<_J~cXN8304grCbhQG&Z5F|g|TBU9F_$zqL+?G%vH%w^d)WO@ZF?c_&+FUtE54_9Q^CG3ly2
+M3SxOZbzBGOXn(0~Q2FQYX{Itg8|K@8^)v<!2$xVay&Q;ip5P9lvJj$foBA#>F%P23@TH8z@dx=KXPR
+BRMr(kjlu3O?(AyLU8EAE<M5218RiHp+L8jXs#ip1;M*yH6G2VU?e0|M~1ZjM_n05LG=iPp#zMk8eVO
+=TfW*{?02$XdUz$kzN%q7Q4e0Y5y*r+ub7OF8wOqsXe6M3!4cYEXESy-SN+y9{pGhc73%ld_D*5wBIH
+$cCDZze<i|q9zV6EL^RLE6^N6TxX+Y`g<gEaTte^a$EzB<=3;xZ5b_ZQDZ80$fzGg#!tOX8oHgOJRd0
+rJ8q^;`vz+??xX8`wRhss<ChF<<v1Si@#7-yrB1%S<Fh%gKi>oe~MBl9o-pk&tn-d8&|8M*2ty!iibe
+w;}>Wfo)V>ryv(*0*vSxICP)Q)SUIl<P16OKUW+<o_16B-<PlLF)Nn&_m2_Z?qh2vUt#6mSe;m1?Y2A
+<xXlLO&!gWfxM1CdbrRqz2Tfpp8JasF#dUHS*wd4W*45ejC+&=O`5SDA?PiY3&d0m;8W}**L}YMzKjc
+3)8mRBsmh-e5#gcD%YMgR;*1ID%UnAl^qdvm1|o~yFy(7=1N<ud4qyi@8rGH*$LC@0&tlZ{3>sDhMqe
+}i~-PuOiDT_`X&WlmX0#~48)77HVr#uLZ(=}O*tf*;ER`ykKysk(jZ0d^O)!8-_iB##nUIEaApM)RXX
+qXny8wkW>-IB%R!x}gCGe6`J)LBP#RsnNm8?voMEnXR-4|Y?>#n!ilgzrVfbG^{7+wc-smh#N@$io(Q
+n@83NuN^UBM>lBUgY)`q1SgeIgy)L+~O;+JRv;5M{i7Jl&K~El!$>tFGe6sRWThubGN>E5uP#@f@ibJ
+(c()MjOn#1~o+?B7yX+tGDSbJY(t#GQEZO4ls6K?!m-VCfA$Fo5emG{1(4JNK3=eq};8=Ri+ZXxekmV
+Wk#`&es5EMlYZ}+(9*+NhzjUqs`PvR5?thO3gY&l+XH(8T!FxciUGh61Os_s8RV-kZeI?OKYv8c<JTU
++Nhg-F`~t8NX?m2-2a}9uDd~V9C8yLf#Mq>IJW(9Wz=M-zlk~BfwPg9TvC&Uzq!*UTB^-j$qLmH~t4X
+MFCejny#<FH{68NEd3W;bL+@*(@ASI%&m#5CjLROHqYNGTey|m<Yhsq*p58}RRn-b9{nV#exh9?HUco
+-5A-}F1WqgSUy1Sa!w67|M>C2x*d(HrTceClD$h2%yh;u~BE_{{mD{F{d{tMC-J>j_iBdrp5-@iC*T2
+SPk(frWW#TB8&shZkd~h9RBWtA@mnsY7^4fvp%E25YWZql0l<P?wR3FE(wcjS?!78uaBj3{NUk^p$_W
+b-%J-M5h##B)x~%0!DlZ1({TbxztbghX|I$qir!6BBE?ilqS4DCItyqX&<sU<W#QxP&U=mxn<v+(zPG
+<cZLdCX?0-#w?=kn^#J&e-L!nTk=;vrojIjZ7>d}`Sflsg_4o3>IzyzSlf(8owLxcHK0(b;==(t26Q|
+-RQ@jqQQ$U7-%7<15Bak7W(h@q=(h}z&b460RtM49s(~e6_pt)jsx=V}A4XerevTgM6PA$mf+Um-+b^
+7wBP(!Mvk~XYnDoPkTCODP0CU)HE!9_`Wx50r-!nZ3zO{JH#D@Mcre)@7;>({@NoNkuB!|llk4cnfa4
+zxC@PHBS?Zcn@ohB*y+f%rezvev7abLe{Yj@|=m7T2+N<>apzNP@l$-;M)G5eJ}*WR|S0`{~Vhi8I7p
+Wo*M_Q~Y23uB5uDZO}P6`$HMbg2}ji&1QGICtYm%5L1QmaSo<oL#rgmp5`G$wBZGi<>_=frbew7Gj&Z
+xWU5t=a{ax%aKjN&um4ROjV()*A4`<J>~Bnyx^AAx66U<I2@$U#GceYsw|!{{maGHdR;Wt#t4oSGASY
+bMZ?tX1L6>i1Qo;}GPr0;MPU_W+AoB)WI<E%B->mN>=Vl%JFJ$%ZaClY<J}7~Ou=w>ga%gp9fX*BiZ;
+W5t;55)izJJ#h$EwpAc=J<>!lW;M2>Xe$W{4pjxnYg&Wufhv+7`K+A!wA&4aT+zpVjlF>&2fa5gTXn{
+FtajY!_%N^Y(*^V$B+0k@nN4eIWvP4-X?StvEYU*9Hao&KjtE4#cd(lpUriJFlkfs8Fd5lxmwspQnoi
+Zuq7(FnTqu!U>l;#xl||5{~26MA>nfn?8>mDPMfR(>1=n3cE&nAf#09^@_6iY3Z7%RRpF<=W5nN0b@r
+?U~B>=@6v0;c-Y!tmJY+H0>{rd+LBM<nJ!%Mo&b(xp(_L1Lxe0n<TcIcstD~)c8?YBuu9r}wBeNW@<V
+H(P5BHe8?J`xm8PYN;(iU-xQJo@#+#%XT(r(ek{YZqynsBXGJ>Z9%@UN^2@6bG70*3wTr`e^k&u3u2A
+42<<s|qxL+B-DwzBE`3z+D41;*5{b)M4mZO#z+i%sgW6xX!!L#xIlgiL^WOVPFTxO0U0jgIX<CPV*@S
+*I&)G`f1pPr04T=_@&$W3+p2lpkf_4>H4~!|!w@QBl!j@ra8cUC{43t1mC7>oAAqH$|K`jjrBIk)#jp
+U@h!KyxX}&WEVZ7QSn=mUG(HPJj=v(H$0Pl2Y&AIwMu_BZAgrdT0g~ywRPz5R*|*Q)XQXVFOBWJ9Cu|
+eHTtr>gn1djy&Q*%3q{OJd{;>Rv8bJwUw~4Q5tnJ%kLecQQJ=RY;k`Y2C%Y;&DvF|Knf1Glvgb18krU
+~CmTEDOqF~aOz9ub<GOW8%sLGFuQfBK`^${dJ-c!>EQh<J^4zH|N2Do}cLyh}=^41yzT0tz@xA9Gg_Y
+%PMnp*v?gD#_xH5-p7w^h#8L786*{^V4Sb43VQGjJQfjo!dr1!5eKQwbB203UP|gdh*Qj>_Yv5ROtBS
+1+5hnc&)S+QfkQ+;3UC=RJRXn2>h^X@&(U5vC**VqZGzQI0uX?cc<ZLiYTItr#BC2$MpxU!b*ce-~Ki
+Dy9X@H`!enib8Wj?2TLGJ<ah$ox^c;TbpC99Kz;y891%WrL6-ZZLeYood_$6J0^ZPxMOmAW74FoaOW`
+kXor3$WPq<Z-quRDaGLoh1_MQVMZZ%I{aB;iNIZ`xVw-7}5E_V>O3!Q7#hMb%u8F}VHAn!|_=l=-_XM
+j8#ah7K6D49%B6A4!x0jGrLicMEnjP1g<CkbegG4nj68f_1X*=P@8Ev{2LBR)BskaC_#T1v^e6Tl@4l
+pEB76((+9DK!uAy2@#5u+gqS|#G6X>3x`1FuFtPjL|rH5Ee>)9%d$`BXOB)d6|k`I#V9z_^7>)9=#WG
+8`u|?xzww?=7&066!m@-LUB&_NmkTeBs=u!i#vuMAYYO+7Jr0q3ndXXlsD;Z<gIk8~v@byh+&2{SrY6
+O_u8LDQ&CoVd2~fOWbkGun$C8kWyN~-JG%(afVRyeJJpgfFH~GA;9-#Y+zZ7bB|DE)<ETg|J&&Qm+Ak
+P=>He#{}<^0=js2g`;BQ{*V<CBCL4vy+u?HxFk4K4MsjZ%Hj?kbcwQ&no)M=cOJ|d$*2**(R<9drmOi
+jZH74b-F+QGRRN%wG&3Ks^de@kJN?pSKs&vg7AL*o7vaOQNA-raQAZg4}hW6a=apJ^odJZ^YlIn2>sq
+`xb8LI44B2F3+L`mjbkNB*UWp^`M4bYcYue*ain`1fm3v}>4j@h%StfNDPlJhu;TRBpwGU<hcnw7qId
+Zo0nSw8g^lx$2RKKNq9rM7Lg0rmCxHiF!o?OvD)tR;W`GmaQ)L(xtJiyd7+gb141Iu5;>nP6m<%t}wI
+Imr;*e1!iDCVVLR2uL#>f9x>fD5@E4;<+}Md}?uA+bZ55CEIa_0P9l1S^fQ5c6BrtyLPvG@QW`S<(u#
+(I<462mZ<Lqwa|p8gX~@(YDuVDIZ;h?py19Zn)WZ=<Y~vn5$xyj8fmSsn*J;mZb<B@rhk8^%O~zLY;+
+2|W8>apRU%FqaUBudOp%i8cuJBk;2fn0GEhBmjf<h3K*e%}@T#3llLJ|)L>vb9&`eg%YA%_CVLJWf`!
+le=o$b+B2O4<fCRr!M9g%bIpis-uO@nYsAe>dUP<0W(jaB46BWy>gy5sa1zeU2+!txIEtt@IcmAWUQs
+tH?mN-={wBZ9|*;da&%#^TfUxZhx9>ypu++(O;eN*~j8O2mSN<{+0h2N}FMKzty(MY=82A{9kiq_64w
+Fy3{{h;=NsLmiu6qSi4YIdkKbB&jJG&k$cIZ*lrVb&>4abGO?e`=N#mI6);4Dhk$-9aFK6H1axf7^1L
+liM#OETN4^rrbE4ma@UJ--HFJXd)y)ti^cvYw|E@Sbc=`HOFZb(Fj%ZemJZNW;bh-x+4d%`lN?d&jC7
+Q)nsSNJO=bA1R$R}4T8S@r98)4Hr{c-%c7kv(lr)|WhH(RwyM5u`Q|=k=ayOdrR%)yK)*U!_dV-cGl;
+fkk+>Kc7u}m<_C?F%$b}JSzTZv9;qa~cqOE|^rSb!V$H>3SBqo@71LYESATz}7#Y=ckd$ZV+z5U)r0o
+1hKaKp6ef2e4Xde4uxbK%-Rl;V-YW)M&*JrlqAiT7+w<Y4UT<VT`XB4ujr6ff`cCmS#kA!Qr+JW;GPA
+1;U^K;4u4dsF}llYW%$LTnsR}o`xP;rPM$ig&BlOQ==7OTqJW~GwQZdTo+Tb6){~tgun(jA>zHaf18A
+o3y4bMc!Qoa(?@Cp^^xX4qfk<V%{)Zo2ce`1ZR|GE{0U~^S@rvSSP>Y;Dp><VQ7aOZmQd7-L_GuQMI&
+Mi>NldkjQT8MN*(GpTPbSHOO_HDL$H*zQh=0Fj3h&n+0#a&+adk%ZL;{*bu1u3Ii!{mEg+$^$;YdZXa
+Rwq)?G+y0i}2fsI*Ckc}g=*<0+s3RzSonh^s6gb6_i`xEXxL0)ipuoKVz-j0<PMm~__4Fy}|Kc#4z`>
+80fZHGU;4A1I4r?_y%*Q{z=WRvsSaZ!6|+GwR8xhlOB~QLhp8PNH4|#EX^?7T=su)Tc3H1%$;McBS&!
+i_=Ez55Iw_y9Wo@qLc5sm4PV9cQPhY&Si{2Uc{Jac|K!e<z&hP$w^GZC{JOGAjdH#MIOnRba@D4GUQ0
+c<jQ)+#LNDSvCEflVNWc`Ki}ehT|t%^k8dl>pEDj?54nNy*uKaIZgD@pAn#^8Hb3$<#$z`lZ(%(4NAh
+OIW1l2fFdkbQc@5+7iDuc(csvUyXEVN$&T|=$XR~B0<C~E;GQJi035>_pU^$xch>;`@WITNUCY15`T#
+T$`JU%WXx27xZhhctTJblrnk@0vfSpJalI9!(N7>~yT<+m7*55maX8IKRt$<Hw!@5IWFGQJr3jf}@r=
+W;RQHz6-F{!!#}8J~;%LdI`JK85kykvB6QXGU^7<MB3~Jc{vnJ54q)z5)4g#&1Dh$9Oz*DPLN^@)`MN
+#>>cm!}w<8Pcpt0`Fh6Vwt`&Eczm{7-of}#<hL?D68R?>Pam|}#Q13B%NUQZPRgqoACG)K;}N1;&S1Q
+Nd@AD+s#_KqpN{+##%CZO%lKU6qZp4*1j><&Uxj=y<BO3ejITic=lQHGke3<%DDs~(ehcyqjNgj<0mg
+4femCP0+(h0spDqtk%mthc=XmOR4<RAM33F```hV(TmJW25F&&ZVgn~{c(^<@P(n04Drjx>SGC-$_>D
+=fJjkYZ){a$TLBv>5CEJiS=2GHrnbbOgkH0bD<&e=59$be4Uy;SEk(}@S2pP9}Preg%1@0re<Oh*8nM
+yB&3)5!&$Gfd|Zreg=4Z<tOw(^&;Nr<hJrn!5o4%_B_njx={m1e(=M(~{<Hl0fryra2+alkXfO7ji!Y
+*C+6Bl5?QBLL+Cb^{h({$fjF%)QMF(lpIrM+CUO3v>FS{W2;3!e7f^TaPI6`5hjmZtHN}=7gy~%+!bD
+3%yFx97`xa38#L24g!h=d&p98)C*air;am+)lbwIr<e3i7tP1auQ}UIf&ndaks$cm&41#A$;UFUWobO
+ups?%qy?+Kx_S)s$AxP6xL{bH?4FARVQ-$`YETs3y8n_y-<0w&4B_=I@?PMA5b2R?|gT9`abxNFNDcM
+*R&N*Ibs2#5K+X0kTWIf{+2K+k!Gcm2-6xZI;>=D~afc2)qd2UMfSo4}Hfcmt$INB|qR36crK9J+C*m
+7>rA8|s`2Y$URg&M`P3!!h0w?AO)t#qU)21Johl8607_N>S<lq~I_?Unl4f!GNEIUf=%bNgqbq$qLC+
+2$<HvthgW{P+|-4JnGF*W;4|?`?5np9rr4z_h{ToWu2$MR)k@BL9y}Ts&NGiUb%ktWmSRB_`bTll5Y1
+^G|=^=L!wqW?jrKe>j+2d<mdm6)AN7x#^Gw8-?rbXrZ|5H`2#8|L!M{k1xB_4VecA-JcK&R@N355n>H
+R?Aa6{dSn1O^1Z2*LYmttZe(%Gv7{2!r7vq1)_+NVI_rBu1((kq6n9}e4#XibmaiaX=YWK<E=V6BGGF
+q#K55n-IkUl_~aO(rK`ZKNGKwN7;?Zea;AH=s%<>t)_KZ3%J5<1!)S+r*PEty5gq+7K3l4?yTu8Gt%Y
+6ahYczRK8r!4YAYd&#@tW}x1WNB2C3$dTe=-Ut>Yk{bj?J|^zp0O0r%7UoXIRCsvCFw_Jps6a^S0=wx
+l=^Z-)Wsc=cf6n|n@TV0#IVwfL1J*}MXeZMm0&vS8fBH<p)+lIfVlK|<O$ex_BKm9ahz0pFaD3Y;PS%
+@EE#AxNeZc)3DddbxV#|wl>qNsmvDUTNFnPmMQXm6CcQMfPDhk|6mc~q9W1#%kUxD;Q7o0(C_H)wG3)
+=lqP&Zz{1Q$(L!^i4S;S)|<s+A$^gfV;(_&AIau0~IzC2RF6Sg$I38&ezq`8vDvgvXgTX}Y$7LWCUOF
+|jTdw||!W|XzT^mJj>%t*O%3p&R4k(7u(jiC~{^hru?dy+1aI{m5=BVGQ8YTfbe3$gv%7xe7jS$WyR4
+CHwjec{PA1`DbY)In68HijOAvLqbP-}5^vBdwO0OV+AFsIQlG`g;&77}4zibS;`STN2(YN~3RKL%kOC
+(;5Wd1|gxr5r%f=Y(elVl)V0Q&8TWVbfX_TENC_n(}in9LXF}pR1IvUTl&XF)1)CVmIX0z-yO|X;Hzf
+ol!(`uVHP#~0)3QUeh71Ce}~5@y^p@JcEE*2fcTf^PAYY*b{prVdELy$wU+M--J3pwNrL$dLNCb&Hqk
+^(8uY>aG&l6+>?zlfX9di!WSU>ibi4Jp6wM*xE`c9VczQJ7hrLU~b$%K}Z3xuHQAo_X`_YqCqq+GpW*
++J`&!Oh&s`($8dBY6V{AOw%ubSUK3QO}O7$n`#HnxX?^-5-4i3nBgEg40#G7>DgV6Nz=zn>lS^7FqRJ
+s1>lKRdUz*a}j9J9RQ;6s_k!(zi02m55QJnBbJRKp8?nHz*$?8A<mWP4o>ny!aDOm-$RpbAG}1S(Oj*
+h+~U6%BXSr>-YW`;euidDM3FIj)@bLh>v3ke?Gl|uPhA)3%T4vZzbXlZb3({$FXOi@QAY#@jGr3YNpF
+f7CcM~R_Hk?2@f8|)yp@{q=TIl_xYmRczvT6c=2Sm*b_%SJ#geRD92nGCg+Ntp^xD<&(Mb==k%bPmN4
+Ksivu42oTSPy*AWYhi1fQi&a_Gx6VbaDd{oqgmO{~z+)Gr)MO$H9^osi&Ji?wgAXHjUf&F*FX#fjjF=
+l-!=rbDn<y7`_$#irEocvyqCyHxt^&XvlYL)g`O3y3KfyptaAW}X#iIv*kmePGRQe$xh(&UP^#vD)7@
+6z_qF;)8F1K((dD-fa|jvv0E$ZcRY0MDwI7a-CYdKr{cxo}RKsmhq*+Jv#VsfZ`3$*FLh?D9ja45jCN
+)`gUw_jUG>{I;xt1P_t?9tBz%^57b}iWpGj?&Yd)Q33a&JHLH;io^Q`;s)&eWatl<V)g{c4k%RDLZS3
+R<H|&khWASd+0A#51Uw0dCoQe`DBFu8)w=2|oaC1UgJX6)`}g!th8QE1UTj?PHtI-t-l)Lg!PoDI?;y
+`{(6vt`LX4(o2hQJ#$FN)<$?>YeZOovN8sGuWH#=hE;j1Z-DwG{@5H8)%XcW%<&5}@Eq?ga$=>_gT)u
+R97NfZH{JZT7Rg#_sXJSX}|o7%aHeGnHfOo%xxR0RiMg7?d3|A3|kyT+z4bihk!_*PMN#}0r}IQ%SI@
+Rj^dF6Av^xuHLvAWWj*hC|jwnT4!Rllao|w+wdIIat0O;yff?zWz>kf&R3By?$NekB!AetMs){<@fkQ
+_}cX)KU3*<gYkh2JQJIeyi7?qZ4mYG*xP3qeOinSZN}m@A9~hX<LqIQ4pNNX$4xC}z0M$p#GR1dr>NR
+}d($`3K0J+us4qKA-?sOg_z=E)p=|`~0l0hpI?ge3H`2DeDm7{$j0)K@zhBTpIQ|L8m{_D>y?*n4Xh)
+;j9?n`ssQparVJvIWm*JFHiO2^d$boc=^k=+En^X=a$v$`#u0>y726DF{D6YEre4u`FH3COK055H(k8
+m`aO4syFA)>*w!Q9tcVU5aUsGb$(s0>qSHW*>VGF%n}BV6}270C$}D888e7GD@Kw`%nFy`teO)XXVJf
+vo+SpBZ`$&6NGFf&7FHNC?`Lzy69_ctFDr=f?9Ry3i;t#G}^iQZ3tcjXQy-H*i}YuNt!*rpY5Xw5q=B
+W)0g>Phl4dAaO_NU^BQ5k87vX1Yjm6Ne7_6zLsSoZf{8!O)-~!5!q!@c2v54qaR-OUlU~|xV@di-+fp
+8Tn&C6gm{He>1gLMOPdlgpZk4~P=C@j`i-xlfjP>o)Vl6MnW2*7<Ge<{%Qq?Ro1D_tK)m~GH0d`VpqQ
+c{bygfV0`amw8Lt@|<(}6dcnMf{E-9_`!2?%AIMS<BpMy?~vTKlP1%kwYX;N@^^F33-!J=!MzQ3#}8(
+{1b@gj_km0C#5SEdTH-U?#*m8sSokU}>?7Dic{&Qr-683oFdO+WZ>T^Ez&We>7<V5s1OB)9qCaf@W>T
+PksQt%1tmAYT|T&I`fY>}H|r4FdvjAHv;q7M&5M4caJ+a$riJGpM2u!;e5<aHXcgAK8-g3e+RVQDMkJ
+gz_pkP<-u!=9p^S^iF~C&e!yXx!@WK(1Rm%S|C_Ff>8Ak+K2I46e|`4PV&WPlbA<BOtX*$qbeccpnhX
+8o_3TD?4`L$Bd5P-I@oXe8{`L;fxi5tnkZbsq87VL)_A-#iPt%Nuz;QVoXS2XC@{p)V&{o!d~z!Nsj}
+pJ8>Vo7_bJp|MGF5sjHNKSt@{*?)O1c^0;Vub!_#G_JH8=&zsVkV!jq!0?NbyC(xy?5M&ZZzf`pO_TO
+nM>LGK!kwb>q1hxOTx^*9YekZLGQ@?$ak;!YsgMV%UBR=IB<hPlv+Ny6bizQ<&CSMRK&Le=IFw4Ef?L
+IyS7&oYR<!NKxH3f7rp4k{7v(MwBWkS|_mPH0=d+XW-`^dTtGsEja4mso<K9WW)d>F@Ey2@~dVxuP$}
+prM^zSbEXVIZOU!sr#f>;4;LYZQ6YvXXrhscdkQNDgv~@1{#GVI@VJn5{I&qdHoVcT>H%R9P|r#oW5z
+*d3JaMOL+iIgtmtE3`Q}?RJ@k-*O!e4EArhm<bfFSrlk}Nsc9<c$ACQGu45H;gE)>ncN6;eL{!B9+%P
+$S-KO`U_3p5rtX|kpvCMy2x3mlFr`zu9g#DC#U-#HgLRu&6Ckw@X>fOq*pPtEcXX&myFYKqCX&n3MX{
+IZ$_E;RB(jE2_Ju|1KkD+eSRE5fu-OlOFdIUMfyMhT*E2|(yYjI~-Iww$o<KYihxl?43v_HF3gwVw+Q
+XxgC%Tg2rT0hOBGhrp-f<XmlZ@q>J1k40Mcp~IK=TflZow;tXFPg>^sWgqf<=?vv<oUDRX=BqxPr9y*
+f163J0{`~>ui)Pr5&t%~BmV6Y5B}}V-Q(YWM)7Zty76xZwZp%)Dir@VAMtMww#UC6^y~PygS_x>4_+<
+)ttZ-=ZlVoix27nDe@o%-aJ*Y<-Y~Qs{%sOOLB+rQrXBvR3YCZWw{LdFzumb}w|$^D{w)W+suq0frt5
+c>^=JT7Q;n>}LV%H0t4?1wot`wSOTzXdiv!(m<cL-iIQ<*f|ANyeI4$FVxKaN#fVcq`yaxJ@0peCKXJ
+S$DDYSuI0pbpZrq~-0xAuyFxT~3WT>|3PwgbeS-5wBE7t|#n?u`F!fVlR2^6v)3y$Q2Ye(EEJ>WRJbK
+L?0Q#Rma#YdZqs&R~GJGrRzCXHZ<I8UJ?xabMn`TmcXlbV80S#bY|P?E!IP`;mVV5cj^NIGDt1cwGbH
+=1}uGZ}U!oxUYTW#t8kd2E_f2u1a?Uh<nY`R|3S{w&m{z#69HycL3sU+0qUWx5Zp3UI7r-vE?cNanC>
+1H6ZT!8`=TlGH6#E8oLp3k3}d7baWIEcOu>j!Id@Wf&!q`Y5g^T+y^JJLFSbJa;H*&+%aANxtkb3Ze{
+W0d}j!BofIFpX(hcVbR@K?fH8(98!#JuRFK^8;=2$d7bh4DBX>H($VL6}Zv9{MO=CDj?zJ2u_Zkk7+l
+NEs_T&(`{v09~?<I8skvsncz9!!pB6s?enC7d3$Q|&c2O_t`3nG`cpejV}dWwMChC*O&a&!Tadxtkf?
+i??OT-tD|pi%L^0+Ac}s}Q*@mpMf4k19m&H!4K#XKskx<0?dM-IXA6S!!5E{}e*xzIVHO2)545A#(3-
+@xE`wVR11#<DunvPEZ&!ZkSwoyE-No5E^#@WN|!Z@f2*^aI`%zf_7u^XuY=*QQn(1z##tjfm7EZH#qK
+oJgV9SI4;h+;@iK)do}Z;(A(LBL|*8gQ9Q`zM=KJhCO}w41?}cX=8~@GM|i;{T4*;v>gApveMZ+$PrC
+ZbCGKG4hZoY21vY!wEYK|`*Fbq4)0gLatm+dnBd>sutN3lSq2PW>A7+yi%CNsl48<lSq;yuKt~N0W4P
+3oJp%tnU4WL0+_RtbOfS9FYS5Q3rdO3K>3s-O1t&$A--1J}Bl@cerQi4mxK10Ids+%_Oop0aL9tww=S
+`i^{zRj~?V4X&1N7;guX2c67@(Xe7c8RI<?r@?n$7MDBuB3SSMr}?)&5D`0<<kof!H3YLbzF!3&HW&T
+H{Pb+?vUevEneG7Bto0FX7>r%C!&g}s2#|l^JMTT79VoGPS${nszpN~LT{Q-gx9v}%WNI)kicA3sqm-
+wU21)?55pkzWf9bx`zA?~ACB;B(ZnRpf-Fs<_zLlCfy7#s6t6CHGFU1R7eUf{G2oHXwb78`IC|UuGx6
+z4U)S%Ih~I|dIPorh`2eclDecmIkoIY}^34xOzy%{qyuR$Yw)QdGOs~NG5YJyO9j)Go>;8S%EPOpj`r
+a&kiO+}j6!2C>o!lx>vBec9dPyjwyqZ5PdQARY!V7z%0n#%Nk1*4t%Lk>8Oj13+ps+6t1g>w)NqVcbN
+@&vyHG6#M0u0Onu7EJbahCCYK<_y+K05xRbipc}mHy1$_L+E#yFEH{6U;m=;9j6KBpEO5B0S69seBVz
+8;hbQ(>+o=p>9oRWGKKnlX86oX<~XVE>2xG={MI32@~gn%2|jAC1<1>0Wnrwx5D^9r&J4*dOCkms@;%
+0sU?^{t?IFdDxrtG=Pp_lbcb+&5c3oE-{m^2XaN*wN79Z(yK>x*LgiRU^eUlp;-^cn^0cVaYd=Kngrc
+{gA7=SY#7?R7JCF&<T=_aK*RNhJKmQtCx3|mV($zem&4XL+W4*iZB=8O2L^_Q@533S%a{prL>FgzJFL
+S?831gj!DJ&vR1D!6&zpSU0CUZ+qGD|V2l+K`pZWJW{<d`1>sm*fyGCq)IPtN)gttP#LS)YtJT@6?OG
+yVkK@F57iAKsvwHfchxzU*nt|7nwgbJ=AOmOF@1<gA5I-pj$o&Nke&KX*DQ?nmfkE9g0tNy|at@1X^7
+PLQm>5c$*?9PlV&j&)N0FGL&!<HTRUD~(c1&mdKre}U2aL2Brfg{)6hKo3NVY0#HGNHaYoH3yeUX}T+
+m*_na6T@Hvzf+r^QP_wl%`xla2ImWdx36~UcHUP5}pL3_HX80u3>NkpQc)PdS6N)vVT3?F&Ka(4%%F!
+$UeVKqYGwYbOGO7-;uTBTvLWUo*A?kE~)GE=5nfK&&MR|ud)>Xm&(#P@_>zLF*4Aanj9hfKMi_^!1s&
+Ie#oP{I5;pmcS&VaUjq~QB8MA)KF`bdc=3}(-|LDwVyl%_VPSgor@v&;-apNl~OQIhsIJ#*Rnsxf^FP
+yRRox_-2F3$xbr_+@o0;NE*Q;>IJr3jzJ^dFXoO?W5TeX*Aw%GnK9J9poGgq7*^zym{Yu8+MQb<onUR
+n67TVc?0p_C1L5fX%Bsk6QX&j39k}&gUtg?3g7MhK2AY=of#VGtUU1?YbNmaY6|H2;ETHQ;B#ycBTf~
+d;fXnk*O%_Ap}RwoL5Mt!9c$GBkhr=esaA;?7KAy8jg51h{9vm4LC@dd@*wFJLTM2_N3s`Z))43ybT6
+XOEbX@>oED^ylJv>7p#3u2V}opXl*MG-0M}=7aw<NA?dJ@Vho!0*6GG`R1#$V0%D<&iT}~n4p+45dol
+qiHg36V)`t~GTS^NkrO>SX{WcZYz(R3qU1)Ty`&z%$oD8jkZ0#1|^#W`HwJ5LQrJ~oeUM4y163JxI@g
+$>Waa|`wS&%daipQG4mO-QJmSaA_;(AkyPR?sCw3tuvvDFwejZG%}8KV83bp+@IZZ7TU1TQ;-)od(nK
+3ndp2K0-_f3c4cREI`1BXrw+wG$7Ryr!cM9s?inCl(g?pE6yhIC7>qp8dq!w{d=gsk1G;X8r^zVsA?X
+J=9>88r1H<40d&>Fr8k{BHK2MpsV2k^BY_2~<L7^{Tk0!6IoI7SEtsSz^w~I9pyW3+AM!`zeIJ}+#YL
+)%+tB&)*R2m+4`ncqzHYtm9%nz<I@kMkYj*n?m;PGz;rrHO=DOdvZj4h}_VM?v_l4@q=&%fjcVE%>t>
+<<3zV!&Kl<xPf`!SXKed{l)X^TSNx2}S+biZ$n4YK$9);{cg>r&aL-2>NY-$8Qlf$PHth(gm8rOOAdU
+Cyo_xZa=E>4EF0pH+eSfsT9<Lv!%?_knM-Rx&k8pwC;=4OBt?_%9edK63pIPM`F<4!A3!*P1*XnlxQ-
+&^80la{cCG)(Zsgp+#8%$`(JrTS36YaJD_X7p5#mQ<dN&C&Cn(!V<|<4t^#DWuc$^V2WE7X5GNY@L2p
+5Ga;m65e^VhLr{j}V{CXL7UwJM0s4?Fw_rs+-{uUK_pn~-KBl99G@=x^hO;3a-#bK5XuffstfNECPxZ
+UZ6pkvsi#OxxSpJY`m8ZM}ofFGDK?9>1xpsuRiy0$S&DT)Sz&iPfL@Ee=f>i5@?1c4q5Hg|O4Gif0mO
+KO|uz@j!d1W{!P_)8OY^x6;a)8my_Xz{&iLvL?=_p1}@i#*rN@oej7eLOpiT+B2<VV;6T4lHltTOz2`
+hOJ5#(HBKZ{QK5Lp~FOhY_K$Z{Od}#3+B*(Il3cWXOBDNvyXUx&|sQS<{7g%*g6xRNpQldxFq>R7a;6
+-X2`UmBZF_5g<e*Rvz1R^r5VdOFH?Dm%EA$%7OgO-CY^ccKg{bjc8X@(Y>qXcXyjS>NL44r=@RW+YNI
+xHm<y`D?36~vH|a`OA$j66iy01ESHb$5LUb3X!^dmtILcDxo<93f~_EDU1eL`p^|tImTLXx8VUY7mPY
+B?SR%&3MAcrpb^<~Cl0c4MVy*Hs-|5CLu}Io#hF=mWe-z(E*_E!%AoTF@4P8Z3PFvQ6F3My@e3u3(a-
+o+2`OokF=U?ME4W(x|CF2?G$!RpFlR2Hs=~7Pb<@8ZbU*+@wr;VJpaH@-AG?LR%oKE4?%IQK*mvVX!r
+;l?Q9nWYVPW?Ik;RZ&3=Jv=0MuRzx;&ck9H*>m_(+W<X;B-5uhdKR%(=(j5aoTGlqt|kJGp8Ax7I0d|
+>4ThZ;dC3PJ2~CQ>4%(t#c4CA7dQ>Po>2p*qd2{h)4819!Kt0o3Qjk1x`oqioW8^9NlyRDsgCFGHJrw
+CDsXxSr>i)<m(zzieU8%|oF3%#6sHq-IjX;UUXD9CJsH>Dyu06);RxzRNO&fr87CO6e}U1CKix&9Uwm
+!X=H5R|$eG1RaVV1vU*k{>Y3#$xXP$<--;~N|7W@?fO(UsfIvGvkxgV-}9J!uYNs`;|G;%YskVG<@n5
+nJ+f0M~__?ry=6uIqX^S@EV0C8Y{2Di>?{zs_(SgJpk>kyJcV-0gkPVr|ZHi)SW!dVReJKXv=lR~nh3
+;o$(TLd#zcOFnX=ybGcB2Kadz9KNg-%Q~1c|25g0oW&Q`*v`fNAkHknPh@Gi{x_kbg;V^bevS*+n-GE
+$D_;AqsCv2uNqG^UTS>Qc(CwRyW^pTuZF9JgZ^ZKe@-yV<}TFuVeCD6sStCtRn)=W0`M=Jro6pLD%ke
+cONRItc-fdo<LRx=r0HVes^O{rtNy9}sO~|ogvra7PcCu`R5tuZ8Is{=KxQ@kSpFxE&CVXn6e%DsCN4
+5&Tb6D4Vw+naZZ2HWPCYwIEJWozn_W~5OwJ|FB8covXFm0Brn7(+yvgp!!!k(DbY!{9*|yl>%yhUjY-
+VNwRYJHJ7W$8Vqo3#>`UUP+qhII`x<@x;UZ&`DWM@);raSUD2l<lgbQHN&kYBd!0-Kjcs*|ab3k#^`J
+SV4_BKm{w(GA)|J7`YbX?%ROe*OWv9)Ur@AwBh>VZC~XNA&3%*{}bAfrG9YY#1_hSk&-qM?_yYGG^51
+F=J!LjgOl!@%kI$CrwV6GWEurjHYRc=A`K}1k21>*5sRKr_7l<FEwrcg7jN%y=~#`cPz@tT%46{%UP0
+}w{%(l@`6J9osJ^Wxnkw2)py;!X6?H5B(czuv?@<baTI3RuymJ$EM-C2J3tC-WDLkeK9zR|l>-rEW;y
+5^XpMDHdj^`05E97c(F%2E9{hRRQB6^vEKtX0bYqJ3a5l)EiQ4MQ&Rl5!Vo4nQq0VTqV}e+*b_ClK18
+rptv<0!zwhlwI0*9%}rg}Nl&*ju^E~KakxJ=qwvepRO8*Ce$w2l-&y*I%BnKbn)s1F{$&^(WtWP-aqa
+u>IUwI`6)F6Mt8t%Z5uGLy!Zg=v7$oYa3b$9A}ohKgo(_{(>@U_Ook6AMix^L07s7Ev|YTn7HKxMR97
+b`Ba6wpeJV5K?ZS{^e8qEM=KAWHp~g)3jk;Vw;L>f`LRsUyubV2f2>s9!f%%J5JvDnb~Dd70@`M1hGE
+ALF3|R=h95$gso>DO=rjQ9`7#i0&pQx*(jj7wFJ^?fDr89Hj9@p^F1FZORZW`%w)M&j(W?UcX;D|MZP
++hyUi=#6TzQUUOo=D3Crn1ntNEc{vGnsG2dd{=}_aO=3iGS$nGXT#=|&7^~Xs|crnk_E9C~}1;*3cPu
+0I0{=xEGNmF{|de>EW*Z%|Iq10yogW*kdhi9iHhW@Sq`wlt^KtH;wNow8n_^A3f;U9?qBI>J+tfDa=%
+O#7cu;kQI>>U4bWYQJOyAVRN@ffrEUC7O`Ra`-(($-0qy!~%4PZ%pZ9f66w%~55iyMCghe>eP!f6I9*
+m`7`(gZiHBZX=d;8;<J#KO#TvL&~Q4pV=W5s{fvPig{f~<s_Q6x4E=$GSE@7t(}x~UteRr%J1sqi#C{
+yVwo<dYO%}s#(I_C)%%YlV;tM7J{NUSqN@L%_CAM}5vy&i$FhSukNRMsy_=otIH+2U4Re#-DUW<O%?M
+@lEuCt>)jha!i=L@fmnmEw%GJ$1nL3QCH*s|@t~PRYZ?0|(Vd_Y(wsUnqt~PLWf3Dsh%+v!^|G0Xf8h
+#K{U&GZ~xq7e~ULaE&)bO}^2v-;Dn0l3(A6%`DXN_Eaml{8=zQom$T&-|*YXDOx)4K1V;}RTiU|Gzke
+Vp3rC6XBUGeAkVA5mI?!<m|Ao)+j;Ze!>lAyeo)s}SS>Z7%2I4dw&-w~R`_O8Eaq>aJrbN$y%cg!-S-
+&bP_#{EDWtL#$=jF?E46KOb0s{HH-V@bxGDKB3yAq$EH5O^gM<(4rweB|Sh#ZitOtkP-kHXP_dc%gD`
+uA7r?F75sEyg9H$rPKP3>BLQwX{6GFPboz^S|8+L&{3k%kT<Nc@i@)|ZO1%CwSNZ4d{vNMCpR4>+-5U
+P8v;Tj<uXCB^{#Q$Y#`AZzzjhL!@%;H*<)23a{@K4@OF#aF!=Jax+w7{7%+uXoeYNTJq`RXIeMrsyD=
+xXGw5<Hz-&9m?kTzD`cmJjb9{la*haP_9(Z?SD-4nlm@~JIPKlAK!e|Y|dtuMax^0rrA{p0pOz4rQ!H
++JsYy=U*6Z@vA_yVW)O_8)lfU~S!@!|&H0IeM(&_=yib{OIFPPJVjov(Nwh#p%W`zxw){Z~yY0-1NQc
+hab=U)O_}@fBX5DmUFG=FI>EIxlQ?}7ihX)fVrv#n*Z+f|96M~Z(ktm-u!<={^NddkXL;e1Zu69`r!_
+0e3H_8EOB24_5B^xn>wf;=%9YEgZj4})c9njxB86^YCKYbW9n-7a3_9-O<ikTkXMjhxN@GDDdrUxpnh
+7B%`toNQd^d2Daa{wET;wwxIbWS%`6g4Sz_J_TS}qbX?N>0J?0%r2A?yR*rpY(VlLCjJQ(xMr7K8dh#
+5wiR^t8hFD|~fxTF{cbiVf%-+NDSxSt=4=*r8>A>(6Xi&Kg#V00EeB0gn7F^tz>P?wT|sDg&*;)-H$M
+POK$o13fC1+22$SK95J#&ftcb2EIne-lM;-JQ(>aU|@$hRW7=^1+0y3FJ~!9FGo%v9o6!JUvs)%s1E^
+jzWhaufUL>=`6^~wK*mmh8Iyw4!Y}r_VV&=*#@!DP-wRm7;LL-Sxzx?alX29l2(8UG|z#IGh`MRGVNe
+78{FWkI%MdW4)z?j%xpuBqi{L6VBQQHf_p<INSOe6oDP(b1n&RL!o`LxaDruM$f1#O>*slj*KnuP=2)
+Fqutc@f(Y(keieAQKdFC=y7Kz!A`n&>2dLB)dYQbY(=oGuMz<(Zlke64mm)6DVM;4#ei&T%zN3!UeT@
+hg`&+1Hd1e9Jrs7LUU%y;j|Wfc~Pj>3FHZe~GtzRl4oou2YrViTeG@<c;cVYbasm}9W3YxVdWL)SVy`
+(a~g_zs|pX)MO_S-tv8T4jd{#(ZWa5B@G+4zVym>0=BaUq_4qc^QFRQLb%qCTQm871%(=@{79lXJu}l
+Xe+X3X4wpxIU=NJ#8_vMW9;I*g0Z%O6(dx~9pug<mlzsY%ySeLEVmVis(nv5HplY3f=rr8P`2P=^qtN
+^5y}f{LVItziu9CDb!!n_+jGD?aiLdxkm?l-^M7TYn2WMhBxX9iw688$uX3d6<#xKrKQ(=<UVHo1DZj
+IAR201J7@S2IwY1dfqvN|SpAo}G7&3V(P>MQ)(AoZw5s=3G{KA#!F}m(5TAkf>pC{eOpJRy=3%tk>ZC
+e2?RbGz4w%jhRzV6q<TMVMcg((vvnw1H~q6#z3l;yVNg?vkJD6f4(-SyDWg&rYu=b7g{v?k{5KiADjd
+aNbn&9>9GBBnD*oV*bGr=o@Pp^#QDggy*As-lHOdCTqjwnb_?yf8bjNL(mhKVghLdoj6+ANn2ETSt0l
+2b10tf=KVV`i79|Ap7TuY^~}U10nChXS~Sl9|rylFLhXdE$KhLk3AwIJQm%ce}|x5{u_L^ayy!Sfux@
+pLi#}%{ZfNSzX_mrL{#@19Wrt70X-QY_9T6?Lm>QMqK^x7_%~`Bd~h*i4fKKNK2S>n!3~($H9;B@1S!
+*m2a@m!dJ;Z9w7F+va6@3V&K{8ApAv>)9e^-IpxHejEFI}LH=;p}Tiqx^zJyOy<EGURE%+BU(2oq97F
+o?wLWpX=Vl>pDF`o2l0)0r}c>mabV|tK5*$2p=3H!+)%{!!Lb+A2%$GOo@jk7=6wTJ1oL_Z;b=*P2sM
+Ssu65poeeMfF$jPxPr^2i%}NmJW!&2=UJjfOPnie&Zt=Rre#WCuA0U_o?MT^SCG2g?xs5g#2yn-4Ir-
+mZRkcLhSIp$n7_S+XtYk9#X>}5D4WEN(N*@c}(a@20R$v(5pH$MH3lFBB9(Oq1+;&3?k=JeS28AKMBv
+)K^X*K8MxDBnL<eV6t8so`w;)RK36OkjNk233HcemZ@4?38wu%qqetCU9%kJH{pd}eu)@OpNf^X2Y&=
+SEV1{b%Wg{WS;QQ$^v)6-`O%D<{*Wc~eZWAF3rV-Nb5~G@69}=tyBN{_6F=U4kLn_RTAzuuRfzACJBO
+Cfuhubv+gULY1uYsvO$w0{Sfpa69`!w?W!SaN3>LH!_xt=(GED+LSA>;<Wkf{mqApx4-Q8V`!>Q6$&0
+1^si9y&g_TGPXa^ce3Ks|nY!JO?=m2Q$p~eq(!(Ys5FmHQ77JH4|PZ*J!qrP%ejdki#&V)&MGpY8+m@
+jSxTRbmppYz%p|9#P%DkgD_zZ?(ozn^e0}GuPfB6@C+DZXL$S!LqEs+xZ8yFFs672$4{!cSN%|BU^=w
+1DezTrJ2v3){^nNic#a2I>aB&gB7pQBuXnrsAqUECiN`Ho$6CC^%WW?$=`|sQ^m;HTMMGtY*Rz3vtPG
+)S2Rc0Er^frUrGzvsBV>R3IK=iF9Rzh{4jGV|0`+A!8K9X-m`j%T2n4Sg7(@n&ksu#^!T&yFpr#jLwN
+h;pAs?YU`=z?;cXfAi^O8u&HBOJ*u=)=5Je#+tb0eC)>w69ixn6?rJ8pk8@cZHG%j<w9LPsK?ZHa)kB
+?7{Z7#~(0)>+S8zR#|Lb`!qws(Ttfgq;mE)h!Rznhx=&?Q1Wv-&Y51d=Jt$6)2Ql-|@Za42sJ8z#e4a
+GZ6pAum*i~h&?zXC^iseI1Jk)XnO`gzcgTc-)5F~dUu{|hndh<@afukoM>AGAH*jT!jBx!>msHL{DAZ
+{vfj<pHvAqYu*V+u_5<8OnM6XFL_!{bANGE+L1gfR=gDBr6Qq4_!^*lri~SMS&7M#<L!fR3lkf*a?W|
+1?guLj%@`BodehcCk4)F`0%k4lJ>Y)s&9a=ARv|jYUyqo6fixzArWCMIDml@SW1(K)<{Ycbb`!`26_G
+t*O?qv_l2u%s|>Mz~t+zs^;J_j$qenWJmSE?TBL{HMoL3^(ZcYlld&imy7(4P!|^gw@*qLvr*+ew4PU
+SJjmWf@9(C-!_WuvypW-=M8l`)z^nJ`L>X!H)h!ke&ATypQP%;r5Q}>FDS#*6mIY?s^jaYe614>FGmy
+jt`7g)g5Wa{CfKsAvMPsk2I`rAjlw$HJ}~nJGXbUDh;arwBv+)4d0uWz3Z4)dpF+Gr=tCXC!l@$fRIn
+sJiP{F{=uNe9t{E2es*n!Z;DTB`@Hb<@BOY1BEu)#={sDL<J*-?83sW3SCHGs8VPy7(IdCr^?l2}B;=
+1@dip*l%h@2yw{|JZbv{=Pch8T6{P?3+eTjf}0?IeywVw8nj9@li05yygntL^dHZaKwOlc?Q4v_Of!D
+JA$AA_Ji41)SF2=aH(_<qfO8=wvG^C5l{G|*<Fj0S>?0v*qM()7@f9*g<7?H)+aC?C>aQ^{mUtE#~gs
+&&|p`;%Y@Gk7jbrDkw287zj8!P%jZ4?W3XPn)08Mf=f+?MF9pZN#|tiwhz{MVn@5cD82dge=Wa%^e!%
+8_UneK#0=~A>>-|61g_}BDr?L1#+$CXW|K!+1nJr(**Ks80%Sr-Wtb71=Zs`dNSy3@oBeA?f(7ed^`{
+5Kj-6FJpPxRj~}e@J`P%?nPC$X*_7G}GwKB-Mmx`j3xp||V(tR64piQ&wKEGBvlU#jl_cWopG{rtC1f
+qy73gx8mka1M{1#;9iPH-m^YRLo<lC70q*bI3F%=c%Eh*qWq!xNSC)t|m)C0cS3%>saV~SBvEX=mKPq
+X&-0o~-nY-hf0dS1Tm=FH`2_XXcMxa!ztyz_jMo%v$kwAG?5wQxaRwk<I?(?OP^Kl5<u#A!!o3&=*)N
+wqDvvy31Q@$|ZVg89rc<|>;d8p_&-uVN?R@+~2oF-N@2FJKxlo~f(tHj;p*iG>A4h55Eb(UH$=Imm5P
+-|2AJ3Pf|B1A;1atX_a89TM{ki)`GpSxIwmPO`?0ACsM*Pl!Y?nsaT-3s=yLm}j?TEg(snd7=aUS-|y
+VY6FUTF)d~?Pp~d9rC6x*PkaPhrhU2t=K~*5-h|67<gX;DK(sj$9eHA2R%ZS@hzc#y1YfHybA_#wzMb
+WV1Iigw2%&tXO)Fq4pxH^QvTSy=2k{f}`1k9W&Tfr;d@V(0+hXUEB{oNj!&U^DL9W%#74zrkK_O-4rx
+mQsD}edVVAQh~7A|wzr#lO1L?F_*C=`h%iJ5lM>99dIi?&rFIRh!ewY8MOJWLsRAJ30_sgG*a^+At}9
+i(-Hm4~Y7^05>^;xqH}?&_Egrh@Ew_Pm0`LMOy{V~6@>BEvCOEb>qXKBKwazK+4X0`qac%~3>EA5l9@
+`k<YlKBl03Qh>ZE5qh{A(Z%efWaNV(=jKDqvT03$+Cy&DOwTVuFEjI<HgX%P=BcV%P(_Qr7|X*;df)d
+-cWN%~4p<<+)6qT?4`TJ<yFI4tYzNJ&YdrOl$tlRd1iuB4LsTru8c!R+GKidj63DlSorI}cJ1^g6vy-
+vD*2HAUA}Uqj+kW4<5EJSd5z#kf)#4*dG?<hm&oVP}2hG!$wEgJ9fb{F!hCtmm_^FLUYN5NuATP3(CB
+^2T#Z{2Sk^w<KPTPyTtYti1wVkB~vagudkkv(^ZFy=Qgi}OY1K`O0ynR891;pfQEzAUoS?tK9b^jEVf
+w?x8@mrWwv6cf${53B%Bm{Eib|@uhQ7(Em&6$$}qJ%euKoISj4x2kKZJ2*vc``rKk%tSe3rHq2$)26V
+a(a%BXI~Fv0&@T+xgh_9#IX|QF<3zU^ZVcXGv3M0`E^vcJGBu?e)WfIBwdf7ySMN2tG530`_Jz`zbpO
+JIye5A)1x1YA>_#Ih7&m-DvGx`;)1C4&6iU=V}fUw@ofx5TtIwMJlBB;5qPdc$7v5v1G!m{msua~7O9
+^58_M<Y9Ca`Lq5crAKas0VT%E|(DcsFmu0M~{1>FBzc-Z+|e>uUEg@oSa#52?m9#?;EznI6lgwuPtc_
+}w9<NiDVAD#$)lB=KQ@p+Di_X5}7#p8FBn}5R1BLi4osCoA9{e^b>W9Ei#fB*KV{g?c@KU~MmyFdK(-
+y83L<?sKx40QPYFBgfFBtG8q(bDGQIcT6W?pb}$5N`hbX-1#^1EVERHPRg@<GNx>5qqZQ*;CINy79k+
+uPYlled8+an>gJG_K!XD%`^SUx6jDW+}6GS>z=0E9OzKyoVw$bfh;<;^wjvy_CGlJMdNuw#;s#6+Z07
+f^fDLty%RI1Moy=28qetjPGdQZ=G4GxB&Rw~Tm2dRfzw7#Kj-u$ryp|Kz-c|Fb(|jHw3^emINi<Z4o<
+gox|P#MIo-%<SqJ~ua4K?|&uIpy>6{9j#&a6W=_pPOoa#7j_2c)TwC%^|&0JsRw2{-3oHlS;$7waE+d
+19B=_XEBahkzt3a9a$#&R0Xse#i-PD44>aY{IC)iT=5smy63rzbhB<8(WxTR7dMZSQ|ESKB$w;8fr=o
+>K#-I!-V7GWs*8jhyc0bPK0{&m8EV`IXIVKX3b=X8vn=(LA?n_Zi{5yd!xz_2=ct!%Io#_tX?N#?9{2
+-XD&JsuXv=TKX^jb&UJ3mHWTi{@?5V-|he3>;6B#|DC^IyFcX9;pfYLs{7VnydCFMt?!F@J+_}G|57@
+Je`<Tv$Z18^zlN^ozi+s|8?*i~s>Zcry;0Z5+IYK0X8HO5OA1o`!K}dnpJ9xKh(P}WUnuZ0(AhBI-91
+V}Qh+|t8^&UwzZvM-aOls0F9v!DzR!WL2O1Iq{cE&_gacg+-_|G%$p#wT7sfSU2kGqo(3S(A0(2ov+!
+q3m^yFX|I{}aMtHI1qVjyHNd?~{;FsmWtGJL7P<6^?RAuKErsNYcV6ZCb6^9f%ugo~J;l|z}GjX*~aV
+|*;o=}{0C*cX5{MzOGvK0KVIcgt{!14iv5ec@VWXDiU45llZA=v2<v0e$^C7|Vg5JAf+i{fzM$Nytb<
+yoUIU0-7}n#uJz)K!Zj@@_-KpdL4WzXb0%6AOz{aF9f=83`@%apx=*SarhbNO|c+<pl<|vcPz{2H9%j
+9Wp=g$9Xt-krXwNWfZjNc`ELZOjN^Gb9`}q{x$FiSIsx(o>>zy`zDw6?NHx%<6QOKCKObo0M4neb%dd
+wz4Eo!F?v96X+;9!0CniDsf&UQbkOZiQz()a{mcZg*2HKLq{BH&7m;z}5J0j4rQ(6AU0v&%N@Sr~d=u
+<bceBJ`I|4l5t1A*QHUn|%t18OufeWbo7LI#5WTA+7NgSiCoYk=N2jm3Wx&{Ht!$OU~ohx2I?#1na-d
+jzPHz`q5w_e}5;_=P~%%w%qnKEZjUU(IB3BeS5G;cEc<u|Ng*P6D3-bPjx<1D^pj6TU{^vw=>u67mi3
+@jwgV`x$sU(7<GfKa^cCVr`{E8Q}|@K<B5kaMOYQHJzpRXQ0Kmu>3@7hbda<2o0qp7eYM+eiYER;7bJ
+_>9|Eu?|`2Gv{xpK-GL7WIwh0&pTC%pZ?jlg$Utw(W@$76eFMI&VE+Knrfg>a2cS>eU<?lW&jF3jVR1
+uh&0%hlu3tik7V8vHO)k^d0{s-ec;G(=8j;8JBY}?LyZ}_<{6?Vf!e<7)8tC~v7S<)8FE3^MHlPXlAa
+B?{0DU~4*HfUw3qjt1j|RG|ki}mF`a&VIvlZxF4nnp8zXs?9`09Ya1ay57<BNg%iHz3)-6XQ|LOR(A<
+qP^#fWF~mdAJ*>b_Gu_&}R5_*MXm?w-RIpc%%WVSUDPi`mcsE0(~7&>uQ!Rq~q^m^=ksqHFrZ=zz)*K
+?`HMu382c|Tqf5LGH4A;qXFnz__l!k?Lgb$+YUTgOGwo^h$rw{fNoe1G7S7ipkEZT_%{Oet$?{P=xc!
+vu7r6s@CKkSR5CkTfu5;k;Wh&`ZGgTV^27}E(+w<tJ_lOy5Y*MtkXJyjeVDn81{&}P%;~|74(LsfaCr
+mzz$46`%|OpQ!|Fma(8%XtP7OTLZO^eZ)&Z^h1E{eqfWG%U%bz-+$uF?HO#%9w7nuJQKo7mZ`!As1a3
+1N77nyye-@L@yQlzhMV{PURpf9}wc?J60fNpt}^(jbCzRJoAY3Lsrk90qLjbJ}zJERM~A23}&r|c#qI
+7UNh&pptN03Ql;+8$P>cA&@hu(&lK|0X^a0X$Iux0wG1pbxzb^C8gR0`%LrS$&s*j(vym#&-~^8PX1R
+kiJ#}^Elvl0G+uH@(p+^(3kc@dV${tbmRd@Kk!DNVlA|{z$0D!KI9MZ*+3iKXZ;k?Q}s;$bD&d?uzXG
+diVNpDDC<z5pTHLid^6BL9D}k%`2qSqd;@{62ikOurFUQhAvd3ZJOcd;pwFIQem)2E)ei{C2mS3pYd_
+#J0JPyFXrn<NY1+rkemc+*pD;ceXznM>KGKAfOb(|2-N*R@K%*M*ev5`u-!GxOfY$>348BN^;m?7-`~
+#EcZ9q*wva&D(9dQQA0`#MS-hGCJy9TJS8QKfbN1EEq$`|Q{W+tnbfbRMk<O%HT1{(JZ#0Pi*Xk!b+2
+Y95fo`Z4$eml_9=Xk#iwD3H{6ZF>red|2aNBRrrTY=8O7i@q}1$yWLYZK~$23&+P0(~9Okr$bLyr+Zr
+jxK@xAQd@}6z|Gxhqegmi(DV+0nX!Hm~S|bRN?lK;=K^mM|uP2k<R5j(&d~-TETgw&vG8`BJAfp((gE
+rRDYTAcs_qT=aHsx9;t)#Nb!s^#trGGTp#IAoJWdhbdg6og!BKu{IvXkoT$O@vA8FpSVG0Psjvws?iF
+rj+iG6+1L%CE8uW3V0#&9M-8bVh8&Dl|Yq-B?0E&~Ac%Zn4n4;<EkA~iO&Fw-Th7F{+3w;dt(Ju7yx8
+18)y!ETQ(QoKRzp)$r=5F-84>Wk|hjycH=te)b3w>O_#XB%5&p_J^^cxNm5dQ~gV>BLh#`91wbRM<tk
+I=^XdDQkDU_RWVjywhGP>;I$d$6zdsH1<<Q0!e*y$RGhUyu6Hze2m<6@E0K(>8pv1Y+%tWYGCHX3Q8e
+W5x`!V8H^CmzPJJPA4nS;$rw$OdfsoQS!nIFOWTZ_K@o8YVye^pOCh;Ho}+wim7E#G@~k*++SZDO!T!
+YS01CvW6DpLii0n$T)AcqTKGw+zjREgKL^IOpw@xnCvXeul`By#AFHpgr)oOQ*1>;2DVK7n`N}oTx*x
+!?a*(T69@Dj=`<$FhOuZiM*B{HtIabTnmza4z=wCuL_<sq^@dtL+Gyj=7{~WbnUw`Z%(>O={KaJrtHH
+5Dy(y@As8t7sCE*(368dNQ4PUC;ir499$>RZqcRJYAtXaNhC^1**l`@MB2{JJOVk3kZ0Fn@F>Un%MR6
+I)YgMfK(K@nP2bV_;(=W|!{Li;s_sXBMcs^~ka3hHk5;cJTxKA52q}R&Y-Dz9IfcpG~cAy>zU&n%Y06
+D3{aTZM{T|(LUsF(-W-<HKzHGUdYTC?bC-BPBLTaKaE>3m*WclW5(pt;Og~_zQs3z2n_c6eBsj+6V_0
+5^J%y}Z+AC!^R0(ZDJB~DeBld#PY>T<1?4=H%lfa$`Gg4*NOE#AnKy49x$CaG+R6B)O`FI|FTF%|?AS
+qN{Ns;5Cf|Phty|9Rc+3FCi1zKf0<a|Rw%@Jn%z2lrfA^<%b6^6q9*QXET}4^{u4@rU!m{;eep$2=nD
+tM7dz+$M%vpQr+qAT_cXO;0UIw~o*~~j<E6N*-ly#LO-n}ht5m~Q1`|cZQ=-;0E(Es&{^5eO4+X<Com
+`AJ|JXi@07_1Oq{*fzus+|D-=~+Hu9vNvqUHOE>@ZrNrOiT=kjg2K!r%oj%lZjX?7Mgc+=FB1U=g%j%
++;R)K{r20*y6ov>$&w{x>C&ZS`SRt&;c(FQW9{0t<Z0(k<mJ1jlGoQIkkTbdWaF|#vboSie&;ZfH%lg
+ySBfp<@sh=4*Q0iF@cvn(;n`&*`W=Og+NY3l2NiPD0fkIFtdJ>36|(S%LJ~hz$gEQenR8kpMewD4rI6
+dcQ%F{$LKgp^kdl%TQdwC^9(dpZ^2j6que~dQuj$(QJBAwC8mfIFrHPnAN@5No(@l^|2wqdAeQ6LxlZ
+eC+Eit~LH00GYtK<eH_a=>*QbK9br-mr0noAp06SLN^zV+Yt?Caz<B7DB@`+dJ(ce|Z??>TGlHLtbzI
+_G4bSg>G$SiE?#NKH)@%a<>g^3Bf97VFoqm%eQ4)~zD<t86jpDv9-lBzEuKE%xr+EB5c-FAg0#B#s<8
+B90$FE>502DGDy+iQH=>&YnFh_2S~ii{eJXCGpemBnk@)#qHa-rLLfr@!)t7%4-5vnu;8>E3@7_&&FP
+b4cLWV5*?|z=tn)p7#c3-Q;JwmtHlvIr2MIPnc-a--jm@wGJH3Ne~aM<GkhXd7auYFVusIR_#B2m%<$
+)R@C_N>kKy|={0N3mX82VMzmwq)F?=4wpJMo*82%!|7cl%S9lS?Fj&J_fJq)a+vy*wP!|Sg?UWd@(>V
+oo`3p&|T(D~tlE~N-6TrKF94*q3^cV&1^U}pO;d<etyScOpxKZfByV)!Kt|2f0&VEDrfe?bS&aV?ZhI
+gXQ+*_9Z+GQ+=scSAC~%S(cM82)XBf1ly!G5iLGKca&dRYa($$u?V;b0&8-+cx3=Ykr{!7F4~jpyqLc
+dVVNq_+mjRYXq&{Bk0g+9lQ&}w_*5h4BwyO6B$04;g>P|T87`o@ZT^z&zW+9;V&?Jp$-0Z9-%9b5XB=
+*<q?+i2)lTMvphm!brRQ_lep27#I4~ZZl{p=eKm=@hsXy1D#JHrcwdI^#qa|deiXw`WB3IOzk=b{G5k
+)3Kfv%O82+*jzM{r~R~Y_PhOf);4H^D*hWBCkJ`6vc;b$`Z3Wnd#@W*xVMO(PF>3=d90{jE~1Lfy#P2
+3vPcXe&p*>=`Hz!)4H7-%&3`uYckH+5^&s6qYCo$IL)0)zQ9{~ydB0t3U{8{>k`on5r^#t=i0(U*r0G
+Wh!j_=mra3mP<Vt*f064)OCh`Wpfb3=h1Tz3%Sr6aElMV~A0;POm!F3~$!VIzoNdx-RuP1D?k>8iRd}
+;dN@%a^&-Tftz+g!*GW8^#`!Q82)OF8nvwFC64u7T^Pw=+xX$Hyj-J3*N*Z6cX>fw7r+|=an>K_U#?N
+7tA<*)CYXWY!+rfjx*Lr_#&9PLP|LAq&A+|y!V9&#VFsKJk&VZ9Dsn+M*nsnfppamrF(fF&xyS{4zEK
+l7en3c|F(@Q3q|<9ouV@$Gd}Ft!-Gp^~gPcNfE!-OyX#A7oH}4R_EDi}WhDajh42u7Ze|TVXKcHabF`
+PPes!^i`Utl{Q-sZV*KaU`upgW&`ty3q7LT%f5L)G$Cy{dQy83RL@%blDh5p_Cg>fzho-@irKs^vX>!
+$ZPDf`c?HZGRyn*w8A#;8D(@a(C?ncoiJzZ#y5}&ZAnT=NufWcVP^HVu;a~73tx5|F*3?TUIJt@ugrs
+X$W9lZq>?Qcz8ZMJixz4hbk4yx8aY5aEu-t_;CJk11{;&;l(l){BYjj%j#+r56^=?tYCi6SFh3|+z{g
+1fptv?{rJ|_rCRlNA^yzAVBKkqA1F`r?`>NeIs_LzZPgzhKadqMIH+}dyVJVynKi-w?d?trW6>63cbX
+_?{GF;3e9v$qk@IZwx$(vHVsp6(!q+aJD>+Y5`CPAFy<|R;6xrF9dwiDYBc??KiTUvcv2Ie3$X=Kv+V
+0_;g8f{VV<f`PS#yR&KF*yxS1ekzNGw^hM5LvqiDk={$y{OW+O;wt{Njr*WUlai&Szo~=Ns9aE9}~}O
+MLg;cQQ9Pf9|w6ckY}xfBw9<eEG8Y_19m;wW|d(H@JE8rnrCqzDT)EVl{t1bXVtRJ?e6x!wXE<E@uzm
+KsSa1-7F4tD@1i#Cz{hX(UbOw;gl;<=!95J7dU<w>fkvbhB`7l3U99qSp>ohK?;ow-;d#kGyGJBU&8Q
+f7=ACqKa6vK<tcyVDgR&d6!kuDCnu-6IM$Lc{C09|;NjtcQm>PXlar%U-6qb}s#JN6^{kewTZ0CT8hB
+K%R<-eq{N1T;y+)1r+UnJuJ={IqMQzt6ZXR_idsOEOs=WB(Yqje(aPxS+vfFFg4=yflO*|@Ae8G)j8o
+yNKMJLCaO+22jSg~@Y^5tJ>T(zoGx#ygk)Oo&QW&Ge#&H0rI4i#KI(CSnwkMaNJSf&Pld%j-fN|oH%z
+Unr3wQOxZ%OG|5JJ0W4`{hRU+&w(p8!`Soe-n52`tI&^-6egsx#8a7x^?AOF}^D9#T3>D3CfB`-{|9@
+y9U?e0Rd<0{t#X`@vgkYr9?klil!cAcuv>LYqS1uw5Qns2EKT7;1y?QXD}5Vuaaz7sZu5OEb>q6;<fL
+1RXlqN`S^k2__JzdwQ*l4<@Mkz!Xwn*W$DtTZ*tt(QczIv^KZZX_6x_Jb62ihxxmNMH*VZ0;C1Qw6DL
+lr{^px+W;i%FxO;nhduTK{YUAKh4DjJe_y<`dFu&BWVZ(ZS1h1-;64tR_zka@Lxbf##j~zQUi`UV#ef
+xI$<(FTG<0&0IdK4Q}bo%sZ;`KM-JkvlNXHVwm=U-%6&mKN}_|qLbc8m`Q2xuv+a>Ao0HHG!j5a0s2R
+@OQ`t4Cq*$VnYs8xs@L^3I(*sKC7b1o+oteji{PY=tq}wr$%G_%U7*|9$)R(dNyYiSeUNn>I<jFI>1l
+KmYtQ9XxoD4jnoquLBI{2>AUx!z^9BdiA)C8#j*Qlr3oT<jFna;^G36laoU^uLf>-EXKWN&6+KzPoLh
+mMT-{Tonv5Npc}@0Qv9!9zfPRXq|~cduQl^9`O>9Jl#`QV<MV+72k3_%evo*wd?fDpeCEs<`tipf<#*
+7eI_Es{$U1l9>eZ`vSnuxgnE8MF@dsVIcJ2E2-+#aPr=Na0&2#;Z>zK|@*xp(*4#|LhQv5le!d$iv{8
+a}HszWBK1Aj$_`mDM=Evhrlw$3uQb^Y(?PlNwgUwt)`<><;fF$Fa2+__WY5B)fP{J50C*|TTmci;${U
+>lal+}vE*VH=PKj*uH{2Qc4$`>n(uGGzNF$l<{Qb=R7;@%Ov@`#qdz8*cF=_}{v9i#QBP{rB?nY6v|>
+2mbr_@24$Wwh+slIA@kN4E{qNd-v{@9k}n=vq#!WUS6L33>x4Apl`4f$OyP?_>Cy?IFavnM6LD`dF&=
+~-$B$Yhp5*+qKpefH*ej_Wm~EJSj=_!Z`-ylrGEYTtvQEJW`7BJNE(1Icn-dT9>@Z?<1=J`>eMOO@fk
+b^zkx6G0JH#a@E<ZZ{Yn&gl*sQeQHKLWZT~~mau3t6i>L|H(C|wl*Dr{YPY~U^cW?2N;LpC^)`7q3N*
+1a=jh(;_pf7KpBI=w+WcZ%>4;okoZN4RH!8F7kBf52uXwV@d&uzBSM5*w<efu_ad1lL&EnQg`rho>P!
+=GpYF3=<3SR5VTJ9rKmL2sb{@VmTblL+--{JZ{Wr6J%5kq_hAo@r>!dJ~st#Xl;SsQy;%e$G<j&oP6P
+|A+o_JR)>^nJ7I6Um*+V6?8+<0UL*&LGNJ~>Il0)>wT7}JJVof{qJ<lN<+tkMD6xlY4BuQczq|4+x92
+NpM7ykg9Z&+vmBCPXYeh>(E(k5lzxH#IFGmhIQSWT3p>v?3K~ul1v3pnOhfh+Dowk}ec_|<|NZyhiQ`
+O>4jNQfbQC9(;^?@0_bwgUyo8pIHPXW2zBG53pG2bX&qQzhMAY*PQ3z=GL9=Jp8E<9Jd#&~ipVV-h)t
+;Mfwc0d$+~WRZx5S_2JhN4+R<7*NrvQKGi9H?Ad+4=29f}s{I`ruDf7a1wqrEA8WJmfm!AH`7_RdA3w
+=^0;PZM=xoVxs=vuDtt*>f}aB=)Hd*eBIx8k{#-eJi(##o_Pj>T1(}j`4`|f07667x6&J0``FKiU#1%
+evfkI4J7jzZ(1?BBbk_nB}@Za1pCjonT9@$$KTIcX;AhI8k9Z5CpG_u`TiAAW6;3-ciGJLzef)9U2*u
+cznA*Yww8>12sWqaP_%#s#Dhoa7Vw9kTtCsDvOefQ8BD`+rXg*F75{_+qIWMd4f#ZGUa;CTe3J3UhxQ
+B_ls$t6WzX<QZd>Fqx9#zVoguz(o@MKxL3MjNin9?#3);r<?P$%|_LTL02U?ZLG>qy<Hw!P(u|KRdgf
+k8OeqkDP_H5Mb*+19nlf3p@<FoQfjhKddTZ;8d5`WI`XSQzL+Ld#ZDZn3o5l83@Xh6=RXu)rYwJI;eI
+mBD!3}|0WXh$28+R<vJA(LrX$uw+TFpO>#Tr8EdxyW?JuuQy^J!?5eqix0G4}YQbzkU1m4IvBFVXwd&
+xB+)X3w%HPJ=Qhwn}}72ZD`vjdC_L3VSQ42${yQ+EKGyFJ^!11Qc8?J&3rF_rbQWO@?Zmv9~ek8M)sv
+s#|}yw^f^W|Eys8i{_O9i{xd$wz#Dks2%La7>;ZTynZU>E^JBzc&<OqiYMKvy$uw+Y8rF?t8rT+K&!E
+Ai(Xc?HVK!(O8bDKrFb#tODQRGkqyY^+sl6`8XuZ35{fEy$3_~7)zH;SCGMmkWyhwGuOiHqo`}gnD!A
+~P-$K<xObt2Qiwy>6I_*}DR_@uOvKC~p>hvvum(wta7nicI&Gnj@CnTAPB!#Jh^%|6HYM{e={2l%rtN
+d0HMo&s7v{P07vSS*sB($Jx30c`%EwX}0eTgqV?wlEFSo|y*tBxTR3?2{J9`_jBPKl+4eNM;&7VjBL*
+dNeUIP$CMS<gd#y)?O~&{{w%e{~bDXXb2pD-?VAdY&6)@Q4%fp@86@dI~LOJnFiWE*^9Pl_Pj=C&&xC
+#7HKs6i}fh^J%5@WWu*a4<`^8GyK!Igi;TbDia)nnkU7WSl%73%8e?N)_W@VfBWxfkDM`|x*RRLP1V`
+AE{Ti#dc5GLcEysX8f2`TFT`MvF0sfGEmo8l(2U@jimCU`6%S@j>okoosWuu`aI!clW8hp~aq*B;3(@
+>0`c~q+fKFyvzdk6bYYSgF^g@=dJ^5x43aXBF&fkuoNK{IF0ly-gc<VopwkP8(@3-Cs4fUiO>gnSh10
+W{e2ffXa^-XFZ)NFQahXO&|t(Cm3O+rs1U-@0{cRnB$(uJCW#v}v0`g9gP8960bY`%x(elgUIqdi0>)
+y?fKgAAd}9=gy@$bLL2Vu)YVrpaHP}aYE67H4JEgKZPD57GjQFGXm-GXTbj!?OQhLVU97%nq$D8;gc3
+7h5-G?uD`s!y{CtSgiM6~u&$@@y1(`M_3JHc!^Gz(F)@+YCJ5iVcI_&2gx$M$OML+Dz!fr5dZpw6`k;
+GQ=OC|xEMO0?X=%?a2faP7va{#^Y+Q;wa8YTLr(L^ta~3REAooEqw`R*UVZsCo3k#!q_3BaM#*K+{Yl
+#c+fNkhIXi(jr7If&88XLZK|C0W+^`CwmpRG9t;<I_2fi`|Jn11|r1KqlLGneIE>iviL^XJo)DO0Yeq
+@>WKNt15&?c0~4qoXC?d0i=W2{gbiKqqhm9rm<f4+3!*dXE?lTfu$=){*!PITB<CT8e2*{_m&2qbJ?}
+0WjNcYFu30=?^~m-~sS_^UXJ9hfOOQnlx!bqeqXHazM;bdpn8_;0yfKo-fu0IKm!aBd`a1dq>RHuRXA
+S7EieU2HS%Evo57goH+3a?9^y9(%7+Mr5r#5@DB(Gpgw*2$loCY(4abKQ0rc-#gJb^?|~<d&>_&K*Dd
+5!xSoB<zv|bo-)7yqb+fRBcpChno9NIb>^I{#;DtTskt0V+`!yI0<mcx{&6+ina=>}O*way*ZYkSPN9
+Ym!0rU#~7_w9Q8;ldmZKbVWNc@@ZnQhv%ab+G(fjxiu<(HBM@CW;bY#)+_h=>U4)~%b=t!2xWN&LZU@
+Eo6kH|zlZ2frgXh5jJdh8@5LU=tV@KA3TTz~fADbaeD%xtn(F+LbS?HJ=Kl#UJzP^B=`mbgUPF56hM~
+x4>P+(jHje#QG+605J+YRxoNm5q=arh5ui(W({R!Wyu)$`RAWYIPjYJl+V8H9gdM>8TXz1+f-q#dz7|
+*Bl9=pKk)x-kIDEBd&3d9K;E!f)>D~F#Kgo%-^#Ww;~RVp^jqm6>;QHNnLtk<1NdZpK7`L07czo85YL
+%jyh#UsvwSIWx8bkXRlN@DbsM;WF6a<!Vd~VW#6C;LX?+83ssjdo2EGUl`hztQI&cSFOP4Oi9%E{mGG
+(3=cN_jH|7U(r0S(G87Dos84Ijj@TdotJQ;4<2?CDGVAsdxLpsoYGhc1EVu%Y?5ng7Z8UIc%={=-Mu$
+5?w>aKs+_+i$;3^XAQy`mN`?>bMTN1YO5>!~o!~>LZ-jF8OcZF7el|e>wIfLoX47K!@7zhyQ@DLp;*c
+0p4!duz?mXTqyNf*)TfjR(tcvoA4bvqv{9jGe0X^w(NfgcN_ltxTw!z^tnw*GC@yGO_lJV3)h1-;0xV
+??*uIhcg{~&Jf*(>34h?i_9gY7<M$M`{wj$UwdbkocaRN!gB(;%4l;u;LM;I`D9{4jd5)*?GbQ4$-~U
+l-sgh)Z{2uuazN0RO4&B1>>#x6-eiuA|y+YrCKkR_@aoID(UE;6b|71U5+y4O#h@Hq^;Qycph)0N>;4
+#*m;63D^_IDu%e2346uZ17uHHEBeFwM^zcZolAw<JA(l)meI5zec93-B2<Lf2W39&nD3&$2>Xb$Z6Qq
+v182fBPTqm;?7cJd@Y@(gY4J+eeSSCo0eb-_fJb2;p03J@Th#d@QRS9kio(Mn?y`@pbb~(2hCJ0{`*a
+k*r4t?O0YjR?v=BwWG6k^wo~zwIf-N4mcKlZpTGDMZ^6)6|`Pnl#nZ8zmNM~?zimLi};R;iv51zqZ;O
+N<lNVjW4<vmGO{P<`+@B9aT_*nJ44R>iqPpP#y)w6Xw*5PE=R33HtYqXrqJRmqPM>zI(kjwQW6fJwRZ
+XP<=gVwZaCZY9r!cOId8JRy~uv)SN2QCIX^dXZab87U_8UnoVzRM8wG>UTkB-l3q_r;gSMA@<T}xTt3
+<xL<ov&tFn=BP;psf*9eq7r-D{%u&$XQY0r%_db932meu05eGex}-buQFbuqTea*za!;9lTbmTCX$w^
+rT6XBIeAQ69ycRJ7N8R_z1s_SOi~<To!o>&fzm!zx;>wLezLr@5G)q>O0tzM~&@q^J5LbYtUF;FAP=d
+d#rOYFY;*cM6G#{H|ZPdWqp6K*85N^TUS`z)<uz4V5bjqe*L`<_V+x1Cx~BHE*z)NCWpy=%w%m3u>Td
+J@JrUZY43B^y05x_K(CLe524QJ&ByPH>ZCJb3a?)yIL{5!--iMDBL@a9h(B8v#K=7`><42{Ud@mGk4x
+6NC+cldAM>oWHq>~akEl_h)`>ddTi;61J!*c$abEAojvF^_sJ`B<@>v{_TW2L1<X$57bFq)8pC7eX)Q
+{h^(?>t8MuS=(YD~~a_b;vfLCuf+M_((oufGEqv}~<Dkv_`0AA6(V5>32X6bI;In4LcQYBkfAnm*dq>
+E!&pPKsEtU_qE356lfc#}N(nHteaQzJNX94fEn2TQj`$2T?rZ((#bB)&`qEy;DCw@`^EI#>9>vKYpmb
+_6i)ZZvtMRVSgR9rcABghdLAXL!pnTF`>3GS*tIN9boNqCq+pdq&^;eSo^l0-@X=XUjv5xcTDw_^)A$
+ku&0T=aix#g7e{>swFz0{(&isGu#=ptvrZp7{->z?k&{iIK0RXb;>BUGMXdLcpM!4T0v_OaI6X?%4N<
+SczN%T<+g_^G7hn^pkDyjKAu`a$12nylM(tLw|FEt1-+w=r{r^x^AHcc*Ydi1+z6ZRxk^ckj`y^D>39
+vt%t?jQb)7b>-Of$4P*?0{HG^vj~@7vr@+%9VWYJCPfM9#0Tv*>Gg;M3!3M!7pbmo*mD>ZULbNm{K@*
+Z$=HF#n7hGa^3y^wTiZhLDc~54EmV_YDFM@B;n_=g?5U&3gZ#O%$h(I$bN)|0Bm9J9cdB)TvWrz=v70
+W=X#Xzl+!h{|{XNKcI`4TVHef?c5Q%a_%VGgq=P{``c<|CC!hRf_)C`>4L{tU$HIP_R{TZVM;cT#qN|
+)Dm;IL3Vu5JP#;G;)W=0hZ(;gk<3EpIM$I1<7IxOx*H`YlqBb2B6-6I?^pRZO0Vm}Pl&^$*z?<v&$LY
+JY_h|EEe|ax}(nr&nPPFFVadi3o38F{jKR!M_E&crb#(<8bq@-c}`}hCG)6<jQd+$BD51gEwEcY(d+6
+O$x5&T#8Hi94aF&PbG@^yz<w@S?anl^3v2HU+{2O`#^E`!<<=ULRRUq4CrqxPEZWuxM_y0?;t$9>NwK
+j6>&$K0HMTtY1o`^Le+!E*l<I1C>?T=E_MK-EZ;4yZk3r4Jk@?nOsO4`y9X;2a4Lc4N)|xHXkCc*VS*
+J!Hs`uTkT{9{n3{yg`r!>T4XAZS?~1UFo5^M?@VtR{g>J{D8+=%Ioth!urU@<C?SD<Hs1t?Z9vB<w6I
+smyWsy>_cBifDGUl00&&a3;1pLOyIeF`}SF)bTtZT|1)RKj7UpM3sY-u$Qd{c9z2-b-QB5s_wEumweP
+3uL%0rlqx=Q#OI)*NO`5Q-6-v{j|AYUTJbCg^jE6mW#C-T1)E3@(=N(yNhF#!VH1I&}@giSFO$B*7)3
+Epn=C;jmzlWvYlR!L*kB^tW0r#q^eMQI%yawIy$+@|?E1qy}IX~uMUnBj0ad@a4c=hVlv}DN=xmOI|h
+&?A&Q+&#~<@}gO#b4+W=v6s5Y){oCfdh05H4f}QZQQs~-6#08bKB@I%^oQH416EtoSmHw{ky`vm@cgQ
+Cr{h(tVy+}?69xL`L{>5d(IPl&o~r$_7?qd&+O`--L=69Yqx*@$`d@d>+(oEIUYJc>KyB%Vd>JP>r5u
+oE%s5rEnmL;Un^FuDB^c47E1w-F)Sk^L;lX!luJ)f4^B-@-Ike|DdnkR805@0eN+#RdfJX1JFw4sm&Z
+86`ga3%h_x~FHH+6Ey??ac2j$E8^`difsErC9*FvX}!>N2m*%W+P_(kiQ3Hj+^PHS3yQzSnYh{2c(wx
+-rZ`dl#LiggXV@!Frl@J;R;;G1Aaz*Rlpad7K0N*QL&4F_mzC#)Z_e#Ke=YZXskD=lEWP;14S9JoXOG
+4HCRV434w=QY@(8`d$f7RTBPYd@^}u<rEYbtiHd<W#^LehUq2803p<|2<rep>LP(TK9CYkAO8B_y;*5
+2B~{cw|p2R^DX3i$n}tGBG<)w!?Jj~90O~PE{q4{_tsl)$vQWD82E5zR~l`Y&{3`@k-H;r$GQP)r*V;
+;<s7|F6Rl*vELyZk=7YFL1a&pY68d7Fiyz#PE%W|y18g}rh+Pl<aa@po3pF|1KcHeM+Ug`9x^yO2@)K
+*Qe@4mqZz%ag_u%WHr;uf@UcDqw;in<XQ#(zxW>RN)|L2m#uC(uq&j7z(!Ef8PP3CIqejNC1<Xn&k{H
+Y!nd`2wS>p!kn@>lmHVJyT+%#V14bppnQU*_09UJnmH4ZJZ9c!63GXhO`!eiC4@&PMFswQE-qShS=H7
+XND8MOm$j61uvkg4V0zcLz~HxVTi4Z+pTU*c|Yec;q*{f31vsLp9zUfVZ!e75HmB_=b0{l@p$xR_}y2
+ua(!Xbdm2}drrI3MZR^df~Z&)>0X%VEyDTVAkm9I1&bb{JAV)6e>?GKv@gpQJg~k8&p|qHb@bKfEyw@
+aZ@3PUSoanqM7)R+v0^Zf7A2xZB##^`28m&OO@O?{Q+RQ2$Gw&4FE>t&92y;jfv<@XaUz1RAH&#0@V7
+`gc5faDXE2(J=*DM8@-+j*5dI#|zq}z5<R`R$h*x<mHFqHQ1ims}J`X;E{~gAVr5Q6wB=V;L{Obrl*I
+!<T)<RU$jUOhjPSB0pTr`v2QyyE%-#l4X4w4Te<n^&UVziFJ5xfj&#n(s5IfWQ1>hbm6`14?SB{&nuJ
+OLGh8N(4m6!V)4C({Pen2%4wFE5E(4{e+%4L3z!>?3jX6VT64h8rdZ^7sSziqgvr3!h4Vg16^pal8za
+`WVLJ#TTPt*n~&A@pnE8Jxbv75k=%)sa$qB?}&ti$e8}oV_XtrqGJ;}x{i#GZJ#h;NMuYzLerS20rA5
+Uh7B6gbilBf_7Mp&%|<nMb%}|HjT#i0p#G9>N7v@fJY9WWtnA|AJtBT&g8ZAir5vrL6^<bjA_t6&j~X
+#X`_8|_M-Cs!vqTOIjgJ}?6&*P^GQoCIe>y0ULGib3yG4$QjCP5}za3p85`tq#4SO##-qmGfl>Y$yfz
+^(#gCe36B3*sFJstu4aB`1F&+hF}1Xphl8`1pT+e7iwC)7XGKQJ)3d*?oVLh&vo2l-HTp6QG!-&AO-m
+|iVCG`&x{sOBK0xhFL*H9z%EYQ;3iG`BRbv@U6V(uSlZrcFzmpSCh>Q`(-iytMqZJ82b7jwbxYg(DDP
+YPHk}t7d1+&q&Q!nUS5bDI+IiPsYKFyo@s$`5A>7cQS;zqPd#c(d=S&Gkco7%zoxB=1_AV^SkCD<~Vb
+rd4hSGdA51JIn}(<oNeA@&N1&XA2jEg&zSF+g{7jUn#IxLVsW#0TD&ZNmM)f1OCQU-mLZlnOQL0hWtw
+HSWxgfVveJ@m*<{JF?6DlQ<XO&G@-2myI~I{yF|%5xW2Q@{Tc&5GSEgTPm&{F>d6{=I9kaZ$60>G!&C
+g2BTA7udm6Ijp%SyZPA<mR&nqZn{nr)hIN;R!CWt%pca!h+n2TggBZ+A>09lUc)cS(0k_e}Rn?;`p5Z
+u*e)xb(#I3F-C`>96)z`@e7h1yD-^1QY-O00;maO7>O_r4?PGM*slU0s#OU0001RX>c!Jc4cm4Z*nhW
+X>)XJX<{#RbZKlZaCyaj|6klT((v#66)s#Jdy~bGq-lHHZF?N04NsH63#9Emz-`U00Uus_V|yX=%l+-
+|e3LB6@&fI1pJzX9*tMn6Xfztlj7Foim9=1}oZnU1<y8|zJA>fG=JOZpFE(F1500<W;NY&gDvRK#yl8
+HdDh<9V7sWJbva*Pw=24mkZ}xU}-yQA7&BrE4ifOR3|L*v3@9*!A_YaToA(UImX7jRYf=M||C-urjRn
+Fjho~IK8R0r~UntoWMZP}tpKQ?)GuAkI5T=g<9&sCj_ek65JH`6iwP{p%Sefw8k7V3LmUS4L!rTSUc>
+f8KoJSk`MEY}!R`deL2uG40vsqVH`0{E!Mb-t2*oTT$6*rO-ARaI77L9iCgtK@Q)Yz0LL9l1#>ss`nQ
+QSh!TTEL6*c~wr*TBA|l>90*vT^Q&z>1=NQ{@C1B$$X`QS94XR$rO9}80^#_EM~L2u?B&pZQ-c~vRS&
+qV-c%*UuQKA)-JUOqbjeFrb(j;MRijFoN;qEPwOFdfxZue`fAZ+`7o%G+i_OR7tJs@qOyDYLqf0fnIw
+~|bd0Tx>vB;|0LY@s%XwPRmw%NRe7S0xIbbymKF;!LKEbbkXf+gT7?sz@#|N*0lk>D127gcLbf+vXvd
+cx4G$lN_N%9O>ZJHKM4=gC(Bw2ygCscKwR5kv3fB1$5VHo^RHvb03au{6HFePAG^nh9v9~Nc9T_Y%il
+@(;+v;s~NUXCx*<_$fI#^WNHrQ<P_T7&6%2oox+(ixx{U~L>vYzzl=4j>M84}w>lUqIQFy{~uQ9q)a!
+w|fYHt2CCm5LMwnqm$Fy(|G;t+2FK(8V**z-#t9q+kZE{x60FJZKa+4w+GvYyW{<XZsEU<zWVh`_<!`
+vi{Z=Pem(j3Cubw6_ICU5yWK-?Evz>9HTn|&HEaHw6~7i`b6P*k3W2iU#jvbS&-vx{yRSQMVf5AOchJ
++LgYBJNw@`F?q&jy50`J|o<DJ*<-+k99c5+%HF@E_i8a#crw)L0c##f*G`=`JC>B&F;YxL`1zdSuTJw
+q}9n3a`jdO-t~j%P`A4Fk%5#yo8XJj+*CSLyEo77UVr%LH78L~xZhi>iQE(~Kl+Qr(d}1*W7Ts!IBCU
+V-c(VNM`X;v02tvpiQ7gX{FJ4pz(g>M&T%uj*B5X|=*{7i9&qq*!m#YL*pA4idc}cn!d78woC}WCl$S
+gHoYe$HBJ3TpCKJP&**D2RI;o%HTX@2?Z-c1;8380vwzKFlEy!$pyfWFiI3S;DJ7n34yywsw_FrQ;<r
+F$rVB@YnnfU*rGEIii`tPiC{i49c4K1vlgTo^tB2|EMym1%AK?k)Wv7OB<<{pXGt@;GT`cR88p0Q2?n
+6#B5$DjEWWJD#k`INC!1$Z5rIRTDBn+Jaav5H!B$%~%>g_TNf&aON-|)tqdTDBN0M4mxF}#SVbKP90<
+@sK2uM_i0|RKC+F(9dXgIh61|J9q7@qJnTn)E6V$g#|R*(!fIBP3-Qis8lz(Yg)l!yeukE?W^CzCY#F
+bu+Q@BqR+-?CAL>Dkm!;^c$<{Pqgwdmk<Fqj^Mg=;UfqToa#^AL!2qWOkWEP1=C~)G{d<j7GtSZaern
+hXwn(^M*#;g;4f@pnk^5e2#omei(QQJ&a`Bw#yjmgOkA&p#9Uqp#}2I%ny@r>oQJ?e~{N?0AzaJ!#!S
+#So7~O#OY4Ne)1rng<*`UOhm1B8}iOl%|cV@sp_Ev!0OQlcQ%NmS%N_C@W(l}JC6py_4Rc&hn8xP#(7
+C92nphq76>g?+}^N-v*HS0obF!fYjU-$e>RVYQRow+L#qR_;`;kBaK)C@#3#_i;9;`M8XO=gEEiX4oz
+?g7;Qf?dB7$MH_I1@+%^oMsaMo(&?EWdce7gF@RXJa}&h?YUKgFp0<0&BogtEVc<viR1v|#CgC-9XB8
+&>ok{{78AfuPjmnH|{J%j<n(=}Zn?e(6BsAcFe4eE9l@t~+dx8IQiP=<7*mAVQ!~c>h=k$!)^9^nMhr
+?Xh_{srQ$tdjA)c?&(LD&}H?<=q#_iHjQQVRIR}Zn0@Fmcq+@Rt!q~A$s%B&F<8E00cl%&g@>p_2o01
+vU!XCdj2kpm&>kokwP<*t+~Px{E!!%v2jD|&ieXo=M%_;TfRfn2EhvLgxE31xCS)Q9k>Z*A%!Dq_cor
+QrY67LY_pCJ2tZt~BPv$;^+tQCsmDIvrG>hT;O<L9D;u{5vDpTGsLHwRY`@~pLGqd6NB7=6rGhoW+ma
+&ute+@PtV8s|qFk!u9@vWT&H#;+i%SV(fcoz8AWksKpGe>09T~W~)_WGfs!qeedl7odlb9?K6Wc(hW-
+(nx?9#JEB)ejM2P_|au)9_*1)1;iu63xjt>ly2wE-|Lw(GWzXx`z;byy{mw70>?7>Bm}-H6aS7_lJAG
+SE0iX@`Uz8{oYk%i75@}-J^l>^zB#28k*wlq>P~Oz@Y=0z94$x|E#VTAbL>%s_g}w|L+gqC@1AGsKE}
+tLg!CfH!eYuoaY&s6V+mx#<T}<J}+_0;`8T2{`&IO=Bro%pO$G|gf5sQzfJCHUU!0)3~z8vs4C#E{4Q
+9B(F^LUa*<D&cn*wIIlF6efwl7t;rIq6YT|lw1*-}5xQUCj$;-*$K|{6I;;4qIL*{$rbf2+c!NAq{GH
+u36bVu-I>{E}_N3DqFN3Xv*EGxK{mh)8k&lzseEao}7<1T;}cgPrB^B1N$`qHLD!jtA>{GjG>y0ji=n
+J;!fI(3YtN>6<A({;vqYMyj$4*am3Kdu%%J`nsoz}zt!9GgRJ{a#}Js1K5->&1T<nGAB=<AA}>5|JZR
+Q@s4ZW^W!tBpMa9qD5%9-3*q1{)1E%ir8R4EZA_CEO_R}ZxTNY)!tRa{Hz5>CCH(9GPzDJVIE#3H>g{
+~(wF7zjmM=H7<Y0N+>!(&lu#@em-RBRsfhSs?fIu)Jc?R>ge1Rb$~(CHeqIJMqDIOU%_G>kr2z41f8+
+N_Cb1h-v7z0#E!};tE7v<_wrLxV*1FKsJ-;i{r@#+v1>Qi>qsZ&d{;&De@Uuj{Z>jqzHD7(!f^9NLaS
+cmyFt60QNBiQk^Ew1IBrk8FoO)X<X6It8+R&2tJf5J&t2+pjmTlg<qAc!aq=Ni=Bn6}MbdoH9Qm96Gz
+@Zj}O^X(tRC&f5!X6(p3`l2Y)gDCvKP}&kU4HREUcM{PyF_^)37(JN6X>79J*_-!1#*m}<?<LUq5m+_
+hKdq}{~m?76rQa-!n#30@fX*P-jA8#H(4?bA7BOPvf8a+izI8i+-TwfP6q7KTDa76V(fV8m2sLhK97O
+vj_Jzu3Q4bgEbK3_c%R;fPilc1siMOGU2nVtbJD(_pdf+yj(@XO^q+}(BP)V-enkjs)WT#Fcf@~&1{>
+8QJ%RoF$b=plg8@e02n>;-Ipm|NR*pRs0aeNoI`w!8_8hJp>UUL^=muYaCD1zizJb*tz>+A^wRNQ{1s
+DZYquQ^XxZFrSo+l01#RL<-T08Uwm}bD5Kcm>xF%lF-K&&=Tr|TQ*bqf3>>qv9ejt+oC7KJ~02f3_cE
+E7W&7@-YgGZ`NfXTsb2OQQo5<Im`A>l(zi%!xt+iiJ+{wBWbxG$DXO4TEf>;1~AKBK^*j8sn@M7Z=&b
+A(cbUA=0;GnpY{jhKdSbVmx=e5LAmB0#DBCF+N3*6onTtBxjYtVid6FG@z<0{A?kn8X&sr1{5rx^(^>
+~kyB(DYT3i-jDqZ4_n1sI>0J~$2mD>$q#W2%G}RqxD@||<D=|7aypzTplXzavBMZMF0e{TesJi0ztfg
+XqpHzM7*oaW;=h3(_*z3NYomjm(BZ)5UJVR*kufo)nQ6>lx8Cd~JLva(y$O470k{X@%QGG|74`~8$h`
+&N>ir-{avq)fm+yn@~+;)?_I5fdM(szv%vQIZ(_0@xhW0@PD5Y-KIkmL%Tp;6Kj#SF=iiRs65vS={=2
+>ZE4p;zPa!9Tv=efRzN&G!3uJFj;S$75J+ib+c9+MG4N{0`$b^RmDoz#>hj=pRXH05Q2r3N+;~hy<Y3
+&Eh=BlSMJXsFPWm;5J7>A*ONLx^{$>DE<M8SsPZD{iEPVc*^5Ioy(I3-CX4FoF>(6R)i!`qtJtY$aU}
+iz_bST1L9{@Sr9?oAu!&bcw0K-N<6aN`gXUufIT?O3EMX%=r6chOp=;nCu-B8eJRB>Ts3Q?MjF`-DK7
+A1A#|k>C}<4iKa6&ywug0mthGrbkW}QTl<wy?iZD*6Ad$=2ycsIJe+=wW0sm4^%$Q$}P!!?faFIZL`X
+x=HbBfE*PoG1JY$+AK8_kXN(5`FrnU`W|&K7p0FYybrmZK+6NX_1ag%G+_IqEeOCyUAI@B?=yOsaIN%
+t=|BpcZ&qh{iUtNja1*TjMg3AtA+U(u~jV#@Fdx1QQseD_ePI@B+RV24>u}!3-3WIif!?MKDJWyBX_0
+6bdAa)6(+g`P3I7a{@0>l27T2kHfGx7#)tvU<tYlMtG;mtnCUiyy%p`85bog-d~P_mzHV<>?whs=z;?
+31PrF-E&2(V@DTzGdB#>#RMDG@^)JGKYFMV{F)YmuiphjxMgRL~|J^XS08T&+{ydpnqioC5%Vctg)B(
+Ga)hE#Hk);S$j7<ndH3BLsJ;I{=PRHNl=U)N>4;{qVyoH!GI8^i`gzlyV>D=MjNjRrXi&)5sPxMzy<0
+1oeNJ>bCZge#yan_`>I&!okVgRuD$k^v9{({t3F-1no7{Qtz1%>pVk*sEj<Cq@#%yUt4MP;gK@_T(*g
+51e9vK<w7bznnS%kc(%=3vX=7tmzV>u7TrYz|smfw-05N0a$5uozaDR_Pn~KBNk$(}WJKCi7Uo>x^<&
+eUsuBb6s|Y9}`=*=LBLtZ$QxwN~BpV*3$!%Bo@54uy_H_9`SLT*EDbVFo;VpjL=IBDJs0Ij+(@vYhY+
+b%ld6y|I}E9?tPL9=vB)Jp{TO}D#@hyUjtA;*wDR6@<l4ZnBSq^pu5so>~2(bT$>N%_y=+O8oiFuC`X
+Bt<`<o|a3UZw_FV9-@wXN9PRn5V>+tq}QW#VFJ;L}w3~mW1M!zedK&<b7y$^bB3i6vuV>Q`M!r^K)cN
+p(v3T(#=6kXfqs*Fq#+{9eZ6@#b&(D1N5s!c$ztmKlc^xI?DAJzM$-V$yzYY(kfJK7AtyvUPFj~b)c_
+~c1_Mu2P6cVtv`w!mnbH7Mh`40C_2#xACzZAI3~-`bOTv3#8+MFQ3caUvd5n`V_FXfq}G!AIBP+4U5^
+`-IwEmgZ9^&fI{fNOI#X9}kPG8K99y&2(@t9+NA?Vk&4%Zl|oO1Fyn&9|G`F)v=NCW2B1%xCfAhj}VU
+W<Xj2bG4N$sOzY9}R|-Lxa3d*&NQ&yK%6ssYvUR7dz<y9KdVv5w*sDnnvW$<~O;NF(gIv3d%JYB0yb{
+c@cVmzySu-9-D8@j~0-MvAQ1~#$XK1y+pLRZzX9pHqoQh~Z^653?+VOZ+P8YfUH7zIb)sh7SSqyP%7Q
+YU)agHsiXJp72I>300B3z*h-5Caxyf*C}nQ`#SKleolTVk6Rn^D_eBvd;LOtpAC7ObItYFQVL6#+Vn&
+l(hjw|F#bJU;1Gzy;!-*3~8<mf|%7xCGXMhJ8o)51oC|URVj?2-TaAcbh0iko*XAI_$QrNR>vH0eW$6
+Qg+YY)iBYGQ)TSCtNENIRzQys8h>CbvOeCFFeY?9<`N?^7j#qr!A=$x`aO8?G7QZrL3oR&wyfeHct>8
+4Ky7&;0*EGQ#pKI?uFQjaQe~hTsYny?d(?|Lpv2o??+Xz1b#sSKImC_j#CatYV&Ogj`$zI}lH@#f@l}
+D#3={;8PJ>%0pMc#tL2p!k7w|q@I#c)<6bgbv+;!lE>w6p=(#()Tc%lw5TF>gMfQwVOj4>i|qKMtbLC
+O1uDNKHju1bO$=I@mqxQbj|qmPdqI2-2vN9$zPyA)!mt7rEXR=-t1+(u`ArR`+2N?Z}*LJ0K2c2MUyu
+giSVq^q!oX|C*mUw{6);N!71A`Miu8(=R7{H(=wkB`Nu*8Wd+d!XoFRKSY79Sc<q2Ri<Y*-IShf&-V9
+b%&6;?27%cb&@}&img<}1H}6hR&}pPo>q6`YEg{7NkAuYWwX3QL!ZCdufaN9ROystOJi6E^pcx_Sy@)
+o$P}^Wb1dmL%C7(@q2w$UI6=m!d4Or`Zx<+4k0+p%GzMmdk%z#?i3TEMaCU`IC2nzX%z_Rgs8L4jR@V
+&`Df*olxH^Uovk^p@(F{zz;}nEt#xdpmo(u!5jnY))6ak3aJ<mhgq-rX(VqofX37GgF!E9jf8GxCg(1
+AX%cNi8<ikc(18dS)whIG)d2b3zKLMA<!T;O0~{qquL5!JP;V$ddb1(ylXez3K>a)Hij4U77#+K*WP1
+_u;~1Tr7lnq{DgC1NBIyU?V8*t@ck^+*SdDw7KY_8kb}37*_fw^-^1ie=Q&pkx;hIciS4u(9k{Jz0gW
+tj6YmnmmM!sj153j2Lgns$c=-W=e=wX`3p1Qn}p(3Dr^aJs;IHNKRVIrR`3zvx8!XO$kL7JhV^Z5mB(
+xGzvca7|&2&48GK_1g3t~PLxSGzY|XhO%^aeY4Zz|P5wew-3S}DXAWj3ftBon57%HkO+&lz)!jPEEMz
+`dbSJQ?qH*INBSVahQD;|_fbS^gBSFF-87EnY(MXO$L;>4;LUu7MCmr-Vv^M3c6W(86`U1JoS&bC%gi
+c-Pk<02lE3P%VJ)twy0GfgshX>8D5}JfkuTzT-20PrL+8_d(+>_NbijTqpRhcTiT;xeb1KEcR#@N=LF
+u=~rj_{uap&g$H!Um?i2y17@QVdAsLPEcH{EYR$Tt0L;o1w+6rC6GO8cdxQlM*whxTb}8h-|tNXL|AZ
+<E$$_8;gS-Y#+hH<cr{*^}9v@to9UPT9!ytCA>X%hR5$IF(HVr$psV|G*(}1(3a8M!w#T5MHW3=Z!Ug
+1#&ZYFj{o$*%*6h?^9<8&m{JmldPr_qSAAN-5~QL$ZZw_A@2E+-qgu1=1{aW4O{2p&(-@=4c+rJ(Ax<
+U7kL)Lwqi`{$XlK+*r<NaFigjt+){3c88tJ-5i=bMfGeR|Wo}p)TmekinRw*2hK^^lkIuL*Jvd%t+r~
+*ai<9{VL2^+ugbnKLN$d2*UjpR|$TlR<ofV`y?L$VQs;J_HqrvtDZ9T32_t=-uktFX^fpf3hvFSwL<8
+R};t^)Y47D#at9h(PM$A&@8aD$wjvVW3!ZMC2p=;(}EReEKVqVG#Tmjm7W6hGb!hI1TBkKgfkVeegQc
+rKnhK1#yf8(>$4-Phrsom|Fpw*}^-U<*Qe(hQVg}Iedr+n!k*h>@`v()W_BG>?tU=u}Y?5*=_C$-apC
+BYKFCA7MTL_1~zOUcZ<0)YHGi>*C<rUS-%R!Cifm`Th4xf(d-(V^49M)^E9%iLFu#f&hJ2asJu?5)G0
+xWpJhL%Y+Dam8&yBpuP<>GS4oY2REd$Ln5T|GK9%9_q&E|3MFS}<_N@7T2Ta!)Q%7qRf!AT3d)Einur
+X~DmSUsV1m+bN<m{mS`zQA_OD?6i{=MK{vCtDUX~tbGX-r2^su)E(gj>dVe0>YXjI*;SJ@X8tI1G8;x
+J@Pq3*o`tWX~x07Q}%o<-5(EgeGv3At8EsTgb5oZoKn)cjvp^ug9;qk6v3X81)nn8{;?B<QbCbHw>OW
+wecAclr_=BDbVG<h1+2>74Js@fUfXkwPM=qrMX{pSyqx310L&zET|r)m1#6h&li_bc!)@mt*O1vxcw9
+)O*@-<Q=QzuR@!@7y}*`AE-9lTV>^PZ|5QO&=Jl#}JtulPW@!&msWr3)$qaqOET>9jE<SXiI6i)e%kL
+i?oMo!60DAPmSkA<IM#gqLTBzu`lW_rxA@xoi9b93%SlNrs87k^d;N63*0W$(JnP3uA5h?Kdhw=V*U7
+~d(?Kq^>&?hV##>GpOW)c37NIos`^$rqaZbeWidg77CtZ|*yrXOjCN{DwEG%Ja?9R}<lyHJj2I>XMb=
+(<wY@1T+e&0wkSAa?m;*qz0;P<EX2_w>Ii^BlM0TngMfX|(Bpr@f;to__Vf;j)V!(b3LC$8uOhxm>IB
+`Do*u!^$+9Hy9v&J5-@i^R&83=5&U{sXiXh?^w+mV<ujN=9H*XjFw3`9YNBlQW%S!CY9Rm1Jf$2gvV?
+MR2aAQapy4V4AxLJz;4eDP034*6+9+%&T&IP9sK4|v4zT1aH$q0phf|PRcnfbJ?Gk{?%54A2oOSV9y}
+bt8Cf?T4E4*Y(lBH^FOn>0&MVewP?vJH#G%$@4tye!102XQErA24V?&0ald&y9()kW-2YO^s8Xiczw!
+AtqYDvl)Yw6+&<1yzt9*<2t^ah}TPS<nRX7?<oo(5FvNdt!3pp3&o7mA960BA$W^@pcVHVxkpa@kx?l
+{OBWb>OJ5^tnIQoOdO6DR^s_!s71Rl;jaop-<{)5(g<c&KpThRM^`!@Is$ha^kP(r9^Ly1h)N>+QE<%
+{L51CZ%(9(Mx4SXT)Eg1fY{DJXJ|HW#hp~?ypsM8`g3s`(8IqP6b&Ryaf=k4FFDLhk!NTUr04kFl8=G
+$&>)b7efpsdn!(6}?jm7Cu2YGj$q=2rCa-$ZRS0##$l!$$qrksF&F|^3#U!eZ{Jy7_;vQ8?e&16|*h*
+CrBDP)WEWP6~nv-KZFRep__z6s^-FL@_{}>;3vQLL$^wq&%vF~3-r?<bJtjEvJ2G9CZ9GuoqNAN#ZnZ
+QDc8Y5PFHi%BPPUAED_H;?z==4NtQ*XXJIlWy!dlrqb-dE8O-oZEd34rkT+2E@lcz`;td-3<XhkxHc+
+8vljqRfz5_EJvBwiU*~eE>y}xP}!N&w^X!l$dpMqA3Ql{0z9id=k<EU;;rmM|jqK{;<7Vm8QoA*-cU7
+`K)533Pz=P`eaXvX?q48W5Nv8PUPhDgp$4)i@0dQ@IrBb@p4k;d|s5+lu5ZLU`^QyEgz98GjcOC*z#L
+|3~f?(=X4A4lTq-zZ_Dq0mA?1Ucxi{!N^4R@tsp>D`f5;=G%tMX-5&cxocDiB9o1<g)lqkJb)gHD7}3
+~YpnZBF=P(?cb*HJRL@ZMhyn2WdC#=Yx(~&%?Wp2VM<4d9(ad$)_VCi%-h4&HdNDpT^vro2;gFTMpY2
+88?wn5-@=*AFF1!p?kBo5x!5>CQQ1scXph9)G!$LG|lhRDmeaX1cLxM3`agmUUQ!yp|EN`hkci{OW>n
+3lI-mO`;N`#aljwhs=z-ag(&gaDpOh|h<Z=|m+S+8^SBg5h%Wb-kEz#3P*rXtCqnri@LlhQd3^GH)rO
+(`V9|B!$?){?Xo#T)Wh0`mjVg3Z{e>hEP^v9bA>7|FtcxOQ<Lw5B)d?&{#AI{~ZqC)jc>8C=*Y5aI7C
+7D*sy4jWgWlKoox1NiAv<r>4POm~&9?DEf-FN;zN_gtgv|<L5v9#2oU|Po1#MzOx8gPPKTcD(1Fh(eS
+2YXc9ZLPu_Z#%+^dt;@%`x9fg0Q=vT0Uaql$rtx%Z$2DvAoT}@7M4_2KF`F*YEAzWctx5NNJNS@u0LK
+o76E+7cmdjKkhivESNw@HB$Mk*^yk}?odGDeCel2HJw-i%+heaLdOw(ZuUrVUur=cTNoj@L`n5Uyg2M
+{!@?CKcumiNdcn-$*px`9eprDHq=syEe_!zBb7_feyGMmRzUkK(G!8cRHg_#S>6=n}BL&9})B6{k|Xw
+ARt)InJAJ2hE5rIyc@ddR`u^8m*$Y3LnK~uip<nPd{Hpip~#93C4KR>svFvhlSIYM)wn5Tb<rCQ_Nub
+O(c%FHflD|uD_}q=Lyoclz!hM@sWTE@VhlNy<d-Edz|{<kV6dlTYg~&hL60dEfBFfOlb?Q4B57J-Fg`
+Gmq<7HrC0t)$50!WUINMOSoN$!=gm%V%`iUdN5tz5WSsfn4gmuWpIo+O$F3^{#4C&CcwQWooM&5nx)?
+Z>Py;Gg60{S`(s4HBS4w;*&EI5mWey_Hlf@e_lS)g!M2eNq^io)e1;~+NqJu!)s<ZIsW<ZG@uzlGUKZ
+DqBFxk1;$0INq<#!nP;qOfBg>syY8Hq*|Ae<K0SwG2;?XhZxQ{UY=wu0*T)TPHO#kW0k|__kzCOl&_&
+SGQAThbGcot5uS9`_Q(kV2V-QoZN5~sYgbrKLa=YU%EL}OFgp2xQn2ol%XBUy=&tIMvth|YUXmpFE+~
+;FBrIfv?Skx?8?Y#{TlDHLr+MpQ<--YkyuHwQ50k#arl@vET0&;Y*aV6(r~o&=LfKww7o3&Y4=OS6`X
+ZWt2!M#INbm5-JRp{yY08T<L!4}k0nQ&?VbpulVttp&GkQz&z?mm@%kD59G~fjPX|v2>)lN~|EC2O(|
+uy>J=hzp9Q@<>_5M3Q235E|zl%<%r}0;()34ggwTM5*>VQzBzEH9TbiI(X)@LW|a>fRAteDTxLN!h?Y
+~}V#^Z}$GD#}0~?-x&+SR5Td@D;TrP5Cy_yz9H*vL@T8_S%V|9t~Q7NvA=TI7C;9O+e*P(KXdXH2f&4
+W$`^khKw<AP+w2BW*nUniH(<CSac?B6yq>-lfjn($7QsI29#(~H#6gLRvED4w4NmMv{R!BPtU_)VE3i
+lAN&;5AIj6`pEqrHinA8vNx>N)W$0A@TD!s4(TUzYlSg{<5M<r^zhDH0`uod)iHtLIK_RD9ld#B6_+%
+Unfzp~`)t77-Q&K?l>^cork8j}zto%D=m9DN3-YO|$*CnYPk|(FPfxa(r`7DQVio~@Dcz=2F&(nH<6$
+gI`2j&t=#~guOR5r<I?#$2a0D~#A<}R3}FeRs~E`hp*Cv7ydIrCI*i{N?r4L(cb%NSl9ut{C7qlbl^|
+59oTPaV#J`4+UOlM5u2LL>+;$})(a$D0H0^%f7o7AbNa9OyJ9CBe2eB}(;fQ(72g-s|4<dxOHgJYScL
+<k<X%YFb?ibs9dYPeY2iW6*xTqEeldPf@vaRMMRxz5>|cnd!^L)Pi`4$0Dt1t24O)JB%_SIZI)CxJ#F
+or|oYLj3=_asNqPV_P0?8HJ+y-XGIYhrrsux)W&l7w7Y%w>!@u>ugz5tM4b3!W3PKJnxb&R%FGRd6|9
+Ru*4>b>MS)f<k)rC{sD?_FdM{d?Mz%MqNt;ItP|qiMQn?pGD3G1F3*DB^GSe3gqA1!0<@Eqp|BKjHKJ
+jf*-WG^>Kk6<n&FF*!nUPSg6FfIfw_l<t!Fy3@-%A)8waR>q<)THEyKF2`f|eD&rmmz7W^})@az$Va$
+pSAvE<i$6DI0`#*3C6jG|No}Dhb)k&;I;b9DI{~<RKw5w={wm*2K&Ob8=BPAl6h9!4=<Y8=KsYmXn}K
+{nGEQC{qllNUrA`T-v^!V5g-BW-P$7CNShhvwjR(sJ(YUcX2ir!zXy`n$7bK%$4Nwza8QAzRkmmxB#W
+tZpOS$YC?*GWYR2SI?fsuEK4MX4LFe|k_U%NN?NE`(yys{c8xa4lga~CJI5U?=4rD<aT``LA1%>w%`o
+~SBuZO>{|)e0yX+~J<upD>t|zq+3C4LCq+T1w=5+F(kD)la7x6abdTV3j_VyNtFkPR*R7VA1V}3W!Hb
+e)j!4x*FEYizp(ir&#1mKf;1OAgjF|mP4z=KKM7V|l;FRfa{73F^Cs0UZ--@u-pJ(IZ4iX-GXH-3w}*
+4Mqg;L__)>U%oULiwFNB4qpeqv9}j(7j<tV6?gt7s+Oze4yuFWChl6Qth&TG-aO3$)VJyFp#7K%&Mq3
+)mJ2zK?$i6N-+kS5AK0bYnURHf_z!~GTJC9b*h$k83*c3)S*7o<j(JSKV3q1FmEBYh^X9NrD-nDTUCn
+nnQqJp<*xNd_w7Ns3?x5Z5mp4syf)4ni}HscSgEr&Z4eU<2NPOKDAT!YCz&U1%y$2ff13e3+{cX{=R7
+d`x|uLbLsIZ#I+g7_zyMXB)1f!|sLp@Uxt9U%^lo~kyvGsFx~cL<%&Y7M2pGD#hbiKMMxlE^#!Spf52
+&gU&%!<{bmkgoZ``!ScK9c`b!)nVj@egbO!hf;WvYlv*9Xu@qT%?I<s^f~b&`X1zBDuy3*6TpkWz)(+
+dH_lIa|nHkP0Z&#C4Mi7H$lnE(!Lrvt8^xe%Xy3hibG(WFIoV@P&@z#|R2_+QW}^o|(D37m^)???UU(
+Fz6wvx@pD)A|q^+Y9r+^Ys}m1Bhar$Oj81bn#6Q4U!23ZTy4~gb4+A&uB31Gu5wG@xp8!3UB8l}ExI1
+6$~+0u8`=(Tiw?!B?>U~Yzi&_J@^xK@({>jOtSdz6v0)mQ7e-;HYzvet7>&r@^c1!D2+eDZZo$0@+{%
+X8u+05HjiH1Q+Jd>#X`1`J75s3;$%$~D(<9_on5Fc!>EM(UeGQX5rxV$21q#4bfdCE(tTYBtMFoPJ18
+It2?vy$P2xXiTe(>ak%1~Zc)SRP}7S!1?-MRiik(3&MYt0F*Iz6vHsF~3=^pF!Kx?Y}MG*(^Bvmyj~*
+tUmL4>^bX{}r<;Y4M*L;!d)J@Lg$OfhItO+9`n<SS`!ID%t8KIqIDTG?Vtd^ybUpFt&u#6=`NSrI9@Z
+{UgBLC&QUH+iVz1S6a$a*&!~Oufjdiz)}%dGT03E6c5DV5ji;;=kN6aR|Pg>gxgCejBD{Y`=mT)H8(T
+P5STbFV@gdD!M7{M08cK8@fhskz=sP||49YMtumF{jKGCGmwZ_`In6LZxS{LxjyCIlUn@QB*h4C&ouk
+JX6HcAHa(UL}R{VGs6`fR1SB`p^;E`%W*LH8M{OJPSvofeOqU<N}T*9F6>ztoe?k|?RPC7x`w<0`4&H
+*{``UHBWkH0>thb^tqd*B~2p$n6RE88&^jF!DAv9cB%v3?_)rFdc4nkYy|vVVGCcC(I-1MBkCIk>Cl{
+AA*NQGl6JD_=A{#|vYo>Y7rpgb3ya0kBjis;bU2V0Hi(83IFo$f8Xi(5_u>eULKK%e3yC3n!axnrfD2
+xXuD?G$<mxu+kdf;(^e+$G7GTSWa&-1xYM2PAC;U3p5{B<Fkp<{SM^XhD;QE6l5;v%&;}JisRX!EUi1
+us$|0Lku>R)WEJi|vVP+?6sBozve(J=*+bgo?*8#M2@baDQP&Y4RC^|7(p7at9vw2DjOeXzmKdpDBP=
+uIDKOv+2$ku<H#=n1lGfW=gh-Ey_GnZ)Qd!Myb11NeJsN7Fo5aJiM$9sc=<m`yj&r-$@zGVQp78cXLa
+n8BjrJ?uW=nTu(rs)+isgOL6R2``UYOKc7c)Wq$FOJBP*{ObvJV`C$vIc)4&iGz8Y;rat(4;7LNQ=H=
+J6@J7aiKgNR+v{CzMcHC#7WSIjO3Ub<6mv@xHh&%G*Ne#$0Kss?n6w(tc8>o@A9+Ogjc_sC*6^3pipN
+X)xlNd|=PDv|1|p4wA2tF~)_^>zd@asc=W7yNmZ4d1Y}+O6g^Imrq^NwN@BDEr(s@jz~{^vbE(TD+P8
+lD-41-jwzBA$3!%KPj#XSVT<<|Np4}~IK{m2yqV>m-{r~}>(x~u6^T9>F?7FlwYMyZotKqUHf*O{kM)
+{L#!x@t`+(xdBkO48WLia@yNrovDB_5vx9{W`kCP5#qXK{HoOrC8sw^(YK>tEr!r<syYq%Y>wXp%+yv
+?q&c{<IKxU4QW@Ylw1QvE9_p1k;+!r=f^ey4!pRXpWv4k{~H1!EoI+Rox)ntmM9DJ0seGw;}}8_X4LO
+}o6jMHix@*AWo=kvWU?!^<j}U)d`~`?4j3pdL9Y9?=13yqqAJQ@RIinfaaE*V9yAsx?FJ6qtS(kW8Dm
+P}H8>_~ZoZpnt}qgnQMf>i5G+yDx)hqu{wCc7U{sAq`!%?dJ|~L5AC>ddaY-o<G%|E{jKrk=l&#BMl}
+C%t=@GYF9CGim1X~jjJsyP83B-znlOYMOU~=ctheY#bnhW_ii$<r&IrlP@8pht9~id8O~W&ME1j>{;6
+Sk&fJst+a?E&Y+v8l4Wmo9Nz-YjQC1_03s<`tMmF{?Fg4W!J=Fs})r070XXp3#oo9yGafdtiE`p!1C`
+Y05ot<nuz#{5&=`t-SwiX>ufR($xy7-LDdD$hTN3J<iMtywurkS61AVxADQ33E1&C_b@XI;u_7JoqJu
+v=R__p6&dqG+|q({8sJWQDR)Dg2E)o6L{B1{%;Te~vPHNp^HXi0JLT)7T@#JL!$hGuhqsa9VaU!?f#3
+IL&w+`8N0^biGlNiK7nx9)sqBw;QGs!0!U-QZo!NS-|?2@b6zpr8i8kftS9$ZUqlu0%_a(PO0C*j_MJ
+f7NL2xX21@h_XWlsXOzInioYW4e$M8UQ62ud{2Bf^hktIba*WN|KHPb|_x<j8_s8SicNi*pged~T7)r
+;NKhxbe`1Snf7wS9x1&Dn<EG(sJp7UR5ONF8?1kp5-zvDK39Ir9Oo!g<@CMOyHtfbbOm*{DG@5a*Lem
++d?y9tt*r_E^B8;@k3yK(o%IfIMF-JdyjZU%0t!n9pGKLLSI&`sKW;^saxi}1yKxu8avSHCK|Yi?X)j
+IDT3*9cHSY#$0?)VTdZhR8Wj!-LZe&qjmE8PoREPb55}xS@Nu9>N?2A(m=Q^!z@cCZEFJez^G7dL_w5
+!)nWX^RO26bU0ty<auwC2;iY@@~rD`1z!4FF<Yq9-{ap9i(a)x;cvuaF1E}smhRee%1DOQ?m^33|C7z
+}!UB&(fIf8W_MQyyd|Ay%fu$q6<U{PPtLkby6~N!4vKkV`K2p%NRolM6XwU&miUjR;sGA}8;XMMYl^*
+>Eden~9Co)!~;rXt*`>T1=9eyyoa%xA{KL7mrtC#H&e>B!eXyKh+2}otUBnai~&;caGQ&+pvDT5@-Yx
+IXm125u_?3tORGu)lxguP~97K74FVeYH#qn*7yOdf|&af@>u9W!~F@Fjh?sXD_*+N^P)V7^*X02Yj}T
+wz290NA6#paBT49Nl!#&?h7v1!%Ve$=G{u4(%>q0zwiL^(|xSW0q!y)IWQdH-(uH9t><_C7@EB#O<xf
+@=gVv#+{daU@1;vtfITxI30Lpg?&+aPzvf!0?fi&@9j%YpU!Entc<0E%!#S7lIfP{4Q)XwL8DG3uima
+wdi9@;{OT0DNtfDVc%Gyum!PiOB){%-!K|p}U{Ct*i$$KhVPD*qJss7jO0hVWIKiH6b<@eo74*)T>%0
+%(&njy?V!{fSH+t9DQv@ac5+2vVc~YUm`2OAAG3$u90)B`8yv2XM4Ts?|{C^O(@v{d~*WP<v$f5$0=K
+Z_x-tGVJF6@moolyqg(IzH~|A^n7Z*F#XJ@}o{NKmPgCtr>PLhJiN1s$F#V*yO@pr=rRt}g~;zadR7w
+T>C<cWIu?YkIe7znCIs>Hw+k?gFzvsEr-K<;HTen;9(;=f94mjK4(k(If$v#5(G&jS%<Tfd>PFG9v?7
+f&WC-5@B`To0G>O4?tV8Xgc)5rq?Y9#->RzsVK@?-x4yZx^%*)IOGoH4H{FYpK*2LasoPE>DvW2tHJ<
+utTB9H!YSvTyr1UasB^&{N?2_rMh0$^ecC&Py4E#R%4UmMPli2iL#CdC6|oEsP|GSkZNM+QAuGA;B=X
+Z&8+fjH6mcEG<PDxUdasK|U)|uVuk5-mJKaDjXdvDUo(An;uj|<}2sQ#uUGsTQgHK*ggC|c=*}Ylj<v
+^;i?lhj_C0Q7U!c3}u+C+-fW1N|roLt*CecL%Y(x~>)=Bux^=)aacYed_&Df9U6nq7H)eT)8EM%y-l2
+ug;!sV+!5gil^?J$bwJ<Omi3dUHt^R_QJdJUb`L{6o9P+Ye_eowPFi8s6C^kWTe0;>A|$IJsyrpPv5(
+|Dg*eQ13CtU6%%Jdw^zOw|6feE2P%#?Sgg&XgLT>L6@EQ#^0myHP%Yw$Na&aHi2H`WzyU~U%2>&v6{9
+ey>O!jN<1IHB=ruEa&yTkD{;CR`81uW)(rZ0-{xuBxi-;9?;c(UQSy)}(I;!X-J?7;MMj=h(xke_IT`
+L>QI>6X$Fb{RmI@mr{Y;!SDM60af8StYD%BT}5Z~dqd3oMFw0XF<^LqU4oBhALN7PS$iBA6c+u75>DY
+_@ebX&ssaChhZ;So9#eN|5Wxp8_r{N?QQ>FLv7@gIKh+gS_X?cUMb?PF;2X!qEy{?C(t{&M#8^tWG6f
+1#HDq*GC3mw-FD_s00GH7fL}RD67HdPP+d>N(wy9z1<Y68M*L-aH?|KQHi~m%qhE$}n#iRi+2GZT#@X
+Z2&>8pCBZHC)E~o3;3i)PXRqzefo4Ym|<=-bwn%4L3CIFn!a1x_<k2|*1^)G<L|?9meq7rp5p6MRIaO
+QFto#8=n|&zxA5`kspEF;aLFikp3AA=Y;rZ$4*^@vlE#fW^v+C_gSMYt6Ek8w?<kADav%&|4xM&&y;c
+l0Mq10B!jy!j;oFL9yc}F-YV?E+%KZjHhEV+bTJ9knok7bN|Hjw8)14sr)0S0qivMYwxJaSe#Y5xUOn
+XM8+i0fFE_NF>X;vlEY?9>SWhan|B!HWhXGw5wvkiw~xAAr@jynsnZp&Y_MJ03+YxFFfcvw)x1zp&>1
+fqP4b58D{uRMNO>C;oExMB`+MR+_BopW}YJc)JNl|H=ZzlNhdw<g1Gc@r1`!PUoo_+e(aC{|W*eXS){
+h|Z{z9LMbf)<2@x$HxapulWc)`d<E?)T#LlEq#za<EyeJcjuBM+&eIjIl(FmACxD!pb@wo9dsiXT;8M
+=riiSANn5SnpvK_gw49;45LZ3~&Hf7qP=vucd3GK<&kdqXlJO+v4D+POtGJd-N9?N<b`%FdMaktE#q-
+p-E0I05jFgyt0IMwcBJ?SFja5@-x+z1+FJScerdRTw9*BChO?%e5oLpkh!4<ZugrB;kNFn?KQj8N68u
+3gKD?d0^Dswsv@<6_$El@6+&fHeH@YzfX$ISxZ<uu|T3*4Y>jS6`NT73Kk1X$!mHlRB={YYj(oySK<Z
++7@Wgg*}s_mB5?_TP-*`OS-$9emY|R8SVs-9H$=+vlSGE2s!?Tv7~9jX6-T4WpLVa=@XaeS&_7nA(7b
+d_1{I)PYf5PiTIf^1Y09Czf2p#ZZKo`WvU&bEj_T!yfJI9v*{I^#9)P9qxX;9BHYnQc2d)BtaZUR@+^
+{WU>m8{`L0J_~_l<5+-RodlJGj4-IQULRWujcD32V<Sm8yZI#T&%=i)h={u+5(y+DY%}MOB+<bvv__5
+_*q;bQ212AbSY$Z~242$)}1DOX@UYB*FMBr2sSS$e`v1G1<y?+m}L(v!y2T#k}A`&5T^!h#U&DTF1`q
+6GHx);HkAJRKJqFR=a$X!#+s{y+{W;Jj_OX|AEbn)ZDjqM{eU6wMI1NGHY$d>iyPdkc|1n(F#2PoOue
+~J!2rlO7?N+f}~B=~r5n{hS?T9Mx7Y=9M|!dS~YynH^ieJFGW&8o)3fE!`u7&kwMoPW2Wyxy2%JDD^K
+f<_(egd!&lffHL(zG%)?L(NFG{W#dJfv+*sMvZFOc}h3TQ)!IRc11oYRtwy!kx*zXJS25a=akt0j<zW
+QO$_N(_e-g}iY$0g?<v}9Pj%-R-`h0Ib4^Jw>x(+MNL?L-3fu5VD<RxLN2u*3ALvLTPDcz9bt#)Soje
+?NZqS%ql_h4jAgHK%7$*f~NaCg3p&c5o*0c1K-u)|x#55UG!K%<(-kuemnd0Ey@h;*ACk^G>q3+9^sj
+N((`0+|&(`_#FljBJ3EM#D|5y67<{oxxDm`=7KgKD9nhO%J3qs{Jg%6AvQqL*Tpq`K_Oy1=%#E27PW(
+gKzjLR0Sz9-26mJ|U+)q6A^-hrSh~_X<KoR<H5D!7-f$<RiV8sCPHP43juq67#`;Bw*}Lc+-~HF^JNS
+3GPSMm^AQhQmpS4>&I8=x&VBeO{ctB`SDJ6<_Qu;fTRTl5Rm!t>8CF#k2>Y1!4UHq6o8>b#hS=e3&7X
+MZ{MgO0#5BCk@_F+ehx4|l22@a;An-3O6>$i219`Zq7%dy<<sSyKP6_6M2M0`Op6hkxF{_7ND(EPG^r
+6=6x_q}9o2PBr=5!{7-&j}KqeQ~QWn-a%ChrCmQRU=Q<Q}yjWN@Nz*3mtFjI?JL!53jXe_e(Kr6M-+J
+>9auCwAIWtPuDW@a^QtYl?`lH?}~$ec?|swXgTlSOq8PlxSNwbk;nctC%A`)2*{U`JB@u+>uQBecg=0
+)`ZDPxNt?SMv#4fcjbg#asdh)1_1Ts}vuMHr*{oDJFX>@J+w=v=%#Un4pafO%zV1mBxi>-nOlSRiDED
+A75?$S;<#C8iu7P*e9~*xp^$ifQ^$03(}!O=iSMs6X(qZD9B{oCdNyzJcW!FMgiNGruA(a<=$Oc3y<e
+#wqrt$M#D1g8(Zu7a@FzvF@C@}+hc9D{($j*)R-INu1&&wN8T8H$xYCiXnppjGR36JtqJC%!T$z_J($
+ZL%xRYYhi_zh{Jn6Uk6)Qu#=rVJKd$8mxXzg@+dl0VNQ)}-nhJjQgl}AuPEY6&WD2xsukj5FcrOc2tF
+&e})ufzB7}q>c?l@-89rZP|M)ch+rl?U!^oC5V1vO}c6yZjWWDJOlpoasx(=-L`f|A9d{?+FGd>MaXP
+fP`3QRS2)nIO2QzRXG2QiZa0ny-K~o<pY6f=c}8aY#3l9Qo6l_Yd$(OErHLJ@3?8nt3$3P%ZL{EnB!)
+bRrH>un>x8kurF&BepEg<285Z=zDw9G1m5}zSl`-Z>6|TzQkx!-$<T9)T_c~Md>dps5A~<m$zumk*TN
+hE>6=V=k;BR(e(hB{_t>jXaDeP_O8b|T`e@j3d=>oQM;X~gQI(2d@Q-kp26VDZ9?`?s!=LZJaWShs?d
+nx&}`dYfdtk>0oZF*kM0nHE`L*E9zBWcG$3#|t*QcaAm@^#fxN&<(|{`JLLKbX3r5dqLEZP#L!~y0=F
+#`)IO!xH!ORD=X6PovX_{v<%r6vfkp+YsW<%8%N(9y5&B2vQXxXN7q;bY`5I1c=UPx*DG3-}?TQ$JJ1
+8rRcPi-IU1rbIUvwn<5K??|nherT2FDYoJMK}o76hrZp`OOSvO!1s(H^GWGcnnH^G^Wf`b@7iYsB6r%
+J2S#-HIWZF2d|L3e;x2F0cejhU@|^^%RIl<^6x~I?_@CZO^Po^ZqzuB0ghU&??xjJJ%jD8)vEdaoWoq
+iBe`^42X;?LqAuPF0o7;Rya~^oa|u+b&52y!$dAZ?hE!))g7Cd{C2aO^HYsS+!YwGC8~rjiGaxS+mrg
+LhT%Mw~g4_F3I=6TkkezUK-mktdOq~IqWOV2nb1?SBrh9LD#h%h_ulU8713y%ho$TH@fbyzO74nQf77
+uUTF{e;!HRk-|p<~Xa%Ufj+m$y!g(nAKT@}J^Xg9kvp!}aK)B7ibVv>Nmz>?WMl;YBR%XtxwwT={4iY
+kD9hSV5pvu@~9pLbBbt0ZKCFMj7(^n-A1^K}y{<=Cd0On*($;gIhj!3l6;1Pr|I2@Nx)W)QkQg_6aq?
+X?M+gafk>D%xY~S!TU0UR)^y1{(QakhjYGyM4a4CBZJ8%0u^wl6!sQ6j$tdEh)RbCY<?++L6p<YoOF!
+Y7Y@*dilRnd4x$qUI^+9GGYVmF&fHTVq}>pXkYC<}(SWa9Tqaqx&)6kG`6%C|b2EYap^Q~aaA{$jT%Y
+mgB9j?@J|qE3r!O){5Al9axIO4Sn{d&<bD@CjtV9!s)DzXFx|!WboP?2<wF5l%ScW@lqbJ}Hvy5(V15
+?jPc_DrS6V%CBXeVZ&qeiYiA{F^K{Ygt1YEO<^UDgJXDSsGB%;<Wk$AR0$!5Fk-$q%tv!h1}3N7u$By
+V~DDVuT=j5*<zYw@&yLr@1GITp{_-=(S3E=5uoJ#<+^-EZRQZEDyV80R_?mVQU$6o!<F03S$bLKoRS1
+W@EZ4ENIU11*tMeeOH~hKq=mH>72bM1)}PfA&sS5oV2lResy(KU2Li4xlW`C)web_kn&AADf8IeA?u`
+jPtNPeg^nMUO|mbyx06PaOj6NlN!6hDq+t%VO*T@?ExI!<93`N8{l!Hup_CJ8aV}T)ElHhCulP9Jq9`
+QWvQ$es%3+esn}teHkyUsoeJ<{u-elTzbHh0pFPxoms1KNRRz{?ml!fleH~Y0doHo*6%%pi*3m*nbC6
+nlm-YmNbUcG>Jwz}R*_c@gADN_UqkY;2^t9{m_#X><;0yc=Ui`Lae2meXuY0uZ8nuoFN6r)^{23R-Hf
+u3Z%M%OJ;=mIV2OiH$l*ONu1)^-vZ5lD>4>kIa{fxE%!Ea#+yeZD-iJ9rVJ8lwlSk1F*ech0{C8<gb3
+kFZ!hMhEEBuU%WE3(cr=kuT~igM_XDkI#r*7X>DRnI(nFNjaHKy;ce)qiFduJ|MY4g`r7c(vkUc?_l>
+He>LOTspMI;n&-IUULjxLoo~nV4UZ?oYBDnHPR?LEiZJQLlpKvAe=$kbJXaSRwvS%?4)}mO!-p>x{1+
+Yg^Y}K&tOlR6e70&iPgI1%{d{Z{i$XlIglbWU;R*)FwTFJZY};j50(4q*ZQ{8E&=(Y_ll{zh{F!$Ify
+8*HUZQwnhoW4wBlqbAc@iA#9t5v8Un&8!7MRx*aV<(qH%)Ig=IOk~f7Uml#>Sd%e7a7l2UZLOt273-0
++nuk9G^YoyEEl%vby*VZ&lP6gy9`X)kIGN>BL&l;`Oac69-lZUOG_+QkZQEbhu&W09cY}Wj(k%*wc0p
+2Or9|c6+lRc>ozm+-Z-N0o@pACRM6Jnenc`Dmz~w)V|WJNOF0^<#1<*TapTR@YRGPe7B|uXw`|P1AVf
+Zp3`A=y?9g2uXn%Me*XpoGY|HU_Kx=t{}C9MPJyxv3POxzrs3r4D&^kgw(9nqw^$2{^;@+Uh2-a1RJp
+r$V?K$(e-f^H@k!6M^_X9U`N8$OnAfBh_A7l6l&uEzdd$?_9fEX=3SJl#S*>-h1g0$Tn6Y5gwyh3sc8
+8%8kBpq53?JHjs^Y`smOTLn^xIi?#YWQoiMyAbG95V8WNTHaC*5^C)V#_;M^ez|s?F0Ttm#TLoG&W(K
+8F^0l7~{JM0wj{LYro7n?rP<K*4n>=vkHx7$^Ky-JHpp!8o+ZbJnmI8+GvH)Rzn1p^wudCPxXoNf_|-
+l|~a?a(+DmL-HGStZFC(Z7}0Ssp%@N!T=fH?~A*TdAWSNeB|SLUG)1kAB(~o)_tB1oK_NijXNdu#qT|
+7>zst@!twCTW*4pxoT3Xjq5bA(E#R>GBoF8^h2D!1*w|0+hMMBg!6*vbS*_xuyEA$4$o+qWn&h)CKoG
+N!ho!D#SN@hBpRM|2$_*G_B^U-Nu^~)T+vxB6DE}2(>YkxNFiWBIb69^nGA_%;8Ux@!6D$|7`p?r6vz
+1&Wlmc(H9miE|-mfD6uP%XCtALXWv1dg}(-9s%u|u(F5oi*0kI_~C6-9v@LmFUATW=xE2Otw{q!!#xW
+N(*FdgVc;?cvg)fV+=D)ci9zUq|V9R<S-Xq|`<Vn9P1kYG<H(U(b55v4A|NJ6(q@;U{>l=jA16<oB(3
+Wj>Y64j%6tkC_9}w=(q4KC_d(n`DNP;S-7`h(`$auJZDLp>9d*h1m+|t$XCRU*@%v&0k-??yGOmV$0}
+ZPibd?>V=7td&?uaJLSzB*<SCYmFq`QV;HD@nOVVuhh%GbtPXjh<LH&*=zwC?(!6<3?Gm&+EE6UY;o@
+u>a5=ou#VO~ug!%pXmB|?`S(aBY)<8`?+oNjj+IqaE0#%Y>Np8|H9adwTBO;yAafy<95SIZmD-$|NX<
+L`rlpGf3o2Xi2(1K){cVxz)6-8~L9Wjvmkp(YI1DyI0GwKgi0wDpS`HO$IbfV2wGPd)iLHQO9Hgx!B`
+waRu&(uY;I)3i?W}IvWd~N5DNnK;0-z+Q23g9-kX>whwC@K$FO;B~A8T!N6gN%oS)ecc@=E)9J^|(F5
+MDai9Sjq3yEv{3(6mWs}FsT~r;&PpE47^S=mx%}4U#`*clwDq9(?I_TonXp}Nxqm0lKV&EM*(muH(<g
+S8WI>vh}S@?7^5Buf8-gnM+g?@f}A!3w0M&o=)AbR;yWZhCX>c=3llhLdx}Ahm?AVN3qj*AL3$bE&o^
+1IkZ8GU;DR*Qcx8AJi@<=iXtK#7Pb%yWNt;C9+P5obEl?BE*Q)U~YkC^x*vNYJ>Wk0pCrLiPN`mMsJt
+6B78p-PQ7x8E7^`iK6!EO8id|BSsd_9H=CBxK5?M%JRiuGhR{p`~q`s~y5tkHF#C);no#^=d(5`6sPv
++-x24uid-Npt+N`}VU>kB33pw0o8S>g5Y44sB8F8>WC%Lyki_B)6O524pbRZ?QJM!Cght`Y@p+u8}`#
+=BbB@Q-PLrpo=Tlu*w)vL!qvbS_DR)9T}iW6isM3P(tcDYbk9sh;o~`&InHRqA3<ykfNlT4SoltYWDI
+)7t&{+{ytbHRw}m1Adj373XW1vG&`wE%sPnEw#Ku7l%F%dQ>0rRAN=F^_5Qo@>;0qS@xhzz<8Ss4->y
+o2gtWNHD)R~i#bNr@Ne=)?IByINTK%X@e53>@xE`tl;bo1h7b`X9>iy%7Kk_M+<Q#*TaUz;h;H%)>F|
+rsjEW+HzIWsf>yiF!3SD?(>&%U_EA_oUM#L@9XNO;Un1ydm2z#J?Wuny+Q4M=aA+V6`@61_oBc(LI4_
+bSa(-mK)|#heV75GEb4?@lC^YEG_nwxl6mb&fnSAvk<JOb~8_Miy2+>Pcb6fPX5$>Un|}nn%b2s|N@I
+seysy_0=lRXGWG#p{%CDe6VH$AwWffW?)=I=@86=k^0sa3$WNYbStha4+HT4T|d9|iY_n+NyLTbP;XN
+nSw5IVa(9D9mAwAc99_Rni63}#1-iAqZfbfjzxd1<*$x9Se*{Md+lR~rU%6ZmtUjsNpVX_E;z^CA8Z+
+*U+~;g{2gGq%+fqk{UV=8mSD^d0AH2k)fDwL$wU1b?2X;OKJvO1p{m>B!1Rmc%nZ}af3kEl8+Z}*tey
+Mrz<i(Z~D6<y)AfexU-@8^0%qbRO6o04#gcAqCd095FxF>TQmGe9W&Ef~XK0cus2IZ2&t5oqkno}J;g
+Q)e?iyBk{npam8_Ey_RY+=nRc#HOz7tcTa{L?R9e)j3-Tj9$W@B%pP&o5rQeEIo{&6l5j@#@phKY#Vb
+CcLDTF0_qT#lsj$E<_X1Cpi6Q$;UeT*|-e`@3M!LuDPmMnJ6*EWid^vsf^FMP<LHHuJFV}jhP*_qG2)
+2OJ<lPGr6Bs!!bM?tNb`(w%{WzlN?Sp--&Tzwe%UcG`YKkWy5H!Wh{AR0M5r%Y9$Q|FzMLol=qzAF=c
+6P*=R<Eu~tm+@QV8^!)N9$W{PuX@g>l8z65!ow2i#bWn9*pRzt%yfI(y{!s)FciCZyd0*OsM9$!Qcb|
+-pTCusb24C_T5J;FQLhp<SWHm%<}{TG^o%2Q`$e7t@5?e6jTc%PPL?R5x2+Y5s&QYt_>8OlRcl(tO$M
+_z#1(Y_#cX1Ma(N^70ChKaN6TRNHa!DG}=5z<%2%z!kD#=LROOQvWYyaV$6(azhi$I!v?@wdlgyn-Xt
+`OA92NCGd1Fb_sg<zTa`pY%0%w(|c0P)h>@6aWAK2ml;P_Ex8*GUI+3007xr0015U003}la4%nWWo~3
+|axY|Qb98KJVlQ@Oa&u{KZZ2?n-8^e|+qRP5^(zp&IV59>kz}W7v~kij>-J_(>-xlQ_wLH7E=58z8;V
+p(O14@zzkO#0011$kZ1-{7vu<jWcnk)E!MrfwKI=Z|vLFqkWIkl8V%Gf(OFH|VefBn8Zn9{8RWSRl!v
+?+npbNjAvx_Uv&NjtWny~Y9R$TiTXJ4kPB=n0YO+4s%&N=(~-P@DX^AoSQDVU#x?CrOw7w_MF@!iF@@
+6WLi+I9B!_B!tt%a|{CQc!P}&X~_;F~5nXF=uO@<xmR9u{^kfW^9?I>nNmx)pD6;1)HTAJ3Be+9v$`E
+PR@(fvPjc7?*{2&2`~{1j-T^|pA=D`!So1$PP8C6aXOzvp?b}Dr!&ja1@i<TCd>08gI1Gbv*fvKuqvW
+hRWJQ4=aY>8w2CsCR;M$W_;Ea$uwyo|PSb4R$I;I`{9d48xlAkk#xG!+ndNp^^<#a_=YFu!I*5Yy#^-
+XLT60y@-r>7MQnJM9B+JqaJI;AA5p=i4oemO+XD|&(DG#c@rZRgnN&E$$Oq@=q6U2U=vn^2V@BMhi>C
+qVy8n6TxS5eO3pP#T*)lDswhl_+QmjJhfFM-<W^hX{P5?07(Y%+<GsF+OboX0bl<+2KYu*92)1%zqj_
+`ip*OWUb6f@LhQUj3y~T3b7>+5#dR);!9iBrp6V;5M~)88BhY8|`AAhz1UO#d@6*WeK-|Z{|liXQydV
+?hzgeDq8UFLtUgQSd_rN$yZaNj^$LqC$N6Ohe@>?<UnZwte_1R%^31D)jI6av3RSus?fTCYKctXCrMf
+`8Ukd&<BT@k<IG}@nK7D<)`b65E>e9Iu?7vqMYD=Lu-CK1T(DySOTO#FC4B2}5)jTo028>$;WQX=@yD
+b5ax2F3?W1WJ+Y)8MO|)Ym5t|b+XL2Vs?hDqy_`Xo*_k$`l$yHG-hfkk|X^?wM(mP(7&7Wp`#xo9^?k
+Ol9f02ef-WSpUKwbIy)nuZfCJF?1H?YD=TU!)kQW;-nTYK(3&TZ>4Y`8te>o7R&!O6r^QqeUej{zKtw
+!+psi9Vl$_FIA^*_05Xe6q}d3?vR3aJI{jvljWGqzBJEs}kf=X_$gmie@oW5Ra#6!qt+kQNp7*=MgR?
+h@}AZpO1PNmKur}Qbj2G1&8GfspAA^<`-#(@O~-hV7;`4EcO@E&}VCx1uk0-*&23DP-!viRco79Mw^$
+%t&Kop1c+Ay<Xz28=*Qce8?ElsY@baxxVZi*E?lOWF~_git7ESM_wivkK5B3Ns2u!PwS<LI$Z~;Ln#3
+Dcq@~T}#|6(4Kx?h>5E*c};)2L$DX>XK#+s?>bn~c9?Fsg8X=-ept!f@L8EqYtNntw3rERLLvPsH~ku
+P}=%{D**356-es=D6Gn8*y%p*|T6VU*<AUAVzc#@!W#L#bTz8alMGj#)+zX4MD2QMh2G7pK>-sU5LcX
+hH`t?Jn3cJjo+kSE0_MT&*eo1aXuXXvmIr<TEgl!2kk;lOi`Kv0vK7;q*W7mj@R51e$`a<QOdxhja-m
+iK1u+M76>mPs02fM2u~DPb{a|NH$EDL|g!B<1Te+A8cvfPWDR};L;)}Ajp7jAt7sR1=0Aiz$DTpgiDt
+$o!0*7cCF%&O~Gp+>ofA>k_T<>%{?*r04L3^ucF{;3!G~({-r+x257~}K;o2r;C#uVLR3f<(*|Y@%|X
+G;q8sF%(XcxhyX+!c@hyY?*9!Op1O*vFAV<J&S|>u35a%i+TDv!Qt-Vf~Wa4qo+t&~5g)5@omRVl|SA
+&xgWZW;%E8GG^S@T3`R9MwkxCfD%lgJ&Hedz<%jo!4MJb$?aX0~l){|c6~%_kw}!ltg8KwO}nmeNoTu
+W`BZq44J|tqt1ySIVERye$ET=W^a9&w8D*{}2%I7plXM;sL5REIk2W{@h10N>w5WTIsGKdKVRlb0J27
++(RPS@L$ru`&Ua}eJ;^V_r9vN)|~X(URRj5u9PBN*+WPrVVJlYJ<0`-3~SyTYNiIMY#a2MZS`idwmFs
+A&Pgcf0L?FoOfLJZ0T5-@tl4#uqsp>TERk%i%){+c%|cQ<CfQ|I6xm|&I?Y|X-53RI+7YkTvq|_Cf=I
+i;+-b6qMAjA?n&0?AF_B|6ZSfq;FlFLu7@{+;y9{V{^<|`~EFJa6@K0AhXad&#X*EQxV}D$qg=qQ5`u
+3&&MaIJ;<v`=x1Ks{yxc&LR(d{RzMxl%^HTwT~0fB$NYYNkI*un4gRUc=6zNgwbJ2^W#>P@~sd4K-y+
+tbPW6SPS=#Ze<z&&>K^{o1|^4<0%6$G-I7xAVlYZU1(98{B4rgXNC%`c4}wv!J)VOhFaOF8Chu^@AWB
+*dxFD^PBGfUWQ{tM|*Q#1CUS1A0|31`Er7jgVnH=RBqb-3n*z&!ILUlG?7AXQFqt31y0HOuUSz;x!WY
+jd6ur0h|Izhj}n_?wW#a{kfHY4A;q>v!6aIOu<`O`92H<qTT*(1aS2W*$~gppF-sxe@NLxXk8yMLD)i
++jR6B&~jy_E}N^e}X=gSoA1OP!LrctNr5ZSUTK^3Th4nXZEYL14V3Q37<P!&HPz8FjXU00?3-mpIq<#
+8H-ZC%wIjuplP9uy?Xe3vA@#`9uqNm>(aQ3byNTbGc>XN5EZCJeVi7WlV=7IpZi0*)^lbeiZk;DQRRu
+tgR8E+ONy23Sz4;Xx|`wj(U9Rn1jIp2K2fJL;>kT-|L1LlQjE6%dr12;eH7MS)T_IokHG7#<S^={)n7
+;0L+PU#C%6gCk9MFfKuOFIWifcTmI|mrYj%j1YiqhFwKlLwHki*t`KJ!=B(pfJ;_$mLiI46ke2v(H!Q
+}Vw=#kfl__Ba`0NSk=nf))vxE$quGT>th@)aS}l#(^HNbrTyZ}FUsi+dt5DsP!xEuSz`HV}=%RTrixL
+1POGpIxvw~;!_yw^j)&lp`m$M1koQc>|mJcRUx9?OufaF%4{az&>8pKi%ezshv8dgCde9?Q?F;JnZB)
+tZDr5~7Ikk<nictP<=eL|i=J*a4ITWcc5-Z!v@Iq6*u+Q>a=5rLtzG%c1H@`wcnRrghCPq~^@m#ibTF
+9}PR1TR^~E@9*%bXPC}D6dIU9x_fuEJ#;nWwf_(K52h%_>$mzy#Ymqk-jP}A$`NI(lo5**7pY5`eWb=
+R2N2?VNLd+((CQ%ZM~lU=J$=dLw{htPiyr-?cF;n-!H!X&u@po!m#$_i>51SK!4%u*lMh_&lXV<EmjL
+wT&GCZDNNJAu4<_^Ma<VcW($mdT={DhDXJz1xdkg=qOWLK+E-hT0F`f0TR%N~xL>b?MbFWL2ZJI;$@e
+qQQciI-WbgX^+sDx63b#6VpMj9KR?ZU6F)UD%!~gXD2UQIG@p|Qhws!mMAL%vF0$f9|e;BZra+JyVL2
+M8(AX5xUAAs|P{-7THwm*U=<sEs?yq;5rBf@A#HgzEa(OMg5RmBE&8(!u5;yUH4AOKX#uG_39{1FDOq
+})W%>o-_bVnrLS+}Zn+_a|RZF5Y}~PF`SPk4O?)Q~VX+uZ(`fj<&|mZ#xST!}`g_E~HCJlhVhga91s&
+LB3;Y{SqN3Vnyv6mu=(-6!<DK`$o)jBVRYA&bdKm*)-58BZ*Qv-hdU2qf%UV(?q}W?J<CZrs>8Ig*T&
+w%u*nEi%3&PS@Q4Jv#gp3{F4s0==8>tB(2<COFy&HTEvA_JMmIAbED>^4%P(sO0Sw5RmXZ2|H*0`TB$
+len?@j5vW-<gSyC+$1^8FZee}a0Vb4uS8<|1MJAymH8iz7d-IKF5QC5z1V5uN~1&lPe(oiz0($!)rO&
+bEt6mapkfM8&D)>=0>r3_Z)Uajf7nGQBYaf}E{T_NUyJOK7JkfGMO6u?!S6(J-R5KQo*w}Ut$Mx(~oC
+~+5o@RX&3RHHutF1rfHUrD<IkW_sKWQ@^aXV^7wh{qP@(6~wMhzD^}ORF;GX0Ycja5{0+lwKWcE$gAZ
+){taPjp(amR#rCV3`H!6HSfnXO6(Cz*GTA`hz`t*ZsP_$kqJ!cUCt6fI}O^-|0cA3`Tvl%WtjG_psl&
+TO!_vt;BSQKtDTtgpZ;2Yl|FStPnGt&T?#;b9u<tHHmXejcHU}(vhAFprn?_RD;48~U7?Q0a1!{gqfj
+3#`73$nK`Zj;!7H+3$3J{k8mBjZvB*8XQ{)=w|GKcgpRC^BvP%1R4fR`uyF95gYblmp$FK(5ED#ZG)%
+f>njGfv79M-e1-@HBf=H&DO{Xv_0+u8w&HS!L+<4-IHTtfWS_Jg5`MGDqs83kCblAy>Nz%uKHkvFz4L
+kB@+R?oZa*MaUc?-XNEJ^15e3Ov|~O{@S;cf1p+3M-&bxErZU+xDI~m(C{wtu~}2EDQ)IU<Ip)UJcON
+mQw5WW&VUtg(Sp*gxEl;?9m1;v-x@}s0V_Bg&hAfaDOGDdF@ogXhmE^7@y8oNsjI%dbdr?E~mC1&-`0
+|dF4BoQ-bNo@KVCXz*e3wd5nonP|*$qBcxP)3s3YQpmpk)Sy1npBeY<T4pHc5VI((YZ9IF*3tz6Xh0p
+g|X51#{-+lSzyMNwexBM^~e)J}=V-9vO=Y2WT8o5vQ9D8(mIo`qRCA3v??NeSwaOG!h&^`_iCQNRdEg
+V45ma!jj7R522qpP?D+8@bI-fjUy;dLcj5CpEt>383pynpw0a`yfN)~0^!YaI4gN2>X1KIfpW)D4{~6
+{89|)8C6sCZSS$Ok7iUdO-3nNc>j$n)p_w$CZO<k<v1=6H~@8R}L_R6<aclK4GM+xS~r!Ito>;hC1(6
+nUqv5PPjn7;)0<jFxayttP733d^NSPy(^22gBnrP(h~$V{Aa1))TuheKorzznNTpU%!<IYt%76LU%Dz
+7UR{!XMN~L1#8mh1%GkshYi*@vgtY~K?R>jTkyEIvihMN_71Bb&vc|!xXi>#xM?F2h+H5((u&l0>MNO
+r|tK)5H41xV}*f>;z3U$KPGt4EuBbZFJp0z2B7MQMTJHuV!r?Ss>!$J%=IvkG2m<zHMxIqcoX?QqpS&
+BP`(rlL!J@H`VJ7B1YO0`49`y~E?H1hM@pNrs@1YFiOcT<bZ-$FxkV~JwNNJ*$8T<uAkc?%c97DAGBE
+d)WqcyVolhQy{Ah};GbmJ9nI$o4uWQI4_?#F5%SyVB2U&V(sKo6=1eqUWXHtlDY$?I}zE#4E1EJX-V0
+^_KBHLA`e~wn<kia%naZXG9T3CaXh2JMy^K5>-cFGK|UM=mQES2M13G{(>%^Viq*U*8#0L$8fBEkZ5D
+pI$|x40BWa_B;mxF-wbtmbx=w74Jiie%i}#%gE^%^mZTB48BBtRS-NZr#=Qvc<Bip6&a-uSdsU8}vtX
+6U^D1Bx^eLeJY;*R`V_y+4pM|T%61ote;tI)MhIdy)&a=&1cp3D1FI;vs`0P2t$2119qFpvP><^gz?9
+h90_*fp5wFIS6ouR}Bqam3q&xmv!&dgsGDf9$wA(=?6O_v=WJwIahXML}CRD!?81zP1|v4M<LCw1mQo
+j(^j!a4f|X!a|6ldvdjERf<W>LB<!XU*f~lI*bFBDE!&RZ2VL1<w{yg7oF4vMw_1#A(L?s)}%sK=Na-
+dc#eLg^&X`0bdr|a<lZLmt5u;W+Ev}83$6+QaT4MB9M-zK%BAgKX4F@@}dRh9B0wIl6$so36mTT0m(v
+!0y38AkdWSu`i8A8e{8GPOPnhP5~R#SAfs<Ph%N{;)oVv9=>$t~P~tU8y5Jnpk=Gp~;*o+dXer5}d}b
+Q(`{Ay&(xogeR+f9x%(g4)mn(-FE=3MU&c~}KVh3Rc2WlzIy10hT6o#;`dld(O{YzSC4_bV(2QcxWhY
+ynf%vJzSw1NlKszLw;AhBB^LUMC&+8yj67JI%24>F4daFpUg0w}`_Qb=R!{}jl-VaOA%a0y+;i$HdWI
+pzVVFam%K{rn2Y3DcqlcYEYdgE1y=jxM{G6jC^F#B476mjiP)AXB<9$8L7`ypNFuc=zBP-eiNG*B1?*
+zYvj!KGr{f(K4_c4wF8`<Lm6THn`Uu{VnieGGqf7)b|cudYJZI80Cf6`zVu1YJ+$m$FIc{olEbvoK`E
+?bq`^#`!X#8FG%J3xwf^on!Gpa561?a(h;?KunHgrWg?0+(nVU!Dgi4ORvPqp9)-NiXERJv!&SzsLN4
+0_<#Fiso_W0&dlEY8Aj)ydhwS-tW`7)ja0eDp8C~YQFQ>f&BBuTN(PijtpEvWLPM-#1S0rh9ILJ=$%F
+-SX!{5V&q^I7V$Ii<yHGqVhsSKNaN>=e&P#qjSWA=0J*{8d(MNGvSNyeMM?7ymQB;;g^SnKrk)MAA{7
+x$BJE5l104ZPPjb-0D!mtKYppfebj);KI6lHgEXr7~fS=t2@^s)am`7E${gx*`kO*|~pwCbS-CNt6|0
+`-hl>v`1H*z;F`kKE!;(lo66L<Ep-Uyvr`_o?Gg#O{#atm=7BW7)Xrelv3`FK}cAOsR>0<4k?6E*ft7
+vx)tqdE_>zxcw5QJEb@to6}rR&IiBx}R6dotg{86+1JQ8g_r0v&liL<pS(ag+eot%o!aF?d_MZ<1gQ_
+8xiI!MiZ=9*tTN^hSGP~{Gb{njSy;`Lm%^A}ZK&nvChuoJH`d-5tItOj&Kywpy*vD8lIMfItr8pGo&A
+fS3l<jsjoBo{L)eO{tkHdPhp+FGI%!az$U?2O>dLZSFc1k(1!*2o8TR`I;8(b3ALtBX1nm<Kehp>^rc
+L6SS46+9;L?0lOG6PY}X%O`F7TuuAP;52;N&$p*#IFTiB=v%JihLaOnced~-7WWl0s!+?!oBSp0x1B&
+I(SvvSV8>s;sXl0ob4@d_SEgkC^NU!!p}Y^abL5M8k}q>nw{pnvZwBAsb_hcQw_%ZKAl5}FYJ^a2$)I
+%&&lht!wCJ6>8jw`Cx#s8*C|sD&)&ShXaqm;Qpxz>7N&R$auCFzg(jx=&gp2WiWJu<^TaU1j+s?~%&4
+;DY8Yi*d?TsXRYhRc>n(7r!~5sz9bU+f5^rAl`l|{j#58;3jtiFK=YS|p$Zkzht!MgE#6~BHjMtT3Q7
+um%gDZ7X(0$3J%WAi!F)OU~S~wU>nA5Nv4f|t!uwGd0SA}t~rS~)D1>2uJ<c=|gfSy?FfGr#Kf)r&&z
+SC*1u$~AvWakNSovbBE+gAZ8Vi=i?JMq|py<}?e=Ilg3RE~@4QHB@gRUg^0yM>@~ipz9ayV!ph*q;1p
+f!hkRmB^BSA|Y3Wp;ZQ`@%^k?Li_IIYjIj@Y=_^NeJdB!%vQoR-F<}^7R}af1>e+e1rt4Q>g$fB4O-r
+4Yu|c#R$|zCxqq5*|HC$JHK=^Q99v^W1VxQB*)R$U1wy+$?bKS1Fo|}I8?u>3E1=4gkV(cHcMuz=QED
+ZBUtY$;^C48>qWnNdiL}aGH*;+oc`geRy7*9=ckO5Rl{?#dTV2!zt)+iaM#S_eb6w*6IN$wY3t>2GIV
+X>EtCciP+k_3~GIQ<qgwco&C23<c(@t|QE6;uEnWnq*D{%7)^?u&`7$7O|^OJ8t0kz#&CDY{6)BkLz6
+KMM`s{3B|MR}hTp1WgYwH;Sd=`QN_j-QkkgV58}xq*^eYX0RssynCZq(B|A)|ETPASXh8<}O&SIZq0c
+t+#zcr%b34o!nh1ROR>dFy7I2euqE%?7!(l9aeR@96v!JjxkC6<sz6)-=I9CPkYQ(;T(?;YJjF23Mh0
+@&(q}-c`{15{5f{aqs1zw&w<n~88$xmQBG7)X;hgHLi?82|HN6)vQpVJ>t-5|uI_R3>+7jPM-RFqe8)
+ZDh5sXdvjMzo{IjIJ-*QkY@2?CG$72=ExJv182;JpdApy_?%2WA;7j@)8_uk}9$ylgHii}QIQ5+&Z6_
+3e54#zHnbljG@XIS^dG8DYsG6%=iMk&=%?K_yiLG9PJ%I~>$qkq|<PoIQ%bd2+EV0%CHS({t^qnPLP$
+<8}JjS16o<^3xBl7~3R;n{KR;;{DlD7-0X6wBVUwDe?FmoVwnSUz`j%F%Up<J%kNS{OcGec0`{2#oD&
+D4qNIhX#b!Pm0vjIm_8d>>fIszYYGC4xivRhFa#Ke}U(_Tz(Hr^O5m@0*?cI{QL!*MLZ7k*3RN98d09
+FINR?Z^*r_k9`?py-z9~(NreDoEsYU`^TMxk1ZtlGbL+OPP&P*ProJZ|i)MwZ#bQIB!(jH~+>xJGD5)
+gbc*kewDyHA9E{zY$>_|2?fwr7ms)d}Kzx~I_Hz(&+_@IiBfRAqqhg$r^ZC;bxdWu&5>_|J1XK<Eqot
+mRpE|qIK4zBt_p(OASXe?nVdEA7iOKP_+OYfS;*8DSvA|i^aBTIggksOYyRHN}&8d=q6lWpW9$s?%Dk
+*nlIH3gxr+x0Kct&$H(dY!0mU(+{v<fs1#uxay2jId_h`9Dxg0|XQR000O897^_9m6UE^CbR$m0A>LI
+8vp<RaA|NaUv_0~WN&gWWNCABY-wUIcQZ0BWq4)my?uNXMYb^9^ObaxNqT?;0tAQ<6bx!~h>{(G17t!
+}f`bDyL`cxPkR8V_4Bdb$fn+<QY1&bDukN$%)q7>pec0>nv))xc`~YScH<Ku8K*hMQ8a1mGJ8E1)GMF
+L#oKxL13FzLv?;r2){paOJy1S}QovJ!@>eM+^r)sKieT*?N3}c2rRb`lijP}pT{PTZt_{*8`N)Gc<##
+@&hG%SDXl2!gYHWzMcxc4Uwx8Gg(<J<4K=U%?>Up5vt2=^4;aZh2z&7Q)$@7=KR%IxgSA|1zZwrSB5c
+YJ+!@-OYOEq6Z-??(n)cfUm6o9_NKeOKK58N8nw*Le3YDC{?PpP}(i9iG?Uo9X+OJAUj(eE+EKZWqHW
+H&~dg?63bN8Q0Ai4Oxavh6zL9H(J~ci{N2{zfPSh_-$ku3uB<^$v5+YffDhKLL($Qn<*f|rrxO+{rA)
+W)PbTjFaw?+sNgdO=B^B=%5jD%`0qNQ|DwKvdNvvUG5D4I#%(;je{@){5VqBPAxt5|+;(NdhTHku8D`
+BDdfTsrzt=B>gL0i$YGBN|>oCTk;r#pe;KElnY;O25eABi<o0(PcHX6Q<uVLd|_X6M)PNM<E=lvesl7
+HO7|Nr0rlYgt_KCge>mrh2_Th-}g<o@09*^8NASeP6f<gfMnA;qiaEr+B%S^_`Ce=v(-0*v1V-R%!!R
+)GyLYNwI`kT!s{hwEyi-$$Gni+KAO#EBn5{MdhkxVg{FGR*E4<6_4CXUUZi8(Bt}A9C5;s$dNT6GN)%
+S3#=zk+a?8(MuUdi*=KYs;Y{w=LZaG9)s1YPT1cfPi8YrhmP3%-yt5p5b;VcMLdj%UmW=X#LgsQxtjI
+a)lg-^%^kLca~3o1mE@9%3?sg7g_ci!8KdM32P+umc&N%CyV&ALsG=mHyd%ff(>9BJ^SnNP7f>bSO4w
+C@_f$Y4H72CSe)3x=#@^wGagRs*-2kzYlt42BMxQDqhyz-W?|Wx3%#)IfSQ50RMbhd%$rX3R8ckAT93
+bNel%oOr%`oBu1`oM+3d4Bheo{usR_KWFljQ#5sL2%%Se~p2HNJP|IY24@UD*Nh#Af!A_;`kqTmv$c1
+F~tj=KDoFKbsce1xg76BxeeS2B3(OP%XLN9(D|IPlWvmXoe*8xk)`nyZVY<0|5&ZTLZvPj+RTzHYDOa
+xw^+x-5p@&Ruff#{|WIUhAh@fI)aVyVQY3zrgUnb8a`a8IGLd?ubZR+{(3p<;6jK1s?<XtSftv1WtFU
+x>VBg=9AMm7_5LD?km6bmxa2rgH#Rj)5gj^D$r`Gdp(;7`vh8KWSnn9er&l?mo4-~}lB*w)+;JIXboJ
+M)uj|nI)#?pg37l>pl!Q2$X=Rw28sLd(UVnVrVvW<hkPJhB1-^n5zEZi*=XWZ|2?K861~<89wnjxt;4
+;crxsDOxhL9`nKH>&Q<OHQ~3`+M{ltL~7`n=@BDU>B0ZNhts$v#+#=zfy}HCivX>D6syjl30}<}GvKn
+YMM-ZvRwm_%_dOf-m)B;Ji)#P4F4WaI1M%I&Pgh4;OfS_CYWFQ}Z?)2MOTyhFm=W#X}&Vs-*<#r{?*!
+q`-NE^!nF81N@s5Dlj(DBsuQ&X&LW2j*ZLP1}~kU&@eS`jYg^|V%#XC4Z2v9zy%D*agde|X|+*WCxl;
+FkF9CA7r^i24y<N<@&fstJ3B05#OyfU;PZI>Be_6oKHW^NhCUB1JRGXC0$;<(V;vuFE|!OjM`RP^o+!
+puew-K|;jMBk5;wZZBQTn3#Hd+}nH{xk!-q)Duks<TZtZ$nR~XTVoOI=5|FLqMY?`F?|F$eQnL7=><$
+lE^zODMmOZj>~=%loHePp@~#n6i|I3epe917t=H`#;XehEg`2!~NlH+hVXUn{VnsH(ipF~YTE!l-b>x
+fYy+#Sx4g;#$tal;G&+TE2oeHpd1+rKKAq+qjl4c*~^~Kt4}kP(2wqD|f+j07#*pgmF$D<FGao3=$IL
+^twDygn8VMr>4d+%v;K82ZVI{DT+XLB^+^xat#QX0VZ%(Jt=NXz}Se7jUB+)IF1-cR5034Ia~?BjBpN
+D96unbd;|9ODLzLWR{0E%`T=AE^!8I_wF%xPHYQX)6G*Rq;K4G=YU3Cgr;%}tgd*1J%+uVrA#>~m0D{
+;9EUWr_QjnYlBIY@fpHbF65%D(xPwqkXUrCOfQ`MT9P_Pex+<{Gpk^jAc47C)K)w~joA9KV*2(U@80Q
+)H*Sp1Iz3O8wn+|AiIe3%mK|G=g(d2s~!U!rg|02inT1)l;WJ~z4QRyxwPFbswT067$FhX9ktFkCR0>
+aYv?E7*-KIq8vtJ@7%=6RH|B7rjSI7>Wb$>_Y%A`6DFw2WWIRM63HK_>&l$--oepATUJ&b3=2877W}Z
+J^dbhN&C9+89WWo!#J+JdOdwU5THJvx(^8oV>cJ-=ZFdAYF-t5`Cdlxv@-NWKcwEW((Uu33aI84L0Tx
+-Pa8^e`khb*ANgtsOSkEwLnm1w0IU1nK8w}s#7gHvrEAFR@B|znsNH^x0kJLwz^ZZ+d~eOxQ`EfMkYE
+P?6}hOqtV8NQPMdpb2&poEm<}biw2#Uv<UQZ0=qjMqq+F1UnnU}KVt8^0xkTO9M_CE=gkvayfW_qUH6
+X%X?E)|lN~sUze$bN^g(_L#Lhb-l58N|DjL+n!1XwpYJ6@9#g4IJA8-ay)Aw#xY%ZhERJly*h_I)iIu
+=;xtCy8X@+!qXkj^Ob#U!jta1+@u1kk1`R2gL;on1HyS)N%7k9`*PuzQW3%9;6KyV@Ak<;5i5$NLJ;G
+dhvQj9^xl+2huQMWikOOWUMbs6TZ+B79<N`?csVU4N`sN3~-WXsLQ_{N}8$$m^IB`;8X>gfSYWf<=W~
++$4uc;$RaM9>ERv^`(L27s)SSx4^*wqC`OG?!2suve}%1nGb5>E&8Qb2m_C!wPa*&vBmZkeV9}ZdmBT
+h&iZ%S@IK77X6thAb+MJBcf?_mi;S1Sil}bQGt6Qs!kCODU;sZKX%`-zc*NY2g^5#IHVhPL?!{(ZmKn
+8QN4`adip!us{peaS6O-5xL7B~Kfij(#sq^8gu?xrFJ7;GLbpd7<9c~;tY8eo*{SP<WzLZnEH@)H=ac
+Z8nCkz6lXm$YeWDA|pJq{|)-o<frNDM|i50Bjl(u^9Vcjr^vgYjfVNaZTT4^VX*CGWqnyj`oIc6r=nt
+WE;e6O*Gr9n61Va3J%~nYD;5^&v-on*57*`huVB<1=zzN!p~ry-_tw~4QSohB48$vp!@J$U-mS<QoLl
+bC0T~@(sbbq+KsdPU4R65!A-8GWe1Gwwa$8v(=%k6hLCtLcMzK85<mNmp2bSDXz<Ve0DLIe1+;Q|rKj
+;tJPDj-p~WiJe&IJ*`;IeM`!WjX_akCt*cTx-z^(Q8C=-%p>Bxgc(0^N~)(+wU?Fgi<o5%%}LA5xLJ?
+oBRU+$bfQz#DD)`pf924=cRwvnNvqr~><j9+~Q`8JnwXvn<Yt)mD9d(Kfzs{m8z5C-H}$Zf2bSut#^4
+|WJ=i;o_U%l$H~b*KtbY&7Krq(qL#rC=u&>!*J(Rc@Clw^EGxH06|r(bR4VVa|Xt#9z&N$+N)Uqm1<|
+rPq^x$7$p}I+>iNPpku&HQ%6C=OIsIAvH=o<UWW#M*b5>e$0`L!$~lniT3^mOc)So;eMd%1W<YHs?^w
+H4}+L<d<=!aB$7-11PVut0Tq}b!_cYru<`&v2v%xVfc^3j5UgyG_I-kIv(Q{&A!jz(MstFe#V8$MSk;
+#~ghKM;6uQ7j$kp%mV`a#Lm(pHSc7qyigL-p?7`92So|p@529;!>_;vM=|APEc5a{F(a6wH}R#EGd1s
+3G>1d;}cfr)ie32{SJ<u;|r-^8FMXajSTjMsIxG+;|Jv?HCIgxbmsD1a0V=qB~@YOBK5JKo^OLsxJIS
+nS{a`Z602a$5)U_Z`Q1>|sp<$@8Cvpj)%NQOM(D)2V}EJ=>ww8mcGL=_$aHjdQT(@F8BNHNi{f79&G?
+$(NUdaY8<|;`1H){R(~laSlFzH3zAZUpLxnXaxu3z$WJeJ9wjdTx>Ht1ZzWIvPok3s_Q@p;wSs@P42x
+K3dBK4>w{4>WG^U4{%4>K{#JO9-B?|eqN_lczHTMN6am1&CP+Kn0*@Lw?r7W0$?1T`sCJ?zKGN{5SiT
+0!SzpIb_2U<@=p|V}bu^+(#aJX^pwQoq?Dp(T=qi@fAPG?Wgt@WIV&h<nqH6ITD}3&9*?z;qTWqv~^7
+Rb%Wa)CiBbPpg`p8MSORDVzJ=L$4RzWmG#HGgfq}tO`W0&}i8NMCE4L6Zva~Y;Ao&O2~i`45d8+jR`q
+;&ON4If4&QIyr57C=|-;&TvBZKvewqFCkHPUZQStLIsuL33lz3-H=J4j58qbV9g#%*y96SNBU4p!=W>
+&^-#!O#w7^E<}5v(Z&dKW3<({AP3~Q4+dck<!&^7A)RL-b}hz6$^J`#^=Y>PQPI31f21o9*4k7o8f4_
+jWGq-{07xV)j6sMXKh=XY5Bch9YAKOxQBU@(IL!YD6+EV~Pb16lS7@t7rOXsmz8=>M+<Y&2vJiPzQ!?
+G;1_;$iX-URgiGAutTN*|l;y-;gLZj+1DCC#968r?R2C^VClA94zbwXmPQJfr$UisU$N-GxjW39g`S-
+I*iDMzmIODoKBjwAb^buq(_m$Nrzg27z1Nk}J8IRGwAt~5I=+cF?=q70c*=`0zxBOWuv4mvj(g<P>}l
+MxCrD48+~n4M-!1dH&fnb8Q)X9IoBSLU*DEypwk5XAEo^7M?9Q2ZS9z=J@soxRT^K%+IN@*jIuAvaXr
+PnV6r(h|4jGQ#5GkGTV8hZtYnkS)e<-3rr3A$Oo3ru}}@7$G_fqtj?~7?dux+QwJZgA#guy`!IxDhp6
+vatBOqawRkqvTEUUH<|9B;!@MqARFZ8Gcl(HbGCB_;D1|jq^U8%)bZ(ZbzHoC)A{vlJCZ`85W1G}3ir
+d*i!E)&hES0@iM%*H)zU<U-cseqa<vr%&ZouSLW^=PYEdV&sFOQj_+E=5v_(*_6IicKK1%C#v^b(n2<
+S2zIYp%WX-jgF2Q~2F?ydKFePTKCAS2|H>#l;~GMzME0kVtoZ0I{GwodV8IjWdIn7Bt-_E)GV#e=GFX
+~0@nW+{S5KHEb=v#E#@eg_l5Tho9qN=O@hq57%hddOV}K>joh2>=oqMAX{a=s|{A%tUuPuR~oiw+`~B
+AH@9&CC$;+m@c>N!IXg6O<r1v8ql73m(fMq=>fA>D#bMNZx<w30#nx1MeQeEM!bq;H%3cVqZla^kD8m
+$HNot-{mZ~e9YELs!Y3b%#4WNpSa>PO!SBQ`W<<V7lg;V4w!k{tcr&0hN>@YnCC%qHL5A&bueXQmqU5
+^k8K$Wmr76Q(h^ZW9DV9Yhpd~jtqtNy_`Wt38kK6`jZ=E8)UECfyXAvW|mE?JlK+P+x3{0vuN~YLW=v
+DKc0_u*LLB)7(<3urRbCVsH;EZi;uF~KE#AU@L3@yuO4%%`@q+v!mEik|NHmkZ*Rf{9gP>N_>A<eGke
+P&GFY8FwR%Wa&X=b@Fn;``voM*qnbMOF_;om=EpMXdeQu60G$p`*BA$4}gqDIPUk^CsUQ5(9sY7At%y
+5_7|NpFAA-j5U3XFPrIOW$Jn`I{2Jq4kzRg{=PPfuz!;??Qb4YM@Dv-&WYcu_II!!KVb}pX1-g#F#*u
+Cu2J~OkzN~oTH({Ew66~>QP)O8OGeh?^E`bf;F%;5)OWl{*yaU){VP-n27Dc|ds5V{9BUte4ROlnI0K
+5?xhY9yXlWY5^v*L-LGLAw>yiH)F18_Ev&P;BD$0!P%mpQVuG|LZ06!H}AMqTH-*Y&ABZc)6)ppDBg}
+>Ruy`KVQJf48+J%SUL&rJ?4g1&AC-9)O6JKhAbv3&}Tn#*x$-Zur6tls|v-(}V8=5e%8vKDJMv$q!Hi
+Q~;3O9S2Z6KjUP730Q+>p~S7Y&kAkY@I+3A>!8^QNAF?90LigjB}H}fm&VzQ5i7?=^=($kZ5uj2<B{J
+o{}7`%7e67E3ukBbyF_MT|~7fpyfCZCB$uXsoN^|D^_xBGF0dC8kmB<^^hP)pc=U?w6PEDP;KKO2DVL
+7T=s#avY~Xp1#N+97R4~?m-j$66tOimDH+?5oSAjm_NqE|!VbCeQA`QBqr$JkN-J5LDhlv}1hjg6a-$
+81E7c}oewiXR<}!RP=%$m%_{k{&z1ECEirUVykPqVDDz>Zk6GKB~uG}q`;9{QD6JS=7s%4rHKgdT$0k
+-br{@9p1RB5&1ic@31{4vkUmHCouKuM3e25`{`EVY)uKtVbXUjY*>kh7d?#SKb%*wNKs1of~n!9DaUM
+EKNeaWO@R6K^HM%-vx&EHX64i$4b8KDRL;H}?19dYYqlpkbZZIKc2TUdGAAe!}tLmJB&EBn-$AC0&l<
+N3{5;l11kpN7q)P9Cf%7Th{{7<6iP8)TG8u&Q~NCCLTapxWV9x7kABdC6ppBVHcs239+|`&^`Q2=p5A
+*Z#6*kZc;(-a1DS>6}*(r)w#W|;r!ERRe9_aP0yNCNs*J^PC{CP=F0Rwicl-8g>tMIr1y|u>uu3uY)T
+)PRLr-a<Ax`py)OwpWrB^rs!Yh`FE11Fg)1m_4zS}s1bM}!A-`c#sw014#Ev9?o<wb(d~LW(NXz^Sxa
+9-7MUp$lOtNTZl0vin`n!~9Ph|_JnDJK1hq*}!au7Wg>dRcL0CrIa%y9-SxEVAF7bsBX9MH=Tm=`P4P
+@@YNLN3;g8*|TU%An~ITvEfoYU`{>#~86C<dKGnsb;;3E931dl<KsN%Ktt2Fe&N5=Ds<m3)XvJ^7kR*
+rhAChg}wM(H_TT|U^$rO@DTvb^QRTKX^7EMu!}B8mYmlNz2IpY*$qJ{bQ+&ebm8;q_wc!|6Q75U;qu7
+CPsHgf)JI=Wx6@bfb^3ZPOkaO^4PH+@N*6U{mpN2zmO{9w5~JlAfM!yVVA>4{Db#}>)mABl^^&V?5JT
+(Im%xR}7jQuobP_f1_jGv^s|}OYUX7eKP*tpYqbF71mPK`9z5T7VWJ!NY2zk{~B%7K?Eg^wLMf@e)`^
+8wgrvYYVz;JkynF)IXM)L2P(hu|XYn{|wJ&4n`&KqM;!T2%Ns@)ee8Z`;*VK@FGF^ze2-jQ84-0&j1a
+#Q{Mu8ONT9Z}FHtaJ^vngvlcO=hXUx_uPzKPh1EBMhpu<9w(YUdbI;1lj6A%8i#}^^T)s*X#Q0#YGH6
+L?B`uE}^_%FP1S<b%I|A!k#;@0L*vHna3Tt8Z);6>`{O<>Y0DU2$&f&3GXR%xzqq*XaWd+SE4vF)HO9
+c%avGPmy-2X4@h266dc1apnf|cRrPO>pzUh!M&N0$k7Qtf_rn;Cm#sH9nxysSfWhM>?=PWa8#vh!<sK
+f!!RZ5igM~~2TfEHNI~%^_bopjh?kfIJsvQ_SYJ#?$jC^O2bDuyRPyBpF<ny$_ifhbGV9gwNbZ)lE{Y
+^j06bwt3I8HX4g*+(KgsF107Y*l@6WhKaBjc0x?0pCxgUhT2uH_|Kx*4d(Ub1?i_c?0L#AP8~95Ee@3
+|pY2P{Gq!rUYZ&L`yA!Qtzh*JV<d?YYc7}70SzC(q&EUN=DOyOu?kOSSP4(XNHzp(c49FVh$?$-(9TB
+<@+r_E@c5#mO->^waGVI2O})c4n=UT=S}jmd|EJ;YUU9o2#2}2Wi()NCF;;z0l`{`g7qikQ9c3|?ujr
+JGTEsH6YqK2G0Gg|+u3J90-`C3fy;4P|A8f?y7BswQs8V#UZVZ!3x>DVI4mqsWb;ZHm0&Pnfk+EORQc
+wBLgK<4RVWq9QB61CJS|KY3B%i}c(zKI;0X*UtS4|*G2!-H9&Xyn=~6)&7!t}vQZo+gjFlj_!>3q?vT
+=RgsB-JEpYr+~Z*E`f$fkAh$fy#_-_km020*&rO9uX0abbzdm*`ayrWL=*+iu|58~#BpL~9z1JSC63Y
+fIJQ6nskgv=VE_D)b}3`A2NDhUD24I2GhTAy%VM!xZvwI!x0j$_`M~K)<B4vr@8&-7_NHP-hnE{FZEH
+Yq3+E*r~s;q4~_>R<A`K()ivqpSCmR>cIsP`>C=zRwxZ*l9_q9+EAOo@MQlp9LxZfR*-68eL|9Id(=u
+c+0iAade-*v(<ttw%|tPWDi&CEiv(H019gbnPeC=Hke&&t6-J-~sJBq{R6C#%p$daFWnu*K{kLH&j^R
+dab&rZmsiy;3Wd8)s%4AVk+>Tx#S!6>l)*f9=x<u8<g&ZgZ<{v_|!9lJC3?fDnx@9wsu`n#%LKc6CBe
+~LS5Y~!2SVmX?HJplw?5CCjC1~8#?~}qJ)t**NKnxrOWDZ?+I?V`^LUmS;)^5bfPxWXG5!;-KC^vS=L
+O0<56nB=QG{fg@04C<B#acZhBWXa)Zi}fO)Elv}M-}d0);kZKWSoIQa_|Z?F(g+vOeeR8tTYEmTFNMe
+^0?-sv`t4hPik|T8Ie`noR&=SHWs(mA(Qgg$QKr=u}9;Ccf?O-L_SIOR~s^pkKp`_R5c^1FCNd2<Ul6
+^nTy7!`cLdD^!V(j0$}mfgc^IK+U_&Ym(}J1W51i7k{ku+G?D%qUB|KE?By8d3&5DlC%+#BI~&))9*0
+28)whK97J&|HhDxZ{Z^-~|rK==qA@lVhZd9Ql<kDwUx4N38>)N@FGrZRk-M&Pv?%9?pySiKRRcQG*fO
+LDv8C*T38tY6<Pp9e0#FME+3#hA#4Fq9rPrX#JV}yG;ED~eg=)w+I2_PK%t*N?~X?3rSf~>*@vOchyY
+{5anRwh`5@h}&onFe!qI$g*TY~;mM=3W^w?6IO5S)et?F}&q+dBIYT*T0Gf-v7DgvV{`k2J%z1WERX6
+YRM+}k`^ed<b0nF=pVtoGu$MVmhTur_{m};=o*tW`v-DeMt+33@|Ec@b4;^$)Jr)CW+St#Nfn&jHAEX
+TDy^VW7nxIMwHnoqu5ZYd*1aO&IhB=c7fu#G5xc*E8W^NXtB~U*43Np-vWgpROpTW`%maR?wAQqQ?`O
+sC1i&a0_Zs-|ds#l`cQ|(m>9NXuoY%C1y<`}7!rbJ8AK?};?xV(4?ukffv06vPT`LNTJy{pcVK-!r>i
+>h<9Cp2oox^8}BL?0gju?f%V58h$>yw&SZ{>`nGs^d-HZe<|+8+HnHMNQ56}VRKl}qEG)}zL+Z1n*PT
+v=Ay4-x!N$g?*x%$`Ef3CZCbaEbQ*400v?5N^^kL7f)UwP6S19;!keHLlEYlRo@(#I{V4)9S^A+scJ;
+K7eqODOE}9j1$|;avGpIftD(C42aQfMr8oVvKPtna3+Yzbg~%t57Bl?*ux-=9V58G)COwitjy%9#@*-
+*A@nG`bR8&vpz9f>5+JBxqoDlz$h}#(n;~~OKH}f^kei_rp-qN>(M#6!Y7|SitBx43-CG&SWdm|F1D7
+j+mdaF**G(LZru4*wOR$s}mIAUVN$3eWp{GE#qCWgbMCg2I0s0V*Sy%Io4yrs-myvA5UI3QcC?TjGZN
+UYZkL8oaow)gg3xRZxkvH8ee2rVB!h5)QG9B~Jq^lLmYokSo@2Jp^xkP1CoKyw)vtmlcV5L>$7kJ5U=
+VH&t$>bYwL&@`Z^t4=HpsUAJMSDk8#><rjxJ~XR@h^Z%^#x#c)ms@{6{XzUj@|S(R-fj=bfGxO!@<##
+-#(-9a5fa}<g+OXAk?=25%rRXl_U?7h3bWB8Je)ldor%je5hQoHtF+{dUW_e+2`I(wTTgfkTKZQ0$B{
+8+QSGb7<5(`_=#ZhH~=(YfVN&kokXDP3cTb}{B~<zCQ#!{ZTkY4*JxM0<Y$A}8>0)Xni5je1{xLvW`)
+&9-oRZ)Y?e`D-+;|ekRI=+)6D^Kctn^=evz&zLR-_vC`-Lq$>1r_m!|3Z(w#b(I|WAfbCnZv6snL^@y
+=+Kkkh%tPz|x$z_)ow`=CxfIbBo#tRC{duHGsf8A(eOJZ65h>b!bSI_@LYvK~@6G)5{E;Wm_DA*Uv3J
+3>VhlZ)#mpCJLEv1|P7-=VPt(1%>V(jBDigJq?2E(1xD<pqlqEX;O@JXn1zE+JUZxtzD)Fuiv7Lilbz
+h%tCrK=|_IEV|6lnh!C;Y4IQr@0=~~+B?c#APjE(N2KZ=5}ZUO4;v^T9^@1<XwxHXWC@M<^#q)O6Xf7
+bDy-PRR8sgi+;q)*9WCM_T;*=L2}D`}inJp)>QF5Ct_QO(sL~@cNH0bN3?%$1t}wRo>27k8!t7fHx|i
+#91E0nnsBTwGfy|nfZm%EPLVnu~a>&(PCiDntZn6&Gi3ktnO4-#XvvP)1ecHW}%&o*(J1TD^vg<T}gU
+-Yt{1Sx!7kKEs1XDeE3&<8FeyDOU?%j=98QD`}15GM>9zOHt;B#6LK1&PnSzZ9o`iJwX=qr06eND@!F
+H0_c&9>3k6;^mX^{B-OFWJTHnNQ#5JqzF+a<O|VFih7}VwNVlJ!xQeW8$9q5Q<smz%#?lgkzR@`sO8F
+v(Xk{cDK^c)2XG7J=*{X$a<q4Xn>o+xa#3IpTKQ&T=Nji5dbV=fVmW5{D}L4rHawD*WC-IE@tc}JgA<
+b)9C5}X?0v$jb5E?VA(G!<k8_ojNcB%P`rVkCC0b%lSrQ_C74RTp^FZ;!+ia!0iu;``zf(HVNfz&%|J
+<5oiJ)E4)%`4zIw+|uH_^|hwk6`3LcaQc5p2P23)TQi*XP4=)dCD!A_ABaxH^6-bfaIOBKIVB>DUmBF
+W@05s8@#?lz#&8|Q+@sL~imiivO9dZX~p`j~2*gHb0J`~!`5(yhdps~^F7pQMRKF8CN7zX|cP5zs=!H
+;q{_Xn$`LRq5l5z^CvQD))$F6@RNpa(Gu2&;cryCz3QSI2izjqIgC{aAo~PS%&Mbf}?q3LOp^UIDq+;
+t7+`)jMa%`%nUuxxaK!;FGt}H(&gYT-fZtsj9Fc&6&fyhny#MqGh7Sq*9QvMYyDETh>r(MUcVJOoh(_
+YYXe-c6)W79HVOniSS|>uEEaz*<bav#Gdf|zxX%*XGNBrvcPWbltiO;Z&mWs?!(=0)%nYRa=hNi8RPt
+1@EeDeg%ou*Lt61205;LTj#P$`8-~xXW-88X<T<8}FdW_#q9Yl2pl0wkGRZA|exK$^lDl0DdZ8J*?q;
+0IUtw5@>(WQ8pBIcmf{1bYAouV!_z~{H6X%;N%INc7qGsuPBz=4Fjav}2zW%>MC+?7Ffwd!|Bc42X-^
+1K+gZ5<z~#BDJPwJf=o$CJ6#`7e0MW)xU8G%TB67<9tCZ*_ag8#KC7`8j$s^e8_LEFf>qK)o%S?l_wN
+%Ms;QQ1daFRog(*%t#t1On?H&XCDJ1ZJV;-1!Zaq5KT!f>%teH1Zh1QPZOJeLU;e9^=4^3E6tGB7l=3
+8QZrH(a&(ORmB9&#l4X;5tj%rjaG2kE45SG^VX=7biiU4PRbPqc#%;|BWUm2@$^6#iMqE0!RG{IRQ-c
+Q)W<|s>TN@=g8FZFNI~X@DW}*-mCBv*9mC&Me7YHx;RHgekD<zivj4F)%<TZFpB{0GJODdeq2DOyIs#
+X-)q`Qi2A^0oq_IQ0%=w0nf*#GR7HWF2c!|>GGCb{AvSO11R3~gI={{|@=KWo<GmeSv9S0?u)b+MLDH
++kgEti2R*`sB1Wm&)klFZ6&7z2LLu6=u^rcIyIC_7|w|3aebnYT>yUcCmv_bG<gk<!W1KHIY0Cc`XP@
+B31W+X2P!z-2j}mR$l&KZm8lxutNJ$(T#(8nJa%luqY_h5Daf~?p!9j;&K<7TyHlustjKwr(IZu{U2&
+o@X{*$i2N4At^uueQQR;>!O;O^Z7%!q=DWLvxng<YWw`rX=*KttjP7*d{t+jy2FZVmnuqb?>nsc-h#`
+*~=>Bop8Y@5EuMy>4xt;t{i<Yb7IN~m<RpCXove8=g%T+8i@N&rc3ieHz$I7+b3?Dk$H_2j1>Ya>>+~
+_*Is>lXiohvUd%3pnpd*w>MyE4TC+TO(LQbiHFL7J^|MTxwI1?YM9$?_(vI5NUJ0LOgsyAj^(`1_VCL
+-V(U*1c$xv!KS}17=1z<~Lv~ma^m*)eQ48_Av&Yg@E$HhDT8Y#$7-lW)#qxhZdVbS}+F@j<-X3EHud8
+POj-vfqVS<>L#nY$%cEJi}d|P3IolMj0bTSJGvUsu<~5>z5?~WeD%ILBu@uCYGzh@eIEHs^dq&Oun*c
+*_4rz9k9;YAD@R~RezP16RY>iCbXENveKNeh0CS6fuoAtV7d?cIUu*Fc#a%`0Eh|;ND3|QheUOf_jI8
+1rl_T!)(76lGn$2{1GGso>z?ZauiX62>jO8a~4R5U!M~b$;YY#iu*G0u53W$D(-^!{-p4JIK-oqH@lN
+W(fK0(|8`fs*Reb+~poq|#?1qHp0Z5}DKEM~T!rjYB=;^Z?BQZTvIcSqAduN&QESLgp3fm17bR(}=B?
+eB&`Ur?8!XXL4}Y3NcS<dgkY>VU#zC3R$L7s^*KQbO}-h0CV%W;v$Z9mpper%?OYF)VOo10YL!lPK;$
+CRxMiE1A=UVoD2NYUys0k8Jr1YM)o7GD)>PN|v-pN%xVpm~^qd|E~ZU1*~(`3s$m2TFb;mAj92cmZ~k
+Dv4L@9=tESLuT8mez>Mn0Mq2<8S&AN~&TaH44z8hhD(TQEsKX}9JqyY-nU00}k5r*LNB5wfnXs4{-QI
+f^LVNb&<M;S@VZ!1u&L4920D=B2bDKd7e0%4h)g-VWnH_BneRp<PP1S6jBeL0o$<zT;EkzvKRu#Guwq
+jjtzEkOPYmd~}MQyOGoj37$ax`G9DUR?n;g5ws_!gFuA@ux(8L$gX>0GqRR>7b;j8)u?4`sEwb)Eb!L
+AQjO&?Z(+Q&!4Rk#PJqpg-}KRDqVT`yBQL)e^o$J^$sySf}0iP$nM6hVI6Pl6e@Lx*H$*`n6lDIB5U&
+u-Mpb0L>Ctrd{1adcZ^$00))1deG=til&@Bj0Yx%Sw0h5#9PE+voKY@`8KKgJ!#o(5HBo}Z{8qPcgB`
+&co^jc#LSbk36K*k4mrCIK1?)NR(-m0vRr){2rB#5NfqN*)pc6=E5QvRDJ|KRc{+|6>edY&b#-@*G8u
+>|H+G?=!m|N}yhlBSXxfF<8YjDwbxM<6ozk)m_Ap_AOruP2@Pc07^V)^M@Musi4Nn-e8Oc$1+T`g8JY
+@zvs`FV?&Fg{}_0{vLr9~FZcba;|2M2|zYH524liZ&I=*D1MU352&e_TnJ=vGTRQ;=$>n2jmw?jk)s2
+fD2Xt(0tvpmz(fI}DS($a){)$=He$Nq=A%{;|q+Yk=lrJ<Fib*pVyk*wpr5I}mqi+k-a&7c7lc`rUvi
+kWJPllDkt|{AwNn1j)|8L-GMDaUg)yn7~sJm3QHg-Hkqv@U3pSi+qD?WMjLJJPy@~La|T}KwpG@G9bp
+t)L~5;;Nb~e?odmyg>sy{j#)b?xmNgdjd(<rB=XQvv!*6E$p6TzL8_(4#?S|kaRflAj*rl@H+lU?n-y
+kNN>eht<n{NFbqArOK8VNTb=1LmCp|(3<)GRAv-hcgO&v;`P9)?1!gUwAj?{v8Ajp+PPza2JtrW0wo)
+)@83(eO;YqiiqEmW<AoLcC5EmWa}uGT_TT4<IQT33$Ugc0L00?76DcgZ!C9e(t&fhG)Sf|zSovB!9jx
+_^6bjMVjMz4XL)S{$9mciaVeXZgq{c*@gJPF+-Uo7L_tcw5Em83B;gjqSMU46ek55HG=FUdYb0`!=4V
+y$0V_dQJ^{&^MOZ(4{eh%s-Fj?E0uzE=3n~f71y(z<JWo<9pBR*l{QQei~@k0=Lls?b4HCIYKaUDGrN
+0I1E76mm?s<XN%>>=m$C#7VXB7MN#a=(Gas>#=C9;X+ybVk2Zw5=!%Ora=4ZVgKmbH$E}`3Q{@HZ(yZ
+gq?o!Mym%c<DxiuKQvKqJPmDPr(URhcO`8_Z>bmfoba^y$<71hYlH0uXy=bq%Ku1NCpya_3OF1e7OKc
+Kuk6?u7H;$mLLvs&ro1DyNAb?bFs2ai{CJ@+O3#x<{T^g~amC*^*}8SZD)d3L0DIJC?x#?1|ahXj`4!
+3_x4IJ!1h9i)3-U7L+^)D(3@8#sCr`b6?@*Tm3L8^kW6v9Bdhc3l-wjqcF=gZczZ3l~_qoRaSYJo9Dt
+svqp3m2t7!;w0S#@&?R-LNbTqK_NJrp8~^xv;^|kfSPqFUIu_VPaFqi+8N-?mG6KyrSF|5{=we)OaP3
+Ml6R7_9$^mv06J0(b=6c+Ka_(n^gEfu`0)MU>4EiBMjSkdPzV1Bln+$U19PY($EHXR;Wt2t>YRqp*Vm
+;s&-DdJ0~+d3iNy;|k>&+--SHdy34P_UDxZ7&sC@K7|InmjQnk?3&K+2s>+y02?n|?u@P#T^^r@RFH(
+KQ?tK(cl259}J4;{k|nM=g*9LLE9LdkvsIt^c7#Gii#c$M0cyHUG$i+${<0T~AaGG#4FRK3D4ZGG`_s
+;Z-*v<m8V1zkVYQrt8Jy+eN_JBuP@#!#o&ZAdO8j<Gp4ql~Uc+D|m&s%)6He2gk*5C1?0tUD&K4(p$7
+r$Ah0I>q?JhOa3}&4124<s5a~Lh*NjBPw05f0-Vowx6nz4w<1C$1vA&7jA-^$gySADG!vObS>i5W!g@
+8w(i5gwR{bAX&ymRa4pvYkbn7UAYv|9G)KB%0Q<<lf3C0Va6!ChhaLetoSD0r@p|g_jGwqzKg;*(u#s
+B+GyDaBz~d$L$$Y#u>D2VrU+^sIyeomQP^*PoF87id5D1xFkE5V!FMc~<I)2Wd3kZro^tg$$QeO!Y4*
+9JRc^IqZ^^q4{`r4N8oVpL23~~RFiu<|WR*08;oWhf~1)9sEQs=>cz4zlH#(<hvLG=~K8NL!vkuSD~c
+UhOUK5Sv}UWKxPWjyOFM^n9lctSxez#R%=n!B}jm@Ha~&X9TpjP`gZy*Xoj9lDR1-az*;p!CX0jr4pT
+1S%>uvd>7mj!g6;#mVduyqg2RrqYQX)Gm5*7`3kiJ+lpDe<HF64I(*`8h61Ckf@q7uft{C%#nt#M=hS
+(DEG%|t5^OO<c^^dl;Dx>trNTfcC4p9ROK469G&zT+_3rLtY)m7p!;KdTFQ9JmaA=0SX#`05n#Gp@ht
+QJKT{-Tev(MCd21DKvWKGw@dlFU!SVEo*PKKTjx*DPG+^oXQ$rjt5-ISxNl5`><_@&W5ow26+QCXYtd
+UP_S&`5V+w;#q|1v58c($;zp!n@0m~mIGq1EQRSr`gEI1O2kp>Zt4tq_Ki!l=2gz;eOR@P&fpJ9PNlV
+pj8*<4%TpQRDQOpiOISq4#7s9kGUiUBRybv@M7cg)L#eB=qz*5W($l=k}W%?OP`nN1X1^<Jp)VD7=N-
+J(cp*uB8SsYHSG$C!xEx;7u!#3CeRr*$C>UCxM<?hAWaDh=<tocmh6|?1M}max>-e3LPLZ7Qj!pyAkM
+e3RHx2d)S4=3`PumPSf(VX|`PtTM(@>ZZKlx^DwFqqX1Fs!)Zt`CB5}2`hjgdqTHg9F&69rH2;A@sbe
+nvmY=|9s3ixJO`V}z3&r8dTQi%M=S;JORu(GR;&+p`S}|A{TG`!dQ%r3Pv)J)YLtD~yGCf9l-|Alga+
+qA!2UFNaJg6JrO%Dex+r&>3cizSDljN;_s-+f^({E5Mm0aJ4Hgz`nKmAGlaI0SudK{(ngweGyB~0;-Q
+58otRnbdc!Th@sNLuEXDKupBUa08P&CW+;p$7`!zZu<)>$7>FXVA&~D?lSnGf%<I&JkgH%z~e&YN~lG
+@XmtT1n<(l&6S1X$a!J>SP(OSD5u1cgfJf0!JOvNMCEnNn=ZTJ;%%GG%WWyIk-owU9B{2vl#>mbBp<|
+EI!1&XIZ9qh(2W$_+kl4I!(|7XGVuJ~&#`1zj~Ff~?}yKZFPc?y9%VQWkj-i@{r1y6lo(!Ua@<LoA1|
+c}xd`wc9TXUK9SVIMXrZMAUN?CxANcje65P0dz$|UHmaQh-gE(fI8ovgV@8VLa@XfBAmJY6^4QGx0l`
+v8|dVj}UfaZpLTp;ZMG<SBCNJ4k$zaG>2Mk(G^X@EgCm)pOH+aFedWZk=(wnHLY;g|;449gtxEnmuwc
+xt+75hHX$$EmJvv5f_D-V7KTdgU0@Ew&UrJQ;Eanu=-CQY$ERA*lrr-C8eST`!f05!~3nQTSFqLv_sF
+m+<Vsa?>=k(-GM+i0F5y3>U=nW1*$fUmn3mvaIt4;henGOvXVLz$$rI#UyQJb(y7!ss~V1DgV2y6#JP
+AuG0KeQ<K0*ln#Vk{~8<!)6oy2x?3e{{*JvXHJ&E8gD0=|L!XoT&_UY8I+mKb79Vy+Aq;x*OWXp-;}%
+>?B}BfATR1Qz<l!^ViL>Zs3*;qw^ql&CaY5`LSvXB?Tz!;`lPmq@+Bk8OU&K(gtn+*1azfSF!OBfWF8
+C#Gds%RF8n__t5Wom2{wg^HmzwwF;>5F*-IGt>);$GN@PsMosAAmGXsef(FSXT6Ru>D=PKD5va%6(W>
+|M+A3tC$@rDH;`mVhIo5d>B~N|@HxZ7imJuF_GPs`dmrno|}3unj9d4dXoO2gwm_#GzFJm3@vnFDSFY
+8W9SchqYWDvIldKbzdYGkrcDIv75nd-;)p*70cb|og<77oF`tKcw-ifpze=h{X`sCAxJ57Oa@C&eh95
+9bli4h;NaN6OJf7!(LiXuJLY0>QMvhnI1e=DGw78&m?l1u07VZdoD4^8YBehWg7*O4@)BLhIyvffh1I
+~5AtEGT)dr}6^#4({Kyk(Uy^?eS8|gvZT*Wg{QU2cY1?b@9mmkEcK}20yzHqDj;6W`k2|^Rx#Q10E#{
+HO!{96UJn;v}W0)S6mPXUah0P22f*LIA?AAX&#20s|qGFCuFr~DvZ_jd&jWjA>m0OSX8H~0u{;1<W+W
+EYL<)I-}TGR#lzdz~JLlpn-~mTyC{OfCBr)(LAf$qCYSKPHhXT54!ViikTkB94>Op%Ph830(g`ptAJ|
+e!RTQJQ{7qXfZ}<8uOC#ASP-q=wm$B>d?-j&G*VBjv;=IPg+0%)DsiTA}{$GJ+BurH8=^<^$wT>H`Ak
+3u{vs!(lzyMD0hB~UJpHA;hK;(0atDU&20xvzy;(jjNWvYJ_~!J+AREX56;3?GN(7WW>$)8D`MMSUQ(
+lK;-=?<F?blDFCmy)=+Rn1kGY6_xp=gNYk7$BE8as_-A5jZ;tEusydu|r%JHU<2MrBX9jO=3P2Os**U
+qmhH_>x30Ruf5GacpJ;bT-e#X~YR{5<)QV|3Cn8<fJ(>clMpLufU7i+d&cb-I4?3;}sF9+g>88^=Rp1
+2}Ehjn2Hwy&>02x?c@?($;y&T}EUvdxs;U`4Dpu4n2m82z#hoZ7F&aIgW0=Rt#Ijs$sQ0=2V$XsmcT&
+GnmXa=OqxZw^m&xmr|FeuruTyZf>Ki5GNbn^7!h@sz2via_F`iaYVQlyuAmnqA<h!Z;Bp9NW69KqwPl
+dqcZBe)OhESB6v|>-(v=Sjbf$l-y3SBIno`G%~$Jn5^pmxO}EWx5^u9JTK(Wzm<g4;ijg^}lId-zl;e
+2A39#g~BDViVNt5Z9T@9Yv(SZArbYW*5?)dp&KHHUnnr8K2gcY*fsT<15sp~j(9Uk=`r<tWR*_GJEv{
+stG=OxXx;HX6>X;<95Om!t3!`mORpOViY3Q9KIXjJ(uEIX}fg}F(&udUMD96Tjh0)uOm%+ON0;vt65x
+^)9Cj`xBsfibhlm#Uk6Hri9tB6^7$U~wuLV%#K{;gkJdo%nfBA0-pPVtA*Xx>OuCaS!{^$(Z)JnrAzX
+SHZ1cTh|dqm$X4`JKJX;MBY4d6le6BpekHeW|;$%;FcMnd*<RLCJz#@lpI>536+C>oTJ{*Jp58fQim2
+Vp}GMYu>WIR(Ti~DnBKvq#&``@YF?Sk%Ks0sMZSkE>EBzt1QBXg1B|x+DaJ#(H>1t}D-=hQx<QjYCDo
+z_LJS=xq}oKlv|eiLc9f%MM&l}Zi262^6}$l2w(eHJxye^2b$3J)D!gj$_Bj`NPjn`oBG7Z<cZbJ#PA
+pS)U%Zxf@?#Wn26ESDDLcTUyDZD?O`n+Tr<%?g1?TTjx8%#@O4cVYDvk%$9rJu{FL|h)`W&}ZCH+-7$
+k!6SpA);!qswwSo>mm!RM$gBvEB^Bp-zsj9pf1d0yo1;aFe@6xynnnYrBLzJ+?DrsM3nwPkgSIOm9c0
+(SG#w9qOu?8b;BMw9NG%L|VT2QEE5tG&E-0XWACV1%585Dx~~e7Vvd4Lka4IX1o+ZSq@shv^tTbrCen
+ljEMYIWvf|XoSWRJ>O`LoL{}!4HL^l3TA0uuSLsQDDZ_OdN+lqPm`bI^4#K^A)JNtJEhL)kfbqEX)yN
+v46L^#CI!%^;r1iw7pU@o?1NE@}r$-4||C-tuJl?LI5uh$xsiOpw9cP3*a{DOQe`;XLo%CocOkj@qR+
+H2?dSpO9U!V%Pl0e)*!LjEDN*&SdKX5)^zu|)O0USLa(7JAs`VWo=96z0^&y@Cmc0AxenG25xJf6x-P
+nwYy2>-zGfE)h^oN;LMc)&8U768%FzlN-YFKL0|rpE&);Nu!#Tg4)k8GAV3GCj|1G7a<OD+R&u{Zrf0
+80}~POY1_92CR(z)1v|BE;t$hlnRD-Wa0HgWC}x-I@$_%DubGre>}C^iH`f$E#u{C7S9s$8BQ?h94>3
+aw-+w{!oQWF<wb09yZ8xbicIauiq!Pp>cQ*y^w{)dYz4$>n+(V-UUKktw7sl&?qKiFpzXz{uyNF-7so
+O1)>Y8Yd!2kXv7Jh`TlvgmKegAuPn7D+du^JEBd=h^?hz>mWB?$;a}MoB_y!0Na=*iK+`>F^=^-FSxX
+{thTgepq?R4}D*?6k`kyYCIASiP`!cUL{D1dxiOB3CyW93DmDua|GugEWs-yp3pJBD{m^U(wG@ukVrk
+4m-JUI?Wkv)?aQTg7uKKUF+8!cUYVV)qRBc;q`vq&v-Ire_`%%fT?{c7slHA)gyCdOR!1`?oO6tfP3x
+3Gnr7D0Npg+sY~v?dmcgo<_#vq*QTbjR`(Or;~!m2<gO2C(5znE|0wbVT$*sgWBKw9c_|zugJB0!ytL
+N;1~Ed!qiV2K+jl;?RZc`qaBFMSsoOb7O0ezrf$hsx3FGv?kJVUKS|T7gy-bB7Cb;h_r-pOwr!>LXTn
+M^dFQAu%}Tr^s(p{}MLsXt4*}3(yt*Se`7MNjRy9bc^qTcLk#;%FML%2kGa()C<tPN5e+NB@0vaqd<H
+7?fc)l)2U18?-8x~7BN-ot{x@}_EmH|BjQvy&cb#YW*fxMcEfWXKa$<-&V?g56FN)B{EB?=kxR9A`}f
+fXAqpi1LCblX`6)lC{^kWd#6QL;G&NM4I-LUDx!@8*K0`7S!ixNCWd8FV@!m$<de*QPQn{$^ak+_`my
+R6F2!mupD_Bp~#;;CVA1?z8fxyDCbGjN#6Bt80Wi9IgtOYxv1kLXLcNs1t{T`00qW+9uap@iO9{YO%s
+(^7#j}q+=hX7$Fa;saz``Jx-)*n<LU-l3aM<1NnE{r0xRMpdW<dbn@#DlIz;!H}sR$iE)n^jfCVCP5<
+j=Xe=jH<jg_2y((v(%$eRETx_nAqx?^I-C$`tm&rHKo1X4ct8Gn<BTQ?S%!QU3bl<<WiX2NO@0Ph;%X
+4NUu!{m;-^$9IQ_F#%Mh$d!rZAg=UW%YoC}?gH6u?Xx*rk~PCR9yULbKd*x;j5i%`4EC+_sr;af}2zx
+YoN-bE>v+4{gA>bVKz(s3Ofg$TV>+=*|Kq8@U$TWes-lnN5yN!P3N<6;o5;uw2`Zr*@-KElgDdjxJ6-
+&QPbsU515IxRyUcU|}|IZ8a@j3^eZjIaPoLsvPZ`^Fxabc%m4OX+u(*DN_-E{>t5|%NC%^gLwOZdSR`
+T$2i~%s6&7{cq}5#T*c=$HL98X%WbA?Iek~P+PXZ=qRe*G_JjJ33C}=3soISQ-&E5>Ff`f>@JpdWcp1
+{qDuL~kJULx!yAvB}R4ls;P<c68?CQr3fJSn`PDWeAM_-Sdc4f76Y)f0(`ygGnadP`R6i$qrcTRx98*
+*;q_GdYpUS_g!lY{J<!0ms7J1k)^*db(7_XX|p6y>Lj9qoeI)TKCOZm{BNXwvMZt*frKfC;fZW7h<kY
+h9HydnsBG$<U=si@TKZLtRe>47cE=)Fe-987Mc!wf)Blib{_v^aq$R_ekOu7-3<4@-nX;^hOY?`_Ok1
+rZrsb>U$9_X;&XeCoU*cV{xEY)ZX$WFi)f06A@Dw5J}4?mMCq&6Iu1*f6o-u2@+_Gcg+A>e24?+TsA+
+hUdqC&tind<`QCk$a|Xo72pE*p@d8D$EK|s)=BX`^NiPpTCc@)2qRVE~xx|P!aQ`DNSxdQOb&^Zw)Qg
+SrO#V-S>^1e02{|Q>oPr<c;A6I&-d2%zX{K^Ha!$Gi9Hgu>LRUL)q6F6BGc+Vn|0DxVK?a%(W17z~52
+hgl<rtNWdYRF{pi@Ak_5K1iQCh!%rOwd?Gk)2-DapC`UGzro4WP;rzncr*iXR*MnBH|G)cFG^Hn3&7Q
+UAUPU{fcN*mpH?{nd%F;(9-G(MhCFPH13lDKNqv{-2yg(ynB2*`|h_Fq{5bN3-)pYH{;`hZG#W=&X{i
+gn7s>&Lz(+DwD{Kqh;Ts;rXGnOMg0no(6b!X~WU6XTx$~I!BlM+vzV1OdyHls;Zr^t2~5fx|Av^3nzj
+e+c3^cE5MRXGqnxaSn8q|{80`(uZgg)0_^4-@+ZWkpSAl_VB(s(i}v?d6<N_oH+X`-!yevMQN*@{g^A
+7Ip>ouaBbGCl(i^vWYhWJm$>+rH%ner$eJFln;;qHUThqmuLF_dMgK~SMn>9u7WrNon;-{uauaQqX^E
+@EV)Zo5EI4EF!6rSd&INOZ4M>QHRsS4}nkBtm>j_Glw+6Qsepa-M0@VLG{fl4iM99nR=7w#rXCnA6hQ
+@?)<E`+y16rN96&ddOC+h04!aNDmt_5L4QHa#bO0k>_|!Pca}$nIDFXXoBJkNhKE8XOtJOC#^3FsF6?
+Ltd)yO!88GIK@j~h&uT+aU09<Q>ggtxdE+#m+1{Tj)-6pbHF}Q(~?)`3@)`gy>h>t4r(W#Ej|F;2j-a
+7kftmZFQYeC?kEKXlsmwv)mFD0CBH<c4Hs(^7pXM@CtiO!bj<Y-zk`~t0Kc;n-Ne9lOGxQ3u9H3_&3)
+U<7hR2$t6c$#eGB$jDD)C;3+;OkpHKJTGx&S@jMHZqeGbs)Y5IJDK0DFX_o4p-kJ#H7ehR`cnu^K6w^
+KTi;T2VFIuwQ!T!Rn3hF5mqw&^@}?^k#a_Ml^ge}_9TN!mwf9s20=b^6?k&nLR!S?@T>wLFUlc#Sotb
+JC$_Ag+w&;2z!v(V->X^<sR@R*pMxl-u9b+3RG)ZVtIqrnv45XK?#lO8Ox_z($C<P6}c)UZs!T{9-(v
+dng<5s71knowzh6hOoKNreBR|Z`T+K#8VXL?asgr$)h4E<f}wt;^!B)@kPZEJ{JO9a6hDG>_hP019$~
+?2tUoe&!@f(z5fB<&GZ|`e(z(Lg9dwp@L4Z@cezk3gTyx{I|nNQ3WHQXig4&@jO<;7XOL<7o#9OGz#E
+|owo`-eEkoevuvtv+6-m6aFTgvX<ISOXDFu3s6yv}}7%|-Y1*<hYegnT!jQe?~7{7}LD}5^$JjN!Qgx
+YQIAr{NK{w`sh>6{)7Hbw7m*<}4~y}wR<7xq3v5vPmsYlX@6;!fjyVZ0bK>luMYy>}yU+^(fwqoqEFs
+d$%P@69xI1J_bXKkndK%IU|wT+4j=A#g3l^kW;>GLwF+;aVo+$8*RQ&|Vx0w}dE%#b__nU0Hf}eQ$rd
+-s}zBqgNYoOZtcrad@~#@q8bi>08X(fB|mR9LTxgCtz}jM+;+=n-G)6)iNcq)@Wzw5dL}%z2rtZ)K9w
+u#{#I+(j!K6Z9rJuo9X=sf<u%6OOQ^%4rY{chnTTxLb@I=AEG6J;I<q=B0--IQm8_$>*cix>1iyKYdL
+2|p(|wVekKRcVq&EDTpy*%J`4m^?vZiOo?U4zpt7dJmnJ^A{o$2va%h>prf;aMRA~ds4&ifqXYXk<9&
+!Xie+=~ps<b?T^(N_D%fJX;+Q<c8F(YA-A?<^e$@=Z<93z#U9mcis)?oWE-qwZ1x@GzTtr4rJzVLen@
+APWd?%&pa59pjLc}ks=_TflY((5Ifra@?p)I?A3wRm!2bWBhWxhga0q;`$0$j;mmMhambe*BZgM@RXi
+_gfRPP$wN?U*L6Qqcn7r)A$=Ay`2aW-^4xoH*{lYc?-{t#y4^gAExm?;U4({_rl_L@b`%Ed-x(`+Td>
+>O(RE>v=14F{}+8M;Ps*2RAr$T$zX+MOKd}b8jXa!wO$S)CxhCku-d0&icz6Pt36~+GLSPCMEsd4F2d
+2qwLFQ=Gat!I<FY5w`#vsSj0frQ6Tzo(CG`op$<e-p)dYjw-h2)n5_en|`mb8N<%&G@1-jxO>KZAySE
+H+KEZya}lBprXjIv4dmKCFb@i9zZnvjBzk9NAc4@VMr_^7&XAjKXK+ebk#htI8+IxW=Gwo`r@n<Bnm(
+EJ$+SbmyFhXW(z>gdobSBI^ssTU7nMSmjX!!Q^FQI&#dy8a4boZbV_yk**W_4Q63!R8E5nSt|XI?|;`
+B%8UG2NIOUTb@E?1E+<zsk;(FUB;w(SED}u&KlRU9sROOz#<49Ljq7xF}xDOZx7R3>5yA}0Hk-64MhQ
+lN5?i_pnW(s`tWJok);X6%pF*ocv6|9rvYhs(~~e&p3tE5Xntz&#Lh|E&B5^IaYJ3=31;Xoqb=5pd<=
+T(JGo0R+EtyRjn*+7F-4>zc}Tmsi^lIr(>WxX6%*1fp>t_y-!NW*M&s3xHU;fWLkRu~nG)p5TiiYmc?
+}ooA|=w(4<mvu`8)Ak*^V?*2no}gvqCu(3L>K7wo1KvC`p5wK0ya-9lG($ZA}YGc#lfQuS_{mlT&R>i
+L#IizGqW|R!bip;7Z2L_2L4CPcub=s&J;5CgVN*h(J7q0}47}FB+$`3VWS=@$Zmeyg6`%lC#$U?_wow
+uaVCU6xP&Bp<@*NX&t?M2q)@dDlm%=Q9XmQ;$Evzq)gW)r9h!JE8R>U!XJA%gx_inZw{(EKT`K$9{CX
+JVe-@O(Xnt$lY|IHTFxfBm#wMcuhKrv!lg1TMVS&P(QwPro5|dZv41KaqJmAhQ+}FGOs96-E>p(8KoB
+P-@UwIb-bA)Lwfp#k57Um_QKasBmQt2hj}}J`4XCQ=5CYT$Pwjj`xl#<#f|c3Yh}K%9(q2rqi)MV0{%
+(X;O=i1YZxDaE-k|T1Y}LTUBohyzG-CJ(D%Cd0^?Pu-qj5DdRWoHeDnJ{t4@yBz7i|MJ>g>JmEb5@BF
+M#%b2;b>k&~Ww#)m=^Krd+9B{C9Mv3f;iSTk+_RlQ{%``CFXK2Kd_qfBWI@515v8>62@1z?<pzaBrG{
+ZaFc+6tXg!QnP;zTDW$X_~#7X(}LG00>o9L5Zh7^cy)k}ssWCVx8#wmQJ7T#)BC8lZG;|#&;Ld{1na~
+LW^R;Mv&AR51LkWky0*JrG0N@q=7fu`?QS#PgqL=A;HBN|{GYi4o!o&)@loYEj~AW2{091)SxXn|J`O
+?w*?CmE2v@7msEc7tv5DakOc}j|yzb&#$hqLpnG|hGkEU9+;}6M}x6l<Kyny`U!x&K}*tX=7%u!I!AE
+?Q{9;~DPS8gbuci|1?^mijhe+<OM9*<Y0?q)`hD7;n)x0e%g8oD95<#Jqe!wZz%9*_C~I#)#b#Q~$6?
+CjP&SrQOYq6%?$Kvl0r7!Z1whrsA_lfOIlA2iFOHz_%y!hZd<2lWBKpXeH-KU4S&pi&fBg$m$ZPCh$Y
+byLt}dzwK#K3>inmU-zf5!QtG%H$oJpL+u4Wj=EDW4hX1BTb_hKAjTiKJZ2jms08_2FQn(HPnQ*8Tgq
+2qmLZ@m{uMgwibJRZo(W$-nwuD%x0naJMi{S;m;~XLH_MOAayo=GU6;IW~oSdxz(&)Ul&#BMN>qeQ20
+sLF?y2j`qQ7Mzfs^-^X43<KZDcZ_!bv{>Z0{!IXwM^l`>X{>+gO~aa(AO5vHFHKT3K<WJBH}%o|(3wl
+3=N`pE6tebCD17hV>|Pv6V(Q`9XiAu!;Z>#ak>xad|RrAd{nRB0Z=1~SvUfF5?gT-;_e2}QCqx4h8uu
+ao(_@=NfQQ$7=4>E(>`NxW+3k=GFu9>VsY6`lIUC`mUzFS)T@J2c0&T!WL*ighq{<%qA$2BIo#4ZV!J
+%Z^yXH_Z|H71?aoeyD`bkZv}3f{Gga2|DpRi(thY_UvJ2Zx4+y=)XT#ZS}}?w@E8*0|i+;$AYN~v4Nr
+*dB-|&Lm3N`wYB*i;@|$2%*Z=7lt02SVId<{xdC_al^x}eCBt~~Nx7%|=gBaRQ>Cu_Uz1_H?O9n-9!i
+FB7fe}H{%A6cYvsz7<-bUVcVT#X`97l_4q-T_{3Q&hLl{?n)h!zWta_qG+Oa`N#|Ey%K;3O?Q+H|NiJ
+>y;R0#zC_me=;QoIoePd**Kx!VaA(89v4Y)hEGGN|%J3ug)$_71R)9*@Z9z!-9q)lTh~Ou!UU-UZO~O
+0=1Tv-D_V(p%F)DgZN#w1U(~!;3WO&c;G*obAEip9=A52Acg#I>;V7O}Vi~Dn}6k<-e(6@F;dKX@Cq(
+IKI~4_%e9NznrGy3r|H|?*&P)Y+CYI$uh8<O=r*}xm~3QNcmGZZVKq=y6lHW7Zyk+QK<g!jjr(jPW}S
+OO1awRv4_1<y8L%}wKaxI_IQ0OpMk4>F4inf0BO~<Xr_So5V{gC&g32sSK^NELNy)4D7!1I)wo1jZQV
+7U+aGmTlC<kJa!ydwaj^@g*J|soG}UEoHB>?YP+ZF?{u+9v?eCg~3wcY^aE9<7fXUppL}hU451Prf^f
+C<XIo`Z5LrAMs&a6;AqY0h*<N+0QX%)1o2K%X{cu`H|;-*FG_;Xm>OL3oZ2E7j48mcrjEtn~o<$fg_F
+FJr`KqH_H$9rLp8Gi#U+_-KDG^j)P7TW?n$gie#WT6T-EzIDT1yAwi+~KerfM=0Q7HN&l-jxQ;(;BCy
+kG53FCL`q<hzSxPX|=Vo*NaN*2|m5e$RNcqgRM7*-U-FltwmU|kWmd|t|rC{V#}uKynXat{YS74mrTJ
+EP_5JE)8Fo!2SRQ)vb<Ev06)OYf@_rv@&%J5B;?fz+$iyQLX86?lm0X;x>J?oO_rN)#C?}@>gFYKJo1
+GxWab=^hHKsAi4W;r$Br}nTs^yK#OFl>9p{q>s`m7t{#{CN>I*9-%^71%)svFD%RcD%NV|lvzRa#m?h
+;*cmk9knxx7UC_0r;~_jugt_ISOLYe1Vd+xP`;lJ+4znwWsl<z6pNnyN4WP&jGge4QXAPiohvdvu8p+
+?k<&rw&T$mrLRDD*gs0GMdMCWX0#sS6{^+a(Be|>|m7780y@Ew_7P2z1VIw&x!bigk6ZMc?%I=zjlZe
+-wSA%{yIS3d|K{+-PLdJcMJ*Xhi?YViY<6Xu*z-O<CZZ@q}!I&FVWjyhE7VQSjrezoxb_d*@G@ylUMG
+SYEQS;j!3ofnCqB!DMTlqA=SRu=2C57f4knpG1^+IhFquJWQN9yT=1hb{4sj4oP#c#Fn-8oW1Q&>{?y
+TF-rQ8JHpwoV*lj9~;_b8HSK!gaFRkL|RPlx6=t0~g7jsnd+`;6w$~SvZ$Ljrv?!FBuQ=x7k6c8-~X#
+2DaV4R9cT0J1UasxKJis3r=yBz+e!JkbePT{$-)dO^>^(oV1F1(|QQS#t}`tMrdgPLn5sTL+z+be*Wn
+RS%@oTZN*nQ}yS+W9%a&_(z=%H?P(@~g@jKqFicb7@|{tKh>-S2o~-7O<q8u>j!wa{NtC$a<8YOS%sv
+TNpi%Y+?2u?P^BogP2P@sFMyK)WmbyVy=E%g$Ty@iE?%~aQV>jS=IS19oy3Nd%M7D9N%1x2Vl(2)dP6
+rlvv$o{vBHQyeXrxe{Uh5p{27*)?OQ*t_5u5Pau57H&qE$yGuyr0lI%7O($~?pn{7(r$(m3r_A);rpX
+4myaIpi7ZlX~n0D+(AR*T=7zTYX5>RJ_!O{)bHo<sCU-$5=c1OEV3|(g6XE$#gKqZ=Hhg^{N`x&p3ul
++~+K_kgM;}`bhxrUbgSTh)#z4d0SNO#itRjBx<IPeG10*HlXqc=1T3V$G1@5grI!BpiL&2zR|O?l2%t
+1LoaODdm*g45(qyremGc{=*a)a(N0?l812H=4hfPA_pb7Bv+%wN{^R+IYUIwOSQ+4n~@|mc2&2@y}-D
+HwBCy!2io0-3it)EKDXZ>;p}30V+Ve8xn5?gQHiao3dRDIw*8u?2D(9`tOu_v9W84FhPzzc?+gYUZ6Q
+?M){-EPvly1T@QtYm=^|JDwID5%0Gfb^ksVMT%%3kWY_6gF~O2iZBtAcE*mi6te7LhSCk`j@pD0`gxA
+b+y!(uXj9SRdP=(XX2-DkKBL*cOrj>(u@g3!YOo%fo|ChZl0jR3#+TKipie5}Dr}C;e6b=|_A}SXF1p
+-A;(9{S81VTW#*P&EUAjK=D%~n>XmW{8OLz4<>&N*a*+2D}YAu1_N(a8O;XPt8{2L!Xe-tYbX|NjoGy
+Z6~=4{NQx_TFpHuJkLk!fPsco%ci%9+sjxXH11F)LDM67&?^>Lb+CV@(<!#Vp>3{sc@FIe0;a*p$r}j
+b)HVWF4yTk`IT;_!tod--5Pq;PllNaZljklQ{gZSorRu}S1}z_b`w_CJIBQlE0VhNSVQCO)&p_uFuJ?
+8_A6kAsbC2P)Li(k>VC?|FEy^23a0bixU)5l<ib>l(TjO=&YXLHo3M=q)x2&?Ll8H)l2_A1sXS@qYFZ
+E{`F3|C_Pvjmx~Tx`OjQg%RvkNSr<4kzc9ywwQ+cK{rUeIGr5{@x@;B-=l!3grwJM~@R#_HLgbf0bwz
+hF;&g3WRv;*hu)Lb(A2XiWZ>X-7Ti7mi9&1JlOhtKZl;*dd1?JMflmb`*&0R?rb3^<YdHB}WP*Vmk|U
+L4}&y~yLvsH=IWa(zAO^MNHfUZrJTC8yl;PUkk-mpA7RvCzZTfot=&2vx_S=dO7k<{CB0T&_uGI*P4c
+m!!F%Dk0J7j2eb-f@_JYifR<cQj=Nhx!l&B4%H0(l%LR%EnA6^mwxtx1}eA)DRON}8b{ffD^l_{YQ=R
+0>8@!lQp}j19=u*#jEr+?TWMET+L|k0zopmmU03i}!8oe>Nr9c?p<Qa}Kc}6Q3S5iMxmVT03@p}tMRT
+f*D@Y-O_Fc+^O6?Aolg6W1>{M^=CWVb!6!{h(%0lV;&pBi5=0E48%2`~h#TlW|Q%!NvO2>4xdd0foHV
+&nOG_G6aI|S7u4xl`HVEm$`X|ofq-ffZ`;B522R>SSi<=>H`X>%i=(poE2)ziGjpc+cq^9bK1qNE21F
+;PDQp!WG=ck<C_VO4&6l=XH#f6U7s-EEXT+Iy7Jf|pNtTyy*w4pj^B_8JqNb~WYjBel;`BLVkzRnI;k
+U)^w)8ctD@)&cpmy}L_mg8-{{_vt-~`%JfczFidQ?TKU5X1`4p+AZoiY9ViXDB(i0#PhNfpsk%|pdF;
+<SCVMw_j$8ifrHJ<KGM@Z%F}<Ohs}*i+YvMJeJ^Us%NuJJJJPz_qbS(5=zh;JBcsQTn>cPfb=KwK9ZL
+2_p8oJiyIHZ4b=*ZaGlg)rHcN9#Apx+YxhQum=kiRpiAzW(9sG{Nz#f%6Ty{`uKjN}0;OcabfJ)Q+7q
+CC}GOrwIr>`7o9v7Scy(#}YQ^3`G<85wbv-=2fX*XX@)}pk`Isdc^b=tFUKfgwLKfd&F3}?KDkNIV;*
+`B1&x$KeNg{vQ<eDyAVfj%!K(;Manayv=jN-v#`P%q7W(NL#_!<-fkb*5++4s*`m<&wXfBR}AXyg0nt
+FZ*)B4bi)u;p-)bucfM={9W*ag)8)Rp)rmHWLOE(2@(k=5R4{>BnSZwAxq8_g*<$QOodE^%pb}8k<1D
+*E6BV+<^?h<$*d%^ip;8FR}2vdmkO6kof{HFuO-+(um>*Gmx|xJV<|8++EwZ`7s9ayM~EG|-(qX;s^Z
+!HRazc+SLZ>KKhCeIqIA1IiF7Z0L7e{T38q)ilgnzJ_#jVwpWr-!=cN|1ClV|sSTxk7(~*V4T=IWr?w
+w=qtv5ss+%!McdG#~-<Xl*2@VV6Bk33c9+0QQd=YX<lKDwMW<333^C<GM*l>~yEJqWxAIz7pG(~fxEj
+?7kMwj#3ynJvilBGZdZPcl8p^dQrNOjj~pYvzs0qk;4rLNJ;j<w--{40R!_4SB)uHS@vfRwM5m7nj;v
+Di>dKj0p!mscmhjahquvFX>NnR?aO#m5a4DsP9VoLO}0DPWh$S4?bLVu$|+B8H-nY8w|VCdwkd5;rt5
+ew>`g<G<;n3r`Ut4DCC_5XRO|@kRnV48N1M>)w%qm;vk7sd`fo|2VHg8{&3i;G@I7*^R8a=LnOvfLt_
+v1jEyS_J)``(UR?*6KWHFz^-1kkY;#g3lwl<C6DZWYN!trm<RCs9Dw;m=V6v%zSGx1@OVRSP6bnAALL
+~BYym#k!i{ssk-$V5GRgrCRd8O4WrBdM-;TA@2EAeBGQq+lGQcj2YH-TSkU^EU(g4JG$>vjvJwR_>0)
+^0qq-MTpHtC4A*#ZeU_)10E^QJnK}F|^XjMja$lNzJ0%ZzXUE2vw}N^GQ<Hj`A?|8WDD7i1x*#e(^x>
+1s`Q!rU!0b+;*OUf`X5{qDY^``Kh4#QmxwO^ly4aR};kJj&u5P?1)XfI`M1!XSh|$+JKta5w;6N)%QL
+}(EJv;Ho`?y7_`w(?%$4+`x9TOUQPI_I&3_~gO_rtTWvnJdHIjwtv0-O1;arqGR>9S9mwQ7#yZQ_>Re
+KCk#qTB16I!EpV+tO|4vGS{Z~wX0GXy5GF=Io@{aaje10`;_H3YC>WEWRMp#|$wv}U;A9rnFKX>6QJ{
+1TNdD){p)1s4$LL#n?EyFnwl!)^5S_dU%X;M3-oDYDRd0YNv=eeHwmtAZvR(kX0Zfq1aQD2n!wT@!B_
+ED`^));|Ng?&sb^#-J)bK8?9X5Sayzm?U)60qNPF@LYLZ}%w;3)nu#$x;;Bs%T=R|3q(FV;+LXExw`N
+_P%|1EZu)%x0o2>1?hE|4s-obJ&4ift=<-0LESkFl8+*1{T9kg+AWlUj$0`2IzaT*x`i^nNY=WA5?3X
+<6ivL~Kk<U~^*HW9LvMo$=dB)pc9IJn_7TOzs2*6C{ETOS)Z@~4c%zWCxZCZaW;nhs)T6^6UZo=5&KQ
+taKilV22K+vEhynS2Kt7;!#?8u{{e*c{!0*<S-R{6Vf44_@n`q_5g|(4auRtJ=fznn<NmLk8L3xXb@t
+<h6xyHnlH;^_nZ;q;riveXVF+N8W#3@mB?z~@6LhL*aIIcM9jN=B)!g)1s(DcC6q}M~(F4nC$v;r|{@
+m4Fl(aKrA%FnyToZ;R&?mdN|uoSd2N<q77DKJ9{TCfy&RZBrTNCAle#vgO%4xA?|u*am2G4BKRU7Pol
+7hJ<Ws%ow86}tvTr->Nl`=hM+fj^)G63~v>*bH0BVz?u;nwQ;I#wfQe(wS9#-RRi7I+*os0hr~@%&Nt
+va-NZFR~MUNwSyHWyI{7&Rq2FSrh6!D+4NMJv+1QYX0wIj!e%Sw_k1$@DHmW&H!DA~>8+e$vzzi2o86
+U9*z{Enu-Ql1$!0s{12+3B8`vDEyq*sXEpoa=S;<Zz%5pZtlx1v2Dn)EYEA!YKt;}L`tTK(w2}&xP_b
+CZ%CMx6DOi@O%nXZJhnWY4=X;u8$oT>C?bGCB3hQcOj*h*WtZo(Xu;>A{+W1_gR73ZlcS8x{iCd_;(=
+h%vc%*q+IJ_YL+Y<(8igKT{P)*WnJ4eL8>T?^|Q^BreHyg1)+vcr>X#jy~|Vzy%Mh%%3@I7>j8K3_u_
+(;7+&e?Y%mnaEZQYAB=F`W39h*os<48OT;l^(npCs=(TXtv@pTY~^z!yx3a7^t1H>(~tYCHdQkHY~^F
+Y&af53jLH{m#f*b;kgeDksO*@hp^WWu%0~VG6-0TJtu0`Eo~^B5eT=PGaj6us)eP%gwtB;w!`5!Frmz
+(k87mXn>I>^Aw)TN_7+Z0ljWUp}17YpWRtv0M*ct+BTegP5>ZPL`i8p8d5Dn|4JXmo=u<|2Y$HIDwtr
+KAVjIH;<x<8Nm<@eUuQEeS(ZxG<dr;fNsD{J%k=uy`Iw}G0=6RL|xfSW~gDNtQ}1Kd(Hmuz;K-Y1}Md
+Q<gKjr-tIGa*v}&dae6^$c(e(ZUT-WAX}c3)5V>sV*%7+#)rXn^l)q0dCQni>vC=F2HTH=JIPUyO;yq
+#%eAnRTu97w+WidLDi*yfLoU4@`36yFu={KxxA{nSOVN;YA#QyE+GMKvo)88RF|*-w>-_o$}ZC*1Ns(
+d)KAJ)sdx0JW3_2ZdhBC7(O+<GgwwvaJDFZ{^)CN~7(@yKxsx`(r~!Z4<z!mr>Yekmy)=KPS>F{(niy
+$e290a;^SZ|6WM_@bPrancb)j?lX;Q8#7I`f6Y+xzi>zU3|kY>A_srWu$t>W!cZwacoU&IxMv1`|h54
+1ZEaI*Czq`C}9aI$r7bjEsXsp2&t$l2DK9GeYDaItw&uOffDYojx^kL{$9?O58j<jBeV5~m%Pw)2Qgt
+3}R4D@F4?5lDf)y0jfrAJ)~$b`1T{hlAw03-NzQ@oynruzaCm{O1PvXP3-4Pn~hU6c3dK&T)6EF-E7t
+AwCnen_sbk*h5)AhYzzZkBTez<#YdHYjnXD>POk$>+gnB|E!i+<<~Xp*#o!cUp+Z}f2?vE?@G7ls!tL
+GSCw0y!$hP$lDK;XX89VFpH}1wqx-*9cl+-0eVUGniPM1n)2q)Z^vW?Q`&JlEW)Cv`E6OW2&i;%4L=S
+6YP_gD0$l)=*vDrha)Apq9w+Q$q$IIt@Y?^R65u=>j&+R_8$mko--#OEUDu?8j#;qIZzoDz)CyNUEoW
+=UU{`~7pzy5Q)SRsA00oHcd+AE<eusvS!S>e!`tqawCwDtztK3e<LnBsQot{E5gcFRSP{k@&{9==?(!
+kgk;SR6>dd6%87Zh4oTY+b3daOnspz;9K)e^%X#bKu$P{jU^#*{u}!#gP84W~&L;zv7JCk6Q2`c&sw}
+X6@pU<v2{;<zk4tYo4iKG0p~S_7ZW%lJ2+HKdeP@A#PzZJysfRcaeSE?Z3#Dd3<gp&X~E6d<Xnu_3Y2
+6nF^wDoM6iW$ifO{2?zEoDJtv^ri6N#9_r+Vm7o@ST~vrb1tq4!DO3O!HMVc`X3u$-8(}uFu-#dVDZA
+{>pV?nnTP}+3vvACXg;Brd-`8JYU*Lu4^1Dr2OQV&ht<^dB0rp~~>9gM@%FD0B60pbg&>EhPC@u^k_n
+2tqkyh11?~jmP7%Ul)^0sMCF{-C%CBxt+gKuJwj!ttcj=Dgd+TvpP85u1%f-EhxsyV9*d<J3Duqb9~q
+ho=iy%0p%1+h*&#}gcHgmvv4*j@~2aVae-gzWflL_pKxi&%fY1@vQ8x-i6vS*hwscZFVPQX}HGI3RpF
+nHH~us#u8lCC6TdiLQZ8R@Z^fwhpGvetvuNuM($Au}PDWaW2{j`ihE?vgUD=WH;rYnV6g$z)Ug~h9e!
+0)LFyRdV5-vvC&2RU0GSfb34YPKjQ&xsP^^e^i1<FQ@^0h1N)MjE^4m&SvcC%$KJFk#MHm+9PUrw3(@
+Qk(OgNdd0QYeqNrGn8cLZeY5q|pTYo^3_xoM+VL>P^45QzGD6gC@i<$=q6|F#~<y~n+RUG57OEj?zUF
+c;QI`67%E=2aH_6jwKPX+khP0d4gsXH5kksSMTV$=h6nHC4YZHEt62m#nPnoeYwb#|ccY%2VyCemTpu
+d)XGAly~VA+kvJULYTA+T7gb8<&GB{`rJ|8>fxHKds65<f2w~c6Qn2v=LFLzsW^jF1zM!f%PgVd*`oG
+mg;mZWw`aW24%xQ+1>0@E$iKNl5B7+#;Zn{fvn3KSpoLPS=cw<<it|%auB37Rf(#XoV8S;WtaF}jEzk
+h(*(O+D$1!q78fI0pVH+%+mBR6+e@QkwN24nGLHp(V=8!3D@9B@k+CbfxS%fr*Tn#<r^`lo4EQE@f4Q
+gH0;!@+E)(obsE<Z;f1Mq;q_RAaa6w4y$(I}9L-y(Kh_<E5)BH6dEW{kPX8ifwh6r1F{ucIQ?UCkouR
+j+-TMOl<Cmb6he|rLZiOU1E;(7TAEEDam(}K#}Vl}B5lh?lu_l&)jH#mGdgx~mtx}kCpAz)`je7I1IS
+C3k~S9x|CpD^i_V!;gD2TvF_h|W^OD)&Bd-3_9nG;eoRW1Tne#x{ultFXQeq8XKj4WeH^?uhy9<MnP3
+4Sho2AbP2g4+8Q^xeqick2`2;t~~O%k(QM;X}L+ssZQww(v8ZG*GoeKrr}_WQeI%7p#jm*o3Mvlv}`$
+BT};tf%X%WlH9zT$;5#~6E3JW8)R`g=rRp&UR&@}T{<u!qZA{q3Al~#k%R^YbWw`6i#`b0lov9_*R8s
+C~+KL@v3Geb6eLh*K!4BErPj|l#)_1@9+Cx1SVe_kfzd}e!8S0TgSlXIm=c~!Se_bH&eC3U=pVrv;s_
+lBsbFQ`P)l=K`YM+C=EiQf?r<86yjNdJ1@LRZ+e=GQR5C1Csdw_pe^Y2djRhH$@&yh!Y*XtkJuGj64I
+y9lix!4Bq&L7$~0Gw*7?|MyW%qO^5Z1=`0O`zbuhr?KKj7wXb-*U5kPyVU)_KMQ0Zl$LhxOi^lV{M%6
+`z{7~=h~iuzt-^ALZA5N!*7Z;U)wKQyz@+j(=Y&g5p~cMvMp*}wDBt@^%(ztz`rlh@50B=(Qm=Wrh@g
+2NHr;1QSt{g0(dqpE>ic^4#ck7t+jX679$dMSFML}S1p{etM(igTey!Sg>8XZ-B)|>`|7@0FqF8q*uc
+>}1|C;9cwF{9_SJ5!wXZfTOxstxm-p4ed)Zdrt_rJb*?NcFsq7`*R|`AFZOWc>d~z<clRfXs9k%ZIyI
+s}Hx93(BZ2=~Q(o~dQ9pj}Ha4frrx54iDL)`|uRoe#3p8|PfE$9+uep<X;YR0Q*@wVW2nFVDY9HUYzM
+!c8(<bhbitz+`8q*z1puB2OA<z1O!D*V(#Cx~~|?t-^~blc6rnxhx#xtxb(uX*SMc$Gcxu$#*sCHo?m
+f&FZ^<vr-s$JUAzF)eJKBWx!58R*A8?o@rOfe)FBjdtuK3O*7|1)(st?X?3lO$B{n+DrvKV9qoZbcQ+
+BRB$VAt%Yo0hb@faLKMDe)28jw3MSi0nO;-~VH{`eXfH;QEM_rOp81^w*hLdf>^OZKrwki?%)&;v_uW
+-l!JgdByt8tQz9$ze60MQECzpf=0^|`EMtU4|3i7Zg7m~>99=R}-#qjQ05UlR5eNNQiId;cXf3`KM{$
+%HT&A%*dZn(Q3mn1;-=!HWqt7YLNN>{<}7_66$-DW3w3mkrTv+(o2%)R=KS*WvwcP@4izKumtgg@3M+
+Bw!b60-W5HV>;(&sr}oyzmF_0YmAJR!p~OyJ4;EcXRpUm6FXD4Xawn9(S`pII00v+{$JlId_LtQ}BW6
+zSzEM+Kzp(@NI3uYLS7IKCVK~`m%1Wj-9b58Kv#GG`9?A>+{aoe!Qo;qqDX%R_Z%r-{#d<sn(g;8G8r
+sjQy5(#&QW)d7;*E)^sgfus`;`{6c(jwX<Q*s!~2~sP2)C;61WjFnEtF#0hhA9;&sdK{bQQ2D>@f%~4
+xaK4GV<ogFTfs(WR>#$MU0_F<LwxT>;-&b312b5$UUSAezZX73dznafYnFSbwOJJ!sUr`ek2U72E=tU
+7Tn#rd-xyC`AK<H&fY?I8O`cG;!wx9$Eql^T}kaYcnM{Gso+<&-ueCHpb#x7CB&-L?I;yFH2u^YD3CR
+Z(F9%9vVC<wlee-fyconoI1$WiJR3W881M1+-$n?f0m7vEP=d#%@}UF2=auHg5~?#CBV0^kCR-8^GIb
+IYXVenF1X#WjmP~#-|t!cljN>)z(TC1Qn2i@%mQVtxkF-?B)hu-Ehl7qh_MI;kNHpj1Rzr>&RV&pP+;
+<Ec}#1p=rXvSXr~HoYB13_Li$$^e&c~t*umsTr9O<kL@ttV>_&Bd3kf<BOJB;wGK~p?XA_x(~47#y|v
+6eT{!f;wJdbn-ddwn=zD8{bg}Kc+Qdk%oQxZ5LAbiHcCv@Iu~rof$HrQ)Lfu#!dY*UH>P4!kP*o(js8
+8lSLkIKxeXV09mwr3{?sD?Alv~1izpQ(HiF4sz+pj(>fk!IKyK&X`LanN=+&w&xe7jkAH=HW1oK*f6l
+tbeAJ5G9W0~`BNR$y~&Lp8g4l()gTzS^5lxhIbHY^J`M)lB3i*xYLSaKt{E*6|d_=xOV0uPndS*t)DU
+k5F3iR#?1A-ZXkbZbT^i7HEF<73`T4p*ogZq&C0l^$Pac_EfE|6!{jUQ{GyQnlxD75z6})YDWHT{uZt
+!)eN%Q3QOirvu{*cu@q%+a|2lnOLSTTjLQ@kF2qazE@!20Gp%N~_48*}YfrgxVQow~45OLDNh2;XZk+
+9<@=p21j7NDJH2{_GlS~`?4%PPB;zi89QzOcHyGGPCTswWf7T5B(pd#X}wy-FlOhLDl-NxCud0*tRka
+d6p-0aGQ#qZ*x!)1xgf7Twb(-szYQ(^IiI#q17>UONr2%oI&wEb?qMSQ!?B3iy>5z`2^5bPx|k$ceF7
+NMTE>FTqmZONs>o%Yywb`}++%I?W-WG@}}m|YaPdhh7LcUOz@GHn)F8;vart+a=F#l=!5LlH9wjYD!=
+z;0VJ<*fyJSIWNI{&{%>@2agD$s0}hEG5j|@3uA9PZzT`j8;}*g1G!p{f8(~Vq=InzKJ0ZeagocsH^@
+bepNK_B(^S9UbVGT!WO7K;U3jE?64nIdzmHF%XHIv%x2A>o5P<nJe%_K2rn}&9>_fldxh59q@F-zZ`b
+@&)MJiT=1i~EV{TXDnAFeJy{<)}UlolxS>9S%^^hZl*B(;0CNRo1yO>|u$DC9e5HeV9rMx@cv7S}EE}
+JhBQlc=bZ;$dQ3c{iCP4dG%J$482F_q=b=*6`-s0Do@Csf+@Admb6S5f3tz1tEjGATDX5W*^016OY1U
+b}{?g*sE^-(0)QnEKsL)bF;`wE%^$m`5is&Q#cs8{|%zgz@`&Pp@aJa#N;uU}wizr9o!R^ExkP7|-jZ
+ZrzSW7H{v|fzGA^%*DnkpJr$$e^NwyGpZxnl2J3FH|mMV$yD$>N3_@wQJx_pYpsY9uZifQ#Wl}5kry*
+xNOQv-WYNk7PhGWi=L7T0C;CbMITdq#<#5-TH`yC3iX3!dp@+Sxc8q9KV&R|*vC+!lSF|Al>z-i&b1G
+&ZPR3Pq=KP_qS7$b{H^naLBB%TY&gD&T3_b-&@#NbT^g^B(k3z2Qz}n;Fx7XioY}+7#jhK$5a9*4xIB
+3+`(to0t)vNz)xYx!bV24#*x8zrX?K;}N_qQkWzIXqzEo`@`o*I}oH6>rhdv9>h-+s_-+SDLg!BjjSd
+@~0d<`=%st2UkHcJ`0*nr-&`*ngsj>GAEOh+iXP(;CVwSM~J7!V>b0RZ?C793<P^|6V6+TYDZ}C^1t(
+GG>g_Wf^7npqNa^*N=EKB7>2I0A6;*DV5*=GKxCQsb*@X!U3q@-&0qJ8#bnYsutFXhLs~&Rj0f%2`Br
+6df1~X>_u2(VA|{&)ESy?T`NY^qwvuC88_~l^NeG${JU|9t(!fPZ^`!b`}oo?q;7<GdyrXS-*G9C-1p
+db!E`xNK8)-W$OXsbk)I=FN4`Ar!;xc+_u4L8I&ZHaUoFT-h_~0J?_7>#Hw_?vGd!|Q0pxdj!{I*kq3
+vkz7Jgrn&4X;7myVOJbzIo@*^k=4Ksxts_Y%pbb0s5VaFno#+Ra@1_WaYirHZ@tE^U!!vMJYzAjk_pX
+8ic#$AX_|{M?71tl}alx?#4%g&$k*vTrX{T&<>Z7ixA8zBt?~%yu#Vw8`4ezTNN3(jT0y9!0H-!(Ah6
+mH8)KtPK{n4hpkf89#Q1{n({1^LKdp9Q7+1Wj~sK8sD6PB5YSm%MpfRa=qJDc~99G;&56c*>WbXWW;K
+3$Ifp)&v0%NoKvVQUc*<3RM<n?X(v>-Qf9InZl1#3%y5b|oKtPZk$yMZ5Blt}xurReEpO~sQn=T&yre
+ipI90D2;QjUG-f?`$-2+?otx8_@1|%FaaXP?lSTWd|PZ^*OpV@c$xFJkwrSqj@h^P9!yh3eD<Ls4wCH
+6yw(i-XSZf%%f>T1dN7q&~WmNeIB<;CZD-zaus^5q^4m09s<0kEODrO(x9Wq(6lNQ?ws@4}JOKjnA9X
+3gqVy+3;4HftOue<5HO@d3*hw6VJQ`_)NN<Y0`wRb0`;s(^2-Noj*(l=c(U>Dqv+)-eGmtRwwOlKp2m
+^S;B%m7pNNt%`najg)?rBdgeDmu==s?2Godd0PDfc3FEV4{xJyd~yNK@h>cy6{oaji*>lNBv;1+`&@A
+vr@yU|L=k%wciGyexhe_I5v8jtIBM(hB42-IzpXia8p@y4RIS^JeC>SV0wMpl4>p`s9g#(IDwLsDnTU
+X^rp13?MWCOl02}*@`@ApvDI@OX6A7?PkheZjom$isEvu8?MNlv!&3SwbcEUz(p|o6fL@PHx=itdb^n
+rKDYTx3NVK&FLif6ewukhPj>^h8UPO2zec3k?R?cPgAI_()5CtGG|*Pi7^U69Ixxq77*r+hFG*UZ=|t
+xXa4n-h7b;y9u%^g`Kj&@$Y0SW#0#-@k$FJXYMuKvVv3lnB>2?d%87=X5j*`sx`|=0i4$)<&4malUk-
+c$jm*ZqwpIigAz{#{+!5ovRkdo)zkDt6ipo1f)8qs@U_LqGm<YT*02+YMfu-nnpazZd|WH_+Fi$<Lg&
+a=5tkB-CDgAZ|p>_P(AHY7Z#0aQ83!+R@-fSXy{Efs@P7UUfS83F4WG{S=YL9ZJQ>Pr)AB$yH!jqt{H
+H`x<!v7J|tF&_zj1`E4&%5Xv~jjYscYybUwNi*V*mqv=3*bUzXM&>@k_+<x|o2ifJJ(L(BCDIB(+1kl
+u%i6_Z9aMG7zf=4%&8-@%ph%8uENW3AtrjTs@{0Googf)5jRLIX(!r%=vrl<OLBKHJs4gEWa<(JVzCi
+u(y>I8f`i9I4N2kb9Jh`yo4)lvcva5uu*1UxlkAH54Ah%78EVxMU?}Hjepsvo%)w&DOVm<{y+)=*zbR
+{GK~)HYJ;Le@u0==SQ6g{cw0wK?sD2Tm$Y`r%ci*YV|tWu;oRe6`i&hjk$n{jN6sZAJn5)PCQt>WTdD
+8;o8Y|A^$4HhI2(@ctfm$NcWsKCiMj$zsvHYUe}?`PO#oz+(Mn>X{2i1E(aF{c{`WHnKsRGHEk_X2UU
+(#&ikG3)rcmO9IQjg#BR<mFr9_<Hkhu$HYhLLHP7CtII_3*qGoxg=jH8lTG*_-YfabrdHbBpmAnMk-0
+~*XU-CNS6=L(f&7HS@Puu}!bQUE-xFP9keVX#WrLyAzN0sWCjO9;b$wQMw(!`)$P23S@-^H!0sSvA`?
+ML!Y<(B^7ZcQq0Q2dPA)Mhpy7*0)XW-K+enfIcpbtf2s);A8VZ#+3=CR6L1nL({@=5%U(Gv{W}hbd^0
+GtnZ?K#QE4Rm^KOi}{YM2-~W{z1DF1k<uS<+U_mJ^m5&cr+XFWdPUgI<)1QHz3rtqJ-3Pd=Av7Qr@I#
+Cx`x}%V@k%w+7KIih7Jq2T^f6D{KOsaVbsXyu+P4c_U*cdn-|`~9!ixOQH0sfk1NAmt=iV*4_Zfc$5o
+q~vJYnj;ssKr>de%y6X+zSITc5Fj3gn9<Rhr9r=b(?t*y?+Q9%tjZ)+Ct`}8KNqUv1K%CDsSLG{HY-$
+QZ@nLE9?(rK2yCT(gWuSuhpzZI&a569}-uBi}<Rw<<x@8a5n<bcxY{YYarQS^=DVq%r>m$`^4$7br)w
+erzS6m?Y<H5|-Dp}GY8KEtfMF%xUrkm@B;s^PCtQ(5`i+Jy}?{aW3B&MNOfsh$M^KYWd0l;_BpxL9zc
+#mJbViJq*``to*AYYYF0o~A<HMiAu@u;03+$f^8YwKV2eK42=uO~+Jy734_1L--*o+7hJ9eThja8?R?
+etxG;0Wretfej1Z{wZ_B*<JB6imBTZPS8H(ol?`&zF4uT_hU0RLQ)`{9x8R-xT&;oKOtr4ozzqsGHX_
+YA|Kz#xjdwWii0H2D8drV4#(U#x+^^B|7hdaz`!$Z^hSBQ#HS&eyehp{sehr`fMZ;YSrGCN2lP9$~?W
+*$O+Wi!Rn1_Gif{m6jSl%^K$vIbDvsrr}-HFs;YgK+LmP}P4Is5PIG_gu)??@LnZ8UbUt=!$dgSSLiU
+$qhA_a*gZco{)ZY#dji8%P+koYI_Ql_O&uo9eCY>04}^vOitdL|yH>%RSXSy}k*2%sCd-@&3se>S{IK
+YmGuxJI8Z#(A)QHGGpChmquq6xm&w7DzSFT-{q9Q+iAe}*$oDKJHy%ey8*k&wu5ZD2As4t#+lnk{Pqq
+wX>Evpj?8wx^o6~2JTy&Sw&g<qDa3wDO5_jNO@&>{t5C#u=mp*CiB7hAw7TQDx|hUTU#V-<cn@}u+8W
+}h?n|erj}mj~l-5n6E{}_9JLPh8JbjX#4^SNc`~1J~q+b-`0fNN@PZMk)*iP^X!H)#4mxM4A+({5da4
+*3F1WO5CBv?<di{LYY?+7XhJSv4~MbL#{FhMLqKk5Z^A@C%)QYFMU1p5fyAy`ZBG=cfD5Pb+j2%-rl5
+LgKo6Ff)o9>Fn!9|@`mysil0O%O?NFM;(6Ca{HgieN3l27>JbhY5}o{7T?V`bjGSUxI-I5d^UW_YtHM
+%q3V#@D#yXf(-<_2u>1QA@CwRyAW6iq6v}-@(7j?g#DrN)Rl0nB$`iGs_$#be2k!gAe-PFf?bu@=EZl
+NEuuKuA}kXuqStndxU0b8_;&Imi+Hk&<=Q~>G;Z?qB$ya?j3NlDAUGpLaAtPs%v5W1cIM=yoE#yhiX1
+UnWQuH&M1MU+qDZGdA-Yj7F^^y}{gF2@MvN9iMGw*6VDByZiAWL3>5UP?MYsqSBSZ+h+)clu$Sst7_=
+!6y<`A+)vfrWUIYYCPl3>OpSz{B@ZEPQAum`25XHJISY+(}_!YWb;(<EUg$fiHwYv#C`h(>IVrnpCl8
+2U5%QNP9zX2Zp>I=+xxQK%>p#6If!j%O6n=}T1jv1<?V7ep9Y$@f%|MW&e`lYVW)Dc~5zDMpeFoK0l6
+WR7<#`%NKga>$lIzd0PsB;xrja!I5(vgvDvm_lzE<O7sX=NPKv!uM4El0e~7#RHnZOmc5ToY3QkzeM_
+-%-@r=G|iNnjpN66Go_o!sp4A}{iQoXs4@1WFX2q38tYVY&Ea?Wyr1G#aR*(%E}K)bkt_UU66I!&FP;
+6XlqGP=I-hzlZQx}p`AH(2&7zy=MXu=-+wIIfNWo+WPDXwv)XAv~#u3spnR6$bamlU`GK6u8qOhq<r=
+I6}e&6ZH?+glIW%<ZpZcQOt&6GkGg`KSBuNr$gnJTq<PN`p}8aP@zo!);USJ&oul7ZjB6whcaU$PxvR
+1Rk{*HEti9dc2d4qpcyI!-#@>Y^aAR`@%qZqdWrI7cUGT)Z9^zysiSZF#*@-1Rr}Zw6C%{c=`Udj0-J
+dXUn@znNZNM|xSDQ;2su`Ol_MHjbmNlB1W!>KOI-`uq+2<2lwOF_SUxrAd_fhMd!L@ml<Q3;*lpcP6E
+lq+zU<=S=N8YQgC&jdjOcQ;vWQVw%jDB^qSr`t^NpgZ$JT&s43JOXU)m&9Npr>VW(IH2%LMFEvw2WPT
+@TvFq_xmqYM0ljWfs*P|)i=Afh}Ie4o|!?oqn*N{IqjvsueGKf5z%J0@1`1u<0=f>krpx-IvLys}%8u
+|4#)Yr+J2Wsh2TbwL<PvwwiZk@8&C7a)MEYvWGHF%-xQ0tCc_;$RpWTKlb$b^q~zOY~@Qrt&oGq{t9y
+I9{jW)aQdPA1N~tN7d^T9f$#nYf(Om&~?gmV9R6HR)Mo-UfFv+mo5{sYTUr$m~Fd*HH_}AL+RtTc~Cx
+{guoI$lO3CHnqM^CPqpYlNrTjBb(c4w7;M&mg|1KRtOe8^k*i{)zq#c$u@~Xg4?s0_C^{Xdh#FX$HX_
+pJcWHt)!JS)G~&9SxjBP=2Wxp#Glft`iRi#_N7smL0Mi^se*@?Z?>Ve}3d#}nuRH4v>Yv%+GE4gt?B0
+vrducADld}dasC8A%5H7{4-h~p1XE<Roy_VYuO?S{;V#v(W+GpJ@h^5xX^*Ejgt`lZC?5H=?w6j>VOJ
+^Lx-^l{K^P%*866-0|JdfbkyV^y?SI1GuOUFmYK~GyxS50S@BW*ohJxx6w#FM}+MmE<cDh@*#+v;~{5
+Acy=aEs%TlEE5;?mC)$8Q-J09;glz!?+pW6POk?Jv|*gZaqFd9z8r3o(`BgbwCaaM<PAl%~AB2VVOmb
+h>Gf!nAmF;ClXEB9z+n5G&yPNq$JMV;hEDN_7Rh<nXtwrWm$E{AlnpMjuj)e=^RIdErT;MC@VXa^DrT
+MGUs2?q-<M4w(2J#gRPVf;zzuQ6LBFP#6jU^Ar6E`ScDNV307NnVgko8G&_}Tqf>0zIhtEsQesAu_A=
+V0+M+Tu*dfNInF&^eML76}Kls6S;pFV%>ej&BqhX`Qo=uvXyqewAyhY2KZ)w%KP1|<2-qzmSp<^fS&R
+x28yZsKI?mc?;^6h=6U!T7H?&|M9AYkC2!GV^bA;BS`Lx+WhN8BA5HGD+$$Wbw)$Hc~s9e2<82@~&)z
+b|3Z<iw=pDJiLG_oq+I$jq9Sony64pD}aR0}sxgGdEZK|NfY-`RnHRyY}0)e__<ZT<@=-j=!2d<{AE+
+Zt%|-e!k()`3C>=u;%|X`~L?#*XC);f42lURsY@SQ$qrrs{fpC@UL0|{;Pj~MnC>q(4X<m`0a*C*66P
+JexvkO(_PzzkDM2I^XBIl6h5?IVbLP{;^HL_FJ1P?qmMoQ#FI}gfBKncS3LLp3oBn-wR+7<FRy*&)z@
+Bs<IR7qdu#pM8#Zp*{LZ`Yz5l_Mt=mdUx9`~b;jZ0#_U_w%;G=_w4j=jW=qI0k_W7|dj(_>p*Wa8tdF
+u4HXU=~2y;Al=`Hw&Se6He`U(a9o?c$}%%U6D{`s1qnFE<4BSM)d35d5d<|4*m?Z*Pd}|NcLM|8CUXX
+{^<Vx02mevp-?5<7N#H&A!B7f7oDOYOpUe*dH<2A2rx<+lFr6Xt3k-l7?!0yjo;fl0GgTmzt57IU~lJ
+U`-_*irmNKBxR47l$JEv8lI7ynLU+1#HnE-6LPFUldY-KlcF=TY+3B4zN^uQD2g#*O45+bnQ>waX|Na
+>uRSK-jWvGs#BW#MGi>SUsugFvH^8K{mvCty8aR8ohK7c^;pyv3eH(Z-_m3Xy?ji2-^^J>mr{>1YBzo
+MJavwcH%*>iej|ce>?!v=^3=jHq*ZI&OFYlqed3lt8%R_k&&ChG$=0+(L78X*5`TFKX=Pe}P-MaRVj?
+1I)lt^?m4w^D|%UhU7p#&w9l9J-#;XX4fYerU9jrcJmFq{B$23W^vBS!k&*)uVnl;~={j82`JlxedD)
+!`P0zJWT*kzS+!sE<=d(ie4%D@E&*4Nb5nq?<#tvoo{JsTt<T1Y5@Blq7`XDG~afnx2$swq}|$vyw8*
+Ni&ls+pGzb(xKpw$$$mlk}31d2^r>uEb^2{{-N<xruH=W$xcd0G$&_gP9@(QTy*My{$>zS8%DT}B~yq
+1jnC24=eZVJ^l3(O2+W`0iO8H}o=j0g#>~l#EW4#vi=KI!Eh&3eYQ~iMzUL%at%lEHYQp_^&9NpDM^Z
+D09jQ#R?xFfS@w_e%!Wc(Vc6L2}@QkTrG;gvtYGq|NbqrxL_Y`x4I&-3r)N~b{DP#_r7!6SELQKxgux
+4kbn^O`p64R5iuc5CxPp2eVDN9qW=E<3fN#@LCbCy2W)sx5Y)c$xcPBWX#Nt|*oZR841=*%oC=xS`L6
+i{4Kr&7vhk_4nmJnY(&<fbcZIVnk#638(<H6v+&xpR6>opH=aNwp^BWF<^aGAATkiGr@ZY&qGzCZ%Td
+O3IktRS#H8{;FjYDUrw2?97a*Nf}m0LN(G#%AT5<k-&_he56o4rr9#Bls{AwYDQHT(gTUtHKjA2$ELH
+zU@?Kdk2XZF#yca`ngV&ru_k02oNp{SL!L3Mnx8s&r_-gDXJcG7{3a%GmK(pDZ8<<|%;=##`d=Gw*G^
+r{2^#j0lo~PDfk)R4U5U2z^voHE6rpRQb8VRV`A~<PWlymob92nylBQG5l$vZ#nwn*ub^G<xnM5L`2~
+7g#O%o^!bb)0iOih}anLSH%)JjuFN4YZB;fC?IzyDzC!wVG_Zd*sigv9i8@t+>nbynEJ$4t*Be0o<~D
+8j)5CZIjdnGj2vI%@*8xoB8(Cgh|}%}P&-PuJ?}35lsW)(JDHwa7}GWK6?1gzD0vLL7diZXB?Q2j(Z5
+slO++x77GvQtSKO9WB=lzp(rDzrWM_`rmi>)%?DvcKm%U4jOj$vD6#Sqy4X+PJ;p0{~i`l^ZVgi-`5V
+T`F)|`d*i_t(SGpt!}|wcKmGi$n%|EZzMr6P-`4tGJD(0j)E^$^{K#tFEi>3_`wJOf{VjTU{rtWVU4M
+GdjIxL~M_r%ZzGG{CKTzwt`-JO<x5r<f-<HJd$G<O0{f_5}Bul;VBu=}2I_q+-pUy3hTtEDgH?IHv)i
+<vnzt<Lv`0;{+6p@JaGKVSeE>^pJMsA5mh$jZO7MH2*IwI<P{&%g@e|D`?YbWD!qy<jYcM4XUu1IRR;
+>4}4F-cIoqZ6ztabg<18GB%)^{TxxG06!_iXu}dWn%<>tq6wxoTPW>gvdh3FjgK7;fW^KxP(;e(9G-@
+YSPn_)Yw92ikn4HPEP8S3@wJynbk>&d!2@I1X^E(Vm|@AK}awuAda<FEu6_UDl^fRo-~v+o#6>n;dhP
+8Na*f$QZdCP%9d_T9Wu+BG&(abH8CkTB_Uf(Mm#Z4QfyfW7AFefGMaP)l`Z0Njb2Ag)RRh7LnW$2Q_e
+eUeO2xlkp|(c^>>336SEoL1>lh(#6XwG%!EXZrxfFPPzg##&&o;?J>WYyGb1N6Jt^3lovwz;7E$bO%g
+!c6CL}eRkRjb84l{wl>6tl6TI6?!jv5{ssrLjkH2l>Lb13zb{hXtdlJ2kOa2FRXpTaY;Y}Rnbub*>tW
+{x2jCIUal>q{aeDTn$Dv$S6Ln3&K}dU|#N#*HGiXgX(23@KA_BGf6ynoa-V6xRUuL83T`#ZbhAMaBh1
+hjZ{&)%mJYL*Msd)(4rNnVLcBsyO5vmXwgi%iP3%wyR6peiotl9!x!_)X53yF~lC0Lw}dZq=e~7*SM#
+uxtLAT39eI0M_tEcsJ)=X(3z8yvfz(sK%!y|cwhf#m++jBq)E0ZQ<AcyDa$E?#1Djz5$_ULUCXbQ;}R
+~FYL4oT-#Uk95UL63sSngfIw&JCCMz`~IMYV)KUAwk2Z^K1jhf|{>Lk}u*7PwMq*y14BgD(}B<nTI2s
+FwgapFVQ(T<gZyJ2^%Al!pD$J)YOc;l=%M_3b;6ypA*#PAI2WJBE+A_sgkl#LG!6pv0pFF&06nB~UMl
+-+vh&TespDGQSLh^bShnQA+ZCmNKB6xf4;qlLH&c{(CA3id{nCxm5cBG()wxFWN<rczlb*1N`}CnaTx
+9xjo=QN%iy2BN>jWfWn?$%<rzf>qB*k-#-#XmyuS4M&yXajvcE_#m2JTVqkVZ|0^~MWZtv^^<s6t;eF
+1vN;<wCadUD(vNcOlsfr-4gb<><%ifgizRzjjx}j2hI)c>xMm@ncv!0q;1DN1QRRi?Oo)%!J}ODg^ru
+zXQfnaM<?DubB7*$KISoy><)k2@A-3dX>T^)*L>$+!$jly^gt^xwy)+~W64k7P>?8+|<G@z~uVNFjQ_
+<Oq6EW(S#1YAA4n#Otj~@a{YMWKL&@hUtTLJkW_*l9IIZSotLVLWf^^3JJPS-lu`0o4<;`YDK|N9T*1
+-I6|)p}b9-XUK%i)vYN(M-%4U~LtyG{O!@99D(#e0QOa=X+>oL(OcYeQRv^cC!{1rb&y}OLN0|uA4M~
+dk4+Eul63Ky$5UW(OQ^MntP09#%b}7)6!1Y+@}h`v*TF9gEe5;8m<jA|9KkD^E7k5_B~(wUZBN;8@e%
+7@SOI(Qp0Dpmfp*n`(_QlgWC7cwePLmRbJ>k(|K+*#b0!<@B3f%U*Grt<Ri6b!;=<qBk=Eiyy|__@8)
+`+e=}nLO;7!k&g%F2Cq@6Wc>j~n|L-!OJ^z=BLbMy{Th6W?tEqvzZ~m<L9W?isPN?R}HL5x9`IA`kD=
+c&K*j!8gOIICVWv(aQc~@1_qL~|S(0`C-ZX*AOUOe++8*%nU<;C&!$3J%^+eT7@Jo5Ox$IT-Cc-rwhu
+l0ZQ*f%FH3(<S78WQ7sXhRR2u!ubbI|)h%J|K99U<1MH1gi<2C0I&OKroviiy)mKg&>jOK7t7ZV+lqR
+L=!|3gb{=gSP1$PbSLm8Xs7vaLEuT?N>KTYMN|-+Avi|x3Bh54odoL$RueRIt!|T^rT51O784W@%qFl
+Bq!Uaah$I+D(2bx4fh*$w+9DK!lLW^I4ioGlC?R-<U>(6)f)@y$B3Me0N03f%AHitNe;C0)g6;&Z2s{
+Wbd`0mR93wbP@BzVN1bGB_{#|XUwNcPN`tBsI#TEAu=}+`2qVX){_4gJrlfs^C93)16YvJ}euaWrw_W
+85*ZO*kG7wyr*gRi5AkNRVFd$hGN{@VSyo*MX4-bA<kbI8@6KIDIN+xh`{?WDzRl!JmYDqm&Q`04Wlj
+^}Q-2LB}n{_n$&tM&`Q@TKlZQ!;0g38i8wndp11Rl6w$|L&YuCFBk{IYuVJSCEPC9!??;{WUY0$fW*c
+qE8m>R68CgUa65%hkG*p=GEbjbf2oj9nU(002$p&>Ty3@kNe4b+$-vFHx?G7yH`E#=6c+H>u^UKWFhz
+HAx=Ue^NhBLu79YLz-4p#`+Y;5#9EK)caITHBE_xxJ!>?5?_B-f>H&K9s(vq7ME+f?-@85R#Cuot_oe
+iXdu;Ugryg+<_ZZUeCe(heg|XIG`qlmP?AcQc8#YYD#l?x#)Kp=!+0+cp%cK81@zhgKiI-n~S-ku1yP
+~9|M121F=i=(st3s;+^4K%I;3h!o&^~-1&r_Io&zNzDUk}N1Re7FOGiJ=54G-t!fvQ9Dz$N;;o8CR><
+s5~j_Zc(rt{ggW-~hj)NfEd+>zu4g=I=9RS9ttLf#ojkea0b=N`y~Nu2SD~;s3y)<m5xUwf8FZJ8s3P
+!aK!ZMc?s|pIkM5^*#L(`#*5t&@R>C632f6>8tOQzLfSum?VW8@T)p>`2@XP#COJje$}D_RR=C24!mC
+-H6fflRHak=^zQb--WIn%d*Bd}kPQBK9D8G4^K)w77SnSce-z%?Eb_o1^064~@~C>{>E8WS5By&F(V^
+8HUq8Tp0p$K;&_G#9!Feo!@ISa}^nuE%LwP0a|B#e_jM-LM#h>Ay_*?dDrR2}de?+0EpW&a+BRQsi=J
+**mPfd;&YLEI^RJAY3J?WAcNFvbQ04@Yhc|xtI>H#OspD|ouJ&;Qv^Mn(D3xPX<iJ-lNoO@}q{%3ODr
+%xXd6%{37Vq(Mt4?Ivq#+NQ#Dqel{Rk2~i2A1*9KKo3ZJ$u$6=UEuGSx4n|-DY>>#DiH6%1z1JMDDh8
++mi3k6uFc|$=jsN-Bun?l5l_S&%ecQB1`UbXU9wVd-9yUXUB{gvn@HY&ue7H-ybn;gp?cO<=mpK+s2Q
+H7rAoPwvA&D-@8i?f3B22UAnYRuoOQi#N77nrI&kqDO@xV*8$y+y9OqePvDV-`Q%YQlj!N(xwG)`@e#
+hhzGBdzK_Vz9NQ8%nGw()@94TUBW5u{}<HW>?6UE%bp<>FEDIzT`O-!9SRb*#pbNw-A&K$AQ7ARhOV3
+2rwZh*+25-JwoA1ofr3=+>|Tg3bG28cKE!o}0`CW*~YWr<x6-z^TWx?gnLDn<A0QuN*>Mc_^;`tFlr;
+6W)Sd?ZEiCsN#fT#At=q{tx{b6Se=-%Bz1q!g2Wlw#hzd7`MONGw~nOg#DIlVbVu<>J|ApA|2>@Pb&g
+W)0`>x^?Ts#*G`fF8knv55&<O>%{zDq}W&?#fKk$DE98%D?a+@BXQ)&5%I|<pNQkfkBhIr{#u+ndrTb
+tRf<!mPO)5+m6eGL=YA01UY4SwqC#A{bctmJk8>|-FQSELKtkg|jdmlFo5obwn^FNb%bUa?*;|a4BgH
+H^O*|!+iH-6t@rgX5*QcTdh3`n=eJT7P3Li<~$5Hqx6n>^`CKgfnXDR%f6uyMQe@x-e7{Yg<@D>Vx4~
+4f<_$3tn6$-zd!XKgV$0+<a6#iQZUq<22QTU67@V&ZF`$j5%7Iiz9TB#jhLVeL!sJ-1mh4ABMLLTca<
+kusGJTpzmAC?JO@s^Mm4dGi*_>L5w6qu!hDSQ-#r?@IoDf}!7zlg%Gpz!~q@TC;~V+w!P5T4q#Xe!EC
+q^vA$Na3kpafs@l3Q~ro`6eL;Q}_uK{s9XAB!%BZ;Xg5i7fnU9xP{7W2hy2*sMz)she+}(M7WU6?h&$
+gmXISK5^~zJLM~e`<Xd}$JaWPi-b~^9QTRv-KZ(N6r0`29{AvpSHih3x;dfJbN^{v)6#guQuW*F#PBG
+j~F{Dxq3n+#)6vIx6;S|MC(M*b8drNU)q!bsYNpWeJ6qnzU;`bxc5xy;j??K@MDf}o3KbgW$r|=6Y{B
+jEa5{2JD;kQ%xLlpii3SVvr@1b#^C53NG;X6?HE)>2yg&$1e$5Qxd6n-&<e~H3xqwvQK;cGte>SJ^Y4
+jvLTB#7q;MC2XaI(v8Q*kzdGYtWF0@bHk3h~U7$ppf_;-MV(|>^*E)Cq0IcaQaOD;baL3iTAl39)=Aw
+Yu_WHf<q$$Df-ahpuizP@!jE}bLWm7wC~|jmY|5B;E-Sn54?JI_wgAVUyWo$RD}KvZQJUW_?|u07`!`
+nFn1b;@DzVUM0j9C{H@Jfx1#Ulp_}HROFV@S3_{@Gi1@b6o3~cKGmhRJ&4gsQBmVf7Et)sKdk}l@VGk
+Y52p=4RuR-|UqWP_NYp6xuffOiwd|*)2@Q8@ei1;>$pmnQTZn@dh)3aS9Qo#2peklGnH9W+F4fq}$8W
+kQ95fvKMzJ>?--t`WSe@IkFL}*k<)X>}7wA4J{`|aI&L<%+jU`|5kTKqtG(D=vk_YR067Dt6fL@^PZg
+3f=!KR%?l1t>&N9BqaUZQi^&d2oD>@7EyS(kqk_7*5}B8#<IxXy^DIY;rU8Z|WNw5fVjQ9@?IXxOJ!|
+9)Sabg6?!Nx%mdhN5w~lhiX_x>CzP*+-FE|FIT5V!?h3KRd|SFgd#lNzn53T22M`R!U#j47!?snf>ix
+I=&ruLehpnbZVIQ5!9z%v`}7G8uKpe$KO|^GKvQ?Oeq;@fN9^Gt)#=9v!^?<(CeH2_d=CyJag7kw-@z
+XeFiYcRO-IBBM+F9utO;R^Uwy*7n)ycs5g)@1pAmlue<t_4{DK3*YkpSchvE+*K@1P=JD}EQL;S>=@S
+p*;K8uK&PgJeXQkLXan(_iqk|I&^&**cxbwHiET%HK5rO#boPto<cQKLq&J~B6Hm_zq?dFEiTFf~*>l
+^rZL%nudoo}Mf2+Cw@8)pKE=OA&io)fr}z`NR`Xh-aR8Myyz|Labc5QmkIRnstS@-+r6*!S~*Kk9CDl
+OI{YwkiM~wbcLNecZ!1t53+7>=JW}1`t)gW=FAyUUS2MK{P9Qe>o4b6H~8(h-^3q({2`WIlHx6TKk~b
+wp6!K=D|b;tN9A(qWNPSUQA77IHFPhDW^#k*Ew_r1a*voMkBVjTEAf^*OYL`sAv`sR(XA*vHMUE;Q}}
+)q-a_FcDExQ|KaIjKpztdw{CWz%m%>-KbN{QS{I8z!f2*F-Mymtbv}warHm!NIv`wqdy?XV+(X?&MZQ
+8VI)8UTxUQL_cMsn7=W4F$oyLRr?%*%9p6MApcp;Onc<hPku`(8f1d_=pBcXaD@YolJx$V1a6O>S$~p
+>wxhjT?2lO>;1tyWP>t!^5*1g}MEvrcK(ky5){ujXgXXHFR_HyxnAK<JzFj9k(|2Xat8|UhP}DJGpo4
+h3D3WZixTpR?f}ot#PMD4IBDU`RdTQtxG%lN<nU=cS_%<U5l=re0ufr!4*}M{vAF(-abAZe3-s=^kD9
+=LkD$+D%T{$Kn&u!Xi(n-gOkAz{A0mIdv$z>#9rLTUd-36XK&!qmxeSjfSZ=;f5-E8rdNP3mSVJQ-@Z
+MV3cz;BE)5$tq?&~f?<G$0kwH{b@Ny2F<Nws-qQ&cZgZ{x+G>;H}^YhO?A4l!Z`{&M``|jtTfBv4@p3
+^`5^wU`~Ph7Zg;T-i#&wTaOS8wg!z1!~O<m5AO;J{uQO|7(eu(Sny_$&NFUZY{YsY{nGoyY{Qn%-d8R
+^!Ky59~(|+1q~p`R5N)KU!|vwoQKj{r8gEQ~B9vpJ9MXo;YzrQvX}xJJBGio&8!-lrp0A)W;ux{9I{i
+Y3`6AL;QrAPgu%xi%^%^02kzIBMo5Jmlk0O&#mw~b?Q{V%F4<s0@dJ+<KLS2eTd3nAH;FjU3YZ>euNj
+}zi;0@`R=>#O2SXR^Ugbr_t~>&<#*qGCl4P!ERP&H!u}A3bOgAcp)k+C_10T+HgDcMhg7!E{QUe8Sy@
+>jOO`B&CcPTCVVRN7Ew|j_S5#DV&z*PP3Es5|2?^<jc>gN?=g*&)q{}Sp)TvWn;^C4Xe)vI_l$1F5eC
+W_2`NbDsFrJh@j63WnPo9)te)%Q8gC-qF=V6m%?!qs>{8CAB_dCU@T)A>Z{`%{$=Rf`Q(|5o9_S+Mb)
+@Ar3Iv=I-)|YTtg0O!Tf6}LrmIHvl4xm8?<cSWzU#CO2>rk5(9SCO!P@X%$=nnWh`0v=UV=?7pN0NyG
+(6D{`cE%s_as2pk&Vy5@PVqZ%M46y6%;wRfM;TBykRLFSZzwwmvw#17#vge|<zFHnu3o(=jSs#5PVQC
+sPG$Jczk>h8ix(v|LoEOO`}gkxIR*g#k3RZHzW@IFlJZ=V&dg;P{6~K5-Mg0oxbNAshs(;bW5?JI8c+
+v7-cU}EN5E~<&r&8Gmoo66lzsL}+3Q2xxh`eT5-CURlk(NGQvP=F;!!Fq?fwe>Teogq=I!m>mvs0gR9
+_-Lm<Hero`bKT2YCV9VMpG7^UXI5u!HB|H}HiVfEM5l{v(fH{87q~&!n_`EM>qUDepQUrQaT+VW*UL5
+Di_nNZIi{DVKaDWmQ$xvwsDDs_Pv9{B_XtLWjRoPEZaYFLB>UIqaB}!JiWUK?CJMzx`6)Ni<}9F6G54
+DU**#>ATf2HE~1uU%GS&vb@;O&#xoNLIG%?e7J@d-~u@Uj&;!izJuq;BghTpAN4Nv*%+Y_g#X=Nsx%D
+wM9RU0>j0vmFUd{TF%|#Rqf&Z*pq7an#h=;?sn`FIe`=2;pmv_<at^*CFCbTt4V?~@amX3u9_2zeQ7-
+VroRV@l(GWrMKlF2zhCzp=^#4eu!I#QH_w7=4+xFM-r@DAq=gyt`Qa&s}IYZr27afrG`s54z$9J>~2#
+0#c_{5%}G71{LmNJ}Z2qhZU{UmSX`Gw%=`tZMe`Ld*TrUrlp9dtVC%9Fb2`2F|a<&k$+$ThPg<kQmv<
+rA3}M&h3Dq#X0Dlp{|{83h`?(8@E(%s{<7?^Vk)>ZC4P)$-iq1GP+3jeDRz{3)Lo_vzE8Bh}{xz#no_
+n-0i5<hnK;IxUcO$kB-d8|2F~2Fg{oLGrnr!At|5iDgob(`bl3A!Q`t6!wLoJc9<UJoiMMM0ILss*^e
+p4ej4i>sET^)rEh@jvXEHPi;Kf`D^k6<rnRNo);(&c-LtF{#5VDk|z`8YqJK*mu3u-FA@zahz2|fRDV
+t&8paYHqfe_e=;awS=;ax8Qt#cw_Z?E+4jPF6=69+5@8M_;)`dUS_bmTZ)|NmYLYdR)&}jh;Xb<X>E#
+QxOa^t)p`R0QG@>QZ?4biaDs^X7pG43lT8Wbtx&Z^}ZbyCEa)#Vv9=;awS=;ax8Qn&XxnoG6uM>#|LL
+VA`1K!Xmo>8PuW=(OP3oa-;w&mJJ(d>}x+GLvYSK1lvn@q_&Qib_K~(J=mdqQOv}Bee1ybX2XA`hTRh
+&w8EIm1yYnex3Ca<4^ki;=X<Rb|f980QjR`gbA4e4bXXXTHuDZR@ck$4ec#-20ZWO`O8gn{pDLk!y81
+yTB6~D<(cxrxw0FoY|4nvsgx)E_42Ig7+ts4jX&xOUH%6Q7|;cIp##b*@CI(cU8e<gKk9q*Yfx{ZtwP
+&|XY2g_@?D}~<J<vq-RuDQI?+(OJU>o#(z2;Ra`F8`<igZonLj01<|c+nyX_wN&F6=i2BVJAQ`0f(!=
+LJVmVd%$3GfD9Fo6^BMtK0<dY+(;H|ob|e?cSUf5*bXatqP$4$-h-4$(km0p%Gqyr|KzT%%zrXh<6(7
+o-pk$suxXVkpyq2X)c_gO1Vn!@A`kbq3ln=n;UmYuC!xUVBYKFVex7C)X<{fBf->Jp5dOEX}`5elU+{
+ptA5b(eN*=JflupX&Wq8WDk~4Wd+K|GA#1p^dM;`8Xh7V<`WHbhz2~hb&PwD)?NPqf06~3f0FA0(DKk
+j56RbGf1T;M5ju2Q5LP+zw%lHDmn<O~-X|KkJQEG5ll1cZ0@X>+W(UeAvn=vaqG1Wqu!v|VBsrRw#P^
+<YofKryG2Sk(yZ#6My8H(O1atuoz;EHgg$^2O({Vjo{`jLxo+^D>ez-VTZp-g4-`C3XdP8|$t<ms|M#
+Cc{M@#Mxl0~U14R~0`p!PYEV8!>`{_YpoKCO}G)c!6TIdWt~Mn=Xy;EM8yGB9`UT&BS&Uw@V-Fj1yz_
+p$1FKHvGKL&rdQF4oF(t>?P>5Aa9chlPb9ALJ{qyu!K{beW=}A~}8fbO#OBqvLvcf(LcdhPgLTo{5G!
+>Y4hU*5K39rAtex?v!1-c9rq*@p8?YH4^P|PEL-rTCH;N;>BF9zyA7bu6Ljd)kO>NM%#e83c3*VQS=A
+!pgbRX$tJ6=P=909bVqsCb&Ta&d0t9o;m`2@;DZlLr0a~<@$b>2N5ACc<c!3`#B!=fIUinp@kKde#0V
+J^6C;a@i{%qfJRu)@>@mg%{d?dG8qgM?ozUq(9|km_K7|~jEkqhS?IH5xmx2F9xo`FKY8_*`s$-x$qf
+UByW)#r>)Be}Mfdh-8qN3(Oen{4rQNO?M#*G_ar!p+*o18gwrlc|<@qYK+ce9T0;fEixJOFp#iagTgO
+3x3_2iZeE2YMay0_6c^n#(iggRwlnQmZ^4*!(>7z-Mkmc>MkSA6veBIgf)NZLKWJyu3Wz!znv;>LhQ!
+{dP&ZHRA$2P&SMJ8g!^l3ji{u$Bnx6qZO0n2Za`DpH&?L?elAMg5~B%r^qk&Z;}^(`|T*@_YIFfJoVI
+5vY?>g{IX@s<ox;bf4k?Ndt`cgI`f_Sl`Ko30p$X80yof6n-+{gpdE(Xqm4#c!FUAvk#K{KguDYSbv#
+7=<!`{FzdHVdz*Kf$$jZt(@!*3GUIm_Uad8YN(>e`z+;NATF=Gbj1KJFIY)7X9_yT`@%olwFm?#e@BP
+b8G%RAa^W8VY)XYm)u-%z$7|0GK*=gph<3Cd|iM1-6@dp73-XaN30h76Ho$Bt!p<N;{V0W|3SUi8JFU
+qkMJCrro?Xfw(dbSn6#y5tdWZ|{B^Hf(qpeTct<KV%aCS;BZT+<+IxoNYE6m*3#vU}>>fWY3;GIUn#H
+VQSM+mu%@}LpLEus1G1lsE?6%`uGOngz2^$oxfoGiSEVy`t|EbJS;$Y-m+y2(*XWp+>pu#(~yvmAR{9
+qS+-WMUd{M}*Wfwqz#HWN^$*;kn?in|Yoi>X44_OPUev*a`&EjkpjE3@7RvV*ckbM&2zAcK{YLRex<>
+s+=PLmHMc_kuD@nJ&s$wn=l;4u%jb#9B6nLzM(Z>@}kAkPD|JScyFW-FgO>P7K^{;<%IPjYIq)^>9k=
+n@Fg!^`KTOibVj~ku8Vf_vI59)s^k4x~5@&*&QAiq&&Nlsapm^yVT*R536xqU-j1NqkF5aj^n5_tkSK
+^~w^HtIvLBVObY@&oNT(TkmRs5jki5O)XuMp-q=uu-;w8|Z=zp)4#|us~9s#qG550d6`V4C)!wMR*`T
+=o0~eJLr1;`R6gl_=2;u^Iyf?fxoW*6Tb^UgI+JzMF;qeI*8hC?k7N|(AL&5rqB2zZ*(03^E!}w$P##
+tGV~M{^Z#|e*TCN>|EMEsx3RTpfr&Bp2@@vBC!c(h<=e=29pDeL1X;&B+5q6L&ySE^yW+oqJL7Nc|5D
+qt1agTs2z2P<{ir`s*P%T!(gEIX+O$bN{q)l;&w3dKfNp(k9(ohrAv5~?0o9o=ySTXgS8#XWZ)_KhI*
+d`bxn7<CUU=aJ4iCEEAG85q$QJ5O(4yl``squ5Q{Jz^AGlEYV)>``yFl-MU5^%h%u}DgL*Bp*`Jm6qA
+<s}3VJ-o4P@o04QyPD#p1Cgm#_=D$FLk{<fqoDD2k)4d13<Q5?%K7B>s{~w<rVS{{80`_9#{W^xHJC7
+@lUEJ9OFNr0c|Jr7u0`{1GGnIJHcc0Il+76gFe2Ce84;EeAKn5$EZ)i^BP3+KaD%%581t*oYyDs#<~d
+K^>GXE88kxHNsg|Pj-XIpp<QkB595vp$C}*yZw91+br1i@5kNAJ8kcP|W>g7xc{OmxjFUnHR;VV~{$b
+NaGo3V3{6nTwt@sV;=4ochKY@R)W=hp`(o7f4bk|IiX13SNK+Vk6OsSeqFl+AHF^j+PV119f25#ayx+
+2E=2=)?Otkqw{J7!dBj|bNGAgxxU`}$IwACZ)lG?MiF5UTUB3>(YNpmVnr202CCUsp;w{j`)}pQ&?f7
+z@Un!ks&$oN!Re&wgcGu7?9?ZRh6Zb{F;Srcs%$M14j&=WkTsmQlU*Bh^dCNk4y)blWu2fw707H$g|z
+H_lBtqt26IEEMy60oqvZC+DR+^ox{%J30NIuao|*REMvkG%Jns>H1m|ef(V0`L7b3r#km2)tm1jV$7L
+hz7g|Wm|ww|IL2Z>y&&b`UvFrxw>|3V`Sa%|JoeaQvA_Yk6Z#KmA5pKPEka!lT^4!@zQK-Xyiz@1h&d
+k2cVbK%^E()m#~j<ArH?)U^+7YJzmTT)@6pdiy3nJ+6TQy^y~+4szU-dw)%iZmm2Ie~Yv`iJbFP*=aQ
+eoz54G1kfG23bemZ+xzMLP+<CsgdF~CVbNg4lxI&T_tTAlaR*AE!w5%WWsXB<f8r!{4=J=zrNzb25L8
+*5yLf&7OK3|!FuyuW-ZkAY!47-RB!`ha_XQ0F}{-^TKIOr2}P91r9Xb5xk?#601+{Ty_Uo<7=f>hEXF
+nKLKNINz=7voN7szd1LU#}YA~i*ZC_`j~sg{Bc|@d9-MAG??qd924ZxXNy`t=;=fMG0v6No__}}c-Cq
+26RW1H<FOac{UGQ4QWFQrV{9#X4AkaK{WN*3HBZOsQ$HzT`SRtlMm&%<<Qyg*%(r1o74r)i6W;V>)}P
+K9{%}RgY{F&G5p}K&Wdie^#`K|A%$hYTBR4lU%{cc8958MIUf{v_I_8?*(B}Iv&xG+%$Rp;MFt?Gf%`
+eTKtiluXQyB-A$HUcg-?h`PJr`Vi4jB1gx*(9}yD(RTF-?q(>+*<kam=q^Zi45ywDjjB4&}6l8RT)$f
+tvXbovf&+DB;;>pN&OXM1LRpIp_v1-~r5!SEcg2A?B+vuKJobw*9;|zko7<`4P+&<|TzVc!0-PM`P~R
+DE}y14?OTd2G##*`uqU;1?by>C#ZYCiwnvZa^IuTJWqh}>2=!p`f5X&z&w*(n<vZFaKOXzNa;=>`07&
+4@~`*LP!6H<8|PV!b9dm=pUoK^-Tp70W5HZq0pT!Ln`<;Y*VKPV-)^@jJonslv6vfzJ`Ozeezm@C5O{
+zWsE_as59V**e4x5a)FqDwS*x@DhmJja_Uw!W3l>ZTA0B@AVXpU3@1pHP{SR3HKOl=p+c@X+^XX6IPp
+3blGEqw&(}NsyW!Fm|Z3@OYFs2J0qklzZ(J_`@doE1R8|1}@%c5n)nNQ@oZ$GP+M{Bh_J~MY5lCQJ<r
+}&-q^kZXVPXz`B^0+JJrc+Z><)TH4xPJ$n^twQ=E0I6o&3WaxJh<|H`EGs?uLaQM@x@s~<@(37Wcit|
+q^w8(89aEfpT%OC1v=)=otrsn(xlzKzP|GQ`|sy*;3Z3z@Ysdk_W{pgg8%y3M)0F{n~Vo>lE05hwyvx
+H_2|)K43&HC2coUVybR`+NY9ev$B$>a>l<sXoi}<ruCJ}6=&|nk`WyU-|45tkj~_6Xh;ifa@Ngb~1rF
+1uO=G^JKG5e#bQ#dckac;WcA_dhJ$(wvat`T8*w~Fe|DW}#+Jjfb`=u!<DZ4PogE9IsW5!721?JbNU3
+SbDfbY5->T5)FliI2)#LovQuIH(L{*zF*Z2Z~NULWH}9MJ8+Z;a(a1~Hb7c@2~g<2(ZL0QCaG0T=KB^
+)~8E;JIzvwui-y%~5dqU%Ys6!pfB^WA#2a@)<ZxnKDKC`1r`-!-q3&`naDyKLme}8@;~3y2SPC*W+l-
+mN$?#r;jvI|K#WAry)L!$)n9jorAfBi4!OC95c!V{Ne!*^f6xO%a~Jv-cB?;`xnx7q+fds%Qz;1_9#0
+$o9hOwRn^B8kze37=tiA<^ytx-{$kpkKGLDOhU@>j@X&SOx88b7u2`{x$BI!mV$4aOQ~aB0bNWa}Z+{
+_6pjX$yQTFtCN#Fn(!yE_3pEhsatgjRNyJ<V<zmYLe)HA62kk9MZt%LmiM7$^x>iEgueX!TW>u&<e*P
+qpI^*&YY^8!yg)!2Ir__IB`#=X0aa6*OJ=db*QeY@s*@uc>!eSP0Z9)q8M{`n0rzWCxrs-u2hvu4dBF
+TM0qje6(x*Iz$Jab&*w>Z|Ndeq2|rS{44n3omSa<Bc~sKlL^Y`AlW{Gh=wnr<InLVx0ANisK~7-vyLI
+^o=2}Z&Dv5=1X-QR3Pcs&z$C{HtXTx7cvbUPS<DjGKIP<zD(^iK|lSN)S5oKYv{)UZ7|Y8S=0MOMqM!
+BC$$f}`PXZj;ok^0p>9Gs0<QZ0j>8|Umdi3#-EgwjcS8RW{a5rA&{y%LzS45S3v;dLlLL3iKhk|=ZaC
+{W=cy0&%mp<L^u^KlLf;SlKJ+{LQ@;~B40I~sjd}|Y`Y_NJ-+p`=$6<WRe^<wJFphve8~BHOLK~#7L4
+E(BP}aAg??Kmtt_fWi{f*b3E#f%P=LjP_kbmRGjpKQ4)M4Pm$(<|Zro2JipM>rXy&e4q^quA;4dXOoP
+Dr_y`0~s%&#*p-H6oZ-Lta8&YU|>MOV_d9KWDN-=LWGG!9QvjxZc8?9M%u$Z7H6&<_?xWoIJ|>L?5a!
+mD6|Jpaa=MT@N`$UXB_yig}898hQE6_7~;)`NMeq=Zcwk%YE;?jPM)v@LRWTWnE2QkAr#}Iv4T-^{Ej
+T*wL07<sbg_{MXkcAuhC&NFVJH`U!{|^)j{nxyJCQr-3)(0WUCD1e(xhV>}6A(a%QPy>sWz8e#Fwb$>
+m`i$J(&Ag%+tA9oE*aCZ{!!ff{9)1Ghwn-fmr<u{za<}7f&E=~@>>1!?mr}5$qXRo;mUthI$!pUoHno
+l#IyVgMSY35Vc+=Yh=)V){{BjV{7w}<|p_O3lDt163MlvdhH#x!-55fNQ!8s~8z=bqOEL_<TRP-9JLA
+bubUAIgV{jun}Wk8nVTk|r`tDpWEmb7@+VV`XJC<e0BmsoBF`YUCuQ<?QeJ$edcM`D_01urBAj_ny1Y
+-oLZY-sih4&M(~<>ho&e4fP0P2z(BgS0a!8cy=GW2tR<Iuf22jM#9gfFI;nct<#NSqv#w1;}EFB%#B0
+gEXOE>Hc5UPWH2~fI80-_|KfBQq{awi5VR>UrWje!ekN#>1!reD7Slme_|91#$V-_oV~o*8=mH1kIHN
+nrI^TD)&kULE>of&)%Y#0Gze(m`pW!hZt`=Y5pbQscw7*FH7{7JsBDvVO**}n9oBlNfV-?}!Q0%u4`W
+&P`Svcbyi|ct-$w@|UXrBt7bN!ZKWTpTnVJmV$!(zkug==9p_(4WLsQ(wdn6KN&b8_;|>2}_};IHbK5
+N5+R(tQ5S2_QckH2Cdf7XISX{=c5T6wP14GTHaXF(9w#7d$Nd5<a}#7zKC3eiZVVC@&uO_K^*dGAk4c
+6pYWG8B<b_9}KD3X+=RE%AOb~$O;WC$jdG&3>D@S56mts;8~%9o2TR0n1ZZeUQQrXJSI>S$}0@2SbQ^
+z)z@AX6C;a@riFYCn%^jmo_!9U3<a{M73CGrJa-OPiUL!oK`(&`X+?R{^YR0^fzXAU7vCQ2lR<(ase$
+Q%{FwakZxx#r8XBBlI5|)h8#660F*{5kqGEHh@<V}GE#rUX;h#E>|MlKw{Lgfi@fVDSa~XdgPo0*SmY
+AG8bi^$g8So*zc<Ka!;tF&%>WF%xzUU^DfYQ)7GyzRUCFnjh7d?trqD|-&>WoL>VmuE&hd1E&a207K?
+dhGgn%2_|^bkEt&(J~Ua5KZqGH03d%yRQ#v({W`Hkgg(o91rwTQknO-y(L7{knaFgB|50IT=otlk1c^
+WzOTy3a8F_*E!@|#d<M^<+2CZBDRukWN))3wu_x%o!stjFSoBN+(dVno92#nv)zgAY<Hns?jCZ#bNld
+e{x`mn@8zfYXpt=zij88cct;!%r$h%iL{5^k<Yw6-nYvYtQ-!KRtyTNfMEz%7tJiAm9r8Z+TD+6t02*
+_aPoX=iKvifpT8B2GchPRtj9O6}+!go63a8*SoQZSr4BUWU#s~0cID)hzl<Xr1NDIlQ#dHC!q%WD{tV
+PyettYL6)@N3P9c4$`{cP7xut(Z=+7s<EdzoEtzh=K<e`Civ)R9i6Q|?S-SIYP0*OIEis*jG>Qcu!T^
+q+L8Uasr(OM0XB1D3HBs#Mg7GVu=l3H}auCu2w+xt}a2$4L)r(c9>~bTwT^Kc+486csQw3(Pg<M)Q!_
+*^0LAv`*MDP8_Rc_3Rb)7CXp<`w^cco)OQBw?vDGld1A$xnCZU-^sSBgX*q&DXN4Tq86zos#<-m?$!Z
+4Sx?n7^gVj6en>CTkLnuzj9#PH=~wj|dWZf%AJCubWBR0y^rF1ZULUW&hdkR$_0qlZUigoT$>4iE@oj
+htF2^mnGjT`~DIxR83*_&liR>nyk(1;{ayt#u#k7{bM~~1XvxgODN$U=4jrBg@`jy?yiE;V^cIm!1Ep
+!$;tDIMzt>8@uoJf|;s@QtAg`ET+igY`=UEChvN7&7DbKIc&lKZlI+&$?U{0e>z{~hniOZfuuq%NYbu
+tbtb5xF8LW{FZ!CYFfD#B#AptP`8Sv)&fFM6>u@d@D|hwz7}pGE>&br)87eC7Z#|u2M*?QtztWs)O#L
+Gj)!ht?$<hbh&;+SL+perG8$o*RSZ;^*{7Jy<dN<ztBhYalq;fpmn|1&x`jQPkPDTQ13Qxj5pTH_ojL
+?yi%{md)j-|JLnzuj(K4slJGzLWugEIqI*ycdJ3&VufbgXJr+0t2k>M(6?Y}kB%TZ>StOV2C0_xegXv
+hBOXtvqw1O_9JLrCToc1x3%)gkM%umd3Ovh5zEmpJD%|>>O^Stw=)9SQgQLG#5&F*01Sw4G^m9r<=8|
+(*0+`)k34!1jB$XD_|i2g!}kz$f40^Ak@UT=thiuc8b;t+UMH<={UWv+Ztwo${>GL;2*T<P`lh&R~_Z
+wgWhwhTe}s0dY~gXl2&0VU%RcqU#9QRiQ{E$K`KksOjw9wASV)#M}cB{@M5b?IQR<srJ1Hh_=pqY>tH
+=JjST^R(I1>TeCVs;wIw&-uVfaBp!(^L*Y$P_bSHRf!s)g?>SA)|K9}@OCnWg#I;}jn<%DC<^*nK^nj
+hzkvCaOf$_}t!!(aRl#<;9mMV8UQr_!sN-I%ciIapKHpzRM51=+8We>D?nL^Mhsh3dki^k=&~X?YO{d
+alDKoXX)T*_fwT@Y5EXPi?=h%zvrFNbDq8(y$Ss7cxma@lLd$)solbh~7;jVT!yC1nn-BWH`el_pH6L
+<>$x0ogm$Zusw6{j3ER4q^|mEmvJ+!S8#f+y@n29Ck~aU#U21=uE=NH02&K1DavZS;FO%$#jjnva<)%
+sR6kqV!(#j2R6x>qcvUg)GxzFvk+Cg;s@CX;lG&ZR~698|`@8w3#jKvGzQBgWYIvwYS;Z?IwGty~l30
+`#J+0<d_bFSiZ&?#b&TMY(C7t$JrXTj%@;O*$%P1nSIKRvhQI&wuAW??Pj<|ZkZb;x`=3z2yweNSXBV
+=xnDTW)foQ%!(l8L8Ak3Rb4Vq5nye>plV);+7_=jeqc%;Uf222A7`(RFDzm!Vv+QWdFay~b_8g1mC-|
+G9Ra_@W%AmYjDHTxrReRk}->viXn6ojz!SMOpyC8*@qYY?3Izf+^_t{(QBX$R;g^d&AMGp9M5WIRi`1
+Mh7T6C6F7RsfvmwHgusV(Y|x<Zf8OLZc|w_{<MjfT&qJq}UO{Q<Iyd<YshKt$d`-=QDUXtSTm%w+SZI
+Rv8dLhCu}S$nOG9LHJWY<8{%q`q`p-7Y*{3>V8~oorIO)CcOIYEiZh4|15hxeQm}N?e7jaUHJ5k&uHr
+i5?<O3=pP}B3Y!0QQ|H!LF9{KF<Z=qC{`(|MXjh8Yaxmm{$|}7P)W%8dmz7c#SCZQ5<C~z;6})62I)a
+!NCL?uvq>qbA&q1^ISlzFiVmQNrqL-7KN@HgZKkcXD_E0ZmY7xkGBCnlR~RrGe(q7pR*IEsmAEB*HpJ
+Swd_FJZ6}*yH@oHYfYk3{7=M8)<U(Yx3M!uDA<J)-?-^uszW`2Nw%n$Rg_%VK*w?dvbM5JgZt`Sk9lj
+sU|#|Q*=Gq5}XY)=8})4=`=Kp+z^m<T9L0USyIiBiB~KA=$ncvJx*HGoMSpwa-itOsNoA;NDH+eMSuD
+fS2^Q)GsmC`)8Dj6=O_kZa|7xk(y2QZvZU2|8J)=v1AiN9hcGm!7EeA!8To5{UVwkQ?ViUaZxZekZ+L
+E|<&Ya=BbCm;YD!4^T@31QY-O00;maO7>PQL<`#WEdc-kk^%r90001RX>c!Jc4cm4Z*nhWX>)XJX<{#
+THZ(0^a&0bUcxCLp3w)H-nLmEscV?2ANdn}`ok@bUlR>ON0!gdQo8Tn@t4osFuHF6!pxX(cHC$Sv)g-
+v>4yNrgkd_vAH=wnfOm!D)Xr0~&(A^Evi-6k8wlx856JiwvB!h<ef4}FvlX)|lsM~FS|Ih#P-+UO}+d
+0p9&htFyxt!}q?${x0LI^v4(Wns52=!-(_wc6)G0F42Nut~J(}HKTTYg$l=Wp1QfA7Xme`@3EyYttsz
+UQ7#Z_ZzHSN_H=_vAO+lYhf)wfT2{`p&zq$;fbDWr8?;%YW?qmj#_~#C}iT^sV!c%j=Wp7t8At=bym!
+;>Vvn|9A5G#QE>Y>$lGTtNh+|ey_~i^~Nz=vp&A}{5R$GV{d#@zAt}6J%{A`nufK0mJ_SOU)?CgouL%
+rnfcn9*t@f$P^9UTW{WSNf`yuV*IR=BrYO?LH@w${Na24XeidhRMNIj*zBQI9b{YRX=2rB+Ul)JHn-*
+P6tHbqPT@0jI67=c9ND*Rxo-XR%fi+X6>Y`M$yx6OWVSVEC*KEFP>t<Xxd|p!svF`S<Y4U}rzh>i|t2
+eI};>DnXDR$!eur?;0fq&PiWTI*wU!dT0TxaQt>3XiYS0$8nyw^<U9hc6yX5*%fYjH1W0@{e%aV<`k?
+ye1=Mnckvv=UC@H!fY}#FY5|*WVOPoSmYJ;1u16c*K;U3L)xxY^z=zx&KF9BR0G@zh~mQuu!F2h~L?p
+wXP?fqFsm&KTkN(hs1H)H(E}tUG&%+r){FEKTYexyC7ll7c1|4?f1GaenRWIv{vtmthaT&waMN!a=)W
+%WSJJ+^jAjLmXB9-eYU=`tI5Bt>;8Lh=vwVHB8DgjJ~txm4al<$c`E^<qU(I^e{>S|Ujk+fUz^a5H4A
+;{h+EVh(L{HFXo;-K7w1sNP$8P&8Zl)_ettBgKL23G8sS`$FK{n-FP0PvqYT$FE4;+N$`*0X<`8wfuC
+<H0g8Y_9rO?hDv5C6!bmI*)jk;!B>orlApa0S=SK(J+v_uN(TO#%O9k<+xU!~B`6-J|VYxHZEpy}r1+
+l?m+(<`35DyQ<v_sv@NWP#9wqj~J&$u;TPlXvFmPyX#J+mmbYjrrGHL4I-V5|%-@YlL@6{$AYg<$eB=
+{CjbKFYl-EJ{|Yz|I@nj54g1zob4DUO>MZ}2AVz!xCK+h@wNEn=hp*%e#WDKU*N<${PG3fiF{Sg+p9{
+~yzMESs2tMuv`Jsmx!~+0!=$gxK9;^cpl^ZDP@ZuMuUGMUcK2|>*<HhH@m!xTZsGM#TuHA-L9fZ6HSj
+-98k5$b<#E!T^pE8wjY(_LoV1V8`ccrD<*YT!B>YD~^MV%C5x@Msc(<4D@|P4Cc!yv9y?A#o-%VRmkd
+Jry@*Q{~(*IPNMUQC5NAA}k_d4X?hIU{_dvKs#q;wSsBhqgZk@JxC3pOou(WZyqwAn(Z@UuswyZda}p
+?+Hqo^wN|ZF!+uw6%|-t$hq_?XS_+K7qFONwhVAwni9Nu9$fy8<6pq6X(t6w>I5`GH*oLHvoraz@-xH
+x1tNU1>a46bi1*2O}Z$41@H~KSh~+_E011n>|E7Te(oobr@fnvTeQx`dkV$-=D?g6KW>QN<F9^hrzhX
+`!rsj<jedJH8ZE)M<A-$dkK$|fw~AQ>w~Eet@6qwC(kW{83USP^x3m!_@}xht_1L3V8Cws-5*66RxhK
+#DUyVkm^4%%I0^ONMyj`)2c~apeIAByE=X9L}afVDREr;ySg*-lH%3%!mFXA2fe%fX`X03z%Ruttubn
+J0qYh&JJsN>wXm+i9F<!~fg41IELHE=3$n(_^K>9=Xe9=B`9tZCN_M~h)DbM^_*P24LlM`e9Fk=Kg9#
+3l71S?9utN+TlCI+n8mX@85l!#JO?@(lbb-Ik{KL*5vwes8dT>Cka|?`6Ffs(M*?v-jSYM&HNyvRd*b
+-{i}+iZAJ+=5go^;>mI!w=0^D@(A^PG{-2dj7CR!GzdH=Ps&J7bGw|WDGs|01rxt=V;mnOo*S%uu;9C
+md=NIp2P4LZ8+KW7CoM<$5YsazUXR1JSks=e@&PzM8X3!nQ62yf`F&V@ZyApB;CBf;h%OVyrR|2zKDT
+z^v2&>+V&xCNolP}u`r2!cdGyR7IIVTaC)*y|NS|#=2p&`p(^FTB;M*G`(cNsLiS2Wx8*ny#VCd}P9e
+W6CndwhV`Pt^33sa2a<tV3IpE9%$xbpoO&^<q0yH%UD_f{Q08-A;xtDi^_b(;9we-6M!aW$+db-G+_L
+i4=n%gdTIJvTGss)9K)r{zpZFM40XUxI!x8avXBf`b`GfyiKaqt9CYnCA*j*(&vH{btE$$rDd6(s``{
+U!0n|O*D#I@a~pmddu0<QnN}pht5C-s^7kGSCK=UGxl}d@)OXaa*DBY+i>*2yXm{C4C4*RLY=ch93QY
+bk5vliF{3eXOZD3~?IN!df3l1Mvy2>LXXRVbZqj%D#b_PNrd>RALGdD4d8;7T8>Wf6Wpl(7zkf~XTBq
+|^z3{~SBk!S3?^TC7J(_Jun<eU&XY~BK2tPw}4fUmV%n(<#+(Fp3zcYrt_%U4{@L!wW^J^#4)q@^m(%
+oP@<Hc_@ofGL?Nzy_7z4(oL|K~0Ty3UJVGv70v9qAnZ@8dHO9<jFn-z|5-@=Q1r=6|o{{7>ogF7^KJ!
+ueDADcg=N{mJ82*@qskTLqaffK9W$Uu{$GSF1ed*1`9~HOO{#_ba%EO}66R58Z%wQkUmnkl%xA^|5Vl
+qBb^BovrOT@UtD=pZn#WA8p?7H_N|p>KnbUn(w`u*e|r)QGe@v?T@-HrisYN{Rd?ncv1R*w$OQ-J#-P
+iA2e&^_wd~ukhhoN1D<YfIia_-oal!y=$R?nouVbnBcKhRYMC)||Dn!{X-4FH?cvTi{O_xnEn7rho@(
+p*y@xTID(g+t-#ib0^CHT;WYdDb94&LIEb}zVK814o;dj1_GW8^7UdlEiDyIAQ&i7KUgYQzW-80@xy~
+e_KYGQ}bY{8>K?Dv)#5!Op+<u8_i-ko2rl)kl77YCk3Y{|4*g_-sv@SBlt0N*>mtVaffI3VAD(umM!<
+~OwU8W-%c3;7BU*@KSHw$|A3ZmuS#(J!YiV7f#+X&0sl)n}84?*O~M6uvtW@ZHh5b1c40tL-z>TJhaE
+itmnO_zogpq4uZYJ97UIx=u~jx?Y~DLuPCe=l_H+61C+Yhu>fF@<aK-)4;h8?{5P?`}rN$Uf|;Vs1eC
+Wc`O6zgNLLK^W#p{-!UHUQxfhJ6Yi8zxSuxRem*JODZy`9;GVDj;b`B4Rp#CVtZABfZff>G*%`>z;Vf
+}HTTsrX`uc3{&^@0J?H7=)9dzC%--ABc-ry|6Ob@4sV5jar=F;-oD2s)e;`lCo*Pe6m{YYym`=k9CN5
+<ljO<w<Sl-GKJBNzq$Awy>iT8m`c>w|wc6=ep~MLXe3K36z`eN#JTe1~ygnvCCSH2mJo5bb=v-7VU6J
+m-AQ*v04VS@xCXnrK|SuVY5PE!+1h(w)ZpZTT%H3IMwg?e-(HMSDNX!#&{|Yy(#rT|;X{&^^Tn`{#)+
+|AWRZ)brT7Oc7qJiMFfghi=<@;vVF6ZQEP3U3aZuIixAeEtciw_=wBT%`$bQS7qjgt{p8iH}rLsDeHE
+~5u{u<>*5^s<^y=|f1ko*U6v7MTH+Frxa69+WVc;}&KdZZ8;V#K%l2x{v`v-XW32D~B=yZi*%wjXzBM
+U9(Dhv3?v5F2P}T*!Ydw(?tTfX-2KlKMqT~|p=b*j~pe5n6o&~5M%lldq_>oznov=si0{F{W7d@{n+a
+Zpp0v5|)S(KCQC<ne|@un1Uyjjm1VjmLy{7d-8@@@nF`=D<}?muGDr4!53AxBG1bh3z$7dgQ311X|C4
+|25^e3k7a(}+;7{#aiWw6(O<=tAk$SiA4Bi{fJBBafwQ_NN5<9}+>z<EzlU{lEcr^AWcPLHk;pDB=Bi
+q+MN@8axGl{WIud=%V`<C~qLkh@1j0)-tW-!Ty&p5A*WfKOk@YmFNM|pxET;=TJ_EE*g80Uu1UdNk$8
+$msH#KI7MR%{qr2L(&Ior*mEy!!1l@r^hh`FbuBAc1^KpRwbT@7(1}f1S&}|3BT_v@gozvV3ET0gU77
+3|rjBA6>}!?j8!I9<;7vNREyn64zipA<NMp9s6MaWSkl$cq&We(oB2qUuR7CJCi|?yM%g$)C)-}*9x+
+Lu@QiBrCT@?}P>w<l$!BoIX!4LG5dfTSTtQjry?h0uiV&7PHKV``*n=&WUt*(%^g8jqPljl<_hR4=Z(
+Nd+AJeT&PMH9uOuk5o+G2YNXTbU-;h!mo%0`knXHRNH8hF17-JAH6eA4{7CIO5REpgmpbUBan_%(aN&
+r4K>3F%4ltNAK)|F20<`wxM+G`C1E~lIVNV=y!l|8f}qngLwTK&o8m<v)>BOFXH*X@O&^uJjJpoLkIP
+op>Jf>UT#Sjbsc!mcO81}(BI)*Um9tk-ZkUhomq94jWm-Uvtf@k#n;&LFw04JcZvN^<~!<r;@J&6R-$
+gi@hRNjiu;55G?e-A%l*QHf1^RUIT0&k8txD3Q<3Il<I=>+oGR1gA<gaM(!_Ac!+kT#>a%@qPcz_Mu<
+hPMz2vlu<L7N(-Q&p+PkCcJuTcI*GJFEiXG~jVNlTt3rjOy~Pnte^T>2QE$?Pk2;Q3k&?{vxYN8f_)u
+*`YfeVwRXl_?sp@*0=-A{Ll0jPT|Mj9r0AIc=^?!~yW(Pa`()_RMdCZ?q#HGMJ6`Ye4tUAkF4A%3tUJ
+9o7K9Y+K8Tz!!{RC-k`|Q#|DdE$go=+x4AkqJ2}L2r``wdYm?keEgf3k5VN2a)W#GReJ?ZS9&t+jh!)
+GRI|>iodWOReZc?XCn`~=iZ1HBaq<nlA6-^>Jk}p1VXRa#MOwvl5%o>pzJ=1)(E3w@J-6E<()Pj5(#}
+yIW<wv!{24~1=k^;SFGDX-H=Y6ys2>T3c4}a*5vE*vD)dG}aQL&OM)@Yr;10m@XDOXZ7_q!AN6w;{Zf
+(d?x>ebHXYe898F&mj`vK9_C$CzU=K&o*8-8~D99^D;A|mr^rhoe>BkXZZ-PmfMxUF4G($+3m+S+;3|
+M>SSrvFjl3f7OXFFYsI6MJ{a75v1A>L34p?A>a2@OI)194?+r?K*$6h&Z)riv~U=!mP)@Cq$Pl@2`yr
+boB}7>JtuWPo+LSq3rF{QTx}TixQc>#L|`)N}K7Ed0{VKUZzXCsd&1rW|V$fTJSW!ol@{>W{j9}R$xR
+9>57j`+y5cR)h~>uQplmyu?4v*UT_$Z0@HS=x}^s_vc7qt8?TtK&<=Z2EVx~dXTUaXTAaRjsrU31M&b
+3R2h&F4{&^o{N78<b-(s;de_auwPksq``?qBTFPJumyxIhR;svCs&oY|!(gp=YBm1#6$k$cSk@O=v@2
+H3{Uwxs%f%$g9m)IplH{0b!@V3<SYqUcd!EG9Sww%y|)8Ru(8JI+$u#qt>{p{bo9o_vEwEexh(bNOkX
+IU<k1;4O3U)omo$C~oLdUBBYevUj(yAc~)V{Gj;^Yq!AzPDWPiK5XGKVY4Q+znX1U2sX5C4S`bBTYTh
+@Y`$ZeKGvVrcHoJd6n%&;yOj@q=WD=CBA6O`%!iPc|F@jV=HLGviOb9N?tN${P0bri@|Ki?|@syAzDF
+J@RUiDGSCFRQgPtJ3Z6&??@(5d<?aN$dJBzu67Xg|Yki+FzsKr(QWp`{ZESx*5`71I9<|Mez7uhonXY
+8hDHNU@I~P-+M{vK~4u0WRp>3aWw~c;;I6%Df7N!Q>;9Z^*FcNSJnz;3vxKVfJASRP#&6B=<jWtdty<
+ML(PO?1YtGk46Ho)GEdKbCGai<&p_<coN-H0=*GQDMek4*_a__oPIEoV&3W8nR|EPJq7cMs(P{s8n&C
+Ft(T?I|rU5sjd4U3ro6Z9STMXqg!+<iZY74gm8xZFP?1$pXNFT{-JqU_>6%vsd7I+2?`#%kZ_Sms#KZ
+A9lpr{&O010{wd6(#ZU?k>CGd^Da+;^W3&fQ8$Quo`#~W=W!iaJeFoRB=D2`hQIn;L4R)0^CiH8%((#
+10bFBwmQIvsUtZAjd6nnwx5no2CFJRc&12k5{XC@f^K)A3)X{dqdJF-^Fk%S#tzufxV^i;6c}t}irpz
+-Y`5f%Gup=G;4_gt_^*!Va7NEULI)1bw!e`Q}6K!G;dC2p9;7<i)Z0|M^d|sD&<T<vp7+*Oq%kqxCrP
+`cJZ#g01t*nSVn&N8f2h6@BITG$gTs!rira{KKsHb;9&(;CTpslBA0b<@WwrTQxmHB=EX>ZY{9UFxHx
+2EsK`}x{bq|Y0Zz6vqCYoubA&(YRa0r^_t_+r~;$Cuh#pc|`GOx!D`kCDkoOgh;LW(5BLc<lRo1$eN(
+ZyWNp777{1{_(Q1lfQy~nj|<UB_5BxmM7W=@tY+3_SAS7{G14V?t1az=VRksqrSRETPfOOv6q=X+-Eb
+w*7Vjmg|L1Do%L^;X#YK8{4Pz#3%;+<5$)MRNS_79v)wsM)OOlL@dtGFBf=K0UKG3oX*=-Sk65Dz_89
+i1{kxjf7sWD7|NDcl1NI5X@NxWh;@i!D%PZkkA>De!{a?iM&+&twR3Z}Mo<2P9*T&LihkTC5n6dYLc;
+AHI?Q`NZ7~4;%<^{1%pEv8|O%uh8_YW=;Wq0CTHs0m3f3xz|Fk|3)H}$tD@ghxU<)m;I<H>@IAZ1a&?
+msX~wXHr+OHC!(T&J`#=|QH;*V2Q3jqg=vUYi-4ccU!u-1keA*Qn?nLOYIhBF648@q#~Jyb14Khipi>
+e?Y~Z^n)tQc)4CLfAKC$e(2ine=ze?eqmc8w}Gedz1y?l%Vz<X(<t|p>E}YW_rpE~?}U7j=l7a?ae~i
+qP)kaYm$5nN^?e~@Mj!h?nf5L-?EvuXTxOJkmnGiWD$U6KhsX4Rl85CQeT|ly>ot{TshM`}Z1PI+?`J
+6ED^d18j^*orAWyvxAKI1`N(XNqE+`A8!3V1vS=H;;#DNtfuHG)Tci`5nIfpohf@$P;5&wShL$(*3(d
+YrI?8rD<jyuQY3pQteRc2EeeVQVCFVX@tsx!;VP65B4>ZA0PvdS`V^{96N^BwhB1Te?-gIMDB9F!5z?
+<*rM{Wej8c(@VmtFDdhhrHJWZRmbcQ5Ni;quPdi-d7gfKS!luSs5sw@102J!nFwB-H7wuMWV}xpW7uO
+U|NLo8_+*kHrlUX#{GNo{L4|jquNKPx~+z?0eC^L2LC{Fuh$%+?&|A}u<y{-ZE2xEO_hdNLQ7j;fmot
+yA<`^xHX=r=OB1eRMM&c<GMb#4tIfR{_B;dkj+PTw7damZp&hQ$(ue4SR%aOD=8B@B$6%MMTt?WXxzh
+Oj5T2LsgWm}nqAn-afrqRseUGYnM%XWgmk8OPqxwngrau|;D=B}8dXDY77__CY^|VP#CuGDk($Pz~u<
+9IZKA8@(!2Cs~&O+NRq3r&8j*{Vz>#ENovA@O&hrIC?-7NcqpjVz^Kadaki97q5^1;8VIjYaPUT0rj9
+99g*t7scC{><*UW4v7b&>~kxWK)XxxJSz#ssP`l{?Hsj_HVjIUh3_GFOpCHWwH^Wo+|3M2M53xFTP2?
+25pzVS&`;^R^~lq4-TfOy!n>zeTZ2`)9f3YW)LyU5bVtW{8D$T>)Ao%snT4}I<>TCT|YE-mIJqdCO+=
+ew(kkRj~%pmL!`CKK|OtBR6aR=vgpy57JPla5R1(#c^qrIiUt9BRqf@2Qulfb96^PPN4;<TU@)=2^Nr
+!??(O!L6Yzl%i@Mm47P%;6J=9NY{x)=7#7bu=3%Qhg<!4#mpB4Q%!7<N=;?K0bijU8zv5RG9+`eq$xL
+xr~1V?Fpn-Ly-jBQbDtfCK^8JID0f3L*t2MPL1=3TAoFJ#|R`HOoI2h!K?LfiIeuJr}FsB>OtgxQweJ
+>IrzwC8fP=ha%gJ+qIp>hq{?nP}`{8;!8-jg8^P(1$jE-!+Q<6><7o^&Vr>U69Wro0tZh6(%k+=9+=~
+Owm|?`-VazT&0U?Ud_3};}VT%J9V%#)5<mH`n_h~iB*SvTa&&@WEbM?1LnO0ZE5YMyZiDTyQT}{>)NO
+vfOyC<Uih4I^)*5I&n2zb1hWg!-tqHjxkHQ}zJq#f{(>>w4ZGU=U<GWk>W6EA-DSV!T*MJ_yidkm3FD
+}V<?J)dIrQf%hjQjDx>3nvszn~b=LN9$e{_hF-bwJqUj5w8DO%6<=@qbT=^`rw_F>AN`dc&I^|#Ld@U
+&Y)`n07*A9mjAOrKrbIj?t*PjjAOOje!Q^K1Gneq3E}&Ik3<B|994uFFK;Yd^UE9w+hyqS5Y!faB#o{
+1+F}(k4|Eh?TC!*|lBsj_&blX=jWp(K;u-xdCT;#_~4mZZFDa`XapZK46^Oo>A47Um=cHvrJ`6Puzt2
+r!(|h(@}>VsDlgm)4pX9|1WR4rv_!S{96I*1NaT1F04m2@L7(!5U(`N{jgVa%R0HuI`x{ktOv~-%y$E
+3Jy$^{=f54TTfn}}2aH`U838$V=QZoJ9CfPFCO=%QO?ntIIn;YOT6dV^CML`kGEZ9@8f6XwhTy#>&87
+g~tT|8Jx)QV_UR9tS@vp)?>MLnSdr*}?mj=*fKIpOzws@76vA$mG*rUd=zCU*E_}ut-)+L)QH1M}Z*A
+VBv&QX2nL(tD|ZThiJUD;4qld-czo8C6KsG_VYQyjmroH{@>-k}BdI8%-A(exJTigkyaqHefN>tenR-
+MPMUin1v)TOC2z(zD;GDQ@dcF~X~sd50cK5p}(8bzjK)EF(PN5XHTd4CznjL*7sOj7Z@!Z(F}DEks-7
+yAa)7?-*W6+jlqo2`A!}qDf*Jb;BX*h7%PL%2xfhNx{jru(kA$@UD~X>VXRBBeT7zF_dW``o%1l<0|K
+2ck*Rf*`XAa!}q6<#%AN#Xm;q8LL>5Wo)IZP8h=#TKO54aUe667FYDZ%A~IR;ZJ@)yt2v6&*XJ1B6Zo
+DDns(^v>$jzfx-+(P-@k$$gEqIX*P-YzmvnHc`@^uuq-}~eb7Q^qms)B<@NNGMdHw~zCu`=nbs}GLC1
+{Ddce>PlA?^n=jc{kC(wX}pZ-eQ0&QQ<n+gR@qna%LkPLD+E27yPjmcG6pGR%7PGB5j<0PDw2<38&DG
+}Ix0x{)6P%SHGoV38-(?}f{X+J1FDx|{VQEYg5*I&|0iGd7p+^l-FJ`8-ED-<oSg#;!w9b5^K-t#;|x
+Vyy4XG2O>4@1Q5!FDLPvM}09f9rR`UZ$;eaO6CXcLyXm87u|z)F%9}q(nzChO;dJeA87B)htJ9HnoHU
+lr%is3^ukuUz=J`?v9pYbcBrUL<QS1Wl*xJXlcdjWgacas5*OYVYy63B`d!(s(U|SISj@(LLCR#JUlX
+%W`R1I&SUt1okGF7qacmrv&i8xc@8QeJc{fh&LqU&l4sl!|nk{k?=>}cP7_~c=Z^JC*?<d-+JizLmA=
+~M~)ymGEC{-~n?3Xs`i^%7G2W`2p2kB$)W&cr%c#3WOD|T@}rqfb_u{4M!cQPIOY}rpYlYLZE;Gf|Bk
+|z6$WP19@u{@lsBmHBJv9qs6v}F136XA<^$2lj?7=B~Rkv>nZoLi6``d+pPd!O=2zz<)(<csP%9cRC-
+{y%*hO~&)jc@H^8X&~oDO&4L0T`c6hXr~+t`cN>23)98$-fO`-Uyf&p9EXVaVI+$?vH`E2ya0SOqB;q
+;ASGTt;muI+6621s^S7>7xVNgja{S>!YfZkILr{!ZcSlvjZ4wTA@676k$>Bu&l8v8PW#;6%+rlTIlUZ
+I4$|J71`%;2a5%VDqS=n{vrQZ6QsgJPCUZh1iE03<59A1o=JcfVr{%f}9AB~Q4KMnh}81a4xzFn^_WA
+8BHPvV)ym@n40$n%fd)EGC~Yx}_c#<$r%ehNB1V#%9>eDq@}$4q;x%#-8$qv=m4j<cUf9NK2dU#QC7c
+?)1L|7Ws9JIC<|uL}0HIZH?zB<C;y?%T-w2f+E%mFRc<c}AFVr^hj4Bj>C$Utf>+SQ&NlgT}6PI%5#A
+|7tBYm^O0Lu8dq`XP{~Q@FZ8uiLQc4kNDy17QWI`cAMrr)?mUacZiMf^XpdGl^@OYOzXR7l!b(INxv;
+s&J6(4j5BjazxVf)Jq&zT>qgh>QpZhh`xNNhXPX?#r7vc}ce?ai_$(#MEi~u>tzzF1Y%Dp2Jh5^RueY
+-wn)q;h;q{S<lYLrh+xU40$^4i&-#L#jV$(x&K;KKC?SP!iB=&y@w3z|gxIi2K{r3&KK^w-P^9$UMpu
+L@_#&0WV<Vh8cOW@Ox#(o*Q=Y+^J7yLBR(MKAB-hR;GqnfL&Qw%S?9lUNq+}1Ve#XTQZbB|0uPW3%3<
+MbRkFSb5~V~*2&n#kokj&{-_759_zlQhe9)cWE7IHR^q*KAP>9yR&^r;5MUz@FEIvu!TmtNA85A;RBC
+_;%GtK=~@b_k+6g+y?qWF<wkhspVM0=yQQn+Q!KS$4W)crwd!cahf3B0!@7VMwwfivSdPBG-q3^-h&x
+0?(t53agR%L9n05p+StA(vhySNe}8oTz@@b|@X)UMY2iOi&Tlyp!Zo_-1INyra|fTuRPAJ#eP5Cvc_I
+4zi2J%`xa3$b{WxC{_~IL>ZgVy(elG^UbHVQ%^83Cm!yg-|*tNZI#v=vOjmSLEjPD{S<6*q3#=CNxYp
+5c{)Sdk)K_l0Y{S$UM2Ui4jv8|?muIdXB4z9>05As4RI}`Bg?Ze+4fS(wJ&y)_|VGwDruJE><!8MIGO
+IP-HlI940$svxjU#k)_QKdoVN`#D`;jc^It;&ISMWXQ#`?ee+NI%~R9vnS7P`Vuc1$?()vo>{z-wwfl
+8$cOVsK0=JZpPX>qp3!48E6?<e*@^etSdgpLGht#mdJLE*fM>9`zq+L3jFno^kYuo1f3i7q5XAe+R$q
+cJ-mnbBMv<A8vKI5JY(yV_)h%R=eF%Rs7)H;nxFbe^GWy|Im|QoP+$-J0rtlYGEZ(#>2foV$Z6Rl=ZT
+x^V!nMv>CYYJ^_~K?{wCS{A`Sc&&XyB*6{vpfO^`p@^?cID*mh#G?rdw;bB0>rn{7EPf*;dbYNmk}-#
+N^&jl59Io_%btXn$s#XV}fY{4dytJ8S-?^q@X#>vs!hm40^-ewDLIotd+<I%{T?_8#`NRm0ZNkM%@ES
+$VE#TnpSg0n?-93>AR>tm}q?_&lk^IWx)pC*q$?nXuq}QThN%2J>JOd#}*{$d&QRfkG|Fc~Yz8oR{p-
+Ulpivi}C#lR=WKtHV@Z#&}}rX1?=C$pYv);A3wmpNKN&DCgRL-4)(#bUZn9s=*nqmS5xsDJbYvLAbk7
+zfR|@W4ffu*X}Ah}CjWOvqq}?VTRaT^>p;7vV6+w}TlstF{{iHc{R4*`Vc7d1?KEwu>vP5~*=L4!>qE
+OOLc4V~ts71Q&+`k?9{Cn%(om5SRQ-;gr1Op0KQ8Cf+lQA*Sch&5HzO8XgZAh*?Z6UKFH8meUg&^n)O
+m%|9`T{QqYXTzL3TXZQl~a*XbbQmirL@JzNBWiXk?!k=eMv;a_)<qe}}8`xpdQ)%aOhu;nOc7{Nh{@V
+GQ#H3;mmBN!uD$K1p)9c~5j%JrP|L|H*^P`Jx>@ZWbC$IGb`mRfNgUW?gT581>8nAHVwRO~XrU;y?j-
+*z#-e5dO3r-#DarR(;43-txCIY9W)pcBJV9P2IGq$U7f6aooV)FUnY+UGhBFmrS-O^S^-1UqGAeo-7b
+2P953{9tBRxv7sfCq>q%N;-ZSUAItAvO)MGxwmSapKsI7;v=OdL4d{8tT%eCL<LI8;>Dg(-GaY!kfoB
+@%mw|6pO&f+A3NmQ>YrMcY_RRjS1>n`s0SEG#`84SCUEC-0XDM&B4k>FpVzPEPE^9kVz_T2bn};$x@7
+p{)73Dr#IQ5Zg*w*bfv7`zz$Nv3%$lSK9KS}2H$7C)R$FLmsc~S0;qAZ^&cLOuya`#^|6Xfol=lL$=J
+jS1yd0w=@nMOSHc>UowuYZ(tDU{6aNG7xMA+rsre*^ejkNPtv`>qN5pau5rYTR~bET%YL`-3rl-zX1+
+IO{)koAlM3h8o}TWQfKF^7W~}3{7h};XgGwEa1QW!Xw&;ITm{<HA0;o<yhRMn>m(xz)#y?rme@fpWs_
+8-9<B<UyUtsU5uRHl-(-FYIZE8PC+`(>)gyaVyI`Cj2D!>sfR84UV(zqb>*gAp*&;f$#vf0f%_VUs|#
+j4G9PsCyFhD~I0yN!YeKAc0J`zTLJ{1wMhmthF6thMj*fSa^{dqS3*zG>KA$sAy3?o|+>a=_jkP;B!S
++=Y${2S)<F0HI=QokR_syFl_3Qk@<w(Q(2Hb~WgYplFpaI$9{4V11{FP`)55E5!=<?E=sgY!MNXn+!c
+0~{UCQtnR>hbRr$KBcYe_pM{_tk+vr8DDk#Lrc{c_MM_`23Y<H|Mx?UWpcS&JfBf@mcbnM?2oTOau#1
+zsHd8A@H-1>#1xlHN*IJ5W46Tbe5dU4IT55tCXMdG~UzK*o!<q<mL5e=Dq+g#o|9pJg(+FYKU!g83(#
+7IMDC!(bf7OeM(Es;V9>Ii3sOSMQ5;HM%X%DG8*qEi7(I3h{JtY(Ijh{8G|uimA-ySMlF20V&d9dDCd
+03`1L;umA~@*B+=f_^#F+Jn1?Y~eV!3vAJ9_pw>eME{du)e+3@l4Sn|00Cl=h+it%yxXe_cYy_WDfR&
+)|&ya{?XnzTKl=8a2yH_CT8zSqalTb1j&PSg%WJ8C%Qvl#cFXI;5wZ)88aY!^3HL|jb`Tl2MSH^&=JL
+k0%lFPa!{N9T&B{uOGT$H-hYA7x;!(Ik-8Iz}Ah1L290)JSrFD?V;@5&VA>{J&(g`G#%w(BI5c>ou}}
+QxT!xC)<IgKl)|cw9sk9bEjYvIZrCy4>;a0APz3ghzwEpjoci8j?d!Q>f!~@?x`J#9!Li3%&?jl#CXP
+Bvv49df0?$9Fw+3@kGOUM<~qRK0GLiEc&NEoxUTNy*vzw?sCx^_nP|RDOa@s03uwEwkcDcCEcD6wNlF
+&1ZMOq<uJ?-aZO>ha?mh)xE8Md~D@0sw&t6e-aCU-z7y5szoT4#5H6H)EzNW?|T2kWgJPyxBEk*UEa7
++v_O&$BtWcqitUp-|-@G<?b^pp+QM2W78l33r(4%F4K4S$z#zj&qjq^rk!tW9?vD;jA=Jf-^H{qo+qp
+0@siEiJSTv8+pTA1g;ZA>(%B?Kq4$lCdD-X+QKsLzbEo?$vTu__M@V9Z{QX{!*MKtaFSXF`dv0-FSL>
+oG;`F`)}9Ph+y@|sz6cGtgPx0XQ0!Z3uEQSV;uKp|GGnzbihyH_yXU5>Fwxl#tpe5w~fzhVe{B$!oDq
+82b1<*mtG6{7LS&-WzLwgGA#W_MN<A;ZjVE2q#u&lhe4a~FBIVz?_zjfGeh-@uwI5`95`_uYXNwD8)R
+wJ-x1>6Rnv^i1ML5^&}R|j8r*~EIcuPMk*<k0V-WORF2u2_hK8-)d19+y?U8c4H5xsDm|mva4meeI1t
+*{D|Lo((#DU`hgL4an(ZqRDK3rb~&p0*&AG~-7*FjsFuNiVf8QQ+U*gAxmv;j10;Ml{}#@4_U&TBH7x
+YtA#bbgTuV*u%j03!p>%rhY2WJovx3CHQ<Tu;tPA{;;95I@gVVyj2EIaUxcGSxU@j83P3Z>@zsXRgS0
+eS%}P713xn?8kvB)Mo%T`RJH=T0a=m|3g@ruSa)Bk7ONx)6|<6Xg6)P(6G%R?Od6qoaa<IS>-4POzkc
+~S^dzjoL@2%@$4`3<~O3dv}eBIHZDg`YFh`UcFc%2i?V^WqHK_B2N)06iZ0ma;K0Z92<NsAM(thE^&%
+WSk}@1!mO31@X-&~xc&^pUqPHPUtsZ%Eu85pJ?dXa=Z4dvauI4>{1$rEQ>Js2_V3S>xaIOpc1UO&yX>
+E9E$Kl0tEz2z6`Z1g6&Oto233itAglT7E=?(b*2iJK^`)VsAcgz;;1E-BLmdP==Gw{u;x|W4qO=u%sH
+jYF3K&#+SUW@J?+pnYiz|E>pB#SY13_klP7UNx~p3~+z=PCWYl=ty`__x>InGe617U#n~CLfF>d<biQ
+E<S+%sqf5-3;%OoG>zlMecr9)#id#AjTa4n3NKQ?i+<16-;dg{g!S~|>`srS4bhjNAF~y-4``#hx@Ni
+@kFAU>9&SF#xTIO1a&9}@vtAiN96E$|a?EwIIo|L!_%<AK+oEui^Wj>M|3|3fS5oxIE?ti-Hs^|lXT|
+1bzK3=HVt5Rmw@!rTg$Lggp7%_EXL}Mn|KT0*qz}NcwpHn(@rG%)+{b>kRmEyfffu&R^(AfPnc19c>R
+!kBFm`i(U`#Jt;TXDtLwHr!s`ai7gacnQO+5I9gf-GpLpTy1<91D)<Ginl;JU7@jBICYP_G4H!%lD<&
+3ScY#5q!Nl5-)`9pboumdH-ON<=a=Q8Q>u4>?Pfuaf^u<35hvI2~f8vs8pDp|{x&?{glWQT=&+W<P9&
+_mId;n=P`NUlEO8qTS5RNOR2=ne*|^d6f}K(?ppI*CLeTx{7TtI(56|TH*RD5q9H!l>@xJD!zx(7<}`
+s_*S0uI-G6ku6M?_@4euAy{IL=T^4+Oz;^}S6IVa(y_#qu{w|lo`w#5z(Oh!QJ#ja`1zjfY??&eglg=
+4PKS|=95xNaAv<3IeJr>+=GsisUJAb~X;q#Lp;T#Ar@NxtHTX5|#=^e<OB=Nu6q<4A(y$67I*Z+Xt#4
+*D)9(OC=!uBqBgRT;9Tsus<$M7cIZ!zf}NJ4k&t<HC#d$RsA`k!25PW!SHcyrGaw(+~smbivP?Fo?=+
+T;}NoJ+&G1@uwa57(^ctRK3f=C-}#`lbI)c^?+FEbp^_N_h$Ke)Aep)(Si5y~^nFe^YeLH2a7U<Ar<G
+e3j>%{gZ>PBBQGzB)YQk{ciZjs|!Vt@xQYQ@|_|gt{aR<gB$+VT+U-RBC9J!a3$_J=IDj(=@ibTPR+B
+($5;S1Xx$pQJ|L7huJ7f%)CcHK_LTV$*WIG^l+ouNgs(?`uv|-*{-1MJPwAlP|E1Ysm*F@1&9r}<2|Y
+d=GLWmSEY~vDaZa3nc26nOHb9PjNVn>cXyll*Z{(#?-uFbKbzU{Twf^eNz#e~YPbuW5v=@1Z+XCQ~4x
+IjVyOgWiqeuOv<zLa{x~p#i&-7U`eQm?9{9C)CQ<sjW>DT1AaJmz?IYp4qX;T7wI#I{F9qfnW*lbVPI
+<&LST-GVw_XK>MS5dd^X4zxMVdDKvyWECc6S)g*<e&3YpU*DvU<+iTS%<!YJqt`SBC)kl0`+^fK(1p6
+x430r$$=fn*MdB9{*bwrk9h{=eilwSPks9&5wY3=zploZKMLPs3t-8Zc*6Oi$?@IzUhqYm{Ye78cmBo
+j9UG7PmsGOfwA(*Pt`9qKQ(oMM{Ow!HhkStX-o_g^*CVrGqdi>i5{-S6<T%*=oI{RabBzc$Un9b6I1U
+e9uk#t<2H+M-A6~j4<xp9m)f}U4(70x@F7SY{%hf85&!7Il$%nH<(BH7`8P>tcc`F&tH2*b5xJYxR`S
+5*3!{%q!19o!(bmm*py5`xU(T{6Gnwa9P{#L2i<&^vJX+rI}Fw0!a(i@2uuSVHx9!2|oG&6Wps%Zb9D
+kH1;!IUEZgQ-Q$x>nX)qm>n#zRe3lw10qOq+P0SfAtBquIm$skBS(3XMsjG_c52l*y+>UZ7T{yaDA4D
+Y-nBe%!VZ*{1f=A{zXRkj4ge|Iy}3yIg1(=i7>}7W^g^r2Ss?g37>6s^(nMx=;?{z`T^I){%qI_Kk^n
+m6`0Y0>#OGeIyThRX5!vw);sV<w3xhfp{+HfXl1-_I3Fz`U&s^EmhkM;Z@zEe*=SuNU-zAh*42Z5)_#
+kwr^7!u@%$?T??ryTlN*<xkC^gvUlRFgNg_Y1C_k>a{49t3tp9@1<b1oM#t(ULU9V)QmwFEJ<A!`}hy
+2{q&>-a}ooxX1+n$l07L%V_AU_)byTg>94pV+yQhuHol^^PB%E~&(18lF4GV`mHcbAzvO_^y<keSO@{
+=72N{AZGx-;21+%rn<N4UEc+(bVt-(Zu_slo{7}nbFRTml^Gi@iOy-DKk#{p)yY^XagUO>tF@1Pogf+
+XPyIUJ+J4G8dq~(%XLGu7jc|g-OpL%8od{bQbzA*F0zf@dltE_RdeU$*yZ0DP5(E`OY}3Sb0{C>cCm1
+Xa+)IP8ljC}@vGHa{aR*LOxLj=DW;$1K-MG=U>jAt72NNp<Wx?)JvCjH?Wrc&o-(6rlR)qC>6)Cc!nH
+4f^l3{6saLNS;a{+yAN+<K<&>9ca@>+>{Atscx-^yMKP=^a(k!oz_+Dp(y|B~eU0UO-DWZ;jwdM2R7q
+BmXp(bOn@|9ZSUcfBhr!{h(xhtJ}QT3F0@XS6)FMa5A5#c(#>jASG*AH>dC*#rUM40pCh{qCM)0Mxl>
+ZfX+jhAz7j;cL(mTPLh@v2{`xpDH_ag}ZzzIh?HZop$%oa<k;T3adY59GpW7j+GG@p13G-aVZ*v7|^-
+?W_~HaIC2ODYFj8H5rSR|5lUjx_nS;<UH$Mq<cZeG%YnJ*}rJ6WgD&QQ)BD8-Q*X?J6+es=Xl2E4Qo@
+j<!hGlTo>fm%D+wv|H?GQztsu+3t0GfyM=#$j41wnG=YE4R8hD0UHI2O%0INH82?;x{(acw-*p!LebD
+6J(oy~yO>zDK&V>BKH!J@#<NTXP+%I<2RK@ha$-^q}&^hnuI3E7)J@W8*lZPk9@esH?HMYL*#KRc>l8
+v+Yp$ps&ZRM)pipD@D=$QqZ^VgwgTsp1^e#<a)@l~c?4ua1G=6%R6+UJ<}FX27o7TOD!HcQ%x3Qg^A#
+qYP-<a()`27LE&t|I3uYtt9`k&gQZaO_TwgFrqm;9fV^%ewIF$M=T9)S_Y2PW&Ic=|`m@-q0(`s?tQs
+2Edi;-4JVX&Y8z0$^x18+D`6~F+D|=*XdBa-5|sgzeA1p2OJvL(-u4J(0R*5*?i=^8?-rt_@$Ha%WB3
+i?sfZQe5>%j#-#ZqVWt5cnI5*zeJk{0NE0Q4z{QyY+#8BY53bhao)8BeknhPYHH<}^X)QH_H`Bi?DqT
+-owuIv>X+D3A5$<rz*$5wDMX{E<f^xU^QSJ$m<I{j6^>OLj(cO0<wo~tOee~7&zRrPIkMzy3$uSa+l`
+wuB&7Y$3dyzlJ+dqJoe%ME^HoR2w4tb8Ej)`T?M4qwh@y3q9fmhKc%9?rQbL_|G_xih>B>iObdg&ctS
+<4qm$`?uUOcUzplbj^w+br+0%>0S_SG_SH*RzNG@B?FQ$^R~G=@XW=#C0gKwv=jVOYQH{meT)>ZK=&>
+?zv#LB`@02dbTB-Y)fIcYD-Oivn}}(+R}PUTk>1ml1(&m&hG}$X7H_!ngH4n$5Hpm{yBy70#lwca78;
+@$#gEw<^Bj{wu^1ZrrMCV$+xw`Y(pK1Z759y`F*+BhTgQfWgBWX+fa#?XK6#Zqw@R^{Qu3ka(p}9mhy
+bu|Et^nPVFdHwj<`-_*T3f-TaR2NR`VxcfB>X9W@M$-$RTtyVaECtqHQs=lA-%oFx5Z^LptWU|GvgY)
+f0swvd>|+LjW_w^`n0iR9zVqcMYPY|OBwb=B}iO>}p|SMA1i&4-OJ{aE&I<-rHs{5}!s(h-MIhBdkVr
+N$2*x99<_mUc5F#EvR0FX%_QYFxdudrHl{R=B4882#afnz-E@GbiYOiYH{BcwUM8rSXi<qv2jGQYS$M
+xd+I)55{%Kat-lZN`<s-v{|%kM`^>L6MUJ08S6gC_Aa3GMG5@_&p)X)$GOg)*_!l^HX{w=(W)(uOzi<
+<SN$3-SRYYi`d;Q+BxCLavHo)ZHLAbdwZ*ZLv0ekxdmWV#=$3O{u9ZN2C!*=St*hQ%4R~j>#R$qiV7I
+`u115CI0UhsF1LoQ_uAsyGHfVE(=Gv>;3X$ehg+>?06)&WT@Lj0W-+oZ)w#X~_Xs>Li&_!&ge!S-x_G
+<92{(VN|70A{ot!67)$vFgOp6!;j-AKC**A?)wn-Ryw(sADUy7zJ4;2Dzs{O+G;`uksj-^I0+y7Koyv
+!%^t+GyVOlUi!lBi3>?&B}`99kjVa>#6Ha+3;%aV}4U6xaW>_j+FG@1<wu|JJ0G}<pVN%hI;tj<OAv6
+t9<-&`2QpF;f~A4C*MUr7=Mn^>RsgH>c5nHd_gq*S>z+3pTMePe>luN&y0xFTXJt4?x{VN4{KXjZ6zO
+CE%c7@K?jZRBpoWX;5TQ9_I%yceY#f0x!P8KUk!dIgYR#BsWhO8GNm))GQxUU<z(ExC`sa;66DzeT{<
+dL31wOJ_GZ-UA5edmC*uvsFU!4vIDtO*TGT6gvnV4D`NRS7uI_3Hr*mvs3@_P&I#TAW@|=VC#ESnG)M
+soR4ksBmPr6<qv<|plvT44L1GiNRM5A}IsH>jBzQfRH-{I!NA{fw(@Dli9F8FYM)SL3`LVX)h-y+bq1
+npGD#pb(`)>Wm8@yxuW6Z7A0=2tXB{_#B8nhQAdWSl+DHg5GKz{}Gt@RHcl?1c2Ov|KBl*sr*ywd0u-
+*}p#y&NE*H-rJGiOaB#lzaoaeQ-t=mUFX`~++);#T$3ne3;IXy7lAfa!To2EhWe}XQgruMAlnj;rWsk
+xOMCoMA<wv*<~t?F9<xIn%i{d8jgT42Kkj|G!*b8ZuxoZ|?I8W<8nr&&|31|ZUVcc;E8w#`MXrrK-T*
+m(jxA$a*_UayVdCbP67NI#$BU{DCD}aBr?v&3dK`amKK|6>W9GllOz>xt$WX)o%FusXhRSG5AxBLU$W
+TQR8ESe58JcX7q5YTMNrsH3aWdo@m7%6&GPHSeT!zvtG8CC<L=x8q>~Gz%{~P$b_>KMFNE~08$Sy-~4
+o~+$2SV3Vz9?6qLtTSytX!@0wS*tmVgG0=5Id1p#Lr*T(}epbX+s|EDZ_nP%x1*uu*_12UtfsVA!grR
+edG042k|#N`08MyAJ1{nhm+vm2HXSgn~Pjxf7T|{p%pf;MVISr7M5s%8M{E!$eYTSfj#2>UI(^w528c
+4!2rH3#+7*Pdk}mFZ{=FMm!rE`ztObt=Ve-4nNIejAq{*EU*J8)A@3P~*s(<X|I5U`^F89958Pe_Zg~
+^bf#X^Sb<y}!x&JJ91-NPOUjnd=UxeJn#~0RbZPqe3`cro8$%fz4q2;b`yArMY;skZ3-E+g9R_`;qJe
+q5WdpA|BHp(dXRYJ*hHF$3`$H1y^&;DkCG(6wanuc(yTxcsOx7sBl@)<a3(6MPkolD}^)b|E0K9A=AL
+itT&%6E+|f3&}e^HRX~+h68>>8Af)Q&Gl!GTFX4{`C>ATSfcl9O}p3$MY6jPDE`YOy7%ZkGXI8O*2IM
+UXA;w8sRnIQ>@>E-`OW}1J{+;#P^}$`e3(NKfh0e+26AU-<fYU%35oV4=pkGNTH8e0vs>$3<^tsM&dj
+K3;rd^@RxoS*H&=OIAF&7s_#q}?QcRBUxK`G9!~#UqbW8<#r+&(xF0yYr0u_hf9dERFJtE<B%2qc&Rx
+=doZH%N7sW@>zI;+f+(U9K0sQB_mYnb4(sI(+_s{j!`QYzvv@4G`btre??me7CwCGfH_p`c^1(%lFRt
+?_EXP5cxGM@o6FcK}{`2mc#WPPA3WuF_$>C&BP4RTJ!d!OI*=c>n}mzz%tYdsu)$$BJT$2V-Q_qs587
+M48}u{lDQZ7HFpsiOM;^cHp3^C@b7M~>xfN)g?4`0=a=lv($08KV6a+l){S+U?7>>0F!7bughvQ_w!3
+2Uo+!a6RK8$musSxHqku`?Ak2>h|I}hx>E@?mwAu@)F>vbGWiYw_V^_Giok1;Z;D6xt9&cn!ap-%QMa
+%#xwM8m}9^#h|QZ}2bqWCZx3atbpg~rEg5lJIQ4vNjZE^jet&5?e)3)D*l3|+O#&Tnwa{_JyU=kJ>Bx
+D|fW^7cRytmnK*!SYbZm;zaiN8d*I4NI?{B;pI$GDS>GF)U?ljJOGQyuYOFnb&bF`n&8N0X^Xh5j7*j
+y9D^*~$~R8){A_se)#h$SBsYCbw+#<Yz1dREQ@haC@p@vL0i=Cj7}F*_mGYEMNhX|B0Fr_QAcN7CbP=
+syeF@KT9~x#pH<NfW;qZi#D_V)!lB#FBwp+7Vk(pWJU#L{6_2!BY=`ubV{hhwAKtoRem`|79t6<0vhU
+Oytk_&ZBNzb8``RupfzYEoZY|^pp|dIw8KRDp*GQyOis_D&+d6O3pQ0Lfw7(tQw0k*dKpZ?&UqyH^Mb
+xIlkZEIUx5-(nr^PixIhIWz2q4^4uh(Z)bYwxGr7oiQ@)6yiMze(?O5wg7inq`$gH)LavMSHK(ifiPk
+kaiGED1o(hN5_+Fc+tH^}U#`lNB*!Q_={+xARB>BET1jjsAh_UApTGs1cw6y1X@*-27t#x2?y2bwoZ%
+*Q#Z4Q21q*jP-&@OV}O0=8f6-8?OT&UP4x(D&>)q0vZb^|9f$T20amLuo!E`e`TVV<!y=k@6By@1h!v
+i>?fKBs?|y5_{rB>XnY=DBe!^D{_Ko)b@dre$uv#U3YHe|Y2!_@2Z+u6C%ojf?G~JIBsF)3|SY&X|4J
+i96@U<^umgo##&VG@Y@z682<w9Xps3kbA4JPsq7-%T~`twQfz#JI)FHex}-+yWz{m@N3+sNLO|+-^IO
+Oq+FaxCKu)zQ77i&8nmn<>jT}=EIfMjoN7PRQDT}}t2TDuy7B9Aj`c@(4=1cAy#TnN(<t08o>S}6HmE
+pLuJydCpL_r24y~2vD2XPHANEp@{gV;t(Zqp=b)#uH*OXo2yoWS3@8K@d$h8<%ts;|g+r!rwTYXWr=A
+838V)X>?vdDWazoq66Gu0kTmxL&J4medg6iz=)Q|p*-Mn3MpbWnE=>6*gjKholB;XZjzt%c)U9cQHZq
+zmnUb5HYIJN9r7T924=F2Fe`*U53rp<B3~_odH$d-BK)C-?S`?h_Q;#QpTX{`DH_+~1k=VNXIHJHP)(
+4SkbMm5PU4>&|sdkEg}u`O!4mE3TIoIi%4mh~Z!6+()yXq#5h_#7ueqN%1Lp7QCYK`EzQ0GRxgzsec`
+==Q(FlU-e8EaNvG|)P41p;`ph_Y8|x)cz>cl`MM#>gK8fl$GT5pY)w4Zl~aGye)3$m*m`xI*EsN)if_
+)Oja{o`-A|D48G}Tl9f5)9O9A@)KbWlc-T5Q?j?F!^83Tpp8C&OHWo)f-Xe&LCk!r|?ANRMkZlBSBd%
+pAIzD0AcfInCQIV`TUi{q77)EUo~eQkGeF1#PQf^FjliwytQS+<S+S+TW)JTHvxglGBKMdJSa<Im%Zo
+ii!VQ3dP;7T7;FVN=F#2kcEE?)UV=){~AIpySYFBjW!jxi9_!#p67AcF_-ji<fgu5Hn9bG&Q&vahXTh
+8@U&6`Yhw*fEzl$X~Wj-97ErZ*r#DbDPxoz#OIWYe(<LPvP1Ye*NNJmcggQE^Sdnh7n=FG&b>u<Njh&
+f&okWhR`kF-@qGMwh7<1t8!`3FFzEP}c~<N&<oLhv3qx=G!Y$fg1YPNe-E&s0_k5>4J)h>DlcHs()Ah
+?e%{J%IcGJJxYwBG!?mj&f?u+hTJQ5v~w)5@ixb@r6&vL(Kwq=*tR+H8|^N};iKbS4TXZ}s=x(t|HPu
+=Dg-NZANKTYOOTbB?2^s`y)D;33;+*}j5bf{9DC*xbSZ0V5ACF)i~2b_A)IJr&jebdb|O3`+^pZQ&Mc
+dE2|GbG+$1kStM$|s$FR-MV!Ub*xb_u{)_+0tV!ZR(1uiluE0=GtfI!INBj*il(D^cei+Gxr<c?$F&s
+Zph}xTH9x^FSgoT7d7BMI>Yr_*UU@cHSt<zSMxmO9u6kFzr7OO-9MT8$xZbggq_KEh+@M&ytMsr{xK(
+f!8?xR9~;az!e@{s!<>_H+f2D8dSMITeGhfxH^kb<??@HLz4DwmQAYZbo^H+Ec4jhsh>Ot!eYTmQFK~
+a1B)nS=I;?cZb^3jrI~-frt<72#Ti4CD9e+Q2k#)T{_kDN5jtlU9gSj5^Wys%Y$l)o-BliMTHaM~U|7
+grP%9qTThjPn32zH~6Tky-)#evwlg3@*Y_gTPut~;(LzV~`eo)3>}Go&5Y+tMzaM%{T9nA(3YFLbqew
+jt9TeNCNh#yu*o%T0!F+*hW)`bCbpkJ%*AO}Sa2*@COIv>}cG_Q*Mn70-CIob@f7V~F>y(J15X69eg@
+JJ(@E4&Zt)Pn=_{?{O$!lXEw{72^0M#jkVbzJOVu!28cahCY)bA~_Bt+)*eRTOse&@LA_q=yI&D959N
+c4Ne={$FdOjRJ+Br&t$1RaeE=RTpxSXrS@BHLEN$3yyx1;YV)3JNnGar1zVo4z=66<X{jm3kK+QpxIR
+Bc`Kx|hH{-{+rV7_O{Mb$cxVBGG>qn2KSjtPWl$T;DFC|_c*Zg*7w$yZIs(n^^aeY2h^*MI}X7>~oD^
+}rM9e&(TAuzfhhuUwAXY2BeoV|Mai=WA2zo5t=jT6(+mNU&~LDz4Z`#mS?`v?lr^CkSgjNd=tw*$YO`
+0c{4TNgbC@H69q9b%yow!{Z`7NgI-@x4EG_-7lVdw=*AJiBL=rp^;G_Xyb`W{b$!ICu0MxN$Hj!?8U?
+Vm2~W*}XCQlvwvAvHBB)=?2U+XG={r;5BHj70#=V?s01FXH_||b%Dvpv4&+og)IcXi06--@Zx&GV%I+
+d9n3S#xF^z7&Na*HDV2Q=+{aiKjhCi&%=oBX+NK<*P4&~d0E6e!1>Sh66gsnv`^|j?_wBko=gs%JN9_
++jF1_AU7E2HP7%V}W-ETuzZBuI`4!%z`YOqgC+x&*7l)8y}G?#cGua{@%wW_q9c?!os3fsLi<kWh~c;
+3r^Qxse4<OL49)8yD;un2e%&U`s<SjlQ&j@&~r)6=Lm?nT>-oj(UZe(4La9f6ddGQMMbC(d>i3pQQ^U
+AS-f@&~k9AMgT<mEdppXU+Oq>rQ{a1?A@3I6fvyJT0QpKCN1=HC~~MV%E1F`Iv@zJ1q2LnG?~_S_ab{
+<=$#4MjiKkKfc|LZ!du^Uh_TaG11u8*!`E^-pRdt*XXiea%ZKv=GEysyr&%Rxi?wS=k!MgCg+DZ9#Dk
+m{0z~?bETh4SGt%sAd;^3MzY3z@qL(L@%gCl>D!VfiaS%(y6{2J|4YueUAgKt6`LbI&bez2;&8NuR$U
+A7j61@<eHLO7JP-1$NKLNE*s(a%;C@rx9E+&}A9mq8&kBu3wJ!G8#A0XSNc;2V-&b@MnsNINOna0Ae{
+H>U%v$^tM^G=u@7DsCZIkla2=lazA9AGqny${}m2>8K-V599W|xqApm81X8P0EWi7@B5#?OVz3H@rO>
+hn6!{uKD2U6Ot|A%6d6y6g|kp>OKq-m%m>ux|m@?@PvT5%}91jUHfG4S>x&)Lm|~+^-^ktejoxaxcmn
+)vs_Qp`U-;IT|~%3mif2xx3dP4ltgta)|C*5l<L)QM?(?&)d~L?67OyW8+(A$UJAd=2h@45B}6=kS5k
+Qa$~yMqkwx(Y?Co#o{wj>F>fs2?~o7vRI&1tazp=`ul6ik!@iU+8^eLOqX&pviuBELM`i7f^w{2JhZ5
+=+*Wb@W*9N|6$aQfni~BDBY_@36^u+f?<z8Otrr-AgwWs@m*#2JB)#51;Y5As*V>K-AI#cF9nEp=td|
+Ap5#mgsuubZIkJCc?CB+3rO%bsnPJu^w!6ZlUd>X$Q+3Ca}b_p(2y$gzEo?DvVyyTp}yP;*~D_{YItq
+?vsK;QO0A7alOSLly|9!I}@g=v1UHzo_<nQ0LB14gF`Dxi<xTO4a{0HS~9O)XyeLUeJ}iQkM@R-32|T
+ZNThDx}f&>M=aqCok~;uhwpoUb^cwN;`eXT)IO`c|CQy;?L<E!S^wGjSJ;0x5uLaPP)>;JDLPF$t#`E
+T;r<L``_a<Pa|=cAiw<{NK$H9EN!r!pUBIN>Vuzv~;SPXy&g(_C`+8BEtY41smLl&ela3W89k(Q*<K9
+0;cPG+uH`2AIOl^B52_1JN(D92V9Ur#P@$dheblfNDIMz>cK4nC*g(3GU;TpeMje2=3E_Wy3(vYV5EG
+B9{67G}l4)<dTaBGvmJ$z;SK4^qb-6!J~?k~vmBh~rXXR}eCWMy5KP*y4XP?-M7<ms<XNPl$#ZqFyd>
++x9%rVIA%SzN33IS^}zbJPRb+V(vSx>3gUSL}x@g1@mD@>*{CG~CDG0(_Z1o6FY<U1zBNk05_<a7|XL
+nrrEwW61ps0+7LXJh$G`PAH3Bk$cQFoBLibJ9$vohTeSW;XRb2&!FxI40m*!XD$sSoVmpEd3L)NO}<w
+|vVET!t8%|*^8KrTy#=se7(LHP#TASx*w4dsggrVgk#xO%Y;ORyU(?g(_|=G8+2K?n_mT*EB##ci<9>
+0}882`Tz*9Gt4Wx(?uEkUBfah6s1Q@Re<aq-e>y_tfKS#fR1$_RaoL3U&K1Xg@w`v(r9NWX#A)xyIM$
+e@*?W8=HQrd)q6gjt-`^>khv)a#!)|BAAI{hP69^iAlX9v%f-p(`RD>8y#jLLDL9hx>tz3a~i{ypEN#
+Pi7WI8Qms0&YXDEp%z3EU_=&Zd2!+0M;~)sm0E0i=9iO{LCMW?)!V{@AaZJHige$^87UVI*WNO#acP<
+yKG=8e8gIHF5KW;TNlp@<vPj1$81HXH;Le>$KcPwuj{*61e@3&JXOwlE@t2I=sBr?shj6GCd?c5eL<Z
+k(AY;G(3TbAIq9w+8ew07vlg+2s&7Sn{7cn8HFk!Hc~(lckLSq9Z~Juf92ND=DzA(!wSCj2A4%SMTNN
+DkkDNmNDD!fh54u36)n)|gU#c>7>zE(+C+m*Mm?c*AQNEaGZ|r-2JfF2KNO=p#<7KYBGS5z}X^pMLGM
+^tX*JJVfeP(}EtR4J>zEL<H2e0ROL1+(*0bN%g+v7t#{IFThr*w6e1L67;&gEkt`TdS~9FaAo#(7dqA
+Ij-kuJ%DR_t{E3|HnDSSn1g^Wg~rg&$UKlpV_9I1>T@A+p#d`;jOlmGkivs6NAUT#PTUdBir@@Ej7q}
+v?p;t>!uCEsjik2M+;Kr*z$aNzR2_}x!yP5Xw2t%Xa;a-n!J(ccb1Ea##VXW!SqGkZ<}qh3oxFYm-<N
+6E22!E1807tOfyEVnl7^VoMQPF%d-l3J}u9N+9Agy*US5W90O{G4%sgD)_C#D*8($=$8EOIfo!EGpLU
+7%gJ@f%PfqLm(GGG#5Q68p?{A=x`d!)Rqubm(XFbB$k^P{D@Jt)CAYYz28{z)Qa*tu?+8?{9Ymbc6*O
+CY496_mvOg<>SsWx#MZJV;set(Wl1dxvFg9rXaFZ#LMM{)dlrEIr%Ocw3V&Sl}{NLwW5)O$8oYujfur
+-+5*#U@?tDb9LuPjSk_X?vXS_nlGWlX9+A(;T&jfaY1`?6k?bJ)GwQoBdqXIaioAIB}l7($^K?czw+M
+H0>%T?zNP)$}G!i%CcKa;rY7(W5g9WYW4~9EOP6(kA$C@5=>_I66bA{yUcjPoQuJE7xk|AdBYR$UpyA
+h0uxS?1<tJ#!Wlom{}S}l0OTbDdSOAj=>8?>mu^FREay|EKilOnB5lwSw=bYxz_ZJU+-lx`1lO0ejG=
+uzlU2(*mOZj;7v%7q%V;^_ZQZrUrDcE1ZErd8QTR;<_3WX!;Hz$)vCbIvn;tdhPn-1bPSMUiw6|n2)<
+>+VsW|qZENOm#G&!lF`^%HE+lb?vXairGl-tI*;dR@jP^UI&)ITC#1MrW)lWv|x^6KZsFwatEpE2_e!
+1iuOz1+}&%c1{-w7IDBf@k-vK;4dMBEoe1&UDpCbB1yFHAnZP;d^g^2*O6n@AJ*HOh;HQz+l?>NLOX1
+Npq+)0i>zYoDx>og5Eu`G-)moG2`nA&sj)5E*76>$FX7VkG$U81D^Yj{u(yv7L?my^0NW_{4#L(=z^a
+qex``y<r(6sIy_gUh`I=3u1lc*Flc)}<hi|29Os-Xjt2##UYR~r4;s3V_v_Fn{^p9vV&sk4GukrF@nf
+0uHB}bpoVt<TkFr04v<J1RLwsI=`+Du;m;2t1)?Kn?gf8MYY)g~lW2elqoEEunZ*J&%@SZSxm7f*4Iy
+U!@`*DG`a$X_#5L10J(l$&q=GRYJLC)#Vu}?pyZ>iV%pl_vrV(PX5_$l;f=)Y8%I&PNKadE!XoAj3ZC
+phK)xKjV_Q}%4X6L>lEMVHg5aI?;*7%ewd?>cp4Y`Jm|()Y*xCzd^Qg=POZ<`3+5wz`8yc^=w1dnC3W
+izUXAb^N7@tDd8;`a)E#3r=<(;n&_C`^~DqSyr~D#`gvW)ZXVyJWBU`&Ag^xR_|XNiNi^DjvHxk@HF)
+6EKxhrdEzI5@472D@J#do`}L}zcVlOsbA4YuzC90|0+mzbS%H+3?o{}5c=lhhkIrctqyH@RA^iF?H$?
+sgd797IBl7vR8zPVK`8D$yzIX?p-9kN2G9r)gc~X4NRI>WfhZ7Yuf|{@gAD^T4E1Bs0#{u}gl8+Z}j#
+NQcrKYJl!YOK8V-(JjByg<t;XKXkbi@jP@w(cp{%kCkVVmSUjl$7$(Z}y2?Xp?+{~s8)k967CeWV9Vy
+}6>)KYkzSvP*h=ob}5C$@h_tm49W9I>(V^Wq4%Vz28|>5v~%>B|Kxg9(itqEcJ*fOY=3cqzCVvVt-9J
+VxKN^Pgd#wiTzn`nd4e-%X3f?$8UaU+D<J*--zcme3t9%P`6{i_m?`)U=raq19I(5&R4kafLpBOScMb
+1j{1Ua@(K92O<WI-a$cJZdzmVN#kQWZyP*ePh3@J_``A85)VhDwu=QCnZOId`JKb7O*&m@(Hy{mZ*zq
+0FIG}qLUCIi~;63}eI0n=4uPUaz8hMJ5hv^6Kjks+AJ_jpB<7(*VS8dKvpwiq+Zl3Cg2pkqG>6-=~)Y
+W@)o>bufXe;IT*p>ME!0*J$>e!rU_9tpBHQWQ@ODMAqWpf?!dX#P5lZ0^=$7!5MyTKuj9{}#e?~mN`g
+!}z)pKhet3R;qmQ$WWJpp)DK1u!?8^>ONI4F~hH{EwP*3EZw1W~|tkJM+&~FRnx3UOpZzcfF45OS*gg
+5uvVbZN+^J+&55DV^%K~=Fa4PJ(P>3+EgEGNifI6_cz=hhkLJbo+9^~kaf+Gds1F+*7b!yM0fu}o3@n
+mTbgtcNjAr&0lr3qQ2kRJKcSp1lyiIXd^{ho%G|4dz$S{{Z)rcD6=Er5Elcjx3HZA;=aTmZf4>})evf
+IhxIXq{Xj^aE@>WbVPbV=Sd^0(|k#xLkg7(KgCHfF=qWx_#+ux8T+F#J+_&|6YX!&VP<b0JnF-iOT34
+HReBR|Jh7u$>`Z<>&E0thpEp0SlaZvZ^t-XsNpWx!r^qOCQfojn7Y^Z%<@*%j@O^K@E;@@JTjd0x72=
+0@VtnuFNmuxLCo3D+~CaSi+HAcyzTwx8;#Y1UoqPo?AAw&{(JW#Af`uF`CqzVcIy>kiLsJk9TCW}10t
+uH<}&<~{Qo=kopGdFuV1c`H95-@m_cZ5rRd-+cf6l^>Pwiy9wu^L>%|zG&rb^8NhA(=NWBZ@!;TxySn
+jjdSJu1?Kw&E0@Xl3mexu`F^4Ke&NdN<@?2ruyuI9*nGcu<x=^+r15kL-<O#0OIA`=n=8v2dG2%bx-#
+{?vTWsi`Tj$VYaM+5A@lu*R&xGC^S0|6AG4D_*O~OWZly>1N82O~kHDX-a`E1|ejD2@-urdu3XYAt-d
+1TIV=O+R(h!Cd?>T40dF3COR?P{euHgJj{h=D3w^4ms@kpizzlNCJ)Crt(;ZIR>1RK7ft)va1?r1Reh
+FrJ5O{|o9W*c<WZ^cTs1+D|4o_rB9G|QAX?jZwTyUFbmL9Q+IoBPhFvvXT&n1|`BT;e$8>zF)G)@br*
+Y3mu^F3@<^nF#;;@70_wqzl&KJM%F;_t1GUYrE8ww~y+{7ojKfX8x~y{;zz-<dgX(W!`?@DUEYXl%0z
+vv2&LS^Q4`l?3QZNd@;Ruw>*nZ?U}tD&*$YHPn6SaY3CjiN=|1&PJe0Ixvx)P=eC<RA~4R*an12G-<L
+<?cJ6Kww{u%z=cZch+}9?sbK~JpZ0C}sm3HpquydDeQzx`@iTP-sC$e+&&(kXA1UdiZmIsWJfpZU>bT
+zDh#v@$o=`(RI%&G&TaW3bn-2z_SsQj0`n%Zm6c~)P^zH~R9kD|RB!R>M{{_TL{&lJJ@2LCh3`qAES%
+QK)3^s=w`kX_CjckYmTuKKby5&m^lu2Jy~SkpaarfZRBafg%boB10{dSSxF-MDkxPgv8LaINRNC))qF
+JY)98@I9R^!sc25A7U%Hj)?QAxt`|_oXc#^2e}$>pSBM#?G^EJG7HVK3#X3Uv<q?X{!%S9I6c?cIg{(
+0?*Hs?(cGD`ulJ13GZ;aS)AGEZonyX1-hOH+r^hTiMb4egi=83l%Q4ra@c!o0YThLK1G~-iKd`{4eMR
+;c?v&>WdyGhOzi8Y(A@VFx#v?yHt=1)Rp5!+za0!!hS^RPhks5nAZOfHo53w^m`(PjZ32Tft0meD*y~
+Z;=0Jmo(TGs%&^-i$<if2Z3dRl7Mfj(85)6Fw76ZZ&t*zEuR+30y76Q6T^nP-MK8>2iTzsM)@f#tE@M
+RU_0`B1JAIc3hp;@P|O%e=tBsm)o$w!r&!9(lf(`>VR%#{TsVJ#XkD*EZm{1~#Y*dCMC_V-M^|XNm}x
+mk7CEP=hYYE^^$M^CGo8dA5r5;mvZYHQA>l&zI(WzFaN0jd?iti23~HIm@GGEZ2%4$5=S8i1Up}XU@~
+%_?46M49vQ*UQSm_4P|YW=3K|Ig)_@~%2pMrzU@vKZ-_D_lWC9m21Ob7kQi8|aI4qrF3WXjNS7|-b~*
+mCv(Glew~ymxNXK%RmUD24Kc8c8Io^8^G+K5kT9?K)A1g<$|GRc+mFAJ-6r^vJEuN=d&sp(K=VJe<{7
+xU`ce;h&urcq(?-a%F7_Z6qZE57U(L{dt!Jj~!Zsm6q`F7(Ne#grpzXK+}tK$4_DtiZhS0?bg-l6#Ib
+trzPOMa)1;Wy9b<N1Cpm-B(UQ0~C{MH9<no<Z=>hdkATN(KgR>nWR$=Y~JVWFq|$^4@z+lx49l6Uan?
+DHH6EWSQv+GLasaiKb0%B@=Vsw8}*KJIRF1<JZ+3nfxYC?K{cFyY)|V4c4$c_udw|Y_rSr^XlbzSWC@
+Xq1Iqgb`sB{ohi?wo%u-hD?MdJX`uO${I+cFU4u5?AcmKo2j9rQW1PRMIf6yAMeWt>%Rf3;TBM1R2E6
+OY1pRh?{PJV;^RBEa<$e*~qXV3GReU$+fFey7@}(gU;FR11++ypb*ssg|nf;vCs-?>{QkyETZetu!1=
+_h>=DH8?`6J-xdd@j@!9Pbj;@<#$!|?}M2k^HeL+$Z9?%V&v-nYlaRbBh<a}JMrKoVehWTF{J8ik3`n
+*<1`l|$kKf~_}zR%`DKG1oeP?XQ@qK}~?9wv(W3#-yc^+mc5gFlwunXr|f*v|1u+4QSN90*TfE5;f+<
+Bq8UwzI&g;JQ$+Azu)h_-yidtnRE7Y?Y-AtYwxwbi^h6Y@nyZ(gZxTD88FReal5>9=g+A<tK^Kb!?X{
+5NaGDZ<wHsaxBtuheOvhv8~6K~um^lb^4433fkJgTSV}Eh<EZGRy1?hFPpXAZ;`2CLHYK&$OC^)D`lP
+Tqn0)<z{=R-n-_MMFeP~SVmB+?{dm3=#pN);!*JHonzOFEw0VeOIJe00-zh3_P^o{e&8N#N|nL5b#{p
+84f|IZ=qcxfzj-$zW<w9tJYI62PJK@rOl`~Gu!`agt}ar5C|tjNjt{b=jrMdRMaIY@LoNc6h-A+;Yg`
+)|FTpNG_wEHT@CSwWf|r2ZeuWR*Soy15ecBHCpT%}O7vA4U9V%cY6i%BbH@IKpZ6UA_EAbefTHY`b|T
+%bh#Zv?xo{IuY|3c17AQx#M<PcMb8vHm<=c>~2#fmcL3b<3YU)-bSKDKb3WYXo<5{$Sv=jk6+ZjPO5M
+u;l8`EJa@j^4ms+lrl2kJt0Ina-|=)7c$t2~|M5;L*RTt|6?y~xej&IQ;%?CS4|-mr_tiW*aa-ne7C_
+(8Z>&p_QhcYC6ff2(*64PcV<kgkkNvJ)eIOHaPRIQ5Q(BZ&M)l}6^~+G^Tw2p-NngP`{C6G|`#8@J9T
+9j;GPil*`Hj4w8P88^9@qfm`HzL<hrTySexCOj;^w3|2d1;F+hg=L@V=U9K6e#bVn*}%n(vPH4A8ve_
+AMI_uej&{?BjXAmasyMTQ_i#a8EQCOw0GUmCUoA#s~hH+>S+>$VUdwkv@^G2EIY`AKJAzCpXq)O`_kh
+^$}&pg_pTXU^*LR`W-4T0qQJCH$TurI{gsspEk*C4IMl5XOnp}e<RIjv=_8FOzY|A=ZpIfDQ2(mA5C-
+Kbzb<h7IS$?Ed;h=JJIF{$qGYCx_5*=nw&7Qp2mh_uUCsbczK@i<p-WQ@$r#EEL=8N8X+5)C3ABPaIG
+l)2<<UNlxG9U(A>@gbBx-I80p!xZ<f%$>5|g<KAB7Vq+RH|yuHuT90ksLBuyPQ(Vi#H1=sk`bUFjW9s
+g~*{eh!XU|!mEKZ}P%4AW$!#eLf;CTx-|`aKKsG@ldeb4y71&O-*T`s3&9<B{jLdpNJ+eUJox0M29i*
+#1hbZ--2Dg&LqeveO0}3ijRdRMKDDENb1B-)^*nk8U`~?;ttv>U=4;89YC&dyD-5%~ONlqx^J9;qktw
+)4XW>o;nKM1-2m$6MF_aHOYR39mIb&vW!Lk^9OryzXkse*ZJ$Wm>zVER;Q_tIkTp3+qi!DXlW`7v{QP
+F57rfrS59l|mN6}F?7^O>I{oL#G3Z0O-qz`Z%!Bz~KyAj@TuJhnh1z}9w8ruuL)W4<`5$nN?xQv>%(8
+5wwgsFtpO(k6V?2J`A;`Vc7q||wLMM&cgY=Di2H;TOPN+(1OolwBN&@#GlfJVx(P!9$Lf3InS%_6=(w
+`f5ZQF6)co9p!H;n}xW--S_ef9+((0oMvd4Ar+pIy8FaUbye0ZNZFXj41vU{Bt_&qK27?;EvGX9BZn3
+aw@8=isQYC!JJY2syVHpf;^%!Z!l#)Bd5gz;^Ubl3jmJAH+*Unl={1WQZ159A^$TqCe(HRn6*A+#mK)
+Sq(M0qpP?b)U;zuG_5k~{cnUFDeUe13jBGyS`i;|17guVByG!~vfrV4wokc^<7qDBn48d>O?>Xd_ZoK
+$Tpy6xZoIS6JO3$;Gr{ASuS%yqjeesHq<7O?MIMY%*LkfIXL(Pa4eoK#up2_@cZkM&mdrZ&nM>kz0p6
+Z0(H=>+LCh4q`{__V^R=_$EXYIOq+|NR=^AeL%V}Gj4%(KZ|7o#}eI%3hvt?=9xDDWmrt)Vb;ZM~rm-
+u)Lx+`g)BiXn^Hu-j)7j%!&=ioFEQ+<L>Fh7r?dVmLGp*k{YZPZY^ON-+?*|1TS9Fy8X(~HghRCm9`@
+6CC8(dX11ah`N4i`ulTgJ@k<p1uwJ@1eBRzGeHUeG4@$&zKj{aGxe^*NVt?P41tLGSZ7PJ%iNdGwWr~
+bdu?Si2=D}lyo21FLctnYL-<Vzr0#9zm_@gwN~)Cszh4ziEQ^lIb(#GAseu_%+i;5|15(h&(K_{qn3U
+@I4FDGzFysPoaB0x$9??b*fU*mtP-+yUj6D(nKhM{h`G@>pxbNnxaSJnP3!sTY?>pcF~Kt&-;lU`fcm
+7YD?NwwJnKlWfL$wpz9RU1jZOFs@p7nLC`TTb%Yt<ocorlR?)FcyHJgb)n#bCDxW7BS8>VL^W6OIg#>
+_p2O`RKej2gGa<>f4-_72T0?f^|z5Wg{K$IGSlz~}o4ndmL#j{#lgAbGWOlRVMavvlh8W{YHb&8fEoF
+<p%^5g!WQ)gg9aNY8!#X^gCr^|iTrzR$xIh_q(`4dwaQ@NcR38g9eBWE%4{lCFKXIIs0Cl=S|D*azc`
+Z#&fw8xGKucveOzUjx4K9NjNBlwa`rc3dgy>%P*1y08|P>2-1JkBGXAIwEabF0>y4ql5H4es&^DR~fz
+oPBE9RBK<~jF3BWWfyxBV*QgTf1kTr4CEj~EwFP(%g>q<Hrt`M=uTldaDKotPRP5dll?>8()4hjDo&s
+jJj)%i>Of!|D1F#V=;v<XzTafc=Gv|S!d5wIS9|EU(^1UnS_^r4~(6i|(F@Dr9*r=R4FKC()W&8|Z<X
+CZrOLNr}V%t5r{|&FNTd!}B)0NY)5&b+r?mrn)pG~hX#R;E}IHSI9Q<!agxZhetebUvUzO1Xq>!Z0>{
+>Oi%zNQP+7ry@rnqEDA4lZbWwFmWfQN6#UdLifJh1EOm`_6TB_@Klab?-3gHvZzBQGe9<&>{OC?jZ!d
+uMVHTgQ6`e>9-s7w%i=0E#l5V%*U|y6py#ZY4D}!{xM&0eXaO%c>9{ZJifjf<%#R-mh=Dj*H?<MzOw#
+rtgk5Zp<DFv<oFnTS<DAuhw1Y$H_AK&elgmIxoE`pTaYIFy&}h-^o`BV?pYqlx3HHjDUR{n7}MCdTr!
+QoSM$h*M_S?YTlO#;h2FPAmnSD{H^0-AxS!GH6x#c-FXqu6y_)v_D$-$yId}5?9p`?!&eE{nF>3ftO@
+>PwiDwEOV{Zz{iX=1shV;r+^nW+?;W_#|o6dYahi>9$X)K27Idwz8{Qj!ZQrdf=k9JIDf$UU)HDk(4<
+nd;ZhEbY=fAG7f`Bee~AgP_|F!E=1GY@2-k{xm5e9Op(a~b@0yuWa?Geza{AYzZ9eNT;vbF<0guST_J
+4{ZCp)>0Ekx}<LBn-jx2bM$s+Q@ephn;pxNq0>MoE{e6^gBU$#`PO`wh36?m%s}La-L2Wk8!G`<A2_4
+HN`(JE$C<%dIqEBsbR1nt#|fRneZiB>^uLkvJotCv*Dyh!;N$Z<-CslRi$mDvUl01gKaq5(4)~o7{?K
+>d6jSrFq*KEmZ#(WXsqA(d8!v3jX<nN{`dT7Q>?_U(_pw_Sg|-)Z59|oM)c+3Z3+cRpCss1g6U0Z_FJ
+*y_xm5lY^m{73Be}FaodtGnV4j_d<k_){cs#AuZL}8yQx5(E*NmaBuTB^@<IIxdGa7zguvK0u{Jd~Rr
+)hEy><ps$dUf)<D;l44fyL{eq53kD+;+pBITH7~I?Wh6L4&LqL4yI((_ELU9X82Y23tk=T>^7x9z8ET
+qO~9%2F{;8ARUa})#5BE8s3jC$8kS!1Bc0Embp#tczW0cgr~otT``YytYed)zf*Nyv`-TlgyZ$hvvQ1
+g9<P_$yfT&B!t(o&P(OfB`(p5kHrTgD)Hhxx)-~jH<Nx$Hjvo#m{%@V5bwz!$W;Z4aI#?~C{c2dpIzY
+oPxsTTq#8L)cBi8n2DhqRl_{vruJ5%O(2%U~3=5wSn=*++Z7wc!b;8z{zgl#xqLwfn#?&TrYVai}W)4
+wy1V;be}l13di${*r)6uDow;~Yw?skd@yO{K07KB3u(Z2xn#zHrag70W80CEi<sy)T45*}Bhd)8Dj~T
+B3)GXknI87F3T}++Lj)LyKI_jS5?YbZaRc^a9CB`XKyFNRQr5yc_a=2KA|Z{qj-jf2Yw`{5N!EM!fSw
+T1(H;v*7$o37daB&LGvXMHc=aG+#N6M07bJ+<pN5m1YK89e&0Gto~0;4;TAzmdx?TE>qXQ=NR$M5s#$
+kVTs>A7wywyLH=E;%bLn67gh;-bLjmVaLQ;e1rJ=9MLG~YJC0{mW}=CCrf}Qz#`38Q*gL|H>stD3pwD
+&Oe_yR1QKmSLC{tm7lI!@2RM!&&9}ZRtyqPYuh((JtS;sSaY}zEL4tL~^LJ?!#Q7YA~u&~NM%Pen|e9
+;2jfv%FLFW`1zvi+VNaqtzhFIYhTFU6e#eSb5K<y`{1&^Xhg8WUTH_HKz`3vrkKLxyr@EVx4NOB?YX#
+Kv<hlj?vo=GaKzXy2ofXqQjozNHR5cBW%csvCq2nVfzP_Q+Lo+5(g_6yIj&@rmP-?~%CwTJi$ON*_~w
+OY3bMNAm~xEu}6%EJw7df$EOc^YFVwIZ2e2-e!l~xQbQfoAoo4RkDr01C5I)U;DJS)<h|>dFX_e*KQ`
++kg>W>$=!;(bd0zAa&?VEAManm50;*nm{@M|>EInr2hFuX;=8a5iL~#4OeGCo<GF+D@iy<eX>4oec`a
+|Foq1pr#_c5L1?vD#L)Ms9nQP{8J0`S&mnRi@cIxH*azvc@x#TGeN~OlWWL-{{ii<qL-^=Fx>3Eu{3(
+Rt3pV>&$RHUCj*t}aQO;tdnG}9LBqkMj%k-Mgv*9)JUO|rSUB&40DQ7!M}N>=#NxZR4ej)It#1Nyxse
+A6!>UOhOQ`TQHy!U5Wwss22iH)P<RkZ2e4Z;j=L`F){{+a)iyv#pHQvzPlG-sBr`=zH_AslMR4w>l&6
+<b2?_4QV6`5bt%_nNRS?mnX=9E`Ba$*5xn9xF2Sm#J0jV!BnCK{M4Vn$!x3ND&!l(2QyOMiuAv~_$-h
+4A>uP%rv`Xi(e{wGR*_6lcs82+Gr3=4{8@oZ4WFT^r5w|>^WTzak6ViS4fvN{8-U*qaM3tFZ?cU0@tC
+Hmz7nGO&uIQNEM)=6B-1~q{>XlPbY|SYK7ezeEc#aI^HUvXAogD@um4PtPMJifM(U60obXLDoeTOVkq
+(f@`%^6Zl2q!?4=69{^q&c@bL_zv1Rsab7tJ%jgYml`Kjt1iqwfHGYdg5_d`u3fThpbUp_l0$$&kR_8
+oE@(=Cx)s-(mQSUBTd!|FpR{%>#U-Lx)NJ+9G_)NR|x%Ptj;!S%=~qqW{^~iRaZgE3234k<a|F!oP_J
+2EIe<;qWe;K}(*&XGK{%xDVXKbADa^>5LcW_}-g%pCkRGbUBjB9M~mywCne;=qH{H&7l4}M8DkJ?@h@
+uGgX{<Q@?<}EBpe@-bL^^OQ$(spayc!a4dlUo2Lfm8^7nPfy<5Gd1_#;@p}&S+xVTM2Id&QzpMsk8NZ
+9E|HkjZ;=o1poBKY8`02sUj?1}+bvc)wU8x0q^dir7z-t<54d8wpYoeCsxUnAa{PWht`%~H0Ewm<9ag
+37`FA11Ya9k$n)te*n$4NkaYx`r1eb9lh$E`gpbZg*;0EZH|`J`|5!OjKgV1Krm(o|_$u2e5%p(g_(5
+8l5`GB3`5zkgO>RPLvDuy+QJTz?imTr5v7r*GX^VM}?M$A-0euhB%FKT;mi*4VH!q_=rrb(tuHH-4Mr
+y@%76+W%Ig-Y?Mc266x4HO|OY+V9b)M!iqBL!Kj@(&*Fu0g)c>`}IDR>wWrfdY8=ac2m4x(fg#A(^q;
+{$hW8Uc(-P~Pd}tQ&+20pI!;BOO~e!bBIA_u1;*);h;dpRWt=Y7`*c^xIAuhPlPzML-aaq#e0`E}iZ(
+`J{*Ji28l2_vp5c1&Tg)T#e(Ct19Lw<qjqm@vb=-%oXQ=K-f7MWa^DO)_b^2hP{N@be12iVP9+Su8{e
+<0jh0xp4$ewXQ?qlp2>_1ba##Y`h$>hPg3hwU4@B3KTecxu>_Z|5pc;9#bv?%v|Ed0Lj=@S>e?=$wEf
+q1E-n8r7gvA}HI{t)S3I~K%N5Olq8`k#Fko<36UF>rqPxrLc^zGD`4xNe#Q&zd>*VSO13Vo=}xcdZ5c
+h4c4q<=KhQ;Vm2=2K-BrF7+5V^`OVa8Eh+bBG`RoKGVo$+w7mJ0n$fzuM+m3z+SA+<UC(3EQy<Fi$4$
+Rl+uCM9!nQ-zEJ;cGs#XdtnN|nm#Ea1ag0QICbMH7l1vT^Twr!(5v}J~*;eGiyw0Y4dtb^PIV|CvtE&
+)LW0~}909cn(fpZni4>~d`(<mo}%GrKK%PTq&ZX38C_I1>M$6$=^cRo>m14j4`?w4xN|HW~CxWltqJ?
+VVMFa|%jsAn)Huno}TBXHc5MO-i7IMqCkjsHRQx4^3hX2pyXLD~Md?+d@(xqQrGyofid{Y~s&IW%VI4
+}24L=rN6e%dSlo`sO?uuL^;k=_5V7?pvf|#qfA%st>k4CK@|a4BHJmQ^%N6w@>DHSI2&CSI=~?P`qWE
+_v3w9%gN(GI;r&SKdk#(q(tI>|1peStEmn5a?C?k2;E)8V`Dy?qkKp*H*C5-qCJ>&(7q3-E{qdw;ZgV
+N7J+}y?Xk~kc}9OgLyU0=_SsMy9KTf8eMXzKA1_irUPeE3Kb5b)FZ`L`F!YEpxkvKyJ)8D%#Cm{?qVM
+BRn~s(G%<W5j^sENF?$=WU7R!V<qS4A5`~31~p+zt60{7G!kMAXU2g~3O&ChlU_tIL$oB>8P?y3VchY
+noCD$XeJ&d%*^_Pc2=xi4o)8m%Ee)%#EgZBlgFJVWDzv&@pf>VC(V<Jbz~ul{W$k1KYkrmz6c4nD-$o
+HE^eSjq5`-r^Hj)hQgy{x<@PF&FLm8I`poLEJm6y@Yhp6xP`@lckUxTkfo$QBhVbC0Q9ObR@9C$51aD
+eGc*BVbg~;z~-k%X65#aSxTv6Mn(R`ENQf%v9F$<FVDI0vl(&3E2$q3QhJ=3?xS~(H`LDxlG<9KyJyF
+VvhD|ln}vC3ZsyS%<oG>UQ>L{-AIO%v3bPeahWQQkvC=r!DWhy@pbux0-=ej`-$~M@x%A#O=cQKohRy
+9}Nj3Dn{6pd6RU)NXfm2vAjV*&sp!{W)f<9!OyS5)Tfjh^v{5zD<MTd!=pw%?e_jtTm;)}I$Z2!?2jp
+cV!Tio#7o(|vbL_R+rJn1OFKH4Cq^EuQ;_4N$1B<Ln?#Lgr7R7=A4+jZ<<0qHbJu49e@wEYdfCTw~vd
+XjH?w3bzibDRCNPdpXN<Kotp)Xu1=O@6%9OyhxaK>NGR%!4^#mNI%xim4YEdd?m0R(!iCU;8s|yDOFz
+F5fZr*fz>Dq9k~&z{p<P*jJLcuNA)NmJaha6Sd7ublOO18l;2~^k=z8I)=0x6GYn3bf_OT)ku4-dFdG
+|$9S7OT}jCQ25Jv@#bmrn+-XgI=N}FC{e%+hbX!=`2(2*-)mJ5{W6PzOk&|4%lxUw)yi4YPw-tMKV;o
+DudOJ<)?P21_I3xJ*cEqJ(&cpP6J-v7AW_2U!ZLJua;dk3w+hxQ!wf2@s)@I<PFe#;ZhrF?MPI_=1!7
+lKlxvE%uRL%!Vx>MZO*$iJNj=vWTSAK#$Adll^$PcoU%CB?1)Mhu&p|wT*alD)}0$CII3dBF0CzV*vL
+l7h7JD&ylMf`h$UvS^LC~>a_m3S_5-1JwiC0~ZU5$#>n_aW-LQ?fNT=&|`q^mx>+h<Ma;Ec~M^UX{M@
+d6nc%%0EIp{dbtNyTyG<E77KzV<WP<MA*W`Qdx+xff&&G+ICX;H5apj9$D=(cQ0&q#It7>60JAMDMa&
+(X5977nm^kkDehL#F^6Qr%y^bpMf~D^;7FJR4{47JiNlNgxj5CA7|WJ@i;d<VRT9e{h$H^%k?LyUvl7
+QL+Sg`pGmlmEyDVLWbJxbE+`YEUO7p$kBqdlM-EE%XvQYXQ#?!aQgruK>^fFJ6w5}<v&}~kzJ{4;!b0
+v2bnxsUlE14A*Sw(zs6YDB;bPM}Hocl>J%yY@BlgDVm`q)CeBpNp918-?9ut#w`JhJSrZ+`Qe;doO)n
+R9^quElcyKVY1-(ENDkFItP2Xp%vE=6;gPN{BWNDXkWmgJEOe?QAZgIljDlVL=A*DB~U4Z}5KbOwbp+
+=`w|5@Z=fvhdhBXP=!xzc?;wAO}VQn55EVJF`rT*=2J>9-eXP;=yBox{)*PJ20WS}_HTAG{I=hS0j2=
+*+amJY^!aG>(i-=?NqHe}ZUL@%$UNI5=84ZOkLLRoQyDPhEz&IyyuH(HU(N3>qqnW<rQBvwev0>bDtr
+Apb&J8ToBwp-vE=brBCw_=+W+eJ4Y1cI{&kASu!!Y08{l8K13XN!LeW~*A$+A$o$vAWAMdP4*ZJ7WAR
+mLT1;z|=8pd=Xt>=TpyV7aQdt`HOw=CAu32`TuOT4b|BC+RkTfU+sHvdaIZhqi3?(=M}-2~g#G(nGsL
+ym$E7pZ|SQQwTZgkOiv`wh}9IWMI5myGkm=}r+BIhgK`=Y`%hnSHP!qvcQ^vy+%-nEKVgOd|tCmz|93
+lZA~^P-jIP=yo9s7n0ucjN>9!fcdvFhV6G#8IWh@)jKM_N`3oZ#7~B#OwSYMDb1JF*Ny^TWmv~S4q`t
+i^rAlh_lfV)dY(&Z{gelKnoN029|wJ_4o<RGfB0u{{%~r!6m~Y{=J*_v_iI-}&Pv<lBzdK5&bzIvNG{
+m`tk+p2BQ9#Q!(RE@GuYNfh2_C!&P8b<`#34>jg+=6OUN|P@8DMt{4nU)rmS~c5qsPzSvM^wSqt_L+D
+pP`ttYu`llk|ej53m8AcHlKoHjx_8R^-{xLa{B6F=i$2<#cE*Uv_u{|NTXEQa%dRZKiDIj22u+|{019
+_1b_#I6Fe@X?SMb|XZ`lS&-0;&;FNX;8oV`T?O|5ns1eYFg)9`oz#@Z;ZH4Yqv?ua8HeWmUN9u%&{Ak
+j73k<`gZH`FzhVd)bABKZD0raI?1hOk`;j&hUbmCjOiX*)jzCcJ4wGyu96%J++z*>64B)YYTIF&r#NT
+$51P}!?e|Z+wm*T=_(@*S*n^*?CAHc2epjly8?t8%wX5EK58AlbMs1C!?+mF9I+cGe?0^!Sr$`Qmesv
+hwYdVjEEzp3H=>7Pd)^a7K-Mdw)!@cU>pGbAU`x(!xM9CX3@*btN1buWn@eN>_floMyPaLAO{JfO%El
+ndHF`IY<$EYVBLC-mVxK!{5oO5Lo&zGfCtDE>k6Y+<mwxE0i-`NkTEiqX08;mtC&LNgl{njto&&^{z?
+y)D*W~E)naO3yQA6^@<Na}BkB+H0_zZ-Thy|&obqsI@+4VgQ=?}!**xX(iTFzE2hv4+oUm9Kvgj3uUo
+#1e~kPjym{HDbg+!8$~|z3Cx!J+0R@8-87SUBCxLUB+2X;61SivB&w@$nMaXaqZL|U?m8DLxsl;;O8K
+0efj-%wiRb7W1j@;LtWfv!NitbD9+bJ`=*I_ltM36xLm2nOmkvQ8n$gmX%4U8@yu=Blvm*6l2V%z!;(
+_AZ?VTS9*Y`sZeP$YEybzFfpkJ=nsdq+<B1rH#<`5?YF06%wc#G7-iV7gK>vXoGO&_)yhOVJoP!Y0S<
+ijA*k;qdbdU8SwclJ{yN2dTK93i*k?31pTY&QuV7Kx020P`SssYkxI_J>%eNe_c<7XI|*t5;v-)Vw>q
+Ylt@;8L~T|FTZksT0pnqTMs-_Qbolgp8B(onWk4;~YA|HX>*{GC!dL*!tuDW2Fk*Wx_TlnjOtBuub@L
+7WO<cJ{qSb&9!uzM@GCb*pJ+PSZldsmg<A;&Nq)~EhZY%s$}Lvypnc_@2Pdb#DR^`+$6VsvU^qBss0J
+REPB0;SjRn0F`~}JhjlwQS^U4|u!s?iyM7*5;;`^7!|z3h_1LU5xpO2vKC4ZAEJu&eS~4eL8`f+GkBM
+UTm<H9t(rIX)+2SzET(%CjaYi^zW<fSJ)#2<k)K&+y9si$Ys&Mi1hV|vHS<HvnZ8bdJCtHSiZ6qIiRE
+eLV1|HGRqZ;*Z2a`tb5NGP#1_A#ES_H3(X8&r$Y=k_XOLNAxQ^gr@F7OYRAJ<wMc9Pt(PJ(?<;H%h|N
+Deh2rur0a`xBPFLQk*K8vN23ao&ydb<&3dOlq@Z9KqA^?I-@}qO{e(QzV@U_Io6=*Z-6H5gE%9XRz?6
+dnT4`O?^n+l1J?<iSVg=j^v(qKNe?}SgY04zP+-U$BPbaqf>9=_A?FrX9LmO*db4BBa>O)e_0Sq#q5l
+1S2MK>IMh_f?o#+fQoH^FY#-pqB?mD{C&Ysx{(gFDIJW(95hrfKSe*MTd@RcOSg7@rjm4*WdfWkZPtw
+n5W3fFr7KIoK@Kx~C3Gr2R|MYKPU`&?Lc-*6p$)y(<lUMY%f=B=OUl<cLWK4{9Mz-(zC}Z<pl(9KYyf
+w`K>cW28UYvJ~QkhqN9OSY4`-O~Hhjpj$Si^liv~INqxg!<(6X{bW3hS&Oec)ugxT`t71pPL7Pu{=^w
+K7(iZwD49@kS~e@=P$6k_j<jw(^*p+-Ak(MO^G2-Cuom49n~Jfja6M({>;K+TxB5Ii)vyY{?cI@rvw=
+;m4ZdHIFUnZ;(<)j&9i4I-SZ)pwCmZ7u7thj!t%#Vv?peKSE_pr%xO3o=J{CET=&pFWu%X`A};CJ)YB
+J=wwp+P(Qx^GR4-6m>j?mKCRfj12pb`rFJ1EQ3*qRazuS{FO7?*R7vmk)4DiJeaxcz5tC)lbRHKe4|2
+=>wYj5PXHk2o+;l0uxoJ$ROjCmKdggzIHl=vm<+LCsG^IVcVN+|m@bByF`kp#^DWyA2dbmdK5W5h(f7
+WM)?egS)ve9&^D_=M6qoc=<6By0tbDB4x>l&~z3GaUzkL%-Ca=jYKY@{1j8oFdOebg`8nlt#hM1~hJf
+c|t$_$iP~*eP^`=_LDP@UwLn(QhD*<w=UISH!qa^KPg7chK`pdS1O#?Z7>Q6f0s-lZ?L`v2{ov>3ilF
+Y*<9xo4?R++)0>mKhwlK)jL@Sa2HGx>$TB*GqX=0Yoj%8LhKOYvCykw-{m!NzcI+Iefy4q#;IPk7xBL
+M{r@o$cm5Tu%>-L>)hyOwPDpFUyK3SCFQQ(O4~WkMAUl||sO~rs&->F!^xSuPq07Gz7PmTpbxh-N(aR
+(YzHHrZ*ni<%<Jsx#R*sKCbJO&Dwv6M8?iRRR)tB_N?qh6`SbH|_n(2r^Z{zF1OzDe;gikl(=)rD-)^
+Fuu^nHB&+PsK&@g(jRLdtH(`303tb>!#h_P=KC$8GD?8sa-(`=>RSItCygm$3lK(pJiafp~XoJn5wVc
+yYgHN)$0Ld2F<my1b}_%Zsxp9puq_X^tZe{QaY*)9>S>y@P%0;L8#}3p+Z-ZMp-oLeH-=#$X`D-OBfZ
+CSkXBXoKuA?$AexemF<P*<K`l=IhvH|4DWCT%va5NT%LJG^co<8)7>6on}L9hqjOfv|Uo+pWX@HZ-(`
+Mk~4gx|9R;D;gJ4ErVH(VN|gR9)c=KwXDa-H=E81=)eWTlsFk0m`t-Ba7+}k=T>M|bF$B8`A>*OXVqM
+z2Cx!2rb0O{F{$0g|E^ZT^>Xm4&i@j9PZ;<GRHO^zVoYwMQo27P`i8s$B+Gw(s&o$UrC|OA!H8H(;g_
+PclHFsya@VVx9Rw3mNeX5tg!mQhHh_d}F7mGABrURdf^+;>PbK6T=OJFwmPiQP~!3!l5H%@1{=Y#f@r
+>qlY8pxN>Rk81vKz9$3WeN;gM%HB+DLmbZBf+}^+#B$`Q(yzfY=*4z@#o4aY0f1I+Y0~QoG7x&B~-@^
+M}(}Bs{4R|ANHKpDus+;nncD(bIwyH${52@WQ<c0_8#C%pi!Wkc+m#){u1t6CE5g<RX(Kl@63dpAbAX
+Yj*<u;@6i#i*Oli8Kdrvw6*A`)$19W$jd-0lTPhrT`+vqKYLERN@(FGeCwU&!xXv7)K6+m5#@Qq0Ph?
+!gpzY-;+83YGZ7)}U8g8Rnyn>&#Y);*Asb@Pq&m{R}2km#Wh)$>XiddF3Pi*v`$8dU$>f1jep2G*;wL
+iSP8}E$qJVE<OGnI3M%Go5vc-(Wk+g)>-+S?EphsQLg`9RMb);6^xjzl*-dvQeg)K~5g+L|H;!DN{AM
+w(2C#|Qc})J8N`?<4%tfI*3JT-U)bi3K+5u?@=Tf3<F(TOFcLcFC%5*{9;nI#j=KY@Q<Q>$gwgcK?pI
+r|@%DZU<3(jmPoclsfQfoJrvsldkc^8Na)~%(0dE@1`$%f_9$c_c+c0VRzB@O`2QKgNr1K54cajx57O
+O$&S8K_=rmu59SE1*ZG)pVebabVfJo3T{4@$Bcu$-dnq($Cp%j*Vr@plivaK0atFu8^kRNsK3w0;<8g
+gzCHlK)F10OYqixAjAcx+!y~IW>Qc7=I8tK^8s|twL%Uo%!0OPpvn=u|2%@wO;?zK=_S9LYw-7W(bK7
+2<a?J)WJwhCE8;_LgO{WzDYic@{rw7w9-tINX2gVwx7@cAVISA|(vu8G_IlI%|9n>hYhOx-S;cUIzm{
+@c~UkzK5C=yv9TkIxZG=ZsYg!RL_<_Ylpc*?K-pZ8hb~o~IW0&ue*iQvEoi{$N*vN1=YeM=ML0o43TU
+t#{!)JztSr9Qbfoj7L+LFNXfZ23XD%>2fk6)0x84sUn?&()}-@8!*{Erur=OERoWDMCJaI^6Z<Vt{Eb
+^r+V>a&1Kbh6=bgf9?3-uvRAM|%*!EW(%*eke>a1_<Cuq3W?A(W9M6r$!SfW2#iL`ucwjc@HJ}sfay=
+|Cbs>+s*0N<ai?f@*O|n<%3gGu#w4h{#i0$Nxm3g}CkaQx=j0M$_l7w`ZQ$Ex^h1(@1G*7uR26hBVkL
+dM3bxzBparQjgMLf<LX@_s{xsVubQ{|5Qi&zCemnFVeq2r&-fv;Q&;u$ih={lVIs6LXZYYkgT_#&|D8
+vA-r3VHuH?dd0pe<6>29nEvf)A<Lj1!uZ@W%w4@oR8^xVp|-WkGRZ_3<vdA=xtadhd&PLKB2q>7}O7Z
+DB5JXE;^4R`sU$1qxT!(?-;`0-k@@Mj62w`r3n0n)azJaC`IRm$4Y%pTGPN!?56!TH2z7uZUc|_Cz1B
+obtFICaz=yAm$3DxvPva6@J5)u-QKYC^NrpmKBG?9P~l$0y;Q`C-EzGexR~QCG?pKrHse2RcW{1=7}L
++f_xQZ%yX$<g?|u>YkMndMi%UP}{2`U`Eal&FJquKy*LnB(An!&!hd$=GY2!A+p=S_zABD&J>?A(xPI
+lqk5Bu@v6xss~TDvSfM%|}5#TR>cTcqh8*CniD&k3ys_%SMt@yf+wt>fMZ<Ka%uE{w#=G3xsE32vvmS
+sJ|5^OPp+_>FV&aeZor;BWi(@^f`=Q+A(@(Pc~KG4Vc4Ys%sn$=0~WzMI#o{q5_l+sxJX?J1IMwW>wO
+Nlw*ql8G<2$);M>tn<Zgu|G6k!z#cR8%?Au>uLD;X&m!45btiV)AyCEp7tMK1M%>NG~rLvMs4|y*vEo
+AR^j*f+-7-uEX%!@?+>Zt`@<ioFMfsO4!vyL=}9ppE6q>~hh`8zmf@GH7W#?r&Xv?ck_T!_IM%4OtcL
+nxrBD0Pnu1#RhDb9Pv@dn?xahUe?}-Oz6Ay--m&4Ol7Zi;tb--Y1Uz$^}l4yYaA&J_JG*wi;p%0P{?A
+s^oO*fmQr9M+UzvE2?{^k9=59#B5cyzDW<Km06Jm7^tpl7er_n&F}+ZV)b8%Z=Z*HGJQ;4eyjL7!;t)
+#9xEE7Y#Nu`zXvAs;UN7H|7T@Mg*6^e>%Pfb>sc%qaan(tT^FPs7A_!2{o<K2M?Fm|LrNvK-JEIDO#z
+=*!&;n5UQCO;H;A-bkjlIHzm_oxs04>RoF#&S7gnCy#DNpD1k3%W-E@Kz%wr1NKRV{t=0*JRax8X~c|
+xPuB@Waelc^@UEJftisgoY&PGi7SjBy!5l(tddL{uU;O==HBKqj0-9sa)`a-v8n((`^nQ!l;KUxdL7Y
+jHAJEU|+rRe{zW2i>%Kh+9i2s_(9CJi$*r7_2dFJ%ki5D$$w3FUQJO|^+ZE*WrdA{wCq2AfXe^+A-91
+y=T7A9S;sG{G7i~;}nEOv1+Ujr+oaX&Jo<#pqZh1xXqeVnt3xg6Q9VQN<iwaYDwc1;aw&p=3fN<-R%*
+!4zxAa@$=0dLG&lfmx{(KnoL_*1?Q+rYYirhKmzajtJ5ey9NtTrqihyNfO3?T&^E#nUv!jLVW7t0Rte
+67Q}bp|uSeX-Khp5ewQC76aNk9#gtD*3#^f)cPLWdr7IiW;63FqIZXtbZ4YqY1j#4Zv2{fBjT?gkio;
+#y#G8d{4Ic4+)4Wd?zN5luvtcVq4|F%?)!36bo@aZKMP6mvZGpy@gL`vV*FxseLdA1>T?m@ZZCZQi=+
+|SxSI4;)H_?(zhNWyuhYuLX_ZIsaHsOi<HCn#m0mVv(w+PqP~6G?;6>p_(sP8LL4@>4$1{(z4@S2`{K
+NRU>S<c@lxX+Y{Gs>KjmgjAESkn-M|@*BWO0no-G34?(_YwpC*N|W%El^xM?AIi2{o`MPObOhPVYBrf
+c6+3!wv0vO2>k)e1ZkG#<1OdAO58pc%H{VVx2b(YAu<`tP^Dzd5aa1_h%t_ajvju8u48HY!!DiUne>s
+&OPT9^c&@7PZMS3hNSy<dZ#`i($&*%ygxC8b-q0X^E|D0I?><F<6GIhCK++damHlgu@>JwEqr?*%b4r
+y*C1~Em!_)^U@f-)Kpj1SeMPqQrj9My0=*BvPfm6B{zw^pp4-zXth4cfdq;0S!tLJj-1M8|z0QqOQk!
+Wn3;<gZ@e=rd=&qW!I~eQH=AEkq<2Wuw+o`+^;d9=H*t$P{Aa4}3c`u&jo>WqMcL3L$rH&kq$GO(I$B
+IafTpusuN20v+kn-}WyiQu{ZmQcTFKsRB0KLCP`+JYvRgW|G@VT7UYa@C!Qay<I9vBgG;$CrwQI0qtI
+3I7a2-zU(O`=~6%gc_ZeJak>T*7^FV>}Lp)fEjo)(k2eTSM0+u=qMZ5<U>n1A;Pks@HNv*rDNf{1Kri
+*z_~HUwt%DCO<zC#8Qc7D;w?HJN;GNzbqoIcfYV3>5IIJbjcj=q;FWn!R{=1R2>BdP7jamM)Qw;KRqJ
+&+UgkAiSz#<nqxo49h1~mKdhLAjhas164H@V!4KjDeRm)>aLq!FoA4U{y=pX*^4~$_?4UIJ-k?6x{H&
+(AxN%J5ZR`^L_P#U8+5SIX(OSOsf!1>7yb+h!uv1L-0>{8SUkx~u)Igb8^^LI6MUV%!9pQ2Sw|&IEr|
+NcCp?Vs0h!XQspP9Kie})}twuD$d7GE@+k}W14xA`qw@f;6g1iGgPKTeeWL-?vE)3fB@vrTxGM$giM&
+mP7zJ3X@ppEcsyOnNpm`0PPEn?=uN1)trAXP3~kOM=hp@GPI6<p-bLjb~TVvnzwo?!vQc=-D;FXLsP)
+VtTeX`0PLMjC3LQ^}%Pi;u+~p?xn$J6(hR8?<BZpoL))@y=eTwUyS@qP-YxGiwi!x2G1<?%o2Q7h-a7
+6v&)0ea`9{dJzEfbc16_oOw<cEPLZ0kKUE(C|G?eV$qnvS?76_8ok?Y^;&$TVj_^V_oxFdstaFgc`6q
+A$Aom_(p2PIJiPlloOOj{6_`O*1{GEPdeN?>^1ABp%s-2|2qaU;fFnoK}!1-alob|Du{YII0#ChHvFD
+Ks9J6^sCYgUxG*y4EwWtJBQj#3#_w-g6P@cs4Tz!1LwvpDe4@I?RYJ9OJJ$atkOY(L3#off9nTYyJI-
+;n#UFESJ9lJp@yvENL50$3z?pDCHjgr4}j@O!t~n2xh^g}(UZ7jYiO_MgGow;``9cCYSx<UFgyc;P#7
+T#0jj_0L)hd~ZtPiBAeYzq%a6N1!%lCAsZ}OeXAjfxB#TUOL9_q@DLsKJZpx_`kDG-O^5Sh`E??AM(t
+mwpP;VI~{D=G05VktAP#8MsB3O`42wy+o@yM_FsW^uDYU^#?`Zm=-__*an7f|bxg=O(A(Qz*v5U-RxM
+^81M~7Yl?$22z)j1ca)f<jiq~jomhdxko;xS}NJ~O+9uC0{QkkLqMNN0=@|shZ2g^Brqr7}i2i0xZs8
+uay`&ZF;mgr~tOO?oTQk!!*?hrRH&xbE)EobNAZu{Df@H?GX$JdEP)$Nxe@E|PTQ3J10{ZZeoxxl;C7
+kJk=`8)86#H?u^%Ye`wOQhwa4k?lQGTkWR*>`T#^KA^tSJL#KTt>OEY5C}6X_huYmSxLoNoQr7)c|6f
+Mbj@h9@RQEP_6SW6Y(z0A=opx?!g%m>m>crhjW>#2e?gTr-`XJXUdy`wMKdGLClN$!r#T~@1DmyDo4@
+(OZ4qpFEGJSt{d1<-y@z7Q1+i0qIa8s^C9m)jo&{IzfaKbD$4U2z8_Nq3rOxnThobl_w9`FtR_D64$g
+dJ&`<b+HOk@bIXndW6*VwO-|qGQIobmrxPJL)qn?K5Xx?Aw-GN!mvvobk)L!<ZF@dS{_K@Huk-7-!tD
+WL5cs4%|gde-*JFy=93^6J63=uKa1^(63$&=x0tqLg*XKlFqbp5A@>yAGB_j%!q|MXBeZ~L5fEc?864
+8#*346cb~7g!U^F0dw+U0_WtyTF=Q_CH(`%f7&xSazW`@mrF=BITaDJ`u8@ewO-{ah3{wVhhOw6{NSo
+j{V^waSkN`-(s=sv5GkLUcCGHP;_jB(ZPwh4mei?-Y@vIjX}Rk88K{0lQ_?1+?KST#(uS?alDAFwD*z
+R<-?taTgTIYUWT&~ypPia_JJV}hvAe)*hlK|$~gX~zzlz<6)}chqBi{QgK)oo#7*whF)NaiMSqQbVfV
+VUZNi5r)jKm;=rHg<{&w=sXK-h;ljLda8I5vE^MC(N$iI=YdWb&1*_0L3=Rs$d7z<m3V*~MRcH_Jj&m
+HvKz_5(Q-;6%Oo(dQlIJ@{7m46@nL4cFK4p^IM9BZ>nE;<0eQ`qid&x2glO*F+fY-@pQi8G;9v)FzY@
+ea(ld#Rjv#>)}7sgN;%mr7;qcg@1yYa3~zazfABqVbc->{l@-;FoX<wfkPG7xnc_QXkqlcs>MsGlagJ
+j!ChB$?#jI>2tV3@RQBa@P2WglgYwkUyskP5PpVtFZ%f!c?<U!b5mLJCg4aVT^Ddlrq?Rw^|m6-`+fs
+IFA^8uz+Vbt6}5}<o(?PTVo_ctl}9qS?-jo>w}N;?4il^E!hLZDtK%^jt`_mi9F>gww>WMU|1rnmAHd
+htj%*LhVjfHA{}s%m$1i`24Q7iNz4%S<LUAtmUCxr=T@GTQRO|OV`?Mf-#dx_A>tK@9F<G1n5szrxSH
+cN<%NbN2VhcRGgcY{UVs)2Eux(?NZ5HYie4&#W$9ikCi<l$8g=@Q<aXh-VYeZZz_boimW?j2D&v8CSZ
+97flpG9eLzoTOm?-sW8FHaf=sDs-)(tOETLVBsG8FFNHENn4swV-bfmrE@pD>T@XHTLZzIegdQ;CaB6
+`?MDLIxQl4!=`61^(lkW!RHA$)J_`HQ!>9#dwROWu~BlfNd~mi9C%GOy><(Y{lPePtcuq60n%B~Pe0_
+|Sxx1pId9uZ#>n48de<J}3wz^O0Q7>t(vhQD%ZzEN?}c>c8=~LtBx=tz=Hu@reowR6JZ}lVC$l7(o6G
+2b_53A)68i0($^yXE#rf~@SQc1HeMGEww97AZ93$TLENVO2X54T78nM!;e4Nj}epJZX;6K?RaqU+SZw
+IzymyWp{`5t41cj%{UOdIc~X)K=lDf+kLoL1S%`^S8Ts7|9jV;|v6wz2#-9QReni!lki1o#aYF;#G8#
+pKaNe2#Ws=fn9nd_v5^7U->Lu@-Z(L@Yj4vL|DmI77<o?h*GLVR$!D{ABp~b`0k~pQcOMd_Jtc2(n#@
+)x5UEy3-=C`199FDesZqWBTNweyRHY(P!S(S`fdXijC&KO|l#KQ$ON3$hO*fxIbVb=7^cn`-vxKSG)F
+@q|rqVk5Y%d&b;=aElYt1+<gs?Pa4YKCi;<1jt@8QRe=x3fMZLv0*wrMfmWas=w;B#BD4IMKjF?2_nN
+^yPd_*3G4Zk^@I7$9zVDE*(b<0}NMlN$OmeTU{8eG!7KsCA@Q?wT@5Y#ShvdioFjFGNT>fHXzLeG&$I
+n%i9Pm6ptu@48f*tqZDq6F|TQDbn5mMjPJ%-<o;iojYUVYad*tE*~q5C2>*hXrP5gRO>+GE6!I!pWIn
+kBQE&n{$vp;_i_qv;$UI^e&81zhwT_;NWMvsf9YC%4g@&3prgB~Nv)u=~{Fh0Qh2+ft#IlFn*@j;>^k
+3}4E8vO~luLp$I{W1@EWe-+m;_xEk(56WGIuo+n{S!;iQ7(kR?va-s#^{&xGoIg-IUETAVhh|OP<_vT
+d(ms}pd&j-0tgeiBq@Q@~UWwHuNGZK<#EBSNNZTXDdYl2Z(7bQB;BrcTKuRoY>&_o(w!z*__P8WdFVY
+Ru?-3=@d0BvY+||SUzP2Ql6+A(5Fz)`~(>;&YGVJD$AYW=%L8+8z<@eQ6TCICuPC+f~afmLc8}=V&$=
+W=8$yD5FdX@)R;a8|E)T!-KIuI-DU=pjty>3C0+b%b#{f7_3ZyUC>GzVfiCiOE_sl=aYZNjgyT2>3up
+R|2L1wDwp)15t1I}MnrtWNuLOox-oDy7e@NgG9Zvn3B~1ySCcdU*rMB#XV2-wa<t9v_Y9I&z6++ubMC
+Lbo(C8D(w2T`xVWp)pwu+x`u*$4oSLIf$o7Cd=^m<wDm<RyedlE`)r$d_-$O+7e)myysujA&ut42IIa
+s<~c|*ww%Z+c{%+2f_e5H6~0%EQy^QW0dK-KE9Cw2#(T;)FkAH*_hrA}c1p5GoS6umADqSQ9~I|2X$d
+%!qII7Y?-{)!G6q?ib8uJCZg#-Ta{UWQmP~;!m8lGI$ttB(>xrqf&S^Y%AwKzBR@Wqp7_I(=tllU)v|
+Jtob|o7xH#45frLx@krm_(u31z0zJUL100(60%x|8Op|5w*{3}34HRN8A`L)0d*W5BVp=yPZv=2!Lcf
+;WN7(w);hLUXBx=Fw|w)h)}Vgpm>A(Qe6R^;7wfKN9sazD4uU5}b!gnBQ|HOEbzsey^V2O6j2UARYM9
+&@AFh^nNM*-$?BqqH;%^)@`nnA|@-wJU$9<9k4PV=;&XvSlovfMVvLos{vs06EE^Ceg48{P0{R0@+i+
+0*^PZSJulARz+2(lY4BH#>W}2H&;c+%Rxh5_41Nn4e-ZJtow2O))JlP~`2>yYvGwcwhF8vS#(TtwMJ!
+RwsUkfVoK<3lSurdLekf+*2M&_S5ZfqKN-G<rdMC^Y17~2Ru)*MQfoYHRe_zcRA{v<_v(+EZNIy=kT_
+OqnXxCY-G8$b6t-$ty?TQ*e|EcfIXP%30_kexMpc}vUcuvqv{y(5uKG6%la|W&UPoR~`<HCl}sy@p^v
+@#Q|=CCyet%fK+Xl2sxfuhlD=L3!kL9?`|G%Jcttp(i-nyvg7X!aD*B1o^#-!~tp^fyu7XP*nwZnC|c
++c@d;@+<tznB(~agS(LEH!B{ttL)PZ>hBrq-wP6AbEG&&Rst(xhR3hiy-2?}f}W6lXAnI@Y56i_GRfM
+j5Dmw9qPMC1gV{4Yz;82Rz&?7K>mknFGRwt&{0?YIX{6%ZX2gcuDci~nx)10vKsdcq5R1`fCB46P1Jz
+Y6r<V;8&Cx!@NbHBK9=Y~)T7&L4>GWRq+~=Ps|4-t=-!>rP7_JzY7#H4<zarzpZ{#ugE*uyB(U+sghr
+J=Bo+}3~7#E($hwXkj7$5d>J$-&i8E?Gu`SD>dG%t_urunEyT%J3wV^qJB#&Y4?ovhbq9|-D*&*=628
+vZjv?t1zvqJ>?T|6C6~Fq%O$IZg83@T`n&l^=E$y3Z>~+!u*-T+$~hZyt+ZgqW%AEIS|ZuZ?)C>j%)+
+H0O)J|2MH*lr=<UAa<wIG@5_Mu+{=BYWTNzz|X^YPjxusMSA!H;90gFw=^?V?AhGrIgaI4#&W!uy2jT
+QKky{U0`-gYnsJ{m?&L|%oPoJHeFSk`5##gZCF&YrNUTj{Tldb&tj(gmdz8k*W~Dut<oCT!5wmtXjmK
+(A1K)l}p777HO(oe7d-Y%C9F5Avd_N-QdwBd)nwNrRDvx)ufEn?EMNHC*#<UjLGN6B;X(`cTpFEm>LK
+3kYIp&&$+7Zw31;_JkJ}>M5LZ7`$&tfB<74Y+H768_~|7GS;Q@Otj@Gknmb9j4o-g>y-z`xMrpaJ(Xv
+Ofz+kAInCx(9}VV`El*@G~f-vaqK8@v6_IusmAhzDD>j*;pNXwHglw=k=<CuniTz|BGn$HTr)C{O-r+
+1dl7856mJ*wK!Y(4yAD`BG1Z$V(#9|<Hbm2h8{_C-E+<E3-gl5I0(m;81J)F89#GIJB+pP@gIdRZY0h
+<=_$$g%FMU@yw-Uq{EJqn-&0Jy53zOj(wzCH60750$j-xx1i6#n!y)FyFC?+{J1Jc|<R7BXR>Z=S8-2
+PC`*frZ>!f{x$BLcqNJcDDoWDK$lGaj5b>FMoX1~krm807?A$I!EI(58k=+USPxJaS<(kX!r;uN}OSK
+)B-X#Tx6meC-m)?f`l--MpF`F)yC$=p`kXO>cHiuKq9)pDw(C`qlm68Z!`gQk6~SY76*Pr3)^e%VdpH
+_lkIrDFaYcI2%(#@s?F#rX-=PZezAO%_LN0+$hfqT^(ty$zOW_hga|06$oN;=e6=Cr<TQSbI6_TcO8K
+pUN`Y<K$%cEZ|<p!k#Y2?=CJQ@8Q3*5-7igXm6#tX=Zi6?Su|v29_`BhFPRT;>@puc+MTVZYpr8(w!F
+%@_AQR^;+=*$CWL1=p3-?1}$*@iTgZ90?l`l86DE}TG(Hrf6$$RyfEEabdcKvb;=>nt~|(fm}k)E-Tx
+4NWWa9iSm&ttJAA>u%#!zMZT!9#X9`dLBRE%Ke>HSayu(<b++w}lFX`o0jcJ^gkby$$y~ucfPOGd?fP
+d6gXvFfsxh3cbIt}uB?Y45nOQ>KX#zcUABaYM-NyrT+iB3CS%5A=b<OP(Sa$eWV0$Qbw*{nDxO3=g^{
+l8+5bR0H+YCQYog}p2qPU3OJ<i)xIo{u|@-GlgFkOST&`tY;pSiwip5Ac%zAlju9-A=wN@Se^5&Ltzi
+jpkPs_l4ZU`)8uLCG+p6%Qspwl3_1iBu(Szo<;Skd|nqxF`Pz4lBo`Jp-4*Lv2meSL)QfkJ#fEqHa(5
+LizFLAJ1&wkcw363i}-he-ln&xO|Ce^K^A9e9r`^$j&8%fcQN&a=IY+{A`Z&lmqZ+ty|Tbn+AGW4PwP
+v1c`xdHOyG9lPxCnf3<Ss=I5QVMTVg!3^}66YWS&Or@Rw2!Y~i=E0?v!!TLX-|PHD}el6aQUCYx$7FT
+fi%y+?C8R`3N!mdek*d7c&1c^;dj=5roYy3{wMWILTwnx%#nEaDiw$&7Sq;`eE!Tcht%+=6PVw|WZpm
+T3z>cPHtSHB-=*s(j#?n5B#bz%tp&Ts)syisyN@lH4Kw$1Xshwz5q9e++*g4W}~NoV(>kfk%jW7re&_
+%A3_8JQe(O{LGPfDtM^L+*m$$klXjytRVTaET+JahaM~Xhq(U)HWl_poD<`I+>t2rvEBW5vHsJ<IY+r
+Ro7D>*l;S)`>y_gu6CYycuRj2PIU{D_?N$+&jM07+T;nOu*&;^UGwN7y?FH{Eqv2HSG46$c&&6@R1B%
+S+I7Iu~pc3PREOD`>wG7ku$s!u3Icf)Vl%-}B=l}Cvb67`>nFY|l`~NQHAogrG?OAK}{+)xbRkzmC2;
+Arx;oo<6MB01sU*GpX<MLHw`S1;@Pa_$(hu-7e;Fjxi{AGyyu*zwcSh9bK>KnQpvN!20vn4LmTql{FL
+T*%ad*SI^#yMMiUCsyAYjbcXqX842#%gGh>PsLVkR6M?B%v1Zd5%jg-^ia|&yrEbb;=AU>Nw?KK7Mw_
+aiT=IMtRr+Hq!oX%oWTN%ok&>gzoQisr+h^wXn};>+yA`QU5!s-=`d^kkurk{o<^kN|`95VSdV#FIv6
+Eo{#*IvPBMjk0p7$oc_<Wyksf|=ULl<lV=ioyMJX@VX9<bfV~9!UGUk(3&1~4(r=uRBaZ!7yF@!4p?0
+|ScI=Va0<>jxB`XYFGk6btqylQoCdyOB=~O#f%HJn!EBcTXE|g69DElH!*I7vp!hhRa923HM7u7$!5-
+}}RVD1+3dAUL2^HQ9(q&NrZzcD|5JH~xyeJJZ*?%!^59>spUR^9R=YIBFI<2O+ovUU8Xp(R~~Wz?Q_d
+RP77#I{~W?>3$!x)xU~b>fVZc!8DXrAx9bb)RH~4#ivp*=LoMkq_FSoXB}Gm*`PFDEtRqM2{YlYs_4R
+q5Yrai!HJGeALIwm=B?Iy!!!`jJa*hQ_N9geu5uhZbr_X)qfM?b-^~#d_kK)<9ld)X-`j|EDy#tGu7~
+6@0k=6#Sc7j+OrQ4&pAx|<pUj~1~_LaV@BM%aR1@2y@I_`__p?74vzcbtXh*PB_$hr!G-*8CW}|c<Fi
+<ZpH5@P;QNVvZAh2DI_Nv6$!!Nle6`H#L*vp#=ck4&PBJ#f$YeZj0&vpvO|0{TlIHzUEbFYNF>0mHSt
+=iUr;GG2oOAQNI!^q@xj4t#wvcWlvAS7GYb&tOxxPnjzTTpr+tWTmyrGlt$I^`24#);^>{uy{xrO9%6
+Wdn4JC5x)<t%j$r*K|d?~iLNx7?hzaMR^%4Ufk~&)gQ~*=oU^aY{4N-+WfveS*ftEvNM!2d2wd@fNdg
+pF%QvJ+Q*@Jmzm<u?`;NXBd-=J$zK|rO%J)^F{l;Q~vRIzp-DN^nR-(#||K#AdMS*m$t@<w&Qz9k3|A
+`+PDiPIc4{9hI_@vzRRin6;u~6SaHu>R5hK)S(E7hDE|L@>OJ6fPWT6B2*0YLtEb(AJr4BDhR@TOqi%
+?3ycB6J5?BI7+17iYC;7+r(taY<B8Ef_-p_0-KcZN?**4lwNKV>Vomr6eP+Y|$v26d{nzq{|NjMuS1P
+(RY2w4r^PyIELwv*c@8!>-z_Opw}MkD&YLvsD|ZT3sB|HiScz`-(}KgsW`SY<WQ>t@*ON?lz40>%)qo
+)Hrbc5<%ImKTsrot&!M+Tgwk_^O}<FRNR(k$8?|ZhDWqcr#BE!*vNG4dg^4jjG?@f04M$qF)MPk?*el
+YY?A-bql@yT8yQ{I*DF&&<jes+U$s{R@9X<LhY~o2IZ-U5ppkZMQ#l#<C89Nx4V$urO}#bj8g;mQ5pB
+f@i;Ub-v|B*EJoPunkY?s8Y@^F!<L~w=s0_!x5}f7nutdpCYk9F@wCTj&w}j}VzYM8S^{lh-;yu!{l3
+8QA<+zetklkIdd6w=iik_+juUa=Hj*q1S-ytaav}Wk6>$Q$VDWE)HUSgx<A|Q{yXCf-Gg<DXh`mPN39
+)S12=&Dp&+?oxs&9F$IKwf;AO;A|986yLRECy!L}Gb(zZ7we*fnpP&9B+BcUWd%t(sy;Hf!NJhYuK)k
+$Drb7QjDZ1)k!^)F<~^wciXJ|25Tn%9^a+uQJ#KUh}rg{AMeyk7d@Urfj1<x<9cgu^IVb`{f#|>bGuZ
+Io#)h`dkLxg7~zkH*rF}4J6yS(^%!BlC`W&N~|4L5}YI4e_!2#x=ZN$a;hJ{r_%R9X=*LxZQwR6r}Vh
+<^>SGo`aP?}-C3fI<@$+s!0W$!P0b#^N&L>E-)IwX1zt<)`noA~X&FB^rM6ZkHQP<}JWaBd;XJ70k^}
+ahtheo#lgzq%*4uWC<gR_#-x5SwbEz!XoCEe$Db)$S`wMEvoW#*ZFB3g}$>OaCSwd|)Fp(b;G>oCPqm
+970eTmvu8YAf1Lv0&YSO8@vQkfsbGvC|Xe@_i~=NxE#irR3H<h$&ww_9(LOkRa()1$Y+s<$CgO60b#p
+HQA9`WSs|ez|qHLH%vd@0D!_CCiAJ+J$o#|AwmH_DH5?^BiT{$MoLc04!Y72>gbhSf}>?hSJrnowDsH
+-Zh!Mu>C>5tC_jENJ<=ellbCN$=aJkYh()TmzXn%C3>k$G}q^glloOMkIEo9&PwyaFU49D_&mCM&nNu
+uJ+Zb#N-V3L)7)xWbJ-qEim#mw`@`ZdjbLxYo#;nI11h(#o$`9AT;vC4rkTo^yT-ML+YwN{?Bco27HM
+j;h03{!>cSle+IWO`Z4c#3X-aAS1=0Ie`rLV3%f~uvro6+7)d@cc8TL<lyB%wC_Tc?e-8Xs(w+&#v5n
+9`rXVv;zfKM@=*XproBj+^s!impdmooW1!O(BuPjT6PelHQv#!m6O0>yjkU8Mt<wP#6IdCA1KBIfcUo
+ZBX`WXD=@=cH{Au|JURAf-7?|BuJ3fezZA{u;*unAf^4T8<b=+0VG`1G{)^72l(jzWU7Se&8uJys3VM
+vlstd)z{9t@?o1KKQrHRkoX<&+lzpIO>(d6O@V*S*AncHBJi)>x-XpTd=UTIB{>$n8z;`Qa7Kf3AdYR
+5sM{zevARK7VB5%93q0bkW`_5b1H?Pmvpk#!60hfYHnOz9Gpfe}k_YE|P8z?v=a1)mp7N=UJnm=tX9~
+6DjQSYv$AN3jq`Q7*8C%^yq{n7mo}+#?q_DySd7uxpH@%@gHl#e#N_tK+`gkL3?j^T<X%0)SluXv25z
+VG`{ntzrdph~<^Hu!;+NT1~nsdHRbT-RtW@bwygVa0jIjL;4BUbIncu^0|c;-?$Bcvy{^-Zf=nM$-?I
+1~4eKAhK@<n867&GA0}mU!P~R+bAJmLv53=t9ZUaa+wEH+>-c78{rgM8jgp0<TS5wvj%GYhx=erFntz
+j+5fcsLsCZtXErOY3>eD87^Sm+~(Q?o0B7?vwxt>ahiz_mZX-JZIsMq7UG4=;mfUT{CbCEwHCc0)g?5
+sBvTyCG2&;~KY&-CPwx)CDb>+>to#j?`Fb2%)<%38F?ijyuFX95gSB=&{LZP~uihr?%wR83q(Ar5bJJ
+~tC*rKjB*j?vNwF5ooLBAHS%0!GCB8dCX=-k}Y!CJtl#jVNQl|P~Lm9Y9^&#I;TAS!w(QVm#1XfOBE%
+2W3{uI#}dpo~(qTfHE@6$76->5_Oy${*?O`_YI|DSHr==L0?HR$#%Y&riz>z3x7f7P7u`FgwA=U-{|y
+>1rs^(ejnn9AKpbG2QcuY;!W`MQy4hjnEl`hlL2G&B?KiYV>yrET_Gbee6XJ{au*R^>jTT@hpz=+B5L
+5kj}6I(^U{gPx#?OQ$FLUsCT*5zlh=z<&Z|8FV_L(+PCw`5wumBonM&7hAD@-8$h9_Uu&8FMdsWZ!$~
+fI3QU)b~o{sVS0X=_Po;Da`#}K$!pj3`$rVt&Un^2u*&3F{%`TeNLQ{Lq;$W3QftY_oeK5Yo%FaJ^9l
+2-<U%xw{eMi8wO@=T?L?Co=>PgcfzNga(W3f2t;J4zqVxyYx-6zOw%Av4Gt2l<*65=4b?w{iv^U?@pj
+7y#v)oeR)jhP<inftl+Vr>`F~s1%lhb{<XQA2DY|wbMMJ>E{idwk-)VhARoN5IvZ}>IGF0C)&v2-mS(
+0nJom(1p7)og3Ni|9Huvcv~kxq<oe3HNWwOXqjbvhSDBf9PGKjaA-Ha-x~<VOZBD?@=0~_S<UrnARq2
+vlQnvdvBY&2iQ;zQhIGEwLc4UH<{!d>YszwIPRN=DNiY_Av{Z`v>5kCs1Eess1tS2SlP5VR@Y8#I<1(
+UNSD%}_Rpd@BFm&B(cHisfnJ39k@qCdV42OJv6=ck?Y$s|;;()mr1QdnmfJvO4<xe6cN2qs3ic;u(*C
+>-otpk@FU0!%G`H}3gz87XR?gql%Ky`E(D@Gi|Ci>s*dgD4n7q-Bc?16R^LUo~&0D{{CysQGgCsk3(>
+xzKp62O+zIWT@d;C=XeCiKm#iPm;;AxcK8Ow6_5*_(n3i5!zQ69%_^Y-}J6f1PCA<B2-t#|Diq~~*Q{
+nnn3Vpx*KVr$)Nf4R+Ed_}YS%W*TDBm<ghO$@{4_11ZNK3SytARqc)xXveyX_Z&VqMm^SQO}N$dfIuq
+Sl=-HFS+eodr)R6J--5SE9FNySDe@Kcz)u4u<JW0#nkQ?)he;pjdea@45_?7J`p~KKY2=PX?r&~hWR0
+52tG0d`$MY=T)npn6;oN@pIY9@c+v}L-I(v4S>a6ly7h@TOIfeNeNEpoWzF}HOuEcMYuggXa-kz)?Y}
+FB&TGpTn%6l}a9;0J!sj*i2S4@mz^ssRiBEh*YV33Kaua#Eo5ssc3znNj<r4qk>%}2>5iggX@p6fuFp
+1U%l~1~J`WYp)tfZlRTL$G%r+(ir_{Ce`7g{U$Ma#d$FRprOoL{^ZjbGgUM09>(@YP@F`~nyww?y&_>
+PvLG2K!%~9MXRl-v2a83x3*+d)%9F*Cgu1nxZz?NbcrsIz{{f=@#nz;*g}zH7d*C7da7gZH)LwOvqf@
+_M+Bu>aNn9iV$9LAe2{(_a%~71pD#^=M`xoydq8T3d$>Z1^uVrL0*wYyyC~4SG+>JB2DKNe+=UlX|;o
+KVm%&!974R}6qUaqf>%5o#w*hPC0^0<(38X~<~H|SmO#AX3gQ)0C-90>I<L4%=M}&;Lp{-W#R&bcCSC
+!37qqIOchEgg>HK1<&Mz`eL4MIh`~qY6(z*~{VT>P@=ktb--=j2sTMq=sZ!X4<<_zWuWG9j#$9ctR*;
+JPPk(Or~=M%SD%i=9%&4;uJd}5O#_{8=>t@6i%S~#Eh0`s|43eM+QQuO(J>b#bYww|DGF`q?j9F5lFA
+(|U_)<pe8|93IAb#SH0Gca57T#eY+#P1y0tZoO*`<ysx7xABJ(#>F#y(*r0UXKai-@ZybNVIuMM4J<W
+JV=>*&o+45w8%EnGu}o@`vA2OeP|@UfH<D;k>IuoT`b8(Z9}{K4mB_gTg+JI>tv&gpc~>0Ve?~cc8hG
+W`e*alANz}nog+AJ$eHhM&6Q?wyWBkb-cEDnW1`t}R+jNqQ#hY}!@_Qj&S$3t`zTM&XAC}jp>Ze<8Hc
+}|(OS@!M5(cSL}AV!$|+?BX$^mr-e&)Z`s-Tz+%}E$g#@a5(^{pXgyx(%@kVQHthubFn<XJ8XEQyAjE
+VE*k64=>GNx<kyaM=G>?OH!kk(qeoYIT(9CO&Q92&>$Zg*>nl)`B;cv`FUD{3Lmjln;T$G6%28&rX9y
+^?vFV+78ow&60*&L=KxZx+qApr})8VXw7bg>#uVUVr`d=(r*xwl;h-jd)GCZv_VaQ||=Ns;_;)uu}^^
+GY39ZV{*kAn&Xv5e5Sn}L|fvc2KMw8YWt6<?8o);V!54F%E)@6&(?Ru`8evB`+_(R|0v|%gx1^El-SU
+CQ_<rw0Y48mnWsg}3*19^Pbo3fuUO|()V3xbk15sr8?V591U?6zi#Sbb-VU$8IPavj4?CmqI87<e4=B
+xH#pV?8!!w+?2R-~3tp&7dmQ!k7YaJ=(dPlM|k>&=@aimT5$znJ~;sw;e_x0FKzT@0qv#}3+p0V|PrN
+^fF9(o^GGXhWR7w>bMod9C?z+YL!?Xic&?LjOa+<%C7Y2h(_?qMF%%>rm2kJm$GAr_G<N?hg(o#UPM!
+hdTja8bCwd4T558JaKM)TYdLg7#w1|Bk2g9QR&$?%sD^>%5IVMJ9F(XPenEY(Hp!mexQ<b=tO*vrV3p
+pRf*`!!Ckvs$%aon-8=C<865sJ61w`)S=i%hNiR1e%VfID`Vt@Vh2WCrSRnzw&Vu3Tc%QU0Cp{_U)tK
+*FQ@SIz$F}^F&<VjylwO!c3h9h8NImsAU?EzWA$)>yV_Y$n#$l$wL3#e>qVXJbI7L#o`!wXSaE;K+O%
+y(ovW!W!FuiE^}?6t2-O7~yXA_F*Ht5>^a|gtu0q_)l}N0x`k15OMye~k4;d56GTOad5$(QFnY`T-%d
+$l+>x<CfIJM&>Pn$A=dtX6I8}}Kw5Z&J(TH|iXpndiiNKZ^`^J!XpyXCary;KKq8(j^Nc~ZyoJPBJ_Y
+L_A#eM<Gh_aA+_TTY#{Prw$~n!KeI^XxU^LuakPaY!H8N%>Aw-5S+h%JIPspZd`H(|P?}=e1m5HS;#}
+Ja!%<Wnz0p`T<Ihddx~n@5tBG4!>;g#W`~?<yo$zbDQt`X+6MS@4?y3^Ske{QLG2rw*sIa+Dh_P<r$(
+`A!2CLGvrwllIPiwJSY>fw??V{%iya``9X`_v)KNTudxnFzyB=l5pxe|&;L$V18Zo0&(;k5GQqQm-|y
+Z|pJL%tUXK3aKAdFM&Xx2WciXt5C;5s0w!a->|L+U#C0PH6J3U1E&@l0l8yV|G{88N9x~oSDTr@82#E
+*gBw2{V#`|umjnRs4JbuPu74ZUAVbvIz`oYi)toE_ZGQfhY4T4I*Q^20n1Co4SFACx;E^@%voe+$`n{
+?H+?pP;9}{@lD)-BQ%Vjx8o$16iYp=8U6B_;}_pwXhoa=9F$8&cDZ&^k<t{a&`6H1>US4dx>Or=3Jx}
+xT-HJ$RS>A*3-}BGAZ*QZ4TwBp|shQ2l&#s|2I<}q~~`n8<=NDM-bn*>S=*LBKCXW0qyMwjlsy{gc2=
+Y><`kt!Y42-XHxnKP3z=)u!eYxGPmjYDaqeQfOTzFeXxa~eP=($6>-}!KiXvL2=4n_68!EGI6iGDO&^
+zR?KMm4V>Pn5SEY0pw1XMPZ=QUAS>7RVn$IlZcJt2b_&jHI=+{|cBgkVipHkwSh(jKXx0vevwSssz!F
+Y@J1M`~ZaC)NZD_N!boDyPCKn4+bT#&nplQ!B#3`X3mq&tg;wU$wm1=i@ex*H$|H#BSs#pK%f_~YfDh
+s#ykA^fyXP(M}!hf)@PI^WmrGT+v5xnO^|RmbImjmq0r;ISe$q|IxzOW<&&JMGlAE=#z45{@kf+?MH1
++z)MeU)ZkQY-YKI^1tWj)AwFEt@d@2!>^?^9WLXfIV1CL(DUCL&+>rZ+`cZH2A|h|v)=#XOTux<ZurN
+Aamo4>)*0Tm)DTRvVEb;T_HEZ?HEwrC=^%p|G1X2fEYG0L$3wauAL7tO!6f_YyIKo;!x59p9r3=A-e3
+Q&u=`t1^Ad91AKEW0(}2F9DexLX>x2G{`W8@mA4d99%m`wGVEzZVts3(pp3o@G`O|#Pi+J@X5c`+r{?
+jBglg{A#h~~*ZNj@c7c}Z4v`W5CA@v}0VJO<h>=9#UDctY(_;sps=_2tivC;dIYur0y5L2TI|-nw{Cd
+%*6tz97%Z-@|#%V`lCz#9%}67E8P?V20oR4q-oN#9W$SUlavDXDgKt+2FaqYc0S**~0(Zy#F}BeI{%T
+>)A6U3Xe1Nsi{fv+(-3wO}UQyZ_!%v8afHbX_wh<q)VlAJKxY+;75eA=Y1^jCy)<$+Rp>)PUOSh4WAs
+$<2(DpF_j{1UqbOd2WGQ+n&4YW{>VL4A@J?NbDx$)jNtJ&s#;rlcsz!Q`pyaA58DTuZOrLc`UKVs=BM
+HR(M8W-7raGgy<KLKk7+M#gzq@%YhQ^2);4s+^?m<!K=2~ab-vyo><<##T#oYkUe{V0;?!ei(ktNKH*
+3chyDn=v&mPnLE@=H{(EC*{W%lAZ>i8BgmM9<6%DcAMKh@I$&nU4^w?j`AHoYl*!uA(*oYn^{4EW00y
+w%h;_>aTh`RUgM77*Ht`)=F?^=sO5BF>d)&xStT{+!27O?75H$IqKSHLVEZLu8)U@=os$)+gp+xJ~ni
+`vo4y(fy(=qK<T4M@^rB#}QqxGsfuGzY=?xi{tR+cp4ZxRx{1r%G+bU+*3sVFQ@<bM$GXW^xspbwYA<
+wW06T~=62{5iE2Hq<-A_nbKi^wj#|N@n}|n^NX*xOH5lL4x(w$I<{8NjN#V8<xXXu}<Vw6K+0i7P-EG
+(_Bwd{B=vL|m<4LxM%_<Z7A?@d7*(879es->8wH#FvoUnViF-a{<yqHy#0pBm6`(T<`-S)?eA9xvYwx
+xvH_53@2WGM5|);~#7FV0|IC0*vD80P7Tu~WO`I`}5^*jTc4y49&M^N2!n2W)L1r?yKuWo6W#8_ld9<
+(DS1`YzZ;Guj&@Ve5!koDId-*3F`C(==+gg0X8V&t}^Ze<sImX8VUAOVzvfAlAWQDmRo)%Ozm1J=)4`
+8|n9b`@?M;!T(Bs6_l?c@%#o9$yvN6A(>=J%aF`65GNS(9@uaOMtULEGVNu{_Xqjkspo{O8!vcO=fCM
+`u-4~+ALur7hVDIZ?$dM8@B~R#5cwqfj^k|(%NJ=^4FA0(o>ujdzOt43)saj;OnZPTu{`*%yJQh#3+K
+#3=>l&UK0$aEia8v5E)ZD{%0$_3Yn*@P`AO!(e^EXQWGAr&@a1|B?@68-mPDU}*lFSAPhsEunfd%DeL
+XohJ_a2KJ`o4s5H>pl$`tQbnb|&09DQyMY$|CDBQCY9X?-OeyG!;+AFwMB(|(20Sbi0yJs40wL;tR$^
+xviDOOXD&)(2m<kH@s<d#vnM*oy6=Z`9XAd&jhC-=3K?t!n0KEBnSp1>c$Z9s2$$ef~h7$L7|}bSu=x
+wN;O8nQ_m|tE9Vr=DF&@nf1<9Gas-#G_&8rzENPUpP717<^N{yT>zpg-v0493&;YRh&S@aYF-dU@fvw
+q7w`g#h=7V|$pQ<kz_RW|z_ieAsHIqDWR_%B<SjBS?22iHeJK$w(M(Y>v8=GHuvGrf%sg{;_XyVed*A
+o}egFU8dvN{iXP%j7o_S`@oO5Po=LGD5?{CK?26P5~JUlU=>3e%XH%K4nv#eMCwEF_)rr#fs1RuKZt6
+Ei8a|Z6K=y<bwNnMSv7nu)sZR-H~*LoJj4I5+bHAI#6q6+5>D!(ut9j+$xeWY%~JNRbxs@$7>bXglRK
+TA^kJP7!-l-%pkLj^Sr;IqKs=(l`9&!KC!ql2XO(~LLT&!p=fLm^H(N#gHw3md-9?rrJim!Ex|@#SOI
+bsA&u73%@IX3q?m1-J-4&vmo*vH^CVmJo0^l<W8KSpl6P&C$to0)BTV^KIU_y`D{*8}LVvy;rvdvjY-
+oSyS!{h@)klc7Fid!;Svl369x~9V#fUXi|~J=KCr~7L1$lUBWCl_D&e}%%Z@%UoX{CdEURinXq~070<
+h(k|!Md^xfy4dv4_f_G2kh?Z&ZS!s+`TW8q;_PK*tQcynfPJ#<UV@FCw#7?(fl=X?G%X^Fc(+bdH&aq
+L&#bx+5&m%OJoEW0D#Q|jW^;NfkdYl#D-SoT}F04a&@DJPj1c_kIZ{nT+~H`;&Pq2cR!@6hpfOy_%=C
+4UQj_xJZwSHDYcE4$G(4fH+WKTy4Hh23Z$^ccholGH($rOpuc7+W_**N#R(*pE^t2wUBa?iEDiT%u#a
+%e<lA^$PNmy8A5zoF;h&B}sP#QTqeI{-4~`L1&}@ix=ecxztO}m#$6wm()|vcLwJBh13JW*0MaNVjh*
+tR4#c`NyJarp>2>jAKl%%_^I9f(J$`k7d85&?IJJ#l9~%0SF(Q9LtVnw&U^Tluy;hjy?0GJ65w|S>E+
+j+^z`#2J^b2`?tawwbggEfJ4qZQsaL7tadaWH_00r)rYV6oTeuN?vW?p5LzV+yy^)U1`xF$^KsmNi-b
+}f!pe9OiNb93<$bCpr%^3(2@_~RslE*fmx~FR*C7;jL6T5#!%h;SWf%UhZU}t-<^A51H9oQK_x?8A^e
+cVW*TJl-tO?t$8`4-enWBOKZq_$C;!H3MYNK(M;248NYwygqgWN}w<+a!l=)TV)$e^PUEGtD2aUEAn7
+ZT8LyxF4kNL#J!j>Dq5~#--50=H^k#>ynj_qNJM>uLY>do4Cha8QHH|=S6>Cg}==a&xfh-q4Ofi?EbK
+n-Tx-tbic-a!-4y7I`_kH-%><wfbO>B%~Cdo;`j{^eZR>q_oq(#bh5Z%ZtR{Np1+Igz($%5e=oa@Kda
+LBi_$#+`1>^Ieb>|O^j-3<zZ0VSJnpA^8s2QpmI+_~N6RhjqjuDR5BRget@g<Gc`dxRM7`8K-W$%RNU
+7)W0MgYmO)Bh`A@zdqT`UXfKKxPueD93m1ip8|@OJRM0}EHXd$ZrEx76RzYgVR*Kl^QIrsU6l@0KZbg
+|uo5+!GB?g7j=XJlNULk?yagUP!O2biL^+sYg7uYcuo>!miCyFWIimQcu~g%~B5w)fG)bM-$R+xF{cO
+`vlHW(EXH}s8<C-d%fT^KBo30{)34c?h{Fnb6;BL);?$-T<b5n4Gs#Dh<B;f);mU`{S?X6z<pvR_{=+
+-+ShgX8QG35@Lkx~dH5OG?oRNXV0Z`k-j0P=dibN?Ztah_-@MUp-sm^4;nZhmJk*v;;47-HLGtp}fn9
+3o51@RkKUnSb{;&WywOdQ`W%POLEkEK%pTWK&{-gI0-Dvuoo~>|SV_nk2kN!U8E8+{`k)w4G{vr#feF
+_aH5FR_4zN@;Jg$MX~vT!woCyurg&1eGs#5yMH<+m3&{T(t<71TVz!n*s>aWL`R{hP~sT5o-Sbi)90g
+W9}$E8lM~UriG0e8`PJT~e<md>;)R8zA5V-1{(yk1w<dN{0N*s`MA>o*sPP`z}F^p5(^+^c|^ipZAeB
+VZNqg4{Sfwv7omD8PV`C*>~YCvaTNP0r@+G=$<t6HzLxyfp8Do=Mz4DK;Pxn2|ia2=(4E|jW4UR>3%&
+|yOVuQ(3e~ZAUDG3eQOF?ch@KE-9w}39u)m)Sb**Z^&91VD5v}UfR0i0yQl63-Op<_l(}Jm?nZ0x116
+g*SpBNW^xbr=v}pHjSU=&kzdC#F#%FkF2XqV~fd0+|d{5s2@Q0iGHaZ?d$0F%ICzl}nYA@nHp&i-xG1
+MO&16>b1(u4jsoD7fhpy6s3ezm6v55RE3!V~21UKsAn!uRwL;XN_jpM`gl!+WrBxUawVBb`sU5qY$fz
+E`B<z#zC5P5mD37Y4)mR|w~6sTYs;6N?vhw35ba?;Niui&yF8tZypU=i?l&R}1>4aebc7@d8@V7tQs#
+4Ge<5Xav<!3vHwX{Q%FtyiDNB67(4l>xp5$PGP+;%-<<20K+s+VT6TI8@%CukM6U(0Qz6LK7Rr9zjTj
+<1<?P}J$hIgiTxgGIGwKw!snK$bR8SW0znq(K}H0^GbVkumgC!d`N1>SzRSQ1Devshd@v}uJO6Di$XM
+LoXiskfKGj{z06v?pYs>ELXY9@6G^%tT#C9MbFu9(`H|jAx<q$Ut`I``T=1lSd?StquePFwQ5gEOCn*
+=>KLcGWgIUUVc&-0~mscsfu&*Oux8^Z>Y8~5^cA=T>rZTQ|j5qxh!KE}%5Psnt7(ce>OMpM6fUCVt6p
+4TzVAHx<qh52Hb-6>3sVKzCe5ZVC`v+^)r7Z$qL23^a>_P6jNY#$0Z-`GCCEWXFW-QL^>HIxT>EPRVT
+i_&}4DE7NoIwlM8e#>BbH^BW?>`dJUWh(LkT}wZ6pzg+-D(E}u9uA5z9_Ys_*1`v#<tx^~XAOLc;3Mz
+9>(2KwQLFiW%nk5;-WPnXiRw;-?}0e)<UHOfuD5i5#2~ykWc?FfTkn8&bIGlDP_T5zs)0*&N7eKrd9B
+(G_mW=Fe;XyQ&%GcWeMT0~2j0tcPfwG`wn0w%L_V_qak_nU4UTt3;OeM>y8P&Ny8J-Ndo|r38=eJ5dT
+YqKDCk=z=m!2k*Lbixp!?ndKhLhUd>s-gA?v2TMAp5`_eQU2?Y%k)&CNvxDzc95PnLx9EA9AifY<3&>
+VHw$H~d|5Y+jMpnYyoT-=&8#psf-4x7Nz{<*11+|MjTVe9WHBM?kr@74mX{&2*hOoePW{rpu?}4gtaH
+MdEj$&g0h^J=i;1_YHz`IIuFaX(9L!?$`enBuT4vy~&Y^lICZ{e(W?IJp0x3_N4c%755Z&0DrY5em<9
+%KDAKgf45nx7_V;IGrlb;c&e~p<;D&hH8I1zH8D|IbqqWUd{4(TqB>NZr1vV3TK^a?_&!jQIz*{L?+%
+1IN@^FmI+y--wsF~0MUw7Dq*u@QcA%@2>$+o@x8{z4sEgkJL_&J{TvgC6YPAv4WrdM-MIQUd(R@S3l$
+q2J7oH>bK)RSf`klTn1JZaebBkyDe4`D6z=nkoRu~qvnuL)fvq3hptrX)4<!U4q<GrAa&`zJCdONNeX
+`=cp@EHv0XHXrI|J}6Q)V8T$Yb0Q><h{xVK6Gp_us50MwWw$O)P9FH&XC%#ik8~0@?p=41vQVgXTRIn
+n+cz2_#9S|J%!Xpu!+|FHu#=Ne-95x&!+}jW{@p_dQXA-%Phz%6Kt5O3LWhnuMp!^60d1LwT)ce*mnO
+oYP%nlVG-CK2cJQZb||Es4j2u18u|&^hqRN(p1|IpZ=`G6g22{kplhXPLEJ#eXBr(Njg+LBfxRnH?jz
+T$bH0ZlUs|VikT)CW$MbZ7hFqcRB|fHg(McB?AoXUyWeImDM^-d9?^OdXAmoY-(u`;;-Qi1gH#)2tF@
+)AVtwUO06C{cCIiUY(@3w`jy@+Zx_~QrNFgBLlX{rWvgpn&ga4x5~lZ4SwmkT86iW@vvnJ4LX8uycR7
+O#r&m)(4}WkZ`WEhp<buNiF$f%ZEH_}%b*sw5pr0Q85?zFzOd6!j{P85U3$GaT9#t=~X5vX|<lYr1G&
+chSAnpzTeC_S1pt67A0e;(@$RGsNpnt{i9s@uZf^RN}$Ql+><p^(b2Yv1O(Vnitf^9?(|^-{CoRPZ`u
+5y*^)dYqzZtzSFs;B9R}+FN3d(Al!|`@!IC=qlr;tS}#2R)K2Fg&9eaVr2FNGbHzDspdzjj;%cCr)P|
+|hM`ZRU>*zaCGCDizldex#MSp7#xIiLT>f8!9I{F<x&lgDeUgMwa=X(N)K1NT-F%b{?Io3ace*Xz{|1
+qaII2sSm;|j+ZfwZlpE4lXO!(^T2=H|-M2;DuE9%Lltfj7@o(swVs3HR3nK}InM!Y+Bhy`;p)fa#b$4
+QFxhgg&$be-;;Eue%d}b#ES*UW?_pPT{m&ig2TwBb@F_LVy1uWNKe-=Ro*A!b5j$2*^5iBG=57+!t@g
+lXVkrZZ4##xp}70dAx#_o5o48X4h#vp1!j;eEPsg_5s|Vj4W&2r*(9Eth#l1X?ym*g1uDF(xW^c{T^@
+|ouxj!F3;_1Jx-ET5ZCs0`JxWD+r&|0o9X+>ZS-{HajqP0Jx)nS-M)8jV=H}!!P(oSM_aF*eB(B80=O
+NAZ)XS8#b>vX(|7WGbQ?Lnp1*TDJK-EC#P=ucyj?u-M<m>fmv+_d+fM7B?w=^}{S!0TyRG^DiEZWm6W
+hA(p9tklxs5-?dAyCy)s<UXI+w}+z{7WtieVqbF^CC>X2b^(Hz1ZGmLncR{2uX7MBl-vA8|NhIO4sC8
+Hjm^MTlDv-$p!$_%&iZ;xCAw4#W6}rHGpl*C6I0rXt26h9dStbVocG%<(khRYdP09Qz`UK}<x<LR^Bl
+3ULGCR>a+i?;{>Vyo~5Q6#a-e5>ba3hj>4t1@SS&O^9WPA0yTvo<{s0(Juu3fH)X&4B|w@*@zj4d5Eh
+JHz009d>63_@oU6$h(95U<1zH}2E-k~uJUN)V-Wizc0rtvn59V9*q`VmC$1jp%Eb{nf`>OER?OtsWS1
+Bg-X*n|u4D&~*RY(+o8ns5uRMIGs#v@-MBi}NbY<JPJ~i?R<etbY74ll-UdS7edn0dBaP@Z1+amYh?w
+Y<Y@;1mr6mp${$8LAEFLAqTei_Jpkmo7Vuh{PD-$#(UBQH|uFGeoXY(g$-zeK^eD&m(a<U16+Ou@^yy
+ZZZ}LSCuRU!{;&EBG-*{8|M+rQmhQapIKJE94Cdep$gA75QIP$eR@M>k2v9;VO6E;VM@vcv}VcRiy8v
+;Qk8UL%}r)-dDi`6@2gxSAT^l_((<kPz4{S;JO`(_O9SbJ6zjm#tzr^l83w#@*;)21i2sba^yXb*COw
+Uyh$PV-{~q3-RUY%M1B|Y0_5F9{>U}RE0G5vZ$RE3x$iF5^dZRG3xDl$_4h>N9>RZ$_({85?R#XGYyV
+TU%hlf{$nQX2rm&}amuvYOk@pk+dV}-6!rnJr<r&BaAuoQzRe$*#uKub+-Uqq5jPpR`p~!=Te&pSe7n
+Zs9$HmAyi1L-W_MgiBvO*ERR-wPC%(Z>_zUk_p5af5ZqF>p+Df=ho`K{~^l>L*k{l{YdoslnCkgT^FQ
+ic0~r=%KEvH;C`Yl=S05pK1m0?(4UEyHMa1T0vPrnlOh`C>zgEyp54KyQ{H3l<pk$wpakt})HFU>I@b
+!)0!^Sw@cpv>2>5i!sF}!tEw~mNDIANM&3|X+bn5L$0t}lWNE^*bHPmeAjBBzZpkJZ}>hQ0(!$|-hDh
+?j@e+*gT3^7u$H%<LC`3JgW*GX`|QtTL1ZZ5?ROmgfDXC{M+-O@FmNE;+XLPYpQSVnBw7kzf<Qh9KEd
+!A3ZH&79V8kD3i`wMrSQ2QK1qwyZ2IIZ!vM5DX>qcGQzs4}Nw$2mAty})lccO15NND6z0H`SNw@1QsZ
+5qc-C|02#9K`38@vMHc3MFLL^!K1?k-56jFFUTNYmT1Y?_oDlMrZ9vU03;3$rbWwgvrd(xZOo<VG9!`
+2d&vTNKN3ZhmW8Xgs6EW(QBC8m;CmeTpI5V6thl^=45{Lx$#WOi{*b(IhANZB0r_$uZ}*<}{j*J=LbM
+7;JWniB(h5q)3t!myi(UTCZ}eaOEv4rtM#}Yi$35lBAq$lTkz4kkv?AMUulwJf_k<rF`CfE-{j_^(K9
+~A@%Q^s*KlaJv-Nr!gDVAZuS3dV$=4UZ_;POsbMr3ZAR!hmKZFWG>9h3Ddc*aA<t-Yw$CY+b349mcDJ
+<G+sAInkAI`z<$SkgSPc49r_)~U&oq7dXk2(o&H{a|-iY0(96oNmmbaG#=vOoo4b~Kk(d=ZPCY+WdB1
+><zI!VD>n!sD+VHS%%9}{9wq!F^Qq-5kPRcj)0vdygB%}8DdMb|__xt#J%(wlNj`Pn&ks|M=FU^PQ)l
+%0kLy>}7UH)m9aJ6{Kthx0Yqt(EkGtDM4}pPf9M(7hE@w}Q^;oewt!sugja?NgS`nG2gKdODTSId9Jv
+bP(dW*A{k&^v-rE%iwH}b9!fcob6JULs_4#9c`RY-3o81E}hYnILhwn^dYTqqDbGGjmq*X<NaOu{~mv
+T1QHXmlPvff$hpa$l{L^Ir}I5NPVwQnt-{@jZ&2_jfjig78U<gg;6)0)PQjm2@TV1gkII$rRdDf~BF;
+1MT$W9&B!%P<3o*do5R%G#KuAQ6WfEM!Vl6o-2CEgGH+H*@cNHmk#y6aoB9bw#Xs+Stdz53~5dQp-IK
+=h2r4IGhUdDJoa;&cA=zoNxZjGycfB%-p`(!)tNP0^#-uITPo;=Jya<^+Z{d6I`pHZP7DbhOkC%nIEM
+|l50ed~!nS0j2MdZWz8N!A6^Qf!ZUeKCwaANt{khWEzsQOLuPM<9>IG;tUnk2nYQ&&9m6Fg%;^XJRwq
+&z2UnwE%5hj<^EDA4WZoV0vh$?2LI4`AcZWR?O!$41Wjh`V!^GQ9jq5KO^~jI@%~bO7`*ktV7hi%P|S
+D4AJ*J3`Z<MtV7hik8;Ek#74x}4=^0D5mEgirbi4x%tO?J$BghqN6(*Nk_+EWfZ|LFhVw{IZ1Bwnl57
+@|MTWuu{PXwe(;y@nzFC;uH7)sv>9d^j9nL<E<L}aE!M7BMl?9R|tSm+dF}dg)_Ftke2g+%M|Ff94Tr
+Cdy$NJ5HGzSC7t)M4^h3lanT>UrvAL^qzEG#tLC4I<0PM;4UDPYI{S$SxBD+^77uv@+Ucj<YE1xnG9^
+?#o}k9j~Z*U0dHRDPPDLx%~N9ptnXi#Vwu&27P^mi5uJDWHSagbh3*{6ekD2G7`;k40Ouwo+Dl7@$P9
+TlBkHm<pkK)>6}<P3Ay~|C~PO5({s-o<+{(PbG`d3nQG))J&$!1pjBbgwveFwYqix(NHsl<v?7jf!2_
+nrM<OR;<|<PA}?3H%5wAT6g|Q$hRMb(LzvlU4U377V%I?`qmN~Jiy@wk9!<()*HIciIm;TB1<#(MJWk
+=0Ee3-#pJK4h)@Rub%6Re4;hq>CB|nx&Sl}Bx+s4DwpfSe;dDFuU<3&eI*PCUloWkkjuptH>5fgHvBc
+dkKH1ygVW;Vy>WEoTP!5X|NN-$WmjV3)+KHXr;$YBGBDewokOJo*FAd|sEp;$h_hmp}FnoI&7L!#iSJ
+%daH_P>YbmcKyx?^fBZf00moxBGjfg+JFA%botDfB5H|eudMY>L31zw3>gn`~U4n!SWRkKl12fj~A|7
+wfc!C*Q_mC_tewtpV{zi@pBuW-}J(Zn@e8W^77VKUVW|f^=;dC?A-N6*_*rH+OzlVcgpv@``-H>eE3n
+t{*MnF{N&TmDi3}Buc|M;JY0RG=IF7nzCK=i;^a4{zCC@W?(Dhq^%uUo*l_9lA1?p+)6b1pe);w4Z@>
+T1bnVZ-uHU%XOeB??yGI*OwU@U~+je)f_wC@<u~X+RUH$Lu*1bp1UICikeeUYpum6C+fkA@?2M-w<GH
+m#Wk)uZ69eU50vE#;TC+PIaDXE6E^bF&|%&crvj(L&AYO^oS&C6dhZ~lGvFGy-#{=m{@4?gtoF8{wf|
+NpfA!@?sbPMSO=GHU9y=;<*tVrRz1C(N2XCvon*-2bi1|3~=$e?$)`IsX3X;nD+2jz85u{B!hx&gK3m
+<yHQvTPU+1(;p)9PVgr}Df4r({~s3_%k9elX?Y#xR)$C}!x9CR{5ezLBMK~3;1dcgQpigb@-l_ILLrZ
+enM{nPG!hdQLri)T#lU#@PYj7cSfCaD6P(JUVkXKXW>ju8r7~_96cXZk_YC&@i|4Zyu@rF!Vj1Ed#B#
+*<5f36(Bi14|AYMfzRX9(N=!@71(I2q~q6V=qVj$vR#1O=hh@pr&#7M*h#Q6&SsfbyKHpBwNBE(|EQp
+7!o<%kuC)rbvMuJiRx$jKKto`L9#=#QvD3`7h;)FH+qCL!h_79o}(mLpamRw7m-)*{v+HXt@4HX)KP(
+OyJfM1RCUL>*%6m#+Ggked+;5Q`8?5z7&)5$h2zBQ}Zr4`V$e#v;bsO=NnGi6p@D#~ec{NyxC1$rdAt
+*W0KpRi96&oFP3Ro|O`aYvSK9Ji~4g6w=EA&||kCn+oUOWJ5BUuD8H*hy^g8OojZX+OtTQJ)OiG%w$H
+2jl|?ECKC<(kqXk-^_F~^&ceRHF`dqw5&A4+G1BKo(7_&_Ko66HF1r;c^gyT0kezI>pq-#Uhcd{+Ihf
+`r^RVgQpXoe&`t+fxsYCNcF-a;MgEiCP(9kdW`6!Bv9Fv_rhK?{}zU=uF(zEAe`ol3hp+?Su|5F*yfD
+rH%8xx@M=~J~xM@QYbUY_2;xgM(=!u6S4!icQjq6iiFIl_3pG^T63slZGuzJVk&JM?T!HH?i=ah}iO@
+p4XOvkp{lC+SSDfsMt^VB;FluR=K%Q$Mqj5TW1BwC2nCSe!!8|BTb|Cw}n!jq-Q_&)?u=H?_l&p4($*
+;}%4=i;uhTaY<|!%+4G+jN7Y>CG2+%4<o#>#3FLLr<0-J(^U9B-^rd-{2L5c`sw(mkwfzF584y_je%U
+U;eRWUn-%0q$3teZ@o;)91pfp>sbi5ZVIy@BU_U=H*{ItzHjeI)C$MpJJ4ls>=yw~x<^6-0mux~V=3U
+5X&c$4j8o8M7^hYk{A2rCuTwWk@F}D+fT+HW$A{Xm;b;!lsRU~pT)*g$z9r8rvVx3+Ra<T3&1GyOYF(
+Vi2*z%Bzb!!F4J0dScF0ZRZF4mD1BkzK|1i3%*QsiRYTN!eBogZ?sj;;c^ST|RRT&%mSM&1i~EpoArv
+JSZhc?0s^$QzN1b%dMn`XJUtHlbXsTO?;V7wZ<)$mMmK$i><Of8^rEN`qXiOAJIV);)$GAB;Q{c`$Mv
+@}bBhk&i|mi~MfniO9t`Rub}ikY^y*A~z$)jiX2&avkyl<YCAQkw+jeLOv0BG4jdCOOQ`NUW#0-b1Fk
+V6?r-GX~-*(i}Sn^`3&UM$VI<Ui+ncnI^=VZHz2<kc_VVsvo;}r2zgZp{`&z*bO3eOUm*8I?uJ~0+#P
+ulwl5FlAt-NyT!-8fc`R}@@+9P5LXP@;kegB77I^{kb|Qb|cOWl8-X3`wa$n>X$UBJqF+V?{A9+XQ)f
+m4M@;c<5kvAgmBK&t2`v>7a<aY}HA@3&qg}l4)7xEs$AIN(Ody)4N{y`of>_@H<{z2Yb_y>6(;UDC83
+I8DPE6R_&pC~`_{-XTI2Z-{Y!~Q{(A9;`{Kk`AM{KyB3@*@vMo``%X@(kp|k>?>FiM$Z`DCEV+M<Xvq
+emC-R<e|tbk>7*77Wo+D4amnLZ$hp`u0D_b4RU|vI^==K!;ps}k3b%Ye4?mt<dZ~wBcCkl8~GGb-^im
+xeIuVL>KpkqQQyd;MSUZW5%rCHhNy4kv7)}~Igb<djeNGKZ{%}CeIvhD)Hia2Xz$1~Mfs6uiSi>~F3O
+Kw!W)nx<nGALcs_d~FG0B%@-pP!$SaVyMP7~E7kM4>j>sF4cM>;17qCA-?u)z|at-pH$U~72MjnZLEb
+=7eT2UV45y%UWXCf~~F5wMTDROt@<;XpeS0eX9UW?otc?0sc$eToYkgLB#dy#99XCe<lF5wND4!Jw>S
+md6_laPBMHzW5(UVywU@*?Ejke3L1ke7-4@dmF#<d3{s<d3{g<d3{j<S%XzFJk`4eUW!Vu0cK)c_?xT
+Zx|zydm&Fm?u|S{=trI>^dm16`jM9i{dhxJCiEk(5c-i<3w_Azgg)d=LZ60nbpz@{?vLCXc_8w!$U~7
+!c!L=!(j!k4>5*rM^vLr>di>=^p-7LsSfoc@D&pe}X1R!uyi&wRUMu3`0APcNkGx65N3Onv@ke6$k$W
+KzMDC3|RK&*{)JP#mo+#wwu>3-fJWt4VSbiZ#UMx7?kd_J_iRBkO8p|&@-aytOcVCL-N8Sy26LLL16D
+PA#0K(SF&_g_zM&gre3O>`OqC6GvG!6J<Z(ySegpF&^BaIjlx&91{&qq-RNUezcIe#JQrO&_gFri)(a
+x-!>#<yU&1@&cMK3052wvt7Niy7K*M8byg?1)B^isd(8d{G{rPZp-nLY{_pF2?d@;8=kkJjT;;d$Q3E
+J*42}(qsA@OlQP+R+MKV=A#|CXy+2N+lJ-mdeSi;8*&@kpNaL5E&D@{+=S_}FkTMJk*;f@G3gqV#e}z
+qV5svjLeMXC9a6ab+>^q_FDA+387XW%MuhwvlFH;0<>#JMw%Wt7)_|`DnIeyGq_I^VljY~AG?xElS)R
+etN0Dfm+kr=tS;&nn|0vlWBU>dBMK^w8hl%AEBd0e(i6|G(U1lbamE~rZK3vY<!p39b<oFhrf1I3u2D
+3L(j!)Yk_1`p^F9IGW>!<CJ%7s5{IKC4pa|`1_pPlhoSs!h$w0sj~c_tfQa@3cB**{m#FN@_T{A*z4n
+<VF-#q5cepEI+VJX-c&8mrGJ*`CF$zGlnMu^DW2RG2)HM$ZGv?`2x(Sf%I}>@Mvlo7p{GE|-mslie$q
+BaivT!I!Y~4o=T2XP(LIoFbQtuU?xh*INd&J4&`Yo0W6ATuv+Vo1<Oubw<-=KV~v}r^)R+la+g#d|p`
+D>auBa{&wbvS-1GX#`1NvpJY~Uhh1j$x8Uil+zxJ2$ZdFjIK~f6igIQtxW$EA75cJS`sp%HVdb0xElS
+vv<x-ElA8}~l{RwSx+;hBNp&EG$TZEnoM^E$BbB=n<X7v;!`&p0n&P2}plL+~I;p3|g`wUobiO6|>5-
+!&Z?;jlLdH>*$o0vZ5{=vr1KSw*^rHfV6D?hIt{h0H45W#$sh4Bn7=Ra>};j+J-+l_NN;kQXRV#WP3N
+p64qdL60gcf(}6xu3%1cE|nXs7LOn2)Q1d%XzE)j&cgSVzETru4wtZ;daH#c5=I-o$N5V<jd`v;?)0G
+T<R+W>(gOpHrzWnYK-SUQEopx|LJmliu@h@p~<Da8Sr}MxIS52>`lh{3cIELxgGH?ewgl5E`DB4a>*x
+FmZxESF&=4^%Xw=)`diAIAh#cbq95h?Oq9#-tk<<(xn5WMXUP3J*E`jTTiJDBlB}1vWYIEs`ngW!<@M
+}(o<=y?#d{vt^zm{#;_1T`^%N`X=kce?`gr^Vr}l4U?LW>XezcQ4+;4MS;!l$6gU6rdBsa1ABVFQ0$k
+%xuKTJ{Iv*hyVu^wF0$13DA74;bIR6Z;7&ukYS>C_Iatd&G5^t;Y0(eo++{m<_g#W=C>ORQpCU)RL>B
+IIJ;NgS~#uSK4O{3LQS@;8weATL2)gnTXX66A-Gmm&WOc?I$s<kiSuM_z|~pRgDCL1FMU&QBrrMK0=H
+gS-lP2=b4FKaf`<4^_;Y#G?Fp<Qd4tOkR^>UZ()%Vu7-l#}hs-Lb<sAD?z?Y_y_qrqI{@d-hT$=qFsu
+4KQYW#i*nIlHz0pp_(L&o*o1P?j>SBom`7Cq$@vzMAM$k~K624cLy^CQJQDeKk)L87ClTeVk&Agrd4C
+m@i+LF_Pbu%Wg7TM<7b5=xc`@=G$V-tQLSByiDdd&N-xdBu{)zA>@;#zF$iEi;`it{w;V<Okx*mwULX
+-#jQRHIYRm{sqqWp;P7xHg~e~=#+{y_e@@CWj}!XL=@3x6ONo7t5k-zxlpe5ddS@-xC8$e$MeKwc;Oa
+h>z`gg=mfDg1%_tndf&Z$$Z#pBCjuenONV`KKa3Y+qs?H4o)tUQMT%2Q5UoSl=M#NyWTsG0Mey2r&;X
+=E+M@F0LD5o^y!sC(6Z&0x@qc=G7}vz8-lk@>h^IAm4?&3AwnAt8Z}rHgbRD?<22M%(DifyinM$n70i
+@xtMnp^ZH`mKN98g^P^&3I1%OI_x<IHdH4*JzkxgtxwtP7>juQSf<lyw>!z5e78}MCqkJLqM#VgQ=?y
+VXhWRVjDU_pJ%-f1}31ZzsCCZ;cUW;5j&xmykVqHT6%EfhB%!7-0^d^*x6)s|)Tl^+YeUtM%<YL}=40
+3;zuRt!=Nr-h64T^d6K#ac<c_?!6+#u%F#V>>+Q7%@{h;;;F-9aMC(~*mH2V$K<2FlY!`H-&>`W5RA3
+Q?Yoycqez$i+PRc;uxhe+;>phaZc)9OaK77wZbdI?_s%zaaD@7aR68Ah#oLLN1;k#5xqQPDS0!`3B)H
+<l??H5c#vn#kv)-t|b)ZPa+rV6vVoUNR&S){G(V0lZbM0A1T(oh;=a;C>Qs=dB}@Jd5}LL^dsMlycBt
+<;EHuN<tP`=>tbC^SLBr_7x%?todgb}lUkHNio5~&Ysj0BFGj8={Qh<ma<NWFtn2Yd`8?!e-Hcdg6Nv
+Iu<e|tvL>`I!0P;lSWymv-mm|+Z{x9T($UhV1SFAHCM)`bEJ{-qCkGvG+AB*xK|3LT)`K!nqkw1rAtV
+<H>nA8%NZxsGPF81RQ>u5#@|Db${(63mB6N>Ux$i=!DvCbzF<ps#aIvTO=ClTe#MR^qKtTIr3Kk_`}C
+gfsWl~{*Wi1G!<#k!wSf}<R#P2_b}8sw!YPev}*X^C}R<tR@=F4h_0G!m&q`HR9n<PRVh>#W4OtR|G>
+_G3h?;yeerKXS3|FA(`T<e|umkVhha33(#&-NK*9w+VkD7we)5k(-h8aoHvE^^!lw>gD?<&XeW)AwB*
+Ac8Lo&$kzwXjq>v*=L_ZXa-J#ozno{u^&xn^3(r>Amm^<4IA5fYTW{g6`fPIh;ymA}yh~X5>HjHC<1N
+nNSx)0SeEdFH*3ai(l4XDJ@nWN#A0LlOW@9(bdiXqzLB4O~^E4^4pZU0My6h)DZ<8uNm-2Bky?h_Wxn
+o^#D(*I5aN${UyA<3mb3P87jXg1+2TGUkV+{DaVY>@YmhCm*@5J>Ap6tTY72GJ>$N56Jo(=fBX;=Mbx
+qO`4<nnWFm;K545`{fW<aWr%Tl7xl<Mou|!c*ku2Emnb*Yv3hxj`N$5Zvm*)1B<6JVS0boM+4TiJY6{
+`s3W}R6foP3T{#Gd>3w&ue+Sv74pSS`fSX82e-SFhtES9<^1@(VVZ0&pYKVN{ga0MjKPIF+K=EFE<DX
+izs05freVJ!{LSY<9QN^f8pnCb=Pe!U-ue8Kv)qE`tuxP%^XK!N8FK!7o=q>eUp^0Ll<!0MJg8B&htG
+33%E!4;ZV!AN`a-$i=JRLivcLFzSEhV^WGea{G4CTn_`3B>*?vAhmMQmJS-2yFP3DUk7wv=3`#8==K0
+lZ(_eXpl%aK1HEzWl07KNOjZ>~IBZhzUhn}D!~&kLL6_QU6e9PNj5lU$!B>^~gwtuFn68QZH#=2`6g$
+db8@>9@FWvuux;R}npi;NpxIT%3`7p4uYY!{@0ja{I9=?BVk`j`N3eM|n86%H`+t+E%$f_`I^!DLtP*
+5E=v*8pQmFvwWdKZgR3n%qKYbBG&%1<ov|><9c0n4tKsDTJgGVZZSR&ca6VT;h)6{f8?_E?cn(?cLp|
+vzirqbICuuTzGTSU^?G8%`wEN9Z7%i6=l$(+e7;V=EY}Zj9rj!9JDkIv%gg8W7t8kX`FDpse7=D8Csq
+Zwxp0$9{0!M1&a>tA#kp1PAC{m$a%FCJ$zML|eG>Rswr@)C{hwvxIJEBjA8nJXHx1s*#+mfL?c4s**7
+*mn3{2to`KfzvjPy8I^LW}**E)~Q!m)GT6GevggTs@LOOyI+?Am|84EoHfQ$6Fkf934HJzo3sll1IL>
+#6LWKUnAuF4_NO>VPdNpZjn9x!(gvzA*oMCNn_${R<2Djds21=7BF3wtYWsc)&eF+*Fh9?blSZX!g{P
+51jObjMfe*RY&aJwzOOCHM%cX{p$1O!AA!8{IK-E`hGj3=s<w3+qWkZHdlS5pL=Ti_W7T+o#^pfdYAW
+)#J%y(Ujv_9o3x$}Hui42>b<U8*Ss<N_03b-jNU!%zPbgc3cR=7Y}B1tQ(9fnE%Pqu8d5`}hi~|7&ck
+1YPp#MYdHuwA-*F#Ue!Z~H)_HD4yH|T&&N>m~d-OY6`bT@s)6Xy&gC6kjaW2+<(8zCx{xl#q<+(+NUh
+Q&e>YBhI>aIDasBWe^ske2*`|EbP$69(_`|8O0f$x1WFKxq+v0J`b_NQS-{OR21w`j`ZuYL6C_I~T9O
++W8WmIojB>uPnMxY)q<@BI2p$2lE4g`Zk>-#uSHcjw%u9-&W>uRFc<*uLCXmgsN3<F`=n1K#V<^U3rB
+vo!(h$E+Uh^}O0>{@_EyV$BZ+`#=9eLwaYESLYW7{W5$}$C;5Ie!1nsq_~IZ)3EP*dF%gBRoJ>eLGEi
+Tvw!-{>z($UICsX<-Vi-4Ft<zH@7W)(i<o)%&@%&OZ9n(*fbU8-z4|5_1=3BezI?T@@UDkG$@WgnasM
+ddz<t3@k?IaV^_W}oXJF&iFDAS)<j#^sU%&tOMB_5abj|mL+1>K(Th|hDcK5z<_QDlUcbV`-=9oPzPe
+1;mdh(>{8Es$v=El0G`=04|IU{7i#68db6t?{B1D~rBuguIiv8CVQWlt`Offkhd*LM%!`%C+sbJlm*T
+R_tG4%8g3`Q-Sr><O>*nEuWer_C>%93R%@otV$77ZrD`KVCFOH{;xd?bmX0r}zKv4R5wh%&=M8y=oHM
+zWT5J`q_^^++*SXtB>0kH%uIScuGmwiyrDj+BWZ&G*lkGIIH5%v%4osKbJkI>1*w0IkNm(dHpVr&Yrs
+Du}fy$xAn^rVdrLKXSeVD%ZS+*W_R4*@7d!&1U~Y^hNHP-qk8QM4w#||-MQh&mw&GM=8MxYk5y#Mdg(
+sn?v>;G`YxKZ%$Ja`9s{O!HO<+Te0kf-K0kl^*Os^Ie?Hswmk-iL6cp~cTRXV?qjjfu+^J5zdMsvP^Q
+b!(&Q9;N?;G9cV}tTCo*$lh;*&Rid*7H!hsW!$E-3ixjU%&uEY(bXzG=?0+r4k@k{)<<@Kob7AN3m8<
+KSo8YQCyn{MqOuZD*Z)y6A<^HkSTtT0j5AjqSV&OaHL>28_AhA@ah`H7Rp_FaGP<2IKMmT1)+&$F>#C
+>vPYDO?J;E)7D*@5}bR@wDF?Or^~^nr`q~9F8HNG)`5QEtFIk;VV#fljit>Vj|NAS8SR6D2R}0BRo|Z
+js)=sNXBU#o8x|JU`d%phqVkhjD}86ZJ-7PUhkqpwTT$+I=cH)2dk#&%a|ih(;9Ny?{!0ai#vTcN^HN
+iv?E5#a41J*X&ipSei$BfVyzfGOjNAHpiT5=xT{<>DD`#2#^A}Hyz4lU0a_-ELt3Pd+JLq)c>2Ze>n<
+w|_ymU_KT>HiT@#(o;Q{MURhXvj@&KvJ(7%{5EqxA88!+wuwAJF@oh<j@{{MLQ@mOCe8(D}O5o69~N>
+V9Zi*^j@SJsI=TTI)An^_za0k=|}|=hwg9yZ84yHiTN&eH`^e)w6>ZJToD*{qJwB({#E!@5q_(Bl}PH
+(RQA5=8aVgF8r3e`tyq~&x;%CHh#v%a5gXD`|Z^@uSxfv4d1hC$jG-|&UyKZ38p21d;ZAXKdrj5CcUn
+ybXWS=Lp$G^U76+c!VAxk{gLy=uljK6)zK&7rZ;@E=#$<(u6Zq=G<9L^w&P2q&#E`Q^1PiCj;rTmdb+
+2M`Cf7V(30xkcK_(d|Jt6{Y2X_(uix|R5B)la42t%-!|kQ9<8B7Nd%Z9>G2+GYt@Y!rAOA9WX>qb`ZT
+sGLezWWCmxt``6ua%o?e}~iK61meub(+1-8}khO@S)Egw8=o&u@yovh&nugLjS(y?gqn*6Q@^@7t6<K
+eOo<w}V^G#+8h@%lG)})<-A4d&2LqoB!kH=f|9iYlz!@A?B~Ho<m=q{^8l<+r4M}nEb>8m-l_yTbFi>
+Jly%E@9gKRei=CQ5jN&j-!(V&uiuU?8o#*Y($G%J(xR`97;>fj*EQ|hcQme#wwAW<pQP(3jq@&CRMk8
+9mAijFbaK_6Vef^9MPK_m%VTwAx#V$f>5tFG9n>F4-d20^@zdXrDA#8+uK!?TRmX*2?SC?uH5lKH4Wp
+NQ`r^PYSG^}h{d)M-S8`vz>%*-p=547OYVjTQ(8L!$EbsVnY0U8GLpw*j`2M>$cPt*>J9^0QFFI=Xth
+;F*ePaH5k3QQe{6@E`$xYveepmCjr?Kl1Rkxd0_G))+-*+JACv}ex@pVDlKGrQik=rzQ{PDAkiickO$
+}452<=Z<;-<W)F(AQs{QU%@ocJh}`_U$-eXU$#j-1(mS!9i7R-ue88H>aGM=Jmqos#Bk=nfcwYg4qYw
+lqL=x8Q#l%b*Bp--RyY1*`s}aO8Sk_U!^UMJ-aWNP6q4C(z|&}H5F$)s>fRWzL_v&^ULR6*sVWzDkbQ
+B_x|gj|H`c2(C_@m`|LiQdJpaykhHL4`IfOYE3M0}B%L|_`KN=<7~9<aczNF++dQ52gDL9HoNu0d+P=
+be|LBdTPlmlyH2Rb9z{)lGyZWAH6Emq{`!^PT_1xfy6WuNrY#B2C_ssG6Q7a-|znDMuyBmErn!m35`S
+9l+$G1NDK^93p|JJFPS4`^CmtLH-)>fIY=K7pZZB@q(l!u#APRyyAw|CT~n;o<CGY@wA=G|xZz7TWer
+PzztPAz&U#dFZ+p{HNq1H-;6Ke&I~?7MT%hrax;@iShmSw8s1KepOFyLRB&i#-;G)-TwxY4xw3e_k&9
+YRCS2wO>}f@u+!1zzavSgB#lVFYB7K-gy7n!D~_@?|JE&4t4EECXVa6XZ`Py13sA3f9a5utL-I41!Ft
+D{Y`LD<l*cG-Rt{4CnlTtp@OP(gZm(NFCw|OBa(+7k=pnZRhwQ!<=Ky@)WO6}J&L$_X^ES6BysnSBkn
+%;5%;!6;?dSlJld@w9(NQGkM^5MoA$d%8{ZE}n+}JGXNNlC>Guoq?C2q>JNirN&cTwpON8XrWv=Aa)h
+v1W7fRm#C6f1@`y}sfM<ws>KS@5_y;MFu`l)<+(td<Kn>N6e%Xa`FC67r&7v7!}Y$%57=x-k6^NnNao
+XW7f=#C#0XVNV{0OJv(VkQ#TqqJfzo0ckGv6*3_?KOrW-fu8G9`+W)n#Q*oW<T{VL(c&pGJNoO1;v86
+XFg_p(DZ{mee)*_S8o4|$?uIj#Q33KKWF@pwN<F+ONRdY4pXe?`*Jmt&rd(Xc-X)i#?Lh{)J4B~l!dR
+>A7kM=yM4v*gCh({<zrtn`SE*>Gv4$)!-5eTYZ+fZ<ph)8^((`I%bQLzy?;#nhVkh?Fs%4v?I{+1bNI
+I`-NIuGb>X(t4A=UdVeu2+U|15@ua1RlEez`{A2KZX)$1(NcOZdb$#*X@)GcV>;UUA$G5z=FGpxH*!B
+BJD^E^u*7{jol?rDZesuK+B*7mGNKQPoaZDmMmFEZ2w2VG$DYncpnx}6M5R6jAS3m@{Gn2wZ>Z+^{RS
+`aW=TbZsZ-fzv&zW8b3=6RpquYGQ4Rl;CZqBbPnZ_JVd$=auvT8%sB>$R62-Tmgme$%yEmMq!#{;GM}
+Q?Jb3aM#EjZLV}Q@`k5L`}@`Brkoj`scq`<%hmdUS=zbX&qP)}=Bo_}TfArX)o5+;h_|l~ElJTX_R1`
+L^*cT4$<)TpdU@5_Ihoq)``%bod5>P3`laM~^eclly!Vma?_bQ;rgn)bUSrPIjvo5irAfwF+LQAdI{t
+o6qy4?_fIW5ZjMIKLIq-t}jvVcW;Rknhdj5WG|3xuw4fkbgkIvnFcFz86ZStnC7kYV&)qWfO?w?(H&(
+}_wcdcL5f;4Sx<daeAjrVGE7fgP0%6Hk?o{#<UK=;?~(<VJz_E^S3tv2=NvhVFANBey7Un~4PM`&w4y
+mBDoha~MI^WVDM=8Xl~j0JCv|L#hR_LW85{)%{ZvUbCq7~Pp3S=#%PPkL`#uhU*We`7;*ut_^|?dzAm
+x|*#0aDJ8PP<pEN-pk{wb!L-x^ywAhAAOjvosjoKw>MWNYeRptbnUtFUhTTQ0U!F#NYOt1LzkmxH)U(
+X559h9(Cid#v^w&)o#zs?OAb}ezwksX`XNO7(E!zZ+OlkIaoMJ_dGF}8ea`IL-X$kWo7^MpxnJKhXlK
+R$K3AKWsP)@%_WQw+aoTbDqkg{UPm?w)Cw&<0Kj;cVx)ze|b4cfq?N)<j#PA`h;yo_Y4OXi@-4LFWmt
+f2`<k)Rtt%TzQ=VbOwOvf2CWD-0zTiC9m8usL_VJk81xW6jjO=7a%rq9w$vRLRV4osS8z1@_OVW8>wN
+c3dAG0TvuvE^uT%m$OjkY`A-vsYhWJDz1?@4*0hn$eW1(VH}SGek^<G<4S#<6^@QMLhPVgfvS|Hl*Nc
+?&?k0N>chOf=MKi%^i#R>{xjAztw6wf1kioMBz%esX57-6i`ifmDHp$qvdd;DJ{p6%|(ms21`DDKMKZ
+C%B=>Q%}GqM^_i4fZK>cLqX}GN<Zu4K2o5>aK}!+vaKtlMEVqd_3(Bbn-_u=vHEf3v4I4!_5Wc6ZMzL
+eBhK=d-{dP5E0O<!Qt$<^I@$dXd$uZe1Ia!(vy(u-zV7aB7j(Scv*fi`F94R@e22D<y#w_+Sr^gUNcQ
+SSCe=?NiZvjkZRt#k`35#X<q&%}B#l|)B76N*+v%v}tv=V9o_;tV#XjcR1H*1C=Sr36(Mw4NTreBt|R
+Xw>GMjL+}g+`xdgAxrGYPVX3CL2vd4W`8dL}EqzbhKZZ8$>i(a!mB?Dk8okAF)d*eV0y-9a01@vgg<g
+>~$orYFaXS92=c-ZnX>89Fm1-<+*QqBsgWm_2(LG8MG}~ZF-AS@ITAesUBH*F-{Bq6XoOQy|b=c{GDo
+GO~E;i#%`si%}SUY9NKdI47h6meLD#&1#Lx&9Bz%@djOO%D=R0LDyFGhGV9iKt^1^v_Gd}A(+an00u7
+6yM>D2r4B2K|{=mP_FBzH|HYPpYgI7=A)`N|iIVIbWox`_`B7N}e>m#3snij(N5zzf7*4ffW8oCawz+
+XiQR4Nx49T%i)UQU7RltM<=ifx6UMvyhCT;B^CDv|%5L&xXMl}FPSsl{;l`0ujkzvw89X}Mhg^oWa}7
++<kzTf-CMJ4LO&^7!$s-DeG=`Xa{6p9Pn8>-^bp(&f*OwdByZ?O5kqjr8?93$pOKJ3lOL`sk7K;|y5_
+z11*3cl5|$y(N2yIaSOHA0v*ns&vill!%0Ay7*2F&y7QDhCDi&t?orgq*da)Z#Em!j$J3Qy*hYU9^9Q
+uqzRhJ5MwIb0rX|dMWF83y5b=rAt`BeVEbj{5pfB96C>E2hguOv1ASe?*iuG+m#`?7R-*``fq{xJdNm
+J$Fn>oFyTC`f#$$QJx`f5DJQ81)*jhvkW6QEKT;nCuh-TL?rZ3MWEP?4OaM72*;uS$yBRG19h5C-4ul
+{a=_g%7NNoq26UvYO8*JrV%^yS4RB`#t2GJU1aVF^55S$7rBmxb|o6*L}n1Vi$8zLf)1Y#kZaAzQ-e9
+;jmd1ctF?P5uz(RM%|j4t-Ddr)}ggzT8d+dBTJ55U!rSyO)G^2cC>qf3u1-_y9L!gaQ?brFtz^OG@7m
+wuCcwg^E<pl*61~o$!y2o}?t`?DF&HkGNN^2&!Ms;r#jYT}auTX8|9tuPBfnuRmY=gha}lo12}&b<W}
+UkPzRqm5)@a9_3+`5LO1RIHwA)SV^_^uRs4I@UyxK+aXTRdqDF(yS)B<8=_Nt5FM$nXX}*JXCJO7!9?
+d92w`WJACss(86?(sKIIQrujmT_bipZmj|g}-Zxlb@D3-ye!ijr>Zo0M~vN=DJn5k}-mi7^ecS9c!m(
+x6mOVP(EZg=?JmE~W5egJ&$!@l>a?+xEO<M$yXR?TdDv`@XznHmoI;IozHA5MQ4qf^thXtWrftegczR
+j;DsylN;e0bL<?5S`mO@2Q`w4?RX*Gq~RA>)*+#PIt7^4|U#y*by-jaUju!g8govw>`A#kh=1*O80Qj
+dKW_12Zi{bJydw84Xw+Sye><jE(4&fKFt4)vT7z15)GdnPw^gH&C199Hyi4!FN@D>Thv$E8H8lPrwY?
+N0pE484h}x`ZP!A&anr%C(;e{&;d_Y_A1bGFv=1r?gohg)d@f@=h@<vK8+*1;rm|Utyg$oPra{mS{h5
+EcJ>Uo5J6g!644wxM&T*tmCb9l>P4-#t$;W9M7UxO|$l_a(4X5W(wd;9Q19{T*;L7u>H*3!h+e4oq<P
+rF2p5``qL0Q{iS+$^JBr8Xy%lT8a2I^xiArmo8A$%`!;t#X-aI2jjM5CrBW)SFQ{(1O_TwgTh#9~5{i
+XHxVo#^~Kv2&#c+ip<(RPgNtW)n{v2YiYX??Jc8!t;L=$U>;>an2(kUoDI4S`X2$LH)s}5bW2K(slK&
+K5C*1SwWtP<pUr3o_(~^MTcew_yj&XFir=Bj>esYT;J)?p_GU2qVFYk$lDQLxf~)+<R0+P9{!zTTkH!
+b6SM!>hig2KFdqfVI_K|)>l=KkQD;mm@e&Tf_41G-o*ylrBJT$JW1%CCb7vHd^RTNALQcW;4nB>jXPB
+al>Tkgw`1r2p^08FMYF8b{K>o;SLPla7f0mD{Ej#K6sjYM5a|G&nz0>(M7WinVdL9C8ItcsU&I+6Iz5
+|=SbNIcZLLPgO?xW+7_fW`7Kz7PW9-xp{gKmE(xfN`i#M&gcZ7BA$cOwQNjzS#H`X1g_uYvP{U0)tOg
+f)2n{CJWCbyfK>)%B1Zw@-Zr3qRsUb9oZd6|g)V=TRzz@oUl%S=UMEW9V<V&K|k7FArzeYSqKye6EGC
+sVt9bmiJbA&L3&1Z;JH|ZsD9;-&G=4;gg8<4A*JjLCi+p9v)_WnrnWuTWE7VI!GkcPm=vx1?8&X*8;g
+*V?ej3Q$LnNLNsS<yu}r3waB9w^5_ozdsp<K$fI_!L@vW8Z++|M$MvCbKO6!&FwREsWk23`xtwpb|C~
+4+$_}4$jQhw4NH@a4J1N>wH0aF;ag;Gw*|&_8NY*Gx?!#N_4{Q@8QU;%D*;lRmVWiZ$ET)yZj&9+8Zo
+zHx7!7TsZ41}M!U(VvK6P>*K<}UUHR%PY%Oa<1$GcG9I~4W35W*(2Fh_fb^WWFksU4=f$7<-la;@3+7
+twX_CHyy9bVbK6@c9Ei5^qB1J)~F-{e4Vp=|jQhj(FY<f;L6h*3<7)-T?BCNvx*qHt8)SMC}|u2IAAX
+s<WrOoX*bk^7(luZ4*vyRtMpaz(@BCM|z*CMjy7pdrApzo*~?~4ZV++F4J3S0{7Iu@R%gQJ$QY1J-^1
+#@D#+Wh^$@$9pf14U=@2_tqpR7ErGBKcwQ}c3M+@Ok}WMiz0>C%dh|gYgP4G5Mtl%)17ay+IpQ(I?-B
+n*^c{@)5r-p&Bi@UcftZI_gt!IqZN!6!UnABd{(|`FFpQ5_ins}J4PqW*Dq<XBC}J-}cf^Ci98V)&Mf
+4uRu`l8n#6-j_#3hKU5H}!hMcj?}KH@RN%ZT1X(T|8D5p{@hi1#B}5FbO_gjk07F=7qkX~gdl{X)<Wh
+=UQwAWlS_jhKO$hqwxH1L8KscM+=)zeYTV_*00Z-7@>p&l?bT1iQ+kk&i*_kJtrqK4O+4UA1b8!4^*k
+VeRH9Q(Dd(a>+g3V2j8xS#z=s5jIO!B%cu=Lp&fn$}tr(H7A+B5}Jg$&!n>^Ey`*^8=dHh)!Q=WkYK8
+VD|CuY$O&l*&65q4MjK6rIi!Z$mC7U2-%o~Ft;Tedct=={BMV}qai`~`+OycZ(&$UZ;K}B98k%6pHuJ
+1WgWGg_mdzNRZ!;w1%rT}KA~N(A^13vcnSt|V5Km9jMeD6LHt9vkdv4J=dax?lqPOIS!4=tKj^1d4RP
+jbrdX|A3F)5F%BoSFTRs$M5jh58OelN-+>=ui`WSeNTu$PGELvFiN_~Ns$)Km+bML9+y=scA{E+FKYB
+ssq{wgF=x2Q51#`f@k4k<6evsVC^W!pV5bX!3}hRD=B9*=dvFVkSk4nZ)g?Sc4(c;e%6dSjH%m*=~zs
+C0LBP&M}%&b8;u;%^`cqMEVx?oO~Wc-cZHnSe-n%lGdtBXT?v76ZwrNv{InLlUZexwT#CZvU3)*DvUQ
+9Qs$5uQoPLq|Dqs9d}Q>Tu-GV;d?Igeu?7okLZ%c$M2_8LgErcYmKD8>MU6@&y_`Z5*qhiPkX&LdEZ=
+G~WYa0qFe~#Id?U$jj<?;#M;ooSNJv6Vv<7FH_yk$%q`VY^nKoWXMRU$`v_W3wU~`RooGojXDHps0?P
+C~C@6@g~Nsf2*y(l@qk8iW&{1(0!B=PRP5z-`DO2rHK2zkdX+Mr*od@&y(3*2t^);>RJqJh5HU72jId
+z{{AHOK`dWTAT;IAAiHjjdIjsbR#g%^c9cs*T)vtN+Op9%2s5(fV?g-lENk+(kV^^~B~FX+h}=1aI>E
+SZ@Rgz=CvU4F*A~iEdCmX70#H_MJJ4+~0cX!%V61W}}I<8uFq?f?N+J^t)USFHt7f!)D5u>JOZI1ZMe
+*uJ2=nknL_xZ$boqocCvx(X$dla;3@8Fj${Kma*@XjTS2_KhwE}g~b^1SkN5us9Tg3EHS3C^B7JkvWN
+O6EFzYWXQ}oXlcv+}2bjlVY5z)YdWeoLAxG~0NGR(O9CMr8EZUFkVEsr-qE57KoCLG=79*YPnnU)e9I
+tMq-Y4WGXt8!{1~og}o|a~?Sm`1zM?KE4+n`sWwtk6y3NPVwR(tVKU(i3X?{NlRF}^(a)EQ~K6?Wil&
+d~_|@iBbMnc(LJ5%R@-nwqp@&Fr9egcMs#BWeBv8T<zhmFB-^x{K;n{cWtj(Lo&V+5Z32@ptbZQz;HN
+JpQBkG~*$70rB?sc9Q?{37-d5w!6j(9xmF2bNl#@v=#Nl+s{+}yXDFwHmc?L<^$XxjR$exoXWqMKW^n
+H3FrEK(XNQUOYomQd|N%ZT+{0D-)`FfD@W@u=H&9$UmW@Gwfn#O_`khfD31S+Hxo(a?sAFT3RjAx75O
+WABYzb)0(%KJtXjUg?m9)?g9QvrA^!fCPrj^aMgQ`f9Ce6$|6%+v#J3^-;Vt!Bx{(W88n(=9HNNh_m)
+N(N9`HGN|49v5aB|_vTc_ujAFVxIca4x?5Au`^*l)MJ_rC@o!s9aP^}YB142R(7CSG4};`P{0H};w4(
+T4o*@qgz5z3jvuD&h|q3m6GFxTlJw0)_&b0d;@}0h0hV9SC^>umEs9ML&3Q2do3!3P=~z>;S9)Y<riA
+EbR<IfJt2l=>e$jN=RS8I>3SfDz?$v6M!Lrn*d`0cK{Xu?g7+vBjkNR|6X(tqVrN-FTSp)5qWF?-TUs
+mL^K@B0Bh;GALwuz0h4;uz0A^74S+LM2Di|@gtU_kZjt?H`Z`hyc!8W%74@fFFE#b2Yl@Sl*a38_&@@
+%#K)81Uzk~#V{eX>w2?<siRGOjSC*ZZvC5)rt!|9$<1w=i9Vja<p;5-yCk;*Y#J(8~3sUv}a84zAMii
+g($)&h?m&Fv}!tf%~L@CTqKl&%ZWONpU$FHgNx5=!^b)JqMaTpwMe@-0bLg^r=~m5_c6-9szM-FGbAD
+-_BJ*htGUj_$QlFBK!wIf|E5M)%S%Ito=s8p7z_ZFR&qoRI4fzdD@T*MO*j8^r>sUmaj)sa{H)NcVoz
+OVty(UH+4(|LTZ&65VsbpsE9GfcQz1AwMZus+<D-wRFj?Fp7|B2rrvP_ufoX6-0A;8USN^LB7*zy+FO
+iKobE@*O>eW`a)*Xy+rFs1z>NfLDdvTf8$;+mBbTL2=S5<=w3T|sUm^y!Ivy0()A!z-z;k9St)Tg+%p
+4Dgoortz}h*qJtRvFiBPZ7c}a6G-D|3jM9!moj@FSvK>q+0@x70bk$@%l^L7@wfTKAD%ZV79O81J>OX
+@Vb2WG0O95Evu>P3|-l^O{d2w0v)+ofL8Wy3X0s$&~E?E|bZgCA5WDz%M}RLCzjm#)1yFEt^S<bmH+=
+cI}y9P5_Sy>azY`7*laXo{-fL7GpRs-ghuQ*}|LewgN;ELA*A_wYO~6+A-7Z}dER4EzlGb&u1%a#K}J
+kJI!9RYf7k!j({;;NR+19Q~glWGOBG6Lc@%Iw|%^S|8^n-5Of&(7pgmseCQnJM_GiQN-I}31A(Bmp{e
+ME0yolgfs!qdz$V^Sw|`X!{B^WKSM~M2F?e%@f~0uT$jAyJfj=w-Us#<K2Oizi>lfe=w29lDe^@^o|E
+cTb(`s4p!HHk32o=elI|s1&){FcaiFJe3n9^ffm```U4U4(mA0c~Deo1!mtL}@ewFGqsPbN=`PECcfF
++R5|20DL0ClBszEb`=A@czXU#EMhos&wp@pjU%jqdSS$2N|w0C~v{y5=HDs@_5M>m~C}UfycJda7p^A
+@04Qy#js!{S2LejFOCQd2h1wP-=XW>P=Eb?xu6hbtG>$KmUq$vv;mab-Vd_PdCn`{z-a^_g@un@$<Lg
+EnY7nd!WCCd@}a%cHICN2|RKyaJP$YmF0w7YID)ezk;7Pc@=b>8PpqMC15PXuiH=CPl~GSV?wUL`CD=
+j@>gAQtN4_@8qerfQVD*7c(sS1y}4g<FZ_~_8zj9=;bC5`>T2*O$mybnNz~pWv>lz7d~0~V<{DaW^^)
+&Vejb$q_Je+@`YYNmK)rrV`!l^%{55UAMz^BlG+weqH=bSuXhy87rF#QH`#VAXUN1GB;PD$z(thH+RQ
+e6o2l<{N<RIA70N4On_AT`DeW2b>Q+twBbi>-cv>lzH@%2(*9o<t$FBJg}hIsyG3GsmbPje3Z13cpbJ
+<rao0>7j6l_VtsE`{(iz*B%B7vcH_SOEAwVB<x)r*NIByn)7te!PL6Pf4oUOT1i>-^2A5;)VVI&-^t0
+541l#FV$Y=?I`d^emzL~k?!RN*T0{5z9EQ7fOhG;s_tj#$Eh7xc)OvK=M-ZB7r7bTD}JN>#|2gK?{K|
+`>vDAy?T6Cb3jc)qmD1fx|AO*DxEb!wqX9E+K)Y5!zt&9aqmI7M9<Dp*RgHk_Xg@AV<O3*&P9>2<8sA
++aE5T2V9ui3fUgRkeGhn5cL>>W5^pQw0<#$M=60otoMD_qS`AQ_TFVu&h1pS^~71>dOdQFz90sBIDU1
+y1O0*vh{k;@R@-(O<&UkKQn_D6un?xO2)CAbbiz4VkwKMDHhUJ_hypq~$r$b6c<57+~!yGw$0nIx402
+E+BBwy(tcg^Yd@oY&{2@_sZOT<7{rqyXX<4uo*f=RZhd*Wr@E64?adzQGdfe+mI#g7z0UM1p>xj${Dt
+hjtw}RD$*e*WaO3FI;y3D<EA+2;9Q-gZ3CAv3?_Dm_+I!oUTQo*Khxk67<t)s%k(T#48*{_18&(qb0H
+xc+(ir(~n-?;gkSO8V`N}tkX&)iOMHPq!2JLLL%z^aNjjiBGG^ilO-|^FeyqRC!jwIoeK5keyL4e47F
+3Q(#@ddJ1Z3eCPBQAnG&=YxZjAQcwVZDqkgEDLK46ZkZTg5UI8nN60rehER<NkRRH)2*dLiGvFl?4;6
+ZAK8OjM*2iOQ$yhwt6Az2k^k%&9JAGAwwoxSMRWastjzgS}JKVvb~2l?ho&|fA=X26}aAI*pM0qGi+N
+bJ5O;{obV=r;fjP!6(Gf`0O>RIprP=e6$&3Hk@P&O9QKOQ5&$5s6)AiyxK9NUG;Cu;2YVmH%pq-5-TK
+A&~?Kr)xd#0Z!K`m%x1zU4vW&NY@Q(;J${gn`{gB7gdOK{c0H?T^F<ou77lWCJj$TUWm8@u^Q!#h;*G
+E4Iha}*J{!5Jj7x|x^9WuL)YtsfIsP)6Wf4)I{NL-_K^&MTRi%+dbrgnpo1_)gx!wQJzWc2<9o6(*b2
+6?oxKB~fTnK*r2AE<;Z&jPi8X-q0W%bkuFsB@lzJrg3%QII!s))i1ucZre2ZHMr$^Z>1EM^jqLuLKR>
+JFA32$sA{MJbZ9`4&pxTclxkQTz}dvtXw{(FH2Cwb_ja85hflk}L1lsb*TsMo?d=;7ez^(ywvBM$#}f
+%`gm#pkrocJRQ%DtXT;dK3XyJB|Jq*Qm%cr~K(Y+Zw|6f0c-nq85%JLxzwkQ>KtPbLJ4E(MareJFn1!
+0{B-zii?ZMYp=aV_U+q8Dk>_-@#DwI&6_s~4q+6q$Uqt?YfIKv6|^PoKg-QM%;@3fpRX6Ry`G!9bSaJ
+Sb92@8!_8HHfcUdUy3ahwAuaIST*?~`S5;Lp&ZZ#L@ZZnP*VC9hcWI;gG9+&P6nXApbrVgWmUf-<hiL
+q&!)a-UKSO?<%d;T-I_04MI>_k(aUSCOInVlo#jmP5{3#FkgXup*^XDA$Z*E?FxQdzvVbs3shp(Lh_B
+)j``&V3FRdv1UcdCQ(n{o4_Aj0)5&=1_>{X?AwZmK#AMM$ImQP=KV-tlKX2Gm6PjYo%fh^{&eF`l6AQ
+eS_4<FHU3f$^p<4sY$Vql(3)9|*r3Hm<n|lCya+u>Z@K6RMi7A1<h1@eemQ-<b7L({(1M@xi~BHZ?Uf
+G4nrF(ZIzteic1xxtQr^wu$$V7UIFh<a$8GLv?Ni6QBtMIDOpUBNY(dQMK}sFrIU|39Wn{f=_b+k>KM
+7A5ZwShfhE=ZRft&*8i@Zj~qFYOrJiT#K*^zB}<mLwDF>%BC>7UHnL~W9@fUc{`zZj;lc&Eotx>;THx
+8hT=tG9t%(QB4>Z4>_7QpLqn|%Y%giAUK^3Ka)ZF~gM?WlpmXP_-ProgA8@@dB;)Qw5&3~mWJ9J^ztX
+UtWMUUJLxFB=tq8ZK2dlxi6xN^Wp^JXm|4>iC1(cW29-@Y|e|3l5qKmPGY8DXvX0YV-O2x#{83}_~9_
+#wCXh&Z13Y0v#ceWYW4y8Y~FzkdD5ph1J+UMPf&A3vUig@uu*s3_*UnKNgS*|TSpxpU`|`|i7sJeWF}
+q^GBog$oyw?Cfk}u~=CDv258g@{)Z5*}h~vdF#Qk<l*#5<cZ7(vOXt_Ja5sF_m+<#I}4)7#^uT6onkZ
+jbnP@!{c<J={IHn}{<xV8`?Q%%IM_@^ecnvQec4Rrf6+`Ljy02MC!5L4GtI;bpIPUc$-IlrB&DvIBwu
+bO%a<=FD_5>0>(;F!&p!JsdG5LA$fix3NJ&WvdF7Q?SpAljm65%B_p-k1{rBG|M-P;d6<3<c-o|F~$t
+RzXLx&ELFTVJK9654?96NT5oIH7weEaRU<mU^u<mfNW<m}nAtX*8XbctO3`FnEyS~F>EY$SjD@ds-w^
+iU0jD|jp+ZJ^Pp;iByg?ZyXA_B-GN)-?N(@y)}?yylrCzj+ZUZeB<BHor-ZH6IcEDd`01`#|~-NIxFZ
+M??C#kUqVU?gQU}tb+8LApI^#UjgZBAbq`4`u;=tZ-MTG^fpMp2GYL{=|6__M<9JIq(2Sm&qMl4kp5>
+#|GQKAq5a|d76xs79$aVspZ2Z=E~;wlA2JiI6tA}{ndOKNP*N~o_+)q~kR<AjDC+_#3MGi(14|JfH?h
+2g_jU_2bKVTh44|1(nxff_o}!jgS(0gyW>P+)wAQ!&duHQdLPW3M?|c02uI-tbbJpJLz1H6AaL!zg<N
+1oRm)F_#Z?X~Y@2pVGAca1kq|mWB3Y}P^5HFJHybAu0Sc@?{ColzL89s*Ld93<WhF{3=Pc!^_hA(6IT
+@1gU;g74}+c@8Uox#aUL3@Vp!0_yU>Ny!A%^wsR%kU2~{1XiS0>f`%_>WZZN=GGD>B=_SlXE72Hrrv!
+Ue^42&Y-FDLkbPbP-xOq3e9;*p*5Qn+E}H~z9TAl4Z{y(_z4XED8pwnd_KdQ82%N8-@)*2Gd$0^<}kw
+_XZZR?_`7+8dwGOZ9$_VqVCE6_@CaY>2=$#w`Ed{_XD5+zehw)=ts&*-jig-IM~(1zFg)HF70mFH8Ga
+hW&u92NhF{C@7KY!<@Vgm)FT)>Z_>(GlPZtMnWB5B5z9+-?W%#=pek{YsGyEKeU(N6qhTqBXpQ_-Swg
+hKW{}dJ$8WI}fd`!@U{(gOW`}p)7-*`48G&(9OJUluqI5;FcVSt~nZ=c@d$M=#Wgh%md{y&O8goh{i_
+rnF_$7@{YqhrD%qJw$(h_I00(2#_?aY3IxK0RIMqhhon(IH{sVGIwv2Hx%OKQ`eKlF>2IvW>gLyKBP0
+fzA<n`}EZG8V`6LKRP-pI6C3ZF1LI0dA`8UbwS?*h7S$_a9DK09bLNI?mRDW?CqmrB%>O~Pq^)mUAo*
+mMqJ=8F6gNNd{{WnhT!}kyWDxN3$+RTF$2RV1c$`j7abiDozM*f-0t1A>z{79<(BRfFayrVh{of0YjQ
+yX*nsn45iwEG(J>J*J(^s==Y9K&@k3+6qa$L%W5(Up?Kam1IN#52zy!rPewdg-axGyrE^zTrj6Y~p46
+`^UB05G8A!d;LXZ#bw2Wf#qG>_43+_)}Xy6^>!=M#qAl%NfW;0f;I^LLFKCs63#cs{IC+fG3p10$ltW
+0=e1dI%!!ln=HK9vKpHPn%9{1A`M{5@MnvTv*EY<|t8NLqfv>ZuIDIpX&s86%`)Rcs^l7fLHsQJUlu_
+GKN4gCOViE>C*X-;X?xlw{PS5hbTT77RtIjWJp-prSl01p&=7Tb!^vm7=H{)!01uom*!6h!zB|(-Fib
+iEzXApv%1RHTuJ`0f@yE=+;L(;SWNIJ)-^>@kMC@eUY$q8gfJhYRHre1xH!$f4<8&hDyr#er~dHx;jD
+;J5kp71omP#{tceO4>2_L)ZrWnpP7_rwY3P(2T+4|><@L$umNe6w&E;~HV7Gj(<vc~^bCV}e7Wqg{^7
+zKwqbPf<l9w8x6lR7go0ml><uB$a!>c%_U_Tdmh?Kaa&YU5ekIz5<ys~cHI%WO(^@?7vS4<|8$Q53B<
+rR?+zW(~_B3JmhvPfCS`9?YC3VZhKQ9k_eLy;RCJ9<Ppdi1Dr?AS5o<jIrDci(-d{P@FZksF*lcTV~B
+*I$)2KasMLzwf)C^0NUw6;W8qV7n}s#({1j2fAlD&{>quv{@NMJCsROrOcrN${ISXY^38Hzw1@-91u~
+c%kaS;WGJFowO7mV(F{M8;pZ^?N`_z0@S7O^9frRY=l+wY{3lQOznZ7W_wsb>)=k{fa=UnuP&e;B0Ra
+JcY;!kFw{G6udiL+()v@DUtY^3T`1R@I+b5v2SEqir^7n2%d-?kEwVl0s1o#K|E8Tti`vu(DA)qr~(D
+Bw=@9N&Ok6*ye9sKTc{h-nK^$+m$yv2`U`u(Bft=+u4_7Aw()3ZbSwry|e*Qryt8*l2?|IV8|JK%=^u
+O7Fx^JwQ2fOcp5wiy3U-ZymNZ#Vbq(7wGt+gHy%ceLrwXBp&9{?7CJcmJbrFaLl5fBan>&)?tQzqh}C
+Pk%vQcW$`Xs%KB<9Xv}qDavSU;<a)0%iVnFp}Gdw;{|Cwoclv~j$5L*MAM?5ZAHUQ7#80*sd`)G((7>
+kyW6$gdI@~-I=|a`^ymSmqT^9^ecQKhkLM(_XApnth*vV<(Ij|Wk>vRGYHeKO-g2c2T@8Fic!c_EHf-
+4N0LPter%#{$`up#{|Au4F(Nm{R9p~ebvuDqq=5^_@!-o%VeEaRUpYibU@E<*TbbyN{Z`U|@T_yN%HT
+;9D5t#qbw{Ks(t`WTI*fL0C^PW0&YVa^_{P~VUhYmf<>uB1!b0>ZC%{RpHlnx#|hz%+_a^wi{`kQc`X
+&{cXpV!sZeap0dxqtuumv`;jwInn&6wir)obVbdJm$Ew3m3?>gRA57t*&!;{TUuj-!&~QZE!<F!!L^S
+6}zp)|90m0UbaCzi>B-F;luj^KgLVo|L(i*(rd51MvNa-R8$DOj~_oyUw{2IRaaNjzJ2?|b%5a<0lyz
+(m<<~@Zd|-|>(<4bvPCRkzI<XvMn-skets<H)xZs}wDs@Wwd>$jt5!X9&pr2mci!RQ;eHtRYVkjF<_v
+Kzv!++CUPGCO`6o`Cpvub1Mn3P|yO%!s<P(7>%SYgj&$YF+^x0>hiSM9EcFuXkk#+9u4?q0Sz<PIq$E
+^G1mtW||AAdaa@y8#(_SIKk9pSlt#&t~RKiJ-eG7kBGy;}S^pTb;?9r()*8f1q|WC#9|4*6MjcUoj;o
+EtmKys@i)N52;Q-+c4U)htIJ)`=CMVfXIc0)Obor=NZ*WboyeUyAR*5jMd#ERF{b91tD00eRpExxsb-
+^WJ;!3H%{Lwts>ge)~<{W$0}D{R01f5$D;4@3|WM&!0a}9EODc2L%Q7g&v~={|`R+fVOShMl5sUoLSf
+~_z!u!^Ugb>1NW+`Dq$-%H8tWhXn+rZzQIl)BjC2>d!pn|iGn{Q8uAWNz*|KAyNCu>5>0-WsN^`&x%1
+}_u&s2zBIYXmckI})rg!h&Lpg`fXMYKK2pWJdcn-dT9>@Z?<1=Lc#TQ?Qj?dsZ_zira2cQLbga44R;X
+9)6gGAc>M5Fc+4S%0#a23<Ahp0c((Dw}@pVx`<4-;Lyc=4qxqkaj0_VtY&_{%P3A^Wx13G4v+^1v5F<
+7<e*K4$)d2A09F_lWLc8qyCDoxeylV;@oAj>ghNtMLEnr=Ot9s|ODr?8CaS0yMB3en$&%fgS<J=I8+5
+!E?w6dISB3-{m!%KxiW4fA42b8bUuJ8q2tjWEzID-elA`@lQQK)O&l=zlXUJ{v0z%`hVy@$0I^_mx<J
+K@D;LvUO_h`9k6le8T1}@A&;;Nv?*T_-N!UUv;L1e<fLItHPMI<oHPWoE!@4E$ZzM><Ilc$O`kq}hO!
+*;VQ26y&Cvl}znp%7|2U7h066#=b&EU3HVPU(CyHVkBAABqQ`DOF1NRp%hyTw%|4bZbnsm@0yQHHznK
+Vbog$oyG-)rm1yeOJpoD)pX&(;bg9{QT-{;!B8)e^;khEH7f%sMk#+VeY3dxlTyyTfVE1GYPDnmz9Om
+&2dsyn4uxAwKNSR{($Li8~$8d+4=09g-I4I`rts`<tm~!Duqh8$&N=jTJPYJ@PHlgDx6kj}T2@oFYF_
+*)wQx+4Dg7B=)I&*eCU58hTVXeJi)6&EfCk<I|}B9ODt^e<u&vFXDle1?&OeB@Muz{T@}mFr91*N0Vj
+27&0&o>zM|$B=(;VGY#>K$DfZnX^{2|8l*kLCk=X=`TizRKhVJZ*SyB|UnPe5usQtM-wXX`Tgyj21e=
+p|NLoMx;=$!~3;4rNzPdDoN}n7>B}{{vY0%Gg;-7VzDDfoIP)GE@ai=}QCq;jD$(})jv}e#D?HNAFZ<
+`qACwKf|XNWJHXEk=vAiFyq&Dn^g1#Rn+5wvO1NGg3|6cuMP4fDs)x%v}y=ocpq2~5M(Z<q#^Jx9CjI
+pl!TCk1`rjL*_1`7#Z?wl(XQ1pb`guO2#ds1N5TD}X=zB971*(14sr(t_U*Yh_-BbBMRd8PHzO9YI@i
+M$ks4!ND|GnTG9aXVcl!-?qxxe9LsEu}p%bJ-c!Y-yO~44}T%`f8@xKeIX0kVXwd&xB+)b3w%HPJ=Qh
+wn}}72ZD>1|1<`9v!>c(XseI8WvNH|t_WV!wNo&$VX!YZvl$RPt%V&nslIh{}%)E!_i$m3d26c`x(3N
+9c4uAIdLjM_`eBceda0E`k8}<OarA*-C)%h{vFKC4RznM3d-e4Lkn1;=ZnFh86*fVG_xM*1GqM-mZJQ
+hkTQ<#Ps;gmByLePK)pEOdHV+?((dHsjaKnz13fo`>0$!4<=@*>&QGHJ<9e*N`Vs(v|%b}b)H+m|v8Y
+zwb24P`EShELMZ8%ygm$5LTNFg=&9rDtb_&@)WKQ%u7$reQJDfaacK{N+IN{s;K8E(rZ+y<P!Yo_gvj
+vfJ%~p4QMIX#s5AzE^1Xis4krG;CuUggrA2@JZ61b?lQ~$_%C#GPLv$rXincc$#VWE9=qH<Zyu~d{T%
+i$9Uyr^Zp<BOZ^`;YE)m~0Q~au@)~Jyr=ulWe*N_#eYxvJdTVtU?OYy2+g$d%NoCI_7Y*xNH2j_QDF5
+*gT9xXg0Zrr>9G@p}U;mAWzwar(Z?{9{9DmnLnlvdoJw5$h;0k+$4dmqH2pZJ-btReL2%B<WV>Q<f?I
+~@{F<{SsbJ??7Ycc-;{*ZlSWF+K3#l^)U_d+hSYSk*5KYxBB4K2~pl1$LxlQ!qH!k(FiX8g?M+U?*|K
+|#ST_MPPG>q`j<31l{#32`|qD~smNolC1%uNHRw`RAVtzk^(;Ia+`>Vgq~?av|iSSP!7Vp7&bj(ZyeQ
+y<wc+XwNdoSnIOq0=9)K;lF+R_D-DZ{8{2ZV8DQ3GiJ<4pFVy1N%o^c4hDmPCQh74Q>ILzzy0lR^!)S
+B({s-~C-A}g9{7R=!~(<#Ne9+2paK3AdWcwvIrcmgPWy|1|9N`XH2+eLG2fYEz@FigUd)aG`d3_kjUG
+LERZL9GQs@us`WjyM4}JC3SM6-W#OEkGJDb=h2;c9$_g;}By!F;wLLY!TaD|MdUP*a?KIk6SImqiE3)
+ll}TG%toL2b{)Zub2C)(yx5*R@7@MvNHo+}gEk#Xbn;cG)uJ=H^mdTpac4)r<P|>qneh3tWH)Y(w2ag
+Y53KphKtR*zm0%tbdfY|5eNJ*_mS?KHC<D(bj*=q|e^lLg&w&JHYa8_5MR)VIi$pvEs~{HEU?uvSsHU
+dgvjVHEWjOJFhE+E`bKv1?U8Bpu?RO>_H$7L+=rzVJp~=z&aAYAxDDjKua@?$^ZEa@aSsye*nz3tINp
+9IP&C^PyPlxA9&ya(P7h)hW`Eg(}D#Hgd7kv<lc^?1NZ`ex#x?u0gkW-*a+;w-QE$i)oTx|pOvfJe}i
+p7|5=yxOP4PF2zDAB9ZicCEfR774ZuG%G?e1w<Hhfg0cemNG{|)?)?&!7q4&TON9Yh}Q|lITDqPRL<n
+O(E_a3%+^X6x<hPW2|p_}N?CG0ojH{gXm=Xvwy3HuET3nQ&oO9KZE6mr0Mz_`=VoNh_mkVohd`~ma|{
+ur{8`x}aQJZr1#7Xp8#d-bqk!+e;BD`3xWyzz#h0sO(fA=`(bAt@<|CQO(hbjxHi3H-rp@Eo6kH|zlZ
+2frgXh5jJdh8@5LU=tV@KA3U;jmKHx?d`2)xf}NE*;A)DYd-B-i$CU7=RcCK=vXfTAC@g~Zh^asg*~v
+miS<qB0Adt)EMeq+BK#<L3je=p(<Uk{Efq1atgKAHf!EBZI`(akaEx5UxbNoQRw~ZAM{DahB7Z~v1OL
+zVn2+zUHynWr<PDo;Jr%h`T3VX$t!(QezQNZ(zoj0+4q%s%3G@UqfKOKEL->qwAtT5G@to<!lLz28+g
+=H2cl_15s@7q(ZUZ;a1s#GdtX#R0*k_42t!}_gcEG^Tz!#xGf3PM(2kxM2!-fsmW7OSn!wpx9dn5ib|
+7U)$01eVFHb)2e4Ijj@TdWhHQ;4<A?CA^qAsd-PpsoYGhc1EVu%SZS%zyQKZ-T#C|KTItW2`$ZIAV|e
+;fEil7hZTl=(n2hvg11F5_BEk5d(m`tdDSByZ+z6UEr@?|8nffhh8EEfeyLf5B~vQhj^r>1H9d`WedI
+d;)_C`r46HlZn-y)yb0f-GqQfbKC`Gzn>POr?v41X<Dxo;QRg--$pl@e(+POch3i2Z@P%%{cY+p)JLj
+jCYt;AO;SXHczJ&gB{9Yl~UoFuh_dI3&4zj^-kb|trL1yqps3o8V1zLbR&v7k&rbYbK`#*9m)sjq*-y
+{FQchu$3p<6iq>tFv8eiuA|y+YrCKkR_@(R3Yg7x=69KiN+-?*D)W#7^Wd@PE()#3RH`@EB`O@E&rI`
+@4_>zQgCk*TRqSnnKhynC9z^yTBj1+mfDNPT$qO2<PR#1^5gaq3f(izj2OG$Ff3P?RK4UN5fm^|McJ7
+F$eB@_;(+*CmQ8)aM`(F!9}GV{T94nL9L<$*E^5=={g_VxQ-sKqjH^&9&Y2S=FN2-E3XIsOI$~C9z9&
+gHm+kk*Rhl9*u!-Ub{&_vj^sRg;Mnx<b~MU0G~D0Q&ehv0E#!*W@8kXs_w#P+MSMp^#eF~Uat(8NbM7
+0+F+VyvIe8N2`{C^KaT_*nJ44Qm$JaONDaQW1foT3wqR4~J8XNY4QB%0*O`?ZCBs%z`z@;S|Kx_B5ZQ
+Bm#wcQ-H=?3^S&N<Jqzx|f|(s%5aKIQz}z`5;XoCD);81VilAI>*U&phU=lVL9ub-q!qz1)w^5bgbeD
+0q*U|N9o^zmt8qk>_ks*VE;_CUXDWmGl3`{S5ou1MD|n$H1tWqTYx)7wRk66UScc$7hMEe{5B)w+H<6
+vSrJXo_p@OIN*TX3F`;MNBDKbBKT_LvdB|#4xiDc)?KO>qQ--IC-$^a-@%?dYHU}UA8P<!gQoL(;W4?
+s$2u4DB98`7<eCS0le(c^_Ru%ZdLL?Ko9mm~x@gi)yXk|NUw!X``#lff3F6nO<DXK|@;I@NneW;IeDo
+Ai!U<>Hbjnd@-B;c}pw>s!hfrr6&Bu?M>SPbZ6kfk3ah@Bez7GTPM-B{J5P!C<O%r=y*bl~@yqq8XFD
+IOJPt@ClKGryEZK&};A5o)1trK;^2j3H*RdRmBabEAIFJ8R(F?GFL=Ce2=w=T^I6MKo+&&58XdVbViQ
+9pjbO&_(c8VzcFs4+nw{oio<2RT3TA9bzNz5Whd(8^u)3FCa{e(c%PCur#pO>uxe#<}TZu&ZV|*rktd
+bviLWualD2u3a0a#shOh&v8UUy$yS+s4rkoc*_eJSF9PH_=PBwaT&AES!;t$px&vTA9=;Xg$vV{ELrl
+Hy7mejux|ohpkaR<wI+wF-iJC9_CukMs4=0ovD{T(S~ShspI??La1i=feW~{CKEHb{*u4e}`R`g8Eb3
+jT6=6>kd*f0cu`iDL3ThLg#^suS@$_+GuJI~;9P@rt`6DM=wQ5z;OE0|?2V2B?ANe`x1}@+Mj{A+NqH
+c(K74}tauD$IIuKEIO0`(Ep3Uiag8+m}H_R*-_s`VeX^~4iTq_h8jOx6dmF2LFjJb~{4FV5C|Lht?~R
+@4cwKV9zHUpJ|20(GWmTy?S~E*#K=KJvT|b3go3Q~Q_eGuR<=es!HiUAqIHu2eHRu)9puSWv55!8qi&
+YK^M)JO79IpLyn)q?ccQIS#cU<m13YuB+vJgTMp4fIq@HG}LcPpSWZb&FP~`*P8YJ$gvkKT9m$W<;pb
+h;n`=O6@CwX7qJiiAG!d3Ko>E$y5{u#(U0iV(SvLgZu&SYq_I}k()@@i*yq5WE_jUf729ItUb=fNOv(
+nbcxz28)gSwaPJeaql0MG8q>t-z9>ny`#(y6F204FRT-=wz!NFqR6}9Qq)Kq%<>8Hi|4me3)Ablm|1K
+yme`;<P^KTfYL4-xkQNPRRc97mh}nL#Iy9VWU={xf#$*uh$@b|L7<$;p}h=%bIm9T*r$k3asn*ayzf&
+lh_aa_s}2;|TuCdmF(I_n3@^G5NavtXnPSe**>#xS#D_tOF72QI|n&iSsO)I(4d``*M5D?y`|_T;5yB
+!{ff^mjA$?`H#6d|2TnKBKD1=qN2q9D{z=IXO7@I{DG{INF9)S$Wk9TPF$QdYt~HG<t)yT@Q2-4^IvI
+A)dRd@-WQ~#r2Gpt9_-QIfB*diS)jhgak;Tx0KQ8-l=q0pBgd*=n4eGbSQ~hKeoArv$;Oph54p#WF_7
+DV-`LBA4q`7Ibq&~ux{d%Dz%Kv}xPTY%+whsdbLY;T&nm5}Q3(5Ay?S+$UayanYi`IHILw?mll=Yt>A
+w5!6S&EJKUp8bb<i8>FK}PtrcImligT^dnkM`o{Lk{`%OAsd*po-hhtEN6;gLrk5jAGm1+GN{59A&%@
+@3Rikhe1pFI~mljq|(jVX5~d5RWo5Glg%!y{d9w5%L1BK{tHzfddCDS2?$sAM>!U5&pk9JY){MapOi>
+zka>gD~4~xo|CL8UgO+ie#|4|FLVj?${ZZFC+m{H0Xl{n2lk(~Zrv*H6TH^B8|iP&9w___d>`aoUS1C
+UJH@<Mr8xIbuC?KBO}wtL!@jQM-!9uO_Q(yc^=R_9x9C^;n_cza?l!_H&hGyFm8<x>UCm|j<apTQa_3
+kd!!~T#u-RZRoM#{Pz1eL3yTxK@;&<$J`)M9yc1cNz_?@r0(P%VA>2$gs4u?a?Q^qjJnQi)@8XonuUA
+uN+pY;NdQOo*w7IuiWG4!>R*C10qbKVCP%=z`YqhhG75+2t=r;)?Sd`8+7d|AS`&NUPA)BT**40*dre
+ykt{V=ma5Tob8t!K72pHSpFSe;0<&ao+;p1Umw*^6xvUx0`6qY-esb&9!#I`Vs3_tQD|U3FNiXTE+{t
+R;<Z^JM<s(7Ux8X9On$L!PcF1j)Ao})?QfqVcmyyXArMDk;5RT0^aajXjsD_Uwq}CbHo_xcJhLAPY3%
+5ShInDkP~8%ya#pLQxPKHLcWJw54k3CU930kFRc<|V9gQ9ctCy+KKP)hbHj&$54C&rv?X_pSWhB%N8X
+Ng1J+K9lgEoWrW_%%GGErMTPN~C+#`az8e|E5anHr8ca@90fAO@&oEyZx3jT3i5Pl0aIov-WV=3CkoU
+wGG_JH6g)=+;<74x5!@`vuh*F#Ss%gK``3!cJHLzZ9cHqfSJ<Hh}->$C5rcV908{Hqdv$BrE$SCjYSz
+;7exf;`|))wtj@V!2xXalMqkyeA1`Ax>g`#3QT|FgE-$$NnX1c=&1Hjd8#W)QUh8Vm9`Z0E=}tV)vds
+dz!$a<+QVhcyU+SxVq9pm)Ep&^-lQRLusdIG+yFqPj~{G2i{yDzTx?6Hz;@?0iGOyr?0h9@b&_H!?V|
+JR00E?-U&}$YwNmFBc8i<lj};2c<Nd^#j_34y*OoxlED8)D3ke9lrmAdkH1IpzvK8b+8Z~X{>}LuJP+
+Z(<uTYr?~VMQ`-bZbf%Oz+u9B&wD(T8h9xYXwr6lvn>B<Z|f>;R^*90m-+(&R9f;Wou@6j9@J(MuMCQ
+ZpulKA?Cj7<`r)hfoG!Xx1fM$;%0_{==MW}1@1-!u7_`;{#53GFY+9XyttJDhtKUzsWX9(*qUJDVX}G
+iHR6&7Y?6uXFj_qvATWdzAL7@#DnRS*mddDFa0h6vrXrw?LMahv36paeX?EI7>z00%b6dJCHwTi|>yq
+z4-bG{CTFh5}e6ko`8y(jNx2GY34T#C(~g{KR#X!zk&pA6J6t^x^R>9rC%0Dt#~?XEW^!Krt|pI7=zZ
+!3=5z3zk_$@W^=p@7y1~-<7GCZVc3L6y76Z|3q8u>^GQwQ-u}k&8%GCcr_IvLPtMFrot-|$chJB<Url
+oQwAs^B(`SzHz5mbS1_b$PvgRhGPfwaPJ3V=f@51CP-{7&gb{L(Mm6e?K=&Xer9w0qyjPJb6^pRQ9Qj
+*h>vIeB3PRpE~HG9U~0n=uujZDf)8#sTEuO=-iJ#|KM*4#MtY&?`kGkR|3ye#pON7raRR~T)ukAP#yt
+mJ9)GE?U+bbaSvGLz@b<5`lY$7ZI^Po0%KGdZjAr22G3HiP1|Y!i~_C(qK%!oOpDld_`H=g)pTIn!4&
+FEwNu-Yz!AcSh2ztYlwJz@<q7E<elYfF?MN4rn9}YzvTl<1g;c^FQtXZ_{xE<3Q11@HA?Se#Ss!kWp)
+lHzpcWj0MI*qs~}vtTa{|YmN0r#pGqum;y~&Q>-b`lwry>6_|9Ua#N+L+Ei<*Hz{T>v&I}~)|z9@iRK
+J*uDQUhGnbny&DG{wbG=!ycv&=-K#SHAYe}?ZSaK}|7M-QsQfaBS)LQB-N|9HQrYNvTTNGQASd>weTU
+1b_D=IIlEUGT5Evhf#fN9lO1Fc$XtToY^Va>G`SasHNYo)c?T5GMhD#c#Kn&QA>ZE<XIVsS=sZgD}eu
+DHCovbegqwz$4nDe)@NlmwP&OJYkBOEOAwOA1PKC5m`p>~uajv8iBusu-gh#;MNIz*u=QUfztEALABT
+6kn9WxMeeTc|}UGC(r54v-<J8K|FIL&mGURr||sQj6ojbP*|*phtJl6-&Rki!kg*vV@iUUmPn>1p6N+
+pin5uGI;Nz-+S-wI#a5=Uf@!Q`Dr=a|I;OONY4v1ky_sG=L2)G09M4pzFx}Zqc^=bV$kba)%1bIrDod
+(Ls!M80YD?-$>Ps3*6q~2b%jRv<*!*mPwji6<7HNyM#oH2XDYgt-wk_9|XDhH3+A7Mb%4*8$${Nb>5Z
+x-)BTt>T&QBMli`2#IQgqq6JYAvAs;kgd>1uR!x(1!6-dpdd57I~K<Mk=}Y<-@-P;b>&=&STK`Z|4s-
+qYZ1@G}G%A`S6|6hpQl&roQv8Y&D`h8jbi0b1(KS{h`GWF1X0W*hTZN3F&RW0kSSSZ8c7dYZgVex@K(
+q$%E%V#+q<nF>u-Q-!I@RAZ_$HJCij-ex~@kU7#EZ%#31oAb<tW~;fvTxG5?*O?p4o)&M5pC!l=X^FR
+_Sh6j7mO_h_b)t&(0ovfnn&4Ly<kEv|)`7wzYf(i}RZ&e*T~R}kC(G84<r>K{O<{TFSqnL3udr5GYgn
+=kR!^3xAIme6WtqZq%wri^S$<V4yE>MeC(F#QB#7k|&$7y9ITf;uDp)=>ESrWBPnL=wOC*w|k;0P5V<
+}i|6}Bo{jjhhsVDq$l+x_f8_DFlYJ;k1F&$AcWt@a9gmA%GZXK%23I=mfzjvz;*Bi@nX$ads83LREQg
+`>(*<EV2e;-SZ)sL`ygl(VK(vzFAehIp}d1hQttvQ}iUMikg|wsKpgt=d*=tG6k3FT2JbXxG|f?TPjb
+d#=5}uCtfhEA7?xT6?`+ad<g2jzEXj5$i~FWH@pi1rD8~+)?SMcGNoR9ZIQJsirirR9hNbnpm1qnp;{
+>sw*uott_oBtu3uDRm!}|G-ZKh+OpWP#IlUC+_Hi)U0HcqWm$DuZCQO89@6ZE1X$;#)93<qT3xIzQJ1
+01)fMoPy<AtRtJc-(>UE0VORv!f>b3e<eWE@?pQ|s>>-6RNN`1AyR$s4I3|<C}A<&>T#2OL}8HQX#fk
+9^|H&hy`4Yh`PgJSezzZu9rGnRd3hB24D=Kn^YiHA^QpCpB^z`HE)FzHA><S{jMY*l`2Q7LRo<!nopY
+)6WzId9|cYyL+f)_>Y{Z2tvNO9KQH00008031s8R{rp!E>6V&0052w02=@R0B~t=FJE?LZe(wAFJx(R
+bZlv2FLyRHE@gOS<h^-(6jinW+@0=DIvdq24PgmHX%LBMn207eXbQTeS~`LPno$rm8gW2nLN(wBnpla
+G=Gr5UI?tJLHfM9xc{+}dEGQ-fvap7*7(gKkVl@R4wk$wW-#O=2cf#Vl_kI6<{76^beLMGT_ncd~53M
+y>OeT{R{&d}Bsxa|?Ii~;pUmN`O8&%cM^hx~o>nhCt?bpp&^whGnrG?KvS@`JFY59*n^USky+G9_o6$
+YM3d+M1q&&=6rPe1$k6E`O(C%B9{K6>lRf1d05xF_=WWcm1>^YA?N_|Trc^i1jbIX!Rc>4s-_@pV0CD
+eu2~eo65ojQrz_=PmTS|Ec^%Sl^X>p5--}9)CI36rcS4W4+_J-jo=VU^2Bp;A0+_bT|As_*9rp#(Rv(
+WWyg*?~@{7^4{5HhPRyJNTJB%>hNW+rmRtB(=2>hYc`#m4bLL8$(q=AlFg>ap#w!{O{Nk5hc)RfXENC
+>Kb(BC{KQHbo|Ru19m26&FVB-^GA+Eh@bO3GM@^=evU#1RJK*oj%k$;H|C@O>Q-+8?(BVPw9BjTaU-i
+vPc}5x|jMbC`&+%8~%elF5Sz$iB)11KEnC8Iqwrk~kV#%|R@g5v2%oUAc%~koP{_srv|NCEQqfojLo_
+_YFFF4zg8=RJs8=R3g`$4Jrgk(3FBxd{5XtPPm+$04{Tp4!Exuptc*%z9YB8B{}3{PmPo~cVgk1I``a
+x)YOCEwN!*u*KdV)+)R;@*3qiqh)9O;YJW`5r0coYIX+TXp9k%oDUtFft@k<j)VAOxkFF$aXVk3(aw5
+h?NeL*_7E>?{ST*0MIE2u5zX6O_jLNy7P9(zpZxLe;kXI#<KVN-mzH!m$BTKPh<JXC2V5V;mBBimV3o
+metgLoi*%UA^5fjTV_AR57|Sm&{h!9N_z;an3eI!crJ(F`JSZtA(wHsrM^G!fAhFY#2mP$kADVhe*wE
+x-jcV~Q97qE+DW@{qk%^dZhv+u@1kZk-UgJxL%%1E^T9d?NSC+(TB{t8MAt{^E7W8Q+MZ#{(73YX^#R
+tR(C3XVZ&GEA^bp6yt?7DO5RH!<Xo8`?s>JL7VrDg!$5ZSiUYDn7yS%f!g)RjHDE-}ax^0;C$n^n^Uo
+SfV&wcN#D{P}HSXu~DQR;r7Fbjh1p&Aw3g--KhpVyj%{4OTN&{DqHg_pmzEJPH<wZI@V+dW>ps!J&?V
+p0r{sgD_$9>ri{X?o02MEEmH+hnZXtXwAyDs{b{Zw+oE|g1A@;<=cAOebi{z!)kr(3z#?c^^ur=2Udz
+>f$_oU2IB<4I9ZGEW{vtrH}nEpm)LHx0`Z)BH*X%xrT0J&RNp|8iH5<vZ8RO3)fVpwDZLZgJekhh^s_
+o24N@I7k|q)w+IxW-!d7mERz#uPYbtQt4nTCkmdn1?3b3}&f6@Fk!#MUp&FXKjs&RX2q(<dJ->&b!r0
+e&F=B4Yo?ym}m3FWpTNG=ewEpkF``eBG%c1E-0vLm!)i(oVRL-SlYKDNon9?tNwW$^mE<YPy~1>z&(d
+~x3V+HKo749$H20W||Q4?7)t@MeUjh3aGd5O5|;pGrGIo*-7@Zi6mMY+q(0<{2jimjLuTOAZ1qsuoI0
+U^+j?ouI7-z&qB(_sk;PoO!C2j%$NK20_-M9vBLx4hHV0u;${```OjikD=-V!!mI%xE8{^{1&QK-y21
+f6R6W{)F{=XzS1Ax=DB8d9F~SxOQSc#UddSS2p_9*Vw}<yBPS?b*5wnGuGkefNi6wqcj5pW<usvcQX{
+-4L*GA!r&zfbYORW=o&Apkz+O=+%BFExSI%reOqju&*$8uz*__#^JKbO5ko~TOkx0NR7{!u(P@%F#*P
+Uq?Rvvfd(eEt!l}r-glN^8<9YR?q_{qSZarl#F!v1v9Ca&$I_OK}x=s2ZPdjRpgNdOhyx#>#-sqMy>;
+!W7ihij?NfQ}@#Uw8iW0M4mATIq}l*xG9?fuVeKY^#S=vnE6^4@>%(E&F?iorYCx102m^=0T$_z_KcI
+TpgZD#U<9MzA+ptUzx-j)QQ&<>eZ~0vK63fr+RJ#MqGx*wn+?-dLCf1MGh&r6p-1<G>*!!3H6?VSfW9
+FSx5ZQsosI%kd&bYD56EZkw+|4AEyXaQgmG&Ah|CJCDWnrlDktVxf5TMixhuYD7l5=TZEFa6yHhl^+L
+%Iimw$)`oT+OJJhE;N5ULbo`*L-Q+1~UL+2>esyk!$W8d1;zYXAhJTo2u^Vb864jvtk%hm34cgr@P`>
+TK>v)QQg8{pV-+4ny8B~1B}QqEIK1En03+&!{Qav!3UbCmMmEr?2?wv)Mn2a2A62ju%6NJV>Y=}CEnP
+wCd>!GJ+@=X;Ph+E@UqEIo=DE>VVUx--Z#@HXeP;7)3nM@UK!WB^R4I~VZ`yy?sqzNvB~w!|eNDVim*
+Rjxc-K#ogl`5H#ok7$t;dbbl=fQ{0YKoor7aD#%Ew#MUL|C(=`Pk@hwEgy28J<su7(AM8=HX+XYwgZ<
+mIR=7=&1S7fSpFRMB<zYLi1o0o><d2tBp?d^7X;La*^n_{3(f4*VyN0rpj!2}yrzmf%%<YxL-1?Lpi1
+iRFe-t4vyXP!Um-iJ<xikMW;1Os;4BuYJ@bvttvk;`#t!e>rdYu2tBqOi*k^zVz=Q4#?=!#zAXaxC+-
+K0G7Ioz%q(9C_c^k3Rsh#R$Ja#dUZEMHat*W2LuI8}^AXcb)`fb=Jfsdr%>Ix}1AE-BB#ME%M88HLyO
+bI!l9EmWA)Qd_0Ir!Kf;#|@=xAN^?!mBfM=d^t$BdZh&wITs0WDKYvv)L2$BPRB{(kfBb(49N>;=EBd
+=$!pL!t18YM)et7YUW&!jXX^9EO_Y7-$331W%WDO!sjJ6_g$&9SuT|F?*Pj94oszPmE1Ljj{*ky+eI9
+yJjAN*Nx^C#N%4nVJ+R?mb1a)Ev5QEW6}L%FfnVIL3ha+0m^rDY%cA~q9Cp9fE-CePC{VZ;sVJk0Qk$
+~Ou=Z5_+@?yK8AmV~dZjl^u|Qx&0x$zjfDiW)zj&Za*Q@yKJV-IlqH{F)^Uw1ov0Wf2dMOJ>=h;iR{p
+l>6`)We(f7(M)4`rE&_RZ3rf8Rs(<nel(P!G^4h`$TsBlH&uor4&;2Vvhlz%lD_D0R;{tgcIUHts`Ia
+#Y-4H*sDT;M^mW&#)H&<w`G5x~`YUh-{zwFDI?(P$=6E%Z6syb>}PlB4q;Gknv6QSq@38BfQf@T{{or
+saTOj74KA8QiS{HK8tnvSv~TG^UmQEu1FEe`(cy)u`v%cMw~BHY~f}4pTm7!uTH@1N?nYRJqfcrdEZo
+t9V+l-kClfC<%t;IJ&58HU<qR&VRYa-BjG3|$o2wHa5N?&i|6l%@O6jI60(5SV8<b@s64Cd1<GC52W~
+7-+}HC=;j_frVwZk{$&s3r`WWmU<Pgr`=mlf+p+ssjtw4Ek<n{8<-ijQM4I06U?t_Y;hd3^p^C`TWL$
+PvAfEb~?K^?~<ldv_R+)@Ao{1!IsWoWdHV^WSp=Pjs>(!r$w3@cN5`T5YhSzUxj{}@MjbgMIhN7u$8t
+X|v&ND(NlsUSN`2E^B+#R=s*C8gRbl<z{i^efoSneCoXfgOP$-XEGUuZ@c~i(<5aBHM#q4h*C&_wy;6
+V>t5)d5^%@Zw1+1tU!(!vGt){*v^zu5XqWksB6+7c-0c&B^h2M<v2`hXsHEx)8MTS)Y+28m`$_PnJ{a
+B0)Zbt+n1@eo<X=$uyTp@AOqoUSvI67J6RTrvJ>P4Nw1OI4Taxp7T5<+z7#Q{c7_&1tv{{nIc2va5}c
+KO(a&mOB$eTA#9TX3LZezy9@L##&}+7X#GS9sAj98@6}$`;6a?i}vm}sRW))<^a>xMUu!wuqf&nxg@d
+zsg*|!H&fUVIqf^BEGyd*(sTyUDb+XqAzydD-jjusqBTt_9g7$pYxEn&Mx2}Bw>h}Qra<fw-)8gsVsi
+~;Md*z2Y?WItB9a@dYsnvdPae3V1NdIIH8^6jT_8bC7IqgL2ygRKH;_tdS3m_iF-VybX<)V%9VkqD4q
+n@y(B?13Ot%yEqjjQ0VxOA9^pz4~AbP98M$n>OkPAbg-}*rK-$C-8PDzg7ypxsXUgs0e^9H)Qqb&ctR
+U6@SGDpgu~Y?ql5`^@e7}6rB0c$8@P<mp>#zY$Js)L0Hlo{g#?YOwScD5cGxS+2arue`6!;HROx|PMt
+Zzn{|L8K0XDr0|+(C4|AB|4<%1HgE$Fx*KU|tKMEH9AaKs=qse^Fi-1x{Hc+1jg1ha?e+31?s1nk*Nb
+cnO2AEBO{!&eiqoAWk*8?$UYo(e-NBA|D!58<U@wq5cN!XH?wQ}j-n|V@Xn?cwR-mHcN8KRB_5w_km7
+{$=_18|bU#U@0*kf)jQ$X`MLkm7hA+M&)F&v7|G^(@@W$?7-hSVszqU7thFn*-OYJJTc8!UQE5vQe5k
+4_aHhHnUnA<!23ETtkwYue$*=bmE-89FMQ{h@|omIW0u#3HiGPhRg$$$;SW=w;<<V+8A)E`OwySY$}+
+dc7X83YC)E(D56G5#X)j^(1H}p3T?-!6QKl)NEBLpfqSFeUs7sd514TeoPvmeRbn-@nboyMn<Qp@)`T
+!RWCyLcj3n;2O~iKV&NbV4q!px|rl_nEDXW$PBZl(O)@?*{E0KtXH%!0)fB*O<eCPSquQI4s<ko&guU
+pmQ{rK|*Bm9i<jJcT$J=kJ+FIFhIw=A2`S3tUeGsS55G1xa?Q{0COPhO?Rq3kHYQ30rB2+YMmi6x?J8
+l&%ulnh@cI`x&slqm_hsI}M+Tv8}m_XFc|VG^gHIQZ`|V$39hiI|;)BX+}FsxQFgKvNGvc;~GU{@Ja>
+IQ<>xIW*;6cxe5uH2`JGpP@z*Dsz&5gLQ{^V**OPjUsGv-T4y4<Cw0YvvPO<g!x7x8mFAdfqlXbcvu&
+$i8>OYRhcq&l-Xn!O3ctyy=?#nAkkAcCJtUp4+^Dw2-1>Ge&onvwvjxByCVZtF(rTIsRw3Y>d~zn(2*
+keSv&S(9PpSJ&XSZ<cG9AO<W;y--H!{K9T$kvP!ua%ATdFA{)Ni7sGnkDFir=2l3YeLui0v77?YP$_-
+7FIyUzw}ezz)r>St$h*yAMr%!syW^hNs(EXk|eX-SsCLoFvImGc!IwHl-T0#R$dAjJuMc1$Q+mL3g^t
++$y+@=4(d-`$7^WT#qt2^poGx^rJ6f+Z}$QryuiVI6WJ8X#B?Qd5KrdJyr!J1m<yoY#YrPi7;CJ?8KX
+O4>$TF+{PA;cSeF?yV<p1CZOQnr<cCP^FIe3o20u@^T2hw^Lp}tAY9XV>&=Yv+i8Dg=o?cbu?k07Tvj
+_kvQb7V*!;|uGqsMo8*{K`;()-ep{589i9ylvQupx%XfdGx)0s})#U{3sAIUi4%k+8VhUtz4!o#7MN2
+r%A+fd92qHn)X=N4kHUr?>d3vbXBoAgq4anWv{tf(Az^>v+1Y$B~duI@k(d=n<dAP);IanEGOMV5j#j
+EkzRJR?I+Np+^z#xV4#MDhoF#~hvh&d~~Xzts`YwAE~Q)C|X0lX0X5ZR_&gz7EWQNX^#)NjW`3CPa?(
+O1A;elh$$B{$1oqqqwAdY5{k2RQ~1lD*mag93L+=^aA(h&v0Ei(+8{{64h8TA<XXArqo>QdB2JRi_c7
+tZ$cd3P5gf7r0yGI_*|q>XA=LQ=b%p?<f~2Ae6VL4~i&=)x|_gC15EVmf8jkk5FElUgOCExfDe=zbix
+e6V6FDsq2s>Hb@R|Hj4;K=hbqZT_zBmW<T4XZCi6A%<u}B1Nmph_+7o@Pc+6)Dmog!KmEWop*(3I$VW
+7)E*e!$8gRD*3X}^JcY)$IrumeOF+RNk``n0q-Xd=j$~Ow-jp+>lxL75~*Xmp(W>o*>I)232N>}TORa
+_NW+9(O$E&%s`jU(k^AWgk16L#oG?C4$~9<)!?hr39cd<8OrV1e7>zIu+p@Qfnc_6JCi`yrumjwjrjt
+i7+E8I40uqP-q{1z|!Ppq_%guQo>`Bbb+t4kEg?kZm(a!L`QzwN>10Hmx7TWw^KsJP_4v?pncLE9Ey-
+Awmh--h?dbyVK}=<hk4U`G_kt3*dWeFm)v+GM+fkNQ|o(hTO<<QocM0tx3T_W=YuyG@!;V>05!PX0}^
+UXgG!{%aC&><ne|ii;p$<Lrxp;sK8`MHJvu)>rp;t-6$<?%=5EBW}k9F2kBM0&?DP&VIRlV$H02%KD`
+=i_vwv+&!9fqQpC@Fcelw@H08?_BvUr^IS<i-b(74b#SK4tF^b2y9`gg>h$Z*_!aHG-GVJ)?vf@X`Hd
+eg<9{n3HrSFnDj!QKc010f7YQlGg{QVuO44Y7>TAU&nO^0S=L=>pO&47F(Z5&X#2CW{b)Hu|sSC+UZT
+H?XYTrUuErc!sd6i$Nf{3#CK8&=#XRQ(i6rElrer;hLy9SR>Ajr*`B1FCaCb=YjOP*s>BK-=LuOvDED
+F=sbXTezQ+vii%gHZ`yX0_S`kEu=iJ0sd>Qp@_|qLQ4Rag7e`okR=6I=lFw9fDmiD6T6nVSqgel*_n&
+D>Wsl14pzO_^>T;%L3j;6i$ce%5;D_ug|Q$qXKDw0%xhxOAlP?vL=X~ySFb{X<{|nFKWS>ubfBmCtpH
+nhsb|ul%JIC)V`<1rhDVqY4_OF#B@^<BL*!L}bcA#YnSoZ|t<RfKgSyS<KDTTjwygdgt3tUsJfE1L7o
+J3g-_%yA<Fur7#uVnw00iogin~x7wql|b5(UX!vm!yNXw&H*tY2%JdJcLgrMIFC30#LR-&h~F4Hyw^p
+t|oOX#kNp3H7G0NcUgw&@3p~l<EP8Iwmc$S;My=B*RP?QvefU%);ZSe*?}$?Yx_izyMNt>_fEh8xYx9
+i<YE*H7YtOQfOvdaW=LUu&Jv%f%65?Cl{7zyXroR-GLQku!0O$kiiOuo^T*HFuxBU3KA$FuLB18Xj0c
+hEl7RSxD2I!2h2#(Dp!{2T8JDlH|HzDACQ{-OFYMgO0#^SY2$psX>C3wUp1*O_M=mUtXj^)rp<kzFE5
+yehnMU$>KzvWWaqN3Toj_tNWnR-r3kOXasgbNxuxxa8`Rd3Q6dnqMbO?#(yK%mok!-wBz)>3u>@AAAF
+Q*|p!+(``P~i6ZzR39!_Vq6n^AQ*NaE^R$oS_z89P_J>0@8|gbxpQOixK7g@q=^de}^t7Aul+6m_KwC
+E!X+@*vsBB~~F(k{|KsudsVd+vQn887g3X?(aRq)bn1p!|!esetw+JzCp0vg)_QHb=(it-MGRovN}KD
+??qC&Dw*RjZK(%-7Wyr1QhG!9PgD%jy{yLPRtpz-@gxg|;Xb}RQDhsv?2OoPS_6c;*~8BJI@&zxXS4)
+-bszT%)6YQl2+_~ts(uB%@*2(g*goLJo}JZuu!n~vivcUAtKsE3*IKts=h1o8E#&lW5X)#nfcX3LI*{
+CHMsN==!li^fC&Pz{gu;X;M<@Kx0NCoVR9r>cjgugYGBYJjO8*MxpVh+jhsW_ahj!e@>chj3ySzeQ<_
+|7R<5IVeohCeV!Oy-%U|ER3@-RXLu1?^33F%0JpKZ)+R&T(ze?KA$L75iVxwqiv`WmS7T7peK+mQ=0I
+Udh$Q}6BOdm3^)NZR0fErx?!4pLeP`IlLK_Bb7nfbd+4JWQ4!HR!oO-`GY;*`ljCIx!Lm{@V&5%}z9;
+0?oLD@&g6#h5!o7-U>tk5LyPDs%?+M42g|GxmD7}lH%15J2Zz36FjU&ccy=iJUR^6CX_>hP+lXHZyj9
+|VKR{>a-sddheyXd4M;vfxMpGE2;*>53MN<f2OgnUpD`EqrWE?X<+#X?b8MuB^q8Z^IaU-pI@uYvU+L
+0;*6yE4$CFFx#6-?)7AxMs#;QF0RC=it@;anYuEQTWu$ZMgf42c)`LA{}KR3>S$;Jcn3;*KW{q4q)21
+5-Q9eTpFWzgX=T2Rn21=NVTDV%Fy)~cYSHbP>hcI<Dkl-C>yy-REpg<yzF0mI5b!-{lg_h&eZcy6P8#
+*cg?-P!UPu}BWU+DUkh7zfLL?p~}RgoBqdx2a#9L@fEX3unj29v<go%QEn|ecpn;xHXM%YjU0g<;43x
+BNY_MKY#m-n5erP<|_|Kaot2ZhOHW6HGzyKnbn2J_&8ts%!osM1uP!W^d~>N=D7kXqgWVPJ|vi7t@is
+6gwN>Cou8tfaBGC7Y{#j-&JU9e+jb7xwp@Aehv(_gJv?_JQ=3P06!Z|rB|4DqJrGw{^a44K!JBz7mo@
+nTos;Bu<IpG&Zh(wHFkUkRm!k-!lYGpM&k5RI5Mc_u*+b<NFY1Uq?rLC)fnE0q<uL_bsOtof_+h9>jV
+h70ORPpqzp|Y9TIB*%4&H_ac4~OmFciap6@9@3pWvzGo8mv7Q5)<|iuyoGbVwTFs|G#%5HdV3fiSK-Z
+$}<xwN=Ttg9t3LZ75%>GjoB2x0P0}Y-Y1lIyNGV1`^Vj*;!q96l!za{*dh~$N}tB`eH}>MvFWdSs3U|
+ls&FS_PE_+w-?DylsUD8qO62KjJ{a{zSwOkJPky0INKa<f^L;GuRN`OG$hi?@Ix^1?HkQP$%lyIp@)I
+E%#-1FAdvn%Y^4*q?40F!yRW9lCMw^Kn!&7Xxr<NciR~U6w6-cTiWoKMH<{dZfzc!m@02VJkxtZ8Cu#
+~$cT7t`qeN{Q8t?3ba_U?^QJ1oPFjFLX0EO+}J}t#ACt_yURjgCCu;*RC|DL|VY`O<pr<ScU)SKQB@=
+W^QPNla+bh7?lg9X6V5e2MM{p;Z9g5A+g3#JWI)w78BVS~p(&p4)k`W(EGUeu7JuCc$6!!K=I`J_Af2
+I%dw1yX*O6q<1R4Y;2>l<!7KFpJV+9jK+}Jg`2K<Me=AnbLmIWHJZF0D&5;H_C}1!wjW^V=akJlQo-h
+zWiYYq6#b-91#bkVXzu@V&CyBT<w8ZB@OYoA@MCi?UIbgz<u?E)L-f<^z*0g<QK<6KcABFLHL>Q>R9a
+OMdb+eQ-^*Y#C~?0+C3?Dv+RZLrs(pW%9QEU-5dIJclb5Bi=u2#Id!-jhMHv2smHhX_Sk=|9!F$UveW
+5-<r&L!sXc=t1vMb$D<`^>H;sX=-zeqp0=aF^80`8+<(pBsDWt{C&~<A~yT<`NkA+u<HbVV!5U=TzXi
+cgQi5Yf)<oRpx5`1sx@AtDKzM4xme`wNApe39kn4KBy)?*~>E2}b-Oo3ZNGvn38Lr`T&;bA~GG96Wa6
+i{b<1g4^+Wq9-G3%VyWsWJguzYBm47))UXOF9O5hdOlUJjlj@%#hjfj0ZUhiGwt)BaQeQ*R@6r)i@kL
+0!HA>NA(jZJETN$6+pxe-NQieJ{fu>2_SnXKb4IGe6!9>syy5iYcqA&b<aaHP}-&FIYNk;Q3mU{hmB|
+>7WcG?w~~STQnHy6xk-)E2=VRH>}H|#eZna)8I$>t{a7(YTn938WOC}(Q3nz|p+#m70O&Z)qE9m>X_y
+nWoF@a1V}9M~UdO8jR8Qed2x}6K2s7PP2T4*e6A<Rc(Pq<(bm(ZspV`e->O1UasYCO#Z(td%gge!{{F
+YW$U(;&ySXxoUO49~`teA&&!N6aF^5Ibc$R77Gp%lrIULQt`UX=&$p?ezCw|>Nr7E#SCFO%}WfL8rb$
+``aYDYh~229i@!lT=*8C#GiEu(}*O6v?Q|iBC`#Cc(C-&Z8Q%eKp_NNcEf#oIs6%*b%8Ca<2o#ZU$!i
+;ck>r1y7HMeTSJV(Fj}Z8i<V7CeGTDoB%Mhl(c7tUC!lj!0mF#K6DmR<5oZN1ZRM8YVm-0hU|D3$oNg
+F!%dPB(6pEOM^WUEPEOPQZsHb2HnbW#RPR-%5-bE-;jhV848%^qYk7RVw*@61EpA%K>I!;W{47`UGj9
+%BTmUaE>U&W#ZkOi)@$>1qEh`5~%-d9!g1<;Lg5D-rl+fHJ;3U4z;-bcNn233;Wht7&NZe#3T7eZ8vg
+fxHObyN}=n;Nb8=BTbRztvz!D=i6j_i5j$PDAhYuH|p_yBvu$HG3=hB7cno<J@L+L3K>BB39O$8)8JN
+W~UD&J}(_$qvrF2ql|Q&){xaK1;pZf&A{>X4taNg0RF=kZ)S)2QCX1ejEmt;vpRIQTHRm(Ag7Msyd*Q
+l6AdM`U*~Zj02_mFp92fyFe!bqfs4#2DWKNeYMx94^?Bp%`92agS8GrkqcJy6M^au+^W7Opun1@jW4Z
+!?ncOX3ua4IUl$@`n3kx%EJW9Scss5AmCD+_=YzxpMi|3!oEudCtEZO-yavr=VhRZkK$zcE0uFUhv_+
+)FKT%pwWu6Q|9;MS9h*y_GCs;R#zJR74n23z)!ztd9gU=<1%8^T+;KM1}FtNSXEDwTTyWCF{s*WTS#?
+?=AA$x&^y3W9!X7wc9?wv+plOw#jIpqBz!r3bW^)eA6Yrzh8UB*c~+%Gy+ZRa>AF`@LJoS<AZ%Qod=O
+yDbZtp<FBht(pVy;J=jnTr;DbDZExnt9h~yN`}pnbL0}X&q8E3!?wiLWx2kcQBACWvA9bq#RJ)b4ZM^
+Tg@i5<9<Y~&&8`_=_T+Wl>HFPLdRy{*1H?ee^1_Lod42MW2X8QhTZkcheAw&GWoeF0f9>g>Mi$?0xA{
+{0kxfYC>ZjrjERW9mnoWmP&Utv9EMlM;ap`okk}lA;g`1asT`;}l6#ege*s=hTP_7hqBh1N1xK-3z&!
+jkd>@MAU(nHpifDKyn!1d-54YSxb5#u2_Ni6h;`wtdDy9di|C1C|p1+rb8&VqvlD&`Z!J>Yy1|LjK`G
+Ys`9{#Ey9cnvC6VOMvDL6x1;tz}chThkk+3aVHIJNyywuwh9k_!8+zdA0dcbuP|As8S@-Iv}V3gsq1V
+^*_Isg5Z?iC)sT1j2ZD<tXq%*%OI|>QdVXtW|v<`BK@b8}i5?wJtFVln+A#iS^pu?P7`|-=U`PlWW$g
+{_=jlH4dGE9yF-4%>*+xs73>XJOecba)Ns6QQXG)<4j6^N|Z^te2?_uv7vCE%`r&5v$r3+Pa`L-jfH;
+X$g#?!DJHE=U9K7&_ar^SabJWeZC@Xb`?9m{{4Urxd(bEk5&w@RX4^U3Y^uaHS9HJ>IVBZ%nioiLcLh
+@0a~7KAA?jZtdnLDWZc*RDvhG@WB-HZ?8TU2l&Sn4PmT0<j;y+2T8Uv8IQ>{LSAa<CW8-gGN3}DE)0B
+u=W(w1D{1*g_|hT2WAsgR-iWdg@tF_#^DW8YJ7icrmI@RiEN9>B;`6F6r&EFr>~k`V~7xlg!LzZwQ??
+tC<WWM@%+@Q216gD8|HK#~Cd;GD3*pJi9RHp{m|+qc0;)?#eCCkxo5M2M;<8Aj`;q9r@8A65qvK0Z$i
+F<h;Q=N<TUG=q9`TOVYPyyv_Hk8mA^108byXySU24Be>$lP9jveTa+&7OzK=lbxCmPuZGzP@5>_+kOc
+F$x>gOh3<QS<CTdqXg?;U1P*5&R4P!l*l&4!_FJ7Mv|*|ZzU}%5doU-3mg0J4idRR8!>0BCb6tsUbm|
++<$N}20L%Ob>?;puJ%*eVMv!Y|1`cyRQsjndGI$)R9s%2vc#1krqW5SQVM)6AefY9b^u&Qd_1N8n`5B
+6iOk(UnFV<E39-fu+FRGn=#pi2GeA>`2HIM_soAX5DuV4`-9Yl&GXpW|985=ZM1yj%QeR*QJQ>>w@;5
+^F%=SnOFW_7ePP!&s;CDb0i_V26}PA#$6#0)E%x=6l;kXVt}<a3vzNcbxkA115g7bw3@x)0TwgDx>8}
+{$~&QTfI-ZySH@Czvj^i+#KW{(S0KHdmas|4(QAzi|Cn<Wugi^TvL~UZ#kUAhirL0hKZdY&076H{qs;
+mw-6Ad8|u=omsp95IuNwEu+5MWRH}hE*#6Z+y-A?n*q$fPvJ%%?o_|#j+I-v(k?~ejb-m3GZ+!pS8c*
+<Mf#0=lHr|)&&Z+O=f#s*&hFz+9znj}EUjH7=!0R923?xH9newY{!Vf&(csC~8`X2gwaBZ6I9Qhv2Fm
+@IunEcWnw)=vMQ+&Z?Y3QSNne9q0d(NKACNdG^i|4X((>rq6*M4?fV&QiSgwm5pi}HUe`GPYVa)Z-={
+jGD~E-1xF&Mh$i^Xik>v`)XfO?U~_l5E-~d{^Ek0m^C;N`8rNZnHcTX)bI$AKUA*)ay;CKM6wG3v%&l
+Q~t82TLZv%P1#5%o+DwzmGGvX>(324tN7$?*PZV`G@D`NN=2$`r}|7RzQWS7*;apkE=}n;j2P#$eBnn
+Tx!tg(bo~RS>{+xttpiTLfg>qLw3W@ZcnGz*Oiar>35;}Zdi}d;vOBXmd&u%hQfQ`~i7>Y6!Z>Dz$MP
+h7qomY0+(VY7Xy3ApFd58W?*Q5r%a+t9X%-Lg;V^F!JLJB7*<4Alm1>SyCCgzp?HtTdVK$$&WfMXElW
+iV%x;znI+>0;C;}o|E7<GWfmB4`i%Pd0QB@fJOuBBeon<8B={GST0NGDe*^pjc)&t-l6q%PN=q##3<)
+_3hQ*rbF6GkJQjus8GqxA!{$l9iY3@UnegvUk2CYT)da+l6uqpL?bAQ8`2DEJRP76+ok$)+nKT?>NmS
+>gPW<<Do>d$a=)YHqHKdJQP)S#9)0QYvSg`LP;%BZV*4tAto(vP`YNn_?-L`F@2{{vJ0CEC(6_HM)^)
+9oFd<#gcIbUN|!b8iWg-Wl<2&yN!jTL{}qc@or()1^yReI=Ln@iA{sg2HI%DGTLsZEf#u3~J<735%FY
+;}>ialtDO41A3@Q;5buC{B&yi;;;ePUDXmUKZJw)k>6-tKzjC9nSs$uWl2Cekdvc0g{>0Z_#RJHfh(l
+L}uq3`=?sYcEu$SG)oQ1xBXGMmWuX;z5nV_GegTA^AmY9%%xOJwbxX~cW)qJ_7GV1Ku|`ytXgmcB-EN
+o{Q3%ms>jicq?Or$j4o%2a{P#QCJ3d`0$hxS9#jjRD%d=+8k}>_(R9y;&TPrN5RASstJ)aYhywWf4jf
+cw_w_o8z*sc(OBv(i3C|=Evi`Z6LP5PDS?(biG!;_%R>HesmkN*?@e)R$UYfqy)VqJi&n79}GZ4o8jS
+rzj20!U`ekPSjM&B+mJOfG7pAknAP7}NfU(X2KSU-xXdOYbOQUI-vMa%8MJ{?Cbya70*P7M+H+Erz}$
+|U6cb3Q0e@(Ex6<iY;Rwxis7oyT81W+-yK@p2WP{EC1^ng^a#pFM2cgA>^(@wbN6Jl*H2pAY6VZ2Um0
+lly4hC6?x)=2iY1}#!JvME}2cmIFQYZ4LbJ60#&?y!Eg;;`-5=*WhNPJqCTDYIuDu=L7aa}ZNE~wxiJ
+hc<c>du3IM!7om4a~wuTtrqEMWxi@d>R!h?tuq(z|UwCXNG5tFo^$B5-@A~$OCjvvdte#o^*`NpV=-?
+D97$jkkj>QpQTCZoKScsB%V|{`>%+tNJc7CT;qXZR*>-91;Xpy)wR-FBJ<Q(`5BOUOB@}A1>%A5PXCS
+rdbNY=FEL%{lb#+)A4KU<dp#|-H&0wN4@e-*v4{qpr;Zt>wEoa62LP%Yx+Df;qK0b!$v(RHL<`z}XIA
+H;D-wwRexxDloxdVVifKj-Py~%}h(8I=aiyRwsKZxZlV*E;sAf0vtnJOr>%SaM4ZS8A3xvkx;3T(a9`
+vzG%8Pb$V62p1$AO_v3MCc6U|&FI+E7x16clvleeV!S918?Rsdp$BU8@=m2gu8mublU-Me}w`H9*ZKS
+V-;Qwe%RDyNE|ht@su;B5aRz2?)_}<$2)3okVgw{zSA_)%M|rNBF6ANcxVz9w@}V#k3g&#)&}Y1F^cZ
+9`jS4oq;3QR!&IyjWDjev9P5PptwQO$E5w~YTfT#L*CfHJvpZgkHJHxA?gPpe}?W&RXqt2CV5LUN<tS
+Ui|!9iIC&Hp0%aBONwSsIY0p)T!z`mxqxP4AS^&r=Vr!=5ah+`e{Gcqyiv}hbTk`N9xxptQzwh<}pF6
+&{Y`d213(o5{X|d|Iy(9@HJHEw2_d_8~xz?i0zd|0|58}t<qc{@>0Vy3e1^TP!dk72LLsEY=cP|bs>2
+R+^26J`d4>%pLZyu%#2FjYaCQr8NyEK!!Z;r|E_N8<4Q1UK1htdB)yy?OVkyJV_|1k!G$q(_z!~8Mtf
+&sHE*@rRun8*HrhqG7s2}Ie5{e)^4X123k%JCSkM}!yoG5pEJpFHKbMV_r3x5_sw$7AKe`WAVT`t?Pe
+Na7ime*;J}2e!kmF0yso0*~-3#NUkB!K3Qop{;`OIv)NI!%NgXF;T-qJF0jKNz=5JBt5pppKp7=(qzj
+1u~i<3{2H0(wE`oy5uJ0?%Yw^nm@NjqwI2nR_$HTz`!kETHnGca5yyeT`u-jfuIf{|&4D;zb}o^Y^<*
+GH4CPwXCA&e2Db-~=2onxi%(cozyWC&7m?$SH7p-y}`oN6SZt}AY$TX8@hot-s-%XG+Fwn!+A<3zK8G
+msWG@A#NmYA5$lDC5l#de{s0LT#VZfS7uT0LIM-$J|TWg5Ejc!S-fZ^V;umi#tk(srw#A<rDNx}axq(
+6i;2bp3Or{O-enWcDj;i|rKky_$_}g@^mF+z-1P4_y{YQ_v(TNd0vm7E0ssh#^S540qH02=h>+kx7Mr
+8G#0HN(CBUd*!p&evu_7b>g1sd7C3}2fBbap+HKQjr0*5i34)h$K3uqZYKb+&61}cL6W1($-47dh*y#
+`Ac79Y!oo#v$9<(sL&&y$9YT3A&Xe+}!&EP#8J?-W7;VAut*%&x$F#cQ4tzj?$w#OFimsJN@KpCD+Uy
+F(wCP6VSZJ`4G;|{<Ik>*s#Lpu70m05AVNanb#_*v&0piVCUgG!#UH>8f2;DjFx3DzH4}60M%er&<+f
+hU&g(P!T1MC2`CM6OnXR_q<Z!pvZa7uZ%LhRtoX0?rMFCM@+Wrkf3TC_NI5MT#X7U|C0-i~qtMmG$<l
+Ar343osBTIn>G~3>!K>IzhP6%#nAmO)>LjAx5&PpHSu*5)b{2hw^ynEgo9LLu+_wDG#mUp_M%J424*c
+f#_`Nd>+9SI<||Spysy$;=K_6c`|{r`sM{%CC1I;(dGt<j%d^40hxzvPkwD8_o56e7^@~Vp^9Rsy09y
+<iVyJOkyVt_QS~v!fh|p0a~z1vFsS9aForu}tK4M*)&z2V?uf4Hpf2uw`_WFmx)Ft-F|XcjKuwNzkn&
+|A;OT$S@_haqR0TZM%8!O5T3*hoeKk0`#uHic^j2eypZN{31S3&5vsFz(w%S?vo9G(zO%$hYy@X=f6}
+|;zDIK~eMJ*m|GJJ=0=iXlvr6?GRJgV)%p`>>Y*h14%v{>W-qP6_cS#6r1omOXV<pgomP&632?$?MgL
+A*?kqj3LU(^!1&O~OmRr9IK<OTXj~J!=P?Y8PJmxrr;m-y|J>o6o&@+1x4<P5wqnnA#*+nk08qVSmiy
+gT7}TMDQGjiccx@K$_&<SLnmE34=LOnJm@l7AZ8MlT;*U-=Yzgq#(b%Lw6pbu!Vaa@8gLJDDe>1sJ^;
+|L;U4R^ULiukRIbntJKjlyt<=BZ!l<ZFa8Oo9;_mD<DRM?@=dy2?;0)lZ(i<$|F`8b4*}Impy^H2o!$
+S%M~S6?InypjIDP&}tfmq*qXpS^*^&v&e7-bUvNU8?7iW_$G^vW~Lhnlv-l#qcvO>N%*$Z@&HTx|!qE
+MbQ$SaiR#oiP0n^Hiyl}EDslKk%G!UQJTEgSu?Zi1-S06iY(b#E>F23ue?efofN>1Q<{f;9gXZHpV#p
+OBfee0^?ujgNchl_63>^JJFes!>OEG%2lSgH#Z2;}6*a?{N9031pXkWNPnFItLe?#`fMqzL<Hc?Gaq-
+xI#w)GQlijEo_7Ft_*&CQx5u*cBy|veNj8#ibBcvX5>aK>b<jZ%bJCffDtieHgS&0%9JfFCiDfH2MNV
+G@(Myp1=;jXxb8Fv*Pjlu(3K9K{Fzv7bmD#P7&Os{a`GTFUkFVYj~U6Axga=c%vsWY>CS{V(Q9dy>pN
+&?Jk&51YT%dgWF4a!bM_wm(Ad;PEkG7A!-wdPgtO8)dHHmV`2B6viH>*h8U@lig#6x5VP$;jo26ZyQa
+bFNFVwgAQQB4YI<Q_S{=qxgwLK^?d`nii0ntz1ycn~a#{lAVW??fGjx;j~7a!jXj07rhuB^853#j(W$
+iMWB<Wa9-lyU3Fm^b*jAarvs9ka}2`^X1tO`=$4FUZc6`|BIY_o6nY_`*4u(!y_1S&@@d_K7PKsp<2%
++(b1a;?|7U`(Qh|bKIL)`6~npXgvAHP26}AfrT4SF2*~HvW(;UsE(UvR2_dG!H7JB2Zz&S22zzN@9x7
+BfI*cA9O@Fl;askHtlMzgG3*el2?x?;7#VnGq&q))gRqsE-#{YYs5^fJF_UAL4Fg=O;jIQR@(i&Ouc$
+-orloIOej!jVzVP9p?ggZgslDC=?)qhdn$^}vTAD8jA9nE?N_9!_bmE@VTUVq&d(T6Ap;>l6tJj@(z0
+T$J3CfgLQL`rxMe1m4C)s8zswY0Kw_u&xdl-o2fve8vuCi4N{dk1L!W+!Q=Wq3(DYiO%C_)Zk{?!gKG
+$R&JP^~98Kgl1QZ!I|cK48wD;T}%!USl0qW<g~v$ggLmP$(7M$&u$<W6drzqszX&1rn|$v|f2nj1+oz
+B{wQA;zq@%_84fQbSX(?r<u=cT%|GSb-WtP%#}%#&1C5h(6zM83_z&YxN8f~ukpAZsPnj%rlB*&1KN$
+kx(Cf3VO_Pyy>Z20F}+D-)qqZ|OVRZ5<1}?VvU^H>%$m58>cDPxcM_Qx<5DlhlMZ&b)x);(la5l<@EB
+f@+`!@=v&qIe#{}8f14-o38S*YglPJ=iBjhjju-eQ<JULchy6+m<OP4~8mzNO97Sbq`i*!3Qcd4J}l+
+s}b{*H7_Ah`R}>%?}8S&lD?cdYRw9MSqgFh+J1#ixmDJoY1H#W-17TwO6gHqmQ*c=v_AHPE2lg|K;VD
+$K(l#86I}(m8a69jXaUP1BM@4E2Lr0C=ycL*IxKy}PhpVxgsm-SfBAeCrl*yXO?xwy+7Fhb??$er+#1
+tDZkchVv0`$w$5fU<PTj0vSUS`h>lO9HzE}ivgqBi0}CW=Q?qQ+^OjYA>&j8^WklJVqh>Zj_STX?59l
+)ZN@fiF$b~G&#5f4ojbq}h%!LNAfV(eeD*z(zJtJw&qz~m+8kv~qUX)T+vT9FgZAXj>L-v#8S`x$$(K
+EWG4-~6ZCupRon>oHChih5yRS=(=2b3s2L{yJK8WUg0CH-3l#7=FgV0zet=_iQNMkuxZGF_Q2KuY~kt
+!h>A?IO!hHUuBa4#KO%`RiNkUQ}i)u)pf(uwpEZ9B}st%e835b5jQkLG<6(|l~R_$fA+oyBj!5-r<&m
+J^avouPEu3d6;^+Ksf;LUcAv?;S{O%R#*P`>TBa9V5zyaxp~y%!u4fk@t>3gMY*<YU3aP?-#7WN0L0*
+kGs-@mtUbA9@p5cd9JbYgseQXJWg1bC9IRo?yeQi^qo-W?WxeAq6DkYvd5RcEpQ$>7L%0{*e!+b9$AU
+E!WP->KFcObWA|E%!+!xPfJYiudAJfzmIb|0wz67nScTP!Zderq@R3wuwWA84qCbR!cPDv*1$NC6e8e
+t=UT^@WtBi%30nLRE<IJS$-@|}QD-0{{y;lybZ6MC+oTuR@^=-VFtL7W)XGk1ohCJgPKGq;+rN|Srer
+%R+64vz>)`@0!(~6<6!GDx0uCa)gJ)+%=vALFQ?xy7@(BwR8Xke#LskY}@zVxM^2&{*BD?Wuo!=B2cl
+~Y!Eh;k}fP6VcN*m^#+^?YdS`Owzm(ERE9V7j5Rjv1j<<Ih#a(#lzdf}j~&@ulwxv>|8|ULZjRfHezu
+@u<&m1HdlkG%Y9MHr3ZR`AS<J)+H+2b#=sPy7fwR;C)r>_Z3`h+;9m^ty<mFtelmrOhcBSmF^{N$<&G
+GdyJ^hulPP~5GyFl|A??YZoHro1P^;R)}qo;31$981y^UCYDS$we4xJ(<#TVt{a=H|KELM*1xx$O<a8
+~RUVultP5T1bM>>q%K(g%)wGvIT*feX<Hu@x<yV`@ck@S)jv<<}<wCjB1H@c1*AmxH>wNuL9B9wb(I1
+0pIiL~f`5W+TU->@$*z4!ux#_EBPWsPU(h^b{IX2%_r;cGlXDb{h9uO2Mr?_5(d6lo^rNOMDudhHNwX
+8%6ywH=3)oU<=7q^fEhQtB;~Xn{W4j_bOX4h&gfEX>1qyD;OIGP>iczks~zuJ0oHK+Tp3lXnX56Zube
+N@Q<6Wi!q%uudrWs__8#^|lWa_{{=_IMAk>C06V(a~8=$*t9t9@?gs4!HmAakeDY{#L`Z3K8|=hdsds
+AC@}}xML~`jNm<!RxNnxdH>x@feNq7ki_xjBO)tW0X1Klt1Tk`#Z1b4o`}E8TVSAshMZzgpgflJ+_w8
+NXUZZzOM(;370`FdOq<cmj@86b4|2*b0x(5d&v8#N<i^oyQer)tPDU^)#Omf%APfJXRbpBB#%M_R=F~
+)n}C=XV$QJekm4Wy~T8q~yDr2R^{JjZK&a;%<7Ij~aoxjykv)4LKG`E+b-DkNrML~$6AtLo$VC5ZZ*u
+tEAxbrO%8W#+-LJc!k(!}xn131YUl_HY%_Fr^Zw0sCd1L4Cmt>Pf^hq3829@QJp~$L!hD+vEWf6UfpG
+$6`}AV?O1@PUH~SOnaY{_bH`54SCNEbm8P>mWN^X8R;vdKG(QXB9@=*XZ=BXmT!@Qu)(&_9j&>LILZf
+sf8vF$${l#O5A64SczZ_^?7cfkCtKS`cWUUIZahJ{ya+Gz%iSiro6g{6`l<1h{uTzcbgsp^_d8^0LX4
+{}ov(g@x-qU2<QXO$>%)({{b?WNU_`biN5P2sHu(w`xEq9$_h>G2Th)Pt!{@gu&kr&MZV<}n0zdb80d
+jM6#X-?(m`~Vmxork_B9w2`mI~#$jw<eExMkTG;&9cU)RTA-E0lX3+7!$IK!X4wth3s+o7jv&!0D!mq
+)(#@0{!UEM_lpj1Y!lCplpTTs~hDyZe`P~`Ip&MT&DZtSE~}=r8`SYf$=80`=2y`j62dow`xkPDSBA3
+IEI9`ZFsX7IU=y_!Q^)^<ZfE#m6VO~l5$UnUQj<(Hzjz2g%)_b#gtGtbs~nQd&&x@0s0ML0cB&J6uPG
+);?K}fxS1vAK|+BiTXsDrl-x=?7!8k*evKuch_v-4yjwf8$eL^UHakV|r?|HYp`X(TrrdSb=sn8kkHz
+qPw}?3{*jlKJnhC~P_6D7&&k#0PCQ6}Myu(G0-BNT}r!x}zbU5zn&NedV`)5d`vAcJ#D$`<F>Tl1Whd
+@v1!53Efl*uk#UWAVx`BAamYck6Z;lm#2=VM7O-T6=nX(hZ;{wY9DtDq>I-brk;@~z=&axzb{+*IRZR
+u_8wi)*|HdX6%$U3Xq8;auQTsDSk*>GeK+vrpM%cVApp;$_Et42ay68>oMi-8x?SG}+xFClvYJ_M&hp
+;&NaN^*WE+Ufj`Afqq288<m>#-qNFjr$KkVsbEi3QbpwAEJ~z={F_33c7v2B1#fcWjka-EWsa7hbXo#
+7d<X3AcSjsf<{I7H*i8-|Nm?>xm+GzV9&%W$%@g%aQt?If#S>nU&?Gf^&S@<AaS0Mb6n55<VinyA7Dw
+F*qB_hUxXUGtP1$u6DmaN(xhUK4%4zkJ_0dCtaizNK!lU9j&<dOKH^}M<{Z2&&(0y2BnkY;^A-Ycl8v
+4l8K+L7ShYkO^eZ1iL3`qUhIKRjlfl@pb?ZWtM+bz)S^6QbQ->zT>{=hqsI^-zA(M9OQCDDB;Q2oDj;
+)natP6tR~J^^1~2S(&ZPhxJt69VYPKaNl@cIeLO)QjI6y?E^i_Tnt`;+*I{hXmk1PsI=Uc%-4RR;R>{
+BLnM4Q$3Jq_oAjd|LV?+h<2vxrM{i9Mmuv}be|8b@9T$XD7opVn(lVI!oEfi%`~g-uYn|l7FbZ!cc)G
+O?s4@KQvO-MMg32k4C5N8E2)i)wjJv0&FCVc%dvVrxn*4(v}z(`K8m;UK`w5@@{3{&CGX^sr`4aWBfF
+Q++we5sb=IWUYOnHxkWUXsoEk4PS-I-|dNBnTZNJMhIVNydhnRx<LcWb<r$6T?)nAyP{sozCHrs)Y6%
+A^_9Fxgi9}w8Il#=S_1f{h*I4wnsQ)Z;3p>q|R;XpeYe)(mV6imEaecpSXS=xvORCux4t=QQox$4@6r
+qyZaADRQ5a3a$?riKjH3+IrNU3D+9zSg-4&Ax|)GuvSa?lr3wFb8Wh4~oi8ov*^*(E~q(e2+i>2u$wJ
+Pnk^jD3e=F@}hg#pw{-Ouo90zt2b1Ue!})7rn970TB1x5PqGK7x1rIDyIvlx*Fp0xZ8-X;4TdZ+u!=)
+@q9}NDI<jWY(NxEvZ=l*)cw0nmc&Q$-DjsqOIg@U);OXIOH47&$55aw*aY&3<hcbr~xG(nqN1v||Hd0
+0goa!$QMokJvZ{*G_%cBloUq>9dD$%{m@BW$`(7q6+*Pv(D72aS$Z%fqCE3>qE<#p)1W#^7wQ3o!IrP
+qP0U-tZ#sb%xV>i-A-tslTK8CQ94q1D<I-dp=gt_gq3k3xl#MtW%$N~%rVdn;EhJAjHU^4_{`PQ-g_Q
+D5(^g;8&-GQ)doiF!YjBJV9^08|fzf+^Yys`~(PzR4}K`?_u|>g&4ITN%=!I?pKG)Yo(C!hWhZkg2xq
+N2`G}?Z(pT=f>5=nYiQDf&I8<hU3=u{m}({tU7ATe+^IR3^Z@LmfzMNdi}NxKNcMS0Y7ULl_Q;EyUFT
+jyX1i)%dzL?&$4#3_$|An{09H%UB3KU0A>fdf=hPEGQ-|3S_C;sSSMPP);8%azoo&Sxy8pC`S$+n2gd
+!IxlDw9Y{3i5f@lcWN4<WfeWEWPSdbQWft~i2HolOE%ph!@+mRh*bY%?QU%+aO%d1gK^@WEuAPU!4nM
+_xsJi7aiRim&l09ZZrFvWunya!-o;rD0z9_;n8cT-L{{J}vkyu`wun|aV5n&V3Gr#IyaQ+Ge%XCua-3
+qr1Y_p-qSV(~Yow%pKfL4MW6It#`I+WZX4G8~t($q|KTfaOI1%S+ROQpDf_gv$f!ogfjg87WeJTYJq*
+fg$SgFK~&;p94`Vu))Ziw%6py$?A?TqOkByrrus-mWKwPx3||ggpwe!qSGA8*F93u5}c6&cpB1_)>BG
+D3}EVi;GH#rTh!hE#`UkxklZaG&ur$Qg%AoP0^9Ph`E=q!N{9R49S|~cOC=%HtE3|}NM8)wd#V{4Vbf
+fCLvWhC^yCXeJ!~@+KZchcbZQSOjcL$>@Ll-jgC1QTt@QNBBk88}I*`IIeFtOv+Tc4If$vP(sKvn^dV
+C9vQ?#eaLo%D$4!VCJ{IH4c@fS)?k;pc~vBu-dC^Kt=KQkMO$_&WLHmi%NX?M3!x*2i`>(HTrd)_VSg
+^9jLxqa4~)%cW7d*N(hU9+#!Z2a>HAMS$aoWhY($A0DOI62mzULyq^lBFS+HTaa)yL>g_*g!T9#6iF!
+_b(_YSi2SlQKiO?_m-W*Yibh8`WrWJwbu%xa!i;B{`-o%@bgj2GBAJeKG+5KIiOq)JX_$e70Sayg}*l
+V>kPDLZy5HKLT!KegA(w=i@-|@{!k%!s`%4}Kb?W5wxT4LDLm&28WO#<gl>+J_eK#*JOE^PAo`4pDeo
+#m2?D^oIYKGQlJCaIiAqCSP)rG<=d99ThF1<+acbJbc%mRN5kTFHr&;-xsN|dOlGuX|pyZu#CR1>_J#
+v31E$eSkgEu|prN9C#@S{r32u;So7z*@&U=M+mO1hg!3QgL8c9HolQq4u18bb}Vpz9X;YxylB4ry`zQ
+0g#{NX0eN?5>w4zZ9?uRnMj*7r#i(qJiPinq786uR5mFWfXM7li;ZdVm}3ard?P^M_oZd8-#p^(&|vE
+9r4pslqc<d?ltIp_Z}c32Z`{r`&@QKggH;juMt^Gy|)!bkl_5Ih|`CvWB2HKrXI{vyLU%6dw6p!5H1}
+^R@q<R&26g!##~U|iX{UNKkM{|l8=<?y01pJDaS_5V6SwwK4LaWi`(<ocqZE4H47z6AaC(SB;L!1sI^
+ctH1PKB$hw9X#3B~`4z20$jK!rCN^c{h;bwW4XU&p{Sz-k$y1g+c#inji*s$GG_Vhx%Q62<voXBcBn%
+*_b?<z-n{OpXj&<MY^OB3BKqA;}u5XP5hkRv5q!{O@a-H}64HH%*9Lf%$jMS#o5Y^FO>mOY5#b#hWEm
+TQ^8N@z%cb~AD!0Uz5ZR-lPSyC(zSy#$S6*7!5x#XA~=l3$>b28Q!8%9v&SB4tEni!NFY_(Bhuy`hC2
+o-$8Hytm|}{8%IdRFDl7$oG{Vlyl1xqU9_HBz+?k>BJ)0ViE9sH}@%X2bM{NGDCaI@B&>>6wBNZSr&g
+N_e&273rQ2{jyK);<Z>>Zmf`7I{@gEtB`I5lccIiu?k3^qKedu|fw=?#+VTz5-ig)Vpo@f(Nq7xYQFn
+|`@=6T)g2>5Y(VYn>4rkb{nyu*Z4Esf2{w5H_@#7<wI*{O1ax@x_hd`gAP8<dL$-{&a^lBIH*d!;@K`
+#jM;cbKgy{e=)_}%KVA-<5;jCZ`m;(hVj3x1}Caks+AIwK<k_AU>HX80NDn~gClfry`F<1%_H$X@-W{
+3wj;Mn%{A4oZ@T6|K%okVkpSMn`I1<IOAcOpMpuKKG$OA|?lHb(RDz9RNl&n1(I7dgok|2@|2#-7o37
+EZ~l}HNY#>1!MBNpH_vJlJL@!QGJ`t;qw)v#p7Ji@ICB^H~m=A>V;;ZbXN>ryepKTL7Aj)ZMPHw83dO
+7Unb*xSQC^B))$9B?+OP%27RNj&N4OYQ&Y8QHpxeYb%|4j4JBp_k+<{pO$haPcb~FV4+o%Dz1qDI>df
+CLSz5IDmrsWqnkoahRxZS>>c7SknG=llOw3j;SOQnY-hnlxw`c=lemV{qGnC(~rXo-4J?dvq&l1xQ?N
+U8#Yc8up7BI7!ZqfJi?=N-#6!8IGzUb7QDTQ=P?>~0}&V}x7fy&&qY<{a0vOQg_>-QL)%@N+L_ganyS
+7k`yzmZ>36>d&Bxj@Vw{2u{wApztQy#PsHB2YR3CT~V1rRd%yJB*th5%R+PCO$6+L)AS9n8N@tV+yhz
+fp|!^hW}|I6XWn#SHorthfQ)6hnfuFJXS~`*-v-g^i%F)^D8_MT>T|yZUBZ#imn7wH;t|!dv1%IgP(y
+|<86twg`m2|yT4B`J5si6PR1RYAEDS0Eg!HI1P5xj!%|808<7?O0<@@w_XBJt@YZ9Yb!us_mK2FQ^J4
+F}EdZ_;3NImZqg{VZxK83z%BPTnHY^~5L9Y9}Z1(|wcK6?4c`x>Wi25a~)qboyuUm?A*arA|+4cw}Qp
+@NS{i4DmUY^wXbim3EYySiA5rU-fP2G6Hs0~vWY$qC%)mwD?zqwGNY|87sqw!(mo;0qiA%F6|S3-(N-
+i}N8U5bvhF=0C%bq7<_ueU{MBYJ;j9z@#sJ9u+X`TbW&8($+3_|DHdeB?qs<<DQ?xzSPJ1&-#;VAc-U
+kp47sqJE0iip8Bs8iikR*Y!VdLjg`*wJmz6_8_ns+si@vr=sniG`m^u@4?Tv?S&M)BZakSPW7H>x6}n
+x2kaL}cUPdJKTOI!yyDTl*(yGcN@~&DHPZSRfnULs`S21qka918h)cHxKEPSDU0ZcMa;?A<A5&|Sk-Z
+!sxpx;P)0YtTsk2-#lCAs-L>KzMgM7YOa$j7Qq`rpbNp{#kzDQRwGRhbczao0o`BwgZeh1)I^^SGiGe
+6)^r)`ajDGj=IzlZIl3&2Qqt2~RmIOenK&J9m<BX#`d20+jZD5q_s1D;xt1={ea%(xlHxDmMMal5_yv
+ip+y-bWDewU5}+0`z#;HwN^isN1%{T!WbVmn~7?dDTQ-_siT<o`lAhEtc3}KRe~C>BgI%mO@nY<|pg-
+05B;8FkZYL;D0zUe9te-LRb*l9!NMySA1xL)jOlDsIz&)92jn1N6Rx@onmyy*_-jbkNQAE)I=8j@VPw
+RJ~br=WMI7Z?q?2Dz$WS@Xldmv^yQ(Gp_+hANz}C%J#w3RY4Z#IYuSSNSQh{iJ0O&Y`9&W>`F4G)`X)
++ccj>aV^x%u%{qOgRU9Mjh+jCNK$mtMj_ps4Erm{1B7M7EI%1Y|4xxY3|84Z--g=|1bxhAfH)pw|=co
+8n(V`w|zRNUhOgDUT$9gOL!j$S?OFK$EkUJIhUtF9+Z>-CxFwU^=F(fPoYc8QG5TKOkMU;6Kev00OaU
+mUw1E!<a1!MR0JD0i)oHRZC?cz5S4bT9`hh%WQwvyZwGbZ=V%e;)PMf6{d|uR+(nXi4d<z;nEt)aeaT
+Vd=~N#<YW;toiTaX_)tqhHVeZ?eh|FblxJ|q+7j0`8bg^d)Wmq+u{$-{Ro7HoC0s@NulIA`ik28YGsE
+Wy7$MP&?DF3?I8Z3w+NZU&Uhl0n+wGBT3GxQPLPx@yv*Z-b$)xR^0lB@M79M)4JnjV?SqG<0qFMLm+@
+YLbxCHiCTvBG$s$qdvV$az6|zPzYRB#Yu3U#_ZajZ>8sWbh&$Y(WYdmj=qi5+Xqf?cSBR;MXUL6pFT7
+pTW@DqiSZRp9|IZY_Jk6ye&Nfo_J7fSv`FSCV`8j=C?gp%j+s?yGf<e5t6qe98sl%6k?TyIAHWQoi3`
+2^JeWY2Le5lZKS#3HtD$`ML#v0)dgj@kvK-O9h%Ixpga<PST^XbpJSIy+udi{Dg{vn7^iM=P@osu2q(
+E*mU-Zt{el-Sca_qs)`OaaX5@b!xA9gwM0Q?6?P3$%CG1sd1l@L8bcQ^>|F#3<6nr0V;euHsJ?&0~T-
+Mk!;x|`PfLhtX}YRM%(t591%)p)6x7vSbs_Iq*kuS+Rm2h!Y@#5?8zD|lsNF>>2>{pfmy3wH;Y<93ky
+lF6Y;vmI*(glwJ&_U=ki8j6=;+qDMShYY8TQ-A}!0emU&!{17xoCl+AHH;m<EhB8%zVwWvIK996q&=D
+kL1&n05nC7QJ$=xvfh^P9Y^JG>fgM!aQIz1N~uK54>FlE)ya-IjxySR0HZI1gh!kEN62RW2#~J6hEzg
+jcelJQZ@+yii~H6bG1+1X|{2gpy4VQTeP9`wqdxQu$G(bD2=`K9&p^Nyz9`uH=Ez^H6z6{7{o%O8Llf
+Ru@-c<1lzU+fUMW7I?B9vK`ILO7%dSlwK>*>W1G31_u355Cl#L<hw1>y&{MVHsH{_p{LTkB}boIRiIS
+ghqrCH=82*E&fxSuqAeEb)(}j;k8*nwj{(2O?u@Ru+UPfCR46HmB^T}-Z|I>kTn}Ib<FuGyTs>YPg7j
+&vg-<2FNrWmCKg&RU+Z>m_0v(h+rLA&&E{A3<8{syounhxP-%x51_k<jmD|~);r#1p`4LqC_7n_?8?^
+Z9nyR$cAGN7dA?7of`oB%siA4uS}TD+{fRDUjxf9^FNn5hnTk1(?b{p*&ZJ7DN{I}wmOT81}{-U2wq&
+vxoNOB-LbA(F!jsu>`lMycbppH+vZW+<K6FIYrN9g169wcUO~<)Kon1Azoq1f{S}Pw6p$|4Vcd6z|DO
+7fLLM&-JYU`JS@$@cE0n9_U}-afbtUiPX37f595MJH^jYHWg-eVr`;Zf8mDW`uW(w{GDp<H)vqx{fJK
+V7j<*Pjt&o=C*lPZI-m!MB`^2@r37Q$L}5d>l-~}es&!}R2{OM}OTJMow+vVu<1*rEKOS@K_VABHi|k
+VIcX+TQ5BCC`4Tegurwd8^RKeV}<giCOfJQLP$aMaF%ydKFOoW$mvfKeXEex7sqtDVv0w%;uHjWDsD~
+8c24p!4F3l-_c)}I%?z$0ViffZ?y$k0l(Q}b)_Fmyjfd-ze4>{{tf@9?B|K#8Ql0J?P=ud=Sg&)@xxz
+G3ODFz%xEyXHYc<Rs&(4r<0O4~JiCz)6`ZGl-m1=|vqnUET;3PJiK1iCq-Yd)m8}BObgwoFgKMeF3b&
+$3Bi!^VQPo7sk-#9(dFBLjGx(qwT;rSh{gPwZB+J-PR`1L)n4`d^y_aXh*5}FOa>YeopEj(v5dZmo~3
+lfSr|p%sZRb+u8N)sDMIznb|C^Pvct;m=6PXW|N~!gKGaZaCHDZ*i#_jK&~+xFA$y-!*6V##lspp`fO
+G@eex`&bCEo)atUEBIfZUJP&!u#rTt?#0!j?W#n1<z?UWYihtwYvlEUaa1E|3f{uW*U*@s)q2GS}Jm8
+{zWgW<6<=2j|VrFgpR6B9Fy#2-Zy&k5mQLt+JzY-kP0^%@L56%9U*!DpjE#7-56eM8a_9<u;Fcf>Rvx
+Zlh>EtH@E5fVx|o>@t227})Y2+l)CohXOEoP~Gb&4r@UJw5=O5Ftw%Fzr0tzeq*U!GrZcj6@3NP}1i(
+kD*mk6A_gbMAhs9wkCzQQdhCQn?#Nr`_u>g9IRdN0~5`lwW9@N!YDrCT}Gj#BC6K|^<sPx*GOy@-L>+
+aO6O?#N0sS(!A4h3;4gy+yxlc?ksgFf?b>}<wRSiBnzbC9|2RO;%C;CS(-WLqhP_;ZKY94$_p)#J$T(
+BsKv1GfTm5)m=q;j(kxeA7uoOSBi?{yA0@oH7nBvKrOB`nI9}RmewozgsWN*>RH~Tei<(q*=y~Ug8-u
+6D<NKoJWEXuKt|I4*GR#vC|_ceV=X5qD&(NouIa_Ck~CgV#*?%tZ4{;cc#OGU<^tNgW(3*9SPjN6TNs
+ndVOKUtI^vKe?G&~z#NqEK!fb>$a|@JpOmeBOt?@Tu>>Px(~ir+jMUI=VK$I=x1l?qNGXlBhB}=-T&j
+bgQ5Glj)@Mxj}vN(?~CKvOuH|O6HJ-9zd!w`tUTAimH1knScHwr;lM9U9l4N;GVUhmirqu`q?f|cJkJ
+0fQXfRKGLHtsnzco^U?d|qUe11)0+X_tOKqdcEZ)ej()+&820AKu#GE1HjN8==y<F~D0fJ7vtV=JoCN
+8+Iwif~avwf^WjuMT09(5VZ{g=2lL2MBPM;L!C&eDNoo+P4d$yYK8_D^dkZGmFcG4A$>N5wCyyBH%Xx
+-{(KvK73ZvKULx=`x3bebsNLEdAT&8k8lI$1fATr8>4z%Tf1dJ@iW^bUF?IQVs0ye9_U)mL8!#JgGB_
+aDBe1u|^viI4clblD{o(^63ct3ni^bWXvW#gUZm$7u@9n-=+Y>yglOGdcN6`3>sZ2ly8tg0{y#;`V%>
+LapfekDsqa2av7mTZqFH_mt35vwX9Z|2@qG8apk(!ofH!MHjcSy+|^4{gVtX??cNyDZfq%jhIHC!u<p
+)p7IfwDE{?JygOjb%^xA^x}o0I{iP{lo&CdS`@KGY{G*p2{eeE5k^Jt5sF&h3z76l;_MTop|10zZy7T
+yaat-Frfc}E)QTPdF0H5rXKu6@|`}BHvlk!y@WmgNi1Yq|5e)@C<j`HCD!`{2VMOAH&<9m1xF9#G9!p
+Eqn6h2TWQGCqEjLz6hqJmmsfG`NjV;W`@%LfQ_ffGetE4x|O%F4RcwWrz>Uw~!4vLdaduGXQ^!XAiap
+8r~V?=v$XRNwo%_xt_+Ki_-c%v$@k_TFo+{XBcG9fmpi+<?2w?m<zJw`*OwuE5tgw2?5U`oum05T$*v
+K`@4j&q5PckrR307kYf5)*G*J!`s&QS!&ePAt)-6s4}#;%Cblw$0$Lgo{p+z>=Dz4Bj`7M1Oor*MDvi
+s;U`{r1M==Z^UC#oyhu+$etolR|9kH`-@g|wiVwVlZRG*^DC=Exz#=Qpm@>s4YN+4PNIy*M4#j<%XJv
+D8OQ{dIdmE{SP}W(R1g(-@^QKqekh9Cz5n`$}Dz){ROY{@J5q06xeXsQPdf{*MCX3pa5mc`BQL3st0e
+d~3#$HJiQMo77RBQ6;GF1GG(XRQrV#?iwGzxE^<_U+Yxe_5Nlck48E2cDnqikJ))^}6ud(k?WS>q>h=
+j|0!{_J6gdpMnW6;tXx>^7j?f{H2kc-Y~0IOmLtDffBUp>8qfH5F4{^>W+cdb@LA#gtdT4%%!?gi5!k
+mbwXl#$P(Y(n?2aX-=Gh$SA?+12%?Q%9r-zm)S9w-p(Sr@7<K9OmF&x-k9{=A(Y%9H3#Va^wt%0HV%`
+<*79Was(|ujVo$&;p30L)I06!24y4-HD0Hb_3lja<?M&=k<X-2IY2Y1@I`67RJPWzE`#!hc?&qkSuEk
+wRkceAZB9foOPrcYkMPqTl0*=#MP1Ml-n8FNi1&!fr&j#w359J2x#lNuz3K%ft9N?J#R1Dn~h6Z=@q~
+Og{<A<*1snp#(J*8$>#mmi;H*kYEb^y^$e`AeP_}#eTJF14>Jy<!0H2dDt+E??$TJN5hg$#U{wM>_vg
+_dc5JtcP@x3;$v+6Vu}{Tn8ron;oz8-*@yr3Guym(Xfxn-vN^zVJ8Idf`swgmYMKVNh=8G_Q?-qJshw
+L>P-nda9ekzs|eH-yk)sUQ0liL*hgoEz|)$J%FpGs?#0~GneNz<(JiVKllxBJcfP(n&wEvi4)m`PGFO
+&>K_Dot+xA?CkHruQ8><1dmNYIt~#Z$c3KQ3Pb>NH6Q)k|Chaay&aii4lCP_J*D<8J)85ZepQ0#F8sV
+Ut(Sne5)txAU9Y@=pVbTGN->=C(1CoeIhLMI7#lt?Yy3?VYrnb+S7GO^ShD=ty-6E!?(EWapi$;6DIu
+u-*Hw?(L=?p^sG2no9ln2t@_8Y0n02&YB-rK_^JWO%g?rW@!i2<K}zjrYQU7KZU0+{H}{)mZw$$QxIP
+T#(Rxb7T>-lNI)aXix{MdU9=c^lHcADg`C-*2PU6FEy9-Ui_m)ly35ZR}9HJimJjr}a5l^LMeE+oWNJ
+<nyH&h8z=a__-*R&NtMDpEo2QwHfem$dqHQi`$Y+^*$YLx(1I~<8pd94KrFheKM-|gCcL#)ead0xYOI
+ME#1z#<ILaKv#60Gsu$5=35!-$^$e|%tuPEw+rznHz>$tl7j_mq^dv)EE5dlg(O>8&Ojm!sBH;kNG>&
+%oQp5~Y3X2nF`+Pe7IO^(|wUh!4j=|^^lrSzUbdAfr7qP1uaHD!c9jcJ{k@npmq+`;WoI%vIKV7cmec
+a+n%bNF=zADt70d+r~7~Yxm_^ELZ#bGzt3`6M)&}RE~J%Beya^=ELr1P&&Qba>Ku12&P6HZDIpQgESY
+dSk8k|bL!PRIJ60r`Rf%T89-U^BASurq;2XG%V0f(G4GJ7fdIX1wqLVC4_U+XCJ96o=yaKGXZ2-hIPP
+#aWyPCP>;>%eBIJnDR91MZAGqSHE0QyS7zRvv!H0c5R2g>V3Pic5Rn-N2t?ZS8M6g)k(PRR$MfTeObQ
+RAD2jhR&|FX^g<KS_(K(#qHnc(>jQrk4l(@^DEN)qkq5Mhl-qBX4%oHuCW*@J_*u0wND@E)yZe)$?E$
+7uesc`YN??*l=d2!+Je|<tjM8*ADeX##l0cN_wD{pv<Mh@G9fCPaSL<lhzD0Fuw};xt;m=6?iNYUM<w
+cF7N}t>ze5~5I#~G#-jyi+2!iP?Ot#I7wC44M2?IO5=D}CR{-CBBonSHi4xzRplI<8pSubEEpwC>R9x
+TnfKb~=7Pw#QB<et2#Q<}5?nWAOBdaK<@6`zC%{b_QwR#QjE?x-WKNW@^m`wbdQ=fpxyGZzZJj$OwJ@
+w(@#yg-X`~PLMN=eW2>~_N!o`{cULFyFQQ<u*Y1fUjHh%)K444{Xw%0{-T|MfQQ=s0UrzwVk4gS^v2J
+U!^N#H$UMIN1)Q*9DT^h53Z#7#olEI8Izhh=Cfupb>=d{DAnqiHX9xPtqE`4w$7<rIsA;`c-$pkoRtq
+?Mp+ze+joh8Q+mS+dW@xH9>{Eb-OcXNFIjmQLm?0_RPaZ@aQw=#mruu95zD+kPdhDGv3O-Hvz4Wpau_
+%@9;Bdl>LwpK;grxR|>DRCpDdMJ7-p^AqYkrH2ijomp#mApVE|}Y-h(rv1((#Nq?|Ebu?%r^2)+X<F_
+-V@zYn%ai9LEPxnA4@V2|?n{2e47bnEJb7;@eXoK7C*pMu*YrYSt)W+!54kVv@?Wb<Ht`8vPMfH4b6*
+Rg$XqNnA6l`pNDPg7m_E+zvGF3n)l^3vww+JoFsQA(GIy-3$qN;xS2T$Bm;xkfA>PI7>rb?b_p_v6ar
+t2IW<*J${uV)R2?j0{$mVWBb+j0d?$V#P8eKe#DnqP@04hs4oI*^e#NAQ2o6lM9{a6+~e>GI`8xf>VQ
+Ju1LB@C9Y;y_t6?evU<8=FXm!v47!D>MLZ>M{#4$uyqhI12v<r0sbBPJm)f6pp`e1XzYO<>8Ib8VbYz
+CQJ+gQ7{MOFP*v=Ex9q>bD?9VJXv6#|yiX=`G|uOzsjNB1<L)<1pnnU$g1%1b^g$HA|!sv6hHRd1V@=
+!CEF(_VyvecGE1uvy<CU4{`_Kimb1oCaPrO<+ULgEDhoognYcy;o*&3)9Cde)AFKo2m+R?t-M)qfth(
+E7rDr_r^QK5u&TtT*hqEGx@3=`j+XJp)q${1!eFZOk~Bco^`c*!Y}Q|F;|!#$1oZ<v`XTVQ#^)<%ee8
+YXbGLl$Vr>ZT%FVLX7w`2x$4gT_^}Rhulmzvnp&2r^W$lzR8>DPOB(vq@hoGG8SQvuJ1_%Nt$oXz#$e
+3Z2Vo8MX}&G`xP9UeYQB^8E*vy?x9OA5u0P@Q!E%zfWCiK!EK7JbC_laa3OUy);n$Eep!>~FMj^OK01
+shF>vxNxjcxu)U09MPY3&h*nl|!R^<HsIN~M}NKg}pis_Of(pQ!496w;9g*63v>+Mda6k*gVkM(M&ZY
+>QAGu{T|7{aA{)Waj+1R*LAjp0+a8&q$IfC)z0NrPn4v0&xE=CSX>1Zlv-u6y&l$L*=uf4j9bYyEJDP
+<(wTd)cOPp&F$kZ(h0UpeGy)Vd**JOFu3llrDF;lhu{TBFfXH5Peh7)x4FB<#rI&>NH=;^syuF}uzym
+yCZ>$QF#p2t_4GD66t|7&@(w*hfck0GI^kV<hyBNNbRwR(fSWtOArS({Lsy0uCmM28{0b*SeZ;g~Z2v
+m$T^D@z(1ue`iBmR0n{pB=8?Gd(r1o1S$#v6$hTngdq!o74dtUW;Vd4p3b1an+)K;kzpv;aLVbUeJ&u
+HL+Yh*&>UUvVXy?<V^mm`E8U|_3)j<3K)wIeWYH`gV+{BKP0SKuzX2AL1WPT$p=q5ZLk^UEe9psmo>8
+@$9H1W96=mOfceSBZMp|7#LHF~l8JZFrO|QYdZNoxA<**WvMlpgNyGNCj06)VbTsuF4a@qEhtYS}8hr
+``AO6l@GP?!R_+9+kGAL8R89NU~o53N4jOc19#J7wv`}VbiX{rK_kHI{(zQw?2*&wv7a6)W9cj;XcE!
+_l?Gfrt<|=fa2vg#3+zDKF1oK?+hM{z^~WKyVeP2F(UV?-q2g!U6>fW#el1f)`UI*Xb%7c~#cmv@Kr&
+#c*p5DSYAAn#S$rnd-T)JB%r^<9z)-Y`1fww&?IO`mjdroPV;}9?&|XA)mN2OWZ97bK*Z#A{3K3&4R&
+>z~>Xn#Cwv&I?Wt!X``G>c`=-tw@fDF<Bxr}H587kYoJPL^x5ZL*+3P~=YRCfVYwkwgRlyM4o0r|56A
+|6rv!Sc}sc43Y?fHD?PqzR8cfGsdCoJFHmnrg!wAJXC}m3ritmQRNytzzW^Wl`=~Ossr%dz6of$A|pw
+LjHE3orrc=2u2a@+R&~Q?T$dYXbEBQ%@0L;nle^ESj=I+RX(rN>dWrrjS{cg>iQt?_d1W832B=XlD`f
+0j`2HQA2v|kt@OH^cH5fnRkGW86~l#34A0=c1*mZib)g2SvFeyTbDKZ#f2VYrKI@Ec5O$KK!XSj2@gm
+tqrOEqU!-ZqUgrmlhAK0Nzq;^5L`Bk0vIfmWegaSSV@Ch6r4)`F323B=CcEMy>A??NA%k=kG`g@7~{z
+89$roR{IZ`WSU!gP<Fda0<_y@tqYjSN}=_>Wu1MBOvE<I^x@$P+m27rIo{Of64HWi~DiJTjXefuP;=p
+Q$#Ah?}zcz_vio`|sNo+-CA@>LZr=fNsY3hHXehqv!5}n0rT-?0y|}SIh1f^wfR3%Y7(yC$js;dK9Qu
+aERE(21Fykdjaz<MYQU;zrSOET3_*L7%bx@&!?Vd$|-$6dYUSu|M+P(KVAm2R{K&KWH5~*<gKS^ex-<
+DJyQx=-D#gjZ%URvLU0Z3r?gbL1b%EyqP>T<e*RCWYezbcOFNyq7>&XKv!HVkP7TnUPh&f5Pn05F(-E
+!;?+DkHIt)A{aSsEei2Jz*CEb#MeuR*Kr;!PFaF<Y>@V=RDjHO=Kl}NbYl5kM`yPfu3sjhkH&3k|EzO
+1e-?ymf<Ke_MA%F|5=vj@=5PI}jI9xuuA!%MQ9@BfjTv>x9gZ+G36(CB>L_3eRPR*YL~`x)5JF^3vFO
+u&>4q6Y=h(KoL)$|+(R2LmRidnB>_PInTaYcvUajFlH9$6#~Z2`%10oKovEzzDrFCTarqS?$hPQ{2%M
+)efJl^0c+ysH_d$u*J0dVwZQC?(_w>X#74<T}(Gh0?DAf+Kl;^we^}*X9K3<@LzeB+8q)<TUmXeOkH`
+=Yh6g?MQ_JI!M6iOd(Pp4uL!U<<V!RS5Fh-js|gx=r@TQscCRMgV;gp=p&k#))h>nCVKCIL#rit68td
+zRn1?EbrCAA*Svap3x@yy5I=Jo{o$!HC*sYb`)g&d+bCq~eNCzIifl*=H9;qdHZ~YR*8ZV($Cs@ja3o
+sUU_!|U;PRR1P@Cdfp>|{bT-ZqS14J*G?vc39yq=+mn9@G~3=jKivdF<?9t3Img#&x$a6^zCUKf%D%%
+Qo-&degX219UJj<6Q+6M5{6+?_TANJC-WjI>c+5Kq%wdP<fyRmpGqm_CI)#vL^U;*MeYRGx_W@9O*WP
+qMsU;I=XO+*CDg@GkTO@uZErFG0`204l*1+IKz)xix<PZZxWj6xVdl^j{ZB)C+=m`?!?sTtGn!z1+x{
+u3gHHr<nyX~eArQkd>oRx!fUbhVfXUP!jn@3<6O5~);-xtGrk1cg6l$!$t|m{l`|b^a50MJef)l&cU%
+O+@hKjAX!e%#zgkujVecpBe{U$&6I^}LUhJ6~*JpJp;yx|Ekbat=x8lxNx=?qBo_dD13D*|c30-KIoF
+VKWv_79^2UsaZY|!H6*oOM+J1VANoT&fDf$PKb+!lWU3*2U9RvHrC7nfM63LI$5KsW^u&U#Czy!f^B3
+f%@)REKdC+sRa;fV<blBS@`^UazGSHpes)w!E0CgK!$uvIma%sfk{M1vu3_&(?!u!MKHnYZgAD>%)65
+NmBWmn0&%E3S{w(0(hp~Y7}k`H43GXM&Tb+*Pv$|(_kHo?@`A-s*vj#5ghpml3r*x<DT}Pt2-TjP+bJ
+8&xNH{U_aE5=wnm@p`u_NnKlFKNE@#s??MvREq4|EdQ)=SswGe_VqEoNVqYQ>wAUpf@mTCHy2Rt$N|$
+)3Jj8=8$%Drlv#^h@#+$tx#aH*?`ri9;oe>Vv)oLy=4bz!kTobNCLajtCaEGOc`7`jOKsP~nyp(CLFc
+U2Itm6Mlxo5e`U8BWQ6kTF#DK6!2rsWCcxQUm$2FpF32`0Oj3~IXx3z&TY&|jt{yo8r<s>fCk*F`&7b
+WVr$_%zI+-1_>BO7U|WJFF~z$dE|!AVWZQ7!oVK&X9QVMT!K8&oB#(xP>7G@j-^9igz<)iCE2$EO8A(
+^2JhyB#E~&#42Vpq)c35b7_SaO$^6d&qNKwG1p=u!;vpytj(n~UL4GDWSbbuaC(2A55ut@iCwo*9P5&
+Jmf^@Hv5nz)?S^=q;ka*0Y+*RIWa66)$9+WNc7~(=O>ry3@zy|b6T@-!RlJMgcotbKXE;@YW@k96OcV
+1NjtbVqjN9DG(Nb@7Yc<m`9QC4!NetH@KK3@3ax_tWn@cI07|w81(kdz$UWWK3E8{KV9Sp}E(&A}`Hz
+3~1@J)yxWOzQ}jSSz0_$v(Gj`%i)<0M_&%<x9U8yMb#cooBsAYR7sEr=H~9QOx`SqyJOJdNQZ;s%CyA
+U=)ZU5Ljs9GCIM7=|kmk7Rf#;=v4$M4T|3Ds}v^gz*`1k>RL$S^SjYNr)d|II4se_c7dn_)dnSYH0B}
+hA%;U3&XPz-^lQM#A_IiYI4Oj3@=06%J6c;a~WQP_!5RUAZ}v#Cd4%i--37|!?z(G%kb@p4`w(XA{0Y
+Q=#Z8wY{OAvp1ZCG7?MM#3os4y6~Cb^)%8lSNnkdu%qA3Uu4Xn(%w`GLWHOsqm`xVgq%)hxi{;p8+k(
+>X(Y8c_$J2Gx<7yUE4K^p3&2nZF3pPiXO**rQ2b(5llfrD0z~)V6Gm+V7z~&`pGmP07z-Ak>31K$*VD
+lQY`K5?8H(>J|vuS5GWnl9-v-!Bl)c}Fz{mgPtk*g&F%Nl0+e37e30?Rv?<)$Jx-?{!E;C={>(Uo*$u
+B%aqZ)|jr%;(+VIWj+BhFL-#NvVN30?d#34B;FO`1{p_i5oV`^Mm~`{D1ei?!SsVY7*YXC6(wp#jLvU
+fT?>Niwx3kAi3CZVK+|09bYxLr`vPu!vpdvzLZpX6+d^WR=o$E_*@|zL}icT9pmfr^xWhP)BX;LE_)^
+HF;?%jH#=2^Xc(}zN_!I;aS^2fX5M395<Zeo$fI#W&T$psK@9bQ$+>`9`+4AA(oa`~Mqn1g^BU?DQ+)
+y*W7&!t*g3xCOFfQZxQk!K+=Kaw+j#?!j&4N44dBVkJ{j_3NCqD_8w4$gyDm`aFj1`!fQCAz0~(2Fq+
+>iTz~KbveO$+p*OMNW!$-?Ye&6DXlCu(xu2%>SGpJe&ssk`!VX^mFKA30+D<pRzU|xr@;)0Aoi7m$I)
+(uc*bLBGoqDMg;^(d(QG;Nil(p_LH!?3)d*m!a6b_N?fxc<k>ss@8yq5DS7cGxogSi-xa4W!?BD@v=s
+c=xS<XBaAfZd;WCv+;xnWF_@%3lsgq52IBn;y|LjR^lj`;yW4qv28)mKS<A3#2G4oX<PXg+B^(4;<|g
+?n(KR>w-mGKp5j(1;!*-#^AETeKc6~36b-V&KbS*D13KWwfj4^Q2{qF}u5j+o)aK8Dsml+><i=8!sPK
+r~Io+uGdn;CNrMUYno0171;QoY<FT3_N48(J+VTQO<hWcQC%<x`O`#QQd^?p`V-Q$elku#FCGd>!1o9
+<)-Ucq<CO8KOq`YQbLucwERhp&mz8FD_+^P%+_rY6HNOe}(|4o?ziH@GI$Cs#5}(!24RJ>eIV@DD@1?
+^TbX=IBel+RCqop%O9Ni;-$xAuZ9?*;Pq+qg9s1t5b92vZnm97u{o|a0F<DCaP28FWOF>N~yMoBpego
+qgrsT4@V8(V)#Hd?R=N&iT8bV3u+hhX#?;6s3qcM?5px0q-$yQX)zfFp@vO!d~rxO<;HMKiBSkvsW$G
+FBJP>Qh^<A95-05enyOA!6?Uys#2Rn{4lFSWpW*QleKok4z3>xur>eRN<gP9#p|Sj8plV|y9+rd%uAx
+Z@Z_`$;8I(%wsHT39sm2tO%}(Lh=wh<8mAT+VuOxOFRc{{<?~I}|f<z+}U))}!H`KT;h3f9-6?}xwg5
+uSl!BPAZ+e_#s?R5_3U)DfE(5L8(<R0!-uuUjQd@BkJ-7|2D4?9T0^qM9d!>=y%)=z0KpJ9JLiK{|TR
+oy`6;wJoRgB#f(b7s65P6%$nZ9+?E29Sw*VV@K+l`|2i_rfpQxL>_Na8M)q64hP4c))E<jESI9=2Wgj
+U8Z^QQ9_y^T_IFDx)El1lOjH!$Y?haN@s~eb=OPipo`H-&Cc6VW~k(NIfklsc<U2R=T&wE;&~s9R<&^
+-)d2ufXTrPD0C;$xibrcS;)!8+m>9e}mRB}=;fK=UTr-1kFb{)j#2qd#5G6)Tvx2KT`?bkUrK8)w`Bj
+qYybbjcS3`cJX2{H!+8Uk81Y-H6wpr(&N+*IDF{bv5RI*;0fY-0LpY`IlPA19DN0_cXD)=DDm+_*6lV
+;%zl{nl^M`dsbOtb12hTsV<ouU3!H7d+GpcVG<<c!hQ`NSBdebWLRK{W%}nMrzQ#qJtEL@O>z0|>DlG
+7N{N!BAhVruuN2ba9P%5CCSDAvurGlHQF6yL5O99W4+n9)qF&e)KOz%!y~kG681K-l&?A5i-Pe7;^9?
+?c^raUBS3ZLD=^?<t9y>YQt>s-~I#e1Is{F-704aN5a%&U)h?3=LB#Yp%)ggLzP!MPzwcSsBH3L-vM`
+f<<<I8W5vbGn8Uq&=dfb)@8{4mf#uMAx$hiaqqs7Mc%x{0n1biaN>{u>_<Y-%aLk>f3EguP4AQ2MKWX
+C2za1JXe%=Q0+L}CTG}dNoTnoL*1M6`*#31aZYE2%B+mmn%4|ul7DQ1;BVghoZ3$ujUgHY$C&Q-m04j
+Jk<hM;e~&<qU9dYCbY>dj+(5rUPvxF#vWJf1dKLEd<TC;9UFold0`(KZ$(8jTTJ;S$R*v;*4Y%c>3Dc
+qt(AxLQ(GW7N>jW>o&->$qO@t#j!ExT+5IMYQj{h`ZA7rR1Ckuv84t2CHcj^mMIVig<4vE18!sv4dy{
+C!JfNU+Ag@#+T8{)L1D$jMtk9KD%kpps@#O%h!^tR8^C}izw7$%!4uJEwxlRLHl&Dj{|wYRhN3~25}w
+#>kOo~Ii@C>ZZ^Yi({r;~U%D7f9=aGbjJ_CI+lwxSlMh{?i{bP`ed}UKv|pi%!ANy64Cvyz7+$Jzv9!
+6yLl?v2cCL%zMP@73x;+jp=}Q*_-P<VVk7>c6xe68Mx`NZwWT=z`_s1ts55OF)#g#GPf`KX|8P(sNBc
+tH+qbo<KYGhd{<Opq9j^a?S1YKNdks`jiMpmR$ehn1}uY{8zJQ3o#KT+i(O@DGJ-=KMXyOic}fcU)2L
+7Y|W${W+3@H;vtMoDv(Wg!N^t43*%yi~94b}F%(p80pWmB!%{;O(Ju;&*jUXzIAm2~8d9oT&b{>ztUu
+bWS8{>pWCW^usSH(tgx9(H}KVgfW*FXNo^EbrVPbfVzoZ^-aX%u(aar5q1Y!|3Y~biHkHYeG^s#Jr!A
+RE~g47E<$^hs}n?*t_dC2HIV^tnm8^Ks^{5iS=YoCrfcG4wQHzpEtF60ZK5al8a#AOob<<Yj)$bqlt_
+)KK4jNq{7&*DVVn3*7U0@?gwJa5liXyFMXh=xO*xI=v0*Z9|83F2{0z6}m{&9|F?&}XK;=TtK$EZsyc
+A8wv%Z?7^^U7C^iT{PWym?wW4n^~#@$pU(X6C$`&co?o$OsJdQUctciUt9>A_z-IGT@hgl1jc2(9ovo
+{-egL!Np_LT&nXebs4I)oH2=Z|P3$8-(iU+C$k3olVUfeoV=D+q5OC`orjQ-z?Q@cPUATf?S~-qtW2q
+GF$apRe%~?wYx<hECd*xb}3a=*hg!H7CpAHIZV?<)m>ckMIwhkaQn|W+{|H>AKN|`gGqrDRCeX6?kUA
+Bc2&h*Tq{PBf@{UV@7q)>#%KlCiZO&D3+;BQ5#u8T(}*#MYQzXpaE%yvn6*952Q^#x8}Y~neqofAT8v
+h`gGYnU1eNxG2ztge9D1QTi}p@$c04z&{j4|LWIt^+6N^_)LBH`KY9F|;pX!tFh4ANsjKVPJzJ%soOp
+nEGj0t>%Dlsns3OehQBS5VSKb28(?O&2BD7i!0$LLi%=5-nB)9Kw_1~W|F$_B|wE~0>5230wr($>xC0
+uwI8k{UgDUfS561Zf1jGWsd59BO9e`>1%LQA;&w)DHEc&N|dR(ViizonXp`m#;fk*;T;w-cfZE^h8uw
+3A<zjRZZkjRTKW$Ky^9z<;-1Ws_MN!Xy+JAQ>xTLKSkrhgcmf+9fr8~3`Z|I)ol7b<m@WS0B4}oqDu<
+Ha}~S6*Y|PnK@(tTN9`uEvWas{*#x!&OyPvS>fGuKpZPEqNR3AY6EIVn@0=&=mpHdtqYrXAla0bmWTj
+Xd=+Y|j@FlF2`_-sUVzSe#cCyUDb}LmU@jh24;h{r9boiru1eXSwnfN%z(*i;&;qc4!N6hJR4uYZr5K
+8U*%sF$Y{)jnU)a<D`;+ztx22!d$R7V79E6-feCjX*U&HDu!)Lf=J0^R!19Wks|-4R~0>WJgCr>L(+3
+OIJ9nj>%<iN4yYsv4xAL$iSL<anl81oiWQW0QA$`!BfE6RIu0wA_&*A4zvk;YmYM6%y)@SU1|OIby&T
+N!A<zrHNW2oJtIe{-Ej^gpjLm#jS9_Jk{Hmn8JviQbfi`9PFCQb;4n$Gr|;8W)hn4ODLc^n6BdYQ1G!
+6l}7x^l|~FrXq*DHsY-}%3UB}(PU)nV)6Eq$;j+qzJ=Fcj5gzX4$>XTDh;y>Gh|f>LSip`4WsV_#P;X
+9#s`@6ne;CSdB9@l2)E`A|928UMeuX_04RJ2zInFS!^|DhhYNv==BXsm)Aw2%9i^~O~abJTMS!D#(qH
+z30wfHqt8L`EsG9uMOWyH`fDzQp?B>ehx4;n8%cYzOSkr`?B<<-)<9E0$KPPL;SOiUW-qJViDyU0g6j
+I$ka$^c#)9211}ZP0nd(zsy^Y~=~4r{QSqTbLpU;Nx@7Sgp{hgAs<tIl`4%mQeWskd3R206*28Wy3MS
+_GmX{mfMS+E=F@z5q1?Gs{3LQ4UF9uozh|7ro-t3>$jjsjgFTj=;*LhtG*U@z~b%$=z{#A)#*ZQK<Tu
+nG&jgc{hMH5jw1^knBOp;4a{+WE)2|Z1mZa`2YE5tr^9c)eLVaYqOQ<Os~ioqL3Y-bPc3wWK-Y=J;Pz
+E?Q}p|x?ZpgHw_5<I^P)}FwCfz<<+m#m9sO`pMy=Yhhn$u`?I*eHe^RxNNBdmp&k#a$I}{-_vI7x9tB
+M1$X=SP^KZMZ1;T~-4ld@2bwW`++(hf?z#vkWrbfFTsW@W23bqB@SsL77<v2KLi@6#c{Ai7%P={5Q%S
+E;mD;O_JCOV>DHW<py~tnS!j;AUX0a2bU_*KPv?)id$-KCWj%*M1B2K=n-M+ULt;qP48yl$A@MW+UL5
+&xKZ}%B58TsK{C+B3VGST?@Y>q3V@iinEV^-*NT<@EfnH?xgn<y{~LP#}J?P(+p9xpF{+h?%#ftS$Va
+${K~jihCdmenkBxGbHh6Nzk)~cu{&Htu<Mpdk|xQqsr`;l&%M=LwI8xG30jVfJc()d3llAO$nyx?ujp
+J1EKWiePs6qiXDC~S(QYgWy$_HgJ{iIqU=aUXA*l0!OTnM&F4C)lKb)&3U3qr)_vVymZ)cOZeYd-2Vf
+V2)<;vvge-dB@R@`k)*&y^jr$n97ZI*6x%Kol7<w?5c-0B=8E_FpC+E~m6HsdlOuVBhGSiFg+Xp-A&b
+C$&RdG@8_Px2jWMZx`qDxVggcnJHOlu&F!LMpG1R5qu?po4P&7<>%%DQd8wtD)!#mAvOD*;Uo9v+<P|
+FFQiS7goz@aLxjjj86`+*8xjL8=zaQkEp8adF}^GMD?~#sjO_%IQxqwuHd3i7QYTX)^(<{Fh<QM!!S|
+u9hT|Z${CN-NrUjSYR7q1bv3P#?~2Qp;+$h#Lm|D@FQAT{thpBXZd%F|d&i<-Ci(-R;u^i<mv+<WZT2
+4gsngpee5S2SNs3uN&5MnOF`(a4b~cBSyqMuZ@@z&olAmS#CP{^=>UF|MzMR2GPDH~~oMa3d9_miA4v
+d0`cPFhl2Q#0spLXhT-ID6yuTP7Kp*LJX-*rg46BnAryMw9zQfTGr?OyHZaY{yvdfg1%5fmfMQ<g#Zu
+0p-U3WMOUdQFMf6x8}V`>EbGqmCqT=U?$Ml*)^e{VhC)zCRg4uW458XmV-{IrDI2dbxI<63Tou(8;Tv
+=!`Jr%t6&>m#N0}GU%E7^J<~4`FmlYAiUUP$00Ewn5}llW6$#ATuI_PTngz97Y$zv5ke*|W!e%BC=63
+V#;&EODE9Vpf24dLi9X>p(_u<)d^u(xfJ3}~x}*_~QTUO^Cr?*9oPBc2!cj#&J>7w;%Vq2aF}(H+wZ%
+lG;u6}@HvN>GaK}h`5whwv$cVQt$<jq<lO23ENmtFC&#PWjL6_1d;wBRuCqGEonHQZ<i@WW#l@}H3;<
+d@=*TkVZ0mwl0N!9(0s5vHp4b0^YOQ#}PKp0;1H{?`MT~)~)w$Zwz<qEr6pca@2Rn>L$oQLZkw07(R#
+h8_{_U9{7iqmy3I@8?8zDTe%!0;b$hUS~)+GsKagO3!E9?1@s2B1por|6v)2inV_iRyNbt@!N?YylAD
+?zNK!p$50L%u?;}xp5Q@|6SM5y6>=Mm(L!&@;=<H|0Jcp?`_FJjkdx!I^hev)}x;RcaFA*S(|Ayi>u0
+10J5qZ`IR4sMcrmROk-Dr*bGLN(Ct}G!iQSnAm4=fHq0KKgW_80iL-jcWtCw!-8c`-)b0Ka%_)362X*
+#)uIb?AP3MH4O~QHMGp27h+wST=J8y!SGF~=n5{8@cKph_ae|<Wg4jdFijVPod-G`35@Jz{VOuJ>?lz
+cCPaBcXlxB&gDR<*I&kbG@FFgZ%_^!vBMZUdg*cisf!StV5XDg7KjNsTUb55XJxhfw-GS6Oce5SN<h2
+%GN0jyA-7hvUr;1F&Q8r#c)2p9$z!OgLw#odB6GGt^#te*ubEr@S2G>i~1LWH%xWo%j#DSfSQ;J6MW;
+-HBg`SFaWi?Vz8Ft>V&BnFq8xb6q1F?>Xeu12xoBd<vr;S#MB^$L^y<g9_Mw@x6vxkm+lKSwb9YI=vO
+2XP!FqnWsmYr?1f{e2bgj?=lE}=D4#4;j;1Quc)-#YR)-_UiEJy>&>Wt<_H!*$!pMA9e~KAu$7xNB{5
+%B^%(Mh)|B9Uw&9g=2lZb#njw}7j3w@}VYlRc;gmk%91IF;@OYeQN)b_2ZJ-5k0Yv;KBKE%?2k4SL&o
+rg*Ct@E0wd5xtrI4EGK80G{PcYkTqK*#Hkn^#8I2|<+98p!?N0}ZHnvb7DXuh?7mgotsJDfI1$%W;vl
++c4NrrO+}h`DyWGeeJ`4RH1fvudvkr|Rc;B{!??vR}rNca82?Ov#O^N*u2;xe*SDZTCs+8eRjAV{#6g
+YGYb}eJx5L3k<Jbj@neAg||D9c}=fM(%W=!Q6KCld?Y?_FOxb*VLG}$1@30N3F@$+KHN`~a=At$oDDI
+{InbJ4WAOe65^PlIKa?V(!<nje7%GX;x5*75R_pyn#>^n3yb}zNBw=s+<G*?y1El)t#m`|Hbr8MX%e=
+M!<yU#^>e^qR!OaD9zbA|nFTzk!#GA4)X|dRLX{*+F4{;0wQHr4LnP*!zvWY9D_N6^XZ>^fAk_SA%Cm
+hx8qBmqfG7q%d*nKK}=r7?rI=)GeP<O)|g>YW1{*g5kIKoH;J1@NDMlAV}4Z7{q4bbq!wPI&*_ip+Hc
+wc|isEPx@`o$n|Eqb9@itrzRoW#b)F;RTG#C6HW%O!Yry-)QV>^8C2u>prjKd0Xtp;O#zOg?20KGdts
+&0yX9IUD~38#b|&tc!M@6j$R%k|bY8kT|bIKL2f~JS?Fu>_g(8X;P#5W7`Pzu_fV{6mc_{oaw8V(z^&
+h1W$E8uuL+&YhZEyM*gKk48z;q4AGL|!YKnz>?O%DO8lx=j!68am~S>&2|jViD@klR3B-+*_&68w3sf
+giI|3>vCS3F#QokPC3cAE?<V)Ohh2ZyQ)#(&TvsJHUD3o4}+KPW*%cfJkeMEco=Zc@{Ep$r&f~_4-o8
+e*ZScG20u14rX9EMrtCWW$muHf_DtnyrvQ~_p^q;SUfu-`!Ky_}I?QYhCuLuL11bXO#m>#I*X{OKy4Q
+>DFdBD!%DX(YrK6M+S)<aaq^w=_t6x5(8kWdb*;DtBj~;QK-;@JAt!+3A(C>;kZmj2tX5m>>j;!>LAq
+kh#o8f>?1p>Kw(shVt*gsML~gLI~?m=XIZ`cIfDbnk3hEnmjx}i#u%Ch%bv?yZAjD?m5_S4@Y`l!^5C
+N>gXuvfZe+?K;kO!Rz`@V$h~!M<3jocE7u^TYv`S~!)CLQpB68@RaN8G2h|RJ(k_Wm9q23PVh_<D4{C
+(a?N3yf$pbL*dbUt*aKyg?iucqCJ#VUY^<!D|TP9G7#|!eV7K<Q6edY*AkoQ8IGOva4ou$Y4E*;D@es
+nC_>`mJah(c8rLA|*~dF{TqqHKvJTH$(_!s)5*l_d5N+f=Vlk~gC;b$NCi(G-R<r9_o$V<E>0R2|Pr`
+(w4<&PSw(RsC=Vb-SuMn%ZBH_sRD|-d|Y3_cTHVW-VZuS5<Aj+&yI*+4;mIek0sC`Lwa?`&*>^(Gv!2
+{Fbs!^Pqed(p$>*Y;Z)0x)q+cl(AV2e%|QZgZGq;Ug5f@tSv$6+{5oF+Y_p)qN0FP*e~flWefYdrz~!
+c<Z(~g5N2}SQx<TZ_CoZYvS&IZ$#qW|cH*A*lzFjx$|^;#ZWonJ{{pgu7nQxMh9tC4>;0m#g?IFRQP~
+?yuehj8^PSuXou%AP3C+W+{06_}#pi?udQBPKSYr_1Zo}yDva+{viAc3$pR3{a_*UEFZaj8*rrjilzW
+|**qicZaVu$$mS*|X7yrF)Pf-3lG5!04ZCixnKW@qFTdb!rkW6JTayfY6XGcZA=>L8g;2gvs6SnT@_;
+A~l=V|y#U2%)DOf4+s*CWEY}FQokz*1+Hw=8Ko@ep1ADL4;lUCyiPI9hNj|9sS)7znXO3S)wii@x*Mr
+fD@RobniizOXXWwVWAqcq2q~Ld-#cGp|ixzJaoKgX!<2Ye6nXCw^N;m6Mfw7LFj&KZ}IKIPdVbeTYHH
+Rk`gb5^_CIb`zjn2l;WTM-m7cKck{5_oe0rh$%M68#IA&*!|%CQ=7e^ajRk$?gbow7^cGY+G|e-VXJQ
+i$R3!Nl(x}?FTY$gbBfY-Y^w9X?dv(I5PmJiz$&h1K<N0PG;w$=<GW=aJLf<1x-Eu`qy_??)DHNtB7x
+Yqam22aPJpp<eYvtNRg328NxpD_ny>I3!mvRTA;M2&II|Pau3wkML!K@KeJYpdKnx_G`6T<T-hub-Po
+5NNPzv8fq!_bio#&W3Ra1n=v9B$z7Q4U|>u!+NuIQ)jgpE(SSVQ?^qV>z70;am=vad<n2SywZd%Hee!
+#&8(Q;pJEczvZxvL)|C_mvETRp`F8W4mWYQox?pGe$L?~4ns%t_&J=x;Q|hqak!GhIu2jra36=qIQ)j
+gpE*>HVQ?UaY7XN$oXz0^4sYSm&fx|Q8#vs|;Zq#G#Nj>;KjQFn4!`B_XAXloA4hYj;cyX$g&f|=;R7
+5#$6*tP$2qj|@{*re&ey>l`i<)Devr$-P7b$m_yC8Wa`;V5_i%kZ)2>0KN`zD`X3&tw;F9|p?D@QTn%
+NJI>)pM#Cm`h8WeBmGHN#szKtakS=9W@o)0Y+4Q*9+VmQomX7m-quLrRE^Sm19w$t8sZ)xB$U3L0M<h
+dJ;E-bp%1BeTgklEmYZ%@fIW#Dt0lT=q8*BS|6ih>qIYh=UXpJ1Kw|Ekq5k4gN4*HT54t0x3)bD)Y!f
+`1AB5yArTB0_8b<xI%q{&}O2gzIyYs0MZ#x65tPQ#(^I#q{<FHi-;AV8r~B4bwF-0on{)N2{7bRF15>
+}G>fR;e8^ELVA=3nN~tUZ{;dX^T%chC*J839OvT^>bH9>OaMMEf0_u_t;R?v@++PXU2Ld-_`sgngesi
+e1g~zFe*c_BTx~n1H5*jPIS>dnH6@pP54=zTUOGdQ_Y)h#beXanyEbW*tOr4F!<N#arQvx|xQ+kEeKg
+(G*jalZ?IGQ))WdZoHK$_JgmP`QKLZEgv<sM2xjw?-`{LJo^Q^homC_y>2bZj&&wr(MHG)-m*TR`*Kv
+%Dv{%DWgs*r{w3Q*JGXys9AvD}>GA<;$oS0%W<BONzM^d2rNI_B`X8_&f4-Ww~2C_?`lE(s=pUTrP~$
+C6s$uSN|RI(UWiSu6)R8lKIzL4s!e8$0TSkWI7I7!pk^Ue~TN)3rwdcO_|>0f3iGR(VYHvz3VN$>;8%
+OP-=7k$@s2y#b>1@hIChge;b5yP#V3}B)M+7Da!N`|B3WxQmPhGMpHh4OBOR>$;qX7W%?(QDZg3XB@m
+m1r<m3667G(z;z}x&mMdh*lYV!3!c-x}9Gb#h583IfpXf<%^6$_q;;mo-t%){DJ=fJntmrcynf^Z`Ki
+y->rTowCkqeo=yPhJiOQ@X0()Ko=_D$FlSX?}3Qqp&QjrS<OKb~In!DJN6w1}GRy{0$bqx}9j{cQMM4
+nAbcrM;A>OyAw!=g~4^wT<;yRxlS(3ToQBS*eYUn&s56Fu7Oo$cw}BOKd!*<YqND2XJ%aFU%~5v~qJO
+H-~a_7&mYKnVI`@a~3xbkR#^iNN#Mn$jnjPtl{RXxcNvIGe^txxOuP~KQ|BM=9UZ0JWP&{o7HlBoy<I
+(o45SP%w;k^xOuf4A2;7Fr;nR2adQ$k^I<88<YqIi`!+f*!SM!`#Uk3r$*o=riGx2ilyvtIr3tWQ5E7
++?r6SOy+{V*C7=J@qBlYFfXAvK7FbYU-1(kqR@H>Ns>lusQRm+D{`l;QhO?C0h0Dn`#2JK4e$eBI4{B
+JBBGqFFl%VstIBh-EZwV%LkU=B)0^8`i|W*0pjZKc?_6I&qpxdBqOvKRY#d<-SqE(B=h;}cJxT3Qnwv
+=75)E^Yr-yXeg2?Idyex6;vWAvc?8IpjcHX3uQ!yNr(E+~vdQ;HbuJ%km?qUrw)_PB~q2dgOGl_*T2p
+A;&MrE60O$vS|-$qwT3X9kXfb-F7&#LSLml{4J&}LNOg-dAg*5Z%;cjZ3Ept7SeQjnzL!XSiEw4GJTn
+zOh*n6a%GrWR5Z2JB~ZEWj8&WAQ6sV%9>#z3gxuT-%#aG=qU9o^v*cKcmRVc^aYM<<ZsvJ8_7XHMv{>
+!3gVwR!Q3{Ej>nNo3<~oXL!E3Fy0xSb_wk^k1&X#31N4Cwyu({dA)ClonTu2{jBTb}-v>^Oyq=j@aJc
+c0)v+WLBZZ@Se+g89a;7h*4R_ZbVzbv`M77vRw2Q!&VimBy72Zz~qq=Vrx4EjSq=uSKzg_pOFub;m%A
+TTI6q@OA@tp9-Uh=GG5qppe`JY?uF_3#lRV@8c06MOYFabw4gpAbKBQbOXj*G*2EGBtVH^cgcX+F2<&
+{p>jg<J{{_<{Rdv&R?)FEq&4AB{$x5bH>tJGPAOm<>XrOmgg7Tx}vbCxWsy!t<>&VxvFgS?RTtMyKX)
+Czy7GN_=|P@UFmk^p8<N<-}<ZS<*&Ps3Xea<AN=zSzro|r>kt0PVb%ZB?EhczTv?|1|J@RxaR2?$r<(
+*Q+<#tw@Xsv)|F3_)mw)^Vhd)n~r`sRSGS7E+^B>KxJKsHR=mj~hr@UfAWmWZ^f2ygi6Yi?N`<{k-@B
+8z{`yY64(?frGc=IEV{&mY^k3X^X$)}#)_RO<?d+zxc{=WUimtKD5)z^0H-1Yh!Z@%^RJB_>d?A^D&s
+k!CAyYC%*|IpzhM~{7Q{KJnvZvEuM$xlD~{8ZZ)U;g9tnXkSU+rM$1J@@T*9p}IQ;m4mkFLYh}`Ik$-
+UY7o!JA}R){6Ewo{7>iqe>(nudxzY&`~M35<M+!TkNPkK%sw9G2YQ(Cnlq(``R*R(dwQ4~dYJF+VZN`
+2`OiJfcnzAT`PCj~{QQn{;zoG!qv{-s{Ow_JL2+)$s)hD!djX8Yz&^dyVw<<@R!ffESe#d4E20jIIUR
+5}WtZBuIrf5;medlf!|JkUc8nY`1Lf@HmRTibEMz*2ob@n^!xiB1FuO3pA3m{k)`6=aS2J_5qp%QAKm
+1qVJl)%m_<4o;==FMEe6Ed$`4@UrC#5d&SCYx`@rzUap}SJk>?*VJv*3XVv9$~yCHNrzM5$Eb5`mKV%
+RKQbFTb<Aq8uXdzO($!4dvm!z7Ruobu|=pe0+Ioc@6lE9g~#0xE#VmB&n&WZA=|oUQ-UC2t<>gpRZK<
+mszc=tkx^&;}@43;KlDUF<^E8QxhhQ&n@H=GdF+I3W_Wx4!gDwd(QaTeATJ2+uT=PPd0%ITZ7E!bH~}
+)_UuBn-exPYsSAqLrff%XPQC@hEo1bu3kof{YI}*g#A+#4Tgogs4tw^pLU|^cUW^8G&w~P0XBVrpt>7
+^i!r&|e3VM7Ge>O{Yt~$?FQUoCwnUTYBuB-(P7$D6{01}eS>8HZ{>&jH){3?xxz;9Og%q>}_&H>UWgX
+%n*XqSC~TRhdbIV`r-1;xu{KRw+`Eq1$yGbzemfyPpME^w!y7+6z4voCvayF(fD=7B$Me-@kVH~gjdv
+ih3CR~7Blj;)8}(AjG#VPC%Fm9jBp6of1Vh$|ZmXHQN^vE5cusLszW&MmaquE?jmoR?edP|O8(bxujH
+MO~7ow#wfg@flCoTHWgi6KMQ4fXiqqCh%27`O%kIp@CqOnS=n{q9RCz8l(hM0DK)Y9^`5aVx{?(W!Yd
+^SWs-4svcEX+9#b=`2}`MsWm&tqR!5<LypEwaFp66EGsCUU@2ZXMh@IVKHc(*v4O_|TS;+|rPwa}cgJ
+I~6%`a`Qzk*#LWps<IZEtMUQkoIlj$wd(}4Hgr8bj(Td<KCB!jr0G>>Q){Z$3_e3Ye9d$!HP`j18HQI
+0gf+)pq3lk>;wy(g_J_?>H^qTuOA?I^{hrKimvm(+Xtj2Ssboy~KBQq&`cEBy~219>bgELnwwF?4Uqx
+-wkfJn2LJY|9;3;HBzV%Svd`3i8yJBCCD%)xRI#G7vQ`OxcjooNOo-S(qtPiY!GXd?{rFuYDt2^-$f5
+9U%)A>K5*=NdL-f^c~vgKHt#l`)O?n4yaS6W?=tXnz0B9X>|tl!PwE3W|S5bSqm+hg}j~4$So+fXRNv
+|alAEm8TkVb(heJ-Bm;7T$$-QlGGKw~NJwLlwQvqwEAKyokZa-XIL-V|1^fmNvqI%VREd5>H7Up%HaL
+(B&Q+1YiT%i6TV%(;w(ukU8$&5AjOQQFp`9N^NZ=VBHY$)r*+WPa#2u9uM4}SGY>Q}&8W(cyuze~LZS
+O}0<%U4If{7|2(B{|XbHoce@q>2gYcYJF4+(@Y;9^w-DM%3HSP>pb!V^^_d{Ssfzqa5bfsIP5f0kcr7
+{;{^;;;kE4S=|mBx*s#5jkzS6A4)h?|7cJsPO@0NbWu|BylepqIjG1YYesq@wnT3F&-re&xN?s0w6xX
+7lc~FC@=geFJ!t)Clj(9-d%E@Rlut>e>cx)x*$DvNKdXmq|1*)O^Rrf!#^;EkR9+EczEg`_!0$ti2}X
+=zuE>I32T(g>(!}*d<t(4_n!gyuh4l`%JD}B0$)Q(G?Y^`lvDJ5w2V>}k%1%<${`ZUArg2Rxqy{jShy
+eL6Y>Z70-n0^_3BJQ_RVzX>$mue={lf+u@8(@9_9Xv0k8Bh_r|-!vk3WQmPZ_6ek2Ui7B&ebG%!o{H%
+JHL19-Q5&HM#~_>z#sK_o;GPW)h;Df^qO2j0N@!5Ib>!CoX-5k?g1V4}_qBkDAmzXMOyw!s}&wM8Bo*
+cfhA3=U>8odz-u{2si(E!SaKmXKE!<W;r6o$fpsqTXpHr1dM0dgkv%{1p#Vch?)CBoR>V5m4?CQ0@_v
+!Wx-e!3#1H4tB`%uq*w!<o02Z$xq-t&v_K!qaZ%B+<CrnKFHvFE{g!e1_eT$f_jx0LIy1u&=J<=uJ7p
+Q`~pJOFC;|8(;i0am>&t8<mYM=nqWY71m1Dn&l$jj(_suMhZ*1lb=IE@n51%rDO^OzLyO#D{s#D$i`-
+!peqO|Hk{7F|o-#DaE#H{FZ(v-zeF-7?ayXCl_00R2n+UlH-tw;)j2agNazCF$r=^1I&m+-_xrCJ@tJ
+kO`I%+}y8ESu(49$Io3{8BQ3{`9=p}gK(ePw?5yZC|ee3?balx#vC_somUD?VzNl7uFPl2Dtw9YQ)uz
+f)h3rUCk!A1!X0VT?cVvir*gP^aL1OOCU@59tqO+W)?wRK?&RGT0soGCK%lb|4w7=ua3I<u(`M0~w1-
+bG0{(eaUiD3AFiEw=A>rfp#aCx7Q0IIy~E-4YxrUcz@vjjewtmcO<Wy3M`{#9QFq|ND1;7KnA4&1ilW
+MG=R<wY5f=+Kn6b!^xMLYs2W48!C67^flwA<*oHw{6%GAW^rS%@EN?1Tn#(H)c?sSba-1}89&IkxCkP
+Amh)ch_Evc_0<ef@)*r@m*GA!{aGEA|Vbnj7^OdRo%`+|N@XG5UQ29xmnLanTw4}>@aC_fcLg2@nj5c
+Da5WC-*bLx9giCPlRkIug;y(ia4N1DRhcV@fJxikLtWlNd!}zQ3v?vTfjz@W%euuq<e=Q63gReevi6<
+vduPB%}u3#b0~0KOQh@D3tMiL2Us?{2P6(K3U$WUh$Y0gS#HaLm#XkX73Mt4uf(DB?D6W-51!QZ1X$f
+(<t}B1{ZI`Anl<<bu7qA`)=O941%_FKtexT&v5asa4HDbkEmXPJoob={U!y*D+0YR-|>px(tTYJ8I^d
+O_b5f4cW-5(jt1HIjk1l}PssKA-DTTXf8qo`6Pn!pi6T-7eIvY3Um`(<A}2w=K>JI0p)4bztiX=8Bur
+j%L0)d^RbE=Wemjjt9}x1`2Ojb_TuJ(;si1E6BmHf36q4oQA=U#vPKt){Ks3l6^yjIpjzj%~^hKq)+L
+lI|W+*4<+dKNVg&twl0#m!mpRG?>?Vz&i>qUGM6+{uBAOTp9BcMM5nh`JcvxZ~^rz-kmdIKT704K2+6
+g}D&TK6|V*Z^-50Bw_3Jod$YBpBikUck5&HOYsl6}2SF8cAg{9_ksh3sAW1lvp-bltUYqgJM`P8D<Y7
+!*WBRJo=Gg?(t}9R6-CLVYeto<mM_yB<3haC~i?O7e2lVgt#V$kkR%_WOVK?WOU-sWVGT(;-<j-HTd&
+(4Emg!VeVz`8r)0VLCBI3Zo8ks?#TDh_IubRjZ%>9-;-XS|LntO@IU+T8T`Mx4}X}#bGv)JVvfb0!lu
+|Jm|-s_aXt$zxUiU-ZO>m!)`7`$^?7c|GPWX3@)fgf7K^E1nGJU{Y$GYSHfWKTvSIFrAq{jf%p*LEr+
+pV^7uaW)*cKKPFE6w(YWgxVkZ4Ow3zipi3TY+os7S72HYLE<WP$oum~PBSN=dH8wRit2FR(S2<T?s1v
+kM9>H)I!~->1Fj<C<izxhU{9I|}UuvsT+JX(fvbaxE$O**0=3(piWLD-J6LTTJdkn>0(2m9d4~&-3e|
+q$Okp3zf?<4HE0c*XZfuFCiu`zSghJ&9%|=ZbTk=gqY!ND#^~}JOzqBV=gf#X{)Ukl8nAnN{UNM3N0y
+iTOkW&BR5lfhs|aww(AOPkeCwN>czNIE2Xfc)WV5huU~M3-XyPl7xVP9j|BR%#bmNqs>QOx&EfIhyqt
+{1R)^h4(>K*CwWQRe6f!Y=F5^=~XDPMYN>=kP59tf_3*`6&f{a^WDJoe>i)NwKlCzlT6$|Y)_%{Nrsn
+iFE;xa0RWTC;dSet63!H2rbmE{K9-@_d=SokFc#dhGr$6f|YwiRU(=A#tX;t~@1p6Jm%#a3W1$jL5T2
+<)M9nCxw`WUsVbVQ*!nXang)u0u>;`lJ`LRoz^DS&qeu{vZz+DR~)r->0*ex3N@bS>{;2++s_GB8LJZ
+qkR_G3l|lDXk{0s7q0?VL7hZ9Q%T7Rhjq52m?i`gjSF3o=#r9cwL5GUD0;i4%uc?A9C_yakdM5^>8=S
+)v|clrkS(2F#$w29c45KoJ+rMX&Ru9NC{8JHKnm~b(I#lgC`<)QEY#Fv!1+Rp{R-A;J*5};c9UXuVJV
+PWlwIhskeku8P&VC&CR$kK$U%=<@}5V^)AI3Kh7mZl1pTuDC5gU^A!aH@<RmTW?rjty&te%ave-(g=|
+k#=$vYuslzuAuC&h?sQ(*Kl14GQyn-LF&QiD_$<kGeUM4PN}w`Gh)q|s+#p~Ye)6TD3+W=H^)7s&Ho?
+*))znlxg^P>9L}MV8YxQ}13BXW^i^{DQV;y*QAlE88?^8PvXVW0h9oYQe}etffn}*eElKb69dA>c7zT
+s~~3uPk-~3@&Rlvr?S7g)NU!lk6zkR+V%iO?&0kPS}Z1?GOmLh5psg!3oNW~wlLXYZ4~hGB@Z)X0{kz
+9l5~{jBcWN2ygVo*+ye^YX3e%)Tzs@3?>zXiDBD(mOT&vvHgn0Hm&dp~-^=|46;nb;0+SCO>tgah{A9
+E9Vm-~>c6Ef3-+gc`K=Hf2y8HL~U0?rs{`36j`K?E;Lz5mqHSVD}Lf&7hK9+Y}lDFy8IysQI>zg-+xC
+aH#CZNhdJXeppZgJlS>KVX&A4(1bI1J=&K^|@cd02!hPB)a>;W>%^{6+iW-2Pf_)^c+SH>dJ23%LD44
+i|I!H}bd(xqT7Aori?(F~>6!Hl9{L?!TO;xq`zD+`W>!S8+P`!izgf9_8l8czU+-_@3tWJ9zpIarck8
+d!#?(h0HTgzLVcD_k8}<{{O4t|K0TetKt8zKB#7`o5i#I9QnTr{#&2WJ|E_;?(_M#C+)xG>3ef1bMJf
+e;{R;A|CP`Gbs6aK{Qq1eIwte^fR_*L-nPO3B5T9y4a2$nQ>Pew>`4YI{@O;53~JVuQ@9QM?|$OM6Y4
+(bS6pUL!{Muc(7%?$*TDbb$4@_g6*=>``1s9z(_i-(#pc6+Xa0#>PN+%diCa%hy3+p#t)I7DBxK?`7V
+<K*$0;7}+r1b+p5t&Ehg&(^!r^8PH*wg&VGW1n99lWd;xLUv1BW^eH5^XkFp0xN4&yl-%V8{sF&wHn9
+L!-PhoKx24u4cIcvjJ!{%LOhl*8j3ws6?U;dTzUaJY%XjU3i+Xyq`A!vLS|V}d2zK9xfQhZ+u(IE?2o
+mcvL6l^k{vt`~*F77llExP`+_95!%R!(lmxWgJ>L%;zwR!zCQ1a%kXC!(lv!ksK;H?2<?~`XV>Ca@fM
+*b`H02Si_-}!(0wCI5cpm=1|Guf7iGxW_pixh5u#lzsHM?S-pqX_%Qn;N?zW9ynK0l9W!~o^<$80&Xv
+lqRAum=hmhYrz2w#7@#c>lUM`PWoZmgyl*aQ{F3&a&TNeIn;ClX?=5!A({O6#8r?aQb?F{Dq42PGwJd
+x{t{r)8d0Hd<^;N3h_K@I|Z5GJ`bfNugQ!F&8F1)aoe!y(ULuLC$P0@^FU;{mRQH-4CctN}P4Cf0>$5
+AZgeWDi!5GJs9+ZjV%u7Jzp}LR%TFpm0w#^ef<hAHX9+zz^UEO~awR0-6XH4QKSN0PlgfV}OD*04y2-
+eHGwVfO|)<xK0BcGLqqHfY)(672uyaz7b$Eyz$|X9)OA%mNp-NFLV4AfGMM)uLVDA06spNh20A93wX;
+hE`X!PF#A}52RMEZ;Fqz$2MCKgEZ1Dk`2%p$HH@FruA%zDsDFeham<en;M3fG8^BLEo;#M1c_18BKr<
+EK!|*-__*Q^T@b1LC0F>gP9|oLE1Um4x0=^C4et5GW-WJ^NI*Fw}9^j%$EZ!`De@g(KM<~d10KZOPd=
+LRfB{DyQ0SfTOf}gtpKAXsBJ_m5cwaiZ;z!8&K`NjZT1Mf8OkMQawh<A{Jj0N}+yjfu1nuJQwSy+VU;
+kAPO;Hl7lPlLV=aD+3aL%juD1F(Ju^qGJ+0DNHvOT%`6%VskAxd1<hH*}zav;llr!+5?K;G<d?H-P;X
+fI+huZ-W8eIg91D2H>~wmVuuRfX}5cdxRxAs3Tx+1sE`!kbQs$0~|V=rC$y3);Tb40(;!sQ(y%7L>!>
+e1nGganE*avhA|r8X8{J^z``ON%W;IZ8(7*J0KNk667b&$uod1cz}o<R0dFqg9RSb6n-BPp0L$iq>;a
+BYn#Xt&nF{R&yc_WbqxsM`&1d;SxE$U_u+IlrJ)fmvC%|tO0?)zTCykKFX)HZDfCXv1tN{*BhkOB@7=
+YW-8BK%-(|KJ0C@q5cz#bR!Di$;QDuB%#Zvl9038WMJ90%xJ!swp`7;__|i7<oX2=C*#8m36u@V*In1
+Hf|`Fg^vm17N~ZMkf(q9mnqiIQkYAHWuJ3w=n)7+?oaHiBeE_OE!#~0M7#00j~~lgm_NI1b9B4m&pU3
+18x9l&13YpEC&(=Ox^|qEG=Mpv;%C1cN6$O3vl<XP-g+(2k?O+kR`x30UTHiJO?}y;KLl>3~+b}!(#w
+G2XE{U1%->OP#3^{3BaRP7VmL@>f3l52r$?NX0VS0c-hA45gt4+*dbn^gD}s|>QO$x_w2mv0JhtCSpY
+OTU~U5Kb2-36@aBX6BLJ7Kg8Tz+1$a{#^c{d_0DNIJOV4(IACyD8k7)z=T?OzO@D6~hHZVWs00&kwJQ
+Cmqcuxb~1#m(YOHVw&3V6dI%~b%0Rx>`R0p8vKatLkC8h~5xg*gl02$Sw(=}!X~^=HU4*bfFce<RC#8
+o*CBG8y<3;DGyCT;TxI?`L6`0JL%(q2@v6AK|VCnJm2t@a!hmHX?lEFRTrG6W~h^6JiJa6@c3|vwi{L
+&5uBP4)z%UePHg~064;r;N1>*E5N{~Sh*wtEPINjp#k8&XP_+rKL~$)hPOY@LjMeJ8`vW}@*MCGaD?g
+4vwST9IOYZ3X93KAfrUjl=|yP&!9Ee-yYR-N3;?|5Wymw&V*x%3Z$9A90sPAjNE6_j0V;R0J_TX_UCc
+flpko(r#{g<x2id^B7~r5cAir3q0MEd?32+hM8*efhcoX2Pw-~MixOE@2z1aT(tlSUn6}BM&Z*Bs<1D
+*l!@h09!1N^Cp$w?Q$`er644FEHbK{^1>0{GK0R(4$gPksPxDcFAsaKdpeZvgK(&UudbN04Ulvkl;oR
+;Y)7#{w*BW$l9%;0})O1bE9QOvbVRMt=tF65xXYJ_zrRSbqWPPC?n@m<nM3HmIk7hXYJ$<KqE<kH8xX
+_FDkvehKz~BP{!p$p%9I(~vK)R{~snn%7f+Z@`-i_?rMfKh0?3IUYQZQwDiQIG*DO@yy9KkQszI+#ca
+Nj^mk<M>&pg7x$0w18$G-JjW5@xdOxyj^j8&1IO_^Kt9J2uH!iF;eVXt2;bs3!d8wW{DI>LqrYZ2?me
+HuafFLGju7|wVww@|;`aY}*!MvE#fcRRBg^{{sw=D<7i}A`dj`0TeOB}E?@#9|jkufz5X8P5!*>8gcO
+?`feqU4r#K}q$K>UW7s_02aK~I$C_hJuSD=F{Ao~<oiX^+o#k0SN7Z|uYVNFVlXeb{&OVedKl^t2D{!
+(QEoeS9zWxITvGRZ{PRwi4iJu0$Z|erSgjZgbWH&_*fUX60X@UirGs)~(<^%59E(7tEn<bK?o{@8dSd
+o>EYqV6wRZ%t~*!dDE8)a+62=v6wG{>t2{@PfZ6`KI6xaCv)b^A&VC;CItlr#NlwT0xd6x|8lZv(<bu
+t(@&FKyLOSr#zyk-#~+i+moF3kiL9J@215s$g2_Dx%Y%ukdDW`J)Oc9>?oxU1rB$oetU(XoNe3?-mJV
+J3=VmY~!SEe~1@o#^XciA2Ja~|r>GWC&Ki^50@~Hc&H66;c5LjyB=2eH4T^K$u?-DbwNB;*8=j9!4=H
+^Sxy%6j#p&9630(X4C&w56mnF}va{|65qZekV}DE(6yKQlx8k|Z2Hh)DxGOy8x$7f*qy6WwY0H(aVac
+<Ep#(m?a&1sO*0aH$aJgW31Z1L0S1K6n_ikca$Hwmx4m;5)XK(1qq-t0#q-4ju*{cOko!m!A2{#3bf{
+n!DaVymiEL2dQ6t!Tzjvn$!is>9=o4|Dh++4t8BST;53iAC{zF)8Fa3M4iz;@V9+)mqeW@|B-~qoY6m
+3w%^K}DSeu@U@pfs{9(@I(y+$$ZQkWGK?H_*yx#CC$_Z<z`gj%GpJ%w4eZ1@8mCA_%UT=8);Z?yqOhP
+#i<+A>Ja-Nu&NX%w4S-5Z^x&8LryUBP%Lj!sC*=NZsue?HK{G*RPB4^H=aml$Aw;61Qdb@pxKbFKD);
+pxv^4=lq-}&yHycH#6Jrq&iJCd~i9cLy;!ix3Z{*?I|AnPAJbF(D<lDGE2ne_DZck)b$e*>7gV(xA8B
+<a;mX<hA@cWzG4B<rOo-gz}0>Fv53>93cha~CdbCsc~>fc|*cFe%i3m_)q!OMc^({rK}&#rT9g(ojAr
+`(_e6qehJ)adB}ZK0cmIpFW*vwOV2{8Y%DQ&!0~gEm}lwyzxe|bm>yEE_XIrzI-{k_10TSQBe`G*=)4
+^Si5#DdCW1B{O$JX<mGkAq;k2Q+_fTwY%I}|hiw}2M#WU}e7TYQrD7S`vB^rB?zx^Ed13{LeOn@9_ef
+-7lSF3jlgPF2N@Ut0iDbMlk(A>Sx&DMi=AV*CDZJ@lO62CRC6d!7k!5EkQc+PsYHMrBz4zWr9(?dY^3
+X#Mk<FVolPz1ekSCvfl9uoG?c2$#uf9s#vNvIX`@!DrWW#xhyxJj={rmTm0|yR}_uqe?96frJ96x@Xo
+H%iUeD>LA<hwJi<b&@e^2HZlP`PMtZzn%~_YL{SMTvBDbdU=dE>Ky)$7=%g7ckGqGq6hNv;#qIf}pbZ
+>%i{-{mFD`BDq<bPgYB}kxkOQ<W=cKa$Gtpx2Gf=!jFLP@eqDGgf~I>8zKC12wx_Jkva&!8N$B+;Ts|
+RF$jO!Bm8IxuYvG4L3lfazZ=3o1L5~T_@fZM6~ccG;r{{Q+adgS5WdqR{DjfaziC0%Z-#yb=A7H_Cgd
+>8Z#wouB|H{Jq}GW<`fNUtPTxkPZ|)^h$BRVj^avjg;YUDt7{K8A&~`I~2U;C?llf{0UkBkIf$)Ea@V
+g=WF$jOgBRuqLsZf=zFj#2_fbfA39@?J{7z|13{zRGq;WHro?GXM!2>%*{KkgBp^dqTc5Y*Y>FlLH_Y
+I_|y43ghLj6@2%iAWQzM4Epmk#5^eq<dc?(u*xbI(o_@yc)t^2jNW+ei?)>gYb7l_^lBBWeEQ^gl~rM
+5a+$0LijTfzQYxMEKs-}C=>vNKLLd&fx<qZ@C8ul2$RV76D9KFe2H}4CXoyGO61~;68Yt*<O&}R;m1M
+vnGk*fgwKKSD<OOhgntOaKLz1mf$)1E{9y?HDTH@=gjaG7L_qjx2tORckB0DLA^Z#ozXZbH2I235@J~
+VbcOd);kMP}}O!jzMrKHT#&eG~AZn`FRRLqDGqvyC>wX^0LjXK@jl$kTNy3BF0W5$e%nKNgkOhIP^XZ
+SY)qSIx@U5y^*%u#dqx#kr8+?haLpQ4>POPe_sJ&YPPVmNm<nl;+F+7w+1gvWG^9~&1pBh#J8x#qd@G
+dntRQ0DmYj6%$a;p&ldFg(zoJJ&dKZsw2yQIX&d9%8wN(U}l_rWOOI%*~7*Fd&M#(=^76P(vb(F8Y}f
+;R6O-Kb?ArqaKE<F?@;+UA5>QK48f8JZYwDFa`*pIa6!CVeVZ0+{~+xKvd+QK?8$>g9n>126Q*m2k2k
+b%|j-#0o_ydX5-wsX1#e>HxJ-G<{C<WmRUDfZ`PS-54|dadqDTAW5<~Yqn|>fkhzvQ4LxxFQTh{;&A?
+)_ey*8jg2o{8AJU(xo2bDg%mo@(&7M7AzyR>za?iZZFH<u?4-wn|?n7tKrb!s=a!*nDs*?J}>*wmsz~
+$M)XeNft=HfAPs#ZJ6Tjd)+Gt-=DHtKmQU7CB1DT%XECio}<Z{QBdE2B>9a?hMHAvC~Gp$IcT3NeZ1x
+idkK-0s@R*TyFVcq{uG!7*hP$Z}$0N{ZV(Gjo=9UUENw-|GNP$wcZ#ojd-_6!bDLImF9fgYGFaL0sn&
+w>$C&1WXeY)^A>Big{)-$QmJ@^x0zw4Vz-t0w0YY&PZQJoxy%`LQ1l+yEBs?psxc#H0rON+QZp{KCs5
+9o!Y~h%<cY|dpJu{<N7XD`OG#LNHqRy#&hd?d3znpm6Mr0#&f?tPLaoR3l=P(<B@fiIj*tC(`7SAO@W
+?lvZat$Ht5OrzpNvZTVPB9?VRCbi7fh(jTy=SKJdT;<l%=OCXYPw2zl(W$H>;LTj^Ng<(FTk<H6Tof1
+QpMK5TrNJPhNF?J!o@w{IUgbm$Nr8=U^~6#4SY|F69>fsU$56Yz^j19q#}Gd)IHJ0a|(AyIY+BtTR^R
+FpQNXlsA~!6bx)RUxb`A{d~h6+|Qp5L8kHh%AC^q9QH?qJS%ipb<n+7Lo0r|GQN;Jc=X)nwc|mj+b+J
+^{U>x_uto7mEF#sJ$sz}`}aFP{P2VG^G^p&Y;g4GQRnpO)6Udi#95^0TTZ&{Y(#Z+bj{S!sa{U$>6jw
+z=E>^l<~i5N66a=F?c5_9odHtlOqDO3MY31@_aWE)>JYmGJEr+I<*#~wQ@uY%@9(7dch~y|=>6mM{#k
+neV!i)8z5lGA`z=oSEl&CW8mHLb>#tU=T6K;$m>=}77F;VLB7(mIS}n9%wcu*i>xWdm=9<5#oZS#sw^
+pq>wIZ&odTqU{^}Jg38g=UEwbxY*i3pDfcWw-;UpL~Wt0Jz`3$D5P>c8Ary;j|b-(OYtFa9?|L+jR$s
+9gCEb@iTlf4t`EYQfjnkNAD%%2!pXSn&__uD!O}mA|W2|EAwpzKS;@s)qcjQc$I^2*yoSDzg561z+(W
+diMJoS5>JJuKHEI)}JffsGsUBH|e?VAAaM1)~OL55fN@$*wt&*4-c;y9$r1%;CG`Ap3SUY-JCijuXUU
+#ig*?Lv$XPQkn0+*=L-TMzWNZqW$>uEB(zLBTaIDB%J4hatmxnMe`8!q@fdjd>cF2uLP8)alb?R9U8P
+DDo;2WT2L7xAe+oh^h57n{rTFC<75wY|p`6!4SKK4wA3A&X?EBU4tUP$|;I}{i_~Uo#dv+f<aA2<<cO
+E%%<e=uId%pPMi$(9g`|iY`prG)msHg}(PQm_l_$mf;xET7uYaH_*YuB#L(;U$1nsVM7+`W7E=%zaK^
+`EzI-#%IMXj!vnjePgrccT7Owr$%+fl7An+$oxW3!f_vqJH+vqN1Yj71yt~Zr%FQx^?SDwrkg}k>leN
+Up=|r@qIM}Sm5hb{>f|mRT!Rzxru9&lam`AKYsj#gBdJ8{5L4QH>(adW{qaen$-qAh0DOdY11ZIv0{Z
+Ne6oD`as&6?y?f=`Z@-m-f&$sHWsA9vdo)Ji{XKfm>_v+fjaas9*$55UZXG*z?A@uUsj-=vnO!ul1~$
+GH6Mp^m*EgClVZwvA+;R)F3yzJAt;@O>3;*H6heczVsWocUXreUC+_!I^tX;ddn9iFwZ<bF#{nWsz{4
+ucede^R9^7-eVn{#loQ)3=;RGB;S(@#GgSGhZ>YZje2aYBCn`RBu*eDcYPZ@&3vr|$JD*D0RQs=hT*7
+&5u{V&T_#ioJ>_@Y@LvcES@of#2d`U)vdoi=7H{@l>7{Pxt%GOM(Bbx89nhd<;{W7zYmP*RMD5BOjlA
+_L<?q*I$2a&Vdn~P#reM!oor`(GB>)5x${2-1GkX?;H5xq3XZDhcjpF(`vq<=O^|3Q+%#Ee9Ohaf9%*
+XQ8#4dzj^cKwUJ{c@PGK>hq7|zN>QGR#>_^Cp+Ee1@4ffT1on*^HyT~pv15mM4G!1<<PAN6N5Ho9N0E
+fjM4~?uY5bl@#M>g_>qHu^6}fkl$SZqAjvhN!sJe3F1tE9Azk2oRsWofXY@#uIrrJyRVQ>ImXbxS$2V
+MX>ui^byUwvgJuc0~g243U<T!0(;!{eMEL}Isz#B3F5wOORu2O^C&Dh?Y&>MIVl-xLXZLnQMHkyEEmy
+?8P3tF14dz;CDJg`Jn8C+Gq4a{pH%x9<>X|B2Ec9Fzx5-xs+>aY)%Na_p2y?=2#ctBYF`<%0j0Uw%QB
+CpBu+C`@Hx95^T+&cg**kRxC$2@mKF&EXMpgZyK6HD@yb-L3H7@wpF&b{~thQCM3l4oy^UQg`^^Pb?I
+vxyt_>XF1_lpCQ)%Bme4;gc-;aE9cM^ULaS<hQ$LNN6wIY^uiv|3r5$kMeb4@I;s5Mw%vzA>jIG$ANp
+{JR9*P%dXc(oE*^fh#Zzn5s?|jKkcpmQTS~$MSuah#pg*7E7q|~Q;~sH)R7b(#OOcL>!>x+L!UIyC@s
+rLMN`wE`Uw;+#Gv`cju+!pE5>HCP<K)ScvSr0AnLE6byf7eIp6efDfOzm*k^8<8xo4Nio#61PU!PTGq
+O3l@=hJ6wQtj0~eQvPIr_*Y2OZwB$27cx9q{fXKhp9au2mHuMARfp)avg|=#RXYMj&^>qMDm72N$#N5
+@=|&mg9GE???oQ)<IrWNNN0tq!>2BN1_!@BH^e5XO|7Lisk-72vfO7|b&M_v{;;sHV)<7ekDot}ALuX
+s!14lp;N0Q>{A%}P?eo3l)nQRGZ%Av&Q5<F|4vcuUpARVx-4u?$?e^hd^%)$jK4X(^epl)KmPkEtQ2K
+|iQ2pO%miee8_|@JU`Bz=bBpyQNEFKmYaKImwCR@OdoqT<CTk$;6N?uVM<|+=^1AXwP9~60Xzv56Na{
+peRK4X(QeSTJ-!NKY?I9PqgCe>YOmiZ+Re)J6gqH$L71P40<@hC}0EG~>?BU{Mg;Vs4Ucq@5%sNyiVw
+H!UPPqv@%;qZv!(EU5b!KKfg{QBIs&}WmHf9Uhi)+W_a9BQmA(JmSIHNKzJq)C%7jZww{KX#ELG6N38
+JQf$;!`IrljL-15#0-o#MzxTo87*Xy;*hU6%vT&%&FC*j4t`%QWAnY@nXEi%ZuQw8W7Jt)GW^&JEB`H
+9wyX^=>_lII8`yx|;)3nR-jmm0H}O^YHpc2P&1Hq+@Onl|Svb6vEKnQ*_4!|FlcpxOl}V4alcy5f%h*
+2cWn`~dnK<Y{`D%NC!NDD4H1x+9rNOWE-pIeglL_3w#Sxf*8+`z7%M)z8J3hw$f+O<()>CcdO~qlk;;
+>|d;-I>KK7&J!ABP!!9HxLnzjiXduj0@<Rx*0sYH(m+lUllBj3#fFEdSUHd>C;AbN>AK^6IOv3UQI0Z
+l08-C#O%JmV%e!W!>0jvTC&Apt|sy;^6h`Gd3xEP#c+*)<&kMM$5F67@3^ZRwgPAPbv;$6o(Ot10yiT
+_<Lc=_6PV?7L5F>T#o~nC!c&$7A#m`@F@=-78mX<+VYyLAJ<IQDh?|Z2cyr512)O(bC%kq7t^BU`P3M
+BR&mHw9G+Gj{-JU-Iw95oicM<kiZNc>U$XrNek=d2TD7VT48Zr)Q%@D+5Qs-vxST$HO1@tAg1kMcy{s
+AATvqz^d9h2M=lF4$>Br%pDo2@*wUr5pJ{%Y(#!&y<S?8?pjQ@S#Ie**$&(;4<z2}~LI;EtfYywvF5g
+o|L$S^p#<?BK`;fPKJ=2#_-?HfGBF$Vhlj9;GvMw#&s@WcBK9Xh}VdHLm+P3%Q1GhxC689aD!F%D(nQ
+5H`a*rX*H<<Muvp#(cq+PDEaO_?%fo!U;RQ>TtR^2j4HckW!lFQ=!c%fNvHWzwWcMz6p8@=IfPh=oeR
+1-S7I*eYTn;!*Me2Ku~t-XJ-3Li3H>!NvM)V~iPoeV(Gaa3T0tty*=h#yWqq@Hc4CplR>ky;FMi>a}0
+(sNq9SPLAAt_ubO9Ygc*ZnP=p==bn>k)211C$nSv{9PkDB35y3g3^-s<kwbhTdu*5(D_iq`|Cnr=Gx%
+(bG1wPlpwHN(7lz&m_!rE-qN1WE+<E7nqmdt#^{JZoH+lW_*B7V`i+(0UhYl6h3E}*XJMJ(s!rO1ZZR
+7#iffXKExw8BKKV*+Qhqw-2pbzM@(P!m@Tc2MJ(B}`9%_a_<SsvkO(W1q)88c>>ItY9Fby-G@8YOXYa
+Z;m34XIbJo@i`sU;z$v!#%;l&Olt4$dp|h+xp?G9<u5mG3uXvF$Vtm)e-Gw*|UA*^Y@p^v7<)|mEYyA
+KTMxKUB-<YcX;a5sWN8Fn4=Fq_@E>uB^kPFUTI_r9MB8!1UB#p#Dy9Jei*sON24p$Bgi9pj~EHwflCQ
+P(f{=;XmqjlA8uCN%}Py8-TA~5Pn-eH`|rQsOmy1fP``eC88T#u;R8Oy)^;o&zzh7g=1XqC5q&^M(1$
+>M$7j295AtW{BI|GH7V@vMls$U%=#SCUPMtc*@ZrM^AHV_l+qG*a-MV!%@52LduoE0?-b*e<e2v@#Cr
+4xm+}yH7OvUwTOa582X3eHcmMob}4sj{)Bb!WQiFz~d0T(srL4yVv{cYdAy~M=CNW+E=4IlWNdjjz&N
+w%zR*dua;JwUFo$MDY9Hxwq?ZRPD>82A<MNllwJ4O1G9L!aM#^G$;T^r3F3`eAU0kB^tmojV)ZnlopP
+fgf5!b6x{CdVu}mePUDOhgcguKnKtX*2M-Z>}PbHalygCG0OLx4I4HTIli7xrSihhzV7(P(v?ZR2t3M
+L(b$5gij6)fzeVNE$N)YH8ryqpJrO$!O|k!r7cUl%$76h;*XuR+L2IQ`k=nM0)kh9j*w^cO;~ih$qrC
+ka6TcDvVE<JgGdV}!I06g&MrTz{O)Qa|oNR2X>bmi7*c#;9${~7yUcwXP1Rh|M-SH5wSr;C`5B#~}%P
+*B+H!GGC_G0+mvg(#$w`>C&cp*dR!uavyMQxVx)9wLmc5)AP23y2He#nWKzz$xsXV0d_n03V!S6nRY#
+qitsU+Fy#9IRa|2@mLv4N~82@&sfGUt2;=-@p%VYz#qP2f0U<pgB4;orn1^p6=(s@0NdTM4*oi#Dya@
+_J<yNNS=TGc_ZI$y4%Th$P%*7IX(c`ZGS}L+FAbw>;`^!{;R$x6S>3(frqX4V?VHU_#-zS(01w4rSif
+HFBo~YI?M!bTbn0t;vAW={R6d`c@-*D_;+A0hTrWM-7$<iwkeAz%&e>|b3b@-J-7icvW4vg7Yn<_r}H
+jR-p_*{SX94^{Hy;SXY;SJaIrN{+rNW1yayj_PY#}8i|8fLg8~;|*F7%9&XftiyZ&Qysj_%Nd{6wtIe
+j@Mvc>V8ciu5}7aE|i$UE?(2P%(qE+gy)es}#-?L=|?2ORL7#4p%C<N$w!?}WzWoX{RV*!nJf;2fKet
+;LRMPGR~Qiu2`$-N29RmL=z<$-CPY@wu&AKxc47)>V$qXpB&#yuz<myUegN_!-Xs`X8R`!E+Cn<!60m
+lscC+Lx!AkD#@AXAwzaKPV^z)QD0r=V+H>)$bWP$(=jMueb>ID{KvJI1OAczqxg<N{$mCIv6BCIt^XL
+}KSukHBmGD59fLTY`@Nk|=Mo0b_f+!FicT4^BK1C<@98`ikS}shM<uWxSlVE(V2ynv)#rCgNJzLx<Na
+8*`8<ZrV`s$Ne{x)M%GzHZ7a6=;q{B8}kBwR|J%wA|5_#w&k!?R4SjvI{TyLycv0^jL?FOh$AIF|)%z
+0Gp?e}Vzeo(vgna1Zi8r$~M7?|%c+^jQ9<BfxT_W1f_)I#a=wer_;KRzt7`6rR+4QBrz%h>-Wwc)wC=
+W%yG-9Bq#>*xNM|BTMVYI6(KZoa|7^i1hD(&wVTLQR}n>?cP=3VtqEuQvocJ!Z_9_-WIo#Q_7c6Zr%F
+5xb5r!d4T@5~uJPuNmEo&h`uG@zC$2rcHl`nmj$W3++!1pgCxY<_rC7eovmuzQobc#O6H2P3}Rz?7{D
+R{XTkSOAeJ(x;SSX43G!2zx&yTz-Jzy3I6NA-p?d&Y@DfMX8LP@Jr0OGvd`By?Yi67_qERtxaE=l5Pi
+ldJ$`boOorf7G=GiPI5*Dy90vR+1_l=V&&nCerUphmn3}xZpZWKFzP=~@HY1Nae7!b$Jjf$GDtevt2_
+Jah+`7^3j~~~3KV`&-5&hi#ZX3^XB)0Zsv^TXx>bcYr-TTvfrGI>XfIP<ddo=X==rJLW;cxovgWaF_$
+K5Lp?7ssGW1+u4kvrH|k3Dj5pN#(LTo{nYxBz*K_V-L1`Q<U7PiOYmJSl$0j2UrmIM^FG=g6SnMopFe
+0yW{K&!=9nXSnZ#NSeaZdW)~uhECA$bnj1GF>Khdl#wGx_H*}Mfq}XSv|vzQr`MG4@AuJXq8^Go(qp2
+xG1lK-8s5`4pBs~CU@-DnaJKgyxPM?TIIsr{|JRL=HvKMoMbtE@jazx7E>3@i-h}CK`S%~u>o&93?Jj
+w2{lU5XCnlRPVM6?iFTNOuE|TvPpMy8BKm(3ja}!P9kbV_))mQzs?b-hR0y;r|gkIsOgxF#lFx)np-m
+P2y(XGcHe>_F)e?QwFATJ=dgC^J>XmO<IQ`z)v7t<%8KE2RiU!UXB3HnSE{e7~Lei#@=9(CV`bbj&6x
+%zMOGxU&{-`!_%_wJz6g?dJX>%FGOLa%O|!jR$bHM+)m_K*E1PMjG3(n~MJ(HkNj2M(K8+vf&>16p8@
+_>4jS*7NvTohV5jU9wi9{U^pAK74q}`0?YDp~K|Kla1ZO?&ABf|HuOLKo;5C-E;bJ_s4Qz_cqmu0C`M
+mTih!vYkzzSbq;E}(3t#6b+NdX9@q=Bynz>QPwgUy_IxY{zu9(H9tWP4$C()quziXCU)R6F?jIKy_jP
+o1w5hw&n@&tjl&7D5+T?e@WNm@9mGB4J94`7yKFWSfR*Y?Ho&~V-m^17)S^Te5*}vxtky7HHHf`E8ii
+wFC1|At18U1_o=<#l3WTZUy*kh&+oSB(vY8N*5f#w{czkRk5dIb7p25ahdTUEBojQ<)mXmFqEy~zXd_
+4H-vEoq!3-Me=;c$Zdd4&;sX<M!D~U7qKj%l?AD(x1IG{@6z^k-BlmjvY<?6&MB#7+~m*J+M6zD+9KM
+Y~?}y#HpmDq&_Ok=^7*P#cp!`3*}TH&`N1PrElN9@6h9+Mt|RZ_X)h9zove<xL*L>tsL5CMC?(0)d{8
+N6S~%H&Cd@wzOQUtXoT1rKWh-%L2qig$RM?J`WonmyN>`5unXJ=EYJeGjm-qkHEY&PcFNbIF#11f(xm
+w8?Cdz3bHis~=+mc<golUAU3cAOV6$~U+aKaO<i^?yo=aT3cyYGl%N5EqjQzv@j2%0+AL~(*$LC{n=q
+)__@WZCZj9zdp0~**GFYz)x72<Zq;l+#CyLkV=8kV~zfj>%1OEb2CXH{)o5q?2y@Wv(=78cIC$i2<}?
+4!2E*#DB?urctWMT=zCtXZa3jBTXmWP6I2xVPD#eXRdQmcZA>;OL(1O9BHjMvsH~)3RmD>~n&bx_2@D
+<*9*UXRv+ndEvr^$ln2_#RSJ!Ke^PwcTK8Z;zYkLWZz01r$R<W?+QBSySK~>eP`GG-QD8*9N!H5{gsR
+O-fn2AaH>BHDeW_r$M&;l&t8&~lXFaM)Q@xL&i&`SdGpS(I|~*pIH+s%f8~`|%=>!HmASdO9ka5sR_E
+vE8-7|J2A@@@x4G}9pSEt@I_j(^b&Xvre@D<ma%1Gxqd7>|&wbB9MQeOLbGKP)nZ2KDk!fN$8_!ss!j
+?Vqy)S1XKHaKeP2+dZiH{w8FnghEHYak&g7F7@Iq<Td&vU~^buPs=p+~@Kzu!@?YK~0p?~4t4`g14pN
+Ag#41#*>0&6Q>-T=ZJW$$=gDXWy4II+_^gu;yShkNDOg7bo{3_apBk?`*DlCov2$6>wv>800X-i?97_
+fLX&m_Mi0Cbf_bcvq3-jgb%XMpssxKRugX#?-A<}YZB{{Z!CCmf?0!{ql3Z${~mbY0n_KkhCzp28?t5
+TsMaQ*Bz7lmCvPBk8j*0j*`w=Dk@-rOnKNgac#vmA=&Qj?<Rvf`FIczG#Qh_B7RTHm`#SVfzhLYZJvp
+8qu)dVBD5H(++f``jNe=aoM6>@9%YS4KTaTQ=%X{y=*U%I@4KKf1pCgOM+-{!#oHg_g+4M#p_rGrMU%
+h&@iPh}$IM{7sF8F~xb;H7Ie7Rfxx!&^MK9j^+_(}H1ACV`pHg;Kk|48@!*lFNq9cV$X2%PZQ)RVZEJ
+R9G=VZ(-V?qy_DTF|ztPN#x@I%Q0IO(p-lmiL34N=|5KRr704`~q7Lf9b@W@%w96=x4rP4&c|<DmeVL
+6VCYUwJV*-NS}4$m)9!#uM9Q6yY@T(m7(TW*D5)cD-iC*IbEGc^#5C(d-YXE=WgdNJ@2Uh-=?n_Z(e!
+ujPG~wf{X#T$7nykSL(mOf@^OBbysJgljbBkDNY|<EzwDG5_IJhr?=BzuW4tliFBIlY@xHU)58=_JE?
+07a@y-P$xf;huh$P#XyWxO!K~d?SK<>^3w1i{Cxi5wo=#sqPt$kqbJEQ##^0Sk>sog2Se@y5Wt#au_(
+1)?zusA%HE(r>>Z_jm?m+#lhq;b%i&Mq5ew?{F-L>w`PD3*z&9Sk0FOt8=VCXQ=T%V#VCb=*iqG>>5y
+*|P0={WtI8hU+aeci`g31w21CScJ=A>?Ot&wnpegX#88Jw09wy_y@??)I;f=!ebXmr^Q>F%I(CMepnH
+^wRZvDg@={8HrDo^X?C%W=XV+HS!pz>!p<-VHDvBH~yxdB1h@^dHgwiuX5$WE2HAm(-V?=Bn=B4nw*r
+9-a2ehT1w0Go_!ON<I@`?C-zM1pWeUszy>}0C%24GPi{E)=CIJ@_>{!n3F-DPtF{iixnX2jo2#!14UH
+O@HYnZv4c2n5*2s6C-kF}zb5L61z+wJ#eJ3qpz#!cvp;wo*#KDP434IdMi$8RKeCtrXl|T5}Ibm=@Qf
+LzYw+@R>@0c>U|6>VhVWEQ(+xFzog0>Fp9iNn*5Y{FtqLiD@ZXQwk?okovz#0`%jI^FdMOb>a>C(1K+
+t}EScirBto4(-3I^kDnZr$9-+~&Dma=Ybj%q_?*T5x<p<^16My7|rXJLGrE@0&j~|Ec`x`SbIa=Wop4
+kzbU5JioFh*i+Zj+~Y(BIR!8-t7=wO-u%3UdCT+G=55R?$lH;(E3YUobU~!95~J&M(Ul(6wNiDpQM%p
+~T`^17T&SzA)pZMW<z2e=Azj_^RQ6QW9YS@FNZlpI)4|il)6Mg!r>`f~Gt@K6Gu@NrneSQXS?*cu+2|
+?o?C|XJ6nPGLj(Z$$Wp7n)us76O*Bj|=?v3$w@OJTb^FHeB>rM3z^^WpB<(=Z4?#=Sf_b&7<_pbGB^c
+Hw`cz1b=yeLkP`Fn)jvW8|&&sv_fBP%#NGP`+pOm>ItF4^6(*XC@@DatvNb3Dh%t(;pmH#pZ)uY;lAq
+q%)^Q*(#rj>^r-ou3=%iGCZujsH92zX4E70|XQR000O897^_9#AmlS94Y_+daD2c8~^|SaA|NaUv_0~
+WN&gWWNCABY-wUIcW7m0Y%Xwl?R{%^+c=WwcmE1@dvZx75@S2*$NG$W*GZgi-_7g9N%zb+9)^-2o3TX
+lkdzf=cmMmX2LJ*jNXbt3+_~ot&rHW6fkL4G6zYY-t~a_r@+R3dNiPq*Wi=c9h;MdwcXqv}S-vik%d5
+%@o({Z&z5Pd{gS~@2@7E-a*WOwDDak`9_9B^xv=mdX%Dn1IcyHF#RhD{Z*{oW{h47wd%XAu73A}?pMB
+&BIURo8&cv)re>#`7HA<_zAoeAN+IDLBZ>g*(}K386xPQ9nEU%h*K`sDq)*Kg18C6wEl71_dzqS>-q7
+9xtgWRYh@1@IH-iiqY(C5m`n?(E19<G2*xKUTl6%%oJm05?%33&B9eB2MNC-a?dRd?_OQ63vpiP<5{2
+@@k%p)z435ma4z!+2th=Q~k_zJ9$<npYyo7QZEV(uDn`S$z1<h>pGQK<Yv2H68_1!h6>Lpx)DVQ6po^
+y_be$Z!0qJoMC3?yS$2{wpmDEm0|sH1Tn@dzCHZrJIrL^FkOfFHgl0ciQMJzTWikg^N*F+@7)hz1oTg
+<J&*x%_ZPI|&?JYzVV|i6Jcqv~Dy_YBNj-MUBJC2^8zBqYx{PJYz{r1br$&0A{VaIbnFHU|we)`vTg@
+J4x>8V@B?!C@oM!<X<;^YHrRS^!w(0h9J>st}Sw4^_OD{$t(pYh~MI2)hfmuZw2833%-L+?^l5xtC%G
+D8^Ecp8b%*m60f0h}g<6BO3W=W#X5iiN^kj-x{T6?}^4$rmyGl|Kx<_i4Gz@uPlsQWROSvx5^4R@af5
+fg!+uLGOYnO5+8rlfljop$dgwWvM_UcD)H;48XkAl}No*h^d&ux|!h|kE^N(V5$r~KVRo-J<F1GmidE
+2teqF}<sv@x(hLX-->IXgFW*FO-kv-^{R_0@=efTl<^T~Og{s3L%p9Q5Dygml|5JPuZx8R&+5yiyf-j
+SK;%^HjA*@Pq==e5)Z#%!9yp7J@Kj&9^y@WL0^k;Mv7lCh(CC#Q;<qwc}X;yhPfJ3hnDXSI#UU{$dy?
+fL%li25n2NyeU{tAVOpljcIVAR|J?D><?4XeP;@!O}rz;|=X1%t2<@M9tZf8@guN51hUly9Kwlha-To
+V|t;+-od~EF1o{#&?p_o-l$jrcN_RET!AiMTSKFL0IO%#Syc?`QC*wQd2SWB3Q4<jfmoL5=fBv<k%tr
+K1T>cqyHDW2+x|1p1fH{&rY7a|JgTSYPeyX=OUd3{uKIZfHP+fPaV7RO~TY`kEdA*071b&d%>fj_hX}
+Zd{+6QcMyI%efLZB=C3c0U%Ytz)IiXHk06qg7JeIk-Nw6ODLSgVtJ&09xEt4<d*tXGKFhMVe=s!fU!6
+XE{p=(<JN?^<qY>E<!a4FDdmvc^@VD$R%}N}EMf_O`30Q3J^Zwp*csg)u_ikx4TnG?8QqT9pPg#-%RB
+&KSZ)=jusXI5{?(C>tD|&kZ6$(L{G;CHu;rsqh@b7Q_oGyMk|NH3T!C+^EKX1~XK1?6roBM;EfL@J_S
+A&1&V)^=~532|8I`|OsAA|c6!Z^WC@<&|Y4=#iyK7^~Q`JZ;6aooqk)1P0xetYut`0T{{Z~P4l>dEUf
+*kgAHY4~||`uf%Hhx|4zpZ#+3<oMOktwzU%|Dn9U`_1{^KNKI*i~BH8s^~Ki5>8*ZYWzK*I>EQ+fB*L
+4!MFeY;q1X+@S%JVg!c!3G9bM9>$_iGzk=#xfA<?^RDR>*Z`Rk9Pg`hKhNZ}fFFcfNp~@l>1aY5^7vp
+K{Wrtp7@Hck>%_te<5CIOTjTUR!yMU$kh=EBl0{$^tfL~GoXq16}KyZXLGPz1pQLNpcNmSh-HjJyZT+
+U|6XHhCf3@Aa_!{#zMFA*`=cRW~>B;SN~ZRUqHmPTC%YT?OW-hq~Y(~nvF$(h7yo`L)|U4y`rOac^ph
+8{|K61!dRs;ctx@ZrO0HUa5@Mk~yU%ZHC1LIXuytRL3RT~&+uF8>69Y7~#kY*|di2xagQh;?F8&DVXs
+#%^{Y<mhjiiwO*kP3sWf)+z{ea6;Nt3l=_$Y`UC_HVl5xP!L{#|Ea4HYosFOIfA_a2>jc^jrt;rP<#f
+A_<O+rwAiAoy)&7|W$C>H9S{WTARB)InhlJd9Oi6NMNv?S`OIL$_%nn)pn3;_DUb;;`mg`7zeDfjYYi
+`+P6-s#g((Ee3@E5Tv9h;;b5#R7U)O0j87_0w83O}ujX)t5Alo%?Fxssv;eOXbBFwWq(A9J;TsPN4?*
+^An4Z+^EU<zL2ca3LzQ^O5Ne?GsysL`G!=~Rs<<33x?=k*LbLUv(v0~%8WdfF^Rxtv$BqcsVvId7HIO
+v#u@{IN!r){_&}9{lS0-G!mC0#wb59+b@nP}uJ$d=V$0HJ{R&By|l$i8LO=O06=YeLbo))~p5Sez{S$
+SzSF|^$6>ZxFCd4#LGE~nj?gd5~dZ5u#gftY6km*CNbthi9p^@-oAqZs?9u}T%%0|8>I>;-ggXnbd_b
+-P)@NASZ9)<{D!N=W+&f%`z`(ZlnMY{$IE0sCCM*gJB3F&HdRHthA6$@&B+_@@xc#+P=la9XfZ0i4iE
+_Tb)V7n6J6tw!LD9j#RuPg@7I&l;%8(%5lB2*J}@%LWqR~Ho}--rfG4vx|1u`7>IFWh04f3XzeM?!JC
+RNVh`6vBd9fGVz_;l@HxfF5&}_hlaggDk#)qqHIiE(143ywM>@q~h8!|0`U}t^G*ZlsRbkhs_BZ#=9j
+HS?bzxl10T+zokT{pkM#!AcT2<0ab5+<u@V5wZH!)|qkU`PP|bh%ip{r2~IX#Kr#-%%jajYu}Fe)sSM
+RG%7>F-R=c<SI~=Tg%3wQ=t%t+i!STWU$jD6IgQ&eaGx3$$fsh@Gn}$cD=WPW=<u@I*Zc7+*92LQ8Fg
+8m>YaeC2rv+^)G6bJwjc5)P<TcYq;__b)dH;t=;s-M^2V{sqwVIJxiJp+_c9B$IDQ`ddG@JhV42XdNA
+|&ru8-OPg7c_9w7(3-FMdRczlJ;p?9yKJ)sXfNenlB?X^WjipM4X8^|vmqiGJ2b94xU-*x78&cLspZ;
+ESixf~c!sQ0!GbeWe)z{xfhn89(4xUg$bmH$vSWJ3sJ!Zw9rlbt`&o0{A!<9g=P_J)i6CN7d}S$e4I0
+)I@a(!DpJ`e@S5o;W7oAECw3D%-;c-5Z9YI#7TuCiPg<G-Nv4Mc|!Lfa%&O0Wa$!yPjlG-pE7yqZfH`
+33S@T`s%r6PQA8~v}FOhSB}tdJ5v8cD+;dFK+p7{0zTBl>2z(hAEMC^X*2Y=s~r<ad<O1QHm46RZ)3s
+NWYfIUV!EyVsftO7MFLhhJ20r?%U1g+(DL9bA(?*Ja|R3H;Hx6=cbkn-A)ElZ6#Q^=yLBR9oir&Y(QY
+_#H1^78<)UDNZEjCRa=pl@Pt&70HO$#&$T`3{B7n`+pp~*3k>3SsE0DVIsz3`RmSx{2icJN%wLsB8r>
+-$;X-P<@Ur=kwe&G*roqU<u1Z7cJd-LStK--P|CHOM4S>fsi3fpDQeG<M$(s5-n#g<M%wvKv9R?8gFJ
+x|gqNCq?!Xs)bo8oJG{5)gIWKTGMoJx_MM8L8ptUEW8Br?P9+?smE)FB<r{<(NC*Vgue(eLM8rnmEA+
+lFv{J!Is+iSH;@B5Y^b55`=bz^D<IX9fY{Fy`ADibN0(Dg!P&REr>L4$1`{PRDFh1k=IBtp1Iqwy04t
+oBn^U^d9>=OmCR(tZVd1l!-~9al@KH;djBcbWEkl3v6Q9tL5iYX&9W@|Ydl{HX>L$bC@o0Xg~TLYLXp
+}_Uv49q`irD2DO6+*nz=yDTG}dbZ{*R0=`m>SAx$HWgMYBb{Ke$E{|MH3tNH2E@@g{E+f7WGjGb({H9
+chv3d+^ZXq3R5l#<XSb<2{24ci^|>v!GiZn?Es=D|%{O2<TkPEDY<QF$fCae66d5!N<3g^FJ7IFfoEl
+`%!(hF&Mg#Ip#|@n;W-Y>S(T;#nmM)jrgqjqVU?U2uVO`17#23A}-Rh~fqfJ8O_kE|(Yq1wtyqA`w18
+gI5ln7DaR6kA3B2A~}c~4(HhlEo5z8APYoX$)JRETy3FbZvfFUg0wtulH?N3HdYXzNl7j>4>b>|QkKE
+se6)YD1;)C%?;1Ira(0&<Pz|fB5_e>k2aeJ1(Sas~oC+bDcZ0G2p=hXz^I5Y*>bEEZVE*jwq1gcb`U&
+bdc3y$eFCNw3f--0(z*#vd4gur?@8AOclZYSGcke!R3q`Yy?sgg#eHU#T{?!LufhpZ$Z1~RFKhP3uto
+LDUnss<9YO}4=XlPn>i5uw`x>!rX!6LLb0WuURC8GijMC$RB+x&6GadN`3*>@R`jEFCS?8WoTtN>QKP
+(~p~dz!a0mdx#dfnSQU3LM2aLNZ(y^D>@^X#D+Sk>Vy5aEU=!V1!=|)AYy(I20%t_;EQ&lD0;y@fo)G
+^$H{Gq5|p{%2UTbO7({f%tLhz10{@?#)!%~=p+Yv1@h+rIO`(578GKduZOtlES6~doHlE!kdDC74(wP
+c&iI4I&ZYwd0~0B1gnH%BXp3xxJX*Ht2<xGGA^(%D0{H*HO{-E83-|0Hbb3tkh(aC_DV^jwuel}4L0s
+Jsknm4kqI*W$Yr=L+#`)08v6~h)4WS3=M?w<DE)-)H2prr@a)w!ma#3U7<=M+p-H{BGQ<4KQ1A9xyr%
+b+>q70P8H$mQXh&AQ}Ajypl3Bo`Q3O;#LGOEeyzdd>S`t37gJ;YdAMRWvKHAARW)eL_;cFS5SdXWHXv
+4OrtbE^aSz?e#8b&9^g0&aT8yQWZ=EVqKCA;XZvzn#8;J^uNN<98>|oD$x)(*qxlUj^1OUS0<NZ$(xK
+&@IrBcaK6wNH+9a1W?ZxNw7eEx4Uk18>4dL%Tl`JEKgr^-*6aSxdNM7*@uWSSS}{XECK#38$kQ)vSjJ
+5{)o-i^u=)7Dav<?Bt?fFN`34jn9<+VP^aA%VY#<5`cg+l5NVU~wOA`=$syf=5nY6RkeCNPMk7E4<bW
+6|ihm9U1Jg^3?p_J;s4mp-kCzbw!o@m67iVMt7qb|)g-H7kIfC`VSxEX3kDr`&e3!mNjB)LC+1Dsl#c
+~ry4UeV+p{8Tgg_HDe+6!B?fg^=134@5?4N%;|qQMTh)w&M+HfmT#a?=B0RDc&|joOkd=LqizG!f2uf
+DO#=sEd=(Z0O?f)2W7UrL()a9`ADc+phOKDTs4d%NcB<R|y)7OC6;FJYpn+5bD)P0X8t9p+Mjhk}&<R
+NHs6<&vF97PgOP}gE8g?YDv%?j15n_Bxxh6RvP7**hJ|D+}i36R0$g5kBN4XWfg8$MLDcF64YMB^Xsm
+9s;)HXC9Sv^3su~Y<=GH>596k1>7d7=X6~23Sjg9yH^bJNPtU%oCe#oq4>Duk(|G^p*i}moD)Kfp?8M
+M<lyfu($f$M<gKJKR=Cifj(|r2mppLT4TN?I|wn)^E;%a*o)rQMW80+s<wrZ`u=E@s-S#?FWjyT2b&Z
+w>gDh5&SfO5$&qiRXDO`G*ymIfMfp$ZN?esx*tk1N`ot1S2C;szvvES<wNEaMwdqk?V2t|;1J6}udXe
+w~0sR8hG!TRE3?0*KS<6zOt-XO{%J=*y1zHcib%I_)r{qwb%YGq`56J@eS0uw(UiwM8|7K8W;r()Prw
+$88ml%TnOkyjr%darHRzHY?VkRfBK^+TD;A=L}C8`a2e|ja+UQz2s<p^Ri{-rQ&ntmCK}}$h^70VTJv
+AqNk6`o}%dvoUo=YkQXYFT|8d{fjcPd+#T>~DH@vFwu%-`cG={%?RswhSeVKKlL%I{9*fXBE=!n_bl`
+I=ycx`NP$@$ZBDyGH;x-OTUZmOb@~U3HOu{3hl-8YWg|c(Jkk+Z%Z3Cq@0fkRroxMAL@#5qy{y6*P`0
+WY3me%?<;k&oAdd4}owXGC7cg@X;8a^#|>$wHVcAy@5_om^!DM?~>$RftslMZRV9oXJW|7Vf%p~yoTT
+wtuynPZ+OwX3{^IXF5kM{ih3IFuEnXk8b+um-g0hS&ak6i)lx&HCWYyZ92@8r70#D=4BSd7p~zbl}vx
+pL6q58y#9$8K8~j;I<0CMB-LjJU+W#NvDEg0}^<G8kW;|tt!(Z4`HcR@)Re1lL{!toxrN83{clX<R!s
+U0OmxdOWLA%ZFyBPO^jW7?X56gl=tpcQkvWL7#P6&lA{b^%Nj#9&}3=TF2yDLH-KYcvnB_Z{irg~QLf
+Ce7~U$WID)L%KT8&|qQkW2FsSY$g+RNl8mpcM#?)f*!Cf=X!wJS02Xv&y{0i*G+#<<_k++#i>ODB}_V
+?gv7?sEt8l*i28<g6}up3yfNwz)Wp0p(^==nTG1&7BdG`_zfpnxY(6310olcV%T$ULubj8Q!%TWJZSl
+a@yCaLe{o20`0&IOsA$HnBzdbzO&J<CuK`>4%Q7tD;}!bgZM&$iCHO*=pLTRk_+wgi=|A^KmV$MF602
+tiUwFJd?H?veb|)8*3XEO>0<r6kUy*B*M<sA!`n@P7MDM%6lB6jt94$&Fy;cfOHta9b?i1A|R~B)UOa
+e3^~t+=K5I)=p2=rEQ<orny=;WX@=Z^X9ICTi#z-VQ)gagEUK#InxNbsmx>cK+cv6;1St|?LWi1qyG8
++Z4C@jKF2{H%?_s{q<A=mqA0{ASi1OjVzdgQnl^=iDx=OyB&!NJ<IS^FAl{^DXq3$6H77yjp`?M;3)6
+6Od(Y7|?DuZQm|Niv~os6Bq{(MG3Sr}zDjfQD4^iDxLML6EakMIv{;2%H2_FJz8Rep#HMm+&zZvxQq$
+jMMDWvc{QgD(@x;J{O$TGh?~inu~%GEMNnnY2(ca$3wlQzeLcrAqdJQ%)DtpmbIP+C*sT4#|i~Y%0Ov
+OyDq+LgaBeS*v2QmJz%94%?c*G8^M52$n!;+-aXfasZmN%djsE-wNeOGvF9B1SS@t3P)6=!_Pxf=?DX
+93VkR|oKk{?ei~*gnE_*{yDqIpz^~YNz}`vvT<>98z%zlNV2g~m5~(%L<8?)nDmgjCG)g#@hfV>Sc+0
+vPo~p+~jSLAWgJx+uzeuh`bo*fxPYsaH#EicC?qC3PsHc_oKpKGwdW5{-sm%Iv5dQFB5bhWwCe&KG!D
+u8N>_a-lbNJDjKjfov(j^6Y*K_;h$4ri-Yt+a^fD?NXODUw;@W+p6A^7;wX0WyNP^_b3i6Q~5*iiniM
+MYX}@R`>!8&&zGAvh@18s*e$;2wPBryiw=Yg`-E`=&q*^7q+L|EVm!I;Lt<XjXSd7(ITL(7q91OI46g
+-;MRO7qD)5i||}qBe_L<t{H*m=px6UtsM3|J1Wu@;J9t<89}?Li~R%Qd|~$ptg7D}xinsufoP372te<
+HcD12})nKRDvhHR>9rh`fhP_J;2dC{}(T=ul;+a}?rPJ-g#;x}I8)v1dtL7{*CUR%!tO|JG<VZn@^L2
+4Fo>2v!yWMUD9rn;&3?Ed<plDMmb9CrDzu>ZVcWIL6v(N42SbGVYCy;2NI_nrqxKW39@{KJiZvg|aAn
+3T1RIKX#t%z$IIESpDL`A!gUk)1pFw8{Aa28WmC!%ANGLq9wbrr}B>`4CGUUyj@GJ!qL`@#)@)V~rWW
+)<0dK8`2X6mBdtLzytfn5_V%7Cb!-T16GH-lzo+g7++2;z{RJT*7vBBS40Ik==;-`WqWq2Aoh@2+uF5
+B2Fb~hd{WfFg0jG`6P(yL_H|+P{r#>M~JCq;j_w$YhFnzw_3Qkp5osPCkxO)R9*#Jus}Ps%b>rDbdv5
+=%sddy<7GO55hW2+p7UjOsZmc#OD|-3Lr!0^JXTh)cC1P)lW+nGxqZsMIEpdavREsW-x;fqr2Im%DXd
+)J6!<5F3v}46rD_E5sh0c9rg|_vMyaNKAgdaA=6bvj%cyQi{^cy&9fjBdMF+7p56CnS=X27vZ9s$SLA
+ukZj}LOkBhA?~I5!g{m(=R~;DQ}TRT0$Wjwm(>cRnuCjZar-A%#aRl9Ix6X$suxbSgeR%ZD{p`ns{-g
+CoZavao(6ODnnIs4X{`kF~ogJT@H)!AIKI#~a<O(Xfs_YsZ`oJv%DS(R*1N#)^8_k5<=kNg!W0VED*E
+(?ixZW?Gq{fF?D>W^T7Y?WaS%8+UoS@Ueru6!=57kD-m>9&Vo-CKEorD=aA^xhoubffMa|NAGuz)1#d
+KHKb+`KsN=Qt!qkk6Dp$6v;q@K;=XQx;T3^qsDp0Y<!0K{|5$n?z!!EV%%C%nqMxyXU?bv`UD=j{KkQ
+o#H9JN}o<nOHn%dTe7>nMi&_fJmzqZIwPrXh?M*c@N!+H*#-IXax$qWUWh~@5JJR7QBbdUM2cS^Rf-T
+lWu9C|q#r%O_e#z{q1E40_<^5Dr7oi$D2$c6^E!~R^vlZy8oW$_;<apelV<0yon`3wC^(_{*5bf0WSn
+M!D*>}s_NK{Tqe94Ag0rlNWXOC*`h#l!C&{rKqd<AZ~+#2j2b0M9Zn3_}om(q%jcMy2}K?tkfBg7is7
+$S+pZbMxWgD;5?oz7gg9j*}5J9-o%Lm`P$p_ZOvYZKBW%0a~0~EwX7Khk5A9jUE#N6=^(=Fd*Ce=_ha
+h`+@hrFm>Vc=Ns3*_9bpHd8C*Q@+b)W>~W*rMunrYanW|%I7o-9Ls`-&O~Hn3AD`L@t9!3wr8cb=e74
+@k)dSoW6tS<^(ajEPK(M*<Uz;(;XWL!=PCLAMe3*Qsl-*re(4bgo*f^E&h}wk4UKTaC%Y3~lWUlihvH
+4&~&XMAjsBT6ot)rSjU(r*CjrGWFrQJM1nhOyS@2?~e3hDW<nHIQok+max^OiZ$A1E?nim)|#7ANy^G
+fj4hjf0Se&LbQ_U}0BrUXrPd*Z}CK?WnfqBc(j)kO}-JE_B4yzx5yiaVW{<5n3zmBCgC*Lkd9W2jyF_
+B!K??A0OQET-J4|k9Qwqr^>&xSfG&U5JB;oqCwN_ILnY57qY{aFl`6GnfM_hrFNj;e}g_+$S%RQ8DUD
+vWrhAp%<U(17N&BGJ&tncP0cE;I)*OergE2J!agL_Owf$dVI@ExhRe``PxpM>^<)5+P_9Dv5bk>K*mZ
+}NsC<o$g?QtDVW>l~O8Zkym!b^^{h=7`2rIi}fZRTL8_AJNe8LMvcp0i30UfYFEQr0ixQr)j_N-t;NQ
+Qao<g#ap(Bw>Rl|UoZK|p*OP6E!GNvV|@j)pFo-39<s-F~>&Bh&3tB$Mo2uds;eeR~YaWHO3!cw3ctc
+}2$r!e`^YXK@aZcRP04I7$J@yqm!7@i8A`U>e?p=3||n0A^ZdbAeXy%Vn}@x5ww2U4fB~w!eqawvoLk
+;VE}-JDE%M>D))hS9DJ`hVF&w=8l>jzNy<jzrF~`tW$PbOI=UN-9D5K)|(J?ms#?8=-q^z7I_QPgnTf
+=dN`Z6qA53{@Bnb|&hM2MoWw)MH%egJBQQO`303agZbj#IvQ1Npc&{_2;yhNXQyO}1msM|}?;-&n3Je
+sL7R3y22}+*~x`Q-wyCuJ+Tek&cqno$+7z-cw8Or*M{$376sPhl^Ff;XF3Ihr4b_<kz<@~2QB1fsZ)y
+tl?f7e;|zt3L3@~r7{yXn!KT>aB!D{@H&tJr0WQpDM6F8p8r(@iR1(EVVLgZG0Vlx>87IU0cb$uAADh
+I5-+w|%L75Twn)J}*~;-GU*vvnBmXxsoJnp%7+l;ttxgujBDH^ui%)*L~Q$`O4hjjgbgJ?_X@SCuwsz
+Y)J55xg{ak&1<|v@Mn<QRo|=xY?=aFPdI#J7#Z&OB%>U%_j~i+Z_?UmaeF%B^EI?4B>Lz*RGr%%)*Xr
+8I%T2k={iKbPgin={snnQTe}`5-thQnj~g8sPfrQ3IOJPamEq4<ae65zlN#qO!-8%M#k@a6$5l|r<8<
+P7?#l?F<_SitB=rCkJPxENuRxib>MI}0K!y}MBRbRrtHE(fK|L*l)CQ6_Lc6X0*NEykSPBj+m2IIMY6
+6jL>tEd3<kQ(zo$#!*hq1N&ciz2aK2i)2wHa1+$uwBGvi+(!8W}3%Fh0}vvSZgt(OKb2v_-dd6pN}5L
+fMmy_;R{&Wx7W51SNHAW^cQkXXALzm(=N(xI@#eZ_acPtm>u|nuGBL6zH9K@lBRYIk*}&bPVkMd`M;n
+8M?B2u($ts&(`SaYQP3lu&>7p21ANr@Tm_Y`rr>X&j}0^?Y<e!Cb_!dj_&Xau+`St52lYz)mp6me=hr
+L9oo`uh|u@toSBE;Zjm-tXNod13f(eP)v4~>+8(-9GEeK86-$Y6+o0r};aum<Mdq%<91UrQg{1NxRYY
+*d6)vsjBG+<ZSbUQtL+o`!+d^**wnq}lN)i|FShiWgZFa-+>CzidXNm3mXEuvHQ}(a5yC^Tqv?CC>js
+DCGX0K(sYiwkL=q3HwUdQ!zx>&EaP82~qBHk9uy~2AHxPACDTF^DJ+g4Zi&W8FA46epM0O}$SblDB+5
+1-8cLJmyI=&9(~Z&{$2i!M}x`{aAZpIe|%Q`dm{Q{CCV@sxG@scu9f$j%MDO>-9?dFhNgPs>x8hRd$A
+F$b@ef43tOX;Maf$8Iv7_onc#4-O_XecUVIZ2eqY9>&5WEX$N^>9Fm=T63QaRCkTF+qaNg;33!ej<|6
+?1`wPvqn-kU2aGYaLZ8;|Lyt79U6t~}8`Vdkrtk-P9o{{8RwGP}sB@S!eyyu=9Q(4m%wp?(+DZURk<8
+>;ut?e9EsGNKhqB`VQ<Gt>_Rs;%SW*gc%hrcYt=Z}J{{#F^tm-k`fD|;ph%qn+2aGN)Q8m9BA5C_7uU
+0!#itS4SY~nee0+u<FeB)*`UD0{P7LU9`PF|}4mr9ItyX{D3tLlP)4|6)$b74c(TUWI;1;y5pl&-tk<
+Y&ImN+qJg8^;6&0y<O8C{%S3)mH-2=6Uow#QX1RLCkqW-7>A$)*rc=G(e-jTg(+Bm)4f^L=ULEd(S<Z
+jhV~jvhLn%j{z6j1Qs#g3Y?w+cNu+&g&ci7ntYc0pFw5$*ZIGHo&WpCo&VeQ-o1YITAwVZWstCy?EmW
+{akn|fv-J_4J09QJ=IBnh%5|3`JG+>0LZ$@R-QWN2&?~cr%tlahymA=I`~tv%WbzpbUUtAT(iIRM7-&
+q9F;TRLlQfFLFkgG$U<@*r<H*^h?f%~N_{LbuSAZ91&?sp{jBGe`)3ABzta>`m0JJGUIcq}7RnuVv?g
+~4Vag8!{3Dm!xqmyW?5|SGSI9wRs_DEG{g#Xq@slNUg)gN?(YV+}_4M(T$cx>uUVTfDBS>OGr)NPJQ{
+h>#soX4X`cIKO(SuI^;Q}pZ>Y*N6@U*?qFkm=<;0b!N_6PpraWrntmXMrhRAenfpcpXv_4b_-Dd!d0@
+sa<3O49<$kSyd)Tmbj=d895}C{aUQ;L?$wE(TG>SbTiT2xlo#8n>e4;xXk9uin$_NCAhRHW)+Rz@sFY
+qWuB!|N-<{SNy7ABGN}t?aHI~`0-)+RMkf}6A~U2fuSr40tV@pq?ug$G@nCK(+KQEKlJ8JNq1xC71k4
+vv2YrT|as~vdt87YXRBAm$8ogvPHelf`Ty!Fzm<}6fc)Pr(e0f6}H4UyZ##rZ)Nhw<kWujrXWk506Sy
+?9I`C9ENh6r8{H?+!O|9s?}lZj)P=f{s~wsP_mBViC7T@fpDB-#3-&VF!w>1b5vf8$D7kzArntFD1QH
+kHc8&IZ$%$d-8s<&3J{EENfdoUM%PKaFHSa%30?PqY%ZYUYO~QB|3)<S+745h+lT;0?QcZn(2;W>kx;
+GB0f_c$HJG121_fRjAu2EBLgtOCv^Yo>({Z=0ATPoxXbhnsPGA)?6Ta!O8xp0`2V7cK7vFX;|TiEYC_
+gYzX3<jYp-}z>+rodEoUBSS1_OS94_B)9p7@5>I8pc0K*oZo#qVdPfRTzMaQ;&oNF{yq>2+e$^<#$UN
+A`A#srfpKc*o-NH@^QOODsCHRw|&J*u}w|{8fF54A?fLE=L_Ae+|;T8z1s8rd`VR9SSeSJMENLr>I$5
++HVt?$M)H*$PBjPbU~=qU%-G4ilhQaWfdPw-GGrLubbcyF*t1n|{#zK2=(ozo&w^V4CDTuj~Tz){e+(
+O80O_m2Zxc?H&Ir?%r6vK4t1hQeehfgbTc?J71+CH?h`pxZ9)6?7MeL7)v2LT^w1SIttl@}%F|#G@**
+)gLx_^uzL%Kpec`FxG5u+fg(_HtY^g|5w(I4#bVBN9M5JF=vONR%^(&S5Cf8#m1*o&2|-TAK=yzMXus
+<-*+EryVW6iEjrX1xnyU}1U_%YLQtw;BjKYRRHS6fIyYD39c>cT8m&Ahr9jdGkG?;}Oq-^3Xtycf(*2
+LJfYFLp@0$CAs^&^Ef0m)BimDGQFH_9LD`XONd9_e2sJ8&f<gJk<6Wx*y63YfC(lvtSOIS2b!gs9pUG
+I20#gK2g1KYQ(L+>zUZ8BTSes|=BXo!B!?z+r<&p>&Z3Pb1AH1sYrS7T^nkou219!@>8DV-6QbT*Pjm
+6R-sPv{)^bl3Zx4jXfL&k?Wa5ffl^H&AGL=v~^FU0|M-BA7W$FWo%Y8D*r%*Ten0_#fsbk85+MVq+Sj
+6JR|Ec20L$sZ(B1Pcz{*ZI5cLs1T-hwXRz)G)L@NWL&MCG`m&Ok!#yx)SXGJEdX`$Ye}n()wW&*G9VQ
+X9h28bH_-NmO8rhT!JQo)T6qbxV4~NyoHq#?L@Eyhr$LBW&^wmy)T>ZclZM7-1Y$zo&+|P_x=4)}M><
+VS$uNnA%>#*cjF42b&_+$u{SxX7*!-~Ph=pWtmAoQz$Do1=4ni8#!66aecc2KMOoDG^p7_><1}Xz{Uv
+P;9NvGol68(DeHadI%{Q2o$m{^PWQ-;K?-zy&z5^9m8l!6>qF7W7}6=Vx)<H*||%Kz*eB-BZo)lCgj@
+jIsmIog+?4=z-eB<P`WGbN1^F;jBO<9y+t_F+mK5qfRrQS$LpwB~>!c!iCsQhOf{2GE&-#v{Ze`*MCk
+6UR?Z(e}(YyVYQ+WF0O7r3?tF<7s_9+?=Ug5XO@;8`hW9VUI9!LC$uX#M8J~CFV7}3vzGB>yryV_^^5
+~h=LDO<G=9cPtY+0Y{g$RE>&jPU5*Nkh`fvA$hckEmV#(f;1!{j976ju;>4XoIIRoJ)I}d4_CEUYd%8
+|ApSX?#OF){Cv$%Oox)U1w^ZCc`qwgPY3HMPSU;qe!ZVM6%Zbo){kZ8D`-vT83#Z_vOa7VUiYndjve&
+c3)t1C>G#pD0ek;}kEOoJROfRhB<v4hCN-Rgg&wYw%GLFv@zN?eyX#}7TqWFRBT$Rgb-hw!q~%)ntOp
+)QWlB1YeKy_Xs0ablbJ1o&OHEYy()EsP?UK&ctQYaWKzGotGTSc1I?sgYx3`ZgcUJcHAhZ=yGEPk>8n
+V@nDAdN6Qbc*CeK;&eR+4fb<u?f`0<tFZ&rU_2H>rTVU^BUuIh6BYvMPJ}ESb)3;urc0Ly;1WpYcn1%
+e2ay#XbV{TQ7p7%!F!a9blS1!C+-(JLU(<U((*DA(==CPv`v?CFh#&0j@7)3SAO1;jf4mv@KM<W76`Q
+xQrG4*WC~fZhw?Fe{KHRy1;!mvUrWrAzhrBGO0(&RY$(qyf)txgwX-1U{&HFg&+XWRFtZT%#rXEs`84
+Uc3m)_dJpb4(&y*o2MIW)}%Bu#)CW*wxA;=6xL|NVUJ{}Da6;P&-dY8j=dwDPgD^Yr!0H^=WzpS(DU-
+W~sZ#s~Us%>xyZdGqxSt0{KSyL7zjo3fSGrqW+(v#=~k0e|N8;ben3;`dx=z@rt@?SWoW`52*K8KAY?
+Os-zlp!=$8dChgB(|VNK7tYyt&9U;R?-iGKGSjZk8#%wmA8M;N-oh`}h`P=f)%RQ4s^R|uP)h>@6aWA
+K2ml;P_E!5~aNHvS007kk0015U003}la4%nWWo~3|axY|Qb98cVFJE72ZfSI1UoLQYb(6tP#2^rc?|l
+lgCrujPz=Nh9npB%?J!#B@3Y(x5Hb9M!Z@VlorMQ<e-%n?tU-o45MDCcd&S)a0vo?<0RAl+R^vCCiu6
+=uIplOHKV-Iap=Sep_mT*5r+6guPHfw(|&Q56MF~AQub}0co7-u0FsCgQ>@#Ir8uIR*l<&Ox4OHM5Z>
+YOPCLY=e^1iL;Xk>Z<&)p9CeyJJZ^7Diy2x=r*;n{bUQ5-LaO2HF-{BbYkR>q}^puT#Dm5WeG?8fWY3
+wyFTAlmO(OykB-4N-7WaF7q-A!9{1_JE0-K1_KKYLtU`=Pqf}PM1sW?qN~lc&V9xtGg{)f>&9w?*lU3
+JUYXkh#xs)NEx~)TVH?W}{8%-|ztEx@Rn;F*O9KQH00008031s8RvlElX*>V`06+i$03HAU0B~t=FJE
+?LZe(wAFJx(RbaHPmUteuuX>MO%E^v8EE6UGR&`ZfIE-A`a$jmLsFDg;UP0Y;W;>t`@h>y=p%uS7tSF
+p8JP>PQSiO0t)S#c=<0f?ia$prvVO9KQH00008031s8R+9<`dK4`H0J6XU02}}S0B~t=FJE?LZe(wAF
+Jx(RbaHPmWNCABa&InhdF_2|ciT3y@OS?TEc4tG$(5NV-EDicb$8vwZFQR3IkwYwZ<3WM39?yJq%KLt
+QG5H}pLqd500bpDFKzEVSLZY}NnkLT8O#g@z~J6r9;~YJ!6eNe$o#cfuIuX}-@7Ls7t3{-UR~GX(Z>(
+}Hh_OV#eY5%Cus>EuO$?MVo%el%quw)t9&L)QC~}Ov`nV(KlNoGevoCA7P)v7e=K@fAX1;A{@($@x>$
+)tvKDz!i&Z57L|Tb?nn@wwOy#l`X)dP4Vwt5$K9%A&t*@yW1tbO#|56}|Nu5CH1j;YrX>OMjNlge}*Y
+$Gv;KA+fZJZFIaZz49$hc7T;OXe`@yYq|0U%4opXZsZDpAV+TBRj)bFvo65^$L&6TmP_Zbeaw<f@eLt
+u7GP+cK@w{AwVoVqV`Sr35Imw5rQ=vZ@_IY0RL%b^#z&l8fl*T#U{m@zv4!=zIV$ejHtVd;0uB{CISB
+c64$vIzAVtXX5ec$&=B===21hz7|I({}SJgPM!>e1TsN0^3AeD`~k@nNhoJXuX8CK1m*=JR4wH+ou^a
+iSAMlhuB5msUdu9v?uex<7iooztN^_kK*`cYS|>HVX>}^z+l!)T?*iUjUQ+Lh%S!<Szd^7)>s?g?xQc
+Lin&zuF;)$jOK<<lWS-ehXvf4{?D6*jTL^3H>wQ3Hl%&aORtwp&4oQfQHu$o?r1TY2;f&c-}_7=eOG?
+xdZOlHJH#zc&OYJkIQC9PI-(3eq-T*3xR3BtIL(BB#Sz08uSgr}PDe@27nK9W1VO7kS!8!p$w`6{0dF
+QH_O5aSFn9@`jS3M_(u4FtTw4(MKs1$JOjfE4L6NtV{@SR4TrvKp8JD881&T|$HjG?CL}Aw@2y!2P6L
+(+eD3jN;xW@!!Nuf^19^6geJq1_@w@DkwgQKZkBEKn!Mx7c^O1NffPEjOuC+Ak3%@=)JBl0-eV0UW!}
+fM23W4+pSkA4D3DC;G_6cYTq=PTd2h1yiT)hfSf2{NW*`NBwveZ0%Mm3-*q~@-b<#45{}2yb5AxbA%Z
+UFFl=E+(15s9&47@vq<HwrqepvRpt7hyTTE70Rm`f9)CHBnB41vPiSx)IS7cE7_kb%!2~;bumPuJj{r
+qzUEKq-E#TAIkm3}NL{a0y<SJ#<*V;)u$5Dx60d9yZug1W)MTJ6otVj=4F5=XB3*4q>CJIdDs`r~nuW
+hnmq^dz0u{MQI%s(F99WRc^ibI^hkc*Rc_@=ZNDRe!IRy2{0R34itX_Udvyq&ER%u+R(}-BU__MDLHw
+vM9OIy@u_d8MstM90E_F=H7U$2J3hX@1lnwA0GqJ_oi6_+*f7?YxGRrJ_BDQKSMj9dP;swbNg|!O0(H
+GUo9q5z11*Bz~Lakbk<Z?NVQ&!K?dq-Xd_0Sv-Czbg{Q?#<}h}3!{g^Cqn|*_fBj^12E8n*7|e89f{4
+L5>_yhsXdt2ovYtkLuJru;?CI#M?rP>cRYWHsOD9<Q^n84F{Pg(f{CEu3=lJC4`(vbUQGw3PBn&km^1
+Y$BD3iR(cr4YVNpU3PI0Ulv7i2aW`_YpKY_GCzFzn}`d}&xW@DLhW{AxfTP)~uK#o9`bu!@e;*`-*3_
+9@Vc4YAg~_)e~Yq)7&27PN~69;-J^5PZ-Z3TL*~S#b+i3zf$JfeCglCSd(;Dz7LRxM~W+ylUE}W{2WL
+bs0*&#y9ca$?4hmM^8updHe*4IeG%*`<1vG6<IWdf6HW=NuWE3`6>O)hD?=Nf&~R4902A^Dz08|g%gQ
+bE1{~;%{hhd=d1H$G)Sax;H?c~@3*@!%-CP}=rXUA^{ULt3qp8UI;$pQO=2{Rpt|3giB>b+Z3H;UJS2
+902u?md|H@${7+YB`%e0csUrE)$-eXflxh#L}22#lqxVuSC#NW6!Sl?^tm#KMMls6T-09d`emKj$*`}
+X*$_;esX6F)XZ!Z4cFL)FjeYq%zQ=^!RKXs}Rqm^IM%6Zn27i8Kxx4DT{Ur+_WWHIHh6>Jp*BNKi%XL
+H|CKN>{7cWD;sr>61=%^C9H($>{vz?9>ra=1_<k@f+Y~{D$}-p1}|YPm<^~EplXO2Qfvjl&E>+4D5tz
+P}>SHLl?&<7x4VU@!2^b^z7*3;`r<Y&?#k%!T|u-3n`=CKZY;<-G8<JvfqpM`!9R_e~5i}cYg6y^#9R
+&@p2Y_^ztA%_ytPL`t(Uw2_RC6efS=K)Q`}`a8aKaEH!TeJ!qk=O<WjV!1U$qNBtKE<5xWe=D(Hd?f<
+`sQ25GemfX$>D6OKn!P(xDP)p~+G34lb7U<*g93<|<>KxE{!OTPrZ!9qTT2WF?ul;vO2LBz*$!g1ftG
+9DG0}bQ9y~47E|8@cMwzO3ib#a;8wA!Qh>FaQLcu$j{z{j7HvehyxLH{j_cI$01y;=J&tE~M7CZaeuK
+Ty1c53jm;nO=cP0%qP`%UpnxFL4HWMU34=!bab~D0NxN!yuZ;Nt)#21_^o#_O3+(x$s_vyfodrbyc^@
+N8q4WH~veEX)Kb|CJ@N<9=K7WJx}e;S6Sw~8MCK4DT)j_by2QlUmSeNvw;^-Y#{VMuh>t<SrPs}j;#s
+ca3~(epT-~W(I@=58ajYU|B|961_aJVVV+d1GK`;OINvqERv4b57yu4xFgBAEr_fM5U9cY3^Y*6wU8e
+1TL@b^$-_g3X%*vpnKZ@O#G|zQEAw8jMIWRB*dqe=v$Q=^l_{VfrmZ+}%i7xfGMm`XX%gbImBW?|}=Q
+uD^jsE2&(;)@1sj%w2$iP@tLq=d9s;k<UmtfXLbFm*5g?;48Jju|)aj>LXWoS$GLUaHU#o`pF^0#TLM
+u;$RgO8>m;&ZW~o-Suq)!jCAVIEs1)OpccRV$bnuW<qa(>0*%H8@07UnKLI16-;n*33djjCjIGL8MJR
+G0iKK5Q7wbsChD#9JI88F-TA?wwV?EG!dqq#np~7RjVaV6i|sJ7*VLCVNzOG*mFP-P^v5(XGxt<Y>mX
+RGBI2ECYjbW;y8v#GN!{#DaCXvj*lP&0#_BQa*EpZI?0{hcrhsWUQ;_jX!4C_>3l9p-WeN486mU+J#1
+jXo2lS6)<~vhQDHzWtJ7ts`lB&Pc`9zgZoMYJl!8BoK`IQy*-ccS#Nxgp&=E9-@m4VCRgo*pz_=24jv
+WGrYwlFg4dqw_xuV7gmX+rMBLe6b7gkJDv|^g%9dhsm<I_quQM#7Ja+M{ePcY!Lt)F!uDaJo~Mvp}sH
+1bx3Y$@WXfw)a4i;WuCQNU3P&ve%74}_}<08^ALORpgAO5;Y2&VHi$0#$xwYBb+q0yVwKz!T06AMx8h
+`?aj9$K7NK>rHKQ5nnW*@Y%JO$_BWipcXi^39z9Kh|Vh3<;ez1kP_UlJ@N3xLThC;BX1ff2?L(9TGf)
+cKhU9<idGg#*i#Cg&x+{^1Jo!3dThg&Ss~R>1!Zu>GOLEFQm~cosEwFWOlf6S6~K|naREpTHnL$jR?I
+N*u-EqO(E0h#8-6Nus(~uGv9Np(;G@-KmDj6Ci{5j3wB1MZ=?Oh5M;PaO!u-zU>|3C>ABC_d2d4C6cs
+xC~X9(ug*Yv1;Xjxe;oIgK5R>29Y6+2vDqF7u3AF+~}$Si)zEoeuJ<QLGR7Lw?6+Xdj!{!B63vM6dU^
+Ob&7J<N*Lj7B4UevFTdtL~_L1L}KH=oXIo(QbjKMFxd$WPVXN1=7i4yu>N~&Fcje8-4Y?c!rPP{qQ{(
+fcH?wK!Eq8ow49A;+&lJO3eTe>H?&h3p1+U!?QgXGl0IQM|Xl1=}-J<<B8Ti%Vegw_e?*kuc^cFXKBO
+nGO3o9z@4c_dzNPEInk;f4)~5hSYJugGzI$N;v<1LH;*>vX4=Nhoa;ya`UW))#jfb<Pas~N^i8UnMi4
+`$U!6bUZ@H|kPvS(@=F_~C()#u_JeqHdbe7`^x%&RSdNki@GTO-O89q89oxZUoS{#jjQj)fEK70d@N<
+7|CpYQ_DoR-|Llh+b8zgoDylFEP-ycBD6=I99+lG%)6>QIiHQ*amA>TzTP!Oc^x)58%q<IigMF=?DR0
+@dhdY`(~)*7_OxZ`$&JJzA<jFxazN;z~I$*s<B+$&P}>AHcVt-pKNDtfv6`PmAJawG`K>EK#eh*&bmK
+&dji?;r_ldkZD=fYy|-~=sa&SaKeGc(kOSbF@n6HE@z5bGh8>lpa>#B70GLudJ~lqgS^NO<YEb4khZP
+lF_}pi0^~1>GTzdPdh4%wbXVUg(C<g!l@Fxj@HTYr6s~gVCY)fL<-7zCM5<Ka;p4PpLG(3FMvY;YWl~
+krx9lF%SSTlQPOGuxb+|o&7wlgfqH?M3Wg%5eMQVGrzO4OP^jdh<gHwfkeVeTNG-c=v=o)y5aqxLUug
+Jp^wuHGLe3i2Sg)}jUs9Xt<ZMPl;%`1>?qTg~=E{m#}M7m{D3TL4WE;Sd;faQj1?M01y_#0qVIO`k;@
+N{$Sm8H2gA7!Ua2TqjKx26{2h~$MvznLH5$Zdnt9wpD}K=GuSK1tqQ&QnuuyVz!N<++7%0GR-+h<H5T
+;tSlT0M7sGv{+Ty+LB2H&5Zm|gdD})olJSN0(A0~zfZFdXsNE(CW`hohEKN60_;K65d-2mfVf^k&yDx
+b^KW|wfYBUA!H?ch8}=AN;$h%PM?7e`fTJ1Q<DQJKViB<i$)*lt<bh`Da-~|)z)%HhXf%qF<&w79bb=
+P2#Si0$fBX0o(R&P|tFN1CYj~s0FRX68l_FP4+yHwUMINH~PzOH`0*V@AyE|+8Fo<{2^}e<bx9|nh^~
+(rQkvQk?)c0`*8BiiNQsLRz@x{fz#_xj|vYM7DZEg7@DKRi2Zor%Po&%AoWJXFa`a*9hNoUXw%3Sn?9
+y?z)VGu%~>Tg5={5K=L8`YMjtF-#k5tWbz!x&&y-%+a>#qwblo7v+R&}~Kqk-}j_KZ`$(`eCSz9y1l~
+&~Zw!Kh0*Mw)Rq+@|C4Al$!et_sV{sq|2gjT0Sop(u+W<c%>JDu2_tkU?~Q&Qr<0+<|bs?eAiJ>y<!^
+JEf>R-H~|~jtjXKXy9uM>=G%Gt2IvV>yrRUA9x2Qw%#&o`CRJihV*?>Aib`Y1gfU`Hq(E1J0~_M=_z{
+_WWdlI_JEY+VtV<vrq}GHYx9A4vD$rM_dn1xSg#zs-#2B<-uBf2vExCP@MpMKbfSO2{O{HiJ6Wn?UmW
+3vwJgkWqC0G^}isF!#izauqiD~q$xcfeiqx~i(uN$FgDmZkwU=QHg5n4h=6M!-|ix7;cP1s>0$PC&Y9
+Bk1n8|KIsNw>?|qKU#wk`auSYk_D+SR81!89lZX_)X%lL<ca-OardewHn#r0gQ42q&RGA1Kq)$JcD=x
+4G{uSro<3(1=3n6HEz>w!@LgnPmE4a#=Fh$x}cn?CEd51*I7_q`p`~Ri!`1wa*Q6!5=g#THrp@_+`Yw
+(o`7!2pDTdsO>4cfshEnRe*;d6%ex`9-Knr9Ho+}zcf(N6MH)Oi47Y2g*)Dq)oVTX-IxP0~<@`IF@WA
+>s?a3YRUfhAR2X~kCX{x<-HJD0`18c(6>h|hbDpcLZb}JO8u(J#^YeY!X&)5DyeRX&vyv|L~^mexGLS
+Zppi-bd?E|J*e#1VkIxpHh@Sp~o-P}W-Yz}q3<SY%uE6Vctq^|~vnA%bNGr)EWcP)VdL25NMb!0OoV$
+d)$o4O?v4dn>jefIo~aPUDI#xMMV*{m<Y_i~5=`_Go?^worX*0rvOgiqp1Y3b-%jjQFu<8|*(JPg<03
+cCOvX&Fknu#APy-R+n&<!P+s3s~+BLNCgY^a?>;`Dw(a(8tXvsCVQ7+?DHxqXB33x6>B{9gP?H!4qUt
+f`Yeb~dN+{Tx{OZmGV|wtR%^`yinaYE;eE?|JPh5G?Y=QhW}G8ZxF-tTS=_;)1x-7To`)41DVRxcpR=
+mrb3iDf(UbAh(RYsjW-sAbz`;2Jf~l<mUs&fiacvGj-_*sDPG#u>mk)RY<m>^|e9!=juj@tjC9VT)5G
+s}(B}jUTzI{`Mnanp6FGhaLh-Usbqq><S8HZ1^)XbpO%AIbqJxy)Thfa!GHo<=5lDZ)XGdC|KZGmf=h
+>@)XNQvUWtlpdTyy(s6pN>EMYow;cX1&isJD=h1lhyRPnPXGLAYXHQHOU0DPs8EoRn_b?BU_=mR?|vj
+#c`{Ay<MjFUH+gSsbac%nzh3mOYbx@JH%!imen4sw%&a~%?m3w5xyOQtQ%y!5o^8e2!{OKf_VBMTyQ{
+4Wl86-TRV?@)lvmFvIewSPRqr7{Iy(@9jva4+gyj|o9Vd{P&G4%V>MsLE)R$Lbh`<V{%Zch-~DuUe<<
+$b)|vYQ_lvSk`1!N=<BqTFOhXwLEEOTgj;ec=`762?_|*qZUu{E&h3-2=e)Et)4Thz7>yD4A<~^36_+
+kU>H*2q_p*0S?)fCvuOB**5^aCx<u&SV;NlJ*V8y%JhvE*~O2rj^LtZo)e6bEUMG+QGJ?Twl2r|@DOf
+z$f+byDK$oP|($*Yeic7;Zv-FWZV8A;2;6j#JV$ymy<Uw%~1^v?{UKK6ORdD05peqe7eZVeh(Qy4%y#
+fq4{F-|cMtk-c`u%$EEe{7y?-y1|s9(mH)iWk^$^mNc=GaM;AwZ4}N;IL;2TeZVGQnZOLz$bM@`@yO7
+TD9?D=<7taKqNC|}8s3AV&bcesuF>070G*B0YY|C1?TtnJL#Y>t%)KQALy&-K%T>J_F<E_XC1{&)ilY
+4ePeIhsK8d#@Y5>xE6U`vO6fsw*fc{6*a6`xK&b4(Jda*s@%2Hl}ZIf&0rrHTJYtJWlQB-#9VY5^`Gy
+2`K`v%*~OVQ)0Lw|^;dNoWRDd(tF1F5O|gYAm@we`9#_fNh7ES03G14h>D%q?qXM^x!|*1s-eLyGu=v
+A$b3viE;i-SEFv3jP2a5|#>2H-0d|2%V?>KZ*Eb3}9Fi*jW6Z0KBUJG{3uv!d5%pW}BOdi9&Nl0g|GU
+F-<WI-fX-qi=`~<_4brZUtlgS6$Qt%NFIP87OmGy5DPvzZ+Z-PAK6P#|I}4DV8DQ?CiWEzaf%y{G2PV
+wgMZT`%PMP?U)X^I6LUl@S;^W0gkgru@faPl@%R!qn$K4p)F9ZhIr@E@W|_*(aDc6;og0j1Z1<!IBjK
+<Zga4EQ@Lnae`9REvCd1Z?7f1Q})c{j(y`nL4Qsi>zNCDP~$8(BM9t!xAP6dv~p+Z=|Z~96$Ef<rYhm
+__^6t_7hu)<tbFHGa`hub#ptH;H+$<I0rjQBwhBI^FH7H+?(+=O^q5|c4T4j>Rl%rrImIo5=JVby&F-
+_&Cd%JluJD97+WlWL3hLD^^NT($B{pVVz1i%&Wff^$}okB?yBeMyTXxC3dn%H+XSR!ox2bkXdkXRI)M
+yr<}%V6Xz2o;G{zlk$oVInvgmq}E%1RoItmUgDYLB1>nqY{c?sWzVZXo1^?*Dt)O`UZ@;P<5z2Fg5qY
+op%m_?rA{i=wcB$H^wJncsHL=#Py|R*S><8un`H<*kC3eg>evMeTa%&?_p+%&J!(I{g<s_|g1i20af{
+h#XqR@C)+?2a@|F%{=zVb}&7Z(rmb@y8N7kJ<BZ1TFd&IIqSJQg`9plOyM`=Nkb7wZuYk#LLMXgMV&C
+po}y$3bTUl%uOrzOD)xPgr!(DK-*ATzc|BbcW&pJuC>90RnW$?W$6WBWKbY1Est)-(apBLj~~;H(4Ep
+106dOt-q?Tp?T9#WS0rJxZ$}POw|$G}NM^W7r$v29&N=BdiysKW5Y+e3$Q639hZX8b`Y=23Ql=w#AFn
+8B{f%0aA(~H;Tuo8e_99AK@I6Gho)mS~OWLgV6#`w7_nk54u6mG=cePn<YUf83GOgT(jY2-va8#jlpT
+TRrsS=dm~-wTp=64J$lTekOn1^&morBGQpwMXo9Np23TlXD4F%r5HP*8=`T2_1$WQ|a@w5L=HC)HJ@D
+yb;xwUF$ZMD=H!gMw;|(Rp^F-Oh*6i~<HhJ1n0Bu${Gf|ULp^G#}-r{hN7v#xQ^cinX)nUE2P^t?HmT
+s_DZH-X$L;SH%(df4D!H)wu9`C@TNr)vrgiY)SsI5D(Bs>B8U~EYYQ#kRINU|&3MSQ)mpjoXlZ??`7x
+9}$zZ1mW|hkx@zBWUv|P+ghLd9kAOjU9uFYg(Xo=Bs08HfbO#;3=Et*dhM9m5!#A3nQRoZ03Zt4U1S8
+6<qMxYj+fe`mZf#OPG@hxSO~MftzIWfu(`irG%*<`(CR`x)Mc4x|tsbdY6-9`)KE}wYQ|<!T#l?qfWK
+S5Q`O^EueF=GDlj?RDSnKnlo7Pr|j-@@L5^@O`Pr>jehD2RZx@DLd@`f2abDC6wfVS+bv9(=Srq6NIr
+L;ttJ_Gi~&Dk_<L9y@Rd0yR#>YcWFL96U5E8UKpW_Z(FP^?;g$6t*|V^_<Sv7wsQ4w#V6x*#G_{=uTr
+G4~oI$HKXjUXMvpvkm$ycG9uu^41!#&=B*Ge6gb1`$Z+(sPR!+#T&ru1F#bk#?IiWaaSuAM5`N7E|U!
+QZ>6@ebwf7&u>zH;A7lm;~6-ESO(TzL^d$DcDI7!ONi-xpO8<%iHR_r6+arIgeVVjni}80G;X^Jvdc~
+Jb0qr$^sxv7S0Z@A>7RKJjHz_x~(HeCtoLcrG<P0{t#Nd={59iN?lX?Ao)i#F2KktDszBJ8##3$d#Xt
+RFwJaCG^_q}3&?t^z86)D+>U=P(!8e&4@5*+-cbh`STcj&+9_sTkgKX3XX!+N?b+<;Y{X=Q?`X*6k2l
+cz4W-k0D}>MvW_l&4!_FI1MbZ&@8-OCxI0VD$k4?})FlnkAiPVJJ0=5;y_o*Ci%c<7ia~|)Blhcc1)(
+`1SCTcbTsscqzohaPj2j63VpZ5T#I47t*ApFBX7RIhqOk#^(<<YZ|m~gtJS(8zclJ2<+62v&}X<A{|d
+mWVS3rf{p`^8(N=^&{~i(#0eZ8mgZ<H|-$S~dXeLeCvQ0Y`-Hp=iGaszecTVzuNDFDl>C8X3@z8cbt-
+T|uJ>>=?W~m_oJC4eeRp0nNy4vuwXmX3QgWiOOCyYQ4?9XhZ<$=&QMU#ElnG5X=NN?VbRA65Nw1XHgq
+49fZJi;&^)w?ku*=QsfO4hZ%OCeQjocL%P|I4QW}8;ZuOHds~`asdbug!^*Rn`!C*8<JukRYTmdj^Y*
+K|qhQ6B@i4PmWO7$}iJ4J!rq^(mr9Q2V{It!VTIO*Pk6J4|J(u~BH!=@@4UOc#l)nvxS1~X=Rpr2!5C
+BVhR7LB}rV7M!uL`}}R7vs4tES$DDr&~58u~F*bnNZBR8{=f!K(faLtWQ@AFLeMRHy3)J_SKE+tYN-=
+1oUmiDX_!n|DyDAH}R|NT3f%szY)gNa5<Pu819yqBpA$-AAbjb8D<@%=+!G#OVoblTORPag*upkS02q
+9lBW;nujw)<F9r0Yg-!k%dnRmR1?HSovnA?L3LJZJbW<qZySP10v!0}4+g#}Nx#v%&?9nus6um)W)PA
+cKw+D<v=&dBgua`OeeO<fI@n;7*E~?>F`Zw!r$(W=!D_%M<%Zq{*LEKWkgnReLg_4~^m)C0tZv8aMFK
+CF8b`q;e`<{gZ2$}!SeA=yx8>`9+VK*lGpmVo-qaX|8V(R(ApCoqHnrc{GZz`A73KK-BEwe?ZNetBb?
+ZG-#N02l2@h)v((ll`s%kHS(|Bafygjj=9vb@Zjs$z}XF#eWETMLT4rN%%Sp~Th`0~yYX;%x1&W2`e7
+JJ1Ub}RBbFjPmwUE>O4Psz4=)t*UMM}fNL4GJgPaf0T#1;oZ|14VYBg8u1^ZilYv;cgz%Z7Hof>AXqP
+<bSi!oJYU%hOA#z>EBxBQ%?Zx!J$#;9v|D&wh_g{W5!D^@qUI)bCfOAy152VUz4PNVG(Om6-6Nrpgn@
+rQ?PVUOt!Qzro2JE>#Hu^>g_Nt`eZEIW58;6AR=!V+!>K@@FbvMtdZvmGvn!_6~e?GNda=dvUN((#>7
+>PXByGd?NL%~FUWBZH<2EVelk}{R3!VD^VMI~;}t<SBBn(QW@NZiviI>o3s*Cv==Gc4%S<Cm*Et*>Hi
+`OiIO@M~&l(YxG7iMmGE3`T2y@PUcYx&vxHV3=w??Veb#-kUZlZ&Z(C)&DvRZU>hI113)J)8Q*!M>l?
+dY=EKsv(1l-5wp<^;1FNn}aYWQ=WRkE5x}by9iIuqL+B<SsNTv1Z8QJ|zla-~w_!&+ragg6F|98y6OI
+S=`?_Qy?cv;jNPfPYjKyyFl8ji3p1`nqjd8U5-AHe8&uQ1tW4WUE<{SF4Zvt`x^1oxVM!%Dt?$ytYGj
+(G1!?eby@qRl|u)`Dhk_(hHI}aq4YzdJK`k%a<_);-=vhuP1_})z@?q`*PBcYLlVnIPg^_D`_-!iGkV
+_ws=_Vvr;=W=5xjHGGyJ`a{iCF3SVW_z0jcDjceae&oz3=f%=<DOKLmSz$mf@BhBp<0d;kM*CEv6!Nt
+}Jue;NOS{{Ij2hi4OD{L%jYLl;;~?|W9uEx%3GY>Q!c);MTI)rzmmVzsP#ZEs5niVcKaCJz+5QC_WxE
+ZV?vu-yDz8zpQPhsw=n7ETfs*y+B5?D%O1LWrn-+CpRJi+l0$E34y9f~<G%xRWpJy>{HokMK4fe`s~w
+$wKwc{oa%f?CtvNrEGYc?ml{D$3t&qcT_9XrH!ey2wq58-X*Mf(>1NOI~E8Rjj<|QReKB@n{uaanhZl
+><-dD>tZWydCe2wc{ktc=<;+S=4|O`FY>lVxraHt}DW64M6M-SrbzlXVw!Gs_5%zv3c&0Vyyf8ft1#y
+CL)EAM7oi@(AI%M{pTw5p1JZL*lLz>uZtH#DC$L4zeEXs=PqRamllV~?>lF!<^q))Qf0^DfaodpiTZX
+Q5*n#)^loE>&V*_8r041_#Xwv=FbRyc?4mheZ$iXjFPWVSOVk&aj8+ld?7<!v3w)!MlQ-CEuwDw0EMH
+s^lTQg*n@qJf_u#VDar#tENa@1A+0aRup2$z77lytT&jy1auj_ce@VpZshne-irbm{#VU2eaS*U5M$|
+X{Z^>i1H^P=#J@7-kG2Q66`|LK(&UfR=$-#2{qjV2k&!mH+|iOY)xrfBU*8`oqe*S(NFichW9q;m!{3
+2ZYKYMJ%CMF5IQ;d4k>aBu=lTiu`6$(eks&z$Ut%4utxr!s1{JR29`SW@jgY|@8R3%+>Im*`K}+Hid~
+sF2&?x<zCiEZQp0W}qP1%9;c4gS(+??oO|R~zUOP$kPd^)ork_9P?`FEbk#)zhWkWOTbf}+M+T(*42R
+!Pqhk6TQAOVh#UVGPbXpf;6nWn8(m<Tyocwo)~97d~pe(-tJR~IaHY>97ii&y9@uzGdQ!O7?JuPTr0K
+dTzLJ>{e94Hr9s;w>%JP+Z72_2_hGzCJ^6taPz{_@c(`$H!IUBltj5-TJyLR#(>+V0EZ2m~`Cv9pn8+
+SceZAPVflriVu6}U<PGkcz*Hq!RO2)O3+cuHmufK^@ox_9BmjE2j=NlnS4V*?CKi+is@hG(Eu;zOy77
+L2&i~`dku|HZu>DUDC!M}P57v|k+fQlOM^YC)W9Hz5epEtsiYrkI;uH7v@FuR9#9vnYnf%VJV}@0V9)
+XV%tT7e{tbMfJRu$&RE=~olG;&@2{-<0RZvP6aMbXqLX{=ewUE^`S>m2POoA|#{yL#meX+{w^nf_8Zu
+i90HVZssI>0MgQ@VjGm$yVk4-RsAxx|vPp2mHZ9YJb(@lxZhkSQ)5`b62Mbj0e~)GEEoscS=gdq}9X$
+}7uIsT)kwvPsh-dYp=#w#_3W8j<gNa7L6}i4v$QJWX5`VT6!!qd0RB9Y%)PZFO`r5U)X2=&M?xh6)4m
+upKWW34U>-cmKVjML}D?>a73~F9JhppNyb+@R*foTsM6cA18b7v#l^IhuV5MU}(*Um#6r^e6NgN_IfX
+$eAIv0|L?)eYM=g&1`1<?)~oQMQ%Fa<8$$I$6E8FM9#TNre)Fh{T2@>XfT(w^{id&|H}1<IWt%FUB(~
+HiU+SF*zcS~RkA-+%Nu8^tHRvQ={x_wghQJxjsei?rZ=2)bmAS95sGOLy2W?g~*BX$PMl7nBPCc&mUC
+R?x0d=jf%xG%+=pTAf+YOX%k<E%u;~tJ^HCg5LY6r5OBi#~8z4sayaca8YIX}Py+q0ycseJuJUOF6%i
+^Lgje|Sz!RJ)?=WAv)E7m^BYbLHMGO16V9*PYho_i^S>p#1Y1!6gRE;I>v)rVHHG+Ka5t;BxOl;w=|c
+^$dgYht>h97zjVT8FQC=00`*`{4NizGEa_wIC=i`X#?z@c&uoJ_*13~)Fn1C%|#LtS4|pu<<*p)Iy^h
+DQNcWPa`ud$=(B$atVIgFn@Fc@s|#F}?{P=fUL~@ky_WlFyRNpFX*W~-zrTZ%8mjI&iZ9IO^t(B$Y9`
+jcFT6>w_3kcf0D5SD8U6mZc&+F{Qa3<VGKHK*Z(ft@nS*gghpQL8%p<+`EgH5x3mD27%&%@<_i-Q6qq
+Z?NP7ss4xy3irIj`*>b~DXAe@r<!H|`!L>RZfbID5a|v`;f=PY2vQ)tUZpt<kWPHoi+ZIHcQF?H$c`&
+~8+l^jcYcD8;7KlhRJVllEb<cIcfAQI4(A<`55b9=cH1Hm%-oC2^!6M|UCgJK2G*;E~S;micY;bhnmv
+P_#vsCbZHT!yAtGM{Z+L-;Ti~)ih1L6@9ujX4x5rnJ;5pd`DTs^Gv$O9<jepGYMYr*J!T0<y-GC*=X@
+xkyRGvTuptq+d3tf0lnKEWC7hBnmYZv_u}6#t5-02sy^zycsY9+zoN+#wejNPS6U35J%oXY6W>(U?B%
+rPM^&$t34t%7tLzivXi4d$u(*-n0A&Ui`kY>M+}oUx%}jU?@_k&wzu)Z7%$qI1Uey#F>pGqDyxG~a)J
+l`UbH77%fH|;5woP<H_!qcw9sPQ`UQJn&P%$$BXzjRhr;Aj^-%%PcLSgAsLmS-*b{>Z0T2$?ks>c&*t
+aXJ^WXc~y7w+kAZMED0j%RciS5KGSu0P&&3HnZv=fIlB?=xZPI+gCvG)Htt^etY1rjZ_qTbfnk2f9j<
+yxd!yg5OfwJ<x)$F{U^7WxcL=RZ$-m(uUXGFh9LkDRWhVn<ed`_k1gTVh_4&tak8xNfTNRd~gTA1YWD
+~idOmh)s7JEQ7)CHhYEG_QGs6N!A8FO5kgQ$7}2=p9LgnzJ~D9qfm}U0c3tu%ptsjDSE(8)CwbwgJmp
+gafGci?;vA2_rrU%MZ>$XKY!(ZOr^39TbxvYgR2820cKM+-xjr=M=b;%tJG!_yK08r6uQgrmGc5jbft
+HE3dDK3B<(CM4MB*4WQ=~J-ur%0m$FR4<XZXWoD7vmX1>$#i^v%iXS<~zDARG!!xNAQfTnt01Hd3!zZ
+|;d7F@bkkQ%_+AA(J}cq&swICBZW?oUOX1e=%}PVeDnrrr13#r6$!1iRs^kjIUzx7zXa?`9PeO$rKl#
+j`0#%I*NjtC;-e-RhJ;UAago2c!>tGE|zKno0gbKzCD>T%#X2)p84A3@pJoR;}^+V6w~Rd<Z<%==&aL
+}m~D?3PGd!Ozjl+ZX;2kq@;5so_njr83TT54HO=gyV?d`erP+A^5+N|Bv^hp|>w`yYLAH!qDRdIcT5~
+S|j6yWn9lrW>#+MLu>&5=%1|n}5&8}SggUUb%9iDhcHKBjn=flpnZ#U4t;Ov`FhTc<FyN$`ax|_e7`O
+&Sl;jqEb>3Y-^m*9X_XcX0*9NLKJvn3%~u-B%wl7-zJ>9Qg7l<q`ZV4O2o_#<7e&(viFjO$rC!?6@m*
+=R_cy7i&Kc89!mWz|Q+Z=F&ooEn0*e=A?tT_tIt-4l<qVl`v${tNNh5U+gZ#GEoO@m>((EX@hoK?FBF
+wvmaZ2!IldL>|fc7^;qOSYey3=-NPAVRoy6l_Y7i&oeMwYj&LM9=1%jIHw(9%BIO@UY^uH$l2X6*Vnj
+qY@G<r)bWHY-c4>IyL>>CLX5O`MrX|(piw)2dVJ0*I{?TwzC6E;(SFYg94qXfUCTurcaD%9&Q&`Rh27
+#~Cc?=Uhp0{Q=7N*-H+M?V{vf<T9th%31sRe~<J{glaZljwQh2#~HGJ^k3Rtq5;Q77>d}Z<h_veB7A0
+_0h9z6W?QAd<vd#Iy>KuDRl8yysNrYYTBMv8vN@%$l%805w+aIyHlBS7DdRD}cfzh8X5IdAD(_{XOw7
+sn?T@QjzBA3yOdy%nMFzZeb=9$JgzuCcX(8(qgVQS7c@{s=@sN3EijQ76Bl2iA&uI43xJpD1MfNQ_(R
+Q6QP51Kr9=&~D?=PHjBg)`qiq>(}*Kpv7hqza1!Ivu2}F+EYUe>a;WL>C4;}AXGi?ew3`Zx}u#&_y-C
+qSkR~RuBY#%>RScl3O-|mx~I!OIsWSTH%^gcHseETr73h?gZ5hJw-`%Ofo0_wkd{C!lJbiFj*rw185;
+0q&q_UU80r0!1-lA(y_s6eU^s}uSZ}duV#?9M!OvBZ)9T01@b9(EmH<qpg*QjAnz;xMJ1Ch<xna7~Wn
+7mlbs3g}eRr#vst<H(Y2A|(9oSEJecB;vzGmFvacz_G&nn7DKl8IfH*q;DL3B^u)j*-u2Ym%aAq|+Ku
+28tMn#OlJK8w3>;L+q696CB7C}-{{va%`iIl16x&YifSfX<T`C}J`qI*8f_t$4uM(G7*X8ZK^EQ97EE
+N}4GKiC^N`YO$;+UlqUX<E>E`K|cKJfF}N9yq}(T>V=xN0Y)d3Ht;{Hh!dc3vO7Cjkf(!n;=3lOPSrN
+18FCu@K_wb$+Vo*|v}o;oq9&UoZQ+I<tM8$fbY0X)Ddrhv4MTzT@fh{fc&uXUtgQC_KTt~p1QY-O00;
+maO7>QTc)F+@0RR9|0{{RV0001RX>c!Jc4cm4Z*nhbWNu+EUtei%X>?y-E^v8uk-<)cFc60CJVmo7O*
+Wp4HxIgc*o!Y<%%qe7M#_|wveCD<p%mI(<TUgBW!lVFThoh&L8?wR2$ghFP(K*!1i%IDNQME5dOoF$#
+hBg|!hh$tkC#`f=-palk1I-BzDP~g$y7KPVz*CEh8_Maq13WO9ctC0>Y(&jq<#B4w8&t(6cUposX>{(
+Bu1NNHxs#5p{-E)M}!)AtEc3b$&HUsV6m4&0Q2MhMf0P-cbG}pJP9;%<Jy#u&Js6kaKCKXufs}iaEz;
+7!8~0O7X^US8bCaY&w1b>6LC0hFb7v_|Bo*^VjP6TZc~zzRZ5PpwdCo}WUnTIASZS~PwZ~C5`!t5nYf
+E6x3^18PE&(<k~#FzSMdi>O9KQH00008031s8R%I~uGa&;204@yx02u%P0B~t=FJE?LZe(wAFKJ|MVJ
+~BEWMyM6aCz-l&2Q5%6u;-MFzq3UmPH*%94ZwF*bV~;Bw*suPL-Ryv__5-*^Zzf{&$`~+N5c^u?w0ea
+)=xIeg58iKe>ghN|I)k1j5R?lA3_XsvHuMgIg)5E8q!f{Ca));q{f2l?=Rs5zEx>OF~c>n|fO_vECW|
+($pMneXKRB1m!`nYy>lk%e>NRiQZ?ZiE)%Q;}C`OMKhT^heh)Omqk+)6EN?W7q?*?1R1AFk+;Tg<h-Z
+$Bc28U!6%2prx7XO1?ECEof4&GLcoNs><9V`abcMbV{-n=1vy`BHK>Fzp>L<wnt52^70I(!sXaE2q)b
+7JP88k<)zl_?$el9TP?2+k%3}2E_hJ;LMI}qBBWF5}gRVbOX&3jQ7toCqWHlNkWYWs}ZJ)GJixa{@xS
+uU5uBZp7_<Zlh#iIAPQ3=B#P<+nEptv@=7MX++gr@w;!Y6k<^#(f*B;>~u@pO;qa%H8Kf6;FVDHt|CL
+S9vT5LrUTW^iCi*jnIBK3b%E?PsY$Vc+z}I#o4i+5^6m))=Y@!w8vP3%hQesY9ne8h125zqma-9<rH+
+M<O}!j){X~;NFER(2?qxya%XBU1{tBMmgV-MxZQH8wA%H#SP6k(HkHFejqEN)I&nJBmFya?DV>7xY?b
+zW)=Hscy+Shz;gRwnHcostfaKALFAER{>Z-LxL*-t{WwnR^K3>gf}veAe9l}O`Ix+`Fr4p9Z^+FV(*0
+F0simi+G)%vtWaM^Za&`#FsnO~B?kdE6o@l)#R%w7BF5y0c@Dc+AF+jafm>?p{#qocNc-j=v{1b|J2o
+F4b?xX(Tqh~+*pS1*9ew9q)(Az6!;;*}D_sCCsjVe9WPeAh%s_y7e)$qj{@OX_)B)5^}fbI?VS`?Mj7
+~}o7tf^)z%uH_yRfG}+RA!rH(TL1kv~4xLI@)B)q~Y@Sx%X{HdvF9TVHUDn&@kC=x=YT?-Mr&;_gCQ*
+DLKm9i|_tXoaC^UMxA9jJHC1)L*mZzfw(8)R$N)szuSV%y4CB8NL!d$w@OYV4*md8O9KQH00008031s
+8Rz;@=4!{5a06_r&02%-Q0B~t=FJE?LZe(wAFKJ|MVJ~BEZE#_9E^v8W&an!@Knw=py-$(NDk|b69fY
+C|U0l>j9L_eCgS+I&#i4KSwOT}P%TNCA(h7T6)+`9t2Ns1{)_$@E>%UODVCgZ2C3SPSkY&oU23t6DdD
+>M~?#vxs0a0ZNi!Izc#aLvJo}fO30IA2{d(*L-pl@2d-Rsbu4}=jh-E9z){NtrV|2;AugJ8&G(cd}Lj
+!gLJ85=RpTKVA6BPliq5te*X?T;m_SE~&)j1h<xo@!mcKbjDPm1}mB^w|qgO9KQH00008031s8R{l5|
+z~Ku30G2WU02lxO0B~t=FJE?LZe(wAFKJ|MVJ~BEa%C=XdDR-*ZreEa-Cx1UJjg<A!-*5m)@TN3lXR!
+EX*y`rVz91Z&@yFfB1>9P%4LiB_dSQCB$ASR=}s421F<8DJog(9>8J6A3`np^;xr?{GNMbG(T;jv1e|
+$U@svk_7cZGUA!QvOA!JWU5UmO@AEO|SdgNV_!7mNvltB<>DUDW)m)MGdxfe$n4WdqGejlWCLt$XE2q
+FME_d?1!IVaCMa~jeG3+GA7{NNFW7S3bT?>n8jB5b~lGd@olyh_;sKqNuPy3X`-J{+E~&-n;`KIgtaW
+cWQko;hx(BjLZfym@(*rg7T+C}D{QchVv7IXXHbuPA4PJ$g*=MEp1<Gz`VMK8s)lvY)b$W^754G+u;k
+!*Qj6kN}R3j_Xyh3?#l1vxe-d#PhIb5olo<q@V{OOhEFl93D3;$~d9GZ4_sO(=6bA0Jxh`M)x!fmKVT
+S5`)<H!Ai+8;J{=208oM5Ji-T0Fz6M4NWe+X_eFaFYG#jnVb9jg#DZK3Xka$#tpG-XRw9<nC$=SZy<~
+!h=aT-<_$vvx2b0mPdr&Uwdg~OHxUQHM_&D>N4CN{{gp}!vBf4Sbx@snVQVI@5KG86j2G(^xMt4#C5D
+{-pQ|e_bMfNmkj>Md@EKehHub2w>oO@}IWP%-@r9C2_#e?8&5y#;~Ut9CGZk#TW#$M_60||sr<?qZ@=
+#o5oLV~(nga4E<ZXn<T;RxVy#eAm#kb{hHaUpmBVk~t&KKn8mp8o!)GXT%pP?+p01qz+drRRq%T4n35
+c$mm2GZl375aP_@8&m@e<ZPGxOva;184B-f8gix+a+~JNKn!rvc6MOy5s+;V;!KD^6G6ldYPu(9r#Pr
+DBn-$QCubw~AWFS8^X}#tB?<zCMabb0L@mew6Bj@%x_%@Wi%6P>5SaNo&O`9_D10IdMre|R7*l{uDF>
+oVhm-fW*Okq30SO6^iYicvVGNbsVEG6HB`#Vwi}DRiA&y9Dd*oPSw~Ta_M;b8@tycFyZP7V#9Mk81Bp
+)R0VQ|NQFYs;PRHP(IBK80-cMmM!>eweL{5N>58MaHu)yN96C*)6x;LD$cW+aJuAPD<XnRd#ORM`Q#-
+lN;X3xJwB@0}iTUS5mu8)s&+W=LEZgcg#tmo!?6p~@m`^ODwN*#kN5?5`4mX*!&hk+OvmjfFHb=w@L}
+mDi3vyRs|v742=4j$Q{T&-65+DQA<zE3k1(f7d<o9<v=#+Mq8`mCP3+Hn2!!eVr&U?FCEcP!3@gauY`
+kC5n%evK*RX#Q3JJq1zLP&Gv^%!6(KWWjI?c5WcVE_XqsG5Z_m~`29|dzY^a!AKu!=+Nvd0C1`k2E|u
+0yH$tK)NrTlo>t}I4WPT=<TI$PmDVyby&2l@tlF_=`HCRAt#Kp%l<{!?bOm+gQOsR?Z(;dW@3TmKOX;
+-t*`W*b2CR`$@%{Bec#-suHL4(q~06&eUaX}+N^akpE=^CMMCf;rZmFDXN>Y_Z`!}PDe7jsAckWazzL
+FPW*VKLY32J>xATu)W{gdHLMTEuUd%E?2Jtw|7uYz0<P$<GYvj*5nDRTEVCSwKUzO<<{3LDdU5V~YS$
+dKITnRpNs`k+gIXR6H2;FW3r;D8T`kc*TU;c2uR6S^w9_Uq2<VTbjprTj`c0o=i?9fv{)ZN#UAueg7x
+%2)7%hOHojq0_}yNI<ARINuuvyDwRY1<6>+lZjqYBt~R4-h9E%SN?3}L9b$=m&lU*g;zmVA=tg1iZ`i
+loyuJW;P$fFpvjnjhxll=fY;F`RDm>yfJdq2>+{vhI>mNp`4sxtEN0sWlWPXo(MQ|G2t4Tq^+?iXtPc
+;R$rH?1Wp*JzoKg@>B#&BYXf!e;<KtTHBc;>nYw521{5bW$q5<l@>EvI3$3s6{MH`)bk{o@{yf7W*Sk
+62<<xv1Qx>f?N{VwpyLFtef|Fl)k*!gOvOx6TA=Cy1;-XG6fiDL`C1P{E7;E*-Zaf(q_yaT7m_l+imw
+QE2b+oz*VT_kM@T^cl#r+Hd}!$@TqzDOXE=@m;&SEWZbLY1g-`VOl2Cqe|QuReDw9a%(H#;BYe>E`Bm
+vVMFpli13AGd;Q~@G#i9h033TFxtKGanKQm#m~{?DKb=i%12Cx<^cbz1<3=ylnsO%PP+<K%W$aEXP4}
+bi%pYO$tBs!4D6X08Hk$g9re7F1%fq2WjfVbWV#FOUDfiViMZ-JH`Ph2*7Y&tRTUam}oJcD;)rv;caZ
+w=l+kZgpx@&#=3yqp0(g7wjd>oI#vd=3~yf_zw&-a%EO!oy0)pV60hGYMED`{qkucg<5G{1>7|1i?VO
+{9&#nzV*6rCLu&fZ0VAkxI2v@rR}<eVWxvwtz#$oYBZDdm~+Ym7eB`u9)~8ESYRf=b7LCn^vq=UTt>u
+Yn9&BCc);A+F{CQX;zx9HfUAl`m5&sh5{-2LExfo{UD7$D^^<#(R#1Hn6EYa%Po^kQH)QW-#)#(esk%
+}EPtuFsj$7TMRM`(=Jx9M+h1#Fvh=C7ZP8RbiwxJ`+L{Ji4xpT0V-!B_uMv2$%c*a@wYF_*=R%%t6ui
+5FDlEUuzM;NCrep0KXj|*RJ}9ah1<OCE$KanV7Il>5=WrelqyMi^{kxj#o3tEn*YXYxmm>!$`A}Kd9j
+0cYENUzYV&5Y1Kx(w;Qk?-6n@(zk+=jzD!|CKPn|NEs&f-vyaxVz9av|3s%Oyq#s?=FOyHnE}MQ87>v
+p6PU9IfhwiUz8qc~x<MAC<@W6&`sotWmgYhkp};GLt+jf_{-!K#=v=t_j4gW|!iuj#1mEm{%O089dfI
+W_w6>w^a3vZJ-nOlN<K4Gi8?tyNb>Ovvw^59Ac1r=zoi@nv6@^f^8wF)1XN0X@EYRcFhi%dL<fM96MW
+GQ}uQw(*$^m<%_*+X8WMFV28iGr6I;02$3)QN?B1%ep5z^fqxY&LUr*1BAFlO(b6%TUgxc-xs;k38-R
+^;DC|`mu&w)NYNn=FJ1Es{+@`V95)mzh7OS*t4h{BaT3(II;ut`2>ue1qhEXcV%=qbep0W*1y32S2Ik
+>n8k}XGbahzXn_OUV-R}><db!gbo2Pj?l=;-J@>jPYQ&89r$FD~Aws{qvVpz_53p#J!H`{8tq_nth)!
+R1$j;wp~3`Xz|PqM*3?RSt+rah^epC3tpU6~eL(2JB`bEP2%{VZ8YzbE~R_VU61!QUvNWe!x@If{LjI
+1h=i#(+hHPHWrpv?=^|baRd1?$0M3<2@v931q3#s|8!heY`hI9;Qm?83qpXVsWkx-eF!xk-u2q!I9Yc
+@2n_{LvAG#F6i^26l7y34g(Fx+aa!A*cMG~fVV|(Y-&j`avo4+T4uWol?mlZr)!NFm#gNWGz=e41PA7
+hpbv-*5)?^mqSj<{r5Rs5HqR<I>yBDjC<nG0&5|SaHt?X!o*SS)F@l@_jL+7O^RF~{g2BcaZt={cb;?
+^*HWd&Y?ql)0tn`9Y`oi$YmtBBy5rOehN9x213Mpgv{-(KH{n_hvJnW3{M9mgJQ2*T>kjwq}pYP0FV4
+=tTAuGBM}rDT<?E?G;lR7+dxh8PyokdBp*i<AI~0273tNAgG*0`?kqrP-R|AvTh&W)7+zj1*r-r&>>K
+T$iOOJy&IG?f%@kaZirtAr4Jv1umsPGr3DS@gxjjpEhVLEy{WJO=Go;m)w*U7cWmfg>z3G<Kk0udr2C
+yb(YG@!b$VuCDbI<Tg?UxS(Lp^zo4aT0&-L0v{rEx60_UNDANH=5~#_#e2<;5&7)rIShpYbOKCcqg`?
+(kap!yBh;yp0oMcG8>B=TI?`Ce>8eIzc+dIzUcB={&%Ax)j!NM%d3<p0fHWb2Z4hMULg7)h5!^N97Xj
+Ntzd$3<ieh+qNnPpp?db_i>cz7)m{MAlf0YlgQb}pTN&o1qlzE$(-{{T=+0|XQR000O897^_90XEZ^9
+wh((SFHd58~^|SaA|NaUv_0~WN&gWX=H9;FKJ|MVPs)+VJ>iam3>RkB{`1WzJ5glUX%y$j6-i}051&N
+@Dm;{8UybN)FayIX;(F>%Jwt{{ok#)I`_*wC%YC-AR&mlU&JBBphyL&_-CJf_dh=W^6CEkhxKW<_P>A
+q>3`X;pNIY74}bdf`}O1c*?wK~Q~%SaUw``P55N4&&+|w7>uJB*ci;W+!~a=7|MK~#AAk7a)4%%ky-R
+;{{mu3LcfX9EKmYO9UpDEVzWcQQegE%&Uh5ye|JzUh{MCK_UH=%$_4*e|{1-${AXg?E$cxGMA=it@HG
+-U&oIx&3t{`_N50EF5*CCrHvV}ulOg{Lojpu8!oBjo5x1H%}9(wjn&-i_o-}n2_2VWnzb+^k*cNO%-b
+dTRh`F+Iiqx?SM_o)iKfo?+Ypbw!>(DnL<ue%7n;=VmGy&w79L+Ata8JRxcbip%$=N5S$0qs_<f8#p$
+{WaaYGrzkfRkNO7g4-?2`EoCf-EF;Pz%XD=H0Xi`y{GK2PV@bLupi}F^XrJsuSV0d`~A>w5|4-a_$?;
+V=IeUF->uRM=={`f0UWwFriXgyfy5soo)%H(cpkay5yjW^yB+#%nbhRA0{Ub%%=dc4_Oww3j=t@d9=s
+#uEs1>xy0ynGd@q4z+DkkGm7lRqcwNnp#inBuFbjP-o(4?YZG5Q!RKbPFHp_)GK|b_Lv|{z2*Z&p8Nb
+NO0R~j^L=b_x>MORPj=tbg(;O_4A`@4t2^fSx5okCxr-%LN#zgsW#0J_{a=0i`)>*t^C_x7Xdl5<6<W
+8($jYV**IpZfkhc>8~MUItw7XCMR_c**~1dEmpq`pYrc|GbydfA~va4PbAc;_E(O9X|^JHva)ebU#67
+6BVFDA+QPG7VSv&F8r+B#T|NMlWcf&b{lmdVPNRM#K5icKGM4`Ct~#wtN%vc3G&V|kmDK1^+Vo&{_cP
+N^!dlnKmPuQU;p&S^~FKC{&BPXx1ZkL!qau!_1q2IjoeM#t=#R@_4~eWgin|6>!17jFWtc1$lb)<%vU
+ZvT6whbsPSm$?%?j^?&9uER}L3<9e0`E5a?1NayN08`3;4;%x`GiWqt$m8<^j~{08PX+|-TF{FX0W$D
+^LR%x`3VBl8=X-^l#NN|KDsZ)AQmvyhpE!gEx3jtc8!;b)<+PL|AF*2%(iR2Xw%%!TKu@EjGMqrwapX
+0Y-zSb2^r&r#($sys)P=cw`=Ri2~Db5!{mtj68W-ND_--Njvg1{*(vjpw)V{5GE7#x|$%{5GE7#`D{l
+-^Tnlp5Mmv+jxE(&u`=TZ9Kom^J_f6#`9}DzsB=xJio^CYdpWk`fRMv#{3%dYs{}PzsCF;^V^x<&ir=
+fw==(;`R&YaXMQ{L+nL|a{C4KIGryhr?aXgyemnC!Sf2;;JDA_W`aD>l2kY}-eIBgOgY|i^J`a9=2S2
+}q`5pZH4(508^E-KdC-Xb``JK$~WCrIXbG_JZEWYo}GkEh1-ptWWb5yS9Qt_kfXv&JCIVvu2H*z=e-)
+8O>?pE$L?iydYb9Zoea(D5im|ynmig(;)em(Q+nO~o{o4H%K%l!JrqsF7muOB?h{IXwH*sm*ba+iM`S
+vZM>lUO*3g_Bq~iG`C`IEjUmSU9P2mz5#0a8l<kD??)8B<43UznS^X%x`9XGxM97-^~1G<~K9HnfcAE
+44IWbGryUYAv3@1F&6e1OJRQ5fh>jjWe2j9$X({QFu#TQEv)>7=a(JG!VY9%2ePmOS=fOr>_C>mR~~$
+2HuYujmD$vn!B=KeU)a=_$&#F`Ig>SKvLq)<a<U{RYtCfNnauBGekb!gncvC$PUd$pzl-@@%<p1;7xT
+NA-^Khc=65l_i}_v5?`s|Wi0NviwXAZ8S2@J19O6|D@hXRSHD<nY;cn$0Hy$+}?c5#Qo!njAr8%l>y(
+?Sq%GSHG^{$DY?#kA?CgwLWzlomi%0{(j+BvCgR4W_R%0{)aQLT?r{rXZ2gN<s<EcQ%`NG+@zYzZre(
+v>Y?WlLB&l&%~~R}Q5sTf)kguoeN?xjVQ!xx2VaZa}TfZ)JWf^ZN>=zdT2;Q2MKG;x0YE^$DfFnxk5|
++xW-)EL46LDnARAp9K!3YomR_+F0v2(ySb5R*p0)N1Bx*&B~Ex<w&z~q**!AtQ=`p<LNe@ZsX~;$s95
+J9BEdLG;8PS?mXQbX;zLjD@U4@BhAW@X5~n;c2;kWG%H7%l_Sl{k!IycvvQ<a2lLC3X5~n;4(4|-zk~
+T5%<o`+2lKmVJKEJNOP~IF_i4e}{l&lMU}g86^u6?h^rQ5X^t1E@A8$tQev`gQze|5ee@cHz|K@%W{)
+6xzg#RG?2jM>m|3UZ<!haC{gYX}O{~-Ja;XerfLHG~Ce-!?s@E?W$DEvp^KMMa*_>aPW6#k>|ABF!Y{
+72zG3ja~~kHUWv{*&;Zg#RS`C*eN{|4H~y!haI}lklH}|0Mh;;XeugN%&8~e-{3;@SlbMEc|ETKMVg^
+_|L+B7XGvFpN0P{{Ab}m3;$X8&%%EZ{)_Nmg#RM^7vaAM|3&yO!haF|>&5oDI_Zo3uR;1z`swS<H}~?
+Ts4sY`;*t5NG9Ojuqsn|#nU5;-QDr`w%tw>?Xfhv7=A+4cG?|Yk^U;L=Cj2+yzX|_M_;1306aJg<--L
+e?{!REd;opRR6aG#3H{suee-r-sRfWH<@wI;K{`}g%@Yic^@T+kSsCK_dze>M--8WgEOx7op^~q#?GF
+hKY)+dwo$z**pS)WYSCzJKbWPLJOpG?*#ll94DeKJ{}Ox7op^~q#?GFhKY)+dwo$z**pS)WYSCzJKbW
+PLJOpG?*#ll94DeKJ{}Ox7op^~q#?GFhKY)+dwo$z**pS)WYSCzJKbWPLJOpG?*#ll94DeKJ{}Ox7oR
+txqL?)#vr#GLBmwf>VN5LQq0f0&Pe<gsitM`irW+X!;9NLf1bTN|;}B{}7g5;}*ial;D)$m7wyNDi7X
+ZeF#|zMUe6~>qBTtFeP*)3?)p3zVsKj5SHr4Qh7+oxe2OcE9##p(xph(RDvR1GIPBO(q5hZ!s{=B{vs
++NDIx1MiV~_4nqI^77hMTM|77Yfmi|KJ(NrEy<zWiUObJ~H3d|IkEhXHn4)aN<`&!rMB_?NHUI{@7Q3
+**2SqVi6RS8WAri8A9p@gY~r387zrn{7&@^C5-r}A(r52x~QDi5dfa4HX{@^C5-r}A(r52x~QDi5df@
+G1|l^6+AUr))c2x9r<&f>VN5f*6Ba_HH&IDIqJND4{B$DZ!M`l`xbrm9Uf`GQFe9BdR>2$|I^wqsk*D
+ezNbR7fpK6q!&$Maqpr?i(a(oMT=gvd~?yH1f98}Ggoxxiq2fonJYSTMQ5()%oUxvqBEz<+Fey1U4PM
+?%u82^b(L6GiFK7&&q^qI7nN9V`X{CYl~`Aa^{IcN66-3laS1SWY40KS;~x6#t4n(i)pd1g@1gQgm-b
+ed_8zK1k4yX2(zsVodgrnUg9)o$Jo}sAl;D*Rln|AWl#rEBlu(t>lweBeN*GF*N?1y`h2T^kPUYcL9!
+}-qR31*{;Zz<@<>6EwPUYcL9!}-qR31*{;Zz<@<>6HxUghCc9$w|)RUTgD;Z+`9<>6HxUghCc9$w|)R
+UTgD;Z+`9<q=dKLFExt9zo?1R31U)5mX*Q<q=dKLFExt9zo?1R31U)5mX*Q<q=gLQRNX;9#Q4->}ox`
+#((~9{501efBO96uRn}G*e}0)RY~*xfBXA?{a^m$zt#Ff)RXzYT*XH9bNN)HU4^QiCMptdt}sJ2s1(;
+;4rI^d05X>;T_|O}q$0C`T$$WJ=EB0OgUppq*94hMrmn-yHuOYx!0i~f18&E-9dJv9uLEw!xE*ji#*L
+CI=NPvGZmAMRiJ4ZzdEoYp+XJ^}+#a|+<MzPq8Mg;+E+BOtxIN>BqB&MHhkDj6NFoQ|4vaehU|@hKSa
++c@*+AyP>@Yx{OkN;!;afy?VC3qy7(wQu<5Tvy$%V;y8X^OX5LIMRMTklYyCX!ESX2q3N-U~`DNa1a2
+@;f=yaWkK&3M8TOUZZwZmAeYZK{)k@dVtNal@K8DW}iCouvvGxTQEd19xWJ8Mw357z1}^+!?sJQrTtT
+=3+}%fV(j60^EFNg2R~!t}yNb+<cUR!%+&3Evzfh*uolHps|HD_UPK>Di>;20IUqK0$^o;IC#NT)>s_
+8;3|u%;UQ`KkThJo@wFRfr|~p2u+x|wgS@#i+u=|LXHwaUTN>Zez>YCH26>xQ!9pR7x%{Ysl?qsx0y+
+1f!xVHj1s%+HzGcTP2eUIElfg2<qV48y96Z3&FadBfzzKkp0Zxc&vZy9RHRY5GD8yt@!6|TDneP_nl2
+77r3v(%z{|j@ucrF*7oyE`2f?yXv^9#@XVtFsfdoga5(Yu=k`*Eg*9KnHG-g2S_Zh7kg79h*H8RwQ#8
+}8vLdG?e%JSESbl82|{*;DfHlstP%9-fkCPszhm^6V*jcuJl<B@a)@v!~?YDS7skJUk`Oo|1>B<k?g5
+@RU4zN*<n)XHUuF!Sw7Yc|0Xv&U%2S<k?g5@RU4zN*<n)XHUt)Q}XO7d3Z{mJtYrM$+M^A;VF6clsr5
+o&z_Qpr{vjF^6->AdrBT>2zWUG1HO-E-^b%D93T0R3-~^seIFmeWn?ZRxQu*DI60o391kbQvy<cD<oM
+29!fN`#T%IFjE<c&Pz~y2t*8-VOTe!}@5czNhFdvxt01q!jzDUAF*jWg076Lm90nWlV2P_qkE0a6O9H
+ZfcmC$I?g5hi=UNXYOwI^SDHjw!gn2B5R89ZU)zzVkZ0oFdSwGXiNdhXJCAIHSZ!`cV7_5s#Du(c1c_
+JOT^fVB^7?E|cRU~3;>?E{}E6m9_ILo)(G+Hf}}<CZrmTZCFg_Ie|{-pF2Wgx4F{>y7YwBYV9OUT<Wt
+H^S?U?Da-?y^+1%2(LG?*BjyWMponqMUJe<5sDmHkt4j`$X;)Ren-~tSb)1QZm4}MjJp6gKMfJbjYU3
+gELPyIj2q5ytc;}MmX&W=aZC1kW5q2S-x3G+#KyO5xMgEe!AFklBgY0&H3kURIr3pqu>m)G)Ug3K9}5
+#3aPyHm5sr3bM?1pNj_hbhINFgN?TE9NqA_j*Ze!dA-0Xix_}`KJ?`XiyYeVe7-5GZW?#{S7aCgStfx
+9zqtUIwY?hf4S#78*su`})t+;Vc(@E`{!N01YfGsuO>739Wb1GzJKfXucEQN~`9i98`#UR~paVENp(I
+3ZX*mn>r4iM;MatUHm{orrZO^12hT?nGX9BG#SA>rTYF6M5Z<Sa%|?I}z(n<aH-v-HE*JM65fJ*PV!U
+C-S-zvF=1(cOurE$m>qLft$}ci&%~#FGmqEN#vL$-oSk`ZiFh4LzRfdD{`n35voKERU$%_#Gy(;sFFB
+TNeEREhbjr7O5#u@Ayi2msw9Lei9?lyP$hAwk`SsS4pkCDmBgV+La35BR7nU`5{D`Yp-SRVB_UKv9I7
+OQDv3jtgis}MsFDz>Bo0*)LY2g!N<yfTI8;dpRT76P386~jP$eN$NgS#qger+cm4r|waj23Isw56o5<
+->4p-RGTV&dJzbPU^-_~_4s9jL@RP#?$Qv5ifzv59SL8t+5&0+S=iERzA5{C^&~N7sJ8B*~6`opD@Y<
+|redWACoaZeq^IBIiPjK!&H3+4N?Z-aIFh55T-gf_a^_A+z<#_aPU4xXb&U51(dO5WW>&bg@x+6*fu*
+_N1^q!A9j(S$%Lq>{WSt87IVEmCsqNIIOm^D_3g+nZlsj&P^+?4Hauc<Nfc3TQ+vf+c}2sYV0F7$g1%
+UYr_s}<HKqjyvN4jTZ5a}c&D;qr?T<hW9uH|z+?bqx25$nJ&j$92DNYOL$uLBCJ8ny=#3Y2Y~EgtSJ$
+?Hgx9oo0|^IB?Oq_$Ee#8d@k(M?N$l!OK7utzqB59u^Teh3BUlUk>)=5SOvWww1(coBG&k9pJV2gIK3
+p2_EEu*`j9(HN_D_sAN(`@kj9>d$!Yvcu5*lk9kQt&QV~sUvtZ}?!&{*TZ#-Opr8f(y4V~sUvtg%~ea
+LbJ~)}XP*hT5R9Hu%@jSR0HR_S<;3+}<bGvc?)T*4R869H`Fbu|qXGt7eC4_G>cvNU*bNcBp1&)$CBs
+&Z^m=nmzC>p_-j_utNvsfYuIW>#S@Y%GO!gI^G&~Hjf=|_Bxx#4rS|X9y`oq=Pd*rz5AqoGa0w!lfOH
+T`0i{qJ6=F_j-orl<=*%r4KiswJFsD$<Km70xEo6luavs+wV_s>6}fki*%9f8>N=a=j_|FsA|t%KIxB
+LAMeb~oI~2LIB4dTV2CL?{4#2^xInL>>*I?BgP|d;0HlS>Sm2F_pbg;6Gh>NhY4Jg}4g~=7<&g2O)Uj
+!@nVAUK@&B3aPAo?1tg9AD^c;z0@!NEE>po4?$;D8+*Z14sQ-e5f$FnEKP=mCBP>&bwg4AzqYe{k@dy
+@4otOj=zL{9l9Z;DGuJQ6B`UgQHPs=97NU<a6=KS~a0nll5dmPbTZhgq}>^a-Zq=iIa`egi)G2^Ejpd
+nmqFpZ`>zu8%`{YlNDk@AtoPEJsU2<&hW$z)Z|^FiN|<y1cMi;*W?YJi7B4ElQRdn<afFg?{p{6{KPx
+m$r~jTQ#^T!Cl17(JjDx3-C~z$;bi#5SvCt!{NhQ&X3MoW23(N$s(fvP0*gNuu@DL@UK<vY6Bh4OF6>
+k;-l<&Jsa)(jFTBlPJUe)!bS-`^7oN+-leS<`7Q4>a4Z0R@daZdLlEt%ww7TswI3{<HNvrVni0kGJ2T
+bL4b3A{;S-9Dcy^%<DhsxvzvRvfgzS)nxks5XL>%kkZ2k*!y&f^0DH~X<S(wA;t1a2$>@~sMds^Ypc8
+IC&}$b3sUB6nfj1-LopzF{G5PN%uyw%n|mH&pZHOqjdj+Ps~A!#}y%5xL=r+`JQi!x6cSWdcX!=1ue)
+ZtvY$CLQc_z9kg-W<^Hu|0HHgQsp}{Q%;=!$g1R%@f}XacbX3h^>kh`<NUGtPF@dx$xvjy*!>E+Tqof
+=l9T3<`{E_P$yfYd5}ZDA9VPe2pKxZkk}}zWr*q<tN4kt3a-D(e47tw0btFm0AB*k+FRZ)oL6;0kd|W
+0Z$%Vv6UV<d&A)s}k3H_Z?DVZ?wEDkR7qqh6_cn7bqyN}<qXYTOCy1ayb<M;gX6`QY@E5dI%Tc@rB&U
+wN!?uw*E7U)9}{N-%Kxl&lprFhWgI*?oGLdQpNihS&*9N&Gnk_dR*f!(qmex&?KmJ`;`-3lEUVYNse-
+#fjJqZfx4psvdNBG<q*$NKz{_$S%E*b~^T(2tAfn&evIb?0t*zOY^Anq=tVg{N!01K{w+bGJ-4;5W&p
+HsH4;Nr%t}laxy<_@YLY>%%@+6Z-KocFXgN7oWS8FLvOgQ8s?#^BcT+Iz$n><@@&Y(%*H_&klKZ`5*|
+~8#j36ci1T3tqJ|ujUgX_8t*hlNkJSZ2hj~#7d{dhMSrHp$Fn3ae1;CX{QkHRPGW@Tqg;nBiMI3Xq`T
+SvaysLZbqdb!ZY6W^yyV)gq%NKXa<`JZcwTeuR+1Obd#>F|_TusOb}Q+NXQAD#<S(8brYF&o=??g%fM
+Ge{mkNf3kL4_}tIGku)G#au{9=EW1Ack#mIHn%V_2};OX?Vw2YxAJSRVMLl3{t^mr{o1fnRDFmIr<*W
+>_BhML(AZeko^I(Ay<?y8`e_LBk5b9|V5@eyMa=0r=%PT><!m;K%c_<at>E_=DgNz#j#F1pX-aBk)JT
+AAw&!TDKzbN5LO~U+m0^z%L~d3-)J;f4Cy>OOeD%z%Nx2D*?aw11kZ))Jd!a{8A{f@NqqfYj+>`rBq_
+U?^@!QE__^Xi9fb7@JqGC%D^w>5-S70)Jv=k{8BKnGVn{q#De`?QZlhJ@XI>B;O{Ldnpg$+rD|do;Fo
+o372ub;iB*7K?D>K{Uq$d2;4gx|0KcqX3+ww5e-#@PyA}Ku_@%01Rp6JhidBKX3jPZG;#aH+{8jK*;F
+maMRp1xDeKp{3g1-TO6Z{SM#h+Pc>wLFz--i3jXWEwGzEZuh4EL4t4Q$pp*{pHct=X-}%^)`uoCdjx-
+?$8NlhTf5z~2Rb2mUVjJMfF2zdG<sJh(dWcfsF*zYG2j{8A>eI`E6%xZpP~`Pk?hz&`~40Dh@ASp)bb
+4qXHIhu|N;FMjwMz&`~40RAEP2k=k9KY@P={t5gNPpt|3Q}83sS`ufi3H%Z-tO@+`5z>W^kS>YK)&zb
+ncv--&6)y|;wd7?1zt+4g;Mby;1^im|vVdR9UKa3c-OB=g`MByr+`VqWe*?e75$gtii67Su{I}r0fnQ
+2!)(!kpL$k1tw4{h;;Y)|N_|<q@@$JWUKfd`Wzen6EJD~1H9Q4gccz^3-yNDleS!a=*w_7PN!hVA6Nj
+hvwI@y%meSF-u6rtmzz!L9c7jw5==mT_)D?dt@#O{53%vY+~K0f9v`-dMjPZAG)`N*%x2m2fMlHV`LL
+G=I2M}FzP-ko@GxAO7d^G0E}Bu_t3E;HEg+I<JQ7M>)~i_k0RP3Q)C7y1C5OI1d}eT&@p_)EJL{6`;l
+%T+d`;yP8XQ*j;kTRdKQ?lud(fL?{(KsTXx&=t=FeF^<O^d|Cez~2Oa1O6uX8}K*5-+;df{s#Q=_2q%
+DFOMep8}K*5-+<o)zX88~SJ;5x1it~l34Q~96Z{7JCio5bP4FA=o8UL#m%6Lbfxip>4*Xs4ci``WzXN
+|4{2lna;P1fS1%C(rF8Dj}55YfxUkk?u@DIU1fPV=70sKSo58xkye*pgw`~&!h;2*$01^)zosc;(;_^
+05Xz&{251pX=bC-6_fKY@P={t5h3@K4~EPjQb0{7djJ;9p|L7VM#v?u}Es=ZAa)eB8K>d?o#Ts>zfB&
+3X2Jc3Xu$L1(^D>)>aW-=8?qOD2FvmGo|vUP0&e2=xxTmEU*#zRT}X*(g~8yN}-w`8}#EB_Y5gBVf1k
+`*(??R3l?w%gesjS6`jy^1SOL2!(IXl{pzgyPZt`&Ch=~(B(_p@6Uoaspb65FLUF*@}+IO$P9A+NWcq
+&;D*qD<4fMic8F7IeBL>RkyD5a>C+|^7D!dNEMJnpiA2rJ`;dnG@!fi%2hgL?6X;p!1@tQP2D%BogRX
+cc=u7DLq4U1n?gPK1vE~H)N$@A&Pl7)Ie-iu&_><sIz@G$v0{$fU6YyujpMgIM{tWzC@Mqx9f<FU)7W
+^6bv*6Fbp9Oyg{vtR}9I;#BtAMX6zpvn{3SSj`Nyc!l;HwH>6?|3UtAej8d{yvOg|7;}Bqcdl;BSJz0
+l(xb=LY;u@HgOZg1-TO6Z{SMo8WK2-vs|j>9D-y`beqHyslX}?^&$ydyw4^phux6(6i9r*Qr8ppqtP;
+=tJle^d<Bo{}Kd$0L~yd18_<LeF?xB1ZMzF$*eB{ID_B}z!?N*0M01#g#9dHKMU+<5&KzSKa1GU0{dC
+SeiqozBKEVueipHxsH@qn;D`MzVm}M)XA%2ZU_T|#VfTSw>}P@fEMh+k>}L`CSztel*v|s{S;T%8*v}
+&Nv%r29v7ZI@vxxmHu%AWjXMz1JVm}M)XA%2ZU_Xo4&jR~dvf$6aFLt#Q;OG68-8ay?&<E&K=(xVv;Q
+~8c#10qO;Uadpzz!F&!v%J@RKZz+NBom=a-6M*T`jPyMeJ&UT`gii3+!hR`&nQ=i`dTs`&q<(mWFw0G
+A|8sGr?)VX@b*$(?o6txtZWM;5Wf<z;A-zfTs(dj_Y^1e#iB@T)*S`QV&x)<kLky9rEcSpAI}j@C?Xj
+h<pa*GekZozSynk&w!o}(esJxPr3fY^`~5aLOxUEGa;WT@|lp&6#1Nu-Q6akXVB$3r|QwFtdI31>g|@
+F3nV04<@c3_d@8F_sDzUvcFQ<XLSR+!)U)xr+adHbzfIQPckNXZJCD36Yn*4e`$r!nKgy7CYFc@RyeY
+F#m<~B;RT=`A-SYL3Pi0o*I<S+*bunfqFy5_PA2_u-%P{Z8`@n|!tlcWTfzJGPhu=H-{kv+-E4_j)*T
+KAW&bKraX6}}sqj#NKU-J92AF^AP1InFuD;02OzNXl>t>rJl-Nt!AyYE1kRO6EuwA&=~`_R2y$KyI)u
+H$hXFV{JK>25ityt{+5bDrV7kZmpd4>$4$Zp|M!Vt7sd(1Cddyk<JTrgFD(T<CT7ES`4hz<may4kX+>
+=|IJRrbnL_CGMNU;SQ+hyj)HZci3Rrt(*b)+PirTEE#y8u^S|}Y7@@QL)5=`oq_eVlKqYBq$|klq$>b
+!(7f;fxItbxZ^99KkT<_q#C$}(6jH<WFd6rpF>(gvrQt`ix*T@kE@b~)Nz!Mo^zvJFD|ri>5Y9l?f&L
+!QO!?Q6{j@TJctv=XAexAGewR4un~*UeZxt`R^}EFFdkBY*B6;gi;XVdr2H)p4S3PvOUKImP2kZ<4{f
+kgApnriUs>%_(n{b|}s+?DFUgdq~Rl#|cQ$w$c$Ds1@3=bh<K<@EAKDs#_@EDNfx~t*lO|m*RVVwa<$
+GDK*uBGe`Az`5Cz>$?X{R@Y`kW|b~XlFp@<CLjCZP$S#c8dxZV%Ie2%fPv*Svo7w>w98408~pDd>_x<
+6>i64&{Y}m4*Kfyviw5P#nmOt=|WboR-kSI;11Q2cOA=AlYzvO-HI|S++0(Uu9J)Ov?43yXk40HbS<m
+~x0AoP{duA^ZQ(*X#`6Uj87LS~%YX!n=ffH@fCoojspGJmr-Uc!z^k^>J$6Y3UQzAy6^$+fuX2~C4Kn
+a96XG*V9L{BbS~(^CeK5O|N)Pwcw7dpHsogod`)TDIcH}%eJ;T|Z@{p$$&QVq4+|ZjJZQt$GfprGt99
+?%(&!1NQ0+}k#>)G??Ox4{=uF58yd-$k-0l2;v9jF*+I$#)BI&h}eHyvmgFuhdA&84&lN5DU=Ozrz{{
+UFA26A}id4xF27S(FQqRq%o;_`_fb`WL}tKyMy!^Pq5Fdy>1AGvPO(U_fsk-+v)OgnzYLMU`+V$u~kF
+*Q4|b7Y}F1DyxEfNNSNos?&Z<WTKGMy<5|Pqi}MnrNg=RyOngpO(+-;K9JY#<Y2h{Y~oT$GAlRX=x&m
+dI+rE}Bv;SD@p4)G-A#xX5Ro98+GXWD16A%awI{FVY2`28-+(Aiq+8sXLD_nDI9dK_^->W7YLMZ>Jzt
+}j0iddqF6iog9-Job$0jrkm<}9!)%4pJ?f50T)l0cEA59keO(+;>I&hwk7WE#OkEZi+D)FCIzp-KGIh
+SLL9s&j=Lvs@X21FU)!#R^LML5HAZo04_srj4guuYg45EVuGvNNf7M4{Hxelu|R7!pl9C0%DgwH>Lxy
+A@QU9MdPsSPuaMD&3QYv|C9F{P<YORK1!fn%J%Bz?t)@e9T}N=sGYkuyo)k_0;)5lJIWz<{1N0Hn9l>
+15F2js){lov3R#$2LcB4QqbKg4x~G|FYZaA<$?FNYHnTbZg(c?R$1L}4Wwq@A(8cI<>v4ccPkak*SWb
+5qSQXVOR?pt^~m-0x16qzqmuVBs9%9OM+rPDs+1eQzrK>i^kta7Y+_6D*|FTMRC;E_IJ=dPg`nghTi3
+rB7#R8&69bZ6ol#w|Tec-1A0+9b?HR$(Zsj{DC@{!c@tOPUmDz5kG-ea#8IZ?0FL18KF7FSY<U48=_U
+kp|Zl!!>6EI+UsfA04dCm7Rue%kIAd`Ey@_`j-NtHePFSX2)^yaYn{<QMh58Pw7Q3nzRh7L>&{6=B!e
+h_%T9S3r^I*{-e>6?Lsfh+?#o&nkS>8Qr+Uf^OodAFQzyb1V=ArXDYK?A#OGSDy}&v`$&uusb(!O=9k
+mEuSw>+M#a+K+FG$ZLj&(9eK)uhU)yVo#f8;Pr~;Y2|At)^I6N(M@n?Kx%*9-!PfC6ur;epPS#FrHgE
+@r!6{A&wy((@Y0~Cu2>6;Upwbdn{*&!KyUsoMb?_U>pYxKjWG|rzsBPDE!S67!CD@Af`g~kI^S2S+ta
+eFzACKM0aTJ{*!QKhQwPrB2TxmcpkhF){9ffQPb)Wnm-!WWoEL1#suIzEDY%o9IG)cpz6P3>sD6~tv8
+Besd3no{EQ=F~d>2oD6He7auktMu9G>UL(){wXx3ptzehcvNv5P16qyfa7!H4%_@K>k#{@?uFfBoIR`
+|rQ|Px|G+>ujs-cKyXa_&fOn9I<}!W@*5;0s=qC36(gBS4^DZbxA%PR;(+t$^`6kJ?Wnx5dZw${{v7<
+0|XQR000O897^_992|gCAp-yaSqA_B9RL6TaA|NaUv_0~WN&gWX=H9;FKKRca$#;~WpgfYd3{vDZrd;
+nz56SO6c}vOG2-qPG~H#`E&~P(y#;}z#7rVUmOM#bTVNkQQc@B-=;}jaiR9zsBk9>}mVK9hP=f#^od<
+IOsXZRix)M6kA`CrW<|otRVNmL=AXnE3r9cne4lP@i(MPa@b{QS^MmyXOo?u5<d(-uUM+&ysTXd+s@X
+}}w_a}sdv0awu&I{}75>U5wQ9?XFg!4lIRaF%gJfE1ab}y8iLw^tG0@Un9ICzBwpGh6e#>%7ALWKgq%
+z&?Dhww93=9u3F-bGPmGtwfHU2m+1oum?ccCe-c|JF+?FIj#NND0qFuQ1D6402hakLViqZa7KKKg}}u
+uF1YBVEz<i_*ilsn`H*{P|{y#J>Ka7P(dU&Qi*zxY>ByIaFVN81bv#tMX)9+*sz4GSqW~~pGXbiCz1q
+|Yc7j`uVU}j8+jRrq~$d(0!w&Y(e-11m)tdQhQyRr7QlW5dJ#(RO^Yp;;7CAqorc5`9v|WJ1N>zyqNt
+5$U(YhR>a0$LbtFBuL0nj+Q&hPK_NWS()|+rvf=n+~(!i}?UWYs8D!Kc?IajFj5o}RJO@kuTfcu(?y!
+E-dB)5@qEjO@QO>ge&&Agrl@k1Npr5^BN*bmmy05pLaOhK-t+}BG+yhO#KE7A8PVBSQ%BSt<!TrW1|G
+{<^gZ{Qy4qPU<<B$H8gi+->=wj__~ia7PtY@wY?2(wLG!dsYm`d^Nb#*Hsx=M!FwBRqRW7;O!2(iF|Y
+(-R|={Q8OZp*};;Lv6Pk%EAk&bGm5~-Ly})+Zl52j8T_0{fZuKCpB{4w~Vlb1APV^;}|d+&!4h1j5KN
+6_`0olkQpZ^*^t0f{TQu;MQlcIc#z{4sEU7$!h=r@C=*C@zJnK}c^Xs;J7U&#*h=A%Hdvfcv`k6FfTV
+qB&?Q#-6Qq`K84YhY_au!sQ+a~Lb%L1(X(o>+-ou-w1$t|Wq2VgV%fwNP95cl5=~kqMKHIbucl3$+Z)
+H0?N!?!Sit1g;O1$ItrlGy9p!tCPJKR^1`^TKq`I}G<vwu)a0|XQR000O897^_9HT)>U7XSbN6#xJLA
+OHXWaA|NaUv_0~WN&gWX=H9;FK}UFYhh<)Uu0o)VJ>iai;pi$Eh^5;&x?;&uvJhu)-zG(;sO9rO9KQH
+00008031s8Ruz=IrJS4q0Lvx=0384T0B~t=FJE?LZe(wAFKJ|MVJ~%bb2K(&VRT_GaCxk~>2n>|kth1
+ye+9dHW-L$JZq#yb-RmBAPt~oeh>m#kzD&;xN4Whwv{qUqB}<gN%$pY^cCO&QgZoZ`Bmiz$8DVXt!WP
+9v3#BgvA>abCJHmg$9D?Tg<u4PLpU|Oj2lICebt*GYo;;a(^8DShe|>Gm+sj^AvGV0*?*A`;XU!X{ma
+kdy;_{U%f4l6}msh|1*77wkzqITZzg@QGjW<@l{SPZ%TD|-SFD+lQ{5yZQ?A;ZsezffEm)9&j{qpJ;-
+*{=o>Q{gK&YD+#P+Rt+?|kQ#x87K_Y|U@qbi`#VR=xSgTWgm6Un|~T^ZjN2`p%mxU;h5G|FL?-8>_$b
+o$vhZ-~R2t<o|cN?7uC4bK$rDy8IVzFbhxrkAMB|arKAp2kvJ-|M|NwzxB3z<mW$M_Ty#W4Jtou`(fL
+6zw^?|uPpod+b_TR^R^ehx9kW1wD5|bF8t}AF1+WbD^|N#zP;wHpZ)d4p750Vv!DIwJImbvz4h{%civ
+jP?57L=c%kh#ZQoz^-RQgD`~I_k2kPIU`gf%M9jkv=)W56h---HnP5ryB{++6SXX@V#_3vE$yHNiw_4
+gVEXbuFL1%c*4pqUV8E(Dqlf#yS?84+ks1ez6r=0%{H5om4%njL}WN2vJ`8jaBW2sJ-K&5uy?Bh>r|H
+9tblk5Ka?)cgoFKSIrq@CiTuA4w=QLGvSOQ@@A;O$aq1(u7zODw<H$ghUf+no!pS&5ua)Bhvhcw0=Zd
+KO)VKSnEgpgdhLyyY7FMOKSLx`U^>oo>5<v)c6_oB}uJ3qrNPu)o0XKBsF<PeN|Fx&#13SYW*2?g`}p
+>sK1od>>2fSNo_o%u9VdL8FiJU7SE`wCAEA;eM6egwrA8gCDrrySCZ=a`<A47{=O}#p1*4()${iqN%j
+1FS5iHHe=Vt=zrT@G&)?rls^{<TBvor@MQdn9YiLDlXhmyiRcmNf&)BM-u~nL}Kl=_=+hA!|+p4w%Rc
+#5X+7eW?C8%mkP}P>8nrcF(2@Orqma(cWW3^O-L|ev0^EuIcPPAoAG(Qr}k3{n$(fmj>KN8K4MDrujd
+Y5RuOSIl4TJI9AceN+{_=zM0nh<J2qzSPmR5YQg35h1uG@-5usU~Ea(9ncj6ADcz6``*AQP=#aYkt%<
+KkAwvb<K~u=0{!gqptZ;*Zin!e$+KT>Y5*Q&5yd~M_uzHeQKB7|16VKJ!w)sX;M9DQax!>J!w)sX;M9
+D(wZO4A9^KS&z;m8Zn?at+MuM`prlV2^e>X24N6*K2%UnSX}gkX7G-|%3nkSrezaeR@s@Rx?w7w$#wA
+&EF4LUL1m{jmx?lGKN%icLD}AQfmwA^Wc)YGNmPjrU`d;r^MEV(RsvF+3c<+cLd)MN<qmt~|``$50_W
+XVCxFmb;;=L1+?D_lNNlEtp#e1hD**h5Td7jE;I9%FgxZypQ_s+;scoDvLR+7C8-#aJC-Z^~lyd-;3z
+IQ>Ay&T^gkYq2!_by7ZcM#vZB*;1Bcv+Gm$3aPk9ET(savYXq$nlCKLylJ^8FIWP$$GZr;Peei2B$|P
+8Jr%KWN>;+lEG;?g>!IvLXyGhNlAXf>3qRumOgW#jZmSDP@(N~q3v{`?R25-bfK+Hq4`&6=cdpGy3o!
+|p^ZzSZF8ZWy+YgOLR*kh^P|-KC^bJy&5u&^qtyH;H9tztk5coa)chzlKT6GyQuCwK{3ta)O3ja;%}>
+Sm*AZRwC1~^0@cj;=YyJdnehR+dMRd)lpv_Oe_j`!0`4zPJ3HbhcqHDedZGQ5-zme#ge?gm{c<*l}y5
+?ih<|p0zeMC3>48YHAL^u2lz|S2-H~b91&s{_}{0zX)Jw!MB48YHQL^u2lz|R9jH~b91&wipCeg@#@V
+WJy;hT!K>q8omO;OB9o8-9l1=SiX)eum)ZX`&l`hT!K}q8omO;OBXw6F;Tb5G}3O5QLD^0FA)NDTJIZ
+5#7is@^V`72b#(z&KN{qP%C~(bcp3D(T!Llh~+xbjaVYTK)*jqbZuRO$S=<Cj}u*6*&y-@^ZS!T*VZ<
+Oy!*5A_cTxh8$W0#x?X$&gc?8SB)VRN0t6aA=q9>ei~@uiKj<a8UX%g^89yFhO@LS856H;I#wZ}l_yH
+N&*eDxfj31DZjg7J)!uSCh*^1FM#1}sxBU>>>0nx<|$jDZV_93?T0U6nf(LO{LKOiGpF-8G##Sh5HRt
+!HY;3pZ`is5Gk{3Ih=G5oB8pJZfB#4)IXpJZgKhM!gNlZ>p16b4oBlZ>p17zS1FlZ>p190pbJlZ>p1A
+O=<NlZ>H>BnDORlZ>H>C<Y1mIY@NF&jkD&Cc5Eg0)CQpG?B(20YAy;n22MLU{`aK=ziLNKvvTPAcMqP
+%@4?GCdO(e-fDh8Rx>eHGx1ha?qq_RcHM)Tx1zUca@RalKO|4JW|&&@O#P5N)tX^y%`^4(PNI8T`XSl
+Unz5xd&(zzyiSAYPHkp%}XYGfZh;CS0^NRTqnS`2W<ZUuPb+4Yc$=K9AKR?_~bh9ee{i<}^2V$hh5-+
+jGQulJYO=hQV<Wz^8$VAk=oNk{Xx}O3cGLMW&se40lo2Gx=EB5Unq8r7oLmo7RQ!kGX$^4p_YLG&+i4
+P{W8l=!{GQTFq8l;|MAFm}kG@Ce<8qH4OCD43Jjk!oY4?iShn;K)AdY%55=2hx>_@N9P1t!`WWL}#;-
+avHE!;i^zLEQDjD?~S*7Gka+UL(5kv@*}bk7-6_(7F+#8?8e`^}`9G8;&7>`4U@L1SMCJzm0g{YNmUI
+{%8x)jY1>5_t92K&y6q;+WUwYksH&3u-->xXmcY5g!DclgPI#L<emc`?IpTVWd!s-+D~+&$_VCtbdc!
+AJR@TF5&2=c@f!+n2tFc1V1jl*;g$F!G6W`g7ZhGCJ|aV4f_OpU4Z%m`hnZkrP<ZwIh>WZW>IH?@v5&
+|PGr_%}@QVHsnFbT&3kvX)46zCJ1*O-zmwrcd@PrJp3FHN(=gEh(D=1+c$#W{f8JgH8ycd+<%ox!PXG
+(B}On?dZ1tmDcqtcuS5%#;aj_6v`LWKQpbr4-^T8OaUtuCT#u7(Kv-RdE_*0c~|zgz2xuK5`v?00J;(
+KSCqg#B*$9jSC)Dog9UgeIIABAj@ukLX5D2q)g!Msy=5gcEP=Ai9wg!il$b5#7iM;lx{eh;HPBaN@0f
+L^pCmIPum2q8m9OoOr9B=!TyNC*C?tbi+@C6F)pebi+@C6K@?Sy5T3niMLJ?-S89P#9OC{Zup6C;;pk
+pH~d66@z!~w8-60}cWZ#?hMx%g-MU0{!%u|$ZVeLM@DowLTf;;*{EYk;Jsu>6B1Cs<oalPV4H2UIa6i
+!t{OMB!m@h+!?shxTwZ{@7MEBuZqI<pgm~0mUbsujcI<_uk6=S0vs0h5xf7xgU;&ivkDw;T5h&bKt%|
+tiafjHf5vR)=m7iL~NUL!JCOG1EW{!1cz{=P+I><LGR?%8{LjOf_s(2|!eS`-+<MgJ|44U2P8NYPC|9
+RLY5PXTNoAOmoQfCd0sh4UN$2{<<u!Ei2V4;>a>8Y_wHh4D6#y)b@5Wav7rDaOl;Vn2*OtR=c12GzGj
+X1+z3Z-3Z9bU%ha^s2vsBAF4Qn{wp^9hT)jQN<KaBf9s;L86<AYDD+`I81a?S&iu4$239{-HQ<2`{Q+
+@la-MEOm%7fnJCePXi)-%W(FtP%tU{!KXm`|k3{x6$vea;Q;ZnZS`<P>wF&?we+2J7xj=M3^(j3Q)%@
+K5WPs>?clgOgqI)a*$t9xe`n#y+t?ZpmMAvnA5rTSmHWMA3lDqS$ZuAu4yiZ6^>s~8A86vu$SD%m!5P
+bXO3ehpEt`Z&GzD9J<?N5l?2*G`FgXrKkDODZZ9woYW4?Y<qy5~8S$VCX;eKJ9G&-qU#iS9Z7iQHX92
+;bcyi<Wx+-yv;Gb-8Gidd}bJAiC%Lolc^A&fn=Gy660zZlZh6-{~Q`=lq>sqI=HYSx<D&`8ykk?m2&F
+Bhj^E7A@4|<@QS(#v&rNbVu$zBGitt_9DW>T7>E`<`v>hJikys#@~Wy6Y~}oWGsDCLKdNh?9M)-n-eg
+oAG>pa=*FC)cI-|+(Y4nWAqsWpFwwQw7Qs=tbCl?2eS?p1=Qz=gG~plIIZ1T0z99;A=QPm`KM{qxbC&
+3apNK-;IZt%MPeh^akmWZ~s0dN0J7n`s6e=pAv1G5x7WSb8S80xzLbM2REY|t5g=IE%X%XUBcla-uV_
+Ids#i+nrvbrXY6_wuJ{*iy_Ir&Gj&!x8jf0Xt)M(pbDR-$`;-rYuY&(FI)_ALFQWNH1QxXoLZyE|wcU
+Rrl|65UJd?k=MHnQ(VE(Y?&>?jgFL4|n$x-AnH7KB9Zc-Q7=gZ_V!>AiAF$cMlTX%k^$Q(Y;*n9wNGz
+>s@JyV#K;Wy-aj3*G~tD?&bRF5YavVKOH8z=l`cyi0=9S=~be8{(pLn=$`+dUMITe|ED*I?)m@e2+=+
+NKOH5y=l`c;MECsvbe!m(|DV!4K~(J1NuqoHe=7Z$7_qUtYl)6|wT|eRSM5ZH{&x@^`rk=(=zkZ{q5s
+`PhyM2v9s1u(bm;$jqC@{T5FPrzk?7F>O+<(OZzekQe+$u}|1y3On<Kh0>T>QLCAwaTW7Or`Jx+AJX2
+ht=xqFi6dL@ogmvi?t(e+9kqb}#}S)%KeI7VI0-Sb4(t3`~uoVx==*DG<1x}3Y0h^|-S7(4g7WJ%1<J
+;u)cF4+*XbC0oezf0D`?A&AQ-0zazFm*XG>T>Rq#V{uV;{^O9TVXcdaRPpll}HRf6Y!JlLt^+@^ZdL=
+mZ4_&i5>Dino~71PVA8H(QK-jabkyjkLFR$j1vVf_sBD-n{i@qe2>=dx{*6}#rJ5{HYF)B_QUsRy{;R
+%V<&u%R%%m>5@Qd1kJjkA;U{*#_h@yl6F;RtR9j+y2>a=KwBFZ^oUoI=NA}JX!o(<qxkvWS6vD*VL*F
+BNX9{6r?4IwDy)%anW9*ynk-amg4rA<??~%PT2M=SE#@r)&XG&vYl*Zg6dzTu1BL04l?43D@7$fw4kL
++D$_=&LlJ+gP1;U@y__sHIvqlhtL?f1yunP7X2bBOoI-kFn#F$!nyk-am8GcgVz-XnWwjvvMi9gU1}^
+zc6UKn)$Wj&bbpK6yV4UDp!h$l-nRdm4K87NfG~K6yM1y?cvsB=A1@It^Xd65}}Fee!Y|I+hcoPUt@Q
+H>OS~M$G0u+27pgA)+<+$^Pa>4-u!iPxd!AdWZ<keX_qMLK7oGbD!+5iO|G|(A+2cYa%o;A~g5O{+b9
+)j0nwrvXdr46C*-%pX{WG(8P$)+$TF}A~Z1~H229)ng~sd2+e)6lO{qFBSLeZ?4*g%#E8(`Cp&2(G%+
+GH_sLG02u+L#&3&?yCPEV<LUW(&q&XZIBQ|rN?4*g!#E8w@Cp&3sjAGOn-6uO~4h_brF1k;4(o`44h|
+1h2J87aaF{+F1lbtlxMKR(u_sLG0>Y@rFG!NDhUGuYo*vtdJSCqa;eQAA>im6(vAS&~qi|ATT6~tp6^
+blRkse(w%gY`t$a;hK(^I#*<wVW!5zC74WbS<X};w}&Rh;HPBh|7a*L^pCmtmVNDq8ol9%JN_r(G5Ql
+UwN>H=!Tz&tUTC9bi+@?R3024y5T3HDG&OIZup5f%7ep1H~d5d<-t*+8-5~o^58hp4L=bzd2o{GhM$O
++JUC5s!%sv?9-Jk*;U{7w56%<a@DtII2LnVm{6t*j!6l*_en#5gszl!3`iwY?>Y~q%5#4)TpAnyN*6_
+0vMEAbeXT)usIQ;As(Y*)u8Sy;w9RBPK(Y+t`8F3ypPoJG5y7$IDBmPI8+n-$^y7$RGBPpQp>9dPO_p
+zwYNEWEl`0O&#!T&*`ga1QB2mgnO4*p*uI{1H;=-~e~qJ#g}i4OkXAUgOzLUizdl<4697}3H1aiW9&6
+GR99Cy5UJ%Qdxv6ONy+CA#PT=d`looa5*1MECsvyo2bT|DSgf-Shu*S`BgL@$+t?>n=qVbGEU9DvQrf
+^61PVsfwwXsF=7<#WZB9m^e<Qp=(qs=1fARFz+&+VWrf4nyPK4v00#-DpiA)v6Wzn+n!bvFR(99Ka^9
+cig4q@UWIspeBGlEKW!dvP>5;Hmg|z0s;N0k+H^OmBrx69Vl9TmlpH3RE}2Lg=I@l|?-&=h7MgBfCg@
+&^bi=D!Y<^QQeZ?yJ+iMl`cdF*^R87M&(~YiX8j{uOdfL<q(~-?=@ai~>{OH84M<>P!s{`Auu@u-Ijb
+*?NYODe5sK#<&$23*|JFl@4*d>J-?$%8gy1F^nSvQ4ObrU|W+lFr@99&OrGd3Mssb}WzWI9Y#&rIt$b
+E>SK**<SNI8$$!26GMV2G$#9%nj|<)f=WAo(Y@ObJLj)L61kLjy^g?azbCDN2iWy%ygg2A@Ng})UQo*
+qk3T^Zdw!7OWV-S^sZ~ue<wBD!L&`!-PCNb(m+c*H5;Zh)KW-8tvP9A{*LL^o5Iz7bY|$$nQ_9*_n4*
+{DO}t~XKv`{^)jEDKE7$BwK6qz`DvtQTWXqSq_Lg>sVRU@W5Y93(4NLxmr~OnBCTk<nF>pIX1C&ku!L
+v!XbhI{%t4JAK2(Sg<RC0@r`A-M(=+Gwz|2%IZClgCh~8xPQe$XSV`x*;Xfrj2HZ_ejQ)6gTV`x)jXj
+5ZoQ)6h;%#7J&Fj8Y^Q)6h;hHl)M8bg~l%-=DFHf<RG7>_m0&373Sm>Lt98WWh7hR-H~n6+syJ2Pf7G
+iEX~W-@EjQ$90hGBai}GiEX~W->EoGBai}GiEX~rZ6+6Ff*nsGo~zy^#Yq2GnE-Ll^HXY88elcjx$+B
+FR+<#t}YyXbb(rb3g_y=F^$=`8EI4vhm2Lo%o%{JW;kuELT0Q&X7+noO)m(UalbOtkRmhfb2F1O&rCP
+mtZt-g`r&4#jYF22nPIZdS!%Syv`xrTGal1hHZv9|%gk>Ydcn+0rZ6+EUS=|XnXy2bu|S!zK$&p|Gvf
+|s#sXz#v({+S?`jy!(P-1(-Y}M<5oq0L7|YRM%R$TUQg>)Irles^NyC_uhB=tjFs7stYXLTlDQOr}(l
+7y=Mnx-Tqhf?(noBi|A!(TXSHl>RhA||KL{FxMDTiv9JzB#UiH0!}4Pzu4#&u{I*P&tDf`)Mm8fH>9j
+9bt!`>%$XlnpZ}8)i~A%%p6X1a~7hGBwHNMy_4GhH)Jl#&u|ziQ6cRyiAg`QR=^wo5`J<$(@_Yotw#>
+o5`J<xs#i@lbgAdo4J!$^mpYIU6_#@ea?+O=jOm#ZrtVEER4BX7<1G9J+GTFo2XcB%60NgN2+pD0F!5
+0$8r;0%Nu4qMpyHOwi|gvI~RFw<Yn5m<VK%!)2Jmc44;jz=0;a@)7&>V0p7y6xrNwSk8FN)V~8-*968
+clD9qvV!o&{?qa}s8RH3MucbRJyikfM~Y+S6ubPy|2t&xQ(k1JB`Vil$^uE0_4M`N2GjS{E0j}k4qOW
+feJFbZ85g)WSNE{uULjM5jTvZ^ovvch;xMXnc&LIlW0&p#U7M_5kSQNm1zYcml_V{A**4m=v)NPy`Wj
+fCB!iS|d6*9kL?uVd}%m8JzjiImu*iB0-1ng-QKWIdYLrhaXjc9yu%=h4J&{cF==TWp#p4(MMSPE-*I
+nppd2@+x7bId@gBXQe4BFB8Gr!ABEAgc;r<v$OE)D}*6dH#ziZaxGzr#N49_MjBvpSYvgG*+<P+qXVP
+;wb>AsIAHu}a=YSx-F&~f@1!(ax)MitA59+Af6?d`iiRIe9#y|KTevb6d_1LpZFCFeyN@Q%>t7q)$^@
+ggD&5L#<9DN5W)oO8%x_E?W|`}iAZRnTB4{()+n^0~rjM_jW<(3gk#hWafDvt$gEreKt_=lgQym8xv3
+<l%1T$EqX>Dj6z#udpU=W(^QxKZw500eQ1V=J$<id)5W5vGFY@&kD?4p9u+<W9m_HUW^Y7m;106}OXq
+d{mwqruZwDe71D8#BZE&@8i#WZ!6tqaDe<(JZw=XdJ^Jv@QH1vu$uBdL#KBOWmq83e2ZOfgPmTV>^;j
+?<mo;I*4o=+{oPf6g=%oz`rW(xKK|z)pwbZI*>s|QXoT&WI%=)!IbX1!blE;o4%JupJQvRs%E?8NVaL
+UiRuMa%b;p$=2>Fjm{{>9_SS;LB+P=uR1pM8MZ4WWV&{KiTnk6CO_LL&^@+K+&XMdJtwJRx2;xYlsb*
+r5wLxNH3XWuyGclL2IFk8Q&GNq1W_Vw-H-*#|60`rpBs0`no9^@z)J$!PBiV6<_E(9~oZ2GYs!hB%sM
+)TyH9Jk~mJ{{B*xtGwS3T6*%%E=ST^z~&%Ia!8Hu_b!cM#O8hS7CX(c(yY?-kT7zv`(Sm*rR8<ko_^b
+t>xC^{Jb!RFIlVE=RJzvOY&@XKiXtcWMq$2C2EiFi7pHomvB*TKkozhWDxES8DdFL1y(Ui_PdW>kDOx
+{aaR!nF$9vl4+9Lh>R!Mh)gTgr$KN2mAy!!fpe+o3_y$i61VttZ$yuRD?Ai5Dd48eHJp-P#{do#w=;n
+A!y6dDf%xML`1SqUeH$4u7OR0nvQr&f83}-FV<ZH!oskI04n|@iI~l0}*~Lf|$ZkdwAbS{rbJMYx5jZ
+y;`xt?9)3KisI5!;!7-_X%X<&Cc)zQyL0pt)PB@pTs-AILejxZwRbCeMwpJR*&`LNQYLOv%L5%M|7h>
+*`IMudD$Ga}@3h7lp3vy2G&oMS}D=R6}qJ{K4f@)=-6$mb#>LO#@ex{(R_TxLYbXOIygpCLwse1;hj@
+?l$(3He-QM9AkFBSJpc84>ci!HAI02qQv1ql}mZxRD9=PcS0b&sH-N?57sj4ZHPh*x*FNx&{rCiVkeL
+D#&rXWjWJvOXDd9{5Sl9>Bb4j(M0zprhC14ndxZ$-p_znnpc_bRpvFOdxcrSbgwSIWV%<D*O~5BWhK+
+SqO4*%ZXRH|S@3flba{j6p6}G2*#VyKZ!+C$&RaysNtZQD_soBX>7Mz&X1eD+D+o@y+~zwHaMb1YHU=
+<Rue3Ab`Oi9q(=Mz)IPJm;B)S6cW58Qcz8NML-GTYG14Q>(<xFJXk-P+0dvMl;wFGBf_>Qq0IRe%R9C
+pDSJ>>Q+aVOLu$1$3zE4z6tu*FyQFyh6_3W{6?D<bOlSrJjGI(3E30P0lvrkWf@s_!x#OXQW4jG#y65
+CdqEIm`gMWYX%CqnQykP;>zL;Po(oivpRxXhY~AM{6VIRJF4BXQRQ9`nYP+;^WZhh+6hJpx)}^(pDd5
+Z5>iG)X2*L=Jtpj{^)JKPzCPji%iEgMY|Zlg~FE^z;#7D=i!OI!gTcY=8I0?hTcBP0A?)f9h^|Ut|^B
+P%J)0va6xaMV*nn`)iFjqzdz;)1PAo?00Z!Eu5~fu<?*rlc393q1|SgTJDg9xP%4M-d7IS|uIFu@bE4
+DwRR$oD8w_}fe9UVP+)lpaDHpdPoo4_I*Vi+ETah*}0GIO$s~lWTzO*Ta$4Slf9pDA>JEnVie9Y@H+|
+iGDJ%%^RmpJ8cMn7RDT3@t4ON6N#>lm?@`=Ber)Qt{C?EOAyU@&!~ixGRp4|*6(-RNP&-tvPs22(fIG
+h#3LK_`Q$8ygw1cm1FsVd}<aM(lMz=w~o>qmL1LgHj;)yp0jd=Rojz2P2lxf#CBlMl7EL!RI}USUv}W
+&-)m$d=3Pk4=`f+90)%5Gh+E12tFTX#PT^5eCE5V?9I$YDEQ3RRdK%qa@Ll(EvtK%5FlTLWiNg%LLor
+D4a?sBT!cb^d?A*-{<#Q+0QpWV(^SEcgaG+kEPGjV5efnF%~*ERSwupBgN#@KMnZtYjM#}12|izC#PT
+^3e7??z<#QzXJi>_Ob0qjY#)#!}B=|hRh~;x6_<WNQ%V+E_r$*TD$Cl67TuzO!;g1)&*bRIhVZ$F=K8
+sD|2pfKLY{ikl=Mgsiro79Mz~>P*{Pr^F0{h6R5jOlbj9;K>!qf;GetRW!Q4xG*!*6eeE-Hf0Z20ZP(
+1qCKjj-XjcS9Ey!Dlx7_Il`|BKXXP-`)^iR0N;d@Y_qG3$ddcVZ(2$42p{2GaG(;Rdi7md}hOM3vY_5
+;4>S3dtr1@6?|s<Z10RNs)EmKpY65LMOE;b?X$f(x~K|1vwgN(wxTNd%=X#dA6--hpV>a!E2N7=@R{w
+iy+yi61fSVH+l!=&MDUsIv%O2YNCcnRKHKZ0i$w65?X%s%7Kz|9+h^0f){z9C**=^8wT>kC%=X!4U<>
+35r$*U6+d`58*}SPyw$Ju%=>mzosZqAi_Il|8$-Svjw$HVe7yATD+^N;Q3j!Qv!(X!kL{HzTQ8xUht8
+Y-Ct?$$*8-CN^#gQPuQ8xVM%y3YMyyYkxe$y7lk%R!*@SBsyjwA%ghTq;hT_AP1{NqVRkeX5!)0{taB
+>(Aezs-RCa*+`n<v(n1jxIzhaFk84y*#=QIlxgi#rFQ_LL~o2*%X@t0*)j!j7_m=p6f_L!`Kv?{<)4M
+G>lELy<NHx3BFM_#iomHP>9UlD4Sx_NY{}BpV<_f!#P1Aa(Sa{ip{ArM-qHyQ*1iwI+EZsn__#%bRp7
+qqil*zUtLEMd}dQ@@1!n7CU2BYvFWZGJUyiG^v7dtiW`>C4e)u4O|iL4$dSP3F*d~w%jX98JjSNjoa_
+&t9tipCkJ(~2ET3`X_S6_#Ow$j*k-+CMwwMje=LYyZ#un2Y!3v68@R=>9X~^qHg3oL*O;27&5`1QhX-
++LVlHfDD%H~Y5BMCmUt8AL{21PFT%&xNO&l`xNI8$TnDw|W3L6HkSv#Y$wZQh08Gu!7yF7z%0pV>Yya
+;JA8_{{csk!!sR!DqJ5i`?v82tKoYUgUD`LhzaG^CI_q7lO}hpBKC0Tkx6fv%TfJC<ULreI`d~iQCA!
+S6Ts<LV#@eO><yJ5&~qyZ|@*4N+Cct{H8^)BMAYr;kS2?7owPZj19lNhP)6}++%F`?ZJ$q6ar+!Z`uV
+1r3f^SuVn;D&hd4OVCduRjKJR-?_dO9Fy6@sYEj0!7{P~(cQb-olyO=oN?S-=+OqLdgnh@iG9tcu8zb
+VYw=*KXdIuxot9LRYzM8MM4@@m-Y3qwi5%(NF!ie~Sql}0zIL3(hg5!*cFF3)7_=1y+2)UhNM97WoVQ
+Gt_OA&G$zs!jE#6d>HCk`<pK5>{4@rhR$5ubRK5%G!F7!jXH7NfM4-DPZ5Qv?7fctWD2WNLyZq=*Af@
+PtHF$<zc-ND&U4;0cMklBo%vkoK5XX-kt!(=x}A#L#(GRZLZJSrKFA>157s2W3SJmgkW@;Z>qQVrqii
+p3+v4mm+dC!85EXzJ_O*2w+X{46BNd;u$95SQ9+Ms^Z&thKX?21kbRl_(Yyz_AtQHbFvFRrptL9V2-b
+d6SQ<OZ(xtl2IBlIUDg{sJv^&^i-M0!449K!;*cy|;TzcFv5tg`Q8zPScK&7J8BG`aI>73X2wIJ=rQ2
+}>aVFO-nHqzSGTyE+RGf}?XbkSkc&Elt=``M@F?cTH-5Nt(#&{1f>9>VT+%4C=wDugv)t|$-^f`>np2
+N7ta~PLDhjGPo7*{UJxCKlE!^V$jOen@tjS0m#rZJ%y$2BGt<Alb9Vw}{NP>fR=6N+(KW3}geU;R1Xm
+p<qFvgdqX<2m1#Kj-_3=X_t;`ujvkZ$f{cDD$7t-zTDb6Z-o^ssDujJ`w1f(BCJ@{U`MIiJ0Gn{ytG~
+HDSK5_MGplKj-_>=X_uGobPKq=lk;Kd|&aL?<-q>pFMC@ih$t6W&LxkXM-BT-M$wzWRB03_IPF~D*Gp
+|>AwImOtM!iYWpYIs}(`Q3H1yvUgs4Yp+ft4PnaJ)ftLM&{VRkF^&@4gM-~EyPmw>e>$wm({OdEl8WV
+!KqTYqux<0wCAqeK8hOA&rQyE8sU~X#LF2acuymi10Udr_mLB$E)Ip8WU<pCkIXunR%<qz!pF9aDq#@
+>HJ3P&;89=a%T`}!xm_07#;!O}E{awM?nrg|Rwdy}1f5fq%@-BJ!dvG<o-S3ej0*{S%G7ZPLs<bppt6
+@Toh>9PQSc&-)J(G?-Po4iLT1T%P#AR>1Yql~n2Sw;NrCT|1^!INIalcJCq^Q7=R`JY5LeY+e<%++zF
+vZd$Mo%I^RwewpvWalbhk4}#05_e^G?-E8pTW1l%o4CP9tG$N^<V}n-0(tVb0^vN%HX%?JSt(VV5q%a
+oeA-;*>5rMN59mA6lfmRqe#&IM^$FWdY|W9pWAu3KRz~y|(vcE;!7w9wuNSt3+8Q~M4!Js#jx{(^x%j
+7>2$Lg482ym@kHMHhgX?IqBUSOpRreo*34;c=JXnZKEquz~{0##->gz~CJ-QgtQQxpF_LBJLe`cWO0e
+<5`@agGL)DwE^9kx{x!#T}7)3?WwTF7l7G{Y)e)eR9GDYn1TW+rSyWltN^y&A7zx^DC6NM0>srhAvY!
+gQ|_Ri=9;B~14gsK#_}f9gz6pRw)lneL6x<KFFzc&+*|)4l0=f$3hezQ=U$jISnotp$@29SNB37nqRg
+es)GoZy|wN3klR(NTAk20<{(rsI`zlt%U??EhSKEA%R*83DjChz}!z0wjm0!oau`mXm#{O5A->@XZ~-
+Pj?+Q=81USGjp?5IuQT0qe<jmB_g699bDy;h;e|Ju?z#Uq)BW1JhUvQPM%ZQ=eK?XI-CO);O$kldX4-
+Fsw&z;dR+?W0SiG12!;6drK;CA=%TYby<@o!{3TfFCG+g3N-0oeKXXAeHAKu_mRDrz1h*uCg5bFT5b_
+B>({{HeSjCl2UmFZqRUSqm9YVV&W0H<44Fx@kLCDZk8!IAtFS<Q4mMOHI&%z+h0@?ZKU)BSh;is}A4-
+(tExBpe1fSMv5M2E6T9^D=)VPM54vkLbL+BYDg5JEj{yD!>VlJL?&+3_&7P{aG_11LQwnXS(OndnXz2
+w&E8|_u(s^QsE*@_4-71H$Z~{*4M~*909yk<}n;p)*7@H_+l#qo~>VOW57?fFSaw_nft{K2D}>bY>13
+E7$EWb%JSbZf^E=R25|Iwn1Qmz6FBPexR<}p9QAM{&!Cr>?%BYyLQ0lD775v3GTkx(M<jyB>pBz00*T
+cb3ndn`F&IfOV$3T?Xt9cXuEJPVKBq9xpU7gKN3q4~@_kjt{G6;<ER)aG7;DI}C@hzMQ(->DnOLlp?<
+1(%!usO?{R#!(0KG=M)K<L9fESsf;|#s}OH}|0Nd%%GC^OGSWVIFDOXxT1FJ%A};)TP@MYV<9L^_)%B
+$C-|`H~jWNLooFX(^4Ql{AtT(nwlKBWWp(q_s4XR?<jXNF!+_jijYC5-Sbz_LjH>ynA5_F()m=oU{<L
+X=vw2x--8cSw{;ywKik?O#fa-(y`_+Fr5Iy5YE8k-t+E126F}tZajk!p26eZi|#)Hqc#Q&ZdSFY?TaH
+OE%K|v{K^!Dgb`}Urq}i|k^))Jh%Q?U<50I^4P#RT<w&{<R2akD22A%8JY>3`-x1UO?2ei4CwGPEesW
+it?&o&GbU(9eO!w2e&UCDVZ47v}2I`Bk2C7f?>KLeR_No}DkM`3qP+yI8k3SoBHsJ4up$+)MVQ2&Xa@
+g6BzkI>YK8<+<-($pY8ea$%;x~;iL<;eN%@<;Y_{io96@~cF<_lGY_{h!+i9#}u)D+@lJ1^7~g6K}rr
+l10l=0XWbv7y!mNb#W-08)%t2)F$eQk+<@u78CTD{4YaiWfD=DNxL)K~RC>Mh%h*6*p=os2|tC)#d!-
+I=K1^g@CCqDg-=ziIEg6eOV#k=qm~VLtj-0`1zVbz|Iv40XKiC5HRy~g@BhU6#}har4VTSYK1`S-%tp
+&{!N8IKEF~3<nxw7AfLAt0{N_AB!hh3Q3&Mou0kN6Un>Oi`Hey#pWiA3^7)-Y{35ZO>5I0Gb9BE*yvT
+IFNW8>!zec>wbZoGh?pFvO`Xaw?iQDhH7y6awH6DmxcvdjouRFAVj&T_6b*B4OXC>49qO*$We$83U^u
++@wal^0vZ!+Br_E${zf_;nWUa)U7-3xXN)4gEdVfvyy;~d=!_Sa1J{QnKpJ^z2pbkBbZoyGa$IfOX({
+AWeZ7mq#1s5D_k#!)p^<lOV06&a`1US+!HKkHk*c)TXg7mwG(`QmZG7{w{9Z#cHb`i9%1Sl@7Rjr9!|
+th2u1@EYq|;rY+{hVyHzZ>VHpeZvtp*0*BOW_^zC`Oo@Rc>c4#p(=*;4K*>WZ>Wf2*U+3~3)42W3A0<
+R)U>e*Q}~!a`q7UW@z(su3aA25h>1a`P>9Fp`~Pr*F*BUZ+yvoBy3i`L_v$*5d36KL%^qLA%m_*|E)O
+yi0vTci1re8r89_C~<tvO-fLvt+<q(&zF@g$#%hwsH0lC3Q9mohHDUeY{kb=ED#t1}qd7Ke!<u6Y#QU
+IA`1bg|*Hwi)7=<(oMMj)TTb&NnhgYAq!K7$>MKt6+=j6gnvU5r3JgWZfkK7&1sKt6-Lj6gnv>luN31
+~)JQ`3!Dk1o9c&#0cawxS0{iXK)K6kk4QrA)%1ZRz`$;wlN~)vz-wkpB;<{`Rrsw$Y&QLLO#105%Sr?
+h>(wOy-#l65?{a&HbNozeLNT;`2CCs!5?5m2>u`=Lh${J2*Dp>L<s&cA+{W>Q5Cvylo1n1Yarxw`#b}
+v`M=8c15u~j3NR_qMpa1o3?nA}-KYu)oMXg9I~!HO`U{NclTnU@PN_Tx5KOwwiwlBDw|PDxm~@*bjcK
+anNMeTZI%JwEIg*$_yv*2DwSi#xFPZK?^j)U=@4Ur^9YO2cY}Zl#^mvHvy6I{ZiaSak53xZvU5!F<J;
+~!Cw&bR(Q7En~c|61>yk@-!lsr8iV%u$+4>=NM^$;6v(|pL0FrA0kTASuWVFO369uKjZHqD1ZacRoqA
+=XXPd?*yRr92*D!)%%lh2ol&$3tw9P4l5p+>i2jh)wY#-dbJonN6j+U^5gqqC6gA8(Ft}t_wc1ajaWD
+*9D*1Dw<YDp}73y@eo@@)9NS`x1Ky6I?jmYb1L|Jk`c@2RPgyUBbLvp;PY8VET2=sXEx=g)ln#}G<iH
+Uz=-8@D)@Yf5zFUH@R?1jX>}Be+e;n~v4J$LjzV#5$>SmR&`qnOP~2DYc!*td)9NS`7nM97VxQc!I&v
+hzXLiO-t0PAeeCEZ{v^omKr6rGt*h-sLM_~ierN_f;pG~VHM*^RRy?rKkYKbp4aIdriM8N9tFdKf;L&
+=dKz+pE0riW74K&a~RFdKf;L&=dKz+pE0riYRvL4d<-_)QNbM}h!{+3=elN?{`x0%XH)dMG)P5Fi_V(
+?iLT1fSXPn;uGzB>2pR-}F#&B*AAk{HBMJBMCmU;Ws^$97*t*4Zn>%G;+abHvFcCQrIX2pV{!69!icR
+_{@gi^iXmnxS+%Af)>^VE#USKUu482)f=T42HQo`3CNL59HwC!^@Mq7;xM@_L(J_#l-#t54xipk#J{r
+pkf&E&@UP%iKfX$`$ZhsMH}{b`k`ZrSH_7?j7Cb+_!a@DYY(Sn~kHEh&$8p1_mk+34*}rA(HV$o5e@C
+)^%iLP*NcL~p671aEZR|+)Z{_xHnbU(|VY-flg)L(#%&n4PVSTy+r`2aKkqIrVpb8wto1Z+)h*9$rQN
+wR;tYstsa)yx*$TdbHAU7HD2K5{2vg{DQY5Rscv^t~;WD_F^kRy!LfQ&NYx5hJ_YHZ%h&UBq*Bm;7u5
+pQf~y4xAaf$V0a0HXeym+wpue-EODGd))s@$#AJWyv9GIJ4mZBVIl;8%G%N@|oGRi;)TtAG#sOXNfNf
+2up+`XExp7!Fa*XY+lDm4ah-8Ao$H^8G+!pun-ZBoY}%Ej&S5mUoRsNeBW_KAov4&7=hpq(p)VOj+{B
+p%7Sp@%n2Sf!jUs4HZTIgpJ4GK96591G$RoF$zetypMkB6Kt2~)DG`pGxx_L>)Ntl<A0v>@<ztLMK9|
+*BgM0=rG6MMw4l)AyT;~acsNu|YHVvrDo4L+^4F&x(*C!c)d`5;CfqX{TY@xP)W`xZas{3cgt}p`mjH
+wYoKI0o1fqbZST_}32%}lVg(PM3f+FymD$J)#U>kdl&XKr>d;^i~j%QFi-)@FNoHsTn-?0WtloCBEMd
+5Mt#2=fg$Kg{m#VI%^=GZ+^@%<ewHNCgNRTigRNyNAs^4j#<zVSU5VgV_U@8S(O&J;;1RH@Mk@yo940
+-0TH40xzH00iJW{1~)sPz6bKT$kL95<HGX6If&UyI~jp|F7a%{8HibBDR2N{_OkkGkPoLTOB{Y^u44;
+}qYusAbBrWFSQByVq1ijeNF4~zU>td9u4jG2frsXLc9(G6p}Agh$IGX=;Q}LGKFuwijFdoV*Iyz9(%i
+x8DN1jfJ5Dj;<<s1`myrkvuX9L+G<UL&q6D|OlQkYixXs<HRY;aJcW-9|^4Z6dL(ZhRZ-NoXXFsncNS
+!qIvrJKq+dQD2fqV|L<d8yX9_BfR-CpxB&nzTSnkRV0KuK=%6t9g)rZi9Sx`3kG=2@O4IQ`H(&%8#qr
+Fow10S-Vk2i2${pJ6pN$Y-48g98vvw2UMNbcwHE2uqx;Xil;tg~JuiNmdr*ljhd4Yl@80+*;npAg469
+memzWrMb1tLS&WZ*0Jj0Sp8f(Pi7>S=6cvQ#nJk?9yWEzG0pX;5mbPTGvWn5*UMjuBldH>to+D0&GoW
+rz~PO#^*oi3c$!<!juejC&#h+#L;h)Q-)2T2pMAU#APqHll-*hM|C>9?Uy5wh+)?H=PTtR*<mrc`)Z8
+haWH^04cbYW>xv9A`JT@G_pW~Vu(eZDN>pVoizd5cw5Z(Uf2AQKch(E`fCei6{?kYP)IE+7cm5n;`R&
+&=_-_YZ4Zj|MN^wr!L&r?K9<|bL+kj0vt<Po5^-`phcwUNx4Z{NlUf-PM<=aAEy?_pk}r{8=J>kd*|^
+F8W4UOw}?Sf<Eu&F^MCKrg@fy}X1Y(KWxHjV=24&F^QUj(per0bZ!l!*9M{jk*AGh>;QqFL}s*&G++m
+9T%z2ALdztB-s4n0Y)GnwSXcQHh+ZeH7-+~KgM5*l-T@n)+&^C&mU(ihRoRfDUJuBynFr>J9$Wu&7Wd
+d4kh06=hWCBpY!Z|p&EPsyc!$ibAh)TsK}nbz}qKe&E_w#?L}4g`~_YYkUX0o*v|;$Gt47Es%w6PXCt
+b!=hc=N8L#<K_17SuQFhOf_?jQ%4JoR$=f`-(K>llfj5QvW+Vf*Pe~<>7A7jq})!OspTNr_S)TSI2+w
+<eRfkRSkew@D)Ron9uY%P%+o1frSCKthE<^fV<^OI~{P`y1rsm7)=C{c_4WR9*gOOE76`9r4bgia*-Z
+%vb96}6cgEu%IO`an>T9Ly!Yy28Cu#3Va;Fo>ya?qWpe1){cCH|cXE%QutXiP}t&N%XW$&Qn25x9?-9
+A)x&X>C~1ZdDWb5@11VnK%mK2L~W(`{qS^$3}Hl1JK+3;Njd`?1(E#~qHt54YZ*Zs!_IY#pkS~293yD
+a+u6<t8uWHwU<B=Xy9XFS-@(ofM$mPzvy&0Dk?ibZ1Z@YqFEfIsyxoJ0ppRtt5F=>F+da$(+VOT@VFb
+;1yRQ-=E?({2&xnvuHzPtmJ&Zs;ovbF}8rIIEj6gn}>luN3IyW#P<g<|xA)if*2>EPg1oG+J!U*Kk*~
+bXv)47!q$ft7~Balz$c19qdF6NH7u(j(LBalzmaYi7Yt`m$vK9op{L=%#!u2YOaK3%67fqc5oFar5>o
+n-{_>EanIE}o!NUL+ciOm*=L7WYqd@eCGMyLMe<1oG*+#0ccm#q(6$M$yIdR9y7h#q+c(<iqn+-1pkW
+^HdZhckw)}>dbH?nvG0#?qozvoL!7SFg-kV#T^<wJaxq#8a+Iv#2p$vJaNPw8a+E0fna*}Fap8!>|;b
+soP&%&Fg^W*h?`-14l^PQn|ekVwnK~v!*+xbVc2+rCPF?uLB(~kojj!yVc2-$h+AVjd3q$mu<`T|m&b
+PU^hktZ<LM#pknQB@kqE=asxGdQ?Yzc_m^i%1i_1B>SQEw799^t$;$n^-o`&LDjvgMHxRj&I>zni)qb
+0sR!@W{i%)LAqVKG_7#XTS0>{p1(IJ()d5La<@^OO}Aadh(<B(CA;<~2xM!qLs<L|nnq&C^0$z|qa?m
+g#pH*+wmnBnnknJrGvo(h`TDP~`^u3ka*t95}!T3RP~fCxNiqH#c~SAguPy4fZh*R%`BLWkXnvi)b8@
+;jbyA0ffC>gw<wFurWYbZRQ}aRPgP&ye0~)V;>ZDQ7O%@LTmtEaGv`27z+f}uCP#G9SVyC)}^pmVBHF
+<2&_k8Re`NnSR$~E3abfhlfvo(+oG^kV0{Y91h!RS4S{V_ST3;b3PTfyZ!c>(pbf*H+V?URKz@JPctT
+;2-=F%&6$bhJ>2$BcAiqCd-l;Ii@6YWQ6bAYIc~_^xAiqB!QanRH@)!Pm`HaFKzdw&$Q5fX+?;VO~0p
+$1Zo0QxG$nW2GX?{X}e?G2x2KoJY?}<Mj(VtjI_}>p`*ci<)gz%h+<e!HSo->jP3&nG4GK3JGGn5L8#
+ottd4I#Xlt^tKr#rxD`4-@g+d4)lE-;DGt48oh)yiQ>d-t0l8oFRnQT&Ld$;muxF$`a<{Zz?4VA-VY;
+HEGet{)L%?hZ&0?zu7$}6$bgu9yzD5P>e;%FM|A<CngmJ`OR$ItT4#0xqd`pkl)<UQH4Q%&67$-5#%?
+sLGd$!{Jt4Gt}w`NW}BKs5#%>Ba7tm2U-N+en~>i(<4Rx9bN_|8VYP5XLVlZ-&c|)y+m+78V*ZUQoro
+d7xgI6kI1<>f!ca}NtB(<QHzVVWpjru4QRLz-@x>hOl_(RqsD`P_v7-<%j5pW3%m|vq1q`6ke8>QrlS
+K@mi)ze(=UZ4|0R2;|4ET==69&9X7}gl@9${E#z&nId8w1`SjMSH-TdMkU?+r%k%e^xgsW11wV8mZ8f
+)*Tl4Mos`!>FMMT5w1-6hR9Pe1=uAH|}Oc?2UUE5qsnHjI;{+h1FI;zfi<3IJ6gv*ae67LJ_;*&|WBF
+7aZCPMeKq@dm&;M&S_)Bi^sWagdld|95zP0e4M++h?kFZ))?{f`4g4iImFAyIckh}`8YR?5icL-q%q>
+<<6JaGynLL4#)y}XbI%y@@^Q`?BVInvHDjcK5#0E8_y~huM9ypbbH94hOX<)1FEgT#<3u4s7i!lUB6O
+j4tzk{<bXlztx=_2;5TOg_iZOz<fa9KFP3&}enj*r$M<pDBo$g3KBO(j7juBD0%Iby)16OT21eL3oSq
+%_j;5t}`Ai>(hQ?AycGCvAY;KMb#4ngJWk#mfoa`hm~2ayQpY%zkhdh2FJP<gk0gb@_@&=GBiU`aj6Q
+a~iaxmb)K5^<Up8j*<R&g+bz@|#W#I0Omsb!QntB%)LC4Uve=JaNR4s9}~V3Vh~|@PdH?pKr!l+9>du
+>E6c(DvJk>Ga@2I8yLZnCXV`qshB^!$e_Sy=K3i{AfG<wC<=ULHjOcYEb_%Yj6gmE>OG=zRefm=zVSR
+ofzRA9FSID|aZWEGDDas%agY%&pUAsR<Y+GObtLYMXcx@B80v;1_Qg;(6tORcs-c*DF%%8O?2DmhC}v
+*_B||a$VyGC3*%w2>P|Us<>V;zVLQyUht1tJ$j@6fYS;y+jy{Iev<tP;jv>8XOP-q~?#6alcY#=mpHV
+}F_8wl;34TO%)20~M31Bt%Q1{1BF4JNuf8_bL9wO1MNqI&r)g?L%L{4N7tRx8)ML<s7JrrVD(5&&U;5
+p_e;?QBd?H#FVO<{5QE)9q~RQ8zT*&PzK^*iW~!K}F}s>Gn&E)PM{!f}ZB>Y*2CDe!BfCBN-50@Nn#Y
+x}6tebb*|1XY-8H_tWhYjEG{Gn}pyH{&WW$VRVC>?qF{kXYr>yc!z|JkgDP)L{G@+4qn#K6>_?R7cca
+MobF)96rCZbJJ^XqZ^-Em-aDZ?<a7t`ozNe0x`X#YXe2P*v5OJNr-Pjs^b?rwVAr^Sd^!#>0{L{XTUZ
+MD@YbLd@?oc}6!PIYR|@&?oGXQVc+QnVK0N12As=?VN+BPfjirze&&E>7hxc`*kPpw(QpktrX({BxE?
+z0*!!x)P@)=?T397LZGuufSqc&;craQJxcZ@6TkJ<wI$$6(u)9pw3Cn5c0c)DZ1vY1g@L_Zl<9E{q84
+Lso{)04l_ewlw#p`Q$^NguTdlXz;n{jB>5<H9hWahA!M$Ay8c=U>(2uN>a)zIdE}BCO@Pg@KMRo)SK;
+v_EPSmh=3=x13|VA@L6PAst32IsIh7{RuNlVNowE{6w*%Bz#!S>nISaadDc%6;TjK@QJwi<$=%$_vVv
+}j4z1jPq?pGYkm^bUm0Mq!k|-^1zvexlb^iA7rD6CSJmq~jy|0{TC;;h|M1cx0u6-Psqc7-*A2e#E|z
+H^H1E<Ap0<xK=$GPLM!y<Z824uWiBQ48g;~HV9tiy#UJ%{}#tXvT-|uH!DBsm5LtGdx{UmIYKUtXWi_
+E1^DB|@6Ei-l_6uLOJh}{Syjk9P%vAnEZgcqS$WO|e@6oq1)S#Lg3EHy@!p;&D;D2G5^LesHj5p@z*(
+RB1Js6Z#<V)0op`ip;gL;Xts6|o#`UBEAxPZaCY&L^hd*<CwF!jgVvbRlXZoEa4fXJUtWQuq^3)~#pe
+l#PBA(XWm#vJ6H-3wA&G6HeXQPn*|O<R9uVYmlhI@7Vj~L)&jIvKU4}FZL^cIErc#d}4aHGhUakcrrC
+vXi-Yfo7F4I2zRP+gK?o0`xfw<j0>gcf3{L9UJ9i+xG+S83w1c4Ss1s;zyIWqvn=C)9yZL4LyfDyFLd
+G1Gt<NdG>+9z^eZY7f1+-Ej8_RiuQqB?oDe>|VA@WbfeJ-9{LGT8pVZ|~l$#N!3_hE~>RW_59Mx_>++
+c7KGZyFaCyTC-u~3H-i@0QQsd0Y3A~fREQxBAJp%Lev8cXvhLi)*B28BkPe`0`?n^K7hA73yK>hBAUx
+S-dtN|nGT(`CAS$b5xRip4w#<VxF`YD$YsCJp43AT$s%rUpW&%s{wc(m-C$RRehuCmKTTv}PbL*t&sm
+*_L4k@~45}2QsLEVF+@lf#C?UsDWV#@~DB~2{NgHVT!mB&2j~iGs_l4&MaTN<U-3AFS^k3#mg?VeDT5
+y4PTI14GmwATYc@#<&1dgy`%syy5;XM;N|v<<!>?KrS`_V40w^f`62^eUN5a;pavjh1oslH@&RhvfGq
+KiLhhAb16C+jAfGWZJlngKL8Jut4(Mn=BI;jHtK?3EjP2~+Ewj|6)`7@99XU5M-uKP;ewDn7ki=EOMh
+<ti0=yP{GOiF@`>X)32Cpl?Yr*TkV8Cm^Dg}5gcvS(on`-$=M!XihZXhqMH(z1EOKY_P8u)sJ;0oyRR
+~hj#TBQIlpVt{c>h`tYG2o^0x<+uNlt#Q*Ue$<~%NmVT@G;CXWNud}0P|A;UNWyMzzgOTp3%tKu2w*X
+VJQSR94P=-yDGp-<#h$%a#v+fkg<JHBVH~V2=Nw$V79D^7>V&3g?O=Opo-Th#EWIs<KA6wGgc!^jn7L
+*Sq9{6U)P8i&nk`JW;cy^`MkCKB}NK?*s+%i<<TQ~`zAk!-0f-w2)m{bNJ;@-P;c@gh8*i^1yu18g+N
+XU!1Pf-z10)2YQJUxR!srIswu>aXO#jleH2i(ctTu~cZatUNV2Zd$P=Obgh^f+zxWjcm^SP=Ag}r&YZ
+$VsFFFlUHrVv*btHHiy!arS`s!~P@S=E))gF1&*WP5ni(<uU2D~I*f1QC=h738>*Vhn$6zWQT0vXhm{
+Bk5vSH8h)LIQQ=Zy506P)j({r>j=*f`Ihtsy7tkXUChbF`zq7I}!}no9gp0G1wbL*7R)!cxk-Na|}7t
+U;D2k&vJ<`Epl)4Vt&^ttNJi6>E#A1L~#SxfklNVZqSe@ZqSe@ZqSe@ZqSe@ZqSe@ZqSe@ZqSe@ZqSe
+{ZqS%4ZqS%4ZqS&xz1m>n0&9bbJFE>RuCdk_(zJo$3KF$}VGB~Vf#D01wV~k)(zT)C3lg@W;R{l>q2U
+XXwxQt*(zc=D3lg`X<qJY1mM>m@q2&v<*p@G-DYtw<S-Itlm*1<rv54FB`N1?^*dP3aNaiSL8k<!ojZ
+Odew7QT2pkGxHfc<vgI!1J-6-Ns3;|@l2j~Yjc@#8K=bcYj1s^Z5zjOd0oj#R^s*E6E~zBp2fA8%wtH
+=J>#27bJm5#0#Jkx-kyua6O3^_*5Kg3sF+v3#xwKJQ?}^0^}Tyo(Xb=ZfI-9!4ymD}vAa7_oe=2tFTR
+#PYc!_}tHk<#R>w`7k4v&sD+aql{QSR|TJsGh+E%6?{I)h~;xt@cA?&md{ne=d+AhK34^w&og5ATors
+CV8rqnF`aMsvneq5xj7P8x1UXcxzEj!z`Ffx3e0_Ojs({2XH#JAb8{rHZa<p>bDx_dfpz=Y6qx(m90{
+!3&!&Lyb0hC<iSI~q?}F~{XB%TKic70?Awae<=At-95&~o!V=jtwBq2byG3KH;M-l>L8)Ghtb0i@^wl
+SuMmm>)QvW+p9ia3%N;N1-j_+|U<CI<91J88Al`-C*HYjlF5gl`WXXT<O_K?TCM2Tw9$c$uK$;M;?z8
+8N&}P-O7!!Ly7QUM46i`1as=Mhq_#)DC=maDWkGM-o&Ce0%T`BSvSFNU(005zD$ru<j}&mUWR}-E~GR
+>mtFr5k@TQBEh;bMl9<h!MX`XEbAh{x|@tx)(O|Ge;p%cx+lVQ>+fL1@>#fU{auV$J`2~azlRaaXW_c
+_uV=*aS-5Wf8yT^D7Oq?WW=1TZh3nSe$B5;#aNVf?t3xcGh3nS8gAvPT;kxzjV#M-UxNiM>7_od7u3P
+^;Ml7F&>(+mO5zA-cy7l)nV)-mwxBkP7SUwBat^X(^me0a<>t~Z|UAIKIZvAX>t?QNu*R7vTu65lK;k
+xy+$+fOqB3!qAHo4YyON8sz&nDNpZizT1+s`JqYWbYBwfeESpxBY>`0*$s`o?8P%J5@fRY4BY65pldU
+a9ZVb0nN5zRI>d5o}`fYR;*qiExJxv3a%ba3b8{Lu_8HJDdo2_z;^{>kcQv9X`b7)w;t8@{ivh+Qf+E
+6Ecstc~aDjACw5!@(|lV>sltlwLHW&(7Kk1@D>lTS+m|^BD}>zY}Tx|m<Vt25SumYEhg|5zdgie&9s1
+ZB<Rs0Hf!cu;WSAF>)5QBYlR(2u#U}|xmMVbgdVX3&9%agB>2o`&0H(&NP^F7*37lSj^z1#`xFCS8*d
++Ez%%={;s{jo0t2{({Tu_9;mF~Ae24)b|NNL|5^{JSv+R+=`*wgeITO5RSJYfJ>_~$5?24MJh8;=pp3
+RrJYS@v4j<YLjt{QeEq2ug|nyZE#N$5D+N^{k4njlB_?P0c+=Bi;wf{q_%TWM|tb|k^)os9VC^2hBAp
+a;gaEsP|1b1x&h?}{T~<vYBA5xep&<mGsum<yh;$uzh3I+9LUI+A5Zt~<^-lGQe(!@fPt7S-I>>qyYH
+!)#H_eZ7vPZ}UtO<PBbAx}Q0(Fx|`ZS4^*99M>4BnsFcr@IIR|WB@+k=~^0*)j|_kubC@q9m#xhEw;Z
+(Oqif%E<;Ug4QdZhe$f(N@#EfQ*6^B@Ud`O=n${~u$LiKsuP26ib^F2fhQ1@#k?h~H<ErOo^z~AAcS}
+<niAf`q2T85C(%6hEt=L~x%(&8u@uJcNo5jB}msh80X~vbA8vq<>kzbivn6(*BWP$x#f&E*d`Nk|<<X
+6TNW}$tfohq5w8FH*DLmBb67p^mcb^Sa8K1cTLz;;5a_RXlR{dhA2X4+>}lLN~{v*RsC7(qj)Ek_waL
+#Hjr7(qj)Eyo!_L#Hh#7(qj)EhiblVz%WJBWUQfh1o5d9d9|q2pT$VIm-wdI&C?}2pT$VVHt^L$6GEi
+f-TsV0Y=dCcFRRZ(Cl~%ZA&xJ?0Cy%MudC@84>asVnoPim=PhLD~t&FTxCSa=NcnIKCJYjC-IgWj0pL
+RFe2nL%7~E97$ZVH<BSOTOfVwkGs%dM4>^PxHiuJvYZ-xj`qnW5`Si6j0{QfHFar7Xbut3^^mQ=;`Sf
+)&0{QgyFar6|9mo!WeEQZi0{Qf9U<C5%+sFvy)3=Ec$fu7j8n&KOeOnlTeEKM+nWaKLTNx4Z*~W;F58
+K~V$Y%#5LOweg5%Sr^h>*{2MudF!Fe2o$mk}YKeT)eCEPBm%w8WR-xK|3nAK<|V!5?Hq2)>^YA^1a#2
+*Fb{BFlu}d11?h;CW%ogy4B$%Y@*0VatTzd11?h;CW%ogy4B$%Y@*0VatTzd11?h;CW%ogy4B$%Y=M*
+VatSkcwx(ge0X8YgnW2m%Y=M*VQW}drZBE)W}1pSl5tHN#u?6^#)p1Fq|E-xln&)jceDJfQoBuM9qlI
+O274JnqqqZC7{N`Dbfcj|a1-RP`fIr2m~JC;h-gGM#0ahkC%tnBZc3wjy&QseV<**na35NaLU25XuGD
+r2E&@NPz6b64daf~oi*l(D#38sSce0BRbat5Ady^5|_jqWO5lG?q4MuPuT6-TOkiwaEMsN}Ml>?06qT
+G&sjG$c~Su=;=KF+NZjNraHy8Ol=kk9EsMsRV!s2Vlov-v6`kk5rqMj)SF^`*FvbMF8l=zK7LgTEBr4
+rZ=yWd!XMZ=Poavt-X^MsQ#1$rFq~J{#9Ff_92Mdl|ufsYebof_8ms2BVF^?7=;ZpxxzFmK<6aG&hbj
+f_943F2Nya*EiYC2-+!jUuOjE`Zlr@(2Zbr2TL2R2xiakU<4OU_p;>Bd!TvXG$W7?-Jk3b+-JL&zXv4
+@bNkp<p{c;!^-GN4zQ==X6VXdxen35g`E#8u1^Ndxk8NTE?G#V4-9gWQ=Cvb?pq*kLYa*Hi%x_{Tpvr
+-7!*mGj+xgv$pxxzh)?V}jm>E~^!A0PMJZdxmm|N$!MACJPm-r4G_evPf^~ZQHFr3GE`k}O9ZkSCS8V
+AfD;Aw#hi<#qW0MIF5W>Ad)hfdG%v_N-&+3Wim!Ew`ZURKZ!pm~Lr5@i?78$4>X0GOweUWY*N8@Dq8!
+`ZH$K_A*4o@6-ZKhwj?k6Mi88TAb0b8V6l$fu7NDV*q^-^WW4Dl_ITu4Tl_XLciVv?AogdVnz8+<7%N
+FQ0F2j4%Sjd5H}g$~9)!GOuxxzqy5-B2;ZOcU@)#6LS+U9w^>u9v@=_?%yPv2GnrOOtK?|<NM#--~|+
+=9J9kLZG;zRcd@&KijL+Lo+UW8KSNOrhrsbT%1aTB>^Bec5`p@TxovDXaa@1y951biYR+C{qmHO1UlH
+yQI37dnv?8iGyODJVQO&uH>}n&bIlF~TDx#XrUFsRgXY?W?a6GzLrig0J^e}f2)to)X97R;KIm~*EsO
+H>ywn&MXKdkYHYR>oYY)pjX!E+l?&6#aHPZ8DR9@7qieH**L2;{SeHwcJo&fa9nA*$It!McN}=KOAUX
+A#w$KdYXB<1xxJ7*WmnF?Qt;)tuSD4mF~hvj^BI5`EAIcwInLb8doXBchr!BfKF+RCBhQT{+PQy_apT
+=!3qU*E!J#ef&5ha16UxM-kO*ZdVB8bDGzBL^Ye&`Fjx6oLk4*i>T(@_$fxbeCBrWoI_M|ey#c*Tm-&
+ZjScp#m-RsOLEoVM8sxK`H+_g|HaplNA*wldoaYasn%X9cKImi2YeY3?Zt^@uRC9JSuRn-t&R%4`A*$
+KD%ySM=&8FIRBC7e#7;oT2AM^u$btVUNiEpTJuf)Vu%f4u^evOwEL^WsEvQvbpW^)VgNf6a+ZeydKii
+ihKGDJ1!*0E_oRCB(Urv;*#^9MNQf~e+vKPwobn)654InIRR!OkS2n$1(J5{PQfcdN0%aPDXK0#VIb>
+a6P!T$MPgcmVlyD86B0UQ%Pj#JtRo6r!55yE%e`sHS!^Q4G}VVRMfI`^|mo8APOZa2x>V_UG3r1oD|=
+R}Q5?v-?@5s12Im%RE4B(98xl4LH6(+s_67B|@`@d7*BIhzC0!IKe+V%CiJV_?uhR2rz$ku@rEKzj>4
++MGdjB;)M-`N%P79#W{Yy7{wu2*m{|7ILJT0kF^&k`DfPh*l?78<_dogYL{lOv+2fB{<(35z%f*_5l8
+xGyLh*cBmJ{Sc#*=He!Y3Yq5k>(Jm+w#f2NnM7*5~MY-Ps~XYXeQ*#*YQ``Nv`!N$S+*?yi`ICnpL><
+lAt42RWw;CO81@4=z_<{oyWaOS=_!5c*!xt}}EUy2j=bH~|=;lTa8+F;|j{rmwn0@$}rY^!k8es+{sC
+LFY%+1k$t=1&jL5*)H`ZfEO{BldH9_&qpaKfj+H9F)n;53;_YP;P#dV^t`Xn?0nSfqlEq8efWtF6#jf
+)i=+pXS{rx7kHb7a=PXaZ+LK=zPXW|V;rV$w)5P^QTn+7#Zg3b$JAfL#&;91+c-o&(@RoFk(Zk3?O_D
+=ZS)i)m_HkLFapPYcsC=kZx_255gCy~jKIF_zru*HZ)1#L{v6%JhzJ~QW(0wwQyUq<{25bU3jcs^8+Q
+oi&mNDE1G>aF*SJ^e3cxZ&rfcTtenxcpn<GJ>`<T&zuB&w<5$I!ii44}JbBtg<9oWDK=F^FBMlhdFs`
+p?%ojl11=F_P@Mz9|Bvt}ZL)f}2+1om!nf)QPqS*D>#EpBJTG8{Rpx$`#|u?$B_YJRQyF&wlG9-uk!>
+PT26j$dK~+tcGL1CducafT7kwfSqTGRP~<cd*=$SDN2X!H5)jrEexLG6E~qahefqPrG<NBd;{WIlL5k
+r5U>I&>_(3&D$73cyxC^Bk+Pb7nLHfG_#NShP=|uQMMb%E6p5J&xrJb8a1rYpyC_S3++1@!7imsy+?$
+1$YV;8SDNh^Vgz2+E}n77E6uWBlp?P*yPtWDywdD3UL}xMn!U=pBd(;q!Ilo`pV@IW0$80c<{Q#K&EE
+5j!0K#Oe@*25)c0VQa)NCO(m&0UtfNT(G`SWc73rUo<bS0i{d1D78`3{~)t^I<UO2_`2kD>YDb@p|f0
+}1mdy)QWo?FKVR)tII8LSE%m`joVY2IM&ApO%EQSX6#CRj(2{+V0LT7~q_T+aX_2#?aWiVi^%VH<gxD
+Uv*MCs;m6^30uL`5?(NcY(hLNuIe2JOU(n=7!lTL6T?g3hNG%Jad!R7(uK>EiXv&%+n=+4uLOq_$DJ*
+Wsb0Ch9uAIx~q(MDg5QcMxKty^33(_WklD0l_`=q-`rr26-k_#Zhm(nRuQ&_NaB1m$$E<<&P*5U6OuS
+H-Rc>vA{*JyMiOUcBm3qeiG!7gJjo@#+r_;S%hRr1JQyrb9NbDp*JWks6Op}R(=7Te9~))_L4cE;j9?
+RUl9x1*9XiV+5ZR#%EMA!%Vt-BCk~_v<itNzL#92ll_(?V-$PUeRum&SLG~2~y7TKZMPM*fd4(TOY+>
++aMgb_?UwRnr{5Ql(MaZ7F=O99!T*{uf|f%~wHIV!S4yV(4R?2y`d$XjyR%pyB9d+-1wa37SDkL=Lw0
+2@<ehg9Y_MRrJqB~xUFX2;YBAfGYbN+LU?oe^Y*nrqo%Ms`TMDaZ~r53yTZ7iD*B>O^*E18)G39nu>&
+WQUsD1{s0-u#=r%WQUqNc?m#vsJWM&5oCv&dk-@L_d#tPMRw=_O99!TCYRKv$PP98)n9}A(9fnDNu1_
+!4k?IRa?dI5Kt9Up5lNgu#U04!Dt`}>INDJ{5~n%N4knT~+UY?OXKpjkQzUWb`dCAd#F^{o`GX|R+)1
+7#NaD<$VhuqON4rBv;>?|6#{x+ly=6ucXO4q)DUvwaxyo8q_oPVT%$;XTjwFtD$dJUDyU1FFB#w5-L=
+tD5zegr<*j|eyPB*ViNaD<|XZKDdarW`%9!VVS-XV#jgCz~&__2;6iKAUYByr}CuzZlj(as{0IP(`+N
+0G!)CFv=WIDa{Il*NE7j)QnTLmKBV$NSjj5jWaiWOIc)&Npj$QAZx<o3*SY$m9Iw<a*xJAd&Nzlf%4o
+Kqluer&S0Nshs(V4n`oQN%j)V@!>K<1o)L#81S5VWyPZ2=MrD+;oj&O{>n-o3J%C)EKiXbh<e8J`|UL
+h=rbH;hD!d=u6%Zlp;$mC8L9~AJVRchpH1pNn24ta7}6)>9m!9GFZO+Yg&`C5%}`nY#n9&zCdm+={Nf
+k`Ud&%?Wxz}0iyaJjZhf(n0ne*14lv+3^~FI3JfFVkXTWpmi!%&(t^eX215cDbdIJ1C)4gH(;_Mge7|
+I0H&QJr;=i~ahoIv$t0e)&3lma57pCJP3pmByEpluq0h_-78LfWArh-s&WAgEm$f~a<D$j&H4K)=|lf
+9<W4Q)vZ3R{J#sSsl<2WOYzOy7hu1K|Y7{ul3RWGDGC^izDjS2z`EWR71K$i6cQC$Mvrvj}scI*gph0
+oYKF>q&cl2$m5KLAdj;ef;`S?2=dtV`3OUh$F|RJGL#D`DyR@#P>`56%77s9`EZZ{KQ$hXG2r?4aFPN
+4v0traz>n-9?GQ5r?;i4i5p8?OtU-9}s}l_PcYH;mE73dQt4;>|JHF~*0PpB#0Pmm>lsNzY)n*2~W`4
+Da0la(*176R*>SX|<+RK2~man!kfZ<ZGMI49!>JkGO)i48iIco`a%U`i*u_gYB)dzdnuUSj5QT>`%3+
+ybvVuiz2@N4pM#Zlz1dF5T$)bWyUTB?*8ywk7PzkoCOH7fud#;;jrP~h`5ixX8mU-vv@zXWAGUwe0-{
+Kh4|wxi5Y1oSm+bu(1@e7&9lNRgc$)ZaW*Pk1SQdFsp43^f3Ky^Em&&_m`RDr4MJEDjXFIEV#;Iu{42
+KUftIe-&y|+%WjNP-yZsP4PyX7~hu{7zzY5z>paF!!CxRR)c7?iLZLNfg$gae0fF>qbeXZj6^^e8L9!
+&BdiNZjW89E8lj&fU!Kz=YzRn=Fc**-A(ZBv9$_gU9w90|9K<8U;pQ*Ts}Z8~<ID5vUDy;kNWCi-ka`
+#7bwPbHHbq}v(C>o02J{FauL1oO<aJR$l?q4=1M<44{~+Wwtp8vxAoT|e0kJ5tA^UPzy$c(%FR!XUh%
+MQdSM^hn*EKalY|9*^{$MO19wD}7UtZJig1oNlKL~kU*H1xSH#7u!jp)HcUL*P`$ZJ$T1$m9?r@Xu#u
+G3Ey0#e^q3Wynn9ooZn>Rs5OIf!Qpc4!XbnSveK!*(?c?9d*z>vvTIq~28(kb0Mw*TW88y&Bl5IfxmB
+otlHx2vY$mMrD8=b~4lukovA%K<c{+0jckTygJq3v2$|}4<0)=2l3!hweql2jSxFH2k{88gL4p%5QQr
+byYvXF0#YMP1f)g?d3EU#)&-<Sm<mXZ5c2BQBWwsrjW8FG8X@G>tw&f2h({=Pa@}f#C}MfoqedvUc|G
+b~C}VMudRHtU^)AS3gML?4K%N`q+Ai^(Chnbycqg+NMKTXJ=ufW;NPT)LAob}mw3i=VW(bCMP(x6J^%
+{Dj2n!*(We+z!+{Rc5Y_q}^3Tgg|ZP8c&tWRShu&o-4fNfLbtP1z@%Rz=J0vcjS_}hyAsHt&KH$yc6v
+1qE&OJ~tkh5M;Tm<dRY5K_~wE(&WLq()c>NR6-*5RWhs?xz|ds&5>`BSdt=xVosnaS)FX1vthFMg@-X
+f)OxrUa%TrA|N$F$V)rOD3)=M8eu9RHNs3lYJ@Pi+K)(tJENb1xz!#4N@k2lfSMWO5uj+sEZ~R~nFSn
+WGiCut7|AT)D4a3tEn-Y&y+!GaS#N7%dDPz}mq+z3SjBFo8#TE+vToGG@~HoySRR#b)a3H0zDq8T{9U
+M_F=iG;G;WRH!6Q`WARau*Xw33~IvNM@;Ok;}RD-XJ<xvk_*h96b)`dM(E=FD0L$&tRMKneaJ`+$6L&
+6^FVF-Juhav2t9)`4sJPZU79mK;(r9I?fq{1GmVWh$ys$rzk9;#tTd#HvX?4f=N^3t1l)Yh0yJc?_~C
+LS?Rvx!f|c3eLNdFh>cD!1e6DY+e2gBROz#Y4ng%}zZN+i~>=QDx&G^#>s@y@}7{cAN*FiS4+4S5-jj
+U67aF#G}^6Y~oRDV|MD9*p6d_<mxW*?KJM4Py`(U$izNhGYpELLjalF=c}jWKA*YL5c_<^=7!wo^Se;
+aV>a^*vCr2}iG@*(5EVUU?~Rfkv-fU@eZE?{8)BcYhk=Dr@1jxGV|LM~>oL1%6!w@^9hE%}VuOUz9<x
+<OZI9V1qqfIvl~LPc7JSt9m`yLzCuY-&>K?P{MR||$1yJ7OApT@zWX#SM<vnI+i*${H*cZsf_D=u7Oh
+D?p8Uj+^1$k*V0f`<5sqccJ)$4O1@(SuH9N9L@DKa@`IW6QyK|LiGM)ed7tzP{KxiG4yU}*I!fy|ME)
+Kf6DSM*b<fYej1<7h?eI9eg+mx5ZyWeVwd@-UF6G73-%$5TIr`L)*U;c<-HfqD~<43`7-E*^)uzr3#8
+Pm%t*uG~)?=XNWLda5QM^%SHws-H>)q@KbmHmsi#*#-R+R<SGksX{>NDa^6~ekvE)y8(VG7umZD`l(P
+r>M6{!i~6ZpK<X*T>#BaLDj@ZgbZ694H36xo#4Kaemy7J(6*hgj$lhIH)0d0votn0}$lhJyEmz(q-A@
+HUURM<)vUk@s1bHc)&qel5>3lA-cO&|#`1>t%J{Q@$QT<f)`z>@n52RI8Pf4q&o|0BkJteK8dJ6K=Ix
+n(!TIWUfPV2nL-U*#2S9ggo9CGi3BIwB^(t>(2QCd(vCH5iuDUlY`Pl<hqehP}9CzD7E>d7S1f_gHEw
+4k0$p`5s^`ywr<CzD7E>d7S1f_gHAdF$^gT7OsB^1F~0G~b1^p!NuIqy_b|pCc`(Q>!`Bf_l@NBQ2;m
+y*bi?defUnNlR`-wU*q7>aDqvwjMm>bwfjt*Xf5F88SuAc|}H=RSY7p$k>XCLgW=0LK)Cc3SUu&8}f<
+_qjc#%TP2X0g#^w5$n2_6FhxH}F%vaED;a@2uPd^Q!7za$C;FXo@zR#ELd6W~$!b6#zY~R$Pe8?6k$t
+)9Myvj;^b*XIQhl{NtK<$S_EqHqqoq=%bzlEkaOj#@fkb}fn$e*|uH%}03C()_WK1A`ipY43nCT#L9w
+YY8)(GTJNu>8{o=gc;1Ih?ge^#V8EQe$!!*EFEGW39Il<e1FKp>A+WHdUBJVj2U)6ErDYMHt)pF$Z5{
+V6gLVdkeuMReIu$p}=R(h#7Y*&-p)Wz?i5BQF>AfMo1Nf9FD4;wMZBX&5}W>M|*>%|u<M<+X@K=Aqm0
+MdTj3jTDi6coOT;Pu2-kPl~jV(ervnpn6h7RP3ivMnV5sQQ~LpR?2H1zmxI``p;5kK|7r(g;4a9lwHt
+IigG{uq$v24QX%JhiLa7!Z%t@OYP@1UV%Y$jch$_Ul=hGsgw4BVK@knL5~X;J21SI;{@GH1`p;$*wb3
+BOMKvfQ*%qYOs0OKOP1&DJT1!2BGhU|DpOrCf1J=ZVw9U(;oz)W}OGzqfKpDMLfsN-qnLlqpVy|i0C!
+#q<o(&o0HX!9CG$<mc=ADh`Ip5h3aRT$54H?-nPtuk{zmv_e0?iS~+}wg&=DA&UL^=J{hn;+&A{T+mb
+_;?*r`;S>S&1CMN(Xo7@|#?QD;JjQFE24H+0>~MTe%2Y4m#Jkm*c!S1ui>vkTpl}@?o!gx>Nu0x_q~?
+bqgWP2;j13AHVF`tClVPM>GH2g@>KXp8U_klWJt5UhL~lPkz9#zCyh$76O+4LZrZ#fqkFpUYgT<J5Uj
+rb9Y7H>%M-(^!OS5ADLcxM*kb8SD(@Undu1zvzw6`kUfml%`nY%!(|Z}B`*+Bc)WHeBO#C-jCcn8oaz
+2UUtqfb(C;xlc}D+VOs_qo|8J((@%d`3DUe-^WI(nu(g3oJksQbdMhYMs87YC#A({eJ!_#ZmGa|HZ6C
+>youy!*e5s)p6#6bEO(U;Ual4t!-neJKtGp75a(98bN#Yn!mGE`bjwMxsWR<Tp9(qc+gyr%IKthAU?7
+5}+B1raUL+F$V>%(`6hMvis4;*A*V@<QNb5nZkb9rJINUTkHlZ?!5aLV0<TpmO%_h>oh+|HO1(G5epH
+?yF`0p6Om`f53Dv-v7dMFW!G*x)<+{nQl&t7gevw|MqVTc)|V$rhCEuN2Yth{#T}(8##+a6dAL1K%nN
+~S`CQ`V>SYbY1~>QF@DT;Au-3gi=>Jlv#CIF>XTF|Lp40aRs`XjCn;8jQar>)7Ll7LsaJ*?c!=$<s7z
+g}AyNOmosm*J#1KL`Umj%u+uLIdz(YIE0GzKA48X5C$$%(1WB^gq(+r3bKmriy`0^|RB9_d6s3&GXWU
+mMiJN^L%@Q#ZN;2oD35XJut;N^o1;LEA9v=H@j!wiU|5(C0hWdJXyE-FPs1XCHnJ8m!_4xcd~D#!>B<
+wLyoiCUj_2E>6W2E;C(fI@7=84%$v21M}>19%7fG@`hJT^d=x!GPSX^JFVUU{g)EQkIeNyeeg_7*C+m
+wCE@n>KbS-P_`LoxNP(5+TSqU+vvY#x_5;Cj_KY^{|Bb~b?rYg-COGa#B}er{M&aK@K*W-ru)V1drbE
+R`ad(>FK&O&bZ?u#&vdU4KVZ6dEq=&!?^yf;(NUYw#&oYf0n@!d95UTo#E9wM7mk_kwXni;ziF;A-K%
+E8bniFTnC|tp&UDXz@2`@tx6~I%m4O%RKk`7lVE+r#y%+yuru+5wpP23iOOAFKdKc)wGTjSyIn%vhf5
+CJw*cX}Z1^W`yy<lHvx)<y#O!tC)mFZrvuQA;Vb_LV@#`Bj<_txokru$9jN~ZgXwTkI}Vy$MnH^6TY9
+kl~*GTrn4S4{W(e~am!|8Fzh^M4J~J^$Zfy66A9O!xf%HPb!+f5UXo|KBp*^Z$2D_xk@+rhEP8Z9y6N
+3Gg$f`w8&>GTl!A+V+;Qp8)@p=`AKe++qU6Eha$RVgkf1CP3U`0>mvQK-^*i#4RR3++qU6Eha$RVgkf
+1CP3U`0>mvQK&8b5sI-^>l@=4A(qaNsT1<dSiwRI^F##$qCP1ad1gNx_0F@RKphY~QL_FgEW4hP>|IK
+u-|NlSJJ^vq{A~&-{&-%yQq_spr2YU%s5$)Q<h=_J=W<*50)-mEGG2Jo7NEOHsBM7;+A7um~*Y@L#AR
+5_zk`Y8B+fOrsXk`0YMi7ncQ13ycs6)L60i6!@9z-KMXxmWYQ0;WbI3ozmwI5>y@@YT82;|d#iV?`C{
+R|_JPy0DWAfNX0j0pJ*Fe2o0i4h^6K}Ljph8Yp^xylIS(|(;1$ftdT5y+?AYa;o5OMP!si73c)JKf(?
+A_y|wev=UhzJsR{Dp{sGIvIiBJ9v`gWbQQI7+coF#N5D$n3x+Gf#5sXG~iV3bO)OTL|mpjwlD(0cl0p
+=!FOzDL`=+GjEIT3mk}{B4=^GoCUs^n>tbRaW<<#62qQv1Y_{q`K0KN0LOwj1>q0&}nd?G6Jeli4K5W
+qHLOwjr>q0&}&Fexw7Z?%pVFOSX@?ir|7xLk0UKbN{A0uM^(ESo+YQqJHl}&Z7Wh4Z`Qwnu4Q{BuK6v
+a$+wlh+}Gt3s0!%THETTrqx)yXRW>Q$yXc~T>iH`U2&Ix1DBx-T=50bwhP8kMPTUTqQoo9br4pgLuWZ
+|N-&8l2+$R!Y>ROm(uzG9e!}QkjrX4<nEdUzAa1LOwj%5QLoST+ayP)5#_;6Y^n`mkIf>$;*U%*yN$|
+WU7-*9?DLpI@#o*=47gKD<hCk=Qc(lpH4QDnQ3%eqD*9}iy4L*k*O}WPACwW>S8wtQP`<2wp%C-nd)K
+(33VY;U2M^8QAmk%sZ(9-P2pJT6yNAm;#BHX7n?tXfTy~6p5sjFR2Q2+97&z(;(2bXQ_5U$m#2O%xO<
+Ti!CkhMx!^8O@LX`0CwMNn%M(1e+|31ddCup8yFBM}!Cjv7xry+WI0X88Rw=~8f6p3)1E9ZWZWn0m^9
+Qz&IQ{v1)~El|+L!Fsv1HfI{S_B@6BV9OIN3yG<^$d!&&f={f8fa*l&i`vH|6SXxm-0;OHsWjN>ndVq
+DYGBC5q}B;MstmWI$J{n&^5c@*E!3h@ar3cyFx8wPOz+K;YhiVg*k|#9lj^wIg>zTmQdZ3gXSrPqgE&
+MbNUr3!k4(c9#H1^q(f2vv#(U+x_9D2Jex6n&{2~c#ZVaM0XazTcn>Rrn`vqhfg!zO$^>4{dBrJ6V^P
+ZM7>^*Z?$ZeaVU1PjPC=rWigNVW?3%leG!kS-WTDB>+uJ}Hp}>GSzDF{>X|@4OrTyKsMpB$MS*dNdYs
+62vy4CE*_M3~^{8GFsFzE7L`C4a1$$>(RtD;Q**{UeDp0SH;}QqPB@R3{4m>xm<a6UXP_L1^N&@4Y#B
+%(SSn@APrQMPM50WfUFVNqlkmHgRl7Gn{(7u7>eez|h@77E4*6+sg<JSp`JZy=u*u!oRmU!4r!cq^rM
+VRrh+k{yUyF*y!VRs43J?tJ~g@@fItn{!4g!MganXrL}JtVC1uoc2;4|_yd<6)1xSmfL931Pndo)YHU
+?-^mf{hkx%+wTQozWrVj=G*TTVZQxd6Xw}(YA0cy{ib#i=Gkv*H({RrruGo#*>7quVV?b__7UdUZ)$=
+t&wf+;yIAbmZ)%b-&wf(}2=nYWb&xR6ep81C^XxZum@v<NQ%4B%>^F6kFwcHd#|V@2P#T!m(!e~Pmi+
+0Vwyf`s*Yp{}yz!boOPDua)8`2D#%uaKVcvL6Um(mIuj%0DHqADF@M!a)o*||$QG+}~OkXC<bEN56!a
+PTszCxJiNYhsd^Bie<jxf)Wrmqp^InwkzVV)yRFA(NA()3~%8~DVag>2vxgBG%ZPYhbf20k%pAshI_p
+oMJU6N47Afp0%r$OgXsXdxT;_M?St;M<QDvVm_uTF3^z{b(T@`1YfPY~b6E7P5hFKU&BJzWrz+t9<*>
+LRR_qqlK*U?MDk)<=c-IvPy26(kd`n1vZH$ut_vApNZSDBv8-F=Nc<Fbtd!1W9Bqr-gwNMA<P?(nX`m
+><1urNFptkO=Lz%pJad6CkI$X2-EU$ZpJy%+=J9#vGGQK{XJ!fW_&jrkFuAcdnaAUqIl??1&s-zS<MG
+TqVIGfXx^tAteY-6Z=G*N$VZPm#2=ncBgD~H2Hwp9Yc8f6IZnp{Z?RJMS-)?sa^X+zzFyC(X2@BXQ_w
+BY!m~Xd-g!y(`A<Va1cWyF;Z@0&U`F49km~XeIgvkTCDSUf9C(O6k3&P~#%@pzwZ%Tg4VzZ2Inzv>BK
+)rsbp4^0)FY7+nlZSH~m?tyw<+rvh4b(HTznKlxvvS_e0*C1gzW1NU32_$u&nZHj-~HPHA<l|#&l2Kn
+_-2}rK#$;QZ|4Yce)i|v?%|!i<u-p5Y4e%Rf8WkiYn=DKy+(-JL%f+G#Ch<W(}X}gf5b!X-1p5HLY(u
+y=`JN1T=(q~A<pP;sM&DaH&+R9Mt?I)2#kK75NGs%UnIm$vu`gD;!OXB|HhgA?OsA)pc{n1KsO12fo>
+6kDfZ$Eev&iMpD!IH2qwBiNaOur_kf%s55ZgdJ%m}?znUP-nd#r25CStjBE*^L&0|8GnSMopv(lSqgk
+)ahCJA$Pdh?PHXQwx>2!Wk;65{Oi_BtWXPH$-%LZtQ2w~0guwZ3J<S?Mix2#4!W_wN%VHPsAf>bJ)Ta
+mIOjg%J1<`5jKvZ^`p<<oypCGaPvTV;3RLHvh4k5NuK|zBou&>0va>^yMZc4=iwbPfqiBPaZ7t9>3DN
+Sysw=N#OSa>V2LBelHN!$i)XvH_PM!Bo8dWxd}YCkWquY4Akp$jI%8ZsPcIuH%<AMSLV51pnZ+pm=uv
+bz!j0~Z;{B2P7xTFB9;9p0vnE^FE=JdU)rM(vER)y{%T{?D|_<bSoZkM-_0_)!76+5xn&giy(sW|;uF
+)GWreI4;Axpi-j{*sTNxPVGL?KT1JRVy1nLDgilw;V)0Pc7^*Xz&ZT>D#`!Ep@-Yk=ZEgM;{ADC$Rfd
+Sw8QZm&GIC9@e!}K%hc>OF;uaGB)ei3+XAY9ik1N8zE!ywS#L4Xhg|FpfllQ8epw!Dil@6@)un=tRRy
+}XAo@AS63moV@2w!Dup@3g%<L6~>iUfxfbciLW_B+NT)FCQSxJ8dr?B+OI&mJbo;ow}C~6Xu<|myZzU
+ow}Eg66T${m%AH<fq&{=K2Df#zbV3e`<)=nx8F2jzWq)T=G*TSVZQxl2=ncCnlRsfX9)A{ca|{Ue&-1
+D?RTCq-+mVe^X+$$FyDTc2=ndNRq6(%Z@*c>eEVG?%(vfF!hHM95$4<P8ezWu<_Yudw?LS0zeU1)`&}
+o@x8D+BzWr_x=G*TkVZQxt5$4<PHetT~?hxkNudCP%{BYXxJ;HqZ-6zbq-vh$rIx-jp=JUWtZ!1lDw_
+X)c)~kTBUIjLAbzmc~l}Ui=1vYSXApE%X&O6tW;mo=p_`QJQR*SSoQLhQ~w+Zxj>(wBtmj&wOfqH@VZ
+C!SxdVvjkBljm!;M!IcxE8e;CXw|ru|H|c#D=ilD2V+;Th>YT+u6Wv^VeqDhlvlTw`KA^Q)^YRQE5jl
+P_Ge&i30b$qA20qADd-X)=LF(qDbzTqbQRGjHClZQ7txRZCNDiHL`tipdYcwwY6C$B<Cnj1N8#!i*wn
+JI2Rk%woKY1&c#I2mPx|Kxg=sN?=Q4vfqHTRiDKz^QCy1?Q4|OG5(oGaxUbfhiIZJhCQf#3nRKY6C;O
+2^Li=gUq}`HOj&l;raZZxJ?<I0#NaVf6wk*&OIq|n;Vxo?cRPr=Qg;LR$1^SVOeoyisaNn;j3-nhiDQ
+%hb-^7RoqILbixL7$KBsO4Qxj?jKa$M2?uTmoxh_+0&FSXKt(}4e`;*x$_7MM@dO4`>1e$VvfLSp)IJ
+}{NETOd>w*#KW`z`j;4#F3R7kG4$O!v^|cWymeEas$<t$$D9!A6X>lmn@QY%VKHYOl~})ES2+aKnabu
+)JLl49T=wOb`lnO*e=3i58F*x;$eFTOFe8aVaCJu5oSHi9oRb?jBWnL$L2#b@1gstLAi%b5>|NF0m4c
+TJ4jgH!wwNP@UX*#RUUSPu-e0p64rRwu`bs4iE*4TpBPhw`NTLum`{vp!hB+!B+MtqDZ+eW%n;_=?=)
+e){mu~P+wUx4zWvS-=G*T)VZQw?5a!$OB4NJ$E)nM2?{XIlOi%$Szb%s+j6zD*ZJAIC+cG)f6;j%c3M
+p;3Wpd+CM1ki<a=|F1(%P2E1-y_Un6^xA9E!jMS_BrBBCxO&@}g{8CKuA8lpC)?ytlPk7N}Rtg|7@u@
+MYk@5s>JkvXne10~_J8k>eLozS}Z6E&;{3Et9`DkRi5cAn&BKWs(PjRPtaD=<gt~&<_F|uYvd!!e*J=
+2oD1G9Y`fT+WM$#w_X((mnz_Il?+ivRbZUAzJ5ma0^_%(#&A8k5vgQ|GOFZ@S8bV`H>v>ts(?MJfFD(
+X4cgYHW4NC5^Q{lXaJ@i(<qK6&C10qDDj89Uwmy5o^#acg%m-EA;8{y0C#nPf)^z#O+3;-hcNf}+1x}
+V*x!}4DZ34t;#CM)Hg$UX4fYcQ=@-{=%1QxKSk%npH0v0EQcy1gxLB**Rgosl)F|=i30*(VGsMw@pp^
+F<yu(**6aT1X1l2jxRZ_DK6y!Ie193>6(H??x1vw@R>E#<;#OZi+|8Zmx05bJHrggx3a!53SKx7yn>$
+%D2m@O$#4YRg(oT(*=-PFp6%&juDc+m{QD?aK+SEtBo*8!=JazC4+?Wn!YSTVY?Smx&Xj?aKwsdil^d
+W}eOx7J1ke!eS4*N?77ybA+WHc8xIOVe^Dp4_hEC^RPw2au2&sSm9wygq0q4gRs7b-6U+_VYdjYJnS}
+MwTImytnskBUCj9QyGNLBzx#yw_Ip5>Z@*>2eEU5l%(vePVZQwy5$4<PF=4*_o)G5S?<rxv{hkr#+wV
+DHzWrVh=G*TjVZQxd5$4<Pbr%cFhjk&=Pum3Mn?}CDY_~G;QN3Kw4~<mHtxT%ZmdTBXZRCN&Hi3CFup
+VcDbu7;s(Y`#e?&JgcMsyz7Fz1y#NR-q*f1_l#Iko@h!^A@0mWdN>TP7s8woFXi<<=&qQ?DNw$bJ-yj
+YB_@Qhi$%s3#Yywk%Xn^rI~khUrIETmo#%grWP9+)(uculn}`C&vE33J2&1PHt_PIN|jNa)Z_%$k0=N
+AUA0Jf!sj$x9)OKy)O>+S5zjrF$g&KU@O-w)syn>ppl!lK_hKBXk^-fD!`$tCpSA)Ak0}sGJQu|CQi9
+k<V}nh_nmJ4pC{bAg}(2M#F4=Ad%XSs4%LYQb?#D~I8f&v)ky+%?o*vKQ0D>F5k68y^1fbMCN_Ol<f(
+)gC!Wgj@RY)f6VC#8#eXly%To=%`;9=ICh$8nrruk;_#LhzLeNztL#S0C1YN~)LtVvk!(YYn?a(TaLZ
+pi2yj%rBvej0&kLt;Vx=J!JUsPU-jvo==NcuMfIA;Es07u845a2lYQv%!$>~9Hh+poVP!0o+$Mu6LR{
+XGG0*YytsxGmQ|65uHPPXstF|C|6v;(sQ<G4~e)IJ*9_3n1mjuLyAV_%#8}9={>L+2d;hoIQR^fV0QH
+5a8_bI|7_N{*?e{kKYsE?C}QzoIQw%$f!X~L^=&(B64XE6Ol-Rn20PI#6+afa7^s%#<n^6{^k>%p^4(
+i%0U!IN)Dnp@^KKwk&J^Vj!YaxairlOiX-VgQ5;$CiQ-6mPZUSqd!jfJ-xI}=`JO0_)b~Vj<i010Bl$
+g19NF)Q;z)l_6i5DhqBs)Z6UC7MpD2zL_(XB!z$c0$2|iIAS@4PCNP|z4Ek1uoOvKmkh>7_49WfE#z9
+S~$(|5!~C_ThP$UMYEXgtJ32t33@s5`_&NIS$t=sLtih&seXC_2PM$T`GBXgS102sy+=s5rz#NI1kq=
+r_bfh&RMUC^y7J$Tq}8Xg0(|2sXq-s5QhyBaZM@3W<hD2z`b~2yuo;2xW#y2w8?m2u+4a2tkHO2sMUC
+h!Y2q5JwFnA<h^?LL4lJgg8wQ32}rV65`xIBt(XMA|Vpw6A6(YpGb)G_(Vcv$0rgZIX;mPx$%jFNR3Y
+<L}q*<Arj*g36U3{rbA>?AtoY~3NaCRREUX4qC!kW1{Go=(x(s;kvoN$h{P$xL}X1NCL(1DF%kJvh>6
+IBPfSF{6k;OMr4SR5D}|VdL@C5XythS6#7kSmM7*&@OvLM2#6-NS<(Syn7jAQM{>>*kLledE`WI0g?|
+u=*@!}Uz9B+LQ#qr7)Q5^4k5ykPc7f~E<dJ)C(nio+V?|2c#@q!mo9B+3K#qnwvQ5^4e5ykOR7f~E<b
+P>hzIu}tK?{X2v@gf&d9B*+E#qkOkQ5^4Y5ykQH7ExTjNm-?MV~gflyskwglwy2a<_4Q+Ca>(YWo|f$
+NVqIXL@K51k>au<Q3W>@i7L3JNL0ZcMWRX>7%*H+B$nV-BC!Nl5{V_ak4P-RWkg~LZXyy(a1D`If;))
+B5?nwemf-dwO@z35NL0bSL!yejfn0gX{%ES|3vIpfGW^jj1)-2;DX4=)E=YnzE@btiSqdrrXqG}gKcZ
+eh%J!1@5$lk_k64HFeKbKKcOOv?iTj9p$l6ELL&`p)9`f}O^^mNOsE15_L_MVGBkEO}5?N_VWTh#Qm8
+L{ini5%QN@S%ek(H)IR+<u7X-Z_JDUp??L{^#-S!qgSr74k>rbO175?O0XWUVQYwWdVYni5%SN@T4mk
++r5o)|wJoYf5CTDUr2QB0HPDZBC=V`9w|PtTl<V)+EkalQ<hGaefDAN@Sxck&UKAHkuOIXi8+GDUpq)
+L^hfd*=R~+qbZS%rbITH64_`<WTPpOjiN-Fo}xsWo}xsWo}xsWo}xsWo}xsWo}xq=nR%!!Q$$G9Q$$G
+9Q$$G9Q$$G9lfgIBQ)EWdQ)EWdQ)EUHDKevp6q(UPip*#tMP@XSA~Tvu%33B;6h;#%3Zsb>h0#Qc!e}
+BzVKkAVFq%kF7)>NM!zNP1MH4CFqKOr8(Zq_lXktZNG_fKsnphDR4T2#*BS29YO{^%4CRP+i6Dta%i4
+}#>#EQabVntyzv7#`VSWy^FtSF2oQ4~g#C<>!V6ot_wio$3TMPW3FqA;37Q5a34D2ygi6h@OM3Zs#)`
+?h6@xM&hZTr`OyE}BFU7fmAWOjRaTbVZXYx}r%HUD2e9u4qz4S2Xhd)V55K6pg&q)0QdPph*>N(4>ks
+Xi`NRG^wHunpDvSjZw5gBj2NL%cLyW+3#(40{-@iir#39)EmD86j{(1MHVzhkp+!WWI<yTS<o0o7Boh
+Y1&vW;L1PqI&=^G)G)9pHja6hpV-;D@SVa~zR*?mbRb)Y96<N?&MHVzxkp+!aWI<yUS<qNT7Bp6o1&v
+i?L4)`RG0`g8ps|WJ=w+KHCL%sUOw1JJ&`UB;OhkNyn3yTLqL*8qn27iYF%j_*Vq&JKj$S@_Vq&JKj$
+TH2Vj|)r#KcUI9=$~J#Kc^Y9=#Ou#Kc^Y9=+u8#Kc^Y9=){j#Kc^Y9=(L|#Kc^Y9=%lY#6*NKh>5wPK
+YE$siHW%)LV7vkiHW%)LVDTZiHU_GLV9`OiHU_GLVB6uiHU`xM4CcTB2A$vk)}|TNK+_Eq$w07(iDmk
+X$nP&G=-u>nnF<`O`#}}rc{(jQz}ZNDHSEsl!_8*N=1n@rJ_WdQc)sJsVI@ARFp_lDoUg&6(!P?iV|r
+`MTs<}qC}cfQ6f#LD3PYGD3PYGD3PYGD3PYGD3PYGD3PYGD3PWwmB`NKaJw_;w@*|gPSaN;PSaN;PSa
+N;PSaN|TbjP2M4G;$M4G;$M4G;$M4Ex3M4Ex3M4Ex3M4Ex3M4Ex3M4Ex3M4Ex3M4Ex3M4Ex3M4Ex3M4
+Ex3M4Ex3M4Ex3M4Ex3M4Ex3M4Ex7L{^#-S!qgSr74k>rbJen5?N_VWTo7RG?gYtR+=1HX>w$x$&r<EC
+(=~Pok&w@Vr8X?m6aw|)|yyZYhq=siIue`R@RzWSu1xUO|2=GwWe6snqpaNie;@SmbIo>)|z5jD|aGI
+t;v?PCR;X|Y}shCWuwWKjV4<*nrzu<vSp*mmW?J`HkxeNXtHIa$(D^KTQ-_(*=Vw5qsf+yB3s&?B3s&
+?B3s&?B3s&?B3s&?B3s&?B3s&?B3s&?B3s&?B3s&?B3s&?axv2O6z$UX6z$UX6z$UX6z$UXl#7uzQUp
+vJDFUXA6amvlihyY&MZmO?axv0Iii&9?<zl3bl#7uzQZ7c?NQ$4G&Ea-`0HA%MqN>_RQB`fEsH!$nR8
+<=(s;Z3@Rn^AIjY}IVH!f|gD4;f06i^#03aE`01=Plh0%~JL0kyHBfZAA5Ky9ojpf*+%P#Y@>sEri`)
+W(VeY7<2PwTYsD+C))6ZK5ckHc=E%n<xsXO%w&xCW-=T6GZ{FiK2koL{UI(q9~v?Q4~;{C<>@e6a~~K
+iUMj=MFF*`qJY{|Q9x~~D4;e~6i}Ng3aCvL1=OaB0%}u50kx^3fZ9}1Ky9ihpf*($P@5_Ws7)0G)TW9
+8YK@|RTB9hS)+h?7HHrdijiP{BqbQ)(C<>@GiUMklqJUbXD4^CT3aB-T0&0z-fLfy{pw=h~s5OcLYOS
+JxTB|6a)+!39wTc32t)hTht0<t>DhjBziUMk_qJUbfD4^CV3aGV;0&1<IfLg04pw=o1sI`g$YBNOvwV
+9%T+DuVEZKf!oHd7Q(n<)yY%@hUHW{Lu8GerTlnWBK&Oi@5>rYN8`Qxs5}DGI2~qypO69B%i=1==Sn(
+yGlBY1QV6v}$ujTD7?%t=e3XR&B0Gt2S3IdD>i2Ky9ulpf*<&P@5|XsLd4x)aHr;YI8*awYj2z+FVgU
+ZJ{WjwonvMTPO;sEffXR7K#FD3q=97g`$AkLQz0%p(voXP!v#GC<>@86a~~4iUMj2MFF*iqJY{$Q9x~
+}D4@1f6i{0#3aBj=1=J!G^zZixaR&K+j|q{tF)hM9@A!Azpuc-Sh#U2H%Y?XLfA^3OH}3CN2yp}d?hz
+qw<lk{m+|a*!(nS#VdH0kMH~8<K5#mPw-E%_R@V|ROh#UWRF9~tu|Lzqb&LiHvCd9eKH#-S&_W5QPA%
+!{y&OYDlA;j6|o4tfM`+T#H5NDrnCJ1r%`DQ;M&OYBvb`eBtzBxdMv(KkV`Z)w_n52l<Fi8=zVUi+d!
+z4w}hDnO34U-gM8z$*MH4p+fOj1N{n4}2ZFi8=+VUi+v!z4xYhDnO>4U-h{8zw0NI80JRaF~jS)G!qh
+s$nW3R>M?8u!gCKXbn>l;TonQ;x(TpcN3(}V+h%>xe>ErqatX-9YWNGhqPABP^)fIt8P*U+@!Ow-0p8
+mw2xH%uU7r9R{gJ5{jXO2uU7r9R{gJ5{jXO2uU7r9R{gJ0{jX6C->CkF2oa9~LPYGDjp~_=>Y0t|nT_
+h1jp~_=>Y0t_nf!Aw5V0S@B4$6LMZ8ELTtp<z5HBK<W(XJ&Ni#%@h@@FhGf;+@5s@@Q(1=KyA!<Y<%@
+8&sl4gh-5lJ%yj)<fgB1c5h451?;X@=Mlku*c_h^Uw$NJLc35G5iiW(X4z6*I(%h>95kMMT96ks_jEh
+ENeN5?Q3pV;Q1FY;J^$*r<pXi4K+8kVdK*BF#;*NOO}c(%dAAR5yuLH;Gj@iB&g=RX2%MH;Gj@iB&g=
+RX2%MH;Gj@iB&g=Rr|!Mo5b1%BSWl*9Vk{EC{Z0KQ5`5z9Vk&9C{Z0K@f?VM4hABUBI?5=Mc9W)intG
+x6oDTmDIz~iQiOh(q={-E1b>*Mi2g815&mJ4BL2f9MF5CNiU<&s6d@ocDPllOQUrmRq=*7B6%p-WDk9
+tiDt7ju+x?l3_L1;E;y5Bn%yER0nB#~gF~<>15{raUCrHGTm`4aGF<TH(;tnCC#I`c3eU0jWM)g0V`k
+zt#&#3-qRR1%o{~6W)jOu?z^*^inpH=<Os{UtH|Ff$9S=ByP^*^g_Fc4;9&$Oy%+JI+%ho}x@RR^-F1
+6kF9tmi=VbBH%FNfB^jk|N^7Bt^)HNs5>glN3QGCMlv$Owvp>5aLcuQUsouq=-B*NfCNtk|OrRBt`Iv
+Ns8zblN3=RCTXro7#ZS3Ohv?ln2HDpF%=OJVk#me#8gB~h^dI65K|FRAu*Td>O6+P5Sts3AvS8RDXtk
+}Lt;o(GZd<u6snsPs+$z5n-r>>6snsPs+$z5n-r>>6snsPs+$z5n-r>>6snsPs+$z5eM;3$N_8KAco9
+2LsX9=pI#8)PP^mglsX9=pI#B635dRzuL?rb>N<>mGq(mh3LP|tZFQh~y^+HOHr2Zx}+wM=ORGAm6BK
+G%H%X_gZV!s!wBKCW+Dq_DEt0MM$u_|IeVpYt3#HyJ6h*dHB`>KTD#j1$oUPOvG?nR`C<9$tO&%B5fk
+rELp<~RaU%y9&y#3C_JCrB?MMdtP*Qe@PDrnqJUEo7JtR5KtV_02^>WG=l7aitysZj_@gfT&VTfE(k4
+05`-b0d9m10d9OP0d9CR0^I241h~O12*{P5Bh17-FSVZcwVn^Oo>yAWYpv&v(sP8DsON|-QO^-vqMjq
+RL_J4niF%Fz5cM4KAL=>6Kh$$Xf2ijO{&3Grt>=BM=L4<hmDclG>v^N}98n+YIf6dabHse8=Lq>w&k^
+yVo+IExJx9EUdX8`p^&HV2>N$cv-1AcFd0*@KK<jy>^}N=4-h_J|_%vHp=5i)13;A`UGLY4_Eaex1w!
+Syrtrz%8R@Fo@%TE)_uP-&RNP1QWzJAq~iM%^)nfTUn-HXJRf7&w9-?|rzPvEs>;uD^2nMe-Qmf1kPK
+tG^XzrRO_bCCD<32`3s-t8PaJG$-u3`_e+=X>v$sWHy^-ajP7dEfgLLY(`(e?*A$zxR&`aSr(Y2_en{
+-#;V7x#0Wfgg763|AG+bgzsMw;=J(vYeJkGe%MKf^TQ9jx(HP854#C*hX1gK5NG%gdkJy&`LK@=XP*x
+fggE<r*iVSF&xc7uoP9nVBE;F}!x2K9eLfr|#M$T1=ME6$4D_e7gg66zm?6X&=))O8oPqwdM2IucAMb
+V%$k=~6MhHBUd=@e``z&Pa_YVkx1CeV%#%9-ojLohE8Jk@TGB&#wWNdaV$k^;!kg?gdjOsu}bs)&t>?
+V-0*%=^Xvok=(W@mtm&CUQBo1FnNHai1k><<SCfdi47K*s*#6d`aR;x%OK52pxm_W5v`5NDr1-Xz4?=
+g()k3C=)&B>GzMLCd-)zd~F0<X5Wezy~PnC>Dt_>qveevn`X)jpWzL+cJ@;uq_i`A+NVSl-jKq%a4TC
+aVfSYb>QQLb==73#`3H6_11?9yY*7}Rr5Lx{9YzMhFEW%8@Qg_>TGTCxt{n)ZN0UBr+V_Mz;z}+W?Ki
+glyyFkTcZ5S!Jg_>vL6NRA#Gf`c9pQm!{!K!J?t7`iHFS-mU`F%VaCH239}w{ov_TqmI%u|>;_?lhdI
+aXZ0@%ETPp2COYfn#s6l-XyG_`@!|o7PdDvaTY7e_dSmR;cNvMc?Vmu(sC&n^iJ~18=<`ZLuFrOHY2=
+j^Ym@uChPYCmg@su#17|#gviSe8;-+nI$^X>PNFyDT!2=ndtnlR6P^E(Oi>^I+C%Zu2v-~4XEJp0Y>A
+xwM)yDm~Wu@&;m$!(dOPzxg$hQi7TdXR~;Z9VAAiLL6%dR1WIsxh&BTqMNx{^NB*9Ctt7BE&KG<6T0;
+CpOwL$JcKs32|)w_<#_{)sMFcaZLUAm=MR)Zx0gUSo-ZALL5iG-AjmL=(qa_as2#tf)K~fkIRHOZhq`
+~UX7XM+g*gfGAo2Q%Y3_=5Lo6uA#O(b_>d51pN}^PfqiZg0{h${1opW{h_lbfM}#>0e0)NPv(Lw8gup
+)B0%xE9;=ghB`L8R4IQx7{jE<#u*0Jg{vFbCi_|#Hc=4|rqenO<L*RkpoU+z(IZPgoM)f-~f8)DTPV$
+~aB)f-~f8xqwU64e_L)f<w)m?x?qB&r`Isvjh(A0z>rB&r9<Z0Bv6%Kb#HKy|7zFAa=Bs&Xj}v^!O~)
+II!kHjCT+4VLy{Dm?>Ba-FKgOjTm0Dlr46x7w(bG%6)cz!*lQr2O1!Tc%RZ1WadC$_2J3wNWW&0wZkH
+iPi+RAV!^H0~?^)s#C00iEaa9Yt<>%2FBK^Zei7JhgF@!suQi1a(r#oDb}h?wkngY%H&L)Vl$P`nabx
+ZFy@)c=S-bqGj)p1RK8~czGo`mGj)@ZsjSb`O-3eFq&ic#7n#&9>RjED=PLJemHWB6CC^n4$kmN`u5Q
+e8)kAXCLvqza^1vLFtFwHrdPuH%NUnNFu6jtJdPt#qNTGU2p>D|w)lUl5PYTsf3e`^vbxU5T-cqREQm
+Eci1lEXB<#MTVxm3Aa29B4d%HmRGajCMnR9RfAEG`2qE>#wnDvL{%#ih#PQe|;pWpQ6+abIO|UuAJWz
+~atEaJxUw(mqmkkG|?2ebqhss(bWR_vowc(O2C=enGXa144J*h}eG<xO33-V)1)TPX;oYULl;O>6L+c
+GVsv!`a)l7dIPatYs&)lszALeP_GdwRGR3EDwS-GV(%{riN8l8Mw0K5n342*Bw@sSkED#)?-9dD_B~=
+5$-hT3MvCu|oRRW-q+mqc3u&S+YSEY4JAU*7g4~ep_#1}YnC<v6LvGM^{DdJlYCC?)kQ=rgf6I^?w;g
+}SkQ=xiKV!&^+>XCz$PL|&e_+Us-Hv}`sPCYEVrbx?pEFcB=${#?9rO!^8VCK7pcwZ06+^JsuNi{9e!
+~##^)*AV*KZkuz5azE*z0!;!CwE$5bX7PhG4HhFyv;<)tx7Qv%2#X!EWmOF#&GL{51h?#r*M42tn%HK
+M*2fq)i0b=|=>F)9kfCIL%%QgwyP`Kse1_3xw0`wLmz{UJHcN?6p8R&0Y(H)9kfCIL%%QgwyP`Kse1_
+3xw0`H4*M8{epmSHoPXn4W(ZZ5YC3z0^w|UEfCIz*8<^ecr6glhSvh&Y<MjY&W6_l;cR#<5YC3zM7Wp
+qGk&@=$j=!;{x#wpG_c?BusECi@|XN`&MLnnZp$cF6G7zoIn~BJke|C|bvB0E{b82&k>Dor!-|^+O@w
+paPsl3@xlM^mp=mWyEv{NNF+y#tyPmJ^Iz*@=@apd6_CG>npeqCkp{0otI~pCJ=OB1AynUJ=_mJVS!v
+r~JS>3arAm=V?&-kyL!wj#TBgnbTcyW%P41cvmP>yF^Bgi?<=*%oZj*07guMp&@IGQ<2kfY4-z!8F+_
+Y7Zgm!10zC-|=#JnLQ;LKJ#9d66Jzul1GP1UY-HpS(<vv)A|mjUi%7!#QpS>~;JpLC#*I7bgjF_8J{L
+MUb=C=m<m3UTaTw5>x^@K#;T7=UoR0g1sIu5LDp@ZxaN29V4GZFluy|IFD_?c!kCg8-vk-X@X#{g<S+
+Wd#x`$BMA07K1q<X*XS9IA+`vk3p9q<B#bWb4?26TpQO>iMqzm10YT1Q!<k0}!Cw2w9b~MkiLt!5`@q
+qKTf7sDvCOv>T6V|^v0vfYVOb&ZDh%%gej)WLtnYp*D;U3#2c~5O>;J;})3QS5x8cx5St0iyaVqc&;&
+p*0#^vDQE1KC6kQyGlOOO;5Vk?*P*vi9r5)dD@k^}xVl?`OQTIl4Bm7+(pl~1f&FAF?(>s5cMm&t?j)
++=IEPu^y10=E>K!0p3k>z$!)y}<3mwoLwB9tG;jFl&<swpY1~(lvR&Zh0Q~J$bvd$pgEXydS97mwYJ#
+{Vk0Ym&!o<%I+=R&NgtnKf%(JS)c(jVAGU&pk6Lrt_%!h*_Q)Z_T|yC97u;M2jUi3Q&y5VWq`0{9cW*
+Guw^6b^#ca%7jj?O|DqUDy@3c>HhsKd*CW79L=gdQ-i`@y^L0Xio2OF(-27|^aPzVyz|F@Q0d5}732>
+`nK>)jDyX_aF8<$%tM?3XOIjzP0Ox*uy%fw~#xSvPNy0$D9^#)tPmA~$m2{(`He$CTb{N1$n-8SkaK@
+p%Q1UbvDJ>5kRF1pU{y-FC46)$HAat2;|b%!7e=s7_+R_xqOkTdge*E52!?b&^nAZ&Z~EE3cQbc`UkO
+<g^4i6Go>ojt?tz&^FJk=leBKqtEp&Vj>y*9gLvVBceca5s7O<ORa8eLC@!AZ%3k(Rg?V!3k=;cQJYP
+)FHxPvWe3K!DJKMGn_1*A0`MUo47>~Og6DX5bh)|?Y~SIj)MF7&tS62Jp?(EtxnSq`bR-xFph%50}}+
+{=-%0#Z$b$mGBl2Yt0zwp1dAQoPml$4fFKy`5LpFB!Qmm|HjaYB!}|z=!47kmVX(tQ4(}*<gj)!E9ho
+8s_BwKoAh_6(<t~Jy;P41diZ}`mkGv)b*Z60z6BBW&Ti<n$APoJng9Ksdj}fJCs@s^oJx3VE{@6`|F!
+smp6NIrpPG*4$JmmQeI`Hr~EfP?Ihg0rM+Sv?l^Cwp}p9!N*UGFvr=g{E^T9<GF9Zo+Y2u^tNI6-j2Q
+_}=t+B`+Z!AWyCvzH*4dxq8}93F==WKyWh!x`c+^yT4cS{@-V4=>CR1Z$rmB0ypuULgO3#ymVrP6&;8
+c=llz^3J!DG$ncG+d0}1;Kt?f@==0dl*{}q7-g0gEW80byhQ62UV$CX(kzV2nZsFfCcFeYyh>96E@^I
+DnWhO9@4*h|_+c>E98LLn6Lxrw42D~qUA1--g2AqlKj8M}aGoH%4ZCsW9C;Y7ac*2We}gcXY>@^8ufz
+_opC<?=yH48=yc9cJJVOvnwzNPHRGRZdD$9rJ%`*7btx1Als#~uJ!rtP_BL5i-a+fv`xZgRv%RPcY?$
+S8mhUf4uxqs%_;}-oQE_n{`(mIAjj>CIIr;G)F%`zC`9+3t2JXbH#F##7nhxh3yfHaQ7`(z_r_#7_pB
+nb9+K;DfjpBq;mlgHuG=WvDWfn<*DpAnC6`*XO$ZG^2>XsX67(BaApf-u`XzCsX8^_T`27eQBN?-B&p
+c}#m4Tm>CIAs5D7&><fOaT#>@bcrBHn^(AnnC-4k&;TRp<LVV24$OAXXupJup~GiHc-#yfKBILUS3`%
+-X_tk&p&K`jp6FtT8V;Y6m*aZq#?`|#{o@+wc#?>Zd!WM?G*-CoxjILSA?|x_%pIhC7H)iQEbOOA9(O
+*6FZpS3n3u#;-1=OdqwNclIu2j)voQLv$pewrarm0{4an;_d`*W>Bz7F_rcuOA)75Kq^1xNo)oXOn#a
++|UZaP&Xx#Pyw^Nb-Rvxn@0Tc@La;XUp)fBt3jnTYl5qq8tBw2t=C#t1iB<zJP6crX!5o!}oF0HVDL?
+zWEjAdkzfqY0X^aJzN1pH3OL-a6V(&%*uI(SGuITyPyt(%v06Tt}0%=fD-$(SeHufd~i5<8c>tbcpDK
+%c!Fx+zhzx)mvm0+(#W9rl}YgQb&hq;>3;A(Gi;4@rAO{QJRU75OQ>k42F!58&~ggr(v<<G`k=v<mec
+k|B)4Pbd(knq=j6)PRlCtLXM{RuVAq$nxv5!a&&@>iOi6rDcVpYHRS3NZB~&Ra&(GRKqQA8o#Ma3oAY
+x!Y5Bny%SNYZvc)IMM(1hL$2ZGHXGso0a>><Obc{rL$<aAFq#?oNDsOd>VsiB+u>(mahZD4PBF*G*f`
+lj}njBrAZ5&cfj?U5SjbxMK-M0yH23tEuT}Hym5g%ERa&mNmCIKX!99^L87}8FTF48oG#FL|oqzEAO<
+i^}F@;+prT)j=UME=RqWty6ifpT<-JPbJ~M_0%y$U-@~%6|prer}2e7^x^nS7{wUGRn~`iBw2OIl4xZ
+A`()r-XX_CO3KkZsTN2|Ia(lJL0ZbuBAq>vm~wQ3=0v2X+?YGZzX%t*N%TN|%GG;xutJ8)(Jf*QB4`_
+PSLqmsAlm3Q4Hd#@tM_T_5l9=|rgagaw9y?h3xa8*J47mk(?)klscyV2=ndN6A*Qx*<sk_u2&-+(-Q>
+r?XrgO4w9P%BMGgrpM-S-miWHWkWo{(49`||lVYG)`HO$KrG<x`oAlPi>F+p&%m0bkEW-Chs!DcH@2!
+hQX?IQ@$mbr(Q2*cjv;X{JpW>4-C1UGwnhajBU9tOX6m~Hd7W;UM*|9yUlngb?0-%pS?<367v3{-ghl
+ps*yCH39Q3pDqV2HMLDH23N#VIafn34(A(Y$r7Yp||y&{4hilcAh5)XUIpyWJKQ9cO4`Mcf@wRB&YyH
+B=_!M(t_-#1DZWKPnfgW`aYtvmksFJfjPpQ&DJL_5X3JtwPlF8txsMj2-hzsR|vv&z5~Yz!t!|S%p_s
+3)xn(v!Bz)P5d_D*c7Yp$+4kD(Ny1>QBhLtewT_ajc<*C8yG2kRe?`VZ*lqP0O-YEYtxu8fA-1+YMYc
+k0ZGGxKL9ojSB8GR(a+<h{YnH1o$QclkTR(Y?Amr7$cJC2k7Jo)le&U(s!3n}(mQ(i#@>Q_Qgu#o>5a
+ke(+qm}X3Sk2eBg-Htw=utKFJaiaynaEDv)bBDA~=F)>*r}5LGWy2e$O&tv4=e%4E{8~_bg$lhw*R1p
+)Sz8h)bI57ig3bKwG~^1VR99jptwl(AFs~R3L!1wu>fp1kl!Y(;S?7mN|ZrF!<9IT0sy&Tff?s2?|8e
+*5??)1)e=LnHtY9XBG&<nlw+%H=bS2og)k$HGiJm7eTc3g<}L^Ra(4B5Z(;fOFI+<(bkt}!bJ>ieTgi
+M7~1+0Hv{f8KTm#PJfq!MBrLG>AV#(}xtk!*S?*AG5h7c^ON>H@Z2j&5f^es5lG<iHi#(uFLX2#EndU
+LX$kq<d5(F<=rbQK@vh`&m8$xC454jnb;pSg)r?F31;a|k%|HHJsMig!RF|A67qOCt6yC90T{*<_jDB
+9ZL;5+a6Hh<V=^O<nZ1>U_NJh!oMfO?2zENe$-N=2A%W8n~EAj3=AP#{jXv2d6cLj>y9U(wbEfx7kA{
+ELna<DERzV8g;RO)m)4Z7iH5Iv`Rv-bIW>pl)MfhDWl&pV5Mydt3b@w3HxJw|0!WjZocqH!XJv)s6S=
+AqZAGPOA(;b>qD>`d+B+25la5&uEuuQpmk%(Ix&n@2GxsnlMkoJW6{yMC&-*RUle7o}`@!qIKg}w2&i
+Ow>CwyB%*cWgLJAxux@;i#u34~@j+U4k<4XykhU6L7?1S+0%5$d_$%1#ARVR<;Ts>KRo9E~E!?672ob
+*VA=;lKz&Ae39fPACA%{VLZ+w(aZV2#=5A$EaU`M%Q&S2wXL^uTa##3DZwm^Vye1zzR0N<Ey#T5wfjg
+Qfe2LZnEG2*Bf;9KAgf9cJQ6tgc7;oDePCU-|9ZtW!h8B8`!)IlU}JWbR=ByN0?wqA(DZ7hlrfz3|QI
+R~M*jfEF<>_aSW?G$kbvADHUbnrkdZe!sUbq&F|jm15*tw1zx?Gz0bqH*K1bOb^)ZhV$3ifG*UEO8Fe
+xba!i*bt2ypJNC%J4fdq1mngRXm5^S-1z)eg5YKs>12Um-1q`5O9;k|FY-Xa%`VYysUO&gA_zCWOjbk
+?Zahm<HiB?#r>WHl!i}%cLW>~W_zKM%2*PbFvZWA(8_&_~fGFH}j@Ac6;nvR38ipv`c#d`+h{CO&cut
+V#T~|r=Llkafah_&vgyGiC(fW)q+}e5CrXdVBzCpu?Fx>bi&CCeHjqlI|fH2(nKFv`G!)+`+Af_P>H-
+11&LmY0r?D)~y^=|XWe>R^9E<7Y92LZk@OYI2oZ7jZ^V<IAa8?&>t{XmFs{FrtN2=R>{(Nc^M-}o`@8
+NCqSEE5(XzVUNX^AO@2zaSk4A-;|4r)fGxjIYIrDG2g?rh6_0f_$I%(BzF6-{-xwvqFq-<N5`14+Qx>
+?<K1t$oF}YyXLI+`4IU%f_$G3ogv8C?DGLK41#>0kI}4!Am8WX<Q<6dZCt-g(*=TjpJ#|52=c8h&@Up
+$_j!hx+IS{o79+^Fwn%dff_$IP)5!rrzTqP}Zy?C``2x+y2=Z+#u>$W!`IaW>2!<%%+7gifLB6#m+FT
+*V_xUnSc3zBc={QYki1Dr6;I6@FODAZXgdpGN*{;z_MDjk*E)fLFEX_P349+xnl^|!CwOh*s!I`e{!(
+f?(MS|c<i@OPeFD<?z2zI%9lpsuiOSkS32E*JsK@gnj{!W76Ov^6`!eY40?Z9HVe48NWOP^P0IJ|({j
+Xm^>2)L~+KOqR}$&J1H2*YxCW0HRoM}!-6wk#2H`~2)VL3lrLWriRa?fFxJFagrd(h?!J&o8+7u-S`a
+1i@x6xEZk73vN7o>Bbo{wRrzD3B323L`lkT3%6zB_4XuA#P=HO-quH({;FHnbn3O6j^BR$o7Dc~M_>Q
+wtN;Dg*PDBa9bb?y`;gv_AAI@8|J?d#)ct4N{b$nsXWIRz>HgDp|Cx3FnRowLP&2q$)UJpc7E#M0YFb
+2Xi>PrCwJxIOMby5S+86V<QTt+QUrg<bseLiEFQ)dz)V`S7mr(l>YG1;JrS>J%zJ%JBQ2P>UUqbCmsC
+_B5FQxXS)V`FNN9{|geJQmsrS_%NzLeT$sC|aoXQ+LK+Gp4`sC|aoXQ+LK+GnVJmfB~jeU{p1seP8(X
+W4hDeU{p1seP8(mr?sNYF|d}%cy-BwJ)RgWjwi1`!Z@@M(xX~eVeDTzxcsdU;U4-zW)6$fBL_^J9+*8
+9LxUls~`UGhyUj<{u@wB0|XQR000O897^_9LozfM^Z@_>Yy<!R9{>OVaA|NaUv_0~WN&gWZF6UEVPk7
+AUtei%X>?y-E^v9BQ&DfzFc5zCuQ+8dNfo>fX%ec`2Lu%$1XNr1fDlTY<kERf?8xVC>%Zp`C#4Jt27O
+5He0QI}@9umCrLDBtE@1EL7q3L^Yzq<}OYFS1hCsKSbslENh@XyDkA8FLFolh7k-Ta<A;yrU$)W=ZA@
+0!;qrnp5ixlQ5TqYvR#?vh0^XNj(<z>XVy5@3;=3YB%<Q9D#eY$?Pe*NZSw!XPqt-o&GfB76GU|kO`C
+lGCF`)&RmmP>fK5Wv4cxK>S5sB$;4UbBrZg}v$6DpI%^40Hk;!cghmAs9blva+RZ_bi;gC^Qg047n@k
+ta}Rhd|pCSSVQl`HU;tyRhz<WwtG-+OGyBZqG<T<VZau5SbE594$4&U;Iv239=wG-)aPQzzD9&a*(jn
+#9th-6b7O57zWfC`(BWBy%=pM)hz49a+!cpZ88|1&iG-rp@DJP_`n@yZ?h1;7NBR%yBg#|a6Ty*RXnp
+*b4u`ogxryp9&#A96u)9*4kRazb;?!H^RSplgXpU+8>Wo*K-xu~7L74na*t7$GkXA7`&tz;rf2ue+)j
+aM~+~=KWV##Nq8m(x6E^XT>uM6F1f9Uswcr6>eBWuoE<>*#5=bbKh4NB2iRq>4hc<|`x7Tn2w+p#|cd
+z(h55I+D=O9KQH00008031s8Ry#YL)2#sj067Ez03iSX0B~t=FJE?LZe(wAFKu&YaA9L>FJ*XRWpH$9
+Z*FrgaCwbW%TB{E5WMFrR^^gPr5}LA1relPC=!KhW#TolaO}#Dmi|3!I}cMpA_vFu%+8K?H?3mM!HYh
+y_M`c1@!+M=^|V{wR6x&SvAAOnp-pUIEI896;7D^|nRLkE)JcU9lAP4<>nepmZg<Via0)#;XZ9Qp#&>
+AJcT9r|Z#jz*DfYtJ8ek*fYyzB^_TUY)%(opdr2wrpc9joO>=Xr3JCBU7$J<m@m9yLhA<#YqrRs}J!_
+^POn%LXmx8k08_8;<tu|4xmG*!Pc6|l+veh(#68+~L-a_HTAs+33qrQ2s8Bmb|sGX^x$)p=IAf_pqzq
+zWOYO1@ANW}UG}RhBD&+k!QDX+FJWMJ;B^oPXkgEJg%1#C~HuBwQ+*6yU@f#%0$LFb{{km@cE$nHIcu
+o$*j>TAa7YdXiZtfjntNv*U)Nfc;)->G%8Ep%SZshkQlZ$jIP3J`rD!Fx`LLekY_TLesm<LVkuMg{DO
+xtcFF_s^6A$(xN<4f-ICu@JE||jPk|kPcRQQmUH?6pUTM~uhTvue>FK`+ap?`%xQ$beOF&lO9KQH000
+08031s8R(n_Z8T|$T0KXRi02%-Q0B~t=FJE?LZe(wAFKu&YaA9L>FJ*XiE^v9JSbJ~VHW2^cpW^0XgO
+oa&>;!3T#Knd_h7MbhV#(H_C=}YJZEdpTic}h>>puJLNJ=6t*>O7|51YF8{qBzBBba8hI9-gOkn`iGo
+q3+Ea4AXnRK{5<AYQGrTtdoLd?t%^!aHVV#w3^Vs`@TAqWUQFVk$eG&gGv27}J~JmgfTHMR7XM-i7aB
+JcdE16VCxjMjgN>PGuxFYc7z(!!JEZvUK6AcTpjyxO|bNyu%a0n;iIAt;u|&Us`OXr2+l9M;QUGD<Xb
+3<!cE)N}0!#Lh_e+p5+hod(O&?Cz5%g@1w)hgb4vJ@8lKQ<<&v+x@N80gDys#lTg<6eXXq9E#E`V*Et
+tFl>)7kK>nd~uo8<koBkajWk<2h_#C1r<sYNSn<k=1dE`AM)~`Ll0H>LRSj4H2ES+*slVP|lDtdAj3l
+3z03WBGtToppXge;I<e~(mB+k?qQa`BK{BCX^qj;7=g&d16j`rjWsX%qQ7ONv%o!+(*(l9_W^<SB?^&
+2!I$8N-zbKiCz(Dw9{3UvzP`_Oi)eSQ2%<syBAV<dWAcls}#l>Kj?qDg0x}Q<xNSBH?2!m+*Wems#2?
+sh|)D?dP!KxI9DQ8K`BJ&Y(!u$D2yoO`ydUn3Dypi<}={Dsf7ak=TRLyhx{`8<|Ba@;6GDS)|ghmUB+
+(XAddWj$AEc0XkqYb&ORZ*(Bj3c#)}eW?21sj42X)nx*IpNlRIpneRavR4p!wM3PAnMOb_9x`u`d$71
+Qex62?-V~J@LJel`OB|TfiIJ97iie4i_%#!$?1G6%wlWe@AXS8NHTM_(Au`U!Ziq(YYkj*RCF#c1nfN
+*{B`YrHvHeG@jh9mU@*H_QsXO==A`okw7<~mLb0SRa8Qi2~i8h&LP0(Ht4Ovbmo-8Re9UG`ZdlvFlTx
+xFz<H}qw}CCqcC8b3=wHMlKX?&4Lkq9hN8!^r#w05ABQ6$y0&2rUaQGKnC#Fs3Vk0=x;IXZd!Bd<D6x
+ln{ALR8CjHeGKbN#A+!Oft}Djy{W=OH7_1&QKh=FqhP*}moIp}w+UJy{sLuoVh&O0spe>NokKr7IvTb
+rvbv=6R)wuqH7ZGutH>KO5TSzF8yYq&pP=hVtPQ0y3`)7<GI{Q6TeahjUDgB#Q`T<z{)Y1!+gt?~Mvx
+_xSEU@-m@pHd?%5?K#-GB^ZlCzn|Lk`I1n7!MH)6I|y@nGNsc$>LKU7^QL%ip%7tfa*+bQY-{-MBTBs
+Y2vpj0Am^rbDB6S_PtmI_Z<6h*2HN6{7*bO4$Va8otbRt9#PZf2{bYV+O&f>Ha5;g-$awd@NEdVj0}B
+FyLmq~+z5GC}ok{FV$;eV8~XDlOesy<}q9gp^^Ym!7vj(Y_J)gCNvRwS|>}dWL!v*Q;wiJk>j@Dr~{_
+ByEnKYZ|`<4r`d#TLUExYoIv~CL_3Hn<Qg1WlhCGyGhh0*n(@AsZG;yzvfrF6l7O6T5@%C#HayCV+L>
+0wALnALP)wLVpsD{c#5GTl%0;Y>aS`j>Ua@o<zDxjUvO_Q@$ppQ(7PQbtlsg&(el*QLfgNy(-tLfT9w
+oa4C8kY-i7)(d1anGW*M$$&*0>AmxcYoXqSZEo~XS3pe(kemglDOIbcH68CT$#V*k(5MD0kXIcKs={m
+GyQXQx=sISkK^C$Ur@GB6Rl28AiRMq74TvQ@t2wzXv<ToUjk?L!+NRmG<G4y~@1+A=ku5@r<`3V8YUs
+<p1blTPsbMlI+%vz)N&z-dDoAPNoP2;fnbcJ$X7*VM7+v7`=z41kFcJK(+D*3Zw0;U8xrIIL)sh4B*G
+2J4|VtpT7%4&Kq)d!A=zu9TaX!O;=HM`Tb3>}1dorOu5N%&pSbR{0J?6YScWTEp4tVH)1FXlP2eB@fR
+UA#X@k#krk>o)i2=nUJ6dXHSvFcOLzTP|VhLLlvxZ-chwnTk1Q@euPeSF54b1O7a}BFR=*r@KtQ8ZP;
+9NT*0bQ-`aQZbxT9q$`|<ld+66OaoZ>n)|B5OAsm@a@&9QyDwxe)^Anzv==4&%j%O97UBb3;yw1qUTk
+5MVEo8JE@J3%yf?7jUUS-&=;c>H;F;aYZ5L6;!(~(QXSHs0Q%D0_Qje=IpH0}ZHQ0(6>G*Wsri*Hxit
+aPYnFwo4Z_WR(}5(_QuaduaBw^$k;mKT?Yq}pJ*CFPET<?ZC*{?V;Ob*EW7Wyaz_j~Pi<Xmr2JXO83A
+kD7gtHx*I!fgn{G<AptS=jx+}Emy2<JFl^dL|LnKwLiQ|uc9=QhXKE2&{JOC(^d9Y2J6dU9n_tDCWAU
+!i0l6VP)h>@6aWAK2ml;P_Ez^u&#LMi008iY0018V003}la4%nWWo~3|axZOjXK-O-YcFPDY;0m-V{0
+yOdF?%Ga~sKx-}NhcxwW^XO>rs7Ys;#ouOw00RYkTHJ#Mq*^Noh&P@0IGVP=MwlvMuv0qFN*_^|9`D+
+#M?ai-B|0F6ci-RNec(KwDLlR-SZW3zdYu(QYNHqTf(olTNyl2vh)!ec&W)AD8pP>n`oV_f7@Hj1mHN
+~Z~e=0&BS<B~;vc({az4N+J=mg;L&%!k#+#>Uxi+pLEroli+oLMu_4jq?xPkF3{Y+Z*Ya0mR-0gHM`O
+QS~@WN~q9;hc=t!*-dMM3P;J9jnZKirBzbEziHVVwRk=J6iGENGB)byVyKu*%EZSF-|5{vONaR=LGr4
+C-aHg>c7reI@7fLXMv*6%U-lDg?zGvDqT;vg>SprDZb8zWPKREdC&M|x9~DJj014;w3<XV(nvy6jqe6
+lvSk_E@YMSZ=ekMuQOgeFKQ?^j(TUKG5jaXWySy{!|FcEOjJ#7?9%L7&A9jH)L<$YS+HXGCUA)U^rOi
+>23&Z=9MJPea$l#Ci0k?NH-S-LFd3773{T*g&ZG(pB~)|frc9wSrK4JG4?sz|e&llQ<MD<}Cq1G>&0&
+mP-W$v7^dV>^uflHVtQXpdmNFIj${S%?ni>131?s!mz)o}+ORMMOv>$4QplPtvlAZc*6?tSTNgQ&yeM
+fMYIY<%37SE}MgaX0=Z^P_VO#oe(^!$f~$~Tvrz-?|zOhF3;i5!PUuW|L7dlkINg&hm*K0mB^a;;Lpj
+hGCGL*5JaC=QPeDx$rx0pH)u2r5E_9nD(pA-L3l|cv}#e;M8z#zt%a33@obi4BY?BO^vGYiHDPEZOZP
+a~B|knd#+U&$oF>z}c>I(m_pLyyXkj{4KEQ5mx^#ND5G*c=_^}2RN8|8YBNB_Fo22>_Pv)E{2e}w!78
+?3%o6)eYz}!+MdMu>5rN}VMVy!=%By)HGf=N6bjAB-%e@*t-hmSDM2~mfuIgD&QH0I-RQXJ1GlQw%lu
+ilSg4vO3C=%FfN{`EL7rZFEAIMBhw3KJ?(RuUIfx`ZjA&2SC_`A=ui@X?>5i$9#40a0E2e)#?!aC>!l
+$<T1Zi}R!XezbpnzW-bF3w$O1w^hO0{WJY~XJg~?x3i<@<n7y|{>lF35h0~lgn&@eBUB?a^l-laD^;e
+4gOhjg@Pa=a{RzqVabu%@bi99cdI@bFUY%bYMW-ikPpD{X3s|55IlN7VcQoZiV8~(q!hzdnFsb6ZUPX
+*obC~~o^uN#t&_*n3RxPx1RN|Rp0sw3P0uLMhaP#2+l_U(bFaj?kj<7$X0re+A@%lK1fD=8Ss7%s^FZ
+fIgs=~ej0UE8wX_>J9K@F!KZ#IT;mgN=9^XSrW-JH%RRl12oh;c(ErY1o$;unPST7xG3pN!h<*|WQQn
+nQVu=poUF;K<`l;N#6)^IF#(uI}eZTFI`jm7ZQ-v-{g5W6wC?Gd9e@3j;F%rX4`|An(|fHEUjN5OA6e
+b9Cpb#HnTsh)_M05SWE@Bz-@px*kIHG*@{JLmKA95wHBdx&;Gkj9%yoHb{6Ejo4_8wm?W2z6mK^BnjK
+2*=FyWi!~{(*%-W`oTKSjlAj9@&=v{Zd<Px`SmXFXC{~1e(!+U#)7&!p(L&N0gQFsW{P`Nx1Da955&t
+G^xtNTVIa;KWLS4pjI!Q)*MyJ8o*<5O)!07mdU`35VmM-<2GzEqkv<l>~(v02YRYV$yL$uj)SyB4i1c
+|iGdWluf8dUJ7-Yed2vsZ2QvSm7i94#4$Cd|HrHp_cmgBH+$qleif9i|l-8BnjXB1M@bH}UXML?0akk
+5n3SuJeGXF`8WmpeVUD^O;2Ph{376u@Sv{A059xf4hGfU0odY0SX$8-d_BCwtx5sF)duc+rJUQ?!)1W
+J=WZ6Gp8QRN5b;A+7j}|J(5)8%`c5m@k=OvfyF1m;#Z>f!9W(nOrnc-_b504<l*wyQ2rxf50~%D*2fL
+~@&I1$;>(fo@-WD-F7InL^~)p8oPK#M(f?7u>~}f(#=v;DB~jiQFSjMi)OfigQU1kv`9h-HDnq>YWyc
+J*!{xGP1~0<puSBDR-EcYf&DKjI;AI%%^&%w#UqVCfdrD*#A9zY+6(4%F$%)YbeXqU)aO7bCzeg7zd-
+Zwo-@$nB7(|(QD+Ym~4bEi}PxYJv7Kxja{o-bh>l>voFMG4Nh^K4});F4@cZNAVhF6>TO3vfA@h3!h-
+2v32X4bj}pQO6Y#SDj^6R>ErWSEXq^bgc@gzyk>CPfOf>R)lX1CuB`<BEdlJ;bzkO;Zlw6_fD1j0cmX
+V-bq(G2)|nOcQ&BvnWgl*NPENr2=hTcUTi_X$<bp9=it7fEGR5>TbXAX2;fb%W86v=M$g>(U#So$t;+
+>MDi(}1xAqyH~?}<32SK)kt1*qGl#0DA<4Nk$;6N|KuZzdFDC<l4Ah4Aw2TTc<Nyxy&M+Tgf8&A%ySh
+By++|57-boT$e&<v&bkHOof>%@k-M9I@F6Q$T^t4cu(VmXYNdMWU5r&v0TTn8d<Z;DV^8%>MK)FbnfG
+Ku#_Wtk}I}+Rmc%+Oq-^E#8u25qKYRGlHj#}Vj&8y49R)<MJZA(2Z=Q9kS(AV?&iiaA}G@eCw$)ne8T
+9PomW)qsISzhq|0#!;_JVeh2v>Ru0Km#=ZVT%E_(r#}UPbN5E#CVNv^ZZUX_$xZ9#^{8RSKj9H$q3z0
+SygL@v@BFqA~fkiOe=pt7`GxU9#;UP{8puXK&ZymL_ZcH;vC{x^zHs!=2>eY>9aU3%CE!#jz?VB1p#h
+S^v|fZFU1OWpjbzZ$OARjcrHQR=pES7Y&3!9uv67Y6V*%$@IBX`?^^~A&^qq^8~o4F{*eMvK=PQ+(Of
+5r39`8Nx9RX!AyTnQn(=6dkMWY0CH!&i7)j04X*x}-l9nn^th}W-t&GWM)WPvQO=4(m``NRd?ai%@B^
+1Fg<NW~)Zgsn4oasN9&b!^W=|M|ZlEIi>{kYcA6_)|@I0b<vfPiBR+N!Jn2J#WYD<P1nP^QFcf;vFew
+Ib-*Y7Ta6jzJwO^La50Oid^ykYEG>mX=UInL$tjW&|fih#8(avV4YARxnd_T%iIWE>_=w;(}-av8fyG
+v=#2MH2XTl0OGZYp{da(Cy1Nij6t_vD`;z%w_y+Kx)y%;VLRLigmzz2u5$F?VjND4o#k8~J;Z2%gklJ
+9Z<HuEi>vI|@#6N3X*RT8p!_FoacI2(SGFX)9Z=7Te3+DFGhd6YG6zgcsnJA$?E;+W5ZSGRTrl_qY~b
+(>KQ+l{JlnSCbBMHYo(5Qd0eJu<-dS($6%eRoBU>VlkVwAFYL{A0`IlSl!b-Rvp%*;l?uimDZ98a{lv
+>)O^(|u|L%93Bu6`+9_a17G0UO`<Xq{faQqHMa-S*%dB!;Wykm7kVPB~xg_ut#TgH!0P<H5Yho-vvu`
+5z6628z(jMSTm2n4@}|TMlwQU3l-6<@QR1we{W$1F7D(tc5z8OH@Q;bk7-w7EF&dcvmzwOiW4@!boWU
+Cc=@7IwyAVl#IMRF<~jBJK40u$-w>-Uj;+~i}g$=0)-$MJO<N6Z3OnIG!s3|&_X`=4wC};c2C5eI5Si
+1Fiwn_hS%nrBR0$k+%T|!;aBtz*(@(p?nMF3^P&L93EWDG;RE=hl=g5m8t$hn?;8U=5u3;8lO+YppbY
+}4?h^pS2#kB^6&jI;s@ZBA$go(DEsRwI%uWfx$Ed-i#hW~~$towp(Zlu5_|Aw0zGWwT?rjUNa0GgSJK
+(cfI(dY-_A&>Z1?iWV3UV(jm9e$P;>savn1f^>5}M|;n$pHv<Z%NVcS!=_ZGnC_bO%Pg)YK!w+$V)a*
+zvqTYdOse5DM8>n`L7?yjk7GNc|q|GLhWM#6YF!20^R2qJ^(BP#Yu+f^eSlVzdFT4So!CU<fOs36%o-
+n(v^^a=ruu6-H%1!%QekGsMuUjU({m6yg>jgbNt(Z<%-u3x@d{n_E5>RqWz)@d%4ohes7J!=o%@9VP=
+{87^T{>oBQePhLO#z_wjv!VuRXQ^g)pPT%@{vw#aV5wkbp>Y+^;b6ZFwkoL2jf|)>th1l6`+OVm-HC?
+@D(1I%{Y1Rx9)Mi^R#U$z>i*W-Mmvfr%)h)IC0|{uqb?bOjoBhIt77h%;iLdUcYIfOAJ!5eV9(IBoU#
+5&TxRi0X)7kN4slkjE92n)zVD5ta?!Xwn5<nSGVL0tMX=we<sUy7|0F_?@>T4SX@f1>Xd(iWz0GvCd)
+pG#W9<<^q0B4U!@#L!<#8pu~9+!!4Wp!VODHFXST4uLg8wD2B6VsznkZNT<;LAY6W(O~9+5lYIxB<Ib
+^M>B6LWBlil@wj$3G!G->|#PZAGF~kGn(Mf1sc+74s<@U25UfYHkp^{r=($FYq@qsNlT8Zr9zT`A=#+
+-jv{NGNrpaOL@uj=Ixfoub7oDaR~3qcm~h^VfzBEei8T8ht_3cI<-|TG5Xx6uXUftpqUi!-YS&CUSc3
+$7Q*f}fTO{7#yoAm?I{Y1z*q|@<hIMTMM#;qT>p$!TD}D@w5rXH<Ua&^ELakr-EpEP{)lER>z?Dt**v
+Y%I)BVGvXuscQ&wJo)CuR0MI*pSQG~tm}xF|zGCpDo@`)Ar$2?i}4j-Pjsu}&a@0XKoK(P;dfR3$6Y5
+xU^$;8GMa!wg;dMqoA*AwuT$dC!sBVxiRt%tT?(Z)cY{T$m|{vh|;QRW{Kj>!1Ujv2gEw)Tqd55{Z?3
+oZ6TaOMEl9&BsHO&#Qcljq{}y*Oidn)pCiVj2OiR;S|mKm}ysZ&(J?ijfVmKM#r_DHwfnBQxYQ6c{Yr
+O+i4-@g%m+_3{6P(F`&E@Axi@Tm6!6)X<e25BALeEpzxr-x7^TevdkR2$2bgUado>V?bR)W>Y3btoM2
+Zxn#Rd$?@iCON}Q(+-<%069$KAIQd(+_xY1R??Z2_jJqJeg3V)q8Y?{xtz4$z!HJ>*J$^yPxZ>x$c%P
+Nnwk>T!c(+S?%7K)amXaGc8b3JDbjc0yX=!4q<3d1U!0>UFP64O<6ks=pZ){`r4&wIKthY3SMn>}G71
+Z2zh>b)-d35Mx&Tf5NhbL_>!0oO%UlB+_?N18Iu(JlN3-j*}Nz`Tx2tX7J*D$GcQ<r6rk@QluGjji6&
+@*KGK*5snb<Ua4&OGX3sU#vUW>hcdRhB)fT2^y$(bPhq(+S<~!)KjSXCN5Pq2kie?_u=@swF0tk2pNi
+sLqpLPe(aH>#eBa1tEbx5*!4D}?G84V1HLQ8@uboWkDK3>tp@v!;pFL|b&jHNA((zaod~u}5pWqS5J7
+j52q>p+u@D0L&b4CjAn@bLMj;GKM-}@gbygF|GM!i`khlA1i^bt>kk<;s<y+JYb1e#69*fA;!(nj1SO
+&lX-wuK6b2T3PP6*!F?E!F1GRD=h0scpc!nS>+S!X=ur$R8wbh4E{3__E;a@uHn-Vr_u3^2C*DG)!{u
+XcVnHg1}`wq@B`AG$UL;e%b-YBp1|pzWr$mMeI$7062}k)NdsBx;5gNEEJXR4||0?9$g?xl2#m>v!7P
+0zb6`?q!>-EO1d%3H-F}qg^KOQ(xfwhQRwfH3I)f3?EMHR~SI16rMJOgv|P;-RbW>QAt(EVy+qg#C#t
+eKc6?rxvIly^tETf9H(Vtb}@LZTQ&@sfzRm3rCopxdEM~Z?1qDXw)qDO*m@G*{{-{@`|>IAB!=0g{jc
+1mPwuhx1^)Z>U-1x&Dg5JqJ>mZYy=8YK^A?N@K0GdYm*w{v;{o^{$o#tpL_YAA6+z%_VOYJBgkp6uc}
+RxyD(RWWy6tejtxdDBHY1{cdx1hALw7uMD%{JnLWTIojNw+1@X^C88Dau9si>1mB^b|^P^FKgFQf^;)
+}jbHbQwM0vdj1V_cHVRKEW|GO|uy2!wm^_a`nGW4rt)i%gN&r59|AcV}4YMn=JfBmu42oWiv>mg-6Us
+qEt>Jg$Q@^n6V=qL?V+MNYw;Mz9|t)#m+0xH1jTmrelLv;RCR!8y_4>w3>VKw42CKyC16wb*k8_`-U{
+}wErz0XvXxnAtl$z{5NxR9arzJWroK!%kTa>q)ynhB3Gq`pz+`b$ZRSc1@e^opP@d;ZTSSnSsgN<VoG
+#t?7$0Ds>i*m;aPWq_O(3*>NL~rfynBCC4P6<G30Fg?eD=Jj#lVlp5s(ceXx=ex|1x08c&yEV2%_C9|
+&lQWGK0=9;SnsS;_g4ADo^=7lRh&_r{qzXdWj~psuON33Gy<S{@NKUhieIg_kW=fl~sGL?6oz8HlWDC
+5&18Ce;Th{J35RxEjA)*F{^dzK3m`v5RT6xXh?HBhxWc=lj3<cO`NE!#w*cKVt2kcB|FpDDtx?yodig
+bo?%9Hs;kh+HL58X(r?aIY!5-hW>+-cfs3)0wg*$kN$M&XQYeVP0BqE9*M<Ig_~&V#B7Hr#qhfuRI3Y
+=!^rZpE|CdvQQ_T9D4~a@kC4KG0LtwZQASyu<!j*GSply+!W%>z(hdv5YF1UJR>%w}^!G!e7h8#Dulu
+`YhK_0Hoo?I{cZ!7*J4|3oh4O%{TU<o#)$K`L8izrKX$a~sf?0}8T+@=zPS9yWpUK5)Uk0<}mKQ2TiD
+2|7M5BdO-la2FP>Vebmv)892(Z40)IW#WWdaT*o={-N1OM>mZkS>(&ilNSA8H-Fg0<V$(cI^?TqTpq!
+b~YE8%*82aTdOJgZ{ov$}+x55JbT7=C1IqdE`+Ycsz5DJI1`#4!?6xoJS<S<JKxrgO*T9j`{l%PwVk3
+dUBrPQ|8kIU61>`7^(C8&aEKoSiU@ps#-qGvrlNmApR)$O%CAP<Mnt|nu%vTtioHD7bF<RMFPj@zsF-
+aLn0$^j{*idWt!bgl8Ekpu&(}KyoBKi+>~zH<o81mA?V}Lqj_9eWT$z}#B-2O0v)aKpW~xUEaI00Br%
+?o;<ucQq_*HuUOW;>*CLecnoR$-cb$iQTZ%k<4$>RbSwuQJd@U|UyvFx80Hg3?gxDbhMd@&o#Dz>{42
+uo7)ld?)$Of{bQoNjFG#`RH46o#c0eH~@+wOEpe9rA5Cl&9zBtzvO?{-(qI&h0Y%{?X}7@%8d_dK!W;
+$9PeN$q_Kf#X1=bn#enfLW&yPIp*8Dbi2yl7^;{=)_MNi-X6c$ObYx5u7mNS{jtDXvZ+zNnG*sYx7K9
+^uf7Bc;NUxE=HUp!LXLp{%AyJ=_u`*qVxL3OG?}~#7s9m@bh!y`9vHJD;_a@t;+RH#dt%=yudXi#i=!
+0VxP>!1vAKfKue^5RNo2e5)`^bqxvgdRz{a5P;Y<^<=Xe;C)gFPcX=hu0WN~*y4d}*8CN?hQNF9HiuW
+|&;b9yDSC@wl8Q1!}?#{Km6GJ5T$^(eT8UNaATbx^L*1y3+-HWr*4IcgX?A`lIc6D*YE`K?>_~sk?QV
+;lchciAR1{?b*?>rgeeMmR*&WZn={>RUMPXGTqp8gkO%RM;ncnI#{el@i_NBGSt(kU`0C>NbHMeh6B^
+ZQ<CVPfYOD5^&{2q^_m;sl_{rUR<D1W@%ofKGBOFv>><Qk@uAmt9*67jmu3pFi;9@0IAg^BoI}14^1_
+@BE>vC5~3g=QR&i;^|LygMh(=ynCp2Ma(@4C2#Cn;W7Y;d%+z5f=2<^ljInqfgJjpp@3Hys|Or~5$-5
+ez2JSw8j`%Io=#?VO3Yi5d;Z1Ao<0kjBRXT_X6d<WzmB`78ik5pOBNLEl*rLy9fI{2Wh_`a>L~7ZUOu
+N_cPl}%pF&9+q2tQ(o_}5~aL>QMjSG*#n<@yge?&(FcZ0_NJ`B4)IuaSb$r=YoKq+~f3)i^n+S_UP3u
+a5IY%e5H{pduPPCCSl0s^T&>;?qCm;iAFEsdAPL4!7~!%Lo<-G^<nu_v`OSkw~op&IH@TKLo0LcZ|g*
+u~uKelhOe&>gvWm+V3=kB^}xgUKhd`R3pk&S!rapIw8~%_nQkn}b`<?bZ@*eSW_H&nKMcqvbqzeZJj<
+@wHn|Ip^C;Ij`gX3rXRRTnfjlNugUO4L^l`ZA$*aC9<=C67&qL=@0!Odrn`v)n?|`h)Vu8mi#z#t(D<
+!e$YQpvp}IZ*#n^^_>cEu{yNF3<OV!FegR`XryDY9BY2@b=UYqWFLVS9dnS%023g|iR{Wlqx-Ftmo>j
+^Nk4anriR?T5(+Zs^%HnAfMSfdc!jw3M{;pVR4s4{?D~QK~Ef3*w285vZ8)>nC?>BC)w%_=5gvecbTa
+XK7R>b#TLuLzqDJBy_%j^@3Ph$M7ap-(y=D(7{PzV=xhMdsviKcAKjp}}#DO(xQh$A`(A##j^|8p`S^
+I%ufpkao^?~`qAg^eRW4~iO7<x%M8h453q=PR&def+wt4evZBe*BZ7JedU#sjmQBd!iISr@{)@N7dzr
+j*Zms-q*P7qZa|qr``6`1^f1O$bMXi?8SP>UM@toyB@Mv3z2QTTo2oBJ+_5z{_+7P9Q;>pb{ZI`b{n7
+Hig2%Y>sqNBAuBtvufv#E38rWYU8!n#9E7v}3?rjg2iA30j2Xe&D-X;GtENn9l-T5l^kdsxf7o=7%B;
+j7T@k-zd4ZU~Eq6*|45!XXIkep$eB>`}Iz0?Vez+jfS<pjY*`Qked}d4DU)0gNMfEPUIO=I<KB<(SU^
+hBWv`@P7o<l2vPx1Fx_VquX#8rj7%DUDe|G_Z5ee)e%k6y@qJX+tT!wrbM<@C6>9vVRBRmL?><BWp-A
+vFAWc{KLuanoi(uz@vgOss?9I>Z!wbGcmc;4fwd5(Nm_yBwyYeq^xjAWGc=yTIpVtT+Rgi;2E_TMP~;
+|Jg4Dloft|jCm<Y_SHiRJbqVuL$atd+P@q2ogAny%DjR5_sBZt<WU&U8K+Ca$aAJy-j+gc`OF#=o$Qc
+c3>zeY`KAor*-O7$gE<TK{e9R9zgJUMf$v+}ua<3dDRBM!9NkT*=VPz&`<HM)5s0Rq-yVaF8V!Ua1#z
+&vZo$%L<x)n+)Cmm-lOJoW5@XcH7OTV*wXwu1F+^?buu9BOA1ka9BP@yy>h@AzHSm5PcT?lERfly|yt
+^J=`T?@jg=Z1#kiGViojAx=*{YFaW^py+S|qhKy3&k666(6@zWPp5_u+LHFL-OU0(b)hX}w*J{$YCo>
+L;M*u~@%vqxXmTKHVMftcE#aUOqEDUC6s%Q^-eOSIEc9gxtqp&RQ;G)2qvbpVnTww_or2`7=I7rp>!H
+`$WH2ObygJ)pv`dQ3LXm59x4cEFdq^psnR*ETB63uId;EMy!Mvx(Ik>LmXV3>A!CKP1Wk@$_l!_80+U
+?7P@)hVh*1)H?{RV_Lj$;?lhLf!`+!z0r@W&WD9l~Y*~EfKou)%FV^Y2b@!`(T(=L`-5h?oepeo(S#4
+M9D_-sEbI(OmJDo_3Co=zCB%+s?uFU;T@uT5^UlXp07*x|djXl&frms0Icl62vCCl=k9yQXV^^f1_L_
+bPI>X^8L&V?PTDEfeAUS2OA+C<979<gRipa54FC+~iaE-ugE&%xEnY5(XPv(e6ebAvdJ)%dA*B2(;RE
+bR2K%mw|ejsFKwO9KQH00008031s8Rz~4t9%cam0F?p&03rYY0B~t=FJE?LZe(wAFK}UFYhh<;Zf7rF
+UtwZzb#z}}E^v8GlEG@jFbsz8c?yxzTbs1qE*lKCwLJ{V7<BA1MsO3Q5p(Qd%Y(fAY^U9vLyW)Zmwri
+^!Fxv*T9OF<Y@CoFsYYe70jC-?z#Rgk=`H9sUY-U~`{OW$E#L!<C9Sd<Y>L$aglb~g^Ko~LDd310;o)
+Vwe?9Im1yy85Yo2m@2L=aiiM1JhzE&Hkbw5aCga%oVv_+Oxm5{Qk-~m1}@K0V<Of0dg^2HTc*Z0DVDR
+PF=>(696MZ$5XO-iu$HB)dIPKs(hjE2q~NB9-|UF>*=xgXZIIFmZ(S>h^u*=mE}m?SZwjm^G|-hhHhg
+EmN_>k!^C5B9z+&%~WO6@D(|Fb<+j3S>!FL9$sFH<4Z&3vj2EkPRH!wJpbOk!t9N;_hp$*wD%O1;px?
+{)4WGx<?yz1?iahZyX`QZ+y8~Zl!P*!FMzLC`<oWgjC6xqPNxhcIjVtFt<6(;ooHT3s6e~1QY-O00;m
+aO7>P2t&*Vh0002-0RR9Y0001RX>c!Jc4cm4Z*nhiVPk7yXK8L{FJE72ZfSI1UoLQYO^?fJ#4rp+_x=
+hovuPoOGW#z2m_=deCPO!+7&lQGgB=A~F68g)IuDOG;vUIYx<|MUHb8G3LaJRf4xDXq4A?;&J7kanL6
+Cg_>a%#7Oq<GO8LQv}IanIi5l;0(1!nB>*mLu`&D78!W_WpfIlnjOb>Wy96UpM8E?}G}SRtO1Ur!7z`
+N^RmbSTEUP%G6ld8oBE-xNh_uzn&IxKof`!chidt*ceHG|g;(1}O-AvMO>-TtJB48=eagEAFNr*%tA;
+<o^fvN~QfSS;HfI=Kf*-e5f|C+ZU7_i`+d6+F}*5rYK;~QP55J1i#cDP)h>@6aWAK2ml;P_EsAzI%9|
+q007`D001KZ003}la4%nWWo~3|axZXUV{2h&X>MmPUu|J-d2DHJb$BjtdF@*JbKAxd{+)lt6`rJE3PG
+e^wl#55S&?i_Wy!Vdv>8={IRZ!WD!hV+B_`wlz2Dv)9tYC0+~&t}5}5$@_V)Jq?SeANv!Y^Q7RMs2WR
+{jAsc+5eG_0~LZf|7mw?Z`E%BrZts=ZpZBzL?>Wx6Ow^CC-FwaRh9%(JsgkNqUW%427hD0r0>9=qU)h
+~C$EEIf9ZlOR0yn7T0<jh?W#t7@60EXqX5(yU^6k$serV0p}|c~&G$rt}Y|m5f7_dOnw-6luj41yAdk
+7qVKhDg!U9ODj3Y)lx8CgiBfB>~$enHdptGIwj$mxEEnv@mVauo|Rc5SjbCJdic)n1Xx7^CrD%pf{I0
+}lqWLealB%)6|}@7;zAtz(rJx!+kg#D6N<9*+54p|S(btU&+}Lcx?txrt?xZ{x0K<M)!1LHJ~=;SnyE
+huV_udlz^zjmi`Up#6o(^*&l9$+s=Peh-WI8UCvRmgBFX)%SZveP_DOrhfTvM_t!~xDsp9;E*ab_)Pq
+8x_ouwanEF)___h%m0;-o0DVyyS3kK;J)_oEbgPz$y2SjseSxJ!w{)M?~fE7b*PgEvR7&W?kN4{u(cy
+kjre<o@aD-u~Y4-a$ige13FwwY!67Q|s2j9&YV4w|+W$f3$Oc^|DW<?!8g>4BeYx_t^n1cbm(r-RBc}
++&({g_XgK{lji!L&kh2$(}5v5C6eIi<=LB~tG_9MPfsW6Gk6~SeDZEz5lr?s6P%u39=#7<AHDlYlhJ1
+nWQr~la~1?Ll~oY9rHJRAQtKgN?0UAUM0qo2TR*UiEESziXi=T!JiK-1Np(m;tf*vKbwu>3ij{pst>z
+VnB(#lBF7E0a;KT33QvN20=XkuftPo`#V>1=f*VxKqzVF|FlUd(M<f%Pu7UDh>d6RE^L0+~lTES&024
+UcDc2=8vArStlk@0$RGislbPJI!mlo2F+Awx)PM0I{Rb2>h9zKQrxFZA7^6WhZ7SAtu+>A>tnd-;H5n
+wGLCvfA&BcqW28X5Bd0`}9YPY8>b>k}A@npiK~Wk~Sgyhl~1A6eXqX&C*(=S;=SeF@zxd3br|qtYCZE
+(dpzLEb-j={<X7Nc`shDq28E?p%&+d*UpfYRIJXvp4HhJt6vqXzkfZezpt^%Ndb+3n|-;*uPFqIT_em
+;x4<K!(|)7KH4`Kp*dToj<(fqsf!8P@bg^2a%h%}gWj3Ebg06fd-8|-t@-gx)DTzPg$oUdSc{FWWCy$
+^jzk+A^Xr3q<X>`AdbTm>0bRnt$#0KcNsu(sP^xDoJH#)^wmGMqiOP1v#bpe3=4m5hqDQ3=?5w@{2Q@
+0tUvNv$&`UIxnxtCW8QUMFYXU*5gq_iFeGu4eiz^HfK3DM|5mO)HdGvGzCoNGPI&;qnjk{8j|JkEfxf
+lPpfQ#KO{1BaD}I$%ra&K%E1)P|3Ny90n)R=~%hA7x?bLjXU_l5M$^Ks$Tei*3#!@9vJDNAuCT3WpX{
+B*+y#DgbL61{pP+a%2jl7b^c?*R5L5GrebBw&^ebcH{ac?b*wl<oD3}HVN5_6$l-ybKA379CYY^Yc00
+`s#-Q4?qFloKVYjKl>O3<14;{@t$C|Fcy=&!*8jT)dYI4aZplB200EXG<W%oBlP-0_T{F<B5_+OXw1b
+1V{P;9>*0i*iI@VT_ksey7jo6o1EhXUR+^hD=K|bYlQ-96#u=gbv^tD8zcJF*r6N9rkTf}k}GJ)dE!X
+-}^=$vI$vV{LTE0`(S=&J=w1=3fQvD-AeL!XWOMo9}ct-uKFeMe56s%igq{;OpiDQePYj8w>CSyq(yc
+pNvYN*{dCQUlB0d2CT5`E}bY<zgwY#NH>t-3sZ|L-{D{L=713WE_JLa_;_wunj|lS0SzX>@p1nn8As8
+Sk-C*vE(^Q5`?XDc$ZLHMN-Xpc(DQ-RkqX!L@i+-sekuJ0etp-@ap{R<#F)l?Bep>p&HicmJNTXW$TT
+LeE1WGXAx^R=E*GLhY*iys~Hx&I+wHKpY^faZq8#0lrqL4G1ix)1bx{QXEI^~umZRz4h+{#=lD7()wp
+Bob2D~$TgU{brO8t)5=5FF!DPla25ebf(%-D~4S(Na_N4cO^2M*UgkCwD!8CLD3f!!Mo3W7KW$FKPe(
+tlg>d&xA42Oxy=&`&N@yc+6!@-oZBD)n3sleIGQdv_?fv^e8wph_lbqW7OD3G;KCesLo7`$c$S<=+hW
+)PNSQH^e4P+S)<c0E%yHCLmw?a=%?i?iAGJe*IX$z*pn-<waSlS#M@qir`l{e1Q0eEM{M>wNlbcOC!q
+_2N3mSHY``4}tO@6ppL2%L`y29n(++GpZ&{Fh@t|jz4|sbd#TfQC@tReY+G6CyHvwLF#U|1wix(Jl27
+Bo8B+;SXQo$!;TbZ5E%@1RDpI@R}Cg>aoWZ)n5CjI8GFMyl#u)*m$4c-x}bt{p#fBpIre>jm_CP)&Ya
+`n&{5v`#mGV3i)TQ~Ul%&Y^({`8ub2_Art2&COg%WU2Rr>^8izJJ93#41x<95|A&OMxJes|hEQ%Evzx
+Z%|K1TXXBSPRR{iz3rQNqy;ED%q8g(T^qTu_&ta!R$p0$A+PA{}&E5CkFOJBk&B%D+p|azl6m*Dea4I
+3|Mc_^K%rC=9x!$n+LzBFfa&T~^#u7MRP0nm*T+;igBuDmJpZXz()Yr+1}q6Xj;rKLkr^6cUwgjG!uG
+<RX+v@HD#yYf<Ri{pq$25N;Ut2iZ#Es7GuLN2kid5YpX|lC=4;eXPXx3@1{OxaZ_T$c3pcQKiHgDph-
+psm7|bF`*+UZU*NWjAs~`@FFI#wk~_|%A-*~$jhq9j_Qo?QIbU2uP~=Ge6U5Dp*5^%uucnF#_vf}#8o
+sYiWiHT9ABqjNP_@2FFY)vsPqF`sP;$M3?KtoOnIIxwGdE*&@V3F<x1yOBNBC0U=h(UywGam=}Mi%Lt
+T+E`3CJyfTC4cA~@3NUE_ab4&^2yYT(HXOX-y4LA<I&l2`tEKpNi)$ni_G$JBbS#aKU3&7mI%Qj7m0t
+rh(4=L~GIwynR3u)nXJaQmtCYL(2gSiKuc|6GBd02s1ct9XU+xG{inXrq43L1nbf+12Rxn3TUs#OA%s
+XA0bozpu04rnNpfvK~blm4^X<Y7yk4K^;`M9Aulgm_h{zu-akU_`Ay*WG_+2RxOHGgH*UUA&5}8J@%f
+0{hdyGkL>CQv`3!mI=l>}MB&{~eTeR%3iMFvd1th!aY5rQdYwmQlWfwQMduuCyQbJQeZ?10BRD-=9h(
+E>yeNfD>JIIq&eMCZK_Iz3(OY6*pU2l)L%K#{fx{GHA?|ZVhC$||>_wVZAOrw0<U|DrzT-$m$ODlqLr
+NJ)68gx<GsryuuG3q>pOtAHC@C>M*Qitsx{IwXor*Q7ZWXkfAdT=UT#9HLkwbyfv@mVuXD))(r?-;4$
+bfDep3QT`N4=)B?N_!Tu`}7)nN0Wm>C_qf>`FjC%dOr0XU}ZlK+`=W#DwH=3&;KO?f0r%_~Cl8_59{9
+<A3?;79Fg)<#>HB9QQpx=?(16%W0p!bdwCV_sM;(r&+cOs%B|N1r|IoZMsNb?d~}?54OmvL-tMSuy6X
+}cox;WI;~_P{-I^*o{fiTXlv@>|Gsy_!Q8}O6j`0Sj*`O}kG;Wd5)8ND$bW5L<@<3_2O)=f;o<G*)As
+Jqd$XMtJ`>xG%KOBho2|I|Xja$%rHC7==Khpw?c0;LY=64zsV@hUNjnzm1{*Hb7Zs!)Yv&uSj~v>~>0
+s_ru1YONGeKHx$h!1CqNV%3W&HUm5=zNZ09F$+%8~yCb?ykA0C;qzMj=)Qw+TG=NWm`6e&vq^((j8}G
+-5A#2~<$H9XFuh_Ipo<jx|a)Gq7%zziCZlvFpiAtL^LQjW&YyzRz&%wP=Hvcv^BYi>qnZ0;GSc7Gb;?
+3?6now%<F*7Zou5j0T1>ZBj&k?JyuVN;cj38qttDC;x+VgXNDC@ab0yxc9#axVI)?-`1m1aDMXY==hi
+5&C$g#=Vuom{)umI;g-KQF@_X<dBvWxyKUCZ7?`V4#`EWzWpl8B<c?=EIk1@Q7$#4rJtjLtCX*qP{XU
+a@!(+PJ@z}RmOtJox!63~PCaCzLbk*ZwMpK!q`7u=wQJK>B*>UgMOQNQ+i6fdwYI*gTs;qO$D=3VBD}
+WzroR!V(-%lZmjZ#ha%CaDfBb^@U$2secbzqN*2lHMvHU88G`<E%h<86AN8{O<7S&cyZ;||<^S*ATL5
+_;Q$X7g<gu;{+qR1)+;eKX<rff@zBVAmF_o334_uFZ^hEy#{GzsSl423zy$ayZ#5(cgsvNJgk%b<OI<
+Z|J4@cDc;%0$lmwLjEYD7dv|gy9d_1;H8>f^LAhjiDgnJHu5Q{n^dq;k20D`XkF!XWm@huOKDnQO};e
+~)e~E%Z$=E+T}sxntwCrbjBC~X6B9MsN$3}A#cH4cs-KObNj-3!f=2wVwVSUWZZQB2jWv3msa~ycF|0
+crdtdjs-wYQS+xiMPN3QJ}y@g(X7vmm%$?r*So2Qj$+ehXg$j!FK^nE+OVzc&GLu$I+64P%a?4|lGMM
+j<TM(1my&5kf6|4A>xhB6rNIyk#}*jlZ3P=%;F1_P^gM(BnKo7Hc0W}Cp`gM>;yQ|SQA@1O9W<Le&?x
+Zhd(*h}Ra(gZV|kv&_!f$a2INfFcho~m9Ukl)dbJL(cS4}8W0o4oF3c`=f2xME$Q@R(J1?8`mkR{BH9
+ZT-Op8_Vgs+<Nmst8L?&Ym4>G8i#eYbvz%dy)SC8V>urE2T)4`1QY-O00;maO7>QrbTJw*2LJ#X5dZ)
+q0001RX>c!Jc4cm4Z*nhiVPk7yXK8L{FJEnSb8KvBZgqGraCx0qTXWks7Jk>SILkaN*~oD0*iNch?d*
+2ytTo#v&c?GZvWA98P{Nu7SpZC=X7b;A4giXzFKuTz_J{;<?%%l}ilXbwYq&VS0Mj;2tu32OZnn}uRp
+)IfKvqpDDxs`_vfjuHYz?`vBC{Y1uv-CHt2OSId(f>?Qf=URZ@0AqX(pvq_aX<r;Zhk3Rcp#AaFxTCE
+%%@BS!g5OX=she*(8dh$pposE|AsAik&Uxx?3q)mD##3O}9`tLUUW|!}noFi|)->-DdXi)vg;|XTls#
+n!TA6x~{<P8!{j)FFs6RVLkgPyyun3Z(4N66h1T-b>?V{TbN8HxhNpjg6C<g8lIumaWO*<%k|z0vzkI
+t*%>L4z|r45)lw=u1;*HFHUWIJu&q`>S?1ZqNQShGILBcp<7H;#uY&fHB<X}VTpN*=c}i|g$(&S_#Yh
+V$yVHG%?1E%;`Hw!PE+pvg45OWKItc4M5Nq-ag*yaS>_paDzAgm<hIstIF?vv|8Ema>%<TAhBaLMnX}
+9f~Wp#C2?v2Uo{J1zjIe+s#7jN_LUuSPG&foC!^NTYsitMx~)){x~E`NFlTQpkeo}m_nX+&li!m8aBb
+*plxBCGZ07;Qb?@U=X9d7N#}nDE4GYpb%e(ft<82yq|3O5B&#d+!2zWR5t7`J*^aAv(GEA@USrmx-o>
+6cbw4y5|r=_`X)ctzn8drpwvc3jQ(&OL33a(e3U{ffh!|4B!PU)MsAG94d|pHU(8%GM_!mHJI=a4$;-
+sB1)!kk`U8R_p*UPVhSUu5waD}wo(b7ej({X=tfR>0U~u+eOK!WleDNcV7hEHuR=iB;B52gtU(wNY@R
+wR^Btm5<p>@_g`|+EOOtv9o3t(pBdpgD8Kdsz*Pek>Yw9IVJu{5e*TX(NCo_nn1wL0-R}qG75gvSxU!
+iBFaF(ElP?^`KM{8->i29VMKYsk!Q-5?%pgx_#d7!>H8&iK<`Y@lZRzr~dTkJ1?A0VPMqTg-OjUWJaH
+H}FtDqO-E6o2O|PJF~(z&mms<s%jmp&R5Ydf$@+gCvQC+f`8&)ExyoouXTtEjoTm@BWWgsNf@}{D*3*
+C$qvu<p0PDf{8@ML36bcaVO#>BDW_BAP?%{=0Gj@4rFpTIkL#R@gbr*G@%*J$MIuh9Ild{>+f3hlvVU
+#zI)-6?5|yNzsGF8zDXDFZ!Z6HJ;ocw1uL0&Xmh7`ugoyW2oJ*wlZ&j*u?P6p&>5H{3^kTb9NoT(lA&
+G^mG;OL7xesq;U8PoL8+&iJUlv?WF<ES(w|Yve|>d{`;HmnTJis(7m1Pol&bq2^)T1KLWzp&);8^+bs
+pN+P*mt+*cY&{%wee<#z<v|Rq#mCuX&!#G^MnTCQcIaky>?CyA&#RI|=*^P5}ws*Yee>E9Ksw&x4#&M
+hk{zG26yE3W`E}o4-tMnft-I;<=uzl1?zir+S`i_#V00d3BCnj4QU$b=$-zRHmGFN6V*vTKLCdhGL~|
+(+nGfh!Y<G%#E@8`#%5YLeP&Ahq>^mn+x4=fge^@;z0{?BPaglXedn_s8V*{jU3eUWg&6A=(YJPp4}^
+6;Y3P9CLZ-3RE29r$l3Q1sXo^SMrBPsi8_x1nk$YT3l1B+Q_8U-)Tj-EMKPqM$=FS?v=(T;)NPr=8Wp
+W8VYei$l=osbn;hcU&sFj6?L~TV*5_u2j1zXsP7kX;2IH<n>;1`zA5Ah}aI_js$n0__?I%k^V*=cu{`
+fk3zDgDdP<Mt2O6)Xnim~|&!;XDWucOC>@x!OfKUWjcHS_1E(-H8?{CVWl$W9s`hIfWYikD@Mv$e748
+$BQFT`#ULr_d@%5#?p7#21%p^BdiYWRyxz)Ewf%JkxHxZc1(mTB+q56LXzy`+Vr`2;+(RUqaEcaItq2
+D-bP4tZERTYnsgJ;SK5_Bjm&kHN(hzS)aBY$cO@W@TSviMVx^b)E;R2?#{_e@9z510*7b0!=B9$(sy?
+rgm-rgGjDi4oFkZHId3bvyy5GRjTXPO(%@v`a^@-h$*%Rl?xWu1&NT0QGlPH9h~nKx1`V7ub{iW(A1`
+b!VuY+mB?~uMkKY5p4m4;Rp~`jVaGN3Ug>u46yvaUsZ+$q9A0`=BXZvZU6T{s46pl{le=ykWrNBTI(Z
+Rm-YfnR^{9F3f(c&+~{u^G0C#Zj#qJAPxVUEowO)FF_O(SPTqxq)dGc*Go_&Jn`{%(tzUC531JjIC8s
+9R;^zAkXFcNRuoXdh0@0)(2OQWHl$m~_R6T(;6@6xeENG!c=^u&vQ=GTb2RXyXr~HKL-x6O~Z;Jc2OK
+IMk89$0>=u7V{rF?UEg>XnIeB9=^@T(NRQKqva7c+d(wEBpYPhD!+=NegjZT0|XQR000O897^_9Fr)I
+4U;zLCmjwU-Bme*aaA|NaUv_0~WN&gWaA9L>VP|P>XD?rKbaHiLbairNb1ras&67QA!!QtrcmImRSsZ
+Xo=@@9CA1MSvmV~ZCvCp=OBDvDJkbhrUPKrO$!DNXR+48-QbmH+0_NB0p3yI+7tmYD=NKskLpjH_gpb
+~-594+YFzr0jDb<?ITi{TTE6<P%|cuXE*;41TFue<k4O#(Yazqnbyt+u<>c|+ybjMmh$-3bg<+6vO<<
+aoI@km_S4kq|N@E~HI@AV?**7S<{kO3-P4s&E;A8yV)nm_r!GB8xJg!{Qk%nf7xt3{q_rgqLs_bdn{v
+Wj84ljgn1G)NIj~&AWL?=X4C(b!L{J4_}y)haI$*BiaX-7JCT18G+wZ5yA>(iK`SNpNOG}Cye=vW~|p
+_F}caTse1=3CigfbC@jv1UN+of!AbmJSB-E)8&)}^E|2ik(<++(*>(***}BD@Xg9pi>DCPicPHKGx0r
+6-2=R}0V<kF}j$}iHoNU*ua?<?*P)h>@6aWAK2ml;P_Ev5D>OXr5001W;001BW003}la4%nWWo~3|ax
+ZXUV{2h&X>MmPZDDe2WpZ;aaCxm+ZExE+68`RA!Kxo3A*#^s-C_$PF5q^(hhX!zNg5o^Fa%bnV{K(oO
+HoO4Y3{e*3|}NtlG9#s`4CIw%y4En96mF8Nv^kfO*VPK2>h-aT96{oSXr|*Y05PdL~a?8OzdjHH|k|x
+(F}f0G+9h;n5c7JPF|9qlGibz<yw)wzxvhEB;<-QHF$FTVR3e~FbkGyOmHr>Y|uckir2a1;sNAsxF8w
+dRRxobteK>FQ74m0zN@$ZmWl}ql<j+MpQ?gN;N98x`k|g|1m6+)Q03(<F~jrnAtoPaQP58X*zs$g$rx
+0w;s1Fh!6aJ5<hrSF@?(i6YAID-CFvb2*IXpkLq);-PH0HTOH%T`=#-qjee=tNz~66N+*7fR)yqEwZz
+}zGl7nNx<FqCxdgKCxvBj5+sr8+)OIA09to6tr4VP?vB?YXjNB+eGKNqK5F#TSuxkb5lU#}z;GM+@nj
+HIqumTz*{KCAq3c}I(UePt(N(mqZmX$r1NQ!*n<B{VS9r&N4qBG4-ZA0cQqdCArvVB@IBYhDhf7Uf+o
+c)4SxJfk~i=Y2syOTpxnb;K~WnoQ2kzJnrm^Oj4nFh(<1G5N%K0c4Y`pmj|=CBqw9G;ARR7tvHN69np
+aUP3r3O0rX=<Q{fq!{H3Xq^Z$I^_Dlq8X|Oqr-GA<#Rd8K_1mPCW0xFp!FMgJ0~+>Stxct5y9)N1zyK
+w8C;-j~m1NCXT^>MKH<jA8Tt1^i&)3f=LQ0tLEe&RVVrc)mTN<KU67~ho320vDYi1IIlH%;vP^mM%W_
+nRjj-+W`<}yvgniZQ^8#u*78If1-fVMQWDu96`(Jq*2%84Tf_T7k4tnk`#3MLy-;#k-TiCk_-Ip1X81
+V@jGJx!G<X$nv1uQYuM57gAtLG&)@<U+{gu&e)O`vlXxW?-c}#{7o<g1y3RX}xs=p@YF4qT8bB_e=II
+jvRqt`VUIm90c0R;GmUvUi}|byP01e&)=UcU|&O>6vH65E>WieQmwjRf=JDOMGBkY)9OKPfyC!<DSNV
+T&pbhzf73u}du|=U3Px)-I`<sk4(>`ghNE+EEx|b((Pl&-(59Br9q0AHBwi<a2yY@tQm_8@_n$pMNhf
+HO#7-xz9?z4tHa<_bXRF4U_R~T}=2@c;3<R8PDhUa{CI!2t*+VCSeUXB8;vrMR%{M<eo?k7lAlM#tcC
+yZzlGc^x{_z|&CH@W=nt`XLWEd8GTI(*C){gaQ$Nk`Pj#F4UKg|Br9?S%MtRTod!@01ayH9IM>X-mJl
+G83t8Q&(iOonp#8g63zA4PD=Zx)wV$LDA1htmu9oX=)6*r2ca(LTLvpN`t67wyx3I=Yq&f*;m6onQXG
+xJ=J+1$R9~gI88wS`K{b=)Ywkq&aO!yT;A@<Rd057l(zxffDbH9RvrF$MkJyVv4rQy+1!cQTBk&0IRL
+~Tm-HzmuRrfqF;%-TuXI)y*LFjg*`)u^N@6IJM365BbV`8N=t;ut<onK^UKAVRyqu#1W}4$bsa{NOJ^
+$br|f!*e_o(H1~G@N9`oySG{80It1-tc*s8BY91^`)<Ox1HBCfnc2RDbt*`AnIFId{a(1W#FxD6MY0u
+>o&B4a7m1`O^F#O|T~si(S@SbDHtl^sjKKC6|wHQQHxcjg<Y&H!vlT4u}&ioMDp8r-tWQ7!UFl~p-bU
+q;YMBe$Yv0~v<GnuRHY%2Xp{eT?<9HA?BNVYn)smIx4Hk|fE>!t+foYIUk~g|$?09sGMO0MvDmK?w(x
+!4Tkfw(I3$5*DgXle#(sj>urTm*k4?n9O$oRPPzt(mMv|83>vTEMidIer9C3M2%MDew$}oEPR0iHV|u
+4xRD9UHp1?=Oz6_pB>;|GB7%XR11OB|OU08wwV`ox23P@?zo#YO^v`)^#Ho6h)m^>2X-ajdNX<1TFs(
+VFdq|^1-C-r;O-;fG>i`S0UlQI(#NLUGkFedk5pSV#QA>aodcjIF8<E+JyzwRn5>z&KT^?y^!=UShNX
+u?^#}8yry-rkKmJF-AurJI6&+In}v8v;EhjDBS=>%*{l(i#{h5-qZKY3n;YMGA7kAIgT4B&|O*l;8Y%
+)uGAN;_)cp;pjxmvne}V9hGpe=0Qv9Lm)8Kp?AN`$Ct&wm@EWFek@b-{kFL3#mhFfd!sa8rYh?g1sj9
+km^~7{0Jzm21z09=*$~79SOYQoniKu8GhjnmzMgSH+<U;d!rI@ib+ij3OjH|SfIAb4ZOlEWAw)ifw={
+<jrOM$4^Dkqu?)P`c00nrZW6EDT~g9kCi<D`(+rv>ozx2Q*Zy6^HIs}3=7P{cz0Dax`<(pf?q;{&3T6
+4aMfQXt5vC}=gw_S;SZ`v}b!NyTuU?2JOf`?75k6u<cogb635<%y0$eDxF%k`X4|;Ls1&GzAU1Zjg;M
+K1;5DdazPv~?I+@RK%2LkkNGuztI^bYhLq{!O^&~0v00{w<kV$vxznw*qOM^LoamHifrmqa$fBQA%Y9
+5hb|25qBTKCX^IE5Y}-X?%1654_A|$J*o_i1ijc#N-)g_Kw3XVkyh4{;7)@-M3t>R$330qjY<$O;mN~
+mmj#UhkoC4DReq6U%go+w5nLS4)=M%vpjN>{P*Q*{8NF=bpin|*re-{_`(!}Er)u-jKI|Pu*SkYMhe@
+Y>N5+6Sy(cUYIuS57cEBl`qIZ$6P;?`vnM7Mr{)wHH|p2uxl7l?P#0xORr<sP%br!=`-Th<3{DTN*V<
+XlmMi}}(efdrMG+#VGq6~pyVCI4++<*g+av-Qu;IEZkl3*l$AVsF(o^8p;PEw-{(o{vqxh7U?NcWBQ;
+_IIlw9qf&v}Wd5(g5~ek#}<D{QV(^DjU!Bq3Tj#@jUyXNm^Umo8D1Y;$8oUS2U@aJ01}jrUL)<>wDmn
+cOL;Hs&F8jo(+WZ4z@+4LfsKW(~P;##Q&RwRE(*Hyx84@8#)QH)xAPXZt~bICPW9nHw~2rljBB0kAMa
+Z~KT2y%`#(H$6g!T#t-XceeC9Q$GDj)6-$`yO856?dvQ(-?<vo!fBl)26XMwB-M?EXgU39<qGmTb5r6
+r?ljd?3r+NApuOK9Y%yyAhL4~;#E5_Ti-5U#FmsL-+`3bcs4>$PGWCj+1~roOzy9H8!G1-efQSD{Ymo
+Cc_QPCj&ZB++3=$Ki2VwZ7fk3$#jIbN>B})pPktxx?hve-FB=`)`|M(fESJ8P6{E?3`#s{NcU@SB+d+
+R}=7G3)}4bcwnc@G<@C<}sx5lE=<Y|>qYms%yP?~#vDP!B({T7*~Ls<~UpF%~!xdW*<kwne>)1P2DXF
+RDp_h+FGTsJK-<aQs5Y;d}`E4hMG`;le3DgtQ;+*9^bmEA;JsqHBq-fvC5h!=t~R14-5hfzuc2WRgno
+jMa7Gx~Y9OwC+U${vEwuTrAkr0s*ss4)@4Tnre;P?IOR)AOHt|(Tl-&OmH;$FHlPZ1QY-O00;maO7>Q
+6lR;YY1^@s=5&!@t0001RX>c!Jc4cm4Z*nhiVPk7yXK8L{FLGsZb!l>CZDnqBb1rasl~>zx+cpq==T{
+)~gUPYNNjm9FMyca4GLveeiz~^wRO4`95we+5qyj*(UC0041AwGJN}jfQ5dkdD?j9_57YAf^oeHu{Ge
++>AY-mQZbis1L60*q?#)-UUL^8e-q*&@fxTXvI4UAZad}LgtMeZDsUxH^HLi0q6y`7#`G69(~rY8seU
+No9UrNUg#@uH9h8y0Z3E<`E|eh0i|!O5anturPWNtmQ*CIZJvSL=dHh*n=h@-)AyMjM`G>1D8{Trg+J
+ixrV~Ypj!UeUJ*-A>*}#(QuavGOGq17%CmJX`QZv_y^0Af(Pq6g=S%RgdC8(_)Z;yU$0nQra9~A!5{@
+&26td)YIHq1Q+7qS3#Mny+=N}RTl4v;;EDPAlksBAhXpTz3!Yx3fSIvd`L5t*(zqVwi9MW3%4Ns#OHY
+Co<$vLjD&vRY<U=%xqt9oP4jJmTQc$efB3-7I?0{X-#oe@;2SIy2HEGTwqe75={)1*|GGX60DQ7E|OY
+bAiHZ0=2;C@$I>AJ4|4|BwT7RO=M^5h28Eek|nhirthMO+t~Ovx-&JQn0EIwQY6dl}SVjuQ^feh)|IL
+vpMc^b8RJ6^k^D5kFGl9F_b837C`u{0!bs!rq5yhHV4Sox6S@HtRKKLU_J2X)Ine7YAqIBpR6|ueHxw
+@|#P&@o*TLl}>YI8V&os@nBr;d(~VGOC#Pir=7F&QEzr0&iZ<v_S}6M2d?k*PovSS|E{kNdUT4#nxUV
+>+lH2BA^0GulClA?xr}hH2060A(`)MTVb>@eM%cDp@Z6lP80?BZ&n97G$#Kpneaz@f;Bj~Um0TRTzUS
+g1W5fAmpsb%kCFC3fFpUTOsp7=IHLNilADN|6;S{1?eb`6!mGmq$<$iVK(2iTisel2_$7nJIJu$-W#f
+xXPrFHlRF;^2Yf~$id4Iuw^j3oC{4f^j#<4M#Dr;%R+4Wjp9?@JBTx?}$tuEraW6xl5^zmlf9T6!3cz
+F0@9FOiM3mrP5*?~rdrnosprIz}8L=O^DNGQB*0M>8Z{uorWB6RUIr0^@4)^epN@b4|WiUZO3$whhOi
+=Y6<rFSL*X!K6;6;X>hg8C_i_l!y*N9+zDrgW3q>PUH!TvC@)OO7$A}@S@I#uJ8OW)$`{U&}JptJ<6<
+A&xbOTrJ>1MXe-i()z)TGxF_cDxKe`XK@A|9g?bLf3})2|rV(fkXJchtoqoziOzlV=*_C6<WjH#G>rD
+-Ut$St!^lff#P}h5poX#Mp@g(}=yg!MC$Q6*)S!L()s(b6TaJPZ8odjqT&MKCG*j0G6t*&TBtR6t*hZ
+5}yXEY&#F43E8xL(LpnWCKiO?7D}q98X|EJ!K|qgRY)cbH@hXsHkzMh>1odtn=8nig}jJok2fp<=cyt
+X4&>tEdhQLhb5_{;2LUuyU26g=th*;}dL^$}T~mQX-VZW^t{07L}$ks;j(41G}cNGf6QZ6PgOPuh^3!
+ht^A)WOq-|zO7iJv|BxjRlL>50h+MWahLRHt~irSpbxla=npw)T;anokA5&mAD9F8CRLM7?@vlF^Xo6
+w5nLBH>I}?D$ZIN3$f+LY3@BhhE2CFH6;gMku_7TxPuf7!jj%QYG~KXFw|HvuhiQOM$R~gkdRc4?Oxb
+pw>~k;&H!4z0TdeeL`PIV{!%M=JB#u>J#jz(?w(QvM#)iwT;?yTkUz1UhGZP)!Vt%(Bs2{efs`E&|?E
+?GtZl)X7R`aR|U@Z+QF!nWp4Jq|o9-0_ssxc%W&b{B`+MEShu|OU(|3~EI#S{MEcF8>pR^sa6uz~A4^
+-ysYC?YjE@EX{9TuY=&J%=u%>4K&ti7}5|_G3bc>JP8n=Qs8NZ@V=Rcq8FZkB^C~9y@M#hXBa8(Korl
+-{Sb>$?<+O|CMpKoYN^*=K;5AFw0;<j>ng`YqttUYc^*R^!uug?w+KA*pJX!F(}Ow+jZ(uhnBWSh=7u
+ohn8FV<P}}pcikKza6xJ!w^5C5rMq{tsy4Vw&2Tc=ud5!36(Z`hj)pQZQlVa#o?iu*nbvy9{K9X-)k(
+J7cuJ{iYz;MhE!u)GDaQ8HGy|2hX1%he9BFH`cUFplKV^o|i3GzfF}g%_^~1UHdtTqK3&*}uHct&=RW
+YD=h9z;y2`)y*4OA!T3A{8};#qrrzkMYo$X&0|!5|Fg_ieNXT`AjkYzclG4gPpdVSf+Oz9eB=^oHD5a
+_w-eAj+fK3HJt)OZNG(Z)?kdSET_)^ub2qOm29NQftW88-4reIa@z|_T}!S`<s0g54E<3L;tnw`~y%+
+0|XQR000O897^_9HIncK=o$b3o^=2KBLDyZaA|NaUv_0~WN&gWaA9L>VP|P>XD@SbWn*b(X=QSAE^vA
+6J^gdr#<9QauRy5In3QQe+poVoJyWUUxE;;7b|!Y?c_XVV2%acJ5WoVUXvT8>_O~B*hrPprA|0nmn`k
+DE2p;zK_V(*`_g06|o6D?@F0x!j@c;QL$)h|=RZ**Xv?}JRikeFmHLAL<qw<12JY6O!{O<)18%N)%s?
+N&d;4pd|KO9F%F{fc)z5d#aiKEv_(Zd&~&z`@0{ajC2(6g#68-@)SRBBn)SyNUUfOk<=QCeOvbJeJ5u
+9_sv>-gXxyIz)66D70M{Ccq}(xxo)+C0brW9LDo%x~+YDzaixA6!)Bb<}K@@FCLQ4G$vtd6wjPGRxJN
+K7E~~4gYouK-=f^2@vH^FS1&XdbMnT8cEKdzDXJwSMZ0|N{@N7S{g8KHcRzgqM`h)fLF%{qXR}RUNx{
+{gIt;vWs#*xp8cSvH=5`?PJc2ZU#LZrZuGv`4H`$wq^i}y!8iE7xqcc=c-AvJ%6a?z;BUopkMZNEZmR
+PG{Yftl-qF7e2ktk6aWpG|&nDh1qXV-Eua-<^fMFh;ojEJuDG^YapC23?q<K=;(P?o5l$yU@sx-UER5
+koA$ye%mRh8A~n20?X4Cwz)fo?oFs?BKN5|9eSY#gm>m?x?)%T+!HKDt1eD5Gzle-r)jj}K!D%1r!KQ
+mb~>Yv5XXJ^^-(pMLf1ukb)4@F#qf%mDi&ZD8PKIj84ybrDUc@OU~M)+)akMGsDJjr^8G9e=)6&8jMD
+5+xXf5>%;L6-|PCXa&on1oC~QqH^}VN}HI(--6O>oGAy$jWUwo!pIs#EOrpuVNI7weJK}}70vcVB@w<
+7-QeDlI@q$7eUVZB)ToT35>{6oYe0k<GSgkC;TV+^EwNCOtS=P;ivZUG^crc;b?KpOf$@w0tWuHsCur
+ZhR<W!~5Qt`D*8x*k3ec!k-O|<Qpfi$*?d$Lm26zt)z$n3Gt}kJkgdxaZxdy{9+t5C=d}9_D!d@U4*9
+x^^FYaUB=wqTRE#zfcs4)7VOMiacxA0F|f^cMoK^zRu^)brdSgz{W+X+x&xS~5a>}!SgHY;Ee84KP5g
+s`AF&`Rs6VKM6r)>5!geCk5L6vK4GmLO(5Wb2Nt)jM-F_xUahC7`t0J}6-dyh*Nb2Mdb^Y9L&GP3{Gw
+Oe*g>s!RBP0v<$>Z}gb;WtLuAV7U8tkj&wb45#&osCE1Fw3uf%8M;ZWigy$~sCIgDT57umq(Kkjj93E
+=6_Dn`M;=qDg?fK%e1tQyoI*imMb=mqg}4%f!TW>3&RpgS&~?(Jm+&<yZ=N1xGO5zbA;KTofxvetP&B
+@M9e=7Mt5w&!UJOos8+shw`+y%l-W!Y#9QKN*yc%+Y9LfxxxoG-$QI)IZa9{{J7{xF+TMkF#{=wQI3X
+K)G97eAJpz7*u$Hr)@n53y%Hj?h%n#4D-5;;!nDcXu&vkvccXmH`~_2dIhCZ2pzeH=J%z}|Hcf)(M?t
+WcUCmBVfd$rIG6$Up!BPk7Ghl!Rb9h2M(gT1}@PhaUicUJRh|0Ve!7IvL3IZu4UF1cMJBKYSd-VBKL0
+hes`gjI0ImY~Iwm!ZfZ0?=e(osuuRyLr`ELk9sJ^JUSoAwQTiX^b9yggK&{_AnoCLz;0$W*qJ6NQZ=N
+}w78KgmQA&BAK(v-w&HHKZ-{$FUyVjCFT5uX_hq{aSFiPD*_`6x>>6AjHMgTwuC+%1ZwC=?31O(=Ep%
+xcO(win{|iC$g=(x$Hl$yYLM5X6$Bh;>^AdpOA;+D;Kw<z7TD)>)m#4WHOz{v4CT6My$=Zgqa(Vty3Z
+J*w&fH=_X{oBzWn1u{_|tLZpQmt*&Z)`aFmJbR%)x3HK1q(eox8C|Lz>jQ-&u}1wDyR#vpv1)!ja)VP
+?9RUKzh^*X)piU0o<_wpVJi%nH+jUsu|;>T4iIs)PSOqxLfBIUl5whKJR*q*BzeQ&p~8lglV>3FfyoI
+DEew}0H3uU8{6$za<pgrT;k!6OFG}EN<?0wVL}tZ4meDm7(u|9JrN=2fe@>sRgI%BlN%+#CFoF8O}c9
+6K>Lq>3?9c12k3RS-qhe^@_5jSPhl{aPYDI1(LEI)HY-5FwG!w1dbPwz5gu3_O8Jhl0LDZfYf$r&l!k
+`m00D2jz#*WDd8tvFRp}~g1hBkZWGSC+U^*MV!Xuj$5?4n#M2NFmus<CO^bydqT*$ioImv4!Y4kL0z?
++Ao!@Q)U7OU#426SNW=8}ShYv&LqV9B#Z>p%M3xtl@Z9qw4I*nGO%Rt!CgY4dB9^RMOvXeZueDxZTqP
+xLmK=M;$Zl-=2R``*<W4^;y(U~ug6bw?o>XP6z}H`PjgbhrYP^ELQFzyd^v22P+icuvf7;u2D|wTWQc
+Qz~*H%#{=yIIs$EbWo)O%9s~PPhzpasuhCv)az+1Qm)h1*anq=yS+kwT*dAJ8%IY+SL;#N(>sh#!7i_
+=J`v?`KM4C8p0GwxL^aZY0dQg)P**C{6!(CrH66q<)`>aLyFx;wDB1uOq-qfWMtetOCAAX{f(R10i|)
+}N!_J#Te8E0|VaHzh;{&whjrKS>PL@km%)2gAyUOPox$&%hm~-7N0DM~Ij@AY=yea~a_z3GOea?ei;#
+-TXz}!fecu48+idvaPA?hFEI)9AM%W}=J8{mN(Wh8CRqNd=V4ek8cRl_`3&npcpNFB@N*a#w!h3G*vV
+@9RVI8>5=xNjb<mafc_8Cz$-o(tgUOO?zCik09kwyLp&p@5aY?Jg}n@xNnqfTTJ+#jZ%}MufsuHb6zu
+pD72FDj9qme)-K4V@ytllgaHDliMeg+Y|Wr_Cy>R-_=LXI~to42idc~kN@{wJvu+aU`qyv3(LnzG{_0
+xK`XUw_RuUX#80?87}fzkMjr#*neSIM<^#(WZnI&Uwbl)SlX}7Fqc3j6`V#oCUM49jHxTse>_J-QWkF
+wFC)E{(gxKvF_rgn}G%stCG;mkJ52B^(Mb!pvRp2NJIrc(AL&0Q8&^NhGG_0(-hcq;7Q!AJVcdX^ZcB
+gC{m^U3aT*c_<WZ)%KgTKR04x;;#CGG=Dz|%hr#yIr5=ih$y>h<&J7C)T+<>jkypFey0`uWHYb)pq+C
+!I{d3J)l&F=#0@_<|mTgiJeMJ)y61Ro7E=BD(`lXuzUUXdrsVJaJ$+Z~HInFF*dgL04cFki}8l!Um`g
+EMcrob~?siTvIf7hNvS?CGMdEgHELKVF>^=B^^rY4pkTMnHwJ*RO%Wu?A&-Sg?f*X-tSAy9TGwVm$AR
+rP+_XKj9w?2`iT(<XBj(1B%C*T!w}9Wigy|Nx;-YLm%+gr;w-(2WmV#?VKVf%lkhf7(toHHuVbt#=(z
+boLW72tl+TaK7ki@ON#^HA=*gZ4bv1#1irEP{KMJu0!;?=X+0Q_%Pp8%AN9JTJG6#f71v`{g_Dh2qZ`
+nn0EDAgZ)?WdwyQSL0iQVq}nl8VvRYUQ*N|yETLc8CHEIwJPIS~r1hJ@=-&7Wio)w)_uKx$*FTf!FJ!
+;8Q^G75VC^*Fs2>n46)2l2<rt>+`c=ZR3Xy}se_%g}-I4IZfHSWVGvqSm#b110%j;5(^0O_u1(qkG3E
+2rzX4VDplOzfaP}xQy%*>WUU)GB)K3K-8CX;K%LB^X?(&kc;KWs^U(9Wo46wMFqMZ$Q(1k!^0u=;1W8
+G!65|P%LG=MM%OAq!^(%TOc&<Z<x_25R;O?hPZr|P(*m1;>kEEizQQ915)VxIhH4;OYIRpN{PM{JHw>
+Y?!W=pih>L9kThRd^&jIG=417xP`3beR+CTT5@p0Je?(u{f7W=+yF6p3*KfFag5dy&-hK)8TyK8li*0
+(!y;;;abB+Jsrj=&Cc*zSs5uDnc>5F=XGpCi}i#52e81#>E;c;f}0a)IzQ)eQw8wK!;>A2%9aRRx8hP
+#XF+8KiXN0`oSU7Fyd-2!A}-X~%EA3`}}__VB^~oZtUq^rf6sElW|JVSachyz?&RUq?qYTKl9S=>DTf
+N0@rwp?Mxm-^J%$Yzby^JG)J9tMoR>mzVHCHOVai#Q$zGweE&z?t(~5=~8PHq*i!6W!-FD5WM(6Q|uN
+=&e#m`y<0&0wi@Y2j7xV7fJ}hT{tr~5)?zCRk9mxq0I%L)=!rPK_q+}V*mA+u6~O6Kox#yijFkhBTLN
+~STq%BB>O)nCg~I`;cFBN{yV92H4hh>ksQB*wS@Pfq!-fpXJ{cjn!yfs@pWEQmck#O;Qi7Iv^`>Z&_h
+^9PJNe?%bQbwlO-5x?#(-$w3uL>AkO&P`CC;-&)|fDM0Gf%7)@p(2_^@92(N!u@k0A+Q^^0ki`_Ag3;
+ad|IjP8^9$4DP+P!a{C<+q`C{GWf39tyy`Te!DK_x=L(6r4M*n`sR#IT~#7lc-+JD9Hi*u}04`EIECC
+!@P`*|D96W5nkVzY-(T9#8I(b7oq?O<LsruQpct*viAXKB$iaFY;;l`6znh9t(W3W&KyY!%??PVoI+q
+3?_rGYkK@IV1GEM=7#BvCpk7sE4mLZ3o0r8s<6*+ysrYxN<#*-r`IN^m9ZLU^;@+(Vl~L_~n=re^mS8
+8<ENiNy+PES3KlR0ky5X#r7@=U+4q+LK(_!?ibxmwaQ0EEp43ym@Ie0(l!OXJ4UaL8okncK~;9)(H)h
+$`gL5UwHkK@PqNdN&IcY=?{6ZrQ?pYvtCkc4CEAa&BLa4+JqnX<{VTDUGDAau{I!E8Pd>_*iwIg5OVW
+_y6S0I(-`4lQ+!3(#zp%C&_ijwLbQYGvLY^eH%j@8#%sasf>t!!KhR(OLnC{i49afO>TS#?1Jk!d|hJ
+!}Lr%h`%p0FK3cxbu+Y=0pkX&%lZ;Ub(+-_S!clG$TD2L1dGja%hBlU_`#!dp#=nDPv>)CX3=~zV>Db
+wqzdvNv2=ptPCmx>5#^&nPkpOX_k;2{8g_$x#D1ai6CCf*!Fk#93`Tp)UT^e&Ke2nO`OWweTogtXbHz
+Njq&5DE45Z>KG0?ciW8@GC>BUVCqf=%vDj_K^d|=Y&&^*RoR`96f<Zn!*R_;i=T+Q+<9eFssMrPuhd0
+3{5`RN&YdyOtp0Hhj48E<wZE4qc7&_zxFCraiR-W=n{m^yCOnC?sb1DZaWi+fPv^$?Tm(&-TE1K&SBr
+-<OUlq=+GY*muwNIE#T_O4S>$^=(;ShfexCBi2x+k>}-2=3PUv}h{1%cD_e;aK0Oir%HOt4<7%Tmy@#
+Vu4|g+VX^tXlV*!s7AmmKUCtzk}1SOre=HKfeP+~SBgkv;3cTJM~V)4&W;iPVaq$CbDtdFpz&FejiLB
+Loy}Fvp`ITUK(gzjv&szY2*(&Lg*<pnFHaVe`5chdNp$|;Z6Z9i8K{m|*y2A9uif(josTB-6_|D+F|#
+jq3#ZWCC;&UA63L*>Ok{<uE%ta-rK0lhyKb(p1%K+Z%DhxuHl|}7j-s<wcpc-*&@gk7*o%lErb_a<49
+~HP6zZ&)TwqKucMs>gYvJIYc{zA7;ob&tYfgTTl%Ph9>n1sUDlKeZUT+UfcSzaqXS82_bsW8r@d%x6V
+Gk73GB01fiI%9gnx-u>@#DjXvgix=#|d$Oqc{V>F=bM#BEv5zTw-chFi+-rr2*cIeM)a(8Z15t$kiUS
+-m@B^kM8u&Z;kjTKb81f3oQbq#<Tg>BcZ3GoogQ^gFm(jNvvTu{^Yu>uE^-gb4<e*(mS-#PMBOgqUM}
+6o?WW+3L)1@ZPUcy6CfG*21dujut~@mO$5~sqT&hN)F6k7lD4w`0EVySlG;G|yhQt@-h+z>41-QR-n0
+fXbgE*#0v6=?kh1Pv(|BX6yLHeJ7fTMab}7a%v0l96CQ+jb2Wv`_*Vciup0YiR8V}4wW$ne^j&~{Yx+
+cwG_JU5_Wzh;@i_=iWi#U4n-|-_|v@PJ-Th|eM9naOxLp~hq>TdJZL;7meAupYax^?YR;+$_?;scP7j
+Lu-75x^1JPRXq9x4m~oI~#gx3b_|$LmqTV+llv1s2D<rP<q%LT}J_|%k_5f5v>2H<#u<=bs)v@JP+G>
+T5ug*M#b(w#X$VF)s&{hzl)|i`4woYvTk-%RRTunt$lQr0L5DCq}5uEu6h{bRAFWHn7`Yit>Eiz>Z<+
+vm(y3z3!Rm639gfZt_S56ms#>Uo9hyK%uP!ubga_LLT3l1oQyd?<`i+!#kO|kjE1=0_8+3(gX&@*6)#
+<148-iG;vFS!Qx_o(zR#)84=%-cnYkL$4p3VS^n=aAy{@Ns%mjx7Y;;k**MT+X4wPzahb`x79%@$s3;
+gwB4y=hqL2j|xU5!VA`m^V*JkRx_EU&O)1+QJ2XnLFOKvm&K$ToBeBGp-E&b@1!TC=yq+Ts4IbGl{G5
+=v@Ri)r^puf6SHFK0StExQl}oketpar!Z3+s2fX8&jfh%t^9yKWc=@8XdP_gMqeC+X&!!5uK$w+7vd$
+;F}*)Gv=QUb8y7Fz~DC)vUYC%NrYi)#FuDitn;=2JpQ!Q(7#b!xf?XBYUQSb^af>3*GtzbAgetnEnRd
+nO*RATEX(avvCStItlBCB@lYtfe^GyjgDHo7dos{NokkxHzdSaT0VDnF4+C3_?*_W<Eghq=u%G2w+e4
+>P^(t?U+sAwZ8^1!GVRCwgF&O9|mP}!KPdV6|?o-^lKx|N`^AzC_gYSkHW<|TFdMK*Ry8&1Ip1x??&Z
+IYxzcyrX(t<-Bu?#745xPr?jSTc~kP|%bs$uEi1&@eQI${sB8V=wHhti(lKQsKNO7UNGcXaayyIV4%o
+vRDE6XU4L7MJpgXoVz3*<baRA{gF%4S_$<#*Xdv`oriiiZeTY&ZTrNhSwfUL+;)LY@S@t=1KJaIC>A_
+M}>&P(U>5N^mYoYJ{25+7@53{Tui<53gF2ZCO+D)&K?4dkI#Ftq(}6Q_|m?lQ8_JYb8^GPfk|)*1Tq>
+id<45OcsMwZjzB8j4<C-B5ab6@7smh{x5D&R_#iaV$h}+Q??`%?WX15Pg*3uV4UQ3j395fP<+W-$z4e
+SbwRb7K0Bh?V?00Rmjk&TK76zYln_$Jr|DJ&-dKIYzU3GhRMxNpdY8e5pXu0N&jbzQF|A`IhGz8sGMw
+?>55ZU0rtSN6VMaYA=NndF%2;{XkUGDf61Zo#ioS~KRcrYRl&5S*li{!{d|GHoi+!2GWT4Yt-7VF^|+
+##2>!+7x>j4@S!Bpew?{5$HRl7mn<#>Sp!p?gW^<WzxF+c#*jg7O{O?9d{OXN^GshwZf}3*l26qzS10
+oqP#fMh&Qi3+V#d38$)u2zODHKj2Mr#W9aMxzQ!_wqr)@2m?Ex$RGSB(vE=#Iv~=_!r9=4yIh)yekMB
+mu+iL@!|RJ9fZ@fQPMgF|*7-lZU81AGK1+whv94{ZF<m{UvV>X+d%N8udG&MOj)e?C0sv0)I~8*G?}1
+$8fNxjQ6z&&$_c1gr3mqDAvqItG^)?ukukF`fuvH}9<fHD8kZ4JfyEWYiB|*3G8g(K<sn+l9bbuD<xU
+$p*;*xGFyKg~b4-~qm`a3X~gwXyBlXVUQ)V{Xu1>da?89d`lPh9P(9A?n9EO-zkI&rXBBwGeuaM;YI!
+aA7P{j#e%+Ni6Lz@OSGbV%J$gBN{w5xr2a(4R&AIz1UBPta#c6>v=N(rZ+!)T7qW7nSduzvU2iJUXE9
+^#JToY#!+cP1_buy6<;5Vi#SPbM2e8!8#eJO6uAaTfr%LVJ=1pZu!j7x>Ma55U*m`HcPD|V|#_k5op9
+x@OQ}J7z<!t0J3Et5J`Irm?2#i<=Xb=6K$~EsNI8Jf5c=X+70dD+`@@)ze3(zqdL(o%sA`C&EG`Zb{V
+nk<Y#0%H0R}OOffKE5q{E2fMzA-(}`MRFrt<YPuNZPb#){S^@jO%cPEwUAatHhTgd*_pf(%ZVLYKm`M
+|hi+g;rYlw+B9HUGR<(I3!AxqpyQBTiq>d%BCC9x21;h4=#;FlCdat30W6^T-I(RZi9bPYifJ4zB@t8
+5n6K=<2~$t$P4CZP?qMc7ZOVKUcHYw}HZ2Cd+~{$ELNRt5If~C@;$^9w5*99hE?TQz_r@T@3tN1$u4#
+#|$XnT_CAjB_P0Yb2QO})DMkwA*Yj@%xvd7SeHc2$)Xb<yY>Ow^EDvul+P9!yGLAn@+ex{B=AiBfdy1
+FCH{>Gmw)(&{$9(;M8imCX>?hxiA4a3wdqa^Ak3H<j2WLi)CDiT<T!1CF=x<e47*#-{w>-R@Jcq=Wn;
+-*MM{6a*eRhjns-sry9Iiv6~D-5cK-f^&S<%9Kpm2=IC%*Jha;X<Yy!Fj*UM&OZlbm}rbBXSSCZuGWK
++AA#5Up+?ghB1*#g-=&4ML-h)wM(VE4Q&yP9pYJin^Gv%f1#DI~iqOX05iuAWy^PCbZ>q2yk<Uekd?L
+md9|G~A8^!;yfW=2hn8RF^2xZJ{KOp1%A#O0LUd;bf`l)%L{L^?Cz-o{1-V9NP`=*)?!FHr9-69=j5O
+Tsf3tF$$?9^KQVM7G?E4L^ikfv`fw2J|iWAb5vkLMAW3#{W2X}CaaSw?z2;r@IsNu!$muqj7t!*@BKs
+zRlp)eYme^noL|Q<Fr}+Jk!_QX?UwniQn$R=ah^I(p(_VYx8UPD{!CtnlT1!D+{~HD=oJ;A-HgDCph`
+7EIL?Y#Z9*ol%aK3LlMFA}^DX_s{XKy@U=Tp4$IPEyJ|vRaIw&0pCt-J%5n8?Ms^+z}-qteG{Gdh43Y
+p$-k>m(@7eCkeYWr4e`Jw8k0JtQtR5IT%>*4_zMN8h$(%r3s&6-0?->Iwh)^5TY5ZN*#fWbld)7!#&U
+oJ6Ix$iqeMHv~Bt0=YGELw-T+Dll~MdvP)ZQ;Dq6({mtKPw=~5$@t_E;DYor}$%%13rY{O(iqw!T$qL
+O9KQH00008031s8R=NpobBqxH08>2x0384T0B~t=FJE?LZe(wAFK}UFYhh<;Zf7raVP|tLaCzN3`)}O
+1(ZBCsLC7eg4R#gVo90p@PU|F2&p<9V&Q7oW3`3D6uFafQ(utDoJ;VQdXNIIi>fuLw_Z6*??CLQb4(B
+~X?gl%#6p}4P${Bnob(FGH#5|KcVRe@9l2w<SRlHnDmM`gMuZUv!`lP^S>~Fl3BF`opY&+PTu_#Lj?A
+`GP0~4@g&gtQ&gZKNNkN5S289giWyi&M<f|3`x6jffX0pBt&S)8wmlvkW3yoy9BgULj!ioC2?nqORq?
+84j@X;i_0mARK|X<f#7wiFkWWtp#-dYX#!U<E4?886rR8QcH+3D9?N_&GfO^6}%r-}jHzkZN7PR0hhQ
+F!=i*;%Y`$AItn#o*i?2djRZ;&QosP!GhG?Cm}V|VNn6sqEy`-^IvM7#d^$1U6|otGJsN-afD;16Gc*
+Bs0mk5woXM>-^}2;mML9NCdeO<->zX)aKWoj^vn;#EL!m}1YAe!>N3x?3<1~>aw@XwZ1O`Cx37pQd_H
+6Ja&qwbWdFybANS!iJpTUh$CL2$-Vgi7JH(n(S(P&eA7?Q1mKNX@G?}-9SKf@V4fa<K>=$vM-p4IKTz
+E4x2!L@&^F)++)<TNr`M2iTH$XqRn@lF*Vmo|ya1vUi0y&@%Ap09Be&y`VF570$pR>g_fX8VhB|C{Ob
+`(a>qwhV`%aTi;RS`<fm_ij@u&NZm7Sh#-U0-sZf{K#hGg(EzNy(y;gC1v6fIWd-iPfsEP(ie<)C%G<
+l9%{2VEey-9g1qrz|P{IQO6M<SVxq~oXNUCx$`7wXrzlUlxbecFoXr3dLf92mq0Xp0;|0+Iv4b9?1XM
+`PVY>OPxumWh)h&r=u4h1Nz4Yv4kLL27JX&#(Cw7X-?Gnn#ueZ24>1Hb6+o7C7o_<$XyUX35BLENK1b
+f0Spmpg_8>RFsc~2eE)KW>vf@{0;}SRtOy?<IfgsWSM4;}~DTw=wU5hkj=kWF_O6v%?%Q!d(R*4n25L
+cH`1*0Udz#7w3GEqtPHAsZ~mc!!w=~uSmpoGZ`R6)S_RkTK|2n;AM!KH!*pewbJ!W<G+Cu1^>vJ5><#
+ER&GBkf?#KTA?C@Vh_5LjV=kCF-68^c8xr3nI)yX_ghRqms|jht`z>;|v!F+6Jn~iZV}X)KDodGO-je
+J9x{2^Q10lP77s{UxPxIJX(=1*DLS~K}R~sagYpt`F>9UX04289dS;lN(cV}6cxOz){RD5;|U{a8qm=
+y8oaB^tgmll7-9OyU;?l)42J5*plQOAWn=u8#=>%t2-sGB{*A{Kp*qj=w8bTsEQ9bUKzEfl@oB^iebl
+rCv!?x=R|gm}QO9{Q=~Cr8V|-g~yNVihJ0&%`1V=NEMH$zkVtdDXM@kWSxdeQX1U(2GeCW{puBA438)
+=V?A?t6z;cgVt@hi;;>uEc3YO`MXgjR4cVnlEVX^#XE+XIIrzVvQ;)ZNW*o3%C9h7ot3Jp;y=ho^W$I
+PTbA*sVwu@ZDR$Ga=24O36cT4L<yDJ#&+wkW+AD+Yt_t<QYKGuOLPx6xVznTm<ZEv0ltGaO`tPGQLic
+UpY9ZB_TvN2p$S>GNYbS2frVQT;<6Sj8eN_YJu@D0rvw~XvSPhaV{v>k#99o6@#5hdcb!<<dvE#z!f;
+;lN;Q{=Q;vdyq6TOWE-mx5(WgafEj&n?x`WD)3!oEWU#Rq@W8Vyj^aJ2D@GBRV-Uu`ndw7>ZfF@DVwM
+#|N#X-@eaDBA_iQju)e4Mu7_p%E<y0$02#H^)65#MEDt*lTbP&Ie%4~;R4shlpq!*m@g_2H{=@A%4cC
+9uldhE72bufTkOJb>^L70ev?3ZS2maB5qAmQirh3lET_k<EKl!9`lXMd2-5L1oon=zHQvb}c)q!&8Qi
+Y(5{5?m={H%N%(1S~cYRfahkuo1GYUpZPhD6Fr(TH|TV(6|SBAAq%{5%^<}A7)bCw0$zyPs|h`vPBpb
+AZ{*wmAHmiDy`mOP6FPE07l6_py*dnsUT0$MD*%45|a{2RE~wVz@z;mws`##7>@N_DJ!fOOjtlg)HoK
+wwrf#(nJLdYv`*Puwxx1btOWXRcbUJKvF&EvI-SS$<GM%IJgS9QD`6F(HLpd0R;(##XUDV;TvH0!AQ_
+#3MF#>p1hGmj6N$kL`An&EgVA6Dg-G(sLVdckeKyr@8q^ds&-DuDiQ%%2<xBX|ti!}CG*Df$^N!Zxhy
+8b7{_3d}E1VE!!0|8RyoS_^Qm3e@Ak|re+wuTIl~++}0JOi_U_Xfr@-Zmbb1t)I6}ec09&9#mDhFbPR
+uA;mL>wiAP=O~J8^5W*Yakm|kPoI14TK5^=N!}~r$RN*u$NU;$ekB2E?}wkc>tJRK!Fy$C`9o>NLh3F
+VzGF=*r028i~2U-`fjoP>bqBe+HRH%QzF~KBq-L2hw3;`dTS?QaTONhTer4j@f}VApq^%Gc~>JEFYyd
+=ORL_H`o6Z{X(~(FJ(2!&aPob4^p79*K7BfT@5t4ry}<xfxexRLT>o!P=&d{(TaVa9Cv?=Ai1P$o8CJ
+H#D){B|!TZAx`{D7y|LylE*7LY%cG*i}d@o2jV74rDeXZXkhRvI;&5!Ws;24N|#-3`mZk`IQvn}WbxI
++}<c`Z^XrJ!a}b#a<U3G<XY_xd^=SO|XN?Jy|#p_YLxn|*nIJg1d50?;W7>To-p!aaC%o+bX$i;G(=k
+~?jk^d9mdC>dIoZO)oYd&n)V?e5mhcz25oxbp%G?os8kTo2m4GJcZ=@6zY2A$r$b%!rx0_|b+zMTQd%
+kzVbwjl;(5!PidLjaH^>b?UfqZ1JG*XAJ`^NYf4@SMEYKxzOXlpR2EaxR^~SV3=0hK$iOt!BJUsdMS0
+g=Dm)Ac3(n8&l3YkeH-+GONDR_OnT#T<?Z|pEEzt{a^8+ZVt{@WAm!XcfS}5_4p83*aHFChrr5%Dvjs
+_|JZ9h&`c<!L*}=y0EL~$OAQnr3EiA~ezFASV!fr(kIzDfT21vyuTE9xmfq&0%4bSj7W@x6t0)vuv)@
+MlcGc-C4jh!$vEu|?40hu372p{VP(HcbxFuL&p??lOz`7>%FBc14tuz=R3#W}wa)L?N_9$jU3l)bT<4
+r^5Z(4-3@TjrP|OuE$vz>$0CB^EX^N-j(pD3&Ta=|u&2F_MnC9#rQx-Neft)%Exs%x4gZPLT9n3O3;5
+waGxV;E=zT<oFFFxv{7~cR)iE?0JDYqE+E2G&%zj>f*`w5D_NKh{Z02s&d^Y43g|se#LzojkTDYm=_i
+M8|L@>Wto?qzzV*8;yNC)wDy5ruaO^|wnd^<@VS-XaE0g2PWs9os^^R%+*dSMOj1Z`L!e(O8rHVh?;%
+#rd_O)C(WCJ_aVdxjYMi`m3=PngQFhU-G)}k9z!h%I@ZWsv(e-ve*>H{33FU(U*!-D5+_CH~nVV-bcR
+|x>4_*Jsh??|e*;e<og@Ro6-7whJPO7awTC;n{hv22XspW;bD%P))$?_BphJ-e6aCQ!w*sgbj{u@&Ty
+~L-b3U4gvfh?gJt_+Ks878_#3C1>%g{Y{6$M|G<R}*yy<Cx9-Hipnc+W2#KV(5{zeWC%|XlKLfr#>=v
+w^Qx7*5n1aCE}l2^UgZB&uoPo2zw@+IU4@2`tRXD26JoXE5>zvyPfOn0QLVG477<u-DeBIIK}&#NCQr
+wqu|}F5Qt5<jA5zRH^|GR(eS-xr4IsNFb559atVA!iQ$~`MWZvF6s<WFkSR&POIXR3$ZOe7Pg|;xra5
+_LPrX$dG?D`8;N=zTe$v%VxH|9_z~<TA<ECo@mK~^iL25n}rN$}s9ZGZnnNo_VN;GU|RRX-;zgeX{(n
+CMN?>@n?N`1<Jq>jE*ZLHEhxmlmu=8Q}=5I5QdW7N7HcEH8@`A8+@x@NP(fthU(1StBi7Qk2ZO|Hwea
+KpIYzMA+Ky`0_o1g#wN9QUMPPxD@lC+O#fh8Kg;Xe`UoSUljV_gk#!9!m8b+QqISh%aS)>Enmq9T75I
+Y@ds&$sh(!lek+1&33IG*wA5mEr7hO_24FuRa90IRo(ZBBDM=4J%%1n?2e5m7O!7<Hs$9ci^_GVl2++
+Aj-WliGh=a4ht1-K8ti&B)_w-|%+P8cU@y<RdHpJU_0n_dQ>!nzwK-!ihc~BnQEAN<P@^vKPd$`sigH
+;-6<}8vi*4^rR}$0<bm$;9{Ek$><m%!c8bCM>D>m54;fKQ=_L<|3WzJ%BYSDRKS8TC82c2L?NAH!P;Y
+e_NWnN!gvaQWv`_Ds5d8?N4$0@T6;mPYWIgH}%eXAK}sHWo8(-}I*M|)l{>RT@=S4!qux9)aEmr!Q{s
+fyBVZw#A8GSezDGh$K~^qj=}m|4suW{Xw9Y2!oNYkZ`N#r+`M8etPFnKHzouseBV`bOL5=8T0^r~pZa
+#~4#8zOn-3S54PfJR<<PIPG&|U$45(=K^5WmYR;XYjapgVQad6IpL#x95TWF{DGPaSJ#;ck-b0qLJNo
+KVqhkJ48C_cBmoU3iAN=(I<3qB0uWc37p1__YFk$elitR4S>jPI!ws8_CgPH(4`-Ggv?t3@yjRWHGRq
+u#rAiyk@sy_TwK4~7Q=65msPJh^-J01t13-zXj^b`puEnjd>;N)QHK|3k5zVY@2)71y;u2Z<<`hpxny
+E2=w|&nR0@zOPs1(Ta93u_`jX?-HK)2>m36(*~Qyxjm_cX+Ly(&0W1r{2Q(p|5aE2~%MP=+WKc015m6
+i4ZGw3g^QAJau@GxL$GT;-ltW`>M#kU8LP&^0XYgkl$`GJLn`gA_Z1kYX20zjdYZ8V@GS<xO}?ths}4
+Bo@A%;SY4PXzXsY)Lm!6GnbNG=Wd{z)io466VTU|V@!I`#ZZd>fXbkv$hOjCT~TbbTB6j1O0uS|#Q2-
+#*9w715IL)h1Pj@Y)*$wAt-)dpne?#MIEY~B|GP@lS*g;W&EH378ZBV}q5?enzHYrpli`jP^{|^ZgH|
+SI7kCeIj^=O#`V(-^>O?H<JZ){^?-^u{d&2-bg4#l8CSm*rGHYup3+DU$8c!pu)`^|VXr}1|gZ8H{qb
+shD!KuM+G)6NK)R>7BvFZ#lBG&wYxLKLA>KeT{Dr8}$+S@9wX_l6H6KDoAf1`^dE_dtIj4cLi2LGPuZ
+Sn6nG9E+plMM*}enTU|KV?WR&FE{!2au6<25j9k;2vWf9(3R4;D1QgbR?v;mEYg9JyIY~62_AR(KIIL
+*F08{@#v<+KnX#(a7h2qqq8;C9B`kuU7TJ^Lo5wG5RRg9&^?$*HH>(Ly$kb_O3*Hv2u=1OJWw%SeU~a
+s;mjnm^v-0}A>`g$y?xF0_fmn|LesyYYW;;X$o#OXGpGx#e|+U`&9%}Slg!vA+qhixfp517_(17+q*|
+C`#UuR!k4|!@Y1AJ2v-+A%Wuz)9m=LA*Au6v$W{FGJ%5HUR%8yYrpOAHZEIkVts$&f70LL|_`a51u=g
+urr9b8u&qP;R5KFeDDFvr>dvj^&pHEiZK2W=G-n}f)j$dRATp@h}xY3%gSpg!eh|Lytcso8s1WJUQ$E
+y_9`+ubs5_bJrQg+5DYZ3?z2-B2wHbei1y{-U?DK{C`WcTacgfTC^C9evM^S@)c`*}=rRotgygF1|ty
+lqj<s7sfriA+}gL+adZlg|g{m49cl#?a)@85ov>p4#LYK&#+gNL%IqDI{wT;L2JxPPId>Lyxl67)M3G
+Nw$i^djk2oqgTqJdC^s7b8jj9cSVnI7Sm*R%N0(gXum(9t587IyJ7+OAXJ<RjTE#95T6hmk-yJ`l{1Z
+@10|XQR000O897^_9LG$P{&IJGfXb=DZ9smFUaA|NaUv_0~WN&gWaA9L>VP|P>XD@YhX>4;YaCxm)+i
+u%N5Pj!YOz8k3V~TKG2L%MUKrRkoz;J`wNgfncpvjT63B_f1mzFQ^zjtQ2yeYElpcN8JTF&*%?3vLXT
+&{$Mg~$=;J*$!&a*<-8F@vheP=Q$?7*uNwa$&!`DU+1m&T6p;KBLk?7Tz8l#s?83MP|j`Uc7H)Vz@xG
+hi9knPR=h*oWsJNDJe~Dn<7wHN-d03w`6Z26{K=q=4cQyG>OP{?0I5cN@YmYTPV2(b6bjH3GVcRl6P2
+Kpo!odH<!01MR-|}i3mOw6lMfzqK#Lp#wJ<nM)NXRMo=b7<D8D2z;&HmBXe3@C%MR6%3bc>+e+jaS%B
+l(&D8pw2I0)PpNfJ)(nif@-nmq3GINL7d9p@Qaghf8@QH5~LeKNkJkh%G{$+)je;@=4k_kR1d4(rRNf
+k~!pqKCa_Wcb-T`RzbH7w|?0-J<NE~&f`RGKmXy^>X)5uyt&xP*@<AK~cmx45;p6~RR&wE3wBG;91s1
+l$<ZXWx@0*Op~qS&0n$A<fgIkcCJsU~`2_ydf+V#@sXHDNz1&JdbDlen`#aa+*-bBV2L0ps3bYWO!Xs
+Xxb!H-;FRUNFWnSVPbD?#kd=GTMxcw`(Y5j41KOqh6@-(WWnJ-6I(_Y{|>|Y)@be3caZ*><U1B%8;_%
+Xeei3Y?ll8U&UYjn>*^}-$J8n8D2#KtK^25nO`)k&Vf#H8I*w|SJEL|TAGr64>*u!RxrJ>m^kG=;CJo
+ZO1ufPhPi!rnYCNBl%6uLX`UY0i0kS}#_ziJECKgnAEK;<lY#q1<HpwjrmM*d!b<G!;W1>kDmuoCcJc
+vOoC<0MXHOW+yLw$|vVEJX#ZTE#=_SR>F@aJLjVJn3<DVE#!e`sV6&TyHex8RgD<6026T_F@L`~wwNA
+*Wy;VXm>W+XmK%c<$6_I-Jft*Fh(xOjiv6wNi|H2EQD`!N8u;aZ;98WWmC}?~6YC!fjmJ`*Vn~J3W6p
+sf$c-iju0Kh>`hzj^cxn=2EwLdOvuho5Q`zw<bOa_g_%U`usok<8M+F0oe?0Ld*F#JQ`eRuG(SP#`aO
++*qv@=Tq--o81r-Ltw+-KpLR$_dcLGKk2#}9&+xYJt>k@A>!HK>JzirjOU4*>yUFnSd0t5HzSHUXIFo
+d<n+6(GwDXc%ndkV~zwfKGZd@lf*jlBAUh0`@XVAQv0D;wNzFC5dJWDI}wA|*amVTN+8+DU@N?&KQNs
+|(%&=`&>Xw762`0-|y`#ln%-lYcLIZ_9Abm5=wo}vNX7}{<aR69ZFnvdAYD4f83BlY07#vD?u{&D+pI
+vF3$?87Y4E7ZM5G;ONFFvEvUeoltdq^=E)B6$73rnOO$uC$wta#1(H(>XPS)JCn#T$p+;xp2pDSZBb`
+=d3{TR&RPRbDhdtq8ropT3WWRnD+@|)M;WDJ-Zqx`3+NJjWxLV^SRH6bPmV_vCcX%>56#guj$v#*DRj
+TUcPYS(n>`v^XdHb-5>8yLcRjS_J0D;4#Ivo1E9K;Dcjx4feoUTYwl<_hiZUc&9;kwd<?I<80$4<fa&
+3E>#0S7cZjW>#=+B>=w=?d>+Aji&Cj&ku;u#e7va@8f8YX+Isixhz)Cnw%3?~(O~(lVZP`ID=y<7QRR
+*uZFoGYC4|%Gvwc*fhY`Zne{zf?Nei^u;jGL-B>a)d+pj|nvmB?xjiO{aX9T5&V@ZTA*<GEcNM@wwHy
+zA2(OVQqi>jB@um_GI7XAXu(%-)Ie`8KWaYzMA`UK##`c!Zj^el_f5+&YC3U-l9ECi?Za%soY2d+-Gz
+QM^|ET?xemlhh=1bkG%Zvl4Uz+&-7ef_{n??k+~ojFzyWg^7ue>55s3eli&=6%Uz@_E9X`R%tG7i)yU
++L>MN3KJl|}QhXMmk72mQPXCdf`WZZN8A9(LP)h>@6aWAK2ml;P_Erlr3#IQ5002oj001BW003}la4%
+nWWo~3|axZXUV{2h&X>MmPc4cyNX>V>WaCzNZZFAc;68^4VfzUS-v5|Rp+PiBtvC}m1bv&1IJaI1l;O
+JC{f@Ibd$&!?9CC-1pXBPlPkd$msGSkj!GO<YPE*6V@2ec#JT||YLMX?h2J6+0H#8Ie{LQTaonW|ir7
+fO^WUlbyp@xzNuhWPVZgAK%cl^0Q(^mfG4U~eE~GG(xz&R$uVK%6PXFJB+OJUTf$G7~2JE>F`^(*_5*
+%F-e#(|iSbvosfBy2xTxDlt{1jN&5b^`b?V<|RhrScN5~F6^rajFxE{S1)p9zg^2biIREIo8{?3l&cI
+6!i>F?aV#e>)^ZF260;A$dQlF<n~dnocp%P}8Nn9E30}WjW(578gx0Mo2IHd4mtncgRblBKC$lJt%GI
+Fy_HLB{??laI8C|LMc=HXx^?Ktm7#okpfjIXvnHS0%2+xR{zP<)lxT?K4POfAeO>1x7AH6+0eseNDee
+v$y(c2Sm)a#i!6wOh9Hm~A*JBRdk)H}`9X<C%8)D=B9Q8hs$oO4KHfE_MJqu$wa@;VJ=ybUQLu>xn*Y
+lHR#K3yCQctp>~U+GiBv7b5v17}3zI^)bm7gQ$)4(%FR?Q0MO`T_4oy_bvZUuuQ5)!2?IojT{Qz!(jL
+EA6|VD>g8T){MqnwP|>FXqr*aD9cOOnaraiP5!OQi*yPsYZjWxb1hg+6SLK37#UOO9>nMbHVLkJV>20
+u*Q_^4<U&nLVyw?odE>PPpL_5K;RWe(u3{y%5lqz;{mF8Eg3BoBZ%h(^iu=7@Z>na3ZKi*vX$@&(eX)
+CJcx_vc{W=<IE<BI_o)Q)IRCDZpA`CquM?Qr7U9MpFiBJ)sav{YqjAc;_e>D_;73t(RESAZobpVG43k
+Fx0sbosTF-<h<m^&(%mK1F7;`HcLeD~d6HOzCwOxwN-oHdpCYFH_#;ofjz<>m9Zx(QWAo~-UzTBy!4)
+&zPzUS<Qk|6ayRb(H66?z@tHfrV+%Y9-ea(J4hF8i-|qccQpRmoZ6vMzJZiOJ6U~PCEVxy5cZAzErE>
+Hcjm@7-`OUd?AaA@wi{8c*aTt<7q9MU>G7G(!NID5vQ!C;!>%Mw{8l}jzU=?r2ZNeQBssL3DvIxQ8c_
+XI3^Yr(G5pDZHa||Iw=mr25gzc3Ts=XON3A;o`ir_BnEkvLTYlVwFc6=P;x3}%Y;o#z%D3su9p{=W^n
+_NlF|-gbTxr_yk;`n^`fDO2_p4+1%1XGIFj~<j^{LjI!Vi83gZivKnlI494iruXPO&+sP9Is{+#R{Y~
+WY@-sD%C_8-LO!6rWEe@?j`ZshmRskVn3*iBmE{X^B@kt<f?C|&2>F`Zru<vi7DS~2w`P1Kq>J*D;G2
+L$DYl{FBnrx@#CH4YaUUi2M&f4w4`#0T`H@5sV?nJc7c6p-B&k(U+|h2V*>nk(&xDQI6uaf|`sxpZ>1
+fd8CYkDRERQY_?e2&q;6;UK&+R58^rn!WY7UsnbQp&n51*a|4ly6d<oi|$08dC%OfeEf;vKR@;lJx%M
+!EKf63NUMr+wwxd|J(#IBp$P<IVZH)6&iS?n-`)L9$Y!6`=&o{BR+FfWV#&V<8|mm5pd+{a0&LEKzW_
+ff##ntzgs!tPbp9#hVk;pC;_Fa?Oddq2XB~>svoR%ASanjul;Cf270{aq6-Vy%KTMy9TX8OTKaS|jhu
+~K1`ltv1h5GrYH)ltFn<7jymLWUc@j_-G`bp=YRFohtg~m_N^Hrp-op-zRgbYr`yY^KcIuKOh;Q2>9e
+>UaJnCqE}0X&sOzgYWV+q|Ia&eSl}K_NKuX4^y(6i88_w6y@kXa_B<#<GLCD*FUFV1$~lHUW*vST2x<
+c!B2zu`o^GwwKDmB<S<u{)qVY_V%BC``zFE{*Ui}XrS%@Zpv#+mJ5|fVJ&xd09TPh%|Jwhk2ARa{`c!
+Jq@Xav4ruQiPds59o7bzPSmsm-%2LQUyO4jKs8aqlL@<e_2rEKjbfUnI61=y)IyHXd*{yWrT`Qc{%aW
+m;{}+W=mQTZUim4LqBdKw=yU%q(AYQZzLGXqeGF}1k3P>8qkegG$<OZMQic$Se-9OY4dx7o>a)4B`8I
+|c*3PiGHsk?afFf%aZt}i06gCecaMUR@v5X2~%nSyJ~5Y0&hpcAdL6){;MBB1u?ww<NL5u4=*_~xQa9
+ix|jP{n~A&2)jPYQfFSQeGnHb8{}coI`PobeV^$2plu2%?`I8rBqbfnyh?WprlH<2WY#WnG7%Gobrq~
+n&dKHX>QmUhuk$}^P`^KsBMB>7HkXjIK5VR-}i@2LkJ*40A5GsMITz}H;q7NEaX%wsfo1@haBb(f}x6
+9%POTykUrSVSm{M^uEgKYcVUoZ!rvIr)yAtt5oBrBuXzK9(=wM)Od|ZK^0d%fq$G9|6@H|+(QFNxi8)
+lZv$khG9lUk&rC-X78ZP~s2eTa=QnG>2y(xyJuEq|MKI}euTQUoBbI8~)Ao(fT4;S*ZWy~K4TiwweqX
+EGzpqx-Jkis5CutHLkZ*#qzm0%kO7^;7Svqlq_;+JiiTs`MM{paiT;(P!3=`&{i@O*FghtU)Nk^j7Ft
+E!Dz`vpzm^qJ8fLjW{C1cuf(eisF+ZH1bXWjnN>jE7sMZ_xt$uA%4b;`#3QLoj;oyfgI2@nK)yPHw~7
+JiKM+d`r&x7DKlt0Q>&Ei6vHU>*3m0hC*s{|26G!PAIz81j+7Ng5zZ0PVDk}+eB$8ch_p_yh1+o=N6*
+4&Haa?Cr{fVp^v{wK*(PnwC8~Dl+UJZ0zB4)|L?b}1ipD!eQQJ?o)9qS(1(-{TIJVdt2eNL%Aj_1%59
+@luik^)P*n452uO2v)67Nx`=Q{xqiOO_VDcFHi<6ZiSH;8e&nIu*9=&|QSt?P!f4yGGVMn~Dwkstu<f
+v?HH2$?9S4BlwDzZo+gjRS9S#l88MIEmwD3r`mytV3mlMpgWqmLmYOws5P&+KW|n)%0{%-7G4J-^QUS
+()a_gy)=&E>mPGnpNw2?e<utW{bieIk;T~_KOEtd7s%1=6Slz`sPT&_i0UC1DsTfJ-1O{wEI8@6QUXU
+?Diu{4IDDI)8L!D97(h9yVT&O4oo@`s}gx!Red{@*fo0oK(yW_ZIUqb4K!Ph!6nBIrag;xX%Gh%*)j6
+eb8WZ54ovnwD`ZE|nw#ytwL-SkiYPsF)6@q^b!<o7epU&`e&kuyzS5bmZ6_^B|7cr_G^c)4cfZRd{tk
+DJN(MUh*aBdbWE%+fdFwE?VcR%_xNVrFw4vE`&xX~;R@L1tGo1l)nqAwPBPWr8c{0noR(NzE_FTu~WP
+da7(;E2mBiF;c-H_fm6kw*oZ)ueDso!~{jr)d-o9UYU@*TRT9jT7x8oNhz3^`4=jnkfZ+q@vtm=oK+c
+~VML?l<eqW9Uy6-e*^4uN11rG$VPnLc5)g!v4Ky1Mnw{)tKvbJqEXS$<C%D^?m1i@@b9aOlS1hO5N54
+H1x1m=9mYE^s)+~j{P^M)Cl)(d^YYB)Fw8d!zM_JjpoK#M(q0ytT-K1dyD40c{QZQ5D<o&0b6VVyu}i
+|+r*C3lC7p8+S?n{tk>t%h?;c_=s17xX6{4g1!Cv4WH5Km+Gqk-^R63%b*pe4dgl?-cF*P#*w$LRPxt
+&jM-t$I0c?Ks1bOkkf4(>Rg7b<0hk)`R&-9R1f0whSw5}^qeU%e|&S3O4P6)bIvWYIA`)xmls_z8!k2
+EA!TE(gjqVw#1Qxj~QDoP$S)&AzGp58fCn5Pez>gndGzOAOJpHOra5BeP!pabgeP3S@2#o<?zRY~^%Y
+u7ACy}N=(&zPj4U9+xV6rC#+k-5N{b2DwiZF6cqM<MFjJu)O&Z#J2`R;<l6V%*=;9Z6&lsO!@(;!|Ym
+$f7b1oD!FpM#|OBFU;71-I|J5Z2bbI?nh#9WtLNzR$`P3?hK2NID`jSRJa-t^z;|oLGEo3M3F9(xK8t
+FVWklRE1^QB$W%-nSuU6Pj(`D_$+Sj|&%{%(LA(^=8ssEW7f@TTfE%3^ISi%CoP<16d9LcjERZ8UyQB
+l*aTl-A$E{ZE$@Q_lid{r%{B6XWbmL)V=XChCzEfyU?M9mj<>3}exxSy6Z${@ki!H~k$63MqT3dXp<f
+MfLo!T<Sgxsx$ZY~$B#@G5ZO5Ylk1{zkjEbS1{v%{KhjTSaB(HFAuZ&^^Up7yn}oq9V{6sx3^H=?hCc
+_8+Kz1@Akt)dTDaIZG5y>rhk*2jf{qoJeDqS-$?{}7CKN1oqsNKUD*)10amRymmUJzn=(;yZZ>WtaBC
+XB=HZf|D@V56Wv5)43X5c?Y*e)h6qE0HB-%N}z!}-@SnunJlfl8ZoP{-HEjyJ`gg7UO!_EqGB4&kqep
+T6A4tGXVkIX^WY6KHAz(?ne#igg+*L%WvuI&fdTI>GxX^8oZrAeZSDj@IKLCd?0N&rxxNiZ)`;f0D;d
+MJGKb65^|6|7WH+dLLJI{|;P^l%n7RjP$Td#C%zdLkoTVW17|_c?&q36+KaKgv2vY=dCdc=Z(rZHxtW
+4MBmPr}KhFgw$<n>|607y_76VSkzHyuIo4=_|w8d@9+^}OJJBEw6q&jc2xaNr>w=1+|eGKW}TmKBxXE
+sJWMbWTnRM*+Yz!>C`T?Z6h0FyMxk8wRF*T6MqrNk>4-=fl5#EEkih6gNX8!*KX}gEdZ-6Ppv1>QXL6
+S*6eCJlJt~>FG#i_>%EF&9Pkz0-$ql_%X^7_w11>o~5~EOvGrPrm1$3lNH>-+DTG2Y_j^w;g0DLeq8B
+@!8FurS%=9rhy>r^W<P6)1>%_fIv?e8`aLtzn6|SLy3Ho4rRB?5nZx`G>`<&U*PKq6J&nz#L|nMr<VC
+mtO$uJU*x0erC4B2QBF&#o7)DL!uV5pgcD<X4_07d|$urT7y$P(ux7WXEZ9>k<>SDAO1RETfGB*TbcR
+envV9jC4EmjRg)l%qYxVAeEXGUkbn2KhONb57Qr@LEzo!k=11E#!%-)XHO*TpsqbQ9NR-y2M`=WX%4l
+~*EkK;+i>yA6ac@y<19*ar%o=QRPK{`;a%-E`S)Fwx>bI~8(u_Ki7$f|*zMT-?m6VVMZUr$?vNZx}S#
+u6RM|Z*>pC5HFmiHV5yGAFG=vOy{}GE+YDAz{<fq>BKRVTF_?~7=_x{+c^%0ahlBQW7j&bWG6X`Zd9F
+Rdzz?jBzdI9#<k-Fefkj+ERPeR+Rf>R1HVax`t4ua)z96ScrD4PXF2BfhYeK&_6h@SZ39;1f#I(AKTt
+~p1QY-O00;maO7>P9Q#Q9+bN~P}s{sHd0001RX>c!Jc4cm4Z*nhiYiD0_Wpi(Ja${w4FJE72ZfSI1Uo
+LQY)V=F=+eVf!`d?3hP?JN_rr=9D)7{D_`P{aW_ScE+&vrW9BWp;Age0^`fB`_sY>yx9tn*0c70$j@)
+viK;l9SA=Ia*n<1Qd4NcJ12tJs1r3US;#E>>^L<ys0+zJWrmydcJoM`Ptih;u;lAk|oRPqL^pP<h)qs
+$-FAttSIwEa#OUIMG5cM40@7OwQIfCY|a)%ozL5<-X`s3Ugy<$nj~*8bMt{WmLz|_hQ^J1SZ1rd*=wu
+hGP}+ZLQ%t)?IrxLhIUO3|7NWWB$>?~%x071URkyGlAB9-ah=!r6$}W6Ltn}_FwUZZu{^61Xr64EJgJ
+(LT2$*C8WdI8B+&CJD~t7J3Bc^I_GnniSzeSEFp{Q$0Td;)#jao;>E2%N6k#<Nc~e~A>cJN`Rei;SFR
+OYb3*2m*HeZ?Vo5^09UtI8;Ns^U|WK-fhfZ$%hRGzoVJcG?xHUgJ+W?8HXTA^%99qpz6EY|!D!J^LRo
+2IQ+$*bd6$rleF!*XSdyoTw+8YazVy{_t(CO4a1<n45kwb^Jqo9(Ug_Oe>gbYWhrYOz`7Ji|5YI&Msw
+{MaC*tj-fg1)ldIG(MaaD}=l(&Qh~R&1|w4zJp#e>~coqJzQ_s#o>$>2R2{^(}d;9U>F0y@jd=7fi*P
+0R`$1|GQYLODmTB^_P2Js&TV5@CR`=;C;w(1++=kL{oD3Uo7s2gn-Y+|TH2TEtBXxrEbWj8#j4uA2K+
+h)1TcTktK|~b3USaiDH>c3^LM_=iX|Xy4eM*4)phBnn6JDEwE6q?rq0%OG0Fx{oB6YB5&3OzRa3mz5A
+1gAo!5XVG9P)IAXf0NFqplz-X88H@FQ>W)n5L7p0C^FIXybA>#F89`^l><U{RTTkv@ibub|W7tXLN9R
+)c_llB{7!4*s_=z2o<=E)4-ReY}9<sd@-nB}d82H{5=2A5P4=-PA-|fCK<$o^A0&Ck^1*S@j+^m?vB{
+W+)rN9XE*J_38@nd;&;?L}CI*by<{Gd(`r$*U#S`Pv89b>eb8FZ($g3>rK96T}n8{HJn{@0w>A3uFkT
+v<rbjA`AoihavX*GEsy{hVK6Yjxf0i~YNq(BdCfG>EOSGHZvffa?mns`nazRj=Rno7#yy_e$9pn`Yz{
+{nPJi3h#o4B%1qM9FTSXR=CbGzv*%pbYEMY#s1ghJtnpAb~b&yV{xW3bA@A^ePf~9#;m1bqu#X6k=+0
+N@STc(K3O*;Jt+zs<;if6@)W<=n&MZR22VK0#$<AX(At*3ymtGsOa$v>*1oZ{VBlpDG~CVOMu*L7Yl@
+Y?Z@JS=$A-^ft8y}hX%u<3L(R4r56B!$bafnJB>JG8~4Uz`{4#hseh`Oh1m-Z<C0eXz>vtGfcHrH7V#
+#W|8~GY{CC^D6nbWc0-(`EtygT4x2E($||3&me8~Xkf|5m&knJMU7W`B12vb#(2yZ`Fx3YP*bh)<YEc
+OXerm*O|e|URSqrAiKSrxZ3Q1Su#3(4mN^K*6hKIUYj6oKTA0MN$y@U%TP&s-5btY3f+^DN9MI3awpZ
+P>Y3n>&ndkFmo|T*R)V>ctm;$PFp7}6f6jMOmI-|Q|N=G~Vg3fph4stW{7^qG?h0U(F(=}jq+Z_weDh
+3B{96Xtw7dcU2^BCsRFipU5!palBVO|n{1qhN)fetK|@mGdDvZs2_+{h{Z!pC+17nNF3k2gWu1^f~+Y
+{`IIzsd9DvTfJR;e!XTmYX$Q;wi8kSz1&N^6~+qN7Fv=z^0e&YB^vc@JztNw0`2@@N?h}=2uH#NS8;C
+ku2;@f!X@q?;cLSee(VHe|qxtFEEWdPw@hT6&%%r|G55U^v$b(YqInF>(MudCl3$)czXY{@i+VnJb9P
+$uj6~;0p2(1a|8=$4g{BB%K%1lUgS?XO2{nXzds`PdUFYP12O2t?w9cYW|K2-m?d%`@pxIfL0mJAcDY
+5oA<h!PAqxpzr?!v1J>pTO2FOv;p;+l(`CnWW<f5Q)MqB>jBRqnGnM~#U^6L@2Mpg}2{d-q8G9NkAqj
+9=fFR&53p%)6Id9^6!ZHhGaD&IEHaFPhb@z``Y1(t?CoQ|Xi`jbaR9m21+Q|1I<fvx}+GTypZI8Cd@K
+(UZcu1*oc$#B{r`!r1MC)cN=3wX@XYQVp`<hFKHjT;sHYbL*QEYz|)3hKI%uGM&91g9hT7KZ{5`bR_K
+#<heESsDt>?cf36@_IY63ramvV_0;M6VE1zo<Vh%A_1&r`0%If6*uy_tj_+C_jT%ToY%R0*4KSxaS0)
+@#}Wt(EHT58KbG0*Y>_4RvihPqG$aUn!w-aI%NJ8~&yU=>d(FdbQD`!+haf*??~B!DWtm`*rOW|gehO
+(O^C|fM6#H?|MSuk6u+FjThOVtuQ4&l6#B)7|uI4Y_$o*GsmJ7T9&4r0P+C7km?}0cD7gs}qFmRrW%^
+Y5yZG)jC$)7eYN!!T{P>if>nVQTm^Euv(K2MM21>j$m)eVl1U|I6wk1Hpk@m{?tk!syTy+H-S?GnD+G
+$>a?dwU1qCj=~i54`KVXlWhzrp}TwzX6IB_A|jgRv`JZ$n1@2zNvwOZ}m60oG;(VRy;rF?E`jiQMA-z
+4&O9%?y_>5R7g$j?uL{U4rS3c1j#nx8yF;f0!$JlHf=7=2GMpb@ZOrwt9k*Am)q2%<p>KY0U*ZNrdVp
+^qxZ-sz|^Zo2<{u|5}37iemTOn+zj}z6>b!gc*JXxyOA@qV?8=b28*n|DawJPCstfAKQf#lb@~3_^9K
+GKCZ8vxVLD8aTOLj672OS^@yX%i)A1x(r5AOzS&zOLk1aG|^8cDGH(IhYKl?OP+Ejl4a2IL<fdj%bJq
+0wHPGM*#BB%T*Yl^v3)EKb^rmgvu2gDI2#1Y|(d3BAl4uTj8vJEHl=cb%C^SW5K<_VqFy1Fia)6vg#2
+j)5IUo`ur+w<d9w(dSehS@yraBy~HKF1e(3=C!GvEl1FFN6{7JZFBd^O(3#dAgq*m)AvIl_*zaOVTUW
+)snw3H@;=~3@F8Mn@2qyw|R~1rMJ#@SP_2Nyy~#y-lpZ}*=E^J=O9|<b~dl-0_2`83U5o2m1sB#v1B<
+T;!w@l0Q`w3^v2ESwe<NzRswai^LQ3PmDf%(GmnmO*Iy~Tfpw<yL+T{k!II$6X)<35S$JBN=Ric;Sid
+i-_S*`icJuDX66t1njEiUoU{_Q_-%oxr8Z&C;@u+SMfdRo=!_YrIg(98cjRVxytR*v+o@_eNZ;U`}HX
+B&!sm5V?5H!-4szn8RA=_8BC#4s#U{QMl=sEXM4Li&AGPPCbR23!gFvViZ;<I_0!@~{oCEnwGtt$>z2
+CnT*O#&k;-wh<@5sH828rAm`y}=+d!AJQbFX#CHk0h`{WoxkayYHsYp1*l(;Qi_Oizl!D?mc?*^2gUt
+kG)4v|9t%PFE4+5>pgsS{MX~}U%t}M_LIRYp^$@w<n41f_i!Wn2TGLSb$)@vrbiE!Rduylqbw&Qeg1=
+Jjb8;c_qjP-;R{p~nvcx0SFlRqv*U}4&ZE`3-G=aTeAprRFE-0%*b*RykDf7s2_OG^u?`>cG61n>A-e
+OpBTIK$u(p4S@{gmK?}7AnWo>;*jJ~(;cwb$Zm2SF1u|qv8jz2hqPC#;B1RP^kF3lYam+C4j>{)$sof
+XRrj^(p}wx3!-I3RQ*O9&k|{^YD7a+REAO-}sVB3~n;RnE7>67ct^T(9beL|Xik<uTy3YZMpq<++lqj
+IabxL9C#WOs7_53DOpRMjxdpJvg~NAi$$w_<`vD1dTm#TQ9Z;XafPJ2AD&`V$KCd!@MVQuShBLrge>k
+nSEnfOpq4Zf(XRIedb_$bOO(y2bEx{`$*{k@RunXB$g~f4?fW3@lO7ToTlpnfG7MC;C}QJc?{-%!HHV
+uwU`HR7ZA#>9l#|%d3f6QIl#a5>qn=1sy*WU&Mh}HP4TM8+R?pxWPk)7ckJNc`jWaBE(L-%u~VI%Z53
+#<-T3qTTsLASy*waNGcjYxwA6xtS)fA2j)n7-``u*A0OitXw;&N9hpoEy8E`dw`y3Yzw%RTtp#4Yzn2
+f`<>mAeRo_|XE8wP)e=OsK}yfDb^uUoWogX9I|2kpbF94Om_@EbL|EdGfo;n)rS-U-gVhh@i62-n}ey
+Ppg}+;*qItlY=p4pcUcZbj+Gj!4G%yMEI1M9~q=RD<l#BI7xJAD!#SAr~6Rhwh*ccYsP99uAP`D4Nh&
+pPIDlANh;%uQ~EN2?lp{XR@&a1`aobBd5)uSM<OQ5#_Qqsyyg+9fo5WP7)EdeQ4v~o}Nu{D!cDO>B^m
+CEj{#OoOkUks=O(OEqjDyz^)Qcot)<x+HnU)Q*%*V=Oy`%uoBubVpHHLfh8_-qhNmZ_vsH${`bq*sHy
+nyG5zpyXr~!kqsDuN0fxq3>?!US{(iitSYP=2(VoZm!jp%4n(2iH2aiN$7~{o8>UT2z>fvv-Hj%$gW?
+`Ed`>$N(_G{Kp%@pJrZ=m;xlytC$_y;Qed9Pq$GwUHTo3XbCFg5b!bT(tQ43B7JDC9<DwOU9xC&qUsO
+YSkWdkO1kCwmTa$Q&`7b=daVjOIcVSjOTJ`^bi$s7a#kJshOc-<nq=2K}-IzNVwVg@JX3C4*wurG@c{
+foJO8FhhiMUNm%JfUKo^nrJqvdzO?2Bt@>@8>H%MgtSG!8zWUiK%S~j#&|?3KK`RQQJ?WAqJsNNz6}&
+`%D}7p`b6-&HLScucL9L~<jY|g5HnOqdIkv+d!`_bt>FlaBAY%D&|`sUZ30U5$a<WklT%r1A;A3D%~Y
+ANL=AwB5C~#qR~COjG6xm_#TmkeAF}x?RLE=kZb1Rj8HQR@IL=6n9=svh{=xUfS)J9}2T!Xyf0NhO1x
+Qr#PMC+3z8QL8pc8TKNLdv(qDEuCGiiC5HMHo)$!LP&VYYZhU?ZQ{aWVs2wzMYvZEC-i9;07Fr^8odR
+A^-qL)40UK;!*}JE1-}2|>#JOK3`)nZjiWvfaoCK%}cdee~GJDr!tTfJT<Ao?ni{oy0dieHgx~Zu0uo
+)8Sz<T(9SN@6wYg>^}MiHkanjM>O0RD3ip1Q^Y6K-QQ+7673k`nt6I4hT6HuS2esGfBW0tlBaCoSZ*1
+bQ2Yih_rQD2W;<<7=w*q5TERA#GS3$cyH;ER((@(reNk@S(`7(<d7n6wzYEX<6jF-|?L}ri;r1BEtU)
+6%Wr(jx%pyUZ;`zmwDNt89dnjy;j3Gi}bjN7nP|Gt;cx`0QpbZ?c4N`g_0KYp${$`m0DIX+*NivuY{I
+3L62F4t+NIzd3eBKPuBGNsSWowWW&~QB2+2B#EK@4a8R-a&B!R3biMPm@M-)xgZ%Nj_ZfZ+)*eZtyEF
+=3Hs4N}4YR(n}jn~Tdt9A-tA9w_;Ik{Gw+bWK^I6NN1G=-uM}_+3i>9E{R?W7ruU@y@TgiT8B?WS`Db
+pt#!8=o&T0$ytx-l}B=eEu1#Mo&Tp9>U9>mWikw(wU{|OB5Y1V92UGbAl&P3_C!s?yj5Foa@^d!@a>f
+a(g3_{@u*8@c8p}01<2Vlbp+)F5dmLyM>gP)9I$0{Qx@;H$;&r+<5LD0i<uJ+g3OPOqw${Ec1K6{y~E
+r6B+nWcLe}IV|3rS5qJLzIGf_*lKxM{I0{{`Pci2nq_Ly<=CvF5dzFT0JDUA2jxQP}MyNq9p>h+sYIu
+z*PK{eFe;AFTZbV(SiIbvm-oaOK^58ycOr{rP!uW9lG&T{Zwc21shbQzIJ6c2m=2L0-Z8_sWJsoDEIb
+6OF-T+f({93_#{*;z9Ev7ilq-{l(?j;bTwbWO$9{Ak?eQfSlMcZ1KHRERZiwEc9Fcn=;&V8QUZB;Fs`
+QS$p}3%NnvP`-w-JbIXZF^D!t^|gZehfjj}yDrQg=1-p_{Txo+1>EN(q4R#DPiB6R&9}0ru`5v=mK~6
+cJ+ilsDOqLzsGJLjOn@$7l;*tCAt%G`Px9GO5^R|vAMV)~-DY2mqdJ$)V1;+GBnl?Yqh${!TwEfbhFk
+&p^2Td0(nF!-YkD4H)?G#vp>jx|LkjFnnLhb59w!%7f)0Uu-HupgVLcp1$SY0}#w6h<Wax0$*7p?}cz
+g}t%zngS9e8UME!;W^!c4%KyP<4EibNl;b5zp8R;K4u@qFVp?0Z@^CqrXz8J^15o`;#=0zZLYwT9PC3
+x&H>%~uU^0&tLZ-w&Ap6T@I^R>)ge2#VL&i$XniwG7r7$y-3yl(4^%Ru_<$CK1fIngM~J?^~^KX~7bw
+w%w2god?tlB(9_oV4fDmgM+tM2bR|HX^jUte7}VwF5ce96e5-zmjG`N#HnaNz=gY>1&8s0tbgccBSWF
+XHc5OOmd%(kUTR06>O7gzC#;Yn#GVn)LSt8f31&lNB=PM}JEPL$QJ7;Lf%LGCNI}vS7;|sP@DY!d$89
+;h^9|hc+z^`FZMgnW2w-=Vs64&H>f#uj_libw8R>mqe;TmiPd{~-G?rjZS;N`!8921c?aQp0nmDwP8o
+P}DS(Wo8AS@CH<=$bHh)Jy&6ky+Y24x)Oj&9y|K36_#$S}Ht9|g&NDiOecM=zFLph+iHos+zGw#>>a`
+c1-L5(4Wkpzrf+LE<4=h~X40$wU0IXxW<pFH9WhdJVmiCLo8aoPe-r2ZJ-vB(!sXHp77snie&T#tmhD
+iBUVqj3VDqt%?>S54}~eD?t8dkrjB}L^cOj)Vk1olO&^MafLCEMz6-O#<STt-j}$>MSA;QmeY2`5v77
+5E@oEsXn=LP>%Ewa_lDo~@%wyEkyv)N{FUh(J(rh7zHr|s=(P=4oYh;lrO0UsRo|n|`B6qgdts5nUM_
+~lcv`kqCt9}YU~$J6akOIpxQYE}+FfdUi;}48h1UXJ5pD6lo;f_83H%v*37_SGDMH-ym;}X#%HEWpHc
+-@`qE`zI_JA-zQ^Nn+(PF&FCyiE=k3!+_SHvPw$dc9QHy$yPVgqrsV}v11ju2t<wNHe7U)5b*ctpdI%
+U?n?LVwy_-5ToQhsl2$^^imCd{32q-$fsj(GMMKeeS(M1rw=X@eGZK1#OB|vCL|^Dg3ETr|4EBmf;EU
+7e(G^PDOft3YZU+Nz7a1ctO{LxqPTM`8*kk-tfqbW2_xk$lPq29wjHI-8b7QM*p~Y9{ci)-b7wl@5#l
+qt)}w~ZXir^&<AHOMj#o07WvG`M4RPHb#B;ZYVKR40L-AlZc9V|YxX`^2n#u){~JdL+H(%tce}%?$yJ
+6n<k5WD^mrb<sxff_-y7UmZ&ciE=msY-UuyMvN8e66JS7=vI<*nw#;doPPD3SiC(_sa>{DV161L!exd
+8c)oCQeUAQZy54DG%XlcjGOE!wjmtrqXu?*|tG*0Fz9H;wVN80oomHSWImPgK00V_-7x5-yhK@Ekx7b
+pU2IyLP?{6FMZF77M>|bodi~3&*~5STns+q*+KoMx#LX#v*haUG@_~?3P%*YSS9iKx5n-HQ7;Looy4c
+@|ZwGyhg|+F7X;#Y&<#DzGpu-6q6Xbl8@{Hc#<tPrp;}t<u%?vKf_unr~Z-B{*f;!B3{8_XVbwEIHw{
+TYvtEsL8!Va8ghj<^uQR+{ONlX!Myc55`wd3$s4gEjgk&Gs0i_p4WiJlYP}_W2l8#50htFUho`(&(pM
+jDA}YEr-5n9QKt91$;VS?m8L{ix%)mw~1v&z-)UoYeR+!Gf0GrLa0U<oq2`SCsjzq$|X*d=R8wXZY18
+H8>fC%e~I~IGEy`{Dj<0HEzf&r7ngeb|3USb~>P`13u;0|HqG<WMyE=O-B)WNVHryPeh^llw(@n`hbs
+Q>eMhPwCJ%xnitYM%L$C@EGkwg8A(MPx2>>e;HC=XL_#XpD=M2iq|cMt{h2as&_UMcy~*I7$VA3pxeL
+B6PrPl0LusqBq8UL0f%7%rU%W=i^tYXfC87DM3BIH(ArhvN%eQC$oDib~e!tiOM*_TG41x5eior^89*
+bv@0DmDdb9kpQrH07#04k-ZEn&?;z`2><{T%#OuuOoJ=f;%bJFx6;W~R6#D2Q#rx*qJDkgG*fJbUs6n
+ho9Yckum;PGixdgBpjemHlU=X^EMx|4YqvUAR39j^A$0#EsOfTGxPMia0lET4QbLvcwWCHjc+~7<*Nc
+Fc!qia@HpSos7)8#nGMwU+Zp)o~tupy=ZY(f-|7v-Z7V?;d;*MQr_1ow0z9r@r?d};R<5*T=2>yJ9^d
+gkeU6rZgZ+e#1Ra)ho!wi2x;cqtQ+MD?N1rIDI9^h9TpQENvyPXSG%&yk=9ahh^mm4Y%NDY3rJ(?XMm
+K$rxhkG98o7D(QJkD|$zjh}FW8@yVU8ZJqdR=rL9owD)z*R0$siX)t`sp$q62*Y^L^wro=Sukf6YWSo
+Rav$Zf;iXB#g2ONp9?IE2YE&@A(O*{DH@VWRe9=Q)3|{Dhd1?77BC#<|cS_f1=pTee4!m2HvjW?tju>
+QWZB6(yj_dMtL`V~}tjVln)-_QS@wd*vw#&GNKX);(QM+Cv8$<C7ZTzUu*oHsaHQl&XG`Abw%%V-Fbc
+i~h=k}cVXo_oty5q%$-RA8T5W`@1WKgywWMs@USGfF9qJDcW@lu#*W9VxuZgS;eL5!eb7jG4!n>;Ul?
+E<q1zyk~3#<_Xo7NL>QwScYa(%gL-N>)?IMV62UB<F$YG?gS*`CjM55M}Rlc7g*rje4Hq2X=&c#C5|g
+!3nfHCAa!m3*H%Z4^VSYz)-xI@N!2?`G9lF>-Gp)G(2$R!gs`6UPl5E{!KDBS~3U1bu}+kCQ4@UeS&M
+*{$x{H7G{F%j+Ju-CxAD`01L!dX1BRphaWFNz<pnc#7!PJux%|FP*gV_p5<uxKi4RyFsvOmK8rtMS>q
+-nPmVy|7^g~@vJ5Q|_&(HTY#d5{49j%cv>mih64_yT;|LF*uo=k(7kyJM(RMI1TZS7r^LQ@mk%lxOvC
+wJcOu&VXa|GFBbB1K*EJr<QqSPh$V-khUDZHyUPL8q3$78xa_{Fr6P#jrnD^{3U$iL%`zHr;GEks6%`
+Y>2yTZn4%(_|`a@_6@GUT^-_Hdc`4Vfm|6lLkJc9VgR^5;?5P0(MMp`zofS+f$h94!r5)R2IWsK8|CR
+iz~=Ims)-iBjd@kWMwM9t6j|RNzjiON2(cD;XqSG_PW%V7F%T5?m&7#Jnq7H+z*7~y69+3%lt+wp^P;
+G)mvVB=RB<SWbSERUNc2?LzQ62I(RO)F*PyDuoFyh6)=qIYSecT6A1FE{@sqA=uCfrkHCC9AZ9H=FeV
+XhriZP~P~LNAi-JjmC|1rX)6i_D98HiYGr!I1oa@;{Z;vsdPE_(9vTP|m;f(Xvq6ZA7?mbu7+A09S<<
+OmRW@6xNF6MHpb_8jIaJeB3)r<$s!tT{<;?1E$|BCXux-xW=EcaSAC-W{G44lRpDalbitMp3Uh;==<u
+W-h)YBrpCHq%Z$xcIeF=CN$7uB0FRd%?ppx+5kmv!TO87!aJB`~Ye{-OvO30SPD^qACv8#PiV-n1t1=
+BLv7qdSC_?8tp-iIu8?!0{6NRmuL?VXWX`s+k`RB7dCOFI&8czfF{+M)$y6`gG5$(%aB4#_8bMR)t5Y
+<MhW6G<~ZUi=mq7?%~@k=uG7XhnYjDXs3_UggZaXYvXUb?y%k<%+XQoaBy7rDZBa-6l}{zmITv2g?*r
+Ie=EOO#nUg;WbK%AZ9>(N;OxBw^U%KN`(avW}Jp??QoL_ok^PBN(>CoYsZ17&^U8i|R$t1h9)*F|XEM
+Os&k{$V_&6*h<OdA;octjg9($B^xhldA`P6JRCxx}KM1zD*h_AmF^lQZ^-J3si^zfR9`(z&R1a1|Q-2
+~3@6LlG1?N~S<TDbg3kW!1?Ka7!T}s?L2%Qkl{F6wi;jFWRpZD8Qog&61c*jx|QOlt(r@LxYk{ijjtE
+O6e4ibmHw)2ruO<gpsH*1BNYq^bT1WSy7it1ckseq<rn=0r@Wle9h0vk$+y+)q3=>qgKF%Y~SP!i-~d
+1nT?un=P*?co>%~lLd?~}xuaC)Qa{K}n%urqjLJdun+O$%xQfR?YOUQ=SPfFjcYWjuJYw7=#xx-Fd_8
+e&hL=HOqVduL9H=H?w>HhC4O8$AS!L4t`v(z!pzSm`ki=&h1qLZXWo3eMDKm4M&8huHA;``^ZLD{6u)
+_VE5sB%D<^ga-qp-iIBG#<uNznR~Od~i+k>*%86$2rd(}BP^FN@^Q)nfPwv^X`%($!HH?!a6|A}tU>4
+)<J|YIJbQqd5Lq?b~mMeO(u6gzT%#O@p0k`Tc}UH;4j6i#_I!F7pL32!gq*Y~6eMVzvR@HW&vIlTn~7
+mt0(()rnAp8zYLw6hW|-@#)@aP4o{!I`VAtTHua{Bj+G|^h4aoEXmHRAa|g-ga&iccv~U*U020o2Pot
+s&o?#2U__EMsU_S2MDO`0EQFTR!ynomXU2`TRfu~c2!m%6I!f``ltZ+lUC>#&X@c|8<<KL~I`E<aR<|
+RE&3@wUT0E)-{dIPM&ZlJLi6+XSFI8d{{h6WxS{Cmf^nT;h%WB<lBBB8<@gQlc<UH%3PNuS!`Nv%zqn
+qc?{=|v2`j^rzwye}kTIGSh#m+^B_w{mf0oyN{SpI8DL=+<rrdELvDh_Nug`>bqZ_U^s3duqfTi!8D&
+0J?n@;`o`VbC$>6Fxlbaw!(ZMAE;ZM@x`>!_KOMIQryC|BIsT=0q3=TaNTwfZksgXHC@227k~FrH2C_
+PW*9)py4GPudU1`xN$MqWcZZiCi0o9vc=F$eC%67^m^V+%ORQpag}f~7ix_o41PwYR&AjlHpzf{buO+
+0tqL$t(G!FRX|O6#Y3v-Z1!smz$Tc_V5)Pcg#T#|XI)2-u*q9wdVLO)?`Z+nf0_tws3dkm^5n&}np^w
+UFM~Yz;J+}!~OcM~+pr8s?q+V1CwA;0STjd$&+Cc}RdaHbc)wSXI@fa;ngE}0H&j_?fjaCcz$_exZhw
+Bhy;Oq;laz}xi^aE#Gn@Wv4H@ZfrayPptpU#r=Wrkwhg3NUd<`<{i6XbE;NvEM{F;x{^!vZ#`mJ65rT
+e27l8nKrMWe0CsFGV`-zg1!hs70#J02aLBeXx0olE(+_2I$FQGMag7Hbb)v9wQ1qnvHR{v_UXv-Bq)M
+7EDw*g;dP|lkDkrP6rq<bpj|{Ip0W=oV@4Mu@s?%d%Kiee@)Afr2cdh<AJ+y5hPG+eSvREGp58IWp5A
+_aal$Q=ZME5C&P?{7dZV76?CGZQ~vduD~@dl`CSqU(&qYFM00(I+Qf)Ek5SXc)itsO)`l!<8MiZz1n<
++Svc@m#wVy55m)Tj~lC%!k+6OyrBzu}SeXf(^DP;Ub<uqsJ9U#3SQhf%cyR*;O_WqH&$=%R83^l{Gec
+#t#IWl>fEvg%-rsL;N^%zo=+1UV4ZEELEUn&5$E$s(hmF^wil;kg<mh+sW!mTXJ35mQd2z=L-1Bsi>i
+G~redNUu!_9}{Hu>$dEe7e_Z-tjGWaOhZaq=1{6a!n2;)NvQO_@M{6_mEm&$9u)HNI(nt<aL~(ELe+~
+G*1)~uA>bR9fi*ClD}FmAPL0jee08SQE%dc_kM5HP|=~@BKlz_K~%?9Ch?MS%e%_+b#hVd64X%RcNJO
+m-Y$D_)oykqy9ECDcXYJQjRw)TwHu1Zo1l{--UFmVz$$O(j*d!2eUIwZh{6kIA5tZnYY(^TPbZ{%O2P
+;^biz4p$dpWYByrsHlxu!iq>1#%+F+p0iO#nZl1sM;cZ<7N6FE?h{2xZ^s%eTdU?)rR^&DGUqq@eaT<
+S!;UAHE(E-?R<3%4iMus}R|xLWM!&3u|NY<6MN8aPX;GBMfdl3)C0c~0DB5FGOrk>xsH=GR#nE@oD1g
+VlVwA>Rz+-A=CZ#JU(C5Z7ZN$M05uDH-{ZaVukL7!UAp$PiouhN?5L9d6-WtQ7vqqM&msVI(vhF{;f0
+fU!yjk%eT;OJ;M&10&*u=HI}<NW+`i2sxGYYfd+2$zGn)nw&Dxg$Y)Ex$O08v5dU&;jqp$v7jYSk?NW
+nC5U;@@ftCM+6goC+YG&y8FuK?pu8QTUit|2u9NKTLsy@QC&C?daY@*hlf%<V{H6Hca6zp|8&Tu-zTf
+Gy-TRfDyEiaD<F7wkK<Vk#^lVyAb=a8obi(c?2@iIX>>AW0(ZQ1zsE<`HPSP!4w}lP!RFm~v*?3QH8T
+~f5gnr&(fqPB_xwyM^wt>0ISi0zDGXEi4M_ex|&m>PbS-#3Bpr{D5@l&D#ZOBs=59NE)6a9BA6-f*Tv
+AF)6WEZG1X?bvLo%enG^nmQs*DAe`k;)O;C0XgY54!5kvqHHcOI;Llolu?=D*sWOn$ftX_;uqYCC4As
+YIBFFDZ4WIFyy)|hy3M7p93RDahj<i8dje?8jmsSz3d1YPe`4qSh$YXRBWv>hJ>q$jns%;x)LR#S?qX
+|W4=ccu$wYlH<wk!f?iSFKD8u|m3Xwahp-cAPjzENDQgl)9rYEwgC<m)^~j{yCXhZ#y)mQgb889*>#*
+iYC(zIO;>^@&XD;~8`NG<ja~R@(qf~@}ADB{>k*7Cn{^Ghmzcp*Xv;xhn)l34FtOtrPivjOPLaFd<Hk
+YIU#)&m{=YO^AsH!oDS|Q&B?KbyhlaI<~LB^TTPRl%;b~l(0Ou+K7c|#5yN{o|AzN0+7NMY%QU!?y!o
+Xy70!DGi*{E8;{^Y>~)?n9~~AgUGAnvZ~_Jitf^8T^>zF4>_B>Cm>?Sa3jFE;*n2I=KfF`(7x1;K}_5
+E-%1pIxFm{txWz@n{E>ZA(OZBh!HMUh+w}sif+aMm2|X&9^8OCIg*3vzeMHKNF4%o)5Dvo??T^6gyC7
+C#VedEYj7@;N>W9tv-gc}Q}81ZaV1Ig^01w5fwi|(ih?R%2p1zLwQc>bsltS);3=CFr?#_*c3XhmdOP
+I}?pz>xokhRqy%*jUn%I)KcWicaq=ENeA#QBASkWZ23|ju2_{ihA0k5j-ym!}M(`&QY)^wqkxfgkzw{
+|L>1e~-WW9;S$E)Z0y`n0=avp@qMB4N=*gxjx^|6#WW27h!+W@rqCt>Y+ktwOK|=YfA{Y`JqR3}lKva
+k)Yls@^9Gs;S0R$htva784i1WZU*DS0iED_<h93Bqp3&$qc`-qKfCW6whtMmZ5{TIzW|U)B4^<UPReU
+gHtBvAJNYk^J=2QGgi~3$X~xTpV7K#(2fV3-G(+YW8I1)Io1ps;<mBOxE91H08+qii?&9GZ7wk}J&s8
+dsudKsrLN8}l-L$(XE{j^J|$qI4iWNByA4y<fH-QzZqTmlMMYi#`rV*))Z9pvtieQYlfZ!Yuu&hKVeA
+|sa|eY<2xA!3p$k;O1XFTMMgfN5dmB$<XBWoB*vaWn15Xcv6iHN!kK?W)eiKrOLPtkfSSV|&I>iDGu+
+EspX9!ccoUhhH%1w-O;pix}+{#@?Nq)+ipzDOu8?_N}$nfrR@>28Es2q|iR2lgN)$vSo1!CiF#3oMp4
+A9xc+KO#53JrmMhe?#o6kRR4&LKLR21n(mCW{90j^q#HXnf2%NN)PTF&pTCqrEZqxqf_Ys`YYk42w6F
+bW9gS79YN1SSWIiAWHiEz&fog-H~VzrL1v064%zTsTjf#7&Jgj(gnK0>=2{016P19R8A_=6WB1}3^S|
+%Xs|3m<>V5?1S3AEaZ>Cehdi*@?d)9+O~Po2-Rxb*<|dABoyt3&<I`PoI{DFY`Yc5Zg&y{)VR+nPB&k
+6(jg;raAF5ETH(zJ8rd7u^tq-&q>#Af?-H^Hef$T^0iiq!<qf_$Ui-zaa8$NmRY0yg!fa%L_qHQ!Ykv
+Ff4%#K(o^?gW{oCyS!H=gz_0)=8nywgP`MnexN(&kLOFkTiU<>)H<W9O`m7gUbL1jG8r%6QX>caT>M;
+e{#YAt!+r6bMx6d$*9m=n_M4*h6Fq7e1cXGhNmie~`%#_Z#*vp_E3I*+Q-t65I<|c!2D``1VYD*qcab
+HJ_}$*bvj*jkpzOquY)^eEB{hlK>8BQx?F`2VNXP?R%WV^nk-CdCNtRjdt8Qe{?##Clh}-=pDmL^$ak
+Vmf>+}BSOp4fdu9*7KP3680OaK6XN_d-~_%mcQ^i6cAQ7zNaZpLNga%FR~oQ)X~`4ou81aU)WrB=L{`
+rmp3iD^?em>H<WDoYaDg%Xyhdcz>xDHUctYbSU#z$5mffPPXQg*5hvA&!GZo)2j1h@A(kSJv=yF+6>p
+MVm3Y2Sus*~8NV+Z%i1H7Zj&Tl9&exyQ<Nsb>c;Ou)JId!*RRetn(Q?|t_537?(p=Rq3#=3dBVH20rn
+zsP8PUjU;G<w_e7;+BQb7z?}8wORK>w|Su6USl6X6xy+Y>HNSDbZ_`9x8ysKq&3T)bsR3ICOD1?@czh
+2<Y4{41=iZ;-V<C<&+k}0~7JAlYm|F&2*5+zz_2`%jy->R=IiYy7S+$L9xnCO2=4JgL`k(1jN*6Lgtd
+jsxu*i8!Xa-@<40%HZPB^6ulE!pSzz{_0;1b?vg$@$nHyUzlmfU@(LcrI~=Dwk{9<TApXTu=t)mpI@7
+;PRQyXPv@=<9WJ)%7_b;B+?Fqe|C}qI>(%Hq+j(2XjV7y8-+g$+32>$D*zdKF%f6*Gq=zr}BV3zS;y8
+_)AhBXj=i`n8xf7NVF=IviRT}pKk=2VZIYZnypYmag~1-YA>qTO`GMA+r;3a-w~cQJ6t7-3_WI6&G}q
+wi(J;8EkUhT~7QTmTK9i~bmX<H8-|6BS46E=!xOCb(9hLn;Wu>Nzg!sXYnX)p`lvVmQ-H4NUkV$9N`x
+$Mt&R53_#KlNmelfEO1$B;UQ#=Q0BBghR<eVwMcD0ay=^$V6f(w7ms!OG)xU*6w3>9O1W$r$AMkEegu
+9j9tiX#RK54^7=AcH)t}g(e77m(D%=z-==IBlml8-d?5D6-9R2VG~QCW+RLoGkVG26c+Y5*tx*WQ`up
+2IzkD&p0^LuaJpJ>r2Tt?P*I8Yd+zp&NkvV7{Si!=ZbdvTW!Z=-04HKpLhMh&$HDFT_!y<Llz0Xp^9R
+}gC_{zia2zQ8We2x#xk}?7~GC<-By!8t|IB-Iq&=dnFS62`@8ja%@&>4A*W0VPJfkH8X_lWEv8kEZF*
+m&w)%$Opjt!!Y@xzhfTksPOPlW$4X6sIRc{Boj>()$yGgKi1_D4bcYH9WPs)TLjg2c0h~PQMLjWyJau
+R0&H=Q0R`~+W)gyBhb&rIu8<hx>7C*Am4)&Kn@a$`Io#evNRK2{?ZFmQ~a;9Ceq5#Al6vpHW_S6pzi}
+7&&9>C(OkIMrk)@s>5IbgY?3ohB_Q{Ut08Y4gtf6za?TKU+3A#Zz6AVSl3_ON?Ta~CN)M2HK9N+w_{S
+A9vKM)YwhmL9hOd)K&Mc;!EH~=}<l4O6;rBIff60YmK(tv+cPT?KH9h_TWMrhF`zI;6p9~Lx4h$#BJs
+SCratPD2ExO}Px$?l&o{N#{xubDDc9N)u6;6;ZYjyjvUH}C1a=Iy->^z?a%i&Eb{7_3_Cu(?pmPV6&!
+M&G~1n4+g%)^=ly9Psph&v=c7e{ufC9F`;SgEUPm_BEgLtHe$`XmWssxWu-9nv-%IP`#q4`B1i6RKM0
+XmMS$uNFGIZAw#B6|ayMvxK0OU#a<<Ja}eQ7*$yqw;(beWgA$88r?@>xLed6r^!#56hs5b+zIh$Zc47
+o>c)**5#Wx4*_&Jit>?-97r+0K#!9gqi@Zg5%3d=+V7JLyJ1pCwE31ttugYpynBt%A*OTE5Mrqc=(?E
+N-j~Od}f_D{W09fZW)i#iT06Eu7N{xhLWxE*A9@)+S6ep$6S8E;d%b|-fI^;6wdOtI9j<|rBK(`9v@K
+NJLT(H`h4=|!NwvSd=d6^D9qAp`&idIy3uGfv){a+Xi+oo@(&wqOP_Rk5ex&QdP*RT9VS~V9PZz9^3<
+1RMqSyCqA2Q*i>1G=A6jL2q*Yiv?h5uUPVROADf$15uTCZi9;0FKkx$4_Bb@tQ!#UBog$(nw2-x0qdt
+`$JQDc<fDa!U%+r=Zo@r<JA9h9O1^i27(Jsioc9tS0?DiQUAn`l^g_jPb+z9gnvS;WZuavmQSyMOBOG
+-ZNybm!IOMgGXpR*iWd!s5L1chOW=8OR0x_XE0%9qRAv5ESnm~|4&9;RG^^#dy|f;u*^)130ko(*U+o
+S*AkF6NvEq1&moL8myHtsmz%q>fROtz|W)?NWwaHP&U2q)JmVE(VynM?&AQ>)g8)bho0nCO86vMjH5N
+Xd_yRasavvDLH;hU<?>h0KL@DPlcuFc+h3HdEU=u-2+AX!GoD5|XpF=VJxrL)E27u=UkPqcABmH}gm_
+rs9Z{*YannnhM=iADcB+dTdVMH`I_O*5-v>DoB?&*WkC<(FTMfpk5reh)t$1o&`%2@OXM^XW6?$k#p5
+Ru>Xp=WnFY0&(Wd_Y;!a&9*D+uF|$5u9>5*)DAx<_g%nUx)mI58Vjo!AMqr*;lVcI+R=?Y@x8BbG@<j
+c7g<N{eG%Sqh7J;=pHP6%_=0n^c_U}Dkd)14QDQb>I*ET)8<oJXLrY9hEjkz?7r=H0o;$jbRdceXW;R
+{?O4ooltiiZ@?)j$G>yO4@eG}WzP+T&e=4P#ZRZ1qn*fR##mgaD%(toCcBrTrt<R+dCA>$S1&b>LWPK
+cafqD}TBK^!3ZK^QQbiI`w-wT3*%6u-8}m${V3^!c@h?@J`9OqgsrkBd!KXCTMqeymGhXEr5)+{WwxD
+=~Rqj|!bfFRC^_<mreMs&peEzsp&+d2y}D%bt2sHeiJxb+qUnAcr|S3hP#Y-E!5{xpw5}nPE?1ALn-G
+<c64)^{;rGJTt4zG??W?w#5nkGVDPpsdSA^P7WdW_RcJrLcub|Q^DKcpE0)hduPe6jF0@`?D;SON__1
+twd;(!YP_$uR$`_UIwnC6rfE_4svy!LNVR&tDS6F&Z5-u82Na-dZ;rX$0m0@X_f#$ouLb6~^gu~)V?4
+GZQdj1Vr#oSGRv^AEH<+WDPIQ7?&oVcu|GIuC+DqC`o5LgdDmd*$tAjttWGd+sx!_QybKqnxX4Hq{Y1
+fMbKy2WL)B-em2J)KNH96v<ZE%?66pbPg*~oQGc>e<NL;qB%>^t8Y^dTqSHy4GC&qnFU=~k^IyXK^U%
+)bm+ZG3QianTG?Z#Z%VIvJ3BeTU(|hGXpC^bQ?0DRwLxNHjLMom~?naWqt&4(Y9_D^AJ*vc&mS#GkUm
+GmXDKD_Xh~B=U$6%;YEX94N?yLohG|px$tH11u3jiCIdxC_yHDkh(h4d<TkTzc2~d1bv4G!{`##c?uW
+hXn67;PY(V)JNW0rgFmLH_lFbwz_0F3^D`dE@^63zcb}^9N9C6u5KsBE?}Atfxw_FcY;|jm0SU!r6Rq
+^uV6c1vh<2*m{CNp1Q?Zb*+!$=6iw%R4H69HUT&Q%|@u%6ns%AX0uv0)jxD?TYvv+yFH6h?c)@C!k88
+egCi?#@kTD7@grta&nzm^)325_XW;luRt7n`$9*=`;UWsUyruli-W$gdyXZ!(O?_$N?u+xY8G?B(E2@
+IMvq!88W;*TDSU<MjSFk;Q=L!BTwUB3$OnB^7B|E^Z%lO083A{k3;U?uwHft9F!3Umd^t-R~YwzkTxk
+_kViw^e-s~xL8D^#;7I2_R6mX5$cGao(%A>!KuP^a{Cn!Cm?-}u*F#7-F<g8fi!qH==q)=lj;NWF%8@
+*e3%llH~9r6Bf_u79|tMhxd!QAtjXE=-~+b)$V>Tw;C&pJgXRH}fA2=9i<0RV&O$ykTOof^63bnu-t^
+b=(SiD^=OdrE)Wdga=bKc0W0&Y);L&ip`B{hlOKvF%JHO)vb=T`@I%LC?DeWnK_7tE%F1t27XmRIz?1
+0x~I+WxAV;dI4tI<}@d#2~kw%(nUOYKB@j<zDJnfd-8Z|2#WS*w*>71+aY0h~44UkVszbYc|FWDoZNP
+sq%m;45p&arq;37znQ9zv6q$iGc6e6$MB^^5w%ncsv;c_{wyu)7=@;Abr`eR9D5oAGddZn`{N%2=z7m
+W((r}dz;=%QH(sbs@)*AAWxS?3D;csTn3-(<>LriUai<*1U0m`zL|(kC$VeEQqBHm$yrq)CvMV08aDv
+Rn_!T-8}KP$NYd0xQkZ-gRGWf#AT@5HT&`l7JC(_%5%<91dW*La^gl$^*JinElcWb-fk-lFq(6k)rj|
+BLNYTSy8BoGr{UCWWyuGf&iI4IzJGkc7$MXe9lSTn!H|i}1b=YN4nggUHAf;u1{TT}omagG;e(~@zrJ
+{tPIrq<ti)n~(_)Kyc+GqUTZtu{Etb6DsYQF`E1bur)+zgNPl;2H}VEI1J^d&b8t-K(m5CMyT!}CMHh
+QsmL_p#{nd=xEAzw4J5NO>+*!_>&aFMGQ6{0;BgX;Gzr+O~P~{N>1GH0gN7^}yOO4(IjvX_H5Z^3Kbk
+`uCh|BYt~*{lRy?s6QO&)Eoq@>AuU(8tk{Cpq_;R8iyw_WgeJl{EOE@r7%_g5Rp0fWgR*z6{L#L-~Y<
+t>U;~IGDOzLtJWjmYog<Hq4oH{&(5m_FaVqO{NNA6j<3a!Wr6RXQ7d<wzMqFynCG0{j-x<H9VS{b&m|
+Jo=SWkF^KI~bTUVR2W!_v?6<3>}QUk!iP$3)Ch}u|4>($?G*ST-QhIhczWDUH$f0PVy5Fb8@hLKJAhw
+xx%Y@%$!@t2EMh(Zygn><Apq1lP)6sV-yr5=)m$0+Lley4-$KKRt5YbT@o+|iZ2tJs&Muk+wg-|ioLr
+)la>e(^;8e!EBXj?|=QFrA49-=3)2tev9AeyLy7e6O)0rn=s#0i5t5|JFPhCinGcQCi~@QfeHysW5XC
+<id?OWW3@2KQNHb>W|ckP0MY0p$yyT<$$IGbJRLu@yGcjbY2H3`o_U(OiAoGO1kGurs_nSclEmxc@_A
+7FBJEe{;uyUB|r4xfsDd_Y4`QS@lU6&X9H31q+!HNXpi4A*h>=i&|j<54(auI5h<M|R+}Syi$rq~?82
+PQ<>;wE-r3ZA5{`I+a(g}>jsrTJ&qoMAVYEhWcg=KS4~aWR;wdGWscv4((VQNg1j9Lv`V=kQx{$;%>9
+ly*eWa11fh(&W5i;~Pv@6nsxT<Nmw63R5SziULZ<!slX1KhLBLY)_7ghV*$U6BVLJ7n+xfYimk~29Oh
+cT&dN>yf9q!GNKl^3}hk00#yKVd{+=*s_uF`b)S0O(lIe_t{cx)zm;lR}7F4CE&BO>ypni(Y!3%P)`N
+p7)hG84rftTMygs^nUFb@D9gUr*+c)KKMaHVHov7^oryjTg{aT^0IB$&EbOw4GeDGR@D-wwq0jwQ9a1
+Z2k1xLv=7!-7tSo6Ubd^{KFp$+ADD*+95>-85$fmBbB=N_!$ovnyobrd^-<?@e69|zX-eL9#0KYZ$|-
+{l>mq};*EMFn)9Q)7Jq|w`4bQ9U!C6+P?fW)>ikhSmkJ!EN^TAmtY5L$30a4w$?%JeiN7i|hY!|<}13
+O(9Ed2LhIaciD{L}gnHKF-aoPt?GYVvhP$&6Tm+q6JrE-u@H4Z8X^lzKwDH<)46!*}oEi}tn#qEFVm(
+W;`18go=#k$1o{^U_SEX{ryEc%U3o<+th_UXuac1icu6F7wY^@@}s%8K`8ik<mUq{Qtvv|Fq1?E0&2R
+AfB6aXEgi;`~IRT55(x9x`2^HR?OGX{lYbRVxs$Ho%B1;OG%XPA=hLGKVT^ONff2{!4tJ7KTQ5RU;B&
++$Ee6#K;pAz)D^EWCZ_Fe(aDl7V~i$Ax6jy}eDG=b5MYB>miWoV1v=<bNp*W3?E&^cH{OUlGjpK?v6Z
+>SCk*E0l@F%8?K-W*gvi!cls9nG>d21$9%y#3O|!|TawGZM5A9B{hAYUK1JT4_l>?5eGx`^<<|Dl(=w
+bsGemd~^-)H$6P?q=~aVd`{S2tSE4(C;nPLNd4O3w{!G5HRG#5W9=P|54uI5kZJO#984I??xAeU%;CX
+gu^7yFJ7F8I?S;ej^TKpLkcjb>iTVK@VBX0p^T2NC~8o4U=;rc$PgdA0g4uHU|#LrLR6aqPK22xdV^G
+kk7qmtb~~=<AKl#)|Hx!CKnfGawBi1c2eev^A^sM>!NNq*;4tn$MbjhnMO8iG|Z;9owNv8XJQJcfT_T
+~jWk+%FM_~tpb?n8GB=syL=A!tt7n*fuHix+7#{)?8Nj5j@>cu7!EUWE>=TPJ<`)-@qzTLuZIO{YRYc
+V!%+8T=`U)j@Vk1GQnxYCq_QPOKs4vsexEDw@vCPm2L51caeC<?z<lBC6fh~h2qQ}wGYt<s6FEI#$J5
+1&w|3v!Q#vtU7r!_qO?z@BMFTQ;_jC@vCmBmhjchA_r(BhuL!w%{-Dqvd@2Pn&5C&a=>#eNan7p6p^6
+Ic><O2j?@ZW(^RTYj|=OtXj~<JVcySo?HWB`s`ZeKx$)4d8TJf&us;s<n8Saq3U6j9QC@P(p`L1~mkE
+G+*i(NkX345jkXzhHq#h-vS<dPwj@2*n9LPkGAo1PMO+kx=Vjf@@7s29E?4d6=TcdY`V%Y&tHy#0IV^
+hONCByVAhCTJ`VUKnRCH~;KZbEkrXw@+R%5U=Nyh9sX2iYqSz}_;s>*G0IhV^a^D{9OyPV&(CG{l-{M
+`hI$LCk!<j?PcJIb1L6hO|6AzHq<o6|Q!Z1r%C#s%p^N?V!1aHaQQvQ3f{vj)ib6kX2`ICPZYdnP1AU
+WF<OH(w_u2>YcspW|Fb%#dfPuR*YW7!m|Vwu%OjRM_^64rWq+pkFni^a&;TBz<SDh-Nps4d1F!4#h(M
+Q2V&M|x1H@mO@ACm|;kvjxJ2WY!mk1(OJRXUXG?nQ*MPYxLnaoO@ghqLz}%Aceu=u{F$lll&7O2dN4%
+n|V~%9Jh4%-c}EWlSC%eRVUMy(?BqXH)erhg4t=<HJWI0!XWT3syw%=2D8m;I&Ue_xG8^(qyY;BA&OX
+R{UKjf=s)RUt^Ok{-XrbJ@>*1Gf*L*MIY#1<a(ubWC60jn@(H6xL){DwH1=eyFh8EYQE>RZ!FTp|q|Q
+`!N5F`km;)%p`^sh`cC91|hp1;?)db(61|80we$xrAIP7SkHNNm-Avps^Wz*Q=7%5>U<snEJ5-{=fOA
+u{s1}-KmCJtTE+<`MK^?HxY9~17QTMkYSN7`ySx0?yG!M0LfhwvHDh8bgIP@P8=vLua`W2Vq>YH<tRL
+=koTTZ<0ZD~JbXwM5_)MjgawKIW=dB&Tqwr^-3%yb17g-$gul0uaZeWB3!}0;Vm5$7AD0Y>rs7Ir9Xx
+eUp6L)Mkkhb(PKrvl?*<3zONyQQ1b&ntw@ab_Nz|rm@wujIK<SX&Vl^-|N&1dcosDKYzn6<GOL8YNfH
+%5272aueEv)K5wix$SfaTW1lya-<07_ye;>9p(rJdY$v_%-_T%_WbY_T6~-xLln#R4AW#aKOBJAXlW!
+K)!Fl7$;C5d;th{drbBC3+0+hkpyREVL42yp~f`u00Kg5V%z3jFh!_Nb21t+xK+Fg*N)l-U)MH7!or1
+pvk(DS$QY7CvfB8IlR>7eju&>hB@qZ4g8GCIB36BlSgJP6W3C`?jSZ<p2lDu~{jpbI_F;+vdnZeRuyl
+1(fGgId-N!j7-4aGm=skCt{j|2BH0!)o;k0=vWt0B+Am%^or&egd+aL)kDxvG@4H5KY=2>pf}rRo>I+
+WKwYtpW6W0;qEkuirO%r!hJVw;PRqrVq1MLVa(c5V&0H9J2h5YyIn0VSIzyKMFv9Qmj1s`k+;-`@EsP
+8dw4$?J)9))-@zk|FOUBChlg-D&oMCF@IMRfCyyTks1=$m@%MCfh5w8!<j%6$FD5iCUYz~p+vk7#;rK
+8aDvqJMxI@ZAQB}nBFZ1`w=+Wb`Tg%Q~1V`3UX+8@-XNSqtKR$e<G0$SSO<xW|ME*X^Tdpz9Yj$D)L=
+tj~BK0=J@ibrtT*uFhm(47y7tHTRRmTW==<!WvrM>R1P7La~bL%6kxq7G&x}ExXFC>RQy?*}oc>3nYS
+Fc{aej6i)&tLYCz~KM}%XvoFE`fh<%4Jbr4Qx&%M-7L`(AF^*33J#(4kKQ&+0u|V*^M-kMbMIULo7n_
+<U1`HS3^|QO2p2{_7r6ug3YpxeYn-8#e_VRl>{{;t1Hw`t|OO7`Y(bTgRVpg7;qF~gYB@_BaixTQcA}
+&;(<hsFKSJKPcfMwf9k*55c%L)O_GtqMEh$1%<Pm-R%E_+Gx681v-P~(H2d4W6~zYzgp;AQ14lXX6%D
+01b)e!|`hPi!n4f)@SK%z5BVjV>e)vi+q#)pBKEJ}EXlK=R9@j%KG|Z4di>W2u?t%sQ8HZ)lqAl_zCh
+m0U9{@nTjebSt6N3C~{j+Cspq6>Zko)%d7f(`oj?>6@p$8Id62US`OK@;r7kRk=cFxaak3R;jccnLs6
+9_RaSWFU$v#@IU2tH{g#%otz*wiYvAFCv~uHt1!;P5I9{p!2KK$5E@I9qmTanZ$hb3(31DPG*Sx)WlJ
+nwAEIx)u5t^)B+<DqZZ<?$Gl-pFP%#d&#aTBHH7y?W?0(sH(5bBzuY4W@|JF>c>+P)yH}03M>=whjQe
+97X$@`+<YL9S$BJu1EMt*t&DJT>JL}3TBBh}!t!)koHgWHgwC>l-|TS|CCgne`G{Y&Kc1Ab*e<$J9TM
+#k;mY((j|5Cqc#v1>&=L<BtX*F)4<94Av+1jl{si7YK1Wh6{Mx!^nLWl=PGWa)I2Z4cb`J_AfAeEJ4e
+D4aK!L@v>kPqIeW5)$qr}NF=|$<gg2H3_F9vvd!c9+2%|Qm<3mbpV;5=N#aiZh9-qRbRG4%v&$$B(C?
+IMWXIcN(1#&#GVJLGV-=8p2PBbIv_M`<2A-mwi&SOXiEf_jYCoe_l!n9gW+LH4b3eXz;K;ekk99A&Ia
+Dp#-j@r3+O2v6$hbNz4-)L88bq6~E=zfI4(qod+pNLD4B+TTzBRWi6US)zUH2SYYJyQb6ToA=2jT<Vw
+x@|>^Da*-{u7~8AAupbBeQ}B}fh*5%vDiOc+syXue96Z3eJ!q>328>CAM&aw$>RRVya3n)B2Px_3ZDV
+>ibP`8s;4wqYnb1+uAgS0X`jP9&Oq^$&q(~2IR!HC>L6Y*Al<ZukCzr+QHA}?&Y2<VVOx`aD$MqrH9(
+t=%M-U%w){3(w2fUc=;giE<Gv=rq_?V91FZot<$S*3lqq30}w=mC#scfYa<q?lmRH<`X;j@yL^9uduj
+wB#<!pwMcG!WzMAjU)~EbZ`5d@w1|H*oC&g%ZV>ueu2k<b~SY*!QB)GEnq3*+x^$5`v+F|L_0ve|y%I
+P8$`;=TA<Gh73N~W%}r6<zqcOddX6hFa-tv`1ad_KlrL=_R#Gq5aG4#q$KXapx-POSE$-6n46_AffG!
+Gu2~{Oit~#Lo%XPYob4yi^6PwAttqDjS~S&5<@ct@8+)O>K>q=>5McwiuINTLWv7@>Z)2d1W3<$psR1
+%cy5C^xxX^cxxIA<j>^Sq;@5d((Pdym$xvqLgeNvaYy7rOn&7t*?J0)rre=N~EFJFYq9;~Ji%IInyT!
+YBH-s1oBc1}eqZe1zoT<O<BFprgQ;&|8eQw(x+RvZU5GHb!Qofm}Kx!|hseW^UTJoL46nG&4CuARB&0
+&Y182$S#hUBfmEhOc&bO1CV!V{}1dTxgak-o#549T?+Ho316^`@kkmG3_;pv@qEH*Qbh+)%9>99Ka+5
+w<`uV0z8Bl+%KU6^WGGQ@e;%jvhC!fAv*WKZ8r7l(qmC)5IT=Od^GOnmNVp6b{fPYPLjyi+I>Uvjm{#
+?X6&pG6iX+cTC8}*@&)=H@s`fKj&0g<`~yW2Mo>yhYI5!jo*T4CMjk|hCp_p_a+*g6NC{jqu!d6=UuN
+xueEE>;b4Le3+H7KGl(xX+gl`<I(X9_W)ekonH92x#5@3-E$c|OgSI=gCAR>-%D(QSNXDeqd&EIEe__
+76pqkDVeEhLJfkyf(#)Qz`2<ROG*f>#r=G<(^BZJl6$M^$AhtPef2AZBKucGbw6b!z@}o$=Y=v7t4C1
+_tzCO<wM?X)1z3-x^;9AB&k<s`-rd%<(z~B1K|Y?-$_;(7)dn;-5s0cg32?-&dww&(^v5OH=^1^%G}l
+dSl%D^K!xN8N>AEa;eo=`<Sm2=tjimB`!Xg3YquTeM40as2l<(MYdeBp|&E?Pz&HwY7%I$&Jm6`V6Es
++by4cu!rzO+<>B!4ZH~cLQ{$ME9k-?0ke=%jtp%`EdbxPk3|sbqOPoiiMUv{~jE=hEi@P-gheKa<(Ge
+IUfe_Y+7B81baD&XseCK_JqvcSK08^u4`$&2jPfUM4G+jBGAb0gxTYI$CMTKfp9-T>f=#Uh!6k8LAN+
+}}^yE+{IHcJ2xaVG*?+dcm%1kLq?u5!Cj&`9l(kxmS3PrV}Kr$@6AZly<z#7q8;gh<HUDAv1)F4JJWu
+1uYZJJY;ds6NGQ*(<nHsM7*R%5JkTvt50m?*Ma_@lb7q;ipI=*X9$*hPT6Rf>AmC$m9C;YV_c%X8dDu
+9y(eTBtI$~ag>buzybMRF4)(dekCpmQ>^OX9bSR4@tJ9`fTZQWk&fE~$fsQU?sKj4wx+T%4P6`~8JAj
+9bTqx?pb`)j&yumL33C}!`LpwZxqR(siX545Oy>dZP-KZw_%0nO7F9gD^;b5gfGbGQhnA@#GKbO;JvD
+h=2{W103mu_1`o?zD&$OmK`<gq_IS!O*Ub^@@?1Sx3h@~DUX8u$I@o0x9u-bz?rBh@zQl<^EE8K%8#z
+a_1PqT*>TXa~&8G3hRfJX!iZ`<W{PL0r{-wP?a_V~pxfcT<%R<IX1FO*FI%FlhK&c^oJulO?+V}wn}@
+?e{chNiZZQ2~enGmwQ5a5r+u&n@d(qflZc=g7e@CL+A~Mq@82vls5?Pw+{LE<#io5L<cLYt|}YT^Zyo
+F%TZe#7YN$@5uYw7i>uTzzW*YD_a$hw73{~+CF(^h!i~wL#ov0FW<y6`|c;tFG>tIYW-5b=dKtC>Fy`
+uaIDI(YBt#w?1SYmi+rIGFGo*~vNB;9Bl;^ne)00{v*)i#Ta14`dHVGDjs5Gz%i|YsV}bsiyW0@7p5v
+!?Q9@lqwVzvQ&+{li0eO!;+~F>bQM3Or^i-i>HplKm>#vgLs#yDT3MvTpXwldtrclDufAm>=RC~I(cE
+%Fl%E38Y#lbi#L6=5nEba*=Gr*$R^Ze-9@n4U>fB9<q?D?Cw6H8EV2TOF%q3AzWJV(wRvrw4SoL80_v
+W`n<tMtC{<6uKO1mz*XQeSw72Jxf#_=x^V!!phW6N=CS!!0Aev+5zAB*&)q9o?dtjZgu$#1iC*fsl0X
+2&6J%#^>x#=Q-Bu$vFW*n8Vz>r0WBjspz6hW9rg1?YT~)M+rxK&a7BXiP1ZKt4o(IRw_{0kk{yX)V&W
+U!FW7<1x4a3C}gFEwO2_n)>jt*XbC*$^VQnuyoOc|@Ogh}oT{c1kLe$G<%LLKaf&DLTYBC3yid_+v(Q
+aN_r_|*+nY<=eN-#i0U9bOI}Kv$$xb6uPRhU>2$KQezegn*8I-S(TozR4uxPYFiO5awqKG6XtS~E-Uu
+06Y(2sV*AL~J$sqb)UFaX2}BmT0yu*+rknUqq*oJq+n@f);iKbA-lqfHzELCP*_3P(YWXn`q?N&zYKK
+uS2-Rh$?#>{i$F*2l@k6v+^H+Q3oK{HBgCF!2mV;U&eg@}D=wb+#neS%#DX1L&z=6~4#<p!+jl?Oi?Y
+GM~bwZgzO)Q?<yM>8fu#ZA_vV{&Px7TWjS~vb;M9$6VWs3!7tTt<818d1EjQhK|N^68p&3o*Y|-_Kw<
+IrQqzk{K<Z~SpR*-IV3e05)S+#oT=Y^`G|!hEcbXoNwLJJFqMrR$<Z5knNk9y>?jttUM`PE?em)32h?
+0s&Ld-}P8J)=ZN2{per!9sudOY6j-H(++foyTki_!>4hrID2mW>4F<PZ+2_m!c*em-nPTknQP_2i{BS
+MndgyP&Z-??G<x2*pW>3#T*Cgoh@!Em@_G&b%4jR84P01*B07&Pe*^ztpbEp<9@kWzcjJwH;)Si`P)!
+D%rICIY6pa#iUAhNrc@?2Up$vF<2T--V$b4kk&b1LF|Yv21kDe`wcms?#1?&xFyV06K1&6}U_inezEt
+Ai#t5^IjX@$&O;#G7c&K){Bv}33W~}=-9}m{oFBf<F_RGS|NHJC{<k;W4eGc4h8zgbL9o;^A5gH^+Qf
+LpS4`?QnYq-x77<w-%1eXRSoogU6m^HXi+=$C$;tZgjdF>dlJ!qGOxMThEbJsgey%61aWm_-AUYi|EH
+?H%4#w=BG~;eA3r1ty8q>)FXCAXdOeJ#(^Plr1Sck$Dm7ya#yOCab~G%?bDgIF)8dgWuPE)*b|ryTH6
+bbCYqm80cC@TEc^KAFGO+b>MuF0L-ocsKTIEekhhym+))}Uk4k;8`fp$=*#+_Ni(WTFLts}eKMU{@1v
+~_4L^Bd~|%*tJLEUxnHQEbV_;itD?r)ha=FN>lvM($B?peCeY8i%CbzCSr6)<z)4v;rN1ZX1i%M8pb9
+LOrr$PyI7t^2O}VT+dK79WvM55dvJA5^`g6BINnNq&Un?QTQqe_`dGoKBz7~t3Qrs>ATV)<G==kQ;oP
+4S9Og@CdmlXU~$eIcDy4#>G8vHqM(sOEK034M|<Bkx>>5fMu&tuB~P}3aq~cZ4(N6R$5gT@%U=h!uLC
+ocfs&&;4uF$b9!Yd2o?k7|q3-DM*yM;>t<!7{Y&%Q{quNIiR**sl?DFHPMa0h-0qYi#2}ugG6(G-YK1
+9_`TH_g|Q%58s$n1ij`CY~^y0$g@Iv*R2<gHVoWfC@hI*kI2MntM9JKl_=DLQ-t{zSRxKx1o{_YO=H4
+bv9yGGFdfhFq*)>JGHHMVNJHsKhfBI0d5N<VVT#y8vlsqTrE0iNfbuo@~|_mF5({k;MfX+)4>!SxeLg
+AXha3rgQ8fO=3*YZQv9ybfN>PO?=MOxG3Nsp)fCE9+4!v9C2{NCR_kGwwP#%$p?9{qm(}hfUy9*#d^g
+{KT7j<!IQ^*jyJXT%Am6<X=BY<HD>Aen{{Myw8e|36V%t!k}c4S>!R8;%k6<2rA3T_ipcARYo+nKkP_
+YqBRoepl%*gh3!{Eli0(3aOQ=6`Onmnw^)8)!VcFvGr*Dd<ytupIVRz?gwOV7&WH?)8V+g-p0`h88$u
+%YPh}7X7m(SZ>NHpn{A_YKoU96YoZ5B~K1W&rbp;>1jpA+%je>z}j^U$K=y7TwUg_rpZ&wlc<q*|Vq*
+EM>q0?)A4Sz)=%PO(ZSCw;Q+xT{a>Q6qc!pf$-|2)!;a0gPKUy}R_%;ds~>vso^G1=@O=sa?Y}ZZ<)G
+&L(6qgT$Mlj1S=T3tNwz55WU;>nG29o7k`}u&~*BQv>_X-qmV^I?WuGv$f_73<zh@I7~!0oo_F03ex1
+y)sV*4g51-9GN!ES>|&K2!o=p)bs*wCtx7J43C!lJmv5f`EqVO#;UCZ$BY8>?C#Wi%-z<{R7h|JyZA3
+a=p`nN-3~OGtO`81Jm|E^;3fUP&@r}k<^ZE+!F%ogf?QvPG3NBlkCQpza;;F5O4nvPZ#BWGnysoRW4E
+;0D@|IAdFat#QM?C9Tm!UHGEt&jt%r<n?<amX`6oFAV!|0c$xF}7c{hr-119#<_keDMEDfvk#u8Nm^X
+k03!Hk9m1hsL;4LHq;_Cx_juN=CwMPHe#>t?@K5Rq8qjS|?aonu^UH^`dmxBY$9quf0AZ*28Cci{|%|
+vJJ394iP?Nqq5p8H>XRBt~7RlaRA0qY>f9v)P-!UhU9(W`_%c$ua4Uzd7CIllSm|-uO`C=Ce<kS95mA
+7>JIuBE|&q+yKXyY7n_xx(9R^?6BWi6Os`)J%X18LEWu6AmpDfzso-j(iwMHZZD=`ssx>CIK_h9EBjS
+xotK6rR#tHrK^4X8yAJgebO<Avc@b2dR=v@l`AK&|z!8qmQ4zM)S7f*f&8uM0|JsExT>ff-_uTTEt;P
+n1jA>jeO0(#qhLvPnxd{1Fb@fH>a5}dEo`$1mVZ}x&;<sTT>M6f0O>+$P9y?k?={3rhL{JR$~Umrhx^
+5%H5XJ%*vh)_rP3KqMyNc)mae|0X_e$;PZY4`;uM=Vfr$M-W?Jo!r96-A^~yQ1gCU2Kj<V=2JRzoJQ9
+iwc4y$VKtajTDUAN^%UO;<T|>P&O)W6hZW-V5ygXONaQ#d-a#!jHZOP56XZ`e}%d4X{xpf{~5HAI5c*
+hbnDr)b=MIML1AvjBa?~I&STOUxt}h@jyI5Vs2=Mf7Ou1>(6#M?;2FeVBqyIYr$ZRiaH8RaQ#Nd{o+@
+HpuhZSYVJlX>0S4;xdW>^#r1D5SvoMB`gMfI1334XMy{yJ63is|^-QaJ%3T*nu$)GlQjvK=S+4|DD%M
+@)-{T@bQ83h%+fqwB{9zl<lk@RXEx-fW^)v%#$&KC!ze?|?#!YVjZ;O$VKkeYE(4z@0!)C@>6c<0M)S
+QrL>UR_<7oWISkLNOKtl)|qs8yUqmQ|FPGI(ah+_o;(6+?eL5vr(8w0Sft>%PT`!_{f1`jr+-pD>O+6
+)xeb_<d1KxwS_8GU3l^)1Qa#vM_5)AA7NS1Ny1C?aA$TqHppzsIjeK)e6g9^YVQ+ukbN^8{`711!n)9
+s&W|R*#1l^wG#eXD-ut;;UEUo&S$TPV#A-CMDl9>mijZ(k{!E=EOYUNW`LVnztDEu|KN(4BAJg&JR`A
+I@2ekpOhZlnUUEYdc3VpjG&slqr_0E$Y0G^tHGEJDF`YK0v)Zvd+n*5Y=j20ClfxC3ZAI=g?o^iq2O#
+T9|(5CXBNmeP8jp!{56(`-WmQ;ptgZ>LZ?2?zLK)5NexZ}C!2y1=PlfZ*51Wq|HGF1!*8YnoCB{IVx`
+T`Oy7TK!Eu{c|D$(gHSouFXJ>!A+l&o&hnj>;VACVmZ=JpD3S<T>rRMo@%i3d1bd5QRp*-ssk+!DWlZ
+g!?h(H{gMRhL#Zqk7h7@*W4SbKP|JD-v4GCygQ1t<>UDE$-A2r_`9&dAw0lVcy>*j@i!4LJh`vmouv2
+Pol=W`85#y1|A`ir;G2<(N;LI6&RAjP4{U}`M6gK92pyDKcr$=8bBF3!HEXtIo4p5Y!Ln=YX@}ym_I<
+-2VV%%7T`1!r{f@IwPH2jcWKSQTx=-I);!FT2DU4(0L@iEuwO}uJ?0+^pB!W1bdB=A)<9?b`c)>CYIS
+B|h$EiCOI9QV0gqXs7^9WX>li)5WZzE;y9G{S^HVtLrD9U6=Nfcxmm}xXa8z!7{V-TT;etkIFSbZUqD
+{D&rs8k_B-vh#R;#8)D8l1_t!PL(uL;iiJl4}`GmR{o@!&4>FNljYwhSeY4RCLfA!^i33bw_{jwDC{5
+wYYai(VZoLynz#H^Y7#x))g4k%jliz4fto6>}yB<gtHvJM@Crp60k2RJ`7Ee;buh?Ek6s%y6ptBdofR
+zex0xf`fUfg^o}xp8R14nq@ve%7N)4Rk)`-k$G+f|>Lsbu-tIcb3;jRnGhf@&hKr9)3|8o77~HW=O>#
+kUwCymU-Qhpmpm83PR;ZO3*i{vXfq4~RpU4~3sHv<JR^MOTzK3`b(GGIx_AR6sTBDmxXaAaD1C<kpfj
+e)56_xl5iixJ1PZNbsHVbJ@=NxWKuIV!JGatd|B0H>6lY$sK$%#<wMTis4A}K8pCkaOPE&ibXxhOaJ9
+d=vYP>rR$$Q7{lR2J0VZ64nd|JxUTA(JR+AwCW7b{!nEv?uiZRG$MO0o~KzO-BU)jLr@ivWC(wnAlqH
+#04QB9FfMVoO2!Gk|j2E48oY`$RWIGsYb4G>iR2p2`%B6Pe`}Nx}%9Pv?rC}U?cg|ipCBaM?m9^<qs@
+#tNm1kF^2N(p>f#IuvF>Apch$CUP=kSq1X-z(eq$nB|On)PRVbCCokbT%4g(o=sQB9kC;Fj(KiOS#%5
+hy2}H%d+nxHU28w{Xw>j09p~}4&|5v~t)_sx5#mxf~31ye|)nC4wQtk+yr!AtV^K?*7W;cOYEa5paU;
+?oH$6k^s|COvj_`%jJ&C#pBPk(swzhAyqFU8c->BNS1p^8?8bp<(<^k|T-;YM)4kbVK{ITTrQ=w0tJu
+(<!N?Zk}VbYORy{|$6|Zoa4uw|@kUtcl4kf#1Mv3dJY$ui?zi5+Mxxhu=t-ytBc47;o;?!`pGY`H^~b
+!<oM(i3#?b1h_)F933&L_F`hze4^H7lBo4KK^UjWz2tWmfa?g(Z7lnlY2a-xyf9>h{6Vzfj81+2PIE=
+aPNNeA<<ysVNKn8G7-B?-j6z02EhAoBpR_Ingn9pXT|4H%frMRSh0A0}mIwL;fDAjIM0t6ymECE7+MP
+hma4tvQ#JpyP5||14FdU^&Yv4CA^uqk&zedDUIUleL4r)&AiS@I+dawEm74?-ky3Cr(`D)$s<tRc&V8
+9mzDv4OmS;XfU9Ph}>t9%=I8sDyvCLt{x#+n#R3mSM;+HlIfT6=ssGMT(_WxP+9&Qe4yLQfi0`84@AZ
+e{-VAmyJ1>8Kyn#itGG>m86jZBSqD7*zgqFDPN4m0UnAOudsSk?`rX6HEBq`YCz*2RUQ1E1~4B0`XX>
+Nz~~5r1`Na9qpJ>dF$#JU9kmYV$a@Q0)r`eO<RomFsfMO_OpL(c?wyJI#iWU%i2uJtpKw3-v;=q<%3O
+$HG$cKi`lN_R^sW>BpDTHo=!N=LN`2mp9+iPkddd5FcZURn1g22*EkGRuo=#*w`3Ze>Q75C4<9J~&#l
+?z?MHB#@c%n3l$TT`=o5SE8M#l*A~gnd1Q(;hARvK*0B56a&$g<M`jA}?n%wI>?XYHQjo8!&TVh(JqW
+3V;4Ovej(krKnIUgARh{NPVX9YiwyCyj0^_Rbgsb>pH{*;GvcH>M<lMy8nMU2B>f`9$}AEF<)1QwmAx
+6XESKKQ_fpz+7#19tauAO;~9eW=hNwg-K9(R<;25}pTr{RX>vCp=PvkD^vkeF%4pO!e=|0o%e&b#U7A
+DQzdv<^j2n_iiaGmCr%8`|PuK<-5{*dGELS@u1r6e^-8>L4NdSMp@h`5{JxPXb8d>+l4a{`;~~kl@v}
+?jpZz-@DM-DWyV%23@e^}h;7ElnFkS#bUI5mrLwrLiUqsuB6T&1;L(Ou)Ky6aE}zXo+d)|+=NpO__RC
+Yl^e#48os}&WR`R}kex7Wr4UqhT<I#<?bmZ_;LkWN{Ox%!9*L3*&{4y)i=K!a(z^k{-O>TN}%|Vw<j3
+N5nLx8r*7X@4I{~K@uQSY<QyhmC$i9dG=3<?g(FQ6g6gktp3id*Afl%SuRT1ZZI&@FxCL0sKwqI4`Mu
+OtA{7Zf)EtNGqfjUK0407U}b20vgfBtY`vUyUj(xy&glJS!IuU`ii8dO2(0h5~ACa=b_H4zK5lpO)JE
+bO+R9t-?L(gaxVHx$V9HnnJ4d9X=gTtoEF2)^J47lut>s;Ngh#NR2%^xBb?-1S~uzn8Qvu#5gCXaR&a
+0LAlI=%M?DHF*9FUjA3=AF^2Ioj<7b%)K~k|4uaP?Uf|RRzgYFGw@D!c;MTZAX5|~s(}Dq2Af*-**@Z
+e!tV-%8?}#w~sIMp^Nx2YBZ9?81<<<jZza@(+>O9QG2!Qym*n+vJ>LK3%(FU_d3Z@q@TNty-9~|+A!J
+d+9!(v6Atn_{y|D5#1JTwC-rYW}L%!*|*we95>T$AqcESQmz)+7FhG|D8Zp`sb<wE3?+C>@%myN{SQc
+-BFkFTGNv|D-=g_Oa4&>(5~ARQ#M;FO0;K;$7Hb2Zt9cB|7>DAJB!xs%xh*M#G_TMlsdM7|Hlgf9e)@
+CcFX|pY9vTx+GlcRdm<TpLTc3%w%fv#H+A#89c`t<xT6K+3$r2zScfIEYb#~uR>gKZcH`Rm0sxcL`%!
+l4k;S^9bgGQG4q4@W0V~qJF4pxEHl-Bj<}RYB|abWi9$d4|M)a2-<imXo$;-n>sj<-M4wwsiv%oVvzc
+ECbve&7Vjn-RtuHR^NB4@f7h$-s`8q7px0^5M)Klq6z+jTRx%8<k-?9gLZVT|-@ow8k=QmTCobw9Dsv
+BYLb6r)*<dq6w@#T!6bQ!96P;Y~u)z#)g@}!djYuJ!NjijgPG+?~;rEqF=6h*@n6~l>&Yaot3uk0~oY
+g^5_3yHP(d#=wvbMh;fax=-(ixg2A<GUourQ<1J2Awpm`)+YC)fH;0BvX8JE^g$4*2kvrDEBcuadm(e
+c?-*YI_${q9EBJ~z1|8?M#s0aG^2I_>6G@-1sS`?QRg-EM%Kgl8)I*TB=<1Uj;Zf8nRiyoV^ncSSm_l
+JN>zFhW0%OKUSe+iaUsweGY~~}SVhT28D_w_@|AI9?7ic_8N?(C>dG2@2@q&Kin0M7ds>-rATwO~cO2
+`&KngawH=J2pAG*oyLG*V;1-%U$Mnbgvi-a0DF7zj^K8qx4xYA{-OqKA6lp)mg#>N!}hnh>~)eBcxhu
+95~_|I~WBQ<X+eB%KATW=+T!@u_`ml(aHQ3wisciI|d)U7t3uIb&+dg0lC!hM&CV93V-ddqo@!=vM3B
++Y{NMSGZT4eCS*8(zbs&zrHjZhP>p>+NKOqHfekPpnPn{&Td$X!Cdo#usHcq4Rj><Vy~oP1oi>R$DeW
+*)Wr09-a=uwZ_HKQ9)6Q^4PainQN6Nf`9mD;90)RFR1bps_06%v8#)cV)NIVvt==-Pe_y{5isqPhYIK
+xHuv0krs4T!j?9;kDYUA?6YEWIH@M6~PZKzeUOOd8hrxMiM{pN|5EWR*@cYz23kq2LCw)fF&6F+yf3a
+lFF&E}zV+M&W$2dHc{k|CX_>(V&3pd{Ff#EFteYuzMr$3x|Jn3e5R_|QR8tgZm3|*g%7J2$9Z<fqvN_
+?5k*tSP{0K~VDCS&GL<S6?cCnF|=NyKO%3bimL2q&t9V|H}Zf6gLZ?5rrJfPN~}a7VlT%<RH!7oL0^$
+a8E;u99->#nrGYSSWdd(%{ZKFI5mOXY}a|2~;PdNbf>!6<Jh<oJN4wrIGGh?^)jCINFU{(ypH%h|#g4
+LSD3#UI&w|T%E5e)u#3ZaU(QJ23etq53gDvy)vk{Loy)CL;jEyD6x@*g<EX0Q`QR9f1j>Li~>Lhr68J
+;X4zq#V*Hsx9O29uFME_s+5<T5PiOZ4$3Th#*)2>k9c>ibCBmb-BeIInkaWjtr|vVF(}vAvIO5q%Z<A
+K6`gp?ry)+3WFYYJbKL6Vf$A`(#OL=eEa7t>|RuvhbmihZ+^yrJRoulK{ot!}~cX43@yDO`ov%}=+A0
+Ix_(-+ah_a%g$D=h`$&+~I1s1-y4Qh0zZH6)YrrZ8y^%IytiznOq|n@DY=GyriNDbr4X*$sm-Nsuy>@
+<no<098D~4!;|Y$_tnL1O31=w28Ppln5p5bV@_PjAKS+l9vmUU^$Jg4n`H<aY?FRNs<vMY%g?lEB^q}
+T^1Lp3t87iRii1Alp<>Wqu6)<1DCk_0o+T~HD?vra$%SQJ4?yox@%vG)@%*%EPVO+o8uK7g?(UOSzJ>
+O?KOF#@PjHEEaX6y46Dly!E?6}XYpFUrPru5`8!8zF0>O%<B2k|O6I8&dEyT}pV*vNdAV8T7{)y+gS@
+OVMK0%cM6-y>(Sp!%;o0TD(m!1$#{8Iaejt$-=UYbm5hd)gyT35u5e+iIJy5t1r->StAx7H<l}&hfYT
+mRj6t)_=NwcdiI+J(jvTxIQNsWvN=}-{~6$lD~#e?IQ@bUru_~QHHH*W-(P=vD_jcAzO5OLbN^y4r+>
+Kogyky;VX{z3?fX<re@$@=g#zBiGT5|FzUJ?4iN5Ri0!Wff=hsytu%k%#6-5)vbg7_I5f>b5C^MrE{>
+kAq#@yVC^jKKNZnLXY=hWK!{i!Re(q*<|OFklO4gYg50XS;J2Ajd7Ek+O)M0-W-c-&A&>}<B-l)u1=P
+Pc5{j5|L$ECwXT%N9hyDC#KyQEz;s~B<fv(-PpyGJUCI$(oJGDA#4XpS%;Df~k%M%Zeb!xC8gVEGIVQ
+1Z$9ptS<OX?^3|%hWz%&SC!IiNp%KW-uy{-Fz03Dc)nj|?K?cDCNSySehc}t==j38=W>{X4b2za`sg3
+Mn%x-q;&fJ7VPXspAwT2CoiMN9>YWT>+j2B2iSRf^e8Q@?vygIiie)Xcuj(Z#E1=pa`(Fi=NB&kYT&!
+fNO7FStZv+UF?jb5AX(5>iQzr&OhYQXx(|dO{i8dD&z84->kTUML(A6<o3NQa|0HhrjcBHO(eBl`$e&
+X}H)!@_CcoWJ&~BNx@^Xcz)h+oc`zJHAoJCeDy_=)9Blfq<2}n2}~_i^oChx?3qXF)Lq@gwAMV7t^25
+(zbJzrOLR&gexA<N0LUdOxVi7B@3eonOLuQ5wQ8il{p9V-XD<&8mFFZT{LOrsq1Pm(99eJM%c^`Z=YR
+JfJ^bQdzj&NbvFZ2d#CYpC<RM-bihwQwPeu9+w1|{8cD;?cP&J#grY+hHCrK}f<7e;2MIw2|DI1cOtm
+%kj%%T^oXB6Pdd|^XVtgPi&vY|)fj1rbWOE!Z5^{;NUe+DPm@pb$BjE<|@O#ic?A)CWVpz!VU$dbs65
+iMz-|C@64>MCzf7CEb!@Lx;AjnfzwR?OiRwfWvIE}oa?mDWLc%58yvhe#;BWv^VOW=_(wplq7}7jx1!
+!1<$993+(Wmc+1mvEHh43(U#<5?xJ*%dVCSFP@TXNU8KW99Lnm0HB_s{}`qNhYd?s8Rj!t&{?pb08zV
+UUWuv^v4&d4HAx<&j~=BD(?x#$@c!d39{(}VFi^yPtX@y$^*EIP6u-hUxi90jcjitLt7;`uMdjsQR5!
+3#KqyzZR(cP3zTOJx*=JXr<$?T8fK;#qDP_PeB;}F6Iz)i=`uQ#(D7s*b4ep+j-_1JpWWUlb^1Iw(@v
+gOPcZbogy6*g5z@3Vfz6%zc;od!rnwq;%>Pg~?{=!mkmtpj}4zd2>`0bNtPu@OZ(sTTOj{i@XYjSk*Z
+ZtW?bU>qbi}W645*nRM-i=SkgWkh${GpLWu?o(3<_|1xF;|;=clT5SJiLo`sg+d~(2j4%F2`lRM|6%{
+WyO+J&~-|4!3cl)8%?wZX7mOPhTpe_J&uC^Z9cnmPOCoE9<A|ks+gxP=Xs8Sh#AbJVboDUf1LLC^{K&
+sAWeO8a{5tAR-rTKe)8OUO49|8m6pT`M|Ft{U1OTdbpEVtqCS2T9>E<l8j2CCIl!YmB*ymSG~BPBo82
+CiIvz({CL404v+ja*7V%n=5n}78vP?2MrsAl}U&vpnalsvZ;QUI%L#EarBkVT*u&)yUa6^SnToFl>Vr
+uMV{i?3sZ>gl3FDM3+Vjg9zHkX6v%}O!wpjL(TlD=hEUNJ}09FUJ>d|R5BV=((bn*<nMdvxLCR+#_fg
+e~W_*?`V=k!r?>mpqx%jtLa~WcNC8`-s%klCvfs`f;!B4cB=;jPXmRl`98-7`>4udmkkwi!Ugs#Fl~&
+BwoYF*iwTb9T&^$40!TbIg5R&rYIM5-L#x>6K?p-WcGt&e-9St9xTlQ<y-YBspYk-o0!6Rs)Q(|4&=c
+G`Xjt7@s_8~Ml|ekdOnrWQnZwh2t2d<W@<YGDqB9>j~`O$L<Lsz$jjksQdLJze}idjeNKRDI)}alZ2j
+ZBhdJD!rd*S;;FQS>Va+4}jQ_B?g)&K%N2bCo8LcazcxTJ)L78LHp|Q)bLscNE^Js2wyq(mjCJDw0PD
+L1JrwnYefU6C!0&b(zYSC=DE&y{$3L0IiY$SIs4tlLjaHRUitlU#CAnv9{{UsmJ?l*&2=Y3sv`-)_bR
+$okcnFFt+m&uElZ<D7_zW+XX`{(Cxk{@3@d-?RoAC6zVJ${w|OZMlN&%Pqe?z%*bKhrlLJNkHAVElY!
+M3J$$uaRhON}FiL+@@Zp=-#X}wrQ9%rtA5^5!(KXouS(F73HcUdlS_ZMfNCbD@+i8e;PLu+EsExG1q{
+pTUMX?@PcI4#9CQOKhbT*!ALL*z*9^M5X*!SPhhdBmyxG-X#P966aSf)<hi8=5qxi4#Z2go(fi76Zfm
+S+uSl<RPI-|W1<5U*2FWdUq->C5-%Z(|kA<^W*=5t&6rTP@*%bJ5Q{%$|Q5A{t$M>J&qAU@iOE-r$gs
+`6-+5L@07bzW-4}wg0494@k#-IJ<3FaL|osZN)LdD}vwxvKFs_BWB8fW9-7z8dh1vL9IgWrH_J6F(%U
+1rz16iAzR>9ky{3QbDJnKx+wO<IZ0;^e0$99My(x+K|rzNv%YT+QcO98S&R%etybk%PhAv#lufyn9~t
+E^Uk_R*#1aii4Sgi==WgwxRR>tsKjVX>!-`22S}x9?@0O$y_HcEaI|bs%S`Iv{hYET^MSK<g8jQ4oGr
+O1e$;Q0+tFO!%lLmh>s*a2mZs95%N;K$!jwYuVye;B*OCU)tRn!&z_BF|D|@xdB)Bb<b_n7%~)+dGoM
+@cBN7SF5y4+Az#c%S7CCiT1)FA|IwO07C>n<o`W&8)jf6lfAFUt4_0D_CEI9Wcm6XlPllD~RPIY<nsk
+MX$B~f(wH|HdxTusoIkV79RcHgRo#gQW7TH(sFz?)TemBWi>ByT4SW?EgDgTy;@wndI}ddq0vz!^WQ-
+XCyl6mYF0c4Vewg;j`7KfQkb_IUc{$5*djzE-{k;<@;e8M5I3M|}lQ227th_=oG`66G;^Zc|ak&P;_8
+uuj{p1nPZd!6dLYw|{V|Ab4%oNS)l?bumr*btg0jx9ktA-+%dK#{nLzfgRJnMwBNc1MvQYftG4Z@Qr1
+<6E6Ga@z;Q~K=?=U@q{c|bepa-Kn$j2$H?Z-X3_>^07_&*!s!~8UhOg&;JKLzsviwb<jJWd62)cB8Km
+@PK$-}23z`F!U^zr%a<<IMD|u>iRttlFP+@&JdX<vT8BLH&VwPJDKjaV3@^fR27NL;GN6>iGloEbBq_
+o+1bU7VrChhf7;0Y9uN1s@lWl&KHGFzt*>dX4u_?!e~&Qvza!AY3)#x$~Zjs~Z(#5lyd@vx`{8x3cdn
+k7VwPE$8a?EmD^;lZQRXinJZ{4KsmogDgeD{B-3v>0%D(p~=I(zSIcq2|<LpTx9evrd5MBQ9Lnd?P(;
+AVhI>g{H@KL`4DD=oF-elF2Xr7Sl}N$5oxx1=edLLIOe#QBbW*5C8;fYC+NRh;uH0q1s!q@i3N!H8J<
+u2txMHO^fbXXCQUPx|E5)l=qW2NEYXOZh(aY4o>ouaIrWt>P>7WG4uolNfMY1_H9F3%O&=-h5i6q4MV
+6_F!g`1W?)V>S<0h^zxWlMF@P3pJ5T^E?I7oX*(`GaWj>Yy5I|e%C9sKXBdg9OQG!vGkUu1vg+iA!%2
+B=l|Mhh>Jq^P!^v<uS*kMJ2N{AcMB;dvYX%a{r5L&x6odRV;8*G0c+s{suZ0xqRX`3&{j^pP?io{iC!
+LO1&Tb?75g(e(F3@vG`pCnyzsnrYWa|FBOquDfzbrtAIitFk|83}1<X3f^OuI&Ef+v$$;yBJoCK64kn
+N4eH$8}23ep<GUahs-p?GmQq#cw8^6qxm?nS@N3Qy57$ntZ^t>vX9)=w%NH>lXF?wNnw;XPq?CjzkD0
+dw9NQjvNXtV+^axDJnU*q=s~l?w6Mmcry)2Nh{6g~%N?)`$mTu+2uYd2<8zv;r?lKVsX6_?KxI77Rnd
+7-G;_|v5hZgH6T8k5HYqd2OTcJbh(9SDzq81Xx<0H;UE^Gr$<bMld3gVJo_%L7lE3K0?c|)GkrCR@i1
+(w+nmXMu)sfSzAzV74ND+z&79%i81jd;fS*Px&k1<YuXt;=gtlg4ROqt+a*NIb65%4-MWzu0q?eZ1jQ
+Czp4S7Z$c70!s=`csU-1*h-9sw+Wf+Hm+N#Zd9)&ehtHZn4M+>QCA5N2JQz;&(L|o80);v^s2aPrIi*
+nfQMDnc4wS7n2mc;vdPM<)J~}s?f{~cPmXV$JnjVJ|ud}B>Js7%-E@NUKqIw6IasIL`amZ?7@9Bt)-0
+_K-*sOds9_cBJ=UH9JjLAcs<77{H|vF_xmTWPPn0ZmzB<*fxt-`vG5Yk6~>3c`D6ErA{T6B8d4Bp2f|
+Ucuob1~46__Zx+{UkI`TS;HO~2geC+YiS0QX;&Q$AtFJv&WP+TC~fwiEa;6<GGu2+BE2sO=-3}p<R(1
+Zr?BMMtkfYhg;7R0!)HBD7b=F5p;9aiJM`I@(&jJhq3e@Ch_xcn@29KNr4#`F1KDPUnR07vR_5)YJI`
+Hzwalk+l+t15+{*-WEwc#~+lvp-Nv0|XQR000O897^_9{;(4NTm}FDyG{TABme*aaA|NaUv_0~WN&gW
+aBN|8W^ZzBWNC79FJE72ZfSI1UoLQY?Ofe&+cpq?*Iz-nFA0_^UHeiPbpSU>*J52$q$#$cC{#wGZDNw
+BkyKIx{o{9(NQsn`+WA=gCBMi#9`BB)`|(8a?7?8*eU>z)k`jR?jH8H1!V{X(bc%46#Wci{vh=CQNJu
+9%L=ok}N1q5muVzwaVt9BsrE->E`XNgWvlvSdlPE5yab%=p8ViKe$jb$u65ktu2@}o|6a<r8=9~lpqD
+jWM1g@0HLcQ=jO=H4*6LV1xl=DnktH~FCe>@G2-<}@-{_ewXUdiF(jGF$B+NcvSYW(_GGh7iaK#ySx0
+!;{lMGP{}Vr4TH7LleC217kMaqSs;2tI|x49i(eFDtX4=@q>&2BzlQqR`O@?Y%faFZYKCJwX}A(*zGu
+%23FF5A9|17cYO=FNRkNT(`WZa9?p;u#i}gTL{W%=EKa=h;hFZ8j$ajq{=+el<#>FnV>)r8JOE2!2J)
+x7z?qtkDeYW!^oG$ZTLF0=Wa%#(FhH$Y5L;%V0g1lc9{9V9kJ`mtUq-V?#?+8c`UU9x)ep2!|0_oB{*
+c2o<DGS_Nk=>+`Oc)Jf+`_tk3FuEy_5C34aRUOt1C^;}0k2XYWpelkvrPuwNK|7-5MA3Rqo?=VxaZh7
+sm1Nn%aYmHp}M>HGJ<3uv{dAJ0$Uy!&ggUyo8BP5`i}W9Z_kf{C2bs6vu%2NM=YgnPDGjXnq;Dj--T`
+oL1+nsO_h<Fe^>O-A=AcxZ}b2wy1@ClK4PG^!N|u?e*6c{g0)+3}4=KLG@KGDOEY=OmT!9N|#XD}oHC
+H_kFG!4aqiy~g1`*O*5Fu$#bYLNC=iK1bKE8mpySO<cn<7la2YK$Paa!d_rVaRSSLkR1Ie912R*<-qj
+gT+SGGIDQzMe|du;y1zO@^on((NX{@Mmgx{(G8RKmA>u$eI%WUDD)i>{#j|I>9+cPTC4^F;G6MNdg%r
+yUEEXBCp$rg}U(|J&VUCk}-YSEA(=GJMjh2l1jrGaboJZgMhBV_PBd=^PC$Z#h$gJF0NHlq8u{_P$kX
+AXpkfvKpNYk7RX^s0)$aH8+NOt%u`6YfprV3N_kU>Jp_#DB5Nu&@cXQT*Y=bmcN*&6mLOzS%~($@pKq
+jdbJ`c`*pFOKxJ?$8by>1*BL%xC1ZN~V3^!Jo#Y03fX%lL@R=R6UCHsC-ORT5i83E~}9%N2ZuzNQmfi
+Uf@!!449QiM%A}lfztt^oiIa|PUy5xnY#wgjZ2wjpl)T-tTAY(%{4$~pE&!(d1rjqsnZ~I!_#LArX_f
+BI3p`XDa&BHuKG39E_mKU^nZqE<?~wtRF7K$JXM&kWA@Y@8R_dCvZn!{lRSG=?mQ}Wt4HM{qtXSSohy
+aJa<!=J_nQ4)b1^K7I9*3r-g~QAA<%|p%vQV2>{I2cQ{@Icz(SC&BO>qp_^QF@9AdICPe>|7fy!3cS}
+&^&<4-*EGpCqC8(W`i$aNYs94%ppX1uQ<mOk5%jE1UeW}zL1?|x?3+H5PXXhhgT8%nPGSx{@T^(VQY;
+Ue_~)BUtpdTix9PbE$IJ=Ja}iVfIP=|J7eWMP4@RrR7?YVO9qN|h1z*xba8RdKqm0(E^b`7k9fSy9>A
+sCii_A|LteuE*pJhj&$by^rr|WNu%{iv>>myuDADI|t5<OPKmpealj&1;CDqmp*OoATl?(=B1G~x2xQ
+x1=8YRZ>1Q0%-29YKsWV0(6*ngx1MTyVD`Y=gp<4ynCtaO`#@D_O-z=@?fph`=Rmn}8_lxhWxYW8K-D
+fyP^uI6K27c#A~!Bgs)CpG!sCO~x-`*P7oQZEYzJ*uxl5;CZdK{hHp7&jEMbNzcDcJ5wzAGbmxWeTr7
+m|h!co;x=CaTNUFdRG{g#?`k;_8mWtq!eb=OL|N?iKnu-nOD172>JB9|>o5H<n<nL&W#I0zt`zm#*b{
+<3Ot&?J@rM`h^tgbi(6{?SYq3;5iSoj<a0i1jZ3U9$PDgF~%KtsSZ^_jGmH^_Ptvt02<pv1=5aj=FTv
+Ay+kh4%MnBGIZyk0vuv{_U<n|+Wu3wvCDyNdbNA*aAAvV9wTmWVn>&qZoA#s>ao&Oha+2LJ968uY*9N
+L(Rj57<gea;P)h>@6aWAK2ml;P_EvFLqD!*@006`V001Na003}la4%nWWo~3|axZXfVRUA1a&2U3a&s
+?VUu|J&ZeL$6aCyyCO^e$w5WVYH4C-NRh{JA=0T-5*-nI?f9t%RX<&D7BsQSnfLjHS4a+W%)(nH&&^~
+t=aH+oMq66gF*Y6HpycL0mpgf-`!4Gt#|Vu&F+B?Rcnq6;96!61W1<Jr8%YP%MDWqNdLJIXMin|kg1l
+VW?u-VwH<ihJce$%SBSd;f9!30kNa(8r@!PV_QJL3+MgfE}7aKa{ZScB()<`76;8OMQ=BoG7^e3G--1
+lzquq-K7&LiM{R>mhcq4?h4dJ6ZCZ9((B~<S^5l?>1TM6zGjT|YJiDaS=G?Ife&cZW?s$teKeUWx}11
+vtuS&@)ChiexV82NEMwTAn~AqLS!oWOW!5?>Q4PFl;G*frMT1Y!G`t3Q1qQ##4SarmeX~?2G3^3bSUu
+{n1GH(h<Oo;iDpz$;Ar;7y_F}fGryQ$=^%b1!wESj$&Fd^C1vx+qbRc;I=W|-dIwt<Kf#ZXsX$r3D^Y
+kXPKK(M&7gMCd82);&{~-x+vzgz>@^Adpua{p()&H6K+=yA-zL%qau{2B%^kSwh=>=}-8VZrFu@HPNJ
+zsbB9Z*XH1QY-O00;maO7>RzD08oj1pojm8~^|#0001RX>c!Jc4cm4Z*nhiY+-a}Z*py9X>xNfVQyq{
+Z)s#MaCzle-*4MC5PsKRL8vb_=1EBh41<vdO&xa&(ELD?U>Mp$W+cjHBa<pgweiqDen*O;q$HMAJKan
+CV9Da$@w@vzQat;<f5Z~OX%hIp@1=q-Q52<xDg=olM3*@i3Sq{$!isVxJ<mSlvbqzbx|1tehDZw*E6y
+`nMaV=E#W-G&a$K!)%I4KzjHU9*fdJ>UdVG;#m2$B>ra~UQnRuQTXIM&P0T1qt562#Yk4{5h-|{Tu-y
+~8Cg60KHFpCMAnMoEz5OlCmDwpFh#5RAaaC}Sd;ss`N62yEN;_&7E@B6>KJe)-VI>om{qCyhHQytVyG
+Q)Y!@Difs7EA(QbP~Zmbb+-zoQ+D)uS7^FXb(?o={yOOnjLaSrIJ1TTlR;uz?I3|yv_yBiBK!^D<P@Q
+QA7z=ID(J^NwRc^emz7|iL%1heJlv5gpH9lMPN#Ra<M{+k_0Jk3a>+r5DDf1n$1FO80tsif&Qk+VR(>
+3(ea#^(u66^hzt*o^8Cz{YF3e{Kjm~t;|U_DCSi%bMA|h15+hruftJ$%(2h`Kxs6huB}5E{!x8e$B>r
+$+_L3^HL-ulk1>}FTGP%nUl3E^EqFJk~Ycp$EbutulmeP4QN_X$zmR_6b`siHy5Lad$<$|Ow{vO5hR7
+5r>-N0v`TCFcp&1qGn2fWr3bTeDqb#tq?%D!;5?PfxIFG3UVXD>oC$tKcvD8hzi=t6H`t1{~(3tk+mF
+HU3IN!Cx>FEakan+3T10M@#wh^7cm42Z*99>f4CCx~S5>YU9W<P63cqH5$OL|dyfH1QtIBFAchUOmcY
+WdbnGu*ErU0CN6Z2Kp}e%qbh_J5Vo7>JJfm0ZD$rV{~!#*Z%$=_vz8L-LF_47fZsF?E9vv>^nGdg_JN
+1MGMKY$aMX~z3{m5e{@N^Wm?0k7VL&BzOjtsq<<FHe(Nl(|E4S|SiQ2yX{?XDeUqrnx6I+fx_77GF!j
+pdD@_RRi@!A9mVwF1X*hw^CvbNH7E&+x%R<t)CwgPMCHPbA+YP&f(hIdHn4-%KoBzXo)w(_P-l~@Qlk
+Tl1-v7O~!lZroR`0cID+fz_C+WZB)&9`a>^wMhSYpt3bjBHRt)ipk215x;W4H)Igl#m@`6YrU+D~Uib
+;GI~VsxWD3YJurQDRl6`2xL#{!8hHn%Fr}W!7+Su^~7(!Ais^Uwvk@kj~XKspgSuzzfAq^XoYyI7upU
+r=W^%aNt+HtQlk~n3P6v(5ee4i%g9hwSWjVRsbO1>h1_S$H7qlx`0y@GtbK3M>mpZg(4S_$)F4h9W%)
+lnwpCyy5{c9yXoHEexo8#y%f_-qLea7pSeod!e^Y{>i-2yp`bU`B*;}MlBV_)0S&x@Ty&eBYjnad<vq
+~f-;KyWCcg~BK>%M>$LHz`Y?>)xsZ`<H`UIeMnqY}lyfES%wr%Qa0u&=-nP*fD{A#`rd!HUS+z5hi-B
+Z18+d*AG&5YMjd^ylh^AF$Pt!?S?GsRl%SL%L&{sawITNZ_v-!}?1Y>KzF0Dh*53HwR~XBzqAuCTLAY
+nz5=>(Es$gO>iMcbavaxpmN(DmXrQKb>5izyBvXKA&8lPS36`cV8AQL;%L`JiFO{ZLBI<zJ0}U|6tT1
+j_RoPY{bzx%kCnMzt7&CA00o5I2wr7i^Ce-7e~XlpEw>IIoE2#oq(T-G@1><_R6?8nOt4JpFV*wnt0a
+fqG~hRvS@ntQ^mb={8~-euHu;}qHef$*eRfu+Fc7ZlC?WT-LkdCP`mb%Lc2FwtAw&cdnQ6~t?TwWIK9
+3+nd~kEhh&`&O!wPXfb#(XL=n!iC<5;fC8d@!f8>4g{sT};0|XQR000O897^_9^%=0has~hZ+#3J@9{
+>OVaA|NaUv_0~WN&gWaBN|8W^ZzBWNC79FJW+LE^v9RSZ#0HHW2>qUqPf_?9Ek@b?8!~4VJX)TCC`TH
+A7Jpg-lCS%vK^bl8PgsKYn+7(M#+&itC_-Na^9-!@J`>Ob!kX&Z%bP?BZ>7aBwinlq^UbXO*cGi(|rz
+QYu5J5YkY?rO>01e<!s=(?t?sXXh`cFxN)W#1zadW$G{`HOrhY0`3B)?t`gIF0R7+%TE`7#4q3c@$#>
+?@BaixS^v#!MBv9`bq!SPJi~Ex&6EayF&CL6r!UC($&{Q-W`sN<rJ`2_oe?2PA^}InW&Pyj=ZRg8KO3
+mL<Ay1kTL{ZFdw`*mmr;DpL@HI}jK=K7FoE>+ZTq89l2fh8MNUm7Rq=`|4PhL^|B2f#q~*+qlq@h;ZU
+KNv=@*fdE0!3kIMX(bc45jgNF^8C#PJyE3;7?Azj*i0(X-<x4QI{rY}(9dSqfUfcEKb0PTotw$P4@EV
+Q2-(RXx=Au&2+jDFp1x+A^P^t)`Wv1q5tH7E<Q$)tZ{N<X@j(9vvM|-Sd}bSyAPNW05^{p@j5UPJY>?
+ss^lrT;lOyH(VS25SJ73_|)!r*4V;yh4D+ps9}T>!B*?Zt)o$coRw73qRrL^#>m{y=FtXNNLT>6`8u>
+ok_GzNI;_c)h56Y!tdkcDZ076GCKDFuXX~(Ap|{}PyUvnsXtBy8A0Wt87?DRaa=B#0PGpAfbDr2v7p<
+*zF>|Zkc%!SXJp*Gv6TcMxr9e{gMP;zrEM!{SlWdk;_nebU=o|^n^Lk3SA@CJV$(6umi7ZMgYU`z?`H
+E!};tNRGsRi;$R-~Xc^kC>3^SQ0k`5Zw&g)VXi_P4~$mjLYAk2XTj1SAlN(>&m8(}&*43MLG?14_^oa
+fDmJubv#gS{kyV4pl*iv(bRQUc*=W-qj6I^|p0;fGtYdAj9efgd4X6LsbdFMas}AFv#nOyv@*jI&}_K
+vdUB2_HCST?R@^cpkJjrjh;h6!*jl^oP60sX#8j+^y3nQ5VWG%8w+qGol-;F6HXv(AAz)7X{dlDg`G1
+hF!wOTIspqxBZ>wb^a`_*>KjlpRoN;LfP<S-$&BYr`+cJgV*Rdop5wN4EfSWZ*<4<6LB^V~#?l<fGxB
+_COgTF|G%Q(y$Ee_ml3Hdaf?_;m;&G)9LE#lu^<k3y_VnqmC(p(oKSakzlZfi_=5!uUwuG{23=qs_d~
+c=MmcT%CfI1}5pC6z9e+9oee8)v~Lsm<kEU_5ybTJ=JOa#;ggr4MZCb5!2GBnXkTO5lv3<|=l1WO}wU
+Zb?)QJY#L87zPkYFOb*%94SwHcRf_x9@YX>oCHObVjnAUg0J@XUw9nACH55q~x0B6)1k+WUm{7;of{B
+lfQjDfpy{(2)ET1<(R^;#eP$8t!+V31(DMeQk7VWNy4-}uh6Jc3Gs!?BC-BjYTcj-*}bq3Fy{T<id1`
+xajgR%F?O{W2*th?jP3n}{DfB{d$q6{3(r<!ZJA&wFwbKIem<UkX>V<KgY3vdyRcmxIR@h{ZqmaABSA
+oWAMY^av6Bu{djh16Y<v7Fxo~`szQ7ipg-PcsclqY{_@tlyST@;=T~y;HlVh|xxmD8EX(!g(*1K3cK@
+XwsUuQxX`a0bU2HyT1lc@Lxw#UAlUbxGbT@uT0b~<syeuoxTGG%HvyY(wZppK0##xsnJE!Xv0fV!Hwe
+b30P-fK8()Co;BB{<Bx<`}A-z3U}J0Xk0Ydi(>O+pQ;3Wc+HNdk5b0_J52)8-l=Lw=mFT$%b-3?7oBW
+1OE3=1={#CJHWlg?r;0nKU^UOdI#j5eWx<1@Vcpop22|MJCBvfB~6F(@c2FRfU7P3A!jI!0N*o<Yo0P
+Wl!F8BnL$x$o(v>lv3vFpzl#`N3_X<|{csL_5k!e?y`k!E5h8o@*yJXx@Rx;)U^MEf?M9vMtK!4yY-o
+mevgxVsoou=?Ih2o=sT~8<D&qDK{Q#*uWOI9{2Jq^L>0nw`&UOt|(9L@ywJW0sm(%@(I)XctkdxdUL)
+2*dc19?{L;0Wx@5sh0{dO*`BoA%?jVSNhl)ATo``87c9?mXE_0H@%cZ2Qh8u=bdt`YDZxpnUg+o^d?A
+4<%t`i`{P3&eI(PUeSlazei&rRGMloly|}p`3#B@5rii&zOw<2T)4`1QY-O00;maO7>PTWwO)m0ssJB
+4gdfl0001RX>c!Jc4cm4Z*nhiY+-a}Z*py9X>xNfZDC_?b1rasy;ogtn=ll8=T}^@J|t2H>TA?R>soc
+2)M$~~he^`}E?j~&V>8>N&C7oKY-7@;ADLOF<b`0)^*!hKUa;dhZb<RvI*H>rs-$Qj%c@Ry60;0w(+a
+79a4s~_RB#nVeoUyOCAyCKn1r-+Krb25m5|K^mFn!nc@#wjBTB)-rkOl?I-Nyeem1$i4o{(^5(_OPMF
+nO6bdBJ6f@o11E_?-Qqck=NTnfg-opP8}M@zyB1V<}BYg>j;ilS?f_Yz#5(^~6R&C;~QH8MM;QDC4+A
+)1uYTS??5C9<gL8q=Nd^pY}M5KdNT$I^3QvbDM+%sshwoR(6oBxxGM@}nVysnh=T;z88Yk)+lQo99{L
+2rkGEqr6iHqH@A=!;g~&;k5N08H<$lJ$Ynl;*s<G*iDtMQ7XecAkrhZk;s)T1iYt8tAO|&{5(&#YwP~
+JZ>4owZ`@spmDMM+l4z2dDJKe9HHEixP+In7;lpPVO+oS*Sm?GiHlQh%poR0tPIU~JtP;rcU+I-!Lt6
+l}a4QGbU26+8J@N*nM_zB95A|n%eKN3YlFUGnm-dp`kc^lcA2snUkl=l5hAn|fyf<?^odUc8E`E|3EN
+?!YoSeMmjG`J};f$(@G~V29oG)r?%t3sK_j|Cn7z)8Fx(XECgZCDMvMoat<U6JIqOKj(-nDrh(TDXJs
+H#7>?kxU`Tz63WO(jK*p;Rq)T#udG5Otuo>XVJ_q}Mp`*IxS1`r{{B_b#q7-=$D#4twx^aUdo_o5di<
+)!&s^9jf|lsu8u<+vB$nD)d!8;KN+F7~szeeqPQtCLSy0jx#~Za48-iD#gP`N%1iwrL?rLo7_+(13XN
+~(xXS{7(zzMSexCY2o=$T!z3)knvN3C2aKfObcz;%>>W0cyoHY8Zt)|j%Z_W>guZz_`ky|mH)s!5X5h
+0qS{(K}`zZIbuf8bD2xI27_zu4H8-91TiI1c2(Qi;o0|XQR000O897^_9Oci(cAqW5fX(9jsAOHXWaA
+|NaUv_0~WN&gWaBN|8W^ZzBWNC79FLiEdcrI{x&01}5<2Dlhu3tfD1FQ@<(&p|<kv5CVCfRO)CJth!J
+s=mzibdJHNTQCU;{<!{Z@(E*?^bMi&n?y;Vp*CQ&hv0)NRDFL_Fc+eT-&y-NbrRCeza6eL4BXFB;!Jn
+AWgXn6yvG1to$CA#g%-OMsdc|h|RM=NGb}|Gkxzy-!oEKpcXNEECg=gr)8eFLB`74aiAhDl5-~H>8CR
+oHo}42EWb}qPKdo?>EHimA6piIPe>y&r)tSUXFv`=5|*lC{Qy6SoD)!x3%-m)!qfPbJW{fh6n_xJZ<n
+$nV3LyCWvW<0FNEO20ri1p(O6PrQoGA#;j9_fvaDGgNU6;^EdT?fh$Q3p$PDWJ!qVl-kgO<)cpUQ;Q4
+6XCrvE(unS2VsK_<vJqcif;La9t1d!B?}EMhY=A#Nln4XJ!mJaf62dyhux5XBll4#6WTmAg<${Bi2LW
+U`<HACLftmU>+NOod<}OXmdi=uC0Js3a?<7KEnHOz<?JsUpvTV8LTdr7=Taf+T}q1Q=eCKu`pNQxYs=
+6poiv4q+Ug&Ls=Y(=<pZ;gKE|e|MRO2Z1V_0`nl3xa2B$f@_#PP_GyZvP_%&sfZB(ATg%g)?B!`<j3j
+IXo7hOT=vk+B}>f&;4zHo9=fG$sm(K%_8T{sEH!B=F+=GKlS=l`Z^(a~x@9oxi+^N-XH=-yGLe8=;fH
+|=d@$)q8b>;(q!Lw56|sz;V*x23(qn=;W#qgP#UR5J*Yk@uhlILwmrSRBcy7#RLF~x|M2mNjPl<PsGd
+!IVE=u#DZ~zJ6pPx=n{V$`di!Oyu$MoEsK(4xZc)5_Qj@>Y34?$&6sz9ZIa;G(20L(IHP=RjR)H3uX3
+(^qLId&74Js{*A82e9fOl~G$j*gD1BBS{t$gJxF7Mh0m<s&8^%=tMi2ZtEEHBFK!`u|T8(|HU2hUD>8
+Pm?4Lu<)(XO_;3sqABKa2x~|Pvsm(eetA1ZL0~}XX93X`47nICg31i)8%3cYmb@t;DXcS4&$P=ZJ{nh
+J)+M+YltJe$rSP_gT_O3VOeeSR2$t-k<N-D0ppJI@qgi$$;7biL$SQUL;b(wIdq*wW`^Kn^>^2Ku^FR
+i|ey?!b-JyyLfv-LHQKufB7?5kvQERBjKE|+I4^MpL$558QH{*O3Gv!o1twGd|l;o|0tXtF9_aBar9y
+$lS-=2RRS)L6BdVVw5V^roIw&i*S$^AEHCbPBXo9V5qu-R4Zn&3vOXC*emeT(qf==$^J&wDGwHFNtd#
+0J%0Q-k+1N&BwD6<1JTzN<P+)y#VdJ0otF+M0(BR>S=i*P6j^j77V^wtM}2EB}Mpg6<qysMI(6QMO0&
+|KS<ZPtU$w>@WLEYkN+91oao?{`Luab6#5MUS$XzfIO9CT@=@u?G3{&EY>+0AAR^?W9&&d_3s>eT4}d
+40BZDIe#Vp2$^PQ6vi7H(0ub1r9))_UV!mbhDdz_yH_nd4Lv$d?v>5`^f|C3!s*66hL||gTB(5SUVXA
+|74X<gePP2ZT8{J58xod)%f)Uqv{h`fkrh7{pNDKLFiTwuIle$vAUwEGv;+;wBLlFAfjf95G9O29se{
+^<tb#Xlz<3faCS+itsj)IV{(wGNfe?Yl>UqHF|u7G~K{$+G}UdNLg+JYxzGi*ing;R+4Lvxc$?*``P@
+@#T<dr_O5!p;^f&n%?8FA^i%567=sb~hBiUY=i!Y8Z@-EeMjOWV4<Cv}`~BuTXS1_pk28muHpt+QJs+
+g=y&Sx|-!`eUNw{>){>mz+oXdTn_rKX}5RRlgq0M1k|PCT9w9U*!+GLlztkYdm~sd@cWu7_=0_}A}ih
+C&gskd5&hg^QLSmC`-DTn0i#$kUE}q3BxmDrlO^1Luj86Fk0a(FuiRbN>zc(~7wpy>1P}^@lDHvv92>
+jnk1|A?5IkvqnNo#UgO;V5kCEM^_-pYB;&*#ZCHL^A-1obN=eDEkL)59SjnLZ3)pe_P72Os$I=t`ZWZ
+4PQId{|O+B8-p>`IzLV{>2Zk`W&7a=-K`4}zU0kb2KFMPjGbA-OuwLXu9W6S1TlHqF|YkH-8!YEOL@`
+K2-Kw%h2l_UZ)mg`BqlTA+*4@_hiWnj3u%LcNjeqtJId+vTaQ-rek@KCG6Cs^!_Fq1g1k(Zqa5E?W%@
+L^ae=Vc00{8*DUm8~W8!by8ig_f_vdJhVyDrKwZ_<d%lru?j<B_Mz};ghLVqar_v}o_xjP(1buoySLN
+^zbc#9$?_u(dZkrU)Uk_GY5>@4p4LiQ-B@d($gSw*p;!vq%S5T(q`qafeX{Goxqi5_YJ`^d)~Kw*exk
+1py2yWPU?G-ojj?K8_4{WubEx}(_@}5O5sRry#*~uceR2B*@rpe$Z_FdL!q*!w;ry_)<he!WR6f=U8j
+zwRM8Du3xUKf|fOy1iI%O9V*=eq0`OE)#;H2??1J0n@|L7Od-PUm3b_RHI1qx}9w3F&I3?WdTDCFJ@U
+!9W$4MKh3<&ELsP()?=UIC*CY!+DBI+LP|3j>5c##TCaBKsb=efU@U)eNj3;(}W98#sVj)}g0g8laJT
+8`SKFrk{D>;QU)PS~U3$wR^Dlkcans`+XJR@5mR3*BCpuu+?GD5D7dnl~%SBUK1xMz?@OXKFIqZojnc
+M1#Jv<<FV!YkR!g2FIP<X>VK{nS`XI$08mQ<1QY-O00;maO7>Q8eYI9`0001>0000Z0001RX>c!Jc4c
+m4Z*nhiY+-a}Z*py9X>xNfc4cyNX>V>WaCuFQK?=e!5JmSn#fL7U5DKN6ZhDp>reh7p8A(RL+gq?mm+
+!p~zr!^b#>&Dq8ZWqf(AZv2Q!R~JdbkdYiZ`TNl$FCyR%5y&3*KB?RzXs+s>KoQh6wY&&hTSD^@Bh3?
+WOQ>^)nlv#(*hcIJ+-UO9KQH00008031s8R>$El7NrRQ0A(cr03!eZ0B~t=FJE?LZe(wAFK}#ObY^dI
+ZDeV3b1!#kZe(wFb1rasy;^%y<3<wy-=AX6dnxRc5q_}=PT-C;CQxg@hhg`&FeMMt*w!Iyl$kN$Z1%f
+f&qK20rySV0D3GP@o__rLp&9b|{AVw4=`*+T`Fw7`=os1dU?L`r*f#RUA!P#LAfN&Zj|M!KGxr=Z4GE
+9F(fEo_xfU~+1dgE8=aCejO>74{Bch)JzZVRnhc{n3ExUQvYJNPw{4J*`EF5~#^Nx?jfU@z4$N2GwCa
+5t;^E7e@K8nwwzE2#bu7w|*NJJC+K7Q~?E|+tB%sDca7v^LawJ7Ni`L}=3J-I|QK+hw>2oe-=LE!?2A
+#$<6XyEza2ub?uNQkhpx5p=;T+teP4x^k7gyqojo=XOJ;tLD&@a13J@!Z45hhIprJK?|7D&^`y{oQ}N
+?VGb&<)B`vRw~t6rCL@O@Vk7}w=K2C1%4zPO*lbxfCM;G=?KaMcudf*p|QmUTcrQ2IpZutdDJh(oOmK
+elx5@9v@!P+VI2INf!9#RoQ&eJjQ?g%Lm6{Yz)iL_4Q0$p0xoe)UOX;%2L2TNQQwMjp)UR%G8z&lrs^
+9+S4M@|5)(FvEO6ovifH!;@WM2tlCYAW1|yJYK||vRcmTDOO_A`3D}e^#RWeJ6SVJpjL;d~_x82rt=l
+bgOyxsbt*E<fw6A;nswW)*sUhkiAr1Z6nc)yPdkjBWkvxq3mBJo<2ua+6fTWX;LIVjK}$~U{`CvE$<(
+>Xc5InE=<Ug@4FwutxuXhYP#Y97x>V^JX%BalS7C9kXi;v_E$Ln7>FFR%yHcL^(~6^k=%w2Sp>HmFSk
+*A6igydb%Yxj1;~hmyXe)@;c5mC%nRWZ+~!VShr@ZS*I)qyYi7<e$Z0gDgDe@c8aNz89HpTsR}1duX!
+K<48vB6oZG-wDMz!4(GYxC%MQ1pH|G$CKohQF}Io`DXciJamp`|!pbi=aJ3$WWYK{1GAT(5>nKU4j%<
+>Yq%E$((Eq3xC>TI^HG2`EccA|7xPdx1XO+s&F{=g;4P{$_Ml!V>MzA1uoV5l|bGVZ?SCtFyN&b!HVp
+WykBg~*qJWN%M;JQdaCN~?sUWd^k*rQW;dFCe5G-Ga=1Z`ejTwGno8M<w<t*D!jxC3vP(G{9_ZOP=aA
+7YOBsj8eZJE?ApYHh?`r|2wdk*YkQYYGx8bxl#NcdDGXw(UlWX^n4DVV3le0xo*?06qXb$p<Y#qeb2I
+0=PfJT=6X$S+A!Sf*U5k`~9W%YzOLe*U60Oxvp@SSGwg_LR}+hb5vFa<5gL|#C3mv8Q9ik3dmfTVw=H
+biuP}>4T{L8SqlSD{uLEvAC&DinSN?`>i64p$RYb6<vg(@s!J@1D5BoFv`eq<nR&Tles#-~pYPB%wGG
+snj7cDP*4`P>ud8b&mF8;FNyOS;29S)&(rI0HuP%?<GELUo^&I#VyV>nB^nb-J!}=P#POd&*wy%y)x|
+<9OJx6XTWVI_I-`=c_;e3r%7hgK(&70fn)<(0QJeSa{Mrq>hP5PwxUT4s!^OM%qCTqqM?l~EaQMB9Ja
+v|AXXUfHG_q@5u6gCNjH{N>oF>G)7GJZqG;i@5gtHC8zf-_AqP^0DQ;H#BIdgI8RlP*oKX3K3hn*>kL
+!5J?&+;e?fz067vr#%gZ{YFGI6RQ0=VDuObWKBgNz>}MDdjC-?#3#PoGniY`8`!gjZ0LcJ0*Uo?AAxp
+ege2ZY8}k-x5{)4vNy&hfzs|yv-nVF=d~{iwr<ogvBx$=Xk<m5KSY$~@3pmt`^a|fB@WV0_Q#ym8X(P
+vc2!;&ux4~lobsnh&k&e;VnY3?-EW{p+5ufBp)?$pZ0*EN4BLV<4u~SMVHCW>LRSI!{!!ihfVo8Y^RZ
+GQk8CJ94CWTwGsk0Qmlp&n(B@_iLpa&C;Gqq7Dhc+B6wJ^pw_-VE{I*j+n;wfPPt*P8!RvFBCclksy%
+HPWh5YI15Mzyut%zFFVs$<5EZPiIM<+s!)nisZLN4M0s)I~S??KROI@hvq`ZF<FQZ=}m4S<@aE8A3L|
+fWN6dsK4_)LU!9of~C#B89`BjAB+a@Ch>rsM<j?d3cTMZ@TMft1L49#=R0GSi*n~)dJOCchAD9>i{S>
+8l;H$390;OLR1}dznQZ)!!Tg!%HzbwxzOU2X{!t}9w^G{k5%K-V`YcUEj|f?sNRy7oG(amk7JG=CI#$
+!qN(?}sFfL!q7O4`ckMdt@Kh;lK)r0bGrCK}Pt?$3z-#w_jukY3ln)QR~eyjferw`v2g(MRe5H&?{sx
+2Wk$)xC18Z09+I9Eg(p&OdyVqm^&r<5yBA<xV?68Z<^DC9-03OYk3(ZHXgfDjiZN{OoRG@QzFP=MWtI
+FEpRm@}mox~~Wcc!#<~PNiIP0~E}$<(xW~RGg1PpU6s2T&0&*NgsZK7Jz@9NRMO+7VA6K6-;~|$+Td;
+o_%b6v75Ko*R9JNTULb<V)-r|h-b`5?;<+T>=`9`%?ad7AU^5sq+aVK^eH2(*OiV(r^@kA(DZB`&D14
+i&lLF2gs`c0=1T!oD=h{s)$1XJ3$dgX^XZd^ZGAw!&2Xx=F*RG<soz1_k;lGjl0-Xm*|B38qFac7d1%
+V$4l2~kMRfwAr)pJR%o%XB;!fNQcaRrwL9iQ1lt;<DvA5?F%!0X-WOZn~_pC#(rvSF6oVKSRtc827j<
+$9{bP%_uDplWaE=RTfjRmOs^SYX|$e*ebwSzUKp;BK{5-PQ|MXX-lP$`mb`ffEsJ${%BK$yXq*$$foo
+=kKbo(<q_u2QbnwPrHNkVxun2n&F|<}0bX0#A}H`a`*V0AF;+GxV~e;3w+2vT1@wA?2R%o`?qfLIFyw
+X(>e2s#f<5aztlx2j+&)1?iho(qSc}Z<R~ZIAi8JB*8so*wz0uF_L9Sz1r$JJV2g6BN&!P-f;8)*Uku
+DCaowQIG7eFa|=!p9ii&}zABiG+})H*G!lbJ`?^{#*JIDa<7#&Qn$?WS;DLZho5A9)R9G5(3F>|>0H>
+w)tCfw_5>hhKTctX(^6}dY)`>MYkIhCv%wsB}+<1Gm=XMKJ6^#BL=I##a;eAO~#rsC2Hw0!m+!i!mS$
+Y*A%v&>#R4<xYaau1|^lSKwLqdVh6`4w#O{=9gBD9RuIr$o{XdDDTr5{5G<9}5ujPVQi{ve0ye7~^Vn
+E-g(24~u`tKI3wV)`S@C-=Gk15ir?1QY-O00;maO7>QU#8p4@1ONc13jhEh0001RX>c!Jc4cm4Z*nhi
+d1q~9Zgg`mUtei%X>?y-E^v9hR!wi)Mi9O0S4^FQq=Kds7wtiS4~gs42HYfw)uKRAh%0g=ZAC7b{jkg
+)`rG?<m!v-8q?e)s1W?-DH*aR%yye;1*@*D@(5@?1)`TB_cc0PG5=ldXOslMTqK#Z{N_?$UYidNk6>F
+xQme#T&sc^_{YL!NWI~&igS+SP+XBez$RqMDcN^*uhgeXheN>v!DS7hpy-3iSB&$xU;!uUh30-CX0nS
+^$7i!cDH?FNvdX-b(3D{E!QZiFSpT#&7)(QK_;wGpg#I%mr3f>XNfDS@u$S)~6hsPAOKq=iD3V3XHXR
+Vym-+aYmmRs~f;Z(ZX_RU%f)xTdMK<)VWz4d)UG3STA9%WrCg45SLSLY7EFs$8=$zObL1D5Y&_*@D7K
+NF-I&PT3wW;)miX-ktF2i69XYMS;{kYS|7sDOW8~C*)H*+c?{wNPK||7?v&F&VRm7=w8hEw}d{<-zN0
+%>rYAOjjRwVfYA^ul=;KmeNPQop33WY4|invlVg>$=?KW63TMQ!WZz8@%8KphrBsZP)MYpvmP)zQLig
+O$G!09D*z7yTkI>#5Eu>nxeEUso-h9K94HB+|@oEE>$~W1<6OhVSq!U=|q}@=Kp-%0h`+t!C)m6cdS=
+LD!1QySu&bpG&#@fcrE-uypb;}gVT{PW^{e#f?Mn3XIgh>CA%?n<yuX^Zn#Eb!FdEK<yCpx3+{*f+Uz
+Wm|*^5x}sULsKaepoGwDnZSeUjH(`egE+xjW8GqR)%Nv=HbV<et&m;^X}m$sHhWRIy!?dtaM$GtkLM8
+vInc7$-DOny=g6*yZ58fV)4k@K*);)UD5b5ef53%YK*^&I**cw3y_o5F1Jo|Vfo39{ZSM*to}YO`DvW
+cIG*rNLsQ3pj7Fn^SA;DSKcb0$Vm*yjKI`1;o}Vc5%UNupuS6C$W;Cgsv9yH5D7%k;h1Noe({R`e35M
+V_EC&;bHUuqTENs0+tx~#nT8D8+fb1<sVKQ>?k5Z12(ly&fJTaMO=@CDx+d&q6tj`X4{*e(s<=j}Bw+
+-KDUF-eX7j(-`OJm`p@C>+{cf#I}DlCXCr^EKp!A3SI`lO0lr@ijd5WVm0M_%(&sLgOvt}q*YohD&7k
+_Vw_96V#(GB1TO{n{R5x~Ch`6%u|v<TCNyo&ZI!ou@+k_H>-Oppd~4&go~YYU@+?B*xRxQMgVtQBadu
+-=zC#JzE&wN|t=}u2wvq`MNeOTnDpN$Y4lUP%5wBL&f>h$r9JxQA6JbC|E_r&LFdAwKLu8afpsn!*iA
+exCylRcKC0v&;I^g;Y>#vp`gIE^j;U-ksfhJ!0n}vyZn=L8@P0jA-sq(&HVlB0V>AjTuhU|3$y7;zY$
+)y+~46)m$XT|N_W14GTu4}9tF&uGn-%wU(q|H<XhG8KM@CuvRi-?U>HyVJvnI97&k^;AOLJ3G%F<C84
+zRy&+2_?GChJGK++Q#9K@WSkO_l%u<pkb<#l|3&80a>;){`vqWlj-y_Z-w*n_6NFxLl#es;DG)(5D68
+}F_L&rbLO!T)Z`hs)ydg80g`A1QV2{al(b2~}<4`^0&PSBdiY9e3qa?qAtb|2B)(Ea43%SbyfL7AGvm
+^aG4Lg7;^RLUuCi>U4UsJx6>x`Ug-;0|XQR000O897^_9d0@(k>Hq)$VF3UDAOHXWaA|NaUv_0~WN&g
+WaCv8KWo~qHFJE76VQFq(UoLQYT~E7i!!Qio^%aDt7-$5?1v+?Z(f|$87wUGF9h<QQSPw{S5H0=o%66
+I|oXF$dk(VS1gIG3n3N?8ygsP<$VnTm!i%sxrWI$xQ0M<xNa5N68$_DC<hNZf?RTZBVMPqDmvg@gU&3
+_AdmOU)<EWd|C0O}DwE;=Br)g5?5c>Ml)e*Y}_Y%|CPwZ{V1<<q=>*=@FO<#u|ZMXKfCIZI+HCY3dgz
+z5Hc&cvsr<>G|8HI857HmV(@M!1m2?2N@=#dI%fIi4jgMtm_&wd+o4%JAHvCD>y)nA){FP3YW@r5o8Q
+Wq(jh0|XQR000O897^_9%;Fi!$rk_sg<Jpt9{>OVaA|NaUv_0~WN&gWaCv8KWo~qHFJo<FY-w&~E^v9
+(Jll5L#&+-eiV3~404gA2D~%u2Fj<Zw$3B%M)smB(rD#zgFeG7t0D}P}@tn3_(?98tb?-eF3~nT4E2p
+P?kVwpJ-!C(JFc=K>7<^Xi`I4uF@WW-4#3`qT|JC^H(bJ=BxeU^XVK)}11<z+e$bH#(7-p+=9?uuWA#
+_w<*}?PYFGmN@558g3H7gdJovY<o!Gop81n2D4hs!r-?=O5gO%jJZ75tF>c=3~LKY4p}e0p)rW?9Z6U
+IcL>{JjByzZWl8SzfSA=x<_OeO;7AoakRcK3@g7;Cr(?Tf*88#eE*Em}-r91TgK%##OxXCwDxJvfS6i
+(H$qykc&7=Clik?0K){a>>uYN40`ZU5(sgc6|b{0jXZX?Dqy1HJkN5EMOi3{JWl761rLZ19{ZgLGB3F
+hlZb~|1kdbW6I^xzTv*0wka$dgoA4BxVJ<zzhcrww0S_(#@3&{a0_H28Z-6@C4}hkId(MkVkR%iN)T7
+_@eKK87(qL)8qKA6XBnu+djo_Tc3Ae`rH|d$2U>2vkcZg)FHE)H~7b_mdfuS_wd4eq)M#2KipeS&35`
+aMHu_yTBcsb<}NX3c7h@QRH19qCUNxZ5>62bhgh-lHRYHiTYYG~81Y9t!&hP;-Vigxn%<IpwJ9DMt-I
+TJiGlX>RpWnS{5EXnen7K)QjqRPh_efqT(cTubp-kM52l|-iRnlF2Mdl8?p37L;cMoKH(3_9gvct|XR
+hk}jS-~W?-#WR*>V3eqb?0}z~7iFGOUwVetjQW5jZFRQi@X;`=++o#<pD;^{I4!w(m`%XOAsA}VDv1l
+%@tmRQAy<T6az*T3pHnuD<$t|wtw)is>qF$QTfX+--yKMi87<czJ05#6>>fgW;eY2!vX`C_{&)7`4<T
+O_?3W-ZIa$&U=z!o?1k*K4g;H0aApu|0Hwb{c*6ULrn~62KP?G4*Y`M@<J7!ncwrI?{MMHHr(lOK0(d
+-Y?IERjDse?aL20;ns%$A13HaFCwKDvZ7a$PmNA?{Z+-Su!-4Q>;zH5D%Hfm*0h4Ky|V!0Q#@^^%o)z
+X%GCApnYiHE{#1u>%{AnL}pZX=p@(__myrOY_xw(vt4r4Xnwsl){oP1*1`i1NJ4(<oAt|p@NHDCKK@5
+lSz#xHju_Tb^_XEv3G{mjC)dei7^|1we0KekkTLm^OHbSLi3y+D0O#V6<`adWx-YSRO!EEB^5jX1L+(
+FU0)y=Qp(VEjv-tGvl8(<Z!P$uE}uy(3X)H?z$Rgo3lE!sP%I%12dxGbV?#qF>**}3%m#kQAe2cW)f4
+}Mvw|=O{!Y*m)PuC9w<yXLOb70OIsV5iPKkYD_!U_MGi}QZ63M}gV9@WlI@%D-VPCOoF6=VICqst;l#
+WwpGUB3b0>Ck>A?XWn!fxG1#fT3!9(D+e>+FMA{hs0zVC|Q}83IpZMZ4_^*uxwXglu5YZcIXjvG`GiN
+KKxAq{HZT;E#$h+{`^xl^}@&!6o65i!hN#mY`x2u&s-w{hX`~|L0_B(?<32Q#zRq%(OX)AR^8+#wm~9
+jJqCd5BJ#s2uZUOr#d@H)X_Ti$U`SFC{Eo@iwg>EcQZU)l#rouHz8W#@;`tOO}jh^#N?yMQa9&+KptA
+~Xc8BEsiQCz=wlBRhKMpLYVo=<;fQo&j>D$5t3jGpEt722$79QQ$&2-hi|zIqC%@8jVaWOSmf|`};hj
+UZRJ(^+8~RjmwEG#rpr83(>sBEtsdXhOBpiedf!#BttBmX?knc}0mPAS&5p5-<Wl6UXv}PMS`T}gw3;
+u2)WQAiFF{OF?1WG=+`64=QprOHcD@QtLAc5;3fHY}OfdA(jtv?fe30nhuv`>CiE?2JX<}nqWW@RyyH
+g6fk=_F25p1YKuLF5Z*Z7Qmmlz#e{Oj%xmy82e0)e&9SC-|l5QyjBxtM)&^NPEl;hxHBKpLv$g*^fB{
+9*M`^ftWA;=f6vcG8*)AjuyekD3F0A?qpCjpF!^EfaSL~S^FSGYQ$oarO8_5s4o1on60{F<R7GK_l{)
+5z4h4L5T)b}XyQuR`6OQM5V5~yUyL!iR}S$RTOcN!-Q1|%qxf%}jZSWE>f|~BSZJx!EVXiCXq*U+o(B
+Fl0wRQ@2atwmn6bO|{)C#^52DDuwcNLU9>pRI^2l{gEH~R~M3HmsfOe+)G{Ur&1a&1&7TFJ~IiE=h(s
+E<3Ma&@rA|Ul8QPkZl2Sd}*FV3}vM3Q9pU=*Zd1=Uo(+p|59XDq3wO-iMOiP|T-!fmQt?kYJLb0S~V?
+wI21b&WJ2N7#&DW0x8r)>xW<_?Z-Z-Xv7g-mcS#)F9cFz)gVLGG=GK&|}liPggJ|$<U*}J(~5VsabDY
+TcQoEciuRkOX>sju-bn@s!9Ot^(pXH>~}ZI-O~Z39`x*!X>!s6Y;?xdj@_PFHJYfMz{ZxI#P1B#yQ}N
+wJm<A}P*zqruu_e4Ij+L8wKFWE;yc`#fyHTf&!+H}O<W6$E1IUYkJ}bVdyIDC1d7H}ACXA}!EdYI2x>
+Lfhe*M7s#buz)oR+*rWLsBO_N#8+h*IODW^?MIjsmlf~ljtzB4t&|I?u@;Bq85v$`X*C#{aw8X*F8(6
+RK@^Xo^d{!tU5BRk^5{ST!vaq3UY*$mdoA>^{$YD)q&$kySc3sZR(yT{enmOR#uYyYvtxKPBnAf?l`=
+z^XFwP%4Qn(W#chs<gtW=)Gq%}-{o4F3`)Jq&z(dwTxi^7Y%3<EINNTFkaJUb%c!dLm2R@huA}6<vq0
+E)m0H`}@{>n<axm7z+S*ZEV5g4I9lCVlSHVLqPgfo&xbMSZv~>+>YxPDB>!J5X!<lzT>IKMu8R#6)My
+<E$9}T-PluSjd38aYYyaf!w2c)RIdNJ;e$pGhZ0a0mZHd(%;mp9_cTa`OjRae-cTjdQZI1CM2@IR3}g
+>jd75R3TJOQEBzVHZLQYDLv|=MAbSEMrW;ZAxKUCdnaYCX=YMLrSKGS%p`iLY81ITNEbV*Ra<gCb838
+Z!e3-6<vCT+rrHs$@*nzH4NWjob`G(fokjc2ocQ(JZP*t24D5fe|D{t$E5P9r;q<2o9*{zW8pFBc%cV
+UU6?#Vu((eEJn!Uv@7J+1nW%L{$un#fF)V4u6-Hd$nexk(O;>Pl{Aes5S#6yjUPu1xAA*82H`^Z9;ZY
+(l7#9*^i|b%C3qUw@&BIBb?2j9#f}3-RI+5!7>EzwWT!quJ#l^Y9~TQh#)%Ktt)<vh3!YEQ%Owl&^k|
+k6l!j*%BzOx@Xx|j*)0r@Fmx(GO0!5xDSoL*q;UcrKH9X2F6XAeV<VwVJ-Lul1XBoS?iV~&Ya`r@>a%
+7skDM+E-Ni*(zCTW9sWH3;?*7o=J_d!&z%sZv5^}VB>Jaha=c-M8MI&r%hM0<}$Mg?T?)UwgJYbiQE{
+Yk5>24ft$*s<RO~Bf$2g35eS|VfD3cC1bXm86z8N26TGNu2azLlx`p|$-$#Sx#PHnpTfGC;!mRCd9L>
+Ac%cb;8+#*UAyLg0~6G?Ms=Y!Tn^@`)LLOKP|Dc@UTqPpK6-u5VP8w0xu2XSb&BUjPg5N9M8g}>2Sfo
+h;l_|c;M%;R?}KRnK{x~Robh|VT0s8Skv*+6dvSjw!}^%PD758e;=d;NWQHRq$!ZV15c7Wd4A5Os2&N
+=u{Rl#xJoCKrRYgaaY_j5n0iWD#sO&!jzE-`Po&@VT3{u@2CzCuo{?l#$_{t|vB4hT6Pga@|7-*B7=_
+wRk+v$3k}fPB$26jHOq@r+O@l3Pag^+UVBM0FPb;yE8mHE?EkIa-vmhoinSi)nE%3Rn4tLJ85Y2L{Fw
+idX1NoNe)rP$|wH*=ZLqA>Rx4%F8tOWNlcAy!asNBosGxRts3(L1l<<tqgy?uefGd}J}vSwAO@t=`sH
+J0rpw`TO`Cs`e<RR~|;6iGIZLu64f%>Y9>RJXFt-EuRz-SD(|*%Ku{n)`ia@t>an;pdY*@pkZ*B#Qq(
+lb|hoWxJyGf0hJ+n2|+kog(e5#hnDGg|xK5KPwe_kwd64x*E&GNFm|ePo1a8b~4(AkxP6+x>J|VewHD
+7h0oKwIL}gfesXkna`yi6`29P_bDW_(s4Makf|?|w^SOh6nZ`x)c+O^Z|NWFr@jAt{&cU}Y$uc&fk^t
+ep?e=x;+cKM1?6OJC*|ttq2|`tFq9Ru9sUt4qN(_w)OzBMws#wDxz;T3ek*rM+q}7k4p*r%aakZhEax
+t|8!t?`$&oaz1OH!>*cF$bg@Dl|_t`K{nmucK<AeUxE%T?&S!3wI-7}quTqFTc`r*B=pb8F>0a&idh?
+qbLpNE&e*=sqB)b}Kz3$|@5go+i9OK!}RaPvV>_2xib0N#VYa({Bz?w!-xszT?IQ^!t6U2B$8L0!dV0
+;s{IPKrkhI!F(AU;sHVk(L@zJKqiyInnjsHKm}|j1cGG%SpyfTQ<w~`mfHy2ialR{(;;l#R}x*-!81f
+3*9mPE(KH!Qi=<liP8EUL7s50Sew@Zd93(L?9W0!FJgFWxE#h06tn;W^hz-(Jq2IBHj~7xWl5lQIuMJ
+_sECt3CV?@_uRK23U2UtPH1uw?016bN)IN=!0n32C<s}u%vy_4XQ|HkTpE<RUj(+wA4u;OtlKxS|B&i
+S)yGta|38j~x?hV%_gm18a9aDiB&H2|+c6Ge3IR!uVHur6nLnWh??aFGd)<tXXA4CYGn<*i^FlCD#Ay
+ImSutv}$UUAuLNmD2}=Y7B%BMUaLjl&RnIw2XDaXLy2YPjvOXst%HOog3{huC3uRb8X)(b#Z1-PT<LY
+hFiYx6P%El$Hf=6L1=BuR=MK+B1^d1dIf0)rBa6%Fk8QRn5)bxS63%hiY!X_EagM9ku+7T)1q6#>!Zr
+^uIj_Kx;&GY%%^MlUtx!mlFigEk;~_Y<PIFX63#|5XSfkZkV&A-i;jH-T%l(hhe|rz0hZn~h?`{+`ZI
+;Ww|&F<_IMfqZP?$D7sRXm9a|Xnr{byXy@jV1jEg{k0$A4AnI)xIbVV=t(d?y8Zf9Iqm9r@m`fq$a&4
+N67i*FIg%T=-2|8!3EnNqm7M^!NlFRWEzl73NuUwf=Dr;7(<vnLZ5LY<k1k~znHIlRIKEn&{Fier4>v
+1RZ;$L14o=`kAA@r##WG2^IMki{O>f+2d|U3$}*naKWQ^_l}J6)+))i2nu%qJt}!sbC|kJi}sviR(ME
+4%?4)Q^eni4!fu0Eov!J>H8j35Q-&*ltRFlJ4L^NdXL3B=m1h<y`ciuhfrjdL4xAfx<+89fpmj6T0_9
+h+NV`G!+jnXa*tHq7b!CAWre4{dVdC$Nyz;vNvBu&yhP;Bsl~<Bz)O<^;CJxUQAD^ZN4*=38dpWfb@`
+M&1M;psAm2UK<r}zGpa7c8^Q>IC4w1_ARlZVIR`5iogtCc7FUz7tJ)3~sfQH9+T+LG-S6itHU>w{CWl
+LTJcR@aOPL6*&esArJ5*eHeiYV6BmbBcd^BHshz2v#9y%1_=^~4`CJlIE5T2+=ivQ7heH=65;mK6p>A
+coe=SQdkZ6~YmDU;r&TnfIL?al+cYAS9ML0>iEeCYdd~ey*RY)fc3~cdV)Ru>J*A4w`_l^M#ES`tSt#
+g|U-zAPe+^nEycLqj1rX*ICyE`fHmVuiu_PZhCd7igm6nwB+@^7D}%ojP~R<GI9yADY9Fhs+hl@WfoH
+McAhQ~0?py7$|jgm97^$VO4xGr`;b!Xj^M0@;Mx0kuP!gQ$XpcyZ<9L<2_=E5#;QI|mylVeL+)4FT*f
+eu&jK(s!cbKwpw_fAd#2cQwPrG-@DLAz{qz>H<x~nBNDxo43V(NEp4r4aJHLE;b~>g)+AGig<w4}NgY
+f)}oA8?J3U;X(wSq3%&X%@(Bsdr{+Qqk!#6oin1aJ9zBrA+pL7WTU?sNPQELRCXWH+NTHl2^j(0i+Ou
+>b(WEK6>7r^0z36?Q~9z+=aGVlt}@sE?$u6<E_`VYALk(s(ixnu7P3FsTx2G$vpsge03hyX1d>;fAF#
+S?D3nIUC^3CCs$-6(3K%rwIvF1(7@-Jc3|ZjbI-xRgFfAI*^d&bSzW3TPfV2fj?RLfN5F;;i7JJnhvi
+I5>p=H;Q0WC56%z$P|#U20ztt*9}KclgD^`1x`na9-<}z_Oq~@K>3c5)?{@Pr=XALyQ18XU6gv+>J`K
+WK+<PfgSza8em=C4KQ^~m{4<Kq_^k!wEUa>VT=W}#1bpBn=fh@S+A^e>H7rO#3^Hq%0aGwa21o0^1B?
+qwaty#xsuOTrGfE_v3+NJD1fWQ#<3Njmbo%kZ#uzot1-W8Zfb%A(UgxzQPt-PZ{>5?a(;%`+?YRyOL2
+MGuQHWI5q?oWVvfqyGQR1dj#KrcXpa5qx(qVvO^HeD&C6eUm_G!j)93joL=+^C%Orb{ugifWGPsX8(7
+N8%^hoc#y0tHdF)Pq67`H^w~d#+X-j<!xuVtvc_<BQNdW0){1%<YX*#>~mMz;3@N*V;u#s14$JDvqFG
+m?K6mEK}HGtnq#~H6#cIyG*xNl1CZ^<wf2~vw3f=Y@`n}eIR!0nh_m2VDC<KP9I+#sn08{&ValH-s{U
+7|%`U|0HK7wKcz|{o2>!L2l<8$CgmEPT8uY_=Yg+7PSmXN#fn*hntW2ol<PJlR5W*tVNenV%SW?52mH
+|!4OVRL-h&PDol!pNhiVIobq2GiDyv$2_Kg)81;5efZT@Un>Se(h21LXKG7iXt_Rdj1D43Lvzl^FL>H
+kN)Y)35>;LMTh#6#JT4P=|~vQ>*qECs@cMq;cJ7cq_;*)b1pW1Ron^MAis%x^?B`=;BR#DNM85OYf2#
+)rR$I=7sGoFE0Oja*RrET`TJ}`gAh@iAa0M7!RN!lEdkCpA}WK(j>`_8S;@c4O3O>E^iEUj*mFTIndk
+hB2_PrCzS)<x6%Fe&8y26f+rZ?>DLX~Z_ZQiZo?WF^=_@vsEHh=*F+HDw}wR0hN9{Poy`nMwN(umqj=
+Jq#^wIpX9Ky~U`PpCwgg2&r7;6IswvI)I8vN8GO***SMS=Pk<1-YTjd4X47E>%jAUn~0jinE5<HMmFI
+<ugY}f+IY}rp4mpO3}-0BTtKx<*`fhc5TZmqZZ!&=}?%d6DWoC`)C8(?}mK%pUMtAunnk{s>kn@-|ey
+!!^Wtt@sWi=AaD`l!TPx~_Iuw>#KxnqV6tKd4yjI+DN4x%}(-u`}$}W)r~SLnE!(^dlBYeTSHRj~Nf%
+@nzrP-|uUF@}5Fi*}!5MP(k+r5oQ4VF<LZ0t`DU83?7H>FOP{y5&RXzp?H#`E`L96wFO=N9^ssiTNlv
+B2c4@~rn_s+z*fyy?|*KsVPb=kQI8IDWB50^V6K!?J9r?&Ef$;?L-I%_m!NZ<%B9K6QYcTf^Lh2+P+y
+X&Z3(N5@!q#XP)D`t`(uuKHRtiFdDHe8sLYb1*wFqsW?B?2gMN98%ptgiKgzhE5Ig`7=lXEYf}!@Bwv
+G*EQ>)#0r-8clwy8oy6`JfjY@faSc1t;l>inuR1!7r9k!YljglzZkKfY>Hzab;xV0l!oM9h~*aaBU5q
+TpDFQa--L?7#Tr6~9{)#Y!B0{q-E2c{%kV^Z#1E<+S=j%Zcwl9kItyd~=OYV4tO{aMX~eYLM@DF%9Z1
+vlGKVcOO@PpA+orT6ZCrVy@n)ay5E!-FjoFIu6G6A^U#JzG)SIJm9K$TO;9j7#o=50DUSUU)W-g!Zp7
+dGl$+^=FYwpLwtvcgyG;?UwQvMb?}f*gM_MVX4yhI&4&GbCTsKCQcG{~+dLk?+}elMpc`|T-eL-c*}o
+kqN$K|3N((z?5;B&&YfISncP#!dP)h>@6aWAK2ml;P_EsO?d4G@s005x|0018V003}la4%nWWo~3|ax
+ZXsXKiI}baO9bZ*FsMY-KKRd8JfsZ__Xk{+?fPvNR=KyOOqJ(lYG>j3JN^AO@dG)w;>GHFfMNaac11z
+a76MX)=n2gumoop6Bj-cMc)M1ATVoIz^%KVJt;1Ia=edN5`|)*D_0~f>?5yVFDEaWTAG28ahlA%UzkV
+^+rW-Q;RST!;7<VIG(_=1hql<SY-u;G#x;W2rs^Te)Hke-Oz>MEJl%I1TXJiIsd!2H@ENaZeb-eNKjG
+6^PxxdEj-L)xCZidKUz+;8p{N8ZTRuiiBm#m#!qTB!yJ{h8D<~I<nrqL@+u6|nmr{;$&)rD9Hk9^MVa
+XE!|}nHD=HG*l8%3J@E0P%j5C29!1)2N)Xr_k`TXFN-;a<lOx+31wsSigb9WPl##=G~ecQx*))}HOLW
+!Kqdm}A*fn;F&-8v+tYdsoj5OGO`Bh!-1JZ^^BNn*#_q;hJN&?!w?r?!$;)MF*o-c}{fP}g(6VM_PF^
+Y*%oN$A;~7yt(*;DPOeRx`A<Rdp}2xm-7sRufNHO5g<cEjRzu9bAN3+xIML5B+Nx>CPj!$p@NU&#5X<
+2k7jRXV5FK3+O5es){mHMJAxTp%vT$*#ibvm~XKh=y$VM$EXctrVBM7{W%(xikz+NgAS-tStlZ?{teZ
+GUo4Dov4DG~Hb7lHIzaMFe{z{3m<ViHD9oeCYo_UN?g$f#J5vKVwd$#rO@kh}U5DmYZl29!P~WP37sE
+UqCe|%TeHDHAf-AGMGpn<eEqWS_^pLKdd^U=#;`jZiiSLL*y4#^h0@q64Ch}*!24(nAg&9R>qkl+p`e
+YK_k^jswe=0}Q)~6F4;~Pjt?7HnT{gvk1RrDLC-Cy4yev?cDj?nXd15ir?1QY-O00;maO7>Qr7x{Al0
+{{S$2LJ#b0001RX>c!Jc4cm4Z*nhid1q~9Zgg`mW@&76WpXZXd6iX5Yui8&zWY}UF2Qn8L`b0rfuU(0
+G|;A{PR^UPG_n^~TC=-~YfAguJNu9<Imsb=@oILS-+VKkPNx%~v)!+2Y^=#DAuVbz`!_xlFZ`~`RwCF
+9w;<}RL~lml2qjj$l@@}FEa>Nj+U~VjZ)^@%-4!m*&p(}AoL_u|)!y6wjPb!DuTwCHaQXP~^~bMe7Ti
+ctU}G?cFU#xj{_XDS=6-ntmC_X2av@DNnNmHI31tF&yOnzuaxsaq+B=TlDM<W{dU3BBoaa8mG$Qe6Ty
+?@gjdr6-uqwC$-hd!mzM}F~)p??KZ^j{n$l$ID&VhWa#WOmynQ>|ExGvFqq>{Z=aFT)|f!+xp8lx067
+D)C6o?Mzw*(gm{BJ+tQL7k;BgIJF{dx5fqN~=2hWU;@A&#<=$xe$&~3q;e^cW@STVewX2uc*<sx{0FL
+3FCPZ16N0IUt^&(w-nn`s!+`{YT^Nhs%;7@6v5ZH9>j$5e9~w1dFZ*9x{y-sP#4@_Vo+AG+g+vv_trT
+!1Ee|ttle)hg=a2XbSMOivEBjMp?2nDCi78s5e}!8R2gFpuaOaC$!#p|HV|N*!k<3IjIr8J8Dp~?)<k
+V<3Al9hFi(g2r7FC#i{bBs*A7Sb9K?U;)R{tZV<5yoZpmnlVcD*NvLB0ZC8*lS)~8_?o+3H>rYa~1K}
+#dE>p68`@`1`sG{Q0#`*nKyvPJGCi(+D7yd7Lbg1yr4ffLQ$klibL*X=GWZ?smfaXluZ-X!7Yh_;t2a
+?J}H;UFwZx5~y?45|<EFlQaFyA48DKlO5-!NUtc4`7Bp(^^$?D+(@YCk5{YOl%QdX*CV{R7JBcsDZ6h
+^GitB@k;3vTYy_Q?`n>ypive!+<3AE#RK(@CM|T~fu<s0KReL@!kwU<+gezuwki9BW^nRi0EfpjgE3z
+*WBr)Td!x|8?9DpfNum$*cPVKr<xmRa{tp&Z`<d&A`*>~p`V6~rlA~=jB=&srA5cpJ1QY-O00;maO7>
+Q_TsJU-1^@t35C8xn0001RX>c!Jc4cm4Z*nhid1q~9Zgg`mW^ZzBVRUq5axQRrl~-GD+cp$__pczl2i
+b)!6df=O#xfwy8ni&y4oiw*C<=>~D2oe4Y9y7^d+2Z9IfoP_CGODq!LTWw+jqWm(Q>(5F!*$*V=J_Gd
+2MXVy%&~_zdZRY==>#jf~BjhRNT2dJld6}J6U;b{El4>KiP}t&wtpyc>dyhb~rKL2=-ev$h_d~hB+bF
+<%iqX?|;9^gBm4Ep`F;Vmp8wJ=WpL!y?S@^3hlB=crF##TtWZ~*>=WyR+>tbZn3DXX;~+`e19)=Wo(|
+J>%CMg-aZPyKNzF-rt|+H;`~VoHx;6j{o%CNycLVZe$SQK@7V?Wm|YK$WS<s`MI~ysSH|4+T@YH)_j*
+SW%9=?hwewt;@d?D~ZG4O$D|~PDQ=?JOVseL0z$T@FB|n0$Wz6!G(f7gv=$v_TCs4`){O||T@Y%-<CS
+k{1V|rDwhTjVYM^+ws4`9IkMyL+5qD1MXK4MDSoZU9U3DUu>U{1DDaZB1E<E61yxX$Pb1$N}<uK1FGR
+^qd;`CI%hf{tV`I+o{*_ui!Q-HuTTB3e6bw)b51V)xbSTuETA`yUduR055BRpw9AvyyApA?`pWX*A&L
+*qt~%7+V1n$38NBzyWe@`_co;NW-O4V=aMfS&Gi%Rj9E8cd{JRMvFy3$u5e-6Tm$X0B!URc!VAuAZM6
+igd0kRvm3hN`U7E~q*uUG-YclrW&E{V=j@&FsH(z(75Onohem_Kwo-GIsFFv|>Rzd-V?rrMQIE|6Tr|
+D!dJi5g@&1xkrX-9uOy(j_(j2gAJ0-k8rqx?O4ys;*PlEtbPCEE2oX$M)bd=WMcwGZQsbe_PiYd%v)H
+PR5tcM7^^fPSV)F~{eR|c5_crhZn2*0==$^-x>#Jow;C8yMpz~J=6be1K%LPPt4RLxBvCG?{WYkTJ@p
+PCK#i25=92MH89XFb$AS^uCV_Q$dCK?ia2a6)|Jf2n7A4vEUq6X`Mh<r1m%&S(H(&^X8rUOZR{5bLBQ
+@;)XV3u?n28d)~1H7*=%mAr!+hrb|Om`<jRPx7wssP~Srq5T9L=sknodkEah3YygvT5P%mY3wL8J@Ch
+OJ9Z5@CQykkGtO=hm!@yI-a@~u_(6q-!3C1JAg7YDOQs~mW@_Yy1!DJF{@n`(9%(OYi3}v_#6pdkV_{
+khTIPjAGm4YqO(@CUQ7f%`UG9n;$3(iFM#Z`aUdGmkW9rixH){=Ykdlt1b@VQrr5;Gggw%Q9-JoT%2w
+)?$rs_+PxP#3pX(fIEkI3w#YzUn}A8!qW#b<3X1TlIt3j^qR8|zZKi95js_mrs(lz=v=mIghc&mzwwN
+$|W6!jZlgWGPst`M#H0`u%=|9csg#J&V11GR24Ki=Rs@6W=fzb}l+RnF!4DJBW_kgY=f$Q*?=|agJ;z
+9j-z`pI`!+NOvgH4IM;mYiR*!NJ%MRJi!A1<v|Yvg&LWjG%J7{Id{PIE^HDK8!+1CD3PBH3PTTj62LQ
+Gc%mWX<|?D3Y{Rlx$k}>5*MV&oR7^LsRdO}MryzYz?RqX4dhrFDnWIBAmp!_jTIeHz;T&YB!wju1Ndw
+q(1wiLjcI*LLv{N?R!eW|Da!<sfvS@hM0qd}WsCMJtBmWU>`#v%8f|Sj~AG@6OzTW<reOpMA=9p1Dv)
+gkW!}5|;j4U5FQ26H}*MX52S@sp8(_CtWZ%h@YSK3p#7hxZwH6B=Id9dqx>8Z6s9|SXU0zB<aJ?xJ#J
+p<8br1u9Wpl`ro18*4$-!!m|!Ya#F1oG9*P2lmkzr_*9ir2TlzD@f}v5pfV_%5E-9V_5h@wi{NfMXrr
+XpTaQ5DFINXl~k&Dghj*Xa@-M6u18hSOYY`Mp$xCjH5Q1p*F;fo&#ap7E51Anu2E`$F2g^9M(4qx7gm
+m{M*42vMZv7EovB=-cMy);s2kD&CFT|ThbP%qeG)k4myK^^Q|FfJ<CQe1vDauXd7|RmP+W}Kvrz<-^!
+?<DC}aSCQL~3Y@!#O2k41d)4br8B4!h|V$eh#ZEIm;L1*Gp!iwlzF#-H~95k_XFm1S{TBBHF9+>#dOR
+r8-AMwp7?q#An58C54^SGTnSl$gQ75NC1#_b;8<^I61>`Y*|brD~X^U$GJGaKuV-+x*S33!~o(3~mSe
+XmJGRI9VOTl@=9O9KQH00008031s8R_)cVRFotD06K>N0384T0B~t=FJE?LZe(wAFK~HhZDnqBb1!UV
+cx7@faCz-LYi}DzlHdI+dMyYXIus*04=i}A91_R5HO`KM*uKp{7RVu|Db0B}!<~mE?qct^U%mP@50Y|
+{yTjoK#GyFd)!kLq_3G-H$B!RBQt;XCZZ<lvt7)e1bxA+{XYhGMzkL^1T2T|V%Hpch)s!F1R>gK#rZ>
+0sOg%GS)zkCyug{*IKm9^2cdEYC>L(dS)jHlxRHe20_TAe*zyA5nl)+@_O6QfHsqfx=&(B}Jc=r6qH_
+z3&C{?2CIL%<p$1v?j>1JD$wJNpwR_!YDwN5ws(W7-)Y}7X0PUjzWo)qQOE_0n`H7r6}$J=eToAYngM
+EyWt4)(50_ZwYH=lOCs&tn*RxNlv2(7EaPyex}yqTcHJdZJzfhTxCC+@`gzw(&|&)ch^Be!JW5gV@w*
+=1*l=6xqDk0z~{P&1?5ZmR9oDd&2i7{-Eb^9%s8Mu5l(mG<8$Lz&DMqs(GSUMY3<`Qs3x%fTt`i;BOq
+@(WCi1&a(MjU8<|mOXQf*M2&vN=k~AX_cg%NN%-scI@33Co#r?46U|gU4C+~t*MKr?o#v~oNi=^2{H6
+5ka(7b}&9=htO$DIvOMRPGEog~e$4y3E?us&@_F0<id8tR&j~>ZaSVO6&t75ZFGaZelPyYFRJ{rRkbq
+@Fe=<`jy#f3)8(ffP7et*AQ!hdTTy<VUFaWoEw<qtJpL*uo6fByd5H2&i0U~6bat)Z7|z0`-Go3<BU?
+`au8z4#iT0s`iOAmI_jL{$TARvTU47D<%Fn`IKK`<XhQo&!c6kyKDbq*t(6qZ(LuJflG$i>P@EWKhsQ
+=C*ND7n}GdT>-o7)T+oo>JkLRVj)A$k<yEW;t^rb<#j=Dcp~=qyW4bitK#e~-c>*@VB=h^vm&n5$2e<
+HP?<^47g(5@&vSh@pGTV&Y<k?b6SV{Z2Y)0oXZ)mVHS*^&f+?tE79cXY3Y%O5qFQ?^>a-bK5Hejv)^y
+*bLIg(^iI*1PEnL&@BsybNZS^W$1IDsAziHwdEu#Ak2-!HR3N=fL)oel1J<%U^R%~&TFDB6U7R32khC
+hO2NE5B<Lfye$1KuYX)XC_Am%e^bxA8}SU)N>2Y(TE5rqT(`Xmwi@xHU;JY>JA+a9M22G_JLSN~=#)k
+pmsev}h`|f`MV9$1>b>N<3tTn9T@n2D!7mI3o_24YiK56cK!U2axp|hj>628e<-I>}j?EwS`>p0LXx^
+0uZwEaF3gWq+)`sYISaPTQpfB1j$vLBtXCdSkjSaHi*)u%zEZTKmB{rs1*R*B4>i^2bdKy2+|eyb5)n
+k3O2wLcD_bx0t=c}B`BDiJpG$a2ohKcAO(b*V2%l_u2_L4f|ZB`f!v@Lw9JJP2~wJwEEX_Wy3Mo2!tS
+j%_zQrHQBV`ix&$Kv|A38#624NT;1GJ6Z<|_0BK2nKZQ1DY)Q1i8>j39D_Y81nRe5U&3&0Ka1MERJ78
+pUGhl7Q@0(qkFR{#T2%}p0{D2Ttb2I*&()L8<HT_@8J^?z;BQubn1Y_vf;K}WhZ8#4leyh|%1F@!}xP
+*=!52{0OP$i?&vLxnnCRzOs5@-NovCI#z(@N-k@7_BcDDOcwcrSG?dHt2;6+ee6V4>PQDdw@^WrU5as
+B=$D#NEl36>)7A!QXm<$BVi=^1V5sFyeS~jQAQQ&U7n&fG(m-s)`-Hq0GXA+ViMq6^W4Ico^B0`#fZ$
+R(E?;DtE&bjB#34(pE9l9z5U_rkLq*vvH)eM)#nz}OEiZr(EQaa+&DnaXSjn=YQri3@ai@Op<M%LoGO
+6j-N(OLI9a+Z<8tRMA%*P;?5h)lUZ8Xr!LI=+C5Zisp!zgGNQC>AdOZP#ZUD!Kd{wNeAMw`&DSX>(;`
+|H|7cXI<z=0d;MXfK@k43I6m~Ryttq23;R|%GDlc#@efIJBZHPB~{WdS3Oq$(?l4+ciFbray77!y=rz
+3I&qK$0F>kcEtGj2Rz|7rZV}5oqIG_sndu&Np$rx?O+_tbwz0nG*fz)P)com<-&Q+<?J9VJWl^(M08G
+vb40|Xj|Yj98m;0E|zf-ZwgVwCo@li^4#6<zsc-3@lL@^@qfVo{vu#adlq9RpNa{<^4#>Ft(zQ-k16{
+dOay>oH6~C(VH4#336dB0Lb*Xv$J62!TO5#-L_f<@gaq3d9IK)P<pb-_NjTtgbu244P>?wk7(M0Aunw
+&1&u?G7Bq<hy6ARlGB$>6S3}s|g181>#|73bwZ!+939w9y6njfUns~4}HlZ9BZ^(2V)Ssy2vuqN<u&y
+JokEJE-<iSaNoGv9!uN>LVxGGHFS<>rMQ6F`Gr{s=pe)wVG~0QR{B{qE<NcH>+0hzS}a89xWXnC2<Vv
+v(EK$PW@2NMM#W_yhIg<$yI3$O*RQ5gJ&|mCn`^_2h{d8J;O`%wqfyM|$Q7sGkogjLT(OqmZ;VN?fTA
+dWY^IJiKYx@wH%{6MIz6l5G)EK<l)Gf5mhGK?_#VUGCtaszcsHkH^9x!D`GJH!C0vFq1}UZA_uc*g@&
+a_BODy6l?@*1bOQETTqDiF=-hTjM5UhWESZ3s%Xj;dHrZw?!dLm-SguSEgx(^eshV4xHQw8f}o8?=67
+^DN8@%^LdA4&C~swi4^Vgp2SkFH^}8?}X&Im+tK<rFa-+pU^;G|6gQOwzsi}Zn#}jM-k_4rRaXv8Ef~
+;<Yk+Z4dk6`uDNC5d(XIrxq<C-H`i+9vF)zxA??d3_rmsy8JSNK?n3y=L+Pb6&tm(l>xN~T{=Z$!@i?
+$84Ivq>5PFox+c0Mnv>0%96UcL`2;z2!M{KJSby##@Vz%<srYY+oJO(V04<F{-qnaR|Z${7873Cn$y`
+>__Uwi?4YLlCChjXx!Q%1RBg|2_8lQZ0yUlQg2J)|1c)u^GXO-q6wovg+bkFdMa+hY5C1aohkwfTZ|;
+ve2$R^P(br}PmJi8k3S(t0Szp4^z>+21G92S@i4|>LGX51=6{<c>?5Hh(D6okvM2}@X1gn39L@c-B8w
+SBa%4y4aB+*ahA}RCqQg<ognRjI8gIAY-SserA4!VvpP?0pVKOn6Q1g-1Pdv=Fjj@hArSZa=nkM{*ng
+>TCB_@Q7CCnz;y98zLq$(NPi^ci$oIR7p;sU=;$!SY#fl-+z6KAJe5ag>N?opoW42(9IcU-x!5h%tb$
+z3o9jB6usEf5)Zg3pZeXMv@gjZQG?l<mY(_N-I~!m~|%)%w<IZVbRJI-$*4LYsGGysenejPd|=>lpxu
+LzrDr8uc8vh!^FEKx7a=CJ=71SY?&xrfuUAxC?pF7#W5}6t2NVg;NrDH}ruQL{1>li*-K;FlCnifwnV
+Gxl*VEz<5>*QW$PNX+2^xRp{3N$<i)F5J|Bmf4KE5v*Qk;W0OiYd`;&iP0ss5Czq_L_85AC!PGOJFp{
+jxH3nzEPK}MH@}l;(hev)g&@c{~;n9}wk5C`7I*iHJyG?QrFS=xg1?OuK(bCX3pD;?s3-rXmhLqhy0d
+SAuegt<J$v08Eq5<nTAJrh!*y}CCQ)fQoRkJH8VF)(~GzP6%-Lfvb@wqTI=i*n^*qkUAAft6xFq<4~C
+~NQTQk^9gL1AjPq=X~$yvc3g4=_D3mXxLdMWXKkLrGbHa7=u01=w^vu|P6bx+bZEhKL9kevanAMz3z;
+Jgqj$i;OLI7{-M4YK&F^!y46(Mj&}CCRWnsv#y3<HU+G-bc4~}&M>(&rc1|!7G5Vs;+@H{%nusttQW3
+{4D~=RcikT?IlS{ebGp|KC)ttjS9)8k7u1T5G;y=*e&A)Cf+F$SMx(cd0^b)mgpA+<bw(?JA$6oxG6J
+^77_mgQ{5Y72e;p5tFmYSg+u7%z3y|p=wi-y<3WP;b-h2+WBel{Um?to<UVR`P``znT>=t%fF+CIG&b
+A+8=Vh^(IFx{%4Gtdr(Tt)NSOg6IxU4JOKM{cGx@bM~z<yVm&bh<&R5;Fz38Vm{Gy}QW_1f%b3Fg&@9
+*lqnBUBVko=i|gV5oA4uV4*kR<M^5J^j;%nZdLTeK<-=8{}$sasKqn>oJb}FUUy}>0<}|;$Oe(1s7t%
+TYk&mAg4hNcpqXj??E3ajY~6w*7j~2(q0FDqJaqL4$;FHqxa2Puh*ji?(oJSws6gzFVvmg!^YV+hHZS
+p&GO<-JxQx4ptBo}xr<}}s0Z3qkPQ&a_c{8AbasEBWv87HtwzO#EAXLEi^z9?g1-5|uKfcWzxf+=J`8
+{lQm|>{cj`j3UOY$kYU!RQhERE%NHol6mxLBa5wy<Ol>%q1?E%5=02c?8*GH6DH12?kZ#gjLLk0r@aN
+ZI7ZI|AtZ3XO1fR?vyx(3-k5&t|1{4V~hb3V^a`|Q$SHO@vo!Xgz1Yro~_Ta2Dd6Ok=6QGEtv-GCm%m
+^}utoYf=-Fl|bI$83v=BC#f9%UMdu48egMu}R<{niDrMJQL`(bn#GK8G{-vNpQ0;-N$z}tQCr`PmE__
+H#&#4Qb4v)oA^H6Alrj1z@sm)M*vIx_7@u#KNj^115+ntVA!mQR%TH||Mq34ut&@R;rgzSzj1mt01Td
+WSpc`mqnw3x>|)*GPW(Wsh7J)Bmp5dUuHqcbNKr<9gq(oLIa$00qThi|W0QHYp!_g$qmkvvAmxa^gM(
+9YFoaTXZ*4f=o<c7c=I{al@*1}B>H|)k4-e6;v&nwFxidjzc8(*@W#)6U9Qy;hCz-yK47a{84Q)RM1h
+%OMG8&4Lgacux@Rz}kJR$7B-|W+);?57<{L2Q|w<MEd<ZMr{P{H|@Sg#jX%)qYW9^H6j+7hVYavvaHQ
+9ZMVWU<i|z|hD|X28z0i!i~eh)hRWG5CKD!nogF99nM&d!T+k22cBKA_vb-NzgV9l*Q1}K5<DRt&?Kz
+07UNV0SmFk|3j3tlfYcC6Lt2RegL3L#Uu^X&Cq;wV#TSPaz^CfqII_2Wocf|RFYPxtS-|W)KQw8*>o%
+;WMAY79s+7PXy!Oq`}9<mO=fa)Vo>ZLI=J05fQ9b5ozh%#Kxc!)>F#LMgU7+Mx~kdglE8%n?Tg2on6^
+nlee}qHy|i<R#s_g^mI11AiGhZQwD>0@*R0fl<2BkNUV6AMFLITECG-SzUe#SH&1@R9q=v)iu`M_!76
+dngjiW0JWhDiWo0X*(+4PD0Q>B}vc!fvPA)&ujTY4nN))J<)$EgMbvG@yz)f(AJ9dXVl6rSPTdP2Q8R
+ko}hZ2D6G12Qhrq3t5p1L3-&5PCpI^_fD6<>u+@Eli9a1_p8wer=uDaL5KtNQv0|Sim*`3=^<X*HE?t
+x5ljoHjX#dNqerq&GkUHzyAZ60vnoq@5tve!xhiKd|HBW!@@?Qkaicue2h!lRmWyc<}`yCsVfIo0x}W
+<hnh{)s=jaIQ<OH3f>3o179<$BI%;hQgMDc^6!5?#j5Ke;ND(=i=mA9BeT@Cx<$*4gB(7u1QO4ylOQg
+Ux7rpTUY}~K?*+XL}%-#&eEO<hFkI>l<o{!1D8;%M=L!ifSzzZHu!R@i5`t$GYM5F|>8L7z26Y?J$`|
+$-=)Q2=&*qGR8PoRztxb$YY0e+Y;*v{YC9elKLfO3WxFFVXIx)Z){DQ5(mm<{m;lPuy4GgWRfT?6yl9
+PgBMkxjb7Qx!=K=S}raQo$Ara$?L85Xoe6LN0m4Xe>LOnnm-%coHA(4(|ByXoFRQq{}8LnNxY)ahN(O
+Kjd%0n$RQTvlcI>Q6k_AQmG3*WhGE4Ccx(jo+VWp&*$inQSxM^wIr!%>zdbIiZ32kvvWhomMq@WoR3v
+ja;Ri7UP-cGn1F;c_^Z(fO-jBTgNZF8N$@byOOtv^P$Xg19uWhP03a<D9efao#n!|J$oCa%j5>qgt!L
+^7O8blH&;<`NCu+f@T5zC1j&bp<uxnZ_LOFX=&zZQu10d*yg-0|f-NE3eo?3>6{2TD}Hj<Ws$?qM`fW
+Z=R4k#O0tsQ4azd|^x4|Ju&9TRn>SZ@c5e`6TI92g-SiAlZbKTNOS=LEs^Gb$%rn>|N6IP7VUpl@SJ)
+?ZOhwq!>z!x>byHB=k#4(Knx{4#?9SGU5zm{xvU+;v(Cl|Z+n9^|dp@zc#Gy9Y#O;+9KRNMtwuG5(+h
+5XJ*rl0O91a<;SkA&<;gS!0w)mJtRcnkeq8Nf_7^-1cg$VJRIh_)|FO7?K@LF2XePw@0D>b66kJjV9C
+ofIC)*A8Sm#i1Lh2KxU0`CsKHtMInk)leQ_qqY*Y7k%5OdIKT;{G~fbc4QAXSszAtdBP*GOwyat>GK>
+k_CS4vxz@5%AccH3vwd3jZyvG%8drGx#`$#+>-x+k?E#0(?_@?Q27+EIqIiuir#@%erNnOTyg%<}XZy
+3?W8MYgHnTYP9dYSA9G~XEoM$mrEf(gI`j0?R^?=KPeRkP-=Z8Y%AFS$$jh`Ylx{?bAp0Yv=Kmmu~y;
+1SsixRD##PSP9E&ej{qT`zPxnJ#e--7b7(Go5hXx=s_(CSuUAYbQZ#bES+t@ke&4^0>$)M+1ZAtbgj%
+%li&}brA=1S~SNX=qvnhoy9j*mn)(FPZ+^*hb_>d$zt4Ql#Gn~5fhU^ROU731@Tdcm#p4O`tWQD89iW
+aM<8U!Oa4EdBzN3q?~-w_j`5TjxM$@wH(oh?-Mds?$U|0#CpdT;3LQ&^ANrLj%1{cT%_$Ac&2sY@@c;
+<Io)yV;r@94ULgwLVNx7-iZPL9Wi$C`u0>e;5Y(|Ft6SKsu)|j~KgnJPsauOvBABu^fekeP5v*;!Pos
+h|X4?+%&ZkCY#b3Dy7{V9=$M0!_E31ZGJx&Z;#A9SgQhe06TjC*p6+S6&O+u`}x#(Usg&Az&}OPlRk8
+whwewX3gY*T<NB!n~9ki1*s_4>?}L;Ot*q1#?<=qBO~VGMY$ghnDidW*5gI;T(lw&s9OEdb2g?RHHfm
+b(-LWfPts@r+<l=KK=td3kfNniU{o-p^!~w*}yJl5Mk2x510Nf8m-cDMS_x_f)Ww@rClm})0t{=^CFt
+N*{r-#{f&8S1jYM!yPBuaI$g5QuPma`BTHMUhxjqvZyQd=$1sBg=UbeB+d^#$zNVWa*?TtkLunGFeft
+=M=WvwBb`XnkVz%tKBcsiyXOE1)Xzro#;3n^G#e>^0v8?34bp^a9-1{Z^A!Q#+e9Db_NaHa)IwY;Zrg
+?l<7DiI@P1V!#G2T}Q5Fh|pQk`GpHX5A(@*m52&7uD3T3N~s2y8*VV{m3}+r|olc8gFpux){fbFeq*y
+M08rHxd0IzX_O5$l6bNg<cbLg4g4Uop4fk?8FF$-&S4uVF-b<_=9*5fW@vD;{Lt33=wjqC{n*hDgmPq
+3dTK0-MxYPKJ1wT!(Q~cyT48h$Q|^F0>j!|%ryrXD@@`j)_tHZrk=HfVIaEV*<e=umZOa1Fu`}Q7JK?
+X_4^CStCr|<C!(K>4sm>Yu;CdbDxj*f1`)(`za==tF6QjtFa0wTQ+z__4xXL4kKTRakWFgj6mn)!lUN
+CZ=iVX}k*Bd$2%|S~yCm--Km+?l*dHWO+bIeyD2`u0r~i?~TPa=kq<rvE;J;y(86O2cZgR#B#huy7IV
+~waMT{&on@`J`I;~(ehqsiQud%sM=EG#hCegYqTj(H*ytQ`rj0o1nbt?vixgYXyjP~c#{jAl=%kH-~k
+L1Ryr`Ml!!ET6qyQuJ4*JKCwv#Re@RZi&!ID{X>r=nU!=C`UHPHbyiJhsJ%O35LYme*7TTGxp(K^>M3
+<5^wdu-EPgz^)SKfXDClJ9?6t)K`;kfkLxt6$49=?bnhkJ=(!G?Xfo6sI(1w62%Y%qH-WB^p!4ev{Bx
+~=`IsRQw4}uKfi`mCKzDh;i%w@v1`m2E*xwr5L^V``A1B0iYgad=#r1S%x*5qi46A=(t~ScQ>=sIvU#
+3>zIft8bjhFuapK>q65&4aFD}_grKm73A%`yc1T(BKuIDF|O5TmfYBuS^!l7$`STw;DN~z=slhS7$bp
++UBQ?7*&vWjgl3vkr2D*4pRo0im}h~?Vcwn%fUq`kDJHdk0<&f|ZX7D?RT0TqTopv1-VO<Bz6v$lXBl
+MkLEd(7v2r-4TSGxhKPXh{^ib0&0}%#}z0$dvwS=X}!+YD#W-X~YqQE4xaEma=y3_ulb1Q9n+XQ$VRf
+KVQ-W+^09fXVw^$;N~g?yCvHVfJ?OAs@qhTak;upH6NQfK?DRV`Fb2)l;jZodcfa0QQt=2fmiii^bG!
+e7P&|${%E(+7629rp7he?xL=^p062T)70U*o4JH&P?0+|&_I4A&=Xtt-)c%%37r*c$L(TK#-T;|W_IP
+B>(%!COK{(4`PvS+N<<}Y>dD~lxn^SM6ep9PwH4Zo(5es9JChKEOzxQ759G(ECRMNE)+UQoI$aPwKud
+$z4W@}t|6PbD6Kf4$v^dOOCCz&0@$^AfI<SpKak*J1AOUey^!_u!~y3AFq*LdU7mKM9iYoAqJP+q}OX
+T@DV>!NJ}%X$dU9m#LozG?T{Z}>UHed;rRu8!IRhSYq%q9UkXCMD;rBrPN0g+1!fD7!iL9|eX8B)T|&
+WpnqMQJ5YfX4A;{fUF5v*7sOC&d>@qiEUuwjab?zz|<ODMm)~p#jy&RW0@3KNHyXs=++>!5BeNYzQSx
+w$6e1&zz!MvNysxc%fY`orYs)R;e*gB8;`rR<YJt|1nfC2i{$vr73K_2(pu+dR85%_EFXvv$E};J=TP
+d5t6=(dz20Camp25DkV^~}t3uKpi-s?U7rCfHDc$6quyP`>Tsdlw+)fb2%5D@m;wn_=`q|qjL!F_|_i
+X4<uF0!+FW<g+`QpdtQlL!YP~d3WC$0b%*Yd%7&QgshmGIH(gPZ$Qy}%8@x8lX3g6C3|%#{TTV}P8T!
+`I`z+$QepiU2&OI7(Aeo*4CfY?ftLm#(;!+T!n$b~IC0<`B=jp5>gdiJDHQ*Yxi{q=bV5w^-PQi-oD~
+Rcz9lOEoC8dD1n;c{*oR7U6gsJ^&+lE9nX^SO3F!FxOVK>$a5=@q(a%WfIW>Bp`rbgaboUkb_A^RhTA
+3Si*TxnJb)PhS9tXIDdM!uthi(V`A}LD!gzdx5`WfGFxq}7rU;IqRqT#GG1`P9DI8^B3g|tt$aGrsSl
+>)75Q$1Ridh%ynEUqbfp0&bywKsl^in*PKxYge`rc%du(C77MLl=^!+*96r^NnThN(<#w2E+f;=fg<A
+km*^LYRQp+k!<T7AshJ#+&*YU*W`fF?j8Lm<FS%E)hv-Qvw@$*n_(fhBxYV+w%d$BDg_iZUyRF^V5%P
+-zM`V39b#G=tkow6%%xd^*cbU#XRcw<Gx`i%A)zLNU3Q#)%aUWAXaDYbkDOs3UEST1litPWI~$dgTrc
+nz8yI{pRc7ZscI-irIuob7|5H#{;2-H=rnLy7Nb+v?*W4FFQh41i0pi7b?Jtw*cMU8ckWo%1-nPn_lq
+*t{01O?*urH%2^P81jo-0u?<+P(>RwLu%SQ3VFQab3-8KxygIwMb`c=v%!}?7<x<~ENY|vS2gl~#I9+
+>VLt2abOSKPJX|F3Wkgpvi{O`|am*x-2^7lWS1P9Y|3*DFmy1|aamU0M|BP^T~&+NJB2Pz45UNT+J5<
+LPOgOrnw65NNs<Ii&2pCE|1=ghWe(CSbY$3Q>2#bY^otiEY;@V<}hNY3ssmCc7s6&%d)I53t3pTmuK%
+;1Mu?Z8<3xOkB6APNsq{RDV+%SUS;Fk}?tT>&&P?8$ytO%B6~fJYP9D^#_@)C|Xp%{ds&T#XEdGqu_e
+0OR`8;8lw^+@C+~e^A^kD~AB!sLM8!9VSAeGmi*Y7qjl2UH@|&Wm`bq{u&1UfUG3{^Xa^LcqL)BLy$5
+6>S-oNdi}{!ojE>0z4@PR?VbL4pQyiZZBufq$ksys$TA~Od3btXz*1A{AjsDQuOIio62lxI-NjNG-CV
+=Wy~Nv1Hv%*msge>hSD-XFPwaiZhqNcSHJ`tJiH9Q?g))m!kI^=HydTxZ)G&t3g9&q}pQnEP7yM8;m7
+zYUEIWB#{%3C_)f-V>Gh~rDsG566Gv&SP{m*_HFxv%hD3SN{v@hvmaa>&nRRnJfyp$=0C`>I9ybgExj
+;^)4j5W+h^FWvO5hZ6D4_(`3(**tve+D@4GyY4ZGIK7bfb51NoO77I*<v{}5Z?cE)+xBlj3oh!(s7u#
+p8c1~eN;xLKu7*>OnI^aDeM9#c1aU&8ZKnjy?o^#TD0lq6$Kz-$y*CnJS9uVf<nETFVVXbt$|XG11^n
+FPhj^PGJl#=V>(f2LV&YlBX5qdhf4BxGg%wj44|d=oXzd?Vx%I`%HIa&v#K%H9nh93cOL4WV+BrE#`6
+d=_)#$N%FBRqk!^!50&xFbewEzD;V&@V|IJR8o$K+A7Jj@7M|=Du{QL^HjBghoG7=F<5Abk6^>W3ncA
+V*-4|e?oR&=92`}W=27q5Su*{fK5#Q?RxAoCCZ?_(b7hdRw-`++W|?f3h8m~JRB+5-;xE&a>RNWZUpi
+D&$thD8pzyWO!e;sT;rEiO)modx_1dUlSq$N69mt-qaL=V1PhZr!Ic$p5@kcZ94v)~DO&OBwz0&81PI
+!^`fk-ztE}j}U0Tqhn^#^85Q`R%7#<SoeBm293YgGqYp*-kHH_Z@;}GKhR4<V|=hwnYjKfN8r!ww%Jz
+(*f&C<&NUaH_#C*Rqh37g!^(#-zviZDmce@>@!Z7>X$}ePJE?4OOS!OPi=wkB{v0dy004f7y-kHommt
+s3Ip@y!ly+b#hnY(q4^FI*5}{l?K@M}k!H_YiuPL+Ol?vhI^8D?omk-dief|AwFjc5jzPyo)!hjew2}
+@rDl>u>O9&uQZ1^Yb2l){T!;7zo<2!p(-i|q?U7Cv$?s5G<dVt@Ax$(D1&?kO(~R++KsYLle_R;JhJG
+hp#`InQS@)m$#Li+HY9dWRt-zSGVVlD@Wi@WMu!v3JDVDk9K!GEU6(VuOUK_^k-fuY+ov1vPZcQhW2k
+93E2pdyyq+aQI~oNf|#FH%p~p*GJOYM9x;)=4Sgb#&_;~yh3m@PS`qAX(%XAHdD)?8VE8!LJqg=G&D>
+2jLipb)l;PbU*02ZH<uK1_$F_O$PF_doJhC#p&6NW;hY4^7BM0E`n2M4yT*L>?;Z!!Fg+Oyo#!NdP3R
+tviC1;DgMl#&5|=xl&uBq^61E6O>e5o!;<}d^1#iGyX9U&kMVu+`L$|R5-fT&SoZdSjttW~z{dfr2s(
+;gE@u)rYrTqph<8}Zt(AMqHUS8>0<o?yUuuPlU$5Z++mG@Ej5Oq!T?WeL>Q`S_g&caZ#SXgJFr#HsSG
+JKg$WvX7J8-7*5x|sgjnhCun4ydq1r^11)Z$K3&xY9vbf`WgO8WektZmCbf9ZZ1=OQ)W<O4-5f?{aM`
+QNjD$ORum(Sjn8?O>?Y_6nQ~qFeKssm({MCZsL2Yr`~3Xb>ZFlS<f+Uji&q*wumX)VsedP^zlSpolo$
+M=`F9MK1b6v-RLR)({iUvdUvB)(zKOxV5Zpuc(Df{P8)Bic5jm7g9~~90M1}qt%*pninb}>;cp+SM?T
+-WOv!;w;da6IWwAX=bCbNYF|QeIN2jrlC?+{FG*slN*%!KUyTOslU5n-4s-hI-22Z}^y8<qGkunj{4y
+M;P+Ku(Aa&=DF+s8c3O3JOpCQ*yu|Hx(Uu+^B8-C&5MSz%gUg(faergd=Py+X|{)wsrZ&BHYIEIfzGp
+}I?*^>{a+;yc0S@bF=j$TX*;lPHQv7H!L@9Gh1mH1F}srF$_0eCX8-??>aS+1Fp~xk(2G#l`vgxq5<{
+!+cYpt9&pJfV{+WfDIbqTV}^&)K0Q4bKzw?H0B4ryUgOvGKtmwOx<5G7FrxNIO7r>rAlA6UYXczfC@F
+4e(*iIzxv{uCQ8}*R4&qqux*KTGRCdHM|NWwM+N(zRwiNiG@&=A(AARD=@%dct5N5k=HROW-HF)5O?K
+Rw!{rFje{pf%d2o96^t@81XJ3B_>`zRL$0{{#GTdeO6P<HOY976O2AFiz9pkJs1}-!)hzezPd-$*5->
+(vN`p4;)YyKBUP4+D0zW`860|XQR000O897^_9XAn#Y-~j*t+5-RpAOHXWaA|NaUv_0~WN&gWaCv8KW
+o~qHFKusRWo&6~WiD`eeNs_t+b|G**RMG861z)GlCeFQW})o@8;o|;+g{SlDE2uKNV1WXQA62p-&u;Y
+q+KVlB<sHWzVA*N3<eBnH0@TQb~aIUiBf3vr@x;M=8vzy3e`x29t;gP77aujZn1<~6JH;TlaQ1ab<-N
+L-MJKQ`Yp^RllSA<WcC&|Ew~-R*Mkvo$khleB3ym{_UZ0EO9G7)1!{{aTxTCc{LAN?<!!cvsy0xf<3i
+em4X7|iE^Fh!AY*yXrOb1f!)mximsdifYa7ffQ>%QluPQXdHDj#zof{;u!KA2FL*U2^heK~6TBPtxz!
+Oc1W_*O$pRF$EAJz+aC@&yhK<cr{g%4GZfW0JbZL7oVc$Yng2v$GS2fKa)F(aK(C;Vf1e|?uNV=`4@1
+utE9HX|7aB}FVJ-V=-56gvw0sHi{%TsI85z0shOt*Q4-G<{tnG$x{D1d2a;Njrac&>S3IPgZd4Z!f_8
+P4r$Ya9#F_#}<&En%<4Dgx%{hIim|{^NuaCjTFuwM4^(7TY}I5wHi;;@zGfKGhLt6Ni?rE?ua8d1pS+
+L(j!`qvZ9kUTyHTtN{(PW?Y=lYWfO1-5_RMu@eAVrnDRx5b$picFMrQGvXlQ?YAyQ%P)h>@6aWAK2ml
+;P_EuvVp^;q!0018f0015U003}la4%nWWo~3|axZXsXKiI}baO9oY;|X8ZZ2?ntySMo+b|G*&tGw34+
+Sa97)TSV!~<hRtJG0MJ85W|Qj=U;3)hZpXC*KD+jp@;nlz=1X?ckJ<Gb(fzO&B<2L}PrmlcZ@N^7D_<
+O?p{+VA!kxW$_a2p$MrTGVrvU<98ENO8_`VMDM>Zoq1e^jDA@bjGt8Uu8;L!SACLT9z`)X0s61OP(x&
+EQru9k(}72l3*;8DbuO5B^%9j0fx(@Mw~`xAt();0&0-Q8**oR&yt673+9AHrUge0zfc>lqyaUr=pq;
+rgb87s1t?iXojojKjYj1<K{J~HpMz8-TQ1WGuDB$dA}p6XSjRw_)p$ToDe90`Dh&-VjUW_DF$HFU$Ra
+Pcz()$SLiPK8vHX72^>PsNv)(Dlu{S$+<CRKtf&Dugj>=`vK{~9MwJ(v^uq_80^YixH`MG+U)i&=Ue6
+%lM9r(hO7)TfuA2F;abgsBWAQqIqXk{hKqcU$fTa&iHNH>;pxd0=WSyoz_LR$8?KVM@Dfm^w{wJLTuc
+5zS2QKcmp8zG<3(LuH}^k(OciC4r815eXWR90xdSlT{ZJ`LgI`1r%yljD<9xG$>vQe8@mY!#N$!Ns@f
+m+|c+@-%`cBpmkP)8w<?9}O=D*OP(MF{RtWg^7X#>IT7R@O^L_53Z-Tck#`5cs->Udt2wN7hH{Rzg|q
+Idyt#M(+eikyV2lTq?esIhoilOP8q@l0i6fB^QdFm&_$dnYD4C5p;ey6lCAKl@A9U-el7Z3s}*$nPqh
+S1CTD|>31$|CZhN4$(i^T8ahE)Pk^ChGJDt>yGM+{8FO;d$QLEoP`Ri!Y;;9@THav$gp18qL*QG|AYY
+9Jown+q?r{}PHYvYXE+)#a6D8EO2bjb{z9qr9b2t9)W6WeQq_Xe(Uy?KAix1)X)-X8-!9UyVN)#&NAG
+zfMS?CGh9f~}N%B$1E9$92A)R9llbFcvBKuR{#!rezuvW~tHd2$!}<jlJ=OaGzUPBc)by*cQ#1V>yjJ
+J{SA~ZKDt&mGr2(Ow?Y}*tf9QU-83AYWHN8HF6~?{dJ4mX&H?&6&yv{V2H|x?r@jiO~ZJN@12ckpMRh
+F-vs3Q(rbe0^tt~NNY(jXB}=E5{!1u-08mQ<1QY-O00;maO7>Q(awqdm1ONa43;+Ni0001RX>c!Jc4c
+m4Z*nhid1q~9Zgg`ma%E>_cyDlYE^v8`R!xuFHW0n*R}8!dN^4uNw?Gd9oW*wQq5;x0SZ`0VYsfZjv(
+*<!dJ_jhe|u+0O4dqpvOXkQaz5U?c^q;u7<hoc@_fj6u2m@cfqyAVZC3wl|2(t&kVBFl3Muq41AR<19
+C*%UqPYTe6`A<TcVHsn%D#}0C3<@l`2o^`{t-%}<=zBKg+|vDl$L0qLYpGm7Ufxr!%;`@Sbf6XWb*U)
+ZgTe%Y|faN!zTwDG*7Y-D9+*Gujk+Yd|HGyOe(fKS3H7W7Qfp45APr69~W~2YsYmWQp`C(8a$Deh17`
+K+sh)u|G}+rwM|O5TBxv0^s(C77Fky0rR00@#TrmKx+qdrnH*$sDmQ26UJ_53+HInBcHkO)JnwO_o-Z
+CBKFwi<$wLfXij@13#mjj4_j0)$FIOuTc)z`WT0F1kALf6|KR%=FC5Ar<JkQ(lJre#eUvH0zR9yS1*;
+GMfIFVeRWDYE5FoZg1s7@O{O|s1{fh+>HT+((H8uWfJ0>;9B3X#{r0^DXR=JJ_lud(@Sk)srR*Ub?Xo
+UhA7^4z6Is-G-^#Cll;8HJ!)lKkwX03tU%R>%{|i9~~%sdX}N%H5`g;x+?vaY=`fcEAD#NH$}}^ae`w
+)lh?zyp(<ep|KKs$cx&@f^K@V@jEiGa^`!@YKw|lyRsJ&5zneX@nltnPkCMu6u@i-)BYqyo}OXq{5x4
+1l@6UkeUp+J(;%f;liBZ2X3;w4c~<K4_cLB;csz|(s1^S{VgW4c2=qg_+_QdcM2N%QrXxG0T9heAHu#
+tXUGaHuG>#&2DzAOe&}tO9k5`Q%Og9=UGyxQ;tkdddpW2W*X~LvLVs>cx%7&*nb~;{!qQ}7{t78W64s
+%ldy8=FQI3_O~vI0jE9+sSPH_Ei|@7w4pRTn_B=Tk#yvZWwHW6yd3|G4+$Ndv-+gm0|X_v$x%J(L=?b
+~Vw5)*goo<kwjHaK1gC9pEUB<~*;@XeCp-eBl&jNi&B!XSafeaI3B*RdAA9lGYbp?<sT{*vNgo<<Ps-
+ozvFtQmkSE9IZOSzkXudJl%j$G?XRPrA~WHY<1@%ttEe<L#E;=8c%yNS!3gPg>4E^Gj1&}jH?Udb}Q(
+m(YYaw_RFIA4w*mV&fY;jmNg~_-NJ&a6uK@of%GZx26Jvts8rOs;|0a;=CNgnE3aK>nkag(5IpAfmo{
+u5!oz7V@pgT5x%%d+j}e|Z%iS|fH5(hM+r4To7rlEss0iq)qoHXgI(`RDQeIcydOTdB*@|bZZXtg5JR
+sZ~Y4^65#6i3uAylh-Wj@pM!lndWSWmohkkbusKTJpF26d0x(D<I=v%mwr;f{LT8ryd7T!LF$$E|sc+
+}cX;4?I4&F*d9AGQbiL0D;_#9Fv-0VO4MQh|!C}sj)epT;tuWxq3g7OwF9OSiJuMP)h>@6aWAK2ml;P
+_EtBkmbrig000yW0018V003}la4%nWWo~3|axZXsXKiI}baO9rV_|M?WpXZXdDT`+Z`?KzzVEM?8ZdS
+j*eZq#^suM{II)Wq2$I0-oQgu?O0yDUiWEpH_M&KiduK?!_K~1HRwrp*{N|enb#ZYq1A3Z$S)=wYak<
+bMZ4mx_^vr_vv62py+*)DxAnQh9@B{%COMHQ?a9BVWCxMNr5tPtnD@t@Bf|5@Np9GmG5EcQ2+k-dI2<
+s5Gt%pi{MR4r-g!^Y>3kSXuK6n?{pf12@5+US9dwlT;yun<w<ZgB(Cxp_^9m6xu$*n?;uka;A;85_Tb
+sn~RXr0t$1m7xQ0bd%6<U{ev9&JQRM+MjHfpdJ%iY$qIyko2alrc|0aT!#0hpMS$G~<&?^dL0I0tExC
+%ri>~Zik2P_JqZt>)bSZE6d8S;cfp4*H>3R|9E|M{SyP{gFba-1COF!fkTAb&yVjuK5UX0M#&tt!!^9
+w+(rHS-`?JT*xbX;SfbJksa!I<pf+HxtS263vstc$b8xSVkGn@=ck$3_FKfKF*4X7bguduH=RrtfUG5
++hg~%s+pnNQfyrM=BBxb0TZ0ss;C5b70DnHd9YT@$=cCF4mk)8~}dlZ{U%;Bk<(0Dy*k+WM0SEH{?L7
+n71TJ1u6ovExN5V~}*&?YujZt6xV!ZjMXAC@DQ*myfgQ>mp-(}hE|TZLp-uv4ORH&-1oQ<$L!)YhU7r
+t3IA7)g4rBqi=D)2afteKN(dV~D<v=ZjYPbNK|Dv!^r8q!3=fO*r*bkt)=suSicX3$|Gv8aXelPic_I
+<mym$Rv5sL_z+Z3Q9(UvJ{XOMir56_G^xcj=T;)^pMQ;&K;uFY4q4A0ZHpPVBlld_9z!p(Y|^I5lqie
+7wR%kJ_00)I!4^ZxjWrEgzhBVjie*Wf7A8;A<%p1u%%8eO=^FAIEppp5Y7bdwlnuMBwU(wE2#)002(u
+J%4z6q$$urw8nA0L$+!=IwPMgTIBqrx&0-qhmHA7=R`0~mU6^bG`i;74L3{Z9>>_Al*`Effer!HL*K$
+8VhAJy<M&Y|x2&hrnV*J9F5<f4<VCcU*hTeQ<av8xtC8COGfCsp$3{P&6!Ya@odzE_)2@hKV7vmc3F0
+w-lT&-yf_*g-uk-m1)Mn2`ZL_xQhRGTx&BdRRWZ{`sSnUr`UqaT0AqTp<H|75Ezh#O_n1EMO;56_gY&
+vkviBp;}~&0=C8|45x{4;YeM`oSa=ho&BNV6f9z}?qi5HE(32Y4%fcaw3T#D7q5dX3r<<K3aYSUzU3a
+w*&@pldK*?-mND{xsxN5xkr<azV<i1)SX$IX9Udg`Oi?@BD+)RdH@NfK=|lf-$8Ea9$F)7E>t6idMsb
+o&&9rfUA2AR+>{p@O(d{t3o9g(rIKta2sRGBU{?@6J(weqeoGcc;O~z59zqmB7ggtZbgyF&$k$YMegd
+f;0Ik||#u+EeDa{5PMv9aAB#UyBlVE)UcgUjO8W$}6rm#{cf(KP%gr768>QDd5}PK}6!Gt%R`ji2T0A
+5cpJ1QY-O00;maO7>PaFo^(=2LJ%#8UO$x0001RX>c!Jc4cm4Z*nhid1q~9Zgg`mb8u*BZg^#QbS`jt
+-B{^w+cp&cuD^mX5KzigHBE<MFqQ#b<E#a83{AQYa1Dl)=$I`nX(E+lLHf7vk(8*@sf+GIF`<V=zKie
+u-XTsV6A!_Y-(9U)s$?Yd6;E&3tuo7>2ajjg&kYp<GL}l7rATGyilwZeiXmF6Y)uu9QIf@_77H&xlP!
+^8x2%w%k+IAQpi=OTXquoU7y5T(6-?tSzbp9FN=?zr`X}1o+xzLs{@(s`^x+Pv6+?eiW+TPuIz*B&^y
+2NstFt%fkrg9&3>LB}`tAJC?jOH?IXgX{Y4s>!igE!uC*TH;uk)->NZv`$TNc^cn6F?TRXb^xFxlOTB
+pi;dX$<~gHQk?_-5hhNdZalmq&{IGRZV%w3l=MW%`B;Pex%7Gqs(b$Qn7>>3FL;W6;WIXFvjyv&JN!m
+&koOCq6366_M!-_v!oPkIz>A`0Ds|+-tmrSf6d->C}TmTtO$+2&R0eqT{CG`&EgRktXe{D@#OW%45_=
+^tk(Scf1~Q?<l<XZ4Q0MQ{-V%R;2mN0455R|VHW$&^}*E8PO40Jfs%ShqdLxnfHy>isL=bg0q)ZZv<A
+R6{*4r!16HS#CJp2Owd<&(a787FvlKE(!NHEGkXA&&{w{$xA+)$EEy@qjGqaWDI-#iOZ0*^s;_Y>Ev*
+L=$oW`sp+X^5uXEChbKUjAqY>A38^(7O_$}9TOuhFs&4A4ua{J?GVrKNDT%=Z@P077Klg&RRebE%93V
+5qADv4ky=Ol%a|IDZSl4e^%3Z8*1)Y$>-BYtKirYgSxCY1rB$j-#Uns#%A>pj<LEyN#I%s*ibkO$AR-
+ZHK|#q^|IwW72>UH<ES10YgmPiQ)_jPnjky&DR2U>(b_f)zB*hS3Z89;s9!ERu(Zkz-@^es+Iwmt(+l
+<4UNu*O`E$+5l?%_>mIw2;oKGhFcnX)pv1B`D-x2hoTUj%V-826N#ZZlMoqy~S)@jH1m#;K1xuSe*cg
+glazGaU?iwFb^g}6Vfof{q^P0+0^)~%nK=XpqQm#`d9tAVa%n+G^7@Bw2T_x0rG!ZPZZI4S!>V)|^zN
+cBrCV}OI@KecbS)xer^ph@SjSf?pqPhSXpX>IM^E@Kg;IXWT+(1y7PS!Nf!MAlsGQH${YyO%I%2Q%pN
+{kUsfX#yWqHz)UQn22dj*LxeqEF>pXO)Ery5N9RgvIV!E9Ogld9PU?&@cBu_wef_!QKd+rtvzsG)7yk
+302g96wbvG-#R3Ma=V7I5TZ})?m*D>hlHZrDY~6MTfm=4WH+qvgPysyLv(TNd&t*%fHmlFw6Jl|u(zu
+853N-L2jcd;jwIve2!ac7^X~^9!<q$8J6^9W3R^042*M$AV<w2eA;QtejHiCH96+k(0@{<0clG}J_q(
+{YM(i365cnQzh~p7072G>2jE(z?F{6xI^^x$sq1szKME5SR4_zcY1dY3F!jifT&aH34&N0KroUm54=u
+3b=T&b0jv8K2F9NzsRyP4bVMPQ%?3mRTF4FJ$Bf*u&UkAbP7)9h`Vdx>;Y09Xl#^>?dM)Pp4yh$9nrT
+iL)2AZ}L;{kX*K+W>Vv))xH3bH97;5RL284;(Zeu2za_n8uO#SV9vL!O#)I200=CBfKjDZ!G6=jUXTo
+#vCT0sX)2UAdLs^dZ#Izw}6rw$}zveroqqw-i>X{TH&f3wHPz76*iF3GO=~Ofu+G_DlG}0R!E-JNcLr
+*-<u)5S~zYR2!2fJsO~<j2ZPYivSA5_G_Z-c80NOwY-Qsnk~&34_Lq2SzbY<2-)q{5d7CUAF1J5#f5y
+-wQXf<!Lq>nL_|~R8NKN};DDBAKT?A94D)jKw-Tk(vx3}o!h*btEs><8ngdIZcX$bKxb%=D~um7DpYk
+F0%J1m-U5BMWu8XqBDV%ux4;QL>xLequKDZ7+VkkU+P1`q{aB4k)ya&VmTC+}#Hf(P~YCxjOKtQlAIT
+2}<;-)Mq%HtBLiU|UOJ-ySY`3X^XN9nx`xFdM>`-bh7l3vH}OU_wry!<K6KGY&>#B=s~6Af=^HE)erY
+P{V$hnGH;aJ$KNTA8qJe>gS99WJ>4?{qb=VoTGvP8Y&3u*g_)ovuEgkpnz>~zD46OqLtiMR4vQqkoLv
+GkH-R9k$3Ez+l7S_(4BMZfY;Nz%lH}`+o!y9*@$xZl+ghg8Pt0pwUZMrrN(fBW^Lw<)Y(+Svlpusqlt
+z6CjIsc7G_%bCJg`*k>1b!Kwr`6A2{lHvQ_q*d$-1bS|vd32@Du8)l~~Y&op!SSd~)i;-L##y4=Oxj^
+P?<FpsyF);-A9Ev9unTXmPCvo|L%E-rM3+1z3t?-z}T|8>v!KI(Xbe`|xbvu8vLWA4Tl;M~CYtLpa1v
+t23wN}*%LdCNqouI;wZg6e{|P62ZT{U!Wc=xewD@++1a?<1F3UHr*A8C6AgZsTU(2w7~v<@bTMHk8~&
+Jz%Mgy|8l4)&cZ%^k5Dtb01_^X2LJ+DdH|MecZa-1W>iE`2+7?P)h>@6aWAK2ml;P_EutI+xegd0040
+q0012T003}la4%nWWo~3|axZXsXKiI}baO9rba`xLE^v93SZ#0HHW2>qUqQquWN)tFIBilG=!dlFwgO
+vMG}(v22ozbOWG=GkQFI)m=zja|_##p-eu)~?rti7uc*jR4QfFspJp$Kym#t_a%W)}pIaNRXSG#)Zw+
+~UtVxlmFFaDvi9BacY=Ifnc*;3BPNBfmbCzH$9)5-LLEOtaLDfw!`5J{ueh?JC)>%Z=P`}5oFSkvSzr
+bS6-<iqWaw*UV5<EJmTpGe9DNvMoiUXFWbFzsF{_=>FAdK^B{BH?0OB_a7EEeKn!xsc=z2P1NOcm3t&
+`rA!-_xIONx4mAU+|V@I<dUqS^_mqK;VFrVl082^6UoW9Uq6tT=UhOz5Pt_4c~8EpdG<*XiAVJ{K-(g
+Z;>Tb{f{D6<kuwRJpy4WQ8Ztp?p?%Qkn|3tM`BuAKrL<;S<Qr-uU8TNd6=jfpWTVxM@h+-@)h(Hbc4(
+n*@t?8uNx{V`%DuR1NvlNPs;f3J1u*HRt#q~7OFB)v050`3?MC<oNYl36D+3aAL0mB~h;QF6nWQ$lGW
+`IhcnV4ATF^L>G$DPf7A+GLO+mMMM2cud%U<Z<N<#+OC8K^#M{Y3k%!oDxw$f^vs{%WT`H+R++sbTe-
+K4MuuGHoO)*G?TE3>V&kAPb{w{}%%-<WF=XvJ0P>(ZQ;kwg0;^l81KI2rnYT3LK4`XHyhmL6+0^y}j!
+=|j>@yewH%M|Bo!BmUiRRyGJ*b*psg1}M#%rb;RYwo?szy<VJ0Wl3(aS^oizb0BwXI-Kc#ozRqoA;>i
+h2dlUoDZP%!A}T2il2`(em<t*`u%q|*uuJ8Ez1sBPqS1IAEnX}&xPnW>LMZ(ND(g5i4P%=tpL>{85cD
+b>rle|-qKf1|(q}&l8xDTONUn12NP@z$6bjnqKA+6aAvi?u2W@8{#cCn$e0JY514mAa0icFRaoHyDW&
+o&`ndS|Oi(?e?$vydrOv%q`aPAMLYS3%(t14lJ9SIs@D1E0JtWhLnxn*)W2%aJl3<;{CX^Epe4u+@K9
+;8g+Vg5^$mms>ct>Dm)b*t6uO<svJ@=7~ao}m^DEC{N{jlTcr)y0bHJ|w`Jq7`~vu5%^_9Vt|z257iX
+&3MJUkgV9yma#xBzqiig3~p@2I9^8rTF8ie;RPMG+!P#KZN5$S5iHu!&bw>cco(YJF56PY>Yl%u<~#^
+SWMcnt;Qi3P1C&yNg0o^t1(N}m$;~_}5*Hfhqqc7c<C`+g74m-Gann%{%|QzM=yD934F`cO6pF)UP#4
+jj+IP<d%2Ki5z2{2QjmK*Z_eG~sRk=pD;CXU@NtFQm8aY3au;3?CPEMp`GJ+GpG0N%7X88irQ|Gw>7m
+>4q9%H?D*;HS~d%|qzvkU#GT4b|hoNtiRe}Yyd7qk0zzvzf{WnyswX&jCBc5l3^lj5mZa0bM^{NYHKF
+Ij~Wwg$%tuU<m9;srlO`0fzlzUEbVPxe)E=pJ+C!3w>}?En=l1fNj#s6m{=PELLGT9ia?ICR&0VP&p1
+QUF_I{s<o&70mt!yC>(%%#KYxDLao!^~5bnH+HT*y4m+J`twzv-SNz>x*1`SxwPKY0$a<8i8-P@sTsh
+&82fqa%hOKLi)@puVl}n%z2+Gx6r4$F#ezRv_fZ|H9~3Sq=lKBk$M?eq&bI10ZrZ|mebU2Sv~VUBOK6
+kbH%V+;Rd9(7svBvVP9vSm`{5qEZYj<5ulC|~$7tf;?ZsD%tevW1s~R<+H*~-st~=zcl;)<#&fv8KqX
+z^iOQWNdwRU2Toeke=$L+Ni|7Z#)Tmc8odfeJB+;gmpe#dBTHjyKRYPLDu;rwWDo@xcNN$NywsK&v1u
+!57d8o#d&+V+gypAr5<MU>}oNRA&ffsc1{n+zTva2+2W$cn-$5Gmk)y}Q>>KIakI8#L&fmr@n|l4VQv
+Mx_-%Au4l&B90ve-bAF>tQHgxQib%~(G+TvBd}Z2PJ+%^_%vNvd8s?ra!q3v<)=>1z`Z=pi`avNN2hC
+P_bx{4MNsRHdSV5WjKiX)syQd@i6t8dt(A+qFZJ8*)^W5?uB8-gv5{0c=k%G1QghOT;K><;Z(pL1$>$
+Vb`WRQq$(`81;TT`E>sR#V2vsimRv%m|O9rZ>VrN{rHf`wwU*C<%-4Z<UuaFcvZK5X=71<`r=xbG#l*
+Pu`oOIL(81#J-ngAhvj`K}IAxU*~@BI%@O9KQH00008031s8R+5;!9(xA>04Nv$0384T0B~t=FJE?LZ
+e(wAFK~HhZDnqBb1!snYh`XOaCxm*TW{mI6@J&RATkehTCXrW3-rOj43OJw2F)Zv>~>KM1`aLJGHZzx
+L@J3<w7<RQkd!RSRQggs#3uFe@LaxgQO?fJ5(1z4P*hwRof@_0(r*1H_#}4kl4+3<iy`Jvb4{4ciP>?
+Y4g6wF?jGvY;TM^z4~-~xW<jpHpXAfWkAL~))5lN0k<Gy#e)P8!!&x;ansajTx7F>#(=v5pN|Aw3z95
+&&Yxn%_+ttne@`h|xLvn7IDB;dCuqH{el4(uWD^z3!O3qAMm;8L;3}p@6L_U*yCAm{F=UbxdQka?M<<
+{fyvuU>g{PDBjkSgb}gRp+@btg*ho(K)!#!5a4@q$uT*Iec^1fB;Ey-@s0opwV7(uTkAM)TS6P{U2zN
+PKwIf4vq`nDyG4FeiUvO`!*td;sx8a*p9487oVo+nP6NcdQ5E@l>}P7hE*ez|DheG9|&;QukNAuySyb
+*9{+`JK!OK0L=n}QT7avA;Mk=VligxHPR`-0_?}4<kE%aC;2?`exO?cJTRu2P)%%Ybi7Lb=Z}v+Qvtp
+JXUxvSpm|d)dD33E*tCWRHyqi)U%_Jo-dQjFnV_xn^Yej^t)!!fIUYTa#~@`nkY@N87HQAoz!_d+01U
+m-@Vax!X`rapmZFwcTTEw~QuGj|=dcZn^q)%j0EA4a52tcJkkyWB$OVZNA;SvMaAaGpw4>h!mO>UKH%
+jUlafX-VoY#Yk=A`14`hQ=SSSN(B15-bcWz91Id>ItHWX0dm@fMllBKcz{4A(WwFpY61J?<noI%75O5
+4dG=(=_1WeiK)4ofU0%%#d7hEvW(JOC<|5!|WhgO8&+nn|NBJ<aYJ_4$LNxw~yz^160wYJi9{uuT)hj
+8Psd6ms+(AD4RjWN&d<YuL{a`ch;|ydsZE_#zk@mHZ|akZqu)mB_svt_?h^P)NLg9ZMCsVb^C53d2D5
+7T4scjy{y4r@&LKW%)mX}MuO%z+PepSjh6n-C2z1b^+rl1e;FFuA-cnUZNuy=K<;Y=W-IicV-l8$Tr@
+m0B!fbqL)sCw^&;RXD+SZo!>UE%DdD+fzx`hCBJUdS)y_fQF-d})7kX{uwe}TYX7KOaDdm}e=DYTjWA
+UnKIhMEQXN!G)#=^>o7l8UcKilKa&%Q77H=&L5(}rdHS7_WC+*H*Nf{lPyct}YLY2_s%&%6Ne$ZHxX(
+bdTS=#A0VUNFenWbM%-Bd(N$4rfqd=O!V6?`*)@#Ukkw_sf?rW2rOh+?rmic2jbCER_LK(*X6p!0@1p
+&!k)*zIO$V4?BbGPwi43*~ZF-v;5#^D7)pn3#AM)WXEK|^Z(%tXXX1o2>dUQb6x$M>G_}vMjCr}1QSD
+_JYMzFqn~Py8^|?KqC$%3)XiJaTn1P8BfinvNoj76oDX@1+X-gvcUF(4PM`h29=%h*C<$c?>}jzRz^z
+xyC2_MMJU}LZkZ)UZP%VKb3yi}Cj`z(8w0s8i$KKIG5I|znN>_uoIPSp)6eTdJ!WsaXBQ+!xm)QZz1k
+d(vEQQHIWXy2v@h!CSWVyPyzrJ|7Ua$V~c(Vjs|8=Cnf=qoVoqM`Kf0%|@9DX0WPZUgFJ<j!_Nr9B>t
+V3dhdPhOtG#+VN&pXJs&KBQirl5511$rFRddtwU{dAv=fY%&i+}KvK2!Qzrh)pfxCAya*;G^bku1++i
+`+5X?f=Q%#;bWudz8L{Aw<4C)z3JS8%DorrPDjM07u{TXs-t8>;AJaHBVtseauWeYOsAWA2)x34iqlM
+H0Wcmv3sgfO#826FA2B8$0&k>&J{7y0N)Z6xGG34Q;DLMy{EAaZ3<tn%448grg~$T;Y^x#gu~ASbVp`
+JrFa+K)81*LnSPp>`thK;^6w{eV<=YUrV#Ng0s5C?1-&rFVw9c4&UShygcF>nB3jDoP8#c6`z7$d5H{
+YigN1%uTPb2eEb;;$M;biUU9Nsm}YZgf@#O0kt*H))XsrC~62y(IAino|V%|hTM3};4U`!Sa4O$fZ&v
+1qVqU&FiUhnJ#4yT(N-FGoO?#o43tF|du3LVpT@Q~ic&9s+N9!}G}XRPRFIHwlK+>Lij>ix4=K3{<~`
+z$aetcx0LoxU}z-F=Kum0T0#YR6_*nzS!FVa+*DTNwK)}GFrhAw+Vq?OT}UX1Fg0p@HT2Q0(T)09bQC
+KrIm;R(>oQW1r=ooe8}P>4Xsq?p6>l`s!Db3qr;_tL<bA1UOS0{*Uf0sbS-XxgM!lRN0!sNFDd?2bh4
+y$S?F=;Ez`RVJ1H47+l_$VTWG|kkmD&Ot46>_{6EiW($K7q1HX!pz5v{gkP{rI*{@@u`#;I)-95$q+x
+Db?x@zxnSf;o+nWO-hkAOE-y^B%2;A3EXhNVR_0^Y(aSfrTKVmAUpFM{5FI_?!>1bk>s-JWuT7HR~9a
+iOYXz<LCP+M*);h8B7ZY&W}zJ+x>?z*Pe?1^zE!#IpiNfPW|d1yD-^1QY-O00;maO7>QJ0R@o9OaK7)
+_5c7O0001RX>c!Jc4cm4Z*nhid1q~9Zgg`mb#7^MbaH8KXD)Dg?Y(QW9><aA_nx2PSh51(E<smSSKny
+M_E<aNod}JVF&srWM96eqN$ijS0{};m*SnwHRln@YdJcIYkrYME%nFE;U6<_Yx<7UKXXa0S@{@P&+P^
+P<|LGUy`RiBjfA##?tJg1|J^z&8|Mrc4?-2eGEU)ff)VuKc=Xbw;{w%%7<t}{|UWW9#yp))`R9?Og&z
+|3<@Vb2Z;^pt(=jC6&D*3LyczO3lc%43L>D)DzD~TuJcj0BZ`#e1V^sDe`dG-F?KYaE4?)8him*vy)y
+u54)y)Rk#yXUXIeD<=X6o1cmU;qBg^6HcHvUHX&e}7kBzWCzq^=IYo?_WH7-v92teEH%(m-PC2|AX}6
+%iq6z_UUJ@Ke+qFaNap%wkOWGr6=3p{_v`pyVoUr@!s95Qttld*Z=q*|I<HwB!&6l^Jl3%e^oxX`#(P
+V4-)^&zx&1C{_3N@rHHw-3i$lh`|tduRrEW*NOwQKd-U{;F;AYpvGwVjy*9^LAGN3|Q6WG5%50sXKh{
+od>NNL=-PA^p;+}qG4^y6g)$$vk@Ti@-fX5ND89bYZZsKWdwbV{)J)iK1Pk(KUvDU;qT<LPf6j~y~xr
+i&<eR-nJfU9)haJlQ9=G-aUbISIWS@z=zkF(Q*LN3PwjnH1mCA8w1bupc;`x72Vr$@wd^a@!|;u9&Zs
+n^R|B)*hR>x!qBwbh~2UXR#4T)Xe7?9t(goolZWQ+v$e$`c;c_yS!ML2HH*wDHPu;)yF%Ud+7|=i#CG
+36K8$^R#$Q;zO^BGg|0E1gV@ch^N=fnJCMdHs~py0Ihg3G5HV=?_@q!JVAvtE6l+dsE0-g>de8CvtWD
+9g6la8i-p3w>`*cmmI&=t5j+_WeuJLk2~g@HtbB2G;yIwaxk`?<p1rWs*5QDeiVM_OpsE5@6{xBZiIq
+AE)KQ>v0<{v7e3o7jvXm<0k@^VKN2rpa+A|cXl}N2bLwiMPB}%PCY9&%Dky?q=N|gGD)JOC*RHP=N)I
+_8vqSQoOSLh)g-dXv|M#dsF5oMgjgU?VCQTl#lgv67Gb0g>^`zL9gL<dGzWE{mHSqeK;Qel>fQhhPvN
+wi^1d_Pf2sl`YwMybU}M~l+YBDEN0)I<haGCi?md;Su2m85>s(g#)YE0hSSk+gc~4vi8-Qc@#{8c91v
+N;_;+LZT89y&};ck`yS>9}*==lq5+>Qidz<;vo@wMUq~TC{L;eN_`|smFX3kvSrGaDM+Ruc_nXo?Gss
++TxW8fWs1wRW2PPR$=CDAo6$iNlssl;qMU?_+~*X<)B8!zB%FIa<RZzF?OerE`Ibz6g+5&t-Y-jkzsM
+X`7-WUHw;aNJY|s-buQ1b=gPfHUW_nu*ydFH1_X1s_&>SW3UJOuqn{pKzrKBAy5p=JTX}ZGHRis?}Oq
+uHY2kXX&tb6}%B@dN;TN5;s-`d}3zg`=(XQ(|Aw1}t2yWVPz668EVz56vv#3~Uh5eGqs1RVtR8K}{Xp
+va4nh(tt^h(tthC%g16(<l*(C5WEh9zA!<p7HEGmE{b0PCQlKsk~E*czVos^3Dd^#!q>BbkE+qsoiaF
+)b=1~+3_rRR*#4B?HkOyg-Qh3*fSs7GoC`8_JXI1hmRcwY6&{{*s+tDgJcdSoc6#Yr8#)>g!y#6JGKX
+&MLcBl^cIg_I^D?4xe>Edw382<LEhm5?Kcq*&3w`)+M|~+SlEKaL(zlOde}>+2X6*iI7kx&>NW&E9r!
+?q6%Qqdo-`vpC`xLPOvOq~wwbZfw9paTJlLrx>C_h=HXYPd;-hWW!V`&+&YLJmk_u-kvbpwTs`RBwU#
+hl<r^i<>F`gLd<CPrN{=3^K@6+#U|K+iD7bbFE`{Kja1kIG9X7TU_lT3S9C=r#FXP@t!+4~P_dn}zEM
+9@#$15c7AX~I)29^SV{ugmu69`Aa0b$-Faa?SbPW^J_fEVW1fn*9E?$KGk5Djh#UE;%S~B$}c<TH#%G
+8?;w$dn9NPPiM}X#B6>2oOkk<cRWnn?Ezc=Eo~Hc#2s-b+?0+Py3y_~zV{kec06b3RI<es=W3=Pwcx4
+L1l772Z#w1U?a|7xSoQ|(;XCb%<b_&WEFGvl@bHV)9^K<Cw5RAZ^Oh&Wr!?ouw}NMp+8%iL0cwx#*%+
+i@TkzBa5AW>!;)cDpdJTuLv0@GfKl_1&b2wPf1g3;=FhRCQ?lcQqucvS_Gqp$QlmQhO<>5>O2{R+Q4b
+C1BnAzF`58b^z@T@S0zQziH)lCRFbXs|b1z)3==YUo`mKZBBz4AhII}|s2srJBA_+~747^#6?nD@|2(
+;j%J&-MtN(!`k=v<9ZO_P|34EAva0tW_4CjUM7jo%WS@qZtaXhpDehYD^B+z5!`txHoZobgq1gr>~sa
+fF{LUh~c-TJ=h;Iowo;`zO1Qb+o6dF*+uq2*!pZHsFuE$>{Z$}l)V;PKeo_AJZGnw@7GLBmY6ItSv>4
+a%MO)f`p9jxh^NZNv;C#vYE5&wmZ+{WT)j^Wr@p+-z+D6TI(9fmpfzKw+x~CEwRjC&H1N=O&ZN<&1_r
+BvNdv3q!)ZQTpD~A11GB#FvIbWDkkcG5PBXW-QAdl{vMpK*%RU43>&rQ6Zb>ttG^%*%Q`P0vPx@1f;W
+fuT1Pu%tm^DqGN1A>X!)uyrpQMLV12=tr-9|pw-Dse`&WdL^HE`9;_tnqk+Vn%azJ3_xJj|}HbGWqCk
+L6TG?S03RXW+=@vFbZ#)##vsQA=@X10Qu!*UV52m+Q1zai<;MITx+>Q$K!sP5soSKBJbrA2VF8JUO$y
+T>Y$IxU^n_8SezE(e@awMKj#b4TdYuz>zl&42E;$Evz$8n=0sGRNM1wV3|28qh^@mhjVbonWeale8$-
+);yUsf^?<86HSlyAc<SqOu*RT)vn`{3J<Vb!ZGsf_LrF`-)^j*Vm&<cJWE~HAwsp~3D!X>CqF=A`^{T
+JeRbSVM)y@gCjVC)?I>wr_3|Dd*n3B5Y>q*lrrv?@ctU&|y>upCgTz)iRb87TH19uIapVX<<+G2*Q?}
+dkRM7#E*dbyTST~_Ddw$t0yb*gI=+@0#uNv=8d<q|beOY3H7b*^r!H?OYIkD7C&zF4b)n%~8Z3@wXQm
+!`9X;qqGS#c%35XW-;4Gf=a(&Tp^!`g+X3(c+6v%FVf|YnErzH20Y$tpmRXbtQFan|N&#pY-Eio7rcr
+)>S#zxM^S<4Y_75rT$FVZC28zMc;H-G^Ym60&V)CO=r;N)W9@f*AMMh`^0WXF?W|V&?%=*)mDFx?6D~
+4acZE>6U{mL%xU!XQ(te3`X}ntz(d<D9HZUZN?HT8M4@W0(fQ1#@oU(2wxf=d*NRX2oiuAMX;(<6X0x
+B;U9K^Mwq3A}^Q2$Q<CnO(MxV+0JKvnAx}v&9z2sR1S+kaBOJ{BAylv{z6c3F(ow~GEvbIT{6G9n3<8
+2eBoI1}s&Ur4U2Kr51I#!$x0k`_mWKI)Wyc>hXYeIh0*>lrgv;|$PY+=#BRb5-q=q(SI&iq?Q%2|pA7
+7f%T%BH`$Tht!0MX!Nl$Zv6T!?hpExToRLUa}R<a5<v}>UXLR<gMy=s{RtTO=}r0T|{g(D`#;UIMQsp
+)e(4T9UegkT~N;0+V#nBjuwn_bslxp#I%jfM;#0??O6kN4LnW_JTy={O>@TK3Zqvf%~Cen8d-l`vvs3
+aH0Lo~`s1AS_c1$dx2*e(w(js6sGQ5HX)db<?wY3d$?Vs4xXwIW+8WJi)wRq(udaOt9_rGBVo+Bat~6
+d=$KI{EMguhGU|j90u94t6eo32alwkGBr{k+R&*2*DrQ8P46Lns*R@?lK4$++BGvUy{aE>pwh3;_aQZ
+j4X_G{JQvZJ1xGYpq=>RQz`ie0oXmm`fq)12FI<y`}n^VI!gb84W@p3RwuYa1CZX*a_a^+Q?HEMxIgi
+Zkk3)TOT!x2fwGu0<J_85Y!)^kr|=wah?G(d*k@-}Y&^R?XO|-&<$KR!wHrWL8aPoynBp+BCsU6WnHk
+n<lu$;o6mP*N^O3U0R)oe)ycF5Bj~JwH=f(PR63?=&V<?$5o>%mFCpI(`(?VfuU+(G{cqDmDQyaRMiQ
+pT3rS=rv`5Nah+YO4U@B6y}UX-t!d7|>9jL6rv~amxH_+atJA<$12@g5PI`6Aqs^LA1B+&9D;lWl{;I
+3N%1z5~YGBqZ=@6}l(aaxOqC?j*&8dMp8tb8%KaR<HXkaKBs2@7#hfe*_sr7a4R-<>Pu6+ic>Wagq(|
+A3DCKNTBXVkznImaTS{Z5aWr0N<)PD{l(dZ%lPl`9`Ej5>C03x73HcaFfrmM7}G0#gZBvv=neSYo*f?
+6fu77H+)W;Vwp9P6Mwro9mbum^uP&9f6wpDkq!6Ng%s%3B(D6=7m6L`seyV=xDfV%&4Z$ndK!7<o(>=
+e<kndgZFb^kvwhB)K6?1?N=RHKK0AbJ8O9I|2};a*QalChbYyp{T<!WuVk&U&;`0ecjyU?&<us2EAzJ
+LgTim&xA0r|LFiZuzk}bw@8Eav11PW#eg{A3919$y?R}x}b1l#w2Q)wvv|obTey!4|gL>!&<r3R+t#3
+Ww@qEYgot5u!&u;;8SYQiwg&#DB1=nIhFxU<L4SoOtc7uO|e}jL6e}jLAe}{jEAG|{cS#?SQxUFjoQA
+)u5y**$(C@c49?Ln&GX6#Ay2^hr!6R{_?5cpgmjQ~?1jlf-e+W<mIDe^f`7B*5<QPSg%-^MH+N&yhZ0
+$s3)JcC?l3sER}0*PS(leEnhl!UTmA8dvNn_&yNEaVcTgDq4_;RA(C7Wla^=%WnE3zZittQFP@EB)Bf
+j~)Hk(T^Sd*wK$2{n*iu9sStRj~)Hk(T^Sd*wK$2{n*iuxp8ajF!<@mj(+Uu$BusN=*NzJ?C8gie(V;
+ICvAfWO;Aea=(dh->pUsZQyo3k(NmolR=^tW1liG#raJ1*LV?@Suebo{4^VgD=@zcj%|eSUSrB@e7xO
+9}-pnBQKx-^C)<R<~G}c06Ei~3bV=Xk+LSrp7)*_9y&`b->w1C4}1WvR7!t)C`;PTgahLdMFd4`i`IC
++MXXE=F=lV>=23hXJcXE=F^?SUWq9e&E*ci4>r)A1k?Jp+ilP~!m_d1}-%nEXjPV0b(u$^*RezyLkt$
+}_G!<H`fR@?c{;!^$(PJPqT4wD|}>;6ESXkMM(L@_=1D1I#A}_0SD^Km(MD6L1apx5m?eKJx+aL!MUj
+w4$dKJ+0_zMNcbwTG7*ro>ug<qNf!-t>_E<V2(UZ>1j$|;b+`=#+_%}dB)w!xLX-_E8}iu+^vkem2tN
++?pDU#%D7t@cPry=W!$ZdyOnXbGVWH!-O9LI8Fwq=Ze`r9jJuU_w=(Wl#@z~1)~tO7ZNFPU91J)M!|f
+*L(;avNC}Zg*u?c8bd-QiQKdNnN>v)e0B(&}Eb|?^!+%Nt69u2xcSLhBsp%I#){euPEP_gh^_yK$r3%
+`XQL<?87wmA45{0@Exzk{FL6$d|fo3g;az`wx1z`wx1z`wu`B&YACI)&fE56q+hs45<Q4?l>LvckW@z
+rqjBs(`a9EBq_`AacqE{|5gC{|5gC{{}yRC2pYG?*RNe{5$+qdfDOM;osp0+)@ts5BLxG5BLFjl>`0*
+ejqvJg#Uz}skA+a1{qWW(Shhda)IOm$pw-N@B<zy0LMy%ADm4AJys(85&j52c(MYXtR(nB<N%y&6#fK
+%f*+hv$?#|R0qqpvXC=d*;Rg*>Ky{S@e}TWiU*IqB7x)YO0KW>TpHkrm`%}QBl?p##r^4VU0FB!ZvA~
+lAGeifjPCWF>x`<~Htde->S9KK+-KB2gp)b^3JTz;SL0D<UdWz@76U0M<)F__5d}&kwQc+?+KmnL&58
+?&CSE*_NEVRc0l^80u7Kx$8YLx^k2?)xq_PTM_1SlXQR>O{Uuw&)gmJ%L%LIncV2b{COxEw3dMhn=e&
+YP$+mpVqqr9NO9T?yJY=m8DTj&MplO#Mo;KS*TX#1lI`i0`AK(G|KwPpI%@D2S>P{uBNaeh^scg#U#9
+gden23h)Q`1N`8pK<+jQe}ErERf_OO_#^yatWtzO!XM!Wb(IqQ3H}5>I4q#Qjl!Sc2bq;J{2BfXKUl4
+l;m`1A_(5-_0)LVEE7V`1Vhe51$Agn!0GIo$+bGztKGTM+&zX%b&=tBvPiTY+C-ABj{uTZe{uTZee$Y
+(Y3jYfK2LA^C2LA^C2LA^C2LA!)0p|hd0p|hd0p}r{q<q4E!hgbl!hgcw+d1t0x2Dk*x<gN>#AYa<s=
+fc%G|CGLFD$&U@WR3i3oiiX+NrpmircBUor>G3xSfjIskohr+o`ynircBUor>G3xSfjIsW_0YVW;ADD
+sHFZb}DYC;&v(ybZn#W0|#u60~(+SN;I{*Q@cC0yHmUS0Z*4>2s<^ppJ35;s&uDHcdB%kDn0q;Nuq%l
+0*MCr1N;I0AP_vlBjJ(ozH|wZi6Zp7mX1{u59N%zc%p#JI8TUX16{TV$PD}y0Nh%~fu`{jL*Nyt;qwd
+}l0+sY1wf=a?#m7hw2E-qiXInldX$;H9cM(@k8|Ga^_DvORWAh;y^;G~;Bp;K1IHyv_HlB?Q(ZGUYjo
+02>iKxq8|UncX0ESbFPGKKt>ZQ{uX>!A*KwSi*F*EMjziPD#+hc;H1(1#Z{xr}Z%)(P#w};wW-V;vfH
+ZH1rn!Z2ZLy{KdJgK+D~PS=4Mv@p6$9SWT-yvBU*DG*=*w`edT+7owa>oKz~fL?n1LhndzgXAsmss6Q
+(fbr{M4!`r(gO())$x9ndA50fX_FA&+mY`PDRqd^;x}9_S#5~E&X@0(Y~WvIo{dWd~bzaaO<~EyPz1d
+9y?neMx8k<)Ol#%m7VND3+GEkBoq49*6u7L4i?jaWlGuw^v%*H3ot(SAM#!^ou0C>;8)M^t8R9|SPQK
+Bl%M+~zwH?$Gmv8kmbmXY7PItG-5%nJ;EFRr{ZMEzU{l+pPgtg}*@73uFFUxfnLeLwyZk~3E?8zPfy*
+Lr(B?$LtjAm_ukU@87=Y%7vsYg$bY}{ndAU~Y56_&HWa<J8x`Qb_1^+pQ%oY_U(VW+i+3GpYk+;doN^
+Ll8?-wsFQOof3&2@am$q?Z5_K=g4-h!(ffUJdXASV`U?Yr;IiG(I{fg3Yrdvvx9Jg?a}g4lM6Ve7rI_
+1=oavvcNlpg$1tWOKZC@NuIem&pFK{mkLvEMe!gU`Nuy?Bq<&bX(s;{LqUBDZ4{<w#NpWh=m=T;vFo5
++oNxTPa{%-966oH^qq+8og%1qa`JM5?l&h#kEaL?ok$3she#oEgmj)F#>iRX87?tKVi0#a<;!Oj$wxl
+ManmV>f55vNl_WWeI7PPUtm5gP42JIqgS?*+F+!>?Sdm6#^aXcGD-yGaydMX}VUYwD#0HVkXb(gTSCL
+>``3}-~L5d!B5lWOdIU)*D^uQTWkfH~Q9>OJ^$frflG;qihq9hPSppj%a91SuZ1qvNFJ&97z*oU1Fe7
+XUjZsf<>M9LZ6C51?glrvJ!DCLZc2reS)Co*7h6_2Dz6USX74tY_E84tu4MFuR=!XP301MxpOSdJ%bC
+)qqN=H7W@kZd9=7DY-d2AG4eQ4Ns_NK)EFX_FDDJxZHoKqN|=+$B>e0)`0kNl#6Exnq)ad$va=(O;94
+CedG$lqOM{B&A6-S_+p4;R2O+qKFuZykPGRN!p2>L0jQ4#uM{GmI7o7kfi{b0%R#b<}xCa=j@T_TSa1
+U-JrBaCg<&E5D%x5SqhL(*iMOIF32J`oSDTk*~~JRWljeRw>zdRA`IxngD{`W6`bXmatPbuposPzy96
+QgM@Qg%#FUdf7tTS8^Z*V;ObL<-r=OgP7*0hR6$w9%KTBXnD~ydIV}pYc!vRS9p_Ghq##v-u;LyS#Vq
+oO3z#!$+DBrJrw`=M_Kd1*{e{wEo9A|l)VHr7DFdRo2WJKDd|Kb`>pA4Jn_TZOV#Li6r3F??}JRBmKz
+M!`vi(_3EQEW7brzhs*Gp;vkqr}U{93OLXrr|g~bRvA_IC^q&jNy9KH0s2&LJ#ruPrF3CoLo3ghnxtF
+xy(1S99H(e*U_WmS)mexAeac@w@0rVPe-v^ugFF@!{L|SZimEhjJe6#%2x1HiRowec9;6t4GSD25`-L
+L?sD$KCQu-bT>=r0)Wpt5cd2le4|bQl?Hrix$e$gO%;8ah;E_)|SR5U~eDr?XDDsX+Af`_?_K-86gLA
+7>^4UT2jY?CU94wx4yma=7-ky@?$w}TR37j0h1xX;-Ue!S|6}lj^mHFB-_gWDLZ;zfpn^p02(OD~VUw
+ic06+vu^ICWcv$iXtFxQSnWz?6+j2SNtgrXsR~1#v;v6gF`{myrE!kB!qL&W5-Mby?1i^2YJRA)XVFx
+FDV&9+83z2);#$iNr*SiNuI7A9IWoVIqf&vddXwGBH_VGONqJ&1}ogglwCvL{EZFmZ(93`cit~(7pBF
+UVw$;vc<~c)%L-+*dT&%eF?X4wca0{%~ORw_fg}E5g9iGv}8hP>sk**j?1${_vATnaS>Kw+YDzSRy<Z
+j;gIm!oSdulMY0Tsuoc<#v-~9$Q6~|Oe(K-oBAykxizh%Yu{qZ%Ln9phOgkKXBikMkPZbYIAN{bk(JV
+m-#~Bfh<1FTs&HveV9pRMC|H)~^d5DZ%Uy8MLxWx4BPoukdSfPs~+ey;W+XE}A5G04855Y#gco4Fa?;
+y$67WW*Ngk4tp$ldKCp2x8TdK`kRgxUixu9O1{q7V|BgTz;m<ZX{$09hl2F6+_v3q3wEZw1aU8a>6+b
+1u3Y+JhJ;=N?Wxhj?I164Ujn1Q~#tQ<uC)@$^pK_nLTm<yV<QYDda8x{C){wrG*dvxu*;Jgc%it8w9!
+Wf4)nMMU`uf_rib)6cvbl~b4wOsD{8+anT_iDC6nMeRWC(Bv-Chs+-ms8v(}v`0it4^QbcTBD>^`VzW
+U<QUsSwpnu8)Aw>!PR}c+<5f<_D+l6@2J!GtmY7V8h%R<HVLACxU`ltYV4ecJj2W=L=F&4HGcbJ3m1b
+a8m&&#nuYv3Q(5ivQ3{-(BHv`={^692jksIhVv&_sdcARxBPBY);7<IWBIHYx!nWbf4hiiU)835Q;-W
+fO!o|@~JfqK$5(^UMdS!X_1m4jTD88~2uqEkqmyNa((VFRPbG-lss;5LQdG_cQM!*!@jMTw3@qo)wwp
+#oROlGHWj;Pm6i{P?k}aNMl9L*)~XG6TmUV{`c#IMSRl5$3cS=w{%M95Cnn&^aVWnybvf(Hg;w4iK!q
+)3%=KT4$h&zu76&rj-<Cfx`g4cO5tys2w%TQ`MjXnIX+I%Minhv%pb5G*3*>LUXz1*W<wTwawlP9Ksn
+U%{0>h&6+#|^MLO5CHe@gL)OJq?VWY@&N}eaePoZrVWZ+C=9qyhU1d~2(YDRV<(gu;){be#c4XJ((xK
+BOZPcZV^E)<bbW#B*n>3+uXxdyuipNcfn+^~fE={uId@k29Igd?Uhq|VS*pbyW#nVm=JZGTF%(ysH&n
+iM@rpT31i7lhA_x-_eX^xixvu-ZU(y}P$;%4BYuKA&5N~nz-FRQ-2-bjXx>hiM=y~?urDFNtJSk2EmR
+Iy^~^<=m?S9PiA*L-IUqh?mUxM<GNLUWR|n@VJD+K;xG&^A!ivgx^;1A}kpblLVSBXvdFTAe*?P<aF!
+7N@R}PSAP_tBQbyV^P;O14pd~?I&}_uwBWOxaL4^&Kal;o!qFRG=AjTo<o~FO;M<sP&O(vWu}~!N{Ho
+I$gJHc`zdEN6H*Dnwo93Thq|V~mX<dUX<S?MC&8BSlhB6e2z1MNz2jy#a_cxgUM6SzQNJp|&#vjWk>h
+PP?-s@{+ZN`LbQp;LE#w(khEUa<pSS4rM0?Z2YZW@)qKXD>@z4|P`Fb6FbE~7L?6VlhUat{$%p4zKR8
+5?mZJ}I-OK)jf-c-hDa&~ON<(iyn{B*^1%)l|V#VPI=(`bV-vs8|x(g`!L7?pg`S*(<?8Y{(F4OEGj;
+-*l^t}YdlDT^|y4u?_}<s36tDT~TqczwkypI1IV`LZUcA~I#2d0aJ}Rr9!NimRr$YKkgUqr%;#Y%{@4
+6WlaG9W>3UVjkNR^Vs#BeU^XMT<o)^c9mY)ReI%^ZF6XT4;2k6r)E9OYzA$`Fk3O`>tVir-NyD2dwr;
+5`?t%b^K1w7`{D8$cwC}e%{7*G9nf!wYy3QRY`+W@SG5avY=6he|MK;9XK2w>W&u{(B*@`@=p^ThU2>
+w+Q#`=IY7h@cIu$ieHHp%s)KmVdr~Efhe)IHApOxRVa=qz4L2o!wwj67=9S9U~v;iD#$N;w-mP2KWQb
+Nm_vPCDMweVZ`E&SX<S`>%&f!%@f@H_aqo$TwRPT_a(JNO;^92U3Ve<=K1lmJy~lnUVx+j0eFJt%Dt=
+$hkX%h{~uPRycf6Bv`RTrAm@l+pcXIr+9+SXs{REmtp=tC#kh426G#e}jL6pPMbq(XZX$M@3v;=5-4H
+4!`JBw19st;9m>)*UGuK<=h*PRim2(QG`Q~?%;y0+#Fc0d#qgdSndj~Xk)bKrb7ixe+Ud;aOvpGvnXY
+>+=kd7uW&wYK?hqj=UKTKvA~1djEsllaSJ}!MiFm_d@BmZo)ponX8{6RG~-ziz?R!?%Qd9s8q$IQwjh
+8l2w*E6v5?C`F1Z%B+;z7(8cNDslv^&!Eq8LZ!day};J7XK;g-uf+mDg@xP}5>r;j`OxTB9d`naQyJN
+mezk30IfqmMiKxTB9d`naQyJNmezk30IfqmMiKxTB9d`naQyJNmezk30If6D^gFj_sB#9=Pb)PE?#au
+JJkVZ<GY-+Rh7T00=!@Z=utn(ywj&am&rb!ZpgmJ=7w-iPLwph+fzQ^!OsTW(&6^3vIY?+R`2%6A+qM
+5SmyrY0-QO&9~5e3(dFCd<)ID(0mKcw+POGhC{z#qjdCzhFdsWG~NmF-ax^fGX_0l&@%=-W6(1OJ!8;
+Q5uS?hj6qLz_#J*w6&`UGzr)WJou_6vj%}21F6caBES^#3x&HDDGS8Kx=gQF|(c&3mo+0KLVjks`p1V
+EIt)pjz`2aunPo8UO&$YNmxWzNDJm3J&@bVFUxt8((NjyLS&+mk1+<9bPJiit`37(!0AoJpBIFHPWr}
+;e1=V?Aq^Ld)j(|n%h^E98Q`8>_%X+BT$d1PHYSC5{i^c8-Fpr<9hNK!BaSBBuq5L_98D?@N)2(Apll
+_9t?1XqUO$`D)`f-6ICWeBbe!IdGnG6YwK;K~qO8G<WAaAgRt48fHlxH1G+4)o2+HJOonCBtQw0e@?N
+H!l)_l!$1K=z0=Srx@jaMDWtRa9z|H>Y*F-fC>aZLHor|;cl#0_$~b0=M)RSh2O%@MNt=1?i79pzk}b
+w&n07V@H_Yy_!syW_!syW_|XSh7WfzVJ^b8l6%W6MpX<dgpWG?@9{v^n6@D(C3iVjHZY<pI6%;)d6g_
+s~<4)n<;OCaJZ196LDqO>r4SsIn`jW9z_;>iZa4S3fJN)R-M5nCf{@8MVY*8s|xjwdBA6qoaHVXd<{|
+WyI|4BGEWF-(D2oI#gbzb2*4-K=8!p~J{iSUE*E)o6+KOLp89xGg(7OqZ9f*;Jc;Ic}BKf%w+tt9v}{
+2BfXKUb_J!=K^jda`8r3;ZZ)F9rSre}SKC)55)7DezbLSzZ<(<fX#TooYc4g%f*=mOWdIEHsf3sdAfJ
+5d%TXQ-2U6dPghQ-qnkT%jt^zMMeIit`Y*%CQO^GV8w%2f@tw;4?J?UToEX!MLb1Ty5i{<501sGLo&2
+clz1W(>MR#(j>W4(9<<R@f{1s3;?dQ~`m|B>+9UJntlVNE?%Ajy>roZT!qZtnvI`(PIl;*rDB4LA3h@
+({plJj1y@B~g#jxvI3p#aB;Njd`IdCM65+PXp1H}CS;{E_}e*nQd_~;4$3I7Q{cdhA!A2py!AbThL0s
+a7gfS>DFfGLf_AK>R^HbwX&{1JXGX;Xwh!XM%1zBVQJ6Z{E&u5MF;Kf#~i=N30*_%r+&elB!VhCjof;
+m`0F_zV1n8ZDscxuXL<*{HZZbb}ty00mp<xm8`^U*TWjU*TWj2i3f-@S`qt+u+~e-{9Zi-{9Zi-{3#s
+Jm5UwJm3VaxE*jF!b!>}{3rY;{3rY;{3l3oE^qhVaU0#BU>}{tf&u5MabMtE;9THb;9THb;9TIO#&&9
+Kr^a?_Y^TO{Y78R=VW-A+YHX**c4};=#&&9Kr^a?_Y^TO{YHX**c4};=#&&9Kr^Y~KGz$L?xO@ksF3M
+T=orpugo+Lzt?o{ZGNWp#xo*f=4ai{urs&AL-JNe8>Y5~pwXCSoze}F%T!r1^Tm$U5w7k9{eL|dqn%S
+^pYoQHUAMXP!zr<y)LP}gQ2UzwzL0f%1FwOyb>*XMDcp3mg@q3o@~%=N4(d#?&>RPSW&f~S}3RNXb_g
+u5$FysvDBYeLh94$0;^XP_n&W<pUF@Z_1zqUvjmW^*;F=*CP%H%2w$=q+wu6&$`!aQJFfv(BQWTo?V&
+GIj6_1zma7>TFI;)2rSdKOyqtq%*I2vX$3Eb39cFt%~$t^DNsqhRvIvRp-qq@O_zRctx&n6S=;Pldrs
+m`T9_BlD9Gu_T%0;?{<Re7X{N#)c(FHZe9;c^R8Nsy4GMhBAYjvZQ0bZ%zvM*^QseR+LQh3$&X@J`Uw
+?tA?#C6f5r4&-FaMiUfvWn{b%AGF+Xr}`gMx=ffKpnlVgKm1VJlSHoVyD5M=9Rc!MCeLqT2-NdT;Z95
+sSW#qb5MN6!}{JL@PGS|VAFs91>c!ioYZO=61zIp`>O{zzV<z@npkjJ%3&i}nD~DM;;v&W9xBNAk_^8
+!3V-{Xx9c0>6)q3NVz-T@qP%eh*ESGG#uHrA{)1%3wFz<A4felR{+*l_dk23}mt7k~ygn(3C-axXEIs
+BqLv4<pZqhjOc7fw^M%rc?4l+*kYJPBG_Y?6|qEvNTp#ZWU&p@=q?^mkb+V(tly2`=!}3VIr2238y{H
+%%beS&fcDt8iK6TF=ovU2iJfedPIrn2G@Xckp5*pigpEvdN!}lQ*&Bdq2J#%hXNC>lK+eN<sqpVhXH2
+))h#WK4SQ-_b{D>_Js>Xt<v5`$mM1VJP3TH8pVnHU`h*W1R7c4J9`_em#pl3t|HaYNz$%&SK@$h+o!8
+QqV66SuyvKX|@FGf_PJAs6;YB-Rd6BJ{602zybtB!uo5KfHev<Du<%+7d0xj=l0CU)!vH7dH(1w$qBc
+R=796*&vm9|7^Xz%P2(aTna8(>#C#3l*6$#2?!O`HUh8&<i@zi{P!mWA(a{-$|o4oW_iwQFEwk-c_48
+1NRxIH~T|}b=L~27xI2y-RpgQyt%|zC9+X(y6u>vt($5$o!)i2d8zI6QroFES~qVNT~Sr6W?qDwc@aL
+fsSfo?cJWi2s@^6q^L~5rdgHE|)|zwPo{y{SWt*QI&>rjO-Md%tgr9muz1Mqo1zgO<kM-IDDjC;YaYm
+0i>gQhKT2;%JU84q0ZK&%ItZT0E_NKUx=5*?cGcc)3-w7I~%b2cSa=7B?2fLzqn$xOlL?5%s4{dVAB-
+x;dg`nCDZCEw>R0XFB3P_sA6jTwaRz=^Bi7OvBH`c0*ROOVKQ#sF(+cGs4_mcozTh*(?t&SVHY*lw$w
+nKMZbLr}=RY6}QlxvaT<p|oN?;x-%G+FF(uz52@>~}EAHxU!vBndU)CbCA0XjtLLqCL>AA?MdC0REL9
+>Q#QISAMA1<i&$R4h~EOTH787PRXx6V$JO*328ed?%P8w;PC^waV)w4R&9?1DpFLaBmr-3c2OL|F3Ie
+2&$4scyO+zz+XC&c99CqZP$zO&vFL{Oki)Iw*`cR+ct?bU4wOC};4;mDJjhW*{)t1@6LF7ok;Ru7eq%
+XsdXch{AeIB?ChIX2+?<D)gyTi2#*<aa$-(kjgcltxpmf`!OzfQT-M|-vd=ac}qhel-&j+b&egRBCua
+#g}+e17UNRz9vz|~kFFG2DWXvH8aq`(R(kg*^c3uG*acpK&{+LSLw(^#6Ze2J1hev%s%X(a56NlnB}<
+d9^U$1;&`ptP(}7HP5`N-VgNEVvRy6jM9xA>u)@Vk3Du2x<=&epECECFo%9Ydn}zk_8{HOQ{m25?TND
+V5KI;wKB!ZQlLzMG9S+Jt-Q$^58)rV$jRIX0FpOoVliM6`U625X)ca>4XQ&Lm3ZWlN)!`aWW0zO#3IJ
+9tcbwSoh$m#P_fY{AtIAlxp@%{8tvhsn|NRrn}w*;XjDXO_*fMwRwt@)IOH~qtS8arVU|-oB6V}I6&9
+ajlZ*35BX+jTCc-s{k(gbUoep}*+we7HV+`6?K#=uEUyq8Qq}@5c-z6KIuGoDQ59(+3T|DTD*`pY`La
+JtuvS3B=3OMgZDZrjZ@T5l^M(kLjo#&989pvml+si33ASagtC-#flgEcVc|EJUm`?I#T-DQa@>s^94x
+ero5$Q-uCt${k|Dy!baa#xnXyLc*dIiCkQZ$+fvvdOX-DYTeA=nq!6><6$IW1}c5iquOKc^AwMww16f
+bx~|1a(nG@LggJ)+eD7GqnrXqG{?ju5mlDTEQLjyIUyC3Br}Q5l0?G_$Bd22BANqq8FTG%KvBBH>3EV
+;=7icAkwURqJXIv5#UzzTp%{)R4N5!=(%a5dIjO`d6GAf%89OHi^;{O)OB_14M@By7#B<6yBBCJJqG}
+Jsq7iuvm}3iDm0!*(f*;6rAe(R?P$EAn?Lknw7Wv49h-||lFJj=R?VVW4qe|oSBBFt+3z1H04<tFF><
+EMzH4yxE1T25HJ%ET-a0D3^5zXKvQp8{bVz6yPut1TsKwJdr)gaQV0jryhipiyjG)R=KLS(Cukm)GMv
+vjmu-#s8~QDhH+jin;e5nZ%EWOFLou4-}OQS%hG4wSnqiniaU{h3{@eHb;46O1CT%|u|U<({BgPP@$T
+aOoM9QQ)Of1?k;Zs79BOP@YzH@<cYP(rlw>yte&OBO3Z0Yjgu+R7W|Ig=70OfzP_cHE|lzhzdiV7)-1
+Ctf}U^qk`3?xLd0bTRW5scf_hjYd-8Wq+oR&ZxwNFt(yICZX%M^EQQnWIMor+oN8J_m(Z$Wylt)~Zn~
+&}ido3TOq&;Tqog|r70YP5BmLsCY4kK>(iJ?6Ez`6sp&K@@QXS1X0m-8+{HlAR*;HOPt*VT?xuzux-G
+KUOI7O9>w2hJmuDX9+RYS8~)jIP!(_A&pHBZhwIJZSJw<)A}TV}K-v}wg{LBY^L8Ruqk)4XkJT4T4`w
+e|teY&#Dv&py<UH`hJ`6&5}F&Y_)S8dhpfMMLXAw?R!ngjvXNv!lC#Rgbm`1HjpSVP`^W-DKJvvSENQ
+#W3XM)D2oVr#+2xn!%X3>LFkw#vg|>t81FUn7Hboo6KoLB1J`D&+gHM(}!!Ffr_SHv}}2qfzx6}n$cN
+Z+5}mT2(ngJp4K|DTI<NCGV1=gOp_%2CL34Vu1^TG21c!|EiSspRbhv%4m%q$sfneS&bjfOmJEiKj<(
+y?dj&lgYOc9OK8DU3JN3(0H6h@1%s1yarJq`;a~S!|vv=h%CYKzBpjYm;t1s6%8TA$?C^$BUag-r?or
+iN%*P(&KvQ~2`V%ChKj^<ispjX#61IHD@p;tf6IX-l%VUgw>7Txu?rF7N0kKTFbSGgYom?x;i5fuxl8
+8forX^-yN<qUo2^#9yM*$2l3XAuvoPlCiCE!uxrW!K2IP-3vJXymNXU|+HA*kpf4Op=&HOqLk*-Iy#f
+ST<}+KC*+(NmE3j3mOrP=pt+nb|WH_Zct?@3U%6}dv?+Ex3jiAM42H+1@;tMtK6p8Qx>u($`*sHq=Ou
+^NNR!9qDY%Zwm?yq?P$R0(iSXh$w3mfBwF7@aCJkq+986<M`n#DlDVhBBQdAM$QtxS>rNoG_UN7{F|l
+HIk@D0!?kdeR$br6EapftpHLdKJ`3q~*u8+~N-kgKe&R>74Q=gr3TpfifE;nCy`uY@nY)%cFuX}xco1
+B|+Zc_+m8)~EMJ}2v4OEe`4n^ULtnP$>7^9;;0aNZK<QFYrC?`zHx81?lnj@R?9X3X+5(QztgbDn(+e
+l7=bR`dvUVUUh_*#r{<IE5LnKMo}B<=#OA>w6DcScmopdl@;)SAzvzH~MI6JJv{M87Ig_&4zWg(7F`Q
+*VO0c{kQX5>G{2sE%l$TH|>Y(P3!A#`l{v)7jCDh&^krejcD14Xla&i+8+J%M^t0AhbT;u%Q4{LSx&9
+ckky7VM?RHp=CZNnUf3q@Vz?M3RBeoQ><U^v8pRN=>EH%uL??nl^Cd!q{Q<OyATQO7%4dfnxb|SPxr;
+{4U9@8MQ^mz1lD(jQeQ^xo1<l`!1B|s`dVFyl0WO#uUyu;&57?r_u(vuyqJIk4+G&Z=jth&fHGVeU5Y
+n`|gfaRH*tS&Dps4EYTc%9xqT-x~8htZrSi&4CDPj(_W_W}t@2e(1k7-s_<=@PySb^qL)04W`MJ?3jn
+nJH?8p51eWv<o8nVI5OoN-<*m7g+UoSK_3jW+79a{KL>wkdTm#98*JWuK<1Ow_VR#a@`GWlw7S!>AcE
+GgTfM6|FH<m(Z;fk4@%0@^8+u2{Ecwu<NQBGpM$vwPT6ZCN^D1?rIV3Q1yjYrKUx*$mQJB_|~d+w&D=
+f+@=W7R>pET&&#pwhQ-ph^whvb4c8oL8W$R^S(4foDQRpznk&yh<&2Ya+_2QS1#ZqRY4ahNh)?=JMsL
+2uincQ=8W6Yut>AGhGF$zDHiM<FaXw^?^Ym$-M^*soE1*#ixR_%cX9U2Ac07klZU<VpZC;rY(46gx*z
+UIII>Ao2>CmS3X)8H!SXVwUsJvi3xl15@$YssDPoMtwzcQ6YXg~eh01Nh`gFatzc>~aJ>A(Js_Kz+da
+OTiq>d;~8&|&J(VcKRX3tgZ+_Z)b-z2D?IRyd9F7SO#Ni{vL@#}lyQ3E1%j?1=8SMtdGm{nn_1!VlQ-
+1nkI?q|u)8*(XPbl5&TVa)**~SLC<J2t_ZU;pEM57}sxg7HYgve$p(Q7EUYI>KLrfXw(42T>)HI0N0g
+c^$Os+7UA)<2d1+DTvwph73g#YI$eQIx29pSgx(Dhv$bxhCEU8A$q(!G8yD#n{E~oV<tNsm@ZF*C-GM
+@PD0z3NZg1u8IGzumT{;ORi31v?m(l8$BTW=VgK&2s+#Rap9jJB(R=uTXdV2k5_b30ulb`<V$)kVw-u
+qAfrw^X|&;Q$#|NUwI_a@l(x3~Om{b#s4kT2oKb&<O~R1LKUw|EC?^SOXo5qem;Az9Jc*dAQSp?0M`x
+XMGNO?&j~hz<Sxn-#T(DCpldxv;}n!^S;`sE%q6?(neCZuqq}^2>)M<$mABs$r8=14bZDt_tZ^26Zzg
+RMGgx{R+8bgtt9_s37Ccu8PjXiflu*a{s|yiR=+7*{WGCJ^*<e(ePzh?;G@;FQUC_0YbkC90j#NZGPk
+|noCKGF{1w9dO=RP_bi@6JSeG>lY5i|Sy2*XQ4(ZN(RFpA9UU`7{lU?{2uB1U@<Gn&gB;C^zNpAOLPW
+18_B;F0J9$e$!v)@K6Bh{rfU;=NwxT0j)Fe4Zoik3RK8CCjBsO3pCtxGTMUNBRPVGSgoLakXO}JBnRy
+l|lE#}A_wFg+@Dqw3?RhcE4oDw^%Cp5Z==YTTNigtB`HyS;}!?>`-+bdplp~@5uF1$zqiVQ2!zmBN`h
+p7XH$+-Ry-Bq%N?xT6>Drvfks(zmD$#P&J*p~Z1Z#E-W1Sro2CA*3KrcLxW$=$)R<H1%(I8cpxh_=)N
+9nMGP2p`Z;dvG6s@@lye4%`K|)r`bv&frCNYJe?BOpqAa_XRE&VnH{M?Ea{^N|jZFR@ywc$`2zEAP6g
+>Csnr76{(X(y?Ayg3Xd@2P?0HVG)Pcn4i!+Yk>9#iJg5%pUA$405*bnS%9TL1qEpE7z9>|xj)`{>4Mr
+A9F6uUy#&ZiZ4#nHlscL*w%g?&$DphTNpQ`TXoL2x-^^T%KOwhI8Jm4~6;5E9!O<fRbLh+n|s@J8eML
+|<_GifF`NHraG%i<as6=|jFY1;BfPwprB$9g^ESD9~XcU?NB39Cwqx*GN=tySF^HqQ%$d0s!yH=Uj)I
+z`0ziDpuj;cXKi)iqx6!~UdQr{0w{k8{Os;-@w(&NkIXY<k4M&*RN~nMfZ!&YcIH!O!E|n={^|F0IxO
+bfG-+k@TE&szI>b)`GZ-TA)Xc2bc58>HMz8qiWJ_3!^`7VJI)!qAF3^;wZ)zRqaDLHM*Rtm|>nZ9(qn
+14%L*sjxRQ6{YhIbU>)x9)2AQ*7gn1AiWbOI79?z#txWAJ>rd7<n1xuFix*Zl-8y++Z5~irizaAc&1s
++x>RErX3N5k<<*mY7SXkJxumIYz(G|KwSx;h`;v^3zrYTNLQ=DwVPfSysn5H<htU_6}R#_#nhC<Q^DL
+#i3pJOrD=6E?eK@Fi{0dM#Tu(G80Q1ljBI4zv$eaj1%nW)gms7}SGPUT0YvNfm})u}}|(fNi^or*b~%
+28!yl~Ri=HVsk@yo=aYt)d%y>)5Q1*zf$0ZB5tDSWvmTB2kR~!nTSkvY6rsR<Oip72Hr{wFEAQwU*fV
+*;%NIIHoh#@xy^eIer2*7Q=o0S;Y)WdoU3fnbgNEY1^drwdhCxBwMQg`~PXVJKA4uD^B13kfKJroI!)
+Bae|C-z@D9`T6dV6a$vihsNi;0)~gr|L!V)LU^WK)Lycm62J<;JW$_@>mc@hln_9$!ZJR2Fo@%9;QMA
+4okxG#x*4>I!k9eFId*D)iM`9?_ERl=y8WYvQCZn>+XpMdCQ5QWAY0kdm{0KGm|Neh@^1uFn|E*O{Y8
+BJg=WXhHb4g`yG^HTn7;2{PRoddoF%W~CU$IL##KXo6RS=FJg8o3J&Lfy7>f%vb(5Q&kG0ss@;IIhTD
+DroRn%N{$cGyqBf}g{JpR*j_IU2+*vNl|L<v5Pr+(J#d1!FD?dVC!=;@pZ&mlfMBD{G$i=&5Y7Qx)Z+
+dy+|l1>|0sE2_l6Ea%@23`862tRoRoaH34y(Zw4j|KQM^7{+j*&YZ{{I7AI<bPT+WrHw2qkdSSCT^1l
+oRwFbkyTdBG!!GmI=qbH_TnKGRWlFM|YN%>9L2XX&i@L^dWZu<|!>;lsdzeSXs#8Um9?jV|k{=D__FM
+Zq+h1w@Nu=umVG62iMZA6!{nV^g+cu1#BKJ9PZQu%bI^c;cd1S8@W#bnSGLJ+g(NWDdE2CmVmV1WfUf
+W*@U1iG!q|C}$EgQm$ijj(nk&4mIDgqysd7%o<5OpezUNO8Vk{A_HTyqMd40SAv+`25M+|(G(eThHW1
+I5kC?g&T}>v0?Dw4&A7Vdd1JS*|}A4M^TP?3_B(t~4r!n%Es#*=b<8)M2^QVY$>{xzwRr#aTHdLWhb&
+KT4xw`pJvwCpmByu0uwwoakd=Npy>}2W)7}b!Zi7)Qg7?hh03R8LA9mJOYeDCx}BQNTc!rY#9l}w>@^
+K3|cEA+{p;%2j9uq#)#B{Kwum1ECRsSIm|=0;m$jrA6YN6k*CyN3W8NZx5`IXL|9kRGt7}gqfTaro}E
+qD*kU_DC_C)-xE+<`ZpS)?Y^2>G17184i(8_Sxji;0xd#2#C@qOr`$owDQbkUrid?KB<|@{<Sf&)YFe
+o%kk;x7NX|BpgD+Z>j%vs1qx7wBE1GfXlvYT|QE5OAqfG8W4BdrC!$Mod|tuu=#nptT7MT}M~m`7dEM
+A#mEf@)0#d<{FHi|ewXizppm+%8uQ5+8|?WE?+#(*DcRE6)qQ&I5@Ho_qw1PKHA?=pLv-KFE7GFzIw)
+(kbkM6YH}<`^9A)Q)JD+YKEWR_Fx9BGPNq=%Pu#!8+tW0FCFZd6~*H1aE{}2tAGV8-d?U@4BgDTM-<d
+tTflwZUg+IP&@It0BHfqaX|BkpJ(5)y-{S|sOzeOe>-ju4r&(21HkV3n+M&#=xh6<KQ3g|2Wwr`4n01
+h?{z%v<_-Tit%siD<W;gEinrmckBCYZ=a4~u6Y0G-slEX4L76V(7!<0M-yJ8>|vX@nHVGa|O5e{804r
+z}%Yp$As6RKvJf#+CGnJ@!~ZpZd>t=7to8W}ff2C9*9lV{*)qH0y6Yqi60Q=Mw@s?~hjGL6HJlZNW%>
+u&7Ws`E2&+)h=u&cM|U*ER#kkw%>jQ<ouDTIXeJ?T4tBtIWW$6scRCf#Y7iPQ{gVA2`6eA2TqIe9j(F
+kD<!B9<!LoKnm4kmgpE~8FlLPt;eC9=L{SWoI2%On^Wz`&kvnrOJC1fpZx%MxTYQXq20B)g1V-S`=Cb
+b<4kCXKh=5b*qq9lXW$qIb>8oHRp4y__M7X1zV(Nrd%sj~zrOzsJMFu+F6#>tR1t`R%Kl)J&99W<Hn>
+H!SKd6!pQIPhUq5^PRk`ptfAi!wpJ1RJ6GrQGh#$VLS#DTu|Bj}wE(xE@0@fxTwj%fJMGw_hvi<s|Qm
+cD<tS$r3EaQfq<r~={f5?4<nB%=s3UnFYy0y^zeFTmEfFY-QB1o52Cjm8GhMb1&Ch^>pM7k9|x^Kd%2
+VKHPm+_{{Y?H*?SPZ*FkS-HWB3m>}I3Zi~?Myg5D1s!CME4+ABK&d5eE(23oWyR^C7$$<=s1@)h+{u&
+<cZu|=&&0jPhS&kLZs-=X!l8EriN7ex00E9z*N+QYr8K%#g~6zyHQl+*95WdN!&kRSc+tB!FEBEzNv`
+Tlcy@4{{vf|5}Q+(tk*-*{+Ik09ufL~&`uRe--8HVMyur0e+k=FmvVwXppSqO&=jJT;6AKT2LE@pdWA
+<c8GK8*w+C%xAq001SSd1LmtKTF-EP(;M<*&3<U99ODu`jN8<h%Qv$92+w`k9=ncNZtnCM^lqxQEh*}
+R7|GYGisvc`pihGC71r0+pY@0;ej)#LEJ?Q~tzfkO|(ln%VF4dNEudQUZk+W8XkK~lcN2k&8E{}Oh-?
+nx|u)54e7DZ3S7yoc0%$O70sA;%je??V!gm(Gj_tc6{&koUwN-zxEVSrZe8@MT8~iNv>RE)*Fwi$NnR
+rZxXnTMN6Dyi|N;KW4vYN9>-y#zmy{77W9GFAHM>=-Lbau!S+iJ%@!cJj22m5}a?hFm_KW^fEVgNqz3
+nBtc*}?%}}i$%Ed4!iR~ndsfN*m<h5WJ$g?y3Z4sM{#}fdDH0tGD#KD4Ql`UF*(G0!XNZyF`6ggpY|}
+m{U@B(K?g82#5+@b?Czn|>5&FCbb-!$!VfI#jdn`Kj{(!2_2c<?u1XR9rPad?=lfR}Z5w;4R=4;9kB?
+g@{4{Ayzn%s)?w5=$etgMNL=5L0bm`-XB;*-RSPH-terL)y6F_%I`iMbRiN&?8e)+%gVV15(Y_;!=Pe
+@qhgzNSVwceWf0U&<Nf)ccPpX9PrJ1w^Cz81Z;wJcr){sE!W7dpa8BS|+WR!bUs=wSyq39C~z|w6Dt?
+u4fL{Gio948@Jm8K13b;s3z{dCPOUN>%IoUuiv!8d?E7FH|^q0x#MZ5xqj1D-etA9{<%!%ea%W<#~rQ
+1N*=lrFDrRs7*A}(JtQYhlU$<F_f1A~w=ir*A6R@F_Uy%4o@hwAZy--RB0PO77^9NZ->{Z<Nm5@1@<g
+4|eFJ&oL3h&0Vr+=iT-NgL*~Gi#ro|)rlx~G>hE2R-1`p4DqjsWqN!TupOCoJ8qSJq}Z96GxT;-NpEN
+gGbV~c_p)!ZbW{Pezv&<|h_Phu!SmAzwo>`?9i{v0;)62OThx47ThU>^6sZxKrWL)h`M1LD{LaqNINx
+b`T!nBW8Mu?s#<Z0}9Et9$AyfuVyMkRXuA!%*M9HFJCqiW=QW{eNp~eK-06{;1tP6<@kF(Wilbnu)%L
+M56BL9@R7-6tjC!A*ok8RmQ8J&iYrgf95Y`_D`Xn-(J<k_c06jN0d_hfK~$)vHD|K4SYz)uBhI;oZ7D
+U><f;}KO~L%U5pOisOA`fw+cBP6l=ZF(xJK?9<)UGumJ3hmX4`=<3XudKOwqP$>FW}!U^V`IuK{{v{d
++zmX3Qex8K8(;X|rBel(kgst)8qA>n&ELR1&yU)cKLjVj0Qqx5l_OjPxcx5g9o<KJG@$&H!CX;JY(@#
+?AI<i_CQ1GW_(l*7I?xOk(>WU7a}QCo6jg;CXw+*o0pdP$}g#s{UmZ%i|)Vv>hNzaO&Kc&oxh6_Y$HB
+z|MrQI%@kDhOA}@q6YTNA$zmNM`hdrX5ws$e(K3@j<;L)5_yRqV5lxete7G5}k5xw2^#2Baz=nZ;5Iv
+c~Ch2``MVB8awCfHyTiG)OhOa4`>0nZ<z8b+gl7%-V>l7t{=@><wM#E9yDS3uu_*ByOyfdWv(Eaa~ZA
+&G$4Ej3z)aM_lFqHTg_r>;E=YyuV+SIFO#!eP5iILmgd`(<lJb7Ran?P?Xc?l;Wg*nnnGALa4Nn3bK5
+#l>kC5{adT<WRqs}FY3e_m)dQ>f_;Xl2Pz?ZWs!|ID4;mv#lXI;1nrj+3PzwcHofZnTZ2K(RjoE@_26
+{DHprh>8mccZdu#eu`Tw0<V0|&EH?E`MrTz&>BYW@KwDgOp_G(BV)_hH3NHwGcbitcMlV=mWU4eS2Zu
+&&V_{Nozd#r1$fu?}r~^*X$KeVNAn8mRGy0yK(>pl=OmeEJ7%b^cLU<99(az8#i$ArXNP4kRMTlT9EC
+3QO!%B;__tMap%#*}#Wv^&xN~6yV5CHU~rz6vqH6@*={RW)~$*x2VN|SL_#rjS_^t#{;O6A{g;}I|Sn
+?3K>oy8|NbG(SaNaZ0Xzp1`YrtF+UW5k&j&{#fR{T0!bw2xA??ACm8VoWTB|X3iRV28cg^AR*=L*G1m
+_a1r$8rL*PD;d>5YYF977rqF7#_Xx|Zz_w;Q5JM_yRqLSoK2Ga>v?jAgj^zS3${ul@jh#0qGUx&ScHy
+f}wP;2**Zr>N&rr<OK1$#CiYQ+B~P-*0a`QYuKv<IMPlJAG$Wb(67#a_|{7jvQpADuB5Xbh`HMi5>GS
+c$>7kr6fT2D7Y2kV>ej>-RKxP|c3or~iIHXMa&>S+8$}mf;!DGCXgGmR)GFcn?kX^lkVsJbw%&CJpwT
+uwV-RLOalae_=aI>|HTcSY~M}vXKMVC5FHvf+{jg+OFBIt1G?iVqxm)!gV=7UKf-L1xZOd(|5ylAw%6
+B2`Y+-#DYLw#nTHiKwiV_bNBq41bMv;(e<wcu~kI9lbGH8?(i)UuKiKrTW>*Zo!<qq^)DZ!1>kC<7kn
+MDRc=69Cy1>eF?{DcBDRbezz{Qc29TDyVo+~|Y<V~^p8GXm7fByjwKxP1^#GRZ0E%@QF@5LO8(<fva=
+!-by3FM{0e0OWy0CX8@<##f)Zwg><~^(zCVds_1&9l^Z0!*rz<NPN0apOm6)}$y#oz|!YC{ye91#$hn
+Ctrk=&*2$4)Z?}I?VmqF<?-@QUAh_VBZ<lbq~n(5QOVQ44xtN-wB@U+oQO?Cw6OqQhq$_)?Z;-{|aDQ
+!==LG-w%fM1LCa4i1?R|vl_MZ9UxVz3(uHoxk%AM=9qzMyYoTxl%21ua*U2u8LnF(lv+Ew0YcrFfYs=
+!Pw)mE^?lG!iVOMiFi&~l5B}0friVaDH&7(CFM9(pQlOikkf$5e(G9Ff`-ImkzX!2Kx3Hq2>*GFxNKF
+^rAc)jt>kWeF1}qd50`w3r=oalW4Hn&?eN+?XJ+zOyZmbYFb*bedtxUAGUd{&*K*tY-08;C>H?W_F5I
+)}%w=>er3SRu4z#C0nfi?FqG*@N*i^R}81edu*#<;07Xa-JX%%2AYGh7N;`Zt1n`76vsoPULx{D3f%h
+XEM(uoe?Rp@DyeRs0oJ@uR{j9=-EU3a`6HsgEE1B0YNV?$IwQ^f~ke^i`+7{2clPl<;4^hJMxQ-}CO@
+7bx%kDnoheSMYxb&xeG62<L}<>%(VI;o(~!!THfYLHXiG#QuiVe)A>t)uZ3O^UhE2{?GEfybP~PzN;@
+^d~x^H^Jh7{4tLhRZ{9cWypv14OE12N&z_gZ|1P}z^wql`ymQz7y)3W4dinhB(WCeO^NVNCAAkD!ix@
+tC_4wV7TXp>QuD*DA*Bp1xp5O7#JCacN{PXfAl`mi4OX_*~-BpME@$m=0CA25em_`!9dc*$y%kssGe=
+d((<h$Q3M^^$PQ=fbmp6AcYCojKx{_1i1EWG^W^JlMKzx%=6-B0hnd>KCdB7AW7{6(vTe=aZiQ2eSJ8
+~J!<Gxb#U&6(3@_3rcX{Be5s?&m+hvorjP>*=&l_vgn?>~BA|zwLbKvzL!wyv*&bC-&X@?_3}6%q;_t
+$9v|t@7<+$?{SvTUzG>neLsBpWqF<-KTiFf`O-IEcndSl^4?wSMQ$wj3LAR<<NaiQ|EzqT@4_GWkZ?T
+u*{df%d-dq<XLpZ#^1X3dil2P)JbY0;`J^ZO=#x*r2+y8>^2wvOH_fvzzI^fWb??OKMJ~M~ze9Ly@AB
+!3m(NP?W&h=of}UDZAGg|jbgSTvu>UIW{qEW8&+cBdN_hOqC-qtDB%i!@SDv@DpFRKd=a0U6U7s9}-n
+|R2?&_DbP(7jYyaTH0m#vqE{P<l-?X%`CFMB^1j*maM9Pig>t(w~ea`*E`?~Z=;;`Ke=d#pdX9hN_Nw
++)%u8C$`7<Gc*dKP`{V8)U4^O;75o%6lj4jI#suvGMcUihKX6v)@0y>07Nyq;K{HF>i8PP2O+JpWgk)
+kpAiJ^^3dk&o7?kE03+V?p}ZP?A48zntlCQY3*22>GgT{*|SeS`&weJzIyrc#iuPJ@Aa?6THm|--Dl<
+bU4GGD2yM)N`SSgH?<7%l{^;)C-=&*QH#6R<rqzneJ;gOb6I4RVyI(KR-@Z!W%hEpeX?b(^MR^_iNPq
+P$zB)VI`>)FD)?(qS&tE@oq3^X0_U;&5H?{lIyZ`I&{=+99{o~*K!#^@Hbl)%j)35&V?|${`zipFXxq
+J0xNzcOPx83=xSAFJg?fyl0ojz-|a+BJ#+&av&`mDTs)r<Y%?_YoR;`!b3{%v!n_n*C*e2>3Y`uU-cZ
+wAe8AIN)4>hYsM1-$#6lGI^$o9bH!-=p6>`W7Rwjl18yeD=CLmJxTQN6h>gc-3Z#k{{3fd@ZB@98e>9
+{hZwYm6&DdKQ8aypM3S}ZBA<`{46|u{`5IB8*SgxefK6u*H7O!b90Yl{My~L!XIGJI(_$>Rr2Wi;Ll!
+;Y+XNw-{gGj;^1emv`Duz#ufcZn~h&Rd-43ecOObsCboCq`Tqe>O9KQH00008031s8R`xd5Vsi}u0QM
+&U02}}S0B~t=FJE?LZe(wAFK~HhZDnqBb1!vtX>2ZVdCeMYcN)j_JHKKg$K72S79^)>N-XKvdc-<aBp
++K&+DbAE%K#fKJ9uVRh}P|I@4a_sUx0`l=j4>+m}MUK{a$TtZ8aEtW{dGuq(+CCi4$7+Z}rolrT4HGn
+*|$XX=GxV>d>xtBRN~Bcswy(c9=i1-A?D*)^2C_IU6jPnF#jA;b2DaX_ILo*vt2quP@%d3oV!=jzp?O
+m%Vy-WcSZb50B5^9kY>CY$yzm6TrCzG&kbuOe({aXpEGcvRE>=aw+c3>BY~A&t^h38Vx-IntL;DCOsw
+C9^42cIi1Cc@RfJfzP@HRUeFlI$Sh`}mq>Y=&DNasJfiW%S4S6zm;ZQke664Pw8E}<>t8Qh|Lonkhfe
+FSH`{j0Kj<<zNYCsElQWbWPgtC?*Oxz@{dofbxMp{^u0CwtY;Oez_GjSkeAvI)-fsX|O{DYa;_~I$8T
+*9KKfXV^JUu%-Kej)AI)3}=;@xr3Fnqj*uNQv!>>%*3b+~;H9PGotFWRuO?=>x=r4QUa{o(xL?eXEuc
+Mic?+(F}hn)HSuO4i`K*4r<x58wcCagE3bZ~*Fx60S8n#DCAFIgwd9^nc<>CXSVoD(DhbU;%G=ti_PU
+BPLV9<cKWHYOl0UHjIa<XV@rChm5l+H_;?c$BdAKWJeC+1*wK`_{aB=pr0i+`o5gRnu&aq&Eq6t1HqJ
+~1dN=+g4HpbDH#c^5m`x1JR&$qDH<CCqrOAda`L$vXXqge@TAhPNGc^F6Bbl7hGN9V!t|nv1YhX^GT$
+Q9O~jn?sc0e@axR8V@R$+L60>&>B5DFeHI29ydnY{6Vu`m?OTn#Ju)YJ-XXIJ9JdBA0t`<3IV8OVd#m
+7vfksug-hq&LgGGRPr0woHx!C^JWH6=`@QWjUZ!f$O9%4*NaPlv#zUvT6Yv9=E?&spgfHd@@b4<Qnw{
+NjS!c9c6h%iEURsttH#a};-+MxSan&9p&{JBxd&J@$01m)K89KiIby{vzYlpYoXx#1u*j;M1^<MRKu(
+HcCwoq)Z;rb5*^|>P$@*oA^#7izX-vlm`FzH_8^YHpnobA_<WJi#C#Ay#fjZsFF-I1TPTzl4cRCqYH=
+`+yl#nTU<LPnkZ_ihC%@(#v}BbRe+_DL425U@Y5ttOIOh0dee-xO<NXiZjKc@&6({pgz2mnJY7aHM>6
+NJnLtQzwAf%*SZ%*z3Vos=Ca2^B#MWeeCp4tPX%1sisv)xtT~b6j0f+H0H$GxllS%damnsu|pbdg!zr
+WK5;rIIsq3wflo9WQ{RbQsKfgFOWa}eal1&ofpno9dU$~S>|xIY^8`vl9U7zo6o`?P>!NVv{Wf-mvNS
+R?lwLV=%aA1ybi_*l)raYZESFUF}^y@$};iJ-hq4!sHizJrb4eVSU;P#Auy>VEz`%iz4X!Lz-ccBjce
+U+q+aUO-)K5;!<#+6G}mTwwl&`=xvfcMd9C)ngbMx9{y>3;~Szg$VImrrxTc(6Tmz>fqf};=e>SfdZm
+eVUdYBVAW{5L88{F|6fE}#!)b;&kCb2HS1#L?)Ixu*ab-dCKSXTLq2I)hPVfj19!$kg}=dzj9RQH0Kn
+Cao~jRa31&-j{}Ll#$ZWGlDBX=AHdGk1%zlA=TL#LC?u(4-4`-n;rzF;&XHTD3WtG_rvrbNkwJ7XoFd
+uQl=9Ab6J>!v}Kws8Ym6Vkz$VpI}G9;NGfDAb^*(?EK?V%!tp%K%;dM*Ho{f0yUw^l;2r4V*P;=`{*z
+2%!e($Tbp2CFb|7Y_!X7oUCyXCTy%w<2O@IV3^9X_eZWfO@dx@#Wwb$E8bbun_ioaI)81;oh~QQ2u~o
+u5RcDvP8ub)?MY@5E0G%z)BnsXul#(K!$7iscwxMfFEKb4Nce<+hWgZM}y*MUHbSLfYser3tP_>zyL7
+_69>TwW6Ezuk3(a;(A<EsMwK?t-bNSTCXSea?w;AB;K_Mw1@6O*!vy6~BDvF#E&?&)!OISh@bO25+gk
+J`y6-@;BYUi5)P}F3LtK^?5!(qnRq3KC)!nb2TqVGsnS#)ELdcC%e(!hif%x;)T@b7gR%w-+WtLb`Y7
+Kc+D!I)d>-lrNJwYu@g_+2qU%i;CQcuKygH_uyQ_~r2?#JTZQK3L1hZ7OqqHHkip;M)JBulsgMzE&Ws
+8k2TcJ>@xZpM{yy|N937Fj+75clAh`AiBw`}_Mgy4I#!`JiZt)Y`3OHoPZawKJ{SgE(!A^bP=m1X3JZ
+c=plXy$-L3!GTw*q$tE51Jpv<4Zr!_VYXB@SZsz`mU)i{+y1@5f@vwECE6B*MQYD-DHkxpFl5W0Uz3(
+iybv@JEm?$yXB#MNH))EK4&@x@IwHypA0*I`#t9me!PW@!UANo#H6{+b*Vk`y4d#y_fP92D>DL>sAUi
+-&shQvJd##ZNy&H9TUaK{d(sO-YJWi#8JPoYC)=a1bcZSlLFO6gX5aw~W&sqYG1QyM?G{VM8nh97xW;
+`=;ihj+LWWluHs&Kpc1lr@gi1o#|TcBCvuK;mQV^?g25&ws;2{m5H!!Sr&+(UH1xDeu4&iAfUudE(ud
+w-90%8)gRmBxZA74F_umyX@khCKBYv~p*8AXFX*t>K};p(?#iIbnq3NKCl*WJ34IXKlXhs+tn|)o%A@
+HDA^~K+QdsZ<r|VYvi=N;O45ebF&=gPm%wn@|k>LxoxwHV-k671pDEs_OC-9O!QMU9ex^c^9h_V2oAo
++l7_A{>%-oXdLWn%gw|Ail1h-zSg`C}OH~oOYE%~G5RKm-P8-Wv!`&#71Yc*7J{)!<q9EMl0x|{5cfk
+RnlLCu;!<ifU+o~AcfO!)$P1u|Fug*>n*;cFF{`vV~yM1(d#Qu(xeFhnuy`w=|yM27V<<*>E3ffqC;g
+CzSEI5GpDN402(G?x%lGtO@aI9oD^LJ_^#j4&*y#^sk&Ud#98?CC*DF<2Yt<%s0s-gIad}$~bZw2-k6
+KX6-W;w!K7>>#ZEP&+fVRb>0(mjOO!*>f2hjYO6zyIUNtnWWWATQ))%LR<Gusjz)BNX?TfSBRqvT#KA
+EMH|fsVx<c%NC9e-X1btRp+|?el1g1aQ&v*E&oj{mYn^O7F4yO$N46$VdZPz7F9uBb$2?Q&Q0Ay@;eV
+Rf|2KLnQvHe^<oB$jkyss9xFd874`#Fg`8z+9Lb>o=Y$j)L55`Xlj?&+q+|FRL$84w;MFPH`IZf0qnl
+ORq8Bc6>Gn#T43XA5-6!k>3r2Czr_gq?quuWy0Ce5f#F$yP-JZ|qp(87lYTO<G>+NXLc^=M&qbgp%b3
+gn`)Pc6ikDzp5JDs3Oi&4id{)u(&pN~dC(HBBm0SoKdF71x1p6#-=_=qo6=Jwr9lk#K=$HbjT_By51P
+Ut#~4BVR;j9)f?+p<SyW|o=4x(QL)LJqhVJqsKbJ@{|Ch6{dv<MMba)bdHccJvwB35xTCCvPRISe~(*
+OL+7ElwVc@z;J1;PjI3RUA>;jEE(ck2Z-!eTsY6iR}kRLBajtexT%2-%Yp#ioYJ-USoeS$Wi_^*!406
+P>8-6W9s~#`BozoAC!Q#L5ItDZ#|#pWuKOM(<(cvc&6XEDnl5$KZSCIB15^i9A~(p{3%puhz{1P+<aD
+W+On~H|6a-?y|EKa!0Cv;N=SV#*M7rk(OM|VquJv}a5%SIw5OaXaQCAH9O0{-BHhq_wFX&Yf1Q*KK3e
+MMEGts6rR3ro6_KAFiROll%wb_Q#kw{s7pvp;IbCFC<oK_+spe!^{Y6mZdd|0gI11W8a*U2XtEQvCh2
+~b}g+4s))HVgy}yi&56OLglc@EWSX1gra*h+-<nf!w#4v(KPVQ$GsBn|NDiGxx_2SlPMi9EgXf%+5o&
+o%Go<1`M$-NjJpwwMa%Q?@6FQI>p#GrPq0sck(fM24xi{LI`|I>Gg;f**30jTlLdvU<QJa9O63&%i{@
+=1i6sCzdUJu_q{E{oKufDwCAYF6#7=$FRnXZh8U32ZL}f`0779ult^e^L<JY2!uRn54tXDBmOz7(wsx
+90GmR!-1arR7Bz#>LPAyH-xXE=8j&UzDqt<s7XU&rg6)bMIn!VrKRAEK5l*d;(3^$vw{M2@cS;rrcWK
+ZBMwva-;>(>Lx8XoEgY7A7-tW1|yS!uE}DnHiEnbrx9)Ue}iARs@o#^`z&KY9>4rg6#>S0duihYS(wU
+iu3R3Onu^?y2eaiaAn|ke|sV(8Lfz1F9wSBjXJJ2z!jlS0TwMAISp&<xssQtGr`aYffuafIz|=#L571
+ld+N&LI5l8tc-nYnyg`}M#|Md;*_1szgL)YUAt}?EHef9ALsE12$O8#7#KXtp`uguZxLm|$ubYC9-7D
+hjUJh2hWBZdNURBJf2Zcxeg%2Kc_i_#m+%6V6OhMMvOp#W*$C4I#QC8pVt!bJb~?Wt-0^2PN-}6kg2w
+*<P)h>@6aWAK2ml;P_Ex#nB$2Kk006?B001Ze003}la4%nWWo~3|axZXsXKiI}baO9eX>4?5a&s?VUu
+kY>bYEXCaCyaDTX)>Jk$(5D;5sL#TN9;M7u#d&P&vor+bAPjjwNTD*p3>_Mt5_}CfmGNl6Pl+R`QUy`
+DI%G$Y!Am1nlgYtdcX9NPMUZstN^w0B+yDeJg^W&CPNx^SYWW(yW$cr62we`MIT^J}>4?CZnXtYmw$@
+zKjee%8KGcvxyc>p44fPSCPo)(OfP>lhqp8);%%x93{o(rc9Ts`Y3wT{TdzY?cMwR!QR1PG`orFm5g4
+toJF-1>)oi5GJ5#>;`_5#=Mz&+mL@W<<Wcn9`D63`^yJZ#7w1o+MNtBM;4%Z6w?Wcd>3UO?byUh*w-#
+lwjyCCLa`{Q-^P-$=RZtfnWFECe&+8II+yxHT>g{gygS@#a%K2{eLagO(^rS3{ayR;MmDaM_hy)(J(|
+lDLcv%;hy1x2mBRw=*6}Cj5>c2e2n>x+9!b@3SW@%Ml78_ts{gvkEk6BS<<}bsSdX}sTP?~xAC=*rnq
+Ntx1O%76>ZB*N7sXX*IS+h*HI$EUp{L(zS?Cj^(Eogc3#yq-A6rr*CBM05>9BF=_T~3YRh|Z9p<yC=6
+^h(xEnMW^*Tt?|4$_t>S*qq#M%{E;`eT5Nl^z`KP;>oLXQ?>djO%?6)w|(jN#w5W+a@~+gR;dacvW$2
+7>J%4>)bTMQ+`mQ?p}t$_PbEXE6x9N)PG&ckssf~y-RPTd3f%@(ub@^B0yLgiwaDvK)N<Z((7KapIB>
+dBMjOyHysr!GL7i>oDd4j7v-*7zT|qT+ZhYvKNGl2Yw`{@Ic*lzVSLy25-?&}#KvC8h@NC>mso%=1LT
+W5EKNdIRQ7gu8%bu%I^xFv2?DZ?Mj5Z(ABNWMHDQal^Vi7^vPDiSmYHM9Lsmwsj$_rZiAvSaQ1r}o}Q
+RQ3qE=#$|AW&RZ8<{|ZjB6DecB4-sYv7+!F6A}EG4s;Av+N5QnyyF1+v7~EXLAu<A4S(KZBSkfjkLFA
+c`fQ>r5M%}CW>u{S>;&MMGS+1l@J%e;{mQg6a8qsv)ld&uf{vrCG`8~KaMp~+Z&AdSj4xwkcPY`TC#-
+3@);)IYS0mof8UdD<%EZw$>}GG8JRQThS+%zjiYTC0{vWGh@}a^WAjgMLEl3smFbSE<rVtDxr}PD)X^
+g`y+qsf6^ZEtD(a$1A~)cCN9OTVRiSE_Mn{o~<jN>pWXJeJ`T{&#)Y{n>nOH8t+eOv$GKr!K@cg#(jZ
+!FHbXBdkB21@m-n^Mkcj1?dv&U!Vx2Gp>o<A|ae)sy>bgD&}PG6i|z|&Tc$t3y&W)8w6E0F{7qoe3xv
+VYi-cu`zI>m|i9hiFsvm8!_z^3(?u{fl;tOBJFnFUOV47Ca8BAJZI@!IIm8x<QVuzH!_Z+Kon?!bbz1
+)&9I4fqq6%UTH`DtHn^ifM(P`N+}~`i;A5IR17W-#7j8=d)TCz9G9bav+-}Mop&=8vPS<sn*3Cx`S>m
+AI3}`6#72&xiXH8<@QX4lV_pmO?-ucXXQx-4i94-2GI=c_B>_W$jA;i)U+{b23vs!9r->o2P*hC?wmT
+~(R5A75q(+m+MG^t}9aZJFT$?&+LmDWhB6?qP@)BIXERrMEIw&H4Ss3kVJU4}QtQzf3$EJa6+s20ToA
+s>7213K5A_u3aRg7Fo_)nTZbf`3<imC=;FL>y?cX3waOP%WqNV2Z}pyWQO#7t(HX%3~!cXlCF=2TqBH
+}DH|>aX)udpbB@DH4=YU#!5>;s5KRs<WG@sUUb}x^2I|cz&vChOE6RAbT&GdehX=)e17*o1)R#Ko=v#
+29$rDf(TOQ4^`2Wi3E-2bE#Tf0Y-D3X{S0VIeGjf5aBY25-Pfx;MJ*Ig(#z-NEK+r5^}!h4aB(_a0od
+cguCf<l(yO#K>&fQv<1V93^=@or##x(C=zQl?6PZ_<LJM(CNO&UPGp;v7*U%zf>*Ei)X(8;A4LrS%pj
+7m@)qF01}w#T?Wb^P1LiVwkidXDHsBL<3!5qh8yXD&?%IIQK^gAZ0B3m%@GWBrOo^f};Jyt=ix5i>Y`
+_OFTfdfs4KOJaMPR_p2CN&0%oZTA0eKKGw*l8_2q101CIm?KSUZ%f!XtD-%)3gLerrvLwbsHVH3krCZ
+Mdltz+EQ8X2k@@0Aj5PFHHc%T7jbgfLLp>mP@~uh_yZo1%U@dt&c-N-~mzV1$Q?BATpeW{NVxdhc_YP
+dqAx9We6aMwVsEJPY^A=4%w0*w)8S&8iLr;%aCaZqSmvJX$WE(nOvA&f8+!l>^~q{Qn>;L^?+{|MCd-
+TaP|*C;eb=%AWVU1=`<w6oXBt*l!2)ARY->U0jJ=X!O;#rz&`c3t{rR;rtmG-l9$5#j$2E^6i6Sp7Mr
+Rb4)+K9)V!4p9E2&5KCYD6Oq9bE?(UJ6eiZ`TC4f~?eDImZK6M}k@TyhNOaN+!RC-es`MkL5q6Y%dep
+=Vg5C}kfQADBHxMZNI1E$a;Foit_0FkLi6p&Ds#GKm(Hg6)d611&c(cxO6nE(Q4?zonSi#8ixzpbUk0
+07l*10=OpH3HGg6G(6mpxN*+W^0MG^y?5{zR$Jf5BD?^2m$7YR0bCfOyMq-Apn>YfEvBQNXwQPM-54$
+cNqlGV4TP_8}3C94)-X9Ab?U>WJTeLONV<TYLr0$$(I({$B(`t&7PouG60|>lvz>p@`$Aan*P+qCIBE
+k(3PAoS-WAt0qNsr>C%Bg05(FAyndU)eMZ57!4!zcEs9cP%r+2!c3JW|t?J4LARd=H5g2fX0+!yaa!-
+)x{atbG)zV!-gnpcgb)i;Fh5&R7^l2`tm9M1*iQemCE;FB&XlASkeDYEtYOR`*3Sa~FS;y`ja2y=mBk
+ka@Z33W?kH;7SAS^9i4Q&BtREDam()F+{eM{$;>XMhY0Ee7{ne%h!eB%CHMuC^N03@qS>4=Q7M5A|J)
+D8>=JfNmAt0W742yp*^0yY5vGd@K@ejE&BRA@uN2Ou6-eRN5I0SgY`QXl{wDRvZWrZ9lc{(N*vfdNFV
+i3oHk2M<{Ec3^PyrWBeG1;HtB45mO^`lE{m7WxjO;J_e%*rTTL(WNI$fw1(Qra&>60&!7jvvry`)u3t
+Y6PCc8H@=Y~Bz-ii%xLvC;J##9azL;QM6He}W>YvMo#MP;?q&n%&=M&40e46{IKmzQkU%D?o3*#4?+~
+>nFaY=Vad${d%a2X!?M3eqpZ;Uv3dh(VXo6K-)u|`J64W#{rA)jOz7;f7CIP^VQ{XL!0STwz2T&P=N)
+lx@=s*Xg9oDHMH?dMU>TxdXwz7NDa1KMVS=y&l@nGH_7v0;NlOAa9up|pWXRwmFYs7(ViN>Xx&;8f{I
+(MIze$&`zS><vmJ;O5i9|1TK7(gd;R^FCAIG`(jWe`9|?752u2GBK>+(iQe=)kW`^$^^eX|aX_)RtO+
+HPeCtbUm&E3^~wUDs%_1y%a}p;?qT_2cq*D&;vOzxCbIFT{t}mQ{bar2L@9hrcs0(=mF1{92iW2n0Mj
+G18fS!<BBSCjQlWwdR)N=$F>7epLQY;1xXX#CXfm2@6-OF@Q)Pt2!*6@K`;fP)-+$#H$EBmB?ScLW)4
+UnS2z(EKqw>`B==1^I2^clk515<IRS#f0Aj5xDax9WzyLaa*oe9G0*G2gCO5uWhy6pE{;W6kjc*J@Gv
+i#$GS7M(0O(>c$eao~&c^_vr9~#Z4R`O}oU&9mrH8`3d!(f+HSO(@;od!B-p=V(%a-<-Kit@%-U2{2L
+&Lqiu1mR0t6G+F>qr<NIiScPdj<9Oy)RCG5+`6KvW3f90Wjx)dR5Af23ZmTfQzMazL0CRuc6ZymO(fH
+Yf&XlwnbnH1R$G|jj^myN$2@C>NDrz=nX6ppT3c<xfTqdnE=R;NE&J|;J^WB%2MVD3V;}JhXdwvS=y7
+dSWBJp{cJwa>OS2X`bI1MEX(2#!+PAGe=CU|W3U_t!h#U<iR&vD5ep(IM41~0VF>Zecu_Q^UzWulg`}
+Tc!e9uA!*P{f2V_|sP>B2_bFVB5VtcVv5yKB5wh=2w3&=tYHh$=m1VipTpsoL%9|HZ#0fjsYQ=zT@I1
+Hh!|0KxRA#MGqVF+#gXF<lOlgHl&snF%E_#_CSNmTsDFk`g!e+WZJx*4B_8KdGq4=b4(|BEnVq|c1c!
+VuDd#4p1T+Ae<zL#Xk;3Tuo~IS*5z{&Eq9P=9$Hgv_Xo{W%Pw{_<lOLJj6k7(xx^FJTCcmVXUHsK1C1
+<StE8;#n9%TR#aysEy6T5ZWU<yKoyqZEO*SP#aqYA#}|;UWFml#?ml^+SpHF2(_^fVF<OcEDWJGwhlv
+ROm<`z6hg*fu`?U9A!KGE-h?4ECVvb=sK2=KHv*ylQiUPZUmS@Qg;0NK!Vu~&pTZF8FIPbb{n|5jCZj
+fl`pZoiLjC1)7()H!p*y)m5V}egf9FmvF@*ZdBX@F%(^1-#kKM^7rb7MYi95N(5b7^a-N_|}P=9&mPA
+)No`pft3<PztW)c8-_$t6xmsKNZvom^tZsFHthCzlvP{pHl1Tw)0Im*?)}5<ys={KB1FVh9!g%$;0f2
+=$kj?&K0fsK5Nlom^rF^_N%f<PtX}ZT)k1a*3(X{^i1*Tw)0Im)Gv(5<{rJ{MnscVhHt@AKl3%hERWb
+<4!Iyg!V6gaVM7;LY4eicXEk?5*1&#lS@p6`pe9nTw)0Im&Bc1A_$$mjOXs;5<{rJxaMsLg!;?Eom^r
+F^_QhPxx^6aFDrL)i6OLqN!`gMhERX`$(>wc2=$i_?&K0fsKI3J<Pt-uzpUNKC5BLc$=%5%hERVg+{q
+<|P=DFDlS>St{mVypa)}|-UrKj!i6PWqDtB^;AZ$*lb|;q@Lj9$2CzlvP{pFK8xx^6aFIVp55<{rJT)
+UG?459vV<4!Iyg!;>8cXEj#)L-=0;^Em*$KK*tZ7%lAjyiT1$9j9Qp9)p7-eBy9P$jqfizx_0sFFX2W
+uZ!TBP<A2vfgFvmxTr;wbeMl7!68#v$3BF4N7LaF~eX84N7aji#c{2$9Wh+gVMFXvvBM>jyFLFn;|Jz
+-o+Hh&f{2bJ@zV@O?TA7DL;l#OKyUe%%(dwE2sPzLM=H7L#QPKUm*y!WW5d9uQ4`!3x*5&Eo%HY7%u1
+svhhXGE9pli@oCUs=ziq*P0%dalFiE?gzia>&x2-3*JR_@K^tSs94~_g!<IQ-1`USpz=+R+2E*1Y)Om
+8AXsJ3r3Q?!vWRi8uc)U-0v0OMa5<Ezx8Y{yPHgP9~PZkBC(K5|LR9FJP-Mnf85rlrHA6r|xdsq+QtD
+@*gnb80hs$_B!&B#H8Eu{rzVRL<_VOgkIz6#31=K4;<vQV?McTzhbY=?Kuw|Hw9rb5H`X^;xt<sI{F-
+i!*hWV2^`I9l?Z-f_RxdqBx-uXnso=Z?llkh}Ej!}xg+LO;rntqtEUgJC<qV|&ZDOUY~@m2CR%FbKjj
+CA#gq#UKdFVXTecPFYwAXK(#>$-<K>y7}9nFoaTRw|{$LGTr|jlMUbwjj?=;ZUJ{_j5@Nl3EZtQI^ea
+pfx9%uGFY?`9IL<wc~m&Ma11$MBfiEzMc~*z4yi&2!d6DG`3_KFDO?c3Rz}P&a$kg@pIgVTgAlrrJT^
+PYJrK5)JTAi!7WviYa9>lh?c{M8hA=96gSdw=wxv8S!w{PEX6nEJA7c;bKEt>SL)gUKtQ3y<KCEQgzm
+#DJWlT{?d`<a)?#k3u0ub80E}JyV<hrN_A`IV%-$Mo>4Bv_md2(GBeC`s33zqZOh12;lgvugv=S(+(u
+xZ<eK?v(#941Mru#rU&!um?HFW;vzmR*>A_Ff1znB0xQ5cZ8?;m`T`_Izl4@AsCD4f=8WHU2PT{EG;6
+nsHU9H2PtKq22367($z}c9X#n8u~8WWH5w%5ur*eO2drNrc~zvczZE+AVBQsC<ufe2@o&C5Y~&SE%n}
+1fgTGGFPAVFttIsu3}KPqoDATxWO_6}+!CQE453QyPX`!)u;T$bDinnww6jS4OE!)p0%CnefLF<^M>f
+0Pec^&06A+vI?_LNuOS8v*xG9<V-7b3%g!+EBm)`?n3qv2B(jW+%i0DrY7%~`^!S-hc3__@q)0|tr4P
+ncICqW1wS>$OTfoCg;uY(Xa<f%S7>0t3`ggFmE*Z~4S#i=t)g)(*?g0Mpb;_eiIVS{1cU6^wOeE!0w)
+bvRLUM16`1Yl$lfUv^^RJdUNWmBPh(PBq%B@lW7K|BvqVbdM@5CSiRo<a~i;xUD=Pc_s*1b!;CUDQzo
+{_d5YMG#kOmRZ=4L-s|4KEJ@<E-X<jox@j5h5Eia^uR9*TTC&>9(a_@&OM0Lu>^i9^yGtB9ZV2_(0<<
+>e&B0;dip_Zjz921m@Mr92*bY5K0BESXVQ=JWEL*Kj~yWf53FeG>*C!1afD&Zf@({)Z<&LggaFyN^J4
+`BVKcpITXVq1n7`Ccm0<|g*sOt8@g^kflQVUOLLg73#&6C<@K9mLD8zF&21D5F=qfZ6WuG^cVF;VK%A
+IsDge?l^PC6LE2Jh%Z1%$-IH)fXjOa)h-%nnu9LWZZ)nfTjt6$br<9;^@-!5*2-^__)#WZL?L+buB_>
+SAXh2s>aQE`nZ3k64J$LJ)SyLR`4=B%2C#WOL4f7s9-<a7=dCF2+7QaAOb^wj=et38g*kW8;@)5g3WH
+ub?046BoR3j4C<J7wX;@`mq*<&_q$CyvvfU^5R~MeG2HtU<jqsoxCteg&n;Rqq7&>3lQw^g?M}V!VqK
+Z_=R|T{=zVXDp{Yv;4>I@1Vh}N!7!|3HnPyCF!%@W?0Xn<4ufyvj(wn;Ill?O;?uOJJ&R$O3OkG;)~7
+M}WMRiK#O@^v%f@KCY)@nu%#_$HTz?*ednC>eWr$Zdo0VhNH-_*pBGg?_Od1TK;`ir13^B%5Mcb1fJX
+F|nt#$T;bDp2A@uAZnoL<R~fQa$=53YWn9|8fxYPRr5sW^;ZKun^ZiK(!UC$E!Ctl0`2rb5HT$3|9)G
+Xla?Xj7^aE&N>)n;SQ0T6k@YM#~%5Ndz{8Mi_Obg^w|QutnURYB3bY_|X=zIoHA`3)_z@)*^F^t5J4w
+NR_+}d^~xu&sKS|;<L>8)HO~=saakHm!8=$;i`1b5#T8THr-K|P2wHDuun8a($v0a2}-7rG@tVi&M<@
+@k}yvpQda5UWEZqP6+e;lG~@jkW{g5sO}-Rmv(7~09471?%xN5}inZ^EjJ>@>_Ayv4uQJEM8fb=uZTu
+`YP9H;#%)jf)3Lf`u2(_^l=-5l;kagmJs~XpyA!L?peIFn$TgDLTFMpdAnRmqZ?OjG?=Hv`fnbX$)n+
+!r+RJ_^6KAXExR05E$v-r8Y5-nd|uEj>3wA0_51_*i-&u-M-x(4s8d(?jZb?$LgjJ5YT_Lml;n;g}9B
+)$9RZ7<T6|M&3Q_9?l+u|IZ5|Jf<$t@`EtS6;gK6&EY^?-3J$`w4N;x4MG&7T~L|IBc)Cek3XxxaaVL
+DXFd&jk4lOmI+|g9fQqg)Bll(O<L<)ht*wz>)q&Tl_o1)*IJ6a0xgzR4eG1a{kvPJy1-FA?&`%C93~=
+H7X-Gq8_LOYqO_-OG3>84eF-U9cR8!Nce1_TFcNdIsTC)>I&)uYp|B;i%1tJhO*)sM>so=IY2>=h5Z<
+W!5uwI}E6H`Wp_Xqnoo+1{o@pJJyAIW#y#j}BI_xU>m9JFQE$VSa_5KT7(Qpgpjhq^|l~8%5DL`DZ)2
+F5{>Kfdx26t05zxEo`f90yv)+@fm8Cy=<n}`2z&Zw@K-`+SJypdQ$c~L@gsbSGrnZ5dL^36_UuC%{O>
+lKumr;7!2!`dO#V@0_&`6t&xeX4)dnz~k(xf%P|$&4k8zC8Q*?PyUHs#(=7Px_zF(5zNLO;%Ao*8Dwf
+ay=gE3+*6pzbYC~Pw(04Mp8{Fx($SG??$(Q&~5GH@Y`o|bGLxF($-o{qNzn@s;@&vUc|I8<oKGb@_hF
+t&HWwChCh8nbG6d^gV!(9Pl}8p>}&v2$%V?06o+|XUzI%FYE5x)q5il~)>)KxAbN-@RWC*RT7{%qsG;
+o=o}n`OK6}k;+DX!=+vAm=Y}KyAn!2vFy?q*dqE!bANo^fO>A!Mt(ynLJu6pfyJaF@~E&^uxR$ZUW>=
+CeS(Fx$kqwR~4b=~>)vF*&}US(95QPyQ$TyCF^x4-o@^02^avUK@xh<7@ID3`Kx60N<V2xc?gg)&_3t
+K;93vMfq%>f<NZ$`?WUR<aGe-<EqN(n_A?eer=<smrMwi)B}vxdB;OwpJhXF1airL9BEsRiA0?KxBaW
+G$+b6x12`$QSaA?s$m=Qgi>*YeBbKYH#bXtoBYJIb2aG&<TtU4`CQ+_zBjr5Z*a9<6yh?SCcwvfZjq~
+%H?{@*1|)?sk;aU7po_{fqm)QRH(iCYOp_&wa@pvs#C3dBJswu^){OOS;(e_)!@ChRCHzB3_dcpI{R<
+muP{ug)>s}A7cD5Yn)Cxwwe*V%r(vY;aeq4!*$3_2~R_QF0Kdw@6nvF<8qlQ|{AP%?l6Uxix|EYQ~h1
+3r5$<)X1HXm|51MTy1)#s@_imd=ApoR8UbfFUO-)}2!%kOr?wdu{&J?Hvf`6`;-7^o>X=_^dN0SahO=
+&Zq{p$*zw=iOD!RaMjJFaLm~e%zSL+uPcnpFDni`XqXMcCj<Tbw>*U!O~T&vLaNq>3-YVtZ~6pRYNx_
+m@2&wDoJ0&u0wvM&8t)DZZvCZD_3gCYA5V9sp<Xl&*`+SuM;wQb@J@{i{HOIJ9%+&^5PkY`T9GM_Th_
+X@ZUeZKD&5$adP$|dj9a$4?84}z`chhP87W;YI$UuW~&j%&Od02hbpwJFq)WlzNbBAt0WWXwLj+SAmL
+plwSt)1L<X)jzlm1jlLSRe<**wtQ)oq~BS-4gB#yxSYGiAw9#QI1B{2ZaaGOnoi_4zZj?tZ6U8t8@m8
+c6C8%24uo&gSW%ib|e(k2v5lxFta7DN5Y^#0Z?I!FAKP2=y}G+v&ZK6-WbV|0G<?1i)OT~>TmSy?dg^
+HTYWO0(4@LmQ4v*1C~N3R;}@VQPwV?{=smG8lVy>Q~bNUDn$LB~<M;htF=Jv7UoimhuMFUNrTNQ4Y9r
+BJ$2P)2eKs2bqcF!?IK>Adrw}1%x+8`&@t|)BndVUNyAJ^>%x<^62e&WZE9O_9z<t@{iF@XtWO*G?=$
+8uMq$I5=3W_YV7#S-$y&|?QRQrB`JqtRNIN&Ye6`GcFU_;<cU;c0Nt7H=)5+AloFooM90U`KJOT-Zjw
+Q3$WTzlzaX7;K@}-Ywo@nQcQnEy5ED+?=@p15WZ2Ta2c6uvMj|HXhL^7Kg9=5zJB~*1zi*;(N8<O<KC
+hxvx}%zHSFNggmyhf`5FE0dl(|&SNZ3a13al%u{@P@xV^Gl{%$Yv1ouh64QhJR>RynPPW26#Q=3Q+U+
+6sA0gw};~yKpI&@)}B(a-vQ)NHaMuNAI?YT=%17Y-6IDix^*3Dk?g1PLR>OQ^pAF^Ad)t+8oo0%}U73
+t_1}2R--f#t|a$Y(rJn3mFB&v%GS!4X0PhUq@9bhSVxzwCNJAiKE`$InkLze`tTl#GnC(LGkJ&QTKBs
+&hqX*_x3{!i+m^_%r%KgKTN!Q20$>%IN&ad*DJRjy-K}Nt$L8NjE9)2xtxGI-Ts88j5~vSM&Zx#&ojb
+yWs?0~do_V#NVac;%1|9amSj4=9#J*@s=*o3EVw!R+MXe^cQuU<~O0{<I`a_$;&C6nAQZzF-olbMe?@
+@YIEEbW3uKPw;u5&k_)FvCcy0y4LD;e9V2+Y?)XL4wULXBl0zsqZrRl-Oiy_Rz`>$!%!!c0uIsgIu2%
+SSZ?qbe-{ks1n+q->fxG~H=uw>nL6=b=Tk)G8g!SoS9e+l)p1`|C{q4R)W(jP_91W4LXrYeR_oZrAR3
+)RQRIse&03lR>`;a{AR<RrcsTQ1OJ17BCtaV$c)!Rexo-m~T6(?IT^~F}#7;@_lgyww2%DM$+$5OLe#
+}4K%-rUdeR<x%G6as+zV5bY<dmyNU;PzS}y2ehe9Pq({ls#Hvhv%U5mvz1n1Ht-am$@v$!UcJF=LI-S
+sM^O3hKe5Ohibvl3?@9%0|Ys8MD3vTO5y_D43+$Ph-Eyerfry}i0*nQr1ZTCN*q@zpq#4$a6_FR_Bp;
+)HhRcdm-l1Wpm!B5*RdbOwShHq%X---dc9@E~+tA#PSf4d`po%x#&wd%`mcD%?Xd)GCM_3~etJHy0y+
+u7uPcl^cE-ax_<qn#jB?7I6%V<i}~Yf~TOtyPnjC?Ejk|BJZ{b9d|3)05MSC$G-8*Ex+;4_Aw2y0{q~
+=~^DagA1`V=3;WVQM-h$mzQ-Z_K8AUaJyL5R_0o<Y>VoNPmn=Pi|Wz?D+q1ze%#+yJuvIp7B^9&;{tw
+gHqw^S{<v1o+m@rA-j-{>?dU5z*AKcfKi~RaP)h>@6aWAK2ml;P_Et9_c3sj2001x*001ih003}la4%
+nWWo~3|axZXsXKiI}baO9eZ*py6baZ8Mb1z?CX>MtBUtcb8dBs>?Z`(EyfA^<2xCktFo{(k09t`9m%@
+S-tmkvpaJs1W>OH@KsrZkaCYYf|G-yKOwl&qvFFkk}O$mHGec=x-1n$PDmz^6Jq?1eHq&dYkwjS;oB>
+;D`-GrRG-XMmm|c022|tPZt&cr<IcY+vE*^z^6i&rZ*Ngxvwmqv!<~!S^fBLcqnx`(HlX-o;K#Ayc8W
+Si`%!pWXiZUoWq2?yl%a$b{jtz%%D~gPGh{Wo@7q?VCR6_SGCJ(f!C3Dw{se^19qZspE>9NAP<)u7%=
+zF>||>tYY>gR94pUgn44N=T#-uL(6{s;r6$S`}?cgyBGMYqIr<2Wyz(=m|J3j;h$%3j4WE_%YtitQ=0
+3tQQ2(97%vLO;2buK2Vr`7Y<FOEt;GsP8~Da@SqQglt?nO7Nb-8Eh`lIz7V@K>R={El-$5a@iFzX}QK
+g<V<th679RB(n;0>gty3hm#Yj9RsDix5;X0uG>z;eZ`$Ape@wStGD+%4BuRdoEVFioxC^P@mS)fQH|s
+j5PX3`j349eoa71o(5Hy>&eI_?NjA4XQMN{uwH??o8A2pN}Xu#Jt7jTEuC&uTXsCp%$B(D_w9SBCGte
+6IMIzy`b1qBbOuan^VUGl-@`~zvyURW=$ci*L!2VM<U>Tyh6kkE))fnWIavyCJQ=dFlD*y%!6xmXXc>
+CSa`w;Zc5etzgc)7F1GF>6s$cCtV8f1<c~dJZ{4)ecnU%fX=^%SHR9}TH-^>*d1E3WC*Zrc%rT6kBlK
+{jQljR@DQYd!8_7epv&0*?dACM8N$p*vkBL_vMtO-r@kw-A6yl53AnpufY0w;f*u+n~Xhf%`$0pHje%
+N;K9Nm5$#_lm3EcfZQx86aDB0ILBKV{pg#{vh?xzqV7)YVDu_PiS`UvL_kDdL6XI)rEWsi_74#q?l_d
+||ou_9mc_QOFoMCBL|p(J4NFr~BVZBH!Sp*lTQV8Hmtx4vkFb6P91)kx8$FK{}vrLx1cZ3-8c36fdvx
+N_ZOzl*t?UV~4?WR7E0YnOE@kZCM#vs=$STmw;oDQ`&Hq3Mlb-YzxTi>m<HzMJAZ6cXk!yi5qxC1rsY
+hAw{KeEr?gv)|VLWF+&BI)bJp&NZQ1ec!d%`VaV+jFp|@<2hkrA!@K5E3s{RU={gzI)_71<6Nj?kyw4
+Kb1yZ)xjC7blq042Hz;_m0wspsP(V@C`h|_SOO*9{<V$ZZlusA%a=Wqg{=-!`E?<?=x=L&h$7RDg(>F
+4?UveBm8cfOl{9RQF_dAb7ysX%3#dL8m!RhLgP^M!kb+GEK?*IJRLv?OU$*XSz9WGzxm*9Y%YiwP?CX
+h!j+!aWp&JZY)0NhDRShbh{cEQ2H&Trx?lv<TA<+K4xWS;6Sq%NRats+Ib&Y%tO71U!lQ04c9U-V`l9
+sKiwbvhPI78|^PaHDiyR3f59m^v_0O-l6-Ts&%6j^^!><a4}jY36!drWUqG&ek=DI1K>5N*A9Of!IOF
+e0i6D+1BkjV@%rRERM+1tP|6<?$7C0cr}7Max?aOsd^SLdsSiEc-{8&2B>T#s?PY4vkQk<||L6pAkgj
+-Y&$266Ow)yfOW#3Qcd?$>wvz3x^-fs{6~KH^?-onIFwTeBkfcX>TnnB>%hi$KWuQ9(zLw%iIE-3+je
+ymn9Np4M2$S=Gx-BW=BS+bKB0(%LK_Gf$1}EAp;<5xvJJAa`IVwuyCmLw7>iXoMYaL}XYPUv;ZU#cOf
+u$}eV@ZX*&>_GkV%+qR<1sw$lE+CjNNLVpsi+KmxVs{Nl0OltFQ?N*$`zTKT#V*fI}<^G4HU5)h#v?T
+Ne}6+>>t$bb&A-aqA5nTf#q%5-@4U~RGKW$;Vfq-rLU&v7YlNirn}0_J212pi<=B+7O|NtSIPffo?U9
+-rc>3`*vSH&(-hZ^{N32)o5!$mWPKRu*R+my;Au@I`&sk2fgBIFU9=r{kKf#G(lga^9=Dr8kWIIo<5;
+5$zPj}sTZ7uq|HLBG?agyB_FV7Oe<g4YlpCsD3^3kc4B9R|vLBJ+-|UZjeD8zmf`|~psmp5q!%qL1$b
+O$9T05yTKi%R8twoVLjD?*#4TR?*z>pytI?d06-#YZs<GRw92fy~weh%;Tv=hhVtU^OWw`9$Kfvj@Z7
+-18#zrk!)7Mc5&pbt8Bw$&SEYX@W7nG&D<r-s1x?e@}d$Ba>rz*yW=8GToALc8VVY*IK%b^Mq;3;!Cs
+Kdbhqlhpl0Io-SajQB55O9KQH00008031s8R*s7O%pe5-08kJB04o3h0B~t=FJE?LZe(wAFK~HhZDnq
+Bb1!CZa&2LBbY*gLFJEn8aByjEXD)Dg%~#uQ<2Dd|&sPj~ADk_+E?RW=p*JAT)r;I<8@)WOD2cM!NF+
+;ANra;R-kG5!%Sjq1T_9+HfEUe>=Nt}a=(n(62UCflGEtTdETxuC1ertHfX|$=!GDdDpDSStRZ2g$&3
+NZ69A3i3<pPclrwf?;4yXGUhd+R;H6+2@!FvgveF94RAVogj**U(Po$oIeN3%Kn1b^)S{*5M+1Cz^R;
+}AoTZuC9uj%>56qz-;ubklyErWx9e_Bs#j?T*%yX*zm`Gx$G>Ye6vAQhT^nVFi;3+4(UnR?<somsNTR
+JP*Q2sC^_|3Ee<im!(7lNR4p0-ve);F*RgD!%8hzCH@DRarmWnnWS~%ULANyCGI1^8qYf^gtU@QjuB`
+}y|U9vET2JMRZAj?&F8eTkvg}dR0UL;xsSdY^CW3-;3OU*2#DW7(LPW(Q?+=RIO(B0G53TGu9~ni8VD
+32K2xa^u0bXHu)r0qx}z0&Epi&J*Hb%D#mlKJRl(G_Z5eg_HKUX1@$1uZrYN>^S&|vC={mc8Zxp%?w@
+<_>dw}$ru*Abawh|iIA~@v`S7{swonsK|06sM30Ox6_%Iz>$Xhld)7w2aTGETILcVD?jK;LYF6duSCz
+JnzB(OaQ^P7(-WiMMOgKrRbWmtl{!%n%}O4tOY1XQiPVhIdMkr**P*+{3HkWm&+j6V?t)a&^<1z;0S2
+S;;Cuq79iQU~EuEzvFAYb{Kg$n9m_Ah4*}6Q#@4}=x(!j<~@Jw{Ks!P`KGgjX9TRvNFKCh?FPdq4i!J
+QN9X0AHHsm9e`qhhC~@C7oSvUhWA(Dj0o2{RF;^ESuYO}b+2zX<z#lepi!C;?XT?(+tUg^Gy*{low7u
+KTsU$O^a3&V=H|Eq&QPYy*nTHXBH;ny;T(p#VB$E_EXU&aE6HWsOhgE`^07qD>z>4e|Me%FU7g)@;V>
+VQs2;f5A1u(j77&l@JG^=ru9yd)9?#nvZn(G>n9n?A|tDK|W;3q1k>vFrsbcJT-T)6AnZii;cxME|1!
+oG0cjnRiD_!<lhAHR*L?a;lIcp5lSAP>$KPU;*hbxsk2)AL_W*1%`tc0o(MKu~mPw`a6Y+;SYmnO0Js
+d=#z#{DzP)VS3y`P|6}n@x+azaAs2+;l-#1r#=hMs8}v=O`0u^Bebxtyj}kxBD97mavPlef*>{?lZL|
+szhmsMS8lR8K8`pm#*C<R^e0{v(X1O?UUWlRby1ArO1eU3fq5So+pyu4z=tKe<0+l1%o%TruseGPzZ#
+cQ+wZm(Wqz~VE{eb5^n=IFqVTX4rRzU(OdKazy@g$=3_0WDcMSLS!2!MoQ4M)#rBk%ED93OlvK5p{OE
+3k8BpGrIq-#Y*P?nO6qi*P2stg~LNphF8X&`B^ml>q4G^QHQ#aAdz5kl*9mAYN1JpsD8N@Lwrc`eF5l
+$vswKNiwexM=z9hmYIE3v1(;Ool^BCmWv;q&KB(N7Ot~ME5V|)B9C)k3%8`T6{R*BJZP7w-*?CH}OVz
+B4_HFI78Aw>p3O&7w6vv?JD$>2=QonOXn1S5rh@a*jQ9Z$ri?~ao423a~QH^^H9j=t2mT!L%)G|UoIK
+v?p~pT*AZdiYROyu=a}kO*ih!1kJUh&c0|pW%Y^&=e?!ZMO!#NKw+3}Sy0q$bgMY1?_&9gQIz`VVl13
+0>=o}f!-#h;RP)h>@6aWAK2ml;P_Ey^X6?}UH008m~001cf003}la4%nWWo~3|axZXsXKiI}baO9eZ*
+py6baZ8Mb1!0IV{c?-E^v9BRoiacMi711R}35kloEwDT%ZpE^bolT8lXsv+I><5a!IbFt;t=2yR<75?
+YDPkxV%{xH`R-X-I;S{&Rq8D>S_Y`D-XLuYG=c(sS4qotZbMhsmUZ?|8w>?;rrE!OrdiQo8v`l%0s1g
+d$)kQ_7iSzZodC;dvp68BnNPN3BP!9a8eX=uu{Uu-yVMa`Pciffyq@WwUrB4-T%<s|McbV)7Se?#0Z&
+mLghA`TwyYk$+j{Dl&TD)C#f@2g~z#pDoRs1_}m^`aH^fkTl<}KQDRIUnbJ)rQ6%y_ieL%rV70nK0Xn
+>3gMp;Euohn2OuMhyf|I-Q6==@EnMX_&o|W5sRc#0lducm$mEHlLgQz6bR%WDQA@qT9k~+^N8bM-2m0
+6U_z`@jz3JrVIKj#|YNrg9cl}fH0^R+ocB9W`9d}%B*Do3TNq_6D5UfI6fuoo7z0b7@>6ICS<>Eo_4w
+azfw+*BAYekP{Mu(#%b4vfcWlnA<~rYMYVo5_hCQ=px2p7!1pvPlf=!8%!3n96V$Lb)$js~KcQ2d)dl
+^P(0=r7Bnx?uLNpjMgiIPADWdW2X^i?F^P2!))}SK*+o4$_M$UBWy9iMU)zw;sB_Q-J56KI10eLj4ee
+<Rn!iq&wG^;pt6kBD@kR_Ov@)Bj>(mr;ux^)l+iO*lH?{p+k#;#jHM-Z1nH)9hSe0_1tqRzVV-2>wfv
+Z6ita@2aj`;aDoZD`MPm_LcgSVT-%Zga@Db`ldd)f7L}Gr{RiqcP3b<zzTPMu`Of$I^b?z1&P8<jREQ
+sTo4<{xOQNo_?%N9qSCIVblBUxE<4}z&3eJYJNaomWH;&8v5BHN1GN+j|;ot|fjM3!M1R8BmiGBRyHC
+ojv{0d?#H)^IfCT3`b&!S9Qp>Hb^^i*=+u((K$|4)}#jgnL8flHAx}(<FgB5JgHW7e!Mm^X(koz4KL^
+^|^PuCOm80+0sQAagxi?qMLeCjLDY>!~0Cxy>up3&O5id_ugZ7?kr03ufJd7ibokW*VEZRfZ;h=4l?J
+x;SMEMQ<E*uX;0FdF^3blE0%zJpDGiKF4dO(*8%U6U^8~@-QT0<nr)VE-r7w7Z^wQ|Zk}y@%?9Z3o{m
+m)CnnEcp-wizd5YvRymHuq=_>^45`nr*fNy}Ta;4=f9Q7rR`XtAj<`p^lg4h@D&<B=!@C;4Heb6`Inp
+<as#2nq6X}i8_mUUEXsfi}@Gu6D@{G`rlN7394I#O*1BQ}=78;8%8a&j6p8!ea}yV3|<cBKJZcH4<SI
+&)mc?g^LusK@D$a>diHM$5^m0Yax*@+;bBIF14zAbJ!SNE<hvHhWz2mXiO&5{oxjqCR79v+P1VhG{dx
+=HVDe1`=1yu?qrwuj4!V_4TIW4?3ca;&_rzlpzTJFiKCS9?df{>})nWo5!g%+WVnmlVN9^Oy?WZ__px
+>PhVbBW1j5k*T>=d>^$&mg^l_jqxfAT$iGla0|XQR000O897^_9aeqi)9R>gZ<`Vz_C;$KeaA|NaUv_
+0~WN&gWaCv8KWo~qHFJ^CYZDDkDWpZ;bXL4_5W-f4fomgFO+cp$^_pe|*1d<w8bF!`l45UDtwp)R<8=
+4M#unn1(D4VNH2@;hw7}npudr3+nEy)R{hnN!YIro#7WTw;UguqkW?+#4JDope8K&51574FJBP1Wr8v
+1g*D-!~WnXrf>wuVqooPzx;Lytps<ZZ8+)x*3wo`TWJR%lYL`WP4BKo{>L{5kxY2n30Mx^7_v&zyALD
+Ce$<;kC~|0g1otTtLK0FaQ*Jn%{!$yVUqH!3MW%=YQhgiUP=On?I&rOA4tKAFuG+T$;+_sE-~`0FDF2
+?<XI!XV=~(2c^2h`oT)c1B)&{0QAD#WipUjNdcR;$T5fMWnM~r0Ruyq4{B{&9l*?0-AN`%k{3`^2+;O
+=#ab{Ia3kD&}NxY|G$1sw-BypZWNT^64G(wU}-e=5YBMiwc<d^4yCJ9Rx3vwA=T<E#iNx~)0WCVPGK}
+BdBvqFNLme?q&jT+<g1rnz|p$T=xW+bM9Y#E{Ox#VI;&<=8=M5=nL-S!if(mIoimS?l^%r|ed35=<mL
+oV{FpfO82jUQ4-J;s8_vIc#vjCS>oXBp}TTar!>@T0UvopHecIL=#u^->ikiV{&Dwh%UlGNoB%bKaG-
+=m`IUH-%N{L87W)F;6)drrAiIV%ka?s})Dy@``RVnC7i5^Onw5JXcDa3Q+?=4-9I}Q+45~Pc-AS0_|9
+V`t!__=2!i!l~~F%hG-?Y)@-1QL{Q6IMv-5!ES-_3PfbY#UDn!q4M&A1tuW4nT}DBhy?T5Dm=Uj&@n+
+-;BqMM+OzOr7i~ykDV}_34k)8(l+?~Mm8B()~El!*S!ub#x#80ugQ)*eDmH+&EggMZ!EYj0H1gML+J%
+OTDs7to1Gg@MbSF3b+{dw)_GI4{-z+Wu^0xfu(XGx2E^APflh2#>dC~mPI9>Rh^7Y1z0Qr;J^ngsgCg
+%z33H5C|1p`Bh4=(VWKb0$F};+LLkYu?(0cJOm$=3#kOfthD6rUx;aP#&bu@qJh+2JfU!6d0jzvUY-A
+NBE=yE%N_WY<G_e+($QXEowY;AG^@G+3f0nsS02X@=DcA3wI?Ce_#bgN>ydL2b><TDOuI8r;&t7KX3{
+xdbqfb>xb})h+L9SxnTW}Xk8)fj=qBm+``sdENX>=084xg3tT?q3A7e2neT<br*RlIJvxVRx!aN-oKG
+v^Ih{cfn9emCC8xbXPA?|Ic1+KzGx9tkQ^>XNfSv$I9UIU9+`2t)=FkR5R?$LD7?W^l*#muX2S=4F9Q
+ZgFmUt*AeC3|iN!9iZ6{X&~4%0Mx-Cnw$AlRMSlU1YWT2<O8eAV@HHyxNajyWswtmMyU>VO!gS)P}^0
+sq*6gJ7UK_O<wmE`b3{{<KqMjnCUrf9*83LwbD8rLzq`Dhz>xDA|E>sKQbQ5$!wc>^m;<PWly@_f5A{
+E9;-N^3N_7eM^t`w^q89WLcA`R_y%29CXR^9lsF@-}`;UGC^}&`YSd@{s7l`OJ?n`vMxnKVVAi+Wk+~
+aYg&|K-=tL?_zFt#CoEZ!fkWWk3KkFiUDosY&(~`&2+67!Wv$sDLIXfe&tE(SvGO_{moFcK*mQsw^Tz
+<bcYv4g0AMxc;@&uY)EdEjTxBTG>%`a#P$0l&)4YUC#CgK}p%qsP4q9v}4?f|*B*qIyT!40~S(i}XV=
+}Fu-_TERa-6O%3b>>Ny~&~MqrE0>SmR)^G6EJmhVZ!PbPU^y)A!P-7TV#YDLQrk%j+^`<L%$wP#dXE<
+MEax(v>hLO1<e=xw5<PVqi5nyHa13b^g1hS<SE}EFWCPyFJHSB#Nue+1bylepzVAEBzZ5w1mrf|42DA
+hn4<`#67W~sj72;T4ifk6&aW6`sS-UNZ*1cK<eHw*m3bO{iq38vtg>Oax%!Nj%2tAgXzPZrr<QE)16N
+2vPWtZ#}nK_hjrj{R4ZQicg}_Ho5&)Aif=HWrQe%}Ngw6IaG;bNsITxJB3g1-<H<_4pHo$R8e?Arhor
+{C(GQ6}{5@XZ*wS8!Fy+AXA5cpJ1QY-O00;maO7>RtuxTYqCIA2$ivR#80001RX>c!Jc4cm4Z*nhid1
+q~9Zgg`mW^ZzBVRUq5a&s?ebZu-daCz-LYjfMkk>B|%W~ovD$`tk3WRu8}E{-kN?q%cMS}T`Jc~uk$3
+`N8szyP3W#^w9%*N=JPK~bAcavzRKtwms_r>Cdi(=!|nhXVnh)%Ia2^SYYMi*gy&wJfX2qF!e7@_%|h
+1A6;f_Ylxme0}@JZ$+`LSL=Gh?=RwFwJp<!MSUS&>OaN#>FHO;=cngiirH4w3n{)=7>HU%%dx1W6fgd
+C`}KD}yqz$ZERAJe$qVuOx3Bp9x8J<HdGq#$#!X}$rCBu@3}Hrtbh#?ZTFlpZTo*-F=?8`RtJ*pbC#$
+Gl4CZCA6lo#U<F|F0<`3U|H{chmbTyfNka<#+lQy+<Cqs-Ko$BJf%yoxb{4y4|@?$*~Z*O0`dG+FlSJ
+T_Se1G$H2Z(i@W*WkStfw=W<g{1;2>h1jwf&N%6@42F>T-KQq*NW_I(n!E@?$JlwfKgf-IQffawB>xu
+Ed)nmxIA{8fDpZ3g6!aUjtv5c?Nd_cq^+oTFEJL%(RYXnS_R)2ux8XVepG!bRmLYM9bClU~C^>^5d-b
+o?i3Q2mk4ipZ;xKc+ZEyke(lW`CEMa8IVcjTsZiIHIbIEx@sdj;@JY%+|VoWi?O&Ii)#^8Vk5H*|E+)
+zU`kP*h@@EK><|rE8HS$>l^B(>UYEJRAt!Yi<y98dGUS02Y8yFA=i4wYvZ7Rjr*lDHCsiGlb+t+BMHs
+|U76&7kWXHP?Q5mSd&ZyLm9?A^lr1?5H2*fkhh*6m$f7JCB2oh&eRfY7o0zA*7B`%}SlN0EonrYOjVQ
+VycN)ICiC<y55W|0B`8G2d~d)dyW?J?p?<GedQyMw<Y0}ns+2HMfTAiX6>g?YIj<}RKF{$TL(?c3Mie
+0wv!z4_z!-@drLA;g0p2Pa2^2bs$f)-yqsWz^N>qOMof#mR{g&Z2xcxgPAR>L!D4S+ONzohP74umz|%
+q4eDjRd;kUI1H<Ln@L#BYE%sX)4|}?cQ2=3-@JHr^Ml6y@(Xx|L=edL;`=}S9>9s=@yW@bzkGRe^6K^
+#tL<M-PR~wGZr%_t4{=^Ft<7dL*?dWpy8Yn<0sQi$0@WDTlcY|D*8u(a`2QYlj*kH|#1{XNQF0A)x~$
+VWlh=nK{X42IPxt}8T0%#G=pM_zt<w)z!??(6K;#%XW+>FRt09UuQQ^6W7g1Ts`sy&0d0Zr*Bu3ScfY
+F)=?5R4$6~2MR08VRh*fU%u>~=!^0O1qH_;OYxTg3m|#TmX0nkzlM`S07CAKtw97J&b2R{h^c+$_!Cg
+Y;%sLn2qTkg^_%MJeZ3!^03LJx_7`VVnL>q3i4KzPoiK=tOln;aO9&0Vz%4nZwZhrPOGtO#{CWWc(|%
+DolKFe}7r6qWt>)UZBODh~IC4i|5fgL#qY+uBd~`5=fC1APuZ~a}i<hRVh{Hu}JGmW?*B=Xte^N(M^)
+{gK8qe*}5jFLD2VkflcoP_y=i`kJ!_?#W%WBP$9z#o@yNBVkV(`t;O{oC`<1&4CVBFGw0W^STZlnTbu
+;;t_v7pNOo~}f6w!@Q%Nf}97&R5C-6MB&XlS&kvuKxj~&3K#0#+iqJlLMWw9Y!U2h8ZWWbD97xW5g8K
+pUJ6Ag*jiG01BfxAmxI@$p9Nv6xqM{r;=uvYYKG7(j=E@O!eE-pyO2F3;<^_XZ^!v$!%47J@*T-yeW{
+AFF*XZSSHy%gnujgdh?WI*S=N5a*`19&4trx&<FIlaCbqJJR5dXa)}nwC}l60B`9Awd~=J<R8mNYZMR
+MO)zY(EN#fKN9~Tf*eQ^2yn3i@p*XdfuQ9&^B$dFp5Q}wMkjUBGeaa?7f6x^-RKX{1br1yjwmJGyEoD
+6_3(OL6zXL-i%Q2WQXreqR`8eV;E%l<b@*0Z!+&_$PEa~{xkKPSa0XXVERkh_M{9~9%Ho5>am%#cj+9
+uu5a^DJVot1Q1!^VZbe^J_t2E!;FS02$GO`0;m(hEY+=^Wx24eUN`iCe3b8AIUCue7R@INDO5a{_j%Q
+V<A$WmM&W7ksaq@;+~OQmx-mIKuSEVf2HOt26PTRB)95Eg_~dBVxIOe-cZ&7_Pf3C<e$2?CWgc#j6yy
+;9t+rg%sp?$O9EAZEHp4au#nBEjAmzu~+i6}F_{EqtUgP$y#Jbwvw9u(Y!x7GNPtv?t)oW2}WfV5MND
+r8BjO5PvDwV!4LJlR2^g0V4Gl<?*5@VVO{Yl<Qofurbs=&dsFIMM2@jF*Zf{enQ%oVXe0HqR5Y__q|v
+a$r}A+MC<$Q_uuf?z$-xG8Z;ua8O(~|&1D4ctbERa5e!>y(u!8%hjm`3OG%L(Xv!2q8h}zp@H$bnC54
+Z%0Ik^+oyjmNAFe<J03s65N|?C!o~^rAK6HiaO2IO#TdP0Oa+ENQN=;l^TO!qxC_7>T>4_l-V8Bdx4}
+aZjQBmutL}u$434#sgPeRBK>bzb=wSoiuQOXsB(A<@@I^!?_iG)Ba1Cdzb;0+=KpsXgSrhpI}ycFvU7
+Fkwcospp#^(-qkdb$d5kC6Z-w>Clp7nAoJP{VVe+wn$nqGVQN$#V|YF2up<>Fd|0r{Z%**LVqCb-Ulv
+$7wg2SbMw$23|xTq^lghLcv7+A<Ho}Kq^OBRS49Qu&%7GVC~i`^k|8A%&rYmSx$jQCAfJKIxc}sDRu<
+<&(n_%AFvzLLnW33ODM}6jX~c9poS;a78vd$juDJS0RN~b!QII6H>)wVfHf+UtSH{Y{NA$!?XzJ1V7P
+2!^Ue<Y6PB|HI9_%G-gB{ESeanG11lM0mPaOPn%eO*eStrWUv^urB|2qEkq0#jnCEArmTNebHheFOb)
+Gm2jM5C+3ET?QnH6X?WG7Tl2D4B(yB7fSHLxBGtqm62DFgi${WxD+Ai`>8BQeD0Lu0%^^H1c&v2F$s`
+pCyhP07SsyIrV|7v|ARSy5ExKrr@UsTHXnQ7wqo9F-ME%8oBADxG5ofip0%yF&zHcv=0AwPMsd7^O85
+Z>dSOp0VR@pc^<aih4$a@j59hg^qMy2sxjFF2xj&XP}*AO@fRBA;}CJ=xNh{quwP8&d&Hk*?jBkq`Ae
+$be11M<5UyFrb?f7ajGIaWm6kb6!}3qedl=j0?Y&HKI;sVMa+wuY^kHc#{wgzG^gGiX(}qE6}2xxM=Y
+0QRa{Laz~g&>kyfdUB{^fHsKKuT{}6qVJT7H~_D?ZxmHu6#8HC8V#$}wPHkGxDBMDDdtd=@&X&57b6a
+$l`#fUkoVL2d{0@lRzFL4IBJjA?P@GiIXbm0&OoS3RuN}LDS2N2s$?)IFBZ*ulPVwjULA?%k(XMG)H9
+e)=2!*VV>P=*@+M6;|-)v?Jh8IU$AWv`7ai=FetG<;LkN+fHC$H~Y=#Nn({)M~&y+osKsTnD=ySZK>e
+fhx|X5qG=tZ9H}sbceN(fW+PwRn{!3yK!)6yf&sjThEktNEl8Aj-?PEAml|8fdLEHxzovS-C)RIf`h5
+(JfP4AF!sXcu|H`}{^Q^-IC488hgij&5mO7l%GQ-Tf<I-I4$xXBj*AlG5MX4Nl)A68RxGuS>R@3eKap
+NNY0+Gz3~ahTa4$#G3$t%s&d%(FeEq9)EN(QX&5_c%mfv+aMe&f1C0r4uJUDv!Ip|<8t>``AcoRJiex
+XK5Az1@*NQh&JXjT>3+Oe@1k&R8ipyCisb0zQqm^~8nnN>~NIbVWZR`O^ytA#SwCMjbdKpDU}`W_Q&A
+Sp3O^gwTK17UbAt;M0CFmR$c6k;kFCCrv83Z}X5UYf5QE9Kij&rdM6O|OA5h}ISo8f^Pi)~`~yd9s95
+hp85TikgtJNfE{%tjJLJ7M-kNXAhQZmgW&XCLJGPx6(mKk3SKwj2K!Yw39Gr6V0+Z``77aI?}Fmub+;
+?@I$K;45c>(XY#CT{76QR3CZ3j3HhSPR6b8=OYTr)wLOM)IflTemdEol1v8Xw*$W`U7$IRJ&^0+ZY^$
+;W+?JKKkp|YRgtfpqkebGAkH*Z|t1ybro3|1X11!yJ`M_H%D&X|>30XEph00_sF$aiFsH|%pmlLo`9O
+ZI@ken#+H%G1#dQDr7OOUj5mS$<a<rzBde@zT5qcTe|Zj`Y8Th=-sqHJwZS6j>Ogds?b6q*(4lE~BhA
+_T-%QCX+)8r-O{4dU^`UCD6kAjQS|)-f4`hsUvFl_X{$;NAMnR-*(tz>bd4ZMZl(vUwa0J5+h=k>^-0
+WxR;;v|8FFwNmS3m}zlPW06fvQt&`<^O9jLC|tz!6_^v$!N4&$A6F3X$<jbu=b+mvvd`o`;c&b$pbVI
+0j*7MUDof)O*8vAP=0Wa#9|pL2B}-WAkl@PNn=<>rt0=}1h#(#;8&#a0|LV{&lO}~}{ZpN`X(U3~5IC
+7kR^<L7l_-CkXltdmX*tpy^+-s8AKRX?Qs}2D5I7rg2wS=$mT-C~Xa7&BE!=S5t?3-=?Dp|k(q$6u5j
+beM?!cKtIt@>D2I-N8n2T$11`0F>Z;0hEht+Y%gn6$@R3b?OG_FLHJqrDF+z*(onab-~RZ1@2{ryl4F
++{<3rg`d2GcRUQ{QiOR2D`Hne%!yI+=Q|l_{xHD>LBpba`99M$h#yWTGs`@Ok>(*Qdm|zv{D_`r(W=E
+OUW@{8|FLtaDgvO?oy3z10nL*DV;+uyUCgnDep$RBECKz{K{EZm0vGPmkF(-ZSwgbZS_WC7L3GCMXBK
+H)eRa9f6Q@*&Y=NnQQC_v)(;C3T!?4ilSJoIZvpsfh^?p!4y}2ZJWObvQ@tU0IV-P`TQD+&=j4YGR2t
+&32<F!g9duH@o4dhrSgt_XF;&Kl$^HGjC^|R|?J+Ji7`)g<#;(hPI~(|a9FlA@yHuE!NE2j!&Xj<?yC
+0E)!I6$h3`vyGpYm2qd2=$Vwm8Cj6&%N)q0u#_HG4FibC_ZUHt%0Y3PC$=9dvl=)G=vU5g#&_en=zn*
+XTo3#bvsxAMru8RPeIw@<d6)jGfteRtIKu8C|Qr`9D>D-m2wC+YN78bC(rOCQ<KUb)~dA_Of^vixA^X
+N9yug<@-of9MQ3X1-Sd0RepMMtV0qTAL*fWOTFRZ5hpa21kNTGaw>M;t+(t7LECkiF`HSUywEyJ@gL<
+0h!1m<Q8gQRyoaX;_U3H?eu&bH;)xGYnQ}fFU5fj|5J^6&fCu1jDhM0t1%&Sq4UZ~^O<y_s5#1|Ke0X
+b!RBbN)iedKs0jIr=6~i;Gdy+=S+#O_T(IB!BIvJ`GJ(|+@31?Xmzjq=iG*6Pt8Zf9<+yB^ycR{pOm^
++MZc3$0Fvhm<+Wg{JA^p+#xqpDIc8ifUlGOX5c#K{D6k*>PDzpNM6y2OJtnV3OLhgN>Q%y$#=+(e=%J
+~$Uk$Umb%nQ*CPwwO|CKOP=qt7}w=5V3S+e$_rEnyg>xFglK$ikLnOf2lA`<ZS&gr3~hjGMLVqC%}nn
+2LkxA1_l6o%3d>ONxM_vdKY5TndUJm;>QShI^YIJM{m_`f{wL0O`@&C(UI9f>$A+atxoJmZNNQ9c|$c
+4;NLUqt|h4K&}fv_909~2U&S*0yGBSEA{v4jmv**!G-rnreZ5NUuE=aYnQ{w`Rj?g1o88@3GDf}}V75
+(VmQ=haTCr6N&seAs#E7F!bQ3vTKf{`)JVAbtl}<%V6+=<IllGo?VFpSxiAIShihgyKU%sUzldZNznK
+NMEWT^s8Odfga-s&u(obeIWVBhI#g0V|VqM@Q6A_32Ih>c&X1`=o-2^yzk%nRC60k4%(EV$K3n+;|Kw
+N1oKk6U8Oi`QH?@Lo~^55l-CAhzDRX`#x4;3N=v<w$YS%BoIF5j~){rQ%&!VY|9OzLSE+F+F%<h&l5n
+Vn36Bp`;zTd9AWggv!`Jh42b1#{epGE2v;tikQ|@`RD{sF#%76O4VpQ8V0L^D)gdP1&GLu_Xamwzu86
+5+wnZ#bZMMOH+6EaRufB@II3ay1{SCCHh#@UuyyoJl@m*5t6s$HN5<q*?6m{mECyfzFX5$Mc<Fr`UDy
+uzp~8Ed7xL>^4KNl*x~xe~VN$KqF;gVYS^@z~5v!2<kJ@9nZJd!hAQRtUa2>E|30f`CHm4xWs1_Ma8w
+!5FZl_qVch>zHKL@}ZfvaS!a>2oS`_<yv6(9&vSsOh&2}E+&{7%#a6|1F{(m3SF+MOdO)JPPctJJhLz
+g$dabZduXlo%|MJv62p(AUMaia+PPZIETu!l<vh(^~LOA#y*yAG-c87hx)8K;;K!Lw~3$RxyHLZ4HwK
+w}7%$rYfVPVp@`XEW}fpeo}u#K&z^B{i~<fwVuXKbnXfN&_^f`3NKrfrL^IUhj&of1b1v<l!wMIj_AA
+>R?yI2c&-N<5m!&qS({E3PahpA{2jJ7k~isXY}%4EaizqS60L-!J)P%L!kk0fqS1>D9&~dLJ%wt7F;=
+VMdzb{JPFkIH<=Kw@s!0zBXB!)UsD5;^Bye6K5rbw=wRPM#WgnJmjDYN3@u&?_?KJKQlUp-(4OnJFb1
+zt?btf#f-?cARw6oU*r?suNd)>UIJ?p1q@4ax-jXRNZgVueanGT&0O~AAdG~Kupk`8wI>7`rrkO||6s
+mf_WPgFU`7@t1-%~~N#|A4Kgc4V7|pZkmC+cS8JyPp)`cNl7{XBBR(YZ#zcGo<!Iv5MmN(SzijZ{BRM
+g|ywqt?>!CS2Q!FS8NY7wnJTmI|=+sdtOX^oRa>Xyu5|~hTd!)La0!?sbSRP_L`-0+XWQA+HAXMV_^Z
+G+bnEmyZc=Zy0!r?uPC0|0s71VUCEtToDRBP;2sLRjAm8noMv^H$!Q0~IBT-M-8$I|id^jg!aErIz~P
+nv>a?xLoXv?HD$KU(5lb(@-^Cr~C8~uV^QH}Q5`bO3)vGS+WwOYfqvDIMUS8_8f977Zo~i4dL{g66op
+~87?uy=|d*Im_LH7pW@9rATxH%Qw;#1vg0?uCu>mKqrBVWALCij2gj<a)o+WlZH^}wIc6pH|BIklB4;
+mC2ga2{aE)UjOlq};=~_yLFS2X)+7)r<JGRkj#TmtQ9~45yjvI(X&Kr~_R3z#28d?%HqZIWFv~A=}=k
+f*VJ<Lq2nQ3>uAtppPJOKa#j-4IU%PKE#MK>mB(E)F1>Oapp71Tqo5yi`?MAU5A<X85mEH3Od}KwWx@
+FK}0%<$%aDl;9ew6dy3pV%KAj}yk3HS&gF=W^VpVfs!Qu|_<po{%6OVaN^lxvYKthsbZAqb#~lNqqeQ
+nl;GsF|F~#QwD{6MmRotFeMZ`o%W04~YsS+7#>J!5A6nAnXe)L#@@9LmW1>?L6Xv;jf>rjN$5wig5*u
+i1-99Zp8Ut{2PA9VxA!w<V*cbt{zK{N%IEsghp#v~Kmz84&wDkpDgCqz6$e2ngRNx85KVfyt#o;~bAQ
+)}^$cahh?>LqZQ$j64FHW%V-^-)wsmL@$zDNwDEI#>`tAOi1*-|m3Byek^?=Rj0g=>*}5)>hy>^BFop
+gX!dtQYb39>w{RNvW&`ju@zyCW%X55Zb@25$46BhQ4W^Qntjne=nAs;4v|A7`ND*E7suy!V=ZhJImZY
+$YO7g2;;}f?O1_3Pe=AjK^rLq=QdgpAo3tv6WF6ZSPrNQYb!H-e+K)qUxHFH3;qJQ*edvNJ=LnqLqJv
+;ZmbFeu`{x79VYtpIF$uKu_3m!a^=5)4!?{Y_uoFh!oL8Ja+N-CPiN<lnJ^OQv+3MQzF2FsW{Iy8)&;
+iz1{T8TR9xy2(g9fT&eo6>5s79pp*fh-K2bmd;1hYLB9mlqjhv*%n?Qk&k9vOq-SeQv#%Via|1R5O!O
+yN@_^YX5N=cFo1<C@~fFoFj!IIP4c&?w@wI61<9k4{jvgo*+%)<{hUx5!telD2nWUEH<j*G~$XAK~R7
+++110&|k=Ip85w?Q@5NwOi4BCwoGwnIKLJRB8raYM$T31Hm&cxBne<ZD~GOSJHW&@1}$||sl$%~v6=R
+J1$Z5mVJ647=`a8uAo4<+9QdvY<sE{*yL)$f=YeB+W=$2g2Ewg`!|Ib$=ttHPd5&1EGl!$r3?kF9A<E
+dnxz)+%MlZH8i`PrkeI_8>8Ca{YCZX|NWErBYhiqcC2g`RT;D-0wBguFG^^?Jf{Y!YpfX05?Ix)!{V8
+U`4Wv#9r9*yppI4}U7($O7Pr)YZn^ZQ2;_^E*QQb3OWFj~i13MJH?5f8oquf^^O7`ZgNNFedSBzWfUG
+f*_+F>qQ@$}^88Dlycl&D%2IF>wU^Yelo2#Z%4D;b<5)oUfzvTNzw<*j6DN-ogwT5iEY{<%$)c`w)!;
+(JLoZI+W6KHNovN@C!n%E%9HDlbJF+m@iq{Hvmax-v9u$rHv=ZkAJ5N=WW<%grzBP8oFCKPZjgegI-{
+s6!ZafVu$XCVuiOP<PXQ0oWqd6T79&S)WwYWtgS{JBSo14-u6^#bf1>JmT>g=j9qd2zcO=;)czFEJsz
+V3&AnqAbj)X2d}ZNCGQ9=kwykA{yb)6R0<GTi27)o+!9%Z0r+9eHTgenY0%Yez6%n{KuBMabIUX7+)-
+~;Vc=K|%4_k9l*K|(sE&;W7qA&Yu&rDZ5*prE7ySuG_7>b)wQIEW)Z9Rye&h#;U9FS_Rlg`oA?9ihyU
+GUtP`Wu`i+SIuWx`*M(t}3}s3hGp;8g3pNd(IQw!s{vFzz=Vpz0h@ql*R6B>{CiF2x&_FB}q$s9qM+Y
+aqqA_A8%z_omINsN4A?ZbnGPz=pdJP8RbagMAougQWXpr3({^dB0Ao=4H$4Wi3-sL%#vd4EtZ4M@Z`I
+D!Ht0#?3z5bx~jI|c+`n3%l1_9vnOvJ(D_zpbUF}3Y}MRDPb)k*qt2m{gy@UgT!5Wyt=LpAH6K?E9Te
+%hQYS2FjNQFVlzvAJbs>$#a5EeWt%t6LAVSB#8IBO;c-}7xG46f?CBoJ%i-(W%;ite{rWst=;Lp7f2(
+JMQMxQ&kfWCW6%!nw$dbV+dhp^VAq(&f^+#1o<mj@A%D28&|w$(Put6zL(%B{klOCkHFpQLfkcOYKbs
++*lMt5)gCWyYNy%p&@x#nP~?S-Yn5Gfu%Q^VN<;{%LbEop=g-r!<<p#tWF6y=Jm$E~%PcIYO@4bPQdx
+UM{!Fu;5*{>auFb9%q2mI<LKLcG6N~b5w_bwhV3EW?c>InY+E;L_<j)70Ei6H)UFJIotN;?Q(;Ggv2a
+d8JbbB)3LuNziL2Xx5~*@HAj&v^O851r>+upx59xY{wBBWnB}^Iw@Gappo%lwI;MDRcLs;*I+6Nils|
+x>%*HU?XKL;ZSB6X&xx@e@#gMc{n||sw(k`ZI2BgAxhgz?=b#sL+*p8)UD8b=TLT>SL1I*VpP8hOgdA
+B0gATA?yE$hKyb$pl%uMexsljxejI%_h<3R3187fQFkrD4PWj(~ewQ==8>G+i#4y79JYEc)wecvuY|$
+pf^Nd?(gVfZl@I4e^N+Qukl#6S-|yXCJ&35YF@rgBI<3_J|BSpl}^l#07Lxg&09)g&SH!_p5Xq-+0d{
+1Czsdv-kKpz#|gwfhfGiUEggn78^Q(4{i{8fOIF5z7~+q9MIlWgcbD;K)yL{3DE~$0nxg*VIsbkc=Zy
+1mdmtuue!whXi4a6>tkumrZu_(&UTBAf^-9)oPM`<jxoUdWH0%26q5LAcs|t2ruz;%B7wlWCDm!E)47
+I{&#<7ISFZ!gNxitHi&6t`F+kaw>!CIU-Q*q33UzY3l0Y!J&Zm?K#K#d>06JqJu*~~H-JIo~VLGsPBI
+nK>A2Hqch1J?=<zIme(8heS#9Ync9O69SR{(RKKCF3*w<5IY%2hmqx?Z{U>3}WXwWs@AXJsDnwZ58=p
+S+aZXTCRri0UrnGe0TGOW3*x_}aZvm><Fec#Ov{f(8%}4_YX?PM7YgrORwvm+v|WLZ@IK+Xw9zo~;L;
+i6Z^56T(Rkh=9>>uhI<$P49<`Om@3J2Lf{>t!pHhS3m~oE!EAZi9SxN4iu{E3ofkm5OA}_Noh?U@8@w
+pV8H!dAo$lo2eXve-FJrmef|upvFX?$nDHVR-yPlyPU9*5i)#Nfc`yL&|GkTUws)cTWPTPeL+iaKxfx
+t%x{s&vI93)O{?)>w)B9ybcLt_lf9DribF2p&HT1auv4XY_{stF4k!KD7uQiGqMRpBE>?oBUHC%P*AJ
+?v~XLT9HwK%hyneIKp8`AL}Oul4X9C2OBkvUCiRda{tL~ZyFN3>}>mc<V)898Le5!2K|A_I4NYszfZ8
+6O$yBO{~<$|Lrmw4nY19BNpiq9};}i({bXZ!OfWg+3iSeCn?u8G(IP(6<)<YT7#_BX87FttrS)iWqm2
+2mF*i!YGC0>^;J4Lf<m(uES`dvZF@Cttx0F0l0&Tg95+)f$7l?c0BU7fVDr$MKn8x@f(g>R0*C7w|uI
+V_c|pN2-HPqH}u?K-mlhb-ZfLYMYk5@k*IgrvT}q36+*Xt+Fdy~<*Gs;+2jmxou9-RGy`)m?lIDuhVA
+7s%=H)yyVLxX^=Sr}Tm<H7x-VL1iQP5*34x*)3(|FUd}j(m(zj`WMR+ge3LIfB<>V&plhXpuq-z%-rh
+LeYl8YzlyzB~pFUYYzF3xy0Jn^C7pl${t{^46REbdQYCJM%ytmK>rZ}L+AG4Q>Hb5B<P&ivZpBrDg`I
+EoiCTt*-9e(9^T)6<c~%KS9l6faw>dN!Je!y!`kn13@50w}&!k@#hmrIa}V>gRI9nHslh)Y~eyzl7KE
+`+F0D74mT<i=ub6gF2c(SIRdJ)VrhpC!X$8XEN<2^nBR@rW>Ms>t0p-;FP@ng^#l5pbgSw9cB8Gt*&8
+uq9pwqtdJKjnp0V(Me`V{{_f_tP&mBOJQbTbTE{sqpf0@3T_Wvq&M8*Ium$Nj^{I-xeKX73U4M|<p3P
+T%wmZ<jU8IC8nCP+^E(F)AsC|x<ovn8K&>w>FY${WV=pT&mPr7s*kZ=YtP<HGxHV1O69nH&Dfnyitl|
+r@J2%JJP>ITeMG)}^MYtb7}d4oJ95;F%$x{sIaMZcb6(Vod$SHPV-J^klQ{xNpPbGrE25Bf+~8lp6HC
+~MDFm}o?uZrq`AdyrB(A2fN>%J1UGZh@0Q=4_Q76|YQLujn+f9<gHyY{zc$V8z1Nt58u}`mBr1c7ERy
+WB-1_Q#}NpIXUUBsIU{H+I_q#s)+);cm#`enK|0i9>qTtp8|vvT&P(FbfFu3HN)<Rusc5iUI7OH47Q&
+;ArKo-xsDj>;QvS9XpR+s#2{t}=>6C`d<e4`x58<c4aR1WZlds8{K3>K=kI5L4}_URpEnP<j1uo=Q;B
+$xx4Ip3Vk?9t)YZ(@y9)r?nKJ566&;8dn3o5SBz|upl1qnIP#%-Fhbel@5JVq}G!b<A&UN{Gc<djtuS
+P=F$E$2fzfclQVu*wHvoFp<pDGE%%=EJE?3iKkYV65QVcZD_eTC5u?S@mO>+T|TY^Nf@(I<&iITBG5_
+qd2E`^}7S7d`XaftHQZoxQj2rfrYK&JA<8z01%VBXkM=L|XP+37a9SoOC^Y4op2)w@@f%H{3*m)-4kr
+`}OaaKY`<Du%6Y?ej}T&{YgP6sNm9$(a5f-HS3wIUhO8P?bYu`@_;=*+Q8wf+;qAS4K&_YD>ocB=CsR
+EGb}H<ZEK-@=-a_OJ)CZ16xSF#A&L{6fN+*ubL+=#^l*a@!gkQl_k%$63@B131&d3IWH`cmB|6X4Q|o
+thAxv;L)?X3TH)Jz{U6uR_1}2@x>X+Wl?Ci0mrv+hOJ3mKh@7{BN_K7drYW=>YbMkXlRQ2(yEbyqOJ|
+D^l7O^NUTH?(lbT=%9$NoKl_uVnu!bWU*;6_Of=#^Rr!H6W<T)HkW?4Gk)zPck{V!1~{Z1zgQDxcvf3
+;bzXOlQ!8ndG0D_?|Ak<Daoa;!)}qyqnW56|*aAq(41Jy_!%u52W=Uc<LI#=H|L8@-Ys4++c?N$c!H~
+OFK7zdVJ<RY=j@HEV8VTm2NNdBik~KLiyJ9ggxSA?ybGQ=XUnDEmHrk()MObBfBxC!VJEu(Y=xLt;8S
+siJjl{#1H-8l)9yPg7wt;muSi~No4Meo%y25tgqChT8dBKMCB98_9EqIvuONc)CJ$R#MEu8p;C3~XN3
+&emFigMtZ0+An(I2N;4a9mR~RCc*1`*-u!scc1LOu`*Y4$g)pNCE#oQ)^=*rPj{azscYND=HHz&mLH+
+q7~+`wZecM}0DyYlMF?iznB7_>$v(TTx3RQ2x?jPXi#%qqH9`=d!Tw}#rEuft%hd39>)4*r6ElS47~`
+7vLMdjVb=(31~aj_3+$t~tS(ovB|-gjbd!Dt2Sl-NZ$iKBV{?RL)AMfWi5d5c(-7Jn3P;oLbOyA1+q*
+&|DC(&i$z$P3pQg)c`^@te4OJOpCeHk#6zTYwaQ2V04r;zCD+YWjHlsuFQ3EmYTKZZ7(J2+9Wr<{(^p
+uR~==HDFWWej%)4JO#t-Fy=cGzRTb@DC&Hg)a7wH2y?0FkT>|UKxU)A#IJ7n!uCBy+W23{LbyrDHbJ|
+*&Xv@A6V9T%RfYv~}`&^Y1q<7rB(J>2eKV6O52bi{E_Xn%CcsqdlJ=n@TGPYWm4yUGTc)wWvQ4E}Y*B
+xl!fwBFD=c8o}P3^mOpzc@&^xUND*RNC4(cpgpP)h>@6aWAK2ml;P_EyS-G9Zc-006R8001Tc003}la
+4%nWWo~3|axZXsXKiI}baO9eZ*py6baZ8Mb1!LaXD)Dg?L2LB+qlu+{VOoaWJo0n&rZ`!>!~{9Bu>t4
+Z0Cu6cfD~uG9*G0&lJh>C9?WVpWpuME&viBK}pHwI`^T<Oe~VX?qc78U1~5G95DD~o5e~bWf9ENe8tO
+B<V6sz7WC}@+@Aw__*Rc+Fq3_V9#%YKX;o%b8ORaGvozb}(PCL1v)B47dwzKM^4asl=YL?+4J(&|eNY
+szQt;J?6+*C+AFjW@{CE{eFmW^!Ng<BetE)Hi`TMiirx#bJggF!?kK!UY7{H1SqE(jWB})tat=JR?2l
+G5#u`J4h$!C#-X&!V}&D8jMSz9JmWfbf23sFv{X&O(`tQ^r*l$6ay92M&76D<bs&6X*w2=CVP7S%M%)
+0rrM*hlP4-Yl0<!Dc)c^D2%v2W7rFCKyE6hqL#ZgtHZ2h>`sBCg*GQ^=+DzQp8a_;h%v?d>RWjX4iQo
+4#dMuWTirNn&)YL>>T`-$Avg(kSm;%b(G{{(F>*?Z_JTX7%%GC_^=NGe$+T1<04Ifiphk>@nizmH=bI
+fl9o4O-n(etz4^Cn(Y{%OhmZGam9?JV9-s{1nic6vuqwGv(sjae!HYCu;<Ly%pm<3MqKV^zMJ0^`VI>
+O|M)SGIK}im-u77@idIgmJFQM};E<c{1y!Va?>y3w`eN0z8!7s1U^dA3SAPq4+5{oM4w19IFM%Bu@m1
+KKo*C(L;HJr<79R0HrIPk3GU@7&$SC{YKs9`wpRT_uZvl@_m#tcYw-GKWy^5cXRJP}}Rb6&+IS>7rQM
+V_FAm10#Kyg7Y)^27V<$=l0|>&eB*`RU~1>>t1Y?~V9{|5&jro)qjnO;XP>^ry269Qrz~@(7IaLabe*
+&QD(BsB@9T0OjCd7W1M2-xFV?<%w2W-%zEY)Fp5YKP^Q9uBKdq3?mRYN-K`0IR|NinI&n-YPBa%qJX0
+n0ra<Nm4yB&>1vcFEx6#ua>2k-0S>DQG96Trf)$yVMe|66ZJ6gg0j<kxIP_QEEEoqb2Tp7*fgA%=RE!
+bm8p>qErXZjZ6Xh%jf*JsQ0r{{AxS*(<O#DK`^AW+ABzz^**CP6t7$3bDHfDz7f_fNmxc=@Kg46X7{N
+5c>pw|D}zAutl8Y0h?Dc7!Hj`|a1F)z^-2Sv&AvRFsu()YmlJ%dU$93@rLXFqkW#i?rtohg$U7<ehr<
+M_k+v52=381nqLq7gK`pT-rRSu_^nH=qEFx1WL}dH@O<jl-}8_a+1~<G>uLds6L+auW-KOBm_^XA|^-
+4{0V6|Hhloo?*lUCp36m9Min<<6^)bGv5RSK58DtLi@9ApP~#QDH)r%&OV$XAaGv!7?rVMr5rqB7-4X
+DFiTgfDv4&WW`pCvUwWF0vdU4hfrDdqXtOzv5`mT=VFpDOM<v}e0O1EcDc)yMBIk6a1^DoZse4looya
+Ur=Fx(!d7gl69k(@6e_&V{C6(wrL`eaO1UwYD5Pt|*@+hnSdH~f$5KeVtlU$(z2afwPlH(2197CZ{Ws
+DUdV@NxJF*2Io=qP$?V^+(M8tPWX!0>|j|FCT^1VaS^Byo$)6b&7Kwa&GI67s5YlL;STjan|V%fu<H{
+C<lS=R7Ke9e*H0u)_;3B|JuB8F=jRE@QA6F|;^MhJ~#5b&4@kImF1y7g{P-Pi;wx?%j5o_=TdXLHFw5
+cA2&0CaL;0LhA|+KV9J|3ME&;Ian#z-ej68N3yu>Om(B)2cXvBmK%rQ(sAQ-4g0%3hptRp4+{W}PY#<
+sWgh%{s%F%_B~I5O_lLu-Bf!|!aRd^qomQac(UUOBNpDk#(m-<XO9~+zE`SJ;eD(+5U!I>1Fl4-!>E3
+rJ_u@NmxFvXa-?awA^zW`H(QQBJ7=+?Mm4z5JIyh=NDI$o6(w`4+4sSI}M$B4=ULnX}*wsej0WKcqVB
+Ca(^$e%Q%rzQF$U+%Oe6K9$xW2NSc|$D{4gD(}u&qRm`ux`ww^#5xa>e@!?Y~a>KkAg@G`+7f+L%ahd
+@nYz1>}V=#8H5QfZgkuj%!*;R8h_6(SuYdR3YZ$3D7n0ci5{#I9dYkuERRpF+ZPqthN*0;{yMAn7Fqn
+WjqNnC_JUBk)qBm)X%u-#bjI^1O@+7iG1@Tk1KKd;1eGdPWOBjmtag+MDp0_@~U;@WPUn%vvaG3eDBV
+8xeUBwj|=8ME{1A{2KSNGur_et`DPE#fuA-{3kV>s@US)8*1BX!Uuu~^X0-R{z-PpTo0%KtYf*gv_tT
+#zuYdUX@f3E9KU|%D9I@QHO6Mi)M#QJ{XqKl1Tz&c}O2Twqu#4+Yud5u-#(ore5v9o|3ZT7V_-hgU8Z
+7TGU!T0kz4!NL7pK4JdcFWt4;prB8MzV?DwCF%t&~oyg`tLZUBV{(?_%RWQ4qRD)oc1zFflw9*=Rd}w
+3CSu9Z9=Q_*;j1&9AQvvcGoC(&@X&!q3*7wSy<$CV1kfKV})UeL?8lMerVB^vlTG2T>hfU6ZBD?28np
+E5{lJxJoxYwkL(Z-LySQcpUdwk~YTIaastpMo=ePYP&*L#*1Q0$a=)i=4>sn6vgn|dW09VrI_6dSXdm
+_!3e!WLE(DILp<4ztJ!@E)K4&#Cu~Zl1VIB2t;==Fim0qOo|I!ExNZ~hgq;8$bUu<<1qD$N2J9@+WiN
+=HCMV$@1|=eAEn4sxTSrJZ#as?6OGF;c7|raWE?F#iQ4+Zlg+kA8Lj?0JQ4^4wunuA*lsITmP%e3iD#
+F<+&4sQ3xah%?y=IYpS%fiU=eFcEPd<6DHgM%khbpR8nNszPjkl~w@|@g5J1fwI3H-bhCDm(jFrQ(`6
+lVm^u`2r@(?bNf&y@(g^EUG4nM`l-dIt$Ogs?Mz9fj!SmI8~*LpL?F{vD10B(dZLFH5<Dh9Cg6O{eJt
+L;#fZ2M}+%W`7;CKL^i)Lszba^8z)?r&ZiMKYnq$#S~i;i3v2(<`6zt%#oF!RMzTtaEX?UnPLd4PBY1
+RWD$wYW4<Wd`~qIoqZKMA-E9}H;(@th1!}M9?TP!McA)KHw0ozes&aN2*ss4ewLbd$no?-6?GG34sFE
+mTLB2?<d<NE$h9Y3s=)<Z4a%S1#KxM}>Rd!SdNUTf=AbBeZGLu~t1P>>gFr`Wa0sAcTKpuu7JU(WJ!O
+@|7b`pjWx?CQE`Agr+XBaAAoE&jS^iE{c!(GjxlSD6s9spsgkpsVxGlSLSVwNtF2(@Xt!S;g@l31YQp
+T$)uj+=v{Cu{)B88BZ}i-+cuzkN7;H!yF!I{#o@zdL)YikWv<n3!ZdY)HKZu7H8$9K0%@Avb*pJis@Q
+`4GZTxfbB~1fMNsQ3b;hj1L;(-bk8`*>i=YPSR{FWIdEp0}~*=Rk(641&T%`2au@N%LwqLSOqR{Lkkz
+Yi4+~fqvIk97gJG7A7Y=>8c;9D4Op>EE0_l(cnxWlCMhmk;Rd=eGEiaOwZMT<O&_2OQ1M{I22??(d*^
+%xnZyVQ?4~1wcIlp`eERexi5^Vuq2qFJk32MrCyl7Tr{<%J+M^eij&`IDH?V*_Vzs<2!IV<yB3wwJ!;
+D-M02y_JKsu2gnwpkWt0{=E!TZxvpireMsi%fy;M+Pmrp?QDs!yhaftqbPI3`revlnO}(JPooIpir+o
+^uiJgex)|EZ&hkT4Sq1mPbh`n;)7r?F)UnuwhU6?0%6`nlwve&^EHh!K0(+e|Yi7mjmTbhI%>X3a31W
+IM(Ddl-!kgrYfZCqn$<zLGD!ZM?!=H2etDSwUjjw7zaUxP5QGqy4U`2=*Ie|KfQEe#q_AK5jR2w?9~c
+vDV^K6IVKl$m>eZ-${O?MImC}`uFR4ZxSbuEtbGtg=<RB3+_$hupSC9+IT)P6*J3L~2DxXM=3RtbqSU
+CuoUfBQ9<-H@gOeqf3=e8ZMzEy;UuW1IzqL&B=wILsAu1~u<_uYF5~Z+hzuZa*h)S0_yi{~8;|X;XGz
+4AIR%AomDoU+}+LJCJhmJ9iwmft<<v0qSJFtpXR&EGxgPyFdi=MU-WQceaQ=`>xsrU-)H4xjvA>$LUR
+|%y*sS`Q+@`!yD|E!{1W;8fjcX$H#vrJi@KGBX=3y*Gq4)a2uhSE)Jy*q!0f3jquvQX?!sn1NkCxLuI
+kFcEtgr^d$v8n4SU7DC#8luM8z3p93o~UH6XE$&qq(hZSZkW!n1`CWv&WndE<_Yc7kzoo@@1_8ctgZe
+~SCy>Yjn~O4yq<KJavvoRB#zDj>i%4#3#HD?gI-oNM%`*Y^I}+Sa^#`(W7sFP8iD;Ga7ZQ(q)XJ*Sp!
+3b;b9Y=Y%KC59&m)wOm5fYEvs*+xg9jIO`3^5;;@-Y6FNg-A&=(sxwmD@(>HMo1;#>YGo%&5US~@??T
+%(!+-m*^t*4m;rgB3%4flV^1pQq^RD+(bvUXD!;dEKXh}t6Y{AFw(9~)GH$5kY%u57<e5{v-EM~AKHd
+gswQTMvNA&xZ!%bn@FUjjm+Vq#IP7LL(tBT7>9^N~32~Po*{suim~O|GeR-#^(UEHjaar)`>`99|M^y
+dT-{XE`_jjE&yxMXFo+EF>~@<{I0XiZ7`-12IPF(U{Ds;!}0DuXWPf?fVD;5B_H>DW9!9$Z-E-Y0%lp
+@?Z>V*ncoC|ivkIH4;psbO*0Olz3hin^sU2!g934Q0B7R(tr*khO^sj=T5v<Q4|{MRx`eH;U>mt7Fc@
+h=)8WWur6Y!zQ0TN3@HLHkYxbni`kwB|RHyztF>S0Ty16Jjw3($-V9djs144ZlxS};ezo=udPmjWQWt
+8m9hFufT9_3bxqyTfwB!taC>En%|v&tiz9rh^nXxKW=TMks;_x4kCBS)z7Y6$@L@;T-ne?IhV%(&sgd
+{1$@&Q_7P1Ze_Sg-X<5Z!`AH(yB}yA#XfeWwF4FOoX&(-@}0V>`E;MbEK8v*zF9c3Y8}cb$sdVu{f{J
+C<FEb;Cyx|bGh+f>b9o8f@Hz=co=x?9(U3>S!>v*R3b-WYR%Otj%#%LaC(XTl4cU(B4VRhi5E$_gN~n
+JQ<UbA0^>1rO^pibTZxk3wT*XpFw~^h$yAG0N-4-T_u-c`Vj{4vGVRB+wF~cq!6OjuqFnC4|Bnuznqp
+U$7IeD4lU)*1hcT8=O{dkOoXTN<tV8>rvIc4^JZn(ol8Kn>z+(@R{$2}e#I87M@N(2vijA)*bSSKL?b
+gD+YB6&Ag>mnTG}*Vs(NBDvdJ+gZKSg=F``K9}P4isLO5>D+>XzxfNR09hdDy<)Ha)%Zq~E^nZ>gN)k
+r!?V>ptsx(v|>P&pJFbT)8et!b2Aqri-s;MEfN7SMg-J*vS=5YMV3l)GfR*=30$#iaYvoi$gNX8MWFk
+VUH{()!N<5gH9ncXbQw?f$~L9y<U~H-?p_{8iG-FU-1Xi*Qm>#7Fr+K$Pm1<CBW}^6bo@TpmZ~qj^Wm
+{!sNp)1as+_rWpQ6tsVSJlJ0OxA0aJ~hsV}At<HP!2sPu7%dwdEMlDG>(LkO5-IUhlFNwNVTOs6|+Fu
+3vFIAxqoH|K(YZ@xb*r`0OUF@E_qMkiy3pF{A`C{xiGH?u>F6h;~=1E70#K2m7vTZ~jevCA(k%qNfqy
+=S^hBT|}OJrJSzdEV+chlr}`K1P<TVc>Q$`k*dC8%zMCi}MCDt0hKGVP{Z+02-d1Ns7nRDW+aQkH?L*
+9Gf~W*A|{#zSh#u4E~zS%B?g*UJd`i^Iu*M~Qie>gYMAkz@HcfW5X*KW<QqL3SpZP;O|j-Rt*=U0=Sr
+Jcc#hgR`n~pn*^E9GoXuV_-{?U%>>=V=SGkavX3aN&?2t$`&+LtxqdDEv70;NNsR(UX*0`J}IXPOPJ!
+11;~SCdSSfNP6n>D#F&7apohSEC|Np|e*+>o1kwxtg}rUmyIncXc<Z#=V*5xIgXNT#n}C&%>Rm26BWh
+A0ms2=eVoR~g^oyjqdU5nq;(l`!$8LE!qR%~c2U^*(BTw#kUr0j#Q?p&H6WQha$6Fwim0Q!z1ahD0Q^
+)is^V$Nz-Q0_dov1dsN%zpVX}`mPZV=|SW^4d-4sN>(xb|Dgg%R(aAe0jVTrg@2U8cWMXyo-sfp97yX
+=(lb8|kTAA0IIuhC1F;y^LB+sQpOW23k4U+AhYKuF|pAzQ;PT8M7lh<T%*eTz7_cUAz+-4Uu15Ns~S$
++_snRjYxLGiEFAVG442&Y_(}4_>A76;mJZKvw<sl#ZQ9o^}9CWw4bzw0xf>R9=nfkhmQCCYgTr0Onhz
+D4EB^#nEV9mRsla+^>FnAr6JuWntD^E1CH!;`exj9oDrjYbCxPwQ;`k&#RU9Wq5%K%VTHz)U`DDNtpa
+pFH_wi4t!HcPt#%)xuxHL=WQ&*pVRFp#{2Tvp1Y3m>^9j#Lk}~Z7Jqg?qcT-o$;<j?Ct_s+UB4ThH(4
+p|VXz4*ZH;{%RCTNXzsXBHie;i>;C$=T@D3~m&v%5QE&fOjMpFq+A!5@?2bPmsb8X)sLIhOhfhIdVy2
+PMz)&4G1}8BK%<9%MjwcZ!I+JEO&e+8!f)@GH9!W;~u%m~|J}ww4nJ)p$pGMV?sZxKi_LXtIZvno}(>
+)@D^T+EQ5-$wZiPNQA#-v~Bm+N!86H-L=!R9H*f#D{UM>BGz`U<9&Sh%5#*#T|4)n6<b>l&;g~l?B6E
+e>8MNt-fiNK*!Q}C(6JO<2(gXh;a3|yj6Z5QrdjJ%XX^~RGj?tGq{Cal^3chS8~0vsUEIsT&!&r8oi<
+7c&&;Zv$y>`~J&f1}y~G2oPkD-s`nt_?)l}EcL>GhXk``@PDU<2jvDPcCb-(j2tQzUsAUxDR9Yrg{8}
+<7RV*~FP|J%(DAQxmqd;gmw^%rFIw83ONwr(HYYS*fF;$7!V+mAL!#*!_~RMQiqzVOe&R}OB}?Ue~C>
+?xxky};j73qyJVsrdoIO#YN2b+#0$?;btU;MtrlqWM6Vz!uSG<<9isp=@*ppw!_@y}sCCC|jH8Ku*2l
+(D{Wt-@fd7)#2UQ+uy^h4oB*}o4SL~=*^p82NB&g`}6RoyCbi8(${rI05#`2KO?v&=kRTZ-#zPo$sDb
+XcvClMxmk!KwzH5X*F5a})Z(5zoJJ+C_xH|4>|N_{5pQB&8!e%SkJR+Gm5&7a{{c`-0|XQR000O897^
+_9t>{;I(gpwkbrS#pCIA2caA|NaUv_0~WN&gWaCv8KWo~qHFJ^CYZDDkDWpZ;bX>wyOaCwzjZExE)5d
+NNDad1#jN>tTO`mza4fh0}VVr^P9+4><3WLlzap|YrvR8w!*e*2Cuk}2CsQ-6r9<30EC@OV6BFc|Cre
+(L3H!73%=DHjW>6caKoL}u3h+y2=xi|4IAAQIkwItAXSx>0sD$#}gK#cZw;IBkEz!EpHe@xk!m5GG4d
+a|R!scTkKjB9M&1@gG-jK76{2t(mgOSS48kCzr47`n$KMXBU@e#%s<LElL^h3^1FWso)E!i#krfu`1^
+x-pmb(Ma_j;1%D4n@vp3E0l%~5Ef;wN7j(fQOlhH&BDhqdsAdtI3Bg4KUrf{&&0@mv=|jx~Ra*WVtC%
+RV2(Glz2tLmX#bix0c259}D$3UXjHxu6b7UjsHFCU@rnD^66prAUAo*QF<OUaa6L?Q+uo<Xj&5&RY6j
+W1}4EPi>ULt+pXxZSBX0kN<L#rHeD!yt16PkUU3EosW@{1nQ(+}@(U(n${CP|Y?0=-W_NaQ~g5=OQjR
+tYDb_Ds;FL6C_lkV%P7HAXKxj+4HFhd|<wg4Kd&iG^fKTCL)8I3sj0x4CPcCP<Ejb*@m*hs0M%Zqh-1
+=&7xU`18tNKo)d{QPUQ=1*fYnK52?l71d9;GqCff%2dIt&fQEfR{0!SfsfIDyxj^&s?DZdgz3sx+5?`
+JR7!t~Q)65sTaXj@sI%`Gt5-2TG_%(%<A%-_=9h%sIa4k^=1(dLIw@JlhG4n#<ltJ+ONm!f(XJ35fH+
+pz6()^hKbOuGo%tmg_+_^a_G{7hp#D(|$dZ*MzwLnSbL-HwsCCSpC2ugUi6QMJQ!G#XAXl7hrKN?w#a
+=EP)+@wqb=X4QFq*gN1!Ql}>oEFhP5ZK$%v%6zyOU)>WY4<kglkyS!@FJnVO|F7V^%z-o#MukF)~E|i
+*35=s_FaVk6mLWx4Ku71co*|V(U49QTN>F<%9Oo<1T^2o>YgLz*8r4C6K@~Cukc_0?(ZU&r>zi)?YY5
+YxhM2yBS~9RKe{NyeMSh`{^wI;$Wp8)33dlOx<fC?7}vSZhbWLO}U&$EeAF+e7wVmSH7s$r)rh;sLxh
+M^wTbR>>l|1%<Narrhuc79VP;Eg+@5Id{<#&)Qc&Utg;Isyo8Yz>yKcn5tUIkGMeYO-?EwDUqV_mNeL
+8{y_^$FtWXr^pU#K|?W6ve@1xhGlR6_t2>bf6Te7$Ok^PP(wuu^RlZ2hWy}rK*FY_(lh6h``q3|Kz_M
+Ep}z(InEvZxpY80&cm6<3I_^?1W_r{oPCT5WiEejc5iY}4(N{R)OU0h+0XmM)UVu%Jtr({Bt4DfOUpT
+d29Wg99w0K?DQb_W2;(AB=_rGc18r&2+krh(nXJ5<&0eUK@WmVf^>BD9hj=+``tO&z7qOW7yQh<{EiP
+_HlimydwKrW1qZyLiSNfOR#lh`kn=U@C&+Mt{la{jrexKPJ@mFJ+51pB>SsjRmP<4XID6skM*!A)v{z
+Mmb?tYF)WyxbDRx1lNC|;jYn;%=GbOI)+{TKbXlMkJ=6=$w=q`ncGJv^iRW~|D=?OErgQ_5zV;>VoSp
+#iVzA=zWH#<tykt6f7>@_06%58>Kx_D@M^*ilvl>Td9SoY+uN6qbqNr#|q*qa$y#TYKO^Fw}XEJmFjS
+Vd_o3jO5g>VdcVTLFwmRMGGt(~on*MV(R_%fj5n#@ASaHVG{jJPv49$)Z^VcdQoPILr~WH7Ol9(b{I@
+#!N}ak+(_E752Z_}dh{Ict@<=cPX8ni%_v1{BKxJN8ya&S@!aB)EOPjnKZ5wN<6l(#4IXWZMJwDk?Ek
+{YHX^Oiz4z?ZzzP$zYZUT)wfX=zf}}MOCOY4J0e45$x@8TM*%@cXo9h->JMhaJUd#`q5GUr73XQ7}sP
+*q7HNK=h|LBIvH)2+(hm|A|V_dIbq+uw`mxIa~fkTI0vql(4yY*5bVpdd%Nmea$CJ_#fi~^*{ikeQ@f
+0yp-1zrz?s4=Ir^{`^sabJV^8({COwLJ#<3rcdaKS@Z2Sa+N5iK$;|<_Z4;HQhvMo4mP@M6c<t`@Mqj
+)1Swk<$wtd~oxw9_f+R-^Q(jO+`psr{ARepc<JwZ3zPX=5eq>EmpMZ_pN1NVA2>MkN^>8a3b7$>Y(@h
+RV<SE!;c%rnBC)d+i;7O{cOhQPGeR<L?4%=}Sez4L$o0fyyw4dM1NS$1W_bxP4K7`gO4}J!x>b8NeoT
+d!Qz%dun1!xH_LZ)A>QP4!agG!!x*Pu5Ze49`5`PP)h>@6aWAK2ml;P_EwW*CDch4005Uu001Ze003}
+la4%nWWo~3|axZXsXKiI}baO9eZ*py6baZ8Mb1!URbY*xhaCxmfYjfL1lHd6&<|J!LS};!JZgzdF$Yr
+1HR8s4WU6JmQ6%`T$h7?vHfM5VUipBi)?e2MC1`k@wE>p2d%=Ejbr@Lq1qobn%gHQgr+48g${yHnRL0
+R%b_(@Rm2O9mY?=zs`?=%bpX!a?%<p0msK^i{Z6)ToiWnPuOoH+}#{IQ5PH|31I*I(K6?Cj64rf1VXv
+ehFiZ#es+xM3v^wjL9lvv>b<`TgggE_{h5i9?<WK4brV@j;G%`r-Y@A1^)<2N5rWI1&Ef2&5aVi)_o{
+jK$kLD@t}z7IC`y;j<dZ<J@1|@ifW`zpVrfWF$NQl<<cd;1mAvSd=Yd;Ik;>EENY}%j}k?8uk)@c<kc
+x-H#vM{q$jR`SX{L7YBf=GEOw?hL?*~mL-cUFFpDdrzQRv3<irukR*!*J7-tJPiR{s)$kgIBfe%_gh9
+?1FgAk!0YjK=w?P`^1z*Px;~8nc;AK^$3@7*n&yyhJqv3o$^w@CzaCSBv`)p1V?T?wbQ}ZTYnYUN-re
+B#yBt2FP=O^OtE3w-T*-3-#ufb0Ye75>M@KXaHJ|F&<8aQ}1@WKFB&zJlU1~}M08~9rToRrT7eq(?)&
+j&s>z~biFz$XSc51$SE!T?9fvw>e3;G4(i0v`>JjLg42oAOc3_Va;%Gr(os1q^}X!{_&l%a4Ei^6A~>
+M+h#(a5x;yqb#g2JcUUh#O`DSzv=5(><9Bo@H_}_gAL#5eZqYjW=U2!kFHKeJPor5V)s~F@8T3T6?m{
+8oQ!~zV7p5ASPbBoC?69Ju}t94`HFAibf=lw!xO<njK(j4r!p=PYL8%m8WGGPwp!Csl)>>ayVyeLWc&
+e?k_HIQvNi2gTP_4!@g%!vv+>|~aLg{@DR6WbXO&=gu#Z}^)z)Zsmw!~EWT2FIlk$iKTD7dq01*$u8z
+wh~@-gSItF2?47N>+Otcn77WF)W8fNoH-Y(;dFM-~e}krx^01&GBVizN#;u;V7U>jEZ}87AVis0!f$Z
+k_>);`N%>xB*Xj6G)=;K(i_E(N^%}j>BFnWshr_@3Z1oux$lWB=IdL`0p?O_Q{g}{w9V|sQ{dslyOc3
+-(OrXau*InGO3DhMINMYSQ%_QMw=n&KLZVloQLrmWQ3{sFyVnH0gLrqYte%VV3#$R6FiBnz_~P39+1q
+I#zAFSitK<?X;x|rfU>^_{dm$0ic0{--}q;iF*G9huGCqug+Fd!cLq!-yI`C64!8SM67$`iUaIo@rkz
+r7u`C74R!9!`0uK-+s6ko7Q`&?S3iu2_m(mC3Uw$Tbz)s-#0r-Q?vYds?AV)x}jc_h-7DQ1@4`3!bBP
+9j`vHd-Oya4}BR)iS8LY^n7-vl7pu!JQ60)jq4c5*8~fx5mA3UC`BoP$rU;v_B~SzZ-+1~QGM;K=Vy0
+A{}jH5MCMh+<~z8WTP+R)DGjQBFN#11DfgA{P&kjxZZT{sViFxE3q8$iRJ3V&w(!B*zGGhf+7(9f)m%
+O&n@fLt=L)9TfaG19Vk-3ua0+3Eu<+0)s!pA|t{xc>WSaeH%+<zFn<7#>>zrwkn8psnkC>>La@^f;`6
+vQDl`RDj;D<y%rWRMVS;dE~LXsGeS<xi!HdXs28$txB#hn$>>j^*pl1;_9#Q=zk%ga&j-I1xL|}rm&C
+9PA;=jERRWin6dN+&JT9cMq&G2k%OCH8gsI@pMyslXwG5Fb<{18H@#INGh5~q~10uqYrVxZ-#lrw+nL
+?xBa(xOl3*ll6a3B&-@8Tj$$(P2C7#RFQF3g%j0U+&F@d0I16W`JhI<$5OVgq6X>goX$ARNTjeA22$W
+oZ@`9<E90+c&TVQWJ3*#bRWg&=}0xM#hGoZ3aV9=p~VoC_+1ibjUcLN%8^Ci3J51Km>(RiPAvHhR!6a
+m4Gd>D&-R1Dx-3r9O2EIHwxn7^5;(<>kQz8?S^4KoU!4TpNFuwHimVAunlf`0Q)ahRdX=i95&&6ETk{
+)<}jk4#O3+C;7Rbn?5C@>dU|p~>5Dy9C0!6@*blJ^yCBw@#@=BO%zHf9%|mJ4`r+H-2__Koc?(1wPfm
+C9c>N$z;@oXsKF)a}xaO#yy*r-l=a6xLA%ivO$VN0@$1e6LLw<}XyISI1t&&}XNL<z+>s>7}QkEZ^#_
+{BMx^ryQ5KT&TTC=n}p6>T1C6oDBjSp+Jd3X~P%lX_Pgr$rcShxdFovDGHI}n<IePbZd1HZTfQ1PgNK
+ez)>&8UHI-GPl6c;gO06`}@?-2tdD)WFG!I|Ai{8hPOkKxv=`UNwmPst1M*RA%7F9e{LQ4g3a4@(INg
+cjLW}%Nt0oiX?{3LuGBk)l#{8+fdJHcjZ1QR=exHUd|b&Kr(Ble!>Df5G5v43tSQ-`l{LpYg#<#jXsA
+D5NaCDg7``kXM?&lq4onkrH6q+1XS@S?9H%gOY9KaeuS`I1M9g&;p)}onw`pLW(JMu8NN&k&EV5`wmC
+HT2Lp=E%<a64%s1U!IZ_=tIUqAc2<Ji-4;ZR_nP{h+%N(37^(MHaxWA<GX-Q~Ai2<aD^j0fWC+`2i_!
+#FUc$Fkel>vIDEYNv+gw%0!TrU5Y7b|d}?NTDQwpC9j`LUQu3ck-oRuv&fe6tyo?L?zWRhnsx`zy7pq
+R)!+`Fy^c@2~6GUw+=*?sw=@d;FfBrtAG~on`wG{oL<XL9rjtoI+Ls<)HR`jR`9}LscmQ^DErjLa1|A
+P-?{j6Xi(lc%&mp>|mDGlF}mPc2s3RE~AS#NJ=6`mB47Z1QwRdF<AvGNW?^IMCXFA+macjBLj?Vm+BO
+KiR*{L=K@RGCDfZ>w#c$!mjS7eghHy+6{jv}(W;Vw2OE5tR9H?EDytr_vPPkcO<iJJVmDYDjWu(arv+
+^3`uS2V3h-ob$wHHbG`9?Z7$_NZ1$dUrI^C9hDE%vap|U7lr_>I!Nkn5irjzR_e&0npnN~UiHo}nS;M
+>YswRw%3{IJHf4b!CM^0KJ-a*5qsENyU}Ou^OCEYY+cRft^Hb;Mj?aDiwIXLs3D>sfi7kVUO@6UDAUH
+Bz<R43K^oK;i)2rG#9PF=`1eO}#GjX-|8%wg97Q|AMAKt|!BjAz*PoRL_PMG4i;Y7RMwLl~Nb?Kvg+&
+z>aYGk?}+DJ|Ci3?WYD2RH^G%$}7Om#&HkHO>G><a%w$*PD?PIEYxY1ss<tQB@wEE)+#Ux#jPoJHJ(n
+|Lt6*Br{&OYtw&@73So>Vo=mr6sVYN2YF=8Y)6&DBDC02UHgUZqpG#ah!MZBQ!897P>^y@H6MgjEx(N
+qv+p7$ymw1|q!z)NR1kPn?wOv8danQ61X$kVXj%{I}%!XVqE`-8u<D7Kh<DDx#&=^zphD|)#Zh<9TJh
+HUBacEN442mDFWAPHEt<-9*ad!kB+51u51|1OWXuw8zo`s_?^|t=fc1qfqS)K_Iqurp4t{}PYH;mKfa
+kZ#Z3KekmYEb<^Mri~*(#yEOM^KCxRS1F`OnQ?folq}{`c2suJ8^WB=rRXoVa*<XAX8B3XAnVjhg{*z
+|4YXxqz36mjZe<(tsaG`yI#~Q(}e8y0X%yTk4)g;4=6is6o=hbt{`FQ3+;sdAav(779I^hz)n@%R=L3
+kJE#Uw8;0s8%9a``N=7AxJV;GHr|gWzjWyD(z==OqLP9jYk))m@BSK+AhATELF@#SN*8+m%px76_@4r
+y`rtQy&eIH}yQ^cDM<vkklzd<(1n<Uu1p!H6-23JfsKzdqBO3>uGnUop?!>*cHYdnd!acLS?g0m^Z^f
+U;`slkraLUD3)^!>V)fRX@Nfn*~qFxN^RefC31{mnFEe7(l@54Kt)n^2bV0#u+U8AQ%xZ3nE493RFF-
+L^M2fHekS!|#m|-Flw-XIjtc9o8^bTuYMdUa-fkqIeO9w;(s9LBKwqkKA!5pivzpPn1wf9rS!B7HMD?
+RFvpE)DO-eNy+JuTO$|>y~~M5$QT}KgpQzQ`cnkP5nY1mx{|Cbi_0L11MIfp89Eg-cuI|b$x>wvrKjw
+_;e?mI92rP&f^v9)iS=SJ!ZgQYFJG!n!KzzK#_ab_c9JDuCayrwKKdW2xxkzp2R3PKHGp*n1K<jRYT2
+QFj?(GeqXB9XhX$yAj-X8#wf*)pt0wetYh?p~B3Ox$b-|&H1?K^#$+!m%&!2>a=Uqsw?Y^l2Yp6>JX@
+(~u8`;V~V77Wzk2>7*n+6lkAhH3QVFTU@9sPV*lX}>w15Q7ddQJ}#JCZj=vBw$;jVZ2=S}4Zs{G3hQZ
+h*8sU!(7|0Itri+mq$(q^{YMdNy`%I|wxdQoX5qSVq*AsPZvNX`<G6;DRnfSYaiXwYRw805`TmOnVfe
+tO!$1Q!Nwqtfq>Q9o;*c0jqVhB%DTiZn%x6NB|~U<GC5O{jKI0A&Sk4GRYDA+33*3c%+lK&+wx<XhU!
+4|09dj(be$8pRV!t!3Y*ABD#vPbw^*|@5wbR(Laybf3oQ}-}q<a7Q)ttj#qFu9i4fY6#Qv??LxKfYBM
+(R;J;xlC)FVGfH_5(aZg9JkQrPwO5NS9QD<hjO{K;y?@?OAfve#vOQPX*n@a_Fif1i!obloX9hcyt;c
+DH3EG}Vl3!jP(&two?T=t-=Fo(q$`c#Z~W>W)oBP}v;vZo?kD~XG34>l1%gnlM6(Wky`mS+DpWVBumV
+;ccFY{LV(GCaoPAH+z2SFqx)cPC=MJI13NST={&gIS&q>G8PF<%)<uowXIQwwpuxDHHJBe7(vZ1kd;I
+P-eZa=uuH6d_O$M=y1L!?qGH;BL0t<pg<*Qzb5XeA+Hu_>>UgmO{k60Q!{MTs@goyjE8h}mX}{uPFpw
+6(M!L8t%$9{62_$t(XzCR(~5UTGWn&xHu?hZ)P=cA19qq@3WwJK;T+Bou4#0I53dcndiQJeq-EwD6q|
+EM8fsQ`evhA@)MZwy|1J2h6;DHMy3KeAg02?W)9TVnw@udS#0D>+sJ{7KM}G%<YQWNx`jhhFNaT0&*0
+;Orak<B1sZpmRxDlatJp1y8-i_2A?n9Zm6{E&pEV21`(<F`1E#K1Z9li!vqQh;q+GrOJbFW3l@)WgA_
+T3C<%XE10(Pt<b#ES*<ROJQgWO-kEfHcCQO6j&BkCYF{)(ag+Q5O;mHB0_ucKP|k=NaC5GF2vO(#q6n
+In+k)%%Yy27sYEijJ;ad43NGhib2c{<u_+WJ*w}rkH!vW>@Hcg;j9bVzc0WG@ZPpOnixVB<z%L(Y}h`
+Nqhq=Ge%Oi$c45_y2~>)COqE>CTFz^hWi9vy&z@=>pJO%;jDN*<MzUhWr9JehNi5;dPa^bXISR&x81W
+QbAcI7OUmKWUOd{%5kX0(dv{n(OpV_rTTbWH|pqq<xFiRMe_<cE_zc~M+{qvXezZ~2<;4`%6FV0`j)w
+P!%OIs!G*BLafWkHP(`Q$aM?{Q~tP0em|aZ;}5Rz)FC@L>`aH2!<3-Zr0F7|R6hN%(>2P&{IU-&A<rS
+NAo^aj0#_ANZC!f2LbnGT-+*k?HmYiE?!|n_PEJGxbS<J@3)Pqe7Q}#^Y`_wM<9=>RI+5nn>J{f!LoF
+#GKpS8Is}C8rh(8sx*zBMO8Thj%VHSX*F1HoTy-c*+7pOK&K3E3d$>qb!(c6Y-N^it!wU-F!Fb6CM9o
+;mD=YLpXqQ&a*zX3+0-}9Z|ZZ~yM8Ac38<9ji#&--e9fS{evQ)wVLg`}lzz9NJAssgaEMPFZ_18{(qY
+Gu{1c7C{zAC00C&un8|(GbFalVl4w?&eAvb!-{sDs>j+ywOyzIQk@($7NU@7kvA(npa1avnU7ONsg??
+@r<lpu{v3+jN5)`a0J3zo=C50atg)!{~nq%}QE3qMjbr;fP;vNbHF)j{y?Hp-I-(6*6Jki=oX`Z|q%0
+Xkf&51IB43kN-F;~}?{+mQ5hwH1Bri6~FU+?Dd<M>(h5`D7@P?YtJPvUuzk&&~hq8mvP_4|sQm{gpp{
+EQ+k?i;zlm=S7t#Q0{JwwYfNWQO}^oTjsE&PgNW#@Hk&!Ss*Kic6y_LI+EBtX+~<wQ=0QI1k+Ukth(~
+#YW8Z<v;SiEI!+I`uA3Jf&F3dV_dJet6{Z>X2v>)m+K9UOM&W_oUT&Yqj6&7wj&v<97qiT9{)K`DFZg
+wqGj3YhUxMiu%}ncG|Hj-NsJ(VKh-297b0**XpcesPsxU}|d|63d#EY@#1t|=K={}OXmVS`t;x!h&M7
+&)q<547RrxTn)UngCYVv#Lgzy9XG4$RxrF@$EucV1o`E{0>zFzVXXDq58toR<RIji)FMOY=@3(~8y)d
+b$DT$WhPN4|?XyD_{80l{!A?nQSb8aaeutnQC4!)Oed$A$#EHet_afYYRZh;YZj=bnXa$gvt^Rrs-Ak
+5&fz1H{BzmTZ8ho^D?+qZ?MSUfiN#mdFq|G2kWX-0!2j?Y-BiIaTMF!_N`y1qQf%$ArHdzeTYKdK+^Y
+DDEUzT5CGl4q8n56!VqpnFe^=+tF)T9W<6us3h(<3q;3mZGy%0-^o5gmNun-9;sqogR&>WeU%)KzJ<M
+W*7nRlJ3-u-!zEFrnsUugjVskIJe2ZSc(}l?Bik87+Z{2jG!v{I#ds*^*GkN{Txzke<BQ(JV#FO{!+Y
+0a<n|53iKr?vK1|Gq7-yE>dH}NlbK%ZsO-wl|6;tu|02FTqGTtRR;uF?*RD%I~&nXVh?$LX@I<1~^U#
+kbiVH+P~{9i<F9QgKIWEP$wr@5w0F7+dJ{ZA!YLC%`$Afc)tLPxuDo+eXUK&17AYttxusHFA^x`d@Bv
+^DXmy0dVc^E0kYgr#sVhU7*kl5v=(_=Xb=)sG%J~4QXThr3Gu$q1}^J7`AmrHNt9K%Q*I2Bt03!0U=v
+j!`{FXws{Ao;Z3P)>>TPJ5cBtor<&5vzsWJGzka0!ZI()pH`N^2r}2HZ?_3`c1LO*EmjeYDj7ut^)*(
+{9&?8%i_OU^a6XN|UAU_&BODbZ~RZRkWZWOR`#>!Tg4Vki@Ues6p@$)QiCo!<bh5zrSjpgKO^RB0{@f
+h<2f-xk2HKHdtssi(fF@SOGsnsYgh_CPFXmr<#f92Q-#txD7q5#<u_E^|u@b-4J^yIcxzZHVF+`taF&
+)Ei*E6|Qi5#IMX>$7-Vw)BkjM$KrW#(E=((nIv1H32g_C$<=DX%bm`N{EoTet&Eu!Q-w_<VK+`u{y<R
+EY&Bj((l@<6!)rF{;N11We{@U97##*-p7JFb_FEdHDq6p>G$=OKnX#wcOz}Bh@fo<V(s*ty3RqzAwXA
+)>R)I}9c)Ee9K%wU7rycdM0z_l^LiRljwA%9aID5PvgvdBK#l?x3)lydHhLlxhgy`Y!9M{|O9KQH000
+08031s8RydFgR%`|U0MQcw04M+e0B~t=FJE?LZe(wAFK~HhZDnqBb1!CZa&2LBbY*gLFK={cWpXZXd9
+_z<Z`(Ey{;prac?cw>u8?NHuo_K)By+Z4MLZ<l2CNBeTB2=kGHH->UFXAo`|e2U&63@vz|_W;$-9U5e
+#c&~7Z7;XyTytLqm#K*D{2f=I+13{l->R3&=c705fYM$b3pDkd45y;?vs1E9m~I&D3=n)I7sDsr}$!N
+2IRVUCFf^n-@iUTJO7T%b_AfwuU<G}7+v*=W{h0^HvV~Z|ByJCoTp4^HXv6IKf3)7x7WkFhan0@GG-{
+xbrSSI*<h~ZimdrMnS5d*lPYPePWWmql_90LN0>H-=LP+OnMt~oAk0Lr%@HPp#wfU~WsVT1QfQg8f;^
+SERQ#C*!DK@7d@>;y<YU+{c-SXl%jCE?X4<4wvug1v2!b@HS~p!5m2dIDnz-lVWVA8sjj>)a?6V;oku
+IrNu#9ZESxVTVVpoI$7mK99E$E7YxF83xN|EnEyG(NqLTRfAqN1n*!~yAWd(Lx)oQ~i$F+lO;0w`m1e
+^{hhKJOE2SuHmzWqktTAg@;eA0|=&LDB?XWd;(Kdl)Ll?AE~eiRK$HxTwQbAo%b(Vl~(B@kb_G#SM!r
+jys7(@D;}m29|5~pCIDWOD(syJf#X_yA7`bq41w5x+RLO71Iz|)Nm=R*4jWsiG?GDUkcJp`xG66r=5i
+f*JL`iG-#!F<IAh}2o|{$3_`?@VmeJMlXQ`iQbBTRd?A@Jh+pxEDFYE>B#2Z$)5egEt!bg>2lkn%X&)
+S|Q^jY%g<e@Qm-m@W2h$u$NY1q(@9evNKlQ?oAjF8-N&@K!%7O_LBQ#Cf8qOa$nrSLmXc0XvJ#jmS5J
+Ag<zTx6IoK6W?3EpSV=kTLX3KlD?SG1IU!6Ac7tb!D6P4fj9+ALRu&auoCAxI*KW4g(q3c?|9LhRCJ%
+9N67Vl%!=I_ipnO{+dxLh;OP0kv#}<2Ty6c1eBdND!d}L!?<Dy^t>Q(cD%Z?QNh~22y#W;*%r<oQO)%
+ECW*x$XW8{P0*R_;7Tt`JKG^3G1>igce*2uPxp=Bm`dK_7vzRQ233_{GU0-o$;8)!(^K#ES^=m!&_Uv
+o_FM7?6oG}15HyXFf!WV(K7je4-*AyKT!8v-muynmP^@85k&#-5nY%b~hJQUOp`{IP44V~l<Xo_%hJu
+;ZssTO(wJoXS^5OdSHX$Q$km4C5(3@)zO+~;xRHvMWh@FGvd(AM4NhYm8t~Hxwy<%FdG8ZoP`d{P?3j
+Qr<!hWmT9e6&5wh2hV@EdXvJ~8{A;5&@>w5hTLgz%>(AWRh2wgBM{;3{4|Z?l6-$7-`zlsgWw8Sy0~A
+&ot<iDuNUUGs~k9_`~a)y0Q>#_~meVY?xcwXqcCnvvfzku62kyA_buJoDA!1PcC|rF_m=)*~lh_Q<|W
+@z?d<mg3DuH>)e^l^jE#>Cn<?SZ+okW`!!tOfAg>V;MHS85dOTNO)A)(AO0dDs0C|73dc>BKHOYKLS4
+Ub(fNu9k7-B1Rpo>JF@Y;ox$hZ%2+{z)!GFkx^AZi#XR5WWsM@urLHJg-YGh!QK#&%(O53HY{bK6a`o
+r=b-5P3-4hq%!MPG=xcEzhO@&^H=NLO+t)9_KAU#KXki!$yjI}?Dz1;lvcW|sMG*5WZ#EB1f1N24jL_
+He#6Og|oszbCD1}Q9ot!)UN9H<+m&e4%-gc5XEwR@7S5G~sgTff*6zGfUTM0H%@>L3^oAI8_055vjT@
+Md&B#6lj1k7YG8a6P)iig5?yM`Rm#E#~Hm+TI9UCskwjB?m^80I;ePE^o%e`}zU+Je6-S%fk?Cr&f0m
+_N$2li;9!t7!%elTJ+);(7MMRysxz{0qeDrYsFzCw^pZ6Bezy_1oR_bd%QbO&JNt<9Ano-&hI?^Zv$G
+HVC7s^HC;PzHFv)Oc_C9@{}6VylX}Cn_l6S1^0=!*p35!VK?+En^uDqga*>r+Fc1s=osu_I`GsaS+sx
+69RmcEHYwbmO<3JOL04B1iqg=QX3WD%NM<+17ov66~C_+rIn$&%=mu)4|jLmUkz99SA1^{80{3W@FoG
+5X>IzQVeKahG7Crm})u1qyln_)*|p*?)<jT}zWSH<D4+#$ybRTn^U!S}%xw~Sija3{Tl!-{m6VZWdK3
+s6e~1QY-O00;maO7>RoS;bWU0ssJ{2mk;s0001RX>c!Jc4cm4Z*nhid1q~9Zgg`mW^ZzBVRUq5a&s?m
+VQyz{ZDDe2b#N|ld7V{ZZ__Xk{hnWOD%#v`!AwO$qO_A>444FCqQIAFirmEQtT}cRI~&zBemiF;ZIY#
+3fqq$ZzI*T9-Lu#0^#Z_Owp^rKSwrVKPnoqmH#B2vp;MOM6q(QY{q!&JNgr1AfJkuRAfUtmUD&L!w9F
+gDI$P#qacxI%vigMK(b22t!=vF#m@UCxbGWGb0?Sz%g5ezA{`mgs>$fQ_VWfz;GJFK@rti!1&u1s6=h
+IWqpK!~BG&Ja;&S0MF6f%*~=$5NQ=d`ODM4IW`)-r-1h$1Fs6u|^8i5K+6>shCeE0@Gg%rYKXHj^Av?
+|pkZPx@q^3`RiqS(?2eVI3ZqVQF3T0U;7ThYH1HJQhqw@iog$-|}BJ1dlvv@eD>D4#l1NDC`4M35*-F
+FMFlEYR@^hMXtahQkyenB(uC<f?*4>WX8ZIk^S{oP1;yESbc+g0A^ae5bK0fII|El<rb=7#<2;N@SG=
+Dg#E(w=f}zvl)^1KPiV!GgeRjB4C(7NoBvQOb>k&X7UEBs6wGkr*W|5BLLdzf<C<LBTuAOfeBxCJ>Lw
+pWLJ1p1eZ%EEgo6W}S!~2qa$DY}Ta$xzvOA&1E~RI>f2dE~a{Rc^ukIX#YGl`R9>p?rBkCosFb=RA6!
+Q}AlEhkSv}GHrhC9U4vBA;6eBo0ky=Qx-cT8aK5kd!`A|AhR<ydg&B3rtcX_@S3Vs=cnQ_ObY3yUj{c
+QA;j7{m^S!ueDR#dnYtPmvTGNgDRJ^k%ri?7qhgUGkuIX8AZph2qLxr=&7ndE<1E$2@dzt21`Ptay{{
+Et74VxS(BT?gpJ}#cNMi_4F<m_#Tk4wZ~-e$g-|51jH=7WgGnM;oMy#Qkf1)+qS(;caW=&{9pX9gU^F
+~ypSqqvR2TASqa9CY<xw1<Ae4!l4b)C(p6a9Gru~gW5yR^b%D!OH#fTKvU`EL!>-}bCTkIE<iS><f3I
+^@)f{xa+--XQTjxLO+iJoWr3?Q6P)h>@6aWAK2ml;P_EwDs;w=9L005Q~001Tc003}la4%nWWo~3|ax
+ZXsXKiI}baO9eZ*py6baZ8Mb1!mqW-f4fomX9N+eQ|B_pi8cU{G=uLRJHJq1F#++Moe;vq7BQeTWQkL
+=L5CD3YBS+ED}VZ|}J?Bt?qy2Py*=IdkWJo_p@-^z`(E@F{oet<0?n(?V~BwNjf<+tls-|M=&`ZN8@V
+1lf(Sw3fNl!b(FQKfR??WzvLRbRHMwPOJ6C&go6_NVDnm^5twg`<_-iXpr=wc7?1I+X)#d>Ggj;{r2y
+V*P&OFsaWPl&gtjtU;O?*-@W<u{q?Wx3MJACmBHpILOV%yv87U#;qq4INuk4Gprp2Cp)I{_79KfNS(P
+>NYiXA%x67im@S@VXSR?FGD1CBrvRsNRTQ2E}J_jFd+UgE&uo-8<AU&PsQTsHWyC6^Ny7+an#TSH3!Y
+6er^p~m(>C;A;PWnY<3p}bArgv0SwycoFw8}C*<<uobT>0eQDZ8P#$dECWdmXCCN#qF?sDh@-NE{_&t
+27PigVd>vt;;aijs=~@55iap6}F&%saO}LNbTt3nEqGjguh#hH3&XrQW!~jfm04IQ6%%YNL0R#B4<8|
+;Cg2b`Gsc)Uc=5hFSJZN5IzAc4r4w?$i?gHH}Bq2j!<r8wwutZvb2FtV34X@L8YX4BeaMa;0Rx91eNW
+aI(U<R0qP2pCKjaxvi_*xM~mMuq+1+=Ga^Z3GN02lysWz*Nfdi2vc0=;EK3V9FA*8L%Vgx98|U2;8$_
+-r6pNfzk_47DA}3^8(6tjW)yiXLl*m+6nVq+Kq9~}>f+!l-o<?br+f>8{_FyI<-l9}&6(@+xDZh$s2_
+sSTv$C*_uA~2=h3Q)4CW=D(#p~zPwCYT;mA=(g>{Z@vRJ`FLn5rxbwuHbo;#PtKzT)jpC3e&G&!|5;{
+$1mZiqtWH)5p$+ewme)GFGXA9+g9DmQq<LMimFvDycKU2WGFF*h?=qp|!f@q$0bl@nYtT)b1QF?kt@4
+S}_+0`HBKSE^rGXQ-HE@Jr1r!Yx62I9*g?*^U&{{)b7y|oT2P;IWjU!Cv<*Z<7K=rsctMj4_O`sZN>K
+~<<EO|dYINXMU^GJ>aQ380oJub^S_sO!GR`JGp)3v244)%)=kRW@<Yoa-J;WU9x!_9F74^6s~LOF0kq
+ZDG;GiuW;Q^_pT1@EyeyT4dIPwnJxxp)1~~OwE<|%0(r*R&SE8Uh#}JA`WES!U?M9)~`_XYba<0S*>_
+gs#Fzf)NTa=cq!w1W`?-Xo=O?7~YS|G&u7zNFGFy?j-g5fC#*Q@TZ8Pysl6f^?Cgr?&T#yo-5K3VzIc
+F`qmrE|9$YFTEmJ_;5KsK9@Gk7?1%Ow%8&>^Cp^?P<w-FL@sfeOt2q;|{(cxh?Ikra^>hHV&=mV8@PI
+j5jJVkGKe+XRfX;Ze4v_CBOnkj8i@DIa!B~RCf(}!e{Arm0yr}SBNH|&eQ$DRh4p+-?R(dP%$&q&~BV
+_?J*PMac>=tV(TXw&Cbt%7|#a@eNhj!c5DqK;6*6P5;v6*QU?8f12TgNubqCn+8evLJZjA#=b(dTS{{
+tT$BYNx7K`dExew?JRvvHyR=pR;Y;&t-YKtk<+6U`gT+&MM{b6_jeHhFA-HZ70WuD_>$JO4=Z3M?V1#
+ZC-{*Ey+f}(M!XL1kkQfNGOAnxxY%PM!57@0IMcXv1tY>Z(KlHozogFPk%U4;LjjTA|z&b4TGr<Ij10
+tj9#7GOPvFyiTA0judWIM$5#@ChagyUO?p;x)tKq11msQ_A2n(oWCJkN5YF>2ViEDEg5zH|kScb0d7t
+C&1r#{od*+V>*1kvY=bD7r55tV1Dawx27Huw|w1{TW(H)3v^lXZ2;)vVQP%u%LG$;tI3^THnLar?S5a
+AG)2C!cG2to<)psT!HSE=z4f8)IHJCHd+E=Cdk=0V&HHLSSOInLuZLmVFo8IA9H)O`=7aK{|HFfW5I?
+)O8|En&-q8~WXapE#a+WL>Yb|BY538(_XNd>MgC)c$8#!yAr}G)21T9RSAv~MEdcN?h`K1>=Dmy;DTo
+?AcZe<TbzUL;QV1FJJ=#A@sss{;6%~|4zr+cOc;0=BlXYR+bzmE4XX6>#7f!qq@*^Qb#t@I7!MwYoBS
+{*3*|7Ph9jhw2n1CDzPL1h@CL#Vi2;G!$lztB0<UkxlR;c?Gc@6=#^HrYJrf}ulQN(U>gd`A0dKGbqE
+7`*-Nd(uk!h?S>otcomo+Qce&=)AJ{wGlt9K|QFU%0VER%H`8as_a265A)DLvNkK7X#S4VQdpO{#|Zs
++>1tyKSv6K@=HBjD9=Z#ep_7NR^vsZJMV1~v(ze}6<*%-;|HgmQZhIqsVDB$bO9KQH00008031s8R;*
+Z!lEeuB0H+)P044wc0B~t=FJE?LZe(wAFK~HhZDnqBb1!CZa&2LBbY*gLFLQQhE^v9JS$l8WMiT$upJ
+I<eLdljX$xaGHwOll|+XP6OAa?H>xQ0ZLONlVG%W{{Nc!#^selxRtQ?h+IAxI?d%x~V0Wh~1&VDO2v<
+(dnvoIoaPS8JXqM?Ea*>_59d2Xy#LLC=7bUH|=8CQ}`!+A+ryPsUjiE?0WOE{d=0WHkEW_+)f)$`%>Z
+E6%>;;+f{|dcYLt?C0Na-hcjj?HHIS^te!b!ron9n)8nzF0OvNz9O+c*KQao=fDDU4uV9kSscdB?12k
+kCQjEl7OrEN=t}!Xn6$j-qF}g?Ykc|$d8)&xpk8u4TSytrWUL4DD-;@k930GMZWPUCY|3u!>xX5jh<$
+f(aNzTRapk!&pRM#d>S?~!{Rw#jEWDx<_G-Y+2JD=<ifwol;lC;r%ZM{q_{^8-0>1v0O3f8H>HW>8kB
+*hcJK;J_1Vdma;c?`8yl20%2h4uuuHzr=zQfp`L|OlolxIX4X+!uJ<vCF<pFwF6B`Qp``zbBkLdqAXZ
+-EfJ<wdSiCrW2v@09)P-}w_(cWbZwR{61(zl?&c(1)&|EM6vVyb3*VT^MoD{ALxB8;kq_XG5SP#<wv~
+LJYkdnOwbcy%mc>!I=!0Cw-2@E}PHK(A($pIpYyW2DS<H3IQOwLk$F5IK$Y@=h=KtSe}%L9|{*^=t+<
+f3J5V_sn``YFlErNm_p%)522sBkui&rYgAs5?=mQtz)d5_NZmBbR4ytTq+lAl!Ixf2x`x7wQXhrGBb~
+*Zz<ds_PFx*IL7Jm@P!2i=s+LHp3;lBGj>8_Hw*bBC``n*Q*vNTnj(+z25P?8#s1W!9ig+H6HINyKxs
+V$O%e>5tODSw{BRnI?sBqWK3Un`&I$JglK;;t4CoIqk%>U!l$Bt=kVK^kihk)rM<pX1H0D%eIbr@xpW
+)wy|P~kuMyfP?(@GON)xDPOwCJxZ`Bq;cc8!0}Y=Z@NmdIRDf+$iP9u?!zLDS-CJd0N!%vlTo+nByF$
+rk>VGxJWga;5U@8)>24FEstAGRmhJ2TM<HejvC|F@wTP`mJ{ezaY6*<^Bai4d_JI{QNf9Hy@2duy&P>
+)xwYSd(r%)g_S6ulU!p}pm?&*d>X_plcsy=sr#Lnh$eJ8cK&KuLm=saQIFvxfgkCjdLMg@x%m+w~5~w
+a>6Z(2p$@t`M!*#l5^cdXt0FB;9k$XLHdYF-#;4zg30W=+)WCb3YoW=<7`q&Sbp>6;<?1S(U?kb)OMD
+j?AB`8ikZV^fEUSW@KDZiCL0M4iszed+%mY4&q&OewRCfvgsX=lQyN`mYeNZ<A$Q8Xb18Kxi$0|o|y$
+1!(B2?zjjxaE<8KqVmjWJF1<u;zO-0pO3|9#_hR2*SAaIL**{qb|`B9)Ndp*+jJf|Djh0Oh9L($1-Nz
+Uvj5k7}?CE&&D#$B;PNvzSYE0AUKX3l`a(jE5&AwGK!g{Rx*vMHkZhBxq=*A@JcOmNgSn$y}{<DTaJV
+AXlfn2R`8T~#+|t%yAFI)I50PlTFc7y?kf{7q=0$=E%1n%H40HOO+0RL;MI%q52GJ3Z#OWKSJXv?6vq
+ol$a{!?r3^uU4LAwnM8XsVL^G7O>u5sfIAn{ygZMaC6B)6U+>}5d2O^2oppOC+rrjk)e+8XA;{G7lQz
+ltH1?F+W6;B=zpWIb~c^Ck6c&bc=-g6!^SpVu`Ty-3x=I`YO+rxmZU6C;_O%e<!*i*tignWagZ3dQH@
+XW+0Nh3%sCCyYf6UQ_a@`F#y4co}%-i0KnO+H!|8%1XttJ7GNguBM|$_7<zdf-MOq_d(87G^6fuGB_g
+T|!dx{LnEc`LYnO8En9zp3Qnt2*H3I9_EuV-^%b)Zfee6;ws>9;Fzrd<ki>hUQP>}qB)1{l14#`xf-(
+okn=bI)U&G-TujTkXzu`^BG|!>&yg9YS(`8Ki@DnQy`ZLbeh%!TiZejBHpDs#QaSEbBv7P*a^O;;a3S
+p3D0yNS19dw&KDq0#=p?J$PZ*#Laln^eQ1dt6;zG8E_+-?yFnhwnthCTTv>Zg8a6dDimaOcEy=k$Roo
+0Vxlq7(IDc?fKC;L8rJ3qGvyYi~GX6&)Su94V-@gDxYF0d<#ecWbJKgv!dVE*Z0<?|NSjIIwJjF{qjR
+TQ(iIm}W3!X3cR>(tz(sDBUePJu0<R^LTK!B2ksn$K%Iw9!H5f)3!~6;|S^*CPU4zYBcGVX^GjmPwt)
+aLb`?wn>1SCcL12mMc-N61iwlj@|^AE!C|08<>QtrtXX$D&|oL#2dlLYj8J|X>2<?E!q|Zn%8f6kQE1
+6>i`NCw}DzKYt>g^&dAANbMq8Gxp@wm4VUwuVAd7atf@72MiwiWr`Ahl{dE4Pu-VHFPV>_c+HVl!ME@
+Q&NN^LX&Gfg+&lfk}zFaXF9PG>Q?>>IGVAk<)_>a?z;qdb2l14jV4To31S<HUK2HRR`9Z!bC&1U0lP9
+2#nhc{n`C!^7L`1R`I7=VuP$LQ_oH6jlm1p{@)Bgfai^|TGBI@m7MbcYHcax?^rXW%SZ?e<2IW92Q1e
+m)t;UTek;n!}@C$**rK0$&D9yM3%pGt1jkt6}XRGp}Y$JHc*5PkQ;wv`PuYm|+ENyLuI6kjv@RNTK)3
+mUdG%dOB5U4c;0T=bnD4Xwf}(g}0K))Pjj>oxfCPLwdci&+WbKQM&;TvO&WU#jk!d__^&z({2Ypstv>
+jPhm4KjjPV~4CBgWcxn}EtA#ePo>61KvYL8y8#cW+zX*tWlW)3rU$6<FX)?XTLQ-PE#%-JTS~i+Y509
+7)dVze~?y^EifZL!L?xA@twu{4PK5e{LrDy$}-L~8fy2(=@(Z3Ggf<#}t3)SmauTmMk%%poutH@)hBv
+o>&I0|7|?6d-OIa1P%3OQhN8{a*Z$i@{%hV!U&QoqBNm3h`psxGXZCw)iDy2FZX2?Oyz)#5IBJ5sh&j
+8LIZ*CT$uzb5h1dC(}j?=S>%<H_>N`j1V9dYIKM<i*Zd?~b9}Kd86VM>mfS!t(qKN0&*2>P}Y`d2Iot
+a-Y;?m5(v0+pA?$a{k{FZKB%};;u5Yf}K_(>Noj_S7s8H`CHA1y0=SP{OrVaz~}Y1W<@V(gU_IVJNUI
+XLkce2c$>EC4kEBy+mn$@?7Ox{3KqO#M^ozsHpwOjc1vp);zCCL9>60)#I0h(@&D$g783772{l~#y(e
++V{;6fCYe1b~R*|~{y9`dvMU(;g)BgfcO9KQH00008031s8R$mD3+e`)k074P~04o3h0B~t=FJE?LZe
+(wAFK~HhZDnqBb1!CZa&2LBbY*gLFLY&cZE0>{Y%Xwll~-GD+cp$__pjhw6p}Md$hu(<2J(=m=^89ei
+rQNr+CZkHW1EOfY9tj`7`ETO!;56fc9T>OiAA07+;1F@$0LGI-L5vkwMv&lZm8BERf>N$jMK^z{P)N+
+vJ`JSBtage0~68cy3u6I^qQRC%&v%nzZ>8MsMO)6g{WJ}R%<;a7u`?t>h$!tpI)85`i0~z(Q6<dyoSh
+`ZW81I<owV1yW5Ym)Ul~p0bIe9yq>*r-><JOE^lU+R-Y0yWfjUCqs6186dO{rI?Wz{mqMn8_7k?Lh15
+H<9sy}_54;2X0qs`EG9fo~0|}b6F+>TOY03C1A(v7LnUF75>zihi1HRqXAgMOzzXJ!!iiFG!(}a9lGY
+zVy1w5iaA-ED1bShA;m^0)NOru%V0al>1VlB{vnW*(>G|DnsRar*P$meM8L)m*Gx<iT=Q}UkH#F?(!8
+Za_~P@<a}6%k8PhzkAwK&u8nnGjSqu#}gir1IV{$Z2uElA_@y24;Tw@%`1!`E_=2dyP>=(f?Q%SwBq4
+;EAIs3E!h=lDKTzxoa9wuOw|PBFb%g<rPXc81vajXgU<|97y^>LM=rxb&#T^e5aSk*+UQWsj(+1M-Mq
+zFA5KakaUh7p7xL@C3X3fe%i^4qYYi5*0e)<TzBfBCT-K#4XZTc-yzY$-Zs3@Oz>XfN&@iEjqV`Cm_I
+?l;wUq0vtG$;Co3BOFDj~380E||H^>g;4?@)C*8=LDj?cC14HUw9w1b6N;eux~CdB+jC8K!-y*DJ3UX
+q8KgMmp{$C~!J_zc9k#<r3-8otk*IbDTW7>Aj+4-V7OHL+ne#!(AZCAK}Vd+!9=9=DJAX4YGb?}F&|3
+N)0{P|2N7j=H6TUg0p19vdX$u{`V`?|_z_d2w`d5;Pg}wnsf{@^uG5YF|bU6rBue>j3)!+j6bDm^~%Q
+j*LDhp7esnhM1k#v!3vv!0Z{K|HbBBn9?E#jX&;xO{P|e9Q*yjeQ?u21;gGAfqvvCb`bcLfN?V};HxH
+ne5Jm(4j_a|=(Y)rCP672wiV-sn-aJi;7Lta7zVp1IOdiUHqLv6%%y}vSFPVS=18<K15fF;f~<t4iYE
+)Q0lgMDngl2wY5b3qs?}@5R@G22TxAqPg^Uo?h$+jA3!<9Z&QN1nfpbA{VmWvF&8_V=Xh&fh59XsgUg
+WFAs0+*tjPJ-|F}6c;yjT$AhOcH)nzs^a9N$J6WN*yu_Nzz*Q?%z7qgAx2Fu?+r6R*(121ONX*uYMOb
+5b(fyQyr+hSs%p=y1BnmQ{{RjL|D!O?-U0Y2m1G&up={5gbtOP!WH0Mj8bqcLRn5y7c;);BujkxMwaK
+!vcS==>rf$NVsh;YTq$kmQhScY)403^Ojc1sf2M1nN3_OcG+$0L!y2YitH(^7*%Mu*^&Bi;Oz0)j9Ze
+STCxh9e~|9ZS%@l-EMuJMEQ=LX%Y>Yq2$v_mvUWv<tkZ82_q66i>Y{>zhWlLXsZqCl6(v39(dTnygKZ
+2lY@<8;;Z7#x?93ky#RsuO9lX#Kb-}5$`-B`#CQM9*@9lg;c0LXES@~mRW5c)Sg3NtJ(CN<CZWs2>b3
+IBlvcT;elf(olaJmHDNFMn9X>btKt;F@y>);`WA_j{7ct(Eizj)fzvWdqp)yvagae$4<OA-%IKOoAk(
+$N<l8BdypIHZ__TG@0k5$LQi6&)z_;xK*;8<y<|ra9x)iJNxNs0ObEEvA>9ORh24F1&?+nXOH%(Jig+
+T}|S!HCKXC;Jw3j;2cZGt@f4+*)&R%98l;zv`N4W9?aEhNtnh~2RJlaY_IMng{940(fgVvG#3wkjF`t
+6gt@S9p3NlZg`Rl3M$dN;G~XoYbWkf6fZXi=w8p{2^?=~J<oQH%RG)+Tz1vURtigyDqJ;8!DU99<3ut
+JBOOipJ4)fSN_6Bd%P22^}`gtdGdT4cLbdYP_-T|$<2Xf2Ma!yrUF>S|rY`XhodeEMjze^r|G0(7Mb~
+oSHViGGYl_q8C*c8iTGCAM_*hikj{gBr&Wi1s>Yh~6TM|Yh0qj3tK$6|Jj{@eB(+GO<`Jui3m+S3<4o
+{atnP)h>@6aWAK2ml;P_Ex7&HOB1=008MN001rk003}la4%nWWo~3|axZXsXKiI}baO9eZ*py6baZ8M
+b1!sda&2jDVQexrHZE{^?OJ<t+qe<`U!MY@CnaS|)WfetclJz@OWI7YNhfw6Gm1yz1Cn^ANF50|c028
+7@9qNNo3fl_rq`MBE)oUo3%d(oe}E0c=rDLT56d-=L~1YMWbFvSlhlTfbr3n>`1Fiu{=NI@5Yao$&p;
+9b*1i{q@TP^acq=wr!M+4y#a?~5de2h+>y}3zPi-mT)9+vRMcn`U_1jN>Vv^a5qdTxDh$EH&e-QDMIl
+i+I+-Hj<UbA}?FO@}iBt^t=$gGtRo5^6XNcjD|?ehWA^^q`&1y2XQBb-5rd29<OvE6@+yClYaV1J9l#
+nOqE>|GM1-pa0yQ(HDtJrgh9JS4$#B_`~Rer4m~@T@-`j*n5KSaJ4e<#F(gv+jWxID7S%>py(_bY)91
+Vc_v7<rDV$>L=O%^ZPe%KU}>f&-z?AK?puGAcCC(cKz|Ej}!Q2efDu9z#b4Bv$eBfsdxyvnKCyH{lPZ
+!c@lyH2Z3-v!@!LbXkjpvByhLj6O@7OV`;qRGD6r%eayl}u?oN&VQ|ZtDWzOwV$H6!;Z?+9G6N;4kQ-
+zP#uppO>-b|30Q0?346<<CkT(bd%D{632M0QkLYz4XXUR5-(4Zh<M#519XRhPjE+JJS-;m=WZ8p1J1u
+0u|2fc$Le7<nDp^#~olDIFcK=6JX_1zGJ^cW<H6hXhS11Lfc5s5V$xxygEqGlFx$WJia<!W${ubF#m^
+gXEoqsx_q9^=BZZAdK2@=dU@XLmgE<HW8{SQe}|aU$}}+`$Cqq%p)ov3Ri$fo~_5fm6ibyg&}T)9K7+
+P8iN+?1D|r>wLY)Y%qH)Yrjsm{0%bZy*D7j3!OA&Z&T0N@GG?zOlS%~bl7YbM1h#itdxg~9$PFgKEx4
+t-_2eituNj=VG8eA8tMj>p7g6Lh2n#<?8OqSUM$OvE;hQ=Mo@vx@Kx@}^g(a-UM7(iK)-zHWCP<gU^O
+h9VQIm@V8KEjS=DBI5-zq0r26Okkvlcm5i@=;>|f$QQ)A28=v2v#Tr&l4mcoROmZZO+fn;DbZ;G~Pf5
+GH|>A=wOWuuBTQ6WRhRQSNKK|CegRI%6z-$3Sb%S1-AXPVuc8Xssde;AI|CMp0Sb;;FmVY=0b4j8`|i
+Q@@~e73px+^!LlBW!20fvI4DzUg>!a?>r5aY(AV8IlpSAfsg*zkpe6oZ`pxz+lg{pSs<egWWwG>^|MW
+?tTt#@eJgq@3Ya6HXRVP+fk5IRuGBYVMn83_ba@1(&#m}(Q6Rxvb>T-#&BfRnX<{clk=p3Q%>WZY{vy
+QHT{TH&3HLY^XVucPiJ2}Cz~v(B;Oc5FffW^I=tzY8%EWJ@lCfeKX)oSsVj4<%G|0lw^iBydRP;la`A
+mv*|I^$FB`_OYYi#0pER=L(g_p2vb*V)J-jsB&r538Zz>tA>`i&hP#8tFL+x}6b#Vbe$i*sy5j|R}RL
+zNtWsX85GRTk!0Sl~yY{q`Z8V;!E+N8{ic~t>P!BSC4LKFgaMf?joE2YYis>_YD#KIJ-eT{nJ<TeF)N
+y0r5J}AU+4Fq`^C!AZJ>e7;GGDp_%m{y>`*9c-xt#ef$ORFMZmzr4N@-<eP5eH*aA)S>YG8vHq{9>;$
+`XGWt<<ZZvfiwqoOM}n}8%*@%4$QJpyC0;m*F12)s|IJ=8X>_(!u`pF4egiJE^h?@i#o^lSm)3C1*zJ
+mAiL;*v``{zKSAV#@*<nh4{)D5oX>mM7-@O)rfi!-B84FVC7=c9fDQw+A(u78mla*v4tNEKY?AQBWc~
+`YY1vmYCYXY2-~_{DWMPmshZIMBqQzn|6w*3!)-d3ea|cj?^N4LXJ|!HbzwD%3!%%Q14KRUXEsJ893X
+BW=3xj1OIZ3!=j~6V4p(hZ@_!mgalxX!VNgKv15JeG2V?RRH_tD!jsrn@HvUU6<OXE|=^Eg8IiELKso
+UI<$S(-sewph)3PJ~zrrvt94IDs8T4rl4sl`D#+AYHyl&F7|SGv{-im2=GOC{A;AR~(lXpvJm!KF4?R
+I!%FSyLQ2oES70jJ<M=mIpSfM$;ylXafCfU-UXypNm$n|t#0T!AS$9LQ_krya8gd&g;_X~L1d+tFZBz
+*<c6{UfGUGadrTXcIy{t1M-gIV6T@yL?vxP@LF<{ChowDDZYi+z%s`~Kg3f>btK3QPRhy*jt^ll*t7_
+hiVtg}cZwvIHKw2X&LNegV4<;UC%zzqj$@dydnP=v1gV0x%8_fo*i)A!5!yM8FSrC@`F_t{xD9eL-VY
+``;OHwIHE#=q`6H_mPX0|&(j>>ZljmJv@Rf@xq)Bx-y7nZ4-A!8&gu2><vfoWLCoBB{I70rP*X=vM{(
++L}$F&9=Nui3I<%IMO;8r~0wJ(hoV$pyo`I6c44IeLOl%`Z8}PtaNBJbv;xIhUL#Padb|OU~0Lk5hA=
+?ZwGY$xihtInVdvJYOJ>{*;_A_TpSD>hXN}gmG$ql?nSLkz}f{?w3WU9x}<#g&OH-zceZiHDi5B9%-`
+`>wbw;9BamU+Nsay(V1<JkH-_*_s;I&KfRc3U7pk5IpLNkSkA!8k(qW%@?V_er$g`lxzd=kVyO_|GE3
+~%cywMp@dA;#{HYbN!GIl~b=h-vRzAmAHc>Vax@E$kPSNhXq{o&$=61Uc-WnetgS$?TCv2HG4^Uu-ym
+g?X9vhD<L%jpLUa%t|J1l1HZiDW64FB&Iz~{^h;}kbuB2_!MHau4e#X1y+9>#2ZdVYxij&U>wRBgEVK
+N!rq%!sJ?KN!-3ThGCQo_qt*yZo?q%#ao1)066;F%Y;-)rL3?ZaU>uz)~P#eZ?~!R^pG{%e;G3i8`I)
+=H26RH_7%7LB|nDI$Ywn>mRy)*#^MMKKn8AUHvReyCJCc6#Si^BrB9mT*U~|W=nS?Dt^>bJS4_G?Y6w
+kqFtV7dvpj;Liuv;?l?j`pyGNX0VWa+2u#fZ%+lGv&%!vq1sFo7gJs7kdvd6)pNfT3qPRg9AxqIdDFf
+g|{rEy84|QKBOP9n5I(n2I>cOH_Idi;6q{04*VSk$>andGe*r}~N7WQ0TqD=NXTDxjXjwX50NP%*Zpr
+NZ2!OEP~v-N8nsZvTd<|$PwFe?QdPE;WtHUP6CBo3lNg<f`-Iyktf+}T*&N+LlX7SXdj%Ft;ikDNqxW
+})t>nNgWHjR)MIRbJmH#}%eZO+fYZIaBgY3L1rHqTS^_BXD;qD2ZqtgS-4jC2iv<p)Z{EiUA?m4rMJj
+F9m^xW2H=L4$|617jfM#`3lD6!WEWlmz)8=n%Ejdo#G-xv!siY&QcOehxgrHP0`Lr$tWEcm$vdRNg%j
+_Wojpgw*n!4^+r=;x1);!_))YriLs35>GR=<KVf*OVwJd_0T=nr{2ZBhwqlySlH8(I@=!;aBTr=GZQ}
+7J+tg~5pDaAiTvasNf&sYU`1`5U38Ap=q#o9?Tg!U!DXfQ7Ezk*LuCy#Mip6X}i(Eq%(Vq)QSu!m(aX
+lj&w>W$bDq&>Ck9hT)rz76_UK*_1$Q?)Eqs2lm1Z^4JX;Do_<F#XPc`;~E-m3D~sGcdejV02D<@M`Ce
+9}#*>vJ3417TrGHjfSCM9TthSetM<>5m$wx_<Cpy>>lRb63gLVC<39aD+~5wnE8n&$-$VcjRCjPxH-b
+yXDepjSOfjIBTb`8r-0Gv?m%_i*tbvnD$F(^T4boG&VITQN`RJ`9n)7r{v2ScOhq9BT<RMh60yIVoz(
+IX=~%$-2P>K2+wLmz`eVD1t{yGDNx|wnPQcN{&QsDJzM3Xt^PMSR@1GBT1t~|zIwyU?cem>Tm5=!Y>$
+2u_Y~OHb~%uRvHgl*bha*B5vX7I^~e>$qes0PFu#UV0a%2*1*g__wZ}o*BY;g+6o?V?Dq}ZR+l|v&Fq
++bnW3m4dmil_kBIB|jW_dD{C<^~Sl=v=CqW;G~-w99r2T)4`1QY-O00;maO7>Q1#(0H64FCXQF8}~10
+001RX>c!Jc4cm4Z*nhid1q~9Zgg`mY-M<5a&s?VUukY>bYEXCaCzlg`;XkV5&nJu3gUubwU>>0cF>~O
+;#xSa(*|&2!@i&e4hOAvm%1fRD=H#&=S7kJ?fqs*N|bi*;W+67T^K$+$l-9F-wbtfaxxM4)%)w6tgJ~
+(`9U^@pZ#<AoAAT8exPszQ}=YS*7d$o*IT;~FT<sHes=b|FQ1=1|4OX(!fs_h*~)x37e-3);)jdBzIp
+dPb!1AlmX(nU@%8&ZyZ5iZefjG9_pd~u8?li#S0&aw0oN0?t94^VBg2*1n{a9Owd`(+YM0yfc2YEYC$
+vfH+-`+`x5|yI@|~Qxx3#L%>{eDA-J~Otq}eX7YgJu`sjpxC{nfko56s)?jVx6q!-Q*TvqF`Un9FEdw
+rYz)HV=@f%l2ATfk2_EP39hDUQhQ=ZLKQ9#Fu4m%=g-UquXjT7uT&cCfmq07@SOAzWMI$iwkis{=qt!
+zTMlcuD*Ir3rrW`-rddzLoS+pEm!&aW;Ay6d_MVUGRd;MEVB&DTuw<4%zw7pXC(dUTtp9{YL-)Y!`pV
+R*0d4Nh5t?6Zc4Y5n3g&Zqglp8X?i8T5T!CUaY~zoTetTa*z@%BHOv&E_-T^COss6G_}OH#k%h>LDr1
+Y1CMhb2v(&5Ef_Z{rzLU0XDsi`!u=s|}-n4aHD!CEFi=b`6CWR*<{5m3RIX&?{sR|}7Ds2UfV93y-lR
+=n&J{oaJldtf&k?C6RYLHL7E2Or`D^uoHCd~Y-Bi1<XJ)x9GW0o7>UmjZ~8tH}9>%k=OgtnBd>RwQ<F
++k)lj))|$a8s5-lhh3Dmn7#V3aj<36APZvUNdLgSr${Di|=*S{eL<2RyVzJ8=xTK6wOM&BAA={LA^xR
+rNIg?NbIvA^7Cj`FRR#QE-@#i*CcRUdnu4n6LBvG=ey?oqG{!U#pD=W$tJg8QWwIubtyYRfb*SLE)%!
+Oyi|x=#`!_88#5O>wd3ewX3HhfAc5Xg`feDkzb(Y6=j2o<1Y>X`5?Tc;=WS_cbKwJzo7WpK;y8j!v#+
+&6jA3edBe9Or-a6za72*vk@lF}As;hD@R;?;6$U!THC#-d4)J8TK9i-4HNLjg~Z97*@Z}Sokp3Hjn?3
+FAxJnZt>;wrd`-%&rTQ#KJh44pB>o+`gfos`{mkhQ;!r0pJbGWRMUN2_FL_59asoJ79l7`cRqS3DdKb
+1Uu?QWU*DrP-%~3{kCG3sD<!tq|*>3MLf~YOY&~{X>yLG{M+ogI$bWeqhaP$vomSQEGkD)}0O`fIt!+
+IA1w5Pm$r@gQ^V7ou9k8LzUbcLk6QB;~%yLzG31lRBzFoHw|Xih%IpUu~pO7C=5JmI@m#QecHw0COmt
+6Oc)zTNP<bma{E|Q*}@{0Jab9hDxfPbe@=08-nMS7Glt689OB3=0~zZh!fSN{@&{>oIfvG**l5slNhr
+*g%n)<oN&HPA)-*YMUM%E?^<p^yBIy8uELrc`d#AT`Y=!woMDiNINKZUX#VzEnbd_&5a<f>7=jrnUD+
+h;8gpqACLxaVWX}2;d*{%6`<JOys&pnOV$6No;Fn+gITIxI5Br_WArw?r?xJf_)NB#JJ%xey}PJVQB`
+;iNMs#5#3Jg{`{dvkGms%r~7yT=Xl$~(bYa(;cXPr6hY`DH3D;6Xk=g_zD>?ipAj=yx+Cztz>R>~X)c
+Tm8TKRnnW*f3=H^`TTTmJ64e;0Y`ZlMVIF%FI!{vj$P{Hs4os`1{PJ$_}9C{#TKpvIJQNJAV1V{P07$
+zU8P<lZEdhols#}Z)D$j<wM_#Vi#y%iASW`JjcPDeH+v+{ty*tcQ#pJP#F#ms`NY@z0Ga1-)ow}9b!n
+ByVxg6<`l9{)LF{!a)(9vDlT@*%djS8t$`R)YE@~K8M50`$8p(q^$3M1PwADI_3O^VI?8x{)vsf2-bB
+|>jS+r#jD^*pu;CUt2d26I2<mBeu9(MO*tKeFGrKYVaLJSg*fZ}@^vGm`OrI?|qkQq`jAYGkM?M2<_R
+VjDI_a=xcQDdPzIo-o2di(v%>0Rz>3w@|H!Doa<uQaC4h`r9&TuAW~EVrJzioCD;SUp)kn2Y}KmW8Kl
+Sw*%xZC2A6X{Z>w6H!l!w2}EHK{YidJd1coW@(hXjS!Vsb}q4WM$WOin;pA&H!{Sq@lqo<zsH%OR<#k
+I8_z)DR9E2%-1#69j(<tV#k{LVqn<*9b*VTWF?iWczKW#sq9WZ?C}8&k*r}r0$VZ29ArseLqgaMCDQh
+d<ynod+6u4kCP4h@vgNu@ANtF=C!ihvgHUJW{0r>%e5%qZ7EB*uSp2mn|p6|B62^3MuahxpOjss`J&V
+7|e+*wO9>RnL_@SM6OeT@B!w0(#rDfOMHu79vY$WwJGL)PN%k84!;v7v=D7ZhNY%N)Ag8<|=8!6ww6u
+-bPou3JO~6evE{YHFB*qNaFJBU;oAX+Fdl*0JFRPe3O}a7*Z|or_CnRR#6OLbI2)-ZzAh%43|7&Et;B
+!$^ascN<oH3-1tSjC+Qin;hbdj{+t18v~O=P!fqGg-j*PDLF(a2hRIstTC1Y!Hi!-7GtJCc)(=<smcU
+co{&W&v+b=kvp7e%b~ggZTww58a&s)U$}W={pU6d9DQ=MmB23_X&_3toJRhO5Xt=sgR8{DRg8}QHLa!
+tCuw<#$2yfnR43UEGt#sA)A&&1bd3rhx_R*1~4(eI@TLE314RT{hD?nv;`QBv2sNzmsy!(I!l%0~s*J
+X>;i;IX<m!|{%Vd5SEQ9egr2VmeL#YbcBsqESjCF~8ThTDZ$0s!MIJp;LSE#T0)QMEO{*+>f=WIJV`u
+Inu3HLdqCSDLLegd!J3DoK>B&;SyR0*a{8LCXeOyAJ@TgHXl#6<;{X&-s1E$t%moiHF`HSm{Oqha8^~
+?A6<K&q6SC14xwI$o+Y5NHJIdc>uDLw;DoOb>SDqQ30C~G<gBw?1_!}^N%mTe0Fttc6Cq+Kad=bV(~}
+wMAz3oD3ZGxx~rD+gT&FtamsYdqFR1>$^7o;RLc%A=C<Q7K;*bX^)qrJ-l*nCW^@~8Fm9Z2KQ%*o#kj
+JKv)>aDz$`BI8~IU{ez&<n0XRA`0?inU9W%YqM^E_b@lMQBtZGT5y0&OofysPS59XKZzu2)!4Or?;D&
+FsLh>}HzJ&!g+Xe1wYg&DtK7vvK<ARpDr2z#J#de1&SrH2tn4y~A;b_bdYuIrd%bCZu9=aJEc<2+;`#
+v5gyJrV3<6(i=;_9%qQO*p2G^24|x2IqEzE-~}!a`F5s7T44C`FKam9g5x4BtCZN<|c5_dQ7Lm^ZO(F
+BN2%s;r#*Ng%JyaYKvt=27%KZR`7Y_019k#6xVroOb&@GJ8bHLEyVA-wORkd`=_rXx*1FEW7zygRt~s
+?lgv0WJS7|$XOx>ks<Fs*H->Nvs!k@g1*$83Z$MY};B@bvx&|3xmpA*qfe{j^*92Y|iEPuEUw2S?#LO
+Q6`lB<^PlozEhiSgqxW2++DdTtNItO&%P7e48k0bs5r#Ss4FMSihCxj8PPtLr-0=PF+B_r}PI-`7caP
+~XiQLXD_b`V6RA(-En)Unyzzl~eW@G6Lb4*x%kV-}4BbLrX9sP4Rc#8S^zS0OgHzN0*gsxtoKilMa~)
+P#mV0UNXuzYJ9o3K0OT!5cVjaI7(;`_o`xr~(ELp-Bc;1k%Sn-e{wV1vsB~mSZoUUE!Agbj5|g4OK;~
+p1y$S_Uz@*BQXr)8sOR05lj|^)JNj*6M-12NhT^cp_hs0RB-yza!EJ9_TP9+H0Kcu0>F!9Is(U`xvvW
+$xwB1Qw|L`VYMudu09uw<vTGLdl2mB;{`s8iW!vFDmn*_IEL{tKtF93dtYBc}`pPRAcO*AVr~CHh-<k
+m8I1+V0yxxp$VhmNu3Q(VFsq@e|O@Y9ZY5!(AAHM0H&jya#PZ+@omhrj!oBIApv@R4pZEf-UX-`ce8X
+h4+eYa7c#m9?@^Ck<`Bl)@($*tOn?pw=3HO77GP+0d7*U@h-2lTL~f+Wa-q<Xh!X>iaGxzXVXaxrj~e
+uoeCgy~n~jpJhlOLJ5y%ATcX?nAaC;r8Jy{j0}ZH}j7X!-!c!649##CB7&y$7VaAKo$}`cy>iP8S3NV
+tk|^+I*)gGaZrm6Rv1RW&?jrHc5pc1G9&$tZ!U1%$G{gf2&ixE&M4f6wmyG$&dG&C=D#G&vc$-;aQJ=
+TnuYG*JbT^{gtN;P`T^`tuOYu7{%~J04zN3qLp~XdGyXfro;Pk<9WCm@Cm2D49%8xAXzz2Bh`Jl-YKY
+lLsV~AeZhSc7WiXlOa^t@EG<*J}8j3KNA@yBNDtYHW2#vJXXGZrLsglkGvn*}v4Sn_Mh<1->lcU5z)y
++q0Ed6Eb{>;OzqtxAkPIv9T3j7yPO9KQH00008031s8RwL+a%#u0)09hIV04D$d0B~t=FJE?LZe(wAF
+K~HhZDnqBb1!UVcx7^PFJEn8aByjEXD)Dgt$k~A8#mJK_x%;DHy@bTOC_;4+1+#Me9*-gC6dgDvg7R5
+R^H*vkQ`}lnhQnx)cNlRKwr?nj1!Q4U1hP+K;vm(Fc@4KjjtxBeODDxm&H+@?<ecDOq-}nlgV;FY2zl
+VyY^ef{Jn_kRhFmiNxeV$%U6?&caxiUcav8amv@u1-zINQZ!Z4#r0L7ae|ObxGD|0v{=X+#*>-7^oc!
+f4SFb+4x?N2E&*cC9WupE~PtQ*0SLrTorvGd5^|a3Fli#;#nN*DeSr=*9wI{ibZcmndo0VzXPX7v0>i
+6quw2bQMU%%1hvl9qR6lLNKw@Y{3x4Rjp`{u8RdVTR`{yq#hDw1{G8&o3&xX480tc`%S2=lAJ?Cad*J
+->pCb&$#fQHEGCRWVgE6*H9qmF%OuT2Eb-mgOo;r*#t*Mb!LWR-I}URS8vo^BSwXT!|{@0N1qPFlekZ
+SeRDyGO$LB2sAu{EV7uq1RX>Y&6!5+%PFbUqC!!vsv|Z9(0chIr0*!-<&Ku-%L_9o3Y6r4f_$bNqs0)
+VNTNXHlgQ|7ev}>%R6qax0f`siefI<Fn=G*zCM^+>`xfd9gc^CE8cn=OyM3J+WiIeVNyLki(2J7f49%
+}hlJC41VI5ilo2Y$Ab9h15R11b6WE-F|uH8az(mo3VOWUeTo6Nk+MhxJ9B0L+i5P4qh!yu9t>c@yc_C
+QhgdFz!1qZzAMW-7zGD1Qj;J&k|?wX)cUns5hU8T|HzVRYQGI!`MpDRiqt8&rXvF8pd$M7OIxVSWvl>
+pqW~7jL^F5TQ#|j_Mm~YWwZo_0{D0gmN*68<o}ba{Yo)nI51Xf#^WloZZ~Jyg9r-tD~k>zXs&y?&@~(
+Yu0ThP8WR_HR}{RHw`lAnvlyK-5YpO{m+$7b-vg{P5mXRoqsh{C~kGGR+adx5LN0g(_=m#QKYt`mp_3
+1DcS~hSmW4Qeh7ZAxFP7rAzPr&HNJPt`&6}zZF>GCWwW^qOIR)M<B$^0(<bn}9@jz357BGI4MN{{o2v
+XGe3Qe728JJ^!)?C|{Dh2apyh}7jpEw3tXclaTUJNvJAYn<j#6WlGFyWtEQ*6@9gHEUMp#4`HYjnj>7
+qEs=>$ZaxanR%*!k{=e1+O|o*vSLLPwaDYtWpfr!>|}sjK99fXB1gP10v&6<A-t=h*{{p+F1(iKeLx(
+^P0qU{RauDRk(jk^&?U8qiQww&rP2rmk-Sixio(kUvryfS8KnAw)B%yEYC4X<<mVIKRA{L`_jOX#zkH
+QKy9+vg1rl^AwRKzb9>kR2qBq@9hHxlNUey@clpCkd1Cy97oHUK)tSK59uBou**-&xY^g8(Q^>lX6rI
+iRg{VuL0hX%^rx`;xZj$xp$yi9rtj@jz4zJ>$6LgGQFm&<8$2VeH(3lXJBcE+4e5Y=6nkF>PH460*J;
+!q-rX26fJc&0`?cT9`mVYRoh;%y49>WXB%*XxCOU-vrB^nJm#CYnQ|;pz<cOsior7vZ^1yYxdB8c=<{
+_W@3XzCa>M3y2pfgF63}y{aI9o8k(>4AU_*?2<Qb)7KX3S4=ns9b@eipS^;LE?%Ni~oXo19_b>*;bCV
++>*|hWFr=K$QeG?;>g*`Wj)B6k!;WMo(0?%x9#)0aTQ)(`942ptEy;5Cs_MzqkvmqHL)&Gr2DAAlueF
+I`yN5ASRMPTE7=Qi<-bXTB?)=<n;Cxpcn?_%mI;gn_fo`sa}H&eGKq@)RGetMXWZ3*uhv<CEf&n_&2z
+gphYNKO-$kM1N?j<o=%O$1J<*X2O>!F*-5(WvphjM&Z8DrK+@eNZPIr39R>3Y*JlvG<k6VMZ7IY2{TV
+TV`oyu8dLW94`Ok08-d|o_3_n%786f&RRlvbImgG8hyikL+EOeagRP_W!O_i%|ysgYrg&Ll<7|Auw98
+*~%iAIVcW&CI>Y>U&yhqoCeBif@1!9y~YmsBmYp0W~Xel<EMN?ask1yHgx6t)^BN#I+Vn5K7@z>vrU5
+qFisD8u<uK>~(JSADq-d^_d(7zzR=(Ntb1?3UHWSrwWl@FTg@NdX-Qjg72j%GK?cn3DLKXtq@&Ti&G~
+5AJY{6llUsMX@gWm3NfER2DbSx=%-a4_Of4b&w;MFHNgh)_KpXJWK3-64gnyQ}=`BD|8+0j!{R6S!Id
+{YD52$3dPQ=j>4&nFWDcV?Gd><GT0n(_eRdDz*U`P1t0ASR-jFgAS!?7>8uKzJSA0En(4Y0!Hg@Bu{R
+F{hCo?ofiLb>y|pWB`3R?E3DJ-QO3Sbor-`z1)yIJ&N2iY<Q9u%*>2k$Q0(S|PV?Cpgu?qF;zzIX4Mr
+k=t^UvPDS%4ZnOd)h9jbv4)K$A*?ImG#C@$hPKcnyFYeD<Q^0oI1IB>x*hS+1J+6W_vyt}B>jOqCvx_
+-W!?ctiPPc=zvR{hz|=0pd;4h%rFi!iXX(qIIgmyJglDu(!*sI@@WMRaTGJ4jbkf5zyI=?aX&lCb-I4
+CED#eS7Vf5_;<_uq%Q)Oh@;j_p<}&5sii;(8zMzK4q*#6<IfkTVc2=r!qZX`fLph=Kd}Lu^<we<>ThA
+0_o@y3)rdS-GLU`SJ~wPaXj={n480<M+SY;nzU{jrB{Pd#T803c*8u7rPEgy3shFt^Qw34GWICeQp-P
+>9g+-@*hWIP<m*4T&+h?Pc7B~9whr`;E5}2sLe_AZ_w83}&#~-*ZTEE7lqqbjT+JBAZ2CNN;{OgNA69
+}iv(qafuON23ia^6&3=<26RUhCv4^Z!z^({f^@{|m87@!HvtKx>wvlaJV>h0-9UA%J8I5u`>yJO*7BW
+`y-2a1W42L+5ALle5#s<@w|T>;cBhVkwrXn6^+!Xmf}Y*lj<*pa+#W&xr$6D&R0sy3a!^5?2~Q1h9}K
+G#Mm3;xXbXE!SC@2AZFUb-wf0uRs#8DIfD5tk~crUio#oiL&<C4FN4I_5)(h%b=<d!)n?sxs%o%%7{3
+rXPt&Vb(0nq1j;Cf%y?7hR<Xe-PRTSy9B2n&_bE_}uz)5M-wfh>lcrs?`GP(A=a_}TGaK|VGa%g7S+~
+ky9ZEAO-d&>eMJ<!%eXaEl?IBIZ(OnBelW|IL&v{B^?pr5h)5x-^L{?QQo7<qqbH|qW2a)4ZpUqopHO
+zbvI~M2H^$|5Jt5s<2)RAhFT|pLmZQYGcC_Y=_&no-zsMh?^Ys@>hLGGNUIQo2D0Y7R)-K=T)FioG*W
+s$)~nUR881&Uv88=}q)Sqzv*fy*|cKT$G(W(Wea0m1@~g-WB)PrptIP(WxbL(%qXj4dRIb8n=XSNDDB
+VmN&nK?ZS%R^&Z*#)^c+zx+OSXD~Ls*GMtK*X)ozZdX6~Jp+#Tq~-UmP}Uz8`^iUD9emiTWtG2f(sWf
+dMHHyAv@bq?clPc|X8=0u>{cd3iZ1afo}XQLPf@2m63~KKpbA&bR04dC^&UC%-`wYkf>x8&Dn0C>ap!
+4N67r~-W{4+e!ZV-24--P-ak?1@Me}6U>lO0z*MUn8Zs*MM6O{oD)x;{q%HP?t0!I!O1fm`{AY>sR3w
+&6sA|L$@a0a9GaD+<ns_hhAfUTugher5r$%`oe$9JIvVU-vf=k@8;>>uA@D?n}xdGX^e@RfiBK5U^%m
+9>ErX<ni*a+50v8f+DwQ8aX=Cd3^G=wNyLatKMOS6!6~d9K=h6xb4~W!m8Ej>IP*PdWm#Cf+o*`qlIj
+x4wEHG$SdY<6~fR*rZhhW+zGpb$R4Ax%E0$6U88^ah8F-L~PPRxsdvrNd!yjL8uwGK8HXw5*RthhgC-
+jRf}syz`0sI16z<?lYIUh6@(_Eg8VG-VQh$qO<K(%BBmuwT*HiaxK6Yo;v9b7QUR!M#<F#_*AAaQ_m(
+=JKi7+$vV=#iB-XXNmgt0au`y^qC#o16YimOan9A@Nz7Rj8dTc$iDMGi!$tc~3fc8jD>$qU+4rZzbL~
+H?91#Vy^09D0^REaNz4N%z>$E-yQpnctie&NOO0hB{fqBUvD=Z``unFLq8eCUiF5+gX08XR#Ahp`9HA
+Yh@}sxOm^D(*E%paw?9C}5}wiGw1BH%ly!SaF-!b<)KDc$+lu^qOSbHGvyw15H?7s3J6|nwT`G8teo5
+q?(RsvWTnDLHj@pBP%PTMTQ8oT|!(9YNEZkkIHr60;oHJSuCD|@V7r@<vmqH`#dpBP@#Q(Z{qC2{mK0
+c><l!mBVUNVz?EkfW+K#n)hv(H`4%jSL02*_)^v*2#jZAxLPEbu%XSmE5H&yt;mMuKo|RY|UI#3}8PN
+tK9DPDt4(UL+ay!KtW1FA=m~R5VB!kk<-_E&|^`^GNNn0Xd3$#TMHC^Dmd;kc-jM-vv2+J{y+=rg%5{
+m)vFL3{>hjVRl&n>;jR^D&iPhIbv?K<Drn>6rvgfU<>uto@gktEbTeQAO3zU+q_5<s(ml0q<I*83g&G
+}bT=d5YL2L}YH+S>Bt<0G}1TIN&pUVKlQALkOL?$cg&}zBp!llsKcKWU$lfa|n85WOETUaXSyU;7YQU
+u`w`mlQ~*xDJ5#Oxk3$Uvfom)PFk}KmxMlQDt}?D-!&$i!2^nSt`0dCt}VX*@t}IXI9*(S|07~)X@Lg
+83DWK(rnDA1bR!t{buZBJ#{?O1=Y26R(q$Hv=T+G?p+h)*ay`m(Jn;e<OfZKDo8u+vG6o*ZjDh?H=3v
+P8G|B7G&ybx+f)pYmIjxN)`qZYX%!w!r)B7Evl}A!HPR$SIn-}Rei_@-20|zw;rw0v1NNXu0la5#VGz
+t22t=G>;UDk(oc*z=Y*R~a`y*9p<0P5X5@GXX41%Zs-5Cn!yUEyqjNx&G#6>k!-CdZEC2BSDT0<)vHk
+tHZdHp9Gd^U>ReaR+W{^!^a~xf7eHAO@-tiIjPNjBXb;49x;kI`zj%W{|slj$NR+s@{b&O5NeNrxRZv
+roHWs8N@JHAG&EOb~>~WAObPHM<e<BwknJKxek#YnBv*VJ#(oJFp74<Og!tg&rRp1&6@)owU#j2X=2g
+}Giehw6UNfOXi~e+>m_mY^r9RUkI~KQWFHqLFeDI}>T9P1MFt9Ffvv^W;p*~2R85|l(Te^-g^=^?WRu
+iGB|v}`d37FY90N;fD!l<WLAlB{@@fNLARRa|PR|iaAVJAew@XVsyS+4a*0NqjP5!0{J%Z#8S+wj#3x
+g^uG+RT+1ejh^?WbNpFGPew?Y?WWbQ}17IEEQk7*(=CQsEOC+82?#)#jvSWrE$Yh$FYJ$jmsEcE;(z&
+^UE1jbEv6PiUu=nzROtC<TWk0eWZ@%XoRV%bJ7wqO?&j2~@NZo@D9H>5;OOhI10xq{Txcl-N__ID9BJ
+ky9|OPj@_mNpZrIGO@!UO`g)c%2CqMs|ZvoFF>OL)v<d_mS&W~fv7{>j;NFXQfG)#X9A|qe4JXYVZ2g
+}y*+$uhs6L=hj?EnWkR#L!gF5_OyzZcu=gX>%R(EzPHJ?UA!QT;URv;XPm`cYp<0|aM{ZW}KVH0$m2%
+Vq*Q?tz0Bx3{rMtz`D_YK=O<?K<d~jnYO2Yz4#cc4Sx*>ur#d*J7J`ECf)mi8l^EjO*+Npx<0HiwwMV
+m8ao(iAs2)5N@pMHsH8028|FqT{?hEX3FS6Xe{G_D%Qv<!>x0XsqOO&Eti-l9lou^U#wt{5GSjMl?W4
+N<Z(^eaq9;8GNWdf)(e$f>{4|LW5w_~qA0O;sbI5P-t$Ju6d+B&gR%*@?dfJMk6UiLclb%?e+(Rhtpv
+epOb!$@uF<7X^OoU=m~mPys_RbVra~=3zoQhK%B_3dCHQv<8<b1&kyi%OGJA&w`e5;Fywj2#g2<0ySO
+n#@h-FYD`oe#Sd<gHP>B%RJnCk;1_&l(xMJP86`xK%h9)&1TCr_Mg)TDqy`fS1xc(`&Wpa9gp%hwcVL
+gH1$J46jvwi>3^E9g<aAZ?XH=8!>-sud1uk!{R7!&ZzX|~v>X-A+e7o$|S-UylgT(!gmO~WSf!4py@o
+b7vgTE>oJ!A_htSYKw4etSIhn%E984mb^Vi9BUszWTnR(WNoVl0cWB1#2pWAgVWUsp{RxJJIxNevbf3
+I{04z2Potw01GEgl?kpb+$_br}`_9ARS1URZ)x;Fi0cN=k;_@<|cHBV~8o?O#S|o?W<Pby~G;$C!Xkk
+O`O-1ik?4ZAk^B;Lw)M3svTPDfE4OP%<T$oud=#^wY;5njzDV8Z_&9^-FWVuv^nMLG_>2)#+zWw^qNV
+f2GR7*PrMBqn}A{aGSD()rBWKezJvu3VyxI0V1?@-CdMsY->J`W;3?G=BnB`dH6GH0)_eOiHUYuDIh`
+Lg%N8y`l&CYjUPrZD@6$oK+Sd(Scf1Mp-0Ol87#9=G!`8TZw#M;}PU7NS9MXlY6WdLZBtVOZH80++6S
+t~mDz~rU7^~Qo8vG>(?F6GMBP9vTdh5KkL(Of<y<HPg?WC3Sj%xvTRPtu=OW=~?x_va?H7x<?hCwyK0
+h@KGk0jg$d~>?MrwrbyT6U0ygW82#mPpzxyorO|=B#y6Lz{;=i^+A)+Ir5>B@%vg80A<ykT+<=p;3sO
+KETqip6pnr4n5fAVUuR$+hqk@z7ciR)rKcWt8C3yq{+%>mKh+)jLcf-L7`=f)vD_bP-)k#iVih0f|K*
+8i@-iq$yNrc<`D%lG%@zgUqc>_dM<~;R^Lt9JY>P<)h#Xkq8wBn)6=+*`(jDkRG)Ep!s)FRWnbr2Xg4
+N%3lIb~h^ETQxwdk5WyYpt1p-F`u#5NxMgS04S7wohUM$Z=#Jcjjq$&@D!t)|p0MT;mioym&&Q)@u8c
+*mhiacvUvNPOLS*viO!(wY?oy308WFo6Z8+ho63)uDu+V-N$#ZJE65rL*aTm8BBs<`(QxWjk-U_~Y*i
+64PZDAWy}Y){LMa$fO9H_vVM>43(pQX2&<t*}KzQt?jcdJDC{EYe0KH>_=$*vy4;Rp|D<b--qXP${6M
+B@so$ZleDE{p_Frnc{8_ZbN>L5A9`LjCEKYWn)x^kkqx>hVGQ%BQzqUsv)V~D8|rHLc8o-eVCfS->PB
+Au|t@*G=$m6Aq)g2NV$thn2^EmuCEUDFJYEs$-#tKYn2`*G-K#u;%yYV@JU7jS^^NFLKH1>mwHu!fMb
+D5RpZO3X}@H_+2&#kxe+|pMkLeWr94?OkeXPXiD_T!krEuEy{EXRv-eDlfqdX&vDWl&nbZKx-tcD8ru
+82YCKAxQz#em>QUd4>Hvo{a*+C=U@QT`okB7AKBnt_!GH!4uYCheC+cs_>vC)l5r5@44>TZKK!*C@3c
+5!-%uXl?(VVgFxwH#&syMQbUS*L;XZ~1(+6vEcl4q>5aezX=sHS(j)r_8%Hu%R;VjWwh)!F!A~A&e6p
+4x7fS0Mk1^CMT<Tn^c5%GKKdRdxrHwC8r{ep4XU)5R)4NVCN<#NV6GFwSirGc)!P8Eghp28)?rt)=;8
+~kZhfiE=4#WU8A4gnR0YH&L-Z}5E;drjM*w)54(lt?swm$@@IFOuB($jiF)}5aew=RxF6io9&M9v3M`
+EB!G*=BRlXZ#(YxS^wv)rRcXw3B-Doei3vON1bMN>=zDo=2v+aidhPN&)Mqqu>X2)Bsp}n((zVS|UZA
+Sb+ZiExaxBF$21%7iK+awS~6_A{6c!z6)V?h<?j>I^vuan`kUYDVsoHB3?bcvpUGT|7=EFW9&%y9~I8
+Hb*2=*uhyQ{T&&41;3f5r|@+om`&3yKxr~FO%Tf72hHwg~h?zQUq14CY@)Di7e<kbb~Zo!}jRq8aGFY
+p?`Jt5oGNcdqI%lO6~I?&}cs^yWdw?Onw<bb^_-68DwPee`M&=-%~@p!{(r$!JTw+KAQb#=c7z}xPSi
+=yuXWb{@s-G?^Mnb*Pye%dsjzYmZ46JtO4}p%_Sn4T;tUmrn#+VaK$1b#$r`ZrYG7DdexA{v+*sHHrl
+El1KKJYSAM|S9w(($Un1N1cDKRyiEhd3=)R7ru~)|(%q}ZnJyj*mElyn3?ko~jhBjD=sqAIoI4rBk;O
+7z+eKK(ig}1Vlc`HkoRj9K^oGfbr1OX%0j1LxP4?fmI>Y+99RTb*?Q+~=WZ_g)rwZ`tFu?DqIX&P^$&
+a8bp*i8&PhHj&!>WD&(hO7?&5(H=t&~A?ZX%Z<2I`ldSjRx01*b5*s-;s;F`{AeSSBrTRx;K1Zq%E~h
+k_0pnanA?Y?|sjGKP|2T9ogUO0p(vo0uT&?GPVIK6L1(PI>s~XPp9Y^_C8wMY5hIz`)FsdZgJGiEOZG
+Q+dhaO2$D$cc&+W;ueRVjrx;}$A%?hDN(6-aE~nPW?EC0BobZ1(n8^u;VB%nmJf|#D@D%UfJNkTYPd?
+wf2cJLdxXc24HVMNG9h-Txy+089ywE^oq|T2sR23D@2eJhkSzX=RBibU?Sht!;=gjtJYl*TLR)iDd^G
+6DM^xRmK*WXLK_fLS|w_?^Tl=4#f5djrpvmI827dMjqusQ<YZs%BrtqJd;L(%Q~LN5zW+Y92v_ag>8Z
+Z@B*fYFkV6nU(y$IbY~bEkQ~s9Bu6-@`HZKYxChe)#ZYgvTB!%F)w#Q5rF+mmU*|Yy3Y#;LnR?rG_Q*
+;)XFJ<vVmQz)JFtz`g5n`hLXW^iOf96`-7F|AbqH_hPHi(o}wDi}0s*{ROuQ{Iq!U8jG}Ei2`xJd5sK
+v@B$$ho`4Pr-KtVwzyo(EhH0rcK|!;3H&%8^i!@FhtL(2rkJ^cBXIB?k=Bk97Z8SB@6WhH&#GnT9<hh
+P>sy}pPL2AJ83=W5?r2;x?o|zlYPx6YahTZ2ebeP~|CY3DH&<+_A8&#PEZ4E6{ENOO^XG;uv59rulak
+5a8(6pJ%BfNy=zO4mxJ@RaHOO)p7KlOPQ9b~+AuO*BInwVH)H3gsJx{pa?4cFY_>bPT|0D@Teyl{B$z
+xkBJE4N__HM%ai$nMwINTN1Ck|r|fv^NqN=tO+h-C<ymmHs(QU+s5p`m@o{+A%(OeechqF09<r|BN22
+9wOWMTH0v+5Dm5fG|M8xI?BOII6w3Hi-NanF)Dd)Luy9X?`AgqkTzwS6T>Kp`It+!o}C-|Br8o&sjt#
+UIfdIUDwC*5W@@t7=c!)Aa+Y5n28ZB(Hh5Q6VDaQS1&B__6zidAVU0@7u-Vv$n9oiu+hSJ_hhM3#g#g
+bGgoAeqK0LT)1DMDnY8&^1W~d;7h(Ho1_LC1?>tSLtM(sl}A9|Q)|J)N~F9H24#;+EEOYF{gglsRQ>4
+l}S5U#n!Rn)dsu;ZzLk0v8-FtsD597671kc@Cpzr-BE;+n0dQD7M}zB%^ik^lb3KmRjz)&8II&2Ebz#
+=)%7JyqJDkGNT8IN)}p1`%$-j_HJLAsEUK@<^y^gA|7()T(TgW9{SklZjTV-ALo`&m#`NgWY?J_0=o#
+@9ntv76B@0>YT*5O565Ow{IweXu|iK2rydP&RidGSJ~RM@1ri(CgBP2`o`3vb$pa#JbeEYjeCy7$2+w
+h6)|e&-J^Y#<@<S62F@39mAbCLn<7b~MifDnwD-H(tXPI_QIsq7Wvl>1Ng;xvFni~MJ&LkWkA0}K5vN
+h-MiAkEq~eI6z)^z-C40IK^@Arq!z4V>(g+EhSp*#Qife*jZo_q-sUtAZ>sYU;teSM6%3#8eYVOgj>%
+gn(P<o*4u~uoUtu#+#JdrSWXkInTeXF&h>_FG!_Ow}3ySdF+yvv<Cl<;!Xd`3%u>-#F(eu4jaD~<YXh
+3|PCnt9)x)_oJVLr?Qp`8M$U8JfRcU46I)^n7bio#p-j3nC@Tb=I6!N$BO<7HoEXc{|aPj5;f_X0|k(
+!Gso(jzVz&xM)mUjA~s4HZWM$$c%#=kOL5)5CJVDcevlZBfGA`9qp5lP@{|T!1Hz1>o|&$9zfG$T+`|
+ZMtJy`m^J7FyH<CE-eZ^A+Zm3bHSm+B9Mpbf`M@M1Ew0b?fyOTQl7J#B)3}M?bhH&VIu-HC26c#DB^h
+DWbGTNYMZ8Iiz^d`I0a4VY#Q^KzFi->LG5+QCt5EF1G)yf4kcPpd#G=o;td1H5gC~Clt4Z~z*<(hznX
+;P}FBF;w-qcxSbqfm37pPF(iZ`*wEfW*(ypz}O-i6;S?=(l01h}fg19O_>XYb$p%E>JJ;^N)nxa+u$s
+B<58qNWbi&fG#qan$G0KJf0lf|45;5l{uSAu8kxua`USo_Obqcw!coIW5e}`?5_;B!Ne`!cjbUnK-h<
+KQYTeZ*Jamr1NxGLYCzVCiq&K=l6vP45#<Vmxy07xo1o>gC7Hx5fb%(YHrRNh$%C`nVGpE|9oOj62p1
+96XWxp5*<+vR^HZ}X=X&b`i|7%@e^-`-VGm|KkXg>KOS*W()B5xSuP@RW?2OM^Lh|9IK=Hl3!R#Wq<R
+Ydw(_Adl0(fnFfDk`s=(vz9P7TtBqCI414ldVuvyEY8tsFqpw_c;Lymwu>fRwEM|i>xm-hXwxqgAZ6A
+C!%+;<fm4FZ3#M2|LDcT4X&>hvI>Qz-&RzSjSMkVU0scv_gz$h2ItAt+wI6({KLqg>YX9EZAkxydMfL
+h(u8A{G@VhbKGHZi!&4?X$_Xin5OKDA2U0Fln)NfHD<hNc%X&FpT0{w1Y+jKB(i00wS#&x8cxWmjw?w
+O<Dj#N&^s6dl=jok^MGPD~&wM-|IB^1u0V8_`Oc~<sg<JRF9U?Znk7l{O?t*AMfziam>alm6h2c4);x
+Z9BY=miX;Iv+ckdGGKb9K-SH+1Gpg;X3SRjryoC>)?lbm4A`7dcv8N2}4y5%ZN#cN*0z4M>hr*mdK&z
+o;=ol3eBd{W8F9?|U#S3<?oMM-wVyB)KkXk5_mA_^Wfu?QZv!&$p|8MV_D4ysXCLF2Y6m#~Zm@q@Y{Y
+R;ZNFj77A3|OJ@_p4HgmnQVKLQct3P7H~3_W^K=%fhQ(LBgd1n8eMxUQ=5`1a4jH03Hq`>(1}OuI_Il
+rpXN64*GQXB+CGt<Xt9y%t@xA&a%~4_RJUpXN<kH&q-wwXp3>&nt@RQw<r|*@a*su)bF)^Y=zA_S-1*
+QZWmzP&P_Tg8QuD2Zj+3onTm8VVCBW{eC=#Oga9r2IgrKr=b^cIh9a@q*o6<_YbP#V;|bQ8201)E5Go
+&J|8Q!VviI%bcSGkmtWKL07m`A<KN)t2l&Y`nE${p9;DF34@9`m5KUHAr#4=vp(bVMw-01MFCsN%KYz
+aG((8VH8u($CqgyQnFul1{k@D~T?1PU`MrOfJOfNp-LET~}4(b-e6O`BcMd;H*cT`G(9^T&ippp*)*%
+m@?IDWxWhmp745e7$=J1E9Q{-Pxhiw$cVqu_3oi~c{h^kFrT9TRcQ^2eTccK>7ngr!E7K-@Strjy5DL
+8D_PqqZorK6L}#cQotN9>dng-NndMbG)j*V12}Dv>SWMgEbOgftyedM<v`7af24hrLa&gT?^&Xu}{8P
+Tn4UJyH_D;IY4S*lduFw#bvwU$uqewW*)W*5V0ym?P1$;H>V5OmMaYd;UYS00I?d^zh?^5OW<Q}6T?f
+vFgqpVGEg64W@>optxoB5BUg*vq(#~UU*5uAq)`lNglKvO9xz8+%=X|5LP{lrXl*Q-nUB?am!~SME=}
+%&UB(GR6e~)=DoCekO5Ox6{n7hP`gHi^1So_^Pk3uIAmrqltHgD!2XZ;g#eN#UnSdgsZf%`Lfy;btp<
+X`R%w$ng5d-|<z3?9er(p1PR_>0n2{MwOGYBemB!U}y!~)3hee<82tZ1r0Q<>7FHM$U`(3q(xdypIZ1
+dMgm$eg|)3v85S1}|NPEitn;_e_gi16_8P;GO#h-F2&A1-)vvvt`+N_2~HMzENMc!_4WObz?2A<{p#V
+SMw_}t#=mXN|oTgHJ0^*k(m=`73zvU^p-?vjf{ebiu7P&a?>xaKZL$I#*v(nfLwdS!ir^D<Xy}I2O#$
+DIU|JG7xkFE#ut2R<Y&hJ!nmzs_*r>Jb{T;ky<^A0!n1SI0mCt>2SExk+s<y_4RnV9PBtT&hF<jkIbH
+GEcL4);x?6oYETY8q@CB*;S-rK?Q1j4J^Ulj>75~Xo``%HSLd?GRj&Bduln3wM#lb%CVAtl|Ik~{AV(
+9~q_jK}%2<GhF`ifoWc<<sa3cY^I?h$|#Dgxx##stSPS`uomAL$FhyL}Dq=;9KNfK`dG*%tvoOPr$t?
+~3(ha`1Y^yX!ZTOEo}jR#BWzF49$|J|g;ydKH!Ho=#U)#d;>4>7bvTXD79$+&-oXbhlQS1sR<lAjD#f
+rRgbF&RbfCuCzlVs$qG(s_n|Ur3s;q9E7xdm8=8XiQFG1$;s*26{4nPn&8&i(kN6n)w<E?Q5m{+Id>0
+#IFimtj$^FCeOLFP3&eFAXK+wSk7p;9kp*Ru9DF(EQCyhI9S<L_Sy2N~o1hq!0YePa1n7b5Tyr#uuZ2
+ZC(<0j@S_C^HtW|1qJxG!WLJ@>S)6Lp(zNoKS<&;*3&`th2f}Q+%^hAYw5~V}LCv-ZMm9YoyZ0gU`z{
+6Q%XMyLh-hcwB^)OcZ*B%1H;x&1oFQ^*t`!XVk1JtyJpC)?X8`5j)e`t99NHu|1Jpafkek3C2sDh%1C
+@=~QG7S<_MU~iq_R4KTN##{HsqA^+Gi;|;4zCoh6R48U)dcxd(g}Ul#x)a)Z9=CD^#<k(^9@cIfPp%t
+yC<(zY@De=ur~zsOhC>LFi5Tm$qga69K`C_P(#?%|9<(mAO7>1_hKUlsPoVxnRt+Ijz=-;OuPx1|0Xz
+xBj;JD!zlZ0o@eMYsx|}zJ*4!=y%{B@W6X#3`Eln>SrXtM)_m9#b@2BK=J{OT+i=i&`~2$LdQD62bzZ
+MW7u{_HV^vw%>4QdrZHST^Oc79GHbe#Ma)0M>UX`I!F_jWP%01>^+9hBc5Lq`}zYaZ@VsBU{IRv2qtw
+ZK`PL^Xl(6&41A`{_k+sYzz+u2D3hWJgS+ZyW;k1JBr(M%7F4q8Q^#sspeIq~Ab*R_iK1{B3qH6lFb@
+~Ro)GH=iZtyt~1MTmK|tMe#ytUpxw)yMhO>E+ENQR6c7W?{8TA#c&U%J5J{8}Dm*ta|$Ym}+jN{z0`l
+x@?;$@P%@k-n$RC5xrJh@m6g=)59Aa2ly#%j=6r#3L?4+a%BAkH?OI(!f*RM{1o5Y7vXyv7ZQ_ov{{Y
+ld7O#6m3QpiwW2e-o~9LzD{E3?;hQK5>=|mE)IcJkk^@C0rv%3RYD~4@U0pR-QQ@}lHKqn!rZqGL4Eo
+#&O0YcCLxDZUGbhTxSg(oC=z8>LA~E`!g)yi5yh&DQQ-t1{q=eC^0HjEpLf9e8pafCFye<oU|K&J<MG
+4IYr}rXg@i~DkxL$3VIgvuSt~%=jr<FX>(^7GjPn6^;ZAiJUTJ|fPVRw~Ks`Kw}nYa6PbI^B&hNA6$@
+z!6To~){7!h=+u_1F};4{Ua1vaAFkL-RYmj}kt@fh_IbFmcagU<}uLA{GheeO-ro`Qe&2GN=cTq=WD1
+a=xGMgS~%<&##u7T+!>bulM*KX_5;}?2%1#8)r4qYvO@Mk#+$c#3nCJa7qKYfGRJBUpE`=>jM$KI@-u
+FT}E-}A;J;8CY%Rq_@c8m(lX@gXbdG$%+u<ycfeO^Y@epyJLjofRc30&3{z-NkK+^&&j}ur{@bFVI`C
+npxPNI|5_Zk|Cn9j!<{o26UOOGuzYASQUDKPv4}^Hk`|M=-$-Jy*@6UgR-%H~?42Y9u^a(5-e|>lR^J
+0E_{t9R5kvCf5GK{q)@kWb6jir3)x4JKFbbf>DmRO(N($;9Vq^e}L`_x7I^GhP)Jk<|%#0OIBgs<K^P
+WbBm&<Wo!XW9TbaFLg6g+a(bJTemqggP_V59+oN$rW8pY|+DjjZ3Rv0FO)a=$GWfUEs;B$E|6&O5h#j
+x$VqgMe`~1?cjU)OP&R`pvOEjPx%-4RRGA)zuPQ*BDzh>HsyeGl>TvxbH~T+lRH-YC3OGjDP0yByuZJ
+o#o!}+Rv(u<TzRB@B<8vA)Z@sF9<#?zCx8AZFZH-Rs2epWj!49))`-txQ}tXCw^i@&=-=L)pI1d4h5A
+cu;11c_G>>+(n>P~_2G~;HSxMn(Q*sk-N`Hmtc7DAGzDmb6)k0ANDX-Hx5drKJn!1=Fmw_YgVLl9(3|
+~M7%1Gq2dEk0&$l;bE5~ke2x)pSvKk|is>ogDC*{-9erApCaldPPaPu^B7>AKbq+qixje<%-Fp?lM#X
+!H31ude?DG0+lt4DZ56Oa27wRk2KyB=p*B0ZD=rlZ`+W_cf10hPxUcE1_{m=@rs(K|T(89H7M*nPHd|
+hZ<Xq6^Zj0Hcn$$@y8|8F1e4#*3v#GIoie$k32^3pYE!MQ1f`P5vl|yotB)S8&>uvI~Zm`9y60#&SY-
+`n=JJHU^CX(x8c^i0J_mbWtn{%enJ*LTOffSzs3Y00%)#89PBo!>jA||2pyK8i`9)zYP5KD_Ks9oidA
+a7;-h&<=t~cMS-H@m)yu#s)-kxvP(R<QnR%BMw&2wDr%CI9Ct{$gLNk&S>V#htowik%HW_}06TT(7As
+Q8mpZw;WuJ!dR2QS++=^6pnnVPxSJ&4BNu6@c>UQg{zq_p5|)i-hIm<Cfr8G%0Q^_gna1XxRAF=w~}d
+7JJ6cOjjlZdwen3^9!i!6o1A=xGyyzakw!@txeRyxkmk(BhVFm1}5C#~i4@8wd;ycLku1;tDr=`~o^Z
+t4tQ!?3xUmtK4SP-ZIhHM1V@2IbK$7vo7$f*ks_j`WAjQP$xcrHei4-%rMom(oNUg#~X-;A_f!biIE3
+%WWhDPtcM5<z%TW9wTweoNJkamJX|F*%SJ^!j-yQXx`~SPscHgeTN<WYkqqf$b75U%B6={IP49$w8M!
+_9Vyx(a8@;!<Slx(~>c)4N(Kx$Aw{0K<tyA8jC)!4MqHSDHv`y<G9DIneNf%}rsBgqc09AF&r1Jm`*o
+f#Tez#j&)$W;kj4`2F;jQ$<Ni~r)D~*)ZxC=dK)<mmS7TZ;-J79>N+d-11<5{sLy_TuEpu=XkIAAk_x
+vX)$D>O^=m7dA_SEx3W#LVnvS@#Q4jl=N)lSYuH=S^g%i)&ZS@(Bil)&r8U@j+^x7I-JDNsFJ31hajU
+79{i`QXNg%4ICwr2Hs@Sxhm$i4{el953T05r-3pu8v7V=4W;p1cT-B%OSZAaY2ab3HZs{SPT>%i2_o=
+<mcQD_9af=?2_fy)h7n*@4j4|O5_R62TwxGI6@l7lkAu^b+l?CMRLvd&byLxEJGo8EZPrw>sunZK5rV
+SXW_G+oEJ5EoNd+eJ2-=qSI&dQpMiLA3&pyE+Mk~ytTUys@>CV1Y?>hV;@9tv@Tq4dYcXJkaiJ9YKPm
+6(e<<jmPi2$?(2s2g`Y95E?Sc}tJtb?c#m0$zh{+isuInWQX7NFMN3LM`FGIA`=HqbLht5O2cHbWpyF
+c1Z7)^U^{c1xO(fV_dC%teTbfh+-b=(Wm=nC$mk$9`XiESfXdT*OJJC3zbsU|c}N*Hg)wGAPdXAkwSI
+O<Dwg+-Q*zWDpKXMHLngO)^`r8|1{^dk1`>Q+9+8C6Gd`GU-D}1*!b_QR|$c2q(7+9QuNsFR&+$<qHx
+IUJ%zq_#$*}uf_F**kIxGzJ<B^8h=~;OTaY2|M$B65A#U}9cfkAyxIjWm^I*v%SeC*n{)?lO%aT(Y1z
+j?*y4pQQgLhBpa+N65EjNW1Ov{XZE3DW&(hE{Fs)8%@R3jo07V*PTl&^$w)<9P`8Ex753CYqD^wWpv@
+8Mw$%y!M+t!VbSFZa!QZvlJaiUl=5wZv>!ibD6kz`UAKM(c~)9R!qGb9uuP*h6ljz#WS;4yWv`K5(0_
+pA_^XNA{na_2PaBJZ2xEW9*id}ibj52$IojJlZ5<kOVQA{9{{_<2mCd<%PtMhJ&JhT?&b4Z&-N42hP9
+J92i;JTF85fH|st?BOu<)Xw-?@3vMUAk}HQH)@9cx@wA0vpc*`&65SC#3gM^yJ*MwwGh|!(T#ct($Q&
+LzrUem7CY-Uf!M7{3&2Qe;LKhc{Om*qEl61fFHpB8tpOoQ4^u0-M(qUYF%nOJJ}skAt5RC8ASr^y00A
+!tuSu0>NpQc`VrqkAX@$fALaK&H^(OS1veu*p6r?l;kcbcs7P=N@=5+WGC@Y84J+YDOJtULTJNyLV?N
+t^!$#!?KFVbZel@rKCeU;&jOVTBP!Ne0tjHTd-34a51BRF2I)KL?<utsB$`6;cfwMJSjui-}-*n>9|_
+%qdQIcxrlItyL!Z)?1peSw750a=DHm#g#hF)_{~LKZ_m=H}MqW4fnbuAbW)m)pmjt|%t-N16^l=6sK`
+q3uP=QjdccH|YRND{8;>7dKrKcm<JlhxtlCu+~VvjBzCmgA!MV?b!xT2QSj<(`UzB&%=_ajtbGbxCxv
+%A$$cygsUG*Tg{p{D_4P*O)VrgdNHZ+h&Es+i`(<do7eCBm+z>XD9vQLO9z)xwz6yb%w?3Va~Y*x%?X
+_83Gbm=3IIEC;?)LZ_Mw|OZHM=eE|4&}11n*h>I4nkBVyTgrOw_B&Y{5qQzx#JSoC$;oL9N}GKEeSS}
+hWzh*4JN0ZRKxth>85=5>IPp3#?sk~mze`ct+F{Fpe7B8(iU2^482LR6#35|E)L)_jm~@$2OqLR$+kT
+pX19{+NQ%%)a*rH8%@BHL(HT0I*}e1xWz+IMa5^PlV=>Ti4r#C&Fsooz6pF*OvB&m5foNi|otEw9WY@
+aGkR&VQXbyS9nZma?=+})eYR~OWI(#)s^<yb_3r~cke=%d_|Y5g&^-rET}<%F9g<PU8P;Kw^svO*eGd
+VhK_)`-_@j?=Hz#$7mLYDtVNZHh4)Jqdc$gmehBbtRSfpKQd9hpyss%ni{@~s1GhVJ;MV=I1Gmn1;MT
+bg-0nhe@$TT5&|Qq>6yEVVIziNI-Hkzv;59S7RY$4a4plRSP6yB0wFv43ixRPQqDL(48+S8iBx~Xw^y
+AL0X-VhAnnoVKn&mEy?(jQ&#8+EML;k59B3ha%Kb1@0N+j3-B*LdgO*$3V1>1ngx>1E`0^2X#bOsA6T
+5_UACq)!D6{0~rai&tB>+Cz#<$ie`L8)F5M}dPQ*-e2QDFyU5PG~};9=T2ZN-4qzejY53{5lSN;|3>8
+k3u)mstSD|E;dLKIESX483b=)TmR@=omt)sy&8GRIYXgqprMqtVYo{_qIzZvTfY>%X5EoxRMaEUdHyX
+h1%^;qXmhLwnlj&$R^o%XbB03xq2{}d`mnbbXMrz{Nu8K25|RW+vnj&SgzfLN-EErSp&qUAfDE7@N!i
+Pw_n0Y)k+USp_u4uB4~IVNPK)ArxD$7HTH4gCzQw~N-Fv?D@AAOyr!I$z&1bOlWWoeSw9U3ksxGvxNX
+L9Ah{GSGzo8H`7-+T-=QQ0aar(6;D%&XT4xR3k+>GY^9Y%C!lK;5{fX-b3xNFk1s}48gM>zl{n(CS3O
+#klnYJJlM8}Gp45{Lj4lH(r_iXC)Vz_&W6sl}JLtiF3fe<a2%vXfI85wM1nojaAe3!XT+qXj~>7-Mg(
+hqbT2;O0>)4ZtdBBdwhlnQ8f|xXH2oS*BF70+{o*y$D_)P+3)uu5KozGNy^!7A)$AgE*GdjpEDkDHl%
+x-4y;*gD*q&5N)gUS@vO61Lr4)o_3^Tj`ED-@Py<0a4Yq`%+M~cXAAY-u}?>zSUtM4=)ING_a=iw!QK
+<4(2zv9EOxfGIac89j`VM&MZdku%AWiP8wbKIX|W@BNBW{)l?a1_2K2sJW{0@I?^SvOuYN_-={Xx&)g
+!OAlaQ5Y1Fa|e)|f-QU%(X&7*s!e`xLSa5xEcd!`UHk3ZIK5F@v~WdZknhz*EUQxKOwA+o&lsn4x|^*
+YjI3x!%U!hgdOOpWsSrQD)(e5nMnNZ3(!wVG$fyxr!*MiT=FnW!FC3QwN<ImBOfu9uTz17&P4vZvrcr
+2D3^4@?DEvrrO_P{t#@BW>+UakVV=S2=!ZM)Fg?gsoFiDv~|tXJ}ht2?zF7~r$p9$eWYY&TNt=9%}YW
+x&57EGshFt^Qw34G#B0i0uS0eEaCTCr^wuD$C?xV~3FfmE5pBh1&Gl;qsw_SGTbAdrScU(P=2e`1*`*
+?shaIJDnd80!ex$F(5gIt)F0QT<T-sY1(?s_HVcO$w*>IqD<Hh!G+88bT;mhoDfn6-E^UC_x>;48y=^
+r+sPJ;;%e!oV7a5m%;SW#}PgJg^sYQ!Xs{j?BZ3L~a1_}16IjrrJ|q&p<m%=_I^6#Ki4Wdd1_-i|@ku
+NT=W)Jc&_sq-`<M(ZbFq23~7vkx`?c}mq=-KNFTte8xHO_!%OsE{JCJa~%O4(W+paG5w4HC<j_1bzn;
+FnWDfQWGTxc*rFz5ws}l(8D}W>y{AS%->HIn<&Z3wd;x+(h%O-J>r95M&77VU0`4GWYQXRq7)dC1Sf-
+Zf|7U)nmuG)@KTsvtRXo7wt;D(-h#-i%=p6yZ@K2z>estao9U<OsRIk?U#lihCe>>4Yt$IS{mI=sFl?
+nXyvOAGg!r`ywPJm0z$*3E2CZ0uLG{W3&ido`--YG8`~ExA4Vxd;`$AB49elvquw=CXgORSU4xM}HKA
++}ax-XY=Fclt7!#@6^4Q+y7G&0@<F@Ql+9aXeP{DHqY{IJzIMr(p3G)=!b5zf9ACw0D3z_o=?^Xq%{D
+h95~55AHh{H?Xr(N&iirYS=~c00Bv*;>cY)>>!qHMQCJF_@(&#H%KBRnsp4A1B-Kxm?gYl_%MJ4ZH)q
+!NUwXL_s&+$qVmxbi!xX((Yl~GN&U7r*ls&eVm_K=dz%Y<3GU43f13!+ius-N75*$F?Q5dh2hJh2D^G
+5R5tn3(^UxWnm<>;t}|x^dbFXd#udh{I&*38I*L9pb^Ta1fn&IxN@-x>R{<(QnnrnH3lZu9#?B}{;*B
+J`+I($x_NI~Dz?0uc)r1agql+sz=mo8ha&GfMo2<t+yxM%ML1`(kL8)#%aJ2)^I~fVk3@B1fgy^$?ED
+NSh7{k!$l*Z1;7(6|EE$XUC1!mz@^lwpdwAJHpr`OW#aUXGKr{{waRCt^7tPtn%&rWno?pXJdj%+V$B
+So)^73D(l0RnM$^S9uWV(4zgl!nW}H3k7xWuSw2R=)*5sXaU&1$grY0n4=j<bZ66$R@OZrD@;+0$M%M
+5(e!P5YuJDwsgc&6Lw?@pn8)9+QgxQQV>BbAQ{Jh&;J#=bovPvL;r<aA)mz7%O`i|<&(1y64gl_1i%R
+u%IVGGx5Y$Xno*=(lf{!HZL@Vb$>lU4D%(AtAWnGOEh>en`TzUN{|8V@0|XQR000O897^_9A5BOcE-L
+^4u+RViB>(^baA|NaUv_0~WN&gWaCv8KWo~qHFKlIaWpZ;baCvlSZ*DGddF?%Id)v5?-}5WDPPdY5S+
+SjKdv%kjd2z0}W;c0~Y`1roB2yG3aZM3ig0$>J+24LM1Aqickdhob+4feuF#!@70E59`0L%<_c6RPK@
+Qbcy3l=7#7qCkfi(Yh<%y~$kezE@U(6^VA+L`j$c}+PSH=H;z3*3ZFoWKodsXJq$CsQALJi3bg**rOR
+p6Z};ba3#;{iB1U`_A~vN#+b7$+|cRa~EAlFy=h|;oaX}y?NV{U;^J`p<u_(lef?0_m?l8o_zoIgeo#
+&iR%YY<_@&&j=zX_oIsUy=$u_Gc|5suXBzW`6ZuhZbiu+2k9$QNI4b=!7O<I{_~DEi+jZ3A4V$q`74}
+0fNGGi845)(Rt69v`NOYZ4K)x<iY3imy(si(8c<u4U*bmtRzVML`O^Fkqhwvep`|vk_ZzHI2eGSvZ4|
+D}*EE$bC4@NwK62zR10qvuOn|O038ek;+oP`?5J9Y_~pYjEM>pHI@7P|?Dru|)_tLuF4E}(&LlbBj08
+~S~^7-Rcir=gdmE;gd;{1*#Z?0WzNIukyg#4!T;aqcHfM6TD+E?t{6^aT~<xB?@0?u<rm5R697L+7+5
+DUDFy>N+a=6!6CbR(ks`hVsU)cdp)3t<_H@IVxp2YRvPrSoX7776e?pzLK%wojZ5Dz!kzVs@l#8rgKa
+%chuN>o{t{E)7WD`9~0)ZFJNc^MxFb;%Z?gBy`H1qx|0c;93MLey~Bg@H*XFUKwpn~f6&!`2c+e|{~=
+$}C{r})oShk!JUi<-&Wi-o2_Uh+aW7yjx#NIgPe3*e%?*5bq4VC?nX`6LAOw<u9#e>I(YrJb@YOs?qT
+_q_mdmALH9a2BWC{Y!1a-CihUks1@UH-FB4bpn4BiKXW5%f;Ff5X?X1&(h?P1<xd}+M6>%6;)7_>JXi
+()Fjkm|p4mZ(zvbX7?37Aj|cmX$RVAdwbQcxJ`ua}uXsQhDpeev}kponHlRe17k3;>H+o+Nl7R3oP`B
+`+)^r=Sk|FcZnUpc426B%yP#c0<(xGKRo?=G5+G^v&xI!7y+BFe|+`k?{8l}etJ^G<`M=kRON9L0i!0
+S01R>(yRvO*TtHIdY8=Q;T=)x?K!3>oPk=4myWG#oz|Dag@692qAQy7pugi+0Bgr!KM~Yl`PQMjH{I|
+Q~d<$p|{obWN83{l%a7G>VcnEVs$~rPXj3#I#Fh0q*MsXT2(N3@>YP91oX3+f5AWn%f9F9Dg00~~fKx
+=&~T3B$e*XuZn4Z^$z3>_ySr!5EO1q_o36bYQ;ey0Gh9k;%1588v}-k{UzpYGp1aQ23~?bCz(KM(g-r
+@O;Wzdh)g@lL;0#9-@m9=sg(Pfzy$>!05K%;&Li)5~v%Ej<DBUW5sYBOY|RmbQd!soV1LQ>!N{U(=p)
+)dwF-b%|STY)c3J_VBrC4^B_t4~E0N0n~gK>W;-ueFg}`9<1aZd~+&dcSs4Xzq`P1L&Z9)xsThu{^^5
+94+rmuh|N7`*uUF902EI4I{hx9l0t;5@%}920ua@&pcGp6$%?)b{&3<EFn7S*-F1FWIn0?fhz$x5{wx
+&EA{B`<W=`bBIPiH0EIM&qC-F--0HgxG27}hlw;u=La1UxB>9Si%25AO^VNHU&K>IMUOaeBskR?{CLW
+a;+A3q*;k3MxWm?e-vDk$wh8)K+{=r9x(h?hA#VXy-Qfh3t{8s?*IdYzH>Scr6i)lKGvtk$O%&UHw%U
+cgaUbH+IRJMI)ZNVU%q5%YYYu(($O_tu>RS5j(o7R(KWgu7%Q=!LBWMN#HK{;M!?FJ;?$z?flvO<JM^
+Yrz2nQvLyc?Ic|GEYM~g8$eW477GYVcnQuNgzA6<Yd@4sLgwsMMw*=-%c(wAQvow&mr=YAlB+*q`>H2
+e6?(Z%TK@Ry^Jw{cghw(nPE8;4IV|QpX&skH4KarkRxb5ctN6Y>5WAiBY5XSrVf<wH5ywdzgr|1@xVI
+XFo!ve}I_23-FD}|S=&XYtPpAH67JJ6MPNmcxYpJbPD=!ryot>L4wKaHr_nY3{?^@X!qxUzU3tXvG)8
+6gvnhD<m)WCv1AOplOu3T&%?Vr?2t=&?~KvAaJEP>$DWWO#Il+Xqy1d~$#cpz3#717y4CYRwUTQ|u{I
+IStHk#K&pfuhC2Hoz!D9W-2Ctq0b_1)b_h3!<RH07mj7TOsnx4HRQ9BI^cZH0H;lA%D`h^2odE#O~6W
+?n|ar<g#s`a=+7#r>kj9L#=*v)zEf2u8?B3ns2va#R{45+=vz`$>is0t1=#T%xW|aH)}PlBciz)!d8t
+UHf|jk8=&IW5n;mvOa?sMZ={;j>GPo`n9sz^#v~%kl+^K=c-WX8R6B2>mCcR3g(lj28hd$sr3H~D9x+
+~x<JD(z3F_MF)Ui{9fBoT4-B^WRuK%@bze(k<U3E*%^Kn==3ez88Wpy*d&@u{zl|W^gH!=(@qtH@j-p
+-qE<(fv`d=qUg%=?)}Vx{#UmEKS%6Z{SOm`c2nE-sf?*Tb@nH{QbL2Htq{bn7f@w6|(`)+B?6bbMeFu
+D^M>diZel;KAzAqt)@l)#?5(d-ry~efZ$f@87R_xTw<y6qbeG@Z+cBcBlK7Q%q-^OxT3jaOH~?%mgbQ
+uR@-524e$u??;edo8;2k<w2HeocaN*bL$f<+?ns;(qK)J3%81=9FL`iKv_mEFVroI)zgpdGQRAq{C(Q
+xtg`N<pUiohRJKeiIDd%CPh&6ct}|idbmp}2NI)Fly9W_r917g?g-F@`KmO<8pNgAD`QF|%+uUo~%Cq
+fvKpXEyJhC^Zxh;@}wSvI$@Su%$kYcuQ{SbFGXj>_i`?@J^Bngj4m7R>Qhl=BkF@Z~Iu~*v2K;Ui=@F
+nf^(l*NV7H@Xix_R;>w$S-hh42-cobin6!u5$OcfTCn{}b*N`v3mDm`z#CLXX`;U`$}|irzd~1jRN`5
+$$%d<FO8|xC%X_Y&sHIx_*KI76@YK>b*b3zk$0LPh89CO6v-D+c60R9NZ~@HajB4$>bs6Z(K&IK1VL&
+TGg}lE>5We&s|lM?|I0oFg2JS9hJFZQiJJQBsU=jkKqX`h@t{|#xZlxF`!R<Xs*S>Fhm_<s|rt}lwEo
+(A}CWo1QNP3@H`9n*bO$pcm&nM6tU||upmMO+>@E*W;e+jF@ays{eWftQ`>{G<EX`y3wYkIs~d}ZaMb
+~GMp_PMUFXb$p>sxSy0g)lgZZ?ghp4dK_ovPv8SZvU=RtRI&w0#dz(J6Q^C=B;XU~Z^3^P0e_rnPb6X
+G2e_DeNcVKq>QFoEXzwdzSZZ~q%vqjvw;tP{$~IH4ljp`+biuUF1{dfffX!}q^m{q>j5VEAdcA`pAT{
+pW7%dI_rMAX+pw<Ou~HR>)%uUxcls40YA&{lxvStupn_mw_*m4gdz;HW+tMZY}@rI+2?|aiK$~C?D<R
+f~Qn9$q1>`%T)$mOAs~F#a)L-*hOwYv|vLzQUUPzP8$T(a0H~#9zm;2Vcgv2CMBLWVk@WIvXHH`DcWj
+Au~t441~+F)qmkSm9gS$1j%l0%Q<5qtz)k28(x3+sogSRiTNKsZICigW!=D&h1YMlyqy!oG2`PI}cur
+-|PV<7n6f}_xa1jx2slvoh0lQSJ5om$(Pkb+tPZhmbNJtE%f0VN&le};P8_X$SOty6za5qt`bD=^p|A
+2a66q&I^7b&@_u)&+VLZ^b@oSw4EK2^#Oqco8L`GBrR2IW~>jN;gs5JYKJO#?>#fFp*U$fYU4!j0tP(
+gtk77CgSX@Y#|Q$<7R6tl*Q6e_|4kTs<OL3J?w{!SJPZ)`(R*q8Kv7$(5W!La9U(vnZBN6cZT%0_qPb
+KxnN(6gip&s^L)p2vp|ALo?sYsYR%i=|VoDvObjrnxv7WIXtPuC#`ni`N2o&%mG11P9E+4gKq{s9H>o
+m6rMQrp2)#wS@cO5ZNY-+>LdvKNWdEKd!D>N^2HM;Hd%RrkZVB`R`0c7>4ewJebr_?j$uLtWcVJbz+r
+<P3#IFqzX5FeV^}1pH&rkw6`qg~;Y%HuC(w2lXAqv?=>5@+an{24Gw4<(^<1*IRj4Pgo@WqF!V5p<A+
+|k#XO{RJ2Oj`>jU1!4qR&%Q?lEdYnt-^HKDm@~)QeXc{1?R6YGKLG2CNtP+?&IIcb8cVICCvH_%`NlJ
+fYQ2oJx7@CFkd9l;!`924EJ&p09;hB$q7DtG9U&#uV_ZWi5!;ESx~wY`x{Q-e@sDgZG9>-N1$}eUpZG
+V4i1@aRcnzghwwD>=WOrHr0Adssb4V88rc1iG(eT?-Zrptpa=Jj<b}gVwXjJ2*=1~ULt2SUizr^_>AG
+-TCAy5C!vule_M*b16C(c6?q*vqlG`f05zijaDz05`;YJ5)`BuJ{Ro00Uy3Z-|FW1r^Dlgn6K^FyX(T
+vGL~xiMeS&0k=k>{J=l<az4lUdP=9hCQ*BDw)LHeJ(j=2ZR!~7)&VaZDxYS4NTqjtk<-{`44*W)p9dC
+M1|Ra8B!1#6~+=_7;i9OMWf9g&E_D;QeOkvi&GgC4_1ZC;4S&wSL2DU4vARNmUgVZ88#F!_qYU5P)ug
+R#WZT9yT3C+a&3>POPcBaPnsmO%!i@G-72jiCtahfmT<>v7zBY1~9OEgB0z0h$2I(;@t>Gl6CkK#eGF
+>|Aam&w>mqg;@wrCRq^qXq?A@qht|ZeX&9da}X#iWf5Gt>j){w>o881b<jN0F_#IIG@D0(6M`(L;~?Q
+0K@^GVfWl{%Fe5RvXOTtyI1i#^tYaBIY#`asSuz7rBq19S=mY;Ei<8t`2XL0v4~+@(pl+8DC0V5&PGY
+uhmcc?{TZet4-+k4A)|F4W4Spcz{xpN>LxUD+kVknvC^H=j4S6KTpO*B!IrGkIA%#YInBwyo&oJeKG@
+gaytj<<&uz<*t8Y93@;*^<9zs$i0wdjYHN1iC0CG*kTsBaN_K^Dr<XoE?-F`Q+Ia}qUh8nQeztAhl5F
+;A5b)x2R57kO}52L^aq<i=Tnu|Z9-!4Bf$c*3<#9YnqU$<meyFD{}kZpK(_7Hc3W&Ra^WtSr*d*f=hh
+T#Dty6B`6$1!NGA$j7)Sj&V^OzoMS28Aa<ga5ir6<(lfq+N{}Yq-p3m?$^UC)cX$So2I#l7L8j?MPbP
+0iXx-CF<PEvJRe(?N4QAi+M$P1WX|JhFDRcYd@n=zgnJoF_UlJ7&Z`+0mD?FQdcG{fUy$TbJAh-J4Ld
+++Htfbf725Z6>IV9|wZmb#ob`CX^U{~hJqPh(!|wct8~eD!)YzT+T-b6D)E-RQ{o_%8FzM_LdZ>Ju$2
+<L1`2{NH=h3QV!6`c#p6=}r`-NQ4FlpJ=qlK^Kd?-(CgYeUO2nVP9)sQlr9_;^V*xAc-yz;E+$4_+n!
+$R^WwoQ(M)60LV<nI3T@&0o(_Aqn(ja@c2D^H2y_Kd}KU4=)_mVWvx?m}y$8numrOS_sw`@go#BYnLZ
+0zMo2mk#jI#LsPsxJp-qQ7o&bwwVrYxyBou$CpaT7*p4NidfnZw$~?D<E@~uRN7NaX(`HtrZj1-qXsv
+-UD2UHt6Q@fue3ERgwboMdSu$XYp_$Bjw-X;X?HvHtkxwrJ+)P)gjRJd>)>JAu`}aja$xWJT${NTK}x
+5YHva4wGTT*udb}1}cO8G~;L(`FJzU;7uy6#-p;d^pLq~khrCj)9q8;F?K%h+K@Z7KjD@6GP%_m$(P6
+bsvD5w=?rk0h@-s&2%VUKP^=p{v5o3+G8)6(RG(pgaZ$<*Sgq$+fHV~N>-FV(Ep8lWao;e5wXj<U6I&
+^{du-0?JwlZ%}}Yq%POt4o7Fe?0oMqS@f%VfQ|nOcmQ{Ep#nj2kq|%AA7s~!KYPf7WN;XRzH~W|Fo1?
+gAB8w_F5^VihV%}Wl*uAxmKOJS)Or1if?rpD{67AN`X~t%-TXLW!C1cmWz7L7PRlQN-BH}>;itP!C+^
+l3|dNEK-@xNenNbLoE+3?$!2|2Mq~~3SZlx2+9_!S*4BPU)xJfw-?{PHtM0Vd9<?2Rjkw<s^|s1?ebj
+G+`J|5QcQ!?SJ)u@RDJ;XRsZ<>`w>Cv;J^eLSN^z7rOxcNadraLVqU^M{J)&*`PoHw5UN>}uE5Sx+z2
+C+^Rg>P5gA+>Cg|(bilUw%N_sJx?gC^J=2Pl3}sFISB9jTxRc~6fI4-O8{Wryj@!g*-=?kM^5INIEy$
+5HRnbm~!Y<5BObLl!u91xR)*gw~@hCRMg9K08Wp(96f23~y6BmPojAt|N~noC{ouhY94xQy1y0Luv2`
+C-Bc1z(gk)0Br7FWa1=MX2CC@DgZHq2Gv}$AZT;|g2=eO6Obd^ZiudqY|cK0Qdw&0Brf{2;Uo`VnLX&
+V(TfV@Z16BaW!U^g9JPjD*v~_G9NmIThYdYC+^R={FYJ(@7SeC#;9t}nyxBnHcI?HsFbuhtY5DaGN=n
+8q8(X@pHDv$IMEy&dsDBwFA7sOc@10xhJz?+;SEn?7Wf1<z=&hKqHWhaZ)~t=KyJ6$j#-`n*t*f;11h
+`+po>i9mr7c=jTfd}Dt7_<%v1+Zg#w&iTnmpc^-O73^m8w-r6&^^-Wc;$ZwTiY*slv+ik2ABCuWG7tE
+6Vr<9ei9nNM(Fny+~`zu2Rjf0?btPNuifQxzhd?YWY>j-XfBOz+$PRo$2jwsi$wDkE-6jB$}y$&y=#S
+j#qT}t1#DU@~_j}uY#;-^5gP`2+!2%Z`9$h0<G%w2VC~BsoP(xy<Y{`pv_;WwC^rQS=(YZN$sWyF#}v
+njsCS-{x+@tD#R_d{3}}hRfuWmD{4-q8ZHL4>i=cdVrc|W$$ooA0eDhYYZ*Y6Z7Z~MLnDETM!~PwYQU
+~&-fRX?1-sTPV7(bY6=<DVz(!^O7H~CY0h^csRH5CfSwQ}xL9c%+OMz<kP0Rvd#R_Q2_4<Fa6R?8Y-c
+G=<3#dX}Zzpg~<EJmHyPc~t78Ix#QLa3VVo1H}+%+_<i<;Fouw_kakbH4!Gt{lWjOKMkx7r4Gjjpv#x
+0)q|_RMNwo4VI?L-pCBhD~8p?bvLLRUj^_WaoHXt8;CISJuH^qjMeQ!P-8nQODj?{n`q$qK;iwzvj8h
+v`z2Y2K0KG)`n)a4QR;24=mRJ<+&zmj=OC&uxnMWjUiu9pT131?5eJ{6>i>IQw`gojEyv{t)NS)`de#
+S+klGF=oUuK&(pkCqP9-`t5C$=Nb9;u%i7BSo3*YRw5+Xz6S}WZvs~%ALCIPxO<TLTPKmmb_)92N@8O
+yG?h5`%f9APnv^-So^fypyhK!|b8)-tL%3C32y#_QYKX0V_Y-qNv*LvQ2*($3$_g-?_Q4^#!E2?#)?K
+@0*!@h#?)>&`2f7Z&jAD^g{+v-@K4wgOHyfy08fQ=82_y2b^94vQRx2GX(E$FrtrR{|l^`)&a8?=G@$
+K;TO6stP*hm@`;DAYFSJa=1-F6(pys6(?hY^ZU2V>-|qwpv24x4fp0zpB2oWizI>nnF7C_rp@Pu6CR&
+XNmW2K(U#JeKtY8mrys}NjR_T+TMnJ3tbsrCFnhe`cvxd!Mw!P{Q{M0p(cjB!2sqD9<ws8c#^3zY(MN
+aP%f^jG}o#dS2oK^`o}k=4E;5ffPYg&{c4J+zo}P#N%hJjrCkaAp>!fg)eG2g^SP=XS<(jdWClk_FNQ
+X~KS<JAdo2`nn3ph-Xcax^`p4;|4}jt;M_%QJ^mbOQ=9yB*e2UktDP1nq|Ke#9rHMlqoV~->J-W)Shw
+0AFx=x~Rh|4lb5-z6B?vXR^MZ@PdT4U`;j~+Rlc5fG^<d$)atuEQ?y@qK3ul>s_NV+%j09e|#R%bcVF
+P*zl#PH5R)|>UZ&T`JeykQa#41`>~W)9~=Kytd!Tkn4<0fc;jZ<w=|nL3!l<TL@WNX1YX!4au9$F9dN
+6qP$^u(_S~nzkBBbT;d<_fI?h4EN5Uz2E}xfApa84sK97K()!Bb4)|0)Ky(Pmsa5_-i%#uhpqz?(oZb
+9hAY=YsnzbBzTX+{?Z`VF9auhWS0(_$u5V?xD)wFxZPtm&g?_iL^m_Q;mK0S*1OuUD%r98A17!i9(T5
+ueCON{Y-v1s8M{vA}6jhSxc2GAb>@Kk#pkxPyNF{0Efk>ckF1t)h;BWv&RO@PE`w!u3+gbgNJR(X<!M
+Yi~T{(QJAjw?0G!nU@i4q}IarLRFw{G&jcIjTzdKGrfrxjPk8&)O56<s-+U2&YLwM$)h+^0D{c8G!J&
+cP9rE=~Yb&Rd1Iq$kpL^QmiUNYa?#(7ERvWN-4(Z6Dmmtfq(I1CdPp@R1&fha}@akjsZhS?bCG3`&8t
+#CIm@HMXC!anvx!y;a%3$CHV#yiQ8@lNu>!>ZZZ7tdt*wp@yGNP-GwAIM39*oIcGyamvp0G^J2nx&ZX
+BcVPKywJX5i_k5{`7}*5mW$5nzl5;f*CHh2w4&S@Z?ykb0(TfU&0MESawyhF&&HF&HH8~x@vQvFJE{v
+h*DzI32m?@HRF-7rK*eoe6x*I_st%rS71N^S@BO~JrCs}gGEebWFM}$-w#*os7l_*Y22AGLIrBmWW$s
+Ryv?_NE7bzI3U<~&6Mg)|}~nZm?|VD!~<K>DsnXN-79uS2RH3A)TJSCZDJDgk^i027!y^#$=@U9op4h
+tLIjP!YUCFJx$HLau6&aW2>d!5e^x!{xkL38imX6aZ3R;35tuu^N7-e;X2_{*jVPyVJ|Es9x{ZNyFxR
+YJ$E~3sDhCx7rko1YrOyaQq@+ZDg@@zjtZKfn6!#Xo4U<HFr@f((qANdpR-krqZWt-A!C<M*Stl8lJq
+XxO_=*1xh2!%Tiknl5k@QuO5bg#U6=n50+^#l&5N9jk!$IEni=2e7hyfldXhiEzFrBEDX-d=>&p)mXc
+u(+3EPwtu}QHN{=}S;YG#dKF_Ia5@l)R-eC;1GYIX~uoVBUT9&g^<RRG^G!LzORJ|(2OZVHfAEyCqQ$
+C1@bt{3+mY6h!z8bNZvRWwMeOpzc(^l2!v{gkqbdhbF<RMrU>?xtNh=!6g40A_Si@o|P_&miL8Fqc0K
+CdEc3wJhXZ`BRBAun`FS46ZHZhUUP&*ptw`J6AVk2WY(Sv8f~LsuRfl6cuOye#tl@etZ~yg@rP9g@&n
++llpy8z`)Jh5^O)w<vIZAsa0Vbq7=zg(p67mos#v`o}-~$$6l!*eDvG-kY$Cdl8ES{@Fi(l=mK;l|V_
+;KvV&i4q6RgpS{Dwy)Ld0<bK`0=f)rwsalo5VE3691EZZUZs3!HeoJpUAOEBKsnb6F<^6CAqBYFidf!
+n!8m5BlVg6HYI$fM$>tyGWG4(ZMlw3Zk6+I4mf4W&)YrFK|IJF5#nptCf-6(;e?RcXUa?~Jw9Bm?V9D
+RmhaTiz<ox{PrUAGP=>Ay_}DU^U-RyHG9eqqD=r}CB^0o)dmCNEbyS34(i1%O*8WZmlq)eS@?%Cs}Qs
+eP`-X~Z&-+o$2?EkH|Uew+ROm1lnm(wz5?nkN3wp7&*W|8g__V0jbMeZz!q;XTjGvuAa4R!x|L_ZBB}
+)oJm%a>u7^I(wQ+hU+G=m|YTUlvx@bgyc)<L;GYQVc7g?cnv-^<Tts9y_65ARPAhXsg|;r6CLoIW|tg
+#(V2#Ne~aD|EdCN2ofR}XMX<O**dEw=Uk6411vlZipb1eo?!KV?prd)g!Tz6nedIuo>RCbI0zR!kgk~
+SbrfuUUq2GKXsPZ;Iv&w^q(g!A1nqC~&*EDl!P}KG_T~tbjnZ+yngz_g-HMDM1XAUcE5?FQQxt%kIs8
+6mT)&lV$Syc#Xt8HQz+Y<y=QWA1pXN;FoNP&ol@E)^^PPKR{{McS}GZ9EX6f2R$sh4chfc0J|)?>2K%
+Y@h0ekRre`dmK}4K5)1$J%v4!EwQ`V=BUQ>u)5l%Wmqdbn7o1uPxmyd)uPTg01D!wbjK2ZtW0(U=&-q
+wR;0ukBw^4REdqM@auFv&~RnunCzELmjoWl3&>cy*SJJehWavC=c#}$q`|<<w_Yn(_GF-Ngu&dYLC7h
+0e)p#GW>5vUxp#vbxM~wv&a;!}s~68#Cok#G+Y>oWYyU^D(ZGh+nE`xxzX$ZN;_cf052~Qb*A#B)|DX
+zRn|ljw{tv1UYyBa7nVSr){tv2fx4hHP=Kr7y^g6d07X2T*z8VSPe_*4U0oddnq1hXP1=?Eg2=(3&s?
+av`j!@$bAq{b(%U;boPYJ&Q&j{cD@bcwvt`YtpyGAIxLa4r}1^OkOC6t{bRKacUETQBap$c*vX9=crg
+es(e4`&Gto%zKaBCIuz?60woY^^nOl)Aso7LK=SxL8U0wagX=%P(ZJxT!&+6)J6g*ytfj#~=l)V0|;e
+O^y`^H6U57+{j<~A)a7#3bt{0>1BMuY;wHZ#aN+4xq?Zbhb!r2)68$lR@``}oyz{h)AsS*hr`wH>bJ8
+>ZP%L;b?VBNQo36KU$>Qm+bU*D>+4dqv#fqUZWYREXcXWH&D7RwYnSN8+^4jtW49_hs$bD~^)v7K+0q
+!b{cFC^C)=BAxYDO#3~X<_d3J_u1J&21^1#j<xCD!L&}s;6kk0T3FZ+7nJaByYcX)7i)`S#0S^bL|XW
+FWY&du{9gyEO>a$faFF4I>!So%K)Ap|!T!bIvf8y?cPbAq0^H?Jw}I{wWSs1l@Y{hOQfcu;#FS1xO-%
+USBj-PXpi?#%VWt*lC~YYSUj>FteRZ>-Xr*ud7*yIMls=5bJ0_y)$Vw^4Y0?*44H=FI(NW@0m$$;_@Z
+RicU;&<K`0Qu{piX>p1MU$fX<EO4L&Za7QbnH;@w8iu6C9FjuU(@dl5AKx_`-T$#rAANE^v7F1pJNp@
+Y_Q87KPG9NsR)^}M@ld*N^{QW$sr=5tcoWAgl#)w#FKd=Ul=KogJxn@l7ebiYSd9&O^4VtFI<P4LV(M
+bgP2AX&vf8}FRB*S0ncCxc75B&e&Q^y|T|J*xPm^R_GO$~nk2QfU)pq04sx7LzQAMluELZdlSD3qJJ5
+5RfgK-=69Hhnrk5^0N$s6fAoPP7WZ-2kLH`wppJASbL*TLZZ>X*NCiAas&Hr&$8jzH`OAEi?b<K!Ycp
+74@E%X-{kJzP+y0og`AJTbe|TF_qJh0kc~z20N7)hThlQ7(by+vGM^!BwD^U2zOZV6;JA-qn%6rmdiM
+{~M6621{7%ZL{P3Ij3OxahL2a<*HksMX3|0D(E_o+@+JJ37}p-vx7zBII0RbKc1SqsnA}zv(qP^z)g8
+D2@d-*h~g!Mgthm#@XamHTS{kA_D$~mtZD<-+<uaszM(oXJ!`ymXQx!n-nr|~plsx?J=(8vtDT(~d2X
+n%D?<ALQGS#p&xjINo;%}ZR{ELsw?6f$@rv!-%Ai2rZyW>FodD7C5FG%~Sx^T{qr%D;XV?#cYRWu?RU
+z(<v}p%;m2Ks&)W&hAwcA{fZS%L(tQ=_JL}pbv6<HN_`&T=qRr5~1d2hD9S`S-AXp^DSmKqK#rPZ*4F
+}d=mE6IFNDQ`uFa!X&Z6)7H6E1`$Yil}CV$_6V^Kq%D7vO!s{)hTTR?G+GQ-ibAm4r$)Cm0{gC+o9w+
+#L7h5?yOaK#H}}?i+`(4lDa*TuW<p~zu(qKRTjLty^PP?Rrvh%{pT;z>sQ*ao_T#G7u%*8WO23qSX((
+s9|tk>_$>54V848iqKXfbvQDCvks7SH4i7Tug~c<~rK0tY7JVQPMOS3ZS6yDyH@#H8OBY4PK01GbwS2
+y?PB{6^^F!dXK6*i53%Ow{t){BWaNCuXvW$~|zI*d{^!Jnh`SI18XK#zkaxFuS1rJgw(YT(MF492BH-
+H5xWJ<|I3!6cJZgEY458t8RU-=n^@q|mYJSFkCO5}0Li&)oG+hPTwL@IKPT=HM-Uiw0%f_I23cqJDmZ
+YKJ>vFCA-hvo%nu_si?6q>6bh<JJEC=aUdGhJ;66>iSKHz+QtkF;i!VJ&%OYbXjF<*H~DAF-cPHz)#B
+ul<WWm6q*fOhkd77||sErm$du6M)&g4x$_!dGqrriovqlg47~sDNl7u6V%km4csk((u_C2>|$S{Nx*~
+>xUyQJblXbHO#%jQM~4zWDt1(e-Ip=wVORF**p1;+VoK|z+Lxhb3=*zd>$q`_F^GE56^RP-g<nMX*iT
+S!!8-$F5*ZD7Vn%sv#x7MffT?8R7RX_&Rx9I}yAw~X25|K}B3%ffqj_K{R|1~tl(_{W`bg*Ym=wOfIp
+<QT(^Kmt4@T)Cg#K498erA7;Nhr@Z(Pi|F@v6lL4w^S^y)8WLWM&QMtG=3IYfWb&vaH?$>GZj9$ct|k
+<z7&V~<PySq!rvgQVcgHJHaQ3ZP=H$_FMGs~rUyOyv>?VrmH@uU3#DsYp|()x>vcP~meLxQPzqeyR*l
+rFO4B^ArDr1mp|3di5{-NfDat{Yf^^CK-+=T03r%%2hNzsSymzkTlH}QBoK>^kRf}7}IAt=5ZAqsRuf
+(pZE)*qKiWrKx0^`WPDYq;8bzyDbUDM=!D1NgtTBHMIqB^q8`(j{j7rIK%T;WP#6O+{-<1ipy8_#h)?
+CNUq=(k_;IBkWNY@cz_7_dzWfA%k;X2>)vf_lNwynju$&+<ruA+OXz(`EQ^l~_Cf9Mj2*+@Ag<o|{bJ
+`r%OxpZm0`%G>`QI{@0}$UBTGtqbxml*k-kY%KdvsOKMC)<o`$oOXwTWd!5CIlo!K|;oL&#I}s*LgRP
+bxCiD%-Qzo#45E3^O+=;!M37Wpp;fZC?t_<q?7mhFbk;?u&$u7fdMGOUaqDs1yO_+1Qw8V`F|5$${e^
+n1FoL0`%nuov$d<U&!$)@8MAN01@AltPv<uJ$L~W8g9!ETG1cx;&4TdVp1!PvXEe2ayTi%$X-Ja%7ho
+{p<xPR11yVBM;LHKK5zPZI+PJzdlBk4A)93{VUSYT1O+`Nwf`xky4*LWQ4DL=lW#+ficsM7q>#wSldy
+$;>YZ2IG*C+H{$&BwIWFU=-1AtDwP2z;DPYrNl(CXP%^>*9=?#!2g`yl{06m5Z3iMg2KI2p9Kys-Rxo
+7Hec%TE33LF&x@)-*5dg9hmHF4{x<U~4lnMGAy3~&OLB=}KH;JGlP_vk?QT*$dd1xFgYIg|y8V{@Er<
+?c15W|9cVPnZgc`7D+@kc%u(lq(^c6$cax<!B9T#YN#k^t908CrIguuZ$kTqErIWQNod5sgJott0HOx
+(hc+1`8%3|4QP{s#Q_Z3g?i#(rXcw>lQKfcmRf9wV3on+OOS(jJdp%vOgPY&IZeTsILgVHYqY_d-Lyu
+acs9}URLu?%ix+8<>BB}o^Vm|E$V6)RN9Qw1m^m==az@`c3@4SBOBCbtaH2zMVT3`|4hs4Oc?VxjCDX
+*9+PB3Z^qmgEsMSHWS03@D0vYpS^>RTeN@$R%U2AwOTtPfJro#ce6eqj*G@S6oNO_Sg;7)xK?n0e;z>
+BGRN?;(6Q<XHk!sp1Jjw;JPl+g6b0Kz`n|L82a4aCAll2N<X5p&f(HmrT(5;Pc8k;){L_y(bb12j3{V
+|0I?^QCN4oEJqMjB9elLueI9{(K+<YSBgki8;Q^1?(cf&G94vFN%Lj5<Nm$o1zTXk#l21o#|&#JkG)$
+`cWviBSu_Gl)@rT;5+34J{N@wP%;67V!2Q%GATn8qzsWu83j0*w1MHko$2Bi=!7}WU;<B7VcA6nj5**
+AmJ3sVCcnejSNQU0p?;3#fKaP)yk<c?3+wi*MY*|)T7w9_V0x!PvqF51j452YGbq5*(u??6WdS}Ds}t
+gsu@CyNkTmOIR*4sqd___if-qV$8C@IHTu5}l!cK2a<mV=#deCwRglVWL5wNi{#^kauQ9^IRr&&lJk|
+sRgMj(GVDxent1~iavKgh4XdIajZ7$Kh(DwfJ;$_#-WDfyXSBvX7xnxkDZ3&K547386$0|@?{vOJ{U6
+7v|TIU)y`hFSu@a5Xcykb~z!jqM8<Dm+#cpbvyEILuI@$owy|ZoSCH?2`H8R8o4jJF}eA{F1ew0&>>S
+8;tls#Yq(Dr3T9=4Uvn1pu;B0A!o^9Ju382`?^x;rR!XvT>-kX8C1^2jQz^qHih8NpUMKz;Upea(8hL
+F7G~=exB066LggLSs<!%2MBhb1pbA;4US%sl%qDN<;6K2)^N?D2dVF|ra4^iiDd+#~b>9Em_m%s9ya2
+!{T`59DA<wCt7NUkq?38+gTtew&az8dpi#oEjnv@?LrQe&wy7PZfO9KQH00008031s8RvzWQdPoHT0C
+Wxj04D$d0B~t=FJE?LZe(wAFK~HhZDnqBb1!prd2D5KFJE72ZfSI1UoLQYomby)+cpq>_g_J%DD0rAP
+;|f^4#-2Aq+NkD4dQIwRunR2(Gn4w6i6zqI&6RYj=yBn&ah#A5I<7i9q*2J)VU~%8Npvawp%8xDUBTk
+Gk)!_{5SK97fM>nr6Kjeg?-5-2@+*^4Qthpnzx+=q((?yzk2oK%h#`7|3K=I*p89gxE-;KZcm9}jGX^
+`|I^32Wf{~6zGl)eAa9nJ;r;ddi>sUE71=0F8iqCq+_OOQXB(}yr00EEJu=xST~5yQVrbDqzU`H^WW!
+}sg{3OG`Ol(*<su1Q2x`oYvTxNOo7wCckaN=TwdG1uJrcD!48|$h(!S@i4Ra#tmZ7i8iLO?2Gt^tv41
+xiyooe@bzFHw!qYS#Wy#MX`s`_w#OU}q2J|OdkZRjBE9CjGsGJvJqWPTcmY)jY1(Gmu@azjSiXpa7h5
+qT2^cpK4^)T-5VG;4});HlM}_`9@}=~*kG^kxuFI$?l|h%zc2?68&Ihll~r{g~0VgYLUA&;kbd;K!Us
+rQ|Un9wW;Q2PDfhr{21R9WS7qs-$|LUSq<@3?L)+Op8XXJuzZ{+W>MRHI}pBNWjSRV@9i$7F0G~U&H`
+!0?3F~({*q-V1RpkW)w*+e~eoO3~=MegTo)VjUf)$9kUyA%f80#JVv7gT|a#4xXraa@@?Wd4Dbuz<^;
+3T^Jv_AGq~sv4Oh8`RJJOfsmJJ|8#0pCcG?axz@5%Z<=a{{ENbx>;8!<fB;G2Wg6S~8dwd?8pQhZXm%
+?3kE`#Di<rmyp`suZsJt^2w{je|R=9AbZPBJN>9vKGM*I~i{*AeBFBw8h+haO`gx#5^p$-(JMIP$8SA
+*bqQ;L=AvVPpo7#~!~Cwfc&ln9k|lpW{J<*(FYL^)>BNtQ|((_{=Cq399*b)=WX0Rsfa>9>r`YHXYJa
+a>qwx=q@M26zMd-O^u~mZ8rGHniJTcB6Y%t5|-|A-A_}tEZyV@L)`M7_5WEU#wm$}-0~7fQR4EUSG%G
+KQ%rdIaI13F-<hlj?e6FV0e%l4<F$Httkt*au;LuxT>wWWB!S7%Ly2QI8@${G;li09ei;MEcuKO#4#X
+i4A0<03FfPVk;Z5sKGfl9<5Z$VSyH+agZe%~=6^hTJ*M3u`bJnF_%U$QT8|q!Cx_DOax}AlyKWDQUe*
+a0!Y-nPtdaPUnv2c$Q@T!W~)!i|R2SR9ULwvL0S}=~Cm+4$<<Ah3b-=!V}dl}cC`F>_<XS^<|84=uA)
+)0IF4dxH54%)_YYFt*aAN<6HAnqDt1lYIro`h?#%B-_m5xyZ(MPt1sG+0P@uwmn9W#*z2@eE0(%|j5}
+58JF$blYGbHNE}p_+LuX3vL&4fceQpPi~))Vq_+4zy!9T6T@|%-U=V{(`YM-95<JXlbzVUrDtb*8gh#
+J>2PLV$Mo_U!3LtEy}_d+t+J%is_*?#SVh#J<4KVoKfJVMPkB`AM+Fz$_R~^`k<SLptze52@`4mT=Zb
+KWR*!I?p{hcITvdztVJ6H`-beoiOD#P=<2GMHxG@=6Z^?VF;7V)!uuj@TzGS(vC@$0>8cdJS$H%~jHk
+v%w1$pj`dT|ub>9<I+z;=lgr<h%8Xge2BECr{#p7Or%-j~J6vFGu4u>7dCdXW+=bLt%5@OrT9fBO|G^
+|>ag2BW8?^V4s)y9KBa2N{R8F;#xcB-7OTwABQ;DO2zo2q|1E+mZd)ge)#og^iq{f&QP;R70~=3qeKo
+?-dZV_?-J2P)h>@6aWAK2ml;P_EvU@@7Q?_005jL001EX003}la4%nWWo~3|axZXsaA9(DX>MmPUtei
+%X>?y-E^v9RS#5LMHWL2MUx6qyC%d6lC%v2Lc;ZYInYMM6B~_B^<}x`NA|Z(hNw9pet;_kp-?ISU#aw
+$c=gBz40@z*b%d-pkB@3jR`GQ6Jh{uT+ZU@occxk+3BN^>uZ@Wv`k#o%6oSy!0^5*o-8^-25^Vw>^Zk
+(&ki-lS|7jfVvi6=wmC2S{RvEH+7%)?Z;Cfme9Fu7sQj>lVJvQ#o2?pY+_1RLZ!<z5KM;KP{%v9vbbf
+l(qi=_8K?mb;86iF7;;j?9%#7KkwADM{RTzDU?nx`QsPx6JqSj+G!+aG!Z0_z6}_u}3f6$t-2DNYdDI
+h>M9uj-R<&k79xE1zs+N7$|!r#5PNC4${>m19}_!U#P=H+1mG#oe3_kN9@;G3UWeZM})Kwr}<vSED^p
+>JUnQxPF!iI)<6!JL}c1DH<pt9xRXKiJTTQJi$jPNt~#`Y>6FaR!bvqB+OUznFCTG4hz(tj&Xt@g2d*
+&7*YZKALutQ<GKI!k6Y@q>IXRz7b{t1olijuTARe~nwR6R!MUo;CJUAkfu@c%o??5YYZL#I-a&<RcSZ
+usx^Tq7f@r8B4dc!5gJ(JyySJ$)K6~l_faJu@yW|wR@{lI=6PcO*g)^GELwOq2<f{kzHld*MSvhj2@x
+xE-quh@I+oX%EkGQJtFz;-oLB6DVA3;Qm?<i=Wzu0a^SA5X@s4<@@DucpNH5^RTTK3uHEqua@F!REJ%
+`D|%Hg$ppAj;EIk$gys$=?W);WKfy)D~4=&J)BIGxZy3%uuwXVX7dk=@zwQ;UC$;L7KraHXg7R6v9z%
+12g=0BaC~F3i{Z`i%2NAg;ImK*a}DpVEk%OFA^we4<JpvKGn!3T3k=CNtJz{zZoV5YEt3rw<0Tp9axs
+GdGA#DY6dUZETAB|ToiqoJ(mPm0XSrQkl|C2NZ~|^i+Fo}hIoGglB&}_;bJpwij1p}M_&H%C9|?|#p>
+PWX($7tF{%*Wb2cdWp4swYVTY)b@fN$gc|M_DWlnVz6dZZa5I~8#VKtQ7KD2gR_cBG{f3lOmydKy|!8
+YNy3VQ-<R$sUq{iu*L?I{lCnzIgh6&mE^^Xj0Y?ngL`eQDU*pd>-Tc5de$w4_w$CAgWT+WP6z*@54Uw
+R%jIP1&>36WBkaHJ<#$A01#`7*6l~)0-icMBG!b!DWq#I!6*tvEFV0V90hb-$2?YW?d0A|cRW?9knUs
+{@JZv0KnMrQB?1^@;F7;5u$b@R>u_Kg*Fqy1ClR!g_LFeIde?wT0NS05efLF=9YJHNAX^j`W#}AEaJ;
+~{zwf<GxSwg<erK|`+;!<pLcDv?yT3<WSZAJ}vMhp@wEIkHe|8V{?!9Rg!-)rHbN^n0aX}r1?mZK}p!
+$;-RCU-H#p~I9|5g9(ob-(?Jw32(h_>x__e=sjc`9LS6)K{|t}?o5XuJiuqIQH^*n{d{mdX>@@<GI@c
+5YkAI*;SCGs9r`*~F+6krxf@2NAk59#mnC$OIOXMNy!+AMJRe_q;4pu5cD?%S%hEC2D|7rp-rs?=gGD
+dS(y5+r$?=&38vGr1Wq4Qq4s;X?nEN6TOpnKzb!(pxke3OX&II<2*t07(tbeGOEe-@>ZO`A&Q;6V;}p
+9)Hhk*q+e==K3?=cX}&rfk#l6tvc<^bt1t<o^!E&g$1?8nwU2tO%PJg0agNHqIe|lb9+K1dIz3p(1Ci
+vV9o+KtE<8!$gJ^hHi@^TB`)_Y3GcUb3NikC`{%8N~EJk3}L$m*v{#y$GQjfQRK31_r#pgmKnV%+DrT
+c?er05<HR}?QsV`&-6bx+(g2Uv)*57eT(qTY-V&Lk9^=zdZh5=pKaD*%K7G#(b>sJT+Ma1Ea34N{@!0
+q*W_Kx*$28HmCS@I7oE<Y+_rk?teULEEu69>f#ve%y(WJ;t6whg3YJ8cE_rMaBuT1rV%&k2)H)0sc%P
+j;==Kv~GrqD0}qK(r`bKxjrho@<`4D+04g`nM_9<V?-6HGdNZ<f6pY@C(moGMz9txbxn>8G@uy9l}MG
+=%ap5RKQT_)KgO?K;weZifw$9Z&G2aY9!((-QSn&wL^KgRkV(oU=HkjDMzO*RL5FyXmI1p>G!vBf0<o
+ydh$l|9Pjz}b`3P}j`IA~f@HKMj($lCr3bqaaj!G-6UeHHS8vK)TK3A_PgsvRi!3y>WTsqmt5~yF7r7
+J*MOA%ECNRk>8JF=5LLxJ9a2f(3f0}h!LjQ$~FIg4*(EEK!CD`ug{XX<JbARM9r`}1gEw&ipof-cL!n
+lL_ZQ0iv@5=&weKs#E8`6nhrtzmfw(^#fc8Rb6K>E+Umio#1<qVBFHnj|8%^QAU%x>w8<nv^{U-Sc?L
+O-fA!2r#$ADFrv3VND`6%n(P^F;^o8YDcuey|p?iE-xs6Ck_=4-}_Qo{z9l*pKvDtvIEb-61Lpjm)w<
+^;5cGVNesqKYc^u5OeR~eRqT~174qnaqXt=}0HIn{s;7jQs|@}CNa%usc7Vj#UbvA*)%@|9!l!_Lmhl
+-mR1dwdIdo!K4Pzve%BTn7pAkkWDqMzZn_i^|KLHUDNa<dU&?zw6F0`<ZsP5&$HBa&vJ1PmPC+U5qWd
+o(%^B^CPZq)#qJ@*>BUbVR7oceK}c^js-)lcy8^b<QjXMLxSRt;Iz?>~R-T9i}uF`s+pfs9^@cKq>x4
+GHQY7P#O0RIWWXY6gNeziAvC!d59@+s{mEQ?uwZ`<{KR#;K>)_3F&2Q~6We2VW6SLN6SY)T6J|{tP}#
+FFfjheLnyCB7W`<sFCLB(Rbm)u|o6kfg<@|UUZ~2+<3xw(aI=h$Ir*m$f(q$a8y^lMtuHYveza%H49^
+5cx<%KMh)WYAKBltki9v5^8<VR*R#{VvD?+CS6fP}+S2M)tCp?`rfoS`f}R=(phc=Tt^7fYy^Yeq*$%
+eBt1?}G+6LV72T0m?II2p{0j_v{k(=M;H1Xt!NWXBjX1LQyb_hOl8m`D5-`ci`F9KekLQlP{fYtx9`#
+Wmg$-~IjEwV{`L~G-i1lbr9>VE2ysjfm^XcK591gtdMq~_ZQLSe)IU0!SBp-8=;CA6?|=sD6Y_05Mi3
+W&*W^<crnt(d5;v%=S6AK2%gIYV@LX$@7Y9W+79^97}`6sG5^H3+p)T$_!)G+1;Qm1diC(*Q`6x2-jI
+zC7|+b%O9bUD#!~4-y0L);l;>k6z#?CAYp@qc1(mQ~&V%=f&|m-Sw%(UhDbC-1Bpv7bWk{@Fu(dF=yq
+4^TG+=U~C))DSLI^X=PN7?(iZ6@O_p3A9XulLy#Qxdu`aL=mmOIlp<v-icaTZjBc*{OegTUYVa%4Qgz
+P_V$tLNEcVpCw#j+xTawZ1CR3S?!;<35M5varr0B-47&dyHl8B32@lDNR`5i>*z8GApyS8xO*C;Usa5
+21+D>;&W7L?jtQS)64#-S_duLJLW>3k`Ot#gu*tgta`n5T9AiFD|%1I2J23rDzh4Xft4piE`MIxyZaE
+SHx}dPVT}v(Tx=(UAJ#YM9nO)#F|{j!UhmTYV1)T1Ba7%;XKS72=**3DQ&D8_H(0LB2%i?04_TTjd6A
+sh$VB*B4EDNtB6tx?IUGqFnily4&gyE@%tkWJsO|aiyP44%jcmRy-Ah<rgnn$#SGP)tujv9m_0IXD`M
+Lh16h_znGQQzoT1zIjDsieb=PXupz6u%hj{3_*TzdVHP9}LTmKn+AG=daBn-5oOa5$bt0PUutCdGsXD
+dd#j%)h&{ghzVdoDAC0Y8_r$WPB8u&I=cvbF}fBdm|V(W(;-JVnnGRjSx$1$&VMNzj*ckSEyZ6kjls!
+t@isO%1Q6tH9aHQb>GBiyZup{T>nPCV7^s}9v->JgyOeLrbX*3#WKso}<ZvQdY4{m7sB1MfbbU&BlKh
+B4j7IH?B;QNl8e1O7#555T8MgZgwpgz~lo#Mr1JH9zVJMEZj#vqY7zZ%p}3Jk;-TjSXRjlIMzbwrzR5
+Zd`rEEl07prGDL}S2P=!fnq{E+S21^xiQK@ryk`8eZ>J?^#ljhqRA;I=t;KQIh}DAi$FdI9g|5#jC|a
+&ZF;h3(>ij5{xl3L*mdtG+iwJV5>pFWj?`Q|Oma#iP*MUYJK$wSOk+}|D;=|NTQ8lp9{7ONP>YUgmrt
+w>s(L@jDK8l!=wxoqf6SXtZ|xzJ_WEI>)d;N`eGni^^%$!Lip>CGHHxz&&yCtZMG<kmx|vwr*fdO3^%
+-^n)3Ak0T>=0;T}27xB|%bqbyp)qfHW%;fr6y9%j;@l6uwM5;H67TzuDsW?H0$^J&n~!`Y(d)wrU~DZ
+*3B=fjX99I%<K*JO>P`4JF0Iqzg!_7LHsHj5OT?<f!Z=o83`?BP+njWer7Ca(9{L_YUvr%>Jb-u@6Hj
+pSWuzd;*V7nmOGSCP};hNDliCmBBZy1nvmhJUN#KxjF1g%~772pN#(iP)h>@6aWAK2ml;P_Evp)eKT?
+h005^M001BW003}la4%nWWo~3|axZXsaA9(DX>MmPVPkY@Z*FrgaCz-nTW{Pp7Ji>!!OB1_dB>AD$wM
+)XjWrS%EwFG?Bu!8lhK3_iGpu!sNZB5^{_p#pLtV$?#CgcW0xQ57iR3vvm+xH2><JlJUF2p~ZYGnYDl
+#!sw~;D&Q0S~IDl6W}%BZt;xLH<Powf_2BAtp#m8pzW94<Fusmh-wlS!0HW5n-yy7@hi)O;fFc%H|<p
+DJ0FsuD?2iIO&GMVSg)2$h?<Qo^p)Mo7FA;2|QJrYgpJq-Gs2eu-5g!cgbhhM{j%noLEe?7E0Uq6ys2
+^f=k00xTQZLtE)Al$ExdNw<tx%!pJjQzedvi~J$uhXj!CSo|VWqlS{vOeYyMgt_cMDxHYDutO&O96gm
+Xb!rVbj|B5uPNT(RQ9e|)+TvyFDsNeKQ<c<k!PwIcf3J0*D3*V>PRKy5OBl!MOc`<Wtf(z9Rn`l7&3S
+;;9%$PlfS%JdEpEuo0!S$$EiHHt;Xq(ms-f#e2Jg*A+`jCF2}zPk8?8fvQ7CN)!1{SG2IQ|QB|JL!GA
+uy{Nad?BJ|V3nRX^7nC}O^}Mq1_~g(+2}6CF`h)LAZc&id)RgoUiSwL7qTtty>tSS(|!70g~lIR(O%8
+N-BDxH(!Eh#!tczJ-;YjvO#eJeC<20(+G+@}zC0z02=g2R2CQWot~?1bTR*?b@f05bVEd%&5pRxO0ao
+4I&ZI?Y3)-m};vknTl(f)@mli8Cw;O-H6(#q)x@n8nWX(79<Cg%{kx97q*hQ!JZij2H(79YgA{c%2aM
+=+tVit;RiFP^VzM0Fls*UF_qUDu=J^@Vjr(2m;urus}VXi{8VPkShBa~@U!*l?c(`m&<AEN!K27kSR}
+r8{_IqopL#nujZ6zSt!KH+2W(&z5(eD<A-N`_iHoDDn9XLFGsn^?=X)<-yb>>7z7n)6e!W2KiNh0df$
+=E~Ou;Vax66?W8}~QLHK}GUE?SRYc5ujwYZZR33#*JjPHtOp7zH+gf@vvwh+6V+CaWvs@-#1xnE`W;h
+11DA?yNnr+)zYGq^Icvu2e~M9;I~*Ub+Ee{2&*)%^Cx4S#$p!`AQoO=}+)Av?>x&)RlOvO;lhYxBH!q
+pSb*Tr~oiMwkf4R+P?gfmA<0H4x|ls2)>8vPgw2kM4UzFTpZ00k6MILG$3n3jAd<=e;}(BV0LgoLt(6
+=N6-edMU_HDK|Vnq(J@T7mCT#!(xnmDSynEQTe&g~eKXglmrP!%@HR_BTCxyDHA+4_ySDB0O#F%67K^
+bCiv{icxrS89rmY*aH3<khx1nsSOe{J|ml3%~lGlYsZsj6JEL>VQNHcA+WgSc%ft7&_uRpv!S&+c={`
+R+z_-G>O4KnL4AsaD}JT);+26E(*>b}ffe6mz#Cf;-L+pyPDZ7k6wIwkLSq^75B=pbGb!-wKZZElcj5
+v!}3(ltB{;SsEhg%5MB@?)>kt2Nq;#bVkT|B%+mT&UYJ)seP>P~oIsEDjDxX&^${qMEwGfwi4HlQu<X
+iU13H!nWew2BnMpBvoA#1Rzu|%E7^%#}4=A-kaLkB2$%zR*5CVm=p1Sv1rBXtU=oxvf9Gd$X-MJd@na
+g4oJkTV;oEcO}&^q_Lyo+02?^F{Zdp9eA76OKT1>;QC4VZZl_{X)ac(J4y79Mlu-ys=SZrHsJExver{
+VGPMikqxwiUR5e#c;<Da38gO4L=R0FBs67e_f0e>^96NVk@26y-@9ERwZTE~H$(6(+M-3Ao{)6q8UKN
+L-4;(7?~AUm1WEsPDr;-lNZwPhP_)tVq;MkO6lwxK^eJ^w5Gc>13|&mgOGNzAn(k5(QEd6ee;{ryop_
+Bz(rC!>+~a4GkJ57r60Db=yJs&wp~9En%rxi}KfUq5@mVzgM6YpkBW6ff|1G(CD`{fS)z+-oS47ficr
+og3=LhRR@Oioa0h)LM_TobO?#Z5!#?a|bp?j9_7r)7J9ZS)X<vc#EOnBEsoD+%u#RY=~EXN5iyL8U_X
+&bWQXfA~jTwk7M~S@%~De9}1tu`$sgY1-`c|;*Hl66K<KoTFDp?N2GTAAdjqYtY|7E*&`Tt<7Gwt;DC
+Nc>_?VD=z+eDC<dItT;S%LuUU@H+$&kdNFtn^JCu$L2u2~(eUlL%i-&<(*<`&{yM4aJvNYKnw&nO#yY
+|#Wv+|r7#%32wyN0@vK7>Zy1WsMlaP<3=Rp=~EqZf16!YCBs9V^-fWrpKSW_+i6JA2_@O~rM<cAz)10
+MA|a2g6df9W|ZRhKIqV$@u3;n^S)K$RX4+8QV)I-C{oQ(V>(%j+fE%rJDexj=_Pq4PXy0Z@CA%wsn%>
+toj(LxEF8&U9_AoiJ+r?qMQ#_(PO4Nhtu7|iPvj(*9!APb<ererK!7ZQ87JrC3V>lvCtUy9&R!|UY8P
+G?xS`&raKoESwEmuLE(iH<|?QAE8hK(?<iC}YL&TA`uuOs=;%u8vFB~|%J1p$trLy9j(TdSCq^b2)!n
+`!<ld?8H3<b+FF8-SyS_ur#0mpRq9dF~V2?=F+yS?xUz?`k9ko`3NY`?G-xAAGJh{eptG}tp{+QaI@$
+uuz{@fN^X7n8@?qKaxDy2h4S0Mi<D&#lRFsB~9p8mgb2?sigUg(*4cU=~^Z;lvz@7$dZsDz2;P%}(W+
+o$h?yN>T%bV=qODopn1h;jJt?A=dv0xfagUg}iajWC;RS)>LFlFZJLVUo$exBtIjbomtwZyG<*ZCEg;
+%dN>yy3tiee<$^ayOMgGa;#d=WzY^iU!!I9d%8D_zsG4FTtWx^-85aYpV~J?+R?Yh$|wH?P)h>@6aWA
+K2ml;P_ErvvC?_Eg002ug0018V003}la4%nWWo~3|axZXsaA9(DX>MmPV{dJ3Z*DGddCePXciT4dyMF
+~rztm(bQiqSkTE}kMI4^lG+4wc?_H89qrbx)*npa6kwi>y=eP;k307*%9+C9|R76-swm>J9r(Ou$1K@
+f#jyxf^4Q9vvwN+|JyI7%3Kp223+k7<(T;5XFw0*_JmgO{=vvBTv!ifK4z_KkRQ{3xaPDAv0+qs$8mw
+E6SS&dx4LBN&L-j3#8B(&^kM^gd2#ntD-~5)*)4ctiZ?jwYsKr<6Fpou(wTVHpfLl-yBb1J4PyeSewF
+XEQG)HvHog)7W<Cj#wBkV>`h)V<CBehrmbEw0ATSh&V@L5b2seT~L)PHnSNC>?N7doM|uQc>XmHVl!o
+S!jKE31ai5EAc_MTvi=UAW|D9o(8P1dG)jV$=zY#y|Jn-~y#ZC9W?#;(TO=Pt0n=0b4N#7T6l1C50d{
+W+7{iF!4A?vc*jUUqGNPGK`Jy<9ZW22PkX6qW>pAV>``LBQE@gL7a!YL2MJ-T?<&Up_I1OxPoDJ1^dw
+;n&JoVzmp)^GvJjTJ}axmxi{pU|Fk2~FBDw+*2mqrL3<I~wSn44Q6ms^)I69I)V`OKewdjIBhKKI<(2
+r9}pQwkdhi(TS_p`UW#xB!k3SX((y{A;ntm$>=Fc5pA!V&6*&;esY?%%X9&)pZ_<8B;&9*@khHaLX_%
+pgJXGi5HJ&Eb!4+)0!wT`Wqm)rD1K*jqXBan2%rF+d=HpekLw{s{Uqy<xgm0C36TEG-av2x3^c!#?LO
+s5O63)qJ(=j5ldR|z~)H^`(dLGf^uUp;W+U?KEjqURnT-h9p%}q0`{wb1FL)3Jvvcf$5y9Ddj~3JYIb
+`H1Vk`4h&=s^Waf78|0?8+-sh&gQBatd372jZ<?Y)isW=gywvlu`sY1A|%4r_751&Fh@a`cRJVtara~
+&5?<Egua%j~Gd=(e779JNx)#{8ff3$}Fb(c{35bv}+!(lE9l*(9~X1LwVWaCmh5;-!gSO!Zqnwnj8?_
+K>A=eEAEag=~2Pco>z~6@MC->fru{g;h5jWB_SO)$0Zvu-`k7=BQpc;E$uH3a^HZD$~|xd995STmK80
+n<9w9SnudqS|9}y7&%f<)qPR+yg|p3rz<WuFgw-@71=uX?n=VQa(*o()%OS8Dj$l&J;~Vy=<NF5W7g~
+$qdapKwCfoSc}2=t0x+XkfPdxu2-DykL6JDSB+rHc4Y^#h8B7GwTC&{E6`~ySWU`rUNmNS@D(IFn{v0
+K)4r@|_$5JdfbS)d!jCy>nE2`kIEHXrm!Ph|*6OwtDdN*OIlib7kAixT~q+=L((~GU;T*6?LQFNva%q
+kn$BHiQcDA>v}GGe>b@dDf5%CwNJk?$V?a<3=aVBZ{_58ZvOJc=YKROM9XJWBnK*o2(FJCDss6eBti&
+ZoAE)`L8(l`xMAifpRb`es{^Y#BfML~Co()7RpXZ6Rk;D|C@VY`Fj?(Nxxk>n)&Sbjf5XK_x{9@5%kI
+NYtR-Q~C4lVB*?@u|E6^IwR7?zh-xoo&8FlrRcFx?y71@`{Yy1bo|jwH1B!Lh0qNc$ycq{1D>iPsAu@
+hx`vc-)C{H?Sk;rg9B3A#_F8Lfr=~SUXKIF7Q(QU^G8OR@V6FG)=Y4RXp*3`$ukiQ2(d<l8BJo&Hk_~
+EWWZ;u|yp1q*5tOi!Z?YK?AF@`)Hre3!fL@I9SYfQ{B3GxJZ&!lYvxXMSe^EP%+2lH@^0QHgy9DZeY6
+rd-79BE)iNL<4B2RWBCncfhfVulobPJRD`iv3SfnqmSB>SU!9e1U_b1mjpWEHfjUZ?<b*Srr_a#H#LG
+UG%Ez~d<7Zjv3xn7x;gwPbAVp)s`J_j6s{_~w0|{&~ZHbWUC-6Gg`@&nGy<nE}<77@b7!l0Pe1MzO98
+NT3|g0jf^qQW>$H#~Ry@XErjoH->mLjeKmb^6=f^0S_C%d=8MtY@wCSHA;4+W*#ssv|Z>c(e&QYpkp4
+5Rz3K0ID%g%qgD5u|NYW!^&Sj;Xl<Wld^vc~YQY)XiFqF~ms*Aq{rVc}68sM$FC_ey^mBb}WHO9-(-F
+3n6%v5G0CC%#zBb<?3x^L{B~u!!3C4Ij_x-Wly+kXNFz*vx>ud0*gc;;Hc_E=K)TSXag8k4!I?1fY=?
+v=m8m(eA9&y_V>zx)kHk2fy-<Pw9r=yWI#CcRjSj#;>#vJr(?otI0c^1$oaIEQFo}x1b{zTx{wBCLwI
+kN&AJcgz^V}?Oa$xB&%*%4Y%A4ori4;N83YFQ|8z&8k0LH0uwOfb9^lIRWQv1;UG)uf;%8_A8mVj`uS
+6-TMEtiT{5MBz<~aMG<Z*TLi^_Y$eG-{k1Bzw{pTLEkb*Mg<5ba90HxUk)4m`s3>#s@zH-a(~~K{t+E
+tzu0~nk(s@qWY65=QOepQZuWKxB4sATcPSo^PC()C5QVWzr=-##*QWv69K#5#J^QEmEHIzBn$a))Q!A
+DIj=vDY0?~m8&mdlk^Luk$iDZxhKYokaGVjh?_@yl4p-#1fl$d2tfB=X18@31X1wb&NfH_6X@KB%u0x
+^Hvrh}CB+-I-I^>rx`M8J|rL%*J@2XKw?L<U{d98P|%VmVQ~)Q#rF^>ed^tGWk<ii&sp^b(;!CN!vP-
+IJ3Ov)eNdx|$*PXKO7&{0tN|>$n!G*<OnrbhAcAzQ@G_H<AS#Pa(sGL(unI5Qrp$zz<87DuDY1Kj-T^
+qVuw*h5Kj-HdJxxy+dP0{$cxbdXXexLy#yeXafP;16$*rj0?VoR{<H1KuupzStA)gLY61E1n0TQEv}x
+u>p%P0fA-mWHm$hGS9wOM^88KlW-k#hkMl+UAx}|+e3aL)NBImV-Q+jyE4_wqQ?uu=&3<#$JLn&sz&{
+H>Pj(_sS9YWp=^eDl(TVthfljCM80P}J1=sp>o>e&3U+Gbtu}Arnyupnb@%iQHlG@4H(1pVfi%=6mu$
+ycKu%TOkTze@1P??@LWWU)<aU@h6>JkjI-z9v^ATV9GOn0jm_y{Je9IEUMuE+=hvuK_ONT1L5!a1XvN
+F0(<%<?!y=Y=>5W}M>?`~B>f6&7ST*gxlsw#baUH_0vhSeE^2HtPpLA2Q8U|7Eprb~=49N6-jF1_t}>
+^PU}N4mLXQeBUdcu#QHIzegc0s_wr*3`5gMNp=SS5nNyIUF}_8WAXuC34F~Ij!pPAmBq^k-ISj}*HGy
+wpl(mCJ+LpIi;dq=)cfpXHvGyzQoY09^Yd5!F)uUaYddmdY^7e|k%l%M9hJKTddd$CaG*Znjbm|5pf6
+nPN18&kP1Tb_Y0N{IPG}H8X7}#u;|GE$3BOBpM<)=<Z!&la#^=zjk$G3JC)U8e-)6`{JRp3+=)L+@9R
+Z-By;J6%edPC{!f8bCD49`mYLi()r?0dbV{zJVw{JW)n@=Dr2kjzMOW*FiTTeSHo=@BM89^8q<FpMV)
+EB1A1#P)w8lw4NS4PsRcJ)S6BOJ3QKJ1fVn7L5Le7^PKt4J3p8rs0M<D{~6hOS|+LBkfQK+<rslw{Sz
+1tEro>!o;k*?5@L6k9M>s;4pe&cbiK5>zbQ0v``kOaThsxCz2Rk+H_t+2G4iECfn1T`T4A^C_gC5@cG
+hogRODz<R^>b*)v|9{lX%ct|foS8p2R?H;aG)F}iXIJEq^OUJz1^J)!BEYyFV0a;xmL&i7jkGEMX=li
+8z5CnHd3@VE9N$zr0J9GkCgdnc1_n<0GZg(|ZiUM6KR|M5A#c%TnCyGtU5+SUB<=tqJJR{SzdST0F67
+_ag+5fssC@l7{&!)bz=oa0rLfhmHl%FD8aFykqun8sh$x;ZJT15h*+>8Qg<%lS~F)Ldc%$lQ3LY7vtS
+qXPpQkMlvgzzN<DV3Bf*RCE%n_r%M8g0I$LVK6+S|FNEg%T3Ko<!`DJSsxwJ@f2zvJ3&GHKA=6;&~eu
+nF%gwSaAc}Xi34;1@XPmYrp87^iIn6-6Br`L}wb=m(avX#3Cp1m7ZsQb{o<}(WOe4U;_7~-3AT9*$+|
+Wx4D-{wFuJb^M8=TI5Qg1GtTMxYRY1xZ=4U?!?vOFFi&aH$4Y~IZ>OH~dd_A|JY=XZPwhD-SD*2{MSu
+7iGo$Yy0g_M(VP{dwD$>5cEIK1RUZ9aH%J3GL4SowdiOt~b{${Em{szc)JF9N*1!kX^n|<lF4tO$RRG
+Hv&k57hH@91#VJ?Rat?(xgYvR=co?hBZTYX`^J-|Y?E)d3_r-O=W?ihyp!&=HHb9FYV0UMkJaB4!H0M
+)AaUZj1Y>StGb<E}*8#0(~BD2a~f`q}MxKKRw6zEtw>d?SgBt@;0orK%aUE41wZth9m_<AZj}^aeujD
+3xh5wXXu`<x|joFN4z`2zt|c-7}d1e7b-pH+Uq@J9dukETIvSsvw2aSlC<&=R;tTZ>ZYI}f@p3O*j^~
+ER=4;?Xv|jlD=OG4X})8JSbHZl_Cd$u6|wL?it6*>)C^%y7gSc@`8NY|%<W@f4)2EZPRH(=!#Or;M_)
+Rv<AaC6uP|X~85IF*603lLZT=1^wu*53l(EUFRux+H(?;w=tFmZc)#ufRH*&Z_g>KNNFcqLv(MhlMFt
+pAqJ6CZhej6}*Q`Q`jctFBwSpM}|M-PT7;x2j&&$l5pTOZc|hmAq4J^1x}myDiQk^DBN$ujTnG~*cZ;
+*d`~8~nNpII2jdiG73D>DM6G#r64|GYqWN-7@M`CY&f`67kcIABc|OzRhEP8$v!2hk%i%qWN(c=BFd%
+8s_E2<x5N#KnLCgN=&vCUXtZX{FuFp-WPWm>X%V+4&G3}=kN>!|0f8#>E?LOQbFKtb`z@lqVg%o#ijE
+a>NldpQRzWF1u?&^-iSAAOf>Yjo{FDech70?k^pPJD=Z^lRcqC)xU2W%bG#xAyvj2%B`e&DRJ~oFqs;
+TW0%;}T+lsb&FP~>`JLAdR^O+a&b|9i1a6}8<j$Po(wFRVvwbIbA7T7t%u7Ecs9*jV?89G#7v_v7FT=
+*1y%-9+2{2Ne90|XQR000O897^_9<bt{tQ^)`Sy=(&j9RL6TaA|NaUv_0~WN&gWaCvZHa&u{JXD?%Ka
+%C=XdF;LYW822jApE=j3WUBpkv2tJc9JHF<yMyEL|5DLNlKGEvPwcEC?O^R1^_Lyj_+^3`Pxq`NJ@74
+KJ8mJwMbxhc6WAncD{Dz&c>Z+m={TJw%E9{u`w?4Dg2&Hl3|tRSsA6%Szc7pDEV!kY{-wiRNtz_EX^*
+t7JpY2+8Ysk_OeBnzU;@7NqjL$_}BMImK1T77yR=@T2}n+RXj~br}LRAc!JGlL;XvNohI+A!z1}_O8=
+Nam-*{3MvxuuS$r{6-P(J)--X|0Rm8(;np9W$h|46|e5wi^z;`u5D2XGKU&9>GB;T*&B7;{N7lp=8xh
+QLh>{*>StYGwj42?zTOmYzq-&$x*1Vlb#OsTqQl}s;_3Lx<N@jM$=c|OrIbzQ_WsastYNj$P9<@iMoj
+nKPUTwP7l3-#tT{FK@6&8u|cPGkRhI?ngw;guk||6_KM&$Cf7vLE(`c{WZj`{PM`S;{lS0Q4v6Gama@
+-Y??pGEwi7av0B&evw=z@A*xCcoi4w^+h>}%PaW-aADjs!7q+~e3?x1C@!PEd{>J=x~5+{Pq<K#%qD>
+IQU7AmpCz+z^it_1?}y3ES^9V7O*{-fE|PLSsY-*$qD+qYSvTt2KYvQAtE2I_Oe%%wEFI>fL{*(FW>6
+ZjBri5L`Y-o>?jOE7jdpQS^``OrGW|!g0m$s*8rk91e}><?QLooKhk|W*+l?+3RZ?~~U{BwP_F>f)>E
+#tn=dcq!eDL7W*24!6A4bsG`6N2+MK6cn&r?{xSon2POw+Q2p+;#LT_r_wv4}2VYN}+^jmAZiMEN+vN
+xFnKD?o9!h+vVHP$9pl;uJRpz=>(IVA<*l0G0W;f*q4U@e#~QnGe$#AV#BnIG-k26(e$^aXLxLs9jw_
+U!vBD)M<67p-~dUy37Dx5~)|wH6S&g<L<*1MpM*<Lc_^?#QjhOCh0VlRuBN;qeQUt62^gj?MBmll#cO
+lLW7&lFD5B2zdO+=MerB%3LcmEc$j2Z4@PqzHfNbkCI};i-qVOp52*~a13+eo+Dec`ZC_u}HnqkBs2b
+0Ku#{KHhz6Yl>Zr|Mfs!yBtT2X+m0#oDhFv#GX=(1z1fIg%_#%Io(4ctUv%G>Hb5C$KW@eJ*Re1#zI=
+Vo-Gxnf)z;$emtH55A6|965CIXi%?FVnXJ?_L02hqvV^V6U9jt`>4lj!yF(cccA9XyL#dnfR_)s22SJ
+pJM5$I}Q(9Phn4{Uthj9__vQCHm{(t7nMugP&g?ADo;-N5|3O%hxXs51w_S!&mz+etdTL>ig&^)O>Yx
+8ofAtd3Xw7Pmicc0d{x*^_~Nemj}oDKfr^%r-v^NPk-q~&ks*uA=Kvpb}xFpcYJ!d|Kp3j<LLE|$FGl
+04xkIq0Pw5BSI>{3or9MLuTEh^&@w!Y4*mu|qmv)@Uc8{@_I`vh98(|nk6!<BeE9tjr_m2bFP<I1!>0
+$(yS=9`4!E&bzu-=Mv3K~g8$H{5x%d46)jI+>$5c>y_|p#u^axtqga7tV5073UZuXB}ogTwa#Lel^@u
+{x-)8WZMH`+TsJVC@fKR$v65V26_h`>P2R|gCSk&ZnF7<zV~5RT=?lLOPAX9s&P0NM#wx2F;(cVi<R6
+E%7V>lju*Kh4H@^aKdcqi*y~XNL%E_-q>DX))^03Ov=S#YQqIlbsDduz}E*egTGspHVV~0|sbI)$g}q
+w~f05y<<w?2VeC1_yXu4{@L&Vz{#oWrx~tg;4Py38rYHDS9z9r@QS1YK&oJ`-yZ>m>G#h}JMb(6o~7S
+M%4;6CRh^Cx5B4_x0W9)}@zk8cVGP}J4^Zh!tJPvoDjF7fS#Al^Bd(QRq?5E-L|k!R2o;5`st=QBoW#
+&7Y~boD2KFH3ZO+}9BylMl9q@(4B59x(Jzc<nstQ58izjmcK(rUAhuazusncREOaRc@GBHgK;|v-D<_
+g&zYG+oY&^u|Qq^`O{871$MNj}3ffglpi0^$z+=<#%JMT3EGR(+sP{k?1ie8pQJ$b$jAMC@UwxKTJ#-
+cu`wWjRlxJ6}IyJiue<Us4n>>-oHd6E2?<FUvCpL`@y+IKL%O>I9IKMLRTYI|FER5GC(tP)ePZ8T1kc
+i3d*Vlszg2NIlihmvJ?`dY%?#HTX`No5Hb)M<-OTVFb={IKI?Wz`zEB=P_&?7;KhDlN@-af{wo&F%BK
+tdf0o^+ZM<d$yNLgP_7pf^HRt$^hdyb!Ln^R%}I$cf}u3dwE)3)jGf)+tly`u!yg#@Bp*T-+noqV1sp
+K&v<Lg4s7gdmyVY-X&V{FgX&7lBYOyzWK);5fy>bQ}Zg;G`G)m*krk&)D8B1n4EUTdm7}@#$6lOdHj!
+Iesf<t{9K`(&g&UnG^MudM;Yo5{Sk%5e?%0>XF*CM(B)7l3TnoMWaqW?TE;LWIB6iVQ3PWp3V4_B84Y
+^0YN?jhv3mzC5b76u*Ix)ST)wit(N;PQougZ10T>FiI+t8@&*P?CyWi8mo&{bGKJl^H>1-;}!aXIoMt
+ml-hlg#ghP0A;m;z~GAm3IS+n-1A$*vd51w3Fu#Fxr+3u4ksyz;FM(99!|<mwDlyyqsg31cJol8=Z@G
+t!SFppZsS|CSDxwhU$#-+^^P0!+N1Vu<Ord^AURaTpQa_z_Ku;=Ywx5GxmIHrf~%;o42p+cVh4y==2#
+>^S8Z~O)Yl@^I4@8y!6H*2nJz^K4%b?o?vU2m=AUUufOC<gYF*d8@cPQf8f=kV00Z4m+(XPAP9yzUXA
+BBys){uNX`VV8J00MY><VOZIJj_#K%d-dx^v4Y-Yxql{Ze=)o(JUG=`=1(zkvBD;M)j~ZwvErRS{>3E
+v8kit3h)6dC-VGgNGo_71u?I`VSE8BW@6v2jK_0vbnnn4I<l_K<|Nc!=uNK=^-q1`T^f-Jzq-xSC2sT
+ABy*(yumWaka<zSo|pi03M51LqDZxedbJ1|BiY|9%$3K5)1`P`<y+D(szRFw=o8ARq&cjlJJ<yhxK)Q
+qFH;;$5^TSRy8xRSY<R@4j8G;Q_VvD^bvOeE5izd-s-8pD0r9Nrg;e4<J?7=1iyDs}i`)#_J{bg%=I3
+t0ygaxu<FdUT)ADd_hUL*(%*vNHVpP7mDU<T`+6>B{;MBB^Xq?G5ahj+!-m#a9cUr5{^nlkW(3?qqfw
+~hdoEbKhS2f6{=0vgp4>~;uqGEN`;jX*WQ^!1Z*j{@#>+v(L`G<5_dezY95FfMxt+1Vz^-^!OTO!x%3
+-t3&bd`=0ZAW0`1@wO6DZyn({qicGPheFsI1P#gt?8%_+npc7`eaR>SW|k+RB#3@op*V8C)vCHySUJ0
+j;KyNp)wnUtBX9J>{#m?7BN0*+x1yBfy|_8nHb7ocQj9V-H%1bdff+(qKr{bdfgw!RdSgZ3woT7<`a5
+~a8Mzw;opl|JMd|BM09gl)z*#?{yJwnU!Ch;!ttxNdz1V+DcT)}(N0?(BD*e3tk%{&#gowVm49(>JNA
+!g7vw{|lB`a-thL50NyPf;1bVwxPjz#E^|sYs7uI1@Q%0~7RT95po!ru8h6+1;A~V{Jauf{Sr3LizGO
+60F*T1~pJ4O}a!7Ef+?!9>N)86qbR06g-8y$Nwh4#b6Je`c9Nm^FOd*C>5V-}b6qDrwr;!owYo1@kV_
+$@jlBC)J&^tm3A_P(kIgZ{t+m`_>7G*Kp?GB403A?QGrlKM5#2F1!)2TNr=jFnLm#=&2vseqiu@4Fix
+H#Yj0%0hX%m?7fHBG>!ge!4+C#Nl){Ii|Ugl5CMlv#N{M&-0DfKx4!TWR)UQ<(X?NQpQf_@%cHov!@P
+YuIU(6&(6-dv99;n0TeDm9bKaw8I_s~OE348En-PWkr1uwX|PPF^<crqzDjB7?DIICXtaiEw;V1JHs*
+mc4gxGZj?OopA>VL<yZdI4xF-&f`EUqist$$*XTb^sbeEC^ena5vzTa}lUY|EM;>ip}rd=_S_u_Jxrv
+3R0IILj|yZWB{f=D60*np!mtH{a=m1{=N-V0z<v+bTK#T72{(PF(yy5t7%7Nk~uu>J7SmtTGTr*FP(Z
+CoYq<uUz%BWdsH{<DMU@x>6%>J|@6O2`oJQPGWAflAtoiKr@jzvgMyJ{z*e7OA+5SC_+sYe;91d3k-6
+R!KRFhsilm&OSVx0=-LtJw~>lj?5k75YU6AHGF$AM<I0qts?HD=uX7OU*MYaA~`es^SNR;4A?fBBf3b
+~`eXs!ePlE}qXdLB;)X#o!YXXBA@hO~n23=k10R7?*1ihOzm;N`g!>APh6NPB1es+}V-}$D=D3q{Z4y
+r}MsWm7c>*WL4pnYfqGY0hXh~*_#(i$pRVLnnLob8QqRAY@RWyF!`H1Hax5DC<L3Z+<*g23e;1|gJG*
+TQ0nq3(p99+ewdu~OW*tyLvoJV3}0ckYPHgVR6^MV1);OLw{2jMl>t<tIP=6DJt%*SJPY&d*%(0_LL{
+5c68T;PyRqx(nC4kEN?et&S%C1YgtzkfVAh37BPPD%E}r!V$i{gr?~k*5czKOG#f3Gdax&!_YpO`HN3
+pYM|~^C)`$<E#DX@YTs7wDHsN-s{%~$6c#4FR`Jg2hqzT_<4Bn><jpaT0Jo7$n}L^;9?6Syv^(LVdrd
+X`<$86S!`<dX)+rDpFIH56n?XP4m((nMAi^)6LggUYSq4rvZTdwWqC&0W_xLMdDR(4_$q}BzU}g9Rk3
+g%$ch$gBsX+MfOgJ1wUX{icGya9d!Pl;e#~Ag5i%DCMFBVls#PWRzTAPDTSc700@P(maSbbd0W#BwsM
+Rn>B{z8=%?sK0VuGtd#EosbU2l;(jSbe`u<<ukzPdn;3+=6Xsr387lH)=Y^Yt}VU9_tUnKf8c&DHy*C
+a(+**I&3_W_6J*DIrwvdNPOoIdfV#+j)3?j?nQ7N*VR_9fTC_Jc^su#YXTQ&S<E!VSGysCaaIlS<ze?
+KV1BtQV%tKP|urY%4X<)%+gR~FjG{K+=uAUAQd@!%kX}s1Gh}FGPM+c^J+G)q-GnW3?RRAv_vZxgdX|
+Dbx|}KCQPSMDn!dJ>LvBThes(HuSGnD=cE&YX@&zYuBt*#)RwaR1CvyHLka<S)zSU|3{FO%p9*21UtW
+PxKGg5k&kbAjlcI9uYcHUFT#D|Ek0)N7<7_8#IrMHMQgK+1Ak0QL8pl;U*&*gnAFrfiu*4EqE%RLAvL
+Y=%2xe6TM|nC$z3;3@Mk$Km2IVvvJg71n43O?At+g1snT5zu<?9^1J>X%DJc-@~=+&pS>&_{ime9s;=
+;k&ODR9)F4UR{nzDDN&MOGw=s+D#*2ZktCjf}{@GB)^Uu@l|mjPK?IeHyTTs=+iHr|<g!mhE62@oZ2t
+5WP(n*Lg8A8uA@uUXy7fO*q>Mu=#me0lij=4rt%P3i-R?MjJ)iy-|as`6XaL0?3hreMI<_a4_^7i)w*
+jfUQ8Qvq<UO(&-c?7v^@dP>u~bv|U^yq$Z#S-iEV^rsXB9H#H#WoBmqTAw{e(o*_|d41yet4SBOIW!}
+;A!O&pbL<Rw5U?_Bo;S&bv_Dl8;)O6VDOc;s35MiO;_!IZyEN%<qYB3d}#3D7^IMW4uk0U~m>aCOlRC
+JuJKZ_NkFP7LoDVRiyZSQ+D2%+4u6OoJuY|Rb}dZ^*vsf&B$fYk>X#ozJVP5m0R@F)e{ZIO_p9?OI<&
+Pfh3XQO*cj$0obU?0hP8-2ijeMB}Hx*C0ee?GQ9;PIH{ZTQjE1L}P2ei#BOy@#DQS<7oDiU@#TGFWgk
++KleP`B4K5+he=)@$Z&0aD)H#=Ygg8l{3K_DV#JtC8A*)c@Ki~Bt+(Ix#J4{?j*T$*!_e_49^y9Gnp?
+q4nAOaK-TZ0@~z$Z*s9@1)1LLPvo;<8?vACW_~+t4VSs5+7tnzF7P@4P{*OX@cd+cxASRmw>*t`t7DR
+v!Za&MmfM#3)UN(i#QQCJTz4I9vsrbz$5@6<nqR|{tsmOAVtc2qB;oz^m_jKR1wx_Ha7pT4ABa2SZ0+
+2!F+0N0^R>x-t&-Z?OaoYdshr`o@J_x4ACp3SE&*)9|rg~E_0)Yj%$mtRQaOlLUd*lTR!NNgf$K-?-!
+af}lk<jebdJiJSC7!24&#?xrm1+qZ?F(NsXw$#c>42k6Vf&*U!61rsM1GWs_JA<}BUU--@(1r@WO#OV
+T*miKV^uOW)9-Hd_;l~-6Jk-a<eIc7HjJNuHE6SLs&lr@j{iO8`FIz#TX@?98hVpmUZv5mZzrt|HVq>
+@+k{t}-Dnfu;vaaAf1t?bx!+UhR>sW4ufSe_M3DepmJT5YL_P>(;N~({8m$}G8}Se8q-u5kn9&&_&Yn
+lNbAcrc%gvk0JJEbLLYCE<GE(Xge`(u_E$0&Qlw}K#284nO7AG~B=)TC-?0IbgCBmmY6oH;G>VCqe_i
+44(C21^stqYJRa>Yx#vutOi83~@U?@Bh-qthAhyTFdH5qXjbL9n?^93kBwAh#Jb1<{m6stt#WFM2oFE
+&@TCWY)HfUhq>Fds&sBPwXx)CDh%zD-7pS=)RO~w-!lUz%sfQZQkF6fA#Yzh_6?n7o&L5>TCqzdaHH&
++i$<Uzy0w3qit)Q;zL}h_wk?Yhx+TIZQO^A8}USl{*wI`o>f)xzb_^j2{iuDa&re6I4p4APRb=7mg0*
+7XE?6$E^LzDy3yUcEUUl0_LP8j+rOmAWK^OMD<(R+0)_S3`Ngj_AhZkM1*!d$-&U{k7q9n@yU{WI`{L
+>G-u?mnlD{VhFArg8YW{lGC|d2#hmYUcxVJmKz)rIo568PsPdoNq46+)rd|$TB#Y_uD%)6k{v!+7u?P
+BL%B{C~CRkJN&ensT78tQo#u5+X4^=^)oG4M9PrMgUrH88r!F|+g=bVc>d(s-bLgc)78(pcLR>z(wBj
+!MPi0$@QN(XCjimAsErUmdj!VToqPttM`ow{I75x>q8a@c0n~dqv)+v!Bcf>S?&CNbL|?d0Kn;51yEQ
+Q+N3IAO#LE^uxDwO@{O|<7%r&hI6`|;zFLr3%1}Npfj7px#}`+lVo-pUzFjujKTvt?s-9Z;!M+`V%9$
+hvqYwBIw7XRFK{P9XOAgbzqIHT!AUZjsPUHb3)<`IauA!X;?X<2x+LsPnvIh8HB=np(*x0e*XI#fW!B
+$V^yp4Bjf=P5wVIfCBskXFMZ$N>v&kZYK2_wBGn`N76X0ClB~hE4OMvb2kVDl){;f~6=*4W|sSF@j$e
+g;v<&r*9gPMOk7WnvGo{nHhqj@%pQ9x2=Q=ru}x8CZ6*RNrqgxC<?u)s5t-cE~#HKxQq?Sa#m#bi0O;
+X*pI=$~Il=%Bhcz&qS`3iK9d0~4r(Q0-)wOwmi3IYHv{03gg^VSD7|!X6vedG#4dQt56qoAty)wB4z_
+uOX*x4XU@&GqvOMUC1@F<ja<0*uPVlp@pdFVm0cna?{T8YmIE}!p$F6B2X_~rs#dE({O?}%y$p<{@JK
+)PoKess0gvHSpe_SGNr3jH1jT(!%j_;t=YVo;pIK%ns5;_2Z54~E#sh63WQ_JzbAno+o`^XCdPC~_#*
+j{Wdm|Wo*)J81qWT_ed;aDH3gk$({0Ohd)FtKoDSw8n`2d7?+(lyiIjTRo8>d4^X=MfU(V6*IKGTg85
+K?Pd?s{~E(KIqMLxg0isX0ziX`K7d2v)C%?swIlB_PPX>*wU5R0POp$%2NZs~3(?<<^iDAD6CB<+s71
+9-aNm6>-u4tdJg-qA1Pw~2pwKWHZz^rGm;G8xY&G_xf7+7{wbIvytlZXU<Wj|!s-r9`WmG9An?v_p|~
+<vxSHN^h3M75WaOmnkkD5xj*fSV=lU0wJj-96On~oUm3E_bPrndvNYyS%Cf3h)l$Ev^!)sYKAD#qPx-
+dgNI+D7^P@uyY<&ru#K0W)<&?Ym%gaRbg8X}^}A_Ze{IskeDzmo;X(BEmk<6LJ^bqHmkuQ(z@<MIXJ2
+hUe9*;e-RSGDzIyaE{C)WKH(x&b>dUXbwlq)&zs=Kk@dTF-ESM?ZXwgcMc4t6$Wr(iub9~e=@fIFG7Y
+ai=XE?(n8@tyt`_6uAixi60upXW5oI9m0eo>XS9@(YwLVhFn>k&f${3%?v94`RIVlQAT30p@h@3uv&k
+<ZAKRM92&mi&iF08C0xJs;iWB72j`%TNIVygn^^#^zCdX|qU(A`OwmPzU%%HQj8EQNEWe+-S_FU>_Qi
+xV>q=F{VH=Xo~{95)Ps3^SK!Lgk&dnd|u>p;VJkjT6{}BJ~76C84gBQN#3WWxrZOP4hAeTkT<@i--`~
+%QOev%f^syvwp6(Wh%ySD>2j%m7|+n%A;7S?SNF(`Z7}fXT8#7fAxDbAz@K8+sm$uyXgWGQ*a<?@jsS
+6V7nk#0g?df=!-o-SF_K~RopoRU1}N|h%Qoc8H%ZBi5ogA74jdV9q;i&EpcS_6$42}U(!qgT)DlVv$C
+<g%rd$sY3Fhdd*|!G%3(Pw<kM}fj-+0S}Pe1auytn|qgJa~NXAnB3D<DGfT3Dw=lu$e$EGk*sle)A9v
+lZF*VfyTf)F03S3QnWtLV*W$670}jY-9DAY-t|V*%Roqt&6O&QtG2skpTdX((+aiNV{3%6%+S(+G!fw
+r)pIdNSms;1X6Sc)&o>zc#{{B4tjWx@7U;l+Pu$QV3xO}U)<1kztXO+Pm`PRxPV-Hg4ZSeJWH<ew>tL
+t$oIkZfFG7SHFy0RGvcy^f6jJ%f4&+59YI{$wpC&RsaC|(J)nPw3){!LRCJF{*y!<FK_`8u%VYZB!_M
+7+eb>@kn!SUQjflzX1v~^AF}e_AF`O2p{bDIxth=e{ZhV0uv)HafN8PAL_MXAObZ{`>U?k$NrLPEgtp
+Fv~xg)p!!a^U+s5NqDvY1zsVW}89^vokDiNJu(qr3^o;iVgma?$1NvVW7PVF;b{s8g5IR7|!}z{B#6g
+u!9Ya4bV~gACgkpn|MifKk%9c4=9}O3_FmXNnp~4@T|1tREX0jiYo2=#ef#QLnGg)7K7q9c+8b-{=ha
+BIRM_ZYgV8@U9^@5&#fTAJ_eWVKrREC3#d@aM7_c&}o0?*L!3A3J-hfIJ;4((?KmuO{C;KeRrHGKb<{
+s-?)2M8DMV6%G!Y|lt7J3Feyk%qD?J6NFbO`7KY7rWM+}pD_8UO+L6=cs-E25w;F-tEf&YllGob^_CC
+5@BTt!*V&jH`AF-XI{(>|=R2^3Cd`K~(x;UOByCRh{@#xITAl+ipBOJP+90xJ*XpVE|U@*>@L5Zoubo
+)jWS;Ub&*m`7~DZ6S=v7vYff!ytIE1?jGd{vhphn|_A&}R`t;W0nD#;}PN!-Ia7$Uwno*JWnKJbsbrD
+H`!LWgr>}Jf7s&9S02b1pzS_yrocyp&ftg$)-Skg{_Ujy4Yvp#$$a`Q`gdH?m{<)Z{tgrQ(~9hma|TA
++h&BP{%n!NGeg?~tsOm^YR2Ny@m%X6goUg*4VB_Crj~23Fv!^Zt+HC+9aGYUb|Y4gF^@jWXX1OS_6M&
+)N0}tOB}B-sD8J*2xy-^-KS6kshA{9daqL(GeeX>RmhKWAg1gdOmzVPtLouQlN1+9@%!phz-J~+;stw
+m{A`$5F$`R@m83H&{6L5tolTuwT-QOgJVEC^|f?m7M=DSSaA%`G~f}v;R&kIY*Sq(;{;AKGrrwS$BB*
+BxgK<Gv+;&SL{Ii0G2bx!9<WU~p5(To_v)9GPYJp7%JTz4H4Qur=13iH>FoQ@czFrq|BafmDe8%kBOF
+E`G;gzY2~A^JTfmi#YrI2RA?j~-gxDOjK_3BiPuO%>yB^2UhSnM|mcje#yZ7@-K5&r84^tShZ{a5bqG
++h#|sDNx)6p#xYq(}k4|=89C1EXaO@Xy7NR(H7J4u3_*xXdYyD{&ehaaK4OAm+j`6xFlK!^(4>V##c!
+^VuOMTQIhCbf6?>sqM)!wC5B%}U^NYqnx_u$s(3fF$H8=yL6KQCp9bYhj7P_<3PYlzc7|Hvr$m-5!1~
+xAH3`zs*g9<)cw@)aYQ`%AJPQ_N>)@0{=T3lyPP2BHo3#}j28`WniZNU|aa{=)uqjg*Gt!b4w9(>TyX
+ve8y$CFaN2Rb=aRp^l!OElkg2rzFpJwQb>K#KD3EETG^I54nv<;xh5tBW1Ei-xvTjM;SC6COHrJO;e$
+|;y>SX{oe18EHg<W&hvx$KG&3j`t5_nGsCI0m`*$`Kj)YDWpD1X7rHDbN%-Hst_OJh*;j<a9Zmxixm0
+%<yKyWIlzS<|Rk%RRJSwFxT;p<8_9ojmA4IvR~kH|K-d3&z|`;@K%(w3#?l@$RM!C5Na<-hOE3Rt2Qv
+XcZ5|j5|6T(1Q>Fmo3>RY)UUYKGk~3r7iNJID@kk~E%nGb)>WU<vQKaO_|_Mb8hS{h#_~8y9rfOajvv
+(IV5sP<x&qEOUXX1O#<a8ZuzqbYcq5ehiCyzS)#X09*!ed+a1NSp@UcDGy|>~Iyp?7KXMDQ*wxC;hPW
+p-~|F=KQK>fU^AAt_kjdSiY3wNqs%UKAu6-O*KQ+w(ASp58oge>_f$qLAH2{{Qj3+G!OPpz`OxmnjS-
+l?4saKJV;eVyRB&4ZP2b6Hi^fEq{2kahx{(C|K2*04tmghvR$e+8omD<0{NXj!#Ep6%fE)iVkO5eUKT
++PThF$oixonM~SBaKpP)MCivzF(Pa&KvCRF%<YzY;!aT_6X_LUdIr`|FTLAcZVv+54&PUYC3*^`Q|oQ
+ZJI-5OyLih11@BmY>OfiH;88Pben!>9-e~0L9X#G9x7g0jQcIRjsh)GB`}@>plCfOEr(J2^m_!xuAgn
+yBP3FDzXEQjHfrn7LX?{O#Zr7MseU-63sn%`YwdWP5GbZJ75@*5txNFa-2HQBZjCVV#h`C`6Fn-J?>D
+xpMflkGNk$qM5($Xgk2JS800Z4oNM$o9nC&c$Y(L~|gbhX<^M&|nM?x$YARUp+B+}+?6+|Yg1WjAkwc
+W$i}8@S!7Iuerl6e8&;GO`|DZ($9akxfKEk_%|s*$ZH??t%OxyH;nENNI&_!OuU#kq4PCWF~4(Ho;Qv
+t?;nV$dg@6uJS<Ntlw=Nq40?we8^2AsFF&sK!8U3RwI9<yLTf7OEew3H@JbJm%>i8vb#|mW4K+#Mf9N
+4t(|hW{<JCV(Ke=Gne1$bnGc76FXuUwgJi9PD}p5WpK%r*qnchoYTG9D^1Rh)zzyy5UAh5oSEI-JWC+
+ytIe~wf(+jsI5?+@n(XlAZU5FdoL5zf`)GDHXB9~2oTXOs+&&gOp!IlvQ>K-%CY~aSFsN%PB<<pH;j3
+38lfX#H#x`!r!CIi53NZ}vQ@9!GbK7q0|dmNGL8kO@^h5pN^41x{HH;^4*Sc{+;)t3c`^I!yO6{eE8I
+Dr1I*O{yF*QioXJ6X=U(OwiCR?yQ0S6doJ!WJ)-GOk1)lVzt|uf_n5?Pz}EZ27|M<6V?PwDwUvH!CAd
+AXow|PWW4k<xsoT;gMpFWR?#d{cQOh!zKAn2MmSog7(LB5#cOR7EHP|${xjTdxni=_h$p%3m<AX>s~3
+q5BX(t`%GZH&eVmkMy*CLDwh3WOZ9v@MM|X`byXGNa7WAWXG)O1#N~0q-9cv3UnMwMdXcC*9Jg2<%U1
+@5woqniZy|b!sKIpaP<f&>)}4@ZJp8Lcx#%R{&;C$5e>#`0{E`zgF-DIKXe2ZW@EN>2$Ms^ttfLwMP>
+`tQxJE={EL9KLK@Sc~9bjN}of|JR6?HWXkE~iK*VIAjS1JzGUuH#)dFc%Cpw7PHgowVc>rGuxs5-47D
+{!oBOS1GUr^ml^qnCT9`#-=zym$BlLm+k|V4EK5A|@8Zu6=h56>n&^RJ}240w%Su`dnK$_VTl$Ocb@d
+j=ol!e9BuAAj5=n`PlyOu?v4XtsZObWp)Tv!6+}p5_-=(K0Zi{D3*soHS7ERD_9M50Z5XyLp2pxL8F?
+(*%^TLS)jYmG55(Lg7=%aaA-ia>uNo70XNw2k_y&n><)Bg6$cbhb|>5mfN1WLAwJo47F0uczo!1;$81
+kcpA2m<ot6f>p(Sm9<UBCFZEks$4&548*S_V*KW?%hKGPUwY(^^(Q$n*))JNHnrl>@uX)(uolhsBSuy
+3^7utsx;#N`VSde;rGEb7zT^Csftbk-DFu^)m+auq8<)%I;@&@Jdsc&Rnhoi%9Ar*HMfZT=az_?p}Mb
+8hW0u0LT+8kSdGb1)&^#jaPN->9l<vkvXRq<3rg{n5b@FA(o~_xQVfGkdq@=^T*$)oQV|@RW@~k5h9E
+jz*zV+cBEWxWR%ls-arohDNfp^bm4pW86#}4CXs^CsG{fR$M?O_-6~>g`>*ir?!rDas*MGVDPl%{e=Q
+*`pp_|B_72m*D_0w-)a`N@T0>KMv^q#?NK<UD}GQz%m}o@HF73o`?0~`^3koi#zP-j_bbcQ_QlE?;eE
+5Z8p=?m$`IRD`?75hi?38PDH82Z!zNu`v5}IlW+w0>3`JC9C~$dU7*1!636~LsbSp*!KeuBxsL4-ZIK
+s%oPd&(W_@uZgv06%~{%J(&6A9F3Cr-B_OrMh|-I5@!LyT@lh;BiIJ|6+PG4XL&hK94=)gL6ImfD-Gt
+tTyeJ)3Bw-u3xrqQY^fYTa8}JUpXK+l_cM?yu=-6G`cWv|@HeqtOC7z=|hN<75z8521=5H;gKN?wYT(
+jrxHQ-=@eYmwn~m)i#<dNBdc$SI(8gS%{-GN;1<}=j?&yHe_jaUF$)Of3!!mLSoZTRyfWD1Oh!P!&t?
+W$&&Zga!ql!5tm-hwjdg*7iJOEP^ci=IP?+Nb_d$E=(!(<nkUU&we<r{ikY0?cQ}M@Aet5uca_^wU!r
+DNLYG0==q(`S_yznGL%ex8O{TfYjQ1=ZR%b>vYLurfX~kq&vR;PrZkeo3yy7r=(ua?BD7-$YdePaejZ
+XayQ37=^%&TNF<H)rtx|ma5|A4cGa&01TUJ&LTE-tjdip!4|oDe^~Ue7IFu2=kywq#m!C6U5Vy;~%+g
+sz=)Fe|!Jb|G<l-?GoP9|^|~1%x+<in!vDMRtM=3zHH-n>-|wO8g5h7Anb{z-V{A(^vV)5~|$Yp}|C2
+Xm?=!Cnd%%L-w!Uh0wZk3*dDbvbsI!Mi0&vqHHG@n2b{6#$>e>R~H9CboE7txY2gwXiLCeCv^FSv4aV
+U>_Vg^!aEK*#`u}M6YFyYI7jPrKE@O-$|5S>Oz5ai-bHE}G<{-f@lUr@{BU^Mjb0v}oQR3S?9<gI47?
+dKpW&(r_S5cHP&Y)_cU%d2^~K-?MUi#7q?S{j@Bi#_J#v)bPS@BF9k7E-Ivc)rIxXunt<N*W=y^EhN~
+4&d`f8oO%5=5v1!5nheH=fHtpkOGf(E6xIvMQHQkH)K-!P+F=d{`-olg)HBeT?K??R(Jophyr7k&`|T
+vt$|F*R!I>#em3r<8Guzipq3>lo{18``z*j;$dlu3inW$r=`e!vGt-^G$3=OU2Ih3`-U#tOMt>{kB;S
+T`GNQZ|~-wIYxa89hSI56JVYC0q63Y;c&U4Vx^+-_L>apW(eIfL>KEfMY{SdbH`YBTJRH`8vHO1&ikT
+Pz>r#y^BN8w%3Y~8W4*h8n7)d~)Rhby0CCAC<_Cf6JnJut20;@)x7u1uBvIWtdnxqQNR2Sc<Nx$UvDD
+JK?jEhnW?KH$lf{K}90%v{S{B#dWesaV?3Ym19$lHWT!2?o;T;OLN)hAGdBPdj%G$bgQ;VMTqx+{YLl
+8L+y6fE4N9n6?swZBVCFoOG<FUo`ALNA?LZjoA$yG{H+`U7AnmUF?pBK=N=vYgEigT6Q)oBq~&Dh?Bh
+V!ON>eqSkmNFG)NlJInRTEjg4ZOc4<L!A6$(u8+fWsb>n?Bu0kV~o5_n5AwHUl>Tdd~N&>1w~asEv{g
+0w}{bRs6ZNmT5zoRnyo|Ystb0mgWr>dc4MV6M@a`so4m!+|z#~l2x!4l^m&er1H((?V><BOm@A1f6a@
+JM_ER#3-k=65DU_YmRfEYk|V{yZj(uV%@^k{a*Fa$U>pMWYU3Y94sp~Mz37>fRj2E`e`hW?iS}WjgG%
+6Xw6uI$fK*{OByPhveQ$RiFgqhDGA5VU%OW1lDU@!SVLSrcZFrtl=>+O$BP9|}@(gb_a}%qt5wi+Co%
+Q<f;LJd8Pzipt(7P4*`k7N_HtV^|CA<o}OP2?31n1U)r{d4%Q!YXGJK%5q3hEtkfF8iB0Y#d?Z_(zx%
+_#W9dV?wuw>OU;@4~<LsLU3X{vH1fMMypHZ&KWQc<+%D8O{)(66gYSk*+z>q%n<4N}2SM1NEt;Vy_ig
+iPLytsLT}-mAB~(Rz`wsiH`T;-ogv0A$p4BEjS+2h8a(ep^GI}p$mt%2}SG3IcN0{srV=%@R-jf9VJ^
+5dBF`W5>GLPLOqa#yZb5AppGOl7~r<XI1*b5N9ZgFC!IL&Pl38xlM%$3j9mr4`3_GB1vqM3!3!K?hHj
+3+TGqi@gL^7;rGAR>sZ_$iFkmJI0jF%=n1vi8U*jR6juJ&T+^HpD_d55JOjh}2f~Q;$BP`=R1EPo~(w
+ZF6k&PX72BFJjHlASo8VrQ6^gyEQy@l^c>~8EJJ7DRA0mjnPCzRmu7-`m2UENhE!o^?5HQ&ajti&^D-
+M!4KbGDfk7LGEwl&wPM^2bb$kC*VIT@z6oLYIZwe-b^oVcRc`f23B2F`zE37P~&ob-Pp3&l9#^<rVrN
+QS-@2kd6&Tlo}m&_5Une(f_QC<mOC?F$64S6_jqb&KmH2yzPhI7)BsqDp`XUkS6LJz-Uy;-sj-IP6(1
+oewhw?7DX3TxDZLcZ&Rw&@TA^V39i(Aoi?{~MR(8)gP)HvRxbvOMShV(F1^<w<U6Dgw(hqmaVX|V8Hq
+@5);-92NjwsDaPl7JqO!P?`zjC&#Zn*PeVmti%y`3w?sJ=Xo5T!pv;Y;5mI7%BTC|q#Gmv~J0MpAPA9
+hci>5Gk8SqcZ#JD{O<{sg+o%G--DFYA`)j;RMVOT^!evcv&(ELfy8CtW0gA<#&86#*a^4?F-;0}ETAE
+>sjE-~cJWRVh-3D|VE#BpJ<T<}5ZLo%LZ%oSq+?g&%8RI`)x1fg_4GL`NlZg{ViJxd#qSxAcpQIT{+q
+pdP0M9JM~b2VhTgB@ZPImd6R*-R@%T!a93s6dZOz2U}u;m`HKqT+1#&urB!Hur82?EtHN&0#N(rAq@L
+x?VA|(nduh~jPR_-_UY`f%N=UK%SL81!X8Jk4inMHf&Bl0od};ce>7Wx?{2`?tP;R$x7F6>T<Xw$^Qz
+%p_B~|+qx6R61%&uK9gC6ZcC1JcCCyp}OUIyZgDFW%!wfoCi09YD_g_Kwfqm=zS4O2^>yX3jggEZ2L!
+JaCAV@P*8rV@SRr(XUea<vr-;Gt_fJY|aA4rr_jJiev62=s8k$@SUi3F<0quUUUof#gv76wkeFl%naX
+1|_=szdS?;De3BGrDkyj<cLip&%urPY@y@7}yoIL67;0z}D-7*Wc*9l}>=E?dp@3V`7dt-NAT{=Lw3O
+sMWBVpe<ecS2?3&aTP=vPmhRWzpCh*e)Ku=4xkNfhID<EPeKEeo6I|QI5vt{yD}K6;xOru#{+zrs6c&
+jMB(%YUHnF2AyG|XZ5H5yBqSzlgH-;Bl0$8%V4SknB#>X}CJ%5UP1bN=1@Gthb_x?R|ALCHhgJ;8t)n
+R+f~}a}ywVNPELl}+#m1+g;94yuP4E~MDmjDaK{gt^c@woeHtU4JT=?WIFxaY!oR`g~7r=Fzo=R}Qfr
+Mm5^-AX1nH^N{m3rb*FkYdppL0TQ(H+||YJa1?VJDzUm+jnz6BseYD8v%DkE0<XaNu)$q3N(2#GO-0S
+7h}nOwDlz)EPqJ6FG7y#|zLNJshP4Bn!&3ORTaVfYAgV=u%iGlsrIE!A;m0>(D{p1u(ifse>}jgpYI7
+tdc9IB?}<SmQv_No+zC7KBEPv2w6xyR8hkFRrK7p%UV!K1J2UyY^kU`1l`7+m0bg4V?z_|vWpfn70X#
+iCh}8#)KH)yS$o)SYO|Dp4{BnZ{l0~sI>1q-)nuU~XCmh&(KD&%F3Oi9r_R&bGTGCGTBKc0?*crf(nB
+H_bo5uN{*xz9kgTW>JDc%l$5ni8#`w8_|65VwuokOHi^S5`o^fG2v$zTro!T)(-^B%{`?^>NreS}kEW
+45fq0*4WDnmWzp^skEk-_t%j^p7~IvEv~l*3y62}K6RB}5_2RD>~`W>%4$IJh6QM~ez;i{y}rp>@#ci
+_@zQm|G#(VsF@S!k|$($V6>Ymckel$v?^2GYvmuYrQ>T#X43G-Xl|kPGlKr6{_TYg$fvqwXk`y8JWmG
+Uv;`}z@D$e0ecj4fC_z$K@}Poo_lerSD3}@kQ-Lg(}0hxd23Z~jG^I0$_UrC8&^4A1F;wQ3cdPjodOo
+9n(;qybFk*(`=I7nra7+~V}FaQ>%^8*TH7{dI#VZdAP+^E1bw(`p2lI{u-YAwny?3l??p~~K`a>o(Pi
+D6Ht2DNyOC-6mcB9~{UI?QIe{)4a_K~y+g2|fzl?grPHExZAlM!sM`~lX-CVJazSF*+e~B*TLD9!i{s
+lb!r}2A}R*e;@{g-<`_YYs4nnIX4Y!c6!y#1}a0pxemR1VsDxvVLYuQ;=4l^191xKs1lQI0z%x$b#b4
+m&|6rFII_ruG6OVN^j*5Fv4rC<LAklWz^cN&nX6kknqxW~7Dc393+;vlq`_;$m~LVQaX9fi(>d13(S~
+>5L|r0#cKzD%#98ozs{|F2+w9TQFtTM9cw7O?d(&RJgpHX(Je=Ayc9jGSH4j@|BJ~%j_Wz+aD}<MO8-
+OjFT|0<|)^T-rW$j+bnm9-c2Y@fZM0w_ee=sYwt>6o+!I`tDKB}9dAE;G$}{F{`z+O=*zF*$=hGY-~8
+#@$=hGc@#x!c{?u~nG7G~HT-ryW_U)BI?p1i8&?z2IW>+!BBD6NIfC=5p$5u9@&AW{Jd(r0KH}AFq-W
+ELw_>b1BaA({=+To0w>!87@@OS*wLDV{>%X+2NM;Z*i^C7G##64b7=w=}GhmjB@JBG@^dYYzL+dSyn<
+o5q#HsyAF3Pvx~F?GVs%F2jR%xpZcmBzH=pJzS~;<AP2y`=I|Zv(8LuhX3B88PkFxGF1n)vg=8N>zVs
+pJBDN(&(d!NfYEg7e~&J@vIZV46lg2kjlXVa_Q7jOfG|DF^=_aa8JF991VeeZV)z&r<{QU9jZH@H+#~
+P_a1dTdP2A28n>vLq@Z`Z1&(=?r8}KT=SpJmVJ&jeVtluDB7Fn(1zkX0FBoczs5jJ>xmm9g91KuJP5H
+_?AD5PB_U7jF;W`PFtR880*(4~Ia%sB=M=zZl>=~;a1!Be8Q6Fw?RsZqRykdQLOV{ISFsr+?97f~b``
+4Aa%0EEn(y|o1$V%iiHBS~YA>HkUWF3-V;C+Li38ot>B?PUGer~wG0rC5k(96ofhe{P@YIUkFA>hQ1+
+m3%1R<dcrnVTDhE%bA;=K7-?47w&Vxl*sfbZFRdRiS`X&$dF|736<My(`_E*VI)C3t$vVhnQrPRgyJi
+cUa3C1LIy?CPw?7vU@;Ak`T)T!c&<Z(&90>$aIQ2MBohla41Fea0tw|<;FwqJCU7B$3RqQYv`zoV9O)
+Mlb7JCqBls&b3IbJJ&_8$w<`jcOEB?Xl~$9a?Pnh5(+q&r2GOF7B|Ly@+C`|wLrwB1Ez!z=`oU>DN}|
+h2Ua+(Jd^+Vjx1?Sz=j2$r$cwi<$FVgmSG<Du4ogz#{>1GajiV!I@0n@uCARmyYVU;Gd%9o?=?Sz4Re
+r(tf}0E|!%l?f>luvk+|49{O3nj^2fV|+2S^@)w7t`gvXu3y<o%dtc*_}meXiq-tUL;hy0|)#I4p<-o
+f4-TZ?6)+$LZx2TE?pD1aswibHW#d3{h~@IhsNDodasDC&`{&%vxnc16$BErznxJUHUg5cLF+9WONh4
+716j;o(BWzRgG+%9X-Uoi`8(OPTI!<v@&5k8jiqP1BbA>(2=4;7$xr*=RFLjk1h$z8}D(B$adA#?y{r
+TLSCT0T8-{e)r@ct--sDl-8o;y$4SN~$XdA`6{5##wR*qiAdTX-XqTMZgbYWRJ{f3Z)`sex^M41W>>t
+V=u$%rLsBHbL+SJwFDtnTiGg-}?lqnotz?&$8D0?fYb5xiTQbiiNWIGL5{s?w}{m-T&rI}f!BwZsv9{
+SJD(kh++)gMKa*o9=UQYAEv=CDDFA=(iq3Gx+Pv1LPXI2iwt6uC}(gir0Fu51ns^{D~p^zRXTyi_W`2
+}r}au0ZtMmDzfUtpjJ4MTZ6Irl<P%izFV|zrW8xhCAeBIIw+(c!49W7A?QMJFLf@Pum^JmkQjDO86`u
+gAp9nmx*>UA%B86!c90yoVBQO0oR9v;Qz=Wtz=Qo&Ni`~&GT+_wu$ZVH*A5wA#8cef2;;J&t2jxu(}a
+Lg1-a@{t^^?j{i6iK9g3lDW;M=4RsaAS#<-}!R~|2Mz}cm&ylj~NCB!^-TWw_YR%_}IDGX>)SRF}Ef|
+XnKX+@DPIR4JKW>+?&ygIw(h8@`E1z!ik%FEZ4@u)<!zYBDkr@5p^au>czvRT=lY*M?j|p=ZfZf4}b;
+p9`ca9WE+13rXIwo!JsZfUFu5!VXDmEYQ3ic)qmY->tk)$$zuROM9^9=PoFcJNH+$L7J)$4w@bARiLK
+es&V5K~$zgVlPx09z<vbxExIb62E0y!-?Fa+eYt$9Mx3D^zp5;PS;<)N~V}B8?-6_(lKF;OR-A1u7k;
+hqZ-DP89yLya;RqM;vsd!5dLNMR9l4YV!mMR*gD5{En9r5@i;@&vjBII#xTjoz;6oc0vtW*)95g%tqE
+1brvyw>t|5XSHZN%I~d&4&Xa()Ev*buyyIRr8uTy^WNM{WCVn7ztHY%95qC<`N=$8T^hJsy-2{C;$?r
+=x-s-(^StLp2DOjR=QLEd6fBlDFxaQrf1Q<KC4F7;%x>$TN`XXckzTyHLaFUvIeYEKP>K)^>gA;VNNs
+n+dbnzd0gI~U|edGp%Uato;BA&!^?M3YK+d@;X&_|Y%V8LW+zuLFy>@*+vT@u8%H;E12L^MHT@UMOW;
+_9YtQ!HJF-ZcPn(*mj8q8vA~WOTRHS<;T@mcUh*u#)StC?V;5*i;}l83VQ-w5vqK6H4;gp|2siwga;Z
+3yYf2NweuHAG=p~RVMYhrTetpoMW93ld@S_9c{c6!(tf><6r{PO__!>MfG2^uQZ~sZN-@sAePF5;5Di
+}xHV;8oiM)HscRqC23N1ytn2WdO&typ>0T|}@ZJL5XrEa`>bzsqu;Py-VidLzZw~Pzig?SJhF8(7Tg{
+y;d73qU#g{tu*uU;fa!>5B@En%&i_bZQTh<hIgU68g1W^cTOb*vHZU2He#vTBQVU)c-U12+c@sUR+wc
+u=>KM?PqZ|nRE&H?vitG3SJ)cBnEzU!=WiAsakJbH@<d~`Q@gzkP>#8$A}b_b*a_af^LUdBNmZWV@=c
+n7+T0}O;5c`2*3;^^U)${njfR_LGE)pt<oj?af_nh|&W5m^xhqM#$QNG|7C&<gz8lOVk2pwwLu#@Gbq
+h!Kc)YaBt{ZD%ZilIgIppLW>y(Xb-c+){U`WCrN?ucXM23e?rK@flRKina^9H4p8#Feh1pe0LV9Ra6@
+E4+hq4P}4mYk+WK7tS+=4aDiZ>53u0P8&oI>w7F!o2FmtQ5Jy?!K?pEq0SxF%53C&Vu1%O_pf!1{4k-
+EZyW+gGM{g2Ozf<v!y53?Bx0_^a@r!YlrqlV<(gk2G4J029=LH9x?#b;q6j9an6O(dOJZi5CAVG~?fH
+n4idCG3dGbnP0OU3sR50XvVo^1T0Cucj`=g}?zQ1H7A1hoxK=mX?zd*>X!^Ef)4vz>?ME7+2>Mnr)o2
+(<&rI-gbQ2dXQ$&V%&^6Yej)Yv+VRb?T@wlJ<{dI~X&WdoDObS1gOYhj`F-aWz{Q!LRZ9wLM{iO3#89
+7%7F8qy(X6-nN%CV)q2*_CdV_e&n38wtX4QKIcJeNXaVD3<U@SYc`GAtjk@~;=Sb^46Y0pU$wW}=b`n
+8pH*wJKAl#XtzEnR8rtUNY((QV53jtv@2vKt$Ns!CZT%ZcqY~CYVmru*yl{CQJm9nBlD+jwhIOMF*h6
+34R&DUDGQk|`yiY|&R+ob>i-bbBqYLwIbB<fV;YF;{uCk@mga%l#&P3L>gDqg5yK=Hs(Nk3*D~AyvRp
+3E#-3-P5MgB5+vTD=JINUxg_Bv2Fe76IB{3|z-0_vITT=WDx?4hr@@4{z?x^1EEhJ6R1TG+=>s8(+}H
+)^SI)1j?wEhxc6jH|I@Ftc`l8b|C)74XNA-fk#OI2lw#6p@q9f|?hfQ$qQDxki|5h0k$!f1=`~ru6C(
+K_Lx_+<Co~NO>n>Dd~6UR*37xjmGS5kR8B9(rPtQf3r>Pm;ZglSTjA#^lyLQiusQY;rE&j;r-{u_urT
+A(4*qt38zQJvW5IdV)j2P`R}!r3|RP_`2JtZS2Et_{ddADj%TS^<PXH|e^&GVs;%afY}A7CPs8>9UA~
+f`e|y;?j8iiNC}PV1cXW6@=qg~Z-$w=pFI^Ss2wf2`<KaRnk4s>4FrX8NU&f`g-@i;Ms5+&p0+c4AN(
+c}+=3qtfe9{eZP<9(x8j>u~w~3v^*&YyIPB}X#E%qpRkH%M+*|-WBuDz@L7$&_+`4XZAsPvg<+4&OvY
+ZlOeo=v;a(n{^Ar?fR~QP}WvTOSS2YOq{J@dgU%=o59)XVAM<gR5(#qfbyup9wyYc*v6n8cCFT;pQsp
+vuzFGW(sO;Qm}m`ETf6?r3l79sA13=l3FpNyg|k7s4ldMdoY0Yr?E%gEsfgluqs-^4XC8O9velpH9QQ
+QYPOHcE`X-ees25Yb!mf^lXRHqZ5i5Z(AEydI_TrC;JkaUSFeDs>dvmJxMWSZ&{wXGFl>iF=^s+E&zI
+%uX)+YjkP4DS<%R^ZjwqmlUB;z%F!2iw2Y&V>d<1{Z-K+`#6`nWii1FoaEssHc9L|LzU)xH3vP=r@tF
+tZCw5~B0DvUZ?{JVY5<LX#Hy|Fd)QkS`-yv3B0d0bo~Fus-GnifOY53?VPF)FgepBj%lEK~DuZb)ZjL
+8TMW(NSQi1bi4hi5`X&tQuxrzdCN^*<=xI<6-kqBKeurkmAV%xNCnvEbn}E{_(?j6aBZ&KB!hdo^N`c
+_=+tjo0}gyzWUWhKHj?kOh42a5Ny^&DGl$6iH4egc;4~KNM;vG*42M0o>sJV$eY8(leZvh933s8qpU6
+E>ba6VwHkU5YrX_s!Rnc2<Q^f}g4SmAPLNF*&e@w@U#CehCNa64^|7r1Cosf_j6m)&)|qxH6;EO}J|`
+R$Sc@ncyGjeC#!H0~<ZtutCKSM+Yw@rW$FwZa!eF4{{pc1raycIFI#_38^Z7KbDm-X7U1_Pq463nWAk
+9FG!TN2RN^+SdO`H)NIR!;i-Sy(;c-U;W@L%$tqH>r91|2%LTA{LKJ}i@AmV3!$8X8*yI|#}Xe6X^eK
+Rzgku&@I?JvM3F+gNjrfM8UYGtpW13SjHw!F@v+<wUB<RqlLVA^V}?DTXD!?+|h0IoWUM&Z~0bR+lL>
+^x<TV*PzJne`b6oxs|Xpq;i*YhGT}w5pVj}S3r;{=Bn&won}ejd*D2h>*7JBh0w00DQB}W4XF^D#-*Q
+vNy^q!exe#+7<HRvq)s=vq+XBSYz>9>p+sSK^VCQnUFx;nN!@q6u7!~<O%|LsB~w_0*DbrhL*<_gERR
+dDR-c&<kVfA90n?$=#r^Z=LozbZ1}>(QoQaNH5ghm`5d6Ndb1)^=b)jiKnxn52#_1QK1FxpB*iq(Fd%
+m_xyoX7)Se5Bx)q<!nDPw3cC?&ujwi;aCH@F;-^qThjI31-QpPe4=NTT(VgzxSXdv@NXkj#A<SlJYoe
+XS*QB>Ioi3Bqh4hx&2b%|Jy6*gk?G?x$)K$c|eGNA!$a|H&@zjC46xy<o;SB=H6j3JF@6#OT``U3f5{
+C<qwi*a~bdTTHENM?R%c7pjeyV&a!OT2ikTqM4M728s$jqC;Hk)#)TPk#uglhh~$9kC3Io6M_ilQ^nS
+(?)bR90qx?*DweW}gYI)9z?vt$%O0-usaU@`6d6a%7AoY9J;j`5Q|A_(NfSty-6WcezPcd5QA%(<T&N
+R7CRC7=HEx?hNsmQR>X=$NKT`3<B>pwJe^+<t?)_*|zWsHy>2hLs`0fi8w=cSAurfnKfV`LhVPSBcKc
+xL`w8>=}ZliIs7nU48&23+EIkvIB5tu6N0n-*~(u%K&42U1Ugo;7oDcb7{Xj4UZ9KxG+YF-ZYvw~9>O
+XT{dTd|}!kU~4Ky`ahoKH~hxR=GJTw7ru2&@ZdCbZ%*VN!c#H{?^|IGMH2R7&we)lbEs#&=@a?Gk}i7
+mq{7g@p`9wDmHuYlqbvFthMgMUQz5qo90k7biBuGXZ-linoYTkN*SYw%TlrJG5rrlUIPl<cfw$)*snV
+rnb$P7<C<Qq6w-WxI|?=$lrvK|85R&9HP0BLfALuc#yIwemyK$V>LY$3Bj#@OL-83`qr+c}%MoH>12e
+$Wc}>m#vt~E3gTl+#;2=X=r1aC5E6d+A>zS+fvbO-9Xo_p<^9!4XbZfbXfL*Sx7F#OWj(cLc>(GTQuR
+Z~~KdlaY^YWH0bOI<{i`mh1SNI*wS>T9iN_-0?R=j~Q{RuSC@O2;`;EIJVaw0M<4p&P0?V79jR;Dr^f
+{dsRgfiBUfPna;{0+#lp$KSSqs>NqnR9-zWnXEzd8{|mPO(;so?z$`Pc5a=9qt<SlU)sd2Py&nFf%f=
+_qzg6Q@)XnJF_MO^_ABnufsjFKs+Z?Y(sH=Ub5r(Vi;{dd=$N3{3H72+Xt<cH=kc}L=J@l%$SKWD<8D
+CyW5?5NmNzpvcjtkH_z7r`3OLM>4G$|NJ!y6+R@1^Ol_Uc;!8iB#aDs;)tmhjH2ck3BLSSPH<Imb#Lm
+M{7z<SP2DANWt<h|Mg-w6`DNWbXf*?2z@6>1?;q1E3I8tFushvjiA>T~1C3)VkD(TTyG$h{3d(07w45
+d_o@g)q2t*duf(LpbIU5JD%NnP!*9!{jI!Qh(GLR*GYO;Bu-2L)S<-N#rKH}eyP-pARK_G84&lkQ_c&
+67^cIzBOY2BHMBX(gG8Ho{l^>6l7JB_$3M_{pe+_HJoa)uz1XWPon@^JX{ZSL;Q4s9ef&N%JXgBsS*A
+P(YZXJb%!WtNAp}w$Oio4g%7MOXM&MO}b5$7VRzRC=}W#<$&&~J~xuMOgWnmCNwNiM1p-pq)Z7+U3;P
+ER;U-lg7fuK^p7i(h5#w8J%?m$LH5~XRMJBwn+Txsr=9lR)_=uY|G?R5yxOnMQfKEVZx$`Dy#sNNOg8
+PnZ38T6QDr=&^cfur*j+pJr7LvO*9E#If|&X&W4V?T4)IXU#T!^6r@~6<RPjM8l$C$sjB(XMvqh>Gbj
+WHAn-kv`O_F4{k+QGE(o?tc)Qc(qwo49?lsq%<+Cf3tsV<#X`K`R9*+HP;Avn@1X@qG5z`mkeI-*A+_
+J<o$NelT+839cYs%Ilir&n~hfx~lZ#46h>bnM1jHQK~umC@LyxoeUSitv>bt2sA|_i|aCy{G%Fj;M@6
+`LTd3JlOiSV@|#YwS%wI)RN)ygokV0v~|TiuGM-?Fylj17A$teeVr7=w8Y)j((Sb*=0ndZouavYl*X6
++zRGjVdm1)37G%d8;i8w3r10Ko+QUos?j1JkkQsbVDO=I{yQQo@Y_uIm@jDQyS*$?&4e7J4(I-P`>Lb
+djCWl!(uktOm`9?0n9Am9PtD+(HBV#LOM+_lkW_vjSHLAk)M0Eyfx9Qg_lG*Bt7%tW|xLSEcR+}A4FR
+Mw=YT}Va@*i!SW9)*Qbf$fZ`0RD!yf&CKJ02ErMZ>o`x3iET+F1esVOmEo2zpR@A8X+ol|REOd`5Sr`
+F5AC=B8&+9rup(q*v>X+nR;`ckv`0!Qzr0tDltJZ&!P%xCf9+;{m3&aax;>x=P@1iswVlYDxVPUW(Ec
+C&v0{WiW0qyj;fx=B+Aw_{C)++}Y~sVRiU!J#=drlZy#O#AfA{o1on48@Z?JeBUjXLwF{@;LT6mANM^
+4ahxRYlF9Bv^TyMr_!D$yd*Cxc9;cI}Nn?%g@VXuT<+F~houp`c9amS~=rnm>9Uh%q8tH79kCZwNN$k
+8DZ+&A8PUlEmBebK={ud~^W~|_Y_b_^4`fFju^2`e1h@(W|LXFl6{y)b2&GOjEOcqgmJ#;Y6RT&8rYh
+_BQO!8qWfUZb0ptd9Aeq&iI!%1EmlcSg_!|PLFMeXK2E8ip{)-+s;u<lK$=gG#C*{v1p)PYFgdsKV+r
+F%H2cFn_ZPvv?JxEZeK7p=GDosw{xN!Iqub)#0%>gsj5tG;y518iKEQfkBV$I}#~mUf)O<v5^Bn)d$$
+mt7HDw%<>F^KJ&!q!-#nWa19Z#ZtfE<wi|=HpTBy)zCZ4OH$j=z#12M-l1a&GX%T4{L8amN<o$bEeu`
+7<(1-tYCJ<a^7$V%5|`3PRZ@EPlR9~3UHaW_of>N_6D`JvVH*6BZ9sVD{Wec=c|fz`2^Fhk@9`!2PT&
+PCe5+hDqVIF5Ns-(w);yb#t3Wy|a;!kNIe-Cim;+YMW8CkNIPXm`MT^i%TY7qpE=mbHV|a#33qxejLY
+5i(r@HH_*s-fIquYU_@k&ta0KBZk@1XJr)%Iit<NHkE<dS4PE9RVAlZL)h2qYbit%rBsqTpOqte#Qpq
+_zFvL4$8-==edZvBvpRCy~giTPW_>o2*VRttIa6@FqGM+;rYv0#x=1jZJJ2y>xgVovY=18DB#iN52=>
+jk>Qk!}a6<b|ga|?$#ZPc|v1xe>9)Y8X6%Zh4LD1D1+8k;F9|?tS}Qc%S%b#Q}6IT3=(C_GsOrR9_-x
+oo1zgptYjUMaF4apbUfhx?sK54b;5uLsgsMjXDbkQybj(@SE23o=fN7$RL&=iZONkJ2LyrFjccOU3;!
+HGw_}L$iX>&Jr{w6G5@SBttNa>iP7+(R4U2RQu#t{Y%a?EqyCK9NX3qUTbO?}UD=rrxZ!PQ$M6e%&A%
+OMypu*CYMC(-l)+Od85nu}nhp|q)!7>>~M>INTB<#C~lYbtCw;K{lQfp@O&L+3w9Y<+4N{1BC-Q*ZnZ
+hPv!9=2l9O76*b+)vWz7@M?qLW4ccUhz)vG>KY*27Ij-3b48~7j`-lJJ2!pF@yfG%RNqq?IHrK7jHuL
+Zzj-E8o|0#WRu6n{;{Q(Ct7TIXko8L@WUOdO-XCuRA7CDe;mkIu8uIrLKjGs1`?x40lZp{XzI77#<f=
+XT4=|_{zpp>DfftJ(mqDAp=9jeDOa4>4h4oTHP&IQ&SI(48HjMecfEBg1a|F-IdyfeSCgR5MHuY=)g!
+=CTa)yy5~UF;YwztTQJKH-!YBw>-jd*0cvMDNTFGOgT$DYYN$)0R?Z}~ihNiP5+kr&|SokC|L6UqvnN
+Kqb(P;5z$Beigz+7AArK{$nqau?s$&}aD${`yvx^D2w5qqh1_rHyr3!<+${QBAiE|r9quFe*r_L#UWT
+O@HpCK3!T=~Md6QcdeBmXn9y7tT`)isbT|XFY!HT>nuY?iVWV4Tzp$(l$3Y1H$V(Lz}HJ9Mp;cKO3l~
+L&!B%+X~kkPx4qYT$aNWl{@2fsIM2-Dtz60@GyD!C;&*=Io1ZXoosDCtUU#!gwkcS#BH?27F@(DMlB@
+meCs)_mM>bL1N~^vTNsb_5cdBoP;Hu)q&=7<F$rj+^fIlK4s5emZ)vL+o{uU=SB7j6tn{e2{bg_at8Y
+VC>$>c)C)nQ}lVNY673<U=+ZjAK_aQ7@vbE)UwiSYLgXJ4qx@Yw8-or;Vz&BdX^`(49k36V?dB3S;OD
+?qB{_Z?@zIXV-GB+mKh<UsBl`%O!@=cCk){=|eXaUz3@6tYfC=xgfCDLybLZja!yV&oMySzRwH=uf>Y
+1~DPJLu*}4Y{E$pKc5zWS_S>5GM;Oe1{$(_E1s3$mbE}JT;0M&8OfITFzn&8ZH-1bQ^Tyb;Yelsi24j
+LH$lhonn#1qE*RNJFfWVjg?@vwA;lukGL_LShVe&APQ0uU+XNa989Q7gQL-_NaJ{ptF;FLKmh_kFRZm
+81#V9%-sJL!IhKk4zlDlNiPfkmS6{KDmI8tjHYNAAeiCe(HxCNk*oOU6I37*B>ryzjqranxMDx+MI@!
+*#if|fL!<F=+W}BcF?y*6vB+lQAD+ugPkDdj=o|!t#hU0I}da8etyoTj_1sCjaCM;T0Z7YkN2x)y|s@
+m0pn`NoD@ldN$Ge20ElEO=K(yI0X7z^Hfa_guBI<=x<u>Rc*zZN=<iS@1S=tOUJBO@Jn8Z|L<^*CU<Q
+B}}t-C3cE(ZyloXcf~<wK;B9XeGWkrj1q-gy*^N>V<{aqV*<gb$XbcMm9F5>6V1#bW^iUWjgBO+HZ59
+R3oLV)nK0<y+lproB22yk1d*mD_5`B+G?sVQ5K)*sn$fpT#Da*UKq87%8wjK-K@%}TV1sRG_4Nh>(!*
+ccGbZy)}AxRSJhyK7BU>w**x(_-Pr3uamkllD~ywZp&Z~3XGk`;Fb!U%udP<ySMd`^?*epvzIEfya>P
+%~8h{@Y3@1yj*`gB{Z#n5224k40=cV{m5Jgo-9<Dp+CuKtSW0PTvs8D@TPa$9RCQLk`ejs?YmVoN!if
+XleVyR7c7O=dI<0{6Jw$*;Vce?kY)AA_oED>$-b1bOAb=36M09xs|XGss3l?jOV?Z7~-f-UCV$PKP4p
+kAQ(t?bXL9hH+@*?fDPjJ{u8U?=;=7~Jm%nl|K2eIq8r;s%;$ah8PUXSu1}!_Jt{vvu(E{=w_h!=qO_
+(FZ!xp<W02j#|oo|06tw2OnGiJj|gf{f|T)z;|&MbR7t{fOKwYE4XnrbJiGWMty?RLw#nmKF8>{_&wa
+KJdiq0>@KLPD|=v7vUjJ{cP%;rX2}28yHsHGkYNsORQuB$p1uJ(?PqCW3GCHyEtrhhrTq==v*rdGfTJ
+9-t0aphy|=0_9mBZwL9Y<Ab47Eix3#yaKh|li`rIUaz%7PoQ)pjNM+cu}wXC1=#JaW(mjKZG{OE=yRq
+a^&rXGn*>#a>aV@PM|nf#@Tc-mx5XZ>;is+vv|<E;G7*rkvnsOaLz8>GW{qLM~GvM$PB<=0MxtVXjem
+AowS`K+-BS;iX8%y-{j$Hir7S!S2`swyP{1~@D7coYdn^lhE>y-zG;VeBMysT2=I+dzUQHD#zm{}ztm
+rX9Mi30FP&;q>JTry+%AY=v^uY(Y-}w^x{y9-;A}Q#qMM;|V!^p*FJA6E#^_?OEQDS9y{C15FKh-Cf&
+%tZRF8qrNt!WQL(xA=~NoRYE}`)Ih|?mTWSVFD9;(Td+NBaU6EciuHzhg*3FtFRkR)SLx-|1pZ&CY^`
+w?&9g~-k)RQ#oEK1mQa%8%_fBK9)|#5pZumGysyPf@7d`&rVDH(JZuI!+(X(HkFhBhG+0p*#FRu@tz|
+3>5VghcB-I#i?D+Dy<a0D6poa%>VJ})evJ?!TdOdWL-*PWP&=uXOLl!~p6s#chzihPJ*>97Tm`wClss
+Deh5qpcp?FdsQqT)yF`oumbvT!!2~If*b}if<OZ$VZEt^-r?yUL=<(Ti2yyj8d<=R`=YFn?1T`T9OsH
+Wo?wV$$~GR>d2NjOqH!rB~Sm(B9w_H8og(-!pTD*a36{0w&vhVT0XToREU?nub_4{{60KIvSJ7zpVx;
+}hkSG?eW4$_k6bwQp&rPbMEc3WU<P6uF-en&5jW4IXXQEHT32XQK7c;OEWJ3MJigSL0Pm`XZA;X^c5M
+uJF&Uhr2|tRA?W!-H+kK5d?baU!sxbA~wZ6NBWWaqsXLjx5hDP3?ue8pGZq(L(`5lk{G~Urph1Rw07%
+iUq<QGkMp2%mbHo^K8E5q9Uf@+(!Mx<z${_W~Bv}60t`mEBO=sJP_$OE1Od)5xSZuBdzFpd+AJKL4}t
+pVP?gB#qJ{d_uu^W-9(q}3uS7g?Syrlq_bPpcgu6r4rrFC`v4L+e80Uqp*G>R&ASvt;&7n>|)lW`MF!
+cegv5d*aukn=60Bm+j6D#Xw%W3BGT}7q0yHb*3dKWk+(OG8E3uZ7&GjUgr)(I{+v<C9eW?0h{)%1LG+
+^S+lmSv2=hCYtI2#)&S)zKMg2&b8}FbG%l^d*;h~392-g_p`oFjdF}4N*}x++Am9;;#<kjOtS!0!h?k
+c7`qGkt&97g;TXWs$mQBEVd<&<75BoJgUa?4Rb)A7gPfx_<c=a5>F<k?J57&m^s~qh)kT>i1CW(vTRl
+Ps-cx@=Ph_e>up;te-!B3Y%^W&u&VD#ojutLE$on`M+snsC8NR!?=_z9k$>Hw50`{u+H@TjO2>*)r->
+Oj`4U8A~dl3R1t&qKv?y#2SjzP5Fn>hOrvdbQfHO^C?6LbLxa{uBb6!2>FR+WKlA<7~lu`q8JTTMD*y
+tJb+aY@fT?#>NJ5#%^N0(3P7z=5i7Z3q@MsHMur05G3Npl1YPj4~#UwNmh8})TnQ%NNCTlK+ZEv%bao
+GLZ@+Ey~{RzyJ_XRsPL>pqT>)wbB$um*ppWJA{2TZ)Pk7l9D-huEBgxYEGgQk(GqCh9Z}#TK{O|2ua!
+xfuRkf^n3Ga{w=N;AAFsi?n5`PU7adGz6$V-C2`<_#dIEfD3nroETnfVj_6GT)C~7drrzE_}%_=K60k
+zO>^||EeuA4&EML{UVs(RNBW$RU@zMcY)nj7=07ngnXw`|kRud|kY^V@A`5}~VE@MYDT<ufyYmP)f->
+nh0|%eors*x42)(q7s-zXM?fZFOc!(3KYDHuV_oO?ac<UKJRyzV)Q#4nh`CUEXw;lgxQLVAa;MRqx~P
+%j#*=x%G6m@w$#Q)FZcaJ(NK>_(3gniYDBcluNe4T@qR>0Lw)5mIOYcY(b$wLF|Q(lf%14X%tOSBa?S
+D5kAF$kwNO)YPI$x+)G37a=f)iFS?{?<m>sU#laY)Y=6?h(M_~pfxQu?mdog02@DD@a20as6X+RP3#f
+!P7-*EJR62wjgADq+7g2;wcKM>yAWJYk8IAK(#^%xXX}n;sb0Vt2Fcwhc5Yw-)#;2AU$PJhBV@5rsTO
+c%oR`aq%9R=SanB>E5G|GihVi#L~xzds_Yu2l5b%TGHm8YCpLTEl^Bx7`NSbmd*L_3SE`}-;aIF%2$v
+McbL7nAsE(~Dvw4|UvS`gwkXy5l_mL=c<Hg6OocmP`?*%NoXIvW1#Z6|7(FE6$Onw&y++o4{U|##KfX
+grGE<dPBBh%Ocx^4@sa`&aV_|a*TP>QNKEskb&x!CjqqE{3`>d>~nrU)Vtuu$dYSV_rpoq<woq=%(!G
+*bak0top^7oMR+HAofM?GMTV}LXIv1PACd>DP$;EHt5S@PJThzE<{O|d$ovWR+;h|JA|?9P-NJ#}Z=G
+twOE?3ponqQVr)UDBhPHmk2Zw2sY;c|CY~dlG{S$J#MR`od>Eu{?=0)hQ9c~^tK$%v$z2YPj6r1pELi
+q*cnh374xA34S657q^p_GV?0E1NvG;49d!3B@-d~7^t+vcKwx6?pzKWS+#q0zTk4W_rMLUV~138pWr&
+9qx`jLEa<q{7McfS&DapEsQaD?(?5&!52Q5<Y-F;ZQdGBn`!ncyo&*3U%&M^bAT8PaHxXC7F|goF=X$
+A4+FeS?dj(HOy4-t~y55yywno*ZTRnPEi)a)K>PGl`KkV`sl=$OLg(&I$o6PF)Z%(*{$!J-Q^pm)%sj
+)%_poXkxM@VzoRF%OR>F_8ly&0z3KQTEZ`+8aQpMFI@cR6kS*D`DQgS~8}MnI9w+1#Hm1uAcq)drw9;
+2g(&;oArLaCQG(Q|SbR?1AoOMarO2Q*YT$X2Bibb;0yRab%m?B~y6nmrCE8#ZLpsi-Um5y5-mF>=i=(
+TQoq~lG>H!M>@Pxi9WQ8rl|;;Wv9snF)Y1a9Ix954N#d(*X6Y{=Xee~;epZo}^`=Lv=f?Zxiy!_KD42
+Cz58g-}M-b#7fs&NB|rhE`>54M#r&F`&!MVS=DAs2CkRlyrpd;-nzv8?E|o4@k6D&MX$Il%EC#X_L_q
+1Y8e=Rlcj#jB=YfCi*tJiZkeEkq#+qUcZI&FJM~#qoq4F6fPB0!s6N}m$BLEE;2>lb@L?#gbzJ+be7a
+&Xv$M9JJ4@Scvz=8e5=RdytTy8z^Okwc)s`Ji_`vJ4}SUS==fQG|A)Qf6WHMj$&BFt5jsB{s&4Gz4g8
+oPcxI(6O^#`WXOSVS5osjI@p*0Uui5l^jG_Svm8~Bb+`)|0A@`<G@WP7&QKqdIoTvXT+-f+O&~o<GQk
+yFG7R?ld{968oKC+y$ww28>Q38)ooDqOF2&yP|q*7ihFE^h}(Y*55Fv}kTDx;6l2hBf!Z273UEeGusQ
+LCE_GW^vMS=HjNBUrr(&0=rPO4H_*Wq#Dk5_G39rk*noK1nh6`DFk-nby?WFOf~!br^abA~%R!k0pzC
+LahF|!kT8-oaqQ^@~I=c(St}L$?F!jqHP1uNwQ@KRt=y4ZFZ_g$WM6Rs@BkX)EP!&WxtD!!w+{i2zQC
+={S9R*`?K6T{*J>J+8khG6<JUB;OqdA3O(&Cma_>O@hi>F==L)7M_8-WJfb^><y~hq&PY^ge?(0XmyF
+064J=-#&>g=0l&K6B<P*k3oUS{W(3OUrs*gChve%K6YL)12ntPV*dR@kkwcu?9fu|GjEKN7x=Kmtw``
+>z7FTaPfWUJhA^DnvC^B=OXj4Z5BVsLxi$Wvip&ALyUNleCmD>5d@Ak3~!%Wsc_^Zi=FExE`8x@wjaC
+!tpe^inn-IYZifRNT0TN+pX&3lC1KX*}yugHll|Y?>4`U3N=D?i+a?3QLt#CR;9s%-C^kOX_lmt)IL|
+RDe4LM92FkDBQYg@zv33tt_Yb#TX{da=Jg{*8a<9txiLVvEg(S!TV@`I@-2Ftcnm1uP}3~^+&?twD<F
+@D&kV&_9Wa5GMP7u;hh_4W^ZWNxQ#sMi?|_a!bZt!bPp>e`J?s>5Otwh<t3*nz+>RV=}%DHTxrAj-1^
+panfm}!zw&IeNB!w~S$7L71(N*rwy-LNS0+liHRBVd)q6%OsXou1x%p<%R_<k+<)5a8`s3A1H`FD4?p
+@xs+U#n@gT!6a3lNhb1l?!$Fi3jJp|9XSUze_Puu<%gs6|;7TIx6BLh1b7@Qv_nn!|e8%r-Hqmv(UQv
+$X5wqq{hWD$3b3^Dl9tcGw=ex~i7ypqX-X>C%=i8AH^fCNhaLJAkXYCWseb$ZZ=@C@(S$z5%^(yKQyl
+eP4}C?p3yR`m5b-3~dQT(&>DvqKV~WnNw4Zb=;E4B%fy$8&sIX=9AqDElJn4;(8QPI-*tFN&5`1l#ej
+gH0Q4}-bm<5<D^Dem{fZ<-ra$k*p_tvHZM8<3r#(DVI#2IIT)ukc=8S&<F!uR5U?nhX%=(PUj(imxS(
+|Q7q$dRYbJ=iJ5V0S;n*Jtnmm*>76(Lumn{que@&UDVeSos(@cfYpAL4lwclEMr~B~V_j`M%-+#Yn(b
+{@idQ<dgD$3-zeYWX5-#qU|A2!V}Hg}@4vv1Gg>83&zKH7BJ-8}!evgM!smP0O39@wZ&n|(gRx!AU*c
+14~u>%<}4dIA2I;pVgfH>XXwSqC*%e~82>Hd<{99^gZ3fa^~=a(*_Y*nN2OsgQyGymS$K*^Sm-2cLE<
++pp}Q)lbeet5zJ!?_XNgIVQn&-HfzrXDZqWSEu9D?hf*e{u4i`nggNv$gO!y)KBpSQ%tRcq2?OR8@1N
+Hz!;R)ru$HD=A*q2{Y-vK3>WJfKN@T(W;xy1yfAJB?KnHZ;eQ675mFWU<^`-f(MB_^owL^(D@wTbJt|
+h~phZh~^-&(*T@8Mz|6&bVV`1)z8~t=@FElS$n7<C|tH!+_F!q>H7IFGh6#o;l<71k(nnLLx>8x!_YC
+DX8b5}54sgEs-A=SW+_NO6r?Gj5+2uLyPA)5tTnjWbi8$r;;F#3Y_bQrEdvkLLzAu6mnR8FGS5&6U;e
+~lVP@&tC?hSiGh`t;Y!y?_F}&;dm4a7*noJ&6Qt2j}p-DY9F6)>0=9T}NqLz)lr|2(DD8il&P3@G9&e
+IrQ?=MDw2l9#E`H(>s7TS148zvq@RyFwc_k?OHHERh~+kQHwuA-ZprWC}*23%hLw^V|;HL6Bb1{U7Md
+~8G-HQl=;<mY-;W8A<qHN_nzY4{il2T7?z+K_EcmH3TThPJ{;d445Oj7hME)R@VUql>kca@nDjB8ghV
+3;_Exh~kwCJ8l{jc;hxb^EGqom7z6H)XNKREYqQAqzVzd{^B3a@s$hZ{wAlUuL#M05J6f7wyqXEHRSF
+Upgrj)Q6(6$93e$Nnm$#6M@2L=N1%LIct=bJ-_OQmX-uIMGDOa>MTRGJ2>eG0Q;O|QRprx?TsCRFfA@
+|{u}vsC7-5Lq9XS(o(<PNq*K+mRofze2u)MT2rMrc>cm(7Z8ZUrAkx+=aJnO69kLK#&K-JA~J{<Gg04
+jBj2Nj`E@`;_Nb^Z6y71ZeB^)9fwpnDQ}$8O}Xbw^bx}X)R>7_j-ver)5**EBrfb*XhG_<7je=Eq`9b
+Sp$(op4rttV-JCE~x?%#Ph-_T)#v@|d+8d3qd328KMaRiBq4h~C!vRkq=4Ikg7v;=oP3T?h`dyq*>I|
+pM@w7;%Ue-8vR#XIWG$Mk?baAv-(9KTtoXi${i;$L#$oHcJIcw2uSWA0z4|Sp={HMTwl1+{nwOMZVqE
+n42wuA826kKUM*%;OuHcN%-X?g8zkhJH@=qj1u<wvDy!*!#x@gY*pd81&GPhdIlo}!bW|4e%i`Y*1M_
+l@PtZ!Xem0Kz{0xJW8kAr{VHRqUPYA0En*-G2DZ*2Ay9l1;TmTRJ1cT)`Od?|eFm=kx^6tB%*=Y@Q9J
+J@gD-r%h=~T1H|uFN!1^F5oa&OfPc0=S0F@IV{o{28kY}F?^*^MP)-bG&RA2!y3ZQSkBA3GeRW>Y7z!
+r_)e%C@Y)&Jum+UBh>l?uUyW?}@AQ8AF-tLA7VTwn8ZgVrL?E7Xp=ExscNCGd85&BpV0p1g<_SB?A!=
+)Wo2T#MiR@6`@DH{hKKk;jumAMTw=D`PO;4F5!pkjq+6lBRcl4DH_As8M6~^R8y!<06a#Dw*LY8=SWc
+4kj0F~_%9O)pVSebyjk^B}$-|4_rURIn4ixF--le?07Ncu#tWS4K53=XQk+jQ4)zlHKnn?R#u%3(wVp
+^YaSJ6i*p;7|x%IpJ^xa{}&Z`rbX(tt_SlPTFrB{_W=%`_EpsTr|VNG>li%62&EMPQ=Zw8Rf8ir-Q&!
+GiIq$9m53dwz{obXq60`7Ba^e24PK05Ab9G{Sok4>gfY3I3<$jz;nYHHHNjc2Yz!K6pnda8<WDqP0Gj
+0{<ot4x3P1nuA`Yte<xlk^^IJ*+fdeg$HPj`YQ4+oz^=bjv^+H#!QOK?W%DyH+{sx-mnZi?&8#@GXU&
+JXCYg>~YOe<MS6vHHLyD$}Vh)=dcx!s`_%`a;?jx@#zP#$0GXQ5sT^)h-#sXtM_FRpfMz?lr5ZuyZYk
+AgCV=sZ0#LLCj^>a?F=)(8CnL|s?>4#hFs7NpE=JEnqiMCU-<Lc)c20&o#5x6~HQa0QLQ*~LezFMo{F
+*i0^M}`;I5s2Z5mA(XiMo*##uEG*nj>rDR<<%RZCCi(|gawN1A|eB;a0y2$z+@kPpfznePCAql0Z;lZ
+DMK3{L;EBJ3+&CiV;mR|9@E%;(yHBlCsUwEg$jZRXu8NTU6gJLU#Y8Yj~S6|c((fi{`pAu9{3u+|JZ3
+90e3&m_?8BI@zusSGlAs+Z=_26e$`UaW&1Dpe(oQ>I^A&T28t-PR&Z!MqFu}E8HU^RUJZ-iyJNobh38
+e)h~W8ATPfyXtoPUQtaQ{MEt{P}W?L@E1Ls9o>0^|*llKyaI%Q>|-Es^5CoZ{dkD&eTZDCIdF3MuJQg
+cj!zHqGlaS>liE}tUlB_(jmNxM!LybK#bU2+)exOMiSKg=hSc&2TZeF_H)+<xhI_~W@3c1TT!Mdf_D7
+4*)g^|<S=Rnyg3LVEtzy}FNUGBNc7$aCw5syF%XY9hqT{fk|DcP#U+md3`d4<9~Q5I%N4Y;M}5O}yUK
+?qz$W_44D#hCuquy|9}*5P~O8aoP<KDg{=?#}5qE0}$@W8uQU7M$uY#fthi}a-*3Gz+Y!wo6U;rIs|y
+-N_G2uw`uweoQLbc`EyGj-GI}^JT}XbqWYg^Z2fxQT+C^mRuR_Pf~ExkoGRRl2e7DdB=D|rwXW{gP1^
+hTu~oO~`HMJwm!M&3x8#MhWYp8ZqQ_4?wZyVhDAdJb+<J5I!Fl@e&4o9%U=kOp!$$yWcvMVE4Jepk3D
+1lAJx&)OxlLeVOAvN;#9{6%E-^<YBISII%`d?E>i(nrZn#rIZ?%;_+Vvjv`2b$lBcqO3-z$NVZ{SAXD
+^D=OqIWo>O9{oAV{d`&uU(b`8LlOi1Z|joKABa-G`qSw`NcY{8)^<EbhhL6Xe)Yjju*f&8sl2$JcFro
+*M?hBXIq1~bP-c($Z_kZo%RPCaUM6&jcRW#nrbo2^`5TVM8{#;;?YP6Aj*K@rp@)v@Fzf0Fw47j0DoZ
+);2MkOaJwsx|9bJp!;j_z2YmK$ryi$r*|DZ;!u+p1-RYQV;58bTNfYocthRasOV(Q>pbt$Pj#cpw2tn
+jrom-|4y1A=?svq(?BEJm#X5&gXB-}AWt(LI2kS<d5RI*T7F9e8h^N+4>-86T7g{eHriAhzl!!j}Q0C
+BooF3$A$^wa99$gfQnD_^FQtC(BT_s90GaY5GrIZ=z8)$J+?crY5#HyO^lZ8jYA!K<M>&?iwn54+PdE
+=IRe?f%s&0sV3ZxEyS4z^=xkzJJ3gu;<S$@p<=<?F$s}Q3?<S<`HfjRLV|Ssn`{_qct_MWUu|K<K-<X
+>CMpBtP@0q6rfBfZR_3#OeksF><b^|RbEtE!+9kkyO%g03<ho2QUu?2w>yIYTL<Wlgo!UJCUEq;K-*J
+FiNuWuLYmp}g$RIe#=nvMh*oP-c@D{cxC!SEG_m~iO(D)&6@=<}?pp2c>i+n~Kf7fO&Md)W+I_Z%T@i
+M%Q$7vsLL_b{?A0ZXEgL*;<>b-Bu$W{fC!?*bEYU#Ioglh7Q}c<DAYU=1V1oj~{4%5HqZbSDL>W!ei|
+F;Dx`NWt0I#g%qdBbQ$5&M~D|hbSALYZcH=_c*ytuso=swga;$m?hBpJ+!^JLKH6@6&kkQH^I+|w!Lu
+8rhDYb%>S`}n}l`}6C^SmFtAR<Pqb>ata$?)zLMoT#^Whv%9C=fs2-cTVLBa5%OT$YH-^kTT=}jCC+j
+qg~{4XsEnWzCm#`O2^}*K!wTifs`V+?Q+f@WC#+0z%VtOPM08|)^wCdn5t`Gd{*EMMm;;08k~`c=2PZ
+K<ku0l$YIFh(mYhSk`|ji9*QKMWb-L(6kd-->+Igv`Jdm6?!D=~aRSxffwJSBNX;}Ql+E8I#dwlmqcn
+a0w|P?1nQ{N&*MEBS?YH-@^6RZpz6C?sqGh{<@!z({n6O25`Ykd0ms>cnt$0fo<(65LrlVrmSKWO1;X
+(JykL~@JzwbZ${n?-4*Q1Y}_Rssj|NP?j7k~a)ejon)`{Cby|J$Dr`M2u`!0Q6IpUH?r#K}4|SrhOav
+Dc7tvQ;ofm{LslX%koGB8iJ9Z$=-!{MgyT-&0uBSMcD?=+FFM6ffkb>j;5M<e2w?L;%Ly<wH?HY}O`M
+HZhd9794&g85_OR4<)O_ZZw<qq`Ua9R)Z9qXAic%J>Try!e2pRrSC+0*}^=<WP_zjya~IXT73==k=dZ
+TFRp(9ZFfot&~$!4A-=f0I&xZEevjZ@EQR*637B>AAW7y#n&P*Nu1P#z^h+XFB^s%CDRBTV!_((_>uX
+eFY{c<A8%nO)t+eb#CrM(F9bNslBvw@#lP{ljG|nb*7Tbvud4ZAZpbB}<;U{rS;ph%a+y*SP(@AZ9@m
+X!=*q;U}&fmDGb<vX+wVMl>yGl1}`>5fnTZxeGR132%YOfiDjn-^a2sT%_g{*2{>jLZVEDffp>ZotHB
+l%ms3e5rPcJQwqT?mGE6_-%0Fqmk`H%zMs^H+aQ2yJ<Yvbx>a4bxM9Ao8Yn^AY&^51x=yn8_wPI+Mm}
+yx=IJ7l{e=Y4X}ACc5wrNIpK7+noOZ`)k8y@QZmHpr(VfiCJiRnv}qMRtG#ya1>Ndn+9Lj14OKBjEAw
+bAp-ap%E2`1&x#xfNwv`DOrbJF)j9+#G#ITyy<D=gf|dXsyw5cQ7_y=l?+q;iHNs-tC)74-f3Vy7qWI
+YH367#IOAsYuw}&npE823f9F%)yaXCO~v;`!_x-I%iv96Dko%RRd%X*y5wr#>G3Vy77O>f|Xe(LaV=Q
+G4v{1?$=_!rPzg@!3QGBD`fC>>U=L!YN|L*C$RH+qMh@2Hnn$rRIahPKMtTjbW>HRxBWz*Jb2=ihc#Y
+-E>>+NUsfUh3WZ?~9q$2r1_mf&<*+q^=@L;lymW5MVQ*OtiF6&vLTPjt;bg=$%9X;RIX6jH{%W9G(N;
+j(iNqB}b~ASb{WAQ|v9urQBN;)TMI+#{3RLAr**jG$51X2mPohiLfQ|w%=Ue>+H09cmLekX?3VWMeFg
+K?I&*@KE4lsyrgL4mfqHYdVZ?VcI#?;XG(!l(h7Re>bUjqFoZH{J-*t0VhTRK|Nq+i*6lWqB+dVNiZa
++|07xK~q~sf0^fV>Wwzefvt;=|3NE$2x1qvpBLRSHzXi0tc9rg|PNj7eI&nf^E<#taujx7RJnUVL%$j
+FE<;HMc0dsLQ6EWVtl%p+04#`d&%2)V`1fq|DpBVy~Q1Sk}Han$fIgB!`Xy{?QIuS}|`dX=LEDD|omE
+d!CtNyu!WMe#2D%XFTR9Q}*lA8nm<VFE%kxplrgeI3e5RG_&;(^{7m-YsxL{IGSi)aW$-vdBSh=JP?I
++N3Yb^qY8w9>57_GMcmE@vlJAheskxj*ipC>WKm*At6@Hdak$P?MN;)mb;Wz-y6&xBB82hs;-O3%DyS
+U==Xu|Xv+qsQFciEjq?hQGHL&!gzi&<zxJt2LO)w9fhcerP^FuWrCw$B*F{EArR?$u#^)@f_@b0fN|E
++!4du(fJZYkGqtQ4$t)>9)RdwnsI>9Ihh;2g^t-+V#{va)AIn%ld%8o#4NTPH~3jA&tQyyAT&Mhl2iU
+O6`e&tMW;FOB1+!=`Jpmzf^3dkr;j5E1R7?H4(lVtBZ<*;o}Osa{gAsmn2f~aptJmvuv-(-HB@UwvxV
+?>Sa>1p$L-eljr=JAxik=GxEuISGfF!RD(kv^kWk$vv3s2XrsMzhhhAb@E9`fJ&B;!?Mo<MNlmFloH9
+Jn*Ugjiek8ei=5cZ46I$<Lq58QqueP%}(Nu;$HLP$Dn*eB3_U8@9l~-xF#PzhIJ|bI*!$&fz?o}dav0
+Cdw?^p+6&AN8x6H&8x2`vR`=Y}#7lcTj*glEx#r19)q81cO$xh0x;|1Jl}&97m$;u|{9ih_v_P^sp3`
+Y>-awcv_&KGYQ}uI5KZojPK|c!+Vq(G79F>dF0h_UpdD<y<zT#D=9>rDt@)V1#(olPhO((;3Wfkkp;Z
+=i>R5FK(Qf_;l_OQCo9<J48e_5l)q(fdT>yN*f8m`kDCj9$BWnZioMn!r7ub<@`-aN~63R=&}_^YI|c
+WS@gklcHKlCL*eqTPW7**~!`XZ9@Zk-$W_G9gLhm9tFKXh+r}6!KTQj#mA2YP^k{<Zm<Hff9D!B`il~
+I&28GnOx@6Ifrvhr&pKhRZVg9ql^4?7J5QjD=c!Tux}D9!p5}`xuN6U=pGTAQHh4p@rE%nWTEP_X6S=
+vT1|Bp&~goD!<|AaHk!^70Vjzx%T0*3ZsMJcMu5KDqccztg}+pjw*&UDuEXIPoZNm^o!YCC{mKv1qj;
+l`H>{!22vQ1P)JZja@Y7Z>Mfb6rWhuX_O5l>w8yMP3s_*s?&s_hL(R7*>J#(GZXt;|&HQJq&PNq9#|N
+kCHe{B8x?tA0Pr82jD*FveqhoG!*daqs-4erNoWl`=^GxRT5m;GFKK}Z!1)LY%QTV3t)=FBd%%3jifm
+_Mg#Qs|s<2P@D1xxqWm>-I!YrK8=^NgHT?QJZMA3yIq8xYG-P453b%VKOROzKL-nw>rt@c8I+eK7n=x
+8X9+qf;r+`U)t6Stt}78P)l*)s9X7;zJBuR@sr2T4w4V}^U>j}{U=Y>9Xo429{v1Y_EI+EWG@N{{}6W
+h7W8=7-$<`jO-4^ivtUA)&}Os!@uaeMBav`EcQcQt$B}>@pRcLzl(D&6WF;L%6miZ%(K}tc6C}me*9a
+dwJsQc?z8%R_vp&6&%|;nfYkHfHFHY3&HbJFql08T??fKqXQI-K?+j`&p(B%F$ExTy*C6{(z;4>!ho)
+4{nK^dn0p>;g{030~%H2lz--ZRTPOtp#+@u#$Og_;Moj8sxTipM*Q`pGT5Ag?oZi6va(?N)o=zQSF*f
+7M=f)2?fD<3=Fy2+~GDvHF#{T2AI@q&%w}IiGwOjHQ&DrP5$Z!wrkpF`E+FHvw(EcWD@)VJD;LOw}!-
+iuuagACJUG6s^6Nb|Y>A$yi^Px+|$B=2|H0<44C^TXy4$AD9J>_1Ev|KGyg^_%o`GiEq$|BJAH#6nFl
+-p#tVd!8tA2O*UhPrIWw|*qW{dTG?03QM<~k?<uC1(GA)DSbM|~hcn<V+ir)>hE|2#q?IWJRNbWAX&-
+HFuS|Jo4a#?`)9RZyy(xOT5Ud4Qo4_w|EaG&+r?sw^t8~5FhuAM+&&GQ2Gq*E%ypf1GlD;>IEDHRni5
+frDy1fJcYAYuvQzzu_6&_z?S7G@!mCy3|<LR~Vo2?70+rYAJvt_)AWQGV>Eiz6Q@J%~BJ;MLU-I_&5m
+>*u_)0RSX$N;0r-;VHJk$h#y355W*5(JfzSW4}vI}4EzhY?0394CWO8Guihj8d3RO^A2_U}C{d;D#yH
+|04Gw!Y3uy=q|^YQK9h|^KVGe=o#;L#N)o5v<$2hr@D_2419hdiKP8UC(0frA_p@fpwN%moLu1;<5f5
+uaVJ?yEu>I`jE$`7Ntwls8<;$SCZhjO4Zfwu0!F0U6c{w#mBXlPa=j_4%hmi1-%?WeqJ$wCs}K;a*#=
+4cyQ@d)I+IMnbUr^q{NQ3-cE;u4;+J8k+}=s<-s}A7i;d3C_T5I!byX9yA>u6O#BZD#zd?Td10<T}qR
+GfzOD=|>&D98uHvy=4+bQc|tf<wl8i+%b7o(Zk3*(ZgDhA%_*5OQ2&*Q0IYIHp3v8Mz1+}LR0dA@;gY
+1Z5eLDNVXP5Z=Z&}l5L{|<r2+?>A&w3vHjaSE_wYt$Tqu5-fC)3V14VHxa@nT%E^qQcN2L~7EnDvmo}
+AZms~>}VHK6I94Y^e?P~-l(CX;Wj?y2m{0%JOgV@+AR(|)>Xd014sh`A*l7!ihwM1T<nHwG=(VqfIv~
+i+ZO^Vtd5xQ*`4oIPz~hKzEt*7thh`hK<#~Q#5B#^yBLwSn4smD@-;WoS1Dc>WI1P0($9+&Hv6LN3LZ
+QcfT>x68werj^fI3~0v&tUEDFJdMpq63i<!>5$^_5$N)`2iC77Yu6UA3{BNP5n$wowIM3!jD@$vllxH
+vwZHV`pC*+&F$4uPnJIT6J=wj9+71Sy8jFA0!exf3%uA@e@hxu1S`e)rUbmvdT-@AbGhlE!Y*xc~C`c
+b0g7CM)>#)&2wb@su7v`QCk6(9?%6+^0i&`n{KSv9-0oMQ@%x@C#jRfAtN&JN)6t{inT`&-Wi5z&`Wh
+&wjdZwhk!W)5B*!96oux|E%{Phd&)W>AgI7zW-wX)uC6F#m?3i6Fzv>`^)S7N8#&je*LuK^^VF-bqe3
+#RoN@v-{b!L@x{Tx=JSIWo7E}5<Ze5B{bEVNuXx}d|L2l)Uo*kSKfHc%P?hEzO7r~nvxl!<@4tF{SlP
+~Rr5%qeQ|wcUANL=>s7mpGQvCP9i^JYej~~7Iu_E2h_dHD^^JHi1OMdzEY4Gl@8tTW74i0~KvH$$X#}
+C~SK1PIS-qtRS1e?IZEy!TYk(FH;*^`ae5O;}Z5HE#{m!9N`fx|6>6TaVZxV_Rw^oa-b&Gmp@<7ofy0
+3VqWz1xv~KD$zJ%6S7f?`_|CqB73Xx0zMBuw5}_v6E!AkkW?Y|0H?#nm%SS+BAA*jE_K`aEIR-<IfDE
+WlFjcF+_LVsuJ4uAh1@H+^TS}YFqw~AiO=7V7?^2IYL~(4A<giOV@nG2}`Q=L;fm%n2#5eY0Ighul7T
+u?ZMkr90aVuMSaSQsy~iFg+}pzw8AwJnR$9fa4|(j;1XrONXf9WMzz8V2B=SSV)AQrN?)vyAgi?$i;M
+=@TZs&Fgu}<BARidneq+eY^Kr`=-?m0>#JIc8bXtltCp0NHi`&48WAMzf&M;jMH8hVgF~td~yF=pj6l
+zP>#V+fPN`I5F)7E#1t0ajx&0#BM5q&!EM96SG1H4MwqpH$<S22>SFown}nC*%=XKG93CDHI1>@>UNG
+3B6<da7=!s@UC;>^bAH%b8F79^=QZ2LA~hP+lSfimqt%rFv@O_;TE)xsEkXAqzRu_gQv6noh+jB_&@P
+2}I6oTDd?v!N4PGV-Q!cIn8GCSU=m}-)C%hGWxTha_n^f4Zp)kcG%hU-o7b)ptG`<%sd-k#Zy8pOwH&
+JM=<iH&(MUf3DlbK7q#NOeAvUPv^^IJY?U{)S!q45Q8^>sPSP|DY@S5kI$h9|8_#MkxdvxkCPHGoQGW
+eUtB$ZsK3F1dMBQticLy+&Qw*Mjt`?qX4NPoCC_;jU5*M~TioO+WD8cd;4|5c|t8pV7pVn!BHg0h#^(
+d;=Q*2ur+|?DS;oBJ20J=<zI^IZxJd_!|<`G!zE){+Up)8^Dq%jDxtzJc;)sA&R+%tWBAvdy(gb2R2g
+k^<a{=^8ixZ)3{gDR<KH5Mrjcn)*aY9WU?3fWIz!Yi(|6;@WqJAQho*;UI;+Uzg3>rVm}O&n<{Fa-<@
+Z{oAtOck8E?C|9zs=!YEw38D-DhbP|X@*}pYc5wo8eMyKvk6_b6mUHuKyUd(<ECeJ9c#x^#m&vOF9O!
+C1JOV?j0zn#buq)!&YP?t?f5Skn#j^dlh8~eJc;H0oRyNOZ4v&u74xhAw2A0(N_R5UFgyCY7RL*Ozt1
+@fRGBwA2WmOa?|>l)h3{4)@OiljUTmz&ODMeWs)q{7?_8gB!~~TQ_=>Eb4fs9^v5!5_W7n!E$LQ;5kf
+h^Z+ur1MK-e|~7S1M%F#>R^?fUfe_zW_gWpC2AqnsjthbXrcELx>E-J(O3QgCML&FQHiapL8ZpzqH0@
+hM=g!gkIw!J#NIWG~{;g`G!4Snyb`Mls!@l<aoY(c7HhVf?){=X5GmoNJO4zstPYbHak7(Vc#|x{zZP
+geMUFyOLQvLo=hfbfRn;91-_(ZW~eHd0SS|!18Xhf;<u%J+APLXZy{z51h=aNy<yszLu8V70)x-ta?U
+bsbBT+6;G5_UiFa`&l-}7RWIuryCSyU;kncxT=D+axn!L~N+P6>7XQ2}d==ZYC>PL^?WTCZGR3YsrHn
+HUoE3(|Sd({LgKsdq`5o~Np{Ev7%K>Mzq9>d|Ie6VyF3vb344sp<!`E&3<V-AfWr+ZrnQzXDypILw#U
+waX%a=_?x_5>1@EDj3&gvtl=o4sb`Zf!(rR$_xmBZh#xIDCH^$Kz3k#T9D3>|%OnHR4@*9J<1^AfFO>
+4$4z8Ir5;kuX&RYV4EI8>5wbI_5LPLmV3^!V^}*LSkbbFNwY^rKd(`h1T2eH~6|m(5+xzm4X<i%*TN@
+7U_)5!=G?#{e=qKP|K^3)rmAU@tNEL1Yt+*YR0`7s{6X_kDy&JG2bjok?N!?6eNi_-qm&FipaQ2>2Ob
+wTb_o}TSCU49ei(+j>pf7jE|s!)hHYr7E19;`rXKSi^J4XSx388z?*b7L$4@i7dc{p)uBupB3;SIS=<
+Cl=Z5A7i3j;@)y7mJ(A#r$xSb#mIZ!io^|Rp?58ln8f@mw}lLw(l*}07*q!@8!@rFRjW;A`9qbXf9bM
+9O)qH~3q^pUTIma6Ij;)6Ep*1FuybV416>7uT))i%q*ymy_bA_*dkxwdw-L&*xG&o`C<{olo4hOLhD*
+WYb0SE^mjXs*f~Tux5OJITw%j5;w?dQ$>7f?l1$fZNwT<5{aq>~3lKC8K{`-OjMQ9%~KDlJcX&vc8=c
+fkq%}?$P4t_23&?#Pxa~(K=s+#N_SFvCoHhSvtW}nkk`r{P|F$vv{c5L1XOxv<hmwci6RknN?)mNR)#
+_GR?@fP94kl;UwEE)mfGBj!*GnOZ}gAlCyRv>BIknHUoZg0(=3_`LR_JUffgQ1y&Li8JUAma|dCW{D}
+mB3<nG^?x_Y+Jt&}AT0~pp(M5KNrxxr3Rr$jL>yE5VJs}0f_voVyZvt-*Ygi+Jp?L}J*}}oriN8)G$G
+BjXyOS$!RD&y>lCyssA4H=mIhEB{3ifLW-9dJ?IA3-WbeJvYQ({qaM~(&jVEZI=Kwc`~I0-%bwGXO5_
+jzSr%dpMPY98NOHk!T<_5bkUw1r%BlfL5(@ITCOR^1hmIkRx<I0m)h+~iven}lrN>gTHhB!E3^B=K?=
+P46--Q2$VN@r!2|?r{CCrcUuL1{q#vpsy^;T>=;^Sa%D773sgp`WM8`#@TSLq@jH3p~*ZFV({iCu8;e
+kqN|Owx7m1aCuUGSpCDpY%V{vqeD8seV03iSws?S<D=Tb4x-+0?|1d<2exaJ$Iy$ios7cUUwylaii)@
+oD8+tEA!P8ISNb2dN$kN40zpkViGm7bz+5ClB&@#nPqUg}Ucz-+=#rdAEOA1&}uQwQ_=OB{coa-&7<d
+&KZNIn_#Sk=`VP08Ug3%LwVw?{x=nwRrYzq}?DTMR8lWbLWd&@+?F9r=|cy(rJ67mnJ))h9(WU{f=jk
+yfVq^bYYlCadd}ir!J58m3}@8t*^uqOzQjaioznrIPoEP6X1@`;T@+&NxIKQNlKj23aW>I+8thu+zbH
+Dv1%nmHV&)7)$piu8`UksQF@+phfih49<k8P8xwsQy+_;-i@b<Y&A+F>@k8E3y|C!$-{gy1GauP8jle
+7^lF+<uO_9u98TuDh@?Y5|0IwfgWlOyZ<fuzY57O@wyQn*$yGSCcav^cpdLb6!GYKi<5zKNc0H&14ge
+1Z9?$hmPhMnyU5v;{bUc>(Jty9($#|M5&(C4LAe(h74s2cwKwuz>CPzt8-_9_=fq+%uy`tq2OX;7cK~
+OjoC-d~Qd8dh*kQuAsO%~Fg)aBc>^L4P;{u{a<Boc~aP!I>a0J$Ki2x&oJNIja)vvU$)@xHM|_mBD|t
+prj+%WJx$EZaxh9UL1AH%SuVup9}=R%0|kD0EGv)xfX#NT*28;kR}0-rxuYSz3<ZV0T#{J_1Ih-1Q4`
+$^hvhC<LClrRd2)Uw9VvNC12}&u1+XA}v-Lx!1X!7Uy{HdHdoLzxlTh{%wt)JXAhKET`S_SJyaLOro*
+5994uB_&uoCHSVdjJ5bvlmiQf%qqN5oozpT)MYwq$z~(V4$pbuz?CC6C9)+s7QO8`9aPZ!_-0sA|x;S
+yE%Zu-xs8thlE;+|<`X<EAa9)gN^PKzBX}%{W*6t~R4B1i<KJRdk9F52jyBcDuU2y=lKhTlt8sR0>`c
+>XCm2bBiJ+|J)ILq;Js)4oe!#BR>vbTPN7qk`4>5zX2q>{Q@6IebNU0^uX!pAxQU{()cclj4dqLtXgb
+b-E1uP1fs8C=O~n5}RQ$BwgmxIeWr|8YddjUuD_xQa@h)L~$Us-ydIk7OsgqG}s@M^n4T-)>%fCyeZ;
+8ZzNX#%(rS;_hpAM62OWml%Rnx)?9@kMyn*U4+dwl)IKb6|I(f&v`lE!nM?vHB(ORnd`Jq>J(&2Qc)F
+A){Wo#dhni^;Xxgz!Yf@HkOpa)_GyrfGmwgCzwb@b;)3LtXF10(jF*Gkgu6$0g;pG+aK~U>OHgJt7sN
+BqXu61>6e~}r^m4s%QJ=c;vC~{{obXf8J@~OGp?AFX>yACLym?h`p?*rB73uVPRpe0?n^bxbkz+<^o~
+(K=vVn$k6t^Qm{UOMgg9qche^IKa>a${$+eUsmCp>uTi3a*ze^FGu!p30M4kp4z{W_Xi6Srgc+V-wLh
+c_^|<l78+5N4;y>#()pt%Zr7M)FWj_W8*;&+)V%LE7CmdX!su{c_3C(HC>dq3<^px{ojNW>e+-=e%IA
+Gvtv`fo(Ks0o^tasc-P6K4&mo7m>M<O))%ROK5~s+r2%7G#$6q71JKaB#b*)Ik(5@<ZO^8FkTqWkOs5
+2N5c-iK|#@L<s?i_;ndLxwg)wRlVfZta&&_!P$Lgk=oMm5D|&EohU*Gy&{YO7VfJbEZr<Z*wMRc%gkp
++$;jl+a?^wrM*`fhv>T8DcHKKzxwta?t0IB!sB3M-Se_b=s4FUmY;RErYM0$A6_n5^wau=RyR4G}&s+
+}->L3X)>lw;_q!Ie$6$TpSnqOlN$5@uq}o<k?1%&ihCuN(Y`4>)R>#vCx-6}h-ZaV%@U#T}<jd#;#e-
+TSNKcp!?!L<L}YKEDgh+Msb=bIK3RAxQC;(QS&GG-5koRnC$4^o)${`ndH}(~KIt>CVSyvbvM@Rq61m
+K8_rL*eH(r{N>ejp1#uuvkE6(JiXPDd5~JByfl+47VQk`+e7tJhI*)8uj-0V7aOf+w}%0=dYL{?&LXT
+t>Su2BY8n?UrA8bxeQn!kN351t;I#3B$S04qwM6giS(JQU<*jE&M}%8h&#^dKVqjEZ?CV^H$4pN>!=3
+OHEA;E^e5E~zvWnWw3GLP~&g_~?B7Y$Lq}5FOTF}2U<YY7wQV-N_IriCSkoqC!dcq9SPkh~*&7dl7N%
+0tI-u@NNG~P!|d)El`fbm=iMNN>a@HRY)-e5WiV;ZNw$Oen)Af3*I)ccRt@m1iOXn{>LMn@I!82EX#m
+F(`?Z#NYd!TXP%x3;P#=i7FUl1e%HzCoH{On4`0U|0vaQ8+BBFBJ4$0tbXfG;R<$D5!4box-T(>x6Fd
+n3==;GPi9T*^j5gekJC9jY^n^`xCw!=Lj#$M*`Wv$rng&_`6H58Gdex*_63zpr27NZlj7jEQAaY&{<7
+VI7Xj&*9OVYc-M4>XC~|6out`C+!OQ2N91Nw9u!Jrd*^O)x4V6B`>W*ZZ@#Sq-9BnU+9sT0kD8o;ze6
+rNqN~mBeiLtv8`Ka^udbmXjBB`9)b$?M(ppOkb{!>G^vwNt=`0wk{Ze>2)3F|XLWhSUi=R%}V7byO>u
+_TwyDG9}W92l=6|8UcATuGM>Inf-ZEkyyMP~HmK*j2uyPaV=hf2E7P?Je>*U_!U2F2|F3-W9kX3o-`I
+V!FLi5-&K;B8!RBgwNzjp812w|h&x{vOk~^7SwxGs45wq-#t_RVsR!zK{x&aepgu2{MI3cHJ1dX@cSR
+8|kzUWay~Yhn#k)S{0V$MX~w;gAZX{#y-%stk!6HjfK2Rl5(4+j9A0#4kuzXY~YHP*3qk<=U}=1X(n6
+uC=+XaH8f%T;IlznqjG1S<PtJP7(xe?9>AQ6D<uKpgYr#Y%#}3cR)lh?DU1M6JJ7DS7Zrk2`C5Y_+sr
+Ts2>NhaRX|QK$jZK4L6Rj1p%ig6hkU3+I7rt=7npQDPbtuh*q(dEOh)H#=ID72%|U2$Ix7Lod6QozlL
+d4FJh+nn5IcE-zwA16R7*?fiPlASwFg_o<UGT8a;>d4p72QHD~u*~Qqb%>HYU?N87>N{8pwi!kv5`tt
+?J3Hlo~>crA!R5l)Jl2GaX~FyL3K!i;jk@DQ6`XH&)5B3`e0JhvyeW&J+6&>4l@MlcUI;f^2F!!}0^Q
+w`K5zLoU_{xeA%m=KXD!9k)${p|}|$CQa_|DXLKA_@drW3cTbEu8Wj2sF+c3E|_ZMLGG~u$dzyLuzbm
+`4}(hmic$dZNn$N6)DAAh3sOs9V?Rv^wVd-)j(-r=PIaxcGT@QlNxma&&Klbhqn?qzu9zKz(O}wCO9u
+LnSO)w(%V0vrJ4Ye@>>%XNlIe#ZGx4q3_$)*v`eH9>sr3=_{jZpGKq0oT%O=RLB5|bgBVvl?d~&Ul?I
+xR9H$Xph3PXjpfG5d=ZF&&zi|T?}Tv8|5BtIWigLnc~yX{>w!8BsoFWEDdaTQvmnbhfgRCF_6E$jI}^
+F18`uRv`na|yQkXMF`BhiDdDLM=vP+@<DGa21bmiTEZXK|NI_x4@rBtDQ`;vP{nzGZJ_gp<_(1@J`}<
+?4|LC+ge^U-@>7=+umiT3`_4C??RoS=1dfYr3mMa2g?gPqw;xmdUGz2ERBft)OOSk@ABfGLd$wsR4ZB
+62g@goT_gE<1>K`k>FLrwo5KXfSch)0%+c9AT~Ccw946MLay^HM)r^4lr-QiR&!<=0s`^SU4NDasA+K
+1$-Qi|j9U3Hi$>dCF8WGonhYn5*0ZUEkcGZ!8E2u(hHXcFgon>zHZ8f4YQH5rfQZ@!Cl9<R<G>z+piZ
+_In`T^Z3mV00{Rvzja?~8iRi<P}DD%>dQT_`@;eL^k<jH~Zwz91mecarnTJI+i*b0pTY0aK{prF>6-P
+pEY53BYk_m);M2aNQ6n>yo<x(<SPT;6v<=U_%UqsCw%3Y+r$>tyAZS-70+ethWkK$>e*GhrYo5$GJ-2
+Kf!&1)jAAKL4zje-?z@F(LjYQTdgtB>WDwa+AVuPdV!#6|GFh{Y5gPIlH4H9!>V0;6ZavXeVD={`S0d
+#Wyvh49Jt@;3P!)Y-o1xZJBu2EsgJI9m3}Gy!WfQ4wsrg0@8I$zG@4rbvSVcp){5Gze_cw%FD3r*6)U
+6ZVDxr0Sft~BDOX(O%0G#2#X61LypH9=zjQ4B(y_$bho67xSVEfr(y_?rlXNTxY5&a%+Ld*o96AINC$
+Z&l`(!kSwU8Vr?=l_AzpbW2fnA=$WrCQ|%ZIJTi-SkW;fwueKO7|gb@1fL;ZMmAFAff#B@dpwK1iOwe
+)0Ut0es(o_~+!OA0NMh?=KF2dS-`ZdXvsF+QlrQFaPp-|HVP_@bQa>kp0z*$3P#xynMC)BKh&)Klgt)
+e3l$Oe1(54Qnfe`Tn;)ap%F0s+9gmdU4Dz7S_DDrnd&U~gL2TqXlZ1IcLdbX>@;n-hO0)q-J&cOIqEu
+1kA4wB`qttHcF&A{wJHohb{lpP_@v=D_8}HO&cdX{1FHrzfw65<c+x(}%t&(tvnmtjBXi24)S{jsu8w
+V>tNDUw@Sr18fY7?24)jt*j`#Z;!=a)iVmkldtX}=M<Zw1`nQm#z6Wwy#>q*n=7K>>QEojOXMlEz!It
+^<g(}#OlW*-e-vc0v{Nw#;kV!33tQBNmdZkg;bkvaF5Tb*y*tel2tJZ0S35^{RdQr4ZV&OJA$U-e4c;
+Pu;d)Z{!EG?BC6H_nOQC^LSc{7q63Zf)U%4*mnAnihcJrc<W%m`ji3wc53ryrT*_kFIu|>TbGCycINk
+-GQ;&&w241WyddHZu#Bu`oQgtFHM8Ksp^Z@2a&GuGWs3yWzY}bM7n{iY(JNV-}1QdZemTmM9;j$oqCB
+o_l~TVQ+B6scBlcS`xGg+e|AhW@5TFvC`UTT%jtK}PS8R3A|0eE6?Bng{~StSPet{+!qT`t#zUZu43l
+8{P}ZPbuZ&Z%)rYQf82z%Q{~Uf<B>z>NXa9b#1i#H}x>5bF4g>B?y-1xv>e!y7=*&78^&@8#^qFTY2h
+_zybpfHfEeIg)`PTh~WikXNnQ^X6^2Dct2KPrnl_Q4jOAfixW5FQDuMApHmrn8mM96oY<iE2bKP;Z+M
+dsOiokaVZBs>B?#y+@1jfhMXJPO*WBaNhH5Q2}KujyFVauEsXqy-1aaZfIfBaR1abdcK*y{B?wrE}cU
+)>EUD1pIq#)8RCe(OlM?`j%8p>Z;jfrjcET)hlslFVe|j`d}xrqMP7nKAAmHapdiXaP%IieM3>VA)O%
+!G()A(GuKW+HPblJ?hJR*;h-LpnE*Nd=oc4RHlvw_=Q59XipG7Z_YnJ-+LQu#xdXwFQLVnC8h1yU;AG
+%}yZv#N79J#qSdT_usmY<rTLTh64^iCHh+i*rHp0&}?#%GB^1Yc#yu#g?)m?SYN1Tj0TmiSOXlPz#-@
+A-frCGO`rClqEkJ?SU=h>V#&Ne%r#3(Qr(NxW|YHMss0PAj&zs+LR<f>W(VY=4RgZCBWwEZ>qOj`w+R
+ns)04E9!~$4@p0OGto(u3~e|fiL@)MfmC#;n8_B8F8q(y`<4mmpDiMEso^$03_GEunXQqFY$+sr&1%d
+OT&B0+){%n@R~Ady_cGQY<nthM?04e1~iWrQ{MUqC>EB+^NKvD$ZbZz2N8CDk(KIFF}BIvse=m(Wl#%
+a%`7%+mzw7=P)dAJ_urxcC;WNcHL65Ym%wASlNds4!hyK;fJVyKKvPddoYXgQh4^o4Tp>E~9C=0@Oy5
+wauM^YJxeHKvPCsLC$KB-h6gu8je9+nZhQd0Ap$aQc_5@?c!B=f8EO^3o4Y)ikH|e`pl{TQ0*x`8n((
+2R*sy1|}$J*`+w)YWwZEvQ<xy$DyDx<EExvlC{7E)a;3AAWx;guEJ)0ed<pcys|lEF8g17S0zfEu7Oc
+bN1#5tloAQYh@=xUGs(HCPc(n1mPaB$mfjPpC{)@l{xJwGxIbk+NW8J&0I(9Yuz%Q6t3FZ+wKT#(@ph
+ZJa|t2~&G8u3TB`S>&8$LW;p4&K1V6{oK-QT`Q)f36^x?sI+3SRc=n7R6q6V3<P!dW&2nRB(B=pFGM0
+ciy8Z!WlM~ksHTny--<R(z6sMa8{S6=9t{=KSP#UFh26ZNn3k&zFcoNVCNrpBXq+JN?;)z?N)aP}4}J
+B|6f|=6&W!cZXNVwqjnVytaFU<nR%3~5!24Z{NIc->x`2366`Uk~su(|gp{Di^3>R!ztDjqg=viXY^}
+zSm?X9Iqe7d*(X#>B-V!VZ2>Lzh?vmDyPNpK@$cis4KpEb~{iSznDG%}L|pWTX_?Y%fn#uiT-dpkNK+
+g}iE?!^FbM8(joO=xm*eO{N@a4}}wbjCAI<{*b7+)hCN$csLV7|qcU2*V?`_p^yn1lZ*H)%*?oDDy?p
+N4vj4*7kG*5<!TYyGr<=A{%1JvR$-7TNXPga^BH#DTj?r1*YVBW48d|#blbimqI=^LIQ~Ksv&(^E+qM
+`0TV}ss8DG~TKWU*9tbt`J8AGaSBKqZZ=&_zd5vEdM9D+$?<BWl0xF$lI*CNGtBs@-wT>}rCGSpWqe5
+EUpnrLvbqz8|2heIb%amj882o-=t|ODH;WJQ^c+X_?(nxb5g?w}0J9zexX!|CR)YHLRWHJI*rCe{2wE
+%bBG%OC6JzILh#F02l78!ENk!@9wsbt2nc`@y=bh|Mg6G%SAE1Js$g?A`m865_<vBy}1Qd%V(p;e7C%
+iL{GL6dndMv#xW*QUN}W=C+D0_il#0^gktF>}y>Uzd4tL1Ukxax^Wj-0`AKHFouAT8Bd;(GbeL7`ztu
+53Voh2wZh`-Vi-*mSsh6kj-KB_w3V@V!MW%Q^pi8UpTo5p%u`wqLTzNMz7)o2t(ZyCgfH{@kP5vc1Dg
+j-aDh^w&(4V)dviVne2HL)9hr=S#33XGrJC?zN1*rESu2Rn&kdsHSKiIP^Rzi?6Ezv>9IQw$>@ktwaE
+5k*bu1bH`zP9QZ;GX?W4_myC+>Zt|F)W_^0=#G9N8QrTSW%RoFDFiyK%Xuv*W1i`clfLRN*&`K%&7m=
+0R5;=maScj{agcwvlvM@ASmM^%$jT{F@~<4jbMJX?~s#a#+rd?>aREw5eecGqxKZ_MHgdEY}ZH0~Pvb
+8i33d0NctWxS^fOVLJt@Y&c|b`C>Bw}p&*Xtb+bHQT1!E!@IP;P%;o2o0O1vvqiKL@!R(r-x~Mn#5g8
+Pc!JsiR<4XEfWU3t=LmiTNm-4sQ1O)>WjT(>l(UHLT{yDsxZQWT3%xRHbR|)G|^PF2BlHYzbCN0E}MO
+YJN?q>sxvU9-J66W@g350QW{g~;WKCWyk@g`Y$n+LKFbqG)p?5hZ}^7aq305Iqr!aDuOH~Fq+<qwW_%
+S-iEa}52MQ~sziZjO*92NkWE%xyW#+>k)}-xWi(sQX0iKaa=9P{YM?|=jG)?;~i*@tX>4B!K%KrgthY
+l2uOoK~l`%{+^&C45HNZ;q<aefJ6$W=WTf0E}H=^OMzpD2?b;naK@=MFT>i_glZr-uINDU=WE?KZUMw
+wBV>x}uACC98YujxcZ&)soSioi^WQ#b`KEh)V=Q3ui=pG_ZD$>ILsR=Xd?;QvP&&nO-SxP{^B17a&u!
+n<$>f5W9&CQ*2k)lF?W#%M*zxJ=VQw>V=?A=w5morS;o*v{0_6e7xxQDV8&f;z+#?p$VPXOdE_o1sGa
+-mW{dRQ1?G)^eIk>N1-%n?i!z}K{`)+a2gmSZro>`fXVGy3Gdi*322$L=!>SLad!XX+;{Ya1EojNMGI
+=0F0Sf)*2|}Rl&MYfp%ZkinKa4Z#D;p-MXEs6-d4WUEsR7<QkynlK{2zd3qU~xEtfHZRwBB_XN;a9d3
+<CFSQUNg=9u0ROrq<bz4eirrC^fh1vZ*?t8q40KC|dHO$K1XM)ah&&8BFHS@bX2f|nK?c}VMJ$G~TqS
+$1m4S*yXUIZd*M$15kY*|Iz8y@=HnGz`h0Ewj&)#guDqY@OivmJL>8xMvx#!F4&VDL`>t+(1^~xA;z&
+)wTGo-@l6Avd6u|$Bc4ar^?K6Z<#)fa9wfhMnTPi7#L}Lza%&9;r_BYF0(&1<%FTaZ~zTB!k4nNH=$~
+n3o5l4M(9~+^zwKEE%OkioY7Pf);>$;M7SlUFnjPEFEdV0F~SjgNVn1cb2M2@6m}d2>3ox-`CF#VW1!
+fvnJU#)F_oZ<kB53glB`w(N7&_R{FQN?*g>804Ul^J=j;l(^l68Ji|WU?XPn|A^?)pTP!BofeU<c$sW
+pYNcWBjzI)7<1gX|OJ;Z$)5>@?=VYOIu|QW=(ZlS9;GU5-%ODmi$p&g=<0&-KiJTGVy3>fi)T-U$Ur%
+O!6A>eWQMw%xM~!&tLx|Hp&Pa(*?=lDBCwLXS$3BB+zdxgUmRIC^L46JdJvAT^qq8ivx?AaDBFm8|ey
+Kc7rsjg9d5j}15412iTK^Z#LK{+gXCsvEDdla$fX?xad@aRhBUv0V$++}(Vmi<pJXN*kh|#4)RLf!?G
+roWlOAHBC8JGvib<n~n6t_fCDB#)!eCS0QEP*hyqTw?o%XDNsxUVM;&Ark_^mPbA+N*3cFkYcAm((8n
+`V@9F-3_8vcbwWLDtKD9c}WdX-bUrlLSE0$5R!<5QqGcS`-U2xGEZzc;7r6|JIK>O)%dM^oCue6nA#$
+t+cQt>am=CFn^e#AVRpp-ctK|kP%6FC2NdqsJ0Z)+vnLFl2-xg+l<_nnT4m=LaTLbm$STLpMdW|ubfa
+<>X{lC2^H5~(`tq76Mq%r0Yg7Hc=Sgn#l&ltIYEz#%fX0-P9LcE?dRJDn)?>(Tg;Ql1|iLBXx9PNe1S
+WEY>hR@ksd>vFHz*SPED!y%l`Q1UJ?GE583UX#(ZWiqNRx|3|T>7O;c-$Z}gYC;OA51gU6xQ^EgIGD4
+d<vu*(j^G@-Cl!uadLqpIxG~Y>;Rv`8hWxCp%Z(DLcVk=4#uY#I5JIAmYNbP47+pJ_mY1R~XX#1jNlp
+ezD_DR$%KAC3g_7iXIR^?97m7e5knd>$iW^750huVT5^GC!;ImIJB6Ph%{o<Q!j3@4NFkrZBR(|*>Ww
+z`Oq^CV9mjrcv#mc56$`8qsn@NXUy7{51E9QojCNFs}QAVsQa8Cq$6i*e$S?2-Bp=m)jFC!~t6dSz=H
+dzS-@4woA@Es5|l5Hos$`^7{yGkxGHY?hU;eB@0p+;0FI3m4ydRCrRO0<`iYNKJU!WqG6sR?p9@b%4&
+@h|0IxV>|Cd{GX5`Gvn-{PN58&dyFFs)(MjBYKsBW(!p>L=?3!Us{UjZ|DsdgYUNOm)r6dipF<4cVqh
+L>#9qv-N~rc*d<HiKrh>mRyLi7Mb*<(UB5IT#BZs}C$W4-4YL{=D4o-{XhNF0lqL*A?NWmoPwDI)P$G
+ln_wR4CbevPzfTh3#N?b8fO^`M~MHSOg+0?l>#|b;n`1;(J^E59zGWE5bc|z9!m;Ff&%>_ZQ-JdSe_0
+V6VVTWoCMrDfZ$>@IgEVxwr!^N$wYrkpTk5#%TpevQ``{Oe2_%$aYoFC=gB!5fF(v;%xS>SwjK37%G+
+WSylzZA*uZ>u5s?LT|eNe*9txP163!Eki5)<f8=$IuCKgz6*>NCasxNuyiNK-g}z9qXQXdco|QukUj7
+;-zO7Orj))X^!94`Clv*{?@`WK42*yu$;DvBH(jgG&svrgnla~2^(feaw28d3i|pg=@*MZrgGWa)Fy>
+tT+C*9L8=eP{3a`5gFR<t3FT(Vw74TN-y5hu^7yL`-BOIE!_m7QG}{F-Rn-(p#;Nt4q@`Pn6}Mluk5J
+2Rw?d%)R78#<bFMoY-3C45ofW3|aGa-eN52xFAwrRV!^3I|GPi#_mHh^+2%2TsZNwWxbq4MP7#mLQ;<
+F;3rRNyVa?VakrA4lS#!AP`we=?EjQc&^VJ@avM<w5N^hwv)N8hZ=TDK1~ge8|Lh(w`YKVq%6{w1x|R
+ORobv)fyW<&Sp_59`0Z4|~gVrFM~dYPOvk)t%YwtSL;2C=ck(5@qO$E>z`JPJgA~Gc<0y<PNV-Z4G@P
+6-3eueF0`GP4N~(fYGMAXv%OkOrT2Xhl#4Seu_j^<x`Cb{N+jIsaJYL<*{%edbzR_*k`CEu=k$I_&5H
+7W?=lqcUE<vWNs7^4O7#O(o=RGzGUqtMc&sV#|Ko#Ye}4*Kh}?R9&#n=IUQsgZZ*^HcPmfeNZYf!%_V
+27Z|$v4-ETNyr&@SL#;Dd}L@ZHaNqpn^UZP+z&BlMU_f42ZAdn#rOndzrS4CD24>s0-tN?5gsD(hdd2
+HP6fF|}b{_lI@Ik^}GDuN?Z*TA(JY7um+Sb?cjWF|hnKk=58QLWR_WMd&~c`RVZUOpU5r#8H=P`R^bN
+Lm{Rsj^z`=Gn30j`)Xp;3QQzC48*H=bty~z+x)ay8^;)K-pD{j#Z)#tWD*5Q3o`-iVX^2*|m2S!azjT
+8uWvH;b7mmNG#C|jErL)*(+0hdOvynwNj{qNaOLdLO28b+)PLVqJ(XN^Ojugs_Z6&fT6NHb^sAvxesg
+N2T*U;#t^{I%5enL$Hi`}Oj;3k06+Di2PpFmg&#16XCAbrtD||5&9eDO;@mq<ijHZHt(KvD*ETJ&i<p
+llnNbjnoLXZ-Vv%K&1Ux5?Fq#AzXz|W3-Pa;Dk4EPbO|nXqT#_3U9E2fzF@lsTBt2SXs4fvwrr36+^5
+pkpUbvz?A!*Zf<O5|l=$i^UhJ=l<f^lO+q-|^rQ3T^~lm+Sn#fA{|oLFZ&8WbL9rK32!qi2K2weccWk
+`95Vj)`PI^FwzI#X5MKj|Nl&oGe_3Sn=Z}6e_M|#$&B+W+>LO^i(ApI=bw3ZTD`tAu*$Nn=u>Bm_4V{
+vwd14AZn0%;AJs_Qcypwlb9MNx0BX($M-LBD;m)+T@#WmqA!3+XjBFUfVQ6bsbjdc<Z%-G3fVt58+6L
+3=7WEKju&UfE+0(F(PT7E$xKgOwCQPlTBBF|=hD)2q=3CZH}l(AGY2QmYj|0hAzJesWS@LI97#Up?D>
+~upBDb@D9$KO97gdd8^g?<X9HA({Z^_)v{9PWq$I#oOSomcN8j;YzXo<tYj9|#Oy8}T(pnRAY1h+^ms
+0t#D%NnrTK|zv6Xq%eB5<yO>T4bQ%!a{Ws{oazusVxT^^jDv)9fY>uGBM*9ZtkF_No}=Gm$dsr{<(ZP
+^x$dQUE7+FWne%22Dee2%BPa2+I^rAT$ZQvnxh}0qg{4S9G#RI;W>HLbTq1ZHw84zK_cb9S<EpI{hgH
+Oh@}7Xx!;3=jK-FOH$EAq=m0YL}M&6YKBzfOfCe~s?}GkR$q*!{qbUu4UA?iH+IDpWqM_)fs?CsO(<5
+JI>TyXbo@LXLOWwK%IOO12+K;EN=1W?jBL&3CbYVlRE1SYL^{WhyVh+P-S>)3)6Ushr{8a&Y=uHqGfh
+!OIy<94LH*{*GQw}NcXYqj;R^0GF;0#>OZ+1D_jeyW*nRkL_tB%>g9B5r``jv6i7@zC-yYYsf~i71ZQ
+t^;Ed~6vs|0+h8qrAJ-;XIS`F83*(B?vbJus=#2s`K~TMb8{3k+^)k+zaPB~$iyPz_|Ft5gIM$0|a;0
+w8#$W4`j9+JV^EE0djrd;nD5^U_OR1$66DwCKAh5~%m|*C$Q$iohr6o82YYR<(gR4RomLvrMdL?6p1W
+J80y#_YOJ)O$FY$k7G+b*^BNa))5+i_9!5RZ7`~O?oQIO>U_s}*~arn*gUNBX0q)nT4?0eeX7hDb7iB
+SI{89qy6Cp(l;bx?VMpjTL{Ju@BNg_`Lr&K6-q>@_mp{Fv0r<`*oyoR7CP(kLKPK>n<SV7<vxmq5>Fa
+nC->9v6&lck`*{j=<7m6EVhR_bm_dJ|?$W$v6H;nLyqp{qGNuLqpK5M_piBJR{pwQBR72yS$r3rYC-l
+*l+r_y;&P}=jl&UxqcOF|Tf%m@-DLJ(}WUv3UY=c9S@>uA<VX5&R^O1USmkOjJKIgr?zvD);c!|qXgU
+kbiQtGU@!hCcTDdv>4!pj8v>aRXsb7z_()^xu!4Q}vxB+dFsfeR<2v1u5^`!{hbDOS`?by}7luwe4pZ
+O$mk%Gdgd+{pRbhzT9*kK^-eiIG5Cy>#BYoHR*TLQP4zcZq?e(svb5ygQBn@kwzpx>!086KYp@{_;!q
+4h7uVr2h`iO5W(zCS|ne>@^0Ze-`%Fzpu1mrs-Ip@&6{WW{Hd4??^#Q~wK7myjWd=kn%!i7ibv>Jp{t
+(S6|3}YP(wosb4e9};1<qLwIZQ{wsZRVn;if3ov2;WYUM!1{r0CJUaze-kPhm-l@1F!(U<Yu48ro**d
+a0lqF0Eft(7Lby4T_+$WA3r;x~+9HykbO#7qsQ5m2bUDA!f;YH@3Mc9YeluD!8dT~=V=t3BT^PQBisq
+w5UaN}$96Y)~m7&k<VI$EHy^v$+HNq)gEk=(}W_<aqjdw3Y1c+HXOMJ3;iv#`}*A?>Hb8;(Xh?o7+K~
+S%<_4QFVl(gBAx!n$xnx%Zt(MRlb5aLHvz$xo8<NBY6TXfzd|+L9N);n;7b1Iv<VA$z0f#yPw;8dA;N
+@Pm6OnUOVU^#f7pGR*YP(KSZdYDoVLXOjHO&Z#48&7GVMCbd8q>?BpT6+ajej6XtdjUQUoX)IRKNike
+3#QG5|cIZe#w^i*I?sm5fjQhBAQV1-3Vb<Uv8Wr9IFMt!oP{p%vfosOBEZ40c_MQxGfM(1y|drC6Inr
+OTLvC<D3sjG>mNp)ABQa@W^rfq-;3qj0)Y1nS53C{W+rH(RvUe5nWF{8+O^(-6aVnP)iK@K`EG%=M@@
+bi>ERV+5;)>ev@MMmb;dqJS<!^Ipm7j!N6xGXWk(F;xsi#Pe-AbjqC<Z{brRvU;|m!TOyY>^+5M_Jhi
+20~Xj^`8$(@(8W!4`-ft?IwQiZ0e8ob?L`W>(&$`FDUXMR1+r@e0@BnJDfQkYRju~o=uW|k(O^_HC3O
+lyyky<4~ga_toKnLdt#Q2@gSOH<jkF;E7CavV>QS5`G;w<9U;1X&m;QvxA6Aq2v!Uye94t7(QD%pwQ(
+SOPgy~TC_DragacJtMDKm=%fHqZ5E`KCmoE>V+j@xRho-$b;2kf|H!{^n5Lb17g;U^aP6xBa%;K4Jmk
+d-bDw_iR?5%0zXOkvSuJI>B$!avflaG_ZK#=f^w+j$xn7%lo08=OLGuk-2w8ga~epCu|S1xm6I6mrT-
+Hzx{&1^o)2Nq~4yI~TK-c!2{w6Y^j+vA${e9%!VUw8>k#rM$P1CntqtwR?~u!~Hq9$GSrtp<iT%6c%0
+gs@=uwEMYZ7v5@=+1vFpU|%fFp=&jOr44dkHf`9(4g?f;LDp4Pb37M4p3E^{Jj~l2EGDxWz@#QDbP6y
+pD;>XAE_HnQRnv}>uIs&vZ|oP){M|ZIR$4tIkO8Y>y@GDvwJK-T``dd|ZQ&*Gy|I*;G$6zFy~_H-tDp
+fZ5Ups)xA!9LP_?z%@%6XZ4q{(q{je(YqS*6aS2hM-g`=@L@rp)4WrId>)!n1=Di@D*jZ=3Nwm2|}1X
+VYQ%tAitGF=3jo4Sxka-Zo!-V2t(B_(_63rtaIi|HN}I$%kl28o}-e?AK=i;N?kVd)4%KWp?7b@(mZ;
+K~~#BBpz%(pQ30ER7oPb+cP#<5=}fq5QFoitPJycvX?dZ)jCc+2If=STrGo_qyH}+}K_}ozj$j#-?|X
+3ky!zbrPz(0qMGWCljxZ3XWaXQ2*8!4mMb*A!jy!=+vNp_zW(u?(gaTiUyX7Hoi6z(FWr;a9CSva|n4
+^skVuf<_45Tw}U#=h-e#3ztvZqJbUF7xycN`wtx<+t^3z0Cakerttg^MwaWw3u-AdaZdfrk-Rjyp?uD
+tW-j4Ru#x{<Wc|uhu+}X2k7peHDl4?VX&Dh)G3`*Xjp_a@W(kRAFIwh@>rv<US#>wa)U(C%FkW(^FIf
+v*q-7Bqw#Mxpr9^iRKG*KM+S0~^p!`)^UJl2Uhi^j}R3~txK$HA1WZ1feEibmvW(%y3-isDJC^xvy^K
+`ozpRvqu)1@qk2Bp8jPNoL{y7ME$U3P_8jge?Seicfd$gKD!TOeyBZbmh-Sd>t>t#0^mjB&gT|Ap%eV
+cAlNVgy^$-c%t0HSw;1evT<>BE*I1MQe!%DC{}~@fRMgaZ^84`2z!pt|NZ+Br~hYgHr%yb^htDO`YgQ
+K#FYa-swWZbNe(`Q=!I(<-35evDfC}5gaRqf5C8#A(?I79+YaTI&~sLPGT=}()n{<~Of|e5@Uip$eIW
+25IfMWE{F;u|+S45dD8nU!*elQ;n?}na(srq!2$-E+QFtlrfHSrOOK`2TQ8=6sv1`*Y3_DugzRk*Rk~
+|i$O;!P-j*Zj@3Va5N8;|;<In<22SZGWncsHzwtl+Re;doXxzNK3)3-e(<g;ANype;CBICtirJ?`4Lp
+8JbT;K{IUR^-sGi5j;oa{+RMABgGpsl>d;D_K<QF`m2|A&2^^fFo&^8vF^XY0INf%Q0qcQQy1aB9SI5
+dP7u(BbUV3Ylw7-v1?JU(<2|87TIj=?X>MM_3=YOZ~+)bOD@hg@xh5(lX3ZGG@KLsyaIo;8ZU31=F`1
+NLpsg6uwd6qw6>Sj4ZD>-eh`B923=7h{i_zng?|o`StIt#Das~JUTi@DuFGB2G}w*l<k?S&`iZD{2OV
+u!GEfQZXZ43GBe%!nNyiUuPOex$X|CAPVA6(8bu?*{raq+fGO!ElYC0ZI`Z~ASk<id4lM^4hW??K{p_
+@A=H37<lYrE3%u!pt0=1RNq32fC1xjD~atAcqEtD94xRYO_SYjmF7xH>oC9F@Qz-u1}Go?+3X@6?9k<
+fhHiuFYOByg~ZFTXx+-ujf>}#4onN`xVL}X741cX1oxP{SqXBE7}E-LonnI?Y9v>)OdVRs+T=0aE<9L
+hh~ANm6Dl57=&iN0Dlkd+jL+x!9+M0@7_U?)3x7O)=#m@uy;52n&=3pR}el!<Ydbej~a$bFzk}*`D0k
+K7*Ph}9n3IOY;T_TWC5-;O`<t(Vm|bgz!sSp=8V7x0D?N?I5y60wE|@01A?ATrV}Hx<Tb4CXn0!u3`g
+V4xW(8zc~`v(GvSh(=8-J?!k>zttU$Yo3BgxU)MLF2chR*b#cH{)H%T^Nnv5@aG0V-OZM6?l6CyF`AN
+FMu8H58ro|b5xClB>?x>E|19FpBlWCGeHM&?k%szda(U8`6EzmknAeuba;+43!CYb%7&9d(jnF(Gh+>
+0&}AL#+aDZs7>snxC}={c$e_pNne1V$$Vk2vgHtaV4JNyr>63MBW-*pZz4RY;wr$thJ>m&S7zh%M=4q
+lDUsM)Tewf?C=SVK(i&f$QA3L>US6OwQATzpz%FEGT2{r^z0t66F3eIqEgLuyaP9qjg901PIYLa4oQv
+5ki39hbpo%gv?c+0uuijVP>S9K_T4@?5g`(gt(;IEUmbLSVkF2b$4hF1&7hGWupzORK~rX}H7K%SrXo
+vBfHlzB{uNqwlU3UoVFXiHvo^^b&SBHRI5UyQVKlNCI#KN=KS>-btSf8}I*Ir)32q5gr*E<D4gGw6Nq
+EcMZnq=chD^atN%?Syo>f!qnJMf?^P~lvJxKB#?hU(JOrMCbRRp#QR{E%a(cm3yBppI#2zI}M*ic%^6
+udCM%sI5pySd#J1e$o8M7P@}>_y+IE>BAjJ(069SGsNLO&GvVMk@~oRLiI)#e%>^1a)(K#UrK(l0Chu
+6*aD!EL3DT64GZF<8GG2szh}UhqqvmWyD#gA(xm^lWYPr2A4|*FG3vq516fQ2@8dANrAzQ@<plqtaD?
+Q!VE>hh|Y1}ijNyAX2^uD@dUvb%tC>2c`mr82Zq1=AnM0PCwZC;vQd%4SfX`U<*eYTkTQVmNbsC_MP0
+IK8Lgn(wD@n6;6wGft+$Qa$=gwC4;J$RS`CAoNGJ$L96P~&W)rqNhdGUy0(_$coRaOpu<IA4y+$t8Tc
+ug@?lMkklCT3jlyd4yET_sV0((DLd3tV8SM*U~kHc&Fj1B@W12wD@W0bmllV*tTV`nnpYxg23dY!YO1
+bKyTOZG{TWk&rXIHm+cin`0qQFzyc6O!Yg(l>nrfE7B@ml75~KM6><x+9BBC($<@6}M}ADPm;_QptW3
+ttKfyTG897KWA5@vk8ku(c~gSg-y$9o*QgjcTSdFL=s1CCY-@xzJtR<CPs>r#7Bn$ec|Gr5Tl6Pglzy
+fgt=y>?<s6q7>!jq9iqH-fmdI6Wt&o%OkBiYEE{ZWo*HV^)RU;di60IvupLSs`0?(wqG|Bs2YpoXkm(
+zBt#$@Yq;@vA+oL2Sph{7QI^A{gX-GXF6XPW4ksu2*CY&;r0DAEk_?c#xJOubfMqsHlRWal6V~0`D15
+jN&O;Ws^%(RuSQVO7S$=lEW`#=9zvFSHx>qwVTjtbQOM0fzUZ8--}AL0aSby{RHNAqtOYx!g_V%-2*G
+@lVZ&aPUt(W_!<niP*_4XV`Y)-0cHre;Mp8>a$Uu54Qh|4JTjoi4NSIKJ`>G1&fby;!>`wHFU%#35?4
+*X{#0b8yy5ElIp_aI<&T$h|J(uP?bWX}lQBS67HXr|kJ;G;VmXV73lRZc#Y56!xduZ3jQA&!<|xqdq>
+bTgrRlTccC|7z@H#Thl71I+gPaHzU3Fm(&73^;~4d?Jr<9MkN-YiL*eUZ#}gUC3RX2Bys#Y#<j?c-dy
+la$LFhpV|o~^f#tHTy}GJ_m$jpvb^8`E0d(){oJt5GM~PT%Ze?9hS+3>vEh2wc)IM=ns-Le=rL{-5$=
+F7>yc$K1dr8yP)Y}}l6RjQa7|r-H<r_la!UmmX+VzMqdTB2pyge-)d3v8mLJZzSRmSlf2S*L$G*;<n-
+EMW0>}hm&YhaWv)k*5XCr{Aj+evV=ix{rt?0E9Y!>zj+3i56id(@r!oZLD(xgNB^MzT-F5@@u8;pi=?
+_3TO`ry?BNWR@3cah0eWTL&wa>tww_<JR4TF{n&guS<ntT`(Xkp6FphX_KT0`jq*hQSbwkoUh}NFp<@
+R;O`Kt_q0vaHMu?7-QL>TTE&&rsTdYxY6d-u`nR~UksWo(7NytIu&n5Qxl1O%nywjE+PqibPb;+EQ+a
+w~K{Qeh@^Y~_3j$gu_wVn8Cz|M`-V*HR9`smmay|5C>OwR|Kt=C*7c8q~z25DLKO*tDxB{T@&43v<NF
+R!}YSa9h@WqY#K5M7}jo=QidgR4VJ%;dg@PqByCHXfHvSS7e=xj7b56kjunoqALrMw(Y=DVnmrk{V3v
+(2D)b_G(@?3<P^Jhff1>L*vEX%k1hRY5BdgA6f#6{lv`bE=I)$^BZa=b%%T+lcO;m2}4iy?DkXfE_!w
+az_7p+M#{CZ;bQY@OH~>;Ff|~c$R3(!h&EIm`ruZ6#}9o-K5}J-0m`6qaTq3lTT5~nPO}nbawP{<Pdy
+U!PKcBhDgUp^3(Zds1wI1>7?~i__MesN9POFs8>Yy`lAinM*+vqL~YM%(<`NNJ3VctgI{36Or;~6an!
+yVXJ$eGZ~`ecyAFVj>1>9-#Vju9Tk~#r``-3f&9+8+yNkYP-6nb0ZQK5V8)CqTU4hz}X$IZkK)CAIkE
+;}$EGyS<XaL_6Yw)#N+znc)ya(7inM`y^YeUeDh`c~cy<ESYMrCFIY<}8pZEf$|1%^=<{>oW5KH{glP
+W4Mfb(X5^;`~H8$dc*R{BzE5Q6D%Y^it^f#<9p0)`FmIN5}#J>j!Mh_AlSt$ZD1~W@^{BFf}*HkC*^1
+Ms_>^Ke(R2Z5G)kUqW+)KAO`q>o8cVEki*Kb?=48%Vkl(R91weldtQXlPO6>-?@n#*D4>wM|=c*qrWA
+>YrNU+88kw<Mu1h5L~_N=&)g$4LW8lFQq)$6m_F?`4)z-CBxvBG-}<sO>hUBQoE3wdcRWWGrx8bu1`S
+EeQ17KBj|pLNdV|((qk1wQq+_;}qOU^PIywj4Zvpg>xGa_Hg3x%8U6p=766w7oNwz}7O-ZS@VFsLEX%
+iL-7Fvvkan;DJbU%n;b%&zf=S<dCZOJwUL!IwdLtJlr5$mwT7V_NbX<A~r7|60XUy!9C@pKF3mG?DMd
+7>gxlU@JkSMxVH2fVb+6w_pOrS3-^$A!wBTSb|S#%O?TERIegAtpKV2TW&9vx{k8zhWpm7Z8?WIr@7e
+=JFt5htnhlUf4<Ch~2O<$WA#V{C>uvrJZ_f%igHHYVgdds>}`5=E$$k$%+E5C))BfalO*lh<F#svLV9
+;cEB@8QgDf%#M2a0a7ag2wKFkk6oNyWVO%LSB61huUc2cGE|_{epcX9~lf_N6M7=>AOlLhY$myg0d@a
+tD>L>$m9d|b?+_ADQAu{xQFrv$lw7BXf2WZVBW?yW`B?kkt<3g7*JM1l4li$*PtE79kV2r{JoV$w(IN
+^(E+Oxn=1`Oap6v}>)k|3ibQVBxW&&P|&RGl|Sp-Z(MAvOfktze4SsvBgANbb{^;*A8av6$sLk!8k&n
+{`G=rjT)g02F77Vw}z*;bzD><1@uyu~-~~zUW{w)ZMc&>R>q{u*W`EiiX4RF-|eon3>8GbL)th%=4Mn
+8gq2k!b&j+Z-?*XaJZP~n`~D~dL}zcx!mwtgiLH1O)XOE;E+XEvXQ2s*;L6|w*jn<Y&@V&qp1l~yclI
+AnMCJ{`HY<_@l}+(iePh6QF>bTFt4sa42#E)fdk(n5pX(*iGO3JA^wt?NV^-&MeBrm?GQUw5%eNbhz&
+v`>%-1wz2)U(7iPVbm8Ys_z0pfd6{+8GTK)6A)O*+O8fxaQ-;b&-hA=$jZZh@wXuM6yvQ^wkOEhhZxu
+2dAH=~(F7FIm1&aNCK@2X0*K<2<n^qa^Wv_$u$#7~kr#FQRhxu*27wD=hf3BUwix6wIkD^#zOQf<1h5
+I-m%8^S@pqpje&&XPhf9ah{g*P?;<NBFg^(9Z&Z4ZDVsXaKrxM<cnk@7Z(Yr_ub);cy6yz13(yT|D|A
+{JJIV&|$`N@xz90pLn9wr&L7|4674`U9B?azzL&(Z-JzonUUW*hv88~>|;BPC01gP3a9SXOyV0v6XB=
+P*H_o#^TDiLoZ5#)KJj$jH4!7#u4SXTEJ}l&`2$COw2zl@YH=eGHZ;YiQMFt=8{M-YLg?PbNgk88ao*
+@e?c@uXpSXuDjWDY7cr%Kl)2Nq5Z4l6_FrZs~{#iAMO^$l(;Ppy?&U5E^a4^EbUUIH5oBByq+d`+9Nb
+0rDE-O$rc)m)wTz<qMri|({b@WiX6N}=!DuOTp5h=XP7X>LC8+`KacLrwOUslTImjepxunq4oQ7&&aJ
+E)hx9JG&6tn-8@mD&~dxM)|TBg_1b9nwcb&Wajouqf0e7g<BVn_m{?+`gV+QkUsfk^(t40A@3F)x&t`
+A;W0&!Xe}hLEw>|V~Npk?T&7(IR<p-7*OBto#pL*X=4+&#FG;!0(Cj*nb1bcUNbU=W0dTnCtkkVfAI?
+D#5j9PZV*WI;Mt=@g$|)7W}L}^sE5$Z1ibL)><SMutp<^?qTOWEK_nFrw$h+?OAp~gZDduv>L4gJtDH
+M{0DylDQC~r%C`G%kS`H`uP)93?=v!ZZ8`x5{rAz9EFRA(X*zHJs0&P}`u$K0hQR1Yd{W`6^<XQ6uwo
+-H)abPpNI)Pq|hF|JE&&baOr&{Y-PMAt9OUYIteOh%+2ZMDm16;99n_YCAn#9%Ddg2J!ESH8;$i?EQ<
+iMseTxlCJMB=q9&i>Ag*<8OdTxq{C*Sj2{jq1d*yHwR&X4T|e(A>hT<ecm3IEHfgVZ&lWj(_VN?NQdx
+8Tfz<)3dY1`MI`XP(E9-duiM%2k)5f-p6CKcchE>fu=|b3StnH{q(f)-FK)L$Y=wZWFRICHt{saaYOE
+ldtZ+k3?WH;*GcYkv!Ex*Fb<!{U5CU6|E}FoNJH@&lABvLM`Z-VELT_X{(Yb&*XnFUz<awO(u;IOxJX
+wbZtJK%LAfN8*2LTicX$2jPvM9fy<LXU5+?cEtT$M&|DM8`;SPzff+p*{fPEtpRSU&A^+>X{?Je<gP|
+|LzwOfG}EnWv-e*<*9ONMfMG5DoSN;q1;|M1UXJj8!~88)i5JKue$Cr(A%X$~dLYU;3UY;}^>kt88q#
+dsip_%EcDzmOc*{`-#>f4+ZTA%?|kkU)>X2GJZ0f4LZ!7LxgqdSq@&@b3`!1n84VFGV=}*3jZ8zqW4A
+(*5Gx9!p$Z-}8mfFf<{9$vuYojeawf@o4kzu7d%C=Nh4ze3#tyjCT!f$-Z?`VUgKIgG`m)6n|C1S$~i
+fMHfRxXRTqw8nX8){YM$5_hhyW6)xLf6d$3Z$N0}2zPFF3mM{|wUW@J5-D8-yclIUsgm<1BPo$P+R81
+w5R%Wb5-otmVR#Xwk6Jce-G)3OSzd=)d1JPeiuLlDzX@3RwzrmJg(-FbzksVWtF;S77!@i^fP1$gynE
++Z5dR2?{<HUv=^akpLqtj!r_Pyi@{CJ7qounp-N{=|2ocdro2-CuANGTxiiZ)-(ht%z4CKs2$dHga=5
+{$yw%gTNV^89n2(=W2~>|Lv993LOye<#QP>v;3{_Hp<4565?oe?I>AR{L+sNh5MoK)pRqCuf6Ht+3r>
+4vXVx`{Y(z7xQEG4sp4hlD7W+=-q#w9BplWn{E#GH@`o*vvL9bHw7Z@x3Hk@m{n*%a_e2A-AT5;0-j`
+wKJ3rKqM_8UuUX#F_AW5KZ@3J$-xK<r*Xh|0iQfa}iK^I#gdochCTohdJ87sWZ`)J`^3E6O^c>Gmd`n
+>$Yu)%XHYp&0^%im$*#mNpogc_W5moXDW7f4AN3y{9ioWr)bcr0+W$H|`b70~+rQD+HyBVv7ADq%-wD
+7p3Dd}p!+`82kS*<LPRI4QWFxLm6aAGKDX^8>bB?^r462Q#7y2<T(st-LVNH8|2HfBV{L-HUmiu|%fT
+i$v4j@4rYPL&y2L>`@>6{JmE?Ll}5A(u2;S;2L0;H-u=!4nkOw<t*6S6_egZ6i#XZvJXgre}SieEwzx
++u>xI&;DAJ^TpfCcUQm0bN-=+dFyljq1P}st`2~&a-RmyIL=GPwSe}P9gQua1v|^OZB(i|<CG98Okfb
+atVMZA;duJ?tylvhAqrBvTqKEQQ%K{pOvh@{G;}fQ#WazHWYvH$2~sqtrocJq`B{!Jh)hc%&z_zhZwf
+?gf^sVSJ~=&YheY3G@2UyI#5jJ})O1=v<=xIU0=5$P1*1nmqAzgrXew<=xb<#hL+4b%pzv%%awpAPtT
+!r!N)pYrxp}0Pd7lDO*41;%t>@Og<@MBkPg9N2f3K7VDm??)uA_bJ1ps6~y^JQro4+D*t(2I}`(0D*D
++#)*J$N)d&YF$##g&zt$?b3cH!P>#9|#cF5L9AfPtQc#abH;YY&V(NLY{ZUF{?5ZAqA*1phNcG=KwVX
+*v$(N&m}Y15ZZX&!LQpV$bPp)BIbV``Ai2}WwN^BAa)jWrjOsS2$yer`lWUkxhNM973(5Js)Mi&YJ=8
+Io#b{(@@~c9HxjSjIl!Hvtu<S-rete17i{QMlz%z`J!yU8x0$57#u(^0Khl8?{fRXbs1H;s@|;kBM%Y
+=nLJR;j2cFfHKvNKh78#ZB?LR4989RqV4587>RF1f??t5NLCKb25E=JG@bzvxasM*U4jDsDqR@~O#s&
+I1XAT5QlPL)s}w!d-@#Yv0!fCMCiP9&okg*$BRajwy;4`SvZDN8#`zme7F*+^ppYBhmqx3-e)?PO;sN
+z>%}?~|=G*%~C<sguS8hQ$wErbi5Lmc?qKd{*T&9o@F-T28JK4F5L(A%NhWlQ((cc~rZV43rehYBwLv
+$64FHsi^L9ZHQA-<7s}W_T)?Q1|SUbMS-p!DoXey9l#11=LJD8m5a#)l9BRegg=QFU**L`MLR=v!?M9
+V+JXu4btk!d5C6iCoiD#ct4a9(F8uh)x>{V)<44V>|Ajh-KR<r<!=uBe`1Sk47x-r%|M~Io#mfWR<ny
+z1$5HbckbPW|4D}O}Jsc*7K=zR#`xMFkpvb;tvJb8pG3zCeg)ILCWSbF-&{^7&<3>aYid+q6(Nr^Rvd
+M!7Bsxj!F%?PKFd@&gIpJb6mv5-UF&r&|H=@I67`Ho~o3qq8U@PLc>;v{Jm3;-xtSGJG_$|+6T<zAc=
+j=JB0@jU&xQCP_>N!UoMqEJC4VIlU%oaywmc&QnB2V$+IK}V+EcmdYRk=8mr<QLS{zWw`o`DqzIw~c4
+&>!?04$H&dnL-HxQNc|exMFe-MCpn@N<T&W(yLikcE86rXi?B{6LU}FV6xjG<ITEhpjxQg9hY6Spmgl
+%U7bH<_5qo-SqHr9_CegwCt=iHe5dsUQ>qmV>e;yGM9s7OohY}Qrkjn{zwaLX+&G>d7stmZAK+J`(Z)
+Z=$Moji$%l9LA-~;j-=-_cW}|s4R8TmFf<eAO-xsP!iE4}Te6?CNnpAevsueJ^CAFf{bEDZ<Rx3G>m|
+E4=sC5$^Wz|RzUBm7jbwX=cvgZd~_9t~mv~0T%{Ic!tb3;V3h$DFk=f@l08JR}Z53%XchU!vi5`O;z`
+jh^^-{a#hbRY1Jae7|v6<PP`>nE=sKY9G@fV;F&(Ww&<N=Jm-y{vnGwoV(mpPQ<up-TAu3+QJ0)08ST
+s;Y!}g}l{&raI9c*EOl0WXH#!cb5HJH_MKXf17D0Hs5~d+*(XW{d|yxGpVsaExj|(#E#4+E7{fbl}Ha
+r_!bL$-<*vIuAEPVMdJug_x-I+_;>IX{__of9pcv^e;uNxYX*C1EN8lnY0ie2^J`4~HKx9$0w0l^5A2
+WlYrg3~U+^Xgn>3o68q<Gr3PeHY49-B}Rm{p4AWE2~iy1<O3~u#^=!ihSi*h$X!vOcDAI+YQSbIZdy=
+AzQ0yd;B>vIs_#odtn?daACwMMiXu5v@Hvn?ljVD^8Z0Wz=~KKsXQ%1aY$T*97p0{5j1v3~2$7*gE76
+kWX0=+ol^QnoAAy{O<-T3bIauQ<I?!{53Udi75i<8hBJndJn~Cg}<vKf<ScK5r>#fRI3VE!s90;MNhp
+h6G5nd~WWgWrUJ`y<e_IPoI9;Mg#E_&O(yIpb`9kP)h>@6aWAK2ml;P_Ev3JmBMig001*3001KZ003}
+la4%nWWo~3|axZXsaA9(DX>MmPWq4y{aCB*JZgVbhdF@(lZ`;Tb{;prKWpFT+NUYUs(?k~=b%OM8#Wf
+dPa<~tUk6Mu{i8Z+-c9(Vp*Z;jU`^Ke6Imumtwm|*CCii7_UZ0s+`VnCtGuEi0<}zvalSxrEwNOMb_a
+yhyJ*s_E@a<%>5p_k9Ruv_&Gx3DLPga*R{ZJO1bx*uD&ne88w2>^8N&ul$)v2I-%cPkXtSM>6@^rmV8
+`eCVO{VTBUSxI7+-c3ep+X`BH$f$7nszdoWF?i7ymm7ET#NiCvnGZG$@f$hd@&>b`676JX`a6oj9r_@
+S9?*EWsyynn!yHW!x<_2s07VaO3P+Pd0R<x_JDBl7&nREJ4JeSL3#@-9Qj%RS;3O5u9~7`aTH%h<Ovx
+${RxS#?iRDf)BEW^lW6MI@D{YhUQ)?C2OTd~q$rBku%Pn-VzzGJbXu0gDw>FvtD*|lN!U3tCa$w3DY(
+)vmE0}~Xu#+T9)dUIMx?A{72|4Yy(ziidqN(ONHZ&5o7qV3pkgciy7z5UvP&Q~!^387_y^4mEpg`R%5
+apXvaFR%Q&6DsOf4!f8qK;_U^RS2W_#~FcEcHD%f3&|fse>rCO~Bs<ryOiypn?&ZW%-b2eNIZ2qlk!r
+^lq;5Vd2H&4{eYHDe9D7SdAj%TfE1$O=tBc}_M|D(&R8l*PJadVS6|AZo!2m8PATl9ii|S#N@F$k_{&
+bJ~q+!;R?_mc6N6IO7j$<g6RAj^vI`fIMu0-+s8*AaznmO{iP$x8UrVW_37+qc9mo!TIty5%_(SM(+S
+K(X%lu!KeNbG&Z_XqdgDAn&BDN?thUAfFrAz+SR$Y3Ht~*R`4#YV|bduRHJrhi>HCYqCl*_Ya&F|MA2
+(NG#<nxx&Q<{mnBsU{fE5W!)lIZWCAROvl&~{>>7t^@V2s$%F{MZ*Wo6zC>XdB_#4bnMKan-mg`mBu|
+R0eh@b^bB@<5#B9(&3Ovq(7ILCeFx7}^_k-SAX^gt4G27|m-NSYdm@}PvFO=R03$_Hiy_N}}f{1~>YV
+!KlvlenE4pdkQ}2y+30+5jX56VbL*XbBhu09`YIN0jUaT#HyGYE^)F;YI5fm4P}9R2OilW3=V^NWwuo
+@*8w}9VMF5riDlj$>~Mp7Sao{kCa)i_ngj1&C7j2T<@nviRvqO(<+l+Nkzpq1E<8pJGGni<0;Eseaky
+D{m4`+Kzo!_po3zLl-w3%0{?3N3ei~N5x)ma>WgT#)CH#F;Y5a_CZq0dQ+dH<!?MoUCf{eZ@X5Z%$s`
+07W6x1oF;iz)yd+zu1j|~1CM%1oP;uuJf??EOUWH@}@KazPkle)WFpEz6hXIj<HVxxBZb(q2(_;%F5|
+PJ5uY-c2tvI;gVu~63m#D{<+pvl50F^Z>(<Dt%@o9R$BzG`yA5BLTa!yYB{AG|uAXq_At8G+C!8xQX3
+}mUfNmCCYX*$D9q@d6^(<G+{kjgl!mW7JcwgV3-W@NKL$6ydxOaNTP_V~-WrnS5}(4Mh+1r#@%%hRjL
+a56<8#(7aCn-n0JmfEUugcH$B+kZOP*Egl1GV8n32rG6c0+cyVS8G|VHJ<=6q2z6$cJb&={E1EJ@Lko
+Ez+05+w>R}Gn(bILWD|dm@PR*Qh=RB57^6jQMVo5u1l#;dTDUc#c^-EZr$b|ymE|Tyrv#g5-?Ym|7YD
+9<lrQjcPZJ!ms`Iu)FHd^I*7YG^?#zMr(YP{)T(c51W&H^70*yPwjNdBW7fBI~a(P(TxF6l)oCOYf%o
+{>yMSqB+TY>Be^u!m2rSs@>-0f4+h9`~4VxVY#Miygni3TueFnY{dFnT=+(GYSLi9YZs`A1#w7zSJcr
+n{Ac`YXjG5>#JVDWRQXN9rzLLTz-<wI`J?#3ZC3@SHu#fFYe4!D+Nl=#r#Yy7V&`1qpXhR?G>#sf%2a
+9lgQ*u3QJwTTVeN-6CwD#l$3A)v!diYb_L$qwHE`fJ`y?lc`GKK^La*7iv@ew_n*hZ8f3>Ur>9mD$G@
+}L67-4)&b)>GF5{v40OSO^(15matkuDgQBs{AlC{k7$0EYpKBQRRr-UB^15RctoBJ(7jtZFbHj31=ly
+ohEhC@HJ0$vF$GEK!>VK!^9W!6RJn-<p!v7-z#rgd0>$lGcUYkJBuAy$W;tYjr!eYS4xI8>?q)~Lb3U
+?<^4*`%oKzgRT%fohgyaf&Vdk_xV`|%hBDD@iXL#dm=Zu}hDab`?tbTv|d)h*9$r#&-oP{HNST>V5lo
+~J<d*yGgDo^Wm9TI2*;G$sVpg;=$ze$Nz~oK{q2Sg#+w3QP2gPKKEmZ?y0WseUry8*$IVP03c&Z4;jk
+i62kWj*RE=(pzBJ8RH3ATs@@z*z5l*5s|OV^E9z{qp^rSe85}|zdPQBJcafggpe&%Fjw5)xs~@&xZ*v
+)jtX+;xV@jwNQ`m2v_l&F?y)^6?U0G_`)L&VEO6_cb{J4fn3-+|cCx8%ZBv~Y`j=U@(X|(=58qOe$8P
+yMyV`2u{C6*mA|B3kuZ_dW18CCNr87H@n<m__W7=;#vdh;R?X1JQyO)j@b`Q{hV<%QX*&+AUx-Q2tFO
+&o?w?aMWYqkDB=jhrcdfPos6eTrE@iy&GTG+PpU7Omw&<l0kbG?9mWb3tozsGLT<uW+&s&BfPCv_Ptg
+8s2bZhGimZc~C<Y2v`k?7f@?V}Bj@pg#n+a{ul3Z~wpE`VU=i1>ixUVPMN;zaK)C;`MWr;0K@>{_5{O
+<T3fWw@!)uFtgxhQzY0hkE6vOz9xVC(^GQs=V#9kE))!pcvQbT(ccb6@>T;B6*dwsHcV8UhONI|BM*f
+NnHWunzw}1?>?}c5co792|MN0Foj;$tq<3<05+tH$KL0FC&Uqg2^`=&AsjZn8bjxe7ZieLtdXRRHf@f
+u$d;4QjViN34%>}XtW*>?HfCC5UlT3%cR)0d?<9C|@8Rv-=-dXNg*+49yqwnjMKunVr6o$G>UI8h8!n
+U}9Jdy*MVpGs{=^_SBgN-8ODj`2$FL?_nfDG@=iLH4fHr%a{T^Cx53cB9gT>%wPMfb>ICiV^L2+n|hH
+bfMoN)J!q;Et>k5EDL;1<>U1PHO73l(k#SdQoE{MejX;JSxy~68vs&ZthW>)yjI}YGrK+daucrsSams
+AcyE`s_5{HnKl6O2CcV-H?RYc??rxc!^FDQp#@wT<T@koMax#Jhnf(b7>A#Eg2dwckxiwRz~RQU42Pe
+%<Acg)+AE2^!||>~Uy>wAdSrS3Q*ZZ~_voFq6Q)B3wG#lL*pPMKPC7l3yk?T0C}L{q!|G>Zi4AaXfMp
+u`H0~uXAmRwq=az|RdVp{jFJFb_tpT-9Bbr0A>Bwkg%Lj6IA0_%zt;Rhw>fmkwbsnZHryVq%9zxTiJJ
+lVvn0TG{?DSWvX!!-k`UyOCuI;3ef{oe^&<@-l6D_on#*F$B-+q`cq(Rtkz;bmXdms0Us$zhlirKt8V
+EEl0;O^rA$9*XdSpHipF^^v}vea~ztC2mc8Ckc=N#SZK%Y<=A?)SgOKJp##{^Ek?N$OwES0p}}pAc;A
+DRhc>51to@Lk7<^)_6%Z!lDL3p#dCq{e{Q1d~KoNnz|3|Qj2dp*&R6E8b5((btVIa{b;^5-LP+=N`ok
+V@P9AHV{yIjYpsJTS{6C5yut+IP<Ct10c*EquB$D!QFGzg_{M=FVxj){3L0SC3x}(T|3C(L1@$z3yxE
+oFj@0jX@fmB*SDl(1!1@1NFsP}Sv_!rKFCM)ovGeaOP#^C3+-nox2OqW7()PfEQ}3h6zW`860|XQR00
+0O897^_9L~CIrQY!!e_LcwuAOHXWaA|NaUv_0~WN&gWaCvZHa&u{JXD?`FY;a|Ab1ras?S1`s+c=Wo@
+BS+=%<B<p%W~}O?3+_8&pC;^JMYrzT;kr@cZ!#$B*<n=ks6YUtxmFk`_>0ONlLc+dgkWdonD?J5kR3(
+C{z^+Rp1kGEwiO8tHE-;lP;D;S&Qp>kqu;Cr*$eT{jik!TeUV1>-93tuXc9kWw8(gp`OO^EKRQBSUsK
+=rPM{c>e;GJGyN>w5%7s8RhCrOef}}elDd|;`X#GrvXpTtujE}^Ci#_&r`JhYad9b^Su&Ngc(RU{a{1
+@}PPDVL^JM3VxXOx2lIan`qnVtGX|c*{sGXE$vgW?!-Lf2tcK}hAXPI2U*co)1*D)9JNC!VJ>$J#|Z0
+uFO5F_!n$R#)0HEqux(=-zMCq52Cf)fP6k2C;L7Xk*5=29ej6e3HjS`>2{f~+d&p&IN^yYuU`QbSkGD
+rmPvx|TUMsjsD&7v*9&<OT|9AaY6I?4Q9v!MweeFqhaclgSK5Wg65n%b>gBRxFZyZJR2bprb4+ZU+i8
+3AO6!HQ-+tHxi0VS+7d?A3@W^=rQRE2_jE}-N#A<N8>=W;EDpqT&<SWube5YU(dzmrJl;mORBS!({!H
+7Szn~U(bvT)n~4b$cDY`{93WVWK0&FklUgjxVz!zhC37?M&q=nDs;jfRWU<VoOH!ZT{#ul?Fv*tJNfk
+u{>`KN}T|$3h??@yQF`WrH??pm9L4Fwbl1Z;Gded3&!h(DPeFHu)4gyg2JEw&3!ogmppOG@Tn5219uK
+Nz0-r>_8l+4m;Qe#^h<PkT8LE^&A?WCB73@Dz$%+?9eek5pIy{Cu0Xi&*I=7A+sWce^l7L!>b>LH>Q*
+5juaeQ^{;51>%rtiVyD%O>p(pFV<kb5X#UN&yUz%_^~20b9Z36U3QF<~1@j44N5hvcl4N!JO~FA$Ck_
+xv2U?V_s1V6F6s;)s@JT1#!y^3)kW{%`yi9b_z9R`5F3El;))XzeyInXE;NjSn+LIU&jksC$pqZfc$#
+S_k>HnFaX&j150WAspt%iHqkv_Ej-e9bP1qo;0|maF@SYC@h2&GCMHFZiSrWplKy<3WR;8GvP2GHNQ2
+pGu?&Gt9C}fC<vbYo5DreV{+~d?eA_zvJV(O^Rz~!PqKBCFv;cMmI#Zjz6{R5()u1ucPpI^LQQjs%QZ
+)dhdSc=be}w=8Ww3}NJI#5KXT=nhmxXD|kjSu#%mb(2<KvMC>D#WzBV_elNEoCzTP*8!7&$|og1{)5i
+D6ZNwygmTWcC{=mjb0YGVe^YvS~S!8FW8XOA30><N#5Fs>}|;QjD03`063zLCFThy9=2528P8_k4Qg4
+;D~h?5KZ35Jn$<dvj*um%}HMX^|N@kLe`Dzay>$(iIl~GOH_m!r9Ec`A_s>slQ0JXl*0<3S&86#0O~Y
+A69rj<^k57^;B#86syG8yEt4$lut*+dALNeqVxbO`gL1x<(>hzLdNYC6n9^=it6Hs^K^`SSW9Go?Yk;
+IXv!b{`^{!Tc=z%#Vle&irytDa0;L?BxEloL3%c}O6#S~Q%Sab$u8|Xz%ZFR1t79xWMx({h42$C{qKp
+JyhFc5;n;bCxj$x9$FYJPMCj{xHra+<6vNlJIe^uQLC9-_jf&tO5a6biPZoT;tp3rWmBo>Dij=d9J?A
+0jZ570efyD9|%C98SSRu7;NlB9K`#5U&cc3(a=1x<F|S3T=8*qSe9{4KJ!ZnPg}hxuOl`Y?H)Vu4Cd0
+_#5-o%CbXVff%UmFZBf2KLoxVjl`i}ru#fT_61pc)mw3;wgf_1dR41RjWu8xdh-z0g9JIGszb-vXmo#
+?&%!r~iE6+V7+KUc>0$(9+qKbB5VT-5JBcnC(?vy=Ft13!oHyjl(v>1O(G4-;$swrTElsfM{}&|>6eU
+Eg|6_7wvUayiN`~-qZV3_FiBfHj5P41&-JKU2@e&RC1ow+Hh`u&Rd1o^%7Qn73Xh38ksDL*~`Z)^|EM
+PI^3K}*3wy=4aprJK$1dn7xq4VN`=SROm7!k$JnFTk=1IL`1(+(i!$p)&x!e##L0Ie9jlJ|gj>!)+C$
+sa~8f*pb}Nr6LXd7j-(CAkg4RxM&>LT?^`5dv!wChCg=_#2dfZ8Q7g^!+Vp!Eq>|#f~StHjt)Uc>OcT
+K(IjLV$KAEx?uPJk^=%`<%W5UvK|<73}vtnrN6uil1gT<XokE=8S&<X%Yf0@`(z3cQ7(f?zme-(5Hwv
+acMX8|8{7Yn?&c4Y(tlf}(;Fj&K}-V8NM2^>=7CK;Y)iG-p!D3OP>wSc0*mBEqRRv~w;=Ni5W@MDtm=
+K1b~Sv(#e91$X?I$ZLjm1S`8-Rfwf4YW!E#38X}?mMFG2djpm2&&5Gn_clI$9zpOCM<$DS@p^G={U0V
+6}VRFY4%R|SXwTmZ;dO2qGjG{U(BIkk^tru`-MU4aym`>;bv7b&~PXvn~>03FfJGD-Xhl@;Hs#=53~u
+la%cs7qj1AZljnp+`zrfeIl^KmyyO5wxWFyS$7HD8oLCFL{p&Sl5g6*M#>Pj$hzP=FmYc9WoK?T#91y
+36Ouz&Wl?R5=u?z779Q&dATv{S?12zXuSbaK%C1<%gE|65iQkpnj#61QZ2klU{!1>D0vk%NWuUuMQmS
+05}Ct{Pc5ga6>+&=)$2?-3u%UP#|5K@J@eGvJyT&;8}y6(Pm}Xr%?+wbVAO=|85lf(-G6uX?$4|W>vW
+RB^cx2n@-<Ds1e-02&)U+Nuj&<n0)-7Ka<gY}v5X5`$RjPaf@Ao8B0%w-j6hL1u944)*+(nyj`atu78
+6-^TRXt43n;<XUsXk~|D;T-BG)Dk)!uUu+oMMf|4gGDi0PyR^`N~xF96Wtkr1b+qoZfy#qsF$6uzGv9
+tB$MvKz-G#dzF%fex7w{y9AAfn*-{PEXCFqi6hxDjm}!D0OO`=!O@by<w&saI)V~78nNf<TF$=Uy(h`
+$~DdotBF%EbI=z#m7!iwq)%e>AlVr}F#1Gf0A^1f1Kk$DpDD0|B3hi3R~70-U;`zX9Ge3hL8XdX`<6i
+P6T2l*pn&*SvJ9ZDP+x#8hHh|_?95+%dg2=aftX$wDfzUGj~xiql%xzg=zDEp_@I5{XPJ$TY)NE@Wpt
+`TH2Jqxf?7_weG<?QLy-(tOW?PVHj5Me!!hWpo2uEyR2u*qWnG~a8X7>3Q;{qw)}Sv@z5t+?3Ng(QfU
+9K>@|WovN@;dEq&5tNhHxM1F3Q_c-Hf6}jZK~PVp3#ay}W@5B;y9!jxUUl&N3@1PKQzLfUto5w`eHA+
+|^i@s=E6p?g%R4^Fg%)k*F>Ctg9z&ak)Ji7-TQo4txr;C43H8o|R=$hQaF`HZtkVGPuLpQX9eA8Yo4o
+de%O`Iqk<Zr5wALOvtwd=}Wzpe*(|RfKlfs8fWOT2BQghn{B4#bCJ$yn#qhn^QkmTigrfTby4Dx0$^G
+x&>`xMA_v2bHwTSA5HzCt2~Q?)Hw8)%PdvevmYP(^5BVBhj3G3OKx-V5&VnDPg%l{)MFZr1YK6*m3P4
+kFEEEK)4LY*ns+q1(F{tu!>icT2zfXO2ngX3l&@iNvL(>3M$e|csMD2YJ@d_=WkO1_tua0{7L7%e=@)
+Lr+=&U*cJLRTTLaa$^F@#<e%K!VFscHjYd0EzBssTR`vu<A(^a&c&2vM_la2OUhomUlk%wcv)Ie7iU+
+n?W`y*&MJ=E_}`6Hl$4t;==GO9xi1<s$UeZD%9>dE#+vH>dX5Y6MdV5A6kMQhfy70*KGi%@T~i^m>C&
+MVf~jPyQL%4m`hI1P`FF>MHmea6dpm?r9_39S_D6aa$%!Ufmxjf<!XSF0fd60|Q68(w2<WaV3<kQMG7
+qHh-INEa$<;N%)uH7ySJ#`Zx)ER6uw^En<)mtMmo2#z^ysdmaHMpc=3qR%2Y9D%%bkHubEc1aIn5{3+
+pSc)>ecM;Qi0go&FKiw=O$nIaImDzGl^99f39T5vD%B0(?G7x*>Eid)q7Lz=JlynXBN`_^segi_AR-7
+|Fh8KZw%_i_=nXwSZf+CJwk5H3lHI?E^H7E2C4f${g)-4@%TI5Ms1CaW|fH=y0#1%1yH^8g!l2KEHvR
+e>_<^Lj;3qy^%-Q|!~QWs_`NBbL()0v#;3qmUwJ%`BbPxbK1W(G0-hAcWuIxrR+w3YrxSZ#v_2-6Pl`
+hT)WJbh$FCt~IOi@jE^wzljo56(0&f8DL3JIpRZzb8?=LA)u^wv*xk7-p#&(K4CMhfBr977C)D0xL=Y
+ZmKy59AIf62ywv`46%w#4X){LF$bjQ#5EWODPAMQ|nyqG1D5D+G(BcU9va5Vruav(5RvcO?_&>!Zz!2
+DqG_f;%cJ~00fP|m*kgD`5hqXP$pbtc$mUp$nh={`5I~8N(;^ZAAlcSkD|1C0kr_F5u9OT0>7MnwE5G
+xe#)pder`5*r0FQ@O%#ImUJp`h&njA@Ri-We=VFhQ@bYcauK8EgnUcQDXbWtJ?hDuEG|dXo&&VgeSzp
+7@}M750WbJlOp?mprc_hDgLH)^S}Hu$Rt9)Trb1yC+!Jxf>SRWt%R?hkY>^3@-d&3Pd$($4F2sMiBQL
+@V{TgK|!P68Fx2EqXOQ`5?Y8jqwM~JhcHJad3!17EU6u9Mg@*&VPMD5caV-c#@`@WBXFdvaNHxN=v{1
+ROQjS*q#S05Kng=Zoi|033P^K<yMUq_KvKmxj&Q55gK_AK9<wGpGLS#<ndMM^PHc(=mQlGtaVr)vziR
+IXe)ctcyUm<ZUJY(%PN7;j8a=1PtPtI$DdW1EetuEI@bLl6nH07!ctnKoaf7FNw6^PSo~uV`F66n;ax
+=+OR4>5e%tn#cJw=&brFoLY2ss9(+#C#w?jq(p-+?c7vFJm)<YCTxg)$03jZ9yxauRasuPE+Nkj=?;O
+&dgmpgI5irIPbi#=u~?s_0A=$);k_@HikBKc4^eMv&WqbzMS{f(0wR<dz;#e`yUC;GCSl1opGUpkE0v
+(UMo12~A(#pyV}%ujPD706T7S9Ek~7BSJyfW3zr-Hu6|`yjW|^iB8+T2?aH7eGE=YtX4J9)F26p3G}2
+ID$<ty%nXIRyUJ-mag*d2OIXhsKQSpiHw@1NQL;DD=qfih@6yE(!>0V$Kh$&7`W8=5H1=SVsKaqSj7{
+|Bi8b7YF%ujUI!nxf;neoTg$E0K@uAS31?TkMxC1?tqqPpqfGW?kPP-j-+P`B3w;E?(tcw+gQsNPmPx
+`vBG)BCjDw8B(AC3-!1cZx9dVp0dstIbA1p0%9Y&`Vt?0P=@4%hty9rv3JjH;ZXeW8PO@RUp(PfkDrW
+HWJ`o**TU57HBHd;m{#)OQ)rmo+KKsH8<G!e9axe2@l>Z8lhaIr&90ph`(03pX;x@cbBBRw4ZHJq>El
+*p_Sz31lD`66oM3fQ`1K#SlWnp$~(NFeq=MKI?59x)WLnwQOOp>80oSBqzQ4N{d3X5O<ap)1Szmg?cL
+LW@9uVZsm$8ZRX&A<y_2XE(r78jXQAb4A5G6S4!UUs&iSp1XVPmsU8NgAw0?101Ye20fH`Ew<0{Z-bt
+fMoZV!Nu9R~&Xj|LVaXo1CDTcy*2H-Co$Etyg`p<#ADbQg&Brh`dvn-Zf1H|qcMKq)f6&`9R)t)J*|E
+N(Hb{U|`@N1=GL!3uVz{-@3)$Tfcl_pTRs?#ZNwBuENg=T=9(e8AnLKxySkL`i57foP*D^o!M_|36Yt
+9(}2%z|E}wVfca>g@V7_f9fdR7ncmCnud?pRrWl;e21>8feDX5dIYH@v_KKbxRd4vC-=Rj8yabrm<q!
+aV=+OkB=Rr|HD^j@6Zu>e)bB?MI}(D1?=EdmIa4DIZ+ARA1EFC&C}pUp-l^Q8g2sPSw)gM0$YV`8Z9z
+_`Sfm{211%kZKFLE*-nxH`cx_@26I&qqNm}U*aHBa^Ae!rYu%H|kI@R+(YzB0Yoqep1F8>f4K;0B(uW
++Ba7~W5m9>TR=9wzL;4=y|4^uZPgY=Nm@Rygz=cg}D0HEu()e3r%tc{YUy_;tMX%0|3Gs+OClSy^CQE
+}eRHXUN4I^;+<m@StFZ)Z{SggN_E&E|(k&$63p_URLUyZQ9#@aX8MsX|$+5#TKwvZuJaLZGnG_>;4V8
+jt^sCEN{^9r}fbTnb%7+0nDc*)t8Ic#yI}@r&{owN>UxBHq84J{3$Lf#E<WMu4?V7!Zqi&s966=?3W1
+k$*MTdKf8yRvT$)kb`Lh5|iLk0b3F}sEW=9TM2DJsLqMm&bX&?q$_h0!lQESSS!RGatf;bZB-!difbZ
+2JI|<-2ei9i#xEpTu551_7a)_4PB_7k&WRReXCeueyfRe6-}<l}lwNpw2}Cq8DnKI@o`TC*DUWDdbQD
+h$i3#1ES>I|$>ENe0#f_Yy?xW}AgQHmX?b&e@F-5aYed-}Svd`%8eKON<6p@vfb3XlD@UBJ4e|JJUdP
+lBuLxmjP>I9F)q`K{Nc1&ffBP~HaE^BprrhDZyzsK!zRG*KEPkKFXgnFwagk@QLPG_nYPKqOn8&vuxB
+umlPfkC}blO=VB>ce^noX`>lk+){DzLlWeoweYErOd4#!rK=9qHK!hq`7ed>IlHy(UJ>#q4FA)Ml{oj
+L~U}hYN9L|BoC05Vgs!+VS9U|V$MO8eNnAI-NEoYRuCrs9p;pf_Z&VS_{c)&2qJGlD?U!kz5V^qB?b6
+(1O*OgKdo(1<>ct*Pj=%{1Vt;lyrzZ9l;?AUT%7|{m04Gce=vGfP0Hr&HMyWMIK>H!qbLhJ?xtu8KD|
+J?ig{MRl+22i4fG%wa+<|1pqIsB0t^t^XL|xv4Cg)ec6*WIF$RXWS*>iT?Db+$@+LnLe|ALR8CezM<i
+UhBLhfMfP>Yp%1H(P;)dGF<?(}_MyobNE^IwMAXWs_}8wHNj9nI@_Qp_-^(^c5LFX%Y^27jDoF$#Tl`
+zod}g;~am-`wMbX*|bcBV5ZP(ZINsUFv_-c)|dU=Pk8xm})9sX_0_2Od-%J>WlG3gvoqY744>x8XF-Q
+GK2yC4cruCGY++p44Z>?oIAy;oMOQY*{0X)c^#%CeB)v^!}LFK7l|(|gmix3-FHXPbFcK<P74?i6(j$
+y<y}bpe2ss*pknYL6=G~??`co`@sC^?!$o`lt=HAY#Rhqqf$wv&Hn9BjR*P>OGqN4j;nTe)w9{^AJKe
+urs-j@P*+Jdp%u~Y&WhbT6!VkU+k<TJ9oxTexuC0o2wN*p$9dc3?Re|`9`a#pyH1swCJg=13sT+^SJ@
+|#o=*~S|v6I%UjU>V9M4M(fDuz56^^S=kuKjA!uvNSojpn14rOH!htLQ$J_YWE<gWPn*5qAHEx>SYOb
+y+hEA5Xe-t@H3K*sg1g8&PIKI|<ke3Dho46Mje?xuLX#VP||Ie)Le<QHosR%NgT1ZPo7bfU1l|1&BkT
+5IcOR>Tk$p^e0AHPCgktv=ptZQraNXgmW&tu?l|vvoYzLK6~ONhEKgM>em}`irkO!8Y?>P`J14@tF!M
+<e|d8r|Mkb$=V$TDA5Y(Z=-&%e-hnAJI^14yle*YcvNf%oLU@pemtBdV-4SB=vD3t!Hr_lxkcPj3cE9
+JyHbfTw-@~W>sk3ss*7cU^T?@Ni-I>ArSz5E~KN(a0ZgcYgB&9p@xtqGM)m5i*)Y}<*kBnBAyj#)}=5
+MX(INuLdHGaQVhU^2DEjGh^*@nLmKPJ>iE4DphL(oD8@K=KJRbw2vAx_Q7?hM!WaM<4My*(LfIPt5>!
+SG%6oqIBkc3tQnl{RxjYvs+1@c{K)9i4taJK%1S^-a`U{N{XQ@Cc5B$SL~4Ejod{g>eDC&MDPW-!n$8
+a=fLeTutjv=MbLyddc1#{GU((?Uo#K(OO0t<qpdTK+#$GNN^=nz&~vki2-6V0Fjk|2;KAPLml8RwwB?
++X<e6Zx!BnzJ6mK-m5=v_)<lGEhAw6Z;onp|+H8`=o;9mo)vblio-D5HoF5>eVP<ig>T$m_x8CzTH7M
+A{CRdH^=^jTBIqb?T?T*^v*kD9^Q+GsB)P#up+u$JRYj?|NOvlN%yCv%)=oo5C05uPQQM92+3V=IAiS
+69s;;k#VF)6=gLSR)BJGA#`n2A%Nh^K%~j^iJ}QfgrIcbd!=EuGoz)F~a3)crWTaIf-F;p3aN8nee%h
+U(UPt*6meKKLhPLK50M-`c3rMn-UaplN}E3`EKapr6b>B~wrwBSK&KZWPlv`r`Pz>IAie5@g&Nr!mmc
+*)c%Hf)hXDD9!yWhrGCDzpsfS(AT=DG_6wNMV9CSu0?%Y2nxfmJfvEO?}h{puMFZCkjHb2IBw*5@=+g
+--=wV2m<H<h%P<&X2$6sp1OS=Dh02+Epu}o7!o`xkMST6$iQmT)!Qa#?_ux*(LDy_(`qYGgD)R8^C~_
+KUx95kOba`HcW(2+kpc?cIP;+077f+>C8%n$_hn9REc)nU@(m$JQR_urbd6Z>9t}%?;<jr!^Oc-#Q2F
+4gBR}|$SQ_95Sz*%TZf`@dyy755=GplGmVq-jw;VTO184G=Ey~@>h@2q8WynXMuo}Exaa+=Qzp~Cx*6
+LDS2`6#%q>t!`OIJkmdRuf>!#es2`JKt{8n>08vzmE@+6M@fQO<u|41L(rK4xcn;&;*Zmof+CZj^+U@
+gK{Q89XcKD*Eq?hP6Cn#&&b=6c)_Wob+R<S(a8b{8Vbyt)D%zJu^354f{mU!7Z>5IK?RC}&~O^QPzrt
+b_byM|sa40F$EPR6Dq)u1ND<&91bBLKn+psyiA>Um0|XCUInF%=ZH-juz5@_H?07{a2WCip(c8yVe0q
+vKZVbAxGX!ht5v<|)Q`PeJ%=(yCtX2$mncw|WukwF?;3DUo;oQj?rp10>S9)Way7?IP{y3L;FCR!!b;
+Zw4lCSY{h#VU?f+whqWbCFw-4LUmovQ5>MaXQ~SPTPKxnS5en|^>HK{><wtJgnqrr^z>WCuX-Jcx$kG
+m-qJ4_|<k-gVal{Pm{+#SVngw;evlW4x%&+GJY>e+>Wf?wB8*kdoBtq&@<4=VSCdXy(TS44VV<8BDOF
+Sym}nx8p{Tre!$31lY^Tq{gDvL8=8muuocY`WtLq?fG<*3%r30u4En7OsX{^O6&wi<!MzF)9?)D#^QF
+SQo;GI9b5+`MMEW6H^qyIbfCgMh6GY%f>}1WN?zyl^zLm@6NsNxb3FZ~$<wTyVy!q=)h-c#0{Z6c`*X
+a9gnqn#{lky=>j-e}1bbRuo%1O%ivw!aSoFLGNE~pbcKJnLY%IFix#;ejhU9h3oft{E4P)y?PxYPU_)
+$}0A9RLPof5;S>#x**zjNOJ^+Iv9KU2H}CLpi6g17q0%%khn)Rh(+iKj5nU>R(WG_(7wFi_E8<s%wJ!
+DB<gJbu0^lf@z_tHy2ZAopexgt*Qi)eD6a%{W<xZ$F&Mnap8TU#Cz5%z^a)iLGm6q~-(wVQMP_D)oKe
+ltQ(S4@ykE+P6y(lUUz5Tb;@cz0wwAqAqH;YuLSPo<d0MRZL12nJZA0G?^Axn9)RP3j=_G26(k#PFKp
+&of^ewS(fQc+FtCC+3pA{DfL~CfF5W(9RUYi0g8_EN}N<*yvEo-LrzjTDnKa&<=ivI9;&LsOV8=5GY+
+KjS#}^kNdF#I-=WPH9>(e(#7h<NwvZrQ^R!w}o=bu5&J@#sxXT5GS4l+6i17zre`c0WGd2x`KW5Y9wN
+4&d6zG;ts&vZK$V~>2Adac*-Qyhrc4`rFq_PUaBC8nhRLkiN0zv|dbj=%Ygm<)%Xr?2n74e+g6Hs(+J
+Fg~y{zE_j+h_p;Y9&^~01SwsW909cxVn#?V3u)_yWNg3w~OMdjR~p-XWt1xiE|zM26x*)BYaLQWVl<=
+QRk~+KPikyN8U|U7(OkbL|@wTT+l^q?r79?p3I8kS-**2qDX}Fxh;GTvPKaKTql~64Jv3(GsH8x)T?s
+n;G?05p`x0wKdf&fxXe_C`pCmM&OM^c!Do>JzBx;_3-#&&XaJK#dsmmx6y=C*?U+>Rwj;v&YO#9Lx36
+!d)$a?iTbIjArJ)977MK`Y{S+;S%gcd-zRO4st28dcKo(F~sVh@Wm%g}HIgmaj9d-+w(5)7y`Cmwy7A
+5eDMOs6L(Q_T-@8M-q9qk@gb5UuQvktkb`sVs+`L|UHyMAdS|K002E-zbN!reKpF;gS#7Lm<nPS`7|@
+2)UgLoZTdj?$n3n><dDsJ=;yQx>OQfcmu#7>j7MId&JRJGb$BJ1JB&;$cG_t$C?0(hPfH4`4*9ztl$C
+-ryA=sh&6|BiCGjfIO$2iP|Dx47_+`o1)L%7*dt@k&4y)??$WAp;h^tX%+orXvN)ZbX7f3R}mOP0{I`
+b@4kt1OiJhi)Geq>PBFrxUEfpm8S0>}XaAXN2GdJ8I>JEl-V8a5RSnYu0I3tURtpNA#A|d)=W+)`O?#
+Fa_O$N&s|M-^*o?hjVQ(L^S^B~gg^}MRRH3)MU2)KZi952@QATd6y(jkXukGHXV@EY8S9y%dv@nm2u*
+*N~J=^_Pze9KwHJ<Gs?e8BRdXE4QsK*t(%3-ne4h-5(DZiKT_)mS&+k^IF(8j%8`0}q87tX6>nkbBIi
+)R<Mh1cLN+Ff@w!1zMdq_^(5jT(c3HZ*%jSRKFc&%?tDC)iM(bYSQ`-edy?NToL7-&1m%oV{4{nZ~S;
+>TLssr#k4)7#+Ir<-sZMJZ}Bt?_Y!#pyQLo4Ie>!4T~(~`vmYHn++t&%$*gy|Kv+(8~#jeF(8(x%QdT
+v&};7>E-7~f!5u5o0d9ks+%0j8X+{>$6Gfj*p%(VY9W?`O-yQTwTR8hd(j*;i%Z|2Xqb*5RJz1&JL@4
+g4qCQ@7FXf?o$I_hTq3#tcg{`i2FRc*EMzK4#q|z^0G5ZUUD0~!3$n6o;_C#q$?VliTfY8;L_m{Bv*L
+05^PYG(SH=yZBaty&fqA$E$lMSh1%8#M8&)EB6)AeYJj=G8{pNB$7%U9&8aBebG8z6^D45-hz_Zv9l6
+{~n|tzqqnkkZwnXgvIv3!G<u!4SvYjA0eQH+DE{_|1q}?rmd0tRlB>Y3Vnka6&oX+r?F*omNvfI=11u
+YPP{t<dVFgBk`<tl_1^s)<!)fle13-XB4p!pKEk54Eku(E%@7_vG5aMr>h0+Pe#u)x+W5<!`N+Xow_c
+>Z<F^>L&jGX@Hej(_8%)vJ`cXAM&Hzzqi<BfcGZqO>ja>ixx_~bA7a2i&%$wQ7CIxkd5@u~LOvo99)g
+x;50MCuBEIhh1DWvmGcUgc`t_MyU+fpUD!yq=JPt3l6O`Oj$3_p`;|@-^Q|V6MGy>iF+YNc6R{I9~tH
+ym(9&MpQT6s23`({nOQaVD$-76$ejT*tZr`H^OQ-Zfyq;CXkhWxr+b}T8%1bA5F@4eVzPO*As5$yzpA
+E$ZPZm);a+59oFv0JciBdec`kM1Ytv-{_-6QLH_4joj?!z1TmTO4(<fsO2aAXqQ(bt@y&+I<u!KfzmN
+?M=vU-s?>o`VsJs54s<xiyJqn3()QxZss)_3j>*&s%g{Aa6PgnF_1{FYeQGVknJUJ==Bd=R&4|yx2#P
+2f5fu-ZOH0YkHGNnxE_rra2Jk#_^|c(KwzFO0duyw%AB>ZOqyoXmLa!;_I8&^lYU*Zy9I&^zzmAsE@>
+(K)yfwH@OFc$b@l`vS#`X)C;M74+h7<-d`;;K*xlWP6a4$3215b0J<AKO@c}Qu)jvjjJs;jew_3(@H*
+Pf=U)bYm`rp5+2G6Cm+w!&Bsk)kmHn1|8c~{hQUHs6@Z)cSFD4g(Dcl&538DDy~Qg3Qd=T}q_!xVX>6
+xH)?4OMfMpi1ekTTh5uq-r`1EyioW?~d~8b$xqpo#4v`meM%3&3!sdB*xYB>r96|HJYj<`N^8R$s8uL
+Nb=-Ldi0^GQr(6o#~t7HqwxAG^zYBkW$TtYIx*$@^b{y{)TA@_t83g_Cpti)fpgRt3XK9Uca(G=t$A6
+pKC<Ac($=-5id+}QZAdpKtV;CA@~PN!x+c%N7?0k7M6ilEySwS=&hmh!OUH|KsOVJi>k%A;^sNR7c8e
+E4<C$HPH}JTF7X+T9s(13aG)CsE_^L;9^P=$+@o^W1?}(H+Ce8JA6j}G1C<mJzwCaV%uKy3Ez-joaCj
+n1gFCV>e=IK-C$q(@4)V&AW|MATHc;WT(;zgMBC;h3{)r%KyUtH}pY{=uuBspw8IBGty-M%#6UU>+B=
+vahz{dH5?(|v7MS5<=w>VwXB^AsuPzR=w;Hs0jsyvCra7ry(;wlS{fjkz7py-llp`btjm;?ppgVTj?L
+3qUK&APiLe`OHi5w^bvKlcJ!=U>Nv4=rCVj8Q>5+@!v#iZZ2CeXzp2f?yK+gy~w^dP(yl&cb8~T-sm=
+st5lcGsxdV?IzASm0sPe^*jMK*PR>h&jGJf!8Y4tQb?Q&C?h2{#)dl2s>yTnm%vPDXP69y~GtJZ?0dQ
+VQq?l8m?*U_%6Wy~BwOb6995=e{dSqauo_k)<JN15!dm(zsf5ksh@4~A&^lOfLr-yV|viE+er%!tq{O
+||!@brkE(HHvv89Z=-BZM6Xi58YGUUZ?E(EZHx9{L9%4B|#%OdTNDQ}XhMx;Zt%3Mh0KS(G;B8zJ7n{
+iWMY@6|mcK{3=dmODP3c)&0W_9(S1`oFfufU-;B>)(~&*=~bmxs*9xxnb7&c&HDNI9?JhSgP!bX1_i;
+r5&i_{lg3A^`h5udh<@olFf_mmmFt!`3Ai$rRm=yyVX1bUH_79gPs;yh$)7i?XODzF!B%tY+73aRr6$
+fMM9wKwV^zQAO(x-3KX}xd8m;gwXG%YXA`jms$c|ZX<TrIU>{bKjr4jD5$+k9Q>dAM8{VJFyKO|(YSK
+NPU-I<tKK*=N<7j4z4(BHH3KXl*9yzXDtQ7u17p;#UPHVi>Rng|{8}zssm(v^Ao}A^{ziMyvQg7x7KG
+v8Iqz|ohCeG`(ug>0L5N@b$Lj--b@m@rqvm!Uro8hR@y*oR5zwLg-#*%j7C<wo3w6??0T;W3a<*kQHs
+<*1nYt9yG+uPw9L6hO_n`Vw2Lu@>>q^I#}ld8SHi<Bt>aGQXC@d0-o-8~-L-vcpx%*eUvY4nvd^^%TP
+4q?KnC(8LAbbZFdC2SJ&sP4_b8#eR}vj6@eADyB<52x3w!FTOo(T*jk>I`{go}^hL9TeaF*B5y7J@oY
+zH*S+n-&GY)sw}Cl@v<zv_Pq2qr(0%Ce`k&|Zs!SX&UzKT8;5+gSF+}pQkz@mI8u34VhC)Bx2w?wv+G
+_-;R9>6SEg6DQ1~NMll0p28w%@Ph~zU28N*_B8h2|sX`P%oQ3eMecf-F7$N#Z=@fE-Q;UJ23+4A2#Xe
+Ua%6#O1o1rM_%f|m-mA1!*YOE;YF9$a1qJ3Ev-VUf_CAOB&0fBdof_~ByrFZ=r^ULpzQO6Yzzc7qV8B
+WO-N;ma4|VjgGcy0JYCU{HM7sv{@egQ)-;(smyjLVuVBPjlUY_Q3&=?BmCe`PcD(e9SM9U=E;zgZt5j
+I*4?L???i^R^3K4g6VR(an@)S9yE2Zsb~#h$3^qy-d<xeeQZ?*BO$DvaSe9zZZmB4hGY2ztk@b%Yk)h
+!2Rv{EMm8Nat01r?Io(>|G&!CO{CUtmx-DaLX5`7{34s+$Z~C%Q4Sv=8Y2J?fHTQYWWl3?@=qndjSup
+{dPhaoI?`L{~E58z}<qX|%J23%G`9;3^<)N({2o4_OtSL&F`izP`8gO1HsB+(T{kf4w5m64v6aS7<6L
+m^=Y)FjwWA~tU2_So3`Bh>1IfY}m?`qkYzR_2v9W=b>4&uJKgP1tJ>rL*9G;hbBq|FP77s=fNYN<<z6
+O2fTYq07tyf#*dKKL#0o88wQ4fW0H%@^f({t9bMlS`dY>1%TIaqxW{TfY<MQP)GI7IETRuhBN4lTXBa
+Q4fK;=Q}FYhYt5R=qJh7Kbwmn+~h$ld1=$uy-Y%tv4?W}Oy}#hllXR~A8>)bw9=s=8?de|brlK8`k&`
+-Skk+KAEoyPlts2-TNr|jX?EQbOent^mD(ar38qH9E@`#1^WRlQ;4Gf3<E32w*}rNt@)sB}L^MRv^w_
+4nHaEAO7Av$%;-oB-HMdodPVvc>mUQYA11Eh>i&dq=n<ACp3uW(Akq$V1FephUb1gV%Qf&dk;jY{czW
++SmQdhm$EHbY=+*-T!_Lj(dT@}7B<NIP8YR(m~k#mXrJp=OdZzGd9jVp-~f$wR0*J}Ci_crXva*f>dS
+G$V00PzE%Bb#iflLd8KEo}0g{{m1;0|XQR000O897^_98;4-PP#ORLL}&m2AOHXWaA|NaUv_0~WN&gW
+aCvZHa&u{JXD@PPb9HQVb1ras<vm?<<2I7-{uNlcQX*$)jpdn_RmG{BY_fN`oz12)yR{Eml|+e<O^YJ
+61SOBo@qfSW20-GAvL=(Oy1ip6mP9lfjYgx<-DqGgS<S`1XvAoDyja)OmaVFy;HxIDN-;{8E0%9}Ro$
+@Yg2D6WeUmN={^xYJ%geh&zO#NvfRFs2dtR=%eECDe>$ItA`O7Z*Lsd3uUUDdmFH~E*U7eSWB&Rtda!
+tiw_q&28?0tDm*mwD=NdO!C`H+j|;zBg_9KiWRf=%&z!bYRfjNP&bN)xs`HeAFP^E+NjlBfa{<3|+D*
+}AIPoaH5p;yAvzxL6gb5N!TaS_}TO<ka8u=Ke41wcyQ!deH25y2XJBH%I_aGb5P!TohF!=5uIjI)EC3
+*##A3d<}(pnK$!!BzUn-*ls*wE~4Gd1d+wEMSKu;WHfD7kPTy}cVny@n{D0kCU5w*Z7w&E*1Xx*Ws7^
+7&zzc~NgJ-J_SZ8j3A<9lUZwS&2y_I<#gggutYy2|Cs|=I7<_E%{R*1n8QWpG7T|<672DO-A<sD5!kZ
+k}!nQmu1*_I9U9C8vY$`cs_gvP_Se7>FL{fakQo&MIfHbjau_$;MDdh2D5i5}8Q3B*;#y=sL0s+DkP0
+MsVTPzaBo7KpumNreDFZT^MYK^{DU*=`H<=-q804g|V6XL*RK`f}hFZh<1%?Ow|H{lm*WWWEEZlSjm)
+en3?0{9)TfvbP7>MSbvTM@T~84d_c2ow<o=;4kAN1oP$n7wAhH^a87`MhTRmA5dj?|*geEIkh5j^0ZK
+IwL=%Fd_|3(e1=23UsE2_RDbleZ=;HE9wkDk|iVpb(NeAC`qOOvugPOdexXS_!@}T^p8v=(O~@h-~ay
+2_~y;q@xW*bCl#o$CIWe1m$x<F)y7=HhjeGO9z2O>cJ&Q=T9*+A&P5`Qp9dXF3CRE@S;=_p70UM@*L@
+{J;@hyVd_;V5ic}p`u@Wi(k(V$@#3>lvz<#@nV$hGkG{q$9zA$Hk*+=Babcn1SCOFpcXMEFseLEh`ob
+iF)V;xz=Ez|v%5I1f)_MeIXZ(HQ`A0hr)@3{ft^&esWm==P2Ef51fqgPiTZpVpD(iJ0`CUzgL7|x-I*
+>%vqlCAS{UlenYsy!Ea0ircoFSb8cB`m#D(1?+qC^WMtI8yQ_NIT4Ccd3(QDPTu%Ko0Bs6zZsDbX#R<
+F=5N9D&&i%+Ti$3$OJ$dX6^e7?1Kqe2~%48snA=Eqqf5XYI2YmFC>lDtClqDEzxDYQG~hgkSO&|@kK6
+mNPdJBjM<Fr*55zosNmUS4aOE|by*1(ybP*<y4dI9UN300Iw^Gu3tieUabN9=j4ff!gZI2X@T^6QD;_
+MTX~BLvHuqIY)yaYo4No&%I+q-^+NvrKyl$WYXx3Vu)YvV|Nr%seZ-0LOhd(9kXZi$QZ_{10+l@Z%cS
+r{`GMJjW10OC|IsgX1KUVc)3X7Kwg4PR_uSQBEhcL{E4Y!I2(B6RWJ6_~lsGbqG6(DMTNuf>sB}+4HV
+x-a@#-1xSFfvXp{SJjTCp$};%u8XRM@62B`Hnz|*r;(dIX=p=0^-fKM%0031PG{R9AqMuji48Exw6P!
+M0Tt3MUekre|;+%{fmVy2t2Cy<s9|0h=xOdtsh@sd+(+<$=l@J%zqCBY&`2JjIb~c7e<6J_TB?UU;<a
+7kxaNP((N)!83-Tfwx}knjf{W%8k?)SzmkM{6TypweJv;C5NZs+aabDaYlQuLo3MAYt}gP|uiVFwNSC
+~bCi)v{1)M5%3EJz3rl_93|6W)7-GV*d^O7x6fpu?jF<OjbOAT4}$9!J$N3iEt1#oet{I~2Db-p9P`M
+N7-xnKz5%XkL@&e80`#ZXpYYzx#!DR_-h3!N}WU+Sk$bC|P#g+cwkuB$ro0Pq0=3FsfqNtw^*&!C)+t
+SXT`94QjyW&ll(;O;4>AR$_wNL*Sn;tt2aYsnc+HJfQ(8eFveGlREk4Y`%8DK?_MzIwHJblfOll))rb
+GqE(3!zx9L0=4`x7zk;t+Ekh#BkD8&B1KM#TsFgH?fMDDVE0D`hoB3Jn6Ru!1R8{7MHhi$5BEQkACAK
+x$EPv-A~RKm)5*-&J!kNqG`6puIM{U3KvlJDkodv`e1RM4>+HgVK%)a44frtDQp0JNV{plS;x&3#*bU
+a~OIY?N?9rGGFb`gV<@5@z0&t-Ph@z<2hVvc#%!R_zf>$+~7h(%z&eAet>l7%3H=vG1zAU&O0kLR5F#
+%HXL942Sk@2OzcjIu|eU;|cB+MAoMC^(4xGbdx(VoFiQ+#Pkfb620Ktie4^zwJNphrFBXh;o0B~FY-K
+We4{i3AqAXs|hH8GBXzN%w?bo&%z!TEP#u0WD>uic1Y|_yFfliAcxj<f7}&L;akRYNG`y1z{AQuMb_0
+Opz1l&Gbk`cwNztSw}bDPS-eLzD=YbUrXTQD}eubdeI{Kd`df7`eo{LkDB^;W>-5x!%X|M;=6`Lf8s|
+n1(MDxNZ1b;z@zUc1i@aDQ2w#~e)v8Ldn=qCSB=i*q@g!YMRV;bkS7!#1C3qeD{tnR5nL^$82;@i6S3
+P0q4V1N+!#yo0{ZFIc;=2>m>~**C8g5?MrSZ$f9Qzlkk4W#4s9`Nldwb2a?#7eL+=XFXHO6*n;F?U#;
+XwwTeOh|EI4oAfld!L7sP%El@2CzTpMR|azO2oBoYpx7S6FS&hLdcZhg84Sb1%$k6{0M1_DY?s&Xhdt
+kBNFk)n_RCx44Mvpp8zHr+DZC$QLUcMO{I=amy`&`||w4C4sY+zDeL@3RzWQhv>@d)7qu`c_iyS42Kx
+tArbdavVD(!eGNJ+*Sv2CSm-YfQBx+RRPzuyyMZUe57C_YBzQw6{^yx=Fok?Be&6Y{%OC{&EX^m76Q*
+v`tqtw>!SsaszBON)oQh`YusfNo@yB3;EO20J*@vAqpn0&n2QL7bB|0PiY??wOpFzIx!<Cn!6So$6U&
+PMB`4UgTDu)e*cFS~@87V8@G_0hDgVL}TcuLXS)?3b(P>nQLt|*x+Zfz<gJ5C;xzJmRhyf(qLlBr^1_
+Er;#1Nzbmn!_<#=~GREy66sAStzpSZ`!|$Pw@afl9oyUx{lvnZQD6VBGMd=-Gp{YdbxX)_PA(dW}*@0
+^W`owG|sk<n-ymf$M?76TgJ$J{4U@{Bg6x-{_Jq781u|(e1Ix9#eJ!`JimeoBN8QP4~Rmt@i~IusrTk
+@Hxx77UQbQxQvb$RkaaBEA9&OPrz`TkhE!B9+6UtP3ed_SvVt;I7h&G<a}4{%pLGx5XZ#&GwC2fE~M@
+)MPxCczvHWXol8xOyU@@;3e?>KiwbbE7mIk*@ovAv+zA2fZSD~uM*zaRSRjq?LvV2Vn|vktuvj3mz~&
+MAVcp_E4nm7%h5Ph-iV~xPU$$G#`ZX*d4SUSN>E8?9HfZ?Jx-BFDT9Qg#$dEdYft;9Yy`dqCkrqWmiz
+)?b$}6{h7Hum)P~;n4905k|sKzc?vg@bFy2sE5sAsXOU<E4g<ouCz21KJpB}Ih22b`cKGp0sI3yQ?jQ
+VWtQ<Pc#@^I<PzBzd<+OHxOAOgh^ku<cLH@3+c(?zaA?xHD%#$$er4>+C&Wv+>Pa_V#8x0JH8=ZZBTT
+ZN;~=rFesTiq3MeR?Fsmo!2s;1)~;N`_yn^cN`N?6XR`Jn26&q>P3GCigd{f&9k)Ffp&75N*m-U!9{}
+)@4x;21EmZYOdiV}&;W&4*&*-!`)@k})lP2g8is!ZQKf-LEtXo_QD`Vi#*n~iF=P=aA*I?v(ktCqrx|
+U$k!X|fU>p$VpiY448*JjkS%a-v*5}(vP><!k(m?1!((w7b4sZ2LhfvLvdK2P`5fKwcke^fA)buKXhi
+ie&KzxHSFj)NC_saStk5{fAVS5&kZrJTD8z|*7@W)1>k5t+fAa%D9gPypvyRsfg`Mkp}lx$z}Pp~@S&
+Iv5mk1#hnP4~3<U2W!|*iKDL2D&!5w4l*P3ncbqOpA>K(I$n{V_FKkEHaB|t{uTCfz2FoE_%z9aKgt)
+TbXz)CzzsO9K>TncD4aJ(#nYD$3z3k;HtZ?X4?qTF0khRHf>h-INx#oy2}sXFA-MYUru5BS}B2U>D#a
+FmE+XlPM|h7Is~u;nKXgLKxP7x2H#15&E?90#T8ClEXMNnG2iAzTB9CQOC0jytR?Pbb{lcEO9~6-g!N
+{Bd3j#$4&G;EZJ8CNYEo%C*iS`{TA7>#qi~J;YF`f$HXtigGqgity*>+<u4?VmIjRX{Cp_PbnBEkCPQ
+?ms;h#Iw4;p~idIHcCr1TTT(;m_PfhvI*^T#%6fsFZ8N{ge^1{g8uH7I)|kt_*C)Bj$3>yoTk-y)ENc
+L}a0N9Zjq@nxen@H9hQ1J)jyIiM&b{FAVk7J9|E>jc{^&ou9hX1>U}gH{7<3rUaVUTdO#(QDy9Cld7~
+QK;V{w)AB&B{!Dz+KMF+i+l^taOyEXt<3afhCcSp-}hO@&>=5)JAFZVp(={z!cHt(v=dl?ihr?5xvI9
+iJsIU37Tc{e`_y_P67oDT>ntZ`P&lH@yjdw(JO@NC+TD6I02Gt&D3-12#Ai;<uC*`oyj<2L?A^O}=gd
+yk2a=^u&iJRsmNUWsc}mpOp%YVxep`W4?xE>Ew*KH*LL&P~qpsqGT29EK13{7Ol_wpx=|&<cU`~S9#y
+v4Xh<R83qO2&6>R4qoRdGid8f#Uan8m#=+;BL0sPa-bb%rnJ5P7CMSBOpaz(iJT9@ebb2*U`XB3Xh3n
+b;KThfR@*hioH?VNgJv%@rw3r#F~LLgzX5XRd3Uovou;-PUWRdR2f?=*Ct}QvZMe3=?WvDV703GdLNn
+>2E_#dQyc(k_z|K5FTG?gZ-3;(vj%x*qg>7ZH0Hdk$dubOWyNZ5qbne0mdDs-bI7?e9)WZ_g){Vk-n&
+(9i!;bDU7l+a@1r;Ds+h4EOd%S+pnxpx84a|RlB2|QH48fg!00n03Aq!g#62BP$2_Zv5)aqW*vccNl#
+XtitK@xcQS$I4pipRrW0Ko^Ko$NQRcLzU^vJEyCtN8#Gc(cBx!@lhbJ3L)$w<jamS%|mzm-TE!psUJa
+ZR5d~{Gn9qcm541!Yd<=~}t*rtUUsIj{d&e96)(c|N!AW)Ca$YMgk;2yYcuiFB9Z4QN(3u<PM{nA3V?
+_4=|H`{AZ&|ea4qqhXF0z#<f=r=}#oDFVTQgN#XnGQzs9fm))7^1f_^!I3Rq5&4gY`M>iCNKNujytt|
+jee=No6@7wMQIll!$W)(CKBgOr~%oH*FLZK&f0E-<<8q-TMuOZF#&a{$I+8DroXG76DD7!VlERupJPi
+2isr?(Y!6{Dwey=_GmJ&Z1>X}vf1Z*&HFcE7elmk4&r*RPF90@(21hx!JgQ)dl|3J0m-t!N9doHm#Ye
+I-=!k_BTfuj?19K6o_D=pWQG}awE>Yg{hE-9N0cXH<+qdQ}lzVxej*;@B9>BI<%X1tfyI<!7dQD<*+|
+d5^vWEf4@cq<rlvb#04um3?U7SLjFmwdB<f73>nX0uB(j>z&Ap^)dkfcoGFEi6kxHixiFh50+Z5~)5@
+GpILVttp4W6-p@ul9HM%AhA~a-V^Ogiu}K9wlwH(B@>W&tlQG<?e{BVz13%4j9Pt_=-H>sE;5kb66h=
+X>nP{h=%BwQ3uc|qyFF*`Ns2Fa4V`ka712h&C>>Rob|aUZx%{g^ieDoer$1^?#f&x%9_9IPRWxlC%X_
+5JtetQm(q?fXRbk6kBYKK1C>DSgnBHN%&e(GTDhGnwpG?QRb-&Qf5LR(sDIrU`jEosZzv%Cf{c)Oz&f
+FRoh$Uw)Hxs9o|?rr!M=JL0@=d}n@0Ln?YkIW53%>^HP*kTm-0X_y(LsP@$5O+<GDJA(ai(rL`HZXP!
+5mPQTfX0Exv=kY0}%{z=~$oV@)iQ`s~hdQ)@Yg*M&|Z!Dgh|k~b>g36L#s@-1h_YA@3lN-mZ1eR@E%i
+1J`8$&;6PJcz0c^c`Q*7Oil`^?ULhLA)oOr8Pm#ty8oA^W$HBgsE5OX_5a|st=gFfV~?B-OiJeX7I?~
+j?u<J8HOLoQT$1B0Ds>Mo~;>c_}Z8@j_G6Ds9HYwTeGH(yL@<YA=iuT@}Z-aj0t$5v#69(n(B5Bap$W
+5+-D?N1N4QfEvZd(wL0{%<>HXWQ!bnt&_FY~RdRh+e@NY>w6!DdVKuBC2@hptg^wQV<7&))-MJOyK6V
+EUF|wfcLqxT&SD22&v9Vg8_>;*$yW<Ggy%tZX@lnS4PPz*Vb6J!$6S5qye|SVDfkuMD79UcC4w_8N3k
+Pmwyur$R@A1(A(me0w1a-Vvh2tLTpEii){5k%h4XIBlwZ|1shCo`TeSvTwj&mjB1ZzY79;U?XiWCGx4
+vic~0LpQJr?BjiWCmK^lsL9qdGnET)SDcG1c|V>aO@HMQvKkjm&@~;hG06AKhT1CKT@CtOuTy;iG4lP
+d4y)1j6+)SP*+C%;TfgM`V+YEL3}EfVlcoz$q_K<4lnnxy{_uK&UL*C2WdW=LQAK6I6e2wnsRr%k=N_
+Exx0PVrWsXM39`9R8=w3W-QfVMF=<E)zR)Rhf!hbhsmLr}uQ_R%u7+US{O(?5s^G3YZH6@YYLA=ndc*
+oRuwaEK=h!Sj{0xwvqI&R;4F9`o|KNX)`vwLOSfhY#$!lF*-&qk2FNaprANr!;Mfz<6j(U!lOJRx?ow
+JWT#4+VzwC@7Bar*g%Nff$AP!qnMQ9<zt;L|%khyyg{<+=hITYAI0R;|(A)^VKTn;SMBkFRcSuHM4KE
+^lte-#YY}Q4)zSplHZSqmV@_uVDQSCquc-hi4LBO5B5<vI)Dnab*Es8YK3PIn^D18(cA9l6DK+i6eB@
+`bV0?Tw<LYn^G_M-?t<yaJ-H~t?P3g8Hd-WW9d3goqq~!{fG6_rZ@a%M$1D4^;SGkW=J@It{>pmfs)2
+BKI#_6iT8@mg!csdi1&8y^e%_YE3_r2%<N4N^0dNm#7O_R#Yi2p0CxgpbvmYOMNEjfGLBS*Pha+7R3|
+4+MWYo4O62NnEX;H5(yGelb^!hhsOt8#e7P$28K1ZJek5$3fsb{6d+i5>&1vvmp5B#}0F|xJTj1Ch@-
+iZdJ4*YRtXsT)udUf*rj6M96?%7cqN5@&FD=+&A?e2B3Ob2YbeV>f<4kLkx_NB{m6x1xn8jH}nH6SeM
+1Vm@rlO3$qptf`j*_&QhQTO_bwSt}sm^EJ9)?fo1~K_Qbc>iQ@oo}x<;e@E|M&rZ5B^bFAZ;oL2?cJT
+G-|4J7a@@uWr(%3n+5~>o)Me_p3zO1T6a2dxKe3aK}R(rii&SyOq)L83A;#4$e!ImMGkcM#KFOi8$W&
+sTLA{hdhjH9_WTqL85^=!YM#f>SL|u?49ia#$7!4N<gxj~=~L|nbtmEQIY=>n5sq4xicWs`OGW4*g@}
+L71Gki>`QyCmO2NtxJZSrJwSFt_bm_}?3pjf`hk(GojL1MjK}r`(P6z2CQ;<CGhD?KY`UE8Fpf|DI0_
+9=L%AJFK=#frGqR$uUa|ITZ*3<LT^YrO?Hj!VSo(ChkR_BFdyhPraavKexC78yMn#TdF$U}Vw$ggXij
+*Fi`!Qub?L_Q62&OvSSIeS{ZB(PtJuf+7L3<VayekJ^y%*^Mj9(Tcf{!a@s>B_?wjHVl>8K^u87&9Yy
+F7HAAtW(230m9~ZMHRtnMdfJc_;*)aCn_HXjN!KWLN>|1zHgeHn7nzDRV%z29<PfWRrTGQw{MDkS*P{
+!jf5QCH{0Ty#T@US+84YFv$p1ZmgUNt*Lmdd6^)?obQlq(57Pq4E;*xLMb)KM8EHJj+RtP>+(-}T4e-
+F5ey?D?FIP|+zQGhm2CK@(ej!9UTr-T&FQD4sB*eo2R=S!~8NjmAUzEQT*%zE*Gya7e%Bw(BP6TINrY
+udCNwhAPY?Wlm&GmJhjIXZ;AsmXY(PN&07JPSohK~Ua44pYM9eS_WaOu680$;!x0m9&8I$Yt84F3R$x
+M2&Nnt5o(SQgF!utdXgA^fSPugAmGe6<lOXI8%26nLp_)l@5WBk`G6<=YC>iX7Yh@HK5{Tj!jZNLRPr
+!07{^<12PRrTgh#t7KpAPrpKU?dc2POzIO<P8fy&ZL#0}NF*5~#B}MMxnJfcB+5G^&HC;wmG)hf_7Ih
+v#`pBUXVB4ZMD`3kSzh-dfU>B|)<eI)&5yFL!}vFfiO5h&iyIGP%gtW84OAsVwznXjy=nFzylC%?R?!
+-Hk#T#eqj&s4UUAS~l91?&quuoaiMf);UTa>Y@|I*!=5{_h-rQh^b?6^2SeSPpv?%GoY0|}QJlg0Ahb
+31$#uKGxr`sQNeofF7F1RNZ*oO~ZGe_Y!gtbak(t4MH;MG$jZr{?5&m~$5LqVH`nwW$w_cC;<Q&bYXX
+EUqHVZ$C%c@|3EYr<J|;B+;~)~4vx4!(0`F6~_Dn-^{4111ItS2Ue<{q+);dk>h~p@IHgKb04c_w9Bv
+eNdvjIqT4Qiy@jGX1Zp352!iLruP}RlG6*DY7W3xjo3a$;BKYKHu0FZTrub+h~9VL`|?$aGJ8cwd~~2
+w!7cQhOvQI{gI?uwoP&Vop+*3z>qoiSuD3{DM4<r*$Hj%cQ9G*n9o~9VN0u*q;rwGhePI6$P)h>@6aW
+AK2ml;P_Ey@wdEkEy006Kw001BW003}la4%nWWo~3|axZXsaA9(DX>MmPbY*jNX>MmOaCy~QeQ)Eo8U
+H_@g4JP&)N|Z8*R6{OcRgIwwdi3Tu6HPg?4ZyRZL87SMClSY%@-IjV4rcHWY0rV5-C!$)AgSUNNkJb^
+TyxvM(G);8LyLkJ1_SqC!4CsNL1uCyRXw^O_HoEs=B?C(VT8sb)xRp`x4fvMf0erSUcZ8A#nYTR-9E=
+Da%-1&-z<e_Yo`Wq{!vHZ`uB?sABme4C91u!?67o6<JAZ{2iQ}oJ1+*oRs?#$N=jQMPG`Up67|roMw!
+dG-5=~-4vDl#yDv>+cYUja&lKCs4{8tq!#+~j)?do*H(<PI_$YAD@cYqQ@mcuL85F#>Vm8pvW&^yj=5
+NpdPiY?5ht5{uM^sOlWfTcnl_C0yv_({bz8v-HBlQ`7fl`mql!fhj1{?KPRus6Nox=$sap%}Xhox%Re
+bK4cq_L>o25-kfk;JD!s`lUrcGU(f#4sQWH0QeO>cLVfI-m;{G=Pax~Ey0vgNYBh1XqD@5VO350=JUy
+q*c0N|P$#xU@cO1grx=o2Vv~Y%7{&v?3JHiehK9P9mD7d%~Nt1dg!AqHZ90p5$qgv)78tI~2|TUM&tz
+ti>=bBP;R)7}KX|xuZNFKg*walfjDNf^AhaC9L=he)^~WDS0l4T+iq8_wfBRICZdjMiAwdvO&FL<kSy
+Nwe1rs=S2+;5Ty;`1v~-gp?QU&ZduMPx}2q(xg;&j@G_5I?O1gCI^nf1M4b`Or|XC;E?yvd0&hmHPvO
+StjGV$f{D9l1?*~GIz#EW@uzTqlk?BFRejibAiLP31sIomQ6-Ech!K5usa>F&dAHW?Tn1JVnp^y3u03
+=ilIsL#|h=KJV9!&x`eB9z|Px(;TJDc|&NSZME^6IOX?_R$RfB5>Fw^!k-uV23T{%FF=IYZoCE@-PL+
+EM-X>hC{%_vTAQ_Yh%g*F9zYP<nVMJlZp+*&2mv(f4A_D-i?^ssy{bE;s{55Z~&`Z7X}yVZth2hAgM+
+l*JCJp_+0fXBZTd&GckD1RY~mVcJ%(h(<e5Dfx+c)<j!aW7Qm28H-rT*-<jN*dw>U7CAfGrXpmxEeb!
+Mj<zmyb-Q&CYHU-7*0RH>Xj738{=t$2>xU)TvYOU)<#*MHxF3jW0>5G8Y{%vyWRFnP9R{_>V`OQ|n-O
+Wes7O;5)q({C-cZJ9Z>d#AbN8GnSt?dHRW3v_V;lt28p=3Vn0qF(u~w*T(_$@309v!5>-Yy!=%Lt$*G
+H?PW2>>&Q5~4fv8b@A$XIF%j@K`eL&#zp{!maOZk1gj(j+_?{YR*d<dO-2U4_q4A;+0a2D@e|)Oy-X7
+Q*Oo)80G>78!SyhMgDBWspF8N}?Dudq0j7j>Ca3e0^%;2B`q-`xV&3a)P6h(jl<Qi7iL}*nl1!ksMs1
+dju<kxIbkZcVKqYeR?7=x8-0I98pIPyhnz{s3`ZYxCje?3ADm0YWl%&*knF$$`}HsV<WAFC<uHE>sYW
+dtK5aGCjDI0tAVxnzAJ)f<YQWGxvQLQ^FW}t!*AiH*y}fpL)_pmMNh!p?eI&ICHINy1hHhNaV#4R%p<
+s5wJX>zW~|;7v6z+@RR&1~yJT$W=E(FF<*aSu=LR=JIju)g5?=kY0l)Mu{bovr88#3A8Wuz4%Ig)DK-
+#@HiQ0P^->!@TX<#*7b-doSUB0HJXhZ>Z*m#nq&}Vt0i+e+g^^d?>Hor6{g*YVvbKKk*g5KQB3~n@!d
+(!zHtpRa5?kp{elS!(m>dno3QYVOLh7=^>qMby$j8vXdd9e+?v9{d-m?3`qfwVFF1*1$+$Y077*Xm61
+x50D_N=CcuKoYi~GqKewyA43qV+T^1%;T%KRdY0wUSZ#xCoG5R;I5)&2_19W=oboN(y^eEmN8i1A<4_
+8Cap+#M>`%cIN%Y0Gz?aCHwGlZR6_CK<_0a#(5Qkhtg%2j4Ijw@VkKH^E+keK^9}3C5eVbLOcolH4eh
+-zVR`MV9gdr<^n+uPps}n&V_?U`(eUDqB@PfAg|jaam`}u+1ov+oXF~A<I6EdxJqc$of5R{n>B)hCF_
+^t+a?GZRsxvD#xj0hiP`}|hzQ#=2Q6-dLHz_hK#-Su4MN=b|icJfSuBfb}=p6AeC*OcZL}Z|1V=%ybX
+Ch0~O_@T<11N11fHg22Ldj4FPzR+@Bc4;>L~$+(MF%F-pAzr|^K3|DQVD1IAVhML)feR5^&U92G9zv9
+idM^*G+g3;Y^R3+|0>Dxe0rv=#`^=_;sbV7sm4q=5O1Q0LDi)?Cl2F?ainVyUV;s1X6^b?>f^7ABAt<
+I`2)OWMs!&TG-%y}oZx-XYcC!LwF0>qy7z$iZDA5D4X!ePN_=Y^r-OjfDO9%TvE8v-S&E+wgTRQOlO;
+&Ts;y{u+=qYu$5pBMm3{b+7dF4fG;DtXhyGBBF$cBD+D8+}#0ZGP0E0}WHnx^{J?m%kUD2d5KJcOvJm
+N5)Cb@VxBz+Z};1gg;#ZDr6pcG~1lR%pTdQMlbZfKG=;E_<wa=K+I>5Q%<EGz51lIJb~KjF7YDGFqjB
+fvotXvToLdmDgX2tf`uGsnkH&PjM-nJMgvpGmG+a06gTa$ZwNt2k?hLI+THTBoh;<wiue&7H*#3pF~T
+2u_YWw3(dm&=h;(K-LJHH*3-G$dTTQM`;FbMBpWo&l7B?J92NnNhfYE5$LtF{DvmbgC4Z(fY-{tC6i|
+dFfcZJj2mNILZzT)`__$nBTui!t3th$SGe)#ENU#3g`*z=CSFhR7$iFBGI)(6$!s5gZQ+pU{~;V6l@B
+@vL*4*S!F^e7;r|1BIbA^>hJl36!Ff}i&hd*K_3OdK4zHPBG=YmrNaOX4+|f#;upPs+L-%X;=gAea%H
+Mc-q2(3<r3Wq5epEer*0b;!n;i&B5G4TwcyflPUcAWQADAfFB$2G0+bSf247YAeP?4>9&8QirH9TMiX
+d}R`lT-(R$P^!an3Tum9-1G|mQ;af)?J!fUkqLvYVT_eiHN4=D?xtS?M5NykJaFXp|0l`IKoJvZprkG
+k-g*lgr(}a;TQNUD~aTB<Vh<m(hl*#N0>L+n(5Do_!9GZk3d*o)ne{ay&X0GPE{}0fQ<GrYrlZy@sp<
+CmlV&o=^8j=eGW5lW3?Ft_y(<Rg<vr1{p|IFI1q|QRorF>^KFJ=1#V<jq(>|X$l2$}*nKAaHA_o;0ZZ
+CfxJAs?&2}rRM0L1uCcTKm9rbpR*j%)dI_ONBEGKF&`c}z*?Vcf;xW(BT+$o-G_*BgZH`^Vw+F8q3zQ
+ZNN!PmGZ#IUGpK!DXivhQx>Akr7aBn9z+3mFP-#8(gJR*PUrx`&KK7>14{n=<gUz@}~C%cL)c2@WGoi
+KH2R&1fCTmbiaDtaw>G41^90)0!P82yzS?fQ?WIIPCyI(AOp$@>%i|BQ+E*DK3$s^!fqpE#(aK+q^Nz
+LX*+GFNI>n2`^K+M=Qc-#84DT!AZPx6pOlgdkJD`ekQh}ec=hF>#u0xgA&PVSETV+cVk@L>OaYxW4$>
+zdYuuk$&;vvnFrq?k)*<ix>)L|!8<vP@O`!}QrHMc7dt#u@&5ate|y3o;M>3K*H|1pvHwDRq}mIJ?ap
+^nxNIXNk;gd`o!@|)NL(!}g5I?uuc^&tcw%{$Xm2Vl<xxhvjrs|v3IdR42ad+=pa5v4u^t=rSSXv4&e
+_bYjZZD-au`RoM~ax0HKdJqF~+P_8@ZvTsO6!GK5iX;nu}LGOl(kr2Vy;pkEk<RI$vVJD_W99zKc79F
+YRdt&9}@ypOF_Ypn_Jv?k_$)hg<jwx9#%n@qh@|i;K@NDItN2g*|zV<^U7SGkVL!Qr{$Cvuq<4rc)E*
+?ivzbrWn{CU-ld~`Iul%Q$Bz#Ee^u8XjgHr+#B{H2*`6HY+@TOaG*{wPVoUX2xQ|<#aX>7MBM9R(6D%
+9fRw@V1CVl9;^A^BcJ%xbm6G2tUOd`noYZ1`%j7Z@e0-39rVDJ?p-=5-2HW$r@fBGZ4zDt|dtEoWA~H
+K$MIwx3N$$5lXJnYg4c0g{qxb$|rrifWYnN-K(9q>S8r>f*mP%_u^h|2;(+{pS)@NivmK~e^;L)~xPw
+iT)d@i$yK(jPd-tzIq$P}OVx;ltXMcw&^g#PXT&dQ7ME{P$uE92KyXJ*a5U{2Wxz#OzNSQlrDS*FmEb
+-xlb1`&=yJ|@1w@i|!x{7hr=`HEa#ni|Ngat_q&_>c}8K)k@J-u%Y`;NU*x^d3&hDTsA>`S{=`LLTxv
+vN%6~bmwzaG(jz8m_aKTGJo<3E}j7y+db_&Al*OmVH4SYvmw)KuZ3cHb77f8O*Za5w~f>rXybJ^4O2X
+NL#@yJGh69kpz%PrU?A{?KpOx9<}EH>eER!8eD=r7bAgZ%@<WOW%`UAM14$H1hkPU009+)?2OX-9@uR
+%)_|T?A2SkLSW}PcAD27-i-gpXC6)${vr3Iyt-FKSse^5&U1QY-O00;maO7>O*6G`WF3jhF?DF6T<00
+01RX>c!Jc4cm4Z*nhid2nHJb7^j8FLiEdV{c?-E^v9ZS?h1x))oJ*zv9CE5DAq9k$MLxFj5qoHc8uM$
+-2!j6q=%JCNiawbYgcH(4<|vX5FLP+N@jGZJE=iX|ttWvpPv1K<@V-{j#Lr3}g$2Vf!C;?t>3WhmM`N
+G+>J7ckj99ea|HyAuFD14|`5&w3f@c%cG$ml3*>!_5I;8aYM%shr>ZYB+_>WK<ZnAz!4+DwUO&BM(_b
+Q2#e(K%4pye$q~;TdbwQA9#}y@x&!OEHU4wt4@bauZEudi)pPo!+jTuR>~`~kGw2sd-zx}=U5r%fd*m
+@7j}yDy-q7xLITAfgj_|ByCmAB1a;bF}on+bJ!m%Q;2SI9ax6cT~4aieN&q?U)V!&fee<u$!3+XxDFe
+FP>V1=QdhharB0}6uOyqN+S`o!|q@{_Deas*oogyK_!6|fUGS&BoE%*_|ZX7_<*GL*QU;MZODhu!X+v
+UffnU6|4!UiLBagCE8qTb<bosM7q2@ltBW!<fF&vVvdcLUYli`Gh&MQKFLXge$&>&w*$<BEt2M<t;ia
++<*<c&GBfP<DoYP(~2NaI4@(75$5OT<5-j--wm8l2s$$}!|xi16p~?|$W@5FWcij2LVydHod>Y&inZv
+>1|!FI`>sub(1!#F7|K~3J!%a`;QXUUi}2f9S(d*zHF~tX9*{;bGqe^44$w++{gh}d6d+1n&*_ncHDZ
+wgQx}BuneN=t;gT~gYEHyIHv!BNDl-$h3oD@m>vjbLSd<(RtZd683l5P=!FnqJD8(76vmrBKzyp^k;;
+9G$XD<;e*t<6uJ5I6%hs=$6KVM!gm(_BSuzSNP6sJ*3qWwOCD&=x<f;=x)mC{?jLk3PioaJ`)-NmJF*
+7fWGC~?9mfl;N@%y#+JVu2Yp^c^b%MXi95$ZDaK8}|T@1ZEegbwg&H$Q9f)WO-!}x{RmmEjhj$TAt1M
+55XmVn#Y)lgfH4p?$5WEfLQ>Be9{_O;@AEm$mC7r=m;jnA(~5>c`rdSVNM$68`IS`DS9kWf-c0X<dh$
+;d60jCQ$%2KZ`%`fWn4;DCv9fdsmw}W3!vZesnX^9jCEA=Y@5|OAsE!Ue4#MS2P7;xtD)od@_b<4_vg
+xx>u{S@=E<W(DNL1<IeQ717lblw!2tFvrw64!%)^jEVH=i9@^!*w;2Uc&fHLUKo?L=GGZ<NRx^{?E1@
+mxmqhgbiZf2%*Z0LIV)b^T(!cuYr&Z;OZKj}Eo^1d>QVuZ`fu>~iDD)zv#N-;UBhY*t$#tfsbEJJ?Tq
+~|WW;X}*Gxjd{nvxSXdF7XazW%3A5LG-c*w#5CVaeIyzay4*qvLt|?R>;fd32Wf?1RqxT{jm*i1QirA
+x(5$7)F!g0yJrhKkEN;1uBp^z={7|a5+mM9<jQs##_Ultqv>s<V?Ms`i6{3TIQZ1l&wTUHw+<iq_Osv
+l?)R((8*I0@<Q_XdSoVga@B2Zxa^mFb+H*H9-neq(+DsNp`aC^FPtzCZi}XkICHgY`F@1%ep+BLo(x1
+|w(Vx>_(AVfM>96Ro>Fe|j`WyNt{Vn|+eT)8{zD@r?|49Et&(S~Ab$Xt@L*Jzr=zH`ceV=|nFVVlyzt
+YR}L;4Z@8~vDGp?{|v^eVkZuhUQIXY_OWMW#^QX=L0c$<sE%n;U##*jvj8s-#1Fu;^l}(;*h~<Dtg78
+J?g4DbKb<mvrM3l8-u^gHIU7fetaAK3qVB+SPz$@s{LQmifzyTB+9Rjb`h{Cz(FN<Vjz1cCsy@Vb1o~
+Jh++_hr(E1<O}mC+v&V`*r*W8Z4nV<v^D~<S#$L4(C-mvb>uri09`rP4mzn+Ac!U^iJ3jJ)pbJ{pET3
+#N}Rw0Vmw4qQTV}h<c><+6VM|J{Zb;CJf|`NbCYqyi1~517n3lEmn_7`h?s3xwmtb&`%{=aS+E0)Yz+
+8pW)z__$Yl?gm%&ic@gm(v1*P%+?-9~p4);Q@*^iz@XPP<|#BAbJ<DKaJ+sD`>anByC1*K(cRmvmVaM
+>#fJ#;H@?Srfx9=L4T!85QtW(ujrkyL-pY{0Uf^B`#^gmX!Ib$f!33140{;Yyty#soiLg|4S;Ur;`NR
+*4T>?bx`7Cb#tmk`)d|9qe$VN%TINXgk$J+kH*gQH{x}G`5yi->Izn*C1<C$f{N|WqsUtoa5UUl@HGn
+G<a}HD^-<C3OfxFAC-pCqta-gs3uVpLz`8BHZ>G&PaeDlxg#cN3WjPGfp$>Tl){>bIEtax847nq9L1=
+05OEZvKJ|J)kR`7=#>*6es+bC5QlK^^YG9};=VI;vs+?Oz=ho!h8saRVwlG!9nvRnVoNS6E8mItGDS%
+$ZP+b_!Y@=vfqDBQnjR@6I)DUO~bG&J)0yWWfP086r>Z7Wtn9<aR(qfa~j`&~G>ov@FWu+?21JwbuUR
+lxbU{hs087dwW4NZ|w(bA3|t2XU5-yIBGd;0|^nz8%Eu__CBO~u^RmO<2RHc?}s;c7IRn4gRe=cO80M
+bPTPA6mVkVrZi(&=xY+?5Mm>!9BCU%eQblu(+78>jqal!lY`a)k2KaY3Twrk<6<oZ9cc6bTCx9vTEo^
+WL7%@ZJ~LoH3SNGq+FRTftp$!$rV#;NYp?yQtIFq9z*a0ttP4>3l$_dj#njKLF<iLjpkR8AccGt!mA*
+B9l;~jRlQL`Y7&sE5^rLg1dzopp|(5NHVI^1I$ZCR5gh8Yz)fw8|5*4&?~b=0ztN1W04}nV$bvYN?6<
+sQZjtPBeQVM3EO8#+Z-v%zc#@}$_*9Yz#iwOR#HE^)iBHJPsIj@*&naogB);{@_?9CoG7u`zli*(&64
+fG8Y^B|_&7)b{DH;!?WTjkHgbJ<6P>x5mT4IDY8Eo+gbE?^skZCriHa!U`dbzA*Vv1~b;KyVNM`KJi^
+WzS?qKFbPw==WHk@_{-J+f-6on=)`2G`W?7L8C$S-dkxsD>D!PPIRB1oTHWaoC;O2O~S{<!L*|m{PAw
+Kh-D8d^869BpVpDob5}cvV|}2eR}R+m(GGMdA`TwyQkm3d-@CZ|AjLg6kbd4Qy<+u{mR`_uiia%5%4I
+Pu+NU;Z`k-UC5et9kH%aw;7EumxR9>C``BBS!S-vf7*F!@JKwJN5Q;o~E7PIGLs7ItaK})kB1(wTM0)
+IsY;P;7G8yO`txL3l?8HFDj%`{?Oww8ngr(LN3mOd#X%38rF3~o!bpurwsELSUnwoquq$7%&W?L0#8*
+6yXwkA=m-!u(5*FfhQa;}lqSLTNZ2^QWwM#frH{9~~gxOKpZt=#DmWIo@^#j1H&V#{buNppC~%G%oz0
+odr>Kbv$!DJpj=*h`B}#S~~wFHD+Q=%D%5!cI<EV*KvwQI}_|x`M<hP{mu8I+o03*`1af*)Q7mISamX
+atGy!kKcVYYc1if8kSP!njsIG9n6`vj&NoTdoN(>3V)|y>J_960JSMmq`&|bt4gLWx_Y=HO*>F45=F(
+S)+L(h6T>+H+sdNl?;weiIlJ#0d4emqu(yL+Qyk5;CWPRmKKj9DfFu6yKl(0V^?J#th~(o>Aiw^^kQ9
+~Ay7TT=FW$L&=fgV}zB+T~Jy=3yAIJW=ap~S0F9S{1Gfup9?bgPZ&)?d(bshdTzI^G{Wi~**7~vyszJ
+BvM{C#rsvzu3MUc31L;QUQ32XCMI$H%u{yL|!vzj>QC7(5L)cJJ)@dvAU4?~88(IjWo-_}}Yq{pZT1|
+Gx1tYgl*@<>bw)FK%v}-P||_WLEkFas8dm^Dl3%U)fy0u(|&E=K9&q^~;;*pNBDtXUD(nc)9-rP)h>@
+6aWAK2ml;P_EvXR(M)y<007=00012T003}la4%nWWo~3|axZXsaA9(DX>MmPb#!TLE^v9(THSNoHWGi
+=Ux8yDN~SU|ZeMb`I+LE$%w+m;nO@R+P;@jzf)Z*HU;)au>hb@6y9<CH674!o=cecJSR%1l>@I%$1^5
+ZuwX#Z^{Y=)4HZ7CNHX?7s<25%*s*MfL?Y<G+L$0d|Xr)%&E7=OuYF*h`X>`rXoyzHv`SHr^vYh8zF=
+y9?H=Yc*!Xkm@oL3cJS3vTewC$X|SFpmIy#dzl^*a#aCvN5}=eC{AvbC+a-Lf;5Z%zESFOu0geD_3gb
+RNywTJKbG78ob9*(`@CmStJ4RVg=FS@Dfs%ozMcQS?T^T8dZ9QI*=TLX;9M0ZP{mZ{=E6vfVST3K&}N
+HX9rxE--&aj51g*Q@j>-L7FUWYgQoHa^;3gc_WI42+-JBA#4usA}8q1aJ08y;U&pei*~CEdI3_h%!)S
+7D?4We@}9FRUhPEUl*1ocx)IoGP|&6$K{_h@3A>--mv}UUKV@`F^J!|9-KDq0_l~*Oo%nZ5T6PP{#T(
+J`7Cw9Nk|f<VjWBU?7fmcc2F|%sx@Bv@^p!A17KKpJ{D|7NJin~Om8j0X9FHcWCnMUOQTLmp-?q^-dn
+9`>ZAT_5E5?%ymsYT!kn9^{w28||X=Zo%_Si_ydVeu@QR22&C`2pby5Huw;`O@VjHE#Ng%cV#-O2RMf
+JjcJLfYTM;WY<667-UnoxjF4zp?UHad!H}^JIoN1MiP3oiD&{;H0p-n+5(&*vSig)j1P={zx{rEZ-R;
+6ormmt=P3}w_tXT69H)8(cq{px{?ytl~lqqZW(?7^EVv8uZ>NK<GZb3r8KtV1sGGidMyk)O`ZLI&@Cv
+}0wKuDcU8-Pg+=abvE^41+!`jenu(hRan|y+MHJu+shVBu#Uf^F0bxKO$P5XHM1fsnbS|t-8T*$IM7<
+z`FD~8!g)rY#q6V!~q!*cEdO=~O2A(uQDtN5Pxf%Qh&W;xBrd7*b0J^yN>fP7>cyV#TVE<5T3(-f|R=
+5!0Hks6_VFu0u`@(z+5e7|vCB-$<Wv75BI_r0@h!bos$>Ua`O(1V{=5Dl=6#By^9`Q>@2(W-c1j(#-L
+3WDH_l$joOW|LkVw*UfmiX#~okBc>;P*jA<Xp_XwW)z<T*UZ(&YsQj^>4uy<yZPqh&===sqV4$hai@Q
+r|}Bf{jUN07_bt@0N76etAj!S?5Bd2xY6rB7_1(j2$7UFcnmf6IXis>-0lS%d`^c)6pLg>mBmdvG$lg
++6VMlyf~{_|+<0%CbR;BGu=;>(K-G~9jI<0~!7ywQCa=)F1EUvb;OXSU#}ih4LH1rzttN_dwCkd;YBI
+1wn`N;TRXHeT$owGX?cMlQ2Bik(J^Y@+_ihyDr%+A+zbs5Xc+~5kp{$L477h{slQ^5ROR-N5a=f!cw`
+>d~^AXPjPLOFc&+523>oi!xFjj*^FlLZf0xH{VYF6sT1}l=n2u|SjgH~cZ;LJp2efm9lBNonBsLhEWI
+p8x*jv7tUlQdH^Xdq1KcK@|3^+OvE6F`xH-XF7@4?qS?jsAqScOYM}r?l83VdX{}-E^byeaIg>BN*!%
+q%_}y4PwL92JDAg{i*Oa9F}NQaO2pkksMD(&0}xHrCiMkX=A#66xhMT$3uFG+hR4jX_M$5ZRej4{ono
+g{(DjDac1}$a%8RLuZYf?H;v2WyhRj1VzBHY=MB%H7rg*GRsyps>``rJUCn_ESZkm;vVK;eVe37n9BC
+NOu^wRB6vF%+a(XU?j2%Pd$07R%9<E*lO)N^2L%Oc^Y-c@ltW==?$T_eq`V@4ZUx&pGeLD*S<X7(N0R
+_)nd3E5>ZUi+qG_yacNdJjCisF^*L%fp*b{z%pL>hZuYxa|FIFx~0sP6`Ea?!NxTd}9s@35Qf1x#z`Y
+qM5o0+KAQdjC3Zf?H=Gx;+;C*waT#dVf81)FW-i3COJmIQtkw(R_5j0q?MW@;GZX;2#fk+1FcH3D-Uh
+bWE`37=vg$ZOSO9Sd7KVnd^e@-L!kG<6_l8kuuW!Fq(}d=(4wu30*maks&Ssv&l!s2VPYNfgwzP^p2A
+CXH?c^0zA4AnGqXtlTq@@@+}n7v7IPypD;&`fdUFYB3!WlocIGS>?d;UUrh7?Uq%CqAzo4=nu_NTF6S
+&9@_o*H^*N?+rK!P>>EYH5x6xtk3LR(A4Wk5ax~2y`k~FmL=nF)rqewia>yIPp&<+xw5#BZnwubzUCy
+)k!F*XP;BP|{}T9NM%4skv#W+5hGhJi2~=RHEkGt$P0t2x8J7}+xFFD6Ka2V9QviJSC-osRwBU~=$RO
+8Ez4)Nc$c0B^`C77kz&k}+%r034VWp+DLv>?xOcxOPIvtfE*=P4#P!izsT&lHb8CXnAt_Ta&w;>##on
+{%HTaF`^G2A_OW~zQgxw>CZ6oo}<#)W10F{*iq?rfVMs?PB5ZscyftZaD)E58C@od(x0`2II0Z<46JO
+xKm2JTEbUKdUa&9wb<vBV{2}K?W&6$97`<!O``A)IIU8@lL8a#oM$V``4cH@=;|T1Bhxxn^zwE^E;q(
+9_TL^?PKF8E{t`aXTd_vz2I-Q-4rYDr0#tVb;UPLG3aV7y<rVxNJhfnS)O;5&Lk5d_KglK3ha8V2exL
+$$_<AY;EeKVmcIypW!ABb`^M#heA9}w~G76iDPrXW!!PU@XnV|6^Z?g4lo{q3p)BYBU9AUt-Fxvan?0
+ee-oV3kDuA*$k+#W9SLuSC8;JdA<TLON_Yl(w;)J1$2BT?(*6t91*?<iXSZ-p+EASKuRvUh_*xD0`*V
+zRu`A3{V@pTcpe#zf(Rb)q<UqUgsfszQL28at9m*yAsCI@fL8<H6GAW^_}ZN^e2G+)(V2X!W$J9mb0E
+=tJzv?fLzqFrDLO40s^u-Is13G?3sD$_X@A*@Bp!uxjU)*>*0k{slf2zR;L8<qKuTxvItd50<ZY3feH
+ZI3SF|#u*mofdWj8fKSW(lIzq=l?E`cr;sz2ow6m@%M2jWiun^iN&90%Q0K<CjR@VZiK#v2`iiXY;d4
+cr~ZhS*a<JBg_+*})urBE<U+QqgArHaVE0UNQu2u(ZjK)nPHMPbXp&Nf*-TP^xN^CewpBF(6+^;_Yps
+;8hai2wBI<u!ggfZvmcuG^k?zYY5Z8l0f9*lnr$3plX(@rKSv7h?xpCtHnD-6Qa9;N_3h{QpSjX>FYz
+uwJ17)qwUAYUd-7!V&sNw2M%rcRbtxC9ux_#}stcNvc@4nmT+L@H&WR=y>jo;kAb~o-zz<-Lb#C_BRU
+y?!$L}gQwZMtC=mgLvMFoeDv7G9QpLB!|-|^lkNnwBlu;<tIn>pM*n6QlkuMg;`6zm7*dPx5Q=QQ&l=
+G@j|Xws|GU6)8NNZ8f4&;`U$0z5ft-VR2T*bH_M5lQ5B^KQhkpPU1g1)=ON`ewK49Ed;<^t<Bj#Rme_
+^YE*eveLC^XtZ%mv^70#Hi>1QY-O00;maO7>Qw0AcWg8UO&7UH||o0001RX>c!Jc4cm4Z*nhid2nHJb
+7^j8FJx(9XL4a}FJE72ZfSI1UoLQY#XS9U+qiPS`>#Odc@yfM!b^J7U)(73{O*#ww7EEQaocHKk3y4>
+#WO|l5tL=UH2-_|0{{UMvSnX7)!fAr2`m=7i~S~##d_E5PDFWKt5!ajZL3;+RIVG<cB0M7s#RHWv~1N
+{G-Z=6Ze?AlR+s_JuE|<m*4K7Mw`=ehjpy%nXmTXr^S;#GjJ|!y*0MO?G?nDvKg(LSWzIj&ca8k_tmP
+j+mARSoV^&q!m7VcPn#=Dx+4AKnul##i|DOG$UHM$Dn=0!h-z$~9{;6vLzjtRA_p;WF%)6tbBc8wL%*
+2IOn>LqXE+&)7e;<AMlPH&>R-KURD_Mv?eLZ^h4?ms#c>bRs--uPWu3jI#vVUY&yv7MYHJAe<5#JsF-
+nUor^GbKSO1^f#@snCEJjc;U(J#S${47=7Jzr+)vI17FRjqWB<?^3{ao#H5d&?klm6kphU%oJ6|08s^
+l;W$y+U+7ng70~=udY<F3-=80@S+C~?k+)!iZZ)yGvG;WziNxetD?LWd6j8BpEv?sw`$W&dh)zly&R1
+(M4G&YRSnRzE4vEU1sq>`vtvsXQs-^ibfv085b~}g2r%gZ5c>9d60*>P12-)}nH3J6`O1Vt>g=O46Bz
+bFGUgK+#PjILN-c=1mHZ?w(9@%%WAQ<C5{`c%;cV?hw<@*Rs!dghD=9KjWL-x4n~AGUC${ogD}~-Pcw
+kTzKkmAfs>KiKKmA!~1@}ds)z3OnC<e8Y-4UJipA4(#-oa;;F!AqC_(WeMlNzp0W<q!EbS9EXVecEYl
+AaNdvg*RpJvAUe8>}yBPFWZ74rY{fH@!sVfb=;P8qPb213=#7-3Io9#D*=Zyv%4*nZU)xw(M5$-NLsl
+WGbH{d09&(lk*9X@`&gp-ema-QAiwKKcm!6Pk6I1mo(W%cc6?M>=I^(PKjKBE`rmT@$lz@Cd1{r%gUO
+NGqUqsoYnHI{S~x!>^2VgaivO7TWSfskZ{W7TGpM$(}uqhQ5sD9#4B{X1ZY@U!JwkdnH=3J>jX%LSOd
+~17VE6bSF&&$qAxID!Bas^UYx#ve`#(Maw!%Iz^+>?5-qFcOnisi)rKVa$qCa1QDN?=lJW+UO4bR_fK
+9!0)7@-U%Y|weYaqo4gd-9`n0pKL^Ff|vn@m%O<q+VEi84p*Q@7Ec=chFsQ8-t{!;JrAgl}`jQ-L|mV
+xn^1N&urpR>OY;6J(qh52+m?Dvdfpv7V7QdE^~!kZ9rWY;y7C>*XYclK{+3czdXNn4@GM277)}lpPw~
+j~Qr!tV)dizBs=e?D#YXnXAehR42<#op(xAI&F9ws};~0C|43d$|4o-YN0?LTTn!8p>a2&l}#%(iEoA
+)Kr+2nnMQ2`S_bCJn%0BEz(*TEg+x0R{~<*!L64Gdf)yl8%d?G^B>(O-IuPIsi42qk>&7;#HByKMqh_
+3;&SQmlg_^Ib0QRQt$_j^=H38`o7V26l1*{6R16>XS_c9WRbmDxSi!@DV;{0+Zvi4e^042eL5;t4^1&
+6fr8I1yp^Wg~KpYR4wfgAWIyur}m7Jp&P{z80SOHlBILls@91#UFSE4?4p?+^_9`Hlg?xqU4r1Bn4in
+e>=jX~ECCrP!$r(UUnvVuL5as4h+FIoq)i;8-?UW`^_`NaC|C;Ra~jmKhB=ZAcfoB{NN6<Q;l|sdx((
+LEdF_R0n9MJqg~n8KE^prS!uznTq*b*oz5Wi|((LV0P-!3Bp~@@gHXO966m3`7FQZhMa~$O{?HscRR-
+&G+QJ@o=BL*JU(BrZN2mb5cgvQkeGEI=ggbitlFS&fmAd{7&KL3SD{lR^``2g(~XolVN7$??2?{HP7X
+b6?HD)cSe&Cw;8B7jTs6y01$rRALGuZ_P+Q_8{6KHMT<*ke))H927xoRYf)<HPuTz%NDf0eC?oih-f^
+^ecjwpZe4B7E)CZ4G!{tI$hU+ZU=Q-5;{ToTYXkwkheJHW0&0Ps6;r?Z~~D%Q?REuLk-t)3B%f`7ILH
+EmRr4Ci~K@_CQzCc|?H+8p_B72l#$3-l@z>y4jKz;@w#XmGm87oES&z$y&RI2^iA`Ttx(zzB>&;-Rhc
+A<YB`aIwkJFklP`XYH5sU*97T=XTtd8kBFT!6t$p0zGXpBj_i@Qth;%kssjw6^bWl+JaPuBEhuYZ-5}
+Gap2g+CH>kHl$`kdvYxyfr@@D=WymM=$jW*n`-uuxu@R>y@?E<d%+$RiMgdBm!IfvzV9Wr8blZaA{M5
+lg%ql=7DHUIuA+$OC-%po!xokRd+5swHdgU7o_)iXietYe}de~E7HFr}`vBYRao;Yg97vWMoALMx=l2
+)m1+Up8rOqw+f1UJc-2@RZ_@PwI|U^oUpC*a*rFy4X)Mj^FOKgneJ)f@t=mJH|97NCJAWcfO0BhK<n|
+3=P+)T+9b3#084^Y<ib&wSl!CG0nuZ(0rK09*(I3{_XIz*}Ie2Is=Sz{3yHx&_gfx8ML7Pe<<H;D>Sx
+#4X{_Xka>c$j+M@;N;l>GsHRpd$yJG)`ydvV%|5+(#%dYgtx=^hOG8rjoM*svMz>;-A(C$-r><S*Dmh
+|JaCT;;4h%=PexlY(Ba-JSR$op17yl9rR4~q8EGU2l&DpxiJ3!@*GZo)OMyRHwr}_b$Gk=;7gm`K<6P
+X!CC1Ni!g&TrNC!b0$RbD$-1&ho>y_Fr*b3_fo=5<81x`1NV4dBMqKI#Fo1}QG_y-ZJs&RdgWVb83QR
+C~PB=?%%p1IVSZ*~?S;$7pZEYMMIca6fmz)Tx$lTO62i2OhH47VAN$?{xk2K1Zt-D&MBxkO(NJU>_`X
+H3!US7c#4+tKspD$_1TwjpyvTmopgIfKyJ1iohekZZjOLi=M)k0Bv=h@NNagXvkBD8q0Jc99m(frM+=
+30TAJs?1lS-hifR5yz|oZ>9#)ph^LTa@xj9Cvv!UkU{(4`M|s$%v`Cq{5xh1;JS~;Sax82k`CC3$q9h
+#y^<84nSq=x=>ygXE@hopo5Gmml?=G+FU<mZ-<oEGTS2VK>s1B+BZE0*Q$q|!(W+q;(qaR4Zc|hG^h(
+_Yl6>rB88O?gRAr*I4H}CYM32)WXrO39rPK{X>~lL$wx2NiPeNIkhd%}AmM>pf5u%@E?;4RydJF9<g?
+_m?|C#x^8HUY!b>ORnx&6}L8nbpjzBCxl#GZTKd4M&qK#@gRpvPMz2JdNvrZ|o)mW$XiS_kokb6xDLJ
++sh2M0l@(+eJxGULwsYdxpv>bSHS)g#mO)?g(Y=kM@mNXYI`bbj1Sv2^+YXn=><bhGrp`^YeBir#6xB
+0m2M&P&p&IgaBTz(0$+xsMR@wOAa-N2<VLx<=CYijjeZz%jV~tF+h7uF(BiSIt@xr4p^kAr5q;6XvS2
+$7B7369Fv!kHK5tlrW3`csrWE4c$fI2cslUiH1Y@Iu+H;U;rwnISu8Aa#%ab6InLH)9>griqEN_lLt^
+pirfklY+waUdIB?*~np04q(J(I4o2$U#_vE24+y(ZgX*vm)#LvhD4<~|QK#{`ZLlLaGjMpdtll2%RUQ
+M&2NO<scG$5dm^<E3#Eh3)-Pt3@>F@M<$v9UE$)Q4&P9p4E#=13Pt=V-&8<0gN{R4s0;u(4KFZL^(*-
+x^$Dumv6Xy%?L7OAinqP#{7m4NpS5N7sg-3XO1Lfz8m>npfHSs>o>c3H{5lg7v-^tmhY2ow1ta$e!}k
+swVGehN+tt?60i_UhMI;F4?<5^D=bP5lOJvaLkc{aFC6SG3aMbxjLUFII^B+9^f|)5Dh@`w)Q)fc&HZ
+;|CX?u1??`Of2VNB=iw54QkD@Sb2P|1<0W#pS~SB{@~FwW-j)S~*q#?>fDCh|TqvS^TyK0M6(W!zIJ}
+sD;WCj|BN}HsgFIw!d=B%N%_(Q+?qnGI3@zn71K6WtLFzA}c|mm@_}o3b1qtfdPX{2Oo9+c5$0y+Z%9
+zKDwuETgXSxI0qz{n<mXsdjywymrg+-tcH1Bk{57;^GBTxheA{dhfcs(>-c<jmf>OF4V*@TN*Z9m6gH
+FtAFGNSot$(iwq@w8HUS1W6m$qrkaL!>1S<eBd6U=d=rM@|4OzB3{N9HkaF?QmG4kI9QU1UK58H*IRB
+uGC#F4PM&fNe(iFO}>NNGpd(U<P7~9BE_i|WkJ`vEHDt#!##LAen67_LH=s*mZU6ao~jJUjV_1TO>f5
+sLe1mD05rM=X7=r-3~7Or`Kqi6z>akeIhD(jsxYwlQ0y?9k18x!%c-Q8Cm3ocSQp$vV{S;WPsAh)0Vc
+Dt+F<uFvc+jU$NnRiks#iw9S<q3L8h7ZNZwhuEpsFc3EajhWi;xhV1*^Mp<Dqco)1~!LSf!su}@jpK#
+jL<?tX9cpmZ6FWciIJm1Yi8g)|YMfdw}_5d&^wQg1lX5YNd0{T4lsz*pJMKxtlQZBa=ssFF)d*cgdP#
+aRvXfMu~*u%zM+1E4&!=jf<D%3uzFY~R2V13y2?IA5Z%I{@(Ys}`Rm2SdXgDSDi}8XkJ9<BJUKlqwxa
+4enUrkSGKmAZB8r(E!Sw`4(nxbTtIEXVL(=egKMfFnC-4!Yu~2Cd<kZkEYR~9^(roDU@8xthVaDQ0T(
+$WS3&8cMX27bw;)s+&~CcWq6Bny#V}r-|PT|wVL@lntbZamM5wbJ<UqUE}xkI=ZdS=o@|w!&uNxjz#$
+1V5*^{i7OcZ+(a%kM@=m8A5lOnOtS#_p+k8Sor?@ZEhx%#g6DkZtwOZTrLZ-8k;9lqsbxpTLP1AA)8x
+uREMLgX=iIUJ$j8wEAliCcurBh1b;;429{A{SBFz|aQ$EJ;UTbYg(!f{}0Y^KF!UT6|vgZ+gUq||-)8
+S(k@^>Mg}cRw*Yeb_3lu`dFB4bBCO@#<@B9wLL%LXd|YV>Yn+*yM26fggrPtcd%3=B73M>`}aY7^pq(
+E{i*KZ^C5)@GpGupH|>j6fR#%Jw})U(441beNz5ihV^_?E*T{Sd`d3-=7_#H73ATfO4|h4IM$@iL1$Y
+(m{TF1gu?}_3^*aDq5^S`@-ruaG!1(+_6Xwz0Kvrwg1^}Hp2aAb9Y=lm@r%FrE$1&&$SS@}4;F?z4yI
+{N)As>2xWXM*{oVt<hinhl!iaL;ya2G{uGP<G3U>H$5`ClloV1OTGShyvEwyxqXy`MI41aK-u%!7i%8
+6iDWHWUA>09B9IUq2OAVwHJfaw6ksIeLP#d}=Zf78~X1v@PvJltSLv`;;D>c%>>L5mL>7qH~k6L#=cl
+v&dhc|g2eW!OVdRnAj3ULc0l1le?QVivZnu`UP}x6dF@&mGcHZavLy98`l`bX$$mC21t~g)WE=m%cmm
+n?bIlXtBJ;)sdQL9gQmUePGveDz7(H){3i2<u|?uVOO-FYTy(A^8l0m?MkjM5zOqlBLzC$a|d^v)`V3
+js1qhs5)Idnwy5}&3CCS9pi8PFcflm`Lg}{tW((=b<;CDWA1{l5$EbHf#ACdD-;u+TJyk#;^t&k=I%p
+l$7CW4PsjnL;8<rSsQi!t6r8i8Ip4X^KU7+J863*;I0E8s<GG{}F`#vZ~p+>M~)kyNa(iE%_wDkmcP@
+qEb3h$dG=Lar?pJBuI%x)2zHzJNe0ALy}Px9d5N2;_R;`LHlyXQ_h=ch+*`$KuU1JloeTA-eMSO=pS4
+l6*zZEHW6Pr0*rM-fX_?@+anfcoJMI-jrytQJ#TWN%UlrZxhNLCGCxX|=gtp_rS!1=za0i%UAD93)6n
+F0wiEdY91H{&pXP;W@W}T)rPPd$n^mpPUg{uTZIzv!5*ML3?q5DebI7WevF28XNlk8NyGeai4vnH~9+
+7OZ)2Aya({P1fo-7I;pl>A}>Btz!eD?Bm39`u${GjE6J<X*v*qw9%-n}F9K#738u;#Z2hP}d_Z#CCNz
+if*5I&R4r|RPgRpUw0Uvgrgm*)yKg_5vR_M}1)9Q!yt+<i#-W58vc*GvsbKrbpyL26Dno$|PCun$WSe
+N(d6Hzu}^++TMFW*;~9}pm_td2==cm6{Jc<g+6Cq-dO4Zf|4bby!!U%zB}5~EcxEl>?~d6XO~m(iKAb
+XQgsV)ET2=m_yrGntrBO%9zv18Ne_g+)=t2E>VnPP$e_R{dtEMNdD#;$uVffWtMKK$8N4&yQ-%0g`<Z
+BZlAz(74Cf`7`D>D-EkvBW1(`N~K2A)~dEz3Vg<E1_B%J_cs7w=D%SrJc|u82KO9&>)3$Px=0t)oBF9
+!jcq#d_IJ^%L-&mmgs4{u!(om!kzSG#vjEZ;OuXQA5W?|@Zrk)+p!xsHL$-=ZzpvHjFfIN#4Ss<3-mk
+f1TKgW2{cXAo57W}IR$Al3;@SVW`xut4+2*^)dHjO5DJxh?VUkO8CdxX+t)B};pI&oO13fBJLEz?pAD
+$uJxB%xzb|$p-3UOw(<+4}k9L_g$P36^PT}SPM!1}ILmF9Lq%;r)<<rcHy^a$3lcfrj~IS4WewWhA6Y
+oJC#{d#hl0jG`kTw=wd<HpNw1wyb=m8%-{?THkG*<MV*;97-?otw%YHKuqs$uybA3u^S7*cDPjD}U3T
+aK1xRrf$mu+e-KuR(#?|!Q2+>pY(L2OT;>ry0_`k$m+7nuKgz=Z4V-f7Z@bJ<8f$SjdU1ik6GK7#cw6
+$(=Ex$8ky=U#u!XyB-o|^9edWzf6i^Rnc&3TvkM$-J1RGtn<MvhNm{KR_xHW(60wBz>!>v3UtKJyK(S
+cBH=4GvjV9bL@=Rk>;nby=v7?q*420R#<=-$)D)8aDWeJ;E_Mo-Vuj9@{U-2H|tQdrTku1MgnKqrYS3
+BzN1%$8x8OfCcV>4_8XfZd{<HBBwBz<Kbxj<{Q>dO>CqV9l3$FSA?VV`yEh8%k~hb*wO7qffEzEv#*)
+WvvEKjgilzKU>&7jqBlSU_8~#S=ao#k?yz0Y>3^)lIH=yU>=(fJigfdP$rqvHQ&um<EnKPjZ4rTd@ql
+yB9Am?=6PX)?3wN*SP0}cLpMEXRHny2Y@#AXf)RPb@#OnhbyuO;ZDXJqm{XVI2O~`&z{y}|8q~rvH#&
+jOC$oaAE!Fz1B%3lKeC&7G<9ERv;T43zJu&wNs5>=GJWQU1kf0>4s*&Vgc%#jW!Zw&?aDRj5l#J<_Pp
+;+Ax(ob&-yIV8|_fs%4fII^oIB+N!|fmP+AIe5^RkbSI}w-`y!~YjZF^Al660J?vTx)cB!myn3@e%<y
+St~8oTX%C|%zVrqpeMY7{gBf2oV!^kkd7T69#jPn#z6UD}jsbW#*1vHw77yvJdj8z07A_@PYpfLVQwH
+^w!lpW$0CWkCK)W+*mP7qN^(?MD+#_q^ZY6X~}?P7f9(b~hVt*W>02XRny;tz6<$vPONzT80iG>i)!S
+oXQ@Zj4%uzSoVS4&xzw$tY9og;3o9e9fhCvyH*-WP|4dY(s4+h2E73TPfEONmR>Y~9W0+elMg(<xcvN
+?-!}j>C1;re0jdolye;3ewyO6Y$c+Wpn9eR&stT(({BYH}jzI+Nw^D!y-$^)|a2fmN7!uc;K7U3V@!b
+bN(PfLC+wzy@jbz^2MqH7q0U+KA31(jiVO9wKg9S5_L~_1W@CdZCxTAs=GL`J1HyRtGu^JBnJ%bJc`R
+O1HFr}yRUp}r>wqJA|8BFE|pFm|w%)uL{SC#mQg0Zxcei*g2_n{BZeqv=0;{E)FF+-vAR~`Bvhr^WMY
+GWQ}0CxD$rIW#=7s9jF7s+4o)VxJgI1O#v<M{u7MLd4n%uKxa#svJuJ!@xIIFOJ%<?vlSPbS$zh}t(6
+Jpr!|synTB(_t=s|60MDa@@;jKAfFT+<7{9@wW<lAZ78_KaRlrv$KCa{pHQ+PftMOBSgZo_-1JQ_02E
+uK0E~v|7}A?Nc>#DqhvRZ-VmujcrHu=d=Kygb{xj8-q!7VsPOT5=S{mjLyA(<CV>SqGv;DK?H(={IQh
+m(^JyfDvV;D8JkidY?h$g@+dY$^eZqp)Vm@ivk-0s1-T#uUdiuis>_2`IALVUC>qGn?!2t!L!!63X>2
+_1{${tEM9n%w=t`lxTQzxMt-EY&Go<mgUxLWiSUft`V^d6abEnW;ayr=N^SRLkEL1s}ODMnEErW^D%i
+EVE?3}zpIS>Br*f9Rbvju!NhjXg{`IQCqlOPbg^?cga7*EMHK8uX~Wdv|1zL;yEOVuCem`62NjQ-Is_
+8ed2K5%!=&o)x5etGm1>59W7_4HH*f<FHZdpm}rZmn*%Za_npcJ31uGF$QL`RHbXM=I11u)`dX+Q9i}
+G1xKD3htl(FSg*of9DI5>lFsSF(!P{Kj}BuEr0i^(VDNld*v|(9kM{8O*ImzE3K|2rl$0}m9-vRHn0G
+rqm;xQAJPnHjw)f<Z<~JY6YZ|e5sBPoHq~wFi$e^p^6F#cpk^}tI3BS;g9%11(eneieVHiRL+}p(wbb
+9V%Sd3}Z(TQI|E>wq!0PoD@FUM&uCx7-in@(Z>mU%V~&!y?NqHLwg^G$;-TUR?wK&sm5u7|dP{i0=bD
+@2{JQ~J=|*`3+f=9*F#_mBq9iMDdBZt0yh_Cb;1k-`tQA;uB+lGX0TiClqo-Fleut;v<>*LRyWS{)5!
+f1Hx&7HJS#wFoAZZh7IooV7JTVlX0-WULAUc#1dB8@9UFj>qCx(5+!!Jkw%gpTWZDL)zCLm}gB#?UVO
+q;X_649_{iU0~}9hItDYX(jDJ%53ml_y!SCMC%w*O$It%%cP{tHAYqfZ{|it{0|XQR000O897^_9f9G
+GA>i_@%>j3}&CjbBdaA|NaUv_0~WN&gWaCvZYZ)#;@bYEz1Z)<ZeUtei%X>?y-E^v8ukj+lRFc5_Aeu
+|YZ0jWgg0l2^g4v1650U>J>Z^5l&8~;S&?b$RjDkAk^C4Xa$XI4u28ZiWl39^SCt%dL%qCZfd+w2E>(
+_tbFT``s?_D6CWKD|GtR!Av@*hfD=tIQBA@bEFil>k2X^W!HsqBVMR&UOw*G!{Ec3!m&4@sZ6RI0(gA
+o9@phCF4G3uyd(|=_ArFoE)?9ZdNqyvDmCq>9|8rDXCbTt4?3V(5iSXgi<3fft{3sJ7{j(ZM$ula*z{
+wJ2^D}3pATQ%2Kz|v+xzI#jo1M0`<X#3cn#%_sHtI_yJH$0|XQR000O897^_9-D`3fWdHyGiU0rrCIA
+2caA|NaUv_0~WN&gWaCvZYZ)#;@bYEz1Z)<ZeUt@1=aA9;VaCuFP!3uyd3`6hxisDH@2I5W7UnvteD0
+J&sMey&PC}J)N<RyrX84+e^n_VI^txew<LorL)K~JqY+-?tFlq4agAh6WI*uyY%lYy$2e=m$@^-mFsM
+97pa9zJbS{v?6ZZ*l=pO9KQH00008031s8R)!YU$Z!e(0FW*K03-ka0B~t=FJE?LZe(wAFK~Hqa&Ky7
+V{~6=Z*OaJFJEbGaBMDcdF@(lkJ~m9{_bDFOFvi+9O14&(ZZ+?mo&L+&}$kro9l<gLZ&5Zmsy!qNopO
+V$bY{Xl9EVC_GY`;I|PV<#oFR<I4{q<P$b{gQW^42OEKf_yVUJBedxX#wyR5Cv016)j^t7p_TE%{OZ>
+QhvZI1tGUceGPHSqeS`xa|_;YgXo#cX0O=|q&D0H)}mCTveEzz5^=fAu?Tax^W<=0tGtE&Aj8&fxC<|
+d{Y7ujHH`zX`7;<d@FAhTJ)O0rknunY~5$nCo&!J#F2{P=oL)umpnW&}Qa4zkLciNp=h_wyxTB9{dhm
++N_B$|v8=7pOt$Cg2BorbV->9pf_K>ep6`7H(-|dt|NKmQl<!O1RZ3NsFXJ_IX7?{bw}4W}<j2=ndr+
+-Bv7l@jhp@;ZpeJ9zA;W8?P#|WkgY~SwVP7%oQVBH<#p82x)NK851dlrMQyvns`g6z{m1Ky)v*jH(8c
+wR)N|^(VQW>MK3juq}>2n_e4YCUy2)A@#5}+b8x?#drCM@oe8>Q{V!+w9ViBP4#jS2rjkY4F=<I+#X_
+c_TljOD&<4XgTE4Txk6`AXxz>Pzk1&E1Wao&je>6$JER>WGF4ofE&bjqw1JsLCmci*(<Wu_hM6qJsbI
+_{$-l_Cf03!#cUw|P+jiz+_nH~bww(z6jRgvj}Ycq1UD0of{)9{qSsBx-(QeYwv_@hl_vOYm&su2Rrl
+J5%0Nc&>_N(#Ud<U>U>CT_Tr!anO2I|IQzBS4wClHj<KU`|8Fp;~)IYcNfa2h*9IeRc)F2IpzADjSin
+HUUMS8aJd71x)vGTBPmD_CE*(nn4ow(xthq4~cUjm^G5THw`>Uo4NoSClSTM3Dz&(TLS(tgWas*ug!Y
+DH=Nzmd_TY<R<)o??606cAwX-z9R6Kd_-L~^^8cIR-15_=TM}(RD7AJqu(hO+YL`*S7nVb!WutPI8O6
+YSiv8X&4FT3$?G=ziI@F9%%<DJ@GD90bm~*_XUO;#%=HdwL(D90hF~RDZ<-FuD0!4`eVFj^#!(0`$yl
+^RSh^%ffG9?gIGPeOA82S?C2;$@?D8CovS6ADp!0tg-jbY@5DUFk5IS|dsA36&h;`@x0YhaKJZDPwO<
+`(iFS~cv2Qc@+4aDpbgM%y&ms`SV^3;1MS&~?Y&_coyi79DjjVm|>rXJ@nzu<=QH-l6{-r?1Fw07we9
+1tS8Eq2=1`qyVs&{5>h9BCijSM+Esg{T9c7E8p^pn?p+8NU~?1i|9a*Q*D{i8_5f-<Io=LH0Yeu5r2-
+}&95lrLIeGsW3{E2mF-%JL;FEiPZB$1aXB&)KE*WyH5WbkF)MX5dV>s|8%mm-2a7KUtS=ViFY8dckB0
+#lninjDXbTA6e?=npJq*?>-^gGc$Hc`{7m-i9G!K5r+oWcTTo-Dtilc*RyL`bF%Z*fr9`EB4*QwT4wP
+pOoK^0iV&s~M}iw}l^?!+bOXxOFkiGkVzGh^>r-WY5`1DYTb+pxvY3Lr&yfsiYLC3C1hnhkn9dCeva2
+PPZxi<EOL<2jhmMw0@ySLA6?aLit`a!HU0qd0R88p|-n&)LbXz5>vOrN|GG@89%~ezlME-#0$;hx|t7
+T}9T%WqfMrNo@Cb%6gMtftd61K|Vkqt|kBg@q4sIn#FBa?_QWR$f59X*i?tk!)7`B9m*Iv>?neP!+A7
+_pJ7FfrG(w#!aBOfEl|{~hfFR$zQ>OU$MynpZ@54`+>PDh^U*Lcg57-DKZsYJq8~kT&ilt;tB=nx?~M
+C7*JHaMahN}C-xm<i#YGRp{Uwx=>OdrvdBuyi8TNqck$;!4Nqf|#DXd(uCtK)2u2(Cs<1DhB-L2#{Pl
+FYv6L^xQ=^~nCckRK{bZn0!eeYs5LLqRUj6W!G*nS=X%iY0b)FEE{z**IYQpq99RRfaa%u%|a4s|=ct
+Yj2QB-0iVF%o=(hd!=wPX}F{tbKZIr;&~m?f`==UmDuRmtiL!`XEDZB=ZS5=1cO&hea>yCAbAkH&hj!
+0TMHpS@u_qRUXBF*OFgmni&I_)Zuo-Yw|B<2<>Y_!D^6@i5zQ#XKqW9OIrwRO6&>&JXcN$4OONy$Es%
+aYSXbhbS<~i<oj>_`W@oCpKlH|TiLni+Ng^N`Luv8$;t=F|EGT+5M%#kIZ?w32`XUH0b6l_t-gEnV<B
+&FTjk!JP!aKhXf_9@#=d<;Vbx>BG`f#@@RWPdmC>s6fv4uHq3=5K5CVW*D5flfy*Pz^8Xdu4+)a^=wr
+fYGaS}H}87L<AS^GX_eWscLl3qJmz|5P?;}l<YJmI30n+?FH!X1+}e7m}DJirSOkncc_Nj$y6H!*(8B
+-kD@Y_1?0z?l%q0b4Fc$%ud$V^udBtE{2WZTckL5{>Z)P<#j^P6H8loU>T`fz82^Kx<TEuE1sCJERt<
+RA0OH$gNM~RF8llH=Nq3n@s={;A|zrO|Pw6t@GTQfgBBvFR3GbcAI^_5V;M$<1iU}6e6W<!N!A&<sGA
+JKtJ#R&<~z0C&TiV2($xt3%{{y6S@4E^Sbx6Jyp0Z!bUB(I2v(|tBW>(&p?UIpkIk%<t21Y2qSy}Vo_
+h73Z6-5?y0sr&Hgoh_i8xYFj?jB&E#rx8@M*hiBR3kri#O`Jw&h@jv@tJV5dwAHyL{eE*o9BSG=Y(l8
+cI5)||!cAUG#%*F|1$eh4l+x%$WmgZ_F95lj~-{&>qXLAyQ`Mz==t$)Fvm8$|42<i6oLnH?tT-DJ=ns
+n-m8BYOh%fE^WVas4V^daL{NR;?BP2klh{i!UA4mk!H+raP<_DMy>EI7Fg`>w%lB<MHx2^;xGv@qt^d
+VdDP$o30^RKWX39F`sC?;z+_a>^`km#Lcx~f4cRGUlxA`ZP@X!{;WGOdwt?z+c3MtgLYq2sJUa8V}<-
+wEza1q_WNxq^GG&yH(Wk-5_DWoCBeH`^`sF8$_D{57`aD)gys(f8{A%6lISWQexgelkSYF{zkc!ho4<
+XVJ$w7|-_NsWPk;F7#jEGA^!VKA!z|2Eqw}4U$4&mcTC>_6_m5`BM+%XY=bea7xa{@QvmfUdqdQ~mWY
+@9zTbt>bKUz6FZ_S?AYlNnV1-3@xqHc_}iZdM8!F~A<mzMtGWIt``u5cy>ip$(SNs(f{SmOOGCd~TlM
+O-$&!h@RrIw9Tz4bGC{6;Y?DtDH_5_h5XQ;tqM*bCdD0){y?l2}d#_#Lv0ox9s6<RN^FAEFu(|;$k_;
+0x$av4;m*4;~P=YuMz#g%61>K4lkVcZt~ZpoS$L{0>tfp0}^O5Z~9An^NB+%cY|W`W?#>vyG#ceV}5c
+qA={8UzSzX|)<3gU8$tfI=&kFuH&Q2^6yEh*kMqa0XQP`HqqHzR$KO0%kM&@9fyHS(fs3PNuvqnXM~~
+Yeyp7t=_0zHr@ACzLmSEy`sO97;3Qj+tyB`^tbbc}WFHlPZ1QY-O00;maO7>Q$^@?N^0RR9Z0ssIr00
+01RX>c!Jc4cm4Z*nhid2n)XYGq?|UubV{YjZDOX>MO|a&Kd0b8|0WUukY>bYEXCaCx0jJx|0i4Bhi9t
+TG&xP!|?-8v{GT?NO5Yu7<XbVh6~-Cv8vFA()6V#Ln~kaMLuWfduMxAlXM3-rWVkV{lmzbU^4SVNgzG
+LGcVyq>D}mICBC^vyF)ZN^KTnPIcghM+VMg52CJs6Tm6z`iLw-eyjov?t`g92G{c^%@>%s&m&6Jc4`&
+_zLMeG!$g-sfu_hwJJU3cF<Wu%jpVz8!Z}qti^^UYqp2JX)U)@xGgTFXUjd`SvuYxr6<<=~v_bFSwdh
+b2KXy+Lc&eev(@0v@?;g*4d@CVQRJ-iuzTL(*HO*<h5nTb+UiV||0~~&?@X#6@1&{xiaAKEe_dDW`*t
+Zti?u}_)X@7ZX%{Nd>0|XQR000O897^_9<n%PeA`1WjuPOilHUIzsaA|NaUv_0~WN&gWaCvZYZ)#;@b
+YEz1Z)<ZeUukY%aB^>BWpi^cUukY%aB^>BWpi^baCzNYdvDvw5&vJGVxhx<R4Ox<6vY*8RlrH)#z^7>
+u7g9XxV)9PvNoo;ESHq53-aA>W?x)Vlq|<?P*ezFK4xcTXMXe8UH1F^%LSJN|79z2!xH#QD3R4PFT{*
+VNlHOxG)+mlU}ReHG$B(uyJ1;E7DC*}sMk9y3A@eNtdz&SBl1!#mlWQnJY$3w*Ya2q#u;6*A(@G+EJP
+Y7ya3v9w&I1zmMkmDiWZzsQwB_k`h6IG_|vnW;};*#-oA=ooV<K9K7Ta=%3>4cf@kHi1eq;bO%;DQxq
+Lm!X}ORjlq{zOEn#MBUM`4`k$S=M0Vv?9^OR?KRYsqs$WVhL@}+;XM*aK8<VzGqU%&Qx7fe>Eo~A!iR
+HYqiMi#8BiY#8y6h`CVUccY(@ntTGk|;WJEo6PA6tlMlvsZFal{|HK8#kgX=!~H=dh<do$#p8G#Js|5
+{Zv0lxqGGm#7mJ>DbqAYw59kg5Cf9rc+u<qKomsgJY|TJqEasbBeR0%<&dDWe>Fqb1<i9-$X}5%6D9e
+L=SPyx!Shm(H3Mcmo26C4fRvXkMq7jf#iL*}vG+<X%Ph(_fU;h~=Kdft{X8V7_K-YzqCGXx(9wR*Sr+
+Qo!8#Zcmd!-Mv+Ge%mGh%N2LqhM++vL=r$kA$%r)b=$JNNL^+UEhWZfl314Bzo1x>;^vY(|CBJG8atB
+)C7QJ!KfgyY*8%S$dYBMwk>LAk^*1!FLX%nYq;0f8Z^nIPP704g5GJmX~?Lnx#$F9(}JtrotC+zT@Du
++`G;ECW#UWWQ#fA||!qm_0fzA=A)n*4D^827Szx)8;j#ly_W8F!g>_sLDR5#Zr?itgSIMF@;ce%VrQ@
+@B+1-L#ji~_vq@f+2~wk4V5cEYdDA;y`vm7r{$i*#N4$(8RiuVsWSm4A;z4}n~-K8!HQy2&+(GUQqRz
+aW-4Yb(Lo5~e6IP5W%cOD&dYKJ4NUY$nJAVsDp_bB(5b|~PK$w_hGTZf*jjHr*x=ui&7fF_EHBuc--e
+Tp>0S-UXjI=CBgLu^#Rg(wZIe?D&Q;Y1Vr#o(+1dX<P7<tiM`gikq*^JQsj8>o0M!Xn^BmKz)>w@<BV
+v^`l@*w-WYIM%!=R%Y1$z46E`Mx|9d-*5r=CHATS{Q+(?v2*c^Ue(%K^$LHaY(33P!c~^b{S-8%j=su
+F@J@DO#utu})?2kU%Q5b7VP)DN2rU76!*=K2VJ7IRG^fHtI`g*=cg7B9)vel5tUp!pn>pvRygQrJ`sK
+D5GTzTta};euKgbjBc83LiY@RjranMAzBf3ajc8Upg{}*iLQ*<mSruCmjJe=VUuOw+><rcWf9>CfvU=
+!(f<fp_v>j{+t=)^HZeK^Rk9=o9zhhel+hjmOwzI}>WZltG~;pl*@hNmG4u`?XwE3SWYUYT3r&upk#e
+abL#WgXMb1zY$AC;XekF+X)HDlhAS?%27Lb0W4y{WVAhL8raslZY{11&`TB-CF=%{B2FA*3)WVP~R66
+V{^4m#mk^+sfJWo^8mQd!234oSZ$qVL($GKjD#0k&JDzCA6mF)DZ<F4%u6NH8)6HyRDs3&zqA5IN`9v
+1BDyAz2&yOm*bSgxbh7-OEYUlBSU-SGFA6Dv0O<l`sPCWxqzGD`qZ5Mf;TU<NgF}&8Jn#+M%zFX8giZ
+$+q61#4Sthx32ZfqZrsS`(LxM)$2Q$8LBko4HhpUog}oRTR?Wq9EGdfYT@TIh4KQOmRQHO;o9<w^T=I
+twKt%qqzo65m{}}S%s`4#^?gJ~Nz++b;CwYyjH)cfWp7J8bn7VvlVRRnFZgUhu;20fP_;NxednV&{m!
+W$;B`|7Tl48ET7FMGxC0{xxOiY%EoVaLsr+mOt7gd)9e!X0GKKb45z&?4iJ2BafXo(9uz{oDXRV)+DN
+`~lWqlY}Nmwna_Rj=i!BV!OS*e$5ixf;RZQE;Y>?8Q#Ss7Er7?o<M=OU=-hMg~Q*cBBGC+z>-KPX-P`
+~Gq1veKcU3GJ0lused(uEtcLJ}5|g4)Nb5Q16qW9}=ruDyk_d6<W%6=yiZ@-LmV&aJxIJwQ6P&{Ix^T
+X?b`AI+gApiT8*)`+HdI+F$2H9++c$y<c9B$8XhI?lOLNa`9$-0VcIeypy*V<C9naG_MtDU_1Q;`fpe
+T&4pS4NoAzpc<x1f0zu2?x{HsH{0PZmA(AGnfFM)(+t$^8@%$9{xGjc8v+b{>jGPFafop)!>#~<Hq+k
+&&^Ja^%2qyo2`svfvACAo5Pqh+HgZ6?Af@j%+Yu&Baq#Sqh<d(&;Sy#6T;%-YR?4OH{sn11~C3-F}^}
+fx<cc9S8yt6QD`PunojLXoO-s`gi^*Yk{!7Q^*ZB9hX!;7qA13wW=)k!b6Dym?68i9gjGhZsH;7Gmwq
+_-dq2wHoicDn~RlsjR)jo|_A+fMxjZI1hXQ2#GQ1&Mu0iyL$Vw^ashsx+y0rFM$*?LVk>HOhyUmD;?;
+3D!!un87O14j?40@rZX3)9wOiC<u<av{|y{6dIS2W7p_0+|$WVS9YQQG#J301s(V;fs%py(;HQE%AM^
+@jiZ+fX24<N*Kkl6fu6W3?4Ia08alvWO4qi?tw_UNQ@zz>X|Z%>rRO*pjIQaLfG^CFbBXp3^QONw*G_
+B=x|M3+2$L5cqwD~$<sLkVU_>xzDCT&0=mm3v=T24P&<59r)<7P@T?u0ea#N_5UIlGi4#cDoR!+=-{E
+a-@A!}KsC5Hyg<NO!spYZUE&pGbWumxRlQ56vhT174Rg{P@L{`1=8XoqH|KOf%$;L{C(N3~2J(N66e!
++sO4p|-C@-G+s~72jOg<5?tCyVdQT5|b#;<}Lzocdi))dKbN?jk<p=<~rLU3^85iTA5Ge8^U2R0w98n
+RW2x28`t}yk|uHc@sw*4jJy<c&3%I0V#Md+9aE_D#0b@T9{MCh(lY&)n{6oA+}Rjzwk~Z$)@q@nd%5`
+F=BjJ<KBU|t=y6fy7C{}mLyw0m$M$id^?-HGH*7i`w6*YHwC_dyx1#=@$oI%q|NbqIyJJsNVmI*ryJM
+`T_g~)1)aS?Xt7^I2)NOvp8S=TnQ`Bofj;Nq%W-Ev=jb;qOdVdPdVcGs&lpiy90P;R(5ScsJp9)+-m8
+?J~Rg&o@-P%+MlBA2-V;=3-iBcm={eRFpWKW4zOmr&z7N{8iHB-)k>iO8Q$6oGmC+M;!EF)W37_^huE
+~oB1nC!iN|Nc#Ue)4Yo518>6#V*(vhk-75!CgIurR#Wf$N9hk656EQPxnP`b7bRD$FU;3`f4D!q|jO$
+yPMt?&$VfBy&90el0SNAhR5s{)<FGp#uB;r12c0Z=YMTsxlW$x%;8b{Z=csEgl@3<&L$(ZYrB;CnB8P
+zt&`6&`BC=Ck2Q;09kaBcsSF1b_x`F^>#IISQ+pxqqa(Hc@Dv6>*PpBf_COqOVxh)<391^l!Li;Ng;D
+j#Y48wRoUhwKXxU7B>MQfTO8DeSt>h%opGgH*jp*Ax$j8Mr>ynTOn+}wO%c5c(R4&>S5vx;Lhg5U!zE
+h(8WWaowv`?%hWmtfWX!|jeCwNDW*r|c<nTJl=-`?IOPx;Gy0kuz{A&DI*jo>;Cplo^HEa7PHqdd!KN
+V?$aeJ2?Vh7e7-zc_l18IxlzLzZ!jAN&Myj5#5W13ej?AbP(8P)h>@6aWAK2ml;P_Et#W{Qq_b001!*
+001BW003}la4%nWWo~3|axZdaadl;LbaO9XUukY>bYEXCaCx;@|8Lti7XMv;#hdzrWk6M8r|1nv6QFC
+;wRc@wB-x6gC^TAPY_77XkyJ8o=>6^ckRm17adti6&PZ(W@jddr&-=nhJtCq!j~)>n<@prP?vJ|fobn
+_4gXtqm@RU5J<jDO!Cd-Z4d}@Wm=O~KeIF2s)Z!OnG)9dT&_w-gQ6;s>j--kZYz$`Sex)Z57k(BO~Fo
+xG8YI?slYgwmsBNeUN4Oo|4)GM7u-!Ux;`u_ZyTFq8`5k*kt?Cgxhrjg2!@;d~wqSKz1t++`hYhxO{I
+6At!yUQB4PbSrBGVLWYZJ23wUdWPL;{5nH%q=IKW=?-<lw2vc*+4U@SiNeY(8Q{*vO?A{#aOv()$%CH
+vW#HN`*&B@gU$`xR+5!au@r?#KJ)GDbaKn8md_?BVL120`AEI7L5<WSi|p@GICGBd4Av-_VW)nZeu+k
+j+9WD7{CDGse@4!u(6M`nf%_(21Ud*-H4x%Xxi}q9%=?LX+|j?JI}3h^qU$v$Y1UkIKHqSlSOP=ENw<
+yl953lHY0l}F-a6KZUov{tRuz@9Xg2_q86oS)qHpL~u)7yfoR!!F%sLbDEQ_K=A)BodtF>8BQcU5?**
+|ExrGN3dh7NSeh4~|k7L_P?t@(nUH>`lJ^Xxcv+Pr=9;{4+3+(qI>Lfw)ZCMrat4gSbS-5pc4jn62$Q
+F23#XtMm4*Cm8JN2@9X`iW=A`0oX8tSve)gw%M+8wm2c*na31jiO@Bl;$R{;T2YiKe)o;N<$j4a3O1i
+mr>h=!+d}L%nC#2uuUFB^PHF_KO2Zqrx(3(%;!o;)h)Zn*Y6vZ{05V}_>6SfG;q&SRKjc%Z*LGt_gCl
+$hpn1+d+sfPJ@+V?Zm?GpXR(W7*rWLXbuahLDSeDfej9%xdPF~QC2qEX35i@!08WjZuPVf#!*3-_=8_
+crR}#T0He9E@jI66Ia?nBq_u)V61VCp`vssr#;)W_-?*lQV(^Hx+LjK${i8a>!Nqh{Oyaq2Uy#3}j5O
+<*NcH6LDrAi64$o^oqSl<WCu2#$6*n(btJDdHDoUIRTW}0@-cG^EXo~hR@Xmxf<vur-gW@AUV72H$+q
+@w_V*?>S`wp&={`E1wl`*HFR2I6Kv%7$GI+quU+3aF2ZlTZIa_$xu`Y}rpB7<!T&XY-Vv(NjDe@8gl2
+q=XtYpVG5aN)Bj%2}+(irsHlWUU>u#r`6Yhaai*IjLV*PZ46jMVBeF2$jrUbe~ZkMU1U((`*jo(n$vk
+G!AbnHY^mnRew+sOj5?r{RMc0}P%LbUx&oN{3aGY?u`NNf-X`P0USWgPqe&<`%TBT<ZmO^2uIL_E0{B
+)!TY#GcfTjnTM*f<50J^&VlRc$JW!<5{O{?mt&!9t_KBJGbln{|mJ`IBY(1S+tyQ=Jqpxj-9l0Uyp5h
++_LSPR&7CGSdkS7&i%y9{QMe!+)q?ir^0d+W?TBz}}We27|4g@V$Zgz$D5xCGaSYD({nLkHY`1<yt&>
+wk6HMV)2dL&<X&<e)n@r6ZU5=-D;BS0fIk*x@}2S35pB5YdjWl-wPF8<)Fm)QrW$%3jfL4twl>V!y+n
+?<ybmW9rd@GoRzKumNI560g~^;z5%MoQeEgGWgnh_3GkHunS@capX85h3gVJhU-U<gy(cp5C$)VCR$g
+Mp0(>4*e&`%yYDDa9-%EV=pwJzXi+P<!d0bF9Gw`NgtkFcmo{N`(gPXuL7-E+LxTa`LU8)!Lg7PUgHA
+{-+uH3ldME>2)vU@|V;j>hOhdo-;myU%cOR}ocGt2e?bpLm&zHnln8Lbx0dQQG)Ghgd`o0O<sbF3L=#
+8t;z3$R}z|(h?BV}=AW5%ci(<#NTpI_y0Oq|jy=*6dl_`SY2gr&WSDX|QyG+T*~vI_O0Jt-6Que>l8P
+?>xAWI8bR9myDg{U~;d>~K8Lc^@it{VHF5qCD8KH#jYAnhZ&CFPSvywQNzkm&gZ!X0_mDcJBt$BYFSM
+a^SAgS0@dgir<I|L6pQ|g~aFZ+o8&gCL47M2PtbSW7B43vt*3~tx%_s-|SWjRHO^p6K`Z&m+?>w!$r&
+scSeMj{M-dDlCL}Ya1HCD0<{8{ciZFJ9P+bck9o$f^yN8gae-B+bh~4|K}{H_%T`q7Ff7<-J{pCa=|C
+#EE|hQ>4@7@89SBC4YBYp<hQUyRqp7z7x9FgK$t!MnYLhCZH7?63$<Cv`bHb0*m}^>m`D^uqH`We|7Z
+Nw=VmPqI#B1D}B$jftSBS75WXX3bxqTZjlKbb?yNj3HzIYiCFQMqpO8#`{8@P_T!*VU<53Jr^@=_=$q
+C4u3mv5~sNacXf2D??gQSWiDW0?1Q^eu&b&<(8TUQBbX$7o!2WBb;?Jp{JlT~g2L22te0)4r8@i$|nM
+p4V&x*G@B5mOfOIQP?I^mo0lpYFbGg4LBRPJFh|}We+8zpSM+X&nMJfKTqvDt7-HXP)h>@6aWAK2ml;
+P_Es9QMfn2(006TA001KZ003}la4%nWWo~3|axZdaadl;LbaO9XUv_13b7^mGUtcb8d1a5yYQr!Pgzt
+We#W}PWE3$n^DHK|I3G@<5dJEX9yop3?$<<G3iXXmG<TR8bhTWb0*g*>*1-S~y-?<>!0;XGlsR$wyoL
+}hMunldjfw&2;EuvbIYErOc&9bI(()HLh@Bq2N50BQ_JlGvtZsh2sR%y98IiVG-x7!WuwSl!Cn6f0Y-
+t>tP&W-kdxx5@A23h9>cA8rvb!0!$*x#EKsY^nm{qAMoolW{htGc8#n9PSrlh7Ab3Y~ygl<qsfE^%OT
+P9N~`m?#q=qRk<Kz2vCu{Kcn{ae+{!RIbO9kq6<@^7%5tzckK{^M#$SR@EKs-YBKzzFtvCPM-Y$P)h>
+@6aWAK2ml;P_EyL!%;|>$007qo001Wd003}la4%nWWo~3|axZdaadl;LbaO9XX>N37a&BR4Uv+e8Y;!
+Jfd5u)bZrd;rz4I#uLJx9b=+L8p9Nb!M4K!_FI|Yh3R%mG)v6V=bOB|ugw|A(;NgO+<4w6W|_hx4h1W
+e;khsK&H71E-XyiA=HrD1=cJd9mvbtiH(;E#oEVC!UNg^~tr!7Xr&kkQIjn8Tn|Hn3@6-rHciLSzNxS
+fk8ANx*xnu|h&^apzYp2?{K0)CNN12+j@ZRyDUH7LdcDs+G2&k+H2-6-3=3^!pnpN-Jb)tY$3zI{7r4
+rXQ2ZG?}NLC+A5zPtv#FmI<7ZLQ54ThI$jMuh#L(T>H0P$?Mmzg3$^3VmUux{|A{CmoFG!Ew0u*_4oP
+(_A%Sfxa<*aHk~ZL%ojZ|JQ>j#PFoxu6YS$Sq3BOfO8UbQdnQS0zZlT7X)Kx;P8c1x7%J~kgb#)NVT|
+Rt1*=lYt++$q4MN_A-DeCaGnLcdS-?#uL@<h5QEIObgqFaeLxS3T$IOl?<F{PrB^m>YbekIeo^_hKpV
+MEh(V(>4&jTS^wRS3c9U*Cn(0Ma#b~1x6z-cCO>=(NNsl&aD#Ei^x-9)e~1er5_#0*Rp?`AV_vUSR;k
+_L)Q=$$Ya4bik;u?1m-G?vQ@_bGTZCw=t(QO;5sI!wEXrNQIJQR^#)ga6cb9@1sSBl{vaDLgI}CT)`)
+y1p6@NuMGOekCM&Uwiz%0+MbAx>qcx5c;6Af@_`;$3&gcxTcNDQ(#b!4~48E9%erxICqBb2^;|X=zIa
+BvT)JZg39;?Zisr*B{SB(S}|;tDxYMR%7Jw4Jj(Fk!Pr|Kb*-SAha?W?QJXmohaTJm`V=m;>wLre3~L
+LQox4fPO0-rwKBT<oR4(=pP)h>@6aWAK2ml;P_ExDs2p;?r008k!001BW003}la4%nWWo~3|axZdaad
+l;LbaO9ZWMOc0WpZ;aaCz+<YjYd7@jHJ7N`Ek!p{};m4;@bE8Cg~uO=ZcI<aVZ+%o*f?BBJ9Ra}Uvq$
+NlZyT|5prfRtn>?KBN%Z1M0|EcT7X9*4u>pb|f|qHgMhXMEF$svi8S{}~LfR<dU6GHY|e7G=?JS=6jq
+3D#7+s5fQRFf$#RdBZL=RMyr4no5?5r7XmN7a3c_Y=nT23bANpS=7m32)GR7nqZZ6vf<6jJl5snMl_5
+)VMX~9pR#ZN^z8Xyu&l~8+sI9l-ijhCtE8>+T+Y8v#D|605LBiC9OY##vbSZKA6HdbP1uoI`AV)u**4
+Vp7<k`ZUA?7AjMpr+Pmcj{Qrz-fX5R^(2?fS$c?_u0fWhaqTySjuJI`C8wn^=8_=gM8RCi9(nb;m#(m
+U;MtFkE<hDd|)V~~KkAMQGubdQe#ashjHc`|_(kglQ@j|O#ldD>xP9(DuRfNZRJ!LNZCW=GKUMm0^?2
+KSTV^c1G-hSN4OHvsfb5Ci@7lD7--u*n-<)#CoOk_vg-(GMQ9W+c3AR;DAJ^I9%aY)b1!(;-=uYfv*Y
+28MvfR<gLBFj#^Rumj5*DJ*Tp2T=P(lj`QQDbpXh0lG^*qY~%qp=$H=z-uC*dUtW^HC`@OV$HoKJEW6
+B_3X%(Y4A0}2#OW{1dN`@9RXG1s5^mN?V@R`jx<L=#1j}$)UuJc;<a2fdMt9QN0Qga-yXg@y-JS`(^v
+1#UY{PPZx64&Q<xYU|138fk)>!3Yt?ft8pTK>ja{=S7G(wuR9!2gpq{m<#0JDCt&v<JmCLjcA`_YFtw
+j!ONJ+|73%~`FUGZyN3du15N=>P2r$C}-sN_6Bd)+DG`O#l5i4j_v21-KM3H1}Xrvm~E3x>l-U-9a?p
+0KaJy4m8lu|fhr6_>T}<zO^?BkLMS0Kjm+KoJz&B^UyN%<6W7%O*qE(ZDd^?fLoXt5fJ_Gxjadfxm9g
+<;g#fq2u{8+j?<)b#Zch360OZk?GaRo8$9$SI}`*g0~wC7CEnL_6nrpQ29rNJvh57@SfPtuB;2yL&y^
+vdZei=WRs>NVA0aqJM05!Gfr&(xSIpwmyNoSFmb}Po1ZX{S;5yc+UA5cN*iW~?u6ZnN-pnaS5*rS3sI
+SNlnWpuJrP_75y18m)~i9;1lSCbY1hxn`Hvt|3F=r|fi*C?V>$*F#1!W7wLx*pkTg@G-1L1P>NmZHm+
+#qJAirVL0J8^DZFb5=C7C3ikJ&#~0s@x`V-nR%ag1J@f}0p1O(zf1cjcDlB`gh~wp=zOWeBVm)vaCuC
+}Tkpdw9bEVHhdcwY){d+sy=B1ZT^<<iH^GS!`N~<@EhXM@VM*i3bai&rHvleWSnCK#`{1<igoQbGH%Q
+7HAz@hKBWbs${_1=&>Y<0pj2i1urHHg17BTE>>)T5-b(nsuB#`R+D!tG$aq@jyg}lDV|=EkjbTl&_(E
+-8y6HTv2KAsa{)srHuS)j(0X*p=53KdgbI%kcJ?=hOL^NmEbeezbpYahE5R0``FAlwKy!?7VP%m8GNH
+A?gNdT6+gT>b-Er{Gh~Q?E(-%kF5?70QX6>wOz(VF=tU)3(6~0&vUtmDnHwgga2-yQc_r`?dtlo$PZU
+-nR)^+m0b+p~W$W|Mrkz>Qgo)Me3GH(umT{zm<FwzC%7Y4=|Bb8CouSFp$o*yXI!n)OxF9gl82L}j7Y
+KkI&WOU?MsJNSPty1`KiEGqsP7#pW1F95~I54Z-LJ6bujN0Q?=DG5Cb<1;L5pa9~ss+SAxQ%0rE)`1b
+8~p_|O~C-M6QueCXi<WE*Lv4RRzP!7=e(ngT+y!QFtJ=3QaMK=nxb~k!L=m;v^D=w%b$gU1P^lEt{sT
+ZVq}T<Es~n{gVQ~DFgwLSlB78fPIoiGQ6(+x&daRIHqRJuK+HB^^+BxAy&#=Y@^NZeC<Rz@nFDcOpIw
+6aEN|Kkcz1Qgv(Q}R@yO_q#hAGXD}=VP<_L?%2ka`@*cGoWv^B&*XhF2{DFc+SS9hpOyv>_QCw5s0m=
+<NjRA8-ejp3EBlO?+=TZVBIy9Q}%b6y!k$jVzK5!jGPwG$E(3rktIt<Wp+&PD6UNy`LS%J=UnP<?OY4
+N0<rFBTS^x#3LSfJ+D^Wu60dr=90hSh;d$*heEt552QFL3~$3I5wRcxBc?vOM|GPztdAg2xK!0T3sMS
+=>~9jfXN*suEBAHa`v@5wT7U)Et=8ORnu&yfBfT9@SkI2kraAq3W8YGX$q@+-x){;<goLlL)hz5Ub`)
+6Uthyct$tw#(NH)45DDb`z|21NSDf`j(B4qJ{+?kj0eg{a4;G<33!>pkKh~2=7bu&}SPyPD)NC;ECa4
+3~=-GsV7Zrq#?Ho90iHAW*=zs$T-IbEDN7+Pi6=r<=<aemEygBVt|Gi<gog7F80O&WxW@vVq(fTnqQt
+9B#;Y<$&!puonjQZ<Oyfr3Dt7jd&u`88uZmb*dcHt4DqQISfL{*yN`4Yd3)Num8PUw&`CUb$$=w8%5j
+P`wU7pnb*@FW6H&U#Pa^jth`z;sg-2hNvgc$#HTJ&rw9fwj91`0NFDL%t`P(@s{05|Nzcd_B(~)@}=;
+)kK?NS>wtZxwwG{YVHQlyF_NEtl1tz7dTg8PL9ZfTTUnx8;$#-9@3ZQ^(8Q1f2c8mkWM0^Xyl?VdKR1
+`CcD>E=z2@_;D=@f&hoUJI?zWBlqay9ghTz$#4-~bISD!E@TgML;MvN|crkR}7{x(22d<gY6&U9OmKk
+7$&Qq#rq_aF9Hkct+Q7gox5J&*C+Bvyf9Z`1SzYYf-XT`qR>&srg4^O*a9t=9beu-Gn0jC3oS7eEZ76
+pWDl@NYl2C){ug#gJ{7&r1z9G<dc%x1A0aknii2okI77DIKq9mo(PX&FvPA*Y#TwIdj=g5xG&FmQ|1L
+?wAhgMnf98|??%>j#+Xn3Z;I&&-uwUtfVq1goC8I^+#8p5Ew{*Qs=j{`WgP9h=0I+B0e?P*2+)l?6lq
+G$2U30UuOOr_)R)UuUx**YXwwhhY2$)Rp!zwdeagb?zW4@SSvsrVQ>LtQE?uw3Sv0S~k#%slo!lc}do
+;8<Rg%dlrulay3h8!LZ)k6O(CAGL3wPBfqDoADrOMKu+><OF<TR!>XybvRRFWlrtXod?JcL!Pl691Qr
+sNW?}w&L{P_%#SHqwWU~hZKTb+KhS|)b7|zrv&&-!_NT>We+;%X-*n)^V55~sbdpOQlbiaRJaIR+QTL
+z!fy7BWl<KMSEm@VGwGw<ntlluK&TocO41d6IjRi<^+#bR`WXY%<fmG2wyzf%vGu3pMBd4z#>vLZc0{
+ojhGlzonbPwL8n!7}ASQfd#aj>?3<<^wwoAQUW(226N&aT*LWx$@sqf*f}p$%89g<H4AukTq)7F+~Gr
+orFVEYv5r<@(Y?_ugu)eC+si>sAMS)bS4{Efpb`{>m3qr2B4yrK~Y4x#k;I&pmffvnhAX<IM<BYJ3n?
+&JBr`zj`yyD+{I^I{E~<d66Akmy2l|FDuI7~NlE+AM&f5VJhCdhl)wa#pH?;)v6Fa#Ot_3z@-bn<9l)
+fzYb61jvX2J0PvQ99UQrhl8V(wT&SH3Ue1U1Bzr8!TIDS2hQpQk1)|ssK5kf)dDGs67UJvyKh7PPhHH
+Bqjv%{G?wsUrVc07y>>@c%8sC(A;^*|~cKaCMc)|m6<#X=BuCQc2<PAcI#OPLG3(eI!A5FZF(sW<NV4
+-ckhZ;5;12Sky}J|wgsG3D?^{X!~2w@1F|WeEP^YT;oORgTzhEk*Wi)(rZE_X=S39%Fkki|*EQ3`OuF
+Faw29*Zd<}cYy!Z8$bSdg<~<fW1PRO4(L3;X?pqI_-_h5>~YJ9jnqILygc?;X`&S`ardi4EwPe^N0&R
+8)1kUVZG^s1)+7j5s5gFCRQ2mH><oQW3>Xk~`WDR0R(80_@+VkGlh66$2606VM>)sHM?6K(OsUYeP8B
+zh;@cH$25-$O!E4vA+r2qc)H#q6rq~UtsXB)`DeWTihTjNgjwu){9muXiE3!;?qKQ;<je5)K!LaVfPh
+)S{OVKb>kQG_Qbm<dqv~+9K$7vkGsrZ(z(&|m5k0`0T&1l`~c^Jo$0QVC*Jk0MJQTNP@g##nh1s;A&G
+J!l94clgU@aN&aGh-ZpOSZ!dR99@7sW~LYb*^olBv7mhu_KvocTJGH&R?X;A9i&~b-7m6%>X&VFjFE#
+Scl!tX+s@tgR`3%+F49wd^b;9Od`HpaTQCwxp{GCWk2_ZN0x|5?9OcuHjV$ugPc8k0s1-%rfQ(d2UXx
+4+PnONy14^y>XhM>OIw^nRusz#kUT*-PCskb6|Z6<H);=6(ro6HQjT0+jy;W2`NS}vLb;E4spd#0X6a
+Bh9EWpLrBt?bIF^3Vk)s`-tjfCC6-)H$ZsRe<@GTs9VK86|#$IiLB<}<RRJP_h2+ta*9gm)ds=kA&4+
+L9FD^?6KOYRGv`Zsf7Qi(F#5lWz3*-Voj>u7P8e1d=bOxhE6j+&ylWeX_;qvJ678y{ih4(2gUjkOOSK
+MotS<QnxoA4PHRUo`ASzi*3h;Qi%fuVszuU!&si;!agiftKle%ns^NTUDZH@;hDfLjY@gmt#`m$ZCWG
+W*e=qn|bXLUplFwAmC`+pm1w|>UbI=qy`9P<xq|;h<4|;6LpW&znE1yYXi&DOxp}1aj(SID7;6@^Eti
+q(x^yGr(l#lUGp0w^AMB+d96LN08S`&Vrx-j6%OiESM>@#RoPyzz$H+DoHi2#uFZ3@qbrU#e-<2wCmO
+(nonu6{l~@YAwZco5AF-ngLO2I7Ec2l}nnHteVHVgI1>MH8IPCw`J<P9AXly;vVb9+vvruDl$9zR9pl
+zeOSZgoq(EH$<8ZkkSx*8)hzRR(?p{$c*b)50zM0Gn3s!kP%EJbINcCn9I8@HfA{$a*+me0;^k#8y8=
+%fZ$RaS4|?{<J`h^jK)8cCC8^etv&MHgD^s;S$pjYWwdDDd>+jf3nidYF@Xu>Le+(7jhGJo*Rb*~Y|Z
+X?T{|13}NyL|%#jLBS9j4W~KCsPMs5vvzhgVTWYeZ(k(Ol-<VaM+*rywnBlQJ9U!tmYjMnma5zx%N#4
+2>0zkq`UOCv!4{fZNc)-U`+s9-FkKHkH2jN1zUB%U0f!gJ_RNIjG4COa#&Nevg``&4{QEnnAYj)i#5Z
+>ow^_7l7x)K+(WnfXPe&+>=Tcr)u^4u9Q>z;qbH-WoYq>yBa28h=;vD^+xWg)x?m$yQ7_w+E8Y91`>V
+368thlaz<puhG&YBh!fyBq)CYN1AbAEPqe00@$TJo3w!?NfUFrYcoyi&%p+o3)|?mH79!=r-K<xQOOx
+W`@LyEfO%^i8Q=<oh87j|YbUrL5%7bQLtjo8#WAj-wEP(A;XEzrR8C`x{iB@dg#^UUjkW{3;IhY4FRu
+Tjg!RUL$|W)v*WBzefHIyj%6Kymsf4s=M&A&m6XU8N2;Kw|>zzd@~=VwVxPu6E2u*5!T|&^xu9Vuv_|
+}iatDayyA~utV{FV6KrsH^_Ox((4GdVd0wM7km`@$WvpdX9kub)i2FQ1Q%ZN7!HEIQs{R|4InvZsTij
+5_1^u*T*}TlCNPw;;fF;8tWw;JbMRDD%hNvWFtj)gf$eEknD0|S$9|ZD5NGTao??C`+8bUBmx5EhcCj
+^XDn|WYn_@93+(h}H7-mXkvH)7Ytp%zVx(MSE|Q^MZTJ4tNhVKcTPi72}-PnBf?y9Cxn8CEj;V1r6DK
+iVeSm$$%`tAgLXsX?kXjB&^%V?WX39#_IV-#x6bD-bJ;Q`uuy@H#-(A)~^U8&QO`SA|%{0wn4&QjS>V
+Gy6*b?gyoO=8Akc#8k`mggqPxA%n#5T1P%XKadYC5^^ZT{Kl?vn@Rwivs6b4yN0PtrTa#i7o7TU3WX#
+0njZXULow5Tcb4L5r5gD^mtrp7$7I~ADrVk$zkxA=Vf(DSUda0emx$}|CEeWmMStWbQZ?{|U7f!^pF(
+iCF6l-LY$BMxuajrVvnlAIU{7BB`T6r;URZ+CtsMTqOl0AJEE>`Mo^RiVy&sF&Ss>BT^7B`6e&1&2I^
+B>jSjYSzNt|)Wt9b=;@C7FKm1}nUJbCegj-ELLTUD|HM+5$T40j0d1H`xY<4ZeZpU;8q@L?xhmk$vww
+j`c7zvMK&U(LRRIbdGtEfm44T$-E&vFvmB<PPuqJuwM>RB4Z5*nyw3j{gHzJ6G{WJz$+!nHfO}PVwXd
+dPPV!u2uK{{{~P?0|XQR000O897^_9?0G{&Qw9J4F&O{=8vp<RaA|NaUv_0~WN&gWa%FLKWpi|MFJW+
+LE^vA6SX*z~HWYsMuQ>1?Y!|NGWqT5u0BPbaX@exF9qeHpDq1?W*+`;BQt{kj`|Uf2q~s_`lN9SNMe7
+Hfk;rrVzH?!^-EK$YuN4|=MxvCRKd*f{o!Lqn$W>Zp2r@4-%(1Wr><Zy^I0gIX$D>XsN>sVga=Ee*^p
+gSXJo|PB<{Nm0MS*rj+ogR!>O`4LurL_Gekqa_?hL^o!pZT$<a9cLh0>%>Bcy1B%*?3MB?CJPt#TN#1
+xi~wV2o6S>2x|NE+ClS&q<9+hfwKk2v43|u7zHjLDT{Ikdy;DVRe;|#iB?_NRiSCq9hZ>L~(Ejo`=O=
+OiuC9s1#b{;H5|5*BQ!DC~$pKL=0;F4ikz)9RE0(#qp39XXmryv(u^n<7l#f=vU`w)3D+EqF(IJ4vu(
+98shkHax$4sVlw8ME#zSY7q3qqV@2zr`!)oSDlJ7&WCJ*qiCgN;5Hd*tPz$gXA#K=z`Nq=1Di<y%i9f
+P%T1k)I00mVR%f^(OX0-ID!iq;~A9~#`3=5gz(@b7sV}bXrHmo*iuF{Q@@Q@wvj4E1o?8D3H*(nLrQe
+^VIm=oX6H-vQYcU7%Wq^Lg>a~5$lo1Mdv-`1#EOUjuCg(pf~O1v$cgLdHFy%hSU2aglYF~861IPMi9$
+6mBW=c!j@;+T#xd4F$hak%~w#{-|`Rc0lrvVcXRQl=2SS0WuXAjk3c9LY>X0du63-SLm;eZR*$oRXna
+LKX}-cfPxK%Mf~rDlC<<w{}xvkB)4arAfp0A9Z{PNoB0c-v+Fm1?v@R7Eo_}>b8;_lB<qSnno#=F<Ed
+37?yAV_&`murM$wz>378|j@ueZtbmm8aX8d~vmoK+iZqoT$C{9hZlVRfZSt3Ow1^-oyK3i3#r$#cp|c
+blPL>zK$YgvdmqeuTfiun%n|HV5S(&4%Y)j;kT0<@hDkexqr!EcFLfXbEO3W+N4TZUmG!D#h!5xD_<V
+iFH!69A{ne5Qx8EITZai3%tE)%>7LuwsjTh+qT0Xz>Yvln|mgZ&PW#(XEA#k(!7h-H~tztxyZ&FRqc^
+o3Fxiedy47q@XLjf)>OigD->V{Qs#>IY-j3dX(#jJat*EtI5<;1CyrvdBd%j%T{UrcXFiZ`m;?<*jz0
+)o*u|kC5fLC`%40ZL=y-8S7y%xbp;FvV=_wUV=$3HZ748Dmch6%)RqNE~4v|OjeZBh6W2yRjo3^Y2!A
+pF-U6QaS%0B=oy%uOd&yS<w7RHVu0Fb)*UKxBBie%rLe2ESV{pn*oS#lq@LB4!F%KDeI;Ee@|LfXE8`
+C$Gss1N?bT>X8a=joy_Q+VhR8f8Xvp$x1F2dUT>LO?*LQO7rub=akiBpTVKPWE$&z`yFB1JxiTPjz#|
+xM-J%`Zm@ms1@y-VEm26SBNpi85zH1)%6KL{2-uUC8ZG!YIky&`Dl#(J9{m@bT1Via{ki1+sP>cOo(a
+P18}g59m8dY0=^KCrDTYfBT2$NW2&#YpMpc!{<*Xp0DcHTJ^KJI|i|vR99O-jr|P#fE^b%WRMPV2>~)
+1agN9af9lJsp!iS&5fB{u#-#~Oc~FLD2hRxxKc6&VzetfMkSX>WKkt<sYk;C&BRN`elku~I>DcWb~Tw
+8YE)heW17;m!__^b&JC`R3mP|R9Nw^!OFp1DIgH26_3?TZ9!>qCKj7*Yo<<GJJ;e3%QF~<Gy*4@Twx{
+PXVpGWb?u8#9cTZJ;w`Ocjk)DRBn&7KJZI98P?dbaE$(!JA1ZTkn;>)tCZ$#7#;yCzB{n(02G@m@dT7
+(Xu)?juCrEa+X1f2ZOZ9IJpP5-W|(lr<h2rcOoWBD1xGDN6*^Ew#<$V1da(Sy*j|NF>M8`uujH>LtNk
+QT~vE5DK{S2?-uQ3l<;A#^n8i|yQ~%94v>JrtzASwh6cBx+0`AuFnnN)P^7{CrSGWN$E}-@V}|LFv30
++=({>`XR8%&rtq&?hM6`uaFPdK_2BkF$KQBJM?EzFPI}We;iBrE3kyW?qF4Qn^gBP>EbJqz6c^!ck$>
+Jd4x??A4MO&N`58Kmp~w<#v>?{VultU9Af-`AO06(%)c5&AD-JI!Cz2I0|XQR000O897^_9ICo~<d<y
+^o%O?N;8~^|SaA|NaUv_0~WN&gWa%FLKWpi|MFJX0bXfAMh?HX%u+c@&Oe+5tZ5PNGYkG5%H)L3NO>^
+5kd7D*P@Ls1B{McZs-Q6;H3*&z4ZZ-x(vlI=LX#bFPJbAUt^=f!z*m?(-ml6^0k(kiB<o_GEkemb4YI
+ag#M(lTRYB63Z6u85v9g1{`-d_pxBIhoTu&6reVDkM4g6gv^n@9;$-qy`W*&-mDX70N$J=AZOjGMe&y
+R=wbhYH>+r4oj*tm1050RI#IH#I22wp0Ru)Qr5Anal&)WWKOfB)I3ujPKzW5fv;Jjv_w7@dLkAD)fF)
+yZI}B5{`N^Jvw}*+Drj-VSw)lGXh|nJajz5L@r_Cc+u&}9Bq;~rIqZ|kPUrQ<v&)mS%jEJOpH7lrKc0
+U`em{SIa`yV;o0B(WL?T)gnbYy!&0x7)4nV<+0Z3%`n?_9%AAWy-d76AWKEFilMVV<1T=ky8N~xw`k5
+0;_B!OM>NrGlXU35!@>RPZqNU79P$h0@?5cq%z&zUYI*qxGJ5Q!WE60sVJjfD|zheW4fqg;~`JVcP9)
+POMNvw_HV!FLu5a2EouqD4W(lyEdR)ecwDTV=k(FYvfAo6~D9N=e{LS}w+94CI!K<cy_;x?~{mHFM}d
+Y|JJUHbDv|3UF2`88}vU3o;^8uH(qT!e>C<mseC#`^LS$oC8UNH)rrmi44$@*8-d#9UmNHas^(PDq<a
+mk9o%Rt;0vp2jRg(Nye`j0VEX@6F^IzWgs93v=G;@0ig9X-iIH9%BLh3;C%{WOVfP90%O#^=*)p19|<
+u&bgS3KT4y33SOns!IR3dHnaF2Mq9m#;&?T)bK3+-Gq-A9!pE3qgVEA7%6QqoY@i#Wn<W`is*UWf~rP
+RIqo4oI#(psdb^A`e28sBP=$&mmgB$zWQ$+QGNV~9<!1y9>F3Ms}JTc|jS(VeNT^wjG&AR%7ZOvu~O8
+wP%2qv!8dXEk82dh%2tV!}x1bv9VX2gskZj;Hd!YaM-C)XM7pIU9L0&PEkg7kh&NImuH{6~q_K;A>^O
+wNV8m0)qwi_m8p7uH7gD!SaKsw~k)z2Tgi`tp0HWJ<Ps<i>caX)`&b=sZq5HRaLG#j)qbEP4K+CE^+s
+IF`^b-s~*Qpnk?>lLK&E3fMAk2FlSY^|HZhISu+Wlf_EYkRxvOzWN~9G$jeNElmrW1RRv6GNhW}kBwf
+X_X`h6uk(2}RGoepCEtZ~0DP%V?MP&{(6#9))VLm5FhJsVYs4pk(+sn&OMpp>m^}^S+>R4+!flO`ygL
+)P8D&WEB)H4viiZ18yacd(y=epX+#uAAi1c}#pQWIc}YlQ6B_llVS5gVFw*2}VHO8L_GwnmZ>nK7^!1
+dSotCy`%^`e2E?ojljbx=O;Yttas{2;g9MIoq~7Otc7qEDgxxoGP~6l=@<vNJ##NF?945)ZFfK8rtbM
+ciL;qBO7k_Ns60W<8}=v+~j)(e2wqXM|s|3c565c{-b+-!)GAlqhig1{+9=v2iPI+7%L!gLm9#<S1>u
+Srw=H@pnF&mlFnKb6AO}9kWqbJiOrjC;O=HKK-HrdPG)bxK6apLDJ-f^4rS0d&G;WsvA<y&6i{gb=_*
+v$mcXIP1m>!E5T!^g3fQgRM~q;wnM+x+ZJ^*6I?0VpP_v?K;06*7MrDo+_P2pg=0>Y`_uBvqp#Tmu&s
+GV_Me=O_z=TtUQyFPo@+^e|89J^zk~#NVFbJyD9Q^_XM!}Yc68oDW*8awN5KlB)V860{qhBHe5Y@@j>
+vbc70SFMj!%1o*cnmqa8v#gEhd9lk<>Gq&fLIo-0t}EvK_Pm#VOppF4UheB2%o-eXy3VTEfDxVt~Q-D
+2?dTmym?-$pJnPH;OaSsRvN6@3t}##i*ZWfIIC0%>BE}e4LOuK0NV39gdnvIH6B?rcFnR-_K=^G4*Tc
+T*Mp0bi;HO3X-JFiw@9BG&2(>CLFzaJz2;53$qYX?u;H7k#RQ6jmw^HN$K`i7hKYeW@P%S>V-?_&*E+
+j-K?CitD&XSn@w!c_IsNN43Cs^3y-P3Ywp|VmpC4`5DXjdZn+5(qvRyCk)*U}TINY#fSouqL4E%p&$6
+nkT=pD}4Y)T-iPtswH(w#<k>V9~a-bX!59J%;ThbJ$d9yD@T&0%d0b0RlW-wyfw`LmrX)CVDQ%XDptT
+*HRiRjx?P3=vxzKa}iZiK+<?q1VB)nj&tlJ18YbWAWUL6MlV74v!9w$a2mnbI^$>v($(JCoZ-q+&s&0
+LrSBHX>7hjii`H5Pyy9C@RPUA-5ZoABQlMCzH7qW2c`1(fFQ_Sqpt(Sn+gek8|~bE&HVV#;@N5qfXFT
++{MJye4SIag3)T*sYlpptU0pd|Tkq;VXlr*B_CTPBg9j?u)()yh&L`J2Gu7CuZ6n@r|K&}fGv!7o4<q
+$9hN8k<7|4e~aC9F}@OO6$F`?p8(mWN5?#sXg6W<RtlDTTc`j_Fs(bv#uo2zfA=(byc4&fE}k6{UaE$
+{oN?GYM#u6BH@!ba-5H(j98M~iqm;A8i}c1?OUT^o+};h<zX2KNN92}`jmG7f!IzumYSl4H}U2MnAa)
+FKa&m}9&}PEWD-fJ@p$Wp8)P6llP69dA!?+s+Q=Z#y5lT!bALURuC8$Term<R*LJ0nM2BxgLq(uxdn_
+Gm+`8&mp6BPKo-qFNX!2Tq383k=H4_*lkmj9F}cv=^I6gTroq!==46SF?ylH*k-t?Q6n*C#NEDI2SWB
+Cq!TvBn+a4PK%;tYk+GFzGYzX^AYcJo*em`XqQc_HdM{{kGOE0>?}8VI`bgRh4@SmerjeT%+#$*PU=(
+28Es-qcl1;Q9g7nExKjHn$Of`>W=S(q8nkPMz#F)gZA5TWb;qeW&CS$HDCfhS{>m+%wA}_3N6SaE2q*
+qJ@lM(M!1V|Ar@p{qPWq|7Ko9x3FxPM&h(Vsx83*2)@Wc_(`hn!ApKF}awI(v2lU0Ev3v$_ARp)VLCb
+FB+C+}oRhUzKCLC*3R5bkB3#<8XvxYVYZb7l-Xc`D}lmyc&U$akf#a1cR5nBG32t{|!}#2=$yQ;J9H(
+;C8v%mF<vow&b}@Hd7AC4ZyjXSixHyUO{3OQ?oo4sksMS;=N#t3dehCbKi*<l8&BJPb*Ev{x#Bz6=PT
+HYA}cqlt(keBcpogXAjwU4;);;<0Lm~)vCz4k0~pbOq_`&o`j8yZPofKa@cD4x1v00TMF;gL3U>D*Fn
+c!>7*hc@HC?{HG;*{-_AaspS(W4IO%QU=LSS8_vl^V6svOFjexM-ZQrJV(Lt|uAlM<VApr2;kN?krch
+aa2$?P?nxjvJ8#&h5V06C-vaEcZMoZ@DnPJ%boIa_**TR$ir9fiY5@VvGkIKJ(-nSf@#se(eX!dTzC&
+O{WqEtvKHe$YkK*uU)8B+MgSuJVcT7nRK8G%2){Xx1K>x*OZAo35>#=nN%4Z8KlsJkx+`ike8HklHjc
+hMf^MNV+YQc+PR2dmGcDKxnxF;0-u3GIZ7@oJ2m@-fT`<&4jgOyboEr8Ucq>X)_@X>OfPJ_0#5X=moi
+d3Hh8}Lx};;#Q#Dtl^NpYiWkOTLHaEzb<?ru!5f&3z91{R%eZlf)$LQ{#u2cz$yBo}3wFzHCalopSVJ
+KlmztRy#&-TcwO88{jCx4)&C3qxH}N{$#ByqDvM&T;+D-=8u1bdgu2LPkO;Mnxunf#UgV-C7K2{k#cO
+X)WOtT2N(o@kj+w`{uT<<D^J&zVGB4;b<=5f<=41gKL2zU@)!FD6xCq(YLsBUq3KaAvCtlp1>&x7&v|
+C`eGP3gY?P)h>@6aWAK2ml;P_Ewz!zyVnS002J%0012T003}la4%nWWo~3|axZdaadl;LbaO9bWpZ?L
+E^v8mkikyFFbsz8c?wf5n>2NIBo5QyfP`QgyCD>1t-D&ZPH_@o7sNyGgggmpnh7D{Q)<<pzu)I)%iv_
+WCtf1I!f^DhWu=OuP=YT3op)u0;+^{VQ%dbxa?sm4bO?ez2s`jC!XVh72-Z+zV?yU)y@C-z4OPY?>;u
+;wmauD45XdRZ-4QG!e1Co=#Q1K+_UR*!!eFXrbHGxmn+A?HfQi#nllTDJY`Xv~59I<HD`4Q3IJ`qm&I
+|2>C(Drfz2V5JRm@CcxkvVk1g#81)fzrvS{@@1(=^w>+h{zSgSR<xBsm<6#8}-?Wy5+5oI|EVD(VL-9
+;}Pc1`55o+31Je>h5ZFdw+MW*Vo%!0c<@`T;s|tb)g_uy2C(2sb7(6E9L1P8Je6Fb`Gciqw&deYK)a_
+f7y@!OFSh(t=aUbHC$dsS=}3At&52^2(h2#1#|TSP)h>@6aWAK2ml;P_ErGNiWpl0000IB0015U003}
+la4%nWWo~3|axZdaadl;LbaO9bZ*6d4bS`jtWmHXX+b|5h>sJujVGWQOLvt$-?6B_8ZEXj1zz)M;$Tp
+KGl_gcA()hC9KKe89Dg+20`S`>SC5y#EMSMv}Oj+scpjrK$AEkco4MFXzWD!Edqw$Gs1AFZ%ixrqU_{
+h*_o5EPb4HzO3RR!`ZqJtj|@4bU-kem^$Gq_`jSZm`5wmw3k%jZ`eD^hc@<k(o?J%Ym%L#+=&K4K)}U
+8WY&gW5)4LogxBkLW51k5%nO4_T=JQ$tF<gAe@?t1pHwd}2N|j`ayB?R3nPNJiMSso8L8Zrs)j@n&i)
+JAG1y^3YrhvrYK@@egb^aDB;IPptKvwQetc@QgR`3*R4Q%$m!+%+@C<SxUEfAQ7Mxx-N`sdxZi^oe05
+jw-<EW_R*gdc2QTx?Jo1>^UKJ1UMU*~()#=9b&SFL_38297E52@ml%C)%ln2H;8BJdvAQ)S&o?$-f7U
+CO-dZeK21cXsg}@t5ri*gqeb(0M!r}_<bqLai7>QfYfcxw{b2vXh|7`G}BWN0cHN}~i^}eZ;dmjmHA2
+)vVK5-QFyT^-Ha(*n|ai_}$?m8;HWpr98TDdn1I<~9nRj*XLlb0kbUY*T6*hD=}?jksV%W$+6Zlm5!5
+M8^S2_C$06X>p<5CvJugpwPg%UQL<pTNA{9dd~NBr{w6hjVmC6TPeD&GoTPHE-vfTSKE$*iBwEK@+|8
+%te+;70FmOE+_7OZyeRxDjJs6ZJ_&Bg(j)C-ITbl#9H-%rE;mpXv&<M(DAQ~h{M);%}XUV?l8`SOZ5*
+>O9KQH00008031s8RxePjlf4rF0DwpU03QGV0B~t=FJE?LZe(wAFLGsZb!BsOb1!3WZ)<5~b1ras-8^
+lN+s2vS_g7457%QbR)Aqhxw-9<s`V!y8jp42v1nxrOk|Qm>6sgXTD+`A2x8L(N!x@s&uA3A%R6x8EXX
+csb{cVOxlH|hZe{|ZmHqD#nzSQ>Oe+Qq7i*K6UK5NU{vMSr7%9}!~wo$iQWw#Z5?W|U7USE~B={NN4z
+caH|hqAp>ev6BKx2`QKtIFNJF|Ab_)9lopHhQ5fLC!OyH(kZ+WmbBT0KOOe3uaWhE;8ePH~XXe-j+Lk
+aX~=SRav*%)LFF(w*;(LHPG~+SGF}}y_MNHk?JPBYK+y@LcQu*B=uFc-^0{}@}w?QXR3V$v*=q_)Ax&
+u)*P=c6nxxncSdIgZlgcsdf%#-^!$&;G$xu@bi3Vg<)^F625T=a@+z|y(8}-MFe7;}@Z|@S?XAkx+H+
+WDtWiL_a#!X!3P=Llzwv`05(IF4r&+FLeL|4>!(QhtVp9SSk)@j~r}>R3w82gC#u%7W9SP(vtFx^ZR;
+hhcl{skFLY1jb7pl+zVOQ2#9qx1sk_Y5uYM#}o0amvQwFLpyu%{-FMYGGw+Nx%QkDOYmtS;y`uMa3{O
+t~#V@_uG>`yLQfKmoG!MN?PDlxeR@UCV&oH?=KMvp0<apj8EHko^c2_o?*(bTtF2t$HYdsaxHy;NeOh
+&gN^viMX^k8W-cjodW$a&EAw*t8wQan~s3O!&}g=qdH`O1c75(1mYU`wE<=oz?iBzq)zBeDvYTWsCn7
+0Rx{Ao&B75pXZ64jK2KLhE#25)B)}i$eEbv-x5vGP$4=R20xg9H^VH@*o9=Nz{BZ%z3Qzz}bf)eB#w+
+d`+n!i4y=|@As>x#@Eb$ePcn%(c@q5l=5a4ydRhVkH_L=$~)Wv~d{UcS;msY)f^PMVLE5R2Ub(a<OWs
+5pY&%SK}em@iC@eg2O-Ly_ZsYn44oF%w239uMa!ORF?za%V<swfNEzHCt&z{TkYuvRt}uu{OgHC@i=v
+2BBPv4MGL$R3dT&{fU`n7(5yZx%||;6z}?GU?jQi~mgK9u&#1IHf`X{%;1jA!oq}9vqfH!-RT><DEr(
+dKdlbu@Hq_jE0fk@l#m@Vd3t~pviXj<S-bVIi4Kdm~6WP_Y+UJ@xKBEE$ynSAG9eqB?hDu`h9J>z_{)
+*E0!(Jq0V-Cya=D7J0A!aoakUE@Du|J9&SQzE9<Iu`In}i*m6qadEIEIU`$}n1GZ#E5$}Glj|=sXRl%
+O%E`4A_o`B7%N^eWZ6~G-+3WNTh;@b{FQd9g6;iAplX8Ao@>9Oe)xZy$pH7UAZPfu3D^1n1Kg!M|JEO
+kM#Jyyts<EalG_O9uwf)c5s0PCP+2WjbQql?mzQ98or$&^BznjH!O_|WN5C<vJQ4(Hu~anj6Ks9{_?<
+4wm}@n0C~v}unX+!HjHU=5XgehT1cdi&w@lW;#LbVMl`$AfWBcGtFh%%{G+zJC2mTMLQNR9cpTG|PI^
+z%Q4WrD=M&%i7<ouQOXh%3Fb6gClG}-OxLVTSd5Dt0<AhK?p>^MIWYo{&L8UL6R4wb`2~cxVy(Q4B0I
+<uvghV=yJpiGOBPl*aed>p$|V-<UJk4D*!OTFZ4r@QC7{i=`5B9<|t{ETNolT(DgpC896TG_gTfBa&@
+6WjQnY|EDdJUJkS^fqCd1I%UzylR}f?0XJ!Wf`Q&ZkB{%mP^+#S7q`QH<-E>Sm8{neP-i6n~XV~LPP2
+~7$hFM6hb7Z(FA=k;2lnK^Pnum}C(JKWStC~ZthP8(z-0>PQ62&_IA0%Y2Ex`gOMoEum;Ip%~H8Tfcp
+^}x$@K^3(GM5a8f2QLZBRSL0XT-trZ1DFQTy$yKa=@VXU~i#*4p8SH4vYY03+l9)%gAN7J!F}{Hc1Zy
+HK!O5Xf=_u?=bJd5R4-`0DC3dSicQpF*`$fy0cr}A5<V6Xdo^m)pHs;szM^=>{XKfzBWzKK{*JeTTtV
+uDBdZ~9;J0)vECwLUBwDj4%j$m3Qk`QRtZ<QF51kTV=a<~K`};M^i~Ypq@#+Bvu(yVaV#);*Fe@Qpl*
+*VwBQ;4BxXoLLRmBAI17boVwmm#(r<zHt?dik+oLRmFOtlt20b;ncVFX@*a4OmW^gR&O**eM_>1`hRr
+C8<Jx?PR(I^H_)Q@+ZN^&(z7=R*qDtdDOLz5Dk624z73C+0nfaDy?*-nRx7-d8R?G$Mz?By|l5vcs&a
+d=4f2pT=?Vd2k5AoV;*(Q4~rHj5Bhgs>JN=`OWIj=8x!$z{Sl>>dfvQIXAfWuGpv9KUJmO;zUH2AaL;
+YV2Flk6wAMu`8xB_^&-Q-siWF6F`<K<z;Tl7Sg3mSqS8iHR-~+3XwM=MF8J|pF&k9mZny|lyzQpg?1A
+2?9R;AMjf78bUuKJ?2`v+f)F+e7_*5;Gi<2!)DAk02=aHR3fWY^0s{iS$k`B1DN2bPzCGo8LD;im7v6
+`v12Rsdn+og@Med>)F#<r_61*p|T)I$H+7k<oij3X@2Z1Zi&UKQYgn%SVDpv1*o%8@MK@!;hIVND;p8
+J46i^8-NxB+X05XW7>L9=~yk_giLur0?u&*}*5YcH*O-&rD#y+g!ha>5V|Xo2g5VKXpQUsYAl4eAd{$
+#Q7SJ%PdyChfS}=0gk%G6)C-4`o66Xxj{!M9sVPx^FCk*VpNm6=}Wx?uXaG5D8$t{!>}$;HmK9ZC#a=
+Z5qApDv)QO7gWTtLc*7Qncss&g1-5r8ggJ$gXUdb5$Ax#nK=ghW&=a3s~fW;Qof)4dQMUWBZwVtm>Hg
+|ejf=F0_zWe%nPCmVa)}N%6i2B{_P3f>Xfy5aNcS`|C;JSBT^WDv7=eCPE+dGS$v9qw)Ykkk36Iu5K%
+&5>w;5|yGN|_{BuERK{|?@ODD5)-zImTDD%crdsR29qJv~B2Sc^9FyJy1``(ds*8fKzgSPqrut=mAnH
+`9XD&U3s;*0wO^7E8*?Eh=&OtJczcP)X1GX)*zC(a9jHw42ew>9=L&|EW)!o->=Tc9T>YaAc)dn$Drb
+-*HPVf$dlb3Vq8lDXJRID`*^{vv+n6B54&@ddt$8=8rn`G9B8U(F$B+R*@(WlRDu2$Zd|!^{X)aXfKL
+rZp<A6Rpp(XL&y)+8Q*sF~HyJ<ERG{X{Dbes>xt5-q29iLU03lB3|T&-HD$A<}1nfzGlP^*tpdi^&D&
+*0TD^K3ndSjdbE0nN%W-V#d#-A9}<C|Bh^_!64ulHDBY7ZD=?#Wid;{o2X=<sA*rXy6q(_!+}rM@F^}
+aaFdvho-};;^dD2f2rZDecCCWid@d>n_pxeuHMDk||G$!{m#pzHR2$TUmCQsS!QPX_EZncG|_tVAcF#
+cIhb8$krPvXM_4<b{I$e$K1=B3TSN+f&XE+k-k6w*aZ=w{=_m86qY{CH>&SzT6DruN774$>CRy2;~6a
+NB34u}{#Y^L(CECgDY(OE|ugC_cf)w=E~^d^&*?6W@?(DgmT(Af+END#XDJ`+mUF6`*enNLGVc9sCiH
+@#J7HS9eE?M^R2D57<DxkI!cUEjz^m9{foRpj=MKCvaopxoZ=X9%rgTI8E%yc6r<x4R|9Kg9m(a-Ym_
+5VG<a!z(a7${{;H0RfDS!rPX08URrLqO;b&3^3SP7!xqnA^o)Lm=bZnv-Z2-r^J^%L#rq(XYWFAr|Kj
+s7@-CdVKBb_$&hD|`Cr1zIUq?ALd_P?$Q1{w7#(fo@$2Z`HU&o#*@R;PP!mt=Mi2~~X(Upb{DeZ*heG
+_FQ`Myq$?uR^C__JQ@ByzvbNqo5!Zm>%oR|~E&I9N`PVKM%V3xWyH<f(WU1T;MRj6&K#Rr*!oc^GyaQ
+QiER*x(@OWOdu^@jN$;AaH-s&6HYpqD?pnF+T8Ltw2#Rx|~8R3d!N@xkz)=9*Vj`*LMb@?*Lb-`Xi5o
+jY3etIxJoZ7-EyEmo+PBp4s3khU;h1YW)EV|FV^4h`4;L;o<|tpVowUO3z^)a@S69cYMk|V6tEIGqD(
+(q7@#b9{Ym@YQzCcU6<Mg0LN<&k9dB9*LITEQ;c&3Y*^?<j4E{Xm>TLzw>mf*;R}D6=m;NrtS4_It}l
+E3tk={1hB<Z%r)54hJ-{;R5V;DS$N2|T^jOYMwu;c%MP}-bE<+!)P>F3b(^{1Nppy|qLz<iRGiR5{<s
+*|J^i511HaUV71Mim_4RI&ev&+B#J-GxtlTqw+E-Y+coM21O$!=eOK?xTr`xvBlG%i<6vCYMH5f*t_P
+3wX#J|59HGYcggw|i(+aBsKQqXApuXhzG%L1fgqY4*ny{}Cq4&-IBM>x3K3hrnvk1I1nBC!`tvV4$;(
+f!>0BGahnftbT+%u2=#u`ZDz1xx^f9Ns<H>j2jH!maX9%0{LA-hc9$!>j3>#Yc=6W-3=<b<O*S-cWNz
+qyEuIGu4;_P`05CqQ-ar!6J`mk_?29t&xwZX<U~@<Tsk(N03q4QNg#9-c^(91C=&qKny#jEkIygE2M4
+&zsRLY@_vBn`yjmbUAsL%qiyznE9JLW>kZ#ktKK^WzAQj7x`0p>wCvOlR`7b>pv-pVr!p~%APJ@8{xy
+JQ%gSQmclqjt@p!u^Ycm&^bE<b@Ao35r*@rsY#Y8`g!JG`rf9^t?ty!Hor|3)f}!n6G;Os|x#-rF>to
+PUN3rc&J#CGN1(i65?YvNq@RlBDC%2R}8avi=DRY#XkgAy%S>{M%Y4vfPmx6zHcH;OE(SNd=YYKC_mu
+C%8)sX92S-n7S=-b{T#)!PSWoLcR`JDCbv_vk>PeN1x$Ef<p-o0BpT(JJL7*mOx3xf7S4-Jhi*Q;ltW
+Vuz|i!d&xjhlQp3m{MWcu^o5XHwOW$<K_=(U=K1veNk{WhWr2`^a<0j!=dxOHh84amz*#)Mby4@A)SK
+^`{64%&=wYV&W<N{(t;-7LO(eHCb5QVwv@UqY&rEVes!Nq=pHSoj++8a&T0O`&X((KUuXMO~%2MK0_z
+nzl`BdwX3bp-_E6sA^x=%zC-muHx!*=6aLG!^RN~h^1G2WbR=*jQ-XmU_VjHJg?;-*~yc#^9AV$f@v>
+94C$$WBjo3mC547F;1`TuCXHd1W^c9M&_VlX3w@0mV&pwIW?GOb}-H{?9Y@gT4fhR_Lt4FwCzE)IGu=
+nGv^#`_Ub>-k7Fg0^@4%&v{U5xlJydD3GY7>dT+^?t-ukx?76$ERK}X%|kc+@tP_SGPP!j^G`W;_gBp
+1j=EsNcPwhW1nTe3Q4WOfC%UxkYkxm%A%_eloz|^!E6D_DzcmK}etS_~C-L3n%S!^rm&)*FMU4@|9R1
+sgvsUh@;YBjM3TP>@1dKA3P}#^xCxgqLMq9kPwp1T`)ds+Li6psFzv`Q7<niGVaVVIJs3&sP9X!X|BJ
+h}U<Nm4K$+&{;!?}1J1D<^uKD0XT3__+>doZ9s>`TCU0(fcj%oH$yEzMvcZ+6(R9<PuAd}D7s2z%g?k
+IA=fyT{k}WXh*-&L;oOuYdL17|TyA_}i?Ydpk?&iiswv7xas{K6hp-Qv=(kaC?2+>xqPAlf*hZS6jTy
+SNk{d?)CA|n8KeKSfGNA4`rYEr_t*`jF9t<;cXKhc}D_Wc|A|C>x~CJvv54QiPx~W&#e-Lm|lnPjFef
+mDw>v74i|-;tt3qb_<~ZM#TS+C#*-hElzoe5_Qe-YQtT{7H+y#B9U!`ciZ36v^d1Y2__v0`w<^L?2yG
+lw?fWku$Tg(?QlRL0STmFkgLla;`|u*$>g49kkwFguwx6L>Nbw&~m|xP95v=*>5aDlV)>CH(0|nhUAf
+Rdj_EMf)-h6@_8eG&ZUoG8gBccLM_XIh!4haHeS5PwVE6(VW=h;F%FJ3&qeewK9_59nb=dZ4w|5g3@)
+pc?)rrEvYPc(0LOh443d*Z=p+eN%x95P~q3;IjsKb8)db2K-L;S_W+OVYp5+<8A)JlJyJ@+7%-E1mi;
+hD0yrZ$Cg;I<HIdwMIWc$+-i_rVtE*DKBGhh|X{sxk9%XUuVIy&*Ua>jN%uEgs@MK`5=BiWCO(#hxQ<
+_NNn=ByI6ID#j1oWXRZEH{R$&BpT0_ph2Izb1nJ@6)yM;umP?Evy;Z;QXR3WZ!!2d>wO?`{yg%oQUzr
+Mayi$MYFNu69cagv`KyHLigPcU44Ud7)+gCwn<*WWVg26XV!<W0-CW7Iqi(tImNbKVD18V|l;g5PH?#
+!q^9g<pDAJB)%<xzJS9A}Wh3t2tRqnx%Mn$G)U5G%g8KGkTTdwVQ)h8CXKo_d=lzLel!*9hb{?8|tTq
+V`ep=!&Wsfr-OpziX7ZP9&qj{`{`(d@5-53GGgst@dwb`B4Wb$Y#GPia=Ka=EwI42w-vQjle)NgM$^0
+dXMX*JZ8giH|fnJB=@HC6Sa)w&>!NA_;BhVha+1b_h!kDO-KJ<5xU_)%otc|(ktd@N4p@$FrU`((;mu
+(-YG!7cTr@uK_H#l`aG$lgrV0-Nd%qB4AX+IpvWw5yLKuy=#2{!II=!(L=(4hrp+K+eoEW_4^T@31QY
+-O00;maO7>RWKr%|_1ONc<4gdfm0001RX>c!Jc4cm4Z*nhkWpQ<7b98erWq4y{aCB*JZgVbhd8JoNbK
+5o$zUx=)s0Yg#4KKZAriVmvCho*Z##Y;-4G}95F$u5$Xjwhvw|95>5~<gu)kPGz`1bYfL(}PW;_>eaL
+ktPNrdUSfY?%Bw{7fdx%mgT$u5yIb*{F;S5Ho~;5!@Q?8=x!bk&?-jRII%#pfqLj_<~kDpHx22&Fa@Z
+m0*g}`3Rqu%WpT{I}a+rdlj%dnA9*y>WWguR{r;guU|f3>NIw@79ucuF_}!#T!qkDdDCj1-F_8;>$el
+251G5n&?9UKNm)?E%4{lEh2AOhne@9ft-MDK+ssfvGG%pc>;`tO@`BXFHECfd@}O}IkB`Qh`1m*rn6K
+yXM)^&kuQ$(IergP9ZrzfkQMvgC4=jhRi5WaKdY;Hy&A&oP;lw9!tM8anT3K}q*uI6|pjMWYuAEKV<L
+Ml}IE&YvJR6woU1}f40%E}dsGJ^Pnssjm5z4wK0%AV@7(nu2rh<ym&)Qpa=&<)<b;O#1_3e3YdR3yIT
+_;^O#(C%{b8BBH1DY8nRGE!4(R1gW5E4+h*iuAN(1MM4IU9q|kMp-zv2azc?NuZy@ms0Dh_6%;Hahqo
+oc+&a>z)@BvFNKb3i`OlsP3b(DZ<)#3bfEr<#~5oH~>^e7Aj71yb5v#WM4W!ZfXyLlcMSn_#Jx!p~Td
+zO<Lbq9@%jM)m-S^?R}x%3Zf3<)VU}y1hpZPxrZD$6rd!Ypnsucoe0R0oFvC$+Y^19*#mLm=PA;4eeW
+FGtcabX8)ec`8=z~KsoTq*L;U95>#hbHf$w9LEOid%;o<Wo5X(a6FqWo3SH&|<5eeHy43VTYkbF{C$3
+n$4<CYzHu+?g|CeI<|7qD_M6S=q4`QJYMI5H=b#`eYzX~CDS+@sQ+yeJKOBVw4f*1u7R=B?uw{A@;3^
+gHoVijQ&lG0KI)MIPV8d*1}59pd$nqb%wwMZF&)DnbZqjf~=vzz@ye^Ko|6)LJEI)3$u7Rb_XeRaDeo
+#5(FIE=I2O!c|r_4EAh5fIsd(v%!XlahBOqh%C*e?wcFzK%t&VQ#Y#z<Z|wgY`RBH!Zb+FvCJ_N+3#E
+70n(ibfim!rW>}~Lm^u8Z@@m}WIZAAA;7bTIOg0H*F_u6n;O}tFz7#d|KwZ;!{*OA!`-{;OBF;LscjT
+sD2a(iQmS!h!U!!tt6cf%*YVFkV(iL2RncKDsk7@Ws{KCUtc3Md$7nlYW{<Jn}c<fZ~-w?g-bpuBzZp
+RQ8S!JJ5-&mR<l(tJPdB0SU5SX-S4FT9-z^al0;$5jrk_e6GKqMiVUMDrrhZ}cq$VWwuL<*)^I=T%mt
+#OB~J$h6H?+_JrqEo7tyYg778bDYR(WL8is$?V230m)DjbQL(*mkHJU5e?V3XxU-?py`~<ZeTY!&>|s
+bQbGzYphnQ9N#;A5w`1_oEK_W$hlJOAl>pV)c4^Un)=R)kQ*0%fxncuBoM}bRYLP()_nI$Ia?GKIhBC
+5HwIz(NWR@s(ps1i>>NHIZ9g>h$e{xj?`X-(>)5*zEmPap>n8mZq*a{R*ZHoI{4R`0(a)8!%I_dYyNT
+H-Q}qqfOs$_nwmV_mU>m6a@)5Z1u7P$Kcqc4mX3M_!O6wp?QP~9EWxTSRdTjg)P)h>@6aWAK2ml;P_E
+v}TS}u+R001Ws000~S003}la4%nWWo~3|axZdaadl;LbaO9gWo&RRaCx;?OK;;g5WeeIOxc5Nz!lo&7
+9f{hq>BXI#7K5~DHZ~4(J>R5R7om{YWTnJP$VTvvRxNNjl_@PJid8wW<&`2Ec2>hu#&=1F1UDtW%UG#
+l~Nhlu%cvYs%I%7BuV(Tp+0LV!uPVEW-Zk={MNc?zt%cQ)=F-n<Yk(@GLcIK{*dQ_9zCp7QSjx3mres
+YLpG(k6j=sTBgVffri~8NBw1~!(#&K60nvj0%@kb0ofIrdjH)jaz}GRGRyJoQVecze8n|hw*Gfs{<ox
++RD@;B5)P_{?WiU|IvSh->=a`9>BN(y7dn7$R{vMN7sxFOuQncLEfzAreoR;8E#1zxLz9dO<wuTI;1=
+})AzQGVqXHExZ`+=EC380Ykm4P>IHefak7PZ+(0evx`A_t#^G-)&}lzinmgQfI>f^J#EXMcEJkn7`0o
+vW2nNGNJhm9W*B!f%)}_D(JD98l_`m%d1U`8mA+Zow7>R)@vkDA`S{@yR7jJnv)<6A!^so#bTip?}$M
+4eLs*8rR;WdeN}NLW_-AM;7&>z636yq{{GBRZumz=1V1)bXmBl=aOkLF^w9)ivqV!0e-ttQaE+!RE20
+6Dtkpk{K-XCZ)8>EXdAWo)EntE$;vd5TS<%$=0|U6$wD|+5(95-p>ECEE2`6w+fWa23a?tev}{0)O2b
+8muSb$sKzv+?E1$9Ya7PcA@h7O?im~Fb0UPXdw3FRFZT?7VjZiafW$X)k651{6wv%wNmg$y0OEo`-k&
+AN~S4wt_vkv(Bh=gJVqZ;2{Sph$wBWo^b5xIQYZIV7qF8a>e*Pn+)=4YVz)>C#mJ-7co{Qy70M`^_jg
+HPDm^+}7}?fHMKhIV>7>|e!;kZ*#xyWx5c?1=3*<Z>W42jV41M?vM@w`H4)s26`?f+=cPL$^h3t=kJu
+qhXzfi``Bp`wEUX=|#l5UQ!8Gfni(3(+0><rn7#P6JHoHrzgd%dlx)6-|ioy+4gU+v{5~Z;Q+@zIndR
+DrExE_ynax(aH8~t86K@1`*scJuNa5K?MUwUacwxwgcUy4+r{lXn`5pqdT$5;^|c>C=#Tn(`m4$~mje
+&G43QwxF%X}?7M<TtqMA8wXkg5X#$X5aGq%4byC7!&?-$p1_?i82{qT5mf0x~T{rutj;qrY?h9w?vS0
+_X8#IWRyn#Kay2qKUKf09`*4!9eirPMN>Qr3L9Yn8dR65o$_Ip9514j8SD!A8YTv!EW=CLv9e^`?O$l
+zqQ3cFu%e5H*y>WK=HwJ3H=~1NIIGvJM=H*eZ=%WY(6IwcoDYkpm-%@%8F1h!q?Nm9;Od*uV&j>oQ%x
+88UeNouxwz2T>j97qM7WjaFb-&2bj6#%%0EO-4uI0Su3i-pb)aT6B@xDs4vI7N0(&k+;B-G4)TS;=*m
+ZcF@J+4<7(;AMfwlsn>8$?W1X$SKCrg-3-M=2WMmU!fJi>MOFC7z(tNFboJ{D7up01ILqv`#z#uKRb-
+jPf%nJ(aiEg#P)h>@6aWAK2ml;P_ExQdM;K=T007+r0012T003}la4%nWWo~3|axZdaadl;LbaO9gZ*
+OaJE^v8mk-=(%KoExS`xJw{m=JsbA%{W^g+hfkw-9uqV_af(?e3ZqLi+3-SB**A0bTvq`R3o>AP9t^&
+z7vSQKj|4itmRKVqHlKM_sfvL1Xku7G%Ly1UWXileKh`g;E<Yz7H_)FtBIq=oks{d_q~{jv0O<79z_G
+*+wf%Sr!Z6T66!X!JZTubW}iT^bv3*M<QU)FG=$H0ZZ5fV?(eNLKIX2U)a_z^>e~mk2d65qu@d(QZ9z
+g)*JS3AQgDrl>tw%PF6`g*^vENwW`m2qj83`4Z6JYL&5`{7yYsNB`wh50_O9>7n;2tEU@j>(8hV8|B^
+wulUkwa=q&CfTY^SX&NF!qgQD)d9iUHiIjn5|a{a4EdvcwjnctG-7&i>nDQM9-6Aq4pG|jQD(=?b(pW
+Sme{$YFD>yq>4Ik;c+uF_isgQxJnOdeX;)Lj=xuC#+Uj{A{3ni}C#&;381#2-*g0|XQR000O897^_9W
+kA^Jx+VYs*ogoD9smFUaA|NaUv_0~WN&gWa%FLKWpi|MFKusRWo&aUaCz-L`*YhkdcXUxK;@Z+N@XUS
+?Cz!7^Y(Ii+`6~B$;3`?rfEi^MabrvB6TEX$IYaFd%qVzJV@E;-Ao@-%_NpU-~;gC!}kU_nM@8E{g<6
+?yEfg_xh~s-|L{Kt2WOW>tKi|T)M`~%T~<`B>Mpg~HpM1uZdHB$XT9pMEbG*^zR`_(XMi3|po@cIv#p
+y><yoh@VxtcZ4%G=4>1tKyMRlR7`evrOT4mRDkt=9W7OSFD(z1k>P0G!@2RB7`Sya$<qq7`_ncb>Ywr
+jQexvsBv+gD9fH|pk6SE}u@D$kl+mBo33!-iQw%S`?2$=ew~Zg;Col~LKN&AHBVovXLE-DO>+>QrlW*
+>&4?{^-#K^td}uSM}!6wp~9m=zCPOEqr<O^t<0YOU;DM?Ao-*t4ygwnC4%yxqAKW<8KbuO}$Y?ZD#Vm
+YIj@wrt>#j-DF)+R|i~aTWr(CwXX8INq0>N6L^~HPb<B}I;{ba94Pp_)X=4-dC#ce=Xyo3-eyhfmcMQ
+4u3pupQ}hmScn0fJ?>eXS^z>)>H60($y3l2Aha$`W8VmQeDfPB)?OGDH^kTCsyJDL)-C|ug8=#qN9K^
+0GO4EFc6I{R(!CJZ~DxjJwD;HSJ4z8;g6=39AFWRnw#hIyHRZ!1GyU5yAQAqo2*Ik-MKb@Vu{e9LJtL
+IQC&w&KCS?8nwMOK#Cd8rw7|9tx9*Jwe0$+lbUmVTUPt(IZ%?_B}2uW)Ewu(|}A)t&qRq6VB6=XNcEL
+HxO`D<onpE%hh-Iam*{#MqwU*B16vN8ff8VbQk1?kwUKt9pC8;KIe9vt}mafv*c}u*i!QfVt3}sdNbh
+r5k}ZMzJq0ch!~7U&&r^F!iFYD&Q>8#4qf0)e&0#>bOSE&y(spD~lZ0ATE9X?&ltd@yLROLzEhp7Cag
+S@e42n7~kpYQg5=+T4r;(J(#lbMjddw4IrZ3Z2)mj-All`t(NO`2775ig;D{yV7F@*IDA`=e%R;DZq@
+CY{^<*#(37gwRa@Yuc?oMQb-i7c2({|fl`Q*$5M6Y)jCdpq+)+#_Kx<MAQ*IZ?3aV_Q-7+Lz*tu&iD_
+|=xTHyV<<pSRB(p6bhS5l4)x$ck=6kN~}wiY?9*#c&^1;oK~-t<yuw?!zr;-A1GuJkQV03f#=Qp&;MT
+%Cc?YjvmUHPM=4WHSC(`V|%I0gzQHgKfC$>J2cO6|jU`Y`$%37=4TE0Y;e@4bXOa@b1;ilXtIPoGnhz
+o}ZnlV}nTq3Nrax=Q9)>PeEez<?DJ^ner!2c@1*8k@BZbd8cueK<X__$5QDxP9;FWCaYj?g_WM+{9nF
+${rvsUXA3*tpHF@{IfL;&eSGlZ&97&#emz^f`04$xe_WiN{Oc<y|K_oJ2>(6#_Tc2~)jR*$ci%iYI5=
+39S!>DO?EhbiPenDSVf_v;27~Hu=@*bQEIJSn&`#3oay{i*_yH~B_rN)G)=Qw0f(?%91gHWjsUW5%G=
+}~^eC$iM@Y^s!f{W5+>O4nq$7-A67h77aL6&#)upfp~ee%ffGzG2?vMa&I4se({s3HiRzPaG3z=!R?n
+f%jaI`)iOI-N8cc60?uO8;CJRnkxIcSym-YNJ8T$t{u>B8Xv!Wt%oZ3GAbqmJ0C<&o%5zQKYtoUTNGM
+*dpz_|5H(xs9quQuXnH+MAEweNJZNMIe^v$tT0n3OBC`&g*y<ST5wN}x*Z6&HdSvxGB&8k!304og{B2
+}j%Bu?Z2-cxQ(1Ffbhr~-R67I78jailh`}96>Q4W_ZCU`6N7Ztr2~jhZpy*cTx1DaMQ-Aqn9Z01yWgy
+Mh>N0Dyu4@Fs1a;ZTf3fXiL7Z|Cw{JlfFzLJHpkt}4nYyMm4ESES^uyD>ZfA}fGsQ*2ongj>k4HykKF
+~dk?7ICJJ;m`|<Jhj-;ifQ{Yg}*a^Vho4!?k)8m`yTT4L|#z;^!)5B2FeCqK=+TrU6y}r+|<ttPvO^S
+F=0eUEcxk+J$$$AKrBI>2!#utTLD|hGr_STm6^gvu3BK4zaa*oFwnTPEf|T3H?7)F;nUJ_j#S)(z<8L
++5(Tz7C554Ef&{(7z}mxHN533Im_RWub^%r;LwOY*FD=xtad~b0&{yhQ%}dA&d5v$Iexo!)(__U?fu%
+o_gxFRizrv^)aQQA{BX|^jswET3Lw&d$;ut;$jRh2EyM=E;><v-Ul(9sr<1AA%OYm#@Rhr|c!{e+J>a
+OImrQX>?8UaN^vyzSRgV?gvLP0TxcmHN>Qu(r#C5q`D)+UafWQNn%}Qit+?hY2V7F)Gex{1g_i|P23R
+!Aa#{8c7X;uz$_IohXL-n$*9)RJH;l6|6!1yW_c{JR1jvc(ceF|E;!a5f<Zo{UA#Tet^*rU(xScHzV^
+J|zNc7E;P+WquPeJ9J`&+Z9G%Jze0&wE?=iz$oG^V!>um^)YBTkmfrEQUuD&@PIy>nYQ1wABxlc&(_a
+{v_Tx!(V*TL-hlx$}hbfDvjoo5bK%|>kaiPX#iaUF{tBX^<<c8))nwORQIo=$Habm08jS;nDI=8fP^A
+4ZaCu!`;CVit}CeM+s8OORM_IWJgq%A#O@v4l>cN+lid!Xb4`5j7~lp2bu><dIH;@o08*@yOk+4OW?(
+hLYzC!KQSJ17(9{pr7ZGbHbUl#?V(|Eim5<{!OBjRMV_YH;c*pC@Kv7z!o9xPQO(r5O7bq`}*PUNI<~
++^X*;J_CSb0kjV4$PU&!mSIn{+X#(5(Imoj;CEjT%{_FJKpe<Ur35nY=TluK@yJ07`tl>@C^gpi`MvA
+Xu?h8d^dGf%$l)$c`q*(;aeq{lIa23ygNFR|QNNm?rx74P;m)HTg_GzDyoW$ILM7b!Hv00crN*`apm_
+niZmn4_j6Ya8%mHAoZt?KoU>9M0DWeaG1^*WiGfjK!0DeIxn@eEZat37xk`n77K7ni)GuqBf@DFD)%@
+dRJdt$`V%$)l)uhUYOqKiv3tAFF%jdS(dfGh(CSbw_TQtMT$~PB3>q3Vu#mo!h|UE;FyQCt{%MX@z<`
+jr=G1V$losl@^5w^+gs{Y<c#nocS0g&NsJ3Ue<y$VvErg)p$0bngWwE+M#?~Uy0+^1xhRrnwun7K~%m
+T$`(wtq1{KI&x+-hK*&5bt;K<3^<VOVoACW^YEaNODy4>n;T9yIuD*x=k41b~h&qUZt?%a#;K;X3mnB
+A1%?mKz4~x-J7G$mET|rcTyk_Lz<vyUc+_wOoEkK(!`~8H~`6%Ozse*bOs9)}W0Y-hlnr(<U%#wJo!i
+k4E$+&pAGVyYkM_sstsJQRt27huqC_r>WNgd&_vK9J>$U6NfSI;rV|rCeR5#R~W|v4p-$RunyGnaI4J
+7OrCPzULy$w`E=8$7gYSuS%V`s;i3SgWJQa~?vgGEhky>zqBzf1SNxP_r%V(Nc1Cug?H+~i^SNP3KmP
+cm2}GEHtn&nlK*HKUx8WQQ{_yJT!Aw0ckzM?IUQ}t_Ts*qa-GiwQA{BmMRhe-2s}BJ1<Bx{>^gJCTM^
+$u-MQ>&hSGT`-^B<!o)EC0O4@!)7;+GPQ24$q+_(e>fK_QYtP$Y{Oc8$vsl;K`-il*~kK7fJ9u_vWB+
+wPVYxuwM<*9(s&^@dC4xa(y>$ZWuPK2KwNb7lVJ)uy5lXVBpD7i?gDdrhP;z?E$yKfNYg=HsXDgrjg?
+7Zii@);~3kyf~esDEr12c^Ifl3VO%}Dh}x(zVbk_7&Tt}b?h3-R9S@1v2r|i_8|vKFr4lW+9EW>8a+1
+4<F5iel2!IrlO7OLJ|=qdAJ}yWuuTssI)6+g>_0GU=-AM*yAff>f(jRgk3_*(Pkw8+@@EG_Uq1fm>}J
+CT;t&)@WGQ~yewEI^0;$QWc7rivjNpT~Xhcyfy43Z$p`8~%a7bornUqHw!eE>!`91;UHD=NMCx+*^Yw
+y=!{?jkM|CBh9U4H)=F%U}u{xe}$4jK5*iE~*x@ShnL=2Am2D`IE;ChVV1Lz>uHg)_wZP~37Bn_ay+i
+Y{JuPj7Y|MS;J9Mpz{?X&{t^g#sTn3jHYqrb<>lN1;&*Ko97s26`e!2)m^(bcOjwp!8B)Kf7B|o*{)2
+r1rAjmAP@bvT@TD1Z<O4I}CmQpz<1r+ScUR2Gu3st+d)zxo(RF@j#IDdW~6R|6TH(0YoyMp4}nuovN)
+nj#Ev$*@M-lE%^hi4)IR%5!8n#k00+<9s+)ID3$}P>bX($!^JjreQxhL+YA`T!tm7Kt`5MkTnJ(KY8*
+inZV@!^<%bV~0w7DPPcG38qWQ4(Mq}cq0=TF0t|l`Vj9mv@wnm#+mUCe<nOagYbs*~&z03$FX7FH)g*
+(wq74JgOee_%(ZFlGjhjVIw0dvkZ>_*yf9T;r*Wm{wJ4#<@n%?@<O5%)oMeN+}#YzYM&F0gE2TgrqYA
+^3k>qcu;+4@NWQ)K_4vMbmE*@={^>MR85BMq~c@PBNBeLXwQ4g#S#3>tLn}ie#DVNG-u)V#0O9wFC``
+{2i%<tDf|pQ6No3%1C8Ic0%%3`6)ApKrOUqF(KHgY$JdmUq~|PiYO7EAxb$@RkfHi=ctc;a_$>4TcP1
+i-CSYNDHDk*z2pPYVPq|^?|*rJdZsSwfH7dtDH+4kf8Ah07s|9O&&Aa_f_B=1^#Am0RLn?<jH{ZMa2W
+!+O98ZO-ht{oX7+73x$~fB%r2i!X$TZw^4PZ%BV+@|<9Az^qlRgtiN|u?p$qG@Y}6f{@V}lJx}Al*YJ
+h_c=ye9m!H#5)tL)2h7QkEGao%}q`d<6WAXA=?##?<LVcv4$JWhApt!|R({=6<s!Nf##$;ilogvq9CJ
+7=C@uC>v-u;CsLFhYSrVl5M##3JAfUHk3#oJ%qqLlyroH9mRy>+>NWFa-|YbJ8ZKyap?Z-NlP)k_CxH
+Sw?!VWkpY&yQUyxpRZ`3-ie3H>{?5zfx^A7QSBy1=IB1q_D}jjgK95vJYZqxWl`njEl1HM8}$*u0ghI
+YuF$%zvzA?Hr1ccls@&zQ6!l?ulYNSAgYyRuJmmnk#g+~;sHf>CZ&-JoYuEyRee~qX(`PREI&lm_>rk
+xTIuP7t_f|a$=LvJ_nk1Ab?<kz0N?<?a=e#VS!)=Bp3=yo$%leK>M9envAaUwK4uYV%WoIodKTDo9<y
+llmoZib~NRf)P++;=B)ytU!YKek!sdTrpA}MPyGgmn|+cdl-jAlU@%O*nLfMG9etKPkSp`QNZv+rTCN
+=F?7bWi3JbOGVS&^3VEf~JROZIWq9ie8IKNHW3Y9E?!K{+xdAxcE7B;`u_AfGwDPMG?4`Mu1tY4t2-z
+AVS?tv2wtS0HMyP<&1M%LB(jYiwzp7$NlLIUV2L-%o*ZCEVv=Ud^BPaeS&}TP^VdQ(fW}>a^chPhFW`
+B`*B*xdLrP7az4XQ|E~Em2i7ehZHiZ_CIgM%>gF=rw(7RtflL5P+3r3B_2r-ZHu1O-k$22_e1ycI&G;
+tXo;az*2>@I9Mys1l{03mGAUp0)X>qi$?I;#2(L-TA=4hA$7I)I~(-$Wvbc!Wgkw(ng81TIMrlt5C2M
+pX~c|0pXpjUN+Y3MWv2kyBBo?FzrCRMM25+v!!b&KE*QeoFLw@R~FnU!sgwsWz*bs!hW8FY&rf;JUv_
+8D^Be1(U{l7~~^b{aN^<~bOw>?#qe7C&jYdf_pnQ1ap@+DZ5k*~(hY9wF{El%3;B%ouV+J`<#xOUzHK
+fa5SBmD#y2qg*}g(d9hJ<l$tdCQxrMRqwuiIE(QDgfeUQKm^9MO31EsN8Gj)wqP5<11J->Fb1fCd_{W
+f4^Nu>!?BwDZW025Qc^1%7|6!PAgm|z&-nby#GS|Q(aFXvlpJnIU3QDM5t-cYNP#be#YMU=`P@3wBR$
+d>m;L%ytA(x3ROcTF2+dK<{;+MLyvBip4EQleAJ&u4^!3Z%f9`>N@mb+;=8u8UHw({sIER6f{&-vR!N
+@0GIwO_H^bcjz$7x{w_JTB0HjO3D3a7Eh@1<-Sdn<Mr^oH5MQLMyU1d|TnVTzJa*ky*9DAJF_kYc2Qu
+0<QxsxYWKnr$j@C>9;3at@yU61PO0YRLJ=1j<H}qDn3XK17s@Af_KN^9`ZI>p|WOUW~}6L5`mLtqs|w
+bg0E!9pF$nVH1Z$FW$^J(`(p<m@b6h9CaH5|FFkrs@c(@<$8B<2?fn2E6wq+G;pJIMfCue0Ca{P(2$c
+cNGR+5bwV7-TPOyH3LM4UMh(wHB?oM20~LspjJb;AFO<{K>dAwaz@_<avuy)7lBgiY3$I=Yy9-n1rTt
+SvHTEE~%H(Z(pn};=GSp+3`#-|oopr&_pd1yfIfr9;%n8MxSe^rgRmYTRG$>B{6eUzZuLqctC+_Uw)8
+rcHLu@JvJOxS1aRxM}_KhV$%T#C~f?Qx{(c1+denf#-mcBasAyzZSP7=il#KBnQ<dbulnZngGB}uz-<
+aruE>NC^BWIh@9J#?c|R~IB5?Ga8swKTMN$r%t2p9NOWVWtI8q4_;@{C)uMwmW}&IZM(XhjC^EN*ke;
+7j@F<vYfEIneI=wN6QzqV2;VGcAySdoL${J^+g+P*ffs0viLvAaX=&vS~qIIjRxfvU7Q4tE>X~&XgB~
+uA_wNsYFJ@#Y49@~OCYjEBqXs|khOYqI-;^VQ_73=S|dg<;3$?h%W$ij^HhOPI2N}L3FZ%$J?QOA9?+
+66o8VJJFfUT@Ew)VF*jG%JokdB!;Rn*`@xu%RI6vNXp-}~qGv33e6efHc93}uA7h<1t8V2f}n_WjySj
+20&Yk||Iv1J;Mjp;ldoF|Vbau)ySXR19xN$gx;kT8%i^Lt2>^TD2BE(EOXk%_Gn<jIOJ3h0L)!#Y&IV
+5Z^`r799#bG~Am-V^yroKZaumEiaw+dXC|nN7p=>^i=OPTvkTy5qbQT0i$VSL%L-G>D;k<L4X(pm>t{
+)6vb%%@O4++Ea&lAi9I76$4{ZqSXnA^-w*}bJOV&b&8k)(>)_Q-keFHAd#Fq3yHxSGVY&b;sTubS?!T
+p?~Od#94K^%fc-RmuaP6pV=Xqo0qe7bi6QM(`J2+H>_{0o>X9a9DRBjyEy4;;_R)YwCDVY=<&_EWI>t
+pv4;CPlcMcl~FIFhJRK39~3~qo0lDlRtf${+mz?36KF;~JQViEOMaW3+BBr%x^5`{dH$sb;wp%dh%SI
+=JtN5l}%USJJWf+QTq)Fch|ic!elP61893Iie@la<G#k+8%nt2i`~#RBV)^zWQJ;j$@!G<2$xB8C5PI
+xrLDAUKn0JnwyYoIH+`<v3K#lxqXV$CJtZ>@RZW4B1~~O>rtSAZ}o%&!DhF_a8C@(hnpB8~A_IcAoDg
+6EHEkqw`+U4WnC3oEsy&<>u<PCBm<66Z3oO1Wm&+>^m3AxFfB4N+g9_j{y!JdpqQG^{hNv0RuoTP^@~
+SM%885-fc(8L+T*nx}-{G5|78@QGnwX-L2Jy4&-ek9=T+|@;OxRw|Fra5f*D&>r#uOkH8OtWLZg94lN
+exjzA=hEr~ioHF~oJeLvVe_ZB^tPfv$9H0M?@ft$$oy=a>&hgW8hdTZi<td#G>GtRksXf7`$U23^BOx
+{qqg~J`0Sp2SKN4;Dkm8zFJibUEHu;ei*?*fcr^7Q*Y8L}WG)34Ee)*y@9tVH$V*79?VZ?JRRnM&`h$
+SQWy11!$Sf}bmG&t?F>rK?2T$$WLTWU8K5w;-d=TYOOQf#u#q0W)7NgCzu9(lm*40&fA<0f?96M7${s
+ls;a=2_wIkn#RY5#~tY29<j_Yyf=D+-r3tGQ`K1@n+`V=&|Acb&gOZnpbfY1Ztm(cgB+KVbB&j9Kd;Q
+s<(Mhn-_HDe2>UY~9HBy({b<K&E)t6!u9Sl#?pDggxogvL2E7;7mwbIBNxYoEUKByeEt2YI&Vo5wlN@
+ew;7BfpI-|2=bZC)%fE1Ft1_ZEm+T!(ww;24w5C|WUK!1q?$~{Fu-l(Hqf}30z{tFw%y~hAgVRO$i*Z
+Un35cJ9Ey{U7`j?+`UB<4OpSaMfw7ORsX%;(_jg^`@|&l!^saEnM&48;j6^iBy`NxxX23DYhXc<7^FT
+*ICxy-R80TyEwT3thQIAcwsg1tyW+x<w}B>6QV5Lr<eqB82ZXEVC^Tkl&6bCPg3b&h0h3ie?D&=97<u
+Pw_8Z12<Bw0tF~?R~^pPiDZkuK!<C+mIcB1C9TCNp%T=m^deQ?KK>TT?8)QDL6WG0@S#31UU5|P0Soo
+gOM<oJ^HZ293~gW2bpqLj{D;e>;SCRrU1rwj!AHZgB@M`x7yyUk3*^39E*}`#Z|sE!(Abh9_c5BUJRE
+)T#%vR6c@qTbKs}nFvxF|V$*+<1=bZ98^$_sBrC~3ZO?E@06h}NM_sb<aNGY!ho}SCabd`7D(gk;B&f
+x(NO1Z!|H*sUM&-uO`WJo3pxuk68{vKBkDKMm=^?qGo`Z8+QCNS$R^LQS)3*(hdHK-Nm4RH*f+;JIQ@
+k5DLX$OQIfV61}18|?)gO&H-UhGSBo0B@kTtd_mgBw;djBC^`usB?GmAhbeTgp>UDchX}ga?KB?7KBj
+>N4ldd-}D(;6H%IHH#LONmRz=Uu%bJ4k$wHh56Q9yL|F15W{OsUz$+l{LLRH;j%NFLF{@bL0_1Ypf*X
+K&!V6uAHdwNl6V*C$PJ9y2FA!oWQz@EpAx@?EzsR)yyq8CZjv$tUoM19oVZ!j6nICDEM~ti>24;3oa?
+g7rtu~+mlB$Tz?`xI>TbI;ss;@VkKb0|utJ(5GnAq{{YY4=WjAhBw3n2^pEa#bz!7$-PP~~F)OW+tfL
+)c5%8H1&RV*WVtjJuAfMK0`kZWRn!)$=hT<O~zj7DV5#SXbhxB+D?j_p;?sl{aSI9|%H*61nEjuZ=D^
+_ug&T+J}6F(?fWF)SA7Tpv%?#!|2LCo8OH>LI0;1u}b8)~!ywba2p_QB3NA6Ff?;a7B%+xy6gDFMe=%
+9A`lB5@jY_MV7Xo8sBKIDrVN4BgvWEnJkZTOomm60aa0|L>G^I#sST3TuVGV9cG_!RExwL{I+gWtH*t
+DvD5n4nbDo9Zdjf&GM!9;qT(vU2@I__9;cm`ShOuxS7dPtv(Ia}Tnkhblx+vY;3g5mCNt$<k{2`pSSH
+N(b%#*RnXu2Hn&qDlSS-%#x{N`A@*LjtF{cGvI-uwx0WoJm1^*VcJKq7(6CGuCw0*{(z4tcapG9j}o`
+nUFiJN^7f9V93NgZr3)e!gXsw|LlHO1BGVm^@?RD#zf^hUei|IFzS6;$d7I-EJ#($0+|oPF5uhE_d%2
+uuI)Ar69)IlKY7tTLy$EtlBIn?Ej>!zR7MInw&dU8$<B{#`fq|1Z}6hQ%rd#R6U_!+EQiz{_{FI8sMR
+N~1~p8S9FG3oA*!dGgF0+K6sDmg|51dRhrD_4!{%Isd~5XZZdj3f$wpT?-z05~Z=*8|wGmZxj^LJxL?
+<QMC4^?g2vSZ+I$tKMw0jH@Yk-3Tq4jYrb&kh|a&EIJEFcp^ywU^p1Jy+6kzbb98>qmvZJARIauzueB
+XtyBxVi)Z9&NEXGL~XYC_ruD1ay`4^|}!BKp#`Mt4)9zY>|3k9>rTRPf729>15{B7pshZvnZ;QL9Gx8
+ZFEBX_skTBH00eM5UVOctIqwBC7gDjBVs?*6s}w7Sgj8U(xZ0h<_E9OH%LpBfuqw#D9IPR6hwS~s-iq
+@F#eFtY(bw0=lAzQn}eZo#>h#lQ2VNAhwFc_j>(p+n=8N-6v^q+`_L>4)A==(zPf1}`xo3`;Ls==k`X
+nK(AgD+nar(3{ptCt)6P8+%NOLPbjbiC=1Cy+C~BnDGHQlb}@+PDyXqX-%$JU}10srl>HSr#I+PSiAR
+9fxXj@0<2H6;Amb7=Oy;1s&<=mO<n-Lk)r72k_cx=S?+d|iX4*YK&9y|2~AP*(n+2G0MvM=6zcuK60y
+5Jmp6itBj3II%GT}|!5&1$%}psIYzF^IQSj%z{Yx<b?^Z1vm9yDrFwR_W#qA(2I19ko&W=gyteHqIzz
+1jM61vDWq3J^Q8(_zp+$T6_cU@^NoZ^MfA!v}(wPFIDNNQ#;Q*!WRA%OIS0hh9d4w_EZ0f8a}9Inlav
+Ue|Vy<8%TlpN>!Te9n{pc@YR6GS!-#ii+yYX)&InJ{B$=^d(54s0t5Y?J#^UJB&ZbMA38uFDxl3J^;}
+xlp5-jJJ3NCp+m3pp?NRJzd$YEr<&4P&Xe@2fSA>4IF4QAI=CIdQVO=4m@~$&3@1W@6_1?I($#mec-z
+<^4SC0eIL$Vkm1X6LYTujYKQ3Z<kx_$1804lF?4f@352+U!vkU7cifW$U3A+M!)V$bayhCto<w&Ju;Q
+dA{4gC-^MSm%p|DV|LQ4N5HBl*X;?Z6$OgO8{!INDBZzD>A%qfTQx)%qSv#f3q+}TRNlLtGrS=>YCGY
+5D)9W(3jJO;n>t?iKEX6iF?es{gTq~QTf^X(90wmVD=wz9L`;JIyK!=fV^Z<!sh##?L_Qt8-ziBX7Nm
+uv!2(YNoJVIb7_-XXWM@nxpWBM-7i96sy!@o)Ru|4t>wsZ9rn6{@~dt1gvA1xWF{sh-vpyhCVMhr-gb
+*dV}Tn@0Cliq(u%ejE%cL>veZWouA?drH@x%2vN<`<1Rp+3InaQhJ`AOEAK}LZSgH4KI=dl`C71NmZk
+%gkhXDDa6RqiXlfuObEO%1H#X&iT|^=N9I1`!b6oZroCq&48Jv%|6zy=5(Ntl3>@D;D#KV4sXYA3CtL
+kK0%QOHQ|>?tJyoS7J^c3J=$nu9i>Kk0)3alNia+9x`&FY>>9*cRcd8E!cx<)t<ES(Q)Z+tpE(y1mYG
+WpxYXwD@C35h|_rW0BXUieFVBF7&Fo`jtT8PSt%Z%gH|N8_#@FR-Gu0kdtZy7mrEGD*w3n!U{++30eX
+JZ60WyHA?$LcYfA2zr?dM|#M84~5_?>S%LG&?u%0*m)~{4TdCoh3Mr4yKOk8vSB$im^F!-{?}KvM#G5
+D&Y_0bb25`E4~ba>~_)TJt2(D@&*s5US>PIuAE?T@}ylh*S+AyuVV7-hCLwrXj8bEZ!g&#2W#iZ3eJ>
+wH#4du^hO6`Gg%<ZW$dC@E)ntkB-b5!BOTAJV^oFSS!a)+*P_|bD~#CmYU@&i#aeUHm4#>S_5`XnXQ%
+K!k|*DP^S#MLD0PQ#;l=r)|J$0`l*Q6z7utQ3lD$Rcs;X~bK`*pT6VA|;i$|;o6DR{aXEHMa9=Hrp#x
+9qQMK53`+u~|Ac=U_XNcl<zCwS_F>PIBuA&~2>aSbsabdP;R(mL2~PP&PgeiC0d;<$_kJ-_~-UYpAS<
+z9><_B^5LCOxDPTMX&W?<O2+<XH2sZYG{&Y=1%v=T64mN7izWs@7QCR>kdCnEd_i@ubn@qKR*UN}Sg>
+&w7PF@&P>e-t&yC7<qPX9Q*y=%UFuhdoyinqDx^6uYZ51!n=648aNQ{FLc0c3ed{17>V8&Du>aq?2t`
+bX+N-VsrEuTt&!c~MJ(pJsCW_X#CwG8NF#T-B=SW(5N+}t9$wu9sSb_fBt|r2?IUyj$*Sj_naerp0EE
+N9<Qn*Yd-!kC!Cbwe`v$VorkB`kH#)0L2l-&<BmNz!J}1=LOXgeWg}G_)vferJE{{|4(SAvVi!hq;d$
+I~XFF*bgNW01H+FA#{)%4}ChUY$3KZb7_!Xy7Zg#cSh>0QLci@*K;$#0;Dy^l{h4WdQzkV|;=r!71Tz
+`Z|vee`Umj)08=F&;gAlEMZ@b|Sk#a-6|*{J|iH*$rjyH32m1W5qMGC@jzhHoR&{b3>83#McRsD>in!
+ixda|XXH3!i7-van3w-zU>}#ElI3o*ahqb)-Dh`3e^&s}pVz6m+067cb+*fxhf6LwaH(=|0Eg;N_`)<
+?K#K9Klo10zz-sYnkaNv1yDw0E!b#F<kATA?Uv0esDUFdC_3Y@p;CDZ-90xowD<rk+qAn?PHT>?dLz_
+k?0o=UEQPDeR(5NqHywt8G2eu6VAu!>GBjC_;G5l&cOvfKX<-l9I@8vTL+9f*Ov?!I*9PfhBU|YF|AR
+-dkPZ~)7Lu7F8G2_KY9qdf3c?2pmov~pa&KJYeTr!8@g|8&{p~-z)1s)A%J{FAunH8Q%&_j<0JaAu+$
+XNBJS9b4-KJuHKn^xOfXQ;)1PR^3W<H`2KN_^xJq4*+@BGoy+L!92>;PG~D9GriZs_{F>?QJ(+eRAm(
+>{+2|F_m8FTej`5c$l#86SBMdB0RJZvlV~*9{|or0ThXOziKb-qr`=QRbd%x5;koj!;<h%Ve%DSPmu=
+;(RJGe5$^&>15byJ9e;8%jEAp10fvZ9Iee9Q=VXV|ttTdrR`?;YIc81ag*2<ny5?gi7@aRAtX4E8Nm?
+$GON}t(-=UgFC(Eg4drH}g!J@5?o;~~SACJD_BuIEfY%zdgWCnDVoNBG!zEg)!zkB-3U*SRdWb?2cob
+7!-<yVNFy|DYK?Y+ix2!^+(FjeTc$FU#ex9YpckAr(<LjoFd`p0RK>ILT-iQ4y>2l2(k38BOsLijRz=
+^}+Lz8f9t_kXLQp0W)6Ylez^%Ike7ZellW;@6#7X6oKdMBY0}XCC6w<j83QPmbLJ#JlUdOw}87*mRDk
++GHp9#x<Y*<U15|eA6H*ZRXgEq<wqu^<9}Hqzll`9gE^2UOGNkr~NA_SnUKw$#|gp)297l@${iPwL!K
+1KAF-O0QAzo3Gs|5Y*+F5$uJV_*08z4&KNuhqpGZ13;O?0P)h>@6aWAK2ml;P_Er)+-hpcY006fF001
+BW003}la4%nWWo~3|axZdaadl;LbaO9oVPk7yXJvCPaCv1?J#XVM4Bh=Jh~6N(4YYI%5Zv6}+ASyy#b
+RP2isU2Zr2h9uIc||$xCs1skL081G$hU-lT_6&_~=QXOCABgNV32_G3;D-yg2qHa~fQx9R<o0Fgi(5t
+m59lr)V++IwDX8q}(H0cppWBDIGz5NF@jtH(6LWRaLkL<#q?fM5xWkA<*vCtiX_uuDo5ZjWL^MU4hye
+qfd;!{l;zJX`sQj*Mxn7mv73sKBUeCshjN*{8T{O(!6uq*8kHrGiZ?^vpXY;3!si02FDn4m>^<@B914
+JvFmj)m*?%sYo0QpRx>V41EV0H(L>GncSP0HF3rR)``YKy;m5fSQN%eVUxW#IiCPb2)gJ@OqD3*<&qb
+TfqcT^#mFzgnMep&jt!ibgxnV0dMjd%iUs^UZ7m{tjSl{d1tUvEyH{)&1ZRO+EM*H4(DOb5AD53Hj|4
+{T!KV1qdRXB}@eg#a2KL4)%0Z>Z=1QY-O00;maO7>Prw^6HEApiiSb^rh%0001RX>c!Jc4cm4Z*nhkW
+pQ<7b98erb7gaLX>V?GE^vA6J!^B@IFjG}E3nE3ODUO7Cb`|LYLqI+@$BR-ud|)K+sdXST7qnjDN;j_
+cC=I3-+ui92!NF1%-*wZR8td~1R6lU(B0^U27|#~rGIX;sZC<EF<Dudy}!qwy}k3R%&2v_Y;vtORe6&
+wwNa@$<1VVa_(?BnRhMd=7U`u{X|YrrU75_(%ILbzic4s}s7hnpfNHoX%j-;=u}YizYK(wC!=IyMZvg
+Yk)|;}bRcY)uvvptVY_0cJRk>D+GS6XXoVSvf@2aJ)^zvo4sJYEDtu^*gUhk#O>vWIbC$p@mbycMKtf
+{ly0jkSck=EIbo|(FW6-euJnQoxDYxd*$`THY&W?R5=?AzHzYO=))A0ZfNu_)J@w6<;Dq?--EA1g*ko
+?VPpQ{_LESwUYmX=SwQNjS4zhkFV>r-IUBdil?3HKxbh_NTO(Vc*#jFv2hN=ekN4^-O@xV5L9VPHSCV
+YWrrqH<EGn=Y`$`c;=yxubSdoFHed^xr8;GR8=W}j!VF5QNPrkH?NADG|!f2iz~fO`O$e<zDbMisa|F
+k(9;|E3TEQQT<TTY<n@dmj@2?VfX2lY{k^yMK&{FO=AUn|VOHp+x&l@ht4iz7o6^YN*h*cbi|gC8S}G
+<*c9G>-y_GS6({;-SL!}<5qWn3Xs2`p_dQ9_udGf>2hu7z`)03C4PEU@{XRlwqd3DZfanH`qkIrB5v-
+gz-D(a<BYV4D(U8||nx-o$KWlLfD!@aMXMcq{G+vC*eSB24q$&gc9rcVM^zH15Z-<_VH@q`?DbqX?M_
+~E6lnSF_gfF0Y%y12=zvY3hFwl4}@SIqSM3}wEoHT2Hx15@T8SwYWA-)6;fc2O?3{J>n5O%4yXo79-F
+EwJph-p+uLW_iXq1o{J-SGoc`t3_TeuE#)Tq&ldm+pBDG1z$i5pe6$@NEeHy0@Z+TQ*{a0D^SPOdY$Z
+LEBu;l^0Y>lQq!p#z}%jEH<-}q8#~U7#!*vJDha5(6;Q81b+QK>r0;A^T5N9*kS;<ensO)_(*8YGqMF
++WD9Qi~url@3-H3++?fFu}4Avk4pmjHZw@sDdN~J#ufL*c-Hdb|djqgAgmWUf%1!MY3gTmP4*&=hw9C
+21(fd+HEQR8Dv+aN3CPnvn6UaeHhG_?(I1HpB`>$KXAvH4crW_hkIG$RBcmcUIQv#K%JXWp)RZkM`8U
+yxuSl5l{xKyStgvlobtTd-~C`bW=q_K(Kl{twg(Vp0TDly$H)HPp#vqHc7Rt+pdO9JU%d*cq%3q`z3`
+VTahVJ&Xv)Uc(NX*oFjkbiai&qTQmW9%~IF8H;B&8udU(nhox^oxaiF&{yzws@LU>R?yfmOM#k1CP8Z
+g@t>#@-mSRFDys~=OK-|-snQ%69T&sEkmWqYFPn-e32jn*mQb?-pw0-`RDHZAVHkp{xEUeSMyr9YYcm
+`n!EP)^d?F~=4S--D2e3ss>>m-RkI>-L-kwK~@O_{OXn%7!likju-)(+(>wxzl_OurgNTV)Fuu7cqg}
+fvH6#-0mZe;1fe}!JaTSVf8UZjoDpg~)0!E->h_{%=1@(q{;dViume)>Xk-13FGsB{V~&-|ejm<6!S=
+i9^yaU{dC=`+3+U^;k_fKnI^?6`vw&g0{!o%~LHI%3`#B6xAnA%bajiQCcWU!x>Q#U6dJ2(t#!o9uH|
+Ozb92du%1IW_4QOY>m!WXzG}aC;EWfQ=lYhdQ`WkvYrIK;Vki)1*1NkzCtw2=ZKK`+){-F>t&-+=up1
+ECI$;cl`A0TZOc%w%OJ<VI2IzxGj6t^!OJCSb`K!v_(ck~JBV<ta-D)um!Q;CvnhG!D68x;1Djk~A`r
+{E#`SHs&>lSKrBm49O><#zN=4nS%t06e{lUr{C0<9|nAD;%H5g56#4_?kV`%eHS1=~HJhYCyyv!D3P$
+uBypj4=Id6O13xI1NIJb=(`0W;CG3O5JX_(=u9L<Ns-R^mOSNDbJiZ$N!|;L;kLkBg?(?WBo|%_hl=V
+}h3A_;G_xxuMu|9|!iu;8W24fjVx$J}GL@7C5!0Sfb`Y-Fa2l8|(Q2z|HmvFd*8bN`OXy0DoXKWyNE#
+y_#C-^(Lz_ptREHG$Msfb9qS|L)xAjBhF!e+(y8v6tx6X<2D2J1)BEY=<N8_E48>vaZ?~atRNrEPAG|
+hysDkamuJ@q4+sDPqduJf@Ju?vNMvTfl<fRtFr*ks6XJ-AvLdn)gOEYAVt5)IA(*Zs!H!v-mx?T4;;p
+f|MSeKo&O`#&KkJ{6M`HUm;qJo$w;zmx4x*Q0r*>$2kJX^5SI@j&(gW4Op3^*Hl4Iu$8Tg`iN_dFA0c
+;$%_$Aaq-~<BoaSI_dA3;Bm@4xvN638f66`2G}yW=p2!(4rpgyWH4yaWtbA9*OVXxD(V={B=-^d+hV2
+rj3oi*&8k@1`CA_juBW*Ym3JrS@zCD+aD#fd4T8D<ub2NuqS{oc?XKB(IX~Te6tJxLbl_>H$L+&Lnng
+F809;NARl*R&}ver#~F4KYaJ(pIG9c%{6%H&P4KcF7CxRj&*)b=>4*c0V04JHyFJ^Z@+X~W}xKAQp07
+T1~0ar(ii=05P^uYKyM8L+<7=R7!1(lXd!+EK|9p^UR!c$K`w^R9*v1TN1fIl*&@iM3)*Y!KtFx@B!)
+feCHxO5_<4ICYJTKBLwso>9*`HKVx%-s=`V@cpaE!VErLL)6=)JtpJ`{wAv@xuPEWho9@K`t`Jrd8vg
+a=&4};(U8ABa_f}R*l9U`Nn6Hf0wwDl)+AA<F^zbD1cMC3$TtFmNkXbn~YZ1(lyD%Obsp}=U0*5|aP4
+Rbi@Xi-CI(}Qa^{$D@0e}Jmh>3T}DZl7ZCpls?XBENmgKIRmaQTuSAtGJznQlh8ZOamdTw8tYpd?=C6
+8S0KpiNk!8t$C>n^uz#RpjB)Gg9x+{%*1*0__@OPF&f@TrE9G>3O&JVvOVEd2?m2}3;G<IB36?=>zM3
+fZ~b77fY~-%Rq5p#jYV&F00bnsJ0$j{>vnsUfn>wGkgqlp+_R`7v+L(%QEs-w(O%H>f%-uHv7JA$bGS
+0cE3wJIrkwO6-pnowG;1Prndd+O7&2SSO#lcXB<W_Oi)DlrW<76^DK-B1c=9P+MO|$}47i>P4*HTw3B
++wc@0fCN4c3+^(R5ybeMLJwTJd@r0O1g`8uo^i`@_lVv?)*$=&#X^IaTRx0wS~=vf(<DIWm7o^a1Ua>
+tg6*VWgf5U#-*6tt9shmS$kh$C2z|ryYJ)gA-V-MoaORF6=KJ6AZ@AQ<&nH4!917oicKXEnuw$pO4U{
+&(S@6u_?<u=~8}?mmmQhkg}&aTMPrLU@L$El08g;83?KqO_9gX9z6s1m0LX>#png;!8kWqGzeihI6NH
+m5RSF`tYWG5L=)y1SZ?;i4F{7!g2yJqj~zSLgD4x=hz?gibr$=!tk!9s{f#7@_5^V~YjiNJ>QGK~U@(
+tKITTauvHC;uIQcG|W!DVtECe9Qw$|z;Sk!>e(_)>q3u`chKmm^0<mo~WZI@{WNH_tVcc;)ZOpo@AIt
+6{0Hqzn}cZ0mkVn3t{G(u4~f_5O%seS95>{~Z#Om4E+ovrQL@zyxxx_=19?bTsj9^yvaR13YYFnkKIP
+}A<CJvcc$T$bxJE0Q{2cH564z{g-P=Nb6@Y%Ih0PyYDq_vFBBG<1L$o)?GA7E>7QA;CqVYgl0y!H(;R
+mo3we{bLkjo|t$>?}8Qg46z??U<r5X$WXT@>8?s&G#OY99O)Ux&?G1o6P%23!2TuRvAMt_(Zh{d9a{6
+_Ff#_e96o;Z>}iZb!iaZRMmR;Qy|a2cJxgkh$6#r-bt-neqb1OAofbgF9W8rQ)xB5p<mn$Db!DlcAh5
+7En%)E1=?-4&;<CO1{qLTfZ#NqMKCjZktaNo?_sBt4A!2-5JZr#AI81jDy<A{J7n^c3<nMj%R&Q54!-
+K`Nu><>Q7rJY>zUDNA0UvJ<>?9(7vd0AIjoMRkgYqa2sf)MC4(LwDyAdo3b7~jdOw<b-1K0bYmevibD
+NrE|SpMY(-Eg~@j>#qx(8zuao(>&ClK%`k<0`$;=+JNJz@veEX&EYv{-gSij3w^Go}33~_=Kbi&i3zu
+L1Ha`jqX+z^5E-Gd+Zca8<hPaJ6!o04^;5T)jO|ghbE`RTKQJ%$m1ThV-retYb*+2-BVv3sa2X`z`E8
+s>|c0BWz?KbtHBS%^Y^ltBXi9;pgSDRC1!(BOOk{T;7yu08g>gq2l{h9{Z21(J$J{T<jC=Uham&7Isi
+V~nQ0L_7DWr;1x!jTWN*JiC)I|TTEj550xgU_5e-*M=R}}+=>!D{*ww$WGDGRIDgYEzk0$e4gqpWQj~
+dlF1-f|BxF+;CmTCobI>2DB#MV1|aJ$MrpTT7zbXcP^iFe>}SJ|@P2a7TLa}P>8?nmf^cc(}15m?XO-
+|PQac`@kl^(y`#+~9vC^uYi0H?eUD`M1B3geCZ&{w5Tp!2k8XwgHPE2PFQGoU~q49Ki5D{lN_XGwNb<
+hc5P&<+wv&Ul;e-4g#|c2a}=4=Tu|b#CbFNTz5Tr{Crc`!+tCefj8-esyvm*G5!9f;2s)Aef|w2*cTd
+Aiya@M_nHpMZqZi8SSOwskgmtmUpc&>R3&?0j2|1la0mRkgsc|;89M?=MXSoWBIfSpd3MRCSA2BPY7W
+#&z`Pr<*)b{=j($toV4%%RhWgHp*^UJ`H(ngZKY;iKLq`0c9wWQu2%z{NI2H+1C7;%#5O<DWIzBuF-M
+lf#%iR?crSngq6rP89v_n*o1%v^7a&F{whN*~tKk#P+DZ*~=!58L5xYNjRy`TJ$Y(g1iYMotP)np_|&
+K8;qC=?ByGoS%xXW5Q}(P3&hjdIb*f8jI(KxJJuhEmu_d8%N8CYN5Ic$?haVLxXI(O9<ss4HUDV%a5S
+)@})e%;$MLDn#o6tWd+z9I~8X|66634d=R`cZ?e%Y)+MI`VO4r?UCz#lU5mSgeDPI!2Fw-6+WE424FX
+sWCCy<oVV|0?@!<T`(Kzth&6W1CQ<M3<nI<N7j6vvwg$h*rtUC4u^VUkklup@<G@1@goOmOK%bz@(pV
+b~0i-S-;b{?`{wQgA%Euol5i}YoHo^#ek7FP7o=cLJ@R&>TVm#23ss_hwLU|njsIG7aI4(-mr#D9N`3
+;?jIQuxtuH0=Jk0VhSg$k($E52Hq>=y05o}Per0?6PWRd}`vGfR!REvuzSZ;*L9^p^RNG4QF~-6VeeF
+Pcr?dkjFwACZ&#05P9u7f&Sl!w6rd0dI&7vRRJy07;ArKfmON^VBHb&T^QM6@UKvOw|n-;pkGhEE?XD
++8h(y{(P5E;zx3D=*3YfmSy%iNzg8qy((F6h>yD|1-OY4*N0sMddwonVjg+AT2G=w{{^N6pS}?#M8Lt
+>VV9q6Yzxq31EZmt0`c%1og9&is=S2-!cef;WM$RA=L_^6G3GZu7uldtU6x?7WV&7@Wp#OYRj>2IYPG
+<i<paYW*un3Ur^!>F#%>??gIv?81gVVHvyu`ikiIgh-%Zuv$CIO%gOJW{%7Z_hoDcj7zAS;;(wYz@%Q
+tFSj)7=qlhrL(n<ViW`UlLw94jLDlSkhfK2rebrjwzxdkL$u!I1htF#R(P8_beTW%d5u**R|1a=gyl7
+6oWinB!xaZB|QmGtSmu673Ba!2J~npRfR!7Vr=gpHr$N0B(7OaXj_-509RH!%8`o#ak&x^l`rTT<H#0
+gNByp!i>RTU*=$&6?){3T3v27kM-V`^{^*n%XctkYwSe}4)EZJvW-*rxV=4|0lh%Ip*~>7!^F9y&!0c
+HwFpr*3BEBBp{5gHyN;3HfKm|ltxVy+7g<391utBX{(F0-tUiAC=+UR=Jo>webL;5b?{h6RN>w;HVwU
+b4u&3MSKo02NUppHi0S`NyVP>D1&G3M`)i$D+2dzUo5ZBUwgj(7ETa>Q<h;mDVHffcvgD32d2Sb5g49
+1aKC;u5o1N<k>eDEIz2b%KYQ@bn7W?7Ndvl;CNBQJFEV4{x5+&jqHx)wjF8v|KlPk}67Xcy$g{7)aug
+ydo}7lucA(3j_P?jp`-X8JnWgyrw$%kz0F^JFu%HeFOT;~#ASz?YH-bQF3=b+gGS?YOO-lLN-Oyx$_C
+`H06888a|`i@7z|2cSVymy0sT;oWx>XY`|NcpNQn*+$6#@?rAn+Akyl`xCXlD$C>|ttL+%fA?&E?9SE
+5Ekm2ZZ}arg<L~yrjG|=%85`M~DUJ8u%WjR{U%mwEKDoiLqsz~f9QTlfoWvehmBr)>7!T%9ZTT<^%L>
+zgY~R3u7{UmcnqtAmS$!GmXRtASXs{2!PJ=82gRfz}8FgCnq!fuami@%5WV!Dm=#1pJJr=R48-k4p3Q
+IjeiL<8w(AjJCXH+GYw>uD8F(8?pV_196$C+8hww>%r@Rqd_F&^5;sFE18R&1?=NLiOP2GN(nXyC~Tn
+9SH>k~z&>hGk<LqwMK|yaqfqiiYz63hLS8<ie)v2G7G#YzU6z;<(&V@NOw}OjGpcFr+1z6&Y2jwWDDY
+Fx99Lv^ALhYKuk)#jXUgH%*QSR2;1G;lY*$>hb_4cCgNtn5r>+lhtoV%$z>sL*sWvzGb9{D<YU-uNyF
+fg)brX1({P$bB&3=$TMUdpHjjCWS*UoyrADulb9HjOBWvy_NKtS8YUaP9#J^r9JS<F4fpXaYL;ug1s`
+XVW>qvp>fWRN-lU(ib+cAQv%b((kY8o<2xuhFT_8tNFHL7}$g_2ZrEX5J<6NJ)a%Hk)jp9K~$e3hlE<
+IUrCI{D?COZmCg*U?aJb4r$A=q;P8~wln{G8+79R!42z4nT?hd7iow)6MFM6o}LR|2;3G^SG<b?afKB
+jqZXNgaXZjoJa|q!z9~p=@gMOeiYs&UxjSH$;%DK76rt`M4RSNT+w`>9&koeecL4BPE?S&*zkP9ZDnD
+hk#09H*G$5mEDQ!IG?-h>%4nV<sT}jX<sS#@Ru*6z@L)^dMRJle2Yy5Tfsi{i{*!-h?%egbU3h9?qKX
+!x(`RYTlY5h3_sMPRcrZKFs`I3Uj?l{J2P>t9^zSz*N3s>=d58T8;2F*xymR$!VBUHn50NW)y5O+s90
+NlA3b<J5BBC7&oC*NDV$$P!fRIZKEDI*TwSHciJKQ>pwd@+G;)_2YfC|;`nEJ$Otv;O8Je?mKWa&afk
+jJ43OwkbrUa$zCIw=~WFYAK?P^+%v%yg(Nf8!$11&A%Td&tX0i6`sG3rHGf<CCyO{+UP;WDpi)}7P!N
+Mv+2a<}w#vl<?#H&pUSII^{s(k!Cxtc4xsWJDnW|5Zox3`bF-#<(-uD2$i{iXNy%A--653(joGH`@v=
+O2yBxbiqG;bVo{_vh}eZ+U9sr^wRn(A-?<1Z2YLV7Zrhq5hHo}Yh#aMVtiu2WEuuil4i3(6&0QU!)Q}
+)<nSe0DaO5~zrqIS8o2lPNBH_DQx@(u{t><wKXMwDkOocg6P+N81Gh9N5AM4p!iN;CogId0Zw0G(6Jy
+`Ch`J-yqRxE3iz9o~L6~+LibjMJbj_wc#nFi?skIKB2fb6v7Myo8*93dX*ppLaj`r_>2?Rr7^#l<;d}
+JvZKDFx&pE6U0&j^*_qyD;&IP)Pa0O_yxV3dZ>B;ljCs3clMx2S~Jx_xwyjkdd`xsw6hJ>}TDSkhMNp
+xJto7K(VVF5m`RqqV2v?T+a>vEkM>!Q!^N0me3&fWZ0>3XlAn&dfR!H7v<ZNb^w;VyM8sq(j{{vL$Cs
+<mHFEF2^D4EaDk-hDHY6G4Pl|4rDx_#|834(-`A~TryQKcpJ7t0@+DY+NVT~zB(V|mta2l;0}nv_+N!
+?&nS0cdc{S<KenMn8deOPZyZcSx-%H!uk|J(oc+3?NKf3cs`-2$n@HHr5$}KpH}iS8mB9olmIS~hbDa
+_mH+h*ZJ7d$H?GKGX%{G*Y1^p7708scX7>f=D4qs+i{e5`M7578~gwh#H6kRafkL9h(ORk-~O+i6e-s
+fnH#cXFU23cBRaON_*;ni^&fm*>TYhrTHNtIqr=0owGRBt{TRuS1ZBlW#}GoWq=2i_Xc=53ci<KQsVt
+b^51c?T;#<JcAIbBsK7B5OQQ2f{^J<{iz$yTC5i`C4!|+Kwg4wIf*Ep(bxE!PvGK96)62HOxJ&u{eKO
+-WJGwLC$t$FHoQ|31f;9#OewRZ(qUCCmElf5}tHgV3w>zSSZmXBQLtH%G|hV-fDpq%%x>MFsGyVp)i(
+_@K<LDD&fO80Y%0_uy{y$e55WKzJH>`=y<$filWXFMQ7w3<P3l~l-xh$8N@kvEc9Dqo;J`K((gYb=!u
+`NMm<q{C|qu1${wFYkhXFJv1)RAZ4ee8!5{iY=jDb%V}0>ay92<Y0v@|F@Y#)a2GhB3<g?>jpT_bM-r
+{l$LRfR6#A%$O%<0Leu~kgiVZZ5X{!+(JvgU7aot*u!y}QeKBCSonevj+ab(zE<m!poJeq>3v_tDvpH
+O24nIoQAGaVgMHwW+sp#0mcOomF>6WxqvH3>R{>g{I`^c)q&zq@n-;4$CQ?Z9W(0Y757YiP3h21B#^|
+_V$B>#ZvO3@z^LBav+=9VA8)u4x+tiFo}1kw*8mB5$y$HcE!FA7bUaf^2h4oL$7x?Cn?NwZZAqAv^{(
+%-Mla)h|C%J9F!)~)&T8tJ9hgT|B$2b*N1<V$xYNd(JBi5Y>*%1@|^ixW;dVX^?mxTuv@QcaDNEy0qJ
+653_FAzlNHi&simHV`JQrDV%)aaXYFXdfdcQ|pTBzd_Utz*d=nJ}Yj;orRq{8G0W-6Hqd`jpxjNuZB2
+YHlZVGHl6R4s#eB=dEzD5_yd;6cF%m4Lw!q*}G_i|n@7g465&mt5~_Uxcu-fDKS*4Oyy!*A^Lzlr!C`
+e@%raP+!<CCQJ@kAM7)=>Lm|js&?M*_S%kWGdfxAAfoB`sDoN|H)3?i(SUR9s4qQ7D2{9FIEMq?i%gr
+FtVpQ=)O)mhWy$LA)BGkxr%sw5?<_%m(x&?6>G=2E-KA$)2*ReIS&|@dh=bCZH6Ex9)ZueY!+Igc5<s
+t#~JLghinG0pBXs1tAkB6_LIr(?7(@*ZDv<+y`0N-w%2|LO9i@spM7*~KlPMFIr{pUq<54=;a#Hp#w!
+>_;xtq@!G((H0<XC&YA_hLtb<Y;QR#@p1NEndN`@{|Oio~6a<Aipt{OnnVyrMoXXxJlJ+?!{x82b-0e
+{9EQL2X;4*pU$#6e|Yrx$UpNd}#afo9W|2-<s&R&-r*bhRCY1??{~$d#ykFR}#~+0j4|AwAvh@ikA!W
+uQtYx}jNEv2A5@dV}L(e@%bVEKvTv_>vGMan^Re^4P1dmPf-VKOn>!R%KCiL=9<_&)J${+oN4|NmR$h
+WkvoE1q|<u*R*;LdfLJ>!?(J{ddr7%Ue<UWZ=P=Gl4G1^IIVcruCMLWGf{QGi)bg6w5{C_u7F;}q8&4
+pcfq{eG447ovQ3jq5oW+a6<tv8{pg2xNB3AsDnPYk;qT=KY2qXqEa9=2y+wB@Jg}*uqJBAkYOlw`v>7
+}X;5sx)zp{Bfbs2`LMPfFnuDroi^tsm!1AL!=UpE)sE^tpM7C_XSC_z^fw~~rQR+231qb)vnig0K1Vn
+tV=PH;Csh5>JQ++OPvUzu6;?ZjcE*4<b5k&x_T8$f^ZI5@r{%j+5xpr2hes}*1UO}|}KQNdb9+)!!Q1
+*Btuk6yY04*`2ttabS33x@Wlkdc!)+2%tb@+O#M1Z4OKkP+WWW>s2_7o%H%>vS1f$CX^?h`><cM)y8O
+mp%q}YmyjvioT*di?}RvRWf5>=-FOI*<Nj4_=gQd7k4ix-f1x$1^A;(vAcMx|KiDHM)zY(>6(oGD^Bj
+gTG8#NeDzL0zu_mkdyQ+4&+2mX%Kq9!-~D{X+ly>1FCUFY)R05YZaBNORPQ(?@H~P$PX<DR)_p&|(u-
+^U;TJD4oNE{{!!eWF?@YONzxZOlr63-7mM>giP}z&ibp>;l1PvL>8#-W;&^(J}t()X12nZEUQO-EE-J
+Qv>Jz<{@=m5_i*ZB7wbuWt``WH7|{e91GBMtd-bOArLUqUVle~QF|X@7^L?=D7e;91WEAl}DbgWeatC
+`Z9QX@dm+s3(#gf32a-RVUgnzzOW!tJD_VP{u-8c~80*XyC_Hmh{VQX%d+y)93W$Uq76jouAE)k7h4E
+ynXrlr0428>R5I99>a|9)34{4A3r^rzF3%mY%3P2d*5<Gm<JiU7@h0MoP`_qvVz;|Z8`jfeXNl8I$Tm
+K6ZW9Hmwb;a);zyBUux1S6>ES`oO-d&-oz;y_U5?4=Sy%D=geuRuXZRT8>fg3_in9&i%YOuPE5Mn6?X
+*^FTl^TKjPOn0g_C#db7`CI}{0NP*Bl|X)G9c5h!kx73_H4tqly(zUjTdm~bxx_#F7QB-2FMgp0|+VM
+{S`{eqv_8?FX#%f8wWzEFkh@o|;Ez*K)%eHnNm5iYQZ$~7>j6Q5HVRSS)7$~B<K7gzodfW^4H>Eez{A
+Y&bO(=G4dQWJNNL_m`0Hu6iXV6UY3JLVKhvJncjm_2eU!Fy)Ps^;4Nr8Wz>!K1{Q8O+AwzIb8urJum&
+uQgcWNAB>c_1D@Mh~AQ&PQQiaewOOGgC%=G_4P=7PhS}1$g^F&AExr5hG-4vg+EPY?Qcg9v=QM&P`U#
+$i<cbeZuJg5#%uwsYM-ER;}@Y4ewAB0`M2lbZ?`m82>&J4I0Vxl-h{)CxrH|i3w$h>D`o<ufB!T+lca
+tl`7thIuK{q^C(ys`h4yiI4NXAq893m32H1X~en|rB0D@uW({eIVkCR8qqy8I;urlaE>%!}xOoqic^1
+~e5S$-0ZBRcf6AAVudj-UBR)LVT^w^P_#z3_HYyOh5><!FBp*4~EDrcB|TE9?rVZH*mIpA)I<FSy{3g
+s4?RKNy8s9fAm}hXrteT%mn?3&ei_P)h>@6aWAK2ml;P_ExfV)-Hes004^+001Na003}la4%nWWo~3|
+axZdaadl;LbaO9rbYXOLb6;a`WMy+MaCv=K&2Aev5WeqI5E}%MT1Sy(*>Macmo`O<7H!ew76%lyOG%7
+($t}sXtp<6D9(w81^+`IM;VvovL<f60GaSzEH>54gvUtCfY_+OPE!}Fx%=(k8JgenKY3Z0?t>`+Xw`^
+lg%PP~hMl&s1;BAa$KfZteJ9A$6-bq(@!~9Mv%XHsLt18hj)O*B4RY~X6x{*vOkg-gFa__BL_a1Z^B-
+E<%%4lKth4Qj>v!Zx=E84D+7Z*jr;P>Xu8>ZUMSkJ8dvzN}hkv<S+c;<&^paBFy8Mm@l7TkLF5rt3YF
+CW=7^HOxiBX@ax{;29p^CIe6%;!b%&a{#|Wjk>#S=%>Wfz=c!@Ltz!ZTyb)T_^2xTsP(hJ}coQyO!30
++Yp6K0kMhU6;?9Q1hIO?et-Z;3dPZot(m!6t<vhZpTi1N7l|+SkWx?r##t*}XW(E;Ql2?9J$N!JLO~R
+m>Y4MluY3>NhKT=S%vIlg4@oKtPVT;DpD_$i*iRbjp%s|FW`@M$`TT-S%F1Z3bT7-J=~1K~2fDjazS=
+=;@y;4=D$}@3WD!Jwfpw#|8RrC*?qqe<8Kr&VEO1Y675B#Q#)Mt0jJe|n^tfd~7MiOd7{V3)L%cXq=q
+pjT#?;~a67nDZ|M&0TNfY{1St-1%N1GPpM=1a9kd9txqq*q)&R7MRP}h<x2xCzFFee5$9l9hfJj7ULu
+~^Jc0|$~PePS{qr0r)IWMRD$O)eHmN$_P5#Ioj8GeK%7^SdNmt9ueEsXND@G!U#hbZ4lpJU9!qOSK$O
+C6S-7KVlz42xhU9=c8fam}+Mf6wJ8ggtF3_Yguz>y;f-Ou)%~PF=q35Ic~swZA`E0ObaH<Ny$yXE-V)
+O7zJV;Ja0{{HcIB3F%#fPDD&HW#yCq|aF2%pzmH(y=tLb|7)i;Z5MulczjE|F)0DVS6#&>!VSw)tMlb
+I(BV~FN@-Wa4$R5}oFlH?QHPJw(G&`BiV-CM-6qv!@T5BvNaY;#Bi<-w?4KBfQaArwa>~(C2zq0TyBT
+$HaOWyt2gL^d<G18Kj6H2XJtGbptQ!!>Q=AD(#Q%Ni-fvtqIYaXN`DpQ-L<tTqPsH3(QF!i#-UPfTM-
+D87;g)k^XNgo<N3LLJIcslQ#TAg6dt5%wx3MGDyg0CVRZyHr4tXLjn{I^DDW*%e68>zQ`ml-y)BRosc
+Rx7lABUCfkp2*|j$0xa!!41DBJQjAFAH2-vM$o<^L_MV)3{=Dp-a=Um?)RMx7Tn`t!zYnZ&)Gqj#8Y9
+D6?!W%*$#s3Hj0w?sOSOfD|^R-u?pmE2c0Mm!Z%8sM+^j$@lry4K71)IGS;wZL2#!W^|;JBY80U%spD
+u3w#95v;4*qri@9q|b(LGVz)X?dyq2BR&{Y+x$yTFuOqsE@gi?ZO(=-I-bZ(?4dF-OT+gee}gVu<&Bz
+b<X77sh=fofb}D}>4dSlka$!VxwQN7)k$>JDa=v>dR#sa;-^th`4Xb}onUOm{CQ<7CeyUQxAsKyw%bJ
+DSlx0r~Qjz>$K_*Fj9z=EiZD(U7+|w=G_taB$xtj(P?Ry@rHg)&U85Bex(7bJ&4-LBSzm*!+r+1EHH&
+jd2fD))V$lTDZ#Q(0)qL4!1OE;abQYN^lt@!fAKcFU;j7U9A2Y&ORmZ5ACGFcnOf6RpBY&e;6KHxOv@
+(ea4Do+g`(^fM>2##iixA0rM60BqSZ#Si(E+J07p>)a3)z1hqLg>BU;U7FG!z=7lp{%dLScmd`FLr!*
+QAVAp1&DvY)BFxE5VJ0%QX!{EJ9H9&KtS_N==TS-}y1tV`fp71@GDsO%0%Pf3^^IG~FW3Rq8kaCf`>%
+*b+r6`8SL3%Mv!lUMONjF7$Je1R-DBz*V;Oe0KWO{)Xg;!-@A2GnBCOkegBl#J=2?x1B7Nvp^i6>_G!
+DTl*GAHpBiXum-etICMHVnc;e0cc4?KfP@c9Tg-_4uNkP7gIdrhSG_yvcMp1vdpJYg3_Mrib2nuUR-@
+_6goHlTEo=eb!%As}g<F$@vfA@5f{{fJARKE5Bh+>kIbOmFy{-P~1>$JbBxgHN3((hvPX%Qv8N<)8rd
+y-@<KJm+>E&G}=98CK%<g;3s6;G?@i~9CRs%G5r<bZe+^_p1UI@<Ui)V_#aS90|XQR000O897^_9Q4&
+nKTLb_AU<&{MA^-pYaA|NaUv_0~WN&gWa%FLKWpi|MFLQKqbz^jOa%FQaaCwbZO>f&q5WVwP4CI5TfM
+(IFQ5P_r1Pzd+Md6|c!w^^GNZNSGrFWNBg&_Iuo!RBbN|v1H5Qp41Z@%8layFYK2A?{#&gRycu5_J2n
+|y!yOOm(337A0Ow!%THcWB`6fg_m_W3o27hEgkqrIWg`AnR5e2Y;Fh4OVYu>3UFJ>bfPG9`H%Dt!y?K
+eCnK7DeRw<Bq^1!7H);b4~@mfN++L@iPA&p;wl09Q5ZK+68ch3a43q3EQ;b%$wvge`a<#Li8uIAw+d@
+)oCTp2)abUlqW?D)=oXC#dFZtV7sa8|q5xrGhh#{9*~i=xsMPJgC~~+_R(reF=x13WpDC`}QaY?HK|%
+~SWdDeJ@@f$9zm}rI3Y>-&a^1<1&Eal~Qxm{Y%=HQlcLO~MCrxqkGf>SOGY%Z+GM`aVkYkflX`E<ETo
+gst=f&<*eh!#AelXMFL^6Ur!A?>NrEZ*%O(_3Ve74Tv56b%)O$H<wv!|3iS8rlHi6bTPfwUo+sDoEmp
+;A6kS;6&5MJ!^>{rsjZv32tYLeHsRN|wHxzkIQ}nIA&M?d`k2?ihLs3vdB<ro+)jN$XNFTrfUzG~hh&
+y*AWL!TRDtZc)$>*!wx>OnSS-rqmVXJAWV<`2rfG-Zo=LpM~mtO9h$FZ+o+MgBe-TG`1v9gg~Cri;Xa
+qLK`Ydwp+dPk_ZTBM2)Z`v1%hXvLVUuNmZJLbC`#qAPO>wO&bnA@7hW@WC?IqPn}TG?ZFSRkyNALZW<
+U?@`n1-1Y!G?u@$5SZ_A8+5LiGq8#7)ZVI+AV33N?`YuRvM{a}Xx=`AdmvXO4NOf9N)1{9jO{;V6S^P
+4x1J7G4qUkChSOuqC<k`kg-6zN5-Jqi0|p2^sI<dbXo`t6W1lqBWT$Zs4Z%^i=)7$=n?3tf%EyMTYFf
+qrVaBCPz%&+eM)ptOGMTB^{hbD>WjDQF1@6;Uu=C{2rk){KXEH~Fa|+!J`HKF>xPg%wA?c^Q2acCXcQ
+y!XF8#9S4sSGef(EYU&JY47wDFC$5P<%Yry4;j=n&RB(6k_Q3j{v|E3gR~VkXMNCF8WBWx(ON&YCFOq
+PYbV;8p`SbHw*Jx?8y|KhOZ_;x)MI=?^bZA21zz|}Uz{wC)9jrdWQk8>FEq);MDfxrNIP5+sXxu&@Rl
+8Z{_xB)4zwd2l|34(KDE!<jdw6sk*06`ayhsL)c&|IeCLLi#2r}p#axYH936&2u!nZfBhOz#()7-`K7
+4_nk-(``f2b*g?RnwSo=vATh8P#)x6env1H2=KO&>b^ik7V~`+iRhUpBApO1=R6t~}n5{${xL=hH#g@
+(|`D$IoZAp8eJbHUB#Df1Ce4`}q}f0skV;2i;(6`g7^FMt7SnU1f$gz13l7S>_U*a{RHwi6y6Z)RK$0
+T;}96Y&>6tDH?tst?8chxKyuG_C|~3e^5&U1QY-O00;maO7>R1Rb@R{DF6Vpf&c&=0001RX>c!Jc4cm
+4Z*nhkWpQ<7b98erb#!TLb1ras-F<C)+_tgkcl`>KI<2_Qih8l*<7~W19b0bHI<~8q<g~I6O)aq!tzB
+|MawRK%+~0oZ4In^rS899Dz0bXRntDk917I*S7|aZYK@e<|`q!nd>MB~+*{s_5hxfO!adMeeYF?zvnO
+2LkxXw~tDXf~+w`#h~Cv{fjm8vh3S|z1c%Sxx}CaW*ATpbDM4O^PbssgJ_moqgjN~J&5y3CWAngEdHe
+1X8CjR1zVk<AxHSwlgpCsp&5*U)B`otrmVVSW|1R;kUes+e5q+CJ6ga?(8A+6J|rFQ(bdHoHm6Jj*X^
+`EMB)Ps?HsW0=jfOk2v|l&LOt`XU49TxpRlqWD_pX;DVYas~r_NC-A9=E;?gFLeU#s-apWWu;@NC#@q
+>ZK6v+AHRzMURgo6acqj6R~s9fsxIO@sk3Vx!%SiP3YKn}(~4Ze_=f6ySxZxSMT>BrOs-(YX$4c8F95
+(ft*+@d%Xy7rA`sJcsMMy)i(iwGdiiK~Z$rUf{Nus17Y9f2&(B^RzIb->=IA*7;cq7g!&QaHCr4b?Dd
+N}d`3yG(GAJIX9Sha|DOoJ25<Z+Kl{Ss&`L@;-|GdyO5b~$2`yA{1IxCBOuJfA9aPAknjO*J4R`2hgS
+MRc}7x65sfY2)y^E-T$RbDf2?EN-Azg;Ai49R`d9n`POqSpKqrpP~*x$_nXiTbxs%UqtD2^3c_VM}K8
+_%SJCERIv8W3H$_P4vQ}bsqCeV27W8HGg4F;hqlj>tvRtKhlJ~SEom>`1v$1^-Y$i$@xtGP^7m9Wm%N
+XxR^tiWizzru#ks&rSmF7N?;ayeQ<L0Jbroj>fl(7RTxCMuFFX<R6)$Y1{)hM4qiSxeRUE)e-{66`uf
+GIgZS;UlOLfv@l<q!<R3cq-o80HL1>=?T*+Xhp6miV{9VDrqel<FAd4M<m;$yTfwnbNTf}0>V08hjrY
+l`uqny;&S+T5Cs%P0e1NKqp`Z9rcWn}w%_Wb$5+mra<_479`4qyKXddBfbAB!w!6qh=x7Ql#M84TZ55
+1`Z)8euZQl>zDi2?;AOJ}H-aa2D|EZSy*KKLF%{G@YWnix#t_29}?zF?0v(@NhpEQD>V*xU0mYJ|zN1
+!T)}Nbt`TvlI{gak{7R!)eI<Sxu`Y>NUEnk>6ZEeIH0@@FN>-ka8Jb8<!$pod?s=?1M;}AB}{zkkP3-
+X{8ps~Qpwdz*j4n#8sH?rbbYMr8l^g*nmdZ#EOh=CeH(h!@lVQs{L8`L;^(JFM+dJ@;?v^;5m(+Ag5z
+RZgZR|%e#$0gQNhzY!PL9w%d!Nv{h4w2?obAz%t!(s-oSg>RBsWN2RZTzu;_A@0vV~JgFnT`e^(&4@z
+;xA-W<Icf*>yEz-Paa(62o(3kS#;aS_Vo{<_rV?a#?<sSiGdZ5#n9I=u&jv)%W-qk9ANQ6kv@A0)GRf
+#Pp=lib3SV)@%0jBR7r;a)>A&1f)f8VTPVvnWvv27eFMP>ZFFDd4X5kOY{uuS}o!p}S4uPnh@QQcteb
+HI75khCs5dzSPR_g94%eDuriY$O(!Q?SR>OIx8m0?7J<&AZ%XLn%*KOadVaADZQT*KxNgU$Ws^Hn`)B
+eMV>($t{>T=_9}SKB6NapgMkApFK%RBfUz45Q>`bLAQS*yQ-5kS@2cqxH4NB$Vb9Cg;S|79Efh>L|6t
+VNHmDUu0j&>!LtJ$0I4guQ(JSXJ=$}ZC54#75)-re(1p{8h>Pn>rs9kq9d_WDO2i$OSndBE*UCfGeRi
+WmaPwvtA_Y9*80)Cfm48fK_hz}9Qkmf(cmxqHc8v0PsCET{i7D;WCJKGXe@}maekd_Npov5+8G_r|d=
+rn4$;yDsc#eD!;L;_zVHSWJ@!y2xZgV3vmo@CQZr;Uh2LUJfAatG%!biYCu_KSm6sum-n5i@|XyW9Kw
+9c;UZUeu;yP-P8GgsF_g;uM5su8f*(X@?rZwvhl+Ef;B0>xd3UGRw=PO6s}{Q;?6KV$7?+nP3WZmPYg
+%bsT5Bsf?;xE<mrH={zi?U0u|m<ineb`VyMI2Ii*s6W+w)MS&_9=mBH3+ZjcHx)(N%V|N@anA{yV2Gz
+)K4uxx)77_eh(Gt&Qc@eBrFt`fA;h&+iwz7p}MRW@4-Ga|Ypc|A4&UdJuK}Q*!oqD&G%~mn(gn-_1QD
+zlNZ>vHNVQDqKfdj%N$kQ9W1<K;bC9n{QR-Lv0la~3xndugfeQWR`0@b<(BrHIKsYu2a=O5uzTEV|{l
+I6f!*ICkn_u(Wd5dvuSb(u_R{2dNH!1+_-uq)WFzTV&eCi0pgVXt9>_A*t`w5pRj<dF_QqmQfXH)osV
+q5KHiFkpgIXKH{7bgF>`<}i5TbA+H6@DR70T$7sJ0yHV|X;#h|S2Y?dsND_VxB%QhljQ>Uit~&ZX%1%
+=e}1^7oZBs>h_FUini`8hgg?6aBL4Ni#lOH9LXc{kS(@D&7(cJK1%<R-;xvNQ;KXDD*h3s55Sblf+HA
+;(h7r=4hW&O(uhxJhq~Yk!wayLZ03T>=A*2C&L^`s%KZ4sj-&zZDmRt}BsEQB<kz!*~atq6v(2<Gc9_
+cTWdL1kuNf8_?t#L^`jNqUqYzyO?&2T3w^}M)-DXbeGU>c`gdGn0=TMW9IKmPR|gS~dWlCsvb*;;YcB
+Xf%gTXn^jD86l>M5qQ0P-Fzou`1@k7&<FcAe4GZ!mUEofhGql4=3W>QcepR$}~8aC$rft3OC%FVW%RZ
+Np&?TvqcTqoMoW@RyC-hv_eS6Z8$mbI_z!4&}orx)#?gW%Nyoi!|%`^jH^I>0gf|BD8K0vsiiF;XBw@
+2LI{(~WqyVAu@@k)4xf9n3Z{fSkK0_A-FxuwHeMqSTPqC`{|a<FQq^0%_xHT1j!Ef1d_#?XK)V(EzD!
+`NKwxCU%h8BRhZPpH9Vi`wYQPf^z^Df3ASybGZT^Y~YlgsE`-9#Joef&(b6vk^YQ)Y3zslkl-U$n@Xu
+e3wIwSfkQFh?4w~5|l-&;3_&T0a!?sg}&j-ggex>1DIuWo-cQOV}XCq%PXXS+j!Mx6xhmW^C-vaBz|W
+jTW*K$2BD);R2HOxk@{#YFD1GP7PTfOrr9Z8(X#$gY9=0T^rK)Ip<ea(~3`w8e{_9Kl$^fQ)f+Sj6LW
+Q@5AJxExP-Y*rkruxT<Jh=y0KZ!r!2vGaNQC7{tyQMfrKK_Nkp2bx(KThnWNc#CFHF&t3oMyuCF(kR2
+;k(N4bjjW{^_3<FoWfUS{(8CtM<e&tV;nb%`p~b)G+ZDvP*#m^+{WQsDEX)7n$2UJ6unzzThZK&s1Z7
+BgV7ggmDYdO4b*w=bK*Q%~XXktgO3&gJcKtjm%8MOR6Zd!b9zRll=mBM#U4WjjJV$f)&Z3&`7#YpYtD
+U_kj~=f$v2L`*X){kaTU8-ou;;Yvtrk@2R5%B*apf9oo}D8V=%fUZ!l&61DHgXRSnOu+up~{ud*ya};
+AIAbFh+Rf(1F`A%J+pL8qAmTb6r-JI$_|VB=I)=A)7`~M7CW0;e$$X>r~FBx+w}Y(BoTLB2b3*VQ;<6
+U`tO6O|vno(K62v4(!sPe}ar?rbreaIJd&6&x4V7mc}CtZ`mwqpjHd}PGj>kN;UQr21zx^GRKZY=7KT
+cCz8pst;w__!`^D8h{YbXr+>p{RR$4CG7y#-Fd~S+*4bUA!p-|QNh}+v+XC%e0AugavFD~JyX-<0VqD
+?f1}Y4kgqGS{Wrqo+qBMU$G%fevcTb`n*(7^X=jeH82p7*g33;OE$VmrL66^~+Yg83`aOjAK`=>cKkj
+!ntgkve_&~z-Vu7FY*>$F!ab5NHn7$z*(B&$&wtghJkL0b@aTy+#LcYo@!RADKvJFw+qp$_s3JOo~Xv
+H<^90?#1FaR;n9n$xjWc1(~s6>TqhGS?v}49)I%Qlc9S#!r<jPOzdmNb%OlYDQ#CO;llwl9N@v^N*nH
+;mcr10;1Utu_9`64kzKeq2r=t{Se<G9sLe1ph5F$dyn6__D~@zBN`DD%?<z0C<=1OkAKVH0FV-+R3Wj
+8qZ_dOIfoIWbS0Gx>+x|Koja`510GQEn!+A~r#3a$D7X+q2|C9KUQ$jj0aeUK#$L_p))WtVG9Dn8NwK
+&!*sYTikT^tQ)y6PSv?o)<I^vp2X>34*Y$g@`-mFM>r*P)Vv_<D?a#SD>;7Nv@lLQuhD8|G9q7w#ui!
+lrrYPu|u#oDOHHil+lZ%u`CN*K8TiZKb(o(a%l07g(t)I`NdGzb)+K)=hm7K>-qfRbGZe;X>b>mjFY7
+m)lOnktR*!LpZ-L^Wa8nAx^Wens8JsT4bCwH+*gKC(}p4onMgLnZ$TR__sL_GHNZ2GUP~dghDz*7T7~
+(Wi=2r9M=MmK$6pg(4fyj%F66o+rR|4b8Nh4!Y7$#h^yTbUtF!5g939jbYzJmRO)KGy$nqlItZWy$fV
+tGM!>r2-^2lHHV{$Z11>2sGa#o6xK(~lU<x(M_j;XJXN!9?;Aq`B2NNRqO6MLXV1!XC>5$2CEft|d$x
+G#wl<x}fW#_h8b(NQ=+X+;bwfy`1FK;$hq{Td%=<=+NQ6*BxAlBMz7h`1!IK95PP0-hAXb_frO!|uVG
+mjx%o%^yPB1`GI&jh0B5oh1CpusO`QZ7Lx+#$mPz+udnb`1<n{nk~x2j1Yn{i+dAfm`&o4iT#y4i5KW
+u@j<FdrbK2{xUe{|?2a?Ue*6C^YkI5~D?~JwB8i2rmZGPG`DxNN`Ic8gpou5oZ!IdIkgcDC+kB8_6G=
+h^t6`&XYX30D*{mj5|8BZ#LV@FNCRt?L>euL_nHVSHe`>7!DoPB~07Maag*zu_+DdS$11X4fCrCe}{m
++u~|d-O<SNH#-Mu&B#feoI;9b}y9#d31Hvj6^dj{()3ekqwxs~o`1H((hgOv^Bufg+4<IZKj89<X13;
+stZQqDY(U1t`6rppaZ{usU79cN@$JJ43$O~;W7T#@e13?oD9PCi3uj!;nW>N}T$&qMrA0ily-zie3tn
+o<;<e6?OG$0NQ1tm<sPDI>L0sBTnmJOp(qu_t{-FH2+ISaSo8DneU)z-k#jvbh5YV||iVohtSsdoZ|u
+E`!1QrJSNC#e2RP;k!@FI)xAVD@(tUNAzGAV&CnW*sm#*b&S2x5?B}-7&n+G@B96=F5Gj%or^(IBn#`
+APOZIQOBVOoujL)SYzAp&wJErs6vb}llVDxUKDT$%<_8RZUChEH;4&?e*!Uq@1Arg%ycbeUl;%9i2l&
+2-4Hg%a^PM?17Azl?a{6#*LKNTFssPqp91oKofSN?#UcH_NUyzpO9-md7f)r(|MoiM9ctdd2*a0X3z}
+zjwY<!(ik%x>Uj3$*7b>)o)y|oI5D{~9qD|ZELAC_ys#4^F#7*xU;GN&9qnFRs{_f)^>X@UN)xLyp9O
+i6wpDbrdDM88@B0NvFD-BNxG7!V0XiARbm}v~3sDM#;|GktTD0KT}`DC^P3{$LXy3K@GMM^#MUvab>w
+MV5RL4ARHrn+!k-RAnrt<O3q6;yH*A`tT|g{>M|{*{YxNsWInS%MOhpy7yITXZ-OD~iEFjVE=f0LP1~
+ijTx241OPdVANOIVEzN2UWs;Sxp@dMdGy02rJ65ib%xgWI-BEQKvL21!GySCTzyvAU{VuHb3*4pq8Q5
+_7-9$QlQLDK2{39k`hckZAi@Zlze^cgb#bM0P<8}^1T7G0aK@!5N!;QsG0UA4tm>jt$KaX(9&ZFHxqw
+9*lG<#RK@gTMQF{_xnF|Cm$q`c3ockQv2trYWnT)t)Br=2$GV=RgFJ1txumHf3XDlW0c!}$T1k;V$_V
+~!KJ=8uM?Y+lPHTu21H=>8FV5{W|M7U!Un=K$?0vS@vy^%eUG-Hd%VVhD7PdVq}e^W?MG}7Hd0=7BWG
+=@TJizF-WBRH&o0l4;BmvrPo%#zKBod~qiIs}T5O5KrdO^ae25Q$H->M}rUSvd~SOO38`p;p@6V41^o
+fb5VO)yKxXVTFpKc|scvC4?Ss0Ys#8fw?t+tpmHoceZ2POIZpu9s)EJF<RJl26#es!9*T>!2PMqg5K<
+KKbA-eCI^|&=bn-gZFpbq&w$v|{|o~n<n;_leR~X;w)IiVfS<qoiwqcyZMY6LZ2Mvm{23O!cca+MAMP
+hv?!-j$NzLrj*v?oC#z1y^p52OS8Q$lImCSD-_HsYB?PdQn9MF5CGW>7k|J4Hl4XLq@d;a4RR_!#GE!
+C17D>F)kM;KdFB{LKkLS5ZHJ`5t+!H`D_%}!w<Of;&@WM~xXysSAG<h(3y&}hcj#w7NH;BeFvl8rR#r
+Co|nb%u*40l`4z5h##&zy66kGq2OGx8B|5ZY;|<v+k_;;?*?!#BLX;R~05;%?<oUfr<fATBM1v3P!Ij
+FZkYtz05#Pn4;9B=hLNY9Oub7s45ig!$#2tmn`crc<?~(-zD?KtnE_-!0aO8@F?mxcs_au((xTg&8Yr
+V2gdk>B-5|$GI_h6Pja)03BGZ&m@szGWlEv}jC@8T6b#sUARH)(I(_|IZ1(8&>$nSe6ed!Qi5I4PYNF
+*FSSA49#@wFkS#iS#UegPO#gS@D23|e^Qn;5#0Gfi@u#2=<VrWhUBJt8}e%QBtCo|5S_P~Ch;!HPQs)
+6<2qRy!#Ms5bDQ*zI5KKlBJ@1sV6*l;oWQ$$+rv-{{B`~_`U+31r^L^@R*VuN5{-)_MZ?u=&Zb(^|z&
+ScuK*U7@k$8I1B?U*~fNKS||?PH00PHq1TROWH@<m0F*GN*iuVq$}(G8ftqiqGHP1|-S})}<Ypw;{U^
+aS1XU^k-4!)Ia0jk&)5zC}?mH<Fpa<BxxF(P;eJPL$_`pwwh@Riu%yE4qJdGIH>Bf!4eW><TYr9Fj8o
+I5e1O@sT>eQ&(0#bsJ5?te0wPIE*XYSzkr92Zj6(;!B!cXq6pAX{_P^l)@L-a*H&ta9@9b+myOs~z>1
+DTQ9eB1*SI1Y*pC1X4)Z29k%ClLPpcib8mX5+j(#X=FfUO5%<=x71g3-N=A)xFw)M%fGS~Ik+rPQL|M
++pFLfm~@@XR#K1rG95$SJh|VHgdX29BTX1)9&;v+ISuidh4tHy(#e+z3idH(t@hRBk<mjV*~Dd@nV|X
+TiIz_YcD8tM3Q+^Sk#TU@&O78q<{)g0?7=i+QpR7$Z=CeQSZQ2m5J0>w)>-Pv3nHB>>gls_c%@x85{M
+-po5fe=w*kmR4<@ubTO+tHh)0uVGk3RAnin3(7`i=6|{zVrUKP(jG*7plcg}#5^PSm0echS0ndEpH=-
+ilu*nx;>hy5afG}Wh3K#8-4_>Rfxsv~Icc=+qq#F4GLVYGbFmeuYIuh@TZDt5c?AmkhV8F%#6G^HLm}
+PHp{Oj}Cj*RXw_5@uAj_q>8(@M3WB%84>h8!?;BUCjky;uKyLZ%J)%B;in8qMGKoz%LAUWWnq!ZZGZU
+DPIoJzb}(z$_kHfpsoSo6`*4UzT6e%9{zE48Oa_W|WB#Tg7M0-X!!cF=q3>057iUv-5l%T#kiTK>J~R
+`KJ>$y>!&*J%fgdN`mOxy0PFS@h^1?)joaz?RA@j-@sC9I!0#UH)#fH8$}T?6F2%xbK=S1CeJzAMIP0
+KfXS*Rn5`|TkisA^Z|N}3C`L%1c%3Owx2xt`kU>&=9XIk`_U}p-Dc-wRpe{nY^rA*Gjn?Ka{CFzSK+2
+c$Ert<_y2Qbqf>8gZlX-rQ;KLUrxW}SYv9QSRdv3SYeYH)*DXQ)sXIen*3<1Lfw@wLK|P?@Q1D~SS8_
+3}2ghB86n05|W=A$3Qyax?_#U8C^Dg_9k)^PXTZDbmM9HRYYn<k)C-za2)`~e*km6vfCE4qfnG}ajSA
+$R@$^$tCi0C0rneSRO!*!PP8ZRF*G!qF*)jjE0UiW#{%j=C*AkKpT9qM^9<5UM5J%B6_UJx8xTmkv$D
+wJd(iXJ7(zFCGtngyJit^q;Zf&;5WaWsnGqNpf*U;1`|nT5fVm-qfDG-!tC74eNo2?Auzl7g_Xo2PDB
+dy4$}4C{@k_E#R@#sNrWW3SMWn?jl_HVwgsJ*orSG)R}F_&wg?$z=#MAYgon3F^X;Ky=P)(5nqZHegt
+0vW=+BbSk#fy~r}4<lSjxBURXs)D&HmGz?TU%xNB9+D@!7!S_41%|8EzO5cmc|Bp2K8W*KGxUlbpN;Y
+A^ZtqwnE4apMw(2r6o3#~rrsA4gaw3IcDFJ|VJhTlvVb!O+PCXYYS~D~rm<E!}_N5^=xiReyX#HS@s$
+Z7M&`tnbt#KKnuYpB&U-SYlbK@FRr$>jbwJgM)?%_929uGE7UmqPD9~}LB@FG4wI04)Px_{HShcQJ5&
+whCR;^5_<emwm1Utaz6`pw(F9vz>Y{`|{-{q66``2^&{#bx&KYBtY{#jj;mFRyPt-ToGUm<e|G_8&g_
+`tg50`DQzc{}F7M1Bo#&H^U2;W!8w2(|lW3lZ4I$w`iTl7z6Xl*x$%+o6x+PjA9m`Jzw&C<*Ed5%r$P
+EY%ryYLj}yIFOr#rvF6*)j-MYM@=0IZ{Km1mN+6)?yP|s>nK^>|-q`>%9BGL$rQzO?L^U;V;|wlYQLd
+}A?ETs9XupxlK;GEma)72}@|vm3D65iLzMQx76!cyr!dnoN%Mx>?gqK6L_ju5IeaMN>=z!oTh$cT%I1
+S`s)#8lQ*5}JFTS4oJA53O~$nZ(7+o3@P4joUz1~dDk_x{*BcPd-0r@`+(o5wGWK<l<!-^S>05^&4QC
+&Y|Go`|{3d@4TD9C_f}3;<%aK6<=<E*>?yfuJkDB0QDF@&Zl3hGBLX-sE;dL6Rafn=Dg!pB14}d_qo}
+Z^fbd@PeK6cTjSbOf@+bV_8@{=KgN;KYss*t#I(*tKrV*+wu2*JbV9-R(142`Yrk!coe#+#9zdlPwfj
+VXE$ydoS+fkX=8ZTm27E2haj$H+1vrrbV7Ftwtl}gXp2&69IlX4Lz?%vgDX!=H{9Y*_!r5}gvNS-?yo
+xCWuEDJt3q5Ew-u}`Iffia>|(}Xk#lW8r8pN8&qBn89h#d8lyXRjMc;0fu5)8i7BC4*CG2$4w@Pq1Nz
+ez!7xIXCD2OLofweMgW5^+oL1W`C@vcpl<K-rFT!h(zZdN*xdLEO2)W(!zx5bjK1)B^*z#fNh$r*zR2
+YFBgAWZfgelo=$u={ExW39-TLM9P3<?Ma4AMHJU675BMybtKwd%L@{|Hzj!1`N4C?+a&lmmzsPh=FGw
+6J`rU4qlR@6n7D(<eOZD!T41$lr)u529RSoOyz*Jfz5ISFR>}mN=6$JJUcP%rV6Dkx+nCss4>J_TG1w
+gum=OLQ^NK=A<7u3z50V0k1J+FL4Yl!y)QKVG_Q>}$sZ#XSsHrI;UyI(Ya+dK=hG*}dNh*Dr%#_E=f4
+)U;Qa<{2!y!*sG&u(`uksh9hv`j*NawJlHE@)<xl;$3is60r|RLp+EzTzZMhX_G(-n^d0ix-V3_gy-C
+@8hJusNafS(rEk78jiITFIV1|RE5&y&xcrE9>slCE<JzLP!8%`asKO5!n|WNB&O$^y5>`m?5NCFFZ%r
+kCqY*wm~eUa&4=&Kz}}lo=*Gi0)#usq#Ap^?8{yt02MctvOBz3n4qSU^rJu_PW<KS7}-OY2pm=Jym<S
+QPJ=3fL#8i)P}28vuEJD-GTRJI_NC4uUFkc2Y1{Tspteq$pheYbsamwH;zqA*X@*GcKy|sX|{!YzQr+
+8jG^Pi&Alm+Eo3hlT9-TBr7I*>)vv3l0JGjO*W5h<6CpY^<1jX$q3p4EfzVJU)rieCv~d%~X;LH@`t>
+S0_d{lBY|QVi6bxoS%>p+S&P<_iT=yu6aKtAYw6D#aqSfP((q>pIQ<|iD);pkkX#FeZVLLUJS2A~)EN
+qhejW4Vl3DOck#;^rC58oTqHjN$UJry954e~CrgV`{%qReVcz(n2*is|j6pNfr)%f*5#NqZpXE3Fq4=
+WG;wlQni(%FQJjDjKnIcpRjT$xUFIH$VpxXJw3gH0|(8-wrz5+oB(=gA?t(j%b(|G-)g#bi<WJw!xhh
+(iq>xi6+b)3e4lfl})%4Xt1vY){O>z6^F{&Fa^7anrlH~C?HSEyo!?&ZAs?QaE&{NR>BceGIr1sn75)
+qk$WWVPuq}5>}(ogUIB`(>2$J*^Qz?Hs$@W=aCFl|?u&3*uAQA7?5OG}+bl&}Q)-<xjOy<%g3ZZEO1x
+W7?!TA{{&B;k0W!%P<!U-mngo63sh9H$uii&}sHL0>WEr6!&feWb7Ey-dU|@EoA#BN*E{Ss`Ix?lL@w
+BktGLVp$mM9}zxczpeN!Hd;OtYSZB2vHSMAI70P~8Egy}a!*N@v(6u<_V}U6sh`&?Wi>IjKyV7j)Up@
+YVzzqCk4_Equv}g{w_kmM!S!ap4Y#T*QI_fP_lO>D$|)Z<1ZHj#HEqHfALmx2N9TV5Ar;cQMfd_7xg>
+MxUJ~UxJMev9t-amrz=x0>PM8*b(OzQ39svyH#P;qMfh=<TzMnSPazUR0GbK$Yfw|!sGSf6#(&UyjX~
+(#co=hd<}bw?p!LWK+NuHXN`aydZO3672T#<xnRd3@Z_k)92YjjoZJK^gP8%+QE6rW9s6l%+ajQ?%7)
+g0ZcnEdNv3;}rdarnZVl_ruRA+sgCSodcR~*cU;RqQm{NiCX&xq;zL<JSf<S4h8=V;X>|QF*xTX6zvy
+kYQUe&%ypBtJZXr=Ls7qWFyA5z0r+Glj}QZoHcC0Q?3MmfrEeCGtmUP34zu~(x+Z<&egcKnTQZRvHSp
+7}vVssceZXKl^=B%^vk$<7KH6mHQT9u2>YU3E`z!-{~o09>6w7QmFRQ3{+C!MLcXQ`uHL%%N8pB$yUb
+_Ch9q(80*zW?{AfphpJO3G~c#1~gpNs42i6?`}@x;>Y*R*xcI{%^pm*VRC2m-dUnk2UpW$PXk&C&uk0
+-xZtGoauYFI^L<s!uC-+gAtj6LA&8x2Ma;{=1ip0=<#7SJQ*xzE=4!`DYr=3%7FIFJPqT|9Ck$o^$rn
+p9Maft&NekZ&rHz!b-q^*LoL}fMChZ@?G)%5+g2ob5y?ztFJ$mzBe<QVy(}>aNyzZ-(AD)LfGRgmt#N
+U>9e^aMN|8p!R;4Gd;>IXP9Y1klAJ((qZtw?lNObvncJW<GVs_u}4T@Ds1qo2*;nzM5?tWBYxG<p0y5
+962_s>SZYGTsrS>5bX8b(YBWP23q*gh`LW=0sr;V>9jiixR!H0a-Wux^2mVX_O-~u~tKxppjL5WuDA(
+x!h-K2PY9wHZW<joHdYTG!8pE4U9#Y+r*elCr&Of7@Y1a1$?n^+XQ9=t2SJT@wV6hO%gN#Oi6ka0lve
+bCPSPCpK$<Rc0N1bVfqrZhHF9`R#<E8=eL?q-$Z@iyy@w`r&<%P^4UXwa0+wVeui@kMtzuU<v|Lb@n>
+WX%x7dqYQ=YJdfP$u;K9y=*5^&oY@hR0QLKRGj%_%LU2CTvGpNx!<jYEYnQWHjS5^DYs$E=@oIwuqSl
+NVDwzMkBWBm%sN9rlsQbs#b6zzaehjstB&==o*3kaT#>BYAc#XJtOIiP6=OM{^_qE;9S;x@wPZ#zxaW
+IUiBG&3ixMh?s|1=gVJRbfCSm-z_=INs8$?<F|m%W!Rlg!*ejoS_m0GuTgm4Aq0Dfp3<@zmBTTnxF|W
+h3ZYLws&*#4m)`V3|a{qfkI1(-(`Y&KsWIJCd~BdcZ8V17e6&?D`eXVAiqasMK?sdxeoeI$5^zIj+)s
+}%yZw;y<fku9!hMK5<aw3O3?alY^v8w3|PXbmv7ztcBPhE#324KJTF%|0R@8+ewbW{F-F_Q%X+#I=Li
+Ku<3H{029l1{Cild1ppEf@#vEzmrX*zm`xu2xkRGUge)Z6K_0UV!X!;J*q)t{y&bCzERDV8x^V%5S=r
+*C;U94}+u$qtpI$&cee)j$0mBdQG=%m8LmWn(_W|P2Svc_XBTxVsI;gEH}rJT|?TVFCT=!w*`ne7#1)
+(>xf8uETg`w<_CE54CARyg&u(WCeF#3xrZa}`PeFSL(OPhLLUk6#@ORp;do2i=1oMJzwu4{(rB(`4jG
+{Z7tC59yYx5AsPrv?tqDcF_SiR6iZVBHY4=LyTf9Ks&wA>7d=w{`;O8?LF?95xiVEqrJ!dGs0D)bwNi
+q^(g*8BD+RZHr2df-By@)U+sPGd}C&X(;5qL@6*?G_T;4SuuM6p43v0+!Jp3dxej^&@AW|5&nd67dW7
+cMdqAE!kT=zfjI~c8%6-YqhavQPj}`IwHifyhV|Ut!c-V`Ghs|goj#iH9;r`0`-naeQStZV_9`5(g$`
+zn|oq|;mkij5jW7bsTY#O5wrJy0ys6k8Rl151ViNbyoGV_tw1LJwf(|b!}lFW#W>PsCs5kp+U(%^-;F
+K=U;jkGZ56`O7qPdPTxXhL@h;FP(X->uJD=ZF0cX=CXy!^Hf*=8IEk?;Oev>|gQIZ9@=>$;F%l#Tc5+
+=Zo4Vu0fXDgH<CQE9)1s$+r_pgl*?3U#<{%<TgR~hH>6f5@Njek=pdf^zoN#3VoWuxUm*{fU6taGgEs
+BeAD#Bx8d;1A}=^q04S7+L?uwLcfo$CqRcMPMJkgTn)~bm4U>(^*LOGvgTd#z@2rY@iw9!O;r#6Ca{R
+{eYtb{W1GS?hw%p9L!&U1TY-vE|cDecNBkgfK26p@`Yu8mo)@aNNounx`_CTChdUox8=*`X`_@l{T%0
+$BjP3BD@+>W`-9>5!}GEMq(uglC^_l%qGord;&>Ea5t%MRTR+^fepY>rPitk7X@M4`o#WFALF09O{qn
+Ahm<lgnXl5*)rQDc2zJ{6&^FlWe@jr<BSJ^P=~2YmckaQ)ww>_gI;TM`J@by$*(|RbqxQ@Irw?Kgag4
+305C;`wG~_=Pd}45@VNqmQHq%ECmMWTv+{Cm-y*75e|~YgN?D08Ca5nnT!iJml?3>BAJ+wluo!Q1%;X
+$g-rx`?=4qaqoHv{OE6OChN}3t!Tk&}a(xyHc!o)n4+ZBSvmHt^`3}kYsuIhxXD|P*t?j(C57MA0WAf
+h#uKgr-UOPY0zio~hd+&#w&-y!J?Uh`dt9qj2$^HAnFG}Chndj7S!`%6Lr+=qs8vNK0m<m5TWBXnCWx
+(pby#3O;z%vczXtq4(T=96H6F-E2qMp+aqS*dS8LAwp11DzPzv5}9BVT!R8#&hs`0W)Y9Un{5dGe$8;
+)FC>wtfbj>g}IFjkyufWwc=rmxa~9;j=cX+-mgoPDcA@XFgv>s)c_KReaB+oWVaJw$0~nTE|0ILi61#
+W@DqEm~=BO!Hxah6-VE@nXr+ePZ8>o&-582C7A<PXqF%TtxezV!t#ZUQmhw$B$LdU&B$}_&9XJWAQ&{
+4B=Ae#@p+Nnh70j1#A45E7Ud^gfhpf=q~t~RBTyJSTj~jHIF!gyvj3Rx9WlxaFK=s-a$Yk<(Yk4dDRF
+#RjDv~kQ&Y{y8QNouu#)*USL<^PO?%gQ(E5Huqkyy_6Ef^4n}+`P<Jq*i#-3(7?+)1qe9uTu;_u!su6
+Msx7(C0(XG13R>8X@IBE*f^ZqEKA90}>Ob_IM+@B4()x}gN8{M}`;OJVW4o(3EL3s6e~1QY-O00;maO
+7>P_e-97V0000P0ssIa0001RX>c!Jc4cm4Z*nhkWpi(Ac4cg7VlQ7`X>MtBUtcb8d2Nu(3c@fDMfdrN
+(3L_d`T;I{E!;_QClb<jgg~09GqK-qw6%|DmiH0n9;LLkO39793K?FaR13rgol;5KN!x-w>C&GGTT=n
+WdJc@X9rc}N$e}^<qjqv7IyUUV`Mq|PskDc$8Gn$&<7o)$kmWtPyEUbUYL<TbaN>~&=~q704Kka;!mo
+EhJODJoxCt@Y8UQ5gY?ZAOA;g`qmRZx!Wohd77#VX&WlW%NQa^rZPKgYet}<j6pHu&G>Q?-x^7Up+Vs
+RuAJ3Wty9BxX*QoI0AO9KQH00008031s8R!<ka>N*Di0Phw603!eZ0B~t=FJE?LZe(wAFLGsbZ)|pDY
+-wUIaB^>UX=G(`b1ras#aPRZ+cp&4=PQWW#4~XG0aFBnL7TL*Xizjkv$SZ5vRTWbN>X<G_dS=S_>k=)
+lT8N$!<NYVzULmY?zl1Rd1I{Rwf#e@qilp;sLkJ^w)c;382;|=?tT%S*m5ga?bchx2EUZqonTu0GfFK
+QCVMM%%WJ_}rNb+ux}(r52zleAHKJwM*jw427e;jLa@v2u!?n`un)i)tpe^VRHvB4&qGvo`O<V1#@wA
+_0N}-){X;*LJ?k_uO82(2CBVqice=bd|wkvkp30MyEPbz<FqBOHpW7n`9KRWlNW@ZqzS3PiT4Lb<E70
+oKQK7Q9+8o@p(`*IjMCs{Nfv{pKWXDjS_(4rMu^tD(d#T2dhD><B=xp0qGs@|lBF`n5o*&|2?PAk*H4
+X^i92YaLdp$f~(ETBZ15eeqZC~etZoL#uLE;(7aAdG^odX_vXG9t1Ulp8oMd+gwb-Mt{LvftCEDTId5
+Z$#<w5&K%HjlEkr$(=fhss3Dj9C<gAmZf`mP<qmis*R$Ywyjp<z*Nh)-i|Ks*p?aohz#>X7W_x{TofN
+SK`Ct7oLN=HV!yAdl`F+4tVpAAwl!i9Js#C(hV;}sJU;DYy-Th~@vFH}S@s{<?|c|!za>{v0kC?6%f0
+Q+3@?L;P+M3OdzO9RP)sRCV2T!7;%DRRog#~Zh-y}aI7&!-1*gueR(;#a+Om_hyQ0TftJQ&GmdX=BoB
+NskDclrfZHnJp!v<xH+;o|KQ`+VnOfJAh02sF@=pt+v7G(AnCgio6t%=qRXfD1LuQ1}_hRBBto95m7$
+UbAMYp?&X%<eeyfHo{l%23_s#VvDkn*!GfO%KXgJg9wLMKiLddA{uiei+LG25{E%18EomjlMbvg%9Ge
+5!yT^fe)yWOk!0<2sS0AQ>|GoH|Ppv2*#4}p$RgNI|&zVq?~ji!gDpYC~Fs=FcS@1geoNbyPx$}F>sL
+Ms`{jQ0ns#<Ag(5H@Ifh?uf2_(wZjFkk?{7&wNxX)mKlNJ5L$O*L+&qnm7MO8Fk`S5Ig`ByKczAJ?~6
+FU82>6%?gSfdM~q~KJoI(!>{BM<H+90(j(?+lW?oxQ>@yNnqvT;cVi#}@vE1+t)l(k4lhS)XRUF(uvB
+e8(RR0!(s8=VTQf)`xb?4RnO#gxR=Ku$?lh)OVcH^5q6*H(t)1EIT&J&`oOko05Wh+js6Kxzwo!kp&>
+)gU6dtqCo!Q=sXj+)6Tvb>L&XaaSboAFfyU70B{Mx>OvW`?byZ`_<Sb}qi?N*dvu@X@2s<%nSmXUR!+
+9X)pK&wUE33WK4lqBI9W!lkiw3pS(d>^l?+X`%9K$G)Z#x%Wfb9FVCnrsI6hhVgt(U$O!GT*#GJxy5r
+WiRxhLk*3B6hJXXWWyJfByfbLL`yb|MAS}%~OzA*n^AVW?sB1%Y7*J+Y0hYY#BV;j{d2MESbV(&D0^L
+GViMNAw|IZ8s8Gi*yNl}4ika2B#2A?S)lcd6?EI5bJ#Nd2CWhtc1W^TzyTsy*+<o6XiFw5=CG2eq1tM
+IBYV@6<J!M}K4W-N2&QmeNn%)&(Wp1ZCTa<TD&Lj6G572jy45bGwsHYeKilUJw;tIwnrr<*)|@tiQ{9
+B-LD5BVVe2#5aq`STL=9u4h7z;(StFU)$4L}8e`!-{vR??R!ntgfe`@=_?roZUI{aaT@g5{1?j-xlcD
+E9VdDLCiaUt|UO9CpE+u4SWsLXA`|RsiYz34qKTdH==#xCJyjZ!7&`{C)i9RB}heDg`ZBVTr)-6(esT
+9UKAJLyj2~JRVe6!9y~j2bu+{@iI-KfSoh*AMc0@c1nZfw3=myUWclVYCzQ06i+r6;W6I@(c%(ewQ(}
+eVI7krxPR{qrK_JcA1CSKWdUNGkW65q@YJ8n88zQI|<P~9rKT$Siy*OtT6_gT9=hzX*1XF!sy1R;vfc
+UNGDJ@y+W<7DOHlNu>sZPL>EA$}etkb<oRYgO<Y6-cbtfO?fi(D~cP^S0?Q$Tkn5jtg@$G7g1M26=ci
+Ejor0oZieG%ME2v6V$2UEZVv3b?s7h5lE&{iZH1?*0rYesOU}bwPJ2+i*e=nvPz6kbAP6b9dsA>86g5
+c@3l&gM0a&eVD$du&>v$mv+4l;SMJtM}7tnGIyGY5x|nwv;yL$ujPViBNj|wle#diE*lJ>|M0LsalM`
+KsxN#mE;5!8rzH|2fdivW<1jzS%u68x99f4Y&>fHX4kl$^#uTSpE0&&n=CDc)Dtv=->yM~Jssn4F^Po
+F&<M;|YO}gjGW&uz0%#97>@f?I9o^GV3oddZJ1V{wp3SpcRvzsBipg%tD*wZwU)*}G00mam0w`iWjjv
+H6FMB6ZFcufVBo8n3yqN>UjLs^0dio4l0QO;}o=3h`t0|XQR000O897^_9wnxA!H39$tK?VQ-BLDyZa
+A|NaUv_0~WN&gWa%FRGY<6XAX<{#OWpHnDbY*gLE^v9BRLhRrFbursD~O!3fSV7<vF&*aEVk#Gmgq#S
+BDs>BH2d|X9(Lq3X^S-sCzi+=ayYWk=skQyPcJlB7szdF_nky|+O2@E^?Lo8H0?1Eh!h(v49=dEBp3h
+e9r2<|$;#}Zw+_OAc*R?NBDZCPRf3Y#gAbU(HlB1}C<@Id)S4u8#0YeS7=y9~P=t~9FB!n!2mR*kXk>
+zJKp9ED{>DHk4v;dy_BB_bSk0-gTuXuj<>8H-{m`*qa$93xt05!r*3v}aK<_GvF_#5#A$&i7c?FRXRD
+Ua3%mEC%%#jIn3tv4!n+t4bG)}$P5zc5r9Bv*Z^va-CZy2$*?~<T2|Ie=P)$K<i*jN3?GhYrHWtNwIj
+>^%IOej3nN&^Er{=Lh3K9DIWfMDocXL6G)LFHc%PVu2oSjoR*bUfB+yChHqjV+*FKr&#*o5P?L)AL)e
+G(*mC@rsOiLZz|O%!w?ZL?-szTh`oJCM<CwYRHo=q#oL~;%{3(Ho}5V(!es45tjz|ygpk)(FV79JnOh
+)i?^%|3zRC@b6ws?9~$VLJu=kG^Z_VJZl2oqfnRb&9ILRV*GdFmhAMFM<R8y*I{Hyo41tbASZF`tRR;
+TWkeOsxOwOJ>Cf9TCsc&JmR$iqyRyjq>w9}#Z5gb3bf`_fek7;Uc8rIZWHkLKbb&ii4opIQ+*Rjjd#i
+d0Z3;IDBb3Kax!80F>%3JwB3^uT$ip@PM8L55)P)h>@6aWAK2ml;P_Evjbwg>qX0019Q001KZ003}la
+4%nWWo~3|axZdab8l>RWo&6;FLGsbZ)|pDa&s<ld9^&-j@!tU@A`_G_Jbuu=4Lk8mj<+0$996oZn6Wf
+fn=u9kSMX#s%eU3SY*qJ;eX$APTen5ch5}tV5`ZhQ&s1FBgL_6`+@D+y5_q<w2hnzbxRDqAKJFIH`<Q
+(<<R!C*}iX&tmyjoQB=H_Ob>Xsl|x_dhEH6!^&{`~IJi0P20QA5=wT&Z{kbo@!;;+$3hH0Vt`p7ul5I
+y(S8H5-{V4cpHv7c?F~Xc9Z-$#@-}c86_sLfNri-RL@@g2nn$KqpuB-g4t0lX=>fIyw`>HE@{B<{5%x
+1G)T}sK!2|j+=@eb$B?XShPf`4`Oj%`cHnVJDBu(GZhH{&GhOCfp1wr4gRgk;CI8f#w6X!=Jt3@|7jy
+>SYjJhWq75y&lPhq9?^7$ceh7JJv63EXzvZfn3E>u~OH;H=jtFn|Ea(DM@T&PvHjm~mg2gLucbh>`Ex
+W?u^=)I7n4#zDpRY`qqZ7}o2#<n?~Zc0Cf#4Z%x}z&P_f>?Ol_i^76&0Ni{SQP}%Pck_GZZ3DPW@4{Q
+U=fl`H0W$!C_3GE`>$j^yvBum^A)EkL6hF73nfJWw=lz1n+avnJ%@o9@9zV?&i=_qS`01vBMWv7f40#
+W<6cte7MR+xnE}=NPN{Znes0i6+2qN43{w?Y8gHj!pgU-Hw*MDPG%Oz{tfk}{7xj#=*DBR}qUrW9BX2
+QJP{tODosen(g0GBXRsibz#x>icDt+fD-bQ^w-H837LE<r+f59Phl1D{cv4{cqc)b^aSau|BC9S1J2)
+rdE2Bb@%)FoDwRG#>)p<aON!))Kue^oc%}y93=(AiQIvM5t9!g$%9ML*~>=26#rLq5(OY4To}I+6)-A
+W1$vq`@8no!Irk77K7k2dkEBY4^4Y&kp6Fn_U)<dAKY3}FAlo{6<d!LXJlQ7<0~{FNKmt+o0hJHhb=)
+C;HbE!C77E799)g4o%EWt5T0&q^kxHu^}cdJRH<Vm$2Nqx8H`eHIBIB6&HUI6=cP6t>~!D_t>=Uc579
+X0AcSdf+RSY73U<Th!1t$v0OIe^T#12z)u-|-)w&DKi$#H`=hseLKRbH_KSTqH1%(!9fP4M|dusrNXR
+z$YaVWQFk>0%d&?1;OZy4V5)JEByaoYlsWY3|A!3~>|HF`=1$|dteVwqyv*NlOpkiJ5b;UE$C7T#a+u
+xK$F9NqKJfJ!K*2|cD+c{(dpWph-EOZF(r75-XSZ3y$1OnEMgU<&Cv_t0v++<_K}Vs@(TYq*%*?82Qb
+QJ;BjKNp3sY;c1jx2+hmI>0ngeZWibe0Pp?@yEVz`$@x#-cx4M&Cw`{c?9W_!5(GEh}sKEfo3c;&9zf
+sX=qB7)nMRJkS5$>Wujy(05pH40cFnkxotmi-aY?-eLFVQdI$dw7fz|cCP(yVhg<cYz<#~IVAHR>4Ks
+<_1?gU@QN`^42JN!s<AN)Cj*@m%v4+vF;0=RO#?a+qtq^pT<DJC%6TJOc`?g+<@vXZ+dm_bsV_fgH;c
+wghUJq49RJj1Y3IZkjAa)OU%zhwf)~#17f!*D4DV23LE(EvEM!AQhoyxv?hGsR998i^GjK=#|gRVQks
+~HwO>XA-*Ui64)gnV~<rxyP&fB_sbob6U<NG#+-f4&a1nwEMW>h0U_@9Y?DId8x|eIdq;rlXBy?~K_|
+THuP{TzP6|-Hr0FZun`P-4&ql2N(b(gdvvyfKWhYh+xl}>X!0u)Jdo~Zj{P=BDp3!M5JK@w$*|H(?VW
+`;&E>;_BVy0t7+s&Ef>VEp@GqoutE@p{-fBn-FdzUooXX0YNYuqJ2Vz1H6^}#dwu8o+Bv={U_an-%;_
+(mOl4KAhjwjt5yqb7(l@TwNX87^7XSrL8yGO}_bLNqWel!`1>(>QVlQ}a3D6b#=Gh0gZu_<MJbc*h=$
+VkJEbjR*cZ;~eV(-R>yq<GV&}PiNxF>O#oFLVbKMl`_vtprPcc8oG{Cfd9Ti*`Z&7EZBel8<PcfQ6dN
+)Cm<e70OBPfWI|IP&4pRy%N1!7^RNKFif2o%+@7?V8<sgYUkDgQK|#rhb$Cqq7WLFwpMf6`tIFGGqD(
+K3iYlF5gQ|_{wv>CT1C-&bu%3oakQWPJchQFM#T?urGPe0}l0{jT%-_f^x1oJz)mB{K}73p5U0|PEJV
+zc`!-h5bt)EvwIV1y-fDUu;Z;`p}UC$55Q|5`Pw_$8sp??rL52{Lwov(pafK;Xj>1aSlg&VM=v<U4m<
+*0pHbH%1WB>{V_A>zlOS+Rci4@;mTVK`Q8pGB9I~#o7goYvz&)d+%0};Dvq87b_&&x&2Z;^~>l)^iN4
+w=~@B_H>GQseV9a5=?C+MZF*^R}!N-3+r9VYe@h{9t#40)K1nZ+!TajP6EV8sW1UiyiL#({_bj&i;TL
+0Fc7iFecT;|&e?HC11?$sIaHCVcfTiUK|4xP6CuDGz+l(%oiOHX$eYc7FvnnVbT9Nqm76%!23w8`Y%A
+f?Fha?^2Xqu<Vhx_XHSh%DU_Mp2OlhuEiC@r8L+!hl!?4nRWyc8+GIA$`t`4m(Dnxk*Dc2?UUxygY`m
+7>Q;$O=mkCgFWir}%o7_*+-q;q_*r7yiSk0OcVmw{w}xY^b*>!`<d`5|XGr2Q4~}sF1Jd3itRzhPZ+^
+}NX^PqYRDzL@IS|xbrT~EQCH4LVuh!dh=)rqA!<DzwOu{VE7fD?pi$@d(rO>Oy?3r~v<XJng%JGQ~r2
+<{-r_Dqth80II3d9g(eD0kxv#vu|95-Ezm^@f9HOxFeBm*`+b_0S(p0c>i>lNSO%HTqCjT>&#SGRWoe
+q1FYAm5ZXlyGm3DtW4AaN+TD-oZk*fu{?a@U!Qb{=o>;0-tkNobq`n-83P@xYFLN%+MCpax?N-@Z=SH
+f8e_ZoozVP=eIz$CMd|2yJ4j4J{DqRp;8*Ea1nvh#RRH7j}1CW4eBy*OhmsMk3d_n77{D_gQ{S2Rf_P
+67zWh79P8oiC8SO|d7?bovSAz*2YN(cJi)FKG;!=|!oHV)Qt)8hUVLFeM7qF?*}tK`5b2IZ5z35t2CR
+|jA4kcT=%8tezDx_@6-8KkuWkzaNcm1-Fkgwz*Mu_~q%V+9&{RBms+^8fa%J_-B4)}TfJ3I(aUfCyzZ
+W*I$|crbMTxmJ5{U?$HHVl$tK0TLDlphVp;N%XARzDrx-KQS$)YKyj$!g+UE9r-jYKbS^3;I|3@Yh4v
+*)K&Ua@!R*1M|J&<pI9016*))4oK8H9}CvW#z#EbS)Vsp8-e6Vm?NSM6K)M0Nx^{j-!7bkKI&F0~4aW
+N5_Skp#;|s_#0L-Pe?V`BRhcKxFl2qf<XDehHLS_i6Gb4Ay#g6*77HIm%abv#QncV_Y1fn7VK+G(dl$
+Fm^UWC8>snX8H8`&7eG;D0ZAwZ{zIJo1Q=|wZfd&|C{8RxUitTe{S9;#094_c1g<h$#lWvo9Ievz=q{
+B=P3{>n2kZBR%GJVYRAT>x(W!xU0=u&1urp4$1XxP7n(g`Lr=60D3<8655G&o6xDnM}q!;m!LVW{b&?
+R;g|AI7iq?xY+^qBzm%zi2;_)XST7}O?%I7+uZp#TDPhESYHlGvYs4E#%pYJSP?#Us_nv0Wl4qrO|RK
+N5Q1gWV9rA%NsNOzhqFF!Xyh7Ji=a_;8bM;Qij;c+Ic9?gw>|u28r-iu=QW$$elb>aPN7zbBSCIew^w
++?9Qmz=3G$QM9Af2lcs$eb94$3K+xQ{*j1|XFqO%jj*o%93p3z$3%*5@&FSo>Jbod;;-Rf&?nSbhWKP
+X9kppsZbyHB9VJDPA74{VqGGV_-xXxgh4nediIdqpN^g+t{P^0f_a9}!ZuYuEMY)Br8VoXBUF0$}T(>
+D0b;rv45~P*=rF_8cg>Iqpfk4&ZM(@=uoDD{@14_8Hw|edP5Xe&MfV-NP4Pp~`Z9>@wxfzei(9}~if$
+6&}c84-<2$=8uviFW023;H8vz?cpKp`XRw2bG+wRjK6BAaaV_Xtvid;FS~I=n8c<W%1*u+u@*An07h1
+*XumVE?&dzYkp&to2gLOWO<6ZUm<A{+_f|9=&)~yiTiO5%iCZL@p1Q1pX-fwX}MAnrprDnqpfR#=5hs
+oKHL<b=UCxX!bP*NZ~kdNEwhPTaDb6jeYRi_U!|2?6!mY8#+3vtBRLS5qN!qJ{;du!lYpah>o1*u422
+iX@Nz4rzV-5Y0HQ^Cd_4m{y_Ny`)1)MJYD6_j(lD{FCI?;d`s?RxrfsGnaxA20j2~Sg@$~_GLhC~ROE
+Cgyra_iikuj7CjjOTOI7%J%oGyykqyjvM2rPY66ckJnTfo<tHGik%ifDwv)q3!o_{<OKx=RQ*3#{6k%
+T7ise3vwbG9##gp)R78y7+KdWJ8KO3`hzrq}nsChd2u;ILT%<5`!Y$ViPweQK;kMrZhl$qS&4F_W43(
+RkV9L+;_EN}`!hWQZQ_vQsZ67@xhfmz1>q%gcd3q<LR+y{y9RU(ZS}``521f}88YqhC<({%ub4;*z+3
+eSLVkD*g-v<ZVOHX*yLXz9d{zxl8}bCdva?i9dkNx=r=G77+i+i{9ljUy6&>rFx&+v@5h+=qq>$J3dh
+jGgo?ajp5IIoHy0_AZ!zhGC<=F`|<!siH44C%FUosIp4AW;lpc{bikNt2)f52gSIy-WKw)n+kU0<2{w
+a4D^ZJ}GEf-eJ<FGT1<=phC&#>O9Kd?Hr@ul3T%MyatT`Xso+qg%#mhGHq~BgLt)`yBT!M1`vZiJ@KN
+E#m@jTaT7sLp<`Dl9o${Or>bv7$iR~~Ups*_qTQH?G9W8E|YQ;y=F$}#WTc8KW|H$Miu$#mi2WjgWv=
+GFi0EA$IKKv)|$+2Lh-^1f!&S5hXty^CwX=2uu$p%BhT`7??r`SMau!L#1hm(t|vFDa*7hzfX-S0O$%
+KL;el$XS+;rc;-)%MAvTtxAoE9vnS-X``c{xuFD`2TrzVX?0>b2rLD5wNr9M7MWGIr4(qM&mJ(HYNw?
+iMUUkec7@Zf%v(gJoN|xvQpWt3XsM9Q)LAVs{33#v%{`xIWy?WyBB4gjY5K|o6{)zfafK1|u~TWl>w%
+w>d-+zBTumVtJ>X?3BDC}Al6SbslR=2<wxKLxxuf26l_|#Tu_FGlRjCEa&7L?7t$^LXi&Z)9FhSCE%@
+AxjmFW=!UfqAvfVm;@Ngg=wm}1U$@0Gd~l`x-H*1NGLqapTtZ7VcKhOCiLSn?q!`vssH2(@5uX+*N;1
+P_tAiUYDk+e)Q_k1bYis4)e@D3fdVcn4o<>!Z*R*MQv~MKe#9ULy0YTtV1%y+q9eDp|U=6>6;sr>fyp
+2cN}U5JJh+sBQgQxRhPAw0#X`=j*yON_xfqs7p1tvQaUfUNV&&^MV2E#zC?XgT@RnP=OZRL~fJ$M&)S
+y8DZ<b*x4SpvRg*7g>f{=R2bLFU+M(UYAVm;d@cpV7Oo~IO!v&(Uf+2y%A_a$0Dc3ecO@BuGt~|X_Gj
+_P+1RD0GHPhbXT$4)4ZE<>$aW^Jv1+@f@=%7am&kVPcbK+rFwO7?{tR_IuvG9A7+*w;lE4({2`eXFF2
+fE=aZWj#b<QN@^Km(|fY+}#4Vo?hgl1mQI_APm&abs5c%|t-&Gk=p(>^ykTTY=llLw6Nykb9Sb$}&C&
+9VEjF477Qmb6-1!c2<h?qJhSh<A8x*QT6`B})yS3m_udF)y-tuFPyUqlDR^lz404sF%@?@*1FsaNvKf
+(MT;ZJ=D-wDzqQuxWzt6x+E#=@&@bfPTLHek9qJ0a&+g9rDoc~e+%+b6JCd_t?ce^MK$jh&uqF&@?dB
+brjM$psN47k4RU<QNijAw(2Lmbo<RRETsjOcXP@XTs|zm(ssa8Rg5+3RvRqkKQmGyF+LnGlN$u23T(O
+`MLeI?kP~!oO9v9c_AxMv#vWeDP--204RtlNWJW=~GJytthg`ZW?I!}cKh$@;$c>ojAfP_;7;#U`5>(
+ESx@fO>-VTAC_a%)EaW>s$xp`$=#*dSJ5&*z1Nb3L)6vxhSrIs(p#rO&iprILqNHvWA=0`Yn>Go8&y8
+)=+ARCus1kqPxoBXO<-jRyG=q8Q&98Iz2_T<PN_7A2$yy249E(9$dV*WI*9i(KY6{Q}QC{-}_9{T7{7
+9c$BfC{!nsdJ9%HFZ!=oqAyz5mte6yVQs(F1Efn{34duaYW4l^eiybzea2pc_%j#SeFx_eG+TDy8G|g
+uul6dv61+~z4XNlI7xM{^;OirUNm4Z7$u%@~<63KIIw?Ic^IL^+>hMrqHQl%cx0|WX66tmLykQ&70Gn
+&}4t&cUy^3y<XkN;<P<=yWN$A@Zt~L^|Cw&veZ%LS=VxptE#vs!Uif{3l>g<N8nnsitGhHkeP2R_ls$
+8!X9EmuT4zvlh=mr>DHLp5Un|zE_n`iv4Qk0`base+5VyC;!NbBQEMFxASHc0O%@#@}#FWH;Z;ru2%6
+RKqZ2H|+`GC$PrgC9bv3fQ^q_zoK(aasO_ZBSj~w@*TCq9>>hHNB$$t`&q8{aZP9U5#$O&*}lfjL-&5
+aAmEed!-%FG(coYrA_Y>1z{k0XitO$8Dz6m&P071>jE>SO~gSfd%_MS+t|{Dqi-Z?dl1?7grxR9=XEU
+4)a9i<w;~kZS|J0@LLI%u$)FBGnaM?Vgu7_~q;v@x*zFb>zT*~T+-Q`5O0@lriVrv8_hRDKGpGH6&q`
+$9m87OS&H7Ww)&b#8ec47G#l|2-9v#|Q->4VmBAFuTZ6VNr5fE86Tv8Ue30v5LkDc9@Dhjt9!lP6@?5
+@$UR9)#HN&y(RwrZw4w<D!6hW@PkIdKJ5nc1Ruyz6->b12z3n*bE(???ABB)t6gFOU2y|3ecL=(rwu^
+<50}Wd@h!)x9DPN?}aZq>=KYBDV`NEIFTc_Ww{z0|XQR000O897^_9R`W2XhXnutV-o-XApigXaA|Na
+Uv_0~WN&gWa%FRGY<6XAX<{#PbaHiLbaO6nd97GmZ`(E$e)q39^Ijy()v!GVOM$IhhhbPTG({I62xM7
+0idjpdMpAaPApd=b6m=mbCqY{yC~ThlcP>0ED{C$kFoi;KUdYud7rcZh<z=1Fc}GrpQDCYVuVkF;($#
+8}7KxPbD-(2#+3zB$_W|F1qF>>~3h1+5uYZO+eGXEICRL3<I5D+{%nAW!cPJxbTp5WBbBJSBF%`#w#3
+Hwv^hf`U;v+f9Qj~B>2Pz0Xa?Zsm5t$}GJOX?RKOL}r4X<9q6{;Ka<JJ?|CF$XLnW=jO)Z9IR6kcUe3
+|v>ksc?bSSy`ezC7SX|C5+(j<TpT`&6Ut0u*ySgRFm?$_01Ff?>pfH<UT11elmQ(b5MIGyBwM<^&(vD
+Q4nBm_CuFG%a$LU$30En;lfB9L!eVQY~VOX)$>IJb}57K(O2Z8^eIgP<6M=6(`X#wOR{Vcd|m2UM)*~
+D0v#aUgW`l9E`Z1K<t&Zri~|Xi2p^N8!QX`7B3N6!c+aGgYrph+Es^$7dv~TaZise!rhNuHT&5v>fh9
+lUIRxGtDuG}fHDhFeU_)ImsfH^(MXEcXI_uis@O@8cG3CJIg=K9!k?D-)3x!ehI&j@viZQ=Et5hx3$W
+vMebd{@g(s(9v?CXdA)VzE11-qmYk}8|}G+4`TXBL+A6R>YOI;a!xYDi~cfOj>pzN4Dgq<vD?SV>*3I
+*CIsCp5*ALST}$V^q=9(zMbQR9wBR*8jw|t8{g?b}41Lyk`tkunb2&f!+*kQ)>R?Gxf89bkB-RV0C`P
+xb6-W(hIs|{b?B%nMs1@M=$c!44+&gPS^S|)s%`#$rq|}n>!qC@IQzpQC$2*`KG)F-c29bbE|uHMQ@<
+&7&efklv&9Iebc3r$;)@V!r2{e`Dwh^Zyvo@Lk#^_pQBT+8SFRWet4YTmICYZxAfYN`QaP!xPkHCa2*
+lyWuk(GUhm^wAPopC(K=U0l5@N7X!SbluO<dAcoeXs)+&qRidX-k;Bido^lJ51bA5e%0e`n@&nx&b`o
+hIx;)Qc=otbLCL#3N&R6bFyMC-QB(cC!`3pa;xU&H$pYc-4sZ-mV1-TFcr!lkY-yKa>3De}Ng9_<PnH
+=c-s2xxT(!Z3V(6)ZVT$V&(g-NrFP$1DKuShUf;(9xmcw58|QOY4tp%HW4DcWK;Gdk*-{m>331{5DCc
+w_4L=y8=HlJk4GP|IkiA*P4k?cOvASkTpYZgIx>ToK+dwQR$wBceu4>`-XN0U42`V?QjcJ(q>WZ?4Ni
+;vzJvzen4||HC2Y9XthXh&giiw^#nU~L|R_f<NWI$D_oE?k=LY)-a{!ly+f-AGowiD1#j;5P&S2PbwO
+5HiE;zGMnOSiSJDkvWwZ@-B?cu@8xrcZKuHrEwYNsmu3?3GMLDpID)HY2tCSSBwZ5b+cxPTqn?9o1$n
+C+s>^VF-v#BBmJ+fauNFN@9hsm_mZg#8@O`@d4INm@(yGD2Tf{8a92^HR}U})<w^vA)K;&nI9DPxN>;
+cZe#^gaI|8vOi`x!m{@6qoJ|3w;pkZu4-b;?=+dlB*tVa$hVbjTV?j=uLp^jsrs>20h2DiLJocvRAgy
+Uf#3X>uImLt!mNwpu3X(sOZTYqrPq7QzLbs)q>x*{Ud48p<~JGZX>QE%jgB$wHaYUMMd309uS<gh)UQ
+l&71A>z0w<+HOt_^<-qfG8^Sg7S!;kN{Pk*heveK}t+b?`QCTN_)Ky}0K9<QZn!%|P%{M*=kNQpf^ql
+V>5!5It6^&Nn*_rsdc;EEgy&7}3N!oH$Lb3GZjsO2z(bc>vEH43TCYhtTcVV%A2G0KhP)h>@6aWAK2m
+l;P_ErD@0006200000001cf003}la4%nWWo~3|axZdab8l>RWo&6;FJo_QaA9;WUtei%X>?y-E^v7R0
+8mQ<1QY-O00;maO7>P8*Dhyc0001-0000m0001RX>c!Jc4cm4Z*nhkWpi(Ac4cg7VlQKFZE#_9FJo_P
+Y-M9~X>V?GUtwZnE^v8^k5A0WiH}#XRftydO)MzL%u83&QBVp_Ei6sVOHNga<>D$Ss<h%#0D`ol{9J|
+P{G6QB<dV$%ykfn?q-2H6+=Bd~5(TJU9R-+9uGEU;)PfQPPq4geQBi&oc2jVh002-+0|XQR000O897^
+_9VS}l~00;m8$`=3t8~^|SaA|NaUv_0~WN&gWa%p2|FJE72ZfSI1UoLQYtyo=e<2Dw3_pcy44{HY+qb
+>SmtO{h)WF{?|1T$F_i*%sU5@m5l7FCjp$NR9qea|JSFI)EP!v=^Yk(Y<$z2|<A^ZERPObcekSIc;nv
+5nx3m3dRLT<IORR#sakD`pD;A-$6oFIV&Vd^VH2T4~FandMsTm_5`^)VJP0M(p`tPq)d<``epe?;qYp
+?7BKc?1q;m-;^R^kF}KwU=jOgg_oH}StVGAs0><Ks8aDPk@dkAsv7jNH>^^B@in{q@w@M5vm^m>lCYS
+)%(ucOsj7@B#XMqjE%1@cZKK_1tz~8DMOLO3sqNa5&qh`APuN*LUi*5+@aNYTaNEV*_|Mtw4SQFr4KG
+<M&=>)29vCm7wu)Q%DwvyQ)~;>c>ELA^aOR(|fd^Fq(CUMqH@W}q>G8vJa`XGo=u~D^b6c$V#?W(tZ)
+`W+XN%=>CcdVkw(L%p;z8Lv)l}K7)=GPzH_(2?3SQR&%FUfgF%T^VW=C5lN?}DdF)P`7mWiAVRJ&NRw
+?DCN<$ew@<DCGL*w$-fotE5~^`HOIU|FlYRT%Rph-ECVQn6ysg)}U0s?<8u8?V28fn_;@YVlViwJ?AV
+qa!yVaTXh>{$~9i#Mio%skG&RZK3jtL7A(W6a64;qbuVVN`E)49j-g8bqi{D<DOwN?ao~r6qt0Qj5At
+~e3>h)R5w0u`xZ;ztKCxj3BB?ML|$BRy)|p^R99DD_T8tmO1~Ox;X^;nIHPaJOa)1`s7szY|Fvu{Z2`
+S1i0YuaYeMhV?dE0+nrzLUl#!mr49(3>RMt@Ja5H&aL5<&_!m39PyJ;u*RUGz8Xa5KE)|}2dwX9bO2$
+Cti8jhK?Rwecm#&UY-)xVq_8Fl0=qs~>5WHPlbUJbCj=3sCaFBWd(mD+qpunH!3O-9sfW~?UvWOLt!{
+d8@ARG~4KqhNFY_yUPfZKw${Wn+pp+bC6{{f?Ig9Y<W!P~a0SiTTAW%#xX=hQq;CUnOVt1Q)#O$L>uL
+2cbx25RfUPjoczcf}qSQXWC68OZygi$Em<$+`;TS1sR^bl8<IA7j6)2V1#hvz7cO+?<A+8OtyepBBp|
+#K)sKm=9*i~yAgIz;l(WnGY4y|*v}&8O$kzB;jltaV_4!8@TLG>iiAModo3+CW1XnVnQCm^*dxe4V8t
+GkEXfwZfFopz`8}vr=+w@1&RdMl)G_pfi;NvI*`F=Q{v+J?Fjb|P$aCzM;lo8^Uhet9_(2FNQ!95A3a
+TDC-bF`q%RlEr6my*hLcC=HQ*_=)Ju&?(haq$XxbhCw`V!Hmj`1In31a*&hmPm!0q=eEHt-<Q{>Xc-{
+3GL*I|m(g%8Gct_I1vSYe$=nSb+J#ixqNPl=!!u7e4DIK$tJGPQHkPIrdP`Gy^9{xJjj)>Q4)ieo0cP
+)28Hl0v(l;+9wsSCi*gO(!u8267J;%8~x<!x}#WPVAjdip5~?}n8_Zzz76~3<Kx4MJvufa4V5MQj=l0
+yX1;66amh5!(Uz3Q@uVyUds{9mdi4WaX|hn8SnhK_SQ5i+7s(<DBq$`RRAm%Y&`qOy3~x`ia5fyc%0s
+i;z_a1WD9uvgyuizjJ>!QSs<Zio=iOGM<z9p~(?yB(2$9UygLY(@0R4zQ=K5&Mfa7e#jZCS07n2U$$F
+rVgQ>!&8uLV&F$kkgfmbT%}T!bDIbOQW_1Y98NgtW+ohK<A#^jH-gvnN2WsgFJI2UkPhqe7}As0g|>m
+qCL|utk5E8N#wOG=n<`?x5nU(7^G)p%E)01AyM1XIY2t8Ah`jwG*Hp%-)TGJn^|5bSa>BPB_H^in~;4
+P=h`=LY%dbJM7WRC>F1dLuBiV(a6_g`iYKQC-#r%)D7b9Ejp!h+`UDUtc-^r(HVBd<Im`nDslG~9h*E
+3&*)Ukarfps+e{J;nO;Z8JA?WyB#r;!H0T8_PBr3E7AizpPbC1Nk;*1>N2XFU5%po*S8m1R2plSfp6V
+eDOlOxVY3B|{;-~rH-m4ETdSFlP3LunTAs1YA3jX`!KYqErdH!kXTnFW#X?8oV<-bv_$tqW?GxAZZo|
+x9qjSh|HN0G9}L-Gc}Z{ecfW}^iPVpNJtCwLwvXnKqk8c`b}ooyP6u(2=*1az%H+BYf6;N^KxZ=*5h0
+Ba+*vU17M9raKeZbr!Gfnm!dRBX9No=niNSDSIKTkHAM=+OI!<@kMCGe5g#49KLxdGEj!;%Pe?dBBiE
+cGYf!itsd-jYA_@WGX5a$Oq1dPQYD>q53bVS}zcMKR3pr{?z!TW5HJQy11Cv0*B7$_OJ;$5+N10dE;`
+jB#)iUW=267WJ3}Oh0w)3*0Su3CZ<Su#GD}+FRs}Mo||Yefw5fM3&gxM35B0?xo$88FYAKiI7jEs^6-
+t~;p~#fw7;}07w0B$hLx`uI=7bg^fWjYwQpek=_SMT^+wWqOnXD?KWE`;@FPAXT?%pIkBqJJho^^@rh
+|!{W1~2hL!d$T{V?-|KoE_cJ$Ap*$T8!=99RZ5MaLd>BokVrk&hh7P*ZeF{Wv_MBc{gwF;4R?!;k6(s
+uZHJp=0;kmH<Pmg|lbU>C@daC#W-ag6@H0Hcyfr4lPMCUz0^@gqR(UlQ?~+6!O}{43PPIff|Kwo_<%l
+%&xBH%h`VcP)h>@6aWAK2ml;P_Ev3u%=rHc0015#000~S003}la4%nWWo~3|axZdeV`wj5Uu|J&ZeL$
+6aCxm+>u(#!5&zD=Vsi<aqkKMzv}M@@Siq_CP+-TdrN$p5;<CJ3l55>7cYCJTAV6fLZIHNVn}>rUPV>
+b{k-%vRGy$B#?H?01MpD_xztEZ8dy|x$wt{Ki?#|53&f_<;OYVh1B#0fjK@?Bo23KPqGzL-N5y3r1(z
+!4SY!=5B&Nb9>$V1b*#(XD;%!u2gjI<x@&L=SCi!!pG;b0-59|tZgNafJT9xjH0!;?Xtje;aJ$Yo$<5
+$(Hda}u&_e3`|GD;B)LqtT8NjQ#8t7t-+}az^7M$`!hxh92`5$qyqY#3ZA?Bu5KKV>U!V8SRD|E+Q6_
+!Y&&)SVTDS1>Mal<!Aw^K+9#6n>biR$aZrzH{rR_XxJ`|W97@Ig56Goz@Nhg#IlgXN*!rgx?I7(n7IR
+kqzj$Gw}EnMr{-kI*CfY(TJdTp7dL>20z3O8qW+NSD+XC@7ONS>Zb6a02O?nC8goaCYUKDgB3)ovCNs
+1%lrB)Nm@RUQ==uaWR-0rACf1rWlu^qdL-_Ptz>=k$IdUPV0xKH!^^rkbgS5<*IlOJ)g-^eI2ruXWF9
+sc2D+|Q*hbjZR%3&sYS+Ykh(7L_4iW+85{q$*8%pxJ}TuA=ZZ!Z!u;mmciVAr*8ZoaM=Dxh^KzbpSYG
+M&5Wce5&~BE@vM&-7-a9)xM~9ukCF8gtqsgkdT7i@<^WP9nd&rnijQ@B!T#sF+80m?c;&ESpA-F6GL^
+QxY{zdzJ}8L2L$WM2x6_O?e<sL=<>o*-yMai%2ja14cms7Ms8-MW~$aDyil$;*K6t$Kn343yQ&`#hfA
+QZbk`f77V7~Lb7R>5zsTKC6Oiwfvk2D&)2nQ)H+zr53F%SLn+T7SCd%q!KAC%U<ek$x`eH+)(^m25p%
+TW0*UAH4T9mc)RoflR%J(pC!yMOUkH3=<TGqHq`uRAhPrWSHXa3IYs4tnbMBHfM{OZDQ)#|gS4rw01>
+-^`y%M6@H@Ds)TXN^ah%vu+@_3)8MR#ktx9w|-$op=>dZ!<i+M`3THtnGcREFxUQ-B8^cU>@M^KkA7b
+KPLvI|mU(z-1oyVatcJ*c0ma&L$%8z*}~T3XoFQSQMl8a=vC^(X3GD&CHs$KtMxkk}B4WvYF>n=5jTO
+9Kce{oONA7{g|uRgM^k^_wYa1mqE51?)BiK23$~=+dcKQwVV!NA;AnpVCm&giUXpQ@35Zw5+mqDh9k8
+SF*E_|rQdQAB9g$+2Q5IvPEY<1E2dU41Z<ain1AQx0}tcGBaXCe3}HY$CKPNjTOi~R>hO@qHsm#7E*B
+>GdBWqD6NdE;h?5wg&LJ@kIlLPRCjcS`?7;SfgJ?<sRWMxx6Ivh!`ATErCN?r&LxBWw2*#iQpcwZOfS
+5v4>u{I>_qjBTnU&2Ia8qJ8vor%aGSOxTX55X<hb}2fVB@lZD4<5>npO(Exjc1%QfY7`Tf~Q>(z`HGk
+K`F7u3NB35G*6gqQFL3rLdMAZxvvWLRDdGYU`^~h^Ac$B8MPE6Kvv4^1M=uY$;4a+o|A9fj}8XO-US*
+TZS=#NPq};dbl49U_c11iV-DC)I4d_F`-nf?Z69Z#N)u%i?Y}1%ry7KV!OUrucNtL^Rh8p1?nJQ6qKx
+x6hT|{Q&zKD;8j_$x~;>=+J}>&*Gv1Z?6aUx`wYo;I3S*lIrX=F7kb_VD#NxPCm}ZOWr*wyTspL%Kep
+@<0Dgy%@4oo>+rPha|J^U{-`M-t-Oume{LK&dZrp$WV|e)X?Hk{J^eH^xzgu^HxVN|M7Xq$QuoVcH?t
+ePHetWuq6Cd_Jo9=x9V!r+0AK!iUr|D~ZDCyQ6_5A%u@1*m4f0^$8dV2ly>GiLt`)^FIzdgPF)pY;E>
+Ha+&?!7<V`((QJ`gHG~)4e~I-x&vq7+E_IUa0zm55FV_AKrtngS$5lKDu-8$(@5Y-z5)j|KZ<Xeg5F)
+mj+PWJNVmOcq9jZ{T+Gu-YvC29{%dL58k}}@XfmiAKxPn{`}g54}Smfy-yF`dgI`&+f{g031+cf>V-0
+@N(Qf1VeFqUTT-iIw-$5Bw8eY<z8yGF7kKZu3&jI6tfwSzE%$r!yppG3TK6l3NJ2<aRlMLTe~f4)w;q
+GE>CiC5*0w{TPbHl`qY-}5VFE`{X7#~n4o)Oc8MTEtq+O7DLFiVup4uZFE$Yn{Hdf^{lr7^C%^Rp<sW
+RT((tJoxP)LK?t@R2T%v<=F8|xP?oqxIvtraaRIhms0Iq0YBm806z9w|s-<R*5{^|Ej{XDNPUKXoYz9
+4NQYKar;ruv|G`Q?W=_nynY5e4)~lKZ-d@x@2Jtts1#F7;u}->XFj?e^sf1*g0mCHk@YLE3GqS;Mx#0
+B3EbxvAa29<T8&Lo`N=ZCS&UEU_mcvpJ=bG8Y?R+_^HgFfcaMYl+kLP)_#mq7w80zv{I?lWr2{z8<4J
+$m>qJK<SN2b5KSIUqcbOr)@sW*adPcPX@q8KDUH_Vnu$Cen&idx^>t;h^E4LZdFJq{R;SwYv{G&J6QI
+?Jwy}ERjB)z(8Nex={LyA>oiX5ZX1*__l3>JjM8OW?B<dQD0Kftdj@CY{M4|RXt2N(@En}s<W~`h%X`
+EVHs{(ip-6US&L8GF4e(ZD*)1G|t$!&RP=g<&YE|^ZgMj^8y_SS_e&|8~5*?JV?1cZU%0@om$y<UE*m
+jr@I+=k>y2Sgw_8FMj$0hTve1MpQuzA8V}OBK}HK{Fhsx}?}0O^U_`TKsD~NMc0~<UV$#B?+0^Y!>2G
+Vh}3r0D9{88ghs#DN%5=D2XYE)n!c9R#jfVSgT@Lv8x+|DjB#yxkTNnS`HNySYIi8J_rI0LZ;Gpo-kV
+{Ar2~Yb9&=TG;zsU5i#ym4v;y)i!L0pJRXtfpacfK&-{5*o1<hPX~tC4)=T|xsa|Om!kXKlww{_yZ5?
+~hl;hRIkG%3uciSHU*t!U~aKhU5f3oc>E8#cyak8XNsmZRWsATCF@=#gBi5La`3CIiVH!O9{6sMOv9Q
+qJnSi=PErHW&9yXvxAFZt>Srs`QByO}R_SrGo)jmL{S`o>1qRe6a$LgW{K6iXTB60t0G{cTx~H5$jsb
+F$Nj;pr(Fa~nh1qXJFSAxldLWlKv2SyG37czOx#@Dh@{fxSasP6EM@`#g_Dthz1_x=zzHv&25sQJLQI
+LL;|-TJSY;Y-Y<wzE!=xl-_?HaT{_B)qAWAikb$U1#~uXO!|Pe@@x(@KTew!2Tp0jA>JYY+&V6c3;+|
+r+dj2-fQAVhHVZ<^fL}d}G&tV3`qX2VMY`ZK3y!1Qw=4*7@;GEJ9eU8F`vJW98jCWBRloCev)k5U4+9
+Q81`o^)0Z}|$zo?f22K;B^{i(X9n&~R?i&c<YziCzPeH?-ma)SiE&4>udm_{D4sXbCi6hlc8z+C>(OK
++AnHf3(<x!`67PnMJdb!3P6AOTM6zN70^LFBl41O8Odg5qW3eSNcH5fitM5MMSx<9|}_zgMZ`o`~5&R
+6Y{hvoA|cfwKcmonj%rplG~Ov(KwuOz^VbQKoNd&Bd$*L*c7tc0s)0CphXeH~$3=2aAF(vuudt$nwB0
+bhzkRt2vLh+(y@q5w)iHNcQTnV<GkIEl~pK^~*|!w3Wy^WJK|u?nsC*?kq14q0LD8CLqzW$hmrlu2$0
+i5tM;WMpT>dxta(?Cto(^uIt&uWC)OW#Co-(gII}zvdb3UhRG^&g^^JZGBODg!u+ejgd{P-9-h~sR>+
+?{IMfw@E&(5iKG~MZ8?O$WSR>KFV|{-@wkmrWkH=<VFp~$p&GHC%un=8=U62d*vvM1nR^G><L6_bD&5
+4$U3$v%!y2C1#GwOb=;gL$p+?Fz(0Hj2<jmU&mCbNV2<%_>~;oQ^bs*BkU@#nI3t&xyFMs?u;f<GC-V
+SxHOv1~)3&qbdFiBNvi>Mx7{IIQdxF7wWkhw+)71OH|&gHyNs2T)4`1QY-O00;maO7>RY!+;hy3IG6b
+CjbB-0001RX>c!Jc4cm4Z*nhkX=7+FUt?u#Y+rY2WOQhAE^v8WnoY~5IT3~T{VN`DqtHseE46STDk#i
+O!G%cEGK~&8ql_&w|K2*M?w&U%Lr)dCk~`n2RONYp^7_?(KmY6Xw@=@F`u^kRPhY?O`ortnkN^1e;q#
+~Ozy0RBkN^Dezi+<&{P+L-;@>~Kd-v<#e)ZLdKmGnUfBfAaUcY?(`Q0o2`)PUq!oQ!r&t!f7>hb^2>y
+Mz>`&XTQGF$uoYnz|n)j6YFUG;>c0gfdlhgCq+lGX`_!bNBbolxqWv!R!(op4n&w7N93#s-9ZgEnIhL
+N0}9$d+`;mJ#ab#?LW?H@FKvr##?5$-Sf@pXicHovmQrTj^8an1DkeS`XP3vgB5{6PiK?bSYUoTCe@=
+d~2AH*0iC<hI%<i)H)U-<p~GjP>4Fa>F2uw?y8Utxxi7-&?wTS(K}#Q=q%|?A%;22c>*HogfjNoG09W
+*Qkz(~ln2BSXu1{KYWSS;gp*Ll&g~jfKkqErW#QIf$st`@hG8yUqlFWc@_=0T<<cd?xk!1yiTSi?3h}
+uu{d`SA*`Kx-pzgX|F(JE7g+{0)u{Tnl&<SOYHn+{*vcWbscFH&C1tq=6BzwjFbnTK4v`+aW?4`u~q&
+#4Q?W8;)mLuf}7opTy`+(`~3I{%~V<=pNE)c5|Qo2-O8A3{z8pfXTfLO<rC+vh>AnT+&;UYAFj#+9h{
+p<}es6gzEkka{%B?~DNGD@sY$^+sAg_PC@CuGQ`?L5UPPlztfp^!6A`34tEO3D+W^>vlRZP=F>fiQBI
+d6O%$^M2{3JH$5OmRZ^?x#e(mZtSkxJCc*|Drtl=A&#RRb1ak0o2a{X$#FG@lsX+JuDjUeNJgDun9tP
+=3%vomzzW+nbbAkO?@?zJh<=9Dl33iKdwx_*UC1dARxac@qS0XCN2?04mr|aPC1u-0(g;l;`$_o*JDi
+g-28`Q}(AjyP=MqoHH5zgY#H3A^{W%>6FyuK)tH7Xz>;kcxAzdIo3~2&ks8gQM0p%30im6L^K<xQd<-
+{%8gplWm;);tNrhJ0~S6;}W5Dg6(`x@}pQl8KVrArGJ#9CWQE;vOg-=N|Araa*Q)P`)b<kXTgOAdwTk
+~)xa31j9>yJYN=X_q!9WXoN=9NTs2CAAz)q&y*3)5TCP9_pn>JCd95Y{*KDsk0(R)e06OWEBX@V7iyA
+Y?j<w5(Bg%XVZAcr99yvyh=Ku3xuJtDksi(s6$H0)(D%Fq~{q@#@^ZaF6JVV=+Y2h(RdS?-bXgr`Vhk
+s$wer$v<TH(i{vCcJHHzabx0G49TIX2#5KB`*yPP_?;&30cAWH(r(N;_$G~Yx-e84E54ld*P-n^$cEW
+x_gQFW#KBtoz(oeWq=SJXmKp2*k2Q)%c2xFD<fbc^?3Un+)$Str9z$SHiCxkp84noQU;<`_HKx0X(3O
+iv}xCymOI6)~-=!7~VXFvVye2sMs`lu7b(|eTQmbhKm61!ps@~IA7;U7V1Pii(<uO=&2@KJBLGVq03i
+m|yLbz<z#M;&+;;wi_oM(}TZsu=RFP-*Q$nU?lK>`ewACjx_SG?Q;QHa=#swIRcaC^_-&iaDItweHs8
+X+X(?LZk=rELs}2uSUEpbJE6O2ZtC|q*;0n?a9PB4CPfZCpKb5S%yfn-=-_y=(g4vq;_!Uob0RghLx@
+EVk;sIe+6#Yxnq$|yqn-v=!LDSzS)BD4JFZ7q;Ww*iFeqn)9Ewy<$6J-j}kl*j|+QZSB#wiwG`7QOm*
+N^Sa*{h8|lu{ZD`#L&Bhg>jo3Xb-HVp)ojvJ8>+XxA>~f?c?OBQID7k$eC3q#)CP$8PT>kLzti%=b<p
+gS7m=ilqmtk5@tR0-V&K`AQX9uTi-D_~ZmxdsHW$AU7#!WK1743<Yo>(if+&)(8g|l?k!SnGEO8adqv
+Cc_c=UB^Bf_LJrm`$cSF?Q9QdRecYUT*|3rwNNRqk~j$zT@Q05=x#5BaN#O>a=W;#wbH++%ow<vSuwy
+N>_{{RJ(9X+^gV*OL9$mbO)Y=9h~(vN^9|4KI(`KXs91`;L(VO#Dx)8Aex4f!S4zm3aVXr6U&B(Gy{s
+Q!7b9BSnKZaPN1|Wjy(w_A%xQngi?o}$2F8Zc*kzXh4ZKr?~D(0IL;TqQ1YI!(s_d#7q-M2&g`svyM`
+&=SlYYR?b$(%h2uCD#uXa)Mw;GrD2+_`UJj-44g=j#>h(u@CKeYztUSVwQoUbzC0-Zai6tN@t*~?}TD
+rsCden)HO<u7|p=%GNp%x?IP)nz3tdV#Ko>*Hbt$WtQRXb>jP2;OL#EILu@Jf7DGTCp9t`Q<~zW24nn
+^9sa!IoJ2y|eBuk4RyUvCFLLZyjNuIfJ$848r+LJQR1vtF>z-3^qgQC@Y_i9(Cf*sI^Hz7FR-N>E5+;
+A1vK9?vC_Ge3j0KxL<?kB@A`N)ObD%wXV`DOY0u2hI1LJYbErYpkx^;gAu58;hk7Yw>-t|I>oJGZA0m
+B8qFotRE+)ps1rNuZeqeBJre8oX^k@&YA9Y=dT9swgBa9R$<9i)mZonXN;h)LwQTB~#cWT$S=iLNEk~
+(8v><JXWzkxmhV;Kr%y*k~!%w_h;(p<oSk|%^IGJ`i!$|MM`mRzMA6E275~O=#SIk3_>cBjZQ1il`SS
+#Ue`=|q_dF*N)aa|&W549A-rwFyrMT=VqJ$uxNvF)L@;L1uuN!UIr=KoP=Y1~6l@<uQkEOZ#GuJKy{{
+sLa=lve@7+dVUuJXVBRn`i;Cw7fVVif;Rfrmru2JQ=fI8I0}2CQgmw`^HLBOB5QnC&N(aE84E>$q;v+
+;7f-7-GR4SGC&vi77;pMGoa-s{Fa6jT2?3ke@KRwunb_;%+SAYXwRQ0JX$iG0d>AXoEdzLfR@{nZviF
+W2==-&7;QH%I*tIA89MToKVnj^JL9QJ*CVc@4BdMbN37yE{CuLg{){3_War3dy&f25<4%Ou*$pp`15A
+BB8`RBdPkm-|W3N(chGoX}Fk$0)nHYYx!7u<?eue?a?neA|f3fzH;aA3fs@hjZz95CRt5^Ib58AKBEq
+96SrH?nZ`6nfzuLl|PXB_#%^qDbhX6P9V@QlOvHHp5zWL%BA=Y!4l4hS%wjB#ghGi<K?nZYO$Pe4^iz
+I(o(?cT?okyZ8SSBCA(P<z$($P*QMT^X%pM!O!QW*(e<KX+{!Njz1Rt8uIAdBeKeu%`_=znU?hjBDgJ
+vhn;|i!)<BZQQf_tcMqUDr*_nh3?nepZ6Sx_u*GY?h+qGr^NY}G|<->48U>t)c4%x`Il6ouQd;_o{Xz
+kE4Pm?yBc3<8JtfjX9gn;>Z>YCv*dQYHTrV~-Sm|-`~p6~Mjwid0|0fe#$Th4-#m<77VeubVcTEc{U1
+<E0|XQR000O897^_9e=hETEO7t;%Oe5+AOHXWaA|NaUv_0~WN&gWa%p2|FJEPCZ)#~@V{c?-b1rasoW
+0v}966FG_`Y8;XU1%7W^C0~-96LYvu69a54&b-`?PPzEG#k;nHgeaL{?l#CHF;lswCb?i8o!UN+eU%{
+YHtBNVVCiKVg5s^d~G30l*y*4n**jnW|LqOCTK%hr<E5{~!PN|MP$Spa1Z`|HJ?Hzx)IL=O2HcX5KjT
+yUZK0o*(|>|Mn06`1dCV3;+1Pmf$}`Jpz13f&Z9L;GY!O?|7X&%i_rUmrfYRJujP#*}s-px0f|mHuBP
+75S8sKQ{8SSzV%ik^#?;g3ewD%^b3dl&kGF>I~?jG&^rJPSfW8k{Lf!CXv861Kk`z46l3BOjS=<YB*C
+B~01e_0Lp~x%9)t$$HNY}I>1O<^2>J;@gF)_l|Lk@Aq?7kB(o2o>W9}zGo(kCc&bn?+28@$OnC3G811
+1UXK--9!GJ6l8yn_L!8jyBblm>jTf;8m9K{(GePM&6o9~zv$8bAZ|MT6#9((!}K#t7@N>iFFm&rgzgu
+7qyxXoy39-U0d0ANi@|JjG+oL5Uwk2=od-(IE7DEFB`~5kPr=dogCJmAb=1E<_CajzEJTA0g0l1PbOE
+g22z`LxsEe1^~$j6lID>u`|qJx=gXCJ8>Ay2AJq0fKsj$Tmy$JnP-D|7BouW9RgmK&iMxH6kz!*%S;s
+!2;Ve9;?D;mf_w%@kOk?`3!+}YCuZDb{NEW%cypXgB*kl^!;)e)NCtt@OC|Vkc;a-DJYoU*>IV(U!-1
+a|0s*Q#nc*_<`hFTC_zMKjd1nzwPxfvoRa2V6H4TX43P?}mu0QI;J>8YJSRK2<V8x1N;TaxmZpM7A2G
+8(F2}m-j2<A1Ou^gkzlF~ffgT^uQW?9l>i0L;3<)$-EqLK=J85d)xBL*#E8CN0v%_%l@U4Jt2tHbpc&
+l7HGgdOqxerco=HqJX?&_&&O0k~Y%xzdjK1Om(Z+z`XiSGxEG&*JVd2=PyRhX4^4=m!8Kd?Di2#ME$s
+b5_U65+>O%-vq@7#$%RbRXZwJ9D|Z{<J9|?8ODE8H2BwwsGb=E7>Dtw6X4!{1lTA}Vk}|MnV7F(-X%{
+=$9aF2OAZU-WfhH2gLLSp_$x<9qi2X7z6Cg6y1fL}y=QpVcazx9boXBwAXtf>;f17|C;o3!KSnTZf4Y
++~*xqM`PR%nuteBy;u-)H2X3XoIU)>32;~>G3&=b1HqLH7>AYVfNz+S+OrN^yE*YGv85PO#cZWglu!L
+$wU#iJks(H!A1Qm~r-AK^h}+<(K1<E{pDbG}3+XhLYEVS~vyLjc`X7IKFuoJDjec<M8;CMuO(`S{=e-
+yeSXf&K8qpZ=`>_6Pm9|ImM9b-X|KHB0W&aQhzc+0I?3h$%_D#1@15YJ4u?xviCirF<#{7^Ig}ZiRw)
+Y{2v~$nqo}3tN>(fwrp8v6l7u<TVZTh6efJjF3Y`>tA4{==({`2n0QD{orzd+TTEXgv`PVtb_eTSZf6
+Nj5-^2heCp|F2BT9QX-7wa1yap%jB5ANx80a^9^gS^dF`5)aV1hqb2teo7;hp4AM)i(E}zlx?DHzLSx
+LAZ;byOKnY(dCP?i8G&FyyUMU9ww`n1FwGmKDaKHyuOYkL@pnzb(zr^bS2cjkRCANOtXYa8v&c~SRF@
+laz`&ZPSv5_BQmR|tKrJu41g1rP-WsZC>A(uKqn)*3HI0b}>DKc#uhkl@~(<|JQA@lk6kFTxWUL5&hR
+pDRZu^q-yj~iwT`+#5rZ$|tp^%D=TuCMT%8RikUq7wwt0t<TPT-?-vE<>Xxd>ifE7mg$Xd_aI0&w|%@
+K!Zd(&abh8@b({3`zL6xc0lVWmlpHlzBe*Bz6WsPvk*bFz6F^dVvko3$Ys8hfz{#-=62a1tIuqGHyT;
+WJipsz<IL}brcL{4t&TY!^Oc6L$=pN1sCQ0ksC*YR;M*sY<7y49>!+D=FIL{v!CWsAKg+}7n<?V<x4T
+<4>|T&|<2=gDzJ00V#bGFQae280EsQ%K8SWYKy|c+{w}#EFVFl+}4QCWb*)W`V{;1x&&o%5Q_GW$Idr
+wTvV*)dC_V!bag0E|l*N+p9mvWPkrY6DH8o}64IpV<MqtL5x|5!)n-W=~sKTu|L<!K!!iHAWa$e1~4@
+4T;JCj4K?Y!$DrBPr`9EHhMNhd@eZdACS0U9V$L_--pK1;zOGF=BGX*nC^VCC5selglgtYyAcrfXi{x
+({uj~Uj1kMd4FbzVp?ypLpsBv3El>3hBE=*WBJ-xzr}0YOq|BE$|*j>c6BD7;}#y#=rv(xk_;yEm2T+
+8CiL~@;T>M!`Amfn!aM9BhOFa9+A9#CDS+Z~;a`N7G|q-GLe?fG3_2)s_YT|PP^|AIr)AVO!N}hMz@7
+e#MQO$Y+^g4skPUMbKYWL+ZJ1wSTuJg|fS`K*jJQ(dwFT`x9%YWgddNL}k4I(1J&J*!cD1MS9?M=h2X
+g^}oMOl%HF$nUuwF2${k8XaY&Z<_dxzRH%<KyQ629pR!^*1v9(!9HC*v;Nk2yooPXNui2kDyv_-sOh9
+5Y7Joy1wDxPCYK#jXV17!m2M_bA}oNxZVZz$@e^4twz|?#dB>BHv*73_%8QX#9W=2*!1b4H8WG97DND
+;!7KXo&Yq7yT&IE0W>c>Xj7)zHjI+=cV0L2mDu(_)gfMwZ&kgN@7g_Xub4vQ#+qQ`g~4E$k=Wk|>=Ek
+)`RJ1M3*YTD_79y}iAZ!9aPHD_74-h4lk=Uzzan|*QIFW1={nxmkbwz!paK3UfE~;SJT?*6*&G2r!)M
+0obff?r1E3lV`+#Sk=w8<k4KwipE1*D_XFl>VKVWqb0fNNm`w0Ym4Zwj~)e69K17LjbC4jWveZUhkij
+#gE&X`dvf$;)iWJB)e!%qFJAqW8$`^u4sw?;l;Rxs|IKS3YSCN-Wh2W<-hhPq>Gi<M?_MyxI38KE#qE
+iF*LRZ$&tp&<BfA+Ueql%^nY^(=^^|7L`M_B6n8J_3D%?a4<xapLhX$h$*%+O($^+p#eKx3v7m{tP~(
+JH~4rpBs8pdW;t{4q&NRL3}FSaEvV`_r>_`2SE-2GR}QZOcY~#e2mq4T+WgSf@ukiS%N#KX9*X8h}H@
+x8iDoNH|ARrb+ontjak<Zl4^MS7_S@S7)_yLYz@YIj^qPvNRIKcH_k=aSOijI1l9)VM;~GypRjZiF~E
+ARf5ww3$<x$;=-JMvU(~}8Jz~jkM>uBo84E0pxvpVNd<YP88*+PFL;OLIW$0LQ6(Ddldx|w7^-CiXDM
+6fIy-meID_$X&ZxJBUAS~a)1_5J}GqyngMxi?lLqYW2L1h2bshx_%KLh-{7x01cVO2Z9D#Ewa$vBYy`
+3h>y+J<}o{72oU|Mus9uZMe6;V)_ZKEbns`$`={8DYHHq&s9`sHfoxULeyzI9VRwU#K5nz~2Ep8u)x-
+Vc<&y%(yObFP23J4w4JG$2en1?Jb6(WAqce@}}ZgCazimfieY@5jrYA!Sk{R!OGJw3ID4xUIknRPQ8C
+FL$-V?67}YS?y&OFmxd?{%<3Bb*#xIK>{?F@>M@*_KQ{nL;PG$H;B6GhDf^uW6=lQUjzTt47I<om5l7
+)8%pxp~R~S0OjYP_SYQ$y(e4_OMBZYa_*vUP^z;dgCyp0zaIu=^QM66Rd-eHWFvG*8pHi*RWB*!eH!f
+18)W`5Go@*-?gY-Th0ySG5KDpEcI05@&^2<s~h(5$%cQUql$7glg$=&g>Nq;uk!9afnW>@%iwtY?sc0
+iO%9`O;gJ;Ah4_OcFz3!HoU(H0IW4^xF~d*f{y^Rn!f}_y_1!EW4DjD<$AiJKR}3HkOS?8sG<WT1a2;
+GL-q31H<3=f`2}5o=1z`7yRop;lj(cM&Dz~hCUY87yPTUfN$0=2|tA)@H^=IAV%#kp?!vd*YgF>2o9P
+EdCe*Bd<%XT-*4h>Ynza9r3iYy82K#j_{KNCAS59YzPNeaJQ`v~+IVDq`A!Ydd;m}~qas;{H*l-CFH{
+lsdkhy-llwj5*xIx{U+|pBa<0BuB6{)6f5-QI-1vkO5s5Tee8nFt5Um$JwEfM;|IPF_bhwbaSK!%v#R
+Hblh|53>fwauH$V4<#te_qn1$<AhC;cIwKN63x#e-gqPkyEqjHnEDqi=nvU<mucFoHI=Tz!!z`xVc_e
+7?hsS@9KX{%pku(~<63KgzkaLW2AXpsYB8?gq+&6>u#Xz5=p&ZZLfW)Z&;8SQhCMuy6QRiXoH^$C7HB
+^Ys$n;B7!#x9)*}x4{{Pfl$qU&b1!<lG^sqiD{jPdw@e<-}ZZsr~ibFw6Xk-f89Jj=lm;H()nQ2@jG)
+2!QdWU$L}i7bPAUPdqb86v*JvJYv({x9>EQ{-Y7_m+jo38W>}_N+b4jKhceJKT{9X<Pj|Y8J>3$IbUX
+{hZziI{yDiYaljwH#rxZSksTWV56;}qb#2@KE!R{{_8YE+G8Vbtuhj*&YVyy{gl^44AvIg%lzFp*IO@
+4Y0T{iWT5qG@fZgCUjd<AZ)a@VF)-q1MT-GbIY>CW1j(I^g#gyu;gh-}o!LpbK&g|SpOR{L?Bb+}^7i
+2}cFG#<uEg;(I(Wz-#(w>i#tH=uFA5_tqt60HA<V9CVm`>G4uKi451_Y;O5=c`QE+Fub;9;8EV!4M0$
+@f%4cU44j}SQPofMU>1o(5=`jLCiNf@J;T!sDSD=2%md)U2%ZOzZ%AgIzryv!wBLUG#@1$R9=Q_tHm9
+XYM<dsEO%^>tj-bJyxfq_q(fi&E_+`wa1?j+6*Ht2vvJq&$p!oXM)-=ve6GidTM_wN);{4jPYj?OxwX
+?egbsI|;yI6y>2TC3p7;pc74$mAv%gMb{}A;XETOMcYzGSTPMqlj<|UI;cNlc#rLEO{148!yQ%yp2mp
+|2H<C4m!npB+f_*9dJMG~KClE5>17xC!M6v4zG>ai={I1a>Z@qyQi=ag|;XoE}3Y{8V7gPi`k3#Kd`^
+e!1Mm@;nWV(&~Vx!J~K!5kBsLCE^jhOOOcgG&qkP8-1&<n(X7(?;+Gy-V<S+6W$Vv3I6X@Q4k`pi%IN
+__ieYsTDFU`k&f}zNDvr?oVxGUovnB|ED&>H`v&_(<pt+hvd*G{(LO4Z#QGog1_BH@SK?bnYY_Wom0C
++e!Gpxfrq^#jq=t^NOCM}wWB*gjzdo${T=>-T1T9@LSI1-VYEAO@CG#wc)N%*2XYU$cM}0~;Y)d)gsI
+#02M+*R_^@6ojy6lD3Bx4*;d|T$*W}io{rCJ2Km5?EVa&l<)!Gq>!~Hui9mZ-KdGr>;^!thBJ4SQHJ%
+}r%ds+U!49a}4VReU0ZUDB|04LJdE0-2g>t*TaJ-?3{rBAW~k7|m0B-~GxF7RCh=x|?s94ilJ9d$lsY
+A0~Mi<C0uJ4Cr_`f9eKjl)%dNaRE01!Ti4@5n*FhMM`7MS7&0`n^bp`Q2eDnS8|cK|jM-d4NzxLZ^`<
+KMKU-29HhDU~OMR*a>pQSHEFEkGtt(mZWMhr<*jC-uG@A2E-(wcc`0&(J(1oJK;^kP>^)?51u*+Ns==
+}QrHi1dsmL^Iv55fC*R%*G;#eJ<?@o#5@-xly0W>6+vNC#zIq$Cc^`v^@z?`WI5+MvZh6EUlHY*`dTf
+>@!q8~gRL36qmU`0FJ1Cgx!Hm2}&Mg5v2Ncg(dS2I;%gppwfW$+8o=dWvv`?Wuk>XfAL~Yry=kvXTKc
+lva`uboe6ps<RLDE%r?S%>IhrSf#%10A|hU3A$2?~n~i>Y|sS#o{3XCg>_Nk`&37Q%y@z8KHII5jb%p
+i@Rg*3I@B>j%#(2nEOpAa25VgmKinH1vanVLSe=w9)4~*Z=Ee#fD2S^zXzxZADJ6u!8<uD|**rFSvZa
+2p4;2PA|ZQWN_BV09(bicMcSX$X!$pNxR4z1>AzzA=hSVTAU;u_As>eUbP9lz;2<x4Gdana07?dI^2#
+=3oUNN$gRf}7HO(ZOcwE&&h-Pe&a8qX8|GrUh@~5~v26grJaZd$Y=H2ZxMM)T^!@$G6ZF<uU8-5#g0_
++LjMiZx(ZBH!y{C?6;LYIXgKE2%`5hJUT*E-sxC@OUz*Vlh<5=8C8hG7UabAK66z4zY%Jo}ch2}ZWH=
+hZvpa<b|YDFJw2l?PB2J_F!br3w__)76)KwN>4B;c{eDrSkqXbHF-8a5}k#oG=I8xy<3ZHI<Ui5sGAh
+lUM_t--cK!)8F*fa%ZBsCPn3k8xv~UFtK=Rf%!`9Sx<g?V4uUB%p89nikola9!UujWJ1Q|KO>UkR(Ck
+)KS_gl1<Q)IzP))%7C@E7BH<|Z%x^m6tq6PHHBxAxYX{gDLs<V{>f7}B}s$j$G7{QpK<q22e=l0LSWY
+K^39?&45tP_ZI$1nR?$nt(}RFbacy0_Bse%k?K3Pg?CU0iDbqgvf*R){!&E=nH(`j^{;~-&j5W%~ASc
+)=xX*bI_DXXZrCE}9GktY&1q^y##0@f-)VsF;R$NMzB8Aw9I>OyuL``0r#d7blyMo#?j}KlN@U2k}=T
+B?<7$YT74ge+7hlSHSW@}%)6+A>49J-n6;Uc6J@Iw~$)PlBg8?_5PL-(imcPJQbpLXyZGtg;cv4ba=f
+$y?SJ9u_cRQ8XZI><-@Naf&<R9I~F1#VQwtQ()r)^gtVVQai`f)K`f1z5Qc%~4NHfctN7s~ps&m#8rk
+N0f1_;%%r;QLGNDQJ#&2V+SGHSa01hfJMMjc66Z*@p{25H%97McI!GqiSv|&;sjV(mF1ribj)W0Uj{}
+>WtUeFFi`=v10)6XL=-YdsKC_fJJf^&L$&sD05WblQgQX}vT{YXztEU-$)t!xsY74T74FVP^6L8rZj`
+_1`5J0WGOs6IDEg@$;f<e6co0?KcWm&oWBOj-I`n+V#AC!c)>HRGrdJV+dw#<IMgfRx2%5mP`lWTFed
+3wU_X&cgsW<lLWTuxV7?4G|T4!Lq#9^!I_v$8URuSLny3t67=++H`QsB{nvUS6f6o{^X+`3^xFuI-nD
+TPmBo*9@4UkkfQoWg+bBDn_RQLaM3tLUf3d}Z~s;$gKMsuu`2PQ~3HIfw_p0whnm!%|aq%%&R*_yVaH
+l3g$&LB!N6ie<=<Q!K;$_Z4h5uH$yTtYu7H+gL_l$R?@C6eN{xrv?!INH0(2?_7lCCgi42nv{pAQRKz
+(#D+^M%koPDScEj;zTesk4W%8y6+@>?0@^8CF_g=saJhjihL(|Z_79#q2}zPOM8egLuW_DodgRFL0Y(
+sstBIb9_$q_&t%flW%#^`6xQ^gsG(sETaEL2Wb3t0<jmnB%6uV8yVe<w;OvQU|*t_4afJS~0>XVjG+>
+te`+QxGiK6l|#6a7U6-8`XKL_aOgWqA0S(Iz`0#w^l8T|9E(6uWKZO`h-FA#lOhT$~c%G*UbD#b*f2U
+0+!J_J09L-tp4BeB*t-^AxpbU2&)-d%dPFR(E5ywoVVAtvi!(VU~k0RpSIfV{P*f5K+G`f9Ebr`4r--
+R0p3BAPiFNg0CYsqcU!BzI_w5jde$+uW)nD-CmIjLh8`^Sq(T64oV4q0A4~I^|?_DJU9khzKelz9`(#
+yU=J`jPfg%`1gz{XcBd4~n~Refed+JB1BEtYpA9ocP|>F4vti2!GM7R7Y#1~<vHjDh&D10v8r3LE;?S
+FkVihr4-a|m~42Kox&6$4ZvjTR4+ZsM@iB4Iuw2MK3YBdP-OkaZJZ}E7dFOd8Xl>aQ}bFA3!=yh%H9)
+d<(AHhDBX3^YTBbCp`D$s|w(rZ?P^3<Sua(@13|G!RF)Cu|8GdsBq*H(|!FUo*8nXj-w@{*Qq^)+h3U
+OjFX5xJq^^zXw)Bk^S*_V6ldn<%+HSb|orWtrF2E7$r51WJnsJtH0cTm)YxDQ;WKk8D+%y@7tEvjW~o
+!VP6l?<iL9B7n%vq&%sERRrLEwu%&=KU%B<kh+{dS~lRqA_d|)ugVAT*aD_^?~e_OQlX&t)Q=5oQXz5
+e;U628geJ6q^3+X9(wx<3xMQF!$YK?ka+6fLm*=~i2&ivK!Zb{ZcPi#?bo;LrFarIGKxrm?G`#|Cg1Y
+Bj?wzRR;Q;nZ`54Zkr`J%kbQZEiT|Yk92WV2<uSh{82a6ae=9Svb9=<am^^;t<kwatBH*-u}?#z|ZvG
+d1o5kO>}n|SOB-v>u(W4n$i`3@D?Zm|0~7o?icORsTrJd$I)2YzRs6{)!N?ePOJNE2?Im5dg(CF%JCe
+T8c47if*t)2k)am<|iKPrpT2*A}zK{Jwc#Wd%UppqGpL?T{&S@dH5h1+GPC3j^+8Pdu@TO6O;H7og(V
+!bli1ybwYnO72RBK{xY;;2f<W>XfMkXXT;UYGi#_d4zy7;_aUDx}@1X0C>juVy}*f?jP3xq*1zmjExf
+DlD45h{#HkJ7@~sYyOqTLnNu4LiLH%KFYre(_Yc5BKdgd^dF*>V6&hRr88Aksvv3O_2@`{<Qadd}R?#
+5k+edMa(DYXy1Hx=^HsdP~dLP6cOnl_YJl_Ps{Jhfc7e*ug1Prmd3^xV+i&cF76KcXMKWgV&v_!my;y
+#~>Vyqt{@OY>;P^;(zDsSoTb7;$o=XAl9OG+ZC&Xll;60znYIbPLJ{j~z;W{S(E%#Np5?5n2;YcSNiq
+@^Qh*K^=5w9Q4AiW|-PT=pEEDHhQ3AO?ZAF&F_}E?|I&rdpoNY+$@OZayoXDClhB4^->wPi89~G00ZS
+{U{Zh*@DJ64$Y--e;)zI!X_8FNlM_+2?mDxD0>RcDt-EaUI%;H6dvA&w$T{Qtq*kQvNx+j7uwFVOCo|
+GTlI&SKTs~*;Vo!XTes_|iQcMR$2Lr0(fgz8*m?;x*H-L0wp$3<&ib^DP2!zlJdtWp=J)0ck^$0=f3e
+&J>LM@vf<bND#GAycIyEQs5HZo|+MGOp_|Zg2$Hnf=7mwxShX4HG2NNe72Ks^h{ig=Zi_fp_=m&cota
+X!J7S<Cv*5Jdlkb}6-;f+Ieq`0|=fa4*&W7|gUd>?A|<<JDyIs?g?!@jhZk5CgGAAe+MR@k>h#~&G*7
+51I6@kfSc0kWO-X&sxy1NGtC^e`^t#pe%ysy53d5U!|fXzMAGHCLAc$PLZ?p(1%NcA~UZV(Jm@s`lMU
+6aHw60{@tc<U|<n8ua_hIE;Jpo~=4IeS@IF9&*}H9HO8F68bSw6Yv^pDvp82jES&a-syxI2koV|o}rs
+laDRGDo3z6Ai@Q_BEcIprWtq3P4V2WMjf<HKXNueRObl@<RovX>{pxG`xBbq*nvF+62G?6&8^F?Ji1-
+L!1dG62CJ#sVUlE90n3s%4(EIo6SVG@Kj2Rr5?au^O9L4%}!F08bP^3yl9oi;(E+fiZ%pI+o`_BkG5!
+y8Fv+vxjV{t3ykGy^okGv>WKKS-NfmpocOTF0W;Qq@xCUMw#oxmEhWF&&D%1hs0Cy?T3pt8Sh@73VEA
+BMC(Aq=R|v4Tc5P>s`FqmedjyV$Umc(nc5#ip%9bQ!l@Y}^cVJNr`#pTs-^%+T+v`vTM3s5#_n7V>?d
+TmsSXi~@CeW9_-wS_JmsDxKbd!=*YCkH&RU4T2=BkxVU!B>!n6f6GUlpR@gPw+vizXe$w`RNV4$%BZc
+h+!AXmyD}V0_2bC-bxqeq+ky-E1CCmB+bYAOmNG<anmS?aPE~?-xluA}BdMB{?6M){(ncDzB-;OeyA+
+z_;g(8!`8cH1B(DakwU=L$6dU9zuEB~-rb*A(XB=US@-;aIzcj#!aBx#*U_3W4^05JgdLI52J}E?UYP
+no(=%AAD<obDt{ZepgL}3c1>-C-QfLkeU5vAVTkf~K}`4<c;Bz?YzN}RB;=MDLGM<tb7Sp%4ew)h?1I
+rZG~rUC26VNdxg8`ls>xKI8_Ia$k(4bV7=#kNj`fi_@q)^&Y04{)2ut_aVyNLixpSH8gr-Nf(eBirdS
+lQtS?;qI<ukT~2_J-m$oe7MBb)$)W|pEqsTG0+e#f=32VBA(#3;>nr{`e=P!I>0!>M}^0v%TEC|%goK
+|&lptOy6U)~I8qV2gP~-4zV`uv#NI*1%MXuGdpZo^s`BO`f|L(<W#9(f!I19)FZCFA+2je$Lj<}au9O
+5_HkLA9e@+5Pw{!iu;dUDMq<>fte4_~*ZfHUF-AQKu+^LI>qyWw5yX)};-<Cj~5Z7x&eNTCum8jcQ%P
+@(<yqXyYjc-9GYI4Z&TB(3iKkur^v!{c5eH92^e1Vz<Qt=jHwhJ53!?(U5J1K^d<GN$q`7+Q+Iqw)Zz
+6^ZFsO}i|y(lXC$4(t&Bms<RtPTneKjF49-_5JsU~4e7xiKm(D9l7bU!9|Uq@nVWk+_B^5z$AJERRIN
+7PvHV07gPwbkJ9x-dCHwvAP)g;2we{rpbANLB*CyB-@%*8nkrPfLBctn9=wO($_;BaxWH+o;MD<klgD
+5j6zxes*i5ULVtK;j~k{WPzNJRuxU@sLyQvyh`0yfcZ)lB)pSG$2yHIHLGp9Bt!%(7K?^XRISajUUiR
+>O4+bt5_ugT-xnBd|Rpt>uBPOaa=Cah|F4V)~V&t=4tszj~%TIKbx~X2y2QqAQzPkfWBYZHuz6^j!v7
+PFbeK3qum9<4rQ0|ZUeWlHZ>!?||X;a)r2kEESL=<RrD1C}eLxJZC(@(KUz}R-?rvy5Qs0X#Uq*oki2
+ccA{gFOSN<ANK|9Cw&lUdzB>nNdzX6Ir%krGbB`QrLHKg~lzb>RrN#ix-znR2jZY0#W2ueR>t)=;|fY
+ebhQvUS&}6$3;Cc2Qk-B?L!{iLhUL-58UHUs16O+pcWfnd34^%1CVc=Kt0hz_!WuY%ggAn&NHyQfuLh
+;JQko;gr`MeEoD<zOc1&ayJbR*_ffx^FnmF5*94`0sFSi(I2uo<po|?iY^9w->-<XujUwX0%U3IcHOI
+$EjRf(#N&;nOmcZb1!+}bC_NEIRosZtC;c<D%d_1V5w*jqGO*|GL@Eq=&T{jwONA$X3jS4*4BfM^yqX
+N<8cwRT`5k|MOKc(<VOqembc)6$#`43+sfS$R_S^<V4)n%fu*eq=#fPOf%`OIuB9F?(LM9*Q*g`jiAG
+A>=tpAmvMLB#7clsWX(4GeXqEEO)X%9Qe8wGojV&j+h`JngjPAQZ&knu#6bUa<JynuWa^r)_zV)MuC)
+uA)E0&FN6zZ`*$afUH|=SFzWmomz2FG#=_tEl&|3xfI2h*sORx8%H|$0NK9Fo2xz6jT0ZPY_C5t;c#8
+&zywrJD%ZCOxG09LIX^-Ovy(D^6dWo(+%&=Bc21G&SI1x;Z&fhL>oE$>zwq8fC_94AG7C13o|;%?-Wi
+n5=GA=@f$!eMt5)5O2NiH0W&xCoyi)#}3eq?<SfDTT25hLU1(E@07?1Tq)$TQbB=WxRB225G!*`$ht?
+O549}F*vKvm(kt9ZiN&jwr^wDyd5zc(@5n~lRvo<p8PcHv=AKBCckumhN6LDb8=jE(eCzX!iJ7?0y|o
+cSZw+e7WI4Rt`~J}#Qdxb)OVmfjeEjymgJ1>NEv%RJw4lzEXwiAE2_SauH(o;rD4{b)2|>sWy#g?CWG
+Ru(82X#-b`?4SlZX>V4HY@i0d!_uu7**_^N`^QclWF!IDvp5}#O05!x<ePaar&YO~yN^M7fn0oro6&Q
+bW86Mw;$57i_=F*;*zFHwC4*-OqN1}asFAO<#fG6Lf6V#fUL6<}-IE9_NE6|@=+8!DY3c?dMVWe4|BH
+d3(z%0$%m;(Yg)p#fdDJVC_rwszSO>MQ#i2Av-wvMMMNM9DcR|jcXBc3Fq}MSdosof$^F35YSUfM|Q%
+X{78~~&n7ndXO-4>1jAEWYLo^L<0!ih=5(eWH=mFu#k`DUlFPNtIbdn2Xwqo+-z6ww(FanC}Q8aUrU-
+RQ>&TF7pG0mwMdJW)GX9I=aZ2<pk<K8Yd%o{$P-^A`#!7c&ka{cIvd#U*|9nO{wyytg5Ns5WkQ=2Cn~
++=FB4X5F&h!(3*1FTAE#&&$CeRoD8bdZTtZ)`t-{R-kcGybYF1h!)O_?|0-5_WnI+6jiok6_nRAQ_qO
+aHPobEd!EBXMBdEzzTQ8H=70LHla=!uPb;8*6QF-1K|cu44<zXK0`z+t^n>i%lM3JuqWupf%^wBmk0j
+{d1?b;N(0>Tfe~_R*3DBQN(4Ph9&m`zC0`wOW^q&IspA}FblI?Z5bD`trP&GIZSDK`vz`*J2UF-L7Tb
+rk0>-Xw!yd<qkFI8dM>cN<mZOhkUi2exE6ETRhDjdPKD40y)TD}HGA%a~yG7(VN0c^fYVG)k4Z=!n5D
+vbX88nn#?UO&mzwfzIV8qCDL3OKE5v4wuegV(wTr>I@8^H3bwFW)jr<RxhDO~k8jon&M6F@VPPCmicg
+(YdUpEi$CZw+iw%el{`qPKxgcD>$D3hd%h+vLfJ!^g{zH69=-!i8oYpF3fi!f^sXOMOz#t^ur=wj=aq
+{7pQ(N-N0xQuLzV$5kfI+1{sw%)}ghpBmDh9MXC4qY;gJ!-X31yYb5lOxIMhU*JxbN@b>TmZ=<w-^t6
+GLBsw#QYVR60F&MvVxK#&;HyX1>GWYY_&keLNFA`Tv>uIte?$&O>Tw`iCdJIh?rL9Z%pfMin(BA58Xy
+#s^mxh79xUj5^N+@$`g(`L6FD4|>ZxD9x07NAT+1$cy!bSFlixLLv!27`hAQ+S9@EQQd$Vphg3GHH1h
+#AodA{0{CMMcu*^{+jIqU)h9$9kx(VHkIys?8x78R2j%tFUgimL?Xwk5vk+PY*X&5I7#i@VadGIzU4H
+V^t=urB~2igeh>jkm*MN=Dl#@)t_#@!WdkAeC>d3{0g91c4-pl-hicWw7CDo2B*!y6T=KtN$45*#4rO
+@8kZS(VweF7rTwF)4WuN|87A`ZR`tk$l%BlQRQ>Y8nAcOiJq;@(wy*bRBf#FlZS?hHBavBwMqdv$5||
+ZuuFJ<p;xdeFXMReclZa;sQJ;ZL-{aPxKhgPIyetTd5=pxJ$mUWLE~=QZxeUm|%dxP)BJzzMie0@47{
+(Q{>(H*<QPfn%?F-j%7?=6_aHgLZ25M2t$@FP)F(<&Gk9?o~T_@(XkkO~Kg6^A>&UGX#sK2+NwtxJz1
+vyE0W+6<oB#!*NCd=KcBw7n`+9+E{)JED`s0|ES$kolkEn1VdNKdcweto3!b^{hE*4>YPx1>Kugyc^u
+D9Oa<h|(d{f}TuyUZ=NrfJ}B?V?dIUY0k?V#d#!e(#Vn*dtdaHu>qY5tL=Sp%Ge;MqFn{OUD5`<J=|7
+svCEs{V(pAw>I55#fkXClTA_Cq+*tHwyal(g=d21{P&&js*Pze^y+gorO$uEwaENx!uFwUkRj6HVx{J
+Hi@N({?4KD3Gp11^TkkdZhiA&4|z00XQaS5B^V(*Mq<OCa%fnD%nFzRTbPq&)zXm@eTDR4zfdwE+<VJ
+ljfTe;;FbcKVx6Luk+EJ$LzfbA*IE<oZ)fp!rtj+AH@Vbho*?SF!qBW2pfxzQ=q?0nRfGjROi&A!5D;
+qwthE!;hVs<o$Qr)}ZnS&7~Lok`a7BRCDe|CIpId2PO$J50c)Q_g%fH=2O%%5C%2+;7&1?4LTdQ<3;*
+CcaHk46JHGAcq6jCPz>+ts`epGjU@Mq1G%MIfdHtpmPk_s8K=*2Z|%Xgp10NaKc5_n1G@Mu_GZxGc}!
+{!bT?|N@G79fqQn?0+sg84qYO})U-cz=n^d^cll<AE)f$<>|L>ny3U29cZpmi5-@!Ry*@!^fjVxBmC8
+xpV$E{Ww_d&4aA~oQwP533(W(qkss{V$xKlT{=^UvX+=Pv(9a@n)Qa!Yxr&B-JDU(rMe;2>kaa!mtN!
+CJNNxIg0>Y{F;pAK@jURDT$g!RSO>e7VE-xb6*fl4cFn^2{dxP7p)iA9@mWdo0ffTc+-pP9+9#gbL8)
+pIm5(z4_<0*aIlvMf36fTDH9d6t}}pu)l43A;5gS&+n5gJ8UCvm=QEH1P>_$!F(Q8(excZn;LoAg6_K
+%QYefy=zo%xkiQJV(*M~WC%7S1IOqn25M8hbGr>LE%@8*1aI3Y7xXOz@7^*OTv`aeVe?$DX(4#)Ho9Q
+o5PVjaD)vR85%qw|8ep!V)32zUk>)A~`T>+P<XmOpdU@rHJzE&ryW|)LiWAABaVSQ9n(AZob;mR?(CM
+LQm<c8a`gb=>29t$rC>rJi$;jTN#-T7dkv!}}5r=(vY_aHwkw{GX>BXW``jV1<7_sP-x+HZy$XIkr+h
+kzxf?di62a?t<UHmH3iR5^t>85kM+H?~(zT#{}?s(PNhMuIfigU>PP!v)lcI@Z7_g%=1etHvqqp#k?p
+ryawl1-z}-j0vUZ?AI*#G8gJPrY%R2Jn_~x@{Y;8Uekb-*#zvod><U-gaqxor!CszwOd~D=T}qtTVyJ
+i{xUR6+v-DKKH{iTNWxDh)OA(RVm_3JmC{}9_>V@6`~@e=)^-MRv$Pzg|O*yf6y@Qm;o)_2MvRcIk-m
+rLBog>eC!=^4R@Up$-*_(;;FC~ve_W>ArJ2Tk8UjbT;pT)%!DAMPZK^?kBbOO*NMi*>dBFv-rj+ldXf
+xC(&}``@++(-H^TeJB#;ia9}^;!_;gJBn2?+#a0S$l34xhp_Rm%2WYCcmhIlULx(Fz&wht<bSs=AoWo
+fz=t1C^|dR29jw^&VG^zK!(PB|E$YdBwQQ(fWFdgr`Qrb%g?a9$?Uv@UIQUL>n>uy?|0DJv{UVyle|g
+MKmn=Zd8K>Q(SP$JVAoL2q&Hxg=iYK<_i|xddNj;o9=tbIISr$lfLEFwmSx9*)tlPHl{aug}|9HC(56
+k~yx|JLwv)+qa>1T)%HYP7+$>Jz}D`mCB3;&fMmd!fJ7TVIgdBcwwPzeRAQZZ*gqlWZ*utsFF5xnLu{
+*uZ~T3#=uj_4UG%m$5u5k(dnDt&U-CY4)hId=k1m%3)fw6=N%UdBYT(Z^NQp|@~}=ZQHEAL*Cj6wte;
+v@TTC_=b&DD2B5ytIS}<ub_nNu5C!k3`4#K$dc;x)yoyxcrNX<T|g|68LwGg)TLEYrdKB$x4>4VlOWf
+tBtO_r(-xo@3+Reahf{q8a+H5Rm6_}yhsYCK#%>UWnxv2n6@%4$(8tVkwSlcJc+`QlK09EWNzdI1W0P
+|n&63SvS_;H=HCATF+fIcqa8bzb(4H4aUU8Og>j>Npg}tF&Rt;J<E%O`D_F&OtF5(1zi)b3jZEE(7)2
+IT$1#dxz`;K`|m(I0hkyaM#Xq0~&o=zU&rzZVz}Bqz-xKO%bnxfkV)FW5}!E;E-_ch<O#XR?&*GQ_6x
+#{CjP1X(2oJ$p$(7Go71cgWe@>=MI_TV(*Mq<^&s(fnD(BgRYKFxw8AT1uE^!KXr;7QPWQIQ>WAsxyy
+%t>J)mNiM=a!nb)|G^mdWw5nMi7xzT_|M}lrRMJ*}maLWy+m?fzz@^ix}Vv~Wr3wH4u97tNLXwz=MBI
+?2X=1UT-P3*x!*(Ug4A#ERha5HEVesFSVh(DOL!=%h*DBTt7(>9GrJA=*#Z9q%ATFz%|K<sk;oR8OPE
+bQH|>Ti_?Np08QAR5$n^vnBooHqF$D6%&B9w@rjTI-^2lkdS!?$*}|VV3t;RL`8TK_ImeB}vytmLy?&
+VY<lMNYg>zAWoAqPtYZ;n^yHL(db3%rgQ2`N_xe(>74kI)U{~cbWVGdfxQd%NpEl<Y3);fE*Qb9tChP
+=c(icuI)$r9>7RDjDP2YD67OB7cq<(2ov_Q-WI+;J1)MRzJ0#v$y&#a<Jgg$=+PtVD3EMxVa*?-rL*<
+}%n}RB3cNoQCJRtn6^=~%JHj!sLaht%iow|M8xsgYkuyYfWhN!bi9*oE4#(4djRnHMFeVOx`%SagH^r
+gycE<<6^yRLR#a~TVYi@h^egF&z%8CZ?RtUns-B8t<!1~mFic+VwnMM<B`?ztqbNL?qxdoCeY7}&dDm
+9NQxq_v86&JWS~;im>PI@a*XC0a#EZ|*<2M5{<$F@{er(N-APyI>Wq$$_M`i<bGt1C=aKIy(2<hj!Ss
+h5q0aw8?-rjvt)zHaWN~^#`ZeNj~-t*`-f0B3al6p-ADG#6?1xt`BBjnfSvuHT0rxZOWj^*4ld)4n0=
+y|6aKXSR<naBIv$3>0IL?sK2+NwtxJz1vyD*+)tQ~M;-m_@QGz~RC(3|{2)AI;W%KTh61Xu_!c2hSDT
+Fs&F5ElQe1iEF~G*6Y~5vltmfku64p3mMcu~|vUCj~Nfz*L^8ch>9tENvfb91@z){(@r@GY7i20dUBz
+;w4T6zGm^72W+R&qQ1PCy|qFenor0s$)X{R`;%?tK6bd{mog<0$|_olW=-G>+sDY&?QCIqaQ0iY6YPf
++`v28*&&0dcx8SU1FpsG>hWIm({WEFQevSyx<o3?iYY1BR`P7*7Tv`dez`spwMgnLu@Z8DtfVfh>avg
+=346?V$0|twtxDxnVO_Kv(iOX30|*Zv=AUc)Ixp)RcrCtX<JCoO6(S1g>1}{RKIL_SOYl3R>yTntB%|
+#BrAzSHZ~esB!HbI(oF2?WZ$Ep%U4y2fB3V}jEke~8<4cCOVyx|cF^mIvg;_^`rtkZq>J6%H^gn=ld>
+oXzR?5@u@_|Don-dUox12q3J`w~iXw(ZIuKRzY54(y&P=$Usw!A70w4-Hs@~VGPHjGl{XnjLAT#bB@j
+l^o;~fPPC-xHlk%U*v(`|s`#KDtGMeSgmFMG{^d%8y7`dbrFFcwFBs@%v4g6jnCtLtVfE-H46Kru>r5
+9?lB6joKm01sXpfZ2c*CyiZ}h_w9jgUhJ@>5sW2y}xL*2AL{&^90(nI6()!dj}@OEW&bZ0J{@imUU&x
+fROLE(5o$hqZMTjJOgnD((C7!m0o-^AiA*j+iEkHRwrbd<L=Kj1R-aDKSpp}2JV&7h(`=VRK@8vNb?=
+@A>lpXrc9OsSOy{H=@9&hrJJa|@SJdQAx`(D3Xfvt%`G2OFjcAkQx(X^O@%3zLGHQ8W^SbK-_&L_;u0
+$E!=&;TuHPa+bOh-ZwtE<xj?vu0Ru7}Q;zPHv%_E5HpE|Wuk@#nTKVsYx=vPJ?djJuyBDtK$zA6#4@)
+&?zfBej-)3*OBK<E9$^GA88lhuRhSa&8<o0YXqXif}X8vw{fNoriFVHIF=xXR30wH+6i*+sy#D61iV@
+LK>}p{ma4nGqGzFAD`_+EHJ;0q}^KW$yPes8+^a7j}wbuM-rOMlB#85Qs%tnX>DAZxc0_<vbvo^ajE3
+G9g)R93!|`J@Tl>m&D?6iLQdP`4}OMS&wft5-8uj`x!ygQH(-aAfq_CBx+xBQ&ryllL+qsK^dd98@P?
+$*WWNEoj{|v(l?CRCh%PQ_8Z1DL)doarvy5Q2osB&E>!P(quO37lB!KR%dKlXt923vI?sxt34HIVsx#
+;c8gVy^$I9ne)rBu&U88YHPe^$Mypsn-)de}50X$HKbWNM*nA?$Fl1sC`2e@Gminwe&!p(Z`v-YvlOp
+mVd1Xf|vV_>{_Rj95pHXgZF2<)FYr71|<GmMKXogLQz^v^%8{`?Y`?%i=!0J1)tLj=cF5f~))&z#z5N
+Ng+yQJK4!D@~nl5FmOFw^0#=#-_Jd8x>(_bk{y^qauzfk^NJrb}AAdL?UO;eI2HXRV7hB&*IWdOAEPO
+LxKIoQVj+*$ky(XKw9PQ8ge%9X??hBNZKH9soq^f))bljbEhsklH#mJA@4kQRW<tE%^FJPUy&~O?gId
+_OJz7z9J{Bwbl=fCjA1PC4-urc!mk1lGInT}lW)#NyizX_4-7zGtl<4Z<0SmL0mp@NR_hRY{EbTW2$>
+!YqclCjc8$DIi@r`{|In$Gh(td#&_~?s6~%jtHMOYyDm>FrZE!bU*|Eh%ViWl#AZNu!qZg#Ani>eNtb
+>S#Z>Iu+a_fJ8^5o|Vu&CQE72=l)EEV+;72(tX=9yY$4iO+5#y$RXpdRA(p$0;ItwU(cvr467?Wo3ca
+;ts_ChLmyFhKt%sP>yK$v5VXvwldtaR|+WVxuYMTrQ7zHf|cw^4ud&<fk`oV5rjmC(sx~StrTW9`3;+
+K*ACKRjOk8;ztZfMP=eF9<WT`h}nN{MWC;68plj^8v4$pamG|9a$VUp4w$T@_RpR+(UMeWKoyA)jkGc
+ck5PNi$H4>i9a*kW4%#vRl0-csJbZ{+xqBOmQptXqf=6yO|915Z<4m|ghwA9dKN+xMg@B^!9{`x9tcd
+%iL)D=@13KnYM-*Dfl31$V-gSVB014g)o&adh6D8SIdV^IMA|^`7qNAei*BB%fc4-Ya>eb?K7d3OgUy
+1!8YL*gMT7@=g4<6h_O<fgmgM%jCI>-ZwygEhAsn~p=-SsBGVsT1GRBD^9sRP~pN9u3WwF;f(SgVRvJ
+<S4mBF_E_Unx<-Sbl}TDVr^eyrRxO#qhXVp^F4M3Ukr;^vwoihhh@Au2dNN6q3yTxl<P%NpV)CAZl&7
+Q0(=!oK(b5kY%-;WLCM!YFcfGt)H$5uWjwD8XYc~MFJg_vS@tzJ=6jzuy%E^oMiUT)rHhp1*<|q6~A(
+zIBH(GsOTl|gb>)pDqOW7wtu=Ryw>%ss&thyRu-_MdX<fW-tulyVryNis)5k{$(p#@RHmxX5T!iq7>)
+`a4kAb44hNM>(+&x-U93z;BQZ%<6COj=j`qJ+p_SC}7O*2@yp6(<DBecmvUf|AINPU%cT<uyRY6ku-5
+n^7wC*k{M>cmCnM-uH2+>_IcY8B6NoN-!WNLSyI1;qGs2q9OU1Tm1-gb(xRTlPUYLc!lLNe#N8_SVuy
+@Ak?VZDLUbs|bRFBi|J-iiT9Y7=TDd%7FTku<%5(2*;>fzl;ZT1PLM8NC$)lC&mNGY>iqb>u#`5I9nv
+TPR!)y%s5<wN7yEBqT|yLgE-5CNEL!Rb^BHNfGT)B9i!IhxaH6Ndkv}_9y|FWcJTh<zvv16oh!_{Mb!
++j<nc~q>gOZjkGRDdYcyIg>zrGWI+-W0wz*WJCPijr`>dpgwt+9mrx(jLcLge={EEvWmTNjOtcoTBLS
+_A!jX5@M&jC?P?44kWSMnSk~CFO%|tkSFkP;IEh%T+SdKKa4TO&DvJI53)#V-`<%{Q%ZN-2jt;*bz@z
+RauNOaji=*Vx`K<SFD9uq>ncs9#c3`o+dP;Ht28qgdG|C%TrdH$M6T{hu6A=v+ktbXk{khC_@)^qqZB
+05s{HPbpW_B9i`M11BD@rCm9wdFxl*Q94Af}^31{BITlN7^?Fg=-7GOo^^_k~b$INm3OOmD0_D;>hIY
+qH-i~bCJ0OM=e4ZOxM;-P14mwSWnJo$8h9ia}YUFu{o$*%gs|td>2Z*)<{f})r4oJS)-wj>}nPQM^ZH
+lh0Ec&K?$pM3N<GoNm3P3EvuIe?nvfkC2{2NveLK~gU^JpE|RgUfs`bw2`uAt7`*Um{J)YWiH16|BUu
+O>Ns%lRE~UFk$+2|`Bqt$BQj=jN;gJRG$a7?)aHKb~k+=kPml9O_WJYdElBO!E%rCs_j;|gg?OnBF(1
+EY3gupNn9gez6$P81tLSR=3u@SWP4_75uCnm{i!Xt9$I8YoZb6ix8OgSzxS7iDcCBTd2#c8G{>8c{Eq
+-vp|jtngp0!LyN3x&($_(X`SeHs=gAxTmb5}9<xiR8$&;-+(?SaB1&ZYzJF1bESeDsAXVN+ixK3B)yH
+Y3rss?btXduLqv*tw59HaR9gY0;#C0pHUOOp=q?k8?066g1BxT_xXND?wr?;5J-k9)?vj8B9W*Bo0xs
+n!-(mZO)3(<yoAC2c&zS5FJXYVy06#A4FGUX4BgRQ`6x38Z2ych2#kX?Q#Uy`kqGDK<)hUl{m`9ngNv
+N#qACWu9=eL)6MXyg!6yR}^R093f+$>V44GeCnMBu8;W|b2X~ISwQYyQIKdZnisqks2BlW$7z>(_SLg
+AWNuZ@Xy(Ny+MLXrgZIF5TtvsRB#Yv}#OgP_~;I{=NjqN*2jNIGdIKP*-5DF*qWH`G)cZ!oB%F3fMBu
+@StyKJT0S&U*x^J(hfnf$BZ`0o==t^Ds*$kgaBE3xULAK|h*-SJmsE5wwV9boqV~-I@Jfg(H}Ln=nrN
+2_J$E*KGBo6l9gKLF7jneg(JxmWI;Xskeq=ngsN|=B=TaCWUJ&_0~{KlFt6YQzs!wa)wB<c_!8G048-
+UTNdQV5|_;NgXoWDD=kO!)^dqR{~YtWa*64Zn|V*!z_)+klq4Wg&rH-*-4{Qpw$qmFr2fNG+q0&V`cF
+^YkD5;EKR#`E(sWY)`Kk3m(@9kT+7>*(iZTp3L8k5i?7{+<C*mf(@!sfZ1&H1otv{^5jQ2**5m3L>-h
+;+;I99I+HuNooA9I!(?>EjL=~XT9J010oZuPC%iaitr>UQ;;{=-M8xtu3bGAqjf=>;mW);FUOEzjH|*
+fwB(SG>9|I=lTVK#CL^Xm!3(1r-Sbq`R<>fKf-~VOhLWX~vGr2VDxYf+!xLbwus~zEB{iYS)26+kjm>
+6(}ltzV6~#L6Nzv!!Dj64r2SKPn)Spy0Z$MdKi2D@Gb$N-Y-17O9;&NB(}t^%E|p6wxp?wr{OVdNmP}
+J^(AbHUKNJYqw|ON2nZ>RdxS7-T2o?Ih2d6~lBOz*1|2Dhs=~0UMu~0+Lv2;$va+*C0_mfe#i~dEpFR
+m$tV#t4T*ohqRl(HA?4LVz(UBBLJn}Zr>IyU|gMAg6=3{9SpX<a=VxP+gf^Uf;mFVTU-a;j;%Yw0b<o
+X>o$4SrFIDJL1Nw>Hjg5J>WfGGL5@Wyc&1Mu><`4K}{G|NJr32i#XFqFFKEo#3c+8NGh0Vzx=Je>aFh
+{S{y`25j6ZZDopdZ9?gsrC~quQ7tLJRe|4k(^~961~L2W#AJ!o>Pn6Hz%Tch`WhIFY<JYchds$KTr?C
+fXy0tezsxquu)K?kx7D1M{o4E06Z31IgLg5S_LSSHDo5vb-+oxxvE@QB(5B?a8#<=`Q92r%TPv3^wVc
+qVs6s6t|DL@&K6UJ!2`o}{m3;L22sp+ow0-*!tB657WfqjR`dpQX~zI`h1Z~*x+U;L#Du;iUq?euhy9
+0E1bWRkav;`e=w;W)g;*zYt@lPwL@TNNv!_k8B-NQg<@v?q-cH`>sCmEjrh=i8<DEbLg@A}R=Y<BSd2
+_yh>_Q7!zf`^3M=rE-a-GAD4YD+?>sVJ3`)QG>Y>u(a!yEmjp8=;6V;_0{0YJDmsQ?kEU>t@;3=gtfO
+}}9vH(2@Dt0chMdTgL1UbpC)dTjkGhKipjg6cyNjEiGoxAMUdPEnr%atu6HVKbm3kBeV$Tc&~)D=+{>
+D8t-vfb{Y~XCmS$8O*qqp8#4O2d5%Yhx{35b)ZgJtWyi5ez7oll+il?q&^cb(p9gfpDU1ArsnbCR{-g
+(IM<;~q@nPoH9Ll8l@)R66SPIWxj;Q2KX?x9iA-X0@D18B#z#s?bmNyAz!Qs26!~?8Jc-9DMs;`}+OH
+T{M&SqZeUi*kIeiL^!&pUOp?*f$TDbLNy@6U@2XK(4arsL8{2_>l`wC+nLOw+8LK|iOwXqZ#>Et{E!8
+3L#iZ8L*AoOtd%AGq1qX*YZ7vDj9*jJ(U{SRg<ZH0|f42ekFK;zg#V!G_DaZX|4+dpth5|F58fXZ!{h
+%UwIMB%=6XOK*1S!AZc`PG2c65(jWl@9rQ<+gI{M`lFyU>l)~5=nZ#jhj^(!oxeLQA|@Eq+OZ<g!z5(
+i9`bzL4w18h3YNEFQ_%jVsSenko$<eBLtH!(=Pl}uF*xjRAd8`pZFO8%Y(;`uhOXQE!BWs9hKQzN5CY
+5)Tm2u4S?iz^Z~Wb>Buo?AO8^}+2g}iXwCb5?rjw@jMQ|xt|Fv#Xoi9JVHyX6V&KFIAOhgBJNw&K1bV
+6%?<?vwv{D-nE9yk931qyeu#(z8d)h=xQo*zeu9)-X7X+!z7BIXszDO3Rlcz#*2L82j(9iciqc)W$14
+KKM>%+UNMq`myut*ssQs&FNK|dpuNX<4Kf=omG0O>PoW8=!9!AAp#69aF<%2miZoWKKHz}mT1!%9V7W
+)le(gQ60<UldM|zyB?U$yM_ZR`8LyUCeiG#l}_sq9YU93HipO7x;Y5kiU8Ji-{q#HJLakfKzr@owbzd
+P>QX_B{oqxb+*4%@zoDJ-~LL0BpYAdZ{A+8WBt+C*&Mue@T+!f$$<;Ae*2CcO|>AVcOBR{-vx?%JqmX
+j;U+T`{n9(JG}5W1R~J#EvYo5&J0iyBD@G00iYT7D)b+<>vExTsnE4Fe#5l!FRJL~IIsu|@Ze2Hw9m1
+xsP+d37971>9*t%{QxH^&jQ>S(+68{Y2_d_Y{^G7#vy9|e%Z{Mi27ULarA6xu?X~2LmRyAOz(5bj9j(
+&B1n%y%5nNj(O4xzD+wgd;uxZNu^;!MT6mVj#P_n4>h{hjapi~xh7c-Sf_9w9(76Utw{P-#_Lr)s<OZ
+l9UWIs_rjH26v)i8bxK-ZgNze1?2@z1cX-M=AtXLlJJ5fpMpbAqU++`pH0&eU;X3>nQ@V?ywjoeRQ+_
+5<`3FF84kF0zIGZe>PjaIo6So69f^dpu2v^qMq`(wl*qYar8abeO#|Vxnro*V|5o`y4wdgQDdZ@cu&t
+zYm#|+Ch7!;z1}d;VaMGa1F3KgR1JZZTL@Mjv(Iret_&5pb3f*)2Fu|ZZj3V1Wb#=#P&x3oK`%33jG_
+GI6V#ksO0y(aKF0nL21#FlrCnJ#_8cwL0?r+to<AGN!-QWD3@-TWf~trok>$;Gl}>Q!Ap&v(fJ##w!9
+thCV<Ry9#efLcOD@)H7%=B&<<9tg1vYQo#VsselI!`nv4Wv<9hM|=J}rR?Ww|&vtQFSSK?wbRnJ+TyB
+zh_w075P;-&NG&b-11g8HaIR3UTii0S^6SzyOKwCk_a#q^JgfkPZo?(nrBq`xvWGA(S2cF#`5O*ikHg
+Ljc<nokvNa<2tu0&7MeWt(R4mH2o&RN>wCl5e#NNX33DLLMVqP27sHxP%qJkpd@17A_w#-YAkZx#nt)
+<FgNCOPEFX_&577_FA*u~bZ8jFJc;~4tY_bS@G>UFiHOA4^C7#0B2jDFyU+Zt{C$hBp>2kV)lpv}I`{
+=Zk>Bw%A7!{)zK4JVmS_if=`H|tnp^lV^Sk+2uf*c0NS~=3Bc$X~-0xSc?Z$0D==CPzLXZkIo&Y3ddh
+(ouqUd(7I2(d==Z`T4u3Ga717?F%8=H-<0I7r`4iKcawc0_zNN<<EqgEM?L;Tas%W_qGXQ~aONTWH5M
+@)w~7h$OQ6s$O{`<noab77gx#S(t$5Uk4d7`Ik34?i|wwO_gp;C$3c(b>@2G6ABm)fkWVFgAVZ#dxuY
+(Os8ojOTg;k^NJrb}AD8tb(sj!Pb^)09qVNggA0rZNVi%7`eNk;1VH<yrGKV5+R7(S~}23SCs{Dim?0
+wT6NOh)i*{XzOI8HBXMS+H1B-nJwOsOgbtsG<4{|;>04+Hbiokt^RsvaXCt?u72KaS)C$}E&(JvLHct
+J{BWO+{zo#rPOluJvgDu2^_ZX0=Gw|JqsG08_^u?!}zaoHIqjvA1Ms-Yi7q_7sM+jG(+UDFTKo^L1j|
+eb!a#j(%D0$CDosh|oZoUJkIP94~j`?K-84snAS-Fi{%VgMmm60}P=}QgT*LT=ge+FPa8f!fR!<y?n!
+HY0fx#(@;6|RO{0dD{>$+X7|a-L)1Y{fQCO<>J9?g2c$#OKVosBNUS1urnv;QI(c%yZ-W7$V9v5@~bS
+USgzbpVlyNF1GQ|3k8={!nZPhxyW9xHj8t*L2-yyE@<y+2rB(~R5&^^0;rd%Jn~0*YEIyF00!dHG=d%
+81eo|yDpI(qUF&>&sW8xRD0}-pf{DXb410iJ)zjSDTL47OFK<J0%9X$T9ts)W0Qj7r^ePc>ZAB{;uq(
+}uiq}<4M}_Musw;EN9$psOSFoljNL+1fxldN+yyr$qTz)rRB4`JAHs~ZWVRzh9=Zqf!D(vJ0-9B5SK;
+-o^<F1u~O<oH#Zdw`WjtgkUJu8aH`l(X~6@?FC<=Pk<_0u-Kn6QDbLN3d%4M<n)x%Bz?2I@i_s`X_VW
+Dtj4UuB(KyoZ{Fv4^vAy-LjHg1}4tFjwDr@PGu;<sgl0P9{EGpV7$TWD+>$zyl+D6G>+O+^LI>q|gI5
+=Zga~Ia3y(wK%a*5ffa4Y`cOp5SNAW6r(%<ltew$KZkmLbK>?z$4|9uwzUQz73qL-W@RFePTue9LxI&
+BCXlZ(dXK&P-Gt5gvufvl*MQ&>#y<gM)_nA}c8>tj&a-i|6l2qVt#P#!qq`hv<8CQIWdGEuor=Uq8Zt
+ZKKe%*z{&w{(v|q95$a)2b&=I{1i`Rsc%8Q+yt0ok!&_@92!E60>_#zc^ERs?eF}|UnjHE+xVnB-;m&
+UD37|NlzQUcd6&v&1jAa<o2`Xj&cK;XWKgs;d~ArOvQe{I6h^-Yt?b%B${q_1#R`hw#0`%5(tSA_16b
+!XsLKD=cjl>t7u(Ru#zp@|^%w2a;%ysa||&%pRbW5~M+=dV^xIPqp<)5NHC;=zjwLIE<JC=gf>7Udz)
+=pBIG7QxVApx3-r1A+pRFA;#@ZNbuK1gV}7{zSouxH(8a4*Pg}`xO94EsRD{mIA79X_Z-iMq$w=@#yc
+m;<uHMHd%u5TLY!bPzw6*?da_tIBms%Bt5f|imSYlpV#CH*BmQ|EktXlZ6RGdaccoLvS=aWCLV4vSE<
+dqC{!(bjOQqk(n#v4meNS;%6;$=1l-KQQA4FA3zGQEK}=Lu(NDh`3G8)N+A^@0TxrX}zJn^OuUwFiy%
+5XA7*Q;o<ABSvG~qcawKS4CincV;x}F6sGzq(9DVLTkNMeV8sRA$UupPBtS~75yeQC+Tb!YIzE%*x-g
+SikRl7(v!DkWl?F&))nS`a%5$F!h!#k#f{gx<cKOlu}2xl7n_R9vMfyyx<5l3a2>Ux<iyTs}7p0l|m%
+9zHjW2EoYX(0pzf7&|+A_grIS<wtUI4wot+0?y>phdNFRKawPC;X;yht-VJVbqmMQLGJb$tAsrt)dyO
+?K?3PiVn$j?6Q9oHWn`5!30&#JjHHqznf-I8E;^FptV&^1p9&t!n9e=$_b2y{oo=DVCi&k#c3TUeCVz
+NA?ywO+?vQ%H#9<j~Ozd58*n=t;lHOqjSg0N<J#r$^>*6D~m<1iZ5<PMYSP;5a!$)q>B69oZ9YO_qlF
+}hgqR?6^WJk@lcJz+&YwZ}gJibG>xGz?e?IL_g4sP)m=TC<Bp;xz+S1#-p>s$ka7Asx@ht_LfJ3cK|!
+B&ji>tUTmpe~S3cU@z}(P*=>+obn`lAhVSO&TvqU8ZHXN!Jkrdl#Hq4jf2Yr+z1+x?V4Sr?6V+vxTsQ
+9$P3|>#v)>h2A<Dxb?M08YHYQzF3#+?z$DVO?cHo-6p{5Aa5UHZD!IY$lA!IA<SB(uN2L6Xnb@1%ofC
+sQkpHOT~Vl|26NHAz-DVEB)P+A3|OSzYfm4$(CXDW+hIEjb+%;SsM*<)gKLa#xyR^&l{_!Rh-Bd$t9p
+IUcG!+mpDh_Us(!ZQ;2MP6Z3m%MEzk=wB3U>GfvgbPn!r&kv^@_;-O%<-TtR_``1!@FiC&Z!$)&}xRB
+DX2CUBG+ZO_9|d9*zf*RV9slZ)0Py(lk|i)&cSDy7b-O>@oCW?D!2(q>}UQ{lx1$+s?Q+Li}N?UHn^G
+ajs8Z$P7!{d$9l3rbp-t~Us{AayDB^#<``2KFwvgo`+kv<}e@nIC3DGH!6bd*6-TxD#mR(6}3DX3=s-
+(3(->uAnU^*Uo_A5!fo$+DETO;wWBw5iX88wijXJ3O8)KXN8rSqq^<IxsiMvvn3F><D%RTJ-7r}-8vt
+h)oJ1^PJ(%HsnAY#S|cOM>pHvEuF`I67LKC3t$DaK;6bAXT&xuD1zC|y9Akeu?+sYhLO!6;T3ALKWeb
+aFBW-O78yK{(fNl<M%SX|gwU1qc&{zh!1+k+datmtLfkDGXs0-9dZq0-wcj&RDJhIb$ZC@<8Jr76S<n
+~NlZtXqySX{iC@<n-(T%03go%$x?NbdrtJ9c&>+tzQo;~uGzb-!0oI)-P|u*oav9b+<T+SwHh90M`3Z
+|4e9hxA8`ugg);tuD-)QyQ;D9NbFUA_#7!Z5;t`;?N@e-N3>f`>qo=beu$Y^pe7-yHvrXYneM#qjg#H
+_B`kt$PM=|E?n&V!mRAwa?QF6lt8z0DT^yvj<DBH9mp-FqMN?Od~`EtJt<qUX)!a~@NrMiDu;2vw@4N
+L_Tin{C>3bU{;id=*}t`tw)JnD7&QC04IG^QEk#=?WG@{x$Ly?9(Ejdsx5=q7q20~zZkto%;_`pLyN!
+;Gm%U>St7BnCvT>Ll#io4zI*!$&+5HRA&;xYVZh#OQS`ugNh6wR-4boY=L8^1Jcdo@S)!31YTtX+y9k
+#`H6hLgv!ch{jH4m2&d)+WF7cHB3K~^La=YSM>3+373aw8&rQoGzV1SKtfCc4}t`;ypoKD*o`bc2Px8
+%}9s9wfCx%(#M&q`21(n-+M(KHXqI|J;U6y1~IE`i31k#mC+uhx`dfBn#Idlux2i($c4`km<d`(}p2H
+^t40%v|$7g1J@qmX~O{2+1R_|l7Ed4$-yQ5vPg%Fqugjjq$5-}8pJMX=@8J329Zl*S48SYgSbr=_HMX
+DZSWwe9b!(q0gI?d?3*twh;5=ER@ydU5G!%}I7kzVHi3`^9u1L@D)lhQ2LlLrJD!PYRNBF8cpL`QwCm
+RJBn-%1?qtJ5uo@G4R~&j><wDZCG&_g}^{B$~K84jLHv>)BCN~33*;<?3^lfr8xEQ$gxJH`gJ((cYkm
+?4B)<&!r$~JPfkhT}Bn?W1NIyp3mwo02P=yK6bhhmqA^n!P@!8}M>dZoG9U>qc|Yr(tOU>Zyo_HMWgg
+TaHOcA15_U<7ZLR_-=q(t^I*AZSHQ|HQiul2+6%QQvJ4b%lq$BQ9B+Oh|Hvutl2bA@Mrt1&P+?S(1ga
+&3hyZY5RvrZU${$AUQd>%|)HIJB;Em9uU6U`Zqgno5;C~yiMTTMc+Pd-hxY;uz53^hNyX!K~NU%g3bB
+*HOCA<*z`rkYi>hgFrY6BUUM50gM;hZ;x)HHq4?N4<S;4(Ba(%~uvGH1HX=GQwl>o`a=11VyUxb<+yZ
+Z(=d~>llG-8WIX^__rJouR>Db37x0n?z9ccLE7PBID#XLT_#av-w?}kInCJ&O@C1&Oq&p5I?>F88*AK
+K#67X3qm&`lP!A^p%Gdy|LDvVUk80+N%xQ?8MqSdmOz10qYJ^>BI9`z{>Xz})|PE%!r(jGokj?wga&W
+mW|B_cqk_kDs<6Ckf98!f_H8xpulftgvczJ$z#l%*UgSe!};}IzmMy@J_6cuYavWyQ1!&Dpj+#TSw3Z
+0oK;*Kv8a26>eJl1;Ls8QJp-BCLUKd^@TT<&I$rio*Z3ww5cyEzl{o+qa>8^JWlg^@DU(MD6*W&MEYB
+ZBuN4@d%Lc9GnbUL?gl|$W#zvHFczsg!{|m&5@guzIe)lBfyk8JM$rrdo6NIql+7^Ety*6aeRmOAKXv
+M$qVTnfPy9sP*#87=)l!xRI_>_16@_mhPwwBJJo%*p#AV?2Dlo{y$_bwVF!H#in-Mk7B%#)gNqlJ{54
+WG|^p6w%izdEII=!vu-@G4T1>4steCJt5r7S<xF^hTb!?EPjD9(*4Qu{iKt2vQ%>-@azqYf<nb`T1A2
+Wbc;4i*miA1&t@HtG6fuP8|#q{U;=e>=bNv;yu0gCO&Y>zD%LFE)(6%)9d+R)jb&cC7zyLx^ONrT?@c
+NOk$W4PI1878rlFVgyBLlt0<vMZq6|@kcAhTru!}u)*hLX{{gX2vI)j@Lj1Yw)Rg5gAO9-$touejdfb
+Vs>07Ia5Ctjr#K1KMkZl{AddXd3!+}o^|M%IuJ%HaNk8#?rD&}wWGTXhX=@63v2@{CYYMrcTsUe?A%F
+S8^VSs7omqI%nnEsH3olz!$kk)vRci`ap={xGYl_Q~;!SG``OJLbZEFhY04%&~O(7TVh4-x~<Px&*p*
+4lH=nEfPQ%K)n;kY%$kCNh3YYG|VTln0XLK*v$))aDOT=>$OB9|0jTT{$Rif^qc<|M^wYYJKS3YNG=3
+YleS;d^TexzH|Xo2aT?i*h-^toBCtP?1)VB0Y#^eO;1uO@FV?oo!S-L|2aW;goItSJbHTB0)iMQK~9P
+hpH^lHWXjx3ymntnsLW-po({GXw56C`*43=TsdY*Q7>su7n|I?X`mIGlp+uzYu%miAJYhB<+t<wj{sJ
+lu(sFS<A@{NWj(9?Y{<nNbiH&Kt3AyV0IKS%`X@qduPqqBo<}qbd8&PfR;Z4zYD8`BKwEDVL|IYQvio
+DsvZ91*I?S^yWL;fUYDLekUL1z%d+S;%ELSBq*R{mQs%8{#)YEywRH4F;(1oO<2mcPVsxjQtJ}1<OT-
+EccaCJFAxw{*Hte7t8X&c2}M_29Lybq|6E)1uQbSF^Nzjxn5TX)h8b*y|>|AxPSQZFM8@z9?aZ>*IQb
+iVx*fJrv&sVbt&y6jdb<fA0Ld+tOgqQqrfzG6RL(Lbac=AE+8){f>V3&_jnLsMaUao*t!wL-7FGz2J#
+4nVC${e%+px!JX%zLqzRWg%h7xGW+U%GwCJ`cp?1jaYeYc1Nh<oP3;rzIE07g7WNYwJWq4Q8g!u=0|$
+S`+TYinQ6`|M<(a8{?~;&|H|w<{=$P#?k||E<@f4ecw>GcQTvbc$510#)E1ZH^t1U<SwBN)i>PB<vP9
+)<qi9lUpB6M#Rh28+M3r9I`9`XbG<R@{)X7uzMLr#L6r$(rI#arEi73pX>ZEE!zU2Ht&S*XJFULil8f
+h%yXN&^ws{=rrweFBBu#)dwR2F0ttAI2<8$S`4s&E^|yJO%<d!oNTVgprj>nR|z?hH%HGS2ESScgFTZ
+kLTEpPzK?B~goOkoe=F=l5p)DARB9e$u<%Zp>FcKg+|S)=eR_zuncgJ!RdbtitrSyV{NyYsLA7HX~h8
+RNSbEtZUkJLlL!6wdG&pX1QYM;Sn}el}Y&qh<sW2%O8Iz+wVU$+hyyP(fa$}YxKhkKsN6h&Htg%e>U4
+?>!#8A?;87w*)Cf*jMo3u*!yO?Y~40HsIecK?Xq>%X#KOs{?%-ktq+XWKWXe=%y!v&-~8ea8vURGkj*
+<r^B*<(W3yehuA5B$pwXulfNb6~ngRWh*)ChPx+}k{;&AD#&j}mr#e4Ib+3M*%`Q~->6;Vu5uq$Ws43
+lf<rXGutABeKBWxX;ryPsE}viSvKocB~|AF`sWaECHZEGL9^i8?ycx(*`~kH!g0q0sae=uaH=g=?h!!
+3P+U>mG0G@lOI38C!yR63;2ish!tuQWWCl%S!3SAx~RR=_}=$xd=4M#Riqlp`g7U^`1Wv*S%(<pfCHf
+^$Wlv{jvh`d6%)3O11a<p8%{Xysm3kStM$g9_Oz9rF<K~!l0XZ!<Y-l>*PTQ70Ffrt#p65@9K}`a_jR
+2A>&&SQNvSy>SxqD<*B~`7AZH4V(I1@CO*n$^<W%OND`(eSTFXX;;mYyb7SrT_jsU2Opk0o48RtzYFi
+w}aut89_gx+CMs!rX_39}wwRjZBVHb64`yQWAN{jC63Vo%IB^EI4s6c)1&6*Q17nNR_grC*n#m8Uj0*
+AdM=H6Ucc@FC0>KVm6Z=@&G1{j`Lg~S*2C%Bg?eg#Yg$Vw_4SU%Vz#(}=nv&H2KG!5kHy|_|=^aYuO>
+C=cJ0_-VWkZzVLf%fpDiI$Gz8IFZR%jXYuB!*pPTzOH+JD7}}Jd^>!bv>EbD83wsdZ<A^5P`NJn;-j`
+nAu)7;hOFJ-t(j$LCCa`NLqaepEgp+)e{1$jTCZqhUjV|g<R<%;;Nmo&0Sz3HRSxEcI3o%lk2l6d6Mc
+%&MR+g;Bm}11m$BTiKEwiF|b@~^_02>%&#cR9WqrUZd<QsY{CqKwx+#{N}4^@Jjvzau&qm6rrd#3<-5
+1_c5x<1%hx7wc(bjYk#tV4lG|v%ql(dqc!VboaC*82`%p<b;oGUPG`8FOsK3(IZtLwi-yjd-SUnfgzI
+!}_%Np+J-^Qg}yy8|{_3hU%g+p$NQK$9bq#3vI9;Xo@cc`GZXM@XC+~a~*gYn3UtIG6oWQnVnUB0c5P
+1n({#huqnQ!3nYxj4Z7#aAwaUPJnPr24ruU)y>W<I2u|{7@9H=012P)V;DAuK{YpHB@Zhim-1S%X48=
+xNr|}(;-)Q6_r>zzyR^1$1ykG;!99GefcTYm2s|*WY_c(KsJi)OtGKz`vZ}=ftx-RVLrrBf4~d5@&!J
+^c}L)I4?^P{;iw|ulvZ5S)*Z!|-ANra>cvTdagGR_K^$U~j}!{`C=8_61QNIX-ApeO1==SHEg0m!_s?
+P-?&Lj;{j!do48&uQ2xEOFutv<3?0W(y?_iA6I)*47D{PuPB1Op0>d1MTC4Ojp^ec^J;C!j$%(JB92b
+T@)sgHWcANnJ;bT3TF;pRA^#yrA#Mc@c;v&WSB7ie{@5QD@0d;Gm=9f^fptQhAzg)<10eJ^mHQ#ipqL
+ny@0=L3v?*c$>P8G$-YNhRnEbC{)5ayYmL63hmeO?^Ie;*_f!SK%Q`=Gh>g1qGerqfSJSrE|W4RM)>w
+oX_%|iJ^Q`d_Dr0i9fGg!UCl}B|74Y1viG`(1M$axXX$wxe0HM)y`$%HT~-(>1>b;f~ay|;2SwjJ4qg
+~0Cng?9VHJ3eqsog;FBkOZSuKoPh*5wx1}7BZx8Vo>jsIt(;e<tsV}}Ir$bREUe|(Nct)xXH@3dktY_
+p13l#3co5FfcnvSm6eDU3g+He&d>x10o(&}`?uthB6iiR0aNz>Z(C*o$8*@w5}tQ2Lkx%rZweZ;pnW4
+=iWx~NBWp?4XdJzVSgE(NUy&uMuKeWk-+NCVRy1|b$eeJ$h|5f*w~r@BMFm&mwPG$+k7eBcMj<vud2+
+V^MpxE8SEZk&1*Sw5r3GY-WS9Ng9Vr0T|_IEnF~5NgI9wAkbSi1|J5&vGGS3Du{ICg78X@99(A1w!JY
+7+L)Xy(JL2FXO?MuRyDtm~ImLnf}?YXdGB{pOGtMH&6WErhbf&>XxxP8N)L3j8^D*)*Vu6TwhAMzkSU
+39{&95PB0tmyX^&X-H7y9q>6S+hpaBIUclD?k6X8{;knhvt9Lo*h<pVIslJZ&;!zNR?2kxQQAo9!dqi
+p<>*jnhPtc65t1%l)R3yH@sCS=*+~o{s5vLQ<axw0#i>$2NzHq-WV(O>7B&`;AX0wE0Yf@JuR-6xGoV
+pXijbspy4W#<&uD88;q{EH{YF#t?emFy1n0rC0K;KVdMqt*5q90ri5JG+Y`$2@P(+g57`-uoAB9yww`
+o-l^F#zCqyd=%K#N=C}NyKyvXyMp}oQgdmOTeWF)XuXo_jS5~-_i1ZNv;?J9~se?q}C5u%v}<UQ&$7N
+f8vYa1WgA5XK2c#?iLIJZiB;2ouwC8^<fw!jOk%`Ne+WR!Q=UoT<SO$@-SYK=9_PtdMu3dG5%nE;o@i
+`gizOOj*zjDAL6goC(0n_qnoO8g952;5Nfl#zC@QOd`Sz^)Xx!W-O3O0i8(BFD?juDZ9QL+{T7j-p72
+q+J#lHLI(uJ{dNqur9$$wrQvH{3q=7dRtEhT`RW}5~JmL$%1mV<2Am}or5yDBVZ{-TV9bwe_!!cq!Ut
+g126C`@S^O{spj_@NwsM}}0LRNZPpHN)LMF4$de5@|$AWeJ~;x16?Qz6Lw5bsawLwuR<gJFGqLw@M8K
+h|A&L(Y@SECKa?L;kAEandum)UEl9Kkv^BQRwF_>2l1lXoB}4^>57t+}roHa=#_*%}kuev&vOEBlT}4
+pW|}`ajDO<nMpF3%vbtcpWLCZ-PL!b!4CZlHp=fvPatF+Khkzz;M9W%Axq<I7$cneYzTu63X8oX6`A8
+qFh<>agaP*vGZv*83vi$6f)0ahn4@6bJ5mwD{0ie+%sd$&wEA=(`CV=K-jiCyF<1{dIPb}!9q|=n;HU
+a3TY**|H(}c60)$f60D&?|jnCDk#gTf!tX|gNlLO3=@Tcn2c_da*gi)6wcdz;0B@8Q;`aQWWbL5OWzC
+Ws%c!5^8StCE^UWso?w5~EGT9D&!QsXy?Gj&;K;XC~!*p;9gBR2K@=P2MCCTy@@kd|u{hrM_f_q%S?M
+|^2BzE=0<M`CLj8o$53gm5H29oQhjyy~_|przc;QwJ3VT78m=4Q|)yR^4Wd;(6ibnd4Wtmm}^8j0`=m
+3o7zQ0XU2w$j?Q5fOCXVSAj@Whea6mg`ysP`9NxV#OA!N9~u++135MVbDsHVRsBFpL2U36pZjYFt8S~
+JK;H{4FzVx1U>JR>Ta75tL-K)~1yP*z<8a1|oe0#rug_7%rIQ$Tb#H0O3Ouoi7>U4O<P#QvB$`uKLW}
+R$%_$tiEqo+ZXY9}5<C<gA+;Y9pX8V{lqZ~urv5W$r+6NtzlZ3k^+<iePb)_Bq<J>Ql#PF|=$#EN(8Z
+tphbyGfO3H~K@4H*xEu*el)^uBI>$3fQhgQOZ`JSMFR-%x_49Fucq%rzh%=m~gC+SYL{qIM!46(hX*R
+Q}P2{n{r|vWd_PJrO>W%9G@2YM|7o0$0GOhf(UPk^FXqBMhHOspIpzQ&L+}znmPZdS(%Dsp~V}S@i;s
+YXaEA6H)-Fu=ZNqC*-hkOW!dBKy-^ux<eL*T3b#?JC_Dx(cliAzN1zk*403q>HAz4FjigFIabD{A<ls
+#gjio`(~vKqGlnSY(_0{+L&Fo&wx%Mq8&}m`;MV=vG#;Vzz!Orrim-`soo3;$^gtDeGTy<rv*rJbx6*
+S#cUbAqOL~wBlByN1PaDZPhpo;D&2J1xi_d9{B;cEZXa;-Dgy6H^iPObw_}fv)M#^waX~p2UT+vvB#a
+cH@0&OP9vXo0IVzU7bvl9x=vBSJ;IQN9|a;(zZM9WcqtrKWtq328l9fV^O#&}&JCM&0y4I*&@!%51>4
+>G*p=-yO@r|uJ`qClxX!c&MC>sfILp$L#%E=<eBm`e3vWI88K8o`X8kd8_^$9e`M!q&|N*?j3nNxWzD
+P)-tK4%HX4^tY$6m&K#sj`*(_C%?Uly1^L#?D`6l`N5nP-xtzgXa42Da0<SV^5F1!w1j*i#gPqtEVD1
+<56uGZFMDG5tG5<k$T^V3gBT&y?P3<sFmP4Akdsc_{lT5Co2HDbPtfy)YGiT8H@-<oG$~}|^?a|JM?=
+iIZp<>i6sCsE>XS0d6Maj$K&dOQKoR#mDuYy?VFFQ@0`97aLp;-1ej(>qmh+i`MOfeJ=D$mSC+<;&Ma
+p%P=~uEJ1%>q#y}sITPYC>qujE+gGva~=LpXJDb7_kUnZh0L*eKxJHf>xE$+;;B#I3MijDyGZMNXpfA
+poXd$;E(gypUh|m7L1?e1{p6?khQ;W<_1VEJw1d`((3zRvd?kM;!>UE*-w;vw3c%eS}pP$!x%~NC(ot
+kt#dqhhZS}te<lY$BtZmnV1vPJP}v6hQ7X!^_(;e6E@Pe^gG$Pd3;jxS5o!ngHgxt%rS&iw|UJ8Aw+F
+i(SE*%em={&-Rd!JyUK<3d{<u}9ObFbxUr5po};Ioz$xL&l}ua{bor!}gb$#nu$@|Z0*$eZx2<Ze8~P
+b{NPFVSfVv#NdVmP#Aj9=Gs07!7aXu<<k?(;UnTvWC)HOqWr*gp5V+MVNT3mdVSB@8-VDYKF`HFr{!0
+kRq7Ad<`<z2{7I!J<%--XV?li^ViGW4|T1W};;-SB)(w97XAWTdz@JI+J(#AIDRK`QFprh4DJejOxh)
+GLSPQL69nufi*FBA-6`c&~U<r(U>CakoTyd+xc(t;r6&N6W{7dLgTC`if*aMgo^d#xE=e^pU>A%dT`o
+zUPL=kXs0QcH$wpr_TCoNCo2>swZB-jAWkP^GEt7X|Z^ozq$`R!V$jSzI+Emn0#<IH{`}uT&pOrRG;t
+ZJFvrGATBWL_sa0Nkt-|9GO;Ll@PuRcCI#p7KqVC3y=8Fj6ptw*eU*Dt-(H?CAH1FK>bv*DxT}Kon|g
++$Coj<0VX|pe4-fB%xM^PIEs<S;2eo{r4dX;9=c=At-MHUp@+l^WG|tkoNI)jvdp-j|o)p*5|Nq9Wbh
+nM<2>;Kk1Oa@+>&?>;LvkdJHRKHD5LXKX$ifm$*dirTG$m0!_J^~Gvo-=a+QW;@%kTx_M@Uz9)mPml?
+abfm>N$F<>zb~wEM3nAgWlRp9cX?j2uo-G_L#i-8R_5%!Ml5hOS<N84ST+B1C=^}Y@Ke-QMq%5%Ce*{
+6@{>S$-pRQ7P4+!9#HzGl%Qh%-7Yp0!xc_Vt&g!8J5f$Q(^^rxBNYP*5zyuXBa1g4N!akQ@7}x5H4Y1
+uJ~=TKNrA{G-$n<~QA7bCSvr1CI60poKcb?MESxme@~AA88%?J=C6A1##;yIVor;c|{kAon?TbN~eN>
+S&zSuzY)&hPqFna#`>zN0_Bk)2Y73qfs6un>oZ7>2mD5L}TXoD<xNg-JfiZ-Y~HVWwq%M{W9r4*7oS)
+HfkgYh!YQFkMy7HV?-voXZv%dHt(#R#iS7P4ksgCIN#w-CpuS2=&B@>A@ajhRxhg9q!i_(>W5UzGs7l
++<W+_!SVgzEmeKCdz2+j4M~S<y&@xjTZi}E0K1^U9QX|%bW!nAx3wj#BB%OLHVWtk66ron!8dmpsg>m
+h7VI_Tn}~iUgr$Ab+~tzAtCJ0yHI_FE!ffvFQ4w<>lD$EXq@F_2g9DUCDiLY+rdUDqpDrha@c&SPEgc
+)gtHWXI}YWMx9yM0Y#U9t>yi>BWvi@{%G}`4s5kAB^!(Omw<}0>26<vEH5;tihb@*63Dg@deZ&!n;Vz
+o7|5*|B-1TUm(fQ3m2at%*ryeKMR$4PpVRurpI-X;bCBPr}^!fr>feytS^2QhXI)?SA)!G7yn*|JQk?
+^?!Gm)X9x(A*y^=6>)WC-Z-lgClUQmzTJlqR{9eH|<3QN+KAFJa~gMo*MG{@@OxB&Czj;-Er^BNqA*7
+LzjBl~I`t?a+0Oljp&KlS8Ewyft6z1k0N7Yn&iP&7(pAc~A7A<Kb@QveMUT(b?)F0GgO3gCJ8$bAj@+
+#VegOAV7>NqC!>M&5dW`37rn9=>)R}eKES+H4aTPLfLds;0IHlrCm~%kpJ6oz^iAQ;j3r9BWr{kp1SC
+Z1w5`ct3o5GOI-m^>3Ma5t{UBKq0Fy%eZP~(V^DMki4*X(Dx9gC;xUaU$&!4oD3&4mGGrhgbduDH#`?
+vXM=jY>8y&n*azQp(B-cZ+$r!fk8qpJlNk(9M8g^fw`qvTpl5)89&BvX?DHU^5gvK8U(vlaFdAUB@HB
+-8#sQ_Pl-gZB)A%P0Yo+qfy#@94&fUMmd_Abu^?nG&2PfjH%txW|QteU5=GW)d%l0vB1+TuqUn%6$YT
+NRnJ0YOOd4}BN$uHkW-u$8~Z<bytNjrzWq9<d4?AcX|O7QTY3Y}Sm6+R0QURY~0$Wp!7IwimVA2>@L@
+iRf5V>#WKOK+Kq}I#Gshl0_Y-@Bo#BoxI2TdHv$4_iY$I_Sp`(V+Cd#)EHAoog^iSS)PBEKc^tL9aqD
+cidvIym#Zl)5Hw$mFS68+M?M?yx8UbRIV}Ce1K0@=1x}TINc+ow7QVf^tBK5wTMoR4CBj7G)v3NTGNn
+dAQG`674Z&+^Ua_(&8L(I1tIV|p5Bbefi6+wSwu}m<U-xAm0kh!pmGTVzE_Wc;8k3wo_NiW9whglJP7
+(p?DFG8Ph5I1)S>Hf&mvlOXGj>ZQnwO_@{gglxc&@pQW<}2Dqt>cQ$~fN0*C3x^g5j9=-1$uR9MGFj6
+|F|gbhYp~`38UjCI03w5LTB5>_$wX<IB|CkQOBB7|qqsx=8eVdVO=c$;EPY8_=cb`JWz@94Y(LlLwz;
+895VVA{S3JKug*@oe$20z|;huSqCkhuAXdPk4Gl{wd}tJ$q`(Q!`m?Ru_v@qWrHhGPba|yCc-aEqk6x
+mtAebLk%pw)ORx<w&`#mXUwHr-i4@3OsfhG5&!lP^b3nMv4iZ~DOqOt1(lYBXRLXj#?r<me5CJAXC^P
+&H#CIHT*)YWOm9BP;tFHvbROWGXup!@1gFz$^@ICsq{KZ>5(MJQg-vaK3MbPm_!YeblLAPb|d1)`JV;
+nua)Zjl)sCbX|^Pn5iAt1im<;4aIIoaN@ZtNZ~{?1pS_;ia*Joq`5xqfi(AsemnM<xFG4ue^ZZ<Y9<&
+6pKq$bS9R{W}csH2#+oA7c71K9OOj#y=}D{+bhSW9-BF;oW--F*RN(@xgt@@fiQA#J_wkoF9}JJ!I!_
+jJU7EYchiB>SW^Sj<9%pg=98ISZ_&EYj)ruJ7CK(MsOq*dSk^`5N~7zlO?;x^WJ%Tsk>jw*=&{Snw5k
+K@}cnP7p}|}B4DV@cp7kGS9luwBg5Nig6%{`Keb3{jFEQ(ts)R=1yHL_Rs8Ehe|{XRj3xa($SV9~&Da
+A|P>$VH8zdQPKS)XvZSg@o><E07O3uDaAT|}l&R#$`ZJMstt}7}HwLvXA5pbvf$kH>L=$yLWE@jD;-f
+9Ue9F0G1QQTw&5eh~qLTovpE$dmaf?VG~*Hm<zQ#?p~iYm*|XJPu*qq3gS9K6H9JBIIQ{|@l=RwJbn*
+ioGt^<sY*W)3Qb+1`3=+NW@V6|08EAti(;Qomk~Op;UhO;rz~zK7?f3Tg{=iD%-oNyHn#E&aYV3dAMd
+V0BKvN?H!A$qRuVZ%(%J-eE}&ojVPu;;_fBbD^CLIFGYJtY9ned2c}6htZ+!+H2z)T3#01TaQ8VOwTq
+ZxxYl-B+XjE7M`jxwN_L8k!!3x^=}am;;j;`L!2gihyc&@0eZ&Zh~RnDI8Hkfg|4sRnYl!xC+1KM`$Z
+i5cC!;-YTFn0hWy(WUudmBm;9%Upd~fo^Wr4DvzT^s=W#gkv*@XCH-KaH{ycc-5LI;%-q4FPW-$0vJ@
+t)~@3lIE?m3L+G|`mtz`Ab7^T+%9m${tNuRtHCKWy{6xWK-jf8{sf1Dox^pK~_a9B~f}twC6~lyDe^X
+@k>u9)mc6c=sV6A28yAH+MjI=;Z>>@^dX_zT97CXLFe^w3Lzb>t^p3escYDzoT7?>%_4m%c}A6HdJ_%
+_6JQG9yDoj(4?tBlQsrT8W%KaRnVk4L6dd_O&Sn1X*tlO$v~5~0!<nTG-(~sq**|d_5h6<0x-{)S^zW
+w{ci&E-vrpd36y^m@ct%n{XRhdU;pqwP)h>@6aWAK2ml;P_EzJ0@440i001Zi001HY003}la4%nWWo~
+3|axZdeV`wj5Wo>V2X<u?>aBN{?WiD`eZBol_+b|Hk^D7qYg=`g}X91}Xg#t8%8z4E_fk4SCM~Nf~6q
+VX&`|n*+5893i9Vl{Uc6PX>(GA#RSG9Ynnob)F-&I|!yv7LD$`&sXJao3wt*Y4sFvwWxcyWe}eyy@X@
+35cg>H6XR2V*RI#3yS=*Q>zosJ7{?c?S4IB6~bQ<L`9-iiP!zA)m_=W8Q8y=VH$h%rXnQYTxx6?jS#s
+bleX)%Ti~K6xV29^zMURC^gCjQM!U=B<T_q6uRlEn#5h_Y=<RGjT`K0RiI!%%i_T%P9yTa1XDw8vv*}
+G)zZxz;~2p${L(Fs&`FI<C-BiVwKEwIhKodOpFXdoSS9prZ=~?tzpl8Ht3-0?nva--n{Uoc;wx~@A4j
+j?@!+0}GV`Wmy7j0%+R+MC_0Je*8J$%Yn=JE)shOStf4JlF1o(EiOTVT(0`AGn(H;M{$WBD!%@Q#kUk
+l1l(*;gkV5k(AP?eWlz`94eW3w>q^zul4){>JkJden&FwW7mZ&gG4;NFYGd!vW07jhw5a||kO8MK3GL
+!u(c#kKy8Mo0-?PNNZL{FAVws|lT<gAqIw*jf0A$J7{Yu9^y6jyX-oVG2b^E%Fm0*?&+=0|XQR000O8
+97^_9L+eR2FarPpGzb6yA^-pYaA|NaUv_0~WN&gWa%p2|FJEPNaBp&SUuJJ|ZDDjSaCya5QE%Hg41V{
+o;B*gdfY{D;!){2OU|rU91DdvIa>ET65U92st0!BTEZ4~l|My9<>||+sxQ7kXgC&ZTzK^6#POh)!*O%
+wZ4~yC5a(aC`J6pgA5JF#^;Klpv$>Q_PIV3V=V<$)mj?|PAi6Km|$cY@GzZX;Y4N}{=+%htDDl_K^A+
+mPvc(jG8azKrcGcJZu#axh;;6)bIr$%vy!+)C%x3$@ADVw@>0^i;q_?CpFqyfg}mS8Oi7^@MAc_!T$r
+<84nGm<ghKYCB@@uvdjILl$iGk(+$d6sjA^ZwC<7lIN2SEM}Zr%IWxaY)cO2zf-tmHyU&Z-l^CFq%dK
+tmqgXDqfB=v7wxQx;Ttv{;+~jVdWzvXqdQ?h?HiSA$Xvqe8)E<G=KqAC5>cKLzNJ^N@R^-ld?=5N~By
+5eZMSAuYBoovGPv_gMqKEMb`Tlt_v3=BLYhjK}lr-w+adL$=n{5WFrgA=r`g~4z6pD+Rz%|tqomB+O+
+AhA5TD2Dlkk`G|*{hk&AE$jE9&V8@*P$w`5f?EKslC*|nn(%CO}YM%jJtg^U+btn7&w^3=!oc;hpAm;
+150PY2(B?VWf7zvOXz;va%|W*hYsSCL|QjI8|Ap`S)R07kvjAA@INJcLZ!umfFbl0Af1gF&NF5B{g;;
+vHwvuT6wT_zhX;VE<<d?v(vA3HWO-0cQ59BBNgmvZPV%s+$GfJe!Ix6Mg7P$RPvu=c(eROXt%5;p@%L
+hS7|;iRDsh=_xC7(*qV1tC`?jx;R(sA;bk^t|=h@;e@1;J$_CNu|MBD!f7M(M9^BlH52wDqHO`qEAC2
+nBSj?6ZQThOUEg3;sAx1o`y{nuS0cw2HxMM0perSUt@#>f)zQ{;*_2NNP1yD|T|xCNxZk2TvI%#`xFO
+jn!bI?tSj`HgP#r|Svk@{&rt0nS4rf#MVJB_t9s=Xd8f&Kd(f{$Rr#<WHUiZs8T-!Y!Kgjk_Befo^#=
+AwJ`-JULwmDrbmeaG@$IH*ULzzCYD<qB0<nnAjKc6peZqKJ5|Iucqap{iZd<RfV0|XQR000O897^_9N
+z}L7n*aa+2>}2A9smFUaA|NaUv_0~WN&gWa%p2|FJEPNbY*UHX>V>WaCv=BOAdlS4Bc~zCT?IM2Vi01
+1-!zf4g)j}?W9!V++IM4i3^wS|2mZsEGOa~XiTC8SI$LIw4sA2*g8tt24NRo7I-4zl2WspDmY)@CL9`
+o6C}lc#0FTv%N(=-_|RbvY~V@#GotPzo7%10iBjzrODkF{`JrACX8AZnJQ>FL$8U;0+|fUNB7hT^x}#
+ug*g;us=&LTo8&FFF1QY-O00;maO7>Rm!NV4Z0RR9W0{{RU0001RX>c!Jc4cm4Z*nhkX=7+FUuJ1+Wo
+~aSaCwbV%ZeK@5WMRvirI??X8i$%1WZ`MUe=K0X3SU~w`^@>^&s_x4CLb@$>T?y9MT~4>gp<0%LG25Z
+OtG<ptglQ^&AA+dloI0eN@Wi92tA-510GbRfA93IlXhFl-iTQfuuFok>^>ST4%r0A|<Y)giVd-kFZ|w
+3vcXcp^&1gs?Q{tKs5@FF8c<$>v-^zISmK&%)yPB-qDG?(7xn7XBP18ojQqgRmv{IA)X0xT(w~Kx~dm
+g{)L-hUnp7N?~r$L@$E<m6bC0@Gbx5O&_A>-CNxMQb8bH6o<cDXCSB8hetE9CDDu3x`nO(hnoPEt*zh
+5HsYSxg$OhFJRy8H3E|u&}N<?bdowqq8jJHjWP@Z@-{CY<}JL&~5WlFODL_J}9Mr<?9p1WacfR3pxlG
+Zl8WJJ(5=5}eUzP^OO;i1aX>DZi`EXhtA<3Q;ktph=)5g8}#$N%be^H5xlS}r<g^%kA>MG)bAi0MD?c
+*wtclw*=O|CcM-JN3B#4Nyx11QY-O00;maO7>O*fA@ZL3jhG$B>(^%0001RX>c!Jc4cm4Z*nhkX=7+F
+UukZ0aAjk3E^v9J8eMbSxba=T0>eC*yz=Per4O26XMA_=H8)M1aooP>G&CfE5^V}(2{N{t$$#(e0w4j
+B(lv9OL=u7B#eQQKaNbl$mSuU@c8$m~Rvhc9X&K+Bs_a^k>G#FLj2BYXV%siqL^CfIXIly`chxp#d(q
+nOyeLJ?3bie{QuyOo?K&J%#a?n;RMTotbs_hb)QvpF?B}X1fqYTPn7waB!#9X`SK|mTWA@P1IPh?);q
+zY-Mi-h^vaKYrFD$iRo2sj0b}!^kQ$dsgv~8-=f(o_ewaCmUeD8!ZkcVP_DB(YFVxjLv-TY%1Hh@oEe
+R6<))2|<j*FqYInoH3y`3Ya_L?hbv)X&hHnQD=7JM(}qc0#=NCU}6~F@2JVi^WdlEX#{VwOP#@zHfMa
+2*EZ>rrIWAKmHBBmkS0@5Cp%9mbC}L2!Ztoj27Yy@BkXjlmIN@^dK?I;2%p72E=RH0<9DVzsuic5D_d
+0(=~EH0q)2t*n90pp{uB<=jjFzt=(8#^-jm-iG4b?hf1=$%@d3y3qrYR_DUn;Q*EAD2;LMe!Kd&IQ3o
+nX4+snc{Sf4fS!G-dkRE6l5O#&COMYV27qqP5p%JPpLE%-yK2}n&P6>2mk+5Gx&S6R+Dozax9Yk5Pa8
+p&Kx6tQ9^}_P5EHwZbwc%il1}wrQd+NX<BfI#^{GFG|S?4G~H#;@6)UDL6q=kS{R^@EV%MypxMWW~dG
+Zb%1RT(oO2-99NBK6R84yC#&zVKF@(}bPoEs)wkBEn_GzK{~L#7og0Scl80ZPkeAGS38fZXss@)uP{8
+^1G@-Ee)$&Tts2?%`8E=bXbCy^?`3hTcEm6m-GYkXIX}+f#yZFzVNb})3MGhsAbt2An*Yl9_P5in5Q3
+<Q?f!9ZI*?D21J?1Zrm*?i}xcx#D1(T`%J#F`DzXM1A`^@f@R5&eV8KI;<1CDn?_gd=TM4x?0aW1$>!
+%~(b8w=f?>|gkcwyKC<CL&OHYs9UXzZunK1H!F~_B-aer86wA5raNKrJJ9r?4!Xe<PjfmD$b|NXn8Vj
+yDUF}2~Or5JIInJXou`4a;j^UI&6tdi>F0(?&Kht=&b0Mm?&C|Ty_CMiZ!GN3=910dB_a(vuT6?u2>)
+nqpG+Cg0q9UlN3cS#*RTJQZ%i4TorkQ`yH&{H&w`PMKN2~FWdlPI)J)BS)gsA#~)7vQ%<8Mma-d^BQ;
+_M3F#d|}V>fME9V0ng0}O|d;dRzNzWBr0x}V_X_d@}l*%Ky_O9gZ5LsorF;odoZ+YIyksLyQvyL0)9^
+b6hPXBy;zS0K48svJ4p3u_%>$moFyVh7^q&ezDhM7Ao)>H?KE-*FPE)7x4@!`59Kb)!D_rWr0*cj$q&
+F`eKZc3a^Q#T$^OEE<$y0<x1w&@ztN9xo2F_mPz%B&NumiZ=HVGsV>nDz3nvwJ%~oVs;%mM1S^!pUGC
+wce2p!-}zu<?0VJy7+Onk)yi;++74KpAR6i_=AO6)L(Fg+f)VzM$TGToDiWS_8?gOF(LLL#ta_qU(^n
+T$L|sX=6Gw#;yh<__^UG&I`jY-MR7124snRpu?_5l@g_@m~?<L0QOWVtRRf{dGj)n?t`h@7Zu3JRllm
+`cKD8BMyCm0>KbiVW1&m7G#+P$+AGlfP?;qz1K<xt#fAEJFHv<J3__05sY#emT)fz$PbLejFmNVifdO
+<R*h}~^tA=OQeM2GCliF@$)%59L0W;jPUM}Wa`z%Fu1<1`9^ukc;v6^udYbft4BaC^*^ijBJsM!wubR
+#`21?C)$1$TxBS0rx5ni#Ym|bO85t!OfVxct)*l6l@KCJH>lZ1zliE&>DCm))O+~;=Nldt^7+RuJ^&X
+$&a4QYwuW}FqRII0jom%6E6QG$isy4E`_jp-s5GmCGGXK{*Im<gR6Xb+D-^+;|mg@yeVszGBUkYLABh
+d~xZNm;$nzB6K!=OVLVfgf4F6*xT7xdrm=vuJk#TeM?{VgIUA8@Qym3*a+JmaYU;Bl|Jhb2P32bn?8l
+3o%H9Vw&Dv>PC^ch@%5tWZHVO9|qk~=~j&Dm$qubi^#Ar4XG+bNG}!2s&$LDiBS=81>dw`;y0vc8aBA
+vY|yeP?AO3{V7&G00=C}&(<`_O06?ao9h2F%>Lg}cSLPq*WH#DZh2*lHN5Kf}<|95lY5Ee@7lVk>IMP
+Umcyeq<@0mV8O7+=MvTurAII4ocTWT(MDRn&29C`u>AaB_nWr!ydMSe<y1~(UH8$y@{`qXrS38O=6=e
+0QFooeBV?iIbu`Lt$fjH<REph9g@SPyuGB3t`Sn0-!#D0j|L<@~&x)U2hb{q(CZJQ;Dh1Zy9`_+p1Mv
+*kabTx1Xc>}F4;NJi(bqf!JLsvx?A>(&T%c#5E<we#Ph4BcRXYmp@1+tm0{>s6?O2q!G)a}Avm3&<+6
+&Gucf6Dp;i8|snQ3<7iC9@2Mj^{YOsO8@$Hv|-}ow-Z*KB+YzV5zVmbD#QeM+-F&{T|vN8tV~jrYuq!
+11U}OdgFlrCpI#KqJtqGKXsx-Ns{2R}C76<((Owv^G;m52ft7_C7bX*@7q)~y@AWUdp>x2rS5X43-YJ
+~Atby!{>46zsWhN+0nhFhK?1cuDWR1356ird_(x8x?(;yj%Mis|Y9(S{{$6B+7n_mK-Y`*v(r9<*P&B
+YuOV<KRLc>}nbvL=Xa^bvheajElrMsd>u+u`X<Hgz9!esnIgo{`sCg9u#oIQJQ8DdBYuMK0cTPz>pBs
+fp^?VKa_45@4Ey)gR(ay&4ApV5u|A17b9FDtxA99+8+HI!)F0=Y0iRI;WZdV!G~{+Z-G~zbPEmY;(Aj
+Xz{))JM!katEZVY4^|ttJ#o4II->V&b-i8{>!HpMRipzOVUpD~%mp*_?mNj=oAv6*_poE}wXr5p3s;D
+~aYmxm^=3``h(69&Nia&M{sERB3jHxA5X)vxul(-HZAxxm+lFuT^<aMwh?fT3UaQ5>7FS!LAd*_z>vc
+ncufvJT1E3o)#K();LbVFxg|3fru&eDVw8)h*TREqz;GxCf&%}Z(p<o6Q@4PEZu=ZnrDE(-Idvsn8Oz
+I0?B4DqA>C!hDqQSpW#K$Pm-Yg=w!`0$mjJ1UB<j}j<dhtp6CLjVvPhvNa8m=12o1HaYps~xr33th?`
+Amw`7xSUv--|Ar1E=}VJ^LHcvseB)Uzsj?zRRPl9FMM{F?T(!CdbWl7xM;E-*Tg~8@cejTV=<l3h9iN
+{xo1^ofMBKuuosRXA3R;4MCD5>;B%^Scxq0;r`BZb#O`Z_Y4?^x$6MnNFc3FS66r-Mu2^PZ!~h?$~#{
+JUa`~~^z(*&Onyq(3m%k7#K5cNN5JmS^3hiK^2q3<Z6mfEVIcN)l~D4kWiM6pOm~?MRaG7J6}6&EUwt
+kI4MT^=a#~n0GydRuO}^PCH$VOS0s7Rzv-Dv=&&tBF)A;02O9lmRbjeT|SEdkG+GZMnEHwNXh?AbIKK
+~ypp<r~gj`e4e7Z6Z*Qt}<v)3JN|%8%eIPT)RXlH<3}cOQQd=%`Kf2zCGljE){xS5K;v$xhEE4kRA+Z
+Mvd_Do-UwjP;`@vLUh>nu@EhR_n+}ru9w@6sbN4qHoCzh<B)qKv!O$LV%c<&qbED``VbbP!<RrD64V}
+tG7?bq%oP|l=ZeSG|3{%v9TBA0eJE^Z}vw_=#OYGG~&MaA|}QUQIxTT<FSb&x+1{DsvUw>Ax_6$qkA=
+l-j;Yg^*W<N^fP)JIl2?^CboO*OKO@+&;50*d8b31#s2_MO9KQH00008031s8Ru-$~8@B@h0GSK`03Q
+GV0B~t=FJE?LZe(wAFLG&PXfI!EZ)aa}Wo~3;axQRrl~!A;)H)P?pI;FoLMyfEn-qFpHr`NFWCRao2-
+(wgCYotVn%R2~;(vD~ZPN61_MASHCi(KMZ)IK5O34!{sb-p=7~-c!D(%Oc%B<>3!|Q`v`=FVkw}K_;6
+K{2bzBHQ4nu-K%|NZ)g+`NBt^YO#ycM1Al!+e5ns1OFf*>r5FW)IqtZQ(ny@9m`l2(QL0*#^PW?c2+`
+mBMSh>4u5>_{QqeDI2~m?ZBbUoHyRddMnk5>MgkIq@vubE(&)RyH4j0{MZZHw&;^QbapzCC94o2yylv
+a$j+FjWui)k(NW$LLzbaiDFxWssxzCc3wFnZ2fU@Cogx~lk1Gs@oK)7MtcyU=YL%e5lRMapi>D9h>5m
+;A2;>PIP^@9#c4@V?E2gYYa?eX6#$`dlYi*ccceofm{|9}RHOodPlKO)HsQ+GoSQ`#w2MZu`91df?$B
+^Je02GYIum!&XzA!u9790Y=gV7j9AY*hNd4E(konV(apG}ZMdx+3_4)tY_A>1c^5Ip7c9)jiywZO9q!
+Mh-g@-P+VQ@$6sl3pJF-+4A?=`-Awy-CEti7vZ6InXXJ@S2fY&hu^t`$Zn(vpI@wGr&Wd`ktdH*ix-)
+8p9#B6YNrN@l|!!&DrFiolg&nmr+B@68dT$y-d)nIG$ir_R!F}?5oZ%LW3L^(4aWj3(RCM#raf6t-c7
+BV~Db?1RO6@bs@Q)%i?i@Y_8|iQkXdtkSGd)$X_KWV1u%1=>aks$vdVhA@6fsNl~t;wH0qp$Hw-0)dn
+7LDtVvTTdct28v~mRDR$SMx+@{m0o<olu2Rzj)5Mij6pwbUHYc-x+P+3RLDIgjuqeR9V`ZT_Qu4MD^f
+ERSx#h7i2Di>tRHleMM+(JNSvNyT@l^PnCZD!R8{M_WJQoI$Oli|V5F;xHBaEIwpQ)p%tvJ5M(SUD8F
+auAe=Q9VduDQ^zS&cWFg{7beMM2At|9`cZ8Df9P`bfsh%g*x5cY|=HTw&91QN`hQdhz17Z@z!94Z0iJ
+BZrPZ;+p43-{BW6jx^y6&tvkqa`RO9cW>uUZ~=wSBc44O_AmN4Cym$Q?G?w<Yr{4(Kt|8t6?8AA&#LY
+*8~g7}NKGN@h$$#c$O*14LU4xA6VxbrIMEE%68aJ}+2N<S;Y~{JK!Q}M;``&uk9MbOZ~l$Di9T2MX`|
+rsjc_4rbSutm_nrwMp_l(Wx0+X%94me}YV6=p90B;a2L20BO9KQH00008031s8R=N-B9wh+)0MrBk02
+u%P0B~t=FJE?LZe(wAFLG&PXfI!EZ*OoeaCyyAT}#6-6n)RHxb&%o=?@spN5N-{FQb&q-qt{tg!Fc<|
+K8-L+v-qsI>fw`+uZZPIcdG!0*y|Y4%F6JPw+tK<woNI%E9qxboeB_5GAY*L!OmcA%tkK1#PXXTjhJo
+cTx}7FOMASvMS)_ZZ=2C^~PEqc&lnDAe=1Ac!3b4X`n+h4M1@nUKPEBq1Cd3)_PzqV6EGLWeybx>Led
+r#%VHB@HP1{X~n}AVawp2@)<C#;{F*O!6R9hTq$c#SdTP#!{ew>H&FT^WW)sgHyTU=%FJDzC=%{o>i!
+6v1*zqq<rt-Y5u@|CQ+DX<E9H4%a_{9ocXhg+7j}j|f5|_n;VO?huKu@L*w~75yQn7yF21Piz|LFWFL
+C1ju*)}4O9KQH00008031s8R<)@eD5C)Y0BZ#R03HAU0B~t=FJE?LZe(wAFLG&PXfI!Gb!=>3W@&6?E
+^v93R84QfFbuu-S6DrP)Jfxtv>hgaRH=dsJ5^N_iaR1gf)aPYe*KaH{eWquIW@_9&(5>!!stEF`G6M0
+{-6!P%J3Z5Jm0O{X;576h5EVy;$;Leq2X(Z*Dum0f<#z~V0j>+6_*iI{2<6Bw-y$qlyf0*6faXtCL2!
+!aBG7F<WgH4S(L>XUfyA$6<#j=IyiDrLxtr;=LWmhS~ggNR2l_yE-f}3gM3plB4A8SK`4SZm{fe1$pb
+wMyIlXw;Sr@!SVxs&FKBpVuVHJEt)q7}yy2CZ4@zm)C|Sf^EuxFU;zh=9k6TnZc2#|td%f4L+;B?>rE
+C~IA;^>}=hXOT#g9w!)>)~eXV0d4G=hew>si>fzuHaf#=kUiU%$GB!xJ&qMDMFRV=l63Gj2cF-<9_0Q
+5uHXxUGTeUSxSkzt0m-!sl7vSI@3@j8V&f|6`{g+~Vw%V|AEiZR|IfWxHNoXh-!nYuf7V`Ey108eJ9a
+S}SsvPrcF4^hY5}yM1o>6mEPe{eKs~Ox(m<d?pE-$H~k!X+8JG!7ort0|XQR000O897^_97ok@zg#-W
+qmm2^89RL6TaA|NaUv_0~WN&gWa%p2|FJEwBY-MzGWpgfYd7YVEYa=%pM(_PA1ieYXB%ZOy@)UZJlF$
+Z9x@-)&C?&YDHyJjujqUCJ{Ys<J=X(rG!%C3zYNVr4p53hc<*@ruSNqlb=5*Sq?qk0@oYW`x?PxUmNi
+A1jH(T|^4tqPD_Q#*EuQ%JP@7>pKzgc&ytKH%C+J1L^^YD28yg9zC_M7LI-Fl-gp1SRN_x-4<iF(<+f
+BV>8j-KuxZvT9GeExLv$K7&yr+)EkU5u3Z`m68l*F{y2m1~#dgtpqCW~`=Fjt!kxrkmw>YDdq<YLeo~
+ST$yfx>{s|r)FH;KaefiEG#n5)OEIIJ((FcblF6eePZacC#J?wn>{V&8MeD@7v)y#nb}l5vzwYXnULL
+VZH1bQR|~@?RyJGJzOlNR^<6%HZRdC0Q22XvY0uo8`rAewPpj>Eby%y__So4I+#QbUqT9Z_e_MCkSM|
+@Kdwn~pe^-ZYwLKj#M~};!hufRaw?A;Y&NMrfN&~dp(KvF^$f0gDO<G_-EsdsvUCg!Y4K|1^8A@U_a6
+fl(nql&ShuLX-QRt6z<W940=I#vD5cbjC{cpc7pMSky{?GHO7kpkl7b7JePNrVatOfS-mZRG~JFep;i
+zoUw1lEr83k7R>`4Ufl{HV^oWrtcAR!s?NfOSPsEZxFZEfb4dC|B>PSiWs&{TBCb=7b-oDJk?+IyfvO
+dMqs*mKvHgG-_zp(5#_ZL!(ArfkqF7Mo*=N!$PCSQo~{X0migQjfOQE)@WD*a?wI&2iDTS!ogEbv@q~
+g3W#`kC>0<e0ZR#pNWfA<h9poaLNSS4s!&iO2N@BSKtTq=5;@2~Tq2h;GBANk8H!BgQiehkImn3E1PU
+?`oX9~2q7!-XTj3PK<6(<K3zL8~;=&_f&=3&{6ht6Ik%J1vC~}aIL5di3C`w5IgeXi&fs{m?A|@pWR8
+k-%h*VMlB^j!SL5X6O6hMiBl@v%xL@Q!af^a1TQi6CTg+fVFzBJ}bbG|&*h)WTVK||)tQxKti1r92du
+fRbD@)a=XV7_7jgfL&RKuR)S0h1EtD;7wJ@)Zl91o;XWlrUeh07{szSRf^tuYgI3@)ZlDMEQz^;y+6j
+<jcbrhZZscYs7^}z@Q=W6)1>6z9I(|$XDbbBl8t8=up0r0tivQk^(7-d__!3kgudbN|3Ll07^1n5rY!
+tD=B~y<tr(WlDujNn3N!2Nr99gUrB+lF67;Z%vZzt@>nA-Mfj>@*gbhbzC0!q%9rQlLiuVqUjc&-<|`
+IJ2=f&Sq$KkdFey>KVu6$>U$H>fSTbJ$gA(Q|7C;H}6$|HX*3MkzkrL%A7D$Qmb?#1YF;@0Z_HUiNmh
+4+LgCVY^bZUreDV-VOT1xFF6|SXpZis6s)rPp1$y(LErPO{l;aawfiQU4`WrcH}f1JIPt?Ukcmlf<Le
+U}y7r!ua~3U;f$%YVVJZ0PdS=#Rp6S)u<-X6Uk$vYYl@{+Fy}Lzfl$gB`l8U^nf%p<r+A{{v7<0|XQR
+000O897^_9>G1AM;Q#;trvU%}82|tPaA|NaUv_0~WN&gWa%p2|FJEwJV{0yOd1X*RYQr!Pyz3Q%PjP4
+hx%yDZrN_4PT1ruxRU&F@-IZL(?<1|{CeQ^Tu`@d}S|>apT}B^H@WaTG@G>UP!S=?OBRP!z>-+P-+^^
+QZwx1|=e~kCi{%EmzM0s@vxtgYV%_B%>g7Xp+0*6gLq$IFFC`}TS(c4T=-L28_y`17KRH|BHRYuzm`*
+1;+h64%MsUF!-B%h1^Os+z2YI3Kg5%KgtQkK{*(e<`5lGIr70nM&B3@nR7{=m=Vg^n}bWmEz9P#HH@?
+-nd(*Q7yjXsNmlWtqE%?p(XAxdKp20|XQR000O897^_90O^-x)CK?mU=;uW8UO$QaA|NaUv_0~WN&gW
+a%p2|FJE$DbZKucaCyyGTW{Mo6n^)wI7l8QZ;F?$FM}}`E7o=>P;^66U=Kl{(h_BJl|)UH;-tTR=R#2
+zJ8AkbU<TS)BG3IhACGCu+BPk?d$-6NTSDHbv^BPJU}WWue<91IYWMw0s!btp+xyy7yYODQHimbG{{N
+#USyjYvrT^)4mFmU9<YaDjs~d-FiK%i6FE$W8kKyO#dI9)3q4m$kwl=lJLKjYtcGad{CAYfDY_k%HMB
+lZ#a^oO+VSsa}8?`Id8Y&B^MJE=EMOrB5;B~gsQNPnWa&~t1vbqPm{adFkw0qS;rgKwi2dV;%5)ipA-
+Gg%QPTkwCU9M1O!NSgb(d&?cYg4s1uz~ls(!AU#Tv!9X#<$P-RcR_yc4Z=x{mNp2Hf4L#XlILC9ksSq
+1#gMj4Yv*%zNSEKmT>Wci@<h6G_TC9$uzJyxLT$39USU*`8|6ai=`L?%q9-Sn6JvUjY5TPB_V#?YiM-
+aHI>ewKx<%ga!T*8y5RP<D>6`723<{d#H^{Hw2pzIT?}1SXiUFp!8le*MRU$<i-~WlD6jx};sm_04XS
+gk!nk8VWZ{lRgTjC9!AfRW=fNOwRUZ!rO0NEN30hJ4FxF4(-6!+{o?nupitSCqI~a6hD+Sy&TD7_%SX
+2_)3f@)(Fzguer`@Bj1LvUBw1@DcJWzU2@jB~E3sZ|pdvLN@gbAj3VGq3M(nh0edu?|6)|cUBvvX2n`
+bd@|%+PWTANir`$}M_|5vO}a{$Y7mL4eZ)5u-)Gv*vDaoHkR9;o>cR;H->{4p4*lCyYUkmEu&Bu~iR8
+{(BBrz8u_8xRH8<CGK@g7}#oTJ5+<^(^=>(huv`<u|BD%2rk7IsWQ@|?nazWdNM=7z-!)xzxD?4rm)#
+18+(PM@?DFjG1;jq(yqW_i}3^RWhc=ByD}u=9DYZq^FrS-f<+tQ%T$@Zqi9OSWp*02D*X($VwiJ4gt4
+Hh*O7=03^pv$Ct`)t{>#Zq&RxNak#sKa;dCGpG&Z=7zL=U9ohOjxR0pv%B^41I7>hnPqd-6C68n%yT9
+~9qO4!nb4I7W43vgW-_2s%`SH+G`<lqH*Fv$P1fy?#8!E^KrJB7|H)G^KXWTQ0jEP0$j!OocD$f;+`d
+GJ7I4!>C*Dd_`<1LBSnJCPaZ@3$USC;O9hDIsH^Q;fjc%lc<bYru3g3)*Kc=7dY6qDw*~zmvh~Db@y;
+my40VZ}U-ucqRlUZ=pcsq^74>JVta~5Gpv6%)dlmet7`-fYsB!tmm-oWB(pTK_Nblin%^27MJCk&CyY
+OByl8wAkzoP%^mW;kE5Ui>{b;fqr&yfK+^`M+QI>gsc|>9G$sHK2#&gLY>Ih0(!a$c<nzG8VYC_Szd}
+Z6%(g>Y0prqb#3`vQYn*k+6G~)byDFo0(M@BUnWig)homG~$R@>_*{ZmwDuy$A<UgI;asm>TGCfyF2l
+}227kD<2)xuQz1PW1d0@TX~+3G0>=<66yv}fkFv{`f#8$S#?V}$<KP;mr=p-6I4Ih-92G>5dP)D5YlT
+*_o8j6;KP6wbxC=eOxNmvyO@)*X*@yoxj3NV-&agwyFu#9^n$uNIHbeOPht?l6mC8Ee(F4o@S8g~#lP
+^(V|0`+kx{9T{5~h6+&vLjq9X<$OjArh2J9%BkEtFBMiL?qR5Kg>45Ve)XgZS^N4BbL6UnU5C_+57He
+-t6`*_&NDu8Jg)_R$XN+`E~khbd49y^*Z#;5siDrxn*kMxDB3WW%SM4Qs;+E1-ZTW`Q78dluP5r}=dy
+>b>xy;+CJI5sRE;!~;j`>n$@8LbUmuQl-NW*sz<Sg!2Um^n2j;YK#4qNjeirDEyg}}cf>9<vv4;IW5A
+?^e-r1}p(M00)#n{Gl-(2U#X1w>*R(1xr@s~$<e(b?=%psER31<u@pT-+<zPZsa(XbkRk3Ps6;qdwYG
+l!4!0p{>O{7w_cf5`?WA4)I}aY_+1o}ZuyQyq1Z*Y_lfP|oS5op)6XXIJR5&3jkM&e4w@TJzTzk5R=4
+_KC;eW2|wseM}&u1oZ>=kf<aqq1MYAZ0tf;llZ31G~VBTJ)$X(g;`dE=#-egg^tu+6vkh=9{XlCI%bB
+cg_)kP)APqk=6aNho<M1yiH>Tx;H$hOsZ^<x1U4HuOA^wPBxj=wIvkS~U$E(L9T#2+(0(1B>CxZDt%q
+M8U%5yN4K=+?8<E2NLQTTrn>0SuCRc0Eo?&-fzm7;h&WkiM#_-tVjpVv+P=Cbj=T&22{{>J>0|XQR00
+0O897^_9#xbo_Uk(5O&rJXT9RL6TaA|NaUv_0~WN&gWa%p2|FJE(TX>M+1a&s<ldF7jJa}!6l$KUfQr
+u1e>u5kz?Avd+$T49S=b&bW9Ot`5e#g65%J-f2TE6HKmWve6u#x};!p0UA(=^677AjB90h9smaA7J<G
+zTEut0X83DyIapQJu{M=1+sujo;eS{bNY18bhk7Lg+hB0BWgOWWU`W+QKW&4HvGY!H>G4s-IpyXKG-A
+Cf5)P|Qn#8^(piO{cW5JLGV0(^PTHG%LrSRWe(IjkGDD+T>DO6)n&oG|861|?RC`hz{vT;?t%8Z(;H=
+|HW?0Q;RV^*4S!qbgD1B$7!Hk^FDgA9UCq<F80Vz2oX9krvDW^$t`iwL}Q=<-AUrtujYI;zTr6kRX1F
+3axh@!IEK<+eamz?gG<ZM<;sxoCt{aSK#SV`yP9E&-irj)F-H#ek6p+w0e^ac;qugED*RMQgEm(|i~H
+8-S<<|NvfTt-bYP8&5!rbhc&E@gE}9ac+Gm^&|6mV!BRG)r5<a&D7`wSIMg{Z)7qM@IWnYIdki>Q@=Q
+Z!|}RStjHi(8k*HmX?vSN-D(&D$QRT;LzGExgBf92rF=|R5BJ{Iz6Nf*SCn4YhW~!rePKC)34F;wQ(k
+m{5vI?V^ZcaprumUY1Yi7mhM+s>q>*9mulrc?Q?}Ut2jK;T8?I2%!KvHNVT&|s_c+Vo6)C~>ZkOVD=y
+cxF2l0O=IEGE<&-p{Wq8<PPgh&fUQDAaA|+x+dryYr5h<FGj>lskMLQ#%QYf6D=b<*~WVE*{cA{6J7V
+&UT@5fT?s1)w`So+^+PiLDH`TyhbNFpJ{;!^b3@$P7(vsi~{Pe=EO&S=kv(h=(06Qfr|lwKDU+#BOTO
+Sotx!GOmi@s2Kf8a@*3j`n`sCLN9T_Au^I3Jy!h!|~o|$BFK6ym%3uh#!w7A~cOoitdT_9F5aRkz<jb
+-gX+9%B09g^h8Q@g}b|XxbO+uia5`+BX<1bc=W@rUa2eA-5H_6BN3Wi_(*qz(|JhRz>e;4^jMqJ89o;
+NFv2}!loaQtr7TZ&MYxE@4AWOfZ#34!n$r>M>5bFVHrm>FZ^iXwG!ZG5CmfF^SaFWVV>ARSFZGIX5cT
+be6iKY~^*uyQ*!hV>q?%7>B-~9|iBjF`9NPDU=zVKX;&_xoX-f}Ff97VPel3>`eNZ~%5|!RUGM~#SDt
+&){TU9=gk%tv#8-jTW<|@pmFn3^n19KbZO_;Y}UW7RtD*F7Tts39}i{Jp)0qy6ozlHrZtnWa+gMA(LS
+FoRiY9R+(P4f!OYcO@5Bh7RR=0li^f;8W0KEipJ<Gk6$P_!JIFirlx!zGuvc3cqc-CeY20p=KgE%5df
+>#y_EIsT#ti_~5a_PyrA7GO?#N8aF7IL{A?<*l{3!X2r5L6FO#=5v|guuHsowXH37?*=cv$q&R8;qDW
+HT;6Y~E{&I_p}fSY{ddsiV?BlS4AwWWcVJ%xxdmc?%+_5#Z|@JJoQE|As{le@6CiUSW<BC<C*tk>4hA
+d87;7@g!^-m}&#^|;VGcA|>Q5>%F6ZEUsLdfILMf}hTT0t0A_%4C1tH;_kRX(rmxY8&LV{4r2n8X*Eh
+R!JBTTxbmzt2Wf!>7l3%7IvmcW({HMi875E0m@5)jS{31dP69pNjYJ|=D{>*L#^KDOpW^(Ag8>mgIrL
+zb|Q$?Mg}rm&AqaUbV}guE9)(8qaEA2Wixj~PMG$9Yj7GlIL189~s;lu#@EOfU}}QFF~tMfvib_Z+|D
+T_`O}==H*G=3{Ko5_*-;VLlFWu{@1V@nJB{2hI##y7AloB*+vSU}PGE4#^ohk?@=Ne0i=~g1OA+FoVw
+#^B@Z#iy%uN%OE<Nd(4&cq<9tP8q9UR1iMZ<fc0Xv2_RQMu7a$Atb<$wxz48y0@H$N^Xc+NX>CbN5CU
+R>*dQAqH$ZN(na;dThXBkwFz>>=2lGpq_hEhoavS6ekUJoELGFQk334CgE50;)P+kSnIr<UI$1tCOY=
+S%h*#db8vJLVG<T1z-zK){{-Dfbru1%aRd%uPG941|{?tnZ6c?R+|$TuM0f;?x-SUOM9*_6$x=lJA$0
+oFLIi?H*s3$VvvpM!lK_66AEY~H5#JZlox6uaoHX;_zG&A^(4Jpp?X_7v<(u%}^PhCKs&mJU%^^RO0R
+Ey7xYwG2y#Wx$?;Jr8>U_9E;h*vqwv+d6E6ULW)#gLMVgRak4V)?r<PMVH+xuvcMUfqfPB8tir0*VuC
+0GGP%|7Azaq2CN&fZo;|++k{PETd-}|8?bM{z6tvltlO}@fOQAfU0C;EeF^J6EV`z@4f_k&cVORzeGm
+4Ru<x_AzO@PK0jw=p4`FS?dIak+tS5DeZ^C{6dkgkM*xRrl!G28l2(Wg_>z}XL63F@%)^oOxU~8eLu%
+EGQh5ZfRU(j8~caHT{N=+-SRn5V=Rm~@%eRTU9`t(!wewMwx75c2!-?hDQFN?<ZA-{<H5`EuSSqzP+B
+ktHv*QE_Ctzc;zOG{W<!_qXC?qO-J0?DewBPpe`w2iApy|drZjCN{HCGG8{Kke)fV|?a@C6XB}MH@Hh
+c`rJ!U%XiJ2vd$$4O-t3*_@nlw&0MX7Hf~Owu7~&SbN6bs~be-9kk2*uRp$7u^&jOBc3fgB)-d@I(2H
+_Z-4u%@3;5SBgZfrl85_7GlPn&39kNJd4QEItZY|O8O&&>KT<L|HOU>sDZPEb<Ib-apr3<&9{L67<Ip
+ei_X}Kd&XFXG)TL$AKWXV)OR;95&p^KneH!{D=u^-q`THd<q4F6=#6CHd(zLXzDDTu4MQYb#zj;#%Io
+#aW)q#3H>h}F+Olz+=rZqJid`anx&=;W3SL11;>7?85fY;{69IJ8t<B`U^bshQ&^mXWl+dKFc!YZ7HK
+1X}D;-1T>a(Xc3iv6y`*RWvNFg9S^sQAj6WME8V4TcG09mX{n1jhA>cT&wH-Em!QrcP6<lu^A-|1c_N
+lnyP!J|%a#J9nhUCX9zLwqQJPME*aD$%zoI47OoBf$<o|BL|{OPJOPp0It%_!B~Vb4`ZRW5o&fQuzJg
+Pv3#f6SK6SUrw%ydO+Cic6Ngja$7lLo=*~z7g9jvmZaTc)2_A<gcf3P`I(**^_Pr1ND~H#6POpOwuOI
+U3KNRu~uR}p4x%nJ7zjHXfA3WeM!<cq>xjubydriWaad^2uZgIN(I5qa;RQ|`Qg45IWDT{NA+`5Qc<4
+&)@n<Z8ZtmsZR*D!Gu^6;DcYHk^H0tu|f_#DP{jL&1-!1w~jS1`Va@zr`t(;oqaaBuvdJF|RALCKZFY
+osb&sT|(BSe33;r5CDFogX^ZAUrki&zU_YMw*-cwD!d#=sRxF(^_doRF&3>N>Yc2Nu62q*^92!juaPA
+t$(og348y{xoQ36uvmInEIllcN>nV6N@A%bmWsF@wnDBjhr?dd##`*j%(HV+-Yc$#dS|Z$W0oDg;ml#
+LR8omFMU_y)RbmZOHR<CS$1^w2_LLNL8s~OlSWPKsT+^v@%k$IqmGk_Hrw8jb8=YY-{d>3jLAU$rM9I
+B+Fj+pBssRoubV1@?j<|sfS4-{-tL1~W^1+qj&1rq3cyp?(S5jK?_uh9Uk9}BuO@F$+%mTZFb0XoqNV
+p&pE{cRpBH^+~sEdS#NVp;ru8M?LB=1qfI?26od*9Vb)0azKGCfm1sO^wpnL4X}Tc|?~bP4nczI|)u<
+@#iiv0B7=v0B0Tu$spCvzjBmXjY@R23ZZ^8fOLLUK%R^*DT8q*8<Cv*fL9i`}eX6E#rPstQK)ztX6P7
+tj2LaCu`zGvzo*GVp&b#UNoyw+)H3JgnK!xVBAY%1>jyL%a7O^ON?uoCBW^5<;4AaSraYeewMw$3uHB
+g3uZNq3tWFSfqS8>#&Hd?8YTWm>^ojnRsgZJy~3-?5))tB{ZOG9VneLPi7$iI2(AfMAn~QLf^jd66@Y
+7Do%5=)yl}4oON@IZSOVfMS%uewRd{t-h1Y{scs*FH-*bMMEXUV;!=+~qh2PD2Jz(<F_38QYmwgN6gT
+?Z}Qu$!He4v*PjPk*X>w%KYDEm2hz~hfB^p(dY$n3eA?-@rlpXYBI`>m8d2Xm}+27TIHfA;e%U%gZTc
+<N1Gy#$i?*OvfZ`f>(7`Uzis3E-zUef7mA_~{wIN6$0x*H8HB86ZG!`s+#FKfbw}{CN-f>c@6d|KbSp
+>3>u5*ZYp2@)h8%AM?`(jsNoS_q_f}?hd{4ftMjU<MR-R$D?VkXlFnD^i<71aZ0D^tvrnCt-OrttUQf
+st-OtDtbB~BR(?hmD_^6smA_HRD!`~{6=cM%0*#neu+dv*18v?q8yJk51lcf?02^-NZ&Nh!wJDkS*_2
+IuY$_(+HdPZ(n;H`@n_3eOn>v$IzPEt>KaBJRJ$}n=$_}R$IX9$uKNZ^8qhnaf7oVHmjhHTvHr%#XFL
+>DA5O50~wzovW+b_ftS0{dUq-Q$?HSw&Upw^9cmt)W+hcaq5H!KJJyo^QN`sw=2`I;X#DQUT1+1&#6@
+6+tvnRI?jAeFw~cFT}|?iNbeab1c`IOP_e71$MKM8aj4@E=bE2~o>Mw@_dgAaZomh(;^x{t3Xl^&1UL
+tQKGVIa6b{=7b*c^YRHluQ{Qb>W?1fGlE@><7W!{4r7v3f9a&;<dgE}yBrOFEBtk<`rlcgzi!p)-P&5
+cNL$s5wPn4Rwy5{kGQD>X%1V~rtaEB|w>!Q~=not(_q?;|w(~ODY|v=4L8HwEjW!!J+7uf3l%QJpzwG
+%JP)h>@6aWAK2ml;P_EzRm6VluO003VB000^Q003}la4%nWWo~3|axZdeV`wj5b97;2Yc6nkRgg_f12
+GVW@A(xkdrF`!^jc8#<V8ei@KSn+?W`Nj7s;%!|K22Ph2}PyC(k>RF-H$xk_}(5KE=#<wS_m(OQH{xh
+0u7o6>`vn5<*;@DFsJ1mv7nVlRm41Kt01SJfnEy9Li)p;tyqf&epLFa24HELUi;g<(Me*(yJ?t;Fx3~
+H!5r&p;zIb^o6*!5l563+cmd-CZ2OZdwSaL&*ER0<}!8T2A0Vmpu74l2D-DqR}Ln02r<+o@I-48q)Ca
+w6?K92B1BK2enAZ-bvH<h+O4>3E+u{eP)h>@6aWAK2ml;P_Euop5?ti~005x@000^Q003}la4%nWWo~
+3|axZdeV`wj5bZKp6axQRrWlue8!!Qut?^hg}?2;H~HKcUQmML2)MUKy|iY1wo3^gJDJ(42Vg=!F|dm
+nmF2mu$RiScTUryq}68aWW}(3)|<*-?keU`OpdQ~)CIp=Ybn2NfzkS@vlL$d7C^sx}jsNtt1#p2!eOZ
+y5mIHfoi}{5y2iCs!`q+<w#5H|RX$5k=gJ68Ep0)%)2R+TnJ8G=SlRuoEj2@_iA~D5qE^>MJb%w;Mvr
+GWLs7=Vb_cOzfget3}b+rD?TVVcb9Yf5A`f0=_a|@KD!v!c(H67q?vO{!6-T(xy7}ckM(84^T@31QY-
+O00;maO7>PiSQu5|6951tSpWbc0001RX>c!Jc4cm4Z*nhkX=7+FUw3J4GcsReZ*FsMY-KKRdEGpJbKA
+JF|LarWl$n;ACo_^S>E(H%oBCH0PaQjBIp=m#4TmNni#>`|LCT7*?fdL+cL9<B3DUBYYi`aniA`X!yI
+AZl7K<hO{r-7$x5(K>_^TBc%opi830c12>?TUS-)F~ZlBF?chab+^9<)apTc+U}TCzpDjzg9v@s{0k7
+A;q)$T>FP&@kO(z25agj?5Q+ZVX0x8H49A4c1GZ;6MOb<oPN)c>Ww(Gj|yUBF)ly?gr`dIZyW1+4GIW
+{5+6s6~Fi9>m<k{c<A-}{hs871^ITxv*Ib+X1%#cmke5?<W4cn4wG%KhiK#Y03X<dU8D)`MROeCu3|r
+*r(($_6V~6LNcsmo20wBLKuap_d2}m$u{}@ykPAmOf*?-L&j&poXIu^wew1-`Mzl|bNQE=+|I70df5|
+=XKP>Q*E{XOBy<$3fwB&L=l2$RFX)e}5z7~AQZnuKZhsdcEgk|<;mqT^|w8QK5DuyA~05}9Lvb-n3SJ
+BG#?m18wu84vKtVNuPV)!vWOt)Fimo4B~zKwas8$9%S)9aJVkJli&z45qrdU1Gke(L>nc6I&n@Z7sTy
+?TFk0e^hBx;#FePR}mh0^o~Y@A&fa>ID8QX5)I)((Cnt*v~R{&hPwStK=jld-^%xE7XdCl>G|eN_Yi%
+oTeg-5<lmeQwc&10A14hS(Frpfg=sm@C9eicE~;thAc^Q=6oKq?Z720*QocBXoN^|5D%<sp0btTAgf%
+O2dMIVodLIU)D@EO!4^T_>t&J=382hB!&s8_sDU1}2NY+W0SGV)x*Kqo&g(M6K409C-ANkoBms(P_oT
+9>n*(H+9)J(|Ku>=ric6j^(vTWLJ}0)kl`s6I6U5n&-TU#HAFzH?*8Kt7`;iehQq-lmlY1_ZE6V~Q^%
+Q!F=`b~&tWbHkL{$kzvRFu7Bz_Fm6~O->quXs^Jh&KKkfGxe2gHV4j1uRexXUVL@rUNeoF=D(1BR|IN
+>*!J*lGqqN8-*k#8(`cPinYpYbFt@u{<=8%K5vx9Lv82;g*tih+ni|wKOg)@SwDa<I9WbC79y$`0DiZ
+!aMr-=FRDqcXsjS(kY#aG7N7X@i@#pu*Xj&DW@N9rqM6FKa}JKL!;|>EwWU6NV5n{(h9UW%ySXlu2Df
+MzvbT4;W8mbt^-ZqAD*9kSEt9<HM;Np&(U(dlp`$s%^CtY{&+RLR5MqOyh{Muyi0CQB+tOW?N3n_-Nr
+`m(dFg&0O@*fc|Og<cVL6yNG57iaeoFq<?;9XuHJ0|yM@V?OJLF-_GYyKf@j#TyU=%s7boYZzy}(y4(
+u%G7uh=ukPe$nwl=o(lc2*Q0&j+vD+i;lqb+4C9z-Cn5cCu}d=Y}LxR1ayIb{PG%CG`R*Eu!7PE)pV^
+yvd-Hl{5qf)4NomUjkreh0Bk6oP+4%7TGm6E70bWhZ>@uj8ET5jG*@Bm|lT_J%>$XHCW^k(C}(vo_p6
+o!Xco^DGh`43rkA&E$O=w&;NdP#<9ELW6ACaQ=ZbW7ZgM(G1kkN-s2El$2L!M~xOK2sBxgf}HAF2;A+
+YS6t#uVQ=!8isAm4sh->Qe9i^oP|H?~lxoo&%CbOko~V&l6{*-}^_2mYIjreyfmdg!WTu1W6-IX&)n-
+rv>IsZPm`Uo)(g5a`vCSd^jJPXdY^DbpK^0`QDJM#t{X|=l;1E(|sP+m?A-Mt#iO#Qu-NwH2=n(vl=j
+u;H{*1PN4m)jT#u5s~Tb3HGc`Ii?Fxff?c!p|xo2IejwW{9GKsS)1A!5hSOChP`BSUUWeAxe(__uP=V
+G=ARh(>sar27NIyfxY`ZKP<#Z=yI>V=hTgj~5_{03>l^vFHxyPE;L!Um3iVwrmQ#07ee2`vZZYqr#Z~
+6YYqzp(W}X7#KfXo?SqU?$mcW+-|zq?)EY5Bb}aUy$z?MxC8hD420xk%#*u(LEG0*A@BuQNpp6?Uc+n
+Mh$yFhEGU?$y9LAa0kGQQlJ)WyUB#TvXAlD4^1CQW&>ZOmtZ#=}2={GVRzV2oiCdshVXHCk4NAjh@7G
+z5XA2*NjMITBN-48(g-NxjjTmv&1X5y@d=-RTZPKt%9U*lsn3mv(QHr?JN1FVU#4{QXr?TqwQ%FThVP
+cw-ga5fa3D74g-vekp4PnE-Nx@XGieeLRBw@O2$+2k2&{#}@tC~#ahNi5mM@kns8h6U_4d17AceuVXj
+^D-emB3wycJzD3nc<uHy^8Bcy1jDXj&9E{&r6!G`y%Hz<#}e>rbdL~XuG?szylt~O38L}ew2>*Erf6d
+A#K97BgMTv$^x<QJDEAfY|5=4{Hz`^TZRE1`adL$vf0gD5-7PiE@h{J-;y~1dYao*yv!p3E*;50_?be
+4q)i)hO+Xs_Jy3s)PbH=s=r$bifp)AZ`9dglPfPxZMt1s5N+o)T)&L~9irAO<*qZs(T&&K(uwr_s{HV
+o$?&v<JWte--KX>}h7RXi<PxG3yc6{CbtYy^0&dhLR1~<|};c-BBQOb(Zwi@mU^f?FW#iq{uIYly<5G
+-y9FdHaSfWJ3K1M{&PD@l-D3&0vl`>!0y1`dSiWz@-Oz6L8DvJ`;C29Hi}{5a#L$trc0$F#O(*KJ2L&
+|1o4O0qd3(VQjov@`ut2kt`jxT8|B!MA5Y2SrY;joz+#l={FOHhYyWZ)44pafuSlX8WY>{w-`CjScuW
+mO80xY{zVYXnU_*P?Z!%lDQ87MnfD%(nB$nMZaKbffChhr83pSrlT2>^)0~|-SV`casm>QC#U8`QlC3
+A>uM|NP!8RS<QCITYhcY&G~vu$$IQ%kZaXGuJCa>(Z?`yn)<J039myQF!<IxLQ)UaBJNBePY07|4>XN
+!SH1+@6p808ZyC1Zd={?tHl&5WW+uUi&ZI?C}9%fJ5Txu(5W&?3H^_@iycyLdt!0dy+Y#-4slj<9YMq
+<~kqZ+b{1`{wD{DJLq%c93`i`c5rTaewJyiitIQq^;hw^~sg<y-QFn<&f|-&Uck$ug_(ts*ct3%Z9FJ
+m67n2Q@Z}YB#NJE+q9fllbaJVO0prMp4ORAdRDLO)bV@1G5kQ%En<O@i-U%>lw$i-8ksv5&mPHQK<fV
+wh<Lj6(^E}Z*+P5*DS!g>W{O4>nOKgy4N6X8e{DDt>+((Z>HB*vnKe?hh~I!a{Qm}GOQXXvvUNb1sTR
+ApS+>7X__3SrTTICOk4(z|N0)UiC{3W*LGcVu`C6m6+gjw9<S}F%Ey<yY@&QY+_hZo;iW1&%j>0#Mg5
+eL2WAt99*Br1_mM~wSvj>?U|tIvFtNpe>=NRon5{&L$7rgu%jindzxSgUuNqzUF5STKObk(OQH}rwwX
+)(#CnCKkGJ;tEA&bovyPH(}Y(22e@iN&tyZi*}JW~rzZJR|DELv;Wq{l&)ggQmaLbD;(c9rE4SQII%C
+2GZDM^|TW-(7o0XIR<yO13>?XGs_ZDx-LKF+F3leo&?iixM%Fa3pbqDrc({MuGTjTpHu$<N>XBed*nt
+U7TFrOpThP(GZ!qjs4(fX8pM~?%HLt7MX!5M~Pe*Fa^*8cY*ij^OUr#lJyHBAON!MM`B`cF0W4CUR{2
+?IPs3oKc4CkqtBz!Xw3HZ82ldLf8!GWKH<M3cfKqBw|L5|<KNftk4Gi`KN0>d$7$_~|LXL_fFS%YD*W
+S7g@3FT06fLc{9}v&YkK`R9sjEmKcKJhza;!i{|@ZK@4|m{c>I?R`Hx2m|CorB_`fIo!PajRzXiWd{`
+(65cx2-Lf$)Q2=4}FM;<w5Fg~UG|)$qTP@)uO)E$zSoZQ2ex@Z047itvv|b^POfodDQD)ict2NQ0}s7
+kZ!6zOwUwO_tZZ8uq>3r53&F9qYZgWL4Koy^EwxeKYB%a2xg@NQiRJb21*!hvY90SYJ6&S+0t8;f<oR
+iCH+OO69894zRgi39HqNDZ=PjJxW+lx>AIyT+G!<Bx^Kkxb(+f3n-?OYoP28?1vU;%r*nGV}SqoBYQF
+E7*t%>SP1`{ITix1UjxEA!?b%%Xi>}_SxX>$<b&BikJs6v=%)u&z6_i6ii><(uD^;DS7mwuhSRDyGbB
+dEvWkt2K&&MT<c#)iec0^>50w5|D9V&f5$Bl+N_*iir9=)`Q8wR|VAND};MNOuON1(7v((LtbTgq$9^
+N=h!tUP&ls9d(|8+2ETLG1(#3bw&Ngol^!&&1%G{jw9yRa?_?BR?i=(Uw6tqvXU2+4wzn^7z%(!TAL1
+N+ixf_TybVlna#%Vx~VTtkfm%S!6Kf2~~IpmL^UiR2)ZJH<b%GmYs;i;^pOZ5Kk68{`m(tK)7NR%0-a
+i5D!MT&7_(j{?6iGP;@77Oq*UPq?*%4?S1KNXF6Hz9^-;ad7Ow;%A(O1c<M&E(3Lwd?4S4>5_;XUoxx
+9qw~dt&e@tbAM}2XBRP@4vPo%gdHAWzL&o6~2`%3Ws*Z<uX0LiK`y;htF24UFGHx<YutN=r`b%EKh@O
+syTFl{UQ==XibUwKge#jl|RV7!Q6b7z5M%aeaFCZX)%VQia62n)y*bf*@s3LNdE1hh9IAAx6x_ry2-l
+lPAGFqqhZ>dVvIm(VGjF#Pa{=ojP3y}gPklNAd6ZXwY=<2OC+gM{WHx@;$mpN2L532783sWG#Ur2<0*
+B54FTbR)SJHp7<hR!Mm?CTPPKGuj{Dlzz32Af+$ed_)7SyTu*YblB!-Sg{r?31!!5!_NLa;FHmst`-}
++Xgz#cbkr`^_stpiDq1?IY_)v@>I~3r^-bpd{ahXwwpJ*uk5~j>++L2y^gyu%d2RO(hSU`*%`2J@>s2
+|QAZETUW5K(azk&2jTzfbzU8KFS(*ABnXxqTmTaP<*A|2eh)um1&Vp6+)e!Y50#S_(CC2cb44EgxaYk
+}HE8;QO%HtHaYI@b6CCn*|No%Sntyk6cG=bKdD{!pI0*&%$J_xNvD<EVo>+Xx()2}%vt--BH3)e)(M5
+D?&9x7qCn{1!;hpG&4Vsfs^$|emqEq1$0AzOpCrN=n5nE-YkYoUad-=W5EP1$%7dg=V}IwxObu9U6R4
+HY8+UTK1UPKs&7EnlimH9aN6-K(QDH0{??jW(Wtn~G86wnHtX3jG?2A<JajRHHEKhjc<>Y4a9CwwqVz
+SZ#bkSF@%sTu<v7w$ZY!ioR8^R~-xTzE&i%USVN3?2xf6ef|PF>@MVaSdZ1-_s}s|se#SogOQKbNw~w
+-Npx1-)}@Hi?<3@h;J+tH{trm90o)?l;Uh&0k?zJ9;UlE0MwkM2*^Tg5h2Kc<{7fMZgl&TVa~%mDx=-
+;P^2~}~6KUB<#<fTf#Wi8$+7ck0Dhb~_p&*1Y><O#hvC_D(We^1atVtj<!uMpFO$GY$f!<N+SfsMntf
+=>fF<J@h?Uveq;UblZ)dGY*lR<86ORuWQ5H<6c9Oc<{AW#UjH!@nVx7EaHQ!sVId$L_VVo?gg4qBE0k
+AIJ}j$%lcdEj?UqI8{oZ4;@Vde8~mZK2JW9x#!;Z)_rqC@j{dV@citl(r-_-;ZakVtw_qly}FCcBkSX
+O77)HDOA5!qO5=WLS~XD78*lVeAYrg0@-VFOnFuHIFmXTnq0C)x_MYGQ-J!aa`}2v89!Mn?J@zjsW7H
+UC!2LbtyvMHyhqEXS2aTTW62>uvR26I`c#?=f=yM_!(OxfmoFjSEowR>#-)0_IL6oiAvjMEN_$1OZxN
+?nE2Q1y)|a=`pYk<F#bi<Iy5b_hi{!g%V#dpi^00uf4@JdSgIblYEU&ZcPNfz03eHxo(CgSLhbpgjU|
+xEio4NqP>Zu5?wdJS9==)`!xAddL^VBEI>^Im-mTh1EQpJbG_rK(Y35_WFCPj0B3Y8988&zCRRZBD|0
+o_W^@w-vlC+JQ;`^#0#=_6<eE$=BN@)pIRwDP1+B@X@a_F&S7U8oqa;69ZVsUhyl7a35IRS^&*P>n(X
+{EQthIJB#mKjhn&`aE5+Mji=@iavEf^}&b&bR}?+`k#OZ@H3OYzH0%(l7|`o*9IW#C1&zhE0#14Rb|C
+Y`@0pKN+Y~tfd14rB#f5K9M))Q8ye+)90gRPG1LC;oQtfH0nthMG@9B5t2-uULDJsU$w{d&#DBA?ePM
+M)o0*SY+Mtiop4x_JGr@}t^YKCE2z+KfwhekVJ~|q|+()=)Cx@@b`zNzz({~M%lG`f=rdZ?HX;dbtl?
+}~zSYzEs^lNt?{S79R=)Q!Cx9J0!<yZS;?nsS{mfX!^&R5R3h1Po2PKDj2Y`xkY7v&CGupy_||5VPtu
+KXB@5R*XaT~)UK^lAPYtjWAeH*<#OVt%st_z5ULR-xA;`F163(Q-OADcp8T`+MTL?g@{%yl-k`Gvx&g
+!1P<Di~$^0srmv>Q5aum`YDfYXy|1}QX#6rP#0O0lihvYs+0csPYqsFJw*RC?9lc-n6~R3m(|XUEr;B
+?unjSjpbwL<ah32*B>V*;{&6P}cZpEHoq41HFVw+ov%tWO)O!QLGe-D?JG9ENVEycmOK^%x(ZeW1&+C
+it`l@bbVxJc7ygSWHO-PG4wbQ1AE@uNw{y$Jl0|XQR000O897^_9Lu=vMy#fFLh6exu8~^|SaA|NaUv
+_0~WN&gWa%p2|FJE_QZe(wFb1rastyEiY(=Zf%&#$n8#1g4Qg9#ocrJ{^(RLTnK%6PQg<YY4>ab!E)D
+#U;1#E#R1(TYj<p>@v9-}%mkm$i_ZsGah1DN2$t&C-G?1&VO1>qVaDz2ASBU-FGtnRrkaqEe!OOJKT@
+pw2yl$M^kCP4Z4b*p~5vZ3>7`>lw4HJ|`O?3KEk`Rw!`3>w6%njZ0Khw^$UpU85`mW!zgsEgMKhA>=c
+H^gb4Zr{&Hf?lMmGt_Ec!h7|klv<crxCU=Qo8AzJ~&szqgx?nmNvLta#{0Cm0z42|__TYC`wD?B;fsG
+v@Q6G~eG}eIl|Khh474%ZcxB{{;h~`oX8Td<~jWP1=hu$82&FhG60TnWmJiU*ofkquIU0OjOd%m1~Na
+pl*v08tfC3HPsT`!h+`Lg<aF~7N4EUzZL?G@;*_SaaJk^DwypBQ2vNE5hY>8@)E1Ka8lE<C1CBZ`^Ul
+5ZLfRy|B{LT*{nSVeelGknpOyV$VwM_YskEH<l7G%1i=qOta_0g+r|pFvLUK+}#WM*?*X8ieH4^k`Qb
+UR^uK2TX%-UnxLI)w^J(ro8_V4K^{-?P}k*y9*L|z2(Ya8MwCRKzK5%2(Of8RSHDp2h5@&ivE6Y>W=I
+T+hD*+KXC52#7k@<>o(}Bz=jJ)9;!)GP;CX)IL*DPYon))cJ#f|1EKe;q&-`WqISsy&H{0bL%sZm;Th
+7<?V%@6VK3ua9HGMU;uK58MTO?=y1~xrYTn6%F-61h1MjG0-%&OtuTKg72P2<9Ug~UdpP_M^?NGOAc#
+)AQ>fWBdI~#=wpD`+19dGqyk2daaM~28lhA6FA36z?3OKHgv8}&z<+->A;9qzFlpSr`#vkxqJrEOGm4
+e}HBR_y<D*9gm`p$x)b{z*76mQc&UJr{=FZ%|7E1QY-O00;maO7>Qy2BtmT0ssKt3IG5l0001RX>c!J
+c4cm4Z*nhkX=7+FUw3J4WN&wKUvgz`WMy(?axQRrrB+*yqA(PG=U1Hggb7QW**6n6aUFJttRoY|^}#g
+_O3`M3vTYs5f4^-3FN?QP9uUeo-{qVhFlICbvB^oc0FvgE32+5w;Vi)x4DsI;&gSweSmkPA9&%wAvC7
+FwZliacMU>f$%$GJ=lkDpwn$wKa1Xo~vya?x;F_Cd=9$=PQP~P+?Wf93jf%yqUju$D;L<QBOnP4>O(M
+T#OZ-Py(b?QLFFd`g7qA8UeMT3|`#LS$n;uy2`*4?B`npz-N(so^G6TW<d0nKpR0C_YTjhFBZa|rXC(
+VP*fyz-*tXxH6WR~9KrILtzhBcK_GC5F-o2U6S@Vr)YLciDm$6zV7*fmzep+-V0ISDrZt3bN+!SXM}0
+j#U$OGVCp`G6`ngWE)0Gs6vqmTHO&-c2xrX8&f9nK7<8aZ1lb;x}ofqb>8xl7&0oVh~0YmOamOQR%-1
+vBLX8G5t(~@&4X~9@bdsFQ>X9p>N%x8xqTzd+uNN#+1qqe=u}|`sj3?L>8c8ca5Z(+V>x(uhpM9|t!X
+V>*6A>#v%mlC-pC(%K6>$fJ1Fq#Z0bN3d|0qiWO9a0J<pSaAtIU3r>S+Ir+E}kmp7&F7|mCVQ-%aJ>v
+L@~y6$Y?3p^;yr1POJn{`B-Tyog;eYgA5LB11={K0XH|F^vHhc#~CdiGwNGX$4Sw=8JgWU^@E==DnWR
+c_wS^5l)rm2sa(`pfQM`r-NGuK#o;nH;8d$f7&=zIS`SK0!DO=Wlm1mV<|SUVrp*qN+$wz$(qoPvEV?
+hYE1B<WOUF!_Ie~98`EZQ@kaKD&kveHhlKRmr3}NuJ0gm{O-^}?f~`O!HHp(4N29@`u=uEEd^2sTF1G
+zw&drVV<i8OAR42DWcY}=t-%WP;VMurLMA=~`*;=X3AD>?b^<hZ2l6$80ypTNZh{~pIoAa)*!4rfu|O
+Ko)aR!04^T@31QY-O00;maO7>POEQ}qL0ssIo2LJ#W0001RX>c!Jc4cm4Z*nhkX=7+FUw3k0a4v9pl~
+vnv(=ZTy_gCzg7l)WkTj0er?hKS$p_EI@we4u!SV;u3BqXIx`t__N-_kTG=)q%a&z{{q+Lc+Qq_&`GG
+|{pGyHrd}frZ^eOLcL{X$nWo*c49Ziqj|{M}$kM8l-zCyfC&ljw$D+F}e@JsYqcwLzuTkk*4HY>JoAc
+J{rqPF-{X5pPPs0CqsP3gD8qhIsu0=iKPphfw6i3kM`Tl&U{K|Okj5Yfq;vPECO6g8fKXk7-7e6I3iL
+Nc0BVzefW|8_UvivF$nM(X4H3L286V5ECme_+%mS%=t_mFqyvwPDnv49VRflJz*Nh*N_INPl2Kmv_)?
+EvVc42Ix-^oN?246?a3*Lc9P+W!&axoXMDj9&ODQ?ho$5LDy1H|AYSt149+P$Z2tK>;wnC{;bPXDX4R
+3RS$(sJ8X$0J9UcF%=byGKK3&%8jM?c6`g+SM-bxO3Pi5Em;p-d%%PF6O#mCkU5VZT<T#n(RfVrrb%a
+n0bCYj#CTe^ADi+%~^YHHE5J5W{Y0?%BKc%X>}HUrr`BW2rC5>C=u~vJz}?cS3c>Ug^z<?ral}#Gcwh
+=7MkMy4?%ifjP_FmAXZ_q1%~#dN9mkGudX6`-NB);r~i=$FS-{`C20uqTH0j_SpX#cfI;slW@1IrgpA
+HGuL>fVCIB~qN0RAo<mIV9%6!!I0JY9N*B|r$nb82vAm)>jCA-7NMR&iqV<p9Abf^~YHWG4o%k`xckA
+x2?IWe}-bv!!y~j_ULUB39`)xX7zkc&dNc9KjeSUSlT--c+e(>VutJiN1-@ZF~fBfO&r_U#+U%r0({^
+KWj*Ep~Sw%#bl8z>jcn>dBto!(gP;jQu)P)h>@6aWAK2ml;P_ErvSMNy3b004Re000*N003}la4%nWW
+o~3|axZdeV`wj7Vq-3Fd5u!bPQx$|yyq)c;gU!t9}uYssKk*2;%+(ahL|Q^%ibdT_pF_U@T!ClQS8~-
+of*3iG=c66*vV61xVzsKMPWuABRp9%JfYiT(A|iYKy_Pytg<ZcoUkGXZ5TQo5oStHA=4my@?ukD(jze
+f51QqJ0l`La1P*ZzOn~n!41wf0x7wsKur3`-$uVYzRGI<J0c;Q2<-XLtqKJq`pA5uI`yl~*ASOd&0}m
+n)-}U52Y};8_TGGx&>mqAsu$oS4?z;Jr!P)<^47o@nHa>{Xl~or@O7qWcHZ&m*w9f~7>_Mq`>@qMA9h
+9ofD4r>0(*mD7)^L3T9nrYXl#aW_{hHKw>tVIN+D=lICIR^v91J>Y=1}E{8z_}ZOm()TR9S;Wb)ia7c
+_lWvaC(wz*lrUzY3l@R0j^}YewlQeF4@o<hAf~@&&^xks5g;Fp-Jr;mfK$*;IsVCu`z7(uB!8P4*AP1
+CG6J)U8w!5FjvkAJ`k-bdpViGUK9v)NkISK>1Fvx<p)qp0|XQR000O897^_9h^21Bs0aW6fG7X}82|t
+PaA|NaUv_0~WN&gWa%p2|FJWwHXKpTVdF>i&kJCo*dw#{%{cv_=0&1nIifUAJrO*cy0c}-L<lBok$%0
+?9H^-%j|K6E>ukGXl2WpFm1c|*fv-8?{?eVH@IzjqfKU;N8MYv#{XqvJoT&*lOl-Fua>{?#0&BD_^AK
+lGQ@83QB`NxO%Qt~4p(({s~<kwd4rl#d=##cyqe!;pP-sHSqHRN_i;;&NjO|qB~_)HM~1$h8;R`$#TY
+I!@)FIZhP-CQB$>{75AN%sR>LOv&LN7ofykh&qu23VLWA?8Z}7aa&?a8At&4e(;y?tqF}{z*MP;FlJn
+Vzl3O%s@O)j}@zh2I$!upA5hg^=KBwuC%yM@ZssMWl~##PCeNr(~ZMARgbCpp;X?d<T2<+*#T*q=f|w
+ymSQ%$Q}T8FfQe00kj&`nSyZx>h*A<Qfk)Qiua2)bB6>di9h`wLX}JecG%Z3`yeLYBzs?&WnhFqSvt>
+#9o=C*lSE06h6h(54P|{hR$@z}ZqCj8hTe@Um))lE4{OD=7o6jWXoo?ML8u;;$<52iyLGBQvHwQMis8
+sGBd$Iw_uQemhii~yAbVe<arJyVsTN?tD_I=#Ewoe*RG=#Qoxx*h~1Jcsv%XQam>%uX0p*2oobBvxjB
+dob*^m(w8fpo}HG=R~<4DE!nXj9F}_iRPMJ9^~mAz(OOT3V3!9D+fx+aq|3+)HJUS6pngu|iT$yRAp+
+6)ylT=CufDfn$n}F9q5Oj<UjBb2#M+L$ZoY;rngRNTGI6tA}{sFv;F%$0tmfHPDQ50p}dSek(5U%dj@
+Jo80a(<vsIU@^@Np+1;*dx&`|0*_qts?2Papf{`#*K^?NomMsM<$OYo`b8|ElVGx$&5H-2T^Vm5ZD_7
+}+|1U@s9)KtfU422qW2}8V^k(Nx&#YTN2Vj)ffqs#W9M(geh#F%O;9LuW&IK#zD{1H}9yu`K7+u-$5L
+7~L+?J2dGTc}k%>W4?-W&Q7ha|O(CiV;)2dns5o$wlr$h9fS3LHtFLTlthL50M~(`$+HS@$M633f<)5
+$q|~{v`dC)`eTJ;_VC2??pVboiE{mNTVe*Scil}7oU5PJ@ec=1XAYAl&Zre6>~G?*5Q&>RAz+;0Wk7q
+=%V3k6~!{;q2ZE_DVcUm{{VNa?ce|-nDj{qd4B#9+pZ=nl?~(91JOZCDS7QgMXl-R@SV)Cl{{W{H}o)
+Py=B?IZKU`ZgMiX)<di;LeCVu<Dx61Nme(c%WrpX%OB=!aVO+Ip&E)^#g3(-NPgAfA3d-PL_)_X7Qwc
+IyQ2NN!ms?5>IE)HKpIqizE~AuqJ*P1_;s4<_GHHGCnrnHD)Zz7<M%51gJ)hBuk1sd5?!ZPBtZB`_M|
+2Y#nL@pH?{s4uc{=u6T2Ixc5^%Y4(0pWON7KH?gIsI3&-8aPujnPOw$;G3S>X{=uR?p-iNd&$8tti=!
+%2y&FrcuLMIBB+NCjkcGvq*$fN&DpMzcTPwgnX|)}}&=iEk<MtK>Cw+8KQJBG#jddEb`McF3jJNS!31
+N>gI19)q@KBJVe}WwAsZZ(`|(fN4n4;nnPw<ibP6$JjxzOPmknvIhkyBRrTcSK7QWtk-m5Xe=ms#&@x
++8xw00J+1LdZD|$!HM1nq-`A`Ln+lfe;ZGk+e>HQlXPW)zVd)Lq1Oj}Ukz0$A*L+UyUQ%e2p(P!c=1^
+lx4MD{(bvZ`I&yKUQP}3xYIsju-J_}%2X}hP)^o~=E;&`B`U4R>bsM=a<BaTQ!z6ey1l7R&f!Rh=1iV
+quNo|s&7H2kjM9hIkZ{XX@fZe>F^tw6b)g>G~6Ci(IxO(U|=@DxJc=@UH;UHA!!#Q_gDB=O`e?KkG)N
+Q-jS?Oe}X$2f#i$r1bH)An*OM>&Ve>3e)b&PL&Qq2%v;vaWZAuA|U>YB(=x{nEtw(DRHqtLXI!IYFoM
+5+(3GiucKzzv^gGRL>y?1_0-@Y6EPCmV`0h@!7}AW?Mr^2$kTGab6;j+f(r!4UnVuJ6f-qBApyEf@8!
+nXv(_WW@Ude;i*cGC@gEhxlLM&u^<j`H5i}xLnpJVmnlaY7z|%BH7^>=sU}7?r4P5bK?V{`N`e_4@2=
+vB#GD3}^tVfr@!1@+t>;@~&Osi_cD#@8WI9}5DYYa1mKvCJBwquT@}QD5pD7hyNi<OF7<{Pc9$Eniau
+eFt1H{AHzNVAx(Z-bIUg>FXDEAScKp!0^)d`P#xT{LkgBzP-Szb74+yG`2A-(t=0FF93-9Ejyj?TM2b
+y}$0OOVC`L0!a4bN|_xi_bw{<;2oGwMWlhPMXQVshWXJ-%=W&a;I{1AN2D23g{2o)sFY48wi4G3;0p6
+wqr|*<8h3a72T0@ypXJ#3wXtGHn7?XyiV5l<a6>H<RdjVP*m`e%~C(JeY^=nXYX<|>Mb|tFW6Fiu*;_
+-Cp{DQHOJorgu{N{V~-lX4?JOF3ZF#(+GOMX^{a-WX~x4DhK_z=Alfq`nVc=i5z-G7wwstT=>9%Geq?
+ZU>u+g=m5pEP^!#r&EO>$>ZPP``YR$nQKM(TqWIA@p(>3j=ik0ek<LcD+RAwGoNREogX@GH|4qoQO9+
+k3Q3YpHQ7W#^g<4`X#V9nz!Fx0Wk1y#z&nCmzSQ_~8BkkwS4S5WZed9;}PD=BH6;on=KF82Nn(!H+Pw
+g>Pwa9&D0GwyGy9z#^V?_M83ZfVU*gZ2m?l#P6%*^r(N5r*N+@EU6aE25dA=PWA)3FDv4!gG16>g^au
+vJ}WpaN#6M2Gy-X(l={UXliL6qPkm|!jmf@S~9rF$iBWc$h=w9)TE%@%ly3D`gvJ!fvf7yLg(O_uef>
+JLD+E$3FMMGOv$JiNxfY=Rzzl`n;D}1gg2S}15ir?1QY-O00;maO7>P-PYaQ-2LJ&28UO$o0001RX>c
+!Jc4cm4Z*nhkX=7+FVQzD2E^vA6S?g}&HWvQxr(oSbQfsT0<6P{nJI%Dy#Q@uxViFW+9Yato+9O1k1d
+2}T-L}uN&$3U}bB=hm6;IJ0MX@Lm#NyH6;dd@1Kic`Wu7qTQ_wx3s**CqlsJ3iXm6HD?i~OGHSG&3vy
+ixDvzRt^ye)n2(k=_@4z}}==p55+he12QYyeiY8*A9tRRZ$5&<SXo`7meH(T)()%j(UL*wEPyHdp*IE
+v}|%V2hd<}TjvE2dJLNA_xruz#q92<`2KDgM4!9}>G3Z7S&M^3@a6EwySrhs{P}LN7!6-6KUuKhXYl{
+a;jhau?17CzYmG<Wzk2ub?aiw}FYNVtt0HY0mR!T!x77nL1M6rwqY*Il9dCApWYwAxMv02~zj?+QDIi
+)AA|&0qNb_=rVsHe6C~G!iW<s`rS4;b@YF3@^dcBOV8AT+~vjuGrqD2#gZ1{!A&%!#eG^lUYK$a?;EH
+43j3zAU^(lTS$Z*E>gS!BG4S|_f>rfH2}GqbV)XPvQY$Rt_AQUXi(cx2;;oEMp6#lXYyC5D(uj4{SEA
+V32Q)BqzAY6nzIt0u<)L1aeH1oW9$l6VcJxlQHjJ$kRIEL!JfmP71pOhb#ck*Saa#vwNIc4*YpX&H<{
+qXKggUZb!P)vj&=tC6o;JM0VNfSm!`9wX!yo`JG31IWVCHww;sc3K&mL)`>@|J6bC(4kLRe58VT%*!3
+`FdM;`<|&u&gZ{Q39$P<h0+tz$Tg0<rymYdOjTa67Kn&FIgMq#eJq6E5|G^43d=AXt6XPZB0yqDBm)z
+X`@UK_Nx7XjnH2)zJ@r?EFt0Gfd#~8X<zE!<5=;bmk@|6-yK(H$_E{eS5N_LJGp#Pxy7rH-If=dtx{>
+Vk6hg^XKGP2@np(Im~-~xWoD&yFlN}C!ZzOs@GFf#mfp`WRD9^&ytNe^L<&(#YT`}o2YnprQE)c0b1r
+Nq7~<EavR{+x}-XE--tjcHkIWU-NrjcjaWXGV5rWD_Hs7}>dzog3MOkzE+srIB448KQ;_IfX+&CmSI{
+?H!<=#ID!?pNw6x!9F>2#RmRl;);z2lXF*WoS0m=V&li;(iIz5Cev2zdvlJk*8;X>EkMA$T;*a_7#X2
+`^y^z!5DliPI~=7;>0sp4=KM;7o7$XDjm+jeHesIHq{k-6Q=9eJgm`Mx9-9D9ZQf%O-l<J|Y=Rq)ygX
+l7xtHjvm3x`Ch~tr$Yl}J_dD*te<B^wdi#{HC8Mhw9BQNKz7rz*egS+6@91m$>DT06<u}CGiC%7UBMB
+OqXXO`X&DM{eSmq`*dyjT+nc~h0nzK&u={N^p^i^^S5z|m+-WQ2kY41kA-Z4M{)bIb-2EUkIK(mLUA4
+uqVRELTI2Q(&cOE`rVHG}uUk1!f*349IRe?BIij$*P^KchWI^NOiE?k}uz;;sIi~tJ^TTKA2~uCpZa(
+-3<kBjv|*de-L&Zn-u6alnJT@`0psn?W;D__-G?c7(3#cws;(NN2J$fch5)El0@pA4BR^|ccSc!+%<h
+dOn?Ew`2i$LM>1WlDv=>7C{h<#XK>-Np|2HmFNuuA*Abh0Uj+n4Be`*_*@%e~&k3l*`_j5@i6iB(?U|
+PplR14vg7O>m?*wq3I9vc<@`{2;F;#-4L|7yTmjX)q5hJvNk2zb5De&yuH48K2dJer|ya1ate?xn`zv
+7*FK_?>8sz~G2=UuFkf?B6=WHdPUHpdOCr22e-@PLuUc(#l{LlQ>|`e3Hh3bIr^zIz^Q-j-xL(XP&5>
+%$fD5YXJuJC79mr1Kv$yO*jR6o3s089bu55-OOAwPWz>O<4&X`3U?>sSVgYU!}W-vnTjVONmzRIkMfH
+m$HM$<6byti_Sp6A`Hgo=L48S1_|nh7(RL;YR*R8F~(v{^vQsC0#&#tazg4+-ema(G(%=A%+1Z$ZOh|
+Qf?Xrg{?J8@I>!?tIE~E?>MjKUra_FJFP4vi$u|5ry1IGAlz0bRmpWCCM(ABLPC+31$92+y;Zp+wO04
+05H^l-cUVaD|#N+Jh6q^72_Zuiqyy7~0*<r&4Z@x<kZe&%{(TeN$nJqv!qAQ8q*BH?fw^N(RZtS{|2X
+^or?pr7Iv316d_WYJMeb4|lbBqLscuxbyc3MNF#dT`@XF3H3-|y4LcIf=zFFW#&ro~$&las6DWx9I!d
+yUwJ=j7o3bES}Lf3K+ztA&>B3u603i{VO&lxp8ZKtd%P;am0*5QC?@JRA4vJLx3B?}(Fx2t$%=k*X&B
+87{M0q?>Iz11bi|f8>HDP(LN)mD{Ttw^z%(+r=M5)K!VD#IUTK3$nhgHZp^23v!SudbyXpdHvSC$O@i
+j!8)5Er=mO6J?hvZ1bUegp^cR00KXxa*t%}*M^6HRAE0)47%vp6@4@9BzlVM*1B_fMHjj&Vwj2-$g-Q
+P$Q#O_T-Q}yc+iK`{b1e=8#|zc`R_wUvbRyaxJ?0wZhD#u)J067U)*1A7ay`6KG_V#(EWNQBm2<^a(b
+g7xbsIPZGir@G7hC<JNgsLgUT%w^ui#+^p!^0<O9KQH00008031s8R?6<(CtCyn0Kg0Y02crN0B~t=F
+JE?LZe(wAFLG&PXfI-6axQRrtyW)e+cpq?*QYo*7$#+k-2nv_2ylU=^@grV3N-EdU<8gVQ8rhaG)QWR
+SM+`Vx0me$?vw0DN){<AT?@>BL6N-s@&4acQfxr)wv?}cZni>dc)rzC@SLUaisMHVRfc9<2qt7p^Vn?
+m7hDNOx+}X)+Ybk)Qg}glN#qNnYNi|3@9OPNlRfG;ZhJxRC~qh>Bv-ZEgI~DqhVT|bk(JrC1Xpg`Ug}
+*Z*p=Bt(Gk2{6GY7M&q$?Daz<C2lu)d5nHTuJf(kYLd~ym}z!#I#6qdC{KD{O&>1sX5Lhh*2AUNCYxp
+Q8^!^!D5I-7m{^m1`_{`~Q?#q4}`F}r+u1yh)h{`vdIQ3?mkpF_)E?Q$K>E}smcfus1tEx)_vH@E!im
+S5cRvs->btgl|3pF1$bup&fJRIpqrILl@1yClgXz~5*za;{X61A3U2uw<fm1It{FBTMq7Tq#Fvev1A;
+Ag-9mb&|oiIjf1ak+CNNfvD`KWp8<wWJP($bY{0(LDAFklIUAPI6SZxHs~o(Ua(rx?@7{O80<a53^yO
+ie@jcfh8THL5KU4b(rbI%35}N$Zf-6GCpR}%u}ywQH}%E=jNu8Xa*TOp!pTr|FSwkFZJy0-PNkr<ybj
+*8=f05wz)|ToBhPlLkHbYw{1<OlQq;VBFFg9*c^Hpjv7nsl#Uk!JO<0u%e$T)<APpURaEh)vI6F>5Ph
+|VbG)I?QW4Ib)rlB!2I8fTeb*n|%H_`{uCt0B3*aq~}>K9(PsGXVsi0yX@50a3?1SJws9^+SPF?tj(?
+50lX-ov(@O<gIAtpd}+N#5u)ZPvthlO$V-ZZZ%FoIEmGb{a{dYssM+nRI`<*Y8~lZ#$j#I~4j|62yR{
+#d^{7fP+|o<|6Cbf{Q?v_4<P|w2{v56Is;DMrXSHVb5r^3U&&(&^AhdFh$y@$LOAgB}oII_gp8P9PJy
+<*N>)qw`Kv@juKY3?I_0D498A|)N^HWKg*a=PU4WjxvCRoD@jG~(D<7zBbqFTX-*1lg!vIW8yv$a{yl
+*wT?i+AAS?t3R%4Bv-iJMzz-gb&UHup5C&<`kpD1@9D!0j)L8&c>FY_R3AhD(B$vemuNP7gY*Vr$V&T
+)(|J;R7p<%}7Dg{{jf-w-GW!>Q>OCytWf?GDsh)aX)aBie(*zPZ~h1w+<cf2v?qpvQ@9=ZcY?I1H|td
+`uL>N{F&$LN8*`Dn#jZk|TJ^kpYQ|ToEgT70}dmQ^&)(#r5k3&U7q=GZLc()w^*&yi7T?(c2FaKO+Vr
+Axwt`>$52g4MXz*{_8MWPz-NWIqo^%m*v36p(GXz<v1Lo<_Daf463etV>DrUf+Hl44PWAwh%onC)$Pl
+3L+?%!$gc6!0S{M&!HUqYz0HXHztmoDzCP#>Vb%30<F4kWUi}Sg*S)1Vpt5D!hklqImgU4N%l`sUO9K
+QH00008031s8Rxlj@P+tlF0CFY(02crN0B~t=FJE?LZe(wAFLG&PXfI-KcrI{x<r>>=<Hq$}Uoqf5n9
+6Di#G4xgD1g^?c7=HD?b@5|cDo>GX(UfVkt#XzrE!2<9{SJ%O;8CbdQF<3ZF)<ArcKcn$iL`Idd`_4I
+YW`OyEXC>Vb|oGIdg7vZZndYOyfkd^ek<Sl6b=8*;GVhCKUMK(Y<Yd^Un6>tNq>E9oCmT2@XTvVLKv~
+t(F+!LhqO-sfZ(AM5CC!++*&|4tuHHZ87*%5Zw_-CT#IA<p$DJOg;aYN5eSr)B>NMN**EUw6vD7Yiyb
+X<4MqEQOpK0h|p>&4Lm=L<7u`4-~BMq(pvh|@J__w$QuC9IOG|XO*Pz`N)!e-4S;0IZpEjHh~qe0d?X
+^CvcXZ11Ot#VWin<7(Bug_j8A#$wFq}P|Iu>(_HzEG<@|j>nQGv>_#YofJQ!-&F9`8J%lW4S^^^Fdj6
+D$*$OWDO9L2G$qJVG>n-lgI%lS`1VkzT^l6WH-r%F%!fG*5UWzz1l%|h2n@CI)2Y>M+<jvS-|A((p@$
+6<%XWWFGTl?TZTj5}iTNTft@mV)gRwqe0I3eP+SrVVDHWPtig08Zm&Hdo>e`H1=8d_wxZoAPkfL5f`l
+GIrQA9YwXvPzKgh6x!^@%WOA}c%c?9^n4Vhhs$la60E04<x?SS__G~)tgFXO^>|J_o>z|-)Z<0<cuCR
+s(rG9p0#dh~Q@oZtM9x~G|MHRS<iq04ABtlE{$)TCF+P&O0^`Ib0Zr<;Z{_64uM~a1V}Kx_q!<LD30t
+APUZ$P<7k=FQ&E^I;ietn4QJjeH$B_g98n6aQoTg0(ByoYzHif_0ZW+>Nag@^lK*=r$DVYU9D^_{Vw2
+EmET9RvD3=L%qpwg`vudsREWMc()jqx*_I^*Z_jmFQh>WrTwG#USevhb}{8n*QbR5HI}RW{6vCT*R^E
+b0no?t+3?gHmj1pvBD6onpIC)=W(apC&prQR0EbROFq6%UKdJ2WpAyd0yK}YJhps!aQ#k>(bd_DutX$
+uG67PylIy?b|G^>xnRWe+=yA37@;&y!3t9CeonK<*`qjNK@`g)sBn<Wg=8mjv?jBnH-r=qC2$%B5-=x
+_zSCJ=1@U9o75r#HnQP05rA8Oz3<K)Lkcmk1g3{yJo(O7Hl%28`rUsz0sz^NHEP(%SMDa-kZAJ_o&m^
+_Tlcfcu@Zb!qUL4`FLQ{7zOF%Fgo>2t@Awzx~L=q7n3g|LU(zaFB(C~&~?$g$mY=g}P+W@ws5l7-AFv
+yRb(_q4J?3r6;RqP%)N)7@=wI#ifkAuOPf1>09a}1SJSj-iPo$cEjn~(g5{oSp-hx`8igIoIt{euSw{
+k`3NZ_Fha{FI7syNVGNPoE5eOu+0^2vvEm;I^^9+3%O#-Ewqb>4VWl<YUI?Lkxo=T2`I7Uv4<kDIW-E
+Cykb4q)mDlCqrsM$R(({VKRXCs4NrC^Y6{XaS-CZAa!{ZNH&at1*mzcojm{|lQ@M|Tuek5D1Xe!U|4~
+~T8tYc_eczgS0TK&;-q~gz4k|<8H5QCIfG4>A{_}3k!&(ZFsH#rDIFo2*HWz@A6EO7R{!44Mt|48v%R
+sky;b28Dh1K5*gFU9ik>_XLwN-0DLY?07Lk0in(=`5Z7xY6Sc^LoptYtUS50R_Vo@BJi{}<ay$g{@Fd
+#FC!`UQCFWM&*1|kq16!fE7>*uX0ex^YpK{w(IOP_#eKYmg)$kQogFn|%7r-r3j*J=cd*g{vuqm4Eor
+o;TW<0_5Ywgx47>>0JPZ6QI(Vr(Ln?utW|CDK*0T`MwG%y!vl9LIY-7LiL@m;3^HhoZESgXE)1M=7Qu
+%kr?B9TFcq7%foa9H58~Y!~neU7Lg3py2sxJ{;SnP)%LEAAX%~XlyE3hxI^jvWra=Jxdn}yGysQiq3E
+ax0te4P?xxZOi&9iYpg2z_hN%WOAFk+dL=F?|7AtLgwz)bjDA-yaCYFR7uaD=y@2NFq+Z7Sz)~k8#Yn
+x7)*0dg(^i}(>czK@74-_(rwc=iwA8UAfq;7XS`g0oc9O)2>nJ5BGpMnLoUNggt##NM5L?4OY7I%RIq
+j>-++bA7Cspb9in6$2@u$w?WbO8)r2gL%xjHjFb&XfcziDOOIGkQprPqf1|BAhRDz2{g<{|k)Piawq-
+=&_khksSk2cv$sb^XST>#cKke%?C2asAwU%ZG#l$f`)wA)=>>c3YEPucLkadPc%}D-9cI`&)YtZtZMS
+*LxwG-qWzz|JH+z``gvD%`4<qah2OL?|U2Ibx6haFG^Jiaj~+s0xf>ET)e+r{9(EH_(}x2+u!Zq-Poy
+?g0bb|OV(1i+raxDn(X3>N>~*FlK4BzxMl26^Vc3V=wIgiujTxm<@~GV;-62+Ib(dG<!#PPS=$&B8}p
+@7&;9=0dpkAGhA;XL5qX<6gEH44l8ur#(Y62Ba;ojP1Xb9BcUUthqkL!Ye*Zgry9XOP`!$4ZA!|m}V9
+n(I-h*8@BiDq`;?FvS7Js?Am|px<htT5lOo|5ME$2Tb3;k_5{|OA<12XTyKY0BF;fo(G=YMQ~*CBmKM
+E|{<|J;(n-`=`io8XinpBI9>t7v_c>G}HxcpZ`w<jWO7ni5-`MLs5Ff3Tc?b|r~T1$v!p%qgyayIgz-
+gAX8fKY)Mm`VqmwWj<+u*CG9k;GZoQzqEyD+7~U!r@17c5fS@!me79F0Ix$*lKjq)<nG4(SGV>a?luI
+uZVJxN&9{7*1$Sj_y~geaQ>00kUv$N0+*_Xr=&%xKh~Rw${dG$ByRmu2rx&%FE<{1<H;H*3_NtmHiK;
+4#hA9L))v1x1$v_4*GoDuAih2frE7M=ynX2!mQ9tOpMWSyQLk>r?LgBPkf615YS;dSrsc0gqOkp8dwz
+$w(6+M}10ZCo_=HK_DV8VT$4!OQR!AoP`=~n-c07=&UE`W{@#qR=W*sx$4L~!WT==X47koU3)JYfWB{
+=KuBto{vxfgtf5mH$)&2j(O{mH8aJE4CTUUPjJM_#jS(6dU^Zc5Cn3+qkQbi-Qgs)3_>Afb|uKxdrB=
++U`|I9lqY&3XtIgRkL;cDSTETHHeCd2{+mU6Rbnq!dzLJ$L1=u%wCDV3Rzj6<wp&BV(qRsg_Emv$=h7
+#@nIYe**M`mdV<LmH(mx1)A;S5JPUcxp-HFRVXx0pDMn{KX8=LZ6Q^B4ww>`(k<iP6z~!gl?8=imaLy
+eL;rQIsKM}wKEO<8sA)a1Sa7#XP$<>ULtMcfca^})k*hle+k5@E2(JZv^LosnW`s*5B!|+I};D%5+xw
+g&E15tgYj_cf^^v9mXd*WA!8@yj)!Md?vy>bCwYdf1f3=xx_Plu(x92;{PNSWl{xRGVcs8UE}PKbYZ<
+lyben;Gs~#r98vF>H5WaLR5<NFu6=v>`;b$|p3wc8zQKY#JPMKRq71#2a3K$A1A(O9KQH00008031s8
+R<2fbA=?E20G$y402u%P0B~t=FJE?LZe(wAFLG&PXfI=BY;1EbaCyyGTW=dh6n@`dakS-Ow{cv@loG5
+Yq89{36_wgZeK2ObvB&n%-JR|3Y?B}!3gxYp5Qs{pqC#9A`hu)dkhqE;L+gYm_z9ddvzJ-hNmZ#_oXB
+=&&gDDzv*BSZ5(x>jhKUGam_>alM34g47eSJFeZN1>@8xdHqfv2r+7AMMD_{*c$5Ux(lBU;ZLEvrkfg
+G1&PQP;QoOkK$na$TOTGkP`z(#Bbq=3+u{V}BMYQ~~I12F_SW)O;0LSKZTh@e0A6TdH60*N1uSZaAZ^
+-=^8u$rQEw4sSSF%Otyztw#+Yqi>~W%@WVq<6oC@9iOdfBr>vaeTGiJNlgMHWdoXvR*E&b&j`QI^kLa
+HU#zeK<f%v<Vdz7JCMr6h2;(4k?dH2FWa_XWm3V9vTzIWqA|pjBCx9&PuPGA9`G~{{9Pa^O-pfZj(G|
+plVdReKiKwnQ>`;?!1kD<dqSkoQU+NJJ_JIN<dB6T*=@pE37j;Lw^%gLN|0DdzFdI54B{Fhl9i@h_sL
+|GYW(yfP~ebh9oVGr72ury0+U%187yQ!JiXz$$JD1cViF_z4#ODI*D~VT=X9g!q>z445T;q^l#EWv;=
+)iQM$Yg^DRh;9M1eQtV8~U3=R(_nGTxms%e!5?={3mY9wL~@i)WP$|A&b1Ar$U#VGUkbX;<QNC)Vr1{
+qF;5)NbhS(BXPj!v~<L)E!>X!~hB}I?}IDEeu(OIgi^((CuoDZ*l0}m<gHFYQPGhGukeQem{#jhHneQ
+Huj|{(hOh`BxSc4uvnmI!)}ob3|G5Pa^Hb+%Cin(e@6Z*WP(F7vHr?~h1~y)7j;5Qs(VaQb9~W7Aht1
+&wnP>U@V2GSvN$%*s4_G=dIeT=Sz&+P!8^xfUosh8ICc!$iWplzs@_a8R#}!xKamZ<K98e;#vTgOO1e
+sRukyjr@Z*|htmMqY)zAu{^kP9x#s+DvOQ<_ROIWH&NLigDPs<j;%ki(n@`|F=2c`ig!ZlM{UFcTA{3
+}NApTfsEo|SwKq|D51V;HDLQ>8ebl_`EPPjQU*2<=fBiubf6VT&DdiFV=GjbOyDv1qm*H_KE*dlxS@y
+1yDZpxb7>^X3xN-C7QJk>}MoSppk>j)J4;FzCcq$uUT~9YxYBA!?2_O!>KikawQae>5TIM+6_56zj84
+4c+tPbA}yiRLSRR^r{5PVr6BKYHaH82%O@PpX_2H_zCV^StNM?+YG~q<P_zEkH!+pLAIzyV?n#9qtz{
+uA|v5czA~I_<R0x|#eikgn;{^_nLgB~wQ!q+xhqK$_=t9fue-d`bBU_GFfVeV4pM1PK0(bPLJr{ESj4
+EKfDSmMXB2TGDtdI-Jb&hVNAJw^8?oV#_c@DX{Vr6Iif~!p7ReP=gmC)O>+}F)4B}Mpe`67=l1t5^$1
+$k#N7a3U^mEBYr2eElQmufVd(>K3HiT2uj&x4a&LRLeE{uyq^4+3M=njDkzIL7J7Go0^@g@v+_I#7af
+z6WI!n|OedBWOdNMDC;>Evn=XdEcnTox8DW=dRde!VN)rpG3REA42fm7b$ry4&q(ULX6kE=?k(tZnKe
+U7<DA4c+f5PZ>K+YIMw^Z)r$NnrowqZ+)nd-dv~CE#>vx8r8utO{)5yTZCb8nwtn`h%1Fg7%X#ub#1%
+(HjZhB;OGF+H*$>vhz;DL0pmq}$UKkA*!H~8=aJ{x9cp}W;*UbVg9U>#ADyYi$C#zkIVdOWzdpb7tL?
+gFWD1=|Jz>i3|Muzh&gAjr$45WioqqT2{^Xne``4$ROs2Qq+q?V0^!uCpliR;vfB%nrUn0%){uk4)9z
+6Qt>&G8X==R3L>BHN9{&H)2^W(jr@9o|C4C(QFfAU~@<0Irk`3+b#f~_GdKa{v4l_T`u180@izy|Idb
+1e1Y|F7W2XGUzc@7nGR6nlpzS>#%O15ir?1QY-O00;maO7>RiM8@6A5&!@&M*sjB0001RX>c!Jc4cm4
+Z*nhkX=7+FV{dG4axQRr<vi_@+eUK#`4n?-QU+~`;rEhTrpqg7Pgcd2T&umfQj&tgl0y<+5TF52E1ph
+ob3gM`d6M+U%wPrpxx0~*{5aO>O!V~h^w)Iv^ne>}cWG9LT^tsxG~2c!e$HfTm8Dy;NaHli54q6r^-W
+Nu!6wdmTqgUi9($P-m+;5~t9`O4(lj<R<7^)+!o@}rE)KgWS?j^;fB)q&c=qGvvwwa0>P1Jq3b%53z2
+C*MBVO-{C{4n+BM8vq>D^!##<D1+p?~@E#gEs))0fx5FBd;uUSD5!#GC7jSI;l5o|lkcU%q<&`qwuap
+lFehL6Jp3ztHraA@G`E3NMqpOb=hld><DbkwuG5fCCDrkl8i@c7tLgw^Cz2zx?yXUw*m{t}m~Ce);O+
+r{Ma>%bzb>t!U+nelEmUVwZ*MZFnw{6x9DgW-S4qQ`D~&^csN<_Q#^c`B=1CEu{c4Hx}=Lbql%m+hRT
+!-mg)zOz(0JP#1BS=d6Y|jG_$OKBqN2&wHInk*)+VBZllMf~kpozr$taQrsMb<~r}foEA;irU6F!1Tf
+|U$bcZ%SAV&D_WGySR{$9jq-1`?RF-lj0@8jE__>T%ZSmxLkrx?rh@VUr`z#SF&l05j330m#c-d#qrU
+WzZBZP}FhO46M!%o%}gizFw(oK<OpphuyDT1b#I#Esn;`RPNb%Z=uG}O9y_2y+j3k9z(e!fKVpIFA5I
+9%L%=c3o)XAlsc`s!(&NtwX&Ks_I19H(~x7<TmZy@bb+dfbL<nG_*F#tO1Hgh*hb9`80$ffLU3{482;
+ia>KQb-~Qc%mr$m`aKtJc<cA8#EHlLzy+7Q_J{6>;<-O^!J7B}xYW*}hk%Izgf1WnKOD^ZTIOY#-5TK
+3QsfXd-Ln9F1oZ7`#vodlrIfoMzvWd%IHI{*rpvX=0z-IGhYt{bX4{%5XrA(21~EP;2ec)?-G1MvQBD
+gEdrhq1lEXoLNfc=~w3kH8QLkZ18gQgnh8b#6VzNsvL!+1BSraoT=WyCILhQ^M7RM>0Gs}sIo1x8((E
+^T)s;VIZV_Q&MYcy$Civ~1%kU69MHn7KWcxJJJq{lrAfCR>lrg-N}9ho6v-;QV_Xts9y4ALXQ#x4kj9
+ZxJz3_e6DBvJ%xrKDMytZDLWREl{Ro*~lAK*9<{$yY8tF}8<{CXMq<wDV-?0TQM*)<m0Nu?e#xlY4f;
+$;g)8cmxieX~kg05jd_pG1e%gjP;(JoYkPjkXGg*&5{*_8s*VAG^;U%GtM;mMYxnE4xMQU?5%P(s;!C
+AP95IOuIQW4WF#dbn#1t-eYg$5ftYqh^|s$mdo|7nw7{Uc0D`B(DwLQU*Ou**n++VBkaf`?h>{Zw%TP
+RXyx2Hh-^3*L8v<#uI0|U*o*7S$_gex?nmi8`Gn>{t4;i0n!kkfP%k;_wCc}b3R+2o7$t=Br0fkkNid
+9Mr@<4;b#=+1Xboi!`QNuKyP<mrqgJ~RnupP(55qF=^#HmZw^3J}=wRS}9_xp{+XoiVT72`9xNrfEwi
+%F2BFEZR^%rI<HWw|*B-vqA8((II4s}LcH7ZZMzn%U=60PUNssa%w&IKhVFAP;D4sKTQ#(L_u@*`(~J
+j9iKMX|~uz%+qk#G(;n#CZ`~4j2w-x(|9S9Eah31gc-)$l+9#<QI_UliY&b&)tY39o;qQk?2ujoIn0o
+nP2NU6c%`Y$-t8v5jR;XQ0Hsp+TgpWiyQ-a4CNlz!Z5~{Z63q$O{n6yeC=F_}@II#r)8;%v3O1Q9HdP
+|KdS#2-K0S6y9jitiyFOHIQ(kJ^$Oe&|4Q;nK!JL;f+gm4mcC~@)#Z>q8dKIsvl}#!ueeSH+<c(CD_S
+|BC4ehGKFkw<$39&;pL$tlh$baT)-S{=*n~Ibxc9YJwQC=JZaBAks<k4aS1F-@QtmR2~li$ca8EM?SJ
+gIQtifa3jRaGCRlrN@J%XurHs(X?#r*0l14rje1Zo{rIFeXjpVJX#|QO$1|TZ;x^iUE_V_wf9)Dwwfn
+u2Zo?^c{x?6zPFUgJoo7_^9H91aty8QzE#@*A&2*fLjGXZ5GA|?>ot%4C;KOD!D{gCR>_{$8v9TFk~J
+WW=gLxS(YJl(60odlEuCogtP(&Cf}8ispXLjF;N#Bk02)N*#VPBOx7^Y&v0`#VdrPy*l{j~xr`cL=Rw
+Ua?F|NLcBv?0kg0^BNY0~}<uXS^+ztI+k6>l_6gI#lRSJWlT~Spb@^D6wp@mb0z<SKW$X>1r0<1BC>;
+zK-0oIH__IbYsl7|5^dS+qOK!C-p+EJkf0xhs&obyx_1X#rCsApqUL4ZZ9j%>x(K=Lr6?J%+xUjqTwg
+h00HYal3#iPe#<`x*$asJY-I_ZkSWrUbHeUjsp*z^vN3uYmxIS+#Xv1A%ujtG4cIAi(0Ti>><_2(XCN
+v90?W2r>n+I<|FR0|6G9c5Lgu1_CTH?bz0R4I~dUa?G)<`x5lo?UDWxX1Tn~vNZEAKQ1IS_N`v&Myfv
+PBHhPJk)(yVkz$9FmfR(6U0nvc-I>YmBHiwySo%aE1C0M@z5B|4+j}w#pRC@0ntX2m)8AS|@|{oM_n-
+Qm;pg@{glFp;guYw8%RBGCMOX_cuoyu5-!8A7zJ7DrX<?uDhqB9WiQ|{o6qXdK*R4cZ%2kv^C}`Q|#j
+ff(c3^GE5vY6VJk`f5l0_KD2LeXPZeNHZ<+Zz{mNpSZDu4?#P5;)WT&Nzjp=>54`|XX)&dn9e+bAjCg
+KA$v_ODxou{$DKi4eGl>=kB99_t7g$5|ymd~ssYw(nD_i(F{@vR96_1&pM~dBsFry?AQzPg7NI8;xW2
+wmrP-@XGc!pg)iDT^t^AQbM>W_QpU!`wHd@Y?l?v&-6sTMS)xxo2!;L_)tNpU$f|O)mTSh7u-f}Z?v}
+>3f_0jN7-=yQ}$W-{D`I_SeM#Ge*1G<d8q#Q-hch)-@Oj=<rAqnDWdJ-dE$F(X1k`o>iqy;Z<RVcL=v
+{7;jsx`Xum7r9{UXN$1{}&8Pi*s$^kU0dQ`ZC{KGCwcQPvuhIe&yWtg_EcpU4$0LLn5j}=hwx))U|_=
+<H+WozIET*C;4mt*Dah`OmccT}v5ZQnEL8=R^`*q3VHcD`Ar-99F3ln2alKp{mgOR;a#G<M{DwvmflW
+WNk1ARyQ?+J=RMc%n$q-5j7WVMlhwC^4oqh4DB_gl`LIZlpSn+~!*9lsNF85O{jD9HCG%8%$=iebj8F
+^RJ<%FS5NPLgmK9=^a5=tX2T?oNHE3$FL5%kX&c!K3SfV3@~sFM2TGKmn!tt91|j&{CyvNfMZ6YL^9E
+^;+$n*xyaVJ>wSD7>^nR{SXRupOF7JKEKf0^8&k_Zms+`9@tnWpI6$%84O~WO;iJ&bS|~m-AKG|js`z
+sl=ZtU@E^c|)T@Wc)@?Mc$D<V5;6&DrVEmAmBLheo0Ds$+3(zPwnvUj_>RL@D=CiTvbUF2Itj`*J05-
+wfL3XnGJn1>ADUUQ;k&AHW!33^P%$Coyn^!U;oneSV<_KL+@Yx4UC@uDN*m$E|k=!S4a4EPn5$Frht%
+D<G8$}1(u_{b%_+wqu$(#*?gjg;FhF!hbK1(6ShS?)Z>RFRtM+pR1%>C%KrEOP?XwZDj=9MfeZWG=3^
+NDjB)dX~Y79!f3srh{Ui>ZPdoIv3L?Hxb6ZJW^vPgPWR;xw4HrT|M8(;!es$^q#<J1K3%_`y3MdgW?8
+}k#~x}D8YhuA>G(e(J%<_7H?Py%~u|0k59~0twKX%&;9xiK+7mOz7zcko2FsYRth<uGFPQkwW2$2J{2
+(7f~Gq6>=^3ZZ%vad%W9mB8rl^+<g&fYPp2z|?b{5rPe$=fE<1vHmEbo}yTBSwRDXogd5!euH@PV8H9
+1*X@zdSNj~zB?LufaO)#&$H1rDKX5fJWNtl~5*l#J#H<x~%ku@Apww*gYM0~J<rSW!_=((gU_9(GUrq
+_yy^C7)S12lXyXVn~bV@FsL?1U8nL_<|lEHkGVvW<GUnU7Ps7WcjYMacoDWq8*gd?qCq~Nlx`08E>~w
+8D7`Du)<M;Qejw$P4w!S%s~OT8_<Am9sDpgJa^|j#P>b5j#u-1m9~ya`-6Gs)8B?4^XRW~-tP@YZKDc
+mV(<o7Fnf8C9aRdok3cProfVCjX3?77kYubmW1C?Is!!E$#0R_jZKoJim~&yoZ#?dymQ-PTQaNVvKn4
+A|sJ>L!U1NMkoOX?opk9m|WygV=bvrfism$ao`k4HLAC;qQ8ZJ^zCvYxZY(OQtzt<(eQDrcCW1*gfk>
+=BCH?F)-u47=6Md>ocd=;tViC1H7FjCGLO!XIt+S-Mfl`a-iyWDSJbuem9d~@gcQnwk#5>4T4?|ksS1
+4d9W#=r;Xqel4Xe8TXG)*VIF{Pz(V4L?*{E6p^PYjcaKsk?Yt`+Sd`;`5sL$INKABE@!}Q;Yb!x!?j&
+eA34Cjtcun?2a$n7x(N4b5<z5&DD>U$>$|bH{Zok;d>pgrs`NGemSWv{xlcEhpN1WhM$!uKkgudLM5O
+}47<3f?=`PRrfMHu+i}4|f@zWu*+2Is<eK;4#*gDtE!v4zcBw>_lCDj^OkuSmtigHz2WtC*J$!F=#_p
+IpVJ~Iwb64z0vx|~8U4^`bWZDtkZufm-4;GW2koh9qq1OQ2QytiVPs$DbWiVmzxW26K4QF1{ao8Kpyi
+PT)H4ty?7no3Iozj~Q@%Qu+kf#nc!+?}O>~+Mb*LEV!l$rIXgN~RD8r{GL&HG46d~4RLi%W}Wg!V%OZ
+|>RrBS`*-b<V)~rbnD_3T3r7#(R%~e^{bOwwqD{_v7{5o96Y60{k&e##$t9Y&bqbxPcOm<1>EK@fp9X
+`24Vtv`p`kbrvqAibi}jac*Be96dff*K^GgLS1YWDPCyu_q(Xrh?Rt6f%@rNx7s8wJ9y?Y#Ew0hr*>l
+y!pR2y6|kLrK+6CJ+z_+R?&c`(o?s$<?^T+=au-AG5&Pz*g7^n`NwDdN7(~T;c=L-u{~LR5H%YTC6xM
+$Qt2=YQ5-&l75cCn^>5Z<Yk|ij-KmKQAVvjv|S{h#_fJ_m)Yoh`nEcCklhPn}_AXDgsek{I$+}iE6Yi
+K}&G3TOJCxV~KS*<^*VNuY~R0a*aG>{n#`wet*`OwJ_zHr5QDPr9#`sS9l(-g`&O~*4U)-bt;2Z22Li
+0{SG8yQRSFJd-E?c(?E@H+(p<QuoYcmkj{AdPx88r&?JtEQ2r!%r1T3_L+g@l5~Gl<1*Ch+r0-N}26w
+zh2lu@&BzDPQc07-IONU0Cj;J?f_hZDC*sRI{PCG>Vz4SJ1Q{-{znnWO^MC%qq!c?q47~M2S1OAJNPM
+207reYk}pq(%aaV<lipo^oD<16r*F&JC!MYO%VpIMF$MhNTt!p6&r?p=ys`NGhc&qt-0A}~NAUY?qZD
+gQV^@IxC$3hxzx*;!t4edk(d=rd)iRx6Y-0o)`O$}eL8T#V3v6Dt<Bl-IQvovs{_H1Q6f)x*j+E}GbT
+y)nmCDlC5;3dLPv0j{sp>QN#G=L1bl<qSX@`9VL#^7aD+em=x^lqn*YW@Bvpp4mtfU*@dP#RiB~Sfxh
+bPsd9Mqs$n&-g^s$X@NgugQHj$6ld`xF-w_+m(T)yHZLVP9-yc~Z~%P%OZ|o4)Qxagme3fo%={ZU!38
+KUz=ZU2wlXGcFnike{=D8}ex>g4J51ZVwj)h`BzEdBa&BF>jhN9o-v7TlAM2f&kq;2<TEE2)1FA1cBH
+5CmV>2{_7G+o|bPAKI2CVp$Kov;cI-b2OD25)HLUsoW8tZT5~4j=bQ8{SfwfW@toedfs!3Ta=DgsYTJ
+~Py5W-E1lVsAUmc%1a2#3|8#se?1WJWJTAh0`j-y>3<=(N$uk=fQzrl8jR)@JqzkjDw;31ZC{Z{~v&I
+c`*$ozA?W4J%ck0mPoFzXm5cyWoTe=yo^l{*O!Gdcau3g7?G5w~sXOx<?G2lV^eWlaPbCHGZlaix!G`
+nrSP=Z)0<wXWj8kLbN=4+rT@;7V}D>%D!Ma+vA@G=^3M2k<@Nf#;%4SeTUuhp12dry7o59MyAFsiG{s
+^UHNQV&#3Z=Y9sg(aNi@J+;o)R!6mde$kt|o|bH~?{VYsd&|)p4vX^bCd{88;Qa|co7?w_aqK5JDW`#
+P6(RX1pT9yxZED7=P1dDXgMDJ7-TH4(O9KQH00008031s8R%t{HPLcrt03HMY03iSX0B~t=FJE?LZe(
+wAFLG&PXfI=LY;SU3baH8MY-MyVaCxOuyKcfj5bXUGBc}n$aU3EVq(lJ<x)g*iiiE*yW69iE=Ouw4{y
+n#6f=xjliko}w%+8F~snKijuFO@2d|hh8c#7AQ%r<2~0o>ww-m-|R3S(VpGc&op<4#l79eA*x@B6bA!
+B7$)GejyttP(7W4PmJ*w<5(Abc)!XEmLR_o`YJ<0J-8Xo+%{_#6BPbYxMekm{?`xfKuw(oFON2^DC_A
+I)jeRgkC_p;>XhHk__+MDWMcA+IA``(k`waP_d~KITB~Y;1$)T!F7JZKYo6;#k-;rbqwPapbPIFLfv}
+jjZsMbtG(nF^|pt79faFDU$VO>)?|yzVrM6zR^W6pLaNO==FmG8O<n)0LCGgH7%Jhe;Q=VjLd@sBw7Z
+R>pm!J8EW7@E9=03)-M0{m^+QnmwyV@1x)&WQ@lfO+lr+ZO=)R<djyXVkc|FTxtks+4YEQ788C{oFSP
+;L<#6@n_Z-0vEo2D3o<yC$VURhr))h^PFX^Hq(gtiPfGT32sEN_kuc075XP)h>@6aWAK2ml;P_Ew%uQ
+t^}r007$?000{R003}la4%nWWo~3|axZdeV`wj9Z)|mKZgVbhd8JufZ`(E$e)q2+JQScB#cf^<s6fzc
+z=m}jy1W^Nz*w}+R=0^%o3!YE-#NU9q%KZ|`5`fN4nLmzIiinUQ;|bcmi(YZQ%fSMw&@fp_>uLcD#Ss
+pj>sbv?^M&21IOXaL~UqI%R8o;&XIt(I&lR%3|&37qCPq59bl&9SD><olBeW%Az}Szi|4a4CHH+>@|D
+@SVWl|LZs#p7QuFTvSLdd%TnCW6DY@f&Z<eY1Vz6aOKJvOS$KF4++^s)y391HAssq(RF#W(XRGi7a8_
+xP*mKCoZLd%LGQ1>shOx>3|0lX6BvHS|<aoqQ~a0LFShUf4dWwxYGeftCkbkyI>@`HE;F;}ZY$)p6q%
+f6~54T;HiMc}huukVCxOZG&%!6e|>n$(;rj0fDgS!w3m?j+4N{Dl0}IdK;ocAsp?ZT&>*zIp&5n<M!s
+4(E8Qs1IeY?F80MHUs`wQK&PLAto9d699LA<`9!obiA-EfU4l3l@*vf@<&s1q8h?__)~BNF})#oCXyu
+*kij4297QLdiH>%WIq<Wt>Fa_Vcv;FApT14WO`r^aY#DIU2S}U<^Jhb_!sFIsUzSF*81ffZ%0OoRPY;
+qz0dKpG)hCWFgiVG^if?>4<07iz$&aFwY7X2aA!M~ACZU@aQ63tlU_~MM&){cuW;H4KQ6a4pr?W~fo~
+l`L)#Q55^w_@@>s&CJbM+2#M$<`A@QdiCa!`n_8C|}xvgd@Z@#J+%)*5)NgJ^w#ROa0}86xTkUu-?R6
+i!Mg$Ybg<bv}j+6C%EMNoEt$BpaMV@?6wH<vAUoB`=TZTnc*R-BK>@Nu~u&$8o=%RwQ6GA?%r7r*Ucq
+Cqj-+!A;0-33?NV+9_!qzDvX~3YU1Im|0@dt`7ta8pc#$?U8`l`7h>7$n`tD+(u5>gf%TACA2acJ_0}
+Q_DQ_Ol&{Q~GbXtTlQ|#7WLr)$Yvd78=X_>N9FwB-&LTUHw23k@i>)2AK4W7|j(3>Q&y2x+w1c9#HyP
+ET9)$RI)U;<D0m*Y)6odu4Fgt_pU^^Lp;%=rx%I~71vrHQc7@CJq*i^!!7vo{W+7?zpJS1U`chC}ZJG
+e}8omj%w&oZW($n9vT@zEI$Gvj`pLmAYb*IPIK;cQ>e$Zp0$$Q~*~#E}RoU^-&;fd`aSw{*fGCj;0B5
+er~oR_Iz|>kaJt;TxP+H!3QBBQaIq`JjWiZBrA%DalQ*N{NkZTlzMA-Lk`H8fKqQSDm4`Ps)ltQrvG*
+JtGium)6!#o8egu2M)vmc&7&(TS0?i8wVecYcur#^9BlC@;a<8iH~ZSw)4tQqQD!>r5m8m_}NG|_4Wv
+h9!3!uW@mzGimI=k@$R#Z^(Aa6IRkOg4--PNC$C2qaujbTOg(&)2`Y}H(Sf1Kx9A|>DRh<%ZC1ag7&i
+_@aNK(Lu`)P8Eju&fJWeZjjOF8VrUiWy?bHmR-((UPWu!U?cG7W*FJ`XE?*iH1yos!Yb`RGRTnq<b$m
+>Rj0?w&4fO{3~PNr&3W!o9JJ-N!r%~X-D`8t?6Jn1S<sB0K>#>z~Mf>S;kV0V2p)>Lbjd!>eRll`1br
+uD+#x3eY^;GD-f3oV%hCEEe+9?gMH(g-g!-=18f?dF&v_-6R$g>b4}ErDSdSl){ESlsHcpEa1iirC;A
+LN082Qf-|D%VFcvd$WvO-z-b_&~f&8mii=kSxob9r(t8~&l|u1=$D!oBx|(&Cv0A%fr*Egx<X431X_=
+TP8O6`r|43mO=TKI^C(v?r0jy3jgIg>f#aIbQgh#tnX8V?sS^dYEjA0=aH_ARSSz{fz}bD*LmPrs&Wj
+Vz^wgikxPC?sCgu@~8$|t7>V<QK*K~6s^~4d6oA?<uW;!%`T~KHMaTQMyu`4fFe8#3mdYqRHBh|>6Kg
+@$qgYN5DlsuOE9hr%J6MmaR$yrB}X*o0iP|BCGavaL3(QwjrUr_XoEW6>%y`8}(&(q1NQ^~aj8^y|DQ
+j>jUp*H$HK++@``wJ>QU91n-!tIEG&19BuUJwYgP?mRog1lHO$HU-rhvR3th&@}H2TxPKxWcCS>T=Iq
+1~$S(V{0%dX2H!dz44aIFTI?^7&Q1klWXx*dO0Tl+n{<;M*Qd^IDQC#p-6I`OTS4C_t4Rs)}(Rl-tMO
+%Hyz0HxruyUS@WhJF`2uyETG4>xV7}#Dd{C<nm3CvgTan$pauA!N-tbWW;6F9{+bDIF7$ljD>JNDp#W
+0fVGb4kZL0G&6eLM6&A$denlTLI)<VZKZ9ICQ8Ke8Mg{c(&?zUT)Z(}DLb?9sO<E?9&x>k6#S_!<#s9
+DAH9EYiOo>vf|dA{D_oYHpeRIx4eP!RG9H<u0eCyPcJo4cQGGIy^*?VHI_*bq6czl$H_yZo^>Q(sE-F
+BQD*EBx7sQweyyppD$%%TFPoZzXmDcNgs0@N0;MP2K%kX0JQ#jhY!LQgeqE&KK_Dr0s-$Bi2|ksq3}u
+!KveWHymG{M>AW;VK~_v9XAX2FHlPZ1QY-O00;maO7>O`7P%Q&RR92zg8={=0001RX>c!Jc4cm4Z*nh
+kX=7+FV{dMAZ){~QaCz;$>vkJQk}&vRPf-n@T>&x#U2J#za171R5^bwTBDEydo?f+1u?Q5%vcM{IRY4
+@1M|1We_6ffy`7$n<8F{G!NME{l);LEZP?Z^Zi;Rqjj7xE`s_Hf=%4U_%+It24tQ!4owanT@RbS}e&9
+!;ep4WLcFUm9h;2+E4^xmSbE|TnYmhi*fZ=a9V@20J@S$mPU=hd9b%(FI|EwiS{8(r2s8Yhb)U)q9sT
+U_L#6#k~Si*-3`t7>V0T-MpDp?7C_yHe2f8~#b}&fANnevvn`Y{l?+CiJVK!4C1eHm{wwie_2NxZ*|D
+p6lncyjapx+3}02tlFw9X8h`UWrzM<on7R|>d82HUCq}^{(h`xEkDg>AK<5{rsiDN8{SLQ=jFi|{~rJ
+K&0hNahrQ?j`EvhzdbC?!)0gMja+#ejbNcn7n6>onr5cod{;FvB`Ri;24bhK%)w}uedZmjUtlFX~vn4
+m1U$v$Swh#^hzr8J0Y5F?Lpn=gn8qBI#P128fIj`zTUChoWX}Ml5(?zi~v$p^C)vNTom#_Bj-76M=f0
+K`S-6(izQ7)?F*)$n`F;2c7?I8Hb6up9FQ(aBo)N1-?mHJk%OIVn6cAn2Zz~JxY%O)2PWWNYns>Ya?&
+~D?-J<S?5VIG*K%#)x=dNoRt&yrQ0on2%*Nm(VcN{x;uXJYWPuB%#YiuOFe$Qc(WX?{`tRHSvTw&={v
+miyEcy@Ho1Y~;+K_Va`Nqk~s_=?}-R)dU|LzTQ0^n}<h#`JSI?7_cU)gLW_R6a9W!ovCKad0rcw#^#R
+Is15EVud1^{EX38aWpP#-S^+=C^yjr86%#d+l>z%4ejHslZGJIM6wq>>)@P@tWZBl$(w4=a{1WFzzuJ
+Qzf63}1D_eelUYwn)w$EEThJA&OKiJ3P<S<{=;sMvZ$m$R4m9E6okTv`*rPsP_o;B;*tk`S%d6AdxIN
+^6ZkuYU?xmVel?bRFjF-~X_@P{r{=WTm!is7%ZB2$0?Svf~k*Ch!<O`p~7OJQ^J`#L{UxUSzG;xB&H%
+&JxHjy1(+=6#*#rs@&?(y#I}7^rziKlRJ@+HU(J_%WtGmiSSbxl>3ZiCT?|LeZoYw}~$DV(+`%x37-V
+<GsVzFZXv}rN=+)z1~xR6@u^m*PDaGWBufq>mNgP1M|vs7O319{}=sn+QOP+`g5d?vJXhI9HJ~}%p|=
+m6oI)k^yEkSsc^Qbmic#i)+$tJM1^JXF}GChV=i7btt#Evd4XT|?)~}go4=}or+N~eAG~_|djBYyCQq
+Jx6})}*a(@rsJ$`)e$Cvvr4t|7Rngf_Lh;74BGMy#^?(5**J+T>JUQ`Xe+uyxIy8lj{{o`Z+6E}GO-h
+8|F=XKK-i)-5Gsu~l~cY}Gp$kxktpo%W@1^%5WEXiy5Rzp+pWubPaf^wkf<ziV~hF})ea*lQDY6XAu<
++4~cMFZazfvM_TRlj!+&-Y}%dVZdjXM6@An{e;m{()Mz-Tm+P6j)tgsE)3-zNT{N(eaCy`*=F-AE-ib
+I;CmTDy}F^Cqy4rh5TxkuN1|>KWawel^?rs58fU}09WgFJIGG;Cobr{!@~$@b;@i9+Nu8Z-aUAx{vGb
+^z6OLDIs+Sfy%~ETMo#rq6@2sdSVQTnrrL!)4LE&p2<_fr2L~StMe_zb@|c+Hz5M=%<Mi8?$8_ipo__
+U5JW@6kdlD^mbiBL&V)yXH_}(XjKD=jNsI!iEgrVh_m@^p+21ms|@}ye8Ii6^0HBry+VS&qH-k$F$2D
+H`X6(OOgy3&lAQDu_*GlkF1eXI_}&vV!qL3Mf@slP1ByrIVL{fA+^-Qf_I*O>nE??jP<Bu(kWppt2t5
+N~gX)2PAjgcIY>1p_eSSmtNh>{^q?o#a&U+q#bbZn4bHuru@`;THy$n&32?)z?K?T&yqb%-X}&*37PA
+HM6UYHPu<Gm)7n4alKX(&x@bcih)vPlguE(IH}aD`m$*9<hx9<qXuMN&MJ_zb`nKNHMl)~h)XMRNq0Y
+j5I-1X05&O87*Hoeb#l~g1I&sBGtyvwA_~1@*!_17&3=z$vCK7iewlpCmTIWL$kxR?#|4T^RK<i_KzC
+`m4_?3B5`I~wAPNfbuo?gqXIDdgQ8Z8u#YU7G0300qc4z4WE&@vS&m4rYt|<ari{$}!a09r#68puR<>
+k5Js0b8vQbALHnqc=Eh-%dhKrHbeis4%+@%0*isUudc_^c?>s$5<Vn|!$#B@dq=!tNNEML~ZK;tHUx;
+7F6^yjm~k$y#A50!aXf=?h9bx#C?)wFYehuqPUYCxmU6MSDIRtlPz4bkFohagd@X1D6I3oL(Ig_zdf4
+;#N_~$vsn&iZ!+>d_3AFfM8E$Gv<4x3%iwp*Kr=GgS5;q({$)Q9{GS&xw#U+71f+ltNQl@Ct>8zBUiI
+?wO)Z1#0sDQ#LAiv>{ljY#E2CjVrWJN(L*yhwt}FUx2R;v<@S{fb)hO9G-e|hOGi979yQqr$Pf$<4sO
+nkwFQ;9Q+-Vn?$&r7Z5fC_Z{5v1?JXi2k=$mi@sak-B(g;`LVI|u2nf)EqA5y60m@lEM0By88@ZcQ?-
+PTK3a)vkkxe~Q--nOKgyns$8929U(R}ZNtb4N=vfJ;Cka>S>gv;d=RQ}cjQ*V}yKy^WwcmCP~mbcDEs
+9a6~<!?PO&4$_t)s$3l&G+6VgRQp3df~}C<*nJ*)x5W#ssgj&is6H*a4Ne+d_3XuQ?3{vwk`wU+(z&T
+s5JEkp;z0UD}<VO7LSEkvNg2;Jj5fJH-<|!?D@P~pLvHf?T;Zewv+7Vm-<1ID;D)sG01jLCRsVR`)IV
+`)c<e)*azTR9MZH)FK90l&_UsT9>v<Q9<+SCAcC>qdPQ0z3XXB!wqFrODzPMtl6RQz=fB2$%iR)e4R8
+B&O>><q1e3G;^H|UX_**@53Ubm`$;k<9%9E2#?CEcYs1Etq77^!G!QoSfyCbIE&UZu6yAzGcR;d0jvt
+)OpEy03sbI|yBaPL3DJ2TQ19Tv0m=ULMZ^_`d1ckL<wr$51MYI~lws(aVTX`bANTZa3vCo(fjp8Rgmj
+<rl_OwvIdBaT;N+MxjhN?zSF^<Bx!?{}hCZ5r-mGU*#-(7@*5HtQ8A;~PiwrmtP1!!*h?Z@9Ylj@eRb
+NJb|0x0&GVsk?`H1M2i`#{XHei}%vbg3;pS^W^ke&%@-Noe9?Z(@F&MG&TrAs{n0)VzS0gp)M+0E<vY
+}b?OxF$#JNr^p!Q=FSuP9>szJwsx7)smiKy7|4I)O`g)PG6<oRO!FB7<D88Kq#;aJ+pTeSYdDN!CMbS
+l8!d)C|Rrz8ezkF3_b`M|(T!%eymY3>>qJ*U)8laRNHX{!=in3@GPH0q67>YC&^!m8WE<4EtWQ_&z@2
+`$$W<B)G+umG*9fw|#;oxuOAbB9VXy=};3F%ZYlXb`!scK>x#1+(9Cki#Q<gECZs|~kUC^GNwCTGU5&
+JJ2Oyu<$tevFeVKDw^$sTG;cl$xCqDEHl!dVJ+R0#WSx7n*c;&h3=T9btQWr4JC>qYJgmQ-x<!eHT9A
+C#D1_DQOyMt^m99a(#hlITRBx=HYqb4J|Q49bSzY*eFs6?<xV7zvaw|KX<nh?2sAnveuy*t6D7>kPTH
+r5Lh~1kMca(0phW9^51AyqTg!r#V}8B@aIa*RZ!MV&L_RgVrbH>m3oRd*cCS^bgavcR_k`PZYO$3JzL
+pd_)Y}W%}sSB?>)_n(EkFdb@ac~K3=182bf2rP7gX-oSf!oitFH^g_=ny>@;wN1ME;t=2x>6ju+8UAl
+dJ}&6?cMTeUBp3LoJn#guo8dZ14wU}-w_Ua$<Y`K|TQ;tn2cOYG3iFwb%!C8(Kp7~Ajj)<ac9PlDp8%
+!-BEIt%XZ?y57m5OPkYKy#oMF|mL^&5(V}3cQF<fT>yf$5aAq)l3Esxab1w9-3W?77n~s#mVM3K${Bh
+xWFzUtFOs~X|j2Ps(NI{L0fd)D1g0GK1M|mz>YS{D9ZD^E?T;kQ%emOa^2@=?|vhzk0~|azT#HYOa9i
+s{p3vgdr;5GYTcaEWDITV|3i188FRJbAzKy!4V|{YI$&MzgS}L9pI(;j78r*HR-3V{V?HD3XWk)XF&{
+V%O`UBqG;L}Odg3jmeXCB*57C!*Ju}FlY$}b&h9jU!Y-uL7i1^5@PQ3++iC^58*jeJ2J~aIsKrU+MA;
+k4g*NX)*?ElkHU(LGiRs0k{g_1WX%WC!^)FRUyF}tfd-QZy3seHHdJ^(P!m)jR+dp?DjfefJ9q<TRmR
+-g+s3Wp(q1Cr9$3EX?HQmQo6??*xHd@0+Yt#i93uue}4Ojp8*<?DV%)i?mV|0a!MK8Fl!)QSCo&j$Hj
+iD^rEn3r^QpOs0rR7+K6Ef^D$spb~ckqX|HJVsCD^J1Q-vvu86HPN#%(U2W$?5U=8FzBUj8;F}|122W
+lFOP_krRtRDa)|wy;{U;7;LXn5n2&gxQGehMguTR0;%g{)yoOAefjdSZk+HjqQ(nD3-KbDD4E<hI-2B
+M)#8Xaa<8n23HDJ4aI}Ub)nrS>R07F2#g!45?UXU?o1K{Ajt8(Ru7_zmm=+PlHjn={qzrAe>9<wc%B;
+1cYnPLK_Nyut{UsvnZP_8bXnM;K{&a-F96FNG@(|3<u0_t2?v+;A+1)=OB73Gt+gM9+&cql536$O}22
+h!dqb{ac0B|MJJ9&j3iyAwrJQfg_4e03<~=*pmh_xEUItOmFukX&krJMVww>F-QY-)y*3?M;XT);YVq
+GfZozPZ&gYbFv&~AK(B<&fuwQ{n&^b8z>?+k<^IOV^WACl&HQ%f*l&R!X;ksK?zf$Ll(8N2-|EdAy_D
+ZY)D6qATi&mr{+QnK+woQlS2n`gEVJRESEx-ZdPhhU8)1Kwprcd9ti_?Km%}j+fFu>&LOI(bQN*REl>
+(o|3|9}G(}d?o8L{wgQ8VSJ`j*Uu=f!}*M34VR@W&pMa}Op7<Z?d0$q#53ZUv$d)546_bS3?XAlk#7S
+cO}v5yhwo+0<ZG|M{H=uoYXng>{PXBgZIj>D_M(XW0Z5LZtNC9pqAMRQQIhR17kCm64i$z(G2ej%ZH|
+6VY`^L$p-Sz9st%Y><mVl;T8Q)%KBB}@Mt8e+y_7ltmycDyO*B9!m#qQvIRHTJE_k7}2zX`nVV)!usc
+5T=z3kaVCw?vMalTt?hu_Hy_jgPBHG)#Sm050~aAc3Yf67VjkmB-jMS0vN@1O31z;-JPm`!h(nk8!yU
+x;-Og(#@MuI(x29=YrIJ`Ce)o*t<t3WGQSTx+jUu@w<_2={FxvD6PPPNAB?`(`0v06oG%Mi@LZvsYKY
+hwa%p;3W*7NG)v=<?=d||h$O8^3s6XEE$7${1HPESSVmR8Ok>)&K!gl34lQcyZB2B?0T9r;yYG5IF>c
+Lr6oxx>HrO<K!6QE@8VE{o`GSo@cOjOtM^5byuV)uCW+ryX7|MMt4e7k@A^7UT&m%YQImk0X;rwVsXi
+Io5M>;LN|u)Ns}gx@20&NM5S6ZF<l!}b>h0RFv|GAHU9Y#Z8(FlZ<~?a+p<Vo>4b8=L|LFNwZi^#EK(
+=*E8d@4&dBH&lA`*Q4XT*TN|ZE~(~OJ@0g7!ctGa`r`(Vs8&r&%qQyj@a-Np&E?n=$1BB7h3GhyIz3J
+IcVDCL;SG5is$HXyh9tcVl=t))aKx!MQ55N-8IC^ncrhJgoPt-?OikL*1TB~>;eox|r&0+%Wpih2UfZ
+m(R>cxG)J~@jxOwhKmrr=trG&$%21E95Ocx40s``2gEY3*OQ*7frztVU7j}1Fcl>G;Vg~Q!%pWCj#sj
+H8Q+i#L{^-2?Cx`IL`N-=M<ylHIL|HF&Npb0V;bQlzmA8>eB9A04YAx@l*0`8%sP9-H4qK4C6^fL=jN
+(iVZv>eChigDx<YL=DOQjAO}2!KQ4)jD2Ob1;$?mSw0x0W5<mTPjhMMA9)PycI6j7pHmMC5;%EQ7f{p
+xk`4m8U}SCk@2|-54E*;_ZhBk!LG!D=O4tKjR%(RzsEP7ozUpG>jKn$1fDIcQ?<uB;p&5;vp`%+q7Us
+}uyM!hzERSub@yeuVUF%?)i;{$xjNZqZR)x?3a&zL_!n4Cdp-W>c|CGt+JhS~9%ie*o0E^N@60N=X)v
+Ht&3(+5!tg<zZwp{!<2DnD>ZeS!hv)z<nC4@&*MN`?T!KyI$i(crTG!Sq(%B<<f#==Hi9OIxPR8&Xj;
+@mv*y!qqJ*7@gCdsQj`v{I|@FrWg6_f*RRehxi7kYxKp5?}WGa34BIARRsp7&_Z?t`Yzi~~^26!6CCE
+V;pl)S~s+?9pCQXPCFVO<y$6V%!BgyTK(l_oA@e%x!uit0@AU2OVLQ@9RKQEn4y#>1+5XZ?Po$aVC7i
+CW@6sO{g{`bebV2Thk8R=?~dhK!DyY%`eu{Qc<GoW5PKy?naJ5H%_Jwb{yzo9}ywnDprnPD#7BMZft-
+T24{aDgeNE9l&_#O-Gcx{g<>W8$Ad9+hA$7?vCv~y%3Z3)a>qQCJv%S!0<IV;w*l&rZQ<|hA~!Pefo<
+el^&roX3xSQT=!+5_6?@EfQGK1ZrrZI+a2(<7{xQ4TOuLKXSj{#dY`lXOTwnR^o6uI`cBKJHhUQYoMO
+4Bd1!1*XUgH-tHNh1JLh9QbWt9>k-MlI1bP6wt7rN6{Y_ro8-1@`m+c%64sx}(1`<crdqzo#<l?{*sp
+W=Ky5vRBkuji3nB9MyiGP$Vd0<UM%<KGmj*3==eHr7|292N;efvHo(eb{_FJ0V8|_c;gwC%rh#eq-AV
+VW-X)J16=yriv$BdLcXjF@jMDnw`bzH5@$~futWP^ig;^o4Y`Q#^uKP@EzdQ5Ma*$3k>=&#=7Qp_8D;
+RB5RA8EezsWPyZp(6vkECW{OqeGmRrqM==<@pz6&D9}LZ==2j5gZJXwRa>ypp^iK&mwb$@A<J0lFh9Z
+m(MAM?US_<Q}LeJgqFX6<{FzD2v&dtplQuqL*GV1FBCq{jrF+9@yQR{SD10~!p58nMB|Mfl@M3x$u6)
+z}|(?5nHD~Pc>yl*$wxV*2WXyzpDqiWU{%aH7Bk*BBCRiweg9A-<Ad3de;bZ~;^Re9e8`%<ii$B#SeI
+upcjXrm*kWz&z{6@2cj!&$C<Nca{W;bd^nrmIg3cs|*ONPmUDhQf!DOBCf%W8jq4rQ7dFpYPUR(C#UM
+UCtF#tk2Ok#D2tfO=v_<1)k>R$D*#v9UYF4b^%*ASIvaqZ*QpgK-%nCAw`JBo>b1!q)>7g3r*UX^krk
+I6dPO3m%ZwTo^tgLL8BuQh+mvVfh|i5-g{#W!((?@AF?H_z1fD}F%w2$W4nL=>nUKoJU}b;5DM~@T|n
+63(1~#nK<EpH;u&1_S>ZUbA#jB^&ZK6MwD#_65djkUm9BB=_z&XROIQ}bLEHCEpXQ=}GQMGChHSWsC{
+%rZ^t^^MaYJoB!E|5>+`C~^NZcTBoD3rUbMSrOohzuW@**-01)cK)Ms3;#d<t}oO44xwD^Acu=$f2%R
+b4Ertc}#OG|<!wh@o3cTxWcyP5|;xw!{)74mdQ|jpWdamO~#kz<(J4por7;`mK{pv8kzHRi0!UZ?4Lq
+jB|0OnsN0Vj{ULoN_Ncy8^m28p)qP_03WUfdwYFh-EVdG;i_pk&|wlec;X;522~CDki=A>5aGR7eV!L
+*MLQgYoq~_{=mje-uWHQN)wc`q!F0rd^k>TrAkjTt+8wTEvM`op|5Oo_u8E@fbQ`A0crVL&!kV|4B?B
+cI5Yxk9BLhzjt#=Es1UqGV@4igCf{O4|qQo^NnjU+%1)X=wc`*7TrI4|7B>rAt2|4W2RBL6kw=V+|HI
+L0_jB|Cpu<_k;=DoP9@89IT8#}(Ci$&74iMQCia^va^n>>t7tsFt$#_QQ^u}xNJCt1Jq8#k1*nRpYqx
+M5YXQ_C`XD5fXCjc&x~=LH+^UU%^0;s*J>U&T|{d%-Nsp<)VbIKcvN?t`H90_||&kNbu+qf_E!y*VUJ
+@059E2a%mylOE$Zr<^xtG)Hg?Xz^nUQ1p;@w|qD3Gee7la_;Hh$(O+@f+q`l)9JhU!&mCb&^N&s5yq!
+Bkhn{k(3lmttf}Tf$KiY6T&J3ab>9oFb?R}kV?lnLjyb$)7!Fw~Mj&viACkbs53Pxq8g|qz;Aj)3u5!
+T><->}ilCEI05_ovpX=HAc&i=7rUZD4l{x0Yc()0lYp#$U~lOIXex@K6NB=RaLIF587vvd7(XuiHUHE
+#og8QyVq9!Npa*qNk_QQ`b&znyJyoZhEsh9criIyNjW!df$wskK5GQmTLnb21!v_9A!LYR{3>?~5~l(
+3s`j`=C6!KA{x~7q=!W(HcuvIWd5s=7aY>Nu#oA6|Loa=!TPmwVvb5;5cUUrTAj-jlSx_18RDM!14R1
+<R&C!e`r2E8*~{#1L3#ru|6Z}3@&fol+0!B*QAFEpC;mHfqNYY&&_9smUs9kE+N0J*1~&?0jW)%wQW6
+wpBOlOcAlysTow5o!K2Cf(sk9K#2c}bhk@E`9RAG0AxQHCU%^vB(>7<S#$ctBk}8O2Ebiw7H@alfBPP
+$8Fy|1~P`lR3dgMuC^)O%wFIvVsl?}qEaxBDcWZO>I@3FrpWaVZ1qiD*n(F<yZ`{Fe1FHzX9F&V=3$4
+2RHRILiu@0<uhyX-tzA{O0A&V&$6Ljc>(ifB_1j~K^edKBeEozAgAj$_k;rbg;qgA24K8uy_~Z^6Bf+
+E+>-@_@7VpLP7ui#FkN%WN~$A1O)>!Iu^{)$14@x9b%Bc@|e*W1%Bo|Llr!b~Q9HYX7LJA#O(N6zyZF
+2@_%QI%U^`L&$#scMgLQc`Xk|lVx@3c*yf01USWW4c#k?r(d2H?I0o%ZiR^O>F(#2UBs@XWa^uqU$4%
+=V-Y(D>kTg_^(w2|0(RnX@X!-_J<&rZhQMwRq;b^tIf^e5pdb@Y7y?5df}?A%L=7f8MNn~VKuk6T{7h
+KIga?~LN<W7r9-<?{BfPsGWVjM*pT#Kc#g5LgWFxVuBM+e??t6@tC;ZcOFTq(6I6M=F3z$9P@w$)vSI
+B<rV2NNHh4+~F*pIW;XS0jBa)wZCwBrIz)(ysu0xMz@&d$_5gm^n1EXuz%0Vw1_0e9@OesYf2u}&xX_
+H%iikf0EEOBR70!gvnGUv9}VNq6vI3KQgabT~LDRR@6KM-cO(SuL|`9oUbBoeT`+X1TYgM9WjGEh6<V
+^Q^W@8(+-lPzaA~cS*M%z0(0VkQGM65#ol9jH|xx2s8P3$9Cs)W-NIZKs9YLPrO8LKwKz26piQ>=}mu
+}&n*TlrKm}^TB)By_#rkH1jq45A0O+RYDFd~S)(l#u$Po3?>xpk-L{LWGs6vD<=S=7>Ds|%84DPNwLO
+{@p-FcN2t!z6J;2f7jQzXU`gg0Hwyg(RNZ=K`E&Aw&?a<wEBdT?;-M3JV1BU^@(t@itqkJwc*=(RPG<
+|`lO*}d<j**TJohObrsiwy=3|d^g#zSx3*&;umv*FPuR|o)YgGGyIdj57|MD(J!`5{>B87BP?m(J-Xg
+WJSb&qFY$VUI4^NL_vevIkoSA%m@}U@@Iydt>9*(^e~OT!#C1%$K-ytmPb%$!_vhoqsH<b>o{Pe~+<8
+m+FLQR(bXTEyb^^wYCD5rji?@v|%XImO}c<Jw0ZlX45DdH|v<Mt#IX;EB0fi&dXlvE3LHAo|)BJ0o8?
+%j>Q%lb-m;_YLW4}o2RVLDlgnFLX?y-+FB>v+?4-%<l7=ieDx1=2&l=UqlKhJHw)gh6_N#SaW`~RhE>
+!3F{^lMqz&T$a`)e2*uQxJy9Z6cXdD$W1oO4R3HFy}>+`MoIu8Mko#p3<gY})!z}UfeqC-FBawa5sH_
+w}y5_&LBNCyEUZ&OiCE`pi*QI`&7gT^ANkaS&dwxY-`z|aZ~&4H~@>3O7?g)o6myo;_lU#q>QBA%k}L
+O6DUJL4qu1+>r^sx}Aq%w^^^;X6Tk)_ig{0Z*fKyLkBZU~{~GJnME7J)su5UYH)V8EO?Thn+w@uLb~1
+L!B7m>hO0Xes|1+&?Rk?7R<>i*q~yYgYw$UcAKVvJmzJ7JfowR;O2_X%`lQGhahl(tTD6<%pz8>?pWl
+8<)zk(&Z<GrZ7+=-HDlLRF<kFw4J{KX>x)t?O`2X{p6@grklBQJIkB%~x-_TdK`~$E%i`2_-c#Rv##7
+C%;y`&{&S6H+)j6&NxU9H9qIQa|8Lbir*T67>L9;rap=4Gz<Vw)Q#w>1M<kWSkG(U4a*P%P?dp71Sfk
+=7|>Wc3U4xjJQo(B!W7L9)f;<&8FT33?FOP!DqqJ}RO{l5g`>1KVAJ1DAw(K71$&4@-zG&FGUPDIVy+
+8F@y$3}|JZ6kn2*Io95Xw&#!T>MC?Kvf50?2_%a6IQ~XVHgzEbFU5QnY0L?2orySY4$=)(E7kVZv~qA
+qFvL;Kg={SodX@s5<mu!QP(A6M}C!EK<-r27<qbwmcxTBT1{R)I!J(?F?XT(%w+`%B*#J{f{&;9EQ3h
+JfEtQlQJVmxafs{W>x-(6u8_dRC^2=E@I4fjuMnX49SNsPEG3)>{fiR79(}Xb;|grV!GXRN6|{V?kb)
+WB;0aWID67kI5EapbD|-gnHJ$8zVQ0~eKNOtS+Rwm9&Kw9Sa+JD|Tw-hUq)h4lwfINQ*;G8^67|9sao
+@Q&CDX|5iCf;}dYL{M2fd*e_UhX6l4cHo3g};M88P!ye<`G)OUFvU_=07yNq(bzQzNn;&qBRxPp(b@7
+=kQ7X62-X)XF-KtrmQ3dZJAnsIeJzY~&m>wN1x<(7B-m9kuxzJ1vZ&=jY~IyRhM}ACHr#UkP|UUJ|Cv
+=A5zIv#oChgVV%xWo)erDT0p~AzILSw?TZK40qKjRw%}V$op83`f+k_gkMJ3t2cFZs?Nb{3VUzpUeFi
+J>uy>J#DoP!>dI3sw^6DWnV>uzUv$u058P`mVzzvnxrp||8FcsH_2;zCvk!LtZ)rh$ck9`h<*X@i3nS
+RO8Nl`$zkZek3&(+HFnoyGe2?)84R{w&)vTI)J+B@HXz19+f>8GL<9k5|v=@4<c67%nC3b#f3Zs-KLi
+sF1Cti$WvtsJTGEB-h;mLt#rDtej4iB;gB6q1{py!k~80gR@n;={Rtxt;ZOQGUOH<b+irexAMn}x3H0
+>|Cd8mgyryR{W`c*NQqoSo)DtsfR)%VQN_iI@sQxMt9v`OPQ*7Mlmj#o-#$NNFq-bHQ8no}8l5b>_eg
+Ju4c|``4$jb(f`M;{7y`T{G{7i@5F7+dvdVnC>|34h}KmdK2H9JTyA>LE6JjX+cYoE3td_qliy8V#{U
+UB_>>1XUTmic3%mSYqdv*K$B$DAV~*Cp%$FO@<0wJOoD|?j%4<E|9;EKOvOEkrnq^)RUgDMR1H!2wye
+%bFv?i1C%i&M$QLca6>X5!%9P(D!Ps4mXV0F|$s=!RbabodUVwaE!G_T15*`-@W$-dscfw>s0_XFYKR
+xi7OeXl(4MRS7cUnP)Fg0O{TYvw9n))jFv8tEzcaPo=!bYi<&X@#;{Ag2pU%gn#b8mfc0343UQBS((M
+ht27W#&{vC*1J&A{P_aJD5tvLBH{a95C_RFR`322o~`(%!bp4q}uW$E3eygx;6qMc8a@)h&jM64kk#Q
+C<hFLs3~TsOc7Fl!ht{au46SmoSc^s=C-|F6*Ib3qzww1w`C3%2p9{9ay@>?G5C#Qe5+;u!A*S`zM<P
+hCzuhv5`ma>KpRlz>|iuAeRWCcHbk<UldW<S#6nOULBcqGtEP@1_eF$(52eKE07fr+Vf_jOz*b1p3nf
+LTsjhL6eE{`j)26dbxG?I9x27DlB|792msq$>Z{GRNHb?^8?>$Ck-J#g0(-q+wtuf^TX?QzM@qck}P|
+nVLtK6Kb4?m*mzex7ki~E$vvnSk=2ISpUKIzbZs0{%Do(b%;DTpou`f&j{+fQ?R=$)OkFr3JANO?Qu$
+q9yD#sbR=8L-JVY>N~o05h_2c9%_+=u7g1bG@jc--q(|lU3EAvFNr}`fyDHop(t<jCG*#j>aaTCe#B&
+)wMbt<T~I;gUL2)*M7)V`wQO&$z;rX5!s|!6=ezMjp8;SxWc?@n?dk8jiue8Rwi7;sg&pQ9g0!_=skH
+XLt88qWj{|>02HIVh=NZiUy0NggClIfwFP^jPbVHEDdVUMy|}@}z0@`%zEOo&G64?EhC-5KpbzGh@{)
+jat6^9yh@VXX&Zt0E78iV%(d2o;k+UB%MdeZ>FK7}jM6|(li>Pt7bq}n!Xnq4~;gTV)hYJ*6P!wW{1?
+3OTCn}F!$l<cbn%NgYak0EQHdhdY3Tt>xC}i0rLLKow*yV4r9OD@N2yJq=Iu9r;EMp9xfdu@XxBWzHW
+QE&D-iEd1Ts;aOaZ`6gi`Ad<-{{Mf(^AP_enGX8Q~ckLeCMywG<+0uY}JCMKWIU$MA{f4{_rFu{=rQb
+ay*cBx0p-X-M`PFPK0?<!s^GODNc)J(Ow$~n&HJ(S}5A%I`$~3cE+l{kD^Wk&LwVmJ*Z9MMgAT(NX3w
+5Tg=>^PU041a6^krF@yV63&ukWH0Lv+=?WbvO&Iy*Wkbo8Gt}#`sHB+td?9Z<VP1tez`0|?ym8txQ09
+vZHlcu;X?uf)`UmAz?|PAe$I}@bj<Oh`Gc?Dc<wQwl;%wr(+ZuR9ZB=Z*-{cY^s)Cr=I$Vt-S9+P`dQ
+j8#WA>b_HlwY;G@3IHZ*5Nk`-8a8EkOw+U;@)~3GSi%7B)qyhDPnn%mgsJ{p!TwY-teW*!MWYaCbDVN
+ZJ;yadO4)$bWSZLG8{6<$Oyrv-|{DjQYo{hRaS=A=c~?0(phXMho(XU`(Un4HS{jThMk4SWgU~xIKmJ
+YWo_f#)K3NWyT0lU#U_BBp9faRRX?R-Ug!3=O5LqW(%;_$C%wQbpg={I{=7f+?=1BaK;SmWD|Cfs1Kq
+)HIQduwp3kQp!d|ZzS<WN+SKM~jY)CQG-@xK@Q}xHKWQimQ7=|Jqzr@!?2H(+p+&ll*A>LxrwE$Red1
+H~YBeDKT&hV?eB->rZ9A{9J7WAtAk3H=$gZ&G6|DZEIMb%Fw5b|B6R-eq<>d5m(gzmF1}k6~6U5la7)
+o@EGKoM`m&>fi2*0!CdTuHiTe#Mkr_vlKsaHvkaOs89sU~5yT%Q$?$trJW6H9QQPdLqH2ricMkSM#u4
+9_N=&Rp$Xbx^>}vMCqL2Kvw&=)$Lq&B;%5w9!<RLUJ52E5=y?rk{gBqussSoZXx94hIEBBE}VVVN;8W
+QU#h49z;mF@T{kkG}9D|W=VBCpzH9NS2<mco~^SwQztW54|XBi&&}F3D)X4ihlxMc%+F{T>>6vB@X~1
+L9~r(vn}Qi+{U!M{qQLn7-B~m`r#$^_khE4u2fR%#*Ut2slzS_5g`xn-<=ikb_e0k2zR&wbG$<k)Zig
+bpXT~?FGo`c|j~-1WP^^sbTBL66-$MWGW;iyweKHu$J!aUj!oZ!DXjv*|u7OJx=39FYd#BA|u=rE)o!
+6f9gJ@$d)2ni}zwQJ&VOrn^BDbChIv_36LZlMO{~Uzk=T0`xiJoZn)K!mjZzlrUiA@uLHp66UCE}Kq6
+c-6jt6H7DwK*+p8XSAA>;z$_qzvu3OpklVG{%^q;o8Z!QwO&5@X?{0hg~xpLE}c>C0w58I)9_grxDOX
+E^hKqu)*Q2QC}`<va4|k69DmXBquJ0&a%o>!ov$S!bLqLI%b5)L1}>p8UX><;(F~x;@XVrx5x7!!Mx`
+$g)X>?Lt><5?|V0A;R)A0F&;ybH*@kzF}CY~?!^pAnMtW)5>(+mhh*LrAJkT}N?a=bRdFl8Q?1Ko@gb
++A4`og}0k8#ANRsc{7z#nYjBBo=h)`adjkPRJ>#XkgklV0T^!)JAtRefo2NVym+s>}kwaqANB#kHQ-+
+S&N$J4AdT^D*1M{mESLj3VF2siYiaYjee38JUmW#&h!`#kO1O_HV2rEMzK<eTJ)Z!N!HQ5FrG{LEb2G
+J6aH8}@WnLHvdS6Su>mgsK?|0uW(;#9l`CRXupUJr9LDtA|R{g!05@O*@QH2jS%+lEj0Xi<@6|U}J<9
+4W2*}Tnv*<FB6&TcoHP8C7PpWILukOh7i;bp@-5_3|$;FF>tz$qJS$SsLkl=e{r3;n~=LQ*fA2I3Hdi
+QXkZ?VIUej(V2BeR7Ct^l>(7qYzl~EQrXg^cli?(kfME#<#gzyKx){7=Eu+EN8{3sX)Svz>83dIEa7&
+}uDBh8n-;-GmpsIfVHEk{|GcoWc$Z8gSt6Z2T8$A+!4ZRr*{8@lzM%-EMFgHA^8?Qw*E!s-e&XqqT{V
+mnAG}ZGJBSHp$P?^CdSK@l!9%3mu*26(5<|YV066}st=PJ@2id^ecqGzYPtHF(0AIH-}2hAGv_1F&z{
+M>bW+QW>PGTSmG@jKU;92nMEW%G{k@?c7eLx`maup#T5xOGt`NV6t70Fh1^Np=E~-_g+(Y(hyJm0O*-
+i}jK?-^IE{^$;=qEjz#JqfzKBuk1RDU8;!bT1gNYaZ_)y67mRQszDMh=5=-nBFSl0<6&2$iC^Zi^%MZ
+`XGsaX4@J46j2m4Fbl6g2F!3r3Z?gsW63<3s&}j<+TV@iIIYBohykS&~r~}?)Y$^{oM0Kle6Pa|9iLD
+15@Yn}#usP~>54y!X8T_prND)zSUF;9&qiT1?RBt;dVaY-FF(<jp@FyUp-4Ev2(Ft0`Rx;mv!{KPsv^
+5V1pVaJ|X@t%Zuiyd>!nqNx2?(f!%!8XCa?qXe(7b2Og*Y$8XpEVz+X-!I>~+Ph)E}eDgRhw2;p4IU*
+z1z^`+y}257wet7PCBj4j(=KX0<HZG=m5>b+z)(h|U=d)tufa0#3fW2C35X)NF~V`PN-YZO*Cs*Ihv9
+p5lc@@yG6Q6d75}vk~F-FryX`Tx{t_2z6Z4naL&*2k<ai=B4(?@d2o2C5&gu<1QDdITnE!#GMnWsmO4
+U43Y=k>&$z{u&qNNW25)o%fGP1u(J@l(%iBK@h0O>iJ+1;VQ8k~ft<d88lb+1y6v-Cj<Dl0TBNH5zP^
+V`68V4(pEMB0W<RZ)wpd74_dnB<*C+ynY!%$|ES6w@Vrm@lqpm8PRB1y_Af1<KLotz0Y1@*HJ-8P(-p
+l8Mmj}nOI|I<X7^MrbduZNfBPbrzeJG_NoZEDZc&Ss^AR3@?BE2j*EC^Lj56guLd3|k$c6BykyDZ1-O
+t9`7a-*694MVIs5E(^6Lp{b6mKJxC0c&Hy9etTE@b3(72;iIIahC&R)&@1q|6m)=Nn=|id8U42T8Co?
+8>*IbZYW<ai&axJTeZb0KR4!grGh~c#5IPZCDxQD!iBHXm2Pf;O5VN&kpy&eBQgo-&uD5>5=z5G%NiQ
+<EX+QybSq&<i87Q^BsWRPdDsd?C+opD@AOT3R$6Ctd_MBXk$}L<2O#)s2!mdXLJ}n4*hK<R_E!kaymS
+56-JW@TGU#!TRG4F)iieyS#;6UR_A)y-MN?;LI|}KvNK-Ml`k7m06z~5;Q=O@%KON-^g_s&*(Wh<`^8
+-{goEGjYCu<v0BwyYFeWQx=OmeEinZnc%(PiK<Px)_HK#z5*zuaOe1v<&}D3I;LOQC|}6wfeyT!_>-5
+I@AZ1G<wtwZM2)WHliAL$hR_p@Ca-GOJcBeKn#=jL~u{N+mo+oYa*qF9uHOB-pvE7)Hp5@K|`k%s3-h
+4=Trs2ANFI@*YR7ylJu%(1C5D@10(QeGrG}D>KS3v&w1;1_)kb<dV_rrVZ7k9S)n_XNkFH*I%O$J50u
+r>)h3L^gfA>1$};9psN~JeYr6C*x5MgG^e4l#uED3LG)cMDg`-5u)%!?t~3<rQDmFMJV9_rxY&itadk
+m=T0adD`!vBpMc^2Va3}<5O<5c1H#kLcH~=SK5Npy|S&j`HU6*Zkg{pGU2<D-JT|w0s=o|D2);!bh1+
+MCKUh3@S%Eq+y-(|&;ZZjdGDb3CeObA|M+#r-so|>MJz>QK3vA~v)Rzm3Ix}+x7LG9RU%H8t%y^x#ol
+_yl?;AGP!X5CtT`X>lOR;3*<RPQ}8=i(Hk)l3+ch$&?wOcZ+5ngO%2rB#Vmln<RrCtWdl$>L2gn$*sW
+4%8ED@|7l6M@9&v{6437dkF?fBvs9`HuE@p@Rx~KwVKeb%AMlRL5cLzh&m+INSOyj5EOfUdGP~{8>4L
+d>{pjTdRw@a3}R&D&C*EFX#YXfh3-OajfmI8<mfQ+HRAtH7gRUnR!Xttom+GrVBS;SAUxnhJrGn_vqZ
+?>aDA@`Fiaj~O#DhHivi+7Nt_T>or%tj0U^!Q5|j*3sLB0{yoj%<H~8T$KyozgXwiU=i8PLNH%B8+A!
+ddqyA$VGV`%`p^ZrTZ^%l~XJ4%mb_E}`xPjuPEj2&p<*fD8fv+M*G&>uzb97#p}9tUy(5U;8F7fK(z4
+jRhjr>ZE25jGk=#6XjmtnI(O!PXae`t0=Bm91@8c)VNNf!J}-6h;-U8%;yPj*g`yYb-)E#S@D;jiQnK
+gp=t-SnDx-fo0t=;;vcj0~^q%NE;F_yHICC+i8Baf>6rpeYa)Nwr#ypEM|M{45MoqMt*N%77lU_Ly6M
+%R+1j4pOR)!5FpLkcZ8dj!h+?IZPl1f5ph+D@*{^l_jUtRiflqr^?fM3+Lz)gVI4@W_8cPjDL_T-m_C
+Ryy7u<iIJ^I^|M&kHY<J-RJpj=q7v+(-gHgOW5ul_#r7Ytb#58zOXP5e#883}BUy)E{kSNG$r-vi8ZY
+U04;%e4W%R)xLFaXyT+;jdGx9b7a=lb2S89`mJ?qD<1(gzEZ8rA6gK#iw*1c;q)7ZlEU2<iuLM5*|#a
+a|fChc7u?hp~+*@pXwl=WpnncKtqFFNFk-Z>IQ=TuY|h4?DM0`_*v@7*pq`_`jE4m7;0@a2ZR39a>0_
+^MHTu=ui`J%zIg4P>-@IA0kjrWMI8gH-s3$k}3JGvOMx!R+r{GRg+uuSTFiUrzcNmCSE_D8=G3hxDK1
+DMc-nkGwq$tb{s&I^g|#?{8dbEwQjp8&I2QXLl&Sw?gk=|3_|G}p8u^3>5Zpd6NKkyiOa#-ACUc)AJE
+F&`YD1`T|QjqAM<5$nW2k(M-VKw#Udkh(?oCj7sR%c<g$W@*(*FNNnRZ%m?fUH)K$&*d76`fQ1jq*X_
+X&5YRHv_C8gL!PN2zY)+l+5v`xK{0$3jRh|)&M+$9*vATFx+LX8UTF5JJVPZ=kq{a2&A5pyq{2&zAf)
+vqM^hWwN#32)FXIKpgp$>yDUPpMTT(Eu2ul(r^u9jW#2;2j&KtDg2x!ykt;AG?aMrrOp*JJgCyg?*;}
+Fw-7+Q&uT#im7Y#2_JK5G9Xj+f%_URkYfN@#tLGtVhlQW68>dK-EU#n!4thvOZiW-|L6(LEx`4}<`&G
+a!i)}MVsPZ%ZW^?0Qi{1oI&F``sGQ`(*A=I-N874HbAdm;Dg`=Aex;y+<w<9FMn==$3A_aVvkYN=rgr
+!?hA^7A-Nqy)94+te-oxw#drMzd^&B~o6}nFK1OBxX-CNA!ucH3mqTSz0DZWKlIF_?R@0?!zsN-B~KM
+=27=-xw0<GxLMfP%fFehvjH!(H1j+lIyNjw^_pUK8N%I7Lu|7-h_t$-WRKR;@%{3S6SPw9<*kKqDZhU
+=i`x^i8F<m>2gn(0!-yNnp6&kiDS}JDG6U2rA8iE_l|A3oWG1AtwS#MC|JYPEHVh7k9`4WK_$m&y;Cm
+;!}>so|?=oMDzmOzGf|%c@PB>XvsA_>bzao1tLL~RCPl@JL?NeB27X=O!i|*$qc=TmlqWu%6z9Ca<{7
+tGzs^*Z?wHdiJ1Q6tB7G%8L`&dXlNug<-to=a~{0j$lbe2QII+~wX-v?T@DU<#-NarMygrfG|q&H?@^
+ad>rUeM46Rp+--sA2{1Qf4lu$?!wxPB#H@St-$|FpdL&jAH>GL0U_rKqZOfn@*>T)K~(h&dsHP$eoYu
+dk?FF3W+kbB1oA5t*s><(Ou)lQKGbNzVy9lpW%rdN|5_hw-I*Jih&ZLTEl-hT8Qd}6LgorU4Ec_icD1
+|z(@ke~RQ;L6XFeS%7=NWACZlQI~vih_rWM>58{VSS{UONl@u@<k#Kq{wwAe4Zswg6AD!vmM+l@L&dS
+Dn0oaU3wIZ7)8ba9w}B+gZB}2YZP(Fr>?w%vz6?<q&8!8d~y%74HMyX9zBJ&!TXp-*;y@5nUen0RDM(
+_tJYBOgrE&ZlzpzkAUBdjs$Zy3SPvmzNLHlW0H{x8kWZr;hqwmdL$OLf<kwMmVw@L@{F!FWtSGw5(B<
+Q-sAubCR(G_NE!CNlmRZ^HJ~TPCc`MP%4W=TZENZH{?HoauQo<^so8-?&2m6zRRpc1w?=*+lXvLgf^=
+T_$Nriv_^UqRxt?ySj@f?AYbzyyzp&HZ(4M!0apPdkPWm$j+W($thn4FJ8vxYWagbiAA;9)~YjAe`*f
+^0R_c3JJGodRH&km9J~jrg^*N&3;q7Yo{}-X-`B+4_Z1?nAhaje*A`*2a3>%(4}P{aoUG7!|X(a~r|C
+2p?&HqLc#hGll9Lvz*WR^T#_oB^rhenEd^0A7#ClCE7M~?%IujwY}_6?<`NZG~>r~cgGQXINm46y8#1
+7SddfBa2@dspnw7pzE4<3LOoRnc7d+AF|&r=*fH#Y3)p!v!w2;>B1-S71y{MNVl_!WDtcbk6TG&f{YO
+{3&`n1?)SENp&ftw3?ge)`w2{JI4G%VW8nUXi52y6!4xB8`nBGrQ^DQPx*{v~^Kf<Cenor%IVR3`EQ}
+Zn>#5gz&LbIAd=w+XpZ(VX%cxJN}Ko}Rn`gECRk-fJG;1cIS76V*-o%upRQi!I`2JnQ05V-Q-hozm~z
+}G+2pGL{Qhrw({TOdzFc!NRwjxxUh%81K9Z}P`heS^1eg0&-=I*rEs^pq+6p<^D%;%9}!4j$rz$lcbh
+!p+1Pp0_vvkxB(4`zB`v#AdD*izfd$AydfoU0Tz-bzxjk5B@q-oE{-RLcIdbFm~0(MZq-RWecH?yCa0
+k_O8N2I9Ga%PE{{W#dTQkx~rb47;_0SF`ssqEyW2%{thNzt6GajXAif5$G!NhJ;pIMz<6)SDbxILuq&
+EjI;P#<AjB~6K@N^PiMVeWyaa<h;JQZ7%PR!}B$~$&1QV@zQ4P3v^Ny6JAqW`<As#ZqcnF38OZrZjt8
+sEY4ibFQh=1mg9H2ro<)pQBqF71l#c-!xL1D1Av&syFBjCWmx@cZBXjZ~us3HM&6f~XS>ahZAzHcT`G
+**sYdM8@N;e;Z+8fn6u>)1uZ45B1f^Yx4p)kTw3$QeHwZB1+v&QGki?&z+Brx(VrM})+({7cXvMnZZG
+E{OP>Fvdk+i=Z5&(+!^F0P?nmr{%F49=8;6G*osNsDH?lvFO$T2@asc#N)|hkupmJUeTNA3t|5ZZk?M
+nN^nESHXd>94W_MGR%!)0l|Z16fTWDV@le<)yjB~CgPB9~LlII4sPLlBE^PPB@Otb;z#y@<JcT9)OGp
+lBW|$oMl*FE&f?MkrDS*4LjrU`rs4+W~HKzud)k{P5*xSi6%22SUcjt3$&tiz24)V`FTn_XvT-f9;9W
+|h+Au9Xo+JvQrg4lVG#PtNZ6QXgVTchJ%EQ6(XrT#{e2*$#`Ta4;%K<64o(5h&Hu?WJbbTRmhj>09g1
+09`6c=_MgpnriDFR)BQp6Bg3Hl#2M<ISOZKp>WE+2XTKYWzC8DlXO+!s(RXgAN4pQDNFt0}hhF14|1D
+S*T_YPKEa829DNL9GmsERKb*)+Sid3@Y6^@GJ(NU@qHYk;uQZM$I)tPzKy#OV=BInqpLgBUwqq1y#!P
+HRhl;%I9Aj%Q(_X%w_u|}Mn{H(rx^UGCXguvuD7#B=P?p7q4!?bYUj3CekZZ&YDHWOt@#dK8roQt%?f
+N!WKBU1Dd#+5F_MoL#jK^DsQV6LD^Q0C<7A}$ehWKhEeL<nE|0+Q3r-Ql7W*~Y%wq!-KfqOlig8%AV&
+@DvbU?SP0|J9hP+LX#`nE1|>q1~V<lBeDCKt>_ETa^2w%s)6O1^EOh*aid8k1s~Q<Mhn45Mj47P$w5G
+D2S&5<N(|TFr_~XIqvFL!<3y_zu@fNWS1m#G2K^71Qeqrv4?~Ys4wcXUR)69HG(G98m)=9jLG8`En(0
+t{Lp->P#1YmsoG=AcpXqD;64AyL{0;OWroz1$ErRxhqkO!gLmp+89ndPy2j%UZ7VI_6yj94Q<H|(;P3
+-;H(rweK_?lUO7>2(2OStqIa8a0Qrbnm0JAKZvcnNO8iFR*dvR628ZJkNj)3GHp}V~5;V2`C@f7AR0x
+X=NAGBO?>l>q^(J12>7mnSF6VaNkXJ}=-^CUGf5_JSpJWiOW^V(NPVrq*aZ&-h-N$Uds?Lbd#>|Ul=p
+gjFq4vL!q4qBvvg6l@PWVr<m=2r$^{u6UGbgIscEgg2i1hWXdH}apt;rmwik}%74{OmWdvXF4dvtOV9
+EXr2lLCcq6xAG}6bi)$^c+NC&FUyIhj%6Fgox?vOIxqM{~Qb8tt?@M=H_=(*bap`e55(!ra0ffU=#uP
+SRMrp_JA{CoHh#*$aoHlx+8&rWhp2K_&7%Xm7AELHDCj{FdTd{7?G`O)l8uLBs*>3?@*U^;W9`As$MB
+jc!&-a0JZ9)cMqSu_a{}b0Ksh1^Yj8u$Zvwz@cED{E(dKnqOW0^Rgp2Lg;di_FemD$yl5iPFSu8*!m6
+G#9gx8%DF3Ms1tw11j<lIot9)n&#i??qgLlPydOGj}?|AqW*-I3i|BUxycR-eK19<S`1pqXNU{hm+3R
+-4(GVBPl4rnli|2hB?3QsjEcNHQOotkf9L3c4+#QN<F*Z)b@)xGxe!BpJB%K45K*0(jIy}JqRZOvyRC
+NeRzS)nkKmmwx+cOYjtIlHNJkT{L6<{-@-MCc)lv0*+ro9GLx$=}xnsWHgWNT_w7Ca^H-ok=DOc|19@
+^B62;uTUfK=k@9uGewsli@GWatCH`8TNLF_H%XzH_iDyE@$DB+lifEjMXYq4mCte|GDV<F96dvwI+(*
+1I=xIo_vP@02cR#-J{DPGuOOj7e-2!n9d`le`O?8I>COWmFW*~l5)<7FbtOa;QJIQxn-Ng@6De(P-<)
+21q+a($Hvtw<SIKl5OY9(01ph>9zXOVsRh^w(WILdTpMfM4KN3;r&egQWo$oE~MQiX&r~hM@ofNx8jx
+c_{ZdyV3#4Xo(>_5KTe{t~RQT#o8lzfpA%5#GH#^yhZ8`ulz*fqCycT4a=jt5jwa6HlvnhE&c?Wn=ca
+qV8V@;2k^_c!tStf+5#bo@g7JKWoSeUu)&J%01{cq4>S98q{goxR&IjZq8M6seQWgs1WK6@q7S1}X0E
+2w8N_ZiZ;zyGINkrvKB8c<oIU7B4H1sH$3oI>g^;bKNL5bu&7c)-hL*K2GZ#f)o*`Ar<l2OaBuc`B3l
+pVA2JaccXdtPS&5#lDz_RtYv7p-n4VjgXY-<oObTXg_;Dg=cvs&IO&DW@fx=wRvY?w-nOe|=h36n^_d
+cfuGKkMPOAFsQPDK({EI(*{io1<DGuOF4R(DxnN=5$2+X4y|3y&EqpzPn{_5!lU_a(2k8bv{D&{7%k@
+YzK;^}{$(nT$Ve1_X^P!Nuj`8wCy%j^`wSg8^9wnmCYo<vyf2|n4>!wQ0*&oT&%JyYj@T`0LVSEtgow
+MPJ|_hoXbP9n4%ShtIZU-yE2z58G3kB2Xh_rPZ4Y4RX>^7!eO$)iWfm;G4aM-q>HKp4$AB4_f=)V8&`
+DtvHGhGC5R*k|*e(4W(+ot?8>!Im)Z`l*Uj(?-6<pMK2SzE4y9BM(d(yFQYg$JnL9-w*AMw;L^dfGR@
+MpPTGgqvV-bcp#EAD_etv4=s;&TtompL@V~88Pq{pZ&UMDQ)!ygfqO%@zKv~tKDCp#RZTVNx17_TH=o
+<jC5O>hvJNQG_t49xFM@s)1{720VFo@A(_}HYkxxGTt$gs{0j4Sk`OT2k`8;{^*W(`!_Fo?C?LR+w@p
+AwBDN-nSdtI#^c`H#MLdOXIgNB6BQvDR+mpH{X(m;>AZy;qqcU}G^)`ZrhTaLroSS;7gc?XupL>a3|2
+v=&%yxLBflO44Tip0m#+EOJD|2YB-#zcYL!>=Y%c-DT39fyWF68P%QI};@9DK-A)p{G>P+@db)J~f4v
+aARU$f&xsK-Rj4I^zSgn-7K+TfBQIJQv;4Fiq6P!N=4XAUYw}nzbmA1hsqVBHTEfG;S*0a6kCa@{Lx*
+-o&2f$GhS`0c-gRALuUzTNhr!_=hP4hF>keA3}YJ8!9h4EJu^hq<a};7Q&FzEBbcs~fVXP537V`;7^2
+?VYy}a0x5}CZ3;;W=iBVz^77x&umj@9?CV!8=AoU8^2h%ukZZ9*)Cj`ifBWDB7b2NgjCzv0IO9O#qGc
+H1z<WUeT^koZnj2{}E^tnO1BUMom>o+KT+;0^27fU5WBs+_BIomnGc25%cVN8=%lOGERmYXk?>`-gxh
+9sXCCSd8gB0H7h@)vog)-p$BVAzHd;&x8dl+B_33EQrMJg}<sk43d^me<L$%D|<z&tQY+KpHM!_J%NW
+G>@Dr#IM!6ta`QbL6_s?-VNo6WRRmxj>>E^(A5aPz8h?dogw@mz>*pq%sG|hMnh!A<RM{jJa-_Rj5N8
+~Tw>@@;l#O4oUJ7Jq8!C;_Jx`|V!a4Egq9D%BVdHpsVrs!;6kycvh+I0E8yfDfS96#fn(KYX4O+LH{f
+rM>OLr;nBXx_+LZomaOUL+4v3}!Oa&%-cMN@k9AgztWg?UjiVE*7J<YE`*G0kgIpp@3SPGW_5-IWQv!
+ZnD`@GDNB2Y9KSTwzH*c7V~=uH}ObV>yatF;ar16A63JyRrP)E~SX*`G+10({Q*63iN83%nk|AqVjg<
+4N3U*s%=m3sVF5u%<|I3cNs3#C5C<&U`(e*cfj}%@wKFGIFqn9g*R-*epjuXbyksJG?O2*mD@}9GXG%
+d^Ao5#}&_ExUgXGB9~O#THDo3@F*h(_Cdt#Wb+k^=ENfEcovW}R}p1&h7M0gY93?NVKP6)`TT%sOksq
+PZf|6!VtaR+-pf!+om~{+m$vB}e2fbmfoGO(!!RJ45|WCboE3<irll&J36h)8vB?y}E{G9a`BRR!Thp
+cBrnZMLp~gM?NG6T!jtQn1$ngAv#0qU=IKjXh_-^bqsZRx1i~Ng{H=X(M*QRcgEJ=ljJgIP2rue_c01
+9F*tTH$QNnQ@oZX_98f<Y<9XHk<g9iYBoFap*WmjJKqJl{I=+|h;jhv#{FvE0HZ()VaQW*O=jo<~Akh
+sZ93^SSC5dc<sUkt|9M?-p*89%01nl^>2@zxwqLadrT7X2eVXBHpk~Vf>g|f^+U~xrM}9gyzQI(Q})e
+o~00&)=BcR1XUK=#=*P$HwsLCR#)qC{^@=wrr*B-cL?(ysn-1)Xdiwx=a`gLi-7lUXvxp>y!~_^?M@^
+nfQS`|IvZe2KWWhP!_ot&I@e*6R*G<pIjZkP_CXay3KtA)sgMTMTWykOO+k6cXKRvxSKuncEc=8S=Wd
+Vv=JSiwd_Jf4b&A|JJL{)GEc*N++!YWLT-tvrCQE}|fL(|%Q0vhNnxej1kkaj{67*NK^J4G2-M6of)8
+oCv*Dv>XU!})C?7iL-3K5Nk$l3&E$#VNlljjHfM+dL=QkcZ_yMx2myT{07h(bCcAhK%W#a($xmp}%n5
+@-3eic#Tni-Vw~MN!tu*tLOcSFz9rG)~td+PApgoKHlOHF|XO-Rep+|CH2;xM46^fn$tgi_$80YyF+9
+$NdU^?(pLNH(7FC=Zop!##a3_cy<E?K7I2jdv?E9KT0rwq;S%b!3~T+K!A78kkaAM3@aZ6>u4tBi;h^
+Ce0*95N{(o76I%ZMjxmuBmP*-)lwp81c*}ktm<DW&*Oko3C7&lxesK((Efo=-4(c1(pHG83W9H@?d=G
+a!I^ZGk?NHXtFOu05X0n^aM=BVq?*r+w6F?ag`%kOpEN)Ti)n()QPWwFzqI(L1ZVnfNi8p)6&CQL4_3
+6{6h=IO)41wPpCs%Su9JRa8=XgrlFh}Clnb4nbA48d`7Uj)x8Znl)U6|UhVKK`ZPHC@A>=U};nw;lXV
+Li(->U#D`SG`|e%6BHx6ZiYXCoBK|mJ$`Y-$r<m+lp1)I*1;*3a@=gDFE6CRI&diItW+@Y%Us|<#*xi
+cj4@xE}Thm3enY74!NYnAa5+5i&P<Xq0Cf#A9pXq)cF+)*Ya!VqF}6{E~@$19f&{>PD(D!VFn<?<>0r
+bsz-nMJ|L<KwLQ`d<2R%=C|`Gy#j--d@bTo2Pi(<;S^RySr^UQa`xRAeneT=YE2d2K#a^s$spnEy{M?
+q@Qq9$o+gK;|)xp5p>{JW&oJpv-$j<UxQsr}Sb9UY<n!wcAgrw0MQN%F#b?Nh6$+M1Fc4oBrs>^EOCK
+RC+sZ3Gg;4%@g%EX`v$cz%;IIaja0O>UAIgvM$2YP`<E`T38zyVCFjy10M+tm{Kf}O*dZRdG!lh8j3$
+B4b=$l(h(G~gizFVSImPEJg|*<jbGwbTu{BsADW$q+YDfE*M#PK}l$eNtgYL4aZdt#Mz>VnzJsX%_uJ
+j%w5L5mPkmWY*E>cSQ|8VT#QjwqlB*AEWS$P$vz<sLs@heP5x78mtnN(efmj7ic6`QeBu*FnsX3KgQ~
+-x;j-8c%95Ke=nIAo);dAVu($MqVy^$<`f9N;J|uW!!{=QqPRk736`o_gS|{nk?e-gkB<0+9493(#R0
+O+n-LzVbT8MAIY)w+UnS307YZxEqYfRLPqT)c12Hu^Zq9tJDVeL36k5TUSIjJ5E*tF$13ywFn%hbwZq
+2gUdCp3aBhqy+6~6go%fjh|X=^^7$<#HRC_SXo+{5P-qF)X2NJkriIYTiG=M*--r06(l#y!7u`WVbE%
+O#@BJN)hn$}@2PU9;D<_X<s{Vt!T~;#s)B3w;+&u(V=R3)l1*GltWehf*!-xMX3NXLS_iWb+tP%6R^|
+XB)@ii;F$u(9nXB@QZE7qKn^lG)5^@gM&#-GlP)EV%Yp`oP=XD(B?(NO2+_D`(mEfXQx9K_E=HBFGq1
+~niy4v;^&q-$&Hc2ebt5O!)djQIHm>=2SD>4UgkP0&T`%buxPVoG20p>Z&|AKZ(TswAU^>wybWAXWId
+b%k-~d+pr%~A6FwX=AMOSm;67~66(XOV1AKpFfD!&TR@WGCZZ|?=0m0xJ_nc?K0*}q}@X`d%@xA|gb8
+vXf*Cj$!m}C45>(Oqx>GP~kO<3-ykKGr#qAc|w<OWP76j=;3x7L%%)2FseO1wKO%CyBSi%<N=HA4tqo
+K|gHUBuo%l&8cAt+xVEyFBAIzI+_K(5-wOyfMv$uehDB!*=v!IVC@LTMH_g$&$VO-0O%xR^5^u`sdEv
+`87;4V%|S@CshPQRd}9S65Xx$#ez_1)ma2})0=KNSo2!B>xU93-Y}4X2K<K-U+3|T3NSXALmfG=&vmZ
+&=~=E*IHA~Fo;IuCoabF8FEu7yc?jY3lEMG^*^@s$b~ZZn5fmM1o1M9*U5PPHalp(gb;y;;g9llwXwa
+#eB$A}8u-`S%*Q!Z~lAE0ot3@GvxE<0H5lqF$H4}$5)4e9%8ZLs6&C_kin}iQ2lx&(9tTbjZVAP?H*D
+(=Eoy}DSXAxDpVV!C!=Fw6$(3B^MVjFf?vn}r5e3&d@Xsh8M9f<WyVf`KsMxXFT#teP*X%JqFU}T?h@
+)5O4)M_-SkDq1~hY;!1;F}v*pijw-7{{k)H@se-zIjCNpM@Spcu$R`;=D}<>_;A`(VZ@`MNoLh``f#2
+j9nydtL=}4w9u}5_e6CoFGZ7N*w+d>w9et-K#@4WsG!w<EQ`}gHecrT7f(A3I`u7!LZDj5wjYItkbDC
+(noy3eZg(73$922cm_+W;67fsR&q>9j8`o_ZSeyKB>@PRN2n_RjY`kvsa(#jNkzsE*9UD1Ev9D)3Uba
+sgt^#k>@NQeUO~n~MlE?UR5qTe!0V8yU1+9pz7#8MReu|b+l;-S;&ON_;hc({ozNkYiTH2g&pZg(k4X
+m`}z`BF_#s&V#Bj4QD4Pps=&a*}w<Vhr1w*EM!y3x4jny|Bu>8c~hbr#=F{_JcqE(CVuI5i@hBO`7%l
+|nEz>6_u;#cY3pZ2AjKdhCvM^Q3$7^ET7oD=PO)eDE0gLm~zs4zR|j!`eXg*q!5U(-X;@PWoIW;S*=i
+{LcVlQuUB$_<&$NwN3XIzM5Vsp~p&5{iUy`*Q&G>pFURt(^vhKC@X;w)E>wg@2|^=#N8GjPo8dQvN;E
+Kyw(B4rh{2sG^@S&S>E(aURU1e7!Dxc{s(08U`8~$^dJKYAioqE0K^Sw;L9W(!3y;!CG(uc;Kpz%pB~
+;=lK*K#b3Y%EgdE;q8AkJp&Ta>*%qsL(pDl|Og;rb)*7b7unH(|dN^Y({jqZRa{*x;>Mm=)k>L4gMDX
+LgG8f0vHnb;yJ#jC2b@+==-kKQ}L8ppcFWnGkL^$iRgjUI~mbPx`i;eQ%D!>Tt15t-zu1%{koQ|j_Kw
+yT{)XOTTSat#K*d8E7a%$IS+fX61!f#mSy?AeJQd0P73DVfMQsL`Sl#-H5WBsa6B`ILP6G@w+!jp7yg
+wcxh`S<8MCbYD0%`A32+uf)!}xbll4!5B$>2MG*T-IW*1p`LuP5}&)eo>2(F=vju>Xloc?ovZf|+BPM
+|=cu2Fk*V0}gs0Kg=2uD%sy^h?L49_b4WEAX)mZ;~Jo(})e@{|j8sv2F#Cv-+6?!N4)%Dcsm%LOr2+N
+&mw*+IiH<fOg`fB?1IEIxd2c?>u+lEVpqXsP&oCbIuKJQuxT#Sx0!Z{ZJbc9?+4+AV50f;LsMi!Ppbk
+54zc~wsb7sY%Yg>&W2I|Q|Q8Wxj_=bjqs*B`sA`Rt4>d}8y>8RS+f8_@qu2ly3kwuevuIDYzc#PrY<h
+NQP(_;58HJRT&oYy6{z^``+%#Ne~V;;Y41e;PdMuK4t6N6q|n_B8LS`Q?}Knoqx;ef{O*pys19`@m7J
+DIpUG$OdChv-nf<%`+G>L}%J{@{9GEcAoHp_{ej^%TMKCN95>99wtvZsxa(0xeKbrsDRZ&Z%q_zmEPe
+vgi6rfkZzeO-X0K2d7nZG|3H6TU_(slkNZlTQ9_Og@^!(PHKjk{YBp0Z!&u;suTaplhV3!n+F%U({~M
+dGZmU{t%LOL0zlA}Uw57#REUr&4StzLoo<Z&JW?;XYf&Fd<_PZI_zknH-SvTZ`q%E~`5W$DCRN(*PkO
+uwoHr4?KPlG4p_zJ~1wO`j5TTPadaPDEaKe)R%&zf_1m|kRxL4hGgZo@IKA37VWC1f0eige4OmW~2Z0
+NJ^qs9tkz3-2C9PDAoM(z(wr^ZT^|SFxW16G-0D06#B3=1Vmv3_kFIM*ruGddH-JIwx;DH9m<8V(0eG
+>88F28$mGYdrHDfQNxy|5bJ)BQo(f49nfAM>r;Jf55;ND;-;pXPI|t<pN|gq58pgb-WBhG6UdwP-J{~
+Y;Fg49^~pr!q;?r0FY=qqLAhya20t}bS+8blID@B?$DZ6bpmYlGvRR)(K38949jvlCyJ%F28znlH>%4
+^0Up^h{8t3%n=@*~8iUm9tL*Vz3`5F9>FPGIA0yZz_e}J3GoBP@Qo#e@<0VMrc)k7{l@+wnot*(*7qN
+*;qvx9Hcso7quSMT0?FBEh34;X4F%{M@qqOb6^5?U|8%S@GUm&yhIq!R)+uP{Q9c36)e@zBETNRTe0u
+90hknB*m;rA_v~-Tn8zt76WR0^{r~ga!BW%jB<B{UP~wy<GNb=&|&xs!4XsvmEq$|Eae1#tPq8%Q+B}
+78sQuvsxWQ^~Op+teaLHBZt-OL*A!qf8R3!v?wr{+d%siK8`#ZTtH&$tq{T6rB1QiV8T~Q#Qc*YHrp=
+tlgH!aiDG-6s7?Chi>)T;Nkq{DpU4DI_nvOw{U=YAg#Yzz`ae!o&%YQaUvAa+FYmgX;^!wOP5&EEO9K
+QH00008031s8R*Ov1N!|ef00;#D0384T0B~t=FJE?LZe(wAFLG&PXfI=LZgX^UVQFqIaCxniO>dkq5Q
+gvkiV-J}sMTY%(pHMLQQAgHt7tD#R3R@6iz9y^+qBt#UxN)88nu`Bgz-D?JTr`Gv=U%19g}BZqEp(!_
+s%jUDKFso^y8*He7QN?eSNr1l4j77m%h7L)RX#~-`=xVCWAsCHND13aqqVRrA-pntX+2rxaH$2C5_^9
++`(^)>A`cE0v=J;sOgF0@zUY6e?-%Bmm#S*HD(O5nlhQigt^a`rs;eRwng~OYTJTpfP$Xg!78^uvtKA
+d_TuD<c8aQ{npV!xkYqHw)@S2whZTiqYtVcL*YUABy<la@9O)S{CT#&Kd;=GAba;ZkGSQ1g5>ey>rne
+>V85`=lV1{>BAIVg#2d%MzvSgCkvdj$frigHMkgjpl!l&EK1M%$8e!|`v=kVbZJSd4v-Gd*As@q52Ym
+qNv@7-fE&8oHxL*NKkQ3Zqp#~J1!o!VrUcVR}-F?OU(<LO8jUN?vl4Ktf^hIL`c>uq7P0=e1ftCsP)3
+{0-T@I?BqrWVUFQzqO*E{W$7i2KA|k>_tfj29$yAi!iBuwtD*|Esg%TE1Urql^8o#!6-1XzqX7v{)?d
+5KBH67G)=Av{^O%F4Xj&*fc1Q?x^jxjQx^7P)h>@6aWAK2ml;P_Ezf_F5Sij004Ov0015U003}la4%n
+WWo~3|axZdeV`wj9Z*Fv9X>Mh5b1ras-B?YJ+cprr`&Y063P_DsiE}jKqCpz8Y4cG8+X97Q2wa=8nNX
+r2QrX=U{qLO_QW9m!PMY>mRF@Sg&YL%HhU9pQMwd)l(O9jOVX~}sW7$Vp=So)xVeF#7752WC)uH<wFB
+m*8z=~Vlq{HY&2{(EvjdgEtYAbccl^gw9!N9%h528_;@7?J7z81f6k9Ga~FVFL5KR$o<^NZI%q>E&+k
+i~d%MeB%Kw$qi-N{q?j^UQrnPbVBDGtB?g8Y_$YSHd3kewcm(3=5@iPv_r?YA>3%!nDes&Y}bui<?gZ
+npWJ|j^j1FFBYD@P=oL|$d#!4w^DG^HhpNX+^`fCSYNYsr&=6cM<CK-r?@cz5#wZvqUb48kP&9u8@J~
+6D0fHJ&`NM_4FeS|;2LH%vq!<asu>tB2xTt{mglmPHqQr*jZj7Eft<@e<D0G|Hqls{XuAdOuXQDyNbK
+rc8m&gCSw2F=ikboe&cFp93^NW469%OdjF~j7(w6)&p^RXgZ4Z!ykv5=E?p2sZ>_4nn<clgwnRazG%=
+to#hA^YBcA_C*P}$pfvaF<{!)(aP!1jd5Dsgqw2>#wsQaaOnDb(K8*hIETJieg*y?BC>48qw<m@v2&6
+0{j5C@{zl!p7cl?=38*WMo<BCin)j%*5NR9dZik$9xZrRwK|x*tV%cR`D`r%fWMAf}=Gn`CZ&&WH2Yo
+wj@gZEHWD0gb4g@ioowaA7O?h(n<+BC|X|EphbMTCs*ur-+a!N%RE|`j_@FW%?)LQW`uTrv#(C$K+|~
+QZ#ckSLZyG|=-TnB+bN%QU^z_`AqQOXAa<una#j;><PM<TfDRh^G(I&%J(9)PW)go9QH1dy0sdFbpGo
+vdec`t4C|puCr1f2Q&j#4A?_hP=%OXL?yA}MgZc~$o!9kW~e;dmvxf6sI>NbOU5rx`?4PoJ&-4ddkb&
+%-@f2v9#$c8|-p<8oSh?ITcs>Q8C$W9kZTQplA9vljT?B-~Mj^T<AlM4<nG0!@K|HlPIF`YTJ@Y_iAv
+pcdopKuW90)}I>nf?9=U=MM+xocfd$^`O#wVd5FGg(9cG7UiAxz_U}d;Mr8i~YA-xwl7Gto@vagY~1H
+HUgfJ5`_)SweN0W?YPmU#f4UTzj#J1NUz6dyxR9rjCx$C2+j`jgQy%uztQn|+8j>q->!L&eSFEP>(a5
+TEU$JV8yOHJi}9>lvDa;R1Er`7wmb5M?<{t+HO!#kV>_=5i{V7>b^=#`@x3TG)Ox?b*EL?u7|yB_jzv
+4TctwM6MXOZAU`5o(!_h`rheGYMGZ?$?B|7WBUlDlTHM%B$lnrtSKM-VXq&f9TO9H9G9eC~sNcUa#b;
+#CTp^VdnoKVxD>r%rd9X=$yZQ5$bt%xaEX&>6Udr4W%_v`DX4O%>*PH1?!{|S)>#FllOd?C#<cECMHj
+bdlWuKJ&CvHPyLte~HG_>eum070d58REP+uI~QB+I(SLw6o^J%IWM(`w&Idme>=CQP(q#7Ca2*=mgn>
+CcttzHN%H)v&olR-RupufDn<Xm9%lhqNyOXE;sU{fW@XQ<6aB=;<cdgaEu|5#S{nv%}vdBg1mZr$9uB
+2U$<EjbdI<UuMQ#}V3O@rC8rL1G^d}ln%4;WaX74lSRaIZpZIHP)^y;zp`18w5SAkY;ceN2^-Pd6!dz
+U}1?R3`U<h~i*DUZkv9$WVsJgBnPfKj=HdEP9Vqce(m6TPmILFsyT%@z)f`7ERq^3^E&2qJ!lA0;*fo
+s<fk?YxYkVqH*lQ8rPsj>G8OP8t@I`o_-a&B{76ej%bezlzUh!5$}LG|KX#(Q)gj#&42?k`rTn^=eL=
+-)eTlj8U+<XAsUHtuKkO;?+)wNIUobwD7Q(!_IRGaNTqH4ZRJvUgfmv2&Iz{sK@-0|XQR000O897^_9
+9T7Vr@CN_@<{1D08vp<RaA|NaUv_0~WN&gWa%p2|FJo_RbaHQOE^v9ZS>1BmHWt3uQ=DZlLZ)1foopw
+qI!;%XnOGZH@<?*C9mk78BqXz?2o{85X)@{bIeODq>?8C5ASqI!BqzJ8nIr^o@SPu=9~>lFq+CeI)>$
+hupE6po)=cmP$aNYebI9i>KV18yd+B%I^aih8=+Zc*)0nw%5e3qPo@By|`%#ADn<U~%s};=@w)dWi49
+6r&W*lCgf&JWtubp-a@YlfWRg}=U#o~-rNYW_v$a|KATzH0@u$5$q0?ukX0lt7#(D{P4A>j~kWZyD6c
+^R88SRxDhE>EQ3ahHcEc|Mq|Qyh#9p;n=$dqpHKK-N5F6*M(;i;rO{m2fVMP;4efEL+BiIG&7p*Q7ff
+Oh&^#{(Iq%+qvXtaI4{8xJrq07RP${wHeaj=PacG({rb%dh&ZFWE9|5NvCH1nVx^e#R6uGg=X@(p6pT
+~B06Uvm|Tjab=NAzFhWg6ox!-@nfM!lK4<_Epovl*C9(|zo-mkkQJI7&fd;i&A6u<r!XI}#*E_f`+F-
+qVM=jUrsYla%bb6|X?~CCxJ)9N8=Xxk`SmC1Cl2^mgRcF%HzIlt{ZT$7t^E?+aDemq{87k-Qo%{WM8)
+CYchE(CNPG02vs#M+1Xw>Vx_Q}Yf+>8d*4Wfbka(Ly}Ku@Q)mrbyJzcbn<eD<#fN`KHf@B5_FpOA5P<
+oko|UEiIa{NtPZhMgC^@ng2e4O_>T!?&b+Ga3(fg#7N=S53?=dl&xx9Zft8F}b-e=pm(oF4{0N+dk;w
+$Ikw(7sI!M!<*0dZ$`&?+ZkOP-rwE7|Gd+Ea~$AeKfu-Sd!I~(=*Rt=tHXMHdHV5nlWUARW1sW}q~9C
+(hvj&4RE~20%7yi2`x<$F`(cHDH@WfHpOCk`0UiXI^d|j{5HgZ6D^TuEzWtylKITD&QQQh*nq>u;$+V
+VbbueG41gZiU<ULjCCd0g!0mbaDX+fnTuoIqO>c@!Jq|>E@1zp1eD*yybk#XU8Esfd{^UUC@-&3_a0~
+_;#(}ruFMJjP)nxbO9RAm4;2?i{Z_e>zuwwAN~<F6tL?u(k@Rc!Dhuw=Oa%#pNYqJDCjqFj7dwHMGN#
+6PH$WOIbqXTz|b7U~;`3CUtEGeT66uyUT(ommXo3<;tnl7!e9i)U`GQ`=PH+gfd_RJ}U~{{B*D^o=!g
+lad@j74+Ncma<9}KU-0{4q&N_GCUedlYp7Ys-h04l5S2)l@I-ag+ucx0q@E$f<y}{$%3ZHvMIxtq{cs
+3Xk<oe%kqB0!erOvtN`9B!aMtEY3$4?WkTC+rj39VgOrF)`K1hA-Ym|FtAkw^%GFkO>tK#KzJF?eLWc
+J|EYEX_)!z={OrMaI+tJz_6MDu-U7FA*;fW%C;wfj@m_(I$KmdEYz#Zax&ll_n*Q-r9f#mQ+ZFvG|9y
+N~<LKVbALa2aMLb$MMtGGa;p6CRWe?L+<!D1>S9HW#tCDiehVz$a%^<1ESE3lChrh<QCtj;nfz1s4+S
+pK10F4sp|<1M^ji;Px;1MuljEU4})<GirJoJr#&w$`?|VAmqC&ZS6&XVsvqQDA_s>U*?05sO2xcjhaY
+TlG-`!Am$PBDzLY6hXHUkxnyv<?OCG+mf#TD@oNgK%?vx^X7WLfa^v9w=*PKT6y-<%27Exu5U<>I6IL
+X5#r?{sk;5AxIDVJN(6Iscg0jexxiCX$Ko~6FwC7*kqZ8B%xB9OKzksZWNO9$JI&EhaKo9LlZ||w&yJ
+0Ximh$4)_p*o!p?cw`>!?m^$P9WaL&!{wdba}<zkIj*-vz{`qXY%)FzB$qxz52c7t{-{h~)Ux#Hu?Lg
+_Z2mT_05?;P~C|AUJa-<6tmz^Jai5<7>?7{rW<Bek@vXmsRefne-W)l;{LhZtw~{DGL0FlVSH+A!rjJ
+|M~%iPVktJ_?zZ$RIpMqDp6|TvV~!jfYAzcu05}OJZzcWM_#gdq<`BHJOq>j57U+KutzP`EtmbkL=NG
+r_pwII{S@>ZeFa8pzb!|hb*GIBx8)cgHnCUfrC^z9?uVN3=93(@(?8<o`~LjC<rw{(FIKqAz=@DP(CG
+aw)??cjUskT?}AM8)<tWE!}d0C^_uNTwvyHTsuLsmdmIAQ?&kW^trptaV(QB(iet8!%b)9vLdL$;hr5
+cAm5*-=Q#Yl#sZ@!uyVbENMU;|S6JUhZ7;4!CA_Yw{yt`r+HqO6!$Wl#&>cI9r+_mcFQ%wRh{cojF&h
+l4RWZBpctA)Z3I$C7xGcb>5(G;%|3W;voB7>OY?Bri135*TG1NP5batJM4=#{;0<-E0cr77%ft2ntuS
+r*Wg9X6@ypbwZ;y$DvCO!HXjHW@RGX|Qcgtr&(}B)~G_gch)0meG3}GxIvSxttlRD?FQda}TU{Qwy8D
+0K2HnJbyZ$eI{z|e{(Ea&9JIjt{CKx`Ja1ak&4y?yKD85fsH!Bc05W5vD%IA_6mIG{a-)3G(Wx@eT%i
+TV%m19^PYYqvaLSnKLgFPrA~evFIapjcCy}oECcYx7DS%sjwL+n68m%R!UGp^_&3YRFJkJ&AyVFfW|}
+km^u(#X!e~Bt$stAvVhVxv=O4fS27OLLJUk1&1k1DFDMXt(r2Y@b%VNe-`^5XoY5fIIO9KQH0000803
+1s8R@U;w-VX-=0Foa703rYY0B~t=FJE?LZe(wAFLG&PXfI@CW?^+~bYF9Hd2D5KE^v9JSzB-0HWYsMu
+MoT!8&HKN>C!HMABwfb26Pu7*~2gl0xi=r7m8F#Dv3MnzweOLg%l~-N&C>&Jl}W7bK&73wHLff)UhV4
+Oh{F8p^^`zP>aQ03o@yW6nBDK{bRBC@bT08KR(~(w|9Sj{&;(1@PA1qQVaMy*(Coi68N)ZoZ;n-9nM%
+o>1v%?iNF%8PP8&(`cJ_r7n|h{?@>e5GVKN1a#FM-)#ekT5<6&4cjGal5GBQUv|&3eC}B8I0fYC^!OQ
+Wezz<l+KtsV<fe{@KgQLj32kv|VhV&lMM%{@9ce1S@<w1F3qoJ3B#l6&+@3LV|&dO<d!FPR}R-HK-kR
+}1v`msm1Zgmm3st-t#uXqmBJH7`Eq3{gXE+1BIq7uk2eZZxMXzhvG=Qs$0(nH!9`SYM+SVx<Tc5s+zH
+wNgTPFxC%*%)94JIE1J${)v=cC-UksKiX6F{&HxV|qlvY-X$jJRXR`V}u>-W6flZ3zZ?I#Kfx7BobVg
+m+eeo&!MNuIPE({1)>yfDGpOOO(L%D=a)xT<WMqVnb<S!-pW1abQ->eTTmqBi`iHRE}m&G{?b5E=t*P
+o0n>UmC3>rQF<FT^%mbng&bC}cg6n5BB@Z}*aFbdRd8S1a9eJZN1&T7^Y>A=RpJIWysn`s03+o@4ye#
+1e%<l2=5los{<!Co{L<&`fW{fNMTpRn&2k-E<DNnf0BM`RdVF`*@Vd0NRFv5ZvJcoG%Kjj>F<QVXog&
+>N+COtt;lUVTuRaQ;BRnTHZs-RSv%neJ1hF4fhD2LPfYNQU6Q4+WoVZO%0Z?FUk98>W~h6}XnpW$jlk
+YNSxCh$5Nr}y#rTY-v5`SdUauPSr`L+Xb&GrOa$Xnq!V#OoIkaYNp`dnxn!Ws6m)%%ws?o$!XnF%;%z
+tGPRqr-G{K&?YJX1&P)*x&Z;RnNH83^s!5}(S?nV-7ryFvN=l5o5!34Q|-viOsuK4;n~q{YbRPK6o3b
+-n&PMDDoT>?5(zGHHwou7S0c2=%amx#Gw}CX{e%L$!>8!(b!pO%0jm*1octbooapAPII~_f4GFs0R!y
+Hn6I9)-O`8!<C9fb)bhHMzClsHt<9bd5<=?wz%<g@SR`^N9PmX^iXQv9O#k@R^2L6lk$k6qopOr@~>*
+d?gDENjW%J8B0igq`VoT&xu`H3i5Symi4DR59$XA-d`c7^wZBStL3pbUmv#%;EIWV^t50#@o6w^A0oo
+@&3np3nj#zMZ?k^`uNU`y_1a&bz)@HKSWe#89R0c5ppGt}%h9Eo#rXI*lqYooFYmToFZQ-zQo%s8)ot
+7%;R}>B_K0#r<4&7n`c**>GlXYgOnek7{uWz!ZPh(>->&%sCj(OY>c-WBpT+t7AQ1yH4=Eo?>cwe7|>
+ZTW3wPMQ}_<o^qg49WSqzF3k27;Twr4x2wxHKcrXh(u<2XYmc)hjL1XeAqY4CPA|T{POmO}PTfQb{nR
+8-L|~~>LYb0q>+;ewsDl=%k4*15E_&4r;F;no-1rlu9e-q$qrmP7IHstUp_fLNs~%osQRu2&PPRt@Mc
+@jN*!9<Y@EF#Q6w<YB{t2&#%bGBD>fHk_5UM#7tDh`_cN_DL;WaPA8=$z?E{DEJpi-dvFb#1xdML%!T
+orU+&J-R{x6z-tNc82AGfhbJ{(3}WC-oq7c4SK^QOA+WQ;*U;(0iQ@Z*kqhT=u7*`zY&afex65TmMW2
+hMRwBcvum}S=e(Zk?}?%KoaFdA}Y<cu)D)@=Xc{#2O4&~y*q<_m?DM9i}48*ft(TW!(}Yo@$Ulz>FON
+K(dU5iK|a90pSW3t$m_GV(c$fRt%Q?6Ed1)=+~%T$+`SU|o%9JahAu7g34}=g?)vqGu9e~0?k=VS#$N
+5lTgAnGjog2ST>EdaSde{^n|F;oPd1xmndiF7=Q*&T4AoEzD|C}E4z=L{3o}Fe?GlL+YNf>P7~u=^(|
+qczNuA{nnC-a81St+sFqq`S$Il<_&l!Sg89Vr${xJuJs@!AY|8^y2i6Ytb%gx@4vZ=shzZ=PF?Z7g$+
+vTX0ua>V~9aKdj#;DLu!3NGBF0j3Zrip(0-z+~qS!c-Pr@LQ1CuYS<s}mGSn7CDK{?W>1JEhirljw`7
+U7gJIh!J&;+H^iz30y!OXmk6K?9^fN_H~-*&SFD&b_==1%AbE*t=9=eR4Ym_^gum-ZM|U~y0N}oEq~S
+5{xn(Y{Llw`i`v8CBX!D{#7OP`6T%YzJGH5TV9kvo_3Dii1%F)WAglsC8}s*C{}NWZZl`Un&T6nlt&A
+?~sn()l9*gMk*n}Y0kQHHiE9OS8w0mv6_#aS90|XQR000O897^_9IY+Oaz5xIL%mV-b8~^|SaA|NaUv
+_0~WN&gWa%p2|FJx(9XKrtEWiD`eeN)kD<1i3>*H<jMhsu!i2Lyc3OHIg;+Qw-E<v4_rtQ~<Z8Cgvzr
+T>1iVqMdwIX~@=W(VzPEZa^S3%V!rRCSH8l{PIQmC-G9vWxiv)lQq($n73RnpAy<Tl+OB-fGqB1_OC^
+Y9~;m<wxmw$DWTIUZJqh2Ky^golw{Wp<-yR5e-`V@{j2|LdXs)FgRc=g6}^d(+Z~m-=H(1Zp9RohOIu
+JA>ckrX<?+YAjToE8tfjyqG_cP4IHK2!wxskbuCrxd>G6UR%+#Dy+&9*34621<D+G4JU@Y9d&mBtIiD
+l~91#zrI&dXgufjaycX>$5dpddVXZbQOFTmx(<L6kG^9yX4<3*Xz%iGVQkN4T?99k~2^aJqgv3PRx{0
+nY4x|}JVcyU{%*#j>YcjqVT)hxeD`8q9s=Bt!1^Z9&{%|}KQ3~^Sx4xUV1wqs|lgV@kV;2sQy%DMUO+
+}runxh%O1FrT)#l9sVkoS36W(FClt4JP#W=1-~)(rDG9i_BUWDK-uEG#cOKqg-_p{;h<*hBEG7dW$WK
+-sp{+BC-PRZ^Sty2~f^kAr<HJdS*kq$zM=Q0|XQR000O897^_9;0*^w_yYg{#R&ia82|tPaA|NaUv_0
+~WN&gWa%p2|FJ*0SYH2QTd4*POZ`(Ey{_bCK<vvWpJR#k_48k1DNZmDkaR)amFn9r>Nhh1FBnl+uMF{
+fWcO>=d7+t<Z<h?z2eD2PotfexbTfNAYEWxz3s16|f_1#~8Z1~Na&CR>p?e9zYSQ{a$q*%hA6@4tcN%
+W<uTZ5`Mdh3rL#Dl0h4ULBqE7NOy^2c6i+5!iWJ#+$&rTijzDl^o*eDmSs+uONZVO=EY;9-8dScu$a7
+oAXP!pudLOSoP^@beOW3F8IO--XQI3rZm=7FcMUDAl5l_z9~_s>mB~d@xv9*ZRyB;5(>QawwA+Dha71
+2n&a2R@RC4C?zj)EXIvLF8dE(f4zhqAwac5-4upgZfwS%6D1O=@v4u%XRZ=#3Cs{kc2AmVk!THD=`4c
+HLyFF2R|m$}R)VvFe_Ald#6Xpl7?EHw_NLQE?yNc2g*2LTg0N@S&W3icYd?5;OqBgNd7u`LHT%5Y-LA
+KHpUCRb1C4?G-MrphZLGG>p}%^~p1f6tIRzAzFq{YO#{Ow6^5t-{5Mt0qjaLp$?CHC=5>L2$3eGB75z
+s-kgBcI3-%rbIEw*If^+Wja+8yJ;oJzI^O$4Fm^cA)FCn*&zS`1oib<m?t4;li37RIo(-!k|1(M-)ZP
+4Fy{CCCnLI3oAj5xl}YA;xGh(xIII*(E~b8I+DDG2G_Fg+7f;qOQI-fDb~OXqxZr86ua+%H=Z`c<3t+
+YA!kr9PYjbu~F?DoYQxlB5gMn_BPc0poEUx@DAIJQc}&Wl}&f(gM6fYniK_Q@MwL#P){rz%&2dBctTS
+{o3jT$1NFnopL%*n2Q)$FfM`vQo#k(?sY*0QnGMA5W>=6F)a$k-9E%;v=>LpkyKeY-^kt&HHZ}Y!%#r
+4eQmAWLWp=DJm9TSkB%%H$3vJMzg=-ts`fzStAPsIPF9D-N1ndnKg@jm_qQEwO!6vjq)2Qmqxy|8{SM
+RjXUV90FZHU2VEih%9axu>4eqb{Qr?Y|tie`m<l;@S~eB|s`kK}QnFp=PzP5qGF|G61yFasdcBkv~sv
+!Ml@fCgPR>{;K+dc5lv02_x6o2~*jB54H{S-)t55zr9G@{zk1492buL%*Onx2fAnPIHm-G7%N$G=wj0
+G}jyBuZYXL(&kRvt!T<|P2Tw9Hw`YWLm#4-t@`UgAyGbC-Khq{UdIPq^|8jHQ_sh)$)951>`x4Gsr>j
+A^n?@;v%n3O=qt852tzvpXbt^zb@ht50YG|IKOC2akH~YOv~ftf{V>BE)kJ&~bm;tqA=d>~f&HbDsKY
+6QYj_z?+<HTuoRA+)SqzH%m-pe~KTt~p1QY-O00;maO7>PFNFmeh0001j0ssIS0001RX>c!Jc4cm4Z*
+nhkX=7+FWpZ+Fa&s<ld5w`lQo}F|MfW*{CabdH0PH$UcTi@?2^8A}Q`br*r8Kv%?EoQATD<f4|2I#v2
+`B>h6orCYF%vIVN8>v66mRY-NT;srWdxVsz(+7+7N~QKId+=@RaKcnYIOJ~M{-hrmzyCf9!JD?uZdD(
+@Qwm4+AzR|c!#Ra&R~yT#K)HsUQAjOW=$Zyc^yU0cqp3fbq&ce@RCM4VDNK?HR-d9HZ7|C+{$^@Q~Tz
+OW=tdn{_4ypLf-b>CCr$(x|#=nxM)+Z$s%BCf>J4f_0k0#ehjz_+8A~&{=rJ`ASD1hvg5b0+xMP7q)t
+#v0|XQR000O897^_9YTj=YjRF7wlLi0)9smFUaA|NaUv_0~WN&gWa%p2|FJ@_MWnXY|Z+LkwaCvo9+i
+u%141M=k5Pq^TPahDV!@8{NiVbZa0t`b|7^+Pt+8oJ{WTe5ce;+0Jrlj?Yo#^oJ@Q{=^bV^$gDrvMjf
+IW3W?m&cp?;Z-+{CvDA*I#ee-|p^j3%Hi20=^4llMukTG-AYG)AwhrRE>H#wfJJk(+zzmiD+WVRRZ(`
+bfu(GEsg=}@H0u0s^!MO7t!LQRxhVaDCXGi9zJn{d7wzs^oQo10S*lTAw#xfU`~b^TdUsYz-0{@YoW2
+S298=-G+-4442c<WB%Z9s2Fg-MVaqZz*fzz8SwTAJN(-N8MK*1X)lWIR{{Z(&V$kCr7s<+Utm|qdIR|
+*bSDx<t=(%qi)GP0~PeZuv(>cm@p{#@T1Xwg8%R@yUJFPm@_B7R}MYS*K-xq<kSKtfvRSXr)g^)3~Xk
+kEmq28?VT%+x^T$Z!+afg;$t0yZZKag#d!6&1UTAdRO5!r$;gyl1@Z{Wb_=4@sZ($0)Da8l6_8X=A4v
+ck-P3lE-AJ~tNzVRP#6Mr)<BCJiZQa`di0ptNx4jfH1)!G)*&OB)jybJFP)mgT=RpLj$2s3lQ5r{h*g
+G;cQdxOa2mYm0=sC`ymVGJN?hyYesAaczYaN@nRVxezj1F$BeglN83g4rQICDf_L2%!1q;-udJFA}E}
+*szvT5ZFz*Pc_qsbFr;~dR3rbh>|byx!p$oc?^pyn3cH{7_96}430?1eb5}`lD-?Z!bk8e`#=_hC8A^
+dhX|I+>FsQ!Zx-56Rd^$~Yn*~+*`9icP!<5bQ-?Y8i&pR96JX3LFC!_hxm+l5=>`!d!8`5fQ<FVeZo)
++?GcBPv2MN4^kU$6n6C;tIZO9KQH00008031s8R^I^Wm_h^q0L%#h02}}S0B~t=FJE?LZe(wAFLG&PX
+fI}IY-Mw4dSxzfd9_t-Z`(Ey{;pqfP(Rc*RM|<fZV;LP@z4$d8Z?+Q>?H_nS~}T;B~c?Ow_cF{zB^KH
+>H49=Fe9NY@!@lC&mCVtsxn#a5@>Ax>W3f<!}m><TB#}nxzeDqR@xE*a#^5}f1!zCskBy~FoRsH686^
+CCYjH7((apWoT_qudwS34ld)LN>r>u8oCm?(9wF~-WSAC06P2vM?xlfJWle!#_Npl|^6rS5HV`tI=cu
+u=L1Pe7VbDN@n9)(IV22fIVG#rvtJz(0T%#epU_+pC+G0O|V;~O37$kO44BXIE(o%pcS*6HkH8IkEDX
+J3@iz*X3GsL~4Z(;~~Mt?G*Ga5(Ejw0QQBf=K30$J7tmb8mm90V)EUlm3r0nld#n_uNY)|g3=z*1I1p
+MWCC<!5-?Wg4saQwNHb-p%=G?!jvhzTB(>u4WLd*P<xaYq)^>kg_dHQG^dc;7VstHRpjGq9Vh!rEF{q
+jNpSbHiC~edoGFy?i%tq2!afASX;HG98a9P9C|{vvyp#na<Yvk>ACI+`rtRWRI?Fw=D*0@R2s6A^!Dx
+v^FaQdwWL@Js;$x^1hWz%gfI%G@amGQ?h`0;Uylnq@89r8qiu8r;TddC7DM+Qiw^tN`}Pm?V-h{N115
+~A8A@R%jGqP$$?YMdHfGi@R!!+tIO*~b!TB@+cmb9AlgqhSeBT>k!B7Znc{Y>%>%k`m3_iIGY7~dy3l
+HPRK7~*D(_^2lr^lz>>z-x8=164D#N3&fM*XgLdwA}NFZy32aA)YE|K&HQtx#&29@cDOO?|WW+>=2tB
+eAgDyif*_xT-qc-Fq}``)rV^Z;6^)-KU=D-8okgo)tTJq&8zyF}J`s7HgXPyV_71pUdW}C1PY}w@pmj
+g<tKU|EVh|4L_=irk!oapo@cNt{O(>q^6;+4bRH6#bOb`>bf00l$_X${<<C0DYI2<H-gQE;jm=q;IQ0
+mTI?MI>5r#ON<--6isK~-G{xQI78!dbjT^V*iPB<+?szI{kxF}Fe|}jlAuoj4L#C;?#?_n;6!L&DnVo
+<425y!!C{a{Am-)O%ZR4zpj`kU4sWjUZ6}ZzJfs10+HUtUA`M5p7Y<443__%`KX52b_HyqCv@f-HvUy
+#GqV%p%Z^seC<Zw7r(0l^QD1g?e?@pC|5dP4DCNjlxq9jJQUKwXHGQb5MZm7>Wg0VFHY6s*~^>A**IC
+4-$%TE4c}bh_Q~nLmo6L4Tq1qr1+=yd<hl13x=uj{@5e=Z0fyxk(&WNG=5BUTmo+j*{$TL(Hyz{<8I)
+?>-B@6$j4C%gbJ<an~`gsX~isk9qle5idw_FTdebG@54T(P(;w;TMDpChWRq+{({xzOHwNfj9{d%P@l
+Q#;rfO_0FxgZhhz0KivBJG91la*KPlK>i!K-O9KQH00008031s8R!8(AF+mFe0B|J$03QGV0B~t=FJE
+?LZe(wAFLG&PXfJ4KXJ~9`XJ~X~axQRry&7wGn@0A#f5n7!Yp?`D4?n`jsBX4B>7F*}NxUa}BD5HZkw
+k)kGAOcYyT5(!o#8Q(kYqR8m2Ctw_x+kXgM)bzrx{7<(Ik!M#2bxCAcn5Kf7OI%mZjb}o6~F-`vN9gB
+|$VTz<v%`)+GOmf;c)7^F~H*vts&v;zdnz4I@WKM?RepcO1`0K}6k@PU)?B!oMi92r$x!ZsWIgMBt++
+$}0g&JQ6MDBbt(ULUIHWL?nx0hJi346~o36$9zY#MH(?d20uuXyrD}0MV3J}BVHJmwBEj>K2V#2mNYd
+A?)*FDw1{%A7@y)GQgajy)ES2!W8`%(orUn1(NqPSX{GR2x$VfvW0VNsNt}{dg}@AC!x6Y`+%ZVyx+<
+gLq)E_@mN4xANC`6zxsmX$QV)ofQlLdLFjUH6z)CFhqA|@agP*H(Dwzg9++nK3=nuik5;VZfrOXnYcV
+58g2Bqs&LVrlp7|i|CghX*hP$MudH#z46k^v8y&Zf6GA+Gxsps-2_L8X)hqtHu|FrdC6+oHS=CL~}5v
+WncBJj~WvmGoRL-zDeGp|ui@hIO<M@DMTlGRASTQe|q4uA`-B%gTD{M5%Kk1mkauAf<kjoAwTAKT98!
+iZTX{QOcmMOH+a6LA^dLJo4Q}$``R&5tW0JTL1&{O&rm+fV=|7tk!)68JmP2r~v`R&2l&<{}3kTfq=0
+y`a~h2q-d1gUS#B(MHtFiDcwuiDd%B9IGcGH@ng!O<7_MDfALmiM9G5jT0#7Pc_S!1Ybw$x1OJ4p9Az
+!LpK8H3aW+Gm$Saohdxs_Hu!1}@*t&e8$deF?c3w*tp_dYRo1~O6$bYFKm55NBvC3m<7(zr3hI|^Un#
+;0PNO|psiLX(%s$UjY(z;25@r*Ae24dZS-BE!$i60+ETjdNZ$9fEHC$d;G@=V?sF2S*|r_?Q{G1%9Wk
+?krJVj+}~u}XnmT~Kin++K1zmAN%35Rz1mgU!IGf}tE_5aU!>1=n$`&MT6nvA-BYSo83>xp6_JBz4`J
+8zQQJ6cv>m=y8NIl#Ot~7^zB)qV|7%nR!z{^3u$HsTI$WH>dVMcb0~AKRhXi$8nTF8Zmp|ES(S11dV*
+#)|6&N`WUCYEK7q?PR&`m!@G9#)O^q`rO7W|xS+Pu=kpDvul0|c8xoG7<^h4>;O;@yhBBLtj%B@WbKD
+^L(z6Gq{sMV-9~|TGz06>Z(3!0cuJj*0eUiiW9xSV`!Oi)@=0rUax(LpCw%WIlo4`Qu&V#Pq0ga8p`x
+-#&F@QbLN4x7jtdH#!sduqMq|?WWbQn;G)OnOhi$&nu0{{U)ZqSPdU4HC6<+0t_!3FaRqtY0j^fgD_f
+^kMX_To5nvlK$~8ZMeMx|hZ$9&`)#k9e(SBB-A>7Eu_gw|E!^2@9C*82D2!ooK2tzLSvNf`48<bC!^A
+mZSH1s5Tr!+?>E59q5f=-|-ueJ_v-5xdV0p0-V<Ww2ybevxcF}4)iu}aa`COib5^T#LH&3^S#>QRmE)
+#8`_D};ss<9gtRI+Fm<B!YiPWDHgFtgIpjF7s@bFd@$s>7(&utI8a&*?kTd{~j)Fhcn0V$B^5Bj*Oha
+2m>F#G)mN0(3Uo!Y*n$-eLxYoa4=^wvw8_#Z3t!eaIf49E9{M++&Gic&=SgsELeE;^%lUD~sDr^07^2
+$q~Q>0?m;02s`kq>Q-kL?2j<Ju1kGi#C=%!IrNVq-6X)#SHD4DCCogplt0>vym;>@f4Dttzw+uYbD!;
+r*{yuYLgRJB27sqBs%1ru>>I4|QwPCl*Kh*QUdjJzo`^J7?giAlT4(7;gJ<GmEobSv=XuVrW!tyzI*2
+M<j`(JC9G3!VPs%gI`bX+}I+4$kL=OhuCP80ME&l?*|$5X<kT{ar&9JUl=JHoimT6&veB~RM;y(6P5Q
+}{GptJT_1*EKF1Odx<D~jf-GkN1Yd&NjZ4vqZ3NR=>o)hY@eF&mlp2#D0*OJb3JXmp<k{Hn@swy1Aq*
+$NrIGe}_!%!!7GsAj3z!QDcF3n+5-3q>9T!ex<{<?>JrEefZ6HCZaY@=+bFhIGG$1uBWt%}|R}~L!)J
+nBxo=e~zMbowr`QDh52K!ZJujhc>T@Wqk*5oLq-siG*{q+9r#hKauQ_XFTOMEYbPB)m-qC^?_;Sjd-&
+{@-z!k*e9yzWA&T`reKoYDX~V%V_HTVVj%pRQV80=jJF`wm^&cj)6d{tU_ex%J}wqTTDg=yuL~r`^_g
+X7-qQZp^ZIxV{TquTKGsQO^A(>baCj|L}@(x;gX8gV6E819LF%jHuL@8l+>I7rJ?&8RQzQGFv4x8j*m
+NhX_&w{2wefE9#|r7Yj|3jzgTB-G;%=@ZKD>VNUx-swom@ZtZ0&&KWUD2=k(AYMa~;-ri=ri>p9c+1-
+KJE(Y%h?aq*6Y8z6$P5l514i`$YMyJ=^GDn<<>hwqf^?oVJ84R8c??EK}RLD_D1YKw@rI;{tJ=O)4ME
+*eO=X&Sj46e2q+bD}rs3|o1&^`TnjXvPu64=<MFxo{m^j;x&o!mmE%DR;>`q`Q|jCd*iO9ZO?0MF-p4
+0{a~px&^rV<?xrpP55Rg4`;UX`fr2cCN=b4&%L6#R|ifm;pJvlgkTHDk9V3ata1^6)Bqr<+3yjL7H4D
+Mxk2zjAs=WLlUslK7Fy3QwKz;7lgN9oYNlh(1_%BSo)zwV8Jx<vbc=Hk4@4r&+)JlzAV#}4JXWtkz1H
+}Up%1v$i!AZ-VYi&?k;MSu+XHIENlNs*5oJAd-UPnw@zOa+Q_|37;<F_-6UOv(uJ1za$-j7*&r75f$^
+V>s3*B`&8$zg>aLW+g^1e}!(#t}B$fq!Y`@1RauI>wu30((!>U+Aim+ev2oXJ=w62j6&7gJ&5BP<sg*
+!H?6U@{(Qx5$Zr;SYmZ}7moNHmXZEH2{Mm?d-^Ojd-&^NK!5pOYUgG7`@NxZpb`w#5NYo%yN$Bo4!Pi
+CqlA_TUNYreJF8T7UN{stO=YKe(cjM}=ZR&)ON5>kx-3jbxU8|MD|=5B8pWn+D$*luZ$8g&U>(+m5h2
+u*6eMuD_NRup+b!;j2J2nv#IWDB&?4snY!p(|MMaeZh&=KiqNYhg|i@B$u<hzg^!qjW@x!K;pK@)4~I
+5HZ|K;@6_s^p+$>(quuG&*c4JP<+&QgBn)^qh%~KU@A|<s$i$0MoY)p(w+~RVdLJBGqw8bWst;IxoCI
+Ro`FU=GABTOd2g;h7eT6HkfWDT!QZtMW`lxMHp&gNZz0<P)hv>fkOFTGd|11CDiCcg#@9})mb@>L{b?
+2~8cU{Fo(<Z4moqHBW{W$(YQ;sJ7R{}(1G3*EPf0uYA9>sRCn7b^7^J9g4+(=+oo2klR6o)>Urm*A<X
+A~9>JZB00XM>hBq12)tKMMC)(T?h{Nox|v^@MSzwP$MNrS-G<B>erpgKJ9y>BIdc+&AcS`Yrrj3bX@Q
+2L$6FK<sf)MzVS|AR5=NhbB)02jH*6Fx*CiV>R}p6^A4A*29+sMx0Iyqd%Wf&!=g<o1nb(PS4JbZm*7
+Po3u!$ZbHWyz%74kiI+u4X?M;I(`XxQ0s@iti;mGgyMX5&*1Wc5`lAc$;?(QHLS&laa^ZETWp>X^>%8
+0T5e#8YPl%J}A)a^DaCUKA<%ePZVxBNH9(}sJQ!w!%(-r(@6pBaE<9HEeFw%a|ny?q}X_Q^^w>3xq1y
+D-^1QY-O00;maO7>O;`U+4h1pol36951h0001RX>c!Jc4cm4Z*nhkX=7+FYIARHE^vA6SW9o?HW0r1S
+4?%10a-wEbfKa~HpR9FZ_s2<!9t)V%H~EU1(J^AF8057hSZCGWQ$GO)8-IKoZ)CV^UXISS6XeMVRloC
+6^L!4w1r!IoKz(EY?SO)YsE^FK)KsC#!Ky?5pvzh7xIw6HLGj3s(At*8Y`4!bpjtH-c0<K)beNB?YPJ
+Lc6lS#=)rnpx$dNY-hEiUAC?nX?&^B9Fquq>ni=C1=M%ucD2f)Kxh%ORCt$x3#ReM9tv%pHNb9xJiBn
+(bwecJ2&z&_kR!`?n3Aij&$xA4iWofS_(7Ln`yHh<ZmBh26;RJB!rvy}cY&5dmZC7|4RY9>~nic4?0j
+oL-t3wL!c*S<Lb<0=7JNjrqyi%$Ttlmg>v|a@>5ZbxdJ3g2)kD|#R`N5nqb%!!=GN~;2$za8dC@8T!H
+2OQM&B!X3W~X`1Od-TMA5Fm;4u}P`EN5PA2*Qh|iw!Rx^FruiS2KOa_%$g&r8M+PnpYgtUU2hLD9|0X
+&n1&*j4nt9OSS|iOZY=pLJGvp6RUSG8!f#A;sN<%vrx3lU^mP{q2v?SXvZ6F7tte1z>0T}>#cjh(OZq
+$a=W2&>-V7k7^k6^1k4c%u%IrYfQqdYg<H@E2Z)Oq!V2@XgXe}krzqulJiLe3RT5Oxoa!Pus-8KVtsc
+nWDmg8JIgrmNq{t_y$nNFN&*UsfFX@D6yYQwSI2YtC2If8IJ#=7rctBP}R-pfMJa^#Jteo?13bS9G{=
+iT~M5yG5IHurEL-NWzImZEfXj5_oD9S<RFQJHHN)Baxa6|bxq}li(R12e;g^!_XAKR?I3l-YnX6^OJ-
+!6h#e>W&hPoac#oE<locnYE#Q7*?69QT@d8bI84v21MjC?CC6DpkJMtZ6}WMnNGXRKz|W9=^PObFGa^
+UX^{lQLD@;pF@U=dURkC&0Qb<QE%T@ZxLZ58Y&Ly?#8jJ!QSY|R;@ns!n#xd(<@;$ai$*;`fcH0(WM4
+rbc>pT?5sE{-?GDq`dhlEcbzHP|90#MQ1JTEW0a~3?Xk<>&?WuEwih@#U`%KkLqfgYM{MYrZNoHN3s#
+H2Uv7T^eBX2sI>!AQ4@0LV^OgfqP-|~F6n#7MZ!sA8vUvS)6i~x!2BhBNU)=7rJfZ;inF33`KP3{o;j
+k7@TpoRE(6rUvQ-8sE%UFhKowrPd6owrj&2!23IEUf=kCEX29|?lge0w%HRlhVOoY6d<7CKe!AQ$c!P
+wE<Z6%j&XhwF6o?L9x<-47-BZ7pb*WLuu+kYy0%`IZTp=hz+Hw)QKX>2<@j;o~)PFkZ(=D88Lmik)${
+MU34#NsNuP(885k7Tu1%)7?R$>BvgT$}(r|_5sfk{dN%z8Ac*tPYAH+c5(lHw7%hWlR0H7*h)A)(lB$
+pX>2KEtNd@?ITItx(QM}H=A0LIw~OnWyOD%CN+!ld<~<v_wrLphHZdF0*ooy1`&VOc(M5w%Zk=`)a@!
+zAo!pU3BbqcvjwzK+2@NT7u2D$9ZPu>+qu<fVvTnJBJJ(w2{8Wk&L{UcQZQp72VZaxHiTp`j{0U97C?
+rRR+xGhg;gh<Iq?)sGRA*F%m$%WcR&oE9soR_rm^;^>3*K0`aTf#}FyoIim<&#rIv~bX^wEz!2pcj9U
+;20aq`&?GU)-jz(P;KZ|M|19@$Bbm5Y5&ikxkrto^<5v%=-H&j&-WCjuYCL{sT};0|XQR000O897^_9
+IKf!Riv$1wv<v_M8vp<RaA|NaUv_0~WN&gWa%p2|FKTsgd30rRE^v9>R$ou!I1qo&r?7I;Hbo)(9%v;
+5<zSC;2)ZY&IAob*(t4ZNIme+?i0^)5$4MF}d#lquT^}Hx|DO5Hj58$*qPHa%OTvp%DoqyOZf5lKVs`
+r5<@K*2IT72Cobg15<WhrTk2!?oidT5PgTHDJ33wjQhH9}#@Ru3mB`+iT1R|9xQao8ji4>L0p>=oK9B
+)ygvF>?RFKPvrpsCYwoC=l&2;B<YHAlz97z-{~PW1|k&db^C{N(G^f-Yva^ULd#E4sLt&1e60;9tJpd
+_xcPVlls>=fB_1PZnfCeBb}mJ1!NFN^f(R_?s2ia9EWrff&h0@(EOy%gy0)%xW!<axUO-1$?>Ev5=}@
+`B5f?KFnCb^KCo_k;`y&2H)8qHMwJ=B6BI^C~N{`RX948wc?=2HEc#<flTYnpS~nAh1cWH=ymF0T%PA
+8s8EqFb-BgN^_OW9fg&fQT5-gPBpZccla(%Vb8;F)NDYrtt|M#CD5a1QO1a>g(x8Go3$0R&*H<CY@T~
+3Um>f>YwG_^k`5EEJI+$3MA;V}Q!~ENEq@Yx^-~~L^BF%vY1Er8~k>qs>afjA>^!*SLc-~JxI9P9(T2
+`?^zO`ioH63toFJQ#_kW;1^2KC~bus)YL<HC>octg@K%xzk_`F`yTAOhPEJKC<{bxfW}CKU<RA$c03u
+w_M9i=qm~Mt^OH&d9)Ud&hro7^`a-&QNb$fv#1f@D@XJ{>()WpENaSVS?OZ520QQFheca8rw-bs&Vu&
+swk~;sVhn`_F(+e0EmhIu2KE4PttyLbo>uc((wmq3I7=`?F^ahjy1eaAF`cg6$<1yV*@7<H5qc<)DmT
+>Iew0Nb=Nzz5vQ%Sp#A72T{E?&T8+m#%dDTb^80bV2jc%fbUT#o&uH9j#e27h9xMQ`>~V)ts1jB}FdT
+iIgzJ=<6|(uWsDBfTQAQYG<`W3~Pd=vo6D!Iif80}#Ej8Bz;?xqChUmHN#@g7;9=C|bl-)mAE-OpCDs
+6?3(aA>*&x$qMb@I_-wSF-B4M6PPv$)kt<|gGXS5bw_H0Rm2M_jyHVy7`Iu_1C%!&@xxWO=-6#Cji^P
+_^wr%ZW@UnygcM4D8Lu199gd8y({w73~^-F;-r2sTwveRl}Q(j7Mu8@(P+|wQH)4C&DGa9tJh^#K=lP
+hF*H{SD$DcHlQayeax9y_rBS5)Y*DdL6;D(NnHx|MG}3NTm)TZo9nvivF8;NW#$=T#!(6r^T*k9*tEO
+4X_S;#h`a5N`s3p_0K&eR()}FlUm9Ig{M?ZH-e}RCjWc=w%n6LKCZI-5t8HHu`wqOk+3J-Pk-J&@{A-
+V_BD}N`)RDX%d_zX?KBmSg4j?EszT#2@&b8F%5?9$wDY-Ktejyjk>^IYSBw>iH%?ea=bQ_MWFc_><0@
+Qh$EL08Qj*Z7!w-+M3as#l^EYBg0I=K?pxvOWXI6~;4-*Lm0_r8EPN<MFG@3&D|6J7Owv;iHQ+NHGPy
+LUVG{svG>0|XQR000O897^_9v0=>K?+pL|w>AI(8UO$QaA|NaUv_0~WN&gWa%p2|FKl6XZ*_DoaCy}m
+?T*{V@xPve<)4xXL-^8v0#w9tj3kKT8fT|KAqWJITuF>6k|inMDTjN5_D%X!eUi@1?(7#S-8oI&RzL1
+U?(FQ$?0oNP+qZ`xzbS(1(6#*-JpcMd0?)(P=f!vs<Gw8yTZE}b(T{Cg4-8oibyWyC*mk1N$F|pFqd4
+ru2vg+vxbH<?R?Ut9u3xpqdo_0Itbu3|z~|jx-n`6SeE0Ij58uE3HlbJFRK+O2eGh2!n_9@HSJj~2zs
+?V$e0S`4<WJpLwM|~jr?=v-N6{2&%mVwV0jOjVFC;l>2Aota(?btgFNU`MpqNeby4p2bVECX0inakb!
+9y?PW5Qn~K|>N;i>8!3ygPM*pRdJmtVe}vU+wmQc@Mm5nTf9d&b(HDUEYYALEhj45A?7BCp|(>YN!`G
+AjIIsCq2|z3nD>D&{xGi!vO^|h}}UnBZIw_k32Y@j0E1|1M;|7R9kmfmn3|e(^XxXeE=D>eTr+PV=pv
+{ckq3&SQK?W48g1X)E-AEuE^|nERls__#C)u%IZT^9`ib=2|VZtK84{0!AbU)%(#4oAWPDwHT_XsZ8o
+sD1pG1Yf)(lEI+TQjiNdj2NSbCrY@#<FD=+)L?W31>g&^H9jJ#sf>wFYtAP`P+pyt1B-*$C{CKg$!41
+#Oa_W|b)3N9#HF$7IJ2I3Albg*S_>bwy9wniy9!i0%nLrOrXvcYixr1=o!iie;xbB&N~1z!2O8^sc+6
+x$%ns-_yVEE+_;P1K$(10z4usHM>*Ko^E_@WmfN291!^;s@uaYRgv&k2@%Jb0sm_6p)51>jg@jSxKM<
+md2o4X~|2^vS}VsW?QtO@U|+)J*=;$r-%G5qjwr&FHk@hh<X98mER22FG9W6(=^wX4D{ewjl{KKi!3j
+^mvCtVcJ#acA&BmYmWSXjxR>}J;?S7`Hf+sthD1FGz<C)*tiPQqQJ2zPxnz+$O$&i~7fGiT$u;97_y8
+fOD)M?29;&jeMHnZ}WZKu2*=l!`<RC{a<&5aHhv=s5Vf!+PFTAObB6I;HZ!7sPu^427(#8n^)fna1IY
+>zYY+*}tZJWk!P_j$lq$f3(@4oT^GQLB_g%F#eugoe?QL-OWK7chk2Z+BFBSc{Er~nm2;?VwF#nOtah
+Bp+^gpaL9j#W&|V_(%J_=lyAvD*1<k~wEfL~;~glLw!A)Q!W!H?%ScOogue&^Eha1PVYWz&#NSikBf>
+=&8^9-LQ0aj;ReIrdIjSI9>+NgXVa+0gu&geUvs1MMNY?rFp$5#=O}b>%8aTu~h;~ZBDd?T(`GcN%)J
+=6nX>v>JTO)Hev1C+rd>B)D?IeE<Q>%z`Blo6NGC^2U0+@`R70WW}*5o?fP93oD%6W6XO?qgHW=7epW
+is0f+5$EmD)2RO5cy?RF4|?wNj-NeU=dIZL3S5(b4xE{0q2OVve;J8?;gU8R%mPGM0iMR&pHiV)(|Le
+Big4iZK5=PMgjtJ90NJ|3E1sZj+@o>3|}@LTAW#00AK_x~@|lEYKoQm+5ERxU-&Iqg!^JW0KPNlU|QT
+gaZGUMj^{EWR@Nzn!|8G|^5DwbKJl+g5iFV+=>ibzw5Y3MW;;_0kr$$gh-IRnx^wtBAq`ZG?;=LClyF
+l34AmH26krb4bMoqyZs}OD0W^Kz|+NTssE9Ni$a43St5xm8@UFhv``mRYc7UJ}DCdYIQbs0o?(T<HPZ
+g&7=KMj$XufWsu3r_B?TN9QoYVP$QsdAHn#c8VD@9Y1`UC`ez)ez~!9I5%#V>Dn_;2;dBVi?Vcjq(vF
+jfc1TOl-#yIK6Rua8Q7^;!+SRiSERWk@CViGT3S-R#&6$GZepoOd@F|SFvr8<r0OBff_iE<7lK3(}iN
+g>|F)?0nrX<QNgId|v1^aB*ebSqI6%#7fiuiE{9KBpQ%(#G3r<C_}hg6VpY6%)(ty(d+9#Lx3mpaSl%
+17(ZniXXec^qXXy2xUmG!wUHy_uC;cE~&SHnP6IfA9e7ws?=e9h+KiX{%kQs&7?s=$3`jeTOIqEO%Kn
+32mkig%V~c{5}t5?*~KM?~>rkpF$hNu=IdHvL5Jq?C^~z&6&|6n=RXhob+9HGZ=z04Xx@jUqD1yV!GQ
+TD@$LI&(X!R3{|wrI(_i#q9KTsip885F^V}7*Rm+kQ5&P0M{cEvU?tw1BNf!jmmR3rq;Sg-5M3x%a1e
+f-cGippZMAjMHq~Fz^(C#VUDR0#0RcFLD<KnOfl<gOv8UAho?A+n3NIaKAvj>`&I$`=+BGra&D2CHTU
+~PFscHr&x(Z>_)U>>jw>ehX$EI}aFaFM&CcTh!L+-kkRP}q*Mi=UWGPr;&gfi3Z8mTF`IXDncz>yz&M
+kV`qu9Kf3*`DMp3Aqc)MZxOWuGbAXS3y`W%yMq8X-d0p5+SuyO8dM5d;US3Wb1PqzBU_HL0v`Laj$w(
+VeC_{csgTKSZNre3bA(_&L}kXm))dw*tfS#2k?F@U^UlE&9|zlMN~Td?(&f-Bdy8p?c5G;Pi==YJn}p
+o4~M+xE}3bZk_ZU>a^dU%wSl-nszYY#R(7#FXH?k(;Y)XYRYqN2;)%{GdIoVK3E=Ou*q<ft#-$e*CXG
+n^xQ#xm&&Zho1pz7DNmno|t3&A8PCO+(1#&aUC?jMqA<|r^ObHSQ9Gy+Ew2xsH^VXo>(vGcYvs`A~&G
+NdAyCYN^s_D25?c({~-z>C`2fruDP0f|b38gR`ed$GU><1Ac;-#{YY1@4!nZ%Fd>=aQK+#Rnq>#K+}*
+p>NFTUxY$C#)w5PI}mja?^5}e=W=E$&e*gTcR?5nz*e|n=P3vl5?&;`AoGOm-1xNX=FG>idAmtgjh~7
+^^&SiI2%4&DCqu>%raDTMaOu6RJH2B1c&3z7f)%hGW`MfRhPk=cBoW|nfJRRo~sS$agU%!H<%P0Z(={
+Ddo5Reh!xGT7+a-)ofI@G&(Qlnn+ar0G1LIgqAUo=bOuHnaUP_&ldefVuvt$`#z<5xr6D$!&p5e)bSj
+!zx5<NZd4omqpk<}If|D60%QiI>f3s^S{Fo;}2bVgU&qaFcoRVU_W~j((jGXuU!VULsBDG$k7V|zCLq
+eY}jY;M%Pqv+T6L?;hnC=SB1fn5E6QJA{?<mkxPgH(Mz$>LJ{_>C7gvm~*Uv|z!9@FROQ|t4&9ZVtK0
+!tCo7JJ^1Li2C3iD&#+j=jeqV$lrPqP#iL|M(O8GkdR$$wj<SqHSbFEwG8Gq%;2yOG_?d32e-Z_h7Gd
+utf!_$cuf@!qonMSb!?<Su#8}#$(LO<XT`OoS>*tiT%V1NCi4Zw<ah>J@r)9Qe6o%)JEBTM|W%HsrZQ
+|+dY#@LO$O#$8sAyn%(!i`B@a>yf~=_GhMBjh;*)<XxQ$>wim-b8w$vJSWopOicsB|&`D?JR-7~2LFn
++bT&EzHk9gHJtVpdC>w6j|Ik*M26<Wn;o3+;!Wjf<Fvr7$(j~1m<H>|A{Hr}@4Sxy2jy=uh3MYq-BQB
+&Pn(aZr?JU!teIuu?dvs7WG*VBZ9V+BL=ofN6)85Clo8SqVX;T$tQt5Y^ZK$COZizPvn#dG`3R7kZ`E
+YRPCPW<e~>>+<IGKn(dMw}8D_1u|qdQcrYbqCDR%@@5uBh7=dD$tGQBev@X-d=eNKu&cW2YFM~ftKf$
+CR327m6(hwvebdzGb*xO!Nz9eyW_B@yG?*O&ASf7X2#l155ae@dR2lL9;L@DCh=#^eBD!Ed_EPo;3I`
+%-Pyo7Y!T2I#qo^M@DcE2z4aGYt{v#6tnPO38@C~1`o_}|R#&`P4kVgWbH5^2N7?p??atij^FO#*k&o
+6XDOok~ykSNN%Q<5<shO4$_9WYW6lLVfDhb|;)5_e_jjk+NKUj27`D)0qy?n!mMjvrS?n1X)zNK6Q96
+cwB|E{NZUAdx4PhhIdJa%c1^rQ_7!E@jEU)jc=2P4`O28(Okh0TTx`wq#)dxFk&fZ6MU>=eD5f{tQI-
+|PEAn+WgXL43w@Oe*KdRl{=?gsrBAf)v$q@QO}q?T=^ec;kzPPVKy#xS<_U!i{^BXGgv>0a3$F;+?ex
+lQE-7^Nf2=cs4vgB`l{V7fYrTssNhmZKbEj<MXeM%-VHKPoqBJh1&}$*jX#H&Brx6{CvF4xng9yQ~tB
+?SbQ{>x|}{4T|tRYl|-u0>_vAp;`N4<G$Vt|n;qYCirv7P$sd2f4D~Azdk_(LN+Io=$x1)u^%3-VCN^
+d=bLCV(aju@u-PE!dhJslx%2%jn!>^)0vSmUG<Bch2wb*yp{5ccYVSR3O;5_d@q!G8Y81SIPp5kM4&O
+c&T#BvdG?<VWY1AIC=GSkjLF$D|yMMg#?N0#CFXPCj>R85wJmwuWt{}UI<C6BH6wc<<HI;yLrgkon<+
+|$rhD^MhF74Aij4m+WHD62nMjd}$}*A-S*^6+vMA|K%tie_IuW2kN0LgK@44pD1~Vw0NQltU19jbNfn
+<xN|jfJRBnm$8SCM$aNtH`uJ{9`fPK(8ma`Hcye>*me_I_5FFDg>h{8FwI{MdG;1`+Jvb*|B#q!u^q1
+_`0?$O5oUg)d|!lH!z~;3sa+41m~Ke^3s6e~1QY-O00;maO7>RDpt#eu4gdhbHvj+_0001RX>c!Jc4c
+m4Z*nhkX=7+FY-x67E^v9Z8(nkUw((uR0%fLSGNoxb@sp;PsUkVHVn^1<a@zFfhN5^l9U>liB|u5nO#
+XX!0gwPl;38$Fdawjycd@{JFJQLWHmx9h#}8I*vms*L(qhT#Tf)@L+k0Azlw5vn%Da?Y$!QI`+fv?xU
+A09?Z;JBn3ce2W7M-(CDLJlpDLE;ss<^3WN<K0Uls|0+YwDr`;`C7<7?MayS#WWnC}lm7TPpIhsd-cB
+H8MTw0Z!B~?f<x>^^&$~IrFz#K#kuw&7Gko+NQE-;ZRSmSVi+~+dS_2`5)lR1%A*FzjoW5plv_>qZ<C
+i9$Bp+Dt1rvRxaB^eS}Ynk(B&QTfxer`gBj*Rn<KFM8&$%hn?}VrL^wRKFg7w5^!#V9N_PRgM+dvI4A
+ifUA2_2mDFPOD>*tK@DoMRv6eRcDg>N&RdLcPj5s0isin7FRRFIwY~;SEcm`Mp5`9TmB+psRM4rc-R;
+!fY?v6-=JBretP`;&Y&M6%2@`%8u3XzbP-;wjCriu^zL40{QWG1P&6H`h6HvQ-#EnxuwliC|6X08K-I
+LQXqmj&H4_3WzcXkvE8MYEN=3Nef1Gft88fYf$%2<Kr9x<cwkSlAB*6Y*>EDzwSOpi2@=tj$4Xc?I_9
+Lf{WujaFeimuyZ!orBK?xev;Na*S;ywk^gek^06-QInz*&C71PECkxUl;@K1ZB^_@vjTt}xrJ{vX$M2
+h)af0!x7;vjrb#@u*+x5y<Op05wLwMWteBBgx+=O#aGcQ}ku5l$HT=$o<$4bi55B`%q<2oeKLJzVqNq
+zc&<DX(74BXdi4T-Kv`n4|Fv7*M>4aHaTXlTXG?laP+gk3bs3cKAd&o_*r0(8+0K24yA_^hb(%eHApn
+4n1$k_@{2q%^)*)^ToQ%&g-7eL2At_KCVCQVDOrI;y>q+<39uBzhJWe+XO679s4W9bwe9?!eY4R}b<8
+NoIXVgQ<GXu~x)ExJeIZ_J5^wx~G+Kj1lzlZt|W6Rs*XHKC6Tz}E!_eIazUq9q7=4d<`Kp!~&NIka@i
+T0qN{$it%O0pT-lS%Ig7H{|+y+k#eIUy}`(&<!OWr_1T-`q!jw`<yiad>`d|9h&k+$0ic{qm{GTdw>H
+{>!My(&I!w-gcD}CR6_)6*s4*2(DvwZ6Va+-Th4f7c*11B_7#0%F`qBS!G7U4>QZCi3P8<vOwQ`)%(L
+F%dE%cF8&Z!WGi%OAj6sY->IUiSbnKZdWbIm}SV}FA2nrk~r7oskpD@6nfYUveslzouzDcLH6k2Me_Q
+BO0MGZhrl<p{yA_1mRkTjqm_A&0!6!&aBu^eI}FyV7$-;u+VM4pLF#|7Fi07PycVJq;=QWzJi4^gurS
+V5d0{^T;`Ba?)JEbJuN&V1x@I*QD+!i;7i+878a*n<hXu2-9l1-=I!J<@C}`UyOwUM(H8XAs%hr#Tnx
+Ae}IpRHq=?2oIAen3BcK_^jA=mp`y2oTfz&Di}WtPS~9}7B?1wC|W_6t^v6)CSoa*KyhoiNC^+~Q}HO
+>Q+d6`w_6GLxA4?F+r^qjhS}6`M{JHf_iSXTV<A~p)66QEjN2VxT{>}+PFb0SnbW!aKcLEk?TX#t=rM
+^_QZorYO3ye2hzloc3d#hMauQ!mA#PA`nt-gJdaRa;uB~0YFyUpinPFwuVR`fB8SxxWK0X}>1Xau@9L
+v2p@KO=SKFm7G(H`yeswH+5mHXBu<Tyr2+wk~cIK<D0rp{W?#tgep1&xlnrG;WBlp7yc+)9e~<aV|UO
+<m?G$%aGijeb&vspFXntIvX<c#{U8#P1QRrmQ_hV0D!pOcwWe{mJ5HHdaM)nALUjke6M{n>JR0^RP>0
+0&3y{YvMg5w;i}1CEk1uWvAy9V3WPpO!g<*-JZJFl)U3<`dHGfAaCU_&<;P5udr?!3ZH^iJS7j1+ZN!
+rWvSO}b!Fiu+dH1AIF$y-f)*kkK!B-$e9Jq5-8D2t<(jHpujwFoR!eB86E_U>I13Psn>NM6QYrS5+D)
+HJR<7aCEvO=tTXOAw>rmM)<(BL^8aUigSw@GpP(d~g0O<R|tR{Y5rEp{iW-1x{X$!{vitgmO0d03fBx
+wAoNv0f8s3-FzqM34OPwXd2Uk0iYaAnW&HACy?&-<Ga3u5JQ_IsOAdKeOe)F1E3TY=?ivI^-$K(3RB^
+%VhShx~*|^IUZmn2}B^8l{+30eL#b78Pt|k{%3e`BI+fo^b}AEpot(!1`M5=|0Mlr{$yZK!=H5Y>=Vo
+_OqYZz<b!~t<WT^eGW6%O`<*C+kqdvc(Zk!xF2QTe#d+5J;)zyw#TSgJyvHgoE^cY!OmiI%;XdK7{yZ
+^B=;_2N&!di&tF?#Zp4$EI_rxkz42uKu1#6wRGx#BOow1UUxp6&oQ8vZ&_cIual0vwu<KT$b=l1piVa
+qM+aUd@x@s78=9TZ&YCfA3*%r@}92J3`1t0fycOXROcm-xvS(uN{zb`l)GKa;&MYso@HSjLzi1dw3*u
+Gs`1X~k!<TU&6q+H=pG;R<=BpRBMcvqo1g?3Qt6~kkmnCd^tO${bB?l1I856)G0(_@`K$tLM=1?Rcn@
+HG@L!5z@27{e5HS|Aq0k-CzMtd(MWL#c(61nQ}A3naWHObMU2CDl?f=%FnsxaVyNa1vXMe9k|tN2dz<
+&nVKk33TAukXJ@NY+n*H(FrG2@UekSB_A8!bM;~W0UL^r=}=8u5YK4@z@fgA`L}yPhWWnC$gT8}TJ4-
+m=><pC@@NfmIwbS<EuOWqza8Q2&W!!9y3~#hNaBmNs`Fs=9ELN}cT#;T!8Cryw}@XqtJCmBl704Z`Z^
+Dxi%q=rq7S3%%+78(DEv_8;?lYk^InJTX<)FG?TQQwpva<4f;$+s3Uq!4D7O5bR=GT_6RvsPU*1{Q*u
+7TtpTfS%60mh&jYCW@wDvr`5SwOLeA>y&e5a(h7z&x*1ZjK>!Focz6*;@uiFH$F{XX@p5j_m!LAIunw
+c)|fr%r4=F;urs&Lq%V>|g|{8%5=zXlt+^?oWdI*$n@PUq~gbDiRrPB6)47Un$`04y5|R)6oI-50+V;
+yw+cp_CI5UnLdp`je$S<gyRuvAp1A^W!*wNBcH|^zELdUGm}}km>KYgVhyjHy;Xu=Uum^30SpzZ%WiY
+Cr;2+*-5g+CKiV2sF_O!8LS)h~aTzxEEH+Xi4H4a@R28V38DAr+>@MItF^-8ZZt-QmMd^e&rK-vXpTx
+m4|9`eUI6lZBO3JzAdHAT7vD_>_lF#w_8)g%p7N*z;064z%LM>`jR*yDhu0vFfDNng~LBQrMOmoM<PW
+8{%bn$m%_EjeGkxl{W=>6zyzasK35Z}CTQk4JcnC!w89K&!6DV}_K!&W<DUq@Lns}S;q6TVm>U0ty|d
+;ml)`ppH}LV;&ofFj+>RAcc+3p-mkn^0TBlQ((ctXmxWu(u6om|P4!feG^Ti!JdPnaeFes%3pnrz<T?
+%{#TwXIp2;GPSfYqAUATzEQ>w$6g1Q!~<!M+}a=RX`I+v@COG640{W8v7vcRW-}7y`KDlXo=4#TucIY
+wc-d_1FQ{&EtfDlqFCaG@f^@knD{J0;k$cKY(Lchy>b89*t=^Ot6}uf?n;zr9n)E-qwE$!<+j`-OcJ#
+4-*r`CaMNNmNwih_CCfm+Xzw8{+d{>L&ad-zSN7l4ZT^{`y*3<{)3B}3qG(t{jdNWPRXyA(%FVKrtO|
+#9hF&y6)Rfm4^Oek5-uNKlRnlT>YTqWmMi^cFnQUVCoBfF)w9uR@x$`=&!;hfY**@Ko#4Gs~-nyb};P
+aJ7plo2`^-?pXqtm(Ld2k;uo(%7P)aCDl67Y~X%=a$R5BtVuFDOTHz7~mbF)lxqL8Z95@%1kSC`S521
+1_CfGv1lt3SL<~THg)q_J{9CM^KeLuRp>%Osz4mAng%NK=%#4Zum47g0n3WzGH;uQIC_n<-{3#rMw(C
+`p7N0sFr59;bSgd+chtGxB76;6NL9GQ%oTl*N&|++i;B-RTUs{<vX#)k`IGS-e3*JdjCegq1a<?ls<m
+#7GV6S#O~uh!O;!aO`kXBwK+RvVh4T^*UwS???Ol{uhyA%L*J!izO#uokiiKp8&tEOF%w9u&w(u@MbH
+r}o8LGjql$VMw+HVmyPQl+r^s(5072t{ED|Y<k(ujVy*^(ye(o*(o#^^5M=$&*x0<Emw{iWZV_RM-w6
+r*&Iu}{WH4_mH_`gSby&+kqx9-^OqxwMCGzc|A$pB>=iFV67Ci(l;F$@zPG`2K?fd~)mz&(58NPCtCG
+hwr|>u!omlzPE?x|8}?VuXBg;sYChdpAPWVdxzA|=l!gT=hCOi_v6~_&h+mDl}d(6sX4}p^v9f|Z_Jk
+vnT}+9(moXwNwy;vsd|)%514-Y-Nae+QVc}*h+e8iLh<Xv!(>vIW81P{3P=pXoh#(Ol8V;x@HJVu)fu
+ibV6)nwd*9)kb!OwG{b@bk(6D;+h68^v$Y;EwbQ>RLZ>E_Sc12`nkl`;Z2M$y6`Y<7XC$ED`sf)4ZHk
+JXRHwn+>&r~$?c(k8%07_6Y-y9y2SApC$wm5AzaYDW(-+lwE{*AnTLXL^At1Jl_mJ;&aNOt69X!BESy
+rGOMNQ69;vpc%uP*=?l7gK)RC?l8vRgd2Gg1-bBJo1$IChC+;)otoH`rLGFNy$mqf(t5lQD7+t=M-ux
+2s84P#<LI|27UaYqQ^0pJf%=ea*?F&u_d<tTZaW1!iI<bw}~5U!|e#QZn%{K{DfyQc7|!o-9^7SoF8R
+xR=-DKijpU>L(#SnkZjwQ_-JO?p(>@KTP(Hq5KH`19w8Vvnd!#1OvAHM-h;++2F&$;P)h>@6aWAK2ml
+;P_Ez?`hXgPL002`C0018V003}la4%nWWo~3|axZdeV`wjIX?A5_a%FC0WpXZXdEHk_Z{s!)zUx;I>O
+~5)0@_{*0SaKG=_0^3DV(I2ARrWZY;!@20!e%8{`w9{QKBA6c5|!_w#a$Ud>oG0p%qdSbym?<iUZN-m
+Nh%V-1c3onP@7Wk%wc;A&S`6u;wR_3JH`oTR|>MlKh&H-_jx?_$;XT!ZgT=N5B;XOf743dV*#nWbOng
+{G*{Us?|i6ke^5^tKFe0NFzus(1j>+KIfDR(Ru;%PI;wtN32nq;NZzuZkhQP7oy6@8XZAPFB~4uE%@~
+s)R70Ov=ls0WtJUL!R`Q!o)Dd`dq?w}`aJk^Zx)8DBWg^6r#;|%6#WfSv%2DU81j~jZ-0W`iw!A#YM$
+a+iZ;$j44ku8F=gIQOfifle#R`-m=1;PCvZWz8pLsYC85%wNJV5HJ<<D0lS6eTFF=m%1{pSaWF=N|r<
+|;L0+D2#ytE*z<{UDJm#<Lkyq9$;Nc!M2B08v9*?!eAYC)>D<!AGv_Yi2#$?veOutdtx;yCxAIgdB6B
+@|)GG^NR49r!j|h@+T-VC-)(6brK-#{>D)m57S2Mg@7bYC)B(d`doDl3US0G4d}DvR4K^j+tC~O6T90
+H1i4BW_x21s`gcjVfthLWKaDQYjj5N=lK~`7*B`XD$sQBEwPDxBcThiVyW&yBLW-v7S=WDImW2_81jt
+&H9u}lQ&L*yq51DidmnNu6f^0e^-(GzZOk^V?!=Em`;4Lau2G8(Sd<<x`@~6`<qPas(-_ahmT)|zo!K
+A-YtTp8OtRqZkyUSkHA+`aJwC&&#M+rNycDx(=tJoVQ`lYgq(tVS8QBBd?X>~hATTM5@zVR1jA((wrc
+U|QYQ4T$eZHpa>xaknZ8l?0LhkGJ>i(ME+|n;Mx7Qi@C7ttM%<Wk<i@P%eSC8xayET3MD<eNIDF3Ka=
+1CWKFG$km^AlQ}v5a@ppjVAjoDQ&*ptO+iaa7hEDj9TFQZ*Z|)ou@nW!P<72`46wsy`1u0N1PkA6zez
+H}LchZc;>p^Y(|UPN`(|o^~_N?2aQHp%}&<ceAQuGXD%$Q8@P$QQ$++7bl%^a;=x%Y`(+m!R{r)Z8e0
+&S%c6UxSc|3x06A8?{nt#m-aU!ZM7-?sBoklG&)q2e%^BS&0b=arb9R*fQ+Dl5bG$H-f*tizmU7#G0r
+?57cN`8>Fr!r%&_9)w*ODXl9lI~(7U09%)sAvtRF$%cP?4*&i1Uii{1paGi+(c*X8~j=XoA4w@a_2?5
+5g9rmsh(+4hV)m<o`ua3O-q_!XK%Qf#i<d@_)Q&%86+yyQ5IqIOKZ(#aUU$tVkHI@j>sl?*$bM`=&Qa
+mk*PK#^G{gZLJkwfPRptk2kNhfkx<(zyC(27Keb%nW&obJJ*z>>M&q&^r|U2T)4`1QY-O00;maO7>P8
+Z+_Gl4gdguE&u=<0001RX>c!Jc4cm4Z*nhkX=7+FY;R|0X>MmOaCx;_ZFAeW5&rI9f#Xf)s2hc{9Ovr
+Ol$~)MCvlsLGq$e1j_Q$V5t115MFB|5o}24$?=Id55Tq}ixjKnM0*l=Ru>0&{!K~O-tR{K2*<|JBV9l
+z6q)AQdte_;5o%&t&DpK9~J}J|jvN8EkZLa95VyPtCCG|GX?ljpac$FRX(~ff8{8N=SIh{k3>9lyC<q
+7BiNPzi8O<8i6QxKE!dQ2{Nbyk&0J|;MJOnxrm^*~9^cG2>ImTAQzmaVqYvTX8vxz2JkqmR(=7T(o}N
+Vjijy<Al#uX3eNw1nv{88D+v6TPiik<@cokh3Jul~y=;BvQi^6EhL{I@S-87KbYOZMK2c+HC7q%=@-!
+Os?pTSq*AbO&@DbK8I)B%#szoOIG)$Pd6MK9IS9n$rY@N+PP5uKbjp7_z8mG)a>zAc9D9U)I_cVCskA
+LnwsphdMo%uWWJ?D7|ev^^nvE^e?d7<Hk1GZB33?Ol%yHo<;fFGNmi0ol{ZDnBOw(z$e|g>o{GWml%`
+|BpoU(}5c>I3StpOAU9&Vg5L`Z1HI=i#pTAPF0;%gJC;Kfe2`yp4aaMYBiiF)aJJbc{s|A2*uE|r?z}
+z1wlCHB&!$4)dCTq|Q44Wk^1LCr(jlf1&35-SM%bHbrL@w4OAt~MA+Lfy(vS(Qh!;CN_OtKOg^Dhl95
+^!GK)0&S-R)dO9D1z)5ILeBOmB`8(xut3&)Z9<mhPQK<YZ(f+SipcW;WfJ%lS=u`Xoe;$$s+QGu9GIO
+IjJi>&FJIh{Q7(z8IF3<!kMt3+3kOXZ>i=;8TPFsLVKwhoRz#zN}NX}R|3WHRtWwmWx&4joHQIPhivl
+du8#|{z?B1TyiO}z3(bXZtNl{gWO!Fqxue!K^Z{3CfMP#uWx(!I%vnQQj#ZJ>fCM`VXqXDtyodKCP!X
+i6Gi)Q(S}^BH@%s{l&T8krQt6%z?BR)6Jj4>Yh<+G~&lSsH|6#S!CsqJ(&v6$nMVH`J_d`O?1qlJrDk
+NK=#Z?jHYBs<ZG2%H%Hb90BG+MH(c4-q&Idyy+s2QL{DGU&8tAneq21wXypwMD)hR>sl%lU1RbBi^4(
+$b)IpIIpxNJuO~fx%rkM2`@#E8-NsJ}bOsx7=qb?xA*D1P&K7J~qW2tSxNcYMa2g8sh=1V~TuLlx+F6
+tBvLgI1E6H5}sRSOB)DiEJ52sM-v!kX>yvTnF1F{fjU9N_<tw@Zh<%g2<p1}17$1&k-Mi&K}%#J2*rB
+9_8SiUYYmywa?g@yEDA{ol8BrLCYV<UcJ20ynLp<>mOKeA6?pVB_N4-}lqE>*c|32#wyb8iV_^6syry
+3oh<kJ)Bav9bHs`y!v4aFxv?#q0G#vL0fkMcmkE^_a<(7$}zqnH4Wsy7rh?X0)<gV5Hlssld139eh7d
+9i}FWT`P1?zxtb9cw+LzbZ9xQ0_!R%ccAhApA#^srYem_2UfS7@aul}0sd%2h`nkOG^9o91rHi6eR=;
+?z<ifldd+CSdw16It+KoyWS)4ynuSt>$rii<y_id&tTt01vpB(i0a49@iq?V(O;&$-GfY=L11DSiE>7
+FMhcpL96&ZeL~v@`@w8~;ioRpipwO4fQi9AksHt?#opUnE6a`ke*Uk2US7SqzP*ifo+}e4-7z!AjfDX
+~BmU-w#AIO<4Bnm3gK_)%>GIlne}8`Z#_9jr>3(zm;e38>w_JXjUtE5?wwvZxr)Lh$r_=e_d)06we!s
+tX_x=O?o1b4T&pw=9+jBtwT3De?%%FRW5L{BaCd(z{p!ISYwuuAH*R61oXUs?^p9GF>y4Vg-(Xe&zg~
+||d5L$3c`hELovbGsPhyqf?v$nq{2OFSlbE)SD5L*WNyQ$3pnU$AVbG6sqo3Bg|3_k&*ZEq(R7$WONZ
+A&;tZBJ-_T%F-z0%%|L5{htUF;-hX$k>Fmfwk(7Mqe>Q9ZzPa4loo?fK52E%(fd6^n|B}y+jhvG|`De
+<Y1|G1)+dn5I{XNuvspwam`xO7Ga!~9g&xR5wGo$4i*6p>!ZlHs<7@@{2n=OYpM^iNlF2ft=dM|p|_L
+k*h#e!*pb3Rnl1~wP7=4}kQPsj&*3V@=4tE`$a%GoJtXLmv3YU{tX+ybyXF%1fJxlb<_;1XNtcUVN9Z
+hwcQlGUNO1?Kb3?4~!R_px5aKRQxa3|=AA5i?IKWQ3;{n_l94s^7*h7(F^-LNZ_d?0wKs%p}2cTtmuu
+f3pKA3Tb`DtbB<I3O=l_AAG%D6*J$`c!uXrnW_t~5NX_=O@g!zl-gt+Tf7Dlh}ffGuV~lJkz%ZKZ&eS
+ci}aG_*+;s(^$)ZV?H8Bnc#9Mv5iTRAMX^SF~<e+2JCzBB!Kob~!aQ5pg`nlWMD5WUKCGA4{Qotd$mR
+*wmpCHPKi|jD&<V>~UZrEC1Z^Iy@PT$vV(^j4Y`9YExBv#NFS59#3atvX<m_&nO_tvpeOYJ52YYe5mf
+>=y>;JvMPHKbOAJ$1|tzIl)PJw+S;!SC#EA?lMWd7;EF?lJEImGj$ROT*46LzlW!pY3RooV?^d~yYZW
+-E7Ug?<dPwp{J=&9aRs+r{s|_DKp<uDpnRkayNEsxw1)HLIg#H5Px1u6wyQ}ETqqj%StACId;djdj(+
+lQ(ybLmXL##f3pulEth-mFmNn^6FmhSNfS!nDHv-<pj9>m7|X#DI*iL~BG+1#V73IM*Qs>2;Ja^711R
+3;0k{gZ49T}p68%Z2ge;Ax^*d_7P6G5lPNz=K|w6jazI9Qs&jh{hynIOUkf1|z$I2&ZS=5srLaEqxQd
+5;cI>8oD;wu>z~H)rnV&>!SAO($2igNzY#+Ul$-%7AoowY8_<DvT#O@^?+7*o5T8}UALDkV$I2zO5D1
+1k3O;A)Du)-Z!)eUYiK9*5mw2^=Jv9)7vHM8SWb3N^|mVaW4!lbRNakC;6KWkxQN3GQF*ntr#gt4J5i
+UXxoi<x!<nT>L@r7|5WKKU;NXU=c#W4f`vi_pbp?s+J>K468C)(@hc!e^WKcDmEe_sS<##o?Yp->Z66
+T@qcM^F+;72fdMS0Fx#k^oh;Xpa-0Q{40z|Ioy02=DhwFK8ZWh5ZyIv@-%>{HBS2OWzX$P<hW&9K}ev
+WCFBK@OZGLbe<CkvGKRhDBsV|7)tJFFmhRrfAb^8CV#{+a#IkS{Itu{m1Vmh~BJbq<vP!PEnb5cv|x|
+&wx}*bCd$O6d0%dG>|>P*gkTNJOr_GND=%cVW<HEUDT3;W+sRYK|5RbXzl4^b!(-pCI=JjN>krHXss=
+}(C)I7(gDaEI>3kBbkta}buJO_x>`ESY*@K=Y9eFcp)(FvL#Mr}DX>&lAZ4@bdeczt(yA}|9_A;`R&m
+CpfHz~$Mwn%)Jx*zralX=J(Xz3St}Oizb=5Yn4SOaBgUw5e_nn)MHXZKWUn^{e-h4-nH;4F<4_*;G38
+xtiK!#|>YqdWTJNhw0)o1V<CFPnCHsSGa6!~XN?F*e_xpx$^u3qF}%+LI^=Sd84`*d>T)gXbJ{v=Dll
+PFWwNwL$)ub8M`S?<%H*;qxpp0lBfh;Gii@HhMhr-jF<*2=_edPuEI>84XxQ*$#VyWyhVU_s9+h`Jr3
+T<BK{@ldoZt5{bQ;I*tg5?QN@J9c5V(yQ}{xet{Fb-}>dj)Q}P46k62?{Z1vm;_6REm^r-1~W{Qb}ZQ
+x$qe0aRXwP5URH6e&-8ds=}vC>+smt;PUl#Jeqmw~m-hax)2R~n(aY&;PF|81p((43<a=kdM(DeQXR9
+;uaa8C!M;yqjAgk=H_D#xdo0WOT!NRSQtB=ljys*Dg>r^UYakVf|_Y<8XWnm+&xOH0vo(s^q0k#41)q
+w^90*ee`a822RxZg~e_<$mcf>DPAEB91@R#lR1UGHX-$@J(?(INbq&Q1<b4%HB`FX7aa@$P(1CK(vPW
+3;V{oE#k<lIhWpC!QopSZw$NXS!ikQ>OBH8hzev#K70buTFmGAGzXuA}V1#g2!I!eZp`iYQQ>q$iVp{
+_(hHnkIB*T(cn~4de>Mc5d7`>^5fN~Gcfco4S>?W%a;%VU$B3de|`z(#H?-p)p4`{mYYLh0)r2x(KK+
+~FeoUT6H@FHU*xgkEo-v+Q^QtpjHO-bUBZ%r1NCANB)c7kV-i#>DL3M&fQO25eB4z9&8y&MOhD+-s}3
+jynGiYs@%Z)8^!VgQOU`fBL_FO|z$kC>I+)2DFcMHa2EePVig|p0>zJyytRJc*RoS)p9#MRNAU~{}Bx
+%Ca3H-zVzR)jwI{C6^^6!MF8~Jy#r%e8xq-(Hz%IXRHlYhmNcra8!M<X$VF!;IDQFRTbOTLo}_#K`xz
+@HPq1^SI=hIl<rCZBm#vfXMTEbxcduU{Pv5GHAnl@l<%DLFnmdUf1qsJn!7`F%{n!Pq|26$CtytBBEr
+XElui>%^624_QjXp3-Y6KWd7}w1p-h<`uRbS}0aw7Q6`HA-Eymlj&jG+3s0@D<NbBc2%}>>{K!*T2gy
+t6{kv<SS-IOKL)2I5t|`C6oKU@_qY?)YSl1C({IeA)r4Kg)%;d?#s;hmgUd#IOHt6GVo(0wDI}zi87{
+E+;0(XBieFAW(#2hsr#I)nT+A;%z5~cyOhiL4mIcZ<%~o(k5@#lf(4&L@0#Hi>1QY-O00;maO7>QpLt
+<Y02><{FAOHXw0001RX>c!Jc4cm4Z*nhkX=7+FZDDe2b#N|ldA%9ia@#icU0;DRI}<X?&`lrJs)>_$l
+1!V+*lG8HVmXiq$*d`oOHh_okN<to1tbC8oX+enA8Zjg=iuBgV7{uWrWK7EEt+a2q;5sdOGVzQMi!~M
+l?88BH7vAM(?Q6#ZI-G9Fy3#sbzUyJ-8Zr*<g8Gk_<)4y*RQ#5L-A3z^XpK2k}H*cUDvqrxo-2Sltn1
+a!fz$KkC<+hs#W!8o;Ip3<Xm+JxT^+~);fp_eED5Axh&gmziFyQcK{z{bF;25aLw%Nc3bo(T;Yq^Xw_
+Y>nyXrtz$vVZMwb`q*YkH*Vgfph=GCgs3+0alJdNjhzCWEl3#PFj%jbVRIeV4Ff5geNmq8N1X2@VF`u
+*ba_2;XLa1;=|_vfG9{(5ogl5D&`{CK*F5Zj;n(X*G+Ab9x?4^T$)LTW9(%B4T(G#C?gIObfm60A~+c
+~$BPq+5~H5p0bJrUaz1&~4LUe7#nLgBy`h(J~TGXH}6sB^(5*WdnO)S3T}+7XyW)KeXHmnPoX|S@1$G
+;GbyW2qNEek*S49Q=pNizE;H|5YK-`rdSTvRJ(3U;r9#pAZUb?M84n`>#SUhPgSXeDzp*{@4g3q5cfN
+<4_;3;V1{1R4SIaL?b&0+9pMfHd8b+u4AwCaz%v`ARoP0^f~Xd-2^@iDdp#Z%YvIKfw~6O$9+%VsGg8
+}xCVOHhj@+a4Qe6@E6r|vS^q)*C#1r6ksqR1zxL3{oRP&ZF*0V0!0i*jF$1brX6djo!Ixlal8<mOK7J
+Xf>XQT8&&t;7yKdSb+%Jv8jXED8jDr|`rBZ01^FrkxSb{mb*fQo3drrDU}_Z)~R?~cU*7Mwt&nD(c!8
+`BWd0ZIT-?Dz(ln(2Y%F^A|1+(1GuX~m{0pSEI#Y5-e+v$Vjh)LnqG8=f~yJ$M;!2_MJ@WAUZ}#1fpY
+Vk#Qk6-Yp=!-_-YlAO#Ug#4NOCpLL|E%d+FvQc8z$oY+Gwb4};bwUhL$~)-{05xQuYo&eih_U4?2jc?
+`XB%5|8J*CTcEZ9UAF}2q3>Ph%YF%qT*o`0va0}_dd6`b{k;a1&!>Do68QtHPDKtRA$U1_Tj5nnaMq2
+rnBazfyxr-?e$6(vg&5_nC<m@C#dPn(!1Uu%~in0{BAxIenX=?oC*OjL9%GwDruLR%VGv{4;f^yKxyf
+i<p$}s9pj{m!3Kv~~&oMid!ilTyl@FGY8EAW?I7tkeemH;VCiHsI`nV~F3W5K}TVqFv|OTmWFBu;wT?
+7Ec=Vw71AqoFce5SS<tNc`N3F?LeqHdjT~5n{ID9+H;9T25lkJO9@%CC772?4W<Kj{HKE#>aFJiXVdA
+d~Tt;bn$rtjT1FvHrO7NBa1hkdg7VO)n0+<l_>r>u|Waxhg}AZNQao?^hVxk%zu=v-q5kF5Ha4>a`#x
+y2WH;eMi<V@^?+x52vS)A0$cTQ()$w@zm|yl-ozUW;qZyfgyhsdleA0i!W_T_7C{Fp2N(wUe)T7Ta_{
+*+pFITht|xZt;k?rTWr(7~Rg4<gG561yZ9?v16JV(8IH^Y-i&<3_7_!Y;S?lR7_sdpaXSdNvhm^xr4t
+wA}dtDM=JISO=V+4vNs+Hwj{a5l-)MIkj@1sN^j48}F(kP(Xvbqe+yvm@ZeXAC7T|kio&QSiYNXlH>@
+n?+(WAOpoHw6_ES}iH`7MQvdG)|C+*XogiOR55?TBU707~NS0=!)WGcfv8w<i(ySE2Pm`f430gQEofw
+5HkK3VlhWGbS9rT4iJ!|lhVk~4U*e@qiap*@36taU{W`+VuA6dtZUBN6p;MJqe#`PWRd@c(v#mt{mN)
+?Z<rDwS&eC&w5u#tQ^1T9Q@OChTNn|n7&1^Nv>|}goQ1{QqzHl72-tDRmF|jn@ZWCf>sur^D5Zm0_Ou
+_dIBHy$ogV26FpaYp)id<@WqzwlmSUKgI)nvzU#9Lt;iudJpkJtRy~0@?x>a=xIZI`}r3NTKF9J7_=a
+jp7j+%5jBc}IquJJLD(0@)xTYVVDkN8DxDP%0s%|wOV4oMDtF)!1;cR{|Lj>=*YQ)my30f_#OX~<>oi
+Fhx|3>zgd7j?2~=qEN5ycnmvVW?m=;Bf&J;E=P9oLDbW7e-KHV=u&bbjvw=i|@wVfWI49*3OX73bx2`
+SuKl2RJ1g9@xFKFLEgg=s{loV`y49CgJHNX5|#MHIEgUj*1j><&T+OU!vX59F7i1{F>^R+zjE)L(+9H
+S7l+W=X1nip15GN>XyLS_z&jLchY72@xvJaVL60B8j%=lW|0pOv3vWJXTRgo-m9h^%JQXnN_2vJ*`}H
+8QN@<+_xJ#DhmYo(*y`yIZg6^UYc1q|<WS4yPs9pZPg8h>U{eWrUf2z{>EIF#lYe_Le$r9>0iT!OlJm
+lq_-20LB$_oyQXJc6xV@FxIrX<yLf#Drz)@fi5oYBYYV@IvbZO(AJ7}1hH&^k^8<a6m9O-iRE4cXOGM
+<$2v{)G3aPEI=!KAs<VD8b(0&fVbd?n$x-(qs3Wj4XVByySC`efy66n@nK>?uxok3M0HPQl~=?pT8M?
+_$)l`Zm}j~Y~2qGe%Cx;xxPQ(lCbroxF^hLrI!!Kog1G=CB2}381er<IZsRVm_(=YOZQk2b-2m0AJ=6
+bm&XaZN1-k1kHP}mx$Z_6-@**}Ug~t<;zPmaU<RjIJQ8bE?T#YuXzU0LtI<EMRO<Fm>)aGf9PFuyGZQ
+ySIk|W0$=GJ?;kddE@9eK0SA#7a%dpQT6c4{+F9>$D)b|sg0peIA+4pprX%*<kWa#udxdZC(qf;5q9@
+9(%?OVLMCw0u?W(rWt7K>XCPJ5f{yim@(xO;KPEbq*R&i&$+K4_qx@KE<!5wBSewEYKEZgCkhqRl_uS
+)!ln3NP<{dX2~9=P!~_+^Fqj_{{2iM9~YJJL#6bLymI%e1^(SQyk&E6pAX$6{$y7tQ)yp$ua0r%qtiP
+`TURPm%se>1!v!31dSV&CGS;HRN`M%Q)KZOE_k5@v64&ts%4<!Sz-WZE*O3?OkTsEIB&sr^F-hZ^tze
+g1pz1s!*B7K0kes`frT3p7kPOzxo+E9kI&9Fn@zOIi()lju9vdJFEa@ackvm5CD;VsLY{)&dMjQR)zY
+Rn-pB^s`MJ3SBPKzUnV2#1+w)KFE-t@=hSQ)WW_HD_Ugvd`!Z@Bmacgqyg!qGS-M}z^94u=2V;2K|#T
+O>JZ1Rk*4q(OixN6}<d8zceXg$1k%rfA1;(w1byER4+muqap!4;8a1ZZhfZG5_ZG2`^`L4$8ckY^vEg
+VBEgP)h>@6aWAK2ml;P_E!I_7zAtu006lZ000{R003}la4%nWWo~3|axZdeV`wjJWnpu5a%C=XdCgc`
+Z`(E$e%G(y^dteQk-mC$u)xc@U}!qD8HOP+6h@+KuDW<6y)+xP-@d~;DalUOuD}cg5h<SU+%Htah7Jv
+T!mt<^qTPOA0#QM_EfIpSq>=B%<DT|g`}XFSA1}-G_m}G*uC8AfXpP$z-?yYd*SI6~&0#N}-|ht+dfX
+Q1J^AfG`idkPYhhssV*}%6bI%4bR72||;3Xq{4Pq%|Myp*}VJ?z{Hn9N91i??ER71~)mROLrUKaL2%f
+t)x&OzTi?m@7mYBA^N4Z-}tNJn~+d0leNAx+cwU?Rei*b&sxo_2>0;l4&4{-~ZGXf1XeWwb}t4l`VV{
+dkTT=ua7`kr<HH38>I;|0}7)0#FkLZvdBw_QLXeW0>@Z?jERy234eO`3$1MQ7~GT7{<u=Oc+J>4LAgX
+LOiNfO&Y}axX(Cgn;gA3m+;ywhR16nP)(bLFzIS^Ps9Tuy)%t6lh($GDu0ZK1M885UD&fP%u*juoB;j
+6I^5Dfh?gP_JeE%6>HJIZ8HR}K<(lh-_28@3oRsK%h0YR(_)f{mJq!5@m@m<Vm#+>vFG8u@v*A)W)+?
+p-_&sdHQwE2!v%+rXjw&D9F$~~2BDDek#_aPv_jZ1uVpp0M%G8C9Y!y?_Fgp&?>u1114?Bnol{F?qFf
+76BYPIl2zF^yth1Cg}P$FL<8^$%^Dr(2%Py6VaJcJuI2S3R}a~7AbvSdoSys-WYHz&5%G+)lv=l|Z;C
+jR~(w$`GpYy@j7J{9{@Psq)qo`4R}?K20eeE}Gy@rUhaw_u<R$Z|dOL}8vfpx~Zx<61HXM~2l(h6QvH
+=|;XM6>TW^fZ={iPP)*Ed(w>sf<}LLC*`}lLk%qY!4+rpEotzf6<jt2d1MiDu=<`%%6Sg@<Q#`D6;{E
+yQAEKI;f+N($S0I6BYQ>wVNs9r)*<B)zBAP)<C_}nkR~x7keIfu2APhC-B7#GhDpu`cGbfCW9FnKO3h
+@Hg3I)9<oC?91h4!g25;lpDSb|e>q-@BD`Nr&xF^HfPIcMeatyRX-ol6pLAbVKU(W@G@gt5|qu3F0qh
+)|%&c`5LRFuUQ0LlwH&Y8&qKf(ZHNK{Th5WJJTgGk4elaZc!AYNP#!gIKkdrNfHsA6Ean1Gr!-_t2HO
+&@7tfgze<##dEF&4_k{wVh;Uj`cFlXJF}*VCC%U_QGrlPQF4fmm}Lx3Osayvnbmrx6aSPdjl6NAA>nZ
+u54s2^kxaCv*>V4Aj>`baM-WBCURMz9o_C)_!Fz|aLY*q5$0^b*<EM?aYqUT7ohM^tPbRMX|$L$qKPW
+@rgnQ9<o!6^H$|Mun+QgBHsFZ`m@2ePT9!&BljLOy$g<$&5jAb50v|7r-e@j{rtX<FLRQ(EpK(<_OSk
+Y>iX#W2I$X{aV*8u!fUcqN?s_u`Z?EbTVLmz-p&!$PKs?S_b&l1Xep7lTE7$Q_HT6)F{?x0ehq?itvb
+96IR5pS?eIR|s{`wlF6NnVcOqQP#wo+I%UzpORimM4e8v`ZM9Z-grty<|QE0aXFMjNhP0<IO9>5yvwc
+$ZAHVI9uWefYQ?_smU^9P5~~-BNXxhvCrHsG;(uzsUy-O%sUw=V$cJ&+eOnY$&@D`tdfl#RdT0_Cz|g
+8yE?Tq;{}XYtq;L>z+0qIV3THf{C{Dchbj(Hl9-dX)|iZfs7|pT2`%i0u0VA;I00k<M%im@kM<^J}G(
+O*p{n23v5dxg%su{WLLY28_Mn{Yk8Fl1S`-7^0@L}4YRX6w;ynd=Tp6uROW`J=gK6oVk}zn4^T@31QY
+-O00;maO7>Rihu;h11pokQ6951k0001RX>c!Jc4cm4Z*nhkX=7+FaA9O*X>MmOaCxm*TW_336n@`daY
+`Qo2}Ws@C)%|VId0R7(<ql#m208d-C=hc80auKwk-emp1Hux0Bf~XkhO-neCPI^a|TM$)F5wL#`nPLw
+h<Dxq?0N9!qo4ttz-=+RSF;awxam&kGJQ=+3WMOpMQMwLkb@`POnz13@7px;8iN@Y}@dzspx<n>nU}e
+nTd2dU}Sb~{2k>xD#)gyA8uPZ9e+o=zLI7%Ss9ss_3f>sVvzZhdAwjZjN278C0#E@tuD-CO}VrSI(h4
+qey<*e3A$Iy#wqi-TCLua-45OOis5soEP%D~&n4s1I#AtSdG{$S4Y;4HD+JzFr0c-K$G$O%adZ?#uLS
+uFT}!qUh-iAg1N6H@#j=%Na(+W<6p@e4J3T#xR-lM@0FGYMs%oMX;%6y5Pg2k>SVs+qP1VyVNet9WvF
+{v?7=r_G7^oyizX?UGMnEGE7!S8N8v$CfgLu(TSBPMhgAy@h)21NU{(!4Cjg(ED0zpeFT1p%c2;Dhcb
+zP8K*iiHf-LjI=9eif;0N<p579!wt<zl+WZ4jTme{T#<9E9P3Rj!jFHAKL8H8wA_jcSq7ueG{v4@8iy
+RNBBRS`wsZhss058%`q!Pj6bKe!OX#Du6sU69XP@Etv#zO<1KJ{h96LA;kV5dh1gpgNf6QmQWOoGg%Z
+a>pEJM=|c2!h{EtisUISop7A?Eg2zu&uz!i$@Hh>9n8VD6xYzh2o%kaM<qw=zCfT&k1NAeHb8F9paFJ
+$<S#Bt!?+4!K2Th!{x$ik9&!-qoO+p+)g0(RuoU#F2Tg{EzU+8qLsXR2hF%ArM#8lf>UHY)kk<8b$$`
+vsaI5{1?9yu3afG@}=I?{vjP7;oZk2EmYm=#u{&Hj1Xev#Bwm(~|zrEd;z`g((Fo6^exrPfTDcU1O*P
+xP^-=J0Y%`@y!%w|?c(SHX;>(dn2f@2nj;wU$`YOrX}^ld7Y(oV`E^l5Hmeb97i_zK+e&q8-HQqedE|
+<!TY*FczImnKf*}ZpymBa;1VsO{T%qrkm;DC-H$Q$~C89y@qc>ghEx`wc2s{^lA~i(2&#LqxjE4d>k%
+x5~>@WgD6cMF5+4H3s5K4O)%00+@l&j4>ek9Ahrf9=;a0U0S%8~y48ZPj>2yQd+50kjfl%gb)ZQD67=
+t$38aPBNxp@<!J2#6vunzu#INmwwgPLrszsWRSYGpKZj=Li<GV@i{7T$oufH3L<$ZeRs^#!tEE=AaUH
+3^6^cTUlhr*umW_<?i1m=)E+(kp9>)e<<@R<ZKRnI@#d8Kct#TGW(Q(5S-*p=#l3|^TIsi0dZB3Wg!n
+%oq6%ylCy5zBjO#^Yc@UET>&sTErlM|0C@>q?YNR`>M`>WS-4$L0*-X0tPE!X+LjwHk$8@A;u`cSKUN
+IW`8Lc+K*}6CXG_1k4Up=R50wHxk}ppI>S{p8UyvtA>G@JKKz}mxZ2;{eQSMEI#6jigDU`oU)*LIFvj
+IU^-EHI56v9(}2_wW;GXC*p~*BI=()P>X>>oEQuqC;IWH<6_SkP*6S5lwU=FhZM_XGxEx{2M|U2w$@x
+bEcsh#DlpEqCY!8EIy(^f}dR!je>^!ik2>+ygoR9CAm+F=C((b)d2gJalK`O>I<dVa}EejTE7T^ELNA
+p5!ZW*n1=3Ui8dOQjXdrK)p;i_8e4cN^!W%3zWjex~$_GGKg56y?po)@Qot;qk7Hn`s8(F5N19#EYx9
+1EMp)81p><iA|+@hZ93dd8CaaMQSvf{g22f<9Tw7<8*cJqh-HH$AM`Ztm$8yCUykT!sy9!Df}Z2XcdI
+{r6TiMYY8%(8kF_Ydu>+>A}=7T<<AUZ|sHbl<|U{)-m3emHr-86r9w^3Uv&O3PfPMD54zTYdo0>vad;
+wy$MNjO@;ef)v`7#@SL@4M5fp^eC5$!N(}XuKANQPdn2mdgWpd60Z>Z=1QY-O00;maO7>O`#ub8d0RR
+9z0{{RS0001RX>c!Jc4cm4Z*nhkX=7+FaA9X<axQRrosz+BgD?z+?|BM~T|nA+0HjW9d!HtCJ4Y!PiU
+tXa-BrBJo@GzAkPzsq?Xnz@Vt@AU-=wyt2X!o=?FVBSw!8hkyAxYga*up6m8d6%$D!5Dg6UBRQFe+5U
+Q~lNb%j|Wz?~#Xc8U-}wl)?N3=@;PjPS_QjlvYGum(DrOG?<)_fQ(msJQ?KX7KO`&qiYqm_-f_ju^Ch
+)({J_wGFKW(}{38^(<gNU)jJBp=xR9)QDAnEwZ>gjKtUnul~EbeIq2`6NU-gD8#DkumYofn0)E#esU^
+3`<GX@-U8qbzCH)5nqC#4jiWx$F0)zWv(+GF_#;xL$uL%?OtL(*o||Ukf7^AY!tkn(#?ItC9Y^pw-cI
+DFrn$V;6|M6rwQC?HY&MWc*{fDdnRs)*TJvu$k6?Umy?RH<NGwZbt1Hlnk?AmU`*01GV{Q|}Y3AdXmQ
+OJ`?}~WrkT$ROjM=({g|V&X^yds|mWgjrO9KQH00008031s8RyY7YU%LbV07MM{02=@R0B~t=FJE?LZ
+e(wAFLG&PXfJSKY-MzGWiD`el~&ts<2Dd|_g4(m7b;Pd*xl?F1{8ER*rq{&cCnk6A_xfCrYyF)cu6|3
+TlB5p&=2gFbU37LwvwO*5=rFD;h8%#RhLkvCI?w=YGpuwRc4ae)ofcWO<fnd*(%hQFVkf%+`idwWVLQ
+Kzlg6}Q7uITciT;2AHRP3$gh9=c>UAu&o>jN5-;nbR@^9wBBoKjwu^UeZ8DMBP<1{5{E_-bZeso@s#U
+FGC6{?@(nTQ}m^=G1nM{^Nsx^E{5zPpv9R$I9*tiv_Ge{p(S&%Lf(lH85NOC1I;9OSHaL%+SvdD|fTM
+O^Wz<XJl2%3Kn51~8B{;XQeof;%wzYo6_MjBDJCsf;VA=KOgg>ZH?a7YKMgxRWUu*pvPXWcuThp>N^^
+^-q{umf^a(7}#-mJkO4dPPB-eHV%^_Tv==BX(^D+~NCc;v=DMG~8a|mRY+@k(bp<?1E^x`1$6;;S$++
+u!vDAL=yN^I@nyM8zbu~$$~!%QL%m?!oPgb4^(ow&I|lA$(`DYQ8@nFRvVe^lR#O)9zfVR$VSGR<#Q8
+1Kw#{JN{tv2nGfx;{)yAoimUo*=qLNrMlr$-qoX|~Hi{AG$fgY+3m||Kn7)mGQX!!nV2d>=CFI`NhL)
+@Kf}J?1@Bl14Om@=+`Wv{*CH5i>x-P|2o?`Y?BFp4bipoG*t)LQOrNOo+Y)qu|ecQ8GneMdwLnPCS*_
+*H}5Nv(RykF>Z7%Oio9enBhi5=qybQYvO29&jF+hmO8SJv9VvZxV$?@kgLW!4fC+o{D}62Dh#Jq(uvW
+}|%OfH{m3SPvDNuWb&fv|0<efGe0?UiOeblP?dztub(Gqiq`^k<^Z(ZR(y}&)8mMR?`U9N{9-di()IL
+O_OV7xSb-nO2edC#IEPk(r)yUH10LTj<gL<tHD=Nn-qJm%g?S;W<{Nvp<&4N24{=O1vFY<>LyNc-xP1
+o%$qZF=FE^^d$KQxLls_%v_d&%y#c3$62kd8%nl_{h-A)4X0S_#+QZ0~DB)NPWGo>Rac(|y{0@$wLLr
+YImo#JSayoMaiF1fGYFW|$5U#G^yYNWs6yBhKqvxL^GKl@|?K@{!i%oppV+=j)0$j?9lXKBLd}oxs?5
+LH75&SOp$#E(i^@<j7LYD~6tF#oHLy|zid70ui59YR!Y*e}~(>YW%CdH$0dFw}uJ9e+TTgUL8b8E28F
+8p-+U$gT$;Y!!tWV?2sQS<T(O$Ge|fEMf0Ho*2CMxQS!98YSJcK0UY`=Q>=2bJjW5uPmGCk9b%+9z$!
+I~!_8em-UlWrHo@#-aC~`NOcBb7AKobr`~kZ4;0E>KS}H5Vn(X-?l<_5qb54IoOEqI#EwG#wo#{<jUk
+DDntjF?BE=Z<VU3ol-{E>^L$TXdR%Rk!nUQ_cG~t*Ou;xWG&eO3%shf3f@ys5jK1w*wtvlD(6==^MK+
+!cHmmRjNI$s|?_hSTDHb?R7|XbMTllwesONxYEl~Tmn7stFm!eoTDb9j_|M@$JTnf9pNkadlhI`_l;W
+63(DK79P!F+FO3NmT3mWBQGc%yLmu%=8HV*dwFO9KQH00008031s8RwiW1Ht`7n08S|Y02u%P0B~t=F
+JE?LZe(wAFLG&PXfJSKZe?sPaCz-o-ILq45r5ZTfwB)JZCZ&ve$tel*uHC$wzf0QWjY=AhM^?rgqR{Z
+B$T^Lr~i9*@j+lg@J@I2v@hj@L;{P&V)wTn0J-bi1CzI%Xs(zzbZsx$#ovE8FW-K5{`N25zyCI8A37=
+8rm7c<9nvnVT3j`j_BB4d<8t3_P4~LJv7H}3{Ph0p{48g0+8fim;dMROetalv-k82$j@_-~z3u(8eta
+ixgrzv}YB=`XQoPfT2j0k>nZB~;&6fAoy5@r!)m7WAx4a+pV{UKG1TYw2iI#rgSIE-R|EM2rr@XC40e
+-}XT>o9%cHGcNelw1~fcsqiDuRXBQT?tK3@)P_kfC+l-|ENQ-e^M%Ir}&+5qa9@k9;`Ra<N!!>S`EZb
+q%jmUx}HXD@l^q%ueOB#pJ${Y};4Y1FP7&?V+7jeS2)SOvnL8NKnJDTqrK*H`Sr5xn_yit5>fq*Jam>
+My6VV<U6o(o3p>QeZBo%l4W}Q>;7tRgFP`)y1Hz|qSChOU-(8YM-B+P6mXWa*5Fl*e1m9g23a*5yF$J
+b4Ikivv$}0Rvv#NM&5F~3bGGXFZuN83bugc}DS`LTZYI3W_^twF1D6(OUK*r3qM_RHQpvP#+nNY<CI+
+<v?A`3EzS@9+1|wYC`~iN&(ACu~Ya4bgnr#afsrgm4xn)3k5Woi7<(@t1s{vY`uw9FWAyQrRNAASoH(
+dpGoC@>(PEjfibZ9T&T-R)nJ(rt3GTPxYb{iuQJzR^e+yg`C@2|xG(3P6OnzKRt#<!Y-v<x(Y?hsVFR
+|@kJF)v`a?lRWWvZfZMur|v*qwJHWZFu721V@yo&ZEiiW~r3GQX3~f0roEmSKDJKfwdB!a(xd>@xMCC
+_Su$8g6=&RS9^KV9ES7}lh`=vW|>6DOMfOyZ-Rt#PCDn;-ZDV6TCZe+#PddZ1xj|Pq}VuOoWm}MNg>g
+25Jtgvfvx{k)q}wj1UVgNz};C{iblw?OdZU4y~`ufXT=g4ev;geFe?>LiZQW`eNWu263}VslMVfsFb>
+rpP?jp4uKYv_gvkb=%zJP4;kZ7Xvn4*6xrtUDbF|Ntv5q4vhP}{<zME6uUAb(CQz=);quzHnrE(Qd9t
+8YE9F6t+s0>b5(}WMC>DM`Xp5;@Bj*C>N(gYcM_DV5d5hN|Wyi|B-qC{&29r&fq8qkGCL!>KiL$8aDv
+8D$admAUvgFUh+H=D+a5hIkqB$mP;BN(kBX`z7;D#HuI1;GU+)FHFbc%WS-(iH{<w9^Ks!kRxAJ4T|y
+nOsMVZ&dws&^0YKU<iR6=Ay@@9{wLZ9v(dY`|;sq&sUC}sDd?dzKxY~!>StA+dxYCRo6hWKW=2(>w<0
+Ika{%s3!Q#2^EhnCW8WZN9C#>Za?%c3qz%dth5C(jXbTnIJteZ1EbL9Z+pwXJ0jaTZVQ+$NG*qE}!v#
+5e7XAYzQ^qWGF-ba%0Sog_JAJjg9<#srrt8~|_wv?N0cv$Ay1z0vafM4~bu2B$=(~z&U2X3GKcovUWV
+FPsTzRPa&&Muxe6k5KOd|%nHSs8ORoG0(IV{qX3-*fLZA!_q8CjQHMQ9I~K|gFZL^CE8*93VD{z1CrA
+5D_8ge9|6G;Mj^SDmQ|W(83eD`mAF(pgqu>-2dR_>1x*M-+M(y8W!(EwE2F{TMIf{_;Qo*l{OeV06{{
+U|<RFM*@*M4hBkM@epaf4-$099jFL|ngvE6!z?xk-8?+>cAyuVeQEZylWl?B=t4R-2QP`;s0^;n9L6M
+G`tXloyev|>QpBX8<+16i&F9oFR5DLyub8A5Gvm{s=*-7CGK5ss+@`L<Atq9ox>;={W{+^LxYUt4b)}
+r64$3$E|8#D!PwjZv%8oA4D0+FQZc1A7;bk3Ej}?QqtWTkqdk{@JVU&AAGfxANLdI17b~$4eJjREyK}
++DfWmqPg>e=i7&}|0*>QQnlVXh_~Gpi>Mf>kAB1!}4%Y+0GpMN<n2JO(vIn>yGSPnXQIUsgE<Aa;=t4
+R%n*e2cYB!>=_@Jj+2BTo5vPjOPo-Qe=u}Dr!3d1=F}S(R{)|<`@N5frn&#5Isz(8mF{+?}EoSnJG~5
+h;~XhYQWOI9UFEaQ8ho(91tm8WmvkagC@N}A;ce5h>0jc>6E<({ps^y6XruLPppcG7!?$W>#7~<&t_8
+regY)p#cwuz7|H>{3%8pl_G~<8PhB9-Lcj8dP8TB#5?KMcqvkt5!1<R6xGE9CE{Y!@+D!ALzn*-yH+9
+x~Lc}vj&gO@j#8c1%itvJXSR_fjKbCrl63jj*t_IYQ+7x@{`06Y6;tS}EXa(oFUmFilb4o;hrY6Y#SN
+a|zK*Z}mP}sv@bhqNZ^rCH*iv>)u&o^;FWs#B|>HsJ`8c0Y@D}ysC%17mL@f#!?4l$6YG&{RPj=iY2W
+jsmSxbh+lBHo$MG%MS5YTndME#_A=COH;1jUT%$#5^reI?f-Iy_oF9;dqGDH+nhak&%CZ1c|`T;#x>y
+0W0&zQ_T|2&k9c|Cz^(88f%w{W+uf9E<R`Qn0ljg-^w=TLs=H8$r;&B>WlEyTY+vjvjZKqMg$ZE5l1V
+f@HLdX<F<mH#6^r&t2cG75YqrDRded2g~*xv=MmmwaTvh7>Jb3ut!|1n*+Fbe9ZBPrsv4;GO?KEW`KK
+M(qwxPq<_1Fnr37|^m-y&q_6bZ>NeLL#_V{DLUQ)o^3SMu?3b5doZI^x;!Eu?*2{etXB*x4YoRn}H&+
+N=Er(NM;_LKtG0P@E==FW_=dsG7Klu-fCmivrC+<5gGo`Nm))=Xg*4@obx69jWIY4n7WE$C<qp|KfjS
+A{9qrYmQN;lsgwZl#20FpvikJdng~nu0?SouVeM9xyi$%Gqd0H~gpNsu=gjInlb6vOPS~k3wDC<w}J1
+;ofxDVJ%*`9=(<?=~J4c?^b4xM|svgIyueT9w9#w{b3Fmo*~(fj=tC#lJ`lIe}pu?(u)*;WzNhR;LdD
+3PC96E=TgR?JxRmfhg3lFX?o_Q#JEJ~GxDh_FC@IAZaO)=p)M4!H}Q&m-xaU<jq2kScN9&r>dGnyi_A
+DHPmn3Wv=p`1)5!}-*Yjcq&C^h0_2l&F*-dRDJS3&295V+7>LawWY^nnQSM6oX@=%GUERz*uzh_-vT^
+*_w#Anduue?{B@A^VbTX+NFn1<AN(BzB2vkyPL`RjRZ-+_8W@sIR0n@%AbKPDR&8GKb1ycaDJ^v<Pzp
+BKD<ERyTJkQ_g*TGz+m9c^I*41J_{Zr&4`rJ66?GV;`Ai+=-9O9KQH00008031s8R*FdH79}4501S)(
+02%-Q0B~t=FJE?LZe(wAFLG&PXfJSbWps3TE^vA6J#CZQw$b19D-ilas6<x%*5^sDm8Xv5rfw6*W4qI
+N=Bi;RiMpeYB2|*|S-rXc-rdF9f&eATc08RvVJ2q^SO5!Pv2R#_`DR<ytyt{xqRq=@l*`}CswlE$n^!
+hzmA2`!NSh`zNl;)5Q2J+OGMareTG!P^q;;L{g-WF#GM&}0bDvhbvd!v=_*;|J-{s3zzWtCl@V3g<>8
+@y3l)TFRxyxid3@OpYb0XGxR;=LPyh%)|ET=HnW%7pS0Tyjl6^+d;@}+99-EVDEKc?GlUS7PctM~gik
+YPX|QNzR|0neNNd-*JR`sZg)|N8vJ_Y+EbQtsu;)3hkkMUly0-^rfR0LTRM_8btifHW}l_R|&zGA-n<
+*El-mGSj~l(3{;>m;74^;FHmKB=Ozm+iCJHD_2!Lt@GvOw9dA*M*kHgyn^4avIejkjoNyDMwRF}ZQEL
+;jY#k%*;K1tk&Or-xl9{MZNyB#JHEyoY$Bq35sgRL`(?Im#dE6gSzTB4nGkoxwoWfL>6s`ipq6)8?N|
+Dzv}iKbiK#~DB5RW+kX2Qv>6j)(Rc&=Pz9%r(t<K!$%PXCU@5utDUS+0>r8^GgO3r}FUuK1+68w=AS*
+h|a^NY&@{)ag;b-+0O*(NK%x4Z400sTe({4sx@mlOTVYk8BU&92T2A<CbdtknH#v-gI&-@yB5l&@VXl
++&m>A_vT+S)xsuG3h2ql51=_>ldyBoAH-j)8^~_k6C+Jt!(m7Fr(|Dy6&dSo=R$ysX(S9SpFi(<;*A5
+;w>!Q82&lKMKl(79}Ao`*`X+ko?d1+r)!axLIR6xAkk%=rERtn*Liy>Bn?SIoI)8YTW9UAE;*5<<;o%
+LDP+aS1F-qAK@EwHpd`m}anlR(JaTG!0`K`^*JkGcIFIHA{qM6@aW1j0YV3r>MRvtQme;A8w+P}Wu<m
+5AV8r>Hji}*^39fpHxNPX~xB>%hQ|Oea;HTxeuvE)7g-p?2W}0gYta>WB!jt-<IWw~jEs0n)2Ls0H(e
+<lhuc))EBq1i=)VmB3>NW-}TkM)_HIY0*f#7<9DHTf~NuYX(mFgS)dk2{9#RW0%QnVF-7FCNq%uzA{h
+iwGbqF|q<?eY?Vfqx6h#H2hc#WICPn`#5ZO|=1~<xPXH70f2Ev{F2Mxd+NGamf|5a8oQzRU015rWpol
+n$R323A`+;RR%B13MdYEPP)m&Y{sP_z+g_2P(_NxKGR4B8Ekrybz4;&c9g7ko6SDKc2+G465zf}gimc
+o9C@(O1W3*-6(mMARSf1MsE;AlOMF9U&(`xvN$$&o6bJ3oJi&OrsLITreg>d)mMJhBOo=&3jQKRjKfN
+X~IuXc<>2+*tydzXL2<38BfHp(adQIy?u}kO+^er!eTLLvF$p%I>Nkp@(fVGQkdNCERp1u4*+(qIs6q
+vqCbJAp{tTBTE^b6D_s1a(;$|ir875j-<EHIIpRRepjcCD=zw685rX<h9uE^XCYRM_xEQxlCu&scdx*
+%>*z%2W+AzgojJxBFz3H`^lJCzn-qC8g!NwAf{5R;yDY^~`8z=aG_~(Ok{81gw-KJQI;C6e9qO@{6*n
+VF}4P>uP&Obf~o-nVy5pEZgK_m#?xW1h7fpqiS-|UNU@uskxXSR0Be(yf_B60x~;TRrY=h#FYSN?4m;
+pn>5gKXlp`cl<d1B$}C#}g%BwM|J~LZ=%t`q<@It`q*_Nhpt-0aX8Mw<IW4Z!eIuHyd@E4N1wF9@2-F
+9(0#=(sAZu$vOwOt#GnAxFy3RmqYW5RTc0fxTV+E9nO9^Z87&<L?PASAv<r@@cYHU1~aHO}WwCOV4LN
+$<w%D4K#*Z2}_7+ADUry5vS#YzC~XsnSS%C1F`mzM7z=%hEajHj?}OtHRrJnANIfv(!vDM1xGDF>Q&7
+4WfBjMSQ!FtF|3ZNaoM@sjnjo9P!H#93A|=a&y`m)Oj{hQZ_-o7vYe7%j4ydGmqnBAeOQP+c|XG_(5;
++^n(t6M4%F|G3FOAqmcCLR2$D>E{B#l+2>Yrj6Bt!=7!C=jR3LJx~u;GXa6of}Gp|rh8!Fbt@G}GFM1
+a%hJ!k+z_NRa!{1!hJF{BW(=@+)0VWfYgoSpq!pZ-t7U;gARbR^!YGdZQAS1?>C&2($yy7U2&o%abwX
+0(OmQw$uqV=_R`1j4bUq*XT8ph5&?&_lh680@oz@u%KJ-$+a?jqUs0S+d0<CnAtf1#n^NCg$LYg5%AC
+T^1>?j6S|Larqa8#(eqKJPLW5>jpW$Z9P&*iX*bO)*)DDz9CQs78}IG;8uKx<TrKPpf`qex4ESR3D>Q
+V4>c`c%t1qXF0A=bsUgpMOS?2`Z?#D5^zT7|yF*N)6^Cq}8GHq=Cw)$H1Muxzo7L6C28OYu0mYYsYzJ
+HRAxf^*t+*mlGVh%zzaX75s~wqH$}dVYgK~q#|OhI#ja+Bg;xi*n_oN`VukBnN#DB>HB=M+X$5ps48n
+C1G{>W!6F6)c(DM+l&3h`6Qe`m`i8}9Gplmyu+aYbv7|f%AqA<BY3p6N?4SY-faXdn`jJ*?Y4kTLv(f
+s>8f3$0d1Cv!C34)x>-<KRJJhOOYoYn1OtQ4?upgbvbq)G{L%m?Qm%GgZ#04O)@}V$@mTO#}DN3wmwn
+&#(6LIe#_V@4Ib8WexGd1Lv9IEvp7#j2Bk5|jSA+czcM`YNJF=FkI4vSK#zRCc0NgfAu(@#}lEDJUuV
+oYo+U+0;2IVpjJ8kq4u(IQ-19am%J>VyZd=U{sGVVWrJiz)z$!ZRV6$~n5P?kbaX9#lI6`XxTTj;S#J
+5IvK~^pLJ;TJ*Ird<N*8gxx86Cq4spPYpUi|J0yIbx<0TVS4D;PwG)R$NkhH3GOg?Xmc&X<pkC`irWZ
+Rw-k&`%q$nsQD=g|fkD-+9GwO}?a^v~E@e4bp`d00vjDl@qC8NG{##J+{-je!RxXl<6A8^^#t!KC%tK
+<6H%piBw?y$qFG0<G<N%O{n=D~2k|b`jVm%QZ<^cbmh1LcFPgVWF8P~q&uq!0=99R`JByttc90u4AK5
+!vXcTQbQ_?)nyH2A<prNIX+EPMtoE_}kw>fj8L+m+^KY>DR%CZmuL@E4U<G|milOJP8=&7@g#0+JI8I
+_psRn5{c4c`P_vLFW-R`WtGW3=Oy9k>9zlESouE5lkDo>J;bZyKG~l!atGSvOW{g*TKN#dVFIym4eE<
++MN<Ht}$F`+N~+wS*9MVsPK)#xVw$Ubs(0<DowXru%zLomV0K7=GED8Jfwc9mC@w?%6zr&g;ANBEzkw
++amWI0m5*$FZ{@z9h}{i9UaQJc)`W|>^1co<Ufj*Z118JKjg(b#U8jf5nD3-YEv~D2B@h~onP1J9U(J
+_~GGEYX=l9_CZb23bSSkvH6p`zE1s#HF0O4iE=N8f=Y9dSPBJVPRdz>gyStoB_pbO6_m-&qKCRnv=x4
+RZ2Jj4cS&C!jeVfy=sc7!otk|Zzl7PJ)0%~4(HGF7&_(qWw3J=I~M9XAy|Urj<>?+kZ&0rt_P%foo>4
+mS(bZQWqDOvfMQ7g9`yl_4hMI=?)=5%Q3^Y~YY<%Uz#CAdh;>+-1;@9+Isd?R%3D{e{W~%vsV?wZxri
+GI6uHc%3=I)|Zb=KcTW*CeApmxL||GL;<-a2U3d$a|>(HG}H7GL|)05nM*q^C=(nrMm|1}V$m~3IX;k
+Nt}{zBE(l|kGe$1mdWg5p6t#4FW*OCtlMUx6q%bN|!s9H~t!=#7n%OlrO$9kcmi!_fo)lR^l$srm2q2
+_>kZSD+N=~k>29HBUEPSSrn3@!Emyd{Bj8WvQOR#<e%Ao1YxDTf+na-s9aMFZvr@gZ`WNnwu)OYub*d
+UU%F{7ZhDay7aEt}jONITqaduol%_^QNZt_M{mxrK}^>8wazENo<|MK?1+gE3!~hMaUl$C_>0J(#<Z?
+1{I1<_|}Jk{B<G8L(>wf{<o;?(Co^3y0aa+Skzy#gK7|9p9Rm31vNk;*@Q+V9`hliF~V6^>USCRBc-1
+%MQ#q&~NR3aQPQ1Fz7qfqnb9$JWr~!=y)*PQDeWRXtpL!rGCG?MWlN`kvlRY>gj>S+j1ww8aEu#UShb
+oDDN?7PcXl#OyJYj<!dVZ^V9J)7C`!W*xG+HBf}|E%)7gAq5fD03dcwyV=^(MK3%c_pElbfZ%K!aWf&
+)$3|hJO0xc`A4x7!`A~Ru#IgzUiG$<PMuIR`-jI)o8*3ClFF;;bgYWSS!M(%)99FP8^VtEuMw)g9Z*L
+|ZZpXw;9b-HY;djCazI}tZGj7>zhWA^K$T5e6zzV6bA1l!Swe#>~=f&E*{G8Pr&n;4x*IGn@si{^lZI
+0QGQfQ01RS5KZkdwoU$|0=3L9}PGsoF+kh=BOdw5K>h$O`etS@){#Ni*&PCrPg+eqfBPSH;5IEjj&0G
+gd8iv^DI166U~V96!>ubqy|B&a~&asR2D}_CmD3;ut%scWyE%bRe~)@==tSjWBBLhR>SHeCqv;uFZov
+nd_GvfWb%I5M1x?FH^K6<OZew}&Jq0K1o$4*Y+oEqRBVe6A0sH?Z-KjqUP9$I5@w4qd=%VtNprWO<mp
+c@-aL8!;@PX$K*}<VSgnTXRklY4I7)te^77^L7vH<Eu{;pO=zikiXAcx<E|52gWZ<~8PCG}iN%t6kB#
+VRov)H>{-A-`6Wq;mwBgN{l-dH9M@*w7s`Rb?v&(_CjsFFx21yVPQT+qO&iLsLVTBTBlpJdi(^hbMCO
+1jKn0GDDe@)CZ^t#S%`ZtE<Y!l2W*q;0jym)LG<eNa>5>w(E6EYE~gDb!%m{zE9E+GeHXEuD;IQ8igG
+hZNFI8Xos?JqnZzBcljElx0JO1NqC#yjay)$?SGqo#zpbRW#Rb5!2}=+om-Pj_n`_8?{ioIWVDC-@~(
+LNn2e3>mX&Eh*X~gJGbIU&Cd5Ks8z@!q+3wv98Owy@18UnGbI6))B!k@Z#v;s&!)Do0t;fDNQEx12f9
+DRpbP15cd@oCL3vO{eOFXrmWNJd=L|3l6*#BiF$Rs_5AU`~6v$KSlsUgQpYkd8ckpcKXcBq3{rh`3^V
+AA1)guEGz><Impr%F+$4M5Uwbl!2TOpKux(NWWweFd(2Pd0Yfn7>V<mSp&P}|`Y(`tOB<Z9>6Qw$q&g
+#tcCFrf2WdCk_j3X&ndSmc{r?+)VQ?hxX`8`j}TuQ3h1Yj#J3S|E44w1*}rY}WaEz<jrcf5+}dOlSYc
++hk!Vd52r@@ejBVugADm;O%l(RGpuLenM-iUJ$@|)a5z{tE97y!C6jQwP|7fjC>5Nevb?b3C@tMLxV2
+9PK963%n8hxz&$^R1OAxLv`0lwRBR{F23kmi9GI|*uOMQ9pFFx2M6&WlMA7tZl`E#<^vbi}OflPz9R0
+4jZ_H`!PXFfKB)q55>zKDr00(o56vHMh9ngU|rR}g2efankZvB_Nn{YB)kvUc9Y!-cU&!z5z8`Q5cl@
+975P}93BjnB}XI*KO`?_eEXM>vq;iByl2$6WQYs`HB+8Zr?CY`D!k8T~Ll=gALvlmf?oCZ`*uP+e6r3
+V%Fz3M6HPyD28^`Vx;Z>6||Z?Qdv0Ye+fKDeGK;&$}xJ)2CKtHlmTGXRBZ&5gTjTNmXSWUTjEZ92Oi7
+ZsN>z>T7X-u25G<#EeG9UN@->i0F~KJeAt@k5aEs(5rpVj2ye*LWKe$wV7s*>CL((A`7``YBgh!gBb>
+M*=-;y9yyw%n*PB0MH*p+Q44iSlGD*uilqeUBm&j68HIRs)oMM-e%k@<n$rIWR^B$N+r8mo%;+-gvPZ
+V&O!#$dE=P@3^T6HjD<{sBXw~FcW$mC|aFP-LjS-rz4semb10iNZjp?cY2X#jW==uqbc4=p13<Pf^9O
+aR>-%C}hLBKnxqH%-c)E!YiWPE%W(tMoQc&eqSI95j%x%P`Da%Wr>2etzXHg>vNAs02)Kt(4hav0fbx
+ip=TrM}H<7rFz`+jl$Iy0}dVRbt4A+dY&KHmmeuDyUuRsglEcTn{I9wvKL`s&4I1qc^KGYu4NbHeqZZ
+X7;sjAI8_Jdypm^JFQQ`ZL!0EI9|!2VFq%J;J>eeyY2F*c(qO{LWf#+>@{2j?m8!<%uz3qUrnrSWG)2
+h6zqs}J>q1cN5r2vGUSn`3c@yx8o-|UmfU})N7|o4(g6sygVWm`-oS<&F^8E!(ucsInBgBI<#|UB#c5
+0Gu>0^fEzoUCKFq#zYac+jraOl3x%t!?%B5LnJaM1`ue}1kS*!RYtkMnz-`*JJtX_%V0O@@B<!y9ep?
+N+-{hZjw4I2)9>T!JA-L|w>fUwIOj`%_w*BOe}T2u|HbXQri$Ivi)ydIc5=5MQ}$?+IA&3Pr3b-Hd@6
+*9h7-rqzVpQH_uUfz^nwoauJvDnEiY;&0hZUAE_Twd;)<qpr1UFv%wsJctMa-c-nu`BTsk5Xz##lHVK
+5*fJr<}zbJwlM7N;9DW==(r;y?}ad?vU_;QIoYXhf1!g3+|Mi1BY9~4*vZa2;@b>6{w}Nc_Ra-y7ty>
+Xs~#6Ov_MGHJx=ffhIcC^BS*fg9a!zJ=Mbtqd#dKqWa<03)X7vyf^D4wijCqAeyHDPJ@l!9%$URbjY3
+aPD|SiW9YDv$vTR5o_)mtG7Mbbt>i=czF3UaznV})QLt}Z5G#y^;L>j~#&=ON;*MS6VgX$2Sa+=|dFf
+urwd?_9OiDm#s7_}9<2uJhbu3rZ4hvL2kbxD*yu?{>ET5kb|46j{jx^90jAVE)a-|0NM11q?F6)*NJj
+xba(9(!d_8N)p#<!kGN3wC{Zk|toZX13tnP(gg~o)#K{845@Eb$(_c=U>#fU*DJt56WDJ?FMSsv(dS4
+qQi9Y4h|aZgLSQ=Kj7P4f)qFCXQ0<H;QQD!X>~zK9PeQ0p)X0kYR>RZKh3ph8&`S|cFkp?!0?=$EieV
+^NrHf;8-}Q}P4$j@H4RhNlsFN->tP}kFIAzu9p;G-(B9wE;)=^fxlq?RXeQSGp@%9*%<`2x<oR0Xfxg
+a1!Wr#5uv(Y9y21HaWi2$7twQ=0A{g6Er&%<ePNT7l21Z}tR<yoH%{5?X<B#_H$kD=PE(P^vl>~!eJ*
+R|Beaz!zO-*L&k2ZEw5G=8Ivy8#m(ehFXnk5z?f*~XGxjRV2D{8umz*ZP?+<6NgAhqBQyXnwR2n!eB$
+mn|5zY7E=tTMpN#hx%yP_VZI)NKG~vgqMWCKQmM6Z+eH`jLi-#Uuzw`;fd-4~BH=NMAmz<(`d2TOk0R
+-<x|t{X2xFm?b-p8?Mu<jKT-#qC$R=XNb{(ike<$msS4Y;iKewwSIeDyv<tt0sq7ADu3Io)|*ZFew#n
+~-GjbB%6^qLj1u!X;$veW<cT<@>baMhIv!Gd)JA5fg#iKs3LcEe2!>kpoXhNBkJ10~o;O=zd{`R!71L
+E|yqjJtz1!<tti+NFcP0G=UCrefD=xlB7ZNH`x8rrH0479^{HBdVT#q5zQ8VOSH}d*JHBRcr9C*XzBy
+rC~qx~9WdB(Lk!}~G2xnxD+!q#9@nKBBIf+q%g`K20_{-v!vnO%_un#7Im`Yi~s$5D8HzJK{2te)2%L
+-pf8_5D?!+Ovb4+<F(g-4+2~Cx4h@X%;;`2COD_re6+&lVb@rqQhXu&o+w=Vf(RjH+%q{i9Kcf#-Dxs
+!h>QxxJr$&{##twJzN!^4^nFMGg!LgBi*oSf~+cSG#-pLm)hUg;(mWzjawDDAdySr-PHq&=&b`N2Ct`
+-a{S#hKk$e@k`>0bhW;)cCTSNBXY6RAe(8}r(vdLoN7rFL-+ml1Rw=g-IxDnq)tS|HJ`V#NSYK|Zm`&
+)3cTz$_0i;HsIjAZfRUP_e?l5`FZrny<30%VM#Q?GVpc*$&cJ~X;uoChCLUa&+cX@kX+Xq<pU><)0e?
+P+8$G*~pk1=`art;V|aC_Tw&E1Jr^}8o0<VlHOJ@bB!gxC7D($$NH0Hv2)Q5>!Tc|EM-Ve39*abvN(J
+WPH3QItCMw~#|m&?X5z^75q4wgNSTq;i;_;&X!EEA-%%>809|fp&{UmbY{hW^q_H=|@_uu|aqu8|T|0
+2eCgYd^!ycg2l&TG`Pr-`;dYy$ZN*eVyS35HmPGNJzjV_w0%#{BDC67EC*O!ibfWgZg%XdU3}3VR==E
+DPEZ57Y!*GIPF?B-qwz1Gc&Gswta_ZNc7&BR9Q&a~hH7e`LAmJ_KzR0tt1MPTe5`ijV&$Eh>3Axn(h}
+awKwobdzN6%LFyYT=umG%IUM+G4VUQN{Ni>)bB$|)XS_Ww>1GSYSnhG5tI6~I}0``(DS0&l+vd=IdmM
+1Z)+LmBSElx50oO%ay2!k-A>tS$?E+A_qWnduB3o|fV&#^+snB)g=y8x#<-Q;nDVx+}$?As+LFZ2Q4O
+AbG5W#19cF~H-?cbSH!-8Ve0Ay2kr^heX?MImp!#Y`EoEJZ%<ACs@Tm0$D0c>0eO44ymjm{}U;EFb8k
+JsJ6vU1pz>DH*PF%n{%(NT$A#!%C_}F25l<OB*^rKgM$?n|{6R6X-;zd80l%W8m4x`NGjNy#8jZiPVv
+M%J?-M3qNe<Ro?3F)YCIxZ0p*E4?-`1JzR~Bvn&UK2mA8KO?49tkcm9FeXentt8>MjUVfa4V&k2Go7^
+xwZaob}1rH!9_WqhL*xtTL9gG2s(it;dHr(>5T<jF)#3th?Tj~w7?V|PJI+M=<hO^||CLvzL!hbv<Y?
+`3x8lU%QD4Ak+`MDnb^sia}Hi5pV2DEN9X83~`sAiktB5NMa*SoXY-wJ(hG`4B(L5om%<TNxUn)B0m6
+X(xhjL3t<Dm-AOf1<sMFx%G)2a-;)pw(>8x&-i{wk|#gb}w<5q+^dw`KO&~TRod=nRwD<n^O#(S(a6O
+)@l9)=c;#<rHO8Mz~M8!tTA7tfEW>9-*9$ftHS$Ii0jd@%Tq02sm{^gJ}1aY_K9~q=L2Pwdw6En=M}N
+v5aNZL4?zaZB~w7f+|enl5kuFKoW3|r*psazuOtPEdl!)TvEpCZFz@cMXv*ln?)5+I(?TZbH;ST{@`D
+_EC+c^xS5>I5inf)#b(byz&fD&3L>iLQg4J!DvNNuJ81{ErljG$8o9^LmhI9Y<?$a(Ghr&lLAOAI){!
+>NM2QSF>hJ?U}Hh=m}*+4`WX^r11Z7Aeke`i!tbngj$FMMB}%vYz9_VU8&yL31Y=`?H1b?X&B%hQR}5
+2=-gjUgjuf>-l9b~Ulf!xeyg3Z}CzxlX`8NYV4*iO>fotT$S5S9x$<AM+;0-o0bOUf*c1ZFH_`bZ*KF
+eyC!^o9rH$C#KH6+tbU>2Y-Yvd_T7RXyJbvmv=rO_XPV1d^*REg^M+;YNAA3Vx2F^oyNn%pPe}AD{~I
+x!B5N$_;SL31rKgM<L3ydYXiPVuq)|;p-dei81PY#kNwUBE}&oJO9wh|LSNJ^V-xHbfM~bdemv}jIcl
+vxrN#?)KLHl{NLTMQwMV}8GvEt9N5ASb_)A0sKKWxVt#-exi4VJIx~bN!yrkN)Ks<Jd0!(c%ps5z=4}
+3?#@4~C^)zKEgw>92b^vVfKQTGzd(Dd*zYJBdC->~~>@KF*WqLaGUxFLa`M^!?Wt|4pp^j%2xIjt9HW
+W2FoXqPCxZmZ?hU$YD$|5oO0Y{9r3hC~u}4DDuF=Q3j6$pA9K`%hqaQ|o%hqhuFVy>~&82W8idIt_#|
+M(PZeFy9X+M?2npAv4aSbybnn`mIdBm9Fn^#fS3Ggd6g7-<|#F&skAa;_p>mtiI^%4B%%8?>~6xCO&-
+daQfh3=L5ixAoanc={+~~=C>2^KNIo46A|B^hzAq#a3UUo3Hi;fg=0a7(ITw@U3TZGDs{`~kYCyhz<g
+w!w($hOMBGHn8dQD|?l24ye%}ahv5xA?9kjK;*ToJ$0!7!D?k?z5K?Jk4tE2gCXc<IHd8ur4rZ1y)oA
+txXbgO<wRj1`eFlU<~CVu+WZu8Gw+MbxT+SPel;zbxRp>F;>*hhKwCUh}YXY**u%g`tWW)1b|%wIY#m
+A&4k^%Z@+`P({g^X5{#-jewIdrHIaLO+Gc0U>~LsgYpU0kC`1-*w7`pw1)QeM~p$zo4EkaDMSOz}0w}
+z!%Xx$nGM^ouFfuP3f=5-I~>=R-p1k$C%`Q^Dpp0!GoXoB+;Y4H816m5<gh~q{I8=)G(Ry;NE!5dD@#
+xR6bATu$rF|clgKq`-}63-~9f!zkl%XcN@(s)NNB7L24_;;HiHDP)h>@6aWAK2ml;P_EwwIWPV{T002
+7a000~S003}la4%nWWo~3|axZdeV`wjMa&KpHWpi^baCz;0?Q$DOlHh+nMGqVoYG^=+v}Z3a7~5XUl1
+Ix~%XUbbb?h-1U=wJNZ35kx?uIC=LKksQaqn>#aS{7>?@jJWE<frc>!SfsqCB2GB5bj{t19a&D=RZAG
+pk&#>ZVJ|`k>^ecGK#|ZnG+@EB$txHx<0L2lJ+0Ci&$wQ3+4KeKvykwrlcfw=BBrdd7LC^<q&>yRxoY
+op)CJWnFOUEbsE^B5&Kmrs_|lWL_4FnaNmm<+9MZ@Of4&x}1~CS|_~9Z%=>xHgAhj^5?2uukd3r`*Bq
+?IW~f`FZ1qN7nm01LVaE4EBzIp`D;x@>qe(6it4Jno?Mqzr!ttP{{&#aFK?jgw#!v&cij~E48}}n`tE
+H}b))3f_x1E<l)Ry2m36bS!|(<MvbfBrH*espNf&U^g9Lt0tIdcWzAdY~*_{5!Z_o0@BEMV|>aDK2;$
+8PLukx#+;cw4z64YZk?fB_MQ58)&<(JbAI&NTmU$!dK4>=6|oApYk{7~Ft8~NqO6^?Sg;J4RUNi|hzZ
+=emjfug)Ej8FfZs|NnL0zjjK;lV*UM}!=|Et(cSP0DIsCtqht`qe1;FT)ec92uYQOKkt*pjfnp$h0a~
+;|WZ`tZv3!U;@o5s#apCDw`x<B&#OBTIMH7RRbzR6ApMT#yab~Toi5juQ2CVMK_rOkb0r!YpmXM)@S@
+WN?tVedNoS^v~Ig{zIjQj1uy~{#UpN~e0*JAT`%B&XpaW-kM@(w^vim+5gGo(uP@7YrNZ~|qI_G}&b`
+&pS51A@6m2`X%uVT^)VFVQ4Zej@sx0`|{HhbXjqTxUd=ahhus62*i}kVsl*f-c1B|`Fcz7PszXajnP2
+S#|K2I`@VCjIr3`Pm8J-`dyQcQ$w3VYIl{62tuFN*FBkPE#gAgg{nJ39v|v#9g#{NUhVatcX|6JrBxa
+yl4k%r%P)fF2NyN+!5YZ+I1_{70eWU@&;9R)5mf2~d%;o|RLmd6TSHNY4^I{A0*_K!s+-JedH7m)&HN
+w#8yTGMP>i(=ljK2SYI_XYkPs3Im;RMJL=X)fW6AG&AAQQT^y<P;hY|_{mLn>VQnnyPI`ZS2)x}?$Y6
+bn>ekPu>OHCLyjYxv<5)waBN0kXh)@4S2Q5Q<nZg{2Y_vRX4@>gV3PCM+Z<?+PBw$CzMFi0-@*=?tT6
+Ss)?<CR&C5;~#vvHv2b+2g<N|0(NBL3*x|l2cN$~ENIoW_Xdae0gX3M%D#b~5zlt!YSLl4q0C>-?Lwk
+eKhYWz|;F`~-M?bs-3ia8X!&fYZZVknmcAW_k%H9;sakSlNCp*d{74I-WX*c9EmsVL0>`i`*7DLXQ6#
+k=VQx8xJEshuHJI78;*yLZ!qKAxYu1>WWhk>AbgfxeW0<!-MsMljuCRa?mZ(f42KvceT}fSp4=?1p>R
+s!jNWx70JeDW6F?33O2J_wIMqm|4+Io06J)0^Cglb3gdGZf=lPj>iMe)YYBSeWt8P!J)~VC0}>-M9uO
+^a#`04q}+{WMbwTdV5m*gg#x{U4I6O6fcRq$+dL=YK8)<41QODF7ochpuEa@OKr1u>g<Qu+oQHP06T8
+RZ5Wv1U#%UYq<})Tw`ts@wD*qhlTzg&2dh_cHD*tK?z3k0QsVZk|Ge9~uK34Ntwm2ZM@oTT^+ey1BfO
+@zSL<kwj60_yeqBMI;a=A%}mFkc&L-r}j4L*)}DL!qkT8ZJDn56NFh9}8Wk!cAmRHC^2WB{!BV3=&`b
+#e=%hPy6TUQpFzQ;9(4Bn4z10h7;|0^pyE#ClGf3k^w9A+Lfvx#=8?Ib@&b>qXaMie3=|Ta{W8DNTS=
+&l^lhs`c^`Mg=NryJFQEcuCo!q><{b4lPKzgpw3z$btJ5l0m*Hry8k8da|*J^SXg?%XM0k&yjH~^69m
+nsJe0*fm1KKV;5dn^Rq<(Y-D$B8Jh&g5Q(fiOoVF|rsk4U!yikSDiMm^Hqb(Nu+5tS?e9=z!p#Blo7`
+muI{=}W-2wasuI2>l_`%Epl8qKwwM6BCYV}At{X!X}S-PV|eLFs~buw$5nsw@QjK1P@5MboLk&aw}WK
+hjKtTIGKj+rDh`_*Ch?GSMt+GMM7>C^6Na#NzG4nxmu9fGFqt^hM5DFIk*1Uyqf3)^MsB8%`Pv}d_q(
+!?ieS*dw%hskBp-4;caAj3`-C{AYRRtp4G&=s}L!lm(Cr9h6=BHtjc85YUniy^!b2(OU@aU!sML{?yV
+R*$;mrmAl}EVPUE6>&a-!1mDZ<Y~nO09%PG0T2dwnKi90dh^J(5m}}r)`56}8iF$;qp-9$z-`ttSZ63
+maY{NkGb14A@%eisxbn+~!SEcrEQvPC^vT&dvq`cQW0K`(wnqDeKagov?Ez~`2$<2oqae{;ZkhWUW_O
+oO=Dvp6#R|y8vzu|~zM|CU4s~kLC$o=!F~IXz#WF8Zi>JyJi+t5W>u#@$YNFf99Jnn!6k{!fNZkZGo{
+!Z`jH3HhCSOMW7LcjGqj0~;%#%&jj9#W6Mq9{z7TE!SplId}e`@(=>aXI$8Ov|W?%ImtrpN|0luEIrv
+01R*`lr{<h!<`~|BfU|XX4ot<+Hd9Ds&L9Km-E8S*SjZqC)5*8p;K088|^|V{2!U<<hcy1YAvl1eVkm
+*smVlM32mLomVsDDqU@)L>fnp;fU}j39B*$S}bZ<3>s!2Ec6LTTmZ82!$)X9l={QdS%}u4=qp~`j1x+
+lX|8&Q7|WCAORx-gY)kwH6=rFuQb*J;y&=-Lbh2v%kU^IPFE_v(+ER;>6jGQg6=OV%<A+ucS=Gfz>rO
+Ic%n{l!m=yfVP5K4^!HVrRrh$wVqIrPN(LQMevVB7(b5+}-!0^UPDzs7g#jpZN>$=T8l`9acz_713%X
+(H=a3Dl&g@(ENAXWMD4v;Xn&<euhL0Wx>j+r82blRf0xg!`;M1VmFWe+eORUp+d>w57Z;RI(F@bvIFh
+QybPdU~TZf}%$$7X3(6CYT{E(`UDt(6U-J^-`;ouz`8g<eO2lES7b%d0Q5@BRW7sX+8NOVY*XZRdrLG
+RrTSz!Y{K!fI1?{yeVhJxv9R2bdM^&90t$;M;n9#%Wigl_uf}Qrz^L^xSn^-P0*;YON#XPy<+GeKXJQ
+gknBaPx`F4GUN?wwr@oxK)UxeqbDLh%3Cx`v-L97@;6)0JA8`%Cc>7!10p1~cRR4H1=<m(0&Re!$Z#G
+Vv-K~+caA|@XvwA*n3m&ymf^72CV8T&Ik5{!nZUl;f=<<Do=j+R*vK#;hg9YDgle=QE*ng9t+#dBZ$c
+_TxCITieLGp?ntfvDiKk(R6b@ZINN6=@J)ANx&ZN?YLr>?tlQFfbzp@1~2Sgst!1UfK8O~7Rh40*1ZT
+F3z}pKzYWa88oRX&<MulX0{lAPc{2W&I|nJvD4QzEHI|jN#ur6DT@ful)6CJIsC4ofzrXja23O=;OA@
+R}<ubco^`>7f6&=w$#$(<NiaAS8Tmu4>=xAFn*mAjGhw;!Xb~E=*hLm5IAeRJ+pA06B;NnmxNywa;*x
+E%DE>IR3K#@ht3GJbq~IsTM-+XoHwW&Mw=p_R;VkZvZOoCXQM<ZMi<550*WW~<uApwL$%r^fgo1eJ26
+0AWEVLk;4Uf1zrulr!v4X->BGb6!^7#r9Zw%V;W!{r+xJqu<f&ncmYm2+No=R(h!j8apu7Jq=<c7_w-
+qe@nd;6SD*6XSyivp}hTk&bW6SU1Kl`cJhYA+))sCQ|!D^8Jxyo;pQ6LKTIB~>g)~lkD9H!tD1`ewL(
+gh3G+z;ICb#7&6dNydf0k9PIb)dQM%k_K?LQ-{QWp+*gA+ny)cf%uMWe!hRG)>*K+j3OJEsERQvOJF4
+_CRagd=Jd?-zM|SwylbFUV+H{c@W;>_T}IKw;yo(uOS#J?7n~Med$u~keFjXn!y9wKcM|*L3_r>KI9+
+uko<d9myr77ub?i$H_~}1xb%+ZS}py-b#CeyCqGt;jkXtUX-Ouyda+Jiwic{eq(&2ia<ch|er{cHwNW
+*V@U$Q~nXjwq$wgU@vDOO<OfT$EH-k`3s%kYJ5G2NF3|ddJ9dv6~Ekqi6>cBKsq&v+=sdiSV`We8ES`
+>MSSL47nwW%WQ?#{SMuoD{ltwyu1J}h~O=D?SvDS2DY*i=rBq(p3W0%BA-tUVx<EZd|e4SYx9#1I}Qc
+trQ0Y<p0)Jt*7$Ln_<ukwmMl@j-o;JgDy;)OUNS@2n)o^Cz2)ODZF7A!N)l^E3)pai$+c5-~TK;&FU-
+CR2aKhzTuXZ0mOncEzObrBe({hPc!rS=^5(37(sCV@u(gdO!X4nYEa}BY9;k!G!s?oWV?LS_S0EAeth
+9);?mHzq7Ji+;6Yfkb+FzCXA+zc!wW!>AoZXi7ZX#w)WM_*%-h0$rPBE;)DVgoGD{rjwEoVTsvGJdJ+
+lWfAHWbb81hZ?CCQt3DGudzQO&p-GVWF0i&LCR}@to;S>;Wak(xRGvWtZ&Owu4*O{>XbcP0IR8tW-6X
+=#AW&*9J$rF4)ZF7ggX(I~GxMy#OQTWMlZ!BdI6GTlxzEJ})e8pAy7R4#tCalA+D+kirL9RE&<_yWPL
+;=T*j_IOgs-T{$yy4vys_=jZJ1Kv3x`(Dp-8EaSn<j(kFkP%?O4<?bb8^_H>jsK2(Ni|xV@(8w9g4Ox
+6RQRJWpv|4Y$59-e4+9^zSmu|37xTt3GMRbY9yPU^&tKk!7qiOBmN4q#!3FE*nEeyEv$sJUQP)U5kvm
+UxouAJ`>?}bJEIkr$DhI-+wcQ{;eP-43pt|uCV9O*N0vr5LylWuFXcDm8!tW$eq$3!YRKK!((CJb4U0
+OqVi@I_&?*{k0jUM;5_M?;r`A3?uvTr+0966-&1DI#Z#F75s)dmYz-_oII93~x)#a{><*M7@nn5j}%W
+rP+01@C$ydgtn)?k!8-gC#`z0}(-9PAPEYBKqeBV<*Xe32m~K5E`wV?2vtYL-=Wlzpd|{EG7Ak&3bM2
+xhue!e-PxnzK#N3O*E7FftFh603kM7M3eN&FZcl+(~$~Ks`{_bdQrISoUNLoi1Nf!W<T2-Sk2}9v?-7
+QxcR?9V5n-(=ds4TawOb4+0{si+b%&2K(c7bo7lvoCb5`4yHhEGpck35DeGI9WJ4x9t)1z>Hmp|k%JH
+u$BSx@^)-qvFpV;qM&ML-cI3!tiE=U||3VjxJ5iY@17f?!sE3;@^X6u~N}cR(xRDZlR<v@*%{ZbRJ=o
+IRQSu}%YT?Hai5A!aH57ZJMVNH&SP|i?aYG^o6l58*rna$Z0WqPq$#|e<y(p3u@K(U39WIlmoL-L&;2
+0!DNh00!2mn_?+4m<XW<2hPs7OZeE^9#c)msanxV1zVO}MW7bwbRM&JivP**D2_2~KwySuJXxqYCxrC
+Ui(UcQ(Q8BaFNGkz$DniwORTiX4?yunxqU`Gw=EowxzkFyo?_cOoNGp~#^n{zT+8v2aE3HJ6}LtM5R6
+d*ou#aTG}Go13k-iz>lGY+9BXkDZ&uLjY;~;3mr8bD12Fk07Z+kge(o+HA3l`QD2LanBBx-eCMe8}lD
+R@XQr0tQ1GH?n-A2E!d#UenTtYjO9p=b0%lQRuxKEqJobFs@pFSGo%zE)jp^0{u*1_RzKUfvYBeNu)(
+}7+jYKhkFsLiDtw>ZmNPsUc8m-h!u>O4z_Yx(K_nrG8Wj%n^<t4wahHhy;o;onH*)TBCz5WEA+$L8!_
+jv7?%8C7v$NYSBOL18wi({g?Xb_FRsQK4fL$}09kRX2xrelwH%>jwy3Xu=a5GCB%H*(oP8nRpBJ~xmt
+vnvXwXL+?yhez>i6~eFK$pv6b^kJdmmYCD#`I-q_$wW8$7=nExpEl*iJ3D8nhmPx=BDY*2%e_z76YI*
+TN6S%9(h?jXf!REQALs;VKH;_7^MK8`FNb5n>W~^qCK66Y}?M~ytBCo4n}$-Ge=M8tivfDy?w{QZ1&v
+BNbjrS-?$9wU3d}J1m1?wbO!ZJYnUxFPXVnx2A*e|KB;n&1JIxpYPbx5LULj<28Sny_}@S?8dkDWFb0
++(ph()-JRMa#RdKK~pwK!%Q0S>m6#;jiQkmhln#>%9af_@_VJC>k6ID27jpwxDi)LDYTyYhT9w@ozKs
+)wF{!V+G0b`ED+?~!IklU>4eB6FG`TDEz(fq@IlHvYr117-cihBB*19K{J!L+WcNI<W_oz->qx?8P1Y
+aAAoEF{HZCaD*R+SjUazH%DVC6Y)b%<)*B2(2)_t4Mpx>3z}4@F#_iG%9yFa76;b%2%reS>?t0k1IyZ
+m6T3Wf3tQ+f!hAeXyw;!u?_M^1agZ{yD*>nB=H&fmAj#I6qbw926CwV{9BjK-ARm@Bn$SfSAh2@K-NE
+$9)D-iClk%+XS4!IQ&p0Q=jg^B?zvh7Re#+?o{^0IxJhC@GV$zY>SYL>-5mdXL%T)voQ?-0oi5su){c
+6I`0*{8_k0dz$g8iic97B%@D4}Yw4Ld*z8#0wZ;a|bavrWvzPV{}9VPOI-0+=ye`M3Q$R_svHQ*0qUC
+-y`JL3QOE`#x^oZd_@agtZSno+uoWylxA0t}vE-Gl%0KaP+7{eS7F|NGznw|)FKlm2i2{yzujZt3Hrq
+a%q6`U&p@u`7c9KB2}(Ig<I{y)AGuKAwMg&t3Qc6aJ*#H8>x|0|sJ(F%0mQbad9lVWL8Bmr>*{qmqHx
+diUVPRT)N<$NeNJ-fF8gj_Dt5#aajVpnkJs{jut|nAzYi>7{@c!eFC)5egEGE*@o#Q83Ga=!6W3B8)F
+zp1gjo&Q2Y09Euu4@m!-BLX}+C>t?H&cQm4Cf6Y>EQVr1Lu=fBr#u<IV?j6R8`?e(ecWd9hY6`rKBKf
+84v=UodxL|nnzuTY5QX?AU4tfWnFY_my-0F$Vbc5XF_*`W1=6z0G&K8;3Vy?g6_4fctt3xEiecCbWa)
+j=X7jlkawb;6ip!o3dd15-UqXLs}a3H%I(&Bygc=~r308-k8-FgDj64*#;3Y};Z2$TqZU0)<<eL6$uk
+L#{mwI@%WT$SDR`V!$h>HacP|6DHW%O}gcg=NPd+HN*p*<-3@S*^Q*e2+-)0HZZ4-!AJJdH|)SJHt`(
+pN}jdMM4B+RAF1jK*P)dKItB6t386^4iN8Re8mZH6AIqR(U-FiC+}4g>1`W|ctE%s1h5TUoT1T>{Ao~
+|#~*=jdkuWsp8JM9r7#TNC+ohD;j)08b<DgN)FL^|SuusZYhk8WC`jXKCIcnp-ZW6DX2L~u$6?`x_Zu
+1#)<Ex6L5EuIeFuyoieY<M&wqHPT6||@n%3*8d!piQ6yvLL@(4NlC&<)4Qas7Gz_Y0Eed`Jx^w=Pptl
+-cY`Y-Fe>dLMxw3F#;SgPnOI%~ZHHmWUYYmR4aw1j*+Uoxu;9;PYqEWqgIt*cEe*dlfX6e(HNx7d+-P
+99wm)~PL4IbQ)7ItMAQK9xl_kTxiqF^;3}>CK*OJwsDb7<I)))$(Mpuid?G-(~ucS+KwUc5jA<@x)ma
+@?NP3S+Kkk4XVhq-$~8j9|kT6bIeBftaMGP)?0Knxs-kI-dcIT7r;KuK-6@G`vWI`7{v51c16yVPthQ
+DuHiWx?OKuK;Y!3sLzUR5mnN{fPre*~mAv@&QT*(lT+~Pj&_-DIKf{PBe{9M!O8%+*c9gs<zfFp6`bk
+<$r)rO3zKaQQ-vO)aSmsprtFDJ<`C__WD4MYZ1`3-%v@t?M?zB)G^^VZspwkFdiHCoe=r!c43+}k2!W
+-#AaoL$nr?QV%KJC-D(AV#5K;Gi0e*#>^KQH;u3;y$l|NO*%zT-dtmH+$;{5cOn9v^-A2hUe<3q$x<?
+C=fum%Gco<<4?nxvSjMo{mbzoZC^5s;4DhpNaxB&O0G;mL<oGCC3LL=1xfMD(n*ig`UmITc4!4T>4}*
+esAjjF#oVkmeP3Z332hAB+O%)%O$*~+H9t&qEy(-ehiUNaKEw)qoU*!3{0?Y{qcYjAD+B7r9UKE;W-E
+)NL82zHsln|z7*_=4m`_uqj%}NXvi9O&;9Cpz04~U$)8<S=ctV*Rrvj|;Sr!ZpH?gH)VMmNZBIq~KSY
+$x*dT^D=+SUTMFQ6P#<>$m<NYD3;&y8F-AZ5Qh)Jov*;$;#Q<8L=S0*;f7Z9X!J4eQWOj)dJAa9Ig8C
+qr&L^B7LlXA=a;NFbqNm2&~-<XTSg=v9l_G#3?P?!t}Kf^cIrE!34*`@2UAYbYdu&tO8ZXVXCTdda|e
+$+Q)olwmu7ynHU<OMt8`i}Z|Q7`+enh`;1<n%cRCT%?}Nr_8BP={^dLniWNDXq;?!pC9lP_79#K$C`!
+muLi`NVIdMovr9~of?Msx#z+{z8y@p*@EtyRC<wNIJ~(v046r(lXrcy24${u1`d<lol!hw*FX;|9o1j
+2%dgu)tdZy8HWxZ*1M@AAa~X|^?ha5O=+ckmw8Gn-DQ3xBOe_3VW%b2s{odJgj0Djte`gXspH`c5A`p
+;}&X~uZu+zgPgZk7d13<u+6X5B!(;&klXHZ6~w`FcnOI<r)YbMLF-tls(C*w7|lDq6O#iTdIs^RBhKQ
+_?-n_<CG*5+!)3K#|sH*WP^wys|N`i-kst7zlsdj#9!htnRqg;fJa;5Ex?i}6f;-BmWRcNsj#8^+FDd
+TvL<ZZjUrEb`^$EI)zoP&{4c??4vLkl7pd4I0Z<s(!p7<|KLbJ>N;gb=j<=pgPKFhMn(jP7sK@%^Pz>
+<805XQts_)oxX^yd~CW_B=>vS3qNnl5ME5A@UHJRAG6Y*T^G>*(vsN3B6Dy3c7;j)w67`Vz`!=f#~j(
+N0IT#c`PAFM9bx-(Xh(HO*v*VCA%4+Ck7ahBQy4t=`_4rVU6bWmU*FYf%t!Y8jXYdzOT0BWN^mYNu(=
+l(&OBb{bi-zBF7+_D^SIww*s_X_^@}Jj%INHee%;Ywwiq5M&@<SY(riKc5Z$l+Ei%>`&+2tI&RaW$J?
+VfAMK(9f&@mZJP7%jL{2r->w#kt<#YEu^%0{Q=XnYja%%m=MgV1OJ4U@+xQumZxmQ_lrBQpA?hb_k=I
+~NdJlzbZDu(k%qc#0{Au$#KC<w1-v6KUFDoB|?f5@!i6;}KIAUf8*<Ui`5Ptqyi|@w3C@^RW$%acC2c
+#CN{|5>%EP?cWBv08#W4-%Si5S35zM89Mo6+6#$Xcm<b|z{EKq5J3K@t>Sv%8DZIj`$Y6MO20^e?!iy
+@==>89)ia0z!9cYTV>J0hzN$&+j$&=xrXaH5jZGT+*m_z5q8`0QU*7hpt!+$n6yKDf6l}o$i%E|O>e`
+BOky;Q>63>uK71t$%q8<>T==$zpBUMf-=&!3@aTe)#ih(2jE1uk~A#*$6xrwL&=Z(WtW2AptuQq_ZFU
+xmj%yF@z7;1+k?8tz&=s%Q#TphQY+7hx-V__JL(gd!&Ef)){xi@en1-n$S1>0^`ue-hDe=3`L%%!cKX
+pd8Y*MPCv)N5`*Rd5(8j2o3)sLbh51a^&u&Gc588*Jp0LTMT?N<}GCl0pI--*BsGJ<k6`qo}$Q`6Lz)
+;3swIyS&t02jiNWvlnX)tYNyfe<hqvKSxB=rkIsYG3_Qi^)bk5mUT|0&f)wcJORJBST%rNK-QM|231$
+s&226gveKey?o=t{-v-*MZBnhEaU%~A2D07;5ALtflP?tDJnT?w#&ERTFl2Wi&_Ll5PLL&^?^bvS7a1
+T<5CPpN=5E==T$Vr9k3$E6bmG&y`t<XWPpWo>TK5S{kB7xR0o1pwNS*boBN@nMYnb=wdgy7JhrrQXk+
+AWeE-@UKo+#@sI_z)=F@xMv?5+r5{W>|qz~f=UQU$Pv4E`3XF8(DIioby>G@<h}enN&$%Ya%7qtg7s(
+FxRc_WpOz+eI(7Ob?u!tX5B^#?9*ytsOs_Bm9j<Z6q7O5;pR8T9uCTO%Lgj*P})G7Mt`v{Bh4wz4)j&
+N;p93)%SkgBj9R$p+sV&dX6yL!m;`Y4$C0(-upAdYRJ5IH#7FvhAqnslGtxC2MkA_07GjYHJ(j93hkD
+p{Yi7SIxBtjCa%8nbHS%AE<rK$o-SHG4y3@KF0~vb<MG&)B(#L9IS{>qh*x0sD+W~h$ucp_w>hl$A^M
+!-!K!j6)Bz!!Sn<Nq)h(;TQ<NQcJxNV0j^VaC(5D3XMl0h;PtyL{a?9e+4sosytxTZ3AtUYx7Ru?|jU
+8$@SrAG%PCFlF0ix1*1E0L<am|~n_0mE3*yyV}y_4&rDVT%Re2t|*{{qbI6q))3FhN{#l1G}grWQ<rw
+AM>g!DRt+WYH9;(-WL)ijglG)Q(V#qz}1@cO)bWpFjL<jpM9;Zd|}&Xkzi$9L5CnI?Oy!e(ooOFfDY0
+ANr;n=9P{<r+8%sVw2*;a3mGOCx%loOC#a7W=GG298@=YpeyGnHnAghRWoeA#e$sOT^DyEDmuWW>20V
+|3<JyEJ+`?!DmDO)AJIE>S-)${?;gd6-gk^(t@yQguu0t2G+FFbrQnuo;Za<8+EOENiWiWGb4*9kda<
+~|`&Lbyxvsrs)qvX2$87GJ4tu-JTlp;3&eP{^OP`unc6?xd5AC}tHrrZv7Y#TH(<}j8=fHAY7KKp9?%
+z_WXjWWNpR&-LGkf2mC9cmPZ$Uh@$(HFc2VGm#JFhXl|ExOJ4b4Zp+CziJT%+c#C=i%zPQBXNntHXnF
+|sb_QgPWz&197Ag!D5xNV;!hjdpkz@5*)mUUz$~yl;cuf35r9{vGaWl<gwNTcdg-X5w)(@=!{yJ?)tF
+G~Aks8Tne}bH9rw$4yuwuKz@FWY?J3gz{hH%Cn#A=Ek}541X$$yf5w^jgQ4R#rx%8Gmf!{a&o!RPU*n
+1;Ps2-z{sPpJ(#D;l%(-NBi)P11O%1o0BZ>Iio6)O=0eqr+6||1ZX`~9MN_DGiy8_!Hw}@+y=u$Q1FN
+Sh<tZAnxJQfyw#I>jj5!-}Nf6E)?sG#E9e!(Af{S&*Ix`;Y_e&tX%k`3Z7)S4TS#-CwHvpL?g%HC^Jy
+j<l&#ou}Js5>i_RCJk9ygQQ<u_0(-F&48CSQwXF-l;fq>x(<_qEY1^*?2Qo5?j<DC!v<YW-d4lvwsyP
+3lA?{pGV6ZC9zhWkcS{vCYn!AgB>maJ{m!S$3mvlwuA<+Px>VRM}`nn4l7L2RDY~ZiJa99pw&pbKIP1
+j(B%g)G)|~Ke`TxGe^^9MdC>B_gQkhWsLIKTat~;c++c4uVD|Q=+()xXE(NWLDg(0>UbFBF~=2ld$E^
+3_iQnIt*5?dsei`^F1^Ix<NMk=g4;4_ThOiAwh@pQk9T*Sa=4+Z47cqCR5sPM5akc<Q^ad`_#8iat)d
+yKJKw=aBIVM*h;Lm{2!UJ~-*D7>LuE*UCxhbXW^g}y!6$A7+v&2IQW$Gv%D(dwOA9kE+rk6+&$wRrPL
+JegjEYdz(xH%4A27rq`Xb+o9KWXXTE#+YV0)>GKsNLIMS_mS%aywNWlCE=6=82!4H6-^YiL6AzSX`Fe
+{wU~;)TJ`v}J)HT<*pZhp<(+3ab#((3ygLK6dLh<{Mlle%g+6CT1zr`OF9F$~RH&VykDA0M$l^taepQ
+F(TU|%JyjBfOP!sdB;)Uw0w-tW2^_$DE!$rU>=!I*@iU)Uml{Xvx<hU-y9|0Mmt^9Z872dJGB)r3-bP
+z<@nLP=~*|*-z4_E`x$?|mzm?Q_hx4rpgnGPrhGeZc*frzw>;zT@f|n5UuU=Dd$@n~S@Uo04leC}n93
+bf$rne*Ci2&svpe0i{xFe!6UoDBxMMZ3TQw7W8TdzXq}y)?-*qRr%hG+O8^0Z7xsO}FC4zn4o4+lJe(
+u}91)6`J8^G^F0y#wuZ>4T49GUC95xdNF-V}1R^;J9%@`jW*$Z8Q}4HytwW6(NJMsp>J3XS^~IJli&m
+TA7Y%{Oh*T#k}Pgut6nD#nf-|5BG#+ScT0!)Sp~+L~6gcaG+s%b^qiT}ua-yqr7wcQD++pAVegy#HPE
+VW8s`;+LVrUjw#Guf^KutJ_hSWt%~~GwHIp&fk{xx*>%Rk&1HBLCY@O+w2kdCl*vDz-CfSV>+1O{Q}K
+^bg*t-Pw>ebJaTNu_z=n;16rqosM*VNkB2aw<lDleF;E4#r?*^?ql(DW_{j0|t96A6(4V<!eL(~8Cr9
+K^Dyz&m&?NUvFJy9tCT3tCU;xO>&}TZVTUT5hEkcnboj&<-;I@w%vTgVyornw8uJA|V>V+ap7jpLZP`
+eT-!-Z~0*>6cIyeGBn7w#_Zqo&Enav-`$@b;l(M%>^>v74gh*_*nDT1%S@YP-BC&MCQ-sD-3fDsUy<0
+(!yB)X$K%DjIeu(|evAc!A-HiunYL<zeWX12J6ZTzj|_w_Jy9vc#{&*1z8CvGva-ZJGPpYj$ETXvKDW
+=g^E`&NOI?zip?}xqovoeKs1$)ZPqf0;eF;qZ|V%xZs#9iqMAIv6d&xpJiUH;Y9?*h8f(D0TSJ(d~u=
+I#>ItN;1|>#-o-91c1D$U`Hs`)diln8+pQ`u>Tz7p<&#hjZ?VHkOT&~IGvCM1J-`2mS*%y#B$6_jHk^
+4=6pFKulZHn2k!z!WGehj%Fzt`o{mq7~C}^p09rbdWNmGQmM|}6Da4%uD=PX`?hS-%=oek~I=m@^srE
+e3s!DK`8o-m(p9Pb%|KYpx(Gd!&}y_OMxPJiYdS-QUXF+T#V-v@iyY74$FE#)iSH4XC5)LD!QPpr9dt
+rIM1Zj|gU5PP(^3y{s(3rrtBMnFBCp?x49aiHL}C&aCS*E5a+NsCry?1iR7bVRQ209H<?&KLPrKMcoj
+i!Xekc+~p445=f~!x1t)Zy||!NeY<9<5emzGzxX3Qk&v0>#|XHU~JrNF7#HYdC!ziM5DqDIrFCOARu-
+@P&pei^LLrR$sY2jIb!$Z#>t`_7Xv!0(XaPJ$v|)p)MKaQ<y@?cyTB8%&wPLmitYp{b7!)w57xw;*$G
+nT%ygM>M`1M6{5-$8<E(5VWRJZeIP{Um#gRMgo%I4BkZpEsmowoHq8=?0j&!?b3^MNJu0FF~p@}of5B
+3rX{^knkq%^fq5yQ=!<2|1Iz2Av&Zd45+J_kenbxa(#O+`7PnwiLKD*TrmvQYqY7}OdHB61%Q0UrEpC
+U(1Muw3x{1%e<F0sLVPO8Y*>^if-%OQt?*03<D7QYYpo(w9$Qnh5QC{MYWzQ1J=J(cQV7J1|gtb3W`8
+uH>(_cFE)s&ndbakYiif@>t#j4{wGwwtE{(W@;6?dvL{DoLbFf#Q2pTP^UtPHXs@)c0C_f<KRm1T(>x
+|I&&H-zx(6jdA5XmGBnE5SJ_ZIk>Yj?$tSa1I|jjWI(*o351h`PTgtsKMExAdcIl0b5(!Vu4Wm0*r#r
+Jq`!gf=#Wj?39nY?hK+|lhFk(SCm(RfyMK^{p_(X*6Ypcbmf@5R_SK}}pCy`GTA4({N@>^gveLv*T6}
+KWp1aD5{JdXHr{MTPaJH?7%LU*$4AH$f+^8Y_Gn_LIl@7oALz-?m4z<ohHu%Ufy==Ks$pkfhFiTO|_Q
+QJcFC~XAqki*`{EW2E~?4@>OG+(w86&|n8*DFFkU59hq>R09)x-~?67HuKpV!hQ1Oytj!7frohrH>;n
+@8k|=%c#Q%o!ZxK;lOCzGTa`-+%7GJ7m)VrO{Y3SJy_;91ryFmXGU>MA8cRP^1gF>5iQBP7;yEbE4Zt
+uyEI)_KGPKw_N1|QYx@4eJ9jW(@4PAlZx+^dY7bRlGl8qda6?UfYx&hn#{?;U1t*90c&Zw1f;B}qIeE
+(iQfQaVghWUA{Z{n^PX*Okp`QuX6R<|A-c;XyidHjWUgG{#7T#V(i_#%bt<}aOt?nD*l)m3sJAtbH9E
+2q_a?v1-ubOg}K6b`ngxB!UaU$Moe>@zis2-UJ^&!sqr2i?SR=~vyrZGk?u^p(<hG`Cm8-I`EpYhk9f
+<HB={g+k7e(v0DojUnbH)YVIZLg$1g>MDfI+5D}g_lpdBw;dX%IUTAV%<WDUjqGT-Nnvv*i`%qOV{q~
+tR11vF59i_4|+5%z5(PX>RC7l=iL-7(Hi=6Cd{~dBEd{W9C?I2eWdLn??hL9$(&q(W<@+6{KqIx%H^_
+{;SttilcY{SHSa|I6dmk369X$WAn1uuNA0*U$L=4mov~5sJROb0{>&4;eLZO2Yi_(&<fx4<Pgd&%$2F
+-+@7RV~h?w)q3LR9M&GY70*Xw+u-euPwOel|AJV>h>6~e_>zvArUxLz>dfAR4LR&N|SVes1vCKV#2G;
+InuCAvZ@_-v*uOi~k+slQ<c9?gvZgvlmOdFF`Ok&HMJnH`jEmUmL>_DAGgi5UKF%@i~~pq}B51n0-Ay
+%lMW{Li0ynrZSg`tXG)eoe{mrSqt#y3wE2M&mX_3R27ZZE<JomFERczgBi5r_f>S$F{qx2Inb5IDIb4
+?Tz`fVi8xU92}rY<)q4&#biR(rIQJUtC>s&CuHo}<X6l51U(GN12Df*yg|7{<Ito5)~;U4FV=X3JORe
+Q{6Xa^@h5x{iOm|hZBBc&R(e5BYByDvztf4Y=}janMx9gNSe``{%Tx)w&L2H`gwwdF>(vCWQApVnUWz
+s6uEfS+!kB!%IX|~I$f#flDDGYrm3m1!%&zS=$N&JzAKlnMRT-9tq9`jrd=<l)-xwFWW+VJ)ngZ>JTh
+0&JZCqzrrl6o537SfA>yXd!Fq;QY`eh3+HZu!`>Y4_(`u<kgWG+rjj+YH4z*3&UYSUfUm9P>f13?yn+
+sraaipO(gkaRGwYqX5K%p3mmugXBz6%7W*nEECD^VL8B(mT79)&cIBZ5iF%sp6$lR2MQ2B&QR}89?0_
+vaAproahZ9dOA3*61?GJl$@34d9^uvQl3lA1F<)^b#o&_P7PkKr`KpVezt_w21tBPy=u>%oV$TWIyWZ
+Y;3t^pZe!XETl9Jg6JNA$vG)Uv5(CS7pn{g+_@EssesW<9KFDU#f^uQ;YP0XShSR|djIvmg9-!I$PWS
+CxPzA)i4i;9cSMYQ*)hk%Fiegsc*EBX|Lw%bNhilAqfUFcfm7AF~$fXq-hF|LqyJo|!MMGrTj9bI0c>
+yKGteFUpPK;2PZyS?dOmTa2oY;8t*3Nox1`O7@z5o<24A&;pbV-W?;maNf@S&*Ap}W(9V)1PO@l_9qO
+|e+ix94xJ%j!l#pqplGKY0Df!23Os)J?K52R}B)CfU*W?}j_`e<|~S<sGnLjNo=r6f3+v;W$tk^L{qQ
+Kgda-Is=9x`TLlGzo~msU!_EsHR=wB2mcRHO9KQH00008031s8R^Zr}Gz$p;0OcP503ZMW0B~t=FJE?
+LZe(wAFLG&PXfJSbZ)b94b8}x}VR9~Td97LRZsbT2|2|LA_;flu>o}7Y;ll{8IF3DZ=<YaevO*9dugB
+A#F?ejN+urPO;sfsh?}B(7o`kCY-)&EllZcc_?5?h=uKLx#p5{38Y$V5WJgjQgA4xrR)!6qfCyiWc*;
+G_zb)a&6Y>ref9s8~y`>v_f(rIYAy<Yrgq^#VwG$r3Qd`!vjhq39qvRz5ytm@mIY2vT&AtgZG?FzQvx
+-`YenxUnmM|&sV8M==5EwvQlG1dP_(L5#ZfIVgJD4$xr^)J(K0!{VS-^s`CnomuqD2}w`6En=elaEK*
+X%?LB@ktZh%16C8o~&ZG_>js!cc+1_R-cjYr{fmn_cf^wB`YhC&dHY6J&62bm|9N1AZ6Ephu{o^(Sep
+DU;Xg@+uOIr?KgjVOLFphy;`lRw&a}r!1_I-od3FHv3r(evm)>lMUk`tCnbpoMVydr$ujbu(;eBK2y3
+cCrq{BS*!U&ebIAgK#(peY64z~Cf@gc>*<|A!hL3ar40U8YP|5x`v@XH!9CnlI^*RGXjrjlfeMj*x6N
+-UecxVKYIdx_PSN##)4tl;oxFPmsuPwXBW;Y&4+;l#pKZw`BN9hiWjC}ZjihlS&z%vjppPJ)zlni|KN
+M$7m2a<RT5#@<^+hJ^|Wm?y?8htijm#~t7Ds8K%ni_1QjD_ZZEIAp#=WsqFPNFR~0P|#uw?ch&F8Hnf
+x@Y~=1tyBnVYnF0O<(*38P;7h1PBp&-4RnaUBeG__fj#X*>OgOUXB8%yi|ZjBk<x2>;*4}w*hS-GG(m
+O-o3!<gD2!p<kF6C3JGi{curg$OS2K!(;<SZ`~>Khc{tNCEn{>?Yf=<&+_5NP3kllRsUNu;5@-cE1S4
+{t&I4^j1PM?$s{-~87YHEafoi6{l{W;T4{HL?sSnhR&4fT<K{r>UI7e>~l%7G*!XAT&bO{j)8>ElZGd
+^CjrnN+}@jQ{q*v+LQ{3RPLxwXGfA`@0F9pEp?B$3Ob_)8M$xitE+%tF)nFMQ%4HuJ#L3;GyJ=gB7v;
+w2A^yYi_E#YdJ{?wB5%jC)mjAG8bHxPZ#ZATE$iLN4EcF_?7?qvOOnQb)gp!byJg-SIQ_cPs`!TK~bD
+H!A3U1%+~;Y&;oJ@Kk{k<(?LXg%ulM#i{^d{8iajQ(KPI;b9z-VVrAXs09w18ZJ(2c{xWCW(dOx5f%r
+SyK*=t<U%Hd#hu5di(xgzDi~wdu&YTDn$!YWn#;74G3@5e-)MgQi^RHVPshN==Q0^KNM6L+B}^h`mSj
+gMbLa*!V3)eS5UVm}InmCmrdi5k!k-@QJa7IM+MANJur68>b(~qJL)|{d?0+Y$$9<RjvdEV+=1?r4Q0
+RUXKxBK$%vH^?6vHHU8Hw%!4@xMi6#e&~|A-vJ>u~clfSvabE+k#!f;mU5ZE?iMvfGsm(k+Q-vp<Z*w
+i)qZWD^xzq6CYavA=g_W4BizO-YVLPi6s-JOEx}rzO6+BCnI@*+fK~TML#)7rZTkByW!w{y4%epAnrb
+g{9WVdb}J4fCXl0wUo&>KH#OId7zOsg&dhO3?pOS*w+9~9MXI1!V2z?6~Df@Num4`_-k1uez+|wX6^V
+g#X|aL6k7|m)=NrNJ;zi9b1iV<w$L~F?a-K)g#rXD>EX>TsRDNEl`fp^%v_pFr84*B%5@vW!H#~yXkc
+Zxrw&{aAM8WV8!_hPYRi=aG~eUp4z*fmH{=zbHIB{R3q0fnpfG{$ubmt&%_7}oChge5Ds?;wIi2;K7b
+qvk58qW1nsMO;q_kBm_UEoK<f|l^R|h`~umViO4ho<sPU)-*P0#nQSm#7S_A4PIyZ3@4(E}~?PS8Si^
+pSil+lg`~>H0&iG?zbbJ~?H2JI{{DcVeOQx%d+%lnBh8kh=jbPfeF@Dt~DU={2AjbEbztnPSoqfo6%F
+E=pD|S)qf%Ow=XJ#$LauF+q&i3suw>QGHjmTuAke1x}RbE9R2(<gHMw6iSS0pb}Q4iuyjY*8%1d0Akj
+;mH~JD#FFjaIBm%Nj`9j(0(U;xoqud-y9+i7lZ-uc>izA!h47nw7Y;VX3n++Vi|i}j#bJw{qJI%(dGv
+T_V4e!n`!k$E9@`e@xWpdO@99L9!*>3ucF#YBTayjeGPmQfZ*@UesLRFYLXA)|fp`+hA97;sYva_Di7
+}*AQ;M&qxd@FD)0zi^jq1^z*a`-nv+8j>KIs=10;I9T>y>|w1PX%Ff%J9FMUBD@m)<F$$G=I)=l=F3>
+H6P$#cZRwzLFtho4^wySyab`)DAOPQymKBrP&?DLIRO#lW&5HT$?z&@Um#rV=_)E&fE++R&mT=_$b87
+bpFa3Pj<w)A!+HptWH4H?fOUV@)MLr-?b-us6#)syF$<9&X5lK=F^)u+c{hPwBQ*SBgo6hm6v%v_%C&
+#)?iMdotM@C>)NJ5do={6LHS9N`H1S57w^bUqIlUvawyxn08&5{3>3J5%s2e&-wPXBTA!u=Pc$<~0UJ
+M3KC^-iKj^gJ_skp}_P35jU?_5SIrf?NyhhMs^UX~D3YErLWNv|T)So-VFG=@ShX(pYeF>W{K-&P`p7
+)JQcjmfpQGPJh&2Oc^%C0^(-=4YIvd4I03=pG<GTl-@x{WY6%Fw34krJ1q?~y0j26(>+_Rht)azrl~l
+*aI`=vacmx;?Vw`hF26TZ@;=KxByQfQ3Z&yhyu1_jPcT4WNp=&Y0;rb78cnBryFGC%??e^^#UT*^6|L
+NbolrRl=I6zGM8q)I{eC%Gm{{A3hGHQzldAs(CqqNpw7!vRu|bf3n7cF;)#4qAQPJ0Fpy;E()|-QA8U
+;K7+}v+#kygNCR_xr1DZgH}|==gSt$R^~3!dRLIM3)@pdnuh(nk0QIe`y=T^lh5GwgK(EAm7K>3u^2S
+lVvtvAPyk1|!hcm_F*9B^X?cB=<$#-ClM8<rnZs6mQLF*kye`ZemExzdCEu{nAwW<r4B}MPpMEzAME?
+NB#P)h>@6aWAK2ml;P_ErRN=UL?n001W}000^Q003}la4%nWWo~3|axZdeV`wjMa&K*LbS`jt?Hb#T+
+cx&yU%_f$q(ZAC4|y@xX|vgB8*H};(rkgkFcey%X4H`-fud$&4D#=L4sRkQ+B3;y_hoAYu_YcJp8Jhc
+@$Nvxv9H@pQXl$`3-Yo(rsPM~GF}%c`MDlMO5XIM?poTU<URW+UcZ6wW6yr0JSG2bVI?Kq4dYEm%hjq
+vl$pVH$wXds?a(z$ujnTO@XA{hfZnX&QR+ZEY_)m|5WW0OHs<^|n%+jq>L0A4W3zy9UIWl-RWx)Mh}w
+C<dB@|6j|G!FChHY}PZUM=71`5)5w)l4IO*j+!dXKFD+xmcLk2r6=GW~FZR+wJ8+zc5#m-3~{GuauTh
+;}jBNXteUF4Py@Lpod$U9oYD{)m1<hF*d7Re~sFysb4PJBeIqD&q~+Y;e#>T+5j2iQ$7S+<fOFZt!5X
+v2?QBe7KPb`V@?VwbGRg}+;~qp*~$B6(i7waD{$U`>@8z_rz6LjL-K{L-~-Iu0Q-bLPfuaZ!RXUTKta
+zd<(P;7p9X^-#@J{ddq~tSx&x+0Aa!$;;syWX#AoFfMgnxBV!{*owLV)ks}T3IbhlR<Qbpfr8$nYTzG
+kpA04idKdv-Nmt23a2Y(H0BSV|Q&z=3(nH^{A*c>*a<SnW{7ri#=tFTr&~-ARO?^OHh@#A5FkTmHfAc
+WBG+qe&4uZA?kjtft5Df@}TsGaFHU^7-48lzZ^}y0?$4e6LyRPw$xoGJg&ae<txIV5QXfrs-imR>$BP
+TJ2A+*BXjP3^BgJ`v8H2694hO6#2FV%8@#9v{Vm}TW;AX^{ddp^z)S~|lB&GNkntsfa1%LUpvMria45
+P({i?1Go)(v$PabE2(2KnIT9+lHYrvQ~ga8w-a2M;1v;b<?m*+Gq|OOtIx~jx$rR1~oVwD}=UjY2WmQ
+){RuP62zd6N>-C8=fhZ4^+%+5O*GG1N^6^KwpQyq07N|of{YhK(wWChK?hHYrsZ$bxo0@XYG*KqrVHC
+%6Vx*-OLI-<=6a5UG-!zyA(}!Ow5<ThsX%IcePg{IyxB>_apJ@4=;G=eKPb8k({g^G{CezT1qUHb92>
+TY)MJ!*o9YUJpot>R4(@|7kek+#eLttlgo%xn`^q`R`qV($PRztGi9$nd47`7a7Y#O^N&<irGWSv0<o
+7a`ADFo66q(=KiU^<3Wa)4{3Akv6|1V?JQcwt-g3Li6IHL!L9#w1l#7LW0MTv`qIO%*cgDlJb)Xsyo^
+Kki3!hVRX|CFwlf<gfO6)b|dzC`k{c@jBP3s7EgQ9y|bWdzDc@DXw`miv5cA>ZrJ-gI5B-l`%Qvow?#
+K#x`$elAo6>POKRFJ6$UZdgkXs2ZjD4AmK3=$gVTV{2u$`Q_`R=f{+=jt%_x%UIWnzDg<UnB7+_XXp0
+$RZ7~qML)W%_3d2Q01goxgvRux4M>xMRo2SZ2sV{Cpa7gu#e`(-3k9oa^E<c24Md$dV3BFazBc+h4cf
+!T{76IE-RST1q>?u7LjcSmavvtJsZ7$&tXYf=c7s@pd!xRRsdnb9Eg3fi=r%o+n{B7<#hmvhf(&EdH#
+I9=>jGs^xyAZmb}lMdvvp6kG^j?!LGVs;Ji{RgRA++P1ck-`j72etzrdeLA798&v@j7(Tt)Gn-tsAlQ
+ld-UOuvg9Ssv&$GYa@zLH-N&nz$%K-~Uijpr^7P`i34I_YDfhI*`*VK#S2Ioi;+h1(D12J&^&0`m%n;
+MC4ZIK9NqD9X*M%Kf1b&UFam_bO2mM+dH%O(=H0QdPaK)DP<gyS<~V#8;`SU*Du`s27JXq^?V~!ySHT
+74Yn5s!s(i<1IKdiCii*+fn*{-31!)njJmy!!s<l={e4b2xrLc4UjsN+qMLjNR6Ch&{7#pP*sRJhf1+
+r#rQoZ1oSv7Hr)t74DZT*G^WPs$G9q$#jYGq;E<7(@lJ%ls$pWIEYNlDGbf#Ddlqjqf{CHo4Ko-fbLd
+H#pDTnE~E=?_^)MXm}WvV=xjfyK)Tx-YGAyfvlwVWED+>s$q@UL)-g2Mj4R_Q2QJe^aB!hl`|^7>6a$
+UzyTwEc0e&!D^{X|mFpW)gC6FNuH(2MFW0IJ%#egRUfT2+V~)uyDp2bBU`^4@B2}oFMb=#!0S=`+=Zr
+L#-Up_Ev44X5H2pQq=ej(hDiXBrn+ha6xPH!c9Rr<4wnG|Lj6#O<q^z!v~4=!v|#oYBYI|x*TrFdoUS
+A7cjDCTDm}zWEDCbqJmObXKLrhSB6~$PxB8}$a5`x?<Q**-eU<iVPo>9NExWSe3{{vS3~nVCy6#ZCr+
+06Ibe1&E8&9%aJ*E}_h2f*Gv;MlaD_D4aVOt6Y%B~pRTo<8`RRfAC<YG-<dmrNE8wtUW|)pQaT3pGTk
+;}ixEs`6TRbNX;<LT~v)w92F&t~x@?sI6G(jN?bVt3AaO+mY5;}21fLEJ_<?&P3UAyJr(4pNUUwa1Km
+!eANczZvwoS)@+0fM!+e&43|CDsQ_l1?AuNkN_#oGso*!<5_ANO2-3b@7Boiea7uQ=SLOVLsP+H@1%4
+<^1Mh-GRKl5B1gM=QIj#oYbj+mFK#r+bitYF%JfY@QxXVN=p+1-Bv1CiJF)zp{Ekjb%fM(_5K~gqWW;
+r)|J7Gy^9Qcel_p2gdZKSLbd!N^iS})$G{>#&!RqlbmX4}4@gcr;w=u6n3oY#qSj$DS!}|txo$`19}V
+ToNyhz1?On3R(_Ooqa5<Ojwp_TPLZg6Y5LKh?aWR3!>Ep@C<FOk#F@r~QNZ|U^T%6iJ&JasVA$s0VDM
+o6+F4<Xf_ao=E=<=c)TQqHZoFe_F?v@-V1P2W_kg`KgplEDmNd?x*xM?*{G6aOk_m8{?*8GrmJnZ3AE
+2AGE>VBz|NQIlviAb<R&o~8mq|`af)o#g#8k4F6e6LjG$&ZuEToTZrRW(1jQox$u6T=Y-rzcP<p(7!%
+swK=!<+L0i@M!dk@mJapqa@&XW1Iic?c@7IfW$pU0>8_VxeDy|Lc@-$Vf!{Z;zX>Cc3*9v_)cz@`OXA
+hh;Z>SL0aNAf!Y$=D73Ry=9nj{nQ{}*5eGJ)f{ot|&El4w?g99xBti|C6XlIGF14MU`FWSzp~>IF`m1
+H{s=Fssam#@zLS^^17g^KYGVbJ1o4K$|pEZJy?h$69vnkR&Wcw7XU{zx!gn>BEWe&~r1FhRUkJg0z1>
+{684|J{k16WrQlucG&_gQ`e+J_n!|G>-q<)5r(72MoMurS)zJEfNGlX?dMVi3c3ku|stT8QI8r%Drb|
+FwwF3(t$zpy+ERaH8VI2q=%mEn`5=e)nwqWWSS@13o;(Cx@Wt9?nJap$U1hA<y(3oqYZqJU?9qf;|*4
+*Rv`LYyW871D|<U<$c$!$=u0*Q8XXML143MXjdmbdm6d3Ttrtzip$NNBIlDk{X8X7=TA1yN^}-;?Y3=
+kr0p&?L_$_UKtY~^w@^+C03VVlT_Cj6CjZJcDD8%|v4Kxe=+8ex#&fA!%0<`V-3=E3L0anW%&%{_C(e
+qGwK#RTifdp?=1yoE(H;^BhTx9V_EP@p8RgM#d9vKRxszYcnSN<!SljR3{FAJkZY-N)UhpGyfO$m=wu
+Wv00Z>Z=1QY-O00;maO7>P*nETT?0ssJS1pojX0001RX>c!Jc4cm4Z*nhkX=7+FaB^>SZ)0z4E^v9BR
+KaT7KoGs_D+c8vfvZEDUJNNDu1QRx1Sgjg%CeG1*4py!vb(m?-*;BBEXg*7Ru~&g@4cP(W=4fkJ8-oY
+at&gqm2vPS>j`Asx(U1^eSQ3TTd?`-V*X?K^Cc)eK}f4Ha~(t2tm4)Nfhfl4Spal36fJbZ4k&YF5+kx
+Q$&|FJ!cJpFkI?Y6!jD>G5U`i!^Ydc0e1C;U2*Z$z@`y%k?x$bxrw`S}=2A}|wpQhZ&_{)IlRlfuZZ~
+;B_#g;!ET}YQ&dO0%Vzy-}-B9r}Z#0H4-yl`0YAYq)+(Uqja0x9CcD#lZq1C}0(i&FYfj`Bw47$CM5H
+)}NB`gKxxXi{UPQW@7pHa#{$t`!zT%bb6d_s(c{{TM4c_ziD0NRJt&8W{|c5>FZ568)eeG)_(q~H{A=
+rw!_8LuioI9<IyHf_+NbV<<2JejqfolOkb(WwIJ0%+xkAxNwqLRv(tvuYw9NOe8@D1Bq>zH*?*EM|LS
+#R049;*!qS|IcLO!HXTJ!wz$1kxHN?`J@fP-!!OnBZ>j;;LRWjyWSh^Od%w(pi)XVQpZxzSzTLu=c5U
+r4&)%!dC3O2xR2uwzN7P9IyH-=vl56PcD`{XKOj&Z;3zJCnn?E!Z9lNZ%`*BO92_;6c!PRK=%>}s8{4
+5PRZgL-(f!Tgt?_sqN<_CH%tuZ*|8uhjQCy*gyl&sfS89-N`@=4<3D5KBLNgAAuYhLH##1waVR3%|P)
+h>@6aWAK2ml;P_EufOuGe({005={000^Q003}la4%nWWo~3|axZdeV`wjOWoKz`ZZ2?nMT;>G!ypg@d
+tR|}l{9&P>(nWtd;sACPJ#o$S&4ri;uLH(tKIRfWav>@0yx*w6c3wed+jxmF~%j^JDwD{$Yn0q)nH^<
+mOFVC>ab|!)JoWsZG(RTiibu*ca2DH<84muvw}rWJSM(*(>QA+4pIO83s6e~1QY-O00;maO7>RQ*U?i
+H1poj~5dZ)f0001RX>c!Jc4cm4Z*nhkX=7+Fa%FIGE^v9ZS4(f>HW0q+SFq|KQlS-66zIXN7MrFC5Hv
+^%uiIi_7y={FHoGz@P*iqZ!~eZAq$pdK6leSJ#pH12n+G`$@l7d}CR|h{%e1#tazmE2$h4G2MYugJsn
+VPl_Ec|6E>`X+@Cf{_#5OXEYg!casbF?@r<pqJ?s=u{>ao;Z3R>9RtS%kPY+D|!ey7TAeiOiMm-3mZL
+ef0)LeHC##4!f`%m<1$WmR2hpgY}jBRoe7ttMP9+`7^#B0~gAT`asQ&(>2`sutKTKvh=Isv>xHqm)#^
+&F736$HIv*)%X1?K^UG9nPs(7EGM7VOc1Iy+W;$sQA_ev^CBmdC_suq2%z6NH@%!K39YpZvZ9)_ft#b
+(^Vwn%k~eQjv$0y^I35Q0CL&a<>Vm2Xd4k&oS8i!hF$3Z5ZQdeB4z`2aq8Zw-O#u8L1&heB#+D0JI~L
+FAwinb$M=zSPXd`=Vf}gWYDykvC5XVe0su@XB3}l)T^IBmC7ub+Ya1j9A$R$z>nlT&O)_|97?nm4KVq
+A=(pkl=m01YcVr~{ib-dc*hc#iL2*w|w^Lq#-`Ncd3Er1_%5M9Y$i9O#ZawiK_+b@C2YOv973cE=qfB
+H}m9e&n7D`5J2gn-IPdQn5LTzJUO6!Sb#(OSl-SpjHUdhYrHY7eL{UFA1-pQfVsS(f~Lj8k07h^jI7A
+f(hgcNs^Fnhq(?>3(VaC`}}edhJ(xu0x%BqkwMvbrbUf!AH1NpU;yH%2-pZx;Fft?<Ity88Z9G6o;S4
+7>`bKaVwyF$j<GWEFU#XElLCrZ&0b^n(%*rn`($UZzfya@Z~eH{CpUEBIr!q9bWd6_T`NJB{*Sxn4Vt
+>0rmzxp!_st5b{FI#{!?-hxU>oPZ@bwyY+4IGiXH4OqCR-&djqAz<%X*tw#b+&Vw+B{kX(TrWUqi$XD
+eR=;i_K+c}2lQM&uHXx!}5AShU*qJv&GyZa9crnky6*uYZr2_vn9wlLOtD{CBdkAu;IARm`CcR>64s8
+rJwD$BLFTyI&vQ-_7nGAFl4x$A|k5<BxR98MM{o(iRz`#xlFB4@?e5q5GCh(_d~r{P8&bIXWZMuo>Hj
+c}K$02}xUATvTwJ7`VlA@vy?<QNiE&Qeu%0SkbtasOvyC#mxLf+A)gI%1%!Mc}IE0jz+IR^OpWC<ps=
+KkRx;?QJ@d~Kz2sU-tVD=HjB)t(jLMk2&u`MR>nn`9iT~eJNL;IcC#DuCYKpxXhQs-+~@~~re$|+0PJ
+qh#BS07JJUhEt_dgFr?z^vB_}*+Z!~w64(h8gvo}oW#c_n1a*T})gVk?tJ=bC<lC;9Fn+}>941m^M(4
+OI^%V|q(_?mB-;4uER6JOH&+g#|r`$oDuG!96fj^2l&{%;2O1Im9k#UCKQbd*0<`%fqMGnZsOF<yTw?
+gI(K&#}?j=8NSKGIK+@fTWz*=kX4i8<+7D;#SJ;7~dUIO<s(3U|ab7rIh{<{mD$tJHJ}X62F=K37PwB
+wW@&XujvN=fX-mJDVV?54`S3?%MCrLqR?;oUraUA1L(zjkTS5bF~zFnWt=|4uq0KCj>IseRkC32gZ<i
+WErL5s92t;~4`NjV&3_LQcTQDqOH|n5DB<%(2VlyHWJ{08C!Xtd^8MwApkw&%a!~nIQw@%EgUh4EW2S
+2MnyUE!*#9?BO9KQH00008031s8R+4E0ZAAqD0QwOC02lxO0B~t=FJE?LZe(wAFLG&PXfJYgY-KKRdA
+(RsZ{#!(e$THM!b6=S%~5nuD}q!VNC(n^R1SDJPLXfp>>6d0V0+u$tC08+{6c;SV>^!RWZP2pATQm-<
+8NlZ`DWs@5&aI-ap2ts_-^Qhf}c9xcS+Ldm4dc>)47#Pee;^BZC{VeYu2{XE$f@AWnB)Esmk0*{((8u
+zLR~+obgM0o4X%B3<}-K9IjYbGjYY_zE$Ja-}b{%G2ym;XK!Eg1MfzQ9iwtDCh*txcE>sgA=T0Q{!!n
+I3yK|-d;SK0CrPqysg!WFZy5<)Wvc}6O4IZbTr$E0OW)&9)k7`l4N%zjf`8~cMOzRE0;J^~%ZkKozZ4
+s3f%K)g(gud|w^E7R#PBYM-q1nYY-OHkbn6Rv2Wra<asgknh9XZ=ucv7-;jXt-&^1Obff(2T@1<KKGK
+0Nj^%T0s)v?ZS|NiUG0NOH142N%y1B<ZDQ|KGR-VDY>tl<MNOzEBgfhuD$;ngADuXuIo1Z9=F0DINnX
+luKw6Eu{gNoV3rTh^#FhjfivVFG{k0z>7Stx9L{j~0bffvqQo1Xaa5uBwW7l33g1ag|pvuQHSf<E@_M
+C(5@%zJ)f_MabhKM2LoY1L=9rL!KujBrT6wTZNsiO&l4<EQ9l};CtlD%a%7&vlAa{24BL3H`14&Tr&8
+XwtM!C5WOJLsv+{s1DpXBo4xK@*zKi)Exl&gPudmS@LFwk#ZVJ1wzq<dGy==Q=xn*WUg>rr%OZ~z&K?
+_WbH=-C1h3&*TS0?rF}`wOhk;=h^$AIh-hk+UZjJpX;*ad?j`+2B3OgA}tDSf$XzntQN^E4?w6sczmv
+l>&S`zVN%UNmj3B@hgAW+=e$Y=p|<arZJ?L`MoYUbswj~z42;dU0VPCIHG!PnbroTiHga$|Po-xjvB<
+!biY@Inn=A3jQ}p3-eEcJxr0XUVCNSwdX-^gNat3XC`;D%YG>eb*j=BCoo_vz!YqjS<PR2!*vMwwdi@
+ki~&X-D<kpC%P`w{p8+`oXFpiv$nRYm7Womo)Kh1&n-!DjJCQ-=z>e$NkzLgBi@spXtQ=QE0uY{mO)g
+0C?Ns&>==t**!NzAs*4;NVV8E==^bf6na3%Hmh#T^QSb<1@h>J}<{_kzW~a7eS7TW#Mc+#jI1udjJr}
+I5<bW6m|3Xs}wvnHrw$NXAbg}Q&RI$p562(Y9AL)nl8TO*Q@%E2jVzX~7fi5aR`b#%AqG(R1dsjsZ7d
+VMCz@ENlqG|h^GDUUsL2{YKAxd6*wus|t>V<h}vkaa;4+z(np2;qupwpk>fx(00F5hgQ!Nsg$HHOb3*
+msVmF{gUoYm|)%c@eQeva#Nq$P)CaIT#S1L>TDI(8-{n!+@0!Vn$eOmppjSJh0X0^?)J5BDjswxH|2G
+wM+Gxm+pU{y(cB}fJI!yssAT4Cyeah(_l{;{|67JgAaVU=uLY(LM;#T7M5T+x2BOFeT9<Q`eGK^**RG
+ShZH|a$5V;xuN9sy)d*yMn-hrc&(+=Ibbf?G^2oAvGt;}LS@W4p<(%d6R4&Ft-6=BciEaGe{wOE5;A4
+GptPIx3MXtwel5ibGM|bGmNWQ9em_t>iD}Ya75OlMnD|}UAEGTM&IDX&DqqLcrPyc}rMRkpO>P4ZGy5
+m0-c83zj;H!N+(j4*lCpOn_FW#9Yc387P!MAu^IhgN<#g6n9mY~n!mtM5BJySZTrSnI!@Od!^)D<y@Y
+a{#8$bQuQBQ~c^->2DF>GDOE`~y%+0|XQR000O897^_94~6wBbOZnZ8w&sc82|tPaA|NaUv_0~WN&gW
+a%p2|FLPsWaAhuVd5u<WYveW%{=UCrP``MKYi>6=+FNiTq`6)xcMWNvlw~nmTi(@GmRw0rvXuV!jwIW
+%cN3@~8(A}&muF@kxz?(IQVGFI%at@4-Iu_dR%r{LY1?vnSkz9(p4@s6J^p!rSKNNOyZ!Z-FF&VnBTp
+&();bGRr103af-S<i?8pyCfq$0i;q(J*^{2SqE4EZJF{s?TmqDPJwWm?y-+Gayd%?z_+{++fFLvC=b?
+Sc~Pc6p9>v{Z}1>h6Tm570gCU3**1Ctfg-uz-wu^P1BC`_qZmiXg-xdGCHwl!9JTy`Y&@^8aG%dJ4Q0
+jup0)eds_q9hAi27MQQv6I=rUMYdHN8R-@j-I704jr#plz*hc^a>4qDFl-Tdz|>;(#~BtEsPOEeM@Tz
+-~9;W0s#`>B7}rJXixU2Bs@{go!nrAK;gijm<*_73xDE9A51tq;sr?$*Kz|l7?NLOJ4#Erbj!ggNZO!
+fDl6O)9W&Wz$Ri4g$6NJ@EMrbVp21J7rk$_`tn&Fq10&dwI51~c?xgqbR9rZ!25wnn=H^^&qPbap-Zm
+N3sN061J2&bJ8m-2nLV{JAS^P|2c+)k|%Q46vL8cAtS*<h!y5DQ|#HmXI4{MJBpa`Uz2$hU3-SakTv4
+8$gK)q%kjMbei&q6^56*mr=*J|b6J}}#9Iq9K`-gI50$2U;>uSjdz(69dgl#cRqCQ6oJ#9WPwz%6;8m
+F%E-m9(^~FzP&cm%?h90((Kys&Zeei=!DT7f7vLBa^S4vAjOzL_0@h84_|#;=9kEO5E=zkY}V1KZRj0
+v=T~o5duu>cSlsFWhKXMk5gE4ZLlo%h+{}ad!&12c}ayhWdj!O!NyOaz%-rraaVh&A(6^Djm%i8t$F7
+5n2@3%n7Z2)>e*q|XXBGVLoOp$C1LbKW<fuXxh{d%lfh$%AIuH}O2+2!@%fo|yyB&sY4C+-`rOldMvY
++&W}nQOIPo?}u<x@8U=bI@YuSZ(;sMNeZjeAuMvLt44(mVFSw=EAYX_~K=dleL%pHU~Zm#Jbk3)K~J?
+ZIuvc6QDaZ^5fyHt*plgH)jYGJ(dxSXq9K-0IEzvQ!;+vGLC;vrArx&Muud!_vqY)>fbOA+=+R5}~jM
+F_!v0u+V2QwnVT9I)yQ@+H=O1Mm&BnjRXuanx9<C;UKh$Ncv}%iFBLi>*>R)4V(m-w7=yZNnJ&Wipv?
+%ZyEGr8ZCtMR6qeRQGE?+>YU5OABsnq3XgOF>W_b+f@qd6t2>6EyHyhJ_h<LAIK*rgn~bm78Tizb}C-
+Z?ff$<3Bj}s@--$*R@sWo3q~4-cY5W7c$FZNG#_=x?R}@qBQ@+?yQP{o2DP_af_FH6BVbrcQ+e>K1{a
+DMw`^6zgd#hvMz&gC?amBw?{f9w`u%!!{lkZepMPUXJ-)LKFrkpwJj;YmAzQu+d+2jynVzQm%J{0R-(
+^?VYlQYHTV1ceU(O2nA5cpJ1QY-O00;maO7>PiHU6$r0ssIv1^@sW0001RX>c!Jc4cm4Z*nhkX=7+Fb
+7OL4Wo|BTd2LkNj+-zLedjAiJduj>0g<S*O1Imp(ze>oOVzEA0|u-*wq-lrreEK|HW-uTA%VG^Idf+0
+UduDst72jRc2-hb_@*qAg76ZKKfd2LhtKziuU{S?vaFwCD?^7f6?Tq(_MfxUUO8P{)5r0uXmB=MN;Ny
+D_l6T=vn*qMT56vGK0c|H!pMkOIM?(XyrbM2Jbe@GPgHbNKT&hxc55Xk&oJ5_w7e+)xkG9#QZ(?~YD$
+HtmFM{#=p`HMNG$Y>bAzw=N%fhbdSF}*5Ya)ar7}SOw$zv^b0~LuF#DzG3a&_r?e=gO8Shph)sp7bE*
+70jkYRS1Hjfcbr2Rc$S4hMqRPd4Z1jRtY5+0=ph}f9t7EA3RPw9k+j`q+rOfcItaUzEDJ_`9R!kAl}G
+HoK#{ke4W3u?zMh7zSXYsnPYoMneuCn-6GeIne1xE;Lz;L@VHZjlsIRr3c)NL^{xj@!j@bI+1qs?}I(
+A5g5j+NIHc8ntgIb!~}b)Yh~XcH-9rem4R`aG<7P<MVm$CfdR&$fG9t`W)m@ombY`v4oMbVYEmrKvjn
+Qqnk~u=i1dkZR2c3Y<&lKj#o-hoQa#nX3d*WVO8s*I$~+zsMHCe+W$qVITO^Zm;_8`j!L~XLaA}Z%MF
+Rrw^qB~5)|p`qrODSw}r!nhxZ^#FcL)z=P6Sm6Wj<Q=&Pd|af<v!yy!fNce5)_$GPg1TtvJco0=}s($
+NDZ;=Sr=?e>W#S4QzJaR*{@Cq5(~q;+s<QcRrbXa50EO9KQH00008031s8R%2B$#xfKD0JmNM02=@R0
+B~t=FJE?LZe(wAFLG&PXfJbRXKiI}bS`jt?L297+eVh(^(!#k4+E}f+Rhxi%ZgG_WF}FKETtrQT`7hI
+K}1u+7z8i?Xqh{;``h;&eF6=Vl02y-GpI@|cE5i8`rUmlt6~+1e7y?NRasO`aGEz$_<69zisd?AG)0l
+ssy3_E(IQ^l3$9NaQ91R?G=rjLoYfK{EAH;n{7%*1iRKJSM8&m5DXO?BDpegfO$8v0s&6)>)i^u|;Jg
+0uhiP>3{q*E7r{~{|sOU|)X!x&FXd2&Uf`6T*wJbl6S0cGym#XHXY|<i+GyZiY{<aqRLe^Pe*PBxQ^)
+3ha(ZTS52^%j&W=73~MQI(?KyD@?tc@Phq`9xTIq@vv@=WBi(D?=9ju!WE6)#{63|XiDBfGD$(i9CP6
+_qG8?=D5X&YDqBrHlIrD<n+aY%-yMuJFgfLArF=IH6AD$cnr!Op6o#IZ}Tx=jsvkmnWj)UJnjH&cTrp
+Z#Y0Q2EeX^MHbgJwr;8-LxzS@#fIGLU@$l@@)u>5<_(H2STHF3n}|AixCca}2#Yw&HbGOxd7Z_L2$~`
+|KEFC;xG|tPAbj6U&(469*YxA$`111f_`7LzIlX>&c@E`YQ2F;4Z>R9%4-9lRJ-&ore`IC&{^EUf^6v
+8L0?Yoy;HPh<rtHsDHa$Q7=4=`rpIt{+CzsPHBL5Fo$J48B)qiqVgd=+Q1C;!iUGnDQJwm;HWfy*Xar
+yrE@(q^1w#&acKKYBP_`<Gud-31X==vf$xj1|Gmhk<-Q;p?3*6HQ()igRikIqidksq&lxL4Eb=>6$A&
+=g&tUY}9TpFxyTh$p~sC?b=X8Ize=GM<n8<s;b&WIYP%rkeKy5(xYcAm-5b*IKW`q134>akmnA6B^?-
+Ds>!`saS}hSO$&w)C3P{b00vXVv&OGBmr5)SfQwcxDr8G70G%5mA9Z~_d;oWP?4r%^+G_mah^~w*aUP
+xT>(N+Oi<g8;0>X9nxk&Q=)f7&_~)$%9;y`F8dV@_F!5Ci{%6cOdtBYsOger<a0u;(lb|(@u?AwZ4ky
+Hl$<6;Ed)U^;WaKv^@UHCS5KXRs$(BG!T$X51iXt1kvcb?13<`ek;JwgDr3*zu9RpS)1kaw{t{Y*EQ~
+AF;5KRb@27K2*2^I&k7>9kIYEh4sco`|uJV8buXpR_?X2ga$C@Q!YabS(ghLL1DBh+oE(bph%2vg05e
+kEdQ(;e0#TMmO4U!kU&kpYD`5^!?2pg1HumUqB$qk?YJ3RDG{pQLq}#hU;zjadpB&!uSARc^5iKkNzg
+!XPJ{W4m)ll}15CtQl#+98qT)sG?qiS3zoICm@3Bfrf}?c%T^&McNpn$gqH8fgyI2iYzhX(&f+%6{@~
+KzR2#@C?${#Uv-cdjR&mN4?$}H9E1zr3)-rbq}fBhg*?X|E&g^SesV7sACPV|r<xU(_!*~p&Gu!BMsg
+j|gqlagKAnTyLelhP3S6`FkkS^4;<%)VJk3fp_XYdEuXQpQzJB$^AA^5~ATcxy1FcRuX{p0S1_^^CXc
+7#hH4i`|*YF!nAIHPK#;VnS&L;;gmG)>ffoiZwwuLJBmqB4W9^G<mmD;KbBnDp{*=<~v(##_)Bi(U07
+_`Y8wn)Haj<Y6T=4XJ*q6RQvQy3yOFKuFm!1qwwXz(I<J+!*H70aT+KCpH+0Yr0`1V*h5o#BVh_%+xO
+iOV<muw#>&3yiVDiBW$GA{9EE%y+ahWI~b%P6CPiGSIwmDMbb=J~(Vp3_esjV~0P7M@C#B;u$({+jzV
+W54ZC1X}o+IKV6=-N&o8kl+Px_Y0%Mma2O1Nu7T_r3N(R+j~tM3b8!km?YOSNvqJcvR#gELmG>#68@Y
+ho4aNfAEVvhy7+BHHc4X)xALF%D*Whih5RLZAoFg_5g(`u(vSGhnibc9iAvstS*?N^*>A)#_cJu*d0s
+RLs(Z*S5PQ|M<Nis^n;^2!HltsZ5R0P_!AXE->cJ%EKyR#T_UE?V>Oic-;;H-hTvJ$|lkAje^EQKbuo
+R)#XK?<DfG40A*m{C{CPs%^$kn~wx*p|llvl!b~`KRDMckpk)w{Z<@jA1l9Hvo3M=G;>=tnL^C$ATUg
+Lpo+csUD&?5_lSQZOAd<3G}{?#ygErRd@SQZzd3V6@S>14WOlDX)Z9<lU-;taID~M{6T<z=Hh{%weEP
+*5kM3Ue#!^idZZ}~r?-ZCm~EJOl2ojTUK=vDI=8^KO&$ywc%3HN1C}`8>CoZDG0nf2c;Fe%$Z}dzqh*
+j{X&FV^vicw)5`y<)KcW(6W$I|+H#b~-s2Q(*n~~kzSpB&(Q=6edsK=*F876RgLQM{YCd^~EInP_KSR
+t*c<Tr6G)U^DKSjI4wAS}pK7lk3!hv&+j-WKR+ON&SSeQbAM?a|hAnuUQPdj$~!m34ZX@lrw^uY`sh`
+kh=w)2B#d(3xp%yEs-phcX`MksMeQ#YqxHEeF#^-SstSZtQ1~8=bizbrLe$hdq7_KZx@^vrY(8EjoI#
+Iq2H5vnLJ2n??{>-WoqVetPY|_Zc4bf)MW{+Z-#SaK(QSjH&7J6u+L-NcO)gk;CsZNJe_*HgLax=KTO
+Yb#+|y4%ci=c_%d01z~?n8w*6!J`VO<>fP8RIY5K<=7u&LXj$qRF7McN#cJLOQ|>0t7oz3=O!q;EqjG
+$gRk_UKJ9JH}xPhEB#h4sdi~GlVDRfeKvWq~kKT7RY2k*3xr5l=En{Xh(2SX!XqdwjB7zYt;8|}u{uW
+g*LU|!)aIrufqRUzCfvMPPKd+e-oYNg;*K8Ab-63T+Jp!#!!(6VUY-;}mJ<SGvChEd+M6e6)Z`4QKy`
+gDQDrh1qgX4p{?sRxds>o37(uoHin!kS6opajdDnK>^+3IQs2#5nkuAr!rkH3`xZYNy(m`B?z8I)+Q{
+v?`^SY<$XzpEF^IJj+As<COziNcK-X854wg(yI|K&huP<4D+8RMdOuust*CW`F`|<U#PHQWYInB#ixk
+rN69Oh2-6EfTI9&hPghHhHbB>$t>H+9J5jw$v_<GHvj*8mi>fH4eLpMPm+N@6$MonaK%D4!bX~2jnlx
+Wz>qJCKKD7t#(N3r3W(e<y3;~(Jzk|C<#5}==c|jc9r5|CU&x8DYflUFAFtNXd(oIM9cOu6PeVA*|Ub
+5Uu9`gp88wcHepEshW{SeYhMYu!h&UAkbNfbJlINzX*5^$BRX+xZF$c0wZoJJ+#wAV%kHng#q;Z7g1^
+M=W}**o&Ky={w)+>tZ8vxNS++-#iubzO5TG%MX;D&ua2Zlm;8C3f7xo`d7}vpR4Fi+;6^+@}9I4jpa1
+6iFn#c2|h~GZ_4M#0)9J%aP<Mn7|SI*W27rv?RRi@wSp-k3wo}*jBp!{y0|HIJO42@gjqaIdt)Twvgq
+Kz-}gQUCG)aQYXY&j^XDCZ4|Ov{kiK{L^@@_Ij_9P2*iuUA&HFKY^6PJY&OA%&k0dF>$c-0B<i#X+{$
+7Nd+g%|i3~l?%67M5ZveX1Yi-b04G%O2;t|9fT2H4%C;$T`8}3}(Qc=q3<cBzsfrA#Sd6i!7^lm6%)%
+QiEQve;aoX$|ByP}vAaG1Y&YlRUBXe`FH!*x4~Sv#%kRj56`wFlb@DcHyup>~cgZ3k^DRmi>!e7m$M$
+);=i3cHM>!C^3?m=_G>zAB=8VRtZ8`T2Yg&(cCao0vu-YZ3mHmv9S1D_7SEfCBO5=&k@>IdvYkcSoQ?
+*k0S^Jt8@5WBF2_@2PgD0%ojT58XG^!=qN0ofdw1;rHm&Lp350>zt-sPW39$wo#gu*nRScTgd%CY*}L
+2qJnbuML}$dPIyGY4o$SW;*CV!!%*J|-rF>%y4r4gYYZUrL&yAw+Bb<D540p0QOp{QUPB3CEbEoP!z{
+t?e}XUny|uqL9PM+~>e`{a8y;+jr;qqrrz+a~MmHF_XREBm+3wmb4HMJEqG_EZ>6KM|AD6;Nsg`1D&o
+`|NY<=9)D>%Xzguv^pz}N~ySu`=m*dcE?@4xuPVJtNC=&6zu&n1{&Z2N6Bn;`}7DY)b8<6fk9_vG&kK
+EEhiIxpu>tx^rWia+soGr+;$VcTLTsF9dioGjLQsC;G3+W@cH$`WeC<ViwqwRII#%fCN?>{AE>MP0Vi
+NamfDN2WY0b+gDllg;ib39at8bI$EcB#wG^716J;pG`g8%uQyy?t%stx^PkhLsCyG$5TyYJ!lGT#G%T
+76@a$pcl+j~S1KR17DHf$0dCSopk?4sITN9>PRK6TS)%59G`DwiOOoAQ$z^+a<eZKIc)990R>_tli$B
+I5tP^ipoPX%-3tCAXi|LTYpi?<}7A`HZ-K3lL4WGB%LQ0#+E;%^Yvxyw%+zST58}mRn4eXnV+EnvI)Z
+>3ND$^l4Bw(!F?+`LJNmy%kW&w>Md|~=BBN5Coe^x?!(Zx9I>?+#T+a}6cdY4B{Q9ABzLU(oiGva6aJ
+KtQIjqbC0vtt}ttyUrnI=2vl6@o&3YO2^&+!jq!toENn|5|<8Z_|^JFtyn`79yRQf|NO*)xf)Zs$7Gs
+@y4aJJ&JOX+kK+PCH8nkf4?}DmaYJOfi;M>;qPbhtn|NCqnCG#jB$4jKfWzKihp*a-?4i3FE{WDasxf
+)4;?(i4e%-F->MtXAzmKl_J)7y2w*aME3)F@pWP+=%K`k-96+N^X#jG2lrLY(>(|sf#W^qB3xi>+Q!)
+J<dUFoDi^qDKI$f1ny4*baAX(q_4~eh$<n}Ed@><>U882MsOYhdjy7p|m&|zXe?EBddcRb~MVW5vX*Q
++?oAdT@3kj_>-;B6a~?5MFk#2defARha$FaB1W0G53;)u!d>;<~X;G320Jp@YjhllW;NN_-fhC~0iyE
+qvBx_~N-)sH$2!Do&T3{V1DAc?|!^Y_D*^-sdG+Bi1*jI)H6pK9_Om9Mc$iXzL)_XJcI+@3N5XBD@Xe
+!LY?<n<^!b@Zs_2KYPsfQmiQ0;+1s7%Lkj<HjE5<&XG^s7(JHgJKQN-TgOGoKOm8yu}E~{x2b*4@3d6
+T-m24AOSa#~?h4$mCGKI({wuvMeruPET;aM*;zp44L!@h{Z%c5{qOzUJ!=n5LXb&UytIs}rU_X}vNjl
+}FAue++L9}(L_ez0Zv)aO=O@V#3wOFY^J+h+u2grx;{_@2`WYXb8nE=>gF_R*^l|P|(k!EstK<~o*{e
+L~;+gE!23rN(ZB1~RtIbtGkzbx#z)<V~3+*Z9l#oq<<02x!P8&(Z}OC)7hD;Bg6?Q}3L_@3KO+d|+I^
+gT&Gripmmm6^rbslx3!GYQ@A)bShYw*P`5A4A5cq3{`~tu}$wSoV;zEu7#LTgVvcyrsUdSjh42u!>pF
+DckNb+bfG;g!KnQK3Z<L+G0)X#BGw;nTpf2a{!leKjMH)Tk&se$B56X;*qQl)0~VIn~j1Oue%rX5%36
+VdM_c*y6+G`o8KJ;uewd#QzZDY;#xTPsfbr*2x{yRowV$-go-`TMY-_+L#dTx+s7!}x6>Y%$n-ye)6F
+fm9U%tU%C|D`|Lx0>^h!j~I@96vcM8py{>K#Xv$Smcc_$`EV)R0=P`A<1_a4Qg2yyZ~mT%~XbTy_2$Q
+_s8pYLTP)_AuViv`v42ECw<8#I3HIi&sdNU8sTntlePJ!={}Z|<ydH3?Ygr|L0=p*~w9+AqaCjW>@_2
+pCV7N&73pZY6kx0_;D)w&49O58M~+YU>$0T8C0^&{1%MSSc4!`V!UP8sAJ~l&g4y@6WAkv0Ou9$FF{E
+igoZ1gX+*N{WQ0(89^dd<EtTbm_|PICGYV>QNTHh_tm;5E;p&>+ZJw*lSIE5QNw7O2O)B6xSnNO$v^u
+6uQUhQM)D;KPa>tL9rZ2fQx@f>r~HzbS)jsYU(W&+fteASBfE9yQ8mr$&}ltVm#HSfK)y>jP&}$lnS7
+mdV6wh}{Z6O#7KeIYt>@~7JTWSHGRB`R4ex|sixZDo6EL-O22~aHz1>DLG^ew+^_-c}cmyxy+LK2<M)
+p1CY2DO~tw;J;@{X0h)uzd(S99EK64gp1_(r9XR4&mYO8utBmb_b<QO^*EoaH*SpfFeJZgIW;j>>6{Z
+z)-}887h;0zIQdXJq?KQ}WL>5VKtYM%3B@`Sn?lb?$nH6{!PRh6#Q4!%r%wo|{ixuTOHT;;t1vwL^L|
+IEwOkg>eAF=pc$#pyyFEnBa3tWfkA8;t6f%6(0rX{nWfn%W?D(cvw_pdZpC=!tj;`^#)AplYYaPer*A
+#6>SN8jSo)}?1Epd1+Al2+bB`RN2&ybCJ*={zA++z!B-#FWjOdAvaMni%x(+d*DAgPLC5p=MU^G9m-F
+8Zh6>x50xeGsoEJ==hE<NKOQ>BjuGUaSZ!wS6q;}{4Fj2-PkInNCH6L}yXR_)>l<JwWOMH*H^(3x*0#
+9E5MMq*D-L>CnW~1^DF!(9Q5u|EcXj#DUA9yD$5fgnW({06?5F*GZ7?c~xO>p0mjzY5Mt&ebqJ@hr+&
+WHE-R2rs9`06x>VJ;iZUfx2GARf%pIkTajy-epsc5(YxvCxmZ+2g<=SfgK}wb(g>dsUjX#7CiSxbKkY
+AzHl{67%Cwxsn_|K`S3VZgCzm!4l?%J-jzl+&&iml>dlnCT{o@dA0%P#JzpUiwAzy7d#5G7>S}ViZo)
++PzW*eA-8o6Bbm{l{|8V@0|XQR000O897^_9$SS4dSOow8^AG?48vp<RaA|NaUv_0~WN&gWa%p2|FLQ
+8dZf<3AE^v9xS4)rEHW0r1S4>qDm9~oF^k~2Zg6*OWl5T_D&7m+1fooGX5t$N5I*AeVzjua|_>jFt+v
+HFmc16yE!;do`hmGnEU{1Y|I}nGyQwBCnn-bm#`ulrtL?>BW!oweLZ|dt`Z?0dzy8WeucM|7kvxdy8T
+BE(>N{=q?-@dxNy}7#|<Ok05QSnjwn;RauG=qX+kF6I!&|nnsPsY#V_iQGbG?c{*@aMEQozz`$bnS-a
+_~ACAOSt25%hes%$JUG^TJ+)6^T?exr{L_K23BD<+q6t;xOba&0c2VB5(XH6NpWDbRyDK2mujb-8vP_
+YaLBb$#R6{WyKB5<u8tD=li7C?o*h7m&Au9BMddwMRPr?L61w56(Ctf5UI?axt<ZhTPQVP9Jx8~@y`g
+1k;FrdTpi>rRn-Lq<wx^<kpLxR&C{2#CEJWep$vrSh1a=l0^mh(Q;_<eVJo4FdzJ<JLJ7!XUR?x7GL6
+_wA33o55`2hMI6Pib`zvibKr8>2MSB*OZq2>1ogXA8HV^3#|3!Me6tMQnf_bqRru7wn)uJaH+Z<{hX=
+mo;0%H-r0kfleL!4e$@rK>W<c;U-%m3g$YHChpPWeVN`EO;nHD4eW-XFplh0ESVgFmSeR!%JVgD++(@
+mH4L(?@d54u~vk&m*q_+JMWRw2oe2E?!HlfW<`QlH6UX7WHn7`%EdLolPAm3bVW5<ADDW7>~nHb08)d
+{LTbb0hTFN4&@X_u7#)qhmq`$f!r(NnL)@1W^{vowU5=YrWlkeo7puiOwH4BE^?|jc^^m*Xa+ITOYKU
+<vQyX!J57=6dM?2N0l3Kc)n22n3EL{d%*jg>Sx@#KEO-PS<HBU9`W4~pF*P}C1h;p5{s2&*hEazbm;7
+JZ-n~mkG!`wi?S;)#Prs6Cl)k*Mn>%wwOmJbV5JMJ*ci{dQ0;hy<w(M1>4A}L{lI*M%`PF8VqR5G@th
+{x#ts-<-k?O^ca!gV=e4=P5<^F;^-`N+u<D!2RyJMn=_>uX>{`lVNq-H)K_$St;j2O0^9+ryBzI<ma8
+JDV7%flV$R^k5iLB(@fwN5SS}6>q?QWBpDF1M7K0To<Yb4}<=NNXL{X-pH-Sv#Cu1S5f5@@O;8BX=Oi
+$7xQ^sF9rN?vAWU_aD8H`3!WXDtZ;#R^iaTe&~lka@`4D6ihUW?KOSuaSus09FDc^-z)eENAjg@10`j
+@aNIhq3pX)x!Fhl&ZGts4x-Y~ANY^dQ*YE#Phwx#W6-2G7$7d_cK1lu@%z*KdoP(lVs4Bkr-Eu<$o=s
+MP=YgVhB65G6I+b!n$@<nm3S)r^}-N$jE3u{ENS(CsG4z;JcjH`dyUHq4p;_~(MWOso@{m#a$vEwvKJ
+Ra#2n=BR@s|ITegn>QN@W_#<Y_9R`-*eUfqVe@8e&y!Z1O6oqaO!eGujh5;6LBD`FKeragKT<TqLNG9
+3mH7YQ&X~VoMIn<bxqA=UBePnyT)jRtm|w6@GbO;?G9{#RD##f2d=_%&fO>OF{fM3`&sgGY>x-2!^_b
+QBZZzx-j3q8G>C*P-n66a4SqY%m_^}Xyc~UoGF~Nn9$u6AU}1OYx`d^@L=^8+VKH6~*-l~oWJO9PQTE
+mDwSy&QA2<2f;aBhZN#~K>IuyPGq;7=L7=SuPoWMUJ7~5!axP(3mv$xw1TeLvsF%Z<;7z%pWuSUXs>=
+c%4J?!SOJ@Tvw%PHO{uJ?6MDz+<G{^%bzNFD@!NS}{;foVpuO;U<ZJfBxc&VK<=O9KQH00008031s8R
+-7m?bM^!P07(%502%-Q0B~t=FJE?LZe(wAFLG&PXfJbgVRUtKE^v9RS8Z?GHW2=vUqNUeDix}bw&)iF
+8kVNpkYUY$CHoW@0xeNCJ6RM&DvAI7j_;%_JLxt7Z7lKbxx43HNVX%}BXJlAM|3~1QK0(~*JOk1zwhD
+eMQhe+zqJB?41%&AcR5lLTBN91&sj&T(6xTe(VwJm$cQ%`@p#3zX*dWnTH)XH>sR_rdn3`&M~C%0{5G
+FCIMRE?JN;@G#lbspCttLK7j=g@hc8%6JPnOys|y5Ak|bX!A3A*C2qUiK5bYaUW5GuBM8yuizcI$&Al
+%bEmLwDxO8;uya*ZS(qo2l+XDf7NmqxdOQZ7aWHtxx@P(0VT>ke7r&@8X1W0V>G0rA?B-UD)96C@a#x
+Re>uE$azt;m5XP8{Ao-0(~JZo;ty$uoUvPEW6UF$j&X^6U164;0ORwLJ$zTgWvD=Xr%SdCMk<eB@Gii
+IWku1tfekrkzw^Uusnm*d|HDMI3W#6+m2xo1FD4<*D|q^ouiOq6Yq;lk2;ceBz#v5(rp5SE}FQV_8R~
+Mr;R-H7HA-?F@yh5d@5`W>SAh0i>iwDR8&>!10r3U&q{1HYc9Y3HlNqe%C+r-DVjAZRr>RJMpj7HWN8
+w1w5$`h@(m_MXNkz;M68fv2?T-8{0yCeAP}P^vsFYwVS1=EB+M40qAFvb=c2L_O6_61RN0~^?Sx6qmm
+CRb)KZ(yk%BEFBe@1F)&JQHS53824K$xxx9rD49xa*_mgaA~cuZn>{3%uuBknmRy(sU;DS*p#0sb_M3
+{=Izm7{kom5yfU-H(=-Rgg_FjeShuDL@m6M@vjmCLRwO;#UGQaYx*kgVENY%|U(B(;TtQH&P2;$o5(E
+L{e@yC*NSx&|pDcYA@F^ai1M`&fA41a>~$6Cwt8{lM{AbwWOk2$%(2~iNzF`@-?FIFBPnb%4}KkiMK5
+uI7&|i9?v=Qw6LLtJ5SG0y~F+X?4}d25g3-F9a}SE|HX#gZx$FoX-}*CORH)lnkDT!x1{ek9kv5)-I0
+cawwM)&E&r2)m9{hPUVwSk2v(pn?w7!phP3zS1@(nN9tj0?VJEw1!j1Q%sN9TqE=H)?f+K1SnW-}$_I
+8G=aqN{z$Ir!7%x9Q={>M1nyac3C_;GzSV(#R+n#-n&{BbHQ#efTq7@1(hSqp5?296GFCoKSA79OhP=
+@brC&PY7nmbWsWrw|D?ParXXO7wn|93NIxlncla-1E899(k@Sc|{9mzx4OvGv?&y=bEUG>vgQ~h`T^O
+7M($FLg4WBw?4V6nBX+Q7gWa3!yTcjPzk5Os@h}PS5>k?=m#{6c)Q0dHMrQLJrwARCEdFV8}A4ig0&M
+jN-bg6O8ePxtgdSIrlU(SO&<1m3kk#PYxYPRpj;3&Yd4Gud9R&@Btw|nZQlneJxV|N>{;NBZPVmNxh3
+^+^C&N04Z6BXvR7(fSsm@u)eRIQZVu=4&HinNh<YoNhYjoCP}EIuVz{eu-%F3=KB0h<-1bYE5Gcjns~
+!A>O>n(=f0<uix_=-sP`J&&)kdLz{7{f*@_L^a&Kfp=ku>YCfC<hA&~jsgisZW_KEb+}HsECqN}u7@y
+ey+9U6~w6*RiK0JnhC_f6BtjDu$8vA~oJ^M?!j6J{=TLgZNa}g!6WS`#MnY4^T@31QY-O00;maO7>R1
+I6R}Q761UjX#fBj0001RX>c!Jc4cm4Z*nhkX=7+Fb98xZWiD`e?LBLA+eVV#^(!Xasu<MKJc+g(n+~_
+)b+mh~(>f_hzN;%mMMLCJL<|C40JP23>VErm_q+##hn%}T*Vd|1Wn!k$-P6-E{g@sk*=+NoV&%R(SQY
+t(t#;X>%JZ~jiRej--Fy)*)?D;&;-Xx~sp?(sHrsN<(mY;D1Vx-J;UC$LPf1pZu4=zcvRl>lD%+3PkI
+AAMu{RYj;+vF@*jZA-^H19<$+I{evCI7yTHj^xIAV*qtPTXKvBJWOA}=KA@gh(2LiN1HhmrW_XW*KjB
+B*S**q0UGj2IBjmh<BFMq()VRwFp)<t_zoie#~#V~2zRW;Y3NH?P)w!xi+8r+<9)?(A}Yd3yfmH*a5^
+%`gA$^v|a-0ttPIzy}AvV;9vvg}1V@in9eT8Ayng)VAcSBujAU&{}YouPUAaBoJJz<Ls8Bj1K61lna{
+)!CaLU3~NB`gX@EXgGCybC7b^tsip@E{sx1=D?nZ@iey`XfU2C`^6FnpUa?q`j;pFjZgv%CH%T>y7Y^
+vn`MgZ?s+`Y(*3|&I5I=SRtI&zu&gW6d)71!HoM-tI`5m&yzh`grj0^hshcIIR0Yt~_`|l;RjSN`Qxb
+mA{r)os>1ggWQqzzYUphQGz%GC|%?6o16tnjVz9L6};V=LLWnhyhte+930MJ8Seg0pXC?C8J)#}R_Ke
+=rInBu@-lqE`wdWIYyx_M6!PrX94uglUIq5vm-$r+?oMN6>T=FFxEB`403&_1@f?erS$aw%gqBf>7vT
+j99r_tchq`vYR|zj#yH~X|iCvT8tTJrUlK`@kh>{08=qMO&KWp9#&q)cmh8Qb_05u5wht0`^#d--y`*
+WwZi8=#%U=V3YO)tuYit0J4y<g)zFLE(#T(qMX0h|w4l+~fJ091a4Hrp4oeHI;-9NA`;o6=SfnNDG!h
+wWv{Ez=M{LC0iXOzsBGftu-D!qvRP=UnxJ)+97_hSoft<uf9J0R)4UCi*X_E0~Od6znR5t+jp%K$k^r
+IQ*g=o^u(+aFXe{2Q+$iW7*Fs2~7Fu^)qaL|)R#w0)wS%EetA6mpN`l~f)<L$ctJhljJneT4W{X^z+R
+m7VX7OA@%3(powu}E7GDTr=d`NuAGRS?~{gtC$W#h-xU3|rovpM~C1Te>ukw82b`4Whl|TJ*{7r=izu
+w`4Cxqid_Ij&)qFEkw{R(PX<coidbyc;4_Twg7MTfaf}3$@TCDVhn?k)gn1}+6-Gxv&*s5h0?4w%#)>
+y7A&5N5G~={_(4u5iot2X;X4gDe%T<0{X1}2w<UTTU{^Do$%{Xovu%u83p>6PJW&Nekj<S&cLW~Dv4#
+E^o+sAx1fHK*&rjg_srCF6o=>dj6L@}RJwJoz@2uzV;Q6`r{2ZQNSkEtzzQYi5c;d7mk0&;h$H?W0V)
+I@I<>K<c&Q9mAE-%mD{Ndf@>4h`w0a%{FRQzMfb{S|xD~HYWuiYMM6vha9<S)A~+^lyg>^2WJL}L#b2
+I9llL}6ESmo2S<v;o+ue%iea?Q+A%UiH)NZD<#pJ9f%nc3-&J?C{RGogwUY&3&|4W4HKW^{Cw!JN0j?
+U+t*auYcS9fsXq?sNlo{=KVwS)8960?%Oq}D{jZ;mHJ-W=Oxh3sTV)gfI#6pVT9gxg6SFQge0}>2Q}#
+glj_<DCl$04PAFyn(ROo4y4VS&l(G|0DPbp|CuP)<8jNR9F<T*`?N`~})2X2s>ymK`<M#l4qu20~QA%
+7;oA?74#ygVAU(<OCkm)%X?8;=xiY28=MhH|gMKWX@f;sVfyu}2H=pG(;{0l^aOT;G;m!g4?)Yu(*I8
+?M|u&9<sJQBdi<VE~52!1z_Gk*7p))IzmKnNpNR{^xlAsn*+DB7OX!DPhcLq4rTnxM-EeqIL_F_jN^{
+Hy_TQUiSw;8n#tKJ2pqw<_kTu`mg6E2Em4xK0B6S}}_ce{vjPT0|o?HjX9%rgh9w<K*aRfNdRC)MoGK
+g~z$kIbZu6&2ts4rib`fZ^1v(M;aLBQI6`o;vcFcjiv=g>LZP!1<WWTDPRkv&_tnqU0@TbdM$8D2Zi3
+X04fEPO4kA@wNGkXpFvNQy0ricy;Hi@0;rWvDOwAx);OhQ4Y0!o<-<SNDMS0714CQqk)^Yq($bvH$RK
+(>X#cD|nI4@DnezV;w)-nV#(TA8uo~RSLxJdM#9q+f@cs^iyT}k7-VcyqM67{Ss7;WB@VhPw@n#@U4x
+3zz9H9r7c@#7oKvI|=_)l3P_|IWSi17!?`9i}wUuu6B@kfiaBoizX*2V}A27}iHk1L#b_6T7gi5&2V@
+xSbnk8#Sgiego4jD{lyOtDQ~aJJ>eDlay1CX)0Dqe@7>J3E_Gbl1Wg9%4unYP`R+9MwE;k+4usPQc4{
+0E83NHC~qSPcq;ADXG?irZ@x1aw`ixHadDvV=G-BM&@=sR)$mdibWtGE)uvyCLJ1pC7oSST3WQWrG@Z
+MCy;|gOqTeIiP#fJBALpwp&8D{cs>VNLC8dHLl;tbmo?oMUA{lr0Hz!+`q%F?{+Rq#BjUSRM>P&xd*z
+-JV$AFuzJQz!$?vk)w7+(1;=`T7$0HXJL3FJj<RhY0(;gx`ctOwrmvI$$tpEay8tI~vE};#3i#;B27|
+dV4PKNs25aI8rk5cD?rq0*cR_kWafqCnrkpazi>GxFGJnN&YdZ#};T*DYr@XV&z)2+idX$;cywK&PhR
+3R}-nNL5*n{CQnWiF+T5s@*mn=C%e$Ta8KoSrPV#XUgmUJcF}!K+L^(F)OP!{OIPZsfrtl*g3)JKulG
+3-Hm4+ua6?wK%V@VCu^hL;}Gi<(k!NU29n!7{iLaXci$FM=Zlwh8L?;(!2YxpN1_C?0C0@y?{q|tHBR
+<ANc-$FlFF)?1cG(hLL=Pk?3J072lN6@V=&ixHp)6(ejQcl9^F0LUbfv!?;DZ9E%nirO3vKXf!d2Y=0
+u!Z{$j)wx?FxL^Ym>MipDg)@Pzs1roCLJJBkG2HE)B<3MA6Av#1bpvEAFr5%6OE(fQbeAPZtj^nn-!J
+Vu2dYQ^?ggjDObikIg;QmAv8zLF79I;&~G>!J%MZOeshuvk!J9PYVJ2wktWaUMW>N$UW%QIf!TK5Z8$
+Qs&yn@!imCjRa(b<<r1_SqNK0jccQ)wK(@-SP~T%AzXTT=xx+d}iIj5vH0D^jmgxbEN)`;m>8x1r2l>
+)*^BCp@&avK!h&1g;VFS1$jgTGRMPq8h93?N#L3?6tJtCz@&qKJde>dRLO`YBLTW8J?Wri4sbLvv-%A
+^16B)xof*W*JH{VvGblKF+QFGPJTfy$OV650>h2c6Ngpy3kIuv=H0eR<SqCL`dZkIJUDD7}Al<~i>ma
+5My)-ek`5Iyhq?_3D4r21OOw*EEx*;V2nsrC1%~3zydC^y^Cjqsdg!H=41cSM0Co7KjG(};n3^CE&gH
+G4}qfZGnDQy7_H4W5*VAp=6PZu>oZCVXM4b+e&(`O1Q!&|2*=~?jO3}n`T&^o5*L^;T_fFK-t5?vcbI
+=5;h(Xb;qM5xlm^}oYr8X|Bu82_3lS!Ar|5aVhPHV8TFVfbilR|AjYY+nPP9cM%Nz#z{R78B9|RRu0+
+=_ZI|x~d$pHkU_~AgYX?#R#1vq2Dw|zp0dEr-X7|Qf=_mE);I?#-vm9>g~lF^1n)Qz^XMcZ<l)FUp-{
+8iLuBgrm7M}Usv#eY=O`Utb&8>w2DFO^mB=6G>cz@N9z)KjzMRvye;~9VE`C%znr2PTQ8uc!Ryn2^$O
+e$2hQ>wL;H+_uibSsOkN#b2RAJT*`zPB;~vPK_C+@7f$Vu-WKVh^>-4Me4^<y4r6C|Guvk5MI%>3$At
+I5g3vYQRJOp^B*C09!d~gsiM(nuBfBnB6#Y3zXE<^sg@-5dg|CHSp@lu}M%k5@3#$tPG`y2ii>t>M-4
+%xMAJvnL=p2_adsM<UTSl5P-y_5OM!Aoi5U?BC>nucu1ul=Ae$V8j?bD8{=&+v$FsBKM#8JrZ_MGj78
+Rbf{R8kM&ST3^ku>~WccafvI@QHnfKwT7sie7x0)FDg;KuNzCU3)Y~v1ur=m2`?*GH&22%mc~*p+2^H
+~RT6{2DcfL{t&YPQxc*%g`(V8aU_=SZQWU~vsV)D!;9GSaXiPrD#U94_nQr|wAVd?5652+?ahiYPMbv
+hvw@nrw=BuPAD>0LYlprgugsQ%pBl7<G(V5|&0SzNGpc>g@%Fzi{Y$@PIq!VzGkiSM{f7{xWLnTO~1#
+tq7)qh|cNe7(y&s)$PzJ$Gur5p?Ekt>(I!O(W(^qm*mn-e#t3>W)^r%Nn;q<Uf%1JYrcljoLjy7E{?!
+MAO&R9<QlEF-UQM}kqss?L!#0IAATJI@iOYL%LL0bK)XS$%4S^$o+3rKooNABNQRr%wDHhSgQ4PWT;$
+Rn?|;^xPqYNlgk3Jj-%ZD<TcUnaWc)q6|aZq76t^8!<Zda8`yyAj-uB6eY+l{pNo$m(lRvlQ{`-LzZM
+ktIw*TBk++}{KMeJ^ER*E;28*>9B|_{I~Iq|gMfu0o6Q6VR-4Ue#=jOuziDSww&~3x$*O66vgjDBaZ7
+V3BdG4R-kvc!ZgXC&`xBOz6ewY{U6!V9D;RBnaHEzcDAL`AK2*!@+OxV?gcYluFo?1bJq2E6gJY)fR-
+o~<Of`(E1wtpeRCoNEj~hhsKm$8c!2KDjU4eW!L#m#kfhC-b06!Q6JKWGUA-r8Q61v+$k?N`%$kCA@c
+r>uU=4Nm$`H|Oa4(<bxBo~hysuFB>vP#f;+xYB@j7_}xMYfo9u-eB-iFq8X6=<A7O+<t;hV{^iv2(&{
+O=g~@`w)|&07`N*vsr6AM57Z(&4hapTsusw9kNDv)0HyroQXTvAk|gH3%Z_L6+5b^7>0NiN3T}hoO1w
++ch@7A8+mQsu6k=66$&ihRda8>gk&rZ2^aa6sy>XGn0hPVc$0tR%kW_xT`CJ&15;h5db|=5X%W8G8j;
+piQ;nNi9eG<K%B>=?)_nk=tx{y*=6P!sk8VYX8vu8gNPS_|Qy|2}YE={B%G&`tymc-!s7N=YtMpxlK&
+0Cpnc8|{1*v`(G_ECL&oTJ%Fg8Vv?2WyE>_D7=aD^us#8%0&D;$1LxZj%^59Ni0W8h>}8>I?V(H|7qc
+YVj+7kOy$V&qI!sa6?H;2t1?`OO;Mum22PX{lF<hM?@DezPg+S5!ID-MxOJ`L>Q350>QMN=;zDj_UH;
+rb%UIx>n>rB)9Y}4=U$@P@8bL5~Qw~3#!uvHXzKJfQ1>#vq3!?mzXke8zLe!f>{q{E^%HFBAi4N0epk
+jMk3y3CZ;F*^(fCC1!&c>E$Yv{_k)}al|8FL%hZeap%whr1h3~_`VArY3jVDi`lKt~RW5cNc8AP;Q{2
+<HEj;(|CA%XER<)h|Hx$(?!9f{Ig7^>I?IN{j8m8*Yr`mjXWma2`m=YDD4{3;bGkAXUo8_$4$NxZ#R3
+{krqY<nj6t<d!1~E5}y1ddqueCjEk+rzg`~S7B-kqP-Ruys-T36B&Xj2~8ZTu+@oa-7<`M_6*h4xAO4
+2w^t3@AkZ#r_p9^543$opr4modQ&GGBK0cM-_eObR<sgOeCBR53O_YHkYdFkN{6V*3~Apf~XOr?@L)m
+&-s*;GJh?Fg0C+w<iLuZmtGd1uA0ezK_21HR~ge^HW%gTqhJ71N5QVopj=}2CV|;v?ZB=Ukf<BX&P2L
+%W3DNTSQrUj<aQ94)P@cy>IzBH8P`C=cU(opj1viAA{T)gA!xh4rD%%<NF}uB=B2Rn*G-c8R$1h8Bvo
+Z>1>>^)XnfK{-X29b+eS#;dm`QAlLwotf%F6KEG*+S|9n4afX8IY<0T+2C=`F(<9+v<aGyb_#71Bkqu
+SA81EWUDJ$clJ6w?sG!3x5a$Dep|yRN2wb*Ni>+48=O#A`K~waT+F4o~>gV6mlJTGta1;&?1SVHCinu
+j}{27O3x%yY1kmDpi7QsO=bUk#BAQgB7mA)~3Ed=zd);c<DjBuFhcb<{BsyaDhi(-EnKlB2A01<5ist
+(NpD$x!xBB%<Z9$fD&lVB?ESV6tG&mO=LljgjZ#?3|ob}juUy=<WR|0O0lm*$#QS=GLd&Q)Ex_Xrvf5
++2<%f{3+(FxKl}%ixX|A1{$csQKrveP2;C%w$Q>q2n1y74Q)1oI437QpnoG1wG(3PnMzNtp(R<NxOy(
+UoB;9ibpT~cgoTE%0hR)u4CnZg)`+?5#<hk*c7b%YmLIRV%B%aGJTM|OA^(PH#rvWNY-f!i+)jLCe^D
+6|2|6Chi%i4J8E#v<URqsf$qauqdcyoQ^IBLmq_R($9=9n#$)r!*zpt;b8h+A!?^&v#-t|Y3ohotGVi
+1_zVyVC34@jsRQVaoo+CZNaW-*P+oH*fp6B0y^)>}dK*97Y3lo<xhb`Rj4Ig5NDC5Y_e9D%uv0<ID4R
+r>}oH`{~^JG8n&&7yJ3ABwOa6O7VeBHA4BZukbxdWS$O;YBvJ<xT`q4`V!QqTCm&%4rc`p2JT&D_f|n
+r0D<oxOL)Ln$U)>TnV`ga)qsXh<w!ijR0ggosNXVOOJY&qV^Jdu=Dej&;R_}?1<R#$_6A+#P`d=;6eL
+@kiW1>s@%-}n_~z=4klt_ZkkUOh9f`}Bf*P$MhYQ!i5??#1d_D8VqN&z1L4uF#=P#4x?9L#D6@LHHdM
+4I>`Q=XGx|eUg6zy*6v=)}Ax6JB<J*QHsNm`1HhRU5AnAHC)Af6FZNmfdps3ryYN$DOnOnrabQmRXI)
+I@+u_knOF0Sl->+g$-6B7Ud`D@VFlmBXpC04}j#tu5ypE}{i*Vp#;7Br3i-(+Y|O%H)Qc?Q36-%W9eL
+s_`cjKm@z5%xTg-hi?w=f5}v7ZD*Qz9xs=22BekL18YxQr~_rE(#P!Ija7CJa9hPzt{Tx?KfsV{@Nk8
+Q)g3V9O`zH?+mCwnyH?tI%`)h2gMQUF@izC)2jBwtnf^Oy;)m>S{^#Oq_`VH$2l}m`G<$gxK)fBbg;0
+f?){~Zt<9c}S2=~KlaNfkP5(HkB{)P2aS4#3T^#4dBRPt*fbiU_ucX+7lfAKs=z~Gbhm5cgmS{<Fmh*
+?{X%VWLMQi!9W?Alpa_PWaVVGCcTw`6smF@(5}xJyuf7Sw)WO!=mvI4p2FjJN1^92^{&09K!<4fX$)g
+q|;|cp)#bQdMAy&-#i;+4MgknG;;g|ARypE2^Ex&OEv%NqPUshB(&}sX-*;AaQ8<_Z=J$P|9yL_+AWx
+hID5U`lh)5{h+ZjcUNG@W^jwJ$&d8VlN9@DEFP+SYs&n9NOKt~bzeO`wnntw$&c=7trFXE(1iaCz|Qx
+o#P`$<<sP?*1bRDFVluF@KvBp+xyu&)(A<rkd(C=;>|dBvZZp(;+a}weL5wNhdl6jWR<caWMO-{2`Qz
+};A_y097JrPBln%4wQp!n!4Lb*iJU0}1o5}niP)h>@6aWAK2ml;P_Ezx<rcl)Z008O)000^Q003}la4
+%nWWo~3|axZdeV`wjPba`xLWG--dtyIBoq%aJ<^A%S10usvyAW>;Fs=BMycB{6Ro}!cqOe9F6kg3GqZ
+-NsDRK1l`9KUBj+cBL{BiLCB*@GChG8SInp6==S*Zuj=@5hHM>pY?wIh$^VN6cR|M=osuOuYA21iYXb
+opv5p?u$2GXU(%rbo*>|2JS;ntK_6M))~z*9{y=7+^K|TE-&0X^XWF&XtDR0A!`RVO_=k7;Rzupt%n&
+Hpf0Q2(X7NOTVN;CPe}0J=7xNqqp0B|=N&(iFnqoi?4e0c6ww;x1llVH*Dv8(e2nDuqM{4$fKnlar8J
+-T(3J_c2C~;hN=)S(s{m5K&pUWjl5dsyKvhy+lLXy^P<ex4Q%Od&R~qK!r0rNG1c%cRM(30%oZfa9#z
+_|LqLQS8CH0}HO$=N0+|uPP-$WLNx$z4P?{i9+=*tfcSj81d9V<7y>uMQZ$onZr=zOZe-i%!1eCl1;u
+5asIvYz!(MB?+k%iFkEDsI%FAw{+<Dy5Q*P9ii75K2cTB&DPV_yO9meq=RB<ph6lvu&{!x}qO0lrojC
+G;Xst!u=e+gjJeJK1A@7H?U`T--Lb67f(*Ed>9ldN+3$Y`*3sb9ML{YzHo}{KTt~p1QY-O00;maO7>R
+nTCYs$9{>Pli2wi^0001RX>c!Jc4cm4Z*nhkX=7+Fb9rubVR$ZZdF?&za@<C8|M?UM^dq|#2uaQ*m9P
+%3(2{KHPLfq39Vg*2Ah<irg@pz70IaAzpC2U;kypx-q(5c`^93v^%f74B!7dRWJu^K$J^eL3v*l*nw0
++cc>9*+CM<qXQtD;{u?M6MfLfv)yPTlt6Lx0;A+oM(6Y@*_N5y=myUp`IXx$E0v(Qib*Zk7y#O;qKzf
+_sB4(uaP(E$bWges&bWbz1Kex_MSEdcJ$ni?+C~1V6njJNf=~u@TGj-Bx}1cH5UtT~z#ZCjPh+^+Kp8
+S;&At-*4sJcQq7Dj^;-a;c}bi??t_A+H||W*@(LD(n@>~t-|#sJ{$t>6!eYgb9$3s@ADe4PNJKg=sNi
+lNS?3CO5m4?I=g;f30378JrrH^Mt-Ijhe}%*(Hn))M9IE+Cu)0;o;Dl&#>9KxwoS{oUyE9_<$@o6FZQ
+=hyBx+!-t9KmqE#aXBipOeXMGFoAjbw9<=gMqWiPsIfkQc;z;oA^l|u7rRdn6!rvIwh)yu%B0+Q==(b
+RoW*2X}+gr{x<dRr`)2DiT9$3)#cD*=lR*r=1urFqpfTLq5yFvxA!%dZPjRk~e#0A{Gwx29?|t3AbsB
+m(}gmw9`0tzqh}8TjETKPKvi=R%i6zuR?vx!S*?`Itm+p%&4;72U2<nEbHY?)!nYf5(rn$`7T&XCsPk
+*Xp)j@gq`Q0(64LKr<&lChDeBU>*l2{0C>EghBD5K+fU*=!jSWA)<_D?*)jMBudlt^62RM7q6dv`~4Y
+wQo<_*S=EcpY#wD<6n|gB2;O$_(X;1YoqqT7JU{>D`K#vu9&ehuc~_M2(b0qGd@Z6?Q&r6^j<B361@!
+p3=)^K=>S*2f+wSDiqnol{@2-LRn@5WAhMViExqh@Mp!s%qi8vKKyy_moKbsN+6!0uGdK#_7ZM12Y<*
+Hm1G+fcGfJQgPQXCzfzCL@AzkKoaH|HlL3okSsB+)LR7e5Y@<%HkP=I*RfABd~6_!d9J5=u^F1+pwR*
+?GGY_Sf`HE4FR3a4K5ti(1tq=eh%NUG0PekzxlXDpC?5{ob!`Q``VHg#ty9l76`>tG=u!Y9z3)cJ%@&
+?7-c$LfC-#Pl#$%V-oFf_EaDxOfpeHk~qQYr%FBlun^k-VqOQHiA6(%8KDUXh^AV4_5WMZmZ&<NQmt5
+8wWHAJi-8YDz)pLR(AT?uY5)oFytr{$p)GILeQt6Di+cxdFK`y>%1BpCaFtXzK%PqU!s9<~)aZtSe^G
+a$^$S@1pkTid#nM33rLzJ%+g-11$b&<qioOBKx9tx#KzjCI4?|G+IlzTKNg?y>^zH9It&Gv5T`b;x3Q
+;5LyMx5>*=$1a1gf2qKN9@zVkl7mlr)mycNa=#{r8nkR%0I{qQ*KmCaE0i-A`cod_E<&Mxe*U*H}+}S
+t;gM^@)X9h@C!_OglK3e|gdN_Qlh0^0WVVeSZ4yZ1ka#_+wmvk)Bsrb$k*HHdYexmu1nuQy)++{&e*E
+yH{U6e|wfc{r2T|uU_ZMj(l_a?AeRgUqhXr9~~VnaE3)^dmzRKFeW!*2Hx=egwT%T_)9P&BZdKUFe<>
+GM#!i~&=dfU2=ZSY?-}1M#mey3&{ZUVY}Sctl|*!(_axf1?4C!*Uoe#z0g1%dqQ{oW24^g8N^o$r2g#
+KYHmX!xlz=$+Q7<-NcO#To(kMjHgJ|0pH=E)ls+(xhya#vqU>~kQ9o)3&l5uya6BF11d7`0AL__{_@R
+P%&U1nprjQe5O&Wurle~TV^Qi+=alpYYvAe=pn*xfuY>$1;tHBJa|!f^(6UvQu<Ea(05l1TBosSQeC@
+l+1}qFAiOl%oDg7b{m$*_9+57h*=OCouHwe5e_(zTMj|h9;H&qS_|PWq#m*E1z4n2vQlg6aKT?iGi#I
+c&+i!mZ&;m*E?A!VS40{*5FBYyR(T(QWtu>GM;Cd5_~r-uflE4kABIiPGP!%S-B(TEb_RZ75%QQecrn
+maJU=>fd?DRESArQ8O)~aG{Ie33>XAiE{p{YkU1V{y{oF3Q-jA$cqyK+k-LcLeSGP`%YhD*kY562Y*z
+6;Yc#U>K^#4lD8UTp8^k+`A3UZjPJ+c1`*8&dN2o&GQYB&L9H|jCxz|N_8DEAAlzmZ^3$F;j9xF8Hb+
+?@U5-K_m$b=C#M((4?se)F#PcJ`Cds)-REv2;(ni%)gKuxs6VFIBJW{T8@-K5^(UT=!+nA#XqIl7=C5
+Z*h|Zc}!kV{Y=vsWmMa!_aqDcb`~nzHFLz(QYdzWLc8|!Vl2<UrS~_V9dx=M9IA_!6j`M>%9Z@y@+Zd
+mdF-24U73r)AjgVi2`oAtyo}e(J3d=n>3omtEK_VIleAh{`04Jjzz5x^T>E*&niuECBHS7r0~gB0<?e
+t`WJ(@qY~U!1{QBwaJTES5?rS*t~E*;J#KIAL4xp;z-0#}V((0X5M}{n)OFp8;+^+JcO3s-oE$&7{27
+7?uU|npvBY`PbS3)yI^<qrI3NDG)bcB5$Zx=vB6sR-QQwH!uqHPMG5UK7#yS8XKdn^}oMMIanxf|V2e
+If=0=@zn*Y;Nt2)gJ>)XOUh#(#bc2#6b8uOU|I5?}@lnBz31wUtN$;F#h|R1i^3?l;vtqk1vMPt)beo
+LZn+E*1^kI^{va?lv{NU5XEG;m7k-ckoEF$%(O`!7riANn}%%zCgFU_qHQBGnZlpa#GNv-7R{Tc1YWn
+)_0VDsVOZ`TP#J&n4Y#b-M|s}0XqlILG%>w%^^xP7_WcMXyr5dGdmN!4yqIr@SM;KC3;z|X>T4an??7
+C*F+x;Q<1gWjNG9{uH6z2Xpu;trFdtUt~?PBG{dVmj~>9Rz`;5$j;pfkkDJwT@xCZ43@#lr%sh>ru}?
+wnoL&(c`n(iNT-KUhH%(>X_`Jq?kO<|L*039JxIpoiMHSuZsHk24R|ObZ20ei{bLP!%yagUl*@D5&-D
+KUwbvc30XyzIfpD8ZpiYOE?UhxwLVV=Y@EfjzgP;ioLkoT8Xb1zmh%+RfyUA2s^1+XnmU+fVpSU`v-B
+J`C}(Ttp0;_oziUsO9Phz%(X&9%WK#bq?XGnes%Y20ja@w%4od)W$#ybkqhPA77~NSuitJ9Y`UpMqHE
+UBZt{51d8$ZMp2%C(-x#2g@zwbds}jhI*!~7uAkdlFeG@K(scxy25^4U8xyWR8^$8Hlo^x7W?8l@5(=
+gh8W)>b&G3fIDaz~$DnwQi5%n1haeGxAd3$rJ(t;=!YUKPi{4N#Y3yVVSq5-q$HEkWh9*%0*L{AoE0-
+cPTh7+atpth~XmWn2wfvd4cn@{ScUTO1UhP5mPzQ)tNv_&;KgMxYRk}(c=+&NtqCX5S14V{2Aj4`@Fc
+4Ft0<%R0$`HdOR*cE0g$;e<MJQfiIvXl@WLdp-Scx-Pe7{9q($t{z5=-XW{WB^@P@JrO?A8e@5Q>@SL
+;2+{u*%D+kddk@6cxn6Ls{7$BaCEuT$U4)Sc2gMHAP~pQZ-VfLMb?Bc(R`*F2zQM6%e;F8xlu%okTcS
+0E%Wn64X9pFoPC3A@QC?Pm+K(7^eFLs|EdtVl;`Y$4kVRG{%?&HmXyi*e_#BTdRH#Qb|eGh2JE;1RNu
+PE9i{2aJam-EGacssT33^e&P_oK4!QvublKrM!k1jX12~UW-a@hG-5Kz5%x#R3dt<Ca03F`q{s};2-L
+=^H#0cI268oS=ILP25ukY8u)r|pk_7x<18Jq0>5;bq2DO(B3}Ax<Lc-H=-#~Q34&&KDU@!bjkvO+e3d
+zakc3qi65?d{1HUrwAO66sW0o_2jl7sX#Xci~DKlrRb*(DDzusSAXUIaZtoFx~R6G{x7sT@;82a=&SG
+v*6Ua!Y=S8it?d5WL1*u3f)6{^!^euzI$7k~SbG{$gTwLXv8)+sAiOIR8zghDEB3r^c4?Gwx5zr4!7}
+O^4}Xd(VnRl?RR4&1e;_I7$_A6-*XZ#h$BYFx$C36I%M-$nAfQBpVynujz%S=y9=2#-(mca3av_+V#!
+xQuNR<v5a(L_9H?RQ(-avCSV!;_4wyvQ!KjJ#_^MS=$Jg<5dIf*((PIN2_1Efxa+L5EcwOU^H1eU<Mr
+#i)5P&V&!xuezHYVZmtD(Wz{SSv6T8`X{i3e6Zs{$#W{z0CU}=7d+~)*JF&MNd_Q>wr7K6UDjKU#b%A
+YqCgdHi(NW{-jcFxmQ6w4e_)@MqfXX<7?V27S9uqs<60l}W3#giIaLa6qH+RN}Cqb})$LV=k#VG_UY#
+Fyw9i|&9J&G=6;Dgra}Apk}KCmU{)5n-1Nx5<<U$(-k8L`G!8Z4#W&nYu~BlQq+K$>corZ1-e*{$$ou
+5}Fm6{5yP{PlbC72BCn@U>eIPL&%mQ!v~)2fDcwh{9aUL(J5K4HF;&m_4Ou*f-N1?1x2mp0_oV0AbTM
+tb_tfj4yJc0mY{)pwn#`G!}rZ~S<~hRg##5)%Q9+P6rzH*3+|sFi8dINqU$Ym)95Soo<0<q5|-fHQxz
+d1S68%{ldk(sb#-O66UqHRUG(e+VBTi1cf|%bm(bP_5+jt)RYx&a@^DGOv9_~#f{G;>V&hFG)OH<grG
+grF1;?+UM@wptn~NQ*4nI>%AQ$a%7^II$ep(f?YFMnB4mzU;S)&Y6jU{zDY5Yp-_q5)hktK_JX|~b`c
+1cUJUXAg-*#QzA0luq2u?)C@sbg!AVUa4V1nsV~d^bsiJLSNT2Lk{nFbiZSR$`EAMM`MJR<0%<_3Dt$
+!HGsBAg&#mR)`((?WX7#Yq?@!HS@@xNv0BVeOogA)nvD!C~*$`W0g8*Y9x{vwy+E(YbgyiwqemwRUeZ
+CxP`BGQItX4@&uU_kdymZ(+(&|+L*MnKeQ`^4=?g-ZinjNKCQ@en8j&4Ppjq@M6O?-MIU#M=S<i5N$3
+)wiF%uo3>WUaj2teoU@soqxd`Fxw?KJ{=DXI&0B6L-IW3_R_sR9`WWJ5H>L9t-Nf+d#+hFd)JbD-o%(
+-}5H9M$tE(R(2gQ-M%GLmn68CYA9Ry+(@QSawkwy^KTiPuv?c4!*hIo&iGwwz-^U)XIU&t6HKL*mLsT
+srr>JDWXx<xL>UluBKh!r2_BvGKV}4yT#f!uwyPA+&9qt!Vqb9vrrRG&ebN&?5c0sZgLls0pP4SG_Vc
+L3CS4(Qi=gye&D|dsRwPfnl%ra<OVfiMFJDusqIN+nJ!yl1nmkW*aMNMl3(!s7`oE&43&1hmnjlUod&
+o+-%nWh;p#5GAHJyE)a1$@W(6KdEtLXe;Ms>D>!e18H;lVMWgH!sXEOO+DW+265J<Qz9J4hw{!}Ot`2
+|?wyeavAmCwbb!y7rF)hdL%w()bTT2uv@zb#m2@C2diX5{KrfFxU8%g&)%=Lp>(Bi_;76ViKz#G_4?4
+9i15{tHRcris)l=jfiZd<hIi5a01&YG^o$}oxyFS}>E0()#XBeBWkU)RBf7PF!85nps-F4PUXqi6-$%
+T=a}sP1yTOf#w*9oakdP}wcKZby>DGdIu{_R}JfHfgclih4P-%|73VC|Bl8^Q6Or=vC7q3xVrH$vaE!
+Iy7~)kK{TNI-X7II*EbW&Pl{?g;;i&$Gh6K0Ni2@P%Ags7i4Tho0w2op%V<uQImwneW&okH-fMO6tGD
+69^;_a@}^gW^b~$4qC*d6Bq`KECQ{JgQ760_6*fsR{~HZj*6|%v1)M9vabU|vGA~p?t#XQiDy{hAu54
+K=ZHjjydbNMEkJd1R`{+2j73_WK5m(8uQPH!`+%_Oe{7&LUdR41)X(C|;2OEppj_R0G!u`Z+GOO1c4T
+4LeTHJCB$<DL|UjUc|$9oq4p^n3LySnzJsFqeAh8Dn#R854(nEM96IdM^Nl*wlu*57!i*Z7D(ZR+<pd
+c&Ag)uV$g;j#!EpLXUj-H6LVLA(an#)9ATf#VgQ^TToUM9*k`Lt^xCm^U6oXYa~wgj??vmb)6yXd(4O
+<%8vz6%>-cHPIPoji7&Mb;@Vc3`Q5^JL5LaCDJN6>zgeNE$xM#Y%81%t}f=dndD&#(T&2ElE+ezIo)m
+9ubHFoFhziL53}gW$jH#fTadR>`WfQ_4c%|1Gx^3bvb*c5EYlhIwaH-AuH||m*SN6Y7ny!P-4b3r=Dz
+(qC`%;?J)tqTi-leBKt(~EKAzC`l;vI>_8TB-IGJX0y9M=9YW>+N28I7)u$G@<dwC_CmSP)c1VYP9F5
+nEC_19Q>I(`UWpsbf=q@8Vh8eZ;y5>EV2f?5AWJU`>hl=!F1B?d4TV0D6L&c>b$$hW;|6eV`-vyd@G>
+5s|`&t=(dt74D4Ct!g4zwhLVs#p&8`b%@27LBDR#}pz?q<l8FM##gG9y7$GS0hsdG@)d`m|v@9z`z>0
+w~DO`8U)}qCzTdX+o!HBjAh}(!us;cP03h}wSu31b{kfxB*d@Es1EO}VUHq`hA6<z=T5}RT%5B4S9Es
+RNwlh(0yX;M^dE@bDAqF!Pauo!6GYmklj+z;lZkQWgbs-fGD_jr{g#$p&WC>GKnoy3IA}oKO{JS?IG8
+YoBDe$GjRI2OEj=e$VW8@jH&AuI-4Ru<O89>aeY8+DWz`{Zwr=nUMm=kHg8MbMeNYeQN$5q}bX~qGmf
+-ke>mfhY8UV`o!<bSf`k6+4J{ImX85*V)FY*rIKbWM!P_oRK!3CjpfyYsx7~9FvoXj5?;5s>JQ+u_4X
+wb5imA<i(`<&Q~Rn*ti74A>%d48IywGW3>SNI3aGB$Jq8v9{1eK5&Lh)tyr7zjF2ggeADvy%cuCPkd6
+(*-&1MWXVI#gh5QkADvgm}oJHme#Nnu+v*!?Hng_Kt=`BXza)qBvS#Q;50P1C@0>zRpA}Xw6aD-;xM+
+H?x-+k@#p{ePq?*KPbSxdHEFN6NCN|xwa-Fs#{!Yt195mmp818jx8|u8BPwPdC>&G?V^LqchCGkIIuh
+tJi<0OL)Oei!%g-i=?*KSN@g~AUmpSi7+{t<<-tP$xuMZY($w*t~ZW%mGHJ2xfdb?%@NfS#^6RQw*H@
+uUFo5q9X92;kn8ri*h645DA3Ep9_m$J7g<tE+LTj<NoOpYIVJ7mjKsfS#RrvZ#D38QX}QUY!PDe8mz4
+L&Li9y-pe90#Mnv+;ToZhh#N+Ho;x8Co)@*M<-aE3WZ&EHI6`^LDl=KFrifw-l+G5Aq(}OhjU?yzx%P
+mO^_U4l7_uMbq>DIKsJ%EBSMRarH^Onr&^a9hlZUi`U%fBa=lkeSGe05IO9@%@$50bDuaWDc+(B2V>+
+E2rUG1gVLeR4%`2jgtpAg2JbA?7#G!~V};0m+C(-?Gl$sv%Lvhp<vJanmDIfqd)&&9RAZo*?5#{vOh8
+fj$3?x5Fmzikit5q2Y0E$1%2?&i2KyM1;Of+vVKZX97<4hVNZG^d5B5ybDusC|3ms3%q~qvGFr~(uiX
+ITnWUsXeb092Vtpq1suLEd^i-Gs*WtTT~URQ})<q_!IERDmb_%*$p=_-x03V1=#-oQ4qD@)u>aDED~z
+vqs#0NvF-`}Noonyhr_-bg?V#9i|qm}s|Jl^+6YA`hao60;?v1t#Et&xEU+#;yhmgqa1xyWHr@v_Y<}
+hX*Y)c_3`4=#;HvR6ZJ#VD4}T8Q4#!#z1jy(Jjg{$A!r-opJpM$&CT(+^TA3FZn9zivRlPQysW!vZ|U
+}%-#bRdmDTB-r1SKi)AgP^(gOzhc_HVMijJe$yEP$+hx&<nVWHaC=wiwXS0CUTR?5B`1J&C!7m5!1mj
+fTtj&0Llv>H>B!Ga;PFN0V@UXLi7iz<BCJbI`HL)9k@kxnV#~>BjNhamO>k`Ij8^8fG(%1t!B;=z!(H
+ni8UA>sY#^kfttq7!9t#Ff%8!8z#Dq0xWMbI{UoS6HeEOjHdG0J_MxY-naw#$TnvEfq9JThiUz$LiZr
+@6%=sOxvxAR$ML$gprVQT!rOR%;hncar3E`=_>4cNa!gCyKt8{u0K=384RP;#iT+?++#9gctSGADU7P
+kpJ;sGFf*@9$Lt*aG=&Pe)9=om;yoLD!Yq!C55A82h4juB$;(ldn1i!$*?p@^IYwL$n(L8mL~AvkPKa
+s@(d40li%d%*ph)VNGRPX245YyU15&L=`QwwF8xf0Ow0P;|NfuI$QBz7W(VZ36^*z<6vPNuTUNIn1(n
+*#=$3L^^SVj22P>cyEvqvdCf>;j4^5FW_vDRj1Nu^i_6&;UM<`8yr<J;Fo>H9jv6}MkN)qK-*m^mn7D
+w!f!EMI<#54lR#?js~JZ5nmn8^l5$`rh?W_3s4LN)83>KaBfSV<5HFEy#sVu^#m0Y}h7H|A*xp-VgRl
+TgmsYtL-D)O|);UH2Vvb%iq(E{}pUXFME)mr3;;IXMTUOu-dwDu(|)3ybWB_%ZS1(H)ICI<GLXu%aNC
+{++0q#U>-UF1Y-Nz~lKT)LpqGjR&{L9I?8Yr!Df-Y{b|9e9j#lt+-q{N<~*Zoh-w~siwNA9};WTfq#D
+HF4=o_W!#amQ1nEe*XV>DX)TU${O{Y$A+!(IGL0zL9pv^y&VpHJ0#@fl9!3f|-DPo$uMavf_r+-lBZg
+Cb<W?R^Wv6wY1Bo}ZEnQW@*&mdZS=edtg9zJoYL_E#?oo#pSld^5JwazR>;3P&kqa}uAqX3vQ3p=!O$
+B3>g?cALVB|Y(E3o@a%Z|oJ+A6-9dJw%7m^oA|mr=7r<L(+|U_tw3iarv>VjXp0Xsg5-)XH`r9w$zXu
+hTD6Nk6nABTCdRyJ)k6x>oeNYM9<sOPG!53uAS^L#U#Q;{S@#PmTZZpRwKEXTGAP4VY}9Q7((0D2N<P
+P{_KiNO2z!rP{L9&vCz1RorwLe0}xZ%kvj6U%Y;9&s^t>a`YrAyofChpDu0l(&k+9{O^$ECbM?Qh$T;
+e@{q`rld*uU%scZHo;&D?gG1^k?K-9z#jbyuw%x>3KY~YHw-VUpp(S@uIrRGL=3E)_#S0lH!$u<`L4p
+s_z%>7H34?RyJxrZu*Qo%tIu-*&&MnVV-eop;MK%7gAj~TKRnI=^8vM7YZi{_K5#b13UMSC-eJDPW$a
+5a300xf*wp6rx=v%)?=Tid5+>Ufkd2kk5<^~E~F1(A#r3!ETglAFI#wo71YeAbgdb6>yj``Le?<ZJm{
+N#zwI%4mfRbY<D5G|4i%{ghu8qixy;NuQfW)0-g()))b)W!?jb3*;ht~|caS!$STqgNh)M9tVRgJ(P5
+ru`xnAGR=OaL=9{9r4lt##dC1j*j#q-d$vXJMT~Q5BJLbcM9A~o3*!pmU<;m4W;Bh8g@Rx+dN@HvW2}
+7SGCmz56bp*;><!-P7E0@gtkZp%0fdLnmk=VCXg~NbqO|(v8hkt5zXvAtK${aXWShk@V5c@#00b31KK
+u;sDcCJpglh-V;Rp;qGOa?dFzu6%mE{Li%wtO5hdh7RJhp{Z3g3Lb;?$D0Ih~@0XIBqpa+9yQ5BmlRM
+E+Epu0wv$Hl5bpQK=9>r$41#T7h)lv_vH9rer|Rw)JzZ&Ky-GB4w_F;llypjh_$3#$nX6NTD{ejClqQ
+eX%eev`4y744!c1M(_JEdo&3ne`q^lg5Y~(7qQNoeQHpU~&n?CO|HAtq<_zkt>rp9(pIxe;jjf5V^Mw
+VK*{_D^axx&jYDW6`sQHp;Zn<68_o)ZGO&k`dQ#S-+;B7=kZDKm%?aR`8SA*_GVkOoiN|wuc6a3eZjD
+%f=WSR?9iusLth4wz7*Y}EomlZ@muSVe*54l)^2ah#agB}84aaiZ0Ch+VW>OCJ(I@imuMG*HIc<{PS3
+wF-mgWq&El<bKq1ZUV`*(J%US~8rOo4oQFDBJ40SBTF=sWJr(<?~7Sp%f{Z=fP8eQMCf)b3af|Tc+IY
+$Lk52!kMq5_{vP#>$GR_^Z8h0^W<FAp5^@_^R~Yw_T|-EcO~b3fEJ4C_F(``};M_~Q&Xmf;)^eKR<AS
+L_*0nJsOm<=zL$TN_D=FBz|JuTfT-hmJA6F5DDD+^PctLGWxr_RJ(OZ-X%ozMS6&@zy~cj4_X@I#~Zn
+7(yQm7*&lt(C}WQ?re;^X4SiBA3zTKgvH!GO`<L2QJYY1IM#3jR>ggA?=dm@_?T88<3yq|JaO~-Cpr=
+(%&ebayt~9azP3p<1aU`1n7f7Ij-2@|Xp<I$AnqxR_aV&(XPV=7yo2q_S+5V~@uoE&8f$#I6E0gGCYj
+R)4|@J;JRYmj8-Tb)nRa-OQ99PaRT6Fo#Kt%o>_D|gigWv?g4DsHU^@KW+&Uq{q7)$9(Q(?;1^R=Xz&
+u*|&PVK)+cXCoc?tG8CXl8|%}Y~4rYRmtV~D?H>h+8@r&4YiR-YQ$RHmu&dvnPbkEOwPr0mh)IW}TpD
+)DWPKd%TQLZ?`or>(PHlBu5|^5Ov5$YGO=$G~$F2T3xd@n-B`M($epbVfeTk{|+ST6$+U65xFfaHIlv
+IK@$t+BwRR_{%xZ@<#%--~QxonX*Ia&S<28^V0Fs!~M5$`K881Ew|H&u`_j&lvbDAoPL}i{U1<E0|XQ
+R000O897^_9W+k|TWFG(k1e*W=82|tPaA|NaUv_0~WN&gWa%p2|FLYsIY-KKRdF?%GliS9T-}NhSbgm
+3a5NlVClXx#kMUj-)x!6ugI;T>5TUaa!?!p2I1^~6%OC`Vk`Z2Gb8GziioyrHHN-Gl6Gu_kE)6?D4Gh
+BD=CRvq3xopb5ull6k?AmUyud-xaSIsI*x@y;y%j(e@YYcb0dV8&b(?<zBZ~yw|SH+7jU%mM6ufF+1M
+z3Dh%Yi?AHB?=B)l~fLPj#=}e^YL%)!Y3}mwdY$>ULW;{OwKkw|%u;sxk-cf3^UXJ(@paau%ABtM)^d
+R9)A0y(%f1w%zGs{9LT-t{)2M+mP`K{HURK_41vD#?Qr7+cvteD}gv&N?(c<^rWk=_CuAaH(j;bYc?&
+)roP_l8sAmjP%q2oIllb58gAN^0{ecyy8{Mkz(4ZWuj>!>RzYm4vfp==hWMJlZmO-Od{?ek&XD|>zh?
+Tw%Nk&NV4CL3u4{*O**3aD-2>&@6_1jF>8oqRph4d7S6w*VHHMxy_$A~2-rntW14H$})P4(}Gx|#akL
+tCQm@^t!uD1j_TiZIz7d|hzAoE|a*!1@OANT!GukV=4_Vu^#t8U%2xBmOrrt3(Y|NeE=?;9nsAaaj>Y
+i7qI`U_Mv`^}bnFq_R@R_l5TbE!<0RFK@(!%e+~@Be&@I2Mlx@_BdNpBYp`JwT6BlI(L3D(2Nimb7Y0
+%+HdyH<f~G*U5liu(^Z>u39DKz;D~#A^{>wpt^@|$v5p5kZMfJl3F|l7d5Zp4VtS8SU82@wq6Z4Nm_4
+*ph+$QW-M>Yu3Unc_o6dUp-V0=vAxSnY`NSI?WUxO)7*hF8m16$>TRKrYfW+vRD?YPz<RUaD00RLSi_
+fXtHGyGgX&3A__O#O>L3T*w_7t@DAz-|h3dcngx%dG`yMz7t*yH9mVm0&HONldS5<P>RqM0Ma<>D{*B
+?L^eYl)Q=|kiV%ABMSQGEI8`FDRU;O|RIYhSLbf(SNTLOmzh^s?@0_z}(-tl<WvY}IZ*g}-$VYr<X9q
+J(c(?QNel)pfbNO8^pBRyHL0$>R<*Y}GvmYN79v#JAnvVWQSzX`r?QX{wZZzpR=D*ab2V8o0i`0g=0E
+2ap-i?$vsjOLXZ;mYmL=xzILEx$CRKU`9p=WUsb73m6h%U^F#&*|q!aiiwbzeqT1d>{)>$JB~m%39S=
+gq)o}J>cg%C+>r*kz$yr+3KNH3l<&*Bp_ly*mh%ME@Z}}8dwB_M07Q3N_mxwZXUJ{cG%)XJHa>-^xZF
+48P^~7r+~2gf#Z6U$(uffG21-FAs`AcPD6*^6)VghlsistU&{T}9k)e2rldvR_S0jszX!k>3ucXpFNG
+(mrF%(>QRSmaQwM{BmmF^DG-2kWJ68g=4a|Im-@~)b4`_5~<!+DwRx@y_%SMdJw($aT%>CKN5rx&!qy
+Nd)Z@1Bz2x(XQQ;|PalTToat+d5EHP$i%Z&B1dv>7b!bV$d22desluN2tl@Kqr9oZrTpTwcLUlsuUe{
+pIq1Pq3=Kp{ZSQIjLQbZWDDXurOsI{i=&u8ue5Y<MX&SB5H50<z!LiaBwR6ygo|eG!qh#iCtPugNo0#
+Wpk=Cego*Nird7?uRDaJFA}qAntkaw_9g_{&h%D0~y|X2l!h+A5=KC}pr8aE(2G+F(*S5&y|I(D<f`K
+N+P@#p9!rTA~=A$|V3{|#6SuD?znY4muNe(a?RF<7N7PFc4TGgX-$ktkk6oAf}8(b`%KOC1{3#M?nQ~
+1pKCIXdt%VuF8naLjQ4{uLRTGQTx8)C1*Hl!pDxGLNpVk+7|rcvM!2n^^?kOVEJ<fADE#WtR#Tr)G$2
+%pHjnvnrITko4@W_kTy`L;kq#LXp2z(R`>qO0N<lDn)#7)Zb>fOk``R!yZ4vvKF3Zk105sHJ;HSYb}o
+V72uUwFXpk(Xx`P9lPj|^8n4D0?`eKva{qbt_Q))lO}q);`uk%-b`ZbCq`$n8~5d26nyRbGBGL+Ix?1
+s^20-jC_fxe1j9}dL9vv35%8LVGtdw?RLL!_`<l&YG#N)6sGAy|6)0r<py0JOwS;Zk;<hVyX9+4|pok
+QzCJEnxchZ4D2l9(>J7v+wXPM-{<s~(Cd1<i~;8s;1&cIz90N07e^A*0eOm^VOX*i<*+qth}k%1J<(_
+Jps;M29;U5=*JoLhh*Xmxi7{%5nECr^Kq%s9F+v!M!7(ZjymQiKD1Sd#u)$3ci3W9KoTiXKv{nIbbkz
+feejyX)E=sDV360s>eXboemrlc4Gk)c`uAQ9hwybp|6hz$-L@aZDWLt{b>R-f#p85igj^F$&jB^`Qnb
+ERi(&E;%o5DvTy7<|vVZPr7Q1QG{6q8hfIdWIhsfdJQVi3It3ojFM28=DO_IIVGRMUvJF3F-wd;v)G`
+*>9E^@R)!Cv9T<V4ua?+Kd>Vjwf<g!P5J6Em6m$mjvR*1@5(ozOvm|E)e3flgg5JRKGPqPfix)5qsSO
+m*O|PFP=#Dq+Dkl_RV;gvMi5>4DHetrYMnXeNMK^&|Ie@0FT?u3HUbnJ_<Yf;-tD@f&Doov2u-kJTBD
+EBlAd==nEXw$p<-XT8^$RsQ(Cq?alE13S0sd80V?-b+dt+Xa@;oC7&o2Mj!Ei1Z8&|!AVZadA(zmxiM
+m9f2Ha|u-KSnk`Mm9f2Ha|u-KSnk`Mm9f2Hj|$^vdJ!&_J`R*y?CT1seTQ9)P?nZ3vjvXp(t$50lBP!
+0ezN)26QF|!f~~9+JpAAGM~3c!A?YFvd~aG1PDuk1ETCZ1e3N^7T8vz7T8un%WAzp3zJU(l<kyk)J~B
+uWfqtjrW{wM%rhCrDmx4INPTA=o@``-1iSc*wV)O{6VJ)ylH|pLX<f-8>xwe~CNN^1`EWdBAUy8>OGT
+bV75Ra>N<U{&{X7+S$YN^uxC%m@-Ur82%v?vj#}wdkm5geONdpCpkgl^wLeVUuDhukKUr0DlfkhzLoz
+A(x9unpE=DKIHm<{8c^^GjDZfI^bjRZjxlaz>jZ9KEwC=v-^9F<(_jm3Tomi)U^70e~P@jG&(8@vXU8
+<8vJ;L+pQ@VToXB4En?&Rs1L0aMhN&k+zdU~@-TNFZ$r=UP_;(jlF?JkXyWQnDa&)-SS1*nzn;3vr`m
+Cc%Y8mrDaL0xoQ`T&RMGm>M|eTU2BXp!gnZabm6tfH<0o+8&6<RAaN`RsjSv*XVJb;41YM`U9!sMgV&
+;RIXd$s7ayX$+^%Q3odljcc&fE+Qjv2I1nGOrs`ft?NSCIduA@-Ob0;D6mkWf^M7*zUV*L)8&Ez3?`x
+2hZ&R24c~C?2Hr1FoC{JO?jg73L0e9WiD{H(hoBqDG+obh!a)jX`t%AUA@oa)|!-aQWC=5Icw>eA@19
+b7WWzRUXky{vd<x1HFMuvi2j{Gab!48iPMZ>V8hvQKvvhANP@Fim*?%*DdeW_MC1d1MA7)bD<B33y5{
+Q_ZzNZtqZr0Om2oIF>}hawQ!_kxL<Mny9dZ^3HFr8(z_Q?CBcCgmabUr2Dr63D%&YKnPgjTYk|#|pKy
+<oZJv8SI?@vqhtOqzpK*|M;dF2Hpn*SK{e66h*T3UA@^gH3%a&GrAY4ttgo1Ze@3GlE_od^ng<tM;?u
+tP<4(0EGdrB6F28Z*aC1vSF&YlnFAhIphF2zNk47=uk=o!4mJoXwB37R-e4d?o4iPxGzI0P;Mz~}<XN
+ox2yC!CCQp-7f0)<?AK?a?5lc`#!!#=>z_jl=%v;!+pes5VF~KloA%K%Oa9s_Bv0K!jtBuMt%p;&rvn
+;V$4MdR5b($i}L`S7)D0`6FSZw!Alg<MMJ0_Q$tyK9*u8CY=2Q2YUy>m8L{!?^amCYU7%)Hfh8FGj#U
+o51pTCW{wXFeTGqNzO(CN3dzVp_N`7wQaA5Zj6l5wA79eW#At%&ckR973`*o9rQAfNEo5-UR~_C==Ov
+w=oOvwqhZEot((ZiWd%*7<xLH+r`UK6dHl6JfeN-_ZzuRsZ<fYUMfSC;k_jdAH{3K;KhEo!fLFpET*R
+}b<!%f-|QzdxY8@|UfZs3ELYI1Jr@YPTIrEA&odQpmE=-1SmnNKg|lM7Y~(_1M;mr~yawhwlrQvNH==
+OfBObSd^W;eq8`rrz!uLU|a@`(?79SAZRL%gD{?LPpiTyk_ia@k0>4J}$?B7^@w~JuWZ+58+`2=dlsW
+7(uC=<&rK9s_9PWcn!PngI>>#(XnZk_0;hr+MGJuAeeBAamVMm?@KQ}o<7dgah>b+qGDOYLmFO{Qu40
+o#LMkM9>AmNxe>L19_r9-s%anJws%S;w}*k-5S@)t1YF)LJLjKc4<-fugCXL3r7b;^$!Cnlq_j>DmqL
+sThIIbMVf{io7GtZUtr7jU5V*UM)UiTW}`JbvneuFzT?!eK6jCPh9qo!XV^e;d_-{JGE15yZI2LT=PL
+lAAn8gLSsPWK{(C6u{@RSVtlSsAZ_N8w{=WYU$$!!DAUO77tMbcq*`W_Q~^HD)FA^u4FMn}1zMjZsZ=
+NP;D`ZeoMp$D)@`%G|Bbrw(Af78r!Yu8d|CB1rY?Gk_c9UD4x5e>wKli?z~~*7dHCa;K^QUqr||wL#}
+1_5K*`qupMS5CwpF<|Inu8B+aAUNlaTm~KL;rQJ5j>#h{_-{DI`H@_E<t#HSkdZj^|N&rOIX$#|>=4x
+s1A*FUC)J;TawHaCklsq7PX_X{z9V7Ex`v(o>_VHV-$QV(lp4aLXwRRa-t<th7+B{?DSSB-bCZ=seH$
+hb)|$IosOtxs#huSzO3-^C=6ZF{i&-Oh$6`zZ)+!3<)=eQthD$!?SB|NAq3m3hU+_1m`dwWa^EcBsgr
+vU^ECLRF=BwjSdGeNl6n5>j6XR<?_ZkNq`78ASx6RckPV!>U$s=6@)%Zf_r6ha7bo64OFTeMmlK_Tay
+i=<jS};-xQ#GY=P3Mw*zRNFv~L3D-OS-I~K@TU5@cgb({eAmJVzKly&b1*Z3Nq#W(F>W#tvVJ4?P=Cw
+J|h0<L|F>mzcJ(yx~#re9y#%>NPfWn3ma8^SWJx2v+r;~No~!bj;!KJugIiX$G5;sl67ObSZE7@rw-N
+7q)G`--^t_Ho@97ph?&>pb~2zgL>s>x~B;M0jXQ_)wt;KR!oJT_lf_)J2v&jnm{!0vpvq@uwxl9UGix
+)poyuZ$lL}7H(4WmT^AOZ_7`+u&K3-{)W5DNLgXxQj}B^z~JM_8Xqf3XR~?O<doKR;o=+QhJ4k6iXHp
+RaM{>L<T*++kn2%Ed;bpGU6DVcL3e^2?plXRVq7hRu~K~2v;9_Ya5B2&?*q&$m(oR1Y|Bkm6#w`yvoV
+e8m-ad%sv9__%(c}lK<X`@v<0F@@ii=yj**eM`ZRYw&%NbUy|zKHku_~w-5T|qI=VM0*XR#B8zJ+B(1
+y-Fhrh#N_8^{~UMyVw&v^>LCV`6e{%D&7GxrLu*_ogjgZ?7vO_0vVG1aAG>Fj^Ep7e4U%?WA$3w9o?<
+#OcK0dE5skfXK<e&7~?{Y0@Hv2(%b{J^vmnZ&Uw6kdmqOo1em%~l6TW;330nGA(_DfHT$GG#)=a;}h<
+TNn{K$tuy|3F<R*e_R%1%x05;LzSIramQp+N*7T>=eGU*0B4XE3J#P`I?xSwLP1!Dki`@(7Bcxtx6p-
+vv>AZqq9isWJkmnaovs-f%jMAP0rz|+e;+ECRh;)8nZ|Ug`oIX|V_ONW5#}s!^wQmobdzK1XAx#PADQ
+0GB9^)CRhTW9jc_+O8m@S2rmAFLrsjRP6Rp$ze<+JoJNILf$eA>3Qg073%FBE7S!EZJgG%lPEhuDd2O
+CB&%#|90K8j0eRuwsQ%3QG?o6h|4E(PE$RhjZ|+_G}OiYMTrE4SAXV?4G~8|=B7y;W~Nb$lz;EIsFp*
+lb%u{Zlr4={>gM(q~)1R0G8+Z>bAP?!7ST388X=!k7n94!u*CApp52y6aBAu^j}`S1JUCa=E=rxxI)%
+yRJV}tHLrWYJr|89OxfvG^~y#U*qPhVRPmT+W*zN)MdFYi=@9^ghT@kh2HrdBU+j0%FMwL$3;IFHVsy
+cxJSAR<MQS{A)k)yPVL$$u7QI#i#tdW2M)PmM$o^MH<hicJ9_a_V~2^6RT<-qvSoagI<Mlcq;hgCyBr
+61)MJgaE)Ite6QCSJy3@rnNWXmo&ICB9en*b54aK7FLjA_sz6=dP$Hvv^m18L|{61W5&ZW>Qzm@_~sH
+Rn+ig%9a!Hcljk-(}Pz;SlCP@g1tS2QfrecKJV=;Kw-Mit?$Kh2%5fR17zKGlb1)%S)5x8BnvTyX;Ky
+Vp;rZev+;eu^<1jGL%lX#*uRR1PyF9Q(0_4WFYHH|gO_B@^L;1Ft$3QK@6f^dc^^k;U<3a&dI0N9uCv
+*N)~g$)LQv&9T`?+L+y1a~x5sEF1O`aYj8qDO81Px`fkkT%`2cEXWhCn|^2+1h7d0GmC00kqsYAiXK<
+wg}W>Wr!ywO&hT=bC)hlXtEz_IJ-M+I%r9K0*k;-4+n{0xPsSA=9zs#|&#e8L(T*KQsp+M<sKiMU0kA
+`c?`zgUs>6NDVRXJLXDAySxjjYAOtX{wB&wa%Ae%FBXiIaMw<)c<plVPToGSReD!1xxm0H~kMRu8<yP
+NVZ>2JDv`)+jm7xRSutzHTTQrCy}(0K&Qx#T$o*_x3axpqIXZ*oQO6}D3$rm&SUsyXIO*4vx9sYDy71
+_X-V_!+L6O(tdxU*b_zZopBTWz)2`yvgiM0z)4WY``Ysr26SA(Ce$>J`@QQ)MI}CAGzBx(lRH}X71Oe
+BRZj6)>XY;R~;VBO9UxT!(N8*7303dP4iP)I+WOm){z0W8*|n1akKmf^gJ}gRY2Bpm=emH7($-JZPTl
++D&Iu~RLxZ22(A^<HVGP^d$!7hEFNv=TkLkB2yLB%Q(Zszobr*SgH{Uk!}x~7BVr<oLH5jqex)}&?Gj
+;b1E4$e;&&rb(hA)yMMnqC`7}J@qxYHpn{V-n96gR6Nj4Rn^V#COwhQ1k<kts5ba0_qnoL>)!@uR??U
+@y3r_kyQwA;tw;>T=EW#cn1%jHdVMn7wF&WX&tiLO@e(cEVA(*FJr8SZv`@szvKVO}aXNaULD$0knGF
+d>O}NJ<io$3{|%$71j{FwqaC79!hsD!NR?(s>%Wp^Q)F+w^P~iGO%@OdYu+99KIE6RtET3hz^<CK_(X
+Mh$!8dW^bYn}qH`i~M#T^aR^8XMAG_kM2RZ!r|tBd7yHqPMb$-TfvIf#hy*!J<K9m*O{;5*VaXAu#}!
+hCG^6PW*H}Bi7Wyk>&jbk6E4pkXR9chq~TnkQSgp0tuePEDMSQE&1D4s*{mSU>0Ur1`rzHd;2l5<^W$
+_FkAX(a7g2A*<x<^DQx`syjW`N|ax_9p6}U^JRnRJ%*M?{oJTP%OEQXA#&BGlO_o5!rh<8DS$H_2x@H
+kGo^^W1B3!lkG<}$YCtZyDS{#<%TNxXh`Jg<3*WJ#)!IT;biZtus=QX|Qc5G3zF@lCtY3C}2^MVeeEB
+O?n}Hzw9k5z-HUm&4GBCT2Pn6Ko(l9F>@W-y)u+DTgIYLP5@rFw1I;AC)&we}3|QOY>5O`L%WFS&~Pc
+jHZ3b*tw^IBPL46t8Z#8i&}JM6LfO%H=%H4pGDnX2bEf-&6}r|s^H9(0eWJA9L9NJN@<)smT+LCo3ha
+jOmT0Bo2_WA_vm?A=ODD+^FdR6<LAA{eis6tqqAb%leDMzJxP1yE}_5O<l^^Z|M9$>Pm<r`Zini3!~u
+`cI;Ps4$e<-Ln=F+pzydv}LJdV4337g7PYvij=-VpUR(vnA{!K@H5W|j{j-$HaLTR8FWaA*};v8r!aq
+j90>=+GJesK5RqUMfDPSAtw@E9$h=$dZ@f&E<*`4^I4V*P#qy9SOa(tHA9JLH&IJ(iPb*^%O(cp<0~{
+NqUG_z_z_TA5lNQ|!!s<v7l1koj*#M%6H1RbV~bxjHO!htBj0B51$CPQD=E&vXQ({+yX?)996Go2GQM
+&BMozNq76%P7g>ji3I7bb{<O><GqMcPat)!VN<rTsp{R4=C<@?tR+#$Gq!cU4TpDvQ|!}I(VK~Z;S__
+CJKXVmyyV>&p;tzRRhBFk3!5pAA<W03H;yBqE)k4$4lge4_gDQ;4|_jb5g(%{@B+fz{Jd`}?k6-dW8O
+?{S~*v^i1#GpUbdsx0sN0fch{6Kv&h?8;meeiL7^{|F<G+ijfI?lf>=$n+lp@##LG}PX?B5M)8o$?cv
+m8NI3<|9647(YB$yijjNFSTu0)iVB-+rOxf0R6A<>D>sovUtyJkfZT&@Ez3iZpz@gRNN%GYR88aHGKS
+(2HU#Ut)bq^^mKJfyO50}j=XygH_LIFb+T9o2nk@2K)m-MdZw;Gx5+5A7S)eQ4K$w6>8;rtnezs=$qE
+W@vXd{X?K1X+kTM36I*JOU|~rxC=^8Uh(qCP@1qS)$)^y0Ek{#=5jp>0w8+*na`s!I6U!}b7+MVI3l`
+_>7Wn~gHu9~f%a4&J`6UJ#%phf!ktBnFS<LI;!5Dqsuu@K&q&&Mkh&q^&<5lDd?55x6uHZ_{i8(d!jG
+CNIvo<tEtK(4vMV3a3%qm}rmIdw@$iwik{Po{v;EY}CwFZfNr(*XBJDMj6%)@#(t>9*lVZCo_c(f?A3
+_j2cdQ?sz^$z9XzI3p^nqfTXBUSx=b;sF{8+SpoWmbe0XzL@gTOmtL9gR{@EpIXSe!}G9}nf_PG}n&W
++e$Gxe=mcdLd?&cJ}y1MjMXQpUC+^aRilt9{CzYwyY0h&SkirRGq9!C(`f=3_iyf#qCaaGt<K!AGmub
+tYCARMoulL!#rM^rb&I01Vy*ntmcVtTbT<(a&yH;L}TK<*@V*a8=~JejZtHP6x7HDp4!FIMmvuWuGXw
+GbVh?2b#=xlrtE#J>Qa;YAm%Ff#vN~rnS8LZaLqYCyNKH6ru`o0=uNpB(Tr0<?jnk-0m4Lce>~u>p9$
+@YkJTl`(aHp$5tDKPo1<TjP*2X%rPrq8RxrK=Xe7nfHw8lPOBKY-rnr=P=Ir=*X*(A$v(R+Uu;p1s*D
+mMAX7=pgIR7Vz2@GTXuveisL{|0tnq6tvOg=v`8}n>wq|XdPI8Hdf2-V3acxQrh-;8d%?lE(4sQ9Mmv
+gup>Ls9&5v-%e`ldE$1?wanP4%)VKj(ATBAX<ontjZU7qHuv3ySp^bK8{)(9!j^t%+8dB?Su)F8QA*_
+Wqdl|kQUpPw*$A=m9t`xpW2vk#Pq{LgR&6?A=H%RK@&`0d{O9ioZJ|4V8(WDB_ih>p=#w^^(^!%oQ{~
+h7_tFIAuXN*QgJk6I`I<;VR>}6#hrqOjpEwe1mkdhWHVTjc3)OcbjXePMP1N?j(&XZMztcgcyFzEbeI
+4idDDRQR`H4&r(~1?sS_B)AypAT_~_oU5M5Z}Y|z3Tw-uBhow|Wde5v-IIX}=w55Q-97T0gGCFM@yOK
+X@$l+mbe(LWb;Knf2lRD9x+0M=e82$X+YhF9bJk1H<YkmF0iPuVf}@}PBpoMKPf4U8+eBT8>9B&W>dB
+cgIX@<)hO-FiZneo<_27onJ)p|P;*%Ii&ehPU1=(Kn~IIFX~?EsFOrjoNNOKi8puNV?wa+HOeHme@oE
+bEg5CA6)5mwd=mLuO}+2UxeUlbSWPGnh1S(WUDQTq2Ac$=?fRLO@rT4zNc5I-`U*Tk;D5<=tdjCMmp@
+D&)y7Wm;9yd`sC~OeO>jQx2jIM=d;)NYvt94a<gmHO{sB6eI`Di(PHKRIlc{_wvXNOi_h$J1#_;ia5{
+=B@@7}mX0g00w=;dc#7uqDF&nzdB^2KP<?JopiC~)9l-D4T<!q|T??AS{U9amU*7G~68@leQYCDVeR$
+MMeU42<ClV>Lx{5$=^W2hY({x$2@cx6z#PTst`yDgh{;s@3U{%2o&{wzB^J;{FY#fjj1oRHbq<z4dZb
+He>AyoB>j+q8Hr$cn_9q3!Ol=x3jO@mY5I`Dymq&wm-^P`qcS-1;v^dzQS~Et2m}Pfxjve?rUukJYLU
+x(1j(dzO9v*%#Tbe&sVt@g0`es|KuMuhhMmNd6qrJ^Jwr>c=m9vR=2>`wD;iJIc0b7k(ae!Mpo~B|ha
+lUhw{tv0K_WBDm{nP^0r`S+|EtZ*&wjIgdl?Rvvi;baxnia!|NG?B%ID7mE8ad!=*+UnM^GF(}mPSJ}
+;+QkT>Ov&j7LiJ0aZm-^WlESts@w5t<&K0gT><;e2qC$o?}_at5;5t|TRzvyxtuh9AZvphMUt?CWVN%
+~F9i-24UoS%ORpr2;RrwID##lLw67}RcYp9Wo1W%;S&2*-N)Z{JC=*)Js7XF@2Bwl1r)AC(pV4^T@31
+QY-O00;maO7>PdBh$bB0{{Rj4FCWl0001RX>c!Jc4cm4Z*nhkX=7+FbY*gFX>MU`Uvy|?ZDlTSd9_wi
+Z`(Eye%G%c@?>wGA(9d$8E65c@fxFXT(sI&zz764p%Y=YWJnCw{`=jLk}ZmIwm#H|nCN)-@xJ@+=<KT
+UK-BkRUObWfa4aiDZu44A$oi=Ave@n?Bz-yVrRVL?bNW#3%PLb<4mQ<ByhCGZY>nS>3x6xwdVDmmo|h
+S4gd}ea^d>Lhymq<wJnvz@t!t9X>X1VQ>9ah@nMdGrb#*l-It8N8N?vODNd9@21(DzIAf)k77Ig{m@L
+S13O+6htubyfHf}gM3hrgey@}+nrqoE|mGXlqU-Snx`6Tq&l<o^KZx+(chjr%x7Ssk`}GQy&7hJX-hP
+WG@(${mT@fE>Bix%zGZ>oellDt~%buOUuI*@)Z2ZbA(rcva-CEaV9pKdK~^Jj$(d5}A@~x!b<%RgF#<
+IBhjE3Ovdk$+Eo2RhErTptaoZCIh<6NT*dM19iXPVA7iDF5YxJ?kBwp%}y=8aeVKgH<5vf8I#}M>erc
+-_4J%<W_t3CH3_3%&JJTc^338w<k_JYxrJJrm>Pnbu^Kg6{7OcRgaB!5<1x(B_2T#WAGc|iE<UZ6ck|
+mUy;-alIDg#{Gn$N87*0sLj7<eb{)FI9^SU|Z)Z5S|%3{|D@5b(Ux@Ln3_94`sxy9{!Ck$-O(rny2$)
+C^fg=_i)6pY>Rbj^msxqudG&+I$pzNiCG06kahyY+|p@`8R8N$aN-kI@J~n#Gln3E0q&b$k%$WD_eX8
+Uiw7u*Gffki&@~1v|C<;Z*8Vm)#(I3{o&ZfrZ=0CIXd2tk}X&ARqyxNL&>82Z^AGQDBoqKY<7fu+Vzp
+NmtbC<!ZIK&R&<6>1M#Em6paK)&x5^7Ou1*YzW9%*jy6GR{+I`S!Rw{A<zjE+a0M3$T{R)dj#|-#iNC
+-ImhZ@2L_fsMwkHmL<E-q0EY$$Rp%JS!^`?&*ZFSaVRFDFh}=fP@d&A{3#yBHvB>Ug15SO5deEXkj57
+v$W`R^!-n-@dn>1Vhb-Vn0^CS1J2#iuOcg4kCgcP`)0Y$kXJz;4ZV6Fm}klF57_6QkT(y~TcMlGqFbd
+0d5D{}U2`Ix?i621J_#?aiN@YL6fl^oXCkM)J%a!It3)`spyf!AN}OTrIZ8SSdzjf|sC1G`Z}?TUFvQ
+CD5>^Plgt#g~ukPwA^)tpQ+~=QO`KTg*q2N$g4-L4pymitS6p56}cd=DX<$aF2TKT4P9CSoHNM@VLvS
+gM+g}dlvzoONFn|oExIYqJh#V`d;Cel|~0l#BODT<9Jh1mknpw<@V?`X2!W~hYh@=q3gPKeV=ppABtv
+#dAGf^$o~RRO9KQH00008031s8R>MlHts5r*0M)So02lxO0B~t=FJE?LZe(wAFLG&PXfJeScyumsdF?
+%GliNme-}hI*yrc|D6i@P}t1VM?iY;Gsv89x?cUP%3Lu1L=U05JM1E5wLMX6MNLw-YkSbj<RF^`@HK<
+@f+iDQ&XO8_%HGd(>$J^ezt-8F5Wwd&-uZMNCvzFzlDQ*~L%FLp)Smqj&$5}W;6m)aKnwJC75-tfa_r
+`n=#TJxgp)%HsDy=wV=f4eK|EAuu#$>2Ksr+<9D`t0wYfA$YAUjAW5kDk@H{NuBts)~zB@!jX;y60an
+0HS;TW!dTHFN>|(ob7k!&8uBsHZ^peTXHY{RKxSx$@GN#HD6Utvorm|->a(Vdh>EuuHRT>!0*)spvSz
+tX$xC(Q@$-XYE_lB#?ri~%B$MEeug(+ss6gr_?oX(<?xI*t4h_gtW*7p?z-|{45W2a_XPlMZTT<Zt`l
+$DrZTU(zAbkv{Sf|cY(ceczAH_!=XmqyqAiQs4EDSI?iR3XO8k*;zbfCAwJxz$MYnI2De)EGZj}YmsV
+lrQ1zz*5dD-7qw(e`Znem^q+nqW&DKCA3IL)%(WV^Pw+7_o--DK<LEf5n<p&fVEIDnt=?acgO0_bKij
+;=2+ZyEWs>=i({teP7=87H4V|Ki!7zC2s~@lUVMUVQOSr`g1-Fv%9#WTP&NebrBF;a7it{`D7MzWNK4
+_Tf?S%cj~)PEJl%ty<k&!%FCO#ah9eRza_~yRuSwJNc%2_%{<E!!z}+M-0GwqRn%d!C5xJ$CKsB$sbf
+tNHPloikYA1SadnFw0>@}xrB-*Yarw<d%Y{_+^vr3DWPyOnLLAq+`dtpY`=q!T>*rwth27!s;q~$=TP
+K?%62_)fm3+do2m$tAH&m)dPimPovJr+L3kJxBT6`x!=;`tZ8f44=zX&;iypdoQv%EBuT=(^tX<DwUa
+}QndDpI1d8ew&Y4+$Tt^gh+Uaji)ZJk|GSMv8*Xih!<Fw6K3x@Uh=$3AL5OuYth&C3SxK5D_h%ARJf5
+eKE)Rb@{gW?6H23Co-iMet~1&Z&nJF`N8gxpYktMgdM%5F&8C`X>8?7etX=m2Xw8p*tku1#62RXP=7R
+Il#d<X4%UI_*h)~>B5flP-Xj?nwlXM%y{B62I309P@cd;nju|!Th=+%;D)EV>eQ?BiLHbX=2YG_GmT~
+lOU<~Zo0u)Im4SKT3GmSW6_nPLU%*`Bd|%v#sCQ$3)?Rf!qBJ6NY~wV0x!+y@$89dN^>xt}>mGSLOlh
+&%;2*Cc0rqPePyiVj26p%~dzRJe#@_SdDK_5$TZ5&vYq}B%Y%Yg&{A6idy1B|8>M>C*ai=H2BDyWFu3
+>L$o89r~{tQanb)OYI{k|uzpJi{0YOk^j)!!&p-wnAEu{ofyD=(_stlI)7R_&D8()|$XEv~V3H9Q5pT
+*NH6<zjXLB!*n>=x!gtS4<=8rUC)(w_I0a#K$Ub3|USbyU}b4F#9=gkJ-Manj79f%wr<x$z(22f@sJi
+?(f0;yP{LN<Rx@!9O8GpW5+$yTY0vn%^7y<N?rEAV<&46OH_-$F85W1e~CONejCWhTq}*<>EmXM4B*;
+9GAHOL3cz2G=*nGJcB2i{4U3dHZZJNE%Z~Pb!atTlVH!%b1c5N5Wt1`axIUx4e`XjDmd6skp@#t9-@s
+K1r1!-I38^tJBXOt8b_lb$pl*KqEq3MGZxPZSX7<}}wfHtSV7~p<Z|`?=kJoouj>7&qQoW><IV{QwUS
+PXBIHjmd5REsQa;V}EM(hT;T6I;^cdHdF&2zViSBQwo%sn8O@_{Bh`N+_Se5R*WJ_0<;TZ04nY(<^-p
+1=X&s=wBcmQq3~>#_$4#bFE?thZ`UQ7l5?R6raO!-8TDX5m6R6+((HEn{6o@hn<3vQ8i~$CWh7L>*ib
+aXFGV^}v8QXAyA<2tcI>;CC~hu0#n(V17%qJK?Qkgk1p`2lyMJ66EReu`9<{Q*Tb@ruexJVCk2#8wLL
+LUmZ0Ax{zP<$cZq;{K|$kEzH#TuaR%i?&UwWEMj3NBtVCr0*84VH7$2w8s`C8^a3D>0m{K$?xS%k*95
+$lLOaw+%j_EJodte;m`ey=>p%~O&LmWKSHa2t?x&egiH_bo5O8SGw~SM`f9f4#K%~@QfqQ}&)t;iVg#
+|A<Yr0lIBq_TRHuIuhtDFkY^u~cDr_)eI>2UYgM}u{<yUnMG0(024fI=8vSb&Db<-)<fZ2A{lI3S@WL
+2cxa)c4_tnv3t$x=+j*45@DV#IR^UNtr8XcX0Bu#e$pHw<uAHiEyv^UJgJjcDlO^BOU@wOnL<Lo(}bn
+(o7LmC1DMtLk=+wQWyN9s5&J_d8K;P2HHV(Rk^m?4lGOkWSOKz1OWhOd9R8-j}8q%dAwG1?BTPa_d+v
+Y5{A7Oc)1asb0f=HTn1-waUMOlt>%ws*^}r1Dle4P;zNPKsHTxrMVK#EFNm`^=@`O-iGD-Hh1}BdN-j
+af(8&O~(Jajf^GOPk(?n&bg4#Oe*U>2G`euj!E8JSB(!8uU@Tbd(z1umN`rU<|aivA}<TM&CYGFIWkX
+SRDpNkfk@zm%sP|fovOYeQ$d%S*=on4n*cGK*u4IC=7BD*L_483XEHz;bBhI?e{^0Hi)@T<B_fcXL_q
+Hb;gvml}(mul7b`?3{0$9A$PL3Tz3-}AO@+I&J7>-hAB`1ok?Br94)P`dpN6{Bi1(Hqn6cP(n^`&+v<
+joNu&mjns<4~oy+wNq4(-r95#$JqjPp{S48u$sdFuU<=fMu&QZYRUa>U<cHFGRj{r8}<Sh_@NU$LWQ#
+f%5C*kwrhHro)V7px7oT?MUM{+@ZzdVAMUkQoQr8awCdKyPN=_{eZSlHTEszpElPh&_g?QIDTc~`%{G
+$xYzH|FvD%rC8K?dde~^=EY_3V)6z4}+oVk%!B?<;K0EZaXS-Za%5L(bY^A<>|<ICju=N%w7f1_>}&a
+y<zRxk#m+5%iXwhvkAK*5$KLQ5fT3Y*qytkx9(z;m_b$+8EhAp<ge*tQ$<2rcq3P4M8)ZE3yBOk-vw2
+Ev76-iIf*q2?|p=f8bVMLsMiSX>W`7#RqU=l10^z%`xx=HE4_P9k(gN>nbVmoDj+Sm$9^FRqD|Uc$EW
+y6O_g(c}^H$U`X^vrb7o!W|vS$$z(c%f>Bn+>th~_$>Kzoo$n6)}$;$3Q*uhiWpjEHsVZMVG+fn`cJE
+^n+i^+WlsH5FwwbJmyLz7ChA$$SzgO!@T}|WSa3FcXg`mFPEN^BrliwT_#-IN#`mW)S|!hdsi&P@uT`
+D}wK;xo;u<GnO)~_emEe2QTWBUY<4Io7|1*DOExfyF8mduPB(xHKIXiI)6@*_hRyNr4qbPQWMFB@Ie@
+X`R%Tbjb;7tXSD4$u4DKcg@&tATMp@k!28Ql+JT|OXL^T)R?h}rz5FtDH6(x3_MN3=FbO8x0A4lyG|c
+43`);P>YWX;1J{6q;0<)GqkzO_0+<|D7c%U}1jDQggS^e`g`m7bvAC@wPBOX7P$yFuS)e96R6eNMU4R
++__};TK&fuVCfOh(L^lt10-n;WzK(DH696<S^+rBx!JyWJlod1+WN)(buAl%j1&m7Z};oo@KS%fFVL{
+{2v%ZM8q3yZPF#_^Wb||N1tEPzahu&V^~XKxB!KYUE(s*QD>ihT=T&#D;K+tbQ9b%nZGJL&a)>QY_3V
+(>0}SOBf0!=*;(79MB4D4Q34iuA(ol!dDm^tr4hcv<M&g47q{Y3ECB<xLnu0;ccVH>`fX|I9IkK$biQ
+2-hGqA89pc`s;8oS5MwCj|kCw6}O{~)Zf4NO=w0jGrkj4rc0;%D`3%Ak3G5&1-SaSN+^d%^1*h);dLS
+NI(FULrQFgfvTo5idluGoVhR)_~VVd$mW^XqR=@MuDnIvR7z$w24DEaDrVk*+b7e1+SP-{VD?fY-d;r
+@#hoI47q2yPvxFp$X8fkQ^0@T)<VoqinDdYu&}6Y(ctVz4vlVM-hxT<Ucqz^OJIWL{`zvFW9(L+N-HM
+NrmoJMh0Rm3?$}p2V@@8bGlh|9N1E!K0I_LvI;iKwvcB>(ZK=`4ANb{=U1FJ$h%+Z*S>ekZ|BE&?v71
+H43)1n9+b*mCR&>ZpfvZ(^%a+sv9kdn`c5lc&ip*W^?fEI07L5K@R9l7v5S1P;%}B80^NvF{;?c~I##
+dIvPPoLNbFv&At~y#6<aQa3%s|5-Inzflwqu-Z44~;aT88{>@B-GUT{w&##`uK9AZ@vn_lYcy1_B57s
+qeuOk*Mx(TW;CdkPlkN__ZZ4=Q$J6Spn01sao2nwR~9OhJ^dCahYS=O2S|#t<l^QZHDm)#Pw#DMZP@4
+L=rdac}(zom^tT0a8VWYn-w{iaBEC2)~jtuq+zzLDKT-l0*EL-+Z`awFZMmzPs#0=g$`}s>ZV?ou`?^
+|O!ClA{YxISt<fvZ>!q950K@nExzb!;dTqt5-#Bdz@PE&FE42w2tFFO-n<qO%2PXteA_>x|)$W_eBiM
+0`Un-XE`1QhIR+jP;8J-VwJo6UX;q#F!VWNM~tQs6qLXGjL&m_hikr-wUui~VyrF~Sdq1}_nLhAtTBk
+5bMf?e$7b%RgHLzu0rMlK9B6)3A{8TK{Zm_UMBT@`)#R&h8J#WQx!&tmG!tB(`%wudiI@_r7lk8H*lU
+lmnMoL_vAKiGZ~24sI{!xbFvXN;Lov&V`3i(V}ZkcSD^B<;ThL-EN%BFF$pRZO-kD?zJL7WF#))E3ex
+`&4^RrTluxeT>`%S=P(wl+dFfQzo2pXze9L1>WSe@EJyHaBuu*jcK%OR~HKA`2X_i<sPASpsL7AN-L~
+*VA@5Il?7Q*wW`?MqPnw#qw}vT|JRlOe|hBt1%l*`PD*!N{NnuSFMO@z3zZ(hA|GDd2iNvi>P&v%-ke
+g<kl|nhj}QtKC~F|)ZQ(~G(tv+ai!r$xO_&EUtT{VQ#YzV&$yzPDp7DiqBSu}0AfU#a*^ko+XAd4+7x
+ku6Z8sbgU};3XMVD4nA<NOmg!*ADzlWnGoLI?wT@3p9y8?Y-efoI%^eNj`+j4z9XYCo=S3T{KDJp%pC
+)cW~8g#U+Hj`<x=p1mcuFCbB#pG?NZsvV+bycbSW2*D<)cC~SiFChWYxrT>mH7Mzbqj57P~+W^Z!YX^
+m*qPX)IRzB1gXTtt(khqnTB5D*{JL^BVscUYlgFJaf{pS`Wh2Q47do<AQsvC4@MVeSTs8d;uEjze7^(
+Upz`;Zli$C8qi#P;PIXKzt^jy2)3?Aq?Lg37v&*L+1_(My`>`3xJJYlZgSJ=Q{t^&rln-<>qMQ1fDxv
+g3B}whrXRxlje%uvBm)CaB*L+6~#|UtEpS8zRJOXw&**SxnCNy{=IGQ$LE-02XI@i<UUlsj|Ig}o`)|
+;PZ6P@{D5{Fj5_BVZ@h-4lF6kWIwbPTk{AnRjdtc}e#|2N$_S`qZK8<6dctyznIvCkS_exUX%zT@NuY
+;%rTvE##sBDYyaein#@>3RE2cJ}J?SEuaRU!r=pD*K+QSs(tHwwX6IFhj%q(7+QpxXG*wfdr$U3z5r4
+&f9W!%F$$?jU)D1w29a^x$vqEqp_mk6A(;RsR)!vMV|~kNlAkU>!H^j+s4ee4lO2=w58b5`!y_xiWWt
+yuGG7s6Hu#Gwq)A(!)|_jR0z|lcy{B+4ja1tt(bX-!L-THiN81faz->#$zJWN0_25vc*^N87m;2kS8c
+Q3Wp%Mtv`<)2eGBtZQ5qCV3Bh*NktHc{;@majhDRJU#;`PXICUpMYhSy$W)F~leXZrjwT2PV%FQ)w{8
+_PHs~w6;*Sea{A3$+*OdFj!a~`s3$~j6HPff3N0hwn5hao25(DsXSE$o{_qPq88lCi9tJxk~I3F`%Dw
+fRcD$flNxW*dnb!8J}@!6n_o-iiTL7%d^`LhH|it%w#aw?+`=T^K<(9DCr{ieW~0=!s(+2(aaA%py22
+f>{axSWYQuLDP-)EMb|%=Y67A5^Tv~R3yomEG<umI94zh`AQzvh)D|2Q?c8)X$5xo#CuF;WuPMtAwfh
+EZQ;QupUy#00)gmQ3?iHui}rZ?(IR{F<i{B0<>b9wJ|Es=!yhKGEJkBaF=`ZZyCFtRFHddyHqKmi2St
+|P#OtC1;ZN1*O!8JGVn7bCW9o|MMm5S#xp?mN9Jt9}@E}2a$YS809&dg%e{=~C-RCtq=&s3s#g-#7L%
+*3+D8`+b8IRWvYUuEQxy`5~Y=i%*ZO*`Lbf^=);=nLE{J=V(!orPUa}4i`*=CX(4zj#(U!+dVr0FQTt
+ct5{@t8S|hk9Z-0PV#eUcUPJ`Df2wKeymQ5nirb$2s%I{=zk5POLt|T|7#NnM-;JwqzG~R=3#XitjU#
+ijL0RQe_dDV&e^FuA7;L4X;qYtxsXbHEr|^COUGVZX4(ZNC~P%H&R%Z8(f#Yc4yoiZweBgN9b&}Q5^-
+S(sK_;ikc~Ic|;FdUV25I@<@Hn(z`XtRoXGe6nvC<NiXnnqhB%2E;2t+;Ji~syT0~9WhDUUO9Vq~c`@
+@BrOkrE5r#l`lLDfRx0~>cib~87>P%z6Gh--&3E@N{vUm)82%x#%=xr~BDso+wS_y+rMVpOQ%b9p&kC
+4abQ@@1`RCFptv@Z1NU>S=Y=*)^Rl)IuZ{U$YtM=41!rGy@UK{$9`h7nYot@ODt%Kekp3UEqH_e|%=o
+VZ=n?s7VHr|>EXT~9-QJu<X-SzqA6?`(A!2PRGLSVnhCJ_?d@ifC#VCFYsuB^>!IOxWolc{u{mexC=-
+m(z**r*_@Kws^N9M)l))>qWkIguS%aflWl4d;SNud-eeZd{0xZ1qFuVYYebT^_zM!b+H>_r@k#!wb5~
+1rq*0X3K}eV?hY}P>b$W(8kLH~vq5gU<cY`(l>OB)fhIi>hZCGoV%xm^;3obqw>b;2^wf)HVH6RAAlM
+`-I3dLdMy^5GR$2RP`Gn`SJS0ZZ9zcz-rq=6zV!E~5An=y^-IxV1<R;HkJv?F3S$*Pjk%?v_lVu<W=v
+)oX5mFZ%*KAm2W2|e8^?G>u)*jB5o6-niIjjCWBrnH263S5wRAaCOLjw^;>)>zNvhP)GOlpR2CgqToh
+KUlcPM&<2zIAe=LG>N4U=1(GN~Y^ai6>n>)1{o2wtOGhKc&7>Cl1dey`|FuvgW_uS5+>L)vDfaF_pO5
+SZ_ddR?O}5T#VDt|G?+hEu|@YPnzP>Ko2Q1R#1VNO<WPS`ymE<{&+d0Xcg&h4`u6kd{mMS>fKQtJ)Eo
+K-mu6PLG)rkJx(U-IGCYB;Idf1(LSQuFfFsZ;oFt<FsIw_NXTV&&CV8JL(EAqU+ZFht+cJ2ql8{F{mt
+j|r3eFhA5Jt?#H3Y5J;hIugvGfOV_}@_R^Pim7?aI<-vUQ41e3DG;N^wh=qe^Q1@~PZr{oj1yR^;V@N
+!3{+E7$(mNe(~mh*d~(Ih8`;dv8>x$#wV4jT-=i#Uf@YxEdm4zHqu-@e2Z37CY`WW%C!=lmY$(u0s-R
+Y3tye_-?HR;qaGvcLe^fcQbCe`m~Yvup+brijdc!BaQ$A$HJwa=M%*&JYAJsqkY`&TUi2oD;+%8K_A9
+^|r&-ZgY^slfS$!D*(W9Nzk%)n2Pp~)ZSr53LBs>WBEzw1$Ey0As2){HpVljZ=g@;Jf?HQ3nyZfC&;#
+`U>m}ZQj7`}EWtVb9yUsjDi|Eg&v0Y+e8)+*hNCz(gfj{dl5w-&nL+t7fxWS@5_<O+zVK6@<zR=YXdc
+L6jMa!VhaxZVB6+vy`k9k@&DSyX5h1N+=9#AtVWeJbVFkgY>pK`^^_P#+3ql-Fs9!>sc-N!GTjS24aj
+w&d&`WnB^6W9LY*H_&0h_%(EFFNh#@+!nrpJdgmB^_K^-Ok9xf@Qz0BmsXU_g}AMH<$oyZSH_JHLYzY
+#0&?aXv)}*ti9X22>(Zzr;f_N1{NoSIGxq+E}<zL~BVz@&smgy;Yckj%%rR&@LdpxG)hf!>Lnn2TUus
+V55JlTGY-195OyqaO8O4y^O5%PB5>Hb`yX_;gZP{29U<&n|@-v9EUhSAlvVn&ZFP*(se57*C|r}dP*U
+;-a7P-^q?5gK}?0rEbFm73&seGUXocibSKVOVclD9hPUx+I;vB|H9T8a`wiLy^d_=E2{>4b6wXK|lv>
+%^{cvrs@`1QWjb?lk`VnCp1KgL2+bq+r^7-kbCrem%lWej~Rve6}w2*-W^pYAbq$7P@zUS;wmg5H#;O
+~=Z_P6%=6dw$25DaB_d(eG_v1AW);hCQ4bhkwRxp-76y|swO{4u-uLPWEsJwkLkXSGm5hbsLjz(+$1(
+*?unpkCwo*VmzWIxN!Nkb*X8IlWiTf?ct(Hda2IIz?Q>-Oh9;^)_~?eWj|VzA{=7^RX1_>$nH88IiH;
+d{w+FxBIQkM(RGB63I|<#P<lLht)Y2O+Pb{>z*EZ9<YZ^!hrjah4%f_i=|}yh9(rm7TS>jSGB`{-#$&
+lfC4FzN6l*HM>XRH0(8d#`Dl?%%B#9*Rgh!Zl65k(t1RiPC{G2ArdXZm`$FJ8y(|MOrTA)^=*djb5HT
+QNfdBpP|24V8^1o|4(cqB?&_BbPl17kV*{AGwA~3>s%(5VK->}{J@c!fMW6K&pBsl&7-ej4M3`rigFK
+fFlTH%`wnsAExRx84I$z!C?Tdna8jk=ykG7LL%jSPt@=>iaO(Ln!}LUo-YLZdv>6P3uniWjNfwHaS1@
+6aylYRxRLsh2Q!M06cUr5l~wY@6wBioj_gKdZan*X$EKb9~ck?z2gHZjoDILKF7KV+R^`onbbf;>8D)
+_-KOG9Q`ju<ISb9<))dMmKBj8Y$H?3{SEBe<t*9myPh*~o49SudY*U!Fk>QQ)hn@?EQB}o1MP3&QIF&
+bu=f1wAH1~~yz`mQV6OTD1a0fuuW%V7Jbi>q-`w?lHAHegJ*|))elSt-o_86LQ_2c+fQE)Xq6R$;T&w
+Jqjwim^=?yx_d6P~4YSbB$TSS~5#r*;(j6ErS3=&JQtY2yD7#fo-ET%W{Z5jH|t)46TeJVe9JIlnO<P
+P&kAVemaV-F4d+1*_90EPXUv?Ot6E)?>0QZ5gQckK9FyOQa~e}?I1m5Dj<1#%_3S*<$#QCTA<jtb(aq
+8HU7MKEIx#co2;K_4dxOw4L%zwjVyq{pyn7g+e?`t5JCPlh`|8xa0C*!F=wlUO}ceZ)n}wm*miw=!6D
+;2+p^o>KM;HhB!$H6b0c!U+$_Y&coQp}eU;&CNyzozy{Ez9W)+a?3Ue*V1JC#07I^)+CKC>GT|~1(U2
+4eai2f2UEWyB+~vuv5k?;C`mr}<P&=kj(o@}{JhF54DphqUIQ*Ui2=HKQ0xd{f9f@Bwa#OS&U%~REJ0
+^?|GJz<qAQV`Z8S+0UU4W|R3zaYdjP136B)M%yAH>>G9rtF=tSCI+Cei}0X$#am^DSSaTZS+UV{?U-A
+2mf^=FKbW%?RaRr04Mc{fLx7pP^@340kwxVL*2$ylX<*P*GD=t_;unSSmyk%I$dxzd|a*|8z>(~)D0*
+8u%a=%&JcvqdZ2Z(kPn`pyz@f<Tji?rhx}8>J)l*w&Q{p4PTMG9SwQh_{iE(0?3cQFFo;kM!moE~^92
+@fT)x*{PPI<LjPvKxb|`X4%Ew9j7Ud7QdO*5oXSONB<wbA$ao_uHqw>!;#A%LH_ro@|2ZfjF1lz@DC>
+3I}vQyuX__{^G4NSI9bL|g};bM0Byx45z)IGmy?*PrJD!t_VfiujyL5<E$zrzBvK2}Nh?Y)G%8{3in8
+?_P7Vwq_C+CwuTHv<U?=bv9mibve~M)!_=jCFf<nV`_l$2H5lX0wJXA@FOc?%AP_Q~(BazwY;O2Iuw}
+fdSEu8p12~lqXeSF#_!Cxnw?2mlkh8TIm`CxZz{07;hKgrM!pAT44iat*S^6)xnVrG>R<dTI^u{_L?l
+dsRr1ecMaMPzOF*@L*#X7_X!bzu^X4D~5nCs9FFH8(5rK^QcLeo4-3a$K*mmz3egI`#mL$W3X+dCuCm
+ynYXc_1hlC$E(+@>>+0oY!4XF;dI^6$P=c@7hJ~orsGddC?3VAVKTs5q5+!?lnbyohBFS~e&a%Qtvg?
+;&2d&o4#!`^G>~`SsrYETog3&^O=1i8LYt_Xw!A8#ucK-?+cP+)J2Xl0U2S*$tvH;HI`caaA{AN6J%<
+S{KPNEk7_;<`qA_`UU{W7Sjrbo22jWVcjwKf`p})2%E!7N}yI95Iy`+zGRRu;%m^8?q8)NAOq?zkJeH
+u8z48-xK<#_F+nEVE>d+&K8Nu2ZC#mcbo%Q<px0_4~TB(1llT-ti10oFsch+LM1PV_Gl6<K^G=w*%`%
+L1bObgtviy2rdT@qQ-dHk`@<p7}Y|l>D*~Rz^mj&QMev$fKN7mk}ZtwQe#Eb)3Zqvv9eV4>J_<TYjl-
+GQ(DcckqSkZ<Oqv7@iY+Ouux5i@uHL$`rf@3mE1zu};Tdtc(lM$MeUt?18!WPBPBD04HbF7WI{~qe35
+fAJ!~@O<wa}jL4wJUOI@>NsR;1p$_F|D*iqJ#n%omN~#mDQ}UH}DN7RH3df$OKI$L_k`5J>Lm3Dc9Xp
+_z07X3!iIdr(fHC0$8+cUHy$(Jgq9E?$3HBcIvLNRCCm<CWjxM@9;OpTX0d!g^{-!tn9<(zCn+)JmwW
+|wgdE>dX;<bknxOc9Lz95E;G9u~*<2NP5hZ4q=%@|(oo9hyKh~A(HLkPmuW1`>6^@A~U?lm6!^=RLam
+GKR65Ys!JKVW}kDF;o`n~D~m+J2_t`^fg;KTN_O^254lRq-aV$bQINn6a?C&+tg__~+X2+Vsk%d+*mC
+!AMkdkQ}3uV^oFL5tJpmnf4G)U~7c3;{HoK3_1Tg`r>p(<J3hX^YAI#NYNL!F+^i{rRj|7dGmNTN;5n
+W>!Os3D9^pgpM`x-$f!rm;@}J-CpNj7F~<DyOs?Zc0(LCzVqGm1m+bIHw~x{t8i%F7{le30JC&XfZ?~
+~S(@GdycV++vsg&_b?_?C#?lNs?*M+V1Gl79VIgmv(>4Houl^^2c2)N^JjBCe!b$0Zf9eunQmsp3_^V
+3I+*5!bA{-cG#yQL35C5W$HN@PK>?+&=&|6E@h9Qjb-F&`luIGX(hvry2NgOAF|bmx2xp4&~*=gR13{
+&#$>Ugt7Em!i9U^v~A(xxy7jKGo-c|Ji*1uDGDoRioeFJNy}G_XX*DsO<QJ?VtS9M`>(k6@6*m#yyN=
+7V;q6J9Z*mTbKdECh4*1c>HWVoScUe7s;>(9c>XOD*7_WSu+s5CKNlVh&2=br_YFK8DlO(9c{!`2*>b
+|q`2Vsn)dGHF)mh4-=LKQ6{i4bISY^WCY)tR^^0KA7J4zH1sKyK8lcurS(S?{oIJk{AWCGwOGkf5${f
+LzA<?w!flafd2XC|o61ezauZNZh;Qa^dJ0uP@=)>pHX-kf6ATj|5!r5hMoD<x3I<O^uQHpO4vbs>Xiq
+eN`uNzJoCyX!S89!4oXMUtvp*NwUSQz~=)>`yB7Tx!kxhWg3b{pr)-4AT21H2%iy`77cd<lxxZU(g04
+$RR;^=jR(Fry3%3^~7x5DJs8KHK-rBd(B%3beQ5hJ3dSr8-K=Xl)sw1|(7IglN$wBKN(I7KL)GOMv)f
+8ZVKwePQy?dG=tM&mT<xW|GP(3WdLded5KJFJ3-(Fh2<OY<nAy)FCI#48~Kj*{@Z8wT8paxgNO5>r)f
+``(rguko@{@vrm?^<M;<--?ezxI~T~Y&OM1vS>nBrqs#tU_i1&tFE?s1MX)Y398jOm1{`^m|M!3Xhmg
+m$Ppx&Rz!IBsn_aa^)iQs3+K;v~xTC)7%~*ezV3di7(F7ly5n=lRWA1Y@Xz<w6H$iZ{91`V@^+3l^RY
+xiO(Gp)IMZArqFxKglq9khU6JrO%h&u8ECNE7|6f*Hj`Z7?&Y((qXOE8dNM^m<dx}x6aO~i||y(Gvqp
+p%9;!Dt#%ZpA5~WPFZ^#LT@eV<_r}iCjPWHAR18HmO}%DWAXiDJ<-6(e<3LCi4<$VWwf-8z*7}dj_Xd
+FjA4zgUh{yz0!`6D@`g}JCr#+$(?mFAwTxInznRHCj3c4{Uv)G<y^-Lx7f1YtHeUI23^DBeHIT#HQn!
+ShF^AJ4=5XB0pjAe*-$z(E(L<9oKYVdqTIF$)F8>@f!CHHkD$dMf=gI<7ZUhG@#Y-+=H5-S(`5_;*R%
+MF)Z<we)QaXvpnObv)$$#YqJTG(MzHA;1}fmiQu+`@;$<j05KYFqIMBVx<UqH)g{Bz-Ed-H(M5Id{7H
+VAznG=j|Ut#paYDMRi)e0wkwVIsbM`w0zakVW@@l*6`6r%|cDHC_)ZoUF(cGI+T`c9TnspwB-X>|(sx
+p&6RTr$pY>M!9)xy{O52ZHRTsqjn-Vl#B7=ainnIkC%t<#JbcYZR6hEP9k_Hc%l`<-UUj04-p%=v7i~
+$_?7?_L$1)0v&!;&!Ev=@~SQ{@aOw|G0*;lUOcej78}$U!VefuS!`$7_j_`?!?brBkUUhoE;aLq6;f>
+14MWC4WmjTL1hU*g;Y{HNgtySAh6eym;Z}(tVe<t1w0r0YkCnu>U8}B15mb_x^tP$?yB;%Dyv31bs)H
+?IT~?LB5DaJ!YxSxu`V5m)7MNNEZuadwdro4K+9MhP2hDn2C^#5p>;108ujirLPmLc!EA=Yavuw8BSG
+xkojmO+_T^5+7T($Ui+f>+%0ufXKIy#Nl{dNwdrq2meJI(X(vkT`Fn&S!V&65jv2p%X)lt5(x<yE;h0
+W5~P7KX5L|HZuB!?TGwe}0Tgua9+8rpT@>bt*Zt&L$wWCJT)NXHD7>;I$}ckHtm@clRbqRd+;-7u8<L
+23f^-_x5lvIHEaNP$<;M7D>67Zt#BqP)h>@6aWAK2ml;P_Ezj<p^nW2006-b000>P003}la4%nWWo~3
+|axZdeV`wjQXk~3>E^v9RS50r@HW0o0R}9pPlqv%DYQRO)ZdxpmZi0>XP`H7Xk?5GML<%ImyN2QY?VT
+a1FG~s1Vs)@SNDgP-yf+++x>4Ffq2yLPHB1|>7hA1ru!ly-ClG%8tte~?H^SiWyW150U=0nYaNAg+B&
+!yFRaWvX+gCO>_E2%tEx-Ql>f_BizhD1(bA2DCx+(39dwNOzZGC9?VzDSHW(=%%yynXV;1xyD6?tlzk
+X*x7X$UqXKG%#qNnvkz36BR@y7kLX-?S)p87?!b;@PkM{wZ5HlUMr5c;j>hr(=qCW2_GTJfxsPn8^~Z
+p!UIo+J^llt8tl<U{$b@!CMc6p>OY%<j!3NmcoHA!tOwJlRF25+;J@|#E(i<qg~&Hk$~^)Hfz1-S&Nj
+9&re&zc|?8`jX|CZDQup{Jqo<qrrpXm!JClsffdTr!vm~bd}-_a63BV{O71wL$#P^n3ox(FXn{Fu4si
+lv+u^_~!{K=9@!7UH5(e?JZs*?m*$&yhDVgQ*Xq>L&<O^Mt#bwJV^uY*eERzL~&48SVcgj6yPB4BrnY
+BqtC%b9K)HZX%^4i4HRj1LH#3$<KMyrNvd+5^U1shYe30(e!R&|d9rvG>DL~Xf5ZXi)vSOHs6c`n)=V
+(93Y5nbA~VcH6!jra87FB!p)5aBKRTM0Raa~mBgz7sAuy7{MQHfYp1FXLfy0suV%{gdW)uVrv0AmG$o
+bGuVz2LjcRoC4~7Dk_tPg>D3ub4!#(4I8!B1s^b)KEHy!1aIWZP&9)0MzOL}v@2=&!oOOmRmmOBp~%o
+RE;K#R&Pj-alT=<L%AWh+gOTAX9|Xisg@gKl{<+zNJLMa_@^+kwNi`Z9{T^kfGx)(J?<`nf#j$q2=U)
+P1t-7)yrc)XYPbR9~_;Tl72HNp+GR;}(=`g^y&HKvV`bAw8I(p#`75$l2dsKQ)WcPuH9Jcc0jl7L0=|
+$^fTls)}WiTDNR^dKjx?A-E(J8VsjyKHis9NcH>ZZVDp-L>+^Mrqy+8_9o+O*+|gr*6On8=$udPZ)H%
+MOLX9`ON>=eq+&C`aif;q1=||GkdH_G)37O6a;B3Gx|uJ}0185?;QN@UA5w#m0nV3X!%^pTt%BkN`8I
+`Zn6NEu59f`r0@r2EWIImZPTY-m>DKYps=zufG=D0hM%}*e?uELEe6MQsFe$pc56Ix+Nh+F#6yP8FL5
+CbdN!I=ca`O)YKWxbZOpT?AE(}Yz*(X0UEV9zO%7DHGVxQVBAEwGb+b(Qw!>UsOR0Bw@;*^jXyiXAvs
+?Dgs1OnY-w}(=7GNVZZ&(e%dM{y6UXLNJ>xD$dWVKOwJPaRS53=f5B*EZoglh?hOiSsawcar8H%eb9m
+QU21fg{)xHG4LXS>z$1O#K;gd8s}CRnF%aWTx$Y0_5?M?>#9(~FD@XV?RCS%$iv{GX(&W{~q|@`*sjO
+qNgzQ!rg7ZALF^W$aAPhLPdPACI<9V6}obXXSwjjQd>N(MRcuGU^q*gGbh46Fr9lPK*Cb@C!jAq?0ty
+$*m~QYy1zF=g|`22WT{Vs@anM5Ebe({sHYd*&d{Rw?+$TV;{e-YRTeXP)h>@6aWAK2ml;P_Eu4K_E1L
+v003qH000^Q003}la4%nWWo~3|axZdeV`wjQXk~3>b1rasODoFHRnSXGO-n4zDTyyGsmw_&R>;gP$S*
+2UaB+2W4D|_#4-Sd+aSi5511l}bNX<=!sR#jaxVX5WDiv%YA{wYVHMsy#O9KQH00008031s8R_NHy=T
+aH~0HkvO0384T0B~t=FJE?LZe(wAFLG&PXfJefVPj=tVPk79aCz-LU5^~caqs&p#>)rJQmYYZ=RsI#W
+HTaV5s^rNWGn;c!*F(|_il8%GpqUF-HIUK#CfxUAVC}?M*NVE2fqY_?F7gdkpGg{wDOd{kgDqMkD0rp
+NF|XxiK(6G>gww1>guZM>b`YTZ=)<*_g&wxEQ`wRu5P+0U$*t8?^wp)Clm2~Q&w!1ua24gP`C2eZj*Q
+Gy4lM2cHd6ch`q?We6`8jmbDVS`ZSN$CEFAnuxs)aTjr}133i%qPO@$(O7}aB;Dfs8H|!yNnnw?1HGE
+aDWpyNh<4FY1&1yfVAMfOwO}^YP{&uTeb^O<zjy3xG`(-P>-`jO%UF948_JDoTvuY)v9`-v~frz1Bzh
+43Td@`GGVs_;&$sV(+sGDTBKiaaYYm*H-V~y(0QP0{oqi-4TFk6=!R^?kZf}pEUSS9PfQ*ZI>Jo-JhK
+dqZ$9^Hl7@Nd6evStolfUb2l{Cdzez?qBUeaOy07Fzo6LoB#(#dCoBuG}c%Q4sFd-Me*P6@q7pEZjA$
+>-OSfwyEo#EWzIyRP99J3IujrwVEaLstPL*Xr>G4buNGKA#T<CeIQo|L&SgIXKlX$1|KzbzcY}6%$Aj
+jmOco8<MQZu1OEfTk|6il5j%TNe@Fbg#`qwr?(&K$4t<C(qM%*XJJpYdXv^rEEbsQZpAYaw7VN7oKT{
+?2CW<;7W@E_Z=VP{2s2<|WWb)CSySMIr^dL&rd<VpB$F}h-O4DfiQ3(Tm+D<2v_wT)P^Zf_e2RFZ)y?
+^`ew;#R-b#7cYKR<YQ|IXcS!{;}zPbQOst)mk72eXq;*lT<?iJ@Dld3YcO=@4q(tt&C<PRpV@Hh{{iJ
+ERt`^K$4`lV_;E+6A=JLD@HW33bz`2}9_hh8dNeHu-K5E$ey%W$)&jRus0!^(n~Z3ciGjc}cd-&tQ62
+M@S-X++&Xi-_leKz;nJ?@W*ArvZ6<6P*gl@dgcSQ0!Vciq3!;{5W*zQj(UJ^1L)d*2h*~JBB?SDNaZ2
+t=7wrMM6~gYSHd2x8_-IM{WLVQ==HaiMm{*eY6riYx9s-WiV=l}^T>LiYsxLfe+Yn};tv<p+H^X-!(}
+PTqo!OP8;i?vUKJbGBonUPL6=LpW1u+mYOi5i5Gz2jWT1zDXjZ^`cN~eSq^38nHGq^igmWVA@Ef$iSD
+xmm<zyN19L1hI&!bv=nk}Rzin=;FZOV>;01FPlrzE<?);TDosHasGNNb>)szm*PjwPy9njS`*I6bWPK
+H>nN%vQ%a^dB&`v#4HcW~fG6Bnn1PV>c!jqUbElx3Mtdg@A8W7tBWW4ULGaoY<O+7P1e;3L+q(HgEv?
+J4EKAM<~~i9!00eI5;$%yK;4+TEr(8*m98T8b&$?cEd2@SFPqWE2TP!Vw@UwUn`Vj0*MfW%n<1GriT9
+#3vBX8Q)twNG8sl*lr0do=V$>mdYl8vP%@6&(?tGAeUP7(+kP8~avCg<bRZi{l_di<0FRc-hCK!rLC>
+IaLwbX_Rn<meT_qNaZP5u*#r54qs1lHZqOR$yl|v7-0&GI2*gSdDZ`x3u0iM4Hr2-Odk#%_{l|WJVI2
+u$D7U0Hd3Dsq|t@iS5wa~edww#f+^!KnFaj-~$;lziTNqUUaFxDTr1Vpj4hliGcnO<t5R>0yIZV9Hv5
+!>b6F|`3IZqow|wl^RY^?e2|N@XZgxoRxXHbI6xF6+KE^rTSqFpYEcC0a0-VB)M;Auz%s!3_Y}QYLkC
+Dm7``cEIu`#oo`Na;>y?*>XW+z<K#`GO*a<DyXPNOnRi&QS7yzlx_BLzuTkLs7J#>C|aLs1&n0)fK)!
+?bfJC4d2?LXCz>GitFlEDT6q=B<9yQtpY4TMV~{;q46V%^mezWtd*N4Aou`F1wseQWm7ri`YJhDh)t9
+;VnaKA)tH%8zS}s%i*Do|yyVUp{XaHB0l>QAgA(xR<{qli~1tB$l`+%NyPrWarmAFbxy)T2647Hj1pT
+?_k;Y?96#s2r1U)j=Vsr44%nb1wC{NaOWV>H!2Z7@BzjQLaU_L-hT*=kd_eZ%4sJOi*jwR}g>6;Md|(
+KcV;vbd@ri@AtTx6Cm90b1e7Qv_@~T*b<Y8;+>B@@3t3H1^tR1uktAih?WV%mzt;zQq0n=ua5if#zGY
+Myg&>Tg(5%L`<C|SySclwH!@Y3ZX>TuAQ8!*T9s<2Q(`gNN7OG);!uk;p?uG1%Z(Q3r1>a`BZhqO&-B
+Rt5EZm6KE9%ImY{?yEO9|A&f197ZzHRF`%}&W8nCKHpjGB4YKZzFy}XW8g(!NG}CBl{Cs=@0nR#%TXB
+KOj#!66o#8OV1`F`H0%i_i>y*(+O-3N2!UuxIv2L7U7+eN~mx;@sVisSz6io+TKlCVIz>Y0wSeQpm!&
+V*ks$Q>K)>)9Ndb=x;TdC}J0$q!zU>;VW$ue1<p`A0G^U;~PBE%89I8*`DyTR=M(HN0`edf^Iur17al
+pxR)m3Gj$rZEg0Zr_DFgi|6z!>q}xBNi*5*}_+l;HNF6S>PAr1D1Jy;*~%x>}mqYD~$ZOk|NCoJwVsN
+A=7U+;H_JFT(lJ2YQyq|V!lzo18($fe#CT3SEOAQIr<E}Se6%L@w=J>=0$y~_`7B~#;;q@{ov$*rB|?
+Je{_US0{YK&b7HjC9Rr`>|6%x{3~fVHQxa8Cuh39jQAD*MvlL9#a=iyo24deYDR7ObX`X_oTs~$Gj+v
+pJz4=KqEuc&cs`5g3jA*dJl9BJQN8SYXv}hX8*Df@lX*5*<ev@yPMIJf2Z*gIDXJ|UIi!}~+$?Tf__)
+>TU1s7)k#!&eH%*ml&^{_N-%TG<+XY>ksfm%yciDxvdpkbgBM-?n72N*nm9dtNojpER#IIw(c`EAI{z
+|D(9Lr(N$h?M=iFnUpg1U0865RSyl6^{o-BZUE<dQ%uAKtBR4;bVUWxB!fx)kZm)OunVIS0?mt^e$>0
+POscqSfCTl{T1L*RZ~!o-u+T~0}{j{BZHkv$>SCZcl>y?KDi4D_E2j35J4FaKi@`)<aBY(rl|<iIZXA
+oJ>rFd)*f`|o5(@TxS&Wx_(ixk@)MWsjOL5cO_ONVITEWjTjenD_PWozAtIi*n{+_KfHi5)E0!k78dO
+N#?9&av%tG|jBFgD+u`3cE^$V6u0rnxd(Z)tX>~1xPWkW?RTcG5ina1Dz@U5cUzMWiqV}`$%AWv^6ug
+#_!vs%SfaP_7NH8yIig!|e2y~UWC<G|ZtP`>)bgxZQu+>9R4$461U{1{jJT~il5c<p@Ed_*4Cs(WOIC
+n$O?f_xYgwHGAN@3>Q>V*{56jPgA+3Wlk`C^k`Gv!6RSdb21>5goB2q=<#H^1N6nO*{kRJy5U>Mv``R
+sFX;y0;T`oBbr}8oa?ti)2~X<^oxyX%2svsfrii+xJs!VQI78NG1|P9saxmKbty+%UNfMHRJ4<Rynp+
+<x9{T)?h{4Ebh?P9xC=bhL6B*(+v8_$W7!2~1(vJ=CHu3XlCzRyYuK46c&Y;{8F-&%mu1@AY}sb*gcx
+1F(%!Yi=i1!X>m&QY_zdp}Q=8}Q3sW;=d&AU^@%>?EI$vmyIH&^7*(VOq-N5E<c;XF_e%@BGIkPUcU2
+IPdYs(mm3>UZ*Ta;n%R~meCZRpJ-(|Zzzwv2w5b<4G?uHyYL)f6K0qv5p<IpIx?4#Ib^CfSgF_!^%n0
+nnVjN=UDQ9q>tCHn@7PDHbDwLZAq^Jp+7)5j&ZB_#C&KxRlb&N`w{V(=g7k`A|f9Aa+V^$%g5_b`iI}
+Qa)SlBGYV2&8g}jC*vj+2`w0{$>>we3xJK&ylPAEqMMVcLzuREQazDv5Yv81qfmzl%r-?*dtTU}zDbe
+#8ep)BSjAIc0R*d<>vS4W0K=8qP$jXe<giH1Z?$p?Re7LYZ<J>Vm;r0bZjS=2>besT<-BZV9z*O@ouf
+4q2!mmgp-T939|uR0QJNj*Jhs%F^5@KFHjmcRCr;I`HBX~$5B|gwOgpjebDQI;M0z#KI~bN_-!Xq)qI
+m%9soMm9B}LhwtLt`B5ok|i3^@8d7bqPRlK_ZpwW^yf{)pv=eA&`F{xh@Nw8lBXAXQaxI9n79b0$Ug9
+skbU(Bia#YJj{AwhIrRa*6sDd7E1XwnL#TgP|?ImAMP1-Fn)_#5^Fo@a1e^;`3V*<Evs~;Qq{1iNRFQ
+Ik2SPX&5F6<?hamPCh_;LMuu;_F;-_6bE+RDQilldqH{P)#VmQY}K=>5rAD!6B}FNO?g!m{Z^kv@Wrn
+G>SHC&lzFM~5;fsoO3Z}#@#^9xB-O7lcH+&fR}(+M=YKbbg3nMK#i8ztj-?pQe<AS{x4l;$Qz0Q%ah3
+B_^UI8@;PVB>R`Bui)9}%e^XR6bT%}#hL*`qUzB<J?G1nRO8&iuj({Ba)C+x&22QIv1%)=|fd`R;Qry
+X57<>=DsMlX<R6i74jKj|t)x`WtF1HRh)v^hWb7sODS*o9KW2GhgNO%1!y_*^(?>dP>Y#Fg>HuXB>VW
++P6BH_^ttkD(;WSLTO&dF_9)!Hw-td_XJS=EGqI-E{U`@@2ESU$q(dTl?&*W}jWaW>NNvwpIA%`o8X?
+RbEk|3+5@&k;fh;V=ngXQH~$kMvT@}e)@tPCX}fZDv3e|5Z$w+bl6H9PR#Cn@Zr7t53_eZx@D(uw)vW
+&+{785SvqMIK6;6lx9aL@CsNClCoi(~GDMSQ*k?Q>lplfrpSXFKnDFGs{Y6TVrefymm4U<}2gCF&9bQ
+0evuK@T4&vJehhdOl{86rKG{kuflXqTHm!N_4VyYM>za&|P!O1KOq-86OXjh|8p)77OxT*Z%W?Z{LU?
+Tu*Y(^MqIDrr_bu=+kc%av2>P|Q~%=3>@)l4GtK%x3|zbE*}3?-wE{6xDB-<*c)@ysQo7XL8P5&{_Tb
+Xpf%7-(SI9vRT^=7Tw`=F?Kfb?MC(QC@=a<&Gc2K+{RU+o*8T;T{avPCl<oZ~~RBqC7%6M$bJ$K0^)<
+ZPCCPI|l8`fng>HO-a)jG#8S9hv9LdIAMEmD$AzzrZN%B_aWlIA^_C`Cl|t*w|h+Y5}Dh&`$14X)4d{
+GMS;|LB=#LEi;qD}<vO%>Vblf?B`}Un*W!{9PqS<~KsY|Q(3e&3?~DW*X-67);Wjw;bnk6>L(Y&mLgU
++Q-T)L%mkcHpa7kPsq0d+ah)|O@wGkz2N)%64wZ4ua(0^4OdyUc}KUm#=YpDA|#N-|fnj~#3QH-$6pj
+y`bxGt;MSPAC}Xci>g>8uFmQM!9(JH1)GEjyJlA0|qTq0iuk(@E)%VePAQ>18yi80Rny$2KsYSU7;1`
+_xYc`3`cpkZG>KpT}Tk4fIJq1BcJd=W?gE+?p3Zx+Nc99^~UI8bg^6NDQc=Z5z+RNS_W#{ZQ_Jd}w3P
+-Uu5eU#wh2;O7?hqdsqnbELgs8*42*SUAU4q!kM-;6|`%zktG}Qqa3|=NPA;mS+<W8fh5)LkKX<C|Hq
+Y!<LzZ^&qZ*MXURqkxjo89FJIXl#nbKRxqWn6wz{zajO8jt6T6gO0bPrjE+ZK6@gn1)QVz?ei)PtnvE
+ic;FX6pkF26Cp$yNMqVeRkAsMbTczDdz*1EznA|o$#s6Ge7bS8R`W9G*zF!ua-#+>i)lz0vX?|Onk?>
+k<UA2IN0S&M!W9+Ek#%1;5(iCEB4qu{|0JJdxZnqztg8K5cuk9Qb@=MAY~T*fD?I56zx4C)JG)Ga^Ub
+#52Vbw4`9WZv;(q^OJ3BAsWXijebo6;M@V{KB1-LsR~dTWF+}(IrWND)fb}ej*5mPc+Vw8oG$bUUK~9
+YRZ?W>B4L=R@XQMoU^IE$O-d6or>pH;!BQGjbAo3T5sJ~D;x}`CSG5ayerB^5%9enw>o_c)oa+U5!qT
+!9dU=&EP9P!n-mx2mY@3{LIZuiaEGbF5(jf|OjN^o0%N@87wI%ckw9(qE&<}ou!JtJ%7Fo+2-c`jUKB
+$Gi^~htrR%Mr`KIvt%o(2CVw-Y{F41sx_DK(<JJsdAXv5XO7z&8yD16fH*s9DoA(2+yJWtA=x_ddttS
+P(H3F{kvym{AH>Ru{lXdqnG@hr?-goMDvQ#Yx_4I_iLh;`m(B9!vXOVKm!pMf|`rcVbg{JYhFPP*A_A
+YBhh$m9)Y6t?1#iLhPUmEDG=(*wO3OkWOlZ2bUOeHd@+mX<C|X~0BUV#aL1)1Z+{U40&g<?_iP(y1mx
+$Zfb1JKKTPk=lDB=CjL-0<HV_`aHT3=(=z1x{Mc>nb5s-v0FGd(r|rL6jGKKbD+g4GHdNMX*BBLHW(H
+nD_m!!WBQn10!f-1gKp4>SSmJK;%U$y`&}9kS%vBnQYN2qX|q}%5Iy;vD}wSlPZZ6EZ;Wf%8u3Mki_W
+X=3oIXCTv8KE1>S<dg-0>Qq+S{)X{kS5L}1SwoRkIA0SXO;8yIqoyPi8;Vbzi|KyMEJAM4auK>s3%$s
+y_kgbtDEZwjDpK%E`D1c75!2XaTW08vEA#oN3&>374kefquXpghDort&3T>Yz7a@J=bZ;-sW&DY(;xS
+LPk##wTtg;Vz_tUwp3`n2Ww7hne}}<lpLPN0hF_5}Amd-y^*Kkj}Cjovc@@zG+x7Mm>H07Tt|1Obv3>
+g4&UMH2a9Pxji%Dk6qNn!Dwh^1G{IVH82W|Id4@2@@r`{eXH$2<-I-iY#$kOWoKpEwQ&$bU=gCNoAiQ
+nIeHRAOH;-5y9TCnJY87O<k}6v;`W`@B9F7q=DxQzfI_TBc5@f8S-4EQ;}&Cm<Ai}hTP8SZ=_{A^q(S
+cN%+REV1AG#B0>}z3scT@iXf>IbMak>YjX7o<#2(7g=8#3@r!1bLlgIbzkyIEZj#vJ7tlO`p=S+W?@>
+6gyrtp8)WKZDLu#Nf0!~gj6UmUz~=nT<0qo^qp7M@GrNFG&YTyz~{4wZe+0}njWPk)b|54fCo?QT<IV
+|uUT;Po4a=B&nb0s!nuNI@?6%Bq&s-3Bk$$Z^vKWQ8^sC>NCRJBm8GCI*ydd%Vnz6IK#ahezY&Z8BBF
+ihh;jC9%{?6;8|}j3|TC$J~J19clwN@!L76<GR}HqoO_q>UaRIlh@P8h@2L9w5{o4ppAXZr(&m+Y?xt
+`;|xQFxa&bLF$#t~`>5jtFCY&VHiARqrHvC*<Lfu%)rW;=(`%g89@v$yO=rXud88P9PXiW~OVrH6=?|
+is5gT)|Ep!TJ!Vfu9fFGwM?k5dhvaUpki{C7<w)#YNhIL7KuvLD3`n;u(`>}itq-#ldM#jjhcd6AZ5V
+BNdNJqnRe*aZ$O}xR3nEQDD5`wmK8alfBAF#BPQG_=y$=y!dPV+PGxUh+}HKyZx(Yx}U4sYa6DnT$g2
+_GaBy||7}YSerW)}=f+L{q*=s{V=r$_FLpYBe%*8Ajt~?tm@$PNtoc-~~4hJ)40lCqsMoT$!2|x({rX
+8dydnAsl4DWV3UF{UfXcnI(FkGJKSExSH6c3?FA5O;8c3{_2>P%8VuDXI;cYJzIN65kXyD_tHQOoPdJ
+gu;xpegXxVoqObeJk`-VC!$2}FP}A>X;ceLH>;_W2bFr6>C%?fG!`LOWTV8nXlG9b3#0Exjh}>kb?}}
+*ZF0ucnn=X8m;+(ES+t@i=?ez>y3s~BcB#EBjVAyzPPvtR><FWu5j{t69T72BMUAf+;Qw$Fd2JO6{%T
+Sml;MTb#?JveE4@IosAiOpZ6}nj~Niau6?pacUd9{!2%I5M+r+G=>=$tT~%{CAH`hK|M0@+l2F5k!V1
+8CUo2IiibDm|f><q8Q!ds!cdteOGA5jZ*hfjzL7=~jgU2p1oO=}Yg%7c~Me#4h15*h1!}a2YvXO(+1x
+m6T(9@Q>seISr0CHiVw?2m@w`uWW+b{Gy{;GX#Vrl*P;u7N~FxBhsGqVN*j~T7sV4V36tx$1P66p)a-
+Fb$gk|Uy6_#rZ&s$15!Kl=-&MioT8p_Mq6r4SZa<~MGI&V6?^zr;%3l(5ZP#oBKIkTI_4V#rlad>F7h
+(MqRX$umA9D;2lWueaNu0iGYm6&H@QMYDRwm5+H-aY2$amIbbRB)oYm4$8ofn*u<~n{s64XGpjH}jUh
+j$7$kX9^`jno1napqv9JP#ZjlB8hFxZP3=lFnS0buSfvBihr*P!CU$32^Xck42JYiAhG1y&b)Vzk+w5
+H>gbPxjQnkX=4jK1_o6BVpqLdoWsx51+Q<l8eu^klG%vb~s)v_vCK8NV2EnlMcdBpojNyU_>U967#b7
+K@s{pU>Ue~WtC;q@CCqxXY5b2aR~qKaq!+4e_~LDSeAJc=Yf0pKl}H;eEt{De*Ns9fAudvdHxT-`0Ux
+=fA+KQKmW65&wum>zxl}@J^#lae)jCg|M~qt{I8$>4ZuAA*<U~Z+n@jHpZ@OGfBXzffAGuazx?rk|J#
+qA|L{+L^RGYs&5!;H;Nkmc&wl>=2Y;fNQB(Bnh7Q@#->|^1Z$!EA=L6Pt?UAS|1=CPnpX*by<n4T~sl
+ICixE;s^`!Me}(ao-5s5}Ce(DXZ-yePM26TO!=Cv^pSF9h}QxL*^@X&$ntrnm5vT@~Fa^5fbmceLm<$
+IG4h79Y|a^Q=>GUA~hIqcezUgw4NZLK{j3D|HymwP1oK4GxEMbGx`u%?|`@)+Zmgo8n~s@dfXi4q>wX
+#))yMk$Ie(de3_z`ZxI>P)h>@6aWAK2ml;P_EtW<7n)ZJ007Y=000;O003}la4%nWWo~3|axZdeV`wj
+Qa%E*MaCx;_+iu**5q+Pp=+Jo}*A$_VFKZ3J1r%GmYwy}#NZRbfWWZ3vo|#_p23{-;kcZqJ^N=831PB
+5oK>i?~<S)o4q^i1`Y~Ca#>ku-A?5?Wry7Z~)Zf}Y#Vbwkt>6VEk&x(q@tauStS>dv;MOnG*ZC;5i4P
+%#G)OpNjvkmfiL7Zi|=E3)1BMPLa_c$yoMYzt=GK;w;eJ(#;{UXJeE<59C1S4O@{9>PT{e8yEI@Y4Tu
+k$_3PK$aaKVOR*kt&LWhh<$fgT0oY2~V|%l5g=#6P(LW-C6D1iJs$!D}T<baDAoTadsws)M1Ebv)LN7
+FWE)Gxou9-S<DzbmSvr=qEVJ@vVw)I0%}%PMZK<I!rqKXPl|0Rned6jOCB@3YbR&HE_U3M2jV~uiLIc
+A1QV;*NRoQmjXEyNl#@XmwX$pj+@d6QkG<fV5ZnNt8MCm-YK3iU5%J)@BDthzu}FD2BG|(YLps07Lr^
+VZ_GOmE9jPaAnXyQec^vN9dMDxttk4yCQPjMZwG-Q24F9STVP7_VhAC~aL0dXqp`V9wsicB0rKcjkVL
+>2LQ3ZkB+L^~2x9h(}KhB%(Pu#A57HzmOUs>H9v-$|3w4yt(;)0>#K!t{JhlXkTNk@|a1}m~`l)zyJp
+RqSt$`>8QJsGdQ)Vtdyqs5nscDu}Q@=Z0nWZK^gLa8M#wiVDXS6#9ueEh}+U4k|y{MHP85~VzmsQ1?G
+VHABdk87-5HXcQ#(6$qvzYoLxo!>}9!qteEEwr=M`Wdk-iU7XI9TF^NO>Y;z8iRZk2y2Y?v0$uc+W!N
+TnZEcKaMp1iv%Ajwk>J)0a>gMar9C%d6u^X8%CD8@vBhQAJF(ue1m=GUd95zMMg>c<NNfa;JTq#V_cV
+(*g(M`)VW_x6fBOc2kOuTpQp__Blb22Ilw<t?%7B#4rzy+ma7P{K>lb(2FMbbYU@+su9I9z<B{}1m=Y
+@F=ezehcElEM1B7>SasQ{M*ss<b6CZ;+T%u?l;r30sI+f<2W88~1TXMhI=jzOWMFj*IpOR5`}GT;fQS
+3RiCp_23^uLtjKdtL6D4ykk-IQ%-m1qS`9h@<spJMCn)ylN7OQq*hOT0wOjH)OQDJ#4a_F~r4`q$Sw>
+NOIBSxRQL!auCE?(T%M0Z%&?{Lh<|d&Be<%-@@DHZ_mDR+3A}XAi4<CEw>*VDx91@fB7=_;@g)mPS1h
+Bwy+U=Wc^D0K0G*}-(TWyJLQYB)6<r1*@?|o$cOj8ZQlO&;r*}SPkp`DUyeJ;`@81tpC8`;2L9C7U-Z
+{B?+<@!-v067hd;uf`ueN>GI-lK36!T>pSPC6Xivf`9*{$90r7dWU?PPbiCHC4_$uZur~xXy27X9pdK
+6ii$NU}StP#XFVGJKw+G^=|VYwC}$kKS<9RnW~w5Dg5G}~1dU;q<_%yN96%^U3VE;GPiLJ<3?ZLM*A;
+!sDj@6ef=h!HBwLsN;EZ^QLIxQ5AP*QJ4ntFiei_|Y!1QMxj{5zl1IQUQb_B``2t*RBm?Z8@tBD%b+R
+#csBm_7d0P%5luq-!cb;AbNSzX3m~o#*P8I_vG&L!Im?7r}U9@rRKNMU%o7?SnDO(;+XNAR|tNGZ4;!
+|m@A0wB}QlpR4N4kwY$!)im@;ZakH*?Qhrm}t&}c1zgfdvVD?!qAswP)L>_t88;*_-M3wUVpsVL9+%F
+L2@?gGFX?`3@hl3*v@Ef5d!PWHbUE>E$78+3lpS!6b)l?#_yECProw6{R2i!4b)S+IGF5ElpWQ5Yt#6
+yMGbx|PZJv8zgPSl$;US|(?my{9yyx<#g)B0PXS9ixnpfh*aq7OE@jHMc&G!ne*lFjzOpz@4H&Pi673
+ZmQrsfNKikHU%%Md5QTqH5=B$|SrAsAZJ)fR%M(ld|5LgPUTWZefXImXSF|q{=8Gv%zPosGOkYMB3d8
+>SttxJd7GmzOTzlZ1z~7rr?F4j9zqs<B-l)parPKpeXJ+(;3D$>aLFsF&lve+M`6f@8uBzYH(?`@os$
+ff<uy|Lpz<Iu%3+fDn=(6$uJ~*+{pS-sTkJ4w#We0$F>Xuxml^!h(D4qrg_J4$xsoEbqkHIoTrRQ#wY
+*XWmefggr{58rV3a?o?PH<#&0Fw8~de6hT#Y+yxDD|GSt!>8{HdfN5{NXhyOBvjTB}wm8xCd=mfgCK<
+3xf?x^VCI-JYN-6IbUTRNEz)7L1b5BWy2=?M3D!KI(E8n3I}2$MvghoJRf1FY@^KHdh{xLGjH!^XG2w
+B^MjmlRT^>W|y~CL$F{olt$)#>CCAP2Gq1=2Zx8g1Z%Yhi9_P#OVig7<ca~Q&CfW*|7i5<s~~n-}bwv
+>#d0q!FW0#T(nxyT1maxYkf<V>FX(ZqK73zuXY1~p&hB5;V0~Ie=Ow`7|1q8h8jt-x|*gp$;O++Xw1@
+Jlr)24lIGe0KWdo<zjnEG2uIeK)bgR}2etDv0?bw#88e*C1TMxjOkfcrGFd^8gkX-qS}^tifIr+O;Q~
++^{P~U-as^X5%SG-5?;!fK!o$Vfzft@GGH!kgc@h>^u!BvTOF{L03kz5d>oH0H4Sw80T<+5<ylHL$>F
+XBqicVh@^#y)NU1hs3o9rUHR)v7SwD4>s5{b2P3{o$QqF|lHb&}fF8IQsIJhD_h>s#x6m|D2O3$BYW_
+wnf1nP9#U72%%ZOu{YrFtnz~f0o^_x0{VvBaf;SeXGD~vlX(1I7+R-d_gVSdcoK1=+K3K^J7#Ew$ugt
+E-XrU5pX6-I$=M*+Fyt96)%wHr^io@-1+>_eR_O2m>EfZ9q!rD6O#Ijq-Jr3ht!R9gqUJa!X6zza_3L
+x?xV+_jtj#n&ZV$VJ5yw*xyOD!pU>r7zsCIkibsOPg1|>d?vqEy?z3mdw+Mbpf}bMKS+=b?dz<p9sY;
+oT8<{f+d9-b}EbABQwpky$ynzK4(SfU~mMehX1zo2gJvEKq9qD@`q7Wq>8COLXcQ5>A`piqkysyID#t
+Fe}^L@3;Fzl)w00D$jmS$HW8V3u`Agz;2UX&^rXA<Vr;`Ez!*`{dH@4<rykR!qbRPvH&_8I#UHcy$$z
+RQX@`pN7wXwjT32%*f9cSbvrZp&uAYBY6=N4E{uzyJP+f3f8yqflL);nf9QZ@I=si>}JrTR(H=>gWWU
+(Y>~{*g)P4Hdzdt7W2}tv^u31EEQO%GB`?sYUz_3DsV<bE$N7Fk7{49PO2;s>%PdkW_rc-<dQ&wNYwb
+xzgHf^l}azp-5lDyz(ZJQYp1yo90l&SyNljwq7()IzZc~|!`8)PswxCpJ#Pf`^)<<~hew7q?|;#CL?g
+l7m%4ZxQQ6k38h1Rh$Led<x~ng}Zzz(8b0t9&W*Bfm2x^51`*Hc;ufb30&e#8C#_o1_c_Cos(-wR7A5
+cpJ1QY-O00;maO7>QdzUl{X6#xJYPyhfR0001RX>c!Jc4cm4Z*nhmWo}_(X>@rnUtei%X>?y-E^v9(J
+ll5T#*y#(ieApcf@2Dnot*53iM-a#Xlx~pCTApPj#ozqX@X4>GZ4T4peU|ZAF$uGKel!0D=rkr_Cr<=
+GemcFb#--h-MWAm;&r*+RoQaYh_6q+`rR@7^Y7wMn><s6cq5CC<>u%`2=i~^JkM&i6aOiTPi4FJcjAB
+lr-8wR60cNM%d`vdr?Oscr1)M|dAV(O{{|`et#~hY;`=h6tLo?lfc%i9s;JdmYzk-+%}R;0wM^kZ-7^
+t?gW0mO5MRe9B0_+X?i!8%02p@VM%)3?qHM&bR)8X_#Ujg<P!FkEHzF%UTHdYmOctpU+pJm9G#W_^D1
+Oo?%2^`;S_1qUo)$iwkPQ*MYMS-*%P+UvZ7hk<xU806<_uJS`NPHQ^UJIAV<48me=KrU*P>GY*klzfb
+G8$54YZ_k1{CIUE6Pg9Wu>66DUsG~l{HzhoQS$yG+S9Iz%tM3rpjiUCSa7I4A$!d0IOsnMrT*z;%X#b
+on2jAO#sJ-i|g;-{dg@toV|a4c6ohqekI<$7q8!4zPY%*cy|d;Z^hZ=PvXxPmv1IQ0h?eN^{}pxejqY
+K7OFY&>q@DBfJMm!)oYbzi!6n870ZoWDzPl@RaL-p#9CE%S&bW619@}6l4o~WBO7YzEGj-aI)WL?su7
+D#kv3(S*QTM~*`Lj-QgROXZ9{ga?C;$gXO^{SOcU@Esi}_^Re2}mEET%r?A7ZDJOdYH+T5vTRn8eEEs
+JzhRjO!&rKi~dQ@A@TaM89etJAV7H?V<<$cDuo!BQ`{SLV5xZL+*MhJCJ7Q|$y!*r;WuYT}}jbq0*s)
+WE!$XNVb4Pe2dJOaj-%3y}GL$YCg)?f{^z+|>ub6}#twvPHs&4$tdnK_{?T2P`QVl1e!5hYth=@pI<G
+VX)nsyg3N`P|!lb$#@=YL;B;F@#zjQ;9>lHCbdU~qFl)JA@Yl0=H%u|ty^@oyOT`~Co}=}6wScI_6*f
+cc@PN%XC{H)iCi?QN@UZhyLEfB27u=(m+d3a1??QUE=cDfbwK)LqXV>Ese-wb)aqGIZDrOR!YP8Y$}(
+$`bcH4{q@@c~-pxSeJqHHXq%45oOt!hy0bOJdV9K5W%8Im7cZd+w{4=mc`8<6U7$)dA2<med(=!5$60
+dWU=gG$m1hKv0`?%L0F|g?~1>39+*>(-7r{kw2FWX%01p}3_@;6|B7&=9V(87Rv4nBKbN_v2PZ94SwS
+Z9SxW<@o`pFKl*Xne2Mxdg`)z0P8uq22}gFdL8FsuU|(&5zS^4oBh=<+v`v^O22MXKOJp!54W!?yu2j
+;7F1uTvmmgmjac9$QA<SsTSzakvCJ2zom-%tSSpUMd;dHEbK6Vg+p_U6HY{<3Ylij4k!X<dK0M!m4e#
+|B;6^2Bmxqm4Ti%!H7w{JNukN^wJTrRSteq;%F-2#+~nXLgE#jHR|QCbU~pq0Qm~`YuP?z<jE@Y7r_2
+uECYr^m$d(208azk9A7B6U*Yo7{_vf#{qy27rB;e0EhQKpw>9K|H@!=JCSl1qeuYRxKce~#|tsmew_a
+7a7sKDJ<^S1?H-BiUjkPMW;{C|^GG-~&b#%{m><Y*#h$b{1-ehqSsVZ==w$FM{3S+Tnv!<=a@!DYX$c
+4te_-O;%*=VNBVXf!%wr;nFSQoy@77shK9XkJ7mAs(E^FapqCzDwSpU;X$4uA!WL1g|%8v%M+LSSEOm
+HMDtsS1A0^A}?h#?g2n%ozb+GLTnP;i|4aaT5QRoPdR8np^~2z##Fo#rYh#0eO;n;Xh>V-WF>U0akr@
+(F;@#PSUlaaNWheUhE1j%gJq~=v;R`;<){?BAV9y!R6eiukoV_*eV@F&IRD|z)l?IDFRP5gI*x;OL~E
+ntvYJt+`DU&Jx&P}bs#U%iYlN3)e>tDhVzW6e6yhi%SlC#BmnS$np(skEK;cZLpK8N5UVA`X6JJ5}sU
+Y~h0j+lnyBG1CJYy5TTeH$J-FT)L4{!;1gQO-26Dy9tLEXuW!@nBX3firyU?9lmDE?T2%q>Qb#I2{($
+E9kJ2{e4dJRJW^^)#ZT(j%@Adt;C6v7Mlzqagqz!6XSWJ4xVIA@5X@JVlR|h^O($ryN=a3D<bNeK6uk
+3V`J?a-yjP*P{_RIU>D2nmCRkA85Y<N?5)$6KD)=%w~-mqkc;#14%^Qd(6cZvo$#tbbKOuLRuj-K))|
+Ii!|3Ft7`HIBl?B&{8+#OZb(B+H2f`)q0r(?S#!|r^oyt0>|q#G#)J%Yu%1}u82Mvk$hh;WDyu%Fb6%
+u!4Z)G5!?42aN9}AD1kw#9XgFb{J&k2{kEdv}j;(C>@DmXkXMQS1Zz(_@4e`^52KM=n4sf$pRWy$6L_
+XBm5mG5qkxs-$O?+9hHXpfpfqk8+<Auy}HFrS7b;Q;K%TZ<IoeB&1nex8p9Nj#2CVsjd+1=F&{x7lsC
+#kaA%FlKmL0lU3(CpnWjyCDg!gi6=pe?(?hS9jST^=y(miOeN2ZgDErHA{@*2V*WAZmh%CiV&9--P`M
+PdBnHzCnFpW&8Fv9CR=9O*kq9chHz-QmD8C=n*+4@wMs18Ap1QKA#qLR+jl~AYq1VcHA0vjnGI~()^x
+K?%JG=;e@+9Kol9=6NhZ#7BL=&Ld=qOU2VuUyV}CumRn)b#g1v9LqbAchz|-}+TvduaC+}K&B($(LA$
+>JRJ-_j()D@4h4#|MCeCv|NC-jIL}#yFYY7YlcR*CECbz!WjnTGQ0VI>o1~H)t(YDe6Z#=k?a0IMJIY
+JPd0&sBXUILu;ED_Fzwb6LupYm#F4wVHR$hY|eS>c9DX&+5*9bxR}&`@-BFqR;2Ytxcg=6Z+ld9=oZ@
+p(epaw_o5K<`@#V%K6>qR?!CPOPWe?Y?o=3{kqLfsxu1`y6`NWe*8%t3PA?>Hk(2#w08+VFv{xEFe9)
+)W}2Fr46px*|3viX1!m1;}S!r|Ja_JZPuyTkFXn}X<#7+Jtn0eQ;TQwypwKs%L=z`*#oY(s69qEI|G5
+&KhK_c<5L}U@~zhebF=@{)&XX)rwjHCVufG_ImNJVkX8<6l)FpVH^?c5?uv)b;68j-L;O1E+PcDE{XC
+tqpKDru804r%o@H~WPz+UV#d0tjPrH2X3bmFQnu^_4-v)Y)D|m5uiOZL&I{u`b6s3FCvI5T$wzC%LN)
+}5+fkL6wTqg~@rEoCeJD%=@*>iR31utwVJtgQFD|2iDczB*T#n^(z^WsC}^TcV(7BsQm2d9RKr&3x2S
+PK0S+%oZ%WNQo^1b+xMOgxR-J4w>vl;1w-YUR$_NSwpfQPU())O{>*Lfv7G>zec`>V4?6a1Y|t{e6ga
+mxq0PaOy%!WhjS>(H{o`By$2}BTgP3vpM6PK0JwN)Ivhi`Dmr_X(HMXB$1C+0(&5MqaWP~=z(ELeRPc
+JfziVG=t)Ko6pQ1dlfI|%H={OJzg<@)M8?g|@)&*YtZuTjc3f`aH(A<XI>~6CK%;PYETouclv%;tS_!
+fAroh{K52McH;otR&svImlrJ-j^V9dGWWF>|Q7=2b{o`bitk`V0BMcPcM!V8>>SbRWuPKU#+RG(1t2<
+XNP`F&Py>U@VV^@>u{6pci)jq|8<(aD&*Hnm!8a*VgW#1viuT)vY!ng2=cI9*49Q%&SLf;0h{u7cPCT
+8)LuRzSbbJx0W_DPovTfh&rUQ!+o~(94%h`OBBcC(_s3m284tw|~HMOk7479g->s{Nss$<sw@vOc2AC
+U=9)R!opv^?8n1q048j<z;s~IM@ru23d~C_Xh*i*1`FwVn!(>v(!6s)<L}CQ_*s`GEhJOS$s*Ti^{S{
+hm7;5her$kiXTwKc3+)F`JI|FBpB+S=xTPVxp+RY0>;3EDHY`N22dl3-*p2NW$Lu$%E)l_+z+~P*u$s
+YE>rpibovb+ctwHs$w!|uzE;_A}j!nhRJgeXtR!LH5p2oa9IyFkBE0WnBY`od!wh;Fj>{RKWZ$?4Fp5
+hTp@xCD9Yos1jTqYy7iVh0sjr(klw_GUSz$3X_R%(e!9l98j6`r^rG~WDl(?ZlUo5r!PRlMBFZrZjr&
+ikNEiao5Y%cGm3JeI}om<QeZ`5i1KJ2Uxw^51%rDBTJ09w(J`6Lr<%L_9wA<|q15Im@=K<hnK~^{KG8
+L!^G~Q=oOR71(btc=%d{<;oNIDLHkB^vuD+e$kArK|c5G!?(6xD`qMeZiR+)pe|WNFJ-l?b^3V%dgar
+0AQ#=koCp?9<9XotD42s?1awq;Ch;1E*wx+%3JAUF@YmQa&qZZsZ8p-z;T;jf`;cS4ftueA4JPt!s7e
+p}@wELKi?1_|0gg$V-8!L~DNy@EDOBysSks(>POsX*x$D0H4@g!`f);&*AqW15?@CanWs#-(2I@?5Qf
+%&Ks-nSP4MS(3z!MNlf;(}G$-sj-DBaAm#zB?6#hjQ+OY6YcD|<r;=(jK*9haL1EVk2ycxkdBC!?EiH
+8%pLqGBj9YuC(xkvCtj;;<`-Jh9BMfDDUHu@*%OCQzntAjlGCwYh+au*ao-!3!`q$zy+INN&_c4En+O
+q5-wz-s6Rn*~<+dzn6E~pS32KkT1j1LPcB&tTk0S*wE5O;uB_(@#3r2uq4bK^3bynX71nP-ax*y%f7z
+p8?krm5&9w3`lcOv;f{_6DC5*dml#UbS;Ph~YE2wMv4L)hPj^!(b=8gi4e{9Bzt-+;ff;xbpS02@yor
+T+fE{KVb{gF4>TA@#K}Ms9F9x!%y~^i#;ErDV0u@__Jz)*eUeWhK2Tp)h3tWO>ZjZ4`-*2=o&YJi;Rl
+sgHWpxwY_;IdGXUtlLflWs^uXk$~>RjWu6sL?3t?4N$8aAw_zE8AWVI@CaC57v!;vbqiYaRd7!E=HoP
+)^NZ?UB`%<L(jIQE5WRg2U!fdEZR50X_5hq6d*DxL+hv3Cpfk=IvoFD**W0^Y<NTs;$yde5=siNdqdI
+;oGi75!~!h*-^WM$-CqXTrbxex?o-svW=>Jf9qEn;8mTUvvg$!rp3zzv@fIoNmuzZP7-%=40vjf)uPa
+cial0+thC$uPjIw45t>^o70-irQgqzy&Hx>e1y}6WO`D2Wzd!kUV3MJ0?s`|F=}Itr6OG4Rf4f>9W5a
+Eimfj=RH=A~L_`m-TdP7?fkcwv_Wh%Qw7V3IUV&lzMx8j>q@q5P0l{sW!vh<q0P<)pr<_@k<x;=7)JT
+t)R1b&P{@PX1JDI%Sl02>dQr5T&z6~zU0l%5da@hw$jW8l37Eum=#1{J;4T<xNwRuB|o!RywbVJHL3U
+c9s5cs<pZZ{4mGWr(D!#6bUIrcha~bR8bQJxA;ryutCjJKsUk^wEa23=61YFgTmEiRgZyhg}n4i)ScM
+UrFz!7rwdYiz;2*)w-h6=wWS`V0^2$m&-x@WpL1jK5<Ax5ZZ)u2L}S3+fZi^+53D{GejT!7Q73CLi=V
+_yp>^k!d$9s_+3FMFaruIoMcu<`+PfRY~X;<4j4Y)m`sDJn6`1WSC7`1c?Pl99u8T<@PxdWGU>b|3c4
+t90Ke|Kp0!Rd>`N|Kgm>(~X_*L7`Rle(U<(isy|ty$n$<IXFIriWL%fTEESZnvtXgic6uCBUmo7dRDY
+6k&1N`SB{<GR`%W978zi<NHDVTzP9Qm_g4qR&|jo!Q)*(spxDl|IhK{5w0{(v>0I&mVjRYbjP57-z}$
+Ma2UD0eFg=h8R=>0~`%OPc+K7@;!j$UQoG5hqp-gDJSoV_*g>1TXY!ZFI%MmE4(X6{(moa>`XBt$-Gg
+U4l*5W$$>2GFNFfcMPd~2@f%Q0dPRJ7Yc_J-#r(6-9(5VEw(t(t$FS6uRkH?7v{Cv2GAV06@k-qgZ|L
+I<ff6r)?N<G-Urn(;9qnSmtj64th4uQ1UnUADf~2bNO4o|Q+sUYv{TeWS^(LyPUGH{PlovbC?-HpxDs
+a|Lt`V1e@$g}n{}@GD{CjAUq2CjwXy$AOc~t{nUi0eNp4YQ72w|fa(+EirqDV_L&rx)P9u8Jai<#R^i
+W*kqv$O?cTVAH2<#{GdZ%2BbRs!=bTz(x<rA(O-_vm9wOu9;Gphi={TR?>QpQi-#S^GmD(L6;Br1GKD
+hkx=M11X4DuWY<beYw5>FxMvqdz|CL9i54{qZ!lrSC5ud!*>;51KH{C_d6pXd-jNi<pW>{_*q;*4lsD
+#Q4nwSi}6tUS&mS^Paipi{p53_>tz%&#qNIq)z#u8s+Ne)F=N6waLG@F8NoiN#0YB+*3M8%5mgs21k9
+>$V0V)KerND8+SLxbM&3y-TIQ}r0wOrb>})CyxHx!m)5VmVjTB(6My_Ye6>&CQR`{eWo_P?b>1&#3^`
+1)`9RO3HwcifPaV(MjYaROZ@dX9UtmnnZ~20(h;P{w!}~P;2?4Ui_X6{5F6v#;$cH1X(Q{QqME_Wvf}
+3Dp=0k3C$IZ#Dm-VU4+iHZ>K^!>^YGKVSdvr);fTqX4|1&qHSQ*@tcrxEmiSb9&>Bhgs=({rbR*8MPD
+|+m$tRp^|_1mpz7pXb)6v0q63;3%u7=(o><YCiwc-AOriRQp|`aF=5nsulB(?=k}<Np|UXKPu!X{%7S
+%f-&;U!p}{?hX#x83;sbbJ=`m^kL~q3z|2cxoWAVH!5{oyj18PWp!dFPt5G2F^%vb<6gKyDzACuVRZJ
+U4~@3!8Qm8ER6S)CUO@vW8oFg%XX`k*SH--nV)Jf#oJizpR@#sH_$;=W;q%{~d_B4N>g0sq6Xyjo;lr
+pk*jCL9@)l?Cjm(7Z6=1<PtR>t57)|^Z0Bbkk``E3vViz{}=5e@(4CkJ1_tBgVQ1=5ly&&wZbh`SQ$v
+X&}dOv8hhhF^&nrDb@LFt!ry$AoRGPa}hC77Nbsu&2{-R_wWx&+U`qI*8oV!GVtRl*kjmP*j(eflG4r
+>~?0E&eA_f(~@Tf(HI5Nl(-8Z0=hnL)5jp-G@Y4E!wp*t@bM)VM7b5{qc?7_SP7Z7xUnKM1dPjWs7;X
+pExiL_7=-ET=}x)UJo}dUS=g|V&6@-gty8*GHY7=vEH*zfBU`8ku%tRwFiy2NB;*<O9KQH00008031s
+8Rt3#!Hs=HY0N)J&03ZMW0B~t=FJE?LZe(wAFLY&YVPk1@c`sjKb9ruKX>TrYdA(QLZsRr(eb-kEoEI
+sOl{761)P;*WiMQ)^>lCqfgGFEnv^=u8RY)yK#c_*%K)<U$)*&TdWZB6E1*!*`B8O+rTuGn6mCRR)&l
+d(R&cFH={`uQ*6awKAm1c=|vM=y+k&ysgGx13l2bQH?6b#-nmC5D)^4D#8eFL{_1#e|GL*<>2$UB~(&
+^Uua&=i;jLN8|t{ZuO<d>}Gh3b=^Q!M6gfYN-``PY5enzypB_X`s+Z5L`pbGX#7}FgL&jB=RB8I1>rN
+lADE7Q-MST@v(xCQ^QD_k$g^H>8>0w;|MQ|$vbCf%jGg+j%Xy+{46Vl^x3<?Rew0@w~4G1e=joB8Wes
+mxFR#BD_}WsN!XMaW^4&k0h=qNH6tz8rQ(K*c?epjX2}#1%8YBH__Q!JN3EHWy}JVBDkh-S8^K`Ig3I
+1$FbWCdZZLj(^L`9>z1!Q~a6IUb;N}*tZid%`@!)1iUvHo{{0P4chSwn=xrx-^Q?4w3BFU`_ac2EBLa
+Y%;Wl2cqnDCS*WS5v1Y>qIOkEjHh139V(u5BPS(VG!U#viz0#?3U0iad`LN@XA|L}H}O^m;<CHbb+@E
+jH6&yi~~t8m&aaC9Fj=#M~>Fa-K)=BZ`?+kwL){ZdPl#o-z24n_rnA(&}aTOQ!J_jarfRm!+>|h5sd@
+BS-l~L8twSW!Z>ah@N++D6MezM$kf`#2C6@qVX!n4@~*3{nb{m-Ec&*6~a_fSh^;%YHYgRM^O}#aBs;
+daCU;mVl|lrp64YQqde(Z|F1pc@46}IctDSfNC$R6@6${&GdT$Cxji#XA&$A=CXRiLSsK0)hD>xDLO4
+DBol0u1?N(X}p#1|3rNEM$BUn(T`a!f&xZV<MMTkP=0N21JPnUcZ+k|-0W`Gl$q}TyI7gFK9tp~+tIH
+{q9kctj$d`~=gNH$ozt&aMBTsw7+Q=D_*2i|5@*<i%lrVLT9=a646%IPOeOn1$yn-UwVyK7$|ltjAwE
+?F*Y!yT()$CEB}(z?iU;fCD0qrbZ|4r+UNN*#?0TA_aJ&t$kQprDR!9|CDkmbU65Go+r`bRbjw)6#@y
+K-W)oVA!<nyCL<ajt!xZpIHYkzdOG;qH1GGq|wB<-t1Gais*}SDV2T@G}3{1wC%*C$tBZx%&@w)(onz
+rsT+maA!oW4bHJ6mz|{70I(uSj?Xkco6SFb`e$#8Ef44<JTJ~8SGDW$RwHdPS6d~J8tlFhOy$4VdRXx
+DvzlnZAfr=Ta?(01~bY)$>CtKx;aXPPTx9ck<so&Ka7L>_v4^(@bu-a@JX$89+*glCmM(aoo)+Xa;3v
+p9>r3tR!{9sdifBqGCdrq`FnmvfQ!0j-tyQuSDs<&ZAqlRfS`LW(y>tPrfnLFPNtfOtcd_nRa?*x@E>
+PEhX^y{jn0rr2?%rU=h@^eWig7y!bDfRPW3!T~v!1~ZDcc)^@<plad7YZFP3E7w`OypefKj^MWH!piz
+R<fWwE0%XP;uCF;oF6y$w*%<gY;~i!R5J6QJ^rf7r%~NORs4^)`yHcxqi%`n(cbE-d$X>ST2qN!fXPL
+vsD_OeP6%x>f$X16o&$;9Uym(P`TacHexcW38+%Kk_9M#*I#K=wP)h>@6aWAK2ml;P_EyH4)Bf87004
+ss0015U003}la4%nWWo~3|axZjcZee3-ba^jdb#!TLb1rasomE|L+cp$^_pi86Fu(>J*-48%c*_PY$r
+g8=GsMoaA_x>(x{}#Yq)Jk8w4(ogm$VdHvo{pegC$)aoqO)5kKkODwdVQC!s+<rTX<IqjuI}I{HUtl(
+cZB#tBS!D(?YHPdHm*>e%`_jtKmwC6m{>2An$pC(qIaeBoo*bLR7MZZq3OM{y=TGl5iT1q3-}ea}*4|
+BZgX4P!Oq97Ak{8!3|_wAmB@ar3Ee_QAH^@lL^9_+m(0Ikc33>p`lPq%LvT~U(#E)ivwo8;FY!IWHef
+@*CF#lL#6YP*nrIF{q+2DHorV3u^xUa1sVeyKUG{)n9CYiNm>%NB!z;lL1|#QMmn>~X<ch>xy*-PRA$
+#qBeA61Sk0G}?IfyIM)B?fC{;{C5Y1sa58$V0KAjJV<8HdRy1re&U37C3%@)(kIb7es`St8#x|m+i=<
+R2SW*^|!>Fi<%NNFNB_)==8pG0z(LQGx0=7=2unc4_4B_=%M3B@JziscBodPXfN94Jv2+_*v-l9v*T;
+03qLddpr=VXsFHm9}7N(>~g|B&uGfRRJlpXnBFqp3!rP!m?hExap&?U@wOMg%f&>BxTlOPCjz}?BqCC
+1mHzgz%vsS)tBy?`?9#o*CoR5b!;3(Y$2hPTJ}V`evAH$@1p4f&UU@P2u{g!iW&8uOk<@}E}7_;%EYo
+NCeHr=j(-5E)1(J<`7};^KN)H$l;N5`@e)(cd`r2v(WT4<H!DYhnhA4sz2S9+CC!Cr;u$n<;Oq>>8+v
+zXw3Vh-u&cn^P;{Xu`%q&KLr?diGCd4^vk%p~(6{jY*(;tNPybV~!M)Q%35IXrWISjpVAWUTza<MkH<
+&M<4-pT(1PyDBHcprjOO`yvk`>rbmXoF@!*e=ty>lOi;jlGEvVQ0~4T9hov~I&RM37ZN)W@GHMya9k0
+!K{E@4(ZHmYO&C_FE#9TBTJ&sK-Z*r6vJ`$458+j*iSUSWR4RP#cH-ZZI!UT0>oX|KKfF*W1jt$F$Q*
+lqnI1aqL7n?{PfX6l1ebBipQ+ORbgOa&!p)m2{WzD@ff{GV|K#Zp*j4dyUcN<Us4}iKB(MqQ5d-Nxz;
+p3&@l!E?<CKx1^D2v-vk^vM-gyA3G!@$OlzWSp<dEb<xQIr=_NCe?07d@&6LB6LSy-;YY<~zxCvXz%9
+eLlHA6AkDav*c`Iq#-qR=yArp$x?R9NFY-h({qGW3NuPhVj68fI@1l>_`mhD%eRhBkY%QkS?;)e2I-5
+>E5w<BWUtG4wv==}{)O9KQH00008031s8R&f6yFGvFb0Fnj(0384T0B~t=FJE?LZe(wAFLY&YVPk1@c
+`spRbY*fbaCwzfO>f&q5WVwP3}^(F0GW1^q6f7Npvp?E){qKGX<!5au_A}$Hp^XhcW8z%{NFoE(jT-B
+L3xnCoi}gZn;Gs2EKSu~nHL0aFMjw5{-~8i4VOayW9s1KRoJ+q7H}o3GR@2IyEFdz5q6@5E2C1h!3jg
+IWrEsa3bp1VpaNl0iG=@#$PE5Q>!i`}HoAa`2ZTc?oc_!Vt*N18Qf&xohfE<IWKtpEw*)H!sUb0CrKH
+daLL;f@$_ykCQ``&`=179kg7Fo<WzTUSs1sZeRrB-nrfDM435|@+&s7g{=hy4yYO`ORvDgm&Q7d!~Ed
+E<d%QlZKh>Eo&;>Ze>XuwzyxkZkV@md=zN$PwC&ScaGi_DTrM^+wd8a3)c8T)+>;8qC@;bIT#eF(oT_
+UrwOIX<lqSKE&V__WyV7MsI*wTJBvmfOwc`mo+^`0WEMHaGC+dUH7g<Th~`{8m}7pG8XFLQH+X_J|_^
+ndt?&3KN;hgnj9}7CAz0ZqaJC0~Oj*IzLFq@=|6|vXmsKJ9%X)3IZ-@ECIC@=LbP%O$n8(qWBhdYHUQ
+PMIxz%0T|aLmE*i@$cYX&f34!>)oRI}exC=x&wy1X&pTFs_Fd*3l5LklsXgn(AP7>-KxBkA=B+E3Xkt
+Aic0N9baGVfM;p{zZjK*F=7={a<3<)EE2gjJaW%q(0HRxa<jTks8#;PYBgO`t%3k^P^>+T?&Jw#)Lx2
+Wd4Pt>0|Oky5WDQNC1!mkj%xrp9noYJWqI_5R|&HViNrH3!G&cT=OTj27}@3J!`4obVpW>QO6@PY~=E
+Gz2mc{cCRi<b1i`q<4ggJ&sGrv2A2hWO_MHrvB$;`mx9XgX)v`jj}6saq)ci$pyG{(PW8C~HShDHOcf
+Wm~l)qD;qHurKc4FSY)vO{3q3j|f!mMd2rWzn)Q!6#J$fMe?-^O~(4CkLi8uqQ{{>JMYIk8&?WHJT$l
+)3QyqlZYY0$3gHWIw^4BSv={JZ)JYB)ox0dbzBT=srTdAS&R!99_iZCwH{-j(C7IaRRBE9{_J+yFx-O
+4sr}sdTd*kK$D?;*0Jb9Y-yTR$T)x&xO{{c`-0|XQR000O897^_9MPooF5d#1K8U_FW9smFUaA|NaUv
+_0~WN&gWbY*T~V`+4GFJfh8Z*pZWaCw!KQE%He5Xay3DGtg*Y(P=6ZrFpn6>uDH@fO&H?JNj_LZGFS%
+#|WF@)T7l`rUVwv@}W{+6jgQk^lSO@9rp_z`|6mmBo?Z&BYHt!ymPhsNqWJzfB#SyxKPISPQroR+;AI
+_K#=$_Y-VI3)e<vXoC}$+{hHQ!whQ8OF&12c_mW54LcG1h1N-<;Z1x26E6sdt#JC59a>XE$)?&6)DGD
+~I>@C$z)vYw1X4q4%1TM0Q-ns+u}d?U#B6atSeOF|Rtwfw{FFb}fuIifNL0<v&zq)+MF$!iTb!$2<j!
+wai{*N^JY(2SeybHa2NwUSrR6dYEr^O)QgL8HB^odmL}8Kl$avPqN|L&Wz?qyHVUb-j>B!1MO`}HrN5
+=I&7jUbDhH$=v)h>j~`EIp~*yC=szuw&L;cmX&&e!|ZatE6&EH>+_)qb^E^V4rIU*E%@tMyd`$Zg^@_
+^Gm<pCP4hA!fc`JH!z{Zh9bBVJdT(a$UNpMS)P5N3@#DfeLLYogbuQyo_CxEF}r*R$dhq2LUHEmVnxd
+<AWf#ri4mXaq@^dGd3pFB9+v_AWUkK%5hvi#Kimi_se8)y<Bijzs~~TYtSlF6rHPI`=;|2$+ioj)Q)*
+E2!afAI3Sme2_L&7J58+DB+d(F5RN0lDV)87wb9r^gkgBuMMKIG;L)+DXt{ntkQsC^xW=p;r(^Jmhey
+j<hAQHlZXt|(S&70&R5LzF)MXu7;aU8Vdw6)s_95!XK70on+dF?sohcD|if(3t2+N9kTJPe4J&UCO)t
+7ESIXnxAbM24!SmLh}Sa0^riR1VDNYfe9>QmxKwr=6buNdkG_<eu|p{yN2rBLuuE!(Oc8Ra_Bg3I|8!
+e46rQJY4;3!fCI+>69t_5FE^3#7#N>LAjO-PUBxKYa@CI~My9jx3+17L7B7+$8J21^q0z@u#1M^j}UR
+2w$kX4<G;hL_QC2WD;XDsf8L*4FgMbT^`U*zW~XypSaH^d6HjIru|4cytaCnYVa>mO9KQH00008031s
+8Rz$^xy5|D`07MA@03-ka0B~t=FJE?LZe(wAFLY&YVPk1@c`ssRW^Zz3Uvq3_WpFNVd8JidZ`(E$eb=
+wJP#$Ijiqdt%9=x@H<G72rz$t8ZMNkw1EnUf6X;LMrC_?K0-b+extbD93=7%^Y?>+aN`^6)esIt+#*j
+RY^;^*JsuS#%~aK_}nstS%CT`RMx7@RXLRQ>S!mt*?#D=b(8=SpO#gCjDz;3-Oj8B~&vz-|!6B}?h6y
+NTc*)P^ewFXI<5a0X#_6%KzVgho}cB~Ym>R0aux8_2mpz?&3H3tU2~wx!@qrU*5+8y}_vi3#GWgHUVB
+$eNLTNx$+#J7Crm-dJ0XPEP8&j+rMKD_xw3*2tV(%qG+Ma(YZ;z4<#S&=}D8x#F5+t{Y$_aY@;l7z$Q
+{(!dIhbZ3?0T5E2(EFv%}w>8s9C>b|a^L1r=iMnG(dJhdKRZK!SUczh{!s&Q9TSkQOezrQle7A!4<Hc
+e;U(KdVxLm;Ga(*^j%`WHk>kW+OSMc|2eii{znkWq3l-ltplH8>bGncO=Vvj(sT0*A8l;=DpU9zZHfl
+#Px)RN>tiF(V8E2JTM8KDTi<(650@<>!11Qbwd3$`iAKL~QIwovjiPOedAO2-x@OSx^JGfXPWg(1JZ^
+NCkiZ>P!Rd^#abe~tp6PiHGsQFv5$_D$pkTHQ>T5KH2VK@en^!x~98CPpBZ2{qq_@CMphCdQeKAnf~v
+LpXj7b0x8*5{BWa$AFYffC@-PMMGI&7BYnfI@Fjfp9)GM1|G?&K}`WWS@DHG2&22(MBp`w5w(|X&uBC
+fE^{@4wNe6J!5b!M)&ftl%bp|dy7a?`heAF^UdG4o&_ThCYiy&o*zxpbX4c}iw5>FU;?y~&-2PA!TY(
+ffxtDax3{L&*yS4G9mH5Rw1$!szl7l$0s%+{g(k%7C-A6M{UB0NK<y)L;t@I%5xDLH&H`r|o?r>^mz@
+QC>&qkDZV-uEoj{i66A=bAecO2uK(U#2mLGgx~;VEOhOXy(ObD;TNM{vzVh2$A}(peZm9^T?joFu7W#
+v}>-C)pO0WH$o3*o8q4g&6MZ*SmOJ-yh_M)Ysnu>H9x;-sz!Cw3U`#=u>29XI8>KVDfZKfTO+i{nYz6
+qJertkF8X&*Y<2l^JjYK2<Dfo>A+B-H+DFpwvj(s@}%x*U_((*MnKO7)Ck+kSSSV3^uV?$n;uXuef^y
+FKPvf2s#?Ad|07@b_U&4Z3$%%A+BHi*`Kv*n|3SO9Ya-sSw}bO`kwyJb?TT=Z%xxET2O%BPV|x3{#Kn
+Gt?r2a_B{O=F3~&p#uF5<5a%JAdVf0`$+A6*37xLbylhF1?x6FdCP)h>@6aWAK2ml;P_Ex5BveVoG00
+3tN000{R003}la4%nWWo~3|axZjcZee3-ba^jsVQ?;Rd2LkDZrU&uedjB#!V63^bltQErcR=i4Yn#wg
+s!Tl37O<3xHEQUJ5BQm`>y@iuAP)YM}%-<AD?^9@lCogQAMqJzO`_1{`wvK`E5B$iExG5u%y#{3HV$J
+0>Cws52`$|tjxA#Fk@P%>gDpAGx~cAOIE{7i4=9GOOP9$pfs35DQODq7GYelgobuy0N+RqR}wD5bLcr
+h&@Ki2_ry@E5_Uu?m4(tEQE&qp7YO*2U}1qvNYt(noXG^C;&$uHv?L)>+_w~JV;P|t;R|}o4spP&7re
+E$7!8M2RfWt84VBJ^q5+xV&3rPA;^`TQ_3&FM&=}D8tK^z&Zfal!X-U|I6be>>(!g?!v}TplT4`>%%m
+-jpW-F$VSW<4R=9|(U1@)|q{2l@*DkdQq$1slrxEjavct9L?^VMu|yMnv%aygDx^Jxr=B}^94^?Ws7M
+D+9##?d`|nMc<HK#GaV;8UTUeiF%DgqXU#V#Ff>nQ8=?0u!F`gnY@oWH~~v9#KoO0|n|GH|`(}$xDev
+@Ey0z`kDVsg`Ex+RN8{&JKW#b1#!_**4~Dz`>)gWWHz0U>`$W((DjVnYGkR0cT&v22*jdiFi|o!Bglk
+ewhw0?AW{;Wok0-zF?LX(M483BCMISfMZs!AfnZWP&E7PFoIlbFA<Nx{^i#*Q{3PEItz0kC&lw{PtQ2
+-nJ8&`hw%Z`=RPxguU1>dUDLENH;~F76lIGF~kF4~`Um_SClAm6ehBmE{WZAu|Q-&(Wt!bOZqh0@z6o
+WQ&)%;!;+<MJP&U#G+MK)-#BMA2ShEq2ayvWjBZbR5`UpD&=SraD2p4Isx_oL@?T@)^4CcgV~`f-B13
+(;aV?QQ+X=7IG`&71E6eMR4bSHKcmQi<9-ZF;mRazN2$2)udM8?D4bAwZAgKT3SS#QO6=Dp>c!6DC7f
+sMi*`Y{!1*FHlPZ1QY-O00;maO7>P#)YmVn1^@smA^-p#0001RX>c!Jc4cm4Z*nhmWo}_(X>@rna%FU
+Kc`k5y?O9)M+cpq?_op~G53vJRX|rJu9x}{Lv&CJJ46(bS2m+OsXq&A}suUI17zXS+>>KWr?2h^`%ZZ
+bv-GassiA>)8?l13-)(#x0aHYj;Zs6eQv+w@?^RI)a2hZST90)Gq1(WYp+}f#8!Alj*V+JQo2Wna0{^
+kk(`4-OE3QknubKTlOl2^jxGU7hO5|_ZtISfMP;lFgJ2fuM02_@mcc?umOXs284?)QkWQZXzLR4M~;#
+1TS7Fckp@{>kH^0U^Oti!cyOdK{L*%&nLd#6gI+DTJCBhSUt{L;N-^(*ZM9;khwke}8|uTsq7u>L@+i
+4-%qi|JCs5_;hsq1eLYquVuia2sHl~3yo$@R=`5k#bXoHFknki8rV#8+%t-FU20*3ob@15Q?q26BZ@B
+~qs1gP6-Q;7p}l1SbQP1(9*kf(YQyuvXgKO2#+%{z<m~kr-VDyq2dCrV@d(b&;ppu2#c(`4JH>B5!Qk
+{Q{4zX!(F2ZdLNWYPs7ZfRQjiO|PyQNlUQuAG5{06Wdtxd)v`fxnHsdf;S6oXp2STnFBBDS>sGg4~fm
+jH`j9pnX%4xMwpwb4|#LFJh7wMB(g$Rl?)AZ39zy0;tJvuo)Lj8a4w*Ws=trif9&~dN0^p$oDm&_Ap1
+u4ooH+pr%f?$Mt@K&qk1<VEum)!}Acn5_$gXc%x1hCz14<_hn<{6-ENa)FY%LBA$_)PG~LE4sO`jIeL
+%C_KUu6(=h^C`HlhtgfQ6Y*f$O9e-yOdr}+?b=;<@&ini3KCuD6QcB12@L(3V=0Osq7=p?2<ZaCwhJI
+!i?xJ&tBlbtOHg`i0dlobfLzrCw5+Yq5n~L8Swvq;OpS{IzL#x~Pw4nuT-1GZ*|Q$Hyv$?iCj63P9(D
+?>BB1Bxz^yO^nE^|U%D(5Gp=@2@a})=r2<klqFLlXJEQl!eN_wITDr$G@*05m7R?*hxB;;Snp0SP#b5
+hBNHO0HNqb8<qQmZlGTU$kRc+db#0G7L)AJAi1gK&cZ)-E3_t>JY;g%l<?G^gsXCm5yVaR!}bmo@%WN
+nRLFNKOuf2ItTB=3lh4#Nw#fU{|xnzp9Fj1ru1E&SPoBf*)(Gbf=w*?*ctgFXC9aIAlmm7NH%cogVnj
+GMy>I_Uczf76CYH<S7E&t?;3Ug0<0@O$KFpC)xluKifdo(ArgjX`WUi*2%dFVvYy1-^7|7*-a_zVjA(
+z`g%2=n{s!KA((KSu&lj4jUZ?Mb>9U=ig2S1xm-!bUSUK<si<Eqt`+ODMv8Rxyl<q7Lp&kZFoEMZCDu
+z!jC?m)-gJ;^N+V-!r67+(Dv(a@hJY<5J_9^bA`%i)5NEy)wvHM=x1j{#0C|@frc>r)96wVWX|BIrEM
+q%!-zAn*UxI2Vv4}hd@yi6UaN~n(lsm<cMUx7uAXO=eh$G3OvX<nOZQE;Qx?0PpTlCzU`|UmT+8g`qH
+4W5bc#|(5+x2lUZ=d-^-7-blxAf3fG;BP<i95#xFz4O}x;_&>ZB~%8FBL?e@HF>g9f>O*te}&Wkg1S9
+T~G<ST22ylZ_ex!&au=hFj?NYsnzbgZf56KQ(205H`SN_TVeQI^Ybky=jA;8k&7&#TGBi^qYmZD`^j_
+iOzT|}hweI(^-HM^)%Ow;DiT`ta<E}`PVS>O9d>)JE#>{*^3sKYTz!>SygT%vT2*i2PD9$g`-O@I@>?
+f{=F`|b=EZ-M7sT>Ka-*nO3!L@Y>~8n%lo$BN7{%DZfEgSEZaLSdFnI=@S#%a$L`G9Tq$riBNyHYk4Y
+`K;XDT!4r$`Oqr#_v;e%k)s#sgD;9O%0EB-sK>^B<TEhJBzLZ1P+GZVJ6ie%Q6xyFDAxi8Ax*w2R47%
+JX&g`mKsq<ivExol38m0{c*zCK__TmJXTuhlliYU}c;vQ<u+UNpLCMNY{1ug<8#Q8+PcG5vF;^5_KEQ
+q4j@h3~hEuq+`)KRg1dU*_27Y?f~5?73|9yIfG}#yDFw<@q$a!m>K1KSiAV;s^0iB%jVOYZEbZ+e`p7
+J&10$L9;Eq}5$@oP0cV}&)8>{_qFQ!0x2N<{zK79`a01-h`>?c+=_S1c+F7G{*q8LjD|huU(tEh=uh-
+f87Ej^THdEk=1;W2}zS>Lq`lZ*Zo2IBt#9=1vzF$sRi^~&9H+gwW*YdIkYn}>%8$A^S8{EV&D<7Jl$l
+k5|^bb%=0|XQR000O897^_91aQO$69fPN4h#SQ8~^|SaA|NaUv_0~WN&gWbY*T~V`+4GFLQKna4v9p)
+mBk&;zkgD_pcZ^FHjLDmsWkC%Bh5K4c8N?fb<kak+s-k*vjm>yXz3%`XBla`%5~rHek4ryGnT}4}f=P
+zWL^x+3}u0Ul(g5=L-iH=kI>}=dZsn&M)4<$1<0w;996ZbQzo+Siwha7o~t3VRF4X-2VQQzJ7qQSi_C
+ZQ#8Q|nS7E7DvK$Uik84F5PF43=%?Q4!0%|R)Cw-5b7-+aSZ{^xp9o>COIQ-9(hf?C1R*VCGDpDY1Pc
+dJL86yME`>@ER?;nem>MJ^i2E8s&zvA@LG}ebWlcK}&J$iZS9H(LR;yJcJkdy-`B`2W*|Sf>{$Mm2oD
+x}Yey4J@77YGbN<(SR)*uSvl86~G%*6_{0Wmj7drmXgm61-Wc?Yb{+)5ZElvG-0<g9diLT#8)zD)y?N
++<|>6BtfHxav)YlMZ2g9!_s=@22p%Hy-y!)8SwOw`1tvj;@E(;q8c?K0t4D55Epa*BwBTiNfG>VVFOW
+lq?~ptk(o_k3gm?Lbkv}W-_6?)VvgPgt>k~qbMCH&@83pLRzAi5=t(Y(h28RzDOzxD4sSB#4OqTb?bt
+Vf*><`356`8_z6|2P2^CCM7lN9hH>d+Zi7H(wNEs?|7{TWZw7tJ?w4)=^x1$e42sm_^6FQy$LP$uFY<
+gs+%X7(Bo`!*b-IXW!eWaEN4=|lyNVKqVQ)sY5s3rdhRU23V;A5phjWQGBGZb)&kP}IuO+&LPW^g{8N
+_iyvE#U9G0!^GSHvc^Or;CqKDV$9r|)5=bzV{7PeH+h1{hUhi>0~ZgtASg0;rw|G~B^Z*wQH2>@)$|O
+?Yj-5nZj1p{w-)dN85&D*~9p<)*xMin{1w3*FhQvle{N9v%+0dF*&)9v}BB=)-Mbb|vJHK;1;!o3Y@l
+muQtr?qEKHPa>D;u8NfcQc1Vf;5&A*-CeVI2}WAsE_t?$yd9<Ie}lIweyuC#_}pqZw|zT4^YGb4ZyyN
+5RenX7JbytII_U=gKe|wg|3#PB(^W_l?j>nPyy2N1=KdCBKZxA&^x1JBS(=Ov>bF{;ifKc+*rGdHN;d
+O_oJ+C=@4&rHKCf2L8xsHRG>rzl5*{mL1$<fgy|p&G2$8ft-NR<i9GX}-hs)v{w4hhulhh@3bL9c=FX
+_7Qya9Msn1)@f%H@n_pj7UdE?=6%<qH^Ztyse?ItWj>9%1&9rYYv)_ypZ5>f{ouS1mtf(pc9N*WV1jD
+yxsxtzY&LL&hcB(Cj}tK(>B-T53m4Ey5$qwzj+NHxrm<V^iEZQfwvNMS0Em<F(J!7e+|BER0LVc@2!w
+rWJ0fw1NNdZL)N51d^}A)cRrjwOYUA+bp;jBls6kO9KQH00008031s8R#wR>KdA!%0A2_H03rYY0B~t
+=FJE?LZe(wAFLY&YVPk1@c`tNta&BQ{Z+B&4E^v93R!wi)I1s(-R}7Sk6evnImqlH;SjTZ&V+&^yJ1M
+e;A<)uD=2j+ElB%PBze9c4a_pkJI#?oSIP>0{A?XVk%c4>|+ZedL`R#X@<XmF~e>3q-Iv36beBm()jR
+}+@K?P=mFe+F~uhtU4Gb+ucfZOl}JnP`LCf9#Y5h_{2mQ^66fl?!d;2Kh%Bj9U{g#j)gmfIrdOvDH~Z
+Z>tAHb_VzUfK|HZ5Vko@-JwV_WgjF8t}%LVsL%E+wDSD0}Z9huJgu8Uw@g7C$stFion+HPa;RHLE-n3
+E26osfE9!#W@|#2vmHnUEK^7}BQ4gQ;)aVX04-CqV+tus!nIL+U791II%LGR??6&90q$rH)42<Gqxp0
+mP>iqB#pj2o1$-SnK8|LK>0}NMk1&3i-A@<OhZ&7N!f5sae@<uj0U*glY4EjB7C(XHRzggyUUS4F0I6
+&M=>lV(@|bvutYjHNCV!w3L<b5~Tdr*(HNi_LO3t_3FjLQ*kP01#5=v!2SGxN&RY9Q~CslF_1uw$r2Z
+}_h(4b&3Hx;ywcTD3W8dX{MUwYrmkukU}%zts6=ZM9x9qa64mgjS#h%ICzm0*eNd@>ZoGHq#vi<iG9(
+fIRZOcnSvaDblvsxX!!E|o%Ix&R+bQ&N985oLR3`2vRfSXF_~OnGi+a(%~f;+#<}7frlQAFnT#-{eg&
+g(%{Jn<(-$<|%cf<vjqmO<<|n7G5sXTr#r?S}@C*6u4Ts1cm5@^{N0aFTYVIXL``#8;Qz?s}Eqko0Rs
+^C3T7Chx^psI{)B8V4A3up?*8H?GKwRmP(eic@W^jX2JpROh`gStrxF))MA29@sGj=`%x;+5DmjH=-@
+vI>e^*H_=Ex#qbe;A<O1k_cSSg;w4WiV4tX!%YSc5GQLwSrI=cTKi#s?Lb&VMpp6~2umF<a0+x{i3j~
+m)+jB@=C#%9=bNGgV@2*9Eo+MfU#$iufa+->aXyijGY^mS>Zt*OPr4fR1U|FHM%AFZM7!!;LVp~KxvW
+N_Hc{&95sP>|EfhN~`fL+LAyc|ugY%Z9>f2X;?;yV%_`sXwVD2Db5p{LTh&_wMHQC#m*SLX9TEZm~xv
+T}UHp{#1Itf6~N+<H}B~PO;<~e@5&$TSL@qUdN;`KPP5=-kp)MADHflf-b6v?tw_)tBF`s0q<0`M&H9
+OrYvt!oTH)`{cosG6zaoLiF(<;P)h>@6aWAK2ml;P_Et$~)vT@w003AY000~S003}la4%nWWo~3|axZ
+jcZee3-ba^j#VQF+OaCyC1&2k&L5x(;&Q1l_BOb#V^?E_OvEiKEjoQ<54<R~tciUkfq67~!*3(T0}p7
+IWP!#qj82IiL<QgZBF9&8e5H2U}JM(Y_n)yc-l<tk;zhexme`|tl8A08jE_gN%`VsE(mth3IuEh_e2+
+f~NdJ8mMq-rjyO#6Lf=OTJ<6bTk*H^9&@v$WSON<}6cKV(Ch-Ny0<?m+uVNKZUVUD|Q?lvK|q1^Q~_G
+&)~4p8H>SG>6B$wfQ7VdAtS-WeJGNYNyS1PCz0eT6l^WimAfWq5`e|0oQ0mH9Ml~234Sf=bd0A?;8mI
+?<I!lnUI*L>8fdc|MV`oxemOrqySO?VLRd%sQANU9X2h?VG*EN4VLX8>A)i6Qh_9J8j4zGAUaCpfwUM
+b*%K@``k*>KB;4+ssHFB1v4MP=@LEkz7OvM%JPOjMbRhPY<T%BJHz~kop`rU_**X(9;c{#bbK0mu+A1
+>MHhl@Ao*XJKD@arv`Tzq1GJHL1{U;<{sHR3)oBtL|dWI{0~dtC|95MZIbKsFJfT*wf5sb$8Of-Ut|V
+HDJ1i7>IW<VXwg=HL>^Sf)I6D-V<kIvrf7P0IKzEWR2X)N%1E-6UY#=`4(nSt65Q`c+`x1gTIwl<9`$
+gwrgQkp;s=ekQp7^pCUY>ASO2DErrOhvD-mmrIeF%_)zfD+nz*olY2WSZ2*-I-PMVdJr_2ygu!Fe%)?
+&GJ{iim@?XCo}5fYM;L9TVkw0UK-zI<ekK+?KNX8~rRQ#aE*5M$4RQB$+Or~B3=mL|W@<^4G3z#E>-O
+33FKiKMo_bm6li>DFjT@iOOJ<sU4K}4No`e65+?h!wx)m$jof*aIyLCqW`ZeYW_vB9bs1ORb%}WP$;=
+4+OXUNwti2Rf#8bL+5gzTa8kFzM134YT#Tc!IflTkWEe%UN$i%f+ScqKoCh7*pRoUp?&@rO{btXwK>#
+4X_mH_~b~q=1fia#tR$S%kFQwi2xcg}Dp+bZ#KrYv^>%PMYeM+760!aw~zw?d`Uk?*`4Y&f^1MNP2g7
+*9_2wychFc$-Iiun_4VxU?`sEhU3hgVLaBEN*x%=7-kgdTA&07K%Wo7Dtx`irNSkJ$BEZCPr!f}Of%X
+h<2u)0XeBDII$Krp!ZyW8J+&g#YHpnljR^a`w5WTjy18jQ1tELY=3e8?wXo_>-iRm}441=Z$a>*rBX8
+|CSes2UAZM>1lyryvrgR<@ztOk;&@Si3QjKDMzt^*%+2L5Y?GXF?e)s-Sr6}c^(!cVSAn-y?aZ_s~V7
+<TR6u)mj#qWR5@TtlCob~*#Aa_xp9k5=jpu<)U{Vh)ySli<2Q@;f^fF~X~daAl@Ri?$62Nm78s%ZN&6
+cB1*;p*g%w`vym?t8V<C$;Z=S4!`xW7-mG+iENHbged{4VJDobvH3(Xp7anQs)bo$kjSSUxwyr#WRbR
+Yv3vjEWbhLV{18w&I~ol7jc4q!5678In%eA`YVpMN{q*yQu&{ql1|{0ngR#6H6TCo+Dp<N@v;=X7yUc
+-yit={K6Mtyp2g>i#mjGH@zS&SQnC1{->*`VBB4?M^!;&zdty+jdLE^Yd}s6mkeP}&N$r3g`=yuV619
+!&rEQb2X4`JR@b3?b_L|dwpJ*>57lj5_An^&L>Tw_BCYY)$o(VGmehye9RBubbn(<4fBy^MNwsGN*9o
+=mwUP-Vs`I;#vRcJ&k6eZ8jLWDO-Ne6`5Dm~75zN^TU&9ek{GcGBqn8N<~udh7Hgo}v!<?eZv?@{p7`
+8jSqI)N7r9!sG+K#7|rD6#%ILS3ZQkOv-+F*-%Zs~_x%sYbL6s$V4Oz6x3Oo`nK?>g8dLes5*X*Z)5G
+*Ysv`em!WE*WDowSzD{6+u5qJrM#^t%H6F~e^foT=>MyjC%vBMMYob0Wq5aXQAX4fDNhN?$V1ol^!y!
+zQmySWjW;t)jCkbH6T31u5dgl_PU6iNe$k6XQGi@0sn;G8ISWyDbS!^Elbk<zBqXQcMw;=NjOgKtSS~
+`H;@mOvu}*~GRz$sh5cWg>U8@wx<+w(=0JVj|qA!BJQ}4+@1RjQ|=mA$gOIX$PX^i1VGPR=USlJA(e|
+or)Ml&996;eWyV_bn<qG+I&MmVIx4O_1SO=ikL3N+K12}Qv!Q~WEJQOOZ@$kZ35*NV+E<HigFJObf-r
+PG7v?ZhkkO2Y)=gt$z}30hSRaq*~3j1GmhqVR)V@wzYp`)IwL>#bbft;MJ$qM$P@<TUE|W^k!|K5jk%
+;hTZai93Rg9|0Qlfd(#$_uh6~yX}$3!Baq~7S|^=g|~>F{5IH&KMl%4S&$cBe;h!8pxFiCiUO|6iw_<
+LsIBos9rbF4J0SKoFS>c?2Q;dXYJFymHsdWu)pG`hX#>F=2n*}?pN5GKGoiPQl@&r>`p2nzLc94*jVb
+~X$hmMM#kB<8I!C67YJ<-Tb*K*~n2W_+Vr5^J=XeroZRS#OnyEgL_tXK`N3eE-XF+TO;AIX^06;e(^#
+fb9SSyLvq}w8LmuO?bm783PU>UG80#+q_3xogH+I(>%VuI;V8;FrmFq3|6K>jwvYvsK|;4TWsQX7~tM
+gZFoA_{7n@;3?Ynnij^W3)7XgwTZBjz=TDwgHd%Z(0R-d5(z8j<^X|G8G}>L5ynB4|C~<5NYVKf8^Pn
+m6IZ-!!R?}cXIgz!Zm+x=DrjtKvb-plffDU<mIB=1bYhM(~F=lfR2@K`0^=#E>3Y-dmosG+S$WL+pZw
+5<T^PFUOM0-WG8p~=w(=LebO{OkmBUkVZU0S`R6@*b!eRdb(VTjZm38Wuh_B*R)w*QSEx4w08-;!Zn}
+z#nDXN21R>#5#*eLXOQKLVlBYEv24%moo#j<R_IwItlvKsAu`qw%{W)ev^;Rr|A@OqCZ<WdK1LKukt_
+U^D5nIk~=c{K65A*R3iW{sD6D$(P-R<DiC&u@8g)YcFv&S36GT?B<pbTg~pxkCdc;)`m;~M20vkIvy_
+@F*-+yIL((%C#%YQ2Q32rh8F;Y%@^>(Gvz5r+k%s+Dv?cnGkrjuf&Uu;YUR8lgQjaoJerns~3QUF)d|
+ob`AU(i8LlXs>c9#y(zJ8mVIa8yctLNUclqnmo8=S3^|T=A@9Xt-+~R?Va6BgTPCHZU5!RWmn1gp$}^
+pS4s5;v_@5U5%1@P%GHIBH%N_6tGz|q{Z9NJP)h>@6aWAK2ml;P_Ex5<CH)rx004{u0012T003}la4%
+nWWo~3|axZjmZER^TUtei%X>?y-E^v8WP|J$KKoGp=D~fp81r3^`u!mqG2I2!8VLc6F(&}I`6FQS!_w
+RS2p1gDybX9d%kFejR-;+X@WICGU6&a_`ns|<NE`rf>ywo)<Z2QOha&?04ZjN{w&mfecT4UAUZrYIX^
+p{ZuXR+Ha(VL1G3JYr->r?M6Be^h9;}=CiAf>8nDe;Amu(qn|!Z99T=wiDrQYvjl8MEc^)6;*5J8jKF
+62{RqnuWj!=@y%<K$hkLVwLYv<eLoZWOGQ0;uxXG1WtX^#xFe%A}?}r9E3h+aAw;elC9#-->aL}vcuc
+{F^0pQwF`XM9g`#DvtD%vx|h_t!TMKqD4CS=Z@3au6ucQlQZ}~gYkH)R(x}G6;2%&+0|XQR000O897^
+_90=|xEj1~X@X;=UN8~^|SaA|NaUv_0~WN&gWbZ>2JX)j-JVRCb2axQRr#XQ+^+enh{{EBM$fn=LvOR
+~K)%~(wYTc)QOBgqbl-sxS50fS&sL<<DiI4r3(`uEMuI#7j!hqaz%ge?-N%B!;Ss^b;A`t<&{gR{WrQ
+OXa-a~@^EBH+n@osTE2SK{@DAmpd<`Y{P^m)V3rWCM15cznbrUc|$I{hHt11rd*+xdb$4S<F6NePDSs
+=Lz%JX&hxqFw3(zVZ+;m^A#ZKw_1xNUNP5Q<XN6@*JZ(K9VZ#{qA1S1EQq62w(;XI<UT#=doy1(9A`Z
+7W+89M-zi{;Zbg^uam`cJ@Z4Lk;mxNcet4X~3*7`Bsy4&uvB!Q1A}@Iyf9$afZ^h@6d=1b=>%N<C)wa
+`O@VOkh?}wAoWPCpAsRw5tPlspLlZ(&izl<)$&y|<?OE-(%xtH-QSn<;1F!sH$=6RH_W<2S&x{4HwyM
+J(?{F9fY{6iRf8GMgHaKo$9@z_0`T%NHL2HpO|p~*V_GU)_ewt%4sSP-$qi*9-6&2hKO{#9yrbo`fYw
+*}*R!GmlGBN;Ck{7pH77JxnS!+g%!AGsVYpf|Z=0C?v4cWLOQ%RZYd`6KfZ4p96&NnqT=N4E5$c?fFa
+r2uK|B_Isudns}hAqKWaW)il@BRS};@!8qv@53|qm*Lg;)V-Qqx~IPmFRy?#gU<tl0p})jy1Lu>XBd>
+T@x^E_05=hU&@j%%lhGyoHTyP@RfBg^??&nh<fk9c&qo)Nt%zHbkLPFZKd-DYcNhsnzH)~b@7;^hKM^
+4`Qyu<g@s6DTG6ePg$LPN`(xQQwX?-vCgTM`W1`{!5ujK^n&x6|_!{5$<3vdv`_+mU6BOek}3AT;gX+
+y7HN58!v|9w1Z#=hha0uu~UA&1e`>G0FYy&Qcy8=j6(XxO=I0mKY`qW|&Z+}zBZ0sP4i4-fz9^cZ_3)
+OhXr+-#NURzHhYnKv`vNBaFxybr-RE;yf?jTXAmsb~b#amC8565Z;(XytoJ5_q?qB^)efq}#S{KxDG*
+@v&%&v(h3Q+Q=sFP7VHWno_f8ur95Z55H5=iTB)(=X{hTankuOFU-Z)?tmIQjx&rH$0uMx0<`(T0xbP
+J_H#7uEJzs`arV^<gE@igLl=NQ=L-f#YTf~}zaAL&_Q#%>_3i>~*ub!7IQ00p%MSj==7FDG!}#~mUQa
+bK)SB=xvXCB|5oERi=f&dL@8CU%0&G76h={(Qa3G{h&$8rkprw^UgIRx00+8?dgU{FCBr@U1gfNO8Bm
+;(uB?P8l5Pj%D*(y&nHUnbTJVJ3rio_LQ=`r5F?Xw(!e8C2t_9Bk^S-c9{J=RWU?d}&x!|VzkFXBiHu
++Rn)YuZUIIi48byN38vkbgR0B*<@*JStEW|KSbT>CcBp&Ep{FDvdridW9~5rEBgpFAU@R6r6kXl_wdx
+V&^7-354MTS|AY0S016Hq+=KT!vNiWnD*Hj&)O;I97|*DlY&1CgT*7UgGi}En)o!{DGc{IgxTB?Sb9u
+YIc&3zamWwpdz>TRAM<RTXPpb4W_<o0SnqUu>_h0?rk$?nvjpYANC~_zw3ljP2ofHyygTlu-h#Wv^Nu
+|vf+rz27*Jppydg~?0O2tV24tHK#w!pXfCF7|FG{I7S{IZMi9C(-#OH#N`z0#fB*}T9rLWjgpIzMrYt
+bzP4p8dQG~>3R69P%0sp~I+whl<KhfjOTUr5pg*yFzBAjv}x12cMn@y&=p5i@{+!@&k@CN=OmU_6>*B
+b=xWuaMaCD?eVLkjjtm_~TDs(OAJq1WEZV_y7cnnvD7q1~4N#5R1SR{L1kOdaVcoKN3c_f)nfoL@LyM
+w{9fs42(l)%Nf3cVgorL3@8M!eci{hL-;}Q<4`32HHd$z-${csh7kLqWQ_1L16uF&6R^z!&Iu{K-4w_
+A^$9z&(L%@`L^-d309~v2^D4X(90`|3!bP1h^atiwPfi}o@N{c{Y*s)miqPcmy2M^ZqWDR{wnuXUO;!
+*B5HzQSpdolUnp)kq2)qOpAZh!oKEQc@fhMHC0Lvc+e}Y{AeFW9$*vtbv7N{Doq>Pj#0iDoJ7nQn3<T
+e5xrhG?usO?+fecNdL0DQeF@g*E-nlBc?1E0GPVHmKSaU=o?Z6qDb484)ot!x}j^293*)aw6MTQ0-$U
+_w)8qrUG<{h@BA)(EGngN3vNFA!@){JzAAj?=tFMk#tBQ43<%k|9|MGvq*xhE&$;qn7CCk=&#X&FB~S
+0B~n3Z;j@XCjA^OMEa99o2eNhoI@g+G7o(JYL#bbAq)G;IzdF-Krrk*B2V%+wd)E~`r-29|BNoQPuCD
+Z6kzj-m?dPNGY)2$KcE>7FfkQ64~Z#A$p`ciIEfhY<3vI!!nYg)4DxKwH6fllEPaeJ??DhS`t8%%_!P
+32i_z7DX}Mwi<+?!>WUkvudAOj^3N3{ZeZu3uONL@#L|yo83Xq<jOD&}hQ9U3*y3Vj}aZPoBAj+oL4f
+CdML4-G-YvY4pdN>>dQA$8S1MJvHoQ1LvusWSP)w640so1#&ma!V40Z_nK!<nU+)Bt(X-Fl#uehz`(S
+AOyV!b8Im*AeYQ^pltp$uYHbA-pQdqlR2`jwDh&P&OyX0d&6}92`w;vSE7PQDOuw5K7eumr^?e9saq#
+n_fE+1*Oi^qNl%(*C>o@z}X{u4c;heZW?9E0JQ7|Y!=61!E_Pl4-XID>>>j6{4m8iLdNev>`DX#BoKO
+tRMyH&_S{!$QZ_g}9HPb<2#p6bs9AH%Z=@gxFsGjPlQ>eOSZgFqbeGNkPiV6tURSy!UHTb$c_vX#X_n
+IbEYu=M-7S+Jbzxv~jm%<W+b;=kK(h|@MSGVdj)kEGLuxC@_n$(79J^~2@x-+Uw+vfZprUP6%+p4km~
+Yi-k_oM%Or=R;P7PDf8g)!FqZFfVa1>vH2FV9{Py0oM)m90Pkg9U^MSeWk*}sVjfD8f<D{6{N6Df^V>
+SNn)^nZg=6+*Z}jrkS~cno3|kt@o%W5MW|A{Y9upZr*S^?V3NQi`NgVGglO3L`6;=xT`V5C%w*QfZ2Z
+)LT=bUtrianW!>UlLd-q0*F^2#*2L3!7e>Ye!KPf6xf5K3S6SK3<{a80VSeU5V9zVIWX$Df<nfC!mt@
+%20&W2gl8Zcr(4!F1aE{al)cli(pm{Hu%D~0Q4eKe3e=$1nR`byotnw0-_{No<z7m9s_8ZvQm4l8C<}
+2I$!aExX-Nh`*+>*J7I6;3Y?i4eurCDJd3rXJvT{Ob^8id;KRr+NyjSHhy+|fW$7En&SOt1015-)_WD
+U|z6=fk3Qj7tvUG*phg70d54=4PT1{dB6L{|1CYF#SvqOl<W&1H@aIoTTcGjp7EY!RJDSr7`dqA71l_
+=0+g0CO+nwX`o(GI!%>P%LK<clKMC#|vS3daVt7Ltf{~+&1z10W#AOh-GeTuv(Px>-vX0!hz_Tx^5A(
+Q<5&>K@d^oo=<|HAChOstXsE?$)FJRgLEFGzsG^d&v7sZ66CboINH*DYQZ)S`X<sP*&k>U1+vV5TIBh
+dAU`Q|#D}RKl0ZwZiyA{ovp0-ob17=NO=HXTCbJr5)>kCOWi?hGB?l~h^;7{~O7*069kOTX$cY_rbvH
+~RDWTK_*W^+j@7~v00$W~nC2eTw&Nz5j?jmFm1EMmAe{)^RTnz2j_Nx?(j449xPRc~o2FHa2>I!QW3m
+E5MJcN}cA&88gUV$@^0jSb$U21l&oz`xA>va$Eo+vh|#KQM-X$;sb3YVBMP{vKhyl+)Gx)@D1HWd{aV
+;XOniKny+1ROs&90(hp0Ms+f?gO98`Bz}lWq=x@8ma=;)YDb0`T)T)qskNS$cJJh{>qd4B*-}P7*)j^
+jUifchzyb}y$`Zw$C)}}Fm^?#4R3qe#w8?-s%6p76D2Y!Q`)lOlxL}!{J^!XtX5U|Map_?DC@sjTfb2
+Su>zU#+EOHGrIg_-_95Y%<Xtp~;(JkT3^ITUjxEIks27Rgjjz_(qln%>HCFw8zogkkO-k$GD+bMGd8R
+`=wgwFcKEg+gty3`TAv}tg!7M;E5Idd9<Nm#7P+g4v|38IZFo&v>D3XQeEwkv@oJFO@FgtpzpGZA(fw
+^&oz7!p*8PXFHGAD|}kISM4tCjV)y^43<EOm<x&`d5Ky*9w8^@0#2^%e1FOR9rlN1XN@v(NP)n3lJuf
+jPqH6tzgMyki3eg4)#sH!BXOOYYx^nK+NLOsqc0f;~LpVz)}dVX$av0apb;cd5otI}8n{Z`&7zuHGf?
+vACt}ji$n|GYZSIV=gb_zDf^TCVJzX5(Pt1;1WjL+;f7{ftm?>AlZ-2b@D<wavfbZ0{D6fUv*bIGA%Q
+pmjrapf3t)d%(kss`&jVWn07~VZex8mw%oMpvab|%epB>d!~6bLP>Rwl86q7o$01!0uA*7XZB$zl_OM
+vVD;x&;Bqe7>oKgB9;62vCP*_$#x`P^RLic2v30oaZ2ZhOjAQt(yitmK1J}0R)l8r`sqbasSA9I)5mg
+uFTUf&@h#6{&3XMZnv($?$5(&T!joi@fkDxGfc71r7QihgZ!Q^gRP{;oWnO&MiVeA-ifE3-T&J}8Zps
+yLzpQ%!o^z1XhHW^4BpY*K<PicqHvWrgUMHyPNXwQ^#sl(NsJkG+H|1&r9r!rc{bd0s0lTeJZyasQs$
+49p>W3$(Gsj-jip%k5aqut8Po=+p)&)}RNPcC%R2t`>`g2<4Vbu%$_9tc>n$r`^yUn0L`<xHB&e{2C~
+`?fSuGrN9e~vK&T&!Y1JWJNCHOW8GN;EPc1wsdCYSs3Od8m!Hm&OiIW>)@IHPzNAbQy2d)P2=G8;kSF
+YV+NxNfrb3%NggX=+N)-ZvwW%scCV6**uDMaG6VPK*J+6_XV&)l}`38z`Yca<srJpw1zcQz~8=B4DUK
+`gwM}8RNdM811Y|e^pRo^grJC9&9Z>Fk>;LfFp?IjvZyOnA*RxEx~@e|FWvAtTPcC=aSMD4V$>hmT?Q
+zM4wt%__ARIJ)I>hz0pYy9lJIYw?t*j~)qs)YL%wD402NMzDuO0B+Xs<||mqRShz8grrTGiv92ND8qz
+C)z=9?{nIzjY2b%A9OrV3UIM9q~z3)e(a;t_}SHvJ#R5&wVJLWyuhZJGI1=cv~#Y9pW0I7rW8*Ja_^|
+rG<e#XyFB&1^@ifykA|1m+d{;eS9260fVvR9R0r{RYTCzRWy3TQO0Ek4ptw)Y%?+cID|ir1{EeJvv(i
+PSb>pM~E%d?IKV&S5qXXkj5k~2K!3G>G6U}44&uC_f(yG-xNcENjT=`O)jQi&J7sS(k=9}8H2fNM#{M
+2sdZ`ycG^54E|-wcu+d;9ao-PqK3%M1|$nBxh(w#b{sQKr(qjBn85`i09HUaVoD10XkfQ=Gr#4}{M^_
+qN*v<?|j;{#sMuFlpU*eDhjkw$iPAD`=ZW!(2(&U>saMH}^^<>az!BaO#o>VdP9wOrcgx6TS?2RP5WV
+B?DVw5?i%IvcJv<vEVLScTxG}do&d2bnT<L5SgU;nkS-4CpzsqCMvaqepabbP6&xtQy<99lp0Zw9sP$
+^P_ePf&7%MhZn_}d&`V_MA$#w>1SD0ZFp}~_tH(YI_)NgJ$Tn3PPtYr@)<~9;>Ae$DZRIJ@#d^F4ud*
+awFGYY+S3ocfN@?qd!F0QB$4BMhdTG~(-tt<%lw2)4X!^zafJwb6COsJ%1Vs*6%F@`hzDaa%n$iT?>t
+g2#c4CHeLZZ?w<~$5Ab_cN)0WBnI&7xM~F57<lfzxioK-gZaJSZFP6{zp2hpKpOdW{r>UD$<zWMgVc<
+3w}!T1wL1HK^p#cG`B*q`~h}K9QCWJHKMX`JB<Yp@(3VuUK{;gYnN2&(N9lCpzh#;t;82+LZs1^T<~R
+XJO{PMbq_8Yzw3#Jq!a=?$MI&?|3r%P2V&lB?TeYnlnkoVl~};5jc=DwQMd&S#1Sa_9HuPh;W-GQ7Ni
+zo<?SHS`e;OY^Mt?v|<ox!ULvN)u{N}8hxw5`!Z}TYc9y}sm_@0T)O{;a{aa#28_@ui0G7BP4J?iG?i
+ryovazjswxT_u2rm|hHOACX?ojnoOWF$s)FXt?r18}GKstCz_JKdE4i^ib+Q94S;?78Ez#;D)v2Z)XJ
+fE>+rFTo(!Y_P#=WjvY8c}%<hNG!{0YC>WsAb=83sf|P&F4mykvE>SQz~tOD)p!kIz4SyqpX#CIhhlx
+O|L<ssq}!z+m>n90K!^t~n<^;NvC{ib%kRguxw{(`6jb6|i5>T*yh6DtlNv%l4QDR%%cQdF0^9(4$;E
++kK5ia&RW#H1S}q|I|cD6qme|2fKW;!zz=KK6oa)^`b&_wwdS*@NKV!zwH%Aw@l!R&A=BpAlsq8>#1W
+?f|ntd-K(5jHzm}1{iv?8tW@17!c{>(HGwYI`!`^C?_rpQa|16W5jfO6W-eV-2D8t&6Rl6rs*6o_pA8
+;VH;iY$(`_oH%hNhGq)J)2IP!oujq!c_tjbFf1BQ+YlXAAaEKQq~KCWPOdlm=OLtpS_3QXS_*Cer0ug
+XxC-Ye|YYvnqnmWK9Z{1*3-;qW?9oUFXi5tskS{axbJUIMKi*gfts#e4kb0bWK!oOsbA-MLp}rL^13!
++nwgK$AdFBYSvXPXxVbGwh5L{dDY}Hkr`va0nn4x?<>@AVu7UXG&1qvDYL%vwcN&=F5uU#LJG^rhaZ*
+t$|ChtU_Y+a1kW933iE_f~ysmH@enhwxben5G}B@8+le`w;U{)Hwqabx(4n=oYxh5-j+~PGs1izQNNa
+d50D1@y@{5$b+jN%DV*IVnyRA6Ln5Wtl_+DC-qJIQDoVGN2|B^yUJ5cj_NCO~3*NtzaCv_j=v9iBs^R
+WwiI;Sj!1yr)4is<G9!qh<QgKxUZIQ<&Zo=1%<s5ioxe*lH--<(5wVuN%-PBRk7|70xBVT@;N0}^N91
+5k!h~2~`T0=-zKHeARt4PG1R+qYyfJV~;!kdV*W)|YIb}Sr1{e=HN_Y{;T@%P!W?hz^9H@9$}V1%Dp2
+a^9MTfPF>b64w1Q^gOT(3bnU)9ey&=aBs;9@msD@yEM&$3MTLqb!|we|huvZKc7{(a~G@r_gV`<Eyet
+Ui{RWIz%fOCmvpq3MLU@vM&aVFAOpCh0N?1bgi7&HY^-b;Abh4PYbR+Ft5Ic*UE{DJL%p~k;BG$h-)`
+&r4?SC$)-ctB9JKdcLJzvnbU1;3%dM7#P0gC&c5^yNCd!;{9pyu3qx8hB}0(1FNItFA`DSci4ooDQdX
+I*5W#&VC&Lqg>^)4dzDPM}G!g#_PDDUTOK{l7HTaR>PnhhPuJ@RCw&9|d7&Kf0gFc`<x8M%>wI8pbVU
+Whr0j@cR-nw!$o_ZRWZj_aR{>SLHFkO%Z6_ZW8w|5tmdN!@D8eKQ8u?k~cj6laRx!<fy)$`c~R%<$!I
+dA<hP)h>@6aWAK2ml;P_EvT5lQDh-004gr000;O003}la4%nWWo~3|axZjmZER^TUvgzGaCxOxZExE)
+5dN-TK`39OR1zd-YZ_s$m!=LDAZdfdEsA-DqDYjjRTd43Dq_d^?>oNf&Dn-w{*aKzyW`#S+#Pj<?r%S
+SbFcFRmlbxeQe3h;%P|en&DG2}lE;^MfiK8rOY`N5&F~Wo(a0YKXcm{a$kA{0_wRX$OHfyiQp5<ly}v
+|tnPQ4!bU{i+^T(PIiq4l5<27958Ae9Q8bwi7vzp>4Liu__C_`~s5*D+Zl$Fv+V}@D2##)2#okr@Q_H
+T*{7R%+1lw7#W%Zx}jSzRWKkfPFl3R*`=oUE{+1Qbh6w%z3AQmdVpTNQ{G!3l2cZ(~~F%Ywwrfb^%{(
+u034^8N5+6#Bk*CVoAc5zVe{rqSIrx}V*lF`}k5_k+dUch4645&Sz@*dd7ApQWt7u_oako+Z}Lf%Epo
+7RzIMVj2dx{PgAK!&G?1UP9IzV9qiS{HSS~hHrqm*gkQybN4cKvjxbaNoQ{#gTfJ7;U}TG7k?jlj7l?
+*D*fLPdd$m?0RfMvjqlS#lOseDX4uBwn7?rs6VUYc^8k`*;sG1Gqn_f#L3zpW5^8D_QwG`G{*rO<`R=
+{AR^TIydu}G(Yd5^I;sRwfPSjGkQ}%N_U5Jogb<?rOPaCMPl1XdZ0EivoBrD=&H3ka4PVYW^zMnd92;
+^LUzBs?;<oEgM)`QUdcs`pRs!19%&ZFZ0`KOl`+qHaw+CBi`XwmNH!AKR=iJ(kCDB1=?nWEtA-8(k`l
+hdXs<}-#CV)fjO=|ux$&41r5?7hXovHzuL2T+OLC0SNs0BZ8jNEt?oGqjFbvWggqbdy^`5^_jx_{v7^
+`*tqu#Zu-0-eKVUz<iRRhYp|*(kq`%58Bexiw6Y5sV{zj5yc(e#d!ri|1~aZJf#%$@(i&RR_;;)hcK~
+FLMX)*6onXoG5Qe~c`5>vEkT=jJsqgT*3i|t#W9U4Mx92ohS9m|i_&=87pzD<w93nx;l8ZG$xtbwr0U
+Cdbx}uRnl>UyTU6!CvahQS4sTZn!ys%ZXn~lwq@><dmTl;q9hoN|>08i(F1IukwrF~*!9nd62+{@6p`
+$=~g+4)BhD|gS!|PHC=&j*h(wy5m3Nwe}q(aa>bqGy9N}v#xP9&PjvW3<w{;Vrzy>*c3o3_nEZ4VJHD
+vW%c!vN_v1-1*-I|hZ$vx95Ivz10{*H+JKq`X4L@SetACIWAI*49Bc2)I?ht6t3#rCs5W_j*ARXmpOU
+%a!_OJZ57+hG^;`A<iKgjsi?S<zu$vL*m!w?S{$lROLH7=C{~ldbHqZAVMTkZ(&e^25i0+GexH;Gw0`
+!K*0IYx@bH`<{MM8=LX%xv~f#H^HI|0iN{rqh4<q@vGw$1z&*`w9S*oVn4W@_za5_~!EL>C3q_BNZpp
+sd!~eJVJLp;erSo)T2YHwE`VrG%(hh&BD;$ZBhOqPXCeVPdyim7dCr8U{zA;SuV61c;T3sXC?j|OZ=$
+<;rw~fC5P)h>@6aWAK2ml;P_Exj+5@*E#008~~000{R003}la4%nWWo~3|axZjmZER^TUvznJWpgfYc
+|DE6YQsPbMDP0*f?OTb<{0Q9xR``CV2BTe;KQa?T#>c3Xl2O$eK&3Cb>7UI6`Z=)kM%o!A}3rQMr5Na
+p>E-L=-uiUw-m6En3bk4>+x<|*gS2Xq4$h|V87gM#K@)oCmO*7x>E}akEr0G5jLgEVxq8{6mc#`wR2a
+M87xQQ322U@20P9bG(H4>30OhD#DK1-`y3HGvzRv$POkHsunpo3Uj7H?b21&Ohh=bYm<#$bJmL!Kx*l
+97sief_z5!560|XQR000O897^_9PlF&RY6SoQ1q}cI9{>OVaA|NaUv_0~WN&gWb#iQMX<{=kUtei%X>
+?y-E^v93R_kxuHW2@=zv7^xh+TL}*A2s9z`(pFZGyJ0k+|E3VGwBPY;&PRm89%wfBlXxOU`3O{UOmE?
+|%2-J(#9xvh2)G)^N32EkW?LVyc4!H#;ypg{=HRvkgKa>lzEgNwASp@OnFe4Hrn1HlW+4k;+V<)u>>j
+IM$`;Ccx?vDyc9@$<9W}3i5o@npR<+1Fx(Ou(g(=HJE!kNnXG$8YpqYT46xQ?Ut;;j<5uQ8wqSLc?s!
+49+?~2)@2F@rfQPaSrV{=awOxqcO@c+!$m8^mB&lGKo*bizQD%D9yGIjk4oEI1c5v<@;pfN`LgMXayG
+|rk0(nynK<6<LuRj@TfDqgA^_W@yPQYg>Oz*7SClK>FlF+MR8`3g3-Z={#cH;tGzArF;*)1hV5#JNcc
+dCiJv6CMHxxS#qqqsYAkrExNbYNky=N7>!+b{-M5#FyGgM(g=*AMmQ^PBi?Ga?<$)N-}7EiZm@*O3^7
+R_ungT?37C9FQf&E<0b_QU-B<;^Y37Z>oy<>KNqeUl7HE(J1*rbK}Tsmi&AwUEW##D7y=@B-*V)}kYE
+N+^&`YK@;@jkaP+u8rbrD%ukEoWZhNUT3auaSA(Q8a+Kf-%<;;Ybu25JZK;PbFC>+=Wl-b^>sqwPZOY
+D2r0<q8VlPdcyAN~cmbws2%K+gY9}IV`ISxK-OsOoOni01wbQ>;N-7W7Fs&058a;Vz4*M~3Ec;8(g2l
+hQ#lO$M+oS}P*eEQR4byh=feS$y0ELy@6EE#Scnu7EXVbCIuiPBd_9nZ}=&G5Y20+p-(=HFwA<p+DFP
+$7Ut(RM=y4gkWnOf&hA8{|F4J+;h?orI%c<wk!@|?9a02NK78Km>NRM^3i%2MuO#2lG5j{HsU*uV0S)
+o8{k=?PvSwSZUrbiJ~?;~XH~a4J|cLO8b1efoG7gmBU)CPF+KwC<5LXy742?9j+_ofe7ER*__7nQKFh
+s&YFOd!Q%gP&}e0U~7SStgFa>b|6K8*tC%z&WXr7okPT>iwg5PBmIxg$x)uytfKsnGYTNg?$Kb5kH(~
+y&?bRL0gikbM9hoJ-@m*c`$n<5%KpDX(YW2B;A_jNa5@WP`=7zBq19Mj^*hPz5Ik}QUo>u7VHF)tiR;
+!|NgPcV(W+WImAJsz#@N3eo}28%kr%MC-BKZyX$duAsjbO%-$;4RYi{y9YdU*E8FJ_`KeSF1HH8Ui6g
+h3KzB>tkI3;yv=@!3j=2{Yfq8U=$QDJ$1e0)^F|8o;gFh<o&p5$wEB9&=0@2EtWG4@)5LeEKGj+id&S
+{Q41>F>=Nb5w;|lYe8Kj>iKZhxHK5oE($Mj~2(HogBH_8m05Hv{Mg!(LD7E@$yr6Nkt2%@hf-3Q8=;N
+Da$f=OLMV?w#ld@#p!#4B<3_+LoeBv6@{+hRn=<q%HA|<8oDBKsjUUY44rJx+^nUk(m{dBFjoxB-Mn2
+}dM8^^)@O#)r{J#hz%@>&yw2=}(+=J-Rr>X&tu+dYK4?VK4)>2jf~l~eIJmCdxu(}gUD&0GmEU-@Gq~
+x(s3l+~4y@C#l{Ei1u<qhRE=!IJNYknl=wlqEUV(Dhzp}Ciu#*t}Y^7QpTeI!@AFAiMFbhh1Z`{WmjZ
+5pPZDIFBc*cBi?}7cN@E>_`UHg@}6wKHm*ZWaQoA<qaNw3iykoqk=j`Reygag7IVnbK)&GbC!-!qmU=
+V@{MiS{KO1&PNgqUy1E`ab)Qa35IqL-*l^7#)}N0Lrea0P^km>k-`urf!MztAF+n)t`ySzo00b=*&3z
+4^T@31QY-O00;maO7>PAKNE5S4FCW;DgXc@0001RX>c!Jc4cm4Z*nhna%^mAVlyvaV{dG1Wn*+{Z*Fr
+gaCxm-ZExE+68@fFK{zNZcWt5V9<V?F7uU;fZ;RXA7Ht=cLoRS=iB7nYB~_&SvWNTc_Y6r%q@+0M-uX
+jfTf^bJ&oiVqRk3BO)uz^UB~~jYw`Eaj#@DLIYAsgw^VylMju&SPuMI6oiYya}mPM{&zD}A|Kl8Gb`R
+$zjTx-70g!_CZ4v8o=duOPAsH&nG=k*w$PzZfj37+EnX4%J|isXK5Gse!@hm7k@QEeBh6p7r(<bwTDI
+39}e9hVtxb!PY{8CS~kvm4SY6&qMe<XTj#Ris3=nRO58RbtUupZp-Tqn<N}w$jH^*mpag)p)Bbo`^M1
+?nk+uJ!GTzRVpfxelHX4h+?a`PxLOwCNljII*Q6smDq~kik3#nL+?q9ubQV4+TM$!nwxh<WJtAI@hn5
+MEZNoMqex(r?D(q^>1B~?E^|>$=4|rg=g%MP&LrgI8p^DGsk02LiuLbMCz|0aXX-H~QRseWpUGrm{(q
+>7olKzzcV1j5z7Z_NUW-iL3mDDuVf#Co+_5b_&=-o;CDVmra&xog2POXyH#dybB+^U}!(va7#rOP(Pl
+9EFE4`?kn2Q>6+68NIEb_F^EVglQQSyp!nfto)@6Y@oxAm6g^>z*UiVd@znaIQz{}trJS0ru7DV3@$l
+t8}bNyqMoov0wD+zQ5Xa@3Yd#l#M#fS4{>JcG>Jl{Ys&$H@4123ufx0vC%kX6zDgC_bGT_Yy9=71|NB
+J~3}v-(6-3ehz}POA48LN#TsMeEDJ?sJHy3$c2{^L>;djHF&#s;d7q>X#9_7Jx*PCEbTYG><G<(IzuG
+@ov8>Eww*4p1R1<l2SMQpeU8XpAmjv6iCjRWP#KX+WlNKr>1&av6a?lic?~(tGKdnljP_FBb)tlo!Z>
+`{S1T@yG9qaL+8)sr2(Gb~SOjzkzPhrp<ZG*j+RmAcnocGcc(%ZSxykw`X@W9cC?(g~(K4|XIY_0+UX
+~y1G{v^lU}1mDzAfOT$jEABd6G#CtFxYX?>1~tH73oc+KGsa3niQr$yVOpX?DkVf_&U6(_?3<3TvtgG
+gZZSv(4GHxRrTMyj^^BI)yQ?0kb^n=`v%l!@LR2O|O+P%VYLKERkFhinU(8<(U$*&NSG2n0y=|9dboY
+$qQ{ga53~iP>6z+LB6FTJCSdvg6o8CHcw6}^q9m$N#TznPB<l?%egT>2Gw&EfK*&60Z5|(d~6dDsX;$
+cu*c*bR&!He3Um#G6qS0@gYl-$sdFL{5wmO2pd+-^c+zt5WJwUe)z@fvjs{U4Sy@OzQKrkGiCE77Vj#
+YAtS^O$^sPgE10Pan$&hhT2T2A7JDK9K75u9_4(#Y6NajwAVKO})7K9o8OiVQDw(CP>8ypp4uG0X@L5
+e#=?kV%el>LepQqkE+k);c(ddX#_V!(1#Ey`sl0^8P^mIymb%yPa3N^I35uO`J7+o8NAT-lD8E2-rU!
+4@K%`#rC2eQDBEQn>PLC<(<+X+k%rw*+Pq9oJ>bb%(*;xbJ~#da#gOs&r9NbtS_wYdPf>zU_2j5Z#bM
+0V-@Kv>{pOaVB}52;*DB?c>`^_T8&*U&O4-z_Nj`6z&@+q%Fgi9fb=b1NI|X1y3xm{;tLvPU>G3sdID
+V^=fFYj!^nwQhs0ITV;(&J9FKr!^D@GXQMk<y$XVJWa$P<x2B!KM5T<`TZrj#w!D1qm?LtfVP}@0wrB
+uWmWw_3gpmu8$<Anqcog$Ay}2>Guq9_%QIt+w^y4u0oJQ?_W17%I3LE&(;x8vA1gq)<UWTHyZ4*dy*N
+M^1C7zf%iCjhu*=SJ3R#;fPwyd&3X(!<8*RPulL)Ge~=d4dcnnu%4LN6|h;$DjBoJ}`Hv0U?N`T#M!y
+hvK&HUDGzr9K>n)K^mqe6)oH`pd1pn-a#Eem5P`efr^Z!|~cYZA6%}mi=(mrQ`mS<8D_v{_T7)g8v-{
+1NZ0b`Ey$UeBfV~m<2=A%}u?W#VxNMUJuZ{H-&g~DEW<J95NvZddPZ%XB4oM%aJ3W_uM#ppbtQX^0*=
+-*Q^Yik^qW&V5vC3mg#UA<muPP{u*b#r-1gsa1~%+G^0K2KBG9fYL;Agc*8cPQwyIyCV}%1n1#H0`_c
+hJ{5x<2b=a$y7uR0_67lrOaytt304pbrx0*^+kGaoJd}%oqs4A7m3(ln|^a9RM%$wt|nJG3za>o_dx@
+w+J2oy|aqrkyn^~blMQz;8edTh*d_@*PUOJ;o&P#=h*`^F52mYHc<_juRZgmA@HRJS6HW;3>2+Eu}ZC
+s>$`10G|bbhXOGgEn@;k`b(vtV5hiXU;}S9^w!Gd}YrKkNOU+`c-E`hr(c#5MIU2lYq2EtRuwDaT?LC
+Frr~~6`YQBI*kq!|I@&5&fe!}h7N<676&MVX%mS2Xxe5U$T<kCMnXJxFuWH%M+2c~&D9Gpt!U!%N)f)
+|XyVJp1RfJKj_>V&b~R70XKeAB?dH&X3natbNv=JKGs)o$V&~+l5&+_P+79O3#Qe?x@uu!?3iNY`L7y
+!L8pAj27H}bVF|?=Y>L220Mk+%{^Hv)Bl6t1KD2(I?-OgwzFxW4Z82f4H-*5?&rnP7egUU+o2pL&p!~
+?ECVQ^A)G|5B8Vf&(nnZ<#|4tvZ*;}t<>i)d<C!sqj;K+NbVX)E&`ojcMZ;B=97WbI*l^YZ6sb4b!1_
+}C-&#yo=_>KsgFb6IC~8+Jcq)v-F}Sae$snrBnhL(x1I-hmDUA;z?XSLtY3ALu^L{G{I9Z2;{?Sna{?
+i`c=KLnql0Wn6QjW?((yvJi@nn_BR0yya%m4V@zLjOO&CCl|)WW{jcNNfb)xZrUNt9=%1GZ;Qgg%W<k
+J!idw(GSdbwPDc|2HdvV|4{5yK**?ceurifq6ndP);-Yj}zTG03s9G_8k6EIy=Vv7%p5mHg(4iwX{4e
+dvVi#R*gMK9gT5`b_wPMa&i2^Lvis=doy&vQZELfI=%*f|mKsdN&W8yhswo&j4tNmR-EZJVNwH1WQG0
+%^tHPfJOU19G&Yzyg<`Ay18x(h%EDRcI->GvZ$>;zMuJGUl-deeM+Sb@N3hq+?YWOfTSM;-5uDUFisH
+GA2^EanXBGxQlbxiYMr)n-iddm76%+hW#YFUh;jF~MZG4ExpgUM2eXi~rcdKAXgJAINpoN)+Pr?o$JT
+hzO0Wr^OQ6Q#oS21EnF#IypBOq~l^eL_5X-{nkpa#tl(hQ@r{(DnWP>)Z4n<^|74{ktv0}4W9x``<un
+)Nb6DU#`o+u0pE!BsP0J$`KNT_Y;0o2qpo<E7bQ9-A9H&5WWe*$v@7Zcw2o4X&PdyuuZ(o`k$OdHk3C
+}6uF5;}Y)gH#Or*U$AiFp1#59T6PtLK9KT;vb=d%AJ2C(h=YP5+zjsv=GuV^l`jyPw3;|ci?UDljOX}
+Ok|5s${0cUqU3TpLQbtLv1`cg+L%0reueLk5l0NV*s8zIx);u{~}1omb69biLl^W3hZC%CW<LHxxfp(
+K9uhuxBjl1~!<QB4xFj+i`0+iTTq)cW5y_L7lD@c96Gu-30#N4l=AvJ3163!jTei&b}`wR&!y`>JWoF
+bCp_`nKzh(yPHjeVo0wioN!#TZ-|9=zX4nHO`T*#F2aF$7Cwx7HXMw~hN|18EAhRpkel|bSlGK73JM!
+{=5m;RlaVJ`Z3dha7Lkb|#gibdJ&(}_e?G+<X0Aas88&oVF!s$un|guwWObn_Eg9;Gm@xTTeU-vrqi?
+H<(d5*r)2Ivm>zg+3ToZ9?|7vb-wos!;TV@nID_54HBr^t3ir<Ra_@RVp8^B>rSu*#>yrpX@T*IZohv
+Cp#8tPZ^ccw=eMC)csPR9f#eDdbQJ9`yzAS_A_F~{$2TaTC6Y-A$MwRX%t(<NhzTPv}!Kf0>;-Uf1a-
+R<P_7+Fc}b@G9JE2ZsqiNCLtj;@lLg~eK}Hbs^iAIrQJ=_+eWb~G`b{Fk0|x!D!;tLqR5kcbpZPPTY(
+VMZ^4g!F?A6tzk#0?E<CB8*fzcQQB1yEDdb!u(hO@HK@`yjoyyJ?!QdqQC#`6HPs-P)Q}%?sqyvj?nA
+l+sg&rOtDYj#;@YPICsfBHF-uj#Ms(wW4FX)SL+8DQZ~BZY)}Z%B({@9tr}@j#oh0SFum~{5MFb9k~$
+t`Xh(wJcWlG4pm|L!0doeomu$uwLqRUsGewP()EZ?t8+<!{U{5a(D=yoSc=7Ujl-PStvFNS+h9NNV*F
+{n#%V;(fgI-NYg}+Y;#IQ_|^*WkdAlzSuoZ9i;4yT?N?am$`ZabIiE+zg8P)h>@6aWAK2ml;P_Ev;x1
++72;002M$0018V003}la4%nWWo~3|axZmqY;0*_GcR9uWpZ<AZ*DGdc~e#h$;d2LNXyJgRRGcjMfoME
+$t9^N3T2sz3eNs6uKwYEu0g?E@$qG;Ma7x<dGYZIwhBsydPZh?hGt4!08mQ<1QY-O00;maO7>RogHbz
+17XScEPXGWR0001RX>c!Jc4cm4Z*nhna%^mAVlyveZ*Fd7V{~b6ZZ2?n?L7T=+cuKF>#snS%b99r=5z
+N_?dk2Rw$k|3wX?R;yuECerbtL)O_3}?TG95pfBVi101^NxC+X{ZcRy6^izyJ884TtdfL3L`WkIm2tG
+eVtz>;l|mlX?_B2Vjz2lD%1pxWcG;#IQc`g@wM*Gab4Uvr_K%BG9Rqg!6-Z@aL}V1O8`5V3rxk@B+4O
+BM=tP0e%s+Sd;W$m^=@xsVM5+1W3`=r&w)q5F&EgY(9RCV!jX!PBOyiXci8o;C1aEf%j&@+{*~mE;+s
+3GAlNhBp5Y@q&P{2Q15f3McI4^T$sVoVrR<zbNw$dp#y9IWRh)wm^t9i1MuBA7F-6xt}1AlYCnwDUaD
+MsW$BT`uxuW1|L0Rkq+qlH=*G0l32;6*zW7E15QLS?~KM!+nCL&s!W!!^7MT~xL&7WwaUxwu_$<ytde
+NLE^@@_6Al0hpfB=_OPo;}3SnXP@Jqvk(S*9;r+}UVIVoxbT>EMRY<e~UHo*$RzsGqoW;=dVau&uh$P
+TMEiC|R@e>uy-Ef=s59Atzgz_~DEORo69V@YAVa+(oNi{`}zK%)kSoTtXboT1)F=4DMvLB06xruI#l-
+}3BrQgA&rr=>eJb6yi`$?TE$%}fd|h-I2eUI<g%U-2;J<!KUCTHcul6RYwviNbUY#sRe@W=Y2Go{luI
+J6;M@5d|pF4MCuKa7|Bx%rlo)Spg}?^x}f=oYj);*Y)y8Xq=@La^<ZwN$S;JRD6q|n&y$ArW*0}cW1A
+ISM%BF{Ax^JUeCTcpR1PZF^gPVK{}3_Y?BV$<Yg7C01+>XGRZ1QhB5$knWo9|nO1-KE)hXefV`Ak2-y
+Npd3wi#2w|1{C#M<FDqfDY#s<4GECOj)?I{wK+pvl@!6p|KN};Ct1mL6ohsr#RncZ(N0Dk}?sJw!|=G
+8eo^3n?ed>;g(!2lrzOE7EEh6Cs+`+0~~b2woy9*-G43;6Q<`LkaJg9q&GhG!)GIcNi!e$<b;Ku;vq<
+t|KXj#fGZ=|m^Af|;-DG%SHU;3&_+EaCvlOJD>S$f5`gbU+{gz$#2qAa|sp0yaSLuRpRauze#y>A?DN
+(#fbUOSJ9S&mUaPPv#ek;B>Z_!#uQa^zp%a`uOS7F?$04!<>VY%ZtVA?Bbdpt}f4mlUK8=;0lM8+>fL
+&_sZeBe;j}D;6EPz=h2s6`Tq!R{`X&xkG~F&|2aGUpZ7z6GmwgEdn3>BPGgpncq^?P4u_2^h#BbDgn&
+$Lkkh{ORlW`3hJgoQ;C=3r7?=)r2ZXN-QL05%))6Q&fn0(E1cx4rW1K-)B}-srwP$I#=OwVM+HqLCJO
+yI_Kw_5h9Xv_fBYbIkW?=XbXPB~EzTf3#jH?L3Qh~&>5cpmr-LN2leU+?hG?v;)30!Pimxgv}7H1Kf3
+U0wlvM8-%u1wxBySahMfQ`DjnXqdv*Ei0idJ7B*$ypoBQkv+uh>AQ<9lpJWrkfUeUY8LMl%`576=9KY
+n0muNx-8*xCnJHOrUtpRe;Sx}$V{~(#R#d+faU2PJ&GLYv$GX>R5gOfW9*nIyB_mZSf`cbcbbFsju}~
+mn;UzEzUmpc^swC~i8h+Yg2jmlm#9?=!$r7G`4J#U*Wd-J&6atB1H#40>)_(@bbdbj8?NyaP{J%lrr4
+{BYP#f`1cWGL6c#D*VeBPvkADcaMasu4S+RXyLr^3(2o6+#nQ}zJzT>=LvoyKm=ypOSb=ucz28<O@1h
+P%mn~EIXMC0;(peg3Z%M_+RnXrOHdC+)A_DS4gU$J-X5d3&*m9D`uTwk7iH(!id(-eF+pTC}+pZzdLV
+=`_>zSoE^OG$9Jhxj@p>m~Wmt;w<Fo~DChfjYe{P*=e(Gmrage+;Yr?)}Zp$Zzb%zz~jrT)>ps_WPYQ
+-ink56LzW)cNZM6D^R}f3<&kq!G&I3E-nLDt7h(oaNyK|Hj5yKt5fz_z#59d!vL2`=}Zif1DA=KB1I8
+h9Ly$aJ)p0hvFaBC0WZT;@P5EDzBj;oAggHFMm8eZPomR+I#^|5VB>BBaNrL_Pf3<kK>%8ouEy-kuv`
+oH^X2W%2<8%H6Cizg{kNwROD1o3evud6P}<1hnBb3EQHL0^<i`SykY(rmrUzp7?Uz6%z=f~?;94(+Cg
+cfQkddUEPp_`>Mlp&JnK%fXlvQi`fb}w==ph(mV}DZ_^q3C0jz~3ZuwDQ=sC&O8I$Xl_ymuBh2~q%B%
+=EqCf46HO{h~WUHFp=zi5C2OBt;JT3&1Nt0{4w@p>$GrLzZ-yfuC=A1s<1y-`(Wox@Eu*Mh9kH%4iE*
+ZG{paLZY0-B-@Rm$(WM@kC%Tvz3^M&&oZ{=880!5fb7!L4DdO5c2sE>M8HgB8Vy;$2H>hr)BW*Jb(l&
+$igSz^Dfb#v%u;P?LB4XY;6u2XP?#v$l7h``9VtZa8xFDnZfXs11m<}LNIhTWBxS^b&bjqSXs@>1Smz
+Q$ce3rMtNa5v@JjMD;^@sf^F(qQK{I&wD&KK{HMZGI^#hwvVCKMLW2%ODPA{%yCQ&1Ke}XPH2h%*itq
+TRGLrapTEu-=b{!v*8^$iPrS0>0#T<O-i!6YCB!kFHGPeq>|1cHZUB(V$1-@sC<Hp%>!Snzf}m=|2r1
+P!{(Y?RZy#TWshfX9La2Ih}!0<)4sKt*91S`nIs0Tbwg)(FCDA<34I&AEAr&%wXa%1HhpSJligP7xJG
+OM>Rm01l%H<dUKn!*7I9nG2!fEm=HR6G(s~IM9ju4P5@I2B>1>_iAX#tGdjj6$#=@PzvXlXzam&_}U!
+*g_;Gab65MvGW9xO1g@nK(828u4!dF6mKbvR7LzwoYwaNRs&E_mE!CtUvJL+K#4z-LZoqFOrvWG-;7E
+y7Dl%ksg7d9lC|7x=q9a5|P8#5pVToRNm8WUGW1>!~e&*R+1H(&fFnllMIcR>f9veAtRyx!k&Rkod6J
+2TsK_(<o_>A_7;(DZ}fi#f|IKdJ}7fwIfl*0wLJ50HMF=K!pM{UOfdgMFTYrn^uVt4eQ2fFDX4@0+{t
+O4C@Z=pAJL;XP(z#xMYs*uvQcy{E?F!;9CQ@M6D3nTTc3eM;iHL(^H!@H_#n^l*#X$0#9=Ax%&)uoJ-
+tkXI)YSW<e4`o#ZQu`WAo2O=~i{#UXVl?c4c&H|A%vbdvjX!B-b6u+EeUt0f-44u+4PS;-#kOo<h=l@
+U5hpOmA<)bZk*2H}jxe+k!s8lqouH}#QtB$>1NLp6Lyp2`MZxA7*n3P@v`L9`umtFE0TjGp3J6Jvix=
+WqG)l@Q4$ZE1_(fzDB`+XQZ4HF178;Z_GOt9rqfMQujqFu;z!sOMmlO6f`M_ikRYJyDVGI-V0zE~Z8M
+uJ`I=!$6X>d3wz7NaWPR<lcrj@*=EU*hLtg9RpnWLIMZn>gBxND^JS<=y1RVNCzIZC{20T*?pT%qE%3
+`)o7VXR;mpKMcY8P5l7PU&)-N9ZKM-7a|)>ZAff%eH8=Vkff1CBuu9Hw7gF8rCzY+)kyo9aq7nOy7~I
+DtLy#5lpLHmueS@%CEqngY`vUhC!Z$HZmoN#`bCN59rMfXzlQONmdkQxXxIYrr0*mjw_l?v<XXyTQFp
+OSTb)#krO!C6r64aP5s75FACA*uOZ$lywT_*>h2~opSRSOh-_%XLJgB&pewoc`-DQ}&yd!5iNI(d3(e
+jgSk$T<ku$$z)2X>xK;h6GZG5=E@zXP<dr51JbBeYB@_3#J+{gt2JlWZYSO&(AMnozg?(9~4whZW6DD
+4)QlcT^()CKxZ!Hyn^qu$jX9*x=2(EkylR&N^?9uN!er^5Q3psg*hL*r;P8u!WrF5o?@zRctO6fLmko
+uF@)8+fDl5>SsJw^Z@ek!UuW<qm_6ud$;-=^J1csI|laun)NDAy7WLWz3QvW7)?yrO5FhNPzYnI0RP?
+zf8LJ6uVM@E=lz)Uv9-=YW@hX3roMWLPMSk?mCv)U7o~jo5#s&FE=cCGZ<@&w5tc4^7W#O4&YHwev}t
+`&oWFyEQ%b5kmpxJEwr8^+qbP)qek6g9|dvLJF|DgHwbk`P%*F!faig(-yp_-Fq+P#hD^nC_g2V5HM8
+pq8~)P@o2IEFtU<J?vs)1LUnR7r5t^l7Z8LBTcU)JqqkOvsVN<9Y;4)=I85UNaiTGsxu83khi}F~OiD
+PNvP_#Ltx_2)XorQ%Q+LR^P8r<@|ActOg?>>D=-y4f^n-oDvyE{Qc<&+I&)3I(EwxbEBJzk}4LyFK2_
+M|MJ^(mHAS?kqD)3mQ~+@ha0PYv9UDuF>|k0oe*g(>Re!-C%8Lw;-5B5hsEdq1flX?7z_2ctFEo(H5$
+nOFfm?b3YibQT)KT!R1`sYG??1cM;lig3?1e<b9GZ7IcckbDHyzThOHAf2*RHGRdr<-X#=@k0RG@cmN
+z9cT{k@I%y0ne1-^#KoY=A&>BVceIK-s8{zbelRdgvYH<nYLHA&!06!IdMG7mM9x(H^=TowH>|7Gi{Y
+p<AmthAGg*QU9(<D+Mx%F6C+|DGAsZm4Iwb<avJCg0f}jzNx;XTxuVC2l@8#dKZk%CsA^g7vhV-z|$y
+1%J%KmIsaar2}rba0y17oznVY&;!%56fdc*BbvogyyepbK|7e2l0Gy}iGGZEWz{KFHbE{~oLAY8%|x?
+Iu?slQX?%PrJLyNh?obY!qK#pA$S)O<L~3$b}j0uuqEpWL0NTyA9qP6fusG+<gANq0k$L&B+zLkwuLm
+ooMN63*w~gZ4Rr@Y&VX+n9bc|H|E<a6+w~(_y>)DQo4J4)&`rks%`azN-NDboV;}DO%vEXARy&Vb0i7
+tv}1Q%J3JxbypmgVPNS~>sNK)t+w;qBX6M1_{N?P;`65`HeLuf^voL_Prwm>2v<1-|@^Ri`LPcLj6Jx
+94-Yq6sbwZYmHSO}xxS`spxHbDwjpk_1;g*+rv^z9BM4P3byD&666&(H5QPY+$@&ILX7Srx#Gl^mxtH
+rb&S6ZrcHJproTaJ>|DE7qv+JCH~HY!r@6543M(zXGOtVL7sN6lX6Or4L#cRus*c*~g(;MgBL`@<i*^
+^?5HqdcXMh_td5bBNSPvkr;*XG(FS=btX!+6p+$N`((dWmm!bp`sl*^af0c@#;YIy)bGuVw2ZtEOWpm
+E>xP*iK__wf_a9_N(b#+&@MThtqjAcVwYwIdB=~^RPUUe%&!)~)%>q-&aURC`UuSq{7))!1EBOt8QS_
+2CDZb(7{(e>&~P71!N%%V0un`s4E6yeecZ}gE!w&<Ra5&nH0WReW(h}A_isn~1`*c4Zj$PP>YR@BoE`
+Ds%&3@Ho9AC?cO3bKzD`STciW?N8y$LE2irVi#+M7f2&;|HKNRp4a|TbpAN4{|?%4cxKOF3G2$Xc;=G
+Twbi67uGLh~?yI#UzbWmmVbeqU+XvgB&3q;;-MgkT2-rr3Y1NU!_#L>pasK1jJ@2o0xmAD$*$Z7X!+U
+X%7kSsSEFR-S;}5(+$;e*}om+QaRzyyXTcvoq4%FOW(0l0#Def3d01g1iJ#D3iE7UD6&^z><dCL08_B
+P8Fd1;o(P{Y*!wv4WUD^5+*^ex;AFf>3UC{uNzu)#~T7D0t}yme6?~<CHqw#LxMG8|ILiE%O+{YV4Dh
+kamUApo=w!=#BnH()5~MqFhNL+7?R~Fclh(;Uq-(4q57oA5|((+y15vEOChz#00)o$m>Mpx4vFrlk&h
+Qw!pbwIJL+z!_MG~+pqRniTgZ5Hl0^D#Q_=`mnPZAhHZ?JKejphGWO0D+rA=*KHpj`Vm{ZypV~zT}YF
+BLffsw+S-FkxD{>ukFTexj<HSM`;;5DFCLl5KIc(CiGZI^m@W7>$$ow>MO%pjsSFmO<s%f2Z0D0z4|n
+q6Ku#|YH|V^sx=2`1R<<c??N#=zUWyv1M)<QwGUZIZ?LPB2dyd!f$5Kl7h|WmV2>e$zQk(`Q?6b(z-n
+$)C^(-K*QHM|3)UHld&`3w<>OloMFf6dH*}qdMd`KfNH`F`gTkDX-@g8*J`i+Y~*9EhG?KQ4V4Scy<@
+W+4gDTx(=K+JL!aR4nUo*SgY0BhmsF>$qw|yWTdljV@H$iJl*;3bT-m`>voa;v|+-ueQdi}x&e8Lbfe
+N9Li}LdC{R0Q#*L_UAQ-O2`Ssls+$^96{|RO-)uzmMEM%v=D7mz&$}SsY^}#YaqIOtuK1G&YL!}MsL7
+{I16U1JPaVnuLSlpn~7IB1m*3UzlDi*QToQJ<0(vy#P-Qfja=T#yPwGyyLnvLygdz?+II0<=U*GUeMS
+n|J+wW^B)bn-x-!n=FwKZgIBtB>-qVGkhO@|7Ntp45#+c?*NiJVPdsCQ(wQ@<?>HJ_a;BfFulKNsfkn
+hn8&S_V|~s1RZoE+Oc+%CVNS`@B0roN#fSLDmX8xgtAPsummFn5y=$&us&XPPnsra)K9d_Z)5B8Y+uN
+WzEl&qxV)Hm1QWf0-g0j3H=SH=%ms)i1s(^)+D%VY^lHZ{onuLFH<&+bu>$;f2Spe~b2`|85n=<Fj)b
+7ZVMy+PL-hxFS7$f(W0g6`vndMVl8)AJpIzr@T4<7Z5Etud2f&?6a18PR&<TK<f&Zp6y$vy%JYgpZxX
+k9EMQiyx`$m}x5Y>eU>ryJP9|XFa2!6yM;HSS8KSSdJC)rPkztN`Q9f}(p|IL`Kz>d>Frw}-X_wR^xI
+4nF6pA(K7x%*5&sCNb#pp5ZX5Le>;J-W<=p!G#y+-wMcguY8K{DLn2Wqp>aL1Nf57<={dggt%n<b|qq
+QVnzR=+PRCNWH|{m5-FjHGdN<hKfhezy7cLupsp@=t+_ae>BvogkJk@YK@;BBZQxOt{hvVtrq7Ru7|=
+h?$<w{)baOj9A)1Y`nVOD8dgMC7Og>qvcL3X<g#wWKzk?MsztjqVAL-9ORnY-YE)OFQlNIV<P{njjHv
+IjW=dB^)LeUEJ2z@Nw`^LLS{aksr8faV=h8O2X7Oy*Tn1`s4cjYY(m?N;bMhxM(hqre*MVi-h>`W)6!
+N(kOVS+Ad)fo^MS%OFYnpF=ge|4ZjywAUPKRkz<N2UV?oCTOKZ@a`0!}RF#>i%Z*Y~bBV81^|zb7tt!
+(=eD<Rf;WFs`RHw@P|0sF4YkEH*${rA~Pv$trZp^2D#pn*RS}Fdt7{dZow->iRbkI#E(5GCG9xV5sza
++#~mze-C<o4|?eH8wNdxqME*&(1$es-iSs!LiuY|g8{`Uy`;!^hsSNCrGMAwvMyO&hzcCl);ao*$7m3
+_197BAlJyS@NRH{g8^uq+_cZxur~{j`*ZKz|po?{#L&1=j0q|ns_3VPW(6s`2EmB@S1@?bIz3HM~Va%
+b~Ei~GEbseyN_g+;u<OV_W>oZ;ljG??8aJVvVf4Q30J+4pWIrUd}lHA{=aV{pM`Px?|#5NO_X^0bP{v
+{jbJzEebjSw#(`6ed1m1GNZhstiP(ezUKsolM#dr-}9g`qhpxjc{$tEqlg49~<-WhKe*$2=+n4At2vy
+ugd5kv7`c+&~?xQ|Zl5MYPogKR~k`C}WO)TJ1n0v{oECP%1gD6lo}b8{=3TA9;n#{81-;+U>O7ZuiD%
+H}}_T-l+3xV3hErLP)>Y15NFalT=^i^_$aY>W8ZIPaKF;!gG$+!8{%G#xJzJc=7}w{Gbd=ccjxY_%~2
+X0|XQR000O897^_9m?wif4=VrwHk<$eB>(^baA|NaUv_0~WN&gWb#iQMX<{=kV{dM5Wn*+{Z*FjJZ)`
+4bdF_2`bKBUJ;CKBB3{@_XUJA18B;BJLb;_~T-Kz0JYsqn?dU{ESxTFw)0E35QCYAZ^dtUbq%JQZs)w
+LCt%OZh`b6@A4_c>TL^*Wi&mVMVZYBo!X^`>sRB)e|wvhUQ4fA8(db=5Rgt$&pDYE@J#{j*W}TU#$~R
+cC%}TmAJuYbto6-CJU}+$^!6>n6$C<dQC*;m@IVU9nbm-`SQ|d|{6pr;EC()S@fuN<T5)OW^Z|tW}qn
+ZwT&`uQc_osxFF+axT8^*X!*o1A{OAcy)C#bnWc(LT&s@mtng<s-{>LDj&Rw<C|S?XYJxft<`jIB9l-
+WaO+RvRav(xzo_fd8S>eB(`|!mKdLNO%|+I<u-@+Vy6s-wWYtRL&eij(RSQ6X59%+yYP(OoO?>Z7y~u
+DRf6U6>U8uL&=MSoDw$7z@>fTP!xqi{qUA^$e2bVs(kA8sh%0@a@{r&Rq>!sRci`#6a%tE!r=ip8Xm(
+q28XWPImdnK(Jp0mCsOYl~8H+9~cHth!XLg_}hmmlPsH0isd9KgMzo!N`Cys0-EmAj8@a3OSSrzsArf
+PQB;UALKaJ=`eW=V%K0xi`hK{@>1=s6{ZbR&}#wQL5RdZVT+fZ|hGmYg+}Fc|%w<+b|mW55U&jHG?1S
+-L@@f>#SSc%x(bRs%&ilzXGsu8~~-1bHe#4eX^ygKG#l*zA5$Hk4-sEW~y4$xteuZvr@ZS&Z@duXJzq
+MMWaE&;a}PD96+So(*)<QW^ik74<>q&B>TxlnRQEma@cOv0w;8mTx<bls^kUXswQ|UyKU5RkFLoN*oB
+HZPfqovRA1WTgP*+Yx~919Ws$zn<8y)@;QTdw!6CG1)U7`@bA4~`bAyBdhGh;+%9r-`fY!rxq4+5*%^
+Uctn(=IgyE~gr_V#A4)iUeL4%*e%e+D!j!^J%qI8Y|J((WxvK&`}53A{Pxo0Aio$7nP%^g7|@OJodX=
+^PIroORhwleS;nz=qNTC)D_4p8C`pdzdF#mHQ1YgBB_8QJMmBbn1l1f)v+lhWJr$R5hL?d94tUI*UvR
+40EHJg{rzkM$Ci}Gx_-8yww2jZweT5(I$PXmOWtGGTGLBqnpCHyHgE8uMXg6zoE_Y;pQ5c13xvZM_-t
+uz+SwoD@9j`K)fnjxMt}E-O1GwWPqY7y4h^ps&Y9^1o5HkQv@(E>w)9NSz`lx5kE~<z>dZ2Vmx|RQ}a
+YHSLNwwvS*&f4pX{+8lKfL4}<4&N)7q@#D985RCFdl@K0LS_kf;3J6g)qghd)V^R{bb;?6vQ!u3s+jG
+nYKiqj{JtjCjPGD@B#<8HfA{7|Y-!PHJ>YI~fxeZeNG-M!&euk~kVPk=Veuv7kamz8qq+JQrzE>KEv=
+Dv><8o_^`m9Rx!4c#5`c4gHTX4S!{imXhm*bxqlp0p$59)daOlS{`28_=P}ld5v(?6!0m^P<hJOBl?J
+q9*Aem<=3QA|h8eaAM$Jmx0K}v<?~L$<fixD%}trOzUQKwBYYY$mx#0$+GM0o9D;sdhzV&O>uq1k|ea
+>FQ5PR`QGfhgbP5>W+d0*$@m+6OV3{Z@bdiKG?8DQ-hX`a`VVj3zxvO=!)TZ&#Z+eO|C|Q0L_puJZW`
+dOhi$f0Az>qe2d9oPnOFS;m{7J3jvY#KNJnydqQf=9VL3!A8LM=aCL@?=R^r2>$&^+Vo++xXHlQ?d#8
+m|ZDgYw_LOS<Hf|zYba)Br73nM{7f_sRP4PY<yfT;NGGczJfV_;-oKO#8B#ljiWs|*Iz0wc*UyR7TmH
+$_Frf328S<w(mA|6018lz4xUA=!l{#PscuKx)Vm7<G};#Ey>BXGrgl(_{DXe{^l}6R{xtysye_a$h&M
+a0)8J_)|U?G<^kh1y{FN0S%=Q7>UGRCK0nNcvho~VpSj+0*uU=@v02jRh1WaMc!vF6PDg##SAD|w=7w
+fb=KkHz#=FR5~jlQKmu)Py>(BFDvB{h#MP;Rg-jph=n9s%S^#rhnso#wTo%_aSYi_~aW0*#3Y7DKqb6
+%u1_KO)9Cf&YZLgRXbqxw7$Z55hEQ4y(<mD2V5(fqi0jc^$2V=R(T4$O-gcw1ljO_3)EAO){V#$v2v6
+SQQ#X9@k0<*Jw@vdKAL+3DAmtX?Yw%HvLOITP~Z$e>($1P3X!Zh(ll^k2C!Z}IF8f3DfBWeS42id<T1
+`QKEUncW8(ZKl}pKTSLNTT&qfBoFi+!sLBVFU{R*#St9Q*pJnd;^68xQXM<fru@L#BUGol)rj3cyBFe
+Aa*5Sa5A2&ribBFHI0a;I-kqR!N7-xMwBS)?CGWLO_NVI&^16>HcI&{2_R>8Sy3WWn)2o&_hNuJG6Sm
+zUReS}hiC(C@T?kDs*JWpGptO@d2Ipmpjs~B5k!24#eqh&=*z6xxl@4J3dV=z(@3578Iw<d?(Y<>kF1
+V2MGzrb41=dOjk-hn3rDriQKI*m45@vs!)N#cK3P<YvWJ=6!$66@%lQFeyst_HjIoBrYcvd6SUi)KMy
+Su5vRD*dx%GQRm9kJyucTJu6qd!RZ)hp>jIXyShLE;F1JQ#(e5dosB83Z{WkiQ#(eX`K|Ni*l4G3&Eb
+zkNhfeD3jP{9{4(kam)m=cP0DkALqz>`(uZB~H>*31WbpG7PC61t%M$(k)sg$E=JA0Cu*%I)C3Vo?9}
+Ur(PRhRkm7oe||ZnFoN>8@|HZNS(t5@VUn`)ZRqBIqV@|anqg47ChsqW^+UTcj`AI<f<%E+2>fz@dqG
+wCN^}~2F8vPt3sYsZHG_dy*<BLN3xe#5IJQ!Y7Ztef>U7#>FcxaUw(XZHM=^0d-ne0m2D`8_w?9aA_^
+1&6dVaUmtz!MW&9hwI2(o|H~IJl_YB(56-NaKwB?;j<-|GUu8bT#!9xqRMP6VuRL~cDSCrGD)o3%8Ri
+A2e(!^I<wJ36`@299+%t(aM&rUq}vc5>$aZv&tSZ<y&@zQ%74BvJt-~8Jah<pnkCl%q8ziXv_EJzb5y
+o5K<mN{4eh6v56Z1liAjToklxd7tO-~K-I1Y?VRfPdSL_ml6Dp(1-_17^QT+M4B>yaq;uR=4paK?7>%
+FkhsKz`sg6Oq3mGNbcD}W#;eihgq+5(|4qROx(d--6+&j8)Ts^P*j#k0UdE9q@}9so=jfJrf)W&(zdB
+T?W$kTTqb*(Jc}C`?iAgXV+1$!fpSsJF04PR{p747<@sH<D%Amso~yb6=CP&;;1hr~Q>4||T@4xwS_M
+ItS~l5g4Q!uSX&Qk1M7j^2p4+Ov*QycFd=h<=EJv9{GhK1X)NCx6;vU|c=Nq*tGnV^;KFR|1*=U1g?k
+UK7(!qGdJ<Ozs(KPw#XJ_leM}Hd8GL3%L=fcP79nA$jgQo_N_H|8U1$DdR09ziQK8OM$nptt35408aA
+ocO9qGhzVL5V|teyh|5)f-jiBs7(vUICVkL43TOki3uMaX|fHoBX+Nc?^V|u*^%43Q54OjTr?+vihFY
+tX0-r1Jei8Docerj03I{85p}^s(D@K+eD##h_>4YUpU+5k{|r;E|fL<Xua;0b2y61j`LbAS(;bQ<FQR
+ev?ips!E{i4&`*Y@Y~da=GE>d4KlhMMX#}oSu2T2Z;312an9#C7?uqpHp=Sq4#s4}@j!lcQUZq5A#va
+m+E<02YV83CAtS38a$M{J;IZ2+hCr{vj#K<0WIMBkEWXxqUlL8?bef!LT>l{CXs!_lby8O|T-E>DsBs
+Q7e{Ciqba+#$T5@(vB`@?35%MlLz`%j;`$KRQf{w8KlY~bJpx_}H`OwG6gi@3YfKLAzCJR8ZUf|Mjdp
+2!-ChfnNcM*nn-LFafhcWbKb*FffYGG}H_iu`;|qT+l`nk@8d*(M>c+kGp8GwL{gcA1Lsb1B9lAPe_d
+(dm=CVhYx8XiR8eLzkiZU?}!mYjf(mu;-fl5T!tiA>Kx~KD>c>qpe`R;}i<k8ixp>S`+YA7qv-nK!Jq
+CZ!1w*RER~y-5xwEyov1Si;iTE4;=i0c%ut>iU^wTK9T-NoZ@x#C#2<wz`Wvj>#zSfYK0$P335L?yap
+|WfZHI673+STkO2a5L0fJjEJjv^vx%Wjd|H8g7Z&jS4N&^BoWlPH=niB(G$Y#RpfsYq%aqQS)<%a`kQ
+Ss6G=A7erU{H37&)vJAoL1YeO|P3+citGRgNY#=-40Qr9cF=lzjxMrs{~AOM7PsNXJKx|7a3nW#rb8A
+pwGBfNaz^pi0(v^$dNK0PT2^oPx|5@A|%DpJH(__g4_)abwh4_Z{2$wgYfno3?~0fc%atB+{TURVHJg
+2p~?NV2?7;05F&b9(6L(Z)w+w3ZPUriJH5|d5Df92V?J`Vec-_2Zg|;?ZM8ubmOA;X?j9JANeS(_bMc
+v*xX-t#}y(%jkbR;`ldmI<nRPoI*GwBlsR1blQpQzK>5tf<~Uh%RkN+R&q!Q~nw4l}1cj%^^CY%zhbJ
+(h(Vn_R);LaQ*wO{MR#4<e>Z5W#^?2aPs2m=20|D6&5UR>EUJ-}V21_w_0nz}jG;B-VISC%5@VH<O#z
+;Ldkzw`_u>xOt<m2TSVtkAg#6#WePBmK~IB?8ij5+kYoq}>(sWhb70gnijrHEam5m6jw0^h@)hQR2!Y
+g?kaBc%=~Q021+q!!3QBLXIYdog1eIasa7$~YyfjmzLuxikr%As0vz39)7mV(HP}p1&Y~@x*W9y1$(c
+dGbi&VN(ZA@{}>g(|CmL$AW?($(F2;ix9}=BWcSkV1j_2O|iN$l2m4VQm~loELYPcGcG9|4B2Y;%R`Q
+HGpY^f<Zu$%Dl<H)eZVosT3C&|CgKz*9FFlLfR7YML?K^R_NV=$DmOF_U@zh><8y<2=t1wEJ2w;#wXd
+>Gbl6d3h|}>DR)Z+v5RH9n-s3HW0x<-pZ=>cM9=eZcJQ0U*-?BHeJ0jbnbr9h?BO1aH1EG3RuQyp&To
++~0ZKnY|<N3qbtUM`U`<tOLe$kXkdq$F9uxqMmrb&;Xb#fi?xet_`b7spDu)FAbz~Qa9*x-@hi^{|CC
+2nLV1xUei7$bhX2{ZsNt~cBU0vm>l#)OIILsJ=HYZ_gi;Ibs+MqfY?{z*&mJl=!@O5z-nOT{rO*){9|
+ZWkKV@E1&vqeeW>dvb2Q^~f)8vOCw{frcIl=c7ejV9+E=NXW0co2I_^9Oks-?#h9TMzS9*+lZo7Ml5~
+7_mqC)aKb>BU)PepqDgP+wk=Slbs@F92o*(pU%uf5V9zzmmcI39k)hif&VX6B8t5vTgi^F_R*KzMdCl
+s8mSXCqO9UmV2;}wFjVmhJwpYi`o`3V)UH*|-ff0pG@J>v~c9IwDwZju#D$rACi6*9@w;u46HA--}Cn
+L>&B+t`t(%<|__KWDoI=fZcq#d}(5*Cuy<jnC2$*HE(sB87rt;)rnl{|flYYrq|10C=ydE&TgFb>vXl
+Qmja$jO{A^Kb=0k+q$`vATD>?~fGTJ^7!ZR1}kfp_^e`>Lcwa4~E?!`pW!loDId-ctCc=+K~85@e?RB
+U;wu6hc?%XK){b9TF7jK1ewbXIhdoMoChsD9t)oiM(B8vIiY}MqjWe#R)^?3Y-Ba=7P7Ef`ChOa5JDS
+xJh{cN$bkpa7VWTF<9FCTNrABwu~BVZ-l>_mGr~RyWMI(r9aBKKU^gi|Q+@6l2|eQ&h<lfo*|iwfUjl
+)YguYO17<&wN>ZQs|kn~29&BgXPlcAPrDR~UM3>#?jLN_T$nQc9MA8-Q&5(&`6Q$<ANG?qwC-G!gT<k
+4MBYN`p=gxof*XSaB&?@l#W5fTQ7?!eJlZI0zRO0jJ%5Rooo*eTN1#U1%D?eTeFn^3!8iWu8z+@a5;)
+z~AiL)6n>k61DdAwLG9vksrwW!m180S`5XAd@N?OWf?m`Ni2JVY3gd1qZhmtplx8s{-~BFcgJI3JI=7
+2MbhsR)Shp<?I0CXiS~D;yTMdVIYk#d62jYARbeps0&q~>}(TW05Ll@(Pudu--FW;OfEhOPTGh53@PX
+5@6U9K+rW7e5fO>*I$ONIJbF`9{pX+=Ehx1)yZrIv)$8}4-qBWs>t9=;bIQ#xKD@trfAuGL8YWz^$)>
+KjtDqCy{T4(Z)f9`{E`{B>>95nGJ^~?fb@cq%@o$cfkB^T3{V2;ZhOCFBJS?h1<0?PQ4oyV)VcmW{yj
+4x5%0sw)6e7M78I^)Is^o7GnmULSTL9#yUW%O!%;fzRf8SvZcX6Fewu3>dc*w`WDR<0}Sw6FD!6p0dE
+w`tan@w_7tqKY9!zg4_768u?Hkw8~$v?3AVw=%42|QB_*{UEf5)%Q>5(4WRqPLLWhBZhE)xJlw8Zh1f
+90uia(=4~P6QX>Z8pV*tMuu)(Ix7M|08V1pG_S~lcx~e(LRE@eVsI>uJM=H@vs$Vjph3bp?AJstV75C
+Tvyl>~6M_?YL%Rnk4=MSpYHEWGVzL3+PnHu$XbVx@M~OkJ{9^@s{Cu@=@8MktEpjS&qXm+&BWP_0UqL
+KO$=4yq1;)CSiSN)iCIhUBO;Hu4Q)Nl4i|p*h9rMIL#6<OFdxY?l5O0~%ZvGryV4x-j|C=d?r1r}tkW
+9b=z)y*2=dRl5Y0F?`FdYAb3#2cN4ZKsd$Oh}g9OY^|$dkPBy@+lN&gZeCirp}pOM>usW{+OP<Ltmbk
+ok(1-b}#mhCRNE8_)?{32b<N$(Tcuapfsr!5-_fxK+vJ7O2Mh>~qmg(jB1QW5n`(K~~?Stm|8OG=oiD
+>8KUVyBh|8*^(@};w;8W$ne)l*;6;`eMsc~dI8x#4KA#R$pPyb<~(=kEXC~vPGjdz8Oi$AX~>B<Vfn7
+DFs%+)(umS!em}Bf*b(b;@C2m}ie|yAyM+FY_|L&Wl#0%ok8V5=)#6_kvDdqXE9qTuXB*#f&r8aQKwo
+H7s%q8U42IQ2Cvz|jdmMpWx2qW21}Xs9^F}Ckvr&)AWp?*%w<GBLtSDJ2rNkJM05C@U1RnH|gJ)*yO+
+aIOU=lZk(GCcBpBJ;DTGm7(L;sH>jge3juA5`i^7?1iy2-kmI6?Cx-jC8zr(vj57~VwCP6=d6dE~n1e
+^w%;i6(XYi9`Mkhbp`lz}aGf5sHqF%rvUYe8x_*C@`5X`_B2Vh!3>0*b&4x)_pss$)cU1sf$yGjexXk
+VRgg@g-Vj~aE^v6PKC;VIOt3)V?xvA15mT{EI^L&Z|Cv@XtpA?nC3Aa9gT(^OyqxcO+oKpzdymO42ib
+QN|O|h?9Pf-IJ)aC6<Z*2mC|}N92ZX+JDGCxTHz|WW2K1}oM;qd%A<0%B~9Cz$j4Th+#eH2Z013Zucm
+0xzQsve92Dp04p}sAI*Bdnf=pEWIC<W-x(Y>dh3Vs}l#~G<ECYB5!eEDku_)ts?I|p0>=BSJB#!I41D
+>_hNf`+^na9O2vNuTJ_?py_MsdPXKx2hBnFANxj?Dh%4xMB-l+x{r(&y-$2e*8ufj2j-Xc8r;Xd?dwX
+F?dSX$4V^rbb-Q{)Wm+RJ9&l*9(OaZE!kDb*D<sAVlOA_0V`MC}18mYm8#krd(#eTO^Kl5m8~u?g0Zj
+;I8dplCX=1Z#m3vy{;?DS?e%2V1r?jO@X0ul08QghGSJwc(<53q19cH`!;yc-%ZgBKT&6HYH#SUBbnN
+8CbJ84?(XuO?GQL#w$&*Tem`$0@(#|s_v8j1twF3s*MO=d!)orvBk8nAG{!#WQCwk7i;S%hb_aCnYzu
+!Wk_cw(>&(|6T+@#3aNNfpC0=BoXt>y<cVVno^@p>oX>#%Y694}Q|EX?~P9m^y&V86yFrSYf-jEn3c<
+UG?5={FDVc-$+fxOPTjB^mGTr*`20b9dp3QF?S$N`c*AcX#Pz3o&x_oXp(8g;56fx^k;#s`mr=UDGYd
+(t6kVP4*}Gwvvtl7?=xDbY;Sw_R;o>M2>&#Q=@Nmn*bQc~H)mhe%Hj-=dj`*B)KYL}QpRxaqB&hYk1j
+5elN&DalAbpxwcM?>bM0YjD)1k-v50c+OFdEPh@|hAhi~mB}F2d1ROdgqC`3tdiL5z>}zV;lBsMv%Ok
+hbH^s<XXIR9#O8dC%LGysl^H=}Aty|u!%xibL<mK9;fKC36kBpCrE$#N2+E<<eh(Zu5c6V5`7A&kKnZ
+G{^-1G7aHJ0UQ}uG1$vCWngAq8IX^oqROf69VFgL!cB`4bStiu?nGqxwz5}C%c+zZe#is;vSE8&%Rt~
+kh%J%-wbg3<j{>cY40t%1B1<Z(%pmt|X<^k!NXjUIl9H?(wXQJ{@5+}yGTHXVUElwN=<VUYO|`#se~3
+AF!tfF9@(oP=w~^#d?2dJPns18r_HOuVua0>aBxJkZS3CNG{HPvO7k{ybkidx2NK!T-LUq{$hU#xN6K
+)PU&X3gxkj3WbZQGdW#wv_M*Y(_k=buZ|}dN?Xw+b?U>E!6N?yGS^7W2;3nO+iNF+)+WvS<HD*J5+YC
+eVD~nhD=Z%<6%`!p#AEJO1i??=TJ@BIHAIr)3{>_dFn2-vRIDl*>j3#1jHAFp5xTI{ln#4S<f`>pyYI
+Y#QxRofI6mEVwsi}cjBRAb<R6KDh^OO9!ttDx4Z+Y_yA;IWAY?{siG9XMQI;TZw|o*rk-a$c`P}UhNV
+E<((HT2oA_!*&hRETBiQ7aZl#)bLK=>$q6!kz#kt_T~bCyGH;<-iZaY}J;ekp+n+{6Byqqtr!MPeBbC
+q9Wcc#LG4(Oh8rf~PRAjCTWFo1D&qXQb6<%0SlA1?sULlt>7rBRjF0gjW*o0Qw;HmLCeeU2c~Ltsad}
++y4Z^=4BHlW03{OF`qZ7yCvfZphaEz6M{yDpHmF%*DSmvITaj+#YdClkb(mQJz2et)a`>{%?_qS&nNS
+N^E4PnVHkiMN*x*{M~l*4dt!L<c+xdl)h>h3S}MGUCKc-~cmznPE>-2ABZS8YXLHEbU_6~`U>8iST2q
+84o+2!*(RuxOUPxI_mU7iC7i)3kXd0FrQLg?1h%2lrslz~G=0+)+jD=+qk-4wYJ)qGE>-?zB=wI$~_|
+iY{-os73=}Xc=&F-_MhoTYUsbX~!2OIp^?ygcI@z$MBwnRy_Av_{}x)ne;URtcgbI)90jTclk2F=81U
+($6!eFIuf1q3KoYi7!n*ayYr<3&Jg?O@O{Ys)aOk%)gjRP;imjVV{5i0zDCjS8AI;FW#KSbVHdB8>FZ
+El?5G#jsRlmxbABahilDeH5JZk(_kTeoRJND%$FF9STRrGDxHKtirxMm_{`y*o+<jdOTe$z~Bp4sB_<
+|11HOo6DhD1k(91Tg4&&rG72-Ip@&gXkLXkz`(<xwP7fs_48m~mk&xH3XGf+?j7UVv4hNPrnK|2T@aV
+R>q@I+%5-rntl(_~h$dRZPM-5h+Zi$+H+~iCXV5RP|rXXPgF<PP50rdE(m-mbDVrV1^j7TW5c4YdwY3
+hE3_8N{#=_^yJF2kZ(Xcb#J(A-7|4~r^iIKktFQw>_KuHBgm?a47>-7rC!>>XDW<9Mv1Yc&ZpT2i|Ss
+v7J&kTLCmV$hTQ-~IMD`RVv)lIV<KaOfFq^dCB!OTxGo_4-JNp!rL1+arMcU1W*HeX$4D&fcPiQ=eKF
+t<EKK;DJ)sz5~$~-<Uezr4Yw-fS{VEy+ip{!FjMLqsENF)f00Q(}bjf`7_t3eE;s<*{dr|5^#W#EfPh
+hdb4HyNyso3?6L(<5-i|}nHxkrxN1!&_*b`HdIGh;kVIApm!;S^Q6bvm;PB{@D7V?BA$1>G=3Q(;&l>
+>+5gYnePseT?7yI!S6f2HUsS-al;~G?55&$yTF66(RvWFLAFi>rbe8~H3{K^XSTvEc!$BH0f&0tnIoZ
+!o*8K6S{Nn;^W1m{sxBiso<P26NGn5%MUxUBxLi0uGkO4#C~c`YQGf%F>|n<^A~?0D!N)#HU>In{6(+
+y`}Ez>1KFrR%FtnT(NegCR(DlbcLmQ-j@tAX65-h5>K`p|yj;8Z+c0F%#*>wMa-ZLQv;@%qCmi<e_+j
+eO-=ghfjp_OMNxuYoqFEF`Xg{w#bI|3AsvYQ1d4Uw|^j<-hU2=7^X@avSLd-aQS`f>NK*04r}q?=rQ;
+amtK=7lrHWYyZG{X#*eOU?PhOs2!F6|Z_(c4Tl$%3u{0Ye#Q3{75c<Vk4=4M0OA%ci3ai0S6k3CyppX
+V`W!#87n1sgBE$zwF1ry^jisMlJ?hF#)bp&mZ#kf^165O!00ng@qE>z+~n`HxFo)WD?tF-P!RkoN6`k
+);RGk~W{qEXTTYHiN&BxjH-V@UW`UiUzd52Z-}Yz^X-j|4^_mjl9*{L;0#@GT<mK51r{WX~2m6pZbIi
+M0gUCYr7eO&IPOOLOV01BOGzx%g|eSNt9W!QF$_vF)Jjg^oNF#O@o+bZ-Rj2m96N?o@~Ll))JD!vhoJ
+9a6E=;hHISuTQ--k6UVwyjIPk2C<`Ce<IX&>Jr=|Ls?;v_P_b$)n#&iAc}BP-#!>}kJm+xD872osZOP
+QjX?@~O#00ihT*SCESfSy_FDNtjyfvNYZJe4Mt=rg?xR0Wpr(Ig;4L@$6Tf@NKpVUoz9q$p7930;dCj
+#JLK-Eh3auOKP8RM^b73grj|BatZ?y5MQlC4g4i;xmrMq`4kc{v{0d}Z_x8;l+Uo#{<*^0wuSt*dZ1i
+Hl}=7gAbgmf9mo~}`#I!f%MY%Kzq9DMrl{@o9=Kc0QKJb(Xg_U_}`Kb(CyKquS)JiYX6HUgTIXB3%6?
+m|LV^3IaRP*5JPGEs2SVSFC<MKciUydYpmiLNuuZooRu{}w%@hku%kl2Q6+;5_3-r7aMcZan(w|73@M
+{TWLGfiPlMNWb7>5=Ug~xTEL>en$6A4eO`FciFv3Ny&N?n7j<EvO?Oq5uA1#L|`LIbH$UF4ay`Ug=<N
+2)c{lJ7!6V8jVOW5ZeM&LuCs`34OAuA?2N4$b0FE<2LYUMp_0GR&4UxuhyWf;`FE>twC2v=Cjk_le*)
+W^<vG@!Di*p7f?hlh9xFHqB}21Nln4^<i(CI7$i9r)Vh1}aT<Y78J8WtgHc8mKVcXlOHf>4?=62*gFm
+Qws!R>p$cA)2<@UVzu5ZHFcVH*@5geGP}1udcz8h|K142it;sB<H|*jlg>9wTU!qG{!17YvON)^42Ta
+Q^dp(PBoNs*aA+=f6uoV=f%-Uw+u*Vy8FVy4(SBpI{!+SPp564)F?K7zmKYk46XBv@g|4qku*qp~ilu
+LC9PtJGRQ{^ou>XOmW~faFa=Zw_ik#(JQVVrjyaBW<6pZ5W=q=kH^e+&DP`IW4Ejk$mmT+W$F?Ykh-W
++b4pdKup~%~-d>U|Z9Hag%&eT4%wPtKTQqN|({|gYI=X#4`RV!34=9<s^R`rKGmglyZ#1!`TWlsH9u<
+k~_sJDoVH}38HJ*^D(OwxrV3>U;H%P33jS{n^I2a>hNkB%9+^5#+k15+R0FD^3uJhq03EyX1{U!qYrU
+7U!MfAHmPU6vV={~5bsh?m>ThJ+cGC56GLM#U00gKp(Vn;>=af@1Sv?<M8N+e;?#p81IFhhKYssJ()#
+A2~8!pl}g4F|KwBDFNprH-9<k4QZ>FD76B80-UCg*#!`+UCt`=@hJ3sm@BF{Dz4Ea8V6YkynkF8n2|-
+QFO__z=WdlH(Co8WwKQkWT8Er2}5o*s^<Iz6KyDK-CajY*2dV{gD1^_)O|F*H(i10;p1*<TSal<`twy
+rm<LTOJGIiG8{#jFWrx5;_eDd{utGf>vJnoA!-*qze|)8RNUse=nCmb9k4pG{@}nPf_Iq<nUzwHi@;q
+WF5?03HQR1OS43Aomz1)rHc0{X#d^MEdUOamdQvosLfPDAE+11FWBZEn#53xg!`{@xF^M}g^2UA_WP{
+g=r`(6gg#3Z-VP&}X=t1Lo}k)ygi=wQn%w8Y6=@eumCWRC~#vFsUe;u&$_v3_zA(Hm1kmS=_Z<w=_ye
+#i7fmNnS=UyyD@uzx8kvfH*5har5CtepOf&g|RFwtG`gl|?+Ab7%3>Jav<`jDa)eSEn$Zx-{shgHAY5
+gHGZhy(Vom35buJdx2(-eV8K~b{M{v<=0PMcp|@k;_?`hLT@$JbmZ45Z2XH%*wy<b$V7x<&TCDBcO#G
+E*K!2!GQGs4Q%nVW;1$eM%7q~C`o(NJ-p4#o=)Ij%U~fK`%>vbPrJ4<h`rTZzi_AU!n(;Zm>3KfK3z*
+3(vC(yta}vj$YB0$zs%d+^90UfBN=$Mk&lVz~VQFWo$xM%9+SPo1tG48NM|a?SzTiQ7KO6OzR(@tPyw
+cjK$dwr&F*iXQp4e&m0>Z}-qkEVR&XnE>$c8a`m+8s6&QI_$4qo))vne+O%k9a_NyCUp^WJuJm(4h<m
+|}kW&8mT;Ne}~NPuC(wa9KqKI^Ak#JKojS?tWRDg9QJ29h-ks<5rj!tC4KzI%3-Z7>z>VBZ86P>RBud
+?gYnW_^xwmhx<c(|I+K_%$=C7q%nHXs3XVg@GEG7Iw1qEjv1utf)hcm7rh$9?{tW(4RSKx{Gn^JK_LD
+b;U|1ap2iqBTl%Ztz~BzrnDqC7CWuD534V{e(HJFN>7M~C!7l_QUk4i?LfAI=%Wvi&B>L^`FTYuUozO
+J6GT7WfSNnu>aiFI9;!%a(FSs?4(D~dFQJ~{X`|gGZsj)p;Sl=1s&+D>iZ#d<K0*R0Zn1CjJ!LB<LS5
+SBC<s8rSM`CU&56EyJmvh}MG_%3F#B!h^QXT@v5{gHKA}kt^iVT(W5qC#RqI*964z$$d&O^?f?TAc;X
+u4C<G&FGt6?Z=6(#jo38HO);Bc;vpPe*WILh;Xr@;>%80WMCTX&j`weS(9Id?3Ntew3|6!>i~4eASbI
+2{@iLR2D$$bek$&I;hQmjZCpNk@je~$B6zDA;89cbkHW}7bi&gcN`6a;1Z^+1Mr9r`_(zTP~|v!)_Z?
+r>?|EPS6$fxFPq^XCy?5=;j;_Clp(fT_Yb_nE_^M$D~kV*zt8USpZY?(-~8sq@Eh&iDlooes^22yUj<
+Bk-LKbMdvz$Q#JEtS6OaDQ1JAw5i-FE*jqpg=QKkl|zAu#yQnhc13mootGW<@4nbheq3lrX#qBUlPhE
+aES9iV}37}>qfc6CTCsap@ZANyKCr}J2<J9Ro7l;(cHR|`IlH$8?kehpXL`9i~x!ut`#q4(?8^vasH2
+jV>*us<-NoeY;UH;?Zp-`CB;=%>OwOzn%F;z%@vFyuC*0}oZ#^(!W>X&ER(1A}gpIh7@y`zSI%w4KiA
+cG1r6L<I9snfMu7ayZ6>WJegy$4WyJ!s6@?C!pXi;gZntJ$TX{q`QJ(FxL{(V{P0>WD0?UQCBN0;GN$
+U<Qo2GN7aCkbEuaJ%iYqVMuZ4I10gi$Rf|blO0pk5F`S*D;&J(976P0-)YxJyNdF_7>iWRZT*h`7zQ+
+Xi|DQem1^01}DlgguH42TBG+wNKe|sO;H-Dh=fSE}LB`K=12F$?J>DGs!R6oQ+V=2_{U2JcFJ1wLrg%
+A)4ZRHA@IyJzrAE(RH5j2VC!3<BK#6)8G_2pk4pEkq}6q9->6){O7LB2-;!C2`AbHcdfu5yN#CKt%v(
+bg(u3Vq<1&Fv;}W2%6n*NPA1aZ8jfWpy?^zPeh^)Tw4>K<%1liuIkao&wcL<nn4f4MZp^@oQk1mw#!?
+jxpU(^(UUn+2;(4H@Wr9zWeSwH%uo)C>?9Ms_PX<Y?ys{F!3I4bd_bDWOMMt*%d~m>V_HzA6dcCDSb$
+<+uBvYaGHGkjGsVhZ?|?L*goVIa4Ma$K13&np7fKD9T<-T!6)>g0+Yc3eWzP;<(QzNBo{cL3UL@y#PU
+cR7^y{!eW*`vxNr1Nozg?)6)>&|<D2f4IUUy+bEi5=<U7B(`yFCCXkNM^_<nNfy!&e^9^2?)bemAdk9
+{F3Zm!8Uvg27a*<TCFbj7@%7T?882lOvJTAmC*Nex2<S+G16Koa3Rbzd=KD+$rXJ9(v@t@D-HL1{QY*
+7w+O>b=~~FOi4kRA_5BjTTl>ze!GDJZ0m@Q=&R)LK)Bxy`1a$x4(Vy?;4?r;JS(RKgny+=!U9tx%{)6
+Z!Z{te||bXIXvc&OI<t|MG3*n9TjOeo@4BF!-=k(G)dLy9A%lp`4CK-;A@l7*_CQ!_MG4MH)x<mBf#K
+$s)JWl54@Ok@a2^nf)`Er(3_<7E0|xC&+GpJP)h>@6aWAK2ml;P_EuiZNww<<000>v001EX003}la4%
+nWWo~3|axZmqY;0*_GcRR$V`Xr3X>V?GE^v9hSzT`%yAgfYuOJi{kqbo$dS3$JIzX<XGyxnZu<Z76P3
+=+=>s@k7awQ8F?QieQko&1!Tkb;x#FCce%<#<c%nWy9bjG4+Q@Fy2C}J|pwQ-EEtxgLkBL90d+Tgrd&
+f`bE6?SIj(=5|___lK{kK$Ac<;un1Rjji-6;9j=o-l41PD<rEYLARYZ`dE)3buTTMed|lb~GBrDYuq=
+ySw|fG)9|AHF!B6G59wgk7<!8pR>Y>gsqRv?WARyPKs2_VAhDH=OC>m^&i|QskW2w*^zqiPhTPPm)5D
+bw6b~7(v3Du;0()RPAU!(G$_Vd4q|EziP(Twq>?U*CRU`IDNUHNOjrvZ2paGoj?Qq9UD2FspfYFHku<
+)rb9Q0J?1D|&QZJj@jYx`EgjEfNZ`fDZMlR#W6p_jclWPl+P)#rbf=PM9qKHt6qA8o)XeFi$|6W$;-H
+Lw|!a5IN1?95<R<kU4hdZ|8djUaabu769Nbhg2?HNcGW*ANw12o}p^|(^n1+xv{{{g?!z%G)j)%9Q)-
+f~I7wi62Hu~--<H!=pi*oMp0GK@h*A+ut!R!YQ(_fW_i{d7D_ncInmIOa4)I<EF=pLJ8fbm~vcl>LR9
+t!;X$$OXhqWs8UAvUX6vfVQW#kz1*F8qpkZI(=3<{UTzWh_klJ3#T*gWDI+OMd;c!$5Gh#LMsOZ`R?w
+Ri|)?5$T}TALnuv+R%Zg)1K3K5ryMYbksZ%-p@6ew^3M3f_1*}Z1G%0u*qb>VK*cjy2d-%;XX^seKq_
+eqc<k1|{lJb1P#17GY;-MC>5j9}qVn%DVAv9bYS^{ln?9QV!Jlr0Ga;CoWH2008Gn*lkug<dYhjq);D
+IqxKoDD^3XzCp=Jz?zx#1Zd(mA_p2V+H+bBAv6bLM2%{NX=v!XRV)Hmes9L!(RT4I?W&G!<De1pQ%xy
+5Iq1r9dWOVnu0oR>1<Zxz)<AEL0*)dPHd<Bm*4h(3%%?MFi2IHa`ST@?S>PXgDn}G6t_yn3jN2rt%xR
+uxzs6Wrn;kmy}5wiZ5%aO_%mlXN!mHOs%b3?6}&B<lNW*{t{2pIwDofhg;z+@J;Xm1u@6JLT(k?fr4|
+hM8M+ew+5IExb9$(4v@~#jFyTPY=~1csk|1Pjw8K;u1fPN?CxYHbm3MG=>04rK{i0t070qtaOe{VWXu
+i3*UpRUC#<0BJcb0uiXVk5CHlZ-I*tot!+~9J7ZasX;pHbBWST;~1OsfX0nItY<op3E$fkBn>woV){`
+3IbO2V3Oa$C#T?>$dHJ<QtYt+nZ{j!E;!l${Z(T_ijPFep<bjabM%f{<_r;e@3(tPo}|%n5@7SpZONL
+=z2hp>$aqVMWBab3ERG0f>fzBW=;UQtgD1&g%ej1$mgX>e?~vxCf%vrvI01mduLI)`J`L`ftRclV&D8
+CQVsS1=%#{;Il940|)VSD(wz5D{*KRJ?!2VJWY>mx%hc=bG!U{zgm77NZ89PcgMN~ctO7}^O-3iK@%R
+EhF<GkqoLg};5Gc8ruqQ6tY7sag|abuh3=9Fp%M|smd5Z6{G!B4KX=fstp&`FN&JBBYYpcSZ2mh>i@-
+7U*C~6sDumrZ*wz)y!D#%8WXai9?qL>2tyFp8Ua;X8H#XRCYF57ikQpLkXE-cYW-{d_)WHxLIm#nIdM
+xNk6lqY}pB%n|Sf3q8ZkYzkMK5=2?bf2A|55<xsAQGMfZZ!N>zTM$k4hiZ*|_j}%M=KZ5Fk{G9NT)BV
+@c?<VE8HhP}~3`)xuDdpB*6aKRV@ocPm3heixn~`Kpv!Q@1aL2NTvkf`MDdlj*ora5$)PP=Q=S0fie$
+G4E6N-l}73fd00;S>AqMM9bUTpSK8s({Q}GI##m0HFiwXSHG5v?_Yc8|A`5?uo1Q+|2|z^HGu*M7OL{
+{lB03qQEw3+RH<JW*j<K4(1x{)8ds_ZJTLVhzg4mRClJ@?)ZIV>Q7Y^h(66-1{B@zkTdip(LtVmFpKk
+_O;JYHbMM%1@vLoY<q3kIXq#jTUBfbX?Tsfe0b%dHe!_@OCeU_F{HYD~dY-rj5g|+Y;`1~$^rQD&vUI
+#Zo3W3b-u2=7=``2nCw}tWiA$_U9_dryT5e4?EkQ#!bApmZ^|M1Q^JJL$9+W?c>F%^Qu+J*tGUj!7`i
+BR$L@lBsi)!<+#e*~mz+-=4as%*=v&Tzfw1F#G^O&u9e1J4D$vb?4lstf&r1fpB)3iT+GNvjo}vR(oX
+tLmx@Vj=eHkzKS&FhOf%9(dr8ooIOI65$V>9KnQd{?c_3y7g4_(H(u_0%pMtX@a`T9vE+JXZ~uJ`rgv
+e2bRi5Pt+4%VJf!C5n?0P1)N)`@1R!q*I1SrehBtn5|iRKqOiZo<#TwpuZwH*rvn$too!XXrb2DOw^$
+adw+;dTTZ!t%q`aKDrdi$$AUAIURA_y0wDmp^jbX6{{&H-OP9`z9-G>KA{7&-p!B5+3Xs==bf%p$94@
+i!hsMO-ovkr#vLIz>#Mq6K->V;3M{hZv8wQW5~pr-=bmzcRZy}}GPl;e(rE+ktY9rPZC6v0m_Wh=pSP
+f!V|a&>9J=}5V<9=dD<2X(4+(7fwj6Ch!=56m(^D3zBd@AT5F2mNx=G>GT{ziZ`*16tdzv^tTdlgnDe
+%qswgWWePRIt@r#n3W6YV!(gxRE~bLSHa}hc>4tLEo6=$@4}GB>i`&Xx1ZnR?UOh-arQS5D|*W|yfWL
+-DBdscCEZwY-(l?NT#|t2F0|Vv^Ji<Z5((Yr^rWV)Rny`hTtOAuXuU(BOMOIDEBa!zvH_a+pI?4X+`E
+r4L=IayotGUsasxHxZ96bT_kW#zn4MpMzhQ5&K}fO4dW-pwny<B>7f{fJ8mh#pIWhjjHr7^4=N~_O{J
+`FQ3JR{O0Sr-m70Bd<`fK?_cQ^Ix40v8v<51C7>&EkT1e66kURw671;cTqy{OS#kQZnxJ5F7+UpFoD8
+r07w6q(2k^Y`zu`NOXkzK<)hBDI4`+QCfjZ>v3RmY}z(OhCM!)m{EO>4p4ZsGzD}e4N`G^~HH*>ZGqK
+`6|LiTv@JJ2$fjiJ2#_??JhjWmpS3;y|MX$x36?Qv0VqbFWnffkN8dxLO=4yI?DaJDZQ9D(Df12><$Y
+eY9dm-ot1BI>Gm?iMEx9j!z0YPQ?Q)kK8f(Yt-p7@XiTGPIcVe!5nPah9vufqjJqN`t~&+dW!K#+BMw
+p}SRP}&Hi%z%alxQm)dk-4(4Aj-l}gty<``NpFA~68gT%Je{tHk`0|XQR000O897^_9$0$oIAPN8ggC
+PI_9RL6TaA|NaUv_0~WN&gWb#iQMX<{=kW@%+?WOFWXdEHriZ`;Tb|6iYC!5|Qslh(F;K?Aia>T~S70
+C5^5IkbgsP%CmJF{Vf!cNtqv)6d?SeUQtCe955?pn?I3%bnSI{N}Y@m-&u_;kuGl$-|H&yCN?oVJnfR
+mE@s*9*xX8-?1d6l}u7$mv+gH%YDJ?g_4g(Yh+6c7TvK87nZ9?9!8^4%-3X7aUsGe&m_-eh~)k{NqNS
+0d_rIYt5Uh}SW%=&#AK3ZM|mW<oC;ZTw)2Adh``75JoWt}awBrfiFdA9PCo!kkK}8@2r{N4wQ*jslI@
+5+N^`-_2cWg9MCMw)0~{-nWE(Qy<?(!3E5D@f0Y-y{|Eo30@-DB4Wn{(mSv;=w#`Blvw_$4)P1Xalmm
+GYTHGZJlxGkdw*T=UcFYOT{ht4i($E@>m$7HzWEaqjXv<b^~G@G5C_}V+4SX%Lp1AgLZ!Ar8PvIw1p8
+fZp@Wik1s$|VO!pxshVG;gAKa|yq+LBZIH7r2;7zS*N-NycN6WaQoDIYAMO8{e{0CQ+5LGTj3;Usoxf
+*W)b6{WgiVV4BTV5=0wIGQ}awv+3FU^H;C5I$}c7<W56?pqhdLBoYB!(=@*qie{;#IDPSgyysfY@9Fp
+C4_he<F+Vzzd7cWIaJi;=xjEX(U3!F;1A-?)6HI~NkIS$P#y$`g2mxpazgm|G8c>#KDgICZKd=m#8St
+a^$g_0c!k|*D%~&lBa4yRHQxXG1CdhKR+DpLm65+Ch6PFg+fR~2dnR3b$oif#~MuDm<iSn2mL3`Luz|
+lgoEaJWrWr7)ju9A$Edxh7aIY7(0(BCxX$k+EOxt_l8f|2Ez<p{C84^9S{Xc|O<eja-_H#g-?HV)iq5
+g20&QjMRAh4)l=WAc==uwCz!<-Q?oh$+vsG)zQE;x+sEL&OV7{GYWMF4VS*vdqE8X6+@f*Mc_hf(g-Z
+N(Jv8t)f*+Q0tHOd;7Q9oRBBv?OtvHl(R!Nv{JWh_=M<X8{~vVsDl8jnm4h99fq=&LcLYWPt6{~%j^W
+xTVcqmk`B*?LmMi>p*bD7vO5)rwneoVsugm{z_HI3;M|^Xe~aY?(Ptc@c0lqBfBJCs`g!>7;_d6R^NX
+vCHy_>u{b#kc@@}f*<Jruc!_TMiJu&ur$BUFjP-JdAa-Ya8{J8O`L-YJx(deIMVKVwM8a*LrX{u6MnZ
+x%Mf;mzdPgUOIhvQ?+4#y8Cm*km-<uiQxfer~ut0IP+>#Ku5*G51Sp_{g)A4P$Z{qy{I_SY{S)gh0|^
+==h*5&E%Y*@pWl!$eE)9XV<Cf$d=%1}<#%QKpH0`DGNCA{3U|F5wQao)l@FE;7#Jl#396WcTc#o(dC6
+NNbi$ALNU+L9a|6VsWkZ(@mLIg?}8}Y9|+%*MMpP<TT261r!LsVd?$DqaX7m^RMAG7ZHP!s}Bg2J@ju
+>^w6>Nj_-vZ+-eil&@ws798X2H@~vWRBzMxn!5WU`==p!Cf-8X4b^L!-vsIB>YFYl0mv<=P%aW~i^V5
+{@lVduY(cdjYrKv&z*TgHnWuFp|5h`X>m8sqUnE(vFD&Yu_)@Vm52?vhqAJgE`_6_%^5#2!SS1X$2x@
+~}VK^0X&@$rd{0<fQ2oI<Fw|A!8uQvxRHyC{GO@`pHFLBQmoNR!?E(;bD~axei6B+qsrKGIcS(!K<ft
+Y9j-XJss=m{4H4StV&A!Sn-h3$h%HW?&el&@@05`31s3UM4(^{e1NiT-%B6GlHP8(S&gha+I2ktnzs8
+#NXF<rx0tF#~RP3<f=k`+<LY>6M+P6PPlTUO^!0OcK62|=s5ENgNdchsAiD(4Pt0JiebKS63MB`D%y<
+5-w<G^Bv~R8mg)qiY$(;-h==yi2yI_n4j&c)Ck7Y?CXi;qn7~v;q;7LmwlO&vk1=vk^25GnXJ)sFb_V
+>-F@evQ2QlN!lXb-mL)0q_o4O`=x}MZe3dGHk;I!t+I%4rA&zwz0*1^@rEQ^C;Y8oeYQ6d^DmoJn+oi
+{Zg7PUz29SZ*oC4KvabuaX4U)&z0hm!#cgo|$;gCVw!uCTkiq&@H_6~hpE+dQsaf=yf~D@Z)Tk5Z^~3
+S&+-nS6sW9W&Z|prA<R>gf6MpHSP<WOYi_DT2EBWJ%VLdh>Fx8_PV6r$X)#v?yIaZQ$p9Rp51xz<dKa
+y@C>m7bahK8k|xyY8niPLuiytvaln=*_)SY6+N!Rp`cX#fZ@>i+Pz*v1e2>*R~JN82&2mVmX};bTKx)
+H*l?vaE6m~if$e~3J|DI4F<$5ScuvMER*ol~H|&n14Di~=ZR%D^KFINejLkimKsC*)anPYJIZJDL;P2
+4q1<(9uLqOqY><3*As8Q^&_`6~OwX$Ym)@lwQTC!sse)O^6o1R3_kAXc6!<G)s8x35rMPof&(EXauaK
+<l!?1r*-7qx>mUpcTdPQylEtak)tu^^}I_xR~z!o82QjY5m4KbH5|3=-m}!~KyfQ0GRWcc7E$FuRT(I
+idHyC7v@FsQ|1S4oEnD=g2zwXgk$eztOyxj(XY7atnqJraK6bux@pISC@tR5V(??;m6_Q)U}dlCKXCw
+l{C_yfAHht>(8HfSthZn%iF^<(V<D`k?M@)9-HIA@_;RJO*hzj;pgAb+B^I^?Y%wVYg&9Zc++QX+4aw
+$#sjx9U8f1-wWg%ilYZB2zhQiJ4E}R7j<&W4-I_6|3)rgXLeD04C?JXCFr$$Rx}i;O9NSC&mx%z91mz
+hMQ|x+9c6Dp};tcEtxP~-`XZm+wD^scj4pyu#sMv)p-91+K7CRiw?oJlorxWk@<ZcE(X7Gbjx*SflN+
+QSx*SAgX1-GfdShU1Gkel5t6V)npGxRV!s;ufeVXkgc8nobbily!4e6vHS3nol}{dBEQVK8ZCv9H@lH
+&eK{?B|*ajArh9G#(r18YTuhit_=qzEeAe+t!<DqBl|v(x))P8Q(NrCv;pPUMAtXH-JHJ()s_B^ZYv3
+|7G)TTSm7$(c(4#p2^*&m~J@aTC;URE*aFXpzi{ufOSCy<MN!CyV{1<WqWOxZ-Wjl402jUs76UkG6So
+g_znkqD|tZIHo-vp{B`vXitFmtA;<q<ctIbCYF$H7Q8-ZS)YA4~SGNgq0}ef@wHk=dQfeTwsJn^-;J$
+*h#Q>DSu#lM;sm1Cd-MJe8T0IewT-RgZ_*Iz3bl*tTgSR`(yY~i7{q7}b*ChR7Id)GUcdsLwTa5vR)}
+W6twQ?U|JZSz_*bLh27JIxt1hA-7UVX#(Z5+Q_xS6q~(RD9GD$kqr7JG@f(}dcO4-tXk<4v4P0hm-^*
+><D#tGb^KdaOFbOq2Hp=XghN1vA%#2#jB$Y0|4hXZ=6=7f?$B1QY-O00;maO7>QVtG}au0{{Ss2><{e
+0001RX>c!Jc4cm4Z*nhna%^mAVlyvhX>4V1Z*z1maCwzg!H(ND5WVXw1}YYi3Y$S1AShhyC1?Wpkfca
+@DVjo}q|usPid0BycYVpXXGl@9EqgZ`0fr@V=FQA|!(nT52Sw2iZZKFBAi7=~2fVUc4i1a)J4xbtB^0
+-{5Yu<98?5d0rESuBJfSC?H+zS6`!N~USu0RBcG~=eUk9}AonMRwJ+E*14bCQ3JS=t?Els;slH42N(7
+<)fgh{P$hdxUO*RFq0^M7Ccmn2DpEz~=$Ef$p?RKv|a%Qp$olcs6-|2P=HuHwdUYlXUz`?aMg62V|Ed
+5s+^2dy^Hi4L9C(y|34I{}<lDYc0-w!;T0+I^-i8w^*C?y{G!^E}v#7L*PJv%miNZA@;7GX<hbsoE?J
+sOji$kQ7w2O|06JQv}uvUHy->v)QP@qWmq{afhJqh|JM~C1L0D(0i^eNMT9g7P8wF+~wc~BF6$%0gWK
+sRe1GAmaKy7rj|tJru;S-DMj@v%Fm8<FJqV~5u!m5|JHF;W6X6GBIE~71d-v1^3~C=n~Mq-C@r4adb`
+;q?06x=0tf}-$of3|>ZDJPvhdG7U<A8){WSi;>KKOkrY=SfvtNUMekR!?S}_I<_6BPbtl4bfC3~IxK*
+Yay2)t>86Iyu<pQQ|R{FW4UJ7J+6RPCJun)bs19WvMwQ^<*;!6IzD(WX3axpD>fJ5ldqkJ{%q2SkLQ>
+_ztTEftSX77=}a_&47k7dtKX(GzZSzXerM`6F9&gLI<j#ua4RHQezzq3Psaf6xjSlD`e!z(dv~gP#Xf
+ep!yrWk~|i&?2o6<`6G@h_#Oa@3-&Y`s6z9B9$Am;9X4eK*OIW_;FlQQ3t|tzj~f_`Dvu7yhE&QoOnI
+ff&i$CD1Ajmj-&A~`R;|3P$Ar)3Ju<j)y_b%@eavI?6q~v`CKjsbmNC=yrHsr3eRDw?Y$HiNAcNha%r
+smVD?T)uyBWERhF*TSN4nfqEfhmY{Jf`Uh~g*-DTb_kA4A@8B`60+tF!6W3zav_$M^L^_Uj(AIT%r&h
+M=#akrRp5x_bVOmcu<;0@iz_uNo()Vk}r6P1v{?VpDB2g%`sE8M=vMUV@Hg<wxi)g$gk(~GR8fzY^lP
+WO8KIN`Ncj&A*sZX_VRaJv3D9NjDHk!GNi84+UNpu6L8z${;#z$f1UP)h>@6aWAK2ml;P_Ev#JWMowq
+001aW001HY003}la4%nWWo~3|axZmqY;0*_GcRy&Z)|O0ZeeF-axQRrwLJZA+eWg#>#x|Sps<vuFile
+2>ocGNdA_s_nxsLT-r<l7sFk#`wx&oOm$a-N`oF*V*iVwOo!*^+*b;Ylc6PpJc9>0F?L?k$+NP~lo(s
+L(S9K%g(o{v;sGPr#M)vutDhjn~bX6MnXw#Ofrm716ps22{ba^!zZ4h>rM{6AT4{D{#ra1m$)cT?-8>
+vfG+xe@iEP47Kpt==5e*F0U!jHU%kr_R^>^{WV`SO^X)mH74g{f{=YM)>*8437#Q>`RE{);SH^{TF`d
+PdLR%G(dBsgKd4_jPr9yd<E%l-Ff-C<mUKc8}22n#X?m@TRk3Y7yGY)wR4*9v!1^J0lr9%68Qad}`~W
+&`TJpjdBa%*{_u@?V?)!qgAE}<fX4~RkN+u#?EOQU1WR2R(NJQ(&Y$1*UIGErrGCB3j;;Gu10DE@bD!
+b1!UY9A(_L2(J0SlQGiIz#iudy=B+H@VD)$=#zeH}JE4^$L|i)lJQ|HaieROcrR+*IZ{VY<CwX4V9Z2
+eQG`hTelmGPUZ-4#y!=Eo<F0*uetpJiP)R=iNUMUcW-UB$W@egE<&-`~|iu^{^1_;xclCO0g&jJcI>b
+7x@aO=G^=1|pZKTXvDE8kY8LBz)>1EWXcWl;!{2?2|6zL51*y92E-qS;DhPFt+SQVF2Vjb5v@Xet<i@
+2C|!rrk{F#sD;YW@e(QX+~SFRb3o`ZV`)3CO&R82%HhEVQ4UDnz~(qx-(QjB^%{TKvk?wN>tV;V3&9#
+U|kr%vkg2(dEm#oY{KJ4?^M->5yW~^RFXb?<iRi-1y3uJ%x3uuc)^U7g|~!bgpp-Yt*(a#Ox4yamCN-
+SWZn$m9)xIcC@{G<9EscT7)xG%%nM;}D3Qlg3t2P=*Lo>s8k$CyD<!IpfWZuu=z_<Qv}|f#uv+8VXgm
+Pj$y=j;Qv=N1DhaY@53vTegrS_2oJYt?tOZ*mG!~s%_rt+MZS)mSSQWsJn7gZM)#Mdhe4bKhFpqHLNu
+h33Atr$J6clDpO6k7dpc|ksNDH9jbSj#5U#JK;K{qMz6hXiR`4KeU$)5#^zOg%b0}oZbhp{0|>e&!C1
+5L>}=(Q5~d`-AAH3pO%AQ`c-HX;}XQvD3!piNq}rUAPSa|P?W5oSxKNSCXkT`O8`&4VuC8yFOvEzyeX
+bg6gkE*qh}{|TPX<A@;(NKVFf2Am}_IB=eXy^$SC?X4KY`EoeSLDp-a9eyO=WyaGHd6x?Ua2En$79ug
+QEnqWRtBuIvmu!oM5G|{ECkv4NdP3TV#GVQ3fE|L<b7tOnOn)zGB^wo4SphZ<rBS+t!Y(9H0#s!UmYC
+MQT&*fPA~N&C_ZQ;D|9<<Y8OT$!B~~z(ge=zr<pbOZFjpG&1QcDBMmPFKWdsStq*g#DHDj((;D!R=k7
+O9^l4b?Tq0O!5AxL-v6eL-44CYReiPsx(tXgr<W=q1il_1x=-BNAkjRwOzb1scw$)ZtpiR4*9xFDCHY
+`Ai<AgL%rD7RQxikyS>kR+l^eWtZNp_P7s00JToTUGYYfo_hSp%v{V@+QcJhj-AH$cu%;fe5`=AgSRC
+sZ=WYgkf{sD-mJX1#XYfk(zLjmysMiDfBg1>*cQ?#4a?Th}r2e$qli?^C8Bfy9rw>o&nyqtxM4S*naR
+Hz*`^-SrG|m>>3P?6&MKaa}JR(Yjh&{kHn=$XLC?u*EYyyL^>R929eCQBJg{VDP0>jr0!VrF8UcxoJ`
+|MpT;&a`Apj0d6pH`0d%#qf<l&LK0ooZE%qQ$AV#QDq!}J@2uVm1O2t+dNY&J`G{6R+Bl^TjKsfswXr
+OA?dmx8Uae#4?aqw^Bp2r(^T+B4ch2A(2jzEZnI|B@T#`vzR8u6|wRah6Foo3Agc9VD@(~a7h$uuT_N
+c|~cu#-pD8uF`-66O>sq=iNT#$pqIn!pB(^TE=m{+n3`M~{~b9y2gMg@ET}s~>^zM|>;yY!<+mTp1T;
+qe55@mw4AFY|U_gNMelvA%^S?WZXgvQw=K7StG#gd5;OPS50<^Ov_n*mUU$V3F=sqp?v{n44e>c%UJx
+ku-tSD_SGKUl0Vy@*>kZ)MPh-`vYQ#OS;inPl*vWL#G^z=BU0XyW!5z&BFWQ`9YHXMWshbezK9Cr$R;
+T4FnRpgInfbCH?b{b+q9E=v`E(Tp?G=UVT~90Ta%<U6enqu7&csr?uQP40Fidn4ZBh2I3S<LbFP(v9C
+=N!Udh!~L|HA_G2;vwxOS3~2y;VXb#(i4pwR+2gmzU_OE|$%po^wFPM2#9KC-2!6-%KD-Lp~GHv&cf$
+#xfGpz(Pq%3#%?(XyDF2x4Z=Y)@wafcc{kejkmHgv?20QUo1tL!}(Q?LbWjfR5O!NA#YgHI7ce1(9rZ
+;9ytQOAYo2IAA@Afv7+i)=0tGs1OBAS9^*NYPq@w{t=j<;T`YCpdr#pLz1%H<un|m|6RLVf^>jD^gv*
+I1X842ytUS5C2gn&PYWfjGh{X4iWv(ohwSmz)_sJHf8+<ai;LXJ=72zXO3XxCf}Jt~d>bHXVUX-!LD*
+P&VCr^X=#_^3(_R1mchXi@MIzo`AEG#Bz1E}vg`fqhaqxY5!lCg7^6;%+cFs}L!eygrNia*rW8w9}Sm
+a*a${pC>^Yf91_}zEkxta-xVk}3VXY=RNWI9f?OI&?za`wZkk7qM+hSGZe^yyVqU4cJaRlBEW|H|T>)
+Ww$rILd8R4Q*bia^lv~(ZcZak=GOYz!|u;$Nqs$gAzMUiBJwvZj<K|ql(Qei2MB6*E1(Qb6heLLvj)M
+u~d7r4qyu^ppB2SK0tPSormcnR<-$X#W^s48bsw0RfW;)LU0r+Zq}qxtV13G3_7b#Bu(UAB1jda?X~8
+l+2#fbW`l-ucpzOo-~hUhT%;Uv4=A8&OXY|e)&=9!WcF>u5_P-EG0x{tH?pvgmJuB064)&lZZi=+F!=
+9fVaQw8>Pam%hSeo{+y<}$_aZ`#zKa;Gj4&(Jfw*Q-<KxaK{pI?9FCQnNj4*Y60)KpR4q(63@+>8qF|
+g?I-VPs-6u$``RYu0p#u;hhHw!`tdGun@IRu1m5K_2uFqVGf@0g|aAbNOl?KsqjY!<vDEsQI}a@BC;V
+a+qFjYH7Xk3o))`(sICc@*ae?R*jGr7P<%5{iJ`+RGB5?5q(GujxRLFsO3v(<-Y%Ye?kL=W=~Y|3=p~
+*&su${-D<1p=h7@&*wOh?GPNX>E}`1N%K?IDN#UHg_i{!wY}OVsrwc<r{I)F2pPfmhoB?4N5{Ka1S_r
+KAP{)aRJC5&n9&6bp-SX*1Z@~y>jh{w(b-qV$tWg6nfNPKP#|P|`Tn)5=D@acg}Q13Zp@HVvj=Re72a
+K~1Ba6I*Iy-!?cKqcE(@l2QraaqGh#|aS4<796`Z>WH~~a^A8_mV$|#+4a>GM!KWmnpoK0fofBd*x3J
+iveO=HLS#*+JLw{NgEh-G4o2q9`@6+?!tA@`sPklIlYhtg40MnzVGwE3W65R);v+28_QKG_udY8&78L
+FBh=8%{|4{H2Oc_=GDz8_bSSRSR`m;ew;})<2xNV+W8{&dYnU*_eTuIA;#dgjFMy!@KPF4+`sVf7EcJ
+(8v5kN?ZTgvBo$~CKz*i3XjPI6Zt^kAz*=L>yS)GHN)1pnm_(5P9d3IT`v}y+t|~A_78@x;|g}Fz5)z
+<)zZbqX9l43?bBl6A>GJYlQ!e=JE1w%KfpD1>^^10z?B#wtO3P3@54;1r6^@c?2ejKFwnn>pN!vCT+=
+ptwbC06pvQ?C4jST|$dE@=n?#?dr<NyGL~BmKY_KqP4}qLY4?&mT^G^2xm9tLn<7$mF@$J`lphcGPvx
+R+nny+Z$hn}tKx+u~`yS9tr9op+wumTTXdi?wKvvWrhDdtd&v}>^<*>L`x)XF1`q#G-cbsfb>eEUbss
+kCXm)zD2uxJ7lEbHXyZ;QU@8NTV03hPmofRXfq{h4?66{BhbB(LS6Zz3cX<^x!!_E;H%CJRv>z$({o>
+aUc3I`@_Z317o>74e~$gMtme5ijI+>I;22&hHss?bV*^G6<X{L!dsJNbS1_2KoFR{jBcIK{*&BNsW}z
+(nZK<{GZOF6xS%^MzvN0H_m2G(sSrIvAJvaAL1xJ!t}8|UawnVB7E(NjP%*}>_EB+(!6d;6j@yhZC3)
+5{x<Kf8j36q6qx3YHt2ve$3i^CBH|pT@mhYyhIMqRfOT5a}gazit$?E%6KbcN`ZeTK-^&wYt!cm+gP?
+R=5AYtw)Uvf52@K27|pRIWqjFL}lF6fz6TKM$fknd9ObRlaDQqD00I;pQiS!h45OT#O+o<6GvC&7Y9w
+2W@K;)FO{6M*6kXM+se#a3AE(o{bWDLP2gmzkfT_%OJEeyM;qN6)1sr2g-!#@ZaciI0dXi!?~0I-87h
+NVxW0Bvwjhsr~EHRMz2?NL(sC3^KMwDRLcz6ZkiMkTapAB9YKGi?WM0iwiUG)hR$MZqa8CDK4J%qe_-
+rSK>P%s&8=_kT<#s0?Xm+f)sP`ZNjN4LMOd*>=C<atvAP$rBM`IrkSzaMHB+rUzSI%W7^=zqZDDv7X~
+&ksy5*YG3Kbv^h4rf(~!86Wr#B9J7ap@Ur6zy9SAs(=cC_ejNxQ%p1arXn|}aiXAc#7+)q;<hX+_bir
+#7HHhpjf*Ez*cio1(XgWbEPwq$i-PM|o50T7i=*HxqL<Veu@2EaE2gA(Sx8yxTSU64gBd^mhU@?V!A0
+dx(kH_krX@+}+!wk0sCERY+8z<?4!j7Y6ecC(#K0E_V6u{io$cnX*}@#J<NwlElF*!CoG@$<WPuP#0Y
+OH1v|!%~U0B=T<DC_P*N>{g|tr?~q)ebuR@3cJms&-Ml;CUe%g2Z)Um@K~>b)|PoZlUN5J8I|B>?eGb
+<{l$W^ZOD+ED6S?oph5e_HlnR7@$t<ivI+l0u^aHigL;2#wpIBYgF&(+ZRn53LL9b?7YggtlDqRB&Jf
+$G>MlS2Ywj<Q2RJnvhL!z+#rigT|F`Gd?*cUG@hdykl{l1n4Zk@s=_&V^?yI<cjoa-aZ9z8GR8r<4#0
+Hy_#(gknH(EMfusUGQT)-1J13YEMiRUShNZ^3>7@}L5;sU-6;UE~MLgoBp-O@c^a_^T!aoBk)jk_^$F
+;BleAhX+r;D*G>wyLh`%9tk<KfAs0wE?{%Hj#NSs$82mV0qHkI!bVBvO6}Sr}Erlk@#JEAMVD&Wp*eR
+SQ80K+^)8)J79n09vHH(H7Jw^_k}s8YZ!qO+B*>4d~x)|8Nfr#go}=%JRT7o@XjIhdPuYt!Mi?u8r!~
+SgYR<q(iNN3c$(vAG#o3W@1t|wM{)CkgW=|Uc4x2;diOKVJlyXB+uluu*@G@Bdm-%vc9LiYse)hDcjW
+g1ag6|gkaplA|HG8Z3tLE~6w&Gf2ZIbAbL6}?d(tZ)^`;DZK?gOy<+@~B0%L{5_G9$u9OF8e_)5>6nA
+_KzCW%S$6OubM?1}!L=P#bk#HB4y|0(+>`zAh)Ke_=|(;B=cdhzv(^gQ+w6r8~iuRe|wzfRqrbC4x&P
+js)O^eCo{D+^BSoEg8X(vubkl14L9BwaRPl{cd9LvrFvn6>xaIy+fk^Yt(ISGl1pcI$%NwXcH$(;Nx2
+2;Rk3t*&hx@A^=43SQiuQzhh0rPtI@=kDuE)f}q&np*G3AnW)FkR(`}px~1!_FaK##MV*l&E{52Bq<I
+rk5~zVNj4qf7ZS6Si$tC54n&<}?(g1VKu4fLP?d7Z(Rj{nndtu^k*KLHGchgGv_OKg&SQ9<UT;=(C?0
+cFV4QvbF^A*-1RuJ(<Zr#}%U&)M<k9V|OUU#wGMjXKJL}QheZco7z)8)K-jQkJ3@3SsGTkxeCdNW{pU
+$iA8YY(*YQ^Tt&q6>CGg0hWSc^Z0W1sds?n?jx5e86cQ%%Mnf=v@&8S&&h_&x3fLqnG9?o-9(j;<r<L
+G{kS^+`srS5Bh#q)wOQ|KS@M!1rG<hM~6%Txb%lS@2achfs0zpbI<+6qiCbx^!=K&1?>a11{#YCKi>0
+gH`kkX+t4<UN~_2QU|7lRh&g~If@HO{q;SCOL~ZHbse#D`pv11y~%~6HojqoG6l$G>75!64{)K(k}lB
+c?Er<~XeGs_3fqHyb&MNMJ2@?p;Hjexf)C&b5QVN4_WOzpcVR#!JR~3?=3&VemV#M!w!Kf1=<TVLv`k
+M-$D*zmSEdB)<+7lcd0=Xq>RA$nFq!~S3eK!g5|R|B`_rU}?Odl~D+PX2taegM9^{^oTQI+zrwdZajH
+AsvxUtaefaQ2)gYP318z)w)LL<#>b(H#bvDQgt1Uz`BcpxyB>dSTpiukHTl9A|RgH9o@U{ID;$Sj_Lb
+5Ud#8gSi99c7Tp8;CCOhTfOi0(p;*ABW5cJIEmxU^Ed8>})pv4)wnMB9iGFNEI?6UcVRiMcJ8XWDO2m
+xHl0Y=6d%!^b?Wn%Hkl8#^D?2R)yEam>mi;Dw3B#De9Rwc;mJ1H1m2u*x~BhR$U5}7(CY>i`KEAc7qq
+so`2ix(0zv45~=r>clSQOZ!P{=>N2b9tD){(Ufb!-eU|R=;?6zH-J8_k+`GB~Lj|$SsRrUf6kl}Ohm)
+q@B-xy$x`!q`JW3je{nMm@xU>AOvB<P_#!s1<IT@5NZ>U+B2B+sqb{GZt;Zy_fGjyUzKNqu$uaNfe>n
+lALUx|LT$4_>*6nD&^tox2}O2j)goMcu~F!1ZrlsGAt*))6NdbDiitefEU>s#Dg5W`A$v6pTnau4sVi
+Q%PfG|3TZ76h34LL%$1N`b#345AX_yyIJ=B40=c((mAp|M~mSf=D#|qUhPs65o0sy`Mbkt(={d?M~e$
+73xp+ZNpFtNzZzEMc%8TB#$2gflt;2z)vGiw0jI%BZJO$@o9KTz?%>Mrof5!4gS+@i2cUX;Ue-Khr0h
+N6Mu%<%kR6q#Gip?oPPn6sCLc>MGq`)-Rk<6-LXP+mr7gQ8xXsIQx#<e0iaV#dndF!x)Ai-^$}8oG~Z
+djq(){6V1BHku*{VR#m`(nj^W1b0m~!*k1GZo=^#ojeWw@Tc(?Jn7(agcc>H@{PN^D*R(j>zjGrfVlA
+a7!De_O_A6+HYE{s<WRw3NdtleW_c+z|G#)^%b_wTp@aCLw5o0H4waIJslYwg_%d-kA$w{<D^UB%sV`
+{s++-KMAS@l}NA)+=N@E+YVeg?%78W$EEATHD#*0p{IEnWPk*6m%mF>daoo@pf*f4mg+wDFbEWx>5Fa
+6ro}AbcP~whW(KU8{azMM#*eQETW=kcs)HXp{M?Ku-HDJ)Ui5$iG>=hs`pBzp%{W<n*PsHlTe6fj@mt
+w{K3aT^Qdh9|4>T<1QY-O00;maO7>R#kM07e2LJ$J7XSbr0001RX>c!Jc4cm4Z*nhna%^mAVlyvtWpQ
+<7b963ndBs>uZ{s);zWY}cv<KT6wfe9(1HmHb&TaxsI>EFDduTLl+M;4kBvDIIaXgLu_x*~Zo>u08!O
+R#zY>~xcJ-&J=F*>8oCaG*?<Yq%EE3~mBcBM`$D>wD?Y?d%xl&Dk|y0i_M%=bE$o2*K$Dul6{M4K!YR
+(SeC?4QJ=ETdArM45iZugavU+F{3(vSEX@n$v8y*@!fS9GCPZ_(A@!lBK<q_Mqc3_&S@-_NgdK8g4A~
+?kBmo%hinV34*|Vf6)1}%oX@b%G8U>39^wpFH1TeG+&;|Oy<y*RvCD$wh%-YGT&0>Scg<r`-5XAN?N(
+YjtCn3GrC!?A8<>KyOqu#v`)7q^4O7&X?gcf<gkU=Ml(n9VDz(!A<Ir4#Iu5MEMO*{RQ^bNon<;Fdn!
+Pn6XLtb)M|U-%J#BY?j57!LG2Ij3?FHz6D8BQ_7rornyONI89o;{ny5W&ehTX)Z;8ks-*^{8ku9mx$y
+mzVvGOF&nsBDO2vQm87}W=3g5~W&(vLrUPYX6DoAN)`>yU1)uRezK@%sDg_4P9P#oKo}KK-%lFPOyz+
+l8MR+f*epYT--ZemoxEF^b={psbDD%FZG@+<%4w4?pt1tM!MQH^gs6_FfhFiSQ%txhEuL>8R3_Qmvn;
+Dp<Z6aYbQtVU)14^BzkkEPI~4NII8|N@9obB74*=Jm6{ETQln^?M1!Kl~p2DKTAW<UEq{7<;v^fR_Gu
+_>=wy?Zt4YQt@3?Z#S*exm<94T?g**MQ;8_mxYRT}*e~>`5Rxr3`BJ26uWWjX+Q@Z3dYIcZ%3RX7poU
+5iQULt$7bA$j?;qB;_n$rouQMMH2~wJZf}72vlxY$+Qe1w5#g?5uycsnTUbeErW8Zqbd{$Ttj)m=$&l
+T-6$h!xIox8PL>dVrtj#KI7+El&mF2(M2mB+%2xn5j69o@rnMf4B4+LhLby>0i6Pyoy)ZEu^jC*x~lw
+CU7xPWa$6q<pbH&W70*lGOR%=gwew96ncu^f9Mxn@yW^8g;bG&bl5q-ce2BWh45Kt`!}c4eEOCo2O&X
+p-uMZ&mF*z)IN;$aiVwdb@4M5ZaQhXZMU^F&}Jt}Bo<vKmhH9{8S9A1*hd$C)(1pC{sgjluNFCK97Pz
+jXv)CY%qW!tQi=@jwH(x$$SaX{_(%}@HlkZgdy%7Pxa&B*Wn7R;Wh=pT2=RwHkV+~oXB93job`QD;g2
+quj$=56#uT%&I9F&yXz2?=n?#NWnG;GJ0vedB3nH>$%gozzqFRJ+?73Xt;TEwbVVv3o`pBM2v5<~E6;
+1lsTl2C(SXC6#ES9r=FnW}H2^vAL7JS7Se0PK@X_&#JE-y@^q16EFMxtr*#ODSW##JZm5Zm=vhi?Bp1
+o(i{vV%lg%HJ#zoBhudX&lXcJN(Uo-3#2VCun&w1<pimv?8jKDs@$R+;61{_nx&bAxXQRMkg@UloW7g
+{f6%9Do?)<b(lmBHUf5V)z9w+tLE7286Dt{=36d$790S)HpEZ{(9(C86#Ofo@47~OQIqzL_o3Ak#DPy
+QE*df3hQknqzoU%y0rRI9(h<u4A{4T1eme}u9jHfP%kjUQx3}9#V?c%loFlNf4EgR(kX2IU`)+J`bH3
+Yp8Dp*-es=3CQ;1WlMLb<zQ4TG)4m_zubkA+#5zWc85cQ-OwaDylZg{un=C}kMr7MH)U*1i0^7G-{ow
+@GX5umO8uFq-8tSf^&`MM??<rV3Wn{Z|4B^)G5or_(1>YyzW=|?SY@KI9gZrG}f%e~eS-JsY#OXCKBO
+q^&3HcySSJ4Wg;$DM8At+l?ts_daB{%6!ZbO$^V`tmN)KIGa4pBsxOd3ygW(u!LI1KuTFefrq4;$2qI
+R_O2|x}x@>?qwGIoP%3P41|#GZtt$0IhRzE!B%F7hL(g`H1b9CZ?63>f?LVeYBtD9ewahvJ1bf9MC<v
+A<~w2L;lwV&l0^i`f=T&zWMAw&q`7y#o2dQPd^y1bo=96BxTnX%<-Lwzi83qV#d3-ZD;)RO{Os85RNk
+`jYb}>^CL@+A6OZ!!PlbG(lsnh#7=PtJ+is^e?Z|Skqr?F}B6{7(>ii#4;oeqsE6k1-?A$~d1j+zm{h
+)N1SoR%HyNX+1e#L<aqfQ|^m*7-}&a-_T0!BNdk0nxk59*j;WZgZZpl!Fl1_0wcV3rkU02#ZiM)MD~1
+>UXUiMcNqZrJX|GtAEj!lO|Zlz7|=AF{E8ivU62=Eo;!4CxG_UT4(Q4j)1-zxowSFE>KVg5ORw8GiHz
+f)l<RGwp)kF>m_)ZeB*^wEfa@Ueo$9|CjbA-(FvTwdKHaz_tiDFLuRtbq45qW@Yb9OscI?O?`aSmRw$
+|-?{9Nagh$({d1SB=X@!GkL{^*Hlv$%PW&1r3eK1>XJe_y<?vi$z9DRi%*Lg>%eUW>PAk;(-)(<#?%o
+Mm`%mYC!JD#8i*VKlPG_dzR|{@%esE;g21j3NNbp?7Ki;5efcDkFt{>mPUSGA>bENi8H;uAiSf0`TVk
+iB(TH*f#P)h>@6aWAK2ml;P_Eu0JxH@AX006Of0018V003}la4%nWWo~3|axZmqY;0*_GcR&wb8v5Nb
+7d}YdF?%GciXs?-~B7F^69ZOkvX<APj}o-;y4|5lQ_rrY}%9NNR$N0tSM6E!;1Q0fBW7C00JOLd$zN)
+`(brv9E$`lfQyU!zVNch*J3hR)>U1|$wVaUO<q(Yo|So8S8~GN_x9BDB-g*C`D&G9EB&?HmHO9hTx9U
+ZeE(;f%=VTz&OFa5`MHAcdK~p+9cS@M7Tl`L=l8PGEo4#Tg@{XWLys@;Yp7k7tYuzTP0L$;u(vlWau`
+yaiFbJ>_qcDQyVX^asz;M~o~CkMC3#lr*FW9fzW+(a3t7BM=9Ov)lg_xEZuT-R<;~3-n%tN=U3{L)4K
+`7Ir2cL|5BCIoUgnG4yS)0Tsy2X@^L)LDt7MkSF}-~y=lMc1Sb9L9o3EGI9D1a(lGiXv{p=x5lg0U6o
+!!5Y*{Zs8p7Uz>(R;v54y(2xA{>P|=V`ftsY{qC!If$(v*x{#TIVL7-@{g#RhG$T^#(B=6$+4kos^U1
+W-?Fn5<ucN-C$DXlRKEp-X0Jd?42UFXeFyR@T)9_lSvk@fn-N}dwcUVE=$1HGL0+ANGpc<?C-Ekqf?s
+cLN0;KlPswwlVK^-rFxDZ{2EP`Nl{jls@TD3w?!?z*NeD{;mvF?@Ls?$@EnOeT1eauSV9R8hcK~bWSD
+ncRfQUSEO74D6bcFFFB7WO&_GrV8%WI%3J}iA0+cL8mRIz&d1#G*FZTS_9s+_L&6KQF4r%bc5T>4;@l
+g6z3v2^LE&zW$;O$<?(&^}e4DaRZI4xyIJGH6A7(&RhhBEK@B=d$7b8;u~lnFdSIEVD??Tf!mKD@lVy
+>T(nLZrV(9)<8CT^P$Gi_<g!r;QbTw*K_bWTOt&4bZ4;P8R`reR+LzJ9&HY_T|MjbUmVnSGPZ1T&ssS
+@bs8@#)lVg-duf{yn1o_0v?`(hWMptw-c4e--u_T3!U7z#N|M5e}$2~rvHtj41kc~>?#=-MZ6o1>|^W
+9JurC(%OF5|nF5Yc4&h5P#P%*pCGo-2Cy^f>_$Qv>M-C8vpzA}D*QMDUYq_n)`{Hty<%Oj6iFjGbLR5
+EB&>3X?p@Yynx8BBHt1n>RpI-okL;UR(^2A@HX}$%V#z_joO|0T#2EtRsbHq>#YJf;Gk;7sNv4R1_JW
+XU)l|g9Tdudw4iN}c4NpCi;&T8Ow6Nh!HHHRta@sS@vwS%W$!X<-88x+;0PzqmC(wvcvDK5o)<|Vxja
+vI*1n|g!FNhxN4dU3$uHoF56XA5z_-4BG;bgYhLlFcR3-cFQvF;HY|G(<f6k+=o2tnv-aFwW+8PG4-k
+goEl02UDm(d(s`aiJF4x-Nzt(OfvZBRfEf7*pjh#ap^O!L4*Cls6%ozO*$mH%LhO#{xU$DBA+7^XW`4
+VF7HCC?pO!44=tgk=rH6_kYj=xsO8q%I<3OwG*HUoYgB-*U!Q+_^8C0N_i`zKG?6*4k$Xwd<rio-!K@
+#om`Rz5cmq}e=tos9Vi+1R0_Q(QJ7SD<W{I+FL2NIsnof5%(6>L|+=5WbWPt}U7UyVrW!2$@YGFX#k%
+0i*Q>F_Bm?kA01_U?fPC^3(?u3u?0(-z0kQ(#5M(4wWu$6cYcuJAMN?5Ls0TT;Zw#55_k&DFe5yh{5F
+kDAvRV16?Xha8NjdLInQ3(T9!@+nk`qT^-Bo$}d^++F&KAG)*vcSeEEN}`S9RP-03|*ie%_-))=$4j_
+&b~+Ja#jyN6-=OYSgT%sYjF;VQnx+b4ZooP8=!z0w0hb~S<|V_VToB8ShJ!H$z{6=mU`z|ZjDKY_O3Q
+Qhe;k?UZJV&9WQKTOjM%LH~~73c!-z4r?+vjC=chxx)$36IQuD$aXP&N<2z!}8rcI*#jLJ~z>V2DozB
+2upH5-v1U${*uq<ftyekVh(}xSW#wXi5$>(D_#Vv$hz`!=LsCI}s6!K_TL;}Qu0>_KSmuZ;`f4&In{j
+R#pfm$mV02T#j6GTI?J1E5|VE=TQ<WqtKU+PqjX=ZZ}Lok&&G8IrZBw%`heiCFU@q*M0W?T9^E3b^mm
+&5=F;IaS-w#|!sh1QGDptgVz#K#q$O{D&r1l|RT5$l_ZT_My*QLQBODFMWuh}ntaHxAE4opkK%$^lC1
+1+bbVO>v2;H!N~d7pPYO7~m5%xoje5Al|f|aR?^J5V;1G71%I$py6rESzOYdJKXp{!8_FK_dsz~cksM
+OR%nSCr$;mX2PU1wJpp1{04GIOTN+lr5aeEopMYZnop*aIk_u1<bA6B*w#M~=29wrmfqH(-*yOBUiA`
+N>@)G!~xP-n9KvYq;pj`@9Al-GsAukeHHmkd(&7+6<xUzhK1yp7o|5+C)koR-#IReuoy2hW=hAQ#11y
+aUA^=>n1{G*m-<<3K9u#mag?MX`Bv1VEq{N6}8elI}pn%|@EiJWzcWx;SW(DGyfoL;PJnD#oZEZO%Er
+?tcbq~$ET;uIZ>l@Wo*BNA5{dt+A7*=F&C<@wdS+lzO%lUEn#SFhNf{>VI=bTi_ggHPQIx>;rm(lZ1F
+ESq~@U%a}!zBs>~+}ysn{rTpCMtXj9JQmN7PVmQb{P8XR`0i6ckUO$_Y`)=XIU5X`2aJjG3@6t-MLVG
+`&yJcWC`#en+K+&3mGH#xStRqyZsu{3Gdj_h?r0x<?`7*~dV_89JoO$mUSaRWx?Fir6zzLY!{m8J?jy
+S|QT7D5?p?lU0p^!*a=bTjUFGa&wN|RVH;QNyuwPKH%;ivR&e(H+hwKW~6sSb~)-0%{;Cmfh;CfKcLB
+kY*b^!h2zEs2kZ`E(^YbF$U%fI-5kzfcg{^GuLsRPwC=Yc;A^RhF&v+nEg#zO1x3%7H#anPap(sH`8>
+f}2!`6WrJ;G5+p{Jcf~(5&^W1#3bsfC*|9#tCTN!!dw|@YCyN(JUd*d~;}%mVnBPMWpy_EQV$Bnf5YU
+O{(2S0@2bmMnNN3p#uN$QHW<6Ug1C98!O;*W}S0qg4)#NNevJOzL9C6+#P>kyZ|F<3(~XH0&LD<mcz2
+zr6fl{+seu%?6B4;{^(9pb!hpUo0mXd%gW#Gs+a&kZDp$yh*6f|K#yp&7?d=FQIzIeY5NTJ#j89!Ks9
+e(v*&FiflNTlg=x=G-NZ%3WJb~!R;b)8l5!3TEWS#b<J8!zXJQCnw0%b^2u>6=RGPA7;W>`cfkFfsLk
+3)6BN~KJw8vf!Dzs}bA+!bn>j=|4zXuXtg9?L7(cTJ@h5UBta_o^k(&bVUJchrNyfVsVWUtE;W`xKlc
+7x4($XzqT#n6*_?pMp!MLV;Qi=+TjpQQPmd=9?pJg|acH+OlRE|7?IH=%5x0)1Y8Y?gh>8dQ0Th_CK;
+O$R-W;Ny(T26!u2W!yCK!~lLsCCAYy!fC)nV0a<1qq(;90Vo7IaO{qBinwPMng9(N1yP~h^QvK@oC__
+*syoi+oI^dUfkis1F&}laX+R<%=V&`yd*y`sh}Eg6fY0JWvkI|F_*qxYP&NoZ#NzNz4lC&?FF@nXf)l
+neicx7cvYBhZ??^WK)R6<gNGkHHC`-1myaH+pQL~tzGZIyH2gls9<~@U5xHnEP{gh0vnZ!9L+=E#V&+
+pNaB1VXK3a+RXM`?~|gFO`~88%UWI}2jmmv-QZo=vRXrax*QM6(63d>{Gy;x(G{p6i6&5Hc>nxGaP+&
+%{ym7440B9<|OvfIB%(H&+;%Udv5)A41eT2Gh(@;746+Z1$|z{pZVe><Sb|=?NVj?F@#Yp18$GE19N!
+q<u9*^OvY4tJgEYD@YqsV8GZ;Q*<sosDRcM_>U-av5bpIyp4Bo8kVRLAQd)*1r6hMUT5UK(bB>;T2E0
+Bold9Pyw+#LaTXAUr&D`Zcv7);RU5Yl&ub{7)mSv~@==)X9dtVyqh(6k(vv-{o($~}L6{8$U6VM~lAF
+zNR304vAbF*hB7TUI6#ZY}xf(sa&6Bl*hnv`(8NjN3LF3z|aHWB?BN6-L5p1SRPN*f!l@DN?d5J${yj
+AGu12t?GijacflF0+R{nW4#55gD)=xJIS-lZL0xG#2WpaJMG*O^>m1OuHHr0QkDq&r2ezG=RSREpTJ^
+^&&WT2HoU5CF@jXq@LxLB2BxL%G%JtB!C0(kr!S_)mT&LQQu_9kXPy0G+f05}cXq*XQEfljlbOV=kUY
+&!dxwqs|ET>2p$eB_%%>DxB3U6E>$c>(ee+dK=rX1Cd`ob&crNpI|tD-&rmRI$E+QH*%gV(b8RGKmq8
+_^OcoIg8_ImDYPdz#wh6udIlY1fxgICBCqwS`08W~|Buvurl_pTtgHc*M4EK&+i`LZvjV9rO)<%;Qkf
+(%r4FV!(l5i90=-PF!+bmr!DCpp;*8j@q)@Nr)We4=s)n@3d3b??p-_nYrW$^PxecKun?CRhB9EKc!L
+9aQGXokbXe03laopZwA`0>~I%$F71Bsu3w_Q5QvS>&lOsCYj&d588bgz&#{9QR3h~Ej%<zau?OEU~vE
+iT&Rn_)1y<Ueqfi*Ry@fznF*3P+?Hj{bu<3Zv2mX=zdC=v*(1%|H(JiguJVsv@zyQeY2)WX#uasz9+T
+$KsB&Le=rbfQ^C!l6^4w`Q5+2yZZ31Pp8zbGo&TUBxz}wUFb3Zj+{lIL!1_&IakRCs3aRu`2r}65VNP
+lLS<tV4Ns1~LND@HBQ!;hkB-C-+Q|o)K7sEvf-U$dxcJk>i&q18o(BI%EfYx*n5SIm5Ne-6E33nLLx<
+OR*U-b0%<4*#IVF*M$HgwJJ?sN9RPt1FNaICOItk+nIU{cNVFFmpO3+;%fMH;WN3&oH-i=|#C+4Yk9U
+AC;+R7u29HV*b<pQ?~YA>xpwTbJ87CJKwjknSXX!~%zqn$QUZog%FAlsAlF?eXDb}j|qlEW!9l*N669
+bu9NawlS1JwJ8vakGv<#>#&Kp#($CVsdePeRVxKfAivo!#u;wD`iVI$$7lUM?y+rfX@J;N;e`<V>=_7
+r)VWoj6E0onA0`%S~^bYt0o>xW;`0Yl9Dh`tZ#CJlwh(eL*s@FvD0}&nQk3{Vf+MBsawp~KTYlJbF%O
+Bq&ky96sxAzVSIz$;+@rBlRMDLNoBCA650wwm-g<Daw>j@p8C29=nVt3bvW%w#oLoALT$lcPg^6C?jw
+h}IrJ3B#W5+YPQzi_?bhr(k+R#oN2I*QhDt-#`>h?Pc?L8}(twQqWNEkJe37a~LN?IY@5JHu&}jVxII
+EX^v^N_J!ijIt?U~ojNtCkN>e%&<UYU=<9I=JT9CgEf%$;Ks(9XADaX-jZY&Z?3sj3+Z3=5$xT*yOhh
+$;_<f${(fR}3ou7`-T*+GZeH1v;q6BM(Sre9yeZPVTr%R(GmTyh$u?;uX#(sm9tB=sOFa<`|qq-)w?_
+Oem+D#{|u{9cJ#iW}f05PGMBY?t6Xtm$w(E;&LI0Wp3pGW*FT|KQjblb;@bw7YyN%4*LrLt3bv(Spjl
++nPMC75HzqMP_58~K@L^Qdr>6QHj|hK`NIwy$Ml$l(-=7s22-FBoUR%e$S8;u+ld-rp)O)dwGhy2Wrd
+06Y6a|xBUw|SKcw1X`lbe3{;>rTRT*+Vqob089%iNkqP~Q}AVb+9_xBMxXNsT)A*ECxm<i@-0quYJ_Q
+g5jl~ab;dtOLF-a_CSdTc^H@1gWi_CJCDq2sr9Jlvzs{a`N+Q)KCR!@5YusdgKpL2FKCk>AS<BvOGw2
+Bz+>n<8~UwT4L`C0BPvzJ&>IjWQoU<jI0bo7m6B15#(&W=PVVJ5A@<JLPA=VjY?g47^Cl+~Rm8k{-cH
+cQmU^GD*-xMU14H*M$ei4vg4ulpfT~E4&Ss7jO;mu?q?@a)*<22Ogr>=_*%#uNv$BLQEpgc9aT@xsR0
+bkRY$vVjp(yFw^$<Y7+AEJRuxot+XTQp-<y(HI8V?!@!9Fiy2-usc9a*v|uMMS-o5)bDfOGnI3I$m|h
+G55EUTA6^BVFYdjWrIVuxNA4!Z)CvUESSLJyRTDn4mE<P+e3L-*NEX~i!E^OS$b)`}gnS5aDt<&W}Q#
+!_zWo-XW6MO91SQ7#2s(WzauC|f0+)!vkSvm2#>Wy!D8Z)i|w48c%S25iyZ+s|LWFVz+vEo92jPib$i
+SoKWKRKMy?<8tt;>+S8iAjtk>~}Iy?g8}~d!bMZT9D@opkXL#i6u*1l})p{i|H-r-97;2TD6jZ@F}c%
+ik_TlFk@m0V=t09vM%<)qE~#D$~7L3M(08qW=C$3@mQ0z_vH)mJo*k@N#`n8`UiOMee^BNa2_M;0i1#
+OuHC2xy4uRqFTY#?=IdDm^5jdUJ(_=$vaDtK<;mB_&-dwfXtYL?=J@#Qldr%2{`;e&$eD)@kR}<X+X6
+w;wr+M;uol4jArdP*#a~M<Idc2k3phSv3xRUV8K;X}vMr8#+-z@Htwgi9FqOWIV46>$%VZsY#!^i21t
+9NO9I8r9wS%sW*S7eEFdI5Q`0pPYh;8=>P{A;qH)D=p>rE#>_nS_Kp<Ln1o5{_^`OnuEx7RP;-MqiLz
+HPM~>W1(CdiDO|9UcOhUAZfDN+Aro%mMYo=VNhvWaSu*T6WZu94|>8y~Lw<dF2_+`{Jc66Vy|tu!srg
+V$lw=1s4OUe@@o*nj>?fO#UgyzJLVb2;<Bv4A_B;+|g0IBL#A47=y(@W;;@&Js8T13ddd1R^&C98e~s
+}{0E37JlZGXPsvN93gR`a`bZ_V^xS=|!mNakwV~CNbix2L8Mh3FeR1;jH{vY}jn*%Rmh&}ea_*!ZoN6
+jQ`Oay>)vWklxioRJ@$0{xg<Sd=8s@g)0IvSn!-D>W2Vv~aC+s4`9*1X5_qG=!7>H;MX^+(JU0QBb%0
+&0XdP_X<GXn_stv5{n(Y8n`87TIpnSiNGvmsRj6RGMsCJDy(nwaYn%U*$Iy%XZ@bmM}+5y7}2Pr98i(
+?T0qNt8-<c||0Mx-!|b0Q{`0>fgl};wnH8G?v%YlKigJ=Ui+*<D4J5Ni1aWcLgMpbpqlYQK(Wlx+*<5
+d4s)ctV(R*#4Q#H>PT^u-P%;|oMMfVGrj4Q_~dlzOmI52gs>{BfCaip{|V0Yx}M)zYG|c2TAWyfnxGC
+PFBk(9L?}ghpP;eoGFT<Hlge!2I=-iXa!HN}njo%)5<g6SBy*`{ou=L<D;%}f(dY90*Xn`r^H@!gH4z
+8nee)<$<!75hrT5S=D-rj`Qo?XFuDVVu-&AV40aD=n>J8&!ZS|$b%F=X)JG4wpsaVt$t?5rfWjKIvJT
+AMu7TY+hRQ+4z7r^1Z!2*-425mPl?)@wiF5|~)G8h;7^8uSqRb{_5kKq-_k%ALAP~RlwXzDK&b3aDGV
+`U}mHXdKIrlm&~;h0#fS|CtE5X^83gY%Ov9S3tO!`q~v!5jD1iRET22K;U?=3bUnMx22gx_;PjovKOM
+a@Zp2pJoEY6zwZ=)N(D!+m<c<>KyL}e!|kwIVGL<ytMRJ{n66jXpXHr5AZWOMH%uwjjLr|tPd5}nxBf
+7^=h@#MJE)H4=Ggo!ybT^N0^lPELRDrr8$pb7#)yxLKBMBY!Ne`-I8U-=>uO{VnR&Vn4WY1i&Na)9dO
+!+_&9nR#?CU8=e_Z-Q0`X;xL0y6$xc1~dMr+kj!(o8Cj)jC*k5JDu%f(Jv2k_$&B^!QjbQK&a9mW190
+V+(c?hFu>H=dVqmZs!Ag6ODIAAcvnk%*y@(?gUpsG<EAiSSO?rT>^sL`Wztv{L{bkqrT+eXSw+?};^)
+DDp8k6RvQe>xn__-UvObNm)7PF_%c0F|uL#O~&lxw`0BHN#^$FqZ{Wm(Dmgwa-bKRJ%xgKrdns7*K97
+Y{k_iLe(57JpuiOe!gUwBp8<Rk*jLb5(}o++SSIyg{hLnJre+1U{OF1I6phEK%}8lCrn!S(V1EHoDEC
+2Qf9|tx^S~m+X{WCT<aMnRfTWd3KL(ibrkM$Xb;jYV^nIuQ<4Jq{JHk%PR-I)Rg4?J55{(R_bpAHtjp
+tXg35e{-u^<@YJ<(G3%Hkgp%gb%Ym{9cK~p3yRmhGN2cUi71%(=vR&F>IySXQXwot{+9DWGH5ClgZb$
+sW_+4^g!_2`tdmWqo|NX0xVm#GsV&e*{4cBO(~Y_p(e+@x=nWs|f^O8&eCE69q2;|Gm8?H%JHI_q{h9
+42a{8QqHl>ibTY8R1MFXc;y{kERyL|A&l)5QTXO<&DHpZpCt<-q2YueFYDRkuqo#tGYsWVW&oa*;q#m
+nt=8g=j@dsAr>s6=+BtZYUtS$CfJV21R0|{`-T(zNH-GjAvLT4kK05Ey`i?e&(m@&fX2S~!dzr|zwO`
+)e@Y(kik~N3+#qzxD=>g!Ivwl75nD&P-~q`Gr~&p?cuchg)gb5EaBAyb4-{A`t4ak{{2D2~TLWEqG3H
+OZ2F7&SuB9)g(=Z`7rQrqE3%4$+{KXaOcrudD(fhxigu<7~zkU*Z+j`kmq#ilj-l|x~PuN^}tm-`i9=
+L|1>C}fhnC9)G)LAw0=b$R1KSYK8bVa+#Qf+KpUFxpwL)fbUKLo?@$i8u?#PVc|oL%LTZgD7Fy-{D}p
+m)U8HTXV<LS-JiFZI<9g?75TuhlgVg(~Cs0n>F4{Ez!8KyYpY=X9Dkt$UZS5%0!+;1(g$OqJy3+i$wg
+uVER0eT5`H*Gb=*OqDS%$_I{T&jK+*iMYT^!RCCU50=}iD{w&P$}tDewZsQNIyxxza1tFyM-gb5oHoV
+R5jhlRZffAd*K`*RTs-2qtGw8qy;8G)E&RYMX;H!ao^qznPR88`w{sKs+E}yh+eC)HjO(<ec>Quj{>p
+enS7iu^lxyisee_$RGcbIMv|XdiBI!K8Pvqa@CUFmAV||5`&K~Xy<)Opt3sFZk_jnn2Y)1D~EVF75He
+=fP29KsLJf5;(58m9m;RzSLj>wvSX9a4oi1aDL=t5I>v_(WW(dr8yEj8<j?nT!hLEYTz63Kh0b07S>E
+c{qWlOypc$fp71Rz2FIy^2OD1C26kk>=wVVT1chrG`0T7xNpkoPEwZS5b{a<UDwM#oYR_6|1@Tg|pmw
+wsefat#XbZQjkks>ejwS48H5Mz(DeKT;w&dKzrSAbmv8~0Ugh6Z$-R<cPqBMul6=*?}5`G=8;<%<V!n
+SO)0PJai6!D?;|_l-}tES$7`3z+qJXgeEmlaLUKV&6EERY7w~z0ET37r#LHp)DpzuD_G=D^HmGAcp(A
+GIUY&xEu-ypDtd4@HI_e?L*~ilc#3vXGe+dCGjVwP)*ih}u2*)C{Qs>EgK`Mv-QxIRJ3i~!@{G&FPjx
+T)x^3VAYVN!)GseE^7T`El>sZFDHQ-Cv}h=;xcaf`*hWxb{_rY`3z;w{JX!N_VHlBz10YxNyVyuYMAb
+ZRyOI~%RufJrMS`Z6F>Uhm%ffVXC2+T8)xoF^;vp5outXs*JERd$EI%E#)=z3|$5<rFeG-TcQo+IK@(
+HxqR_6jeA(e<fFimDr%d@A%kao~jl8qbjy$gWm&3I39gGYKpDG*Kj!3C1LF(LV>Q|Jh^akU)R;@YJ1#
+P%04y$Xt0)NUdorSl$~JZP5W<qC|-dRw72>WHYZhE9n3z|o-J<T7sK|2>~sf%|4A7yWs~P<VJ}ocVhu
+_EhE+NX=E;cIUtV%R|NQ#RYoS8hGHX&@5mpG7oi|^Ru*OyX;J0+w%jKHk^|lge+GF}p4uzkr)4~gl*q
+-NE3)sIp(ccKuPg*2M6AI)|4xtCIAJQ)-#NTr5#+6`C+7<bRzds>g=*g);z3D)4)|(9!N(TD>w4dL^l
+i!<+V#<)NC8gW3QlfN1x_=uHl%RdW7fJJG>ry3l)7GdoruizFJHoiJv_qHD=$aq@uRsOMKN};13P|*A
+GXYD3y`bWtb<^Of?skA+)(J&+Bj5H2P5)^T4_;5#-`)zWif;aGO7^?7M$$5aOTE;$Be1iUJ+_&nHuCN
+H0qwB0@W$Kq#1tNVMdOVBmWW+QK;%nW9p0<ZT%2rof23|A@MpV*9qqd+D0<3i{Puow6tC}cX=gvv4eF
+f9Qs}GWJcj~zqpK*jgJr#z3#{MsYqKo(LDc0z=$cvA-_dDS9@5H#*|{xA6U<%4PdHQ8m6wi&7)%J(7u
+tJa`QV5I=8-6z7rQ?TCu{|muBOr(t>Y%Ggn&Nwj-P$3+trm8NGI=i?{{`l9|wbVEuFbVAOOgebem8!f
+c!H<26$hrlhs}Ig$9NBBmp3)tk4_1#M?j~Fs2R0C$jWxw~cr0lo5ZE{L=LvWOih>{kbQPtq0Y3Eez6^
+7Q~=6DFO7i;&0ihxw$d%cuU^_d77nXEsZJ+lCE_9eQ|@A>y!y5Pw479nW?&*1DxkUc-`Rxg)S4CA^ur
+F>^<l^jvlr?aPo&$%lCULrHx#MgQs%gU(QsG0=hz;)q6qVwUS3Tt)H*oaI)7{=~-o7<Bj>G@g=3DW$E
+6ROZz^4?%e$80;iL?VHLGQOSQ42U6WD5X~0}Q=-nRMpCh5~>h}M32|A_h1`$l4%8Ol(%g}52@$mRl)V
+edb$6@BUA6pk+t4sAkb8G)mCsTCvv2kV4rBZYRbsC3CUJ6`v-;R<40cU)(4uS||+uAm}aj5()3tWQ3O
+ky?|M1RkdY{+vRiD%sR<IyMhmAbZi;u1caNqjs$1&sFb{Lh_`FcXYmbV6uQXd1Tf;OVZz3GG044^^^4
+Rg9_#$5CJTz1uI0#=ZXnP)h>@6aWAK2ml;P_ErD@0006200000001Wd003}la4%nWWo~3|axZmqY;0*
+_GcRLrZgg^KVlQ7`X>MtBUtcb8c>@4YO9KQH00008031s8Rw{$(6}15X0KEeM05Jdn0B~t=FJE?LZe(
+wAFLiQkY-wUMFJo_RbaH88FJEDBaAj_1X>Mg-Wo~w9a&K-faCya(L2KMF5QXpl6@xC_z+yu#fj|xmaY
+7E=1ZUeGN->HwYm3SnA&s5xzprF=8)qAOt#2NWzIl3YEQBa_y@@c89xZ|oG#QQQ9i@xF1R5C?1NR6U@
+1b^`aR}%p6UYtdxGY416lU-g7$_D+p>Yo;w$gi?+gBIY1*9h+kHO_nmXx&12B47ZX}(^TKY+DSI{iYw
+PS7;H!8|*H+0QytYdQg8bk4XAjGL=_6Cy*04ufPv4vw6%m@&K55>b)U%bvtwGbBG`KuAXP&LrXX0FjN
+g87)toHN1=rhG$xKbW}Z9j7bPa4o0z=a1D`;{7gB}2(hQpYWIo3A?j?o>QViKeRd?dn{g2ldS)N5t4d
+iKb=eVh7E47#^~ae?lZsX3q(=r_owT1^I*VXwemaqoE03vu7n`T2dVBw{t=s0ycK7hP7C+$T282IwPw
+w(cyyfy&lJBDafRs&pn{_t2?2uP8U>5ycH(%?feSW;#ecLp(Si|ue7iGF;iu~1ZzY@1Np(UTUu@Z}&I
+p3!LAnkt6Y4Pj)Ltr~hLtL!&E&6~;GV1ayzB_3n7QX>dO9KQH00008031s8RtoNuiDV1_030g-04M+e
+0B~t=FJE?LZe(wAFLiQkY-wUMFJo_RbaH88FJW+SWo~C_Ze=cTd9_;WbKAHP|IWVxRVHKUMyB(a=?71
+B9be+)JeOSDSectndqYDcB;iaFJc5+1cG|zayLb^GDaCGD%_OG4#bO`7eE`s8GKrR3E=eJ>HfN-&#g1
+o85=tr|a#GNeZdgs4Ep13E;l+C)Hb8h$RpheV@RFU#==RI!5ARr$ZpjU+cRXd}Pur%c<oVfInu|7zH)
+>LxisFn`6;t!hGLg!&YTs-{dDhnX8X0_lo5WFc`9O;b7HK6cetsTB1U~Cp6r|!+oa|Vci8_WkIbXddy
+r@LokZX|lqZaolJxEbDHDAR}63YQ}(kdA?bHZifs1ixbY$YDFG<-e!aymO#ukrJ2z))Mzjh;y240myT
+MOJLf%M5JIh)h|@q+^BFB#QyR=}b|uTrz)I&k}k?N~B2dSaX`Q9m^lLmd6B^QEzJ)#<y|Jes7s<rYG+
+&mnU;_Vx8@|`2^-Hx2$G_!oS;`7rdbj7o~hMHvS%2beuiARzt~OTG3E2f0-qUvjp6bMksZhNu|LeP!Z
+k$l=q|*4QL)A*$NaO=~f`cTGV7O+M0j>IZu_GG3mr_wl!l!R9b$dZY3`_kwu^=hhYJzeHoL#ik76bL^
+qK0G^bLY-}b$DOYV8Ib#lj@23&b16|y;H>orRoz5}q97?pdH@;Yq`+0ZgY7fX_ha)W=BCMtA*f#MBQK
+xO3R`5}&8h4N7_PhHU53HomvF&-9f$!bqnNmn@-z`zPv0qYz6OlU3z+0tFl>*$3VY+mzJ4d9fgBEc*N
+h(Mfs+)sh~sm~qpfGa9FD46CRVquM5{2if#`K;_Lj_j5~8Nn<u2Ye9OqVENf6-)Vguh6v?IWR-r!Klj
+8x3?f{yr)Heduwx*ipp}A>}buwR7`f^iJ$ium&uo#%jD+Mo1ZS1H_4C7<@JZFAILd5Y3i1pMA7S*T&<
+D6!k<DLx$VG3-sS9p1LNq?CS02tXJDGS;%xn{asa?6qjeTp-v=&742iZO3U;Dg^G#bT!xIPvWgS2b=*
+w$S7OZTD(>snPP+=mKi<4yCHek{uu?d&1q{!QbCHi|5nQ<=cQ!X|ej5PE0p4KINm4;&+vxk(Kurwr7W
+ofkNWnGJU?!Nw_=jwrv^x-pW>b*yEU5iGfBKL-FZa#S5mb_qK1v4_UB2+ZJ12f53@`tz(J9yG@18-{S
+iVKYWCU|LQnG|Z@e%4<<GB9)|J0e+uYK{l0@!5=7nzrFN5P~ipFZdF?ZnWf<z$ju!?5J1Fj4PuE7@c>
+;)PT#;!4vn?Qz<&q9wAq1SlLQ*umn&;eikK*q6mBoUyO(24QoEYBUGCtDQN*HfeI2SG<J3GI;Rb!-@^
+EE>iN|a-U{ds&r|YD9XO88vBfWRjhTX|#=mbwSu&M!T&slTVNeZ-=@0x01HqwjrTQ<wUXPZsjMuPI4s
+I@G!)Qjt+9U>(+X*XL(354VNCN=py7Wm%WUJp`F6J`FHptDAK+l&#Qv{O%qsR<p@Z^Ua(qd@qu)oF9s
+K~yp(L)YDLq1-iS`gkm&q+-=7Nc@lF9R>$LJQVq)$jbGsmeUvQJ!NCiajEmQ=5hrm9mFUfG`KN8p*G7
+w9UE&v2<bZ(zt9Zovh@+wJ5P+F8M!HH7<l|CqTQGFG#^QbhU4o9GPYUe>m^;tAq1UwN~4%Esc0Ab21b
+P!5}vn3AFljy}bJL^NsPs4{R?~KPZ4fN&$uQo<~e`V0#{hPB0Rv9FGqfTSJ=XC2x{s>V%UlU(dV#60p
+l^xxg&YjbaAltUtP=InMynNy_SmuQ71gVhJU(Be8%=EQjv3*Na2Dj-ar_VL8_N9Y_`drBe1F(unG_VA
+Lyx@g!g{>-qy*%VK;8mzlV&jWi+d)*Nd!U2?IRAzX6;iNZE&y*6hwsd$-(^;y|yx1C`Pb0AY-gvVT*v
+GVL?{OXVK!&%MNkRqTpJ?n3~woQ@8lX<}RP=fEMJi~<vId*tcFthNQ1?Y>%fCR;7Y&e|QhZjuh4@KdO
+j?g|qK~Ob0etY@u;>(AnA1eS6RvY0xyu#GBE)~Oo`oYr_Ds9s2E2f`76*II7_Mo3Nr+3hnt7f)lr#8d
+xVUOQ{0IGX)jZ|L-HM0`}v=@-r4@I|5GC_EDUsfX9_agi$*`Q_`uDuLkx|@Y*Ypj)%<<-Z_PhXZD;dk
+HJyqetI+YHfP6a1#!m_S2fJv=pk=S~C<j;=?tAH79LEU89<em1)x#VmG%e^`(g!J7t3VjiX_TM#<<#p
+?fIehMsZKNa2Qf@TZ!!0@eh+M@5fzK_gb#PdJ@H6)`-ZP>t+7)IGb0cS|oH_u``&d?rx(jl`9M1q|tT
+Xa5in+k)Asrfq_&K@l<2lGWZze_Nt<8^*{Yh=2Fah9=6)e)??Y^?0~y9yiF9=iI>uSz8v<mf|eq0~(p
+AxKW^4Vz$1f^G4X&CUnvKdtWJr>lLosc<XJ{Tc-YWirmdv?bCqfC5)xT6+1SSSeYd;ptZgXN%$RY{a6
+$Ms9k{m~X{>iD7ZfluJ-howqm?KEkHK_R@G2;}V!qDar-=Ho5H{5M=v+wm*)rr#Ch(+Z^<+b>q;>6Fb
+>@_Vugdo*l&1LA7B!{-z7Z<4W7D`%ycZVA7q$|JsO|V7foF8wH(S&&hK@&~sZT2|J`cwpxjo_jQKz@}
+wzcjYtC0P$oM%cQw`3vSB&wN$`yP2w50fO$+@$4@z;83%!}`7r8*BSl80tlxY_P5NLzfp%<Q!H(Qq8s
+ok|($nx(8?cs{zYA-r95v7yr$&svbY%ei{Q5_!3d*X$*k+7$3p-EVf*DqcV>G5NBZVNJbf4Q7Q1DZh#
+(z&VEi^jZ6Yla(>@dV$k<`R|`a}fwVCkb8;saiS8XEqFT9eaU2$Awm4c(j|Gs^97^&t};62Ko+7ZY7j
+CV^spER5065gK5JBa<PdswrV%i$!8-6ZttE;a{4_c250qNFbp|45}2U7LOfoaK7P8}V8nx#-v1nG3i~
+pQQ;heU_%Y4oA;w{@I=cG8K8%yu?Sc6_PBfki?I*~IIu8Lz?_nFg6>YAwioPDeqeT}p-SNzpN{x?%u3
+^6i{#rr!gkXt{MKD<+I)M800;wmnUZOOSY*<chypE-nd4K6%%W^D1JTVW17z==o`N^SsHYR|MqhrzYD
+8L>9>nJ|eZgd==y&cbx;Hv<A1USD6%)_9Z1>4pG=}H|LJfdH4S+XPSH3$ASSzmltwaB^)gXyeatf809
+T7545{^Alqh<yZ}GOzK3ny@kz874m3HllzOmBQw6KPRiUQGHX78+K6uO0m<IRc^L+PaII=F%zISaYTz
+ywJ^*K^{J(v%)(R;+71~)9X5(ghV>|8`S^l=8!q;%e~Lg$xn}hv<+kL$;GMmGVfNxv9bH>bo=B_A+#{
+CI;<M%iuORNso##EC_m?MVbk(_vwg!;w^fhz3ZOc2B5!fEn*oVc43ScQi-m{b?!OSz57t1Q=pya&YP}
+xbb2E)`b59tn=e`vE`v89?%VpTaEcMk%h=74XS`+c~72{-Kl^$Kr9Gjj=)F=GbU1l^1JZjN>>TG%vKz
+z(lT5zNLTVA&ooa30UuY0kkbLfzklKv(IDi}(k;3Ap++4Yf9Gdxsu{+$_edlfa9R(q_O>TZW{%()1|x
+U;-BC?eD(2>o5uJu$liG#s6>W3=pyyj66Yqm9j?<v2>EQM_IwehP&OB<iHW=pys22@oW`w_7+d-{j0$
+fm8WT&H*uKt@s0q0ZDLQ<=61c=;Ml}a#0g#y*ozXiA_Rtend;k9|NStb9=Rv6pCg;@4Fr9gQ@1EI5Dm
+86&>0;#p{m&q4;ggas*_lvf>~LlI|i{z95}1``i(~C`Vr???%_#r__7BXdseNHGCZ*!T!wiLb=0a?JJ
+=)YTMYayK*FIx9IVkbJJwzc|4L*QbP=}mvmj6#dwVjDH&OogvEAQSfH4_Au`(|84+R`(Mo+U+u_^Hu*
+2t;O@SrOW&mpk?uV_u70mT|U0*c20VweZrB~$c_T;v=Iux@gt{!Pa4R~rc1f`WhGAF0|^&QtY^KaMv|
+YnsBgB=Uc{2!0(hiG7M_?3a#TpXPor34^#1%^$I5k1iUtng?fwWW$L`u`A>wXDiz1KTt~p1QY-O00;m
+aO7>P2Y3Vmo1^@uC5dZ)u0001RX>c!Jc4cm4Z*nhna%^mAVlyveZ*FvQX<{#KbZl*KZ*OcaaCyyF-*4
+MC5PtVxaZ?f0?o`D|S70z;3_<E8!P2y7T=XFc1X?;<Y$Q=5skqtD|9wYNKP@K(_Ao3jp~&O$<9B!8(V
+pjxu9lbYft5PJT=R%&o^PNKBK08>xt4rYYK&p^2q^h|gfU8`CCf*n3#Ceg7e`Yc6ygjLt&7>=VI*P<H
+bQJt3?h*o7Kf!wQ@(n0$jt_I7^7x9{f)=-qv^;a1ZycW2*Y)$ONn6!JS&9Mz*b76ba?2#N26+f%VbU<
+mD`t!&Bj2k7B{FbX$IxUE$2GT>NPX2rh}lKJYOz9UZ09Q$4GOLf25n&CIyS`*#=dh__rVv4>U4&45O4
+2S5G(?jcR;>8H`6jf8H`dcv<lfRJ;ZTk74>HWFjt81g;>)LLx<hC}(*LTb`z{LXc?AkHK^9cn*~_csL
+HGw45SS=r^<EDHn!9@~Q=>vandWhC+%0W%>v)1+Q{P7LxXhTtUi}Ihzi!(Q;8$6xI#bNx8BSt>d{9*W
+=?~kAvFf#Tp((2}~j|C>2T&YtRYds_t4?#FS%MX35NH6~T;&M1#OM4LskvdsneSOJ5wj{%A59QS4#fh
+I|}`Im;-6XlWFsOerwQ-4E_~PrxTL2ikMsFERpWkSK})4C+JV@IXai{?naU8;YoLY740GX$LAw$S1+|
+ETh$IjBCn#o^u_BV}<G3w`BQHY<+tu`S#%zlN&|<UfplasDj&tZ2l^96MF_!p)n=#=TDa)9JS<@VAGI
+kV?ueL39Kt^bH|`@WWz-!X4e-^ezvMcCB=$z>ah;jyASVAF0O8G&8ndu)<R}Xx2}q9?Wmw|Y=w-CiJd
+Teg1r}^Y^7ihLuYg*T~C6Buw7nS4`dhAe9UWR`pc4S?M3GnN$>Ju!6XIWtput_xgLABx1JA2J7*BbjJ
+TM0w%ttc0xCDU!H#X`w94}6u5UqX&55#3YUH>LO<LL9=*0a6d_-x;cI4U|O(^6lVfW}_tS}-ub?a?r2
+4JK}iRd16$6Hn^ZFJ@y3k@U?IcyW28r}JmO4}3y6>{N@#5m}~&dV%pPf+ml9F7_bs?i|ERk;~AQ#Rh$
+nkX>BZL!;;>=sZi0yv0U`8iMrsuF|e&fa5@2&MN-*TvPWOh(NxL1x+<1><k8O+jx4-XDm?>ywl}p!dB
+oCz3+9#gz96ITn)tWtGC~7^$LTwcT!CcSHrf_H=U{GTG6ovAM^*y%88eci(2zLH`1-ky=NN8=<+=s|=
+N*PPTi&n-=+<0cAr$Ji~$Ql|e*Zf%>nR4zCtxAC?y<%SHHpaeaMqwipjNtxBpx=`ahtPcEfu3^Q|}Uw
+=({ECf~hjlHwQ()0U)gDdJ2dp4S!pS$hU84T@|7dY-2B(VuX%p*OPrmOGz=)rXkKxw8+3)dkw8{M26y
+AJxikN%w<kmq;AOf!4tO%MckUUO7DKAKJ^y{Lb(Zv<QK64xj(k8JbTO~Dg`qG|vdB9_}X0#$vK3S}EX
+$D4Cgp%AODl!Y+fBE7z-Ta(v&s)UYfD;hnHgLOe1n;`X5({>@1h%$|<1I#l=C)Bi}grzCw8yqC833`>
+O;R8!c8)L`cO{cQ%YO(ggn>@X_##I}bmZVHi8y++3WjSAix|zMDVyUae>l-|EoVs~CYsH@242`Hy8c=
+<Il5wJc@hu`<HX<-M%=?_<x571Y$`aYnv{_Zn;|@puKHerh$3rpMdH?K&$3^wD4j<KKB|i9j$~GoeR!
+^wwsY*^x&rdEd7guLb$jN}7J(^-|GPS9_ch&0T^YVOgwY)feQm_V)n;z|VTf1L(=G{B(0rX>4ts(y}b
+@9Iuy@BZdTm75d%t!(|nM+mG!h@gYa6Fw3%C}=dHT=u;Xjs3yHRn~DCGo4Pvx@y0Y^9(FO!N396{%mj
+-sIUb_P*Gis&?!yThm+>>^`D9mD!irJsh@g2OzZcZ09P$E;5PqgFCk=(LOmTg^ZN9#bSSzG+!Cg>n3i
+$drzp9h#%)R{dQ|&XO>Qu9M$|ycPi%e8&A)dvg}wApD1;x%<nq;0&15#&tVE|{bt)Mqn!uc_d&UKpLn
+)lJCD3wu732>WWZjBGs~6bsHslBX2Ngo?+>orQJQ}MP)h>@6aWAK2ml;P_Et_>>pRgD006l{001Ze00
+3}la4%nWWo~3|axZmqY;0*_GcRLrZgg^KVlQxcZ*XO9b8~DiaCzlhZFAc=lK#$Lfl_WNR7Pg(WOiy!y
+V_chEpJqt*go5t>})DUK_Vn^Oc7jyw5-|M`|a1=07#IcWM}q1+>58CB9V<occZ)UbOY-3dfwgpTegXd
+6}!Ehgh#5(GMN`_A#--UEmksRZvu89lSFP<u@XwKI8{Yn&Wl*4ip2}Il_lHAGKst-z89>J>_O!5V#|>
+8T;xT(i08ZzK%6=}FJ&PH$dW~3!ONszNj%GW9s^+{y;rF$Ucm>K1DmhJ{60>Xzo$u4AtIa(h<FsmC=g
+FTl>DBA;7J_8Ag>_;jLVfs7J=v8tztzy6iKll9f3K^`23zPNnTa(BoWcj^IoxOw!O+kdVBkR8ZsZ46)
+-(n?&SO6I5_Sj%{<>`g<R%5TWyhS9jEcST(gtlZSdWIEpoYL*;WD{r4kwuM=5tH-vq~o&gIqjymxXVz
+_NpSJXj7sfc#)lmw3Q7t9ZV0U*jwTrX;>e1ltI&grx-KK=)k08pOGn7s-~bM2@c+3}j`-R{Q}?l8b~F
+@q++@h1k><%EjMH7#V>%e})yA^VAv*ZMxRxX<BzK*K3}lNrM2sMB-?c$oc(n$YxxvJdeTOzk!bACr4n
+dIIDQpn!D<fa<HD@2H=$s<R~3ZGXU|D#2YTkbUvK^XPGD9aBqXTOp8381r_fgPJaPggmGHP&`?eFilF
+yc7e>*&nSekM<c%}21pi)hoQl1>ySpaifS0I%k*lF`W?*TVVhl0Prc)IcVqU63uH#?Dbn2~TR3;D=5P
+ZB~Jl!%0#>-g|uLY~;g11?gpmyN$dSb;&g%eMwR^sWv#3RhzVQg(+ZSEr94(S8_#cN6cVD=z<056bvu
+-8<Kt9nf;4hJpi_lZtC&P7(R2~9T6bD7r?WLzoFyM%<ZH9m#DIt1ekEA4P*$^kN8!>Vp|1{#3PA{H0m
+ci=5HmqB9lHY<^mBU+DT+SZEkT-1RMetfEZ2#txRGjtFt5Iifcb44a$<sclGiX#Y>#R9Zsasg4K_$<M
+pkR@J2{`0`wvs@^J3+1Fg<|_!g>DkTX!x)yjfOwjQ{eYG!RB1e9tD?x%@bznv2AlXk&O{XRK<3NW`0e
+$r$RQPkmwYY4Ng5efpwaUjokjC}iVe*lf-LhgkBe<69<xNoMV}Z|%UE;SY&K4u02?!79g8)s`!t9pQD
+UIh6iY}B<qW)P{rdiw=ru)g4|XI9wJ=<iMVX5*v>wT4N+x9?LjB$I%yW~J13h8;Dg5v4WK+xX@ps4nz
+WX*<@n6@x2xeeG%%6evb~DO6M;A12Li5P;s!-bHij!FuA5-I;A{svyzynurUrfB{Bxm58OOs0)y8Uqk
+d&o&}Ok?K>1XJgDe@xTCr+z#1v`J!VrTuXWyWQkUKUR=GL}6bE6ca6ROOHwFE;`I$vMjWLP^D|wP#~Y
+Jk5ne+n5u_WaMbo|@(35Ob;%i~lrCEx=K7YnIxN@-AV@0e$%4RcYqavnSOt*J1&(po9zTTkMdgNxTtX
+gR+OL=p?Z>UMA2&Qtfk+t>Lrj<#Wf3P{OAPx?#gFzCk_G5+_TBZ()!o(E)%y^VO?dWxGQPa?JUdH(AA
+HiV_i}F%e`!-3I20fTzyTbQ4Q5hGqccpJYxw}rdYTvQUOGGx83+#P8M2?50le=qU^jwej-}+P6KSkeD
+TbCuM-njOtAA;Ldj016AC7wi?ad(BQs&#yxsemR_mfsu6DZ7j3BaUe^k(1zXbMBf>ySf6>~pVUH|h;o
+PdpYm0EZAwTs{Bdc`tC|fV{uqTScf+1>U>U+Yq0Q*j-)<r1`)z?LJm}fS%VDC?eR&K*||dH{&^E>q6v
+5fJ{NJzzc2mfK;vsO^?_=NDW$McWH-iKEwYX-n<PzjPKrEoomHA{NTwkn8V$14=2qb^r#x~Pw?~w?tr
+kh<UWiA(^aF9``cchoW_zktbmj#46~leI6DUT+z^R|d;z1h^{{*nNu-58IVh8%`8ui0ptf91UQbK*<{
+6T``7M&Y>6YwGC7BnhA_7+pAq*UbSg~3EL$+t*o4fGx>T=w4il4?elZ&6}#h^)hb$vIvx;%Z~Nq;>a-
+?Zp&#{cngax*^POHbtAcD=ngoxBex7a#=@hR6>+w9*GuGfGyP0Z1x*|6#!H`&8ZD57-0droGk(0GzLt
+-|u6X+kmEwC{qNSfS3f7et#jTP8*yD6yc|v$=x{o@%`1=Uv4LV8^g>e-@pCgJI|AOybLk2!#aylpqsA
+_0q{A4G!2=_(x6yD{TNme_8WL<cAa1;iudqQ<bD{Yhzdgx+k?uQbz*SsPrVN^y%*afNKsHN+5|>5Tb0
+6&2--vlXl-*K=;^W{v?X?^3r&&Ep?D7=$pOf(^H@Wfimz3qB5P@QkhV6UwOy0Vf%lW!@cQSg>+vP7rb
+*+?!Ce&ElwCVTWy_CHD#3<V8x+fc*_N4lv#Y4IhTJt%mn$4H)nWSD96LU^*Kh|YTL!v-(&z~rY7%Y4L
+tbM{+0z)|Ck#Vu2Nf#_vC11>D%*cJqMe?(e6V4Gr7~1|z%d{`cdJ}(6q`C=af*#AsN}X({-v_0sqO5r
+wF^Lw5%!kA{~=Q}nmeP>NpLd#J&olLJWe=n@<1h%2r71)p%2sofv`}#LV6WASK2W^NC<4&AL>`IJ;1}
+T8XZD53kl}~nn6h0M<j<IYFwZ57%-Y+0Ka;r(V;6{1qj!Gz;yS=)XeD0y3GdFV!#ZRtGL|dTUKVkB%<
+nBvIlB=VLKxg8<7V!y-5%+Sk+Wx$HB>Wv?cNxfK96T8+8pPZA&|g(})l*EUsW7)p4318Y`YbnTST9M2
++>gNDJ(O!FmE$yEZ|+IL#W;F2`SyEfG=eHlhcnf#EC-zJx^~DgK2es4Vep`#))ZGHJK<bu31yqTQm}F
+Ma&libKdJV6sBNE*D+iV$XrymQ+KXCV*#C>I~9jh}MK!vbyD$uW=P4%!2U10`xTEd1RWsTfHiRErCVV
+9x)3PXxpE;PLSnbnz?Xg;rOLYV{C5$|6F%&I2K!qT7yTCz;{u-+^4r^lL?3gWo^JdiK>%K)R0J!6S1)
+DBrY~KmT)(uE|YGYVOL33a=*pKDK&~L!?`vcezX!k#GHM+yEyuR`KY)yyH1}9^t#@D)P&&$NP0{2pQh
+1m{HvfoZc#UPkxJG4`o>-p%4`f55}Rk3prC|vRExCS8!X<ShD*s&p~_r>UnSOhRzJ;0FOOPblMT74`#
+8(6U1t4+J`mi1c|tvp>r1Xb;opxELSTap^p#A6;^6JHGB~5LW@Fv2bBPWYun8CwWQN!-i;A0GZc_JU!
+G0+ftQ=opw;Ef%y2l=9p{7GzMr<llvnwJ$tr!8ki{|K_D7tOj@&_45W)}kggFL?uI+fDh{km~#^N8+G
+SHim8RvHGBkfavzBkmuc%igO1(n#40dS9A^ChwqZ0R$3+Bw{sRkL~Z$;vX&Fi2nJUh}06Z;g?Qw;}M$
+5n9T2SHIHK`SiWVBCH3-p9i#UXnYIlP%w;Zu$@%4JtNrURq6Upg?B^2KR$=39a{cf<Zp+wMC3uj_a;e
+W5kRQ`i=YdVsy<rb6i=sIBSWkfu^%TZZI}U8Q(EHuA?np`+CP1pTDlkb55Z^*#PtJckV8_lPISUi$So
+V8mu{ipnr)O-)N7)*8eFcd(<Visw-_L}AtsfFhD`Wqe!j-3PC!#(P8K4(G#F#wHK@C$npTqYmp_>qBV
+WMknC*p{?No!r_PS_@2m+)aG3gE|1uP2JU9Q#1ks@Tf6QUdl+*oRz(J;z=&;fPh#L5tQNECAB12O$(2
+wRZO)D%V-)*u!tVznHuq-~D_&4o`0{PX_gj{kANG;u6UtfU-Gl{|&Yg9@e!w#1-y=U1!5nGT{Qi4B7P
+d^paJuE?}qXzL^ApHj#9u1u4vri<inUTX2PTh76Sgh0HLCSEmjA-7_9tG>{c*5E|@3m4t7C?j64$P&3
+Ot(jn>!tzOFFLY8>kXXkzau>$@E-cijpu+EM~5bLbi0z6Pf&<?WCU)+gm{6tfpm-<LdRC5n1g0BAepg
+G(j`Ljqx&J)z{Zkq|04eiX7uk_PCq7UIJcWSo?iUKM`7HEL_DD>|o!8h!f+CVZMgG;W;wQ$&_lDt9#D
+@Z;D%+{t!<T5b*-WH&&B|#vB8Lfo6Fc*#}?lGy^-k_pNi>lRIF|*A9+Ts=(eQTdRfCQa`&lWqbkIdZp
+O<72ukDy+kETHJ$sNSG4+*y)-hmY(=n0Z$rMm!|EKGhqD7PW~3=MYbNJGr(YhVhH9G$O>6opUTvkZO(
+Peh9TiK}p@Bbedl2gK%#7nDK%6dds7P&@nr|ywxeUlER=iW>Fj0X#&E<ft&*k{tP>VbdBM)zZBqWiyS
+afPN$j!2GtR*HWbnuTyzaXo4DNalOPYdi+hVgAG6|Rg4$$|$}w`yeGFoWJ6pXLgp2KhAbw;}<>f|Yy>
+B$ps?|HFc4usmf36nX?}5nxC^ZoVZZmqP#>4o`-z{+ln0P4J=|((dx&i`SC%SX(B>kGDv-hKT)mHzd7
+EGtn$ajRBTr=ZgAR`!GgNc4az=MKJtcPkz%+BG!0z9eH=X;-Ee*ieH&)|H0zEwj4*nW@fK}1ZcXG8S4
+d&{S8u0Xk$3Uc5h;%>?cystB4)wx#)2oW41jB=Uzx|I!&AR_QfuKfZlR@(KUfZ+LzFSXs~GD%<pcmpX
+g+h*I2G9m=r6c-_$O(%;1)=@^LfjJZ$(D6Q+C(QYBDWXuwg&JYE&H)W{)u$een_l&$No0;1M}~dtWye
+%V+VQwKuxTzBa@=}9Pb5~zRg28(k7H6v+V^+BrXz4*2rFE1CNu0m(&Z#d);3WDzXR3Ed@l6OmCDeNGC
+;Oavx}u_&xvrhLzO?W<0fS9B03telU+ty=Z?|z!m5J8<zoI|Jm3}2m*8)&Ufpl-lOy0xJq5c6$JJ@Be
+L&3GY}%Dc<EUw?&Hx~f?Gd+VPGj}ybPkLM5#SVT1la!waAfae3MD5911mGWy6ANjY-W9Dz2<h=#IzML
+HI$rlcOSEio47i3`kTn*4b9R~by<xZqfyPVDvL;NQi$wP^JwX2d^Vo^G(Hb+-+jD0zxs6f-=WeW@jt=
+-fhWt|!ee%(9`uGo?!auC1Fi3b%b*cEpq#mv;P<;$gA8mbdUteth(`$NbA9y+-$mGo==GnYofEy?&gc
+L?ygYdlyv3_V#S!58NUb2W7%ve46!yZ;0aNXBTdftI!U2``n;xkp^eu{S@*ew!xi$NaG8RrjoHb*Wjy
+JwOU|qws0#<YUUlFy(|JP#n*$Vx?iP$~f_&+LatAJFst#m}1Z-?=OGs@CCs0`b0A(WAE65>5p!x$5R!
+&P4~MkLl$VJGg}A~-&b6ZyoqxlG*-_6g78J3MT!m(k(<Z+5d?SL^T4;5Dl_EyYvfKasBLsk)Mev(`|(
+B}w;s6tdt+NM~R!0M*Ony!->h261aJ{+Xc~y|rCnM_gp^*<m|$=lGU&+>vOuqMNpK$Bsx6M{AqpT9EY
+xyO{j-!x()FkAB@-Si)X<RQ5Cj@490ls*Cx!1>jwmtWs(%fkv#)L(G3*C(nq7R#{NpPiQzqcg$G$?2_
+)wF#7`Wz^=a+;8)gwu)$_2whD|V&f=8kTMW7Nh$<Y%Oy*3rYxk;JuC|rx<X98WIJy%>JXVLchT4&#bH
+KmW9meS#=?u?*G}~RKz1|x#-}ig?3kaEFlcA@_2ez{hG=4ugyX+6}zfK;fNkJor9mfGAOFitL^~#vTh
+(q;cdkJz`NT}59T{As{yBFwczs0f3Nxp43iS8Ku#*k^0iND2F@m`*D3HZsY$d%ZZnQ`nj)X>;TTd4R~
+F*-VVjtN>;cf{yoI?%~QcQibYlzh$==jz7tsOz$Fqf-<(v^9z8DYb83?X;EX-wESu#;b;s9%`FD_36`
+eYPd|NO!Eo!P=MeWBxB6Y#E*vNJXMMP2?jRG3Xw1PT-cWR&Lx8Bw3f4)f%s7~H%aifT<*o(r#nv8|Jw
+^|pM%MEuVdPmUs}#EFCJT$GObY?Jo~L-((F__Z6o?gQ{8ZGbdUZ7++Zn+ZKauEb13-jRECB5Mqp6nos
+0&InwC3$U&~yd3^fdaOf8kKdF&Hh-@^<sEcOV$_rmArdOm8fI-L6Egy2uk!?vdFnfGaH_0jbH-n*oqY
+511`vyz}wVt6+3dT4$MX{i9UtajF|IdkWT7T0;4t-wWXFI9hQX5U!RZ=lk-@Xh-H{_Y?^C#9Zr3lbV4
+Y^dr_)m;Ji40~5xO&#L#o}I`Mmd;X*CUny2xZ9j#dKzK(9lxNW)fa@E^rfkk9^&@xTS{<~{Pc&tDiAB
+2@DM9{KQbTovf9CXwRyUg*P>aCo8XS*qHgD2xt=qH`FW48c^&RWd`)>;rgSHgPOYI(E$|EqK&^X{)K#
+~VkVq8HS3FMb^1}mdiF>hiJOO{Pw2^t#UjABXKq)Ss(_Cru^)1uJQd^GujcOpM6Ek*<4jO|vJHiJ4D*
+mJD<6d`ZYJveoL%=>WKjG_H#M!HGSn=tKI#fT)>1VNEIjy%bAzlrvP0&agJjv1u1FF`Z=;n^<8J^84x
+-+EkXM5TPex?t+@F%=A>6dmIZ>m_&t^9h*T0R6D=DfmhC|pBdeCvGEzm~)wYw9Ybeig~E>e7UOat#V5
+)a5YPchs~qhuxF4chXz;4oljB0}Sf+D<kM5u4c*O_*!eGojm;<khn)`D#sd6c098Q*_)&HXU9~pYyq|
+hIdOolCt4gF_I8L_5ZGB;b>LTZnUI^i)K6E*2l|#q`+dDjbUj+ZuWuvuzz6VN#J(;isq)Om($gKKX11
+Pj{4tWTPscF;{>?zc`<-I9dHM{dt{m80_-{fUO`$JMi#!igssD{YgO$As6r$G|o0(}eEw;0dz5fDGO9
+KQH00008031s8R>drF9>6640FZ_N04@Lk0B~t=FJE?LZe(wAFLiQkY-wUMFJo_RbaH88FLPyMb#i5Na
+$#<BaBp&SE^v9}efx9cHqzkl`YW)S+8TKxbI0Q(U&<Hnu11z;RPk6oOS5yiREnV}$l{tJb$nQ(z54$5
+uO9#jfRy~m?$zy`E0wWHpwVbF`h{+=+wFFyGAuJW%YtN+W`)Sh4gI@JGf`%79L-O~LllUx*llF)bvm<
+El#6w6FLSYpg96&EkCUK?9;BFEO-1k!L~$^Wr6|%0K$*)d7ij|h!pT%@qhghog(z0C1FuB76fi)#-bA
+s?JV7JCe?cOmH6jxvfR79cz*Ed+7+@dhD{giGClNP6cpu!!&Nx}fuh?;&K19hKA^@$^wFKyZ+QW(W?l
+{ekSJB-{W&%)pkXau_SrD*=Tn1%ah{;AK)9F>GSOq|hRkX<oUxhkAPtrn!!G`7tm@iTsOTkCv;b{`@#
+5UL=2ARy$_(1|Vo)kQ~Ls~I7CJan8hzpr1GD3&4h+tyS7BSmoDU7w&s0Kx+YQX@J9`!QjNHSQcFOpvH
+!U>qNNj&IS0a=%ML9@!_|0<(QI*Sn$uk()XxrsKK20<LBTe;v#x*dfCnn8cXFRDwF6cQF`!Ak?pVfs;
+8=0L7EP413?25V>f&{NId>mY4c=|<ADad~b=H{!c*Pho-LSjY#N6eVD_6GU>MNS>FHxj6?47Gk@K!c}
+Jjs|LRVd4TwtED(EYAErr>MRVYxMHx#^ye|=LT8Dgv8v}9dW6wm=L^^sfiQEd)Bi2KBO9l#K0$jzb@Z
+YB(G<E>Ix{qL8(`CmUdYXEkN9zWo1(`%*@?ujrZq^q$3=4DStwKB!C4ZM8j9Q$Xbvgom)H_%_&j%_k(
+#%s^(^G?bIq^@S`9}o6Aoe4I<UI3uC?ANK`U+(4sMGlvY&JXG6hMqWC>{vY1+82l=0RQr*&@n;fUpO1
+Tx{4$NJ46~OiP-D_=4;DK1~*{L3-q2w%Y)`VT>%ucAgj{LM9-7fPrB5&WX&LBUjOy7JVKE|DXjy3;^v
+YR=nVe%QWLnp2;9jlfGX61+8=$FOWrnJbAQ$HPAd8rVsSjJO!CB-)RvCTO^J`nZV-U3cw4E@9P{E!Se
+|4@jOn$d%Y^dbhFDq7!{%y9*K8vPrf^b|9xN2TKtHN{nzare)ket{F(dR00#nFtNo7*0>j<Gk`!{$7t
+2hNTnbk~b_eVMXa~toY=F*4=6MlB2~s2=SRvrRv?qzMEVe<$QwZ`r4Wj^Hf`|*tHEgbcw&fD`cP@IkT
+HUGY(LL%DI2ddpgIMnv{kr0JkcPl*A;RfHqcARMyXe<(w2pWbh6W&rKw8T63Ew`leze4YB~5Wt&f_Rw
+^#!mLGILqrw!nw9B8(c$=}#$&eIPDCiC_+j=QNf|z@|tmz(bLY#@?>dHK{9vRLu%Vwk)#*hGzCyq(DL
+%nf9L&-^&yQB~BBVX%XS<a>W5C(1JN|6wQly0puj0tz<n)zk0RRt9%7Q4tbFYC~>Rs6pg86h(?a8GlK
+QNy^7<yQ}z@dA4g(3xtx6&+>XR}DsFBke;Z$nE<|@Qg}=Lf@nt;wIQcvi(BgJ*J^NWqF2&&bXYtec`l
+2sJ|KsL%G@XjcErA<<y15#U;Q9D^c=h>WeEmVZhrZX7nYbE%8qWamY(j%7aO2Sw0e%|Y4nM-5gZJaB@
+$6?_x6ASD8ev~fZpA>{3~p!R;peNtt+@Godo!7i0F4U(eLcRuyoHfQpGMa+4@QP(V)QroLrgyouC8!6
+f;adKGr2`v#c*=-^X>S<$C>yzxw;s^!}lY=aPa<W#KXY^hgXB~r@putd>VWhQLhO=;(20I##DUyIKsy
+`?g0K9&c>5#oYHV|J-dZJ`!M6%S=If^cslBf!R>eoDDyOLCol|>7<x?z5cItsF(f3vy-Lso|NcB3**I
+N{23G)ciU7<GUZ)Gj-ZBF|_Wfmvwv_KzN@Gq+SNi;Sr=y;ua*$sO5OCEKvL^IjGRu-w|B>e2CMZ_=&w
+K@1Jg)u%xhIS2ue^RyWMx>rC{`ehQ6%UGTN&JEa@k?b4F#rA&!eyECCFIyj0RTE@OKZ!tL6&4J(~<CS
+3YPbe+YbfJyUIcSGmn2(&oADI!rTpiMlCZ0Y)}gRP5^ChOozqec(U}_%T>1v4+>974t#T%B=8{)CYQ|
+8MD1VFQa(j7jf>F$$gS;6F&_608FbwH3+d&kY&Nn#{vBfn272P5D^wLT%t5g?zoY97pK9(590{LIYR(
+F5hdznArUc9uKvB;sTZKli)?o$#4B;5?frZs!)O_WXWFcJNBwEuywZA#K5C1U<Y7mC4dtc~V|p{fsXh
+Yrl(DKoh;wnBCbAyP1C}G>KlkSF3j)qPbWX63#zDXF^@~o&2TI1k|L5YDZi@*60<Q~vp9S!oXse(9+U
+dL!)9W#aTCnfIGf1=hyz_A|_3`1km}MnEPeGFV$asGJhWJqZX*2*&W5}CKw?SU@>c==BnNJH=o3J>jc
+S^LKK<$%?ge?PhY#if6QR}dh2SaNGT7*3@)LpNr5$W3u>@xtsYh`#`U~9{w00TNgGa4FYX%K>91(iy6
+6YwFJm9OI%fGtuGv*4EjKgZF%gx_nkNjre~y1cuKrHhJ#00IMBIV{kORh9!0AdxiZTe-ARAjPP$W9uJ
+RLW}{@T`6<$Q(wWaUn(PApxp&FG#Qp`>yX?*j}n1K32wohM*(YlktVMT)aMZm3b2sK`JcA1$w9j+BsI
+-*cKg_lMEa7^ewRW^Fr!)jgUUyg;O7L$R%nlClY(kj#6ocBBBeHPpeLZf9)`sP3=V!a>86YWvi@>d{U
+nqwhU}g!*wvd?uWN7~15*xcJvI|!U4m8SVt@v-+_AGuEJ!;tD#(ngaLaLC3Hi)vvIL8)V0RjAQe})V@
+zFftWz*bvm!^v|5iM~+RzbatF7@I4YcNtX@G7E^{XZZ$puSB28hOw%LkSZgWwf!2_PE#a!-~s%&@(yg
+LZx!NFYxc*g1D3y)s(@taXR>f(Rr=7yeoKsF3>A+h1RT4ECa}&e1HGG-fJq(0G<t5y_)r2qYVd^dwLv
+VGy(vi!vWBk_hIo0@IV!>p?8^7zUZ6ajfPcOk032^Fg7jGBZoP|sQ#B*FvI-!SCipS)A9ct!3<8mKmF
+m`jzRvk1TP-^`Ug-t;41^&YWZ|Ax*UAIn)$==4HzC%MqYm11mxY5XPW{j)SnO00-SOYMjMK{lt>NF+?
+osJ=3BuDbZpWs3R^p_A+})AqW6#S03O|+eulYBQI@lLZt7wWwfty!@o|LzpALMqr2N5X>c9K$d;i1ml
+MmJ*OuYY`t|#w)&|Lw_;jXtY9rO03BO1tpH4Xp0d+Xm!u6{l_ef!<>P=0Rr7tZ&eHCsL6@cr;5t7>$8
+HaDn#&&Ag0`b;i*>KylVd?xQbb$<IgK8s@>AM7PFd*QrZGOMSv{?obr1^em+d#aiswEW>2ZJ&wz<79u
+qN<Eh$_OB{g`R{{VSrb|zQJ__xktVLZNKmE^?@mz%gE5()z9tJU5NLv=OVp=$G{7M>foBh>Nvq?6OMn
+F~VFnHl8jdo?AlDY->?-~p6goueRj|;O@ZMoaSRdD*($%LcCvUwUzUla292aSr#y+?;>nH)|=PRhl|4
+qaoMQ%F6XQF2l=pG*4C<rHxe`~*dr$T=%e)aE!`k$Q+7=NoE4~in|f!zUKnN9cZ(HXmlEtCBPI(T;TU
+x5JZb2mBS9$M(p-}Rr~=;#p~PoIb5=~Hn$eF~1JkK;%j^>iGm`9U15C4PFNM{)F@i>3c`JfDW>lQDe;
+U#bpI#&kbxwzL8-q_dDq(RxV37-CQm|NWFE_i}f<2?}ti^|38EYK{SZj4l_58{o2IC44*!63G@Ttl>b
+=fsLxM6Y+RLk2<WPBPuqq1MkQ1_h|U}b~L*kTu*N>D67IYHi-T0n5J#vA(yD16Yy=;24zvi&v)W%Stj
+AxZ!OF6+heqBiyR%I<l*);of;vly%asrvXy3+0qC@+5SJS=b$#@veeL1*44*q%^u;150)JjEmw0|pe}
+IR2SFC(G)s>mE46X}l#mj1k9G`GdZ93D3+A=R#2jeINY>sgrRP|B?Jm_SY<7n2XD#Ychc&HJ%#Bgf0i
+yO_{h=g}13!4B(RcDNi*!^K1I8F^8e;8p$V8|>3mKZ0LcMw<Y=Rq!OWNhf33fFaNz(gWwzzYC9T9)IN
+x4+h1ifAn{KG1*-(^T(z^#my(ZqklNMczou1fje&K$~<W+O9APY&8F|fwA2|(NyE8h>3@3`q7_Z#AYA
+W52IYf<l7(u$&hBm#yx|ieGTZS9SBV?i1Lc1hyXo0XYodZ4}<YFs2hYqQI_servWCDYjwhV-dvw!gBp
+#VyrWPPsbrrJ4+k>wriOXsk-Q5Qi%jNuuXPT_?iAk~8t<s_BwUrry`M+_kbs3jHZPOm0}0BW-u5+0Ef
+lC0{F`$FX4_IzV6tj)aAj+-2i9)?P8-H)E*Bp_X~<<6w?df15cf6j^KnVf<b)#(C_8BCJt93mj<a3@?
+)+ZGn~9&%7vZOWI2R^wH7C}-or$&fu4^^sc?BJhGH*xI(G2&J`|@UdGioR4qvRaSbz+Lu4R=sYho{WJ
+6sZRP{Gqvro-A6w;9<ynj1QXvlbXNn7z;e2fAD<YUfWjTuGi2Jbhaq<Wd#z5><)fV4Jh?XLF<2&{w3f
+qR={9%agrBk;+z80d>oL-0?&Z{|5L*AT_JOHFqp1;Rj|1opp}yG`iQvbS*vOTJ^H8WZ(6mdXl`owql3
+%8SYy)||5}yp_E!3bsbXq9c(kBpY4)MkwRV%H2-836C})MKe3%7`2QD$FZAv!M$CP|@Gk(1$TI3}kG-
+mR3-U4r3f_M0UXJU8=mx72{M|qWAM~sCjAYQ8)QJncpjq+K|l>c`tJEE`K`rk&)+1vqW6Y~Hy4sERe_
+Y|9z4{$H#1{odC8@HG-fv$KCkU;v$B*c^ZIC_wD{7lE(Al}4>;p+v9COX?xskky}Xt<E_Ac6w(X^QG-
+KM?5mb85573I-sUuZhRyYq?G_s}&Qj#a1O!c%E0T;D7UA;fbGRu<BFS*EwfVq!~PZ5AQm*!>rd|hf;t
+j7#6sNHkW`x&u)FxarFJ3?q9GG_qW?)oGFY0kSt$#y{5EWJ*KK-4GeC^$CxD^6wy420km4=jN|H*`SZ
+Fu9(OWD)IzDW#p@KfR#a&{q^bMDUu5Z~cf^O_@C;U|cSON*TzqufQ9A(n?t*NNbpr@0Ou_aD3wV<*0g
+0PkZAZ{AWEFu20$RfF<uYFO6-I_uz{g&twUwH-UWQd%#!-my&YlM8NBez9qQHu%)Gy7A(E?kia~*!`F
+QOJ@&0{+WW4c+@j&@fbJYa&wQk5;p2Ttxk#?+7KuB0q#rIuCMMFIm*mP3&mp#CAVw6+TuD8_Ymz?Q2T
+04>Z1LnzA(a9dD@g-$YBNduS~Q6=|qI!P=8m9ww$K{S*liDeC$W;n#r0H!k2DCMY&iTm-c%ez})q&K(
+f9^4_ZbjtbQA&nL$YS<F&U3ed|8m$q6=@1#5m8k76gWcMVFS9{jH+ZY8xxd!gotiP%K>`~ht2v%jj1L
+Ac8#M^gV0gWyX<O@LQK5kF<gmPAE;(Hd^Qd7r6S-6Y$08NuKTRl*RzY$rS;Tm0W(#5aI`wB2Arpv-{W
+*)jg5}~w>lUV&N;cboq<|GtsZI4B3YLXr8L<q)qFw^x$N(1+PXjS629u4pfllxS-pCC&xmWLxF&4~VG
+E_A<F1pN(_@Uq(?zPf)&o;OBpZvOsqcB3~oVXQIJm1WF+eMNz3-2bCN>wJ9!58lgXjDzZi)7MQYy&2`
+>PZC+b;cZK=TP1s)5L%m8Du0JY=gv}++KUYSm!1|oF{!-kX1w^D)(%Ynhp4>t0D7Y<M^DrlpkXMsRZk
+xB$J{lj8fe|L+`5UGOpagRnbe2;;)u42U4tHB|vQDT$)oI`-1eKV_#cb)*GPAi*!wLa*@g$*ND)=@{r
+_?>Od4yC?2q~A}`3dR^?tnhW330PHSbI%|*_mO4h4N?$FS|NESXwF!5|nl?H8OQzXKeqiJaj>G2eE#l
+#z!b<(p^y^fB0Z|nz#DVQUfZNmi?XOv({>SCx?vV|*HQuH-S{gz>?UiEKo@^+6AIC3~Bh&M@f7?>*qq
+Wb#@JT<twxvo2CO{I`-r>$~tt4?k9ef6kng~{R+0BOr1@6{;p_ucm`0Z!q@B0)`bYj}HW?xnD9u#6In
+2iZv2srugV@>b&Jkv(UmdYO2q_~6|}&`GK_dXO1a8WkD5_U9$q7kid#$l<Fk8a0%$`oOzeZ9xSXu|ZL
+-vmQ~7ZqY%=rLjWGD9eE?1PhHWqc?6g5Y160QOZX-@%4YB9iB_9Fyd~tL?H(~&}h&^#KrrXXKqpUQ4u
+Pv(}?|NU5uv#URokk?|mxj6>4f!1qvw_^S<~yj-3a)GXR~&p3ACC>{dRl^<Wu-)<lHO6Lb7=(;#FxLu
+_w}T|OtOx<D@aPwxfn8cMUr0k&rjshD3WBMg?{KBBihi;LXQg#`fEqMB(lXy9yKenbhu=c3DT2TX516
+MtNE#UDk_1l>2HbBFzOUek-TUU`%|1b*Mp8WN10(a5rYWZEdMql`L<15Xn3qp%Jdc_zW~wH4Uxl*H}u
+V$C*SNTI0OUn#><M&(cSj`o?xASL1$<VtvCph{*!V;ij3a)CvWmaP<ng^XU$xj5-#d^&nSlM*W}WM(z
+vN9f!2)oXGM-U2>p5-w`HHQf}*;9R6YH7>nw6m|PJz}vkRKK=$hbr5ZeIYpD<PotT3R^gG4)nTLCJ`L
+eOaxEhj*32mffh0q(i+dW2bZ~~eU%^HOQy9d~A9GxC<_1%;I-7t6>mGqhW-M8e6f%Tuz;O|(Y{1$j^c
+BmEB|22$nHS~gKKJ%O#ve*(Nx_D(8udjtn|CSNxNPn<vn4Fa(xWq7gRAR0EZ2ADJ!2}uO1dmf2n|{CN
+_;@yQ4B8!1eaYYP?q3Kve}4(V&MbP%8s{M__S4tIbz5ed2-)ZH8!ZjvIW|Jg;y;L-e16Ou`p)C7*1yx
+Y<A$WA)%u#Tw$-aQy(jaFk(<<VmQb-a}vuJ3M|s4Lm&rObeCW$jFT~mJb@cO@7H04Aiqc6h?EP8B0`l
+s8>nF<!>oRqm++H>l%mP?A!dhG!v>4EZ=}p-6>l4+Bp<QNcNwfV5&h_ywhjI$<w*ToR6)xgy`&9EaYr
+ogW;U!sn{LuT%e2(OqR|G_NV8$R>2sb)-(a&R&gu6II!WT49vG9bUNWSkpj$R2zL~+2xz6F<E+Zw`Dw
+;GFT#fhKb#Jw4wT;kZg1y!*GhO49#1IjCUG0N#&Bb@a@aDWdIxMPn0S4&uRd6qB(~Z=D@fY68;;+CBO
+@g(oUnoP|maSTVS5Gm=QmK36Veqy2(1>U@9^T7c+cSRy%eGl%L2is_dv+@Ca!-g%pIobQG?wIeX--9!
+S{P*|$gmPD_COc4&1;jx4vMqX<Kjzn@aI*eo6jgRN0!+(`=xR<luLp!p@{Abm`6p<g0M1wz{UXGYo4R
+9bT_~Sq7r``+08k^2Vzx;=Uk}|18yaooM>lgXM}2zOJk~JM%xEKHg4pV(=i$@;xt;czMU2Tag95_#n9
+j9&W<N|6ml?>(0(Y>chf8Mi)V)ynBpJR4KdY{r0Y$oLYj5eE%1TmcVg`@hiL3*d4yNd&^-8pnN+-c^X
+BwK98=xuvMPoMVw~KrSxJhlWWXbrk51d71egV{5m8yN7}YP~uNaYEMpPd`mzU&V?;4yyMq69ir7f@2R
+L@}s9H;|Z^xes~|MBe)r{913AGR4t*#)WtOu)_dXbQp#cu)QIjW{_lfD7;!?)9tk3p<Z8S6%z;m=p}?
+c?>dMR`G~H30P4HSbU}Gws~V>JTOfy1KSbG4Xs31JLO=S7Fc21b7eT6Gq<EqI1Pz9))Nn80*J0&w=9;
+&KRm&3A>yGqc9CLw;5EQ#CMnt!ZD5OWKj)#Xy`O7*pxaxhIG&CP+j7o|GVkeWM*!OZI6+4HPZuh|1a%
+p$OAZf%mZaZNA1Q5_dyg`z4(R=jdwhyqhBY+ubGY`Y;{{*c@oHuN>|LS~UtpK$D4BWD7o9ssMJ+}7><
+)buGeq7Da$ry#<KcodC~ZH`>?;C9XF?hppH0$9iUCf$T{<#p_<sRK^Utss$=NL(!c-Y@3%dHrRL&(kO
+;Msx=W@9x3P&kart7=cP~5jvQ%ScLO(-Dr*e+~Q%4YZXNWV!kCF%`e7X7+r<K^4ZT5`7Yh_G#|Zc@px
+9c@zB$LW3NZ*{!ha?6V2aO^*G-*bJ-9_kvHnC7lw(jFk-Ue#2)Wj$Atwxa#qbz$v{%i9vX;W3<J=@!+
+}iv7pR`!Er2$)TqtU<PpRu%?>=wI`#?ObFBm@7>DG7l+aTW&G&y^*$J;Sd&`FMLQm9Nt~mN)<ccf{z#
+%IDVwSD7<OqN@<}lb{lgjWm3xTsyCikbS(RUD20K+lwRErOD!pTH&k9|Yqi+!MzJpaLvyg8VtYeZ38K
+N1<;G(o~wp$%a+gUk(c5_MF8XcdDlO`ZO+;8cvqplTlSnQypr1Nr_NB=PJs%kWJi3T6jsY5z`+f%*jP
+L$_IWl!p0qFGPj_E8y|{Q8%(8pN;ex=?1eg*-#9W<c;0f^d%N!wUCePMW$|6V_`qx%8e!x+>w&QeQMk
+d;Yb0cTV;lV`c38{k1RLPZhq@1g7q~_Xf|2fbAE)9;AYTWhH){bb~)n7G$kL3<>s_HnoZF#HAc$UE9`
+Jn;G3>L}lifKdjKfjil0dwslY#U1&;8=<?mLcs-T@isqMhJuy|6e4&BTR|zvXf-6`1cIQR`O<yPWR&T
+D;>l8H8&SIdKiSha*lL9J=Vw8oXC`vJA@`W)WhK#R(q&f<9&jI!^-AcM^Slu^^0dyAuI`NCZaN~O#^(
+pcjK;ex8jy5u_2yVT;y7E=gk`9s$r|$0@`-L7|+GSk_7<T5pWMd7qa~OqVc}U8Ze0pFOt<v!LfW-$6+
+sp-T*NrGQTGgVd4q=vu&U{<><caMy_ZVlrE>G|sU+c8M3#HJ9hLu-Ina;rmnf7V{=u%M8I2PH0+u%_K
+YqgaYw)L(goON+?lsI5EAosy>jH}y=De>4Sk-<xd;R#-^%!0>|+Ag1tF|k<Zf+0VZcTO&U>oH-|7I=#
+Bjps~Tb$J~!A>Q&F%rT!1&%H5xX;M*Py#-R?R;tT^6g6Qf48oagr+T(BbFH?F{77{^*(myO^DotJHH<
+qO#vTjCZ}g)w4<40@J?eh{C-n+tcR!|BSm2-rB}`waS)L)6HETRc5E(+qo^Pwfp_GGmiSrVE{=)T2{k
+_aQ!$VEHxD0PL<5HR}_jx|Ea>ha{&lG79#C}y{RWS#7RmRI7>t%F}(xgr=))h#<7(LHSFyDxl>*Rj5m
+)>k{mZQ*IR%L-n9`2TTGBaBz10<PRoI4yTtX^6M=xlN^In!chjN&?sB`9f)7zyCNU>eMrW2i;?m&e?M
+AH_+Vn^0x&H)0nWj>7sGCvo;<-EN1f4lMi|Ui))Vc+BrNsj#P(pcOG4!f4`Sp2q&9T3twVhI@9`CL)h
+aWq(J$)Y!|`VD7rDF}$;H&PM&k<0TjP)8g|!u6Fl2qo#^N(<RioQQ#^>cxZ#AkLz<PEU`An=j?8U5-m
+xwV6c``uZ%VyIf8~lZCjl$owYVS@hD4DxOo#gt7MhN3!Ue$63+PEU!6Q+z!IW0C+rp8VakK3L;4R^%x
+X~ZXF~YaSN!d*nbQJnurz_4g50j(4zK%M>;bS1m^hbVx?ZPr;9#mOvh8f7*;PlIkYm1RbEzrQjkaLXQ
+IHq(s)@+A79!KZwH2f!BXcb|x*Ooptyp8COi1COuV*$2K}{iN7IfcfZW4qwzADAG<J|m%DU*}&#gs3-
+AH)UHz_XjpJ@JVgs5zQWB-#t-PGfQ*cUF4Q;5xUxDU+3|OJcJ$&piwypy{XnB16{6NS9l&f*p_6@Krk
+G`+E#{e^+dn$&IA)9ZgNnY;p_yKta6GN1%)J4SuXctj$n+x{+BxN1b3hlxvk=Y2?~hA2HcFo;2P%Y%)
+5Yt4Y58mXKV=!JYYW9mPgQ0s!4xjNigYs&hUAo{>sSUM439H@+XEJE&6uLryrxBpFx4I4b?fB^KQftS
+S~@&4Czn0!#q;Aj2@e9?6;0&9IvaQCYHcA+yR>whLt1lI*fzZpfOvNV9*3l&@FfMw^%FT$dL;sn7g5%
+Dlt7y{};dM0a<QZ1Kcd$=Gz#)U9sVX{>}TP>0w|CmOX(qK4HrlL4N81r)VlMqblR#VgEjNvgY_d4|=*
+T7n9ohUjgY-v32ZasK2lPoFbN{>Nvl)Q3*^dTURa*Oox-ORKClI;_;i=$7M2%>+)x+a@-SsJ?&}Jshb
+O1r5VS!zd94;0-GXLBe#es6kJIIBJ5ZqNV#lyoXuc6xlu)#wI;{4TXX5<H>P)uxIA6HSzl=B--gHi=J
+t1g6V8@#}Uy7^^UC3=iO#jcAHEBnqSMiw4e|6IEUm1tDPMGo%%hi(8(a0?q56T2kt05ZBrw59_#*U0r
+inO%vCt?PTgqXv+#J=dalq_H?($t2jr7OkWYRO<O6`83)Z|Xv>hzpV)}BhdkD-IxE}Ck+Bo7f7kHRSD
+!SC9X5MP6sp5ZUr?q)W-&kG}-yra`6Tx;@|M&Q6c)h6c&67vJyi%d9fho^!oi3z4*OTYRCr=@Pvq%OS
+Z9w}RQ#t31><&%xu`jwD!uGtIb@kyDXoGXk=6n-mcRBp?=6;L6xy2%?+N|!@dTnVPL9ahV!5?-spix0
+{1xA-NkkpCPJtAOp0m4#!R`Auy$#<vZN}{)QRIBkCiW!4bRBe2Z#-%NHZO$Bc!@6Lj{?g64sK0HauHt
+CFL$&=*j<E>VV1?<6I2eGwCc~wq`u<*@T{d_ctE40XMTA-g`a>JAfeWz4u#QCa6TkgdUq$-cZ`#9Gm!
+xnJ2tjJ~NDf`dQAvOXqZ?V_74KJRVwhIbc2BQ<_NxOe<=Xz18#+|xRQnAbP94$VOEwNRxR;GeBlo?Ls
+@~qzP7bu3rN3ej0&v*Xk<*n7@2h0U!)5RdKN<Bk#ZA#Atx`P+B<>GgEXr4*<2Evj0dxW0daZ7HGXq#h
+eCml`;RD8R&u>>-jxX+|+1Zn!i!qEFFIuMB=Nqs7U1p3czi%NG>+TDJf01zvG99Eqd(363YnHik0i#U
+jXFK(!MwD3!(-!(55w|wV-qH+f6j@r%@iV8R98UxylC4HaOD5$SLnw5gLiOFk>6M;@8(QN}>9YH%Ln)
+>D9H)vbk>FnHQ+OB^KfSc8g_x}h)_u%@+^!_%2)ZZgst}F8L*p=;B_`BTsJ~oxGZ&=EXL?;eZz%5*);
+^9BslK0tpN(|0fNRlYoESCPfaR2r`exrrC0Jd<(e2E?9sT#u<J-|iZT=`BM|F2qv+K$ANR4IycW3L4+
+nli@M{(QY$d#4Z#EbAyS4Zn{Fd151xS?SASRmTM_tR8;_7%_a+vBKP8R0EkcHYWX#oW*~Fhh0Zo~-tU
+%K6*bGEm&xH$HAv-<CvwQl6*6Jx)W;3Naw@U6~5`$}cJtl}g<Fz*1nDK)A>zIQ|xKz+nmeNUPp(I><;
+HoNmuCZZ)HNT)TWk-*cjtkjSp;FoDEeorIY)80hC{FnydBoAv3=8EEWSWcv6Dq$yUVY}Iv!6hoCk20A
+aJ>8dYnSBcrUPtCQ#9ZSj2MsTwhmdH0mbj>&vm^_$@xR1+@Y)&+9kEyN~vAFP(KWo>o^0@W)w9W65TU
+V~w>B#C5l|P*Czdq)<F<X6EjP|tE?Gg69FWn=Db}qx}IR~h&lsS)|PA^u~9~gaUW(7`uB4X%o%f)p7S
+#=??&Tws75cC7d>Q9=v6=WcLjK5C^3?%ceb?i^KXYj~miC5j_*C=<=#<|7*%MPpRbZ*&_)?D)|{<IpF
+Y81QzBCu04Id{BH8dr-053omHfZb@U6ApzJ47!WcW~*u#hwN1aeLo!AX4S*nd+Fu(=(Jp-!>2DO(@^<
+me4%jBxLc=!qc2LqtgSJgtD%V|7uA(11U|BuXWvyRDmJdaBBFyQeF}@Xcja{5^c`Zk79^V4I}Prxj$s
+H{+Fz0J;h>Xu-`EL)&J7Vwzu}iW`s#rth2InABc0ynh<rz^_^YY?YrT-@W~$8Vy=A~w2B@mW!Vj_Y8F
+l??k^0rK0H%njBVh_j7yw|_cwxPt1$TFH;mdTHyG`thFWv<7wqY=A)y;K$+Rf=9R7Fdcfz%;*%FtA{S
+0r=eo&f_MN>VE2rBsuA6|MVxG%Wf1;siur8yfI+nL1O@`uvJQ4=mi9(T(`-+tbQ_NBK!#Wv?454Ef@f
+ini|SJ+yV3wGp?O==Ykwh?<f?a+l(<)Yd%o<UDrK{5GtL4;b*Mh8U0PM12jNd2+sq?ebCgZg2aJQhaO
+)bcGmt2-WQO0P|YP*;{z2@4T!{+_pFEh3)nG))IH)bz8A}{kpa6z46*AfNy)-S_)q`Y%7Y#AM+4{^Eo
+YgcK!=cO9KQH00008031s8R?AYzKUoL>0J$3g03-ka0B~t=FJE?LZe(wAFLiQkY-wUMFJo_RbaH88FL
+Q5WYjZAed94|1Z`(%lJAcK3K~Tw%=(gt+2O=t3<bei<OO2D$Tu}t{iX2%)C@#xgS`mu=_nX-VxqSJYH
+vC|byYrsed90tX^~IW{BFoFWm^Es@{wJ*jVHgHChg`Cw$eIEWqEtLDC97(2pUYg7ykN4aDp4!87d6}d
+{Ni6*+WnM+Wcyki*(q0tybPMUDDvGuBIeVxsM6qFt?ciQY{5$gpA?kDgNeP}Sgsf^vp|15LsEi4$#+O
+7M;iO4OqCWXSLYQ2<O?-JX%#ODc75K8^rK{=TSB>HU?m|baRJ!vtt7bHTjF2yC_n>%)hj<%1snlwKzu
+ss32)yZ#hRCQK;l|$*&euRYLF3oqZluw2>M8(D8vbkZW%c6I0)9AEpBhgpyvdMZobmeUGezxGK!+x+h
+q$l2{!_JW;CtgC={@lZ?{uu&kl2Vg-Frkb7(%+I|+5kj~E5$F;;OYPomDGjuO>cRFepTC}Jhb6UPB#W
+GRf08d7mYTW63lC0HX{*J$a`KS;=~Xmj9-Ob<XDG2D>OSu_OEN{Il90!E^RQ3S5E9%yY*G}@oYH4`P6
+uq7Fdm53H9b8mwQct##hiyQ-CE%OY6=Kv+0jS?^b(V57GBdH@E6-G9|AhJGcz5nL={z_ZM1Cw18I^VZ
+vAhK=<dK6al_q)}I5Hfr}C6kpxo5V(YWBr8IA-eXsnLW>R!70c1-r<o&tr?ddcAk;xA@y;McWd~)0jX
+l`V9YMC-eCZJjAK@v)j^a2nU-~76n5TxZYY2MgWg>qgjC@}N<EuXicEu=*!b(T45qYXQ(8J=myU>L+u
+&BI@|0tMv~JU+K2u#C&d(i_@8jo=%|Lg`#X2&RWZzJhND@j&lzI71$1o)3I|x*L)<?+!Xhs2iN}*Ehj
+b3|I*P`wLop@cMQKb=6vx*{vgZ7dR>?KrmD$Dfz-XIuwhaJ(&LNC$Nz0nhzxNsE%!__593Y8qsqBf&V
+(A-6os7zjGVV_#&M8RScGg(2J@6jVgf$87o`-rjEm?(~-CbF1(j+*KUJq$x~2c;^B&Tyrw#-onnWFnP
+OE-s<G{3iPLyXey;mBBjSMF({(o@m>yZOQ8>E?4dA$YN$|ssGkImk=1w5-Cv5&_EudAl&L@?XW30l^;
+Pgs)M{S3zldUxdTHf&Y=8sb94QoU0vz#ZMQH+tb{10k*{%QM1U59*$A?5R!pteioJzXhwtecMa28aOM
+XWQ*iaz)|29hw3R8Fyq30Y(#cK(4%qC8QEN0IF?y(Jfi)A1Pg0#S+X!1)Z+oG@k(%{kQq~9M|RbU!kE
+6m*5D$KLKE;{yGviqF7>}8Td)Kbzf8SL?_=Vh*vWFev0uh<2z?<D?Qd_2*c<*nt${V36~m<Vg`4KrY9
+!D<oqH^XIz+Eh?423oE(#bwkAFl6n?Si&hGt+bGyOwK0syuuT`D{^^2l@Z>z3fW=M5k!+TbVHVWJfUK
+L{MoMNd!xL>a-TxNvkcRSjC)7hVg45Op~4SHYXUo%piU>tS#O@Y59L$$*E{NMWV(mULP$DwrI>&)sdu
+L8CsTT~$s?)|#$geKvzL0@V~UPCSFo9g6eGAyu*IQXBm6K&fXp*Z!0hW%HH%HMJ%mmB^VqIJPE&BZ4{
+*0-bw&caJC9#yrJTm4ohdw<m<^Ks7(-oLxcKR9Edwv^b*}0q_kP&uA~Ka%#}T6w$!Ilv;bkeoo=Pn|H
+oA?9*uq9&tI$)q3`ZoMj)T#{58`pGnF;r6GV?1}^q{Zd6EipFG*t4t949t}IY5E6XNR>fS5(lCl7!!Z
+PA8%)&e)ZlX~`7XK0S;WoY_p3B~mp+JqSGc;0`VV#Uq7Hectq-MnFgf=Va<<$`lr0YF*Eh%Q0noKEtK
+%nRcyvzJQC}^JrJQXE`=rA>kp#$L+xX(VK;@IfjL9&SAFL#He?O@@q#tLeyz7KTpKJBHoD5TsrX13kC
+H{*wegtk6-S>Lmos^WDEzD6dCGk50Hacf4o9}TNzK08gPs;^Bgu?PuP2)`THw{bPVmRsR}(|=>z=>4u
+tz0vdeeny?td_E^!bvK~0SyQnB6pWhY2fo%Q*~%#d=rNFZv1j@3+lyr7;Rq4_;QLy7cKQP&8A$wXq$O
+&XhvC0``Ei}0kPF@x>Srr$FcOy=GT$sK{0vg>!I#b}hEIYo~$E}vOB7!~ozZ%qdz#+}>%z$P53c>NxC
++}JP1OBTCZd{I!RIbb>_yq%!DeLU&mgwmt0D~Fv27T#<y>dkF~<8CS3@af|lr`4Fta2V}kNV+!FwY_<
+Xj-GGcX=q8bh#-^QIWbpL)VX%8EzO%@JZJk=A5i*`+bPgLC&q@}e9%#B?;yIRw!Na+$AffTQ-8T^jtQ
+wKH{X2Stse03poIsp7Z;rwHIi#}yvnDiwG7SEj%|xp#$~S?cXCoIKzw@Fi-Sd?8PQD*t(QXSy?#2Em|
+>LTYk(uYwg}^}Uki|V0XXE)?viab?Avi=aMG<hkv4{huY+agVq(MWO;9+H&2P%vso?rQKmYgF<mT7wS
+Bbq6^l_*cMbOv0@ERT{9$<R-a$Ilf=5b7~{u0ltzo+RH|8iUhnhu);Q%`^4MFXaehVRV(DX6G{g8GQ*
+!)6c1U*BVxia8bfX1a456tV8zgBgtffAoYJ40&;1|9<1<&vUUesBZVB!1UnOg3;Fitewu{?t}~ox%n$
+@PtE{BPg${cK)2If1B`RbZ^J8(56;KqLEO6o@r%Le7NjRqn*>)b^R4ES9X%s=&J~G~ATyxB{{T=+0|X
+QR000O897^_9000000ssI200000H~;_uaA|NaUv_0~WN&gWb#iQMX<{=kV{dMBa%o~OUvp(+b#i5Na$
+#<BaBp&SFJE72ZfSI1UoLQY0{~D<0|XQR000O897^_9F3&AZ?hpU~;6wlbH~;_uaA|NaUv_0~WN&gWb
+#iQMX<{=kV{dMBa%o~OUvp(+b#i5Na$#<BaBp&SFJftKWNB_^b1ras#T#pH;z;s4zoL)RYCy*j$ZImA
+%jt+Q6SM>nCX*elR>+tp_+o6IA9?Jrzp8Gx-R%cBv%9*{Xa;xJyQ`|JU(IH-vE11q*?XJVp(GAzNUZ4
+1hyNmvtZjEgO!Bhxpl=<!){b~vvV|X!?YSW_q1%EVk?BSu*#_ReVNfd$=rS<f(D#C<OO`uI9zD|`I~q
+`8GrE4@J=+^fBIt9xmyZs8rVbg*$Iw|yA*93vY#N5tjcn6#-WaZyU{*-f!OsQ&zI^~>KcG?cMjit%WJ
+0`n!4rA0qg}VbZD4sDCZI{yCJ+cVc1SnmnFb+{M#YgO1KN5q@UdO;U^@=E@!ZXaka(dLy!oJjW3K}<c
+<YjZOQ`DwdoK>jhOQ$d?!5p_;J&l>Kqeq-$Nb%PAAvTSCNOP>HOFC>jJyDZHzN{IGxXdJhhYMQJ1=%N
+WKEf}V9J0~Wev~lYwbllvVJ3R;DA79A3~7JqApqzWQPtR?}zY9qe0-0=J{`d{kV%r%W9L;UjO1F{BxN
+pN&fi)KmYx*hTmP6M*re?a~kaJkQoW&!(m>dnPCLzrUPC<DH_k(nZYCNpp>TjMtm?UT6G<nwu=TZ87&
+KB;HCyrp|_1*aNJR1GYmb;Hi0JDcvidzM=){B$<}tjTU$6dO(Vf*wmXa*Fxyb@Js2wN7u{^wy%;SUMu
+E+IrvpHi6K_x!(e2oKn{(mRfCMuT^B;(n4wJWo(PMA%f67$!<F#XlyAA;l0`luPg2oUV*#L0SK&KNJ=
+#YYOfr<?}BrYbTWbVtt1q~b}CgZ-l^Y#eKD5Y9~$+mIe0&DIK8xKs#IRA%Q5w;-tt>-|@p_<@38=J*V
+;sF?|<{BJ`>BW7)^&$|Pi-LpVXQQ2Tg*ymHbUkiBijl!plvE2)3>KCUz61lC#cNLGZX(C6PK?=T`7l`
+MWNeW6V)ku3)Q6-wFyOn{ArIr_?d*O@0AewiF29r6hzzFR$<O2IutW4;<_q00$ZWyLjqm1@u@3FysW!
+PEj;CMA4d6~^OEMYXjh8@pIb%!{a%0^<f_M5tyM@oe&3H0ie&^#h8ZW0vdo){+0htdL%dvJp87#>Bel
+edJI*2g@($n#Dv;a=}ojzT5fitub{TqA`<90BaAUj5Ha1WX+P*$SN=HD0NueVEbJDUu3XuQ!u!okf%=
+j=d1Z88|&b;xjVH~6YEtQk<^dLk&7lsw$(*o=G!@K;-oXH!&3n@yJs`0Rkji)D)bFgElK87#&Ih|JYo
+%zzD=7_erH5a3RAP6^GgjuL?2_r0O3G7a^?1ZWyaKt|{`nlSg^ltEUjZ5%<$U#*C}N6!Es3_S;;X2ri
+7jilXo%m}jMp5rC+RMOYtIczwY@Nv>c_fu{8eXjG*`D{F0>I?p1t=69Bq`%)HDt=>@TKVG3cB8XX@!@
+#xqxc=#ztdGDzG4L~mI0qVdxP}avdG;yf;6AVy@fe;l}s584%O{;ebag}9|1J9Uj-yg4k2B!S+-$sQ)
+6_)w=kmnR-63only)I0I}Wt!uT@`GG^#{5O_hWIdfs|+?&?Sz;qGDKK9W~v)yQjneI9x4S*|XZnb~y{
+U-XsDq9bLqS$w6Yj653P`@MQ$!_R7cGPNio9%WR#Z<8VNm~70hg`K~`5<VRY^(|Ya3Mj$Ur4{#y<)k?
+r7tvKML;TZ2NMwaDeV3fHdEZ6NK57ja(5IFe(nF(X276uV?(!4f0&z<wQ-!5YwjWEg34al@2&cmE8mQ
+EiKO7H69B~G09_2{PY%9?B!{_l4FiT5_Q~~LT!NScObO!mFaLp_&gPHc?Mo`?-^q>rNQ^jOH4(LTu5G
+cxrr(EBD<Utf8sikmCZ-~NCs-1lHI1NTp(ur8uBk(DvgC-}6f8dy|GMTw(Z6hGGT|R4`gPt6DF}5!T8
+be1F*9Xb=8YqTfGVmo{-}y(#yIETfCrTIGF?7MF8m>-0QDTqc5FOaNV|guThSnJz3XKVCj!t{i~5mZl
+JU=?sig!6&Vh*<;9D@hw!>#rbd)Ce7t^gnrk+dDhgi94Lt%L>xf1so(FOBW^Tc3LdNSdpPeuWd!4fn)
+5n$b|XiJ-#kT^6ipd&0edAU<$qXIN}>N&(vMUdDQD4~KkkSeK(jCtB@Xrr;ap|7j~a~(7oQ0BOgx(mf
+Ay5V)26rpcuf_q-4xiE!R+Xg{kzNt-jab&I?TGBJ*B^wTr($4)zX<9<UEw+q@Tt+5-(zbwPa4qJE7H?
+~#WKb?yX5<ANAf?op83q)GP}^UNsiKjnn<s^B?Nsr6FK=xNBjmeTV>@S$JdoViRxDJICGAN$YLItsAb
+*8bR{ohDhxukYF)f9{5YZ?Ud|SwHQO?c+s*O<kYeWOrbYSJPhjowSMpEY(ygD7#tb4q{rD61TfIMO*v
+HptxjvVtb%#+E%fa-G-0|b~WS^+HdLA_wRl`M_PJn$mV@*IVWG0|)v)=5TeM>OB#!LsQ!I-mulwy?UN
+QE(|672&X%b_s46J5h-VS?|n8)S_uJT?|~h7o<*j7RVYCgR<oUCoK0h8tIIf=0If#y0B#AMcy^}HO<^
+<jCG`@G_<ltVV#0wwGYAw|B|4pe5aJoK@U=iN)A*cm8F9O>9<3c!j&vHy+})q0=N`}Uuneipkm@8hf<
+V`m&m3?ULqXpGAhE?;Q|J%%Rm9GLt9c^3n={iU`IRjJcW@uKXfwZJZQ@t!AzV&syr+gtkMe-6-XSGM3
+9h8lBiI^8=%=Fdj~NM>k}Sz3VY#xoitUJ@GmDLi;%{1wQFTYl=P`e8OaQ<gr91r@?g$pmFg%wC{LZh6
+nTJCC|5yUoAMTU;mKRXdQ-F{#oHkeNn0r&Rcf1)^*!nhVQrFAPi0!oEkUirZT_=n^iSVCfhZNz4`pM8
+aiyfjWI@f%D0VI8=gB5TD+`<a6rKfAN1E{Y4n(^xh(3T6v_Lgg;}H3bDDH%`OSp&yv#K%9?9q6JOha{
+0<uaxttK3mU&6`jmczmcC_?*%pm-}<<)4)mhZA$qjgle*_$~ZaRnb(x^d|#f(qYUC`=RucE51K#AeIg
+qilSL+6SFF^fj(CFNd*y;;q~75JLvIghVhUx}pX3V?!8&5xn(ijtnNJ7U7g=RUby#2!y-&H4P%a9=$k
+yS{;`T2PfYYrbf#!JOy9~?`>X3%oa2oH|xF}1u7x^0PU})7)u9|L5sSe7MRWpiU#kpNsa+a)rQVq%{w
+{l5phNtf0*2G^Uzq%D)8q7KN?{bE6(f^<){Fp$0r4`@f1wUv``shXM^p+#miK?8q<rdA;eYZSfSL0i9
+e({5b6=V*Xu9|7B<Oho;oS4`yO)dLndqpM2Q_0mStQjN()WEf%Jdo;zFkjLOwucI!gY^EGICy-7B8BB
+LRa8MoDb^NBe>R=CP#MZ16o*J`$rVN_PqVfZUzM6p^I|uu5~zY_83lQb&W-_UaUVns_K=@2fLekGV(-
+{B0e5H1)g(-+mW9ezjvV~*)@LV|6{L;Ns@PYVOLEJBTRL|td#6WAYX$ajv9FS?TV|_C>&`wVkU%J}v5
+VAxP!99;&y>S_t&~GKzs->uOy*NT>d10T&4@>7l}Lj)$+_krN^ThCjyL~K(sGS>c${wY)9BNGq#(W-m
+TeOM|F`&*EfVRgeC3eArJp5}oph?AMqM6MI<b+yiWHR-9JQfxhcMx<G*oVRrNB}{d3sDC#a9)Wbna7Z
+EFcw5;|gsmigX@Y5x-BUx^y%$2M_djff?o;qHDXW^n6>U&>_ug8qH*zs)8juEJ^JCBkW{+!K%SSEq6p
+8*?amo)|ESH*G3D9_Z@R52+97;ZwFEGM;2+^lpsLf&#jY>GvPQH7rft4!Jz!e<rs_Or!NH*K0?yIdPy
+=mI(-*6&hz&b<Y~LM3<ok<1r4lX_^){s<V=?xUlyc0D3?kzlSwFDQ=lq~mYk}VnUmFHf5^U)D6$glzD
+YSAZsC`lm*mgmvOOuK#5_c<@+7Pj2_&CT_c7Y##88d_k6>05)m2zGZxJoJP%VZ6RW`D?rcsWU9*Z10o
+T`dF^)^j*cyg?-#HGq_qm)CacTo<yUqL@*^yM?5qXq)=GRFCFQ4W^Ku{2piuYT(1*LnWrfhrjc_1e%u
+1Ir@Giij%sxF*TnruQlIrwJ{%%d+QgVjWUp;QQ3wl=(%DNWPdpPOjEm&9E@L7S{jyg~$=qx;aW<F&WF
+&{Tbh5Ik}Wn&CK;AImVD~O(=4?+ezM1sQXkJSp5~L$W>;MCq_@@ow{25iWH7>JbF{FHs^9m?~$PL9^e
+nipwd!`?t-%<c}q!>)m|ka(-1BNmG5iHRo;=rEf8|kN3vpXsY~{D<yC!to7Hx0d@^IRS7QAA0AAK_SP
+m?FfQg2$-C7=d;*(ugXa5ff2lA5lKlql+w4xBNRLf84Om?R^^i7Mh$7iZ)j8yujuA6dTKc4cn-u-fPC
+0R=}w|cL=t6s0y@AWd_#WL$JP(hHc7CgUUb_3b|Y33R<c%}iKfP)sj3|4FeoI-QI(0T@~r@VDJF+^)0
+TF;BE*!-#3jFhjE1*M_Bfg~Fbawp!QPaZ!IKqUR{8KKYA#ryRUKD+yX&l7~g%nWu^<b$&IdxiEp^EKN
+sx+b4Lf6kQG92+d1-22S5hask>xQm<GiduYgV6NX8^uIB6Ey_8j{nEz6*nI}y-Z1=<ZV=9*OrCyX8TL
+~1(e&}vgb#B8$b}Cr{5bHvkbdEB)Ly_la+JWwwsx@Zke8ip?Gj=(zRLtExNE%WmI*MVE^Zc_mG#}j;8
+4rn+DyRnGLQvj&oObHXRRaCc3@xu{Gtqe1Vy@&1H3E)oZ)zj+wPyZWoZzo+gBeyL&Qm45BO&E24=ITr
+1MPbWGCgDuK@(mHWt_y1%RnH^&)%w#sT`51%SaC-IJqV%7XoZJM<dvV`XEGK%Zn1>_KYM@mcB^yL{Uz
+VJmBeWc63y4roHLf1c|FiNCWVLh$U%dfmJ1$<D&_*cn3taVkMfy<Dekw_7ia@RG=#9fHqWI}UO#gWxG
+!deZ|3mcyK$=V0zb8fYeji{l7g&SWDzK!QRz-QUqYIF&QJg-MzNUdSfNa+v1reY`lAkUQ^7Q0SY%W(J
+U3$9qWtBwwP|HyXfDkN681=)e4Q)w`1Vr=B=5iy+10T>tU(;`H)N0>Mo)us@qkc>kH?lhDt7p_I;Py1
+mA>Rw4J<cs58LDBsccZG3XI!!LYc8V3-}ywI}}1pdy%#P_aA{)f~GfEFZ*T@?A@my?qXz99E}Jd*aoR
+$a^6pC}KEPr_s_Iq6?q^kDcuhM}|KELKdW6`svezAX<Kb){>=TOI#31}l6ixf<xk>h$7r^;NrD8MlM8
+t8+|vuUhX^%ONd}qMY>(^XZ>n2_(Q5d~Oc$DMuMq^U-bx@b|R0n$ITR`)9oi1yvh-uHtqK@hU~EV~k$
+!^Qao3L@PkhkB^deqvb~F{MaZJQLbw9NiceYnoJV-{`p~BCD57bmp8Q#66mx17?!wMjs<9acFfI+D4%
+Nc5r(Stu5$SP*<l|k8tPLm1YxL*d<}mcmIIgjs#Z<8AoSS*%0=Mglm+C)QL+i7lrJhYf_U#MFeN4en9
+~9s4PdTvlrBo4RG9O|{{T=+0|XQR000O897^_9t}3UzSrGsLVm1H(IRF3vaA|NaUv_0~WN&gWb#iQMX
+<{=kV{dMBa%o~OUvp(+b#i5Na$#<BaBp&SFKlmjUu<P|Wo#~RdDR<jZ`-)}yMG1G#i8=e71Ea-iU8S=
+rs-X<wkhIt#n3ARTBc)NWKl;-alK*xea{Oik+R*U-M%b98;K$xKJRa2#^dqmwcb1`)txHEN|m)TRxGs
+<%}R-x%3GtZjjU{~O(W(-wJ53^n~p};D`l0CMu~UZW~D2!Y^%H}bY)?sZ0Jj+8?h*i%A0a4j4EZL7NX
+GvdR5%4+^(nZF6?ODx-}|S)=IO*i8rdj$!mPxXmgti*mf(5Dlgjw>@GGdT`Dn$tye-XMd>LSooS<9>9
+$%(#7V3HCLk{4T;o2~0!G#vHd)I`-l(;z8iFlyUFFIE5k&<%7gntGqAk@3QIq9b+eW}#pb02qV2#-#W
+WZ3~>7oN%DtT*Zr`qVd0@*f_H9Xg*06x%{)~aP&3JJK`M#9D+bChxH$@M~|qcI4oShEzQRX;!TZ+Ww=
+mGy5$qfDc9*$wFK$teG1ZP`6Grp+7w)~I#8EP&k6(&)8Fy}X6{e)j4N1l&wT%-$(0O3`dbqX)o7V4G1
+lZ7GdVpKF7>2N}R95KIbiW8_@CJAWf!y%fkr5T2wFkmaHTdNX**&d#r{XW7-cI01lZuGcjnmy87b%*T
+)L=f(Li7jFg5yLfeRc6xnIqrX*2`qN)0zg6^h{`Te0jPVp9zP!9Xef@eg8I48@wG>&t%n+jtsn6!yM%
+je^Zwzo@a!ebeAn^Au#ht1E>3+gg<VKNffl)7svia|z{DPQSkcI&h;&1ELHcXI$FINim2AMS9k|N}?E
+R{*4jg4wrQw>CrGSo9dfH{OegGsk%uTINS=d#h}rCQ3i1X+dzl&T6TCO8py3bJu9Pv%k6)+I2Be;r^@
+3CfM~b$){9_PnZ4|8-uFa{wy39b&43oo(??1sZ|4x{XIP<$?Hs{==ylyN+O;xK&%W$U9lK%97rZnJZ!
+CS_y3yp4T+>L?q3}qfhJ&X{Or^XE+!%=kb9#z%UPJM_SilwO7E^pN5o8lAmx<2ch5Sn_%!V$C-mF(=G
+cB#p&icGNS?Bz8@MOIQ_y#NL7#6-_-UDjNpaLZ|(h8{T;U-tPAuQ)H|uS*&Kc!P+F&~-~dr`&?!XLJt
+O;IUBR%y_Cm&de?!hQSO$V+51!^(zLF-ZJIuTW@T?u-F%B%a4@I*&<ALv#A?_0JmmNK>VW{U7gdzC-{
+`%E(&(1)z7|V{qgcI`_)@0HcxlKyj+|NVoW%|HPylERbFV!hR?!`bG-9rkr;7S%&p+mrUn9gRe&y4{q
+##BZYCFDH=X)Tcs5X4(uDH?&ue;n#Of8LQ3;mBfgSob3ORx#nvQT*z(XTCLRIdl=uE*JxE4U>NTq<bo
+sl&vup$I%7``6S*@T0<;K#_ua6gK{25Rk^h1hj9-QT_U6-YxIgB`xt1a*3KGn;v|~UV+7yh#s3XfJAy
+kP1}C@Ex>nVK+)2XBnL3nWkW0|nvb+yir;|wtMSady-G~=3eol{=FG(xZaVVgD!ub+-nA{`D{0cRFFT
+==!j>V65EPfP;nofph4ikcWz!`X>v$iTQQBBD45A2+kA52ZW=ULugQexEmQ<oE^;yv1ImuI6QDa6>Jf
+~hEZUwZ!sCKClF^_7NL3vv99wjeiM>V|6(O5}Zgf_W$nU^-c<&#{#g`kAyD=JHt`cxP!FCT{A7-d$e2
+y*|H6I{(dUCNAhY8V`EzUsU5<_B$|uPEZ33reF5Ofhz_Laa#g$=%jj0nYYWO3PTM$XeT}Xnmj&w@+{C
+7Wx?~@2m9EY?V!)lrvky>hnSuqM-+Mi#%7;ix|}&>X78Qrn#!@WNX7hSkSqnRpc4?Im=fx{ti=6ec6J
+N-Azdg^{c+nYA3YyO7Q-{V#Xtyy@+_-#M*5u4|5IoFz}+k_Vaf^aHZ-A?0@qDJ%-bT`5oWW^%IFQnu?
+`Lr08^o6E%*cRrqO``MbKe7PdPaeN5_E<;7%hS{%A_p5$|ih6duli?IeIVSiIjTrx}huqKBYB%3Ze&y
+Zt@RW3UOY`I3u^XM0-QF3t=D26eaZiD<{;p1=;Bc6>RTHL_`~bA9Y@I_AUz+BLA@gp<hAx+I+Rbucqw
+6#Cp0^@E%+7g)7gC-5)hviML5N*^(U!sXPvz)~9g=2}95heEX6M=2_F_QD0XZUv_^=qhv27D%0Zp$;Z
+dEI8@Ki2^dzqKZA{17HR0Q({qu>e(0Z4=rSNz<=eNMmW7E2AI^pq@b0h%vCZU|7L!xpgf0%YV2eRby>
+!worsUUSED{iI{*2ZGeDp=U!^xjw{`M(GNHghW5|)Hp^z@Iv(bRp3z$oQKY5u`^UCiV*u<VV`c@00F;
+{`9#j?mL*x6d;@S+x;h+eecnk9Zqh8Sdr-<uguLKgH`f0+kgOuly0WfTo^mzoVIo;|GgOrs{z$=>cv2
+V#Hj=oTN!9>0NtAx=a8*Gs-H$gm-k>}-9XmW)R{S{x&B*eklV2RZVs+?cmTxnQC>KkFoV5SQK5xzi#h
+?i*-{GUP5h?um%HK1-w63$dNe73dic^s#Z?&Ve#a2o1)_G=`)r$T&B$Y7pE)vsVP}bx~C3Aa;8!G%nr
+%<EBAr8NjkD-2&ebqx6s^$CNUI1}S^g!0BiCcu`og8m^z>=y0Xj@n4%(5e4Fg;zi##!sH-yTCrnSpTU
+D+wS7?4AqPZI7cY}2=h-2$pGRn781}#eI*J8m{LS|JX@R`Q!MGPC7jE+ZkPK{~YlB^`TeYQNnG7hoj%
+ty-tBksp;*HFOU(M>bQ52UUDEosDu>t?WQN<`CLzdR{m%FtswKqVc)uX0>x~PVH0~RkRYYcb9mcP#qZ
+R0Hlok)r%!9?QLD|v?&qWV2*C@ZYaZ<RYgVcr2l5Ek(GZ*C%r$oFN?BnB;+sXNob%o0a1XC6R!36_E?
+8tH@Nek&$2?z}48kh5bXyjl69m5ypoEa-F!&ucjQ(NzO$EjH^1NzVHUTuIYbAg*#d4R>OP50pdQX^7)
+~KiTn#MdLuNm4q!=sOXeYuIpQinBgjX1^rf)GDSX+QYtQ>dQx&Rb+9(-A&BcnyCbNsMcFUwNo27jm<r
+q7ZY!!2QU{K;)6duxWr+fN4z8$LKpn-=8uS5PL4=e|x-1M81$0o8D|XPV1|ZQ=nD4dlQEhZXdbJAliR
+mFS=s*GhZj=Kj?JeaE&yFIXsmrc$#N`twLff?Eq2$>Sn{`LlNtZc3{#jL&Ifko09zXvy*;~_f2J|%u&
+yPP%5aTya<0*|6P~tw~8W*M0%jKjycT3l|3w%yofc0$2NTY}<d`f=@c_$H&X-D29br^N1kNPmFH(hLV
+suFR(XsjxiX|(siX$JP?+@<BZY5%n0xk5w{pEr4~PNp4$r{WdplH$s78Yi+If<K(X|91*&#;GIyS9wR
+Cg^*c9G*8hGJx^*X?ywiV^!_4j+`GWgFO5XtV?e3pBEtw_Ia5W!B>fsB{6HOtN7UfVZ~?Fez*tO0*=-
+qACC<OBKTve#9OeUbu;t3Qp1Aaov&4=&<S;mQSr~v!EqKZYd^6sK(gNFSFpotIMnO)*Poj){&?gUzAS
+l;dLDfO)$GEA}l|<B6rw<t1gsw?9P)o*UKAvDdbQ#tl8{(`h4wg_r%0;rb)aYm3>&z5??vtd47_cUXB
+Yhe-?5TaF2J8*1UouQwK)EjHL_Ws4#|Cts684=Uf(;5jzjE#ZF=y*Qy>A=xu;3^5ulm64RM1DTNFQ}6
+eJCth(n41cv5R2TegGQ)@X-2WSJw2y%Z_M`yL_-L<&E7B74#kK%E&dID`OhyE{LE#*DC|Qy4$e@TZlL
+5O_Ks(;10pKAQ?bDqM^k#VCa%UxlRbo6^+<EI<VuacyUlsJrJi|gT}QV?-YaycUy$QHW~xb*(kGCi^A
+tKyxu6hbO8qEZf8&srQ0=KqM$xEM!MkZy^3>$0U(z^RfD>Uf<24O7hbnY)ncWg-~pw;)8OOIX)vgcsj
+@^%-9j$OJ*gjt=8=O*>}@;~OR(>Z6Jn-EeT4#&lg}t{h{-o93BgX{;+Kx6zOWM&ucyrg0*p4C@+Omg(
+82=)92(x1=@0G)WpuH>o(q5W)Q_03?m0dqB@JA0DybabGgFnt;R5XYH}5_E?$$e}Wq?7*-g};L#VYXi
+BD?p^VK`61NEfnf5=Hd9EMOWpXt}cM9mh`?r-t`mUc;(58q&Qpxt%M%U*b-`s&+kxDhlid@q;SvSGEl
+7n}Wg0lA!6O!<VkHbq>N+EOdBQQ32$uTF|d)Z@~XlMq?v<t)2IaD|xJzoErdl(H7KzBx9m#g!%+Te@G
+A~B^>nk^@T5Qxiw<J)imnH73B}YQp14q;Y}P!svzc&Z^8((migt3%MWyaSnG?eZUKv!KnJR=fNz#&P=
+(3?LoK)f^G)x#7UN_GD-;Y#zQSPIpqPdXXI-%WMAkDx37tfKmUwPRXO0W4EPFw|v{;l|4{5o?+NQXiP
+4Eb;>5pT8pcRGN%7WtcaeWElOHpl4EP!H{D01-dI@6GP%9Ai;uQ-5vYC~Ehmd`k)t#w)C;D8-M;PxAN
+tGZN^w2(9h8|1D=pi}(dg46?XF7eJ~<*GzflPEKZ+67MWx=4ctr50oW4jSH$``}<v8CgT50+O46m{2$
+N^+URd^FY+5xI@fgY0QF4yk!X#6KbB~PV=GqgrOYI+9*?@u$eb4IxAWN_4hI;NV`ymz=qNRgjc{tsLb
+U2*n#GPTLQ6{UHh=F<PjZ|M4y(2)|PBm1+W}ZvbN;{9$blT4W@9*Nml`IrQ8fM88RZw9QJ9EYk$CQ4{
+dPK#(~@6;s?eR9gB0Kdp%NLxDXb{!rz>EFvKD9Q;)QHMCx+TM^UfIL4qJqYp|txQ35dXS(vTx{&d}v@
+$$_KuPMH=3p+D@E_JGmT64aFjPp05`BDNB2{zwlSJ(){bgBU5D!eoC8&XGY!TWYK-fZ@IMr||j(WM4l
+JG3C71jFnv1NSlrEc$*$mRky`exv9NRLmhHQLJ)@arlT=3#q?=G|~f-Lth{)Q@MKJ00%uq7OjW_ccnI
+27+mq)ALD(kOzvP0a;!e9fD{(9ig=UVlbS983g#0MQOb?6%DV-H={7lO?rHwfD(h~J9OIEd=RW#=^Iy
+R)1kk|8M|}ml?~IO+LVj%C9$bG&;Ld7#q7HI(d!VBo*O2(Lw@Krt2X_d2hV7nQ^}-4H`tj(~phFWP7-
+JE?9qig15V%VtWAM@BohFyz%#XdiDQ+<D46&bLZnMEP0<ADOz;S}a^2RrV{m&N<aXNLYb)6hdA|-Rk`
+I?Cj)+7qF^E~8-v5vAs@7d!(gPCv6{eRv!3@-<Ef3uKsUVShhKORVDc+5!o7=<FPOfauRF5*UL%G7#*
++CxnTfaWTft{3iW6EO##+_Dq*T7;pNj{VR{Tj!tGUr~;ov(P|%Q^7S+Py$ml4W{g`mymrB3;zr59aLf
+fi-phi>sj{h>hk*X?DBQ?_w%dS#pT->sN26d$%puL_hfu5lB213;v`IiPjT?+R2=z10Ce}*4L*(rQ$P
+G99)9A6pTh9JeGNv&k~O8x+6rrhD$8XiORSZ_UE?2^49c$;xB#^QfC`!j+|99jkIcjLk>QB5)4>%$Ww
+N#Weaa7HV|$tL(e3-mwMO9;JW{rV0<(lQN1u<L(3gd>xheS0PmepzczQ%L*4AAnYx5?p!Df>2UtYWzP
+X|D!2S80ckgQad`@;x$^M{#8bB0FC?4pey|2g=$XYUuk(jUkSmQHtgGxgg}#GmjntgCtX=s!?P0|XQR
+000O897^_9000000ssI200000C;$KeaA|NaUv_0~WN&gWb#iQMX<{=kaA9L>VP|D?FJE72ZfSI1UoLQ
+Y0{~D<0|XQR000O897^_9T$CBCCLsU-X@>v+BLDyZaA|NaUv_0~WN&gWb#iQMX<{=kaA9L>VP|D?FLP
+;lE^v9pJ^ORpHj}^WufQqOsgx?b#7=v6nYvTQaT?v{*U3)PUcL-XiIBybB2_+YtKWS8`|Se&!KY+7cj
+w7OB(S?!EOr-*2Z3keC|<3T;AWAD!E7k@UcP$yV(;bNOYv4le|XCv5*IR)Ng7AJXT4|ek}QKX4dO@ys
+aVKFPS@fl@uE!nBQZ~;6!Bcl7G82AM<R=b7p=vL@I^e$ydVmq8{vr=lnUekHd_FpG@fVoULpb97hami
+v%mw2!jEV9Qbw7VVTtn~l&KhG3n}`S3Zp-yVtna^Ko8i(T%9TIgKQD!nMh=sCBY1-i~wjB=05VFv%_E
++s4@_p#E}9yAe^UA59D?vma!kq@mEsiR{1mx(#1&l0TQ3)86>8dIFk`#L0$eePDCn0WDRHpz&+Kt;E<
+rOoD~W-Q=&>S<$e(_%e4uRr+J=4P^=^@KL*iJsei~>hAD_JkHav&#|qBk$Pchy=^JXkE6DYx@tve9ak
+EEp1{^aV*cPjziB(p*@WN0`rIH*J4RZEMwMvkOGy^>dyily-gbJ<J)?p?-9E;2I_g9||C&yxZDJ~}Gz
+mDG>zZ3n#OL*^(#HaDqhx3nD0w5-bXIH<A^Y`NL?050E@!7kPIR5Qoa(sCy&L==@e0p&*K8Dos+0n_z
+cjL2P#9P2TJHHYq<J0jKki9ymA{DXm@g<TwJ)RtWfY-yf<CF2#?;{}fetdO?bl;y(#G$x2oLr5MKAs#
+-#Kp(S#rfqiu<#BDpN-GnPoSLR)8n%%2g-#sar`U1h|3R$Cns1KP&@nxb(kQR;^_S1_sRH|4_D&D`N_
+LuNPK$?+#S9>Ip)HkYDXuB<I|CNcX)dE%Q0b{10Ad(0y2-{(}!bB#4-=z-_h0h{0u8|bbfX<f!7h#b#
+i5pKaDSsN8)fYzC^LSpPZj!HBqpDb53Lc^X!=EpwP>010eYR@$%S^6z`4?Pk`DbB6CGGxYO(P`~8nu5
+Q4^mPRv0m?h|+>J@h4Lf(MqEqgsGhS%c|CVvqE09}s)Jc>)UWy7N5C6Y07lSfU<*zNT>q#^v&Rucy-I
+c{I!7I81dy0Dh{J5Q8dvS)AzibZxS-^-89_p6hx!@R2}i2clnddE&>ZO8R+4{5o-R^HU$t?jRpDobg^
+cuYPb|LJdF~A5%HcL#jN$tfA&!l1icA!B@=Z;55-p&_bNv#qWDS0yuLt$sn4?pI?3v2M1ygviIAw_c8
+l*WB!}HFXE>IG1wo8*FzB5Tma~so`64eR?&@15&+x*ypM*I6Mz@Lkx7vS2`XzAf>$mw@ImEd@*$%P<R
+eQcZ5l*gvev27b%wIWjMKy4F310UtXN)p4{7k1?8z{d&Ad&$RB~Duiz1Apn|40Av7IB#x`M|#-+2_Eh
+BokyHR6Kj#PTZiGHBbS1HLZFQtUtm{Xe`ruRr7(;NLUxpRC<pc<-%K>_bwqzXznV)G<(nET9g9!7K6O
+k7EDTP`nVYn8QLWOmv)m3*I>f*E|g+`uc?jjvOTz&j%y|@h=DZ{bKE=_~>TCqDYdC_-znVcVTgif4-c
+9^@S3YdH{XaypoN7i3HP(gkrU4^0Q=J1_mmF-v+~>Nt6#Wxyr;jXz3jKrsE`ulQPOPkkAW|P$_YvjOu
+b?T0gwriq;SN6<WRw#c$ePUNcqlOYAqoVCv-H;k0i`S90cJz8l7#FB4mpD_KzPSsY1l5+rEP_g#o?2I
+$2`80RQ)gC{)ntAP*3QS9%~XP~nrz97MIkqWsX_|?RjI~M|$Jd}gTTgrm^m^tUXk!n)((b!RQs_^FE|
+0n?zCIiZuDb&@(U8dW!^nz@fD5Re;^9%69D(9Yff34ribe5ELk97`$!b~aMNLbvG7$MQYG^io|^ens^
+S)c(~F!Ys$2{B(DW@y7m!iCp3ypw~WMH<AL5l5q<oRLBtlF3DP@hupy>!w(i)2{ItTS4#y|2(vFk>7+
+6Dnd{Q-IDO`;=oU_?^BXSup0=5!8cZ@Byt(w86Y1;7ObETb1JqPYSuvm*y*`eC2EFun5hu8!SYssZAp
+!ql4W4p?-W8t|CH6KXv^+Kgf<CbOc2TY15|vwO>^j&2Nq4{eCQY|<vQ5Cmz4&TQQk<r?y4|TX^fpr5&
+|8?JbB;YLM%Y2hNX2{k18%w$*p2~n#!=Ew%B+^SomU5Qn($8d*_8Y<|{%2R~s`?s_A!8%7{^iRjw(uY
+^<uWx$EQ?>N~f#TWVvA)P^?Zx*BJuUX^C+3|oqRkkmUWtR!~)pZf{}1{3gzMZxoz3fy-9h)?WaFl56w
+9Ncj6OVm);)25StsmhJWFjEi*=Tl-A+(inb%Fq{po+JT9z5!cUjU@8=rEF%#R3B$)s03tf{D3J~4A~y
+1o7ZMjH0ADWjaYK0MY_uJx~&qSny7Q*w2=oOUFUWn%?Cj>FoJ(|U(kT5i>g;clUA@>yO^e0Z?2GmXp?
+G{-;IvUc%N2RrXiIPXfL$1%-ms5WIW1c@Nf!X7hbmD_(NKOfR0S)_fRYW5c;HSp@J-oL}C+g1rH9|P)
+g%Qh^KMhLB$*nQ=)#D%LSxRVi<+J^2PDR{>wcv4<d}l5S;@v7{X`TVy8GUvV_7h#3pJO;hVv#^F2>cg
+(38-K}thgHSVIh4u;z|6>2kDsD%=%+Y#<mpvo|}QG6e%Z1f`k_@`AG2A5W|(bUyQJcog4h?G*RK=gV#
+9X+3cY0%YDnV$<*zY~3@5C3ai7@T5>7DE`Rl^D{X^&a$bB^700yEd0GB5kUAJ}@u4-t}V30<gHNa?D|
+Ui4P3^8@YfO6{kkCuf$Ddj4>z*BdhM_)ZMCCYLRYxI~A>>VO8|`H@R+zI}<NRrC@(R*@HgWt{N}-F(`
+HvX95e+Zpm(ZE2u)0$Jd1Bi)UU+bJiYI49PUs)f(75vXZ6Xnw`ChZ7kszHL~;}NP`GxRA+KP=4-{vm7
+zJ4h5ws^#d^O(fJ$RbuvK`Mrn)MFu85^%<3Z}KyxFaH)6oLj$>ZOIX=F(b+8XdYF@pQLsc9&sNIJz_!
+zTcfQq5IEU$Ka3CLE**t~*I^8XV0+aQBju12@RZk?%XN1#l^`Pk8;kHT<_3RFzzKsfnUnT8&~%v~Gwo
+Eu}<IoL1_T$E0eRESo>`Ai))tz!ofu#B^!Wx0&tW4)t8#0Y(n})|#y@wau>GOCY&4&XbuMZBTWPUW$I
+oOHEo)=~*JZOqOjC+oQ$NmkbxcoQh$~2k>y!uB>bUWMRFYYodjN=6FL71FW!wOlq9TWonO9tdIl~$+=
+)p4^D!@cdc5chu4iy!90p*=_R))9@TEhT~pvs$d#DCKf9#)&ha@8T}m%OjQ^XI;iwUR9)wU^g4grm_%
+h8Q9UKZ}6fo+knO32v3^w<`m((biUn-FHE0JsAI*3+z#)CD*DUaQ3wiEB(HE{gUN(~B)8pwfjYr|Q3t
+8Sqw0Q_ko0oE|P_Yo*gi~l(_FCM$mr_K1q)3gIW&NC$+2xFHJs}cnWkylAPlWA+^6EC`v8^r%$fcRmP
+&Tx0CjJJWdnNjVlA?0i8t0;p?A^c9Q0T-FinrNG~p|%RAi%>qef97#U=&N8QSyY&g51iG4ZCho<LR&C
+CrZRaK%&2MX=UE(vlBRWASw-*@7;I=%{k$bA^QV!Ew=K{gzMfk2{|Yvkmjb|_O_~KTF0OY-7DR_PszB
+PWHN8?ZUL~&VdN;w&;%FY+tZ<2s-02a$U+{YaLQw}x{H`~h^+%0aEy)gI=p`w8;ZLvm?GKeL)oC?XW3
+^7CQj68v#pfnCf4X#UB6el)jKA>XU{V`+RKRI)O6nAj>*vem+RYXaO!&48+S1DijgtA11oIzSFl8c5+
+%K|h1;I^x8^}Mrgk^&-=&|4hvz;P)1BH~e10O5MX$$Hyba9zDQ@EHw?`sH)Op0SbT8R|O`QhsH<iflW
+`l?k^74u;LC1{RIHRqfrOu6)e&|L-)Y~lJXqEM1^IzByqTS`G7hk!N^g5LM0LTOx1B2o;tfz~nyi-ww
+KWqPOeWTIJscj~NFKomzUWk6`%R!j-0RVl4fZ~?na{i>8gR0*hw5VpgItE-DkncT5L)KjRTQ+{otarD
+c$j8IG1MB$Q#Gi98nv`uto7s2e7qYUeD#ZOHLf95hLnE#@OCXhs~5~cC@*a(xxvs;;^1@H8J+0LkOJE
+C7a>BJ_4?3RLA1iMm?9bm2>cwtPA{GEAHd5+5KLdP9;1&R0YRwrY@bdgGD3HCj{R?|!Mu9Z}iE5UUVB
+)urOV?C+!SAy#zm<1H+UGa}b$J9=&?3TdQkH&)6E-VNXXm?!74Ox2CG>XK|7LI(Tp&m@@Mx6=-9E5Q)
+Tg0*Q|Jm&krX1NRnhy)Io8)qd8w`sUIHHt#o0K3srF&ae!R+=)N;r=rrEKrblOhne^j;cu3Bx7mOs28
+Yj#GYr8<(`jg6ghTReQ7Bo%J_QLhwu6u>+!>*PzL9S{rdH5DJ5P`!13ar-M34Y6wk|-`h!c5$nwB;4+
+D)aaM#il~=`>o!Ug}VHqZ?nHAu0f^zu$(iP+={It?-{dRgXxi~61E=8#5y1wAnP~R8#LFC8xDb0-q^I
+#^-B35Om8E*9J1N8o0pXa>lQ%T?HxuhDGfT!YmS3Rn_eChS<_3j!?wTDS>FeoO<cq4(@DO2n>D9=~(U
+W4WdYco&h*vnLm(PtIFNq$qxu!noHc<s{SqrN(i^M2K|UXK?G56W|WHLdFpd(C`Nu4b%1v{veAU5=ON
+Aj`E)ZkNeKTJ_P3n`HyWX~tfufbC}!Dc+yZW*%i6o1KC^(E%}kwmUjA`)B$T+;A6UfPrCB;@#|s{6`!
+_JEGd~kHt+<+&kjt(Njv!qn*n(lW4}PZ;$4#!aRLEZXWGes6yPW*kY`w$z-uho0~gGjYNstDq`2{CeV
+=)uC6@3p46By#!1#Y;%3Hl9*dcm`r${R(l)dm8Z`y~i^jfGUHPN+9|=S<3**_&=m6m@cXD)uZnxFru@
+l@58r*F({x9WDzq3mzM*yAuT|-Pz^x2)5&AoUhU%i%|T1ls~Tiy^UD-rjbg6MjVHt^o&sDPs6uND<>%
+w38KC~5ns;N#@vxE#pub;k4-D$dL7ihBfOE-=xnIKEuy#pgzIH&mJxwz;<3DJ<dcq_Bk9sj$s_?WC|u
+W7-t9Ea!fMdNe7l&e^Q6i3Ep~W?xNZ6}__3s>JQp7VzSgjG8r17ty*T3}cfpbdi8;QQi$Ca4E=t3IW_
+DfDO6_;Ej5}0Ux0DG>u*GZ)CPg;)kFmVA+5@QQ5oH{G5dLF2L<MZLVVj33NQ~<lKXy2sw@qUgU>6HU!
+d|NT1kwDji<bx#0En9qR_z59_BeLUZ>|tjGm8g!?%0Pj9{ojZZ<gQ0+C5Ubx(e=HWEW5^t74{eszHo-
+LkQ$*)3)n(M1j()D{6;F|Q;sNmP3L^b?+Og$C<@+kyx0{Kb!Pvif{n=RxMX?%=mqwQ10NPhEao(iB63
+2*XlrydBPW})<=e6<TUgss)y_YuwLMYHvjC}7{YhH*P?INS-J#xu089tJyhq)g*h{&}|@jphKlE%Mqf
+gjU!)1<?w(GmLKIZl^%nM6#`+bVcIjU|MH3h0{geHUV|IileVMHLM9%LuyXlKBfja>P;FA`mD-mQAWU
+>g>fnu5CZK=0QcrR1-CtvF3{VIphZ^OS^=Z)Xa<bD!46s&+|dxU26k9NS>#nyP`S;vU^2HbhGK2*>)C
+^~-d8q>B4c~2m>?1c4#j?{t(F;EG_8Y$EtRdHu$#UW_>C&Zs<REh*u1-FpWWo`3RqvX?YFjaqZ*d-H)
+>+j=gnFLkLW`N;nh@)zEVk7-b|lpBU8DY;#YY135)*1q=4G~GXVr5=8LZ{QO4Fs9Zge{>aY-u?Y6{Il
+ShQ7I<YM=O<$>S+32@M*6xL|i?-U9fUO=IzXeyHnSAb>>2R}o!Svkts2x|?#J}`*(erlQ?&DWNr36w>
+<ezEZ@nUoN7!WVQQ;nARfm5M|`n#XT)p-O_&Vk6OGU!+d?nx@=flMfei=mTF>IIcPoYO~7lu9i=UfXc
+qMC}_q^j%yUHsdUF-OrEygs@!LpdW#>^4Wsuj>I=fUwk8|)}tZH!~THX#V^QQ{9FJJa&qa(b^BHxY8B
+_<6XtOyL1OrmCzA8ki$P}y{9=l;;i;VG^Ylo{`TDI4a}&l>FH|7v1tE&h`pQ)Zmh{+E1IWV1whGwqO*
+JqtZB-~GwA8_V$6ng#gXiDj))5!?@8g+W^a=e#)>F-Y2Cb*s-`IT>We{X_^A9oy=?t*p@d4;o@oY9`U
+Kn~)`u<%%cCnyg@MHFR*<Q3BV8i3Qv)jjr;1+u$qv`bV^(}v?9?>aPL<jPhNz5OrX<aoXqI1lnX`DyC
+t4{<PsDwHPDudD0r+JL4zMMQzhhv@6D|UgkPx*9djG+!JnuTe-G|Xc3anXt#v?+akS~VP{+%*;(7;J2
+iYF!Ih`mZ=}WcUOrv=qYUa3F?i4Qh8SsQQsyST<>H!&zKbNdtXW2g2%3u-B@~=G-ZQXljKKb_&19j8B
+qOi2_f_q>rT4`D1I{CI$pM3)EQZy{YnsBx->=ijNM401)~h(>Si7jiuaGI|f$~F?0cz8*4<fU0W5Cy;
+}zw090@+r`L|BfhxF#FKkCuFpc()PU}{#(*Yjn@cj0^$>RYb-ytA^7?!bVm&Im$1=d6%pj~vE2ryI=K
+F(Zi#%CxS|1OaCSS?$4tTd?KfYis_z6H&dXou%~8-uuRN1$wgueh_#twQohibi={n=rQBB#&wlMz<Q|
+QSHIlR&#9I8XDqJEn;9E(JBT6ag2-80tb&a(H*id@dd<&e8e5qfqa|KCj@)R+QAK>HXUYZ10_|rO|$}
+znL9}hfGd4k7mNvmq?;@W%Cyo}v_CVqUs}oc8vW07(9q?j4sTQ&^l=|j^x~C0Jj)v~I3Ew*Tws&{|8p
+JGF+W+7L(srUQMQMh<@hvCNOmsiXVCxYZGY(C;8~RwYCL>Jls&+;wFV`xJnc(;o~SP$Xe*u#2QUa~q^
+be%*=93{nMM5#FoML6ext0nh^lkci(wb=@zKRo!;<U>`qS+A&)f?!Qm&?PK;7_V<L6gj#E%E!m9@p1a
+VK=r!$jW5hk~G$xa!w1DzF4~>SeQq-l}K;pT$*pol-_AA3(AtZ(FhU2$uR)kKL@t`Yg9kadPV=9N*yC
+)|nUiUI-DKn1Z^c5V|ckD7ZROc91%WT!r3D4wC-g|K1-7{DFrd?FJ<nSEe&>CAG~Mo8X744Pa7H3#H_
+PX#)#!;zRo9mtSmmZ}fdI&F3Q#w4mkl&w<9XEx>$OkGtRStnY#O;2J-^T#XQYXxoUfhN`6$mZ1~NmeX
+MsH0xkl#p4uyYh{0gq8m><rT7`^CPH$(A-r0iI;VX62(FZ`W`Zg;R!5#Z_mZ2GduM!7O;$O6jX`Td8x
+E@2rLrvP>|B^dV^e8QD`$%mbj$2qh$hfjjy-ckC(~GmaPlOUK0E+t8v(%X2NOxNRfBA$I`)ysrqy%6Y
+V%`IBp>(LdIX?84K!O>r#{)JFgV0bCK6p29;?o$YGu=g^POorjgj!&qyle{P0PeBP?J6nB0OTKOjol<
+rwZ8_+0-0~T=C5$+5u0PLBrs1D0S6AmTnl&)JypwrDH(KGs#EI<NXB147_8XloZT0#b%Mt6LtC?bh9`
+WP49zO<=Sfs2Mq4a^_Z>N0L*TC<Ei|D4!l>%V5C6V#hhrkfwUp37`0|o<xC7f9`wK>rll%|)AD7Xq!H
+YKE$FRuxunOeD<#-oqrMa>p<7H@T`lIJ^X>6OhvAzpHnCtjAa9^bro-|$tZrqLHJ0YW3-D%!OUhmFT+
+!z(*r=2awO&D2m~}cBg6Q+i(h#MjP>e<x1~{YU(MtA%SA#_I{zaOtL&+G$^bZC><`B%+bO`32^L@##<
+}2Wp2|KHJMF&ygstPt;n)z{_l}@(<@J7vL-&`DphV0`l5^~^snK!ICM|5S@mxl;662-Lv4Tsnx2#+P0
+WC`Gz81qqd$UUC@hC?VC+~6Gq{3La7$A^OknNwwIP%G48aSnEX)Q2@7I?}XS7gbg>^nB%L=Coh0`Pl{
+$&_Y;h=@#<D%VVigs9F`~8n5$sT|>LiSMK!N8UTOvxY4S|NKq&=005R26zXyBML2~SsA;_Sc+i;1Ol4
+IkA*EJ7bT4vci?60+R-*uD(I#~XRQS0{@^WL4=dS21kxWZxfa^bY2{?<ambQ@7Wu9huQZ2HIH}81r+K
+j$+=wswpYA)%tfLhHZsoYjI2hguwb0WEA&5_eBY7T{PwVM_SEpkBwjyCXd_6IjC3qZ;Fq+q;^3BBK7S
+SE|S+m)<@4aiP%Ly<?V^tvzsrc0RH2vq+~6Y1UBjJ7ig{yhvL>&BBo|L;-1Y-zl+!GaL|uERtNl1QqN
+5>RL`wz|5pxe```iq_#-$rS@dKLiaCjC5Pb2wFAqGLm>&?>>SCMJ7K3%#`KA$v~w@<|JUFD@yrM9mu5
+?Yq?`RP+jsPx@fz91-ISVzs|!vT~xbcOapjwkp(C-R3GeEGGc1n-LyLk@X!QEE3Ia@s{+Ll?=)a5#2%
+HFRMllB!)D>VETs2Z$w6JRK_>&t2XB^zYwE1&IMRFEjDv4)Fl>2qy;|?TDW)s(m5<AK_ldV!$>ds*GX
+V~fEUu+8hkEl(DErPHpAs%J-sN+B?J82f>t1VWW|tIFy1v$BU8^-vb!0h}6@8nDLK?Jp2V{Vk<;8PF4
+a>1MX`yohmiY3u>uVUT1~>2q)RFA<HCK?{6DjBhH{3fHDQcP>->~Bt-E+&r8CVKV38PAaUnFQY4hl(s
+njBtS98cWC%ggaEXLw24WdX0aYykgw@$T^ISb<g!DAyb6bZKSHtBslQuX;y@=Dc!82L5evMGF4SVrYP
+<)~hvL7Lb+-O<FGBuxqB|QYLlNL}sW|dC*w1k@&|yhr?<EI+nJAOw@BR@Zk9n1+2D*ly$<onxoC8>X&
+q2Mq1UT|5N3$HYSv3Ez6_jaz#d((}O~^np6ESGR&x7Lr?{$RQE=ym2!I4MjpzjgR1#0nvcP|5oqJU0H
+45L(@3Y-%w;w$V!GO5K!X%d7*sQAQ{FV;!>0AcMKR95tU@oMtEb+O8=B&`P9pH7hyEV|q@{O@rO>I1i
+k6{IdW`{EDDPxQ*MX`nF6w?rb<ZYkousMp6fbhXRey6<xAJ~7JhR&3obs4jA&IQGmPRWc?uNK`-N7tO
+^$jU_TsR#^2q}I&4rrcW;KMZktsy{DveVc4K^L0DcowaXM~aK@e|V`YXv?;N3Q0RlJTXJBJ-A2Dy#!f
+PXGUEet~sm)A4KY#{V7h3mOA;}=SrH5Jt~<~`98hIp<M-Cb@TMn9G?1k$4;CCH;jST>p-FOyoHCXaa%
+{!hs;Am56s0}7815&F%bNjB*V+X6<t_?nt8Y{uUQ|O_ts#sj*ZJ`N`O5J66Ne@jWcQq5l<#@1q3e>q!
+fs~21D}C_P)=OLDQ3E&7|qRoW;C?i-twpk<=Z!?dDx_!PupjcPde{-FY-jha9sZ&B4=O?Hkg<n0L8oc
+#b?>mon(IdrO5FdfRa{0=EtRbh)4D;Y%r>*5jynV2C~iz?V9Wf@chW4aTr81dflj3~Hm~8r(gMw-PyT
+0EH^*>jFsC02tR`)b&%9iW<6~%V1wjqZEnN4y{ldhGeLb!czu0DvBs;tm)`U4P`{TR{7q`K{_(iT?hR
+<o4@$?zMhde&@(!ghQ<;v2YCKGeg0f;QnoJ8RM$4Vw`LEu3|@$9HNw0WFMd)JYjl&tHI#B)K;augaB`
+L2{+l|aO^enoEo%Hu^sFr1BUV&&WM2l_v|8MVV=fl$*eB6E*;SjQKtqDg7!Pp98v*f3(r>>>zs3E`y!
+UT7EH@%fYVOv8>2o9d|DRT?5GWc7{a>w+B8EAKapW@iOGPX1@xDqO^~Jp3g%6*ki(VYvWJ-MKt$=2G)
+8h5Km1)^0H8IVC;ibNHqTRaYuo$|?R;LxAzcGxK$=4Pg9;tIBNtF~ZqaCYH&_MJchU@J$(Y!P$mdX0x
+Q^Q9(jx8E<dxcXtc9iu5N5c19yL);9(Jk&n8{C$|6Z$<=VMr0BP~Z!sf`~3o)pT4^c^6$2JaeFyikvQ
+EGfPWE@}r%$uV+k9y%)f}zU2+S@mSFglk!#KIv~R7k5DZKV~03WJV92O2}_$vIJh-~Zh2d+XnH9qRW4
+?iQVd5d6#!>Zv;n;LRY83=&Fc35rWxvAaf*N&trpSrf9_};aBmSs?2;G{KvU~0FMVMDn-pMXUY<&OE=
+tKpF+3PLs2ZBxN(_R3Ma-jtigrFQX+*3B$-+Mnp|_m+9^C`<MqglLr~nIkPa%7dlGh<pbl>_>jK{8KQ
+e9t+hkcqWlGGLJYOKZ^17Ik|vxGQ%9M9D?QhehSx}O!^EtRiylKKXfh)}R^fy1CLwy&tFecz`>f4qkb
+$Ax(RAgUHVzyAIeVGuGQnQzDNf+fD3O6>pegZOzO>HJv#kR~6nW;kK0b{v49bWo1B!9kc=55aYwV=hZ
+{Q|TqM1#LH=+aV0oiZ}5ynjtEM|Ere-^zpzmp*|J^O9TrASKV+~BL?+BL?1`WwO~bCB{ASHQ%ALg7Xh
+sW2B8rR9Doo_MDS<6{1sYp4H=0Hs730AHt9QJa0!aAqFEBs;odWD8X6tMO9`M}3XMP1Q_ILGwGT@~tr
+D0!qe@E!CHT_4?jK|#zfDaEAq*z*7D$<<Z^U85V(Dwg-DmxhEGX8QWpJ~|EP`OJbEp%K=xD<s$_PpU2
+Ek?BlU;*-lDQUL!Vq<Jwve-1tcgX>6jy5(t68k}(-gsLh9O-jZxMq`38?%TqLvi7S3j7~fypSdJ)!b?
+WyeL`i$)$AXF{hMH(k?Jc3KoA>5nk^TFk;uiYd4HCxxXZ{2Y{rkj07_ZNe?o0JP{mZ}Ax6=$vF_UqVV
+grXpE^ryn@IQh^Sswm&c*kPdtQ15ir?1QY-O00;maO7>O&00002000000000o0001RX>c!Jc4cm4Z*n
+hna%^mAVlyvrVPk7yXJvCQVqs%zaBp&Sb1z?CX>MtBUtcb8c>@4YO9KQH00008031s8R^GT{vq%B}0E
+q<v05Sjo0B~t=FJE?LZe(wAFLiQkY-wUMFK}UFYhh<)b1!0HV{344a&&VqZDDI=W@&6?E^v8ulwE7vF
+cgOG^(zh<g?LNM#u$uJU#u*Fz*tK^7T8Uq#K)^vTMCjqFO==KPoIw0xV~s3o%cNF=+&`b!R+-6cCzH+
+$2qj7ntgOTgi=bjZ1=dA%ILgdk67^<$={QQkjo?k^MG)DFb`6|d)REW+&!Y{lQ$b^&<0DWq=Hr>blf}
+u6E?$Ex7o~)jtK{nuv5qk0s~svd<p>ua{Ci^CingE#+3ywNu^|y6mj>~ua;MYkP<6MXIZCiCIsxGv96
+}j$Px>x=oGeXRiU!o6knylDWC|}q@_|)>9`Qs)m)%ok?h>_TwCsc@&sfxYJ_h%S(Sgt|4Zf-2x)9@X5
+u=_;G%#h-yZGUpDq0ps<}roZk_zb>K5m&y9wpu7pr;cPX%WRCQ{S~P*dpa`GD26?6AxzoPozrv&_Rf#
+f`g$!c_q-e7=v^n<!&M^%1al=(>z)UdXgYd*-CKieYri1yct{**@d5&J%5<Hy|>G=M17ZzKbM_{Bc=F
+6W*fJJWRrsM_txWLEcZsT4ALf;9aWHPX%xd?z)flj-di(BMBGqc3jM5{&~LmbpPdUeR;oF%x~7W%kT4
+3Kv4_{aWsOJ$L;Y!Xhpza3EEgg8x2jXZ8k;#&5pjIX_aucJi7t=ewL>;2XHvXWh`>Dx@KHWEW+D6c$q
+>OtjF$klw?I1Nhc6Ja6b;*aLQg{uB_$-rt|xmq0x>Y^t%Rsn?Ss?zm``k#rAs(43guQB7G$K??cw7=W
+)shFP5+3V&orCO9KQH00008031s8Rt?`Pc8dl80N)e<06G8w0B~t=FJE?LZe(wAFLiQkY-wUMFK}UFY
+hh<)b1!0HV{344a&&VqcV%H~a%E;;W@&C=Y-xIBE^v9(SX*z~HWYr>uOJ)*lLJS<u$LiShPJ~B6exya
+DA0!>P-uy=SxclrQgO7R`|UgDkkrMp)2`^t{17SRxqRo!LtU`zt7}&1QmV}jYh88yGp;0y#UferVz<}
+E+3X<r&WI|nq~f*wTO|L?eo68=k~6mz?9a|^wPHW9hljwOMec_O)(F@wGg4C--LO2bTGtwp=S(&zh4H
+o3b?Zd#|4)*zE}bw=>)OTz+gUFo=!pX0HA(WE*EI;eWp|5XD;D=jk`y(!mK|@Udi_xpZh4b1_yNk_h^
+*3v1rqKgn5V1A%Gb4Ep34%`Sk#JDttwXRikppv$JOqDZ%e=kMk~uWD*z|Sh<t{mc!}(=mBp4FWL>khA
+X-tvqEJY{q-7g!)_en78ny~2%8b3=iU7n|$DC{g1*VseY(bKAOg!?s<xW_Fnj+E>P!hyd*#kyNM%cD?
+8GBVhNMJ?Uxq?#ga)q2E0o6gGp}vo;b-lDdv=SLnd_bE}%HHUW;SCc{5;BUb4u~5r6|(mld_=r+Trd}
+G02X*SBiE2Wh{Bmx^xiYAVp4&)M-TupGbKQUKo&+&P(6^>9bm6G7#Jl6Iay4JgkCP#o8I0KepYJrgJW
+C%C<wT9AOST1L<v*}l`)J?$G8ze2)U!R5DRYEPIRD4vs&w2yJz`ZRq0;1RKfWhX`Sgvl(a#NP!@^^<G
+>w~b>MQPv_rf19Et)^aIB2$qAO~!h4}K^*4kMrlhnsLkMd#Z(`UbAx2-DyJuJQ9we`?*sY>ybV^zX>U
+z}N?Tjip#QX1Dy*}QyVM42C?+vdT^k;bPB6&;yBEyx+@Slf#gTVVd;6B8GoK80z8bl@9-UM#&Dh%-oo
+)N*;AT2WUk_DszV2xP_3waAg3v1cIm@%bQF!#fs<DUxJ2>Y|R)XoGdip|VvWAZ`V3gU<#r6h*g%goTR
+ag;+7jbRTrc(k(YlEv%g|#jZ-QlF61|%Oa@M8-#0!YB`}jZj|Q?hoHQNVi|meDSR7zMFCw-_Tmu(H1O
+B=Oe8*{LO?)*kLd=61~%|9-SAO^t?&Z<0=vx-_gTytWeV&l@#KPMhKwK3jg!E1clhr;)&q#>Y39C*bw
+O%JxmeJl6>>4ZMZlxHgWmHN5}=lk)X^blxY=Rfz-Bw@(nBX7=kJSNjs|9PkXA%`)Ps%fWYGGCv)B88j
+Bt(1ffx|LP#3XjOe-NM>|>f<^-)Bq={R%{u}`0uqgpM6<HeRRe2Z7c2eMcAy*#rKK1Bwf;OTrjxMiH_
+>BMv47)QUME~0+k?<XDVZR_2-Vk5WCeLA>wFU0PP4*ehb@4GqYCCnjvIMce`RpgKpzJkdGt)7lQL_9V
+;KtXmq$)^rDtCHH&SLw7{-PYx3NQ5JS4!v)1e!#kh^PCEDImBRmjJyozhZW9+sr3l-is5iMPT8-85PH
+fqoYR&~@VxwS3pHYILJR!{z5g}u&gR_WmrEOmcnHPi#nTIFNWU)FB}-km52=*px#A66e;^f0zclC(Fc
+E#VbexDUP59TVnXuyTl-?Op#4+C?c2N5TZlsuQ#G<0X&ffutkbyF=BM1C6d!$7@9=0ynU*2ZwN2416w
+t2{NG#lAqcB@MP!!%ucdiHmC156<k<&sFlE0iFp8KnZ8>Wxj8lz1V>?gt^6g&8V^@%*;t&AQ|`?>0B|
+_wL7gKP$}Y=dL=^`0oBWH^jMXX8$WVQsV?J)uY~t(-)yr*A*`TFAAeu9}SrB>f1H+PIX;!(P$-$FkD)
+HiCGJwMq)l{so;V+vQsF$y5^f=GUHRKnC_@}tEtCt=9%Ls)lHGiw<=i9;9MbnWxAYm&jC$ly73Q0mC_
+<%x||X0g~D$lz&{xm;}2X7cXbqf8iK5P386jUv2tbtJS}31f}D0-B6HY1zO%FDG(Ja|@%#)r&x2Y+YV
+1z#;`koeX<Rvt?_|{D?*hU?9}awEO1K7SmO`Dh4LU+;7IX9&5g~h*{(FS3Ykdfjzy+=94%!HWM5<?nN
+ITrid~G#yvxSS6k(&)vO#EW-j1ao1DRDUZtaH+NXWS*83bA+WcY1)f^S-m4%{=v1>s@*k{?8@dw@yn3
+&%&(1eCUtcVb4M6>+bkEyT^|x%F$O2y10%T5`K~sPoiiY`o3%pK4J&^!liQbsbN;Wkfx&opL+w!+V6r
+t{{>J>0|XQR000O897^_9=8Bn`*Z}|lg9HEoBme*aaA|NaUv_0~WN&gWb#iQMX<{=kb#!TLFJE72ZfS
+I1UoLQYZIi)n+b|4<?|up)yKI2bH|QbDJTz#K7<PKtiBN315n@{!B`53KPmV=LY3h^s{S+nrq#M$m0B
+8m`5CRC*8BI>egVpWe5T-auzKP$O#6ec4i=^6$N_R#&bx^HxAE_{;&#K0--3oV<P7D@n;j}oQI3nRw(
+u{{aRl4u7a!U7nnzC?%P?I(W>yS<OcR=enwR~OY@RBWmWkq@o^5xG>7D$<jPM#2sC~G7;SFlF+7NgS|
+168YSbcmx5){8L+g0=1J$@fI~Z@J00kQclCZnfK#>6N`KODMPNDOi_~|Jmi)wk$U@DYMmEk?o7+w#;|
+Me&SpO_FTwsS?S*4KR3nFS|kUJ>fezJsXlQ3B;B47s!{b0*?T<R`s@wxZcf4oE+h?DU7gSu`4QgdREK
+()-Q7=NDyo49dk3Q)QU_`|?Ty-0yrYAowm#WNvIxTnt?~2V?@QK&Z5OHL^5YsBP5#QVPH*9bl*1$ekZ
+tQ{@Htq$2)-_+M=WAzBlgK#R&HK0iT!4F-%h625#S)0!l8dWFCW{(O6(uAFQ+^b=b>cA4s$&F%pe|iW
+)GwBS%`*%rKoE&x}O-vcO86y*FMhv-~QAX-TkkNaT5OnP)h>@6aWAK2ml;P_Ezkw<PVw$001Qu001Tc
+003}la4%nWWo~3|axZmqY;0*_GcR>?X>2cJZ*Fd7V{~b6ZZ2?nomks$BR3L#*H;u|1a28hduB3m76Rt
+MnRpUoC$<sG*@qx#QQefpm?AqQTblm+t>UFyEopYK>j%r?rLLz=6}>Wg3q`SNTw{1qfY{dBIABYwW#f
+1ezK=$6-Rkm{<JT2k%kxqzXT&nyDp*}}wHAsOT<wI>DjnosN?tpml}%?q>ypvJ6El|I8KX@)TeI?&t$
+BCSiZ5|%&xA{>5BguMo#QXzK56sp?eb!#K*x%eHihA=8jVI3UxBa%8mo9oI*ZC^w6w}-X)*)2fG5cuU
+fF(YYhH?#C`W)l<MG&k{>CvpX#3nW9K;IThC?q7g+r7GOjTevx{(zu@r=}#SNX^bnbpj&t-m+(3x2Vb
+%-Y#v<6NDWQgG$+U*_|tkDc@d=;dGdXO!}w9iIWZ40SZwf)uYDZtMEa$9{_Dp+$QkB`~>Xtp(%lhsEL
+(la?<Q;ItPex%0jxQLsV#<-j+?%NFfYYjB1si$0)<vIRU2jm-yPB6Pq9SaZjmGd{Xg7}M%_3SRZZpTh
+|HqiCgHJ)ePD?@|}8=!m~{Eb2k4AgPZX`cD{WV<I54O}PPPVc7yjT#Dr+KNe0&_G`|xeWET-KtPh&Qe
+wRK8-Zds+;G@(Mi_UOsDpEraB-|-0MU#*z^sWa*Nyw|CVvyc6pH5SNdG^>HX2>PoDi~VREOVE*8&6N>
+ns#`Ubi5WhsRUvHhAn^{sUNt2w|o|85lgnObd=%EYe0ep2KZbp%kYv0u~E*tr+nNDbNZ*vk0OK9k^hT
+qnJm<fmM~D6((V;EAoOR!`y~B*yE9%7Fbh4RUV5P?w@uyV7b|GV^K^cY^m{YRF78w^zfYO)V9{~EmWF
+Yb?Fe{J09*P_n8!~%{@z$m<}Yp9{!mRA)05nwbOu#n5Gz|;^)tgKi+;We!BZ~`|^2S%<q4_dwiKsV?i
+{g<VC#yfe<?FDy5G@+?dQ#HAMuIn^*Djm8X`NNbi>yF(e1Px8n*)q~x7@Ilx(Q8H0D<x~9f*Uo5hXwl
+0`P>^fO2CjVI<z!UP8PX+D;KbZ6au406)z!M&K+ypYRk!|8WLgG-cP=u{AfOg3d)0lLJsYBTz<1sC$`
++fyVA1Fec*rvvE<`uDDkg=9}iGaeqvPQa2D_Y?N2G<ZS$OSVB)-0kkNB)YJ;+;jH8jFO7Z0^-x4O1IT
+ATJzj8>|N;e+D7CdIcf8A+%l=vFCyB=o}%Nn2ANuB+#W$Y}spyb`Q_MUAGEIJ}J7q1nLabAm3nNN@@L
+#$7fQ3*86YKxt_cIAH9i4;Zb>_SlY`mJ;vF+aGPxW$9U3HqgVbR9WtWE{XfT%!;HZ#!gtVe0WTeDc1$
+9Zddgu^>OHTDH50{(ZG~*JNn#%wGWZwo9(5M9OsJKn-esf6hGH)X;rk88D~7z?Yx4?ZEmiw_&j{Gdw5
+jYg)PMI4Bev9TlSgTD0<;lGpopFmM(9~{&|59JkVFPa!4C@N8Rtf)9mdBGOIKGs8;eS@@t_U7C_!6+`
+Hz_$XQbRPVR=E}%(`v*Ii0k!W_<aLy_|w%OD=&*tfeS8jbYVlJ%(?*HIr$`T#^*6Ch!`X&lL0(lk#!^
+^=S;jG#z_>{P@q}dH&no?XL&$VXJV!wKewA+GwYzP%?!fNA|!yhA~8a-Gw-23``qD^59U^96qu$s-jQ
+n=YonGH+G^TE}@c+H7fZIV-*=YRb|43TIT~X1zs$MBp<u{aPdexwX8@}$R|oC<zMSELzk1=xu-ZUCX1
+hwV>Lti`idOlq-=O{auVb`#vrq7xS61dXL>Iqn4?>q&`7MuhZY3Z;HO51Nsj{Kr@ixL`(ZDeoZTFd5s
+D;DXC?Y-qU~@rd_6Qf8y~V!#{w#rlN8or0f*Pe*Wr+GFiQp{fTe-<sM7li#Di3U@%(I19fSb-#Lesqe
+<eH4F;O>koXmt3rwK01bDm942s!lGJ`6Mp(-a(JrxEG)Q}Ocf{B-v*%yV4>q6x!G@Y6xfjemkLPt}$)
+gERFia&us8nn*mEC!Xz^SI4!z%KL}Ac?#+;x6j4>)9*KZl+IiTHjWOU8xEx$ZkR1Zy}R)Y*N5%g+c3_
+YNMf<CtLQ)|qWtK=)G=97fopMAr_~FZ=pl^s-5g8v4)tnsD>`9)fLQ4o%yUb^FqnTg+OarlMQN(pF0n
+`IRd>%1+1^_2XB?s__>1NkOaqD{Lh^~FAq`(FDfJhjKT<<yi6<53_=L1pwyB{$bM9YTc6NQe#)jN1ku
+$c}jgk0-_^$gD);8Q;zkUDyCgtt)9|}1><oiX74lnhWY;w{N55gyspLq)J;j69-d8%L+^H|1L&z{liX
+j==3m5}C%n-u^2K-9hS+3{pTvlq=JLqJeU4sQcj^n%2ha;^^qRWvhiDckAw6J|<+64v4|nhw4B?_sVR
+DX(wdzCCkm*{m%-`^fEFn{~*@&G-NK?%fanW1}6G;mw(@;d@IQ7T!#T2M)@hdyLahY#w*%pGiYQYJ89
+kGJeE~hixIEBq_oYPZWVV`$`|rW^a+i{|!(}0|XQR000O897^_93eQ{zUIG9BMFs!>ApigXaA|NaUv_
+0~WN&gWb#iQMX<{=kb#!TLFK}{iczG^xd3{t(kDD+Mz4I$Z^sq!iTzXq6r>Nals<Nxy^o$%Bf+b?pu}
+L=nzGLHn^R--n@qE1ZX2uQaJru@tCCGiR$wEaaES3Xxo!oveE3GVk+8hXt?haU1NVX*WXJ(TNKOh;YR
+gxq%Ho#E|E6WDwI!N{`TWkB$4t&sM3GmaC{ye!t%e7XRhkp)j<Sv+MG*&9%6Pc>TJ^F)W@$56CY3kqa
+Xa`aTHZ&l}25gHF1UN$gq2SkM^9HNe_4>zZ!+xZPUF-dQ^&;{4o_j%J4}ahP%pk{#?r~<_#6eNao3pG
+uhYLb;xc7k3I*{iEjcY@%b+;Ev?2wB76el&7?np7G+%S~Ub_N!C7m&#U!O71(bFUoGR*MS-zrpVYj`&
+0fN?RC=R67tOgPcup6eqBn50K4c7f0SK_oNX>1Fk<aGV+~)pQ1CEgi5{z5kLb9d3?@o3fUPz&WJ#CT-
+rdR=_sh4YTn8L%O#|aUix+UkD>R2&Kb{H9oeI_t%vsE`A9!5b+E)}CkWY8W)h&df@0Fi$0dsg;^9HT8
+kaLL_vv@X_=v^V<X*Y?bd+Y&?Y3bd%<al~TgR0jLAYfOOFt5fwmXMt`zzt^0uxp>{Fb$(Ym2br?%KYf
+LS6u;G%MVQp|hhBt|kN!PHB#XRv7hUVT-7o(?Ql)!}jE+-6vzBR9vKwn85PEy*BqSqPe_tv1QTsBA=o
+rJ(f53V>W#S|3z{;Id0j`LS9Tnbl@a?e8%El9I{TrTFN5!Ii#Hybs01stEG$Ud5R*6TmLM;591R#C;t
+IZO9KQH00008031s8R!#%<pZov-0P+C<03iSX0B~t=FJE?LZe(wAFLiQkY-wUMFLiWjY%g(jWp!mPaC
+vP|%}T^D5WeRr2KLeg30l0kuvbqjD0>i3r8JXeFwLZ$M#ZN$NxQVDfk62F3H5=;2|9KTyNTF~Qg-AXv
+<_|e-d<3EW{uF-Z%QXj_x!PnhKLcBBAey<`K>-ENM{ExnE<*9(SYSKi3|c-o4N(q!_ygF$s7I@4QI@H
+Nv>U8Kj@OPw9H|xKoflwG)>PYI&5Y<wRs-e13cc}-YKOz*NVW2EEm2i8+Cc_=XnM#G~{Wj1f9KsX2J8
+xh%Od5ZvROeOlY-NYr-J(jZ1_>e@u51G~yITpNVSC+}cCD_S1y@zY}yD0(w&w!Nz*Q+4{F`;|(0r+#g
+U&0|XQR000O897^_9H;!%bs|5f6oeuy2BLDyZaA|NaUv_0~WN&gWb#iQMX<{=kb#!TLFLGsZb!BsOE^
+v9JSL<)vHW2@=zk<+E*v4$N!-`@skfKiNuEByNSkiqN3YnJ9F&l~0NGgt7^nc$S^`aEJ-NOiCi@f*!?
+xBrVIg8^>X-f@p%tT%&Z5dx1m6aCa>NyBDM7QP!UcGE+)~{ZIOjHW>Z4|*{0)-Vynug|s)UXpW<?9Si
+Rk~klt#m_P@Z_G~fr*TGY=uslkQVMh$97+U34$NkH8+NF{9_M1D}n8V-3rN8t1a*pv{|i~Rm|Lr0*N6
+P)(UyYjLLz%zrDR?H5s#8j-F{?JWU~GytFFkRwO*j_7Sq)Zh<M8?VmE3vLNe-37=N0MM93wmgGL_TCJ
+wYzFNIk#^P_rWr|N94CvY74kVsM!Od^y*YW%1;_dQxcEZ9pZ{Bz(_!K&d>&5BCvOc^)I*in3kOu7d&y
+ZJ2p;j7BS-3@o^j(rFPO8F>lOR}}oh`3#<K^Yq)!XySUrFEHXHiU3*ks&77zFXV#rehZ?d|g70&ms&6
+C`$woB@)soZmxS$6y>V{M-W+G0(&UoLnjiQ+HU|6F2sFH)Kxi%<&EpJR*rP=v(iw(CTp?AG}J1A=JbP
+PqvNP$=qFqVd%bZwwRQpw1#bzW~dJ|ce&T_R|&>8iHrhAJ}<cDx#vtJjXviaOxUe1!KE)v4I3p&N{kA
+kdG1(dj%8HK?28<PqLX{ZC0irl*jlL!xSX;~7&~QXuCW?Pqn5PM&#dOsP@W9IdgNzr)RAAH9IS*aL%%
+Kiq=ZCtuJ<fadCohs8>girL_;t$DU}k&{Xt+6^xf$4HXjPmP-rlCLl1WAB-M~(dsVU>m*|!$lP!vGnZ
+sglw@S`Ron>PE^Ya(ctFWiB%e)sel_84(qM(u^O_Jw;EXM4VPV3OQq>qSKY4Mp?nQ{WLw?v~>9#I_3+
+7NvI)dVMJ_CE~iLH*mHB#IeA(`uE?nN%}(GC<|>k>^DQ^Lfz9dj0x!zplNKCKXe^Xv0%(b1t9%6uk&1
+t%xsPNsQ)f<Q2t~jXFHgT_<4l^|%eg4nl_b`UV}31ox`pYp)wLUHgQ6sV>Ckcwyq5FhUy3WdcJ(rj*`
+EM@%2ee0u=dclfEw2Lc8()Rd=TM1?zKpLlu<d{4@t*|*enIG)apkH|C-6EyKU)B##S{**x(9c{~gsI|
+829eNyl*x@H^1sp2I&Jn-DDjBD)%0l*Iw~dU~<4($C5~biy!_sbMzaX3&RmZEpRd}GVkE`vaX+0i_?~
+;1lq$7Qxi=bcql_gCFs6(g$_c+;b)bkwIhj=4UZlR1IC&p`B#ik4&2Lly54rdJ&0=%6QQ<kd-U?hcxl
+3R=lgs!b7%@s}ry%Pr8$PPw0YPhwK7nW!>I*Sd{lS@srS~v+qQO^QOj54HJD$8i<cX6mz$(W4yJP6u?
+#6gI9b$u6F$TD1xNXF!_K&$tIB3INth(99ku~&(1wPoY;E4RW<+0~8vF(`6cB2iT;HXG11E!`M*`>xw
+y819;CM}=Fu>7H<#YzGoJ+i;9Cu8@@tD@M&uv)vXXnd~O8s-xj%u`~F9Bi@$Rg9qN$(0CeB`X4_<#==
+jiQ%r>P$XNo~av|FUSEgKRk#j9@opwtHCB0e8G^7GyfqNTm%4n1pFj&$^dKcPv7>`*d?x9{)D*)D8xj
+}%#eV-kXN#=ACt{d>tn*x&4H=0a<?gP;I?<h`&fTGg|P;J9%$vuQQx4iMt#B}g(Gx-J*Te&Uszs92GS
+dfR`!1~R~xxbJM=!&T%DK%!O!du1c@6;~uRW_?EKBolkqp&B_E6c_Kijap$ude^8q2UKfw_aCq4XM{y
+I)nQLg+2Sz(yed&xD$;7{s68F{exaY4_VhbnwO*p!Mb6T=qBrweq*sUGl8o+ZsE^N6tZWI=0KV!!QW6
+z0|XQR000O897^_9HYnA!U<CjGwhaIPBme*aaA|NaUv_0~WN&gWb#iQMX<{=kb#!TLFLGsbaBpsNWiD
+`etyWEM<2Dez`&SU&Lu|lNg66Vy5ftfew#gyepqnlV6oo@eBa4khdP&M&qv(I{8<LV`C&;2eb+ILKKK
+SO%8<y5IVzDS&-&$HMglg8tdLft2)UBsQd>@TU-bam8bw<`2>$;tHZSB=sT7RoI(kiL_XJu;XmC^61q
+}<QMCy(WyOsflNcOQ-az<=Xna-3!KHK#Qj^^R{y7G&?GbxN<UIcB$aE%PV2B9}S!HEYa<dYj7o^&+no
+X&k|Y*IF${qftSnP;OE3s&Q0I%<`}4d?fIU$K&w(uA=<OiETx`A}gd=sSRmSs+vw~^+W<D$QW)!^pTB
+%-5iIP4X;Lj{5(|j+|V15bBwGH8~%8^+Z(=#X^2PVQlisGc(M*KDlKy9NZjvyW%Pw83^{$`g(EK><L<
+|7;OXZZaqC=5;?4Kpz3snSLZvn5l<i}L)mQ>?<-Ju))IMOoPi-xodnMzIk^;a9Q<f@MvfiKnG@XAdci
+Bs6#3cTQ6jT{A=<6g!ZnT$5qn@QfO|=QNeO{VM`hmL@d4~*Z0^Ef#8hKT+bxcn&p=_0jn}>({U&*b(S
+DL<fs&dU4d^DQ=+sUj{sPSi6w{g#8{F|1`nwUNXd9n?T)3Y>2Nqihn6Vu_0tY1{2gBI)9LX-IFj%a@s
+_6~So*COo{mE4e661u>(c}~uiZC&pKJ7oH^`Sn+CWe$7NIocZe0kNbIp<THmmK;<9)DS6`E<$RdUo^a
+KjYazb;mB`saoAtn%UNvgjM2YCIuL=*(>&>gW1Kc*Rk`cz1ENl}wuTm543s8&E;0Lx-0qW2$B`CI&C+
+$$z;Dp*D8g0&xe@{?9O$Jzjs!w(Db$vmmyy_71BXva7YPm7a80w$kr9mqEel$<t5t|Co#Lt#1=tG~LC
+<pKheCoNpfzZqwDVHu)D?Qx>E95q>HdU~X%D+~M>KdxGoXH*U9y>p6$1Qy{!cc}&_<2)6A!DNP}6Ayq
+6m`i#3eV71k?AKjMLh97Fr?-4t9Z@yV}U&MVrBTZx;+(9Vxgdq?a)5y9`(ijOK?e-N#~O$bBoB%W<SN
+@u1y-v%&5k22Qqg0uC5vs|r+ij8-abA~{k}{=|ivNYQlDQKS&Pw^X*S5ip$ky^}$aqBsmN>hhW-EC&7
+t6iAz9VzS(M0+`O*>5<!)kW6+Rn5k+*AQLwNh?p)7lT`BIgBFUVDRyCP16*0RhVWHTk|PBW#6vc$be;
+pgj&$LMVZ(M2(nN=ctdqdG$uxFgtN{1gz_24F6lGtGF5S?V{6*z$E$wi6ej=KOl-&I6Y^8kFF0<S;XG
+uo-U&SNVoxMFj9}TSycfML_1Hv#nN>kTn%Ljh})6>_kNW+c%@ZBP>rD{Mu$7aAh+F`<icL3B5b*c;T&
+5PP`psS9veK-KWqytuCl!3+=4@-W92-2ZQ^0SwPKMwd8zaM<!Ass(+VUpo7&5zXX8K;YM?VP*<>g?Na
+Ob;CI-~JpOb%#LG2YqxbvCqfMB$-~O-`Syq%Y(P+{{GtWcHvDR|D^ly`dv24(--hG4B<h$R$xpR@KW4
+dU%fv~yJGQfq%Lao2%CRtRT$5uxLU8THD(jNKA*eWQ6FoMO25?Ii2IwHRd9?NpiNRHy-~|ou@g@6gs=
+7>A<kw7vp5p>!|m^P*K_d>!x9Zx82E)UIMYyNwwTed0cB;l&2X5tRU7H47oSCR`(tny|AV;Q8M3t8F<
+?N$xWKn`Kb><X_aGBb%TtG`s&FZuGjtT7JH9Y>fiA_x=-KD2g_(uOVR_5|j7R?hP)h>@6aWAK2ml;P_
+EtJb%aZ&S008q<001EX003}la4%nWWo~3|axZmqY;0*_GcR>?X>2cYWpr|RE^v9}JZp2?Mv~w8E2ij6
+2}~%Ml9S7YwY)^O=vZ}j<dW#kUHN<<NDf7;L4b#cD8=Rd?c3e+9srb+(|*`Jevm-SOwaUVdiph77x|V
+&(Ymhcf=3Zcw!6HjSiC6nw61t0zV~|aJ>SMjs=lQ8%}tWssILWAPgSzj&-=K@pi|jf<4nsuP5H7)@~l
+)-W$~7;s(P1l(Iu&PQRR86J5=#UzTYI!E;@uEzgzO110?7%_`Jxo44}_o`n;~DMUfXnYPiU5<1|^l;_
+-^hS8w9GD_#}%R<E~3UgfYt_tl-<<q9A)!C&!m2aDnI)j+Lt7cW1?H(al>OzwI;pc<Pf+J!f~dJT`f2
+%-on5k-SuulIzV$5qVAs;HO97`Dy}pzp5WCC@4t$EpoyTVBO0?3b^h@qcSxRwXpV$cnN~E0$y|hG)Ps
+>|KctuadILi+fmsp}Qbn-|f*KviE(MVUw@mv0oP{{^N)tK9p5l)g?X^e3cYH^(f7kF*2q9p(k*dU7lZ
+#f%fe7l<hfN#u+STo8NL+WKuGL3Qt*_tq7N88kZ&8C)I|n5LW=lS1cEt4tvo#U&n~ngyoCBz>EP-BL+
+pp%QpZdsP1=sFea3K+7<Z@r0Jf%t@xUqPhXzBdp(QZOlPky&!b;oUCgGhFRo|7GA-pG{3xLf@gdN!iA
+?WGr2i337<R!sVt}B91ftk?;p~$%WeYAzvO;Fvo`$24y(_s7{_OSZ%U`GGa++&^o|P4dVt?qsJeLy!y
+?zxKnD&8w0)eQDi~+`7@Oy%KUC4zcuV9mY5mAQ>c3#c@ztHvoQ9*2p6uk#T^J;p2aW#E0i(XC7&Zk$`
+(eu}5FaF~(gtQy-Ba`%M`sVV_Q$5Y)FM8@nm)!2DJR$BzzDt}BGvW~h`yZYkU&e@s1phf8efjcb^ych
+8|EPppARd`?F676RT?@9PjrGQtN{>qa2l4v{AXW#Jj3o7b0$VDKSF1=H4uP=&2GS~^7lAMqB&GWOKD`
+A?G+QS(bwNuB1^uV-awF^|76b9OJ1}1n{bj*{JYY*@d@q1X3q%+z^=?JfqqPBN%ABBqiFQv$4^Xd+*F
+3!k*mcQQayA5%fN?0h0F%KQ0v?nw(Mp;+X!pfz2j=j2+_PngMouJ#OJVm;z8gYQyqcWie_@qPzB5$aR
+Mif~yai});w(m^Q$m`^|F*aalNS2puu$5U!O_pt+0l?4;mh&Ur~EG7f(02a^X=24fmq>X!C-?Q%MmO9
++a1UX!c!E<ikD=%+W6sj#BkuE`1|J{D#A<zSx!cSK|86FGG3%W>%~3WfuP{#n9pCvY02mF$6Eyflq(?
+Dpk!({?TdJ~6T4|lvO1ps6-?|jSv<46o6vDm=B&<AUY0#u1meP=GemHL+RM1)MA&6q6M7n`UP2KkMi$
+4rxQM~`%D~;qt2i}kWrkl_R&N))5RQhJxXM|arujZ(Gw{z!hTEF2c(&xkYL>(71?;jqtIE(&^qS)gK<
+!`h42X@-wod?(3{Fps>p)$!j&ZHvMKM@7K{P6&6Y@xaU4y5J!;lK=q$n%p2{lJZ&f^zJOPU?LHrTWCI
+Z-Ogvq*0$IiN{Axf2cfUgdkXjk9~z0vv#yk&?dPLMDg=q*F3$akCBhdc<DYP4Eji2YW{FR_!q9OCccf
+dYgl`DtU3MoL&3~!2mxDq^;g^wgE+x<uIy9(EkL`I9QBAP;gE!LE7w@em}KQVu-Qml{LwQ+Ny<C7(a0
+6LLDU`8Z?shK~hN?#p{X}4vF@$OCw1fP}TU=+V7(KHogb?fKZm8v5xtA4V?P}vi2bMLY!JCpqhvZpiP
+12+mO9Zwn-%+!uGq(6VxDZY$O%eLo~27&v*8s&vX}*n3%nq&E6UfM<*GE9MG=^X<c#lY;-b&Kd1QT8U
+Fd6<z@pu8~xkkP~`8l6$K_=BwY&-E(`Idh>>hb#kY-tG$fLOa&X}9K{0WMblbRE!blBfJ{PSKFmlP$q
+^$IkA5Wf0L4Fa!LOD0~)1~#=Ry`C`!tbarq#_fhhA}iiG!z9C+}3TnO>Q=oIe#8uuM)t&({9Dj#Ttgv
+sR+Xpp)|obhtsw?!hLj;=OCaf9wY3Mn+-amUAm-`N<%}7r_T7@4i<@L!0Lw6X<d?>H}*8H%ihR}-9R+
+4Iq(eTWCm~Yl_l<oG$2%inNcA8mDum19|M9eBwyh~C^vbXuG&ta=l9A~8)C;iBO_Kyk(^VWEGQp%d;=
+xuFv)?*8V<bN?%-4ct_E9xmVmirVwR+Ph}AJ1OoSl^1VNI3B&t!vqE0Akd=LVfoQ=U)FUIqOVV#!U7F
++6uOm}CC;Ko5JS>wV`Ia#)ih@ZCwzfJPG1nLm;H3}rm6lsOY1id04S0z=zkXYb=s!K4;J+};fu9NWeU
+&9dzNta93E+M|+8CwTJDTD-+2L}^CNQkWneF-5TDyB@5Vql4Puy7RJM67%5Y-}le)CI`liSB%^fgzG&
+pgf#x)vAUcRH(Mx5=W4r%IYVHQWmI7wRM^U!f0{k>vgn_msMWa1d}aHw2&0-@MK!>YR`G5+{V&UYbA$
+W0r(X68cwjyfgHBo!pl4*R&GI5ka!659?xSvnwFi{pole`6&RBDunDB+AOxdKIo~0td?EehF8(w7ngy
+rqYxw)gnD?aT)LHkL9kUbVL($fw)s!LXM8wS{6cTw9o*>166ytTBEywea)-$)(=BUE=qi_T#=qNm;zu
+&^&FbqFvg36V^jM5j+INGNm{b`=vSpEP=YSyj^tN=onh$za~QWBIxO^gPvh%CTWWeq!I%zoW)JU)j?>
+TQ=v8FPuT2>9IwT(b(jHdH$Z57_NyrI-*g89Iu6W3B0?iVY%8wr6*D02XL;X!+7eV%K0<rf~sVG|ni!
+l(!jM;2c}-1fgpm9|DKW_?m=3WA(-*0ZPf8jgDUDz7}YZR!~M59`_o|0tH3W(?ypOTx=t9T4OXt)E9B
+w8|?(HD<0Hzc&+LJ6Pub>F}c(reL$Bn>ML;9g^(rL64Wr9Yx9tR<BFw<Lg0C^a%9vx^z!AhE?}}ygq_
+4d&>lD%mL?)tDmdWg=H_iI1?plJj?{2O>L=PzzSHnbil~q&>MjCE$7iIiM0Y&=oHM`#rZgaDpIuF7SN
+|2Ay_`+2qU+h&?A>+r;_`fYJxA_?vD9%ciPKB2v2^y5by5S`6jE5r)s<GnfU>NP<%oL62%3?zY?WZl5
+d=GSoFE~a#;XQv5IdnN5O76TzVfZkPz4hOZcoNcB`1|pMD`EEa3ATpuH&vdSp?Yq#sQ1U#B$&FF}#jR
+*Po{|{P*@9{X3t&p3bKDboq96arw(NKF+SrUQGKRXz-x1O!t)c*V^2JB8=9-X=k<XzdZqG@!QiMhU~l
+1vk%RwEk?Stc1wgutb@4*YbE`&8faZ4zsbC`SqtddWLs~w;zt)Lbmnlw&L^j%o({!F5t=wrWEfNObZy
+icouQMHk$Iy6v}ke+Em?|JjaSmGbzcj9crVF`^WJ$vHc>fqACzIO2f#hiCl(G(*Lzmfyro?()@_waw}
+Eb#((-|Kibe~Hs`B7mThK$LGNh@jyZR=%2W?=PP;glJy_Gkp1{uXA2YBo_++P!s{TaOxG68}{5B$h{&
+H^NW9eHycwIp%$xFa8fBM{abaVW^ONpN8ohzpU{5w2j3IUs)l&4B~w&4EOfg<Q*0$?CaMZpOj16#+V&
+x@yp^Jz<5PLrE+30jXbpOu;x!C#P<!i@h%rlZI5;64xR??ZVRpi#n;Zz{8rNduw&ic3_M*@k9A}A{`D
+8j>kkOPq#^GPiT}+ZZpM(C!|f?26@I!q|S32MF?ynvkERj4Ehuw5N0?oPrdP}p>ZF%4Zg~R9yGq^W1y
+QGQCtfXqqH?n)+>y^ajc1QMmFWbd*gQZ9J+~j9(c=cL9g+yV~FOB_r~qM(ba0&XfK3G@8j8hk`Ph58h
+s!K#Ja^E!_WIoi1aLi0a-B{)H2<0KIpLnV^3s!ACLtB&iKc@mC`4R8Hohut2eE%G0e_!RgSVZ?Cmr3W
+EN}>y?y*Pd9*sh>GqL_yd|A(yD(17PHP)&86mAw?vC*+lNNCu9^QPDcA@PUWh3albVn%5#uiwgo}I?a
+17hdH>9m#}*aJgf?C_%tH1U{0DY$1h$t`$LAi*ez=-T4}zu&|d=oW2Yv|F3>2@Xc9K{UdEjEmSW)mDJ
+!tScH%X)N$$L-s2s|Ch;%TR;{RpT^v@bWroUkPa|rDbW>cF$bJNA_0g}MQh9y>^aRRiw(4;&;o|UbDx
+y<f+Xe*8zBVqqt%XtN&7zNK2ZjG0x8Kt@t|4l4a2bo7<42qM-gg+C~6vy4;WVXc{JmSfIXUlg`Y1mvI
+dPeLPfrB((8k=M7qv9{P4zEZo~BX)d|v5*r6y03P6`z4h%)XFttRweh_^9wdgH(<WD5;0-`<{Fv0=OW
++f`VWbn%>?ja{hg)zyuvQCeFzyBQcBM8H)JYMG89nf}>q)BzJ%Wm@2gw!y_99JR6G!%rylzV_oAb8*K
+QFTbFo(D$gN8wN4D5A4n)aBS)Nr{3HXG<Pv3`r0NjoFZdvX5P)qt9rJgazvRfJ7JP*InVHjm)B9K|zz
+Idbl2y<~QMrFY241|02(BLFaHoHp(20*;fTS{&)D>x7cLO)(`}%%@_jUiACy2!-#~C6o;cPflGB769<
+u}wZ08N(ZozAFAROg1xnpm<Th+rmcj$AypKi7Rps!6hlh|sFe&X@@+C}nt5dn9ip~WWH(6eocv(3xi6
+LuTB*sN492FA=e_b7g+qS8-^zDxzjkk+c%<jhQP8%iq(t#3CBtLKn&Xd4CkO!{jFy98YBzCOzPZM_1D
+vBdRWW_d-NSw4<(>mYMF^@>Lcynx%EO0z3D=;;5r?pH<P%U7wScZT!Fs(P1Tmk=4Z<f1w337r(ZRPms
+Q@Vr`CcFX@uDE%+skZ6UV!izS^x5c1DNC82g{R@SuD%GV_8}<x|MTDF*Y8KiKYaKG9{#1@H93A{UJ2-
+i%FgbmyERp{=!Tj$5>ft%xSkXOVPWA!0@3<gJ4n4`4^FGDqZuhW<6I^R`toZ_BptK@9P(eW-!u99A3o
+^$kuh)Y;XugPX=5!<*qNx~dN+H4fU=x|n7^UAr3wl#1(S7Rg|5xW%S^&O4Zj~Un^02f!~$gXsRj#z2J
+TM_yhO!>)@<ajC6Sh+s*>4$#3r1o!m8S`1zap<_vXdISlsQY6|8+g92&$O19iV)!Du*ue~s3Y(fC8JL
+&QAc(pUsOltG7JTcC~w2BhH!&QYkk|A~#dHpr;wYY5rq9wTjAUt~qx^W<l$SK+b%0vKqEaiW2TI@Mvw
+B2wHF4LFnz4BlxA`WBr2z>BY#(OqT*;zcKS6IoD&P3`7vF--_cH={o(`g(-$?Ijm0n#iZ5reOy@E*`{
+XT0^(~k!YbI*TB^Z6;awjpd(ejZyTsghP86XlyH`;I>X5}YNNe=WuYL)_~d<ns314jRFGgN^mTc?TWJ
+TvAWKBZu}~?>SXO|64?3S)VuguemH76eIcWHaItcRrWR<_l_##p&k%y6PDrSha#VT)EVttneNDHb}dK
+>1%yNhwE2pM_>C)_U-!O93+l_6{sTjIG@0210n^wh-Rh?mHe3(|OcB;`9DqxH8(Q@YiBII8716td#R&
+^#%%#3f3~$W%cK!$(RFJi9WZ%H=l{RXD=bY@8HekCrtRKgX3_t-ONc7deL|=n0jQH_8O5d@!k0t%AIg
+p)0;zT3e`F&Iv4XXk7^QOc-dzGomQKSW0e^EKUW6{-*W;w%l3vXojJgFQOKag~|$Aswy#%LWL4Ac|j>
+L5hW1>F*`>X6+VR*{01anmV~3nkyPy@>%cN-T%2}qTMs;(r8`f&!D<1Cxp?g&|6;?JA4^J>$S{;$=xF
+#YysZ_hcUYLR;ya$L2$Qwpw=CUQru9mMGmr#b0R-2B60x+GRPwL~X}!f=FZ7L!s^Aq7tP~Nt2rL?y3h
+O}jS$7KPiH>q%C=LBGRALk!qni@7E<>Zj(FMrLM?`8_gWI$9=Cn$3|44}GpD%CsP-c#Z(aD>pN74bIG
+hEb?;FEXZ;W?zz-C&@igq@YX_;D--@1?OVaCebHF~*R9HdGOLtOpsQuCR|4d6CK4br+?5ggvzjH1($a
+kp<6HWS3Tt<P#`@^j1Y~@_e^(k>C*UTWYK&F1->urz}z5JsRqOag|$G3$sD*JjW-qhT!t$fti%%)VEJ
+*)0dlCA+H!!7Ltn`+}ba!G4`3Ofz&WDt*CG!WrKA{xMM+Pp{rQmpjGE2YgvkpJGM<{Hne3!QW{1@Bdb
+W3l#vasBD$-JTP4qW>1qy>!E$#JPJ7tOY4rD`w$UE6;n7vnWJieXy`#$vTViu(V4Cbj&cj@k`_VfcVR
+_=}8fb?uQVg5#Ta$Pl`MX1DyRLj)Tc&Q%wQh>kt&<d8A{BHq9R>qmMD5lukwz=@<p4&%*y4sNz3i&P6
+7uhr9MwhIQiP;k7xS7dF7I80_f-9NRQXXA@zRFiO2(C{fo;D)tTEy05{4{Awf!SmKdJ3{D!G^Lj{rvH
+wt^qh@^J0rHp-i7Nn;$0F<xv<)VQIlhoGgUe*9+cuXL)foDwNv!Sbo4)YdjthxRQq{7^JV-z88b&~d5
+k{S_V>Xqc|+G_@~yjs=oPDkQx09>H%E^y)PFt%4L?1A-bv;Nh(82|KrL-%^>W^eT=;v=A3f<J^dqXv9
+nG1*d2F-I{=U4u)dH(3UMLhN4PkT6AZ!HkB$W`{D&9sQGxpP7FX(U}NhVYlBdMjn+0+gIn~|tocwH7r
+3pxPPfiO)!`TgWR?}zboIJlXCJ|+&iWo)XmYYU&7{D@3nBq|gaqpIrPV3rE&kmT<*A7s`lIh7D;l<!2
+>n5p+r#0Qb!KU2ugy-E$uzzNd&|9S#~WR@4x~vk>@ul8V30f(Y1CS}=|Vlah~i@{?n1Vso!bSI?Q@AP
+Et6>lW(R3xpwScGpoJB3!*#L4RIVK&gX~4Cvs?6rtMc5thwQp(Z9DBDTwHTQmw%~IQY{?tuAZ<9bxu<
+CD;LYn*E&Kd#XC(t;$52WMk7$k9*9;07j?7<9XMCi4mtlextyPW3xA&eGQGNZ5lyeIF0Yy#YU93tRoN
+QgXwZXfHDr~&8|>{~^Yz>5i;I_P(V-{>u<hlEx7KDM#={&n#e7a}-#4Ba>|S*Vl!FSkhgJmAfNhH5pt
+aCR<=XYsSa8=o6ekA?>AGv^4wTOwuAH-2)mA#!QZ=V4%^F2!Zhl3h8#?}q?+22~b?%!5WZv4OMwRYJN
+<i{sUkS8|BQ7j6Rv5XMKn&30KKiOW8jMAK1cBF!95l>+-DKamz#l)1BH!t1bt(Iwu+l{RoZ{y|F!z(O
+mOc+PUq9If54`t&{D?UGNgF<&tum2Mj>Yp?38j25zI+}ScmuVoU~v;u1~epzr20KO1R8-7#XD9K<ssb
++vk=F~G~N}POj_c2zS<O_$t&w;R_qvDn#5(Jo((_$?D0N3qu8b90f$zHRk9~2YmCtmu7Z;T$trV>kr%
+|ypm(yUE3u6Z!j#Yi82lYg3@R^FB^PrmxdPCZ$!(m<-%9}ek8e-HA3#*D>`Sovr=p$>dVd2@O9KQH00
+008031s8R-}^q$EOwm02xC703ZMW0B~t=FJE?LZe(wAFLiQkY-wUMFLiWjY%g<jY+o*LdCfd)bKA&~-
+}x&hRMnZxLXahSogD9US6qr-vm#46QNArFl>>*skemnv7yuN-Y&O6Bx_cg&0YTYYmk*~>S$OpH^z`(*
+2VNBUnnlrKTWt#wMNF<Yc~LPwFY|O;iAdddI{Nu)&0}+&m*%S6+shp<GMO#Q&H@q7WyZ@`N`rPKUQ)T
+(2W*?^O9i*$<tmkP1GY}S4_LY4=k)Kz_wPFjEDXg<EH;(Qv(mu!It+d$St(*z!F|fBMP96bQe*`5^1j
+Gl_S1MJ*5Y$kZZ|kiB<kJtcJfJ<CBS+^rqi2oQRGF?>6@uHJbvO!VJ9x-i+;5&QuFYKhv8^^GoDVP$^
+C!7kA~OR4}Xjv#sP!dcW}|^0OnDiRpO;$SL`;=1U`8zcvcbu{p{m#8Ubl=`+=vW=uD>3{g=D@@ht$m5
+2xeN=ZEp*!|--`fA{ccUkz{WZ=?H%yT`lH-OUsp|EasGs?FJXc;5YUr*pzS@lDC9m0+pJmeq>o3&vR@
+VSN>=a=6~)z?FF_Xm8kJo5jd>wkh&t8v~zUuq^cmB=_To&$pxK)9@Z9`}y)>pf>T{+kxK5_wNRJGk@u
+HI*C}YD28pU;NSIzgX}3((Hz)}oapg@&HDq|jc&I~e@6<GRl8izTq5D(uUnp)g~*H%UY@~1<XVIs8u|
+!JHAB{0Sma#b&}zRCtgMQ&`MwfmNT3e_bO8kHvDgYG7sMqylvnX8U_46{qgf7bi=8Y*=uujTa+~6Af+
+F>RvL5fVQzWrB@AnA;q!jKKRlo|lTvbT--{hu;bnv3!dl&%>uy-&_@xsCW_bbA{{zswE6C?3<{wwwtx
+ZTQWAZ{rtUR6a8wK`y3|9v<3$`18AovPRm7&~E)h!0nU;<*qUjY&!L7-cC_wQ5utxG~R1<A+C3i~ssO
+c^F>@Y*+A2ROa!Ms5(m3*@OT|85ILIye!qstr(5w097A(iTeGYzY0|dxGJlT8mX(IU%_U1VocF#xe>8
+k$aui+_tgq?=rVlYO1jb4=<#N%q}DzG0-i4}Vaq(2W0cqxy*i7=2~0Yi_!}likYfaVeK_1+yt0cfXf(
+Q+jBg*0uC@iXN$V>!-Q7pGchTtX)BOXO?aAG3pdS(0?#<;<3XTl`GTy$Nzonl5E-%!jGsc;hfC<78A_
+et08U11W2)?ysJV``?#^Nio<PQ7_-5NVi|4z+*!iG%wQwD~bgCz;!*)-o4G59~!^K}mIWQOw1$uGb!?
+rJPIU=Pbd=L80vGW0p+;OuNCpJces|0dIvhk3C)n<92u?ct($7DY6biJ+bGM(uW}jVajB5NyyH_@2Lr
+xGK-)U~Wz~1qYV|1f9t&5ijAYTBqLd)jktX;aZ&W0^m{rT=60i=;TlLu$I%En4gw3e|ZY?oND6Fh<J1
+uOOc5JT#E#M4emtZx?qA$Ar_+0Yh~qDg6jY;!677C;ERnY7C<L53c{fTSy_m9&wAG%$7kaa{M!#)MD&
+Q|KnKGM<nLTmmBxfD&SK$>;MtxH$J5gvN1w<SjaD3fFWxF7=I!W*(Gg@g2=Fnr%dig~c7vIaS=4h8^K
+FUoK#{<*#3_$skph1pmck*x9`L;Db)G3?i7YwB54WFhZW!N!pUhwzNLm8+>H2&2X*enac0HXce@dQ|h
+>|*(GtxwhFqDF8<0ZJIkS4jkdmIl)^3KD{#*Sd50IP+VErH!B^6hd(F%Iq#Z71w%vEZ?wNwd5Ha|Tfl
+K+pGVr1h(}7u9e2L?Gf58Lo*Sv}WiCVgCl+@@Fnn1PD9V;}65nH;>V1a{qDsfab0{=!SpEWu^kwKUq8
+3rS1O?I0!uN2F>TAk3;yqc<a7thd&05cv``a%!!W=0o^AL(_zb4{nUN*8;-m0JrM^_Ko-1vkO+PM=T8
+3>%k4zcU@1T4iGaWd9=7{?LJ_Cnqn&}he2x~S{}qRQVX33IHIkXEqNrDjbP-@gT;*||MrcPsxScqSk%
+py<(7=EgG{HUK6ZW~ZHkUo~bc^;D*UeGxQ-}1!Ng%<ApQ2S>RvBLln+hDj!NibwMQdOf00Bcoio$O1Z
+pST1c@&ERB43@D9024x9m7cTa5M~E$W$C1{Ur9UzBd*?zxVbb&3Qt^Me&M*Ua9RcQwB`qZrcxsE_3-B
+ZThNZdd<r;SB9-LL~w+^LYnbr!>g6ONqEKSrj@Xo-3mv?g8^Hku%WR<i-mZ6H270+NJwlB+v|>oVD`W
+TRe2$W8fepCj3x3EbVmz&+3mN?iA4YUIdRapPlik_1?;BUbHhryi^!(8a?DDI3+ZEZ(h7}L-N0WJei)
+_Eo1~wX5R_bz5;Z0^MUD_JdIzlN4j}^H3fDj>J7YLl`w0j$;2HScXYfcR>mK6T7HKNym&yu2KDLlc@P
+m+lW2(hBU`{rL1RtF4$w{sGo+&@wf(u0pG=+u&s!YU6cOl_l07W7Dl5b&j#<rVf!NELGB_I<!*svCK+
+Ja#otqmo>mwEaus5lU^4=s@*a<`Q@6SnCEhhXm#aI8rlm!ZthM0R!_Uc3)q&Uo^SF-&s0Ey1@_+}DEc
+1S2}LQI3BxKd)Ad%unCDdjfPzl(e4@r_&~)JMe7B;j~?2Zw#chS1q907+6q!e*|k(h`(A`$H=#U18<D
+~F$0WWYJ;xTfuQZ35BrOErwb9D>S?9ZDtqPXZ@_;0TgBhLE)RjH#zie)Q$ztWo>e_uWx$*#&H4~}z!E
+LiQi4Lckg9ScRLu+RQ7XY4Awu-@pg+1!G}!Qhujxgt^P?IJ(`Bj^X_XG$QO<nz;13QFFu1HpdqHPb;w
+6zw3HwPpHy0`*h3KQuK`3koMY?8<DhzV)UAcFlF`E>^*&ali0l@deGzZP?DIwOy8(k&4qFR*8Ndm%JA
+C~&yy<5@?m#}*t0tF6?MssFHIR&bQGjMqTE0-CBHZsvAy8-+8?JwO>SqP6N?Ho?nPXeqE@I+)W2z0Lx
+yaTI(X~AZHdGT*-mlv?_Sf1QpkQv-uUWQF>MQY!!>f*CIS!i(UNlBw@rOYgmM6e&K=RFOo+0a@o>p6I
+WLu&d*dFCn88;5~dbWLbN66uhQUm#vZ=h{U+25bqhx<8)-OWzo#9_X|~NMNe+E~)(^X3!{SA;`{0*6#
+E`gn=$@owU)(2L-7V5A=Jx#@tIe7Pu~CZ0ofF+pT20GTMOkG)&!cRnvmujxn(n>9e%}*OMs!NXiWv0+
+_vRs!OuhDw-xQH^7i&FtahQsXWdU=)@QfZq!tg&jvz(R3ruI!bvE?&Q)#LmYcz|!o4yGKmpA&)3h*<R
+Zw-t=W}rOl3byhv^UM!Ui)2@dF<KD5{Aie1)dNmn;oH9R&OA#5E2t;Hp38R2J%tVtJn#>1hbwLo$Fq$
+L~VkSd9#vwA5`23!G*ga?nd}^ZweN*AmB`Xtf+m0w+yR7vXnGC7%+<>z!ms~Z>MYx><yR$OF^}Tl_aH
+yL>$4>C91mYyBcG^NjMg@-733<Y-ok!UXSWUDxbum8vS}^9@cLEAMnx=^?&1M3}RY|NJoTdUnyy)Ar6
+mCYGs(H?{#Ks-s+%(^2mBGhG}Z8QVC}MS?PC)`n?t$Lqhc0Gt}kC5&PLp2Mj;hN>HF$VzyP5<XD7)Jh
+3vCg0P~mqG}-xC&Zy%s77QKI-4mRxl`?Z_g%;)l`dzTvTIdjqnZX5pQ-Gu>S^eQfWfxLaLT3v4G?l2%
+mR4~NVkwS719|Nb&Op>tF)8l3N>C8z6^e2uabN)s8cO6!5g^=VPmo+FG3T_Z!4KPouJ5$h;1hnABRWw
+yWfPjMTdX6V*j9#Zk3*(zgP-u&ezLuc*A<-c3xJp0wQ6rXEUcHKbxr-0&MAQM#yI~ZRJ_YAuvc~2Bvk
+MKa0K}KRVJ`YYX)tMF|!)v1K4;k|-b!vNoL%?j(q%DFbN-h(FDqin7xLoeA*!m<SSeE4f@@<YK3x^7K
+5fRu&hrMQuEa3s%I*+3+;gCH)1v+lUO4MV-KV!LC)edVxQ!1o<FX3%uCMLJ{Lc*^KfMT?W>RO=<^iG0
+j?h^vs)Hi$Fd3R9EdR(Ha705l&SNh*Q{|uFY%~G^Tb03SN2-Jpoa==Dt?#lm@l7FH*CLJgnbBfS@Ran
+BCnP%&0|LCmPC9I*3N-vx_aM^I^eZ2SI_3Dlp&CEYYa2`8{Zs6piya@!NH@PoOg~uNwWQ^S5pg><B)F
+Jnrq4-;}GD-~qL^{!DbDjfGRdb;kBRu+S|fnIaKT)F{l`6a$Q7rH(b!qJmjQfaZTEsIWrrA<LZ*6K%6
+TB13Z<op1}QMu5qmTLA4#nZQ#7wf{G~G#2i_<+jyZPn7vbV8Kg?(OQu|VH^vxNo|=7({;2vD_*P@+mz
+lU9Fu^2TOJ_)`<2_%Y|L|s*$_zOGxf&6!hl6xmu9XE<o6p9Upk1jBl9dX$iA+OvC+fi)0jbo!7;%{gK
+V_?Jbe3|gQq7U&=u_D^6kI&kI(L?urn3}?)f~tfIUt3A^V(xUoFW+ikD3)V+mn!fDQ%a9PJyOm5~??=
+p0?6L8FG^Qlhw&Ie4BqFlQ$dJZF=EPLfn%M=1pz!nPC&ox((Wn8n3@V~;2)tQDoak{q}!pD>`$V@cXb
+N-pt83sn~M49-}6h(((eU4#VBz$=yGlzMW!dlGvrNah<+02hw4P`8#nm2-fMrP10oR(^Mrm(}SCmR_z
+ngui}QkhWE~@>G@Z$B*pf{Qc#-kllYA0^J%}CSuqbUhHWEOrA&_55gFy5~T&zsfnDJq_Kw`vr__Ps*v
++-9btRY_3u{z4<d$^gJLn&CX{7mOW7KiHbP}x4GkIAEl`+D*x?3pzk^VYlEQ`SA8TaRODc&_ZAVPKFn
+r{oTp&LhnGyNly}S6mwPs-1O+|ISU6$cS(S*%+g0G>0f}Ufz+AJ4Z@_iZVHAYy@W&d%-dazHw3)s89Y
+LJ>7pc$?~LVz0|*^Q5IZ@NL<^Xa$u7K~iAj0XFM=d+Z2VXmOt&5_>)>p2MzuG7n0481j({$Nd^M_gSA
+`RXB`3vV(iVuA6%Fe~3>-WCTSOmVtRQ2!QgrAHeHQDgx3EE)(6oe<(obK7s1%5QnFhLJ~FgpNAo1$Jk
+2zA_gWjbM;Vc986Y+dZT-!$YYttvQ`INVXJomwX{kms?&WZts=6h-2b;=DtLA)yVuAu5jA}my9dyT%O
+(CKY}$M-sqr`OfZm$xTyzWkb!?m#fv@7u)|Hs-c;-f9oJ3=ux&?*D9WA-jM5X04Ag>Rp1gqud51k>2_
+^{w>dKai7U0@eU=LKH;|6S@&G=u{#6#WiySaWLfpp`DUJw8VAA@fL{gyd>W1r^Br7m@&-7U3OCkOK^I
+Yn79ibn-<gy&>L_AHA$qXOYGFC=2oDBl35{xJS>bNAzi$<6ppU|gC$Ye;_4G}Tzos^IUx>w|7Q$qf_h
+O|{n@b<1mzz=i<;;(+W38!}`8`d*Z(-s+}sUWS@rDvx(P3cFtI#2Y$j)y&4kDt@d7`DGFvuB#$RqcEY
+XBXF%E0NsgFRS+Abwmfo5C+eB*HaU-4yQS^b7=^;Axzuo){KKiDL>A6dpgh8oBY3=|4cPS2)#EBH!7o
+MdN40E&PNU%FS9<gj5p}Z2TUFo^sY@v}eUt;(f^@S?ga?7p$b%ipz);}R0d+<wKXl7SjdFocf|pTec!
+m`Pygs>3a|=`Ux8~f`qZ{FbQ<BiDs__re{GO7f9MIvI!K}7PGt=Y3Vo-*m5%sF`XUHXh2z-D>(INxmX
+bhXT_V%*QR}$o*(<w9Q+fL|u6s}T*dT2k|iWBvYxhTykh&|~Lm$YxAq06!o1G_b3e-iuzYz*Q91C9z)
+VlG(Q1AC}pzBlpWo06T5hIBw<k@6)v2%=S;*>Jiab=9Kw0PP1#`rf)+ov0Ufx6$#hd1cI_Il|&5743Y
+&zQ`dyy#=o`>wf%+sXh}GGROqOy~Tz^)%sx$lhFL4QYDVBbHOFLR`r_X&#HG;e@LOb6k1gvU`G<#S{8
+l{GImNK=#BNugEagE?kk9~DcG39tTBB<5u31xrzuTs{1|ZxLNh!>nC0LbG0JnWZFS4n9QS~v47=kPG?
+tJfrio4BZ5@Vq3R4wg4Jw%}y=0NH{zTLXT)oUARaVD@JGJz>aIXK>Jx_a936n6#Lb|t}Sb4|N9h#2px
+jpXSVh=prwU^cQyf?X1-|euwDP8nY?3x`5ztbx8l0>Rpb=25&V)9|AKt$V$J)P6&yYd06MIl5mAjZ~|
+2-0+{cLKx&B9)(HmgKvV^-S4RMKD<IKa9Q(C+^uQ))3-uh;(q`1e7bL<EcA5$y|{*F7teWy*%(@GB<I
+)9&3z+DkE5XLCZJ!FfX4dNl}JP4@3putO^cH#kh`&8KPKAv>;R!(k)DZ?1luW4tC9y2<4hKkM)r(BYc
+UFktM5lc)ai62%2&ckV`$I35NlGb%nXpY0f8IN5FNU<fV{pWWFNR&iTZ{lZmzTdU5!#LK1isY2rOiYY
+lX<I?B^c7MTu#C%rBOhmbx0>oT26C<O$oIKd1H{hUbD*;}gbiG=|B^$aEx4B==JP*XbH@xAW49Zusp5
+F_9d5@#*jjj)NbfQ(J<@hb@|BBCg&ZViM`8UZW`2?3?kb`>)?oz^iP$G}7?1Ly4F!|3w+ckkI$9h1XS
+H{k%tsLZ6BMmGsTu|>QfxpJe4={11*wp4@1&}zp8=*z>EWyiZHIyBD`qzZ`X9T14*=<lNXXrAjbNXsX
+L2;7)n)o3)m*Qx-DN9%~SFdJ2|+Bd@-^}!g{yt3+#c+B@&IBk>gS|DFJaoHVa?BnC({nXZEv9K@~nD;
+|m8?gDdGBUt=>U$G*ixm2&2D_6i(JbvdQUZdY`ybxPO|;tNWjDG46gJV>GO#K%_&pu0aqFUo%s}QaET
+wrGNSsY~Psb>f#93WB1+ws)yVfI|4V>mg=RfWE=0EZ1=Bvjxk9@1Egwx2BQ3Suegn=KZM$|}_@$=@?7
+bnV`>&j&vYaSjJZqt%lQ+%8LRU(eg+jmocgGT56o_(=~#pb=&WF|{n)}qd^(NA^K$(YRNcW4;k?|WlB
+L!C93CX^_>*P>J<^*^GUo?MrWgtjW|Oau1O%!wWN7Y>nu@Y<OJ?_1lW<~(@)n_JU?lrQ1^mkZsGvgcs
+x^uBrU4xGyMEgPPKUW-&8?!+*CI2}zUR4@d|pQlbN?O1+m(-J|)2fOsWd)M2vd7h^|{Q-DLhxY2dLar
+bAXuJt(&fXo5hax8+a<*UMx7`^19OQz!f*BeX(vId3>sf3NDimD`q8H95rTFbK9(@3}wD6;b6Lyp5PX
+uva<niev^_brU<J-~0m;1-@wFeE9b?uujqC>PT9~US_))jyKK$ou-TV7EsucGssN;}_Wpft85np(=-T
+(ijm_1%#QcLVjsQuEw@OFq*6zZA55T|n+geQv3PR$Ch~fjN5vv%b+iYTv>-A6&R=2qW!H)af<NtO)Q$
+H5Yo$tAoQ_F19wdAA~=(#XeH}a%`RnMw`dUziO1*Z1FeX?RWkcP)h>@6aWAK2ml;P_EtY}x4P*F004d
+#001rk003}la4%nWWo~3|axZmqY;0*_GcR>?X>2cZb8KI2VRU0?UubW0bZ%j7WiD`etyud{8%YxW-G4
+=CP{f#+A;4`mXB{h{gzO?^feXoAblIHMp6S7zjJxNi+Zf+pe_wUaqYZ45dk~43epG!`_0^-DB+0vlq@
+{5AVzw~WX|a^)n97yToidur#w_V-;}-aQoZ;Vuq_t8zB`R7kq^6Zs`i8Er-(*RWj7B?jVVs=OyM?k;s
+!9_6U+F?N<e=&5`ZZN5m)c4a)-UCz;9pB=gEn5Py+#PLuBg;JBcg?K_4MGNFuBdbc4nHJgX4o%T()q_
+YBW;I+BA+D*?qDb%cxW>ilPB_T0rky0{L9zU-*bD$Qe4yo<Aj}p}JPkcV3cmj9qE#L{;GsTmWngYGa*
+TPGGv^L%6&Ux`3(YSEsF#YuVh&=Ctw-wUjz`#~PY}0-_Y#7OdDm&VCq^f#hbbAkgS)LxrJN7uO*!a4+
+z9e*%YDTU=c^Rb|#zv+c++l-wXVdgVXQC1YfDT?~)1AG48bHq#MYO0A1}-;Cs4E^9~Ue*LUzOw%6hy?
+286YB?IsX0XqKBC{FR5*U#^%ML++QC<n0dnp^IN|g&Iy`1znQLVzqagbT#7>*aRq*<XY;}7Pfg`QAn(
+gaSpo2^w<<f19;$zgjNWc#)C4v9QBO~IdF^V`=i>G|Q&4->L7aQJ!lr|fv-Z?z<H##A;_(v_Y=%$$R!
+%=y|*duu=3YE`v>9ozr$Q*cR1+Bhn7z{5X{bgM?wYf)Jl^zG19Aed)%2>9{7-DoH7rtOJJmTn1aC$!h
+drBFUsP9Qk5b){U|>}I>;7C_?>3|mQ-gsn~pcKxZ3&jQL=V%RvGehS!npJJ=Kp5<nxU7GB*VqxTP?5F
+Ke40i9(xwT;2&f$-Le(`Kd;?}5w3aL>fESVCKXl{|EG~WPF87juoAV&uY4k-lg%U&PV09`iXW{GNp1U
+MzTLQZX1o<vH{D`gk5h(y!|rC>v1X+l9_dRLOK3y!EIyD)3c2G{0>h%Pr$Sfe2owP;}gHXFh!I4>U%y
+5IL40j1y`y@~vVtjmW>KB1Y>Q%dM5^wkZBKJKNAJI2^r0_3XZng~-U7tp>wFoWcne~*Ntr6E{?Y9Skx
+^OKW4pSrb9+aIJ0{#?x!svI3=?MZGFd8Ob^y8h+z{hL>Garusf!=c)H)F&?qs!=F#ialL$rzjO731_S
+qDqoDca7U5O7oril!zq|tH}Ez}9aUm3t56sNJNOP0b>9=+Z)cq=2L7WM?Ikfc|HfTvcW;-Ax#$_iTvX
+1=s+=$(Ja(^EBlp=NF2b(jqBw}^>DaGvO~^!DOI@VN$A4s>p0=4Is|ZyFz9RS5$}Q65PVet0sQAqglZ
+V@}0pASKaTcBapTZQ$L33~9AH@l-l*_sFy^LWax(LweejBq`&iih$<Rc0S8}0K^RO(;2UKp-WJ~JM7Y
+a=shb5YB*bLY5ov6Zo(F1sE&@!{@6s{2r4oM=#cFvDc%sq6K6?|U_7$k$5b5+(Qdy<|c@)~J$w9-%*a
+XN7{x1+F8D1;K7KsvT{W2Y;_Lp~i7~^rd?G4N!ccQ;ZWR-`L~K!L-HrPJMkze$SHZvr#%_DdVv8cR<J
+C^Pev+-=4iZy*?X{qKbioS?ItWGsj(nc4oHHibu87%s;pE1jCi}^O4T|`h*=khMfh^NLe=_C|w%*3#G
+@CEnWw&pf^_Hi+q8F*DsC^nW1)7`?;j<XO?~-?XN={4397&s2ZQ)`IAK0Tq&3;xlr4agu|XYBpsA!^G
+`ALs$$b2pfk0fb=qk})nN`{pI~#CKhExu4E>D81V6u`_O7&92vC>2B=69&bLISWC#~Ma>>x{}nHCuAZ
+cKwbT6#wCu;?$RUBVw?Y&)WTN-kH96<z11mdQBVnop1cU<x<BrPz2v3UX*(6{FK~U9mE_S8(C@49OTz
+FJRiPjexh3UMU3c1|F4RbXnE#p%lw$Gz#W|jc7;T`35ZxXWDTQvFQ(Hs-CqU)0jxXu}CcrPo0jpxX2<
+-I-j?px%W)r<~j_DLtK87jVd?XGaT*lp*>2GUxj3?1$!8R`1KJ~VQIeccj3BglYfyeyO9oExZ%sd)t3
+@Z@V!pqUKXNz^y2V^r+gRcV8*KA+Jmew4NvW|n9v--iz(u_xrt+d#n>IN#R>w2?oS?Eef>=0pCly$yh
+2XXrAAyK$fDpd(5;jSrdrnK9~4`}X-5gRHku;*)H6)&_vW3@A^}F5c*>dF3lexI3vR2)_H|~d^}c2q{
+1?Al<el^FgrxFq|K6pSXK&xlF0bC5UtXNP;d_4J?b%=7pT9kOH5?8^>R&nk4@UD(OUCb^c2CN-Q-x<$
+`aW!Xe@^JZizomcmZ$ud=JGI*hSF#%97nfe(bKOO`-`~sMWB%UfM;J1<}(SL_yT@Jf;%^0)q?Q@c`;3
+|s>09FRYkt!qW)t{<=4EniXR=AtROU!#v?$lPibH3ye*G-**`QR_nkVRKn}_1VfwAu{)*NTX{^+|5e;
+}-hY6&Y!L4k-Wxej{7W*E-<+1S);xWil!s=VOb<1awUumDX(F@YT87Dq@xZb46c2!3E>PjM4g)ee5p<
+AW~yA4;TF?Q_w$ro>oWE(a%JLIidzE<6PaeKiJYU!3CzJP2kcNTRMiWf4DJQD!}gWIo0zKV|-IAFZri
+6fLlBmVC}_AmHwA|@0M(QP;wmj6x$9RT&J2;X`+KOK9-R9swhz%YNH<izuhzSn5`Jq{?gx)<VB_(R;c
+ZF__OtNBCocj&{14-dZ$;RY32f`1|5eVKE$rkA0TY#|#&Emt_(eu0!d*pEUR3X-SnLrCq}|CnxHiD>u
+p^~hFIr`?G${X~cNJKHzj^L+z*@}LcM<6C%0wXF(6*%O=46H13~uK1l0M)0MmQ-1MJdeq}_{PgGF?Ta
+yn4flQ<_ZHM`Y)_hdh&s_9pM84t5%pcJ0p;QH#^9yS-)ju<r$Fn7@q|ZZh5o;meh^yeBJR@v22e`_1Q
+Y-O00;maO7>Q=5cjtK2LJ%?8UO$&0001RX>c!Jc4cm4Z*nhna%^mAVlyvwbZKlab8~ETa$#<BaBp&SE
+^v9xS#59QxDo#DU%~otSi9%bWw(c-IIMwg_7Yss^b#cA25nIYv`pLVN~B9tcHE->y)#2fCM_u&^ux9O
+khR5`hx7iTmDNrg$D|%f|IO;+vvBP%TaHF+qbrtW;<*qzC$+LHoZcJ#e0(gnq7t8!t#|lPtQz_qFFx~
+)XsNAy9*rI!Z}ZFByN`c(y!p!&o3ppS{mt*bAB{#u$*pB@x-eW>r2k>W;4>bN>EFdxB&Y0P_|7t}n0S
+`fNwo=*!=n`w*70R2?N$&8FtS1`B?=Tj8xi71t(@WJ$ed>PN4M4L4T)NUHp+3NWO|Lfj|4np62Qw+A1
+piS8rh01mx{oux^xm)+2Zywy2=98M!2mo8M|?SzvITqqAs~9kF2(0U6)L*2~P>J0&;?D#UQ+cbX%$LY
+Y-ic;SCmyZds+RLvi7*#t<LwZ<yW*L#o)UH79-fy+sv^3WU=uda@F0mhX8fSKNsl9G`<8PCUDOtxfJq
+n@ffNOroQycT(&q{5)`J(eeWUf*PZoJEQk<1-~OiR&e#kv86!ktXf16flQH@p)rM4U`!+aQA^{ECc*A
+o?z}M~>~Nu_gEtsK`BLgPEtt1PFjZnMa>|-1?bw!E?wpCuFk|BeY#f;+FhSgB_kVtuKF5ziGY!~i(xE
+1KPBv&1rlk4k<;WT-CR29U%3=$aKx>Zs!A=f=Q1>ao-gRlG$rDjp@&Bg^-*Z_)%40Bqm(;fkqI)kQz&
+^cBaSyRAU7nvrwW3_lLMF{v;%h6+UYL9f8K-z9=09sCW|WDbg3S%zY{V)TdTr+mQwxF|NR*F8K(d7rb
+*gRL=o+e6$m7~#bsI{UtQQ!?&!j4Jg}ifQ$o?oQZH|{Wcav#Kr)#&-{d6f|pN`1X^Z1O>Ycg-T%h{<d
+_44oj_ExRd|B2rcy=JNSUC*5TZjmCrzGC;nKy|4YMu6lc<hNScE&nXCR7xs|Qs<@CyGbN>w$gdalf)F
+1BDg&#;wS)&aJ5kcnovJe1p2`HbsjO$Wksp2m_+z%Sqi0J01sBr0%61oQMU>g!O{Hf#k=okY+0|@!ca
+61;N|2KGy?$uYr~ab7yAzOy5t)>zld<5F49Bxt2w(!>xr)=f8u2=u8h%UGRB1dr!YFOU=^lDjIBgL$0
+$o|v~=}&`byEyM1}(3bdcNYG-GOcbi#)G{^e94Q6fFy9xoA%HWM!u_P8@w;U^r<(e{(ZH_f3av4th<1
+KjAfUOSTYJXw$Ltxzk_B$yHA2>wgiE!-Sgt$-4W73ZRTf@2i4cr0#vDGn2qZ_2o3_-jUgvw~YU8DEa+
+IjWiC<5Wmq1!%HyLz8w%Xj#yUybSLHN4IP4vF1^xg7_z>zY^aMf17p~Jm5ETwoi@zKeBj|Y|y$CK+V5
+UEe}RI;YIDFY6Egou7aA1_3OMbS9&GpV>51o5XyhZQvuCk75zk|njBW*P)g-H_DgNKT?e+#?TS+3Oj+
+YZ+lWJ%=x;`|Xz;gCR93N#{<K)!M>D0hv;`r{K{R82Gr7Z3kxa9aQnOajl3Wc#jDXRWgWq>Y0@y)(3Y
+_ypZHLFLOcdX?0tcOv02&kC4fpM!MLPTvZ3rtEx(Zhw`)7zS?^@v|XznR{KWG0Un~x9pXF2}&mtsjOS
+}4d}>}$g&epH_^$hTz^R?{*2n$Z=rY1El9Q2bB=*J0=(MHDgK)^KXtQwCcCiX2#5V%U@fn7ZKss&k5^
+RJaPxQLFA<{6Oe%nph{`og2Xue?yYR<l)X?^20d3vYnPPzkk9!=3_swoDFe-7IV%B7|Q_gZMTJ>`n{$
+9bUbI@4luqyFCH<I)Y*?$*B?IJF7nGy*Vk7MId1s<K=V!+3bE$hFtlF8kyWcU{j38=RFIstrNz;MjMM
+7bR2Y8f@u1JmKKF#iOX^*Q3m=~Dxik}iB40!$=&aTD#z!wA5Q>1<3wFM8g@8Vf;vxJethvMZ=$jtH2a
+|b*_JkH`LSMkQo4Y3%tabq23{6e_ZAx!jb*BkL7BcEAsp&>MKed2b;p}!k=f2!zJWn*4`02S1BjinIy
+xs`66T%c==VmM<8{ylKYJSbZCqrYmmmvm-SfeXoH?dNy7e{!H)lkM7$=w#r{$<`kn2c#9lzmv#c)3$K
+ER{|dx_kxH0AnAt`Y(~y5b%~mAm?5g`x?ZQA-0^ZXkC4s>0|0dQRieOVD}8svB%;x5L^+lCriRC#(8;
+@i-_Yzb0rEW`MD>Ox?`QBKXiy=q;yMax45C@&<&J~my;8*6WFNI(JN+p3-S1POQjwManWfOB7^FpG<K
+3eoL@aW+&$!1ch^+S2j5rpG#4-Q1-=Xbidp+0OGsaM@fBI{Txl4`YgNEP&&|fB<7RmAKyRpTzPn?{1O
+3Y#1k94nJC5(#mouo<X?Dw!w>?{3mn*syN^1MkDJTbzXy83fR<xW%OsQJIvaFqw2i<+T0F|709aF4VI
+rPk_I0?WEHc37E^x@}4{&4l-#~JH6czU>5Tur;M`1y)OylBP~2ZJI3Lhh*e%$UYk^_Cuj5LqvppG8FH
+tT9{AVw4a-pf{UQ<50g#r{+qFhF_+Ebvo+AKV8;4$q`Nx5Y(*BV!6fWWKe6XE^MSl5R%^ZB>$(=U0VI
+<*YBF-eV*S9y}}*q_GaGz1Sa~VXS;Nx{{T=+0|XQR000O897^_9{T7%r<_iD-xF-MrBLDyZaA|NaUv_
+0~WN&gWb#iQMX<{=kb#!TLFLY^bWp8zKE^v9(T3d75xD|f)ufW*ju{6V_-A&VNx$DlRNjA+)c9WSn+e
+Zl^Aqfpda0$?g`q1Cra}F*9L@IXDcBa)sB9XwsxqRmeuRFD4i^aM(eJ2(RCU>ps4C5=U>fVTj{e5=ko
+*TInXJ;4eZYx+N*1WF`)2jR^>?_rqjP+VnY;|B;W7=A-m{CkNl`Odt%xt+~jq;1xp6l<KZbd2A((W=q
+87OpTYvjz)cBe01y?OhWXKxlSUjFp#!<)Os-RqxUzWs2Qv5hc}8%OxeZqIY^sT8e|s?navon7(X06#C
+gPIV~HGp0pjWFu;J&+A@1#Pl@Jumx!KT@7MCIa|DN3c6)#^><O4+58O8`k)1o%6F<!Mm4fza?SWXmo;
+D2B0nqpt^;lsxCl0baNL+~hCefQ9(J8)mJI%bl*^iH?ZunfBj?2#gU|W-xqHq^)vV>F?>H(YKcm;~on
+|F(*orI*s;C&q$%C2Ks)JvxQgvZ><v9?m#5b!Nj8qh?J(#U(>^t~)ZQTZz;OGW;y8Sl4$yg_Nb^Bd@G
+xzHeF0l9=9Pl%5_(oWXVdJg)KP>HpZo#6c9Nd+6;<sLCGrM~A^6n~QSNO2Fz80VOt_6jbYIl7#w~W2*
+SSz}3+zvL|Z)Le<>Rxo6tb`_0#uDRilzIL*p}&T+%&Y3wE9!SQ^Z5zONR1dF)M)`|Z#InAwPllcd?$?
+PG@^I8{6#flxqKYojar<x7ZP#?!>|9283tL06A`;et{?$`cf;$#p8=6Zg7j*)0z_K#IJOvXDq_l$1P^
+aOaNzKJS{J_y<n|J@1&Y)du@tQ%H><_kAPN}8jpP_(#I7|td)?skKuO$#kJ{L<Qf3Rj;dgjVB7@w@!+
+0l#n2|B^C1fy=d&DN>N^c>C0h=KfIeB;su~t-huqboUhroblbFT_>XoXWUDlB8`T5&@x;j+XQPNLWvg
+6;Sxx$Ad~?^F*OP;0BfnQTC-u%ps*Jaf;b4;qdP1e`#~X%!c8*w&%y;k)k3Qh*rj?M_;BC&;$qdjE{A
+ajbi1TYb=Qj^B~7wo@x`paWat+f5C>0=<zbP$0@bd3y*ie{iVYZgT5Gx#~98rTu=rmbJM4!_AY`@2jV
+Odh*@VKVH9)tLs4JqJH}1>7SR2Jdi_`Td5F{;N%j*b0duiT%ZaE1$xEl#GKwv4;mC9_x09X39}cX!Q<
+dvZ{+=80P;2kv6b6wyLJ$FAtJbywe=|jr+yk4I`QU5SvQbMt^B`b-NcGyoYN+R5DuAN6vg1<kSGsq%}
+b*?n<DsnO<u4SK7^!ZMXR{_1eMqcDElI(Y}jA#?%oBfMbYFZ*ysXz#@>-St~7h`%X?g`YINU9L4XDhq
+1q9L5Lr>xA%+EVs<8&Ns$*~AM;8R4m>Nq%lK7NOa>%Bv`)aW9R&KWJ`MVDc^ahcVe(F7MZO{Z<YzX~*
+(@@3)TfoXaypXDs<^bXUUewvZUdI%%v=Uo>4{LO!3djSzswBcZ8=#4C+cFx`k!k>nJHa)S)<dRoPIS_
+764eCHcaBm*kZ){~7@TR~8@2yg+go;>BE9`7LZf9(?9L7XWci(f^=_Ze65B#{?zp6qUzEJpB4TVX54X
+tBHe~`YvIB~%gF#c;9igD6qSoepX}9ru&kuTt&!`BlA<bjm?6Ze9pvfKTPgufW(hj^st_{X47tAtDu1
+7TiDCpZ8zreaHDYBCrs6sQ!^l+%^0aUR9X{F&G2d!y56Ewe*4Kz=bdc9_20Ik_U^&Q(NSSszR9_<9uf
+IoZke2p28+t3kAxyN#^#40YyR~ZFmC}BH>h((Y)iP-s`n-ai$4$Rvq8lA^9_(5cKIy(1FgXQ_6i2Ebk
+SisU2FhUPEN!9FuL46eMKWf*YTs+ap+2eo^bfg$27mJw|^*Xb7c6F$)N_~6fDpUV+UPRWY*ZIO%2Dk1
+v@Fgo~>wNj?%Uo!!+_&@j5ed@T$^G~iHsgQCJFOp{+)1xtEB!w@RU6)!i2WfGSPh{CoQ5KyolBoz>QK
+L5c1}n5#j5hMo1e2wHVfMbN05XpxqPu`AR#XnS+XEe=+rAx#rV0EGdy>_%>~E+PP<rOe7*<hRurOEy!
+^Q5T}4%Y3qf%uYY5S_#c#L`;#*QbQtt~D#8y>7LoP8b954ra*E+NzW5ta|39~tdnJC=B{`?ryqShfKe
+ukw9@F6qgDj7qSM+|}gJ>QD*qs@nW=nxD<rd5xjQ!^qM#THlR5ygTEyu=^T_dO5Cd+>O>1;0_+h_(->
+MkGR*PHavCAS~u7q#rQC3mmjSF4P(tdp#6Lh1I$})>E~~6e2u+g@CHD?se>JBnD%WC8mNINV8w@G0k)
+e46>5U#aYwuL?=t9ff|@Vl{T2=A>LueRtf+A5S^mhi{!`3%;zC2;EbT8kXC4UY_;$maAVJe{XRYw$x#
+k;6OcNaq(TKHoEaWW?3_HoM&p>K)UtsP)0AT7@VByaj$}6~HqvVvFi74oSmF)p2zybYB)GQ|du`aRhm
+3YU-i^zfsOAj{P1g>w(R7EDMcQUX7*^S_ADi8Q^@#B-65{J+v}(W9Gy=Q?&s||iaMD>(CS;tF4udbcn
+REX6k+i494QTk`mfaMi!yXofSbAo=Nav?eV1P_fbLB-t2N(-P6wJu%ZluCvKRdPg$o<&O0~)bf@!y<v
+gK<+eT)6&(J^BAJ^Vmx#^9Od(3k&!YSqzf~WMP9|*oeKK<=OrlnjW#?<sr=pQT7<;i=$yabh&6}JBZV
+mCj4@hPRCr4Fq>y?PFLPTB6UrT?<8FMD2ZW=)CCD$EFIU&p+vVuCuPELJ`U)iZs_Bl%S{HBOZQ~Cj0#
+cwv~Ylhy}`5BeN#r0aQyf=q$OZe)3n~g4m(rx8;)~CD4l(YY^536`#>jTL$6d?7`?}XiqmR}laGVcT~
+wv|LHbZc4<lF)F=#Csaa>f!s45j;;HWrod=5Br&!Mn`#@0wQF3vKcy$9Xn03K)R<W_>0+tBhfLR5%@H
+Pmj~5j772#Y96rHSNWWi2bF+j(ZP{9+u75a8w)aI+D3)Q1WL*`6`uPu)kqv+FTj*8zP@qLbP<w&>nNw
+I`Ud82Y%<RM~7cfL45Mo%idjt@e`h@?VU|PTvXXyfO(A{4$*CugJXUQG9Dyp*>78ksNQ!i#Zc)-Xi9p
+R2~@qu_lf?gwRM+>Ro~f8HbfIY{*29OYd<&DiZ1-}(M?~0*%MmtK!rsgOoYUZt+YF9C`8tZ<_Gu=OVb
+*KKAbH0rg}G5KBBKrl^!ELXCV_=PLK(AZo*9dV9yv|CC=u@hMw3nm<}2t|8P;c`@#tezVgwSW=x{yEm
+{t0%Tl;OO-&iTz*JT&lf#x%Zu!!YaC1ICm&r#iNzwJcf&&npd6C^9JB0*#cw&ezM8o5eFfKEmQ+(MBv
+%!?rBka=D&7<W+N$s1E1S{;D)A0Dw#r4CGH5^cUTRVvp!b507F&6H(G?{bvnDI47Iv>Xml?vgyi?vEi
+ynq-gu8?+zW0LGTYsCF<b2bkhUido(dz&ymIY9GyddW0~WIVesuwxDh<G4v%j*|Zra_szQ8Zfa7C)P=
+zcLX{-b@YNBJf?{pcp6o%J86SMlqW_BVGJ7#X^+OtFuxvdf{yV4IU1UM5J|bxl$^jvB{ymw!whTGsC3
+=6c6xh!?ZjJ@pp)R8^&uVTrse`jXXEYgq7toWDx8A5F@G5BCevJ+DmVU5OOEa~b3AWCj^OXB_<8}#D!
+!_v-r@~1RM-#~i{(Eb6D614+Xh?Hpnu9UevQ3)+ED*VU-`0N59*rCJ_*FV@(#j<c1&D=8L|^t&X#5;1
+AQ8(Q#AP8pDe+yXuNF76{ok^q4a~)lVzW!K0ofFUpI8iG6li0wj!A237s!Vf`qX+t|fmV5xw2<PqUkB
+2s&1WE@Mp=F7qrRIgdsO^(fYQg?@pFCZnZe^05rYJn7E`ds52308mQ<1QY-O00;maO7>PO)#zRq6953
+%Hvj-10001RX>c!Jc4cm4Z*nhna%^mAVlyvwbZKlab#iPjaCxmedtci~lK=Zt^onII1tasGjBXf0f|G
+DZfHg3?8*qedwXrs`<k5rRgxqJps_Jg3Wyz4-oqsb}Zq=)+yX)B*C-IcI?l{l#gu5;arn5N7m^V!0Fw
+eLvez#h3JmIY|VvOQ2<fANzqg0_p-jw@UJ_~tEz}Pl_81Y#J=p-I_IB@PIDeomooG93tH~Q?|@d7dp9
+$KwD30*JCl9cVUYa<;^_>>zRW_Wov!S6|&X84U5^zDi9KXabU@nM{JcT*l^#-P<&VgKMPj>0+n;zb$D
+Viv{8)C+^JoB^YheF?G&^CI^C^77ogu$bUy10uW*gW)y{qA>?yuKFheI?h2=5{{Xtal|d8JLGJVWiz{
+Vde;ANcyj#l@byX0y?FD!_n~(IQ!x#EO%s6c6dni_MLZ0rFem1PA&bW>oA8t~m{rCTP~sP!aOU$QxaU
+42y#W9qwUhB^``4FyZ8nYlJme0sPn~Y}4us5y_9&iqXLFD@TA$2kJn2e=)_Jf0rgwVj_In^!!Vz#5gx
+pMw)oX8ke7OF0WBu2`x2^An)e`bIfPOL$9Dx3Mxc+e<zX5A)eelA0>{@_%)jzJGwHSN^uGxTW1GeQ@2
+Zn?Lux{79{&aKGJy?NP+MDZ7G@?P?9KhfL)Pb{N+Bou8qa((+eRX>L=Ip4)9`VP~+2!HMNv8$NaD4v9
+j(dK1i4r5`H7Q}Uv;F<Xw!UqDFMk`Y_q~5gPy>fSW1u&DxdSgxF1EMSTcGo8!XLhizmMO7+5OIU%dp3
+|2{RK0_a&_k!*}~i3ajO&`4Er5Hv^yyhZS%}m~L;ufa3GL<=%Tq;E6K_XNG3F!k+l-nQXGT#|+0{7DI
+A`g3_*{Ojhbx-}b(*n)u2}rS6tdG#nta+f31MDl~WNG_Mz^A(erkx$~Tq*1-b(ohJG(Hg!50{q3dnb)
+pB$m~A&Q+gieG>xY<q+vse4U&e5&k>U0dhEkUXJwC;7TW6?VG;!Kl&Z+!7#c8L?sm@{dM>xRvG6uU1Q
+_<<~HPc^4Zcir%bikino%VYdz5XA)qrz4kzJ7Dmd;9MF@qhl;$%oUk^S}2mF0cOh$3Oq|(Ho9@KE9g-
+|Nb0Kqj>gbl4kk+mxuY+jm@p?o!z}(UjAykH|zgxp!M0)jE2G1nDJ=X|Bi#mynbM-Oqc_(8|(o*64Q?
+Sz(Qa!g&)sOd+za(MrL(u_i@!iV}=A5WCx_d<ATMv)}$zhM@RjS#T0J{zmRcFSV$bxdE&5ja5FGk{oX
+tG^bq`pZcjhmT;B{<9W>=Nwl9p<<zfF_ugNKWGP}~+SFJo+cQEc?+m-cR#5F!iv3Jyj5tgR06m+i!Dp
+c_VLa8f>_PT%grgzf2xNv`x!1b21zBN!}lx}O7W~1hB2BZo1{n^E(dw$lxl-dVQ=4$##|Dg(<jTZ;z<
+HqClCMaKcH9VT+B`w%#!b|H*C{B>lWARH996hMUcv0f2Or0fe*s2__H}4Po7&oOn6B7NO4;r2`h-j`}
+yGOl~;|~=M#$W#Wx3+1$SnK@9J_au!#PR9dvjV0j*dtpc^a!rnF}}B8hVM(fDj|e<g)v|k0RMi~>;J2
+OeA_>K_W{E)HK5T!v;)9swML<rLM)nuW*K^$2K)x1Mc`~%j?kDPOxux{LBN_N`3M7kG9n3|B@kvtSrF
+Z+@E1c|n_Z<4XL>1wxCsaFh~0Z(PDn({8RyZ+xt(Dw?*hkLo4t-9godD0#l&9Zvk3*Xz^n+ji6}tLah
+OOA5pU$Bd_9Ojlr+d7#%11U6em841wnQH?Hh(Mt6j{89$YsK<1B^L1-7>(#$W@$c*MWBuGla58HH)5_
+#wpG$FRE`#H?ar2xVUw!dzo<$g3ez2C^`wk`ZlKt`2^JG0`EFMR7(y>@@R|EX7pAgngnxE4FCeyJ!RO
+hfYf_K#&qK<XA<P@Ap-f6ULBTfCANfx#DRK>4FKHs)Gu&?3!AYY9*ZxX|Y3!>yWNGBw9ykq*ExNARyQ
+5)hvmDRW>hH5J}+9Hd7vswW-6>zlCi(goN>nm-y*AnilYX!ypW@xya&RH`2DWA?Iu3)(b|Qg~4YI+s?
+~ubsF@E0uviqE)yr=FoQIMjUF^ebSM*Mu_!?_3Uje>;VjV1@zB9Qg*A{On**E)4Q2(4*{Uofz7zzOE+
+vv#gMDy-`=CT<Elv^OmQ60=Ss0HR=5@-mFLCmjg)(v1rY6oc>{iOYwP`7_al9(26vSACsM0sk!4zuml
+sNTG_}tpSayQ6cJim#fdyX{)0D%dBG4T+kRM6!Fl#AAkrkFxrANr6>!^VLn2|1YAB+es$9hPt=Hkh=1
+wr>0`CwxJ2uypW>O}#lS-H<c>;El3yE^MTS7LqI>fd$blhfLoGYgf>z^Xaf*p0OZPVj|H$^8idUoGLa
+Hq|sQK+`hBP6{H0@QQ~03(2G9Py1_^ovWW-Q)&ZfX@jdq~yVOkY!JE#oqTo2K%2NLR`|s=uc5fk=*~X
+#+)*RyaE+mKFoq9poZCiCj8`ZCmE=8{6Dpu_dYv(CX&_*~j@P)8ZeH_G{f)wES<wmDMz_xAH?&4uXKs
+qM)po~)6S}ItL(<{ZsdAUIp4~X1KL91~q{-l+Z=0UR<Aq?e)W+bSr1=2A?GY|&*!eyCj0%tWv2RiX)G
+aiX8z^AiJnWU7Nu*)}C_2~V83qfJllmh|NlN+F?iW$IJK8sI4i2bU9OXlS{Trvt85^d?{kaC0a6_~wQ
+o3k+A&k$Jjwa?mT$(9VXu+18FvDVKMSV01X2d&%pP>+9Le&DDV%%W~l3BHBE=?q+_I}RXLHo=wqJPfA
+kLgWZ1$Hzz!`~deIhi%$hyMo<2h}9zI$?Zfg0m8^2<B2y6Io2_WAP!)hfV>!(S+rBc5&}vvu2OOdXtT
+bM6x@$QnPDhI)Dd&)Ww7sj4MPZXJSHU)$qqv5jF1GXnMU$Znq1|Y1p#I8G<%0;M^{mM9LL?EmmCbeuV
+_9Fy8D`uqt`gBLFh*CIckumEK<{7w~J~qzP=cN-A^I3iMW@9GWv<~>5wOd;!_(iVBS9WLW=l9FS+A&s
+LFCrgUAj12e3BCtr#LueGuvSScVWpw0M?~Q+pglzUfyE8NT|BZB#e;D8>vV=aukBNdaqy9MK&MWci{>
+qLdl_*4`-5eZirbx*Dp8rw$DyYqD0~YU$(Gjzk;4_P$mm*4QR<V5HzJ51Y%QQS5U!h`?tDzB`(L3pFu
+_1;P<{0x!g1T)yZq0*C#%Z{*o{{iRW!%X6NL0ApPc#60b)f6NL>MT;WgVEV&3&>+m1A|N=iA-wSCY*r
+!TmjtRi0u)w~mMW|1sDKa}DiQXvqhmvAhkd4uKV;>M<yKw+imD&OAA*$f(M8#Y^Nh=#y238O>cUh~&Q
+Ul#)Y{xB?pL})d6!IA(n@1=nIlk3`Wb>eY{0Zv+YHwLA~x*$49QYpxFj$|lLojZQXp*!B@b8e$6|chY
+q8UO7?mkh=uL;dCoGyHzU(^)IA`Vt#3M6Iz^sm@S;Ub#gOJ`Ol>q&6*@S$i+%K?eLFq|+2ZkGi7ek!I
+AayHJf^zqp<lZltK(v!bnK?98B@Kz_>dTCfUXplom5rl?2+%?#UUbLJjSfWAky#M6H17nl4C+_zCGaR
+90(g*O5ybKfHv=Aoss`uO*J4}jZ*03Dgm6rg{5pW}Hozk}sKB@o$N?PuHSuS~N|_BBLhmDJ!$eUHXfv
+wGa6$Grwz>7Pz_5Kzi(;WBDkr?mgsax9uG}@D-Db176wQXi#=!=oyr2OrW1C7y>w3!>sQqHuU&o++bF
+0{OmQ^uyb<%QDYP(p<#EDG8#X!mR<IGJtg)FIwBXXWA?1GC%DTIw#9EYhL@N8_y$z6AnO+(eBTuDWzd
+41R3vUg}Z%~GEG@jCJ*Qi?p=mt_-luT(K1GeL30q{z)F{|mvupzl+t!ZPL=#smB8dVq+>QIG|~AR#){
+*)gI40vK?k>B%TbB(!q3OPaXSioCwZ+jd(8AtN}L2<Zn9SOF~v{lO3gcM*~ez>oxFYN-k{4)Zuq^&P7
+Cz-BaTV~IO0`5s1d$_9kd!b(U4ve*z%l&K`;2tMVYB%qvHvAIHx?O%}XB42@E3p%C*wKOS?aV=m@Snb
+niAS40u!VGutTgo+yXCzGMY0>@)2*WFtBoa>WZ<Gnhn1!!79+z7}RM|xA1fg0HW6JFS!isz;PPAB3m?
+24xLicE$z?8FWD&P@m69ZI98%T<$>y3eS{-wlN3{5gLnTGKLlEc0NdhiVo!qcJ>J>O>--B3NFlyF7G>
+v$Xh#A8_k88?o!W!kMK0V^q{0CTXZWDU!1)y0*IUdXD-Jzd$o5@3aqDC)s3rg5gM0#P<8Y0EUQQX~z)
+DZsR&5my)xR}6#5OXhAipYa7NN@-*z_`tjmN3Ck1O(we$Yr3>ir3sE9nBDII*-BH#Cf6-#SK!AArAkM
+x=Q)r<q*Pw{KpQe;ZO?Irt6yQ|+EhJPE(qNRmgkw5HV{km(FDCXRe<(h{<7mpLR-5;%4S#5pLv`Ki}n
+$Qj*ptiK%|g(V34pr74Z>IQ%?k2g>R<dmDucTZ2SWHi)SF+@wr_iM`{6Ol}#)=g%F`pRZ?9d7OK6$4{
+dpjiqUb4U@4t>k-1qXgddzWgyT%q3a$y;0pvle5gd3+jLOjk^~uAl=%Mk$(Pkm5oaNK?wlipi=3&Zzh
+R)^^IwhoV_05@vgzD59S<MQR3r^Z|NGAi;EC3dY<(dEh#Wu*ce1017S_eX41|pxAO<nzn)hVicta{cP
+84tl>%9c8aA9+$$X6OxhXvr)Y9`U%5bTXs>yEmxo$<oc8C{zm*r<2C&VQJSQPqxRrXl`Qs`Czf%_bFs
+7I{O+1ezIg<oikkln*}r5y$8i(m@V$kA=lC?(j`20Ot0w5-9jS>v;~Gg<t~z|YpZ@`&or(g6$erIm&}
+n$HqoxMQ37=v&9FK(qSeM&slvu-O1&aYThpc5FdcGaqip{&$vOV;x7`HzrZiwJDuT!yADtfl|L7t&PH
+`pMt7%&m@RV&tCSn(1tAiG^Qx;CD6PI(;=T)R}UOEZ_!&)dGWLU(>O!4(pO+YrTn1ICi5_@2{PT*BUU
+zSM=p{2Vj>(|QCU{{Kp8S)@X?jl`H<>8f#_LtZnL9uLU3nay%8Aq1IwKln>4$>3FS1Cx*8!Jn%Qr!YT
+Dz@xo!2b)yPgUZ~u@PFhK*I2uL!Ef%*1k%@TkRgK&0d4v*ZFuXs?tKA5Xggj7ZJ8NJwb#CRmd}O57lO
+G10MQfLbD{k576yXp9TVSoS|^B)U+ZB2~J=2$H}ND?@vX6Fz~RJBayhm3FEt9Bs%mw#E?NXz*5>3Ll5
+UR;of}^Lg*V2I`sm5j3xt-Qr+IlEbaDI9(T#e!2n{4M-wOIkcrS{OgY$6#R(E{%CJ>dZ}fuc5luMY=-
+jGa@9onC+@ESxVUtPT5m3D*x(d)PaoQd2DuB2G(3W&M*k`hqaW6?YFE^Tb3YyC}zTD_&R}P-!)g8z2!
+O%;dWg}-%n~*4Fi`xuX(AMXs6$Wvu;xcR5S+B@6v;&9CW!#;{Ian%JcC=*IO_D0E8mmCDJdyYjI7XK)
+J``P#ir>)tY;h7~^W_aTaXVQWG-On@X80*H71^>cI%BGCT)joHERAT$IDYI_hK^TEsfsE(imq5sm*Rl
+^64p+z_YvUnHjP(?RYR4)IG37>D%+H3p!K_5T0BN98+4~hE$_Byx~#`=QkG^nAm&)TNLAw`<b?gv5Sz
+<6RAyL@P8XZA5~HL2t*pq?T}Md)Y~Dh<QDP&Oxxs$h7m)D1x4XN&+Z5koXwn#jz^*MNk}2<#`E^D9>h
+`899dK3}FB?5m*=t1ki6~&HKy+-Y68-NYhNT>oMOX~63p>%wM*(yeZtY18%b?Tz18>gJVs+SI2Jz}J&
+&2PB=4>?zZCLNpc3PEg;0k*yYgDQCnL4k9^JELRq#z7{V7;LnM0fne^<q&k9c!T?BrDim4)A7+0F=l>
+K96P9OjcRx8Ltsah|9C1Gl%tQ`-lqQ7i`XgAj5=vpO;B$>wclSEt`Trv|rCR)YZ*7;|U`mVame}E=|<
+bD17D~7Fw{MEQ>Z6;9!@D-GU--i%XI#&rVD$Xi<2H%a0AR#cGyJX)#Kxchg$+Ni2m2`O13&iU#n46tu
+P%A5g-wLy8=9!hljK^`U=X@WJ~!2Wfp4?p*2+IAASYz|`MU>c4OslP=JdL*4>OvP_FtGj#wOu^KLF>O
+g8x!l`r&@&{pF>q)~=ab1G0($??GGF*7>`PDw_ta7W0OuMGxnJr@kyeugH8QIKMcO~(e{=we=08mQ<1
+QY-O00;maO7>P()K=BM2LJ#Y6#xJr0001RX>c!Jc4cm4Z*nhna%^mAVlyvwbZKlacVTICE^v9(SX*x!
+#}$6(ub5H~qFjnrYXkvYvw;gZsF74MYz2M@3}U!@mYi~SXEQUa6@mWvd}l7pB}F;zTT9sDWzPBL+%K!
+@)>tpd+Qv*&{NhMc;fHT~H>s?tMb$NhH%2>=PFiWbl6o@ncK>=J@CtNZ)s#tU(-?0WRZQrypw^4`;rD
+me8v6`O_$=Lsb+TGXtye3t6u(Yy&1bp4#~<Z?H1?Azb`;^Jb207l>#8z#Wl5GtKlE04ntqu~CWV&HiD
+zME?}DJpG*?l;7UW>N5dSp2a9h*qQuHJkS(rw+!0LXOT!7?$OBTZ8zweFk`<9$Am3aH%y%T%Wi9$A_b
+0i>908q_lgz;MVEzV?9?15FAk}S@=^i*{^f@rlPL9NmH<?gqRI+_dFl!4D^&_{Aj&~Ts!R`lpg=3B6k
+C#WoNZSaSxN)?J4FZwMtLFBD`fJQ<a&#Ew16jpd6c0{f4Ru(%P&BdAu$=YR29eI|l7F`Q13(BHK8}JF
+>5^!+4TZn&jo~>&dy%+RAY$iy9yRyBdaIl)DB!`gr7np&?_@!ws{lIl3VbppK&S0<;Q?U_b;X8y{H2>
+Hh3-QTBuSZ-~AR2XcCE!f9?Cfe0g5cKlbFoFRl!2w#8UyMz`JSjbaIvtF?FVt!u#lzVu#;N+(x^vr^T
+BbT-XbHQI;ffrFd-zzPGOn{NCz%x1WVL%hlqoroMs^)SS6Ka%V=*l1g-5n1m9L|w%1KpuMw}Ms1)p3k
+}Irgy|FIFNNW_7h1sH%LIs~!>JfN+TQDSUPSUcjt)+^NtpU|OtEMzPD11l{;4~(K&L9i~*Cd@6ANGC=
+z|xRoC$`o+sFI_vx3X=?0*-}O{tCg?`5?um6L&uyV$Y1O8;q9$LoEBPa%|aWP5C#`YN<w^>W$qwDBe(
+1>63Xqx`*{1heOOrj@^A9^d*hcM3gKeK0_<*3@e2D#hL>Y#vQK2^@SYh*<{Yt#6h*TW`{6>8EWM?6&9
+0;s<=uoaHWI%E7ep+{Cz2Aujb;rRK+gDzhXU!HlD|LvE;2n#DJUa;KX{5IH+W&ec-}pv0|eAD&TrMtC
+$z*W;&ms`30H|;8iorXOju*oiD#b(PXnE>7x*C@!wsds{A7x<kmEFIEz5Cgf9twqS8kC*%X$TUJWz{f
+zEIY?FQ!lbG~OXQ1@HTk$c;nAPlW<{5oTe@iENtDfF5U&9B6prD*qD>)wc0i|=yWE@&W0r%UnI#rH=@
+sj1Eq-ZASHcTsvO-G#WMg|r*@>&=%-L>fvpDk0a96zI5dZTxnSk{ve&eu4<c42a@S%Q#Ie-o3xQ|M>L
+!U?8a+Jvn*mpTWw>?aPD5uE!ob%QOm?H{#|z@G<z!AK@&IBkNl*IZV%zq2QqZcZAu3GawpxH4H4Vz0L
+S-E_j?-{)mc!?iD7P{3YG9<Xe(B5Epg{EWva9CGd>0mCY|cb`7(~sb^YuD8R0zLRI@iMFuQ)fN(ztf4
+-hSr_8d&mQcMgn|%r2`;+e~vX5>L1PiX{O&Jut%7iC!_RmmWh|fGll!gnpgoe%aTH`d;@dk#RBRpIfU
+Om+)aB9Pi)pbR|4S&5)IJLBaE6f9NpkNu~TGL|Ow@kO$&J&6o!2|#*6B-&XQf^9lf|Pn1N_{KQyoBK-
+=8H;Ip-U1^L_i2SW*LG35?UU#hJ1u-aYR6ap2aB+xv);5gTBo(W5=x={Vu8`>x_oBhh7owS2b`?n%-w
+Av*X)5d1sz%pWl<K*^zsWf%yIy-huU%@*NptL0n^dm_-n7VEynZ0$rt4;HLL~m<Y9WyP=3YiTZH*pJg
+tjAMSqs`TgxPaes#P?w9+xjj(OZ`rl$WjU&R*;lk2JA@FUo8sl9}QXpX63Bv@-=XerGGlmbd<IrFm%o
+mu99C6gSp;4D+73fd<a-8b?nXc@`i>3I>&CQ{>rf3+XO@Napp>h&d>Fz^p<$!6rGXe908`507c(LpGQ
+<67&{Q2!~+T<zhnttolgVekY$p?(lTok7H$`#L&D{h!bt7wv8(t6t>x4?!KCKx&wp|nbk{1&G$p3xmw
+4rh45iK`+M&zT$74Ta<+#Ur#RI||cc9$`&WsZD2N6X$9Xrz|wc9qn7`3(oz77WQpa4J*Us7Z*yNd^P!
+(8;cbMAL3wkG~0YN@c4D&tRwHv#Z4s41It^F!4o4qrMV@I8c!$6klvB?XgWy8oPNn8-{$`duE!;5xsQ
+t(7hcSE#g-pGXsRjCLdoh}8g$&tm38UqL{FDC*HxaIsSIVl2+szv^{KFyj-F@abp=krB2Z)bio05>`D
+XA=iL%2pJm(b04wsz`SMy%+V+XkZ#H&ZqBrD{6LJBe_86aQyb)(H1UGT(Gxd=TU()>DM;s$c2OeaqP4
+GXJ;lV`cFOyh^?S0T?2K?nD<Vjr~hIIFK?jaJ2LPB>~dVLy8w`&^M2SDZhJpVKho@}BDJndUQ{PPw|o
+?#-m3!yD|Whhh>RXKd61<wrnK{*OT*7lJz!*TZmvD$8KZ9oGAh9+@WBZhCB$%|3@9U(<5bR%2Vsx*Yb
+nW3@x8`bNE(_J3OMLk~Zr`0r3l0|XQR000O897^_9c+eklG7A6zQz-xdBme*aaA|NaUv_0~WN&gWcV%
+K_Zewp`X>Mn8FJE72ZfSI1UoLQY?OOeA+eQ-qUr(_Yqo9OJjFVh@E)g5B9i=hqI6>sJxJv?RMXoH?)K
+cIsE$fN~d5r_^UM^2^Gy6d<Kjf&%9Z(b%l1Spt%+AjI=3__MBT*J7{3;-YoR1EA_wL>6^$5JyY{s}=6
+Y9Zx=cP$57l|P7hmw~YxyU$4maCL48JAQh@HLwgxnN}a)3f8tpS~w!BaR43c}(+I33<GbauwXaZ#VPB
+ibei<LFM|&&+@DLM^m3n7$dL7$4{P*$vn$R%p^@x;cGR5C|hmv<Z2-Ua%w-4hx-p6lG%n#k|n4zp{s;
+z>NJTM7c3wrlP5zWK=S$7>G)#O6s;^V&$A^7!+9Z#oP{BtFv}$=cmmq8Fij-OX)1a>vw%+{Vfg%%&R8
+le)A{kq_<Yjq^?n?`nw-73Acw@;_rLKUc<^kGOtK{-oGuwK@XA;;ho_k&H#ALRYiRgP1rt7b#g=r1Ru
+;_fz5M&-vlkcP#qsm;1cd*h&g&&28yy^c^WErRlz4&r-5Y9(+tHFnqX-O_f^m?h_T5myvxLh`EGz*Wk
+#f7bPI#QH#pvK~f5r7^g&%(H^-hmZpN&x&_}q)xoKO)ZNtkA9miL9s;fRAkiO9j=mpSDE+^{75jHjCc
+Ii8%JospDDu(KdCBZ`qk6diax`Uk=fEU;oRF4ECIEhbhpr%R$Y07_0?YnPcvzNX3<_>~JFAe^mRG&Ph
+L0yaU2Otn&|!zckHagoU6hV6#tJ$3$3llf>GD*h#v(E{BLv14Tr4I|%Z1L^@tDoPB%RAfrOA)$bF;08
+qG01FIW?I5N2>10B#*=C*Pu_#rI*^R$`q?C(<SgU_WfVP5(`+Jre^lO+SPUdr#L#z{pbqw@i$>buKzF
+%zuu%NG8H6{2ki}65p^Xja!UL?^%AAo|uNCMdT$XIv*PK?m=`V0ahL?##@=yE(e?7Ad~O0~b{0tj8PK
+r4%{qoX5xXux6NozUp*#V<dM&wo6-Ad|E2FMhqsvx3K7je`ooAZ87tK1+W<4pG94M%Q=nxCl4=1M-){
+rmUS=?Vek-R&p>|;rpKUk3u!c3W-rMV`NT+RDht|<}P1itff>kql%6Ni+u$?*7u+)9C!n(vk%$Ld2B*
+D&9dua)mJbz!EE(8hb4tQ*to<qWaUH(4Qsy!D)b^o%*PM^5@dSCq|3KsfJGUP*h-Ep#R$Xzd;w!uS)R
+znQg1maR+yC`rcIW{M4Ki8pJ4Q`dL~gsm?t{(N9jvQG(nVtH-o9o;8T*#eg<F<378>(&%yK}<7{fpQt
+)e@t+_Qv!<{c64XQm?2Hp@bl8F_KAOXJqdVhcayP<wRHt(nA9f}*2S@rqhzSdW50YTuxOmC}p=zDMFT
+mE+bHYeUdg97UjFzC|dgC&iZ)nYQ&>)<#%QDp@KC48u!m7YH&svamo$Xd!NDO$4ZCJ+Tss36JZBfwn3
+S?pCrD#NLgdmAE2Xh?`#mcxY4vyuf|&gueIs<wva$Zjz$^&OH*Yx~**r*CS^DtThCNdk<jY$2eCSY$;
+SV?3&2?$^XrD#GTvjqpuiIkKy*9h+LD85Ju@6}2+^8(e<}47G?d&MKejm<~bn&_3(i4`G&vU15G4VaO
+4dsJi3Ey2d_2-^I5HDoYjI6*tIB4Rp5@@9oT%lqS$F1teg%5fmu+7u1CoRru%1#N#~A@|_|Q;JBcIN}
+0EfGK9XTw7oZI#Y2ms*NhJ1@V2=>9VhCD#5qpidu`59ZzKZpRqm0m+S&}Zz(JX|0+}{!1%OuoZRlep-
+UG^tUF|6ftnY%nzI-}5&~;ozMg)e2NGQ81Raq2bDrRGQ-zRABWL8KP1S$lp@_tI8VMrpH>NH{Q9F_VV
+0-S76iow1LG%r9-_btXs9F{B;;25XLtOVbC6Sk-Lb_U|>D8v_DWP*9Y0fmM*XIEHs@@WHTDhNTzM22B
+suyn3-Pc6JF?<0Y4GMBPXZK0i8oYU)#a<<CNMs47FkIU=GSK<i4Q|^aXmq1xhIk<8inUvYC^fC6>P@W
+}rjaZwo)29+TTi`vY;P0ucD7F_NEIj!3eB4-j@NLRqS+Ab7S7)s3O-#d*@Kpg7cuvz4ySFm44GF_o5r
+-ZaAcdmpH8R^1#gD!Q>a=k+FlkH)$KGJJk(R<;Z|%BMzpyRuS+tfBCROi`*+F*~N}VZ*Gia3I=Exvn-
+QWpMUOe|}*;kz$oVQu2xKZDMm;<Pl1MkA>7o^pCI;tge$1r3%?Lz~r+-5lj(<!vJ5S^$lZQkjszyxT)
+s<uXH)>dov6fXLN(Ht5qu-%lE_Qx9)2e0ZYx1(jtk$}8<p=?p;q&mx%4&;=BkTqr!938@{2I!z!4_rR
+PLrZ*D%67utuftz^eDG%f-LO^fTe>(2UWxB_9AYpeYpD5Pt_{KqG+Aah80_{+sHl9Wc<Kj2(p(B;?a#
+cow@;tK-*HF9wDE7Yd-E`OcekK13fn5^WM@HR(CFj@{&oq&Y-I&KGJ>3z*DM*snv0b6fU)19mSK|*0y
+vV*+@qkoWA529;P_wkS-;<GQBS#z0Jom+Y-9&+kThIW28r<?&iKMFtt0nd7HN8KG^1DxwXnR)lWt{D!
+^N4-cFsBN+|w2UolYQW&68Z<U5ATe3A_AUz&FOT;%b340s}l>!mX&@AX!OTGw644b(J$UBvpA9BfIK)
+V3}8Y0Da7sm~hwl9C?l1^(80~H4yz-33tVIeWq|%Ev#&z53LEyD&}CQF@GC27;6Pk&GYI7RQK($He;w
+Wc6Cn3nO;%>8!Fcsk8<5ar@Dp8+qJQbHN|_yIH)Q!<PM#f3(Ex?eP)+dwdCwp_Dky8b*6mUE_^#})hv
+e8QCFEo$KEDkY20Z%d-H)HF+|!=aAhj4xllKxx_esp0kwEoCJ+6ttC(ph@F;F4fp7!)Ji5l86dDP}>~
+973HDNU}fGE-=^(l#&R9Y?E3n~6gQO<nqOP#hw-a(=_t1ZlOMz6J(Ytx!NfEVh{ZWpvr6FV&2IPSDb&
+J2g!X|8$dndd<|PdH5vFZ05gul$yCe&UQ<EZKQ%jo04)&3&y+cQQzau$myJP<}zb^YO#Ku}XgY@E=nr
+wXDuM*{qMP;Bh$qpzV)n8KI*|_>$|6Hh(>t>z=e4ew8`gbWyd|%K=0?wd&`CS{nWYZSWhy!r<_W!@~X
+$@>x-#M`s<iusKAl@Glk>{yY1`KYOS<1LRXfwB1|x&kY-Vsrgv=+4F)*gw_pls6I4SX9fNUi-Q8sYb;
+f*Sgll<VVxOuw$ak=@rEvM<0q_SUNT@&EUy?b*)V7735@+S=4*2NCB)F1%ZYAZfTMOzak*Va4ZVh)90
+Q|f=(r2mKtn|7QsTkXIgJK;pHq?jltP!`I3G}C#(yXhGs(4`2J4|gbq~8^66iOH)MoYcbH?K&qSE|m#
+51zYa_3@4Zvcdt<m*2fJ;w{)%(j}CmyAcMA5+1-IBHKFXx6Gn=l^(cBS>4#La7EVH>X+>r#q^j(3Av2
+*LUqcsCKoDYz^ICn|X>Q+If&>bld)$i6KZCH*DlFd8EdNcnIw$3nhcqm`Yj)cMXSCMAmg~n8Arwbt3F
+;^+pKp7MFwWEs3SWS6$=4q^d;L6K<LrxR;9ROqI;0=bN$DQs-{Bx9g*AFLtYso&Dh-soPVseBb;Znjm
+OQ6Wz46H5YYH1|7oRPd>V1n%7auce-0N!e`4gumjNS(;>ucFI?|{{|it{0|XQR000O897^_9$E^s91q
+J{B6C(fsA^-pYaA|NaUv_0~WN&gWcV%K_Zewp`X>Mn8FKl6AWo&aUaCwcIO>?t05P<Lb6>56$CCXS}K
+J1wu`hFZbllGDx-W!9lVk^er0o*w4w7<Q8F-W^Bz&Rvd9#;D$vFzmW@$un-)t?W!m06PSRJJdl(|9Y>
+vX%dbKeroxkI(FW2fN+Cs+?5^sS1|GC;5EiHc5W|EY$u`ZP?fQpUhbbhiyOEt2*TwdyUU3yV0piWLC-
+z`||qjiIq~am*2jA|Ks&Ld&>*9lU1zJvR3`r82&T+@#6>kma{CcnB1xAr&{#qL6z)HrIOXZ<4cvF;z}
+iPntrmq%w!Q)a@Q<<I^L{)K7T$uy!`s*`^zi)h5gf-vAATac1?0o|6Hm!9xgVmxc&2~V|uy%K@3I!6Z
+$?z*g|bj&6N&H&J+frvirUnfhdI1ROV?NxXjVWMJ?oE=&iZaYa1jRHU+AJi=~(bvBDA1f!<PJG}p!s+
+=z7;bTk2`4v{eugdwznL%>}!;4TWdOFQGDfUl=PtZ)Q$Z2@;t9B0_rfla_e6!0EQ-SL3CM!*qFfJ4An
+WWZM_;49jh6%4poPJ>wC2)MEZe1+mT!^RGz1Kxw_YCPa8Bj5-oz#-sC{SZj&gTA?G0KFd6E>jvklo^l
+q+Jl){S;FJN%y^c}K+v0GV>H*s4x}^FgK-gWVQ_S?Kf~kll=EO2+H5or`$ptTaw`y^ngO=C)~zK#nVj
+N!$5<=eN4fUtI1(V&ycq}8B-m7s6HG6SO&kHybD9F9xn6f5{p2DtvoEAPA}|1%u~yFjrg;^uooP^Ca2
+iBy69H-xGCToFp(Tz1OkrS2Aq0a-ulvl*u(1Q_6!u_w$s&1)KsX7o->xCOuR~lE2e~ce2i&ebs9&a>2
+~lQ3+G_%&w`&Mf=+4lHR~`Yag&U&G%vibu=`*|s|5D{8PG`h%NFjaVhV|KnBT1fT8k*+&=8XufPohI<
+_@n`Kvjf*R`X3wFq|&o&34_Ec$4C<-$&`BAqDkoX4BzSQU7%)LSXyI53R_z)@GF6!TUmiRPhn|<5Gia
+usv!EhHN86S*Mv7sVsMNUwvJ8U25WNlbUjfagh!U$p*?qxxe5!o<r*O`?oj=Wngk$-8Yy6i!__D#ngj
+6*4P6HBPI02LDlZRu90p;>)dI>vibL8c?#gQsFY;5Ijjp@POCARBEoJecvR(dhyM!{T&nYY<2FFMfB*
+{vZ+;^5U?9@f$b|z=xcu?g)wikg?^9B;Va!N0WwxAd@KoAB9+5iCz5OxE4G|oyDUESvu7i+)YJ388rV
+d64Tcn^|jyF4E4&}b;|nL?xeX-d|gjy4lJtd>UmswQg{qV3pdIS0i`N70dN;UU~CTRYTfnJF|y1!zZM
+^zG=S<V3}gs39Xu+X1Bw2b<O+#N#dvbqNDp+5i_A00(^(+JboeqoG8j;8{u=pTcWf4WOypDx8C2rK9N
+D9sxX3n`LW<HubtD>U9{ac~kXjPT&wuqK1sDffc9$IGG_6+km46c!U8SZGZ<1fFm{vZ9&|qYp72c;L`
+^9zyLU<q0kl##taAu0|MHB02lyg3>4aecx0lXAz?sB8xR5m;2ScHHk}w8-9oVeUyenrGS#<k7C1SmOq
+LS(w%Biv!@;uOI<A1{r9sqN&kJu@cz?3#1f>BI5rGf{56wrXLEr(HNp!~<h`CN&Ii<y1MTAQib&+@Re
+U|fgt%yUHba4l6)t)$vZek7Lhhv$PhAtgRGEOKmk&;@<K(72sr~z8!B{?5=Z>Q=#KF3|{ENUTtKi{G5
+8(hkSuAIUE)RvaBbR2_g^Vmo=QWuSrNm(A$TlKEYaJIszk=|dE%IFwp@38$qTr1!}osElTa1gO@_k+R
+}@4Cl`yK+h+=GxRA(MxobkYh1Gbsc*CQfMt9g1T>1{s*XUEzBpo2_5r78gHK@R7OeE*u-_C#-OzoYJD
+3IK@CNi0?<7<Yr{Ph%&xkPU=1~E2J0>wC!2qM5dIdN=!4k6P+)K36ksW>ZNRSlQp$qw<XinT*=f%wL;
+Upc@5BF4O9KQH00008031s8R#1O2A4CEG02u`U03-ka0B~t=FJE?LZe(wAFLz~PWo~0{WNB_^b1!XcY
+++($Y;!JfdA(CjkJ>O0z2{d<sgRwDX4^d?ap>-HSc&#fdO%`PWRd~Ab!^u*0#voXef^OHu~d7kBPEXg
+=8fk)&tNdfGVtSoYm}9$x!l^K`6<{Mg^fFZ|20z3cif_6hB*Yc!%L3D0FA2m0*iznS4y7@-|pNP?z<`
+6e)@b1>l4g*qa@6k<}#rLuTWYX!`=L01QroykN4AW^C@hUff^m-!g}gKD1tXy83)f+$;_G4I8tnkYG7
+}K;A?0B{!eL?86GRt4j$v`)EH&1LJEVw_GsPf&@8KQ1I$`9t`zEkhFWKQ)p?>wJCN33GHGW;g60up(C
+v+EcUnd-CI&I7Pt;OrW}JlyED0e`sn9F8-u5a5d}SKC2xzTwD!9fCNY?xhhu*_tv495!QaQkyyLW!+$
+BtXraDm{zZ0}UV9Iu!Vr(TXar0%X{p-)*h`*Js(&AlwYGq1}ko~13yOBH{^pa!*}7d}N)o);nruPND+
+eAMG1;yam^B<Mm`7vQ`HhXN~qx~(!N;4)r3?=Y(^ZSP66(cd9f)4ZtBvmzzTR-C`)>7DUB9p{qt4!0F
+{=vYI5o==*JC#wW(*s&BSy%v5({j4qf96gGj2aXh(pD$a1M~AYeeM%BuLpvT?{~kR_0z;rJ3-Qkfpk2
+a`a88z|9QpOp-%8H34#~+Ma?vJ)6wiuF8bP^l7rueA3^ZjK8jO@>!?-L<(zcE7Do6W%B0J~w_~xb)tg
+srZ;;>`xuq~9?-kh5$*cj}20Z>Z=1QY-O00;maO7>P~IB=)A1pok}82|tw0001RX>c!Jc4cm4Z*nhpW
+nyJ+V{c?>ZfA2ZbY*jNb1raswO31T+eQ$+>sKri1f&8<kX$6O1o&XZ5@0}a3dlKG2C<}8_BJ#raF?-s
+>7o52y%s3Y-g|TVOZrPX`y!Vw>tRQ*OmaEjH;<j28NEh9yrj|12&H`0J#M{v^{UlE@VO^GiPSsR<AiZ
+0mw&E&l=vy~F{1$zl8B|06SRsGG|?12B{d4-^+Q5$Zutm(G`HxeKR81E1DeyjI6`y0rje2kX+R=IMrb
+@g>mWu5nw@`~T+Anudr3H^Ap>e@^eTz(kms#Zo+iZe5WQQ+2}fx}!35%kU{ZoZrUiTEy&J~y*L2-Mv(
+xcpHtztfknbSrJzNFOGmG*;zmYatpYte4$Q_9|4$q``(y`ZMD8$;A%jt2u)oLxt3Sq`b!o37jMwm-B0
+a<ezM;)|Eqd?ug#mNnW%iFK_;;ucCdU^6N$_y~VZdq1JC{~n_=eUGGtW>N?DB_G>qjiFB?(hgjF=WO!
+lH|g|Msz9-29`;Z#EI*i(Itp-{q_y(Ip|HU%D5@A!V9qvT3qdb@*Jt?yN=90r`?P29YH52NH5fhe%V9
+xa=NQ1y!kGYXg5)`NEVThU+^8d!3IPbx`-np_U*?9eha5Z2D#T5;m6;KD7bb{=O53{(fzGBvuuq6q7Q
+31mUAU(n|Dv6Wqi-NgQIsxwN_FVcaM+X4ZDNAU?Ju-+7B{2y*$4-K#Q=<M5KZD-@h&f#jwdhbmJ&|Km
+mrlr%<ILMmhaP`9sf6dK`wO#22MYt^i6Go%}><<*MAczT<S1Y+HEb%133FT5Xqssx-Mp9MI&Y0<<S&O
+)wYgulgM{fWM>bQK6c}DPO0&gFJL%*FX0PsIJjl&0usCpeB5jaaYku8?LS!rL3CjUe)oJ36wDj*j6pM
+ZpoxVK$Bh`SV?LHrcn@TF^zC|a+##03{qB?EYXF&!4eJWWjj^bq9(zLAqE8b7>3AnYa|W;LpUMm8xEm
+7tMo%Wj`IYRhXfLU5$>uS?169!J*eHTWTQ?wfys}TxY~(MBdJX#d$Guy_BN9|vT@{X)^`@0$#k(9kKq
+f~;D^Nq55ZYSGdk^URHjoq|NOoeuF%=9uJ?u-z57Ay#)N~=*+5~Ttqsu`Tx_>lS}!)oeGx2EX;pps@0
+UOF5|h1aKgCcHK7=XXbk$rHhuqF$*WF4WhpWTk4rT$RnE}5(+8p{_6G?p*7YS=j66aUWDd?W^TQvUss
+nwuhI)N{c_xp<t*-qXay!VNvVDP>>p5#gzbWD{VG8B4t(Giw(%(m;$el+M<q-5Cd*ZZ=?>W0WPFiOjt
+f}K+-zs8eoac&^Wy;MZAr-;Hmh_=$~$dh|^K;+9|nr$O{%EL0*Zu^&)Jl!gbCC~Iv)g0`4r-I=$3+Kh
+iDiSX#p806)%Qk@UdQXUNL3E4@t=pRLbnL`CYuV$m$9MwMg-atj8LnWk^>OgkGh>G}He}OdHj)&l$VQ
+6N4^x=5dOyW9GIONuX1#H;6Wd$tI6HvEP<t3ohO&Z%(C>u4C1Ds>;c9tD21iU#&!-7PN%TCLEa$5c5s
+h?5j+!=lV1%=DD$+U~eLnTg_fddzH5GQeNT<{3*`6vKGc3!S{GT1JXS-DL<lu9mIBKl;^YQOpIZE@+G
+dwCyHP7E}9p`CvFO(Yn@N&9tGgfohH{BEnx=^WUM3&~XLS}uK4CRq6SNPiQ=$jf__!Vv&UHGZ_B&t|O
+_rO6&YLJ!Y+@v-8<tM){%Ve7LQ!RI2HZ?K79G`FVnf|_&FUv4VrxVApHzk=?BeSubWE)S&dRo@xnNqh
+z0(R5^`vUm-i_HLkUTl`b*HE?KslS3NM8fwu+`t1qhAVdTFk&bw4C(5F;DC!}5qCrJUoeRWxdd$DUh~
+-|;i?X^RGd#WsNvwb8lR7-mB`f$X&I=NQ)_Jf4^T@31QY-O00;maO7>RU2K?5g1ONcj5C8xw0001RX>
+c!Jc4cm4Z*nhpWnyJ+V{c?>ZfA2ZcwcpMWpZC+WoBt^Wn?aJd8L<ad)qV=hQH@mh?J6qr6Eq&HVzBW^
+#uxJlyxv*FF}@$8iV5m*`X~j`|T+9QS_u;KkOo3?sF_lI`^^MtKJf7uG9Q-B$lPw88({DW}_k8?}`%2
+>#?GDJy{lHCz?!}ldi_!-v6r?ILt*lTVyn&yp&}+&&Aw`a!TTQXSLW4FDCphy?WY6%@;Q|y_}XKapXf
+W=tl#Q+=z>G<`%k;i!`tA&Qe8rK_l__;<zgcBJt$x=;Z0ei7<03G?g;V3b%CSW$b(=CKIzPmzE}zRef
+_?ie;X<5@?d8C0UsjjRp^_t}2%{wzjrhF)k5@=V$JM%4AX0SK9SWy(;O9Y6<67dr`Zf%ydPXFP3Fjkh
+ODLj9W!%Q&qOy?Sg-nTunLe*i%z!XL2#&H8y5<*BzUbGRdeDwsdp<_m;fItu3poxFxsXELXOE!r4hxt
+M&c3JHlJv*Bf^lWHvr^{ipZr%W9e4J<WO9fBmjvkLkW*c?61mS6APs*v*b^6nm?!SnNe<NzPu_)tPKp
+hpX!s#v$H);ilZ0`i!K$XKFpPIdyf!*Dt)7&Gj;))oFK&uBJ}X+|0#T;AuZ|m)g}Dxt!6swfSPVy46t
+qsK)iX(&^P{mz%pWRHyY&8XibJ!;bGBs5`gTD{S1#kF&nDsO)WJKgL$z@Kx2<F*do|=x~RQ`GJY&s|V
+(;iSwIs>i#6{j$FL@lcQWg!pi)T+Jn9Q&PXh5nwRa?YJ+Xt65B#e-MJH~akoAa(O@XZog$Y!5dG`ZgM
+Po$X>6Vg*Y>*2tykCmerp{@AsmEoH-ryExEI3x5FUhZ=)=+nc^FJWsC;O{H433whf%0B3YA8o(kN6Kg
+-WAPX%s4rLZ#6#gmDOE2t&1z3ZV{Rs5kQU3g!pQCUcAVA#<DgQO#znS?6uO-eG>se8B87cbGlqCrsZg
+-zncF-y`23-yPo?-xuE$-;ojXQ|2S)nE4s=bLJP!L*`@V5%ZXN!aQYu$^43W#{8Q34f6@}Tjo>dcg%C
+<_snO^3+8j?56mB#FPJ|ue`fx|eCZ$cD-K>W-!Lc4Uzz?K`9tJSkUu{D?D&Io$(%A%=5Ng3nHh7&^l#
+UkxnTam^siUJ^snWT`6u&=dCk0G{>A*8`4977=G*l<aIk)7m*!yD$0WjJfXOZ<4>8%pWFM0QOoo`mm`
+F?#OcW*>6T$?2V)Tj8Cq|zbePZ;9(I-Zq7=2>&iP0xUpBQ~&^oh|YMxPjcB>G77k?14QN1~5JABjE^e
+I)uw^pWTz(MO_>L?4Mh5`7Z%Nzf-jp9Fmp^hwYsL7xPD67)&XCqbVCeG>FZ&?iBk1br0xDD+Y2qtHj8
+k3t`XJ_>yl`Y7~K=%dg_p^rizg+2;>H2P@t(deVmN28BMAB{d5eKh)L^wH>}(MO|?Mjwqn8hr?T2z>~
+B2z>~B2z>~B2z>~B2z>~B2z>~B2z>~B2z?Ct81ymdW6;N-k3k=UJ_daZ`WW;v=wr~wppQWxgFeRjbn1
+VvPxu2wRR8xjHoxV<*N6YIN|tG++qb_>{{v7<0Rj{N6aWAK2ml*O_EvJ33*7hs003nH000jF0000000
+000006du00000aA|NaUtei%X>?y-E^v8JO928D02BZK00;mZO7>Q7_pjHy0RRA20{{RI00000000000
+002Cfh7R|0B~t=FJE76VQFq(UoLQYP)h*<6aW+e000O88%p+8eg`F$&;kGeqy+!~6#xJL0000000000
+wt)@<003}la4%n9aA|NYa&>NQWpZC%E^v8JO928D02BZK00;maO7>RG$G|nf0000U0RR9D000000000
+00002Cfe{7(0B~t=FK~G-ba`-PWKc^10u%rg0000802@m7R+hDJp-}+<06hW#02u%P00000000000Je
+eq1^@tXX>c!JX>N37a&BR4FJE72ZfSI1UoLQYP)h*<6aW+e000O88%p+83?7JMTMPgI11JCh8UO$Q00
+00000000wt<5P003}la4%nJZggdGZeeUMVs&Y3WM5@&b}n#vP)h*<6aW+e000O88%p+8(ZR!S5DWkSy
+(j<x761SM0000000000wt*HE003}la4%nJZggdGZeeUMV_{=xWiD`eP)h*<6aW+e000O88%p+8N-^Lq
+fe-)y4>kY*9smFU0000000000wt-q9003}la4%nJZggdGZeeUMV{dL|X=inEVRUJ4ZZ2?nP)h*<6aW+
+e000O88%p+8$(OSQyc+-jxm*AM8vp<R0000000000wt*Ki003}la4%nJZggdGZeeUMWq4y{aCB*JZgV
+bhc~DCM0u%rg0000802@m7Rwn?Xr|19x08{}002KfL00000000000Jeb)P5=OKX>c!JX>N37a&BR4FK
+uCIZZ2?nP)h*<6aW+e000O88%p+8X^Lvwun7PF`5OQL8UO$Q0000000000wt**4003}la4%nJZggdGZ
+eeUMaCvZYZ)#;@bS`jtP)h*<6aW+e000O88%p+8c;#0fxe5RP=N|w7Bme*a0000000000wt){>003}l
+a4%nJZggdGZeeUMb7gF1UvG7EWMOn=WM5-wWn*hDaCuNm0Rj{N6aWAK2ml*O_EzZ%`(R`Y002TR0015
+U0000000000006du3S<BPaA|NaUukZ1WpZv|Y%h0cWo2w%Vs&Y3WMy(LaCuNm0Rj{N6aWAK2ml*O_Ey
+e!>NIEo004vl0012T0000000000006dus&D`RaA|NaUukZ1WpZv|Y%gPMX)j-2X>MtBUtcb8c~DCM0u
+%rg0000802@m7RzQwlr3MH902CSk03!eZ00000000000JecmaR2~tX>c!JX>N37a&BR4FJo+JFJX0bZ
+)0z5aBO9CX>V>WaCuNm0Rj{N6aWAK2ml*O_Evldu6ol7000&u001EX0000000000006dulz9LEaA|Na
+UukZ1WpZv|Y%gPMX)j`7b7fy+Z*6U1Ze%WSc~DCM0u%rg0000802@m7R!w)w)H5Ie08VuP03QGV0000
+0000000Jedqga80=X>c!JX>N37a&BR4FJo+JFJo<FZ*X*JZ*FrgaCuNm0Rj{N6aWAK2ml*O_EsWCO)V
+<{000I9001Na0000000000006du7Nr0HaA|NaUukZ1WpZv|Y%gPMX)j}MZEaz0WM5-%ZggdMbS`jtP)
+h*<6aW+e000O88%p+8W^Syw5(NMN01E&B82|tP0000000000wt<7D003}la4%nJZggdGZeeUMV{B<JZ
+DDC{E^v8JO928D02BZK00;mZO7>PjxE^|C1^@u^5C8xm00000000000002Cfy}D_0B~t=FJEbHbY*gG
+VQepBY-ulTVQFq(aA9(DWpXZXc~DCM0u%rg0000802@m7R+NCe|H}*j06{7M02=@R00000000000Jec
+|vH$>ZX>c!JX>N37a&BR4FJo+JFK}UUb7gWaaCuNm0Rj{N6aWAK2ml*O_Errx8c*#4006KD001HY000
+0000000006dubH4xpaA|NaUukZ1WpZv|Y%gPMX)kbcZ)b94b8}x}VRCaWaCuNm0Rj{N6aWAK2ml*O_E
+sNWs53qk000O`001BW0000000000006dupuzwEaA|NaUukZ1WpZv|Y%gPMX)khRabII^ZEaz0WG--dP
+)h*<6aW+e000O88%p+8smxi)o(2E_{u2NI9RL6T0000000000wt*bi003}la4%nJZggdGZeeUMV{B<J
+b8u;HZe?<FE^v8JO928D02BZK00;mZO7>R$dH_pU0001V0000X00000000000002Cf%V-00B~t=FJEb
+HbY*gGVQepBY-ulZbYXOLb6;a`WMy+MaCuNm0Rj{N6aWAK2ml*O_Ezha)iII;001fv001HY00000000
+00006dujNSkMaA|NaUukZ1WpZv|Y%gPPZEaz0WOFZHUukY>bYEXCaCuNm0Rj{N6aWAK2ml*O_Ewn`ka
+dL!005mG0018V0000000000006duUgH1&aA|NaUukZ1WpZv|Y%gPPZEaz0WOFZLVPj}zE^v8JO928D0
+2BZK00;mZO7>QL=HuQ?0ssK^1^@sb00000000000002CfgtPv0B~t=FJEbHbY*gGVQepBZ*6U1Ze(*W
+V`yb#Yc6nkP)h*<6aW+e000O88%p+8q@aj{<pcl#k`Dj?Bme*a0000000000wt=ed003}la4%nJZggd
+GZeeUMV{dJ3VQyq|FJo_QaBO9CX>V>WaCuNm0Rj{N6aWAK2ml*O_Eus~!Z{WT0037e001Wd00000000
+00006du(enTRaA|NaUukZ1WpZv|Y%gPPZEaz0WOFZLZ*FF3XLWL6bZKvHE^v8JO928D02BZK00;mZO7
+>QQO%33i2mk=T82|tu00000000000002Cfh_+30B~t=FJEbHbY*gGVQepBZ*6U1Ze(*WWMyJ?XD)DgP
+)h*<6aW+e000O88%p+8>IGKA`UL<0*AxH%A^-pY0000000000wt)l)0RV7ma4%nJZggdGZeeUMV{dJ3
+VQyq|FJy0bZftL1WG--dP)h*<6aW+e000O88%p+8pAhN|5(EGMWDEcRAOHXW0000000000wt+ql0RV7
+ma4%nJZggdGZeeUMV{dJ3VQyq|FJ^LOWqM^UaCuNm0Rj{N6aWAK2ml*O_Ex{h`{3gO005^30015U000
+0000000006dujuHU?aA|NaUukZ1WpZv|Y%gPPZEaz0WOFZQVRL9MaCuNm0Rj{N6aWAK2ml*O_Ew3*ls
+xJI003+R0015U0000000000006dutrY<PaA|NaUukZ1WpZv|Y%gPPZEaz0WOFZQWo&RRaCuNm0Rj{N6
+aWAK2ml*O_EtGg<rLlp006lX0018V0000000000006du(-#2%aA|NaUukZ1WpZv|Y%gPPZEaz0WOFZR
+Ze(S6E^v8JO928D02BZK00;mZO7>RfItHdr1ONbZ3;+Nj00000000000002Cf$kjv0B~t=FJEbHbY*g
+GVQepBZ*6U1Ze(*WX>N0HWn*+MaCuNm0Rj{N6aWAK2ml*O_EyV2Ht<^<000JY001EX0000000000006
+dudm;e<aA|NaUukZ1WpZv|Y%gPPZEaz0WOFZRZgX^DY-}!Yc~DCM0u%rg0000802@m7RxUZKBw!2x0I
+4tl03HAU00000000000Jeb@KLG%6X>c!JX>N37a&BR4FJo_QZDDR?b1!UZb963nc~DCM0u%rg000080
+2@m7R#&d`FJcD(06`W203ZMW00000000000Jed#O923IX>c!JX>N37a&BR4FJo_QZDDR?b1!pcVRB<=
+E^v8JO928D02BZK00;mZO7>P&AVkH%2LJ#Q82|tt00000000000002Cfl*Td0B~t=FJEbHbY*gGVQep
+BZ*6U1Ze(*Wb7*gOE^v8JO928D02BZK00;mZO7>QZp>!kW1ONao4*&oo00000000000002CflgZi0B~
+t=FJEbHbY*gGVQepBZ*6U1Ze(*Wb#7^Hb97;BY%XwlP)h*<6aW+e000O88%p+8)jKDVP6q%0Oc?+G9{
+>OV0000000000wt;nE0RV7ma4%nJZggdGZeeUMV{dJ3VQyq|FL!8VWo#~Rc~DCM0u%rg0000802@m7R
+?~G2E;|7L09pe804D$d00000000000JebuXaN9lX>c!JX>N37a&BR4FJx(RbaH88b#!TOZgVeRUukY>
+bYEXCaCuNm0Rj{N6aWAK2ml*O_Ewaha2N*y006}V001KZ0000000000006dufN22$aA|NaUukZ1WpZv
+|Y%gSKb98cPVs&(BZ*FrhVqtS-E^v8JO928D02BZK00;mZO7>P4m-%-~0RRBm0ssIg0000000000000
+2CfyiqC0B~t=FJEbHbY*gGVQepCX>)XPX<~JBX>V?GFKKRbbYX04Wn?aJc~DCM0u%rg0000802@m7Rz
+Vi|@ZSai0A3jY03-ka00000000000JecyZ2<sqX>c!JX>N37a&BR4FJx(RbaH88b#!TOZgVelWNCABE
+^v8JO928D02BZK00;mZO7>R5>)-<B0RRAu1ONae00000000000002CfqHZS0B~t=FJEbHbY*gGVQepC
+X>)XPX<~JBX>V?GFL!8VWo#~Rc~DCM0u%rg0000802@m7Rzp8a&L98)03HAU03QGV00000000000Jed
+mb^!ozX>c!JX>N37a&BR4FKKRMWq2=NUukY>bYEXCaCuNm0Rj{N6aWAK2ml*O_Escr*$K%L004ME001
+BW0000000000006du|8@ZYaA|NaUukZ1WpZv|Y%ghUWMz0SV{dG1Wn*-2axQRrP)h*<6aW+e000O88%
+p+8Z2uE)ks|;A@sj`mB>(^b0000000000wt)tV0RV7ma4%nJZggdGZeeUMX>Md?crS2aV{2h&WnX4#Z
+e(S0E^v8JO928D02BZK00;mZO7>QlMPlUc1pok?82|tt00000000000002Cf!eMC0B~t=FJEbHbY*gG
+VQepHZe(S6FLQ5oa${w4E^v8JO928D02BZK00;mZO7>QQB1p0>5&!@NJOBVA00000000000002CfdsV
+y0B~t=FJEbHbY*gGVQepKZ)0I}X>V?GFJE72ZfSI1UoLQYP)h*<6aW+e000O88%p+8b)*io5eWbQ)E5
+8%B>(^b0000000000wt;iU0RV7ma4%nJZggdGZeeUMY;R*>bZKvHb1z?HX>)XSbZKmJE^v8JO928D02
+BZK00;mZO7>Pjqo%9S2><{99smF(00000000000002CfydAR0B~t=FJEbHbY*gGVQepKZ)0I}X>V?GF
+JE(cb7OCAW@%?GaCuNm0Rj{N6aWAK2ml*O_ExE$MN)wT008_60018V0000000000006du+S&mCaA|Na
+UukZ1WpZv|Y%gqYV_|e@Z*FrhVqtS-E^v8JO928D02BZK00;mZO7>QKBT?aD1polJ5C8xo000000000
+00002CftcR`0B~t=FJEbHbY*gGVQepLWprU=VRT_HUtei%X>?y-E^v8JO928D02BZK00;mZO7>PkZ6D
+*(0{{Rc3IG5f00000000000002CfjQ*?0B~t=FJEbHbY*gGVQepLWprU=VRT_HUutu2ZZ2?nP)h*<6a
+W+e000O88%p+8;9veW`xyWLy<z|W9smFU0000000000wt-0L0RV7ma4%nJZggdGZeeUMZDn*}WMOn+F
+JfVHWiD`eP)h*<6aW+e000O88%p+8^(!W{2nzrJEhYc}CjbBd0000000000wt;^G0swGna4%nJZggdG
+ZeeUMZDn*}WMOn+FK}yTUvg!0Z*_8GWpgfYc~DCM0u%rg0000802@m7R)8{dL{0zz0BZmM04x9i0000
+0000000Jee54gvshX>c!JX>N37a&BR4FKuOXVPs)+VJ~TIaBp&SY-wUIUtei%X>?y-E^v8JO928D02B
+ZK00;mZO7>QPj@R{B0{{S82LJ#o00000000000002Cfn*N?0B~t=FJEbHbY*gGVQepLWprU=VRT_HX>
+D+Ca&&BIVlQ7~Z*6d4bS`jtP)h*<6aW+e000O88%p+8BE&_;v<UzJ^&bELDgXcg0000000000wt)r{0
+swGna4%nJZggdGZeeUMZDn*}WMOn+FKKOXZ*p{OX<{#5WNCABb1rasP)h*<6aW+e000O88%p+8Y)E<&
+7YP6W3mpIeDF6Tf0000000000wt)g20swGna4%nJZggdGZeeUMZDn*}WMOn+FKKOXZ*p{OX<{#5Wo~w
+JE^v8JO928D02BZK00;mZO7>QJ$teCi0000#0000W00000000000002CfnX*A0B~t=FJEbHbY*gGVQe
+pLZ)9a`b1z?CX>MtBUtcb8c~DCM0u%rg0000802@m7RuwRyPk8|V0Nw)t03iSX00000000000JeeICI
+SF(X>c!JX>N37a&BR4FKusRWo&aVV_|M&X=Gt^WiD`eP)h*<6aW+e000O88%p+8JE<F%s0RQ56B_^kA
+^-pY0000000000wt<l-0swGna4%nJZggdGZeeUMZEs{{Y;!MUX>w&_bYFFHY%XwlP)h*<6aW+e000O8
+8%p+8V(5)yXafKM*a-jtCIA2c0000000000wt;yt0swGna4%nJZggdGZeeUMZEs{{Y;!MWZ*py6bYEj
+{Zgg^QY%XwlP)h*<6aW+e000O88%p+8-<PS)!T|sP1_S^A9RL6T0000000000wt*!y0swGna4%nJZgg
+dGZeeUMZEs{{Y;!MZZe(S6E^v8JO928D02BZK00;mZO7>P4Zd=I!1ONar3IG5r00000000000002Cfg
+&~n0B~t=FJEbHbY*gGVQepLZ)9a`b1!Lbb97;BY+-b1Z*E_5WpHnDbS`jtP)h*<6aW+e000O88%p+8$
+K8-vx)=ZeQ&9i_8~^|S0000000000wt;Ip0swGna4%nJZggdGZeeUMZEs{{Y;!McX>MySaCuNm0Rj{N
+6aWAK2ml*O_EsAl^6G2>0080w0015U0000000000006duUsD1AaA|NaUukZ1WpZv|Y%gtZWMyn~FLPs
+PWo>0HaCuNm0Rj{N6aWAK2ml*O_Ez}ke8Ff2001Kr001Na0000000000006du2UP+9aA|NaUukZ1WpZ
+v|Y%gtZWMyn~FLPyKa${&;b7OCCWiD`eP)h*<6aW+e000O88%p+8ih`)-&jJ7da|ZwbCjbBd0000000
+000wt=x*0swGna4%nJZggdGZeeUMZEs{{Y;!MjWo%_*bZKvHUvP3|W^*oZc~DCM0u%rg0000802@m7R
+#62<WxoUf01^)X03`qb00000000000Jed}UIGAcX>c!JX>N37a&BR4FKusRWo&aVbYXI5WprO~d30!R
+ZZ2?nP)h*<6aW+e000O88%p+8X#?@S0R;d65DowU9RL6T0000000000wt>fE0swGna4%nJZggdGZeeU
+MZEs{{Y;!MnXk}$=E^v8JO928D02BZK00;mZO7>O`AAw3T0000o0000X00000000000002Cfdgp*0B~
+t=FJEbHbY*gGVQepMWpsCMa%(SNUukY>bYEXCaCuNm0Rj{N6aWAK2ml*O_Etk!O8<-%002Eu0012T00
+00000000006dubZG(raA|NaUukZ1WpZv|Y%gwQba!uZYcFASbZ9Pcc~DCM0u%rg0000802@m7R!m7DT
+}}f40AUCK03HAU00000000000JecUe*yq-X>c!JX>N37a&BR4FK%UYcW-iQFJob2Xk{*Nc~DCM0u%rg
+0000802@m7R-!8&==}x&0MHiz03iSX00000000000Jed}f&u_=X>c!JX>N37a&BR4FK%UYcW-iQFJy0
+bZftL1WG--dP)h*<6aW+e000O88%p+8^{UMQ*9ias)*S!<BLDyZ0000000000wt)eP0swGna4%nJZgg
+dGZeeUMZe?_LZ*prdY+-tNUw3F_Wo#~Rc~DCM0u%rg0000802@m7R-dh8<cb#n0Ix^@03ZMW0000000
+0000Jeb{lmY;7X>c!JX>N37a&BR4FK%UYcW-iQFLPycb7^mGE^v8JO928D02BZK00;mZO7>Q?wHpV)1
+pol)4*&oj00000000000002Cf#ItH0B~t=FJEbHbY*gGVQepMWpsCMa%(SjbZKmJE^v8JO928D02BZK
+00;mZO7>PQuX|s*0ssL21^@sb00000000000002Cf!?tK0B~t=FJEbHbY*gGVQepMWpsCMa%(SmZESL
+IV=i!cP)h*<6aW+e000O88%p+8000000ssI200000Bme*a0000000000wt>~O0swGna4%nJZggdGZee
+UMZ*XODVRUJ4ZgVeRUukY>bYEXCaCuNm0Rj{N6aWAK2ml*O_EuPwuiBOe005R6001EX000000000000
+6du8MOicaA|NaUukZ1WpZv|Y%gzcWpZJ3X>V?GFJowBV{0yOc~DCM0u%rg0000802@m7R^~jS+%*aS0
+9Ymf03rYY00000000000JeedyaE7lX>c!JX>N37a&BR4FK=*Va$$67Z*FrhW^!d^dSxzfc~DCM0u%rg
+0000802@m7R*Rxwyv!W{0K{+r03!eZ00000000000Jec+#{vLwX>c!JX>N37a&BR4FK=*Va$$67Z*Fr
+haB^jEVRB_IaCuNm0Rj{N6aWAK2ml*O_ErD@0006200000001fg0000000000006duaODC3aA|NaUuk
+Z1WpZv|Y%gzcWpZJ3X>V?GFJg6RY-BHAUukY>bYEXCaCuNm0Rj{N6aWAK2ml*O_Ex2i#`J*&001Qr00
+1ul0000000000006duy5#}@aA|NaUukZ1WpZv|Y%gzcWpZJ3X>V?GFJg6RY-BHDb!lv5UvzR|V{2t{E
+^v8JO928D02BZK00;mZO7>QM@PA8Q0ssJx1pojl00000000000002Cfr#q@0B~t=FJEbHbY*gGVQepN
+aAk5~bZKvHb1!0bX>4RKZDn*}WMOn+E^v8JO928D02BZK00;mZO7>QOCoIZr0ssKQ1poju000000000
+00002CfiCU>0B~t=FJEbHbY*gGVQepNaAk5~bZKvHb1!0bX>4RKZDn*}WMOn+Uu9%zbYWs_WiD`eP)h
+*<6aW+e000O88%p+8GPDpbG6MhrmIwd<F#rGn0000000000wt?&L0swGna4%nJZggdGZeeUMZ*XODVR
+UJ4ZgVeUb!lv5FKuOXVPs)+VP9-zXJKP`E^v8JO928D02BZK00;mZO7>O|{>5eL0RR9q1ONah000000
+00000002Cfo${w0B~t=FJEbHbY*gGVQepNaAk5~bZKvHb1!0bX>4RKcW7m0Y%XwlP)h*<6aW+e000O8
+8%p+8*Qcn*J^}y$i3I=vFaQ7m0000000000wt<`W0swGna4%nJZggdGZeeUMZ*XODVRUJ4ZgVeUb!lv
+5FL!8VWo%z%WNCC^Vr*qDaCuNm0Rj{N6aWAK2ml*O_EtwsgCGF}008(4001rk0000000000006duC;0
+*ZaA|NaUukZ1WpZv|Y%gzcWpZJ3X>V?GFJg6RY-BHYXk}$=Uu<P(VPknNaCuNm0Rj{N6aWAK2ml*O_E
+zED6nixQ001)p001li0000000000006dubo~MVaA|NaUukZ1WpZv|Y%gzcWpZJ3X>V?GFKKRbbYX04F
+JE72ZfSI1UoLQYP)h*<6aW+e000O88%p+8UbgC>3jzQD0tEm7GXMYp0000000000wt@5g0swGna4%nJ
+ZggdGZeeUMZ*XODVRUJ4ZgVebZgX^DY-}%OWNCC^Vr*q!Y-ML*V|gxcc~DCM0u%rg0000802@m7Rt==
+d!N4E@08?uK04V?f00000000000Jeco00RJUX>c!JX>N37a&BR4FK=*Va$$67Z*FrhX>N0LVQg$KcW7
+m0Y%XwlP)h*<6aW+e000O88%p+8y}5(Hivs`vvI+nI9RL6T0000000000wt-e50|0Poa4%nJZggdGZe
+eUMa%FKZUtei%X>?y-E^v8JO928D02BZK00;mZO7>R1z_J+)5&!_=KmY(C00000000000002CfgB|R0
+B~t=FJEbHbY*gGVQepQWpOWKZ*FsRa&=>LZ*p@kaCuNm0Rj{N6aWAK2ml*O_Ev7YiIQ9t007WM0012T
+0000000000006duXg31@aA|NaUukZ1WpZv|Y%g+UaW8UZabIR>Y-KKRc~DCM0u%rg0000802@m7Rx!*
++x`!eF06c*J03ZMW00000000000JeeuO9KFKX>c!JX>N37a&BR4FLGsZFLGsZUukZ0bYX04E^v8JO92
+8D02BZK00;mZO7>PKomn*b1ONbF5&!@k00000000000002Cfy8bD0B~t=FJEbHbY*gGVQepQWpOWZWp
+Q6~WpplZc~DCM0u%rg0000802@m7Rv1kPWzrh}0A^qS03rYY00000000000Jeema{~ZyX>c!JX>N37a
+&BR4FLGsZFLGsZUv+M2ZgX^DY-}!Yc~DCM0u%rg0000802@m7RsaA100IC20000003-ka0000000000
+0Jeb%kOKg4X>c!JX>N37a&BR4FLGsbZ)|mRX>V>XUtei%X>?y-E^v8JO928D02BZK00;mZO7>Re8_TK
+x0000-0ssIY00000000000002CflZJD0B~t=FJEbHbY*gGVQepQWpi(Ab#!TOZZBeCb7d}Yc~DCM0u%
+rg0000802@m7RsaA100IC20000004o3h00000000000JedOkplp5X>c!JX>N37a&BR4FLGsbZ)|mRX>
+V>XY-ML*V|g!MUukY>bYEXCaCuNm0Rj{N6aWAK2ml*O_ErYZCo(b`002N<001ih0000000000006du)
+sX`LaA|NaUukZ1WpZv|Y%g+Ub8l>QbZKvHFKlIJVPknOa%FRGY<6XGE^v8JO928D02BZK00;mZO7>O&
+00002000000000l00000000000002Cfl#ai0B~t=FJEbHbY*gGVQepQWpi(Ab#!TOZZC3Wb8l>RWo&6
+;FJE72ZfSI1UoLQYP)h*<6aW+e000O88%p+8!vG@RNCf}@WE21ZD*ylh0000000000wt=6l0|0Poa4%
+nJZggdGZeeUMa%FRGY;|;LZ*DJgWpi(Ac4cg7VlQH0b7d}Yc~DCM0u%rg0000802@m7R(s_xK5G#G02
+xXE05Jdn00000000000JecJvI78cX>c!JX>N37a&BR4FLGsbZ)|mRX>V>Xa%FRGY<6XAX<{#9VQyq;W
+MOn=b1rasP)h*<6aW+e000O88%p+8Dt&gR=o<h4#cTioE&u=k0000000000wt?!y0|0Poa4%nJZggdG
+ZeeUMa%FRGY;|;LZ*DJgWpi(Ac4cg7VlQT4V{~tFc`k5yP)h*<6aW+e000O88%p+8Db-rPyaoUONfrP
+AHvj+t0000000000wt*ht0|0Poa4%nJZggdGZeeUMa%FRGY;|;LZ*DJgWpi(Ac4cg7VlQTIb#7!|V_|
+M&X=Gt^WpgfYc~DCM0u%rg0000802@m7R<*OmdWZ}F0AMBn051Rl00000000000JecI=K}z6X>c!JX>
+N37a&BR4FLGsbZ)|mRX>V>Xa%FRGY<6XAX<{#Ma&LBNWMy(LaCuNm0Rj{N6aWAK2ml*O_ExMKo!sXG0
+00~e001ul0000000000006du1oQ&{aA|NaUukZ1WpZv|Y%g+Ub8l>QbZKvHFLGsbZ)|pDY-wUIa%FID
+a&%>KE^v8JO928D02BZK00;mZO7>QQtT5f|1ONa|6#xJ;00000000000002CfjIaB0B~t=FJEbHbY*g
+GVQepQWpi(Ab#!TOZZC3Wb8l>RWo&6;FLGsZb!l>CZDnqBb1rasP)h*<6aW+e000O88%p+8((7NZhz<
+Y%dMy9|F8}}l0000000000wt;p10|0Poa4%nJZggdGZeeUMa%FRGY;|;LZ*DJgWpi(Ac4cg7VlQ%Kb8
+l>RWpXZXc~DCM0u%rg0000802@m7RsaA100IC20000003QGV00000000000Jecj3<LmhX>c!JX>N37a
+&BR4FLiWjY;!MPUukY>bYEXCaCuNm0Rj{N6aWAK2ml*O_Ez^Ml55xn000*a001KZ0000000000006du
+i3|h)aA|NaUukZ1WpZv|Y%g_mX>4;ZUut1;VPkJ!bY*ySE^v8JO928D02BZK00;mZO7>PtcsW1T0RRB
+^0{{RU00000000000002Cfua%w0B~t=FJEbHbY*gGVQepTbZKmJFJEkLXD)DgP)h*<6aW+e000O88%p
++819C#bmjVC)fd&8o9smFU0000000000wt=w}1ORYpa4%nJZggdGZeeUMb#!TLb1z|VaAaw6b1rasP)
+h*<6aW+e000O88%p+8<YSF%<pTf!Tn7LE9RL6T0000000000wt<8f1ORYpa4%nJZggdGZeeUMb#!TLb
+1!3WZE#_9E^v8JO928D02BZK00;mZO7>Q^w285E1^@s76#xJ!00000000000002CfutJ*0B~t=FJEbH
+bY*gGVQepTbZKmJFJo_QaA9<5Vrgt?ba`KNVP|tLaCuNm0Rj{N6aWAK2ml*O_Eu~YJ+7Dl008m;0018
+V0000000000006duULphlaA|NaUukZ1WpZv|Y%g_mX>4;ZWMOn=bZKp6E^v8JO928D02BZK00;mZO7>
+RJw#AN21pojm4gdfm00000000000002Cfioin0B~t=FJEbHbY*gGVQepTbZKmJFJxtKa%E#-bZKvHE^
+v8JO928D02BZK00;mZO7>PJj`dyb0{{Sq3;+Nr00000000000002CfxjpO0B~t=FJEbHbY*gGVQepTb
+ZKmJFJx(QWn*+-b#iQ9Xk~10WpZ;aaCuNm0Rj{N6aWAK2ml*O_EszUN|z1;002e^0018V0000000000
+006du^DG1aaA|NaUukZ1WpZv|Y%g_mX>4;ZWoKt!Y-w(5E^v8JO928D02BZK00;mZO7>R98_*XH0ssJ
+!1ONaZ00000000000002Cfj%$<0B~t=FJEbHbY*gGVQepTbZKmJFJ*3HZ)9n1XD)DgP)h*<6aW+e000
+O88%p+8JY;3*(F6bh_zM64A^-pY0000000000wt<N<1ORYpa4%nJZggdGZeeUMb#!TLb1!9XbaHucZ)
+t9Hb1rasP)h*<6aW+e000O88%p+8l?9u(>jwY;0u%rMApigX0000000000wt<>A1ORYpa4%nJZggdGZ
+eeUMb#!TLb1!CTY-MwKb97~GE^v8JO928D02BZK00;mZO7>Qx)lV&00RRBZ0ssIY00000000000002C
+fy6%q0B~t=FJEbHbY*gGVQepTbZKmJFJ@_MWpsIPWpgfYc~DCM0u%rg0000802@m7Ruo!&&;<nm04WR
+r02}}S00000000000JeczK?DGBX>c!JX>N37a&BR4FLiWjY;!MXY-wU+E^v8JO928D02BZK00;mZO7>
+Q2YVO4#2LJ&66951m00000000000002Cftf}G0B~t=FJEbHbY*gGVQepTbZKmJFKA(NXk~LQaCuNm0R
+j{N6aWAK2ml*O_Ey(_5u>63000{U001oj0000000000006du^i2c+aA|NaUukZ1WpZv|Y%g_mX>4;ZX
+>Mv|V{~70Wn*=6Wpr|3ZgX&Na&#_mc~DCM0u%rg0000802@m7R{3)aly?mP0B|h;03HAU0000000000
+0JeeQPXqvPX>c!JX>N37a&BR4FLiWjY;!McZ)ay|Zf7oVc~DCM0u%rg0000802@m7R<*HoXg3=G07q8
+<02=@R00000000000JedYT?7DdX>c!JX>N37a&BR4FLiWjY;!MdX>(&PaCuNm0Rj{N6aWAK2ml*O_Et
+Nz46t_r005~30012T0000000000006du1bGAiaA|NaUukZ1WpZv|Y%g_mX>4;ZZEs{{Y;!Jfc~DCM0u
+%rg0000802@m7R>4fIqtF8Y06Yi)03ZMW00000000000Jed)dISJ)X>c!JX>N37a&BR4FLiWjY;!MgV
+Pk7yXK8L{E^v8JO928D02BZK00;mZO7>P<`C(i91pok35dZ)u00000000000002Cfy90U0B~t=FJEbH
+bY*gGVQepTbZKmJFLPydb#QcVZ)|g4Vs&Y3WG--dP)h*<6aW+e000O88%p+8@r{%i#|r=e@FM^KApig
+X0000000000wt)qO1ORYpa4%nJZggdGZeeUMb#!TLb1!psVsLVAV`X!5E^v8JO928D02BZK00;mZO7>
+R8Iuuml2><{V9smFz00000000000002CfeVoY0B~t=FJEbHbY*gGVQepTbZKmJFLY&Xa9?C;axQRrP)
+h*<6aW+e000O88%p+8JA<z_-U$Ezbs_)&AOHXW0000000000wt*>|1ORYpa4%nJZggdGZeeUMb#!TLb
+1!vnaA9L>X>MmOaCuNm0Rj{N6aWAK2ml*O_EvtOju$xt007?x000{R0000000000006duMWqA)aA|Na
+UukZ1WpZv|Y%g_mX>4;Zb#iQTE^v8JO928D02BZK00;mZO7>Pww&sZ+1pokm4FCWk00000000000002
+Cfw!mx0B~t=FJEbHbY*gGVQepTbZKmJFLr5ibai2DWo~vZaCuNm0Rj{N6aWAK2ml*O_Ezo^D5y&Y006
+}i000~S0000000000006du6|MvTaA|NaUukZ1WpZv|Y%g_mX>4;ZcW7m0Y%XwlP)h*<6aW+e000O88%
+p+8FRk9iF984mR00419RL6T0000000000wt<?o1ORYpa4%nJZggdGZeeUMc4KodUtei%X>?y-E^v8JO
+928D02BZK00;mZO7>R$3Jidy1ONcP4FCWe00000000000002CfdsY$0B~t=FJEbHbY*gGVQepUV{<QJ
+VR~U<axQRrP)h*<6aW+e000O88%p+8Q}91`vlRdU#6|!B7ytkO0000000000wt?ch1ORYpa4%nJZggd
+GZeeUMc4KodXK8dUaCuNm0Rj{N6aWAK2ml*O_EwY2jo<qP004Xx0015U0000000000006du%g_V>aA|
+NaUukZ1WpZv|Y%g|Wb1!XWa$|LJX<=+GaCuNm0Rj{N6aWAK2ml*O_EzjemM&xt007Y~0018V0000000
+000006du0@nlpaA|NaUukZ1WpZv|Y%g|Wb1!psVs>S6b7^mGE^v8JO928D02BZK00;mZO7>PpyV$aX7
+ytkpSpWbd00000000000002CfurRF0B~t=FJEbHbY*gGVQepUV{<QdWpZ<AZ*F66Zgg^QY%XwlP)h*<
+6aW+e000O88%p+8uPnR!UIqXFW)lDa7XSbN0000000000wt;B=1ORYpa4%nWWo~3|axY(BX>MtBUtcb
+8c~DCM0u%rg00008031s8R?_w4&jBF-0QH6d01^NI00000000000Jeeq1O)(aX>c!Jc4cm4Z*nhlX?Q
+Mhc~DCM0u%rg00008031s8R>6_5z`kby02;CZ03ZMW00000000000JecFCItX+X>c!Jc4cm4Z*nhmd2
+nfNXJ2J_bY*UHX>V?GE^v8JO928D02BZK00;maO7>PC6?fq+0RRBo0RR9N00000000000002Cfhdjz0
+B~t=FJE?LZe(wAFLq^aWN&gVba-@7O928D02BZK00;mZO7>O(bDXyj0RRBe0RR9b00000000000002C
+fr*a=0B~t=FJE?LZe(wAFJob2Xk}w>Zgg^QY%gD5X>MtBUtcb8c~DCM0u%rg0000802@m7R?<DWkVFC
+i0AmFJ03ZMW00000000000JeeKkOcs6X>c!Jc4cm4Z*nhVVPj}zV{dMBa&K%eUt?`#E^v8JO928D02B
+ZK00;mZO7>Qh=}f=>1pol46951s00000000000002CfnAdY0B~t=FJE?LZe(wAFJob2Xk}w>Zgg^QY%
+gJCVQ_S1axQRrP)h*<6aW+e000O88%p+85lF+qT>=0A{{;X5ApigX0000000000wt=0Q1pshqa4%nWW
+o~3|axY_HV`yb#Z*FvQZ)`7PVPj}zE^v8JO928D02BZK00;mZO7>Q!HL1E!0RR9B0{{Rb0000000000
+0002CfjOK70B~t=FJE?LZe(wAFJob2Xk}w>Zgg^QY%gPPZE#_9E^v8JO928D02BZK00;mZO7>P?7DzG
+Z5dZ)nKmY(H00000000000002CfykW&0B~t=FJE?LZe(wAFJob2Xk}w>Zgg^QY%gPPZgg^QY;0w6E^v
+8JO928D02BZK00;mZO7>O=fxlfz1^@tR4*&os00000000000002Cf%LBh0B~t=FJE?LZe(wAFJob2Xk
+}w>Zgg^QY%gYMY-M+HVQ_F|axQRrP)h*<6aW+e000O88%p+8N_1|4?F9e;IuHN=CIA2c0000000000w
+t<4S1pshqa4%nWWo~3|axY_HV`yb#Z*FvQZ)`7UWp#3Cb98BAb1rasP)h*<6aW+e000O88%p+89*Jjx
+7zqFX!5aVoB>(^b0000000000wt=&}1pshqa4%nWWo~3|axY_HV`yb#Z*FvQZ)`7fWpZg@Y-xIBE^v8
+JO928D02BZK00;mZO7>Qq5k_J%0RR970{{Rc00000000000002Cfeyw60B~t=FJE?LZe(wAFJob2Xk}
+w>Zgg^QY%h0mVQ_F|axQRrP)h*<6aW+e000O88%p+8jsAzepa1{>@&Et;D*ylh0000000000wt<1i1p
+shqa4%nWWo~3|axY_HV`yb#Z*FvQZ)`7PVPj}zb1z?CX>MtBUtcb8c~DCM0u%rg0000802@m7RyaU7m
+~96D0GAX104)Fj00000000000Jec@$OQm!X>c!Jc4cm4Z*nhVVPj}zV{dMBa&K%eV_{=xWpgiPX>4U*
+V_{=xWiD`eP)h*<6aW+e000O88%p+8Uefd&!2tjO2?PKDE&u=k0000000000wt*th1pshqa4%nWWo~3
+|axY_HV`yb#Z*FvQZ)`7PVPj}zb1!mbWNC9>V_{=xWiD`eP)h*<6aW+e000O88%p+8s1pqUQUCw|UH|
+|99{>OV0000000000wt+9w1pshqa4%nWWo~3|axY_La&&2CX)j-2X>MtBUtcb8c~DCM0u%rg0000802
+@m7Rxco};hq2h0RI3003QGV00000000000Jed?(ggr;X>c!Jc4cm4Z*nhVWpZ?BW@#^9Uu|J&ZeL$6a
+CuNm0Rj{N6aWAK2ml;P_EuW$l#3Tq0syE%1OOfY0000000000006dunbQRTaA|NaUv_0~WN&gWV`Xx5
+X=Z6JV_{=ua&#_mWo=MP0Rj{N6aWAK2ml;P_EyM7nV-r8006fT000{R0000000000006du>?H^QaA|N
+aUv_0~WN&gWV`Xx5X=Z6JV{dY0E^v8JO928D02BZK00;maO7>RUNtf2i1polO5&!@n0000000000000
+2Cf$u5^0B~t=FJE?LZe(wAFJow7a%5$6FJE72ZfSI1UoLQYP)h*<6aW+e000O897^_9e{)wH{W$;tDt
+Z6_9{>OV0000000000wt@992mo+ta4%nWWo~3|axY_OVRB?;bT49QXEkPWWpOTWc~DCM0u%rg000080
+31s8R(v6Y`a%N$0OJM#03iSX00000000000JecIYX|^vX>c!Jc4cm4Z*nhVXkl_>WppoMX=gQXa&KZ~
+axQRrP)h*<6aW+e000O897^_9EG^V_p$Py0Fed;2CjbBd0000000000wt=v22mo+ta4%nWWo~3|axY_
+OVRB?;bT4CQVRB??b98cPVs&(BZ*DGdc~DCM0u%rg00008031s8Ry5(hA;1Ix080-504V?f00000000
+000JedacnAP+X>c!Jc4cm4Z*nhVXkl_>WppoNXkl`5Wprn9Z*_2Ra&KZ~axQRrP)h*<6aW+e000O897
+^_95#q;SKnMT;EENC%Bme*a0000000000wt<~}2mo+ta4%nWWo~3|axY_OVRB?;bT4CQVRCb2bZ~NSV
+r6nJaCuNm0Rj{N6aWAK2ml;P_EtHwD}l)c005K@001cf0000000000006duABG43aA|NaUv_0~WN&gW
+V`yP=WMy<OV{c?>ZfA3JVRU6}VPj}%Ze=cTc~DCM0u%rg00008031s8R<SU;UlIWT03HGW04)Fj0000
+0000000JecIj0ga5X>c!Jc4cm4Z*nhVXkl_>WppoNZ)9n1XLEF6bY*Q}V`yn^Wn^h%bS`jtP)h*<6aW
++e000O897^_9g;B-=Zvy}TL<ax>A^-pY0000000000wt<X|2mo+ta4%nWWo~3|axY_OVRB?;bT4CYIW
+#$Na&KZ~axQRrP)h*<6aW+e000O897^_9A=kVX;{pHxlLi0)8~^|S0000000000wt+j52mo+ta4%nWW
+o~3|axY_OVRB?;bT4IYb!~GlaCuNm0Rj{N6aWAK2ml;P_Ey*v2=;CT005>B001BW0000000000006du
+Sd<6=aA|NaUv_0~WN&gWV`yP=WMy<OWpiV2a&KZ~axQRrP)h*<6aW+e000O897^_9we#2caRvYYkS_o
+L8~^|S0000000000wt)ni2mo+ta4%nWWo~3|axY_OVRB?;bT4IdV{>gTaCuNm0Rj{N6aWAK2ml;P_Es
+n1s)bwy003SO001HY0000000000006duub>D3aA|NaUv_0~WN&gWV`yP=WMy<OWp!g}aBy;OVr6nJaC
+uNm0Rj{N6aWAK2ml;P_Eu=iy2@=B0090p001BW0000000000006duOQr|_aA|NaUv_0~WN&gWV`yP=W
+My<OWp!g~a%OU6aV~IqP)h*<6aW+e000O897^_9oK{>vJ_7&%*#-arA^-pY0000000000wt@D(2mo+t
+a4%nWWo~3|axY_OVRB?;bT4IfV{3A7a&KZ~axQRrP)h*<6aW+e000O897^_96_4{_*Es+HF^~WNAOHX
+W0000000000wt;lQ2mo+ta4%nWWo~3|axY_OVRB?;bT4IfV{~_Ba%FKYaCuNm0Rj{N6aWAK2ml;P_Et
+=Q;D0{@007wr001HY0000000000006duiTnrvaA|NaUv_0~WN&gWV`yP=WMy<OWp!h8cW`oVVr6nJaC
+uNm0Rj{N6aWAK2ml;P_Es>7j3jX<0093`001EX0000000000006du2mlEHaA|NaUv_0~WN&gWV`yP=W
+My<OXJRrlF*0UyWpOTWc~DCM0u%rg00008031s8RwnGr9X<m90N(}x03!eZ00000000000Jed+CkX&>
+X>c!Jc4cm4Z*nhVXkl_>WppoRVlp!^GH`NlVr6nJaCuNm0Rj{N6aWAK2ml;P_Ew)4J((I4007B2001K
+Z0000000000006duH!BGMaA|NaUv_0~WN&gWV`yP=WMy<OXk}t@Wp{9LZ(?O~E^v8JO928D02BZK00;
+maO7>RkB-#KWFaQ9=WB>pj00000000000002Cfs#H60B~t=FJE?LZe(wAFJow7a%5$6FKTIXW^!e5E^
+v8JO928D02BZK00;maO7>PtR1xl<F#rGprT_pS00000000000002Cf$we!0B~t=FJE?LZe(wAFJow7a
+%5$6FKTaSVPa--WpOTWc~DCM0u%rg00008031s8R-o>6mp=ml0N4fq03rYY00000000000Jee5pa}qQ
+X>c!Jc4cm4Z*nhVXkl_>WppoUZ)jm+aB^>AWpXZXc~DCM0u%rg00008031s8R;%8m)9Dld0Iz8P0384
+T00000000000JeckqzM3UX>c!Jc4cm4Z*nhVXkl_>WppoUaAR(CcrI{xP)h*<6aW+e000O897^_9b4q
+F4UmXAda+m=CDF6Tf0000000000wt;WC2>@_ua4%nWWo~3|axY_OVRB?;bT4dSZf9b3Y-eF|X<=?{Z)
+9a`E^v8JO928D02BZK00;maO7>PsLtEjW7XSdXfB^s{00000000000002Cffd&Y0B~t=FJE?LZe(wAF
+Jow7a%5$6FKl6MXJ>L{WovD3WMynFaCuNm0Rj{N6aWAK2ml;P_EuatQl;7!005MK0RScd0000000000
+006du_wES*aA|NaUv_0~WN&gWV`yP=WMy<OY+-I^Xk}t@Wp{0FWMynFaCuNm0Rj{N6aWAK2ml;P_Etk
+<RhkDI008rg0RSlg0000000000006du6$T0baA|NaUv_0~WN&gWV`yP=WMy<OY+-I^XmxI9VRC6<Zf$
+R5Wo#~Rc~DCM0u%rg00008031s8R_91_uy`i`03-AP04D$d00000000000Jec+AqoI+X>c!Jc4cm4Z*
+nhVXkl_>WppoWVQyz~b#rrRVQy`2WMynFaCuNm0Rj{N6aWAK2ml;P_EuwXtW6#p004H80RSWb000000
+0000006duAV~@UaA|NaUv_0~WN&gWV`yP=WMy<OY+-I^bZB8|ZEs{{Y%XwlP)h*<6aW+e000O897^_9
+3{;~n*c$)<jC272CjbBd0000000000wt;|T3IK3va4%nWWo~3|axY_OVRB?;bT4dSZfA6La%*XGXl-v
+~Wo#~Rc~DCM0u%rg00008031s8R-iv52+Rfm00b2P03!eZ00000000000JedhfC>O`X>c!Jc4cm4Z*n
+hVXkl_>WppoWVRUJ3F>rEkVr6nJaCuNm0Rj{N6aWAK2ml;P_Eu*P$$JP0006xg001Qb000000000000
+6dus)q^yaA|NaUv_0~WN&gWV`yP=WMy<OZDC__Z*5_2aB^>AWpXZXc~DCM0u%rg00008031s8R++Y&k
+~#$d0D}$y044wc00000000000Jeekj|u>AX>c!Jc4cm4Z*nhVXkl_>WppoXVq<7wa&u*LaB^>AWpXZX
+c~DCM0u%rg00008031s8RzJEWEu8}Z08<D6044wc00000000000Jed1l?niGX>c!Jc4cm4Z*nhVXkl_
+>WppoXVq<e>a&L8TaB^>AWpXZXc~DCM0u%rg00008031s8Rw-8I@=*=|0JnAk0384T00000000000Je
+ctnF;`KX>c!Jc4cm4Z*nhVXkl_>WppoXVq<f2Z7y(mP)h*<6aW+e000O897^_97MzNm<p2Nxk^uk!Ap
+igX0000000000wt?WM3IK3va4%nWWo~3|axY_OVRB?;bT4vcb9HQVWNBk`E^v8JO928D02BZK00;maO
+7>P<?V|8e2mk;882|t#00000000000002Cfdr`v0B~t=FJE?LZe(wAFJow7a%5$6FLPpJXkl`5Wpr?I
+Z(?O~E^v8JO928D02BZK00;maO7>PFa+w;D1pojk5C8xs00000000000002Cftj%i0B~t=FJE?LZe(w
+AFJow7a%5$6FLPpJb7yjIb#QQUZ(?O~E^v8JO928D02BZK00;maO7>R!jHo_V1pol24*&om00000000
+000002Cfo``70B~t=FJE?LZe(wAFJow7a%5$6FLP>Xb8vERVr6nJaCuNm0Rj{N6aWAK2ml;P_Et(OZa
+LNu0000w001Ze0000000000006du1HB3WaA|NaUv_0~WN&gWV`yP=WMy<Ob#7^PWpZ<2Y-DA0Wn*-2a
+xQRrP)h*<6aW+e000O897^_90>&H&Q3wD4IUxW5Bme*a0000000000wt*kb3IK3va4%nWWo~3|axY_O
+VRB?;bT4&uW-&H1GH`NlVr6nJaCuNm0Rj{N6aWAK2ml;P_E!Ht`?y~O008_7001EX0000000000006d
+uvegOzaA|NaUv_0~WN&gWV`yP=WMy<Ob#!JpaB^>AWpXZXc~DCM0u%rg00008031s8R-W;lL%9F|0Q3
+L=03HAU00000000000Jecp+6n-0X>c!Jc4cm4Z*nhVXkl_>WppogWpZ<AZ*DGdc~DCM0u%rg0000803
+1s8RsaA100IC20000003!eZ00000000000Jece+X?`1X>c!Jc4cm4Z*nhVXkl_>WppoNY-ulFUukY>b
+YEXCaCuNm0Rj{N6aWAK2ml;P_ExC1H<bAV0062C001Qb0000000000006duh}#MPaA|NaUv_0~WN&gW
+V`yP=WMy<OV{B<JV`yP=WMy<^V{|TXc~DCM0u%rg00008031s8RsaA100IC20000004M+e000000000
+00Jed|;0ge6X>c!Jc4cm4Z*nhVXkl_>WppoXWprU=VRT_HUtei%X>?y-E^v8JO928D02BZK00;maO7>
+Pa1ya~85dZ-AGyni800000000000002Cfehga0B~t=FJE?LZe(wAFJow7a%5$6FKuOXVPs)+VJ~c9Zf
+A92XJvCPaCuNm0Rj{N6aWAK2ml;P_Ewc%k4VM<000UB001BW0000000000006dufbt3eaA|NaUv_0~W
+N&gWV{dG4a$#*@FJE72ZfSI1UoLQYP)h*<6aW+e000O897^_9QrWGBiUR-u+6e#v8~^|S0000000000
+wt<B63IK3va4%nWWo~3|axY_VY;SU5ZDB8AZgXiaaCuNm0Rj{N6aWAK2ml;P_EuDTtY<t7004L^001K
+Z0000000000006duNcRc=aA|NaUv_0~WN&gWV{dG4a$#*@FJW$TX>@OQX>KzzE^v8JO928D02BZK00;
+maO7>RFgOr9w1ONd23;+Nk00000000000002CfyDz00B~t=FJE?LZe(wAFJo_PZ*pO6VJ~TJX>@5}Y-
+w|4E^v8JO928D02BZK00;maO7>Q|JvhnS1pojg7ytkr00000000000002CflCMr0B~t=FJE?LZe(wAF
+Jo_PZ*pO6VJ~-SZZk42aCuNm0Rj{N6aWAK2ml;P_Etl!N7U^G007<_0018V0000000000006duVh#%c
+aA|NaUv_0~WN&gWV{dG4a$#*@FL!BfbY*gFE^v8JO928D02BZK00;maO7>R$#!nGV0000>0000c0000
+0000000002Cfs7Rk0B~t=FJE?LZe(wAFJo_PZ*pO6VJ~!Lb98erUtei%X>?y-E^v8JO928D02BZK00;
+maO7>QiMV_qh0ssIP3jhEo00000000000002CfgKhL0B~t=FJE?LZe(wAFJo_PZ*pO6VJ~!Lb98erVQ
+zD2Uvy=2bS`jtP)h*<6aW+e000O897^_97Haq2Hwgd$wkZGrE&u=k0000000000wt-O@3jlCwa4%nWW
+o~3|axY_VY;SU5ZDB8TWpi|MFJW$TX>@OQX>KzzUvy=2bS`jtP)h*<6aW+e000O897^_9V|XKJ<^=!%
+RT=;QEdT%j0000000000wt>_l3jlCwa4%nWWo~3|axY_VY;SU5ZDB8TWpi|MFKKRRbZKF1X>(;?bY*j
+NE^v8JO928D02BZK00;maO7>RR7i?(j0RR9>2LJ#m00000000000002CfdwfG0B~t=FJE?LZe(wAFJo
+_PZ*pO6VJ~!Lb98erX>(z8ba`KNWpi{caCuNm0Rj{N6aWAK2ml;P_Etd1GVy=`001`x001KZ0000000
+000006duH!BMOaA|NaUv_0~WN&gWV{dG4a$#*@FLY&dbaO9tbZKmJE^v8JO928D02BZK00;maO7>Q+^
+#_p-0{{Sh4gdfu00000000000002Cf%q&70B~t=FJE?LZe(wAFJo_PZ*pO6VJ~!Lb98ercWG{PWpZs_
+bY*jNE^v8JO928D02BZK00;maO7>QOMi_-&0RR9+0ssIX00000000000002Cfle?B0B~t=FJE?LZe(w
+AFJx(RbZlv2FJE72ZfSI1UoLQYP)h*<6aW+e000O897^_9p(e#RMk@dSE1>`Y9RL6T0000000000wt?
+v}3jlCwa4%nWWo~3|axY|Qb98KJVlQKFZE#_9E^v8JO928D02BZK00;maO7>RDH+b5zFaQAY$p8Q!00
+000000000002Cfofd~0B~t=FJE?LZe(wAFJx(RbZlv2FJxhKVPau(WiD`eP)h*<6aW+e000O897^_9D
+v}@B@e}|6Vo?A98~^|S0000000000wt-oW3jlCwa4%nWWo~3|axY|Qb98KJVlQcKWMz0RaCuNm0Rj{N
+6aWAK2ml;P_EyH=5KS#J000-u0018V0000000000006dugrf@paA|NaUv_0~WN&gWWNCABY-wUIY;R*
+>bZ>HVE^v8JO928D02BZK00;maO7>QGrZs155C8z%IRF4300000000000002Cf$r7|0B~t=FJE?LZe(
+wAFJx(RbZlv2FKuCNX=Y_}bS`jtP)h*<6aW+e000O897^_9mm)w!1_uBD!V>@h9smFU0000000000wt
+<)D3jlCwa4%nWWo~3|axY|Qb98KJVlQoBa%*LBb1rasP)h*<6aW+e000O897^_9K-pa)btM1*d7A(L9
+{>OV0000000000wt?C13jlCwa4%nWWo~3|axY|Qb98KJVlQoFbYWy+bYU)Vc~DCM0u%rg00008031s8
+R-L`ofUpYy07NPP03ZMW00000000000JedP6bt}xX>c!Jc4cm4Z*nhWX>)XJX<{#OWpi(Ja${w4E^v8
+JO928D02BZK00;maO7>QZn{?EU6#xLXMgRaF00000000000002Cfq5Vd0B~t=FJE?LZe(wAFJx(RbZl
+v2FLPsZX>fFNE^v8JO928D02BZK00;maO7>QSN_i6MyZ`_IegOa*00000000000002CfkQS70B~t=FJ
+E?LZe(wAFJx(RbZlv2FLX09E@gOSP)h*<6aW+e000O897^_9oCtaWPCfwu0LlUY9{>OV0000000000w
+t;5z3;=Lxa4%nWWo~3|axY|Qb98KJVlQ+yG%aCrZ7yYaWl&220u%rg00008031s8R$OHR8I#Na005=|
+02=@R00000000000JeegF%AH5X>c!Jc4cm4Z*nhWX>)XJX<{#QHZ(3}cx6ya0Rj{N6aWAK2ml;P_Ert
+06<wl7007nk0RS5S0000000000006duz5WgWaA|NaUv_0~WN&gWWNCABY-wUIb#!TLE^v8JO928D02B
+ZK00;maO7>Q#r847w82|v;TL1ta00000000000002CftW@Q0B~t=FJE?LZe(wAFJx(RbZlv2FLq^eb7
+^mGE^v8JO928D02BZK00;maO7>Qjlx|=qv;Y7AW&r>j00000000000002Cfl^=(0B~t=FJE?LZe(wAF
+Jx(RbZlv2FLyICE@gOSP)h*<6aW+e000O897^_9Ekq02^(_Ga0FnX#9{>OV0000000000wt=w}5CCv#
+a4%nWWo~3|axY|Qb98KJVlQ_#G%aCrZ7yYaWl&220u%rg00008031s8R{rp!E>6V&0052w02=@R0000
+0000000JeeSLJ<IPX>c!Jc4cm4Z*nhWX>)XJX<{#THZ(3}cx6ya0Rj{N6aWAK2ml;P_EyAaw>TUs004
+Tc000~S0000000000006duY6ublaA|NaUv_0~WN&gWWNCABY-wUIcW7m0Y%XwlP)h*<6aW+e000O897
+^_9`(SX~BLM&a)dK(k9smFU0000000000wt>Jh5&&>%a4%nWWo~3|axY|Qb98cVFJE72ZfSI1UoLQYP
+)h*<6aW+e000O897^_99aOw&JOBUyKmY&$9smFU0000000000wt*is5&&>%a4%nWWo~3|axY|Qb98cV
+FJE76VQFq(UoLQYP)h*<6aW+e000O897^_9lL`lV6fFP%vcLcU8~^|S0000000000wt<&45&&>%a4%n
+WWo~3|axY|Qb98cVFJx(RbaHPlaCuNm0Rj{N6aWAK2ml;P_Ev>>x~Loh002<~000~S0000000000006
+du<zW&4aA|NaUv_0~WN&gWX=H9;FJE72ZfSI1UoLQYP)h*<6aW+e000O897^_9Wia+LAp-yaE)4(x82
+|tP0000000000wt+ii5&&>%a4%nWWo~3|axZCQZecHDZ)9a-E^v8JO928D02BZK00;maO7>Porw0ze0
+000%0RR9R00000000000002Cfs<wu0B~t=FJE?LZe(wAFKJ|MVJ~BEZE#_9E^v8JO928D02BZK00;ma
+O7>R%I2yp=3jhF?G5`P=00000000000002Cfs1Dn0B~t=FJE?LZe(wAFKJ|MVJ~BEa%C=Xc~DCM0u%r
+g00008031s8RslBCm>wkn09UO502}}S00000000000Jedma}oe>X>c!Jc4cm4Z*nhbWNu+EX=H9;WMO
+n+E^v8JO928D02BZK00;maO7>P99Dq|H0{{S72LJ#a00000000000002Cf%=#d0B~t=FJE?LZe(wAFK
+J|MVJ~TJbaG*CXJvCPaCuNm0Rj{N6aWAK2ml;P_Et6gD8m;3000#L001BW0000000000006duR-6(5a
+A|NaUv_0~WN&gWX=H9;FK}UFYhh<)Uu0o)VJ>iaP)h*<6aW+e000O897^_96_mWCoSXmv%O(Q=9RL6T
+0000000000wt=gh5&&>%a4%nWWo~3|axZCQZecHVbaON|WMOn+E^v8JO928D02BZK00;maO7>PmGBg+
+T0RRAO1ONaZ00000000000002Cfr2>`0B~t=FJE?LZe(wAFKu&YaA9L>FJE72ZfSI1UoLQYP)h*<6aW
++e000O897^_9J3F1ztpNZ4IRpRzApigX0000000000wt=%d698~&a4%nWWo~3|axZOjXK-O-YcFMZV`
+Xr3X>V?GE^v8JO928D02BZK00;maO7>QJSNR$J1^@uR7XSbn00000000000002CfuB7S0B~t=FJE?LZ
+e(wAFKu&YaA9L>FJ*XiE^v8JO928D02BZK00;maO7>RwNYAS38~_0Dh5!H`00000000000002Cfz(73
+0B~t=FJE?LZe(wAFKu&YaA9L>FJ@tEY+_+!Yc6nkP)h*<6aW+e000O897^_9M&V-~W&r>Il>z_&A^-p
+Y0000000000wt@R$698~&a4%nWWo~3|axZXUV{2h&X>MmPUteKjZ*_EEUoLQYP)h*<6aW+e000O897^
+_96|It>^Z)<=@c{q;ApigX0000000000wt=Bz698~&a4%nWWo~3|axZXUV{2h&X>MmPUtei%X>?y-E^
+v8JO928D02BZK00;maO7>P8Dmr6`4gdh)EC2u_00000000000002Cfz)IZ0B~t=FJE?LZe(wAFK}UFY
+hh<;Zf7rFZDDSCY-w(FcrI{xP)h*<6aW+e000O897^_9opdo8Fb4nt8W8{hBLDyZ0000000000wt<~<
+698~&a4%nWWo~3|axZXUV{2h&X>MmPUu|`BY;0+6b$Bjtc~DCM0u%rg00008031s8RxqRTl3)P<0G9;
+-03-ka00000000000Jeb+dlLX~X>c!Jc4cm4Z*nhiVPk7yXK8L{FJE(Xa&=>Lb#i5ME^v8JO928D02B
+ZK00;maO7>Q5{OUh@3IG5nApig%00000000000002Cfv|iN0B~t=FJE?LZe(wAFK}UFYhh<;Zf7rTVR
+CC_a&s<lc~DCM0u%rg00008031s8R&J9)TJi<}07Mc103`qb00000000000Jec?hZ6vBX>c!Jc4cm4Z
+*nhiVPk7yXK8L{FLGsZb!l>CZDnqBb1rasP)h*<6aW+e000O897^_9HIncK=o$b3o^=2KBLDyZ00000
+00000wt=3G698~&a4%nWWo~3|axZXUV{2h&X>MmPb8uy2X=Z6<a&s<lc~DCM0u%rg00008031s8R=Np
+obBqxH08>2x0384T00000000000Jee0sS^NjX>c!Jc4cm4Z*nhiVPk7yXK8L{FLYsNb1rasP)h*<6aW
++e000O897^_9LG$P{&IJGfXb=DZ9smFU0000000000wt<ej698~&a4%nWWo~3|axZXUV{2h&X>MmPb#
+!TLb1rasP)h*<6aW+e000O897^_93o;9(?+*X~NjU%jAOHXW0000000000wt<+z698~&a4%nWWo~3|a
+xZXUV{2h&X>MmPc4cyNX>V>WaCuNm0Rj{N6aWAK2ml;P_EsEIHn&=I001<r0RSZc0000000000006du
+#nBT0aA|NaUv_0~WN&gWaBF8@a%FRGb#h~6b1z?CX>MtBUtcb8c~DCM0u%rg00008031s8R{pRO|6B$
+D0J}~A03-ka00000000000Jec*Mic;WX>c!Jc4cm4Z*nhiY+-a}Z*py9X>xNfUtei%X>?y-E^v8JO92
+8D02BZK00;maO7>Q9R-#L@0RRBR1pojf00000000000002CfdEYu0B~t=FJE?LZe(wAFK}#ObY^dIZD
+eV3b1z?CZDDC{Utcb8c~DCM0u%rg00008031s8R{AJ&uZ#r%04p2-03!eZ00000000000JeekP80xeX
+>c!Jc4cm4Z*nhiY+-a}Z*py9X>xNfVQyq{Z)s#MaCuNm0Rj{N6aWAK2ml;P_Ez;7u)uN#007(@0018V
+0000000000006du!c-IhaA|NaUv_0~WN&gWaBN|8W^ZzBWNC79FJW+LE^v8JO928D02BZK00;maO7>P
+TWwO)m0ssJB4gdfl00000000000002CfpJ?D0B~t=FJE?LZe(wAFK}#ObY^dIZDeV3b1!XSV{daVaCu
+Nm0Rj{N6aWAK2ml;P_Et<4clRL(003zs001BW0000000000006duo?a9HaA|NaUv_0~WN&gWaBN|8W^
+ZzBWNC79FLiEdcrI{xP)h*<6aW+e000O897^_9aDBB_aR2}Spa1{>BLDyZ0000000000wt@X-6aa8(a
+4%nWWo~3|axZXfVRUA1a&2U3a&s?sWpZ<AZ*DGdc~DCM0u%rg00008031s8R>$El7NrRQ0A(cr03!eZ
+00000000000JedzXA}T%X>c!Jc4cm4Z*nhiY+-a}Z*py9X>xNfcWG{9Z+CMpaCuNm0Rj{N6aWAK2ml;
+P_Ev_(RX_6t005^8001BW0000000000006dum2ngRaA|NaUv_0~WN&gWaCv8KWo~qHFJE72ZfSI1UoL
+QYP)h*<6aW+e000O897^_9d0@(k>Hq)$VF3UDAOHXW0000000000wt>cW6aa8(a4%nWWo~3|axZXsXK
+iI}baO9XUu|J&ZeL$6aCuNm0Rj{N6aWAK2ml;P_EyZ|8Oq5Q004zt0018V0000000000006du?spUba
+A|NaUv_0~WN&gWaCv8KWo~qHFJo<FY-w&~E^v8JO928D02BZK00;maO7>PC-+6zK0ssJ^1^@sb00000
+000000002Cf%K0Q0B~t=FJE?LZe(wAFK~HhZDnqBb1!3WZgX#JWiD`eP)h*<6aW+e000O897^_9ofr9
+Y00RI3k_P|)9smFU0000000000wt>Nt6aa8(a4%nWWo~3|axZXsXKiI}baO9eX>4?5axQRrP)h*<6aW
++e000O897^_9w_G<cg9ZQqQV;+DApigX0000000000wt@YX6aa8(a4%nWWo~3|axZXsXKiI}baO9eZ*
+py6baZ8ME^v8JO928D02BZK00;maO7>Rm)vr{PBme+9hX4Q_00000000000002Cfxny-0B~t=FJE?LZ
+e(wAFK~HhZDnqBb1!UVcx7@faCuNm0Rj{N6aWAK2ml;P_Eu*QObOrt007zp001BW0000000000006du
+j=>ZFaA|NaUv_0~WN&gWaCv8KWo~qHFKusRWo&6~WiD`eP)h*<6aW+e000O897^_9V;P~5T>}6B9|`~
+f9smFU0000000000wt=j}6aa8(a4%nWWo~3|axZXsXKiI}baO9oY;|X8ZZ2?nP)h*<6aW+e000O897^
+_9t8ypvO#}b{01N;CAOHXW0000000000wt+>*6aa8(a4%nWWo~3|axZXsXKiI}baO9qWoKo0Z*X)jaC
+uNm0Rj{N6aWAK2ml;P_EtBkmbrig000yW0018V0000000000006du(90A6aA|NaUv_0~WN&gWaCv8KW
+o~qHFLPsIZf<3AE^v8JO928D02BZK00;maO7>PaFo^(=2LJ%#8UO$x00000000000002CfsN1<0B~t=
+FJE?LZe(wAFK~HhZDnqBb1!pnXlZVEWq5QhaCuNm0Rj{N6aWAK2ml;P_EutI+xegd0040q0012T0000
+000000006duT-X!<aA|NaUv_0~WN&gWaCv8KWo~qHFLQKxY-KKRc~DCM0u%rg00008031s8R+5;!9(x
+A>04Nv$0384T00000000000JecQ-xL6FX>c!Jc4cm4Z*nhid1q~9Zgg`mbZ={AZZ2?nP)h*<6aW+e00
+0O897^_9djSQI$4meK_x1n)ApigX0000000000wt?;D6aa8(a4%nWWo~3|axZXsXKiI}baO9tZfSFLa
+%pa7E^v8JO928D02BZK00;maO7>RvHr8Tu4FCZ4CjbB(00000000000002Cf%7vJ0B~t=FJE?LZe(wA
+FK~HhZDnqBb1!vtX>2ZVc~DCM0u%rg00008031s8R=Lz9k**&A0K%OB04M+e00000000000JedkK@|X
+SX>c!Jc4cm4Z*nhid1q~9Zgg`mW@&76WpZ;bUtei%X>?y-E^v8JO928D02BZK00;maO7>PaAa-5S1^@
+ss6#xJ$00000000000002Cfs|nt0B~t=FJE?LZe(wAFK~HhZDnqBb1!CZa&2LBbY*gLFJE72ZfSI1Uo
+LQYP)h*<6aW+e000O897^_9j*9)vAO!#bP!IqBD*ylh0000000000wt=r`6##H)a4%nWWo~3|axZXsX
+KiI}baO9eZ*py6baZ8Mb1z?QVQ_G1Zf7oVc~DCM0u%rg00008031s8R@(R#e0u}{0P+j~04V?f00000
+000000Jeb`ZWRD<X>c!Jc4cm4Z*nhid1q~9Zgg`mW^ZzBVRUq5a&s?YVq<S)WiD`eP)h*<6aW+e000O
+897^_9aeqi)9R>gZ<`Vz_C;$Ke0000000000wt?Dm6##H)a4%nWWo~3|axZXsXKiI}baO9eZ*py6baZ
+8Mb1!FdZ)RpLaCuNm0Rj{N6aWAK2ml;P_Ez+;X(dV~000_`001Wd0000000000006duJ$V%XaA|NaUv
+_0~WN&gWaCv8KWo~qHFJ^CYZDDkDWpZ;bXmo9CE^v8JO928D02BZK00;maO7>RDgfbwC6#xLTRR91c0
+0000000000002Cfy|#30B~t=FJE?LZe(wAFK~HhZDnqBb1!CZa&2LBbY*gLFKKOOE^v8JO928D02BZK
+00;maO7>Q*=vR5t1^@tc6951v00000000000002Cfts}y0B~t=FJE?LZe(wAFK~HhZDnqBb1!CZa&2L
+BbY*gLFKKdPE^v8JO928D02BZK00;maO7>QhWF^!|761U3O8@{U00000000000002Cfv~(40B~t=FJE
+?LZe(wAFK~HhZDnqBb1!CZa&2LBbY*gLFKl6SWq2-dc~DCM0u%rg00008031s8RydFgR%`|U0MQcw04
+M+e00000000000JecY(-i=4X>c!Jc4cm4Z*nhid1q~9Zgg`mW^ZzBVRUq5a&s?lbZBLAE^v8JO928D0
+2BZK00;maO7>RoS;bWU0ssJ{2mk;s00000000000002Cf$`ZD0B~t=FJE?LZe(wAFK~HhZDnqBb1!CZ
+a&2LBbY*gLFK}UQXK!s`a%**PE^v8JO928D02BZK00;maO7>Qb2I4IL1^@t-6951v00000000000002
+Cfjr$60B~t=FJE?LZe(wAFK~HhZDnqBb1!CZa&2LBbY*gLFLHEdE^v8JO928D02BZK00;maO7>Q)SdE
+gz2><}68~^|&00000000000002Cfq&!`0B~t=FJE?LZe(wAFK~HhZDnqBb1!CZa&2LBbY*gLFLQQhE^
+v8JO928D02BZK00;maO7>P?2=CiW1^@s;5&!@z00000000000002CfrsuD0B~t=FJE?LZe(wAFK~HhZ
+DnqBb1!CZa&2LBbY*gLFLY&cZE0>{Y%XwlP)h*<6aW+e000O897^_9r%g4+?F#?^=`8>NE&u=k00000
+00000wt*b=6##H)a4%nWWo~3|axZXsXKiI}baO9eZ*py6baZ8Mb1!sda&2jDVQexrHZE{^P)h*<6aW+
+e000O897^_9X~uYkK@9)^VlMyyCjbBd0000000000wt-av765Q*a4%nWWo~3|axZXsXKiI}baO9kWq4
+(Bb1z?CX>MtBUtcb8c~DCM0u%rg00008031s8RwL+a%#u0)09hIV04D$d00000000000JeeK4i*4#X>
+c!Jc4cm4Z*nhid1q~9Zgg`mY-M<5a&s?VZDDY5X>MmOaCuNm0Rj{N6aWAK2ml;P_EsNFNE|LJ006Mi0
+01Qb0000000000006duvPl*IaA|NaUv_0~WN&gWaCv8KWo~qHFKlIaWpZ;baCvlSZ*DGdc~DCM0u%rg
+00008031s8RvzWQdPoHT0CWxj04D$d00000000000Jec6brt|{X>c!Jc4cm4Z*nhid1q~9Zgg`mb98x
+ZWpgiIUukY>bYEXCaCuNm0Rj{N6aWAK2ml;P_EvU@@7Q?_005jL001EX0000000000006duuzD5%aA|
+NaUv_0~WN&gWaCvZHa&u{JXD?r0X>MtBUtcb8c~DCM0u%rg00008031s8R(*MWGja$30H+xM03ZMW00
+000000000Jec>h!y~FX>c!Jc4cm4Z*nhid2nHJb7^j8FJWVJX>V?GE^v8JO928D02BZK00;maO7>O`h
+$tr^4*&p5Gynh}00000000000002Cff$h%0B~t=FJE?LZe(wAFK~HqVRCb6Zf7rJZ*6UFZZ2?nP)h*<
+6aW+e000O897^_9<bt{tQ^)`Sy=(&j9RL6T0000000000wt;q_765Q*a4%nWWo~3|axZXsaA9(DX>Mm
+PV{dY0E^v8JO928D02BZK00;maO7>Q5Se3$Y3jhE!B>(^;00000000000002Cfdpw60B~t=FJE?LZe(
+wAFK~HqVRCb6Zf7rLcw=R7bZKvHb1rasP)h*<6aW+e000O897^_9L~CIrQY!!e_LcwuAOHXW0000000
+000wt=>E7XWZ+a4%nWWo~3|axZXsaA9(DX>MmPXk~10WpZ;aaCuNm0Rj{N6aWAK2ml;P_EsB*V8Bos0
+02a2001BW0000000000006duMxYk}aA|NaUv_0~WN&gWaCvZHa&u{JXD@PPb9HQVb1rasP)h*<6aW+e
+000O897^_9+Prz-e+>WturvSwAOHXW0000000000wt>{T7XWZ+a4%nWWo~3|axZXsaA9(DX>MmPbY*j
+NX>MmOaCuNm0Rj{N6aWAK2ml;P_ErNEN#}J7005RL001BW0000000000006duk;oSSaA|NaUv_0~WN&
+gWaCvZHa&u{JXD@YbX=86>WiD`eP)h*<6aW+e000O897^_9cUI9%b_xIh-XQ=09RL6T0000000000wt
++;{7XWZ+a4%nWWo~3|axZXsaA9(DX>MmPb#!TLE^v8JO928D02BZK00;maO7>Qw0AcWg8UO&7UH||o0
+0000000000002Cf%V=O0B~t=FJE?LZe(wAFK~HqVRCb6Zf7rKX<=t_VQnv8UukY>bYEXCaCuNm0Rj{N
+6aWAK2ml;P_EvxAUzqCv008R&001Wd0000000000006duzWEmbaA|NaUv_0~WN&gWaCvZYZ)#;@bYEz
+1Z)<ZeUtei%X>?y-E^v8JO928D02BZK00;maO7>RWYjPN60001r0000c00000000000002Cf$sVj0B~
+t=FJE?LZe(wAFK~Hqa&Ky7V{~6=Z*OaJFJEJCZE#_9E^v8JO928D02BZK00;maO7>QU7S+gb3IG6*E&
+u=|00000000000002CftULi0B~t=FJE?LZe(wAFK~Hqa&Ky7V{~6=Z*OaJFJEbGaBMDcc~DCM0u%rg0
+0008031s8R;cxgWE24a03rea05bpp00000000000Jeci1{eTvX>c!Jc4cm4Z*nhid2n)XYGq?|UubV{
+YjZDOX>MO|a&Kd0b8|0WUukY>bYEXCaCuNm0Rj{N6aWAK2ml;P_EzNdG{hnc006Hl001@s000000000
+0006dut_K(ZaA|NaUv_0~WN&gWaCvZYZ)#;@bYEz1Z)<ZeUukY%aB^>BWpi^cUukY%aB^>BWpi^baCu
+Nm0Rj{N6aWAK2ml;P_Et#W{Qq_b001!*001BW0000000000006duBoi0_aA|NaUv_0~WN&gWa%FLKWp
+i|MFJE72ZfSI1UoLQYP)h*<6aW+e000O897^_98nQ+C0|5X4vjG4ABLDyZ0000000000wt?6h7yxi-a
+4%nWWo~3|axZdaadl;LbaO9XUv_13b7^mGUtcb8c~DCM0u%rg00008031s8R>&yK>4yRU0M`Wo04D$d
+00000000000Jeb~92fv_X>c!Jc4cm4Z*nhkWpQ<7b98erUukZ1WpZv|Y+rSBX>4;YaCuNm0Rj{N6aWA
+K2ml;P_ExDs2p;?r008k!001BW0000000000006du=pGmVaA|NaUv_0~WN&gWa%FLKWpi|MFJWY1aCB
+vIb1rasP)h*<6aW+e000O897^_9?0G{&Qw9J4F&O{=8vp<R0000000000wt*rt7yxi-a4%nWWo~3|ax
+Zdaadl;LbaO9ZaA_`Zc~DCM0u%rg00008031s8RycQN-FyoG0Lv!;02}}S00000000000JedyI2ZtMX
+>c!Jc4cm4Z*nhkWpQ<7b98erVRdw9E^v8JO928D02BZK00;maO7>Qq{=flQ0RR9$0ssIV0000000000
+0002Cfn-D&0B~t=FJE?LZe(wAFLGsZb!BsOb1!3Ma&&VpaCuNm0Rj{N6aWAK2ml;P_ErGNiWpl0000I
+B0015U0000000000006du_(d21aA|NaUv_0~WN&gWa%FLKWpi|MFJo_QaA9;VaCuNm0Rj{N6aWAK2ml
+;P_Es-YtdqSH004kU0018V0000000000006duk4P8*aA|NaUv_0~WN&gWa%FLKWpi|MFJo_SYiVV3E^
+v8JO928D02BZK00;maO7>RWKr%|_1ONc<4gdfm00000000000002Cfr(rg0B~t=FJE?LZe(wAFLGsZb
+!BsOb1!9hV`Xr3X>V?GE^v8JO928D02BZK00;maO7>QV@>(vA1ONah4*&oh00000000000002Cfv{m1
+0B~t=FJE?LZe(wAFLGsZb!BsOb1!IRY;Z1cc~DCM0u%rg00008031s8R;__Y7-s<h0Nnxr0384T0000
+0000000Jed6W*7i)X>c!Jc4cm4Z*nhkWpQ<7b98erXm4+8b1rasP)h*<6aW+e000O897^_9WkA^Jx+V
+Ys*ogoD9smFU0000000000wt*UG7yxi-a4%nWWo~3|axZdaadl;LbaO9lZ)9a`b1rasP)h*<6aW+e00
+0O897^_95<K34YXJZNw*mkFAOHXW0000000000wt*0j7yxi-a4%nWWo~3|axZdaadl;LbaO9oVPk7yX
+JvCPaCuNm0Rj{N6aWAK2ml;P_Et!@QL9-Y005<S001BW0000000000006duxsVtDaA|NaUv_0~WN&gW
+a%FLKWpi|MFLPycb7^mGb1rasP)h*<6aW+e000O897^_9vUJuifCc~nix2<+Bme*a0000000000wt-N
+x7yxi-a4%nWWo~3|axZdaadl;LbaO9rbYXOLb6;a`WMy+MaCuNm0Rj{N6aWAK2ml;P_Eu36Ou1VG003
+YM001HY0000000000006du61f-vaA|NaUv_0~WN&gWa%FLKWpi|MFLQKqbz^jOa%FQaaCuNm0Rj{N6a
+WAK2ml;P_Ex@CWj$Fb006Xt0012T0000000000006dut-TlkaA|NaUv_0~WN&gWa%FLKWpi|MFLiWjY
+;!Jfc~DCM0u%rg00008031s8R$_k-57qzx02u-R03rYY00000000000Jeca=NJHRX>c!Jc4cm4Z*nhk
+Wpi(Ac4cg7VlQ7`X>MtBUtcb8c~DCM0u%rg00008031s8R!<ka>N*Di0Phw603!eZ00000000000Jec
+w=okQSX>c!Jc4cm4Z*nhkWpi(Ac4cg7VlQxVZ+2;9WpZ;aaCuNm0Rj{N6aWAK2ml;P_Exq>z$!HY002
+P-001KZ0000000000006du((f1maA|NaUv_0~WN&gWa%FRGY<6XAX<{#OWpHnDbY*gLE^v8JO928D02
+BZK00;maO7>QJT($@K6aWApPyhfU00000000000002Cfk^Tg0B~t=FJE?LZe(wAFLGsbZ)|pDY-wUIa
+%FRGY<6XGb1rasP)h*<6aW+e000O897^_9R`W2XhXnutV-o-XApigX0000000000wt<2N831r;a4%nW
+Wo~3|axZdab8l>RWo&6;FLQKqbz^jME^v8JO928D02BZK00;maO7>O&00002000000000f000000000
+00002Cfk+J*0B~t=FJE?LZe(wAFLGsbZ)|pDY-wUIV{dJ6VRSEFUukY>bYEXCaCuNm0Rj{N6aWAK2ml
+;P_EsC$E@xu^005i-001xm0000000000006dukqsFDaA|NaUv_0~WN&gWa%FRGY<6XAX<{#9Z*6d4bT
+4CXY;0v?bZKvHb6;U%V=i!cP)h*<6aW+e000O897^_9VS}l~00;m8$`=3t8~^|S0000000000wt+$p8
+31r;a4%nWWo~3|axZdeV`wj5UukY>bYEXCaCuNm0Rj{N6aWAK2ml;P_Ev3u%=rHc0015#000~S00000
+00000006dud=?o1aA|NaUv_0~WN&gWa%p2|FJE76VQFq(UoLQYP)h*<6aW+e000O897^_9-@||wHwpj
+%a3=r&AOHXW0000000000wt=-G831r;a4%nWWo~3|axZdeV`wj5V`Xe?Uw3I_bZB!faCuNm0Rj{N6aW
+AK2ml;P_Evu`?tm<D007G)0stTY0000000000006duDlHiRaA|NaUv_0~WN&gWa%p2|FJEPCZ)#~@V{
+c?-b1rasP)h*<6aW+e000O897^_9<9YA7)&T$jC<FiiA^-pY0000000000wt<wM831r;a4%nWWo~3|a
+xZdeV`wj5Wo>V2X<u?>aBN{?WiD`eP)h*<6aW+e000O897^_9L+eR2FarPpGzb6yA^-pY0000000000
+wt=dk831r;a4%nWWo~3|axZdeV`wj5Wq5FJa&%v2Z*py6bS`jtP)h*<6aW+e000O897^_9Nz}L7n*aa
++2>}2A9smFU0000000000wt*U?831r;a4%nWWo~3|axZdeV`wj5Wq5RDZgXjGZZ2?nP)h*<6aW+e000
+O897^_9?ZLwqhXDWp9|HgY8vp<R0000000000wt?}a831r;a4%nWWo~3|axZdeV`wj5W@&6?Zf`Ddc~
+DCM0u%rg00008031s8Rs(<cesl`}0N*7502}}S00000000000Jed#rWpWmX>c!Jc4cm4Z*nhkX=7+FU
+ukZ0aAjk3E^v8JO928D02BZK00;maO7>P3tL7WG0{{S-3;+Nh00000000000002CfnTy20B~t=FJE?L
+Ze(wAFLG&PXfI!EZ)aa}Wo~3;axQRrP)h*<6aW+e000O897^_9x)16eB>?~c)C2$k82|tP000000000
+0wt-W&831r;a4%nWWo~3|axZdeV`wj5Y;SLHE^v8JO928D02BZK00;maO7>Q@sU0Yz0RRAN1pojZ000
+00000000002Cfv>k20B~t=FJE?LZe(wAFLG&PXfI!Gb!=>3W@&6?E^v8JO928D02BZK00;maO7>P4p;
+s-11ONb+8vp<u00000000000002CfsVNu0B~t=FJE?LZe(wAFLG&PXfI!IVQgh|bY*icaCuNm0Rj{N6
+aWAK2ml;P_Ezce?o8nT005@}000>P0000000000006duPQDocaA|NaUv_0~WN&gWa%p2|FJEwJV{0yO
+c~DCM0u%rg00008031s8RsiXjWYh)#0ALjW02%-Q00000000000Jec<zZn2<X>c!Jc4cm4Z*nhkX=7+
+FUvgn|X>TrYc~DCM0u%rg00008031s8R>m={R9_AN0MAVT0384T00000000000Jed0#u)%`X>c!Jc4c
+m4Z*nhkX=7+FUvqG2Zf<3Ab1rasP)h*<6aW+e000O897^_9=1~*U+yDRoUjYCB8UO$Q0000000000wt
+)=Q831r;a4%nWWo~3|axZdeV`wj5b97;2Yc6nkP)h*<6aW+e000O897^_9VA>K~<p2Nxp#cB@8UO$Q0
+000000000wt*nl831r;a4%nWWo~3|axZdeV`wj5bZKp6axQRrP)h*<6aW+e000O897^_9KUf%5;S&G=
+Bv}9eA^-pY0000000000wt+p@831r;a4%nWWo~3|axZdeV`wj5cWG`jGGAkFZgX#JWiD`eP)h*<6aW+
+e000O897^_9Lu=vMy#fFLh6exu8~^|S0000000000wt-&j831r;a4%nWWo~3|axZdeV`wj5cWG{9Z+C
+MpaCuNm0Rj{N6aWAK2ml;P_Ew|@raj#P007?#001Qb0000000000006duRqh!8aA|NaUv_0~WN&gWa%
+p2|FJE_QZe(wFb6;|0Ze(S0WpXZXc~DCM0u%rg00008031s8Rx2!w9h3q905Ast02u%P00000000000
+Jed3@fiScX>c!Jc4cm4Z*nhkX=7+FUw3k0a4v9pP)h*<6aW+e000O897^_94r@hGjR61vdIJCe7XSbN
+0000000000wt+zO831r;a4%nWWo~3|axZdeV`wj7Vq-3Fc~DCM0u%rg00008031s8R*0o;!>9-V0Dvd
+}02u%P00000000000Jebw_89<hX>c!Jc4cm4Z*nhkX=7+FVQgt<ZZ2?nP)h*<6aW+e000O897^_9T2B
+j+um=DD`WgTL7ytkO0000000000wt?aP831r;a4%nWWo~3|axZdeV`wj7ZgXiaaCuNm0Rj{N6aWAK2m
+l;P_EyU7-6vZF006)Y000*N0000000000006du#|9bzaA|NaUv_0~WN&gWa%p2|FJfVGE^v8JO928D0
+2BZK00;maO7>PT9RE;X3IG6dCIA2z00000000000002CfmaI}0B~t=FJE?LZe(wAFLG&PXfI-KcrI{x
+P)h*<6aW+e000O897^_9u2ys*+XVmsoe=;482|tP0000000000wt?#v8US!<a4%nWWo~3|axZdeV`wj
+9Wo&G7E^v8JO928D02BZK00;maO7>RiM8@6A5&!@&M*sjB00000000000002Cf&CjA0B~t=FJE?LZe(
+wAFLG&PXfI=LY;STdaCuNm0Rj{N6aWAK2ml;P_Eu>`4Nj5)0015Y001EX0000000000006du|1KH;aA
+|NaUv_0~WN&gWa%p2|FJo_PZ*pIBa%pgEWpplZc~DCM0u%rg00008031s8R-Q~!@stMu0NWb?02=@R0
+0000000000Jee9Fd6`GX>c!Jc4cm4Z*nhkX=7+FV{dGAZEkZeaCuNm0Rj{N6aWAK2ml;P_EruSxfxki
+005GM0RS5S0000000000006duoj4i*aA|NaUv_0~WN&gWa%p2|FJo_Rb8l>AE^v8JO928D02BZK00;m
+aO7>QZOwvi-0RR991pojY00000000000002CfiI340B~t=FJE?LZe(wAFLG&PXfI=LZgX^UVQFqIaCu
+Nm0Rj{N6aWAK2ml;P_Ezf_F5Sij004Ov0015U0000000000006duNRS!;aA|NaUv_0~WN&gWa%p2|FJ
+o_RbYW?3WpZ;aaCuNm0Rj{N6aWAK2ml;P_EsGcJ0b7~008D0000{R0000000000006duN|qV`aA|NaU
+v_0~WN&gWa%p2|FJo_RbaHQOE^v8JO928D02BZK00;maO7>RP^2FW`2LJ$)9{>O%00000000000002C
+fpeZ30B~t=FJE?LZe(wAFLG&PXfI@CW?^+~bYF9Hd2D5KE^v8JO928D02BZK00;maO7>PcN3Wi~0RRB
+Z0{{RV00000000000002Cfx@L40B~t=FJE?LZe(wAFLG&PXfI@GVP|e{b7d}Yc~DCM0u%rg00008031
+s8R^SZ>Mfd{%0L2La02u%P00000000000Jed;ry2loX>c!Jc4cm4Z*nhkX=7+FWo>V2X)bViP)h*<6a
+W+e000O897^_9B1j?A?EnA(f&u^l8UO$Q0000000000wt?xZ8US!<a4%nWWo~3|axZdeV`wjBa&m8Sb
+1rasP)h*<6aW+e000O897^_9YTj=YjRF7wlLi0)9smFU0000000000wt)_<8US!<a4%nWWo~3|axZde
+V`wjCX>4U*aB^>Wc`k5yP)h*<6aW+e000O897^_9-vH^DLIeN+%n1Mh8~^|S0000000000wt?5L8US!
+<a4%nWWo~3|axZdeV`wjCX>4V4X?kTYaCuNm0Rj{N6aWAK2ml;P_EtyqA~8V=003|$0018V00000000
+00006duQ?wcYaA|NaUv_0~WN&gWa%p2|FKB6JXl!X`Xmn+AE^v8JO928D02BZK00;maO7>O;`U+4h1p
+ol36951h00000000000002CfziJj0B~t=FJE?LZe(wAFLG&PXfJAWZ*DGdc~DCM0u%rg00008031s8R
+ye^}$cqF30JIDM02=@R00000000000JecL#To!`X>c!Jc4cm4Z*nhkX=7+FYISgVbY*fbaCuNm0Rj{N
+6aWAK2ml;P_ExcB%--(}006f(000^Q0000000000006du_Q@ImaA|NaUv_0~WN&gWa%p2|FKl6XZ*_D
+oaCuNm0Rj{N6aWAK2ml;P_EyTExYM-`006-^000;O0000000000006du9oQNGaA|NaUv_0~WN&gWa%p
+2|FKlUcWiD`eP)h*<6aW+e000O897^_9_O^!vFa!VqQw{(C9{>OV0000000000wt)!e8US!<a4%nWWo
+~3|axZdeV`wjIX?A5_a%FC0WpXZXc~DCM0u%rg00008031s8RvT}A)E5o_0Dmq302=@R00000000000
+Jed3>ly%XX>c!Jc4cm4Z*nhkX=7+FY;R|0X>MmOaCuNm0Rj{N6aWAK2ml;P_EwuiVqW_R000Ic000^Q
+0000000000006du#rYZlaA|NaUv_0~WN&gWa%p2|FKuCRYjtogaCuNm0Rj{N6aWAK2ml;P_E!I_7zAt
+u006lZ000{R0000000000006du_yZdNaA|NaUv_0~WN&gWa%p2|FKuOEb9HiME^v8JO928D02BZK00;
+maO7>Rihu;h11pokQ6951k00000000000002Cft?8(0B~t=FJE?LZe(wAFLG&PXfJSKWMpY>XD)DgP)
+h*<6aW+e000O897^_94#pLNa{&MVJOcm#82|tP0000000000wt=}18vt-=a4%nWWo~3|axZdeV`wjMV
+P|D>E^v8JO928D02BZK00;maO7>Pb06t&41ONa;4FCWe00000000000002CfnyOH0B~t=FJE?LZe(wA
+FLG&PXfJSKY-MzGWiD`eP)h*<6aW+e000O897^_9CS=Ms@d*F`PALEY82|tP0000000000wt-g`8vt-
+=a4%nWWo~3|axZdeV`wjMVQyt?E^v8JO928D02BZK00;maO7>QYNaq$M9{>Ohi~s-{0000000000000
+2Cfqx(y0B~t=FJE?LZe(wAFLG&PXfJSbWps3TE^v8JO928D02BZK00;maO7>Qp(`0^OE&u>J=>Py600
+000000000002Cf!seE0B~t=FJE?LZe(wAFLG&PXfJSbZ)b94b8{|mc~DCM0u%rg00008031s8R^Zr}G
+z$p;0OcP503ZMW00000000000Jed5ZW{n_X>c!Jc4cm4Z*nhkX=7+FaB^>Fa%FRKUt(c$E^v8JO928D
+02BZK00;maO7>O+aOYX&3IG5nEC2u+00000000000002Cfxveg0B~t=FJE?LZe(wAFLG&PXfJSbZ*6d
+NE^v8JO928D02BZK00;maO7>P*nETT?0ssJS1pojX00000000000002Cf!%@|0B~t=FJE?LZe(wAFLG
+&PXfJSbZ**^CZ)`4bc~DCM0u%rg00008031s8R$aob*L45@0Hy!{02%-Q00000000000Jecpg&P2HX>
+c!Jc4cm4Z*nhkX=7+Fa%E>}Z*DGdc~DCM0u%rg00008031s8R@c|jQxpXN08bGB02lxO00000000000
+Jeesg&P2HX>c!Jc4cm4Z*nhkX=7+Fa%FIGE^v8JO928D02BZK00;maO7>QgX#;IV1pom05dZ)f00000
+000000002Cfk%rQ0B~t=FJE?LZe(wAFLG&PXfJYgY-KKRc~DCM0u%rg00008031s8Ru6^sD|7?^02>P
+c02u%P00000000000Jed`kQ)GSX>c!Jc4cm4Z*nhkX=7+Fb7OCCWiD`eP)h*<6aW+e000O897^_9KQ;
+cYQUU+~HwFLz8UO$Q0000000000wt;Px8vt-=a4%nWWo~3|axZdeV`wjPV{&C>ZZ2?nP)h*<6aW+e00
+0O897^_9V^uN6G86y+w_X4M8vp<R0000000000wt@GT8vt-=a4%nWWo~3|axZdeV`wjPWoK<=Zgehic
+~DCM0u%rg00008031s8R>&%)<5&d%0P_$402=@R00000000000Jec*tQ!DuX>c!Jc4cm4Z*nhkX=7+F
+b8u;HZe?;VaCuNm0Rj{N6aWAK2ml;P_EwxIF?03=002o5000^Q0000000000006du^RXKMaA|NaUv_0
+~WN&gWa%p2|FLQKZbaitsaCuNm0Rj{N6aWAK2ml;P_Ex?)Jfo}@006;h000>P0000000000006duA-5
+X<aA|NaUv_0~WN&gWa%p2|FLQKxY-KKRc~DCM0u%rg00008031s8R`Cj^P}Knd0O|w)02%-Q0000000
+0000Jeby&Km%5X>c!Jc4cm4Z*nhkX=7+Fb98xZWn?aJc~DCM0u%rg00008031s8R_<D_Oz9s00A+~)0
+2%-Q00000000000Jeb<&>H}7X>c!Jc4cm4Z*nhkX=7+Fb9rubVR$ZZc~DCM0u%rg00008031s8R%Ru*
+gJd5700f%=02u%P00000000000JecL@EZVdX>c!Jc4cm4Z*nhkX=7+FbYWs_WiD`eP)h*<6aW+e000O
+897^_9IwRA+{sRC2Dh&VtA^-pY0000000000wt>wL8~|`>a4%nWWo~3|axZdeV`wjQWpZt4ZeeU+bZB
+L5WiD`eP)h*<6aW+e000O897^_9!%D2J8z%q&)v*8o7ytkO0000000000wt)*28~|`>a4%nWWo~3|ax
+ZdeV`wjQWq5QhaCuNm0Rj{N6aWAK2ml;P_Ezj<p^nW2006-b000>P0000000000006duTss^9aA|NaU
+v_0~WN&gWa%p2|FLY>SZDlTSc~DCM0u%rg00008031s8R#A2KP)7g&0A>IH02%-Q00000000000Jec(
+KpX&YX>c!Jc4cm4Z*nhkX=7+FbZBL5WpgfYc~DCM0u%rg00008031s8R_NHy=TaH~0HkvO0384T0000
+0000000JeeOKpX&YX>c!Jc4cm4Z*nhkX=7+FbaG*1Wny7tYc6nkP)h*<6aW+e000O897^_9KD`&3R|)
+_C(IWr=7ytkO0000000000wt;M08~|`>a4%nWWo~3|axZdeV`wjQa%E*MaCuNm0Rj{N6aWAK2ml;P_E
+wL+>IZNY000e8001BW0000000000006du`DGjcaA|NaUv_0~WN&gWbY*T~V`+4GFJE72ZfSI1UoLQYP
+)h*<6aW+e000O897^_91<h(U=L7%%-wgl&AOHXW0000000000wt=U68~|`>a4%nWWo~3|axZjcZee3-
+ba^jdVRLzIV`*<LaCuNm0Rj{N6aWAK2ml;P_EyH4)Bf87004ss0015U0000000000006du%zzvKaA|N
+aUv_0~WN&gWbY*T~V`+4GFJE<ZX>4;YaCuNm0Rj{N6aWAK2ml;P_EvEJATLM*005E(0012T00000000
+00006du<AfXlaA|NaUv_0~WN&gWbY*T~V`+4GFJWeMWpXZXc~DCM0u%rg00008031s8Rz+h#CJ_Sw02
+&4W03HAU00000000000Jec<h#UZLX>c!Jc4cm4Z*nhmWo}_(X>@rnVr6D;a%C=Xc~DCM0u%rg000080
+31s8Rz$^xy5|D`07MA@03-ka00000000000Jed%iyQ!OX>c!Jc4cm4Z*nhmWo}_(X>@rnVr6D;a%Eq0
+Y-MF|E^v8JO928D02BZK00;maO7>Q!Y_ikb0ssJK1pojW00000000000002Cf!vQA0B~t=FJE?LZe(w
+AFLY&YVPk1@c`t5Za4v9pP)h*<6aW+e000O897^_9Qq<Qkss;c6Dk1;?9RL6T0000000000wt?}I8~|
+`>a4%nWWo~3|axZjcZee3-ba^jwWpr|RE^v8JO928D02BZK00;maO7>O+aKr}_1ONaI3;+Ne0000000
+0000002Cf!3KE0B~t=FJE?LZe(wAFLY&YVPk1@c`tKxZ*VSfc~DCM0u%rg00008031s8R#wR>KdA!%0
+A2_H03rYY00000000000Jec6o*V#hX>c!Jc4cm4Z*nhmWo}_(X>@rnbZ>HQVPtQ2WnwOHc~DCM0u%rg
+00008031s8R!L~ptgZ<F09YRY02}}S00000000000Jeb)q8tElX>c!Jc4cm4Z*nhmWo}_(X>@rncVTI
+CE^v8JO928D02BZK00;maO7>Q!swMpw0RRAu0RR9U00000000000002Cf%K~!0B~t=FJE?LZe(wAFLZ
+BhY-ulFUukY>bYEXCaCuNm0Rj{N6aWAK2ml;P_ErMEj%kb*003!N000~S0000000000006duMy(tGaA
+|NaUv_0~WN&gWbZ>2JX)j-JVRCb2axQRrP)h*<6aW+e000O897^_9b?lQdegpsje+vKr7ytkO000000
+0000wt)=98~|`>a4%nWWo~3|axZjmZER^TUvgzGaCuNm0Rj{N6aWAK2ml;P_Exj+5@*E#008~~000{R
+0000000000006duz{nf`aA|NaUv_0~WN&gWbZ>2JX)j-Nd2nTOE^v8JO928D02BZK00;maO7>PygCHn
+s1pojA4FCWi00000000000002CfxgKc0B~t=FJE?LZe(wAFLiQkY-wUMFJE72ZfSI1UoLQYP)h*<6aW
++e000O897^_99X}It0u2BFJ1PJGBLDyZ0000000000wt;2O8~|`>a4%nWWo~3|axZmqY;0*_GcR9bZ)
+|L3V{~b6ZgVbhc~DCM0u%rg00008031s8R)lE<tv~<(06+i$03QGV00000000000Jeds+#CRKX>c!Jc
+4cm4Z*nhna%^mAVlyvac4cyNX>V>WaCuNm0Rj{N6aWAK2ml;P_EztMQ9DK#002x+001EX0000000000
+006duCEXkVaA|NaUv_0~WN&gWb#iQMX<{=kV{dM5Wn*+{Z*DGdc~DCM0u%rg00008031s8R+uM)I}a-
+W05+Te03`qb00000000000Jedu^c(<iX>c!Jc4cm4Z*nhna%^mAVlyveZ*Fd7V{~b6Zg6jJY%XwlP)h
+*<6aW+e000O897^_9Ud&0g>j?k=86W@vApigX0000000000wt@T~9RP4?a4%nWWo~3|axZmqY;0*_Gc
+RR$V`Xr3X>V?GE^v8JO928D02BZK00;maO7>RAC`&9L3IG6uApig!00000000000002CfhH;)0B~t=F
+JE?LZe(wAFLiQkY-wUMFJ@_FY-DpTaCuNm0Rj{N6aWAK2ml;P_Ev|hzoUKw004*y0018V0000000000
+006dufixWeaA|NaUv_0~WN&gWb#iQMX<{=kW@&6?aBp*TE^v8JO928D02BZK00;maO7>QPL}X-D761S
+!O#lEQ00000000000002Cfjl@J0B~t=FJE?LZe(wAFLiQkY-wUMFK};fY;9p~VP|D>E^v8JO928D02B
+ZK00;maO7>R#kM07e2LJ$J7XSbr00000000000002CfzeJK0B~t=FJE?LZe(wAFLiQkY-wUMFLGsZb!
+BsOE^v8JO928D02BZK00;maO7>PzAh<eXAOHZdcK`q%00000000000002CfwWc~0B~t=FJE?LZe(wAF
+LiQkY-wUMFLGsbaBpsNWiD`eP)h*<6aW+e000O897^_9000000ssI200000CjbBd0000000000wt-Z4
+9RP4?a4%nWWo~3|axZmqY;0*_GcRLrZgg^KVlQ7`X>MtBUtcb8c~DCM0u%rg00008031s8Rw{$(6}15
+X0KEeM05Jdn00000000000JedfcO3w5X>c!Jc4cm4Z*nhna%^mAVlyveZ*FvQX<{#5VQ_F|Zf9w3WnX
+1(c4=~NZZ2?nP)h*<6aW+e000O897^_93htAMWDEcR94i0-C;$Ke0000000000wt=5{9RP4?a4%nWWo
+~3|axZmqY;0*_GcRLrZgg^KVlQEEaAj_1X>MgMaCuNm0Rj{N6aWAK2ml;P_Er^X={Hga006KN001Wd0
+000000000006duNroK&aA|NaUv_0~WN&gWb#iQMX<{=kV{dMBa%o~OZggyIaBpvHE^v8JO928D02BZK
+00;maO7>PxTI)N}6aWCZLI40L00000000000002Cf#8fC0B~t=FJE?LZe(wAFLiQkY-wUMFJo_RbaH8
+8FK~HpaAj_Db8Iefc~DCM0u%rg00008031s8R>drF9>6640FZ_N04@Lk00000000000Jeemp&bBlX>c
+!Jc4cm4Z*nhna%^mAVlyveZ*FvQX<{#PWn*=6Wpr|3ZgX&Na&#_mc~DCM0u%rg00008031s8R?AYzKU
+oL>0J$3g03-ka00000000000Jebx$Q=N1X>c!Jc4cm4Z*nhna%^mAVlyveZ*FvQX<{#PZ)0n7E^v8JO
+928D02BZK00;maO7>O&00002000000000u00000000000002Cfu7JE0B~t=FJE?LZe(wAFLiQkY-wUM
+FJo_RbaH88FJE(IV|8+6baG*Cb8v5RbT40DX>MtBUtcb8c~DCM0u%rg00008031s8RxZyiP3{l?0N_L
+b05|{u00000000000Jeel&>aA9X>c!Jc4cm4Z*nhna%^mAVlyveZ*FvQX<{#5b7f<7a%FUKVQzD9Z*p
+`mVrgz<X>Mn8E^v8JO928D02BZK00;maO7>Q+DyO_z5dZ*UHUI!Q00000000000002CfjZ(H0B~t=FJ
+E?LZe(wAFLiQkY-wUMFJo_RbaH88FJE(IV|8+6baG*Cb8v5RbT4dgcVBE}c4cfXaCuNm0Rj{N6aWAK2
+ml;P_ErD@0006200000001Ze0000000000006du>hm1{aA|NaUv_0~WN&gWb#iQMX<{=kaA9L>VP|D?
+FJE72ZfSI1UoLQYP)h*<6aW+e000O897^_9T$CBCCLsU-X@>v+BLDyZ0000000000wt+JA9RP4?a4%n
+WWo~3|axZmqY;0*_GcRyqV{2h&WpgicX?QMhc~DCM0u%rg00008031s8RsaA100IC20000005Sjo000
+00000000Jedd6&?U^X>c!Jc4cm4Z*nhna%^mAVlyvrVPk7yXJvCQVqs%zaBp&Sb1z?CX>MtBUtcb8c~
+DCM0u%rg00008031s8R^GT{vq%B}0Eq<v05Sjo00000000000Jeea6&?U^X>c!Jc4cm4Z*nhna%^mAV
+lyvrVPk7yXJvCQVqs%zaBp&Sb1!XSYh`9>Y-KKRc~DCM0u%rg00008031s8Rt?`Pc8dl80N)e<06G8w
+00000000000JedH7#;v{X>c!Jc4cm4Z*nhna%^mAVlyvrVPk7yXJvCQVqs%zaBp&Sb1!#gVQX?_W?yD
+$ZeeU`dSxzfc~DCM0u%rg00008031s8R_2PCn%DsV0D}Yo03-ka00000000000Jec<A07a3X>c!Jc4c
+m4Z*nhna%^mAVlyvwbZKlaUtei%X>?y-E^v8JO928D02BZK00;maO7>Rls^kxv2LJ#i6951v0000000
+0000002Cfq)?%0B~t=FJE?LZe(wAFLiQkY-wUMFLiWjY%gPPZf<2`bZKvHE^v8JO928D02BZK00;maO
+7>O?&s+yy0ssI-1^@sd00000000000002CfnF&d0B~t=FJE?LZe(wAFLiQkY-wUMFLiWjY%g$fZ+Lkw
+aCuNm0Rj{N6aWAK2ml;P_Et^<_MiL!008m<001EX0000000000006du`zsy*aA|NaUv_0~WN&gWb#iQ
+MX<{=kb#!TLFL8Bcb!9Gac~DCM0u%rg00008031s8RyU4q@v8*@0G$s203!eZ00000000000JecPEgk
+@HX>c!Jc4cm4Z*nhna%^mAVlyvwbZKlaa%FLKWpi{caCuNm0Rj{N6aWAK2ml;P_Et71)wEy*006cP00
+1Na0000000000006duA~PNUaA|NaUv_0~WN&gWb#iQMX<{=kb#!TLFLGsbaBpsNWiD`eP)h*<6aW+e0
+00O897^_9I!Mcs{1yNJ^Hl%<ApigX0000000000wt>Vr9sqD@a4%nWWo~3|axZmqY;0*_GcR>?X>2cY
+Wpr|RE^v8JO928D02BZK00;maO7>QylKaP}761SlLjV9E00000000000002Cf&Wh)0B~t=FJE?LZe(w
+AFLiQkY-wUMFLiWjY%g<jY+o*Lc~DCM0u%rg00008031s8RzGpKy6Ff20Dcw#04@Lk00000000000Je
+eTW*z`=X>c!Jc4cm4Z*nhna%^mAVlyvwbZKlab8~E8ZDDj{XkTb=b98QDZDlTSc~DCM0u%rg0000803
+1s8R<aQHw*LnJ0Ph+A04M+e00000000000Jeb{a2^0~X>c!Jc4cm4Z*nhna%^mAVlyvwbZKlab8~ETa
+$#<BaBp&SE^v8JO928D02BZK00;maO7>R$7ML^U3jhGPCjbB=00000000000002CfnInX0B~t=FJE?L
+Ze(wAFLiQkY-wUMFLiWjY%g?aZDntDbS`jtP)h*<6aW+e000O897^_9E7j;;7ZU&g*f#(G9{>OV0000
+000000wt<C&9sqD@a4%nWWo~3|axZmqY;0*_GcR>?X>2cba%?Vec~DCM0u%rg00008031s8R#wzj)xQ
+S-02>tm03ZMW00000000000JeeImmUCcX>c!Jc4cm4Z*nhna%^mAVlyvwbZKlacVTICE^v8JO928D02
+BZK00;maO7>QG&>wL!3jhF9DF6T@00000000000002Cf!3cM0B~t=FJE?LZe(wAFLz~PWo~0{WNB_^b
+1z?CX>MtBUtcb8c~DCM0u%rg00008031s8R>!Rfiv<P%023ns03rYY00000000000Jecjs~!MwX>c!J
+c4cm4Z*nhpWnyJ+V{c?>ZfA2ZY++($Y;!Jfc~DCM0u%rg00008031s8R#1O2A4CEG02u`U03-ka0000
+0000000JedTu^s?$X>c!Jc4cm4Z*nhpWnyJ+V{c?>ZfA2ZZEI{{Vr6V|E^v8JO928D02BZK00;maO7>
+P~IB=)A1pok}82|tw00000000000002CffckK0B~t=FJE?LZe(wAFLz~PWo~0{WNB_^b1!sdb98eqaC
+uNm0Rj{N6aWAK2ml;P_Ey^l{MMxe007ev001fg0000000000006du4Z0oxaA|NaUv_0~WN&gWcV%K_Z
+ewp`X>Mn8FL+;db7gX0WMyV)Ze?UHaCuNm1qJ{B008s>^a044008>F9smFU
+"""
+
+
+if __name__ == "__main__":
+    main()
diff --git a/go-applio-manager-recode.bat b/go-applio-manager-recode.bat
new file mode 100644
index 0000000000000000000000000000000000000000..91b8acfc0c69a356fd5b1d77650b2cd728b1072b
--- /dev/null
+++ b/go-applio-manager-recode.bat
@@ -0,0 +1,322 @@
+@echo off
+title Applio Installer
+
+:::                       _ _         _____                    _      
+:::     /\               | (_)       |  __ \                  | |     
+:::    /  \   _ __  _ __ | |_  ___   | |__) |___  ___ ___   __| | ___ 
+:::   / /\ \ | '_ \| '_ \| | |/ _ \  |  _  // _ \/ __/ _ \ / _` |/ _ \
+:::  / ____ \| |_) | |_) | | | (_) | | | \ \  __/ (_| (_) | (_| |  __/
+::: /_/    \_\ .__/| .__/|_|_|\___/  |_|  \_\___|\___\___/ \__,_|\___|
+:::          | |   | |                                                
+:::          |_|   |_|                                                
+:::
+:::
+
+setlocal 
+set "branch=applio-recode"
+set "runtime=runtime-recode"
+set "repoUrl=https://github.com/IAHispano/Applio-RVC-Fork/archive/refs/heads/%branch%.zip"
+set "fixesFolder=fixes"
+set "localFixesPy=local_fixes.py"
+set "principal=%cd%"
+set "URL_BASE=https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main"
+set "URL_EXTRA=https://huggingface.co/IAHispano/applio/resolve/main"
+
+:menu
+for /f "delims=: tokens=*" %%A in ('findstr /b ":::" "%~f0"') do @echo(%%A
+
+echo [1] Reinstall Applio
+echo [2] Update Applio
+echo [3] Update Applio + Runtime
+echo.
+
+set /p choice=Select an option: 
+set choice=%choice: =%
+
+if "%choice%"=="1" (
+    cls
+    echo Starting Applio Reinstaller...
+    echo.
+    goto reinstaller
+    pause
+    cls
+    goto menu
+
+)
+
+if "%choice%"=="2" (
+    cls
+    echo Starting Applio Updater...
+    echo.
+    goto updater
+    pause
+    cls
+    goto menu
+)
+
+if "%choice%"=="3" (
+    cls
+    echo Updating Applio + Runtime...
+    echo.
+    goto updaterRuntime
+    pause
+    cls
+    goto menu
+
+)
+
+cls
+echo Invalid option. Please enter a number from 1 to 3.
+echo.
+echo Press 'Enter' to access the main menu...
+pause>nul
+cls
+goto menu
+
+:reinstaller
+
+echo WARNING: Remember to install Microsoft C++ Build Tools, Redistributable, Python, and Git before continuing.
+echo.
+echo Step-by-step guide: https://rentry.org/appliolocal
+echo Build Tools: https://aka.ms/vs/17/release/vs_BuildTools.exe
+echo Redistributable: https://aka.ms/vs/17/release/vc_redist.x64.exe
+echo Git: https://github.com/git-for-windows/git/releases/download/v2.42.0.windows.2/Git-2.42.0.2-64-bit.exe
+echo Python: Add this route to the windows enviroment variables the user path variable: %principal%\runtime\Scripts
+echo.
+pause
+cls
+
+echo Downloading ZIP file...
+powershell -command "& { Invoke-WebRequest -Uri '%repoUrl%' -OutFile '%principal%\repo.zip' }"
+echo.
+
+echo Extracting ZIP file...
+powershell -command "& { Add-Type -AssemblyName System.IO.Compression.FileSystem ; [System.IO.Compression.ZipFile]::ExtractToDirectory('%principal%\repo.zip', '%principal%') }"
+echo.
+
+echo Copying folder and file structure from subdirectory to main directory...
+robocopy "%principal%\Applio-RVC-Fork-%branch%" "%principal%" /E
+echo.
+
+echo Deleting contents of subdirectory (files and folders)...
+rmdir "%principal%\Applio-RVC-Fork-%branch%" /S /Q
+echo.
+
+echo Cleaning up...
+del "%principal%\repo.zip"
+echo.
+cls
+
+echo Proceeding to download the models...
+echo.
+
+echo WARNING: At this point, it's recommended to disable antivirus or firewall, as errors might occur when downloading pretrained models.
+pause
+cls
+
+echo Downloading models in the assets folder...
+cd "assets"
+echo.
+echo Downloading the "pretrained" folder...
+cd "pretrained"
+curl -LJO "%URL_BASE%/pretrained/D32k.pth"
+curl -LJO "%URL_BASE%/pretrained/D40k.pth"
+curl -LJO "%URL_BASE%/pretrained/D48k.pth"
+curl -LJO "%URL_BASE%/pretrained/G32k.pth"
+curl -LJO "%URL_BASE%/pretrained/G40k.pth"
+curl -LJO "%URL_BASE%/pretrained/G48k.pth"
+curl -LJO "%URL_BASE%/pretrained/f0D32k.pth"
+curl -LJO "%URL_BASE%/pretrained/f0D40k.pth"
+curl -LJO "%URL_BASE%/pretrained/f0D48k.pth"
+curl -LJO "%URL_BASE%/pretrained/f0G32k.pth"
+curl -LJO "%URL_BASE%/pretrained/f0G40k.pth"
+curl -LJO "%URL_BASE%/pretrained/f0G48k.pth"
+cd ".."
+echo.
+cls
+
+echo Downloading the "pretrained_v2" folder...
+cd "pretrained_v2"
+curl -LJO "%URL_BASE%/pretrained_v2/D32k.pth"
+curl -LJO "%URL_BASE%/pretrained_v2/D40k.pth"
+curl -LJO "%URL_BASE%/pretrained_v2/D48k.pth"
+curl -LJO "%URL_BASE%/pretrained_v2/G32k.pth"
+curl -LJO "%URL_BASE%/pretrained_v2/G40k.pth"
+curl -LJO "%URL_BASE%/pretrained_v2/G48k.pth"
+curl -LJO "%URL_BASE%/pretrained_v2/f0D32k.pth"
+curl -LJO "%URL_BASE%/pretrained_v2/f0D40k.pth"
+curl -LJO "%URL_BASE%/pretrained_v2/f0D48k.pth"
+curl -LJO "%URL_BASE%/pretrained_v2/f0G32k.pth"
+curl -LJO "%URL_BASE%/pretrained_v2/f0G40k.pth"
+curl -LJO "%URL_BASE%/pretrained_v2/f0G48k.pth"
+cd ".."
+echo.
+cls
+
+echo Downloading the hubert_base.pt file...
+cd "hubert"
+curl -LJO "%URL_BASE%/hubert_base.pt"
+cd ".."
+echo.
+cls
+
+
+echo Downloading the rmvpe.pt file...
+cd "rmvpe"
+curl -LJO "%URL_BASE%/rmvpe.pt"
+echo.
+cls
+
+echo Downloading the rmvpe.onnx file...
+curl -LJO "%URL_BASE%/rmvpe.onnx"
+cd ".."
+cd ".."
+echo.
+cls
+
+echo Downloading the rest of the large files
+
+echo Downloading the "uvr5_weights" folder...
+cd "uvr5_weights"
+curl -LJO "%URL_BASE%/uvr5_weights/HP2_all_vocals.pth"
+curl -LJO "%URL_BASE%/uvr5_weights/HP3_all_vocals.pth"
+curl -LJO "%URL_BASE%/uvr5_weights/HP5_only_main_vocal.pth"
+curl -LJO "%URL_BASE%/uvr5_weights/VR-DeEchoAggressive.pth"
+curl -LJO "%URL_BASE%/uvr5_weights/VR-DeEchoDeReverb.pth"
+curl -LJO "%URL_BASE%/uvr5_weights/VR-DeEchoNormal.pth"
+cd ".."
+echo.
+cls
+
+echo Downloading the ffmpeg.exe file...
+curl -LJO "%URL_BASE%/ffmpeg.exe"
+echo.
+cls
+
+echo Downloading the ffprobe.exe file...
+curl -LJO "%URL_BASE%/ffprobe.exe"
+echo.
+cls
+
+echo Downloading the runtime.zip file...
+curl -LJO "%URL_EXTRA%/%runtime%.zip"
+echo.
+cls
+
+echo Extracting the runtime.zip file, this might take a while...
+powershell -Command "Expand-Archive -Path '%runtime%.zip' -DestinationPath '.'"
+del %runtime%.zip
+echo.
+cls
+
+echo Downloads completed!
+echo.
+
+echo Checking if the local_fixes.py file exists in the Fixes folder...
+if exist "%fixesFolder%\%localFixesPy%" (
+    echo Running the file...
+    runtime\python.exe "%fixesFolder%\%localFixesPy%"
+) else (
+    echo The "%localFixesPy%" file was not found in the "Fixes" folder.
+)
+echo.
+
+echo Fixes Applied!
+echo.
+
+echo Applio has been reinstalled!
+echo.
+echo Press 'Enter' to access the main menu...
+pause>nul
+cls
+goto menu
+
+
+:updater
+
+echo Downloading the ZIP file...
+powershell -command "& { Invoke-WebRequest -Uri '%repoUrl%' -OutFile '%principal%\repo.zip' }"
+echo.
+
+echo Extracting ZIP file...
+powershell -command "& { Add-Type -AssemblyName System.IO.Compression.FileSystem ; [System.IO.Compression.ZipFile]::ExtractToDirectory('%principal%\repo.zip', '%principal%') }"
+echo.
+
+echo Copying folder and file structure from subdirectory to main directory...
+robocopy "%principal%\Applio-RVC-Fork-%branch%" "%principal%" /E
+echo.
+
+echo Deleting contents of the subdirectory (files and folders)...
+rmdir "%principal%\Applio-RVC-Fork-%branch%" /S /Q
+echo.
+
+echo Cleaning up...
+del "%principal%\repo.zip"
+echo.
+cls
+
+echo Verifying if the local_fixes.py file exists in the Fixes folder...
+if exist "%fixesFolder%\%localFixesPy%" (
+    echo Running the file...
+    runtime\python.exe "%fixesFolder%\%localFixesPy%"
+) else (
+    echo The file "%localFixesPy%" was not found in the "Fixes" folder.
+)
+echo.
+
+echo Applio has been updated!
+echo.
+echo Press 'Enter' to access the main menu... 
+pause>nul
+cls
+goto menu
+
+
+:updaterRuntime
+
+echo Downloading the ZIP file...
+powershell -command "& { Invoke-WebRequest -Uri '%repoUrl%' -OutFile '%principal%\repo.zip' }"
+echo.
+
+echo Extracting ZIP file...
+powershell -command "& { Add-Type -AssemblyName System.IO.Compression.FileSystem ; [System.IO.Compression.ZipFile]::ExtractToDirectory('%principal%\repo.zip', '%principal%') }"
+echo.
+
+echo Copying folder and file structure from subdirectory to main directory...
+robocopy "%principal%\Applio-RVC-Fork-%branch%" "%principal%" /E
+echo.
+
+echo Deleting contents of the subdirectory (files and folders)...
+rmdir "%principal%\Applio-RVC-Fork-%branch%" /S /Q
+echo.
+
+echo Cleaning up...
+del "%principal%\repo.zip"
+echo.
+cls
+
+echo Downloading the runtime.zip file...
+curl -LJO "%URL_EXTRA%/%runtime%.zip"
+echo.
+cls
+echo Extracting the runtime.zip file, this might take a while...
+powershell -Command "Expand-Archive -Path '%runtime%.zip' -DestinationPath '.'"
+del runtime.zip
+echo.
+cls
+
+echo Verifying if the local_fixes.py file exists in the Fixes folder...
+if exist "%fixesFolder%\%localFixesPy%" (
+    echo Running the file...
+    runtime\python.exe "%fixesFolder%\%localFixesPy%"
+) else (
+    echo The file "%localFixesPy%" was not found in the "Fixes" folder.
+)
+echo.
+
+echo Applio has been updated!
+echo.
+echo Press 'Enter' to access the main menu...
+pause>nul
+cls
+goto menu
diff --git a/go-applio.bat b/go-applio.bat
new file mode 100644
index 0000000000000000000000000000000000000000..60c0c41d34a8aee5e14e744accb33d028d807245
--- /dev/null
+++ b/go-applio.bat
@@ -0,0 +1,92 @@
+@echo off
+setlocal
+title Start Applio
+
+:::
+:::                       _ _
+:::     /\               | (_)
+:::    /  \   _ __  _ __ | |_  ___
+:::   / /\ \ | '_ \| '_ \| | |/ _ \
+:::  / ____ \| |_) | |_) | | | (_) |
+::: /_/    \_\ .__/| .__/|_|_|\___/
+:::          | |   | |
+:::          |_|   |_|
+:::
+:::
+
+:menu
+for /f "delims=: tokens=*" %%A in ('findstr /b ":::" "%~f0"') do @echo(%%A
+
+echo [1] Start Applio
+echo [2] Start Applio (DML)
+echo [3] Start Realtime GUI (DML)
+echo [4] Start Realtime GUI (V0)
+echo [5] Start Realtime GUI (V1)
+echo.
+
+set /p choice=Select an option: 
+set choice=%choice: =%
+
+cls
+echo WARNING: It's recommended to disable antivirus or firewall, as errors might occur when starting the ssl.
+pause
+
+if "%choice%"=="1" (
+    cls
+    echo WARNING: At this point, it's recommended to disable antivirus or firewall, as errors might occur when downloading pretrained models.
+    pause>null
+    echo Starting Applio...
+    echo.
+    runtime\python.exe infer-web.py --pycmd runtime\python.exe --port 7897
+    pause
+    cls
+    goto menu
+)
+
+if "%choice%"=="2" (
+    cls
+    echo Starting Applio ^(DML^)...
+    echo.
+    runtime\python.exe infer-web.py --pycmd runtime\python.exe --port 7897 --dml
+    pause
+    cls
+    goto menu
+)
+
+if "%choice%"=="3" (
+    cls
+    echo Starting Realtime GUI ^(DML^)...
+    echo.
+    runtime\python.exe gui_v1.py --pycmd runtime\python.exe --dml
+    pause
+    cls
+    goto menu
+)
+
+if "%choice%"=="4" (
+    cls
+    echo Starting Realtime GUI ^(V0^)...
+    echo.
+    runtime\python.exe gui_v0.py
+    pause
+    cls
+    goto menu
+)
+
+if "%choice%"=="5" (
+    cls
+    echo Starting Realtime GUI ^(V1^)...
+    echo.
+    runtime\python.exe gui_v1.py
+    pause
+    cls
+    goto menu
+)
+
+cls
+echo Invalid option. Please enter a number from 1 to 5.
+echo.
+echo Press 'Enter' to access the main menu...
+pause>nul
+cls
+goto menu
diff --git a/go-tensorboard.bat b/go-tensorboard.bat
new file mode 100644
index 0000000000000000000000000000000000000000..cb81c17d3865513adec8eb0b832b7888cd1e4078
--- /dev/null
+++ b/go-tensorboard.bat
@@ -0,0 +1,2 @@
+python fixes/tensor-launch.py
+pause
\ No newline at end of file
diff --git a/gui_v0.py b/gui_v0.py
new file mode 100644
index 0000000000000000000000000000000000000000..88c3cf9eb1eaa0fa812b32ae4d3750b4ce0a8699
--- /dev/null
+++ b/gui_v0.py
@@ -0,0 +1,786 @@
+import os, sys, traceback, re
+
+import json
+
+now_dir = os.getcwd()
+sys.path.append(now_dir)
+from configs.config import Config
+
+Config = Config()
+import PySimpleGUI as sg
+import sounddevice as sd
+import noisereduce as nr
+import numpy as np
+from fairseq import checkpoint_utils
+import librosa, torch, pyworld, faiss, time, threading
+import torch.nn.functional as F
+import torchaudio.transforms as tat
+import scipy.signal as signal
+import torchcrepe
+
+# import matplotlib.pyplot as plt
+from lib.infer_pack.models import (
+    SynthesizerTrnMs256NSFsid,
+    SynthesizerTrnMs256NSFsid_nono,
+    SynthesizerTrnMs768NSFsid,
+    SynthesizerTrnMs768NSFsid_nono,
+)
+from i18n import I18nAuto
+
+i18n = I18nAuto()
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+current_dir = os.getcwd()
+
+
+class RVC:
+    def __init__(
+        self, key, f0_method, hubert_path, pth_path, index_path, npy_path, index_rate
+    ) -> None:
+        """
+        初始化
+        """
+        try:
+            self.f0_up_key = key
+            self.time_step = 160 / 16000 * 1000
+            self.f0_min = 50
+            self.f0_max = 1100
+            self.f0_mel_min = 1127 * np.log(1 + self.f0_min / 700)
+            self.f0_mel_max = 1127 * np.log(1 + self.f0_max / 700)
+            self.f0_method = f0_method
+            self.sr = 16000
+            self.window = 160
+
+            # Get Torch Device
+            if torch.cuda.is_available():
+                self.torch_device = torch.device(
+                    f"cuda:{0 % torch.cuda.device_count()}"
+                )
+            elif torch.backends.mps.is_available():
+                self.torch_device = torch.device("mps")
+            else:
+                self.torch_device = torch.device("cpu")
+
+            if index_rate != 0:
+                self.index = faiss.read_index(index_path)
+                # self.big_npy = np.load(npy_path)
+                self.big_npy = self.index.reconstruct_n(0, self.index.ntotal)
+                print("index search enabled")
+            self.index_rate = index_rate
+            model_path = hubert_path
+            print("load model(s) from {}".format(model_path))
+            models, saved_cfg, task = checkpoint_utils.load_model_ensemble_and_task(
+                [model_path],
+                suffix="",
+            )
+            self.model = models[0]
+            self.model = self.model.to(device)
+            if Config.is_half:
+                self.model = self.model.half()
+            else:
+                self.model = self.model.float()
+            self.model.eval()
+            cpt = torch.load(pth_path, map_location="cpu")
+            self.tgt_sr = cpt["config"][-1]
+            cpt["config"][-3] = cpt["weight"]["emb_g.weight"].shape[0]  # n_spk
+            self.if_f0 = cpt.get("f0", 1)
+            self.version = cpt.get("version", "v1")
+            if self.version == "v1":
+                if self.if_f0 == 1:
+                    self.net_g = SynthesizerTrnMs256NSFsid(
+                        *cpt["config"], is_half=Config.is_half
+                    )
+                else:
+                    self.net_g = SynthesizerTrnMs256NSFsid_nono(*cpt["config"])
+            elif self.version == "v2":
+                if self.if_f0 == 1:
+                    self.net_g = SynthesizerTrnMs768NSFsid(
+                        *cpt["config"], is_half=Config.is_half
+                    )
+                else:
+                    self.net_g = SynthesizerTrnMs768NSFsid_nono(*cpt["config"])
+            del self.net_g.enc_q
+            print(self.net_g.load_state_dict(cpt["weight"], strict=False))
+            self.net_g.eval().to(device)
+            if Config.is_half:
+                self.net_g = self.net_g.half()
+            else:
+                self.net_g = self.net_g.float()
+        except:
+            print(traceback.format_exc())
+
+    def get_regular_crepe_computation(self, x, f0_min, f0_max, model="full"):
+        batch_size = 512
+        # Compute pitch using first gpu
+        audio = torch.tensor(np.copy(x))[None].float()
+        f0, pd = torchcrepe.predict(
+            audio,
+            self.sr,
+            self.window,
+            f0_min,
+            f0_max,
+            model,
+            batch_size=batch_size,
+            device=self.torch_device,
+            return_periodicity=True,
+        )
+        pd = torchcrepe.filter.median(pd, 3)
+        f0 = torchcrepe.filter.mean(f0, 3)
+        f0[pd < 0.1] = 0
+        f0 = f0[0].cpu().numpy()
+        return f0
+
+    def get_harvest_computation(self, x, f0_min, f0_max):
+        f0, t = pyworld.harvest(
+            x.astype(np.double),
+            fs=self.sr,
+            f0_ceil=f0_max,
+            f0_floor=f0_min,
+            frame_period=10,
+        )
+        f0 = pyworld.stonemask(x.astype(np.double), f0, t, self.sr)
+        f0 = signal.medfilt(f0, 3)
+        return f0
+
+    def get_f0(self, x, f0_up_key, inp_f0=None):
+        # Calculate Padding and f0 details here
+        p_len = x.shape[0] // 512  # For Now This probs doesn't work
+        x_pad = 1
+        f0_min = 50
+        f0_max = 1100
+        f0_mel_min = 1127 * np.log(1 + f0_min / 700)
+        f0_mel_max = 1127 * np.log(1 + f0_max / 700)
+
+        f0 = 0
+        # Here, check f0_methods and get their computations
+        if self.f0_method == "harvest":
+            f0 = self.get_harvest_computation(x, f0_min, f0_max)
+        elif self.f0_method == "reg-crepe":
+            f0 = self.get_regular_crepe_computation(x, f0_min, f0_max)
+        elif self.f0_method == "reg-crepe-tiny":
+            f0 = self.get_regular_crepe_computation(x, f0_min, f0_max, "tiny")
+
+        # Calculate f0_course and f0_bak here
+        f0 *= pow(2, f0_up_key / 12)
+        # with open("test.txt","w")as f:f.write("\n".join([str(i)for i in f0.tolist()]))
+        tf0 = self.sr // self.window  # 每秒f0点数
+        if inp_f0 is not None:
+            delta_t = np.round(
+                (inp_f0[:, 0].max() - inp_f0[:, 0].min()) * tf0 + 1
+            ).astype("int16")
+            replace_f0 = np.interp(
+                list(range(delta_t)), inp_f0[:, 0] * 100, inp_f0[:, 1]
+            )
+            shape = f0[x_pad * tf0 : x_pad * tf0 + len(replace_f0)].shape[0]
+            f0[x_pad * tf0 : x_pad * tf0 + len(replace_f0)] = replace_f0[:shape]
+        # with open("test_opt.txt","w")as f:f.write("\n".join([str(i)for i in f0.tolist()]))
+        f0bak = f0.copy()
+        f0_mel = 1127 * np.log(1 + f0 / 700)
+        f0_mel[f0_mel > 0] = (f0_mel[f0_mel > 0] - f0_mel_min) * 254 / (
+            f0_mel_max - f0_mel_min
+        ) + 1
+        f0_mel[f0_mel <= 1] = 1
+        f0_mel[f0_mel > 255] = 255
+        f0_coarse = np.rint(f0_mel).astype(np.int)
+        return f0_coarse, f0bak  # 1-0
+
+    def infer(self, feats: torch.Tensor) -> np.ndarray:
+        """
+        推理函数
+        """
+        audio = feats.clone().cpu().numpy()
+        assert feats.dim() == 1, feats.dim()
+        feats = feats.view(1, -1)
+        padding_mask = torch.BoolTensor(feats.shape).fill_(False)
+        if Config.is_half:
+            feats = feats.half()
+        else:
+            feats = feats.float()
+        inputs = {
+            "source": feats.to(device),
+            "padding_mask": padding_mask.to(device),
+            "output_layer": 9 if self.version == "v1" else 12,
+        }
+        torch.cuda.synchronize()
+        with torch.no_grad():
+            logits = self.model.extract_features(**inputs)
+            feats = (
+                self.model.final_proj(logits[0]) if self.version == "v1" else logits[0]
+            )
+
+        ####索引优化
+        try:
+            if (
+                hasattr(self, "index")
+                and hasattr(self, "big_npy")
+                and self.index_rate != 0
+            ):
+                npy = feats[0].cpu().numpy().astype("float32")
+                score, ix = self.index.search(npy, k=8)
+                weight = np.square(1 / score)
+                weight /= weight.sum(axis=1, keepdims=True)
+                npy = np.sum(self.big_npy[ix] * np.expand_dims(weight, axis=2), axis=1)
+                if Config.is_half:
+                    npy = npy.astype("float16")
+                feats = (
+                    torch.from_numpy(npy).unsqueeze(0).to(device) * self.index_rate
+                    + (1 - self.index_rate) * feats
+                )
+            else:
+                print("index search FAIL or disabled")
+        except:
+            traceback.print_exc()
+            print("index search FAIL")
+        feats = F.interpolate(feats.permute(0, 2, 1), scale_factor=2).permute(0, 2, 1)
+        torch.cuda.synchronize()
+        print(feats.shape)
+        if self.if_f0 == 1:
+            pitch, pitchf = self.get_f0(audio, self.f0_up_key)
+            p_len = min(feats.shape[1], 13000, pitch.shape[0])  # 太大了爆显存
+        else:
+            pitch, pitchf = None, None
+            p_len = min(feats.shape[1], 13000)  # 太大了爆显存
+        torch.cuda.synchronize()
+        # print(feats.shape,pitch.shape)
+        feats = feats[:, :p_len, :]
+        if self.if_f0 == 1:
+            pitch = pitch[:p_len]
+            pitchf = pitchf[:p_len]
+            pitch = torch.LongTensor(pitch).unsqueeze(0).to(device)
+            pitchf = torch.FloatTensor(pitchf).unsqueeze(0).to(device)
+        p_len = torch.LongTensor([p_len]).to(device)
+        ii = 0  # sid
+        sid = torch.LongTensor([ii]).to(device)
+        with torch.no_grad():
+            if self.if_f0 == 1:
+                infered_audio = (
+                    self.net_g.infer(feats, p_len, pitch, pitchf, sid)[0][0, 0]
+                    .data.cpu()
+                    .float()
+                )
+            else:
+                infered_audio = (
+                    self.net_g.infer(feats, p_len, sid)[0][0, 0].data.cpu().float()
+                )
+        torch.cuda.synchronize()
+        return infered_audio
+
+
+class GUIConfig:
+    def __init__(self) -> None:
+        self.hubert_path: str = ""
+        self.pth_path: str = ""
+        self.index_path: str = ""
+        self.npy_path: str = ""
+        self.f0_method: str = ""
+        self.pitch: int = 12
+        self.samplerate: int = 44100
+        self.block_time: float = 1.0  # s
+        self.buffer_num: int = 1
+        self.threhold: int = -30
+        self.crossfade_time: float = 0.08
+        self.extra_time: float = 0.04
+        self.I_noise_reduce = False
+        self.O_noise_reduce = False
+        self.index_rate = 0.3
+
+
+class GUI:
+    def __init__(self) -> None:
+        self.config = GUIConfig()
+        self.flag_vc = False
+
+        self.launcher()
+
+    def load(self):
+        (
+            input_devices,
+            output_devices,
+            input_devices_indices,
+            output_devices_indices,
+        ) = self.get_devices()
+        try:
+            with open("values1.json", "r") as j:
+                data = json.load(j)
+        except:
+            # Injecting f0_method into the json data
+            with open("values1.json", "w") as j:
+                data = {
+                    "pth_path": "",
+                    "index_path": "",
+                    "sg_input_device": input_devices[
+                        input_devices_indices.index(sd.default.device[0])
+                    ],
+                    "sg_output_device": output_devices[
+                        output_devices_indices.index(sd.default.device[1])
+                    ],
+                    "threhold": "-45",
+                    "pitch": "0",
+                    "index_rate": "0",
+                    "block_time": "1",
+                    "crossfade_length": "0.04",
+                    "extra_time": "1",
+                }
+        return data
+
+    def launcher(self):
+        data = self.load()
+        sg.theme("DarkTeal12")
+        input_devices, output_devices, _, _ = self.get_devices()
+        layout = [
+            [
+                sg.Frame(
+                    title="Proudly forked by Mangio621",
+                ),
+                sg.Frame(
+                    title=i18n("Load model"),
+                    layout=[
+                        [
+                            sg.Input(
+                                default_text="hubert_base.pt",
+                                key="hubert_path",
+                                disabled=True,
+                            ),
+                            sg.FileBrowse(
+                                i18n("Hubert Model"),
+                                initial_folder=os.path.join(os.getcwd()),
+                                file_types=(("pt files", "*.pt"),),
+                            ),
+                        ],
+                        [
+                            sg.Input(
+                                default_text=data.get("pth_path", ""),
+                                key="pth_path",
+                            ),
+                            sg.FileBrowse(
+                                i18n("Select the .pth file"),
+                                initial_folder=os.path.join(os.getcwd(), "weights"),
+                                file_types=(("weight files", "*.pth"),),
+                            ),
+                        ],
+                        [
+                            sg.Input(
+                                default_text=data.get("index_path", ""),
+                                key="index_path",
+                            ),
+                            sg.FileBrowse(
+                                i18n("Select the .index file"),
+                                initial_folder=os.path.join(os.getcwd(), "logs"),
+                                file_types=(("index files", "*.index"),),
+                            ),
+                        ],
+                        [
+                            sg.Input(
+                                default_text="你不需要填写这个You don't need write this.",
+                                key="npy_path",
+                                disabled=True,
+                            ),
+                            sg.FileBrowse(
+                                i18n("Select the .npy file"),
+                                initial_folder=os.path.join(os.getcwd(), "logs"),
+                                file_types=(("feature files", "*.npy"),),
+                            ),
+                        ],
+                    ],
+                ),
+            ],
+            [
+                # Mangio f0 Selection frame Here
+                sg.Frame(
+                    layout=[
+                        [
+                            sg.Radio(
+                                "Harvest", "f0_method", key="harvest", default=True
+                            ),
+                            sg.Radio("Crepe", "f0_method", key="reg-crepe"),
+                            sg.Radio("Crepe Tiny", "f0_method", key="reg-crepe-tiny"),
+                        ]
+                    ],
+                    title="Select an f0 Method",
+                )
+            ],
+            [
+                sg.Frame(
+                    layout=[
+                        [
+                            sg.Text(i18n("Input device")),
+                            sg.Combo(
+                                input_devices,
+                                key="sg_input_device",
+                                default_value=data.get("sg_input_device", ""),
+                            ),
+                        ],
+                        [
+                            sg.Text(i18n("Output device")),
+                            sg.Combo(
+                                output_devices,
+                                key="sg_output_device",
+                                default_value=data.get("sg_output_device", ""),
+                            ),
+                        ],
+                    ],
+                    title=i18n("Audio device (please use the same type of driver)"),
+                )
+            ],
+            [
+                sg.Frame(
+                    layout=[
+                        [
+                            sg.Text(i18n("Response threshold")),
+                            sg.Slider(
+                                range=(-60, 0),
+                                key="threhold",
+                                resolution=1,
+                                orientation="h",
+                                default_value=data.get("threhold", ""),
+                            ),
+                        ],
+                        [
+                            sg.Text(i18n("Pitch settings")),
+                            sg.Slider(
+                                range=(-24, 24),
+                                key="pitch",
+                                resolution=1,
+                                orientation="h",
+                                default_value=data.get("pitch", ""),
+                            ),
+                        ],
+                        [
+                            sg.Text(i18n("Index Rate")),
+                            sg.Slider(
+                                range=(0.0, 1.0),
+                                key="index_rate",
+                                resolution=0.01,
+                                orientation="h",
+                                default_value=data.get("index_rate", ""),
+                            ),
+                        ],
+                    ],
+                    title=i18n("General settings"),
+                ),
+                sg.Frame(
+                    layout=[
+                        [
+                            sg.Text(i18n("Sample length")),
+                            sg.Slider(
+                                range=(0.1, 3.0),
+                                key="block_time",
+                                resolution=0.1,
+                                orientation="h",
+                                default_value=data.get("block_time", ""),
+                            ),
+                        ],
+                        [
+                            sg.Text(i18n("Fade length")),
+                            sg.Slider(
+                                range=(0.01, 0.15),
+                                key="crossfade_length",
+                                resolution=0.01,
+                                orientation="h",
+                                default_value=data.get("crossfade_length", ""),
+                            ),
+                        ],
+                        [
+                            sg.Text(i18n("Extra推理时长")),
+                            sg.Slider(
+                                range=(0.05, 3.00),
+                                key="extra_time",
+                                resolution=0.01,
+                                orientation="h",
+                                default_value=data.get("extra_time", ""),
+                            ),
+                        ],
+                        [
+                            sg.Checkbox(i18n("Input noise reduction"), key="I_noise_reduce"),
+                            sg.Checkbox(i18n("Output noise reduction"), key="O_noise_reduce"),
+                        ],
+                    ],
+                    title=i18n("Performance settings"),
+                ),
+            ],
+            [
+                sg.Button(i18n("开始音频Convert"), key="start_vc"),
+                sg.Button(i18n("停止音频Convert"), key="stop_vc"),
+                sg.Text(i18n("Inference time (ms):")),
+                sg.Text("0", key="infer_time"),
+            ],
+        ]
+        self.window = sg.Window("RVC - GUI", layout=layout)
+        self.event_handler()
+
+    def event_handler(self):
+        while True:
+            event, values = self.window.read()
+            if event == sg.WINDOW_CLOSED:
+                self.flag_vc = False
+                exit()
+            if event == "start_vc" and self.flag_vc == False:
+                if self.set_values(values) == True:
+                    print("using_cuda:" + str(torch.cuda.is_available()))
+                    self.start_vc()
+                    settings = {
+                        "pth_path": values["pth_path"],
+                        "index_path": values["index_path"],
+                        "f0_method": self.get_f0_method_from_radios(values),
+                        "sg_input_device": values["sg_input_device"],
+                        "sg_output_device": values["sg_output_device"],
+                        "threhold": values["threhold"],
+                        "pitch": values["pitch"],
+                        "index_rate": values["index_rate"],
+                        "block_time": values["block_time"],
+                        "crossfade_length": values["crossfade_length"],
+                        "extra_time": values["extra_time"],
+                    }
+                    with open("values1.json", "w") as j:
+                        json.dump(settings, j)
+            if event == "stop_vc" and self.flag_vc == True:
+                self.flag_vc = False
+
+    # Function that returns the used f0 method in string format "harvest"
+    def get_f0_method_from_radios(self, values):
+        f0_array = [
+            {"name": "harvest", "val": values["harvest"]},
+            {"name": "reg-crepe", "val": values["reg-crepe"]},
+            {"name": "reg-crepe-tiny", "val": values["reg-crepe-tiny"]},
+        ]
+        # Filter through to find a true value
+        used_f0 = ""
+        for f0 in f0_array:
+            if f0["val"] == True:
+                used_f0 = f0["name"]
+                break
+        if used_f0 == "":
+            used_f0 = "harvest"  # Default Harvest if used_f0 is empty somehow
+        return used_f0
+
+    def set_values(self, values):
+        if len(values["pth_path"].strip()) == 0:
+            sg.popup(i18n("Select the pth file"))
+            return False
+        if len(values["index_path"].strip()) == 0:
+            sg.popup(i18n("Select the index file"))
+            return False
+        pattern = re.compile("[^\x00-\x7F]+")
+        if pattern.findall(values["hubert_path"]):
+            sg.popup(i18n("The hubert model path must not contain Chinese characters"))
+            return False
+        if pattern.findall(values["pth_path"]):
+            sg.popup(i18n("The pth file path must not contain Chinese characters."))
+            return False
+        if pattern.findall(values["index_path"]):
+            sg.popup(i18n("The index file path must not contain Chinese characters."))
+            return False
+        self.set_devices(values["sg_input_device"], values["sg_output_device"])
+        self.config.hubert_path = os.path.join(current_dir, "hubert_base.pt")
+        self.config.pth_path = values["pth_path"]
+        self.config.index_path = values["index_path"]
+        self.config.npy_path = values["npy_path"]
+        self.config.f0_method = self.get_f0_method_from_radios(values)
+        self.config.threhold = values["threhold"]
+        self.config.pitch = values["pitch"]
+        self.config.block_time = values["block_time"]
+        self.config.crossfade_time = values["crossfade_length"]
+        self.config.extra_time = values["extra_time"]
+        self.config.I_noise_reduce = values["I_noise_reduce"]
+        self.config.O_noise_reduce = values["O_noise_reduce"]
+        self.config.index_rate = values["index_rate"]
+        return True
+
+    def start_vc(self):
+        torch.cuda.empty_cache()
+        self.flag_vc = True
+        self.block_frame = int(self.config.block_time * self.config.samplerate)
+        self.crossfade_frame = int(self.config.crossfade_time * self.config.samplerate)
+        self.sola_search_frame = int(0.012 * self.config.samplerate)
+        self.delay_frame = int(0.01 * self.config.samplerate)  # 往前预留0.02s
+        self.extra_frame = int(self.config.extra_time * self.config.samplerate)
+        self.rvc = None
+        self.rvc = RVC(
+            self.config.pitch,
+            self.config.f0_method,
+            self.config.hubert_path,
+            self.config.pth_path,
+            self.config.index_path,
+            self.config.npy_path,
+            self.config.index_rate,
+        )
+        self.input_wav: np.ndarray = np.zeros(
+            self.extra_frame
+            + self.crossfade_frame
+            + self.sola_search_frame
+            + self.block_frame,
+            dtype="float32",
+        )
+        self.output_wav: torch.Tensor = torch.zeros(
+            self.block_frame, device=device, dtype=torch.float32
+        )
+        self.sola_buffer: torch.Tensor = torch.zeros(
+            self.crossfade_frame, device=device, dtype=torch.float32
+        )
+        self.fade_in_window: torch.Tensor = torch.linspace(
+            0.0, 1.0, steps=self.crossfade_frame, device=device, dtype=torch.float32
+        )
+        self.fade_out_window: torch.Tensor = 1 - self.fade_in_window
+        self.resampler1 = tat.Resample(
+            orig_freq=self.config.samplerate, new_freq=16000, dtype=torch.float32
+        )
+        self.resampler2 = tat.Resample(
+            orig_freq=self.rvc.tgt_sr,
+            new_freq=self.config.samplerate,
+            dtype=torch.float32,
+        )
+        thread_vc = threading.Thread(target=self.soundinput)
+        thread_vc.start()
+
+    def soundinput(self):
+        """
+        接受音频输入
+        """
+        with sd.Stream(
+            channels=2,
+            callback=self.audio_callback,
+            blocksize=self.block_frame,
+            samplerate=self.config.samplerate,
+            dtype="float32",
+        ):
+            while self.flag_vc:
+                time.sleep(self.config.block_time)
+                print("Audio block passed.")
+        print("ENDing VC")
+
+    def audio_callback(
+        self, indata: np.ndarray, outdata: np.ndarray, frames, times, status
+    ):
+        """
+        音频处理
+        """
+        start_time = time.perf_counter()
+        indata = librosa.to_mono(indata.T)
+        if self.config.I_noise_reduce:
+            indata[:] = nr.reduce_noise(y=indata, sr=self.config.samplerate)
+
+        """noise gate"""
+        frame_length = 2048
+        hop_length = 1024
+        rms = librosa.feature.rms(
+            y=indata, frame_length=frame_length, hop_length=hop_length
+        )
+        db_threhold = librosa.amplitude_to_db(rms, ref=1.0)[0] < self.config.threhold
+        # print(rms.shape,db.shape,db)
+        for i in range(db_threhold.shape[0]):
+            if db_threhold[i]:
+                indata[i * hop_length : (i + 1) * hop_length] = 0
+        self.input_wav[:] = np.append(self.input_wav[self.block_frame :], indata)
+
+        # infer
+        print("input_wav:" + str(self.input_wav.shape))
+        # print('infered_wav:'+str(infer_wav.shape))
+        infer_wav: torch.Tensor = self.resampler2(
+            self.rvc.infer(self.resampler1(torch.from_numpy(self.input_wav)))
+        )[-self.crossfade_frame - self.sola_search_frame - self.block_frame :].to(
+            device
+        )
+        print("infer_wav:" + str(infer_wav.shape))
+
+        # SOLA algorithm from https://github.com/yxlllc/DDSP-SVC
+        cor_nom = F.conv1d(
+            infer_wav[None, None, : self.crossfade_frame + self.sola_search_frame],
+            self.sola_buffer[None, None, :],
+        )
+        cor_den = torch.sqrt(
+            F.conv1d(
+                infer_wav[None, None, : self.crossfade_frame + self.sola_search_frame]
+                ** 2,
+                torch.ones(1, 1, self.crossfade_frame, device=device),
+            )
+            + 1e-8
+        )
+        sola_offset = torch.argmax(cor_nom[0, 0] / cor_den[0, 0])
+        print("sola offset: " + str(int(sola_offset)))
+
+        # crossfade
+        self.output_wav[:] = infer_wav[sola_offset : sola_offset + self.block_frame]
+        self.output_wav[: self.crossfade_frame] *= self.fade_in_window
+        self.output_wav[: self.crossfade_frame] += self.sola_buffer[:]
+        if sola_offset < self.sola_search_frame:
+            self.sola_buffer[:] = (
+                infer_wav[
+                    -self.sola_search_frame
+                    - self.crossfade_frame
+                    + sola_offset : -self.sola_search_frame
+                    + sola_offset
+                ]
+                * self.fade_out_window
+            )
+        else:
+            self.sola_buffer[:] = (
+                infer_wav[-self.crossfade_frame :] * self.fade_out_window
+            )
+
+        if self.config.O_noise_reduce:
+            outdata[:] = np.tile(
+                nr.reduce_noise(
+                    y=self.output_wav[:].cpu().numpy(), sr=self.config.samplerate
+                ),
+                (2, 1),
+            ).T
+        else:
+            outdata[:] = self.output_wav[:].repeat(2, 1).t().cpu().numpy()
+        total_time = time.perf_counter() - start_time
+        self.window["infer_time"].update(int(total_time * 1000))
+        print("infer time:" + str(total_time))
+        print("f0_method: " + str(self.config.f0_method))
+
+    def get_devices(self, update: bool = True):
+        """获取设备列表"""
+        if update:
+            sd._terminate()
+            sd._initialize()
+        devices = sd.query_devices()
+        hostapis = sd.query_hostapis()
+        for hostapi in hostapis:
+            for device_idx in hostapi["devices"]:
+                devices[device_idx]["hostapi_name"] = hostapi["name"]
+        input_devices = [
+            f"{d['name']} ({d['hostapi_name']})"
+            for d in devices
+            if d["max_input_channels"] > 0
+        ]
+        output_devices = [
+            f"{d['name']} ({d['hostapi_name']})"
+            for d in devices
+            if d["max_output_channels"] > 0
+        ]
+        input_devices_indices = [
+            d["index"] if "index" in d else d["name"]
+            for d in devices
+            if d["max_input_channels"] > 0
+        ]
+        output_devices_indices = [
+            d["index"] if "index" in d else d["name"]
+            for d in devices
+            if d["max_output_channels"] > 0
+        ]
+        return (
+            input_devices,
+            output_devices,
+            input_devices_indices,
+            output_devices_indices,
+        )
+
+    def set_devices(self, input_device, output_device):
+        """设置输出设备"""
+        (
+            input_devices,
+            output_devices,
+            input_device_indices,
+            output_device_indices,
+        ) = self.get_devices()
+        sd.default.device[0] = input_device_indices[input_devices.index(input_device)]
+        sd.default.device[1] = output_device_indices[
+            output_devices.index(output_device)
+        ]
+        print("input device:" + str(sd.default.device[0]) + ":" + str(input_device))
+        print("output device:" + str(sd.default.device[1]) + ":" + str(output_device))
+
+
+gui = GUI()
diff --git a/gui_v1.py b/gui_v1.py
new file mode 100644
index 0000000000000000000000000000000000000000..becba80cdda6987c1ad70c89e68a4e3a4da44639
--- /dev/null
+++ b/gui_v1.py
@@ -0,0 +1,708 @@
+import os
+import logging
+import sys
+from dotenv import load_dotenv
+
+load_dotenv()
+
+os.environ["OMP_NUM_THREADS"] = "4"
+if sys.platform == "darwin":
+    os.environ["PYTORCH_ENABLE_MPS_FALLBACK"] = "1"
+
+now_dir = os.getcwd()
+sys.path.append(now_dir)
+import multiprocessing
+
+logger = logging.getLogger(__name__)
+
+
+class Harvest(multiprocessing.Process):
+    def __init__(self, inp_q, opt_q):
+        multiprocessing.Process.__init__(self)
+        self.inp_q = inp_q
+        self.opt_q = opt_q
+
+    def run(self):
+        import numpy as np
+        import pyworld
+
+        while 1:
+            idx, x, res_f0, n_cpu, ts = self.inp_q.get()
+            f0, t = pyworld.harvest(
+                x.astype(np.double),
+                fs=16000,
+                f0_ceil=1100,
+                f0_floor=50,
+                frame_period=10,
+            )
+            res_f0[idx] = f0
+            if len(res_f0.keys()) >= n_cpu:
+                self.opt_q.put(ts)
+
+
+if __name__ == "__main__":
+    import json
+    import multiprocessing
+    import re
+    import threading
+    import time
+    import traceback
+    from multiprocessing import Queue, cpu_count
+    from queue import Empty
+
+    import librosa
+    from tools.torchgate import TorchGate
+    import numpy as np
+    import PySimpleGUI as sg
+    import sounddevice as sd
+    import torch
+    import torch.nn.functional as F
+    import torchaudio.transforms as tat
+
+    import tools.rvc_for_realtime as rvc_for_realtime
+    from i18n.i18n import I18nAuto
+
+    i18n = I18nAuto()
+    device = rvc_for_realtime.config.device
+    # device = torch.device(
+    #     "cuda"
+    #     if torch.cuda.is_available()
+    #     else ("mps" if torch.backends.mps.is_available() else "cpu")
+    # )
+    current_dir = os.getcwd()
+    inp_q = Queue()
+    opt_q = Queue()
+    n_cpu = min(cpu_count(), 8)
+    for _ in range(n_cpu):
+        Harvest(inp_q, opt_q).start()
+
+    class GUIConfig:
+        def __init__(self) -> None:
+            self.pth_path: str = ""
+            self.index_path: str = ""
+            self.pitch: int = 0
+            self.samplerate: int = 40000
+            self.block_time: float = 1.0  # s
+            self.buffer_num: int = 1
+            self.threhold: int = -60
+            self.crossfade_time: float = 0.04
+            self.extra_time: float = 2.0
+            self.I_noise_reduce = False
+            self.O_noise_reduce = False
+            self.rms_mix_rate = 0.0
+            self.index_rate = 0.3
+            self.n_cpu = min(n_cpu, 6)
+            self.f0method = "harvest"
+            self.sg_input_device = ""
+            self.sg_output_device = ""
+
+    class GUI:
+        def __init__(self) -> None:
+            self.config = GUIConfig()
+            self.flag_vc = False
+
+            self.launcher()
+
+        def load(self):
+            input_devices, output_devices, _, _ = self.get_devices()
+            try:
+                with open("configs/config.json", "r") as j:
+                    data = json.load(j)
+                    data["pm"] = data["f0method"] == "pm"
+                    data["harvest"] = data["f0method"] == "harvest"
+                    data["crepe"] = data["f0method"] == "crepe"
+                    data["rmvpe"] = data["f0method"] == "rmvpe"
+            except:
+                with open("configs/config.json", "w") as j:
+                    data = {
+                        "pth_path": " ",
+                        "index_path": " ",
+                        "sg_input_device": input_devices[sd.default.device[0]],
+                        "sg_output_device": output_devices[sd.default.device[1]],
+                        "threhold": "-60",
+                        "pitch": "0",
+                        "index_rate": "0",
+                        "rms_mix_rate": "0",
+                        "block_time": "0.25",
+                        "crossfade_length": "0.04",
+                        "extra_time": "2",
+                        "f0method": "rmvpe",
+                    }
+                    data["pm"] = data["f0method"] == "pm"
+                    data["harvest"] = data["f0method"] == "harvest"
+                    data["crepe"] = data["f0method"] == "crepe"
+                    data["rmvpe"] = data["f0method"] == "rmvpe"
+            return data
+
+        def launcher(self):
+            data = self.load()
+            sg.theme("LightBlue3")
+            input_devices, output_devices, _, _ = self.get_devices()
+            layout = [
+                [
+                    sg.Frame(
+                        title=i18n("加载模型"),
+                        layout=[
+                            [
+                                sg.Input(
+                                    default_text=data.get("pth_path", ""),
+                                    key="pth_path",
+                                ),
+                                sg.FileBrowse(
+                                    i18n("选择.pth文件"),
+                                    initial_folder=os.path.join(
+                                        os.getcwd(), "assets/weights"
+                                    ),
+                                    file_types=((". pth"),),
+                                ),
+                            ],
+                            [
+                                sg.Input(
+                                    default_text=data.get("index_path", ""),
+                                    key="index_path",
+                                ),
+                                sg.FileBrowse(
+                                    i18n("选择.index文件"),
+                                    initial_folder=os.path.join(os.getcwd(), "logs"),
+                                    file_types=((". index"),),
+                                ),
+                            ],
+                        ],
+                    )
+                ],
+                [
+                    sg.Frame(
+                        layout=[
+                            [
+                                sg.Text(i18n("输入设备")),
+                                sg.Combo(
+                                    input_devices,
+                                    key="sg_input_device",
+                                    default_value=data.get("sg_input_device", ""),
+                                ),
+                            ],
+                            [
+                                sg.Text(i18n("输出设备")),
+                                sg.Combo(
+                                    output_devices,
+                                    key="sg_output_device",
+                                    default_value=data.get("sg_output_device", ""),
+                                ),
+                            ],
+                            [sg.Button(i18n("重载设备列表"), key="reload_devices")],
+                        ],
+                        title=i18n("音频设备(请使用同种类驱动)"),
+                    )
+                ],
+                [
+                    sg.Frame(
+                        layout=[
+                            [
+                                sg.Text(i18n("响应阈值")),
+                                sg.Slider(
+                                    range=(-60, 0),
+                                    key="threhold",
+                                    resolution=1,
+                                    orientation="h",
+                                    default_value=data.get("threhold", "-60"),
+                                    enable_events=True,
+                                ),
+                            ],
+                            [
+                                sg.Text(i18n("音调设置")),
+                                sg.Slider(
+                                    range=(-24, 24),
+                                    key="pitch",
+                                    resolution=1,
+                                    orientation="h",
+                                    default_value=data.get("pitch", "0"),
+                                    enable_events=True,
+                                ),
+                            ],
+                            [
+                                sg.Text(i18n("Index Rate")),
+                                sg.Slider(
+                                    range=(0.0, 1.0),
+                                    key="index_rate",
+                                    resolution=0.01,
+                                    orientation="h",
+                                    default_value=data.get("index_rate", "0"),
+                                    enable_events=True,
+                                ),
+                            ],
+                            [
+                                sg.Text(i18n("响度因子")),
+                                sg.Slider(
+                                    range=(0.0, 1.0),
+                                    key="rms_mix_rate",
+                                    resolution=0.01,
+                                    orientation="h",
+                                    default_value=data.get("rms_mix_rate", "0"),
+                                    enable_events=True,
+                                ),
+                            ],
+                            [
+                                sg.Text(i18n("音高算法")),
+                                sg.Radio(
+                                    "pm",
+                                    "f0method",
+                                    key="pm",
+                                    default=data.get("pm", "") == True,
+                                    enable_events=True,
+                                ),
+                                sg.Radio(
+                                    "harvest",
+                                    "f0method",
+                                    key="harvest",
+                                    default=data.get("harvest", "") == True,
+                                    enable_events=True,
+                                ),
+                                sg.Radio(
+                                    "crepe",
+                                    "f0method",
+                                    key="crepe",
+                                    default=data.get("crepe", "") == True,
+                                    enable_events=True,
+                                ),
+                                sg.Radio(
+                                    "rmvpe",
+                                    "f0method",
+                                    key="rmvpe",
+                                    default=data.get("rmvpe", "") == True,
+                                    enable_events=True,
+                                ),
+                            ],
+                        ],
+                        title=i18n("常规设置"),
+                    ),
+                    sg.Frame(
+                        layout=[
+                            [
+                                sg.Text(i18n("采样长度")),
+                                sg.Slider(
+                                    range=(0.05, 2.4),
+                                    key="block_time",
+                                    resolution=0.01,
+                                    orientation="h",
+                                    default_value=data.get("block_time", "0.25"),
+                                    enable_events=True,
+                                ),
+                            ],
+                            [
+                                sg.Text(i18n("harvest进程数")),
+                                sg.Slider(
+                                    range=(1, n_cpu),
+                                    key="n_cpu",
+                                    resolution=1,
+                                    orientation="h",
+                                    default_value=data.get(
+                                        "n_cpu", min(self.config.n_cpu, n_cpu)
+                                    ),
+                                    enable_events=True,
+                                ),
+                            ],
+                            [
+                                sg.Text(i18n("淡入淡出长度")),
+                                sg.Slider(
+                                    range=(0.01, 0.15),
+                                    key="crossfade_length",
+                                    resolution=0.01,
+                                    orientation="h",
+                                    default_value=data.get("crossfade_length", "0.04"),
+                                    enable_events=True,
+                                ),
+                            ],
+                            [
+                                sg.Text(i18n("额外推理时长")),
+                                sg.Slider(
+                                    range=(0.05, 5.00),
+                                    key="extra_time",
+                                    resolution=0.01,
+                                    orientation="h",
+                                    default_value=data.get("extra_time", "2.0"),
+                                    enable_events=True,
+                                ),
+                            ],
+                            [
+                                sg.Checkbox(
+                                    i18n("输入降噪"),
+                                    key="I_noise_reduce",
+                                    enable_events=True,
+                                ),
+                                sg.Checkbox(
+                                    i18n("输出降噪"),
+                                    key="O_noise_reduce",
+                                    enable_events=True,
+                                ),
+                            ],
+                        ],
+                        title=i18n("性能设置"),
+                    ),
+                ],
+                [
+                    sg.Button(i18n("开始音频转换"), key="start_vc"),
+                    sg.Button(i18n("停止音频转换"), key="stop_vc"),
+                    sg.Text(i18n("推理时间(ms):")),
+                    sg.Text("0", key="infer_time"),
+                ],
+            ]
+            self.window = sg.Window("RVC - GUI", layout=layout, finalize=True)
+            self.event_handler()
+
+        def event_handler(self):
+            while True:
+                event, values = self.window.read()
+                if event == sg.WINDOW_CLOSED:
+                    self.flag_vc = False
+                    exit()
+                if event == "reload_devices":
+                    prev_input = self.window["sg_input_device"].get()
+                    prev_output = self.window["sg_output_device"].get()
+                    input_devices, output_devices, _, _ = self.get_devices(update=True)
+                    if prev_input not in input_devices:
+                        self.config.sg_input_device = input_devices[0]
+                    else:
+                        self.config.sg_input_device = prev_input
+                    self.window["sg_input_device"].Update(values=input_devices)
+                    self.window["sg_input_device"].Update(
+                        value=self.config.sg_input_device
+                    )
+                    if prev_output not in output_devices:
+                        self.config.sg_output_device = output_devices[0]
+                    else:
+                        self.config.sg_output_device = prev_output
+                    self.window["sg_output_device"].Update(values=output_devices)
+                    self.window["sg_output_device"].Update(
+                        value=self.config.sg_output_device
+                    )
+                if event == "start_vc" and self.flag_vc == False:
+                    if self.set_values(values) == True:
+                        logger.info("Use CUDA: %s", torch.cuda.is_available())
+                        self.start_vc()
+                        settings = {
+                            "pth_path": values["pth_path"],
+                            "index_path": values["index_path"],
+                            "sg_input_device": values["sg_input_device"],
+                            "sg_output_device": values["sg_output_device"],
+                            "threhold": values["threhold"],
+                            "pitch": values["pitch"],
+                            "rms_mix_rate": values["rms_mix_rate"],
+                            "index_rate": values["index_rate"],
+                            "block_time": values["block_time"],
+                            "crossfade_length": values["crossfade_length"],
+                            "extra_time": values["extra_time"],
+                            "n_cpu": values["n_cpu"],
+                            "f0method": ["pm", "harvest", "crepe", "rmvpe"][
+                                [
+                                    values["pm"],
+                                    values["harvest"],
+                                    values["crepe"],
+                                    values["rmvpe"],
+                                ].index(True)
+                            ],
+                        }
+                        with open("configs/config.json", "w") as j:
+                            json.dump(settings, j)
+                if event == "stop_vc" and self.flag_vc == True:
+                    self.flag_vc = False
+
+                # Parameter hot update
+                if event == "threhold":
+                    self.config.threhold = values["threhold"]
+                elif event == "pitch":
+                    self.config.pitch = values["pitch"]
+                    if hasattr(self, "rvc"):
+                        self.rvc.change_key(values["pitch"])
+                elif event == "index_rate":
+                    self.config.index_rate = values["index_rate"]
+                    if hasattr(self, "rvc"):
+                        self.rvc.change_index_rate(values["index_rate"])
+                elif event == "rms_mix_rate":
+                    self.config.rms_mix_rate = values["rms_mix_rate"]
+                elif event in ["pm", "harvest", "crepe", "rmvpe"]:
+                    self.config.f0method = event
+                elif event == "I_noise_reduce":
+                    self.config.I_noise_reduce = values["I_noise_reduce"]
+                elif event == "O_noise_reduce":
+                    self.config.O_noise_reduce = values["O_noise_reduce"]
+                elif event != "start_vc" and self.flag_vc == True:
+                    # Other parameters do not support hot update
+                    self.flag_vc = False
+
+        def set_values(self, values):
+            if len(values["pth_path"].strip()) == 0:
+                sg.popup(i18n("请选择pth文件"))
+                return False
+            if len(values["index_path"].strip()) == 0:
+                sg.popup(i18n("请选择index文件"))
+                return False
+            pattern = re.compile("[^\x00-\x7F]+")
+            if pattern.findall(values["pth_path"]):
+                sg.popup(i18n("pth文件路径不可包含中文"))
+                return False
+            if pattern.findall(values["index_path"]):
+                sg.popup(i18n("index文件路径不可包含中文"))
+                return False
+            self.set_devices(values["sg_input_device"], values["sg_output_device"])
+            self.config.pth_path = values["pth_path"]
+            self.config.index_path = values["index_path"]
+            self.config.threhold = values["threhold"]
+            self.config.pitch = values["pitch"]
+            self.config.block_time = values["block_time"]
+            self.config.crossfade_time = values["crossfade_length"]
+            self.config.extra_time = values["extra_time"]
+            self.config.I_noise_reduce = values["I_noise_reduce"]
+            self.config.O_noise_reduce = values["O_noise_reduce"]
+            self.config.rms_mix_rate = values["rms_mix_rate"]
+            self.config.index_rate = values["index_rate"]
+            self.config.n_cpu = values["n_cpu"]
+            self.config.f0method = ["pm", "harvest", "crepe", "rmvpe"][
+                [
+                    values["pm"],
+                    values["harvest"],
+                    values["crepe"],
+                    values["rmvpe"],
+                ].index(True)
+            ]
+            return True
+
+        def start_vc(self):
+            torch.cuda.empty_cache()
+            self.flag_vc = True
+            self.rvc = rvc_for_realtime.RVC(
+                self.config.pitch,
+                self.config.pth_path,
+                self.config.index_path,
+                self.config.index_rate,
+                self.config.n_cpu,
+                inp_q,
+                opt_q,
+                device,
+                self.rvc if hasattr(self, "rvc") else None
+            )
+            self.config.samplerate = self.rvc.tgt_sr
+            self.zc = self.rvc.tgt_sr // 100
+            self.block_frame = int(np.round(self.config.block_time * self.config.samplerate / self.zc)) * self.zc
+            self.block_frame_16k = 160 * self.block_frame // self.zc
+            self.crossfade_frame = int(np.round(self.config.crossfade_time * self.config.samplerate / self.zc)) * self.zc
+            self.sola_search_frame = self.zc
+            self.extra_frame = int(np.round(self.config.extra_time * self.config.samplerate / self.zc)) * self.zc
+            self.input_wav: torch.Tensor = torch.zeros(
+                self.extra_frame
+                + self.crossfade_frame
+                + self.sola_search_frame
+                + self.block_frame,
+                device=device,
+                dtype=torch.float32,
+            )
+            self.input_wav_res: torch.Tensor= torch.zeros(160 * self.input_wav.shape[0] // self.zc, device=device,dtype=torch.float32)
+            self.pitch: np.ndarray = np.zeros(
+                self.input_wav.shape[0] // self.zc,
+                dtype="int32",
+            )
+            self.pitchf: np.ndarray = np.zeros(
+                self.input_wav.shape[0] // self.zc,
+                dtype="float64",
+            )
+            self.sola_buffer: torch.Tensor = torch.zeros(
+                self.crossfade_frame, device=device, dtype=torch.float32
+            )
+            self.nr_buffer: torch.Tensor = self.sola_buffer.clone()
+            self.output_buffer: torch.Tensor = self.input_wav.clone()
+            self.res_buffer: torch.Tensor = torch.zeros(2 * self.zc, device=device,dtype=torch.float32)
+            self.valid_rate = 1 - (self.extra_frame - 1) / self.input_wav.shape[0]
+            self.fade_in_window: torch.Tensor = (
+                torch.sin(
+                    0.5
+                    * np.pi
+                    * torch.linspace(
+                        0.0,
+                        1.0,
+                        steps=self.crossfade_frame,
+                        device=device,
+                        dtype=torch.float32,
+                    )
+                )
+                ** 2
+            )
+            self.fade_out_window: torch.Tensor = 1 - self.fade_in_window
+            self.resampler = tat.Resample(
+                orig_freq=self.config.samplerate, new_freq=16000, dtype=torch.float32
+            ).to(device)
+            self.tg = TorchGate(sr=self.config.samplerate, n_fft=4*self.zc, prop_decrease=0.9).to(device)
+            thread_vc = threading.Thread(target=self.soundinput)
+            thread_vc.start()
+
+        def soundinput(self):
+            """
+            接受音频输入
+            """
+            channels = 1 if sys.platform == "darwin" else 2
+            with sd.Stream(
+                channels=channels,
+                callback=self.audio_callback,
+                blocksize=self.block_frame,
+                samplerate=self.config.samplerate,
+                dtype="float32",
+            ):
+                while self.flag_vc:
+                    time.sleep(self.config.block_time)
+                    logger.debug("Audio block passed.")
+            logger.debug("ENDing VC")
+
+        def audio_callback(
+            self, indata: np.ndarray, outdata: np.ndarray, frames, times, status
+        ):
+            """
+            音频处理
+            """
+            start_time = time.perf_counter()
+            indata = librosa.to_mono(indata.T)
+            if self.config.threhold > -60:
+                rms = librosa.feature.rms(
+                y=indata, frame_length=4*self.zc, hop_length=self.zc
+                )
+                db_threhold = (
+                    librosa.amplitude_to_db(rms, ref=1.0)[0] < self.config.threhold
+                )
+                for i in range(db_threhold.shape[0]):
+                    if db_threhold[i]:
+                        indata[i * self.zc : (i + 1) * self.zc] = 0
+            self.input_wav[: -self.block_frame] = self.input_wav[self.block_frame :].clone()
+            self.input_wav[-self.block_frame: ] = torch.from_numpy(indata).to(device)
+            self.input_wav_res[ : -self.block_frame_16k] = self.input_wav_res[self.block_frame_16k :].clone()
+            # input noise reduction and resampling
+            if self.config.I_noise_reduce:
+                input_wav = self.input_wav[-self.crossfade_frame -self.block_frame-2*self.zc: ]
+                input_wav = self.tg(input_wav.unsqueeze(0), self.input_wav.unsqueeze(0))[0, 2*self.zc:]
+                input_wav[: self.crossfade_frame] *= self.fade_in_window
+                input_wav[: self.crossfade_frame] += self.nr_buffer * self.fade_out_window
+                self.nr_buffer[:] = input_wav[-self.crossfade_frame: ]
+                input_wav = torch.cat((self.res_buffer[:], input_wav[: self.block_frame]))
+                self.res_buffer[:] = input_wav[-2*self.zc: ]
+                self.input_wav_res[-self.block_frame_16k-160: ] = self.resampler(input_wav)[160: ]
+            else:
+                self.input_wav_res[-self.block_frame_16k-160: ] = self.resampler(self.input_wav[-self.block_frame-2*self.zc: ])[160: ]
+            # infer
+            f0_extractor_frame = self.block_frame_16k + 800
+            if self.config.f0method == 'rmvpe':
+                f0_extractor_frame = 5120 * ((f0_extractor_frame - 1) // 5120 + 1)
+            infer_wav = self.rvc.infer(
+                self.input_wav_res,
+                self.input_wav_res[-f0_extractor_frame :].cpu().numpy(),
+                self.block_frame_16k,
+                self.valid_rate,
+                self.pitch,
+                self.pitchf,
+                self.config.f0method,
+            )
+            infer_wav = infer_wav[
+                -self.crossfade_frame - self.sola_search_frame - self.block_frame :
+            ]
+            # output noise reduction
+            if self.config.O_noise_reduce:
+                self.output_buffer[: -self.block_frame] = self.output_buffer[self.block_frame :].clone()
+                self.output_buffer[-self.block_frame: ] = infer_wav[-self.block_frame:]
+                infer_wav = self.tg(infer_wav.unsqueeze(0), self.output_buffer.unsqueeze(0)).squeeze(0)
+            # volume envelop mixing
+            if self.config.rms_mix_rate < 1:
+                rms1 = librosa.feature.rms(
+                y=self.input_wav_res[-160*infer_wav.shape[0]//self.zc :].cpu().numpy(), 
+                frame_length=640, 
+                hop_length=160,
+                )
+                rms1 = torch.from_numpy(rms1).to(device)
+                rms1 = F.interpolate(
+                    rms1.unsqueeze(0), size=infer_wav.shape[0] + 1, mode="linear",align_corners=True,
+                )[0,0,:-1]
+                rms2 = librosa.feature.rms(
+                y=infer_wav[:].cpu().numpy(), frame_length=4*self.zc, hop_length=self.zc
+                )
+                rms2 = torch.from_numpy(rms2).to(device)
+                rms2 = F.interpolate(
+                    rms2.unsqueeze(0), size=infer_wav.shape[0] + 1, mode="linear",align_corners=True,
+                )[0,0,:-1]
+                rms2 = torch.max(rms2, torch.zeros_like(rms2) + 1e-3)
+                infer_wav *= torch.pow(rms1 / rms2, torch.tensor(1 - self.config.rms_mix_rate))
+            # SOLA algorithm from https://github.com/yxlllc/DDSP-SVC
+            conv_input = infer_wav[None, None, : self.crossfade_frame + self.sola_search_frame]
+            cor_nom = F.conv1d(conv_input, self.sola_buffer[None, None, :])
+            cor_den = torch.sqrt(
+                F.conv1d(conv_input ** 2, torch.ones(1, 1, self.crossfade_frame, device=device)) + 1e-8)
+            if sys.platform == "darwin":
+                _, sola_offset = torch.max(cor_nom[0, 0] / cor_den[0, 0])
+                sola_offset = sola_offset.item()
+            else:
+                sola_offset = torch.argmax(cor_nom[0, 0] / cor_den[0, 0])
+            logger.debug("sola_offset = %d", int(sola_offset))
+            infer_wav = infer_wav[sola_offset: sola_offset + self.block_frame + self.crossfade_frame]
+            infer_wav[: self.crossfade_frame] *= self.fade_in_window
+            infer_wav[: self.crossfade_frame] += self.sola_buffer *self.fade_out_window
+            self.sola_buffer[:] = infer_wav[-self.crossfade_frame:]
+            if sys.platform == "darwin":
+                outdata[:] = infer_wav[:-self.crossfade_frame].cpu().numpy()[:, np.newaxis]
+            else:
+                outdata[:] = infer_wav[:-self.crossfade_frame].repeat(2, 1).t().cpu().numpy()
+            total_time = time.perf_counter() - start_time
+            self.window["infer_time"].update(int(total_time * 1000))
+            logger.info("Infer time: %.2f", total_time)
+
+        def get_devices(self, update: bool = True):
+            """获取设备列表"""
+            if update:
+                sd._terminate()
+                sd._initialize()
+            devices = sd.query_devices()
+            hostapis = sd.query_hostapis()
+            for hostapi in hostapis:
+                for device_idx in hostapi["devices"]:
+                    devices[device_idx]["hostapi_name"] = hostapi["name"]
+            input_devices = [
+                f"{d['name']} ({d['hostapi_name']})"
+                for d in devices
+                if d["max_input_channels"] > 0
+            ]
+            output_devices = [
+                f"{d['name']} ({d['hostapi_name']})"
+                for d in devices
+                if d["max_output_channels"] > 0
+            ]
+            input_devices_indices = [
+                d["index"] if "index" in d else d["name"]
+                for d in devices
+                if d["max_input_channels"] > 0
+            ]
+            output_devices_indices = [
+                d["index"] if "index" in d else d["name"]
+                for d in devices
+                if d["max_output_channels"] > 0
+            ]
+            return (
+                input_devices,
+                output_devices,
+                input_devices_indices,
+                output_devices_indices,
+            )
+
+        def set_devices(self, input_device, output_device):
+            """设置输出设备"""
+            (
+                input_devices,
+                output_devices,
+                input_device_indices,
+                output_device_indices,
+            ) = self.get_devices()
+            sd.default.device[0] = input_device_indices[
+                input_devices.index(input_device)
+            ]
+            sd.default.device[1] = output_device_indices[
+                output_devices.index(output_device)
+            ]
+            logger.info(
+                "Input device: %s:%s", str(sd.default.device[0]), input_device
+            )
+            logger.info(
+                "Output device: %s:%s", str(sd.default.device[1]), output_device
+            )
+
+    gui = GUI()
\ No newline at end of file
diff --git a/guidml.py b/guidml.py
new file mode 100644
index 0000000000000000000000000000000000000000..aa35e9f8e3386bfec61fc9ad6f807b458ab35882
--- /dev/null
+++ b/guidml.py
@@ -0,0 +1,710 @@
+"""
+0416后的更新：
+    引入config中half
+    重建npy而不用填写
+    v2支持
+    无f0模型支持
+    修复
+
+    int16：
+    增加无索引支持
+    f0算法改harvest(怎么看就只有这个会影响CPU占用)，但是不这么改效果不好
+"""
+import os, sys, traceback, re
+
+import json
+
+now_dir = os.getcwd()
+sys.path.append(now_dir)
+from configs.config import Config
+
+Config = Config()
+
+import torch_directml
+import PySimpleGUI as sg
+import sounddevice as sd
+import noisereduce as nr
+import numpy as np
+from fairseq import checkpoint_utils
+import librosa, torch, pyworld, faiss, time, threading
+import torch.nn.functional as F
+import torchaudio.transforms as tat
+import scipy.signal as signal
+
+
+# import matplotlib.pyplot as plt
+from lib.infer_pack.models import (
+    SynthesizerTrnMs256NSFsid,
+    SynthesizerTrnMs256NSFsid_nono,
+    SynthesizerTrnMs768NSFsid,
+    SynthesizerTrnMs768NSFsid_nono,
+)
+from i18n import I18nAuto
+
+i18n = I18nAuto()
+device = torch_directml.device(torch_directml.default_device())
+current_dir = os.getcwd()
+
+
+class RVC:
+    def __init__(
+        self, key, hubert_path, pth_path, index_path, npy_path, index_rate
+    ) -> None:
+        """
+        初始化
+        """
+        try:
+            self.f0_up_key = key
+            self.time_step = 160 / 16000 * 1000
+            self.f0_min = 50
+            self.f0_max = 1100
+            self.f0_mel_min = 1127 * np.log(1 + self.f0_min / 700)
+            self.f0_mel_max = 1127 * np.log(1 + self.f0_max / 700)
+            self.sr = 16000
+            self.window = 160
+            if index_rate != 0:
+                self.index = faiss.read_index(index_path)
+                # self.big_npy = np.load(npy_path)
+                self.big_npy = self.index.reconstruct_n(0, self.index.ntotal)
+                print("index search enabled")
+            self.index_rate = index_rate
+            model_path = hubert_path
+            print("load model(s) from {}".format(model_path))
+            models, saved_cfg, task = checkpoint_utils.load_model_ensemble_and_task(
+                [model_path],
+                suffix="",
+            )
+            self.model = models[0]
+            self.model = self.model.to(device)
+            if Config.is_half:
+                self.model = self.model.half()
+            else:
+                self.model = self.model.float()
+            self.model.eval()
+            cpt = torch.load(pth_path, map_location="cpu")
+            self.tgt_sr = cpt["config"][-1]
+            cpt["config"][-3] = cpt["weight"]["emb_g.weight"].shape[0]  # n_spk
+            self.if_f0 = cpt.get("f0", 1)
+            self.version = cpt.get("version", "v1")
+            if self.version == "v1":
+                if self.if_f0 == 1:
+                    self.net_g = SynthesizerTrnMs256NSFsid(
+                        *cpt["config"], is_half=Config.is_half
+                    )
+                else:
+                    self.net_g = SynthesizerTrnMs256NSFsid_nono(*cpt["config"])
+            elif self.version == "v2":
+                if self.if_f0 == 1:
+                    self.net_g = SynthesizerTrnMs768NSFsid(
+                        *cpt["config"], is_half=Config.is_half
+                    )
+                else:
+                    self.net_g = SynthesizerTrnMs768NSFsid_nono(*cpt["config"])
+            del self.net_g.enc_q
+            print(self.net_g.load_state_dict(cpt["weight"], strict=False))
+            self.net_g.eval().to(device)
+            if Config.is_half:
+                self.net_g = self.net_g.half()
+            else:
+                self.net_g = self.net_g.float()
+        except:
+            print(traceback.format_exc())
+
+    def get_f0(self, x, f0_up_key, inp_f0=None):
+        x_pad = 1
+        f0_min = 50
+        f0_max = 1100
+        f0_mel_min = 1127 * np.log(1 + f0_min / 700)
+        f0_mel_max = 1127 * np.log(1 + f0_max / 700)
+        f0, t = pyworld.harvest(
+            x.astype(np.double),
+            fs=self.sr,
+            f0_ceil=f0_max,
+            f0_floor=f0_min,
+            frame_period=10,
+        )
+        f0 = pyworld.stonemask(x.astype(np.double), f0, t, self.sr)
+        f0 = signal.medfilt(f0, 3)
+        f0 *= pow(2, f0_up_key / 12)
+        # with open("test.txt","w")as f:f.write("\n".join([str(i)for i in f0.tolist()]))
+        tf0 = self.sr // self.window  # 每秒f0点数
+        if inp_f0 is not None:
+            delta_t = np.round(
+                (inp_f0[:, 0].max() - inp_f0[:, 0].min()) * tf0 + 1
+            ).astype("int16")
+            replace_f0 = np.interp(
+                list(range(delta_t)), inp_f0[:, 0] * 100, inp_f0[:, 1]
+            )
+            shape = f0[x_pad * tf0 : x_pad * tf0 + len(replace_f0)].shape[0]
+            f0[x_pad * tf0 : x_pad * tf0 + len(replace_f0)] = replace_f0[:shape]
+        # with open("test_opt.txt","w")as f:f.write("\n".join([str(i)for i in f0.tolist()]))
+        f0bak = f0.copy()
+        f0_mel = 1127 * np.log(1 + f0 / 700)
+        f0_mel[f0_mel > 0] = (f0_mel[f0_mel > 0] - f0_mel_min) * 254 / (
+            f0_mel_max - f0_mel_min
+        ) + 1
+        f0_mel[f0_mel <= 1] = 1
+        f0_mel[f0_mel > 255] = 255
+        f0_coarse = np.rint(f0_mel).astype(np.int)
+        return f0_coarse, f0bak  # 1-0
+
+    def infer(self, feats: torch.Tensor) -> np.ndarray:
+        """
+        推理函数
+        """
+        audio = feats.clone().cpu().numpy()
+        assert feats.dim() == 1, feats.dim()
+        feats = feats.view(1, -1)
+        padding_mask = torch.BoolTensor(feats.shape).fill_(False)
+        if Config.is_half:
+            feats = feats.half()
+        else:
+            feats = feats.float()
+        inputs = {
+            "source": feats.to(device),
+            "padding_mask": padding_mask.to(device),
+            "output_layer": 9 if self.version == "v1" else 12,
+        }
+        torch.cuda.synchronize()
+        with torch.no_grad():
+            logits = self.model.extract_features(**inputs)
+            feats = (
+                self.model.final_proj(logits[0]) if self.version == "v1" else logits[0]
+            )
+
+        ####索引优化
+        try:
+            if (
+                hasattr(self, "index")
+                and hasattr(self, "big_npy")
+                and self.index_rate != 0
+            ):
+                npy = feats[0].cpu().numpy().astype("float32")
+                score, ix = self.index.search(npy, k=8)
+                weight = np.square(1 / score)
+                weight /= weight.sum(axis=1, keepdims=True)
+                npy = np.sum(self.big_npy[ix] * np.expand_dims(weight, axis=2), axis=1)
+                if Config.is_half:
+                    npy = npy.astype("float16")
+                feats = (
+                    torch.from_numpy(npy).unsqueeze(0).to(device) * self.index_rate
+                    + (1 - self.index_rate) * feats
+                )
+            else:
+                print("index search FAIL or disabled")
+        except:
+            traceback.print_exc()
+            print("index search FAIL")
+        feats = F.interpolate(feats.permute(0, 2, 1), scale_factor=2).permute(0, 2, 1)
+        torch.cuda.synchronize()
+        print(feats.shape)
+        if self.if_f0 == 1:
+            pitch, pitchf = self.get_f0(audio, self.f0_up_key)
+            p_len = min(feats.shape[1], 13000, pitch.shape[0])  # 太大了爆显存
+        else:
+            pitch, pitchf = None, None
+            p_len = min(feats.shape[1], 13000)  # 太大了爆显存
+        torch.cuda.synchronize()
+        # print(feats.shape,pitch.shape)
+        feats = feats[:, :p_len, :]
+        if self.if_f0 == 1:
+            pitch = pitch[:p_len]
+            pitchf = pitchf[:p_len]
+            pitch = torch.LongTensor(pitch).unsqueeze(0).to(device)
+            pitchf = torch.FloatTensor(pitchf).unsqueeze(0).to(device)
+        p_len = torch.LongTensor([p_len]).to(device)
+        ii = 0  # sid
+        sid = torch.LongTensor([ii]).to(device)
+        with torch.no_grad():
+            if self.if_f0 == 1:
+                infered_audio = (
+                    self.net_g.infer(feats, p_len, pitch, pitchf, sid)[0][0, 0]
+                    .data.cpu()
+                    .float()
+                )
+            else:
+                infered_audio = (
+                    self.net_g.infer(feats, p_len, sid)[0][0, 0].data.cpu().float()
+                )
+        torch.cuda.synchronize()
+        return infered_audio
+
+
+class GUIConfig:
+    def __init__(self) -> None:
+        self.hubert_path: str = ""
+        self.pth_path: str = ""
+        self.index_path: str = ""
+        self.npy_path: str = ""
+        self.pitch: int = 12
+        self.samplerate: int = 44100
+        self.block_time: float = 1.0  # s
+        self.buffer_num: int = 1
+        self.threhold: int = -30
+        self.crossfade_time: float = 0.08
+        self.extra_time: float = 0.04
+        self.I_noise_reduce = False
+        self.O_noise_reduce = False
+        self.index_rate = 0.3
+
+
+class GUI:
+    def __init__(self) -> None:
+        self.config = GUIConfig()
+        self.flag_vc = False
+
+        self.launcher()
+
+    def load(self):
+        (
+            input_devices,
+            output_devices,
+            input_devices_indices,
+            output_devices_indices,
+        ) = self.get_devices()
+        try:
+            with open("values1.json", "r") as j:
+                data = json.load(j)
+        except:
+            with open("values1.json", "w") as j:
+                data = {
+                    "pth_path": "",
+                    "index_path": "",
+                    "sg_input_device": input_devices[
+                        input_devices_indices.index(sd.default.device[0])
+                    ],
+                    "sg_output_device": output_devices[
+                        output_devices_indices.index(sd.default.device[1])
+                    ],
+                    "threhold": "-45",
+                    "pitch": "0",
+                    "index_rate": "0",
+                    "block_time": "1",
+                    "crossfade_length": "0.04",
+                    "extra_time": "1",
+                }
+        return data
+
+    def launcher(self):
+        data = self.load()
+        sg.theme("LightBlue3")
+        input_devices, output_devices, _, _ = self.get_devices()
+        layout = [
+            [
+                sg.Frame(
+                    title=i18n("Load model"),
+                    layout=[
+                        [
+                            sg.Input(
+                                default_text="hubert_base.pt",
+                                key="hubert_path",
+                                disabled=True,
+                            ),
+                            sg.FileBrowse(
+                                i18n("Hubert Model"),
+                                initial_folder=os.path.join(os.getcwd()),
+                                file_types=(("pt files", "*.pt"),),
+                            ),
+                        ],
+                        [
+                            sg.Input(
+                                default_text=data.get("pth_path", ""),
+                                key="pth_path",
+                            ),
+                            sg.FileBrowse(
+                                i18n("Select the .pth file"),
+                                initial_folder=os.path.join(os.getcwd(), "weights"),
+                                file_types=(("weight files", "*.pth"),),
+                            ),
+                        ],
+                        [
+                            sg.Input(
+                                default_text=data.get("index_path", ""),
+                                key="index_path",
+                            ),
+                            sg.FileBrowse(
+                                i18n("Select the .index file"),
+                                initial_folder=os.path.join(os.getcwd(), "logs"),
+                                file_types=(("index files", "*.index"),),
+                            ),
+                        ],
+                        [
+                            sg.Input(
+                                default_text="你不需要填写这个You don't need write this.",
+                                key="npy_path",
+                                disabled=True,
+                            ),
+                            sg.FileBrowse(
+                                i18n("Select the .npy file"),
+                                initial_folder=os.path.join(os.getcwd(), "logs"),
+                                file_types=(("feature files", "*.npy"),),
+                            ),
+                        ],
+                    ],
+                )
+            ],
+            [
+                sg.Frame(
+                    layout=[
+                        [
+                            sg.Text(i18n("Input device")),
+                            sg.Combo(
+                                input_devices,
+                                key="sg_input_device",
+                                default_value=data.get("sg_input_device", ""),
+                            ),
+                        ],
+                        [
+                            sg.Text(i18n("Output device")),
+                            sg.Combo(
+                                output_devices,
+                                key="sg_output_device",
+                                default_value=data.get("sg_output_device", ""),
+                            ),
+                        ],
+                    ],
+                    title=i18n("Audio device (please use the same type of driver)"),
+                )
+            ],
+            [
+                sg.Frame(
+                    layout=[
+                        [
+                            sg.Text(i18n("Response threshold")),
+                            sg.Slider(
+                                range=(-60, 0),
+                                key="threhold",
+                                resolution=1,
+                                orientation="h",
+                                default_value=data.get("threhold", ""),
+                            ),
+                        ],
+                        [
+                            sg.Text(i18n("Pitch settings")),
+                            sg.Slider(
+                                range=(-24, 24),
+                                key="pitch",
+                                resolution=1,
+                                orientation="h",
+                                default_value=data.get("pitch", ""),
+                            ),
+                        ],
+                        [
+                            sg.Text(i18n("Index Rate")),
+                            sg.Slider(
+                                range=(0.0, 1.0),
+                                key="index_rate",
+                                resolution=0.01,
+                                orientation="h",
+                                default_value=data.get("index_rate", ""),
+                            ),
+                        ],
+                    ],
+                    title=i18n("General settings"),
+                ),
+                sg.Frame(
+                    layout=[
+                        [
+                            sg.Text(i18n("Sample length")),
+                            sg.Slider(
+                                range=(0.1, 3.0),
+                                key="block_time",
+                                resolution=0.1,
+                                orientation="h",
+                                default_value=data.get("block_time", ""),
+                            ),
+                        ],
+                        [
+                            sg.Text(i18n("Fade length")),
+                            sg.Slider(
+                                range=(0.01, 0.15),
+                                key="crossfade_length",
+                                resolution=0.01,
+                                orientation="h",
+                                default_value=data.get("crossfade_length", ""),
+                            ),
+                        ],
+                        [
+                            sg.Text(i18n("Extra推理时长")),
+                            sg.Slider(
+                                range=(0.05, 3.00),
+                                key="extra_time",
+                                resolution=0.01,
+                                orientation="h",
+                                default_value=data.get("extra_time", ""),
+                            ),
+                        ],
+                        [
+                            sg.Checkbox(i18n("Input noise reduction"), key="I_noise_reduce"),
+                            sg.Checkbox(i18n("Output noise reduction"), key="O_noise_reduce"),
+                        ],
+                    ],
+                    title=i18n("Performance settings"),
+                ),
+            ],
+            [
+                sg.Button(i18n("开始音频Convert"), key="start_vc"),
+                sg.Button(i18n("停止音频Convert"), key="stop_vc"),
+                sg.Text(i18n("Inference time (ms):")),
+                sg.Text("0", key="infer_time"),
+            ],
+        ]
+        self.window = sg.Window("RVC - GUI", layout=layout)
+        self.event_handler()
+
+    def event_handler(self):
+        while True:
+            event, values = self.window.read()
+            if event == sg.WINDOW_CLOSED:
+                self.flag_vc = False
+                exit()
+            if event == "start_vc" and self.flag_vc == False:
+                if self.set_values(values) == True:
+                    print("using_cuda:" + str(torch.cuda.is_available()))
+                    self.start_vc()
+                    settings = {
+                        "pth_path": values["pth_path"],
+                        "index_path": values["index_path"],
+                        "sg_input_device": values["sg_input_device"],
+                        "sg_output_device": values["sg_output_device"],
+                        "threhold": values["threhold"],
+                        "pitch": values["pitch"],
+                        "index_rate": values["index_rate"],
+                        "block_time": values["block_time"],
+                        "crossfade_length": values["crossfade_length"],
+                        "extra_time": values["extra_time"],
+                    }
+                    with open("values1.json", "w") as j:
+                        json.dump(settings, j)
+            if event == "stop_vc" and self.flag_vc == True:
+                self.flag_vc = False
+
+    def set_values(self, values):
+        if len(values["pth_path"].strip()) == 0:
+            sg.popup(i18n("Select the pth file"))
+            return False
+        if len(values["index_path"].strip()) == 0:
+            sg.popup(i18n("Select the index file"))
+            return False
+        pattern = re.compile("[^\x00-\x7F]+")
+        if pattern.findall(values["hubert_path"]):
+            sg.popup(i18n("The hubert model path must not contain Chinese characters"))
+            return False
+        if pattern.findall(values["pth_path"]):
+            sg.popup(i18n("The pth file path must not contain Chinese characters."))
+            return False
+        if pattern.findall(values["index_path"]):
+            sg.popup(i18n("The index file path must not contain Chinese characters."))
+            return False
+        self.set_devices(values["sg_input_device"], values["sg_output_device"])
+        self.config.hubert_path = os.path.join(current_dir, "hubert_base.pt")
+        self.config.pth_path = values["pth_path"]
+        self.config.index_path = values["index_path"]
+        self.config.npy_path = values["npy_path"]
+        self.config.threhold = values["threhold"]
+        self.config.pitch = values["pitch"]
+        self.config.block_time = values["block_time"]
+        self.config.crossfade_time = values["crossfade_length"]
+        self.config.extra_time = values["extra_time"]
+        self.config.I_noise_reduce = values["I_noise_reduce"]
+        self.config.O_noise_reduce = values["O_noise_reduce"]
+        self.config.index_rate = values["index_rate"]
+        return True
+
+    def start_vc(self):
+        torch.cuda.empty_cache()
+        self.flag_vc = True
+        self.block_frame = int(self.config.block_time * self.config.samplerate)
+        self.crossfade_frame = int(self.config.crossfade_time * self.config.samplerate)
+        self.sola_search_frame = int(0.012 * self.config.samplerate)
+        self.delay_frame = int(0.01 * self.config.samplerate)  # 往前预留0.02s
+        self.extra_frame = int(self.config.extra_time * self.config.samplerate)
+        self.rvc = None
+        self.rvc = RVC(
+            self.config.pitch,
+            self.config.hubert_path,
+            self.config.pth_path,
+            self.config.index_path,
+            self.config.npy_path,
+            self.config.index_rate,
+        )
+        self.input_wav: np.ndarray = np.zeros(
+            self.extra_frame
+            + self.crossfade_frame
+            + self.sola_search_frame
+            + self.block_frame,
+            dtype="float32",
+        )
+        self.output_wav: torch.Tensor = torch.zeros(
+            self.block_frame, device=device, dtype=torch.float32
+        )
+        self.sola_buffer: torch.Tensor = torch.zeros(
+            self.crossfade_frame, device=device, dtype=torch.float32
+        )
+        self.fade_in_window: torch.Tensor = torch.linspace(
+            0.0, 1.0, steps=self.crossfade_frame, device=device, dtype=torch.float32
+        )
+        self.fade_out_window: torch.Tensor = 1 - self.fade_in_window
+        self.resampler1 = tat.Resample(
+            orig_freq=self.config.samplerate, new_freq=16000, dtype=torch.float32
+        )
+        self.resampler2 = tat.Resample(
+            orig_freq=self.rvc.tgt_sr,
+            new_freq=self.config.samplerate,
+            dtype=torch.float32,
+        )
+        thread_vc = threading.Thread(target=self.soundinput)
+        thread_vc.start()
+
+    def soundinput(self):
+        """
+        接受音频输入
+        """
+        with sd.Stream(
+            channels=2,
+            callback=self.audio_callback,
+            blocksize=self.block_frame,
+            samplerate=self.config.samplerate,
+            dtype="float32",
+        ):
+            while self.flag_vc:
+                time.sleep(self.config.block_time)
+                print("Audio block passed.")
+        print("ENDing VC")
+
+    def audio_callback(
+        self, indata: np.ndarray, outdata: np.ndarray, frames, times, status
+    ):
+        """
+        音频处理
+        """
+        start_time = time.perf_counter()
+        indata = librosa.to_mono(indata.T)
+        if self.config.I_noise_reduce:
+            indata[:] = nr.reduce_noise(y=indata, sr=self.config.samplerate)
+
+        """noise gate"""
+        frame_length = 2048
+        hop_length = 1024
+        rms = librosa.feature.rms(
+            y=indata, frame_length=frame_length, hop_length=hop_length
+        )
+        db_threhold = librosa.amplitude_to_db(rms, ref=1.0)[0] < self.config.threhold
+        # print(rms.shape,db.shape,db)
+        for i in range(db_threhold.shape[0]):
+            if db_threhold[i]:
+                indata[i * hop_length : (i + 1) * hop_length] = 0
+        self.input_wav[:] = np.append(self.input_wav[self.block_frame :], indata)
+
+        # infer
+        print("input_wav:" + str(self.input_wav.shape))
+        # print('infered_wav:'+str(infer_wav.shape))
+        infer_wav: torch.Tensor = self.resampler2(
+            self.rvc.infer(self.resampler1(torch.from_numpy(self.input_wav)))
+        )[-self.crossfade_frame - self.sola_search_frame - self.block_frame :].to(
+            device
+        )
+        print("infer_wav:" + str(infer_wav.shape))
+
+        # SOLA algorithm from https://github.com/yxlllc/DDSP-SVC
+        cor_nom = F.conv1d(
+            infer_wav[None, None, : self.crossfade_frame + self.sola_search_frame],
+            self.sola_buffer[None, None, :],
+        )
+        cor_den = torch.sqrt(
+            F.conv1d(
+                infer_wav[None, None, : self.crossfade_frame + self.sola_search_frame]
+                ** 2,
+                torch.ones(1, 1, self.crossfade_frame, device=device),
+            )
+            + 1e-8
+        )
+        sola_offset = torch.argmax(cor_nom[0, 0] / cor_den[0, 0])
+        print("sola offset: " + str(int(sola_offset)))
+
+        # crossfade
+        self.output_wav[:] = infer_wav[sola_offset : sola_offset + self.block_frame]
+        self.output_wav[: self.crossfade_frame] *= self.fade_in_window
+        self.output_wav[: self.crossfade_frame] += self.sola_buffer[:]
+        if sola_offset < self.sola_search_frame:
+            self.sola_buffer[:] = (
+                infer_wav[
+                    -self.sola_search_frame
+                    - self.crossfade_frame
+                    + sola_offset : -self.sola_search_frame
+                    + sola_offset
+                ]
+                * self.fade_out_window
+            )
+        else:
+            self.sola_buffer[:] = (
+                infer_wav[-self.crossfade_frame :] * self.fade_out_window
+            )
+
+        if self.config.O_noise_reduce:
+            outdata[:] = np.tile(
+                nr.reduce_noise(
+                    y=self.output_wav[:].cpu().numpy(), sr=self.config.samplerate
+                ),
+                (2, 1),
+            ).T
+        else:
+            outdata[:] = self.output_wav[:].repeat(2, 1).t().cpu().numpy()
+        total_time = time.perf_counter() - start_time
+        self.window["infer_time"].update(int(total_time * 1000))
+        print("infer time:" + str(total_time))
+
+    def get_devices(self, update: bool = True):
+        """获取设备列表"""
+        if update:
+            sd._terminate()
+            sd._initialize()
+        devices = sd.query_devices()
+        hostapis = sd.query_hostapis()
+        for hostapi in hostapis:
+            for device_idx in hostapi["devices"]:
+                devices[device_idx]["hostapi_name"] = hostapi["name"]
+        input_devices = [
+            f"{d['name']} ({d['hostapi_name']})"
+            for d in devices
+            if d["max_input_channels"] > 0
+        ]
+        output_devices = [
+            f"{d['name']} ({d['hostapi_name']})"
+            for d in devices
+            if d["max_output_channels"] > 0
+        ]
+        input_devices_indices = [
+            d["index"] if "index" in d else d["name"]
+            for d in devices
+            if d["max_input_channels"] > 0
+        ]
+        output_devices_indices = [
+            d["index"] if "index" in d else d["name"]
+            for d in devices
+            if d["max_output_channels"] > 0
+        ]
+        return (
+            input_devices,
+            output_devices,
+            input_devices_indices,
+            output_devices_indices,
+        )
+
+    def set_devices(self, input_device, output_device):
+        """设置输出设备"""
+        (
+            input_devices,
+            output_devices,
+            input_device_indices,
+            output_device_indices,
+        ) = self.get_devices()
+        sd.default.device[0] = input_device_indices[input_devices.index(input_device)]
+        sd.default.device[1] = output_device_indices[
+            output_devices.index(output_device)
+        ]
+        print("input device:" + str(sd.default.device[0]) + ":" + str(input_device))
+        print("output device:" + str(sd.default.device[1]) + ":" + str(output_device))
+
+
+gui = GUI()
diff --git a/i18n.py b/i18n.py
new file mode 100644
index 0000000000000000000000000000000000000000..b958c6f7244c4b920e097a9a9e67e81990d03f59
--- /dev/null
+++ b/i18n.py
@@ -0,0 +1,43 @@
+import json
+
+def load_language_list(language):
+    try:
+        with open(f"./i18n/locale/{language}.json", "r", encoding="utf-8") as f:
+            return json.load(f)
+    except FileNotFoundError:
+        raise FileNotFoundError(
+            f"Failed to load language file for {language}. Check if the correct .json file exists."
+        )
+
+
+class I18nAuto:
+    """
+    A class used for internationalization using JSON language files.
+
+    Examples
+    --------
+    >>> i18n = I18nAuto('en_US')
+    >>> i18n.print()
+    Using Language: en_US
+    """
+    def __init__(self, language=None):
+        from locale import getdefaultlocale
+        language = language or getdefaultlocale()[0]
+        if not self._language_exists(language):
+            language = "en_US"
+
+        self.language_map = load_language_list(language)
+        self.language = language
+
+    @staticmethod
+    def _language_exists(language):
+        from os.path import exists
+        return exists(f"./i18n/locale/{language}.json")
+
+    def __call__(self, key):
+        """Returns the translation of the given key if it exists, else returns the key itself."""
+        return self.language_map.get(key, key)
+
+    def print(self):
+        """Prints the language currently in use."""
+        print(f"Using Language: {self.language}") 
\ No newline at end of file
diff --git a/i18n/locale/ar_AR.json b/i18n/locale/ar_AR.json
new file mode 100644
index 0000000000000000000000000000000000000000..c54cb50c0ae1b7100a96acadf93f3320113ea8f2
--- /dev/null
+++ b/i18n/locale/ar_AR.json
@@ -0,0 +1,247 @@
+{
+  "Unfortunately, there is no compatible GPU available to support your training.": "لسوء الحظ، لا تتوفر وحدة معالجة رسومات متوافقة لدعم تدريبك.",
+  "Yes": "نعم",
+  "Select your dataset:": "حدد مجموعة البيانات الخاصة بك.",
+  "Update list": "قائمة التحديث.",
+  "Download Model": "تحميل الموديل",
+  "Download Backup": "تحميل النسخ الاحتياطي",
+  "Download Dataset": "تحميل مجموعة البيانات",
+  "Download": "تحميل",
+  "Url:": "عنوان URL:",
+  "Build the index before saving.": "قم ببناء الفهرس قبل الحفظ.",
+  "Save your model once the training ends.": "احفظ النموذج الخاص بك بمجرد انتهاء التدريب.",
+  "Save type": "حفظ النوع",
+  "Save model": "حفظ النموذج",
+  "Choose the method": "اختر الطريقة",
+  "Save all": "احفظ الكل",
+  "Save D and G": "احفظ D وG",
+  "Save voice": "حفظ الصوت",
+  "Downloading the file: ": "تنزيل الملف:",
+  "Stop training": "توقف عن التدريب",
+  "Too many users have recently viewed or downloaded this file": "لقد قام عدد كبير جدًا من المستخدمين مؤخرًا بعرض هذا الملف أو تنزيله",
+  "Cannot get file from this private link": "لا يمكن الحصول على الملف من هذا الرابط الخاص",
+  "Full download": "تحميل كامل",
+  "An error occurred downloading": "حدث خطأ أثناء التنزيل",
+  "Model saved successfully": "تم حفظ النموذج بنجاح",
+  "Saving the model...": "جارٍ حفظ النموذج...",
+  "Saved without index...": "تم الحفظ بدون فهرس...",
+  "model_name": "اسم النموذج",
+  "Saved without inference model...": "تم الحفظ بدون نموذج الاستدلال...",
+  "An error occurred saving the model": "حدث خطأ أثناء حفظ النموذج",
+  "The model you want to save does not exist, be sure to enter the correct name.": "النموذج الذي تريد حفظه غير موجود، تأكد من إدخال الاسم الصحيح.",
+  "The file could not be downloaded.": "لا يمكن تحميل الملف.",
+  "Unzip error.": "خطأ في فك الضغط.",
+  "Path to your added.index file (if it didn't automatically find it)": "المسار إلى ملف add.index (إذا لم يتم العثور عليه تلقائيًا)",
+  "It has been downloaded successfully.": "لقد تم تحميله بنجاح.",
+  "Proceeding with the extraction...": "المضي قدما في عملية الاستخراج...",
+  "The Backup has been uploaded successfully.": "تم تحميل النسخة الاحتياطية بنجاح.",
+  "The Dataset has been loaded successfully.": "تم تحميل مجموعة البيانات بنجاح.",
+  "The Model has been loaded successfully.": "تم تحميل النموذج بنجاح.",
+  "It is used to download your inference models.": "يتم استخدامه لتنزيل نماذج الاستدلال الخاصة بك.",
+  "It is used to download your training backups.": "يتم استخدامه لتنزيل النسخ الاحتياطية للتدريب.",
+  "Download the dataset with the audios in a compatible format (.wav/.flac) to train your model.": "قم بتنزيل مجموعة البيانات مع التسجيلات الصوتية بتنسيق متوافق (.wav/.flac) لتدريب النموذج الخاص بك.",
+  "No relevant file was found to upload.": "لم يتم العثور على ملف ذي صلة للتحميل.",
+  "The model works for inference, and has the .index file.": "يعمل النموذج من أجل الاستدلال، ويحتوي على ملف .index.",
+  "The model works for inference, but it doesn't have the .index file.": "يعمل النموذج من أجل الاستدلال، لكنه لا يحتوي على ملف .index.",
+  "This may take a few minutes, please wait...": "قد يستغرق ذلك بضع دقائق، يرجى الانتظار...",
+  "Resources": "موارد",
+  "Step 1: Processing data": "الخطوة 1: معالجة البيانات",
+  "Step 2: Skipping pitch extraction": "الخطوة 2 أ: تخطي استخراج الملعب",
+  "Step 3: Extracting features": "الخطوة 2 ب: استخراج الميزات",
+  "Step 4: Model training started": "الخطوة 3 أ: بدأ التدريب النموذجي",
+  "Step 5: Export lowest points on a graph of the model": "الخطوة 4: تصدير أدنى النقاط على الرسم البياني للنموذج",
+  "Training is done, check train.log": "تم الانتهاء من التدريب، قم بزيارة Train.log",
+  "All processes have been completed!": "تم الانتهاء من جميع العمليات!",
+  "Model Inference": "الاستدلال النموذجي",
+  "Inferencing voice:": "الاستدلال الصوتي:",
+  "Model_Name": "اسم النموذج",
+  "Dataset_Name": "اسم مجموعة البيانات",
+  "Whether the model has pitch guidance.": "ما إذا كان النموذج يحتوي على توجيهات في الملعب.",
+  "Whether to save only the latest .ckpt file to save hard drive space": "ما إذا كان سيتم حفظ أحدث ملف .ckpt فقط لتوفير مساحة على القرص الصلب",
+  "Cache all training sets to GPU memory. Caching small datasets (less than 10 minutes) can speed up training": "قم بتخزين جميع مجموعات التدريب مؤقتًا في ذاكرة GPU. يمكن أن يؤدي تخزين مجموعات البيانات الصغيرة مؤقتًا (أقل من 10 دقائق) إلى تسريع عملية التدريب",
+  "Save a small final model to the 'weights' folder at each save point": "احفظ نموذجًا نهائيًا صغيرًا في مجلد \"الأوزان\" عند كل نقطة حفظ",
+  "Refresh": "تحديث قائمة الصوت ومسار الفهرس والملفات الصوتية",
+  "Unload voice to save GPU memory": "قم بإلغاء تحميل الصوت لحفظ ذاكرة GPU:",
+  "Select Speaker/Singer ID:": "حدد معرف المتحدث/المغني:",
+  "Recommended +12 key for male to female conversion, and -12 key for female to male conversion. If the sound range goes too far and the voice is distorted, you can also adjust it to the appropriate range by yourself.": "يوصى باستخدام مفتاح +12 للتحويل من ذكر إلى أنثى، ومفتاح -12 للتحويل من أنثى إلى ذكر. إذا تجاوز نطاق الصوت كثيرًا وكان الصوت مشوهًا، فيمكنك أيضًا ضبطه على النطاق المناسب بنفسك.",
+  "Transpose (integer, number Fof semitones, raise by an octave: 12, lower by an octave: -12):": "تبديل الموضع (عدد صحيح، عدد نصف النغمات، رفع بمقدار أوكتاف: 12، خفض بمقدار أوكتاف: -12):",
+  "Enter the path of the audio file to be processed (default is the correct format example):": "أدخل مسار الملف الصوتي المراد معالجته (الافتراضي هو مثال التنسيق الصحيح):",
+  "Select the pitch extraction algorithm:": "حدد خوارزمية استخراج الملعب:",
+  "Mangio-Crepe Hop Length (Only applies to mangio-crepe): Hop length refers to the time it takes for the speaker to jump to a dramatic pitch. Lower hop lengths take more time to infer but are more pitch accurate.": "طول قفزة المانجيو-كريب (ينطبق فقط على كريب المانجيو): يشير طول القفزة إلى الوقت الذي يستغرقه المتحدث للانتقال إلى طبقة الصوت الدرامية. يستغرق استنتاج أطوال القفزات المنخفضة وقتًا أطول ولكنها أكثر دقة في درجة الصوت.",
+  "Feature search dataset file path": "مسار ملف مجموعة بيانات البحث عن المعالم",
+  "If >=3: apply median filtering to the harvested pitch results. The value represents the filter radius and can reduce breathiness.": "إذا كان > = 3: قم بتطبيق التصفية المتوسطة على نتائج العرض التقديمي المحصودة. تمثل القيمة نصف قطر المرشح ويمكن أن تقلل من التنفس.",
+  "Path to the feature index file. Leave blank to use the selected result from the dropdown:": "المسار إلى ملف فهرس الميزات. اتركه فارغًا لاستخدام النتيجة المحددة من القائمة المنسدلة:",
+  "Auto-detect index path and select from the dropdown:": "الكشف التلقائي عن مسار الفهرس والاختيار من القائمة المنسدلة",
+  "Path to feature file:": "المسار إلى ملف الميزة:",
+  "Search feature ratio:": "نسبة ميزة البحث:",
+  "Resample the output audio in post-processing to the final sample rate. Set to 0 for no resampling:": "قم بإعادة تشكيل الصوت الناتج في مرحلة ما بعد المعالجة إلى معدل العينة النهائي. اضبط على 0 لعدم إعادة التشكيل:",
+  "Use the volume envelope of the input to replace or mix with the volume envelope of the output. The closer the ratio is to 1, the more the output envelope is used:": "استخدم مظروف حجم الإدخال لاستبدال أو مزج مظروف حجم الإخراج. كلما اقتربت النسبة من 1، زاد استخدام مظروف الإخراج:",
+  "Protect voiceless consonants and breath sounds to prevent artifacts such as tearing in electronic music. Set to 0.5 to disable. Decrease the value to increase protection, but it may reduce indexing accuracy:": "قم بحماية الحروف الساكنة وأصوات التنفس التي لا صوت لها لمنع المؤثرات مثل تمزيق الموسيقى الإلكترونية. اضبط على 0.5 للتعطيل. قم بتقليل القيمة لزيادة الحماية، ولكنه قد يقلل من دقة الفهرسة:",
+  "F0 curve file (optional). One pitch per line. Replaces the default F0 and pitch modulation:": "ملف منحنى F0 (اختياري). خطوة واحدة لكل سطر. يستبدل الإعداد الافتراضي F0 وتعديل درجة الصوت:",
+  "Convert": "يتحول",
+  "Output information:": "معلومات الإخراج",
+  "Export audio (click on the three dots in the lower right corner to download)": "تصدير الصوت (انقر على النقاط الثلاث في الزاوية اليمنى السفلية للتنزيل)",
+  "Batch conversion. Enter the folder containing the audio files to be converted or upload multiple audio files. The converted audio will be output in the specified folder (default: 'opt').": "تحويل دفعة. أدخل المجلد الذي يحتوي على الملفات الصوتية المراد تحويلها أو قم بتحميل ملفات صوتية متعددة. سيتم إخراج الصوت المحول في المجلد المحدد (الافتراضي: \"اختياري\").",
+  "Specify output folder:": "تحديد مجلد الإخراج:",
+  "Enter the path of the audio folder to be processed (copy it from the address bar of the file manager):": "أدخل مسار مجلد الصوت المراد معالجته (انسخه من شريط العناوين الخاص بمدير الملفات):",
+  "You can also input audio files in batches. Choose one of the two options. Priority is given to reading from the folder.": "يمكنك أيضًا إدخال الملفات الصوتية على دفعات. اختر أحد الخيارين. تعطى الأولوية للقراءة من المجلد.",
+  "Export file format": "تصدير تنسيق الملف",
+  "UVR5": "الأشعة فوق البنفسجية5",
+  "Enter the path of the audio folder to be processed:": "أدخل مسار مجلد الصوت المراد معالجته:",
+  "Model": "نموذج",
+  "Vocal Extraction Aggressive": "استخراج الصوتية العدوانية",
+  "Specify the output folder for vocals:": "حدد مجلد الإخراج للغناء:",
+  "Specify the output folder for accompaniment:": "حدد مجلد الإخراج للمرافقة:",
+  "Train": "يدرب",
+  "Enter the model name:": "أدخل اسم النموذج:",
+  "Target sample rate:": "معدل العينة المستهدف:",
+  "Whether the model has pitch guidance (required for singing, optional for speech):": "ما إذا كان النموذج يحتوي على إرشادات لطبقة الصوت (مطلوبة للغناء، واختيارية للكلام):",
+  "Version": "إصدار",
+  "Number of CPU processes:": "عدد عمليات وحدة المعالجة المركزية المستخدمة لاستخراج الملعب ومعالجة البيانات:",
+  "Enter the path of the training folder:": "أدخل مسار مجلد التدريب:",
+  "Specify the model ID:": "يرجى تحديد معرف النموذج:",
+  "Auto detect audio path and select from the dropdown:": "الكشف التلقائي عن مسار الصوت والاختيار من القائمة المنسدلة:",
+  "Add audio's name to the path to the audio file to be processed (default is the correct format example) Remove the path to use an audio from the dropdown list:": "أضف اسم الصوت إلى المسار إلى الملف الصوتي المراد معالجته (الافتراضي هو مثال التنسيق الصحيح) قم بإزالة المسار لاستخدام الصوت من القائمة المنسدلة:",
+  "Advanced Settings": "إعدادات متقدمة",
+  "Settings": "إعدادات",
+  "Status:": "حالة",
+  "Process data": "معالجة البيانات",
+  "Drag your audio here:": "اسحب الصوت الخاص بك هنا واضغط على زر التحديث",
+  "Or record an audio:": "أو تسجيل الصوت.",
+  "Formant shift inference audio": "تحويل صيغة الاستدلال الصوتي",
+  "Used for male to female and vice-versa conversions": "يستخدم للتحويل من ذكر إلى أنثى والعكس",
+  "Provide the GPU index(es) separated by '-', like 0-1-2 for using GPUs 0, 1, and 2:": "يرجى تقديم فهرس (فهارس) وحدة معالجة الرسومات مفصولة بـ \"-\"، مثل 0-1-2 لاستخدام وحدات معالجة الرسومات 0 و1 و2:",
+  "GPU Information:": "معلومات وحدة معالجة الرسومات",
+  "Feature extraction": "ميزة استخراج",
+  "Save frequency:": "حفظ التردد:",
+  "Training epochs:": "فترات التدريب:",
+  "Batch size per GPU:": "حجم الدفعة لكل GPU:",
+  "Save only the latest '.ckpt' file to save disk space:": "احفظ فقط أحدث ملف '.ckpt' لتوفير مساحة على القرص:",
+  "No": "لا",
+  "Save a small final model to the 'weights' folder at each save point:": "احفظ نموذجًا نهائيًا صغيرًا في مجلد \"الأوزان\" عند كل نقطة حفظ:",
+  "Load pre-trained base model G path:": "تحميل مسار G للنموذج الأساسي المُدرب مسبقًا:",
+  "Load pre-trained base model D path:": "تحميل المسار D للنموذج الأساسي المُدرب مسبقًا:",
+  "Train model": "نموذج القطار",
+  "Train feature index": "مؤشر ميزة القطار",
+  "One-click training": "التدريب بنقرة واحدة",
+  "Processing": "يعالج",
+  "Model fusion, can be used to test timbre fusion": "يمكن استخدام نموذج الاندماج لاختبار دمج الجرس",
+  "Path to Model A:": "المسار إلى النموذج أ:",
+  "Path to Model B:": "المسار إلى النموذج ب:",
+  "Weight for Model A:": "الوزن للنموذج أ:",
+  "Whether the model has pitch guidance:": "ما إذا كان النموذج يحتوي على توجيه الملعب:",
+  "Model information to be placed:": "معلومات النموذج المراد وضعها:",
+  "Model architecture version:": "نسخة البنية النموذجية:",
+  "Fusion": "انصهار",
+  "Modify model information": "تعديل معلومات النموذج",
+  "Path to Model:": "المسار إلى النموذج:",
+  "Model information to be modified:": "معلومات النموذج المراد تعديلها:",
+  "Save file name:": "حفظ اسم الملف:",
+  "Modify": "يُعدِّل",
+  "View model information": "عرض معلومات النموذج",
+  "View": "منظر",
+  "Model extraction": "استخراج النموذج (أدخل مسار نموذج الملف الكبير ضمن مجلد \"السجلات\"). يعد هذا مفيدًا إذا كنت تريد إيقاف التدريب في منتصف الطريق واستخراج ملف نموذج صغير وحفظه يدويًا، أو إذا كنت تريد اختبار نموذج متوسط:",
+  "Name:": "حفظ الاسم:",
+  "Whether the model has pitch guidance (1: yes, 0: no):": "ما إذا كان النموذج يحتوي على توجيه درجة الصوت (1: نعم، 0: لا):",
+  "Extract": "يستخرج",
+  "Export Onnx": "تصدير اونكس",
+  "RVC Model Path:": "مسار نموذج RVC:",
+  "Onnx Export Path:": "مسار تصدير Onnx:",
+  "MoeVS Model": "نموذج MoVS",
+  "Export Onnx Model": "تصدير نموذج Onnx",
+  "Load model": "نموذج التحميل",
+  "Hubert Model": "نموذج هيوبرت",
+  "Select the .pth file": "حدد ملف .pth",
+  "Select the .index file": "حدد ملف الفهرس",
+  "Select the .npy file": "حدد ملف .npy",
+  "Input device": "جهاز الإدخال",
+  "Output device": "جهاز إخراج",
+  "Audio device (please use the same type of driver)": "جهاز الصوت (يرجى استخدام نفس نوع برنامج التشغيل)",
+  "Response threshold": "عتبة الاستجابة",
+  "Pitch settings": "إعدادات الملعب",
+  "Whether to use note names instead of their hertz value. E.G. [C5, D6] instead of [523.25, 1174.66]Hz": "ما إذا كان سيتم استخدام أسماء الملاحظات بدلاً من قيمتها بالهيرتز. على سبيل المثال. [C5، D6] بدلاً من [523.25، 1174.66] هرتز",
+  "Index Rate": "معدل المؤشر",
+  "General settings": "الاعدادات العامة",
+  "Sample length": "طول العينة",
+  "Fade length": "طول التلاشي",
+  "Extra inference time": "وقت الاستدلال الإضافي",
+  "Input noise reduction": "تقليل ضوضاء الإدخال",
+  "Output noise reduction": "الحد من الضوضاء الناتج",
+  "Performance settings": "إعدادات الأداء",
+  "Start audio conversion": "ابدأ تحويل الصوت",
+  "Stop audio conversion": "إيقاف تحويل الصوت",
+  "Inference time (ms):": "وقت الاستدلال (مللي ثانية):",
+  "Select the pth file": "حدد ملف pth",
+  "Select the .index file:": "حدد ملف الفهرس",
+  "The hubert model path must not contain Chinese characters": "يجب ألا يحتوي مسار نموذج Hubert على أحرف صينية",
+  "The pth file path must not contain Chinese characters.": "يجب ألا يحتوي مسار الملف pth على أحرف صينية.",
+  "The index file path must not contain Chinese characters.": "يجب ألا يحتوي مسار ملف الفهرس على أحرف صينية.",
+  "Step algorithm": "خوارزمية الخطوة",
+  "Number of epoch processes": "عدد عمليات العصر",
+  "Lowest points export": "أدنى نقاط التصدير",
+  "How many lowest points to save:": "كم عدد أدنى النقاط للحفظ",
+  "Export lowest points of a model": "تصدير أدنى نقاط النموذج",
+  "Output models:": "نماذج الإخراج",
+  "Stats of selected models:": "إحصائيات النماذج المختارة",
+  "Custom f0 [Root pitch] File": "ملف f0 مخصص [درجة الجذر]",
+  "Min pitch:": "الملعب دقيقة",
+  "Specify minimal pitch for inference [HZ]": "تحديد الحد الأدنى من درجة الاستدلال [HZ]",
+  "Specify minimal pitch for inference [NOTE][OCTAVE]": "تحديد الحد الأدنى من درجة الصوت للاستدلال [ملاحظة] [أوكتاف]",
+  "Max pitch:": "ماكس الملعب",
+  "Specify max pitch for inference [HZ]": "تحديد أقصى درجة للاستدلال [HZ]",
+  "Specify max pitch for inference [NOTE][OCTAVE]": "تحديد أقصى درجة للاستدلال [ملاحظة] [أوكتاف]",
+  "Browse presets for formanting": "تصفح الإعدادات المسبقة للتشكيل",
+  "Presets are located in formantshiftcfg/ folder": "توجد الإعدادات المسبقة في المجلدformantshiftcfg/",
+  "Default value is 1.0": "القيمة الافتراضية هي 1.0",
+  "Quefrency for formant shifting": "التردد لتحويل الصياغة",
+  "Timbre for formant shifting": "Timbre لتحويل الصياغة",
+  "Apply": "يتقدم",
+  "Single": "أعزب",
+  "Batch": "حزمة",
+  "Separate YouTube tracks": "مسارات يوتيوب منفصلة",
+  "Download audio from a YouTube video and automatically separate the vocal and instrumental tracks": "قم بتنزيل الصوت من مقطع فيديو على YouTube وفصل المسارات الصوتية والمسارات الآلية تلقائيًا",
+  "Extra": "إضافي",
+  "Merge": "دمج",
+  "Merge your generated audios with the instrumental": "دمج الصوتيات التي تم إنشاؤها مع الآلات الموسيقية",
+  "Choose your instrumental:": "اختر آلتك الموسيقية",
+  "Choose the generated audio:": "اختر الصوت الذي تم إنشاؤه",
+  "Combine": "يجمع",
+  "Download and Separate": "تحميل وفصل",
+  "Enter the YouTube link:": "أدخل رابط اليوتيوب",
+  "This section contains some extra utilities that often may be in experimental phases": "يحتوي هذا القسم على بعض الأدوات المساعدة الإضافية التي غالبًا ما تكون في مراحل تجريبية",
+  "Merge Audios": "دمج صوتيات",
+  "Audio files have been moved to the 'audios' folder.": "تم نقل الملفات الصوتية إلى مجلد \"التسجيلات الصوتية\".",
+  "Downloading audio from the video...": "تحميل الصوت من الفيديو...",
+  "Audio downloaded!": "تحميل الصوت!",
+  "An error occurred:": "حدث خطأ:",
+  "Separating audio...": "فصل الصوت...",
+  "File moved successfully.": "تم نقل الملف بنجاح.",
+  "Finished!": "انتهى!",
+  "The source file does not exist.": "الملف المصدر غير موجود.",
+  "Error moving the file:": "خطأ في نقل الملف:",
+  "Downloading {name} from drive": "تنزيل {name} من محرك الأقراص",
+  "The attempt to download using Drive didn't work": "لم تنجح محاولة التنزيل باستخدام Drive",
+  "Error downloading the file: {str(e)}": "حدث خطأ أثناء تنزيل الملف: {str(e)}",
+  "Downloading {name} from mega": "تنزيل {name} من ميجا",
+  "Downloading {name} from basic url": "تنزيل {name} من عنوان url الأساسي",
+  "Download Audio": "تحميل الصوت",
+  "Download audios of any format for use in inference (recommended for mobile users).": "تنزيل صوتيات بأي تنسيق لاستخدامها في الاستدلال (موصى به لمستخدمي الأجهزة المحمولة)",
+  "Any ConnectionResetErrors post-conversion are irrelevant and purely visual; they can be ignored.\n": "تعتبر أي أخطاء في ConnectionResetErrors بعد التحويل غير ذات صلة ومرئية بحتة؛ يمكن تجاهلها.",
+  "Processed audio saved at: ": "تم حفظ الصوت المعالج في:",
+  "Conversion complete!": "اكتمل التحويل!",
+  "Reverb": "تردد",
+  "Compressor": "ضاغط",
+  "Noise Gate": "بوابة الضجيج",
+  "Volume": "مقدار",
+  "Drag the audio here and click the Refresh button": "اسحب الصوت هنا وانقر على زر التحديث",
+  "Select the generated audio": "حدد الصوت الذي تم إنشاؤه",
+  "Volume of the instrumental audio:": "حجم الصوت الآلي",
+  "Volume of the generated audio:": "حجم الصوت الذي تم إنشاؤه",
+  "### Add the effects": "### أضف التأثيرات",
+  "Starting audio conversion... (This might take a moment)": "بدء تحويل الصوت... (قد يستغرق ذلك بعض الوقت)",
+  "TTS Model:": "أصوات TTS",
+  "TTS": "TTS",
+  "TTS Method:": "طريقة TTS",
+  "Audio TTS:": "صوت TTS",
+  "Audio RVC:": "نموذج صوتي"
+}
diff --git a/i18n/locale/de_DE.json b/i18n/locale/de_DE.json
new file mode 100644
index 0000000000000000000000000000000000000000..b83c2de56f93bb58ba2ab92e2887ee63835eeac8
--- /dev/null
+++ b/i18n/locale/de_DE.json
@@ -0,0 +1,252 @@
+{
+  "Unfortunately, there is no compatible GPU available to support your training.": "Leider steht keine kompatible GPU zur Unterstützung Ihres Trainings zur Verfügung.",
+  "Yes": "Ja",
+  "Select your dataset:": "Wählen Sie Ihren Datensatz:",
+  "Update list": "Liste aktualisieren",
+  "Download Model": "Modell herunterladen",
+  "Download Backup": "Backup herunterladen",
+  "Download Dataset": "Datensatz herunterladen",
+  "Download": "Download",
+  "Url:": "Url:",
+  "Build the index before saving.": "Erstellen Sie den Index vor dem Speichern.",
+  "Save your model once the training ends.": "Speichern Sie Ihr Modell, sobald das Training beendet ist.",
+  "Save type": "Speicherart",
+  "Save model": "Modell speichern",
+  "Choose the method": "Wählen Sie die Methode",
+  "Save all": "Speicher alle",
+  "Save D and G": "D. und G.",
+  "Save voice": "Stimme speichern",
+  "Downloading the file: ": "Datei Downloaden:",
+  "Stop training": "Beenden Sie das Training",
+  "Too many users have recently viewed or downloaded this file": "Zu viele Benutzer haben diese Datei kürzlich angesehen oder heruntergeladen",
+  "Cannot get file from this private link": "Datei kann nicht von diesem privaten Link abgerufen werden",
+  "Full download": "Vollständiger Download",
+  "An error occurred downloading": "Beim Herunterladen der Datei ist ein Fehler aufgetreten.  ",
+  "Model saved successfully": "Modell erfolgreich gespeichert",
+  "Saving the model...": "Modell wird gespeichert...",
+  "Saved without index...": "Ohne Index gespeichert...",
+  "Saved without inference model...": "Ohne Inferenzmodell gespeichert...",
+  "An error occurred saving the model": "Beim Speichern des Modells ist ein Fehler aufgetreten",
+  "The model you want to save does not exist, be sure to enter the correct name.": "Das Modell, das Sie speichern möchten, existiert nicht, geben Sie den richtigen Namen ein.",
+  "The file could not be downloaded.": "Die Datei konnte nicht heruntergeladen werden",
+  "Unzip error.": "Unzip-Fehler.",
+  "Path to your added.index file (if it didn't automatically find it)": "Pfad zu Ihrer Datei added.index (falls diese nicht automatisch gefunden wurde)",
+  "It has been downloaded successfully.": "wurde erfolgreich heruntergeladen.",
+  "Proceeding with the extraction...": "Fahren Sie mit der Extraktion fort...",
+  "The Backup has been uploaded successfully.": "Das Backup wurde erfolgreich hochgeladen.",
+  "The Dataset has been loaded successfully.": "Der Datensatz wurde erfolgreich geladen.",
+  "The Model has been loaded successfully.": "Das Modell wurde erfolgreich geladen.",
+  "It is used to download your inference models.": "Es wird verwendet, um Ihre Inferenzmodelle herunterzuladen.",
+  "It is used to download your training backups.": "Es wird verwendet, um Ihre Trainings-Backups herunterzuladen.",
+  "Download the dataset with the audios in a compatible format (.wav/.flac) to train your model.": "Laden Sie den Datensatz mit den Audios in einem kompatiblen Format (.wav/.flac) herunter, um Ihr Modell zu trainieren.",
+  "No relevant file was found to upload.": "Keine relevante Datei zum Hochladen gefunden.",
+  "The model works for inference, and has the .index file.": "Das Modell funktioniert für Inferenz und hat eine .index Datei.",
+  "The model works for inference, but it doesn't have the .index file.": "Das Modell funktioniert für Inferenz, hat jedoch keine .index Datei.",
+  "This may take a few minutes, please wait...": "Es kann einige Minuten dauern, bitte warten.",
+  "Resources": "Ressourcen",
+  "Step 1: Processing data": "Schritt 1: Datenverarbeitung",
+  "Step 2: Skipping pitch extraction": "Schritt 2: Pitch-Extraktion",
+  "Step 3: Extracting features": "Schritt 3: Merkmale extrahieren",
+  "Step 4: Model training started": "Schritt 4: Modelltraining gestartet",
+  "Step 5: Export lowest points on a graph of the model": "Schritt 5: Exportieren Sie die niedrigsten Punkte in einem Diagramm des Modells",
+  "Training is done, check train.log": "Training ist abgeschlossen, überprüfen Sie train.log",
+  "All processes have been completed!": "Alle Prozesse sind abgeschlossen!",
+  "Model Inference": "Modell Inferenz",
+  "Inferencing voice:": "Inferenz Stimme:",
+  "Model_Name": "Model Name",
+  "Dataset_Name": "Name des Datensatzes",
+  "Whether the model has pitch guidance.": "Ob das Modell eine Tonhöhenführung hat.",
+  "Whether to save only the latest .ckpt file to save hard drive space": "Gibt an, ob nur die neueste .ckpt-Datei gespeichert werden soll, um Speicherplatz auf der Festplatte zu sparen",
+  "Cache all training sets to GPU memory. Caching small datasets (less than 10 minutes) can speed up training": "Alle Trainings-Sets im GPU-Speicher zwischenspeichern. Das Zwischenspeichern kleiner Datensätze (weniger als 10 Minuten) kann das Training beschleunigen",
+  "Save a small final model to the 'weights' folder at each save point": "Speichern Sie an jedem Speicherpunkt ein kleines endgültiges Modell im Ordner \"Weights\"",
+  "Refresh": "Stimmenliste, Indexpfad und Audiodateien aktualisieren",
+  "Unload voice to save GPU memory": "Stimme entladen, um GPU-Speicher zu sparen",
+  "Select Speaker/Singer ID:": "Lautsprecher-/Sänger-ID auswählen:",
+  "Recommended +12 key for male to female conversion, and -12 key for female to male conversion. If the sound range goes too far and the voice is distorted, you can also adjust it to the appropriate range by yourself.": "Empfohlen wird +12-Taste für die Umwandlung von Mann zu Frau und -12-Taste für die Umwandlung von Frau zu Mann. Wenn der Klangbereich zu weit geht und die Stimme verzerrt ist, können Sie ihn auch selbst auf den entsprechenden Bereich einstellen.",
+  "Transpose (integer, number Fof semitones, raise by an octave: 12, lower by an octave: -12):": "Transponieren (Ganzzahl, Anzahl der Halbtöne, um eine Oktave erhöhen: 12, um eine Oktave senken: -12):",
+  "Feature search database file path:": "Dateipfad der Funktionssuchdatenbank:",
+  "Enter the path of the audio file to be processed (default is the correct format example):": "Geben Sie den Pfad der zu verarbeitenden Audiodatei ein (Standard ist das richtige Formatbeispiel):",
+  "Select the pitch extraction algorithm:": "Wählen Sie den Pitch-Extraktionsalgorithmus:",
+  "Mangio-Crepe Hop Length (Only applies to mangio-crepe): Hop length refers to the time it takes for the speaker to jump to a dramatic pitch. Lower hop lengths take more time to infer but are more pitch accurate.": "Mangio-Crepe Hopfenlänge (Gilt nur für Mangio-Crepe): Die Hopfenlänge bezieht sich auf die Zeit, die der Sprecher benötigt, um zu einer dramatischen Tonhöhe zu springen. Niedrigere Hopfenlängen benötigen mehr Zeit zur Inferenz, sind aber genauer.",
+  "Feature search dataset file path": "Dateipfad für Feature-Suche-Datensatz",
+  "If >=3: apply median filtering to the harvested pitch results. The value represents the filter radius and can reduce breathiness.": "Wenn >=3: Wendet es die Medianfilterung auf die geernteten Pitch-Ergebnisse an. Der Wert stellt den Filterradius dar und kann die Atmungsaktivität reduzieren.",
+  "Path to the feature index file. Leave blank to use the selected result from the dropdown:": "Pfad zur Feature-Indexdatei. Leer lassen, um das ausgewählte Ergebnis aus der Dropdown-Liste zu verwenden:",
+  "Auto-detect index path and select from the dropdown:": "Indexpfad automatisch erkennen und aus dem Dropdown-Menü auswählen:",
+  "Path to feature file:": "Pfad zur Feature-Datei:",
+  "Search feature ratio:": "Verhältnis der Suchfunktionen:",
+  "Resample the output audio in post-processing to the final sample rate. Set to 0 for no resampling:": "Sample das ausgegebene Audio in der Nachbearbeitung auf die endgültige Samplerate zurück. Für kein Resampling auf 0 setzen:",
+  "Use the volume envelope of the input to replace or mix with the volume envelope of the output. The closer the ratio is to 1, the more the output envelope is used:": "Verwende die Volumenhüllkurve der Eingabe, um die Volumenhüllkurve der Ausgabe zu ersetzen oder mit ihr zu mischen. Je näher das Verhältnis bei 1 liegt, desto mehr wird die Ausgabehüllkurve verwendet:",
+  "Protect voiceless consonants and breath sounds to prevent artifacts such as tearing in electronic music. Set to 0.5 to disable. Decrease the value to increase protection, but it may reduce indexing accuracy:": "Schütze stimmlose Konsonanten und Atemgeräusche, um Artefakte wie das Reißen in elektronischer Musik zu verhindern. Zum Deaktivieren auf 0,5 setzen. Verringern Sie den Wert, um den Schutz zu erhöhen, aber es kann die Indexierungsgenauigkeit verringern:",
+  "F0 curve file (optional). One pitch per line. Replaces the default F0 and pitch modulation:": "F0-Kurvendatei (optional). Eine Tonhöhe pro Linie. Ersetzt die voreingestellte F0- und Tonhöhenmodulation:",
+  "Convert": "Konvertieren",
+  "Output information:": "Ausgangs informationen",
+  "Export audio (click on the three dots in the lower right corner to download)": "Audio exportieren (klicken Sie auf die drei Punkte in der unteren rechten Ecke, um sie herunterzuladen)",
+  "Batch conversion. Enter the folder containing the audio files to be converted or upload multiple audio files. The converted audio will be output in the specified folder (default: 'opt').": "Stapelkonvertierung. Geben Sie den Ordner mit den zu konvertierenden Audiodateien ein oder laden Sie mehrere Audiodateien hoch. Das konvertierte Audio wird im angegebenen Ordner ausgegeben (Standard: 'opt').",
+  "Specify output folder:": "Ausgabeordner festlegen:",
+  "Enter the path of the audio folder to be processed (copy it from the address bar of the file manager):": "Geben Sie den Pfad des zu verarbeitenden Audioordners ein (kopieren Sie ihn aus der Adressleiste des Dateimanagers):",
+  "You can also input audio files in batches. Choose one of the two options. Priority is given to reading from the folder.": "Sie können Audiodateien auch stapelweise eingeben. Wählen Sie eine der beiden Optionen. Das Lesen aus dem Ordner hat Vorrang.",
+  "Export file format:": "Export Dateiformat",
+  "UVR5": "UVR5",
+  "Enter the path of the audio folder to be processed:": "Geben Sie den Pfad des zu verarbeitenden Audioordners ein:",
+  "Model:": "Modell:",
+  "Vocal Extraction Aggressive": "Vokale Extraktion aggressiv",
+  "Specify the output folder for vocals:": "Geben Sie den Ausgabeordner für Vocals an:",
+  "Specify the output folder for accompaniment:": "Geben Sie den Ausgabeordner für die Begleitung an:",
+  "Train": "Trainieren",
+  "Enter the model name:": "Modellname eingeben",
+  "Target sample rate:": "Sample Rate Ziel:",
+  "Whether the model has pitch guidance (required for singing, optional for speech):": "Ob das Modell eine Tonhöhenführung hat (erforderlich für Gesang, optional für Sprache):",
+  "Version:": "Version:",
+  "Number of CPU processes:": "Anzahl der Prozesse,",
+  "Enter the path of the training folder:": "Geben Sie den Pfad des Trainingsordners ein:",
+  "Specify the model ID:": "Geben Sie die Modell-ID an:",
+  "Auto detect audio path and select from the dropdown:": "Audiopfad automatisch erkennen und aus der Dropdown-Liste auswählen:",
+  "Add audio's name to the path to the audio file to be processed (default is the correct format example) Remove the path to use an audio from the dropdown list:": "Fügen Sie dem Pfad zur zu verarbeitenden Audiodatei den Namen des Audios hinzu (Standard ist das richtige Formatbeispiel) Entfernen Sie den Pfad zur Verwendung eines Audios aus der Dropdown-Liste:",
+  "Advanced Settings": "Erweiterte Einstellungen",
+  "Settings": "Einstellungen",
+  "Status:": "Status:",
+  "Process data": "Betriebsdaten",
+  "Drag your audio here:": "Ziehen Sie Ihr Audio hierher:",
+  "Or record an audio:": "Oder nehmen Sie ein Audio auf:",
+  "Formant shift inference audio": "Formant Shift Inferenz-Audio",
+  "Used for male to female and vice-versa conversions": "Wird für Konvertierungen von Männern zu Frauen und umgekehrt verwendet",
+  "Provide the GPU index(es) separated by '-', like 0-1-2 for using GPUs 0, 1, and 2:": "Geben Sie den/die GPU-Index (e) getrennt durch '-' an, wie 0-1-2 für die Verwendung von GPUs 0, 1 und 2:",
+  "GPU Information:": "GPU-Informationen:",
+  "Feature extraction": "Merkmalsextraktion",
+  "Save frequency:": "Speicher-Häufigkeit",
+  "Training epochs:": "Trainingsepochen:",
+  "Batch size per GPU:": "Batch-Size pro GPU:",
+  "Save only the latest '.ckpt' file to save disk space:": "Speicher nur die neueste '.ckpt' -Datei, um Speicherplatz zu sparen:",
+  "No": "Nein",
+  "Save a small final model to the 'weights' folder at each save point:": "Speicher an jedem Speicherpunkt ein kleines endgültiges Modell im Ordner \"Gewichte\":",
+  "Load pre-trained base model G path:": "Vortrainiertes Basismodell G Pfad:",
+  "Load pre-trained base model D path:": "Vorgeschultes Basismodell D Pfad:",
+  "Train model": "Modell trainieren",
+  "Train feature index": "Trainiere-Feature-Index",
+  "One-click training": "Ein-Klick-Training",
+  "Processing": "Es wird bearbeitet",
+  "Model fusion, can be used to test timbre fusion": "Modellfusion, kann zum Testen der Timbrefusion verwendet werden",
+  "Path to Model A:": "Pfad zu Modell A:",
+  "Path to Model B:": "Pfad zu Modell B:",
+  "Weight for Model A:": "Gewicht für Modell A:",
+  "Whether the model has pitch guidance:": "Ob das Modell eine Tonhöhenführung hat:",
+  "Model information to be placed:": "Zu platzierende Modellinformationen:",
+  "Model architecture version:": "Modellarchitekturversion:",
+  "Fusion": "Fusion",
+  "Modify model information": "Modellinformationen ändern",
+  "Path to Model:": "Pfad zum Modell:",
+  "Model information to be modified:": "Zu ändernde Modellinformationen:",
+  "Save file name:": "Dateiname zu speichern:",
+  "Modify": "Modifizieren",
+  "View model information": "Modellinformationen",
+  "View": "Ansehen",
+  "Model extraction": "Modellextraktion",
+  "Name:": "Name:",
+  "Whether the model has pitch guidance (1: yes, 0: no):": "Ob das Modell eine Pitchführung hat (1: ja, 0: nein):",
+  "Extract": "Extrahieren",
+  "Export Onnx": "Onnx exportieren",
+  "RVC Model Path:": "RVC-Modellpfad:",
+  "Onnx Export Path:": "ONNX-Exportpfad:",
+  "MoeVS Model": "MoeVS-Modell",
+  "Export Onnx Model": "Onnx-Modell exportieren",
+  "Load model": "Lastmodell",
+  "Hubert Model": "Hubert-Modell",
+  "Select the .pth file": "Wählen Sie die Datei aus.  ",
+  "Select the .index file": "Wählen Sie die .index-Datei",
+  "Select the .npy file": "Wählen Sie die Datei aus.  ",
+  "Input device": "Eingabegerät",
+  "Output device": "Ausgabegerät",
+  "Audio device (please use the same type of driver)": "Audiogerät (bitte verwenden Sie den gleichen Treibertyp)",
+  "Response threshold": "Ansprechschwelle",
+  "Pitch settings": "Tonhöheneinstellungen",
+  "Whether to use note names instead of their hertz value. E.G. [C5, D6] instead of [523.25, 1174.66]Hz": "Gibt an, ob Notiznamen anstelle ihres Hertz-Wertes verwendet werden sollen. Z.B. [C5, D6] statt [523.25, 1174.66]Hz",
+  "Index Rate": "Indexsatz",
+  "General settings": "Allgemeine Einstellungen",
+  "Sample length": "Probenlänge:",
+  "Fade length": "Ausblendlänge",
+  "Extra inference time": "Zusätzliche Inferenzzeit",
+  "Input noise reduction": "Eingangsgeräuschreduzierung",
+  "Output noise reduction": "Ausgangsgeräuschreduzierung",
+  "Performance settings": "Leistungseinstellungen",
+  "Start audio conversion": "Audiokonvertierung starten",
+  "Stop audio conversion": "Audiokonvertierung stoppen",
+  "Inference time (ms):": "Inferenzzeit (ms):",
+  "Select the pth file": "Wähle die Datei aus...",
+  "Select the .index file:": "Wählen Sie die Indexdatei aus",
+  "The hubert model path must not contain Chinese characters": "Der Hubert-Modellpfad darf keine chinesischen Schriftzeichen enthalten",
+  "The pth file path must not contain Chinese characters.": "Der pth-Dateipfad darf keine chinesischen Zeichen enthalten.",
+  "The index file path must not contain Chinese characters.": "Der Indexdateipfad darf keine chinesischen Zeichen enthalten.",
+  "Step algorithm": "Schritt-Algorithmus",
+  "Number of epoch processes": "Anzahl der Epochenprozesse",
+  "Lowest points export": "Export der niedrigsten Punkte",
+  "How many lowest points to save:": "Wie viele niedrigste Punkte zu sparen sind:",
+  "Export lowest points of a model": "Niedrigste Punkte eines Modells exportieren",
+  "Output models:": "Ausgabemodelle:",
+  "Stats of selected models:": "Statistiken ausgewählter Modelle:",
+  "Custom f0 [Root pitch] File": "Benutzerdefinierte f0 [Root Pitch] -Datei",
+  "Min pitch:": "Min. Tonhöhe:",
+  "Specify minimal pitch for inference [HZ]": "Minimale Tonhöhe für Inferenz angeben [HZ]",
+  "Specify minimal pitch for inference [NOTE][OCTAVE]": "Geben Sie die minimale Tonhöhe für die Inferenz an [HINWEIS][OKTAVE]",
+  "Max pitch:": "Max. Tonhöhe ",
+  "Specify max pitch for inference [HZ]": "Max. Tonhöhe für Inferenz angeben [HZ]",
+  "Specify max pitch for inference [NOTE][OCTAVE]": "Maximale Tonhöhe für Inferenz angeben [HINWEIS][OKTAVE]",
+  "Browse presets for formanting": "Voreinstellungen für Formanting durchsuchen",
+  "Presets are located in formantshiftcfg/ folder": "Voreinstellungen befinden sich in formantshiftcfg/ Ordner",
+  "Default value is 1.0": "Standardwert ist 1",
+  "Quefrency for formant shifting": "Quefrency für Formant-Verschiebung",
+  "Timbre for formant shifting": "Timbre für Formantverschiebung",
+  "Apply": "Übernehmen",
+  "Single": "Einzel",
+  "Batch": "Batch",
+  "Separate YouTube tracks": "Separate YouTube-Tracks",
+  "Download audio from a YouTube video and automatically separate the vocal and instrumental tracks": "Laden Sie Audio von einem YouTube-Video herunter und trennen Sie automatisch die Gesangs- und Instrumentalspuren",
+  "Extra": "Extra",
+  "Merge": "Zusammenführen",
+  "Merge your generated audios with the instrumental": "Fügen Sie Ihre generierten Audios mit dem Instrumental",
+  "Choose your instrumental:": "Wählen Sie Ihr Instrumental:",
+  "Choose the generated audio:": "Wählen Sie das erzeugte Audio:",
+  "Combine": "Kombinieren",
+  "Download and Separate": "Herunterladen und trennen",
+  "Enter the YouTube link:": "Youtube Link eingeben:",
+  "This section contains some extra utilities that often may be in experimental phases": "Dieser Abschnitt enthält einige zusätzliche Dienstprogramme, die sich oft in experimentellen Phasen befinden",
+  "Merge Audios": "Audios zusammenführen",
+  "Audio files have been moved to the 'audios' folder.": "Audiodateien wurden in den Ordner 'audios' verschoben.",
+  "Downloading audio from the video...": "Audio aus dem Video wird heruntergeladen...",
+  "Audio downloaded!": "Audio heruntergeladen!",
+  "An error occurred:": "Ein Fehler ist aufgetreten:",
+  "Separating audio...": "Audio wird getrennt...",
+  "File moved successfully.": "Datei erfolgreich verschoben.",
+  "Finished!": "Abgeschlossen!",
+  "The source file does not exist.": "Die Quelldatei ist nicht vorhanden!",
+  "Error moving the file:": "Fehler beim Verschieben der Datei:",
+  "Downloading {name} from drive": "{name} wird vom Drive heruntergeladen",
+  "The attempt to download using Drive didn't work": "Der Versuch, mit Drive herunterzuladen, hat nicht funktioniert",
+  "Error downloading the file: {str(e)}": "Fehler beim Herunterladen der Datei: {str(e)}",
+  "Downloading {name} from mega": "{name} wird von Mega heruntergeladen",
+  "Downloading {name} from basic url": "{name} wird von der Basis-URL heruntergeladen",
+  "Download Audio": "Audio herunterladen",
+  "Download audios of any format for use in inference (recommended for mobile users).": "Laden Sie Audios in jedem Format zur Verwendung in Inferenz herunter (empfohlen für mobile Benutzer).",
+  "Any ConnectionResetErrors post-conversion are irrelevant and purely visual; they can be ignored.\n": "Alle ConnectionResetErrors nach der Konvertierung sind irrelevant und rein visuell; sie können ignoriert werden.",
+  "Processed audio saved at: ": "Verarbeitete Audiodaten gespeichert unter:",
+  "Conversion complete!": "Konvertierung abgeschlossen",
+  "Reverb": "Nachhall",
+  "Compressor": "Kompressor",
+  "Noise Gate": "Noise-Gate",
+  "Volume": "Lautstärke",
+  "Drag the audio here and click the Refresh button": "Ziehen Sie das Audio hierher und klicken Sie auf den Aktuallisierungs Knopf",
+  "Select the generated audio": "Wählen Sie das erzeugte Audio",
+  "Volume of the instrumental audio:": "Lautstärke des Instrumental-Audios:",
+  "Volume of the generated audio:": "Lautstärke des erzeugten Audios:",
+  "### Audio settings:": "### Audio-Einstellungen",
+  "### Instrumental settings:": "### Instrumentale Einstellungen:",
+  "### Add the effects:": "### Fügen Sie die Effekte hinzu:",
+  "Name for saving": "Name zum Speichern",
+  "Path to model": "Pfad zum Modell",
+  "Model information to be placed": "Zu platzierende Modellinformationen",
+  "Starting audio conversion... (This might take a moment)": "Starte Audio-Konvertierung... (Das kann einen Moment dauern)",
+  "TTS Model:": "TTS-Stimmen",
+  "TTS": "TTS",
+  "TTS Method:": "TTS-Methode",
+  "Audio TTS:": "Audio-TTS",
+  "Audio RVC:": "Audio-Modell"
+}
diff --git a/i18n/locale/en_US.json b/i18n/locale/en_US.json
new file mode 100644
index 0000000000000000000000000000000000000000..239004dd917e67d6ad7db96ec127e1359c5f4a5c
--- /dev/null
+++ b/i18n/locale/en_US.json
@@ -0,0 +1,260 @@
+{
+  "Unfortunately, there is no compatible GPU available to support your training.": "Unfortunately, there is no compatible GPU available to support your training.",
+  "Yes": "Yes",
+  "Select your dataset:": "Select your dataset:",
+  "Update list": "Update list",
+  "Download Model": "Download Model",
+  "Download Backup": "Download Backup",
+  "Download Dataset": "Download Dataset",
+  "Download": "Download",
+  "Url:": "Url:",
+  "Build the index before saving.": "Build the index before saving.",
+  "Save your model once the training ends.": "Save your model once the training ends.",
+  "Save type": "Save type:",
+  "Save model": "Save model",
+  "Choose the method": "Choose the method",
+  "Save all": "Save all",
+  "Save D and G": "Save D and G",
+  "Save voice": "Save voice",
+  "Downloading the file: ": "Downloading the file: ",
+  "Stop training": "Stop training",
+  "Too many users have recently viewed or downloaded this file": "Too many users have recently viewed or downloaded this file",
+  "Cannot get file from this private link": "Cannot get file from this private link",
+  "Full download": "Full download",
+  "An error occurred downloading": "An error occurred downloading",
+  "Model saved successfully": "Model saved successfully",
+  "Saving the model...": "Saving the model...",
+  "Saved without index...": "Saved without index...",
+  "Saved without inference model...": "Saved without inference model...",
+  "An error occurred saving the model": "An error occurred saving the model",
+  "The model you want to save does not exist, be sure to enter the correct name.": "The model you want to save does not exist, be sure to enter the correct name.",
+  "The file could not be downloaded.": "The file could not be downloaded.",
+  "Unzip error.": "Unzip error.",
+  "Path to your added.index file (if it didn't automatically find it)": "Path to your added.index file (if it didn't automatically find it)",
+  "It has been downloaded successfully.": "It has been downloaded successfully.",
+  "Proceeding with the extraction...": "Proceeding with the extraction...",
+  "The Backup has been uploaded successfully.": "The Backup has been uploaded successfully.",
+  "The Dataset has been loaded successfully.": "The Dataset has been loaded successfully.",
+  "The Model has been loaded successfully.": "The Model has been loaded successfully.",
+  "It is used to download your inference models.": "It is used to download your inference models.",
+  "It is used to download your training backups.": "It is used to download your training backups.",
+  "Download the dataset with the audios in a compatible format (.wav/.flac) to train your model.": "Download the dataset with the audios in a compatible format (.wav/.flac) to train your model.",
+  "No relevant file was found to upload.": "No relevant file was found to upload.",
+  "The model works for inference, and has the .index file.": "The model works for inference, and has the .index file.",
+  "The model works for inference, but it doesn't have the .index file.": "The model works for inference, but it doesn't have the .index file.",
+  "This may take a few minutes, please wait...": "This may take a few minutes, please wait...",
+  "Resources": "Resources",
+  "Step 1: Processing data": "Step 1: Processing data",
+  "Step 2: Skipping pitch extraction": "Step 2: Skipping pitch extraction",
+  "Step 3: Extracting features": "Step 3: Extracting features",
+  "Step 4: Model training started": "Step 4: Model training started",
+  "Step 5: Export lowest points on a graph of the model": "Step 5: Export lowest points on a graph of the model",
+  "Training is done, check train.log": "Training is done, check train.log",
+  "All processes have been completed!": "All processes have been completed!",
+  "Model Inference": "Model Inference",
+  "Inferencing voice:": "Inferencing voice:",
+  "Model_Name": "Model_Name",
+  "Dataset_Name": "Dataset_Name",
+  "Whether the model has pitch guidance.": "Whether the model has pitch guidance.",
+  "Whether to save only the latest .ckpt file to save hard drive space": "Whether to save only the latest .ckpt file to save hard drive space",
+  "Cache all training sets to GPU memory. Caching small datasets (less than 10 minutes) can speed up training": "Cache all training sets to GPU memory. Caching small datasets (less than 10 minutes) can speed up training",
+  "Save a small final model to the 'weights' folder at each save point": "Save a small final model to the 'weights' folder at each save point",
+  "Refresh": "Refresh",
+  "Unload voice to save GPU memory": "Unload voice to save GPU memory",
+  "Select Speaker/Singer ID:": "Select Speaker/Singer ID:",
+  "Recommended +12 key for male to female conversion, and -12 key for female to male conversion. If the sound range goes too far and the voice is distorted, you can also adjust it to the appropriate range by yourself.": "Recommended +12 key for male to female conversion, and -12 key for female to male conversion. If the sound range goes too far and the voice is distorted, you can also adjust it to the appropriate range by yourself.",
+  "Transpose (integer, number Fof semitones, raise by an octave: 12, lower by an octave: -12):": "Transpose (integer, number of semitones, raise by an octave: 12, lower by an octave: -12):",
+  "Feature search database file path:": "Feature search database file path:",
+  "Enter the path of the audio file to be processed (default is the correct format example):": "Enter the path of the audio file to be processed (default is the correct format example):",
+  "Select the pitch extraction algorithm:": "Select the pitch extraction algorithm:",
+  "Mangio-Crepe Hop Length (Only applies to mangio-crepe): Hop length refers to the time it takes for the speaker to jump to a dramatic pitch. Lower hop lengths take more time to infer but are more pitch accurate.": "Mangio-Crepe Hop Length (Only applies to mangio-crepe): Hop length refers to the time it takes for the speaker to jump to a dramatic pitch. Lower hop lengths take more time to infer but are more pitch accurate.",
+  "Feature search dataset file path": "Feature search dataset file path",
+  "If >=3: apply median filtering to the harvested pitch results. The value represents the filter radius and can reduce breathiness.": "If >=3: apply median filtering to the harvested pitch results. The value represents the filter radius and can reduce breathiness.",
+  "Path to the feature index file. Leave blank to use the selected result from the dropdown:": "Path to the feature index file. Leave blank to use the selected result from the dropdown:",
+  "Auto-detect index path and select from the dropdown:": "Auto-detect index path and select from the dropdown:",
+  "Path to feature file:": "Path to feature file:",
+  "Search feature ratio:": "Search feature ratio:",
+  "Resample the output audio in post-processing to the final sample rate. Set to 0 for no resampling:": "Resample the output audio in post-processing to the final sample rate. Set to 0 for no resampling:",
+  "Use the volume envelope of the input to replace or mix with the volume envelope of the output. The closer the ratio is to 1, the more the output envelope is used:": "Use the volume envelope of the input to replace or mix with the volume envelope of the output. The closer the ratio is to 1, the more the output envelope is used:",
+  "Protect voiceless consonants and breath sounds to prevent artifacts such as tearing in electronic music. Set to 0.5 to disable. Decrease the value to increase protection, but it may reduce indexing accuracy:": "Protect voiceless consonants and breath sounds to prevent artifacts such as tearing in electronic music. Set to 0.5 to disable. Decrease the value to increase protection, but it may reduce indexing accuracy:",
+  "F0 curve file (optional). One pitch per line. Replaces the default F0 and pitch modulation:": "F0 curve file (optional). One pitch per line. Replaces the default F0 and pitch modulation:",
+  "Convert": "Convert",
+  "Output information:": "Output information:",
+  "Export audio (click on the three dots in the lower right corner to download)": "Export audio (click on the three dots in the lower right corner to download)",
+  "Batch conversion. Enter the folder containing the audio files to be converted or upload multiple audio files. The converted audio will be output in the specified folder (default: 'opt').": "Batch conversion. Enter the folder containing the audio files to be converted or upload multiple audio files. The converted audio will be output in the specified folder (default: 'opt').",
+  "Specify output folder:": "Specify output folder:",
+  "Enter the path of the audio folder to be processed (copy it from the address bar of the file manager):": "Enter the path of the audio folder to be processed (copy it from the address bar of the file manager):",
+  "You can also input audio files in batches. Choose one of the two options. Priority is given to reading from the folder.": "You can also input audio files in batches. Choose one of the two options. Priority is given to reading from the folder.",
+  "Export file format:": "Export file format:",
+  "UVR5": "UVR5",
+  "Enter the path of the audio folder to be processed:": "Enter the path of the audio folder to be processed:",
+  "Model:": "Model:",
+  "Vocal Extraction Aggressive": "Vocal Extraction Aggressive",
+  "Specify the output folder for vocals:": "Specify the output folder for vocals:",
+  "Specify the output folder for accompaniment:": "Specify the output folder for accompaniment:",
+  "Train": "Train",
+  "Enter the model name:": "Enter the model name:",
+  "Target sample rate:": "Target sample rate:",
+  "Whether the model has pitch guidance (required for singing, optional for speech):": "Whether the model has pitch guidance (required for singing, optional for speech):",
+  "Version:": "Version:",
+  "Number of CPU processes:": "Number of CPU processes:",
+  "Enter the path of the training folder:": "Enter the path of the training folder:",
+  "Specify the model ID:": "Specify the model ID:",
+  "Auto detect audio path and select from the dropdown:": "Auto detect audio path and select from the dropdown:",
+  "Add audio's name to the path to the audio file to be processed (default is the correct format example) Remove the path to use an audio from the dropdown list:": "Add audio's name to the path to the audio file to be processed (default is the correct format example) Remove the path to use an audio from the dropdown list:",
+  "Advanced Settings": "Advanced Settings",
+  "Settings": "Settings",
+  "Status:": "Status:",
+  "Process data": "Process data",
+  "Drag your audio here:": "Drag your audio here:",
+  "Or record an audio:": "Or record an audio:",
+  "Formant shift inference audio": "Formant shift inference audio",
+  "Used for male to female and vice-versa conversions": "Used for male to female and vice-versa conversions",
+  "Provide the GPU index(es) separated by '-', like 0-1-2 for using GPUs 0, 1, and 2:": "Provide the GPU index(es) separated by '-', like 0-1-2 for using GPUs 0, 1, and 2:",
+  "GPU Information:": "GPU Information:",
+  "Feature extraction": "Feature extraction",
+  "Save frequency:": "Save frequency:",
+  "Training epochs:": "Training epochs:",
+  "Batch size per GPU:": "Batch size per GPU:",
+  "Save only the latest '.ckpt' file to save disk space:": "Save only the latest '.ckpt' file to save disk space:",
+  "No": "No",
+  "Save a small final model to the 'weights' folder at each save point:": "Save a small final model to the 'weights' folder at each save point:",
+  "Load pre-trained base model G path:": "Load pre-trained base model G path:",
+  "Load pre-trained base model D path:": "Load pre-trained base model D path:",
+  "Train model": "Train model",
+  "Train feature index": "Train feature index",
+  "One-click training": "One-click training",
+  "Processing": "Processing",
+  "Model fusion, can be used to test timbre fusion": "Model fusion, can be used to test timbre fusion",
+  "Path to Model A:": "Path to Model A:",
+  "Path to Model B:": "Path to Model B:",
+  "Weight for Model A:": "Weight for Model A:",
+  "Whether the model has pitch guidance:": "Whether the model has pitch guidance:",
+  "Model information to be placed:": "Model information to be placed:",
+  "Model architecture version:": "Model architecture version:",
+  "Fusion": "Fusion",
+  "Modify model information": "Modify model information",
+  "Path to Model:": "Path to Model:",
+  "Model information to be modified:": "Model information to be modified:",
+  "Save file name:": "Save file name:",
+  "Modify": "Modify",
+  "View model information": "View model information",
+  "View": "View",
+  "Model extraction": "Model extraction",
+  "Name:": "Name:",
+  "Whether the model has pitch guidance (1: yes, 0: no):": "Whether the model has pitch guidance (1: yes, 0: no):",
+  "Extract": "Extract",
+  "Export Onnx": "Export Onnx",
+  "RVC Model Path:": "RVC Model Path:",
+  "Onnx Export Path:": "Onnx Export Path:",
+  "MoeVS Model": "MoeVS Model",
+  "Export Onnx Model": "Export Onnx Model",
+  "Load model": "Load model",
+  "Hubert Model": "Hubert Model",
+  "Select the .pth file": "Select the .pth file",
+  "Select the .index file": "Select the .index file",
+  "Select the .npy file": "Select the .npy file",
+  "Input device": "Input device",
+  "Output device": "Output device",
+  "Audio device (please use the same type of driver)": "Audio device (please use the same type of driver)",
+  "Response threshold": "Response threshold",
+  "Pitch settings": "Pitch settings",
+  "Whether to use note names instead of their hertz value. E.G. [C5, D6] instead of [523.25, 1174.66]Hz": "Whether to use note names instead of their hertz value. E.G. [C5, D6] instead of [523.25, 1174.66]Hz",
+  "Index Rate": "Index Rate",
+  "General settings": "General settings",
+  "Sample length": "Sample length",
+  "Fade length": "Fade length",
+  "Extra inference time": "Extra inference time",
+  "Input noise reduction": "Input noise reduction",
+  "Output noise reduction": "Output noise reduction",
+  "Performance settings": "Performance settings",
+  "Start audio conversion": "Start audio conversion",
+  "Stop audio conversion": "Stop audio conversion",
+  "Inference time (ms):": "Inference time (ms):",
+  "Select the pth file": "Select the pth file",
+  "Select the .index file:": "Select the .index file:",
+  "The hubert model path must not contain Chinese characters": "The hubert model path must not contain Chinese characters",
+  "The pth file path must not contain Chinese characters.": "The pth file path must not contain Chinese characters.",
+  "The index file path must not contain Chinese characters.": "The index file path must not contain Chinese characters.",
+  "Step algorithm": "Step algorithm",
+  "Number of epoch processes": "Number of epoch processes",
+  "Lowest points export": "Lowest points export",
+  "How many lowest points to save:": "How many lowest points to save:",
+  "Export lowest points of a model": "Export lowest points of a model",
+  "Output models:": "Output models:",
+  "Stats of selected models:": "Stats of selected models:",
+  "Custom f0 [Root pitch] File": "Custom f0 [Root pitch] File",
+  "Min pitch:": "Min pitch:",
+  "Specify minimal pitch for inference [HZ]": "Specify minimal pitch for inference [HZ]",
+  "Specify minimal pitch for inference [NOTE][OCTAVE]": "Specify minimal pitch for inference [NOTE][OCTAVE]",
+  "Max pitch:": "Max pitch:",
+  "Specify max pitch for inference [HZ]": "Specify max pitch for inference [HZ]",
+  "Specify max pitch for inference [NOTE][OCTAVE]": "Specify max pitch for inference [NOTE][OCTAVE]",
+  "Browse presets for formanting": "Browse presets for formanting",
+  "Presets are located in formantshiftcfg/ folder": "Presets are located in formantshiftcfg/ folder",
+  "Default value is 1.0": "Default value is 1.0",
+  "Quefrency for formant shifting": "Quefrency for formant shifting",
+  "Timbre for formant shifting": "Timbre for formant shifting",
+  "Apply": "Apply",
+  "Single": "Single",
+  "Batch": "Batch",
+  "Separate YouTube tracks": "Separate YouTube tracks",
+  "Download audio from a YouTube video and automatically separate the vocal and instrumental tracks": "Download audio from a YouTube video and automatically separate the vocal and instrumental tracks",
+  "Extra": "Extra",
+  "Merge": "Merge",
+  "Merge your generated audios with the instrumental": "Merge your generated audios with the instrumental",
+  "Choose your instrumental:": "Choose your instrumental:",
+  "Choose the generated audio:": "Choose the generated audio:",
+  "Combine": "Combine",
+  "Download and Separate": "Download and Separate",
+  "Enter the YouTube link:": "Enter the YouTube link:",
+  "This section contains some extra utilities that often may be in experimental phases": "This section contains some extra utilities that often may be in experimental phases",
+  "Merge Audios": "Merge Audios",
+  "Audio files have been moved to the 'audios' folder.": "Audio files have been moved to the 'audios' folder.",
+  "Downloading audio from the video...": "Downloading audio from the video...",
+  "Audio downloaded!": "Audio downloaded!",
+  "An error occurred:": "An error occurred:",
+  "Separating audio...": "Separating audio...",
+  "File moved successfully.": "File moved successfully.",
+  "Finished!": "Finished!",
+  "The source file does not exist.": "The source file does not exist.",
+  "Error moving the file:": "Error moving the file:",
+  "Downloading {name} from drive": "Downloading {name} from drive",
+  "The attempt to download using Drive didn't work": "The attempt to download using Drive didn't work",
+  "Error downloading the file: {str(e)}": "Error downloading the file: {str(e)}",
+  "Downloading {name} from mega": "Downloading {name} from mega",
+  "Downloading {name} from basic url": "Downloading {name} from basic url",
+  "Download Audio": "Download Audio",
+  "Download audios of any format for use in inference (recommended for mobile users).": "Download audios of any format for use in inference (recommended for mobile users).",
+  "Any ConnectionResetErrors post-conversion are irrelevant and purely visual; they can be ignored.\n": "Any ConnectionResetErrors post-conversion are irrelevant and purely visual; they can be ignored.\n",
+  "Processed audio saved at: ": "Processed audio saved at: ",
+  "Conversion complete!": "Conversion complete!",
+  "Reverb": "Reverb",
+  "Compressor": "Compressor",
+  "Noise Gate": "Noise Gate",
+  "Volume": "Volume",
+  "Drag the audio here and click the Refresh button": "Drag the audio here and click the Refresh button",
+  "Select the generated audio": "Select the generated audio",
+  "Volume of the instrumental audio:": "Volume of the instrumental audio:",
+  "Volume of the generated audio:": "Volume of the generated audio:",
+  "### Audio settings:": "### Audio settings:",
+  "### Instrumental settings:": "### Instrumental settings:",
+  "### Add the effects:": "### Add the effects:",
+  "Name for saving": "Name for saving",
+  "Path to model": "Path to model",
+  "Model information to be placed": "Model information to be placed",
+  "Starting audio conversion... (This might take a moment)": "Starting audio conversion... (This might take a moment)",
+  "Error no reformatted.wav found:": "Error no reformatted.wav found:",
+  "Error at separating audio:": "Error at separating audio:",
+  "Vocal": "Vocal",
+  "Instrumental": "Instrumental",
+  "Finished": "Finished",
+  "TTS Model:": "TTS Model:",
+  "TTS": "TTS",
+  "RVC Model:": "RVC Model:",
+  "TTS Method:": "TTS Method:",
+  "Audio TTS:": "Audio TTS:",
+  "Audio RVC:": "Audio RVC:",
+  "Enter the text you want to convert to voice...": "Enter the text you want to convert to voice...",
+  "Text:": "Text:"
+}
diff --git a/i18n/locale/es_ES.json b/i18n/locale/es_ES.json
new file mode 100644
index 0000000000000000000000000000000000000000..959775e010487ba1dfcff27164b219ed16e62274
--- /dev/null
+++ b/i18n/locale/es_ES.json
@@ -0,0 +1,260 @@
+{
+  "Unfortunately, there is no compatible GPU available to support your training.": "Lamentablemente, no hay una GPU compatible disponible para respaldar tu formación.",
+  "Yes": "Sí",
+  "Select your dataset:": "Seleccione su dataset:",
+  "Update list": "Actualizar lista",
+  "Download Model": "Descargar modelo",
+  "Download Backup": "Descargar copias de seguridad",
+  "Download Dataset": "Descargar dataset",
+  "Download": "Descargar",
+  "Url:": "Enlace:",
+  "Build the index before saving.": "Genere el índice antes de guardarlo.",
+  "Save your model once the training ends.": "Guarde su modelo una vez finalice el entrenamiento.",
+  "Save type": "Método de guardado:",
+  "Save model": "Guardar modelo",
+  "Choose the method": "Elige el método",
+  "Save all": "Guardar todos los archivos",
+  "Save D and G": "Guardar archivos G y D",
+  "Save voice": "Guadar modelo para inferencia",
+  "Downloading the file: ": "Descargando el archivo:",
+  "Stop training": "Detener entrenamiento",
+  "Too many users have recently viewed or downloaded this file": "Demasiados usuarios han visto o descargado recientemente este archivo",
+  "Cannot get file from this private link": "No se puede obtener el archivo de este enlace privado",
+  "Full download": "Descarga completa",
+  "An error occurred downloading": "Se ha producido un error al descargar",
+  "Model saved successfully": "Modelo guardado correctamente",
+  "Saving the model...": "Guardando el modelo...",
+  "Saved without index...": "Guardado sin archivo .index...",
+  "Saved without inference model...": "Guardado sin modelo de inferencia...",
+  "An error occurred saving the model": "Se ha producido un error al guardar el modelo",
+  "The model you want to save does not exist, be sure to enter the correct name.": "El modelo que desea guardar no existe, asegúrese de introducir el nombre correcto.",
+  "The file could not be downloaded.": "No se pudo bajar el archivo",
+  "Unzip error.": "Error al descomprimir.",
+  "Path to your added.index file (if it didn't automatically find it)": "Ruta a su archivo added.index (si no lo encontró automáticamente)",
+  "It has been downloaded successfully.": "Se ha descargado con éxito.",
+  "Proceeding with the extraction...": "Continuando con la extracción...",
+  "The Backup has been uploaded successfully.": "La copia de seguridad se ha cargado correctamente.",
+  "The Dataset has been loaded successfully.": "El dataset se ha cargado correctamente.",
+  "The Model has been loaded successfully.": "El modelo se ha cargado correctamente.",
+  "It is used to download your inference models.": "Se utiliza para descargar sus modelos de inferencia.",
+  "It is used to download your training backups.": "Se utiliza para descargar las copias de seguridad de entrenamientos.",
+  "Download the dataset with the audios in a compatible format (.wav/.flac) to train your model.": "Descargue el dataset con los audios en un formato compatible (.wav/.flac) para entrenar su modelo.",
+  "No relevant file was found to upload.": "No se ha encontrado ningún archivo relevante para cargar.",
+  "The model works for inference, and has the .index file.": "El modelo funciona para inferencia y tiene el archivo .index.",
+  "The model works for inference, but it doesn't have the .index file.": "El modelo funciona para inferencia, pero no tiene el archivo .index.",
+  "This may take a few minutes, please wait...": "Esto puede tardar unos minutos, espere por favor.",
+  "Resources": "Recursos",
+  "Step 1: Processing data": "Paso 1: Procesamiento de datos",
+  "Step 2: Skipping pitch extraction": "Paso 2: Extracción de tono",
+  "Step 3: Extracting features": "Paso 3: Extracción de funciones",
+  "Step 4: Model training started": "Paso 4: Entrenamiento del modelo",
+  "Step 5: Export lowest points on a graph of the model": "Paso 5: Exporte los puntos más bajos en un gráfico del modelo",
+  "Training is done, check train.log": "El entrenamiento ha finalizado, revisa train.log.",
+  "All processes have been completed!": "¡Todos los procesos se han completado!",
+  "Model Inference": "Inferencia",
+  "Inferencing voice:": "Modelo de voz:",
+  "Model_Name": "Nombre_Modelo",
+  "Dataset_Name": "Nombre_Dataset",
+  "Whether the model has pitch guidance.": "Si el modelo tiene guía de tono.",
+  "Whether to save only the latest .ckpt file to save hard drive space": "Si guardar solo el último archivo .ckpt para ahorrar espacio en el disco duro",
+  "Cache all training sets to GPU memory. Caching small datasets (less than 10 minutes) can speed up training": "El almacenamiento en caché de pequeños conjuntos de datos (menos de 10 minutos) puede acelerar el entrenamiento",
+  "Save a small final model to the 'weights' folder at each save point": "Guarde un pequeño modelo final en la carpeta 'weights' en cada punto de guardado",
+  "Refresh": "Actualizar",
+  "Unload voice to save GPU memory": "Eliminar voz para ahorrar memoria de GPU",
+  "Select Speaker/Singer ID:": "Seleccionar ID de orador/cantante:",
+  "Transpose (integer, number of semitones, raise by an octave: 12, lower by an octave: -12):": "Transponer (entero, número de semitonos, subir una octava: 12, bajar una octava -12):",
+  "Recommended +12 key for male to female conversion, and -12 key for female to male conversion. If the sound range goes too far and the voice is distorted, you can also adjust it to the appropriate range by yourself.": "Se recomienda la tecla +12 para la conversión de hombre a mujer y la tecla -12 para la conversión de mujer a hombre. Si el rango de sonido va demasiado lejos y la voz está distorsionada, también puede ajustarlo al rango apropiado usted mismo.",
+  "Enter the path of the audio file to be processed (default is the correct format example):": "Introduzca la ruta del archivo de audio a procesar (el ejemplo de formato correcto es el predeterminado):",
+  "Select the pitch extraction algorithm:": "Seleccione el algoritmo de extracción de tono:",
+  "Mangio-Crepe Hop Length (Only applies to mangio-crepe): Hop length refers to the time it takes for the speaker to jump to a dramatic pitch. Lower hop lengths take more time to infer but are more pitch accurate.": "Longitud de salto de mangio-crepe (solo se aplica a mangio-crepe): la longitud de salto se refiere al tiempo que tarda el hablante en saltar a un tono dramático. Las longitudes de salto más bajas tardan más tiempo en inferirse, pero son más precisas en el tono.",
+  "Feature search dataset file path": "Ruta del archivo del dataset de búsqueda de funciones",
+  "If >=3: apply median filtering to the harvested pitch results. The value represents the filter radius and can reduce breathiness.": "Si >=3: aplicar filtrado de mediana a los resultados de brea cosechada. El valor representa el radio del filtro y puede reducir la transpiración.",
+  "Path to the feature index file. Leave blank to use the selected result from the dropdown:": "Ruta al archivo .index de entidades. Déjelo en blanco para usar el resultado seleccionado del menú desplegable:",
+  "Auto-detect index path and select from the dropdown:": "Detectar automáticamente la ruta del archivo .index y seleccionar en el menú desplegable:",
+  "Path to feature file:": "Ruta del archivo de características:",
+  "Search feature ratio:": "Proporción de función de búsqueda:",
+  "Resample the output audio in post-processing to the final sample rate. Set to 0 for no resampling:": "Vuelva a muestrear el audio de salida en el posprocesamiento a la frecuencia de muestreo final. Establecer en 0 para no volver a muestrear:",
+  "Use the volume envelope of the input to replace or mix with the volume envelope of the output. The closer the ratio is to 1, the more the output envelope is used:": "Utilice la envolvente de volumen de la entrada para reemplazar o mezclar con la envolvente de volumen de la salida. Cuanto más cerca esté la relación a 1, más se utilizará la envolvente de salida:",
+  "Protect voiceless consonants and breath sounds to prevent artifacts such as tearing in electronic music. Set to 0.5 to disable. Decrease the value to increase protection, but it may reduce indexing accuracy:": "Proteja las consonantes sordas y los sonidos de la respiración para evitar artefactos como el desgarro en la música electrónica. Establecer en 0.5 para desactivar. Disminuya el valor para aumentar la protección, pero puede reducir la precisión de la indexación:",
+  "F0 curve file (optional). One pitch per line. Replaces the default F0 and pitch modulation:": "Archivo de curva F0 (opcional). Un paso por línea. Sustituye la modulación de paso y F0 predeterminada:",
+  "Convert": "Convertir",
+  "Output information:": "Información de salida:",
+  "Export audio (click on the three dots in the lower right corner to download)": "Exportar audio (haga clic en los tres puntos en la esquina inferior derecha para descargar)",
+  "Batch conversion. Enter the folder containing the audio files to be converted or upload multiple audio files. The converted audio will be output in the specified folder (default: 'opt').": "Conversión por lotes. Introduzca la carpeta que contiene los archivos de audio a convertir o cargue varios archivos de audio. El audio convertido se emitirá en la carpeta especificada (predeterminado: 'opt').",
+  "Specify output folder:": "Especificar carpeta de salida:",
+  "Enter the path of the audio folder to be processed (copy it from the address bar of the file manager):": "Introduzca la ruta de la carpeta de audio a procesar (cópiela desde la barra de direcciones del gestor de archivos):",
+  "You can also input audio files in batches. Choose one of the two options. Priority is given to reading from the folder.": "También puede introducir archivos de audio en lotes. Elige una de las dos opciones. Se da prioridad a la lectura de la carpeta.",
+  "Export file format:": "Formato de archivo de exportación:",
+  "UVR5": "UVR5",
+  "Enter the path of the audio folder to be processed:": "Introduzca la ruta de la carpeta de audio a procesar:",
+  "Model:": "Modelo:",
+  "Vocal Extraction Aggressive": "Extracción vocal agresiva",
+  "Specify the output folder for vocals:": "Especifique la carpeta de salida para las voces:",
+  "Specify the output folder for accompaniment:": "Especifique la carpeta de salida para el acompañamiento:",
+  "Train": "Entrenar",
+  "Enter the model name:": "Nombre del modelo:",
+  "Target sample rate:": "Tasa de muestreo objetivo:",
+  "Whether the model has pitch guidance (required for singing, optional for speech):": "Si el modelo tiene guía de tono (requerido para cantar, opcional para el habla):",
+  "Version:": "Versión:",
+  "Number of CPU processes:": "Número de procesos de CPU:",
+  "Enter the path of the training folder:": "Introduzca la ruta de la carpeta de formación:",
+  "Specify the model ID:": "Especifique el ID del modelo:",
+  "Auto detect audio path and select from the dropdown:": "Detectar automáticamente la ruta de audio y seleccionar en el menú desplegable:",
+  "Add audio's name to the path to the audio file to be processed (default is the correct format example) Remove the path to use an audio from the dropdown list:": "Agregue el nombre del audio a la ruta del archivo de audio que se procesará (el ejemplo de formato correcto es el predeterminado) Elimine la ruta para usar un audio de la lista desplegable:",
+  "Advanced Settings": "Ajustes avanzados",
+  "Settings": "Configuración",
+  "Status:": "Estado:",
+  "Process data": "Procesar datos",
+  "Drag your audio here:": "Arrastra tu audio aquí:",
+  "Or record an audio:": "O graba un audio:",
+  "Formant shift inference audio": "Audio de inferencia de desplazamiento formante",
+  "Used for male to female and vice-versa conversions": "Se utiliza para conversiones de hombre a mujer y viceversa",
+  "Provide the GPU index(es) separated by '-', like 0-1-2 for using GPUs 0, 1, and 2:": "Proporcione los índices de la GPU separados por '-', como 0-1-2 para usar las GPU 0, 1 y 2:",
+  "GPU Information:": "Información de la GPU:",
+  "Feature extraction": "Extracción de característicos",
+  "Save frequency:": "Frecuencia de guardado:",
+  "Training epochs:": "Epochs de entrenamiento:",
+  "Batch size per GPU:": "Tamaño de lote por GPU:",
+  "Save only the latest '.ckpt' file to save disk space:": "Guarde solo el último archivo '.ckpt' para ahorrar espacio en disco:",
+  "No": "No",
+  "Save a small final model to the 'weights' folder at each save point:": "Guarde un pequeño modelo final en la carpeta 'pesos' en cada punto de guardado:",
+  "Load pre-trained base model G path:": "Cargar ruta base modelo G pre-entrenada:",
+  "Load pre-trained base model D path:": "Ruta del modelo D base de carga pre-entrenada:",
+  "Train model": "Entrenar modelo",
+  "Train feature index": "Índice de características",
+  "One-click training": "Entrenamiento con un solo clic",
+  "Processing": "Procesamiento",
+  "Model fusion, can be used to test timbre fusion": "Modelo de fusión, se puede utilizar para probar la fusión de timbre",
+  "Path to Model A:": "Ruta al Modelo A:",
+  "Path to Model B:": "Ruta al Modelo B:",
+  "Weight for Model A:": "Peso para el modelo A:",
+  "Whether the model has pitch guidance:": "Si el modelo tiene guía de tono:",
+  "Model information to be placed:": "Información del modelo a colocar:",
+  "Name:": "Nombre:",
+  "Model architecture version:": "Versión de la arquitectura del modelo:",
+  "Fusion": "Fusión",
+  "Modify model information": "Modificar información del modelo",
+  "Path to Model:": "Ruta al modelo:",
+  "Model information to be modified:": "Información del modelo a modificar:",
+  "Save file name:": "Guardar nombre de archivo:",
+  "Modify": "Modificar",
+  "View model information": "Información del modelo",
+  "View": "Ver",
+  "Model extraction": "Extracción del modelo",
+  "Whether the model has pitch guidance (1: yes, 0: no):": "Si el modelo tiene guía de tono (1: sí, 0: no):",
+  "Extract": "Extraer",
+  "Export Onnx": "Exportar Onnx",
+  "RVC Model Path:": "Ruta del modelo RVC:",
+  "Onnx Export Path:": "Ruta de exportación Onnx:",
+  "MoeVS Model": "Modelo MoeVS",
+  "Export Onnx Model": "Exportar modelo Onnx",
+  "Load model": "Cargar modelo",
+  "Hubert Model": "Modelo Hubert",
+  "Select the .pth file": "Seleccione un archivo.",
+  "Select the .index file": "Seleccione el archivo .index",
+  "Select the .npy file": "Seleccione un archivo.",
+  "Input device": "Dispositivo de entrada",
+  "Output device": "Dispositivo de salida",
+  "Audio device (please use the same type of driver)": "Dispositivo de audio (utilice el mismo tipo de controlador)",
+  "Response threshold": "Umbral de respuesta",
+  "Pitch settings": "Ajustes de tono",
+  "Whether to use note names instead of their hertz value. E.G. [C5, D6] instead of [523.25, 1174.66]Hz": "Si se deben usar nombres de notas en lugar de su valor de hercios. POR EJEMPLO, [C5, D6] en lugar de [523,25, 1174,66]Hz",
+  "Index Rate": "Tasa de Índice",
+  "General settings": "Configuración general",
+  "Sample length": "Longitud de la muestra",
+  "Fade length": "Longitud del desvanecimiento",
+  "Extra inference time": "Tiempo de inferencia adicional",
+  "Input noise reduction": "Reducción de ruido de entrada",
+  "Output noise reduction": "Reducción de ruido de salida",
+  "Performance settings": "Ajustes de rendimiento",
+  "Start audio conversion": "Iniciar conversión de audio",
+  "Stop audio conversion": "Detener conversión de audio",
+  "Inference time (ms):": "Tiempo de inferencia (ms):",
+  "Select the pth file": "Seleccione un archivo.",
+  "Select the .index file:": "Selecciona el archivo .index:",
+  "The hubert model path must not contain Chinese characters": "La ruta del modelo hubert no debe contener caracteres chinos",
+  "The pth file path must not contain Chinese characters.": "La ruta del archivo pth no debe contener caracteres chinos.",
+  "The index file path must not contain Chinese characters.": "La ruta del archivo .index no debe contener caracteres chinos.",
+  "Step algorithm": "Algoritmo de pasos",
+  "Number of epoch processes": "Número de procesos de Epoch",
+  "Lowest points export": "Exportación de puntos más bajos",
+  "How many lowest points to save:": "Cuántos puntos bajos quieres guardar:",
+  "Export lowest points of a model": "Exportar los puntos más bajos de un modelo",
+  "Output models:": "Modelos de salida:",
+  "Stats of selected models:": "Estadísticas de los modelos seleccionados:",
+  "Custom f0 [Root pitch] File": "Archivo personalizado f0 [Root pitch]",
+  "Min pitch:": "Tono mínimo:",
+  "Feature search database file path:": "Ruta del archivo de la base de datos de búsqueda de características:",
+  "Specify minimal pitch for inference [HZ]": "Especificar paso mínimo para inferencia [HZ]",
+  "Specify minimal pitch for inference [NOTE][OCTAVE]": "Especifique el tono mínimo para la inferencia [NOTA][OCTAVA]",
+  "Max pitch:": "Tono máximo:",
+  "Specify max pitch for inference [HZ]": "Especifique el paso máximo para la inferencia [HZ]",
+  "Specify max pitch for inference [NOTE][OCTAVE]": "Especifique el tono máximo para la inferencia [NOTA][OCTAVA]",
+  "Browse presets for formanting": "Examinar ajustes preestablecidos para formatear",
+  "Presets are located in formantshiftcfg/ folder": "Los ajustes preestablecidos se encuentran en formantshiftcfg/ folder",
+  "Default value is 1.0": "El valor por defecto es 1.",
+  "Quefrency for formant shifting": "Quefrencia para desplazamiento de formantes",
+  "Timbre for formant shifting": "Timbre para el cambio de formantes",
+  "Apply": "Aplicar",
+  "Single": "Individual",
+  "Batch": "Lote",
+  "Separate YouTube tracks": "Pistas separadas de YouTube",
+  "Download audio from a YouTube video and automatically separate the vocal and instrumental tracks": "Descarga el audio de un vídeo de YouTube y separa automáticamente las pistas vocales e instrumentales.",
+  "Extra": "Extra",
+  "Merge": "Combinar",
+  "Merge your generated audios with the instrumental": "Combina tus audios generados con el instrumental",
+  "Choose your instrumental:": "Elige tu instrumental:",
+  "Choose the generated audio:": "Elige el audio generado:",
+  "Combine": "Combinar",
+  "Download and Separate": "Descargar y separar",
+  "Enter the YouTube link:": "Introduce el enlace de YouTube:",
+  "This section contains some extra utilities that often may be in experimental phases": "Esta sección contiene algunas utilidades adicionales que a menudo pueden estar en fases experimentales",
+  "Merge Audios": "Combinar audios",
+  "Audio files have been moved to the 'audios' folder.": "Los archivos de audio se han movido a la carpeta 'audios'.",
+  "Downloading audio from the video...": "Descargando audio del vídeo...",
+  "Audio downloaded!": "¡Audio descargado!",
+  "An error occurred:": "Se ha producido un error:",
+  "Separating audio...": "Separando audio...",
+  "File moved successfully.": "El artículo se ha movido correctamente",
+  "Finished!": "¡Listo!",
+  "The source file does not exist.": "El archivo no existe.",
+  "Error moving the file:": "Error al mover el archivo:",
+  "Downloading {name} from drive": "Descargando {name} de la unidad",
+  "The attempt to download using Drive didn't work": "El intento de descarga con Drive no ha funcionado",
+  "Error downloading the file: {str(e)}": "Error al descargar el archivo: {str(e)}",
+  "Downloading {name} from mega": "Descargando {name} de mega",
+  "Downloading {name} from basic url": "Descargando {name} desde la URL básica",
+  "Download Audio": "Descargar audio",
+  "Download audios of any format for use in inference (recommended for mobile users).": "Descargar audios de cualquier formato para su uso en inferencia (recomendado para usuarios móviles).",
+  "Any ConnectionResetErrors post-conversion are irrelevant and purely visual; they can be ignored.\n": "Cualquier posconversión de ConnectionResetErrors es irrelevante y puramente visual; se puede ignorar.\n",
+  "Processed audio saved at: ": "Audio procesado guardado en:",
+  "Conversion complete!": "Actualización finalizada",
+  "Reverb": "Reverberación",
+  "Compressor": "Compresor",
+  "Noise Gate": "Puerta de ruido",
+  "Volume": "Volumen",
+  "Drag the audio here and click the Refresh button": "Arrastre el audio aquí y haga clic en el botón Actualizar",
+  "Select the generated audio": "Selecciona el audio generado",
+  "Volume of the instrumental audio:": "Volumen del audio instrumental:",
+  "Volume of the generated audio:": "Volumen del audio generado:",
+  "### Audio settings:": "### Audio generado:",
+  "### Instrumental settings:": "### Audio de instrumental:",
+  "### Add the effects:": "### Añade los efectos:",
+  "Name for saving": "Nombre de guardado",
+  "Path to model": "Ruta al modelo",
+  "Model information to be placed": "Información del modelo a modificar",
+  "Starting audio conversion... (This might take a moment)": "Iniciando la conversión del audio... (Esto podría llevar un tiempo)",
+  "Error no reformatted.wav found:": "Error no se encontró el archivo reformatted.wav:",
+  "Error at separating audio:": "Error al separar el audio:",
+  "Vocal": "Vocal",
+  "Instrumental": "Instrumental",
+  "Finished": "Terminado",
+  "TTS Model:": "Modelo TTS:",
+  "TTS": "TTS",
+  "RVC Model:": "Modelo RVC:",
+  "TTS Method:": "Método TTS:",
+  "Audio TTS:": "Audio TTS:",
+  "Audio RVC:": "Audio RVC:",
+  "Enter the text you want to convert to voice...": "Introduce el texto que desea convertir en voz...",
+  "Text:": "Texto:"
+}
diff --git a/i18n/locale/id_ID.json b/i18n/locale/id_ID.json
new file mode 100644
index 0000000000000000000000000000000000000000..4b19a691e97c392276d80e526d917523e8bcaeec
--- /dev/null
+++ b/i18n/locale/id_ID.json
@@ -0,0 +1,248 @@
+{
+  "Unfortunately, there is no compatible GPU available to support your training.": "Sayangnya, tidak ada GPU kompatibel yang tersedia untuk mendukung pelatihan Anda.",
+  "Yes": "Ya",
+  "Select your dataset:": "Pilih kumpulan data Anda.",
+  "Update list": "Perbarui daftar.",
+  "Download Model": "Unduh Model",
+  "Download Backup": "Unduh Cadangan",
+  "Download Dataset": "Unduh Kumpulan Data",
+  "Download": "Unduh",
+  "Url:": "URL:",
+  "Build the index before saving.": "Bangun indeks sebelum menyimpan.",
+  "Save your model once the training ends.": "Simpan model Anda setelah pelatihan berakhir.",
+  "Save type": "Simpan jenis",
+  "Save model": "Simpan modelnya",
+  "Choose the method": "Pilih metodenya",
+  "Save all": "Simpan semua",
+  "Save D and G": "Simpan D dan G",
+  "Save voice": "Simpan suara",
+  "Downloading the file: ": "Mengunduh file:",
+  "Stop training": "Hentikan pelatihan",
+  "Too many users have recently viewed or downloaded this file": "Terlalu banyak pengguna yang baru-baru ini melihat atau mengunduh file ini",
+  "Cannot get file from this private link": "Tidak dapat memperoleh file dari tautan pribadi ini",
+  "Full download": "Unduhan penuh",
+  "An error occurred downloading": "Terjadi kesalahan saat mengunduh",
+  "Model saved successfully": "Model berhasil disimpan",
+  "Saving the model...": "Menyimpan model...",
+  "Saved without index...": "Disimpan tanpa indeks...",
+  "model_name": "nama model",
+  "Saved without inference model...": "Disimpan tanpa model inferensi...",
+  "An error occurred saving the model": "Terjadi kesalahan saat menyimpan model",
+  "The model you want to save does not exist, be sure to enter the correct name.": "Model yang ingin disimpan tidak ada, pastikan memasukkan nama yang benar.",
+  "The file could not be downloaded.": "File tidak dapat diunduh.",
+  "Unzip error.": "Kesalahan buka zip.",
+  "Path to your added.index file (if it didn't automatically find it)": "Jalur ke file add.index Anda (jika tidak menemukannya secara otomatis)",
+  "It has been downloaded successfully.": "Itu telah berhasil diunduh.",
+  "Proceeding with the extraction...": "Melanjutkan ekstraksi...",
+  "The Backup has been uploaded successfully.": "Cadangan telah berhasil diunggah.",
+  "The Dataset has been loaded successfully.": "Dataset telah berhasil dimuat.",
+  "The Model has been loaded successfully.": "Model telah berhasil dimuat.",
+  "It is used to download your inference models.": "Ini digunakan untuk mengunduh model inferensi Anda.",
+  "It is used to download your training backups.": "Ini digunakan untuk mengunduh cadangan pelatihan Anda.",
+  "Download the dataset with the audios in a compatible format (.wav/.flac) to train your model.": "Unduh kumpulan data dengan audio dalam format yang kompatibel (.wav/.flac) untuk melatih model Anda.",
+  "No relevant file was found to upload.": "Tidak ada file relevan yang ditemukan untuk diunggah.",
+  "The model works for inference, and has the .index file.": "Model ini berfungsi untuk inferensi, dan memiliki file .index.",
+  "The model works for inference, but it doesn't have the .index file.": "Model ini berfungsi untuk inferensi, tetapi tidak memiliki file .index.",
+  "This may take a few minutes, please wait...": "Ini mungkin memakan waktu beberapa menit, harap tunggu...",
+  "Resources": "Sumber daya",
+  "Step 1: Processing data": "Langkah 1: Memproses data",
+  "Step 2: Skipping pitch extraction": "Langkah 2a: Melewatkan ekstraksi nada",
+  "Step 3: Extracting features": "Langkah 2b: Mengekstraksi fitur",
+  "Step 4: Model training started": "Langkah 3a: Pelatihan model dimulai",
+  "Step 5: Export lowest points on a graph of the model": "Langkah 4: Ekspor titik terendah pada grafik model",
+  "Training is done, check train.log": "Pelatihan selesai, periksa train.log",
+  "All processes have been completed!": "Semua proses telah selesai!",
+  "Model Inference": "Inferensi Model",
+  "Inferencing voice:": "Menyimpulkan suara:",
+  "Model_Name": "Nama model",
+  "Dataset_Name": "Kumpulan Data_Nama",
+  "Whether the model has pitch guidance.": "Apakah model memiliki panduan nada.",
+  "Whether to save only the latest .ckpt file to save hard drive space": "Apakah hanya menyimpan file .ckpt terbaru untuk menghemat ruang hard drive",
+  "Cache all training sets to GPU memory. Caching small datasets (less than 10 minutes) can speed up training": "Simpan semua set pelatihan ke memori GPU. Menyimpan kumpulan data kecil (kurang dari 10 menit) dapat mempercepat pelatihan",
+  "Save a small final model to the 'weights' folder at each save point": "Simpan model akhir kecil ke folder 'bobot' di setiap titik penyimpanan",
+  "Refresh": "Segarkan daftar suara, jalur indeks, dan file audio",
+  "Unload voice to save GPU memory": "Bongkar suara untuk menghemat memori GPU:",
+  "Select Speaker/Singer ID:": "Pilih ID Pembicara/Penyanyi:",
+  "Recommended +12 key for male to female conversion, and -12 key for female to male conversion. If the sound range goes too far and the voice is distorted, you can also adjust it to the appropriate range by yourself.": "Direkomendasikan kunci +12 untuk konversi pria ke wanita, dan -12 kunci untuk konversi wanita ke pria. Jika rentang suara terlalu jauh dan suaranya terdistorsi, Anda juga dapat menyesuaikannya sendiri ke rentang yang sesuai.",
+  "Transpose (integer, number Fof semitones, raise by an octave: 12, lower by an octave: -12):": "Transpos (bilangan bulat, jumlah seminada, dinaikkan satu oktaf: 12, diturunkan satu oktaf: -12):",
+  "Enter the path of the audio file to be processed (default is the correct format example):": "Masukkan jalur file audio yang akan diproses (defaultnya adalah contoh format yang benar):",
+  "Select the pitch extraction algorithm:": "Pilih algoritma ekstraksi nada:",
+  "Mangio-Crepe Hop Length (Only applies to mangio-crepe): Hop length refers to the time it takes for the speaker to jump to a dramatic pitch. Lower hop lengths take more time to infer but are more pitch accurate.": "Panjang Hop Mangio-Crepe (Hanya berlaku untuk mangio-crepe): Panjang hop mengacu pada waktu yang dibutuhkan pembicara untuk melompat ke nada dramatis. Panjang lompatan yang lebih rendah membutuhkan lebih banyak waktu untuk menyimpulkan tetapi nadanya lebih akurat.",
+  "Feature search dataset file path": "Jalur file kumpulan data pencarian fitur",
+  "If >=3: apply median filtering to the harvested pitch results. The value represents the filter radius and can reduce breathiness.": "Jika >=3: terapkan pemfilteran median pada hasil pitch yang dipanen. Nilai tersebut mewakili radius filter dan dapat mengurangi sesak napas.",
+  "Path to the feature index file. Leave blank to use the selected result from the dropdown:": "Jalur ke file indeks fitur. Biarkan kosong untuk menggunakan hasil yang dipilih dari dropdown:",
+  "Auto-detect index path and select from the dropdown:": "Deteksi jalur indeks secara otomatis dan pilih dari dropdown",
+  "Path to feature file:": "Jalur ke file fitur:",
+  "Search feature ratio:": "Rasio fitur pencarian:",
+  "Resample the output audio in post-processing to the final sample rate. Set to 0 for no resampling:": "Sampel ulang audio keluaran dalam pasca-pemrosesan ke laju sampel akhir. Setel ke 0 tanpa pengambilan sampel ulang:",
+  "Use the volume envelope of the input to replace or mix with the volume envelope of the output. The closer the ratio is to 1, the more the output envelope is used:": "Gunakan amplop volume masukan untuk menggantikan atau mencampur dengan amplop volume keluaran. Semakin dekat rasionya ke 1, semakin banyak amplop keluaran yang digunakan:",
+  "Protect voiceless consonants and breath sounds to prevent artifacts such as tearing in electronic music. Set to 0.5 to disable. Decrease the value to increase protection, but it may reduce indexing accuracy:": "Lindungi konsonan tak bersuara dan bunyi napas untuk mencegah artefak seperti robek pada musik elektronik. Setel ke 0,5 untuk menonaktifkan. Turunkan nilainya untuk meningkatkan perlindungan, namun hal ini dapat mengurangi akurasi pengindeksan:",
+  "F0 curve file (optional). One pitch per line. Replaces the default F0 and pitch modulation:": "File kurva F0 (opsional). Satu nada per baris. Menggantikan F0 dan modulasi nada default:",
+  "Convert": "Mengubah",
+  "Output information:": "Informasi keluaran",
+  "Export audio (click on the three dots in the lower right corner to download)": "Ekspor audio (klik tiga titik di pojok kanan bawah untuk mengunduh)",
+  "Batch conversion. Enter the folder containing the audio files to be converted or upload multiple audio files. The converted audio will be output in the specified folder (default: 'opt').": "Konversi batch. Masuk ke folder yang berisi file audio yang akan dikonversi atau unggah beberapa file audio. Audio yang dikonversi akan dikeluarkan di folder yang ditentukan (default: 'opt').",
+  "Specify output folder:": "Tentukan folder keluaran:",
+  "Enter the path of the audio folder to be processed (copy it from the address bar of the file manager):": "Masukkan jalur folder audio yang akan diproses (salin dari bilah alamat pengelola file):",
+  "You can also input audio files in batches. Choose one of the two options. Priority is given to reading from the folder.": "Anda juga dapat memasukkan file audio secara berkelompok. Pilih salah satu dari dua opsi. Prioritas diberikan untuk membaca dari folder.",
+  "Export file format": "Ekspor format file",
+  "UVR5": "UVR5",
+  "Enter the path of the audio folder to be processed:": "Masukkan jalur folder audio yang akan diproses:",
+  "Model": "Model",
+  "Vocal Extraction Aggressive": "Ekstraksi Vokal Agresif",
+  "Specify the output folder for vocals:": "Tentukan folder keluaran untuk vokal:",
+  "Specify the output folder for accompaniment:": "Tentukan folder keluaran untuk pengiring:",
+  "Train": "Kereta",
+  "Enter the model name:": "Masukkan nama model:",
+  "Target sample rate:": "Tingkat sampel target:",
+  "Whether the model has pitch guidance (required for singing, optional for speech):": "Apakah model memiliki panduan nada (wajib untuk bernyanyi, opsional untuk berbicara):",
+  "Version": "Versi: kapan",
+  "Number of CPU processes:": "Jumlah proses CPU yang digunakan untuk ekstraksi nada dan pemrosesan data:",
+  "Enter the path of the training folder:": "Masukkan jalur folder pelatihan:",
+  "Specify the model ID:": "Silakan tentukan ID model:",
+  "Auto detect audio path and select from the dropdown:": "Deteksi otomatis jalur audio dan pilih dari dropdown:",
+  "Add audio's name to the path to the audio file to be processed (default is the correct format example) Remove the path to use an audio from the dropdown list:": "Tambahkan nama audio ke jalur ke file audio yang akan diproses (standarnya adalah contoh format yang benar) Hapus jalur untuk menggunakan audio dari daftar dropdown:",
+  "Advanced Settings": "Pengaturan lanjutan",
+  "Settings": "Pengaturan",
+  "Status:": "Status:",
+  "Process data": "Data proses",
+  "Drag your audio here:": "Seret audio Anda ke sini dan tekan tombol segarkan",
+  "Or record an audio:": "Atau rekam audio.",
+  "Formant shift inference audio": "Audio inferensi pergeseran formant",
+  "Used for male to female and vice-versa conversions": "Digunakan untuk konversi pria ke wanita dan sebaliknya",
+  "Provide the GPU index(es) separated by '-', like 0-1-2 for using GPUs 0, 1, and 2:": "Harap berikan indeks GPU yang dipisahkan dengan '-', seperti 0-1-2 untuk menggunakan GPU 0, 1, dan 2:",
+  "GPU Information:": "Informasi GPU",
+  "Feature extraction": "Ekstraksi fitur",
+  "Save frequency:": "Simpan frekuensi:",
+  "Training epochs:": "Zaman pelatihan:",
+  "Batch size per GPU:": "Ukuran batch per GPU:",
+  "Save only the latest '.ckpt' file to save disk space:": "Simpan hanya file '.ckpt' terbaru untuk menghemat ruang disk:",
+  "No": "TIDAK",
+  "Save a small final model to the 'weights' folder at each save point:": "Simpan model akhir kecil ke folder 'bobot' di setiap titik penyimpanan:",
+  "Load pre-trained base model G path:": "Memuat jalur G model dasar terlatih:",
+  "Load pre-trained base model D path:": "Memuat jalur model D dasar yang telah dilatih sebelumnya:",
+  "Train model": "Model kereta api",
+  "Train feature index": "Indeks fitur kereta",
+  "One-click training": "Pelatihan sekali klik",
+  "Processing": "Pengolahan",
+  "Model fusion, can be used to test timbre fusion": "Fusi model, dapat digunakan untuk menguji fusi timbre",
+  "Path to Model A:": "Jalan menuju Model A:",
+  "Path to Model B:": "Jalan menuju Model B:",
+  "Weight for Model A:": "Berat untuk Model A:",
+  "Whether the model has pitch guidance:": "Apakah model memiliki panduan nada:",
+  "Model information to be placed:": "Informasi model yang akan ditempatkan:",
+  "Name:": "Nama model yang disimpan (tanpa ekstensi):",
+  "Model architecture version:": "Versi arsitektur model:",
+  "Fusion": "Fusi",
+  "Modify model information": "Ubah informasi model",
+  "Path to Model:": "Jalur Menuju Model:",
+  "Model information to be modified:": "Informasi model yang akan dimodifikasi:",
+  "Save file name:": "Simpan nama file:",
+  "Modify": "Memodifikasi",
+  "View model information": "Lihat informasi model",
+  "View": "Melihat",
+  "Model extraction": "Ekstraksi model (masukkan jalur model file besar di bawah folder 'logs'). Ini berguna jika Anda ingin menghentikan pelatihan di tengah jalan dan mengekstrak serta menyimpan file model kecil secara manual, atau jika Anda ingin menguji model perantara:",
+  "Name:": "Simpan nama:",
+  "Whether the model has pitch guidance (1: yes, 0: no):": "Apakah model memiliki panduan nada (1: ya, 0: tidak):",
+  "Extract": "Ekstrak",
+  "Export Onnx": "Ekspor Onnx",
+  "RVC Model Path:": "Jalur Model RVC:",
+  "Onnx Export Path:": "Jalur Ekspor Onnx:",
+  "MoeVS Model": "Model MoeVS",
+  "Export Onnx Model": "Ekspor Model Onnx",
+  "Load model": "Model beban",
+  "Hubert Model": "Model Hubert",
+  "Select the .pth file": "Pilih file .pth",
+  "Select the .index file": "Pilih file .index",
+  "Select the .npy file": "Pilih file .npy",
+  "Input device": "Alat input",
+  "Output device": "Perangkat keluaran",
+  "Audio device (please use the same type of driver)": "Perangkat audio (harap gunakan jenis driver yang sama)",
+  "Response threshold": "Ambang batas respons",
+  "Pitch settings": "Pengaturan nada",
+  "Whether to use note names instead of their hertz value. E.G. [C5, D6] instead of [523.25, 1174.66]Hz": "Apakah akan menggunakan nama nada dan bukan nilai hertznya. MISALNYA. [C5, D6] bukannya [523.25, 1174.66]Hz",
+  "Index Rate": "Tingkat Indeks",
+  "General settings": "Pengaturan Umum",
+  "Sample length": "Panjang sampel",
+  "Fade length": "Panjang pudar",
+  "Extra inference time": "Waktu inferensi ekstra",
+  "Input noise reduction": "Pengurangan kebisingan masukan",
+  "Output noise reduction": "Pengurangan kebisingan keluaran",
+  "Performance settings": "Pengaturan kinerja",
+  "Start audio conversion": "Mulai konversi audio",
+  "Stop audio conversion": "Hentikan konversi audio",
+  "Inference time (ms):": "Waktu inferensi (ms):",
+  "Select the pth file": "Pilih file pth",
+  "Select the .index file:": "Pilih file indeks",
+  "The hubert model path must not contain Chinese characters": "Jalur model hubert tidak boleh berisi karakter China",
+  "The pth file path must not contain Chinese characters.": "Jalur file pth tidak boleh berisi karakter Cina.",
+  "The index file path must not contain Chinese characters.": "Jalur file indeks tidak boleh berisi karakter Cina.",
+  "Step algorithm": "Algoritma langkah",
+  "Number of epoch processes": "Jumlah proses zaman",
+  "Lowest points export": "Ekspor poin terendah",
+  "How many lowest points to save:": "Berapa banyak poin terendah yang harus disimpan",
+  "Export lowest points of a model": "Ekspor titik terendah suatu model",
+  "Output models:": "Model keluaran",
+  "Stats of selected models:": "Statistik model yang dipilih",
+  "Custom f0 [Root pitch] File": "File f0 [Root pitch] khusus",
+  "Min pitch:": "nada minimal",
+  "Specify minimal pitch for inference [HZ]": "Tentukan nada minimal untuk inferensi [HZ]",
+  "Specify minimal pitch for inference [NOTE][OCTAVE]": "Tentukan nada minimal untuk inferensi [CATATAN][OCTAVE]",
+  "Max pitch:": "Nada maksimal",
+  "Specify max pitch for inference [HZ]": "Tentukan nada maksimal untuk inferensi [HZ]",
+  "Specify max pitch for inference [NOTE][OCTAVE]": "Tentukan nada maksimal untuk inferensi [CATATAN][OCTAVE]",
+  "Browse presets for formanting": "Telusuri preset untuk pembentukan",
+  "Presets are located in formantshiftcfg/ folder": "Preset terletak di folder formantshiftcfg/",
+  "Default value is 1.0": "Nilai defaultnya adalah 1,0",
+  "Quefrency for formant shifting": "Quefrency untuk pergeseran formant",
+  "Timbre for formant shifting": "Timbre untuk pergeseran formant",
+  "Apply": "Menerapkan",
+  "Single": "Lajang",
+  "Batch": "Kelompok",
+  "Separate YouTube tracks": "Pisahkan trek YouTube",
+  "Download audio from a YouTube video and automatically separate the vocal and instrumental tracks": "Unduh audio dari video YouTube dan pisahkan trek vokal dan instrumental secara otomatis",
+  "Extra": "Tambahan",
+  "Merge": "Menggabungkan",
+  "Merge your generated audios with the instrumental": "Gabungkan audio yang Anda hasilkan dengan instrumental",
+  "Choose your instrumental:": "Pilih instrumen Anda",
+  "Choose the generated audio:": "Pilih audio yang dihasilkan",
+  "Combine": "Menggabungkan",
+  "Download and Separate": "Unduh dan Pisahkan",
+  "Enter the YouTube link:": "Masukkan tautan youtube",
+  "This section contains some extra utilities that often may be in experimental phases": "Bagian ini berisi beberapa utilitas tambahan yang mungkin sering berada dalam tahap percobaan",
+  "Merge Audios": "Gabungkan Audio",
+  "Audio files have been moved to the 'audios' folder.": "File audio telah dipindahkan ke folder 'audios'.",
+  "Downloading audio from the video...": "Mengunduh audio dari video...",
+  "Audio downloaded!": "Unduhan audio!",
+  "An error occurred:": "Terjadi kesalahan:",
+  "Separating audio...": "Memisahkan audio...",
+  "File moved successfully.": "File berhasil dipindahkan.",
+  "Finished!": "Selesai!",
+  "The source file does not exist.": "File sumber tidak ada.",
+  "Error moving the file:": "Kesalahan saat memindahkan file:",
+  "Downloading {name} from drive": "Mengunduh {name} dari drive",
+  "The attempt to download using Drive didn't work": "Upaya mengunduh menggunakan Drive tidak berhasil",
+  "Error downloading the file: {str(e)}": "Kesalahan saat mengunduh berkas: {str(e)}",
+  "Downloading {name} from mega": "Mengunduh {name} dari mega",
+  "Downloading {name} from basic url": "Mengunduh {name} dari url dasar",
+  "Download Audio": "Unduh Audio",
+  "Download audios of any format for use in inference (recommended for mobile users).": "Mengunduh audio dalam format apa pun untuk digunakan dalam inferensi (disarankan untuk pengguna seluler)",
+  "Any ConnectionResetErrors post-conversion are irrelevant and purely visual; they can be ignored.\n": "Setiap ConnectionResetErrors pasca-konversi tidak relevan dan murni visual; mereka dapat diabaikan.",
+  "Processed audio saved at: ": "Audio yang diproses disimpan di:",
+  "Conversion complete!": "Konversi selesai!",
+  "Reverb": "Berkumandang",
+  "Compressor": "Kompresor",
+  "Noise Gate": "Gerbang Kebisingan",
+  "Volume": "Volume",
+  "Drag the audio here and click the Refresh button": "Seret audio ke sini dan klik tombol Refresh",
+  "Select the generated audio": "Pilih audio yang dihasilkan",
+  "Volume of the instrumental audio:": "Volume audio instrumental",
+  "Volume of the generated audio:": "Volume audio yang dihasilkan",
+  "### Add the effects": "### Tambahkan efeknya",
+  "Starting audio conversion... (This might take a moment)": "Memulai konversi audio... (Ini mungkin memerlukan waktu sebentar)",
+  "TTS Model:": "Suara TTS",
+  "TTS": "TTS",
+  "TTS Method:": "Metode TTS",
+  "Audio TTS:": "Audio TTS:",
+  "Audio RVC:": "Model Audio"
+}
diff --git a/i18n/locale/it_IT.json b/i18n/locale/it_IT.json
new file mode 100644
index 0000000000000000000000000000000000000000..70afb3f72c1ff512aaf613c2d42d302fc77722c9
--- /dev/null
+++ b/i18n/locale/it_IT.json
@@ -0,0 +1,252 @@
+{
+  "Unfortunately, there is no compatible GPU available to support your training.": "Purtroppo non è disponibile una GPU compatibile per supportare l'addestramento.",
+  "Yes": "Sì",
+  "Select your dataset:": "Seleziona il tuo dataset:",
+  "Update list": "Aggiorna la lista",
+  "Download Model": "Scarica il modello",
+  "Download Backup": "Scarica  il backup",
+  "Download Dataset": "Scarica il dataset",
+  "Download": "Scarica",
+  "Url:": "Link:",
+  "Build the index before saving.": "Genera l'indice prima di salvarlo.",
+  "Save your model once the training ends.": "Salva il modello una volta terminato il training.",
+  "Save type": "Metodo di salvataggio:",
+  "Save model": "Salva modello",
+  "Choose the method": "Scegli il metodo",
+  "Save all": "Salva tutto",
+  "Save D and G": "Salva i file G e D",
+  "Save voice": "Salva il modello",
+  "Downloading the file: ": "Scaricamento del file: ",
+  "Stop training": "Interrompi training",
+  "Too many users have recently viewed or downloaded this file": "Troppi utenti hanno visto o scaricato di recente questo file",
+  "Cannot get file from this private link": "Impossibile ottenere il file, il link è privato",
+  "Full download": "Download completato",
+  "An error occurred downloading": "Si è verificato un errore durante il download",
+  "Model saved successfully": "Modello salvato con successo",
+  "Saving the model...": "Salvando il modello...",
+  "Saved without index...": "Salvataggio senza file .index...",
+  "Saved without inference model...": "Salvataggio senza modello di inferenza...",
+  "An error occurred saving the model": "Si è verificato un errore durante il salvataggio del modello",
+  "The model you want to save does not exist, be sure to enter the correct name.": "Il modello che vuoi salvare non esiste, assicurati di inserire il nome corretto.",
+  "The file could not be downloaded.": "Impossibile scaricare il file.",
+  "Unzip error.": "Estrazione non riuscita.",
+  "Path to your added.index file (if it didn't automatically find it)": "Percorso del tuo file added.index (se non l'ha trovato automaticamente)",
+  "It has been downloaded successfully.": "Scaricato con successo.",
+  "Proceeding with the extraction...": "Proseguo con l'estrazione...",
+  "The Backup has been uploaded successfully.": "Il backup è stato caricato correttamente.",
+  "The Dataset has been loaded successfully.": "Il dataset è stato caricato correttamente.",
+  "The Model has been loaded successfully.": "Il modello è stato caricato correttamente.",
+  "It is used to download your inference models.": "Serve per scaricare i suoi modelli di inferenza.",
+  "It is used to download your training backups.": "Serve per scaricare i backup degi training.",
+  "Download the dataset with the audios in a compatible format (.wav/.flac) to train your model.": "Scarica il dataset con gli audio in un formato compatibile (.wav/.flac) per trainare il tuo modello.",
+  "No relevant file was found to upload.": "Non è stato trovato alcun file rilevante da caricare.",
+  "The model works for inference, and has the .index file.": "Il modello funziona per l'inferenza ed ha il file .index.",
+  "The model works for inference, but it doesn't have the .index file.": "Il modello funziona per l'inferenza, ma non ha il file .index.",
+  "This may take a few minutes, please wait...": "Potrebbe richiedere alcuni minuti, attendere per favore.",
+  "Resources": "Risorse",
+  "Step 1: Processing data": "Fase 1: Elaborazione dei dati",
+  "Step 2: Skipping pitch extraction": "Fase 2: Estrazione del pitch",
+  "Step 3: Extracting features": "Fase 3: Estrazione delle caratteristiche",
+  "Step 4: Model training started": "Fase 4: Training del modello",
+  "Step 5: Export lowest points on a graph of the model": "Fase 5: Esportare i punti più bassi su un grafico del modello",
+  "Training is done, check train.log": "Il training è terminato, controlla train.log.",
+  "All processes have been completed!": "Tutti i processi sono stati completati!",
+  "Model Inference": "Inferenza del modello",
+  "Inferencing voice:": "Modello vocale:",
+  "Model_Name": "Nome_Modello",
+  "Dataset_Name": "Nome_Dataset",
+  "Whether the model has pitch guidance.": "Indica se il modello ha una guida tonale.",
+  "Whether to save only the latest .ckpt file to save hard drive space": "Indica se salvare solo l'ultimo file .ckpt per risparmiare spazio sul disco rigido",
+  "Cache all training sets to GPU memory. Caching small datasets (less than 10 minutes) can speed up training": "La memorizzazione nella cache di piccoli dataset (meno di 10 minuti) può accelerare l'allenamento",
+  "Save a small final model to the 'weights' folder at each save point": "Salva un piccolo modello finale nella cartella 'weights' in ogni punto di salvataggio",
+  "Refresh": "Aggiorna la lista dei modelli, il percorso del file .index e gli audio",
+  "Unload voice to save GPU memory": "Rimuovi modelli per risparmiare memoria GPU",
+  "Select Speaker/Singer ID:": "Seleziona ID della persona che parla o del cantante:",
+  "Transpose (integer, number of semitones, raise by an octave: 12, lower by an octave: -12):": "Trasporre (numero intero, numero di semitoni, per alzare di un'ottava: 12, per scendere di un'ottava: -12):",
+  "Recommended +12 key for male to female conversion, and -12 key for female to male conversion. If the sound range goes too far and the voice is distorted, you can also adjust it to the appropriate range by yourself.": "Si consiglia +12 per la conversione da uomo a donna e -12 per la conversione da donna a uomo. Se la gamma sonora va troppo oltre e la voce è distorta, puoi anche regolarla tu stesso nella gamma appropriata.",
+  "Enter the path of the audio file to be processed (default is the correct format example):": "Inserisci il percorso del file audio da elaborare (l'esempio di formato corretto è quello predefinito):",
+  "Select the pitch extraction algorithm:": "Selezionare l'algoritmo di estrazione del pitch:",
+  "Mangio-Crepe Hop Length (Only applies to mangio-crepe): Hop length refers to the time it takes for the speaker to jump to a dramatic pitch. Lower hop lengths take more time to infer but are more pitch accurate.": "Lunghezza di salto di Mangio-Crepe (si applica solo a mangio-crepe): la lunghezza di salto si riferisce al tempo impiegato dal parlante per saltare in una tonalità drammatica. Le lunghezze di salto più basse richiedono più tempo per essere dedotte, ma sono più precise nel tono.",
+  "Feature search dataset file path": "Percorso del file del dataset di ricerca delle caratteristiche",
+  "If >=3: apply median filtering to the harvested pitch results. The value represents the filter radius and can reduce breathiness.": "Se >=3: applica un filtro di media usati con il metodo di tonalità harvest. Il valore rappresenta il raggio del filtro e può ridurre la traspirazione.",
+  "Path to the feature index file. Leave blank to use the selected result from the dropdown:": "Percorso al file .index. Lasciarlo vuoto per utilizzare il risultato selezionato dal menu a tendina:",
+  "Auto-detect index path and select from the dropdown:": "Rilevare automaticamente il percorso del file .index e selezionare dal menu a tendina:",
+  "Path to feature file:": "Percorso al file delle caratteristiche:",
+  "Search feature ratio:": "Proporzione della caratteristiche di ricerca:",
+  "Resample the output audio in post-processing to the final sample rate. Set to 0 for no resampling:": "Ricampionare l'audio in uscita in post-elaborazione alla frequenza di campionamento finale. Impostare a 0 per non campionare di nuovo:",
+  "Use the volume envelope of the input to replace or mix with the volume envelope of the output. The closer the ratio is to 1, the more the output envelope is used:": "Utilizzare l'inviluppo del volume dell'ingresso per sostituire o mescolare con l'inviluppo del volume dell'uscita. Più il rapporto è vicino a 1, più verrà utilizzato l'inviluppo di uscita:",
+  "Protect voiceless consonants and breath sounds to prevent artifacts such as tearing in electronic music. Set to 0.5 to disable. Decrease the value to increase protection, but it may reduce indexing accuracy:": "Proteggi le consonanti sorde e i suoni del respiro per evitare artefatti come la lacerazione nella musica elettronica. Impostare su 0.5 per disattivare. Diminuire il valore per aumentare la protezione, ma può ridurre la precisione dell'indicizzazione:",
+  "F0 curve file (optional). One pitch per line. Replaces the default F0 and pitch modulation:": "File curva F0 (opzionale). Un passo per riga. Sostituisce la modulazione di passo e F0 di default:",
+  "Convert": "Conversione",
+  "Output information:": "Informazioni in uscita",
+  "Export audio (click on the three dots in the lower right corner to download)": "Esporta audio (clicca sui tre puntini nell'angolo in basso a destra per scaricare)",
+  "Batch conversion. Enter the folder containing the audio files to be converted or upload multiple audio files. The converted audio will be output in the specified folder (default: 'opt').": "Conversione batch. Inserire la cartella contenente i file audio da convertire o caricare più file audio. L'audio convertito verrà emesso nella cartella specificata (default: 'opt').",
+  "Specify output folder:": "Specifica cartella di output:",
+  "Enter the path of the audio folder to be processed (copy it from the address bar of the file manager):": "Inserire il percorso della cartella audio da elaborare (copiarla dalla barra degli indirizzi del file manager):",
+  "You can also input audio files in batches. Choose one of the two options. Priority is given to reading from the folder.": "Puoi anche inserire file audio in batch. Scegli una delle due opzioni. Viene data priorità alla lettura della cartella.",
+  "Export file format:": "Formato file di esportazione:",
+  "UVR5": "UVR5",
+  "Enter the path of the audio folder to be processed:": "Inserire il percorso della cartella audio da elaborare:",
+  "Model:": "Modello:",
+  "Vocal Extraction Aggressive": "Estrazione vocale aggressiva",
+  "Specify the output folder for vocals:": "Specificare la cartella di output per le voci:",
+  "Specify the output folder for accompaniment:": "Specificare la cartella di uscita per l'accompagnamento:",
+  "Train": "Addestramento",
+  "Enter the model name:": "Inserisci il nome del modello:",
+  "Target sample rate:": "Tasso di campionamento target:",
+  "Whether the model has pitch guidance (required for singing, optional for speech):": "Se il modello ha una guida di pitch (richiesto per cantare, opzionale per parlare):",
+  "Version:": "Versione:",
+  "Number of CPU processes:": "Numero di processi della CPU:",
+  "Enter the path of the training folder:": "Inserire il percorso della cartella del training:",
+  "Specify the model ID:": "Specificare l'ID del modello:",
+  "Auto detect audio path and select from the dropdown:": "Rileva automaticamente il percorso audio e seleziona dal menu a tendina:",
+  "Add audio's name to the path to the audio file to be processed (default is the correct format example) Remove the path to use an audio from the dropdown list:": "Aggiungere il nome dell'audio al percorso del file audio da elaborare (l'esempio di formato corretto è quello predefinito) Eliminare il percorso per utilizzare un audio dall'elenco a discesa:",
+  "Advanced Settings": "Impostazioni avanzate",
+  "Settings": "Impostazioni",
+  "Status:": "Stato:",
+  "Process data": "Elabora dati",
+  "Drag your audio here:": "Trascina il tuo audio qui:",
+  "Or record an audio:": "Oppure registra un audio:",
+  "Formant shift inference audio": "Audio di inferenza di spostamento formante",
+  "Used for male to female and vice-versa conversions": "Viene utilizzato per le conversioni da uomo a donna e viceversa",
+  "Provide the GPU index(es) separated by '-', like 0-1-2 for using GPUs 0, 1, and 2:": "Fornire gli indici GPU separati da '-', come 0-1-2 per utilizzare le GPU 0, 1 e 2:",
+  "GPU Information:": "Informazioni GPU:",
+  "Feature extraction": "Estrazione delle caratteristiche",
+  "Save frequency:": "Frequenza di salvataggio:",
+  "Training epochs:": "Epoch di addestramento:",
+  "Batch size per GPU:": "Dimensione del lotto per GPU:",
+  "Save only the latest '.ckpt' file to save disk space:": "Salvare solo l'ultimo file '.ckpt' per risparmiare spazio su disco:",
+  "No": "No",
+  "Save a small final model to the 'weights' folder at each save point:": "Salvare un piccolo modello finale nella cartella \"pesi\" in ogni punto di salvataggio:",
+  "Load pre-trained base model G path:": "Carica percorso base modello G pre-allenato:",
+  "Load pre-trained base model D path:": "Percorso del modello D base di ricarica pre-allenata:",
+  "Train model": "Allena modello",
+  "Train feature index": "Allena l'indice delle caratteristiche",
+  "One-click training": "Allenamento con un clic",
+  "Processing": "Elaborazione",
+  "Model fusion, can be used to test timbre fusion": "Modello di fusione, può essere utilizzato per testare la fusione del timbro",
+  "Path to Model A:": "Percorso al Modello A:",
+  "Path to Model B:": "Percorso al Modello B:",
+  "Weight for Model A:": "Peso per il modello A:",
+  "Whether the model has pitch guidance:": "Indica se il modello ha una guida di tono:",
+  "Model information to be placed:": "Informazioni sul modello da mettere:",
+  "Name:": "Nome:",
+  "Model architecture version:": "Versione dell'architettura del modello:",
+  "Fusion": "Fusione",
+  "Modify model information": "Modifica informazioni modello",
+  "Path to Model:": "Percorso al modello:",
+  "Model information to be modified:": "Informazioni sul modello da modificare:",
+  "Save file name:": "Salva nome file:",
+  "Modify": "Modifica",
+  "View model information": "Visualizza informazioni sul modello",
+  "View": "Vedi",
+  "Model extraction": "Estrazione del modello",
+  "Whether the model has pitch guidance (1: yes, 0: no):": "Indica se il modello ha una guida di tono (1: sì, 0: no):",
+  "Extract": "Estrai",
+  "Export Onnx": "Esporta Onnx",
+  "RVC Model Path:": "Percorso del modello RVC:",
+  "Onnx Export Path:": "Percorso di esportazione:",
+  "MoeVS Model": "Modello MoeVS",
+  "Export Onnx Model": "Esporta modello",
+  "Load model": "Carica modello",
+  "Hubert Model": "Modello Hubert",
+  "Select the .pth file": "Seleziona il file .pth",
+  "Select the .index file": "Seleziona il file .index",
+  "Select the .npy file": "Seleziona il file .npy",
+  "Input device": "Dispositivo di input",
+  "Output device": "Dispositivo di output",
+  "Audio device (please use the same type of driver)": "Dispositivo audio (utilizzare lo stesso tipo di dispositivo)",
+  "Response threshold": "Soglia di risposta",
+  "Pitch settings": "Impostazioni di tonalità (pitch)",
+  "Whether to use note names instead of their hertz value. E.G. [C5, D6] instead of [523.25, 1174.66]Hz": "Indica se i nomi delle note devono essere utilizzati al posto del loro valore di hertz. AD ESEMPIO, [C5, D6] anziché [523,25, 1174,66]Hz",
+  "Index Rate": "Tasso dell'indice",
+  "General settings": "Impostazioni generali",
+  "Sample length": "Lunghezza campione",
+  "Fade length": "Lunghezza sbiadimento/fade",
+  "Extra inference time": "Tempo di inferenza aggiuntivo",
+  "Input noise reduction": "Riduzione del rumore in ingresso",
+  "Output noise reduction": "Riduzione del rumore in uscita",
+  "Performance settings": "Impostazioni delle prestazioni",
+  "Start audio conversion": "Avvia conversione audio",
+  "Stop audio conversion": "Interrompi la conversione audio",
+  "Inference time (ms):": "Tempo di inferenza (ms):",
+  "Select the pth file": "Seleziona il file .pth",
+  "Select the .index file:": "Seleziona il file .index",
+  "The hubert model path must not contain Chinese characters": "Il percorso del modello hubert non deve contenere caratteri cinesi",
+  "The pth file path must not contain Chinese characters.": "Il percorso del file pth non deve contenere caratteri cinesi.",
+  "The index file path must not contain Chinese characters.": "Il percorso del file index non deve contenere caratteri cinesi.",
+  "Step algorithm": "Algoritmo dei passi",
+  "Number of epoch processes": "Numero di processi dell'epoch",
+  "Lowest points export": "Esportazione dei punti più bassi",
+  "How many lowest points to save:": "Quanti punti bassi vuoi salvare:",
+  "Export lowest points of a model": "Esporta i punti più bassi di un modello",
+  "Output models:": "Modelli di uscita:",
+  "Stats of selected models:": "Statistiche dei modelli selezionati:",
+  "Custom f0 [Root pitch] File": "File personalizzato f0 [Root pitch]",
+  "Min pitch:": "Tonalità minima:",
+  "Feature search database file path:": "Percorso del file del database di ricerca delle caratteristiche:",
+  "Specify minimal pitch for inference [HZ]": "Specificare tonalità minima per l'inferenza [HZ]",
+  "Specify minimal pitch for inference [NOTE][OCTAVE]": "Specificare tonalità minima per l'inferenza [NOTA][OTTAVA]",
+  "Max pitch:": "Tonalità massima:",
+  "Specify max pitch for inference [HZ]": "Specificare tonalità massima per l'inferenza [HZ]",
+  "Specify max pitch for inference [NOTE][OCTAVE]": "Specificare tonalità massima per l'inferenza [NOTA][OTTAVA]",
+  "Browse presets for formanting": "Sfoglia i preset per il formante",
+  "Presets are located in formantshiftcfg/ folder": "I preset si trovano nella cartella /formantshiftcfg/",
+  "Default value is 1.0": "Il valore di default è 1.0",
+  "Quefrency for formant shifting": "Frequenza per spostamento formanti",
+  "Timbre for formant shifting": "Timbro per il format shifting",
+  "Apply": "Applica",
+  "Single": "Singola",
+  "Batch": "Batch",
+  "Separate YouTube tracks": "Separa tracce di YouTube",
+  "Download audio from a YouTube video and automatically separate the vocal and instrumental tracks": "Scarica l'audio di un video da YouTube e separa automaticamente le tracce vocali e strumentali.",
+  "Extra": "Altro",
+  "Merge": "Unisci",
+  "Merge your generated audios with the instrumental": "Combina i tuoi audio generati con la base strumentale",
+  "Choose your instrumental:": "Scegli la base strumentale:",
+  "Choose the generated audio:": "Scegli l'audio generato:",
+  "Combine": "Combina",
+  "Download and Separate": "Scaricare e separare",
+  "Enter the YouTube link:": "Inserisci il link di YouTube:",
+  "This section contains some extra utilities that often may be in experimental phases": "Questa sezione contiene alcune utility aggiuntive che spesso possono essere in fase sperimentale",
+  "Merge Audios": "Unisci audio",
+  "Audio files have been moved to the 'audios' folder.": "I file audio sono stati spostati nella cartella 'audios'.",
+  "Downloading audio from the video...": "Scaricamento audio del video in corso...",
+  "Audio downloaded!": "Audio scaricato!",
+  "An error occurred:": "Si è verificato un errore:",
+  "Separating audio...": "Separazione audio in corso...",
+  "File moved successfully.": "Il file è stato spostato correttamente",
+  "Finished!": "Finito!",
+  "The source file does not exist.": "Il file sorgente non esiste.",
+  "Error moving the file:": "Errore durante lo spostamento del file:",
+  "Downloading {name} from drive": "Download di {name} da Google Drive",
+  "The attempt to download using Drive didn't work": "Il tentativo di download con Drive non ha funzionato",
+  "Error downloading the file: {str(e)}": "Errore durante il download del file: {str(e)}",
+  "Downloading {name} from mega": "Download di {name} da MEGA",
+  "Downloading {name} from basic url": "Download di {name} dall'URL di base",
+  "Download Audio": "Scarica Audio",
+  "Download audios of any format for use in inference (recommended for mobile users).": "Scarica audio di qualsiasi formato per l'uso in inferenza (consigliato per utenti mobili).",
+  "Any ConnectionResetErrors post-conversion are irrelevant and purely visual; they can be ignored.\n": "Qualsiasi post-conversione di ConnectionResetErrors è irrilevante e puramente visiva; può essere ignorata.",
+  "Processed audio saved at: ": "Audio elaborato salvato in:",
+  "Conversion complete!": "Conversione completata",
+  "Reverb": "Riverbero",
+  "Compressor": "Compressore",
+  "Noise Gate": "Riduzione del Rumore",
+  "Volume": "Volume",
+  "Drag the audio here and click the Refresh button": "Trascina l'audio qui e fai clic sul pulsante Aggiorna",
+  "Select the generated audio": "Seleziona l'audio generato",
+  "Volume of the instrumental audio:": "Volume della base strumentale:",
+  "Volume of the generated audio:": "Volume dell'audio generato:",
+  "### Audio settings:": "### Impostazioni audio:",
+  "### Instrumental settings:": "### Impostazioni base strumentale:",
+  "### Add the effects:": "### Aggiungi gli effetti:",
+  "Name for saving": "Nome salvataggio",
+  "Path to model": "Percorso al modello",
+  "Model information to be placed": "Informazioni sul modello da modificare",
+  "Starting audio conversion... (This might take a moment)": "Avvio conversione audio... (Questo potrebbe richiedere un po' di tempo)",
+  "TTS Model:": "Voci TTS",
+  "TTS": "TTS",
+  "TTS Method:": "Metodo TTS",
+  "Audio TTS:": "Audio TTS:",
+  "Audio RVC:": "Modello Audio"
+}
diff --git a/i18n/locale/pt_PT.json b/i18n/locale/pt_PT.json
new file mode 100644
index 0000000000000000000000000000000000000000..1a08dded1bbc4cec458d01e355075cb2a7262093
--- /dev/null
+++ b/i18n/locale/pt_PT.json
@@ -0,0 +1,247 @@
+{
+  "Unfortunately, there is no compatible GPU available to support your training.": "Infelizmente, não há GPU compatível disponível para apoiar o seu treinamento.",
+  "Yes": "Sim",
+  "Select your dataset:": "Selecione seu conjunto de dados.",
+  "Update list": "Lista de atualização.",
+  "Download Model": "Baixar modelo",
+  "Download Backup": "Baixar cópia de segurança",
+  "Download Dataset": "Baixar conjunto de dados",
+  "Download": "Download",
+  "Url:": "URL:",
+  "Build the index before saving.": "Crie o índice antes de salvar.",
+  "Save your model once the training ends.": "Salve seu modelo quando o treinamento terminar.",
+  "Save type": "Salvar tipo",
+  "Save model": "Salvar modelo",
+  "Choose the method": "Escolha o método",
+  "Save all": "Salvar tudo",
+  "Save D and G": "Salve D e G",
+  "Save voice": "Salvar voz",
+  "Downloading the file: ": "Baixando o arquivo:",
+  "Stop training": "Pare de treinar",
+  "Too many users have recently viewed or downloaded this file": "Muitos usuários visualizaram ou baixaram este arquivo recentemente",
+  "Cannot get file from this private link": "Não é possível obter o arquivo deste link privado",
+  "Full download": "Download completo",
+  "An error occurred downloading": "Ocorreu um erro ao baixar",
+  "Model saved successfully": "Modelo salvo com sucesso",
+  "Saving the model...": "Salvando o modelo...",
+  "Saved without index...": "Salvo sem índice...",
+  "model_name": "nome_modelo",
+  "Saved without inference model...": "Salvo sem modelo de inferência...",
+  "An error occurred saving the model": "Ocorreu um erro ao salvar o modelo",
+  "The model you want to save does not exist, be sure to enter the correct name.": "O modelo que você deseja salvar não existe, certifique-se de inserir o nome correto.",
+  "The file could not be downloaded.": "O arquivo não pôde ser baixado.",
+  "Unzip error.": "Erro ao descompactar.",
+  "Path to your added.index file (if it didn't automatically find it)": "Caminho para o seu arquivo add.index (se não o encontrou automaticamente)",
+  "It has been downloaded successfully.": "Ele foi baixado com sucesso.",
+  "Proceeding with the extraction...": "Prosseguindo com a extração...",
+  "The Backup has been uploaded successfully.": "O backup foi carregado com sucesso.",
+  "The Dataset has been loaded successfully.": "O conjunto de dados foi carregado com sucesso.",
+  "The Model has been loaded successfully.": "O modelo foi carregado com sucesso.",
+  "It is used to download your inference models.": "Ele é usado para baixar seus modelos de inferência.",
+  "It is used to download your training backups.": "Ele é usado para baixar seus backups de treinamento.",
+  "Download the dataset with the audios in a compatible format (.wav/.flac) to train your model.": "Baixe o conjunto de dados com os áudios em formato compatível (.wav/.flac) para treinar seu modelo.",
+  "No relevant file was found to upload.": "Nenhum arquivo relevante foi encontrado para upload.",
+  "The model works for inference, and has the .index file.": "O modelo funciona para inferência e possui o arquivo .index.",
+  "The model works for inference, but it doesn't have the .index file.": "O modelo funciona para inferência, mas não possui o arquivo .index.",
+  "This may take a few minutes, please wait...": "Isso pode levar alguns minutos, aguarde...",
+  "Resources": "Recursos",
+  "Step 1: Processing data": "Etapa 1: Processamento de dados",
+  "Step 2: Skipping pitch extraction": "Passo 2a: Ignorando a extração do tom",
+  "Step 3: Extracting features": "Etapa 2b: Extraindo recursos",
+  "Step 4: Model training started": "Etapa 3a: treinamento do modelo iniciado",
+  "Step 5: Export lowest points on a graph of the model": "Etapa 4: Exportar os pontos mais baixos em um gráfico do modelo",
+  "Training is done, check train.log": "O treinamento foi concluído, verifique train.log",
+  "All processes have been completed!": "Todos os processos foram concluídos!",
+  "Model Inference": "Inferência de modelo",
+  "Inferencing voice:": "Inferência de voz:",
+  "Model_Name": "Nome_modelo",
+  "Dataset_Name": "Conjunto de dados_Nome",
+  "Whether the model has pitch guidance.": "Se o modelo tem orientação de pitch.",
+  "Whether to save only the latest .ckpt file to save hard drive space": "Se deseja salvar apenas o arquivo .ckpt mais recente para economizar espaço no disco rígido",
+  "Cache all training sets to GPU memory. Caching small datasets (less than 10 minutes) can speed up training": "Armazene em cache todos os conjuntos de treinamento na memória da GPU. Armazenar pequenos conjuntos de dados em cache (menos de 10 minutos) pode acelerar o treinamento",
+  "Save a small final model to the 'weights' folder at each save point": "Salve um pequeno modelo final na pasta 'pesos' em cada ponto de salvamento",
+  "Refresh": "Atualizar lista de voz, caminho de índice e arquivos de áudio",
+  "Unload voice to save GPU memory": "Descarregue a voz para economizar memória da GPU:",
+  "Select Speaker/Singer ID:": "Selecione o ID do palestrante/cantor:",
+  "Recommended +12 key for male to female conversion, and -12 key for female to male conversion. If the sound range goes too far and the voice is distorted, you can also adjust it to the appropriate range by yourself.": "Chave recomendada +12 para conversão de homem para mulher e chave -12 para conversão de mulher para homem. Se o alcance do som for muito longe e a voz estiver distorcida, você também poderá ajustá-lo para o alcance apropriado.",
+  "Transpose (integer, number Fof semitones, raise by an octave: 12, lower by an octave: -12):": "Transpor (inteiro, número de semitons, aumentar uma oitava: 12, diminuir uma oitava: -12):",
+  "Enter the path of the audio file to be processed (default is the correct format example):": "Digite o caminho do arquivo de áudio a ser processado (o padrão é o exemplo de formato correto):",
+  "Select the pitch extraction algorithm:": "Selecione o algoritmo de extração de pitch:",
+  "Mangio-Crepe Hop Length (Only applies to mangio-crepe): Hop length refers to the time it takes for the speaker to jump to a dramatic pitch. Lower hop lengths take more time to infer but are more pitch accurate.": "Comprimento do salto do Mangio-Crepe (aplica-se apenas ao mangio-crepe): A duração do salto refere-se ao tempo que leva para o locutor saltar para um tom dramático. Comprimentos de salto mais baixos levam mais tempo para serem inferidos, mas são mais precisos no tom.",
+  "Feature search dataset file path": "Caminho do arquivo do conjunto de dados de pesquisa de recursos",
+  "If >=3: apply median filtering to the harvested pitch results. The value represents the filter radius and can reduce breathiness.": "Se >=3: aplique filtragem mediana aos resultados de pitch colhidos. O valor representa o raio do filtro e pode reduzir a soprosidade.",
+  "Path to the feature index file. Leave blank to use the selected result from the dropdown:": "Caminho para o arquivo de índice de recursos. Deixe em branco para usar o resultado selecionado no menu suspenso:",
+  "Auto-detect index path and select from the dropdown:": "Detecte automaticamente o caminho do índice e selecione no menu suspenso",
+  "Path to feature file:": "Caminho para o arquivo de recurso:",
+  "Search feature ratio:": "Proporção de recursos de pesquisa:",
+  "Resample the output audio in post-processing to the final sample rate. Set to 0 for no resampling:": "Faça uma nova amostragem do áudio de saída no pós-processamento para a taxa de amostragem final. Defina como 0 para nenhuma reamostragem:",
+  "Use the volume envelope of the input to replace or mix with the volume envelope of the output. The closer the ratio is to 1, the more the output envelope is used:": "Use o envelope de volume da entrada para substituir ou mixar com o envelope de volume da saída. Quanto mais próxima a proporção estiver de 1, mais o envelope de saída será usado:",
+  "Protect voiceless consonants and breath sounds to prevent artifacts such as tearing in electronic music. Set to 0.5 to disable. Decrease the value to increase protection, but it may reduce indexing accuracy:": "Proteja consoantes surdas e sons respiratórios para evitar artefatos como lacrimejamento na música eletrônica. Defina como 0,5 para desativar. Diminua o valor para aumentar a proteção, mas poderá reduzir a precisão da indexação:",
+  "F0 curve file (optional). One pitch per line. Replaces the default F0 and pitch modulation:": "Arquivo de curva F0 (opcional). Um tom por linha. Substitui o F0 padrão e a modulação de pitch:",
+  "Convert": "Converter",
+  "Output information:": "Informações de saída",
+  "Export audio (click on the three dots in the lower right corner to download)": "Exportar áudio (clique nos três pontos no canto inferior direito para fazer o download)",
+  "Batch conversion. Enter the folder containing the audio files to be converted or upload multiple audio files. The converted audio will be output in the specified folder (default: 'opt').": "Conversão em lote. Entre na pasta que contém os arquivos de áudio a serem convertidos ou carregue vários arquivos de áudio. O áudio convertido será enviado para a pasta especificada (padrão: 'opt').",
+  "Specify output folder:": "Especifique a pasta de saída:",
+  "Enter the path of the audio folder to be processed (copy it from the address bar of the file manager):": "Digite o caminho da pasta de áudio a ser processada (copie-o da barra de endereço do gerenciador de arquivos):",
+  "You can also input audio files in batches. Choose one of the two options. Priority is given to reading from the folder.": "Você também pode inserir arquivos de áudio em lotes. Escolha uma das duas opções. É dada prioridade à leitura da pasta.",
+  "Export file format": "Exportar formato de arquivo",
+  "UVR5": "UVR5",
+  "Enter the path of the audio folder to be processed:": "Digite o caminho da pasta de áudio a ser processada:",
+  "Model": "Modelo",
+  "Vocal Extraction Aggressive": "Extração Vocal Agressiva",
+  "Specify the output folder for vocals:": "Especifique a pasta de saída para vocais:",
+  "Specify the output folder for accompaniment:": "Especifique a pasta de saída para acompanhamento:",
+  "Train": "Trem",
+  "Enter the model name:": "Digite o nome do modelo:",
+  "Target sample rate:": "Taxa de amostragem desejada:",
+  "Whether the model has pitch guidance (required for singing, optional for speech):": "Se o modelo possui orientação de tom (obrigatório para canto, opcional para fala):",
+  "Version": "Versão",
+  "Number of CPU processes:": "Número de processos de CPU usados ​​para extração de pitch e processamento de dados:",
+  "Enter the path of the training folder:": "Digite o caminho da pasta de treinamento:",
+  "Specify the model ID:": "Especifique o ID do modelo:",
+  "Auto detect audio path and select from the dropdown:": "Detecte automaticamente o caminho de áudio e selecione no menu suspenso:",
+  "Add audio's name to the path to the audio file to be processed (default is the correct format example) Remove the path to use an audio from the dropdown list:": "Adicione o nome do áudio ao caminho do arquivo de áudio a ser processado (o padrão é o exemplo de formato correto) Remova o caminho para usar um áudio da lista suspensa:",
+  "Advanced Settings": "Configurações avançadas",
+  "Settings": "Configurações",
+  "Status:": "Status:",
+  "Process data": "Processar dados",
+  "Drag your audio here:": "Arraste seu áudio aqui",
+  "Or record an audio:": "Ou grave um áudio.",
+  "Formant shift inference audio": "Áudio de inferência de mudança de formante",
+  "Used for male to female and vice-versa conversions": "Usado para conversões de homem para mulher e vice-versa",
+  "Provide the GPU index(es) separated by '-', like 0-1-2 for using GPUs 0, 1, and 2:": "Forneça os índices de GPU separados por '-', como 0-1-2 para usar GPUs 0, 1 e 2:",
+  "GPU Information:": "Informações da GPU",
+  "Feature extraction": "Extração de recursos",
+  "Save frequency:": "Salvar frequência:",
+  "Training epochs:": "Épocas de treinamento:",
+  "Batch size per GPU:": "Tamanho do lote por GPU:",
+  "Save only the latest '.ckpt' file to save disk space:": "Salve apenas o arquivo '.ckpt' mais recente para economizar espaço em disco:",
+  "No": "Não",
+  "Save a small final model to the 'weights' folder at each save point:": "Salve um pequeno modelo final na pasta 'pesos' em cada ponto de salvamento:",
+  "Load pre-trained base model G path:": "Carregar caminho G do modelo base pré-treinado:",
+  "Load pre-trained base model D path:": "Carregar caminho D do modelo base pré-treinado:",
+  "Train model": "Modelo de trem",
+  "Train feature index": "Índice de recursos de trem",
+  "One-click training": "Treinamento com um clique",
+  "Processing": "Em processamento",
+  "Model fusion, can be used to test timbre fusion": "Fusão de modelos, pode ser usada para testar a fusão de timbres",
+  "Path to Model A:": "Caminho para o modelo A:",
+  "Path to Model B:": "Caminho para o modelo B:",
+  "Weight for Model A:": "Peso para o Modelo A:",
+  "Whether the model has pitch guidance:": "Se o modelo tem orientação de pitch:",
+  "Model information to be placed:": "Informações do modelo a ser colocado:",
+  "Model architecture version:": "Versão da arquitetura do modelo:",
+  "Fusion": "Fusão",
+  "Modify model information": "Modificar informações do modelo",
+  "Path to Model:": "Caminho para o modelo:",
+  "Model information to be modified:": "Informações do modelo a serem modificadas:",
+  "Save file name:": "Salvar nome do arquivo:",
+  "Modify": "Modificar",
+  "View model information": "Ver informações do modelo",
+  "View": "Visualizar",
+  "Model extraction": "Extração de modelo (insira o caminho do modelo de arquivo grande na pasta 'logs'). Isso é útil se você quiser interromper o treinamento no meio e extrair e salvar manualmente um arquivo de modelo pequeno, ou se quiser testar um modelo intermediário:",
+  "Name:": "Salvar nome:",
+  "Whether the model has pitch guidance (1: yes, 0: no):": "Se o modelo possui orientação de pitch (1: sim, 0: não):",
+  "Extract": "Extrair",
+  "Export Onnx": "Exportar Onnx",
+  "RVC Model Path:": "Caminho do modelo RVC:",
+  "Onnx Export Path:": "Caminho de exportação Onnx:",
+  "MoeVS Model": "Modelo MoeVS",
+  "Export Onnx Model": "Exportar modelo Onnx",
+  "Load model": "Modelo de carga",
+  "Hubert Model": "Modelo Hubert",
+  "Select the .pth file": "Selecione o arquivo .pth",
+  "Select the .index file": "Selecione o arquivo .index",
+  "Select the .npy file": "Selecione o arquivo .npy",
+  "Input device": "Dispositivo de entrada",
+  "Output device": "Dispositivo de saída",
+  "Audio device (please use the same type of driver)": "Dispositivo de áudio (use o mesmo tipo de driver)",
+  "Response threshold": "Limite de resposta",
+  "Pitch settings": "Configurações de tom",
+  "Whether to use note names instead of their hertz value. E.G. [C5, D6] instead of [523.25, 1174.66]Hz": "Se deve usar nomes de notas em vez de seu valor em hertz. POR EXEMPLO. [C5, D6] em vez de [523,25, 1174,66] Hz",
+  "Index Rate": "Taxa de índice",
+  "General settings": "Configurações Gerais",
+  "Sample length": "Comprimento da amostra",
+  "Fade length": "Comprimento do esmaecimento",
+  "Extra inference time": "Tempo extra de inferência",
+  "Input noise reduction": "Redução de ruído de entrada",
+  "Output noise reduction": "Redução de ruído de saída",
+  "Performance settings": "Configurações de desempenho",
+  "Start audio conversion": "Iniciar conversão de áudio",
+  "Stop audio conversion": "Pare a conversão de áudio",
+  "Inference time (ms):": "Tempo de inferência (ms):",
+  "Select the pth file": "Selecione o arquivo pth",
+  "Select the .index file:": "Selecione o arquivo de índice",
+  "The hubert model path must not contain Chinese characters": "O caminho do modelo Hubert não deve conter caracteres chineses",
+  "The pth file path must not contain Chinese characters.": "O caminho do arquivo pth não deve conter caracteres chineses.",
+  "The index file path must not contain Chinese characters.": "O caminho do arquivo de índice não deve conter caracteres chineses.",
+  "Step algorithm": "Algoritmo de etapas",
+  "Number of epoch processes": "Número de processos de época",
+  "Lowest points export": "Exportação de pontos mais baixos",
+  "How many lowest points to save:": "Quantos pontos mais baixos salvar",
+  "Export lowest points of a model": "Exportar os pontos mais baixos de um modelo",
+  "Output models:": "Modelos de saída",
+  "Stats of selected models:": "Estatísticas dos modelos selecionados",
+  "Custom f0 [Root pitch] File": "Arquivo f0 [inclinação da raiz] personalizado",
+  "Min pitch:": "Passo mínimo",
+  "Specify minimal pitch for inference [HZ]": "Especifique o tom mínimo para inferência [HZ]",
+  "Specify minimal pitch for inference [NOTE][OCTAVE]": "Especifique o tom mínimo para inferência [NOTA][OCTAVE]",
+  "Max pitch:": "Tom máximo",
+  "Specify max pitch for inference [HZ]": "Especifique o tom máximo para inferência [HZ]",
+  "Specify max pitch for inference [NOTE][OCTAVE]": "Especifique o tom máximo para inferência [NOTE][OCTAVE]",
+  "Browse presets for formanting": "Procure predefinições para formatação",
+  "Presets are located in formantshiftcfg/ folder": "As predefinições estão localizadas na pasta formantshiftcfg/",
+  "Default value is 1.0": "O valor padrão é 1,0",
+  "Quefrency for formant shifting": "Quefrency para mudança de formantes",
+  "Timbre for formant shifting": "Timbre para mudança de formantes",
+  "Apply": "Aplicar",
+  "Single": "Solteiro",
+  "Batch": "Lote",
+  "Separate YouTube tracks": "Faixas separadas do YouTube",
+  "Download audio from a YouTube video and automatically separate the vocal and instrumental tracks": "Baixe o áudio de um vídeo do YouTube e separe automaticamente as faixas vocais e instrumentais",
+  "Extra": "Extra",
+  "Merge": "Mesclar",
+  "Merge your generated audios with the instrumental": "Mescle seus áudios gerados com o instrumental",
+  "Choose your instrumental:": "Escolha seu instrumental",
+  "Choose the generated audio:": "Escolha o áudio gerado",
+  "Combine": "Combinar",
+  "Download and Separate": "Baixe e separe",
+  "Enter the YouTube link:": "Digite o link do youtube",
+  "This section contains some extra utilities that often may be in experimental phases": "Esta seção contém alguns utilitários extras que muitas vezes podem estar em fases experimentais",
+  "Merge Audios": "Mesclar áudios",
+  "Audio files have been moved to the 'audios' folder.": "Os arquivos de áudio foram movidos para a pasta ‘audios’.",
+  "Downloading audio from the video...": "Baixando o áudio do vídeo...",
+  "Audio downloaded!": "Baixar áudio!",
+  "An error occurred:": "Um erro ocorreu:",
+  "Separating audio...": "Separando áudio...",
+  "File moved successfully.": "Arquivo movido com sucesso.",
+  "Finished!": "Finalizado!",
+  "The source file does not exist.": "O arquivo de origem não existe.",
+  "Error moving the file:": "Erro ao mover o arquivo:",
+  "Downloading {name} from drive": "Baixando {name} da unidade",
+  "The attempt to download using Drive didn't work": "A tentativa de download usando o Drive não funcionou",
+  "Error downloading the file: {str(e)}": "Erro ao baixar o arquivo: {str(e)}",
+  "Downloading {name} from mega": "Baixando {nome} do mega",
+  "Downloading {name} from basic url": "Baixando {nome} do URL básico",
+  "Download Audio": "Baixar áudio",
+  "Download audios of any format for use in inference (recommended for mobile users).": "Baixe áudios de qualquer formato para uso em inferência (recomendado para usuários móveis)",
+  "Any ConnectionResetErrors post-conversion are irrelevant and purely visual; they can be ignored.\n": "Qualquer ConnectionResetErrors pós-conversão é irrelevante e puramente visual; eles podem ser ignorados.",
+  "Processed audio saved at: ": "Áudio processado salvo em:",
+  "Conversion complete!": "Conversão concluída!",
+  "Reverb": "Ressonância",
+  "Compressor": "Compressor",
+  "Noise Gate": "Portão de Ruído",
+  "Volume": "Volume",
+  "Drag the audio here and click the Refresh button": "Arraste o áudio aqui e clique no botão Atualizar",
+  "Select the generated audio": "Selecione o áudio gerado",
+  "Volume of the instrumental audio:": "Volume do áudio instrumental",
+  "Volume of the generated audio:": "Volume do áudio gerado",
+  "### Add the effects": "### Adicione os efeitos",
+  "Starting audio conversion... (This might take a moment)": "Iniciando a conversão de áudio... (Isso pode levar um tempo)",
+  "TTS Model:": "Vozes TTS",
+  "TTS": "TTS",
+  "TTS Method:": "Método TTS",
+  "Audio TTS:": "Áudio TTS",
+  "Audio RVC:": "Modelo de Áudio"
+}
diff --git a/i18n/locale/ru_RU.json b/i18n/locale/ru_RU.json
new file mode 100644
index 0000000000000000000000000000000000000000..dc4990659b3d068f039047cc3671d8e6cbee2401
--- /dev/null
+++ b/i18n/locale/ru_RU.json
@@ -0,0 +1,247 @@
+{
+  "Unfortunately, there is no compatible GPU available to support your training.": "К сожалению, для вашего обучения не существует совместимого графического процессора.",
+  "Yes": "Да",
+  "Select your dataset:": "Выберите свой набор данных.",
+  "Update list": "Обновить список.",
+  "Download Model": "Скачать модель",
+  "Download Backup": "Скачать резервную копию",
+  "Download Dataset": "Скачать набор данных",
+  "Download": "Скачать",
+  "Url:": "URL:",
+  "Build the index before saving.": "Создайте индекс перед сохранением.",
+  "Save your model once the training ends.": "Сохраните свою модель после окончания обучения.",
+  "Save type": "Тип сохранения",
+  "Save model": "Сохранить модель",
+  "Choose the method": "Выберите метод",
+  "Save all": "Сохранить все",
+  "Save D and G": "Спасите D и G",
+  "Save voice": "Сохранить голос",
+  "Downloading the file: ": "Скачиваем файл:",
+  "Stop training": "Прекратить тренировку",
+  "Too many users have recently viewed or downloaded this file": "Слишком много пользователей недавно просмотрели или скачали этот файл.",
+  "Cannot get file from this private link": "Невозможно получить файл по этой частной ссылке",
+  "Full download": "Полная загрузка",
+  "An error occurred downloading": "Произошла ошибка при загрузке",
+  "Model saved successfully": "Модель успешно сохранена",
+  "Saving the model...": "Сохраняем модель...",
+  "Saved without index...": "Сохранено без индекса...",
+  "model_name": "название модели",
+  "Saved without inference model...": "Сохранено без модели вывода...",
+  "An error occurred saving the model": "Произошла ошибка при сохранении модели.",
+  "The model you want to save does not exist, be sure to enter the correct name.": "Модель, которую вы хотите сохранить, не существует. Обязательно введите правильное имя.",
+  "The file could not be downloaded.": "Не удалось загрузить файл.",
+  "Unzip error.": "Ошибка разархивирования.",
+  "Path to your added.index file (if it didn't automatically find it)": "Путь к файлу add.index (если он не был найден автоматически)",
+  "It has been downloaded successfully.": "Он был успешно загружен.",
+  "Proceeding with the extraction...": "Приступаем к извлечению...",
+  "The Backup has been uploaded successfully.": "Резервная копия успешно загружена.",
+  "The Dataset has been loaded successfully.": "Набор данных успешно загружен.",
+  "The Model has been loaded successfully.": "Модель успешно загружена.",
+  "It is used to download your inference models.": "Он используется для загрузки ваших моделей вывода.",
+  "It is used to download your training backups.": "Он используется для загрузки резервных копий тренировок.",
+  "Download the dataset with the audios in a compatible format (.wav/.flac) to train your model.": "Загрузите набор данных со звуками в совместимом формате (.wav/.flac), чтобы обучить свою модель.",
+  "No relevant file was found to upload.": "Не найден соответствующий файл для загрузки.",
+  "The model works for inference, and has the .index file.": "Модель работает для вывода и имеет файл .index.",
+  "The model works for inference, but it doesn't have the .index file.": "Модель работает для вывода, но у нее нет файла .index.",
+  "This may take a few minutes, please wait...": "Это может занять несколько минут, пожалуйста, подождите...",
+  "Resources": "Ресурсы",
+  "Step 1: Processing data": "Шаг 1: Обработка данных",
+  "Step 2: Skipping pitch extraction": "Шаг 2а: Пропуск извлечения высоты тона",
+  "Step 3: Extracting features": "Шаг 2б: Извлечение объектов",
+  "Step 4: Model training started": "Шаг 3а: Начало обучения модели",
+  "Step 5: Export lowest points on a graph of the model": "Шаг 4. Экспортируйте самые низкие точки на графике модели.",
+  "Training is done, check train.log": "Обучение завершено, проверьте train.log",
+  "All processes have been completed!": "Все процессы завершены!",
+  "Model Inference": "Вывод модели",
+  "Inferencing voice:": "Выводящий голос:",
+  "Model_Name": "Название модели",
+  "Dataset_Name": "Имя_набора данных",
+  "Whether the model has pitch guidance.": "Имеет ли модель наведение по тангажу.",
+  "Whether to save only the latest .ckpt file to save hard drive space": "Сохранять ли только последний файл .ckpt для экономии места на жестком диске",
+  "Cache all training sets to GPU memory. Caching small datasets (less than 10 minutes) can speed up training": "Кэшируйте все обучающие наборы в память графического процессора. Кэширование небольших наборов данных (менее 10 минут) может ускорить обучение.",
+  "Save a small final model to the 'weights' folder at each save point": "Сохраняйте небольшую окончательную модель в папке «веса» в каждой точке сохранения.",
+  "Refresh": "Обновить список голосов, индексный путь и аудиофайлы.",
+  "Unload voice to save GPU memory": "Выгрузите голос, чтобы сэкономить память графического процессора:",
+  "Select Speaker/Singer ID:": "Выберите идентификатор докладчика/певца:",
+  "Recommended +12 key for male to female conversion, and -12 key for female to male conversion. If the sound range goes too far and the voice is distorted, you can also adjust it to the appropriate range by yourself.": "Рекомендуемый ключ +12 для преобразования мужчины в женщину и ключ -12 для преобразования женщины в мужчину. Если звуковой диапазон заходит слишком далеко и голос искажается, вы также можете самостоятельно настроить его на соответствующий диапазон.",
+  "Transpose (integer, number Fof semitones, raise by an octave: 12, lower by an octave: -12):": "Транспонирование (целое число, количество полутонов, повышение на октаву: 12, понижение на октаву: -12):",
+  "Enter the path of the audio file to be processed (default is the correct format example):": "Введите путь к аудиофайлу, который необходимо обработать (по умолчанию — правильный пример формата):",
+  "Select the pitch extraction algorithm:": "Выберите алгоритм извлечения высоты звука:",
+  "Mangio-Crepe Hop Length (Only applies to mangio-crepe): Hop length refers to the time it takes for the speaker to jump to a dramatic pitch. Lower hop lengths take more time to infer but are more pitch accurate.": "Длина прыжка с манжио-крепом (применяется только к крепу с манжио): длина прыжка означает время, необходимое говорящему, чтобы перейти на драматический тон. Для определения более низкой длины скачка требуется больше времени, но они более точны по высоте.",
+  "Feature search dataset file path": "Путь к файлу набора данных поиска объектов",
+  "If >=3: apply median filtering to the harvested pitch results. The value represents the filter radius and can reduce breathiness.": "Если >=3: применить медианную фильтрацию к собранным результатам высоты тона. Значение представляет собой радиус фильтра и может уменьшить одышку.",
+  "Path to the feature index file. Leave blank to use the selected result from the dropdown:": "Путь к индексному файлу объекта. Оставьте поле пустым, чтобы использовать выбранный результат из раскрывающегося списка:",
+  "Auto-detect index path and select from the dropdown:": "Автоматическое определение пути к индексу и выбор из раскрывающегося списка.",
+  "Path to feature file:": "Путь к файлу объекта:",
+  "Search feature ratio:": "Соотношение функций поиска:",
+  "Resample the output audio in post-processing to the final sample rate. Set to 0 for no resampling:": "Повторно дискретизируйте выходной звук при постобработке до окончательной частоты дискретизации. Установите значение 0, чтобы не выполнять повторную выборку:",
+  "Use the volume envelope of the input to replace or mix with the volume envelope of the output. The closer the ratio is to 1, the more the output envelope is used:": "Используйте огибающую громкости входа для замены или смешивания с огибающей громкости выхода. Чем ближе соотношение к 1, тем больше используется выходная огибающая:",
+  "Protect voiceless consonants and breath sounds to prevent artifacts such as tearing in electronic music. Set to 0.5 to disable. Decrease the value to increase protection, but it may reduce indexing accuracy:": "Защищайте глухие согласные и звуки дыхания, чтобы предотвратить появление таких артефактов, как разрывы в электронной музыке. Установите значение 0,5, чтобы отключить. Уменьшите значение, чтобы повысить защиту, но это может снизить точность индексации:",
+  "F0 curve file (optional). One pitch per line. Replaces the default F0 and pitch modulation:": "Файл кривой F0 (опционально). Один шаг на строку. Заменяет стандартную F0 и модуляцию высоты тона:",
+  "Convert": "Конвертировать",
+  "Output information:": "Выходная информация",
+  "Export audio (click on the three dots in the lower right corner to download)": "Экспортируйте аудио (нажмите на три точки в правом нижнем углу, чтобы загрузить)",
+  "Batch conversion. Enter the folder containing the audio files to be converted or upload multiple audio files. The converted audio will be output in the specified folder (default: 'opt').": "Пакетное преобразование. Введите папку, содержащую аудиофайлы, которые нужно преобразовать, или загрузите несколько аудиофайлов. Конвертированный звук будет выводиться в указанную папку (по умолчанию: «opt»).",
+  "Specify output folder:": "Укажите выходную папку:",
+  "Enter the path of the audio folder to be processed (copy it from the address bar of the file manager):": "Введите путь к папке аудио, подлежащей обработке (скопируйте его из адресной строки файлового менеджера):",
+  "You can also input audio files in batches. Choose one of the two options. Priority is given to reading from the folder.": "Вы также можете вводить аудиофайлы в пакетном режиме. Выберите один из двух вариантов. Приоритет отдается чтению из папки.",
+  "Export file format": "Формат файла экспорта",
+  "UVR5": "УВР5",
+  "Enter the path of the audio folder to be processed:": "Введите путь к аудиопапке, которую необходимо обработать:",
+  "Model": "Модель",
+  "Vocal Extraction Aggressive": "Извлечение вокала агрессивное",
+  "Specify the output folder for vocals:": "Укажите выходную папку для вокала:",
+  "Specify the output folder for accompaniment:": "Укажите выходную папку для аккомпанемента:",
+  "Train": "Тренироваться",
+  "Enter the model name:": "Введите название модели:",
+  "Target sample rate:": "Целевая частота дискретизации:",
+  "Whether the model has pitch guidance (required for singing, optional for speech):": "Имеет ли модель управление высотой тона (обязательно для пения, необязательно для речи):",
+  "Version": "Версия",
+  "Number of CPU processes:": "Количество процессов ЦП, используемых для извлечения высоты звука и обработки данных:",
+  "Enter the path of the training folder:": "Введите путь к папке обучения:",
+  "Specify the model ID:": "Пожалуйста, укажите идентификатор модели:",
+  "Auto detect audio path and select from the dropdown:": "Автоматическое определение пути аудио и выбор из раскрывающегося списка:",
+  "Add audio's name to the path to the audio file to be processed (default is the correct format example) Remove the path to use an audio from the dropdown list:": "Добавьте имя аудио к пути к обрабатываемому аудиофайлу (по умолчанию используется правильный пример формата). Удалите путь для использования аудио из раскрывающегося списка:",
+  "Advanced Settings": "Расширенные настройки",
+  "Settings": "Настройки",
+  "Status:": "Положение дел",
+  "Process data": "Данные обработки",
+  "Drag your audio here:": "Перетащите сюда свой аудиофайл и нажмите кнопку «Обновить».",
+  "Or record an audio:": "Или записать звук.",
+  "Formant shift inference audio": "Звук вывода формантного сдвига",
+  "Used for male to female and vice-versa conversions": "Используется для преобразования мужского и женского пола и наоборот.",
+  "Provide the GPU index(es) separated by '-', like 0-1-2 for using GPUs 0, 1, and 2:": "Укажите индексы графического процессора, разделенные знаком «-», например 0-1-2, для использования графических процессоров 0, 1 и 2:",
+  "GPU Information:": "Информация о графическом процессоре",
+  "Feature extraction": "Извлечение признаков",
+  "Save frequency:": "Частота сохранения:",
+  "Training epochs:": "Эпохи обучения:",
+  "Batch size per GPU:": "Размер пакета на графический процессор:",
+  "Save only the latest '.ckpt' file to save disk space:": "Сохраните только последний файл «.ckpt», чтобы сэкономить место на диске:",
+  "No": "Нет",
+  "Save a small final model to the 'weights' folder at each save point:": "Сохраните небольшую окончательную модель в папке «веса» в каждой точке сохранения:",
+  "Load pre-trained base model G path:": "Загрузите предварительно обученную базовую модель G-путь:",
+  "Load pre-trained base model D path:": "Загрузите путь D предварительно обученной базовой модели:",
+  "Train model": "Модель поезда",
+  "Train feature index": "Индекс характеристик поезда",
+  "One-click training": "Обучение в один клик",
+  "Processing": "Обработка",
+  "Model fusion, can be used to test timbre fusion": "Модель Fusion, можно использовать для проверки синтеза тембров.",
+  "Path to Model A:": "Путь к модели А:",
+  "Path to Model B:": "Путь к модели Б:",
+  "Weight for Model A:": "Вес модели А:",
+  "Whether the model has pitch guidance:": "Имеет ли модель наведение по тангажу:",
+  "Model information to be placed:": "Информация о модели, которую необходимо разместить:",
+  "Model architecture version:": "Версия архитектуры модели:",
+  "Fusion": "Слияние",
+  "Modify model information": "Изменить информацию о модели",
+  "Path to Model:": "Путь к модели:",
+  "Model information to be modified:": "Информация о модели, которую необходимо изменить:",
+  "Save file name:": "Имя файла сохранения:",
+  "Modify": "Изменить",
+  "View model information": "Просмотр информации о модели",
+  "View": "Вид",
+  "Model extraction": "Извлечение модели (введите путь к модели большого файла в папке «logs»). Это полезно, если вы хотите остановить обучение на полпути и вручную извлечь и сохранить небольшой файл модели или если вы хотите протестировать промежуточную модель:",
+  "Name:": "Сохранить имя:",
+  "Whether the model has pitch guidance (1: yes, 0: no):": "Имеет ли модель управление по тангажу (1: да, 0: нет):",
+  "Extract": "Извлекать",
+  "Export Onnx": "Экспортировать Onnx",
+  "RVC Model Path:": "Путь модели RVC:",
+  "Onnx Export Path:": "Путь экспорта Onnx:",
+  "MoeVS Model": "Модель МоэВС",
+  "Export Onnx Model": "Экспорт модели Onnx",
+  "Load model": "Загрузить модель",
+  "Hubert Model": "Хьюберт Модель",
+  "Select the .pth file": "Выберите файл .pth.",
+  "Select the .index file": "Выберите файл .index.",
+  "Select the .npy file": "Выберите файл .npy.",
+  "Input device": "Устройство ввода",
+  "Output device": "Устройство вывода",
+  "Audio device (please use the same type of driver)": "Аудиоустройство (пожалуйста, используйте драйвер того же типа)",
+  "Response threshold": "Порог ответа",
+  "Pitch settings": "Настройки высоты тона",
+  "Whether to use note names instead of their hertz value. E.G. [C5, D6] instead of [523.25, 1174.66]Hz": "Использовать ли названия нот вместо их значения в герцах. НАПРИМЕР. [C5, D6] вместо [523,25, 1174,66] Гц",
+  "Index Rate": "Индексная ставка",
+  "General settings": "Общие настройки",
+  "Sample length": "Длина образца",
+  "Fade length": "Длина затухания",
+  "Extra inference time": "Дополнительное время вывода",
+  "Input noise reduction": "Снижение входного шума",
+  "Output noise reduction": "Снижение выходного шума",
+  "Performance settings": "Настройки производительности",
+  "Start audio conversion": "Начать преобразование аудио",
+  "Stop audio conversion": "Остановить преобразование аудио",
+  "Inference time (ms):": "Время вывода (мс):",
+  "Select the pth file": "Выберите pth-файл",
+  "Select the .index file:": "Выберите индексный файл",
+  "The hubert model path must not contain Chinese characters": "Путь модели Хьюберта не должен содержать китайские символы.",
+  "The pth file path must not contain Chinese characters.": "Путь к файлу pth не должен содержать китайских символов.",
+  "The index file path must not contain Chinese characters.": "Путь к индексному файлу не должен содержать китайских символов.",
+  "Step algorithm": "Пошаговый алгоритм",
+  "Number of epoch processes": "Количество эпохальных процессов",
+  "Lowest points export": "Экспорт наименьших баллов",
+  "How many lowest points to save:": "Сколько самых низких баллов нужно сохранить",
+  "Export lowest points of a model": "Экспортировать самые низкие точки модели",
+  "Output models:": "Выходные модели",
+  "Stats of selected models:": "Статистика выбранных моделей",
+  "Custom f0 [Root pitch] File": "Пользовательский файл f0 [Шаг основного тона]",
+  "Min pitch:": "Минимальный шаг",
+  "Specify minimal pitch for inference [HZ]": "Укажите минимальный шаг для вывода [Гц]",
+  "Specify minimal pitch for inference [NOTE][OCTAVE]": "Укажите минимальный шаг для вывода [NOTE][OCTAVE]",
+  "Max pitch:": "Максимальный шаг",
+  "Specify max pitch for inference [HZ]": "Укажите максимальную высоту звука для вывода [Гц]",
+  "Specify max pitch for inference [NOTE][OCTAVE]": "Укажите максимальный шаг для вывода [ПРИМЕЧАНИЕ][ОКТАВА]",
+  "Browse presets for formanting": "Просмотр пресетов для форматирования",
+  "Presets are located in formantshiftcfg/ folder": "Пресеты находятся в папке formantshiftcfg/.",
+  "Default value is 1.0": "Значение по умолчанию — 1,0.",
+  "Quefrency for formant shifting": "Quefrency для сдвига форманты",
+  "Timbre for formant shifting": "Тембр для смещения форманты",
+  "Apply": "Применять",
+  "Single": "Одинокий",
+  "Batch": "Партия",
+  "Separate YouTube tracks": "Отдельные треки YouTube",
+  "Download audio from a YouTube video and automatically separate the vocal and instrumental tracks": "Загрузите аудио из видео YouTube и автоматически разделите вокальные и инструментальные дорожки.",
+  "Extra": "Дополнительный",
+  "Merge": "Объединить",
+  "Merge your generated audios with the instrumental": "Объедините сгенерированные аудио с инструментальной композицией.",
+  "Choose your instrumental:": "Выберите свой инструментал",
+  "Choose the generated audio:": "Выберите сгенерированный звук",
+  "Combine": "Объединить",
+  "Download and Separate": "Скачать и отделить",
+  "Enter the YouTube link:": "Введите ссылку на ютуб",
+  "This section contains some extra utilities that often may be in experimental phases": "Этот раздел содержит некоторые дополнительные утилиты, которые часто могут находиться на экспериментальной стадии.",
+  "Merge Audios": "Объединить аудио",
+  "Audio files have been moved to the 'audios' folder.": "Аудиофайлы перемещены в папку «audios».",
+  "Downloading audio from the video...": "Загрузка звука из видео...",
+  "Audio downloaded!": "Аудио скачать!",
+  "An error occurred:": "Произошла ошибка:",
+  "Separating audio...": "Разделение звука...",
+  "File moved successfully.": "Файл успешно перемещен.",
+  "Finished!": "Законченный!",
+  "The source file does not exist.": "Исходный файл не существует.",
+  "Error moving the file:": "Ошибка перемещения файла:",
+  "Downloading {name} from drive": "Загрузка {name} с диска",
+  "The attempt to download using Drive didn't work": "Попытка скачать с Диска не удалась.",
+  "Error downloading the file: {str(e)}": "Ошибка загрузки файла: {str(e)}",
+  "Downloading {name} from mega": "Скачиваю {name} из мега",
+  "Downloading {name} from basic url": "Загрузка {name} с основного URL",
+  "Download Audio": "Скачать аудио",
+  "Download audios of any format for use in inference (recommended for mobile users).": "Загрузите аудио любого формата для использования в умозаключениях (рекомендуется для мобильных пользователей)",
+  "Any ConnectionResetErrors post-conversion are irrelevant and purely visual; they can be ignored.\n": "Любые пост-преобразования ConnectionResetErrors не имеют значения и являются чисто визуальными; их можно игнорировать.",
+  "Processed audio saved at: ": "Обработанный звук сохранен по адресу:",
+  "Conversion complete!": "Преобразование завершено!",
+  "Reverb": "Реверберация",
+  "Compressor": "Компрессор",
+  "Noise Gate": "Шумовые ворота",
+  "Volume": "Объем",
+  "Drag the audio here and click the Refresh button": "Перетащите аудио сюда и нажмите кнопку «Обновить».",
+  "Select the generated audio": "Выберите сгенерированный звук",
+  "Volume of the instrumental audio:": "Громкость инструментального звука",
+  "Volume of the generated audio:": "Громкость сгенерированного звука",
+  "### Add the effects": "### Добавьте эффекты",
+  "Starting audio conversion... (This might take a moment)": "Начинается конвертация аудио... (Это может занять некоторое время)",
+  "TTS Model:": "Голоса TTS",
+  "TTS": "TTS",
+  "TTS Method:": "Метод TTS",
+  "Audio TTS:": "Аудио TTS",
+  "Audio RVC:": "Аудио Модель"
+}
diff --git a/i18n/locale/tr_TR.json b/i18n/locale/tr_TR.json
new file mode 100644
index 0000000000000000000000000000000000000000..3175bd8d8617b27d2c98cf703149bd348eb7aa02
--- /dev/null
+++ b/i18n/locale/tr_TR.json
@@ -0,0 +1,249 @@
+{
+  "Unfortunately, there is no compatible GPU available to support your training.": "Üzgünüz, eğitiminizi desteklemek için uyumlu bir GPU bulunmuyor.",
+  "Yes": "Evet",
+  "Select your dataset:": "Veri setinizi seçin:",
+  "Update list": "Listeyi güncelle.",
+  "Download Model": "Modeli İndir",
+  "Download Backup": "Yedeklemeyi İndir",
+  "Download Dataset": "Veri Setini İndir",
+  "Download": "İndir",
+  "Url:": "URL:",
+  "Build the index before saving.": "Kaydetmeden önce dizini oluşturun.",
+  "Save your model once the training ends.": "Eğitim sona erdiğinde modelinizi kaydedin.",
+  "Save type": "Kaydetme türü:",
+  "Save model": "Modeli Kaydet",
+  "Choose the method": "Yöntemi seçin",
+  "Save all": "Hepsini kaydet",
+  "Save D and G": "D ve G'yi kaydet",
+  "Save voice": "Sesi kaydet",
+  "Downloading the file: ": "Dosya indiriliyor: ",
+  "Stop training": "Eğitimi durdur",
+  "Too many users have recently viewed or downloaded this file": "Çok sayıda kullanıcı bu dosyayı yakın zamanda görüntüledi veya indirdi",
+  "Cannot get file from this private link": "Bu özel bağlantıdan dosya alınamıyor",
+  "Full download": "Tam indirme",
+  "An error occurred downloading": "İndirme sırasında bir hata oluştu",
+  "Model saved successfully": "Model başarıyla kaydedildi",
+  "Saving the model...": "Model kaydediliyor...",
+  "Saved without index...": "Dizin oluşturulmadan kaydedildi...",
+  "Saved without inference model...": "Çıkarsama modeli oluşturulmadan kaydedildi...",
+  "An error occurred saving the model": "Model kaydedilirken bir hata oluştu",
+  "The model you want to save does not exist, be sure to enter the correct name.": "Kaydetmek istediğiniz model mevcut değil, doğru adı girdiğinizden emin olun.",
+  "The file could not be downloaded.": "Dosya indirilemedi.",
+  "Unzip error.": "Sıkıştırılmış dosya açma hatası.",
+  "Path to your added.index file (if it didn't automatically find it)": "added.index dosyanızın yolu (eğer otomatik olarak bulunmadıysa)",
+  "It has been downloaded successfully.": "Başarıyla indirildi.",
+  "Proceeding with the extraction...": "Çıkarma işlemine devam ediliyor...",
+  "The Backup has been uploaded successfully.": "Yedekleme başarıyla yüklendi.",
+  "The Dataset has been loaded successfully.": "Veri seti başarıyla yüklendi.",
+  "The Model has been loaded successfully.": "Model başarıyla yüklendi.",
+  "It is used to download your inference models.": "Çıkarsama modellerinizi indirmek için kullanılır.",
+  "It is used to download your training backups.": "Eğitim yedeklemelerinizi indirmek için kullanılır.",
+  "Download the dataset with the audios in a compatible format (.wav/.flac) to train your model.": "Modelinizi eğitmek için ses içeren uyumlu bir format (.wav/.flac) ile veri setini indirin.",
+  "No relevant file was found to upload.": "Yüklemek için ilgili dosya bulunamadı.",
+  "The model works for inference, and has the .index file.": "Model çıkarsama için çalışır ve .index dosyasına sahiptir.",
+  "The model works for inference, but it doesn't have the .index file.": "Model çıkarsama için çalışır, ancak .index dosyasına sahip değildir.",
+  "This may take a few minutes, please wait...": "Bu birkaç dakika sürebilir, lütfen bekleyin...",
+  "Resources": "Kaynaklar",
+  "Step 1: Processing data": "Adım 1: Verileri işleme",
+  "Step 2: Skipping pitch extraction": "Adım 2: Pitch çıkarma atlanıyor",
+  "Step 3: Extracting features": "Adım 3: Özellik çıkarma",
+  "Step 4: Model training started": "Adım 4: Model eğitimi başladı",
+  "Step 5: Export lowest points on a graph of the model": "Adım 5: Modelin grafikteki en düşük noktalarını dışa aktarın",
+  "Training is done, check train.log": "Eğitim tamamlandı, train.log dosyasını kontrol edin",
+  "All processes have been completed!": "Tüm işlemler tamamlandı!",
+  "Model Inference": "Model Çıkarsama",
+  "Inferencing voice:": "Ses çıkarma:",
+  "Model_Name": "Model_Adı",
+  "Dataset_Name": "Veri_Seti_Adı",
+  "Whether the model has pitch guidance.": "Modelin pitch rehberi olup olmadığı.",
+  "Whether to save only the latest .ckpt file to save hard drive space": "Sadece en son .ckpt dosyasını kaydetmek için kayıt alanı tasarrufu yapılıp yapılmayacağı",
+  "Cache all training sets to GPU memory. Caching small datasets (less than 10 minutes) can speed up training": "Tüm eğitim setlerini GPU belleğine önbelleğe alın. Küçük veri setlerini önbelleğe almak (10 dakikadan az) eğitimi hızlandırabilir.",
+  "Save a small final model to the 'weights' folder at each save point": "Her kaydetme noktasında 'weights' klasörüne küçük bir nihai modeli kaydedin",
+  "Refresh": "Ses listesini, dizin yolunu ve ses dosyalarını yenileyin",
+  "Unload voice to save GPU memory": "GPU belleğini kaydetmek için sesi boşalt",
+  "Select Speaker/Singer ID:": "Konuşmacı/Şarkıcı Kimliği Seç:",
+  "Recommended +12 key for male to female conversion, and -12 key for female to male conversion. If the sound range goes too far and the voice is distorted, you can also adjust it to the appropriate range by yourself.": "Erkekten kadına dönüşüm için önerilen +12 ton, kadından erkeğe dönüşüm için -12 ton. Ses aralığı fazla uzaklaşırsa ve ses bozulursa, uygun aralığı kendiniz ayarlayabilirsiniz.",
+  "Transpose (integer, number Fof semitones, raise by an octave: 12, lower by an octave: -12):": "Transpoze et (tamsayı, yarıton Fof sayısı, bir oktav yukarı: 12, bir oktav aşağı: -12):",
+  "Feature search database file path:": "Özellik arama veritabanı dosya yolu:",
+  "Enter the path of the audio file to be processed (default is the correct format example):": "İşlenecek ses dosyasının yolunu girin (varsayılan olarak doğru format örneğidir):",
+  "Select the pitch extraction algorithm:": "Pitch çıkarma algoritmasını seçin:",
+  "Mangio-Crepe Hop Length (Only applies to mangio-crepe): Hop length refers to the time it takes for the speaker to jump to a dramatic pitch. Lower hop lengths take more time to infer but are more pitch accurate.": "Mangio-Crepe Hop Uzunluğu (Sadece mangio-crepe için geçerlidir): Hop uzunluğu, konuşmacının dramatik bir pitch'e atlama süresini belirtir. Daha düşük hop uzunlukları daha fazla çıkarım süresi alır, ancak daha doğru pitch verir.",
+  "Feature search dataset file path": "Özellik arama veri seti dosya yolu",
+  "If >=3: apply median filtering to the harvested pitch results. The value represents the filter radius and can reduce breathiness.": "Eğer >=3 ise: elde edilen pitch sonuçlarına medyan filtreleme uygulayın. Değer, filtre yarıçapını temsil eder ve nefes sesini azaltabilir.",
+  "Path to the feature index file. Leave blank to use the selected result from the dropdown:": "Özellik dizin dosyasının yolu. Seçilen sonucu kullanmak için boş bırakın:",
+  "Auto-detect index path and select from the dropdown:": "Dizin yolunu otomatik algılayın ve açılır menüden seçin:",
+  "Path to feature file:": "Özellik dosyasının yolu:",
+  "Search feature ratio:": "Özellik oranını arayın:",
+  "Resample the output audio in post-processing to the final sample rate. Set to 0 for no resampling:": "Çıkış sesini son işlemde nihai örnekleme hızına göre yeniden örnekleme yapın. Örnekleme yapmamak için 0 olarak ayarlayın:",
+  "Use the volume envelope of the input to replace or mix with the volume envelope of the output. The closer the ratio is to 1, the more the output envelope is used:": "Girişin ses zarfını çıkışın ses zarfıyla değiştirin veya karıştırın. Oran 1'e ne kadar yakınsa, çıkış zarfı o kadar çok kullanılır:",
+  "Protect voiceless consonants and breath sounds to prevent artifacts such as tearing in electronic music. Set to 0.5 to disable. Decrease the value to increase protection, but it may reduce indexing accuracy:": "Sessiz ünsüzleri ve nefes seslerini koruyarak elektronik müzikte yırtılma gibi sanat efektlerini önleyin. Devre dışı bırakmak için 0.5 olarak ayarlayın. Korumayı artırmak için değeri azaltın, ancak dizinleme doğruluğunu azaltabilir:",
+  "F0 curve file (optional). One pitch per line. Replaces the default F0 and pitch modulation:": "F0 eğrisi dosyası (isteğe bağlı). Her satırda bir pitch bulunur. Varsayılan F0 ve pitch modülasyonunu değiştirir:",
+  "Convert": "Dönüştür",
+  "Output information:": "Çıkış bilgisi:",
+  "Export audio (click on the three dots in the lower right corner to download)": "Sesi dışa aktar (indirmek için sağ alt köşedeki üç noktaya tıklayın)",
+  "Batch conversion. Enter the folder containing the audio files to be converted or upload multiple audio files. The converted audio will be output in the specified folder (default: 'opt').": "Toplu dönüşüm. Dönüştürülecek ses dosyalarını içeren klasörü girin veya birden fazla ses dosyası yükleyin. Dönüştürülen ses, belirtilen klasöre (varsayılan: 'opt') çıktı olarak verilir.",
+  "Specify output folder:": "Çıkış klasörünü belirtin:",
+  "Enter the path of the audio folder to be processed (copy it from the address bar of the file manager):": "İşlenecek ses klasörünün yolunu girin (dosya yöneticisinin adres çubuğundan kopyalayın):",
+  "You can also input audio files in batches. Choose one of the two options. Priority is given to reading from the folder.": "Ses dosyalarını toplu olarak da girebilirsiniz. İki seçenekten birini seçin. Öncelik klasörden okuma yapmaya verilir.",
+  "Export file format:": "Çıkış dosya formatı:",
+  "UVR5": "UVR5",
+  "Enter the path of the audio folder to be processed:": "İşlenecek ses klasörünün yolunu girin:",
+  "Model:": "Model:",
+  "Vocal Extraction Aggressive": "Vokal Çıkarma Agresif",
+  "Specify the output folder for vocals:": "Vokaller için çıkış klasörünü belirtin:",
+  "Specify the output folder for accompaniment:": "Eşlik için çıkış klasörünü belirtin:",
+  "Train": "Eğit",
+  "Enter the model name:": "Model adını girin:",
+  "Target sample rate:": "Hedef örnek hızı:",
+  "Whether the model has pitch guidance (required for singing, optional for speech):": "Modelin ton yönü rehberliği olup olmadığı (şarkı için gereklidir, konuşma için isteğe bağlıdır):",
+  "Version:": "Sürüm:",
+  "Number of CPU processes:": "CPU işlem sayısı:",
+  "Enter the path of the training folder:": "Eğitim klasörünün yolunu girin:",
+  "Specify the model ID:": "Model kimliğini belirtin:",
+  "Auto detect audio path and select from the dropdown:": "Otomatik olarak ses yolunu algıla ve açılır menüden seç:",
+  "Add audio's name to the path to the audio file to be processed (default is the correct format example) Remove the path to use an audio from the dropdown list:": "İşlenecek ses dosyasının yoluna ses dosyasının adını ekleyin (varsayılan olarak doğru format örneği) Yolu kaldırarak açılır menüden bir ses kullanın:",
+  "Advanced Settings": "Gelişmiş Ayarlar",
+  "Settings": "Ayarlar",
+  "Status:": "Durum:",
+  "Process data": "Veriyi işle",
+  "Drag your audio here:": "Sesinizi buraya sürükleyin:",
+  "Or record an audio:": "Veya bir ses kaydedin",
+  "Formant shift inference audio": "Formant kaydırma çıkarsama sesi",
+  "Used for male to female and vice-versa conversions": "Erkekten kadına ve tam tersine dönüşümler için kullanılır",
+  "Provide the GPU index(es) separated by '-', like 0-1-2 for using GPUs 0, 1, and 2:": "GPU dizinini '-' ile ayırarak belirtin, örneğin 0-1-2; GPU'ları 0, 1 ve 2 kullanmak için:",
+  "GPU Information:": "GPU Bilgileri:",
+  "Feature extraction": "Özellik çıkarma",
+  "Save frequency:": "Kaydetme frekansı:",
+  "Training epochs:": "Eğitim dönemleri:",
+  "Batch size per GPU:": "Her GPU için toplu iş boyutu:",
+  "Save only the latest '.ckpt' file to save disk space:": "Sadece en son '.ckpt' dosyasını kaydederek disk alanı tasarrufu yapın:",
+  "No": "Hayır",
+  "Save a small final model to the 'weights' folder at each save point:": "Her kaydetme noktasında 'weights' klasörüne küçük bir son model kaydedin:",
+  "Load pre-trained base model G path:": "Önceden eğitilmiş temel G model yolu yükle:",
+  "Load pre-trained base model D path:": "Önceden eğitilmiş temel D model yolu yükle:",
+  "Train model": "Modeli eğit",
+  "Train feature index": "Eğitim özellik dizini",
+  "One-click training": "Bir tıklamayla eğitim",
+  "Processing": "İşleniyor",
+  "Model fusion, can be used to test timbre fusion": "Model birleştirme, timbre birleştirmeyi test etmek için kullanılabilir",
+  "Path to Model A:": "Model A'nın yolu:",
+  "Path to Model B:": "Model B'nin yolu:",
+  "Weight for Model A:": "Model A için ağırlık:",
+  "Whether the model has pitch guidance:": "Modelin ton yönü rehberliği olup olmadığı:",
+  "Model information to be placed:": "Yerleştirilecek model bilgisi:",
+  "Model architecture version:": "Model mimari sürümü:",
+  "Fusion": "Birleştirme",
+  "Modify model information": "Model bilgisini değiştir",
+  "Path to Model:": "Model yoluna:",
+  "Model information to be modified:": "Değiştirilecek model bilgisi:",
+  "Save file name:": "Dosya adını kaydet:",
+  "Modify": "Değiştir",
+  "View model information": "Model bilgisini görüntüle",
+  "View": "Görüntüle",
+  "Model extraction": "Model çıkarımı (büyük dosya modelinin 'logs' klasörünün altına yolunu girin). Eğitimi yarıda kesmek ve manuel olarak küçük bir model dosyası çıkarmak ve kaydetmek istiyorsanız veya ara bir modeli test etmek isterseniz bu yararlı olabilir:",
+  "Name:": "Adı kaydet:",
+  "Whether the model has pitch guidance (1: yes, 0: no):": "Modelin ton yönü rehberliği olup olmadığı (1: evet, 0: hayır):",
+  "Extract": "Çıkar",
+  "Export Onnx": "Onnx'i dışa aktar",
+  "RVC Model Path:": "RVC Model Yolu:",
+  "Onnx Export Path:": "Onnx Dışa Aktarma Yolu:",
+  "MoeVS Model": "MoeVS Modeli",
+  "Export Onnx Model": "Onnx Modelini Dışa Aktar",
+  "Load model": "Modeli yükle",
+  "Hubert Model": "Hubert Modeli",
+  "Select the .pth file": ".pth dosyasını seçin",
+  "Select the .index file": ".index dosyasını seçin",
+  "Select the .npy file": ".npy dosyasını seçin",
+  "Input device": "Giriş cihazı",
+  "Output device": "Çıkış cihazı",
+  "Audio device (please use the same type of driver)": "Ses cihazı (lütfen aynı sürücü türünü kullanın)",
+  "Response threshold": "Yanıt eşiği",
+  "Pitch settings": "Ton ayarları",
+  "Whether to use note names instead of their hertz value. E.G. [C5, D6] instead of [523.25, 1174.66]Hz": "Hertz değeri yerine nota isimlerinin kullanılıp kullanılmayacağı. Örn. [C5, D6] yerine [523.25, 1174.66]Hz",
+  "Index Rate": "Dizin Oranı",
+  "General settings": "Genel ayarlar",
+  "Sample length": "Örnek uzunluğu",
+  "Fade length": "Solma uzunluğu",
+  "Extra inference time": "Ek çıkarsama süresi",
+  "Input noise reduction": "Giriş gürültü azaltma",
+  "Output noise reduction": "Çıkış gürültü azaltma",
+  "Performance settings": "Performans ayarları",
+  "Start audio conversion": "Ses dönüşümünü başlat",
+  "Stop audio conversion": "Ses dönüşümünü durdur",
+  "Inference time (ms):": "Çıkarsama süresi (ms):",
+  "Select the pth file": ".pth dosyasını seçin",
+  "Select the .index file:": ".index dosyasını seçin",
+  "The hubert model path must not contain Chinese characters": "Hubert model yolu Çince karakter içermemelidir",
+  "The pth file path must not contain Chinese characters.": ".pth dosya yolu Çince karakter içermemelidir.",
+  "The index file path must not contain Chinese characters.": ".index dosya yolu Çince karakter içermemelidir.",
+  "Step algorithm": "Adım algoritması",
+  "Number of epoch processes": "Dönem işlem sayısı",
+  "Lowest points export": "En düşük noktaları dışa aktar",
+  "How many lowest points to save:": "Kaç en düşük noktanın kaydedileceği",
+  "Export lowest points of a model": "Bir modelin en düşük noktalarını dışa aktar",
+  "Output models:": "Modelleri dışa aktar",
+  "Stats of selected models:": "Seçilen modellerin istatistikleri",
+  "Custom f0 [Root pitch] File": "Özel f0 [Kök ton] Dosyası",
+  "Min pitch:": "Minimum ton yüksekliği:",
+  "Specify minimal pitch for inference [HZ]": "Çıkarsama için minimum ton yüksekliğini belirt [HZ]",
+  "Specify minimal pitch for inference [NOTE][OCTAVE]": "Çıkarsama için minimum ton yüksekliğini belirt [NOTA][OKTAV]",
+  "Max pitch:": "Maksimum ton yüksekliği:",
+  "Specify max pitch for inference [HZ]": "Çıkarsama için maksimum ton yüksekliğini belirt [HZ]",
+  "Specify max pitch for inference [NOTE][OCTAVE]": "Çıkarsama için maksimum ton yüksekliğini belirt [NOTA][OKTAV]",
+  "Browse presets for formanting": "Formant ayarları için ön ayarları göz at",
+  "Presets are located in formantshiftcfg/ folder": "Ön ayarlar formantshiftcfg/ klasöründe bulunur",
+  "Default value is 1.0": "Varsayılan değer 1.0'dır",
+  "Quefrency for formant shifting": "Formant kaydırma için kvarakfrekans",
+  "Timbre for formant shifting": "Formant kaydırma için timbre",
+  "Apply": "Uygula",
+  "Single": "Tek",
+  "Batch": "Toplu",
+  "Separate YouTube tracks": "YouTube parçalarını ayır",
+  "Download audio from a YouTube video and automatically separate the vocal and instrumental tracks": "YouTube videosundan ses indirin ve otomatik olarak vokal ve enstrümantal parçaları ayırın",
+  "Extra": "Ekstra",
+  "Merge": "Birleştir",
+  "Merge your generated audios with the instrumental": "Üretilen seslerinizi enstrümantal ile birleştirin",
+  "Choose your instrumental:": "Enstrümantal seçin:",
+  "Choose the generated audio:": "Üretilen sesi seçin:",
+  "Combine": "Birleştir",
+  "Download and Separate": "İndir ve Ayır",
+  "Enter the YouTube link:": "YouTube bağlantısını girin:",
+  "This section contains some extra utilities that often may be in experimental phases": "Bu bölüm genellikle deneysel aşamalarda olabilecek bazı ek hizmet programlarını içerir",
+  "Merge Audios": "Sesleri Birleştir",
+  "Audio files have been moved to the 'audios' folder.": "Ses dosyaları 'audios' klasörüne taşındı.",
+  "Downloading audio from the video...": "Videodan ses indiriliyor...",
+  "Audio downloaded!": "Ses indirildi!",
+  "An error occurred:": "Bir hata oluştu:",
+  "Separating audio...": "Ses ayrıştırılıyor...",
+  "File moved successfully.": "Dosya başarıyla taşındı.",
+  "Finished!": "Tamamlandı!",
+  "The source file does not exist.": "Kaynak dosya mevcut değil.",
+  "Error moving the file:": "Dosya taşınırken hata oluştu:",
+  "Downloading {name} from drive": "{name} Google Drive'dan indiriliyor",
+  "The attempt to download using Drive didn't work": "Drive kullanılarak indirme denemesi başarısız oldu",
+  "Error downloading the file: {str(e)}": "Dosya indirilirken hata oluştu: {str(e)}",
+  "Downloading {name} from mega": "{name} Mega'dan indiriliyor",
+  "Downloading {name} from basic url": "{name} temel URL'den indiriliyor",
+  "Download Audio": "Ses İndir",
+  "Download audios of any format for use in inference (recommended for mobile users).": "Çıkarsama için herhangi bir formatta ses indirin (mobil kullanıcılar için önerilir).",
+  "Any ConnectionResetErrors post-conversion are irrelevant and purely visual; they can be ignored.\n": "Dönüşümden sonra herhangi bir ConnectionResetErrors önemsizdir ve sadece görseldir; ihmal edilebilirler.\n",
+  "Processed audio saved at: ": "İşlenmiş ses kaydedildi: ",
+  "Conversion complete!": "Dönüşüm tamamlandı!",
+  "Reverb": "Yankı",
+  "Compressor": "Sıkıştırıcı",
+  "Noise Gate": "Gürültü Kapısı",
+  "Volume": "Ses Düzeyi",
+  "Drag the audio here and click the Refresh button": "Sesi buraya sürükleyin ve Yenile düğmesine tıklayın",
+  "Select the generated audio": "Üretilen sesi seçin",
+  "Volume of the instrumental audio:": "Enstrümantal sesin ses düzeyi:",
+  "Volume of the generated audio:": "Üretilen sesin ses düzeyi:",
+  "### Audio settings:": "### Ses ayarları:",
+  "### Instrumental settings:": "### Enstrümantal ayarları:",
+  "### Add the effects:": "### Efektleri ekle:",
+  "Starting audio conversion... (This might take a moment)": "Ses dönüşümü başlatılıyor... (Bu biraz zaman alabilir)",
+  "TTS Model:": "TTS Sesleri",
+  "TTS": "TTS",
+  "TTS Method:": "TTS Yöntemi",
+  "Audio TTS:": "Sesli TTS",
+  "Audio RVC:": "Sesli Model"
+}
diff --git a/i18n/locale/ur_UR.json b/i18n/locale/ur_UR.json
new file mode 100644
index 0000000000000000000000000000000000000000..e58c68312476bbe2fe512cab31e8c05d7799e490
--- /dev/null
+++ b/i18n/locale/ur_UR.json
@@ -0,0 +1,247 @@
+{
+  "Unfortunately, there is no compatible GPU available to support your training.": "بدقسمتی سے، آپ کی تربیت کو سپورٹ کرنے کے لیے کوئی ہم آہنگ GPU دستیاب نہیں ہے۔",
+  "Yes": "جی ہاں",
+  "Select your dataset:": "اپنا ڈیٹا سیٹ منتخب کریں۔",
+  "Update list": "فہرست کو اپ ڈیٹ کریں۔",
+  "Download Model": "ماڈل ڈاؤن لوڈ کریں۔",
+  "Download Backup": "بیک اپ ڈاؤن لوڈ کریں۔",
+  "Download Dataset": "ڈیٹا سیٹ ڈاؤن لوڈ کریں۔",
+  "Download": "ڈاؤن لوڈ کریں",
+  "Url:": "یو آر ایل:",
+  "Build the index before saving.": "محفوظ کرنے سے پہلے انڈیکس بنائیں۔",
+  "Save your model once the training ends.": "ٹریننگ ختم ہونے کے بعد اپنے ماڈل کو محفوظ کریں۔",
+  "Save type": "قسم محفوظ کریں۔",
+  "Save model": "ماڈل کو محفوظ کریں۔",
+  "Choose the method": "طریقہ منتخب کریں۔",
+  "Save all": "محفوظ کریں",
+  "Save D and G": "ڈی اور جی کو محفوظ کریں۔",
+  "Save voice": "آواز محفوظ کریں۔",
+  "Downloading the file: ": "فائل ڈاؤن لوڈ کرنا:",
+  "Stop training": "تربیت بند کرو",
+  "Too many users have recently viewed or downloaded this file": "بہت سارے صارفین نے حال ہی میں اس فائل کو دیکھا یا ڈاؤن لوڈ کیا ہے۔",
+  "Cannot get file from this private link": "اس نجی لنک سے فائل حاصل نہیں کی جا سکتی",
+  "Full download": "مکمل ڈاؤن لوڈ",
+  "An error occurred downloading": "ڈاؤن لوڈ کرنے میں ایک خرابی پیش آگئی",
+  "Model saved successfully": "ماڈل کامیابی سے محفوظ ہو گیا۔",
+  "Saving the model...": "ماڈل محفوظ ہو رہا ہے...",
+  "Saved without index...": "انڈیکس کے بغیر محفوظ کیا گیا...",
+  "model_name": "ماڈل_نام",
+  "Saved without inference model...": "بغیر کسی اندازہ کے ماڈل کے محفوظ کیا گیا...",
+  "An error occurred saving the model": "ماڈل کو محفوظ کرنے میں ایک خرابی پیش آگئی",
+  "The model you want to save does not exist, be sure to enter the correct name.": "آپ جس ماڈل کو محفوظ کرنا چاہتے ہیں وہ موجود نہیں ہے، درست نام ضرور درج کریں۔",
+  "The file could not be downloaded.": "فائل ڈاؤن لوڈ نہیں ہو سکی۔",
+  "Unzip error.": "ان زپ کی خرابی۔",
+  "Path to your added.index file (if it didn't automatically find it)": "آپ کی add.index فائل کا راستہ (اگر یہ خود بخود اسے نہیں مل پاتی ہے)",
+  "It has been downloaded successfully.": "اسے کامیابی کے ساتھ ڈاؤن لوڈ کر لیا گیا ہے۔",
+  "Proceeding with the extraction...": "نکالنے کے ساتھ آگے بڑھ رہا ہے...",
+  "The Backup has been uploaded successfully.": "بیک اپ کامیابی کے ساتھ اپ لوڈ ہو گیا ہے۔",
+  "The Dataset has been loaded successfully.": "ڈیٹا سیٹ کامیابی کے ساتھ لوڈ ہو گیا ہے۔",
+  "The Model has been loaded successfully.": "ماڈل کامیابی کے ساتھ لوڈ ہو گیا ہے۔",
+  "It is used to download your inference models.": "یہ آپ کے انفرنس ماڈلز کو ڈاؤن لوڈ کرنے کے لیے استعمال ہوتا ہے۔",
+  "It is used to download your training backups.": "یہ آپ کے تربیتی بیک اپ کو ڈاؤن لوڈ کرنے کے لیے استعمال ہوتا ہے۔",
+  "Download the dataset with the audios in a compatible format (.wav/.flac) to train your model.": "اپنے ماڈل کو تربیت دینے کے لیے ڈیٹاسیٹ کو آڈیوز کے ساتھ مطابقت پذیر فارمیٹ (.wav/.flac) میں ڈاؤن لوڈ کریں۔",
+  "No relevant file was found to upload.": "اپ لوڈ کرنے کے لیے کوئی متعلقہ فائل نہیں ملی۔",
+  "The model works for inference, and has the .index file.": "ماڈل تخمینہ کے لیے کام کرتا ہے، اور اس میں .index فائل ہے۔",
+  "The model works for inference, but it doesn't have the .index file.": "ماڈل تخمینہ کے لیے کام کرتا ہے، لیکن اس میں .index فائل نہیں ہے۔",
+  "This may take a few minutes, please wait...": "اس میں کچھ منٹ لگ سکتے ہیں، براہ کرم انتظار کریں...",
+  "Resources": "حوالہ جات",
+  "Step 1: Processing data": "مرحلہ 1: ڈیٹا پر کارروائی کرنا",
+  "Step 2: Skipping pitch extraction": "مرحلہ 2a: پچ نکالنا چھوڑنا",
+  "Step 3: Extracting features": "مرحلہ 2b: خصوصیات کو نکالنا",
+  "Step 4: Model training started": "مرحلہ 3a: ماڈل ٹریننگ شروع ہوئی۔",
+  "Step 5: Export lowest points on a graph of the model": "مرحلہ 4: ماڈل کے گراف پر سب سے کم پوائنٹس برآمد کریں۔",
+  "Training is done, check train.log": "ٹریننگ ہو چکی ہے، ٹرین ڈاٹ لاگ چیک کریں۔",
+  "All processes have been completed!": "تمام عمل مکمل ہو چکے ہیں!",
+  "Model Inference": "ماڈل کا اندازہ",
+  "Inferencing voice:": "اندازہ لگانے والی آواز:",
+  "Model_Name": "ماڈل_نام",
+  "Dataset_Name": "ڈیٹا سیٹ_نام",
+  "Whether the model has pitch guidance.": "آیا ماڈل میں پچ گائیڈنس ہے۔",
+  "Whether to save only the latest .ckpt file to save hard drive space": "آیا ہارڈ ڈرائیو کی جگہ بچانے کے لیے صرف تازہ ترین .ckpt فائل کو محفوظ کرنا ہے۔",
+  "Cache all training sets to GPU memory. Caching small datasets (less than 10 minutes) can speed up training": "تمام تربیتی سیٹوں کو GPU میموری میں کیش کریں۔ چھوٹے ڈیٹا سیٹس (10 منٹ سے کم) کیشنگ ٹریننگ کو تیز کر سکتی ہے۔",
+  "Save a small final model to the 'weights' folder at each save point": "ہر سیو پوائنٹ پر ایک چھوٹا فائنل ماڈل 'وزن' فولڈر میں محفوظ کریں۔",
+  "Refresh": "آواز کی فہرست، انڈیکس پاتھ اور آڈیو فائلوں کو ریفریش کریں۔",
+  "Unload voice to save GPU memory": "GPU میموری کو بچانے کے لیے آواز اتاریں:",
+  "Select Speaker/Singer ID:": "اسپیکر/گلوکار کی شناخت منتخب کریں:",
+  "Recommended +12 key for male to female conversion, and -12 key for female to male conversion. If the sound range goes too far and the voice is distorted, you can also adjust it to the appropriate range by yourself.": "مرد سے خاتون کی تبدیلی کے لیے تجویز کردہ +12 کلید، اور عورت سے مرد کی تبدیلی کے لیے -12 کلید۔ اگر آواز کی حد بہت دور جاتی ہے اور آواز بگڑ جاتی ہے، تو آپ اسے خود بھی مناسب رینج میں ایڈجسٹ کر سکتے ہیں۔",
+  "Transpose (integer, number Fof semitones, raise by an octave: 12, lower by an octave: -12):": "ٹرانسپوز (انٹیجر، سیمیٹونز کی تعداد، ایک آکٹیو سے بڑھائیں: 12، ایک آکٹیو سے کم: -12):",
+  "Enter the path of the audio file to be processed (default is the correct format example):": "کارروائی کی جانے والی آڈیو فائل کا راستہ درج کریں (پہلے سے طے شدہ فارمیٹ کی صحیح مثال ہے):",
+  "Select the pitch extraction algorithm:": "پچ نکالنے کا الگورتھم منتخب کریں:",
+  "Mangio-Crepe Hop Length (Only applies to mangio-crepe): Hop length refers to the time it takes for the speaker to jump to a dramatic pitch. Lower hop lengths take more time to infer but are more pitch accurate.": "Mangio-Crepe Hop Length (صرف mangio-crepe پر لاگو ہوتا ہے): ہاپ کی لمبائی سے مراد وہ وقت ہوتا ہے جو اسپیکر کو ڈرامائی انداز میں چھلانگ لگانے میں لگتا ہے۔ نچلی ہاپ کی لمبائی کا اندازہ لگانے میں زیادہ وقت لگتا ہے لیکن پچ زیادہ درست ہوتی ہے۔",
+  "Feature search dataset file path": "فیچر سرچ ڈیٹاسیٹ فائل پاتھ",
+  "If >=3: apply median filtering to the harvested pitch results. The value represents the filter radius and can reduce breathiness.": "اگر >=3: کٹائی ہوئی پچ کے نتائج پر میڈین فلٹرنگ لگائیں۔ قدر فلٹر کے رداس کی نمائندگی کرتی ہے اور سانس لینے میں کمی کر سکتی ہے۔",
+  "Path to the feature index file. Leave blank to use the selected result from the dropdown:": "فیچر انڈیکس فائل کا راستہ۔ ڈراپ ڈاؤن سے منتخب کردہ نتیجہ کو استعمال کرنے کے لیے خالی چھوڑ دیں:",
+  "Auto-detect index path and select from the dropdown:": "انڈیکس پاتھ کا خود بخود پتہ لگائیں اور ڈراپ ڈاؤن سے منتخب کریں۔",
+  "Path to feature file:": "فیچر فائل کا راستہ:",
+  "Search feature ratio:": "تلاش کی خصوصیت کا تناسب:",
+  "Resample the output audio in post-processing to the final sample rate. Set to 0 for no resampling:": "پوسٹ پروسیسنگ میں آؤٹ پٹ آڈیو کو حتمی نمونے کی شرح پر دوبارہ نمونہ دیں۔ دوبارہ نمونے لینے کے لیے 0 پر سیٹ کریں:",
+  "Use the volume envelope of the input to replace or mix with the volume envelope of the output. The closer the ratio is to 1, the more the output envelope is used:": "آؤٹ پٹ کے والیوم لفافے کو تبدیل کرنے یا ملانے کے لیے ان پٹ کے والیوم لفافے کا استعمال کریں۔ تناسب 1 کے جتنا قریب ہوگا، اتنا ہی زیادہ آؤٹ پٹ لفافہ استعمال ہوتا ہے:",
+  "Protect voiceless consonants and breath sounds to prevent artifacts such as tearing in electronic music. Set to 0.5 to disable. Decrease the value to increase protection, but it may reduce indexing accuracy:": "الیکٹرونک میوزک میں پھاڑنے جیسے فن پاروں کو روکنے کے لیے بے آواز تلفظ اور سانس کی آوازوں کی حفاظت کریں۔ غیر فعال کرنے کے لیے 0.5 پر سیٹ کریں۔ تحفظ کو بڑھانے کے لیے قدر کو کم کریں، لیکن یہ اشاریہ سازی کی درستگی کو کم کر سکتا ہے:",
+  "F0 curve file (optional). One pitch per line. Replaces the default F0 and pitch modulation:": "F0 وکر فائل (اختیاری)۔ فی لائن ایک پچ۔ پہلے سے طے شدہ F0 اور پچ ماڈیولیشن کو بدل دیتا ہے:",
+  "Convert": "تبدیل کریں",
+  "Output information:": "آؤٹ پٹ کی معلومات",
+  "Export audio (click on the three dots in the lower right corner to download)": "آڈیو برآمد کریں (ڈاؤن لوڈ کرنے کے لیے نیچے دائیں کونے میں تین نقطوں پر کلک کریں)",
+  "Batch conversion. Enter the folder containing the audio files to be converted or upload multiple audio files. The converted audio will be output in the specified folder (default: 'opt').": "بیچ کی تبدیلی۔ وہ فولڈر درج کریں جس میں آڈیو فائلیں تبدیل کی جائیں یا متعدد آڈیو فائلیں اپ لوڈ کریں۔ تبدیل شدہ آڈیو مخصوص فولڈر میں آؤٹ پٹ ہو گا (پہلے سے طے شدہ: 'opt')۔",
+  "Specify output folder:": "آؤٹ پٹ فولڈر کی وضاحت کریں:",
+  "Enter the path of the audio folder to be processed (copy it from the address bar of the file manager):": "آڈیو فولڈر کا راستہ درج کریں جس پر کارروائی کی جائے (اسے فائل مینیجر کے ایڈریس بار سے کاپی کریں):",
+  "You can also input audio files in batches. Choose one of the two options. Priority is given to reading from the folder.": "آپ آڈیو فائلوں کو بیچوں میں بھی ڈال سکتے ہیں۔ دو آپشنز میں سے ایک کا انتخاب کریں۔ فولڈر سے پڑھنے کو ترجیح دی جاتی ہے۔",
+  "Export file format": "فائل کی شکل برآمد کریں۔",
+  "UVR5": "UVR5",
+  "Enter the path of the audio folder to be processed:": "جس آڈیو فولڈر پر کارروائی کی جائے گی اس کا راستہ درج کریں:",
+  "Model": "ماڈل",
+  "Vocal Extraction Aggressive": "آواز نکالنا جارحانہ",
+  "Specify the output folder for vocals:": "آواز کے لیے آؤٹ پٹ فولڈر کی وضاحت کریں:",
+  "Specify the output folder for accompaniment:": "ساتھ کے لیے آؤٹ پٹ فولڈر کی وضاحت کریں:",
+  "Train": "ٹرین",
+  "Enter the model name:": "ماڈل کا نام درج کریں:",
+  "Target sample rate:": "ہدف نمونہ کی شرح:",
+  "Whether the model has pitch guidance (required for singing, optional for speech):": "آیا ماڈل میں پچ گائیڈنس ہے (گانے کے لیے ضروری، تقریر کے لیے اختیاری):",
+  "Version": "ورژن",
+  "Number of CPU processes:": "پچ نکالنے اور ڈیٹا پروسیسنگ کے لیے استعمال ہونے والے CPU عملوں کی تعداد:",
+  "Enter the path of the training folder:": "ٹریننگ فولڈر کا راستہ درج کریں:",
+  "Specify the model ID:": "براہ کرم ماڈل ID کی وضاحت کریں:",
+  "Auto detect audio path and select from the dropdown:": "آڈیو پاتھ کا خود بخود پتہ لگائیں اور ڈراپ ڈاؤن سے منتخب کریں:",
+  "Add audio's name to the path to the audio file to be processed (default is the correct format example) Remove the path to use an audio from the dropdown list:": "آڈیو فائل کے راستے میں آڈیو کا نام شامل کریں جس پر کارروائی کی جائے (پہلے سے طے شدہ فارمیٹ کی صحیح مثال ہے) ڈراپ ڈاؤن فہرست سے آڈیو استعمال کرنے کے لیے راستے کو ہٹا دیں:",
+  "Advanced Settings": "اعلی درجے کی ترتیبات",
+  "Settings": "ترتیبات",
+  "Status:": "حالت",
+  "Process data": "ڈیٹا پر کارروائی کریں۔",
+  "Drag your audio here:": "اپنے آڈیو کو یہاں گھسیٹیں اور ریفریش بٹن کو دبائیں۔",
+  "Or record an audio:": "یا آڈیو ریکارڈ کریں۔",
+  "Formant shift inference audio": "فارمینٹ شفٹ انفرنس آڈیو",
+  "Used for male to female and vice-versa conversions": "مرد سے عورت اور اس کے برعکس تبادلوں کے لیے استعمال کیا جاتا ہے۔",
+  "Provide the GPU index(es) separated by '-', like 0-1-2 for using GPUs 0, 1, and 2:": "براہ کرم '-' سے الگ کردہ GPU انڈیکس فراہم کریں، جیسے GPUs 0، 1، اور 2 استعمال کرنے کے لیے 0-1-2:",
+  "GPU Information:": "GPU کی معلومات",
+  "Feature extraction": "خصوصیت کا اخراج",
+  "Save frequency:": "تعدد کو محفوظ کریں:",
+  "Training epochs:": "تربیتی دور:",
+  "Batch size per GPU:": "بیچ سائز فی GPU:",
+  "Save only the latest '.ckpt' file to save disk space:": "ڈسک کی جگہ بچانے کے لیے صرف تازہ ترین '.ckpt' فائل کو محفوظ کریں:",
+  "No": "نہیں",
+  "Save a small final model to the 'weights' folder at each save point:": "ہر سیو پوائنٹ پر ایک چھوٹا فائنل ماڈل 'وزن' فولڈر میں محفوظ کریں:",
+  "Load pre-trained base model G path:": "پہلے سے تربیت یافتہ بیس ماڈل جی پاتھ لوڈ کریں:",
+  "Load pre-trained base model D path:": "پہلے سے تربیت یافتہ بیس ماڈل ڈی پاتھ لوڈ کریں:",
+  "Train model": "ٹرین ماڈل",
+  "Train feature index": "ٹرین فیچر انڈیکس",
+  "One-click training": "ایک کلک کی تربیت",
+  "Processing": "پروسیسنگ",
+  "Model fusion, can be used to test timbre fusion": "ماڈل فیوژن، ٹمبر فیوژن کو جانچنے کے لیے استعمال کیا جا سکتا ہے۔",
+  "Path to Model A:": "ماڈل A کا راستہ:",
+  "Path to Model B:": "ماڈل B کا راستہ:",
+  "Weight for Model A:": "ماڈل A کے لیے وزن:",
+  "Whether the model has pitch guidance:": "آیا ماڈل میں پچ گائیڈنس ہے:",
+  "Model information to be placed:": "ماڈل کی معلومات رکھی جائے گی:",
+  "Model architecture version:": "ماڈل آرکیٹیکچر ورژن:",
+  "Fusion": "امتزاج",
+  "Modify model information": "ماڈل کی معلومات میں ترمیم کریں۔",
+  "Path to Model:": "ماڈل کا راستہ:",
+  "Model information to be modified:": "ماڈل کی معلومات میں ترمیم کی جائے گی:",
+  "Save file name:": "فائل کا نام محفوظ کریں:",
+  "Modify": "ترمیم کریں۔",
+  "View model information": "ماڈل کی معلومات دیکھیں",
+  "View": "دیکھیں",
+  "Model extraction": "ماڈل نکالنا ('لاگز' فولڈر کے نیچے بڑی فائل ماڈل کا راستہ داخل کریں)۔ یہ مفید ہے اگر آپ تربیت کو آدھے راستے سے روکنا چاہتے ہیں اور دستی طور پر ایک چھوٹی ماڈل فائل کو نکالنا اور محفوظ کرنا چاہتے ہیں، یا اگر آپ انٹرمیڈیٹ ماڈل کی جانچ کرنا چاہتے ہیں:",
+  "Name:": "نام محفوظ کریں:",
+  "Whether the model has pitch guidance (1: yes, 0: no):": "آیا ماڈل میں پچ گائیڈنس ہے (1: ہاں، 0: نہیں):",
+  "Extract": "نکالنا",
+  "Export Onnx": "Onnx برآمد کریں۔",
+  "RVC Model Path:": "RVC ماڈل کا راستہ:",
+  "Onnx Export Path:": "Onnx برآمد کا راستہ:",
+  "MoeVS Model": "MoeVS ماڈل",
+  "Export Onnx Model": "Onnx ماڈل برآمد کریں۔",
+  "Load model": "لوڈ ماڈل",
+  "Hubert Model": "ہیوبرٹ ماڈل",
+  "Select the .pth file": ".pth فائل کو منتخب کریں۔",
+  "Select the .index file": ".index فائل کو منتخب کریں۔",
+  "Select the .npy file": ".npy فائل کو منتخب کریں۔",
+  "Input device": "ان پٹ ڈیوائس",
+  "Output device": "آؤٹ پٹ ڈیوائس",
+  "Audio device (please use the same type of driver)": "آڈیو ڈیوائس (براہ کرم ایک ہی قسم کا ڈرائیور استعمال کریں)",
+  "Response threshold": "جوابی حد",
+  "Pitch settings": "پچ کی ترتیبات",
+  "Whether to use note names instead of their hertz value. E.G. [C5, D6] instead of [523.25, 1174.66]Hz": "آیا نوٹ کے نام ان کی ہرٹز قدر کے بجائے استعمال کیے جائیں۔ ای جی [C5, D6] بجائے [523.25, 1174.66]Hz",
+  "Index Rate": "انڈیکس ریٹ",
+  "General settings": "عام ترتیبات",
+  "Sample length": "نمونہ کی لمبائی",
+  "Fade length": "دھندلا لمبائی",
+  "Extra inference time": "اضافی تخمینہ کا وقت",
+  "Input noise reduction": "ان پٹ شور کی کمی",
+  "Output noise reduction": "آؤٹ پٹ شور کی کمی",
+  "Performance settings": "کارکردگی کی ترتیبات",
+  "Start audio conversion": "آڈیو کی تبدیلی شروع کریں۔",
+  "Stop audio conversion": "آڈیو تبادلوں کو روکیں۔",
+  "Inference time (ms):": "انفرنس ٹائم (ms):",
+  "Select the pth file": "pth فائل کو منتخب کریں۔",
+  "Select the .index file:": "انڈیکس فائل کو منتخب کریں۔",
+  "The hubert model path must not contain Chinese characters": "ہیوبرٹ ماڈل پاتھ میں چینی حروف نہیں ہونے چاہئیں",
+  "The pth file path must not contain Chinese characters.": "pth فائل کا راستہ چینی حروف پر مشتمل نہیں ہونا چاہیے۔",
+  "The index file path must not contain Chinese characters.": "انڈیکس فائل کا راستہ چینی حروف پر مشتمل نہیں ہونا چاہیے۔",
+  "Step algorithm": "مرحلہ الگورتھم",
+  "Number of epoch processes": "عہد کے عمل کی تعداد",
+  "Lowest points export": "کم ترین پوائنٹس کی برآمد",
+  "How many lowest points to save:": "کتنے کم پوائنٹس کو بچانا ہے۔",
+  "Export lowest points of a model": "ماڈل کے سب سے کم پوائنٹس برآمد کریں۔",
+  "Output models:": "آؤٹ پٹ ماڈلز",
+  "Stats of selected models:": "منتخب ماڈلز کے اعدادوشمار",
+  "Custom f0 [Root pitch] File": "اپنی مرضی کے مطابق f0 [روٹ پچ] فائل",
+  "Min pitch:": "منٹ پچ",
+  "Specify minimal pitch for inference [HZ]": "تخمینہ کے لیے کم سے کم پچ کی وضاحت کریں [HZ]",
+  "Specify minimal pitch for inference [NOTE][OCTAVE]": "قیاس کے لیے کم سے کم پچ کی وضاحت کریں [NOTE][OCTAVE]",
+  "Max pitch:": "زیادہ سے زیادہ پچ",
+  "Specify max pitch for inference [HZ]": "تخمینہ کے لیے زیادہ سے زیادہ پچ کی وضاحت کریں [HZ]",
+  "Specify max pitch for inference [NOTE][OCTAVE]": "تخمینہ کے لیے زیادہ سے زیادہ پچ کی وضاحت کریں [NOTE][OCTAVE]",
+  "Browse presets for formanting": "فارمیٹنگ کے لیے پیش سیٹوں کو براؤز کریں۔",
+  "Presets are located in formantshiftcfg/ folder": "presets formantshiftcfg/ فولڈر میں واقع ہیں۔",
+  "Default value is 1.0": "پہلے سے طے شدہ قدر 1.0 ہے۔",
+  "Quefrency for formant shifting": "فارمینٹ شفٹنگ کے لیے Quefrency",
+  "Timbre for formant shifting": "فارمینٹ شفٹنگ کے لیے ٹمبر",
+  "Apply": "درخواست دیں",
+  "Single": "سنگل",
+  "Batch": "بیچ",
+  "Separate YouTube tracks": "یوٹیوب ٹریکس کو الگ کریں۔",
+  "Download audio from a YouTube video and automatically separate the vocal and instrumental tracks": "یوٹیوب ویڈیو سے آڈیو ڈاؤن لوڈ کریں اور خودکار طور پر آواز اور ساز کے ٹریک کو الگ کریں۔",
+  "Extra": "اضافی",
+  "Merge": "ضم",
+  "Merge your generated audios with the instrumental": "اپنے تیار کردہ آڈیوز کو انسٹرومینٹل کے ساتھ ضم کریں۔",
+  "Choose your instrumental:": "اپنے آلے کا انتخاب کریں۔",
+  "Choose the generated audio:": "تیار کردہ آڈیو کا انتخاب کریں۔",
+  "Combine": "یکجا",
+  "Download and Separate": "ڈاؤن لوڈ کریں اور الگ کریں۔",
+  "Enter the YouTube link:": "یوٹیوب کا لنک درج کریں۔",
+  "This section contains some extra utilities that often may be in experimental phases": "اس حصے میں کچھ اضافی افادیتیں ہیں جو اکثر تجرباتی مراحل میں ہو سکتی ہیں۔",
+  "Merge Audios": "آڈیوز کو ضم کریں۔",
+  "Audio files have been moved to the 'audios' folder.": "آڈیو فائلوں کو 'آڈیوز' فولڈر میں منتقل کر دیا گیا ہے۔",
+  "Downloading audio from the video...": "ویڈیو سے آڈیو ڈاؤن لوڈ ہو رہا ہے...",
+  "Audio downloaded!": "آڈیو ڈاؤن لوڈ!",
+  "An error occurred:": "ایک خرابی آگئی:",
+  "Separating audio...": "آڈیو کو الگ کیا جا رہا ہے...",
+  "File moved successfully.": "فائل کامیابی سے منتقل ہو گئی۔",
+  "Finished!": "ختم!",
+  "The source file does not exist.": "سورس فائل موجود نہیں ہے۔",
+  "Error moving the file:": "فائل کو منتقل کرنے میں خرابی:",
+  "Downloading {name} from drive": "ڈرائیو سے {name} ڈاؤن لوڈ ہو رہا ہے۔",
+  "The attempt to download using Drive didn't work": "Drive کا استعمال کرتے ہوئے ڈاؤن لوڈ کرنے کی کوشش نے کام نہیں کیا۔",
+  "Error downloading the file: {str(e)}": "فائل ڈاؤن لوڈ کرنے میں خرابی: {str(e)}",
+  "Downloading {name} from mega": "میگا سے {name} ڈاؤن لوڈ ہو رہا ہے۔",
+  "Downloading {name} from basic url": "بنیادی url سے {name} ڈاؤن لوڈ ہو رہا ہے۔",
+  "Download Audio": "آڈیو ڈاؤن لوڈ کریں۔",
+  "Download audios of any format for use in inference (recommended for mobile users).": "کسی بھی فارمیٹ کے آڈیوز کو قیاس میں استعمال کرنے کے لیے ڈاؤن لوڈ کریں (موبائل صارفین کے لیے تجویز کردہ)",
+  "Any ConnectionResetErrors post-conversion are irrelevant and purely visual; they can be ignored.\n": "تبدیلی کے بعد کی کوئی بھی ConnectionResetErrors غیر متعلقہ اور خالصتاً بصری ہیں۔ انہیں نظر انداز کیا جا سکتا ہے.",
+  "Processed audio saved at: ": "پروسیس شدہ آڈیو کو محفوظ کیا گیا:",
+  "Conversion complete!": "تبدیلی مکمل!",
+  "Reverb": "Reverb",
+  "Compressor": "کمپریسر",
+  "Noise Gate": "شور گیٹ",
+  "Volume": "حجم",
+  "Drag the audio here and click the Refresh button": "آڈیو کو یہاں گھسیٹیں اور ریفریش بٹن پر کلک کریں۔",
+  "Select the generated audio": "تیار کردہ آڈیو کو منتخب کریں۔",
+  "Volume of the instrumental audio:": "آلہ ساز آڈیو کا حجم",
+  "Volume of the generated audio:": "تیار کردہ آڈیو کا حجم",
+  "### Add the effects": "### اثرات شامل کریں۔",
+  "Starting audio conversion... (This might take a moment)": "آڈیو کنورشن شروع ہورہی ہے... (یہ تھوڑی دیر لگ سکتی ہے)",
+  "TTS Model:": "TTS آوازیں",
+  "TTS": "TTS",
+  "TTS Method:": "TTS میثاق",
+  "Audio TTS:": "آڈیو TTS",
+  "Audio RVC:": "آڈیو ماڈل"
+}
diff --git a/i18n/locale/zh_CN.json b/i18n/locale/zh_CN.json
new file mode 100644
index 0000000000000000000000000000000000000000..c1c1b420120e32978b44d8aa0002e9a023a901d8
--- /dev/null
+++ b/i18n/locale/zh_CN.json
@@ -0,0 +1,247 @@
+{
+  "Unfortunately, there is no compatible GPU available to support your training.": "不幸的是，没有可用的兼容 GPU 来支持您的训练。",
+  "Yes": "是的",
+  "Select your dataset:": "选择您的数据集。",
+  "Update list": "更新列表。",
+  "Download Model": "下载模型",
+  "Download Backup": "下载备份",
+  "Download Dataset": "下载数据集",
+  "Download": "下载",
+  "Url:": "网址：",
+  "Build the index before saving.": "保存前构建索引。",
+  "Save your model once the training ends.": "训练结束后保存您的模型。",
+  "Save type": "保存类型",
+  "Save model": "保存模型",
+  "Choose the method": "选择方法",
+  "Save all": "保存全部",
+  "Save D and G": "保存D和G",
+  "Save voice": "保存语音",
+  "Downloading the file: ": "下载文件：",
+  "Stop training": "停止训练",
+  "Too many users have recently viewed or downloaded this file": "最近有太多用户查看或下载了此文件",
+  "Cannot get file from this private link": "无法从此私人链接获取文件",
+  "Full download": "完整下载",
+  "An error occurred downloading": "下载时发生错误",
+  "Model saved successfully": "模型保存成功",
+  "Saving the model...": "保存模型...",
+  "Saved without index...": "保存时没有索引...",
+  "model_name": "型号名称",
+  "Saved without inference model...": "保存时没有推理模型...",
+  "An error occurred saving the model": "保存模型时出错",
+  "The model you want to save does not exist, be sure to enter the correct name.": "您要保存的模型不存在，请务必输入正确的名称。",
+  "The file could not be downloaded.": "无法下载该文件。",
+  "Unzip error.": "解压错误。",
+  "Path to your added.index file (if it didn't automatically find it)": "添加的.index 文件的路径（如果没有自动找到它）",
+  "It has been downloaded successfully.": "已经下载成功了。",
+  "Proceeding with the extraction...": "继续提取...",
+  "The Backup has been uploaded successfully.": "备份已成功上传。",
+  "The Dataset has been loaded successfully.": "数据集已成功加载。",
+  "The Model has been loaded successfully.": "模型已成功加载。",
+  "It is used to download your inference models.": "它用于下载您的推理模型。",
+  "It is used to download your training backups.": "它用于下载您的训练备份。",
+  "Download the dataset with the audios in a compatible format (.wav/.flac) to train your model.": "下载包含兼容格式 (.wav/.flac) 音频的数据集来训练您的模型。",
+  "No relevant file was found to upload.": "没有找到相关文件可以上传。",
+  "The model works for inference, and has the .index file.": "该模型用于推理，并具有 .index 文件。",
+  "The model works for inference, but it doesn't have the .index file.": "该模型适用于推理，但没有 .index 文件。",
+  "This may take a few minutes, please wait...": "这可能需要几分钟，请稍候...",
+  "Resources": "资源",
+  "Step 1: Processing data": "步骤一：处理数据",
+  "Step 2: Skipping pitch extraction": "步骤 2a：跳过音调提取",
+  "Step 3: Extracting features": "步骤2b：提取特征",
+  "Step 4: Model training started": "步骤3a：模型训练开始",
+  "Step 5: Export lowest points on a graph of the model": "步骤 4：导出模型图表上的最低点",
+  "Training is done, check train.log": "训练完成，查看train.log",
+  "All processes have been completed!": "所有流程已完成！",
+  "Model Inference": "模型推理",
+  "Inferencing voice:": "推理语音：",
+  "Model_Name": "型号名称",
+  "Dataset_Name": "数据集_名称",
+  "Whether the model has pitch guidance.": "模型是否有俯仰引导。",
+  "Whether to save only the latest .ckpt file to save hard drive space": "是否仅保存最新的.ckpt文件以节省硬盘空间",
+  "Cache all training sets to GPU memory. Caching small datasets (less than 10 minutes) can speed up training": "将所有训练集缓存到 GPU 内存。缓存小数据集（少于 10 分钟）可以加快训练速度",
+  "Save a small final model to the 'weights' folder at each save point": "在每个保存点将一个小的最终模型保存到“权重”文件夹中",
+  "Refresh": "刷新语音列表、索引路径和音频文件",
+  "Unload voice to save GPU memory": "卸载语音以节省 GPU 内存：",
+  "Select Speaker/Singer ID:": "选择演讲者/歌手 ID：",
+  "Recommended +12 key for male to female conversion, and -12 key for female to male conversion. If the sound range goes too far and the voice is distorted, you can also adjust it to the appropriate range by yourself.": "建议+12键用于男性到女性的转换，-12键用于女性到男性的转换。如果音域走得太远，声音失真，也可以自行调整到合适的音域。",
+  "Transpose (integer, number Fof semitones, raise by an octave: 12, lower by an octave: -12):": "移调（整数，半音数，升高八度：12，降低八度：-12）：",
+  "Enter the path of the audio file to be processed (default is the correct format example):": "输入要处理的音频文件的路径（默认为正确格式示例）：",
+  "Select the pitch extraction algorithm:": "选择音高提取算法：",
+  "Mangio-Crepe Hop Length (Only applies to mangio-crepe): Hop length refers to the time it takes for the speaker to jump to a dramatic pitch. Lower hop lengths take more time to infer but are more pitch accurate.": "Mangio-Crepe 跳跃长度（仅适用于 mangio-crepe）：跳跃长度是指说话者跳跃到戏剧性音高所需的时间。较短的跳跃长度需要更多的时间来推断，但音高更准确。",
+  "Feature search dataset file path": "特征搜索数据集文件路径",
+  "If >=3: apply median filtering to the harvested pitch results. The value represents the filter radius and can reduce breathiness.": "如果 >=3：对收获的音高结果应用中值滤波。该值代表过滤半径，可以减少呼吸味。",
+  "Path to the feature index file. Leave blank to use the selected result from the dropdown:": "功能索引文件的路径。留空以使用下拉列表中选定的结果：",
+  "Auto-detect index path and select from the dropdown:": "自动检测索引路径并从下拉列表中选择",
+  "Path to feature file:": "功能文件的路径：",
+  "Search feature ratio:": "搜索特征比例：",
+  "Resample the output audio in post-processing to the final sample rate. Set to 0 for no resampling:": "在后处理中将输出音频重新采样到最终采样率。设置为 0 表示不重采样：",
+  "Use the volume envelope of the input to replace or mix with the volume envelope of the output. The closer the ratio is to 1, the more the output envelope is used:": "使用输入的音量包络来替换或与输出的音量包络混合。该比率越接近 1，使用的输出包络就越多：",
+  "Protect voiceless consonants and breath sounds to prevent artifacts such as tearing in electronic music. Set to 0.5 to disable. Decrease the value to increase protection, but it may reduce indexing accuracy:": "保护清辅音和呼吸音，以防止电子音乐中出现撕裂等伪影。设置为 0.5 以禁用。减小该值可增强保护，但可能会降低索引精度：",
+  "F0 curve file (optional). One pitch per line. Replaces the default F0 and pitch modulation:": "F0 曲线文件（可选）。每行一个音高。替换默认的 F0 和音调调制：",
+  "Convert": "转变",
+  "Output information:": "输出信息",
+  "Export audio (click on the three dots in the lower right corner to download)": "导出音频（点击右下角三点即可下载）",
+  "Batch conversion. Enter the folder containing the audio files to be converted or upload multiple audio files. The converted audio will be output in the specified folder (default: 'opt').": "批量转换。输入包含要转换的音频文件的文件夹或上传多个音频文件。转换后的音频将输出到指定文件夹（默认：“opt”）。",
+  "Specify output folder:": "指定输出文件夹：",
+  "Enter the path of the audio folder to be processed (copy it from the address bar of the file manager):": "输入要处理的音频文件夹路径（从文件管理器地址栏复制）：",
+  "You can also input audio files in batches. Choose one of the two options. Priority is given to reading from the folder.": "您还可以批量输入音频文件。选择两个选项之一。优先从文件夹中读取。",
+  "Export file format": "导出文件格式",
+  "UVR5": "紫外线5",
+  "Enter the path of the audio folder to be processed:": "输入要处理的音频文件夹路径：",
+  "Model": "模型",
+  "Vocal Extraction Aggressive": "声音提取 攻击性",
+  "Specify the output folder for vocals:": "指定人声的输出文件夹：",
+  "Specify the output folder for accompaniment:": "指定伴奏的输出文件夹：",
+  "Train": "火车",
+  "Enter the model name:": "输入型号名称：",
+  "Target sample rate:": "目标采样率：",
+  "Whether the model has pitch guidance (required for singing, optional for speech):": "模型是否有音调引导（唱歌时需要，语音时可选）：",
+  "Version": "版本",
+  "Number of CPU processes:": "用于音高提取和数据处理的CPU进程数：",
+  "Enter the path of the training folder:": "输入训练文件夹的路径：",
+  "Specify the model ID:": "请指定型号 ID：",
+  "Auto detect audio path and select from the dropdown:": "自动检测音频路径并从下拉列表中选择：",
+  "Add audio's name to the path to the audio file to be processed (default is the correct format example) Remove the path to use an audio from the dropdown list:": "将音频的名称添加到要处理的音频文件的路径中（默认是正确的格式示例）从下拉列表中删除使用音频的路径：",
+  "Advanced Settings": "高级设置",
+  "Settings": "设置",
+  "Status:": "地位",
+  "Process data": "处理数据",
+  "Drag your audio here:": "将音频拖到此处并点击刷新按钮",
+  "Or record an audio:": "或者录制音频。",
+  "Formant shift inference audio": "共振峰移位推断音频",
+  "Used for male to female and vice-versa conversions": "用于男性到女性的转换，反之亦然",
+  "Provide the GPU index(es) separated by '-', like 0-1-2 for using GPUs 0, 1, and 2:": "请提供以“-”分隔的 GPU 索引，例如使用 GPU 0、1 和 2 时为 0-1-2：",
+  "GPU Information:": "GPU信息",
+  "Feature extraction": "特征提取",
+  "Save frequency:": "保存频率：",
+  "Training epochs:": "训练时期：",
+  "Batch size per GPU:": "每个 GPU 的批量大小：",
+  "Save only the latest '.ckpt' file to save disk space:": "仅保存最新的“.ckpt”文件以节省磁盘空间：",
+  "No": "不",
+  "Save a small final model to the 'weights' folder at each save point:": "在每个保存点将一个小的最终模型保存到“权重”文件夹中：",
+  "Load pre-trained base model G path:": "加载预训练的基础模型G路径：",
+  "Load pre-trained base model D path:": "加载预训练的基础模型D路径：",
+  "Train model": "火车模型",
+  "Train feature index": "列车特征指标",
+  "One-click training": "一键培训",
+  "Processing": "加工",
+  "Model fusion, can be used to test timbre fusion": "模型融合，可用于测试音色融合",
+  "Path to Model A:": "模型 A 的路径：",
+  "Path to Model B:": "模型 B 的路径：",
+  "Weight for Model A:": "A 型重量：",
+  "Whether the model has pitch guidance:": "模型是否有俯仰引导：",
+  "Model information to be placed:": "需放置的型号信息：",
+  "Model architecture version:": "模型架构版本：",
+  "Fusion": "融合",
+  "Modify model information": "修改型号信息",
+  "Path to Model:": "模型路径：",
+  "Model information to be modified:": "待修改型号信息：",
+  "Save file name:": "保存文件名：",
+  "Modify": "调整",
+  "View model information": "查看型号信息",
+  "View": "看法",
+  "Model extraction": "模型提取（输入“logs”文件夹下大文件模型的路径）。如果您想中途停止训练并手动提取并保存一个小模型文件，或者如果您想测试中间模型，这非常有用：",
+  "Name:": "保存名称：",
+  "Whether the model has pitch guidance (1: yes, 0: no):": "模型是否有俯仰引导（1：有，0：无）：",
+  "Extract": "提炼",
+  "Export Onnx": "导出Onnx",
+  "RVC Model Path:": "RVC模型路径：",
+  "Onnx Export Path:": "Onnx 导出路径：",
+  "MoeVS Model": "MoeVS模型",
+  "Export Onnx Model": "导出 Onnx 模型",
+  "Load model": "负载模型",
+  "Hubert Model": "休伯特模型",
+  "Select the .pth file": "选择 .pth 文件",
+  "Select the .index file": "选择.index文件",
+  "Select the .npy file": "选择.npy 文件",
+  "Input device": "输入设备",
+  "Output device": "输出设备",
+  "Audio device (please use the same type of driver)": "音频设备（请使用同类型驱动程序）",
+  "Response threshold": "反应阈值",
+  "Pitch settings": "音调设置",
+  "Whether to use note names instead of their hertz value. E.G. [C5, D6] instead of [523.25, 1174.66]Hz": "是否使用音符名称而不是赫兹值。例如。 [C5，D6]而不是[523.25，1174.66]Hz",
+  "Index Rate": "指数率",
+  "General settings": "常规设置",
+  "Sample length": "样品长度",
+  "Fade length": "淡入淡出长度",
+  "Extra inference time": "额外的推理时间",
+  "Input noise reduction": "输入噪声降低",
+  "Output noise reduction": "输出噪声降低",
+  "Performance settings": "性能设置",
+  "Start audio conversion": "开始音频转换",
+  "Stop audio conversion": "停止音频转换",
+  "Inference time (ms):": "推理时间（毫秒）：",
+  "Select the pth file": "选择.pth文件",
+  "Select the .index file:": "选择索引文件",
+  "The hubert model path must not contain Chinese characters": "hubert模型路径不能包含中文字符",
+  "The pth file path must not contain Chinese characters.": "pth文件路径不能包含中文字符。",
+  "The index file path must not contain Chinese characters.": "索引文件路径不能包含中文字符。",
+  "Step algorithm": "步进算法",
+  "Number of epoch processes": "纪元进程数",
+  "Lowest points export": "最低点导出",
+  "How many lowest points to save:": "保存多少个最低点",
+  "Export lowest points of a model": "导出模型的最低点",
+  "Output models:": "输出型号",
+  "Stats of selected models:": "所选模型的统计数据",
+  "Custom f0 [Root pitch] File": "自定义 f0 [根音] 文件",
+  "Min pitch:": "最小间距",
+  "Specify minimal pitch for inference [HZ]": "指定推理的最小间距 [HZ]",
+  "Specify minimal pitch for inference [NOTE][OCTAVE]": "指定推理的最小间距 [NOTE][OCTAVE]",
+  "Max pitch:": "最大螺距",
+  "Specify max pitch for inference [HZ]": "指定推理的最大间距 [HZ]",
+  "Specify max pitch for inference [NOTE][OCTAVE]": "指定推理的最大音高 [NOTE][OCTAVE]",
+  "Browse presets for formanting": "浏览共振峰预设",
+  "Presets are located in formantshiftcfg/ folder": "预设位于formantshiftcfg/文件夹中",
+  "Default value is 1.0": "默认值为 1.0",
+  "Quefrency for formant shifting": "共振峰移位频率",
+  "Timbre for formant shifting": "共振峰转换的音色",
+  "Apply": "申请",
+  "Single": "单身的",
+  "Batch": "批",
+  "Separate YouTube tracks": "单独的 YouTube 曲目",
+  "Download audio from a YouTube video and automatically separate the vocal and instrumental tracks": "从 YouTube 视频下载音频并自动分离人声和器乐曲目",
+  "Extra": "额外的",
+  "Merge": "合并",
+  "Merge your generated audios with the instrumental": "将生成的音频与乐器合并",
+  "Choose your instrumental:": "选择您的乐器",
+  "Choose the generated audio:": "选择生成的音频",
+  "Combine": "结合",
+  "Download and Separate": "下载并分离",
+  "Enter the YouTube link:": "输入 YouTube 链接",
+  "This section contains some extra utilities that often may be in experimental phases": "本节包含一些通常可能处于实验阶段的额外实用程序",
+  "Merge Audios": "合并音频",
+  "Audio files have been moved to the 'audios' folder.": "音频文件已移至“audios”文件夹。",
+  "Downloading audio from the video...": "正在从视频下载音频...",
+  "Audio downloaded!": "音频下载！",
+  "An error occurred:": "发生错误：",
+  "Separating audio...": "分离音频...",
+  "File moved successfully.": "文件移动成功。",
+  "Finished!": "完成的！",
+  "The source file does not exist.": "源文件不存在。",
+  "Error moving the file:": "移动文件时出错：",
+  "Downloading {name} from drive": "正在从驱动器下载 {name}",
+  "The attempt to download using Drive didn't work": "尝试使用云端硬盘下载失败",
+  "Error downloading the file: {str(e)}": "下载文件时出错：{str(e)}",
+  "Downloading {name} from mega": "正在从 mega 下载 {name}",
+  "Downloading {name} from basic url": "从基本网址下载 {name}",
+  "Download Audio": "下载音频",
+  "Download audios of any format for use in inference (recommended for mobile users).": "下载任何格式的音频用于推理（推荐移动用户）",
+  "Any ConnectionResetErrors post-conversion are irrelevant and purely visual; they can be ignored.\n": "转换后的任何 ConnectionResetErrors 都是无关紧要的并且纯粹是视觉上的；它们可以被忽略。",
+  "Processed audio saved at: ": "处理后的音频保存在：",
+  "Conversion complete!": "转换完成！",
+  "Reverb": "混响",
+  "Compressor": "压缩机",
+  "Noise Gate": "噪声门",
+  "Volume": "体积",
+  "Drag the audio here and click the Refresh button": "将音频拖至此处并单击刷新按钮",
+  "Select the generated audio": "选择生成的音频",
+  "Volume of the instrumental audio:": "乐器音频的音量",
+  "Volume of the generated audio:": "生成音频的音量",
+  "### Add the effects": "### 添加效果",
+  "Starting audio conversion... (This might take a moment)": "开始音频转换...（这可能需要一点时间）",
+  "TTS Model:": "TTS 语音",
+  "TTS": "TTS",
+  "TTS Method:": "TTS 方法",
+  "Audio TTS:": "音频 TTS",
+  "Audio RVC:": "音频模型"
+}
diff --git a/i18n/locale_diff.py b/i18n/locale_diff.py
new file mode 100644
index 0000000000000000000000000000000000000000..387ddfe1b16c2f9f32b6b9682b61353837b06bd8
--- /dev/null
+++ b/i18n/locale_diff.py
@@ -0,0 +1,45 @@
+import json
+import os
+from collections import OrderedDict
+
+# Define the standard file name
+standard_file = "en_US.json"
+
+# Find all JSON files in the directory
+dir_path = "./"
+languages = [
+    f for f in os.listdir(dir_path) if f.endswith(".json") and f != standard_file
+]
+
+# Load the standard file
+with open(standard_file, "r", encoding="utf-8") as f:
+    standard_data = json.load(f, object_pairs_hook=OrderedDict)
+
+# Loop through each language file
+for lang_file in languages:
+    # Load the language file
+    with open(lang_file, "r", encoding="utf-8") as f:
+        lang_data = json.load(f, object_pairs_hook=OrderedDict)
+
+    # Find the difference between the language file and the standard file
+    diff = set(standard_data.keys()) - set(lang_data.keys())
+
+    miss = set(lang_data.keys()) - set(standard_data.keys())
+
+    # Add any missing keys to the language file
+    for key in diff:
+        lang_data[key] = key
+
+    # Del any extra keys to the language file
+    for key in miss:
+        del lang_data[key]
+
+    # Sort the keys of the language file to match the order of the standard file
+    lang_data = OrderedDict(
+        sorted(lang_data.items(), key=lambda x: list(standard_data.keys()).index(x[0]))
+    )
+
+    # Save the updated language file
+    with open(lang_file, "w", encoding="utf-8") as f:
+        json.dump(lang_data, f, ensure_ascii=False, indent=4)
+        f.write("\n")
diff --git a/i18n/scan_i18n.py b/i18n/scan_i18n.py
new file mode 100644
index 0000000000000000000000000000000000000000..f3e52cf4f9f06d78877d77d2353f666aa759e36f
--- /dev/null
+++ b/i18n/scan_i18n.py
@@ -0,0 +1,75 @@
+import ast
+import glob
+import json
+from collections import OrderedDict
+
+
+def extract_i18n_strings(node):
+    i18n_strings = []
+
+    if (
+        isinstance(node, ast.Call)
+        and isinstance(node.func, ast.Name)
+        and node.func.id == "i18n"
+    ):
+        for arg in node.args:
+            if isinstance(arg, ast.Str):
+                i18n_strings.append(arg.s)
+
+    for child_node in ast.iter_child_nodes(node):
+        i18n_strings.extend(extract_i18n_strings(child_node))
+
+    return i18n_strings
+
+
+# scan the directory for all .py files (recursively)
+# for each file, parse the code into an AST
+# for each AST, extract the i18n strings
+
+strings = []
+for filename in glob.iglob("**/*.py", recursive=True):
+    with open(filename, "r") as f:
+        code = f.read()
+        if "I18nAuto" in code:
+            tree = ast.parse(code)
+            i18n_strings = extract_i18n_strings(tree)
+            print(filename, len(i18n_strings))
+            strings.extend(i18n_strings)
+code_keys = set(strings)
+"""
+n_i18n.py
+gui_v1.py 26
+app.py 16
+infer-web.py 147
+scan_i18n.py 0
+i18n.py 0
+lib/train/process_ckpt.py 1
+"""
+print()
+print("Total unique:", len(code_keys))
+
+
+standard_file = "i18n/locale/zh_CN.json"
+with open(standard_file, "r", encoding="utf-8") as f:
+    standard_data = json.load(f, object_pairs_hook=OrderedDict)
+standard_keys = set(standard_data.keys())
+
+# Define the standard file name
+unused_keys = standard_keys - code_keys
+print("Unused keys:", len(unused_keys))
+for unused_key in unused_keys:
+    print("\t", unused_key)
+
+missing_keys = code_keys - standard_keys
+print("Missing keys:", len(missing_keys))
+for missing_key in missing_keys:
+    print("\t", missing_key)
+
+code_keys_dict = OrderedDict()
+for s in strings:
+    code_keys_dict[s] = s
+
+# write back
+with open(standard_file, "w", encoding="utf-8") as f:
+    json.dump(code_keys_dict, f, ensure_ascii=False, indent=4, sort_keys=True)
+    f.write("\n")
diff --git a/images/icon.png b/images/icon.png
new file mode 100644
index 0000000000000000000000000000000000000000..f9aae65bbbb712383531d26e6a956362576634fb
Binary files /dev/null and b/images/icon.png differ
diff --git a/infer-web.py b/infer-web.py
new file mode 100644
index 0000000000000000000000000000000000000000..1b37139463bc46aa7600a2bef498452f00cd10cb
--- /dev/null
+++ b/infer-web.py
@@ -0,0 +1,3137 @@
+import os, sys
+
+now_dir = os.getcwd()
+sys.path.append(now_dir)
+os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
+os.environ["OPENBLAS_NUM_THREADS"] = "1"
+os.environ["no_proxy"] = "localhost, 127.0.0.1, ::1"
+import logging
+import shutil
+import threading
+import lib.globals.globals as rvc_globals
+from LazyImport import lazyload
+import mdx
+from mdx_processing_script import get_model_list,id_to_ptm,prepare_mdx,run_mdx
+math = lazyload('math')
+import traceback
+import warnings
+tensorlowest = lazyload('tensorlowest')
+from random import shuffle
+from subprocess import Popen
+from time import sleep
+import json
+import pathlib
+
+import fairseq
+logging.getLogger("faiss").setLevel(logging.WARNING)
+import faiss
+gr = lazyload("gradio")
+np = lazyload("numpy")
+torch = lazyload('torch')
+re = lazyload('regex')
+SF = lazyload("soundfile")
+SFWrite = SF.write
+from dotenv import load_dotenv
+from sklearn.cluster import MiniBatchKMeans
+import datetime
+
+
+from glob import glob1
+import signal
+from signal import SIGTERM
+import librosa
+
+from configs.config import Config
+from i18n import I18nAuto
+from infer.lib.train.process_ckpt import (
+    change_info,
+    extract_small_model,
+    merge,
+    show_info,
+)
+#from infer.modules.uvr5.modules import uvr
+from infer.modules.vc.modules import VC
+from infer.modules.vc.utils import *
+from infer.modules.vc.pipeline import Pipeline
+import lib.globals.globals as rvc_globals
+math = lazyload('math')
+ffmpeg = lazyload('ffmpeg')
+import nltk
+nltk.download('punkt', quiet=True)
+from nltk.tokenize import sent_tokenize
+from bark import SAMPLE_RATE
+
+import easy_infer
+import audioEffects
+from infer.lib.csvutil import CSVutil
+
+from lib.infer_pack.models import (
+    SynthesizerTrnMs256NSFsid,
+    SynthesizerTrnMs256NSFsid_nono,
+    SynthesizerTrnMs768NSFsid,
+    SynthesizerTrnMs768NSFsid_nono,
+)
+from lib.infer_pack.models_onnx import SynthesizerTrnMsNSFsidM
+from infer_uvr5 import _audio_pre_, _audio_pre_new
+from MDXNet import MDXNetDereverb
+from infer.lib.audio import load_audio
+
+
+from sklearn.cluster import MiniBatchKMeans
+
+import time
+import csv
+
+from shlex import quote as SQuote
+
+
+
+
+RQuote = lambda val: SQuote(str(val))
+
+tmp = os.path.join(now_dir, "TEMP")
+runtime_dir = os.path.join(now_dir, "runtime/Lib/site-packages")
+directories = ['logs', 'audios', 'datasets', 'weights', 'audio-others' , 'audio-outputs']
+
+shutil.rmtree(tmp, ignore_errors=True)
+shutil.rmtree("%s/runtime/Lib/site-packages/infer_pack" % (now_dir), ignore_errors=True)
+shutil.rmtree("%s/runtime/Lib/site-packages/uvr5_pack" % (now_dir), ignore_errors=True)
+
+os.makedirs(tmp, exist_ok=True)
+for folder in directories:
+    os.makedirs(os.path.join(now_dir, folder), exist_ok=True)
+
+
+os.makedirs(tmp, exist_ok=True)
+os.makedirs(os.path.join(now_dir, "logs"), exist_ok=True)
+os.makedirs(os.path.join(now_dir, "assets/weights"), exist_ok=True)
+os.environ["TEMP"] = tmp
+warnings.filterwarnings("ignore")
+torch.manual_seed(114514)
+logging.getLogger("numba").setLevel(logging.WARNING)
+
+logger = logging.getLogger(__name__)
+
+
+if not os.path.isdir("csvdb/"):
+    os.makedirs("csvdb")
+    frmnt, stp = open("csvdb/formanting.csv", "w"), open("csvdb/stop.csv", "w")
+    frmnt.close()
+    stp.close()
+
+global DoFormant, Quefrency, Timbre
+
+try:
+    DoFormant, Quefrency, Timbre = CSVutil("csvdb/formanting.csv", "r", "formanting")
+    DoFormant = (
+        lambda DoFormant: True
+        if DoFormant.lower() == "true"
+        else (False if DoFormant.lower() == "false" else DoFormant)
+    )(DoFormant)
+except (ValueError, TypeError, IndexError):
+    DoFormant, Quefrency, Timbre = False, 1.0, 1.0
+    CSVutil("csvdb/formanting.csv", "w+", "formanting", DoFormant, Quefrency, Timbre)
+
+load_dotenv()
+config = Config()
+vc = VC(config)
+
+if config.dml == True:
+
+    def forward_dml(ctx, x, scale):
+        ctx.scale = scale
+        res = x.clone().detach()
+        return res
+
+    fairseq.modules.grad_multiply.GradMultiply.forward = forward_dml
+
+i18n = I18nAuto()
+i18n.print()
+# 判断是否有能用来训练和加速推理的N卡
+ngpu = torch.cuda.device_count()
+gpu_infos = []
+mem = []
+if_gpu_ok = False
+
+isinterrupted = 0
+
+
+if torch.cuda.is_available() or ngpu != 0:
+    for i in range(ngpu):
+        gpu_name = torch.cuda.get_device_name(i)
+        if any(
+            value in gpu_name.upper()
+            for value in [
+                "10",
+                "16",
+                "20",
+                "30",
+                "40",
+                "A2",
+                "A3",
+                "A4",
+                "P4",
+                "A50",
+                "500",
+                "A60",
+                "70",
+                "80",
+                "90",
+                "M4",
+                "T4",
+                "TITAN",
+            ]
+        ):
+            # A10#A100#V100#A40#P40#M40#K80#A4500
+            if_gpu_ok = True  # 至少有一张能用的N卡
+            gpu_infos.append("%s\t%s" % (i, gpu_name))
+            mem.append(
+                int(
+                    torch.cuda.get_device_properties(i).total_memory
+                    / 1024
+                    / 1024
+                    / 1024
+                    + 0.4
+                )
+            )
+if if_gpu_ok and len(gpu_infos) > 0:
+    gpu_info = "\n".join(gpu_infos)
+    default_batch_size = min(mem) // 2
+else:
+    gpu_info = "Unfortunately, there is no compatible GPU available to support your training."
+    default_batch_size = 1
+gpus = "-".join([i[0] for i in gpu_infos])
+
+class ToolButton(gr.Button, gr.components.FormComponent):
+    """Small button with single emoji as text, fits inside gradio forms"""
+
+    def __init__(self, **kwargs):
+        super().__init__(variant="tool", **kwargs)
+
+    def get_block_name(self):
+        return "button"
+
+
+hubert_model = None
+weight_root = os.getenv("weight_root")
+weight_uvr5_root = os.getenv("weight_uvr5_root")
+index_root = os.getenv("index_root")
+datasets_root = "datasets"
+fshift_root = "formantshiftcfg"
+audio_root = "audios"
+audio_others_root = "audio-others"
+
+sup_audioext = {'wav', 'mp3', 'flac', 'ogg', 'opus',
+                'm4a', 'mp4', 'aac', 'alac', 'wma',
+                'aiff', 'webm', 'ac3'}
+
+names        = [os.path.join(root, file)
+               for root, _, files in os.walk(weight_root)
+               for file in files
+               if file.endswith((".pth", ".onnx"))]
+
+indexes_list = [os.path.join(root, name)
+               for root, _, files in os.walk(index_root, topdown=False) 
+               for name in files 
+               if name.endswith(".index") and "trained" not in name]
+
+audio_paths  = [os.path.join(root, name)
+               for root, _, files in os.walk(audio_root, topdown=False) 
+               for name in files
+               if name.endswith(tuple(sup_audioext))]
+
+audio_others_paths  = [os.path.join(root, name)
+               for root, _, files in os.walk(audio_others_root, topdown=False) 
+               for name in files
+               if name.endswith(tuple(sup_audioext))]
+
+uvr5_names  = [name.replace(".pth", "") 
+              for name in os.listdir(weight_uvr5_root) 
+              if name.endswith(".pth") or "onnx" in name]
+
+
+check_for_name = lambda: sorted(names)[0] if names else ''
+
+datasets=[]
+for foldername in os.listdir(os.path.join(now_dir, datasets_root)):
+    if "." not in foldername:
+        datasets.append(os.path.join(easy_infer.find_folder_parent(".","pretrained"),"datasets",foldername))
+
+def get_dataset():
+    if len(datasets) > 0:
+        return sorted(datasets)[0]
+    else:
+        return ''
+    
+def update_model_choices(select_value):
+    model_ids = get_model_list()
+    model_ids_list = list(model_ids)
+    if select_value == "VR":
+        return {"choices": uvr5_names, "__type__": "update"}
+    elif select_value == "MDX":
+        return {"choices": model_ids_list, "__type__": "update"}
+
+set_bark_voice = easy_infer.get_bark_voice()
+set_edge_voice = easy_infer.get_edge_voice()
+
+def update_tts_methods_voice(select_value):
+    #["Edge-tts", "RVG-tts", "Bark-tts"]
+    if select_value == "Edge-tts":
+        return {"choices": set_edge_voice, "value": "", "__type__": "update"}
+    elif select_value == "Bark-tts":
+        return {"choices": set_bark_voice, "value": "", "__type__": "update"}
+    
+
+def update_dataset_list(name):
+    new_datasets = []
+    for foldername in os.listdir(os.path.join(now_dir, datasets_root)):
+        if "." not in foldername:
+            new_datasets.append(os.path.join(easy_infer.find_folder_parent(".","pretrained"),"datasets",foldername))
+    return gr.Dropdown.update(choices=new_datasets)
+
+def get_indexes():
+    indexes_list = [
+        os.path.join(dirpath, filename)
+        for dirpath, _, filenames in os.walk(index_root)
+        for filename in filenames
+        if filename.endswith(".index") and "trained" not in filename
+    ]
+    
+    return indexes_list if indexes_list else ''
+
+def get_fshift_presets():
+    fshift_presets_list = [
+        os.path.join(dirpath, filename)
+        for dirpath, _, filenames in os.walk(fshift_root)
+        for filename in filenames
+        if filename.endswith(".txt")
+    ]
+    
+    return fshift_presets_list if fshift_presets_list else ''
+
+import soundfile as sf
+
+def generate_output_path(output_folder, base_name, extension):
+    # Generar un nombre único para el archivo de salida
+    index = 1
+    while True:
+        output_path = os.path.join(output_folder, f"{base_name}_{index}.{extension}")
+        if not os.path.exists(output_path):
+            return output_path
+        index += 1
+
+def combine_and_save_audios(audio1_path, audio2_path, output_path, volume_factor_audio1, volume_factor_audio2):
+    audio1, sr1 = librosa.load(audio1_path, sr=None)
+    audio2, sr2 = librosa.load(audio2_path, sr=None)
+
+    # Alinear las tasas de muestreo
+    if sr1 != sr2:
+        if sr1 > sr2:
+            audio2 = librosa.resample(audio2, orig_sr=sr2, target_sr=sr1)
+        else:
+            audio1 = librosa.resample(audio1, orig_sr=sr1, target_sr=sr2)
+
+    # Ajustar los audios para que tengan la misma longitud
+    target_length = min(len(audio1), len(audio2))
+    audio1 = librosa.util.fix_length(audio1, target_length)
+    audio2 = librosa.util.fix_length(audio2, target_length)
+
+    # Ajustar el volumen de los audios multiplicando por el factor de ganancia
+    if volume_factor_audio1 != 1.0:
+        audio1 *= volume_factor_audio1
+    if volume_factor_audio2 != 1.0:
+        audio2 *= volume_factor_audio2
+
+    # Combinar los audios
+    combined_audio = audio1 + audio2
+
+    sf.write(output_path, combined_audio, sr1)
+
+# Resto de tu código...
+
+# Define función de conversión llamada por el botón
+def audio_combined(audio1_path, audio2_path, volume_factor_audio1=1.0, volume_factor_audio2=1.0, reverb_enabled=False, compressor_enabled=False, noise_gate_enabled=False):
+    output_folder = os.path.join(now_dir, "audio-outputs")
+    os.makedirs(output_folder, exist_ok=True)
+
+    # Generar nombres únicos para los archivos de salida
+    base_name = "combined_audio"
+    extension = "wav"
+    output_path = generate_output_path(output_folder, base_name, extension)
+    print(reverb_enabled)
+    print(compressor_enabled)
+    print(noise_gate_enabled)
+
+    if reverb_enabled or compressor_enabled or noise_gate_enabled:
+        # Procesa el primer audio con los efectos habilitados
+        base_name = "effect_audio"
+        output_path = generate_output_path(output_folder, base_name, extension)
+        processed_audio_path = audioEffects.process_audio(audio2_path, output_path, reverb_enabled, compressor_enabled, noise_gate_enabled)
+        base_name = "combined_audio"
+        output_path = generate_output_path(output_folder, base_name, extension)
+        # Combina el audio procesado con el segundo audio usando audio_combined
+        combine_and_save_audios(audio1_path, processed_audio_path, output_path, volume_factor_audio1, volume_factor_audio2)
+        
+        return i18n("Conversion complete!"), output_path
+    else:
+        base_name = "combined_audio"
+        output_path = generate_output_path(output_folder, base_name, extension)
+        # No hay efectos habilitados, combina directamente los audios sin procesar
+        combine_and_save_audios(audio1_path, audio2_path, output_path, volume_factor_audio1, volume_factor_audio2)
+        
+        return i18n("Conversion complete!"), output_path
+
+
+
+
+def uvr(model_name, inp_root, save_root_vocal, paths, save_root_ins, agg, format0,architecture):
+    infos = []
+    if architecture == "VR":
+       try:
+           inp_root, save_root_vocal, save_root_ins = [x.strip(" ").strip('"').strip("\n").strip('"').strip(" ") for x in [inp_root, save_root_vocal, save_root_ins]]
+           usable_files = [os.path.join(inp_root, file) 
+                          for file in os.listdir(inp_root) 
+                          if file.endswith(tuple(sup_audioext))]    
+           
+        
+           pre_fun = MDXNetDereverb(15) if model_name == "onnx_dereverb_By_FoxJoy" else (_audio_pre_ if "DeEcho" not in model_name else _audio_pre_new)(
+                       agg=int(agg),
+                       model_path=os.path.join(weight_uvr5_root, model_name + ".pth"),
+                       device=config.device,
+                       is_half=config.is_half,
+                   )
+                
+           try:
+              if paths != None:
+                paths = [path.name for path in paths]
+              else:
+                paths = usable_files
+                
+           except:
+                traceback.print_exc()
+                paths = usable_files
+           print(paths) 
+           for path in paths:
+               inp_path = os.path.join(inp_root, path)
+               need_reformat, done = 1, 0
+
+               try:
+                   info = ffmpeg.probe(inp_path, cmd="ffprobe")
+                   if info["streams"][0]["channels"] == 2 and info["streams"][0]["sample_rate"] == "44100":
+                       need_reformat = 0
+                       pre_fun._path_audio_(inp_path, save_root_ins, save_root_vocal, format0)
+                       done = 1
+               except:
+                   traceback.print_exc()
+
+               if need_reformat:
+                   tmp_path = f"{tmp}/{os.path.basename(RQuote(inp_path))}.reformatted.wav"
+                   os.system(f"ffmpeg -i {RQuote(inp_path)} -vn -acodec pcm_s16le -ac 2 -ar 44100 {RQuote(tmp_path)} -y")
+                   inp_path = tmp_path
+
+               try:
+                   if not done:
+                       pre_fun._path_audio_(inp_path, save_root_ins, save_root_vocal, format0)
+                   infos.append(f"{os.path.basename(inp_path)}->Success")
+                   yield "\n".join(infos)
+               except:
+                   infos.append(f"{os.path.basename(inp_path)}->{traceback.format_exc()}")
+                   yield "\n".join(infos)
+       except:
+           infos.append(traceback.format_exc())
+           yield "\n".join(infos)
+       finally:
+           try:
+               if model_name == "onnx_dereverb_By_FoxJoy":
+                   del pre_fun.pred.model
+                   del pre_fun.pred.model_
+               else:
+                   del pre_fun.model
+
+               del pre_fun
+           except: traceback.print_exc()
+
+           print("clean_empty_cache")
+
+           if torch.cuda.is_available(): torch.cuda.empty_cache()
+
+       yield "\n".join(infos)
+    elif architecture == "MDX":
+       try:
+           infos.append(i18n("Starting audio conversion... (This might take a moment)"))
+           yield "\n".join(infos)
+           inp_root, save_root_vocal, save_root_ins = [x.strip(" ").strip('"').strip("\n").strip('"').strip(" ") for x in [inp_root, save_root_vocal, save_root_ins]]
+        
+           usable_files = [os.path.join(inp_root, file) 
+                          for file in os.listdir(inp_root) 
+                          if file.endswith(tuple(sup_audioext))]    
+           try:
+              if paths != None:
+                paths = [path.name for path in paths]
+              else:
+                paths = usable_files
+                
+           except:
+                traceback.print_exc()
+                paths = usable_files
+           print(paths) 
+           invert=True
+           denoise=True
+           use_custom_parameter=True
+           dim_f=3072
+           dim_t=256
+           n_fft=7680
+           use_custom_compensation=True
+           compensation=1.025
+           suffix = "Vocals_custom" #@param ["Vocals", "Drums", "Bass", "Other"]{allow-input: true}
+           suffix_invert = "Instrumental_custom" #@param ["Instrumental", "Drumless", "Bassless", "Instruments"]{allow-input: true}
+           print_settings = True  # @param{type:"boolean"}
+           onnx = id_to_ptm(model_name)
+           compensation = compensation if use_custom_compensation or use_custom_parameter else None
+           mdx_model = prepare_mdx(onnx,use_custom_parameter, dim_f, dim_t, n_fft, compensation=compensation)
+           
+       
+           for path in paths:
+               #inp_path = os.path.join(inp_root, path)
+               suffix_naming = suffix if use_custom_parameter else None
+               diff_suffix_naming = suffix_invert if use_custom_parameter else None
+               run_mdx(onnx, mdx_model, path, format0, diff=invert,suffix=suffix_naming,diff_suffix=diff_suffix_naming,denoise=denoise)
+    
+           if print_settings:
+               print()
+               print('[MDX-Net_Colab settings used]')
+               print(f'Model used: {onnx}')
+               print(f'Model MD5: {mdx.MDX.get_hash(onnx)}')
+               print(f'Model parameters:')
+               print(f'    -dim_f: {mdx_model.dim_f}')
+               print(f'    -dim_t: {mdx_model.dim_t}')
+               print(f'    -n_fft: {mdx_model.n_fft}')
+               print(f'    -compensation: {mdx_model.compensation}')
+               print()
+               print('[Input file]')
+               print('filename(s): ')
+               for filename in paths:
+                   print(f'    -{filename}')
+                   infos.append(f"{os.path.basename(filename)}->Success")
+                   yield "\n".join(infos)
+       except:
+           infos.append(traceback.format_exc())
+           yield "\n".join(infos)
+       finally:
+           try:
+               del mdx_model
+           except: traceback.print_exc()
+
+           print("clean_empty_cache")
+
+           if torch.cuda.is_available(): torch.cuda.empty_cache()
+
+
+
+
+
+def change_choices():
+    names        = [os.path.join(root, file)
+                   for root, _, files in os.walk(weight_root)
+                   for file in files
+                   if file.endswith((".pth", ".onnx"))]
+    indexes_list = [os.path.join(root, name) for root, _, files in os.walk(index_root, topdown=False) for name in files if name.endswith(".index") and "trained" not in name]
+    audio_paths  = [os.path.join(audio_root, file) for file in os.listdir(os.path.join(now_dir, "audios"))]
+    
+
+    return (
+        {"choices": sorted(names), "__type__": "update"}, 
+        {"choices": sorted(indexes_list), "__type__": "update"}, 
+        {"choices": sorted(audio_paths), "__type__": "update"}
+    )
+def change_choices2():
+    names        = [os.path.join(root, file)
+                   for root, _, files in os.walk(weight_root)
+                   for file in files
+                   if file.endswith((".pth", ".onnx"))]
+    indexes_list = [os.path.join(root, name) for root, _, files in os.walk(index_root, topdown=False) for name in files if name.endswith(".index") and "trained" not in name]
+    
+
+    return (
+        {"choices": sorted(names), "__type__": "update"}, 
+        {"choices": sorted(indexes_list), "__type__": "update"}, 
+    )
+def change_choices3():
+    
+    audio_paths  = [os.path.join(audio_root, file) for file in os.listdir(os.path.join(now_dir, "audios"))]
+    audio_others_paths  = [os.path.join(audio_others_root, file) for file in os.listdir(os.path.join(now_dir, "audio-others"))]
+    
+
+    return (
+        {"choices": sorted(audio_others_paths), "__type__": "update"},
+        {"choices": sorted(audio_paths), "__type__": "update"}
+    )
+
+def clean():
+    return {"value": "", "__type__": "update"}
+def export_onnx():
+    from infer.modules.onnx.export import export_onnx as eo
+
+    eo()
+
+sr_dict = {
+    "32k": 32000,
+    "40k": 40000,
+    "48k": 48000,
+}
+
+
+def if_done(done, p):
+    while 1:
+        if p.poll() is None:
+            sleep(0.5)
+        else:
+            break
+    done[0] = True
+
+
+def if_done_multi(done, ps):
+    while 1:
+        # poll==None代表进程未结束
+        # 只要有一个进程未结束都不停
+        flag = 1
+        for p in ps:
+            if p.poll() is None:
+                flag = 0
+                sleep(0.5)
+                break
+        if flag == 1:
+            break
+    done[0] = True
+
+def formant_enabled(
+    cbox, qfrency, tmbre, frmntapply, formantpreset, formant_refresh_button
+):
+    if cbox:
+        DoFormant = True
+        CSVutil("csvdb/formanting.csv", "w+", "formanting", DoFormant, qfrency, tmbre)
+
+        # print(f"is checked? - {cbox}\ngot {DoFormant}")
+
+        return (
+            {"value": True, "__type__": "update"},
+            {"visible": True, "__type__": "update"},
+            {"visible": True, "__type__": "update"},
+            {"visible": True, "__type__": "update"},
+            {"visible": True, "__type__": "update"},
+            {"visible": True, "__type__": "update"},
+        )
+
+    else:
+        DoFormant = False
+        CSVutil("csvdb/formanting.csv", "w+", "formanting", DoFormant, qfrency, tmbre)
+
+        # print(f"is checked? - {cbox}\ngot {DoFormant}")
+        return (
+            {"value": False, "__type__": "update"},
+            {"visible": False, "__type__": "update"},
+            {"visible": False, "__type__": "update"},
+            {"visible": False, "__type__": "update"},
+            {"visible": False, "__type__": "update"},
+            {"visible": False, "__type__": "update"},
+            {"visible": False, "__type__": "update"},
+        )
+        
+
+def formant_apply(qfrency, tmbre):
+    Quefrency = qfrency
+    Timbre = tmbre
+    DoFormant = True
+    CSVutil("csvdb/formanting.csv", "w+", "formanting", DoFormant, qfrency, tmbre)
+
+    return (
+        {"value": Quefrency, "__type__": "update"},
+        {"value": Timbre, "__type__": "update"},
+    )
+
+def update_fshift_presets(preset, qfrency, tmbre):
+
+    if preset:  
+        with open(preset, 'r') as p:
+            content = p.readlines()
+            qfrency, tmbre = content[0].strip(), content[1]
+            
+        formant_apply(qfrency, tmbre)
+    else:
+        qfrency, tmbre = preset_apply(preset, qfrency, tmbre)
+        
+    return (
+        {"choices": get_fshift_presets(), "__type__": "update"},
+        {"value": qfrency, "__type__": "update"},
+        {"value": tmbre, "__type__": "update"},
+    )
+
+def preprocess_dataset(trainset_dir, exp_dir, sr, n_p):
+    sr = sr_dict[sr]
+    os.makedirs("%s/logs/%s" % (now_dir, exp_dir), exist_ok=True)
+    f = open("%s/logs/%s/preprocess.log" % (now_dir, exp_dir), "w")
+    f.close()
+    per = 3.0 if config.is_half else 3.7
+    cmd = '"%s" infer/modules/train/preprocess.py "%s" %s %s "%s/logs/%s" %s %.1f' % (
+        config.python_cmd,
+        trainset_dir,
+        sr,
+        n_p,
+        now_dir,
+        exp_dir,
+        config.noparallel,
+        per,
+    )
+    logger.info(cmd)
+    p = Popen(cmd, shell=True)  # , stdin=PIPE, stdout=PIPE,stderr=PIPE,cwd=now_dir
+    ###煞笔gr, popen read都非得全跑完了再一次性读取, 不用gr就正常读一句输出一句;只能额外弄出一个文本流定时读
+    done = [False]
+    threading.Thread(
+        target=if_done,
+        args=(
+            done,
+            p,
+        ),
+    ).start()
+    while 1:
+        with open("%s/logs/%s/preprocess.log" % (now_dir, exp_dir), "r") as f:
+            yield (f.read())
+        sleep(1)
+        if done[0]:
+            break
+    with open("%s/logs/%s/preprocess.log" % (now_dir, exp_dir), "r") as f:
+        log = f.read()
+    logger.info(log)
+    yield log
+
+
+def extract_f0_feature(gpus, n_p, f0method, if_f0, exp_dir, version19, echl, gpus_rmvpe):
+    gpus = gpus.split("-")
+    os.makedirs("%s/logs/%s" % (now_dir, exp_dir), exist_ok=True)
+    f = open("%s/logs/%s/extract_f0_feature.log" % (now_dir, exp_dir), "w")
+    f.close()
+    if if_f0:
+        if f0method != "rmvpe_gpu":
+            cmd = (
+                '"%s" infer/modules/train/extract/extract_f0_print.py "%s/logs/%s" %s %s'
+                % (
+                    config.python_cmd,
+                    now_dir,
+                    exp_dir,
+                    n_p,
+                    f0method,
+                    echl,
+                )
+            )
+            logger.info(cmd)
+            p = Popen(
+                cmd, shell=True, cwd=now_dir
+            )  # , stdin=PIPE, stdout=PIPE,stderr=PIPE
+            ###煞笔gr, popen read都非得全跑完了再一次性读取, 不用gr就正常读一句输出一句;只能额外弄出一个文本流定时读
+            done = [False]
+            threading.Thread(
+                target=if_done,
+                args=(
+                    done,
+                    p,
+                ),
+            ).start()
+        else:
+            if gpus_rmvpe != "-":
+                gpus_rmvpe = gpus_rmvpe.split("-")
+                leng = len(gpus_rmvpe)
+                ps = []
+                for idx, n_g in enumerate(gpus_rmvpe):
+                    cmd = (
+                        '"%s" infer/modules/train/extract/extract_f0_rmvpe.py %s %s %s "%s/logs/%s" %s '
+                        % (
+                            config.python_cmd,
+                            leng,
+                            idx,
+                            n_g,
+                            now_dir,
+                            exp_dir,
+                            config.is_half,
+                        )
+                    )
+                    logger.info(cmd)
+                    p = Popen(
+                        cmd, shell=True, cwd=now_dir
+                    )  # , shell=True, stdin=PIPE, stdout=PIPE, stderr=PIPE, cwd=now_dir
+                    ps.append(p)
+                ###煞笔gr, popen read都非得全跑完了再一次性读取, 不用gr就正常读一句输出一句;只能额外弄出一个文本流定时读
+                done = [False]
+                threading.Thread(
+                    target=if_done_multi,  #
+                    args=(
+                        done,
+                        ps,
+                    ),
+                ).start()
+            else:
+                cmd = (
+                    config.python_cmd
+                    + ' infer/modules/train/extract/extract_f0_rmvpe_dml.py "%s/logs/%s" '
+                    % (
+                        now_dir,
+                        exp_dir,
+                    )
+                )
+                logger.info(cmd)
+                p = Popen(
+                    cmd, shell=True, cwd=now_dir
+                )  # , shell=True, stdin=PIPE, stdout=PIPE, stderr=PIPE, cwd=now_dir
+                p.wait()
+                done = [True]
+        while 1:
+            with open(
+                "%s/logs/%s/extract_f0_feature.log" % (now_dir, exp_dir), "r"
+            ) as f:
+                yield (f.read())
+            sleep(1)
+            if done[0]:
+                break
+        with open("%s/logs/%s/extract_f0_feature.log" % (now_dir, exp_dir), "r") as f:
+            log = f.read()
+        logger.info(log)
+        yield log
+    ####对不同part分别开多进程
+    """
+    n_part=int(sys.argv[1])
+    i_part=int(sys.argv[2])
+    i_gpu=sys.argv[3]
+    exp_dir=sys.argv[4]
+    os.environ["CUDA_VISIBLE_DEVICES"]=str(i_gpu)
+    """
+    leng = len(gpus)
+    ps = []
+    for idx, n_g in enumerate(gpus):
+        cmd = (
+            '"%s" infer/modules/train/extract_feature_print.py %s %s %s %s "%s/logs/%s" %s'
+            % (
+                config.python_cmd,
+                config.device,
+                leng,
+                idx,
+                n_g,
+                now_dir,
+                exp_dir,
+                version19,
+            )
+        )
+        logger.info(cmd)
+        p = Popen(
+            cmd, shell=True, cwd=now_dir
+        )  # , shell=True, stdin=PIPE, stdout=PIPE, stderr=PIPE, cwd=now_dir
+        ps.append(p)
+    ###煞笔gr, popen read都非得全跑完了再一次性读取, 不用gr就正常读一句输出一句;只能额外弄出一个文本流定时读
+    done = [False]
+    threading.Thread(
+        target=if_done_multi,
+        args=(
+            done,
+            ps,
+        ),
+    ).start()
+    while 1:
+        with open("%s/logs/%s/extract_f0_feature.log" % (now_dir, exp_dir), "r") as f:
+            yield (f.read())
+        sleep(1)
+        if done[0]:
+            break
+    with open("%s/logs/%s/extract_f0_feature.log" % (now_dir, exp_dir), "r") as f:
+        log = f.read()
+    logger.info(log)
+    yield log
+
+def get_pretrained_models(path_str, f0_str, sr2):
+    if_pretrained_generator_exist = os.access(
+        "assets/pretrained%s/%sG%s.pth" % (path_str, f0_str, sr2), os.F_OK
+    )
+    if_pretrained_discriminator_exist = os.access(
+        "assets/pretrained%s/%sD%s.pth" % (path_str, f0_str, sr2), os.F_OK
+    )
+    if not if_pretrained_generator_exist:
+        logger.warn(
+            "assets/pretrained%s/%sG%s.pth not exist, will not use pretrained model",
+            path_str,
+            f0_str,
+            sr2,
+        )
+    if not if_pretrained_discriminator_exist:
+        logger.warn(
+            "assets/pretrained%s/%sD%s.pth not exist, will not use pretrained model",
+            path_str,
+            f0_str,
+            sr2,
+        )
+    return (
+        "assets/pretrained%s/%sG%s.pth" % (path_str, f0_str, sr2)
+        if if_pretrained_generator_exist
+        else "",
+        "assets/pretrained%s/%sD%s.pth" % (path_str, f0_str, sr2)
+        if if_pretrained_discriminator_exist
+        else "",
+    )
+
+def change_sr2(sr2, if_f0_3, version19):
+    path_str = "" if version19 == "v1" else "_v2"
+    f0_str = "f0" if if_f0_3 else ""
+    return get_pretrained_models(path_str, f0_str, sr2)
+
+
+def change_version19(sr2, if_f0_3, version19):
+    path_str = "" if version19 == "v1" else "_v2"
+    if sr2 == "32k" and version19 == "v1":
+        sr2 = "40k"
+    to_return_sr2 = (
+        {"choices": ["40k", "48k"], "__type__": "update", "value": sr2}
+        if version19 == "v1"
+        else {"choices": ["40k", "48k", "32k"], "__type__": "update", "value": sr2}
+    )
+    f0_str = "f0" if if_f0_3 else ""
+    return (
+        *get_pretrained_models(path_str, f0_str, sr2),
+        to_return_sr2,
+    )
+
+
+def change_f0(if_f0_3, sr2, version19):  # f0method8,pretrained_G14,pretrained_D15
+    path_str = "" if version19 == "v1" else "_v2"
+    return (
+        {"visible": if_f0_3, "__type__": "update"},
+        *get_pretrained_models(path_str, "f0", sr2),
+    )
+
+
+global log_interval
+
+def set_log_interval(exp_dir, batch_size12):
+    log_interval = 1
+    folder_path = os.path.join(exp_dir, "1_16k_wavs")
+
+    if os.path.isdir(folder_path):
+        wav_files_num = len(glob1(folder_path,"*.wav"))
+
+        if wav_files_num > 0:
+            log_interval = math.ceil(wav_files_num / batch_size12)
+            if log_interval > 1:
+                log_interval += 1
+
+    return log_interval
+
+global PID, PROCESS
+
+def click_train(
+    exp_dir1,
+    sr2,
+    if_f0_3,
+    spk_id5,
+    save_epoch10,
+    total_epoch11,
+    batch_size12,
+    if_save_latest13,
+    pretrained_G14,
+    pretrained_D15,
+    gpus16,
+    if_cache_gpu17,
+    if_save_every_weights18,
+    version19,
+):
+    CSVutil("csvdb/stop.csv", "w+", "formanting", False)
+    # 生成filelist
+    exp_dir = "%s/logs/%s" % (now_dir, exp_dir1)
+    os.makedirs(exp_dir, exist_ok=True)
+    gt_wavs_dir = "%s/0_gt_wavs" % (exp_dir)
+    feature_dir = (
+        "%s/3_feature256" % (exp_dir)
+        if version19 == "v1"
+        else "%s/3_feature768" % (exp_dir)
+    )
+    if if_f0_3:
+        f0_dir = "%s/2a_f0" % (exp_dir)
+        f0nsf_dir = "%s/2b-f0nsf" % (exp_dir)
+        names = (
+            set([name.split(".")[0] for name in os.listdir(gt_wavs_dir)])
+            & set([name.split(".")[0] for name in os.listdir(feature_dir)])
+            & set([name.split(".")[0] for name in os.listdir(f0_dir)])
+            & set([name.split(".")[0] for name in os.listdir(f0nsf_dir)])
+        )
+    else:
+        names = set([name.split(".")[0] for name in os.listdir(gt_wavs_dir)]) & set(
+            [name.split(".")[0] for name in os.listdir(feature_dir)]
+        )
+    opt = []
+    for name in names:
+        if if_f0_3:
+            opt.append(
+                "%s/%s.wav|%s/%s.npy|%s/%s.wav.npy|%s/%s.wav.npy|%s"
+                % (
+                    gt_wavs_dir.replace("\\", "\\\\"),
+                    name,
+                    feature_dir.replace("\\", "\\\\"),
+                    name,
+                    f0_dir.replace("\\", "\\\\"),
+                    name,
+                    f0nsf_dir.replace("\\", "\\\\"),
+                    name,
+                    spk_id5,
+                )
+            )
+        else:
+            opt.append(
+                "%s/%s.wav|%s/%s.npy|%s"
+                % (
+                    gt_wavs_dir.replace("\\", "\\\\"),
+                    name,
+                    feature_dir.replace("\\", "\\\\"),
+                    name,
+                    spk_id5,
+                )
+            )
+    fea_dim = 256 if version19 == "v1" else 768
+    if if_f0_3:
+        for _ in range(2):
+            opt.append(
+                "%s/logs/mute/0_gt_wavs/mute%s.wav|%s/logs/mute/3_feature%s/mute.npy|%s/logs/mute/2a_f0/mute.wav.npy|%s/logs/mute/2b-f0nsf/mute.wav.npy|%s"
+                % (now_dir, sr2, now_dir, fea_dim, now_dir, now_dir, spk_id5)
+            )
+    else:
+        for _ in range(2):
+            opt.append(
+                "%s/logs/mute/0_gt_wavs/mute%s.wav|%s/logs/mute/3_feature%s/mute.npy|%s"
+                % (now_dir, sr2, now_dir, fea_dim, spk_id5)
+            )
+    shuffle(opt)
+    with open("%s/filelist.txt" % exp_dir, "w") as f:
+        f.write("\n".join(opt))
+    logger.debug("Write filelist done")
+    # 生成config#无需生成config
+    # cmd = python_cmd + " train_nsf_sim_cache_sid_load_pretrain.py -e mi-test -sr 40k -f0 1 -bs 4 -g 0 -te 10 -se 5 -pg pretrained/f0G40k.pth -pd pretrained/f0D40k.pth -l 1 -c 0"
+    logger.info("Use gpus: %s", str(gpus16))
+    if pretrained_G14 == "":
+        logger.info("No pretrained Generator")
+    if pretrained_D15 == "":
+        logger.info("No pretrained Discriminator")
+    if version19 == "v1" or sr2 == "40k":
+        config_path = "v1/%s.json" % sr2
+    else:
+        config_path = "v2/%s.json" % sr2
+    config_save_path = os.path.join(exp_dir, "config.json")
+    if not pathlib.Path(config_save_path).exists():
+        with open(config_save_path, "w", encoding="utf-8") as f:
+            json.dump(
+                config.json_config[config_path],
+                f,
+                ensure_ascii=False,
+                indent=4,
+                sort_keys=True,
+            )
+            f.write("\n")
+    if gpus16:
+        cmd = (
+            '"%s" infer/modules/train/train.py -e "%s" -sr %s -f0 %s -bs %s -g %s -te %s -se %s %s %s -l %s -c %s -sw %s -v %s'
+            % (
+                config.python_cmd,
+                exp_dir1,
+                sr2,
+                1 if if_f0_3 else 0,
+                batch_size12,
+                gpus16,
+                total_epoch11,
+                save_epoch10,
+                "-pg %s" % pretrained_G14 if pretrained_G14 != "" else "",
+                "-pd %s" % pretrained_D15 if pretrained_D15 != "" else "",
+                1 if if_save_latest13 == True else 0,
+                1 if if_cache_gpu17 == True else 0,
+                1 if if_save_every_weights18 == True else 0,
+                version19,
+            )
+        )
+    else:
+        cmd = (
+            '"%s" infer/modules/train/train.py -e "%s" -sr %s -f0 %s -bs %s -te %s -se %s %s %s -l %s -c %s -sw %s -v %s'
+            % (
+                config.python_cmd,
+                exp_dir1,
+                sr2,
+                1 if if_f0_3 else 0,
+                batch_size12,
+                total_epoch11,
+                save_epoch10,
+                "-pg %s" % pretrained_G14 if pretrained_G14 != "" else "",
+                "-pd %s" % pretrained_D15 if pretrained_D15 != "" else "",
+                1 if if_save_latest13 == True else 0,
+                1 if if_cache_gpu17 == True else 0,
+                1 if if_save_every_weights18 == True else 0,
+                version19,
+            )
+        )
+    logger.info(cmd)
+    global p
+    p = Popen(cmd, shell=True, cwd=now_dir)
+    global PID
+    PID = p.pid
+
+    p.wait()
+
+    return i18n("Training is done, check train.log"), {"visible": False, "__type__": "update"}, {"visible": True, "__type__": "update"}
+
+
+def train_index(exp_dir1, version19):
+    # exp_dir = "%s/logs/%s" % (now_dir, exp_dir1)
+    exp_dir = "logs/%s" % (exp_dir1)
+    os.makedirs(exp_dir, exist_ok=True)
+    feature_dir = (
+        "%s/3_feature256" % (exp_dir)
+        if version19 == "v1"
+        else "%s/3_feature768" % (exp_dir)
+    )
+    if not os.path.exists(feature_dir):
+        return "请先进行特征提取!"
+    listdir_res = list(os.listdir(feature_dir))
+    if len(listdir_res) == 0:
+        return "请先进行特征提取！"
+    infos = []
+    npys = []
+    for name in sorted(listdir_res):
+        phone = np.load("%s/%s" % (feature_dir, name))
+        npys.append(phone)
+    big_npy = np.concatenate(npys, 0)
+    big_npy_idx = np.arange(big_npy.shape[0])
+    np.random.shuffle(big_npy_idx)
+    big_npy = big_npy[big_npy_idx]
+    if big_npy.shape[0] > 2e5:
+        infos.append("Trying doing kmeans %s shape to 10k centers." % big_npy.shape[0])
+        yield "\n".join(infos)
+        try:
+            big_npy = (
+                MiniBatchKMeans(
+                    n_clusters=10000,
+                    verbose=True,
+                    batch_size=256 * config.n_cpu,
+                    compute_labels=False,
+                    init="random",
+                )
+                .fit(big_npy)
+                .cluster_centers_
+            )
+        except:
+            info = traceback.format_exc()
+            logger.info(info)
+            infos.append(info)
+            yield "\n".join(infos)
+
+    np.save("%s/total_fea.npy" % exp_dir, big_npy)
+    n_ivf = min(int(16 * np.sqrt(big_npy.shape[0])), big_npy.shape[0] // 39)
+    infos.append("%s,%s" % (big_npy.shape, n_ivf))
+    yield "\n".join(infos)
+    index = faiss.index_factory(256 if version19 == "v1" else 768, "IVF%s,Flat" % n_ivf)
+    # index = faiss.index_factory(256if version19=="v1"else 768, "IVF%s,PQ128x4fs,RFlat"%n_ivf)
+    infos.append("training")
+    yield "\n".join(infos)
+    index_ivf = faiss.extract_index_ivf(index)  #
+    index_ivf.nprobe = 1
+    index.train(big_npy)
+    faiss.write_index(
+        index,
+        "%s/trained_IVF%s_Flat_nprobe_%s_%s_%s.index"
+        % (exp_dir, n_ivf, index_ivf.nprobe, exp_dir1, version19),
+    )
+
+    infos.append("adding")
+    yield "\n".join(infos)
+    batch_size_add = 8192
+    for i in range(0, big_npy.shape[0], batch_size_add):
+        index.add(big_npy[i : i + batch_size_add])
+    faiss.write_index(
+        index,
+        "%s/added_IVF%s_Flat_nprobe_%s_%s_%s.index"
+        % (exp_dir, n_ivf, index_ivf.nprobe, exp_dir1, version19),
+    )
+    infos.append(
+        "Successful Index Construction，added_IVF%s_Flat_nprobe_%s_%s_%s.index"
+        % (n_ivf, index_ivf.nprobe, exp_dir1, version19)
+    )
+    # faiss.write_index(index, '%s/added_IVF%s_Flat_FastScan_%s.index'%(exp_dir,n_ivf,version19))
+    # infos.append("成功构建索引，added_IVF%s_Flat_FastScan_%s.index"%(n_ivf,version19))
+    yield "\n".join(infos)
+
+def change_info_(ckpt_path):
+    if not os.path.exists(ckpt_path.replace(os.path.basename(ckpt_path), "train.log")):
+        return {"__type__": "update"}, {"__type__": "update"}, {"__type__": "update"}
+    try:
+        with open(
+            ckpt_path.replace(os.path.basename(ckpt_path), "train.log"), "r"
+        ) as f:
+            info = eval(f.read().strip("\n").split("\n")[0].split("\t")[-1])
+            sr, f0 = info["sample_rate"], info["if_f0"]
+            version = "v2" if ("version" in info and info["version"] == "v2") else "v1"
+            return sr, str(f0), version
+    except:
+        traceback.print_exc()
+        return {"__type__": "update"}, {"__type__": "update"}, {"__type__": "update"}
+
+F0GPUVisible = config.dml == False
+
+
+def change_f0_method(f0method8):
+    if f0method8 == "rmvpe_gpu":
+        visible = F0GPUVisible
+    else:
+        visible = False
+    return {"visible": visible, "__type__": "update"}
+
+
+
+def export_onnx(model_path, exported_path):
+    device = torch.device("cpu")
+    checkpoint = torch.load(model_path, map_location=device)
+    vec_channels = 256 if checkpoint.get("version", "v1") == "v1" else 768
+    
+    test_inputs = {
+        "phone": torch.rand(1, 200, vec_channels),
+        "phone_lengths": torch.LongTensor([200]),
+        "pitch": torch.randint(5, 255, (1, 200)),
+        "pitchf": torch.rand(1, 200),
+        "ds": torch.zeros(1).long(),
+        "rnd": torch.rand(1, 192, 200)
+    }
+    
+    checkpoint["config"][-3] = checkpoint["weight"]["emb_g.weight"].shape[0]
+    net_g = SynthesizerTrnMsNSFsidM(*checkpoint["config"], is_half=False, version=checkpoint.get("version", "v1"))
+    
+    net_g.load_state_dict(checkpoint["weight"], strict=False)
+    net_g = net_g.to(device)
+
+    dynamic_axes = {"phone": [1], "pitch": [1], "pitchf": [1], "rnd": [2]}
+
+    torch.onnx.export(
+        net_g,
+        tuple(value.to(device) for value in test_inputs.values()),
+        exported_path,
+        dynamic_axes=dynamic_axes,
+        do_constant_folding=False,
+        opset_version=13,
+        verbose=False,
+        input_names=list(test_inputs.keys()),
+        output_names=["audio"],
+    )
+    return "Finished"
+
+
+
+import re as regex
+import scipy.io.wavfile as wavfile
+
+cli_current_page = "HOME"
+
+
+def cli_split_command(com):
+    exp = r'(?:(?<=\s)|^)"(.*?)"(?=\s|$)|(\S+)'
+    split_array = regex.findall(exp, com)
+    split_array = [group[0] if group[0] else group[1] for group in split_array]
+    return split_array
+
+
+def execute_generator_function(genObject):
+    for _ in genObject:
+        pass
+
+
+def cli_infer(com):
+    # get VC first
+    com = cli_split_command(com)
+    model_name = com[0]
+    source_audio_path = com[1]
+    output_file_name = com[2]
+    feature_index_path = com[3]
+    f0_file = None  # Not Implemented Yet
+
+    # Get parameters for inference
+    speaker_id = int(com[4])
+    transposition = float(com[5])
+    f0_method = com[6]
+    crepe_hop_length = int(com[7])
+    harvest_median_filter = int(com[8])
+    resample = int(com[9])
+    mix = float(com[10])
+    feature_ratio = float(com[11])
+    protection_amnt = float(com[12])
+    protect1 = 0.5
+
+    if com[14] == "False" or com[14] == "false":
+        DoFormant = False
+        Quefrency = 0.0
+        Timbre = 0.0
+        CSVutil(
+            "csvdb/formanting.csv", "w+", "formanting", DoFormant, Quefrency, Timbre
+        )
+
+    else:
+        DoFormant = True
+        Quefrency = float(com[15])
+        Timbre = float(com[16])
+        CSVutil(
+            "csvdb/formanting.csv", "w+", "formanting", DoFormant, Quefrency, Timbre
+        )
+
+    print("Mangio-RVC-Fork Infer-CLI: Starting the inference...")
+    vc_data = vc.get_vc(model_name, protection_amnt, protect1)
+    print(vc_data)
+    print("Mangio-RVC-Fork Infer-CLI: Performing inference...")
+    conversion_data = vc.vc_single(
+        speaker_id,
+        source_audio_path,
+        source_audio_path,
+        transposition,
+        f0_file,
+        f0_method,
+        feature_index_path,
+        feature_index_path,
+        feature_ratio,
+        harvest_median_filter,
+        resample,
+        mix,
+        protection_amnt,
+        crepe_hop_length,
+    )
+    if "Success." in conversion_data[0]:
+        print(
+            "Mangio-RVC-Fork Infer-CLI: Inference succeeded. Writing to %s/%s..."
+            % ("audio-outputs", output_file_name)
+        )
+        wavfile.write(
+            "%s/%s" % ("audio-outputs", output_file_name),
+            conversion_data[1][0],
+            conversion_data[1][1],
+        )
+        print(
+            "Mangio-RVC-Fork Infer-CLI: Finished! Saved output to %s/%s"
+            % ("audio-outputs", output_file_name)
+        )
+    else:
+        print("Mangio-RVC-Fork Infer-CLI: Inference failed. Here's the traceback: ")
+        print(conversion_data[0])
+
+
+def cli_pre_process(com):
+    com = cli_split_command(com)
+    model_name = com[0]
+    trainset_directory = com[1]
+    sample_rate = com[2]
+    num_processes = int(com[3])
+
+    print("Mangio-RVC-Fork Pre-process: Starting...")
+    generator = preprocess_dataset(
+        trainset_directory, model_name, sample_rate, num_processes
+    )
+    execute_generator_function(generator)
+    print("Mangio-RVC-Fork Pre-process: Finished")
+
+
+def cli_extract_feature(com):
+    com = cli_split_command(com)
+    model_name = com[0]
+    gpus = com[1]
+    num_processes = int(com[2])
+    has_pitch_guidance = True if (int(com[3]) == 1) else False
+    f0_method = com[4]
+    crepe_hop_length = int(com[5])
+    version = com[6]  # v1 or v2
+
+    print("Mangio-RVC-CLI: Extract Feature Has Pitch: " + str(has_pitch_guidance))
+    print("Mangio-RVC-CLI: Extract Feature Version: " + str(version))
+    print("Mangio-RVC-Fork Feature Extraction: Starting...")
+    generator = extract_f0_feature(
+        gpus,
+        num_processes,
+        f0_method,
+        has_pitch_guidance,
+        model_name,
+        version,
+        crepe_hop_length,
+    )
+    execute_generator_function(generator)
+    print("Mangio-RVC-Fork Feature Extraction: Finished")
+
+
+def cli_train(com):
+    com = cli_split_command(com)
+    model_name = com[0]
+    sample_rate = com[1]
+    has_pitch_guidance = True if (int(com[2]) == 1) else False
+    speaker_id = int(com[3])
+    save_epoch_iteration = int(com[4])
+    total_epoch = int(com[5])  # 10000
+    batch_size = int(com[6])
+    gpu_card_slot_numbers = com[7]
+    if_save_latest = True if (int(com[8]) == 1) else False
+    if_cache_gpu = True if (int(com[9]) == 1) else False
+    if_save_every_weight = True if (int(com[10]) == 1) else False
+    version = com[11]
+
+    pretrained_base = "pretrained/" if version == "v1" else "pretrained_v2/"
+
+    g_pretrained_path = "%sf0G%s.pth" % (pretrained_base, sample_rate)
+    d_pretrained_path = "%sf0D%s.pth" % (pretrained_base, sample_rate)
+
+    print("Mangio-RVC-Fork Train-CLI: Training...")
+    click_train(
+        model_name,
+        sample_rate,
+        has_pitch_guidance,
+        speaker_id,
+        save_epoch_iteration,
+        total_epoch,
+        batch_size,
+        if_save_latest,
+        g_pretrained_path,
+        d_pretrained_path,
+        gpu_card_slot_numbers,
+        if_cache_gpu,
+        if_save_every_weight,
+        version,
+    )
+
+
+def cli_train_feature(com):
+    com = cli_split_command(com)
+    model_name = com[0]
+    version = com[1]
+    print("Mangio-RVC-Fork Train Feature Index-CLI: Training... Please wait")
+    generator = train_index(model_name, version)
+    execute_generator_function(generator)
+    print("Mangio-RVC-Fork Train Feature Index-CLI: Done!")
+
+
+def cli_extract_model(com):
+    com = cli_split_command(com)
+    model_path = com[0]
+    save_name = com[1]
+    sample_rate = com[2]
+    has_pitch_guidance = com[3]
+    info = com[4]
+    version = com[5]
+    extract_small_model_process = extract_small_model(
+        model_path, save_name, sample_rate, has_pitch_guidance, info, version
+    )
+    if extract_small_model_process == "Success.":
+        print("Mangio-RVC-Fork Extract Small Model: Success!")
+    else:
+        print(str(extract_small_model_process))
+        print("Mangio-RVC-Fork Extract Small Model: Failed!")
+
+
+def preset_apply(preset, qfer, tmbr):
+    if str(preset) != "":
+        with open(str(preset), "r") as p:
+            content = p.readlines()
+            qfer, tmbr = content[0].split("\n")[0], content[1]
+            formant_apply(qfer, tmbr)
+    else:
+        pass
+    return (
+        {"value": qfer, "__type__": "update"},
+        {"value": tmbr, "__type__": "update"},
+    )
+
+
+def print_page_details():
+    if cli_current_page == "HOME":
+        print(
+            "\n    go home            : Takes you back to home with a navigation list."
+            "\n    go infer           : Takes you to inference command execution."
+            "\n    go pre-process     : Takes you to training step.1) pre-process command execution."
+            "\n    go extract-feature : Takes you to training step.2) extract-feature command execution."
+            "\n    go train           : Takes you to training step.3) being or continue training command execution."
+            "\n    go train-feature   : Takes you to the train feature index command execution."
+            "\n    go extract-model   : Takes you to the extract small model command execution."
+        )
+    elif cli_current_page == "INFER":
+        print(
+            "\n    arg 1) model name with .pth in ./weights: mi-test.pth"
+            "\n    arg 2) source audio path: myFolder\\MySource.wav"
+            "\n    arg 3) output file name to be placed in './audio-outputs': MyTest.wav"
+            "\n    arg 4) feature index file path: logs/mi-test/added_IVF3042_Flat_nprobe_1.index"
+            "\n    arg 5) speaker id: 0"
+            "\n    arg 6) transposition: 0"
+            "\n    arg 7) f0 method: harvest (pm, harvest, crepe, crepe-tiny, hybrid[x,x,x,x], mangio-crepe, mangio-crepe-tiny, rmvpe)"
+            "\n    arg 8) crepe hop length: 160"
+            "\n    arg 9) harvest median filter radius: 3 (0-7)"
+            "\n    arg 10) post resample rate: 0"
+            "\n    arg 11) mix volume envelope: 1"
+            "\n    arg 12) feature index ratio: 0.78 (0-1)"
+            "\n    arg 13) Voiceless Consonant Protection (Less Artifact): 0.33 (Smaller number = more protection. 0.50 means Dont Use.)"
+            "\n    arg 14) Whether to formant shift the inference audio before conversion: False (if set to false, you can ignore setting the quefrency and timbre values for formanting)"
+            "\n    arg 15)* Quefrency for formanting: 8.0 (no need to set if arg14 is False/false)"
+            "\n    arg 16)* Timbre for formanting: 1.2 (no need to set if arg14 is False/false) \n"
+            "\nExample: mi-test.pth saudio/Sidney.wav myTest.wav logs/mi-test/added_index.index 0 -2 harvest 160 3 0 1 0.95 0.33 0.45 True 8.0 1.2"
+        )
+    elif cli_current_page == "PRE-PROCESS":
+        print(
+            "\n    arg 1) Model folder name in ./logs: mi-test"
+            "\n    arg 2) Trainset directory: mydataset (or) E:\\my-data-set"
+            "\n    arg 3) Sample rate: 40k (32k, 40k, 48k)"
+            "\n    arg 4) Number of CPU threads to use: 8 \n"
+            "\nExample: mi-test mydataset 40k 24"
+        )
+    elif cli_current_page == "EXTRACT-FEATURE":
+        print(
+            "\n    arg 1) Model folder name in ./logs: mi-test"
+            "\n    arg 2) Gpu card slot: 0 (0-1-2 if using 3 GPUs)"
+            "\n    arg 3) Number of CPU threads to use: 8"
+            "\n    arg 4) Has Pitch Guidance?: 1 (0 for no, 1 for yes)"
+            "\n    arg 5) f0 Method: harvest (pm, harvest, dio, crepe)"
+            "\n    arg 6) Crepe hop length: 128"
+            "\n    arg 7) Version for pre-trained models: v2 (use either v1 or v2)\n"
+            "\nExample: mi-test 0 24 1 harvest 128 v2"
+        )
+    elif cli_current_page == "TRAIN":
+        print(
+            "\n    arg 1) Model folder name in ./logs: mi-test"
+            "\n    arg 2) Sample rate: 40k (32k, 40k, 48k)"
+            "\n    arg 3) Has Pitch Guidance?: 1 (0 for no, 1 for yes)"
+            "\n    arg 4) speaker id: 0"
+            "\n    arg 5) Save epoch iteration: 50"
+            "\n    arg 6) Total epochs: 10000"
+            "\n    arg 7) Batch size: 8"
+            "\n    arg 8) Gpu card slot: 0 (0-1-2 if using 3 GPUs)"
+            "\n    arg 9) Save only the latest checkpoint: 0 (0 for no, 1 for yes)"
+            "\n    arg 10) Whether to cache training set to vram: 0 (0 for no, 1 for yes)"
+            "\n    arg 11) Save extracted small model every generation?: 0 (0 for no, 1 for yes)"
+            "\n    arg 12) Model architecture version: v2 (use either v1 or v2)\n"
+            "\nExample: mi-test 40k 1 0 50 10000 8 0 0 0 0 v2"
+        )
+    elif cli_current_page == "TRAIN-FEATURE":
+        print(
+            "\n    arg 1) Model folder name in ./logs: mi-test"
+            "\n    arg 2) Model architecture version: v2 (use either v1 or v2)\n"
+            "\nExample: mi-test v2"
+        )
+    elif cli_current_page == "EXTRACT-MODEL":
+        print(
+            "\n    arg 1) Model Path: logs/mi-test/G_168000.pth"
+            "\n    arg 2) Model save name: MyModel"
+            "\n    arg 3) Sample rate: 40k (32k, 40k, 48k)"
+            "\n    arg 4) Has Pitch Guidance?: 1 (0 for no, 1 for yes)"
+            '\n    arg 5) Model information: "My Model"'
+            "\n    arg 6) Model architecture version: v2 (use either v1 or v2)\n"
+            '\nExample: logs/mi-test/G_168000.pth MyModel 40k 1 "Created by Cole Mangio" v2'
+        )
+
+def change_page(page):
+    global cli_current_page
+    cli_current_page = page
+    return 0
+
+def execute_command(com):
+    if com == "go home":
+        return change_page("HOME")
+    elif com == "go infer":
+        return change_page("INFER")
+    elif com == "go pre-process":
+        return change_page("PRE-PROCESS")
+    elif com == "go extract-feature":
+        return change_page("EXTRACT-FEATURE")
+    elif com == "go train":
+        return change_page("TRAIN")
+    elif com == "go train-feature":
+        return change_page("TRAIN-FEATURE")
+    elif com == "go extract-model":
+        return change_page("EXTRACT-MODEL")
+    else:
+        if com[:3] == "go ":
+            print("page '%s' does not exist!" % com[3:])
+            return 0
+
+    if cli_current_page == "INFER":
+        cli_infer(com)
+    elif cli_current_page == "PRE-PROCESS":
+        cli_pre_process(com)
+    elif cli_current_page == "EXTRACT-FEATURE":
+        cli_extract_feature(com)
+    elif cli_current_page == "TRAIN":
+        cli_train(com)
+    elif cli_current_page == "TRAIN-FEATURE":
+        cli_train_feature(com)
+    elif cli_current_page == "EXTRACT-MODEL":
+        cli_extract_model(com)
+
+def cli_navigation_loop():
+    while True:
+        print("\nYou are currently in '%s':" % cli_current_page)
+        print_page_details()
+        command = input("%s: " % cli_current_page)
+        try:
+            execute_command(command)
+        except:
+            print(traceback.format_exc())
+
+
+if config.is_cli:
+    print("\n\nMangio-RVC-Fork v2 CLI App!\n")
+    print(
+        "Welcome to the CLI version of RVC. Please read the documentation on https://github.com/Mangio621/Mangio-RVC-Fork (README.MD) to understand how to use this app.\n"
+    )
+    cli_navigation_loop()
+
+
+
+
+
+def switch_pitch_controls(f0method0):
+    is_visible = f0method0 != 'rmvpe'
+
+    if rvc_globals.NotesOrHertz:
+        return (
+            {"visible": False, "__type__": "update"},
+            {"visible": is_visible, "__type__": "update"},
+            {"visible": False, "__type__": "update"},
+            {"visible": is_visible, "__type__": "update"}
+        )
+    else:
+        return (
+            {"visible": is_visible, "__type__": "update"},
+            {"visible": False, "__type__": "update"},
+            {"visible": is_visible, "__type__": "update"},
+            {"visible": False, "__type__": "update"}
+        )
+
+def match_index(sid0):
+    picked = False
+    # folder = sid0.split('.')[0]
+
+    # folder = re.split(r'. |_', sid0)[0]
+    folder = sid0.split(".")[0].split("_")[0]
+    # folder_test = sid0.split('.')[0].split('_')[0].split('-')[0]
+    parent_dir = "./logs/" + folder
+    # print(parent_dir)
+    if os.path.exists(parent_dir):
+        # print('path exists')
+        for filename in os.listdir(parent_dir.replace("\\", "/")):
+            if filename.endswith(".index"):
+                for i in range(len(indexes_list)):
+                    if indexes_list[i] == (
+                        os.path.join(("./logs/" + folder), filename).replace("\\", "/")
+                    ):
+                        # print('regular index found')
+                        break
+                    else:
+                        if indexes_list[i] == (
+                            os.path.join(
+                                ("./logs/" + folder.lower()), filename
+                            ).replace("\\", "/")
+                        ):
+                            # print('lowered index found')
+                            parent_dir = "./logs/" + folder.lower()
+                            break
+                        # elif (indexes_list[i]).casefold() == ((os.path.join(("./logs/" + folder), filename).replace('\\','/')).casefold()):
+                        #    print('8')
+                        #    parent_dir = "./logs/" + folder.casefold()
+                        #    break
+                        # elif (indexes_list[i]) == ((os.path.join(("./logs/" + folder_test), filename).replace('\\','/'))):
+                        #    parent_dir = "./logs/" + folder_test
+                        #    print(parent_dir)
+                        #    break
+                        # elif (indexes_list[i]) == (os.path.join(("./logs/" + folder_test.lower()), filename).replace('\\','/')):
+                        #    parent_dir = "./logs/" + folder_test
+                        #    print(parent_dir)
+                        #    break
+                        # else:
+                        #    #print('couldnt find index')
+                        #    continue
+
+                # print('all done')
+                index_path = os.path.join(
+                    parent_dir.replace("\\", "/"), filename.replace("\\", "/")
+                ).replace("\\", "/")
+                # print(index_path)
+                return (index_path, index_path)
+
+    else:
+        # print('nothing found')
+        return ("", "")
+
+def stoptraining(mim):
+    if int(mim) == 1:
+        CSVutil("csvdb/stop.csv", "w+", "stop", "True")
+        # p.terminate()
+        # p.kill()
+        try:
+            os.kill(PID, signal.SIGTERM)
+        except Exception as e:
+            print(f"Couldn't click due to {e}")
+            pass
+    else:
+        pass
+
+    return (
+        {"visible": False, "__type__": "update"},
+        {"visible": True, "__type__": "update"},
+    )
+
+weights_dir = 'weights/'
+
+def note_to_hz(note_name):
+    SEMITONES = {'C': -9, 'C#': -8, 'D': -7, 'D#': -6, 'E': -5, 'F': -4, 'F#': -3, 'G': -2, 'G#': -1, 'A': 0, 'A#': 1, 'B': 2}
+    pitch_class, octave = note_name[:-1], int(note_name[-1])
+    semitone = SEMITONES[pitch_class]
+    note_number = 12 * (octave - 4) + semitone
+    frequency = 440.0 * (2.0 ** (1.0/12)) ** note_number
+    return frequency
+
+def save_to_wav(record_button):
+    if record_button is None:
+        pass
+    else:
+        path_to_file=record_button
+        new_name = datetime.datetime.now().strftime("%Y-%m-%d_%H-%M-%S")+'.wav'
+        new_path='./audios/'+new_name
+        shutil.move(path_to_file,new_path)
+        return new_name
+def save_to_wav2_edited(dropbox):
+    if dropbox is None:
+        pass
+    else:
+        file_path = dropbox.name
+        target_path = os.path.join('audios', os.path.basename(file_path))
+
+        if os.path.exists(target_path):
+            os.remove(target_path)
+            print('Replacing old dropdown file...')
+
+        shutil.move(file_path, target_path)
+    return       
+def save_to_wav2(dropbox):
+    file_path = dropbox.name
+    target_path = os.path.join('audios', os.path.basename(file_path))
+
+    if os.path.exists(target_path):
+        os.remove(target_path)
+        print('Replacing old dropdown file...')
+
+    shutil.move(file_path, target_path)
+    return target_path
+    
+from gtts import gTTS
+import edge_tts
+import asyncio
+
+
+
+
+def custom_voice(
+        _values, # filter indices
+        audio_files, # all audio files
+        model_voice_path='',
+        transpose=0,
+        f0method='pm',
+        index_rate_=float(0.66),
+        crepe_hop_length_=float(64),
+        f0_autotune=False,
+        file_index='',
+        file_index2='',
+        ):
+
+        vc.get_vc(model_voice_path)
+
+
+        for _value_item in _values:
+            filename = "audio2/"+audio_files[_value_item] if _value_item != "converted_tts" else audio_files[0]
+            #filename = "audio2/"+audio_files[_value_item]
+            try:
+                print(audio_files[_value_item], model_voice_path)
+            except:
+                pass
+            info_, (sample_, audio_output_) = vc.vc_single_dont_save(
+                sid=0,
+                input_audio_path0=filename, #f"audio2/{filename}",
+                input_audio_path1=filename, #f"audio2/{filename}",
+                f0_up_key=transpose, # transpose for m to f and reverse 0 12
+                f0_file=None,
+                f0_method= f0method,
+                file_index= file_index, # dir pwd?
+                file_index2= file_index2,
+                # file_big_npy1,
+                index_rate= index_rate_,
+                filter_radius= int(3),
+                resample_sr= int(0),
+                rms_mix_rate= float(0.25),
+                protect= float(0.33),
+                crepe_hop_length= crepe_hop_length_,
+                f0_autotune=f0_autotune,
+                f0_min=50,
+                note_min=50,
+                f0_max=1100,
+                note_max=1100
+            )
+
+            sf.write(
+                file= filename, #f"audio2/{filename}",
+                samplerate=sample_,
+                data=audio_output_
+            )
+def cast_to_device(tensor, device):
+    try:
+        return tensor.to(device)
+    except Exception as e:
+        print(e)
+        return tensor
+
+
+def __bark__(text, voice_preset):
+    os.makedirs(os.path.join(now_dir,"tts"), exist_ok=True)
+    from transformers import AutoProcessor, BarkModel
+    device = "cuda:0" if torch.cuda.is_available() else "cpu"
+    dtype = torch.float32 if "cpu" in device else torch.float16
+    bark_processor = AutoProcessor.from_pretrained(
+        "suno/bark",
+        cache_dir=os.path.join(now_dir,"tts","suno/bark"),
+        torch_dtype=dtype)
+    bark_model = BarkModel.from_pretrained(
+        "suno/bark",
+        cache_dir=os.path.join(now_dir,"tts","suno/bark"),
+        torch_dtype=dtype).to(device)
+    # bark_model.enable_cpu_offload()
+    inputs = bark_processor(
+    text=[text],
+    return_tensors="pt",
+    voice_preset=voice_preset
+    )
+    tensor_dict = {k: cast_to_device(v,device) if hasattr(v,"to") else v for k, v in inputs.items()}
+    speech_values = bark_model.generate(**tensor_dict, do_sample=True)
+    sampling_rate = bark_model.generation_config.sample_rate
+    speech = speech_values.cpu().numpy().squeeze()
+    return speech, sampling_rate
+
+
+
+def make_test( 
+        tts_text, 
+        tts_voice, 
+        model_path,
+        index_path,
+        transpose,
+        f0_method,
+        index_rate,
+        crepe_hop_length,
+        f0_autotune,
+        tts_method
+        ):
+
+        if tts_voice == None:
+            return
+        
+        filename = os.path.join(now_dir, "audio-outputs", "converted_tts.wav")
+        if "SET_LIMIT" == os.getenv("DEMO"):
+          if len(tts_text) > 60:
+            tts_text = tts_text[:60]
+            print("DEMO; limit to 60 characters")
+
+        language = tts_voice[:2]
+        if tts_method == "Edge-tts":
+            try:
+                #nest_asyncio.apply() # gradio;not
+                asyncio.run(edge_tts.Communicate(tts_text, "-".join(tts_voice.split('-')[:-1])).save(filename))
+            except:
+               try:
+                  tts = gTTS(tts_text, lang=language)
+                  tts.save(filename)
+                  tts.save
+                  print(f'No audio was received. Please change the tts voice for {tts_voice}. USING gTTS.')
+               except:
+                tts = gTTS('a', lang=language)
+                tts.save(filename)
+                print('Error: Audio will be replaced.')
+    
+            os.system("cp audio-outputs/converted_tts.wav audio-outputs/real_tts.wav")
+
+            custom_voice(
+                ["converted_tts"], # filter indices
+                ["audio-outputs/converted_tts.wav"], # all audio files
+                model_voice_path=model_path,
+                transpose=transpose,
+                f0method=f0_method,
+                index_rate_=index_rate,
+                crepe_hop_length_=crepe_hop_length,
+                f0_autotune=f0_autotune,
+                file_index='',
+                file_index2=index_path,
+            )
+            return os.path.join(now_dir, "audio-outputs", "converted_tts.wav"), os.path.join(now_dir, "audio-outputs", "real_tts.wav")
+        elif tts_method == "Bark-tts":
+            try:
+                
+                script = tts_text.replace("\n", " ").strip()
+                sentences = sent_tokenize(script)
+                print(sentences)
+                silence = np.zeros(int(0.25 * SAMPLE_RATE))
+                pieces = []
+                nombre_archivo = os.path.join(now_dir, "audio-outputs", "bark_out.wav")
+                for sentence in sentences:
+                    audio_array , _ = __bark__(sentence, tts_voice.split("-")[0])
+                    pieces += [audio_array, silence.copy()]
+            
+                sf.write(
+                    file= nombre_archivo,
+                    samplerate=SAMPLE_RATE,
+                    data=np.concatenate(pieces)
+                )
+                vc.get_vc(model_path)
+                info_, (sample_, audio_output_) = vc.vc_single_dont_save(
+                    sid=0,
+                    input_audio_path0=os.path.join(now_dir, "audio-outputs", "bark_out.wav"), #f"audio2/{filename}",
+                    input_audio_path1=os.path.join(now_dir, "audio-outputs", "bark_out.wav"), #f"audio2/{filename}",
+                    f0_up_key=transpose, # transpose for m to f and reverse 0 12
+                    f0_file=None,
+                    f0_method=f0_method,
+                    file_index= '', # dir pwd?
+                    file_index2= index_path,
+                    # file_big_npy1,
+                    index_rate= index_rate,
+                    filter_radius= int(3),
+                    resample_sr= int(0),
+                    rms_mix_rate= float(0.25),
+                    protect= float(0.33),
+                    crepe_hop_length= crepe_hop_length,
+                    f0_autotune=f0_autotune,
+                    f0_min=50,
+                    note_min=50,
+                    f0_max=1100,
+                    note_max=1100
+                )
+                wavfile.write(os.path.join(now_dir, "audio-outputs", "converted_bark.wav"), rate=sample_, data=audio_output_)
+                return os.path.join(now_dir, "audio-outputs", "converted_bark.wav"), nombre_archivo
+
+            except Exception as e:
+                print(f"{e}")
+                return None, None  
+            
+
+
+        
+        
+
+def GradioSetup(UTheme=gr.themes.Soft()):
+
+    default_weight = names[0] if names else '' 
+
+    with gr.Blocks(theme='JohnSmith9982/small_and_pretty', title="Applio") as app:
+        gr.HTML("<h1> 🍏 Applio (Mangio-RVC-Fork) </h1>")
+        with gr.Tabs():
+            with gr.TabItem(i18n("Model Inference")):
+                with gr.Row():
+                    sid0 = gr.Dropdown(label=i18n("Inferencing voice:"), choices=sorted(names), value=default_weight)
+                    refresh_button = gr.Button(i18n("Refresh"), variant="primary")
+                    clean_button = gr.Button(i18n("Unload voice to save GPU memory"), variant="primary")
+                    clean_button.click(fn=lambda: ({"value": "", "__type__": "update"}), inputs=[], outputs=[sid0])
+
+                
+                with gr.TabItem(i18n("Single")):
+                    with gr.Row(): 
+                        spk_item = gr.Slider(
+                            minimum=0,
+                            maximum=2333,
+                            step=1,
+                            label=i18n("Select Speaker/Singer ID:"),
+                            value=0,
+                            visible=False,
+                            interactive=True,
+                        )
+                       
+
+                    with gr.Group(): 
+                        with gr.Row():
+                            with gr.Column(): # First column for audio-related inputs
+                                dropbox = gr.File(label=i18n("Drag your audio here:"))
+                                record_button=gr.Audio(source="microphone", label=i18n("Or record an audio:"), type="filepath")
+                                input_audio0 = gr.Textbox(
+                                    label=i18n("Manual path to the audio file to be processed"),
+                                    value=os.path.join(now_dir, "audios", "someguy.mp3"),
+                                    visible=False
+                                )
+                                input_audio1 = gr.Dropdown(
+                                    label=i18n("Auto detect audio path and select from the dropdown:"),
+                                    choices=sorted(audio_paths),
+                                    value='',
+                                    interactive=True,
+                                )
+                                
+                                input_audio1.select(fn=lambda:'',inputs=[],outputs=[input_audio0])
+                                input_audio0.input(fn=lambda:'',inputs=[],outputs=[input_audio1])
+                                
+                                dropbox.upload(fn=save_to_wav2, inputs=[dropbox], outputs=[input_audio0])
+                                dropbox.upload(fn=easy_infer.change_choices2, inputs=[], outputs=[input_audio1])
+                                record_button.change(fn=save_to_wav, inputs=[record_button], outputs=[input_audio0])
+                                record_button.change(fn=easy_infer.change_choices2, inputs=[], outputs=[input_audio1])
+
+                            best_match_index_path1 = match_index(sid0.value) # Get initial index from default sid0 (first voice model in list)
+
+                            with gr.Column(): # Second column for pitch shift and other options
+                                file_index2 = gr.Dropdown(
+                                    label=i18n("Auto-detect index path and select from the dropdown:"),
+                                    choices=get_indexes(),
+                                    value=best_match_index_path1,
+                                    interactive=True,
+                                    allow_custom_value=True,
+                                )
+                                index_rate1 = gr.Slider(
+                                    minimum=0,
+                                    maximum=1,
+                                    label=i18n("Search feature ratio:"),
+                                    value=0.75,
+                                    interactive=True,
+                                )
+                                refresh_button.click(
+                                    fn=change_choices, inputs=[], outputs=[sid0, file_index2, input_audio1]
+                                )
+                                with gr.Column():
+                                    vc_transform0 = gr.Number(
+                                        label=i18n("Transpose (integer, number of semitones, raise by an octave: 12, lower by an octave: -12):"), value=0
+                                    )
+        
+                    # Create a checkbox for advanced settings
+                    advanced_settings_checkbox = gr.Checkbox(
+                        value=False,
+                        label=i18n("Advanced Settings"),
+                        interactive=True,
+                    )
+                    
+                    # Advanced settings container        
+                    with gr.Column(visible=False) as advanced_settings: # Initially hidden
+                        with gr.Row(label = i18n("Advanced Settings"), open = False):
+                            with gr.Column():
+                                f0method0 = gr.Radio(
+                                    label=i18n(
+                                        "Select the pitch extraction algorithm:"
+                                    ),
+                                    choices=["pm", "harvest", "dio", "crepe", "crepe-tiny", "mangio-crepe", "mangio-crepe-tiny", "rmvpe", "rmvpe+"], 
+                                    value="rmvpe+",
+                                    interactive=True,
+                                )
+                                f0_autotune = gr.Checkbox(
+                                    label="Enable autotune",
+                                    interactive=True
+                                )
+                                crepe_hop_length = gr.Slider(
+                                    minimum=1,
+                                    maximum=512,
+                                    step=1,
+                                    label=i18n("Mangio-Crepe Hop Length (Only applies to mangio-crepe): Hop length refers to the time it takes for the speaker to jump to a dramatic pitch. Lower hop lengths take more time to infer but are more pitch accurate."),
+                                    value=120,
+                                    interactive=True,
+                                    visible=False,
+                                )
+                                filter_radius0 = gr.Slider(
+                                    minimum=0,
+                                    maximum=7,
+                                    label=i18n("If >=3: apply median filtering to the harvested pitch results. The value represents the filter radius and can reduce breathiness."),
+                                    value=3,
+                                    step=1,
+                                    interactive=True,
+                                )    
+
+                                minpitch_slider = gr.Slider(
+                                    label       = i18n("Min pitch:"),
+                                    info        = i18n("Specify minimal pitch for inference [HZ]"),
+                                    step        = 0.1,
+                                    minimum     = 1,
+                                    scale       = 0,
+                                    value       = 50,
+                                    maximum     = 16000,
+                                    interactive = True,
+                                    visible     = (not rvc_globals.NotesOrHertz) and (f0method0.value != 'rmvpe'),
+                                )
+                                minpitch_txtbox = gr.Textbox(
+                                    label       = i18n("Min pitch:"),
+                                    info        = i18n("Specify minimal pitch for inference [NOTE][OCTAVE]"),
+                                    placeholder = "C5",
+                                    visible     = (rvc_globals.NotesOrHertz) and (f0method0.value != 'rmvpe'),
+                                    interactive = True,
+                                )
+
+                                maxpitch_slider = gr.Slider(
+                                    label       = i18n("Max pitch:"),
+                                    info        = i18n("Specify max pitch for inference [HZ]"),
+                                    step        = 0.1,
+                                    minimum     = 1,
+                                    scale       = 0,
+                                    value       = 1100,
+                                    maximum     = 16000,
+                                    interactive = True,
+                                    visible     = (not rvc_globals.NotesOrHertz) and (f0method0.value != 'rmvpe'),
+                                )
+                                maxpitch_txtbox = gr.Textbox(
+                                    label       = i18n("Max pitch:"),
+                                    info        = i18n("Specify max pitch for inference [NOTE][OCTAVE]"),
+                                    placeholder = "C6",
+                                    visible     = (rvc_globals.NotesOrHertz) and (f0method0.value != 'rmvpe'),
+                                    interactive = True,
+                                )
+
+                            with gr.Column():
+                                file_index1 = gr.Textbox(
+                                    label=i18n("Feature search database file path:"),
+                                    value="",
+                                    interactive=True,
+                                )
+                            
+                                with gr.Accordion(label = i18n("Custom f0 [Root pitch] File"), open = False):
+                                    f0_file = gr.File(label=i18n("F0 curve file (optional). One pitch per line. Replaces the default F0 and pitch modulation:"))
+
+                            f0method0.change(
+                                fn=lambda radio: (
+                                    {
+                                        "visible": radio in ['mangio-crepe', 'mangio-crepe-tiny'],
+                                        "__type__": "update"
+                                    }
+                                ),
+                                inputs=[f0method0],
+                                outputs=[crepe_hop_length]
+                            )
+
+                            f0method0.change(
+                                fn=switch_pitch_controls,
+                                inputs=[f0method0],
+                                outputs=[minpitch_slider, minpitch_txtbox,
+                                         maxpitch_slider, maxpitch_txtbox]
+                            )                            
+                            
+                            with gr.Column():
+                                resample_sr0 = gr.Slider(
+                                    minimum=0,
+                                    maximum=48000,
+                                    label=i18n("Resample the output audio in post-processing to the final sample rate. Set to 0 for no resampling:"),
+                                    value=0,
+                                    step=1,
+                                    interactive=True,
+                                )
+                                rms_mix_rate0 = gr.Slider(
+                                    minimum=0,
+                                    maximum=1,
+                                    label=i18n("Use the volume envelope of the input to replace or mix with the volume envelope of the output. The closer the ratio is to 1, the more the output envelope is used:"),
+                                    value=0.25,
+                                    interactive=True,
+                                )
+                                protect0 = gr.Slider(
+                                    minimum=0,
+                                    maximum=0.5,
+                                    label=i18n(
+                                        "Protect voiceless consonants and breath sounds to prevent artifacts such as tearing in electronic music. Set to 0.5 to disable. Decrease the value to increase protection, but it may reduce indexing accuracy:"
+                                    ),
+                                    value=0.33,
+                                    step=0.01,
+                                    interactive=True,
+                                )
+                                formanting = gr.Checkbox(
+                                    value=bool(DoFormant),
+                                    label=i18n("Formant shift inference audio"),
+                                    info=i18n("Used for male to female and vice-versa conversions"),
+                                    interactive=True,
+                                    visible=True,
+                                )
+                                
+                                formant_preset = gr.Dropdown(
+                                    value='',
+                                    choices=get_fshift_presets(),
+                                    label=i18n("Browse presets for formanting"),
+                                    info=i18n("Presets are located in formantshiftcfg/ folder"),
+                                    visible=bool(DoFormant),
+                                )
+                                
+                                formant_refresh_button = gr.Button(
+                                    value='\U0001f504',
+                                    visible=bool(DoFormant),
+                                    variant='primary',
+                                )
+                                
+                                qfrency = gr.Slider(
+                                        value=Quefrency,
+                                        info=i18n("Default value is 1.0"),
+                                        label=i18n("Quefrency for formant shifting"),
+                                        minimum=0.0,
+                                        maximum=16.0,
+                                        step=0.1,
+                                        visible=bool(DoFormant),
+                                        interactive=True,
+                                )
+                                    
+                                tmbre = gr.Slider(
+                                    value=Timbre,
+                                    info=i18n("Default value is 1.0"),
+                                    label=i18n("Timbre for formant shifting"),
+                                    minimum=0.0,
+                                    maximum=16.0,
+                                    step=0.1,
+                                    visible=bool(DoFormant),
+                                    interactive=True,
+                                )
+                                frmntbut = gr.Button(
+                                   "Apply", variant="primary", visible=bool(DoFormant)
+                                )
+                               
+                            formant_preset.change(
+                                fn=preset_apply,
+                                inputs=[formant_preset, qfrency, tmbre],
+                                outputs=[qfrency, tmbre],
+                            )
+                            formanting.change(
+                               fn=formant_enabled,
+                               inputs=[
+                                   formanting,
+                                   qfrency,
+                                   tmbre,
+                                   frmntbut,
+                                   formant_preset,
+                                   formant_refresh_button,
+                               ],
+                               outputs=[
+                                   formanting,
+                                   qfrency,
+                                   tmbre,
+                                   frmntbut,
+                                   formant_preset,
+                                   formant_refresh_button,
+                               ],
+                            )
+                            frmntbut.click(
+                                fn=formant_apply,
+                                inputs=[qfrency, tmbre],
+                                outputs=[qfrency, tmbre],
+                            )
+                            formant_refresh_button.click(
+                                fn=update_fshift_presets,
+                                inputs=[formant_preset, qfrency, tmbre],
+                                outputs=[formant_preset, qfrency, tmbre],
+                            )
+
+                    # Function to toggle advanced settings
+                    def toggle_advanced_settings(checkbox):
+                        return {"visible": checkbox, "__type__": "update"}
+
+                    # Attach the change event
+                    advanced_settings_checkbox.change(
+                        fn=toggle_advanced_settings,
+                        inputs=[advanced_settings_checkbox],
+                        outputs=[advanced_settings]
+                    )
+                                               
+                    
+                    but0 = gr.Button(i18n("Convert"), variant="primary").style(full_width=True)
+                    
+                    with gr.Row(): # Defines output info + output audio download after conversion
+                        vc_output1 = gr.Textbox(label=i18n("Output information:"))
+                        vc_output2 = gr.Audio(label=i18n("Export audio (click on the three dots in the lower right corner to download)"))
+
+                    with gr.Group(): # I think this defines the big convert button
+                        with gr.Row():
+                            but0.click(
+                                vc.vc_single,
+                                [
+                                    spk_item,
+                                    input_audio0,
+                                    input_audio1,
+                                    vc_transform0,
+                                    f0_file,
+                                    f0method0,
+                                    file_index1,
+                                    file_index2,
+                                    index_rate1,
+                                    filter_radius0,
+                                    resample_sr0,
+                                    rms_mix_rate0,
+                                    protect0,
+                                    crepe_hop_length,
+                                    minpitch_slider, minpitch_txtbox,
+                                    maxpitch_slider, maxpitch_txtbox,
+                                    f0_autotune
+                                ],
+                                [vc_output1, vc_output2],
+                            )
+                           
+                    
+                with gr.TabItem(i18n("Batch")): # Dont Change
+                    with gr.Group(): # Markdown explanation of batch inference
+                        gr.Markdown(
+                            value=i18n("Batch conversion. Enter the folder containing the audio files to be converted or upload multiple audio files. The converted audio will be output in the specified folder (default: 'opt').")
+                        )
+                        with gr.Row():
+                            with gr.Column():
+                                vc_transform1 = gr.Number(
+                                    label=i18n("Transpose (integer, number of semitones, raise by an octave: 12, lower by an octave: -12):"), value=0
+                                )
+                                opt_input = gr.Textbox(label=i18n("Specify output folder:"), value="opt")
+                            with gr.Column():
+                                file_index4 = gr.Dropdown(
+                                    label=i18n("Auto-detect index path and select from the dropdown:"),
+                                    choices=get_indexes(),
+                                    value=best_match_index_path1,
+                                    interactive=True,
+                                )
+                                sid0.select(fn=match_index, inputs=[sid0], outputs=[file_index2, file_index4])
+
+                                refresh_button.click(
+                                    fn=lambda: change_choices()[1],
+                                    inputs=[],
+                                    outputs=file_index4,
+                                )
+                                index_rate2 = gr.Slider(
+                                    minimum=0,
+                                    maximum=1,
+                                    label=i18n("Search feature ratio:"),
+                                    value=0.75,
+                                    interactive=True,
+                                )
+                            with gr.Row():
+                                dir_input = gr.Textbox(
+                                    label=i18n("Enter the path of the audio folder to be processed (copy it from the address bar of the file manager):"),
+                                    value=os.path.join(now_dir, "audios"),
+                                )
+                                inputs = gr.File(
+                                    file_count="multiple", label=i18n("You can also input audio files in batches. Choose one of the two options. Priority is given to reading from the folder.")
+                                )
+
+                        with gr.Row():
+                            with gr.Column():
+                                # Create a checkbox for advanced batch settings
+                                advanced_settings_batch_checkbox = gr.Checkbox(
+                                    value=False,
+                                    label=i18n("Advanced Settings"),
+                                    interactive=True,
+                                )
+                            
+                                # Advanced batch settings container        
+                                with gr.Row(visible=False) as advanced_settings_batch: # Initially hidden
+                                    with gr.Row(label = i18n("Advanced Settings"), open = False):
+                                        with gr.Column():
+                                            file_index3 = gr.Textbox(
+                                                label=i18n("Feature search database file path:"),
+                                                value="",
+                                                interactive=True,
+                                            )
+
+                                    f0method1 = gr.Radio(
+                                        label=i18n(
+                                            "Select the pitch extraction algorithm:"
+                                        ),
+                                        choices=["pm", "harvest", "crepe", "rmvpe"],
+                                        value="rmvpe",
+                                        interactive=True,
+                                    )
+                                    f0_autotune = gr.Checkbox(
+                                    label="Enable autotune",
+                                    interactive=True
+                                    )
+                                    filter_radius1 = gr.Slider(
+                                        minimum=0,
+                                        maximum=7,
+                                        label=i18n("If >=3: apply median filtering to the harvested pitch results. The value represents the filter radius and can reduce breathiness."),
+                                        value=3,
+                                        step=1,
+                                        interactive=True,
+                                    )
+                                
+                                    with gr.Row():
+                                        format1 = gr.Radio(
+                                            label=i18n("Export file format"),
+                                            choices=["wav", "flac", "mp3", "m4a"],
+                                            value="wav",
+                                            interactive=True,
+                                        )
+                                        
+
+                                    with gr.Column():
+                                        resample_sr1 = gr.Slider(
+                                            minimum=0,
+                                            maximum=48000,
+                                            label=i18n("Resample the output audio in post-processing to the final sample rate. Set to 0 for no resampling:"),
+                                            value=0,
+                                            step=1,
+                                            interactive=True,
+                                        )
+                                        rms_mix_rate1 = gr.Slider(
+                                            minimum=0,
+                                            maximum=1,
+                                            label=i18n("Use the volume envelope of the input to replace or mix with the volume envelope of the output. The closer the ratio is to 1, the more the output envelope is used:"),
+                                            value=1,
+                                            interactive=True,
+                                        )
+                                        protect1 = gr.Slider(
+                                            minimum=0,
+                                            maximum=0.5,
+                                            label=i18n(
+                                                "Protect voiceless consonants and breath sounds to prevent artifacts such as tearing in electronic music. Set to 0.5 to disable. Decrease the value to increase protection, but it may reduce indexing accuracy:"
+                                            ),
+                                            value=0.33,
+                                            step=0.01,
+                                            interactive=True,
+                                        )
+                                vc_output3 = gr.Textbox(label=i18n("Output information:")) 
+                                but1 = gr.Button(i18n("Convert"), variant="primary")
+                                but1.click(
+                                    vc.vc_multi,
+                                    [
+                                        spk_item,
+                                        dir_input,
+                                        opt_input,
+                                        inputs,
+                                        vc_transform1,
+                                        f0method1,
+                                        file_index3,
+                                        file_index4,
+                                        index_rate2,
+                                        filter_radius1,
+                                        resample_sr1,
+                                        rms_mix_rate1,
+                                        protect1,
+                                        format1,
+                                        crepe_hop_length,
+                                        minpitch_slider if (not rvc_globals.NotesOrHertz) else minpitch_txtbox,
+                                        maxpitch_slider if (not rvc_globals.NotesOrHertz) else maxpitch_txtbox,
+                                        f0_autotune
+                                    ],
+                                    [vc_output3],
+                                )
+
+                    sid0.change(
+                        fn=vc.get_vc,
+                        inputs=[sid0, protect0, protect1],
+                        outputs=[spk_item, protect0, protect1],
+                    )
+                    if not sid0.value == '':
+                        spk_item, protect0, protect1 = vc.get_vc(sid0.value, protect0, protect1)
+
+                    #spk_item, protect0, protect1 = vc.get_vc(sid0.value, protect0, protect1) 
+
+                    # Function to toggle advanced settings
+                    def toggle_advanced_settings_batch(checkbox):
+                        return {"visible": checkbox, "__type__": "update"}
+
+                    # Attach the change event
+                    advanced_settings_batch_checkbox.change(
+                        fn=toggle_advanced_settings_batch,
+                        inputs=[advanced_settings_batch_checkbox],
+                        outputs=[advanced_settings_batch]
+                    )                           
+                    
+                
+            with gr.TabItem(i18n("Train")):
+                with gr.Accordion(label=i18n("Step 1: Processing data")):
+                    with gr.Row():
+                        exp_dir1 = gr.Textbox(label=i18n("Enter the model name:"), value=i18n("Model_Name"))
+                        sr2 = gr.Radio(
+                            label=i18n("Target sample rate:"),
+                            choices=["40k", "48k", "32k"],
+                            value="40k",
+                            interactive=True,
+                        )
+                        if_f0_3 = gr.Checkbox(
+                            label=i18n("Whether the model has pitch guidance."),
+                            value=True,
+                            interactive=True,
+                        )
+                        version19 = gr.Radio(
+                            label=i18n("Version:"),
+                            choices=["v1", "v2"],
+                            value="v2",
+                            interactive=True,
+                            visible=True,
+                        )
+                        np7 = gr.Slider(
+                            minimum=0,
+                            maximum=config.n_cpu,
+                            step=1,
+                            label=i18n("Number of CPU processes:"),
+                            value=int(np.ceil(config.n_cpu / 1.5)),
+                            interactive=True,
+                        )
+                with gr.Group():
+                    with gr.Accordion(label=i18n("Step 2: Skipping pitch extraction")):
+               
+                        with gr.Row():
+                        #  trainset_dir4 = gr.Textbox(
+                        #      label=i18n("Enter the path of the training folder:"), value=os.path.join(now_dir, datasets_root)
+                        #  )
+                            with gr.Column():
+                                trainset_dir4 = gr.Dropdown(choices=sorted(datasets), label=i18n("Select your dataset:"), value=get_dataset())
+                                btn_update_dataset_list = gr.Button(i18n("Update list"), variant="primary")
+                            spk_id5 = gr.Slider(
+                                minimum=0,
+                                maximum=4,
+                                step=1,
+                                label=i18n("Specify the model ID:"),
+                                value=0,
+                                interactive=True,
+                            )
+                            btn_update_dataset_list.click(
+                            easy_infer.update_dataset_list, [spk_id5], trainset_dir4
+                            )
+                            but1 = gr.Button(i18n("Process data"), variant="primary")
+                            info1 = gr.Textbox(label=i18n("Output information:"), value="")
+                            but1.click(
+                                preprocess_dataset, [trainset_dir4, exp_dir1, sr2, np7], [info1]
+                            )
+                with gr.Group():
+                    with gr.Accordion(label=i18n("Step 3: Extracting features")):
+                        with gr.Row():
+                            with gr.Column():
+                                gpus6 = gr.Textbox(
+                                    label=i18n("Provide the GPU index(es) separated by '-', like 0-1-2 for using GPUs 0, 1, and 2:"),
+                                    value=gpus,
+                                    interactive=True,
+                                )
+                                gpu_info9 = gr.Textbox(
+                                    label=i18n("GPU Information:"), value=gpu_info, visible=F0GPUVisible
+                                )
+                            with gr.Column():
+                                f0method8 = gr.Radio(
+                                    label=i18n(
+                                        "Select the pitch extraction algorithm:"
+                                    ),
+                                    choices=["pm", "harvest", "dio", "crepe", "mangio-crepe", "rmvpe", "rmvpe_gpu"],
+                                    # [ MANGIO ]: Fork feature: Crepe on f0 extraction for training.
+                                    value="rmvpe",
+                                    interactive=True,
+                                )
+                                gpus_rmvpe = gr.Textbox(
+                                    label=i18n(
+                                        "rmvpe卡号配置：以-分隔输入使用的不同进程卡号,例如0-0-1使用在卡0上跑2个进程并在卡1上跑1个进程"
+                                        ),
+                                        value="%s-%s" % (gpus, gpus),
+                                        interactive=True,
+                                        visible=F0GPUVisible,
+                                )
+                                
+                                extraction_crepe_hop_length = gr.Slider(
+                                    minimum=1,
+                                    maximum=512,
+                                    step=1,
+                                    label=i18n("Mangio-Crepe Hop Length (Only applies to mangio-crepe): Hop length refers to the time it takes for the speaker to jump to a dramatic pitch. Lower hop lengths take more time to infer but are more pitch accurate."),
+                                    value=64,
+                                    interactive=True,
+                                    visible=False,
+                                )
+                                
+                                f0method8.change(
+                                    fn=lambda radio: (
+                                        {
+                                            "visible": radio in ['mangio-crepe', 'mangio-crepe-tiny'],
+                                            "__type__": "update"
+                                        }
+                                    ),
+                                    inputs=[f0method8],
+                                    outputs=[extraction_crepe_hop_length]
+                                )
+                                f0method8.change(
+                                    fn=change_f0_method,
+                                    inputs=[f0method8],
+                                    outputs=[gpus_rmvpe],
+                                    )
+                            but2 = gr.Button(i18n("Feature extraction"), variant="primary")
+                            info2 = gr.Textbox(label=i18n("Output information:"), value="", max_lines=8, interactive=False)
+                            but2.click(
+                                extract_f0_feature,
+                                [gpus6, np7, f0method8, if_f0_3, exp_dir1, version19, extraction_crepe_hop_length, gpus_rmvpe,],
+                                [info2],
+                            )
+                with gr.Group():
+                    with gr.Row():
+                        with gr.Accordion(label=i18n("Step 4: Model training started")):
+                            with gr.Row():
+                                save_epoch10 = gr.Slider(
+                                    minimum=1,
+                                    maximum=100,
+                                    step=1,
+                                    label=i18n("Save frequency:"),
+                                    value=10,
+                                    interactive=True,
+                                    visible=True,
+                                )
+                                total_epoch11 = gr.Slider(
+                                    minimum=1,
+                                    maximum=10000,
+                                    step=2,
+                                    label=i18n("Training epochs:"),
+                                    value=750,
+                                    interactive=True,
+                                )
+                                batch_size12 = gr.Slider(
+                                    minimum=1,
+                                    maximum=50,
+                                    step=1,
+                                    label=i18n("Batch size per GPU:"),
+                                    value=default_batch_size,
+                                    #value=20,
+                                    interactive=True,
+                                )
+                        
+                            with gr.Row(): 
+                                if_save_latest13 = gr.Checkbox(
+                                        label=i18n("Whether to save only the latest .ckpt file to save hard drive space"),
+                                        value=True,
+                                        interactive=True,
+                                    )
+                                if_cache_gpu17 = gr.Checkbox(
+                                        label=i18n("Cache all training sets to GPU memory. Caching small datasets (less than 10 minutes) can speed up training"),
+                                        value=False,
+                                        interactive=True,
+                                    )
+                                if_save_every_weights18 = gr.Checkbox(
+                                        label=i18n("Save a small final model to the 'weights' folder at each save point"),
+                                        value=True,
+                                        interactive=True,
+                                    )
+               
+                            with gr.Row():    
+                                pretrained_G14 = gr.Textbox(
+                                    lines=4,
+                                    label=i18n("Load pre-trained base model G path:"),
+                                    value="assets/pretrained_v2/f0G40k.pth",
+                                    interactive=True,
+                                )
+                                pretrained_D15 = gr.Textbox(
+                                    lines=4,
+                                    label=i18n("Load pre-trained base model D path:"),
+                                    value="assets/pretrained_v2/f0D40k.pth",
+                                    interactive=True,
+                                )
+                                gpus16 = gr.Textbox(
+                                    label=i18n("Provide the GPU index(es) separated by '-', like 0-1-2 for using GPUs 0, 1, and 2:"),
+                                    value=gpus,
+                                    interactive=True,
+                                )  
+                                sr2.change(
+                                    change_sr2,
+                                    [sr2, if_f0_3, version19],
+                                    [pretrained_G14, pretrained_D15],
+                                )
+                                version19.change(
+                                    change_version19,
+                                    [sr2, if_f0_3, version19],
+                                    [pretrained_G14, pretrained_D15, sr2],
+                                )
+                                if_f0_3.change(
+                                        fn=change_f0,
+                                        inputs=[if_f0_3, sr2, version19],
+                                        outputs=[f0method8, pretrained_G14, pretrained_D15],
+                                )
+                                if_f0_3.change(fn=lambda radio: (
+                                            {
+                                                "visible": radio in ['mangio-crepe', 'mangio-crepe-tiny'],
+                                                "__type__": "update"
+                                            }
+                                        ), inputs=[f0method8], outputs=[extraction_crepe_hop_length])
+                                
+                                butstop = gr.Button(i18n("Stop training"),
+                                            variant='primary',
+                                            visible=False,
+                                        )
+                                but3 = gr.Button(i18n("Train model"), variant="primary", visible=True)
+                                but3.click(fn=stoptraining, inputs=[gr.Number(value=0, visible=False)], outputs=[but3, butstop])
+                                butstop.click(fn=stoptraining, inputs=[gr.Number(value=1, visible=False)], outputs=[but3, butstop])
+                                
+                                
+                                with gr.Column():
+                                        info3 = gr.Textbox(label=i18n("Output information:"), value="", max_lines=4)
+                                        save_action = gr.Dropdown(label=i18n("Save type"), choices=[i18n("Save all"),i18n("Save D and G"),i18n("Save voice")], value=i18n("Choose the method"), interactive=True)
+                                        
+                                        but7 = gr.Button(i18n("Save model"), variant="primary")
+                                        but4 = gr.Button(i18n("Train feature index"), variant="primary")
+                             
+                   
+                                    
+                                if_save_every_weights18.change(
+                                        fn=lambda if_save_every_weights: (
+                                            {
+                                                "visible": if_save_every_weights,
+                                                "__type__": "update"
+                                            }
+                                        ),
+                                        inputs=[if_save_every_weights18],
+                                        outputs=[save_epoch10]
+                                    )
+                            
+                            but3.click(
+                                click_train,
+                                [
+                                    exp_dir1,
+                                    sr2,
+                                    if_f0_3,
+                                    spk_id5,
+                                    save_epoch10,
+                                    total_epoch11,
+                                    batch_size12,
+                                    if_save_latest13,
+                                    pretrained_G14,
+                                    pretrained_D15,
+                                    gpus16,
+                                    if_cache_gpu17,
+                                    if_save_every_weights18,
+                                    version19,
+                                ],
+                                [info3, butstop, but3],
+                            )
+                                
+                            but4.click(train_index, [exp_dir1, version19], info3)
+                            but7.click(easy_infer.save_model, [exp_dir1, save_action], info3)
+                with gr.Group():
+                    with gr.Row():
+                        with gr.Accordion(label=i18n("Step 5: Export lowest points on a graph of the model")):
+                        
+                            lowestval_weight_dir = gr.Textbox(visible=False)
+                            ds = gr.Textbox(visible=False)
+                            weights_dir1 = gr.Textbox(visible=False, value=weights_dir)
+                            
+                                
+                            with gr.Row():
+                                amntlastmdls = gr.Slider(
+                                    minimum=1,
+                                    maximum=25,
+                                    label=i18n('How many lowest points to save:'),
+                                    value=3,
+                                    step=1,
+                                    interactive=True,
+                                )
+                                lpexport = gr.Button(
+                                    value=i18n('Export lowest points of a model'),
+                                    variant='primary',
+                                )
+                                lw_mdls = gr.File(
+                                    file_count="multiple",
+                                    label=i18n("Output models:"),
+                                    interactive=False,
+                                ) #####
+                                
+                            with gr.Row():
+                                infolpex = gr.Textbox(label=i18n("Output information:"), value="", max_lines=10)
+                                mdlbl = gr.Dataframe(label=i18n('Stats of selected models:'), datatype='number', type='pandas')
+                            
+                            lpexport.click(
+                                lambda model_name: os.path.join("logs", model_name, "lowestvals"),
+                                inputs=[exp_dir1],
+                                outputs=[lowestval_weight_dir]
+                            )
+                            
+                            lpexport.click(fn=tensorlowest.main, inputs=[exp_dir1, save_epoch10, amntlastmdls], outputs=[ds])
+                            
+                            ds.change(
+                                fn=tensorlowest.selectweights,
+                                inputs=[exp_dir1, ds, weights_dir1, lowestval_weight_dir],
+                                outputs=[infolpex, lw_mdls, mdlbl],
+                            )
+            with gr.TabItem(i18n("UVR5")): # UVR section 
+                with gr.Group():
+                    with gr.Row():
+                        with gr.Column():
+                            model_select = gr.Radio(
+                                label=i18n("Model Architecture:"),
+                                choices=["VR", "MDX"],
+                                value="VR",
+                                interactive=True,
+                            )
+                            dir_wav_input = gr.Textbox(
+                                label=i18n("Enter the path of the audio folder to be processed:"),
+                                value=os.path.join(now_dir, "audios")
+                            )
+                            wav_inputs = gr.File(
+                                file_count="multiple", label=i18n("You can also input audio files in batches. Choose one of the two options. Priority is given to reading from the folder.")
+                            )
+                            
+                        with gr.Column():
+                            model_choose = gr.Dropdown(label=i18n("Model:"), choices=uvr5_names)
+                            agg = gr.Slider(
+                                minimum=0,
+                                maximum=20,
+                                step=1,
+                                label="Vocal Extraction Aggressive",
+                                value=10,
+                                interactive=True,
+                                visible=False,
+                            )
+                            opt_vocal_root = gr.Textbox(
+                                label=i18n("Specify the output folder for vocals:"), value="opt"
+                            )
+                            opt_ins_root = gr.Textbox(
+                                label=i18n("Specify the output folder for accompaniment:"), value="opt"
+                            )
+                            format0 = gr.Radio(
+                                label=i18n("Export file format:"),
+                                choices=["wav", "flac", "mp3", "m4a"],
+                                value="flac",
+                                interactive=True,
+                            )
+                        model_select.change(
+                                fn=update_model_choices,
+                                inputs=model_select,
+                                outputs=model_choose,
+                                )
+                        but2 = gr.Button(i18n("Convert"), variant="primary")
+                        vc_output4 = gr.Textbox(label=i18n("Output information:"))
+                        #wav_inputs.upload(fn=save_to_wav2_edited, inputs=[wav_inputs], outputs=[])
+                        but2.click(
+                            uvr,
+                            [
+                                model_choose,
+                                dir_wav_input,
+                                opt_vocal_root,
+                                wav_inputs,
+                                opt_ins_root,
+                                agg,
+                                format0,
+                                model_select
+                            ],
+                            [vc_output4],
+                        )    
+            with gr.TabItem(i18n("TTS")):
+                with gr.Group():
+                    with gr.Column():
+                        text_test = gr.Textbox(label=i18n("Text:"), placeholder=i18n("Enter the text you want to convert to voice..."), lines=6)      
+                            
+                with gr.Group():
+                    with gr.Row(): 
+                        with gr.Column(): 
+                             tts_methods_voice = ["Edge-tts", "Bark-tts"]
+                             ttsmethod_test = gr.Dropdown(tts_methods_voice, value='Edge-tts', label = i18n('TTS Method:'), visible=True)    
+                             tts_test = gr.Dropdown(set_edge_voice, label = i18n('TTS Model:'), visible=True)
+                             ttsmethod_test.change(
+                            fn=update_tts_methods_voice,
+                            inputs=ttsmethod_test,
+                            outputs=tts_test,
+                            )
+
+                        with gr.Column():
+                             model_voice_path07 = gr.Dropdown(label=i18n('RVC Model:'), choices=sorted(names), value=default_weight)
+                             best_match_index_path1 = match_index(model_voice_path07.value)    
+                             
+                             file_index2_07 = gr.Dropdown(
+                                  label=i18n('Select the .index file:'),
+                                  choices=get_indexes(),
+                                  value=best_match_index_path1,
+                                  interactive=True,
+                                  allow_custom_value=True,
+                                )
+                             #transpose_test = gr.Number(label = i18n('Transpose (integer, number Fof semitones, raise by an octave: 12, lower by an octave: -12):'), value=0, visible=True, interactive= True)
+              
+                        
+                                   
+                
+                with gr.Row():
+                        refresh_button_ = gr.Button(i18n("Refresh"), variant="primary")
+                        refresh_button_.click(fn=change_choices2, inputs=[], outputs=[model_voice_path07, file_index2_07]) 
+                with gr.Row():
+                            original_ttsvoice = gr.Audio(label=i18n('Audio TTS:'))
+                            ttsvoice = gr.Audio(label=i18n('Audio RVC:'))
+
+                with gr.Row():
+                        button_test = gr.Button(i18n("Convert"), variant="primary")
+                       
+
+                button_test.click(make_test, inputs=[
+                                text_test,
+                                tts_test,
+                                model_voice_path07,
+                                file_index2_07,
+                                #transpose_test,
+                                vc_transform0,
+                                f0method8,
+                                index_rate1,
+                                crepe_hop_length,
+                                f0_autotune,
+                                ttsmethod_test
+                                ], outputs=[ttsvoice, original_ttsvoice])
+            
+            with gr.TabItem(i18n("Resources")):
+                easy_infer.download_model()
+                easy_infer.download_backup()
+                easy_infer.download_dataset(trainset_dir4)
+                easy_infer.download_audio()
+                easy_infer.youtube_separator()
+            with gr.TabItem(i18n("Extra")):
+                gr.Markdown(
+                            value=i18n("This section contains some extra utilities that often may be in experimental phases")
+                )
+                with gr.TabItem(i18n("Merge Audios")):
+                    with gr.Group(): 
+                        gr.Markdown(
+                            value="## " + i18n("Merge your generated audios with the instrumental")
+                        )
+                        gr.Markdown(value="",scale="-0.5",visible=True)
+                        gr.Markdown(value="",scale="-0.5",visible=True)
+                        with gr.Row():
+                            with gr.Column():
+                                dropbox = gr.File(label=i18n("Drag your audio here:"))
+                                gr.Markdown(value=i18n("### Instrumental settings:"))
+                                input_audio1 = gr.Dropdown(
+                                    label=i18n("Choose your instrumental:"),
+                                    choices=sorted(audio_others_paths),
+                                    value='',
+                                    interactive=True,
+                                )
+                                input_audio1_scale = gr.Slider(
+                                    minimum=0,
+                                    maximum=10,
+                                    label=i18n("Volume of the instrumental audio:"),
+                                    value=1.00,
+                                    interactive=True,
+                                )
+                                gr.Markdown(value=i18n("### Audio settings:"))
+                                input_audio3 = gr.Dropdown(
+                                    label=i18n("Select the generated audio"),
+                                    choices=sorted(audio_paths),
+                                    value='',
+                                    interactive=True,
+                                )
+                                with gr.Row():
+                                    input_audio3_scale = gr.Slider(
+                                        minimum=0,
+                                        maximum=10,
+                                        label=i18n("Volume of the generated audio:"),
+                                        value=1.00,
+                                        interactive=True,
+                                    )
+
+                                gr.Markdown(value=i18n("### Add the effects:"))
+                                reverb_ = gr.Checkbox(
+                                label=i18n("Reverb"),
+                                value=False,
+                                interactive=True,
+                                )
+                                compressor_ = gr.Checkbox(
+                                label=i18n("Compressor"),
+                                value=False,
+                                interactive=True,
+                                )
+                                noise_gate_ = gr.Checkbox(
+                                label=i18n("Noise Gate"),
+                                value=False,
+                                interactive=True,
+                                )
+
+                                butnone = gr.Button(i18n("Merge"), variant="primary").style(full_width=True)
+                                
+                                vc_output1 = gr.Textbox(label=i18n("Output information:"))
+                                vc_output2 = gr.Audio(label=i18n("Export audio (click on the three dots in the lower right corner to download)"), type='filepath')
+                                
+                                dropbox.upload(fn=save_to_wav2, inputs=[dropbox], outputs=[input_audio1])
+                                dropbox.upload(fn=easy_infer.change_choices2, inputs=[], outputs=[input_audio1])
+
+                                refresh_button.click(
+                                    fn=lambda: change_choices3(),
+                                    inputs=[],
+                                    outputs=[input_audio1, input_audio3],
+                                )
+                                
+                                butnone.click(
+                                    fn=audio_combined,
+                                    inputs=[input_audio1, input_audio3,input_audio1_scale,input_audio3_scale,reverb_,compressor_,noise_gate_], 
+                                    outputs=[vc_output1, vc_output2]
+                                    )
+                                    
+                        
+                with gr.TabItem(i18n("Processing")):
+                    with gr.Group():
+                      
+                        with gr.Accordion(label=i18n("Model fusion, can be used to test timbre fusion")):
+                            with gr.Row():
+                                with gr.Column():
+                                    name_to_save0 = gr.Textbox(
+                                        label=i18n("Name:"),
+                                        value="",
+                                        max_lines=1,
+                                        interactive=True,
+                                        placeholder=i18n("Name for saving")
+                                    )
+                                    alpha_a = gr.Slider(
+                                        minimum=0,
+                                        maximum=1,
+                                        label=i18n("Weight for Model A:"),
+                                        value=0.5,
+                                        interactive=True,
+                                    )
+                                    if_f0_ = gr.Checkbox(
+                                    label=i18n("Whether the model has pitch guidance."),
+                                    value=True,
+                                    interactive=True,
+                                    )
+                                    version_2 = gr.Radio(
+                                    label=i18n("Model architecture version:"),
+                                    choices=["v1", "v2"],
+                                    value="v2",
+                                    interactive=True,
+                                )
+                                    sr_ = gr.Radio(
+                                    label=i18n("Target sample rate:"),
+                                    choices=["40k", "48k"],
+                                    value="40k",
+                                    interactive=True,
+                                )
+                                
+                
+                                with gr.Column():
+                                    ckpt_a = gr.Textbox(label=i18n("Path to Model A:"), value="", interactive=True, placeholder=i18n("Path to model"))
+                                
+                                    ckpt_b = gr.Textbox(label=i18n("Path to Model B:"), value="", interactive=True, placeholder=i18n("Path to model"))
+                                
+                                    info__ = gr.Textbox(
+                                        label=i18n("Model information to be placed:"), value="", max_lines=8, interactive=True, placeholder=i18n("Model information to be placed")
+                                    )
+                                    info4 = gr.Textbox(label=i18n("Output information:"), value="", max_lines=8)                               
+                                
+                           
+                            but6 = gr.Button(i18n("Fusion"), variant="primary")
+                                
+                            but6.click(
+                                merge,
+                                [
+                                    ckpt_a,
+                                    ckpt_b,
+                                    alpha_a,
+                                    sr_,
+                                    if_f0_,
+                                    info__,
+                                    name_to_save0,
+                                    version_2,
+                                ],
+                                info4,
+                            )  # def merge(path1,path2,alpha1,sr,f0,info):
+                    with gr.Group():
+                        with gr.Accordion(label=i18n("Modify model information")):
+                            with gr.Row(): ######
+                                with gr.Column():
+                                    ckpt_path0 = gr.Textbox(
+                                        label=i18n("Path to Model:"), value="", interactive=True, placeholder=i18n("Path to model")
+                                    )
+                                    info_ = gr.Textbox(
+                                        label=i18n("Model information to be modified:"), value="", max_lines=8, interactive=True,  placeholder=i18n("Model information to be placed")
+                                    )
+                                
+                                with gr.Column():
+                                    name_to_save1 = gr.Textbox(
+                                        label=i18n("Save file name:"),
+                                        placeholder=i18n("Name for saving"),
+                                        value="",
+                                        max_lines=8,
+                                        interactive=True,
+                                        
+                                    )
+                                    
+                                    info5 = gr.Textbox(label=i18n("Output information:"), value="", max_lines=8)
+                            but7 = gr.Button(i18n("Modify"), variant="primary")        
+                            but7.click(change_info, [ckpt_path0, info_, name_to_save1], info5)
+                    with gr.Group():
+                        with gr.Accordion(label=i18n("View model information")):
+                            with gr.Row():
+                                with gr.Column():
+                                    ckpt_path1 = gr.Textbox(
+                                        label=i18n("Path to Model:"), value="", interactive=True, placeholder=i18n("Path to model")
+                                    )
+                                    
+                                    info6 = gr.Textbox(label=i18n("Output information:"), value="", max_lines=8)
+                                    but8 = gr.Button(i18n("View"), variant="primary")
+                            but8.click(show_info, [ckpt_path1], info6)
+                    with gr.Group():
+                        with gr.Accordion(label=i18n("Model extraction")):
+                            with gr.Row():
+                               with gr.Column():
+                                       save_name = gr.Textbox(
+                                        label=i18n("Name:"), value="", interactive=True, placeholder=i18n("Name for saving")
+                                    )
+                                       if_f0__ = gr.Checkbox(
+                                            label=i18n("Whether the model has pitch guidance."),
+                                            value=True,
+                                            interactive=True,
+                                        )
+                                       version_1 = gr.Radio(
+                                            label=i18n("Model architecture version:"),
+                                            choices=["v1", "v2"],
+                                            value="v2",
+                                            interactive=True,
+                                        )
+                                       sr__ = gr.Radio(
+                                            label=i18n("Target sample rate:"),
+                                            choices=["32k", "40k", "48k"],
+                                            value="40k",
+                                            interactive=True,
+                                        )
+                                   
+                               with gr.Column():    
+                                      ckpt_path2 = gr.Textbox(
+                                       
+                                        label=i18n("Path to Model:"),
+                                        placeholder=i18n("Path to model"),
+                                        interactive=True,
+                                    )
+                                      info___ = gr.Textbox(
+                                        label=i18n("Model information to be placed:"), value="", max_lines=8, interactive=True, placeholder=i18n("Model information to be placed")
+                                    )
+                                      info7 = gr.Textbox(label=i18n("Output information:"), value="", max_lines=8)   
+                    
+                            with gr.Row():
+                                    
+                                    but9 = gr.Button(i18n("Extract"), variant="primary")
+                                    ckpt_path2.change(
+                                        change_info_, [ckpt_path2], [sr__, if_f0__, version_1]
+                                    )
+                            but9.click(
+                                extract_small_model,
+                                [ckpt_path2, save_name, sr__, if_f0__, info___, version_1],
+                                info7,
+                            )
+
+                
+                            
+        
+            with gr.TabItem(i18n("Settings")):
+                with gr.Row():
+                    gr.Markdown(value=
+                                i18n("Pitch settings")
+                                )
+                    noteshertz = gr.Checkbox(
+                        label       = i18n("Whether to use note names instead of their hertz value. E.G. [C5, D6] instead of [523.25, 1174.66]Hz"),
+                        value       = rvc_globals.NotesOrHertz,
+                        interactive = True,
+                    )
+            
+            noteshertz.change(fn=lambda nhertz: rvc_globals.__setattr__('NotesOrHertz', nhertz), inputs=[noteshertz], outputs=[])
+
+            noteshertz.change(
+                fn=switch_pitch_controls,
+                inputs=[f0method0],
+                outputs=[
+                    minpitch_slider, minpitch_txtbox,
+                    maxpitch_slider, maxpitch_txtbox,]
+            )
+        return app
+
+def GradioRun(app):
+    share_gradio_link = config.iscolab or config.paperspace
+    concurrency_count = 511
+    max_size = 1022
+
+    if (
+        config.iscolab or config.paperspace
+    ):  
+        app.queue(concurrency_count=concurrency_count, max_size=max_size).launch(
+        server_name="0.0.0.0",
+        inbrowser=not config.noautoopen,
+        server_port=config.listen_port,
+        quiet=True,
+        favicon_path="./images/icon.png",
+        share=share_gradio_link,
+        )
+    else:
+        app.queue(concurrency_count=concurrency_count, max_size=max_size).launch(
+        server_name="0.0.0.0",
+        inbrowser=not config.noautoopen,
+        server_port=config.listen_port,
+        quiet=True,
+        favicon_path=".\images\icon.png",
+        share=share_gradio_link,
+        )
+
+if __name__ == "__main__":
+    if os.name == 'nt': 
+        print(i18n("Any ConnectionResetErrors post-conversion are irrelevant and purely visual; they can be ignored.\n"))
+    app = GradioSetup(UTheme=config.grtheme)
+    GradioRun(app)
\ No newline at end of file
diff --git a/infer/lib/audio.py b/infer/lib/audio.py
new file mode 100644
index 0000000000000000000000000000000000000000..9ad4ff74218957cf18782fa71add40a734b47e78
--- /dev/null
+++ b/infer/lib/audio.py
@@ -0,0 +1,197 @@
+import librosa
+import numpy as np
+import av
+from io import BytesIO
+import ffmpeg
+import os
+import sys
+
+import random
+from infer.lib.csvutil import CSVutil
+#import csv
+
+platform_stft_mapping = {
+    'linux': 'stftpitchshift',
+    'darwin': 'stftpitchshift',
+    'win32': 'stftpitchshift.exe',
+}
+
+stft = platform_stft_mapping.get(sys.platform)
+
+def wav2(i, o, format):
+    inp = av.open(i, 'rb')
+    if format == "m4a": format = "mp4"
+    out = av.open(o, 'wb', format=format)
+    if format == "ogg": format = "libvorbis"
+    if format == "mp4": format = "aac"
+
+    ostream = out.add_stream(format)
+
+    for frame in inp.decode(audio=0):
+        for p in ostream.encode(frame): out.mux(p)
+
+    for p in ostream.encode(None): out.mux(p)
+
+    out.close()
+    inp.close()
+
+def audio2(i, o, format, sr):
+    inp = av.open(i, 'rb')
+    out = av.open(o, 'wb', format=format)
+    if format == "ogg": format = "libvorbis"
+    if format == "f32le": format = "pcm_f32le"
+
+    ostream = out.add_stream(format, channels=1)
+    ostream.sample_rate = sr
+
+    for frame in inp.decode(audio=0):
+        for p in ostream.encode(frame): out.mux(p)
+
+    out.close()
+    inp.close()
+
+def load_audion(file, sr):
+    try:
+        file = (
+            file.strip(" ").strip('"').strip("\n").strip('"').strip(" ")
+        )  # 防止小白拷路径头尾带了空格和"和回车
+        with open(file, "rb") as f:
+            with BytesIO() as out:
+                audio2(f, out, "f32le", sr)
+                return np.frombuffer(out.getvalue(), np.float32).flatten()
+
+    except AttributeError:
+        audio = file[1] / 32768.0
+        if len(audio.shape) == 2:
+            audio = np.mean(audio, -1)
+        return librosa.resample(audio, orig_sr=file[0], target_sr=16000)
+
+    except Exception as e:
+        raise RuntimeError(f"Failed to load audio: {e}")
+
+
+
+
+def load_audio(file, sr, DoFormant=False, Quefrency=1.0, Timbre=1.0):
+    converted = False
+    DoFormant, Quefrency, Timbre = CSVutil("csvdb/formanting.csv", "r", "formanting")
+    try:
+        # https://github.com/openai/whisper/blob/main/whisper/audio.py#L26
+        # This launches a subprocess to decode audio while down-mixing and resampling as necessary.
+        # Requires the ffmpeg CLI and `ffmpeg-python` package to be installed.
+        file = (
+            file.strip(" ").strip('"').strip("\n").strip('"').strip(" ")
+        )  # 防止小白拷路径头尾带了空格和"和回车
+        file_formanted = file.strip(" ").strip('"').strip("\n").strip('"').strip(" ")
+
+        # print(f"dofor={bool(DoFormant)} timbr={Timbre} quef={Quefrency}\n")
+
+        if (
+            lambda DoFormant: True
+            if DoFormant.lower() == "true"
+            else (False if DoFormant.lower() == "false" else DoFormant)
+        )(DoFormant):
+            numerator = round(random.uniform(1, 4), 4)
+            # os.system(f"stftpitchshift -i {file} -q {Quefrency} -t {Timbre} -o {file_formanted}")
+            # print('stftpitchshift -i "%s" -p 1.0 --rms -w 128 -v 8 -q %s -t %s -o "%s"' % (file, Quefrency, Timbre, file_formanted))
+
+            if not file.endswith(".wav"):
+                if not os.path.isfile(f"{file_formanted}.wav"):
+                    converted = True
+                    # print(f"\nfile = {file}\n")
+                    # print(f"\nfile_formanted = {file_formanted}\n")
+                    converting = (
+                        ffmpeg.input(file_formanted, threads=0)
+                        .output(f"{file_formanted}.wav")
+                        .run(
+                            cmd=["ffmpeg", "-nostdin"],
+                            capture_stdout=True,
+                            capture_stderr=True,
+                        )
+                    )
+                else:
+                    pass
+
+            file_formanted = (
+                f"{file_formanted}.wav"
+                if not file_formanted.endswith(".wav")
+                else file_formanted
+            )
+
+            print(f" · Formanting {file_formanted}...\n")
+
+            os.system(
+                '%s -i "%s" -q "%s" -t "%s" -o "%sFORMANTED_%s.wav"'
+                % (
+                    stft,
+                    file_formanted,
+                    Quefrency,
+                    Timbre,
+                    file_formanted,
+                    str(numerator),
+                )
+            )
+
+            print(f" · Formanted {file_formanted}!\n")
+
+            # filepraat = (os.path.abspath(os.getcwd()) + '\\' + file).replace('/','\\')
+            # file_formantedpraat = ('"' + os.path.abspath(os.getcwd()) + '/' + 'formanted'.join(file_formanted) + '"').replace('/','\\')
+            # print("%sFORMANTED_%s.wav" % (file_formanted, str(numerator)))
+
+            out, _ = (
+                ffmpeg.input(
+                    "%sFORMANTED_%s.wav" % (file_formanted, str(numerator)), threads=0
+                )
+                .output("-", format="f32le", acodec="pcm_f32le", ac=1, ar=sr)
+                .run(
+                    cmd=["ffmpeg", "-nostdin"], capture_stdout=True, capture_stderr=True
+                )
+            )
+
+            try:
+                os.remove("%sFORMANTED_%s.wav" % (file_formanted, str(numerator)))
+            except Exception:
+                pass
+                print("couldn't remove formanted type of file")
+
+        else:
+            out, _ = (
+                ffmpeg.input(file, threads=0)
+                .output("-", format="f32le", acodec="pcm_f32le", ac=1, ar=sr)
+                .run(
+                    cmd=["ffmpeg", "-nostdin"], capture_stdout=True, capture_stderr=True
+                )
+            )
+    except Exception as e:
+        raise RuntimeError(f"Failed to load audio: {e}")
+
+    if converted:
+        try:
+            os.remove(file_formanted)
+        except Exception:
+            pass
+            print("couldn't remove converted type of file")
+        converted = False
+
+    return np.frombuffer(out, np.float32).flatten()
+
+
+def check_audio_duration(file):
+    try:
+        file = file.strip(" ").strip('"').strip("\n").strip('"').strip(" ")
+
+        probe = ffmpeg.probe(file)
+
+        duration = float(probe['streams'][0]['duration'])
+
+        if duration < 0.76:
+            print(
+                f"\n------------\n"
+                f"Audio file, {file.split('/')[-1]}, under ~0.76s detected - file is too short. Target at least 1-2s for best results."
+                f"\n------------\n\n"
+            )
+            return False
+
+        return True
+    except Exception as e:
+        raise RuntimeError(f"Failed to check audio duration: {e}")
\ No newline at end of file
diff --git a/infer/lib/csvutil.py b/infer/lib/csvutil.py
new file mode 100644
index 0000000000000000000000000000000000000000..79f432b6933f181d9194c50581656f2fd6e66c0c
--- /dev/null
+++ b/infer/lib/csvutil.py
@@ -0,0 +1,41 @@
+
+import numpy as np
+
+# import praatio
+# import praatio.praat_scripts
+import os
+import sys
+
+import random
+
+import csv
+
+# praatEXE = join('.',os.path.abspath(os.getcwd()) + r"\Praat.exe")
+
+
+def CSVutil(file, rw, type, *args):
+    if type == "formanting":
+        if rw == "r":
+            with open(file) as fileCSVread:
+                csv_reader = list(csv.reader(fileCSVread))
+                return (
+                    (csv_reader[0][0], csv_reader[0][1], csv_reader[0][2])
+                    if csv_reader is not None
+                    else (lambda: exec('raise ValueError("No data")'))()
+                )
+        else:
+            if args:
+                doformnt = args[0]
+            else:
+                doformnt = False
+            qfr = args[1] if len(args) > 1 else 1.0
+            tmb = args[2] if len(args) > 2 else 1.0
+            with open(file, rw, newline="") as fileCSVwrite:
+                csv_writer = csv.writer(fileCSVwrite, delimiter=",")
+                csv_writer.writerow([doformnt, qfr, tmb])
+    elif type == "stop":
+        stop = args[0] if args else False
+        with open(file, rw, newline="") as fileCSVwrite:
+            csv_writer = csv.writer(fileCSVwrite, delimiter=",")
+            csv_writer.writerow([stop])
+
diff --git a/infer/lib/infer_pack/attentions.py b/infer/lib/infer_pack/attentions.py
new file mode 100644
index 0000000000000000000000000000000000000000..19a0a670021aacb9ae1c7f8f54ca1bff8e065375
--- /dev/null
+++ b/infer/lib/infer_pack/attentions.py
@@ -0,0 +1,417 @@
+import copy
+import math
+
+import numpy as np
+import torch
+from torch import nn
+from torch.nn import functional as F
+
+from infer.lib.infer_pack import commons, modules
+from infer.lib.infer_pack.modules import LayerNorm
+
+
+class Encoder(nn.Module):
+    def __init__(
+        self,
+        hidden_channels,
+        filter_channels,
+        n_heads,
+        n_layers,
+        kernel_size=1,
+        p_dropout=0.0,
+        window_size=10,
+        **kwargs
+    ):
+        super().__init__()
+        self.hidden_channels = hidden_channels
+        self.filter_channels = filter_channels
+        self.n_heads = n_heads
+        self.n_layers = n_layers
+        self.kernel_size = kernel_size
+        self.p_dropout = p_dropout
+        self.window_size = window_size
+
+        self.drop = nn.Dropout(p_dropout)
+        self.attn_layers = nn.ModuleList()
+        self.norm_layers_1 = nn.ModuleList()
+        self.ffn_layers = nn.ModuleList()
+        self.norm_layers_2 = nn.ModuleList()
+        for i in range(self.n_layers):
+            self.attn_layers.append(
+                MultiHeadAttention(
+                    hidden_channels,
+                    hidden_channels,
+                    n_heads,
+                    p_dropout=p_dropout,
+                    window_size=window_size,
+                )
+            )
+            self.norm_layers_1.append(LayerNorm(hidden_channels))
+            self.ffn_layers.append(
+                FFN(
+                    hidden_channels,
+                    hidden_channels,
+                    filter_channels,
+                    kernel_size,
+                    p_dropout=p_dropout,
+                )
+            )
+            self.norm_layers_2.append(LayerNorm(hidden_channels))
+
+    def forward(self, x, x_mask):
+        attn_mask = x_mask.unsqueeze(2) * x_mask.unsqueeze(-1)
+        x = x * x_mask
+        for i in range(self.n_layers):
+            y = self.attn_layers[i](x, x, attn_mask)
+            y = self.drop(y)
+            x = self.norm_layers_1[i](x + y)
+
+            y = self.ffn_layers[i](x, x_mask)
+            y = self.drop(y)
+            x = self.norm_layers_2[i](x + y)
+        x = x * x_mask
+        return x
+
+
+class Decoder(nn.Module):
+    def __init__(
+        self,
+        hidden_channels,
+        filter_channels,
+        n_heads,
+        n_layers,
+        kernel_size=1,
+        p_dropout=0.0,
+        proximal_bias=False,
+        proximal_init=True,
+        **kwargs
+    ):
+        super().__init__()
+        self.hidden_channels = hidden_channels
+        self.filter_channels = filter_channels
+        self.n_heads = n_heads
+        self.n_layers = n_layers
+        self.kernel_size = kernel_size
+        self.p_dropout = p_dropout
+        self.proximal_bias = proximal_bias
+        self.proximal_init = proximal_init
+
+        self.drop = nn.Dropout(p_dropout)
+        self.self_attn_layers = nn.ModuleList()
+        self.norm_layers_0 = nn.ModuleList()
+        self.encdec_attn_layers = nn.ModuleList()
+        self.norm_layers_1 = nn.ModuleList()
+        self.ffn_layers = nn.ModuleList()
+        self.norm_layers_2 = nn.ModuleList()
+        for i in range(self.n_layers):
+            self.self_attn_layers.append(
+                MultiHeadAttention(
+                    hidden_channels,
+                    hidden_channels,
+                    n_heads,
+                    p_dropout=p_dropout,
+                    proximal_bias=proximal_bias,
+                    proximal_init=proximal_init,
+                )
+            )
+            self.norm_layers_0.append(LayerNorm(hidden_channels))
+            self.encdec_attn_layers.append(
+                MultiHeadAttention(
+                    hidden_channels, hidden_channels, n_heads, p_dropout=p_dropout
+                )
+            )
+            self.norm_layers_1.append(LayerNorm(hidden_channels))
+            self.ffn_layers.append(
+                FFN(
+                    hidden_channels,
+                    hidden_channels,
+                    filter_channels,
+                    kernel_size,
+                    p_dropout=p_dropout,
+                    causal=True,
+                )
+            )
+            self.norm_layers_2.append(LayerNorm(hidden_channels))
+
+    def forward(self, x, x_mask, h, h_mask):
+        """
+        x: decoder input
+        h: encoder output
+        """
+        self_attn_mask = commons.subsequent_mask(x_mask.size(2)).to(
+            device=x.device, dtype=x.dtype
+        )
+        encdec_attn_mask = h_mask.unsqueeze(2) * x_mask.unsqueeze(-1)
+        x = x * x_mask
+        for i in range(self.n_layers):
+            y = self.self_attn_layers[i](x, x, self_attn_mask)
+            y = self.drop(y)
+            x = self.norm_layers_0[i](x + y)
+
+            y = self.encdec_attn_layers[i](x, h, encdec_attn_mask)
+            y = self.drop(y)
+            x = self.norm_layers_1[i](x + y)
+
+            y = self.ffn_layers[i](x, x_mask)
+            y = self.drop(y)
+            x = self.norm_layers_2[i](x + y)
+        x = x * x_mask
+        return x
+
+
+class MultiHeadAttention(nn.Module):
+    def __init__(
+        self,
+        channels,
+        out_channels,
+        n_heads,
+        p_dropout=0.0,
+        window_size=None,
+        heads_share=True,
+        block_length=None,
+        proximal_bias=False,
+        proximal_init=False,
+    ):
+        super().__init__()
+        assert channels % n_heads == 0
+
+        self.channels = channels
+        self.out_channels = out_channels
+        self.n_heads = n_heads
+        self.p_dropout = p_dropout
+        self.window_size = window_size
+        self.heads_share = heads_share
+        self.block_length = block_length
+        self.proximal_bias = proximal_bias
+        self.proximal_init = proximal_init
+        self.attn = None
+
+        self.k_channels = channels // n_heads
+        self.conv_q = nn.Conv1d(channels, channels, 1)
+        self.conv_k = nn.Conv1d(channels, channels, 1)
+        self.conv_v = nn.Conv1d(channels, channels, 1)
+        self.conv_o = nn.Conv1d(channels, out_channels, 1)
+        self.drop = nn.Dropout(p_dropout)
+
+        if window_size is not None:
+            n_heads_rel = 1 if heads_share else n_heads
+            rel_stddev = self.k_channels**-0.5
+            self.emb_rel_k = nn.Parameter(
+                torch.randn(n_heads_rel, window_size * 2 + 1, self.k_channels)
+                * rel_stddev
+            )
+            self.emb_rel_v = nn.Parameter(
+                torch.randn(n_heads_rel, window_size * 2 + 1, self.k_channels)
+                * rel_stddev
+            )
+
+        nn.init.xavier_uniform_(self.conv_q.weight)
+        nn.init.xavier_uniform_(self.conv_k.weight)
+        nn.init.xavier_uniform_(self.conv_v.weight)
+        if proximal_init:
+            with torch.no_grad():
+                self.conv_k.weight.copy_(self.conv_q.weight)
+                self.conv_k.bias.copy_(self.conv_q.bias)
+
+    def forward(self, x, c, attn_mask=None):
+        q = self.conv_q(x)
+        k = self.conv_k(c)
+        v = self.conv_v(c)
+
+        x, self.attn = self.attention(q, k, v, mask=attn_mask)
+
+        x = self.conv_o(x)
+        return x
+
+    def attention(self, query, key, value, mask=None):
+        # reshape [b, d, t] -> [b, n_h, t, d_k]
+        b, d, t_s, t_t = (*key.size(), query.size(2))
+        query = query.view(b, self.n_heads, self.k_channels, t_t).transpose(2, 3)
+        key = key.view(b, self.n_heads, self.k_channels, t_s).transpose(2, 3)
+        value = value.view(b, self.n_heads, self.k_channels, t_s).transpose(2, 3)
+
+        scores = torch.matmul(query / math.sqrt(self.k_channels), key.transpose(-2, -1))
+        if self.window_size is not None:
+            assert (
+                t_s == t_t
+            ), "Relative attention is only available for self-attention."
+            key_relative_embeddings = self._get_relative_embeddings(self.emb_rel_k, t_s)
+            rel_logits = self._matmul_with_relative_keys(
+                query / math.sqrt(self.k_channels), key_relative_embeddings
+            )
+            scores_local = self._relative_position_to_absolute_position(rel_logits)
+            scores = scores + scores_local
+        if self.proximal_bias:
+            assert t_s == t_t, "Proximal bias is only available for self-attention."
+            scores = scores + self._attention_bias_proximal(t_s).to(
+                device=scores.device, dtype=scores.dtype
+            )
+        if mask is not None:
+            scores = scores.masked_fill(mask == 0, -1e4)
+            if self.block_length is not None:
+                assert (
+                    t_s == t_t
+                ), "Local attention is only available for self-attention."
+                block_mask = (
+                    torch.ones_like(scores)
+                    .triu(-self.block_length)
+                    .tril(self.block_length)
+                )
+                scores = scores.masked_fill(block_mask == 0, -1e4)
+        p_attn = F.softmax(scores, dim=-1)  # [b, n_h, t_t, t_s]
+        p_attn = self.drop(p_attn)
+        output = torch.matmul(p_attn, value)
+        if self.window_size is not None:
+            relative_weights = self._absolute_position_to_relative_position(p_attn)
+            value_relative_embeddings = self._get_relative_embeddings(
+                self.emb_rel_v, t_s
+            )
+            output = output + self._matmul_with_relative_values(
+                relative_weights, value_relative_embeddings
+            )
+        output = (
+            output.transpose(2, 3).contiguous().view(b, d, t_t)
+        )  # [b, n_h, t_t, d_k] -> [b, d, t_t]
+        return output, p_attn
+
+    def _matmul_with_relative_values(self, x, y):
+        """
+        x: [b, h, l, m]
+        y: [h or 1, m, d]
+        ret: [b, h, l, d]
+        """
+        ret = torch.matmul(x, y.unsqueeze(0))
+        return ret
+
+    def _matmul_with_relative_keys(self, x, y):
+        """
+        x: [b, h, l, d]
+        y: [h or 1, m, d]
+        ret: [b, h, l, m]
+        """
+        ret = torch.matmul(x, y.unsqueeze(0).transpose(-2, -1))
+        return ret
+
+    def _get_relative_embeddings(self, relative_embeddings, length):
+        max_relative_position = 2 * self.window_size + 1
+        # Pad first before slice to avoid using cond ops.
+        pad_length = max(length - (self.window_size + 1), 0)
+        slice_start_position = max((self.window_size + 1) - length, 0)
+        slice_end_position = slice_start_position + 2 * length - 1
+        if pad_length > 0:
+            padded_relative_embeddings = F.pad(
+                relative_embeddings,
+                commons.convert_pad_shape([[0, 0], [pad_length, pad_length], [0, 0]]),
+            )
+        else:
+            padded_relative_embeddings = relative_embeddings
+        used_relative_embeddings = padded_relative_embeddings[
+            :, slice_start_position:slice_end_position
+        ]
+        return used_relative_embeddings
+
+    def _relative_position_to_absolute_position(self, x):
+        """
+        x: [b, h, l, 2*l-1]
+        ret: [b, h, l, l]
+        """
+        batch, heads, length, _ = x.size()
+        # Concat columns of pad to shift from relative to absolute indexing.
+        x = F.pad(x, commons.convert_pad_shape([[0, 0], [0, 0], [0, 0], [0, 1]]))
+
+        # Concat extra elements so to add up to shape (len+1, 2*len-1).
+        x_flat = x.view([batch, heads, length * 2 * length])
+        x_flat = F.pad(
+            x_flat, commons.convert_pad_shape([[0, 0], [0, 0], [0, length - 1]])
+        )
+
+        # Reshape and slice out the padded elements.
+        x_final = x_flat.view([batch, heads, length + 1, 2 * length - 1])[
+            :, :, :length, length - 1 :
+        ]
+        return x_final
+
+    def _absolute_position_to_relative_position(self, x):
+        """
+        x: [b, h, l, l]
+        ret: [b, h, l, 2*l-1]
+        """
+        batch, heads, length, _ = x.size()
+        # padd along column
+        x = F.pad(
+            x, commons.convert_pad_shape([[0, 0], [0, 0], [0, 0], [0, length - 1]])
+        )
+        x_flat = x.view([batch, heads, length**2 + length * (length - 1)])
+        # add 0's in the beginning that will skew the elements after reshape
+        x_flat = F.pad(x_flat, commons.convert_pad_shape([[0, 0], [0, 0], [length, 0]]))
+        x_final = x_flat.view([batch, heads, length, 2 * length])[:, :, :, 1:]
+        return x_final
+
+    def _attention_bias_proximal(self, length):
+        """Bias for self-attention to encourage attention to close positions.
+        Args:
+          length: an integer scalar.
+        Returns:
+          a Tensor with shape [1, 1, length, length]
+        """
+        r = torch.arange(length, dtype=torch.float32)
+        diff = torch.unsqueeze(r, 0) - torch.unsqueeze(r, 1)
+        return torch.unsqueeze(torch.unsqueeze(-torch.log1p(torch.abs(diff)), 0), 0)
+
+
+class FFN(nn.Module):
+    def __init__(
+        self,
+        in_channels,
+        out_channels,
+        filter_channels,
+        kernel_size,
+        p_dropout=0.0,
+        activation=None,
+        causal=False,
+    ):
+        super().__init__()
+        self.in_channels = in_channels
+        self.out_channels = out_channels
+        self.filter_channels = filter_channels
+        self.kernel_size = kernel_size
+        self.p_dropout = p_dropout
+        self.activation = activation
+        self.causal = causal
+
+        if causal:
+            self.padding = self._causal_padding
+        else:
+            self.padding = self._same_padding
+
+        self.conv_1 = nn.Conv1d(in_channels, filter_channels, kernel_size)
+        self.conv_2 = nn.Conv1d(filter_channels, out_channels, kernel_size)
+        self.drop = nn.Dropout(p_dropout)
+
+    def forward(self, x, x_mask):
+        x = self.conv_1(self.padding(x * x_mask))
+        if self.activation == "gelu":
+            x = x * torch.sigmoid(1.702 * x)
+        else:
+            x = torch.relu(x)
+        x = self.drop(x)
+        x = self.conv_2(self.padding(x * x_mask))
+        return x * x_mask
+
+    def _causal_padding(self, x):
+        if self.kernel_size == 1:
+            return x
+        pad_l = self.kernel_size - 1
+        pad_r = 0
+        padding = [[0, 0], [0, 0], [pad_l, pad_r]]
+        x = F.pad(x, commons.convert_pad_shape(padding))
+        return x
+
+    def _same_padding(self, x):
+        if self.kernel_size == 1:
+            return x
+        pad_l = (self.kernel_size - 1) // 2
+        pad_r = self.kernel_size // 2
+        padding = [[0, 0], [0, 0], [pad_l, pad_r]]
+        x = F.pad(x, commons.convert_pad_shape(padding))
+        return x
diff --git a/infer/lib/infer_pack/commons.py b/infer/lib/infer_pack/commons.py
new file mode 100644
index 0000000000000000000000000000000000000000..ccd334b7320543b0c3a2166f82093564c9721317
--- /dev/null
+++ b/infer/lib/infer_pack/commons.py
@@ -0,0 +1,167 @@
+import math
+
+import numpy as np
+import torch
+from torch import nn
+from torch.nn import functional as F
+
+
+def init_weights(m, mean=0.0, std=0.01):
+    classname = m.__class__.__name__
+    if classname.find("Conv") != -1:
+        m.weight.data.normal_(mean, std)
+
+
+def get_padding(kernel_size, dilation=1):
+    return int((kernel_size * dilation - dilation) / 2)
+
+
+def convert_pad_shape(pad_shape):
+    l = pad_shape[::-1]
+    pad_shape = [item for sublist in l for item in sublist]
+    return pad_shape
+
+
+def kl_divergence(m_p, logs_p, m_q, logs_q):
+    """KL(P||Q)"""
+    kl = (logs_q - logs_p) - 0.5
+    kl += (
+        0.5 * (torch.exp(2.0 * logs_p) + ((m_p - m_q) ** 2)) * torch.exp(-2.0 * logs_q)
+    )
+    return kl
+
+
+def rand_gumbel(shape):
+    """Sample from the Gumbel distribution, protect from overflows."""
+    uniform_samples = torch.rand(shape) * 0.99998 + 0.00001
+    return -torch.log(-torch.log(uniform_samples))
+
+
+def rand_gumbel_like(x):
+    g = rand_gumbel(x.size()).to(dtype=x.dtype, device=x.device)
+    return g
+
+
+def slice_segments(x, ids_str, segment_size=4):
+    ret = torch.zeros_like(x[:, :, :segment_size])
+    for i in range(x.size(0)):
+        idx_str = ids_str[i]
+        idx_end = idx_str + segment_size
+        ret[i] = x[i, :, idx_str:idx_end]
+    return ret
+
+
+def slice_segments2(x, ids_str, segment_size=4):
+    ret = torch.zeros_like(x[:, :segment_size])
+    for i in range(x.size(0)):
+        idx_str = ids_str[i]
+        idx_end = idx_str + segment_size
+        ret[i] = x[i, idx_str:idx_end]
+    return ret
+
+
+def rand_slice_segments(x, x_lengths=None, segment_size=4):
+    b, d, t = x.size()
+    if x_lengths is None:
+        x_lengths = t
+    ids_str_max = x_lengths - segment_size + 1
+    ids_str = (torch.rand([b]).to(device=x.device) * ids_str_max).to(dtype=torch.long)
+    ret = slice_segments(x, ids_str, segment_size)
+    return ret, ids_str
+
+
+def get_timing_signal_1d(length, channels, min_timescale=1.0, max_timescale=1.0e4):
+    position = torch.arange(length, dtype=torch.float)
+    num_timescales = channels // 2
+    log_timescale_increment = math.log(float(max_timescale) / float(min_timescale)) / (
+        num_timescales - 1
+    )
+    inv_timescales = min_timescale * torch.exp(
+        torch.arange(num_timescales, dtype=torch.float) * -log_timescale_increment
+    )
+    scaled_time = position.unsqueeze(0) * inv_timescales.unsqueeze(1)
+    signal = torch.cat([torch.sin(scaled_time), torch.cos(scaled_time)], 0)
+    signal = F.pad(signal, [0, 0, 0, channels % 2])
+    signal = signal.view(1, channels, length)
+    return signal
+
+
+def add_timing_signal_1d(x, min_timescale=1.0, max_timescale=1.0e4):
+    b, channels, length = x.size()
+    signal = get_timing_signal_1d(length, channels, min_timescale, max_timescale)
+    return x + signal.to(dtype=x.dtype, device=x.device)
+
+
+def cat_timing_signal_1d(x, min_timescale=1.0, max_timescale=1.0e4, axis=1):
+    b, channels, length = x.size()
+    signal = get_timing_signal_1d(length, channels, min_timescale, max_timescale)
+    return torch.cat([x, signal.to(dtype=x.dtype, device=x.device)], axis)
+
+
+def subsequent_mask(length):
+    mask = torch.tril(torch.ones(length, length)).unsqueeze(0).unsqueeze(0)
+    return mask
+
+
+@torch.jit.script
+def fused_add_tanh_sigmoid_multiply(input_a, input_b, n_channels):
+    n_channels_int = n_channels[0]
+    in_act = input_a + input_b
+    t_act = torch.tanh(in_act[:, :n_channels_int, :])
+    s_act = torch.sigmoid(in_act[:, n_channels_int:, :])
+    acts = t_act * s_act
+    return acts
+
+
+def convert_pad_shape(pad_shape):
+    l = pad_shape[::-1]
+    pad_shape = [item for sublist in l for item in sublist]
+    return pad_shape
+
+
+def shift_1d(x):
+    x = F.pad(x, convert_pad_shape([[0, 0], [0, 0], [1, 0]]))[:, :, :-1]
+    return x
+
+
+def sequence_mask(length, max_length=None):
+    if max_length is None:
+        max_length = length.max()
+    x = torch.arange(max_length, dtype=length.dtype, device=length.device)
+    return x.unsqueeze(0) < length.unsqueeze(1)
+
+
+def generate_path(duration, mask):
+    """
+    duration: [b, 1, t_x]
+    mask: [b, 1, t_y, t_x]
+    """
+    device = duration.device
+
+    b, _, t_y, t_x = mask.shape
+    cum_duration = torch.cumsum(duration, -1)
+
+    cum_duration_flat = cum_duration.view(b * t_x)
+    path = sequence_mask(cum_duration_flat, t_y).to(mask.dtype)
+    path = path.view(b, t_x, t_y)
+    path = path - F.pad(path, convert_pad_shape([[0, 0], [1, 0], [0, 0]]))[:, :-1]
+    path = path.unsqueeze(1).transpose(2, 3) * mask
+    return path
+
+
+def clip_grad_value_(parameters, clip_value, norm_type=2):
+    if isinstance(parameters, torch.Tensor):
+        parameters = [parameters]
+    parameters = list(filter(lambda p: p.grad is not None, parameters))
+    norm_type = float(norm_type)
+    if clip_value is not None:
+        clip_value = float(clip_value)
+
+    total_norm = 0
+    for p in parameters:
+        param_norm = p.grad.data.norm(norm_type)
+        total_norm += param_norm.item() ** norm_type
+        if clip_value is not None:
+            p.grad.data.clamp_(min=-clip_value, max=clip_value)
+    total_norm = total_norm ** (1.0 / norm_type)
+    return total_norm
diff --git a/infer/lib/infer_pack/models.py b/infer/lib/infer_pack/models.py
new file mode 100644
index 0000000000000000000000000000000000000000..7a387b888f63ecd6f1f1bd3ed10aa2176a944d2c
--- /dev/null
+++ b/infer/lib/infer_pack/models.py
@@ -0,0 +1,1174 @@
+import math
+import logging
+
+logger = logging.getLogger(__name__)
+
+import numpy as np
+import torch
+from torch import nn
+from torch.nn import AvgPool1d, Conv1d, Conv2d, ConvTranspose1d
+from torch.nn import functional as F
+from torch.nn.utils import remove_weight_norm, spectral_norm, weight_norm
+
+from infer.lib.infer_pack import attentions, commons, modules
+from infer.lib.infer_pack.commons import get_padding, init_weights
+has_xpu = bool(hasattr(torch, "xpu") and torch.xpu.is_available())
+
+class TextEncoder256(nn.Module):
+    def __init__(
+        self,
+        out_channels,
+        hidden_channels,
+        filter_channels,
+        n_heads,
+        n_layers,
+        kernel_size,
+        p_dropout,
+        f0=True,
+    ):
+        super().__init__()
+        self.out_channels = out_channels
+        self.hidden_channels = hidden_channels
+        self.filter_channels = filter_channels
+        self.n_heads = n_heads
+        self.n_layers = n_layers
+        self.kernel_size = kernel_size
+        self.p_dropout = p_dropout
+        self.emb_phone = nn.Linear(256, hidden_channels)
+        self.lrelu = nn.LeakyReLU(0.1, inplace=True)
+        if f0 == True:
+            self.emb_pitch = nn.Embedding(256, hidden_channels)  # pitch 256
+        self.encoder = attentions.Encoder(
+            hidden_channels, filter_channels, n_heads, n_layers, kernel_size, p_dropout
+        )
+        self.proj = nn.Conv1d(hidden_channels, out_channels * 2, 1)
+
+    def forward(self, phone, pitch, lengths):
+        if pitch == None:
+            x = self.emb_phone(phone)
+        else:
+            x = self.emb_phone(phone) + self.emb_pitch(pitch)
+        x = x * math.sqrt(self.hidden_channels)  # [b, t, h]
+        x = self.lrelu(x)
+        x = torch.transpose(x, 1, -1)  # [b, h, t]
+        x_mask = torch.unsqueeze(commons.sequence_mask(lengths, x.size(2)), 1).to(
+            x.dtype
+        )
+        x = self.encoder(x * x_mask, x_mask)
+        stats = self.proj(x) * x_mask
+
+        m, logs = torch.split(stats, self.out_channels, dim=1)
+        return m, logs, x_mask
+
+
+class TextEncoder768(nn.Module):
+    def __init__(
+        self,
+        out_channels,
+        hidden_channels,
+        filter_channels,
+        n_heads,
+        n_layers,
+        kernel_size,
+        p_dropout,
+        f0=True,
+    ):
+        super().__init__()
+        self.out_channels = out_channels
+        self.hidden_channels = hidden_channels
+        self.filter_channels = filter_channels
+        self.n_heads = n_heads
+        self.n_layers = n_layers
+        self.kernel_size = kernel_size
+        self.p_dropout = p_dropout
+        self.emb_phone = nn.Linear(768, hidden_channels)
+        self.lrelu = nn.LeakyReLU(0.1, inplace=True)
+        if f0 == True:
+            self.emb_pitch = nn.Embedding(256, hidden_channels)  # pitch 256
+        self.encoder = attentions.Encoder(
+            hidden_channels, filter_channels, n_heads, n_layers, kernel_size, p_dropout
+        )
+        self.proj = nn.Conv1d(hidden_channels, out_channels * 2, 1)
+
+    def forward(self, phone, pitch, lengths):
+        if pitch == None:
+            x = self.emb_phone(phone)
+        else:
+            x = self.emb_phone(phone) + self.emb_pitch(pitch)
+        x = x * math.sqrt(self.hidden_channels)  # [b, t, h]
+        x = self.lrelu(x)
+        x = torch.transpose(x, 1, -1)  # [b, h, t]
+        x_mask = torch.unsqueeze(commons.sequence_mask(lengths, x.size(2)), 1).to(
+            x.dtype
+        )
+        x = self.encoder(x * x_mask, x_mask)
+        stats = self.proj(x) * x_mask
+
+        m, logs = torch.split(stats, self.out_channels, dim=1)
+        return m, logs, x_mask
+
+
+class ResidualCouplingBlock(nn.Module):
+    def __init__(
+        self,
+        channels,
+        hidden_channels,
+        kernel_size,
+        dilation_rate,
+        n_layers,
+        n_flows=4,
+        gin_channels=0,
+    ):
+        super().__init__()
+        self.channels = channels
+        self.hidden_channels = hidden_channels
+        self.kernel_size = kernel_size
+        self.dilation_rate = dilation_rate
+        self.n_layers = n_layers
+        self.n_flows = n_flows
+        self.gin_channels = gin_channels
+
+        self.flows = nn.ModuleList()
+        for i in range(n_flows):
+            self.flows.append(
+                modules.ResidualCouplingLayer(
+                    channels,
+                    hidden_channels,
+                    kernel_size,
+                    dilation_rate,
+                    n_layers,
+                    gin_channels=gin_channels,
+                    mean_only=True,
+                )
+            )
+            self.flows.append(modules.Flip())
+
+    def forward(self, x, x_mask, g=None, reverse=False):
+        if not reverse:
+            for flow in self.flows:
+                x, _ = flow(x, x_mask, g=g, reverse=reverse)
+        else:
+            for flow in reversed(self.flows):
+                x = flow(x, x_mask, g=g, reverse=reverse)
+        return x
+
+    def remove_weight_norm(self):
+        for i in range(self.n_flows):
+            self.flows[i * 2].remove_weight_norm()
+
+
+class PosteriorEncoder(nn.Module):
+    def __init__(
+        self,
+        in_channels,
+        out_channels,
+        hidden_channels,
+        kernel_size,
+        dilation_rate,
+        n_layers,
+        gin_channels=0,
+    ):
+        super().__init__()
+        self.in_channels = in_channels
+        self.out_channels = out_channels
+        self.hidden_channels = hidden_channels
+        self.kernel_size = kernel_size
+        self.dilation_rate = dilation_rate
+        self.n_layers = n_layers
+        self.gin_channels = gin_channels
+
+        self.pre = nn.Conv1d(in_channels, hidden_channels, 1)
+        self.enc = modules.WN(
+            hidden_channels,
+            kernel_size,
+            dilation_rate,
+            n_layers,
+            gin_channels=gin_channels,
+        )
+        self.proj = nn.Conv1d(hidden_channels, out_channels * 2, 1)
+
+    def forward(self, x, x_lengths, g=None):
+        x_mask = torch.unsqueeze(commons.sequence_mask(x_lengths, x.size(2)), 1).to(
+            x.dtype
+        )
+        x = self.pre(x) * x_mask
+        x = self.enc(x, x_mask, g=g)
+        stats = self.proj(x) * x_mask
+        m, logs = torch.split(stats, self.out_channels, dim=1)
+        z = (m + torch.randn_like(m) * torch.exp(logs)) * x_mask
+        return z, m, logs, x_mask
+
+    def remove_weight_norm(self):
+        self.enc.remove_weight_norm()
+
+
+class Generator(torch.nn.Module):
+    def __init__(
+        self,
+        initial_channel,
+        resblock,
+        resblock_kernel_sizes,
+        resblock_dilation_sizes,
+        upsample_rates,
+        upsample_initial_channel,
+        upsample_kernel_sizes,
+        gin_channels=0,
+    ):
+        super(Generator, self).__init__()
+        self.num_kernels = len(resblock_kernel_sizes)
+        self.num_upsamples = len(upsample_rates)
+        self.conv_pre = Conv1d(
+            initial_channel, upsample_initial_channel, 7, 1, padding=3
+        )
+        resblock = modules.ResBlock1 if resblock == "1" else modules.ResBlock2
+
+        self.ups = nn.ModuleList()
+        for i, (u, k) in enumerate(zip(upsample_rates, upsample_kernel_sizes)):
+            self.ups.append(
+                weight_norm(
+                    ConvTranspose1d(
+                        upsample_initial_channel // (2**i),
+                        upsample_initial_channel // (2 ** (i + 1)),
+                        k,
+                        u,
+                        padding=(k - u) // 2,
+                    )
+                )
+            )
+
+        self.resblocks = nn.ModuleList()
+        for i in range(len(self.ups)):
+            ch = upsample_initial_channel // (2 ** (i + 1))
+            for j, (k, d) in enumerate(
+                zip(resblock_kernel_sizes, resblock_dilation_sizes)
+            ):
+                self.resblocks.append(resblock(ch, k, d))
+
+        self.conv_post = Conv1d(ch, 1, 7, 1, padding=3, bias=False)
+        self.ups.apply(init_weights)
+
+        if gin_channels != 0:
+            self.cond = nn.Conv1d(gin_channels, upsample_initial_channel, 1)
+
+    def forward(self, x, g=None):
+        x = self.conv_pre(x)
+        if g is not None:
+            x = x + self.cond(g)
+
+        for i in range(self.num_upsamples):
+            x = F.leaky_relu(x, modules.LRELU_SLOPE)
+            x = self.ups[i](x)
+            xs = None
+            for j in range(self.num_kernels):
+                if xs is None:
+                    xs = self.resblocks[i * self.num_kernels + j](x)
+                else:
+                    xs += self.resblocks[i * self.num_kernels + j](x)
+            x = xs / self.num_kernels
+        x = F.leaky_relu(x)
+        x = self.conv_post(x)
+        x = torch.tanh(x)
+
+        return x
+
+    def remove_weight_norm(self):
+        for l in self.ups:
+            remove_weight_norm(l)
+        for l in self.resblocks:
+            l.remove_weight_norm()
+
+
+class SineGen(torch.nn.Module):
+    """Definition of sine generator
+    SineGen(samp_rate, harmonic_num = 0,
+            sine_amp = 0.1, noise_std = 0.003,
+            voiced_threshold = 0,
+            flag_for_pulse=False)
+    samp_rate: sampling rate in Hz
+    harmonic_num: number of harmonic overtones (default 0)
+    sine_amp: amplitude of sine-wavefrom (default 0.1)
+    noise_std: std of Gaussian noise (default 0.003)
+    voiced_thoreshold: F0 threshold for U/V classification (default 0)
+    flag_for_pulse: this SinGen is used inside PulseGen (default False)
+    Note: when flag_for_pulse is True, the first time step of a voiced
+        segment is always sin(np.pi) or cos(0)
+    """
+
+    def __init__(
+        self,
+        samp_rate,
+        harmonic_num=0,
+        sine_amp=0.1,
+        noise_std=0.003,
+        voiced_threshold=0,
+        flag_for_pulse=False,
+    ):
+        super(SineGen, self).__init__()
+        self.sine_amp = sine_amp
+        self.noise_std = noise_std
+        self.harmonic_num = harmonic_num
+        self.dim = self.harmonic_num + 1
+        self.sampling_rate = samp_rate
+        self.voiced_threshold = voiced_threshold
+
+    def _f02uv(self, f0):
+        # generate uv signal
+        uv = torch.ones_like(f0)
+        uv = uv * (f0 > self.voiced_threshold)
+        if uv.device.type == "privateuseone":  # for DirectML
+            uv = uv.float()
+        return uv
+
+    def forward(self, f0, upp):
+        """sine_tensor, uv = forward(f0)
+        input F0: tensor(batchsize=1, length, dim=1)
+                  f0 for unvoiced steps should be 0
+        output sine_tensor: tensor(batchsize=1, length, dim)
+        output uv: tensor(batchsize=1, length, 1)
+        """
+        with torch.no_grad():
+            f0 = f0[:, None].transpose(1, 2)
+            f0_buf = torch.zeros(f0.shape[0], f0.shape[1], self.dim, device=f0.device)
+            # fundamental component
+            f0_buf[:, :, 0] = f0[:, :, 0]
+            for idx in np.arange(self.harmonic_num):
+                f0_buf[:, :, idx + 1] = f0_buf[:, :, 0] * (
+                    idx + 2
+                )  # idx + 2: the (idx+1)-th overtone, (idx+2)-th harmonic
+            rad_values = (f0_buf / self.sampling_rate) % 1  ###%1意味着n_har的乘积无法后处理优化
+            rand_ini = torch.rand(
+                f0_buf.shape[0], f0_buf.shape[2], device=f0_buf.device
+            )
+            rand_ini[:, 0] = 0
+            rad_values[:, 0, :] = rad_values[:, 0, :] + rand_ini
+            tmp_over_one = torch.cumsum(rad_values, 1)  # % 1  #####%1意味着后面的cumsum无法再优化
+            tmp_over_one *= upp
+            tmp_over_one = F.interpolate(
+                tmp_over_one.transpose(2, 1),
+                scale_factor=upp,
+                mode="linear",
+                align_corners=True,
+            ).transpose(2, 1)
+            rad_values = F.interpolate(
+                rad_values.transpose(2, 1), scale_factor=upp, mode="nearest"
+            ).transpose(
+                2, 1
+            )  #######
+            tmp_over_one %= 1
+            tmp_over_one_idx = (tmp_over_one[:, 1:, :] - tmp_over_one[:, :-1, :]) < 0
+            cumsum_shift = torch.zeros_like(rad_values)
+            cumsum_shift[:, 1:, :] = tmp_over_one_idx * -1.0
+            sine_waves = torch.sin(
+                torch.cumsum(rad_values + cumsum_shift, dim=1) * 2 * np.pi
+            )
+            sine_waves = sine_waves * self.sine_amp
+            uv = self._f02uv(f0)
+            uv = F.interpolate(
+                uv.transpose(2, 1), scale_factor=upp, mode="nearest"
+            ).transpose(2, 1)
+            noise_amp = uv * self.noise_std + (1 - uv) * self.sine_amp / 3
+            noise = noise_amp * torch.randn_like(sine_waves)
+            sine_waves = sine_waves * uv + noise
+        return sine_waves, uv, noise
+
+
+class SourceModuleHnNSF(torch.nn.Module):
+    """SourceModule for hn-nsf
+    SourceModule(sampling_rate, harmonic_num=0, sine_amp=0.1,
+                 add_noise_std=0.003, voiced_threshod=0)
+    sampling_rate: sampling_rate in Hz
+    harmonic_num: number of harmonic above F0 (default: 0)
+    sine_amp: amplitude of sine source signal (default: 0.1)
+    add_noise_std: std of additive Gaussian noise (default: 0.003)
+        note that amplitude of noise in unvoiced is decided
+        by sine_amp
+    voiced_threshold: threhold to set U/V given F0 (default: 0)
+    Sine_source, noise_source = SourceModuleHnNSF(F0_sampled)
+    F0_sampled (batchsize, length, 1)
+    Sine_source (batchsize, length, 1)
+    noise_source (batchsize, length 1)
+    uv (batchsize, length, 1)
+    """
+
+    def __init__(
+        self,
+        sampling_rate,
+        harmonic_num=0,
+        sine_amp=0.1,
+        add_noise_std=0.003,
+        voiced_threshod=0,
+        is_half=True,
+    ):
+        super(SourceModuleHnNSF, self).__init__()
+
+        self.sine_amp = sine_amp
+        self.noise_std = add_noise_std
+        self.is_half = is_half
+        # to produce sine waveforms
+        self.l_sin_gen = SineGen(
+            sampling_rate, harmonic_num, sine_amp, add_noise_std, voiced_threshod
+        )
+
+        # to merge source harmonics into a single excitation
+        self.l_linear = torch.nn.Linear(harmonic_num + 1, 1)
+        self.l_tanh = torch.nn.Tanh()
+
+    def forward(self, x, upp=None):
+        if hasattr(self, "ddtype") == False:
+            self.ddtype = self.l_linear.weight.dtype
+        sine_wavs, uv, _ = self.l_sin_gen(x, upp)
+        # print(x.dtype,sine_wavs.dtype,self.l_linear.weight.dtype)
+        # if self.is_half:
+        #     sine_wavs = sine_wavs.half()
+        # sine_merge = self.l_tanh(self.l_linear(sine_wavs.to(x)))
+        # print(sine_wavs.dtype,self.ddtype)
+        if sine_wavs.dtype != self.ddtype:
+            sine_wavs = sine_wavs.to(self.ddtype)
+        sine_merge = self.l_tanh(self.l_linear(sine_wavs))
+        return sine_merge, None, None  # noise, uv
+
+
+class GeneratorNSF(torch.nn.Module):
+    def __init__(
+        self,
+        initial_channel,
+        resblock,
+        resblock_kernel_sizes,
+        resblock_dilation_sizes,
+        upsample_rates,
+        upsample_initial_channel,
+        upsample_kernel_sizes,
+        gin_channels,
+        sr,
+        is_half=False,
+    ):
+        super(GeneratorNSF, self).__init__()
+        self.num_kernels = len(resblock_kernel_sizes)
+        self.num_upsamples = len(upsample_rates)
+
+        self.f0_upsamp = torch.nn.Upsample(scale_factor=np.prod(upsample_rates))
+        self.m_source = SourceModuleHnNSF(
+            sampling_rate=sr, harmonic_num=0, is_half=is_half
+        )
+        self.noise_convs = nn.ModuleList()
+        self.conv_pre = Conv1d(
+            initial_channel, upsample_initial_channel, 7, 1, padding=3
+        )
+        resblock = modules.ResBlock1 if resblock == "1" else modules.ResBlock2
+
+        self.ups = nn.ModuleList()
+        for i, (u, k) in enumerate(zip(upsample_rates, upsample_kernel_sizes)):
+            c_cur = upsample_initial_channel // (2 ** (i + 1))
+            self.ups.append(
+                weight_norm(
+                    ConvTranspose1d(
+                        upsample_initial_channel // (2**i),
+                        upsample_initial_channel // (2 ** (i + 1)),
+                        k,
+                        u,
+                        padding=(k - u) // 2,
+                    )
+                )
+            )
+            if i + 1 < len(upsample_rates):
+                stride_f0 = np.prod(upsample_rates[i + 1 :])
+                self.noise_convs.append(
+                    Conv1d(
+                        1,
+                        c_cur,
+                        kernel_size=stride_f0 * 2,
+                        stride=stride_f0,
+                        padding=stride_f0 // 2,
+                    )
+                )
+            else:
+                self.noise_convs.append(Conv1d(1, c_cur, kernel_size=1))
+
+        self.resblocks = nn.ModuleList()
+        for i in range(len(self.ups)):
+            ch = upsample_initial_channel // (2 ** (i + 1))
+            for j, (k, d) in enumerate(
+                zip(resblock_kernel_sizes, resblock_dilation_sizes)
+            ):
+                self.resblocks.append(resblock(ch, k, d))
+
+        self.conv_post = Conv1d(ch, 1, 7, 1, padding=3, bias=False)
+        self.ups.apply(init_weights)
+
+        if gin_channels != 0:
+            self.cond = nn.Conv1d(gin_channels, upsample_initial_channel, 1)
+
+        self.upp = np.prod(upsample_rates)
+
+    def forward(self, x, f0, g=None):
+        har_source, noi_source, uv = self.m_source(f0, self.upp)
+        har_source = har_source.transpose(1, 2)
+        x = self.conv_pre(x)
+        if g is not None:
+            x = x + self.cond(g)
+
+        for i in range(self.num_upsamples):
+            x = F.leaky_relu(x, modules.LRELU_SLOPE)
+            x = self.ups[i](x)
+            x_source = self.noise_convs[i](har_source)
+            x = x + x_source
+            xs = None
+            for j in range(self.num_kernels):
+                if xs is None:
+                    xs = self.resblocks[i * self.num_kernels + j](x)
+                else:
+                    xs += self.resblocks[i * self.num_kernels + j](x)
+            x = xs / self.num_kernels
+        x = F.leaky_relu(x)
+        x = self.conv_post(x)
+        x = torch.tanh(x)
+        return x
+
+    def remove_weight_norm(self):
+        for l in self.ups:
+            remove_weight_norm(l)
+        for l in self.resblocks:
+            l.remove_weight_norm()
+
+
+sr2sr = {
+    "32k": 32000,
+    "40k": 40000,
+    "48k": 48000,
+}
+
+
+class SynthesizerTrnMs256NSFsid(nn.Module):
+    def __init__(
+        self,
+        spec_channels,
+        segment_size,
+        inter_channels,
+        hidden_channels,
+        filter_channels,
+        n_heads,
+        n_layers,
+        kernel_size,
+        p_dropout,
+        resblock,
+        resblock_kernel_sizes,
+        resblock_dilation_sizes,
+        upsample_rates,
+        upsample_initial_channel,
+        upsample_kernel_sizes,
+        spk_embed_dim,
+        gin_channels,
+        sr,
+        **kwargs
+    ):
+        super().__init__()
+        if type(sr) == type("strr"):
+            sr = sr2sr[sr]
+        self.spec_channels = spec_channels
+        self.inter_channels = inter_channels
+        self.hidden_channels = hidden_channels
+        self.filter_channels = filter_channels
+        self.n_heads = n_heads
+        self.n_layers = n_layers
+        self.kernel_size = kernel_size
+        self.p_dropout = p_dropout
+        self.resblock = resblock
+        self.resblock_kernel_sizes = resblock_kernel_sizes
+        self.resblock_dilation_sizes = resblock_dilation_sizes
+        self.upsample_rates = upsample_rates
+        self.upsample_initial_channel = upsample_initial_channel
+        self.upsample_kernel_sizes = upsample_kernel_sizes
+        self.segment_size = segment_size
+        self.gin_channels = gin_channels
+        # self.hop_length = hop_length#
+        self.spk_embed_dim = spk_embed_dim
+        self.enc_p = TextEncoder256(
+            inter_channels,
+            hidden_channels,
+            filter_channels,
+            n_heads,
+            n_layers,
+            kernel_size,
+            p_dropout,
+        )
+        self.dec = GeneratorNSF(
+            inter_channels,
+            resblock,
+            resblock_kernel_sizes,
+            resblock_dilation_sizes,
+            upsample_rates,
+            upsample_initial_channel,
+            upsample_kernel_sizes,
+            gin_channels=gin_channels,
+            sr=sr,
+            is_half=kwargs["is_half"],
+        )
+        self.enc_q = PosteriorEncoder(
+            spec_channels,
+            inter_channels,
+            hidden_channels,
+            5,
+            1,
+            16,
+            gin_channels=gin_channels,
+        )
+        self.flow = ResidualCouplingBlock(
+            inter_channels, hidden_channels, 5, 1, 3, gin_channels=gin_channels
+        )
+        self.emb_g = nn.Embedding(self.spk_embed_dim, gin_channels)
+        logger.debug(
+            "gin_channels: "
+            + str(gin_channels)
+            + ", self.spk_embed_dim: "
+            + str(self.spk_embed_dim)
+        )
+
+    def remove_weight_norm(self):
+        self.dec.remove_weight_norm()
+        self.flow.remove_weight_norm()
+        self.enc_q.remove_weight_norm()
+
+    def forward(
+        self, phone, phone_lengths, pitch, pitchf, y, y_lengths, ds
+    ):  # 这里ds是id，[bs,1]
+        # print(1,pitch.shape)#[bs,t]
+        g = self.emb_g(ds).unsqueeze(-1)  # [b, 256, 1]##1是t，广播的
+        m_p, logs_p, x_mask = self.enc_p(phone, pitch, phone_lengths)
+        z, m_q, logs_q, y_mask = self.enc_q(y, y_lengths, g=g)
+        z_p = self.flow(z, y_mask, g=g)
+        z_slice, ids_slice = commons.rand_slice_segments(
+            z, y_lengths, self.segment_size
+        )
+        # print(-1,pitchf.shape,ids_slice,self.segment_size,self.hop_length,self.segment_size//self.hop_length)
+        pitchf = commons.slice_segments2(pitchf, ids_slice, self.segment_size)
+        # print(-2,pitchf.shape,z_slice.shape)
+        o = self.dec(z_slice, pitchf, g=g)
+        return o, ids_slice, x_mask, y_mask, (z, z_p, m_p, logs_p, m_q, logs_q)
+
+    def infer(self, phone, phone_lengths, pitch, nsff0, sid, rate=None):
+        g = self.emb_g(sid).unsqueeze(-1)
+        m_p, logs_p, x_mask = self.enc_p(phone, pitch, phone_lengths)
+        z_p = (m_p + torch.exp(logs_p) * torch.randn_like(m_p) * 0.66666) * x_mask
+        if rate:
+            head = int(z_p.shape[2] * rate)
+            z_p = z_p[:, :, -head:]
+            x_mask = x_mask[:, :, -head:]
+            nsff0 = nsff0[:, -head:]
+        z = self.flow(z_p, x_mask, g=g, reverse=True)
+        o = self.dec(z * x_mask, nsff0, g=g)
+        return o, x_mask, (z, z_p, m_p, logs_p)
+
+
+class SynthesizerTrnMs768NSFsid(nn.Module):
+    def __init__(
+        self,
+        spec_channels,
+        segment_size,
+        inter_channels,
+        hidden_channels,
+        filter_channels,
+        n_heads,
+        n_layers,
+        kernel_size,
+        p_dropout,
+        resblock,
+        resblock_kernel_sizes,
+        resblock_dilation_sizes,
+        upsample_rates,
+        upsample_initial_channel,
+        upsample_kernel_sizes,
+        spk_embed_dim,
+        gin_channels,
+        sr,
+        **kwargs
+    ):
+        super().__init__()
+        if type(sr) == type("strr"):
+            sr = sr2sr[sr]
+        self.spec_channels = spec_channels
+        self.inter_channels = inter_channels
+        self.hidden_channels = hidden_channels
+        self.filter_channels = filter_channels
+        self.n_heads = n_heads
+        self.n_layers = n_layers
+        self.kernel_size = kernel_size
+        self.p_dropout = p_dropout
+        self.resblock = resblock
+        self.resblock_kernel_sizes = resblock_kernel_sizes
+        self.resblock_dilation_sizes = resblock_dilation_sizes
+        self.upsample_rates = upsample_rates
+        self.upsample_initial_channel = upsample_initial_channel
+        self.upsample_kernel_sizes = upsample_kernel_sizes
+        self.segment_size = segment_size
+        self.gin_channels = gin_channels
+        # self.hop_length = hop_length#
+        self.spk_embed_dim = spk_embed_dim
+        self.enc_p = TextEncoder768(
+            inter_channels,
+            hidden_channels,
+            filter_channels,
+            n_heads,
+            n_layers,
+            kernel_size,
+            p_dropout,
+        )
+        self.dec = GeneratorNSF(
+            inter_channels,
+            resblock,
+            resblock_kernel_sizes,
+            resblock_dilation_sizes,
+            upsample_rates,
+            upsample_initial_channel,
+            upsample_kernel_sizes,
+            gin_channels=gin_channels,
+            sr=sr,
+            is_half=kwargs["is_half"],
+        )
+        self.enc_q = PosteriorEncoder(
+            spec_channels,
+            inter_channels,
+            hidden_channels,
+            5,
+            1,
+            16,
+            gin_channels=gin_channels,
+        )
+        self.flow = ResidualCouplingBlock(
+            inter_channels, hidden_channels, 5, 1, 3, gin_channels=gin_channels
+        )
+        self.emb_g = nn.Embedding(self.spk_embed_dim, gin_channels)
+        logger.debug(
+            "gin_channels: "
+            + str(gin_channels)
+            + ", self.spk_embed_dim: "
+            + str(self.spk_embed_dim)
+        )
+
+    def remove_weight_norm(self):
+        self.dec.remove_weight_norm()
+        self.flow.remove_weight_norm()
+        self.enc_q.remove_weight_norm()
+
+    def forward(
+        self, phone, phone_lengths, pitch, pitchf, y, y_lengths, ds
+    ):  # 这里ds是id，[bs,1]
+        # print(1,pitch.shape)#[bs,t]
+        g = self.emb_g(ds).unsqueeze(-1)  # [b, 256, 1]##1是t，广播的
+        m_p, logs_p, x_mask = self.enc_p(phone, pitch, phone_lengths)
+        z, m_q, logs_q, y_mask = self.enc_q(y, y_lengths, g=g)
+        z_p = self.flow(z, y_mask, g=g)
+        z_slice, ids_slice = commons.rand_slice_segments(
+            z, y_lengths, self.segment_size
+        )
+        # print(-1,pitchf.shape,ids_slice,self.segment_size,self.hop_length,self.segment_size//self.hop_length)
+        pitchf = commons.slice_segments2(pitchf, ids_slice, self.segment_size)
+        # print(-2,pitchf.shape,z_slice.shape)
+        o = self.dec(z_slice, pitchf, g=g)
+        return o, ids_slice, x_mask, y_mask, (z, z_p, m_p, logs_p, m_q, logs_q)
+
+    def infer(self, phone, phone_lengths, pitch, nsff0, sid, rate=None):
+        g = self.emb_g(sid).unsqueeze(-1)
+        m_p, logs_p, x_mask = self.enc_p(phone, pitch, phone_lengths)
+        z_p = (m_p + torch.exp(logs_p) * torch.randn_like(m_p) * 0.66666) * x_mask
+        if rate:
+            head = int(z_p.shape[2] * rate)
+            z_p = z_p[:, :, -head:]
+            x_mask = x_mask[:, :, -head:]
+            nsff0 = nsff0[:, -head:]
+        z = self.flow(z_p, x_mask, g=g, reverse=True)
+        o = self.dec(z * x_mask, nsff0, g=g)
+        return o, x_mask, (z, z_p, m_p, logs_p)
+
+
+class SynthesizerTrnMs256NSFsid_nono(nn.Module):
+    def __init__(
+        self,
+        spec_channels,
+        segment_size,
+        inter_channels,
+        hidden_channels,
+        filter_channels,
+        n_heads,
+        n_layers,
+        kernel_size,
+        p_dropout,
+        resblock,
+        resblock_kernel_sizes,
+        resblock_dilation_sizes,
+        upsample_rates,
+        upsample_initial_channel,
+        upsample_kernel_sizes,
+        spk_embed_dim,
+        gin_channels,
+        sr=None,
+        **kwargs
+    ):
+        super().__init__()
+        self.spec_channels = spec_channels
+        self.inter_channels = inter_channels
+        self.hidden_channels = hidden_channels
+        self.filter_channels = filter_channels
+        self.n_heads = n_heads
+        self.n_layers = n_layers
+        self.kernel_size = kernel_size
+        self.p_dropout = p_dropout
+        self.resblock = resblock
+        self.resblock_kernel_sizes = resblock_kernel_sizes
+        self.resblock_dilation_sizes = resblock_dilation_sizes
+        self.upsample_rates = upsample_rates
+        self.upsample_initial_channel = upsample_initial_channel
+        self.upsample_kernel_sizes = upsample_kernel_sizes
+        self.segment_size = segment_size
+        self.gin_channels = gin_channels
+        # self.hop_length = hop_length#
+        self.spk_embed_dim = spk_embed_dim
+        self.enc_p = TextEncoder256(
+            inter_channels,
+            hidden_channels,
+            filter_channels,
+            n_heads,
+            n_layers,
+            kernel_size,
+            p_dropout,
+            f0=False,
+        )
+        self.dec = Generator(
+            inter_channels,
+            resblock,
+            resblock_kernel_sizes,
+            resblock_dilation_sizes,
+            upsample_rates,
+            upsample_initial_channel,
+            upsample_kernel_sizes,
+            gin_channels=gin_channels,
+        )
+        self.enc_q = PosteriorEncoder(
+            spec_channels,
+            inter_channels,
+            hidden_channels,
+            5,
+            1,
+            16,
+            gin_channels=gin_channels,
+        )
+        self.flow = ResidualCouplingBlock(
+            inter_channels, hidden_channels, 5, 1, 3, gin_channels=gin_channels
+        )
+        self.emb_g = nn.Embedding(self.spk_embed_dim, gin_channels)
+        logger.debug(
+            "gin_channels: "
+            + str(gin_channels)
+            + ", self.spk_embed_dim: "
+            + str(self.spk_embed_dim)
+        )
+
+    def remove_weight_norm(self):
+        self.dec.remove_weight_norm()
+        self.flow.remove_weight_norm()
+        self.enc_q.remove_weight_norm()
+
+    def forward(self, phone, phone_lengths, y, y_lengths, ds):  # 这里ds是id，[bs,1]
+        g = self.emb_g(ds).unsqueeze(-1)  # [b, 256, 1]##1是t，广播的
+        m_p, logs_p, x_mask = self.enc_p(phone, None, phone_lengths)
+        z, m_q, logs_q, y_mask = self.enc_q(y, y_lengths, g=g)
+        z_p = self.flow(z, y_mask, g=g)
+        z_slice, ids_slice = commons.rand_slice_segments(
+            z, y_lengths, self.segment_size
+        )
+        o = self.dec(z_slice, g=g)
+        return o, ids_slice, x_mask, y_mask, (z, z_p, m_p, logs_p, m_q, logs_q)
+
+    def infer(self, phone, phone_lengths, sid, rate=None):
+        g = self.emb_g(sid).unsqueeze(-1)
+        m_p, logs_p, x_mask = self.enc_p(phone, None, phone_lengths)
+        z_p = (m_p + torch.exp(logs_p) * torch.randn_like(m_p) * 0.66666) * x_mask
+        if rate:
+            head = int(z_p.shape[2] * rate)
+            z_p = z_p[:, :, -head:]
+            x_mask = x_mask[:, :, -head:]
+        z = self.flow(z_p, x_mask, g=g, reverse=True)
+        o = self.dec(z * x_mask, g=g)
+        return o, x_mask, (z, z_p, m_p, logs_p)
+
+
+class SynthesizerTrnMs768NSFsid_nono(nn.Module):
+    def __init__(
+        self,
+        spec_channels,
+        segment_size,
+        inter_channels,
+        hidden_channels,
+        filter_channels,
+        n_heads,
+        n_layers,
+        kernel_size,
+        p_dropout,
+        resblock,
+        resblock_kernel_sizes,
+        resblock_dilation_sizes,
+        upsample_rates,
+        upsample_initial_channel,
+        upsample_kernel_sizes,
+        spk_embed_dim,
+        gin_channels,
+        sr=None,
+        **kwargs
+    ):
+        super().__init__()
+        self.spec_channels = spec_channels
+        self.inter_channels = inter_channels
+        self.hidden_channels = hidden_channels
+        self.filter_channels = filter_channels
+        self.n_heads = n_heads
+        self.n_layers = n_layers
+        self.kernel_size = kernel_size
+        self.p_dropout = p_dropout
+        self.resblock = resblock
+        self.resblock_kernel_sizes = resblock_kernel_sizes
+        self.resblock_dilation_sizes = resblock_dilation_sizes
+        self.upsample_rates = upsample_rates
+        self.upsample_initial_channel = upsample_initial_channel
+        self.upsample_kernel_sizes = upsample_kernel_sizes
+        self.segment_size = segment_size
+        self.gin_channels = gin_channels
+        # self.hop_length = hop_length#
+        self.spk_embed_dim = spk_embed_dim
+        self.enc_p = TextEncoder768(
+            inter_channels,
+            hidden_channels,
+            filter_channels,
+            n_heads,
+            n_layers,
+            kernel_size,
+            p_dropout,
+            f0=False,
+        )
+        self.dec = Generator(
+            inter_channels,
+            resblock,
+            resblock_kernel_sizes,
+            resblock_dilation_sizes,
+            upsample_rates,
+            upsample_initial_channel,
+            upsample_kernel_sizes,
+            gin_channels=gin_channels,
+        )
+        self.enc_q = PosteriorEncoder(
+            spec_channels,
+            inter_channels,
+            hidden_channels,
+            5,
+            1,
+            16,
+            gin_channels=gin_channels,
+        )
+        self.flow = ResidualCouplingBlock(
+            inter_channels, hidden_channels, 5, 1, 3, gin_channels=gin_channels
+        )
+        self.emb_g = nn.Embedding(self.spk_embed_dim, gin_channels)
+        logger.debug(
+            "gin_channels: "
+            + str(gin_channels)
+            + ", self.spk_embed_dim: "
+            + str(self.spk_embed_dim)
+        )
+
+    def remove_weight_norm(self):
+        self.dec.remove_weight_norm()
+        self.flow.remove_weight_norm()
+        self.enc_q.remove_weight_norm()
+
+    def forward(self, phone, phone_lengths, y, y_lengths, ds):  # 这里ds是id，[bs,1]
+        g = self.emb_g(ds).unsqueeze(-1)  # [b, 256, 1]##1是t，广播的
+        m_p, logs_p, x_mask = self.enc_p(phone, None, phone_lengths)
+        z, m_q, logs_q, y_mask = self.enc_q(y, y_lengths, g=g)
+        z_p = self.flow(z, y_mask, g=g)
+        z_slice, ids_slice = commons.rand_slice_segments(
+            z, y_lengths, self.segment_size
+        )
+        o = self.dec(z_slice, g=g)
+        return o, ids_slice, x_mask, y_mask, (z, z_p, m_p, logs_p, m_q, logs_q)
+
+    def infer(self, phone, phone_lengths, sid, rate=None):
+        g = self.emb_g(sid).unsqueeze(-1)
+        m_p, logs_p, x_mask = self.enc_p(phone, None, phone_lengths)
+        z_p = (m_p + torch.exp(logs_p) * torch.randn_like(m_p) * 0.66666) * x_mask
+        if rate:
+            head = int(z_p.shape[2] * rate)
+            z_p = z_p[:, :, -head:]
+            x_mask = x_mask[:, :, -head:]
+        z = self.flow(z_p, x_mask, g=g, reverse=True)
+        o = self.dec(z * x_mask, g=g)
+        return o, x_mask, (z, z_p, m_p, logs_p)
+
+
+class MultiPeriodDiscriminator(torch.nn.Module):
+    def __init__(self, use_spectral_norm=False):
+        super(MultiPeriodDiscriminator, self).__init__()
+        periods = [2, 3, 5, 7, 11, 17]
+        # periods = [3, 5, 7, 11, 17, 23, 37]
+
+        discs = [DiscriminatorS(use_spectral_norm=use_spectral_norm)]
+        discs = discs + [
+            DiscriminatorP(i, use_spectral_norm=use_spectral_norm) for i in periods
+        ]
+        self.discriminators = nn.ModuleList(discs)
+
+    def forward(self, y, y_hat):
+        y_d_rs = []  #
+        y_d_gs = []
+        fmap_rs = []
+        fmap_gs = []
+        for i, d in enumerate(self.discriminators):
+            y_d_r, fmap_r = d(y)
+            y_d_g, fmap_g = d(y_hat)
+            # for j in range(len(fmap_r)):
+            #     print(i,j,y.shape,y_hat.shape,fmap_r[j].shape,fmap_g[j].shape)
+            y_d_rs.append(y_d_r)
+            y_d_gs.append(y_d_g)
+            fmap_rs.append(fmap_r)
+            fmap_gs.append(fmap_g)
+
+        return y_d_rs, y_d_gs, fmap_rs, fmap_gs
+
+
+class MultiPeriodDiscriminatorV2(torch.nn.Module):
+    def __init__(self, use_spectral_norm=False):
+        super(MultiPeriodDiscriminatorV2, self).__init__()
+        # periods = [2, 3, 5, 7, 11, 17]
+        periods = [2, 3, 5, 7, 11, 17, 23, 37]
+
+        discs = [DiscriminatorS(use_spectral_norm=use_spectral_norm)]
+        discs = discs + [
+            DiscriminatorP(i, use_spectral_norm=use_spectral_norm) for i in periods
+        ]
+        self.discriminators = nn.ModuleList(discs)
+
+    def forward(self, y, y_hat):
+        y_d_rs = []  #
+        y_d_gs = []
+        fmap_rs = []
+        fmap_gs = []
+        for i, d in enumerate(self.discriminators):
+            y_d_r, fmap_r = d(y)
+            y_d_g, fmap_g = d(y_hat)
+            # for j in range(len(fmap_r)):
+            #     print(i,j,y.shape,y_hat.shape,fmap_r[j].shape,fmap_g[j].shape)
+            y_d_rs.append(y_d_r)
+            y_d_gs.append(y_d_g)
+            fmap_rs.append(fmap_r)
+            fmap_gs.append(fmap_g)
+
+        return y_d_rs, y_d_gs, fmap_rs, fmap_gs
+
+
+class DiscriminatorS(torch.nn.Module):
+    def __init__(self, use_spectral_norm=False):
+        super(DiscriminatorS, self).__init__()
+        norm_f = weight_norm if use_spectral_norm == False else spectral_norm
+        self.convs = nn.ModuleList(
+            [
+                norm_f(Conv1d(1, 16, 15, 1, padding=7)),
+                norm_f(Conv1d(16, 64, 41, 4, groups=4, padding=20)),
+                norm_f(Conv1d(64, 256, 41, 4, groups=16, padding=20)),
+                norm_f(Conv1d(256, 1024, 41, 4, groups=64, padding=20)),
+                norm_f(Conv1d(1024, 1024, 41, 4, groups=256, padding=20)),
+                norm_f(Conv1d(1024, 1024, 5, 1, padding=2)),
+            ]
+        )
+        self.conv_post = norm_f(Conv1d(1024, 1, 3, 1, padding=1))
+
+    def forward(self, x):
+        fmap = []
+
+        for l in self.convs:
+            x = l(x)
+            x = F.leaky_relu(x, modules.LRELU_SLOPE)
+            fmap.append(x)
+        x = self.conv_post(x)
+        fmap.append(x)
+        x = torch.flatten(x, 1, -1)
+
+        return x, fmap
+
+
+class DiscriminatorP(torch.nn.Module):
+    def __init__(self, period, kernel_size=5, stride=3, use_spectral_norm=False):
+        super(DiscriminatorP, self).__init__()
+        self.period = period
+        self.use_spectral_norm = use_spectral_norm
+        norm_f = weight_norm if use_spectral_norm == False else spectral_norm
+        self.convs = nn.ModuleList(
+            [
+                norm_f(
+                    Conv2d(
+                        1,
+                        32,
+                        (kernel_size, 1),
+                        (stride, 1),
+                        padding=(get_padding(kernel_size, 1), 0),
+                    )
+                ),
+                norm_f(
+                    Conv2d(
+                        32,
+                        128,
+                        (kernel_size, 1),
+                        (stride, 1),
+                        padding=(get_padding(kernel_size, 1), 0),
+                    )
+                ),
+                norm_f(
+                    Conv2d(
+                        128,
+                        512,
+                        (kernel_size, 1),
+                        (stride, 1),
+                        padding=(get_padding(kernel_size, 1), 0),
+                    )
+                ),
+                norm_f(
+                    Conv2d(
+                        512,
+                        1024,
+                        (kernel_size, 1),
+                        (stride, 1),
+                        padding=(get_padding(kernel_size, 1), 0),
+                    )
+                ),
+                norm_f(
+                    Conv2d(
+                        1024,
+                        1024,
+                        (kernel_size, 1),
+                        1,
+                        padding=(get_padding(kernel_size, 1), 0),
+                    )
+                ),
+            ]
+        )
+        self.conv_post = norm_f(Conv2d(1024, 1, (3, 1), 1, padding=(1, 0)))
+
+    def forward(self, x):
+        fmap = []
+
+        # 1d to 2d
+        b, c, t = x.shape
+        if t % self.period != 0:  # pad first
+            n_pad = self.period - (t % self.period)
+            if has_xpu and x.dtype == torch.bfloat16:
+                x = F.pad(x.to(dtype=torch.float16), (0, n_pad), "reflect").to(dtype=torch.bfloat16)
+            else:
+                x = F.pad(x, (0, n_pad), "reflect")
+            t = t + n_pad
+        x = x.view(b, c, t // self.period, self.period)
+
+        for l in self.convs:
+            x = l(x)
+            x = F.leaky_relu(x, modules.LRELU_SLOPE)
+            fmap.append(x)
+        x = self.conv_post(x)
+        fmap.append(x)
+        x = torch.flatten(x, 1, -1)
+
+        return x, fmap
diff --git a/infer/lib/infer_pack/models_onnx.py b/infer/lib/infer_pack/models_onnx.py
new file mode 100644
index 0000000000000000000000000000000000000000..3e99763bf3ed7988eb2ae33d9066f85d37adf119
--- /dev/null
+++ b/infer/lib/infer_pack/models_onnx.py
@@ -0,0 +1,824 @@
+import math
+import logging
+
+logger = logging.getLogger(__name__)
+
+import numpy as np
+import torch
+from torch import nn
+from torch.nn import AvgPool1d, Conv1d, Conv2d, ConvTranspose1d
+from torch.nn import functional as F
+from torch.nn.utils import remove_weight_norm, spectral_norm, weight_norm
+
+from infer.lib.infer_pack import attentions, commons, modules
+from infer.lib.infer_pack.commons import get_padding, init_weights
+
+
+class TextEncoder256(nn.Module):
+    def __init__(
+        self,
+        out_channels,
+        hidden_channels,
+        filter_channels,
+        n_heads,
+        n_layers,
+        kernel_size,
+        p_dropout,
+        f0=True,
+    ):
+        super().__init__()
+        self.out_channels = out_channels
+        self.hidden_channels = hidden_channels
+        self.filter_channels = filter_channels
+        self.n_heads = n_heads
+        self.n_layers = n_layers
+        self.kernel_size = kernel_size
+        self.p_dropout = p_dropout
+        self.emb_phone = nn.Linear(256, hidden_channels)
+        self.lrelu = nn.LeakyReLU(0.1, inplace=True)
+        if f0 == True:
+            self.emb_pitch = nn.Embedding(256, hidden_channels)  # pitch 256
+        self.encoder = attentions.Encoder(
+            hidden_channels, filter_channels, n_heads, n_layers, kernel_size, p_dropout
+        )
+        self.proj = nn.Conv1d(hidden_channels, out_channels * 2, 1)
+
+    def forward(self, phone, pitch, lengths):
+        if pitch == None:
+            x = self.emb_phone(phone)
+        else:
+            x = self.emb_phone(phone) + self.emb_pitch(pitch)
+        x = x * math.sqrt(self.hidden_channels)  # [b, t, h]
+        x = self.lrelu(x)
+        x = torch.transpose(x, 1, -1)  # [b, h, t]
+        x_mask = torch.unsqueeze(commons.sequence_mask(lengths, x.size(2)), 1).to(
+            x.dtype
+        )
+        x = self.encoder(x * x_mask, x_mask)
+        stats = self.proj(x) * x_mask
+
+        m, logs = torch.split(stats, self.out_channels, dim=1)
+        return m, logs, x_mask
+
+
+class TextEncoder768(nn.Module):
+    def __init__(
+        self,
+        out_channels,
+        hidden_channels,
+        filter_channels,
+        n_heads,
+        n_layers,
+        kernel_size,
+        p_dropout,
+        f0=True,
+    ):
+        super().__init__()
+        self.out_channels = out_channels
+        self.hidden_channels = hidden_channels
+        self.filter_channels = filter_channels
+        self.n_heads = n_heads
+        self.n_layers = n_layers
+        self.kernel_size = kernel_size
+        self.p_dropout = p_dropout
+        self.emb_phone = nn.Linear(768, hidden_channels)
+        self.lrelu = nn.LeakyReLU(0.1, inplace=True)
+        if f0 == True:
+            self.emb_pitch = nn.Embedding(256, hidden_channels)  # pitch 256
+        self.encoder = attentions.Encoder(
+            hidden_channels, filter_channels, n_heads, n_layers, kernel_size, p_dropout
+        )
+        self.proj = nn.Conv1d(hidden_channels, out_channels * 2, 1)
+
+    def forward(self, phone, pitch, lengths):
+        if pitch == None:
+            x = self.emb_phone(phone)
+        else:
+            x = self.emb_phone(phone) + self.emb_pitch(pitch)
+        x = x * math.sqrt(self.hidden_channels)  # [b, t, h]
+        x = self.lrelu(x)
+        x = torch.transpose(x, 1, -1)  # [b, h, t]
+        x_mask = torch.unsqueeze(commons.sequence_mask(lengths, x.size(2)), 1).to(
+            x.dtype
+        )
+        x = self.encoder(x * x_mask, x_mask)
+        stats = self.proj(x) * x_mask
+
+        m, logs = torch.split(stats, self.out_channels, dim=1)
+        return m, logs, x_mask
+
+
+class ResidualCouplingBlock(nn.Module):
+    def __init__(
+        self,
+        channels,
+        hidden_channels,
+        kernel_size,
+        dilation_rate,
+        n_layers,
+        n_flows=4,
+        gin_channels=0,
+    ):
+        super().__init__()
+        self.channels = channels
+        self.hidden_channels = hidden_channels
+        self.kernel_size = kernel_size
+        self.dilation_rate = dilation_rate
+        self.n_layers = n_layers
+        self.n_flows = n_flows
+        self.gin_channels = gin_channels
+
+        self.flows = nn.ModuleList()
+        for i in range(n_flows):
+            self.flows.append(
+                modules.ResidualCouplingLayer(
+                    channels,
+                    hidden_channels,
+                    kernel_size,
+                    dilation_rate,
+                    n_layers,
+                    gin_channels=gin_channels,
+                    mean_only=True,
+                )
+            )
+            self.flows.append(modules.Flip())
+
+    def forward(self, x, x_mask, g=None, reverse=False):
+        if not reverse:
+            for flow in self.flows:
+                x, _ = flow(x, x_mask, g=g, reverse=reverse)
+        else:
+            for flow in reversed(self.flows):
+                x = flow(x, x_mask, g=g, reverse=reverse)
+        return x
+
+    def remove_weight_norm(self):
+        for i in range(self.n_flows):
+            self.flows[i * 2].remove_weight_norm()
+
+
+class PosteriorEncoder(nn.Module):
+    def __init__(
+        self,
+        in_channels,
+        out_channels,
+        hidden_channels,
+        kernel_size,
+        dilation_rate,
+        n_layers,
+        gin_channels=0,
+    ):
+        super().__init__()
+        self.in_channels = in_channels
+        self.out_channels = out_channels
+        self.hidden_channels = hidden_channels
+        self.kernel_size = kernel_size
+        self.dilation_rate = dilation_rate
+        self.n_layers = n_layers
+        self.gin_channels = gin_channels
+
+        self.pre = nn.Conv1d(in_channels, hidden_channels, 1)
+        self.enc = modules.WN(
+            hidden_channels,
+            kernel_size,
+            dilation_rate,
+            n_layers,
+            gin_channels=gin_channels,
+        )
+        self.proj = nn.Conv1d(hidden_channels, out_channels * 2, 1)
+
+    def forward(self, x, x_lengths, g=None):
+        x_mask = torch.unsqueeze(commons.sequence_mask(x_lengths, x.size(2)), 1).to(
+            x.dtype
+        )
+        x = self.pre(x) * x_mask
+        x = self.enc(x, x_mask, g=g)
+        stats = self.proj(x) * x_mask
+        m, logs = torch.split(stats, self.out_channels, dim=1)
+        z = (m + torch.randn_like(m) * torch.exp(logs)) * x_mask
+        return z, m, logs, x_mask
+
+    def remove_weight_norm(self):
+        self.enc.remove_weight_norm()
+
+
+class Generator(torch.nn.Module):
+    def __init__(
+        self,
+        initial_channel,
+        resblock,
+        resblock_kernel_sizes,
+        resblock_dilation_sizes,
+        upsample_rates,
+        upsample_initial_channel,
+        upsample_kernel_sizes,
+        gin_channels=0,
+    ):
+        super(Generator, self).__init__()
+        self.num_kernels = len(resblock_kernel_sizes)
+        self.num_upsamples = len(upsample_rates)
+        self.conv_pre = Conv1d(
+            initial_channel, upsample_initial_channel, 7, 1, padding=3
+        )
+        resblock = modules.ResBlock1 if resblock == "1" else modules.ResBlock2
+
+        self.ups = nn.ModuleList()
+        for i, (u, k) in enumerate(zip(upsample_rates, upsample_kernel_sizes)):
+            self.ups.append(
+                weight_norm(
+                    ConvTranspose1d(
+                        upsample_initial_channel // (2**i),
+                        upsample_initial_channel // (2 ** (i + 1)),
+                        k,
+                        u,
+                        padding=(k - u) // 2,
+                    )
+                )
+            )
+
+        self.resblocks = nn.ModuleList()
+        for i in range(len(self.ups)):
+            ch = upsample_initial_channel // (2 ** (i + 1))
+            for j, (k, d) in enumerate(
+                zip(resblock_kernel_sizes, resblock_dilation_sizes)
+            ):
+                self.resblocks.append(resblock(ch, k, d))
+
+        self.conv_post = Conv1d(ch, 1, 7, 1, padding=3, bias=False)
+        self.ups.apply(init_weights)
+
+        if gin_channels != 0:
+            self.cond = nn.Conv1d(gin_channels, upsample_initial_channel, 1)
+
+    def forward(self, x, g=None):
+        x = self.conv_pre(x)
+        if g is not None:
+            x = x + self.cond(g)
+
+        for i in range(self.num_upsamples):
+            x = F.leaky_relu(x, modules.LRELU_SLOPE)
+            x = self.ups[i](x)
+            xs = None
+            for j in range(self.num_kernels):
+                if xs is None:
+                    xs = self.resblocks[i * self.num_kernels + j](x)
+                else:
+                    xs += self.resblocks[i * self.num_kernels + j](x)
+            x = xs / self.num_kernels
+        x = F.leaky_relu(x)
+        x = self.conv_post(x)
+        x = torch.tanh(x)
+
+        return x
+
+    def remove_weight_norm(self):
+        for l in self.ups:
+            remove_weight_norm(l)
+        for l in self.resblocks:
+            l.remove_weight_norm()
+
+
+class SineGen(torch.nn.Module):
+    """Definition of sine generator
+    SineGen(samp_rate, harmonic_num = 0,
+            sine_amp = 0.1, noise_std = 0.003,
+            voiced_threshold = 0,
+            flag_for_pulse=False)
+    samp_rate: sampling rate in Hz
+    harmonic_num: number of harmonic overtones (default 0)
+    sine_amp: amplitude of sine-wavefrom (default 0.1)
+    noise_std: std of Gaussian noise (default 0.003)
+    voiced_thoreshold: F0 threshold for U/V classification (default 0)
+    flag_for_pulse: this SinGen is used inside PulseGen (default False)
+    Note: when flag_for_pulse is True, the first time step of a voiced
+        segment is always sin(np.pi) or cos(0)
+    """
+
+    def __init__(
+        self,
+        samp_rate,
+        harmonic_num=0,
+        sine_amp=0.1,
+        noise_std=0.003,
+        voiced_threshold=0,
+        flag_for_pulse=False,
+    ):
+        super(SineGen, self).__init__()
+        self.sine_amp = sine_amp
+        self.noise_std = noise_std
+        self.harmonic_num = harmonic_num
+        self.dim = self.harmonic_num + 1
+        self.sampling_rate = samp_rate
+        self.voiced_threshold = voiced_threshold
+
+    def _f02uv(self, f0):
+        # generate uv signal
+        uv = torch.ones_like(f0)
+        uv = uv * (f0 > self.voiced_threshold)
+        return uv
+
+    def forward(self, f0, upp):
+        """sine_tensor, uv = forward(f0)
+        input F0: tensor(batchsize=1, length, dim=1)
+                  f0 for unvoiced steps should be 0
+        output sine_tensor: tensor(batchsize=1, length, dim)
+        output uv: tensor(batchsize=1, length, 1)
+        """
+        with torch.no_grad():
+            f0 = f0[:, None].transpose(1, 2)
+            f0_buf = torch.zeros(f0.shape[0], f0.shape[1], self.dim, device=f0.device)
+            # fundamental component
+            f0_buf[:, :, 0] = f0[:, :, 0]
+            for idx in np.arange(self.harmonic_num):
+                f0_buf[:, :, idx + 1] = f0_buf[:, :, 0] * (
+                    idx + 2
+                )  # idx + 2: the (idx+1)-th overtone, (idx+2)-th harmonic
+            rad_values = (f0_buf / self.sampling_rate) % 1  ###%1意味着n_har的乘积无法后处理优化
+            rand_ini = torch.rand(
+                f0_buf.shape[0], f0_buf.shape[2], device=f0_buf.device
+            )
+            rand_ini[:, 0] = 0
+            rad_values[:, 0, :] = rad_values[:, 0, :] + rand_ini
+            tmp_over_one = torch.cumsum(rad_values, 1)  # % 1  #####%1意味着后面的cumsum无法再优化
+            tmp_over_one *= upp
+            tmp_over_one = F.interpolate(
+                tmp_over_one.transpose(2, 1),
+                scale_factor=upp,
+                mode="linear",
+                align_corners=True,
+            ).transpose(2, 1)
+            rad_values = F.interpolate(
+                rad_values.transpose(2, 1), scale_factor=upp, mode="nearest"
+            ).transpose(
+                2, 1
+            )  #######
+            tmp_over_one %= 1
+            tmp_over_one_idx = (tmp_over_one[:, 1:, :] - tmp_over_one[:, :-1, :]) < 0
+            cumsum_shift = torch.zeros_like(rad_values)
+            cumsum_shift[:, 1:, :] = tmp_over_one_idx * -1.0
+            sine_waves = torch.sin(
+                torch.cumsum(rad_values + cumsum_shift, dim=1) * 2 * np.pi
+            )
+            sine_waves = sine_waves * self.sine_amp
+            uv = self._f02uv(f0)
+            uv = F.interpolate(
+                uv.transpose(2, 1), scale_factor=upp, mode="nearest"
+            ).transpose(2, 1)
+            noise_amp = uv * self.noise_std + (1 - uv) * self.sine_amp / 3
+            noise = noise_amp * torch.randn_like(sine_waves)
+            sine_waves = sine_waves * uv + noise
+        return sine_waves, uv, noise
+
+
+class SourceModuleHnNSF(torch.nn.Module):
+    """SourceModule for hn-nsf
+    SourceModule(sampling_rate, harmonic_num=0, sine_amp=0.1,
+                 add_noise_std=0.003, voiced_threshod=0)
+    sampling_rate: sampling_rate in Hz
+    harmonic_num: number of harmonic above F0 (default: 0)
+    sine_amp: amplitude of sine source signal (default: 0.1)
+    add_noise_std: std of additive Gaussian noise (default: 0.003)
+        note that amplitude of noise in unvoiced is decided
+        by sine_amp
+    voiced_threshold: threhold to set U/V given F0 (default: 0)
+    Sine_source, noise_source = SourceModuleHnNSF(F0_sampled)
+    F0_sampled (batchsize, length, 1)
+    Sine_source (batchsize, length, 1)
+    noise_source (batchsize, length 1)
+    uv (batchsize, length, 1)
+    """
+
+    def __init__(
+        self,
+        sampling_rate,
+        harmonic_num=0,
+        sine_amp=0.1,
+        add_noise_std=0.003,
+        voiced_threshod=0,
+        is_half=True,
+    ):
+        super(SourceModuleHnNSF, self).__init__()
+
+        self.sine_amp = sine_amp
+        self.noise_std = add_noise_std
+        self.is_half = is_half
+        # to produce sine waveforms
+        self.l_sin_gen = SineGen(
+            sampling_rate, harmonic_num, sine_amp, add_noise_std, voiced_threshod
+        )
+
+        # to merge source harmonics into a single excitation
+        self.l_linear = torch.nn.Linear(harmonic_num + 1, 1)
+        self.l_tanh = torch.nn.Tanh()
+
+    def forward(self, x, upp=None):
+        sine_wavs, uv, _ = self.l_sin_gen(x, upp)
+        if self.is_half:
+            sine_wavs = sine_wavs.half()
+        sine_merge = self.l_tanh(self.l_linear(sine_wavs))
+        return sine_merge, None, None  # noise, uv
+
+
+class GeneratorNSF(torch.nn.Module):
+    def __init__(
+        self,
+        initial_channel,
+        resblock,
+        resblock_kernel_sizes,
+        resblock_dilation_sizes,
+        upsample_rates,
+        upsample_initial_channel,
+        upsample_kernel_sizes,
+        gin_channels,
+        sr,
+        is_half=False,
+    ):
+        super(GeneratorNSF, self).__init__()
+        self.num_kernels = len(resblock_kernel_sizes)
+        self.num_upsamples = len(upsample_rates)
+
+        self.f0_upsamp = torch.nn.Upsample(scale_factor=np.prod(upsample_rates))
+        self.m_source = SourceModuleHnNSF(
+            sampling_rate=sr, harmonic_num=0, is_half=is_half
+        )
+        self.noise_convs = nn.ModuleList()
+        self.conv_pre = Conv1d(
+            initial_channel, upsample_initial_channel, 7, 1, padding=3
+        )
+        resblock = modules.ResBlock1 if resblock == "1" else modules.ResBlock2
+
+        self.ups = nn.ModuleList()
+        for i, (u, k) in enumerate(zip(upsample_rates, upsample_kernel_sizes)):
+            c_cur = upsample_initial_channel // (2 ** (i + 1))
+            self.ups.append(
+                weight_norm(
+                    ConvTranspose1d(
+                        upsample_initial_channel // (2**i),
+                        upsample_initial_channel // (2 ** (i + 1)),
+                        k,
+                        u,
+                        padding=(k - u) // 2,
+                    )
+                )
+            )
+            if i + 1 < len(upsample_rates):
+                stride_f0 = np.prod(upsample_rates[i + 1 :])
+                self.noise_convs.append(
+                    Conv1d(
+                        1,
+                        c_cur,
+                        kernel_size=stride_f0 * 2,
+                        stride=stride_f0,
+                        padding=stride_f0 // 2,
+                    )
+                )
+            else:
+                self.noise_convs.append(Conv1d(1, c_cur, kernel_size=1))
+
+        self.resblocks = nn.ModuleList()
+        for i in range(len(self.ups)):
+            ch = upsample_initial_channel // (2 ** (i + 1))
+            for j, (k, d) in enumerate(
+                zip(resblock_kernel_sizes, resblock_dilation_sizes)
+            ):
+                self.resblocks.append(resblock(ch, k, d))
+
+        self.conv_post = Conv1d(ch, 1, 7, 1, padding=3, bias=False)
+        self.ups.apply(init_weights)
+
+        if gin_channels != 0:
+            self.cond = nn.Conv1d(gin_channels, upsample_initial_channel, 1)
+
+        self.upp = np.prod(upsample_rates)
+
+    def forward(self, x, f0, g=None):
+        har_source, noi_source, uv = self.m_source(f0, self.upp)
+        har_source = har_source.transpose(1, 2)
+        x = self.conv_pre(x)
+        if g is not None:
+            x = x + self.cond(g)
+
+        for i in range(self.num_upsamples):
+            x = F.leaky_relu(x, modules.LRELU_SLOPE)
+            x = self.ups[i](x)
+            x_source = self.noise_convs[i](har_source)
+            x = x + x_source
+            xs = None
+            for j in range(self.num_kernels):
+                if xs is None:
+                    xs = self.resblocks[i * self.num_kernels + j](x)
+                else:
+                    xs += self.resblocks[i * self.num_kernels + j](x)
+            x = xs / self.num_kernels
+        x = F.leaky_relu(x)
+        x = self.conv_post(x)
+        x = torch.tanh(x)
+        return x
+
+    def remove_weight_norm(self):
+        for l in self.ups:
+            remove_weight_norm(l)
+        for l in self.resblocks:
+            l.remove_weight_norm()
+
+
+sr2sr = {
+    "32k": 32000,
+    "40k": 40000,
+    "48k": 48000,
+}
+
+
+class SynthesizerTrnMsNSFsidM(nn.Module):
+    def __init__(
+        self,
+        spec_channels,
+        segment_size,
+        inter_channels,
+        hidden_channels,
+        filter_channels,
+        n_heads,
+        n_layers,
+        kernel_size,
+        p_dropout,
+        resblock,
+        resblock_kernel_sizes,
+        resblock_dilation_sizes,
+        upsample_rates,
+        upsample_initial_channel,
+        upsample_kernel_sizes,
+        spk_embed_dim,
+        gin_channels,
+        sr,
+        version,
+        **kwargs
+    ):
+        super().__init__()
+        if type(sr) == type("strr"):
+            sr = sr2sr[sr]
+        self.spec_channels = spec_channels
+        self.inter_channels = inter_channels
+        self.hidden_channels = hidden_channels
+        self.filter_channels = filter_channels
+        self.n_heads = n_heads
+        self.n_layers = n_layers
+        self.kernel_size = kernel_size
+        self.p_dropout = p_dropout
+        self.resblock = resblock
+        self.resblock_kernel_sizes = resblock_kernel_sizes
+        self.resblock_dilation_sizes = resblock_dilation_sizes
+        self.upsample_rates = upsample_rates
+        self.upsample_initial_channel = upsample_initial_channel
+        self.upsample_kernel_sizes = upsample_kernel_sizes
+        self.segment_size = segment_size
+        self.gin_channels = gin_channels
+        # self.hop_length = hop_length#
+        self.spk_embed_dim = spk_embed_dim
+        if version == "v1":
+            self.enc_p = TextEncoder256(
+                inter_channels,
+                hidden_channels,
+                filter_channels,
+                n_heads,
+                n_layers,
+                kernel_size,
+                p_dropout,
+            )
+        else:
+            self.enc_p = TextEncoder768(
+                inter_channels,
+                hidden_channels,
+                filter_channels,
+                n_heads,
+                n_layers,
+                kernel_size,
+                p_dropout,
+            )
+        self.dec = GeneratorNSF(
+            inter_channels,
+            resblock,
+            resblock_kernel_sizes,
+            resblock_dilation_sizes,
+            upsample_rates,
+            upsample_initial_channel,
+            upsample_kernel_sizes,
+            gin_channels=gin_channels,
+            sr=sr,
+            is_half=kwargs["is_half"],
+        )
+        self.enc_q = PosteriorEncoder(
+            spec_channels,
+            inter_channels,
+            hidden_channels,
+            5,
+            1,
+            16,
+            gin_channels=gin_channels,
+        )
+        self.flow = ResidualCouplingBlock(
+            inter_channels, hidden_channels, 5, 1, 3, gin_channels=gin_channels
+        )
+        self.emb_g = nn.Embedding(self.spk_embed_dim, gin_channels)
+        self.speaker_map = None
+        logger.debug(
+            "gin_channels: "
+            + gin_channels
+            + ", self.spk_embed_dim: "
+            + self.spk_embed_dim
+        )
+
+    def remove_weight_norm(self):
+        self.dec.remove_weight_norm()
+        self.flow.remove_weight_norm()
+        self.enc_q.remove_weight_norm()
+
+    def construct_spkmixmap(self, n_speaker):
+        self.speaker_map = torch.zeros((n_speaker, 1, 1, self.gin_channels))
+        for i in range(n_speaker):
+            self.speaker_map[i] = self.emb_g(torch.LongTensor([[i]]))
+        self.speaker_map = self.speaker_map.unsqueeze(0)
+
+    def forward(self, phone, phone_lengths, pitch, nsff0, g, rnd, max_len=None):
+        if self.speaker_map is not None:  # [N, S]  *  [S, B, 1, H]
+            g = g.reshape((g.shape[0], g.shape[1], 1, 1, 1))  # [N, S, B, 1, 1]
+            g = g * self.speaker_map  # [N, S, B, 1, H]
+            g = torch.sum(g, dim=1)  # [N, 1, B, 1, H]
+            g = g.transpose(0, -1).transpose(0, -2).squeeze(0)  # [B, H, N]
+        else:
+            g = g.unsqueeze(0)
+            g = self.emb_g(g).transpose(1, 2)
+
+        m_p, logs_p, x_mask = self.enc_p(phone, pitch, phone_lengths)
+        z_p = (m_p + torch.exp(logs_p) * rnd) * x_mask
+        z = self.flow(z_p, x_mask, g=g, reverse=True)
+        o = self.dec((z * x_mask)[:, :, :max_len], nsff0, g=g)
+        return o
+
+
+class MultiPeriodDiscriminator(torch.nn.Module):
+    def __init__(self, use_spectral_norm=False):
+        super(MultiPeriodDiscriminator, self).__init__()
+        periods = [2, 3, 5, 7, 11, 17]
+        # periods = [3, 5, 7, 11, 17, 23, 37]
+
+        discs = [DiscriminatorS(use_spectral_norm=use_spectral_norm)]
+        discs = discs + [
+            DiscriminatorP(i, use_spectral_norm=use_spectral_norm) for i in periods
+        ]
+        self.discriminators = nn.ModuleList(discs)
+
+    def forward(self, y, y_hat):
+        y_d_rs = []  #
+        y_d_gs = []
+        fmap_rs = []
+        fmap_gs = []
+        for i, d in enumerate(self.discriminators):
+            y_d_r, fmap_r = d(y)
+            y_d_g, fmap_g = d(y_hat)
+            # for j in range(len(fmap_r)):
+            #     print(i,j,y.shape,y_hat.shape,fmap_r[j].shape,fmap_g[j].shape)
+            y_d_rs.append(y_d_r)
+            y_d_gs.append(y_d_g)
+            fmap_rs.append(fmap_r)
+            fmap_gs.append(fmap_g)
+
+        return y_d_rs, y_d_gs, fmap_rs, fmap_gs
+
+
+class MultiPeriodDiscriminatorV2(torch.nn.Module):
+    def __init__(self, use_spectral_norm=False):
+        super(MultiPeriodDiscriminatorV2, self).__init__()
+        # periods = [2, 3, 5, 7, 11, 17]
+        periods = [2, 3, 5, 7, 11, 17, 23, 37]
+
+        discs = [DiscriminatorS(use_spectral_norm=use_spectral_norm)]
+        discs = discs + [
+            DiscriminatorP(i, use_spectral_norm=use_spectral_norm) for i in periods
+        ]
+        self.discriminators = nn.ModuleList(discs)
+
+    def forward(self, y, y_hat):
+        y_d_rs = []  #
+        y_d_gs = []
+        fmap_rs = []
+        fmap_gs = []
+        for i, d in enumerate(self.discriminators):
+            y_d_r, fmap_r = d(y)
+            y_d_g, fmap_g = d(y_hat)
+            # for j in range(len(fmap_r)):
+            #     print(i,j,y.shape,y_hat.shape,fmap_r[j].shape,fmap_g[j].shape)
+            y_d_rs.append(y_d_r)
+            y_d_gs.append(y_d_g)
+            fmap_rs.append(fmap_r)
+            fmap_gs.append(fmap_g)
+
+        return y_d_rs, y_d_gs, fmap_rs, fmap_gs
+
+
+class DiscriminatorS(torch.nn.Module):
+    def __init__(self, use_spectral_norm=False):
+        super(DiscriminatorS, self).__init__()
+        norm_f = weight_norm if use_spectral_norm == False else spectral_norm
+        self.convs = nn.ModuleList(
+            [
+                norm_f(Conv1d(1, 16, 15, 1, padding=7)),
+                norm_f(Conv1d(16, 64, 41, 4, groups=4, padding=20)),
+                norm_f(Conv1d(64, 256, 41, 4, groups=16, padding=20)),
+                norm_f(Conv1d(256, 1024, 41, 4, groups=64, padding=20)),
+                norm_f(Conv1d(1024, 1024, 41, 4, groups=256, padding=20)),
+                norm_f(Conv1d(1024, 1024, 5, 1, padding=2)),
+            ]
+        )
+        self.conv_post = norm_f(Conv1d(1024, 1, 3, 1, padding=1))
+
+    def forward(self, x):
+        fmap = []
+
+        for l in self.convs:
+            x = l(x)
+            x = F.leaky_relu(x, modules.LRELU_SLOPE)
+            fmap.append(x)
+        x = self.conv_post(x)
+        fmap.append(x)
+        x = torch.flatten(x, 1, -1)
+
+        return x, fmap
+
+
+class DiscriminatorP(torch.nn.Module):
+    def __init__(self, period, kernel_size=5, stride=3, use_spectral_norm=False):
+        super(DiscriminatorP, self).__init__()
+        self.period = period
+        self.use_spectral_norm = use_spectral_norm
+        norm_f = weight_norm if use_spectral_norm == False else spectral_norm
+        self.convs = nn.ModuleList(
+            [
+                norm_f(
+                    Conv2d(
+                        1,
+                        32,
+                        (kernel_size, 1),
+                        (stride, 1),
+                        padding=(get_padding(kernel_size, 1), 0),
+                    )
+                ),
+                norm_f(
+                    Conv2d(
+                        32,
+                        128,
+                        (kernel_size, 1),
+                        (stride, 1),
+                        padding=(get_padding(kernel_size, 1), 0),
+                    )
+                ),
+                norm_f(
+                    Conv2d(
+                        128,
+                        512,
+                        (kernel_size, 1),
+                        (stride, 1),
+                        padding=(get_padding(kernel_size, 1), 0),
+                    )
+                ),
+                norm_f(
+                    Conv2d(
+                        512,
+                        1024,
+                        (kernel_size, 1),
+                        (stride, 1),
+                        padding=(get_padding(kernel_size, 1), 0),
+                    )
+                ),
+                norm_f(
+                    Conv2d(
+                        1024,
+                        1024,
+                        (kernel_size, 1),
+                        1,
+                        padding=(get_padding(kernel_size, 1), 0),
+                    )
+                ),
+            ]
+        )
+        self.conv_post = norm_f(Conv2d(1024, 1, (3, 1), 1, padding=(1, 0)))
+
+    def forward(self, x):
+        fmap = []
+
+        # 1d to 2d
+        b, c, t = x.shape
+        if t % self.period != 0:  # pad first
+            n_pad = self.period - (t % self.period)
+            x = F.pad(x, (0, n_pad), "reflect")
+            t = t + n_pad
+        x = x.view(b, c, t // self.period, self.period)
+
+        for l in self.convs:
+            x = l(x)
+            x = F.leaky_relu(x, modules.LRELU_SLOPE)
+            fmap.append(x)
+        x = self.conv_post(x)
+        fmap.append(x)
+        x = torch.flatten(x, 1, -1)
+
+        return x, fmap
diff --git a/infer/lib/infer_pack/modules.py b/infer/lib/infer_pack/modules.py
new file mode 100644
index 0000000000000000000000000000000000000000..2201a58bee9b7808d386b3ef9ac2d1f9630e56ef
--- /dev/null
+++ b/infer/lib/infer_pack/modules.py
@@ -0,0 +1,521 @@
+import copy
+import math
+
+import numpy as np
+import scipy
+import torch
+from torch import nn
+from torch.nn import AvgPool1d, Conv1d, Conv2d, ConvTranspose1d
+from torch.nn import functional as F
+from torch.nn.utils import remove_weight_norm, weight_norm
+
+from infer.lib.infer_pack import commons
+from infer.lib.infer_pack.commons import get_padding, init_weights
+from infer.lib.infer_pack.transforms import piecewise_rational_quadratic_transform
+
+LRELU_SLOPE = 0.1
+
+
+class LayerNorm(nn.Module):
+    def __init__(self, channels, eps=1e-5):
+        super().__init__()
+        self.channels = channels
+        self.eps = eps
+
+        self.gamma = nn.Parameter(torch.ones(channels))
+        self.beta = nn.Parameter(torch.zeros(channels))
+
+    def forward(self, x):
+        x = x.transpose(1, -1)
+        x = F.layer_norm(x, (self.channels,), self.gamma, self.beta, self.eps)
+        return x.transpose(1, -1)
+
+
+class ConvReluNorm(nn.Module):
+    def __init__(
+        self,
+        in_channels,
+        hidden_channels,
+        out_channels,
+        kernel_size,
+        n_layers,
+        p_dropout,
+    ):
+        super().__init__()
+        self.in_channels = in_channels
+        self.hidden_channels = hidden_channels
+        self.out_channels = out_channels
+        self.kernel_size = kernel_size
+        self.n_layers = n_layers
+        self.p_dropout = p_dropout
+        assert n_layers > 1, "Number of layers should be larger than 0."
+
+        self.conv_layers = nn.ModuleList()
+        self.norm_layers = nn.ModuleList()
+        self.conv_layers.append(
+            nn.Conv1d(
+                in_channels, hidden_channels, kernel_size, padding=kernel_size // 2
+            )
+        )
+        self.norm_layers.append(LayerNorm(hidden_channels))
+        self.relu_drop = nn.Sequential(nn.ReLU(), nn.Dropout(p_dropout))
+        for _ in range(n_layers - 1):
+            self.conv_layers.append(
+                nn.Conv1d(
+                    hidden_channels,
+                    hidden_channels,
+                    kernel_size,
+                    padding=kernel_size // 2,
+                )
+            )
+            self.norm_layers.append(LayerNorm(hidden_channels))
+        self.proj = nn.Conv1d(hidden_channels, out_channels, 1)
+        self.proj.weight.data.zero_()
+        self.proj.bias.data.zero_()
+
+    def forward(self, x, x_mask):
+        x_org = x
+        for i in range(self.n_layers):
+            x = self.conv_layers[i](x * x_mask)
+            x = self.norm_layers[i](x)
+            x = self.relu_drop(x)
+        x = x_org + self.proj(x)
+        return x * x_mask
+
+
+class DDSConv(nn.Module):
+    """
+    Dialted and Depth-Separable Convolution
+    """
+
+    def __init__(self, channels, kernel_size, n_layers, p_dropout=0.0):
+        super().__init__()
+        self.channels = channels
+        self.kernel_size = kernel_size
+        self.n_layers = n_layers
+        self.p_dropout = p_dropout
+
+        self.drop = nn.Dropout(p_dropout)
+        self.convs_sep = nn.ModuleList()
+        self.convs_1x1 = nn.ModuleList()
+        self.norms_1 = nn.ModuleList()
+        self.norms_2 = nn.ModuleList()
+        for i in range(n_layers):
+            dilation = kernel_size**i
+            padding = (kernel_size * dilation - dilation) // 2
+            self.convs_sep.append(
+                nn.Conv1d(
+                    channels,
+                    channels,
+                    kernel_size,
+                    groups=channels,
+                    dilation=dilation,
+                    padding=padding,
+                )
+            )
+            self.convs_1x1.append(nn.Conv1d(channels, channels, 1))
+            self.norms_1.append(LayerNorm(channels))
+            self.norms_2.append(LayerNorm(channels))
+
+    def forward(self, x, x_mask, g=None):
+        if g is not None:
+            x = x + g
+        for i in range(self.n_layers):
+            y = self.convs_sep[i](x * x_mask)
+            y = self.norms_1[i](y)
+            y = F.gelu(y)
+            y = self.convs_1x1[i](y)
+            y = self.norms_2[i](y)
+            y = F.gelu(y)
+            y = self.drop(y)
+            x = x + y
+        return x * x_mask
+
+
+class WN(torch.nn.Module):
+    def __init__(
+        self,
+        hidden_channels,
+        kernel_size,
+        dilation_rate,
+        n_layers,
+        gin_channels=0,
+        p_dropout=0,
+    ):
+        super(WN, self).__init__()
+        assert kernel_size % 2 == 1
+        self.hidden_channels = hidden_channels
+        self.kernel_size = (kernel_size,)
+        self.dilation_rate = dilation_rate
+        self.n_layers = n_layers
+        self.gin_channels = gin_channels
+        self.p_dropout = p_dropout
+
+        self.in_layers = torch.nn.ModuleList()
+        self.res_skip_layers = torch.nn.ModuleList()
+        self.drop = nn.Dropout(p_dropout)
+
+        if gin_channels != 0:
+            cond_layer = torch.nn.Conv1d(
+                gin_channels, 2 * hidden_channels * n_layers, 1
+            )
+            self.cond_layer = torch.nn.utils.weight_norm(cond_layer, name="weight")
+
+        for i in range(n_layers):
+            dilation = dilation_rate**i
+            padding = int((kernel_size * dilation - dilation) / 2)
+            in_layer = torch.nn.Conv1d(
+                hidden_channels,
+                2 * hidden_channels,
+                kernel_size,
+                dilation=dilation,
+                padding=padding,
+            )
+            in_layer = torch.nn.utils.weight_norm(in_layer, name="weight")
+            self.in_layers.append(in_layer)
+
+            # last one is not necessary
+            if i < n_layers - 1:
+                res_skip_channels = 2 * hidden_channels
+            else:
+                res_skip_channels = hidden_channels
+
+            res_skip_layer = torch.nn.Conv1d(hidden_channels, res_skip_channels, 1)
+            res_skip_layer = torch.nn.utils.weight_norm(res_skip_layer, name="weight")
+            self.res_skip_layers.append(res_skip_layer)
+
+    def forward(self, x, x_mask, g=None, **kwargs):
+        output = torch.zeros_like(x)
+        n_channels_tensor = torch.IntTensor([self.hidden_channels])
+
+        if g is not None:
+            g = self.cond_layer(g)
+
+        for i in range(self.n_layers):
+            x_in = self.in_layers[i](x)
+            if g is not None:
+                cond_offset = i * 2 * self.hidden_channels
+                g_l = g[:, cond_offset : cond_offset + 2 * self.hidden_channels, :]
+            else:
+                g_l = torch.zeros_like(x_in)
+
+            acts = commons.fused_add_tanh_sigmoid_multiply(x_in, g_l, n_channels_tensor)
+            acts = self.drop(acts)
+
+            res_skip_acts = self.res_skip_layers[i](acts)
+            if i < self.n_layers - 1:
+                res_acts = res_skip_acts[:, : self.hidden_channels, :]
+                x = (x + res_acts) * x_mask
+                output = output + res_skip_acts[:, self.hidden_channels :, :]
+            else:
+                output = output + res_skip_acts
+        return output * x_mask
+
+    def remove_weight_norm(self):
+        if self.gin_channels != 0:
+            torch.nn.utils.remove_weight_norm(self.cond_layer)
+        for l in self.in_layers:
+            torch.nn.utils.remove_weight_norm(l)
+        for l in self.res_skip_layers:
+            torch.nn.utils.remove_weight_norm(l)
+
+
+class ResBlock1(torch.nn.Module):
+    def __init__(self, channels, kernel_size=3, dilation=(1, 3, 5)):
+        super(ResBlock1, self).__init__()
+        self.convs1 = nn.ModuleList(
+            [
+                weight_norm(
+                    Conv1d(
+                        channels,
+                        channels,
+                        kernel_size,
+                        1,
+                        dilation=dilation[0],
+                        padding=get_padding(kernel_size, dilation[0]),
+                    )
+                ),
+                weight_norm(
+                    Conv1d(
+                        channels,
+                        channels,
+                        kernel_size,
+                        1,
+                        dilation=dilation[1],
+                        padding=get_padding(kernel_size, dilation[1]),
+                    )
+                ),
+                weight_norm(
+                    Conv1d(
+                        channels,
+                        channels,
+                        kernel_size,
+                        1,
+                        dilation=dilation[2],
+                        padding=get_padding(kernel_size, dilation[2]),
+                    )
+                ),
+            ]
+        )
+        self.convs1.apply(init_weights)
+
+        self.convs2 = nn.ModuleList(
+            [
+                weight_norm(
+                    Conv1d(
+                        channels,
+                        channels,
+                        kernel_size,
+                        1,
+                        dilation=1,
+                        padding=get_padding(kernel_size, 1),
+                    )
+                ),
+                weight_norm(
+                    Conv1d(
+                        channels,
+                        channels,
+                        kernel_size,
+                        1,
+                        dilation=1,
+                        padding=get_padding(kernel_size, 1),
+                    )
+                ),
+                weight_norm(
+                    Conv1d(
+                        channels,
+                        channels,
+                        kernel_size,
+                        1,
+                        dilation=1,
+                        padding=get_padding(kernel_size, 1),
+                    )
+                ),
+            ]
+        )
+        self.convs2.apply(init_weights)
+
+    def forward(self, x, x_mask=None):
+        for c1, c2 in zip(self.convs1, self.convs2):
+            xt = F.leaky_relu(x, LRELU_SLOPE)
+            if x_mask is not None:
+                xt = xt * x_mask
+            xt = c1(xt)
+            xt = F.leaky_relu(xt, LRELU_SLOPE)
+            if x_mask is not None:
+                xt = xt * x_mask
+            xt = c2(xt)
+            x = xt + x
+        if x_mask is not None:
+            x = x * x_mask
+        return x
+
+    def remove_weight_norm(self):
+        for l in self.convs1:
+            remove_weight_norm(l)
+        for l in self.convs2:
+            remove_weight_norm(l)
+
+
+class ResBlock2(torch.nn.Module):
+    def __init__(self, channels, kernel_size=3, dilation=(1, 3)):
+        super(ResBlock2, self).__init__()
+        self.convs = nn.ModuleList(
+            [
+                weight_norm(
+                    Conv1d(
+                        channels,
+                        channels,
+                        kernel_size,
+                        1,
+                        dilation=dilation[0],
+                        padding=get_padding(kernel_size, dilation[0]),
+                    )
+                ),
+                weight_norm(
+                    Conv1d(
+                        channels,
+                        channels,
+                        kernel_size,
+                        1,
+                        dilation=dilation[1],
+                        padding=get_padding(kernel_size, dilation[1]),
+                    )
+                ),
+            ]
+        )
+        self.convs.apply(init_weights)
+
+    def forward(self, x, x_mask=None):
+        for c in self.convs:
+            xt = F.leaky_relu(x, LRELU_SLOPE)
+            if x_mask is not None:
+                xt = xt * x_mask
+            xt = c(xt)
+            x = xt + x
+        if x_mask is not None:
+            x = x * x_mask
+        return x
+
+    def remove_weight_norm(self):
+        for l in self.convs:
+            remove_weight_norm(l)
+
+
+class Log(nn.Module):
+    def forward(self, x, x_mask, reverse=False, **kwargs):
+        if not reverse:
+            y = torch.log(torch.clamp_min(x, 1e-5)) * x_mask
+            logdet = torch.sum(-y, [1, 2])
+            return y, logdet
+        else:
+            x = torch.exp(x) * x_mask
+            return x
+
+
+class Flip(nn.Module):
+    def forward(self, x, *args, reverse=False, **kwargs):
+        x = torch.flip(x, [1])
+        if not reverse:
+            logdet = torch.zeros(x.size(0)).to(dtype=x.dtype, device=x.device)
+            return x, logdet
+        else:
+            return x
+
+
+class ElementwiseAffine(nn.Module):
+    def __init__(self, channels):
+        super().__init__()
+        self.channels = channels
+        self.m = nn.Parameter(torch.zeros(channels, 1))
+        self.logs = nn.Parameter(torch.zeros(channels, 1))
+
+    def forward(self, x, x_mask, reverse=False, **kwargs):
+        if not reverse:
+            y = self.m + torch.exp(self.logs) * x
+            y = y * x_mask
+            logdet = torch.sum(self.logs * x_mask, [1, 2])
+            return y, logdet
+        else:
+            x = (x - self.m) * torch.exp(-self.logs) * x_mask
+            return x
+
+
+class ResidualCouplingLayer(nn.Module):
+    def __init__(
+        self,
+        channels,
+        hidden_channels,
+        kernel_size,
+        dilation_rate,
+        n_layers,
+        p_dropout=0,
+        gin_channels=0,
+        mean_only=False,
+    ):
+        assert channels % 2 == 0, "channels should be divisible by 2"
+        super().__init__()
+        self.channels = channels
+        self.hidden_channels = hidden_channels
+        self.kernel_size = kernel_size
+        self.dilation_rate = dilation_rate
+        self.n_layers = n_layers
+        self.half_channels = channels // 2
+        self.mean_only = mean_only
+
+        self.pre = nn.Conv1d(self.half_channels, hidden_channels, 1)
+        self.enc = WN(
+            hidden_channels,
+            kernel_size,
+            dilation_rate,
+            n_layers,
+            p_dropout=p_dropout,
+            gin_channels=gin_channels,
+        )
+        self.post = nn.Conv1d(hidden_channels, self.half_channels * (2 - mean_only), 1)
+        self.post.weight.data.zero_()
+        self.post.bias.data.zero_()
+
+    def forward(self, x, x_mask, g=None, reverse=False):
+        x0, x1 = torch.split(x, [self.half_channels] * 2, 1)
+        h = self.pre(x0) * x_mask
+        h = self.enc(h, x_mask, g=g)
+        stats = self.post(h) * x_mask
+        if not self.mean_only:
+            m, logs = torch.split(stats, [self.half_channels] * 2, 1)
+        else:
+            m = stats
+            logs = torch.zeros_like(m)
+
+        if not reverse:
+            x1 = m + x1 * torch.exp(logs) * x_mask
+            x = torch.cat([x0, x1], 1)
+            logdet = torch.sum(logs, [1, 2])
+            return x, logdet
+        else:
+            x1 = (x1 - m) * torch.exp(-logs) * x_mask
+            x = torch.cat([x0, x1], 1)
+            return x
+
+    def remove_weight_norm(self):
+        self.enc.remove_weight_norm()
+
+
+class ConvFlow(nn.Module):
+    def __init__(
+        self,
+        in_channels,
+        filter_channels,
+        kernel_size,
+        n_layers,
+        num_bins=10,
+        tail_bound=5.0,
+    ):
+        super().__init__()
+        self.in_channels = in_channels
+        self.filter_channels = filter_channels
+        self.kernel_size = kernel_size
+        self.n_layers = n_layers
+        self.num_bins = num_bins
+        self.tail_bound = tail_bound
+        self.half_channels = in_channels // 2
+
+        self.pre = nn.Conv1d(self.half_channels, filter_channels, 1)
+        self.convs = DDSConv(filter_channels, kernel_size, n_layers, p_dropout=0.0)
+        self.proj = nn.Conv1d(
+            filter_channels, self.half_channels * (num_bins * 3 - 1), 1
+        )
+        self.proj.weight.data.zero_()
+        self.proj.bias.data.zero_()
+
+    def forward(self, x, x_mask, g=None, reverse=False):
+        x0, x1 = torch.split(x, [self.half_channels] * 2, 1)
+        h = self.pre(x0)
+        h = self.convs(h, x_mask, g=g)
+        h = self.proj(h) * x_mask
+
+        b, c, t = x0.shape
+        h = h.reshape(b, c, -1, t).permute(0, 1, 3, 2)  # [b, cx?, t] -> [b, c, t, ?]
+
+        unnormalized_widths = h[..., : self.num_bins] / math.sqrt(self.filter_channels)
+        unnormalized_heights = h[..., self.num_bins : 2 * self.num_bins] / math.sqrt(
+            self.filter_channels
+        )
+        unnormalized_derivatives = h[..., 2 * self.num_bins :]
+
+        x1, logabsdet = piecewise_rational_quadratic_transform(
+            x1,
+            unnormalized_widths,
+            unnormalized_heights,
+            unnormalized_derivatives,
+            inverse=reverse,
+            tails="linear",
+            tail_bound=self.tail_bound,
+        )
+
+        x = torch.cat([x0, x1], 1) * x_mask
+        logdet = torch.sum(logabsdet * x_mask, [1, 2])
+        if not reverse:
+            return x, logdet
+        else:
+            return x
diff --git a/infer/lib/infer_pack/modules/F0Predictor/DioF0Predictor.py b/infer/lib/infer_pack/modules/F0Predictor/DioF0Predictor.py
new file mode 100644
index 0000000000000000000000000000000000000000..55abcfdb87636a9ee85b8df5cdc1bec64098b5da
--- /dev/null
+++ b/infer/lib/infer_pack/modules/F0Predictor/DioF0Predictor.py
@@ -0,0 +1,91 @@
+import numpy as np
+import pyworld
+
+from infer.lib.infer_pack.modules.F0Predictor.F0Predictor import F0Predictor
+
+
+class DioF0Predictor(F0Predictor):
+    def __init__(self, hop_length=512, f0_min=50, f0_max=1100, sampling_rate=44100):
+        self.hop_length = hop_length
+        self.f0_min = f0_min
+        self.f0_max = f0_max
+        self.sampling_rate = sampling_rate
+
+    def interpolate_f0(self, f0):
+        """
+        对F0进行插值处理
+        """
+
+        data = np.reshape(f0, (f0.size, 1))
+
+        vuv_vector = np.zeros((data.size, 1), dtype=np.float32)
+        vuv_vector[data > 0.0] = 1.0
+        vuv_vector[data <= 0.0] = 0.0
+
+        ip_data = data
+
+        frame_number = data.size
+        last_value = 0.0
+        for i in range(frame_number):
+            if data[i] <= 0.0:
+                j = i + 1
+                for j in range(i + 1, frame_number):
+                    if data[j] > 0.0:
+                        break
+                if j < frame_number - 1:
+                    if last_value > 0.0:
+                        step = (data[j] - data[i - 1]) / float(j - i)
+                        for k in range(i, j):
+                            ip_data[k] = data[i - 1] + step * (k - i + 1)
+                    else:
+                        for k in range(i, j):
+                            ip_data[k] = data[j]
+                else:
+                    for k in range(i, frame_number):
+                        ip_data[k] = last_value
+            else:
+                ip_data[i] = data[i]  # 这里可能存在一个没有必要的拷贝
+                last_value = data[i]
+
+        return ip_data[:, 0], vuv_vector[:, 0]
+
+    def resize_f0(self, x, target_len):
+        source = np.array(x)
+        source[source < 0.001] = np.nan
+        target = np.interp(
+            np.arange(0, len(source) * target_len, len(source)) / target_len,
+            np.arange(0, len(source)),
+            source,
+        )
+        res = np.nan_to_num(target)
+        return res
+
+    def compute_f0(self, wav, p_len=None):
+        if p_len is None:
+            p_len = wav.shape[0] // self.hop_length
+        f0, t = pyworld.dio(
+            wav.astype(np.double),
+            fs=self.sampling_rate,
+            f0_floor=self.f0_min,
+            f0_ceil=self.f0_max,
+            frame_period=1000 * self.hop_length / self.sampling_rate,
+        )
+        f0 = pyworld.stonemask(wav.astype(np.double), f0, t, self.sampling_rate)
+        for index, pitch in enumerate(f0):
+            f0[index] = round(pitch, 1)
+        return self.interpolate_f0(self.resize_f0(f0, p_len))[0]
+
+    def compute_f0_uv(self, wav, p_len=None):
+        if p_len is None:
+            p_len = wav.shape[0] // self.hop_length
+        f0, t = pyworld.dio(
+            wav.astype(np.double),
+            fs=self.sampling_rate,
+            f0_floor=self.f0_min,
+            f0_ceil=self.f0_max,
+            frame_period=1000 * self.hop_length / self.sampling_rate,
+        )
+        f0 = pyworld.stonemask(wav.astype(np.double), f0, t, self.sampling_rate)
+        for index, pitch in enumerate(f0):
+            f0[index] = round(pitch, 1)
+        return self.interpolate_f0(self.resize_f0(f0, p_len))
diff --git a/infer/lib/infer_pack/modules/F0Predictor/F0Predictor.py b/infer/lib/infer_pack/modules/F0Predictor/F0Predictor.py
new file mode 100644
index 0000000000000000000000000000000000000000..f56e49e7f0e6eab3babf0711cae2933371b9f9cc
--- /dev/null
+++ b/infer/lib/infer_pack/modules/F0Predictor/F0Predictor.py
@@ -0,0 +1,16 @@
+class F0Predictor(object):
+    def compute_f0(self, wav, p_len):
+        """
+        input: wav:[signal_length]
+               p_len:int
+        output: f0:[signal_length//hop_length]
+        """
+        pass
+
+    def compute_f0_uv(self, wav, p_len):
+        """
+        input: wav:[signal_length]
+               p_len:int
+        output: f0:[signal_length//hop_length],uv:[signal_length//hop_length]
+        """
+        pass
diff --git a/infer/lib/infer_pack/modules/F0Predictor/HarvestF0Predictor.py b/infer/lib/infer_pack/modules/F0Predictor/HarvestF0Predictor.py
new file mode 100644
index 0000000000000000000000000000000000000000..f9664fb1f89ef068e923211179e1c7e1ce7fdbd2
--- /dev/null
+++ b/infer/lib/infer_pack/modules/F0Predictor/HarvestF0Predictor.py
@@ -0,0 +1,87 @@
+import numpy as np
+import pyworld
+
+from infer.lib.infer_pack.modules.F0Predictor.F0Predictor import F0Predictor
+
+
+class HarvestF0Predictor(F0Predictor):
+    def __init__(self, hop_length=512, f0_min=50, f0_max=1100, sampling_rate=44100):
+        self.hop_length = hop_length
+        self.f0_min = f0_min
+        self.f0_max = f0_max
+        self.sampling_rate = sampling_rate
+
+    def interpolate_f0(self, f0):
+        """
+        对F0进行插值处理
+        """
+
+        data = np.reshape(f0, (f0.size, 1))
+
+        vuv_vector = np.zeros((data.size, 1), dtype=np.float32)
+        vuv_vector[data > 0.0] = 1.0
+        vuv_vector[data <= 0.0] = 0.0
+
+        ip_data = data
+
+        frame_number = data.size
+        last_value = 0.0
+        for i in range(frame_number):
+            if data[i] <= 0.0:
+                j = i + 1
+                for j in range(i + 1, frame_number):
+                    if data[j] > 0.0:
+                        break
+                if j < frame_number - 1:
+                    if last_value > 0.0:
+                        step = (data[j] - data[i - 1]) / float(j - i)
+                        for k in range(i, j):
+                            ip_data[k] = data[i - 1] + step * (k - i + 1)
+                    else:
+                        for k in range(i, j):
+                            ip_data[k] = data[j]
+                else:
+                    for k in range(i, frame_number):
+                        ip_data[k] = last_value
+            else:
+                ip_data[i] = data[i]  # 这里可能存在一个没有必要的拷贝
+                last_value = data[i]
+
+        return ip_data[:, 0], vuv_vector[:, 0]
+
+    def resize_f0(self, x, target_len):
+        source = np.array(x)
+        source[source < 0.001] = np.nan
+        target = np.interp(
+            np.arange(0, len(source) * target_len, len(source)) / target_len,
+            np.arange(0, len(source)),
+            source,
+        )
+        res = np.nan_to_num(target)
+        return res
+
+    def compute_f0(self, wav, p_len=None):
+        if p_len is None:
+            p_len = wav.shape[0] // self.hop_length
+        f0, t = pyworld.harvest(
+            wav.astype(np.double),
+            fs=self.hop_length,
+            f0_ceil=self.f0_max,
+            f0_floor=self.f0_min,
+            frame_period=1000 * self.hop_length / self.sampling_rate,
+        )
+        f0 = pyworld.stonemask(wav.astype(np.double), f0, t, self.fs)
+        return self.interpolate_f0(self.resize_f0(f0, p_len))[0]
+
+    def compute_f0_uv(self, wav, p_len=None):
+        if p_len is None:
+            p_len = wav.shape[0] // self.hop_length
+        f0, t = pyworld.harvest(
+            wav.astype(np.double),
+            fs=self.sampling_rate,
+            f0_floor=self.f0_min,
+            f0_ceil=self.f0_max,
+            frame_period=1000 * self.hop_length / self.sampling_rate,
+        )
+        f0 = pyworld.stonemask(wav.astype(np.double), f0, t, self.sampling_rate)
+        return self.interpolate_f0(self.resize_f0(f0, p_len))
diff --git a/infer/lib/infer_pack/modules/F0Predictor/PMF0Predictor.py b/infer/lib/infer_pack/modules/F0Predictor/PMF0Predictor.py
new file mode 100644
index 0000000000000000000000000000000000000000..06f2b79f5e5c6f2049bf8220c29ae20c3f82d524
--- /dev/null
+++ b/infer/lib/infer_pack/modules/F0Predictor/PMF0Predictor.py
@@ -0,0 +1,98 @@
+import numpy as np
+import parselmouth
+
+from infer.lib.infer_pack.modules.F0Predictor.F0Predictor import F0Predictor
+
+
+class PMF0Predictor(F0Predictor):
+    def __init__(self, hop_length=512, f0_min=50, f0_max=1100, sampling_rate=44100):
+        self.hop_length = hop_length
+        self.f0_min = f0_min
+        self.f0_max = f0_max
+        self.sampling_rate = sampling_rate
+
+    def interpolate_f0(self, f0):
+        """
+        对F0进行插值处理
+        """
+
+        data = np.reshape(f0, (f0.size, 1))
+
+        vuv_vector = np.zeros((data.size, 1), dtype=np.float32)
+        vuv_vector[data > 0.0] = 1.0
+        vuv_vector[data <= 0.0] = 0.0
+
+        ip_data = data
+
+        frame_number = data.size
+        last_value = 0.0
+        for i in range(frame_number):
+            if data[i] <= 0.0:
+                j = i + 1
+                for j in range(i + 1, frame_number):
+                    if data[j] > 0.0:
+                        break
+                if j < frame_number - 1:
+                    if last_value > 0.0:
+                        step = (data[j] - data[i - 1]) / float(j - i)
+                        for k in range(i, j):
+                            ip_data[k] = data[i - 1] + step * (k - i + 1)
+                    else:
+                        for k in range(i, j):
+                            ip_data[k] = data[j]
+                else:
+                    for k in range(i, frame_number):
+                        ip_data[k] = last_value
+            else:
+                ip_data[i] = data[i]  # 这里可能存在一个没有必要的拷贝
+                last_value = data[i]
+
+        return ip_data[:, 0], vuv_vector[:, 0]
+
+    def compute_f0(self, wav, p_len=None):
+        x = wav
+        if p_len is None:
+            p_len = x.shape[0] // self.hop_length
+        else:
+            assert abs(p_len - x.shape[0] // self.hop_length) < 4, "pad length error"
+        time_step = self.hop_length / self.sampling_rate * 1000
+        f0 = (
+            parselmouth.Sound(x, self.sampling_rate)
+            .to_pitch_ac(
+                time_step=time_step / 1000,
+                voicing_threshold=0.6,
+                pitch_floor=self.f0_min,
+                pitch_ceiling=self.f0_max,
+            )
+            .selected_array["frequency"]
+        )
+
+        pad_size = (p_len - len(f0) + 1) // 2
+        if pad_size > 0 or p_len - len(f0) - pad_size > 0:
+            f0 = np.pad(f0, [[pad_size, p_len - len(f0) - pad_size]], mode="constant")
+        f0, uv = self.interpolate_f0(f0)
+        return f0
+
+    def compute_f0_uv(self, wav, p_len=None):
+        x = wav
+        if p_len is None:
+            p_len = x.shape[0] // self.hop_length
+        else:
+            assert abs(p_len - x.shape[0] // self.hop_length) < 4, "pad length error"
+        time_step = self.hop_length / self.sampling_rate * 1000
+        f0 = (
+            parselmouth.Sound(x, self.sampling_rate)
+            .to_pitch_ac(
+                time_step=time_step / 1000,
+                voicing_threshold=0.6,
+                pitch_floor=self.f0_min,
+                pitch_ceiling=self.f0_max,
+            )
+            .selected_array["frequency"]
+        )
+
+        pad_size = (p_len - len(f0) + 1) // 2
+        if pad_size > 0 or p_len - len(f0) - pad_size > 0:
+            f0 = np.pad(f0, [[pad_size, p_len - len(f0) - pad_size]], mode="constant")
+        f0, uv = self.interpolate_f0(f0)
+        return f0, uv
diff --git a/infer/lib/infer_pack/modules/F0Predictor/__init__.py b/infer/lib/infer_pack/modules/F0Predictor/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/infer/lib/infer_pack/onnx_inference.py b/infer/lib/infer_pack/onnx_inference.py
new file mode 100644
index 0000000000000000000000000000000000000000..6633659fc83b19d82611d3c9cc840e9c547734d0
--- /dev/null
+++ b/infer/lib/infer_pack/onnx_inference.py
@@ -0,0 +1,149 @@
+import librosa
+import numpy as np
+import onnxruntime
+import soundfile
+
+import logging
+
+logger = logging.getLogger(__name__)
+
+
+class ContentVec:
+    def __init__(self, vec_path="pretrained/vec-768-layer-12.onnx", device=None):
+        logger.info("Load model(s) from {}".format(vec_path))
+        if device == "cpu" or device is None:
+            providers = ["CPUExecutionProvider"]
+        elif device == "cuda":
+            providers = ["CUDAExecutionProvider", "CPUExecutionProvider"]
+        elif device == "dml":
+            providers = ["DmlExecutionProvider"]
+        else:
+            raise RuntimeError("Unsportted Device")
+        self.model = onnxruntime.InferenceSession(vec_path, providers=providers)
+
+    def __call__(self, wav):
+        return self.forward(wav)
+
+    def forward(self, wav):
+        feats = wav
+        if feats.ndim == 2:  # double channels
+            feats = feats.mean(-1)
+        assert feats.ndim == 1, feats.ndim
+        feats = np.expand_dims(np.expand_dims(feats, 0), 0)
+        onnx_input = {self.model.get_inputs()[0].name: feats}
+        logits = self.model.run(None, onnx_input)[0]
+        return logits.transpose(0, 2, 1)
+
+
+def get_f0_predictor(f0_predictor, hop_length, sampling_rate, **kargs):
+    if f0_predictor == "pm":
+        from lib.infer_pack.modules.F0Predictor.PMF0Predictor import PMF0Predictor
+
+        f0_predictor_object = PMF0Predictor(
+            hop_length=hop_length, sampling_rate=sampling_rate
+        )
+    elif f0_predictor == "harvest":
+        from lib.infer_pack.modules.F0Predictor.HarvestF0Predictor import (
+            HarvestF0Predictor,
+        )
+
+        f0_predictor_object = HarvestF0Predictor(
+            hop_length=hop_length, sampling_rate=sampling_rate
+        )
+    elif f0_predictor == "dio":
+        from lib.infer_pack.modules.F0Predictor.DioF0Predictor import DioF0Predictor
+
+        f0_predictor_object = DioF0Predictor(
+            hop_length=hop_length, sampling_rate=sampling_rate
+        )
+    else:
+        raise Exception("Unknown f0 predictor")
+    return f0_predictor_object
+
+
+class OnnxRVC:
+    def __init__(
+        self,
+        model_path,
+        sr=40000,
+        hop_size=512,
+        vec_path="vec-768-layer-12",
+        device="cpu",
+    ):
+        vec_path = f"pretrained/{vec_path}.onnx"
+        self.vec_model = ContentVec(vec_path, device)
+        if device == "cpu" or device is None:
+            providers = ["CPUExecutionProvider"]
+        elif device == "cuda":
+            providers = ["CUDAExecutionProvider", "CPUExecutionProvider"]
+        elif device == "dml":
+            providers = ["DmlExecutionProvider"]
+        else:
+            raise RuntimeError("Unsportted Device")
+        self.model = onnxruntime.InferenceSession(model_path, providers=providers)
+        self.sampling_rate = sr
+        self.hop_size = hop_size
+
+    def forward(self, hubert, hubert_length, pitch, pitchf, ds, rnd):
+        onnx_input = {
+            self.model.get_inputs()[0].name: hubert,
+            self.model.get_inputs()[1].name: hubert_length,
+            self.model.get_inputs()[2].name: pitch,
+            self.model.get_inputs()[3].name: pitchf,
+            self.model.get_inputs()[4].name: ds,
+            self.model.get_inputs()[5].name: rnd,
+        }
+        return (self.model.run(None, onnx_input)[0] * 32767).astype(np.int16)
+
+    def inference(
+        self,
+        raw_path,
+        sid,
+        f0_method="dio",
+        f0_up_key=0,
+        pad_time=0.5,
+        cr_threshold=0.02,
+    ):
+        f0_min = 50
+        f0_max = 1100
+        f0_mel_min = 1127 * np.log(1 + f0_min / 700)
+        f0_mel_max = 1127 * np.log(1 + f0_max / 700)
+        f0_predictor = get_f0_predictor(
+            f0_method,
+            hop_length=self.hop_size,
+            sampling_rate=self.sampling_rate,
+            threshold=cr_threshold,
+        )
+        wav, sr = librosa.load(raw_path, sr=self.sampling_rate)
+        org_length = len(wav)
+        if org_length / sr > 50.0:
+            raise RuntimeError("Reached Max Length")
+
+        wav16k = librosa.resample(wav, orig_sr=self.sampling_rate, target_sr=16000)
+        wav16k = wav16k
+
+        hubert = self.vec_model(wav16k)
+        hubert = np.repeat(hubert, 2, axis=2).transpose(0, 2, 1).astype(np.float32)
+        hubert_length = hubert.shape[1]
+
+        pitchf = f0_predictor.compute_f0(wav, hubert_length)
+        pitchf = pitchf * 2 ** (f0_up_key / 12)
+        pitch = pitchf.copy()
+        f0_mel = 1127 * np.log(1 + pitch / 700)
+        f0_mel[f0_mel > 0] = (f0_mel[f0_mel > 0] - f0_mel_min) * 254 / (
+            f0_mel_max - f0_mel_min
+        ) + 1
+        f0_mel[f0_mel <= 1] = 1
+        f0_mel[f0_mel > 255] = 255
+        pitch = np.rint(f0_mel).astype(np.int64)
+
+        pitchf = pitchf.reshape(1, len(pitchf)).astype(np.float32)
+        pitch = pitch.reshape(1, len(pitch))
+        ds = np.array([sid]).astype(np.int64)
+
+        rnd = np.random.randn(1, 192, hubert_length).astype(np.float32)
+        hubert_length = np.array([hubert_length]).astype(np.int64)
+
+        out_wav = self.forward(hubert, hubert_length, pitch, pitchf, ds, rnd).squeeze()
+        out_wav = np.pad(out_wav, (0, 2 * self.hop_size), "constant")
+        return out_wav[0:org_length]
diff --git a/infer/lib/infer_pack/transforms.py b/infer/lib/infer_pack/transforms.py
new file mode 100644
index 0000000000000000000000000000000000000000..6f30b7177d17fc61a4173c21b4233172a890be58
--- /dev/null
+++ b/infer/lib/infer_pack/transforms.py
@@ -0,0 +1,207 @@
+import numpy as np
+import torch
+from torch.nn import functional as F
+
+DEFAULT_MIN_BIN_WIDTH = 1e-3
+DEFAULT_MIN_BIN_HEIGHT = 1e-3
+DEFAULT_MIN_DERIVATIVE = 1e-3
+
+
+def piecewise_rational_quadratic_transform(
+    inputs,
+    unnormalized_widths,
+    unnormalized_heights,
+    unnormalized_derivatives,
+    inverse=False,
+    tails=None,
+    tail_bound=1.0,
+    min_bin_width=DEFAULT_MIN_BIN_WIDTH,
+    min_bin_height=DEFAULT_MIN_BIN_HEIGHT,
+    min_derivative=DEFAULT_MIN_DERIVATIVE,
+):
+    if tails is None:
+        spline_fn = rational_quadratic_spline
+        spline_kwargs = {}
+    else:
+        spline_fn = unconstrained_rational_quadratic_spline
+        spline_kwargs = {"tails": tails, "tail_bound": tail_bound}
+
+    outputs, logabsdet = spline_fn(
+        inputs=inputs,
+        unnormalized_widths=unnormalized_widths,
+        unnormalized_heights=unnormalized_heights,
+        unnormalized_derivatives=unnormalized_derivatives,
+        inverse=inverse,
+        min_bin_width=min_bin_width,
+        min_bin_height=min_bin_height,
+        min_derivative=min_derivative,
+        **spline_kwargs
+    )
+    return outputs, logabsdet
+
+
+def searchsorted(bin_locations, inputs, eps=1e-6):
+    bin_locations[..., -1] += eps
+    return torch.sum(inputs[..., None] >= bin_locations, dim=-1) - 1
+
+
+def unconstrained_rational_quadratic_spline(
+    inputs,
+    unnormalized_widths,
+    unnormalized_heights,
+    unnormalized_derivatives,
+    inverse=False,
+    tails="linear",
+    tail_bound=1.0,
+    min_bin_width=DEFAULT_MIN_BIN_WIDTH,
+    min_bin_height=DEFAULT_MIN_BIN_HEIGHT,
+    min_derivative=DEFAULT_MIN_DERIVATIVE,
+):
+    inside_interval_mask = (inputs >= -tail_bound) & (inputs <= tail_bound)
+    outside_interval_mask = ~inside_interval_mask
+
+    outputs = torch.zeros_like(inputs)
+    logabsdet = torch.zeros_like(inputs)
+
+    if tails == "linear":
+        unnormalized_derivatives = F.pad(unnormalized_derivatives, pad=(1, 1))
+        constant = np.log(np.exp(1 - min_derivative) - 1)
+        unnormalized_derivatives[..., 0] = constant
+        unnormalized_derivatives[..., -1] = constant
+
+        outputs[outside_interval_mask] = inputs[outside_interval_mask]
+        logabsdet[outside_interval_mask] = 0
+    else:
+        raise RuntimeError("{} tails are not implemented.".format(tails))
+
+    (
+        outputs[inside_interval_mask],
+        logabsdet[inside_interval_mask],
+    ) = rational_quadratic_spline(
+        inputs=inputs[inside_interval_mask],
+        unnormalized_widths=unnormalized_widths[inside_interval_mask, :],
+        unnormalized_heights=unnormalized_heights[inside_interval_mask, :],
+        unnormalized_derivatives=unnormalized_derivatives[inside_interval_mask, :],
+        inverse=inverse,
+        left=-tail_bound,
+        right=tail_bound,
+        bottom=-tail_bound,
+        top=tail_bound,
+        min_bin_width=min_bin_width,
+        min_bin_height=min_bin_height,
+        min_derivative=min_derivative,
+    )
+
+    return outputs, logabsdet
+
+
+def rational_quadratic_spline(
+    inputs,
+    unnormalized_widths,
+    unnormalized_heights,
+    unnormalized_derivatives,
+    inverse=False,
+    left=0.0,
+    right=1.0,
+    bottom=0.0,
+    top=1.0,
+    min_bin_width=DEFAULT_MIN_BIN_WIDTH,
+    min_bin_height=DEFAULT_MIN_BIN_HEIGHT,
+    min_derivative=DEFAULT_MIN_DERIVATIVE,
+):
+    if torch.min(inputs) < left or torch.max(inputs) > right:
+        raise ValueError("Input to a transform is not within its domain")
+
+    num_bins = unnormalized_widths.shape[-1]
+
+    if min_bin_width * num_bins > 1.0:
+        raise ValueError("Minimal bin width too large for the number of bins")
+    if min_bin_height * num_bins > 1.0:
+        raise ValueError("Minimal bin height too large for the number of bins")
+
+    widths = F.softmax(unnormalized_widths, dim=-1)
+    widths = min_bin_width + (1 - min_bin_width * num_bins) * widths
+    cumwidths = torch.cumsum(widths, dim=-1)
+    cumwidths = F.pad(cumwidths, pad=(1, 0), mode="constant", value=0.0)
+    cumwidths = (right - left) * cumwidths + left
+    cumwidths[..., 0] = left
+    cumwidths[..., -1] = right
+    widths = cumwidths[..., 1:] - cumwidths[..., :-1]
+
+    derivatives = min_derivative + F.softplus(unnormalized_derivatives)
+
+    heights = F.softmax(unnormalized_heights, dim=-1)
+    heights = min_bin_height + (1 - min_bin_height * num_bins) * heights
+    cumheights = torch.cumsum(heights, dim=-1)
+    cumheights = F.pad(cumheights, pad=(1, 0), mode="constant", value=0.0)
+    cumheights = (top - bottom) * cumheights + bottom
+    cumheights[..., 0] = bottom
+    cumheights[..., -1] = top
+    heights = cumheights[..., 1:] - cumheights[..., :-1]
+
+    if inverse:
+        bin_idx = searchsorted(cumheights, inputs)[..., None]
+    else:
+        bin_idx = searchsorted(cumwidths, inputs)[..., None]
+
+    input_cumwidths = cumwidths.gather(-1, bin_idx)[..., 0]
+    input_bin_widths = widths.gather(-1, bin_idx)[..., 0]
+
+    input_cumheights = cumheights.gather(-1, bin_idx)[..., 0]
+    delta = heights / widths
+    input_delta = delta.gather(-1, bin_idx)[..., 0]
+
+    input_derivatives = derivatives.gather(-1, bin_idx)[..., 0]
+    input_derivatives_plus_one = derivatives[..., 1:].gather(-1, bin_idx)[..., 0]
+
+    input_heights = heights.gather(-1, bin_idx)[..., 0]
+
+    if inverse:
+        a = (inputs - input_cumheights) * (
+            input_derivatives + input_derivatives_plus_one - 2 * input_delta
+        ) + input_heights * (input_delta - input_derivatives)
+        b = input_heights * input_derivatives - (inputs - input_cumheights) * (
+            input_derivatives + input_derivatives_plus_one - 2 * input_delta
+        )
+        c = -input_delta * (inputs - input_cumheights)
+
+        discriminant = b.pow(2) - 4 * a * c
+        assert (discriminant >= 0).all()
+
+        root = (2 * c) / (-b - torch.sqrt(discriminant))
+        outputs = root * input_bin_widths + input_cumwidths
+
+        theta_one_minus_theta = root * (1 - root)
+        denominator = input_delta + (
+            (input_derivatives + input_derivatives_plus_one - 2 * input_delta)
+            * theta_one_minus_theta
+        )
+        derivative_numerator = input_delta.pow(2) * (
+            input_derivatives_plus_one * root.pow(2)
+            + 2 * input_delta * theta_one_minus_theta
+            + input_derivatives * (1 - root).pow(2)
+        )
+        logabsdet = torch.log(derivative_numerator) - 2 * torch.log(denominator)
+
+        return outputs, -logabsdet
+    else:
+        theta = (inputs - input_cumwidths) / input_bin_widths
+        theta_one_minus_theta = theta * (1 - theta)
+
+        numerator = input_heights * (
+            input_delta * theta.pow(2) + input_derivatives * theta_one_minus_theta
+        )
+        denominator = input_delta + (
+            (input_derivatives + input_derivatives_plus_one - 2 * input_delta)
+            * theta_one_minus_theta
+        )
+        outputs = input_cumheights + numerator / denominator
+
+        derivative_numerator = input_delta.pow(2) * (
+            input_derivatives_plus_one * theta.pow(2)
+            + 2 * input_delta * theta_one_minus_theta
+            + input_derivatives * (1 - theta).pow(2)
+        )
+        logabsdet = torch.log(derivative_numerator) - 2 * torch.log(denominator)
+
+        return outputs, logabsdet
diff --git a/infer/lib/rmvpe.py b/infer/lib/rmvpe.py
new file mode 100644
index 0000000000000000000000000000000000000000..2a387ebe73c7e1dd8bb7ccad1ea9e0ea89848ece
--- /dev/null
+++ b/infer/lib/rmvpe.py
@@ -0,0 +1,717 @@
+import pdb, os
+
+import numpy as np
+import torch
+try:
+    #Fix "Torch not compiled with CUDA enabled"
+    import intel_extension_for_pytorch as ipex # pylint: disable=import-error, unused-import
+    if torch.xpu.is_available():
+        from infer.modules.ipex import ipex_init
+        ipex_init()
+except Exception:
+    pass
+import torch.nn as nn
+import torch.nn.functional as F
+from librosa.util import normalize, pad_center, tiny
+from scipy.signal import get_window
+
+import logging
+
+logger = logging.getLogger(__name__)
+
+
+###stft codes from https://github.com/pseeth/torch-stft/blob/master/torch_stft/util.py
+def window_sumsquare(
+    window,
+    n_frames,
+    hop_length=200,
+    win_length=800,
+    n_fft=800,
+    dtype=np.float32,
+    norm=None,
+):
+    """
+    # from librosa 0.6
+    Compute the sum-square envelope of a window function at a given hop length.
+    This is used to estimate modulation effects induced by windowing
+    observations in short-time fourier transforms.
+    Parameters
+    ----------
+    window : string, tuple, number, callable, or list-like
+        Window specification, as in `get_window`
+    n_frames : int > 0
+        The number of analysis frames
+    hop_length : int > 0
+        The number of samples to advance between frames
+    win_length : [optional]
+        The length of the window function.  By default, this matches `n_fft`.
+    n_fft : int > 0
+        The length of each analysis frame.
+    dtype : np.dtype
+        The data type of the output
+    Returns
+    -------
+    wss : np.ndarray, shape=`(n_fft + hop_length * (n_frames - 1))`
+        The sum-squared envelope of the window function
+    """
+    if win_length is None:
+        win_length = n_fft
+
+    n = n_fft + hop_length * (n_frames - 1)
+    x = np.zeros(n, dtype=dtype)
+
+    # Compute the squared window at the desired length
+    win_sq = get_window(window, win_length, fftbins=True)
+    win_sq = normalize(win_sq, norm=norm) ** 2
+    win_sq = pad_center(win_sq, n_fft)
+
+    # Fill the envelope
+    for i in range(n_frames):
+        sample = i * hop_length
+        x[sample : min(n, sample + n_fft)] += win_sq[: max(0, min(n_fft, n - sample))]
+    return x
+
+
+class STFT(torch.nn.Module):
+    def __init__(
+        self, filter_length=1024, hop_length=512, win_length=None, window="hann"
+    ):
+        """
+        This module implements an STFT using 1D convolution and 1D transpose convolutions.
+        This is a bit tricky so there are some cases that probably won't work as working
+        out the same sizes before and after in all overlap add setups is tough. Right now,
+        this code should work with hop lengths that are half the filter length (50% overlap
+        between frames).
+
+        Keyword Arguments:
+            filter_length {int} -- Length of filters used (default: {1024})
+            hop_length {int} -- Hop length of STFT (restrict to 50% overlap between frames) (default: {512})
+            win_length {[type]} -- Length of the window function applied to each frame (if not specified, it
+                equals the filter length). (default: {None})
+            window {str} -- Type of window to use (options are bartlett, hann, hamming, blackman, blackmanharris)
+                (default: {'hann'})
+        """
+        super(STFT, self).__init__()
+        self.filter_length = filter_length
+        self.hop_length = hop_length
+        self.win_length = win_length if win_length else filter_length
+        self.window = window
+        self.forward_transform = None
+        self.pad_amount = int(self.filter_length / 2)
+        scale = self.filter_length / self.hop_length
+        fourier_basis = np.fft.fft(np.eye(self.filter_length))
+
+        cutoff = int((self.filter_length / 2 + 1))
+        fourier_basis = np.vstack(
+            [np.real(fourier_basis[:cutoff, :]), np.imag(fourier_basis[:cutoff, :])]
+        )
+        forward_basis = torch.FloatTensor(fourier_basis[:, None, :])
+        inverse_basis = torch.FloatTensor(
+            np.linalg.pinv(scale * fourier_basis).T[:, None, :]
+        )
+
+        assert filter_length >= self.win_length
+        # get window and zero center pad it to filter_length
+        fft_window = get_window(window, self.win_length, fftbins=True)
+        fft_window = pad_center(fft_window, size=filter_length)
+        fft_window = torch.from_numpy(fft_window).float()
+
+        # window the bases
+        forward_basis *= fft_window
+        inverse_basis *= fft_window
+
+        self.register_buffer("forward_basis", forward_basis.float())
+        self.register_buffer("inverse_basis", inverse_basis.float())
+
+    def transform(self, input_data):
+        """Take input data (audio) to STFT domain.
+
+        Arguments:
+            input_data {tensor} -- Tensor of floats, with shape (num_batch, num_samples)
+
+        Returns:
+            magnitude {tensor} -- Magnitude of STFT with shape (num_batch,
+                num_frequencies, num_frames)
+            phase {tensor} -- Phase of STFT with shape (num_batch,
+                num_frequencies, num_frames)
+        """
+        num_batches = input_data.shape[0]
+        num_samples = input_data.shape[-1]
+
+        self.num_samples = num_samples
+
+        # similar to librosa, reflect-pad the input
+        input_data = input_data.view(num_batches, 1, num_samples)
+        # print(1234,input_data.shape)
+        input_data = F.pad(
+            input_data.unsqueeze(1),
+            (self.pad_amount, self.pad_amount, 0, 0, 0, 0),
+            mode="reflect",
+        ).squeeze(1)
+        # print(2333,input_data.shape,self.forward_basis.shape,self.hop_length)
+        # pdb.set_trace()
+        forward_transform = F.conv1d(
+            input_data, self.forward_basis, stride=self.hop_length, padding=0
+        )
+
+        cutoff = int((self.filter_length / 2) + 1)
+        real_part = forward_transform[:, :cutoff, :]
+        imag_part = forward_transform[:, cutoff:, :]
+
+        magnitude = torch.sqrt(real_part**2 + imag_part**2)
+        # phase = torch.atan2(imag_part.data, real_part.data)
+
+        return magnitude  # , phase
+
+    def inverse(self, magnitude, phase):
+        """Call the inverse STFT (iSTFT), given magnitude and phase tensors produced
+        by the ```transform``` function.
+
+        Arguments:
+            magnitude {tensor} -- Magnitude of STFT with shape (num_batch,
+                num_frequencies, num_frames)
+            phase {tensor} -- Phase of STFT with shape (num_batch,
+                num_frequencies, num_frames)
+
+        Returns:
+            inverse_transform {tensor} -- Reconstructed audio given magnitude and phase. Of
+                shape (num_batch, num_samples)
+        """
+        recombine_magnitude_phase = torch.cat(
+            [magnitude * torch.cos(phase), magnitude * torch.sin(phase)], dim=1
+        )
+
+        inverse_transform = F.conv_transpose1d(
+            recombine_magnitude_phase,
+            self.inverse_basis,
+            stride=self.hop_length,
+            padding=0,
+        )
+
+        if self.window is not None:
+            window_sum = window_sumsquare(
+                self.window,
+                magnitude.size(-1),
+                hop_length=self.hop_length,
+                win_length=self.win_length,
+                n_fft=self.filter_length,
+                dtype=np.float32,
+            )
+            # remove modulation effects
+            approx_nonzero_indices = torch.from_numpy(
+                np.where(window_sum > tiny(window_sum))[0]
+            )
+            window_sum = torch.from_numpy(window_sum).to(inverse_transform.device)
+            inverse_transform[:, :, approx_nonzero_indices] /= window_sum[
+                approx_nonzero_indices
+            ]
+
+            # scale by hop ratio
+            inverse_transform *= float(self.filter_length) / self.hop_length
+
+        inverse_transform = inverse_transform[..., self.pad_amount :]
+        inverse_transform = inverse_transform[..., : self.num_samples]
+        inverse_transform = inverse_transform.squeeze(1)
+
+        return inverse_transform
+
+    def forward(self, input_data):
+        """Take input data (audio) to STFT domain and then back to audio.
+
+        Arguments:
+            input_data {tensor} -- Tensor of floats, with shape (num_batch, num_samples)
+
+        Returns:
+            reconstruction {tensor} -- Reconstructed audio given magnitude and phase. Of
+                shape (num_batch, num_samples)
+        """
+        self.magnitude, self.phase = self.transform(input_data)
+        reconstruction = self.inverse(self.magnitude, self.phase)
+        return reconstruction
+
+
+from time import time as ttime
+
+
+class BiGRU(nn.Module):
+    def __init__(self, input_features, hidden_features, num_layers):
+        super(BiGRU, self).__init__()
+        self.gru = nn.GRU(
+            input_features,
+            hidden_features,
+            num_layers=num_layers,
+            batch_first=True,
+            bidirectional=True,
+        )
+
+    def forward(self, x):
+        return self.gru(x)[0]
+
+
+class ConvBlockRes(nn.Module):
+    def __init__(self, in_channels, out_channels, momentum=0.01):
+        super(ConvBlockRes, self).__init__()
+        self.conv = nn.Sequential(
+            nn.Conv2d(
+                in_channels=in_channels,
+                out_channels=out_channels,
+                kernel_size=(3, 3),
+                stride=(1, 1),
+                padding=(1, 1),
+                bias=False,
+            ),
+            nn.BatchNorm2d(out_channels, momentum=momentum),
+            nn.ReLU(),
+            nn.Conv2d(
+                in_channels=out_channels,
+                out_channels=out_channels,
+                kernel_size=(3, 3),
+                stride=(1, 1),
+                padding=(1, 1),
+                bias=False,
+            ),
+            nn.BatchNorm2d(out_channels, momentum=momentum),
+            nn.ReLU(),
+        )
+        if in_channels != out_channels:
+            self.shortcut = nn.Conv2d(in_channels, out_channels, (1, 1))
+            self.is_shortcut = True
+        else:
+            self.is_shortcut = False
+
+    def forward(self, x):
+        if self.is_shortcut:
+            return self.conv(x) + self.shortcut(x)
+        else:
+            return self.conv(x) + x
+
+
+class Encoder(nn.Module):
+    def __init__(
+        self,
+        in_channels,
+        in_size,
+        n_encoders,
+        kernel_size,
+        n_blocks,
+        out_channels=16,
+        momentum=0.01,
+    ):
+        super(Encoder, self).__init__()
+        self.n_encoders = n_encoders
+        self.bn = nn.BatchNorm2d(in_channels, momentum=momentum)
+        self.layers = nn.ModuleList()
+        self.latent_channels = []
+        for i in range(self.n_encoders):
+            self.layers.append(
+                ResEncoderBlock(
+                    in_channels, out_channels, kernel_size, n_blocks, momentum=momentum
+                )
+            )
+            self.latent_channels.append([out_channels, in_size])
+            in_channels = out_channels
+            out_channels *= 2
+            in_size //= 2
+        self.out_size = in_size
+        self.out_channel = out_channels
+
+    def forward(self, x):
+        concat_tensors = []
+        x = self.bn(x)
+        for i in range(self.n_encoders):
+            _, x = self.layers[i](x)
+            concat_tensors.append(_)
+        return x, concat_tensors
+
+
+class ResEncoderBlock(nn.Module):
+    def __init__(
+        self, in_channels, out_channels, kernel_size, n_blocks=1, momentum=0.01
+    ):
+        super(ResEncoderBlock, self).__init__()
+        self.n_blocks = n_blocks
+        self.conv = nn.ModuleList()
+        self.conv.append(ConvBlockRes(in_channels, out_channels, momentum))
+        for i in range(n_blocks - 1):
+            self.conv.append(ConvBlockRes(out_channels, out_channels, momentum))
+        self.kernel_size = kernel_size
+        if self.kernel_size is not None:
+            self.pool = nn.AvgPool2d(kernel_size=kernel_size)
+
+    def forward(self, x):
+        for i in range(self.n_blocks):
+            x = self.conv[i](x)
+        if self.kernel_size is not None:
+            return x, self.pool(x)
+        else:
+            return x
+
+
+class Intermediate(nn.Module):  #
+    def __init__(self, in_channels, out_channels, n_inters, n_blocks, momentum=0.01):
+        super(Intermediate, self).__init__()
+        self.n_inters = n_inters
+        self.layers = nn.ModuleList()
+        self.layers.append(
+            ResEncoderBlock(in_channels, out_channels, None, n_blocks, momentum)
+        )
+        for i in range(self.n_inters - 1):
+            self.layers.append(
+                ResEncoderBlock(out_channels, out_channels, None, n_blocks, momentum)
+            )
+
+    def forward(self, x):
+        for i in range(self.n_inters):
+            x = self.layers[i](x)
+        return x
+
+
+class ResDecoderBlock(nn.Module):
+    def __init__(self, in_channels, out_channels, stride, n_blocks=1, momentum=0.01):
+        super(ResDecoderBlock, self).__init__()
+        out_padding = (0, 1) if stride == (1, 2) else (1, 1)
+        self.n_blocks = n_blocks
+        self.conv1 = nn.Sequential(
+            nn.ConvTranspose2d(
+                in_channels=in_channels,
+                out_channels=out_channels,
+                kernel_size=(3, 3),
+                stride=stride,
+                padding=(1, 1),
+                output_padding=out_padding,
+                bias=False,
+            ),
+            nn.BatchNorm2d(out_channels, momentum=momentum),
+            nn.ReLU(),
+        )
+        self.conv2 = nn.ModuleList()
+        self.conv2.append(ConvBlockRes(out_channels * 2, out_channels, momentum))
+        for i in range(n_blocks - 1):
+            self.conv2.append(ConvBlockRes(out_channels, out_channels, momentum))
+
+    def forward(self, x, concat_tensor):
+        x = self.conv1(x)
+        x = torch.cat((x, concat_tensor), dim=1)
+        for i in range(self.n_blocks):
+            x = self.conv2[i](x)
+        return x
+
+
+class Decoder(nn.Module):
+    def __init__(self, in_channels, n_decoders, stride, n_blocks, momentum=0.01):
+        super(Decoder, self).__init__()
+        self.layers = nn.ModuleList()
+        self.n_decoders = n_decoders
+        for i in range(self.n_decoders):
+            out_channels = in_channels // 2
+            self.layers.append(
+                ResDecoderBlock(in_channels, out_channels, stride, n_blocks, momentum)
+            )
+            in_channels = out_channels
+
+    def forward(self, x, concat_tensors):
+        for i in range(self.n_decoders):
+            x = self.layers[i](x, concat_tensors[-1 - i])
+        return x
+
+
+class DeepUnet(nn.Module):
+    def __init__(
+        self,
+        kernel_size,
+        n_blocks,
+        en_de_layers=5,
+        inter_layers=4,
+        in_channels=1,
+        en_out_channels=16,
+    ):
+        super(DeepUnet, self).__init__()
+        self.encoder = Encoder(
+            in_channels, 128, en_de_layers, kernel_size, n_blocks, en_out_channels
+        )
+        self.intermediate = Intermediate(
+            self.encoder.out_channel // 2,
+            self.encoder.out_channel,
+            inter_layers,
+            n_blocks,
+        )
+        self.decoder = Decoder(
+            self.encoder.out_channel, en_de_layers, kernel_size, n_blocks
+        )
+
+    def forward(self, x):
+        x, concat_tensors = self.encoder(x)
+        x = self.intermediate(x)
+        x = self.decoder(x, concat_tensors)
+        return x
+
+
+class E2E(nn.Module):
+    def __init__(
+        self,
+        n_blocks,
+        n_gru,
+        kernel_size,
+        en_de_layers=5,
+        inter_layers=4,
+        in_channels=1,
+        en_out_channels=16,
+    ):
+        super(E2E, self).__init__()
+        self.unet = DeepUnet(
+            kernel_size,
+            n_blocks,
+            en_de_layers,
+            inter_layers,
+            in_channels,
+            en_out_channels,
+        )
+        self.cnn = nn.Conv2d(en_out_channels, 3, (3, 3), padding=(1, 1))
+        if n_gru:
+            self.fc = nn.Sequential(
+                BiGRU(3 * 128, 256, n_gru),
+                nn.Linear(512, 360),
+                nn.Dropout(0.25),
+                nn.Sigmoid(),
+            )
+        else:
+            self.fc = nn.Sequential(
+                nn.Linear(3 * nn.N_MELS, nn.N_CLASS), nn.Dropout(0.25), nn.Sigmoid()
+            )
+
+    def forward(self, mel):
+        # print(mel.shape)
+        mel = mel.transpose(-1, -2).unsqueeze(1)
+        x = self.cnn(self.unet(mel)).transpose(1, 2).flatten(-2)
+        x = self.fc(x)
+        # print(x.shape)
+        return x
+
+
+from librosa.filters import mel
+
+
+class MelSpectrogram(torch.nn.Module):
+    def __init__(
+        self,
+        is_half,
+        n_mel_channels,
+        sampling_rate,
+        win_length,
+        hop_length,
+        n_fft=None,
+        mel_fmin=0,
+        mel_fmax=None,
+        clamp=1e-5,
+    ):
+        super().__init__()
+        n_fft = win_length if n_fft is None else n_fft
+        self.hann_window = {}
+        mel_basis = mel(
+            sr=sampling_rate,
+            n_fft=n_fft,
+            n_mels=n_mel_channels,
+            fmin=mel_fmin,
+            fmax=mel_fmax,
+            htk=True,
+        )
+        mel_basis = torch.from_numpy(mel_basis).float()
+        self.register_buffer("mel_basis", mel_basis)
+        self.n_fft = win_length if n_fft is None else n_fft
+        self.hop_length = hop_length
+        self.win_length = win_length
+        self.sampling_rate = sampling_rate
+        self.n_mel_channels = n_mel_channels
+        self.clamp = clamp
+        self.is_half = is_half
+
+    def forward(self, audio, keyshift=0, speed=1, center=True):
+        factor = 2 ** (keyshift / 12)
+        n_fft_new = int(np.round(self.n_fft * factor))
+        win_length_new = int(np.round(self.win_length * factor))
+        hop_length_new = int(np.round(self.hop_length * speed))
+        keyshift_key = str(keyshift) + "_" + str(audio.device)
+        if keyshift_key not in self.hann_window:
+            self.hann_window[keyshift_key] = torch.hann_window(win_length_new).to(
+                # "cpu"if(audio.device.type=="privateuseone") else audio.device
+                audio.device
+            )
+        # fft = torch.stft(#doesn't support pytorch_dml
+        #     # audio.cpu() if(audio.device.type=="privateuseone")else audio,
+        #     audio,
+        #     n_fft=n_fft_new,
+        #     hop_length=hop_length_new,
+        #     win_length=win_length_new,
+        #     window=self.hann_window[keyshift_key],
+        #     center=center,
+        #     return_complex=True,
+        # )
+        # magnitude = torch.sqrt(fft.real.pow(2) + fft.imag.pow(2))
+        # print(1111111111)
+        # print(222222222222222,audio.device,self.is_half)
+        if hasattr(self, "stft") == False:
+            # print(n_fft_new,hop_length_new,win_length_new,audio.shape)
+            self.stft = STFT(
+                filter_length=n_fft_new,
+                hop_length=hop_length_new,
+                win_length=win_length_new,
+                window="hann",
+            ).to(audio.device)
+        magnitude = self.stft.transform(audio)  # phase
+        # if (audio.device.type == "privateuseone"):
+        #     magnitude=magnitude.to(audio.device)
+        if keyshift != 0:
+            size = self.n_fft // 2 + 1
+            resize = magnitude.size(1)
+            if resize < size:
+                magnitude = F.pad(magnitude, (0, 0, 0, size - resize))
+            magnitude = magnitude[:, :size, :] * self.win_length / win_length_new
+        mel_output = torch.matmul(self.mel_basis, magnitude)
+        if self.is_half == True:
+            mel_output = mel_output.half()
+        log_mel_spec = torch.log(torch.clamp(mel_output, min=self.clamp))
+        # print(log_mel_spec.device.type)
+        return log_mel_spec
+
+
+class RMVPE:
+    def __init__(self, model_path, is_half, device=None):
+        self.resample_kernel = {}
+        self.resample_kernel = {}
+        self.is_half = is_half
+        if device is None:
+            device = "cuda" if torch.cuda.is_available() else "cpu"
+        self.device = device
+        self.mel_extractor = MelSpectrogram(
+            is_half, 128, 16000, 1024, 160, None, 30, 8000
+        ).to(device)
+        if "privateuseone" in str(device):
+            import onnxruntime as ort
+
+            ort_session = ort.InferenceSession(
+                "%s/rmvpe.onnx" % os.environ["rmvpe_root"],
+                providers=["DmlExecutionProvider"],
+            )
+            self.model = ort_session
+        else:
+            model = E2E(4, 1, (2, 2))
+            ckpt = torch.load(model_path, map_location="cpu")
+            model.load_state_dict(ckpt)
+            model.eval()
+            if is_half == True:
+                model = model.half()
+            self.model = model
+            self.model = self.model.to(device)
+        cents_mapping = 20 * np.arange(360) + 1997.3794084376191
+        self.cents_mapping = np.pad(cents_mapping, (4, 4))  # 368
+
+    def mel2hidden(self, mel):
+        with torch.no_grad():
+            n_frames = mel.shape[-1]
+            mel = F.pad(
+                mel, (0, 32 * ((n_frames - 1) // 32 + 1) - n_frames), mode="constant"
+            )
+            if "privateuseone" in str(self.device):
+                onnx_input_name = self.model.get_inputs()[0].name
+                onnx_outputs_names = self.model.get_outputs()[0].name
+                hidden = self.model.run(
+                    [onnx_outputs_names],
+                    input_feed={onnx_input_name: mel.cpu().numpy()},
+                )[0]
+            else:
+                hidden = self.model(mel)
+            return hidden[:, :n_frames]
+
+    def decode(self, hidden, thred=0.03):
+        cents_pred = self.to_local_average_cents(hidden, thred=thred)
+        f0 = 10 * (2 ** (cents_pred / 1200))
+        f0[f0 == 10] = 0
+        # f0 = np.array([10 * (2 ** (cent_pred / 1200)) if cent_pred else 0 for cent_pred in cents_pred])
+        return f0
+
+    def infer_from_audio(self, audio, thred=0.03):
+        # torch.cuda.synchronize()
+        t0 = ttime()
+        mel = self.mel_extractor(
+            torch.from_numpy(audio).float().to(self.device).unsqueeze(0), center=True
+        )
+        # print(123123123,mel.device.type)
+        # torch.cuda.synchronize()
+        t1 = ttime()
+        hidden = self.mel2hidden(mel)
+        # torch.cuda.synchronize()
+        t2 = ttime()
+        # print(234234,hidden.device.type)
+        if "privateuseone" not in str(self.device):
+            hidden = hidden.squeeze(0).cpu().numpy()
+        else:
+            hidden = hidden[0]
+        if self.is_half == True:
+            hidden = hidden.astype("float32")
+
+        f0 = self.decode(hidden, thred=thred)
+        # torch.cuda.synchronize()
+        t3 = ttime()
+        # print("hmvpe:%s\t%s\t%s\t%s"%(t1-t0,t2-t1,t3-t2,t3-t0))
+        return f0
+    
+    def infer_from_audio_with_pitch(self, audio, thred=0.03, f0_min=50, f0_max=1100):
+        audio = torch.from_numpy(audio).float().to(self.device).unsqueeze(0)
+        mel = self.mel_extractor(audio, center=True)
+        hidden = self.mel2hidden(mel)
+        hidden = hidden.squeeze(0).cpu().numpy()
+        if self.is_half == True:
+            hidden = hidden.astype("float32")
+        f0 = self.decode(hidden, thred=thred)
+        f0[(f0 < f0_min) | (f0 > f0_max)] = 0  
+        return f0
+    
+    def to_local_average_cents(self, salience, thred=0.05):
+        # t0 = ttime()
+        center = np.argmax(salience, axis=1)  # 帧长#index
+        salience = np.pad(salience, ((0, 0), (4, 4)))  # 帧长,368
+        # t1 = ttime()
+        center += 4
+        todo_salience = []
+        todo_cents_mapping = []
+        starts = center - 4
+        ends = center + 5
+        for idx in range(salience.shape[0]):
+            todo_salience.append(salience[:, starts[idx] : ends[idx]][idx])
+            todo_cents_mapping.append(self.cents_mapping[starts[idx] : ends[idx]])
+        # t2 = ttime()
+        todo_salience = np.array(todo_salience)  # 帧长，9
+        todo_cents_mapping = np.array(todo_cents_mapping)  # 帧长，9
+        product_sum = np.sum(todo_salience * todo_cents_mapping, 1)
+        weight_sum = np.sum(todo_salience, 1)  # 帧长
+        devided = product_sum / weight_sum  # 帧长
+        # t3 = ttime()
+        maxx = np.max(salience, axis=1)  # 帧长
+        devided[maxx <= thred] = 0
+        # t4 = ttime()
+        # print("decode:%s\t%s\t%s\t%s" % (t1 - t0, t2 - t1, t3 - t2, t4 - t3))
+        return devided
+
+
+if __name__ == "__main__":
+    import librosa
+    import soundfile as sf
+
+    audio, sampling_rate = sf.read(r"C:\Users\liujing04\Desktop\Z\冬之花clip1.wav")
+    if len(audio.shape) > 1:
+        audio = librosa.to_mono(audio.transpose(1, 0))
+    audio_bak = audio.copy()
+    if sampling_rate != 16000:
+        audio = librosa.resample(audio, orig_sr=sampling_rate, target_sr=16000)
+    model_path = r"D:\BaiduNetdiskDownload\RVC-beta-v2-0727AMD_realtime\rmvpe.pt"
+    thred = 0.03  # 0.01
+    device = "cuda" if torch.cuda.is_available() else "cpu"
+    rmvpe = RMVPE(model_path, is_half=False, device=device)
+    t0 = ttime()
+    f0 = rmvpe.infer_from_audio(audio, thred=thred)
+    # f0 = rmvpe.infer_from_audio(audio, thred=thred)
+    # f0 = rmvpe.infer_from_audio(audio, thred=thred)
+    # f0 = rmvpe.infer_from_audio(audio, thred=thred)
+    # f0 = rmvpe.infer_from_audio(audio, thred=thred)
+    t1 = ttime()
+    logger.info("%s %.2f", f0.shape, t1 - t0)
diff --git a/infer/lib/slicer2.py b/infer/lib/slicer2.py
new file mode 100644
index 0000000000000000000000000000000000000000..5b29ee262aa54045e807be2cffeb41687499ba58
--- /dev/null
+++ b/infer/lib/slicer2.py
@@ -0,0 +1,260 @@
+import numpy as np
+
+
+# This function is obtained from librosa.
+def get_rms(
+    y,
+    frame_length=2048,
+    hop_length=512,
+    pad_mode="constant",
+):
+    padding = (int(frame_length // 2), int(frame_length // 2))
+    y = np.pad(y, padding, mode=pad_mode)
+
+    axis = -1
+    # put our new within-frame axis at the end for now
+    out_strides = y.strides + tuple([y.strides[axis]])
+    # Reduce the shape on the framing axis
+    x_shape_trimmed = list(y.shape)
+    x_shape_trimmed[axis] -= frame_length - 1
+    out_shape = tuple(x_shape_trimmed) + tuple([frame_length])
+    xw = np.lib.stride_tricks.as_strided(y, shape=out_shape, strides=out_strides)
+    if axis < 0:
+        target_axis = axis - 1
+    else:
+        target_axis = axis + 1
+    xw = np.moveaxis(xw, -1, target_axis)
+    # Downsample along the target axis
+    slices = [slice(None)] * xw.ndim
+    slices[axis] = slice(0, None, hop_length)
+    x = xw[tuple(slices)]
+
+    # Calculate power
+    power = np.mean(np.abs(x) ** 2, axis=-2, keepdims=True)
+
+    return np.sqrt(power)
+
+
+class Slicer:
+    def __init__(
+        self,
+        sr: int,
+        threshold: float = -40.0,
+        min_length: int = 5000,
+        min_interval: int = 300,
+        hop_size: int = 20,
+        max_sil_kept: int = 5000,
+    ):
+        if not min_length >= min_interval >= hop_size:
+            raise ValueError(
+                "The following condition must be satisfied: min_length >= min_interval >= hop_size"
+            )
+        if not max_sil_kept >= hop_size:
+            raise ValueError(
+                "The following condition must be satisfied: max_sil_kept >= hop_size"
+            )
+        min_interval = sr * min_interval / 1000
+        self.threshold = 10 ** (threshold / 20.0)
+        self.hop_size = round(sr * hop_size / 1000)
+        self.win_size = min(round(min_interval), 4 * self.hop_size)
+        self.min_length = round(sr * min_length / 1000 / self.hop_size)
+        self.min_interval = round(min_interval / self.hop_size)
+        self.max_sil_kept = round(sr * max_sil_kept / 1000 / self.hop_size)
+
+    def _apply_slice(self, waveform, begin, end):
+        if len(waveform.shape) > 1:
+            return waveform[
+                :, begin * self.hop_size : min(waveform.shape[1], end * self.hop_size)
+            ]
+        else:
+            return waveform[
+                begin * self.hop_size : min(waveform.shape[0], end * self.hop_size)
+            ]
+
+    # @timeit
+    def slice(self, waveform):
+        if len(waveform.shape) > 1:
+            samples = waveform.mean(axis=0)
+        else:
+            samples = waveform
+        if samples.shape[0] <= self.min_length:
+            return [waveform]
+        rms_list = get_rms(
+            y=samples, frame_length=self.win_size, hop_length=self.hop_size
+        ).squeeze(0)
+        sil_tags = []
+        silence_start = None
+        clip_start = 0
+        for i, rms in enumerate(rms_list):
+            # Keep looping while frame is silent.
+            if rms < self.threshold:
+                # Record start of silent frames.
+                if silence_start is None:
+                    silence_start = i
+                continue
+            # Keep looping while frame is not silent and silence start has not been recorded.
+            if silence_start is None:
+                continue
+            # Clear recorded silence start if interval is not enough or clip is too short
+            is_leading_silence = silence_start == 0 and i > self.max_sil_kept
+            need_slice_middle = (
+                i - silence_start >= self.min_interval
+                and i - clip_start >= self.min_length
+            )
+            if not is_leading_silence and not need_slice_middle:
+                silence_start = None
+                continue
+            # Need slicing. Record the range of silent frames to be removed.
+            if i - silence_start <= self.max_sil_kept:
+                pos = rms_list[silence_start : i + 1].argmin() + silence_start
+                if silence_start == 0:
+                    sil_tags.append((0, pos))
+                else:
+                    sil_tags.append((pos, pos))
+                clip_start = pos
+            elif i - silence_start <= self.max_sil_kept * 2:
+                pos = rms_list[
+                    i - self.max_sil_kept : silence_start + self.max_sil_kept + 1
+                ].argmin()
+                pos += i - self.max_sil_kept
+                pos_l = (
+                    rms_list[
+                        silence_start : silence_start + self.max_sil_kept + 1
+                    ].argmin()
+                    + silence_start
+                )
+                pos_r = (
+                    rms_list[i - self.max_sil_kept : i + 1].argmin()
+                    + i
+                    - self.max_sil_kept
+                )
+                if silence_start == 0:
+                    sil_tags.append((0, pos_r))
+                    clip_start = pos_r
+                else:
+                    sil_tags.append((min(pos_l, pos), max(pos_r, pos)))
+                    clip_start = max(pos_r, pos)
+            else:
+                pos_l = (
+                    rms_list[
+                        silence_start : silence_start + self.max_sil_kept + 1
+                    ].argmin()
+                    + silence_start
+                )
+                pos_r = (
+                    rms_list[i - self.max_sil_kept : i + 1].argmin()
+                    + i
+                    - self.max_sil_kept
+                )
+                if silence_start == 0:
+                    sil_tags.append((0, pos_r))
+                else:
+                    sil_tags.append((pos_l, pos_r))
+                clip_start = pos_r
+            silence_start = None
+        # Deal with trailing silence.
+        total_frames = rms_list.shape[0]
+        if (
+            silence_start is not None
+            and total_frames - silence_start >= self.min_interval
+        ):
+            silence_end = min(total_frames, silence_start + self.max_sil_kept)
+            pos = rms_list[silence_start : silence_end + 1].argmin() + silence_start
+            sil_tags.append((pos, total_frames + 1))
+        # Apply and return slices.
+        if len(sil_tags) == 0:
+            return [waveform]
+        else:
+            chunks = []
+            if sil_tags[0][0] > 0:
+                chunks.append(self._apply_slice(waveform, 0, sil_tags[0][0]))
+            for i in range(len(sil_tags) - 1):
+                chunks.append(
+                    self._apply_slice(waveform, sil_tags[i][1], sil_tags[i + 1][0])
+                )
+            if sil_tags[-1][1] < total_frames:
+                chunks.append(
+                    self._apply_slice(waveform, sil_tags[-1][1], total_frames)
+                )
+            return chunks
+
+
+def main():
+    import os.path
+    from argparse import ArgumentParser
+
+    import librosa
+    import soundfile
+
+    parser = ArgumentParser()
+    parser.add_argument("audio", type=str, help="The audio to be sliced")
+    parser.add_argument(
+        "--out", type=str, help="Output directory of the sliced audio clips"
+    )
+    parser.add_argument(
+        "--db_thresh",
+        type=float,
+        required=False,
+        default=-40,
+        help="The dB threshold for silence detection",
+    )
+    parser.add_argument(
+        "--min_length",
+        type=int,
+        required=False,
+        default=5000,
+        help="The minimum milliseconds required for each sliced audio clip",
+    )
+    parser.add_argument(
+        "--min_interval",
+        type=int,
+        required=False,
+        default=300,
+        help="The minimum milliseconds for a silence part to be sliced",
+    )
+    parser.add_argument(
+        "--hop_size",
+        type=int,
+        required=False,
+        default=10,
+        help="Frame length in milliseconds",
+    )
+    parser.add_argument(
+        "--max_sil_kept",
+        type=int,
+        required=False,
+        default=500,
+        help="The maximum silence length kept around the sliced clip, presented in milliseconds",
+    )
+    args = parser.parse_args()
+    out = args.out
+    if out is None:
+        out = os.path.dirname(os.path.abspath(args.audio))
+    audio, sr = librosa.load(args.audio, sr=None, mono=False)
+    slicer = Slicer(
+        sr=sr,
+        threshold=args.db_thresh,
+        min_length=args.min_length,
+        min_interval=args.min_interval,
+        hop_size=args.hop_size,
+        max_sil_kept=args.max_sil_kept,
+    )
+    chunks = slicer.slice(audio)
+    if not os.path.exists(out):
+        os.makedirs(out)
+    for i, chunk in enumerate(chunks):
+        if len(chunk.shape) > 1:
+            chunk = chunk.T
+        soundfile.write(
+            os.path.join(
+                out,
+                f"%s_%d.wav"
+                % (os.path.basename(args.audio).rsplit(".", maxsplit=1)[0], i),
+            ),
+            chunk,
+            sr,
+        )
+
+
+if __name__ == "__main__":
+    main()
diff --git a/infer/lib/train/data_utils.py b/infer/lib/train/data_utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..51a176cceba860acf79157ed0bad2b82c8e80406
--- /dev/null
+++ b/infer/lib/train/data_utils.py
@@ -0,0 +1,517 @@
+import os
+import traceback
+import logging
+
+logger = logging.getLogger(__name__)
+
+import numpy as np
+import torch
+import torch.utils.data
+
+from infer.lib.train.mel_processing import spectrogram_torch
+from infer.lib.train.utils import load_filepaths_and_text, load_wav_to_torch
+
+
+class TextAudioLoaderMultiNSFsid(torch.utils.data.Dataset):
+    """
+    1) loads audio, text pairs
+    2) normalizes text and converts them to sequences of integers
+    3) computes spectrograms from audio files.
+    """
+
+    def __init__(self, audiopaths_and_text, hparams):
+        self.audiopaths_and_text = load_filepaths_and_text(audiopaths_and_text)
+        self.max_wav_value = hparams.max_wav_value
+        self.sampling_rate = hparams.sampling_rate
+        self.filter_length = hparams.filter_length
+        self.hop_length = hparams.hop_length
+        self.win_length = hparams.win_length
+        self.sampling_rate = hparams.sampling_rate
+        self.min_text_len = getattr(hparams, "min_text_len", 1)
+        self.max_text_len = getattr(hparams, "max_text_len", 5000)
+        self._filter()
+
+    def _filter(self):
+        """
+        Filter text & store spec lengths
+        """
+        # Store spectrogram lengths for Bucketing
+        # wav_length ~= file_size / (wav_channels * Bytes per dim) = file_size / (1 * 2)
+        # spec_length = wav_length // hop_length
+        audiopaths_and_text_new = []
+        lengths = []
+        for audiopath, text, pitch, pitchf, dv in self.audiopaths_and_text:
+            if self.min_text_len <= len(text) and len(text) <= self.max_text_len:
+                audiopaths_and_text_new.append([audiopath, text, pitch, pitchf, dv])
+                lengths.append(os.path.getsize(audiopath) // (3 * self.hop_length))
+        self.audiopaths_and_text = audiopaths_and_text_new
+        self.lengths = lengths
+
+    def get_sid(self, sid):
+        sid = torch.LongTensor([int(sid)])
+        return sid
+
+    def get_audio_text_pair(self, audiopath_and_text):
+        # separate filename and text
+        file = audiopath_and_text[0]
+        phone = audiopath_and_text[1]
+        pitch = audiopath_and_text[2]
+        pitchf = audiopath_and_text[3]
+        dv = audiopath_and_text[4]
+
+        phone, pitch, pitchf = self.get_labels(phone, pitch, pitchf)
+        spec, wav = self.get_audio(file)
+        dv = self.get_sid(dv)
+
+        len_phone = phone.size()[0]
+        len_spec = spec.size()[-1]
+        # print(123,phone.shape,pitch.shape,spec.shape)
+        if len_phone != len_spec:
+            len_min = min(len_phone, len_spec)
+            # amor
+            len_wav = len_min * self.hop_length
+
+            spec = spec[:, :len_min]
+            wav = wav[:, :len_wav]
+
+            phone = phone[:len_min, :]
+            pitch = pitch[:len_min]
+            pitchf = pitchf[:len_min]
+
+        return (spec, wav, phone, pitch, pitchf, dv)
+
+    def get_labels(self, phone, pitch, pitchf):
+        phone = np.load(phone)
+        phone = np.repeat(phone, 2, axis=0)
+        pitch = np.load(pitch)
+        pitchf = np.load(pitchf)
+        n_num = min(phone.shape[0], 900)  # DistributedBucketSampler
+        # print(234,phone.shape,pitch.shape)
+        phone = phone[:n_num, :]
+        pitch = pitch[:n_num]
+        pitchf = pitchf[:n_num]
+        phone = torch.FloatTensor(phone)
+        pitch = torch.LongTensor(pitch)
+        pitchf = torch.FloatTensor(pitchf)
+        return phone, pitch, pitchf
+
+    def get_audio(self, filename):
+        audio, sampling_rate = load_wav_to_torch(filename)
+        if sampling_rate != self.sampling_rate:
+            raise ValueError(
+                "{} SR doesn't match target {} SR".format(
+                    sampling_rate, self.sampling_rate
+                )
+            )
+        audio_norm = audio
+        #        audio_norm = audio / self.max_wav_value
+        #        audio_norm = audio / np.abs(audio).max()
+
+        audio_norm = audio_norm.unsqueeze(0)
+        spec_filename = filename.replace(".wav", ".spec.pt")
+        if os.path.exists(spec_filename):
+            try:
+                spec = torch.load(spec_filename)
+            except:
+                logger.warn("%s %s", spec_filename, traceback.format_exc())
+                spec = spectrogram_torch(
+                    audio_norm,
+                    self.filter_length,
+                    self.sampling_rate,
+                    self.hop_length,
+                    self.win_length,
+                    center=False,
+                )
+                spec = torch.squeeze(spec, 0)
+                torch.save(spec, spec_filename, _use_new_zipfile_serialization=False)
+        else:
+            spec = spectrogram_torch(
+                audio_norm,
+                self.filter_length,
+                self.sampling_rate,
+                self.hop_length,
+                self.win_length,
+                center=False,
+            )
+            spec = torch.squeeze(spec, 0)
+            torch.save(spec, spec_filename, _use_new_zipfile_serialization=False)
+        return spec, audio_norm
+
+    def __getitem__(self, index):
+        return self.get_audio_text_pair(self.audiopaths_and_text[index])
+
+    def __len__(self):
+        return len(self.audiopaths_and_text)
+
+
+class TextAudioCollateMultiNSFsid:
+    """Zero-pads model inputs and targets"""
+
+    def __init__(self, return_ids=False):
+        self.return_ids = return_ids
+
+    def __call__(self, batch):
+        """Collate's training batch from normalized text and aduio
+        PARAMS
+        ------
+        batch: [text_normalized, spec_normalized, wav_normalized]
+        """
+        # Right zero-pad all one-hot text sequences to max input length
+        _, ids_sorted_decreasing = torch.sort(
+            torch.LongTensor([x[0].size(1) for x in batch]), dim=0, descending=True
+        )
+
+        max_spec_len = max([x[0].size(1) for x in batch])
+        max_wave_len = max([x[1].size(1) for x in batch])
+        spec_lengths = torch.LongTensor(len(batch))
+        wave_lengths = torch.LongTensor(len(batch))
+        spec_padded = torch.FloatTensor(len(batch), batch[0][0].size(0), max_spec_len)
+        wave_padded = torch.FloatTensor(len(batch), 1, max_wave_len)
+        spec_padded.zero_()
+        wave_padded.zero_()
+
+        max_phone_len = max([x[2].size(0) for x in batch])
+        phone_lengths = torch.LongTensor(len(batch))
+        phone_padded = torch.FloatTensor(
+            len(batch), max_phone_len, batch[0][2].shape[1]
+        )  # (spec, wav, phone, pitch)
+        pitch_padded = torch.LongTensor(len(batch), max_phone_len)
+        pitchf_padded = torch.FloatTensor(len(batch), max_phone_len)
+        phone_padded.zero_()
+        pitch_padded.zero_()
+        pitchf_padded.zero_()
+        # dv = torch.FloatTensor(len(batch), 256)#gin=256
+        sid = torch.LongTensor(len(batch))
+
+        for i in range(len(ids_sorted_decreasing)):
+            row = batch[ids_sorted_decreasing[i]]
+
+            spec = row[0]
+            spec_padded[i, :, : spec.size(1)] = spec
+            spec_lengths[i] = spec.size(1)
+
+            wave = row[1]
+            wave_padded[i, :, : wave.size(1)] = wave
+            wave_lengths[i] = wave.size(1)
+
+            phone = row[2]
+            phone_padded[i, : phone.size(0), :] = phone
+            phone_lengths[i] = phone.size(0)
+
+            pitch = row[3]
+            pitch_padded[i, : pitch.size(0)] = pitch
+            pitchf = row[4]
+            pitchf_padded[i, : pitchf.size(0)] = pitchf
+
+            # dv[i] = row[5]
+            sid[i] = row[5]
+
+        return (
+            phone_padded,
+            phone_lengths,
+            pitch_padded,
+            pitchf_padded,
+            spec_padded,
+            spec_lengths,
+            wave_padded,
+            wave_lengths,
+            # dv
+            sid,
+        )
+
+
+class TextAudioLoader(torch.utils.data.Dataset):
+    """
+    1) loads audio, text pairs
+    2) normalizes text and converts them to sequences of integers
+    3) computes spectrograms from audio files.
+    """
+
+    def __init__(self, audiopaths_and_text, hparams):
+        self.audiopaths_and_text = load_filepaths_and_text(audiopaths_and_text)
+        self.max_wav_value = hparams.max_wav_value
+        self.sampling_rate = hparams.sampling_rate
+        self.filter_length = hparams.filter_length
+        self.hop_length = hparams.hop_length
+        self.win_length = hparams.win_length
+        self.sampling_rate = hparams.sampling_rate
+        self.min_text_len = getattr(hparams, "min_text_len", 1)
+        self.max_text_len = getattr(hparams, "max_text_len", 5000)
+        self._filter()
+
+    def _filter(self):
+        """
+        Filter text & store spec lengths
+        """
+        # Store spectrogram lengths for Bucketing
+        # wav_length ~= file_size / (wav_channels * Bytes per dim) = file_size / (1 * 2)
+        # spec_length = wav_length // hop_length
+        audiopaths_and_text_new = []
+        lengths = []
+        for audiopath, text, dv in self.audiopaths_and_text:
+            if self.min_text_len <= len(text) and len(text) <= self.max_text_len:
+                audiopaths_and_text_new.append([audiopath, text, dv])
+                lengths.append(os.path.getsize(audiopath) // (3 * self.hop_length))
+        self.audiopaths_and_text = audiopaths_and_text_new
+        self.lengths = lengths
+
+    def get_sid(self, sid):
+        sid = torch.LongTensor([int(sid)])
+        return sid
+
+    def get_audio_text_pair(self, audiopath_and_text):
+        # separate filename and text
+        file = audiopath_and_text[0]
+        phone = audiopath_and_text[1]
+        dv = audiopath_and_text[2]
+
+        phone = self.get_labels(phone)
+        spec, wav = self.get_audio(file)
+        dv = self.get_sid(dv)
+
+        len_phone = phone.size()[0]
+        len_spec = spec.size()[-1]
+        if len_phone != len_spec:
+            len_min = min(len_phone, len_spec)
+            len_wav = len_min * self.hop_length
+            spec = spec[:, :len_min]
+            wav = wav[:, :len_wav]
+            phone = phone[:len_min, :]
+        return (spec, wav, phone, dv)
+
+    def get_labels(self, phone):
+        phone = np.load(phone)
+        phone = np.repeat(phone, 2, axis=0)
+        n_num = min(phone.shape[0], 900)  # DistributedBucketSampler
+        phone = phone[:n_num, :]
+        phone = torch.FloatTensor(phone)
+        return phone
+
+    def get_audio(self, filename):
+        audio, sampling_rate = load_wav_to_torch(filename)
+        if sampling_rate != self.sampling_rate:
+            raise ValueError(
+                "{} SR doesn't match target {} SR".format(
+                    sampling_rate, self.sampling_rate
+                )
+            )
+        audio_norm = audio
+        #        audio_norm = audio / self.max_wav_value
+        #        audio_norm = audio / np.abs(audio).max()
+
+        audio_norm = audio_norm.unsqueeze(0)
+        spec_filename = filename.replace(".wav", ".spec.pt")
+        if os.path.exists(spec_filename):
+            try:
+                spec = torch.load(spec_filename)
+            except:
+                logger.warn("%s %s", spec_filename, traceback.format_exc())
+                spec = spectrogram_torch(
+                    audio_norm,
+                    self.filter_length,
+                    self.sampling_rate,
+                    self.hop_length,
+                    self.win_length,
+                    center=False,
+                )
+                spec = torch.squeeze(spec, 0)
+                torch.save(spec, spec_filename, _use_new_zipfile_serialization=False)
+        else:
+            spec = spectrogram_torch(
+                audio_norm,
+                self.filter_length,
+                self.sampling_rate,
+                self.hop_length,
+                self.win_length,
+                center=False,
+            )
+            spec = torch.squeeze(spec, 0)
+            torch.save(spec, spec_filename, _use_new_zipfile_serialization=False)
+        return spec, audio_norm
+
+    def __getitem__(self, index):
+        return self.get_audio_text_pair(self.audiopaths_and_text[index])
+
+    def __len__(self):
+        return len(self.audiopaths_and_text)
+
+
+class TextAudioCollate:
+    """Zero-pads model inputs and targets"""
+
+    def __init__(self, return_ids=False):
+        self.return_ids = return_ids
+
+    def __call__(self, batch):
+        """Collate's training batch from normalized text and aduio
+        PARAMS
+        ------
+        batch: [text_normalized, spec_normalized, wav_normalized]
+        """
+        # Right zero-pad all one-hot text sequences to max input length
+        _, ids_sorted_decreasing = torch.sort(
+            torch.LongTensor([x[0].size(1) for x in batch]), dim=0, descending=True
+        )
+
+        max_spec_len = max([x[0].size(1) for x in batch])
+        max_wave_len = max([x[1].size(1) for x in batch])
+        spec_lengths = torch.LongTensor(len(batch))
+        wave_lengths = torch.LongTensor(len(batch))
+        spec_padded = torch.FloatTensor(len(batch), batch[0][0].size(0), max_spec_len)
+        wave_padded = torch.FloatTensor(len(batch), 1, max_wave_len)
+        spec_padded.zero_()
+        wave_padded.zero_()
+
+        max_phone_len = max([x[2].size(0) for x in batch])
+        phone_lengths = torch.LongTensor(len(batch))
+        phone_padded = torch.FloatTensor(
+            len(batch), max_phone_len, batch[0][2].shape[1]
+        )
+        phone_padded.zero_()
+        sid = torch.LongTensor(len(batch))
+
+        for i in range(len(ids_sorted_decreasing)):
+            row = batch[ids_sorted_decreasing[i]]
+
+            spec = row[0]
+            spec_padded[i, :, : spec.size(1)] = spec
+            spec_lengths[i] = spec.size(1)
+
+            wave = row[1]
+            wave_padded[i, :, : wave.size(1)] = wave
+            wave_lengths[i] = wave.size(1)
+
+            phone = row[2]
+            phone_padded[i, : phone.size(0), :] = phone
+            phone_lengths[i] = phone.size(0)
+
+            sid[i] = row[3]
+
+        return (
+            phone_padded,
+            phone_lengths,
+            spec_padded,
+            spec_lengths,
+            wave_padded,
+            wave_lengths,
+            sid,
+        )
+
+
+class DistributedBucketSampler(torch.utils.data.distributed.DistributedSampler):
+    """
+    Maintain similar input lengths in a batch.
+    Length groups are specified by boundaries.
+    Ex) boundaries = [b1, b2, b3] -> any batch is included either {x | b1 < length(x) <=b2} or {x | b2 < length(x) <= b3}.
+
+    It removes samples which are not included in the boundaries.
+    Ex) boundaries = [b1, b2, b3] -> any x s.t. length(x) <= b1 or length(x) > b3 are discarded.
+    """
+
+    def __init__(
+        self,
+        dataset,
+        batch_size,
+        boundaries,
+        num_replicas=None,
+        rank=None,
+        shuffle=True,
+    ):
+        super().__init__(dataset, num_replicas=num_replicas, rank=rank, shuffle=shuffle)
+        self.lengths = dataset.lengths
+        self.batch_size = batch_size
+        self.boundaries = boundaries
+
+        self.buckets, self.num_samples_per_bucket = self._create_buckets()
+        self.total_size = sum(self.num_samples_per_bucket)
+        self.num_samples = self.total_size // self.num_replicas
+
+    def _create_buckets(self):
+        buckets = [[] for _ in range(len(self.boundaries) - 1)]
+        for i in range(len(self.lengths)):
+            length = self.lengths[i]
+            idx_bucket = self._bisect(length)
+            if idx_bucket != -1:
+                buckets[idx_bucket].append(i)
+
+        for i in range(len(buckets) - 1, -1, -1):  #
+            if len(buckets[i]) == 0:
+                buckets.pop(i)
+                self.boundaries.pop(i + 1)
+
+        num_samples_per_bucket = []
+        for i in range(len(buckets)):
+            len_bucket = len(buckets[i])
+            total_batch_size = self.num_replicas * self.batch_size
+            rem = (
+                total_batch_size - (len_bucket % total_batch_size)
+            ) % total_batch_size
+            num_samples_per_bucket.append(len_bucket + rem)
+        return buckets, num_samples_per_bucket
+
+    def __iter__(self):
+        # deterministically shuffle based on epoch
+        g = torch.Generator()
+        g.manual_seed(self.epoch)
+
+        indices = []
+        if self.shuffle:
+            for bucket in self.buckets:
+                indices.append(torch.randperm(len(bucket), generator=g).tolist())
+        else:
+            for bucket in self.buckets:
+                indices.append(list(range(len(bucket))))
+
+        batches = []
+        for i in range(len(self.buckets)):
+            bucket = self.buckets[i]
+            len_bucket = len(bucket)
+            ids_bucket = indices[i]
+            num_samples_bucket = self.num_samples_per_bucket[i]
+
+            # add extra samples to make it evenly divisible
+            rem = num_samples_bucket - len_bucket
+            ids_bucket = (
+                ids_bucket
+                + ids_bucket * (rem // len_bucket)
+                + ids_bucket[: (rem % len_bucket)]
+            )
+
+            # subsample
+            ids_bucket = ids_bucket[self.rank :: self.num_replicas]
+
+            # batching
+            for j in range(len(ids_bucket) // self.batch_size):
+                batch = [
+                    bucket[idx]
+                    for idx in ids_bucket[
+                        j * self.batch_size : (j + 1) * self.batch_size
+                    ]
+                ]
+                batches.append(batch)
+
+        if self.shuffle:
+            batch_ids = torch.randperm(len(batches), generator=g).tolist()
+            batches = [batches[i] for i in batch_ids]
+        self.batches = batches
+
+        assert len(self.batches) * self.batch_size == self.num_samples
+        return iter(self.batches)
+
+    def _bisect(self, x, lo=0, hi=None):
+        if hi is None:
+            hi = len(self.boundaries) - 1
+
+        if hi > lo:
+            mid = (hi + lo) // 2
+            if self.boundaries[mid] < x and x <= self.boundaries[mid + 1]:
+                return mid
+            elif x <= self.boundaries[mid]:
+                return self._bisect(x, lo, mid)
+            else:
+                return self._bisect(x, mid + 1, hi)
+        else:
+            return -1
+
+    def __len__(self):
+        return self.num_samples // self.batch_size
diff --git a/infer/lib/train/losses.py b/infer/lib/train/losses.py
new file mode 100644
index 0000000000000000000000000000000000000000..b1b263e4c205e78ffe970f622ab6ff68f36d3b17
--- /dev/null
+++ b/infer/lib/train/losses.py
@@ -0,0 +1,58 @@
+import torch
+
+
+def feature_loss(fmap_r, fmap_g):
+    loss = 0
+    for dr, dg in zip(fmap_r, fmap_g):
+        for rl, gl in zip(dr, dg):
+            rl = rl.float().detach()
+            gl = gl.float()
+            loss += torch.mean(torch.abs(rl - gl))
+
+    return loss * 2
+
+
+def discriminator_loss(disc_real_outputs, disc_generated_outputs):
+    loss = 0
+    r_losses = []
+    g_losses = []
+    for dr, dg in zip(disc_real_outputs, disc_generated_outputs):
+        dr = dr.float()
+        dg = dg.float()
+        r_loss = torch.mean((1 - dr) ** 2)
+        g_loss = torch.mean(dg**2)
+        loss += r_loss + g_loss
+        r_losses.append(r_loss.item())
+        g_losses.append(g_loss.item())
+
+    return loss, r_losses, g_losses
+
+
+def generator_loss(disc_outputs):
+    loss = 0
+    gen_losses = []
+    for dg in disc_outputs:
+        dg = dg.float()
+        l = torch.mean((1 - dg) ** 2)
+        gen_losses.append(l)
+        loss += l
+
+    return loss, gen_losses
+
+
+def kl_loss(z_p, logs_q, m_p, logs_p, z_mask):
+    """
+    z_p, logs_q: [b, h, t_t]
+    m_p, logs_p: [b, h, t_t]
+    """
+    z_p = z_p.float()
+    logs_q = logs_q.float()
+    m_p = m_p.float()
+    logs_p = logs_p.float()
+    z_mask = z_mask.float()
+
+    kl = logs_p - logs_q - 0.5
+    kl += 0.5 * ((z_p - m_p) ** 2) * torch.exp(-2.0 * logs_p)
+    kl = torch.sum(kl * z_mask)
+    l = kl / torch.sum(z_mask)
+    return l
diff --git a/infer/lib/train/mel_processing.py b/infer/lib/train/mel_processing.py
new file mode 100644
index 0000000000000000000000000000000000000000..f458775bf62b79f791b419ca7ed62c550ae252d5
--- /dev/null
+++ b/infer/lib/train/mel_processing.py
@@ -0,0 +1,132 @@
+import torch
+import torch.utils.data
+from librosa.filters import mel as librosa_mel_fn
+import logging
+
+logger = logging.getLogger(__name__)
+
+MAX_WAV_VALUE = 32768.0
+
+
+def dynamic_range_compression_torch(x, C=1, clip_val=1e-5):
+    """
+    PARAMS
+    ------
+    C: compression factor
+    """
+    return torch.log(torch.clamp(x, min=clip_val) * C)
+
+
+def dynamic_range_decompression_torch(x, C=1):
+    """
+    PARAMS
+    ------
+    C: compression factor used to compress
+    """
+    return torch.exp(x) / C
+
+
+def spectral_normalize_torch(magnitudes):
+    return dynamic_range_compression_torch(magnitudes)
+
+
+def spectral_de_normalize_torch(magnitudes):
+    return dynamic_range_decompression_torch(magnitudes)
+
+
+# Reusable banks
+mel_basis = {}
+hann_window = {}
+
+
+def spectrogram_torch(y, n_fft, sampling_rate, hop_size, win_size, center=False):
+    """Convert waveform into Linear-frequency Linear-amplitude spectrogram.
+
+    Args:
+        y             :: (B, T) - Audio waveforms
+        n_fft
+        sampling_rate
+        hop_size
+        win_size
+        center
+    Returns:
+        :: (B, Freq, Frame) - Linear-frequency Linear-amplitude spectrogram
+    """
+    # Validation
+    if torch.min(y) < -1.07:
+        logger.debug("min value is %s", str(torch.min(y)))
+    if torch.max(y) > 1.07:
+        logger.debug("max value is %s", str(torch.max(y)))
+
+    # Window - Cache if needed
+    global hann_window
+    dtype_device = str(y.dtype) + "_" + str(y.device)
+    wnsize_dtype_device = str(win_size) + "_" + dtype_device
+    if wnsize_dtype_device not in hann_window:
+        hann_window[wnsize_dtype_device] = torch.hann_window(win_size).to(
+            dtype=y.dtype, device=y.device
+        )
+
+    # Padding
+    y = torch.nn.functional.pad(
+        y.unsqueeze(1),
+        (int((n_fft - hop_size) / 2), int((n_fft - hop_size) / 2)),
+        mode="reflect",
+    )
+    y = y.squeeze(1)
+
+    # Complex Spectrogram :: (B, T) -> (B, Freq, Frame, RealComplex=2)
+    spec = torch.stft(
+        y,
+        n_fft,
+        hop_length=hop_size,
+        win_length=win_size,
+        window=hann_window[wnsize_dtype_device],
+        center=center,
+        pad_mode="reflect",
+        normalized=False,
+        onesided=True,
+        return_complex=False,
+    )
+
+    # Linear-frequency Linear-amplitude spectrogram :: (B, Freq, Frame, RealComplex=2) -> (B, Freq, Frame)
+    spec = torch.sqrt(spec.pow(2).sum(-1) + 1e-6)
+    return spec
+
+
+def spec_to_mel_torch(spec, n_fft, num_mels, sampling_rate, fmin, fmax):
+    # MelBasis - Cache if needed
+    global mel_basis
+    dtype_device = str(spec.dtype) + "_" + str(spec.device)
+    fmax_dtype_device = str(fmax) + "_" + dtype_device
+    if fmax_dtype_device not in mel_basis:
+        mel = librosa_mel_fn(
+            sr=sampling_rate, n_fft=n_fft, n_mels=num_mels, fmin=fmin, fmax=fmax
+        )
+        mel_basis[fmax_dtype_device] = torch.from_numpy(mel).to(
+            dtype=spec.dtype, device=spec.device
+        )
+
+    # Mel-frequency Log-amplitude spectrogram :: (B, Freq=num_mels, Frame)
+    melspec = torch.matmul(mel_basis[fmax_dtype_device], spec)
+    melspec = spectral_normalize_torch(melspec)
+    return melspec
+
+
+def mel_spectrogram_torch(
+    y, n_fft, num_mels, sampling_rate, hop_size, win_size, fmin, fmax, center=False
+):
+    """Convert waveform into Mel-frequency Log-amplitude spectrogram.
+
+    Args:
+        y       :: (B, T)           - Waveforms
+    Returns:
+        melspec :: (B, Freq, Frame) - Mel-frequency Log-amplitude spectrogram
+    """
+    # Linear-frequency Linear-amplitude spectrogram :: (B, T) -> (B, Freq, Frame)
+    spec = spectrogram_torch(y, n_fft, sampling_rate, hop_size, win_size, center)
+
+    # Mel-frequency Log-amplitude spectrogram :: (B, Freq, Frame) -> (B, Freq=num_mels, Frame)
+    melspec = spec_to_mel_torch(spec, n_fft, num_mels, sampling_rate, fmin, fmax)
+
+    return melspec
diff --git a/infer/lib/train/process_ckpt.py b/infer/lib/train/process_ckpt.py
new file mode 100644
index 0000000000000000000000000000000000000000..36d359d5f853452da4e1a696a84b8457b8386c29
--- /dev/null
+++ b/infer/lib/train/process_ckpt.py
@@ -0,0 +1,261 @@
+import os
+import sys
+import traceback
+from collections import OrderedDict
+
+import torch
+
+from i18n import I18nAuto
+
+i18n = I18nAuto()
+
+
+def savee(ckpt, sr, if_f0, name, epoch, version, hps):
+    try:
+        opt = OrderedDict()
+        opt["weight"] = {}
+        for key in ckpt.keys():
+            if "enc_q" in key:
+                continue
+            opt["weight"][key] = ckpt[key].half()
+        opt["config"] = [
+            hps.data.filter_length // 2 + 1,
+            32,
+            hps.model.inter_channels,
+            hps.model.hidden_channels,
+            hps.model.filter_channels,
+            hps.model.n_heads,
+            hps.model.n_layers,
+            hps.model.kernel_size,
+            hps.model.p_dropout,
+            hps.model.resblock,
+            hps.model.resblock_kernel_sizes,
+            hps.model.resblock_dilation_sizes,
+            hps.model.upsample_rates,
+            hps.model.upsample_initial_channel,
+            hps.model.upsample_kernel_sizes,
+            hps.model.spk_embed_dim,
+            hps.model.gin_channels,
+            hps.data.sampling_rate,
+        ]
+        opt["info"] = "%sepoch" % epoch
+        opt["sr"] = sr
+        opt["f0"] = if_f0
+        opt["version"] = version
+        torch.save(opt, "weights/%s.pth" % name)
+        return "Success."
+    except:
+        return traceback.format_exc()
+
+
+def show_info(path):
+    try:
+        a = torch.load(path, map_location="cpu")
+        return "模型信息:%s\n采样率:%s\n模型是否输入音高引导:%s\n版本:%s" % (
+            a.get("info", "None"),
+            a.get("sr", "None"),
+            a.get("f0", "None"),
+            a.get("version", "None"),
+        )
+    except:
+        return traceback.format_exc()
+
+
+def extract_small_model(path, name, sr, if_f0, info, version):
+    try:
+        ckpt = torch.load(path, map_location="cpu")
+        if "model" in ckpt:
+            ckpt = ckpt["model"]
+        opt = OrderedDict()
+        opt["weight"] = {}
+        for key in ckpt.keys():
+            if "enc_q" in key:
+                continue
+            opt["weight"][key] = ckpt[key].half()
+        if sr == "40k":
+            opt["config"] = [
+                1025,
+                32,
+                192,
+                192,
+                768,
+                2,
+                6,
+                3,
+                0,
+                "1",
+                [3, 7, 11],
+                [[1, 3, 5], [1, 3, 5], [1, 3, 5]],
+                [10, 10, 2, 2],
+                512,
+                [16, 16, 4, 4],
+                109,
+                256,
+                40000,
+            ]
+        elif sr == "48k":
+            if version == "v1":
+                opt["config"] = [
+                    1025,
+                    32,
+                    192,
+                    192,
+                    768,
+                    2,
+                    6,
+                    3,
+                    0,
+                    "1",
+                    [3, 7, 11],
+                    [[1, 3, 5], [1, 3, 5], [1, 3, 5]],
+                    [10, 6, 2, 2, 2],
+                    512,
+                    [16, 16, 4, 4, 4],
+                    109,
+                    256,
+                    48000,
+                ]
+            else:
+                opt["config"] = [
+                    1025,
+                    32,
+                    192,
+                    192,
+                    768,
+                    2,
+                    6,
+                    3,
+                    0,
+                    "1",
+                    [3, 7, 11],
+                    [[1, 3, 5], [1, 3, 5], [1, 3, 5]],
+                    [12, 10, 2, 2],
+                    512,
+                    [24, 20, 4, 4],
+                    109,
+                    256,
+                    48000,
+                ]
+        elif sr == "32k":
+            if version == "v1":
+                opt["config"] = [
+                    513,
+                    32,
+                    192,
+                    192,
+                    768,
+                    2,
+                    6,
+                    3,
+                    0,
+                    "1",
+                    [3, 7, 11],
+                    [[1, 3, 5], [1, 3, 5], [1, 3, 5]],
+                    [10, 4, 2, 2, 2],
+                    512,
+                    [16, 16, 4, 4, 4],
+                    109,
+                    256,
+                    32000,
+                ]
+            else:
+                opt["config"] = [
+                    513,
+                    32,
+                    192,
+                    192,
+                    768,
+                    2,
+                    6,
+                    3,
+                    0,
+                    "1",
+                    [3, 7, 11],
+                    [[1, 3, 5], [1, 3, 5], [1, 3, 5]],
+                    [10, 8, 2, 2],
+                    512,
+                    [20, 16, 4, 4],
+                    109,
+                    256,
+                    32000,
+                ]
+        if info == "":
+            info = "Extracted model."
+        opt["info"] = info
+        opt["version"] = version
+        opt["sr"] = sr
+        opt["f0"] = int(if_f0)
+        torch.save(opt, "weights/%s.pth" % name)
+        return "Success."
+    except:
+        return traceback.format_exc()
+
+
+def change_info(path, info, name):
+    try:
+        ckpt = torch.load(path, map_location="cpu")
+        ckpt["info"] = info
+        if name == "":
+            name = os.path.basename(path)
+        torch.save(ckpt, "weights/%s" % name)
+        return "Success."
+    except:
+        return traceback.format_exc()
+
+
+def merge(path1, path2, alpha1, sr, f0, info, name, version):
+    try:
+
+        def extract(ckpt):
+            a = ckpt["model"]
+            opt = OrderedDict()
+            opt["weight"] = {}
+            for key in a.keys():
+                if "enc_q" in key:
+                    continue
+                opt["weight"][key] = a[key]
+            return opt
+
+        ckpt1 = torch.load(path1, map_location="cpu")
+        ckpt2 = torch.load(path2, map_location="cpu")
+        cfg = ckpt1["config"]
+        if "model" in ckpt1:
+            ckpt1 = extract(ckpt1)
+        else:
+            ckpt1 = ckpt1["weight"]
+        if "model" in ckpt2:
+            ckpt2 = extract(ckpt2)
+        else:
+            ckpt2 = ckpt2["weight"]
+        if sorted(list(ckpt1.keys())) != sorted(list(ckpt2.keys())):
+            return "Fail to merge the models. The model architectures are not the same."
+        opt = OrderedDict()
+        opt["weight"] = {}
+        for key in ckpt1.keys():
+            # try:
+            if key == "emb_g.weight" and ckpt1[key].shape != ckpt2[key].shape:
+                min_shape0 = min(ckpt1[key].shape[0], ckpt2[key].shape[0])
+                opt["weight"][key] = (
+                    alpha1 * (ckpt1[key][:min_shape0].float())
+                    + (1 - alpha1) * (ckpt2[key][:min_shape0].float())
+                ).half()
+            else:
+                opt["weight"][key] = (
+                    alpha1 * (ckpt1[key].float()) + (1 - alpha1) * (ckpt2[key].float())
+                ).half()
+        # except:
+        #     pdb.set_trace()
+        opt["config"] = cfg
+        """
+        if(sr=="40k"):opt["config"] = [1025, 32, 192, 192, 768, 2, 6, 3, 0, "1", [3, 7, 11], [[1, 3, 5], [1, 3, 5], [1, 3, 5]], [10, 10, 2, 2], 512, [16, 16, 4, 4,4], 109, 256, 40000]
+        elif(sr=="48k"):opt["config"] = [1025, 32, 192, 192, 768, 2, 6, 3, 0, "1", [3, 7, 11], [[1, 3, 5], [1, 3, 5], [1, 3, 5]], [10,6,2,2,2], 512, [16, 16, 4, 4], 109, 256, 48000]
+        elif(sr=="32k"):opt["config"] = [513, 32, 192, 192, 768, 2, 6, 3, 0, "1", [3, 7, 11], [[1, 3, 5], [1, 3, 5], [1, 3, 5]], [10, 4, 2, 2, 2], 512, [16, 16, 4, 4,4], 109, 256, 32000]
+        """
+        opt["sr"] = sr
+        opt["f0"] = 1 if f0 == i18n("是") else 0
+        opt["version"] = version
+        opt["info"] = info
+        torch.save(opt, "weights/%s.pth" % name)
+        return "Success."
+    except:
+        return traceback.format_exc()
diff --git a/infer/lib/train/utils.py b/infer/lib/train/utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..dd965fc4dd2af09e445a7f625f2681460874da7a
--- /dev/null
+++ b/infer/lib/train/utils.py
@@ -0,0 +1,478 @@
+import argparse
+import glob
+import json
+import logging
+import os
+import subprocess
+import sys
+import shutil
+
+import numpy as np
+import torch
+from scipy.io.wavfile import read
+
+MATPLOTLIB_FLAG = False
+
+logging.basicConfig(stream=sys.stdout, level=logging.DEBUG)
+logger = logging
+
+
+def load_checkpoint_d(checkpoint_path, combd, sbd, optimizer=None, load_opt=1):
+    assert os.path.isfile(checkpoint_path)
+    checkpoint_dict = torch.load(checkpoint_path, map_location="cpu")
+
+    ##################
+    def go(model, bkey):
+        saved_state_dict = checkpoint_dict[bkey]
+        if hasattr(model, "module"):
+            state_dict = model.module.state_dict()
+        else:
+            state_dict = model.state_dict()
+        new_state_dict = {}
+        for k, v in state_dict.items():  # 模型需要的shape
+            try:
+                new_state_dict[k] = saved_state_dict[k]
+                if saved_state_dict[k].shape != state_dict[k].shape:
+                    logger.warn(
+                        "shape-%s-mismatch. need: %s, get: %s",
+                        k,
+                        state_dict[k].shape,
+                        saved_state_dict[k].shape,
+                    )  #
+                    raise KeyError
+            except:
+                # logger.info(traceback.format_exc())
+                logger.info("%s is not in the checkpoint", k)  # pretrain缺失的
+                new_state_dict[k] = v  # 模型自带的随机值
+        if hasattr(model, "module"):
+            model.module.load_state_dict(new_state_dict, strict=False)
+        else:
+            model.load_state_dict(new_state_dict, strict=False)
+        return model
+
+    go(combd, "combd")
+    model = go(sbd, "sbd")
+    #############
+    logger.info("Loaded model weights")
+
+    iteration = checkpoint_dict["iteration"]
+    learning_rate = checkpoint_dict["learning_rate"]
+    if (
+        optimizer is not None and load_opt == 1
+    ):  ###加载不了，如果是空的的话，重新初始化，可能还会影响lr时间表的更新，因此在train文件最外围catch
+        #   try:
+        optimizer.load_state_dict(checkpoint_dict["optimizer"])
+    #   except:
+    #     traceback.print_exc()
+    logger.info("Loaded checkpoint '{}' (epoch {})".format(checkpoint_path, iteration))
+    return model, optimizer, learning_rate, iteration
+
+
+# def load_checkpoint(checkpoint_path, model, optimizer=None):
+#   assert os.path.isfile(checkpoint_path)
+#   checkpoint_dict = torch.load(checkpoint_path, map_location='cpu')
+#   iteration = checkpoint_dict['iteration']
+#   learning_rate = checkpoint_dict['learning_rate']
+#   if optimizer is not None:
+#     optimizer.load_state_dict(checkpoint_dict['optimizer'])
+#   # print(1111)
+#   saved_state_dict = checkpoint_dict['model']
+#   # print(1111)
+#
+#   if hasattr(model, 'module'):
+#     state_dict = model.module.state_dict()
+#   else:
+#     state_dict = model.state_dict()
+#   new_state_dict= {}
+#   for k, v in state_dict.items():
+#     try:
+#       new_state_dict[k] = saved_state_dict[k]
+#     except:
+#       logger.info("%s is not in the checkpoint" % k)
+#       new_state_dict[k] = v
+#   if hasattr(model, 'module'):
+#     model.module.load_state_dict(new_state_dict)
+#   else:
+#     model.load_state_dict(new_state_dict)
+#   logger.info("Loaded checkpoint '{}' (epoch {})" .format(
+#     checkpoint_path, iteration))
+#   return model, optimizer, learning_rate, iteration
+def load_checkpoint(checkpoint_path, model, optimizer=None, load_opt=1):
+    assert os.path.isfile(checkpoint_path)
+    checkpoint_dict = torch.load(checkpoint_path, map_location="cpu")
+
+    saved_state_dict = checkpoint_dict["model"]
+    if hasattr(model, "module"):
+        state_dict = model.module.state_dict()
+    else:
+        state_dict = model.state_dict()
+    new_state_dict = {}
+    for k, v in state_dict.items():  # 模型需要的shape
+        try:
+            new_state_dict[k] = saved_state_dict[k]
+            if saved_state_dict[k].shape != state_dict[k].shape:
+                logger.warn(
+                    "shape-%s-mismatch|need-%s|get-%s",
+                    k,
+                    state_dict[k].shape,
+                    saved_state_dict[k].shape,
+                )  #
+                raise KeyError
+        except:
+            # logger.info(traceback.format_exc())
+            logger.info("%s is not in the checkpoint", k)  # pretrain缺失的
+            new_state_dict[k] = v  # 模型自带的随机值
+    if hasattr(model, "module"):
+        model.module.load_state_dict(new_state_dict, strict=False)
+    else:
+        model.load_state_dict(new_state_dict, strict=False)
+    logger.info("Loaded model weights")
+
+    iteration = checkpoint_dict["iteration"]
+    learning_rate = checkpoint_dict["learning_rate"]
+    if (
+        optimizer is not None and load_opt == 1
+    ):  ###加载不了，如果是空的的话，重新初始化，可能还会影响lr时间表的更新，因此在train文件最外围catch
+        #   try:
+        optimizer.load_state_dict(checkpoint_dict["optimizer"])
+    #   except:
+    #     traceback.print_exc()
+    logger.info("Loaded checkpoint '{}' (epoch {})".format(checkpoint_path, iteration))
+    return model, optimizer, learning_rate, iteration
+
+
+def save_checkpoint(model, optimizer, learning_rate, iteration, checkpoint_path):
+    logger.info(
+        "Saving model and optimizer state at epoch {} to {}".format(
+            iteration, checkpoint_path
+        )
+    )
+    if hasattr(model, "module"):
+        state_dict = model.module.state_dict()
+    else:
+        state_dict = model.state_dict()
+    torch.save(
+        {
+            "model": state_dict,
+            "iteration": iteration,
+            "optimizer": optimizer.state_dict(),
+            "learning_rate": learning_rate,
+        },
+        checkpoint_path,
+    )
+
+
+def save_checkpoint_d(combd, sbd, optimizer, learning_rate, iteration, checkpoint_path):
+    logger.info(
+        "Saving model and optimizer state at epoch {} to {}".format(
+            iteration, checkpoint_path
+        )
+    )
+    if hasattr(combd, "module"):
+        state_dict_combd = combd.module.state_dict()
+    else:
+        state_dict_combd = combd.state_dict()
+    if hasattr(sbd, "module"):
+        state_dict_sbd = sbd.module.state_dict()
+    else:
+        state_dict_sbd = sbd.state_dict()
+    torch.save(
+        {
+            "combd": state_dict_combd,
+            "sbd": state_dict_sbd,
+            "iteration": iteration,
+            "optimizer": optimizer.state_dict(),
+            "learning_rate": learning_rate,
+        },
+        checkpoint_path,
+    )
+
+
+def summarize(
+    writer,
+    global_step,
+    scalars={},
+    histograms={},
+    images={},
+    audios={},
+    audio_sampling_rate=22050,
+):
+    for k, v in scalars.items():
+        writer.add_scalar(k, v, global_step)
+    for k, v in histograms.items():
+        writer.add_histogram(k, v, global_step)
+    for k, v in images.items():
+        writer.add_image(k, v, global_step, dataformats="HWC")
+    for k, v in audios.items():
+        writer.add_audio(k, v, global_step, audio_sampling_rate)
+
+
+def latest_checkpoint_path(dir_path, regex="G_*.pth"):
+    f_list = glob.glob(os.path.join(dir_path, regex))
+    f_list.sort(key=lambda f: int("".join(filter(str.isdigit, f))))
+    x = f_list[-1]
+    logger.debug(x)
+    return x
+
+
+def plot_spectrogram_to_numpy(spectrogram):
+    global MATPLOTLIB_FLAG
+    if not MATPLOTLIB_FLAG:
+        import matplotlib
+
+        matplotlib.use("Agg")
+        MATPLOTLIB_FLAG = True
+        mpl_logger = logging.getLogger("matplotlib")
+        mpl_logger.setLevel(logging.WARNING)
+    import matplotlib.pylab as plt
+    import numpy as np
+
+    fig, ax = plt.subplots(figsize=(10, 2))
+    im = ax.imshow(spectrogram, aspect="auto", origin="lower", interpolation="none")
+    plt.colorbar(im, ax=ax)
+    plt.xlabel("Frames")
+    plt.ylabel("Channels")
+    plt.tight_layout()
+
+    fig.canvas.draw()
+    data = np.fromstring(fig.canvas.tostring_rgb(), dtype=np.uint8, sep="")
+    data = data.reshape(fig.canvas.get_width_height()[::-1] + (3,))
+    plt.close()
+    return data
+
+
+def plot_alignment_to_numpy(alignment, info=None):
+    global MATPLOTLIB_FLAG
+    if not MATPLOTLIB_FLAG:
+        import matplotlib
+
+        matplotlib.use("Agg")
+        MATPLOTLIB_FLAG = True
+        mpl_logger = logging.getLogger("matplotlib")
+        mpl_logger.setLevel(logging.WARNING)
+    import matplotlib.pylab as plt
+    import numpy as np
+
+    fig, ax = plt.subplots(figsize=(6, 4))
+    im = ax.imshow(
+        alignment.transpose(), aspect="auto", origin="lower", interpolation="none"
+    )
+    fig.colorbar(im, ax=ax)
+    xlabel = "Decoder timestep"
+    if info is not None:
+        xlabel += "\n\n" + info
+    plt.xlabel(xlabel)
+    plt.ylabel("Encoder timestep")
+    plt.tight_layout()
+
+    fig.canvas.draw()
+    data = np.fromstring(fig.canvas.tostring_rgb(), dtype=np.uint8, sep="")
+    data = data.reshape(fig.canvas.get_width_height()[::-1] + (3,))
+    plt.close()
+    return data
+
+
+def load_wav_to_torch(full_path):
+    sampling_rate, data = read(full_path)
+    return torch.FloatTensor(data.astype(np.float32)), sampling_rate
+
+
+def load_filepaths_and_text(filename, split="|"):
+    with open(filename, encoding="utf-8") as f:
+        filepaths_and_text = [line.strip().split(split) for line in f]
+    return filepaths_and_text
+
+
+def get_hparams(init=True):
+    """
+    todo:
+      结尾七人组：
+        保存频率、总epoch                     done
+        bs                                    done
+        pretrainG、pretrainD                  done
+        卡号：os.en["CUDA_VISIBLE_DEVICES"]   done
+        if_latest                             done
+      模型：if_f0                             done
+      采样率：自动选择config                  done
+      是否缓存数据集进GPU:if_cache_data_in_gpu done
+
+      -m:
+        自动决定training_files路径,改掉train_nsf_load_pretrain.py里的hps.data.training_files    done
+      -c不要了
+    """
+    parser = argparse.ArgumentParser()
+    parser.add_argument(
+        "-se",
+        "--save_every_epoch",
+        type=int,
+        required=True,
+        help="checkpoint save frequency (epoch)",
+    )
+    parser.add_argument(
+        "-te", "--total_epoch", type=int, required=True, help="total_epoch"
+    )
+    parser.add_argument(
+        "-pg", "--pretrainG", type=str, default="", help="Pretrained Discriminator path"
+    )
+    parser.add_argument(
+        "-pd", "--pretrainD", type=str, default="", help="Pretrained Generator path"
+    )
+    parser.add_argument("-g", "--gpus", type=str, default="0", help="split by -")
+    parser.add_argument(
+        "-bs", "--batch_size", type=int, required=True, help="batch size"
+    )
+    parser.add_argument(
+        "-e", "--experiment_dir", type=str, required=True, help="experiment dir"
+    )  # -m
+    parser.add_argument(
+        "-sr", "--sample_rate", type=str, required=True, help="sample rate, 32k/40k/48k"
+    )
+    parser.add_argument(
+        "-sw",
+        "--save_every_weights",
+        type=str,
+        default="0",
+        help="save the extracted model in weights directory when saving checkpoints",
+    )
+    parser.add_argument(
+        "-v", "--version", type=str, required=True, help="model version"
+    )
+    parser.add_argument(
+        "-f0",
+        "--if_f0",
+        type=int,
+        required=True,
+        help="use f0 as one of the inputs of the model, 1 or 0",
+    )
+    parser.add_argument(
+        "-l",
+        "--if_latest",
+        type=int,
+        required=True,
+        help="if only save the latest G/D pth file, 1 or 0",
+    )
+    parser.add_argument(
+        "-c",
+        "--if_cache_data_in_gpu",
+        type=int,
+        required=True,
+        help="if caching the dataset in GPU memory, 1 or 0",
+    )
+
+    args = parser.parse_args()
+    name = args.experiment_dir
+    experiment_dir = os.path.join("./logs", args.experiment_dir)
+
+    config_save_path = os.path.join(experiment_dir, "config.json")
+    with open(config_save_path, "r") as f:
+        config = json.load(f)
+
+    hparams = HParams(**config)
+    hparams.model_dir = hparams.experiment_dir = experiment_dir
+    hparams.save_every_epoch = args.save_every_epoch
+    hparams.name = name
+    hparams.total_epoch = args.total_epoch
+    hparams.pretrainG = args.pretrainG
+    hparams.pretrainD = args.pretrainD
+    hparams.version = args.version
+    hparams.gpus = args.gpus
+    hparams.train.batch_size = args.batch_size
+    hparams.sample_rate = args.sample_rate
+    hparams.if_f0 = args.if_f0
+    hparams.if_latest = args.if_latest
+    hparams.save_every_weights = args.save_every_weights
+    hparams.if_cache_data_in_gpu = args.if_cache_data_in_gpu
+    hparams.data.training_files = "%s/filelist.txt" % experiment_dir
+    return hparams
+
+
+def get_hparams_from_dir(model_dir):
+    config_save_path = os.path.join(model_dir, "config.json")
+    with open(config_save_path, "r") as f:
+        data = f.read()
+    config = json.loads(data)
+
+    hparams = HParams(**config)
+    hparams.model_dir = model_dir
+    return hparams
+
+
+def get_hparams_from_file(config_path):
+    with open(config_path, "r") as f:
+        data = f.read()
+    config = json.loads(data)
+
+    hparams = HParams(**config)
+    return hparams
+
+
+def check_git_hash(model_dir):
+    source_dir = os.path.dirname(os.path.realpath(__file__))
+    if not os.path.exists(os.path.join(source_dir, ".git")):
+        logger.warn(
+            "{} is not a git repository, therefore hash value comparison will be ignored.".format(
+                source_dir
+            )
+        )
+        return
+
+    cur_hash = subprocess.getoutput("git rev-parse HEAD")
+
+    path = os.path.join(model_dir, "githash")
+    if os.path.exists(path):
+        saved_hash = open(path).read()
+        if saved_hash != cur_hash:
+            logger.warn(
+                "git hash values are different. {}(saved) != {}(current)".format(
+                    saved_hash[:8], cur_hash[:8]
+                )
+            )
+    else:
+        open(path, "w").write(cur_hash)
+
+
+def get_logger(model_dir, filename="train.log"):
+    global logger
+    logger = logging.getLogger(os.path.basename(model_dir))
+    logger.setLevel(logging.DEBUG)
+
+    formatter = logging.Formatter("%(asctime)s\t%(name)s\t%(levelname)s\t%(message)s")
+    if not os.path.exists(model_dir):
+        os.makedirs(model_dir)
+    h = logging.FileHandler(os.path.join(model_dir, filename))
+    h.setLevel(logging.DEBUG)
+    h.setFormatter(formatter)
+    logger.addHandler(h)
+    return logger
+
+
+class HParams:
+    def __init__(self, **kwargs):
+        for k, v in kwargs.items():
+            if type(v) == dict:
+                v = HParams(**v)
+            self[k] = v
+
+    def keys(self):
+        return self.__dict__.keys()
+
+    def items(self):
+        return self.__dict__.items()
+
+    def values(self):
+        return self.__dict__.values()
+
+    def __len__(self):
+        return len(self.__dict__)
+
+    def __getitem__(self, key):
+        return getattr(self, key)
+
+    def __setitem__(self, key, value):
+        return setattr(self, key, value)
+
+    def __contains__(self, key):
+        return key in self.__dict__
+
+    def __repr__(self):
+        return self.__dict__.__repr__()
diff --git a/infer/lib/uvr5_pack/lib_v5/dataset.py b/infer/lib/uvr5_pack/lib_v5/dataset.py
new file mode 100644
index 0000000000000000000000000000000000000000..cfd01a174978d97180a897e40cb59ecadec1d12e
--- /dev/null
+++ b/infer/lib/uvr5_pack/lib_v5/dataset.py
@@ -0,0 +1,183 @@
+import os
+import random
+
+import numpy as np
+import torch
+import torch.utils.data
+from tqdm import tqdm
+
+from . import spec_utils
+
+
+class VocalRemoverValidationSet(torch.utils.data.Dataset):
+    def __init__(self, patch_list):
+        self.patch_list = patch_list
+
+    def __len__(self):
+        return len(self.patch_list)
+
+    def __getitem__(self, idx):
+        path = self.patch_list[idx]
+        data = np.load(path)
+
+        X, y = data["X"], data["y"]
+
+        X_mag = np.abs(X)
+        y_mag = np.abs(y)
+
+        return X_mag, y_mag
+
+
+def make_pair(mix_dir, inst_dir):
+    input_exts = [".wav", ".m4a", ".mp3", ".mp4", ".flac"]
+
+    X_list = sorted(
+        [
+            os.path.join(mix_dir, fname)
+            for fname in os.listdir(mix_dir)
+            if os.path.splitext(fname)[1] in input_exts
+        ]
+    )
+    y_list = sorted(
+        [
+            os.path.join(inst_dir, fname)
+            for fname in os.listdir(inst_dir)
+            if os.path.splitext(fname)[1] in input_exts
+        ]
+    )
+
+    filelist = list(zip(X_list, y_list))
+
+    return filelist
+
+
+def train_val_split(dataset_dir, split_mode, val_rate, val_filelist):
+    if split_mode == "random":
+        filelist = make_pair(
+            os.path.join(dataset_dir, "mixtures"),
+            os.path.join(dataset_dir, "instruments"),
+        )
+
+        random.shuffle(filelist)
+
+        if len(val_filelist) == 0:
+            val_size = int(len(filelist) * val_rate)
+            train_filelist = filelist[:-val_size]
+            val_filelist = filelist[-val_size:]
+        else:
+            train_filelist = [
+                pair for pair in filelist if list(pair) not in val_filelist
+            ]
+    elif split_mode == "subdirs":
+        if len(val_filelist) != 0:
+            raise ValueError(
+                "The `val_filelist` option is not available in `subdirs` mode"
+            )
+
+        train_filelist = make_pair(
+            os.path.join(dataset_dir, "training/mixtures"),
+            os.path.join(dataset_dir, "training/instruments"),
+        )
+
+        val_filelist = make_pair(
+            os.path.join(dataset_dir, "validation/mixtures"),
+            os.path.join(dataset_dir, "validation/instruments"),
+        )
+
+    return train_filelist, val_filelist
+
+
+def augment(X, y, reduction_rate, reduction_mask, mixup_rate, mixup_alpha):
+    perm = np.random.permutation(len(X))
+    for i, idx in enumerate(tqdm(perm)):
+        if np.random.uniform() < reduction_rate:
+            y[idx] = spec_utils.reduce_vocal_aggressively(
+                X[idx], y[idx], reduction_mask
+            )
+
+        if np.random.uniform() < 0.5:
+            # swap channel
+            X[idx] = X[idx, ::-1]
+            y[idx] = y[idx, ::-1]
+        if np.random.uniform() < 0.02:
+            # mono
+            X[idx] = X[idx].mean(axis=0, keepdims=True)
+            y[idx] = y[idx].mean(axis=0, keepdims=True)
+        if np.random.uniform() < 0.02:
+            # inst
+            X[idx] = y[idx]
+
+        if np.random.uniform() < mixup_rate and i < len(perm) - 1:
+            lam = np.random.beta(mixup_alpha, mixup_alpha)
+            X[idx] = lam * X[idx] + (1 - lam) * X[perm[i + 1]]
+            y[idx] = lam * y[idx] + (1 - lam) * y[perm[i + 1]]
+
+    return X, y
+
+
+def make_padding(width, cropsize, offset):
+    left = offset
+    roi_size = cropsize - left * 2
+    if roi_size == 0:
+        roi_size = cropsize
+    right = roi_size - (width % roi_size) + left
+
+    return left, right, roi_size
+
+
+def make_training_set(filelist, cropsize, patches, sr, hop_length, n_fft, offset):
+    len_dataset = patches * len(filelist)
+
+    X_dataset = np.zeros((len_dataset, 2, n_fft // 2 + 1, cropsize), dtype=np.complex64)
+    y_dataset = np.zeros((len_dataset, 2, n_fft // 2 + 1, cropsize), dtype=np.complex64)
+
+    for i, (X_path, y_path) in enumerate(tqdm(filelist)):
+        X, y = spec_utils.cache_or_load(X_path, y_path, sr, hop_length, n_fft)
+        coef = np.max([np.abs(X).max(), np.abs(y).max()])
+        X, y = X / coef, y / coef
+
+        l, r, roi_size = make_padding(X.shape[2], cropsize, offset)
+        X_pad = np.pad(X, ((0, 0), (0, 0), (l, r)), mode="constant")
+        y_pad = np.pad(y, ((0, 0), (0, 0), (l, r)), mode="constant")
+
+        starts = np.random.randint(0, X_pad.shape[2] - cropsize, patches)
+        ends = starts + cropsize
+        for j in range(patches):
+            idx = i * patches + j
+            X_dataset[idx] = X_pad[:, :, starts[j] : ends[j]]
+            y_dataset[idx] = y_pad[:, :, starts[j] : ends[j]]
+
+    return X_dataset, y_dataset
+
+
+def make_validation_set(filelist, cropsize, sr, hop_length, n_fft, offset):
+    patch_list = []
+    patch_dir = "cs{}_sr{}_hl{}_nf{}_of{}".format(
+        cropsize, sr, hop_length, n_fft, offset
+    )
+    os.makedirs(patch_dir, exist_ok=True)
+
+    for i, (X_path, y_path) in enumerate(tqdm(filelist)):
+        basename = os.path.splitext(os.path.basename(X_path))[0]
+
+        X, y = spec_utils.cache_or_load(X_path, y_path, sr, hop_length, n_fft)
+        coef = np.max([np.abs(X).max(), np.abs(y).max()])
+        X, y = X / coef, y / coef
+
+        l, r, roi_size = make_padding(X.shape[2], cropsize, offset)
+        X_pad = np.pad(X, ((0, 0), (0, 0), (l, r)), mode="constant")
+        y_pad = np.pad(y, ((0, 0), (0, 0), (l, r)), mode="constant")
+
+        len_dataset = int(np.ceil(X.shape[2] / roi_size))
+        for j in range(len_dataset):
+            outpath = os.path.join(patch_dir, "{}_p{}.npz".format(basename, j))
+            start = j * roi_size
+            if not os.path.exists(outpath):
+                np.savez(
+                    outpath,
+                    X=X_pad[:, :, start : start + cropsize],
+                    y=y_pad[:, :, start : start + cropsize],
+                )
+            patch_list.append(outpath)
+
+    return VocalRemoverValidationSet(patch_list)
diff --git a/infer/lib/uvr5_pack/lib_v5/layers.py b/infer/lib/uvr5_pack/lib_v5/layers.py
new file mode 100644
index 0000000000000000000000000000000000000000..4fc1b5cb85a3327f60cbb9f5deffbeeaaac516ad
--- /dev/null
+++ b/infer/lib/uvr5_pack/lib_v5/layers.py
@@ -0,0 +1,118 @@
+import torch
+import torch.nn.functional as F
+from torch import nn
+
+from . import spec_utils
+
+
+class Conv2DBNActiv(nn.Module):
+    def __init__(self, nin, nout, ksize=3, stride=1, pad=1, dilation=1, activ=nn.ReLU):
+        super(Conv2DBNActiv, self).__init__()
+        self.conv = nn.Sequential(
+            nn.Conv2d(
+                nin,
+                nout,
+                kernel_size=ksize,
+                stride=stride,
+                padding=pad,
+                dilation=dilation,
+                bias=False,
+            ),
+            nn.BatchNorm2d(nout),
+            activ(),
+        )
+
+    def __call__(self, x):
+        return self.conv(x)
+
+
+class SeperableConv2DBNActiv(nn.Module):
+    def __init__(self, nin, nout, ksize=3, stride=1, pad=1, dilation=1, activ=nn.ReLU):
+        super(SeperableConv2DBNActiv, self).__init__()
+        self.conv = nn.Sequential(
+            nn.Conv2d(
+                nin,
+                nin,
+                kernel_size=ksize,
+                stride=stride,
+                padding=pad,
+                dilation=dilation,
+                groups=nin,
+                bias=False,
+            ),
+            nn.Conv2d(nin, nout, kernel_size=1, bias=False),
+            nn.BatchNorm2d(nout),
+            activ(),
+        )
+
+    def __call__(self, x):
+        return self.conv(x)
+
+
+class Encoder(nn.Module):
+    def __init__(self, nin, nout, ksize=3, stride=1, pad=1, activ=nn.LeakyReLU):
+        super(Encoder, self).__init__()
+        self.conv1 = Conv2DBNActiv(nin, nout, ksize, 1, pad, activ=activ)
+        self.conv2 = Conv2DBNActiv(nout, nout, ksize, stride, pad, activ=activ)
+
+    def __call__(self, x):
+        skip = self.conv1(x)
+        h = self.conv2(skip)
+
+        return h, skip
+
+
+class Decoder(nn.Module):
+    def __init__(
+        self, nin, nout, ksize=3, stride=1, pad=1, activ=nn.ReLU, dropout=False
+    ):
+        super(Decoder, self).__init__()
+        self.conv = Conv2DBNActiv(nin, nout, ksize, 1, pad, activ=activ)
+        self.dropout = nn.Dropout2d(0.1) if dropout else None
+
+    def __call__(self, x, skip=None):
+        x = F.interpolate(x, scale_factor=2, mode="bilinear", align_corners=True)
+        if skip is not None:
+            skip = spec_utils.crop_center(skip, x)
+            x = torch.cat([x, skip], dim=1)
+        h = self.conv(x)
+
+        if self.dropout is not None:
+            h = self.dropout(h)
+
+        return h
+
+
+class ASPPModule(nn.Module):
+    def __init__(self, nin, nout, dilations=(4, 8, 16), activ=nn.ReLU):
+        super(ASPPModule, self).__init__()
+        self.conv1 = nn.Sequential(
+            nn.AdaptiveAvgPool2d((1, None)),
+            Conv2DBNActiv(nin, nin, 1, 1, 0, activ=activ),
+        )
+        self.conv2 = Conv2DBNActiv(nin, nin, 1, 1, 0, activ=activ)
+        self.conv3 = SeperableConv2DBNActiv(
+            nin, nin, 3, 1, dilations[0], dilations[0], activ=activ
+        )
+        self.conv4 = SeperableConv2DBNActiv(
+            nin, nin, 3, 1, dilations[1], dilations[1], activ=activ
+        )
+        self.conv5 = SeperableConv2DBNActiv(
+            nin, nin, 3, 1, dilations[2], dilations[2], activ=activ
+        )
+        self.bottleneck = nn.Sequential(
+            Conv2DBNActiv(nin * 5, nout, 1, 1, 0, activ=activ), nn.Dropout2d(0.1)
+        )
+
+    def forward(self, x):
+        _, _, h, w = x.size()
+        feat1 = F.interpolate(
+            self.conv1(x), size=(h, w), mode="bilinear", align_corners=True
+        )
+        feat2 = self.conv2(x)
+        feat3 = self.conv3(x)
+        feat4 = self.conv4(x)
+        feat5 = self.conv5(x)
+        out = torch.cat((feat1, feat2, feat3, feat4, feat5), dim=1)
+        bottle = self.bottleneck(out)
+        return bottle
diff --git a/infer/lib/uvr5_pack/lib_v5/layers_123812KB .py b/infer/lib/uvr5_pack/lib_v5/layers_123812KB .py
new file mode 100644
index 0000000000000000000000000000000000000000..4fc1b5cb85a3327f60cbb9f5deffbeeaaac516ad
--- /dev/null
+++ b/infer/lib/uvr5_pack/lib_v5/layers_123812KB .py	
@@ -0,0 +1,118 @@
+import torch
+import torch.nn.functional as F
+from torch import nn
+
+from . import spec_utils
+
+
+class Conv2DBNActiv(nn.Module):
+    def __init__(self, nin, nout, ksize=3, stride=1, pad=1, dilation=1, activ=nn.ReLU):
+        super(Conv2DBNActiv, self).__init__()
+        self.conv = nn.Sequential(
+            nn.Conv2d(
+                nin,
+                nout,
+                kernel_size=ksize,
+                stride=stride,
+                padding=pad,
+                dilation=dilation,
+                bias=False,
+            ),
+            nn.BatchNorm2d(nout),
+            activ(),
+        )
+
+    def __call__(self, x):
+        return self.conv(x)
+
+
+class SeperableConv2DBNActiv(nn.Module):
+    def __init__(self, nin, nout, ksize=3, stride=1, pad=1, dilation=1, activ=nn.ReLU):
+        super(SeperableConv2DBNActiv, self).__init__()
+        self.conv = nn.Sequential(
+            nn.Conv2d(
+                nin,
+                nin,
+                kernel_size=ksize,
+                stride=stride,
+                padding=pad,
+                dilation=dilation,
+                groups=nin,
+                bias=False,
+            ),
+            nn.Conv2d(nin, nout, kernel_size=1, bias=False),
+            nn.BatchNorm2d(nout),
+            activ(),
+        )
+
+    def __call__(self, x):
+        return self.conv(x)
+
+
+class Encoder(nn.Module):
+    def __init__(self, nin, nout, ksize=3, stride=1, pad=1, activ=nn.LeakyReLU):
+        super(Encoder, self).__init__()
+        self.conv1 = Conv2DBNActiv(nin, nout, ksize, 1, pad, activ=activ)
+        self.conv2 = Conv2DBNActiv(nout, nout, ksize, stride, pad, activ=activ)
+
+    def __call__(self, x):
+        skip = self.conv1(x)
+        h = self.conv2(skip)
+
+        return h, skip
+
+
+class Decoder(nn.Module):
+    def __init__(
+        self, nin, nout, ksize=3, stride=1, pad=1, activ=nn.ReLU, dropout=False
+    ):
+        super(Decoder, self).__init__()
+        self.conv = Conv2DBNActiv(nin, nout, ksize, 1, pad, activ=activ)
+        self.dropout = nn.Dropout2d(0.1) if dropout else None
+
+    def __call__(self, x, skip=None):
+        x = F.interpolate(x, scale_factor=2, mode="bilinear", align_corners=True)
+        if skip is not None:
+            skip = spec_utils.crop_center(skip, x)
+            x = torch.cat([x, skip], dim=1)
+        h = self.conv(x)
+
+        if self.dropout is not None:
+            h = self.dropout(h)
+
+        return h
+
+
+class ASPPModule(nn.Module):
+    def __init__(self, nin, nout, dilations=(4, 8, 16), activ=nn.ReLU):
+        super(ASPPModule, self).__init__()
+        self.conv1 = nn.Sequential(
+            nn.AdaptiveAvgPool2d((1, None)),
+            Conv2DBNActiv(nin, nin, 1, 1, 0, activ=activ),
+        )
+        self.conv2 = Conv2DBNActiv(nin, nin, 1, 1, 0, activ=activ)
+        self.conv3 = SeperableConv2DBNActiv(
+            nin, nin, 3, 1, dilations[0], dilations[0], activ=activ
+        )
+        self.conv4 = SeperableConv2DBNActiv(
+            nin, nin, 3, 1, dilations[1], dilations[1], activ=activ
+        )
+        self.conv5 = SeperableConv2DBNActiv(
+            nin, nin, 3, 1, dilations[2], dilations[2], activ=activ
+        )
+        self.bottleneck = nn.Sequential(
+            Conv2DBNActiv(nin * 5, nout, 1, 1, 0, activ=activ), nn.Dropout2d(0.1)
+        )
+
+    def forward(self, x):
+        _, _, h, w = x.size()
+        feat1 = F.interpolate(
+            self.conv1(x), size=(h, w), mode="bilinear", align_corners=True
+        )
+        feat2 = self.conv2(x)
+        feat3 = self.conv3(x)
+        feat4 = self.conv4(x)
+        feat5 = self.conv5(x)
+        out = torch.cat((feat1, feat2, feat3, feat4, feat5), dim=1)
+        bottle = self.bottleneck(out)
+        return bottle
diff --git a/infer/lib/uvr5_pack/lib_v5/layers_123821KB.py b/infer/lib/uvr5_pack/lib_v5/layers_123821KB.py
new file mode 100644
index 0000000000000000000000000000000000000000..4fc1b5cb85a3327f60cbb9f5deffbeeaaac516ad
--- /dev/null
+++ b/infer/lib/uvr5_pack/lib_v5/layers_123821KB.py
@@ -0,0 +1,118 @@
+import torch
+import torch.nn.functional as F
+from torch import nn
+
+from . import spec_utils
+
+
+class Conv2DBNActiv(nn.Module):
+    def __init__(self, nin, nout, ksize=3, stride=1, pad=1, dilation=1, activ=nn.ReLU):
+        super(Conv2DBNActiv, self).__init__()
+        self.conv = nn.Sequential(
+            nn.Conv2d(
+                nin,
+                nout,
+                kernel_size=ksize,
+                stride=stride,
+                padding=pad,
+                dilation=dilation,
+                bias=False,
+            ),
+            nn.BatchNorm2d(nout),
+            activ(),
+        )
+
+    def __call__(self, x):
+        return self.conv(x)
+
+
+class SeperableConv2DBNActiv(nn.Module):
+    def __init__(self, nin, nout, ksize=3, stride=1, pad=1, dilation=1, activ=nn.ReLU):
+        super(SeperableConv2DBNActiv, self).__init__()
+        self.conv = nn.Sequential(
+            nn.Conv2d(
+                nin,
+                nin,
+                kernel_size=ksize,
+                stride=stride,
+                padding=pad,
+                dilation=dilation,
+                groups=nin,
+                bias=False,
+            ),
+            nn.Conv2d(nin, nout, kernel_size=1, bias=False),
+            nn.BatchNorm2d(nout),
+            activ(),
+        )
+
+    def __call__(self, x):
+        return self.conv(x)
+
+
+class Encoder(nn.Module):
+    def __init__(self, nin, nout, ksize=3, stride=1, pad=1, activ=nn.LeakyReLU):
+        super(Encoder, self).__init__()
+        self.conv1 = Conv2DBNActiv(nin, nout, ksize, 1, pad, activ=activ)
+        self.conv2 = Conv2DBNActiv(nout, nout, ksize, stride, pad, activ=activ)
+
+    def __call__(self, x):
+        skip = self.conv1(x)
+        h = self.conv2(skip)
+
+        return h, skip
+
+
+class Decoder(nn.Module):
+    def __init__(
+        self, nin, nout, ksize=3, stride=1, pad=1, activ=nn.ReLU, dropout=False
+    ):
+        super(Decoder, self).__init__()
+        self.conv = Conv2DBNActiv(nin, nout, ksize, 1, pad, activ=activ)
+        self.dropout = nn.Dropout2d(0.1) if dropout else None
+
+    def __call__(self, x, skip=None):
+        x = F.interpolate(x, scale_factor=2, mode="bilinear", align_corners=True)
+        if skip is not None:
+            skip = spec_utils.crop_center(skip, x)
+            x = torch.cat([x, skip], dim=1)
+        h = self.conv(x)
+
+        if self.dropout is not None:
+            h = self.dropout(h)
+
+        return h
+
+
+class ASPPModule(nn.Module):
+    def __init__(self, nin, nout, dilations=(4, 8, 16), activ=nn.ReLU):
+        super(ASPPModule, self).__init__()
+        self.conv1 = nn.Sequential(
+            nn.AdaptiveAvgPool2d((1, None)),
+            Conv2DBNActiv(nin, nin, 1, 1, 0, activ=activ),
+        )
+        self.conv2 = Conv2DBNActiv(nin, nin, 1, 1, 0, activ=activ)
+        self.conv3 = SeperableConv2DBNActiv(
+            nin, nin, 3, 1, dilations[0], dilations[0], activ=activ
+        )
+        self.conv4 = SeperableConv2DBNActiv(
+            nin, nin, 3, 1, dilations[1], dilations[1], activ=activ
+        )
+        self.conv5 = SeperableConv2DBNActiv(
+            nin, nin, 3, 1, dilations[2], dilations[2], activ=activ
+        )
+        self.bottleneck = nn.Sequential(
+            Conv2DBNActiv(nin * 5, nout, 1, 1, 0, activ=activ), nn.Dropout2d(0.1)
+        )
+
+    def forward(self, x):
+        _, _, h, w = x.size()
+        feat1 = F.interpolate(
+            self.conv1(x), size=(h, w), mode="bilinear", align_corners=True
+        )
+        feat2 = self.conv2(x)
+        feat3 = self.conv3(x)
+        feat4 = self.conv4(x)
+        feat5 = self.conv5(x)
+        out = torch.cat((feat1, feat2, feat3, feat4, feat5), dim=1)
+        bottle = self.bottleneck(out)
+        return bottle
diff --git a/infer/lib/uvr5_pack/lib_v5/layers_33966KB.py b/infer/lib/uvr5_pack/lib_v5/layers_33966KB.py
new file mode 100644
index 0000000000000000000000000000000000000000..9b127bc6427f5c60c8cf85603a3d8a093c3501c4
--- /dev/null
+++ b/infer/lib/uvr5_pack/lib_v5/layers_33966KB.py
@@ -0,0 +1,126 @@
+import torch
+import torch.nn.functional as F
+from torch import nn
+
+from . import spec_utils
+
+
+class Conv2DBNActiv(nn.Module):
+    def __init__(self, nin, nout, ksize=3, stride=1, pad=1, dilation=1, activ=nn.ReLU):
+        super(Conv2DBNActiv, self).__init__()
+        self.conv = nn.Sequential(
+            nn.Conv2d(
+                nin,
+                nout,
+                kernel_size=ksize,
+                stride=stride,
+                padding=pad,
+                dilation=dilation,
+                bias=False,
+            ),
+            nn.BatchNorm2d(nout),
+            activ(),
+        )
+
+    def __call__(self, x):
+        return self.conv(x)
+
+
+class SeperableConv2DBNActiv(nn.Module):
+    def __init__(self, nin, nout, ksize=3, stride=1, pad=1, dilation=1, activ=nn.ReLU):
+        super(SeperableConv2DBNActiv, self).__init__()
+        self.conv = nn.Sequential(
+            nn.Conv2d(
+                nin,
+                nin,
+                kernel_size=ksize,
+                stride=stride,
+                padding=pad,
+                dilation=dilation,
+                groups=nin,
+                bias=False,
+            ),
+            nn.Conv2d(nin, nout, kernel_size=1, bias=False),
+            nn.BatchNorm2d(nout),
+            activ(),
+        )
+
+    def __call__(self, x):
+        return self.conv(x)
+
+
+class Encoder(nn.Module):
+    def __init__(self, nin, nout, ksize=3, stride=1, pad=1, activ=nn.LeakyReLU):
+        super(Encoder, self).__init__()
+        self.conv1 = Conv2DBNActiv(nin, nout, ksize, 1, pad, activ=activ)
+        self.conv2 = Conv2DBNActiv(nout, nout, ksize, stride, pad, activ=activ)
+
+    def __call__(self, x):
+        skip = self.conv1(x)
+        h = self.conv2(skip)
+
+        return h, skip
+
+
+class Decoder(nn.Module):
+    def __init__(
+        self, nin, nout, ksize=3, stride=1, pad=1, activ=nn.ReLU, dropout=False
+    ):
+        super(Decoder, self).__init__()
+        self.conv = Conv2DBNActiv(nin, nout, ksize, 1, pad, activ=activ)
+        self.dropout = nn.Dropout2d(0.1) if dropout else None
+
+    def __call__(self, x, skip=None):
+        x = F.interpolate(x, scale_factor=2, mode="bilinear", align_corners=True)
+        if skip is not None:
+            skip = spec_utils.crop_center(skip, x)
+            x = torch.cat([x, skip], dim=1)
+        h = self.conv(x)
+
+        if self.dropout is not None:
+            h = self.dropout(h)
+
+        return h
+
+
+class ASPPModule(nn.Module):
+    def __init__(self, nin, nout, dilations=(4, 8, 16, 32, 64), activ=nn.ReLU):
+        super(ASPPModule, self).__init__()
+        self.conv1 = nn.Sequential(
+            nn.AdaptiveAvgPool2d((1, None)),
+            Conv2DBNActiv(nin, nin, 1, 1, 0, activ=activ),
+        )
+        self.conv2 = Conv2DBNActiv(nin, nin, 1, 1, 0, activ=activ)
+        self.conv3 = SeperableConv2DBNActiv(
+            nin, nin, 3, 1, dilations[0], dilations[0], activ=activ
+        )
+        self.conv4 = SeperableConv2DBNActiv(
+            nin, nin, 3, 1, dilations[1], dilations[1], activ=activ
+        )
+        self.conv5 = SeperableConv2DBNActiv(
+            nin, nin, 3, 1, dilations[2], dilations[2], activ=activ
+        )
+        self.conv6 = SeperableConv2DBNActiv(
+            nin, nin, 3, 1, dilations[2], dilations[2], activ=activ
+        )
+        self.conv7 = SeperableConv2DBNActiv(
+            nin, nin, 3, 1, dilations[2], dilations[2], activ=activ
+        )
+        self.bottleneck = nn.Sequential(
+            Conv2DBNActiv(nin * 7, nout, 1, 1, 0, activ=activ), nn.Dropout2d(0.1)
+        )
+
+    def forward(self, x):
+        _, _, h, w = x.size()
+        feat1 = F.interpolate(
+            self.conv1(x), size=(h, w), mode="bilinear", align_corners=True
+        )
+        feat2 = self.conv2(x)
+        feat3 = self.conv3(x)
+        feat4 = self.conv4(x)
+        feat5 = self.conv5(x)
+        feat6 = self.conv6(x)
+        feat7 = self.conv7(x)
+        out = torch.cat((feat1, feat2, feat3, feat4, feat5, feat6, feat7), dim=1)
+        bottle = self.bottleneck(out)
+        return bottle
diff --git a/infer/lib/uvr5_pack/lib_v5/layers_537227KB.py b/infer/lib/uvr5_pack/lib_v5/layers_537227KB.py
new file mode 100644
index 0000000000000000000000000000000000000000..9b127bc6427f5c60c8cf85603a3d8a093c3501c4
--- /dev/null
+++ b/infer/lib/uvr5_pack/lib_v5/layers_537227KB.py
@@ -0,0 +1,126 @@
+import torch
+import torch.nn.functional as F
+from torch import nn
+
+from . import spec_utils
+
+
+class Conv2DBNActiv(nn.Module):
+    def __init__(self, nin, nout, ksize=3, stride=1, pad=1, dilation=1, activ=nn.ReLU):
+        super(Conv2DBNActiv, self).__init__()
+        self.conv = nn.Sequential(
+            nn.Conv2d(
+                nin,
+                nout,
+                kernel_size=ksize,
+                stride=stride,
+                padding=pad,
+                dilation=dilation,
+                bias=False,
+            ),
+            nn.BatchNorm2d(nout),
+            activ(),
+        )
+
+    def __call__(self, x):
+        return self.conv(x)
+
+
+class SeperableConv2DBNActiv(nn.Module):
+    def __init__(self, nin, nout, ksize=3, stride=1, pad=1, dilation=1, activ=nn.ReLU):
+        super(SeperableConv2DBNActiv, self).__init__()
+        self.conv = nn.Sequential(
+            nn.Conv2d(
+                nin,
+                nin,
+                kernel_size=ksize,
+                stride=stride,
+                padding=pad,
+                dilation=dilation,
+                groups=nin,
+                bias=False,
+            ),
+            nn.Conv2d(nin, nout, kernel_size=1, bias=False),
+            nn.BatchNorm2d(nout),
+            activ(),
+        )
+
+    def __call__(self, x):
+        return self.conv(x)
+
+
+class Encoder(nn.Module):
+    def __init__(self, nin, nout, ksize=3, stride=1, pad=1, activ=nn.LeakyReLU):
+        super(Encoder, self).__init__()
+        self.conv1 = Conv2DBNActiv(nin, nout, ksize, 1, pad, activ=activ)
+        self.conv2 = Conv2DBNActiv(nout, nout, ksize, stride, pad, activ=activ)
+
+    def __call__(self, x):
+        skip = self.conv1(x)
+        h = self.conv2(skip)
+
+        return h, skip
+
+
+class Decoder(nn.Module):
+    def __init__(
+        self, nin, nout, ksize=3, stride=1, pad=1, activ=nn.ReLU, dropout=False
+    ):
+        super(Decoder, self).__init__()
+        self.conv = Conv2DBNActiv(nin, nout, ksize, 1, pad, activ=activ)
+        self.dropout = nn.Dropout2d(0.1) if dropout else None
+
+    def __call__(self, x, skip=None):
+        x = F.interpolate(x, scale_factor=2, mode="bilinear", align_corners=True)
+        if skip is not None:
+            skip = spec_utils.crop_center(skip, x)
+            x = torch.cat([x, skip], dim=1)
+        h = self.conv(x)
+
+        if self.dropout is not None:
+            h = self.dropout(h)
+
+        return h
+
+
+class ASPPModule(nn.Module):
+    def __init__(self, nin, nout, dilations=(4, 8, 16, 32, 64), activ=nn.ReLU):
+        super(ASPPModule, self).__init__()
+        self.conv1 = nn.Sequential(
+            nn.AdaptiveAvgPool2d((1, None)),
+            Conv2DBNActiv(nin, nin, 1, 1, 0, activ=activ),
+        )
+        self.conv2 = Conv2DBNActiv(nin, nin, 1, 1, 0, activ=activ)
+        self.conv3 = SeperableConv2DBNActiv(
+            nin, nin, 3, 1, dilations[0], dilations[0], activ=activ
+        )
+        self.conv4 = SeperableConv2DBNActiv(
+            nin, nin, 3, 1, dilations[1], dilations[1], activ=activ
+        )
+        self.conv5 = SeperableConv2DBNActiv(
+            nin, nin, 3, 1, dilations[2], dilations[2], activ=activ
+        )
+        self.conv6 = SeperableConv2DBNActiv(
+            nin, nin, 3, 1, dilations[2], dilations[2], activ=activ
+        )
+        self.conv7 = SeperableConv2DBNActiv(
+            nin, nin, 3, 1, dilations[2], dilations[2], activ=activ
+        )
+        self.bottleneck = nn.Sequential(
+            Conv2DBNActiv(nin * 7, nout, 1, 1, 0, activ=activ), nn.Dropout2d(0.1)
+        )
+
+    def forward(self, x):
+        _, _, h, w = x.size()
+        feat1 = F.interpolate(
+            self.conv1(x), size=(h, w), mode="bilinear", align_corners=True
+        )
+        feat2 = self.conv2(x)
+        feat3 = self.conv3(x)
+        feat4 = self.conv4(x)
+        feat5 = self.conv5(x)
+        feat6 = self.conv6(x)
+        feat7 = self.conv7(x)
+        out = torch.cat((feat1, feat2, feat3, feat4, feat5, feat6, feat7), dim=1)
+        bottle = self.bottleneck(out)
+        return bottle
diff --git a/infer/lib/uvr5_pack/lib_v5/layers_537238KB.py b/infer/lib/uvr5_pack/lib_v5/layers_537238KB.py
new file mode 100644
index 0000000000000000000000000000000000000000..9b127bc6427f5c60c8cf85603a3d8a093c3501c4
--- /dev/null
+++ b/infer/lib/uvr5_pack/lib_v5/layers_537238KB.py
@@ -0,0 +1,126 @@
+import torch
+import torch.nn.functional as F
+from torch import nn
+
+from . import spec_utils
+
+
+class Conv2DBNActiv(nn.Module):
+    def __init__(self, nin, nout, ksize=3, stride=1, pad=1, dilation=1, activ=nn.ReLU):
+        super(Conv2DBNActiv, self).__init__()
+        self.conv = nn.Sequential(
+            nn.Conv2d(
+                nin,
+                nout,
+                kernel_size=ksize,
+                stride=stride,
+                padding=pad,
+                dilation=dilation,
+                bias=False,
+            ),
+            nn.BatchNorm2d(nout),
+            activ(),
+        )
+
+    def __call__(self, x):
+        return self.conv(x)
+
+
+class SeperableConv2DBNActiv(nn.Module):
+    def __init__(self, nin, nout, ksize=3, stride=1, pad=1, dilation=1, activ=nn.ReLU):
+        super(SeperableConv2DBNActiv, self).__init__()
+        self.conv = nn.Sequential(
+            nn.Conv2d(
+                nin,
+                nin,
+                kernel_size=ksize,
+                stride=stride,
+                padding=pad,
+                dilation=dilation,
+                groups=nin,
+                bias=False,
+            ),
+            nn.Conv2d(nin, nout, kernel_size=1, bias=False),
+            nn.BatchNorm2d(nout),
+            activ(),
+        )
+
+    def __call__(self, x):
+        return self.conv(x)
+
+
+class Encoder(nn.Module):
+    def __init__(self, nin, nout, ksize=3, stride=1, pad=1, activ=nn.LeakyReLU):
+        super(Encoder, self).__init__()
+        self.conv1 = Conv2DBNActiv(nin, nout, ksize, 1, pad, activ=activ)
+        self.conv2 = Conv2DBNActiv(nout, nout, ksize, stride, pad, activ=activ)
+
+    def __call__(self, x):
+        skip = self.conv1(x)
+        h = self.conv2(skip)
+
+        return h, skip
+
+
+class Decoder(nn.Module):
+    def __init__(
+        self, nin, nout, ksize=3, stride=1, pad=1, activ=nn.ReLU, dropout=False
+    ):
+        super(Decoder, self).__init__()
+        self.conv = Conv2DBNActiv(nin, nout, ksize, 1, pad, activ=activ)
+        self.dropout = nn.Dropout2d(0.1) if dropout else None
+
+    def __call__(self, x, skip=None):
+        x = F.interpolate(x, scale_factor=2, mode="bilinear", align_corners=True)
+        if skip is not None:
+            skip = spec_utils.crop_center(skip, x)
+            x = torch.cat([x, skip], dim=1)
+        h = self.conv(x)
+
+        if self.dropout is not None:
+            h = self.dropout(h)
+
+        return h
+
+
+class ASPPModule(nn.Module):
+    def __init__(self, nin, nout, dilations=(4, 8, 16, 32, 64), activ=nn.ReLU):
+        super(ASPPModule, self).__init__()
+        self.conv1 = nn.Sequential(
+            nn.AdaptiveAvgPool2d((1, None)),
+            Conv2DBNActiv(nin, nin, 1, 1, 0, activ=activ),
+        )
+        self.conv2 = Conv2DBNActiv(nin, nin, 1, 1, 0, activ=activ)
+        self.conv3 = SeperableConv2DBNActiv(
+            nin, nin, 3, 1, dilations[0], dilations[0], activ=activ
+        )
+        self.conv4 = SeperableConv2DBNActiv(
+            nin, nin, 3, 1, dilations[1], dilations[1], activ=activ
+        )
+        self.conv5 = SeperableConv2DBNActiv(
+            nin, nin, 3, 1, dilations[2], dilations[2], activ=activ
+        )
+        self.conv6 = SeperableConv2DBNActiv(
+            nin, nin, 3, 1, dilations[2], dilations[2], activ=activ
+        )
+        self.conv7 = SeperableConv2DBNActiv(
+            nin, nin, 3, 1, dilations[2], dilations[2], activ=activ
+        )
+        self.bottleneck = nn.Sequential(
+            Conv2DBNActiv(nin * 7, nout, 1, 1, 0, activ=activ), nn.Dropout2d(0.1)
+        )
+
+    def forward(self, x):
+        _, _, h, w = x.size()
+        feat1 = F.interpolate(
+            self.conv1(x), size=(h, w), mode="bilinear", align_corners=True
+        )
+        feat2 = self.conv2(x)
+        feat3 = self.conv3(x)
+        feat4 = self.conv4(x)
+        feat5 = self.conv5(x)
+        feat6 = self.conv6(x)
+        feat7 = self.conv7(x)
+        out = torch.cat((feat1, feat2, feat3, feat4, feat5, feat6, feat7), dim=1)
+        bottle = self.bottleneck(out)
+        return bottle
diff --git a/infer/lib/uvr5_pack/lib_v5/layers_new.py b/infer/lib/uvr5_pack/lib_v5/layers_new.py
new file mode 100644
index 0000000000000000000000000000000000000000..44153b6a23399c6938affc61c71919eaa172bcee
--- /dev/null
+++ b/infer/lib/uvr5_pack/lib_v5/layers_new.py
@@ -0,0 +1,125 @@
+import torch
+import torch.nn.functional as F
+from torch import nn
+
+from . import spec_utils
+
+
+class Conv2DBNActiv(nn.Module):
+    def __init__(self, nin, nout, ksize=3, stride=1, pad=1, dilation=1, activ=nn.ReLU):
+        super(Conv2DBNActiv, self).__init__()
+        self.conv = nn.Sequential(
+            nn.Conv2d(
+                nin,
+                nout,
+                kernel_size=ksize,
+                stride=stride,
+                padding=pad,
+                dilation=dilation,
+                bias=False,
+            ),
+            nn.BatchNorm2d(nout),
+            activ(),
+        )
+
+    def __call__(self, x):
+        return self.conv(x)
+
+
+class Encoder(nn.Module):
+    def __init__(self, nin, nout, ksize=3, stride=1, pad=1, activ=nn.LeakyReLU):
+        super(Encoder, self).__init__()
+        self.conv1 = Conv2DBNActiv(nin, nout, ksize, stride, pad, activ=activ)
+        self.conv2 = Conv2DBNActiv(nout, nout, ksize, 1, pad, activ=activ)
+
+    def __call__(self, x):
+        h = self.conv1(x)
+        h = self.conv2(h)
+
+        return h
+
+
+class Decoder(nn.Module):
+    def __init__(
+        self, nin, nout, ksize=3, stride=1, pad=1, activ=nn.ReLU, dropout=False
+    ):
+        super(Decoder, self).__init__()
+        self.conv1 = Conv2DBNActiv(nin, nout, ksize, 1, pad, activ=activ)
+        # self.conv2 = Conv2DBNActiv(nout, nout, ksize, 1, pad, activ=activ)
+        self.dropout = nn.Dropout2d(0.1) if dropout else None
+
+    def __call__(self, x, skip=None):
+        x = F.interpolate(x, scale_factor=2, mode="bilinear", align_corners=True)
+
+        if skip is not None:
+            skip = spec_utils.crop_center(skip, x)
+            x = torch.cat([x, skip], dim=1)
+
+        h = self.conv1(x)
+        # h = self.conv2(h)
+
+        if self.dropout is not None:
+            h = self.dropout(h)
+
+        return h
+
+
+class ASPPModule(nn.Module):
+    def __init__(self, nin, nout, dilations=(4, 8, 12), activ=nn.ReLU, dropout=False):
+        super(ASPPModule, self).__init__()
+        self.conv1 = nn.Sequential(
+            nn.AdaptiveAvgPool2d((1, None)),
+            Conv2DBNActiv(nin, nout, 1, 1, 0, activ=activ),
+        )
+        self.conv2 = Conv2DBNActiv(nin, nout, 1, 1, 0, activ=activ)
+        self.conv3 = Conv2DBNActiv(
+            nin, nout, 3, 1, dilations[0], dilations[0], activ=activ
+        )
+        self.conv4 = Conv2DBNActiv(
+            nin, nout, 3, 1, dilations[1], dilations[1], activ=activ
+        )
+        self.conv5 = Conv2DBNActiv(
+            nin, nout, 3, 1, dilations[2], dilations[2], activ=activ
+        )
+        self.bottleneck = Conv2DBNActiv(nout * 5, nout, 1, 1, 0, activ=activ)
+        self.dropout = nn.Dropout2d(0.1) if dropout else None
+
+    def forward(self, x):
+        _, _, h, w = x.size()
+        feat1 = F.interpolate(
+            self.conv1(x), size=(h, w), mode="bilinear", align_corners=True
+        )
+        feat2 = self.conv2(x)
+        feat3 = self.conv3(x)
+        feat4 = self.conv4(x)
+        feat5 = self.conv5(x)
+        out = torch.cat((feat1, feat2, feat3, feat4, feat5), dim=1)
+        out = self.bottleneck(out)
+
+        if self.dropout is not None:
+            out = self.dropout(out)
+
+        return out
+
+
+class LSTMModule(nn.Module):
+    def __init__(self, nin_conv, nin_lstm, nout_lstm):
+        super(LSTMModule, self).__init__()
+        self.conv = Conv2DBNActiv(nin_conv, 1, 1, 1, 0)
+        self.lstm = nn.LSTM(
+            input_size=nin_lstm, hidden_size=nout_lstm // 2, bidirectional=True
+        )
+        self.dense = nn.Sequential(
+            nn.Linear(nout_lstm, nin_lstm), nn.BatchNorm1d(nin_lstm), nn.ReLU()
+        )
+
+    def forward(self, x):
+        N, _, nbins, nframes = x.size()
+        h = self.conv(x)[:, 0]  # N, nbins, nframes
+        h = h.permute(2, 0, 1)  # nframes, N, nbins
+        h, _ = self.lstm(h)
+        h = self.dense(h.reshape(-1, h.size()[-1]))  # nframes * N, nbins
+        h = h.reshape(nframes, N, 1, nbins)
+        h = h.permute(1, 2, 3, 0)
+
+        return h
diff --git a/infer/lib/uvr5_pack/lib_v5/model_param_init.py b/infer/lib/uvr5_pack/lib_v5/model_param_init.py
new file mode 100644
index 0000000000000000000000000000000000000000..b995c0bfb1194746187692e2ab1c2a6dbaaaec6c
--- /dev/null
+++ b/infer/lib/uvr5_pack/lib_v5/model_param_init.py
@@ -0,0 +1,69 @@
+import json
+import os
+import pathlib
+
+default_param = {}
+default_param["bins"] = 768
+default_param["unstable_bins"] = 9  # training only
+default_param["reduction_bins"] = 762  # training only
+default_param["sr"] = 44100
+default_param["pre_filter_start"] = 757
+default_param["pre_filter_stop"] = 768
+default_param["band"] = {}
+
+
+default_param["band"][1] = {
+    "sr": 11025,
+    "hl": 128,
+    "n_fft": 960,
+    "crop_start": 0,
+    "crop_stop": 245,
+    "lpf_start": 61,  # inference only
+    "res_type": "polyphase",
+}
+
+default_param["band"][2] = {
+    "sr": 44100,
+    "hl": 512,
+    "n_fft": 1536,
+    "crop_start": 24,
+    "crop_stop": 547,
+    "hpf_start": 81,  # inference only
+    "res_type": "sinc_best",
+}
+
+
+def int_keys(d):
+    r = {}
+    for k, v in d:
+        if k.isdigit():
+            k = int(k)
+        r[k] = v
+    return r
+
+
+class ModelParameters(object):
+    def __init__(self, config_path=""):
+        if ".pth" == pathlib.Path(config_path).suffix:
+            import zipfile
+
+            with zipfile.ZipFile(config_path, "r") as zip:
+                self.param = json.loads(
+                    zip.read("param.json"), object_pairs_hook=int_keys
+                )
+        elif ".json" == pathlib.Path(config_path).suffix:
+            with open(config_path, "r") as f:
+                self.param = json.loads(f.read(), object_pairs_hook=int_keys)
+        else:
+            self.param = default_param
+
+        for k in [
+            "mid_side",
+            "mid_side_b",
+            "mid_side_b2",
+            "stereo_w",
+            "stereo_n",
+            "reverse",
+        ]:
+            if not k in self.param:
+                self.param[k] = False
diff --git a/infer/lib/uvr5_pack/lib_v5/modelparams/1band_sr16000_hl512.json b/infer/lib/uvr5_pack/lib_v5/modelparams/1band_sr16000_hl512.json
new file mode 100644
index 0000000000000000000000000000000000000000..72cb4499867ad2827185e85687f06fb73d33eced
--- /dev/null
+++ b/infer/lib/uvr5_pack/lib_v5/modelparams/1band_sr16000_hl512.json
@@ -0,0 +1,19 @@
+{
+	"bins": 1024,
+	"unstable_bins": 0,
+	"reduction_bins": 0,
+	"band": {
+		"1": {
+			"sr": 16000,
+			"hl": 512,
+			"n_fft": 2048,
+			"crop_start": 0,
+			"crop_stop": 1024,
+			"hpf_start": -1,
+			"res_type": "sinc_best"
+		}
+	},
+	"sr": 16000,
+	"pre_filter_start": 1023,
+	"pre_filter_stop": 1024
+}
\ No newline at end of file
diff --git a/infer/lib/uvr5_pack/lib_v5/modelparams/1band_sr32000_hl512.json b/infer/lib/uvr5_pack/lib_v5/modelparams/1band_sr32000_hl512.json
new file mode 100644
index 0000000000000000000000000000000000000000..3c00ecf0a105e55a6a86a3c32db301a2635b5b41
--- /dev/null
+++ b/infer/lib/uvr5_pack/lib_v5/modelparams/1band_sr32000_hl512.json
@@ -0,0 +1,19 @@
+{
+	"bins": 1024,
+	"unstable_bins": 0,
+	"reduction_bins": 0,
+	"band": {
+		"1": {
+			"sr": 32000,
+			"hl": 512,
+			"n_fft": 2048,
+			"crop_start": 0,
+			"crop_stop": 1024,
+			"hpf_start": -1,
+			"res_type": "kaiser_fast"
+		}
+	},
+	"sr": 32000,
+	"pre_filter_start": 1000,
+	"pre_filter_stop": 1021
+}
\ No newline at end of file
diff --git a/infer/lib/uvr5_pack/lib_v5/modelparams/1band_sr33075_hl384.json b/infer/lib/uvr5_pack/lib_v5/modelparams/1band_sr33075_hl384.json
new file mode 100644
index 0000000000000000000000000000000000000000..55666ac9a8d0547751fb4b4d3bffb1ee2c956913
--- /dev/null
+++ b/infer/lib/uvr5_pack/lib_v5/modelparams/1band_sr33075_hl384.json
@@ -0,0 +1,19 @@
+{
+	"bins": 1024,
+	"unstable_bins": 0,
+	"reduction_bins": 0,
+	"band": {
+		"1": {
+			"sr": 33075,
+			"hl": 384,
+			"n_fft": 2048,
+			"crop_start": 0,
+			"crop_stop": 1024,
+			"hpf_start": -1,
+			"res_type": "sinc_best"
+		}
+	},
+	"sr": 33075,
+	"pre_filter_start": 1000,
+	"pre_filter_stop": 1021
+}
\ No newline at end of file
diff --git a/infer/lib/uvr5_pack/lib_v5/modelparams/1band_sr44100_hl1024.json b/infer/lib/uvr5_pack/lib_v5/modelparams/1band_sr44100_hl1024.json
new file mode 100644
index 0000000000000000000000000000000000000000..665abe20eb3cc39fe0f8493dad8f25f6ef634a14
--- /dev/null
+++ b/infer/lib/uvr5_pack/lib_v5/modelparams/1band_sr44100_hl1024.json
@@ -0,0 +1,19 @@
+{
+	"bins": 1024,
+	"unstable_bins": 0,
+	"reduction_bins": 0,
+	"band": {
+		"1": {
+			"sr": 44100,
+			"hl": 1024,
+			"n_fft": 2048,
+			"crop_start": 0,
+			"crop_stop": 1024,
+			"hpf_start": -1,
+			"res_type": "sinc_best"
+		}
+	},
+	"sr": 44100,
+	"pre_filter_start": 1023,
+	"pre_filter_stop": 1024
+}
\ No newline at end of file
diff --git a/infer/lib/uvr5_pack/lib_v5/modelparams/1band_sr44100_hl256.json b/infer/lib/uvr5_pack/lib_v5/modelparams/1band_sr44100_hl256.json
new file mode 100644
index 0000000000000000000000000000000000000000..0e8b16f89b0231d06eabe8d2f7c2670c7caa2272
--- /dev/null
+++ b/infer/lib/uvr5_pack/lib_v5/modelparams/1band_sr44100_hl256.json
@@ -0,0 +1,19 @@
+{
+	"bins": 256,
+	"unstable_bins": 0,
+	"reduction_bins": 0,
+	"band": {
+		"1": {
+			"sr": 44100,
+			"hl": 256,
+			"n_fft": 512,
+			"crop_start": 0,
+			"crop_stop": 256,
+			"hpf_start": -1,
+			"res_type": "sinc_best"
+		}
+	},
+	"sr": 44100,
+	"pre_filter_start": 256,
+	"pre_filter_stop": 256
+}
\ No newline at end of file
diff --git a/infer/lib/uvr5_pack/lib_v5/modelparams/1band_sr44100_hl512.json b/infer/lib/uvr5_pack/lib_v5/modelparams/1band_sr44100_hl512.json
new file mode 100644
index 0000000000000000000000000000000000000000..3b38fcaf60ba204e03a47f5bd3f5bcfe75e1983a
--- /dev/null
+++ b/infer/lib/uvr5_pack/lib_v5/modelparams/1band_sr44100_hl512.json
@@ -0,0 +1,19 @@
+{
+	"bins": 1024,
+	"unstable_bins": 0,
+	"reduction_bins": 0,
+	"band": {
+		"1": {
+			"sr": 44100,
+			"hl": 512,
+			"n_fft": 2048,
+			"crop_start": 0,
+			"crop_stop": 1024,
+			"hpf_start": -1,
+			"res_type": "sinc_best"
+		}
+	},
+	"sr": 44100,
+	"pre_filter_start": 1023,
+	"pre_filter_stop": 1024
+}
\ No newline at end of file
diff --git a/infer/lib/uvr5_pack/lib_v5/modelparams/1band_sr44100_hl512_cut.json b/infer/lib/uvr5_pack/lib_v5/modelparams/1band_sr44100_hl512_cut.json
new file mode 100644
index 0000000000000000000000000000000000000000..630df3524e340f43a1ddb7b33ff02cc91fc1cb47
--- /dev/null
+++ b/infer/lib/uvr5_pack/lib_v5/modelparams/1band_sr44100_hl512_cut.json
@@ -0,0 +1,19 @@
+{
+	"bins": 1024,
+	"unstable_bins": 0,
+	"reduction_bins": 0,
+	"band": {
+		"1": {
+			"sr": 44100,
+			"hl": 512,
+			"n_fft": 2048,
+			"crop_start": 0,
+			"crop_stop": 700,
+			"hpf_start": -1,
+			"res_type": "sinc_best"
+		}
+	},
+	"sr": 44100,
+	"pre_filter_start": 1023,
+	"pre_filter_stop": 700
+}
\ No newline at end of file
diff --git a/infer/lib/uvr5_pack/lib_v5/modelparams/2band_32000.json b/infer/lib/uvr5_pack/lib_v5/modelparams/2band_32000.json
new file mode 100644
index 0000000000000000000000000000000000000000..ab9cf1150a818eb6252105408311be0a40d423b3
--- /dev/null
+++ b/infer/lib/uvr5_pack/lib_v5/modelparams/2band_32000.json
@@ -0,0 +1,30 @@
+{
+	"bins": 768,
+	"unstable_bins": 7,
+	"reduction_bins": 705,
+	"band": {
+		"1": {
+			"sr": 6000,
+			"hl": 66,
+			"n_fft": 512,
+			"crop_start": 0,
+			"crop_stop": 240,
+			"lpf_start": 60,
+			"lpf_stop": 118,
+			"res_type": "sinc_fastest"
+		},
+		"2": {
+			"sr": 32000,
+			"hl": 352,
+			"n_fft": 1024,
+			"crop_start": 22,
+			"crop_stop": 505,
+			"hpf_start": 44,
+			"hpf_stop": 23,
+			"res_type": "sinc_medium"
+		}
+	},
+	"sr": 32000,
+	"pre_filter_start": 710,
+	"pre_filter_stop": 731
+}
diff --git a/infer/lib/uvr5_pack/lib_v5/modelparams/2band_44100_lofi.json b/infer/lib/uvr5_pack/lib_v5/modelparams/2band_44100_lofi.json
new file mode 100644
index 0000000000000000000000000000000000000000..7faa216d7b49aeece24123dbdd868847a1dbc03c
--- /dev/null
+++ b/infer/lib/uvr5_pack/lib_v5/modelparams/2band_44100_lofi.json
@@ -0,0 +1,30 @@
+{
+	"bins": 512,
+	"unstable_bins": 7,
+	"reduction_bins": 510,
+	"band": {
+		"1": {
+			"sr": 11025,
+			"hl": 160,
+			"n_fft": 768,
+			"crop_start": 0,
+			"crop_stop": 192,
+			"lpf_start": 41,
+			"lpf_stop": 139,
+			"res_type": "sinc_fastest"
+		},
+		"2": {
+			"sr": 44100,
+			"hl": 640,
+			"n_fft": 1024,
+			"crop_start": 10,
+			"crop_stop": 320,
+			"hpf_start": 47,
+			"hpf_stop": 15,
+			"res_type": "sinc_medium"
+		}
+	},
+	"sr": 44100,
+	"pre_filter_start": 510,
+	"pre_filter_stop": 512
+}
diff --git a/infer/lib/uvr5_pack/lib_v5/modelparams/2band_48000.json b/infer/lib/uvr5_pack/lib_v5/modelparams/2band_48000.json
new file mode 100644
index 0000000000000000000000000000000000000000..7e78175052b09cb1a32345e54006475992712f9a
--- /dev/null
+++ b/infer/lib/uvr5_pack/lib_v5/modelparams/2band_48000.json
@@ -0,0 +1,30 @@
+{
+	"bins": 768,
+	"unstable_bins": 7,
+	"reduction_bins": 705,
+	"band": {
+		"1": {
+			"sr": 6000,
+			"hl": 66,
+			"n_fft": 512,
+			"crop_start": 0,
+			"crop_stop": 240,
+			"lpf_start": 60,
+			"lpf_stop": 240,
+			"res_type": "sinc_fastest"
+		},
+		"2": {
+			"sr": 48000,
+			"hl": 528,
+			"n_fft": 1536,
+			"crop_start": 22,
+			"crop_stop": 505,
+			"hpf_start": 82,
+			"hpf_stop": 22,
+			"res_type": "sinc_medium"
+		}
+	},
+	"sr": 48000,
+	"pre_filter_start": 710,
+	"pre_filter_stop": 731
+}
\ No newline at end of file
diff --git a/infer/lib/uvr5_pack/lib_v5/modelparams/3band_44100.json b/infer/lib/uvr5_pack/lib_v5/modelparams/3band_44100.json
new file mode 100644
index 0000000000000000000000000000000000000000..d881d767ff83fbac0e18dfe2587ef16925b29b3c
--- /dev/null
+++ b/infer/lib/uvr5_pack/lib_v5/modelparams/3band_44100.json
@@ -0,0 +1,42 @@
+{
+	"bins": 768,
+	"unstable_bins": 5,
+	"reduction_bins": 733,
+	"band": {
+		"1": {
+			"sr": 11025,
+			"hl": 128,
+			"n_fft": 768,
+			"crop_start": 0,
+			"crop_stop": 278,
+			"lpf_start": 28,
+			"lpf_stop": 140,
+			"res_type": "polyphase"
+		},
+		"2": {
+			"sr": 22050,
+			"hl": 256,
+			"n_fft": 768,
+			"crop_start": 14,
+			"crop_stop": 322,
+			"hpf_start": 70,
+			"hpf_stop": 14,
+			"lpf_start": 283,
+			"lpf_stop": 314,
+			"res_type": "polyphase"
+		},	
+		"3": {
+			"sr": 44100,
+			"hl": 512,
+			"n_fft": 768,
+			"crop_start": 131,
+			"crop_stop": 313,
+			"hpf_start": 154,
+			"hpf_stop": 141,
+			"res_type": "sinc_medium"
+		}
+	},
+	"sr": 44100,
+	"pre_filter_start": 757,
+	"pre_filter_stop": 768
+}
diff --git a/infer/lib/uvr5_pack/lib_v5/modelparams/3band_44100_mid.json b/infer/lib/uvr5_pack/lib_v5/modelparams/3band_44100_mid.json
new file mode 100644
index 0000000000000000000000000000000000000000..77ec198573b19f36519a028a509767d30764c0e2
--- /dev/null
+++ b/infer/lib/uvr5_pack/lib_v5/modelparams/3band_44100_mid.json
@@ -0,0 +1,43 @@
+{
+	"mid_side": true,
+	"bins": 768,
+	"unstable_bins": 5,
+	"reduction_bins": 733,
+	"band": {
+		"1": {
+			"sr": 11025,
+			"hl": 128,
+			"n_fft": 768,
+			"crop_start": 0,
+			"crop_stop": 278,
+			"lpf_start": 28,
+			"lpf_stop": 140,
+			"res_type": "polyphase"
+		},
+		"2": {
+			"sr": 22050,
+			"hl": 256,
+			"n_fft": 768,
+			"crop_start": 14,
+			"crop_stop": 322,
+			"hpf_start": 70,
+			"hpf_stop": 14,
+			"lpf_start": 283,
+			"lpf_stop": 314,
+			"res_type": "polyphase"
+		},	
+		"3": {
+			"sr": 44100,
+			"hl": 512,
+			"n_fft": 768,
+			"crop_start": 131,
+			"crop_stop": 313,
+			"hpf_start": 154,
+			"hpf_stop": 141,
+			"res_type": "sinc_medium"
+		}
+	},
+	"sr": 44100,
+	"pre_filter_start": 757,
+	"pre_filter_stop": 768
+}
diff --git a/infer/lib/uvr5_pack/lib_v5/modelparams/3band_44100_msb2.json b/infer/lib/uvr5_pack/lib_v5/modelparams/3band_44100_msb2.json
new file mode 100644
index 0000000000000000000000000000000000000000..85ee8a7d44541c9176e85ea3dce8728d34990938
--- /dev/null
+++ b/infer/lib/uvr5_pack/lib_v5/modelparams/3band_44100_msb2.json
@@ -0,0 +1,43 @@
+{
+	"mid_side_b2": true,
+	"bins": 640,
+	"unstable_bins": 7,
+	"reduction_bins": 565,
+	"band": {
+		"1": {
+			"sr": 11025,
+			"hl": 108,
+			"n_fft": 1024,
+			"crop_start": 0,
+			"crop_stop": 187,
+			"lpf_start": 92,
+			"lpf_stop": 186,
+			"res_type": "polyphase"
+		},
+		"2": {
+			"sr": 22050,
+			"hl": 216,
+			"n_fft": 768,
+			"crop_start": 0,
+			"crop_stop": 212,
+			"hpf_start": 68,
+			"hpf_stop": 34,
+			"lpf_start": 174,
+			"lpf_stop": 209,
+			"res_type": "polyphase"
+		},	
+		"3": {
+			"sr": 44100,
+			"hl": 432,
+			"n_fft": 640,
+			"crop_start": 66,
+			"crop_stop": 307,
+			"hpf_start": 86,
+			"hpf_stop": 72,
+			"res_type": "kaiser_fast"
+		}
+	},
+	"sr": 44100,
+	"pre_filter_start": 639,
+	"pre_filter_stop": 640
+}
diff --git a/infer/lib/uvr5_pack/lib_v5/modelparams/4band_44100.json b/infer/lib/uvr5_pack/lib_v5/modelparams/4band_44100.json
new file mode 100644
index 0000000000000000000000000000000000000000..df123754204372aa50d464fbe9102a401f48cc73
--- /dev/null
+++ b/infer/lib/uvr5_pack/lib_v5/modelparams/4band_44100.json
@@ -0,0 +1,54 @@
+{
+	"bins": 768,
+	"unstable_bins": 7,
+	"reduction_bins": 668,
+	"band": {
+		"1": {
+			"sr": 11025,
+			"hl": 128,
+			"n_fft": 1024,
+			"crop_start": 0,
+			"crop_stop": 186,
+			"lpf_start": 37,
+			"lpf_stop": 73,
+			"res_type": "polyphase"
+		},
+		"2": {
+			"sr": 11025,
+			"hl": 128,
+			"n_fft": 512,
+			"crop_start": 4,
+			"crop_stop": 185,			
+			"hpf_start": 36,
+			"hpf_stop": 18,
+			"lpf_start": 93,
+			"lpf_stop": 185,
+			"res_type": "polyphase"
+		},
+		"3": {
+			"sr": 22050,
+			"hl": 256,
+			"n_fft": 512,
+			"crop_start": 46,
+			"crop_stop": 186,
+			"hpf_start": 93,
+			"hpf_stop": 46,
+			"lpf_start": 164,
+			"lpf_stop": 186,
+			"res_type": "polyphase"
+		},	
+		"4": {
+			"sr": 44100,
+			"hl": 512,
+			"n_fft": 768,
+			"crop_start": 121,
+			"crop_stop": 382,
+			"hpf_start": 138,
+			"hpf_stop": 123,
+			"res_type": "sinc_medium"
+		}
+	},
+	"sr": 44100,
+	"pre_filter_start": 740,
+	"pre_filter_stop": 768
+}
diff --git a/infer/lib/uvr5_pack/lib_v5/modelparams/4band_44100_mid.json b/infer/lib/uvr5_pack/lib_v5/modelparams/4band_44100_mid.json
new file mode 100644
index 0000000000000000000000000000000000000000..e91b699eb63d3382c3b9e9edf46d40ed91d6122b
--- /dev/null
+++ b/infer/lib/uvr5_pack/lib_v5/modelparams/4band_44100_mid.json
@@ -0,0 +1,55 @@
+{
+	"bins": 768,
+	"unstable_bins": 7,
+	"mid_side": true,
+	"reduction_bins": 668,
+	"band": {
+		"1": {
+			"sr": 11025,
+			"hl": 128,
+			"n_fft": 1024,
+			"crop_start": 0,
+			"crop_stop": 186,
+			"lpf_start": 37,
+			"lpf_stop": 73,
+			"res_type": "polyphase"
+		},
+		"2": {
+			"sr": 11025,
+			"hl": 128,
+			"n_fft": 512,
+			"crop_start": 4,
+			"crop_stop": 185,			
+			"hpf_start": 36,
+			"hpf_stop": 18,
+			"lpf_start": 93,
+			"lpf_stop": 185,
+			"res_type": "polyphase"
+		},
+		"3": {
+			"sr": 22050,
+			"hl": 256,
+			"n_fft": 512,
+			"crop_start": 46,
+			"crop_stop": 186,
+			"hpf_start": 93,
+			"hpf_stop": 46,
+			"lpf_start": 164,
+			"lpf_stop": 186,
+			"res_type": "polyphase"
+		},	
+		"4": {
+			"sr": 44100,
+			"hl": 512,
+			"n_fft": 768,
+			"crop_start": 121,
+			"crop_stop": 382,
+			"hpf_start": 138,
+			"hpf_stop": 123,
+			"res_type": "sinc_medium"
+		}
+	},
+	"sr": 44100,
+	"pre_filter_start": 740,
+	"pre_filter_stop": 768
+}
diff --git a/infer/lib/uvr5_pack/lib_v5/modelparams/4band_44100_msb.json b/infer/lib/uvr5_pack/lib_v5/modelparams/4band_44100_msb.json
new file mode 100644
index 0000000000000000000000000000000000000000..f852f280ec9d98fc1b65cec688290eaafec61b84
--- /dev/null
+++ b/infer/lib/uvr5_pack/lib_v5/modelparams/4band_44100_msb.json
@@ -0,0 +1,55 @@
+{
+	"mid_side_b": true,
+	"bins": 768,
+	"unstable_bins": 7,
+	"reduction_bins": 668,
+	"band": {
+		"1": {
+			"sr": 11025,
+			"hl": 128,
+			"n_fft": 1024,
+			"crop_start": 0,
+			"crop_stop": 186,
+			"lpf_start": 37,
+			"lpf_stop": 73,
+			"res_type": "polyphase"
+		},
+		"2": {
+			"sr": 11025,
+			"hl": 128,
+			"n_fft": 512,
+			"crop_start": 4,
+			"crop_stop": 185,			
+			"hpf_start": 36,
+			"hpf_stop": 18,
+			"lpf_start": 93,
+			"lpf_stop": 185,
+			"res_type": "polyphase"
+		},
+		"3": {
+			"sr": 22050,
+			"hl": 256,
+			"n_fft": 512,
+			"crop_start": 46,
+			"crop_stop": 186,
+			"hpf_start": 93,
+			"hpf_stop": 46,
+			"lpf_start": 164,
+			"lpf_stop": 186,
+			"res_type": "polyphase"
+		},	
+		"4": {
+			"sr": 44100,
+			"hl": 512,
+			"n_fft": 768,
+			"crop_start": 121,
+			"crop_stop": 382,
+			"hpf_start": 138,
+			"hpf_stop": 123,
+			"res_type": "sinc_medium"
+		}
+	},
+	"sr": 44100,
+	"pre_filter_start": 740,
+	"pre_filter_stop": 768
+}
\ No newline at end of file
diff --git a/infer/lib/uvr5_pack/lib_v5/modelparams/4band_44100_msb2.json b/infer/lib/uvr5_pack/lib_v5/modelparams/4band_44100_msb2.json
new file mode 100644
index 0000000000000000000000000000000000000000..f852f280ec9d98fc1b65cec688290eaafec61b84
--- /dev/null
+++ b/infer/lib/uvr5_pack/lib_v5/modelparams/4band_44100_msb2.json
@@ -0,0 +1,55 @@
+{
+	"mid_side_b": true,
+	"bins": 768,
+	"unstable_bins": 7,
+	"reduction_bins": 668,
+	"band": {
+		"1": {
+			"sr": 11025,
+			"hl": 128,
+			"n_fft": 1024,
+			"crop_start": 0,
+			"crop_stop": 186,
+			"lpf_start": 37,
+			"lpf_stop": 73,
+			"res_type": "polyphase"
+		},
+		"2": {
+			"sr": 11025,
+			"hl": 128,
+			"n_fft": 512,
+			"crop_start": 4,
+			"crop_stop": 185,			
+			"hpf_start": 36,
+			"hpf_stop": 18,
+			"lpf_start": 93,
+			"lpf_stop": 185,
+			"res_type": "polyphase"
+		},
+		"3": {
+			"sr": 22050,
+			"hl": 256,
+			"n_fft": 512,
+			"crop_start": 46,
+			"crop_stop": 186,
+			"hpf_start": 93,
+			"hpf_stop": 46,
+			"lpf_start": 164,
+			"lpf_stop": 186,
+			"res_type": "polyphase"
+		},	
+		"4": {
+			"sr": 44100,
+			"hl": 512,
+			"n_fft": 768,
+			"crop_start": 121,
+			"crop_stop": 382,
+			"hpf_start": 138,
+			"hpf_stop": 123,
+			"res_type": "sinc_medium"
+		}
+	},
+	"sr": 44100,
+	"pre_filter_start": 740,
+	"pre_filter_stop": 768
+}
\ No newline at end of file
diff --git a/infer/lib/uvr5_pack/lib_v5/modelparams/4band_44100_reverse.json b/infer/lib/uvr5_pack/lib_v5/modelparams/4band_44100_reverse.json
new file mode 100644
index 0000000000000000000000000000000000000000..7a07d5541bd83dc1caa20b531c3b43a2ffccac88
--- /dev/null
+++ b/infer/lib/uvr5_pack/lib_v5/modelparams/4band_44100_reverse.json
@@ -0,0 +1,55 @@
+{
+	"reverse": true,
+	"bins": 768,
+	"unstable_bins": 7,
+	"reduction_bins": 668,
+	"band": {
+		"1": {
+			"sr": 11025,
+			"hl": 128,
+			"n_fft": 1024,
+			"crop_start": 0,
+			"crop_stop": 186,
+			"lpf_start": 37,
+			"lpf_stop": 73,
+			"res_type": "polyphase"
+		},
+		"2": {
+			"sr": 11025,
+			"hl": 128,
+			"n_fft": 512,
+			"crop_start": 4,
+			"crop_stop": 185,			
+			"hpf_start": 36,
+			"hpf_stop": 18,
+			"lpf_start": 93,
+			"lpf_stop": 185,
+			"res_type": "polyphase"
+		},
+		"3": {
+			"sr": 22050,
+			"hl": 256,
+			"n_fft": 512,
+			"crop_start": 46,
+			"crop_stop": 186,
+			"hpf_start": 93,
+			"hpf_stop": 46,
+			"lpf_start": 164,
+			"lpf_stop": 186,
+			"res_type": "polyphase"
+		},	
+		"4": {
+			"sr": 44100,
+			"hl": 512,
+			"n_fft": 768,
+			"crop_start": 121,
+			"crop_stop": 382,
+			"hpf_start": 138,
+			"hpf_stop": 123,
+			"res_type": "sinc_medium"
+		}
+	},
+	"sr": 44100,
+	"pre_filter_start": 740,
+	"pre_filter_stop": 768
+}
\ No newline at end of file
diff --git a/infer/lib/uvr5_pack/lib_v5/modelparams/4band_44100_sw.json b/infer/lib/uvr5_pack/lib_v5/modelparams/4band_44100_sw.json
new file mode 100644
index 0000000000000000000000000000000000000000..ba0cf342106de793e6ec3e876854c7fd451fbf76
--- /dev/null
+++ b/infer/lib/uvr5_pack/lib_v5/modelparams/4band_44100_sw.json
@@ -0,0 +1,55 @@
+{
+	"stereo_w": true,
+	"bins": 768,
+	"unstable_bins": 7,
+	"reduction_bins": 668,
+	"band": {
+		"1": {
+			"sr": 11025,
+			"hl": 128,
+			"n_fft": 1024,
+			"crop_start": 0,
+			"crop_stop": 186,
+			"lpf_start": 37,
+			"lpf_stop": 73,
+			"res_type": "polyphase"
+		},
+		"2": {
+			"sr": 11025,
+			"hl": 128,
+			"n_fft": 512,
+			"crop_start": 4,
+			"crop_stop": 185,			
+			"hpf_start": 36,
+			"hpf_stop": 18,
+			"lpf_start": 93,
+			"lpf_stop": 185,
+			"res_type": "polyphase"
+		},
+		"3": {
+			"sr": 22050,
+			"hl": 256,
+			"n_fft": 512,
+			"crop_start": 46,
+			"crop_stop": 186,
+			"hpf_start": 93,
+			"hpf_stop": 46,
+			"lpf_start": 164,
+			"lpf_stop": 186,
+			"res_type": "polyphase"
+		},	
+		"4": {
+			"sr": 44100,
+			"hl": 512,
+			"n_fft": 768,
+			"crop_start": 121,
+			"crop_stop": 382,
+			"hpf_start": 138,
+			"hpf_stop": 123,
+			"res_type": "sinc_medium"
+		}
+	},
+	"sr": 44100,
+	"pre_filter_start": 740,
+	"pre_filter_stop": 768
+}
\ No newline at end of file
diff --git a/infer/lib/uvr5_pack/lib_v5/modelparams/4band_v2.json b/infer/lib/uvr5_pack/lib_v5/modelparams/4band_v2.json
new file mode 100644
index 0000000000000000000000000000000000000000..33281a0cf9916fc33558ddfda7a0287a2547faf4
--- /dev/null
+++ b/infer/lib/uvr5_pack/lib_v5/modelparams/4band_v2.json
@@ -0,0 +1,54 @@
+{
+	"bins": 672,
+	"unstable_bins": 8,
+	"reduction_bins": 637,
+	"band": {
+		"1": {
+			"sr": 7350,
+			"hl": 80,
+			"n_fft": 640,
+			"crop_start": 0,
+			"crop_stop": 85,
+			"lpf_start": 25,
+			"lpf_stop": 53,
+			"res_type": "polyphase"
+		},
+		"2": {
+			"sr": 7350,
+			"hl": 80,
+			"n_fft": 320,
+			"crop_start": 4,
+			"crop_stop": 87,
+			"hpf_start": 25,
+			"hpf_stop": 12,
+			"lpf_start": 31,
+			"lpf_stop": 62,
+			"res_type": "polyphase"
+		},		
+		"3": {
+			"sr": 14700,
+			"hl": 160,
+			"n_fft": 512,
+			"crop_start": 17,
+			"crop_stop": 216,
+			"hpf_start": 48,
+			"hpf_stop": 24,
+			"lpf_start": 139,
+			"lpf_stop": 210,
+			"res_type": "polyphase"
+		},	
+		"4": {
+			"sr": 44100,
+			"hl": 480,
+			"n_fft": 960,
+			"crop_start": 78,
+			"crop_stop": 383,
+			"hpf_start": 130,
+			"hpf_stop": 86,
+			"res_type": "kaiser_fast"
+		}
+	},
+	"sr": 44100,
+	"pre_filter_start": 668,
+	"pre_filter_stop": 672
+}
\ No newline at end of file
diff --git a/infer/lib/uvr5_pack/lib_v5/modelparams/4band_v2_sn.json b/infer/lib/uvr5_pack/lib_v5/modelparams/4band_v2_sn.json
new file mode 100644
index 0000000000000000000000000000000000000000..2e5c770fe188779bf6b0873190b7a324d6a867b2
--- /dev/null
+++ b/infer/lib/uvr5_pack/lib_v5/modelparams/4band_v2_sn.json
@@ -0,0 +1,55 @@
+{
+	"bins": 672,
+	"unstable_bins": 8,
+	"reduction_bins": 637,
+	"band": {
+		"1": {
+			"sr": 7350,
+			"hl": 80,
+			"n_fft": 640,
+			"crop_start": 0,
+			"crop_stop": 85,
+			"lpf_start": 25,
+			"lpf_stop": 53,
+			"res_type": "polyphase"
+		},
+		"2": {
+			"sr": 7350,
+			"hl": 80,
+			"n_fft": 320,
+			"crop_start": 4,
+			"crop_stop": 87,
+			"hpf_start": 25,
+			"hpf_stop": 12,
+			"lpf_start": 31,
+			"lpf_stop": 62,
+			"res_type": "polyphase"
+		},		
+		"3": {
+			"sr": 14700,
+			"hl": 160,
+			"n_fft": 512,
+			"crop_start": 17,
+			"crop_stop": 216,
+			"hpf_start": 48,
+			"hpf_stop": 24,
+			"lpf_start": 139,
+			"lpf_stop": 210,
+			"res_type": "polyphase"
+		},	
+		"4": {
+			"sr": 44100,
+			"hl": 480,
+			"n_fft": 960,
+			"crop_start": 78,
+			"crop_stop": 383,
+			"hpf_start": 130,
+			"hpf_stop": 86,
+			"convert_channels": "stereo_n",
+			"res_type": "kaiser_fast"
+		}
+	},
+	"sr": 44100,
+	"pre_filter_start": 668,
+	"pre_filter_stop": 672
+}
\ No newline at end of file
diff --git a/infer/lib/uvr5_pack/lib_v5/modelparams/4band_v3.json b/infer/lib/uvr5_pack/lib_v5/modelparams/4band_v3.json
new file mode 100644
index 0000000000000000000000000000000000000000..edb908b8853c6359d1e98ae381888d1a9906ca0f
--- /dev/null
+++ b/infer/lib/uvr5_pack/lib_v5/modelparams/4band_v3.json
@@ -0,0 +1,54 @@
+{
+	"bins": 672,
+	"unstable_bins": 8,
+	"reduction_bins": 530,
+	"band": {
+		"1": {
+			"sr": 7350,
+			"hl": 80,
+			"n_fft": 640,
+			"crop_start": 0,
+			"crop_stop": 85,
+			"lpf_start": 25,
+			"lpf_stop": 53,
+			"res_type": "polyphase"
+		},
+		"2": {
+			"sr": 7350,
+			"hl": 80,
+			"n_fft": 320,
+			"crop_start": 4,
+			"crop_stop": 87,
+			"hpf_start": 25,
+			"hpf_stop": 12,
+			"lpf_start": 31,
+			"lpf_stop": 62,
+			"res_type": "polyphase"
+		},
+		"3": {
+			"sr": 14700,
+			"hl": 160,
+			"n_fft": 512,
+			"crop_start": 17,
+			"crop_stop": 216,
+			"hpf_start": 48,
+			"hpf_stop": 24,
+			"lpf_start": 139,
+			"lpf_stop": 210,
+			"res_type": "polyphase"
+		},
+		"4": {
+			"sr": 44100,
+			"hl": 480,
+			"n_fft": 960,
+			"crop_start": 78,
+			"crop_stop": 383,
+			"hpf_start": 130,
+			"hpf_stop": 86,
+			"res_type": "kaiser_fast"
+		}
+	},
+	"sr": 44100,
+	"pre_filter_start": 668,
+	"pre_filter_stop": 672
+}
\ No newline at end of file
diff --git a/infer/lib/uvr5_pack/lib_v5/modelparams/ensemble.json b/infer/lib/uvr5_pack/lib_v5/modelparams/ensemble.json
new file mode 100644
index 0000000000000000000000000000000000000000..ee69beb46fc82f34619c5e48761e329fcabbbd00
--- /dev/null
+++ b/infer/lib/uvr5_pack/lib_v5/modelparams/ensemble.json
@@ -0,0 +1,43 @@
+{
+	"mid_side_b2": true,
+	"bins": 1280,
+	"unstable_bins": 7,
+	"reduction_bins": 565,
+	"band": {
+		"1": {
+			"sr": 11025,
+			"hl": 108,
+			"n_fft": 2048,
+			"crop_start": 0,
+			"crop_stop": 374,
+			"lpf_start": 92,
+			"lpf_stop": 186,
+			"res_type": "polyphase"
+		},
+		"2": {
+			"sr": 22050,
+			"hl": 216,
+			"n_fft": 1536,
+			"crop_start": 0,
+			"crop_stop": 424,
+			"hpf_start": 68,
+			"hpf_stop": 34,
+			"lpf_start": 348,
+			"lpf_stop": 418,
+			"res_type": "polyphase"
+		},	
+		"3": {
+			"sr": 44100,
+			"hl": 432,
+			"n_fft": 1280,
+			"crop_start": 132,
+			"crop_stop": 614,
+			"hpf_start": 172,
+			"hpf_stop": 144,
+			"res_type": "polyphase"
+		}
+	},
+	"sr": 44100,
+	"pre_filter_start": 1280,
+	"pre_filter_stop": 1280
+}
\ No newline at end of file
diff --git a/infer/lib/uvr5_pack/lib_v5/nets.py b/infer/lib/uvr5_pack/lib_v5/nets.py
new file mode 100644
index 0000000000000000000000000000000000000000..5da3948c2f2e9edcc3cdac49bdf9f738e403de40
--- /dev/null
+++ b/infer/lib/uvr5_pack/lib_v5/nets.py
@@ -0,0 +1,123 @@
+import layers
+import torch
+import torch.nn.functional as F
+from torch import nn
+
+from . import spec_utils
+
+
+class BaseASPPNet(nn.Module):
+    def __init__(self, nin, ch, dilations=(4, 8, 16)):
+        super(BaseASPPNet, self).__init__()
+        self.enc1 = layers.Encoder(nin, ch, 3, 2, 1)
+        self.enc2 = layers.Encoder(ch, ch * 2, 3, 2, 1)
+        self.enc3 = layers.Encoder(ch * 2, ch * 4, 3, 2, 1)
+        self.enc4 = layers.Encoder(ch * 4, ch * 8, 3, 2, 1)
+
+        self.aspp = layers.ASPPModule(ch * 8, ch * 16, dilations)
+
+        self.dec4 = layers.Decoder(ch * (8 + 16), ch * 8, 3, 1, 1)
+        self.dec3 = layers.Decoder(ch * (4 + 8), ch * 4, 3, 1, 1)
+        self.dec2 = layers.Decoder(ch * (2 + 4), ch * 2, 3, 1, 1)
+        self.dec1 = layers.Decoder(ch * (1 + 2), ch, 3, 1, 1)
+
+    def __call__(self, x):
+        h, e1 = self.enc1(x)
+        h, e2 = self.enc2(h)
+        h, e3 = self.enc3(h)
+        h, e4 = self.enc4(h)
+
+        h = self.aspp(h)
+
+        h = self.dec4(h, e4)
+        h = self.dec3(h, e3)
+        h = self.dec2(h, e2)
+        h = self.dec1(h, e1)
+
+        return h
+
+
+class CascadedASPPNet(nn.Module):
+    def __init__(self, n_fft):
+        super(CascadedASPPNet, self).__init__()
+        self.stg1_low_band_net = BaseASPPNet(2, 16)
+        self.stg1_high_band_net = BaseASPPNet(2, 16)
+
+        self.stg2_bridge = layers.Conv2DBNActiv(18, 8, 1, 1, 0)
+        self.stg2_full_band_net = BaseASPPNet(8, 16)
+
+        self.stg3_bridge = layers.Conv2DBNActiv(34, 16, 1, 1, 0)
+        self.stg3_full_band_net = BaseASPPNet(16, 32)
+
+        self.out = nn.Conv2d(32, 2, 1, bias=False)
+        self.aux1_out = nn.Conv2d(16, 2, 1, bias=False)
+        self.aux2_out = nn.Conv2d(16, 2, 1, bias=False)
+
+        self.max_bin = n_fft // 2
+        self.output_bin = n_fft // 2 + 1
+
+        self.offset = 128
+
+    def forward(self, x, aggressiveness=None):
+        mix = x.detach()
+        x = x.clone()
+
+        x = x[:, :, : self.max_bin]
+
+        bandw = x.size()[2] // 2
+        aux1 = torch.cat(
+            [
+                self.stg1_low_band_net(x[:, :, :bandw]),
+                self.stg1_high_band_net(x[:, :, bandw:]),
+            ],
+            dim=2,
+        )
+
+        h = torch.cat([x, aux1], dim=1)
+        aux2 = self.stg2_full_band_net(self.stg2_bridge(h))
+
+        h = torch.cat([x, aux1, aux2], dim=1)
+        h = self.stg3_full_band_net(self.stg3_bridge(h))
+
+        mask = torch.sigmoid(self.out(h))
+        mask = F.pad(
+            input=mask,
+            pad=(0, 0, 0, self.output_bin - mask.size()[2]),
+            mode="replicate",
+        )
+
+        if self.training:
+            aux1 = torch.sigmoid(self.aux1_out(aux1))
+            aux1 = F.pad(
+                input=aux1,
+                pad=(0, 0, 0, self.output_bin - aux1.size()[2]),
+                mode="replicate",
+            )
+            aux2 = torch.sigmoid(self.aux2_out(aux2))
+            aux2 = F.pad(
+                input=aux2,
+                pad=(0, 0, 0, self.output_bin - aux2.size()[2]),
+                mode="replicate",
+            )
+            return mask * mix, aux1 * mix, aux2 * mix
+        else:
+            if aggressiveness:
+                mask[:, :, : aggressiveness["split_bin"]] = torch.pow(
+                    mask[:, :, : aggressiveness["split_bin"]],
+                    1 + aggressiveness["value"] / 3,
+                )
+                mask[:, :, aggressiveness["split_bin"] :] = torch.pow(
+                    mask[:, :, aggressiveness["split_bin"] :],
+                    1 + aggressiveness["value"],
+                )
+
+            return mask * mix
+
+    def predict(self, x_mag, aggressiveness=None):
+        h = self.forward(x_mag, aggressiveness)
+
+        if self.offset > 0:
+            h = h[:, :, :, self.offset : -self.offset]
+            assert h.size()[3] > 0
+
+        return h
diff --git a/infer/lib/uvr5_pack/lib_v5/nets_123812KB.py b/infer/lib/uvr5_pack/lib_v5/nets_123812KB.py
new file mode 100644
index 0000000000000000000000000000000000000000..167d4cb2198863cf43e93440f7e63c5342fc7605
--- /dev/null
+++ b/infer/lib/uvr5_pack/lib_v5/nets_123812KB.py
@@ -0,0 +1,122 @@
+import torch
+import torch.nn.functional as F
+from torch import nn
+
+from . import layers_123821KB as layers
+
+
+class BaseASPPNet(nn.Module):
+    def __init__(self, nin, ch, dilations=(4, 8, 16)):
+        super(BaseASPPNet, self).__init__()
+        self.enc1 = layers.Encoder(nin, ch, 3, 2, 1)
+        self.enc2 = layers.Encoder(ch, ch * 2, 3, 2, 1)
+        self.enc3 = layers.Encoder(ch * 2, ch * 4, 3, 2, 1)
+        self.enc4 = layers.Encoder(ch * 4, ch * 8, 3, 2, 1)
+
+        self.aspp = layers.ASPPModule(ch * 8, ch * 16, dilations)
+
+        self.dec4 = layers.Decoder(ch * (8 + 16), ch * 8, 3, 1, 1)
+        self.dec3 = layers.Decoder(ch * (4 + 8), ch * 4, 3, 1, 1)
+        self.dec2 = layers.Decoder(ch * (2 + 4), ch * 2, 3, 1, 1)
+        self.dec1 = layers.Decoder(ch * (1 + 2), ch, 3, 1, 1)
+
+    def __call__(self, x):
+        h, e1 = self.enc1(x)
+        h, e2 = self.enc2(h)
+        h, e3 = self.enc3(h)
+        h, e4 = self.enc4(h)
+
+        h = self.aspp(h)
+
+        h = self.dec4(h, e4)
+        h = self.dec3(h, e3)
+        h = self.dec2(h, e2)
+        h = self.dec1(h, e1)
+
+        return h
+
+
+class CascadedASPPNet(nn.Module):
+    def __init__(self, n_fft):
+        super(CascadedASPPNet, self).__init__()
+        self.stg1_low_band_net = BaseASPPNet(2, 32)
+        self.stg1_high_band_net = BaseASPPNet(2, 32)
+
+        self.stg2_bridge = layers.Conv2DBNActiv(34, 16, 1, 1, 0)
+        self.stg2_full_band_net = BaseASPPNet(16, 32)
+
+        self.stg3_bridge = layers.Conv2DBNActiv(66, 32, 1, 1, 0)
+        self.stg3_full_band_net = BaseASPPNet(32, 64)
+
+        self.out = nn.Conv2d(64, 2, 1, bias=False)
+        self.aux1_out = nn.Conv2d(32, 2, 1, bias=False)
+        self.aux2_out = nn.Conv2d(32, 2, 1, bias=False)
+
+        self.max_bin = n_fft // 2
+        self.output_bin = n_fft // 2 + 1
+
+        self.offset = 128
+
+    def forward(self, x, aggressiveness=None):
+        mix = x.detach()
+        x = x.clone()
+
+        x = x[:, :, : self.max_bin]
+
+        bandw = x.size()[2] // 2
+        aux1 = torch.cat(
+            [
+                self.stg1_low_band_net(x[:, :, :bandw]),
+                self.stg1_high_band_net(x[:, :, bandw:]),
+            ],
+            dim=2,
+        )
+
+        h = torch.cat([x, aux1], dim=1)
+        aux2 = self.stg2_full_band_net(self.stg2_bridge(h))
+
+        h = torch.cat([x, aux1, aux2], dim=1)
+        h = self.stg3_full_band_net(self.stg3_bridge(h))
+
+        mask = torch.sigmoid(self.out(h))
+        mask = F.pad(
+            input=mask,
+            pad=(0, 0, 0, self.output_bin - mask.size()[2]),
+            mode="replicate",
+        )
+
+        if self.training:
+            aux1 = torch.sigmoid(self.aux1_out(aux1))
+            aux1 = F.pad(
+                input=aux1,
+                pad=(0, 0, 0, self.output_bin - aux1.size()[2]),
+                mode="replicate",
+            )
+            aux2 = torch.sigmoid(self.aux2_out(aux2))
+            aux2 = F.pad(
+                input=aux2,
+                pad=(0, 0, 0, self.output_bin - aux2.size()[2]),
+                mode="replicate",
+            )
+            return mask * mix, aux1 * mix, aux2 * mix
+        else:
+            if aggressiveness:
+                mask[:, :, : aggressiveness["split_bin"]] = torch.pow(
+                    mask[:, :, : aggressiveness["split_bin"]],
+                    1 + aggressiveness["value"] / 3,
+                )
+                mask[:, :, aggressiveness["split_bin"] :] = torch.pow(
+                    mask[:, :, aggressiveness["split_bin"] :],
+                    1 + aggressiveness["value"],
+                )
+
+            return mask * mix
+
+    def predict(self, x_mag, aggressiveness=None):
+        h = self.forward(x_mag, aggressiveness)
+
+        if self.offset > 0:
+            h = h[:, :, :, self.offset : -self.offset]
+            assert h.size()[3] > 0
+
+        return h
diff --git a/infer/lib/uvr5_pack/lib_v5/nets_123821KB.py b/infer/lib/uvr5_pack/lib_v5/nets_123821KB.py
new file mode 100644
index 0000000000000000000000000000000000000000..167d4cb2198863cf43e93440f7e63c5342fc7605
--- /dev/null
+++ b/infer/lib/uvr5_pack/lib_v5/nets_123821KB.py
@@ -0,0 +1,122 @@
+import torch
+import torch.nn.functional as F
+from torch import nn
+
+from . import layers_123821KB as layers
+
+
+class BaseASPPNet(nn.Module):
+    def __init__(self, nin, ch, dilations=(4, 8, 16)):
+        super(BaseASPPNet, self).__init__()
+        self.enc1 = layers.Encoder(nin, ch, 3, 2, 1)
+        self.enc2 = layers.Encoder(ch, ch * 2, 3, 2, 1)
+        self.enc3 = layers.Encoder(ch * 2, ch * 4, 3, 2, 1)
+        self.enc4 = layers.Encoder(ch * 4, ch * 8, 3, 2, 1)
+
+        self.aspp = layers.ASPPModule(ch * 8, ch * 16, dilations)
+
+        self.dec4 = layers.Decoder(ch * (8 + 16), ch * 8, 3, 1, 1)
+        self.dec3 = layers.Decoder(ch * (4 + 8), ch * 4, 3, 1, 1)
+        self.dec2 = layers.Decoder(ch * (2 + 4), ch * 2, 3, 1, 1)
+        self.dec1 = layers.Decoder(ch * (1 + 2), ch, 3, 1, 1)
+
+    def __call__(self, x):
+        h, e1 = self.enc1(x)
+        h, e2 = self.enc2(h)
+        h, e3 = self.enc3(h)
+        h, e4 = self.enc4(h)
+
+        h = self.aspp(h)
+
+        h = self.dec4(h, e4)
+        h = self.dec3(h, e3)
+        h = self.dec2(h, e2)
+        h = self.dec1(h, e1)
+
+        return h
+
+
+class CascadedASPPNet(nn.Module):
+    def __init__(self, n_fft):
+        super(CascadedASPPNet, self).__init__()
+        self.stg1_low_band_net = BaseASPPNet(2, 32)
+        self.stg1_high_band_net = BaseASPPNet(2, 32)
+
+        self.stg2_bridge = layers.Conv2DBNActiv(34, 16, 1, 1, 0)
+        self.stg2_full_band_net = BaseASPPNet(16, 32)
+
+        self.stg3_bridge = layers.Conv2DBNActiv(66, 32, 1, 1, 0)
+        self.stg3_full_band_net = BaseASPPNet(32, 64)
+
+        self.out = nn.Conv2d(64, 2, 1, bias=False)
+        self.aux1_out = nn.Conv2d(32, 2, 1, bias=False)
+        self.aux2_out = nn.Conv2d(32, 2, 1, bias=False)
+
+        self.max_bin = n_fft // 2
+        self.output_bin = n_fft // 2 + 1
+
+        self.offset = 128
+
+    def forward(self, x, aggressiveness=None):
+        mix = x.detach()
+        x = x.clone()
+
+        x = x[:, :, : self.max_bin]
+
+        bandw = x.size()[2] // 2
+        aux1 = torch.cat(
+            [
+                self.stg1_low_band_net(x[:, :, :bandw]),
+                self.stg1_high_band_net(x[:, :, bandw:]),
+            ],
+            dim=2,
+        )
+
+        h = torch.cat([x, aux1], dim=1)
+        aux2 = self.stg2_full_band_net(self.stg2_bridge(h))
+
+        h = torch.cat([x, aux1, aux2], dim=1)
+        h = self.stg3_full_band_net(self.stg3_bridge(h))
+
+        mask = torch.sigmoid(self.out(h))
+        mask = F.pad(
+            input=mask,
+            pad=(0, 0, 0, self.output_bin - mask.size()[2]),
+            mode="replicate",
+        )
+
+        if self.training:
+            aux1 = torch.sigmoid(self.aux1_out(aux1))
+            aux1 = F.pad(
+                input=aux1,
+                pad=(0, 0, 0, self.output_bin - aux1.size()[2]),
+                mode="replicate",
+            )
+            aux2 = torch.sigmoid(self.aux2_out(aux2))
+            aux2 = F.pad(
+                input=aux2,
+                pad=(0, 0, 0, self.output_bin - aux2.size()[2]),
+                mode="replicate",
+            )
+            return mask * mix, aux1 * mix, aux2 * mix
+        else:
+            if aggressiveness:
+                mask[:, :, : aggressiveness["split_bin"]] = torch.pow(
+                    mask[:, :, : aggressiveness["split_bin"]],
+                    1 + aggressiveness["value"] / 3,
+                )
+                mask[:, :, aggressiveness["split_bin"] :] = torch.pow(
+                    mask[:, :, aggressiveness["split_bin"] :],
+                    1 + aggressiveness["value"],
+                )
+
+            return mask * mix
+
+    def predict(self, x_mag, aggressiveness=None):
+        h = self.forward(x_mag, aggressiveness)
+
+        if self.offset > 0:
+            h = h[:, :, :, self.offset : -self.offset]
+            assert h.size()[3] > 0
+
+        return h
diff --git a/infer/lib/uvr5_pack/lib_v5/nets_33966KB.py b/infer/lib/uvr5_pack/lib_v5/nets_33966KB.py
new file mode 100644
index 0000000000000000000000000000000000000000..73a5b836177b706c306e27875f8391c1aed4b948
--- /dev/null
+++ b/infer/lib/uvr5_pack/lib_v5/nets_33966KB.py
@@ -0,0 +1,122 @@
+import torch
+import torch.nn.functional as F
+from torch import nn
+
+from . import layers_33966KB as layers
+
+
+class BaseASPPNet(nn.Module):
+    def __init__(self, nin, ch, dilations=(4, 8, 16, 32)):
+        super(BaseASPPNet, self).__init__()
+        self.enc1 = layers.Encoder(nin, ch, 3, 2, 1)
+        self.enc2 = layers.Encoder(ch, ch * 2, 3, 2, 1)
+        self.enc3 = layers.Encoder(ch * 2, ch * 4, 3, 2, 1)
+        self.enc4 = layers.Encoder(ch * 4, ch * 8, 3, 2, 1)
+
+        self.aspp = layers.ASPPModule(ch * 8, ch * 16, dilations)
+
+        self.dec4 = layers.Decoder(ch * (8 + 16), ch * 8, 3, 1, 1)
+        self.dec3 = layers.Decoder(ch * (4 + 8), ch * 4, 3, 1, 1)
+        self.dec2 = layers.Decoder(ch * (2 + 4), ch * 2, 3, 1, 1)
+        self.dec1 = layers.Decoder(ch * (1 + 2), ch, 3, 1, 1)
+
+    def __call__(self, x):
+        h, e1 = self.enc1(x)
+        h, e2 = self.enc2(h)
+        h, e3 = self.enc3(h)
+        h, e4 = self.enc4(h)
+
+        h = self.aspp(h)
+
+        h = self.dec4(h, e4)
+        h = self.dec3(h, e3)
+        h = self.dec2(h, e2)
+        h = self.dec1(h, e1)
+
+        return h
+
+
+class CascadedASPPNet(nn.Module):
+    def __init__(self, n_fft):
+        super(CascadedASPPNet, self).__init__()
+        self.stg1_low_band_net = BaseASPPNet(2, 16)
+        self.stg1_high_band_net = BaseASPPNet(2, 16)
+
+        self.stg2_bridge = layers.Conv2DBNActiv(18, 8, 1, 1, 0)
+        self.stg2_full_band_net = BaseASPPNet(8, 16)
+
+        self.stg3_bridge = layers.Conv2DBNActiv(34, 16, 1, 1, 0)
+        self.stg3_full_band_net = BaseASPPNet(16, 32)
+
+        self.out = nn.Conv2d(32, 2, 1, bias=False)
+        self.aux1_out = nn.Conv2d(16, 2, 1, bias=False)
+        self.aux2_out = nn.Conv2d(16, 2, 1, bias=False)
+
+        self.max_bin = n_fft // 2
+        self.output_bin = n_fft // 2 + 1
+
+        self.offset = 128
+
+    def forward(self, x, aggressiveness=None):
+        mix = x.detach()
+        x = x.clone()
+
+        x = x[:, :, : self.max_bin]
+
+        bandw = x.size()[2] // 2
+        aux1 = torch.cat(
+            [
+                self.stg1_low_band_net(x[:, :, :bandw]),
+                self.stg1_high_band_net(x[:, :, bandw:]),
+            ],
+            dim=2,
+        )
+
+        h = torch.cat([x, aux1], dim=1)
+        aux2 = self.stg2_full_band_net(self.stg2_bridge(h))
+
+        h = torch.cat([x, aux1, aux2], dim=1)
+        h = self.stg3_full_band_net(self.stg3_bridge(h))
+
+        mask = torch.sigmoid(self.out(h))
+        mask = F.pad(
+            input=mask,
+            pad=(0, 0, 0, self.output_bin - mask.size()[2]),
+            mode="replicate",
+        )
+
+        if self.training:
+            aux1 = torch.sigmoid(self.aux1_out(aux1))
+            aux1 = F.pad(
+                input=aux1,
+                pad=(0, 0, 0, self.output_bin - aux1.size()[2]),
+                mode="replicate",
+            )
+            aux2 = torch.sigmoid(self.aux2_out(aux2))
+            aux2 = F.pad(
+                input=aux2,
+                pad=(0, 0, 0, self.output_bin - aux2.size()[2]),
+                mode="replicate",
+            )
+            return mask * mix, aux1 * mix, aux2 * mix
+        else:
+            if aggressiveness:
+                mask[:, :, : aggressiveness["split_bin"]] = torch.pow(
+                    mask[:, :, : aggressiveness["split_bin"]],
+                    1 + aggressiveness["value"] / 3,
+                )
+                mask[:, :, aggressiveness["split_bin"] :] = torch.pow(
+                    mask[:, :, aggressiveness["split_bin"] :],
+                    1 + aggressiveness["value"],
+                )
+
+            return mask * mix
+
+    def predict(self, x_mag, aggressiveness=None):
+        h = self.forward(x_mag, aggressiveness)
+
+        if self.offset > 0:
+            h = h[:, :, :, self.offset : -self.offset]
+            assert h.size()[3] > 0
+
+        return h
diff --git a/infer/lib/uvr5_pack/lib_v5/nets_537227KB.py b/infer/lib/uvr5_pack/lib_v5/nets_537227KB.py
new file mode 100644
index 0000000000000000000000000000000000000000..823b44fb64898e8dcbb12180ba45d1718f9b03f7
--- /dev/null
+++ b/infer/lib/uvr5_pack/lib_v5/nets_537227KB.py
@@ -0,0 +1,123 @@
+import numpy as np
+import torch
+import torch.nn.functional as F
+from torch import nn
+
+from . import layers_537238KB as layers
+
+
+class BaseASPPNet(nn.Module):
+    def __init__(self, nin, ch, dilations=(4, 8, 16)):
+        super(BaseASPPNet, self).__init__()
+        self.enc1 = layers.Encoder(nin, ch, 3, 2, 1)
+        self.enc2 = layers.Encoder(ch, ch * 2, 3, 2, 1)
+        self.enc3 = layers.Encoder(ch * 2, ch * 4, 3, 2, 1)
+        self.enc4 = layers.Encoder(ch * 4, ch * 8, 3, 2, 1)
+
+        self.aspp = layers.ASPPModule(ch * 8, ch * 16, dilations)
+
+        self.dec4 = layers.Decoder(ch * (8 + 16), ch * 8, 3, 1, 1)
+        self.dec3 = layers.Decoder(ch * (4 + 8), ch * 4, 3, 1, 1)
+        self.dec2 = layers.Decoder(ch * (2 + 4), ch * 2, 3, 1, 1)
+        self.dec1 = layers.Decoder(ch * (1 + 2), ch, 3, 1, 1)
+
+    def __call__(self, x):
+        h, e1 = self.enc1(x)
+        h, e2 = self.enc2(h)
+        h, e3 = self.enc3(h)
+        h, e4 = self.enc4(h)
+
+        h = self.aspp(h)
+
+        h = self.dec4(h, e4)
+        h = self.dec3(h, e3)
+        h = self.dec2(h, e2)
+        h = self.dec1(h, e1)
+
+        return h
+
+
+class CascadedASPPNet(nn.Module):
+    def __init__(self, n_fft):
+        super(CascadedASPPNet, self).__init__()
+        self.stg1_low_band_net = BaseASPPNet(2, 64)
+        self.stg1_high_band_net = BaseASPPNet(2, 64)
+
+        self.stg2_bridge = layers.Conv2DBNActiv(66, 32, 1, 1, 0)
+        self.stg2_full_band_net = BaseASPPNet(32, 64)
+
+        self.stg3_bridge = layers.Conv2DBNActiv(130, 64, 1, 1, 0)
+        self.stg3_full_band_net = BaseASPPNet(64, 128)
+
+        self.out = nn.Conv2d(128, 2, 1, bias=False)
+        self.aux1_out = nn.Conv2d(64, 2, 1, bias=False)
+        self.aux2_out = nn.Conv2d(64, 2, 1, bias=False)
+
+        self.max_bin = n_fft // 2
+        self.output_bin = n_fft // 2 + 1
+
+        self.offset = 128
+
+    def forward(self, x, aggressiveness=None):
+        mix = x.detach()
+        x = x.clone()
+
+        x = x[:, :, : self.max_bin]
+
+        bandw = x.size()[2] // 2
+        aux1 = torch.cat(
+            [
+                self.stg1_low_band_net(x[:, :, :bandw]),
+                self.stg1_high_band_net(x[:, :, bandw:]),
+            ],
+            dim=2,
+        )
+
+        h = torch.cat([x, aux1], dim=1)
+        aux2 = self.stg2_full_band_net(self.stg2_bridge(h))
+
+        h = torch.cat([x, aux1, aux2], dim=1)
+        h = self.stg3_full_band_net(self.stg3_bridge(h))
+
+        mask = torch.sigmoid(self.out(h))
+        mask = F.pad(
+            input=mask,
+            pad=(0, 0, 0, self.output_bin - mask.size()[2]),
+            mode="replicate",
+        )
+
+        if self.training:
+            aux1 = torch.sigmoid(self.aux1_out(aux1))
+            aux1 = F.pad(
+                input=aux1,
+                pad=(0, 0, 0, self.output_bin - aux1.size()[2]),
+                mode="replicate",
+            )
+            aux2 = torch.sigmoid(self.aux2_out(aux2))
+            aux2 = F.pad(
+                input=aux2,
+                pad=(0, 0, 0, self.output_bin - aux2.size()[2]),
+                mode="replicate",
+            )
+            return mask * mix, aux1 * mix, aux2 * mix
+        else:
+            if aggressiveness:
+                mask[:, :, : aggressiveness["split_bin"]] = torch.pow(
+                    mask[:, :, : aggressiveness["split_bin"]],
+                    1 + aggressiveness["value"] / 3,
+                )
+                mask[:, :, aggressiveness["split_bin"] :] = torch.pow(
+                    mask[:, :, aggressiveness["split_bin"] :],
+                    1 + aggressiveness["value"],
+                )
+
+            return mask * mix
+
+    def predict(self, x_mag, aggressiveness=None):
+        h = self.forward(x_mag, aggressiveness)
+
+        if self.offset > 0:
+            h = h[:, :, :, self.offset : -self.offset]
+            assert h.size()[3] > 0
+
+        return h
diff --git a/infer/lib/uvr5_pack/lib_v5/nets_537238KB.py b/infer/lib/uvr5_pack/lib_v5/nets_537238KB.py
new file mode 100644
index 0000000000000000000000000000000000000000..823b44fb64898e8dcbb12180ba45d1718f9b03f7
--- /dev/null
+++ b/infer/lib/uvr5_pack/lib_v5/nets_537238KB.py
@@ -0,0 +1,123 @@
+import numpy as np
+import torch
+import torch.nn.functional as F
+from torch import nn
+
+from . import layers_537238KB as layers
+
+
+class BaseASPPNet(nn.Module):
+    def __init__(self, nin, ch, dilations=(4, 8, 16)):
+        super(BaseASPPNet, self).__init__()
+        self.enc1 = layers.Encoder(nin, ch, 3, 2, 1)
+        self.enc2 = layers.Encoder(ch, ch * 2, 3, 2, 1)
+        self.enc3 = layers.Encoder(ch * 2, ch * 4, 3, 2, 1)
+        self.enc4 = layers.Encoder(ch * 4, ch * 8, 3, 2, 1)
+
+        self.aspp = layers.ASPPModule(ch * 8, ch * 16, dilations)
+
+        self.dec4 = layers.Decoder(ch * (8 + 16), ch * 8, 3, 1, 1)
+        self.dec3 = layers.Decoder(ch * (4 + 8), ch * 4, 3, 1, 1)
+        self.dec2 = layers.Decoder(ch * (2 + 4), ch * 2, 3, 1, 1)
+        self.dec1 = layers.Decoder(ch * (1 + 2), ch, 3, 1, 1)
+
+    def __call__(self, x):
+        h, e1 = self.enc1(x)
+        h, e2 = self.enc2(h)
+        h, e3 = self.enc3(h)
+        h, e4 = self.enc4(h)
+
+        h = self.aspp(h)
+
+        h = self.dec4(h, e4)
+        h = self.dec3(h, e3)
+        h = self.dec2(h, e2)
+        h = self.dec1(h, e1)
+
+        return h
+
+
+class CascadedASPPNet(nn.Module):
+    def __init__(self, n_fft):
+        super(CascadedASPPNet, self).__init__()
+        self.stg1_low_band_net = BaseASPPNet(2, 64)
+        self.stg1_high_band_net = BaseASPPNet(2, 64)
+
+        self.stg2_bridge = layers.Conv2DBNActiv(66, 32, 1, 1, 0)
+        self.stg2_full_band_net = BaseASPPNet(32, 64)
+
+        self.stg3_bridge = layers.Conv2DBNActiv(130, 64, 1, 1, 0)
+        self.stg3_full_band_net = BaseASPPNet(64, 128)
+
+        self.out = nn.Conv2d(128, 2, 1, bias=False)
+        self.aux1_out = nn.Conv2d(64, 2, 1, bias=False)
+        self.aux2_out = nn.Conv2d(64, 2, 1, bias=False)
+
+        self.max_bin = n_fft // 2
+        self.output_bin = n_fft // 2 + 1
+
+        self.offset = 128
+
+    def forward(self, x, aggressiveness=None):
+        mix = x.detach()
+        x = x.clone()
+
+        x = x[:, :, : self.max_bin]
+
+        bandw = x.size()[2] // 2
+        aux1 = torch.cat(
+            [
+                self.stg1_low_band_net(x[:, :, :bandw]),
+                self.stg1_high_band_net(x[:, :, bandw:]),
+            ],
+            dim=2,
+        )
+
+        h = torch.cat([x, aux1], dim=1)
+        aux2 = self.stg2_full_band_net(self.stg2_bridge(h))
+
+        h = torch.cat([x, aux1, aux2], dim=1)
+        h = self.stg3_full_band_net(self.stg3_bridge(h))
+
+        mask = torch.sigmoid(self.out(h))
+        mask = F.pad(
+            input=mask,
+            pad=(0, 0, 0, self.output_bin - mask.size()[2]),
+            mode="replicate",
+        )
+
+        if self.training:
+            aux1 = torch.sigmoid(self.aux1_out(aux1))
+            aux1 = F.pad(
+                input=aux1,
+                pad=(0, 0, 0, self.output_bin - aux1.size()[2]),
+                mode="replicate",
+            )
+            aux2 = torch.sigmoid(self.aux2_out(aux2))
+            aux2 = F.pad(
+                input=aux2,
+                pad=(0, 0, 0, self.output_bin - aux2.size()[2]),
+                mode="replicate",
+            )
+            return mask * mix, aux1 * mix, aux2 * mix
+        else:
+            if aggressiveness:
+                mask[:, :, : aggressiveness["split_bin"]] = torch.pow(
+                    mask[:, :, : aggressiveness["split_bin"]],
+                    1 + aggressiveness["value"] / 3,
+                )
+                mask[:, :, aggressiveness["split_bin"] :] = torch.pow(
+                    mask[:, :, aggressiveness["split_bin"] :],
+                    1 + aggressiveness["value"],
+                )
+
+            return mask * mix
+
+    def predict(self, x_mag, aggressiveness=None):
+        h = self.forward(x_mag, aggressiveness)
+
+        if self.offset > 0:
+            h = h[:, :, :, self.offset : -self.offset]
+            assert h.size()[3] > 0
+
+        return h
diff --git a/infer/lib/uvr5_pack/lib_v5/nets_61968KB.py b/infer/lib/uvr5_pack/lib_v5/nets_61968KB.py
new file mode 100644
index 0000000000000000000000000000000000000000..167d4cb2198863cf43e93440f7e63c5342fc7605
--- /dev/null
+++ b/infer/lib/uvr5_pack/lib_v5/nets_61968KB.py
@@ -0,0 +1,122 @@
+import torch
+import torch.nn.functional as F
+from torch import nn
+
+from . import layers_123821KB as layers
+
+
+class BaseASPPNet(nn.Module):
+    def __init__(self, nin, ch, dilations=(4, 8, 16)):
+        super(BaseASPPNet, self).__init__()
+        self.enc1 = layers.Encoder(nin, ch, 3, 2, 1)
+        self.enc2 = layers.Encoder(ch, ch * 2, 3, 2, 1)
+        self.enc3 = layers.Encoder(ch * 2, ch * 4, 3, 2, 1)
+        self.enc4 = layers.Encoder(ch * 4, ch * 8, 3, 2, 1)
+
+        self.aspp = layers.ASPPModule(ch * 8, ch * 16, dilations)
+
+        self.dec4 = layers.Decoder(ch * (8 + 16), ch * 8, 3, 1, 1)
+        self.dec3 = layers.Decoder(ch * (4 + 8), ch * 4, 3, 1, 1)
+        self.dec2 = layers.Decoder(ch * (2 + 4), ch * 2, 3, 1, 1)
+        self.dec1 = layers.Decoder(ch * (1 + 2), ch, 3, 1, 1)
+
+    def __call__(self, x):
+        h, e1 = self.enc1(x)
+        h, e2 = self.enc2(h)
+        h, e3 = self.enc3(h)
+        h, e4 = self.enc4(h)
+
+        h = self.aspp(h)
+
+        h = self.dec4(h, e4)
+        h = self.dec3(h, e3)
+        h = self.dec2(h, e2)
+        h = self.dec1(h, e1)
+
+        return h
+
+
+class CascadedASPPNet(nn.Module):
+    def __init__(self, n_fft):
+        super(CascadedASPPNet, self).__init__()
+        self.stg1_low_band_net = BaseASPPNet(2, 32)
+        self.stg1_high_band_net = BaseASPPNet(2, 32)
+
+        self.stg2_bridge = layers.Conv2DBNActiv(34, 16, 1, 1, 0)
+        self.stg2_full_band_net = BaseASPPNet(16, 32)
+
+        self.stg3_bridge = layers.Conv2DBNActiv(66, 32, 1, 1, 0)
+        self.stg3_full_band_net = BaseASPPNet(32, 64)
+
+        self.out = nn.Conv2d(64, 2, 1, bias=False)
+        self.aux1_out = nn.Conv2d(32, 2, 1, bias=False)
+        self.aux2_out = nn.Conv2d(32, 2, 1, bias=False)
+
+        self.max_bin = n_fft // 2
+        self.output_bin = n_fft // 2 + 1
+
+        self.offset = 128
+
+    def forward(self, x, aggressiveness=None):
+        mix = x.detach()
+        x = x.clone()
+
+        x = x[:, :, : self.max_bin]
+
+        bandw = x.size()[2] // 2
+        aux1 = torch.cat(
+            [
+                self.stg1_low_band_net(x[:, :, :bandw]),
+                self.stg1_high_band_net(x[:, :, bandw:]),
+            ],
+            dim=2,
+        )
+
+        h = torch.cat([x, aux1], dim=1)
+        aux2 = self.stg2_full_band_net(self.stg2_bridge(h))
+
+        h = torch.cat([x, aux1, aux2], dim=1)
+        h = self.stg3_full_band_net(self.stg3_bridge(h))
+
+        mask = torch.sigmoid(self.out(h))
+        mask = F.pad(
+            input=mask,
+            pad=(0, 0, 0, self.output_bin - mask.size()[2]),
+            mode="replicate",
+        )
+
+        if self.training:
+            aux1 = torch.sigmoid(self.aux1_out(aux1))
+            aux1 = F.pad(
+                input=aux1,
+                pad=(0, 0, 0, self.output_bin - aux1.size()[2]),
+                mode="replicate",
+            )
+            aux2 = torch.sigmoid(self.aux2_out(aux2))
+            aux2 = F.pad(
+                input=aux2,
+                pad=(0, 0, 0, self.output_bin - aux2.size()[2]),
+                mode="replicate",
+            )
+            return mask * mix, aux1 * mix, aux2 * mix
+        else:
+            if aggressiveness:
+                mask[:, :, : aggressiveness["split_bin"]] = torch.pow(
+                    mask[:, :, : aggressiveness["split_bin"]],
+                    1 + aggressiveness["value"] / 3,
+                )
+                mask[:, :, aggressiveness["split_bin"] :] = torch.pow(
+                    mask[:, :, aggressiveness["split_bin"] :],
+                    1 + aggressiveness["value"],
+                )
+
+            return mask * mix
+
+    def predict(self, x_mag, aggressiveness=None):
+        h = self.forward(x_mag, aggressiveness)
+
+        if self.offset > 0:
+            h = h[:, :, :, self.offset : -self.offset]
+            assert h.size()[3] > 0
+
+        return h
diff --git a/infer/lib/uvr5_pack/lib_v5/nets_new.py b/infer/lib/uvr5_pack/lib_v5/nets_new.py
new file mode 100644
index 0000000000000000000000000000000000000000..1c0f4fa96d921e979fe31bd4151701b7783fbcea
--- /dev/null
+++ b/infer/lib/uvr5_pack/lib_v5/nets_new.py
@@ -0,0 +1,133 @@
+import torch
+import torch.nn.functional as F
+from torch import nn
+
+from . import layers_new
+
+
+class BaseNet(nn.Module):
+    def __init__(
+        self, nin, nout, nin_lstm, nout_lstm, dilations=((4, 2), (8, 4), (12, 6))
+    ):
+        super(BaseNet, self).__init__()
+        self.enc1 = layers_new.Conv2DBNActiv(nin, nout, 3, 1, 1)
+        self.enc2 = layers_new.Encoder(nout, nout * 2, 3, 2, 1)
+        self.enc3 = layers_new.Encoder(nout * 2, nout * 4, 3, 2, 1)
+        self.enc4 = layers_new.Encoder(nout * 4, nout * 6, 3, 2, 1)
+        self.enc5 = layers_new.Encoder(nout * 6, nout * 8, 3, 2, 1)
+
+        self.aspp = layers_new.ASPPModule(nout * 8, nout * 8, dilations, dropout=True)
+
+        self.dec4 = layers_new.Decoder(nout * (6 + 8), nout * 6, 3, 1, 1)
+        self.dec3 = layers_new.Decoder(nout * (4 + 6), nout * 4, 3, 1, 1)
+        self.dec2 = layers_new.Decoder(nout * (2 + 4), nout * 2, 3, 1, 1)
+        self.lstm_dec2 = layers_new.LSTMModule(nout * 2, nin_lstm, nout_lstm)
+        self.dec1 = layers_new.Decoder(nout * (1 + 2) + 1, nout * 1, 3, 1, 1)
+
+    def __call__(self, x):
+        e1 = self.enc1(x)
+        e2 = self.enc2(e1)
+        e3 = self.enc3(e2)
+        e4 = self.enc4(e3)
+        e5 = self.enc5(e4)
+
+        h = self.aspp(e5)
+
+        h = self.dec4(h, e4)
+        h = self.dec3(h, e3)
+        h = self.dec2(h, e2)
+        h = torch.cat([h, self.lstm_dec2(h)], dim=1)
+        h = self.dec1(h, e1)
+
+        return h
+
+
+class CascadedNet(nn.Module):
+    def __init__(self, n_fft, nout=32, nout_lstm=128):
+        super(CascadedNet, self).__init__()
+
+        self.max_bin = n_fft // 2
+        self.output_bin = n_fft // 2 + 1
+        self.nin_lstm = self.max_bin // 2
+        self.offset = 64
+
+        self.stg1_low_band_net = nn.Sequential(
+            BaseNet(2, nout // 2, self.nin_lstm // 2, nout_lstm),
+            layers_new.Conv2DBNActiv(nout // 2, nout // 4, 1, 1, 0),
+        )
+
+        self.stg1_high_band_net = BaseNet(
+            2, nout // 4, self.nin_lstm // 2, nout_lstm // 2
+        )
+
+        self.stg2_low_band_net = nn.Sequential(
+            BaseNet(nout // 4 + 2, nout, self.nin_lstm // 2, nout_lstm),
+            layers_new.Conv2DBNActiv(nout, nout // 2, 1, 1, 0),
+        )
+        self.stg2_high_band_net = BaseNet(
+            nout // 4 + 2, nout // 2, self.nin_lstm // 2, nout_lstm // 2
+        )
+
+        self.stg3_full_band_net = BaseNet(
+            3 * nout // 4 + 2, nout, self.nin_lstm, nout_lstm
+        )
+
+        self.out = nn.Conv2d(nout, 2, 1, bias=False)
+        self.aux_out = nn.Conv2d(3 * nout // 4, 2, 1, bias=False)
+
+    def forward(self, x):
+        x = x[:, :, : self.max_bin]
+
+        bandw = x.size()[2] // 2
+        l1_in = x[:, :, :bandw]
+        h1_in = x[:, :, bandw:]
+        l1 = self.stg1_low_band_net(l1_in)
+        h1 = self.stg1_high_band_net(h1_in)
+        aux1 = torch.cat([l1, h1], dim=2)
+
+        l2_in = torch.cat([l1_in, l1], dim=1)
+        h2_in = torch.cat([h1_in, h1], dim=1)
+        l2 = self.stg2_low_band_net(l2_in)
+        h2 = self.stg2_high_band_net(h2_in)
+        aux2 = torch.cat([l2, h2], dim=2)
+
+        f3_in = torch.cat([x, aux1, aux2], dim=1)
+        f3 = self.stg3_full_band_net(f3_in)
+
+        mask = torch.sigmoid(self.out(f3))
+        mask = F.pad(
+            input=mask,
+            pad=(0, 0, 0, self.output_bin - mask.size()[2]),
+            mode="replicate",
+        )
+
+        if self.training:
+            aux = torch.cat([aux1, aux2], dim=1)
+            aux = torch.sigmoid(self.aux_out(aux))
+            aux = F.pad(
+                input=aux,
+                pad=(0, 0, 0, self.output_bin - aux.size()[2]),
+                mode="replicate",
+            )
+            return mask, aux
+        else:
+            return mask
+
+    def predict_mask(self, x):
+        mask = self.forward(x)
+
+        if self.offset > 0:
+            mask = mask[:, :, :, self.offset : -self.offset]
+            assert mask.size()[3] > 0
+
+        return mask
+
+    def predict(self, x, aggressiveness=None):
+        mask = self.forward(x)
+        pred_mag = x * mask
+
+        if self.offset > 0:
+            pred_mag = pred_mag[:, :, :, self.offset : -self.offset]
+            assert pred_mag.size()[3] > 0
+
+        return pred_mag
diff --git a/infer/lib/uvr5_pack/lib_v5/spec_utils.py b/infer/lib/uvr5_pack/lib_v5/spec_utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..a9634fd51ff47bf90211839231774719154c37cf
--- /dev/null
+++ b/infer/lib/uvr5_pack/lib_v5/spec_utils.py
@@ -0,0 +1,672 @@
+import hashlib
+import json
+import math
+import os
+
+import librosa
+import numpy as np
+import soundfile as sf
+from tqdm import tqdm
+
+
+def crop_center(h1, h2):
+    h1_shape = h1.size()
+    h2_shape = h2.size()
+
+    if h1_shape[3] == h2_shape[3]:
+        return h1
+    elif h1_shape[3] < h2_shape[3]:
+        raise ValueError("h1_shape[3] must be greater than h2_shape[3]")
+
+    # s_freq = (h2_shape[2] - h1_shape[2]) // 2
+    # e_freq = s_freq + h1_shape[2]
+    s_time = (h1_shape[3] - h2_shape[3]) // 2
+    e_time = s_time + h2_shape[3]
+    h1 = h1[:, :, :, s_time:e_time]
+
+    return h1
+
+
+def wave_to_spectrogram(
+    wave, hop_length, n_fft, mid_side=False, mid_side_b2=False, reverse=False
+):
+    if reverse:
+        wave_left = np.flip(np.asfortranarray(wave[0]))
+        wave_right = np.flip(np.asfortranarray(wave[1]))
+    elif mid_side:
+        wave_left = np.asfortranarray(np.add(wave[0], wave[1]) / 2)
+        wave_right = np.asfortranarray(np.subtract(wave[0], wave[1]))
+    elif mid_side_b2:
+        wave_left = np.asfortranarray(np.add(wave[1], wave[0] * 0.5))
+        wave_right = np.asfortranarray(np.subtract(wave[0], wave[1] * 0.5))
+    else:
+        wave_left = np.asfortranarray(wave[0])
+        wave_right = np.asfortranarray(wave[1])
+
+    spec_left = librosa.stft(wave_left, n_fft, hop_length=hop_length)
+    spec_right = librosa.stft(wave_right, n_fft, hop_length=hop_length)
+
+    spec = np.asfortranarray([spec_left, spec_right])
+
+    return spec
+
+
+def wave_to_spectrogram_mt(
+    wave, hop_length, n_fft, mid_side=False, mid_side_b2=False, reverse=False
+):
+    import threading
+
+    if reverse:
+        wave_left = np.flip(np.asfortranarray(wave[0]))
+        wave_right = np.flip(np.asfortranarray(wave[1]))
+    elif mid_side:
+        wave_left = np.asfortranarray(np.add(wave[0], wave[1]) / 2)
+        wave_right = np.asfortranarray(np.subtract(wave[0], wave[1]))
+    elif mid_side_b2:
+        wave_left = np.asfortranarray(np.add(wave[1], wave[0] * 0.5))
+        wave_right = np.asfortranarray(np.subtract(wave[0], wave[1] * 0.5))
+    else:
+        wave_left = np.asfortranarray(wave[0])
+        wave_right = np.asfortranarray(wave[1])
+
+    def run_thread(**kwargs):
+        global spec_left
+        spec_left = librosa.stft(**kwargs)
+
+    thread = threading.Thread(
+        target=run_thread,
+        kwargs={"y": wave_left, "n_fft": n_fft, "hop_length": hop_length},
+    )
+    thread.start()
+    spec_right = librosa.stft(wave_right, n_fft, hop_length=hop_length)
+    thread.join()
+
+    spec = np.asfortranarray([spec_left, spec_right])
+
+    return spec
+
+
+def combine_spectrograms(specs, mp):
+    l = min([specs[i].shape[2] for i in specs])
+    spec_c = np.zeros(shape=(2, mp.param["bins"] + 1, l), dtype=np.complex64)
+    offset = 0
+    bands_n = len(mp.param["band"])
+
+    for d in range(1, bands_n + 1):
+        h = mp.param["band"][d]["crop_stop"] - mp.param["band"][d]["crop_start"]
+        spec_c[:, offset : offset + h, :l] = specs[d][
+            :, mp.param["band"][d]["crop_start"] : mp.param["band"][d]["crop_stop"], :l
+        ]
+        offset += h
+
+    if offset > mp.param["bins"]:
+        raise ValueError("Too much bins")
+
+    # lowpass fiter
+    if (
+        mp.param["pre_filter_start"] > 0
+    ):  # and mp.param['band'][bands_n]['res_type'] in ['scipy', 'polyphase']:
+        if bands_n == 1:
+            spec_c = fft_lp_filter(
+                spec_c, mp.param["pre_filter_start"], mp.param["pre_filter_stop"]
+            )
+        else:
+            gp = 1
+            for b in range(
+                mp.param["pre_filter_start"] + 1, mp.param["pre_filter_stop"]
+            ):
+                g = math.pow(
+                    10, -(b - mp.param["pre_filter_start"]) * (3.5 - gp) / 20.0
+                )
+                gp = g
+                spec_c[:, b, :] *= g
+
+    return np.asfortranarray(spec_c)
+
+
+def spectrogram_to_image(spec, mode="magnitude"):
+    if mode == "magnitude":
+        if np.iscomplexobj(spec):
+            y = np.abs(spec)
+        else:
+            y = spec
+        y = np.log10(y**2 + 1e-8)
+    elif mode == "phase":
+        if np.iscomplexobj(spec):
+            y = np.angle(spec)
+        else:
+            y = spec
+
+    y -= y.min()
+    y *= 255 / y.max()
+    img = np.uint8(y)
+
+    if y.ndim == 3:
+        img = img.transpose(1, 2, 0)
+        img = np.concatenate([np.max(img, axis=2, keepdims=True), img], axis=2)
+
+    return img
+
+
+def reduce_vocal_aggressively(X, y, softmask):
+    v = X - y
+    y_mag_tmp = np.abs(y)
+    v_mag_tmp = np.abs(v)
+
+    v_mask = v_mag_tmp > y_mag_tmp
+    y_mag = np.clip(y_mag_tmp - v_mag_tmp * v_mask * softmask, 0, np.inf)
+
+    return y_mag * np.exp(1.0j * np.angle(y))
+
+
+def mask_silence(mag, ref, thres=0.2, min_range=64, fade_size=32):
+    if min_range < fade_size * 2:
+        raise ValueError("min_range must be >= fade_area * 2")
+
+    mag = mag.copy()
+
+    idx = np.where(ref.mean(axis=(0, 1)) < thres)[0]
+    starts = np.insert(idx[np.where(np.diff(idx) != 1)[0] + 1], 0, idx[0])
+    ends = np.append(idx[np.where(np.diff(idx) != 1)[0]], idx[-1])
+    uninformative = np.where(ends - starts > min_range)[0]
+    if len(uninformative) > 0:
+        starts = starts[uninformative]
+        ends = ends[uninformative]
+        old_e = None
+        for s, e in zip(starts, ends):
+            if old_e is not None and s - old_e < fade_size:
+                s = old_e - fade_size * 2
+
+            if s != 0:
+                weight = np.linspace(0, 1, fade_size)
+                mag[:, :, s : s + fade_size] += weight * ref[:, :, s : s + fade_size]
+            else:
+                s -= fade_size
+
+            if e != mag.shape[2]:
+                weight = np.linspace(1, 0, fade_size)
+                mag[:, :, e - fade_size : e] += weight * ref[:, :, e - fade_size : e]
+            else:
+                e += fade_size
+
+            mag[:, :, s + fade_size : e - fade_size] += ref[
+                :, :, s + fade_size : e - fade_size
+            ]
+            old_e = e
+
+    return mag
+
+
+def align_wave_head_and_tail(a, b):
+    l = min([a[0].size, b[0].size])
+
+    return a[:l, :l], b[:l, :l]
+
+
+def cache_or_load(mix_path, inst_path, mp):
+    mix_basename = os.path.splitext(os.path.basename(mix_path))[0]
+    inst_basename = os.path.splitext(os.path.basename(inst_path))[0]
+
+    cache_dir = "mph{}".format(
+        hashlib.sha1(json.dumps(mp.param, sort_keys=True).encode("utf-8")).hexdigest()
+    )
+    mix_cache_dir = os.path.join("cache", cache_dir)
+    inst_cache_dir = os.path.join("cache", cache_dir)
+
+    os.makedirs(mix_cache_dir, exist_ok=True)
+    os.makedirs(inst_cache_dir, exist_ok=True)
+
+    mix_cache_path = os.path.join(mix_cache_dir, mix_basename + ".npy")
+    inst_cache_path = os.path.join(inst_cache_dir, inst_basename + ".npy")
+
+    if os.path.exists(mix_cache_path) and os.path.exists(inst_cache_path):
+        X_spec_m = np.load(mix_cache_path)
+        y_spec_m = np.load(inst_cache_path)
+    else:
+        X_wave, y_wave, X_spec_s, y_spec_s = {}, {}, {}, {}
+
+        for d in range(len(mp.param["band"]), 0, -1):
+            bp = mp.param["band"][d]
+
+            if d == len(mp.param["band"]):  # high-end band
+                X_wave[d], _ = librosa.load(
+                    mix_path, bp["sr"], False, dtype=np.float32, res_type=bp["res_type"]
+                )
+                y_wave[d], _ = librosa.load(
+                    inst_path,
+                    bp["sr"],
+                    False,
+                    dtype=np.float32,
+                    res_type=bp["res_type"],
+                )
+            else:  # lower bands
+                X_wave[d] = librosa.resample(
+                    X_wave[d + 1],
+                    mp.param["band"][d + 1]["sr"],
+                    bp["sr"],
+                    res_type=bp["res_type"],
+                )
+                y_wave[d] = librosa.resample(
+                    y_wave[d + 1],
+                    mp.param["band"][d + 1]["sr"],
+                    bp["sr"],
+                    res_type=bp["res_type"],
+                )
+
+            X_wave[d], y_wave[d] = align_wave_head_and_tail(X_wave[d], y_wave[d])
+
+            X_spec_s[d] = wave_to_spectrogram(
+                X_wave[d],
+                bp["hl"],
+                bp["n_fft"],
+                mp.param["mid_side"],
+                mp.param["mid_side_b2"],
+                mp.param["reverse"],
+            )
+            y_spec_s[d] = wave_to_spectrogram(
+                y_wave[d],
+                bp["hl"],
+                bp["n_fft"],
+                mp.param["mid_side"],
+                mp.param["mid_side_b2"],
+                mp.param["reverse"],
+            )
+
+        del X_wave, y_wave
+
+        X_spec_m = combine_spectrograms(X_spec_s, mp)
+        y_spec_m = combine_spectrograms(y_spec_s, mp)
+
+        if X_spec_m.shape != y_spec_m.shape:
+            raise ValueError("The combined spectrograms are different: " + mix_path)
+
+        _, ext = os.path.splitext(mix_path)
+
+        np.save(mix_cache_path, X_spec_m)
+        np.save(inst_cache_path, y_spec_m)
+
+    return X_spec_m, y_spec_m
+
+
+def spectrogram_to_wave(spec, hop_length, mid_side, mid_side_b2, reverse):
+    spec_left = np.asfortranarray(spec[0])
+    spec_right = np.asfortranarray(spec[1])
+
+    wave_left = librosa.istft(spec_left, hop_length=hop_length)
+    wave_right = librosa.istft(spec_right, hop_length=hop_length)
+
+    if reverse:
+        return np.asfortranarray([np.flip(wave_left), np.flip(wave_right)])
+    elif mid_side:
+        return np.asfortranarray(
+            [np.add(wave_left, wave_right / 2), np.subtract(wave_left, wave_right / 2)]
+        )
+    elif mid_side_b2:
+        return np.asfortranarray(
+            [
+                np.add(wave_right / 1.25, 0.4 * wave_left),
+                np.subtract(wave_left / 1.25, 0.4 * wave_right),
+            ]
+        )
+    else:
+        return np.asfortranarray([wave_left, wave_right])
+
+
+def spectrogram_to_wave_mt(spec, hop_length, mid_side, reverse, mid_side_b2):
+    import threading
+
+    spec_left = np.asfortranarray(spec[0])
+    spec_right = np.asfortranarray(spec[1])
+
+    def run_thread(**kwargs):
+        global wave_left
+        wave_left = librosa.istft(**kwargs)
+
+    thread = threading.Thread(
+        target=run_thread, kwargs={"stft_matrix": spec_left, "hop_length": hop_length}
+    )
+    thread.start()
+    wave_right = librosa.istft(spec_right, hop_length=hop_length)
+    thread.join()
+
+    if reverse:
+        return np.asfortranarray([np.flip(wave_left), np.flip(wave_right)])
+    elif mid_side:
+        return np.asfortranarray(
+            [np.add(wave_left, wave_right / 2), np.subtract(wave_left, wave_right / 2)]
+        )
+    elif mid_side_b2:
+        return np.asfortranarray(
+            [
+                np.add(wave_right / 1.25, 0.4 * wave_left),
+                np.subtract(wave_left / 1.25, 0.4 * wave_right),
+            ]
+        )
+    else:
+        return np.asfortranarray([wave_left, wave_right])
+
+
+def cmb_spectrogram_to_wave(spec_m, mp, extra_bins_h=None, extra_bins=None):
+    wave_band = {}
+    bands_n = len(mp.param["band"])
+    offset = 0
+
+    for d in range(1, bands_n + 1):
+        bp = mp.param["band"][d]
+        spec_s = np.ndarray(
+            shape=(2, bp["n_fft"] // 2 + 1, spec_m.shape[2]), dtype=complex
+        )
+        h = bp["crop_stop"] - bp["crop_start"]
+        spec_s[:, bp["crop_start"] : bp["crop_stop"], :] = spec_m[
+            :, offset : offset + h, :
+        ]
+
+        offset += h
+        if d == bands_n:  # higher
+            if extra_bins_h:  # if --high_end_process bypass
+                max_bin = bp["n_fft"] // 2
+                spec_s[:, max_bin - extra_bins_h : max_bin, :] = extra_bins[
+                    :, :extra_bins_h, :
+                ]
+            if bp["hpf_start"] > 0:
+                spec_s = fft_hp_filter(spec_s, bp["hpf_start"], bp["hpf_stop"] - 1)
+            if bands_n == 1:
+                wave = spectrogram_to_wave(
+                    spec_s,
+                    bp["hl"],
+                    mp.param["mid_side"],
+                    mp.param["mid_side_b2"],
+                    mp.param["reverse"],
+                )
+            else:
+                wave = np.add(
+                    wave,
+                    spectrogram_to_wave(
+                        spec_s,
+                        bp["hl"],
+                        mp.param["mid_side"],
+                        mp.param["mid_side_b2"],
+                        mp.param["reverse"],
+                    ),
+                )
+        else:
+            sr = mp.param["band"][d + 1]["sr"]
+            if d == 1:  # lower
+                spec_s = fft_lp_filter(spec_s, bp["lpf_start"], bp["lpf_stop"])
+                wave = librosa.resample(
+                    spectrogram_to_wave(
+                        spec_s,
+                        bp["hl"],
+                        mp.param["mid_side"],
+                        mp.param["mid_side_b2"],
+                        mp.param["reverse"],
+                    ),
+                    bp["sr"],
+                    sr,
+                    res_type="sinc_fastest",
+                )
+            else:  # mid
+                spec_s = fft_hp_filter(spec_s, bp["hpf_start"], bp["hpf_stop"] - 1)
+                spec_s = fft_lp_filter(spec_s, bp["lpf_start"], bp["lpf_stop"])
+                wave2 = np.add(
+                    wave,
+                    spectrogram_to_wave(
+                        spec_s,
+                        bp["hl"],
+                        mp.param["mid_side"],
+                        mp.param["mid_side_b2"],
+                        mp.param["reverse"],
+                    ),
+                )
+                # wave = librosa.core.resample(wave2, bp['sr'], sr, res_type="sinc_fastest")
+                wave = librosa.core.resample(wave2, bp["sr"], sr, res_type="scipy")
+
+    return wave.T
+
+
+def fft_lp_filter(spec, bin_start, bin_stop):
+    g = 1.0
+    for b in range(bin_start, bin_stop):
+        g -= 1 / (bin_stop - bin_start)
+        spec[:, b, :] = g * spec[:, b, :]
+
+    spec[:, bin_stop:, :] *= 0
+
+    return spec
+
+
+def fft_hp_filter(spec, bin_start, bin_stop):
+    g = 1.0
+    for b in range(bin_start, bin_stop, -1):
+        g -= 1 / (bin_start - bin_stop)
+        spec[:, b, :] = g * spec[:, b, :]
+
+    spec[:, 0 : bin_stop + 1, :] *= 0
+
+    return spec
+
+
+def mirroring(a, spec_m, input_high_end, mp):
+    if "mirroring" == a:
+        mirror = np.flip(
+            np.abs(
+                spec_m[
+                    :,
+                    mp.param["pre_filter_start"]
+                    - 10
+                    - input_high_end.shape[1] : mp.param["pre_filter_start"]
+                    - 10,
+                    :,
+                ]
+            ),
+            1,
+        )
+        mirror = mirror * np.exp(1.0j * np.angle(input_high_end))
+
+        return np.where(
+            np.abs(input_high_end) <= np.abs(mirror), input_high_end, mirror
+        )
+
+    if "mirroring2" == a:
+        mirror = np.flip(
+            np.abs(
+                spec_m[
+                    :,
+                    mp.param["pre_filter_start"]
+                    - 10
+                    - input_high_end.shape[1] : mp.param["pre_filter_start"]
+                    - 10,
+                    :,
+                ]
+            ),
+            1,
+        )
+        mi = np.multiply(mirror, input_high_end * 1.7)
+
+        return np.where(np.abs(input_high_end) <= np.abs(mi), input_high_end, mi)
+
+
+def ensembling(a, specs):
+    for i in range(1, len(specs)):
+        if i == 1:
+            spec = specs[0]
+
+        ln = min([spec.shape[2], specs[i].shape[2]])
+        spec = spec[:, :, :ln]
+        specs[i] = specs[i][:, :, :ln]
+
+        if "min_mag" == a:
+            spec = np.where(np.abs(specs[i]) <= np.abs(spec), specs[i], spec)
+        if "max_mag" == a:
+            spec = np.where(np.abs(specs[i]) >= np.abs(spec), specs[i], spec)
+
+    return spec
+
+
+def stft(wave, nfft, hl):
+    wave_left = np.asfortranarray(wave[0])
+    wave_right = np.asfortranarray(wave[1])
+    spec_left = librosa.stft(wave_left, nfft, hop_length=hl)
+    spec_right = librosa.stft(wave_right, nfft, hop_length=hl)
+    spec = np.asfortranarray([spec_left, spec_right])
+
+    return spec
+
+
+def istft(spec, hl):
+    spec_left = np.asfortranarray(spec[0])
+    spec_right = np.asfortranarray(spec[1])
+
+    wave_left = librosa.istft(spec_left, hop_length=hl)
+    wave_right = librosa.istft(spec_right, hop_length=hl)
+    wave = np.asfortranarray([wave_left, wave_right])
+
+
+if __name__ == "__main__":
+    import argparse
+    import sys
+    import time
+
+    import cv2
+    from model_param_init import ModelParameters
+
+    p = argparse.ArgumentParser()
+    p.add_argument(
+        "--algorithm",
+        "-a",
+        type=str,
+        choices=["invert", "invert_p", "min_mag", "max_mag", "deep", "align"],
+        default="min_mag",
+    )
+    p.add_argument(
+        "--model_params",
+        "-m",
+        type=str,
+        default=os.path.join("modelparams", "1band_sr44100_hl512.json"),
+    )
+    p.add_argument("--output_name", "-o", type=str, default="output")
+    p.add_argument("--vocals_only", "-v", action="store_true")
+    p.add_argument("input", nargs="+")
+    args = p.parse_args()
+
+    start_time = time.time()
+
+    if args.algorithm.startswith("invert") and len(args.input) != 2:
+        raise ValueError("There should be two input files.")
+
+    if not args.algorithm.startswith("invert") and len(args.input) < 2:
+        raise ValueError("There must be at least two input files.")
+
+    wave, specs = {}, {}
+    mp = ModelParameters(args.model_params)
+
+    for i in range(len(args.input)):
+        spec = {}
+
+        for d in range(len(mp.param["band"]), 0, -1):
+            bp = mp.param["band"][d]
+
+            if d == len(mp.param["band"]):  # high-end band
+                wave[d], _ = librosa.load(
+                    args.input[i],
+                    bp["sr"],
+                    False,
+                    dtype=np.float32,
+                    res_type=bp["res_type"],
+                )
+
+                if len(wave[d].shape) == 1:  # mono to stereo
+                    wave[d] = np.array([wave[d], wave[d]])
+            else:  # lower bands
+                wave[d] = librosa.resample(
+                    wave[d + 1],
+                    mp.param["band"][d + 1]["sr"],
+                    bp["sr"],
+                    res_type=bp["res_type"],
+                )
+
+            spec[d] = wave_to_spectrogram(
+                wave[d],
+                bp["hl"],
+                bp["n_fft"],
+                mp.param["mid_side"],
+                mp.param["mid_side_b2"],
+                mp.param["reverse"],
+            )
+
+        specs[i] = combine_spectrograms(spec, mp)
+
+    del wave
+
+    if args.algorithm == "deep":
+        d_spec = np.where(np.abs(specs[0]) <= np.abs(spec[1]), specs[0], spec[1])
+        v_spec = d_spec - specs[1]
+        sf.write(
+            os.path.join("{}.wav".format(args.output_name)),
+            cmb_spectrogram_to_wave(v_spec, mp),
+            mp.param["sr"],
+        )
+
+    if args.algorithm.startswith("invert"):
+        ln = min([specs[0].shape[2], specs[1].shape[2]])
+        specs[0] = specs[0][:, :, :ln]
+        specs[1] = specs[1][:, :, :ln]
+
+        if "invert_p" == args.algorithm:
+            X_mag = np.abs(specs[0])
+            y_mag = np.abs(specs[1])
+            max_mag = np.where(X_mag >= y_mag, X_mag, y_mag)
+            v_spec = specs[1] - max_mag * np.exp(1.0j * np.angle(specs[0]))
+        else:
+            specs[1] = reduce_vocal_aggressively(specs[0], specs[1], 0.2)
+            v_spec = specs[0] - specs[1]
+
+            if not args.vocals_only:
+                X_mag = np.abs(specs[0])
+                y_mag = np.abs(specs[1])
+                v_mag = np.abs(v_spec)
+
+                X_image = spectrogram_to_image(X_mag)
+                y_image = spectrogram_to_image(y_mag)
+                v_image = spectrogram_to_image(v_mag)
+
+                cv2.imwrite("{}_X.png".format(args.output_name), X_image)
+                cv2.imwrite("{}_y.png".format(args.output_name), y_image)
+                cv2.imwrite("{}_v.png".format(args.output_name), v_image)
+
+                sf.write(
+                    "{}_X.wav".format(args.output_name),
+                    cmb_spectrogram_to_wave(specs[0], mp),
+                    mp.param["sr"],
+                )
+                sf.write(
+                    "{}_y.wav".format(args.output_name),
+                    cmb_spectrogram_to_wave(specs[1], mp),
+                    mp.param["sr"],
+                )
+
+        sf.write(
+            "{}_v.wav".format(args.output_name),
+            cmb_spectrogram_to_wave(v_spec, mp),
+            mp.param["sr"],
+        )
+    else:
+        if not args.algorithm == "deep":
+            sf.write(
+                os.path.join("ensembled", "{}.wav".format(args.output_name)),
+                cmb_spectrogram_to_wave(ensembling(args.algorithm, specs), mp),
+                mp.param["sr"],
+            )
+
+    if args.algorithm == "align":
+        trackalignment = [
+            {
+                "file1": '"{}"'.format(args.input[0]),
+                "file2": '"{}"'.format(args.input[1]),
+            }
+        ]
+
+        for i, e in tqdm(enumerate(trackalignment), desc="Performing Alignment..."):
+            os.system(f"python lib/align_tracks.py {e['file1']} {e['file2']}")
+
+    # print('Total time: {0:.{1}f}s'.format(time.time() - start_time, 1))
diff --git a/infer/lib/uvr5_pack/name_params.json b/infer/lib/uvr5_pack/name_params.json
new file mode 100644
index 0000000000000000000000000000000000000000..8ed51a68370607a7a8693b99cfb35fc5d92b04af
--- /dev/null
+++ b/infer/lib/uvr5_pack/name_params.json
@@ -0,0 +1,263 @@
+{
+    "equivalent" : [
+        {
+            "model_hash_name" : [
+                {
+                    "hash_name": "47939caf0cfe52a0e81442b85b971dfd",
+                    "model_params": "infer/lib/uvr5_pack/lib_v5/modelparams/4band_44100.json",
+                    "param_name": "4band_44100"
+                },
+                {
+                    "hash_name": "4e4ecb9764c50a8c414fee6e10395bbe",
+                    "model_params": "infer/lib/uvr5_pack/lib_v5/modelparams/4band_v2.json",
+                    "param_name": "4band_v2"
+                },
+                {
+                    "hash_name": "ca106edd563e034bde0bdec4bb7a4b36",
+                    "model_params": "infer/lib/uvr5_pack/lib_v5/modelparams/4band_v2.json",
+                    "param_name": "4band_v2"
+                },
+                {
+                    "hash_name": "e60a1e84803ce4efc0a6551206cc4b71",
+                    "model_params": "infer/lib/uvr5_pack/lib_v5/modelparams/4band_44100.json",
+                    "param_name": "4band_44100"
+                },
+                {
+                    "hash_name": "a82f14e75892e55e994376edbf0c8435",
+                    "model_params": "infer/lib/uvr5_pack/lib_v5/modelparams/4band_44100.json",
+                    "param_name": "4band_44100"
+                },
+                {
+                    "hash_name": "6dd9eaa6f0420af9f1d403aaafa4cc06",
+                    "model_params": "infer/lib/uvr5_pack/lib_v5/modelparams/4band_v2_sn.json",
+                    "param_name": "4band_v2_sn"
+                },
+                {
+                    "hash_name": "08611fb99bd59eaa79ad27c58d137727",
+                    "model_params": "infer/lib/uvr5_pack/lib_v5/modelparams/4band_v2_sn.json",
+                    "param_name": "4band_v2_sn"
+                },
+                {
+                    "hash_name": "5c7bbca45a187e81abbbd351606164e5",
+                    "model_params": "infer/lib/uvr5_pack/lib_v5/modelparams/3band_44100_msb2.json",
+                    "param_name": "3band_44100_msb2"
+                },
+                {
+                    "hash_name": "d6b2cb685a058a091e5e7098192d3233",
+                    "model_params": "infer/lib/uvr5_pack/lib_v5/modelparams/3band_44100_msb2.json",
+                    "param_name": "3band_44100_msb2"
+                },
+                {
+                    "hash_name": "c1b9f38170a7c90e96f027992eb7c62b",
+                    "model_params": "infer/lib/uvr5_pack/lib_v5/modelparams/4band_44100.json",
+                    "param_name": "4band_44100"
+                },
+                {
+                    "hash_name": "c3448ec923fa0edf3d03a19e633faa53",
+                    "model_params": "infer/lib/uvr5_pack/lib_v5/modelparams/4band_44100.json",
+                    "param_name": "4band_44100"
+                },
+                {
+                    "hash_name": "68aa2c8093d0080704b200d140f59e54",
+                    "model_params": "infer/lib/uvr5_pack/lib_v5/modelparams/3band_44100.json",
+                    "param_name": "3band_44100"
+                },
+                {
+                    "hash_name": "fdc83be5b798e4bd29fe00fe6600e147",
+                    "model_params": "infer/lib/uvr5_pack/lib_v5/modelparams/3band_44100_mid.json",
+                    "param_name": "3band_44100_mid.json"
+                },
+                {
+                    "hash_name": "2ce34bc92fd57f55db16b7a4def3d745",
+                    "model_params": "infer/lib/uvr5_pack/lib_v5/modelparams/3band_44100_mid.json",
+                    "param_name": "3band_44100_mid.json"
+                },
+                {
+                    "hash_name": "52fdca89576f06cf4340b74a4730ee5f",
+                    "model_params": "infer/lib/uvr5_pack/lib_v5/modelparams/4band_44100.json",
+                    "param_name": "4band_44100.json"
+                },
+                {
+                    "hash_name": "41191165b05d38fc77f072fa9e8e8a30",
+                    "model_params": "infer/lib/uvr5_pack/lib_v5/modelparams/4band_44100.json",
+                    "param_name": "4band_44100.json"
+                },
+                {
+                    "hash_name": "89e83b511ad474592689e562d5b1f80e",
+                    "model_params": "infer/lib/uvr5_pack/lib_v5/modelparams/2band_32000.json",
+                    "param_name": "2band_32000.json"
+                },
+                {
+                    "hash_name": "0b954da81d453b716b114d6d7c95177f",
+                    "model_params": "infer/lib/uvr5_pack/lib_v5/modelparams/2band_32000.json",
+                    "param_name": "2band_32000.json"
+                }
+
+            ],
+            "v4 Models": [
+                {
+                    "hash_name": "6a00461c51c2920fd68937d4609ed6c8",
+                    "model_params": "infer/lib/uvr5_pack/lib_v5/modelparams/1band_sr16000_hl512.json",
+                    "param_name": "1band_sr16000_hl512"
+                },
+                {
+                    "hash_name": "0ab504864d20f1bd378fe9c81ef37140",
+                    "model_params": "infer/lib/uvr5_pack/lib_v5/modelparams/1band_sr32000_hl512.json",
+                    "param_name": "1band_sr32000_hl512"
+                },
+                {
+                    "hash_name": "7dd21065bf91c10f7fccb57d7d83b07f",
+                    "model_params": "infer/lib/uvr5_pack/lib_v5/modelparams/1band_sr32000_hl512.json",
+                    "param_name": "1band_sr32000_hl512"
+                },
+                {
+                    "hash_name": "80ab74d65e515caa3622728d2de07d23",
+                    "model_params": "infer/lib/uvr5_pack/lib_v5/modelparams/1band_sr32000_hl512.json",
+                    "param_name": "1band_sr32000_hl512"
+                },
+                {
+                    "hash_name": "edc115e7fc523245062200c00caa847f",
+                    "model_params": "infer/lib/uvr5_pack/lib_v5/modelparams/1band_sr33075_hl384.json",
+                    "param_name": "1band_sr33075_hl384"
+                },
+                {
+                    "hash_name": "28063e9f6ab5b341c5f6d3c67f2045b7",
+                    "model_params": "infer/lib/uvr5_pack/lib_v5/modelparams/1band_sr33075_hl384.json",
+                    "param_name": "1band_sr33075_hl384"
+                },
+                {
+                    "hash_name": "b58090534c52cbc3e9b5104bad666ef2",
+                    "model_params": "infer/lib/uvr5_pack/lib_v5/modelparams/1band_sr44100_hl512.json",
+                    "param_name": "1band_sr44100_hl512"
+                },
+                {
+                    "hash_name": "0cdab9947f1b0928705f518f3c78ea8f",
+                    "model_params": "infer/lib/uvr5_pack/lib_v5/modelparams/1band_sr44100_hl512.json",
+                    "param_name": "1band_sr44100_hl512"
+                },
+                {
+                    "hash_name": "ae702fed0238afb5346db8356fe25f13",
+                    "model_params": "infer/lib/uvr5_pack/lib_v5/modelparams/1band_sr44100_hl1024.json",
+                    "param_name": "1band_sr44100_hl1024"
+                }
+            ]
+        }
+    ],
+    "User Models" : [
+        {
+            "1 Band": [
+                {
+                    "hash_name": "1band_sr16000_hl512",
+                    "model_params": "infer/lib/uvr5_pack/lib_v5/modelparams/1band_sr16000_hl512.json",
+                    "param_name": "1band_sr16000_hl512"
+                },
+                {
+                    "hash_name": "1band_sr32000_hl512",
+                    "model_params": "infer/lib/uvr5_pack/lib_v5/modelparams/1band_sr32000_hl512.json",
+                    "param_name": "1band_sr16000_hl512"
+                },
+                {
+                    "hash_name": "1band_sr33075_hl384",
+                    "model_params": "infer/lib/uvr5_pack/lib_v5/modelparams/1band_sr33075_hl384.json",
+                    "param_name": "1band_sr33075_hl384"
+                },
+                {
+                    "hash_name": "1band_sr44100_hl256",
+                    "model_params": "infer/lib/uvr5_pack/lib_v5/modelparams/1band_sr44100_hl256.json",
+                    "param_name": "1band_sr44100_hl256"
+                },
+                {
+                    "hash_name": "1band_sr44100_hl512",
+                    "model_params": "infer/lib/uvr5_pack/lib_v5/modelparams/1band_sr44100_hl512.json",
+                    "param_name": "1band_sr44100_hl512"
+                },
+                {
+                    "hash_name": "1band_sr44100_hl1024",
+                    "model_params": "infer/lib/uvr5_pack/lib_v5/modelparams/1band_sr44100_hl1024.json",
+                    "param_name": "1band_sr44100_hl1024"
+                }
+            ],
+            "2 Band": [
+                {
+                    "hash_name": "2band_44100_lofi",
+                    "model_params": "infer/lib/uvr5_pack/lib_v5/modelparams/2band_44100_lofi.json",
+                    "param_name": "2band_44100_lofi"
+                },
+                {
+                    "hash_name": "2band_32000",
+                    "model_params": "infer/lib/uvr5_pack/lib_v5/modelparams/2band_32000.json",
+                    "param_name": "2band_32000"
+                },
+                {
+                    "hash_name": "2band_48000",
+                    "model_params": "infer/lib/uvr5_pack/lib_v5/modelparams/2band_48000.json",
+                    "param_name": "2band_48000"
+                }
+            ],
+            "3 Band": [
+                {
+                    "hash_name": "3band_44100",
+                    "model_params": "infer/lib/uvr5_pack/lib_v5/modelparams/3band_44100.json",
+                    "param_name": "3band_44100"
+                },
+                {
+                    "hash_name": "3band_44100_mid",
+                    "model_params": "infer/lib/uvr5_pack/lib_v5/modelparams/3band_44100_mid.json",
+                    "param_name": "3band_44100_mid"
+                },
+                {
+                    "hash_name": "3band_44100_msb2",
+                    "model_params": "infer/lib/uvr5_pack/lib_v5/modelparams/3band_44100_msb2.json",
+                    "param_name": "3band_44100_msb2"
+                }
+            ],
+            "4 Band": [
+                {
+                    "hash_name": "4band_44100",
+                    "model_params": "infer/lib/uvr5_pack/lib_v5/modelparams/4band_44100.json",
+                    "param_name": "4band_44100"
+                },
+                {
+                    "hash_name": "4band_44100_mid",
+                    "model_params": "infer/lib/uvr5_pack/lib_v5/modelparams/4band_44100_mid.json",
+                    "param_name": "4band_44100_mid"
+                },
+                {
+                    "hash_name": "4band_44100_msb",
+                    "model_params": "infer/lib/uvr5_pack/lib_v5/modelparams/4band_44100_msb.json",
+                    "param_name": "4band_44100_msb"
+                },
+                {
+                    "hash_name": "4band_44100_msb2",
+                    "model_params": "infer/lib/uvr5_pack/lib_v5/modelparams/4band_44100_msb2.json",
+                    "param_name": "4band_44100_msb2"
+                },
+                {
+                    "hash_name": "4band_44100_reverse",
+                    "model_params": "infer/lib/uvr5_pack/lib_v5/modelparams/4band_44100_reverse.json",
+                    "param_name": "4band_44100_reverse"
+                },
+                {
+                    "hash_name": "4band_44100_sw",
+                    "model_params": "infer/lib/uvr5_pack/lib_v5/modelparams/4band_44100_sw.json",
+                    "param_name": "4band_44100_sw"
+                },
+                {
+                    "hash_name": "4band_v2",
+                    "model_params": "infer/lib/uvr5_pack/lib_v5/modelparams/4band_v2.json",
+                    "param_name": "4band_v2"
+                },
+                {
+                    "hash_name": "4band_v2_sn",
+                    "model_params": "infer/lib/uvr5_pack/lib_v5/modelparams/4band_v2_sn.json",
+                    "param_name": "4band_v2_sn"
+                },
+                {
+                    "hash_name": "tmodelparam",
+                    "model_params": "infer/lib/uvr5_pack/lib_v5/modelparams/tmodelparam.json",
+                    "param_name": "User Model Param Set"
+                }
+            ]
+        }
+    ]
+}
\ No newline at end of file
diff --git a/infer/lib/uvr5_pack/utils.py b/infer/lib/uvr5_pack/utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..f4805cdb25e7c50611412a19340ad525d1251d7b
--- /dev/null
+++ b/infer/lib/uvr5_pack/utils.py
@@ -0,0 +1,121 @@
+import json
+
+import numpy as np
+import torch
+from tqdm import tqdm
+
+
+def load_data(file_name: str = "./infer/lib/uvr5_pack/name_params.json") -> dict:
+    with open(file_name, "r") as f:
+        data = json.load(f)
+
+    return data
+
+
+def make_padding(width, cropsize, offset):
+    left = offset
+    roi_size = cropsize - left * 2
+    if roi_size == 0:
+        roi_size = cropsize
+    right = roi_size - (width % roi_size) + left
+
+    return left, right, roi_size
+
+
+def inference(X_spec, device, model, aggressiveness, data):
+    """
+    data ： dic configs
+    """
+
+    def _execute(
+        X_mag_pad, roi_size, n_window, device, model, aggressiveness, is_half=True
+    ):
+        model.eval()
+        with torch.no_grad():
+            preds = []
+
+            iterations = [n_window]
+
+            total_iterations = sum(iterations)
+            for i in tqdm(range(n_window)):
+                start = i * roi_size
+                X_mag_window = X_mag_pad[
+                    None, :, :, start : start + data["window_size"]
+                ]
+                X_mag_window = torch.from_numpy(X_mag_window)
+                if is_half:
+                    X_mag_window = X_mag_window.half()
+                X_mag_window = X_mag_window.to(device)
+
+                pred = model.predict(X_mag_window, aggressiveness)
+
+                pred = pred.detach().cpu().numpy()
+                preds.append(pred[0])
+
+            pred = np.concatenate(preds, axis=2)
+        return pred
+
+    def preprocess(X_spec):
+        X_mag = np.abs(X_spec)
+        X_phase = np.angle(X_spec)
+
+        return X_mag, X_phase
+
+    X_mag, X_phase = preprocess(X_spec)
+
+    coef = X_mag.max()
+    X_mag_pre = X_mag / coef
+
+    n_frame = X_mag_pre.shape[2]
+    pad_l, pad_r, roi_size = make_padding(n_frame, data["window_size"], model.offset)
+    n_window = int(np.ceil(n_frame / roi_size))
+
+    X_mag_pad = np.pad(X_mag_pre, ((0, 0), (0, 0), (pad_l, pad_r)), mode="constant")
+
+    if list(model.state_dict().values())[0].dtype == torch.float16:
+        is_half = True
+    else:
+        is_half = False
+    pred = _execute(
+        X_mag_pad, roi_size, n_window, device, model, aggressiveness, is_half
+    )
+    pred = pred[:, :, :n_frame]
+
+    if data["tta"]:
+        pad_l += roi_size // 2
+        pad_r += roi_size // 2
+        n_window += 1
+
+        X_mag_pad = np.pad(X_mag_pre, ((0, 0), (0, 0), (pad_l, pad_r)), mode="constant")
+
+        pred_tta = _execute(
+            X_mag_pad, roi_size, n_window, device, model, aggressiveness, is_half
+        )
+        pred_tta = pred_tta[:, :, roi_size // 2 :]
+        pred_tta = pred_tta[:, :, :n_frame]
+
+        return (pred + pred_tta) * 0.5 * coef, X_mag, np.exp(1.0j * X_phase)
+    else:
+        return pred * coef, X_mag, np.exp(1.0j * X_phase)
+
+
+def _get_name_params(model_path, model_hash):
+    data = load_data()
+    flag = False
+    ModelName = model_path
+    for type in list(data):
+        for model in list(data[type][0]):
+            for i in range(len(data[type][0][model])):
+                if str(data[type][0][model][i]["hash_name"]) == model_hash:
+                    flag = True
+                elif str(data[type][0][model][i]["hash_name"]) in ModelName:
+                    flag = True
+
+                if flag:
+                    model_params_auto = data[type][0][model][i]["model_params"]
+                    param_name_auto = data[type][0][model][i]["param_name"]
+                    if type == "equivalent":
+                        return param_name_auto, model_params_auto
+                    else:
+                        flag = False
+    return param_name_auto, model_params_auto
diff --git a/infer/modules/ipex/__init__.py.py b/infer/modules/ipex/__init__.py.py
new file mode 100644
index 0000000000000000000000000000000000000000..9f53b2d3f7025b2d71369dababa4e6f2a4affc48
--- /dev/null
+++ b/infer/modules/ipex/__init__.py.py
@@ -0,0 +1,165 @@
+import os
+import sys
+import contextlib
+import torch
+import intel_extension_for_pytorch as ipex # pylint: disable=import-error, unused-import
+from .hijacks import ipex_hijacks
+from .attention import attention_init
+
+# pylint: disable=protected-access, missing-function-docstring, line-too-long
+
+def ipex_init(): # pylint: disable=too-many-statements
+    try:
+        #Replace cuda with xpu:
+        torch.cuda.current_device = torch.xpu.current_device
+        torch.cuda.current_stream = torch.xpu.current_stream
+        torch.cuda.device = torch.xpu.device
+        torch.cuda.device_count = torch.xpu.device_count
+        torch.cuda.device_of = torch.xpu.device_of
+        torch.cuda.getDeviceIdListForCard = torch.xpu.getDeviceIdListForCard
+        torch.cuda.get_device_name = torch.xpu.get_device_name
+        torch.cuda.get_device_properties = torch.xpu.get_device_properties
+        torch.cuda.init = torch.xpu.init
+        torch.cuda.is_available = torch.xpu.is_available
+        torch.cuda.is_initialized = torch.xpu.is_initialized
+        torch.cuda.is_current_stream_capturing = lambda: False
+        torch.cuda.set_device = torch.xpu.set_device
+        torch.cuda.stream = torch.xpu.stream
+        torch.cuda.synchronize = torch.xpu.synchronize
+        torch.cuda.Event = torch.xpu.Event
+        torch.cuda.Stream = torch.xpu.Stream
+        torch.cuda.FloatTensor = torch.xpu.FloatTensor
+        torch.Tensor.cuda = torch.Tensor.xpu
+        torch.Tensor.is_cuda = torch.Tensor.is_xpu
+        torch.cuda._initialization_lock = torch.xpu.lazy_init._initialization_lock
+        torch.cuda._initialized = torch.xpu.lazy_init._initialized
+        torch.cuda._lazy_seed_tracker = torch.xpu.lazy_init._lazy_seed_tracker
+        torch.cuda._queued_calls = torch.xpu.lazy_init._queued_calls
+        torch.cuda._tls = torch.xpu.lazy_init._tls
+        torch.cuda.threading = torch.xpu.lazy_init.threading
+        torch.cuda.traceback = torch.xpu.lazy_init.traceback
+        torch.cuda.Optional = torch.xpu.Optional
+        torch.cuda.__cached__ = torch.xpu.__cached__
+        torch.cuda.__loader__ = torch.xpu.__loader__
+        torch.cuda.ComplexFloatStorage = torch.xpu.ComplexFloatStorage
+        torch.cuda.Tuple = torch.xpu.Tuple
+        torch.cuda.streams = torch.xpu.streams
+        torch.cuda._lazy_new = torch.xpu._lazy_new
+        torch.cuda.FloatStorage = torch.xpu.FloatStorage
+        torch.cuda.Any = torch.xpu.Any
+        torch.cuda.__doc__ = torch.xpu.__doc__
+        torch.cuda.default_generators = torch.xpu.default_generators
+        torch.cuda.HalfTensor = torch.xpu.HalfTensor
+        torch.cuda._get_device_index = torch.xpu._get_device_index
+        torch.cuda.__path__ = torch.xpu.__path__
+        torch.cuda.Device = torch.xpu.Device
+        torch.cuda.IntTensor = torch.xpu.IntTensor
+        torch.cuda.ByteStorage = torch.xpu.ByteStorage
+        torch.cuda.set_stream = torch.xpu.set_stream
+        torch.cuda.BoolStorage = torch.xpu.BoolStorage
+        torch.cuda.os = torch.xpu.os
+        torch.cuda.torch = torch.xpu.torch
+        torch.cuda.BFloat16Storage = torch.xpu.BFloat16Storage
+        torch.cuda.Union = torch.xpu.Union
+        torch.cuda.DoubleTensor = torch.xpu.DoubleTensor
+        torch.cuda.ShortTensor = torch.xpu.ShortTensor
+        torch.cuda.LongTensor = torch.xpu.LongTensor
+        torch.cuda.IntStorage = torch.xpu.IntStorage
+        torch.cuda.LongStorage = torch.xpu.LongStorage
+        torch.cuda.__annotations__ = torch.xpu.__annotations__
+        torch.cuda.__package__ = torch.xpu.__package__
+        torch.cuda.__builtins__ = torch.xpu.__builtins__
+        torch.cuda.CharTensor = torch.xpu.CharTensor
+        torch.cuda.List = torch.xpu.List
+        torch.cuda._lazy_init = torch.xpu._lazy_init
+        torch.cuda.BFloat16Tensor = torch.xpu.BFloat16Tensor
+        torch.cuda.DoubleStorage = torch.xpu.DoubleStorage
+        torch.cuda.ByteTensor = torch.xpu.ByteTensor
+        torch.cuda.StreamContext = torch.xpu.StreamContext
+        torch.cuda.ComplexDoubleStorage = torch.xpu.ComplexDoubleStorage
+        torch.cuda.ShortStorage = torch.xpu.ShortStorage
+        torch.cuda._lazy_call = torch.xpu._lazy_call
+        torch.cuda.HalfStorage = torch.xpu.HalfStorage
+        torch.cuda.random = torch.xpu.random
+        torch.cuda._device = torch.xpu._device
+        torch.cuda.classproperty = torch.xpu.classproperty
+        torch.cuda.__name__ = torch.xpu.__name__
+        torch.cuda._device_t = torch.xpu._device_t
+        torch.cuda.warnings = torch.xpu.warnings
+        torch.cuda.__spec__ = torch.xpu.__spec__
+        torch.cuda.BoolTensor = torch.xpu.BoolTensor
+        torch.cuda.CharStorage = torch.xpu.CharStorage
+        torch.cuda.__file__ = torch.xpu.__file__
+        torch.cuda._is_in_bad_fork = torch.xpu.lazy_init._is_in_bad_fork
+        #torch.cuda.is_current_stream_capturing = torch.xpu.is_current_stream_capturing
+
+        #Memory:
+        torch.cuda.memory = torch.xpu.memory
+        if 'linux' in sys.platform and "WSL2" in os.popen("uname -a").read():
+            torch.xpu.empty_cache = lambda: None
+        torch.cuda.empty_cache = torch.xpu.empty_cache
+        torch.cuda.memory_stats = torch.xpu.memory_stats
+        torch.cuda.memory_summary = torch.xpu.memory_summary
+        torch.cuda.memory_snapshot = torch.xpu.memory_snapshot
+        torch.cuda.memory_allocated = torch.xpu.memory_allocated
+        torch.cuda.max_memory_allocated = torch.xpu.max_memory_allocated
+        torch.cuda.memory_reserved = torch.xpu.memory_reserved
+        torch.cuda.memory_cached = torch.xpu.memory_reserved
+        torch.cuda.max_memory_reserved = torch.xpu.max_memory_reserved
+        torch.cuda.max_memory_cached = torch.xpu.max_memory_reserved
+        torch.cuda.reset_peak_memory_stats = torch.xpu.reset_peak_memory_stats
+        torch.cuda.reset_max_memory_cached = torch.xpu.reset_peak_memory_stats
+        torch.cuda.reset_max_memory_allocated = torch.xpu.reset_peak_memory_stats
+        torch.cuda.memory_stats_as_nested_dict = torch.xpu.memory_stats_as_nested_dict
+        torch.cuda.reset_accumulated_memory_stats = torch.xpu.reset_accumulated_memory_stats
+
+        #RNG:
+        torch.cuda.get_rng_state = torch.xpu.get_rng_state
+        torch.cuda.get_rng_state_all = torch.xpu.get_rng_state_all
+        torch.cuda.set_rng_state = torch.xpu.set_rng_state
+        torch.cuda.set_rng_state_all = torch.xpu.set_rng_state_all
+        torch.cuda.manual_seed = torch.xpu.manual_seed
+        torch.cuda.manual_seed_all = torch.xpu.manual_seed_all
+        torch.cuda.seed = torch.xpu.seed
+        torch.cuda.seed_all = torch.xpu.seed_all
+        torch.cuda.initial_seed = torch.xpu.initial_seed
+
+        #AMP:
+        torch.cuda.amp = torch.xpu.amp
+        if not hasattr(torch.cuda.amp, "common"):
+            torch.cuda.amp.common = contextlib.nullcontext()
+        torch.cuda.amp.common.amp_definitely_not_available = lambda: False
+        try:
+            torch.cuda.amp.GradScaler = torch.xpu.amp.GradScaler
+        except Exception: # pylint: disable=broad-exception-caught
+            try:
+                from .gradscaler import gradscaler_init # pylint: disable=import-outside-toplevel, import-error
+                gradscaler_init()
+                torch.cuda.amp.GradScaler = torch.xpu.amp.GradScaler
+            except Exception: # pylint: disable=broad-exception-caught
+                torch.cuda.amp.GradScaler = ipex.cpu.autocast._grad_scaler.GradScaler
+
+        #C
+        torch._C._cuda_getCurrentRawStream = ipex._C._getCurrentStream
+        ipex._C._DeviceProperties.major = 2023
+        ipex._C._DeviceProperties.minor = 2
+
+        #Fix functions with ipex:
+        torch.cuda.mem_get_info = lambda device=None: [(torch.xpu.get_device_properties(device).total_memory - torch.xpu.memory_allocated(device)), torch.xpu.get_device_properties(device).total_memory]
+        torch._utils._get_available_device_type = lambda: "xpu"
+        torch.has_cuda = True
+        torch.cuda.has_half = True
+        torch.cuda.is_bf16_supported = lambda *args, **kwargs: True
+        torch.cuda.is_fp16_supported = lambda *args, **kwargs: True
+        torch.version.cuda = "11.7"
+        torch.cuda.get_device_capability = lambda *args, **kwargs: [11,7]
+        torch.cuda.get_device_properties.major = 11
+        torch.cuda.get_device_properties.minor = 7
+        torch.cuda.ipc_collect = lambda *args, **kwargs: None
+        torch.cuda.utilization = lambda *args, **kwargs: 0
+
+        ipex_hijacks()
+        attention_init()
+    except Exception as e:
+        return False, e
+    return True, None
\ No newline at end of file
diff --git a/infer/modules/ipex/attention.py b/infer/modules/ipex/attention.py
new file mode 100644
index 0000000000000000000000000000000000000000..0eed59630d76a56e3fd96aa5bb6518b0c61e81bb
--- /dev/null
+++ b/infer/modules/ipex/attention.py
@@ -0,0 +1,128 @@
+import torch
+import intel_extension_for_pytorch as ipex # pylint: disable=import-error, unused-import
+
+# pylint: disable=protected-access, missing-function-docstring, line-too-long
+
+original_torch_bmm = torch.bmm
+def torch_bmm(input, mat2, *, out=None):
+    if input.dtype != mat2.dtype:
+        mat2 = mat2.to(input.dtype)
+
+    #ARC GPUs can't allocate more than 4GB to a single block, Slice it:
+    batch_size_attention, input_tokens, mat2_shape = input.shape[0], input.shape[1], mat2.shape[2]
+    block_multiply = 2.4 if input.dtype == torch.float32 else 1.2
+    block_size = (batch_size_attention * input_tokens * mat2_shape) / 1024 * block_multiply #MB
+    split_slice_size = batch_size_attention
+    if block_size >= 4000:
+        do_split = True
+        #Find something divisible with the input_tokens
+        while ((split_slice_size * input_tokens * mat2_shape) / 1024 * block_multiply) > 4000:
+            split_slice_size = split_slice_size // 2
+            if split_slice_size <= 1:
+                split_slice_size = 1
+                break
+    else:
+        do_split = False
+
+    split_block_size = (split_slice_size * input_tokens * mat2_shape) / 1024 * block_multiply #MB
+    split_2_slice_size = input_tokens
+    if split_block_size >= 4000:
+        do_split_2 = True
+        #Find something divisible with the input_tokens
+        while ((split_slice_size * split_2_slice_size * mat2_shape) / 1024 * block_multiply) > 4000:
+            split_2_slice_size = split_2_slice_size // 2
+            if split_2_slice_size <= 1:
+                split_2_slice_size = 1
+                break
+    else:
+        do_split_2 = False
+
+    if do_split:
+        hidden_states = torch.zeros(input.shape[0], input.shape[1], mat2.shape[2], device=input.device, dtype=input.dtype)
+        for i in range(batch_size_attention // split_slice_size):
+            start_idx = i * split_slice_size
+            end_idx = (i + 1) * split_slice_size
+            if do_split_2:
+                for i2 in range(input_tokens // split_2_slice_size): # pylint: disable=invalid-name
+                    start_idx_2 = i2 * split_2_slice_size
+                    end_idx_2 = (i2 + 1) * split_2_slice_size
+                    hidden_states[start_idx:end_idx, start_idx_2:end_idx_2] = original_torch_bmm(
+                        input[start_idx:end_idx, start_idx_2:end_idx_2],
+                        mat2[start_idx:end_idx, start_idx_2:end_idx_2],
+                        out=out
+                    )
+            else:
+                hidden_states[start_idx:end_idx] = original_torch_bmm(
+                    input[start_idx:end_idx],
+                    mat2[start_idx:end_idx],
+                    out=out
+                )
+    else:
+        return original_torch_bmm(input, mat2, out=out)
+    return hidden_states
+
+original_scaled_dot_product_attention = torch.nn.functional.scaled_dot_product_attention
+def scaled_dot_product_attention(query, key, value, attn_mask=None, dropout_p=0.0, is_causal=False):
+    #ARC GPUs can't allocate more than 4GB to a single block, Slice it:
+    shape_one, batch_size_attention, query_tokens, shape_four = query.shape
+    block_multiply = 2.4 if query.dtype == torch.float32 else 1.2
+    block_size = (shape_one * batch_size_attention * query_tokens * shape_four) / 1024 * block_multiply #MB
+    split_slice_size = batch_size_attention
+    if block_size >= 4000:
+        do_split = True
+        #Find something divisible with the shape_one
+        while ((shape_one * split_slice_size * query_tokens * shape_four) / 1024 * block_multiply) > 4000:
+            split_slice_size = split_slice_size // 2
+            if split_slice_size <= 1:
+                split_slice_size = 1
+                break
+    else:
+        do_split = False
+
+    split_block_size = (shape_one * split_slice_size * query_tokens * shape_four) / 1024 * block_multiply #MB
+    split_2_slice_size = query_tokens
+    if split_block_size >= 4000:
+        do_split_2 = True
+        #Find something divisible with the batch_size_attention
+        while ((shape_one * split_slice_size * split_2_slice_size * shape_four) / 1024 * block_multiply) > 4000:
+            split_2_slice_size = split_2_slice_size // 2
+            if split_2_slice_size <= 1:
+                split_2_slice_size = 1
+                break
+    else:
+        do_split_2 = False
+
+    if do_split:
+        hidden_states = torch.zeros(query.shape, device=query.device, dtype=query.dtype)
+        for i in range(batch_size_attention // split_slice_size):
+            start_idx = i * split_slice_size
+            end_idx = (i + 1) * split_slice_size
+            if do_split_2:
+                for i2 in range(query_tokens // split_2_slice_size): # pylint: disable=invalid-name
+                    start_idx_2 = i2 * split_2_slice_size
+                    end_idx_2 = (i2 + 1) * split_2_slice_size
+                    hidden_states[:, start_idx:end_idx, start_idx_2:end_idx_2] = original_scaled_dot_product_attention(
+                        query[:, start_idx:end_idx, start_idx_2:end_idx_2],
+                        key[:, start_idx:end_idx, start_idx_2:end_idx_2],
+                        value[:, start_idx:end_idx, start_idx_2:end_idx_2],
+                        attn_mask=attn_mask[:, start_idx:end_idx, start_idx_2:end_idx_2] if attn_mask is not None else attn_mask,
+                        dropout_p=dropout_p, is_causal=is_causal
+                    )
+            else:
+                hidden_states[:, start_idx:end_idx] = original_scaled_dot_product_attention(
+                    query[:, start_idx:end_idx],
+                    key[:, start_idx:end_idx],
+                    value[:, start_idx:end_idx],
+                    attn_mask=attn_mask[:, start_idx:end_idx] if attn_mask is not None else attn_mask,
+                    dropout_p=dropout_p, is_causal=is_causal
+                )
+    else:
+        return original_scaled_dot_product_attention(
+            query, key, value, attn_mask=attn_mask, dropout_p=dropout_p, is_causal=is_causal
+        )
+    return hidden_states
+
+def attention_init():
+    #ARC GPUs can't allocate more than 4GB to a single block:
+    torch.bmm = torch_bmm
+    torch.nn.functional.scaled_dot_product_attention = scaled_dot_product_attention
\ No newline at end of file
diff --git a/infer/modules/ipex/gradscaler.py b/infer/modules/ipex/gradscaler.py
new file mode 100644
index 0000000000000000000000000000000000000000..3c265ddb37453f02870afb481360c9cc30b05d81
--- /dev/null
+++ b/infer/modules/ipex/gradscaler.py
@@ -0,0 +1,179 @@
+from collections import defaultdict
+import torch
+import intel_extension_for_pytorch as ipex # pylint: disable=import-error, unused-import
+import intel_extension_for_pytorch._C as core # pylint: disable=import-error, unused-import
+
+# pylint: disable=protected-access, missing-function-docstring, line-too-long
+
+OptState = ipex.cpu.autocast._grad_scaler.OptState
+_MultiDeviceReplicator = ipex.cpu.autocast._grad_scaler._MultiDeviceReplicator
+_refresh_per_optimizer_state = ipex.cpu.autocast._grad_scaler._refresh_per_optimizer_state
+
+def _unscale_grads_(self, optimizer, inv_scale, found_inf, allow_fp16): # pylint: disable=unused-argument
+    per_device_inv_scale = _MultiDeviceReplicator(inv_scale)
+    per_device_found_inf = _MultiDeviceReplicator(found_inf)
+
+    # To set up _amp_foreach_non_finite_check_and_unscale_, split grads by device and dtype.
+    # There could be hundreds of grads, so we'd like to iterate through them just once.
+    # However, we don't know their devices or dtypes in advance.
+
+    # https://stackoverflow.com/questions/5029934/defaultdict-of-defaultdict
+    # Google says mypy struggles with defaultdicts type annotations.
+    per_device_and_dtype_grads = defaultdict(lambda: defaultdict(list))  # type: ignore[var-annotated]
+    # sync grad to master weight
+    if hasattr(optimizer, "sync_grad"):
+        optimizer.sync_grad()
+    with torch.no_grad():
+        for group in optimizer.param_groups:
+            for param in group["params"]:
+                if param.grad is None:
+                    continue
+                if (not allow_fp16) and param.grad.dtype == torch.float16:
+                    raise ValueError("Attempting to unscale FP16 gradients.")
+                if param.grad.is_sparse:
+                    # is_coalesced() == False means the sparse grad has values with duplicate indices.
+                    # coalesce() deduplicates indices and adds all values that have the same index.
+                    # For scaled fp16 values, there's a good chance coalescing will cause overflow,
+                    # so we should check the coalesced _values().
+                    if param.grad.dtype is torch.float16:
+                        param.grad = param.grad.coalesce()
+                    to_unscale = param.grad._values()
+                else:
+                    to_unscale = param.grad
+
+                # -: is there a way to split by device and dtype without appending in the inner loop?
+                to_unscale = to_unscale.to("cpu")
+                per_device_and_dtype_grads[to_unscale.device][
+                    to_unscale.dtype
+                ].append(to_unscale)
+
+        for _, per_dtype_grads in per_device_and_dtype_grads.items():
+            for grads in per_dtype_grads.values():
+                core._amp_foreach_non_finite_check_and_unscale_(
+                    grads,
+                    per_device_found_inf.get("cpu"),
+                    per_device_inv_scale.get("cpu"),
+                )
+
+    return per_device_found_inf._per_device_tensors
+
+def unscale_(self, optimizer):
+    """
+    Divides ("unscales") the optimizer's gradient tensors by the scale factor.
+    :meth:`unscale_` is optional, serving cases where you need to
+    :ref:`modify or inspect gradients<working-with-unscaled-gradients>`
+    between the backward pass(es) and :meth:`step`.
+    If :meth:`unscale_` is not called explicitly,  gradients will be unscaled  automatically during :meth:`step`.
+    Simple example, using :meth:`unscale_` to enable clipping of unscaled gradients::
+        ...
+        scaler.scale(loss).backward()
+        scaler.unscale_(optimizer)
+        torch.nn.utils.clip_grad_norm_(model.parameters(), max_norm)
+        scaler.step(optimizer)
+        scaler.update()
+    Args:
+        optimizer (torch.optim.Optimizer):  Optimizer that owns the gradients to be unscaled.
+    .. warning::
+        :meth:`unscale_` should only be called once per optimizer per :meth:`step` call,
+        and only after all gradients for that optimizer's assigned parameters have been accumulated.
+        Calling :meth:`unscale_` twice for a given optimizer between each :meth:`step` triggers a RuntimeError.
+    .. warning::
+        :meth:`unscale_` may unscale sparse gradients out of place, replacing the ``.grad`` attribute.
+    """
+    if not self._enabled:
+        return
+
+    self._check_scale_growth_tracker("unscale_")
+
+    optimizer_state = self._per_optimizer_states[id(optimizer)]
+
+    if optimizer_state["stage"] is OptState.UNSCALED: # pylint: disable=no-else-raise
+        raise RuntimeError(
+            "unscale_() has already been called on this optimizer since the last update()."
+        )
+    elif optimizer_state["stage"] is OptState.STEPPED:
+        raise RuntimeError("unscale_() is being called after step().")
+
+    # FP32 division can be imprecise for certain compile options, so we carry out the reciprocal in FP64.
+    assert self._scale is not None
+    inv_scale = self._scale.to("cpu").double().reciprocal().float().to(self._scale.device)
+    found_inf = torch.full(
+        (1,), 0.0, dtype=torch.float32, device=self._scale.device
+    )
+
+    optimizer_state["found_inf_per_device"] = self._unscale_grads_(
+        optimizer, inv_scale, found_inf, False
+    )
+    optimizer_state["stage"] = OptState.UNSCALED
+
+def update(self, new_scale=None):
+    """
+    Updates the scale factor.
+    If any optimizer steps were skipped the scale is multiplied by ``backoff_factor``
+    to reduce it. If ``growth_interval`` unskipped iterations occurred consecutively,
+    the scale is multiplied by ``growth_factor`` to increase it.
+    Passing ``new_scale`` sets the new scale value manually. (``new_scale`` is not
+    used directly, it's used to fill GradScaler's internal scale tensor. So if
+    ``new_scale`` was a tensor, later in-place changes to that tensor will not further
+    affect the scale GradScaler uses internally.)
+    Args:
+        new_scale (float or :class:`torch.FloatTensor`, optional, default=None):  New scale factor.
+    .. warning::
+        :meth:`update` should only be called at the end of the iteration, after ``scaler.step(optimizer)`` has
+        been invoked for all optimizers used this iteration.
+    """
+    if not self._enabled:
+        return
+
+    _scale, _growth_tracker = self._check_scale_growth_tracker("update")
+
+    if new_scale is not None:
+        # Accept a new user-defined scale.
+        if isinstance(new_scale, float):
+            self._scale.fill_(new_scale)  # type: ignore[union-attr]
+        else:
+            reason = "new_scale should be a float or a 1-element torch.FloatTensor with requires_grad=False."
+            assert isinstance(new_scale, torch.FloatTensor), reason  # type: ignore[attr-defined]
+            assert new_scale.numel() == 1, reason
+            assert new_scale.requires_grad is False, reason
+            self._scale.copy_(new_scale)  # type: ignore[union-attr]
+    else:
+        # Consume shared inf/nan data collected from optimizers to update the scale.
+        # If all found_inf tensors are on the same device as self._scale, this operation is asynchronous.
+        found_infs = [
+            found_inf.to(device="cpu", non_blocking=True)
+            for state in self._per_optimizer_states.values()
+            for found_inf in state["found_inf_per_device"].values()
+        ]
+
+        assert len(found_infs) > 0, "No inf checks were recorded prior to update."
+
+        found_inf_combined = found_infs[0]
+        if len(found_infs) > 1:
+            for i in range(1, len(found_infs)):
+                found_inf_combined += found_infs[i]
+
+        to_device = _scale.device
+        _scale = _scale.to("cpu")
+        _growth_tracker = _growth_tracker.to("cpu")
+
+        core._amp_update_scale_(
+            _scale,
+            _growth_tracker,
+            found_inf_combined,
+            self._growth_factor,
+            self._backoff_factor,
+            self._growth_interval,
+        )
+
+        _scale = _scale.to(to_device)
+        _growth_tracker = _growth_tracker.to(to_device)
+    # To prepare for next iteration, clear the data collected from optimizers this iteration.
+    self._per_optimizer_states = defaultdict(_refresh_per_optimizer_state)
+
+def gradscaler_init():
+    torch.xpu.amp.GradScaler = ipex.cpu.autocast._grad_scaler.GradScaler
+    torch.xpu.amp.GradScaler._unscale_grads_ = _unscale_grads_
+    torch.xpu.amp.GradScaler.unscale_ = unscale_
+    torch.xpu.amp.GradScaler.update = update
+    return torch.xpu.amp.GradScaler
\ No newline at end of file
diff --git a/infer/modules/ipex/hijacks.py b/infer/modules/ipex/hijacks.py
new file mode 100644
index 0000000000000000000000000000000000000000..b06f3a9c1a70ef515c30d0e7d749923ecb8d0bfe
--- /dev/null
+++ b/infer/modules/ipex/hijacks.py
@@ -0,0 +1,196 @@
+import contextlib
+import importlib
+import torch
+import intel_extension_for_pytorch as ipex # pylint: disable=import-error, unused-import
+
+# pylint: disable=protected-access, missing-function-docstring, line-too-long, unnecessary-lambda, no-else-return
+
+class CondFunc: # pylint: disable=missing-class-docstring
+    def __new__(cls, orig_func, sub_func, cond_func):
+        self = super(CondFunc, cls).__new__(cls)
+        if isinstance(orig_func, str):
+            func_path = orig_func.split('.')
+            for i in range(len(func_path)-1, -1, -1):
+                try:
+                    resolved_obj = importlib.import_module('.'.join(func_path[:i]))
+                    break
+                except ImportError:
+                    pass
+            for attr_name in func_path[i:-1]:
+                resolved_obj = getattr(resolved_obj, attr_name)
+            orig_func = getattr(resolved_obj, func_path[-1])
+            setattr(resolved_obj, func_path[-1], lambda *args, **kwargs: self(*args, **kwargs))
+        self.__init__(orig_func, sub_func, cond_func)
+        return lambda *args, **kwargs: self(*args, **kwargs)
+    def __init__(self, orig_func, sub_func, cond_func):
+        self.__orig_func = orig_func
+        self.__sub_func = sub_func
+        self.__cond_func = cond_func
+    def __call__(self, *args, **kwargs):
+        if not self.__cond_func or self.__cond_func(self.__orig_func, *args, **kwargs):
+            return self.__sub_func(self.__orig_func, *args, **kwargs)
+        else:
+            return self.__orig_func(*args, **kwargs)
+
+_utils = torch.utils.data._utils
+def _shutdown_workers(self):
+    if torch.utils.data._utils is None or torch.utils.data._utils.python_exit_status is True or torch.utils.data._utils.python_exit_status is None:
+        return
+    if hasattr(self, "_shutdown") and not self._shutdown:
+        self._shutdown = True
+        try:
+            if hasattr(self, '_pin_memory_thread'):
+                self._pin_memory_thread_done_event.set()
+                self._worker_result_queue.put((None, None))
+                self._pin_memory_thread.join()
+                self._worker_result_queue.cancel_join_thread()
+                self._worker_result_queue.close()
+            self._workers_done_event.set()
+            for worker_id in range(len(self._workers)):
+                if self._persistent_workers or self._workers_status[worker_id]:
+                    self._mark_worker_as_unavailable(worker_id, shutdown=True)
+            for w in self._workers: # pylint: disable=invalid-name
+                w.join(timeout=torch.utils.data._utils.MP_STATUS_CHECK_INTERVAL)
+            for q in self._index_queues: # pylint: disable=invalid-name
+                q.cancel_join_thread()
+                q.close()
+        finally:
+            if self._worker_pids_set:
+                torch.utils.data._utils.signal_handling._remove_worker_pids(id(self))
+                self._worker_pids_set = False
+            for w in self._workers: # pylint: disable=invalid-name
+                if w.is_alive():
+                    w.terminate()
+
+class DummyDataParallel(torch.nn.Module): # pylint: disable=missing-class-docstring, unused-argument, too-few-public-methods
+    def __new__(cls, module, device_ids=None, output_device=None, dim=0): # pylint: disable=unused-argument
+        if isinstance(device_ids, list) and len(device_ids) > 1:
+            print("IPEX backend doesn't support DataParallel on multiple XPU devices")
+        return module.to("xpu")
+
+def return_null_context(*args, **kwargs): # pylint: disable=unused-argument
+    return contextlib.nullcontext()
+
+def check_device(device):
+    return bool((isinstance(device, torch.device) and device.type == "cuda") or (isinstance(device, str) and "cuda" in device) or isinstance(device, int))
+
+def return_xpu(device):
+    return f"xpu:{device[-1]}" if isinstance(device, str) and ":" in device else f"xpu:{device}" if isinstance(device, int) else torch.device("xpu") if isinstance(device, torch.device) else "xpu"
+
+def ipex_no_cuda(orig_func, *args, **kwargs):
+    torch.cuda.is_available = lambda: False
+    orig_func(*args, **kwargs)
+    torch.cuda.is_available = torch.xpu.is_available
+
+original_autocast = torch.autocast
+def ipex_autocast(*args, **kwargs):
+    if len(args) > 0 and args[0] == "cuda":
+        return original_autocast("xpu", *args[1:], **kwargs)
+    else:
+        return original_autocast(*args, **kwargs)
+
+original_torch_cat = torch.cat
+def torch_cat(tensor, *args, **kwargs):
+    if len(tensor) == 3 and (tensor[0].dtype != tensor[1].dtype or tensor[2].dtype != tensor[1].dtype):
+        return original_torch_cat([tensor[0].to(tensor[1].dtype), tensor[1], tensor[2].to(tensor[1].dtype)], *args, **kwargs)
+    else:
+        return original_torch_cat(tensor, *args, **kwargs)
+
+original_interpolate = torch.nn.functional.interpolate
+def interpolate(tensor, size=None, scale_factor=None, mode='nearest', align_corners=None, recompute_scale_factor=None, antialias=False): # pylint: disable=too-many-arguments
+    if antialias or align_corners is not None:
+        return_device = tensor.device
+        return_dtype = tensor.dtype
+        return original_interpolate(tensor.to("cpu", dtype=torch.float32), size=size, scale_factor=scale_factor, mode=mode,
+        align_corners=align_corners, recompute_scale_factor=recompute_scale_factor, antialias=antialias).to(return_device, dtype=return_dtype)
+    else:
+        return original_interpolate(tensor, size=size, scale_factor=scale_factor, mode=mode,
+        align_corners=align_corners, recompute_scale_factor=recompute_scale_factor, antialias=antialias)
+
+original_linalg_solve = torch.linalg.solve
+def linalg_solve(A, B, *args, **kwargs): # pylint: disable=invalid-name
+    if A.device != torch.device("cpu") or B.device != torch.device("cpu"):
+        return_device = A.device
+        return original_linalg_solve(A.to("cpu"), B.to("cpu"), *args, **kwargs).to(return_device)
+    else:
+        return original_linalg_solve(A, B, *args, **kwargs)
+
+def ipex_hijacks():
+    CondFunc('torch.Tensor.to',
+        lambda orig_func, self, device=None, *args, **kwargs: orig_func(self, return_xpu(device), *args, **kwargs),
+        lambda orig_func, self, device=None, *args, **kwargs: check_device(device))
+    CondFunc('torch.Tensor.cuda',
+        lambda orig_func, self, device=None, *args, **kwargs: orig_func(self, return_xpu(device), *args, **kwargs),
+        lambda orig_func, self, device=None, *args, **kwargs: check_device(device))
+    CondFunc('torch.empty',
+        lambda orig_func, *args, device=None, **kwargs: orig_func(*args, device=return_xpu(device), **kwargs),
+        lambda orig_func, *args, device=None, **kwargs: check_device(device))
+    CondFunc('torch.load',
+        lambda orig_func, *args, map_location=None, **kwargs: orig_func(*args, return_xpu(map_location), **kwargs),
+        lambda orig_func, *args, map_location=None, **kwargs: map_location is None or check_device(map_location))
+    CondFunc('torch.randn',
+        lambda orig_func, *args, device=None, **kwargs: orig_func(*args, device=return_xpu(device), **kwargs),
+        lambda orig_func, *args, device=None, **kwargs: check_device(device))
+    CondFunc('torch.ones',
+        lambda orig_func, *args, device=None, **kwargs: orig_func(*args, device=return_xpu(device), **kwargs),
+        lambda orig_func, *args, device=None, **kwargs: check_device(device))
+    CondFunc('torch.zeros',
+        lambda orig_func, *args, device=None, **kwargs: orig_func(*args, device=return_xpu(device), **kwargs),
+        lambda orig_func, *args, device=None, **kwargs: check_device(device))
+    CondFunc('torch.tensor',
+        lambda orig_func, *args, device=None, **kwargs: orig_func(*args, device=return_xpu(device), **kwargs),
+        lambda orig_func, *args, device=None, **kwargs: check_device(device))
+    CondFunc('torch.linspace',
+        lambda orig_func, *args, device=None, **kwargs: orig_func(*args, device=return_xpu(device), **kwargs),
+        lambda orig_func, *args, device=None, **kwargs: check_device(device))
+
+    CondFunc('torch.Generator',
+        lambda orig_func, device=None: torch.xpu.Generator(device),
+        lambda orig_func, device=None: device is not None and device != torch.device("cpu") and device != "cpu")
+
+    CondFunc('torch.batch_norm',
+        lambda orig_func, input, weight, bias, *args, **kwargs: orig_func(input,
+        weight if weight is not None else torch.ones(input.size()[1], device=input.device),
+        bias if bias is not None else torch.zeros(input.size()[1], device=input.device), *args, **kwargs),
+        lambda orig_func, input, *args, **kwargs: input.device != torch.device("cpu"))
+    CondFunc('torch.instance_norm',
+        lambda orig_func, input, weight, bias, *args, **kwargs: orig_func(input,
+        weight if weight is not None else torch.ones(input.size()[1], device=input.device),
+        bias if bias is not None else torch.zeros(input.size()[1], device=input.device), *args, **kwargs),
+        lambda orig_func, input, *args, **kwargs: input.device != torch.device("cpu"))
+
+    #Functions with dtype errors:
+    CondFunc('torch.nn.modules.GroupNorm.forward',
+        lambda orig_func, self, input: orig_func(self, input.to(self.weight.data.dtype)),
+        lambda orig_func, self, input: input.dtype != self.weight.data.dtype)
+    CondFunc('torch.nn.modules.linear.Linear.forward',
+        lambda orig_func, self, input: orig_func(self, input.to(self.weight.data.dtype)),
+        lambda orig_func, self, input: input.dtype != self.weight.data.dtype)
+    CondFunc('torch.nn.modules.conv.Conv2d.forward',
+        lambda orig_func, self, input: orig_func(self, input.to(self.weight.data.dtype)),
+        lambda orig_func, self, input: input.dtype != self.weight.data.dtype)
+    CondFunc('torch.nn.functional.layer_norm',
+        lambda orig_func, input, normalized_shape=None, weight=None, *args, **kwargs:
+        orig_func(input.to(weight.data.dtype), normalized_shape, weight, *args, **kwargs),
+        lambda orig_func, input, normalized_shape=None, weight=None, *args, **kwargs:
+        weight is not None and input.dtype != weight.data.dtype)
+
+    #Diffusers Float64 (ARC GPUs doesn't support double or Float64):
+    if not torch.xpu.has_fp64_dtype():
+        CondFunc('torch.from_numpy',
+        lambda orig_func, ndarray: orig_func(ndarray.astype('float32')),
+        lambda orig_func, ndarray: ndarray.dtype == float)
+
+    #Broken functions when torch.cuda.is_available is True:
+    CondFunc('torch.utils.data.dataloader._BaseDataLoaderIter.__init__',
+        lambda orig_func, *args, **kwargs: ipex_no_cuda(orig_func, *args, **kwargs),
+        lambda orig_func, *args, **kwargs: True)
+
+    #Functions that make compile mad with CondFunc:
+    torch.utils.data.dataloader._MultiProcessingDataLoaderIter._shutdown_workers = _shutdown_workers
+    torch.nn.DataParallel = DummyDataParallel
+    torch.autocast = ipex_autocast
+    torch.cat = torch_cat
+    torch.linalg.solve = linalg_solve
+    torch.nn.functional.interpolate = interpolate
+    torch.backends.cuda.sdp_kernel = return_null_context
\ No newline at end of file
diff --git a/infer/modules/onnx/export.py b/infer/modules/onnx/export.py
new file mode 100644
index 0000000000000000000000000000000000000000..ed4a4162ff04b7e12642fcbe96847f8ea9db06aa
--- /dev/null
+++ b/infer/modules/onnx/export.py
@@ -0,0 +1,52 @@
+import torch
+
+from infer.lib.infer_pack.models_onnx import SynthesizerTrnMsNSFsidM
+
+
+def export_onnx(ModelPath, ExportedPath):
+    cpt = torch.load(ModelPath, map_location="cpu")
+    cpt["config"][-3] = cpt["weight"]["emb_g.weight"].shape[0]
+    vec_channels = 256 if cpt.get("version", "v1") == "v1" else 768
+
+    test_phone = torch.rand(1, 200, vec_channels)  # hidden unit
+    test_phone_lengths = torch.tensor([200]).long()  # hidden unit 长度（貌似没啥用）
+    test_pitch = torch.randint(size=(1, 200), low=5, high=255)  # 基频（单位赫兹）
+    test_pitchf = torch.rand(1, 200)  # nsf基频
+    test_ds = torch.LongTensor([0])  # 说话人ID
+    test_rnd = torch.rand(1, 192, 200)  # 噪声（加入随机因子）
+
+    device = "cpu"  # 导出时设备（不影响使用模型）
+
+    net_g = SynthesizerTrnMsNSFsidM(
+        *cpt["config"], is_half=False, version=cpt.get("version", "v1")
+    )  # fp32导出（C++要支持fp16必须手动将内存重新排列所以暂时不用fp16）
+    net_g.load_state_dict(cpt["weight"], strict=False)
+    input_names = ["phone", "phone_lengths", "pitch", "pitchf", "ds", "rnd"]
+    output_names = [
+        "audio",
+    ]
+    # net_g.construct_spkmixmap(n_speaker) 多角色混合轨道导出
+    torch.onnx.export(
+        net_g,
+        (
+            test_phone.to(device),
+            test_phone_lengths.to(device),
+            test_pitch.to(device),
+            test_pitchf.to(device),
+            test_ds.to(device),
+            test_rnd.to(device),
+        ),
+        ExportedPath,
+        dynamic_axes={
+            "phone": [1],
+            "pitch": [1],
+            "pitchf": [1],
+            "rnd": [2],
+        },
+        do_constant_folding=False,
+        opset_version=13,
+        verbose=False,
+        input_names=input_names,
+        output_names=output_names,
+    )
+    return "Finished"
diff --git a/infer/modules/train/extract/extract_f0_print.py b/infer/modules/train/extract/extract_f0_print.py
new file mode 100644
index 0000000000000000000000000000000000000000..14ef598d73b807974204664f100c828918199816
--- /dev/null
+++ b/infer/modules/train/extract/extract_f0_print.py
@@ -0,0 +1,298 @@
+import os
+import sys
+import traceback
+
+import parselmouth
+
+now_dir = os.getcwd()
+sys.path.append(now_dir)
+import logging
+from LazyImport import lazyload
+
+import numpy as np
+import pyworld
+torchcrepe = lazyload("torchcrepe")  # Fork Feature. Crepe algo for training and preprocess
+torch = lazyload("torch")
+#from torch import Tensor  # Fork Feature. Used for pitch prediction for torch crepe.
+tqdm = lazyload("tqdm")
+from infer.lib.audio import load_audio
+
+logging.getLogger("numba").setLevel(logging.WARNING)
+from multiprocessing import Process
+
+exp_dir = sys.argv[1]
+f = open("%s/extract_f0_feature.log" % exp_dir, "a+")
+
+DoFormant = False
+Quefrency = 1.0
+Timbre = 1.0
+
+def printt(strr):
+    print(strr)
+    f.write(f"{strr}\n")
+    f.flush()
+
+
+n_p = int(sys.argv[2])
+f0method = sys.argv[3]
+extraction_crepe_hop_length = 0
+try:
+    extraction_crepe_hop_length = int(sys.argv[4])
+except:
+    print("Temp Issue. echl is not being passed with argument!")
+    extraction_crepe_hop_length = 128
+
+class FeatureInput(object):
+    def __init__(self, samplerate=16000, hop_size=160):
+        self.fs = samplerate
+        self.hop = hop_size
+
+        self.f0_bin = 256
+        self.f0_max = 1100.0
+        self.f0_min = 50.0
+        self.f0_mel_min = 1127 * np.log(1 + self.f0_min / 700)
+        self.f0_mel_max = 1127 * np.log(1 + self.f0_max / 700)
+
+    def mncrepe(self, method, x, p_len, crepe_hop_length):
+        f0 = None
+        torch_device_index = 0
+        torch_device = torch.device(
+            f"cuda:{torch_device_index % torch.cuda.device_count()}"
+        ) if torch.cuda.is_available() \
+            else torch.device("mps") if torch.backends.mps.is_available() \
+            else torch.device("cpu")
+
+        audio = torch.from_numpy(x.astype(np.float32)).to(torch_device, copy=True)
+        audio /= torch.quantile(torch.abs(audio), 0.999)
+        audio = torch.unsqueeze(audio, dim=0)
+        if audio.ndim == 2 and audio.shape[0] > 1:
+            audio = torch.mean(audio, dim=0, keepdim=True).detach()
+        audio = audio.detach()
+        
+        if method == 'mangio-crepe':
+            pitch: torch.Tensor = torchcrepe.predict(
+                audio,
+                self.fs,
+                crepe_hop_length,
+                self.f0_min,
+                self.f0_max,
+                "full",
+                batch_size=crepe_hop_length * 2,
+                device=torch_device,
+                pad=True,
+            )
+            p_len = p_len or x.shape[0] // crepe_hop_length
+            # Resize the pitch
+            source = np.array(pitch.squeeze(0).cpu().float().numpy())
+            source[source < 0.001] = np.nan
+            target = np.interp(
+                np.arange(0, len(source) * p_len, len(source)) / p_len,
+                np.arange(0, len(source)),
+                source,
+            )
+            f0 = np.nan_to_num(target)
+            
+        elif method == 'crepe':
+            batch_size = 512
+            audio = torch.tensor(np.copy(x))[None].float()
+            f0, pd = torchcrepe.predict(
+                audio,
+                self.fs,
+                160,
+                self.f0_min,
+                self.f0_max,
+                "full",
+                batch_size=batch_size,
+                device=torch_device,
+                return_periodicity=True,
+            )
+            pd = torchcrepe.filter.median(pd, 3)
+            f0 = torchcrepe.filter.mean(f0, 3)
+            f0[pd < 0.1] = 0
+            f0 = f0[0].cpu().numpy()
+            f0 = f0[1:]  # Get rid of extra first frame
+
+        return f0
+
+    def get_pm(self, x, p_len):
+        f0 = parselmouth.Sound(x, self.fs).to_pitch_ac(
+            time_step=160 / 16000,
+            voicing_threshold=0.6,
+            pitch_floor=self.f0_min,
+            pitch_ceiling=self.f0_max,
+        ).selected_array["frequency"]
+        
+        return np.pad(
+            f0,
+            [[max(0, (p_len - len(f0) + 1) // 2), max(0, p_len - len(f0) - (p_len - len(f0) + 1) // 2)]],
+            mode="constant"
+        )
+
+    def get_harvest(self, x):
+        f0_spectral = pyworld.harvest(
+            x.astype(np.double),
+            fs=self.fs,
+            f0_ceil=self.f0_max,
+            f0_floor=self.f0_min,
+            frame_period=1000 * self.hop / self.fs,
+        )
+        return pyworld.stonemask(x.astype(np.double), *f0_spectral, self.fs)
+
+    def get_dio(self, x):
+        f0_spectral = pyworld.dio(
+            x.astype(np.double),
+            fs=self.fs,
+            f0_ceil=self.f0_max,
+            f0_floor=self.f0_min,
+            frame_period=1000 * self.hop / self.fs,
+        )
+        return pyworld.stonemask(x.astype(np.double), *f0_spectral, self.fs)
+
+    def get_rmvpe(self, x):
+        if hasattr(self, "model_rmvpe") == False:
+                from infer.lib.rmvpe import RMVPE
+
+                print("Loading rmvpe model")
+                self.model_rmvpe = RMVPE(
+                    "assets/rmvpe/rmvpe.pt", is_half=False, device="cpu"
+                )
+        return self.model_rmvpe.infer_from_audio(x, thred=0.03)
+        
+    def get_rmvpe_dml(self, x):
+        ...
+
+    def get_f0_method_dict(self):
+        return {
+            "pm": self.get_pm,
+            "harvest": self.get_harvest,
+            "dio": self.get_dio,
+            "rmvpe": self.get_rmvpe
+        }
+
+    def get_f0_hybrid_computation(
+        self,
+        methods_str,
+        x,
+        p_len,
+        crepe_hop_length,
+    ):
+        # Get various f0 methods from input to use in the computation stack
+        s = methods_str
+        s = s.split("hybrid")[1]
+        s = s.replace("[", "").replace("]", "")
+        methods = s.split("+")
+        f0_computation_stack = []
+
+        for method in methods:
+            if method in self.f0_method_dict:
+                f0 = self.f0_method_dict[method](x, p_len) if method == 'pm' else self.f0_method_dict[method](x)
+                f0_computation_stack.append(f0)
+            elif method == 'crepe' or method == 'mangio-crepe':
+                self.the_other_complex_function(x, method, crepe_hop_length)
+
+        if len(f0_computation_stack) != 0:        
+            f0_median_hybrid = np.nanmedian(f0_computation_stack, axis=0) if len(f0_computation_stack)>1 else f0_computation_stack[0]
+            return f0_median_hybrid
+        else:
+            raise ValueError("No valid methods were provided")
+
+    def compute_f0(self, path, f0_method, crepe_hop_length):
+        x = load_audio(path, self.fs, DoFormant, Quefrency, Timbre)
+        p_len = x.shape[0] // self.hop
+
+        if f0_method in self.f0_method_dict:
+            f0 = self.f0_method_dict[f0_method](x, p_len) if f0_method == 'pm' else self.f0_method_dict[f0_method](x)
+        elif f0_method in ['crepe', 'mangio-crepe']:
+            f0 = self.mncrepe(f0_method, x, p_len, crepe_hop_length)
+        elif "hybrid" in f0_method:  # EXPERIMENTAL
+            # Perform hybrid median pitch estimation
+            f0 = self.get_f0_hybrid_computation(
+                f0_method,
+                x,
+                p_len,
+                crepe_hop_length,
+            )
+        return f0
+
+    def coarse_f0(self, f0):
+        f0_mel = 1127 * np.log(1 + f0 / 700)
+        f0_mel[f0_mel > 0] = (f0_mel[f0_mel > 0] - self.f0_mel_min) * (
+            self.f0_bin - 2
+        ) / (self.f0_mel_max - self.f0_mel_min) + 1
+
+        # use 0 or 1
+        f0_mel[f0_mel <= 1] = 1
+        f0_mel[f0_mel > self.f0_bin - 1] = self.f0_bin - 1
+        f0_coarse = np.rint(f0_mel).astype(int)
+        assert f0_coarse.max() <= 255 and f0_coarse.min() >= 1, (
+            f0_coarse.max(),
+            f0_coarse.min(),
+        )
+        return f0_coarse
+
+    def go(self, paths, f0_method, crepe_hop_length, thread_n):
+        if len(paths) == 0:
+            printt("no-f0-todo")
+            return
+        with tqdm.tqdm(total=len(paths), leave=True, position=thread_n) as pbar:
+            description = f"thread:{thread_n}, f0ing, Hop-Length:{crepe_hop_length}"
+            pbar.set_description(description)
+                
+            for idx, (inp_path, opt_path1, opt_path2) in enumerate(paths):
+                try:
+                    if (
+                        os.path.exists(opt_path1 + ".npy") 
+                        and os.path.exists(opt_path2 + ".npy")
+                    ):
+                        pbar.update(1)
+                        continue
+
+                    featur_pit = self.compute_f0(inp_path, f0_method, crepe_hop_length)
+                    np.save(
+                        opt_path2,
+                        featur_pit,
+                        allow_pickle=False,
+                    )  # nsf
+                    coarse_pit = self.coarse_f0(featur_pit)
+                    np.save(
+                        opt_path1,
+                        coarse_pit,
+                        allow_pickle=False,
+                    )  # ori
+                    pbar.update(1)
+                except Exception as e:
+                    printt(f"f0fail-{idx}-{inp_path}-{traceback.format_exc()}")
+
+
+if __name__ == "__main__":
+    # exp_dir=r"E:\codes\py39\dataset\mi-test"
+    # n_p=16
+    # f = open("%s/log_extract_f0.log"%exp_dir, "w")
+    printt(sys.argv)
+    featureInput = FeatureInput()
+    paths = []
+    inp_root = "%s/1_16k_wavs" % (exp_dir)
+    opt_root1 = "%s/2a_f0" % (exp_dir)
+    opt_root2 = "%s/2b-f0nsf" % (exp_dir)
+
+    os.makedirs(opt_root1, exist_ok=True)
+    os.makedirs(opt_root2, exist_ok=True)
+    for name in sorted(list(os.listdir(inp_root))):
+        inp_path = "%s/%s" % (inp_root, name)
+        if "spec" in inp_path:
+            continue
+        opt_path1 = "%s/%s" % (opt_root1, name)
+        opt_path2 = "%s/%s" % (opt_root2, name)
+        paths.append([inp_path, opt_path1, opt_path2])
+
+    ps = []
+    print("Using f0 method: " + f0method)
+    for i in range(n_p):
+        p = Process(
+            target=featureInput.go,
+            args=(paths[i::n_p], f0method, extraction_crepe_hop_length, i),
+        )
+        ps.append(p)
+        p.start()
+    for i in range(n_p):
+        ps[i].join()
\ No newline at end of file
diff --git a/infer/modules/train/extract/extract_f0_rmvpe.py b/infer/modules/train/extract/extract_f0_rmvpe.py
new file mode 100644
index 0000000000000000000000000000000000000000..c6c90440d9e612b37c6d5a514786a6d0fffb19ba
--- /dev/null
+++ b/infer/modules/train/extract/extract_f0_rmvpe.py
@@ -0,0 +1,141 @@
+import os
+import sys
+import traceback
+
+import parselmouth
+
+now_dir = os.getcwd()
+sys.path.append(now_dir)
+import logging
+
+import numpy as np
+import pyworld
+
+from infer.lib.audio import load_audio
+
+logging.getLogger("numba").setLevel(logging.WARNING)
+
+n_part = int(sys.argv[1])
+i_part = int(sys.argv[2])
+i_gpu = sys.argv[3]
+os.environ["CUDA_VISIBLE_DEVICES"] = str(i_gpu)
+exp_dir = sys.argv[4]
+is_half = sys.argv[5]
+f = open("%s/extract_f0_feature.log" % exp_dir, "a+")
+
+
+def printt(strr):
+    print(strr)
+    f.write("%s\n" % strr)
+    f.flush()
+
+
+class FeatureInput(object):
+    def __init__(self, samplerate=16000, hop_size=160):
+        self.fs = samplerate
+        self.hop = hop_size
+
+        self.f0_bin = 256
+        self.f0_max = 1100.0
+        self.f0_min = 50.0
+        self.f0_mel_min = 1127 * np.log(1 + self.f0_min / 700)
+        self.f0_mel_max = 1127 * np.log(1 + self.f0_max / 700)
+
+    def compute_f0(self, path, f0_method):
+        x = load_audio(path, self.fs)
+        # p_len = x.shape[0] // self.hop
+        if f0_method == "rmvpe":
+            if hasattr(self, "model_rmvpe") == False:
+                from infer.lib.rmvpe import RMVPE
+
+                print("Loading rmvpe model")
+                self.model_rmvpe = RMVPE(
+                    "assets/rmvpe/rmvpe.pt", is_half=is_half, device="cuda"
+                )
+            f0 = self.model_rmvpe.infer_from_audio(x, thred=0.03)
+        return f0
+
+    def coarse_f0(self, f0):
+        f0_mel = 1127 * np.log(1 + f0 / 700)
+        f0_mel[f0_mel > 0] = (f0_mel[f0_mel > 0] - self.f0_mel_min) * (
+            self.f0_bin - 2
+        ) / (self.f0_mel_max - self.f0_mel_min) + 1
+
+        # use 0 or 1
+        f0_mel[f0_mel <= 1] = 1
+        f0_mel[f0_mel > self.f0_bin - 1] = self.f0_bin - 1
+        f0_coarse = np.rint(f0_mel).astype(int)
+        assert f0_coarse.max() <= 255 and f0_coarse.min() >= 1, (
+            f0_coarse.max(),
+            f0_coarse.min(),
+        )
+        return f0_coarse
+
+    def go(self, paths, f0_method):
+        if len(paths) == 0:
+            printt("no-f0-todo")
+        else:
+            printt("todo-f0-%s" % len(paths))
+            n = max(len(paths) // 5, 1)  # 每个进程最多打印5条
+            for idx, (inp_path, opt_path1, opt_path2) in enumerate(paths):
+                try:
+                    if idx % n == 0:
+                        printt("f0ing,now-%s,all-%s,-%s" % (idx, len(paths), inp_path))
+                    if (
+                        os.path.exists(opt_path1 + ".npy") == True
+                        and os.path.exists(opt_path2 + ".npy") == True
+                    ):
+                        continue
+                    featur_pit = self.compute_f0(inp_path, f0_method)
+                    np.save(
+                        opt_path2,
+                        featur_pit,
+                        allow_pickle=False,
+                    )  # nsf
+                    coarse_pit = self.coarse_f0(featur_pit)
+                    np.save(
+                        opt_path1,
+                        coarse_pit,
+                        allow_pickle=False,
+                    )  # ori
+                except:
+                    printt("f0fail-%s-%s-%s" % (idx, inp_path, traceback.format_exc()))
+
+
+if __name__ == "__main__":
+    # exp_dir=r"E:\codes\py39\dataset\mi-test"
+    # n_p=16
+    # f = open("%s/log_extract_f0.log"%exp_dir, "w")
+    printt(sys.argv)
+    featureInput = FeatureInput()
+    paths = []
+    inp_root = "%s/1_16k_wavs" % (exp_dir)
+    opt_root1 = "%s/2a_f0" % (exp_dir)
+    opt_root2 = "%s/2b-f0nsf" % (exp_dir)
+
+    os.makedirs(opt_root1, exist_ok=True)
+    os.makedirs(opt_root2, exist_ok=True)
+    for name in sorted(list(os.listdir(inp_root))):
+        inp_path = "%s/%s" % (inp_root, name)
+        if "spec" in inp_path:
+            continue
+        opt_path1 = "%s/%s" % (opt_root1, name)
+        opt_path2 = "%s/%s" % (opt_root2, name)
+        paths.append([inp_path, opt_path1, opt_path2])
+    try:
+        featureInput.go(paths[i_part::n_part], "rmvpe")
+    except:
+        printt("f0_all_fail-%s" % (traceback.format_exc()))
+    # ps = []
+    # for i in range(n_p):
+    #     p = Process(
+    #         target=featureInput.go,
+    #         args=(
+    #             paths[i::n_p],
+    #             f0method,
+    #         ),
+    #     )
+    #     ps.append(p)
+    #     p.start()
+    # for i in range(n_p):
+    #     ps[i].join()
diff --git a/infer/modules/train/extract/extract_f0_rmvpe_dml.py b/infer/modules/train/extract/extract_f0_rmvpe_dml.py
new file mode 100644
index 0000000000000000000000000000000000000000..6abb1898550664ca600cebbb6d37ba0de8a3d312
--- /dev/null
+++ b/infer/modules/train/extract/extract_f0_rmvpe_dml.py
@@ -0,0 +1,139 @@
+import os
+import sys
+import traceback
+
+import parselmouth
+
+now_dir = os.getcwd()
+sys.path.append(now_dir)
+import logging
+
+import numpy as np
+import pyworld
+
+from infer.lib.audio import load_audio
+
+logging.getLogger("numba").setLevel(logging.WARNING)
+
+exp_dir = sys.argv[1]
+import torch_directml
+
+device = torch_directml.device(torch_directml.default_device())
+f = open("%s/extract_f0_feature.log" % exp_dir, "a+")
+
+
+def printt(strr):
+    print(strr)
+    f.write("%s\n" % strr)
+    f.flush()
+
+
+class FeatureInput(object):
+    def __init__(self, samplerate=16000, hop_size=160):
+        self.fs = samplerate
+        self.hop = hop_size
+
+        self.f0_bin = 256
+        self.f0_max = 1100.0
+        self.f0_min = 50.0
+        self.f0_mel_min = 1127 * np.log(1 + self.f0_min / 700)
+        self.f0_mel_max = 1127 * np.log(1 + self.f0_max / 700)
+
+    def compute_f0(self, path, f0_method):
+        x = load_audio(path, self.fs)
+        # p_len = x.shape[0] // self.hop
+        if f0_method == "rmvpe":
+            if hasattr(self, "model_rmvpe") == False:
+                from infer.lib.rmvpe import RMVPE
+
+                print("Loading rmvpe model")
+                self.model_rmvpe = RMVPE(
+                    "assets/rmvpe/rmvpe.pt", is_half=False, device=device
+                )
+            f0 = self.model_rmvpe.infer_from_audio(x, thred=0.03)
+        return f0
+
+    def coarse_f0(self, f0):
+        f0_mel = 1127 * np.log(1 + f0 / 700)
+        f0_mel[f0_mel > 0] = (f0_mel[f0_mel > 0] - self.f0_mel_min) * (
+            self.f0_bin - 2
+        ) / (self.f0_mel_max - self.f0_mel_min) + 1
+
+        # use 0 or 1
+        f0_mel[f0_mel <= 1] = 1
+        f0_mel[f0_mel > self.f0_bin - 1] = self.f0_bin - 1
+        f0_coarse = np.rint(f0_mel).astype(int)
+        assert f0_coarse.max() <= 255 and f0_coarse.min() >= 1, (
+            f0_coarse.max(),
+            f0_coarse.min(),
+        )
+        return f0_coarse
+
+    def go(self, paths, f0_method):
+        if len(paths) == 0:
+            printt("no-f0-todo")
+        else:
+            printt("todo-f0-%s" % len(paths))
+            n = max(len(paths) // 5, 1)  # 每个进程最多打印5条
+            for idx, (inp_path, opt_path1, opt_path2) in enumerate(paths):
+                try:
+                    if idx % n == 0:
+                        printt("f0ing,now-%s,all-%s,-%s" % (idx, len(paths), inp_path))
+                    if (
+                        os.path.exists(opt_path1 + ".npy") == True
+                        and os.path.exists(opt_path2 + ".npy") == True
+                    ):
+                        continue
+                    featur_pit = self.compute_f0(inp_path, f0_method)
+                    np.save(
+                        opt_path2,
+                        featur_pit,
+                        allow_pickle=False,
+                    )  # nsf
+                    coarse_pit = self.coarse_f0(featur_pit)
+                    np.save(
+                        opt_path1,
+                        coarse_pit,
+                        allow_pickle=False,
+                    )  # ori
+                except:
+                    printt("f0fail-%s-%s-%s" % (idx, inp_path, traceback.format_exc()))
+
+
+if __name__ == "__main__":
+    # exp_dir=r"E:\codes\py39\dataset\mi-test"
+    # n_p=16
+    # f = open("%s/log_extract_f0.log"%exp_dir, "w")
+    printt(sys.argv)
+    featureInput = FeatureInput()
+    paths = []
+    inp_root = "%s/1_16k_wavs" % (exp_dir)
+    opt_root1 = "%s/2a_f0" % (exp_dir)
+    opt_root2 = "%s/2b-f0nsf" % (exp_dir)
+
+    os.makedirs(opt_root1, exist_ok=True)
+    os.makedirs(opt_root2, exist_ok=True)
+    for name in sorted(list(os.listdir(inp_root))):
+        inp_path = "%s/%s" % (inp_root, name)
+        if "spec" in inp_path:
+            continue
+        opt_path1 = "%s/%s" % (opt_root1, name)
+        opt_path2 = "%s/%s" % (opt_root2, name)
+        paths.append([inp_path, opt_path1, opt_path2])
+    try:
+        featureInput.go(paths, "rmvpe")
+    except:
+        printt("f0_all_fail-%s" % (traceback.format_exc()))
+    # ps = []
+    # for i in range(n_p):
+    #     p = Process(
+    #         target=featureInput.go,
+    #         args=(
+    #             paths[i::n_p],
+    #             f0method,
+    #         ),
+    #     )
+    #     ps.append(p)
+    #     p.start()
+    # for i in range(n_p):
+    #     ps[i].join()
diff --git a/infer/modules/train/extract_feature_print.py b/infer/modules/train/extract_feature_print.py
new file mode 100644
index 0000000000000000000000000000000000000000..f771dd9b8ba92262e6844e7b5781de43c342833a
--- /dev/null
+++ b/infer/modules/train/extract_feature_print.py
@@ -0,0 +1,137 @@
+import os
+import sys
+import traceback
+
+os.environ["PYTORCH_ENABLE_MPS_FALLBACK"] = "1"
+os.environ["PYTORCH_MPS_HIGH_WATERMARK_RATIO"] = "0.0"
+
+device = sys.argv[1]
+n_part = int(sys.argv[2])
+i_part = int(sys.argv[3])
+if len(sys.argv) == 6:
+    exp_dir = sys.argv[4]
+    version = sys.argv[5]
+else:
+    i_gpu = sys.argv[4]
+    exp_dir = sys.argv[5]
+    os.environ["CUDA_VISIBLE_DEVICES"] = str(i_gpu)
+    version = sys.argv[6]
+import fairseq
+import numpy as np
+import soundfile as sf
+import torch
+import torch.nn.functional as F
+
+if "privateuseone" not in device:
+    device = "cpu"
+    if torch.cuda.is_available():
+        device = "cuda"
+    elif torch.backends.mps.is_available():
+        device = "mps"
+else:
+    import torch_directml
+
+    device = torch_directml.device(torch_directml.default_device())
+
+    def forward_dml(ctx, x, scale):
+        ctx.scale = scale
+        res = x.clone().detach()
+        return res
+
+    fairseq.modules.grad_multiply.GradMultiply.forward = forward_dml
+
+f = open("%s/extract_f0_feature.log" % exp_dir, "a+")
+
+
+def printt(strr):
+    print(strr)
+    f.write("%s\n" % strr)
+    f.flush()
+
+
+printt(sys.argv)
+model_path = "assets/hubert/hubert_base.pt"
+
+printt(exp_dir)
+wavPath = "%s/1_16k_wavs" % exp_dir
+outPath = (
+    "%s/3_feature256" % exp_dir if version == "v1" else "%s/3_feature768" % exp_dir
+)
+os.makedirs(outPath, exist_ok=True)
+
+
+# wave must be 16k, hop_size=320
+def readwave(wav_path, normalize=False):
+    wav, sr = sf.read(wav_path)
+    assert sr == 16000
+    feats = torch.from_numpy(wav).float()
+    if feats.dim() == 2:  # double channels
+        feats = feats.mean(-1)
+    assert feats.dim() == 1, feats.dim()
+    if normalize:
+        with torch.no_grad():
+            feats = F.layer_norm(feats, feats.shape)
+    feats = feats.view(1, -1)
+    return feats
+
+
+# HuBERT model
+printt("load model(s) from {}".format(model_path))
+# if hubert model is exist
+if os.access(model_path, os.F_OK) == False:
+    printt(
+        "Error: Extracting is shut down because %s does not exist, you may download it from https://huggingface.co/lj1995/VoiceConversionWebUI/tree/main"
+        % model_path
+    )
+    exit(0)
+models, saved_cfg, task = fairseq.checkpoint_utils.load_model_ensemble_and_task(
+    [model_path],
+    suffix="",
+)
+model = models[0]
+model = model.to(device)
+printt("move model to %s" % device)
+if device not in ["mps", "cpu"]:
+    model = model.half()
+model.eval()
+
+todo = sorted(list(os.listdir(wavPath)))[i_part::n_part]
+n = max(1, len(todo) // 10)  # 最多打印十条
+if len(todo) == 0:
+    printt("no-feature-todo")
+else:
+    printt("all-feature-%s" % len(todo))
+    for idx, file in enumerate(todo):
+        try:
+            if file.endswith(".wav"):
+                wav_path = "%s/%s" % (wavPath, file)
+                out_path = "%s/%s" % (outPath, file.replace("wav", "npy"))
+
+                if os.path.exists(out_path):
+                    continue
+
+                feats = readwave(wav_path, normalize=saved_cfg.task.normalize)
+                padding_mask = torch.BoolTensor(feats.shape).fill_(False)
+                inputs = {
+                    "source": feats.half().to(device)
+                    if device not in ["mps", "cpu"]
+                    else feats.to(device),
+                    "padding_mask": padding_mask.to(device),
+                    "output_layer": 9 if version == "v1" else 12,  # layer 9
+                }
+                with torch.no_grad():
+                    logits = model.extract_features(**inputs)
+                    feats = (
+                        model.final_proj(logits[0]) if version == "v1" else logits[0]
+                    )
+
+                feats = feats.squeeze(0).float().cpu().numpy()
+                if np.isnan(feats).sum() == 0:
+                    np.save(out_path, feats, allow_pickle=False)
+                else:
+                    printt("%s-contains nan" % file)
+                if idx % n == 0:
+                    printt("now-%s,all-%s,%s,%s" % (len(todo), idx, file, feats.shape))
+        except:
+            printt(traceback.format_exc())
+    printt("all-feature-done")
diff --git a/infer/modules/train/preprocess.py b/infer/modules/train/preprocess.py
new file mode 100644
index 0000000000000000000000000000000000000000..fbe81307ee661a95b2ac479336671a44ee02151a
--- /dev/null
+++ b/infer/modules/train/preprocess.py
@@ -0,0 +1,147 @@
+import multiprocessing
+import os
+import sys
+
+from scipy import signal
+
+now_dir = os.getcwd()
+sys.path.append(now_dir)
+print(sys.argv)
+inp_root = sys.argv[1]
+sr = int(sys.argv[2])
+n_p = int(sys.argv[3])
+exp_dir = sys.argv[4]
+noparallel = sys.argv[5] == "True"
+per = float(sys.argv[6])
+import multiprocessing
+import os
+import traceback
+
+import librosa
+import numpy as np
+from scipy.io import wavfile
+
+from infer.lib.audio import load_audio
+from infer.lib.slicer2 import Slicer
+
+mutex = multiprocessing.Lock()
+f = open("%s/preprocess.log" % exp_dir, "a+")
+
+
+def println(strr):
+    mutex.acquire()
+    print(strr)
+    f.write("%s\n" % strr)
+    f.flush()
+    mutex.release()
+
+
+class PreProcess:
+    def __init__(self, sr, exp_dir, per=3.7):
+        self.slicer = Slicer(
+            sr=sr,
+            threshold=-42,
+            min_length=1500,
+            min_interval=400,
+            hop_size=15,
+            max_sil_kept=500,
+        )
+        self.sr = sr
+        self.bh, self.ah = signal.butter(N=5, Wn=48, btype="high", fs=self.sr)
+        self.per = per
+        self.overlap = 0.3
+        self.tail = self.per + self.overlap
+        self.max = 0.9
+        self.alpha = 0.75
+        self.exp_dir = exp_dir
+        self.gt_wavs_dir = "%s/0_gt_wavs" % exp_dir
+        self.wavs16k_dir = "%s/1_16k_wavs" % exp_dir
+        os.makedirs(self.exp_dir, exist_ok=True)
+        os.makedirs(self.gt_wavs_dir, exist_ok=True)
+        os.makedirs(self.wavs16k_dir, exist_ok=True)
+
+    def norm_write(self, tmp_audio, idx0, idx1):
+        tmp_max = np.abs(tmp_audio).max()
+        if tmp_max > 2.5:
+            print("%s-%s-%s-filtered" % (idx0, idx1, tmp_max))
+            return
+        tmp_audio = (tmp_audio / tmp_max * (self.max * self.alpha)) + (
+            1 - self.alpha
+        ) * tmp_audio
+        wavfile.write(
+            "%s/%s_%s.wav" % (self.gt_wavs_dir, idx0, idx1),
+            self.sr,
+            tmp_audio.astype(np.float32),
+        )
+        tmp_audio = librosa.resample(
+            tmp_audio, orig_sr=self.sr, target_sr=16000
+        )  # , res_type="soxr_vhq"
+        wavfile.write(
+            "%s/%s_%s.wav" % (self.wavs16k_dir, idx0, idx1),
+            16000,
+            tmp_audio.astype(np.float32),
+        )
+
+    def pipeline(self, path, idx0):
+        try:
+            audio = load_audio(path, self.sr)
+            # zero phased digital filter cause pre-ringing noise...
+            # audio = signal.filtfilt(self.bh, self.ah, audio)
+            audio = signal.lfilter(self.bh, self.ah, audio)
+
+            idx1 = 0
+            for audio in self.slicer.slice(audio):
+                i = 0
+                while 1:
+                    start = int(self.sr * (self.per - self.overlap) * i)
+                    i += 1
+                    if len(audio[start:]) > self.tail * self.sr:
+                        tmp_audio = audio[start : start + int(self.per * self.sr)]
+                        self.norm_write(tmp_audio, idx0, idx1)
+                        idx1 += 1
+                    else:
+                        tmp_audio = audio[start:]
+                        idx1 += 1
+                        break
+                self.norm_write(tmp_audio, idx0, idx1)
+            println("%s->Suc." % path)
+        except:
+            println("%s->%s" % (path, traceback.format_exc()))
+
+    def pipeline_mp(self, infos):
+        for path, idx0 in infos:
+            self.pipeline(path, idx0)
+
+    def pipeline_mp_inp_dir(self, inp_root, n_p):
+        try:
+            infos = [
+                ("%s/%s" % (inp_root, name), idx)
+                for idx, name in enumerate(sorted(list(os.listdir(inp_root))))
+            ]
+            if noparallel:
+                for i in range(n_p):
+                    self.pipeline_mp(infos[i::n_p])
+            else:
+                ps = []
+                for i in range(n_p):
+                    p = multiprocessing.Process(
+                        target=self.pipeline_mp, args=(infos[i::n_p],)
+                    )
+                    ps.append(p)
+                    p.start()
+                for i in range(n_p):
+                    ps[i].join()
+        except:
+            println("Fail. %s" % traceback.format_exc())
+
+
+def preprocess_trainset(inp_root, sr, n_p, exp_dir, per):
+    pp = PreProcess(sr, exp_dir, per)
+    println("start preprocess")
+    println(sys.argv)
+    pp.pipeline_mp_inp_dir(inp_root, n_p)
+    println("end preprocess")
+
+
+if __name__ == "__main__":
+    preprocess_trainset(inp_root, sr, n_p, exp_dir, per)
diff --git a/infer/modules/train/train.py b/infer/modules/train/train.py
new file mode 100644
index 0000000000000000000000000000000000000000..550bef391444c9b6c0d8c44ae3a3809b3ade4218
--- /dev/null
+++ b/infer/modules/train/train.py
@@ -0,0 +1,723 @@
+import os
+import sys
+import logging
+
+logger = logging.getLogger(__name__)
+
+now_dir = os.getcwd()
+sys.path.append(os.path.join(now_dir))
+
+import datetime
+
+from infer.lib.train import utils
+
+hps = utils.get_hparams()
+os.environ["CUDA_VISIBLE_DEVICES"] = hps.gpus.replace("-", ",")
+n_gpus = len(hps.gpus.split("-"))
+from random import randint, shuffle
+
+import torch
+try:
+    import intel_extension_for_pytorch as ipex # pylint: disable=import-error, unused-import
+    if torch.xpu.is_available():
+        from infer.modules.ipex import ipex_init
+        from infer.modules.ipex.gradscaler import gradscaler_init
+        from torch.xpu.amp import autocast
+        GradScaler = gradscaler_init()
+        ipex_init()
+    else:
+        from torch.cuda.amp import GradScaler, autocast
+except Exception:
+    from torch.cuda.amp import GradScaler, autocast
+
+torch.backends.cudnn.deterministic = False
+torch.backends.cudnn.benchmark = False
+from time import sleep
+from time import time as ttime
+
+import torch.distributed as dist
+import torch.multiprocessing as mp
+
+from torch.nn import functional as F
+from torch.nn.parallel import DistributedDataParallel as DDP
+from torch.utils.data import DataLoader
+from torch.utils.tensorboard import SummaryWriter
+
+from infer.lib.infer_pack import commons
+from infer.lib.train.data_utils import (
+    DistributedBucketSampler,
+    TextAudioCollate,
+    TextAudioCollateMultiNSFsid,
+    TextAudioLoader,
+    TextAudioLoaderMultiNSFsid,
+)
+
+if hps.version == "v1":
+    from infer.lib.infer_pack.models import MultiPeriodDiscriminator
+    from infer.lib.infer_pack.models import SynthesizerTrnMs256NSFsid as RVC_Model_f0
+    from infer.lib.infer_pack.models import (
+        SynthesizerTrnMs256NSFsid_nono as RVC_Model_nof0,
+    )
+else:
+    from infer.lib.infer_pack.models import (
+        SynthesizerTrnMs768NSFsid as RVC_Model_f0,
+        SynthesizerTrnMs768NSFsid_nono as RVC_Model_nof0,
+        MultiPeriodDiscriminatorV2 as MultiPeriodDiscriminator,
+    )
+
+from infer.lib.train.losses import (
+    discriminator_loss,
+    feature_loss,
+    generator_loss,
+    kl_loss,
+)
+from infer.lib.train.mel_processing import mel_spectrogram_torch, spec_to_mel_torch
+from infer.lib.train.process_ckpt import savee
+
+global_step = 0
+import csv
+
+class EpochRecorder:
+    def __init__(self):
+        self.last_time = ttime()
+
+    def record(self):
+        now_time = ttime()
+        elapsed_time = now_time - self.last_time
+        self.last_time = now_time
+        elapsed_time_str = str(datetime.timedelta(seconds=elapsed_time))
+        current_time = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
+        return f"[{current_time}] | ({elapsed_time_str})"
+
+def reset_stop_flag():
+    with open("csvdb/stop.csv", "w+", newline="") as STOPCSVwrite:
+        csv_writer = csv.writer(STOPCSVwrite, delimiter=",")
+        csv_writer.writerow(["False"])
+
+def create_model(hps, model_f0, model_nof0):
+    filter_length_adjusted = hps.data.filter_length // 2 + 1
+    segment_size_adjusted = hps.train.segment_size // hps.data.hop_length
+    is_half = hps.train.fp16_run
+    sr = hps.sample_rate
+
+    model = model_f0 if hps.if_f0 == 1 else model_nof0
+
+    return model(
+        filter_length_adjusted,
+        segment_size_adjusted,
+        **hps.model,
+        is_half=is_half,
+        sr=sr
+    )
+
+def move_model_to_cuda_if_available(model, rank):
+    if torch.cuda.is_available():
+        return model.cuda(rank)
+    else:
+        return model
+
+def create_optimizer(model, hps):
+    return torch.optim.AdamW(
+        model.parameters(),
+        hps.train.learning_rate,
+        betas=hps.train.betas,
+        eps=hps.train.eps,
+    )
+
+def create_ddp_model(model, rank):
+    if torch.cuda.is_available():
+        return DDP(model, device_ids=[rank])
+    else:
+        return DDP(model)
+
+def create_dataset(hps, if_f0=True):
+    return TextAudioLoaderMultiNSFsid(hps.data.training_files, hps.data) if if_f0 else TextAudioLoader(hps.data.training_files, hps.data)
+
+def create_sampler(dataset, batch_size, n_gpus, rank):
+    return DistributedBucketSampler(
+            dataset,
+            batch_size * n_gpus,
+            # [100, 200, 300, 400, 500, 600, 700, 800, 900, 1000, 1200,1400],  # 16s
+            [100, 200, 300, 400, 500, 600, 700, 800, 900],  # 16s
+            num_replicas=n_gpus,
+            rank=rank,
+            shuffle=True,
+        )
+
+def set_collate_fn(if_f0=True):
+    return TextAudioCollateMultiNSFsid() if if_f0 else TextAudioCollate()
+
+
+def main():
+    n_gpus = torch.cuda.device_count()
+
+    if torch.cuda.is_available() == False and torch.backends.mps.is_available() == True:
+        n_gpus = 1
+    if n_gpus < 1:
+        # patch to unblock people without gpus. there is probably a better way.
+        logger.warn("NO GPU DETECTED: falling back to CPU - this may take a while")
+        n_gpus = 1
+    os.environ["MASTER_ADDR"] = "localhost"
+    os.environ["MASTER_PORT"] = str(randint(20000, 55555))
+    children = []
+    for i in range(n_gpus):
+        subproc = mp.Process(
+            target=run,
+            args=(
+                i,
+                n_gpus,
+                hps,
+            ),
+        )
+        children.append(subproc)
+        subproc.start()
+
+    for i in range(n_gpus):
+        children[i].join()
+
+
+def run(rank, n_gpus, hps):
+    global global_step
+    if rank == 0:
+        logger = utils.get_logger(hps.model_dir)
+        logger.info(hps)
+        # utils.check_git_hash(hps.model_dir)
+        writer = SummaryWriter(log_dir=hps.model_dir)
+        writer_eval = SummaryWriter(log_dir=os.path.join(hps.model_dir, "eval"))
+
+    dist.init_process_group(
+        backend="gloo", init_method="env://", world_size=n_gpus, rank=rank
+    )
+    torch.manual_seed(hps.train.seed)
+    if torch.cuda.is_available():
+        torch.cuda.set_device(rank)
+
+    if hps.if_f0 == 1:
+        train_dataset = TextAudioLoaderMultiNSFsid(hps.data.training_files, hps.data)
+    else:
+        train_dataset = TextAudioLoader(hps.data.training_files, hps.data)
+    train_sampler = DistributedBucketSampler(
+        train_dataset,
+        hps.train.batch_size * n_gpus,
+        # [100, 200, 300, 400, 500, 600, 700, 800, 900, 1000, 1200,1400],  # 16s
+        [100, 200, 300, 400, 500, 600, 700, 800, 900],  # 16s
+        num_replicas=n_gpus,
+        rank=rank,
+        shuffle=True,
+    )
+    # It is possible that dataloader's workers are out of shared memory. Please try to raise your shared memory limit.
+    # num_workers=8 -> num_workers=4
+    if hps.if_f0 == 1:
+        collate_fn = TextAudioCollateMultiNSFsid()
+    else:
+        collate_fn = TextAudioCollate()
+    train_loader = DataLoader(
+        train_dataset,
+        num_workers=4,
+        shuffle=False,
+        pin_memory=True,
+        collate_fn=collate_fn,
+        batch_sampler=train_sampler,
+        persistent_workers=True,
+        prefetch_factor=8,
+    )
+    if hps.if_f0 == 1:
+        net_g = RVC_Model_f0(
+            hps.data.filter_length // 2 + 1,
+            hps.train.segment_size // hps.data.hop_length,
+            **hps.model,
+            is_half=hps.train.fp16_run,
+            sr=hps.sample_rate,
+        )
+    else:
+        net_g = RVC_Model_nof0(
+            hps.data.filter_length // 2 + 1,
+            hps.train.segment_size // hps.data.hop_length,
+            **hps.model,
+            is_half=hps.train.fp16_run,
+        )
+    if torch.cuda.is_available():
+        net_g = net_g.cuda(rank)
+    net_d = MultiPeriodDiscriminator(hps.model.use_spectral_norm)
+    if torch.cuda.is_available():
+        net_d = net_d.cuda(rank)
+    optim_g = torch.optim.AdamW(
+        net_g.parameters(),
+        hps.train.learning_rate,
+        betas=hps.train.betas,
+        eps=hps.train.eps,
+    )
+    optim_d = torch.optim.AdamW(
+        net_d.parameters(),
+        hps.train.learning_rate,
+        betas=hps.train.betas,
+        eps=hps.train.eps,
+    )
+    # net_g = DDP(net_g, device_ids=[rank], find_unused_parameters=True)
+    # net_d = DDP(net_d, device_ids=[rank], find_unused_parameters=True)
+    if hasattr(torch, "xpu") and torch.xpu.is_available():
+        pass
+    elif torch.cuda.is_available():
+        net_g = DDP(net_g, device_ids=[rank])
+        net_d = DDP(net_d, device_ids=[rank])
+    else:
+        net_g = DDP(net_g)
+        net_d = DDP(net_d)
+
+    try:  # 如果能加载自动resume
+        _, _, _, epoch_str = utils.load_checkpoint(
+            utils.latest_checkpoint_path(hps.model_dir, "D_*.pth"), net_d, optim_d
+        )  # D多半加载没事
+        if rank == 0:
+            logger.info("loaded D")
+        # _, _, _, epoch_str = utils.load_checkpoint(utils.latest_checkpoint_path(hps.model_dir, "G_*.pth"), net_g, optim_g,load_opt=0)
+        _, _, _, epoch_str = utils.load_checkpoint(
+            utils.latest_checkpoint_path(hps.model_dir, "G_*.pth"), net_g, optim_g
+        )
+        global_step = (epoch_str - 1) * len(train_loader)
+        # epoch_str = 1
+        # global_step = 0
+    except:  # 如果首次不能加载，加载pretrain
+        # traceback.print_exc()
+        epoch_str = 1
+        global_step = 0
+        if hps.pretrainG != "":
+            if rank == 0:
+                logger.info("loaded pretrained %s" % (hps.pretrainG))
+            if hasattr(net_g, "module"):
+                logger.info(
+                    net_g.module.load_state_dict(
+                        torch.load(hps.pretrainG, map_location="cpu")["model"]
+                    )
+                )  ##测试不加载优化器
+            else:
+                logger.info(
+                    net_g.load_state_dict(
+                        torch.load(hps.pretrainG, map_location="cpu")["model"]
+                    )
+                )  ##测试不加载优化器
+        if hps.pretrainD != "":
+            if rank == 0:
+                logger.info("loaded pretrained %s" % (hps.pretrainD))
+            if hasattr(net_d, "module"):
+                logger.info(
+                    net_d.module.load_state_dict(
+                        torch.load(hps.pretrainD, map_location="cpu")["model"]
+                    )
+                )
+            else:
+                logger.info(
+                    net_d.load_state_dict(
+                        torch.load(hps.pretrainD, map_location="cpu")["model"]
+                    )
+                )
+
+    scheduler_g = torch.optim.lr_scheduler.ExponentialLR(
+        optim_g, gamma=hps.train.lr_decay, last_epoch=epoch_str - 2
+    )
+    scheduler_d = torch.optim.lr_scheduler.ExponentialLR(
+        optim_d, gamma=hps.train.lr_decay, last_epoch=epoch_str - 2
+    )
+
+    scaler = GradScaler(enabled=hps.train.fp16_run)
+
+    cache = []
+    for epoch in range(epoch_str, hps.train.epochs + 1):
+        if rank == 0:
+            train_and_evaluate(
+                rank,
+                epoch,
+                hps,
+                [net_g, net_d],
+                [optim_g, optim_d],
+                [scheduler_g, scheduler_d],
+                scaler,
+                [train_loader, None],
+                logger,
+                [writer, writer_eval],
+                cache,
+            )
+        else:
+            train_and_evaluate(
+                rank,
+                epoch,
+                hps,
+                [net_g, net_d],
+                [optim_g, optim_d],
+                [scheduler_g, scheduler_d],
+                scaler,
+                [train_loader, None],
+                None,
+                None,
+                cache,
+            )
+        scheduler_g.step()
+        scheduler_d.step()
+
+
+def train_and_evaluate(
+    rank, epoch, hps, nets, optims, schedulers, scaler, loaders, logger, writers, cache
+):
+    net_g, net_d = nets
+    optim_g, optim_d = optims
+    train_loader, eval_loader = loaders
+    if writers is not None:
+        writer, writer_eval = writers
+
+    train_loader.batch_sampler.set_epoch(epoch)
+    global global_step
+
+    net_g.train()
+    net_d.train()
+
+    # Prepare data iterator
+    if hps.if_cache_data_in_gpu == True:
+        # Use Cache
+        data_iterator = cache
+        if cache == []:
+            # Make new cache
+            for batch_idx, info in enumerate(train_loader):
+                # Unpack
+                if hps.if_f0 == 1:
+                    (
+                        phone,
+                        phone_lengths,
+                        pitch,
+                        pitchf,
+                        spec,
+                        spec_lengths,
+                        wave,
+                        wave_lengths,
+                        sid,
+                    ) = info
+                else:
+                    (
+                        phone,
+                        phone_lengths,
+                        spec,
+                        spec_lengths,
+                        wave,
+                        wave_lengths,
+                        sid,
+                    ) = info
+                # Load on CUDA
+                if torch.cuda.is_available():
+                    phone = phone.cuda(rank, non_blocking=True)
+                    phone_lengths = phone_lengths.cuda(rank, non_blocking=True)
+                    if hps.if_f0 == 1:
+                        pitch = pitch.cuda(rank, non_blocking=True)
+                        pitchf = pitchf.cuda(rank, non_blocking=True)
+                    sid = sid.cuda(rank, non_blocking=True)
+                    spec = spec.cuda(rank, non_blocking=True)
+                    spec_lengths = spec_lengths.cuda(rank, non_blocking=True)
+                    wave = wave.cuda(rank, non_blocking=True)
+                    wave_lengths = wave_lengths.cuda(rank, non_blocking=True)
+                # Cache on list
+                if hps.if_f0 == 1:
+                    cache.append(
+                        (
+                            batch_idx,
+                            (
+                                phone,
+                                phone_lengths,
+                                pitch,
+                                pitchf,
+                                spec,
+                                spec_lengths,
+                                wave,
+                                wave_lengths,
+                                sid,
+                            ),
+                        )
+                    )
+                else:
+                    cache.append(
+                        (
+                            batch_idx,
+                            (
+                                phone,
+                                phone_lengths,
+                                spec,
+                                spec_lengths,
+                                wave,
+                                wave_lengths,
+                                sid,
+                            ),
+                        )
+                    )
+        else:
+            # Load shuffled cache
+            shuffle(cache)
+    else:
+        # Loader
+        data_iterator = enumerate(train_loader)
+
+    # Run steps
+    epoch_recorder = EpochRecorder()
+    for batch_idx, info in data_iterator:
+        # Data
+        ## Unpack
+        if hps.if_f0 == 1:
+            (
+                phone,
+                phone_lengths,
+                pitch,
+                pitchf,
+                spec,
+                spec_lengths,
+                wave,
+                wave_lengths,
+                sid,
+            ) = info
+        else:
+            phone, phone_lengths, spec, spec_lengths, wave, wave_lengths, sid = info
+        ## Load on CUDA
+        if (hps.if_cache_data_in_gpu == False) and torch.cuda.is_available():
+            phone = phone.cuda(rank, non_blocking=True)
+            phone_lengths = phone_lengths.cuda(rank, non_blocking=True)
+            if hps.if_f0 == 1:
+                pitch = pitch.cuda(rank, non_blocking=True)
+                pitchf = pitchf.cuda(rank, non_blocking=True)
+            sid = sid.cuda(rank, non_blocking=True)
+            spec = spec.cuda(rank, non_blocking=True)
+            spec_lengths = spec_lengths.cuda(rank, non_blocking=True)
+            wave = wave.cuda(rank, non_blocking=True)
+            # wave_lengths = wave_lengths.cuda(rank, non_blocking=True)
+
+        # Calculate
+        with autocast(enabled=hps.train.fp16_run):
+            if hps.if_f0 == 1:
+                (
+                    y_hat,
+                    ids_slice,
+                    x_mask,
+                    z_mask,
+                    (z, z_p, m_p, logs_p, m_q, logs_q),
+                ) = net_g(phone, phone_lengths, pitch, pitchf, spec, spec_lengths, sid)
+            else:
+                (
+                    y_hat,
+                    ids_slice,
+                    x_mask,
+                    z_mask,
+                    (z, z_p, m_p, logs_p, m_q, logs_q),
+                ) = net_g(phone, phone_lengths, spec, spec_lengths, sid)
+            mel = spec_to_mel_torch(
+                spec,
+                hps.data.filter_length,
+                hps.data.n_mel_channels,
+                hps.data.sampling_rate,
+                hps.data.mel_fmin,
+                hps.data.mel_fmax,
+            )
+            y_mel = commons.slice_segments(
+                mel, ids_slice, hps.train.segment_size // hps.data.hop_length
+            )
+            with autocast(enabled=False):
+                y_hat_mel = mel_spectrogram_torch(
+                    y_hat.float().squeeze(1),
+                    hps.data.filter_length,
+                    hps.data.n_mel_channels,
+                    hps.data.sampling_rate,
+                    hps.data.hop_length,
+                    hps.data.win_length,
+                    hps.data.mel_fmin,
+                    hps.data.mel_fmax,
+                )
+            if hps.train.fp16_run == True:
+                y_hat_mel = y_hat_mel.half()
+            wave = commons.slice_segments(
+                wave, ids_slice * hps.data.hop_length, hps.train.segment_size
+            )  # slice
+
+            # Discriminator
+            y_d_hat_r, y_d_hat_g, _, _ = net_d(wave, y_hat.detach())
+            with autocast(enabled=False):
+                loss_disc, losses_disc_r, losses_disc_g = discriminator_loss(
+                    y_d_hat_r, y_d_hat_g
+                )
+        optim_d.zero_grad()
+        scaler.scale(loss_disc).backward()
+        scaler.unscale_(optim_d)
+        grad_norm_d = commons.clip_grad_value_(net_d.parameters(), None)
+        scaler.step(optim_d)
+
+        with autocast(enabled=hps.train.fp16_run):
+            # Generator
+            y_d_hat_r, y_d_hat_g, fmap_r, fmap_g = net_d(wave, y_hat)
+            with autocast(enabled=False):
+                loss_mel = F.l1_loss(y_mel, y_hat_mel) * hps.train.c_mel
+                loss_kl = kl_loss(z_p, logs_q, m_p, logs_p, z_mask) * hps.train.c_kl
+                loss_fm = feature_loss(fmap_r, fmap_g)
+                loss_gen, losses_gen = generator_loss(y_d_hat_g)
+                loss_gen_all = loss_gen + loss_fm + loss_mel + loss_kl
+        optim_g.zero_grad()
+        scaler.scale(loss_gen_all).backward()
+        scaler.unscale_(optim_g)
+        grad_norm_g = commons.clip_grad_value_(net_g.parameters(), None)
+        scaler.step(optim_g)
+        scaler.update()
+
+        if rank == 0:
+            if global_step % hps.train.log_interval == 0:
+                lr = optim_g.param_groups[0]["lr"]
+                logger.info(
+                    "Train Epoch: {} [{:.0f}%]".format(
+                        epoch, 100.0 * batch_idx / len(train_loader)
+                    )
+                )
+                # Amor For Tensorboard display
+                if loss_mel > 75:
+                    loss_mel = 75
+                if loss_kl > 9:
+                    loss_kl = 9
+
+                logger.info([global_step, lr])
+                logger.info(
+                    f"loss_disc={loss_disc:.3f}, loss_gen={loss_gen:.3f}, loss_fm={loss_fm:.3f},loss_mel={loss_mel:.3f}, loss_kl={loss_kl:.3f}"
+                )
+                scalar_dict = {
+                    "loss/g/total": loss_gen_all,
+                    "loss/d/total": loss_disc,
+                    "learning_rate": lr,
+                    "grad_norm_d": grad_norm_d,
+                    "grad_norm_g": grad_norm_g,
+                }
+                scalar_dict.update(
+                    {
+                        "loss/g/fm": loss_fm,
+                        "loss/g/mel": loss_mel,
+                        "loss/g/kl": loss_kl,
+                    }
+                )
+
+                scalar_dict.update(
+                    {"loss/g/{}".format(i): v for i, v in enumerate(losses_gen)}
+                )
+                scalar_dict.update(
+                    {"loss/d_r/{}".format(i): v for i, v in enumerate(losses_disc_r)}
+                )
+                scalar_dict.update(
+                    {"loss/d_g/{}".format(i): v for i, v in enumerate(losses_disc_g)}
+                )
+                image_dict = {
+                    "slice/mel_org": utils.plot_spectrogram_to_numpy(
+                        y_mel[0].data.cpu().numpy()
+                    ),
+                    "slice/mel_gen": utils.plot_spectrogram_to_numpy(
+                        y_hat_mel[0].data.cpu().numpy()
+                    ),
+                    "all/mel": utils.plot_spectrogram_to_numpy(
+                        mel[0].data.cpu().numpy()
+                    ),
+                }
+                utils.summarize(
+                    writer=writer,
+                    global_step=global_step,
+                    images=image_dict,
+                    scalars=scalar_dict,
+                )
+        global_step += 1
+    # /Run steps
+
+    if epoch % hps.save_every_epoch == 0 and rank == 0:
+        if hps.if_latest == 0:
+            utils.save_checkpoint(
+                net_g,
+                optim_g,
+                hps.train.learning_rate,
+                epoch,
+                os.path.join(hps.model_dir, "G_{}.pth".format(global_step)),
+            )
+            utils.save_checkpoint(
+                net_d,
+                optim_d,
+                hps.train.learning_rate,
+                epoch,
+                os.path.join(hps.model_dir, "D_{}.pth".format(global_step)),
+            )
+        else:
+            utils.save_checkpoint(
+                net_g,
+                optim_g,
+                hps.train.learning_rate,
+                epoch,
+                os.path.join(hps.model_dir, "G_{}.pth".format(2333333)),
+            )
+            utils.save_checkpoint(
+                net_d,
+                optim_d,
+                hps.train.learning_rate,
+                epoch,
+                os.path.join(hps.model_dir, "D_{}.pth".format(2333333)),
+            )
+        if rank == 0 and hps.save_every_weights == "1":
+            if hasattr(net_g, "module"):
+                ckpt = net_g.module.state_dict()
+            else:
+                ckpt = net_g.state_dict()
+            logger.info(
+                "saving ckpt %s_e%s:%s"
+                % (
+                    hps.name,
+                    epoch,
+                    savee(
+                        ckpt,
+                        hps.sample_rate,
+                        hps.if_f0,
+                        hps.name + "_e%s_s%s" % (epoch, global_step),
+                        epoch,
+                        hps.version,
+                        hps,
+                    ),
+                )
+            )
+    
+    stopbtn = False
+    try:
+        with open("csvdb/stop.csv", 'r') as csv_file:
+            stopbtn_str = next(csv.reader(csv_file), [None])[0]
+            if stopbtn_str is not None: stopbtn = stopbtn_str.lower() == 'true'
+    except (ValueError, TypeError, FileNotFoundError, IndexError) as e:
+        print(f"Handling exception: {e}")
+        stopbtn = False
+
+    if stopbtn:
+        logger.info("Stop Button was pressed. The program is closed.")
+        ckpt = net_g.module.state_dict() if hasattr(net_g, "module") else net_g.state_dict()
+        logger.info(
+            "saving final ckpt:%s"
+            % (
+                savee(
+                    ckpt, hps.sample_rate, hps.if_f0, hps.name, epoch, hps.version, hps
+                )
+            )
+        )
+        sleep(1)
+        reset_stop_flag()
+        os._exit(2333333)
+
+    if rank == 0:
+        logger.info("====> Epoch: {} {}".format(epoch, epoch_recorder.record()))
+    if epoch >= hps.total_epoch and rank == 0:
+        logger.info("Training is done. The program is closed.")
+
+        if hasattr(net_g, "module"):
+            ckpt = net_g.module.state_dict()
+        else:
+            ckpt = net_g.state_dict()
+        logger.info(
+            "saving final ckpt:%s"
+            % (
+                savee(
+                    ckpt, hps.sample_rate, hps.if_f0, hps.name, epoch, hps.version, hps
+                )
+            )
+        )
+        sleep(1)
+        os._exit(2333333)
+
+
+if __name__ == "__main__":
+    torch.multiprocessing.set_start_method("spawn")
+    main()
diff --git a/infer/modules/uvr5/mdxnet.py b/infer/modules/uvr5/mdxnet.py
new file mode 100644
index 0000000000000000000000000000000000000000..86a066893ad99cfed77788027a9deb8ed486a7f2
--- /dev/null
+++ b/infer/modules/uvr5/mdxnet.py
@@ -0,0 +1,246 @@
+import os
+import logging
+
+logger = logging.getLogger(__name__)
+
+import librosa
+import numpy as np
+import soundfile as sf
+import torch
+from tqdm import tqdm
+
+cpu = torch.device("cpu")
+
+
+class ConvTDFNetTrim:
+    def __init__(
+        self, device, model_name, target_name, L, dim_f, dim_t, n_fft, hop=1024
+    ):
+        super(ConvTDFNetTrim, self).__init__()
+
+        self.dim_f = dim_f
+        self.dim_t = 2**dim_t
+        self.n_fft = n_fft
+        self.hop = hop
+        self.n_bins = self.n_fft // 2 + 1
+        self.chunk_size = hop * (self.dim_t - 1)
+        self.window = torch.hann_window(window_length=self.n_fft, periodic=True).to(
+            device
+        )
+        self.target_name = target_name
+        self.blender = "blender" in model_name
+
+        self.dim_c = 4
+        out_c = self.dim_c * 4 if target_name == "*" else self.dim_c
+        self.freq_pad = torch.zeros(
+            [1, out_c, self.n_bins - self.dim_f, self.dim_t]
+        ).to(device)
+
+        self.n = L // 2
+
+    def stft(self, x):
+        x = x.reshape([-1, self.chunk_size])
+        x = torch.stft(
+            x,
+            n_fft=self.n_fft,
+            hop_length=self.hop,
+            window=self.window,
+            center=True,
+            return_complex=True,
+        )
+        x = torch.view_as_real(x)
+        x = x.permute([0, 3, 1, 2])
+        x = x.reshape([-1, 2, 2, self.n_bins, self.dim_t]).reshape(
+            [-1, self.dim_c, self.n_bins, self.dim_t]
+        )
+        return x[:, :, : self.dim_f]
+
+    def istft(self, x, freq_pad=None):
+        freq_pad = (
+            self.freq_pad.repeat([x.shape[0], 1, 1, 1])
+            if freq_pad is None
+            else freq_pad
+        )
+        x = torch.cat([x, freq_pad], -2)
+        c = 4 * 2 if self.target_name == "*" else 2
+        x = x.reshape([-1, c, 2, self.n_bins, self.dim_t]).reshape(
+            [-1, 2, self.n_bins, self.dim_t]
+        )
+        x = x.permute([0, 2, 3, 1])
+        x = x.contiguous()
+        x = torch.view_as_complex(x)
+        x = torch.istft(
+            x, n_fft=self.n_fft, hop_length=self.hop, window=self.window, center=True
+        )
+        return x.reshape([-1, c, self.chunk_size])
+
+
+def get_models(device, dim_f, dim_t, n_fft):
+    return ConvTDFNetTrim(
+        device=device,
+        model_name="Conv-TDF",
+        target_name="vocals",
+        L=11,
+        dim_f=dim_f,
+        dim_t=dim_t,
+        n_fft=n_fft,
+    )
+
+
+class Predictor:
+    def __init__(self, args):
+        import onnxruntime as ort
+
+        logger.info(ort.get_available_providers())
+        self.args = args
+        self.model_ = get_models(
+            device=cpu, dim_f=args.dim_f, dim_t=args.dim_t, n_fft=args.n_fft
+        )
+        self.model = ort.InferenceSession(
+            os.path.join(args.onnx, self.model_.target_name + ".onnx"),
+            providers=[
+                "CUDAExecutionProvider",
+                "DmlExecutionProvider",
+                "CPUExecutionProvider",
+            ],
+        )
+        logger.info("ONNX load done")
+
+    def demix(self, mix):
+        samples = mix.shape[-1]
+        margin = self.args.margin
+        chunk_size = self.args.chunks * 44100
+        assert not margin == 0, "margin cannot be zero!"
+        if margin > chunk_size:
+            margin = chunk_size
+
+        segmented_mix = {}
+
+        if self.args.chunks == 0 or samples < chunk_size:
+            chunk_size = samples
+
+        counter = -1
+        for skip in range(0, samples, chunk_size):
+            counter += 1
+
+            s_margin = 0 if counter == 0 else margin
+            end = min(skip + chunk_size + margin, samples)
+
+            start = skip - s_margin
+
+            segmented_mix[skip] = mix[:, start:end].copy()
+            if end == samples:
+                break
+
+        sources = self.demix_base(segmented_mix, margin_size=margin)
+        """
+        mix:(2,big_sample)
+        segmented_mix:offset->(2,small_sample)
+        sources:(1,2,big_sample)
+        """
+        return sources
+
+    def demix_base(self, mixes, margin_size):
+        chunked_sources = []
+        progress_bar = tqdm(total=len(mixes))
+        progress_bar.set_description("Processing")
+        for mix in mixes:
+            cmix = mixes[mix]
+            sources = []
+            n_sample = cmix.shape[1]
+            model = self.model_
+            trim = model.n_fft // 2
+            gen_size = model.chunk_size - 2 * trim
+            pad = gen_size - n_sample % gen_size
+            mix_p = np.concatenate(
+                (np.zeros((2, trim)), cmix, np.zeros((2, pad)), np.zeros((2, trim))), 1
+            )
+            mix_waves = []
+            i = 0
+            while i < n_sample + pad:
+                waves = np.array(mix_p[:, i : i + model.chunk_size])
+                mix_waves.append(waves)
+                i += gen_size
+            mix_waves = torch.tensor(mix_waves, dtype=torch.float32).to(cpu)
+            with torch.no_grad():
+                _ort = self.model
+                spek = model.stft(mix_waves)
+                if self.args.denoise:
+                    spec_pred = (
+                        -_ort.run(None, {"input": -spek.cpu().numpy()})[0] * 0.5
+                        + _ort.run(None, {"input": spek.cpu().numpy()})[0] * 0.5
+                    )
+                    tar_waves = model.istft(torch.tensor(spec_pred))
+                else:
+                    tar_waves = model.istft(
+                        torch.tensor(_ort.run(None, {"input": spek.cpu().numpy()})[0])
+                    )
+                tar_signal = (
+                    tar_waves[:, :, trim:-trim]
+                    .transpose(0, 1)
+                    .reshape(2, -1)
+                    .numpy()[:, :-pad]
+                )
+
+                start = 0 if mix == 0 else margin_size
+                end = None if mix == list(mixes.keys())[::-1][0] else -margin_size
+                if margin_size == 0:
+                    end = None
+                sources.append(tar_signal[:, start:end])
+
+                progress_bar.update(1)
+
+            chunked_sources.append(sources)
+        _sources = np.concatenate(chunked_sources, axis=-1)
+        # del self.model
+        progress_bar.close()
+        return _sources
+
+    def prediction(self, m, vocal_root, others_root, format):
+        os.makedirs(vocal_root, exist_ok=True)
+        os.makedirs(others_root, exist_ok=True)
+        basename = os.path.basename(m)
+        mix, rate = librosa.load(m, mono=False, sr=44100)
+        if mix.ndim == 1:
+            mix = np.asfortranarray([mix, mix])
+        mix = mix.T
+        sources = self.demix(mix.T)
+        opt = sources[0].T
+        if format in ["wav", "flac"]:
+            sf.write(
+                "%s/%s_main_vocal.%s" % (vocal_root, basename, format), mix - opt, rate
+            )
+            sf.write("%s/%s_others.%s" % (others_root, basename, format), opt, rate)
+        else:
+            path_vocal = "%s/%s_main_vocal.wav" % (vocal_root, basename)
+            path_other = "%s/%s_others.wav" % (others_root, basename)
+            sf.write(path_vocal, mix - opt, rate)
+            sf.write(path_other, opt, rate)
+            if os.path.exists(path_vocal):
+                os.system(
+                    "ffmpeg -i %s -vn %s -q:a 2 -y"
+                    % (path_vocal, path_vocal[:-4] + ".%s" % format)
+                )
+            if os.path.exists(path_other):
+                os.system(
+                    "ffmpeg -i %s -vn %s -q:a 2 -y"
+                    % (path_other, path_other[:-4] + ".%s" % format)
+                )
+
+
+class MDXNetDereverb:
+    def __init__(self, chunks, device):
+        self.onnx = "assets/uvr5_weights/onnx_dereverb_By_FoxJoy"
+        self.shifts = 10  # 'Predict with randomised equivariant stabilisation'
+        self.mixing = "min_mag"  # ['default','min_mag','max_mag']
+        self.chunks = chunks
+        self.margin = 44100
+        self.dim_t = 9
+        self.dim_f = 3072
+        self.n_fft = 6144
+        self.denoise = True
+        self.pred = Predictor(self)
+        self.device = device
+
+    def path_audio(self, input, vocal_root, others_root, format):
+        self.pred.prediction(input, vocal_root, others_root, format)
diff --git a/infer/modules/uvr5/modules.py b/infer/modules/uvr5/modules.py
new file mode 100644
index 0000000000000000000000000000000000000000..f63ac6a794100cc95da21dcba78b23377a1f133d
--- /dev/null
+++ b/infer/modules/uvr5/modules.py
@@ -0,0 +1,107 @@
+import os
+import traceback
+import logging
+
+logger = logging.getLogger(__name__)
+
+import ffmpeg
+import torch
+
+from configs.config import Config
+from infer.modules.uvr5.mdxnet import MDXNetDereverb
+from infer.modules.uvr5.preprocess import AudioPre, AudioPreDeEcho
+
+config = Config()
+
+
+def uvr(model_name, inp_root, save_root_vocal, paths, save_root_ins, agg, format0):
+    infos = []
+    try:
+        inp_root = inp_root.strip(" ").strip('"').strip("\n").strip('"').strip(" ")
+        save_root_vocal = (
+            save_root_vocal.strip(" ").strip('"').strip("\n").strip('"').strip(" ")
+        )
+        save_root_ins = (
+            save_root_ins.strip(" ").strip('"').strip("\n").strip('"').strip(" ")
+        )
+        if model_name == "onnx_dereverb_By_FoxJoy":
+            pre_fun = MDXNetDereverb(15, config.device)
+        else:
+            func = AudioPre if "DeEcho" not in model_name else AudioPreDeEcho
+            pre_fun = func(
+                agg=int(agg),
+                model_path=os.path.join(
+                    os.getenv("weight_uvr5_root"), model_name + ".pth"
+                ),
+                device=config.device,
+                is_half=config.is_half,
+            )
+        if inp_root != "":
+            paths = [os.path.join(inp_root, name) for name in os.listdir(inp_root)]
+        else:
+            paths = [path.name for path in paths]
+        for path in paths:
+            inp_path = os.path.join(inp_root, path)
+            need_reformat = 1
+            done = 0
+            try:
+                info = ffmpeg.probe(inp_path, cmd="ffprobe")
+                if (
+                    info["streams"][0]["channels"] == 2
+                    and info["streams"][0]["sample_rate"] == "44100"
+                ):
+                    need_reformat = 0
+                    pre_fun._path_audio_(
+                        inp_path, save_root_ins, save_root_vocal, format0
+                    )
+                    done = 1
+            except:
+                need_reformat = 1
+                traceback.print_exc()
+            if need_reformat == 1:
+                tmp_path = "%s/%s.reformatted.wav" % (
+                    os.path.join(os.environ["TEMP"]),
+                    os.path.basename(inp_path),
+                )
+                os.system(
+                    "ffmpeg -i %s -vn -acodec pcm_s16le -ac 2 -ar 44100 %s -y"
+                    % (inp_path, tmp_path)
+                )
+                inp_path = tmp_path
+            try:
+                if done == 0:
+                    pre_fun.path_audio(
+                        inp_path, save_root_ins, save_root_vocal, format0
+                    )
+                infos.append("%s->Success" % (os.path.basename(inp_path)))
+                yield "\n".join(infos)
+            except:
+                try:
+                    if done == 0:
+                        pre_fun._path_audio_(
+                            inp_path, save_root_ins, save_root_vocal, format0
+                        )
+                    infos.append("%s->Success" % (os.path.basename(inp_path)))
+                    yield "\n".join(infos)
+                except:
+                    infos.append(
+                        "%s->%s" % (os.path.basename(inp_path), traceback.format_exc())
+                    )
+                    yield "\n".join(infos)
+    except:
+        infos.append(traceback.format_exc())
+        yield "\n".join(infos)
+    finally:
+        try:
+            if model_name == "onnx_dereverb_By_FoxJoy":
+                del pre_fun.pred.model
+                del pre_fun.pred.model_
+            else:
+                del pre_fun.model
+                del pre_fun
+        except:
+            traceback.print_exc()
+        if torch.cuda.is_available():
+            torch.cuda.empty_cache()
+            logger.info("Executed torch.cuda.empty_cache()")
+    yield "\n".join(infos)
diff --git a/infer/modules/uvr5/preprocess.py b/infer/modules/uvr5/preprocess.py
new file mode 100644
index 0000000000000000000000000000000000000000..19f11110ea822eeb140fb885c600536290a1adff
--- /dev/null
+++ b/infer/modules/uvr5/preprocess.py
@@ -0,0 +1,346 @@
+import os
+import logging
+
+logger = logging.getLogger(__name__)
+
+import librosa
+import numpy as np
+import soundfile as sf
+import torch
+
+from infer.lib.uvr5_pack.lib_v5 import nets_61968KB as Nets
+from infer.lib.uvr5_pack.lib_v5 import spec_utils
+from infer.lib.uvr5_pack.lib_v5.model_param_init import ModelParameters
+from infer.lib.uvr5_pack.lib_v5.nets_new import CascadedNet
+from infer.lib.uvr5_pack.utils import inference
+
+
+class AudioPre:
+    def __init__(self, agg, model_path, device, is_half):
+        self.model_path = model_path
+        self.device = device
+        self.data = {
+            # Processing Options
+            "postprocess": False,
+            "tta": False,
+            # Constants
+            "window_size": 512,
+            "agg": agg,
+            "high_end_process": "mirroring",
+        }
+        mp = ModelParameters("infer/lib/uvr5_pack/lib_v5/modelparams/4band_v2.json")
+        model = Nets.CascadedASPPNet(mp.param["bins"] * 2)
+        cpk = torch.load(model_path, map_location="cpu")
+        model.load_state_dict(cpk)
+        model.eval()
+        if is_half:
+            model = model.half().to(device)
+        else:
+            model = model.to(device)
+
+        self.mp = mp
+        self.model = model
+
+    def _path_audio_(self, music_file, ins_root=None, vocal_root=None, format="flac"):
+        if ins_root is None and vocal_root is None:
+            return "No save root."
+        name = os.path.basename(music_file)
+        if ins_root is not None:
+            os.makedirs(ins_root, exist_ok=True)
+        if vocal_root is not None:
+            os.makedirs(vocal_root, exist_ok=True)
+        X_wave, y_wave, X_spec_s, y_spec_s = {}, {}, {}, {}
+        bands_n = len(self.mp.param["band"])
+        # print(bands_n)
+        for d in range(bands_n, 0, -1):
+            bp = self.mp.param["band"][d]
+            if d == bands_n:  # high-end band
+                (
+                    X_wave[d],
+                    _,
+                ) = librosa.core.load(  # 理论上librosa读取可能对某些音频有bug，应该上ffmpeg读取，但是太麻烦了弃坑
+                    music_file,
+                    bp["sr"],
+                    False,
+                    dtype=np.float32,
+                    res_type=bp["res_type"],
+                )
+                if X_wave[d].ndim == 1:
+                    X_wave[d] = np.asfortranarray([X_wave[d], X_wave[d]])
+            else:  # lower bands
+                X_wave[d] = librosa.core.resample(
+                    X_wave[d + 1],
+                    self.mp.param["band"][d + 1]["sr"],
+                    bp["sr"],
+                    res_type=bp["res_type"],
+                )
+            # Stft of wave source
+            X_spec_s[d] = spec_utils.wave_to_spectrogram_mt(
+                X_wave[d],
+                bp["hl"],
+                bp["n_fft"],
+                self.mp.param["mid_side"],
+                self.mp.param["mid_side_b2"],
+                self.mp.param["reverse"],
+            )
+            # pdb.set_trace()
+            if d == bands_n and self.data["high_end_process"] != "none":
+                input_high_end_h = (bp["n_fft"] // 2 - bp["crop_stop"]) + (
+                    self.mp.param["pre_filter_stop"] - self.mp.param["pre_filter_start"]
+                )
+                input_high_end = X_spec_s[d][
+                    :, bp["n_fft"] // 2 - input_high_end_h : bp["n_fft"] // 2, :
+                ]
+
+        X_spec_m = spec_utils.combine_spectrograms(X_spec_s, self.mp)
+        aggresive_set = float(self.data["agg"] / 100)
+        aggressiveness = {
+            "value": aggresive_set,
+            "split_bin": self.mp.param["band"][1]["crop_stop"],
+        }
+        with torch.no_grad():
+            pred, X_mag, X_phase = inference(
+                X_spec_m, self.device, self.model, aggressiveness, self.data
+            )
+        # Postprocess
+        if self.data["postprocess"]:
+            pred_inv = np.clip(X_mag - pred, 0, np.inf)
+            pred = spec_utils.mask_silence(pred, pred_inv)
+        y_spec_m = pred * X_phase
+        v_spec_m = X_spec_m - y_spec_m
+
+        if ins_root is not None:
+            if self.data["high_end_process"].startswith("mirroring"):
+                input_high_end_ = spec_utils.mirroring(
+                    self.data["high_end_process"], y_spec_m, input_high_end, self.mp
+                )
+                wav_instrument = spec_utils.cmb_spectrogram_to_wave(
+                    y_spec_m, self.mp, input_high_end_h, input_high_end_
+                )
+            else:
+                wav_instrument = spec_utils.cmb_spectrogram_to_wave(y_spec_m, self.mp)
+            logger.info("%s instruments done" % name)
+            if format in ["wav", "flac"]:
+                sf.write(
+                    os.path.join(
+                        ins_root,
+                        "instrument_{}_{}.{}".format(name, self.data["agg"], format),
+                    ),
+                    (np.array(wav_instrument) * 32768).astype("int16"),
+                    self.mp.param["sr"],
+                )  #
+            else:
+                path = os.path.join(
+                    ins_root, "instrument_{}_{}.wav".format(name, self.data["agg"])
+                )
+                sf.write(
+                    path,
+                    (np.array(wav_instrument) * 32768).astype("int16"),
+                    self.mp.param["sr"],
+                )
+                if os.path.exists(path):
+                    os.system(
+                        "ffmpeg -i %s -vn %s -q:a 2 -y"
+                        % (path, path[:-4] + ".%s" % format)
+                    )
+        if vocal_root is not None:
+            if self.data["high_end_process"].startswith("mirroring"):
+                input_high_end_ = spec_utils.mirroring(
+                    self.data["high_end_process"], v_spec_m, input_high_end, self.mp
+                )
+                wav_vocals = spec_utils.cmb_spectrogram_to_wave(
+                    v_spec_m, self.mp, input_high_end_h, input_high_end_
+                )
+            else:
+                wav_vocals = spec_utils.cmb_spectrogram_to_wave(v_spec_m, self.mp)
+            logger.info("%s vocals done" % name)
+            if format in ["wav", "flac"]:
+                sf.write(
+                    os.path.join(
+                        vocal_root,
+                        "vocal_{}_{}.{}".format(name, self.data["agg"], format),
+                    ),
+                    (np.array(wav_vocals) * 32768).astype("int16"),
+                    self.mp.param["sr"],
+                )
+            else:
+                path = os.path.join(
+                    vocal_root, "vocal_{}_{}.wav".format(name, self.data["agg"])
+                )
+                sf.write(
+                    path,
+                    (np.array(wav_vocals) * 32768).astype("int16"),
+                    self.mp.param["sr"],
+                )
+                if os.path.exists(path):
+                    os.system(
+                        "ffmpeg -i %s -vn %s -q:a 2 -y"
+                        % (path, path[:-4] + ".%s" % format)
+                    )
+
+
+class AudioPreDeEcho:
+    def __init__(self, agg, model_path, device, is_half):
+        self.model_path = model_path
+        self.device = device
+        self.data = {
+            # Processing Options
+            "postprocess": False,
+            "tta": False,
+            # Constants
+            "window_size": 512,
+            "agg": agg,
+            "high_end_process": "mirroring",
+        }
+        mp = ModelParameters("infer/lib/uvr5_pack/lib_v5/modelparams/4band_v3.json")
+        nout = 64 if "DeReverb" in model_path else 48
+        model = CascadedNet(mp.param["bins"] * 2, nout)
+        cpk = torch.load(model_path, map_location="cpu")
+        model.load_state_dict(cpk)
+        model.eval()
+        if is_half:
+            model = model.half().to(device)
+        else:
+            model = model.to(device)
+
+        self.mp = mp
+        self.model = model
+
+    def _path_audio_(
+        self, music_file, vocal_root=None, ins_root=None, format="flac"
+    ):  # 3个VR模型vocal和ins是反的
+        if ins_root is None and vocal_root is None:
+            return "No save root."
+        name = os.path.basename(music_file)
+        if ins_root is not None:
+            os.makedirs(ins_root, exist_ok=True)
+        if vocal_root is not None:
+            os.makedirs(vocal_root, exist_ok=True)
+        X_wave, y_wave, X_spec_s, y_spec_s = {}, {}, {}, {}
+        bands_n = len(self.mp.param["band"])
+        # print(bands_n)
+        for d in range(bands_n, 0, -1):
+            bp = self.mp.param["band"][d]
+            if d == bands_n:  # high-end band
+                (
+                    X_wave[d],
+                    _,
+                ) = librosa.core.load(  # 理论上librosa读取可能对某些音频有bug，应该上ffmpeg读取，但是太麻烦了弃坑
+                    music_file,
+                    bp["sr"],
+                    False,
+                    dtype=np.float32,
+                    res_type=bp["res_type"],
+                )
+                if X_wave[d].ndim == 1:
+                    X_wave[d] = np.asfortranarray([X_wave[d], X_wave[d]])
+            else:  # lower bands
+                X_wave[d] = librosa.core.resample(
+                    X_wave[d + 1],
+                    self.mp.param["band"][d + 1]["sr"],
+                    bp["sr"],
+                    res_type=bp["res_type"],
+                )
+            # Stft of wave source
+            X_spec_s[d] = spec_utils.wave_to_spectrogram_mt(
+                X_wave[d],
+                bp["hl"],
+                bp["n_fft"],
+                self.mp.param["mid_side"],
+                self.mp.param["mid_side_b2"],
+                self.mp.param["reverse"],
+            )
+            # pdb.set_trace()
+            if d == bands_n and self.data["high_end_process"] != "none":
+                input_high_end_h = (bp["n_fft"] // 2 - bp["crop_stop"]) + (
+                    self.mp.param["pre_filter_stop"] - self.mp.param["pre_filter_start"]
+                )
+                input_high_end = X_spec_s[d][
+                    :, bp["n_fft"] // 2 - input_high_end_h : bp["n_fft"] // 2, :
+                ]
+
+        X_spec_m = spec_utils.combine_spectrograms(X_spec_s, self.mp)
+        aggresive_set = float(self.data["agg"] / 100)
+        aggressiveness = {
+            "value": aggresive_set,
+            "split_bin": self.mp.param["band"][1]["crop_stop"],
+        }
+        with torch.no_grad():
+            pred, X_mag, X_phase = inference(
+                X_spec_m, self.device, self.model, aggressiveness, self.data
+            )
+        # Postprocess
+        if self.data["postprocess"]:
+            pred_inv = np.clip(X_mag - pred, 0, np.inf)
+            pred = spec_utils.mask_silence(pred, pred_inv)
+        y_spec_m = pred * X_phase
+        v_spec_m = X_spec_m - y_spec_m
+
+        if ins_root is not None:
+            if self.data["high_end_process"].startswith("mirroring"):
+                input_high_end_ = spec_utils.mirroring(
+                    self.data["high_end_process"], y_spec_m, input_high_end, self.mp
+                )
+                wav_instrument = spec_utils.cmb_spectrogram_to_wave(
+                    y_spec_m, self.mp, input_high_end_h, input_high_end_
+                )
+            else:
+                wav_instrument = spec_utils.cmb_spectrogram_to_wave(y_spec_m, self.mp)
+            logger.info("%s instruments done" % name)
+            if format in ["wav", "flac"]:
+                sf.write(
+                    os.path.join(
+                        ins_root,
+                        "instrument_{}_{}.{}".format(name, self.data["agg"], format),
+                    ),
+                    (np.array(wav_instrument) * 32768).astype("int16"),
+                    self.mp.param["sr"],
+                )  #
+            else:
+                path = os.path.join(
+                    ins_root, "instrument_{}_{}.wav".format(name, self.data["agg"])
+                )
+                sf.write(
+                    path,
+                    (np.array(wav_instrument) * 32768).astype("int16"),
+                    self.mp.param["sr"],
+                )
+                if os.path.exists(path):
+                    os.system(
+                        "ffmpeg -i %s -vn %s -q:a 2 -y"
+                        % (path, path[:-4] + ".%s" % format)
+                    )
+        if vocal_root is not None:
+            if self.data["high_end_process"].startswith("mirroring"):
+                input_high_end_ = spec_utils.mirroring(
+                    self.data["high_end_process"], v_spec_m, input_high_end, self.mp
+                )
+                wav_vocals = spec_utils.cmb_spectrogram_to_wave(
+                    v_spec_m, self.mp, input_high_end_h, input_high_end_
+                )
+            else:
+                wav_vocals = spec_utils.cmb_spectrogram_to_wave(v_spec_m, self.mp)
+            logger.info("%s vocals done" % name)
+            if format in ["wav", "flac"]:
+                sf.write(
+                    os.path.join(
+                        vocal_root,
+                        "vocal_{}_{}.{}".format(name, self.data["agg"], format),
+                    ),
+                    (np.array(wav_vocals) * 32768).astype("int16"),
+                    self.mp.param["sr"],
+                )
+            else:
+                path = os.path.join(
+                    vocal_root, "vocal_{}_{}.wav".format(name, self.data["agg"])
+                )
+                sf.write(
+                    path,
+                    (np.array(wav_vocals) * 32768).astype("int16"),
+                    self.mp.param["sr"],
+                )
+                if os.path.exists(path):
+                    os.system(
+                        "ffmpeg -i %s -vn %s -q:a 2 -y"
+                        % (path, path[:-4] + ".%s" % format)
+                    )
diff --git a/infer/modules/vc/__init__.py b/infer/modules/vc/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/infer/modules/vc/modules.py b/infer/modules/vc/modules.py
new file mode 100644
index 0000000000000000000000000000000000000000..458cfbe860b23bdd8f07abc2934443e6b8b01c3a
--- /dev/null
+++ b/infer/modules/vc/modules.py
@@ -0,0 +1,526 @@
+import os, sys
+import traceback
+import logging
+now_dir = os.getcwd()
+sys.path.append(now_dir)
+logger = logging.getLogger(__name__)
+import lib.globals.globals as rvc_globals
+import numpy as np
+import soundfile as sf
+import torch
+from io import BytesIO
+from infer.lib.audio import load_audio
+from infer.lib.audio import wav2
+from infer.lib.infer_pack.models import (
+    SynthesizerTrnMs256NSFsid,
+    SynthesizerTrnMs256NSFsid_nono,
+    SynthesizerTrnMs768NSFsid,
+    SynthesizerTrnMs768NSFsid_nono,
+)
+from infer.modules.vc.pipeline import Pipeline
+from infer.modules.vc.utils import *
+import time
+import scipy.io.wavfile as wavfile
+
+def note_to_hz(note_name):
+        SEMITONES = {'C': -9, 'C#': -8, 'D': -7, 'D#': -6, 'E': -5, 'F': -4, 'F#': -3, 'G': -2, 'G#': -1, 'A': 0, 'A#': 1, 'B': 2}
+        pitch_class, octave = note_name[:-1], int(note_name[-1])
+        semitone = SEMITONES[pitch_class]
+        note_number = 12 * (octave - 4) + semitone
+        frequency = 440.0 * (2.0 ** (1.0/12)) ** note_number
+        return frequency
+
+class VC:
+    def __init__(self, config):
+        self.n_spk = None
+        self.tgt_sr = None
+        self.net_g = None
+        self.pipeline = None
+        self.cpt = None
+        self.version = None
+        self.if_f0 = None
+        self.version = None
+        self.hubert_model = None
+
+        self.config = config
+
+    def get_vc(self, sid, *to_return_protect):
+        logger.info("Get sid: " + sid)
+
+        to_return_protect0 = {
+            "visible": self.if_f0 != 0,
+            "value": to_return_protect[0]
+            if self.if_f0 != 0 and to_return_protect
+            else 0.5,
+            "__type__": "update",
+        }
+        to_return_protect1 = {
+            "visible": self.if_f0 != 0,
+            "value": to_return_protect[1]
+            if self.if_f0 != 0 and to_return_protect
+            else 0.33,
+            "__type__": "update",
+        }
+
+        if not sid:
+            if self.hubert_model is not None:  # 考虑到轮询, 需要加个判断看是否 sid 是由有模型切换到无模型的
+                logger.info("Clean model cache")
+                del (
+                    self.net_g,
+                    self.n_spk,
+                    self.vc,
+                    self.hubert_model,
+                    self.tgt_sr,
+                )  # ,cpt
+                self.hubert_model = (
+                    self.net_g
+                ) = self.n_spk = self.vc = self.hubert_model = self.tgt_sr = None
+                if torch.cuda.is_available():
+                    torch.cuda.empty_cache()
+                ###楼下不这么折腾清理不干净
+                self.if_f0 = self.cpt.get("f0", 1)
+                self.version = self.cpt.get("version", "v1")
+                if self.version == "v1":
+                    if self.if_f0 == 1:
+                        self.net_g = SynthesizerTrnMs256NSFsid(
+                            *self.cpt["config"], is_half=self.config.is_half
+                        )
+                    else:
+                        self.net_g = SynthesizerTrnMs256NSFsid_nono(*self.cpt["config"])
+                elif self.version == "v2":
+                    if self.if_f0 == 1:
+                        self.net_g = SynthesizerTrnMs768NSFsid(
+                            *self.cpt["config"], is_half=self.config.is_half
+                        )
+                    else:
+                        self.net_g = SynthesizerTrnMs768NSFsid_nono(*self.cpt["config"])
+                del self.net_g, self.cpt
+                if torch.cuda.is_available():
+                    torch.cuda.empty_cache()
+            return (
+                {"visible": False, "__type__": "update"},
+                {
+                    "visible": True,
+                    "value": to_return_protect0,
+                    "__type__": "update",
+                },
+                {
+                    "visible": True,
+                    "value": to_return_protect1,
+                    "__type__": "update",
+                },
+                "",
+                "",
+            )
+        #person = f'{os.getenv("weight_root")}/{sid}'
+        person = f'{sid}'
+        #logger.info(f"Loading: {person}")
+        logger.info(f"Loading...")
+        self.cpt = torch.load(person, map_location="cpu")
+        self.tgt_sr = self.cpt["config"][-1]
+        self.cpt["config"][-3] = self.cpt["weight"]["emb_g.weight"].shape[0]  # n_spk
+        self.if_f0 = self.cpt.get("f0", 1)
+        self.version = self.cpt.get("version", "v1")
+
+        synthesizer_class = {
+            ("v1", 1): SynthesizerTrnMs256NSFsid,
+            ("v1", 0): SynthesizerTrnMs256NSFsid_nono,
+            ("v2", 1): SynthesizerTrnMs768NSFsid,
+            ("v2", 0): SynthesizerTrnMs768NSFsid_nono,
+        }
+
+        self.net_g = synthesizer_class.get(
+            (self.version, self.if_f0), SynthesizerTrnMs256NSFsid
+        )(*self.cpt["config"], is_half=self.config.is_half)
+
+        del self.net_g.enc_q
+
+        self.net_g.load_state_dict(self.cpt["weight"], strict=False)
+        self.net_g.eval().to(self.config.device)
+        if self.config.is_half:
+            self.net_g = self.net_g.half()
+        else:
+            self.net_g = self.net_g.float()
+
+        self.pipeline = Pipeline(self.tgt_sr, self.config)
+        n_spk = self.cpt["config"][-3]
+        index = {"value": get_index_path_from_model(sid), "__type__": "update"}
+        logger.info("Select index: " + index["value"])
+
+        return (
+            (
+                {"visible": False, "maximum": n_spk, "__type__": "update"},
+                to_return_protect0,
+                to_return_protect1
+            )
+            if to_return_protect
+            else {"visible": False, "maximum": n_spk, "__type__": "update"}
+        )
+    
+
+    def vc_single(
+        self,
+        sid,
+        input_audio_path0,
+        input_audio_path1,
+        f0_up_key,
+        f0_file,
+        f0_method,
+        file_index,
+        file_index2,
+        index_rate,
+        filter_radius,
+        resample_sr,
+        rms_mix_rate,
+        protect,
+        crepe_hop_length,
+        f0_min,
+        note_min,
+        f0_max,
+        note_max,
+        f0_autotune,
+    ):
+        global total_time
+        total_time = 0
+        start_time = time.time()
+        if not input_audio_path0 and not input_audio_path1:
+            return "You need to upload an audio", None
+        
+        if (not os.path.exists(input_audio_path0)) and (not os.path.exists(os.path.join(now_dir, input_audio_path0))):
+            return "Audio was not properly selected or doesn't exist", None
+        
+        input_audio_path1 = input_audio_path1 or input_audio_path0
+        print(f"\nStarting inference for '{os.path.basename(input_audio_path1)}'")
+        print("-------------------")
+        f0_up_key = int(f0_up_key)
+        if rvc_globals.NotesOrHertz and f0_method != 'rmvpe':
+            f0_min = note_to_hz(note_min) if note_min else 50
+            f0_max = note_to_hz(note_max) if note_max else 1100
+            print(f"Converted Min pitch: freq - {f0_min}\n"
+                  f"Converted Max pitch: freq - {f0_max}")
+        else:
+            f0_min = f0_min or 50
+            f0_max = f0_max or 1100
+        try:
+            input_audio_path1 = input_audio_path1 or input_audio_path0
+            print(f"Attempting to load {input_audio_path1}....")
+            audio = load_audio(file=input_audio_path1,
+                               sr=16000,
+                               DoFormant=rvc_globals.DoFormant,
+                               Quefrency=rvc_globals.Quefrency,
+                               Timbre=rvc_globals.Timbre)
+            
+            audio_max = np.abs(audio).max() / 0.95
+            if audio_max > 1:
+                audio /= audio_max
+            times = [0, 0, 0]
+
+            if self.hubert_model is None:
+                self.hubert_model = load_hubert(self.config)
+
+            try:
+                self.if_f0 = self.cpt.get("f0", 1)
+            except NameError:
+                message = "Model was not properly selected"
+                print(message)
+                return message, None
+            
+            file_index = (
+                (
+                    file_index.strip(" ")
+                    .strip('"')
+                    .strip("\n")
+                    .strip('"')
+                    .strip(" ")
+                    .replace("trained", "added")
+                )
+                if file_index != ""
+                else file_index2
+            )  # 防止小白写错，自动帮他替换掉
+
+            try:
+                audio_opt = self.pipeline.pipeline(
+                    self.hubert_model,
+                    self.net_g,
+                    sid,
+                    audio,
+                    input_audio_path1,
+                    times,
+                    f0_up_key,
+                    f0_method,
+                    file_index,
+                    index_rate,
+                    self.if_f0,
+                    filter_radius,
+                    self.tgt_sr,
+                    resample_sr,
+                    rms_mix_rate,
+                    self.version,
+                    protect,
+                    crepe_hop_length,
+                    f0_autotune,
+                    f0_file=f0_file,
+                    f0_min=f0_min,
+                    f0_max=f0_max
+                    )
+            except AssertionError:
+                message = "Mismatching index version detected (v1 with v2, or v2 with v1)."
+                print(message)
+                return message, None
+            except NameError:
+                message = "RVC libraries are still loading. Please try again in a few seconds."
+                print(message)
+                return message, None
+
+            if self.tgt_sr != resample_sr >= 16000:
+                self.tgt_sr = resample_sr
+            index_info = (
+                "Index:\n%s." % file_index
+                if os.path.exists(file_index)
+                else "Index not used."
+            )
+            end_time = time.time()
+            total_time = end_time - start_time
+
+            output_folder = "audio-outputs"
+            os.makedirs(output_folder, exist_ok=True)  
+            output_filename = "generated_audio_{}.wav"
+            output_count = 1
+            while True:
+                current_output_path = os.path.join(output_folder, output_filename.format(output_count))
+                if not os.path.exists(current_output_path):
+                    break
+                output_count += 1
+            
+            wavfile.write(current_output_path, self.tgt_sr, audio_opt)
+            print(f"Generated audio saved to: {current_output_path}")
+            return f"Success.\n {index_info}\nTime:\n npy:{times[0]}, f0:{times[1]}, infer:{times[2]}\nTotal Time: {total_time} seconds", (self.tgt_sr, audio_opt)
+        except:
+            info = traceback.format_exc()
+            logger.warn(info)
+            return info, (None, None)
+
+    def vc_single_dont_save(
+        self,
+        sid,
+        input_audio_path0,
+        input_audio_path1,
+        f0_up_key,
+        f0_file,
+        f0_method,
+        file_index,
+        file_index2,
+        index_rate,
+        filter_radius,
+        resample_sr,
+        rms_mix_rate,
+        protect,
+        crepe_hop_length,
+        f0_min,
+        note_min,
+        f0_max,
+        note_max,
+        f0_autotune,
+    ):
+        global total_time
+        total_time = 0
+        start_time = time.time()
+        if not input_audio_path0 and not input_audio_path1:
+            return "You need to upload an audio", None
+        
+        if (not os.path.exists(input_audio_path0)) and (not os.path.exists(os.path.join(now_dir, input_audio_path0))):
+            return "Audio was not properly selected or doesn't exist", None
+        
+        input_audio_path1 = input_audio_path1 or input_audio_path0
+        print(f"\nStarting inference for '{os.path.basename(input_audio_path1)}'")
+        print("-------------------")
+        f0_up_key = int(f0_up_key)
+        if rvc_globals.NotesOrHertz and f0_method != 'rmvpe':
+            f0_min = note_to_hz(note_min) if note_min else 50
+            f0_max = note_to_hz(note_max) if note_max else 1100
+            print(f"Converted Min pitch: freq - {f0_min}\n"
+                  f"Converted Max pitch: freq - {f0_max}")
+        else:
+            f0_min = f0_min or 50
+            f0_max = f0_max or 1100
+        try:
+            input_audio_path1 = input_audio_path1 or input_audio_path0
+            print(f"Attempting to load {input_audio_path1}....")
+            audio = load_audio(file=input_audio_path1,
+                               sr=16000,
+                               DoFormant=rvc_globals.DoFormant,
+                               Quefrency=rvc_globals.Quefrency,
+                               Timbre=rvc_globals.Timbre)
+            
+            audio_max = np.abs(audio).max() / 0.95
+            if audio_max > 1:
+                audio /= audio_max
+            times = [0, 0, 0]
+
+            if self.hubert_model is None:
+                self.hubert_model = load_hubert(self.config)
+
+            try:
+                self.if_f0 = self.cpt.get("f0", 1)
+            except NameError:
+                message = "Model was not properly selected"
+                print(message)
+                return message, None
+            
+            file_index = (
+                (
+                    file_index.strip(" ")
+                    .strip('"')
+                    .strip("\n")
+                    .strip('"')
+                    .strip(" ")
+                    .replace("trained", "added")
+                )
+                if file_index != ""
+                else file_index2
+            )  # 防止小白写错，自动帮他替换掉
+
+            try:
+                audio_opt = self.pipeline.pipeline(
+                    self.hubert_model,
+                    self.net_g,
+                    sid,
+                    audio,
+                    input_audio_path1,
+                    times,
+                    f0_up_key,
+                    f0_method,
+                    file_index,
+                    index_rate,
+                    self.if_f0,
+                    filter_radius,
+                    self.tgt_sr,
+                    resample_sr,
+                    rms_mix_rate,
+                    self.version,
+                    protect,
+                    crepe_hop_length,
+                    f0_autotune,
+                    f0_file=f0_file,
+                    f0_min=f0_min,
+                    f0_max=f0_max
+                    )
+            except AssertionError:
+                message = "Mismatching index version detected (v1 with v2, or v2 with v1)."
+                print(message)
+                return message, None
+            except NameError:
+                message = "RVC libraries are still loading. Please try again in a few seconds."
+                print(message)
+                return message, None
+
+            if self.tgt_sr != resample_sr >= 16000:
+                self.tgt_sr = resample_sr
+            index_info = (
+                "Index:\n%s." % file_index
+                if os.path.exists(file_index)
+                else "Index not used."
+            )
+            end_time = time.time()
+            total_time = end_time - start_time
+
+            return f"Success.\n {index_info}\nTime:\n npy:{times[0]}, f0:{times[1]}, infer:{times[2]}\nTotal Time: {total_time} seconds", (self.tgt_sr, audio_opt)
+        except:
+            info = traceback.format_exc()
+            logger.warn(info)
+            return info, (None, None)
+
+
+    def vc_multi(
+        self,
+        sid,
+        dir_path,
+        opt_root,
+        paths,
+        f0_up_key,
+        f0_method,
+        file_index,
+        file_index2,
+        index_rate,
+        filter_radius,
+        resample_sr,
+        rms_mix_rate,
+        protect,
+        format1,
+        crepe_hop_length,
+        f0_min,
+        note_min,
+        f0_max,
+        note_max,
+        f0_autotune,
+    ):
+        if rvc_globals.NotesOrHertz and f0_method != 'rmvpe':
+            f0_min = note_to_hz(note_min) if note_min else 50
+            f0_max = note_to_hz(note_max) if note_max else 1100
+            print(f"Converted Min pitch: freq - {f0_min}\n"
+                  f"Converted Max pitch: freq - {f0_max}")
+        else:
+            f0_min = f0_min or 50
+            f0_max = f0_max or 1100
+        try:
+            dir_path = (
+                dir_path.strip(" ").strip('"').strip("\n").strip('"').strip(" ")
+            )  # 防止小白拷路径头尾带了空格和"和回车
+            opt_root = opt_root.strip(" ").strip('"').strip("\n").strip('"').strip(" ")
+            os.makedirs(opt_root, exist_ok=True)
+            try:
+                if dir_path != "":
+                    paths = [
+                        os.path.join(dir_path, name) for name in os.listdir(dir_path)
+                    ]
+                else:
+                    paths = [path.name for path in paths]
+            except:
+                traceback.print_exc()
+                paths = [path.name for path in paths]
+            infos = []
+            for path in paths:
+                info, opt = self.vc_single(
+                    sid,
+                    path,
+                    f0_up_key,
+                    None,
+                    f0_method,
+                    file_index,
+                    file_index2,
+                    # file_big_npy,
+                    index_rate,
+                    filter_radius,
+                    resample_sr,
+                    rms_mix_rate,
+                    protect,
+                )
+                if "Success" in info:
+                    try:
+                        tgt_sr, audio_opt = opt
+                        if format1 in ["wav", "flac"]:
+                            sf.write(
+                                "%s/%s.%s"
+                                % (opt_root, os.path.basename(path), format1),
+                                audio_opt,
+                                tgt_sr,
+                            )
+                        else:
+                            path = "%s/%s.%s" % (opt_root, os.path.basename(path), format1)
+                            with BytesIO() as wavf:
+                                sf.write(
+                                    wavf,
+                                    audio_opt,
+                                    tgt_sr,
+                                    format="wav"
+                                )
+                                wavf.seek(0, 0)
+                                with open(path, "wb") as outf:
+                                    wav2(wavf, outf, format1)
+                    except:
+                        info += traceback.format_exc()
+                infos.append("%s->%s" % (os.path.basename(path), info))
+                yield "\n".join(infos)
+            yield "\n".join(infos)
+        except:
+            yield traceback.format_exc()
diff --git a/infer/modules/vc/pipeline.py b/infer/modules/vc/pipeline.py
new file mode 100644
index 0000000000000000000000000000000000000000..76e712c649b95e21f9bbe6416ae8b7050317b479
--- /dev/null
+++ b/infer/modules/vc/pipeline.py
@@ -0,0 +1,655 @@
+import os
+import sys
+import traceback
+import logging
+
+logger = logging.getLogger(__name__)
+
+from functools import lru_cache
+from time import time as ttime
+from torch import Tensor
+import faiss
+import librosa
+import numpy as np
+import parselmouth
+import pyworld
+import torch
+import torch.nn.functional as F
+import torchcrepe
+from scipy import signal
+from tqdm import tqdm
+
+import random
+now_dir = os.getcwd()
+sys.path.append(now_dir)
+import re
+from functools import partial
+bh, ah = signal.butter(N=5, Wn=48, btype="high", fs=16000)
+
+input_audio_path2wav = {}
+from LazyImport import lazyload
+torchcrepe = lazyload("torchcrepe")  # Fork Feature. Crepe algo for training and preprocess
+torch = lazyload("torch")
+from infer.lib.rmvpe import RMVPE
+
+@lru_cache
+def cache_harvest_f0(input_audio_path, fs, f0max, f0min, frame_period):
+    audio = input_audio_path2wav[input_audio_path]
+    f0, t = pyworld.harvest(
+        audio,
+        fs=fs,
+        f0_ceil=f0max,
+        f0_floor=f0min,
+        frame_period=frame_period,
+    )
+    f0 = pyworld.stonemask(audio, f0, t, fs)
+    return f0
+
+
+def change_rms(data1, sr1, data2, sr2, rate):  # 1是输入音频，2是输出音频,rate是2的占比
+    # print(data1.max(),data2.max())
+    rms1 = librosa.feature.rms(
+        y=data1, frame_length=sr1 // 2 * 2, hop_length=sr1 // 2
+    )  # 每半秒一个点
+    rms2 = librosa.feature.rms(y=data2, frame_length=sr2 // 2 * 2, hop_length=sr2 // 2)
+    rms1 = torch.from_numpy(rms1)
+    rms1 = F.interpolate(
+        rms1.unsqueeze(0), size=data2.shape[0], mode="linear"
+    ).squeeze()
+    rms2 = torch.from_numpy(rms2)
+    rms2 = F.interpolate(
+        rms2.unsqueeze(0), size=data2.shape[0], mode="linear"
+    ).squeeze()
+    rms2 = torch.max(rms2, torch.zeros_like(rms2) + 1e-6)
+    data2 *= (
+        torch.pow(rms1, torch.tensor(1 - rate))
+        * torch.pow(rms2, torch.tensor(rate - 1))
+    ).numpy()
+    return data2
+
+
+class Pipeline(object):
+    def __init__(self, tgt_sr, config):
+        self.x_pad, self.x_query, self.x_center, self.x_max, self.is_half = (
+            config.x_pad,
+            config.x_query,
+            config.x_center,
+            config.x_max,
+            config.is_half,
+        )
+        self.sr = 16000  # hubert输入采样率
+        self.window = 160  # 每帧点数
+        self.t_pad = self.sr * self.x_pad  # 每条前后pad时间
+        self.t_pad_tgt = tgt_sr * self.x_pad
+        self.t_pad2 = self.t_pad * 2
+        self.t_query = self.sr * self.x_query  # 查询切点前后查询时间
+        self.t_center = self.sr * self.x_center  # 查询切点位置
+        self.t_max = self.sr * self.x_max  # 免查询时长阈值
+        self.device = config.device
+        self.model_rmvpe = RMVPE("%s/rmvpe.pt" % os.environ["rmvpe_root"], is_half=self.is_half, device=self.device)
+        self.f0_method_dict = {
+            "pm": self.get_pm,
+            "harvest": self.get_harvest,
+            "dio": self.get_dio,
+            "rmvpe": self.get_rmvpe,
+            "rmvpe+": self.get_pitch_dependant_rmvpe,
+            "crepe": self.get_f0_official_crepe_computation,
+            "crepe-tiny": partial(self.get_f0_official_crepe_computation, model='model'),
+            "mangio-crepe": self.get_f0_crepe_computation,
+            "mangio-crepe-tiny": partial(self.get_f0_crepe_computation, model='model'),
+            
+        }
+        self.note_dict = [
+            65.41, 69.30, 73.42, 77.78, 82.41, 87.31,
+            92.50, 98.00, 103.83, 110.00, 116.54, 123.47,
+            130.81, 138.59, 146.83, 155.56, 164.81, 174.61,
+            185.00, 196.00, 207.65, 220.00, 233.08, 246.94,
+            261.63, 277.18, 293.66, 311.13, 329.63, 349.23,
+            369.99, 392.00, 415.30, 440.00, 466.16, 493.88,
+            523.25, 554.37, 587.33, 622.25, 659.25, 698.46,
+            739.99, 783.99, 830.61, 880.00, 932.33, 987.77,
+            1046.50, 1108.73, 1174.66, 1244.51, 1318.51, 1396.91,
+            1479.98, 1567.98, 1661.22, 1760.00, 1864.66, 1975.53,
+            2093.00, 2217.46, 2349.32, 2489.02, 2637.02, 2793.83,
+            2959.96, 3135.96, 3322.44, 3520.00, 3729.31, 3951.07
+        ]
+
+    # Fork Feature: Get the best torch device to use for f0 algorithms that require a torch device. Will return the type (torch.device)
+    def get_optimal_torch_device(self, index: int = 0) -> torch.device:
+        if torch.cuda.is_available():
+            return torch.device(
+                f"cuda:{index % torch.cuda.device_count()}"
+            )  # Very fast
+        elif torch.backends.mps.is_available():
+            return torch.device("mps")
+        return torch.device("cpu")
+
+    # Fork Feature: Compute f0 with the crepe method
+    def get_f0_crepe_computation(
+        self,
+        x,
+        f0_min,
+        f0_max,
+        p_len,
+        *args,  # 512 before. Hop length changes the speed that the voice jumps to a different dramatic pitch. Lower hop lengths means more pitch accuracy but longer inference time.
+        **kwargs,  # Either use crepe-tiny "tiny" or crepe "full". Default is full
+    ):
+        x = x.astype(
+            np.float32
+        )  # fixes the F.conv2D exception. We needed to convert double to float.
+        x /= np.quantile(np.abs(x), 0.999)
+        torch_device = self.get_optimal_torch_device()
+        audio = torch.from_numpy(x).to(torch_device, copy=True)
+        audio = torch.unsqueeze(audio, dim=0)
+        if audio.ndim == 2 and audio.shape[0] > 1:
+            audio = torch.mean(audio, dim=0, keepdim=True).detach()
+        audio = audio.detach()
+        hop_length = kwargs.get('crepe_hop_length', 160)
+        model = kwargs.get('model', 'full') 
+        print("Initiating prediction with a crepe_hop_length of: " + str(hop_length))
+        pitch: Tensor = torchcrepe.predict(
+            audio,
+            self.sr,
+            hop_length,
+            f0_min,
+            f0_max,
+            model,
+            batch_size=hop_length * 2,
+            device=torch_device,
+            pad=True,
+        )
+        p_len = p_len or x.shape[0] // hop_length
+        # Resize the pitch for final f0
+        source = np.array(pitch.squeeze(0).cpu().float().numpy())
+        source[source < 0.001] = np.nan
+        target = np.interp(
+            np.arange(0, len(source) * p_len, len(source)) / p_len,
+            np.arange(0, len(source)),
+            source,
+        )
+        f0 = np.nan_to_num(target)
+        return f0  # Resized f0
+    
+    def get_f0_official_crepe_computation(
+        self,
+        x,
+        f0_min,
+        f0_max,
+        *args,
+        **kwargs
+    ):
+        # Pick a batch size that doesn't cause memory errors on your gpu
+        batch_size = 512
+        # Compute pitch using first gpu
+        audio = torch.tensor(np.copy(x))[None].float()
+        model = kwargs.get('model', 'full') 
+        f0, pd = torchcrepe.predict(
+            audio,
+            self.sr,
+            self.window,
+            f0_min,
+            f0_max,
+            model,
+            batch_size=batch_size,
+            device=self.device,
+            return_periodicity=True,
+        )
+        pd = torchcrepe.filter.median(pd, 3)
+        f0 = torchcrepe.filter.mean(f0, 3)
+        f0[pd < 0.1] = 0
+        f0 = f0[0].cpu().numpy()
+        return f0
+
+    # Fork Feature: Compute pYIN f0 method
+    def get_f0_pyin_computation(self, x, f0_min, f0_max):
+        y, sr = librosa.load("saudio/Sidney.wav", self.sr, mono=True)
+        f0, _, _ = librosa.pyin(y, sr=self.sr, fmin=f0_min, fmax=f0_max)
+        f0 = f0[1:]  # Get rid of extra first frame
+        return f0
+
+    def get_pm(self, x, p_len, *args, **kwargs):
+        f0 = parselmouth.Sound(x, self.sr).to_pitch_ac(
+            time_step=160 / 16000,
+            voicing_threshold=0.6,
+            pitch_floor=kwargs.get('f0_min'),
+            pitch_ceiling=kwargs.get('f0_max'),
+        ).selected_array["frequency"]
+        
+        return np.pad(
+            f0,
+            [[max(0, (p_len - len(f0) + 1) // 2), max(0, p_len - len(f0) - (p_len - len(f0) + 1) // 2)]],
+            mode="constant"
+        )
+
+    def get_harvest(self, x, *args, **kwargs):
+        f0_spectral = pyworld.harvest(
+            x.astype(np.double),
+            fs=self.sr,
+            f0_ceil=kwargs.get('f0_max'),
+            f0_floor=kwargs.get('f0_min'),
+            frame_period=1000 * kwargs.get('hop_length', 160) / self.sr,
+        )
+        return pyworld.stonemask(x.astype(np.double), *f0_spectral, self.sr)
+
+    def get_dio(self, x, *args, **kwargs):
+        f0_spectral = pyworld.dio(
+            x.astype(np.double),
+            fs=self.sr,
+            f0_ceil=kwargs.get('f0_max'),
+            f0_floor=kwargs.get('f0_min'),
+            frame_period=1000 * kwargs.get('hop_length', 160) / self.sr,
+        )
+        return pyworld.stonemask(x.astype(np.double), *f0_spectral, self.sr)
+
+
+    def get_rmvpe(self, x, *args, **kwargs):
+        if not hasattr(self, "model_rmvpe"):
+            from infer.lib.rmvpe import RMVPE
+            
+            logger.info(
+                "Loading rmvpe model,%s" % "%s/rmvpe.pt" % os.environ["rmvpe_root"]
+            )
+            self.model_rmvpe = RMVPE(
+                "%s/rmvpe.pt" % os.environ["rmvpe_root"],
+                is_half=self.is_half,
+                device=self.device,
+            )
+        f0 = self.model_rmvpe.infer_from_audio(x, thred=0.03)
+            
+        return f0
+    
+
+    def get_pitch_dependant_rmvpe(self, x, f0_min=1, f0_max=40000, *args, **kwargs):
+        return self.model_rmvpe.infer_from_audio_with_pitch(x, thred=0.03, f0_min=f0_min, f0_max=f0_max)
+
+    def autotune_f0(self, f0):
+        autotuned_f0 = []
+        for freq in f0:
+            closest_notes = [x for x in self.note_dict if abs(x - freq) == min(abs(n - freq) for n in self.note_dict)]
+            autotuned_f0.append(random.choice(closest_notes))
+        return np.array(autotuned_f0, np.float64)
+
+    # Fork Feature: Acquire median hybrid f0 estimation calculation
+    def get_f0_hybrid_computation(
+        self,
+        methods_str,
+        input_audio_path,
+        x,
+        f0_min,
+        f0_max,
+        p_len,
+        filter_radius,
+        crepe_hop_length,
+        time_step
+    ):
+        # Get various f0 methods from input to use in the computation stack
+        params = {'x': x, 'p_len': p_len, 'f0_min': f0_min, 
+          'f0_max': f0_max, 'time_step': time_step, 'filter_radius': filter_radius, 
+          'crepe_hop_length': crepe_hop_length, 'model': "full"
+        }
+        methods_str = re.search('hybrid\[(.+)\]', methods_str)
+        if methods_str:  # Ensure a match was found
+            methods = [method.strip() for method in methods_str.group(1).split('+')]
+        f0_computation_stack = []
+
+        print(f"Calculating f0 pitch estimations for methods: {str(methods)}")
+        x = x.astype(np.float32)
+        x /= np.quantile(np.abs(x), 0.999)
+        # Get f0 calculations for all methods specified
+
+        for method in methods:
+            if method not in self.f0_method_dict:
+                print(f"Method {method} not found.")
+                continue
+            f0 = self.f0_method_dict[method](**params)
+            if method == 'harvest' and filter_radius > 2:
+                f0 = signal.medfilt(f0, 3)
+                f0 = f0[1:]  # Get rid of first frame.
+            f0_computation_stack.append(f0)
+
+        for fc in f0_computation_stack:
+            print(len(fc))
+
+        print(f"Calculating hybrid median f0 from the stack of: {str(methods)}")
+        f0_median_hybrid = np.nanmedian(f0_computation_stack, axis=0)
+        return f0_median_hybrid
+    
+    def get_f0(
+        self,
+        input_audio_path,
+        x,
+        p_len,
+        f0_up_key,
+        f0_method,
+        filter_radius,
+        crepe_hop_length,
+        f0_autotune,
+        inp_f0=None,
+        f0_min=50,
+        f0_max=1100,
+    ):
+        global input_audio_path2wav
+        time_step = self.window / self.sr * 1000
+        f0_min = 50
+        f0_max = 1100
+        f0_mel_min = 1127 * np.log(1 + f0_min / 700)
+        f0_mel_max = 1127 * np.log(1 + f0_max / 700)
+        params = {'x': x, 'p_len': p_len, 'f0_up_key': f0_up_key, 'f0_min': f0_min, 
+          'f0_max': f0_max, 'time_step': time_step, 'filter_radius': filter_radius, 
+          'crepe_hop_length': crepe_hop_length, 'model': "full"
+        }
+
+        if "hybrid" in f0_method:
+            # Perform hybrid median pitch estimation
+            input_audio_path2wav[input_audio_path] = x.astype(np.double)
+            f0 = self.get_f0_hybrid_computation(
+                f0_method,+
+                input_audio_path,
+                x,
+                f0_min,
+                f0_max,
+                p_len,
+                filter_radius,
+                crepe_hop_length,
+                time_step,
+            )
+        else:
+            f0 = self.f0_method_dict[f0_method](**params)
+
+        if "privateuseone" in str(self.device):  # clean ortruntime memory
+            del self.model_rmvpe.model
+            del self.model_rmvpe
+            logger.info("Cleaning ortruntime memory")
+
+        if f0_autotune:
+            f0 = self.autotune_f0(f0)
+
+        f0 *= pow(2, f0_up_key / 12)
+        # with open("test.txt","w")as f:f.write("\n".join([str(i)for i in f0.tolist()]))
+        tf0 = self.sr // self.window  # 每秒f0点数
+        if inp_f0 is not None:
+            delta_t = np.round(
+                (inp_f0[:, 0].max() - inp_f0[:, 0].min()) * tf0 + 1
+            ).astype("int16")
+            replace_f0 = np.interp(
+                list(range(delta_t)), inp_f0[:, 0] * 100, inp_f0[:, 1]
+            )
+            shape = f0[self.x_pad * tf0 : self.x_pad * tf0 + len(replace_f0)].shape[0]
+            f0[self.x_pad * tf0 : self.x_pad * tf0 + len(replace_f0)] = replace_f0[
+                :shape
+            ]
+        # with open("test_opt.txt","w")as f:f.write("\n".join([str(i)for i in f0.tolist()]))
+        f0bak = f0.copy()
+        f0_mel = 1127 * np.log(1 + f0 / 700)
+        f0_mel[f0_mel > 0] = (f0_mel[f0_mel > 0] - f0_mel_min) * 254 / (
+            f0_mel_max - f0_mel_min
+        ) + 1
+        f0_mel[f0_mel <= 1] = 1
+        f0_mel[f0_mel > 255] = 255
+        f0_coarse = np.rint(f0_mel).astype(np.int32)
+        return f0_coarse, f0bak  # 1-0
+
+    def vc(
+        self,
+        model,
+        net_g,
+        sid,
+        audio0,
+        pitch,
+        pitchf,
+        times,
+        index,
+        big_npy,
+        index_rate,
+        version,
+        protect,
+    ):  # ,file_index,file_big_npy
+        feats = torch.from_numpy(audio0)
+        if self.is_half:
+            feats = feats.half()
+        else:
+            feats = feats.float()
+        if feats.dim() == 2:  # double channels
+            feats = feats.mean(-1)
+        assert feats.dim() == 1, feats.dim()
+        feats = feats.view(1, -1)
+        padding_mask = torch.BoolTensor(feats.shape).to(self.device).fill_(False)
+
+        inputs = {
+            "source": feats.to(self.device),
+            "padding_mask": padding_mask,
+            "output_layer": 9 if version == "v1" else 12,
+        }
+        t0 = ttime()
+        with torch.no_grad():
+            logits = model.extract_features(**inputs)
+            feats = model.final_proj(logits[0]) if version == "v1" else logits[0]
+        if protect < 0.5 and pitch is not None and pitchf is not None:
+            feats0 = feats.clone()
+        if (
+            not isinstance(index, type(None))
+            and not isinstance(big_npy, type(None))
+            and index_rate != 0
+        ):
+            npy = feats[0].cpu().numpy()
+            if self.is_half:
+                npy = npy.astype("float32")
+
+            # _, I = index.search(npy, 1)
+            # npy = big_npy[I.squeeze()]
+
+            score, ix = index.search(npy, k=8)
+            weight = np.square(1 / score)
+            weight /= weight.sum(axis=1, keepdims=True)
+            npy = np.sum(big_npy[ix] * np.expand_dims(weight, axis=2), axis=1)
+
+            if self.is_half:
+                npy = npy.astype("float16")
+            feats = (
+                torch.from_numpy(npy).unsqueeze(0).to(self.device) * index_rate
+                + (1 - index_rate) * feats
+            )
+
+        feats = F.interpolate(feats.permute(0, 2, 1), scale_factor=2).permute(0, 2, 1)
+        if protect < 0.5 and pitch is not None and pitchf is not None:
+            feats0 = F.interpolate(feats0.permute(0, 2, 1), scale_factor=2).permute(
+                0, 2, 1
+            )
+        t1 = ttime()
+        p_len = audio0.shape[0] // self.window
+        if feats.shape[1] < p_len:
+            p_len = feats.shape[1]
+            if pitch is not None and pitchf is not None:
+                pitch = pitch[:, :p_len]
+                pitchf = pitchf[:, :p_len]
+
+        if protect < 0.5 and pitch is not None and pitchf is not None:
+            pitchff = pitchf.clone()
+            pitchff[pitchf > 0] = 1
+            pitchff[pitchf < 1] = protect
+            pitchff = pitchff.unsqueeze(-1)
+            feats = feats * pitchff + feats0 * (1 - pitchff)
+            feats = feats.to(feats0.dtype)
+        p_len = torch.tensor([p_len], device=self.device).long()
+        with torch.no_grad():
+            hasp = pitch is not None and pitchf is not None
+            arg = (feats, p_len, pitch, pitchf, sid) if hasp else (feats, p_len, sid)
+            audio1 = (net_g.infer(*arg)[0][0, 0]).data.cpu().float().numpy()
+            del hasp, arg
+        del feats, p_len, padding_mask
+        if torch.cuda.is_available():
+            torch.cuda.empty_cache()
+        t2 = ttime()
+        times[0] += t1 - t0
+        times[2] += t2 - t1
+        return audio1
+    def process_t(self, t, s, window, audio_pad, pitch, pitchf, times, index, big_npy, index_rate, version, protect, t_pad_tgt, if_f0, sid, model, net_g):
+        t = t // window * window
+        if if_f0 == 1:
+            return self.vc(
+                model,
+                net_g,
+                sid,
+                audio_pad[s : t + t_pad_tgt + window],
+                pitch[:, s // window : (t + t_pad_tgt) // window],
+                pitchf[:, s // window : (t + t_pad_tgt) // window],
+                times,
+                index,
+                big_npy,
+                index_rate,
+                version,
+                protect,
+            )[t_pad_tgt : -t_pad_tgt]
+        else:
+            return self.vc(
+                model,
+                net_g,
+                sid,
+                audio_pad[s : t + t_pad_tgt + window],
+                None,
+                None,
+                times,
+                index,
+                big_npy,
+                index_rate,
+                version,
+                protect,
+            )[t_pad_tgt : -t_pad_tgt]
+
+
+    def pipeline(
+        self,
+        model,
+        net_g,
+        sid,
+        audio,
+        input_audio_path,
+        times,
+        f0_up_key,
+        f0_method,
+        file_index,
+        index_rate,
+        if_f0,
+        filter_radius,
+        tgt_sr,
+        resample_sr,
+        rms_mix_rate,
+        version,
+        protect,
+        crepe_hop_length, 
+        f0_autotune, 
+        f0_file=None, 
+        f0_min=50, 
+        f0_max=1100
+    ):
+        if (
+            file_index != ""
+            # and file_big_npy != ""
+            # and os.path.exists(file_big_npy) == True
+            and os.path.exists(file_index)
+            and index_rate != 0
+        ):
+            try:
+                index = faiss.read_index(file_index)
+                # big_npy = np.load(file_big_npy)
+                big_npy = index.reconstruct_n(0, index.ntotal)
+            except:
+                traceback.print_exc()
+                index = big_npy = None
+        else:
+            index = big_npy = None
+        audio = signal.filtfilt(bh, ah, audio)
+        audio_pad = np.pad(audio, (self.window // 2, self.window // 2), mode="reflect")
+        opt_ts = []
+        if audio_pad.shape[0] > self.t_max:
+            audio_sum = np.zeros_like(audio)
+            for i in range(self.window):
+                audio_sum += audio_pad[i : i - self.window]
+            for t in range(self.t_center, audio.shape[0], self.t_center):
+                opt_ts.append(
+                    t
+                    - self.t_query
+                    + np.where(
+                        np.abs(audio_sum[t - self.t_query : t + self.t_query])
+                        == np.abs(audio_sum[t - self.t_query : t + self.t_query]).min()
+                    )[0][0]
+                )
+        s = 0
+        audio_opt = []
+        t = None
+        t1 = ttime()
+        audio_pad = np.pad(audio, (self.t_pad, self.t_pad), mode="reflect")
+        p_len = audio_pad.shape[0] // self.window
+        inp_f0 = None
+        if hasattr(f0_file, "name"):
+            try:
+                with open(f0_file.name, "r") as f:
+                    lines = f.read().strip("\n").split("\n")
+                inp_f0 = []
+                for line in lines:
+                    inp_f0.append([float(i) for i in line.split(",")])
+                inp_f0 = np.array(inp_f0, dtype="float32")
+            except:
+                traceback.print_exc()
+        sid = torch.tensor(sid, device=self.device).unsqueeze(0).long()
+        pitch, pitchf = None, None
+        if if_f0:
+            pitch, pitchf = self.get_f0(
+                input_audio_path,
+                audio_pad,
+                p_len,
+                f0_up_key,
+                f0_method,
+                filter_radius, 
+                crepe_hop_length, 
+                f0_autotune,
+                inp_f0, 
+                f0_min, 
+                f0_max
+            )
+            pitch = pitch[:p_len]
+            pitchf = pitchf[:p_len]
+            if self.device == "mps" or "xpu" in self.device:
+                pitchf = pitchf.astype(np.float32)
+            pitch = torch.tensor(pitch, device=self.device).unsqueeze(0).long()
+            pitchf = torch.tensor(pitchf, device=self.device).unsqueeze(0).float()
+        t2 = ttime()
+        times[1] += t2 - t1
+
+        with tqdm(total=len(opt_ts), desc="Processing", unit="window") as pbar:
+            for i, t in enumerate(opt_ts):
+                t = t // self.window * self.window
+                start = s
+                end = t + self.t_pad2 + self.window
+                audio_slice = audio_pad[start:end]
+                pitch_slice = pitch[:, start // self.window:end // self.window] if if_f0 else None
+                pitchf_slice = pitchf[:, start // self.window:end // self.window] if if_f0 else None
+                audio_opt.append(self.vc(model, net_g, sid, audio_slice, pitch_slice, pitchf_slice, times, index, big_npy, index_rate, version, protect)[self.t_pad_tgt : -self.t_pad_tgt])
+                s = t
+                pbar.update(1)
+                pbar.refresh()
+
+        audio_slice = audio_pad[t:]
+        pitch_slice = pitch[:, t // self.window:] if if_f0 and t is not None else pitch
+        pitchf_slice = pitchf[:, t // self.window:] if if_f0 and t is not None else pitchf
+        audio_opt.append(self.vc(model, net_g, sid, audio_slice, pitch_slice, pitchf_slice, times, index, big_npy, index_rate, version, protect)[self.t_pad_tgt : -self.t_pad_tgt])
+        
+        audio_opt = np.concatenate(audio_opt)
+        if rms_mix_rate != 1:
+            audio_opt = change_rms(audio, 16000, audio_opt, tgt_sr, rms_mix_rate)
+        if tgt_sr != resample_sr >= 16000:
+            audio_opt = librosa.resample(
+                audio_opt, orig_sr=tgt_sr, target_sr=resample_sr
+            )
+        audio_max = np.abs(audio_opt).max() / 0.99
+        max_int16 = 32768
+        if audio_max > 1:
+            max_int16 /= audio_max
+        audio_opt = (audio_opt * max_int16).astype(np.int16)
+        del pitch, pitchf, sid
+        if torch.cuda.is_available():
+            torch.cuda.empty_cache()
+
+        print("Returning completed audio...")
+        print("-------------------")
+        return audio_opt
diff --git a/infer/modules/vc/utils.py b/infer/modules/vc/utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..a1cb0ff84097d1c7eb82373ccf19db061f595096
--- /dev/null
+++ b/infer/modules/vc/utils.py
@@ -0,0 +1,42 @@
+import os
+import re
+from fairseq import checkpoint_utils
+
+
+def get_index_path_from_model(sid):
+    sid0strip = re.sub(r'\.pth|\.onnx$', '', sid)
+    sid0name = os.path.split(sid0strip)[-1]  # Extract only the name, not the directory
+
+    # Check if the sid0strip has the specific ending format _eXXX_sXXX
+    if re.match(r'.+_e\d+_s\d+$', sid0name):
+        base_model_name = sid0name.rsplit('_', 2)[0]
+    else:
+        base_model_name = sid0name
+    
+    return next(
+        (
+            f
+            for f in [
+                os.path.join(root, name)
+                for root, _, files in os.walk(os.getenv("index_root"), topdown=False)
+                for name in files
+                if name.endswith(".index") and "trained" not in name
+            ]
+            if base_model_name in f
+        ),
+        "",
+    )
+
+
+def load_hubert(config):
+    models, _, _ = checkpoint_utils.load_model_ensemble_and_task(
+        ["assets/hubert/hubert_base.pt"],
+        suffix="",
+    )
+    hubert_model = models[0]
+    hubert_model = hubert_model.to(config.device)
+    if config.is_half:
+        hubert_model = hubert_model.half()
+    else:
+        hubert_model = hubert_model.float()
+    return hubert_model.eval()
diff --git a/infer_batch_rvc.py b/infer_batch_rvc.py
new file mode 100644
index 0000000000000000000000000000000000000000..15c862a3d6bf815fa68003cc7054b694cae50c2a
--- /dev/null
+++ b/infer_batch_rvc.py
@@ -0,0 +1,215 @@
+"""
+v1
+runtime\python.exe myinfer-v2-0528.py 0 "E:\codes\py39\RVC-beta\todo-songs" "E:\codes\py39\logs\mi-test\added_IVF677_Flat_nprobe_7.index" harvest "E:\codes\py39\RVC-beta\output" "E:\codes\py39\test-20230416b\weights\mi-test.pth" 0.66 cuda:0 True 3 0 1 0.33
+v2
+runtime\python.exe myinfer-v2-0528.py 0 "E:\codes\py39\RVC-beta\todo-songs" "E:\codes\py39\test-20230416b\logs\mi-test-v2\aadded_IVF677_Flat_nprobe_1_v2.index" harvest "E:\codes\py39\RVC-beta\output_v2" "E:\codes\py39\test-20230416b\weights\mi-test-v2.pth" 0.66 cuda:0 True 3 0 1 0.33
+"""
+import os, sys, pdb, torch
+
+now_dir = os.getcwd()
+sys.path.append(now_dir)
+import sys
+import torch
+import tqdm as tq
+from multiprocessing import cpu_count
+
+
+class Config:
+    def __init__(self, device, is_half):
+        self.device = device
+        self.is_half = is_half
+        self.n_cpu = 0
+        self.gpu_name = None
+        self.gpu_mem = None
+        self.x_pad, self.x_query, self.x_center, self.x_max = self.device_config()
+
+    def device_config(self) -> tuple:
+        if torch.cuda.is_available():
+            i_device = int(self.device.split(":")[-1])
+            self.gpu_name = torch.cuda.get_device_name(i_device)
+            if (
+                ("16" in self.gpu_name and "V100" not in self.gpu_name.upper())
+                or "P40" in self.gpu_name.upper()
+                or "1060" in self.gpu_name
+                or "1070" in self.gpu_name
+                or "1080" in self.gpu_name
+            ):
+                print("16系/10系显卡和P40强制单精度")
+                self.is_half = False
+                for config_file in ["32k.json", "40k.json", "48k.json"]:
+                    with open(f"configs/{config_file}", "r") as f:
+                        strr = f.read().replace("true", "false")
+                    with open(f"configs/{config_file}", "w") as f:
+                        f.write(strr)
+                with open("infer/modules/train/preprocess.py", "r") as f:
+                    strr = f.read().replace("3.7", "3.0")
+                with open("infer/modules/train/preprocess.py", "w") as f:
+                    f.write(strr)
+            else:
+                self.gpu_name = None
+            self.gpu_mem = int(
+                torch.cuda.get_device_properties(i_device).total_memory
+                / 1024
+                / 1024
+                / 1024
+                + 0.4
+            )
+            if self.gpu_mem <= 4:
+                with open("infer/modules/train/preprocess.py", "r") as f:
+                    strr = f.read().replace("3.7", "3.0")
+                with open("infer/modules/train/preprocess.py", "w") as f:
+                    f.write(strr)
+        elif torch.backends.mps.is_available():
+            print("没有发现支持的N卡, 使用MPS进行推理")
+            self.device = "mps"
+        else:
+            print("没有发现支持的N卡, 使用CPU进行推理")
+            self.device = "cpu"
+            self.is_half = True
+
+        if self.n_cpu == 0:
+            self.n_cpu = cpu_count()
+
+        if self.is_half:
+            # 6G显存配置
+            x_pad = 3
+            x_query = 10
+            x_center = 60
+            x_max = 65
+        else:
+            # 5G显存配置
+            x_pad = 1
+            x_query = 6
+            x_center = 38
+            x_max = 41
+
+        if self.gpu_mem != None and self.gpu_mem <= 4:
+            x_pad = 1
+            x_query = 5
+            x_center = 30
+            x_max = 32
+
+        return x_pad, x_query, x_center, x_max
+
+
+f0up_key = sys.argv[1]
+input_path = sys.argv[2]
+index_path = sys.argv[3]
+f0method = sys.argv[4]  # harvest or pm
+opt_path = sys.argv[5]
+model_path = sys.argv[6]
+index_rate = float(sys.argv[7])
+device = sys.argv[8]
+is_half = sys.argv[9].lower() != "false"
+filter_radius = int(sys.argv[10])
+resample_sr = int(sys.argv[11])
+rms_mix_rate = float(sys.argv[12])
+protect = float(sys.argv[13])
+print(sys.argv)
+config = Config(device, is_half)
+now_dir = os.getcwd()
+sys.path.append(now_dir)
+from infer.modules.vc.modules import VC
+from lib.infer_pack.models import (
+    SynthesizerTrnMs256NSFsid,
+    SynthesizerTrnMs256NSFsid_nono,
+    SynthesizerTrnMs768NSFsid,
+    SynthesizerTrnMs768NSFsid_nono,
+)
+from infer.lib.audio import load_audio
+from fairseq import checkpoint_utils
+from scipy.io import wavfile
+
+hubert_model = None
+
+
+def load_hubert():
+    global hubert_model
+    models, saved_cfg, task = checkpoint_utils.load_model_ensemble_and_task(
+        ["hubert_base.pt"],
+        suffix="",
+    )
+    hubert_model = models[0]
+    hubert_model = hubert_model.to(device)
+    if is_half:
+        hubert_model = hubert_model.half()
+    else:
+        hubert_model = hubert_model.float()
+    hubert_model.eval()
+
+
+def vc_single(sid, input_audio, f0_up_key, f0_file, f0_method, file_index, index_rate):
+    global tgt_sr, net_g, vc, hubert_model, version
+    if input_audio is None:
+        return "You need to upload an audio", None
+    f0_up_key = int(f0_up_key)
+    audio = load_audio(input_audio, 16000)
+    times = [0, 0, 0]
+    if hubert_model == None:
+        load_hubert()
+    if_f0 = cpt.get("f0", 1)
+    # audio_opt=vc.pipeline(hubert_model,net_g,sid,audio,times,f0_up_key,f0_method,file_index,file_big_npy,index_rate,if_f0,f0_file=f0_file)
+    audio_opt = vc.pipeline(
+        hubert_model,
+        net_g,
+        sid,
+        audio,
+        input_audio,
+        times,
+        f0_up_key,
+        f0_method,
+        file_index,
+        index_rate,
+        if_f0,
+        filter_radius,
+        tgt_sr,
+        resample_sr,
+        rms_mix_rate,
+        version,
+        protect,
+        f0_file=f0_file,
+    )
+    print(times)
+    return audio_opt
+
+
+def get_vc(model_path):
+    global n_spk, tgt_sr, net_g, vc, cpt, device, is_half, version
+    print("loading pth %s" % model_path)
+    cpt = torch.load(model_path, map_location="cpu")
+    tgt_sr = cpt["config"][-1]
+    cpt["config"][-3] = cpt["weight"]["emb_g.weight"].shape[0]  # n_spk
+    if_f0 = cpt.get("f0", 1)
+    version = cpt.get("version", "v1")
+    if version == "v1":
+        if if_f0 == 1:
+            net_g = SynthesizerTrnMs256NSFsid(*cpt["config"], is_half=is_half)
+        else:
+            net_g = SynthesizerTrnMs256NSFsid_nono(*cpt["config"])
+    elif version == "v2":
+        if if_f0 == 1:  #
+            net_g = SynthesizerTrnMs768NSFsid(*cpt["config"], is_half=is_half)
+        else:
+            net_g = SynthesizerTrnMs768NSFsid_nono(*cpt["config"])
+    del net_g.enc_q
+    print(net_g.load_state_dict(cpt["weight"], strict=False))  # 不加这一行清不干净，真奇葩
+    net_g.eval().to(device)
+    if is_half:
+        net_g = net_g.half()
+    else:
+        net_g = net_g.float()
+    vc = VC(tgt_sr, config)
+    n_spk = cpt["config"][-3]
+    # return {"visible": True,"maximum": n_spk, "__type__": "update"}
+
+
+get_vc(model_path)
+audios = os.listdir(input_path)
+for file in tq.tqdm(audios):
+    if file.endswith(".wav"):
+        file_path = input_path + "/" + file
+        wav_opt = vc_single(
+            0, file_path, f0up_key, None, f0method, index_path, index_rate
+        )
+        out_path = opt_path + "/" + file
+        wavfile.write(out_path, tgt_sr, wav_opt)
diff --git a/infer_uvr5.py b/infer_uvr5.py
new file mode 100644
index 0000000000000000000000000000000000000000..8c8c05429a1d65dd8b198f16a8ea8c6e68991c07
--- /dev/null
+++ b/infer_uvr5.py
@@ -0,0 +1,363 @@
+import os, sys, torch, warnings, pdb
+
+now_dir = os.getcwd()
+sys.path.append(now_dir)
+from json import load as ll
+
+warnings.filterwarnings("ignore")
+import librosa
+import importlib
+import numpy as np
+import hashlib, math
+from tqdm import tqdm
+from lib.uvr5_pack.lib_v5 import spec_utils
+from lib.uvr5_pack.utils import _get_name_params, inference
+from lib.uvr5_pack.lib_v5.model_param_init import ModelParameters
+import soundfile as sf
+from lib.uvr5_pack.lib_v5.nets_new import CascadedNet
+from lib.uvr5_pack.lib_v5 import nets_61968KB as nets
+
+
+class _audio_pre_:
+    def __init__(self, agg, model_path, device, is_half):
+        self.model_path = model_path
+        self.device = device
+        self.data = {
+            # Processing Options
+            "postprocess": False,
+            "tta": False,
+            # Constants
+            "window_size": 512,
+            "agg": agg,
+            "high_end_process": "mirroring",
+        }
+        mp = ModelParameters("lib/uvr5_pack/lib_v5/modelparams/4band_v2.json")
+        model = nets.CascadedASPPNet(mp.param["bins"] * 2)
+        cpk = torch.load(model_path, map_location="cpu")
+        model.load_state_dict(cpk)
+        model.eval()
+        if is_half:
+            model = model.half().to(device)
+        else:
+            model = model.to(device)
+
+        self.mp = mp
+        self.model = model
+
+    def _path_audio_(self, music_file, ins_root=None, vocal_root=None, format="flac"):
+        if ins_root is None and vocal_root is None:
+            return "No save root."
+        name = os.path.basename(music_file)
+        if ins_root is not None:
+            os.makedirs(ins_root, exist_ok=True)
+        if vocal_root is not None:
+            os.makedirs(vocal_root, exist_ok=True)
+        X_wave, y_wave, X_spec_s, y_spec_s = {}, {}, {}, {}
+        bands_n = len(self.mp.param["band"])
+        # print(bands_n)
+        for d in range(bands_n, 0, -1):
+            bp = self.mp.param["band"][d]
+            if d == bands_n:  # high-end band
+                (
+                    X_wave[d],
+                    _,
+                ) = librosa.core.load(  
+                    music_file,
+                    bp["sr"],
+                    False,
+                    dtype=np.float32,
+                    res_type=bp["res_type"],
+                )
+                if X_wave[d].ndim == 1:
+                    X_wave[d] = np.asfortranarray([X_wave[d], X_wave[d]])
+            else:  # lower bands
+                X_wave[d] = librosa.core.resample(
+                    X_wave[d + 1],
+                    self.mp.param["band"][d + 1]["sr"],
+                    bp["sr"],
+                    res_type=bp["res_type"],
+                )
+            # Stft of wave source
+            X_spec_s[d] = spec_utils.wave_to_spectrogram_mt(
+                X_wave[d],
+                bp["hl"],
+                bp["n_fft"],
+                self.mp.param["mid_side"],
+                self.mp.param["mid_side_b2"],
+                self.mp.param["reverse"],
+            )
+            # pdb.set_trace()
+            if d == bands_n and self.data["high_end_process"] != "none":
+                input_high_end_h = (bp["n_fft"] // 2 - bp["crop_stop"]) + (
+                    self.mp.param["pre_filter_stop"] - self.mp.param["pre_filter_start"]
+                )
+                input_high_end = X_spec_s[d][
+                    :, bp["n_fft"] // 2 - input_high_end_h : bp["n_fft"] // 2, :
+                ]
+
+        X_spec_m = spec_utils.combine_spectrograms(X_spec_s, self.mp)
+        aggresive_set = float(self.data["agg"] / 100)
+        aggressiveness = {
+            "value": aggresive_set,
+            "split_bin": self.mp.param["band"][1]["crop_stop"],
+        }
+        with torch.no_grad():
+            pred, X_mag, X_phase = inference(
+                X_spec_m, self.device, self.model, aggressiveness, self.data
+            )
+        # Postprocess
+        if self.data["postprocess"]:
+            pred_inv = np.clip(X_mag - pred, 0, np.inf)
+            pred = spec_utils.mask_silence(pred, pred_inv)
+        y_spec_m = pred * X_phase
+        v_spec_m = X_spec_m - y_spec_m
+
+        if ins_root is not None:
+            if self.data["high_end_process"].startswith("mirroring"):
+                input_high_end_ = spec_utils.mirroring(
+                    self.data["high_end_process"], y_spec_m, input_high_end, self.mp
+                )
+                wav_instrument = spec_utils.cmb_spectrogram_to_wave(
+                    y_spec_m, self.mp, input_high_end_h, input_high_end_
+                )
+            else:
+                wav_instrument = spec_utils.cmb_spectrogram_to_wave(y_spec_m, self.mp)
+            print("%s instruments done" % name)
+            if format in ["wav", "flac"]:
+                sf.write(
+                    os.path.join(
+                        ins_root,
+                        "instrument_{}_{}.{}".format(name, self.data["agg"], format),
+                    ),
+                    (np.array(wav_instrument) * 32768).astype("int16"),
+                    self.mp.param["sr"],
+                )  #
+            else:
+                path = os.path.join(
+                    ins_root, "instrument_{}_{}.wav".format(name, self.data["agg"])
+                )
+                sf.write(
+                    path,
+                    (np.array(wav_instrument) * 32768).astype("int16"),
+                    self.mp.param["sr"],
+                )
+                if os.path.exists(path):
+                    os.system(
+                        "ffmpeg -i %s -vn %s -q:a 2 -y"
+                        % (path, path[:-4] + ".%s" % format)
+                    )
+        if vocal_root is not None:
+            if self.data["high_end_process"].startswith("mirroring"):
+                input_high_end_ = spec_utils.mirroring(
+                    self.data["high_end_process"], v_spec_m, input_high_end, self.mp
+                )
+                wav_vocals = spec_utils.cmb_spectrogram_to_wave(
+                    v_spec_m, self.mp, input_high_end_h, input_high_end_
+                )
+            else:
+                wav_vocals = spec_utils.cmb_spectrogram_to_wave(v_spec_m, self.mp)
+            print("%s vocals done" % name)
+            if format in ["wav", "flac"]:
+                sf.write(
+                    os.path.join(
+                        vocal_root,
+                        "vocal_{}_{}.{}".format(name, self.data["agg"], format),
+                    ),
+                    (np.array(wav_vocals) * 32768).astype("int16"),
+                    self.mp.param["sr"],
+                )
+            else:
+                path = os.path.join(
+                    vocal_root, "vocal_{}_{}.wav".format(name, self.data["agg"])
+                )
+                sf.write(
+                    path,
+                    (np.array(wav_vocals) * 32768).astype("int16"),
+                    self.mp.param["sr"],
+                )
+                if os.path.exists(path):
+                    os.system(
+                        "ffmpeg -i %s -vn %s -q:a 2 -y"
+                        % (path, path[:-4] + ".%s" % format)
+                    )
+
+
+class _audio_pre_new:
+    def __init__(self, agg, model_path, device, is_half):
+        self.model_path = model_path
+        self.device = device
+        self.data = {
+            # Processing Options
+            "postprocess": False,
+            "tta": False,
+            # Constants
+            "window_size": 512,
+            "agg": agg,
+            "high_end_process": "mirroring",
+        }
+        mp = ModelParameters("lib/uvr5_pack/lib_v5/modelparams/4band_v3.json")
+        nout = 64 if "DeReverb" in model_path else 48
+        model = CascadedNet(mp.param["bins"] * 2, nout)
+        cpk = torch.load(model_path, map_location="cpu")
+        model.load_state_dict(cpk)
+        model.eval()
+        if is_half:
+            model = model.half().to(device)
+        else:
+            model = model.to(device)
+
+        self.mp = mp
+        self.model = model
+
+    def _path_audio_(
+        self, music_file, vocal_root=None, ins_root=None, format="flac"
+    ):  # 3个VR模型vocal和ins是反的
+        if ins_root is None and vocal_root is None:
+            return "No save root."
+        name = os.path.basename(music_file)
+        if ins_root is not None:
+            os.makedirs(ins_root, exist_ok=True)
+        if vocal_root is not None:
+            os.makedirs(vocal_root, exist_ok=True)
+        X_wave, y_wave, X_spec_s, y_spec_s = {}, {}, {}, {}
+        bands_n = len(self.mp.param["band"])
+        # print(bands_n)
+        for d in range(bands_n, 0, -1):
+            bp = self.mp.param["band"][d]
+            if d == bands_n:  # high-end band
+                (
+                    X_wave[d],
+                    _,
+                ) = librosa.core.load( 
+                    music_file,
+                    bp["sr"],
+                    False,
+                    dtype=np.float32,
+                    res_type=bp["res_type"],
+                )
+                if X_wave[d].ndim == 1:
+                    X_wave[d] = np.asfortranarray([X_wave[d], X_wave[d]])
+            else:  # lower bands
+                X_wave[d] = librosa.core.resample(
+                    X_wave[d + 1],
+                    self.mp.param["band"][d + 1]["sr"],
+                    bp["sr"],
+                    res_type=bp["res_type"],
+                )
+            # Stft of wave source
+            X_spec_s[d] = spec_utils.wave_to_spectrogram_mt(
+                X_wave[d],
+                bp["hl"],
+                bp["n_fft"],
+                self.mp.param["mid_side"],
+                self.mp.param["mid_side_b2"],
+                self.mp.param["reverse"],
+            )
+            # pdb.set_trace()
+            if d == bands_n and self.data["high_end_process"] != "none":
+                input_high_end_h = (bp["n_fft"] // 2 - bp["crop_stop"]) + (
+                    self.mp.param["pre_filter_stop"] - self.mp.param["pre_filter_start"]
+                )
+                input_high_end = X_spec_s[d][
+                    :, bp["n_fft"] // 2 - input_high_end_h : bp["n_fft"] // 2, :
+                ]
+
+        X_spec_m = spec_utils.combine_spectrograms(X_spec_s, self.mp)
+        aggresive_set = float(self.data["agg"] / 100)
+        aggressiveness = {
+            "value": aggresive_set,
+            "split_bin": self.mp.param["band"][1]["crop_stop"],
+        }
+        with torch.no_grad():
+            pred, X_mag, X_phase = inference(
+                X_spec_m, self.device, self.model, aggressiveness, self.data
+            )
+        # Postprocess
+        if self.data["postprocess"]:
+            pred_inv = np.clip(X_mag - pred, 0, np.inf)
+            pred = spec_utils.mask_silence(pred, pred_inv)
+        y_spec_m = pred * X_phase
+        v_spec_m = X_spec_m - y_spec_m
+
+        if ins_root is not None:
+            if self.data["high_end_process"].startswith("mirroring"):
+                input_high_end_ = spec_utils.mirroring(
+                    self.data["high_end_process"], y_spec_m, input_high_end, self.mp
+                )
+                wav_instrument = spec_utils.cmb_spectrogram_to_wave(
+                    y_spec_m, self.mp, input_high_end_h, input_high_end_
+                )
+            else:
+                wav_instrument = spec_utils.cmb_spectrogram_to_wave(y_spec_m, self.mp)
+            print("%s instruments done" % name)
+            if format in ["wav", "flac"]:
+                sf.write(
+                    os.path.join(
+                        ins_root,
+                        "instrument_{}_{}.{}".format(name, self.data["agg"], format),
+                    ),
+                    (np.array(wav_instrument) * 32768).astype("int16"),
+                    self.mp.param["sr"],
+                )  #
+            else:
+                path = os.path.join(
+                    ins_root, "instrument_{}_{}.wav".format(name, self.data["agg"])
+                )
+                sf.write(
+                    path,
+                    (np.array(wav_instrument) * 32768).astype("int16"),
+                    self.mp.param["sr"],
+                )
+                if os.path.exists(path):
+                    os.system(
+                        "ffmpeg -i %s -vn %s -q:a 2 -y"
+                        % (path, path[:-4] + ".%s" % format)
+                    )
+        if vocal_root is not None:
+            if self.data["high_end_process"].startswith("mirroring"):
+                input_high_end_ = spec_utils.mirroring(
+                    self.data["high_end_process"], v_spec_m, input_high_end, self.mp
+                )
+                wav_vocals = spec_utils.cmb_spectrogram_to_wave(
+                    v_spec_m, self.mp, input_high_end_h, input_high_end_
+                )
+            else:
+                wav_vocals = spec_utils.cmb_spectrogram_to_wave(v_spec_m, self.mp)
+            print("%s vocals done" % name)
+            if format in ["wav", "flac"]:
+                sf.write(
+                    os.path.join(
+                        vocal_root,
+                        "vocal_{}_{}.{}".format(name, self.data["agg"], format),
+                    ),
+                    (np.array(wav_vocals) * 32768).astype("int16"),
+                    self.mp.param["sr"],
+                )
+            else:
+                path = os.path.join(
+                    vocal_root, "vocal_{}_{}.wav".format(name, self.data["agg"])
+                )
+                sf.write(
+                    path,
+                    (np.array(wav_vocals) * 32768).astype("int16"),
+                    self.mp.param["sr"],
+                )
+                if os.path.exists(path):
+                    os.system(
+                        "ffmpeg -i %s -vn %s -q:a 2 -y"
+                        % (path, path[:-4] + ".%s" % format)
+                    )
+
+
+if __name__ == "__main__":
+    device = "cuda"
+    is_half = True
+    # model_path = "uvr5_weights/2_HP-UVR.pth"
+    # model_path = "uvr5_weights/VR-DeEchoDeReverb.pth"
+    # model_path = "uvr5_weights/VR-DeEchoNormal.pth"
+    model_path = "uvr5_weights/DeEchoNormal.pth"
+    # pre_fun = _audio_pre_(model_path=model_path, device=device, is_half=True,agg=10)
+    pre_fun = _audio_pre_new(model_path=model_path, device=device, is_half=True, agg=10)
+    audio_path = "雪雪伴奏对消HP5.wav"
+    save_path = "opt"
+    pre_fun._path_audio_(audio_path, save_path, save_path)
diff --git a/inference-presets.json b/inference-presets.json
new file mode 100644
index 0000000000000000000000000000000000000000..7f68a27d96b01d89265d0507aa6f7af5a67065c1
--- /dev/null
+++ b/inference-presets.json
@@ -0,0 +1,20 @@
+{
+  "presets": [
+    {
+      "name": "Default Preset",
+      "model": "",
+      "transpose": 0,
+      "audio_file": "",
+      "f0_method": "pm",
+      "crepe_hop_length": 160,
+      "median_filtering": 3,
+      "feature_path": "",
+      "auto_feature_path": "",
+      "search_feature_ratio": 0.88,
+      "resample": 0,
+      "volume_envelope": 1,
+      "protect_voiceless": 0.33,
+      "f0_file_path": ""
+    }
+  ]
+}
diff --git a/julius/__init__.py b/julius/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..69811b0415a291ca1beb845531785ba03c57099a
--- /dev/null
+++ b/julius/__init__.py
@@ -0,0 +1,41 @@
+# File under the MIT license, see https://github.com/adefossez/julius/LICENSE for details.
+# Author: adefossez, 2020
+
+# flake8: noqa
+"""
+.. image:: ../logo.png
+
+Julius contains different Digital Signal Processing algorithms implemented
+with PyTorch, so that they are differentiable and available on CUDA.
+Note that all the modules implemented here can be used with TorchScript.
+
+For now, I have implemented:
+
+- `julius.resample`: fast sinc resampling.
+- `julius.fftconv`: FFT based convolutions.
+- `julius.lowpass`: FIR low pass filter banks.
+- `julius.filters`: FIR high pass and band pass filters.
+- `julius.bands`: Decomposition of a waveform signal over mel-scale frequency bands.
+
+Along that, you might found useful utilities in:
+
+- `julius.core`: DSP related functions.
+- `julius.utils`: Generic utilities.
+
+
+Please checkout [the Github repository](https://github.com/adefossez/julius) for other informations.
+For a verification of the speed and correctness of Julius, check the benchmark module `bench`.
+
+
+This package is named in this honor of
+[Julius O. Smith](https://ccrma.stanford.edu/~jos/),
+whose books and website were a gold mine of information for me to learn about DSP. Go checkout his website if you want
+to learn more about DSP.
+"""
+
+from .bands import SplitBands, split_bands
+from .fftconv import fft_conv1d, FFTConv1d
+from .filters import bandpass_filter, BandPassFilter
+from .filters import highpass_filter, highpass_filters, HighPassFilter, HighPassFilters
+from .lowpass import lowpass_filter, lowpass_filters, LowPassFilters, LowPassFilter
+from .resample import resample_frac, ResampleFrac
diff --git a/julius/bands.py b/julius/bands.py
new file mode 100644
index 0000000000000000000000000000000000000000..ef2162440b69e960770aa7bf81b9aaec48a63243
--- /dev/null
+++ b/julius/bands.py
@@ -0,0 +1,119 @@
+# File under the MIT license, see https://github.com/adefossez/julius/LICENSE for details.
+# Author: adefossez, 2020
+"""
+Decomposition of a signal over frequency bands in the waveform domain.
+"""
+from typing import Optional, Sequence
+import torch
+
+from .core import mel_frequencies
+from .lowpass import LowPassFilters
+from .utils import simple_repr
+
+
+class SplitBands(torch.nn.Module):
+    """
+    Decomposes a signal over the given frequency bands in the waveform domain using
+    a cascade of low pass filters as implemented by `julius.lowpass.LowPassFilters`.
+    You can either specify explicitely the frequency cutoffs, or just the number of bands,
+    in which case the frequency cutoffs will be spread out evenly in mel scale.
+
+    Args:
+        sample_rate (float): Sample rate of the input signal in Hz.
+        n_bands (int or None): number of bands, when not giving them explictely with `cutoffs`.
+            In that case, the cutoff frequencies will be evenly spaced in mel-space.
+        cutoffs (list[float] or None): list of frequency cutoffs in Hz.
+        pad (bool): if True, appropriately pad the input with zero over the edge. If `stride=1`,
+            the output will have the same length as the input.
+        zeros (float): Number of zero crossings to keep. See `LowPassFilters` for more informations.
+        fft (bool or None): See `LowPassFilters` for more info.
+
+    ..note::
+        The sum of all the bands will always be the input signal.
+
+    ..warning::
+        Unlike `julius.lowpass.LowPassFilters`, the cutoffs frequencies must be provided in Hz along
+        with the sample rate.
+
+    Shape:
+
+        - Input: `[*, T]`
+        - Output: `[B, *, T']`, with `T'=T` if `pad` is True.
+            If `n_bands` was provided, `B = n_bands` otherwise `B = len(cutoffs) + 1`
+
+    >>> bands = SplitBands(sample_rate=128, n_bands=10)
+    >>> x = torch.randn(6, 4, 1024)
+    >>> list(bands(x).shape)
+    [10, 6, 4, 1024]
+    """
+
+    def __init__(self, sample_rate: float, n_bands: Optional[int] = None,
+                 cutoffs: Optional[Sequence[float]] = None, pad: bool = True,
+                 zeros: float = 8, fft: Optional[bool] = None):
+        super().__init__()
+        if (cutoffs is None) + (n_bands is None) != 1:
+            raise ValueError("You must provide either n_bands, or cutoffs, but not boths.")
+
+        self.sample_rate = sample_rate
+        self.n_bands = n_bands
+        self._cutoffs = list(cutoffs) if cutoffs is not None else None
+        self.pad = pad
+        self.zeros = zeros
+        self.fft = fft
+
+        if cutoffs is None:
+            if n_bands is None:
+                raise ValueError("You must provide one of n_bands or cutoffs.")
+            if not n_bands >= 1:
+                raise ValueError(f"n_bands must be greater than one (got {n_bands})")
+            cutoffs = mel_frequencies(n_bands + 1, 0, sample_rate / 2)[1:-1]
+        else:
+            if max(cutoffs) > 0.5 * sample_rate:
+                raise ValueError("A cutoff above sample_rate/2 does not make sense.")
+        if len(cutoffs) > 0:
+            self.lowpass = LowPassFilters(
+                [c / sample_rate for c in cutoffs], pad=pad, zeros=zeros, fft=fft)
+        else:
+            # Here I cannot make both TorchScript and MyPy happy.
+            # I miss the good old times, before all this madness was created.
+            self.lowpass = None  # type: ignore
+
+    def forward(self, input):
+        if self.lowpass is None:
+            return input[None]
+        lows = self.lowpass(input)
+        low = lows[0]
+        bands = [low]
+        for low_and_band in lows[1:]:
+            # Get a bandpass filter by substracting lowpasses
+            band = low_and_band - low
+            bands.append(band)
+            low = low_and_band
+        # Last band is whatever is left in the signal
+        bands.append(input - low)
+        return torch.stack(bands)
+
+    @property
+    def cutoffs(self):
+        if self._cutoffs is not None:
+            return self._cutoffs
+        elif self.lowpass is not None:
+            return [c * self.sample_rate for c in self.lowpass.cutoffs]
+        else:
+            return []
+
+    def __repr__(self):
+        return simple_repr(self, overrides={"cutoffs": self._cutoffs})
+
+
+def split_bands(signal: torch.Tensor, sample_rate: float, n_bands: Optional[int] = None,
+                cutoffs: Optional[Sequence[float]] = None, pad: bool = True,
+                zeros: float = 8, fft: Optional[bool] = None):
+    """
+    Functional version of `SplitBands`, refer to this class for more information.
+
+    >>> x = torch.randn(6, 4, 1024)
+    >>> list(split_bands(x, sample_rate=64, cutoffs=[12, 24]).shape)
+    [3, 6, 4, 1024]
+    """
+    return SplitBands(sample_rate, n_bands, cutoffs, pad, zeros, fft).to(signal)(signal)
diff --git a/julius/core.py b/julius/core.py
new file mode 100644
index 0000000000000000000000000000000000000000..6b750418424e76c9540663ac4b2a16005adaf422
--- /dev/null
+++ b/julius/core.py
@@ -0,0 +1,122 @@
+# File under the MIT license, see https://github.com/adefossez/julius/LICENSE for details.
+# Author: adefossez, 2020
+"""
+Signal processing or PyTorch related utilities.
+"""
+import math
+import typing as tp
+
+import torch
+from torch.nn import functional as F
+
+
+def sinc(x: torch.Tensor):
+    """
+    Implementation of sinc, i.e. sin(x) / x
+
+    __Warning__: the input is not multiplied by `pi`!
+    """
+    return torch.where(x == 0, torch.tensor(1., device=x.device, dtype=x.dtype), torch.sin(x) / x)
+
+
+def pad_to(tensor: torch.Tensor, target_length: int, mode: str = 'constant', value: float = 0):
+    """
+    Pad the given tensor to the given length, with 0s on the right.
+    """
+    return F.pad(tensor, (0, target_length - tensor.shape[-1]), mode=mode, value=value)
+
+
+def hz_to_mel(freqs: torch.Tensor):
+    """
+    Converts a Tensor of frequencies in hertz to the mel scale.
+    Uses the simple formula by O'Shaughnessy (1987).
+
+    Args:
+        freqs (torch.Tensor): frequencies to convert.
+
+    """
+    return 2595 * torch.log10(1 + freqs / 700)
+
+
+def mel_to_hz(mels: torch.Tensor):
+    """
+    Converts a Tensor of mel scaled frequencies to Hertz.
+    Uses the simple formula by O'Shaughnessy (1987).
+
+    Args:
+        mels (torch.Tensor): mel frequencies to convert.
+    """
+    return 700 * (10**(mels / 2595) - 1)
+
+
+def mel_frequencies(n_mels: int, fmin: float, fmax: float):
+    """
+    Return frequencies that are evenly spaced in mel scale.
+
+    Args:
+        n_mels (int): number of frequencies to return.
+        fmin (float): start from this frequency (in Hz).
+        fmax (float): finish at this frequency (in Hz).
+
+
+    """
+    low = hz_to_mel(torch.tensor(float(fmin))).item()
+    high = hz_to_mel(torch.tensor(float(fmax))).item()
+    mels = torch.linspace(low, high, n_mels)
+    return mel_to_hz(mels)
+
+
+def volume(x: torch.Tensor, floor=1e-8):
+    """
+    Return the volume in dBFS.
+    """
+    return torch.log10(floor + (x**2).mean(-1)) * 10
+
+
+def pure_tone(freq: float, sr: float = 128, dur: float = 4, device=None):
+    """
+    Return a pure tone, i.e. cosine.
+
+    Args:
+        freq (float): frequency (in Hz)
+        sr (float): sample rate (in Hz)
+        dur (float): duration (in seconds)
+    """
+    time = torch.arange(int(sr * dur), device=device).float() / sr
+    return torch.cos(2 * math.pi * freq * time)
+
+
+def unfold(input, kernel_size: int, stride: int):
+    """1D only unfolding similar to the one from PyTorch.
+    However PyTorch unfold is extremely slow.
+
+    Given an input tensor of size `[*, T]` this will return
+    a tensor `[*, F, K]` with `K` the kernel size, and `F` the number
+    of frames. The i-th frame is a view onto `i * stride: i * stride + kernel_size`.
+    This will automatically pad the input to cover at least once all entries in `input`.
+
+    Args:
+        input (Tensor): tensor for which to return the frames.
+        kernel_size (int): size of each frame.
+        stride (int): stride between each frame.
+
+    Shape:
+
+        - Inputs: `input` is `[*, T]`
+        - Output: `[*, F, kernel_size]` with `F = 1 + ceil((T - kernel_size) / stride)`
+
+
+    ..Warning:: unlike PyTorch unfold, this will pad the input
+        so that any position in `input` is covered by at least one frame.
+    """
+    shape = list(input.shape)
+    length = shape.pop(-1)
+    n_frames = math.ceil((max(length, kernel_size) - kernel_size) / stride) + 1
+    tgt_length = (n_frames - 1) * stride + kernel_size
+    padded = F.pad(input, (0, tgt_length - length)).contiguous()
+    strides: tp.List[int] = []
+    for dim in range(padded.dim()):
+        strides.append(padded.stride(dim))
+    assert strides.pop(-1) == 1, 'data should be contiguous'
+    strides = strides + [stride, 1]
+    return padded.as_strided(shape + [n_frames, kernel_size], strides)
diff --git a/julius/fftconv.py b/julius/fftconv.py
new file mode 100644
index 0000000000000000000000000000000000000000..1920e5369bb49b76eeea1832b7be2a0ddbc8db6b
--- /dev/null
+++ b/julius/fftconv.py
@@ -0,0 +1,183 @@
+# File under the MIT license, see https://github.com/adefossez/julius/LICENSE for details.
+# Author: adefossez, 2020
+
+"""
+Implementation of a FFT based 1D convolution in PyTorch.
+While FFT is used in CUDNN for small kernel sizes, it is not the case for long ones, e.g. 512.
+This module implements efficient FFT based convolutions for such convolutions. A typical
+application is for evaluationg FIR filters with a long receptive field, typically
+evaluated with a stride of 1.
+"""
+from typing import Optional
+
+import torch
+try:
+    import torch.fft as new_fft
+except ImportError:
+    new_fft = None  # type: ignore
+from torch.nn import functional as F
+
+from .core import pad_to, unfold
+from .utils import simple_repr
+
+
+# This is quite verbose, but sadly needed to make TorchScript happy.
+def _new_rfft(x: torch.Tensor):
+    z = new_fft.rfft(x, dim=-1)
+    return torch.view_as_real(z)
+
+
+def _old_rfft(x: torch.Tensor):
+    return torch.rfft(x, 1)  # type: ignore
+
+
+def _old_irfft(x: torch.Tensor, length: int):
+    result = torch.irfft(x, 1, signal_sizes=(length,))  # type: ignore
+    return result
+
+
+def _new_irfft(x: torch.Tensor, length: int):
+    x = torch.view_as_complex(x)
+    return new_fft.irfft(x, length, dim=-1)
+
+
+if new_fft is None:
+    _rfft = _old_rfft
+    _irfft = _old_irfft
+else:
+    _rfft = _new_rfft
+    _irfft = _new_irfft
+
+
+def _compl_mul_conjugate(a: torch.Tensor, b: torch.Tensor):
+    """
+    Given a and b two tensors of dimension 4
+    with the last dimension being the real and imaginary part,
+    returns a multiplied by the conjugate of b, the multiplication
+    being with respect to the second dimension.
+
+    """
+    # PyTorch 1.7 supports complex number, but not for all operations.
+    # Once the support is widespread, this can likely go away.
+
+    op = "bcft,dct->bdft"
+    return torch.stack([
+        torch.einsum(op, a[..., 0], b[..., 0]) + torch.einsum(op, a[..., 1], b[..., 1]),
+        torch.einsum(op, a[..., 1], b[..., 0]) - torch.einsum(op, a[..., 0], b[..., 1])
+    ],
+                       dim=-1)
+
+
+def fft_conv1d(
+        input: torch.Tensor, weight: torch.Tensor,
+        bias: Optional[torch.Tensor] = None, stride: int = 1, padding: int = 0,
+        block_ratio: float = 5):
+    """
+    Same as `torch.nn.functional.conv1d` but using FFT for the convolution.
+    Please check PyTorch documentation for more information.
+
+    Args:
+        input (Tensor): input signal of shape `[B, C, T]`.
+        weight (Tensor): weight of the convolution `[D, C, K]` with `D` the number
+            of output channels.
+        bias (Tensor or None): if not None, bias term for the convolution.
+        stride (int): stride of convolution.
+        padding (int): padding to apply to the input.
+        block_ratio (float): can be tuned for speed. The input is splitted in chunks
+            with a size of `int(block_ratio * kernel_size)`.
+
+    Shape:
+
+        - Inputs: `input` is `[B, C, T]`, `weight` is `[D, C, K]` and bias is `[D]`.
+        - Output: `(*, T)`
+
+
+    ..note::
+        This function is faster than `torch.nn.functional.conv1d` only in specific cases.
+        Typically, the kernel size should be of the order of 256 to see any real gain,
+        for a stride of 1.
+
+    ..Warning::
+        Dilation and groups are not supported at the moment. This function might use
+        more memory than the default Conv1d implementation.
+    """
+    input = F.pad(input, (padding, padding))
+    batch, channels, length = input.shape
+    out_channels, _, kernel_size = weight.shape
+
+    if length < kernel_size:
+        raise RuntimeError(f"Input should be at least as large as the kernel size {kernel_size}, "
+                           f"but it is only {length} samples long.")
+    if block_ratio < 1:
+        raise RuntimeError("Block ratio must be greater than 1.")
+
+    # We are going to process the input blocks by blocks, as for some reason it is faster
+    # and less memory intensive (I think the culprit is `torch.einsum`.
+    block_size: int = min(int(kernel_size * block_ratio), length)
+    fold_stride = block_size - kernel_size + 1
+    weight = pad_to(weight, block_size)
+    weight_z = _rfft(weight)
+
+    # We pad the input and get the different frames, on which
+    frames = unfold(input, block_size, fold_stride)
+
+    frames_z = _rfft(frames)
+    out_z = _compl_mul_conjugate(frames_z, weight_z)
+    out = _irfft(out_z, block_size)
+    # The last bit is invalid, because FFT will do a circular convolution.
+    out = out[..., :-kernel_size + 1]
+    out = out.reshape(batch, out_channels, -1)
+    out = out[..., ::stride]
+    target_length = (length - kernel_size) // stride + 1
+    out = out[..., :target_length]
+    if bias is not None:
+        out += bias[:, None]
+    return out
+
+
+class FFTConv1d(torch.nn.Module):
+    """
+    Same as `torch.nn.Conv1d` but based on `fft_conv1d`.
+    Please check PyTorch documentation for more information.
+
+    Args:
+        in_channels (int): number of input channels.
+        out_channels (int): number of output channels.
+        kernel_size (int): kernel size of convolution.
+        stride (int): stride of convolution.
+        padding (int): padding to apply to the input.
+        bias (bool): if True, use a bias term.
+
+    ..note::
+        This module is faster than `torch.nn.Conv1d` only in specific cases.
+        Typically, `kernel_size` should be of the order of 256 to see any real gain,
+        for a stride of 1.
+
+    ..warning::
+        Dilation and groups are not supported at the moment. This module might use
+        more memory than the default Conv1d implementation.
+
+    >>> fftconv = FFTConv1d(12, 24, 128, 4)
+    >>> x = torch.randn(4, 12, 1024)
+    >>> print(list(fftconv(x).shape))
+    [4, 24, 225]
+    """
+    def __init__(self, in_channels: int, out_channels: int, kernel_size: int,
+                 stride: int = 1, padding: int = 0, bias: bool = True):
+        super().__init__()
+        self.in_channels = in_channels
+        self.out_channels = out_channels
+        self.kernel_size = kernel_size
+        self.stride = stride
+        self.padding = padding
+
+        conv = torch.nn.Conv1d(in_channels, out_channels, kernel_size, bias=bias)
+        self.weight = conv.weight
+        self.bias = conv.bias
+
+    def forward(self, input: torch.Tensor):
+        return fft_conv1d(
+            input, self.weight, self.bias, self.stride, self.padding)
+
+    def __repr__(self):
+        return simple_repr(self, overrides={"bias": self.bias is not None})
diff --git a/julius/filters.py b/julius/filters.py
new file mode 100644
index 0000000000000000000000000000000000000000..afabcc0158e4cf45d215174b4f946ca1b0e3acaa
--- /dev/null
+++ b/julius/filters.py
@@ -0,0 +1,258 @@
+# File under the MIT license, see https://github.com/adefossez/julius/LICENSE for details.
+# Author: adefossez, 2021
+"""
+FIR windowed sinc highpass and bandpass filters.
+Those are convenience wrappers around the filters defined in `julius.lowpass`.
+"""
+
+from typing import Sequence, Optional
+
+import torch
+
+# Import all lowpass filters for consistency.
+from .lowpass import lowpass_filter, lowpass_filters, LowPassFilter,  LowPassFilters  # noqa
+from .utils import simple_repr
+
+
+class HighPassFilters(torch.nn.Module):
+    """
+    Bank of high pass filters. See `julius.lowpass.LowPassFilters` for more
+    details on the implementation.
+
+    Args:
+        cutoffs (list[float]): list of cutoff frequencies, in [0, 0.5] expressed as `f/f_s` where
+            f_s is the samplerate and `f` is the cutoff frequency.
+            The upper limit is 0.5, because a signal sampled at `f_s` contains only
+            frequencies under `f_s / 2`.
+        stride (int): how much to decimate the output. Probably not a good idea
+            to do so with a high pass filters though...
+        pad (bool): if True, appropriately pad the input with zero over the edge. If `stride=1`,
+            the output will have the same length as the input.
+        zeros (float): Number of zero crossings to keep.
+            Controls the receptive field of the Finite Impulse Response filter.
+            For filters with low cutoff frequency, e.g. 40Hz at 44.1kHz,
+            it is a bad idea to set this to a high value.
+            This is likely appropriate for most use. Lower values
+            will result in a faster filter, but with a slower attenuation around the
+            cutoff frequency.
+        fft (bool or None): if True, uses `julius.fftconv` rather than PyTorch convolutions.
+            If False, uses PyTorch convolutions. If None, either one will be chosen automatically
+            depending on the effective filter size.
+
+
+    ..warning::
+        All the filters will use the same filter size, aligned on the lowest
+        frequency provided. If you combine a lot of filters with very diverse frequencies, it might
+        be more efficient to split them over multiple modules with similar frequencies.
+
+    Shape:
+
+        - Input: `[*, T]`
+        - Output: `[F, *, T']`, with `T'=T` if `pad` is True and `stride` is 1, and
+            `F` is the numer of cutoff frequencies.
+
+    >>> highpass = HighPassFilters([1/4])
+    >>> x = torch.randn(4, 12, 21, 1024)
+    >>> list(highpass(x).shape)
+    [1, 4, 12, 21, 1024]
+    """
+
+    def __init__(self, cutoffs: Sequence[float], stride: int = 1, pad: bool = True,
+                 zeros: float = 8, fft: Optional[bool] = None):
+        super().__init__()
+        self._lowpasses = LowPassFilters(cutoffs, stride, pad, zeros, fft)
+
+    @property
+    def cutoffs(self):
+        return self._lowpasses.cutoffs
+
+    @property
+    def stride(self):
+        return self._lowpasses.stride
+
+    @property
+    def pad(self):
+        return self._lowpasses.pad
+
+    @property
+    def zeros(self):
+        return self._lowpasses.zeros
+
+    @property
+    def fft(self):
+        return self._lowpasses.fft
+
+    def forward(self, input):
+        lows = self._lowpasses(input)
+
+        # We need to extract the right portion of the input in case
+        # pad is False or stride > 1
+        if self.pad:
+            start, end = 0, input.shape[-1]
+        else:
+            start = self._lowpasses.half_size
+            end = -start
+        input = input[..., start:end:self.stride]
+        highs = input - lows
+        return highs
+
+    def __repr__(self):
+        return simple_repr(self)
+
+
+class HighPassFilter(torch.nn.Module):
+    """
+    Same as `HighPassFilters` but applies a single high pass filter.
+
+    Shape:
+
+        - Input: `[*, T]`
+        - Output: `[*, T']`, with `T'=T` if `pad` is True and `stride` is 1.
+
+    >>> highpass = HighPassFilter(1/4, stride=1)
+    >>> x = torch.randn(4, 124)
+    >>> list(highpass(x).shape)
+    [4, 124]
+    """
+
+    def __init__(self, cutoff: float, stride: int = 1, pad: bool = True,
+                 zeros: float = 8, fft: Optional[bool] = None):
+        super().__init__()
+        self._highpasses = HighPassFilters([cutoff], stride, pad, zeros, fft)
+
+    @property
+    def cutoff(self):
+        return self._highpasses.cutoffs[0]
+
+    @property
+    def stride(self):
+        return self._highpasses.stride
+
+    @property
+    def pad(self):
+        return self._highpasses.pad
+
+    @property
+    def zeros(self):
+        return self._highpasses.zeros
+
+    @property
+    def fft(self):
+        return self._highpasses.fft
+
+    def forward(self, input):
+        return self._highpasses(input)[0]
+
+    def __repr__(self):
+        return simple_repr(self)
+
+
+def highpass_filters(input: torch.Tensor,  cutoffs: Sequence[float],
+                     stride: int = 1, pad: bool = True,
+                     zeros: float = 8, fft: Optional[bool] = None):
+    """
+    Functional version of `HighPassFilters`, refer to this class for more information.
+    """
+    return HighPassFilters(cutoffs, stride, pad, zeros, fft).to(input)(input)
+
+
+def highpass_filter(input: torch.Tensor,  cutoff: float,
+                    stride: int = 1, pad: bool = True,
+                    zeros: float = 8, fft: Optional[bool] = None):
+    """
+    Functional version of `HighPassFilter`, refer to this class for more information.
+    Output will not have a dimension inserted in the front.
+    """
+    return highpass_filters(input, [cutoff], stride, pad, zeros, fft)[0]
+
+
+class BandPassFilter(torch.nn.Module):
+    """
+    Single band pass filter, implemented as a the difference of two lowpass filters.
+
+    Args:
+        cutoff_low (float): lower cutoff frequency, in [0, 0.5] expressed as `f/f_s` where
+            f_s is the samplerate and `f` is the cutoff frequency.
+            The upper limit is 0.5, because a signal sampled at `f_s` contains only
+            frequencies under `f_s / 2`.
+        cutoff_high (float): higher cutoff frequency, in [0, 0.5] expressed as `f/f_s`.
+            This must be higher than cutoff_high. Note that due to the fact
+            that filter are not perfect, the output will be non zero even if
+            cutoff_high == cutoff_low.
+        stride (int): how much to decimate the output.
+        pad (bool): if True, appropriately pad the input with zero over the edge. If `stride=1`,
+            the output will have the same length as the input.
+        zeros (float): Number of zero crossings to keep.
+            Controls the receptive field of the Finite Impulse Response filter.
+            For filters with low cutoff frequency, e.g. 40Hz at 44.1kHz,
+            it is a bad idea to set this to a high value.
+            This is likely appropriate for most use. Lower values
+            will result in a faster filter, but with a slower attenuation around the
+            cutoff frequency.
+        fft (bool or None): if True, uses `julius.fftconv` rather than PyTorch convolutions.
+            If False, uses PyTorch convolutions. If None, either one will be chosen automatically
+            depending on the effective filter size.
+
+
+    Shape:
+
+        - Input: `[*, T]`
+        - Output: `[*, T']`, with `T'=T` if `pad` is True and `stride` is 1.
+
+    ..Note:: There is no BandPassFilters (bank of bandpasses) because its
+        signification would be the same as `julius.bands.SplitBands`.
+
+    >>> bandpass = BandPassFilter(1/4, 1/3)
+    >>> x = torch.randn(4, 12, 21, 1024)
+    >>> list(bandpass(x).shape)
+    [4, 12, 21, 1024]
+    """
+
+    def __init__(self, cutoff_low: float, cutoff_high: float, stride: int = 1, pad: bool = True,
+                 zeros: float = 8, fft: Optional[bool] = None):
+        super().__init__()
+        if cutoff_low > cutoff_high:
+            raise ValueError(f"Lower cutoff {cutoff_low} should be less than "
+                             f"higher cutoff {cutoff_high}.")
+        self._lowpasses = LowPassFilters([cutoff_low, cutoff_high], stride, pad, zeros, fft)
+
+    @property
+    def cutoff_low(self):
+        return self._lowpasses.cutoffs[0]
+
+    @property
+    def cutoff_high(self):
+        return self._lowpasses.cutoffs[1]
+
+    @property
+    def stride(self):
+        return self._lowpasses.stride
+
+    @property
+    def pad(self):
+        return self._lowpasses.pad
+
+    @property
+    def zeros(self):
+        return self._lowpasses.zeros
+
+    @property
+    def fft(self):
+        return self._lowpasses.fft
+
+    def forward(self, input):
+        lows = self._lowpasses(input)
+        return lows[1] - lows[0]
+
+    def __repr__(self):
+        return simple_repr(self)
+
+
+def bandpass_filter(input: torch.Tensor,  cutoff_low: float, cutoff_high: float,
+                    stride: int = 1, pad: bool = True,
+                    zeros: float = 8, fft: Optional[bool] = None):
+    """
+    Functional version of `BandPassfilter`, refer to this class for more information.
+    Output will not have a dimension inserted in the front.
+    """
+    return BandPassFilter(cutoff_low, cutoff_high, stride, pad, zeros, fft).to(input)(input)
diff --git a/julius/lowpass.py b/julius/lowpass.py
new file mode 100644
index 0000000000000000000000000000000000000000..0eb46e382b20bfc2d93482f9f027986b863de6f0
--- /dev/null
+++ b/julius/lowpass.py
@@ -0,0 +1,181 @@
+# File under the MIT license, see https://github.com/adefossez/julius/LICENSE for details.
+# Author: adefossez, 2020
+"""
+FIR windowed sinc lowpass filters.
+"""
+
+import math
+from typing import Sequence, Optional
+
+import torch
+from torch.nn import functional as F
+
+from .core import sinc
+from .fftconv import fft_conv1d
+from .utils import simple_repr
+
+
+class LowPassFilters(torch.nn.Module):
+    """
+    Bank of low pass filters. Note that a high pass or band pass filter can easily
+    be implemented by substracting a same signal processed with low pass filters with different
+    frequencies (see `julius.bands.SplitBands` for instance).
+    This uses a windowed sinc filter, very similar to the one used in
+    `julius.resample`. However, because we do not change the sample rate here,
+    this filter can be much more efficiently implemented using the FFT convolution from
+    `julius.fftconv`.
+
+    Args:
+        cutoffs (list[float]): list of cutoff frequencies, in [0, 0.5] expressed as `f/f_s` where
+            f_s is the samplerate and `f` is the cutoff frequency.
+            The upper limit is 0.5, because a signal sampled at `f_s` contains only
+            frequencies under `f_s / 2`.
+        stride (int): how much to decimate the output. Keep in mind that decimation
+            of the output is only acceptable if the cutoff frequency is under `1/ (2 * stride)`
+            of the original sampling rate.
+        pad (bool): if True, appropriately pad the input with zero over the edge. If `stride=1`,
+            the output will have the same length as the input.
+        zeros (float): Number of zero crossings to keep.
+            Controls the receptive field of the Finite Impulse Response filter.
+            For lowpass filters with low cutoff frequency, e.g. 40Hz at 44.1kHz,
+            it is a bad idea to set this to a high value.
+            This is likely appropriate for most use. Lower values
+            will result in a faster filter, but with a slower attenuation around the
+            cutoff frequency.
+        fft (bool or None): if True, uses `julius.fftconv` rather than PyTorch convolutions.
+            If False, uses PyTorch convolutions. If None, either one will be chosen automatically
+            depending on the effective filter size.
+
+
+    ..warning::
+        All the filters will use the same filter size, aligned on the lowest
+        frequency provided. If you combine a lot of filters with very diverse frequencies, it might
+        be more efficient to split them over multiple modules with similar frequencies.
+
+    ..note::
+        A lowpass with a cutoff frequency of 0 is defined as the null function
+        by convention here. This allows for a highpass with a cutoff of 0 to
+        be equal to identity, as defined in `julius.filters.HighPassFilters`.
+
+    Shape:
+
+        - Input: `[*, T]`
+        - Output: `[F, *, T']`, with `T'=T` if `pad` is True and `stride` is 1, and
+            `F` is the numer of cutoff frequencies.
+
+    >>> lowpass = LowPassFilters([1/4])
+    >>> x = torch.randn(4, 12, 21, 1024)
+    >>> list(lowpass(x).shape)
+    [1, 4, 12, 21, 1024]
+    """
+
+    def __init__(self, cutoffs: Sequence[float], stride: int = 1, pad: bool = True,
+                 zeros: float = 8, fft: Optional[bool] = None):
+        super().__init__()
+        self.cutoffs = list(cutoffs)
+        if min(self.cutoffs) < 0:
+            raise ValueError("Minimum cutoff must be larger than zero.")
+        if max(self.cutoffs) > 0.5:
+            raise ValueError("A cutoff above 0.5 does not make sense.")
+        self.stride = stride
+        self.pad = pad
+        self.zeros = zeros
+        self.half_size = int(zeros / min([c for c in self.cutoffs if c > 0]) / 2)
+        if fft is None:
+            fft = self.half_size > 32
+        self.fft = fft
+        window = torch.hann_window(2 * self.half_size + 1, periodic=False)
+        time = torch.arange(-self.half_size, self.half_size + 1)
+        filters = []
+        for cutoff in cutoffs:
+            if cutoff == 0:
+                filter_ = torch.zeros_like(time)
+            else:
+                filter_ = 2 * cutoff * window * sinc(2 * cutoff * math.pi * time)
+                # Normalize filter to have sum = 1, otherwise we will have a small leakage
+                # of the constant component in the input signal.
+                filter_ /= filter_.sum()
+            filters.append(filter_)
+        self.register_buffer("filters", torch.stack(filters)[:, None])
+
+    def forward(self, input):
+        shape = list(input.shape)
+        input = input.view(-1, 1, shape[-1])
+        if self.pad:
+            input = F.pad(input, (self.half_size, self.half_size), mode='replicate')
+        if self.fft:
+            out = fft_conv1d(input, self.filters, stride=self.stride)
+        else:
+            out = F.conv1d(input, self.filters, stride=self.stride)
+        shape.insert(0, len(self.cutoffs))
+        shape[-1] = out.shape[-1]
+        return out.permute(1, 0, 2).reshape(shape)
+
+    def __repr__(self):
+        return simple_repr(self)
+
+
+class LowPassFilter(torch.nn.Module):
+    """
+    Same as `LowPassFilters` but applies a single low pass filter.
+
+    Shape:
+
+        - Input: `[*, T]`
+        - Output: `[*, T']`, with `T'=T` if `pad` is True and `stride` is 1.
+
+    >>> lowpass = LowPassFilter(1/4, stride=2)
+    >>> x = torch.randn(4, 124)
+    >>> list(lowpass(x).shape)
+    [4, 62]
+    """
+
+    def __init__(self, cutoff: float, stride: int = 1, pad: bool = True,
+                 zeros: float = 8, fft: Optional[bool] = None):
+        super().__init__()
+        self._lowpasses = LowPassFilters([cutoff], stride, pad, zeros, fft)
+
+    @property
+    def cutoff(self):
+        return self._lowpasses.cutoffs[0]
+
+    @property
+    def stride(self):
+        return self._lowpasses.stride
+
+    @property
+    def pad(self):
+        return self._lowpasses.pad
+
+    @property
+    def zeros(self):
+        return self._lowpasses.zeros
+
+    @property
+    def fft(self):
+        return self._lowpasses.fft
+
+    def forward(self, input):
+        return self._lowpasses(input)[0]
+
+    def __repr__(self):
+        return simple_repr(self)
+
+
+def lowpass_filters(input: torch.Tensor,  cutoffs: Sequence[float],
+                    stride: int = 1, pad: bool = True,
+                    zeros: float = 8, fft: Optional[bool] = None):
+    """
+    Functional version of `LowPassFilters`, refer to this class for more information.
+    """
+    return LowPassFilters(cutoffs, stride, pad, zeros, fft).to(input)(input)
+
+
+def lowpass_filter(input: torch.Tensor,  cutoff: float,
+                   stride: int = 1, pad: bool = True,
+                   zeros: float = 8, fft: Optional[bool] = None):
+    """
+    Same as `lowpass_filters` but with a single cutoff frequency.
+    Output will not have a dimension inserted in the front.
+    """
+    return lowpass_filters(input, [cutoff], stride, pad, zeros, fft)[0]
diff --git a/julius/resample.py b/julius/resample.py
new file mode 100644
index 0000000000000000000000000000000000000000..fd3b9b547d4c33ec7136d32e5f086420d0a72e14
--- /dev/null
+++ b/julius/resample.py
@@ -0,0 +1,216 @@
+# File under the MIT license, see https://github.com/adefossez/julius/LICENSE for details.
+# Author: adefossez, 2020
+"""
+Differentiable, Pytorch based resampling.
+Implementation of Julius O. Smith algorithm for resampling.
+See https://ccrma.stanford.edu/~jos/resample/ for details.
+This implementation is specially optimized for when new_sr / old_sr is a fraction
+with a small numerator and denominator when removing the gcd (e.g. new_sr = 700, old_sr = 500).
+
+Very similar to [bmcfee/resampy](https://github.com/bmcfee/resampy) except this implementation
+is optimized for the case mentioned before, while resampy is slower but more general.
+
+"""
+
+import math
+from typing import Optional
+
+import torch
+from torch.nn import functional as F
+
+from .core import sinc
+from .utils import simple_repr
+
+
+class ResampleFrac(torch.nn.Module):
+    """
+    Resampling from the sample rate `old_sr` to `new_sr`.
+    """
+    def __init__(self, old_sr: int, new_sr: int, zeros: int = 24, rolloff: float = 0.945):
+        """
+        Args:
+            old_sr (int): sample rate of the input signal x.
+            new_sr (int): sample rate of the output.
+            zeros (int): number of zero crossing to keep in the sinc filter.
+            rolloff (float): use a lowpass filter that is `rolloff * new_sr / 2`,
+                to ensure sufficient margin due to the imperfection of the FIR filter used.
+                Lowering this value will reduce anti-aliasing, but will reduce some of the
+                highest frequencies.
+
+        Shape:
+
+            - Input: `[*, T]`
+            - Output: `[*, T']` with `T' = int(new_sr * T / old_sr)
+
+
+        .. caution::
+            After dividing `old_sr` and `new_sr` by their GCD, both should be small
+            for this implementation to be fast.
+
+        >>> import torch
+        >>> resample = ResampleFrac(4, 5)
+        >>> x = torch.randn(1000)
+        >>> print(len(resample(x)))
+        1250
+        """
+        super().__init__()
+        if not isinstance(old_sr, int) or not isinstance(new_sr, int):
+            raise ValueError("old_sr and new_sr should be integers")
+        gcd = math.gcd(old_sr, new_sr)
+        self.old_sr = old_sr // gcd
+        self.new_sr = new_sr // gcd
+        self.zeros = zeros
+        self.rolloff = rolloff
+
+        self._init_kernels()
+
+    def _init_kernels(self):
+        if self.old_sr == self.new_sr:
+            return
+
+        kernels = []
+        sr = min(self.new_sr, self.old_sr)
+        # rolloff will perform antialiasing filtering by removing the highest frequencies.
+        # At first I thought I only needed this when downsampling, but when upsampling
+        # you will get edge artifacts without this, the edge is equivalent to zero padding,
+        # which will add high freq artifacts.
+        sr *= self.rolloff
+
+        # The key idea of the algorithm is that x(t) can be exactly reconstructed from x[i] (tensor)
+        # using the sinc interpolation formula:
+        #   x(t) = sum_i x[i] sinc(pi * old_sr * (i / old_sr - t))
+        # We can then sample the function x(t) with a different sample rate:
+        #    y[j] = x(j / new_sr)
+        # or,
+        #    y[j] = sum_i x[i] sinc(pi * old_sr * (i / old_sr - j / new_sr))
+
+        # We see here that y[j] is the convolution of x[i] with a specific filter, for which
+        # we take an FIR approximation, stopping when we see at least `zeros` zeros crossing.
+        # But y[j+1] is going to have a different set of weights and so on, until y[j + new_sr].
+        # Indeed:
+        # y[j + new_sr] = sum_i x[i] sinc(pi * old_sr * ((i / old_sr - (j + new_sr) / new_sr))
+        #               = sum_i x[i] sinc(pi * old_sr * ((i - old_sr) / old_sr - j / new_sr))
+        #               = sum_i x[i + old_sr] sinc(pi * old_sr * (i / old_sr - j / new_sr))
+        # so y[j+new_sr] uses the same filter as y[j], but on a shifted version of x by `old_sr`.
+        # This will explain the F.conv1d after, with a stride of old_sr.
+        self._width = math.ceil(self.zeros * self.old_sr / sr)
+        # If old_sr is still big after GCD reduction, most filters will be very unbalanced, i.e.,
+        # they will have a lot of almost zero values to the left or to the right...
+        # There is probably a way to evaluate those filters more efficiently, but this is kept for
+        # future work.
+        idx = torch.arange(-self._width, self._width + self.old_sr).float()
+        for i in range(self.new_sr):
+            t = (-i/self.new_sr + idx/self.old_sr) * sr
+            t = t.clamp_(-self.zeros, self.zeros)
+            t *= math.pi
+            window = torch.cos(t/self.zeros/2)**2
+            kernel = sinc(t) * window
+            # Renormalize kernel to ensure a constant signal is preserved.
+            kernel.div_(kernel.sum())
+            kernels.append(kernel)
+
+        self.register_buffer("kernel", torch.stack(kernels).view(self.new_sr, 1, -1))
+
+    def forward(self, x: torch.Tensor, output_length: Optional[int] = None, full: bool = False):
+        """
+        Resample x.
+        Args:
+            x (Tensor): signal to resample, time should be the last dimension
+            output_length (None or int): This can be set to the desired output length
+                (last dimension). Allowed values are between 0 and
+                ceil(length * new_sr / old_sr). When None (default) is specified, the
+                floored output length will be used. In order to select the largest possible
+                size, use the `full` argument.
+            full (bool): return the longest possible output from the input. This can be useful
+                if you chain resampling operations, and want to give the `output_length` only
+                for the last one, while passing `full=True` to all the other ones.
+        """
+        if self.old_sr == self.new_sr:
+            return x
+        shape = x.shape
+        length = x.shape[-1]
+        x = x.reshape(-1, length)
+        x = F.pad(x[:, None], (self._width, self._width + self.old_sr), mode='replicate')
+        ys = F.conv1d(x, self.kernel, stride=self.old_sr)  # type: ignore
+        y = ys.transpose(1, 2).reshape(list(shape[:-1]) + [-1])
+
+        float_output_length = self.new_sr * length / self.old_sr
+        max_output_length = int(math.ceil(float_output_length))
+        default_output_length = int(float_output_length)
+        if output_length is None:
+            output_length = max_output_length if full else default_output_length
+        elif output_length < 0 or output_length > max_output_length:
+            raise ValueError(f"output_length must be between 0 and {max_output_length}")
+        else:
+            if full:
+                raise ValueError("You cannot pass both full=True and output_length")
+        return y[..., :output_length]
+
+    def __repr__(self):
+        return simple_repr(self)
+
+
+def resample_frac(x: torch.Tensor, old_sr: int, new_sr: int,
+                  zeros: int = 24, rolloff: float = 0.945,
+                  output_length: Optional[int] = None, full: bool = False):
+    """
+    Functional version of `ResampleFrac`, refer to its documentation for more information.
+
+    ..warning::
+        If you call repeatidly this functions with the same sample rates, then the
+        resampling kernel will be recomputed everytime. For best performance, you should use
+        and cache an instance of `ResampleFrac`.
+    """
+    return ResampleFrac(old_sr, new_sr, zeros, rolloff).to(x)(x, output_length, full)
+
+
+# Easier implementations for downsampling and upsampling by a factor of 2
+# Kept for testing and reference
+
+def _kernel_upsample2_downsample2(zeros):
+    # Kernel for upsampling and downsampling by a factor of 2. Interestingly,
+    # it is the same kernel used for both.
+    win = torch.hann_window(4 * zeros + 1, periodic=False)
+    winodd = win[1::2]
+    t = torch.linspace(-zeros + 0.5, zeros - 0.5, 2 * zeros)
+    t *= math.pi
+    kernel = (sinc(t) * winodd).view(1, 1, -1)
+    return kernel
+
+
+def _upsample2(x, zeros=24):
+    """
+    Upsample x by a factor of two. The output will be exactly twice as long as the input.
+    Args:
+        x (Tensor): signal to upsample, time should be the last dimension
+        zeros (int): number of zero crossing to keep in the sinc filter.
+
+    This function is kept only for reference, you should use the more generic `resample_frac`
+    one. This function does not perform anti-aliasing filtering.
+    """
+    *other, time = x.shape
+    kernel = _kernel_upsample2_downsample2(zeros).to(x)
+    out = F.conv1d(x.view(-1, 1, time), kernel, padding=zeros)[..., 1:].view(*other, time)
+    y = torch.stack([x, out], dim=-1)
+    return y.view(*other, -1)
+
+
+def _downsample2(x, zeros=24):
+    """
+    Downsample x by a factor of two. The output length is half of the input, ceiled.
+    Args:
+        x (Tensor): signal to downsample, time should be the last dimension
+        zeros (int): number of zero crossing to keep in the sinc filter.
+
+    This function is kept only for reference, you should use the more generic `resample_frac`
+    one. This function does not perform anti-aliasing filtering.
+    """
+    if x.shape[-1] % 2 != 0:
+        x = F.pad(x, (0, 1))
+    xeven = x[..., ::2]
+    xodd = x[..., 1::2]
+    *other, time = xodd.shape
+    kernel = _kernel_upsample2_downsample2(zeros).to(x)
+    out = xeven + F.conv1d(xodd.view(-1, 1, time), kernel, padding=zeros)[..., :-1].view(
+        *other, time)
+    return out.view(*other, -1).mul(0.5)
diff --git a/julius/utils.py b/julius/utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..944b973ad1a38700c1ba98ab7306c233cb87868d
--- /dev/null
+++ b/julius/utils.py
@@ -0,0 +1,101 @@
+# File under the MIT license, see https://github.com/adefossez/julius/LICENSE for details.
+# Author: adefossez, 2020
+"""
+Non signal processing related utilities.
+"""
+
+import inspect
+import typing as tp
+import sys
+import time
+
+
+def simple_repr(obj, attrs: tp.Optional[tp.Sequence[str]] = None,
+                overrides: dict = {}):
+    """
+    Return a simple representation string for `obj`.
+    If `attrs` is not None, it should be a list of attributes to include.
+    """
+    params = inspect.signature(obj.__class__).parameters
+    attrs_repr = []
+    if attrs is None:
+        attrs = list(params.keys())
+    for attr in attrs:
+        display = False
+        if attr in overrides:
+            value = overrides[attr]
+        elif hasattr(obj, attr):
+            value = getattr(obj, attr)
+        else:
+            continue
+        if attr in params:
+            param = params[attr]
+            if param.default is inspect._empty or value != param.default:  # type: ignore
+                display = True
+        else:
+            display = True
+
+        if display:
+            attrs_repr.append(f"{attr}={value}")
+    return f"{obj.__class__.__name__}({','.join(attrs_repr)})"
+
+
+class MarkdownTable:
+    """
+    Simple MarkdownTable generator. The column titles should be large enough
+    for the lines content. This will right align everything.
+
+    >>> import io  # we use io purely for test purposes, default is sys.stdout.
+    >>> file = io.StringIO()
+    >>> table = MarkdownTable(["Item Name", "Price"], file=file)
+    >>> table.header(); table.line(["Honey", "5"]); table.line(["Car", "5,000"])
+    >>> print(file.getvalue().strip())  # Strip for test purposes
+    | Item Name | Price |
+    |-----------|-------|
+    |     Honey |     5 |
+    |       Car | 5,000 |
+    """
+    def __init__(self, columns, file=sys.stdout):
+        self.columns = columns
+        self.file = file
+
+    def _writeln(self, line):
+        self.file.write("|" + "|".join(line) + "|\n")
+
+    def header(self):
+        self._writeln(f" {col} " for col in self.columns)
+        self._writeln("-" * (len(col) + 2) for col in self.columns)
+
+    def line(self, line):
+        out = []
+        for val, col in zip(line, self.columns):
+            val = format(val, '>' + str(len(col)))
+            out.append(" " + val + " ")
+        self._writeln(out)
+
+
+class Chrono:
+    """
+    Measures ellapsed time, calling `torch.cuda.synchronize` if necessary.
+    `Chrono` instances can be used as context managers (e.g. with `with`).
+    Upon exit of the block, you can access the duration of the block in seconds
+    with the `duration` attribute.
+
+    >>> with Chrono() as chrono:
+    ...     _ = sum(range(10_000))
+    ...
+    >>> print(chrono.duration < 10)  # Should be true unless on a really slow computer.
+    True
+    """
+    def __init__(self):
+        self.duration = None
+
+    def __enter__(self):
+        self._begin = time.time()
+        return self
+
+    def __exit__(self, exc_type, exc_value, exc_tracebck):
+        import torch
+        if torch.cuda.is_available():
+            torch.cuda.synchronize()
+        self.duration = time.time() - self._begin
diff --git a/lib/globals/globals.py b/lib/globals/globals.py
new file mode 100644
index 0000000000000000000000000000000000000000..d0da59d56e8c2e482bcda5eeae7cf797b830560e
--- /dev/null
+++ b/lib/globals/globals.py
@@ -0,0 +1,5 @@
+DoFormant: bool = False
+Quefrency: float = 8.0
+Timbre: float = 1.2
+
+NotesOrHertz: bool = False
\ No newline at end of file
diff --git a/lib/infer_pack/attentions.py b/lib/infer_pack/attentions.py
new file mode 100644
index 0000000000000000000000000000000000000000..05501be1871643f78dddbeaa529c96667031a8db
--- /dev/null
+++ b/lib/infer_pack/attentions.py
@@ -0,0 +1,417 @@
+import copy
+import math
+import numpy as np
+import torch
+from torch import nn
+from torch.nn import functional as F
+
+from lib.infer_pack import commons
+from lib.infer_pack import modules
+from lib.infer_pack.modules import LayerNorm
+
+
+class Encoder(nn.Module):
+    def __init__(
+        self,
+        hidden_channels,
+        filter_channels,
+        n_heads,
+        n_layers,
+        kernel_size=1,
+        p_dropout=0.0,
+        window_size=10,
+        **kwargs
+    ):
+        super().__init__()
+        self.hidden_channels = hidden_channels
+        self.filter_channels = filter_channels
+        self.n_heads = n_heads
+        self.n_layers = n_layers
+        self.kernel_size = kernel_size
+        self.p_dropout = p_dropout
+        self.window_size = window_size
+
+        self.drop = nn.Dropout(p_dropout)
+        self.attn_layers = nn.ModuleList()
+        self.norm_layers_1 = nn.ModuleList()
+        self.ffn_layers = nn.ModuleList()
+        self.norm_layers_2 = nn.ModuleList()
+        for i in range(self.n_layers):
+            self.attn_layers.append(
+                MultiHeadAttention(
+                    hidden_channels,
+                    hidden_channels,
+                    n_heads,
+                    p_dropout=p_dropout,
+                    window_size=window_size,
+                )
+            )
+            self.norm_layers_1.append(LayerNorm(hidden_channels))
+            self.ffn_layers.append(
+                FFN(
+                    hidden_channels,
+                    hidden_channels,
+                    filter_channels,
+                    kernel_size,
+                    p_dropout=p_dropout,
+                )
+            )
+            self.norm_layers_2.append(LayerNorm(hidden_channels))
+
+    def forward(self, x, x_mask):
+        attn_mask = x_mask.unsqueeze(2) * x_mask.unsqueeze(-1)
+        x = x * x_mask
+        for i in range(self.n_layers):
+            y = self.attn_layers[i](x, x, attn_mask)
+            y = self.drop(y)
+            x = self.norm_layers_1[i](x + y)
+
+            y = self.ffn_layers[i](x, x_mask)
+            y = self.drop(y)
+            x = self.norm_layers_2[i](x + y)
+        x = x * x_mask
+        return x
+
+
+class Decoder(nn.Module):
+    def __init__(
+        self,
+        hidden_channels,
+        filter_channels,
+        n_heads,
+        n_layers,
+        kernel_size=1,
+        p_dropout=0.0,
+        proximal_bias=False,
+        proximal_init=True,
+        **kwargs
+    ):
+        super().__init__()
+        self.hidden_channels = hidden_channels
+        self.filter_channels = filter_channels
+        self.n_heads = n_heads
+        self.n_layers = n_layers
+        self.kernel_size = kernel_size
+        self.p_dropout = p_dropout
+        self.proximal_bias = proximal_bias
+        self.proximal_init = proximal_init
+
+        self.drop = nn.Dropout(p_dropout)
+        self.self_attn_layers = nn.ModuleList()
+        self.norm_layers_0 = nn.ModuleList()
+        self.encdec_attn_layers = nn.ModuleList()
+        self.norm_layers_1 = nn.ModuleList()
+        self.ffn_layers = nn.ModuleList()
+        self.norm_layers_2 = nn.ModuleList()
+        for i in range(self.n_layers):
+            self.self_attn_layers.append(
+                MultiHeadAttention(
+                    hidden_channels,
+                    hidden_channels,
+                    n_heads,
+                    p_dropout=p_dropout,
+                    proximal_bias=proximal_bias,
+                    proximal_init=proximal_init,
+                )
+            )
+            self.norm_layers_0.append(LayerNorm(hidden_channels))
+            self.encdec_attn_layers.append(
+                MultiHeadAttention(
+                    hidden_channels, hidden_channels, n_heads, p_dropout=p_dropout
+                )
+            )
+            self.norm_layers_1.append(LayerNorm(hidden_channels))
+            self.ffn_layers.append(
+                FFN(
+                    hidden_channels,
+                    hidden_channels,
+                    filter_channels,
+                    kernel_size,
+                    p_dropout=p_dropout,
+                    causal=True,
+                )
+            )
+            self.norm_layers_2.append(LayerNorm(hidden_channels))
+
+    def forward(self, x, x_mask, h, h_mask):
+        """
+        x: decoder input
+        h: encoder output
+        """
+        self_attn_mask = commons.subsequent_mask(x_mask.size(2)).to(
+            device=x.device, dtype=x.dtype
+        )
+        encdec_attn_mask = h_mask.unsqueeze(2) * x_mask.unsqueeze(-1)
+        x = x * x_mask
+        for i in range(self.n_layers):
+            y = self.self_attn_layers[i](x, x, self_attn_mask)
+            y = self.drop(y)
+            x = self.norm_layers_0[i](x + y)
+
+            y = self.encdec_attn_layers[i](x, h, encdec_attn_mask)
+            y = self.drop(y)
+            x = self.norm_layers_1[i](x + y)
+
+            y = self.ffn_layers[i](x, x_mask)
+            y = self.drop(y)
+            x = self.norm_layers_2[i](x + y)
+        x = x * x_mask
+        return x
+
+
+class MultiHeadAttention(nn.Module):
+    def __init__(
+        self,
+        channels,
+        out_channels,
+        n_heads,
+        p_dropout=0.0,
+        window_size=None,
+        heads_share=True,
+        block_length=None,
+        proximal_bias=False,
+        proximal_init=False,
+    ):
+        super().__init__()
+        assert channels % n_heads == 0
+
+        self.channels = channels
+        self.out_channels = out_channels
+        self.n_heads = n_heads
+        self.p_dropout = p_dropout
+        self.window_size = window_size
+        self.heads_share = heads_share
+        self.block_length = block_length
+        self.proximal_bias = proximal_bias
+        self.proximal_init = proximal_init
+        self.attn = None
+
+        self.k_channels = channels // n_heads
+        self.conv_q = nn.Conv1d(channels, channels, 1)
+        self.conv_k = nn.Conv1d(channels, channels, 1)
+        self.conv_v = nn.Conv1d(channels, channels, 1)
+        self.conv_o = nn.Conv1d(channels, out_channels, 1)
+        self.drop = nn.Dropout(p_dropout)
+
+        if window_size is not None:
+            n_heads_rel = 1 if heads_share else n_heads
+            rel_stddev = self.k_channels**-0.5
+            self.emb_rel_k = nn.Parameter(
+                torch.randn(n_heads_rel, window_size * 2 + 1, self.k_channels)
+                * rel_stddev
+            )
+            self.emb_rel_v = nn.Parameter(
+                torch.randn(n_heads_rel, window_size * 2 + 1, self.k_channels)
+                * rel_stddev
+            )
+
+        nn.init.xavier_uniform_(self.conv_q.weight)
+        nn.init.xavier_uniform_(self.conv_k.weight)
+        nn.init.xavier_uniform_(self.conv_v.weight)
+        if proximal_init:
+            with torch.no_grad():
+                self.conv_k.weight.copy_(self.conv_q.weight)
+                self.conv_k.bias.copy_(self.conv_q.bias)
+
+    def forward(self, x, c, attn_mask=None):
+        q = self.conv_q(x)
+        k = self.conv_k(c)
+        v = self.conv_v(c)
+
+        x, self.attn = self.attention(q, k, v, mask=attn_mask)
+
+        x = self.conv_o(x)
+        return x
+
+    def attention(self, query, key, value, mask=None):
+        # reshape [b, d, t] -> [b, n_h, t, d_k]
+        b, d, t_s, t_t = (*key.size(), query.size(2))
+        query = query.view(b, self.n_heads, self.k_channels, t_t).transpose(2, 3)
+        key = key.view(b, self.n_heads, self.k_channels, t_s).transpose(2, 3)
+        value = value.view(b, self.n_heads, self.k_channels, t_s).transpose(2, 3)
+
+        scores = torch.matmul(query / math.sqrt(self.k_channels), key.transpose(-2, -1))
+        if self.window_size is not None:
+            assert (
+                t_s == t_t
+            ), "Relative attention is only available for self-attention."
+            key_relative_embeddings = self._get_relative_embeddings(self.emb_rel_k, t_s)
+            rel_logits = self._matmul_with_relative_keys(
+                query / math.sqrt(self.k_channels), key_relative_embeddings
+            )
+            scores_local = self._relative_position_to_absolute_position(rel_logits)
+            scores = scores + scores_local
+        if self.proximal_bias:
+            assert t_s == t_t, "Proximal bias is only available for self-attention."
+            scores = scores + self._attention_bias_proximal(t_s).to(
+                device=scores.device, dtype=scores.dtype
+            )
+        if mask is not None:
+            scores = scores.masked_fill(mask == 0, -1e4)
+            if self.block_length is not None:
+                assert (
+                    t_s == t_t
+                ), "Local attention is only available for self-attention."
+                block_mask = (
+                    torch.ones_like(scores)
+                    .triu(-self.block_length)
+                    .tril(self.block_length)
+                )
+                scores = scores.masked_fill(block_mask == 0, -1e4)
+        p_attn = F.softmax(scores, dim=-1)  # [b, n_h, t_t, t_s]
+        p_attn = self.drop(p_attn)
+        output = torch.matmul(p_attn, value)
+        if self.window_size is not None:
+            relative_weights = self._absolute_position_to_relative_position(p_attn)
+            value_relative_embeddings = self._get_relative_embeddings(
+                self.emb_rel_v, t_s
+            )
+            output = output + self._matmul_with_relative_values(
+                relative_weights, value_relative_embeddings
+            )
+        output = (
+            output.transpose(2, 3).contiguous().view(b, d, t_t)
+        )  # [b, n_h, t_t, d_k] -> [b, d, t_t]
+        return output, p_attn
+
+    def _matmul_with_relative_values(self, x, y):
+        """
+        x: [b, h, l, m]
+        y: [h or 1, m, d]
+        ret: [b, h, l, d]
+        """
+        ret = torch.matmul(x, y.unsqueeze(0))
+        return ret
+
+    def _matmul_with_relative_keys(self, x, y):
+        """
+        x: [b, h, l, d]
+        y: [h or 1, m, d]
+        ret: [b, h, l, m]
+        """
+        ret = torch.matmul(x, y.unsqueeze(0).transpose(-2, -1))
+        return ret
+
+    def _get_relative_embeddings(self, relative_embeddings, length):
+        max_relative_position = 2 * self.window_size + 1
+        # Pad first before slice to avoid using cond ops.
+        pad_length = max(length - (self.window_size + 1), 0)
+        slice_start_position = max((self.window_size + 1) - length, 0)
+        slice_end_position = slice_start_position + 2 * length - 1
+        if pad_length > 0:
+            padded_relative_embeddings = F.pad(
+                relative_embeddings,
+                commons.convert_pad_shape([[0, 0], [pad_length, pad_length], [0, 0]]),
+            )
+        else:
+            padded_relative_embeddings = relative_embeddings
+        used_relative_embeddings = padded_relative_embeddings[
+            :, slice_start_position:slice_end_position
+        ]
+        return used_relative_embeddings
+
+    def _relative_position_to_absolute_position(self, x):
+        """
+        x: [b, h, l, 2*l-1]
+        ret: [b, h, l, l]
+        """
+        batch, heads, length, _ = x.size()
+        # Concat columns of pad to shift from relative to absolute indexing.
+        x = F.pad(x, commons.convert_pad_shape([[0, 0], [0, 0], [0, 0], [0, 1]]))
+
+        # Concat extra elements so to add up to shape (len+1, 2*len-1).
+        x_flat = x.view([batch, heads, length * 2 * length])
+        x_flat = F.pad(
+            x_flat, commons.convert_pad_shape([[0, 0], [0, 0], [0, length - 1]])
+        )
+
+        # Reshape and slice out the padded elements.
+        x_final = x_flat.view([batch, heads, length + 1, 2 * length - 1])[
+            :, :, :length, length - 1 :
+        ]
+        return x_final
+
+    def _absolute_position_to_relative_position(self, x):
+        """
+        x: [b, h, l, l]
+        ret: [b, h, l, 2*l-1]
+        """
+        batch, heads, length, _ = x.size()
+        # padd along column
+        x = F.pad(
+            x, commons.convert_pad_shape([[0, 0], [0, 0], [0, 0], [0, length - 1]])
+        )
+        x_flat = x.view([batch, heads, length**2 + length * (length - 1)])
+        # add 0's in the beginning that will skew the elements after reshape
+        x_flat = F.pad(x_flat, commons.convert_pad_shape([[0, 0], [0, 0], [length, 0]]))
+        x_final = x_flat.view([batch, heads, length, 2 * length])[:, :, :, 1:]
+        return x_final
+
+    def _attention_bias_proximal(self, length):
+        """Bias for self-attention to encourage attention to close positions.
+        Args:
+          length: an integer scalar.
+        Returns:
+          a Tensor with shape [1, 1, length, length]
+        """
+        r = torch.arange(length, dtype=torch.float32)
+        diff = torch.unsqueeze(r, 0) - torch.unsqueeze(r, 1)
+        return torch.unsqueeze(torch.unsqueeze(-torch.log1p(torch.abs(diff)), 0), 0)
+
+
+class FFN(nn.Module):
+    def __init__(
+        self,
+        in_channels,
+        out_channels,
+        filter_channels,
+        kernel_size,
+        p_dropout=0.0,
+        activation=None,
+        causal=False,
+    ):
+        super().__init__()
+        self.in_channels = in_channels
+        self.out_channels = out_channels
+        self.filter_channels = filter_channels
+        self.kernel_size = kernel_size
+        self.p_dropout = p_dropout
+        self.activation = activation
+        self.causal = causal
+
+        if causal:
+            self.padding = self._causal_padding
+        else:
+            self.padding = self._same_padding
+
+        self.conv_1 = nn.Conv1d(in_channels, filter_channels, kernel_size)
+        self.conv_2 = nn.Conv1d(filter_channels, out_channels, kernel_size)
+        self.drop = nn.Dropout(p_dropout)
+
+    def forward(self, x, x_mask):
+        x = self.conv_1(self.padding(x * x_mask))
+        if self.activation == "gelu":
+            x = x * torch.sigmoid(1.702 * x)
+        else:
+            x = torch.relu(x)
+        x = self.drop(x)
+        x = self.conv_2(self.padding(x * x_mask))
+        return x * x_mask
+
+    def _causal_padding(self, x):
+        if self.kernel_size == 1:
+            return x
+        pad_l = self.kernel_size - 1
+        pad_r = 0
+        padding = [[0, 0], [0, 0], [pad_l, pad_r]]
+        x = F.pad(x, commons.convert_pad_shape(padding))
+        return x
+
+    def _same_padding(self, x):
+        if self.kernel_size == 1:
+            return x
+        pad_l = (self.kernel_size - 1) // 2
+        pad_r = self.kernel_size // 2
+        padding = [[0, 0], [0, 0], [pad_l, pad_r]]
+        x = F.pad(x, commons.convert_pad_shape(padding))
+        return x
diff --git a/lib/infer_pack/commons.py b/lib/infer_pack/commons.py
new file mode 100644
index 0000000000000000000000000000000000000000..54470986f37825b35d90d7efa7437d1c26b87215
--- /dev/null
+++ b/lib/infer_pack/commons.py
@@ -0,0 +1,166 @@
+import math
+import numpy as np
+import torch
+from torch import nn
+from torch.nn import functional as F
+
+
+def init_weights(m, mean=0.0, std=0.01):
+    classname = m.__class__.__name__
+    if classname.find("Conv") != -1:
+        m.weight.data.normal_(mean, std)
+
+
+def get_padding(kernel_size, dilation=1):
+    return int((kernel_size * dilation - dilation) / 2)
+
+
+def convert_pad_shape(pad_shape):
+    l = pad_shape[::-1]
+    pad_shape = [item for sublist in l for item in sublist]
+    return pad_shape
+
+
+def kl_divergence(m_p, logs_p, m_q, logs_q):
+    """KL(P||Q)"""
+    kl = (logs_q - logs_p) - 0.5
+    kl += (
+        0.5 * (torch.exp(2.0 * logs_p) + ((m_p - m_q) ** 2)) * torch.exp(-2.0 * logs_q)
+    )
+    return kl
+
+
+def rand_gumbel(shape):
+    """Sample from the Gumbel distribution, protect from overflows."""
+    uniform_samples = torch.rand(shape) * 0.99998 + 0.00001
+    return -torch.log(-torch.log(uniform_samples))
+
+
+def rand_gumbel_like(x):
+    g = rand_gumbel(x.size()).to(dtype=x.dtype, device=x.device)
+    return g
+
+
+def slice_segments(x, ids_str, segment_size=4):
+    ret = torch.zeros_like(x[:, :, :segment_size])
+    for i in range(x.size(0)):
+        idx_str = ids_str[i]
+        idx_end = idx_str + segment_size
+        ret[i] = x[i, :, idx_str:idx_end]
+    return ret
+
+
+def slice_segments2(x, ids_str, segment_size=4):
+    ret = torch.zeros_like(x[:, :segment_size])
+    for i in range(x.size(0)):
+        idx_str = ids_str[i]
+        idx_end = idx_str + segment_size
+        ret[i] = x[i, idx_str:idx_end]
+    return ret
+
+
+def rand_slice_segments(x, x_lengths=None, segment_size=4):
+    b, d, t = x.size()
+    if x_lengths is None:
+        x_lengths = t
+    ids_str_max = x_lengths - segment_size + 1
+    ids_str = (torch.rand([b]).to(device=x.device) * ids_str_max).to(dtype=torch.long)
+    ret = slice_segments(x, ids_str, segment_size)
+    return ret, ids_str
+
+
+def get_timing_signal_1d(length, channels, min_timescale=1.0, max_timescale=1.0e4):
+    position = torch.arange(length, dtype=torch.float)
+    num_timescales = channels // 2
+    log_timescale_increment = math.log(float(max_timescale) / float(min_timescale)) / (
+        num_timescales - 1
+    )
+    inv_timescales = min_timescale * torch.exp(
+        torch.arange(num_timescales, dtype=torch.float) * -log_timescale_increment
+    )
+    scaled_time = position.unsqueeze(0) * inv_timescales.unsqueeze(1)
+    signal = torch.cat([torch.sin(scaled_time), torch.cos(scaled_time)], 0)
+    signal = F.pad(signal, [0, 0, 0, channels % 2])
+    signal = signal.view(1, channels, length)
+    return signal
+
+
+def add_timing_signal_1d(x, min_timescale=1.0, max_timescale=1.0e4):
+    b, channels, length = x.size()
+    signal = get_timing_signal_1d(length, channels, min_timescale, max_timescale)
+    return x + signal.to(dtype=x.dtype, device=x.device)
+
+
+def cat_timing_signal_1d(x, min_timescale=1.0, max_timescale=1.0e4, axis=1):
+    b, channels, length = x.size()
+    signal = get_timing_signal_1d(length, channels, min_timescale, max_timescale)
+    return torch.cat([x, signal.to(dtype=x.dtype, device=x.device)], axis)
+
+
+def subsequent_mask(length):
+    mask = torch.tril(torch.ones(length, length)).unsqueeze(0).unsqueeze(0)
+    return mask
+
+
+@torch.jit.script
+def fused_add_tanh_sigmoid_multiply(input_a, input_b, n_channels):
+    n_channels_int = n_channels[0]
+    in_act = input_a + input_b
+    t_act = torch.tanh(in_act[:, :n_channels_int, :])
+    s_act = torch.sigmoid(in_act[:, n_channels_int:, :])
+    acts = t_act * s_act
+    return acts
+
+
+def convert_pad_shape(pad_shape):
+    l = pad_shape[::-1]
+    pad_shape = [item for sublist in l for item in sublist]
+    return pad_shape
+
+
+def shift_1d(x):
+    x = F.pad(x, convert_pad_shape([[0, 0], [0, 0], [1, 0]]))[:, :, :-1]
+    return x
+
+
+def sequence_mask(length, max_length=None):
+    if max_length is None:
+        max_length = length.max()
+    x = torch.arange(max_length, dtype=length.dtype, device=length.device)
+    return x.unsqueeze(0) < length.unsqueeze(1)
+
+
+def generate_path(duration, mask):
+    """
+    duration: [b, 1, t_x]
+    mask: [b, 1, t_y, t_x]
+    """
+    device = duration.device
+
+    b, _, t_y, t_x = mask.shape
+    cum_duration = torch.cumsum(duration, -1)
+
+    cum_duration_flat = cum_duration.view(b * t_x)
+    path = sequence_mask(cum_duration_flat, t_y).to(mask.dtype)
+    path = path.view(b, t_x, t_y)
+    path = path - F.pad(path, convert_pad_shape([[0, 0], [1, 0], [0, 0]]))[:, :-1]
+    path = path.unsqueeze(1).transpose(2, 3) * mask
+    return path
+
+
+def clip_grad_value_(parameters, clip_value, norm_type=2):
+    if isinstance(parameters, torch.Tensor):
+        parameters = [parameters]
+    parameters = list(filter(lambda p: p.grad is not None, parameters))
+    norm_type = float(norm_type)
+    if clip_value is not None:
+        clip_value = float(clip_value)
+
+    total_norm = 0
+    for p in parameters:
+        param_norm = p.grad.data.norm(norm_type)
+        total_norm += param_norm.item() ** norm_type
+        if clip_value is not None:
+            p.grad.data.clamp_(min=-clip_value, max=clip_value)
+    total_norm = total_norm ** (1.0 / norm_type)
+    return total_norm
diff --git a/lib/infer_pack/models.py b/lib/infer_pack/models.py
new file mode 100644
index 0000000000000000000000000000000000000000..ec107476df968e51aafc6c3d102a9ed8c53f141a
--- /dev/null
+++ b/lib/infer_pack/models.py
@@ -0,0 +1,1144 @@
+import math, pdb, os
+from time import time as ttime
+import torch
+from torch import nn
+from torch.nn import functional as F
+from lib.infer_pack import modules
+from lib.infer_pack import attentions
+from lib.infer_pack import commons
+from lib.infer_pack.commons import init_weights, get_padding
+from torch.nn import Conv1d, ConvTranspose1d, AvgPool1d, Conv2d
+from torch.nn.utils import weight_norm, remove_weight_norm, spectral_norm
+from lib.infer_pack.commons import init_weights
+import numpy as np
+from lib.infer_pack import commons
+
+
+class TextEncoder256(nn.Module):
+    def __init__(
+        self,
+        out_channels,
+        hidden_channels,
+        filter_channels,
+        n_heads,
+        n_layers,
+        kernel_size,
+        p_dropout,
+        f0=True,
+    ):
+        super().__init__()
+        self.out_channels = out_channels
+        self.hidden_channels = hidden_channels
+        self.filter_channels = filter_channels
+        self.n_heads = n_heads
+        self.n_layers = n_layers
+        self.kernel_size = kernel_size
+        self.p_dropout = p_dropout
+        self.emb_phone = nn.Linear(256, hidden_channels)
+        self.lrelu = nn.LeakyReLU(0.1, inplace=True)
+        if f0 == True:
+            self.emb_pitch = nn.Embedding(256, hidden_channels)  # pitch 256
+        self.encoder = attentions.Encoder(
+            hidden_channels, filter_channels, n_heads, n_layers, kernel_size, p_dropout
+        )
+        self.proj = nn.Conv1d(hidden_channels, out_channels * 2, 1)
+
+    def forward(self, phone, pitch, lengths):
+        if pitch == None:
+            x = self.emb_phone(phone)
+        else:
+            x = self.emb_phone(phone) + self.emb_pitch(pitch)
+        x = x * math.sqrt(self.hidden_channels)  # [b, t, h]
+        x = self.lrelu(x)
+        x = torch.transpose(x, 1, -1)  # [b, h, t]
+        x_mask = torch.unsqueeze(commons.sequence_mask(lengths, x.size(2)), 1).to(
+            x.dtype
+        )
+        x = self.encoder(x * x_mask, x_mask)
+        stats = self.proj(x) * x_mask
+
+        m, logs = torch.split(stats, self.out_channels, dim=1)
+        return m, logs, x_mask
+
+
+class TextEncoder768(nn.Module):
+    def __init__(
+        self,
+        out_channels,
+        hidden_channels,
+        filter_channels,
+        n_heads,
+        n_layers,
+        kernel_size,
+        p_dropout,
+        f0=True,
+    ):
+        super().__init__()
+        self.out_channels = out_channels
+        self.hidden_channels = hidden_channels
+        self.filter_channels = filter_channels
+        self.n_heads = n_heads
+        self.n_layers = n_layers
+        self.kernel_size = kernel_size
+        self.p_dropout = p_dropout
+        self.emb_phone = nn.Linear(768, hidden_channels)
+        self.lrelu = nn.LeakyReLU(0.1, inplace=True)
+        if f0 == True:
+            self.emb_pitch = nn.Embedding(256, hidden_channels)  # pitch 256
+        self.encoder = attentions.Encoder(
+            hidden_channels, filter_channels, n_heads, n_layers, kernel_size, p_dropout
+        )
+        self.proj = nn.Conv1d(hidden_channels, out_channels * 2, 1)
+
+    def forward(self, phone, pitch, lengths):
+        if pitch == None:
+            x = self.emb_phone(phone)
+        else:
+            x = self.emb_phone(phone) + self.emb_pitch(pitch)
+        x = x * math.sqrt(self.hidden_channels)  # [b, t, h]
+        x = self.lrelu(x)
+        x = torch.transpose(x, 1, -1)  # [b, h, t]
+        x_mask = torch.unsqueeze(commons.sequence_mask(lengths, x.size(2)), 1).to(
+            x.dtype
+        )
+        x = self.encoder(x * x_mask, x_mask)
+        stats = self.proj(x) * x_mask
+
+        m, logs = torch.split(stats, self.out_channels, dim=1)
+        return m, logs, x_mask
+
+
+class ResidualCouplingBlock(nn.Module):
+    def __init__(
+        self,
+        channels,
+        hidden_channels,
+        kernel_size,
+        dilation_rate,
+        n_layers,
+        n_flows=4,
+        gin_channels=0,
+    ):
+        super().__init__()
+        self.channels = channels
+        self.hidden_channels = hidden_channels
+        self.kernel_size = kernel_size
+        self.dilation_rate = dilation_rate
+        self.n_layers = n_layers
+        self.n_flows = n_flows
+        self.gin_channels = gin_channels
+
+        self.flows = nn.ModuleList()
+        for i in range(n_flows):
+            self.flows.append(
+                modules.ResidualCouplingLayer(
+                    channels,
+                    hidden_channels,
+                    kernel_size,
+                    dilation_rate,
+                    n_layers,
+                    gin_channels=gin_channels,
+                    mean_only=True,
+                )
+            )
+            self.flows.append(modules.Flip())
+
+    def forward(self, x, x_mask, g=None, reverse=False):
+        if not reverse:
+            for flow in self.flows:
+                x, _ = flow(x, x_mask, g=g, reverse=reverse)
+        else:
+            for flow in reversed(self.flows):
+                x = flow(x, x_mask, g=g, reverse=reverse)
+        return x
+
+    def remove_weight_norm(self):
+        for i in range(self.n_flows):
+            self.flows[i * 2].remove_weight_norm()
+
+
+class PosteriorEncoder(nn.Module):
+    def __init__(
+        self,
+        in_channels,
+        out_channels,
+        hidden_channels,
+        kernel_size,
+        dilation_rate,
+        n_layers,
+        gin_channels=0,
+    ):
+        super().__init__()
+        self.in_channels = in_channels
+        self.out_channels = out_channels
+        self.hidden_channels = hidden_channels
+        self.kernel_size = kernel_size
+        self.dilation_rate = dilation_rate
+        self.n_layers = n_layers
+        self.gin_channels = gin_channels
+
+        self.pre = nn.Conv1d(in_channels, hidden_channels, 1)
+        self.enc = modules.WN(
+            hidden_channels,
+            kernel_size,
+            dilation_rate,
+            n_layers,
+            gin_channels=gin_channels,
+        )
+        self.proj = nn.Conv1d(hidden_channels, out_channels * 2, 1)
+
+    def forward(self, x, x_lengths, g=None):
+        x_mask = torch.unsqueeze(commons.sequence_mask(x_lengths, x.size(2)), 1).to(
+            x.dtype
+        )
+        x = self.pre(x) * x_mask
+        x = self.enc(x, x_mask, g=g)
+        stats = self.proj(x) * x_mask
+        m, logs = torch.split(stats, self.out_channels, dim=1)
+        z = (m + torch.randn_like(m) * torch.exp(logs)) * x_mask
+        return z, m, logs, x_mask
+
+    def remove_weight_norm(self):
+        self.enc.remove_weight_norm()
+
+
+class Generator(torch.nn.Module):
+    def __init__(
+        self,
+        initial_channel,
+        resblock,
+        resblock_kernel_sizes,
+        resblock_dilation_sizes,
+        upsample_rates,
+        upsample_initial_channel,
+        upsample_kernel_sizes,
+        gin_channels=0,
+    ):
+        super(Generator, self).__init__()
+        self.num_kernels = len(resblock_kernel_sizes)
+        self.num_upsamples = len(upsample_rates)
+        self.conv_pre = Conv1d(
+            initial_channel, upsample_initial_channel, 7, 1, padding=3
+        )
+        resblock = modules.ResBlock1 if resblock == "1" else modules.ResBlock2
+
+        self.ups = nn.ModuleList()
+        for i, (u, k) in enumerate(zip(upsample_rates, upsample_kernel_sizes)):
+            self.ups.append(
+                weight_norm(
+                    ConvTranspose1d(
+                        upsample_initial_channel // (2**i),
+                        upsample_initial_channel // (2 ** (i + 1)),
+                        k,
+                        u,
+                        padding=(k - u) // 2,
+                    )
+                )
+            )
+
+        self.resblocks = nn.ModuleList()
+        for i in range(len(self.ups)):
+            ch = upsample_initial_channel // (2 ** (i + 1))
+            for j, (k, d) in enumerate(
+                zip(resblock_kernel_sizes, resblock_dilation_sizes)
+            ):
+                self.resblocks.append(resblock(ch, k, d))
+
+        self.conv_post = Conv1d(ch, 1, 7, 1, padding=3, bias=False)
+        self.ups.apply(init_weights)
+
+        if gin_channels != 0:
+            self.cond = nn.Conv1d(gin_channels, upsample_initial_channel, 1)
+
+    def forward(self, x, g=None):
+        x = self.conv_pre(x)
+        if g is not None:
+            x = x + self.cond(g)
+
+        for i in range(self.num_upsamples):
+            x = F.leaky_relu(x, modules.LRELU_SLOPE)
+            x = self.ups[i](x)
+            xs = None
+            for j in range(self.num_kernels):
+                if xs is None:
+                    xs = self.resblocks[i * self.num_kernels + j](x)
+                else:
+                    xs += self.resblocks[i * self.num_kernels + j](x)
+            x = xs / self.num_kernels
+        x = F.leaky_relu(x)
+        x = self.conv_post(x)
+        x = torch.tanh(x)
+
+        return x
+
+    def remove_weight_norm(self):
+        for l in self.ups:
+            remove_weight_norm(l)
+        for l in self.resblocks:
+            l.remove_weight_norm()
+
+
+class SineGen(torch.nn.Module):
+    """Definition of sine generator
+    SineGen(samp_rate, harmonic_num = 0,
+            sine_amp = 0.1, noise_std = 0.003,
+            voiced_threshold = 0,
+            flag_for_pulse=False)
+    samp_rate: sampling rate in Hz
+    harmonic_num: number of harmonic overtones (default 0)
+    sine_amp: amplitude of sine-wavefrom (default 0.1)
+    noise_std: std of Gaussian noise (default 0.003)
+    voiced_thoreshold: F0 threshold for U/V classification (default 0)
+    flag_for_pulse: this SinGen is used inside PulseGen (default False)
+    Note: when flag_for_pulse is True, the first time step of a voiced
+        segment is always sin(np.pi) or cos(0)
+    """
+
+    def __init__(
+        self,
+        samp_rate,
+        harmonic_num=0,
+        sine_amp=0.1,
+        noise_std=0.003,
+        voiced_threshold=0,
+        flag_for_pulse=False,
+    ):
+        super(SineGen, self).__init__()
+        self.sine_amp = sine_amp
+        self.noise_std = noise_std
+        self.harmonic_num = harmonic_num
+        self.dim = self.harmonic_num + 1
+        self.sampling_rate = samp_rate
+        self.voiced_threshold = voiced_threshold
+
+    def _f02uv(self, f0):
+        # generate uv signal
+        uv = torch.ones_like(f0)
+        uv = uv * (f0 > self.voiced_threshold)
+        if uv.device.type == "privateuseone":  # for DirectML
+            uv = uv.float()
+        return uv
+
+    def forward(self, f0, upp):
+        """sine_tensor, uv = forward(f0)
+        input F0: tensor(batchsize=1, length, dim=1)
+                  f0 for unvoiced steps should be 0
+        output sine_tensor: tensor(batchsize=1, length, dim)
+        output uv: tensor(batchsize=1, length, 1)
+        """
+        with torch.no_grad():
+            f0 = f0[:, None].transpose(1, 2)
+            f0_buf = torch.zeros(f0.shape[0], f0.shape[1], self.dim, device=f0.device)
+            # fundamental component
+            f0_buf[:, :, 0] = f0[:, :, 0]
+            for idx in np.arange(self.harmonic_num):
+                f0_buf[:, :, idx + 1] = f0_buf[:, :, 0] * (
+                    idx + 2
+                )  # idx + 2: the (idx+1)-th overtone, (idx+2)-th harmonic
+            rad_values = (f0_buf / self.sampling_rate) % 1  ###%1意味着n_har的乘积无法后处理优化
+            rand_ini = torch.rand(
+                f0_buf.shape[0], f0_buf.shape[2], device=f0_buf.device
+            )
+            rand_ini[:, 0] = 0
+            rad_values[:, 0, :] = rad_values[:, 0, :] + rand_ini
+            tmp_over_one = torch.cumsum(rad_values, 1)  # % 1  #####%1意味着后面的cumsum无法再优化
+            tmp_over_one *= upp
+            tmp_over_one = F.interpolate(
+                tmp_over_one.transpose(2, 1),
+                scale_factor=upp,
+                mode="linear",
+                align_corners=True,
+            ).transpose(2, 1)
+            rad_values = F.interpolate(
+                rad_values.transpose(2, 1), scale_factor=upp, mode="nearest"
+            ).transpose(
+                2, 1
+            )  #######
+            tmp_over_one %= 1
+            tmp_over_one_idx = (tmp_over_one[:, 1:, :] - tmp_over_one[:, :-1, :]) < 0
+            cumsum_shift = torch.zeros_like(rad_values)
+            cumsum_shift[:, 1:, :] = tmp_over_one_idx * -1.0
+            sine_waves = torch.sin(
+                torch.cumsum(rad_values + cumsum_shift, dim=1) * 2 * np.pi
+            )
+            sine_waves = sine_waves * self.sine_amp
+            uv = self._f02uv(f0)
+            uv = F.interpolate(
+                uv.transpose(2, 1), scale_factor=upp, mode="nearest"
+            ).transpose(2, 1)
+            noise_amp = uv * self.noise_std + (1 - uv) * self.sine_amp / 3
+            noise = noise_amp * torch.randn_like(sine_waves)
+            sine_waves = sine_waves * uv + noise
+        return sine_waves, uv, noise
+
+
+class SourceModuleHnNSF(torch.nn.Module):
+    """SourceModule for hn-nsf
+    SourceModule(sampling_rate, harmonic_num=0, sine_amp=0.1,
+                 add_noise_std=0.003, voiced_threshod=0)
+    sampling_rate: sampling_rate in Hz
+    harmonic_num: number of harmonic above F0 (default: 0)
+    sine_amp: amplitude of sine source signal (default: 0.1)
+    add_noise_std: std of additive Gaussian noise (default: 0.003)
+        note that amplitude of noise in unvoiced is decided
+        by sine_amp
+    voiced_threshold: threhold to set U/V given F0 (default: 0)
+    Sine_source, noise_source = SourceModuleHnNSF(F0_sampled)
+    F0_sampled (batchsize, length, 1)
+    Sine_source (batchsize, length, 1)
+    noise_source (batchsize, length 1)
+    uv (batchsize, length, 1)
+    """
+
+    def __init__(
+        self,
+        sampling_rate,
+        harmonic_num=0,
+        sine_amp=0.1,
+        add_noise_std=0.003,
+        voiced_threshod=0,
+        is_half=True,
+    ):
+        super(SourceModuleHnNSF, self).__init__()
+
+        self.sine_amp = sine_amp
+        self.noise_std = add_noise_std
+        self.is_half = is_half
+        # to produce sine waveforms
+        self.l_sin_gen = SineGen(
+            sampling_rate, harmonic_num, sine_amp, add_noise_std, voiced_threshod
+        )
+
+        # to merge source harmonics into a single excitation
+        self.l_linear = torch.nn.Linear(harmonic_num + 1, 1)
+        self.l_tanh = torch.nn.Tanh()
+
+    def forward(self, x, upp=None):
+        sine_wavs, uv, _ = self.l_sin_gen(x, upp)
+        if self.is_half:
+            sine_wavs = sine_wavs.half()
+        sine_merge = self.l_tanh(self.l_linear(sine_wavs))
+        return sine_merge, None, None  # noise, uv
+
+
+class GeneratorNSF(torch.nn.Module):
+    def __init__(
+        self,
+        initial_channel,
+        resblock,
+        resblock_kernel_sizes,
+        resblock_dilation_sizes,
+        upsample_rates,
+        upsample_initial_channel,
+        upsample_kernel_sizes,
+        gin_channels,
+        sr,
+        is_half=False,
+    ):
+        super(GeneratorNSF, self).__init__()
+        self.num_kernels = len(resblock_kernel_sizes)
+        self.num_upsamples = len(upsample_rates)
+
+        self.f0_upsamp = torch.nn.Upsample(scale_factor=np.prod(upsample_rates))
+        self.m_source = SourceModuleHnNSF(
+            sampling_rate=sr, harmonic_num=0, is_half=is_half
+        )
+        self.noise_convs = nn.ModuleList()
+        self.conv_pre = Conv1d(
+            initial_channel, upsample_initial_channel, 7, 1, padding=3
+        )
+        resblock = modules.ResBlock1 if resblock == "1" else modules.ResBlock2
+
+        self.ups = nn.ModuleList()
+        for i, (u, k) in enumerate(zip(upsample_rates, upsample_kernel_sizes)):
+            c_cur = upsample_initial_channel // (2 ** (i + 1))
+            self.ups.append(
+                weight_norm(
+                    ConvTranspose1d(
+                        upsample_initial_channel // (2**i),
+                        upsample_initial_channel // (2 ** (i + 1)),
+                        k,
+                        u,
+                        padding=(k - u) // 2,
+                    )
+                )
+            )
+            if i + 1 < len(upsample_rates):
+                stride_f0 = np.prod(upsample_rates[i + 1 :])
+                self.noise_convs.append(
+                    Conv1d(
+                        1,
+                        c_cur,
+                        kernel_size=stride_f0 * 2,
+                        stride=stride_f0,
+                        padding=stride_f0 // 2,
+                    )
+                )
+            else:
+                self.noise_convs.append(Conv1d(1, c_cur, kernel_size=1))
+
+        self.resblocks = nn.ModuleList()
+        for i in range(len(self.ups)):
+            ch = upsample_initial_channel // (2 ** (i + 1))
+            for j, (k, d) in enumerate(
+                zip(resblock_kernel_sizes, resblock_dilation_sizes)
+            ):
+                self.resblocks.append(resblock(ch, k, d))
+
+        self.conv_post = Conv1d(ch, 1, 7, 1, padding=3, bias=False)
+        self.ups.apply(init_weights)
+
+        if gin_channels != 0:
+            self.cond = nn.Conv1d(gin_channels, upsample_initial_channel, 1)
+
+        self.upp = np.prod(upsample_rates)
+
+    def forward(self, x, f0, g=None):
+        har_source, noi_source, uv = self.m_source(f0, self.upp)
+        har_source = har_source.transpose(1, 2)
+        x = self.conv_pre(x)
+        if g is not None:
+            x = x + self.cond(g)
+
+        for i in range(self.num_upsamples):
+            x = F.leaky_relu(x, modules.LRELU_SLOPE)
+            x = self.ups[i](x)
+            x_source = self.noise_convs[i](har_source)
+            x = x + x_source
+            xs = None
+            for j in range(self.num_kernels):
+                if xs is None:
+                    xs = self.resblocks[i * self.num_kernels + j](x)
+                else:
+                    xs += self.resblocks[i * self.num_kernels + j](x)
+            x = xs / self.num_kernels
+        x = F.leaky_relu(x)
+        x = self.conv_post(x)
+        x = torch.tanh(x)
+        return x
+
+    def remove_weight_norm(self):
+        for l in self.ups:
+            remove_weight_norm(l)
+        for l in self.resblocks:
+            l.remove_weight_norm()
+
+
+sr2sr = {
+    "32k": 32000,
+    "40k": 40000,
+    "48k": 48000,
+}
+
+
+class SynthesizerTrnMs256NSFsid(nn.Module):
+    def __init__(
+        self,
+        spec_channels,
+        segment_size,
+        inter_channels,
+        hidden_channels,
+        filter_channels,
+        n_heads,
+        n_layers,
+        kernel_size,
+        p_dropout,
+        resblock,
+        resblock_kernel_sizes,
+        resblock_dilation_sizes,
+        upsample_rates,
+        upsample_initial_channel,
+        upsample_kernel_sizes,
+        spk_embed_dim,
+        gin_channels,
+        sr,
+        **kwargs
+    ):
+        super().__init__()
+        if type(sr) == type("strr"):
+            sr = sr2sr[sr]
+        self.spec_channels = spec_channels
+        self.inter_channels = inter_channels
+        self.hidden_channels = hidden_channels
+        self.filter_channels = filter_channels
+        self.n_heads = n_heads
+        self.n_layers = n_layers
+        self.kernel_size = kernel_size
+        self.p_dropout = p_dropout
+        self.resblock = resblock
+        self.resblock_kernel_sizes = resblock_kernel_sizes
+        self.resblock_dilation_sizes = resblock_dilation_sizes
+        self.upsample_rates = upsample_rates
+        self.upsample_initial_channel = upsample_initial_channel
+        self.upsample_kernel_sizes = upsample_kernel_sizes
+        self.segment_size = segment_size
+        self.gin_channels = gin_channels
+        # self.hop_length = hop_length#
+        self.spk_embed_dim = spk_embed_dim
+        self.enc_p = TextEncoder256(
+            inter_channels,
+            hidden_channels,
+            filter_channels,
+            n_heads,
+            n_layers,
+            kernel_size,
+            p_dropout,
+        )
+        self.dec = GeneratorNSF(
+            inter_channels,
+            resblock,
+            resblock_kernel_sizes,
+            resblock_dilation_sizes,
+            upsample_rates,
+            upsample_initial_channel,
+            upsample_kernel_sizes,
+            gin_channels=gin_channels,
+            sr=sr,
+            is_half=kwargs["is_half"],
+        )
+        self.enc_q = PosteriorEncoder(
+            spec_channels,
+            inter_channels,
+            hidden_channels,
+            5,
+            1,
+            16,
+            gin_channels=gin_channels,
+        )
+        self.flow = ResidualCouplingBlock(
+            inter_channels, hidden_channels, 5, 1, 3, gin_channels=gin_channels
+        )
+        self.emb_g = nn.Embedding(self.spk_embed_dim, gin_channels)
+        print("gin_channels:", gin_channels, "self.spk_embed_dim:", self.spk_embed_dim)
+
+    def remove_weight_norm(self):
+        self.dec.remove_weight_norm()
+        self.flow.remove_weight_norm()
+        self.enc_q.remove_weight_norm()
+
+    def forward(
+        self, phone, phone_lengths, pitch, pitchf, y, y_lengths, ds
+    ):  # 这里ds是id，[bs,1]
+        # print(1,pitch.shape)#[bs,t]
+        g = self.emb_g(ds).unsqueeze(-1)  # [b, 256, 1]##1是t，广播的
+        m_p, logs_p, x_mask = self.enc_p(phone, pitch, phone_lengths)
+        z, m_q, logs_q, y_mask = self.enc_q(y, y_lengths, g=g)
+        z_p = self.flow(z, y_mask, g=g)
+        z_slice, ids_slice = commons.rand_slice_segments(
+            z, y_lengths, self.segment_size
+        )
+        # print(-1,pitchf.shape,ids_slice,self.segment_size,self.hop_length,self.segment_size//self.hop_length)
+        pitchf = commons.slice_segments2(pitchf, ids_slice, self.segment_size)
+        # print(-2,pitchf.shape,z_slice.shape)
+        o = self.dec(z_slice, pitchf, g=g)
+        return o, ids_slice, x_mask, y_mask, (z, z_p, m_p, logs_p, m_q, logs_q)
+
+    def infer(self, phone, phone_lengths, pitch, nsff0, sid, rate=None):
+        g = self.emb_g(sid).unsqueeze(-1)
+        m_p, logs_p, x_mask = self.enc_p(phone, pitch, phone_lengths)
+        z_p = (m_p + torch.exp(logs_p) * torch.randn_like(m_p) * 0.66666) * x_mask
+        if rate:
+            head = int(z_p.shape[2] * rate)
+            z_p = z_p[:, :, -head:]
+            x_mask = x_mask[:, :, -head:]
+            nsff0 = nsff0[:, -head:]
+        z = self.flow(z_p, x_mask, g=g, reverse=True)
+        o = self.dec(z * x_mask, nsff0, g=g)
+        return o, x_mask, (z, z_p, m_p, logs_p)
+
+
+class SynthesizerTrnMs768NSFsid(nn.Module):
+    def __init__(
+        self,
+        spec_channels,
+        segment_size,
+        inter_channels,
+        hidden_channels,
+        filter_channels,
+        n_heads,
+        n_layers,
+        kernel_size,
+        p_dropout,
+        resblock,
+        resblock_kernel_sizes,
+        resblock_dilation_sizes,
+        upsample_rates,
+        upsample_initial_channel,
+        upsample_kernel_sizes,
+        spk_embed_dim,
+        gin_channels,
+        sr,
+        **kwargs
+    ):
+        super().__init__()
+        if type(sr) == type("strr"):
+            sr = sr2sr[sr]
+        self.spec_channels = spec_channels
+        self.inter_channels = inter_channels
+        self.hidden_channels = hidden_channels
+        self.filter_channels = filter_channels
+        self.n_heads = n_heads
+        self.n_layers = n_layers
+        self.kernel_size = kernel_size
+        self.p_dropout = p_dropout
+        self.resblock = resblock
+        self.resblock_kernel_sizes = resblock_kernel_sizes
+        self.resblock_dilation_sizes = resblock_dilation_sizes
+        self.upsample_rates = upsample_rates
+        self.upsample_initial_channel = upsample_initial_channel
+        self.upsample_kernel_sizes = upsample_kernel_sizes
+        self.segment_size = segment_size
+        self.gin_channels = gin_channels
+        # self.hop_length = hop_length#
+        self.spk_embed_dim = spk_embed_dim
+        self.enc_p = TextEncoder768(
+            inter_channels,
+            hidden_channels,
+            filter_channels,
+            n_heads,
+            n_layers,
+            kernel_size,
+            p_dropout,
+        )
+        self.dec = GeneratorNSF(
+            inter_channels,
+            resblock,
+            resblock_kernel_sizes,
+            resblock_dilation_sizes,
+            upsample_rates,
+            upsample_initial_channel,
+            upsample_kernel_sizes,
+            gin_channels=gin_channels,
+            sr=sr,
+            is_half=kwargs["is_half"],
+        )
+        self.enc_q = PosteriorEncoder(
+            spec_channels,
+            inter_channels,
+            hidden_channels,
+            5,
+            1,
+            16,
+            gin_channels=gin_channels,
+        )
+        self.flow = ResidualCouplingBlock(
+            inter_channels, hidden_channels, 5, 1, 3, gin_channels=gin_channels
+        )
+        self.emb_g = nn.Embedding(self.spk_embed_dim, gin_channels)
+        print("gin_channels:", gin_channels, "self.spk_embed_dim:", self.spk_embed_dim)
+
+    def remove_weight_norm(self):
+        self.dec.remove_weight_norm()
+        self.flow.remove_weight_norm()
+        self.enc_q.remove_weight_norm()
+
+    def forward(
+        self, phone, phone_lengths, pitch, pitchf, y, y_lengths, ds
+    ):  # 这里ds是id，[bs,1]
+        # print(1,pitch.shape)#[bs,t]
+        g = self.emb_g(ds).unsqueeze(-1)  # [b, 256, 1]##1是t，广播的
+        m_p, logs_p, x_mask = self.enc_p(phone, pitch, phone_lengths)
+        z, m_q, logs_q, y_mask = self.enc_q(y, y_lengths, g=g)
+        z_p = self.flow(z, y_mask, g=g)
+        z_slice, ids_slice = commons.rand_slice_segments(
+            z, y_lengths, self.segment_size
+        )
+        # print(-1,pitchf.shape,ids_slice,self.segment_size,self.hop_length,self.segment_size//self.hop_length)
+        pitchf = commons.slice_segments2(pitchf, ids_slice, self.segment_size)
+        # print(-2,pitchf.shape,z_slice.shape)
+        o = self.dec(z_slice, pitchf, g=g)
+        return o, ids_slice, x_mask, y_mask, (z, z_p, m_p, logs_p, m_q, logs_q)
+
+    def infer(self, phone, phone_lengths, pitch, nsff0, sid, rate=None):
+        g = self.emb_g(sid).unsqueeze(-1)
+        m_p, logs_p, x_mask = self.enc_p(phone, pitch, phone_lengths)
+        z_p = (m_p + torch.exp(logs_p) * torch.randn_like(m_p) * 0.66666) * x_mask
+        if rate:
+            head = int(z_p.shape[2] * rate)
+            z_p = z_p[:, :, -head:]
+            x_mask = x_mask[:, :, -head:]
+            nsff0 = nsff0[:, -head:]
+        z = self.flow(z_p, x_mask, g=g, reverse=True)
+        o = self.dec(z * x_mask, nsff0, g=g)
+        return o, x_mask, (z, z_p, m_p, logs_p)
+
+
+class SynthesizerTrnMs256NSFsid_nono(nn.Module):
+    def __init__(
+        self,
+        spec_channels,
+        segment_size,
+        inter_channels,
+        hidden_channels,
+        filter_channels,
+        n_heads,
+        n_layers,
+        kernel_size,
+        p_dropout,
+        resblock,
+        resblock_kernel_sizes,
+        resblock_dilation_sizes,
+        upsample_rates,
+        upsample_initial_channel,
+        upsample_kernel_sizes,
+        spk_embed_dim,
+        gin_channels,
+        sr=None,
+        **kwargs
+    ):
+        super().__init__()
+        self.spec_channels = spec_channels
+        self.inter_channels = inter_channels
+        self.hidden_channels = hidden_channels
+        self.filter_channels = filter_channels
+        self.n_heads = n_heads
+        self.n_layers = n_layers
+        self.kernel_size = kernel_size
+        self.p_dropout = p_dropout
+        self.resblock = resblock
+        self.resblock_kernel_sizes = resblock_kernel_sizes
+        self.resblock_dilation_sizes = resblock_dilation_sizes
+        self.upsample_rates = upsample_rates
+        self.upsample_initial_channel = upsample_initial_channel
+        self.upsample_kernel_sizes = upsample_kernel_sizes
+        self.segment_size = segment_size
+        self.gin_channels = gin_channels
+        # self.hop_length = hop_length#
+        self.spk_embed_dim = spk_embed_dim
+        self.enc_p = TextEncoder256(
+            inter_channels,
+            hidden_channels,
+            filter_channels,
+            n_heads,
+            n_layers,
+            kernel_size,
+            p_dropout,
+            f0=False,
+        )
+        self.dec = Generator(
+            inter_channels,
+            resblock,
+            resblock_kernel_sizes,
+            resblock_dilation_sizes,
+            upsample_rates,
+            upsample_initial_channel,
+            upsample_kernel_sizes,
+            gin_channels=gin_channels,
+        )
+        self.enc_q = PosteriorEncoder(
+            spec_channels,
+            inter_channels,
+            hidden_channels,
+            5,
+            1,
+            16,
+            gin_channels=gin_channels,
+        )
+        self.flow = ResidualCouplingBlock(
+            inter_channels, hidden_channels, 5, 1, 3, gin_channels=gin_channels
+        )
+        self.emb_g = nn.Embedding(self.spk_embed_dim, gin_channels)
+        print("gin_channels:", gin_channels, "self.spk_embed_dim:", self.spk_embed_dim)
+
+    def remove_weight_norm(self):
+        self.dec.remove_weight_norm()
+        self.flow.remove_weight_norm()
+        self.enc_q.remove_weight_norm()
+
+    def forward(self, phone, phone_lengths, y, y_lengths, ds):  # 这里ds是id，[bs,1]
+        g = self.emb_g(ds).unsqueeze(-1)  # [b, 256, 1]##1是t，广播的
+        m_p, logs_p, x_mask = self.enc_p(phone, None, phone_lengths)
+        z, m_q, logs_q, y_mask = self.enc_q(y, y_lengths, g=g)
+        z_p = self.flow(z, y_mask, g=g)
+        z_slice, ids_slice = commons.rand_slice_segments(
+            z, y_lengths, self.segment_size
+        )
+        o = self.dec(z_slice, g=g)
+        return o, ids_slice, x_mask, y_mask, (z, z_p, m_p, logs_p, m_q, logs_q)
+
+    def infer(self, phone, phone_lengths, sid, rate=None):
+        g = self.emb_g(sid).unsqueeze(-1)
+        m_p, logs_p, x_mask = self.enc_p(phone, None, phone_lengths)
+        z_p = (m_p + torch.exp(logs_p) * torch.randn_like(m_p) * 0.66666) * x_mask
+        if rate:
+            head = int(z_p.shape[2] * rate)
+            z_p = z_p[:, :, -head:]
+            x_mask = x_mask[:, :, -head:]
+        z = self.flow(z_p, x_mask, g=g, reverse=True)
+        o = self.dec(z * x_mask, g=g)
+        return o, x_mask, (z, z_p, m_p, logs_p)
+
+
+class SynthesizerTrnMs768NSFsid_nono(nn.Module):
+    def __init__(
+        self,
+        spec_channels,
+        segment_size,
+        inter_channels,
+        hidden_channels,
+        filter_channels,
+        n_heads,
+        n_layers,
+        kernel_size,
+        p_dropout,
+        resblock,
+        resblock_kernel_sizes,
+        resblock_dilation_sizes,
+        upsample_rates,
+        upsample_initial_channel,
+        upsample_kernel_sizes,
+        spk_embed_dim,
+        gin_channels,
+        sr=None,
+        **kwargs
+    ):
+        super().__init__()
+        self.spec_channels = spec_channels
+        self.inter_channels = inter_channels
+        self.hidden_channels = hidden_channels
+        self.filter_channels = filter_channels
+        self.n_heads = n_heads
+        self.n_layers = n_layers
+        self.kernel_size = kernel_size
+        self.p_dropout = p_dropout
+        self.resblock = resblock
+        self.resblock_kernel_sizes = resblock_kernel_sizes
+        self.resblock_dilation_sizes = resblock_dilation_sizes
+        self.upsample_rates = upsample_rates
+        self.upsample_initial_channel = upsample_initial_channel
+        self.upsample_kernel_sizes = upsample_kernel_sizes
+        self.segment_size = segment_size
+        self.gin_channels = gin_channels
+        # self.hop_length = hop_length#
+        self.spk_embed_dim = spk_embed_dim
+        self.enc_p = TextEncoder768(
+            inter_channels,
+            hidden_channels,
+            filter_channels,
+            n_heads,
+            n_layers,
+            kernel_size,
+            p_dropout,
+            f0=False,
+        )
+        self.dec = Generator(
+            inter_channels,
+            resblock,
+            resblock_kernel_sizes,
+            resblock_dilation_sizes,
+            upsample_rates,
+            upsample_initial_channel,
+            upsample_kernel_sizes,
+            gin_channels=gin_channels,
+        )
+        self.enc_q = PosteriorEncoder(
+            spec_channels,
+            inter_channels,
+            hidden_channels,
+            5,
+            1,
+            16,
+            gin_channels=gin_channels,
+        )
+        self.flow = ResidualCouplingBlock(
+            inter_channels, hidden_channels, 5, 1, 3, gin_channels=gin_channels
+        )
+        self.emb_g = nn.Embedding(self.spk_embed_dim, gin_channels)
+        print("gin_channels:", gin_channels, "self.spk_embed_dim:", self.spk_embed_dim)
+
+    def remove_weight_norm(self):
+        self.dec.remove_weight_norm()
+        self.flow.remove_weight_norm()
+        self.enc_q.remove_weight_norm()
+
+    def forward(self, phone, phone_lengths, y, y_lengths, ds):  # 这里ds是id，[bs,1]
+        g = self.emb_g(ds).unsqueeze(-1)  # [b, 256, 1]##1是t，广播的
+        m_p, logs_p, x_mask = self.enc_p(phone, None, phone_lengths)
+        z, m_q, logs_q, y_mask = self.enc_q(y, y_lengths, g=g)
+        z_p = self.flow(z, y_mask, g=g)
+        z_slice, ids_slice = commons.rand_slice_segments(
+            z, y_lengths, self.segment_size
+        )
+        o = self.dec(z_slice, g=g)
+        return o, ids_slice, x_mask, y_mask, (z, z_p, m_p, logs_p, m_q, logs_q)
+
+    def infer(self, phone, phone_lengths, sid, rate=None):
+        g = self.emb_g(sid).unsqueeze(-1)
+        m_p, logs_p, x_mask = self.enc_p(phone, None, phone_lengths)
+        z_p = (m_p + torch.exp(logs_p) * torch.randn_like(m_p) * 0.66666) * x_mask
+        if rate:
+            head = int(z_p.shape[2] * rate)
+            z_p = z_p[:, :, -head:]
+            x_mask = x_mask[:, :, -head:]
+        z = self.flow(z_p, x_mask, g=g, reverse=True)
+        o = self.dec(z * x_mask, g=g)
+        return o, x_mask, (z, z_p, m_p, logs_p)
+
+
+class MultiPeriodDiscriminator(torch.nn.Module):
+    def __init__(self, use_spectral_norm=False):
+        super(MultiPeriodDiscriminator, self).__init__()
+        periods = [2, 3, 5, 7, 11, 17]
+        # periods = [3, 5, 7, 11, 17, 23, 37]
+
+        discs = [DiscriminatorS(use_spectral_norm=use_spectral_norm)]
+        discs = discs + [
+            DiscriminatorP(i, use_spectral_norm=use_spectral_norm) for i in periods
+        ]
+        self.discriminators = nn.ModuleList(discs)
+
+    def forward(self, y, y_hat):
+        y_d_rs = []  #
+        y_d_gs = []
+        fmap_rs = []
+        fmap_gs = []
+        for i, d in enumerate(self.discriminators):
+            y_d_r, fmap_r = d(y)
+            y_d_g, fmap_g = d(y_hat)
+            # for j in range(len(fmap_r)):
+            #     print(i,j,y.shape,y_hat.shape,fmap_r[j].shape,fmap_g[j].shape)
+            y_d_rs.append(y_d_r)
+            y_d_gs.append(y_d_g)
+            fmap_rs.append(fmap_r)
+            fmap_gs.append(fmap_g)
+
+        return y_d_rs, y_d_gs, fmap_rs, fmap_gs
+
+
+class MultiPeriodDiscriminatorV2(torch.nn.Module):
+    def __init__(self, use_spectral_norm=False):
+        super(MultiPeriodDiscriminatorV2, self).__init__()
+        # periods = [2, 3, 5, 7, 11, 17]
+        periods = [2, 3, 5, 7, 11, 17, 23, 37]
+
+        discs = [DiscriminatorS(use_spectral_norm=use_spectral_norm)]
+        discs = discs + [
+            DiscriminatorP(i, use_spectral_norm=use_spectral_norm) for i in periods
+        ]
+        self.discriminators = nn.ModuleList(discs)
+
+    def forward(self, y, y_hat):
+        y_d_rs = []  #
+        y_d_gs = []
+        fmap_rs = []
+        fmap_gs = []
+        for i, d in enumerate(self.discriminators):
+            y_d_r, fmap_r = d(y)
+            y_d_g, fmap_g = d(y_hat)
+            # for j in range(len(fmap_r)):
+            #     print(i,j,y.shape,y_hat.shape,fmap_r[j].shape,fmap_g[j].shape)
+            y_d_rs.append(y_d_r)
+            y_d_gs.append(y_d_g)
+            fmap_rs.append(fmap_r)
+            fmap_gs.append(fmap_g)
+
+        return y_d_rs, y_d_gs, fmap_rs, fmap_gs
+
+
+class DiscriminatorS(torch.nn.Module):
+    def __init__(self, use_spectral_norm=False):
+        super(DiscriminatorS, self).__init__()
+        norm_f = weight_norm if use_spectral_norm == False else spectral_norm
+        self.convs = nn.ModuleList(
+            [
+                norm_f(Conv1d(1, 16, 15, 1, padding=7)),
+                norm_f(Conv1d(16, 64, 41, 4, groups=4, padding=20)),
+                norm_f(Conv1d(64, 256, 41, 4, groups=16, padding=20)),
+                norm_f(Conv1d(256, 1024, 41, 4, groups=64, padding=20)),
+                norm_f(Conv1d(1024, 1024, 41, 4, groups=256, padding=20)),
+                norm_f(Conv1d(1024, 1024, 5, 1, padding=2)),
+            ]
+        )
+        self.conv_post = norm_f(Conv1d(1024, 1, 3, 1, padding=1))
+
+    def forward(self, x):
+        fmap = []
+
+        for l in self.convs:
+            x = l(x)
+            x = F.leaky_relu(x, modules.LRELU_SLOPE)
+            fmap.append(x)
+        x = self.conv_post(x)
+        fmap.append(x)
+        x = torch.flatten(x, 1, -1)
+
+        return x, fmap
+
+
+class DiscriminatorP(torch.nn.Module):
+    def __init__(self, period, kernel_size=5, stride=3, use_spectral_norm=False):
+        super(DiscriminatorP, self).__init__()
+        self.period = period
+        self.use_spectral_norm = use_spectral_norm
+        norm_f = weight_norm if use_spectral_norm == False else spectral_norm
+        self.convs = nn.ModuleList(
+            [
+                norm_f(
+                    Conv2d(
+                        1,
+                        32,
+                        (kernel_size, 1),
+                        (stride, 1),
+                        padding=(get_padding(kernel_size, 1), 0),
+                    )
+                ),
+                norm_f(
+                    Conv2d(
+                        32,
+                        128,
+                        (kernel_size, 1),
+                        (stride, 1),
+                        padding=(get_padding(kernel_size, 1), 0),
+                    )
+                ),
+                norm_f(
+                    Conv2d(
+                        128,
+                        512,
+                        (kernel_size, 1),
+                        (stride, 1),
+                        padding=(get_padding(kernel_size, 1), 0),
+                    )
+                ),
+                norm_f(
+                    Conv2d(
+                        512,
+                        1024,
+                        (kernel_size, 1),
+                        (stride, 1),
+                        padding=(get_padding(kernel_size, 1), 0),
+                    )
+                ),
+                norm_f(
+                    Conv2d(
+                        1024,
+                        1024,
+                        (kernel_size, 1),
+                        1,
+                        padding=(get_padding(kernel_size, 1), 0),
+                    )
+                ),
+            ]
+        )
+        self.conv_post = norm_f(Conv2d(1024, 1, (3, 1), 1, padding=(1, 0)))
+
+    def forward(self, x):
+        fmap = []
+
+        # 1d to 2d
+        b, c, t = x.shape
+        if t % self.period != 0:  # pad first
+            n_pad = self.period - (t % self.period)
+            x = F.pad(x, (0, n_pad), "reflect")
+            t = t + n_pad
+        x = x.view(b, c, t // self.period, self.period)
+
+        for l in self.convs:
+            x = l(x)
+            x = F.leaky_relu(x, modules.LRELU_SLOPE)
+            fmap.append(x)
+        x = self.conv_post(x)
+        fmap.append(x)
+        x = torch.flatten(x, 1, -1)
+
+        return x, fmap
\ No newline at end of file
diff --git a/lib/infer_pack/models_dml.py b/lib/infer_pack/models_dml.py
new file mode 100644
index 0000000000000000000000000000000000000000..958d7b29259763d2fea94caf8ba7e314c4a77d05
--- /dev/null
+++ b/lib/infer_pack/models_dml.py
@@ -0,0 +1,1124 @@
+import math, pdb, os
+from time import time as ttime
+import torch
+from torch import nn
+from torch.nn import functional as F
+from lib.infer_pack import modules
+from lib.infer_pack import attentions
+from lib.infer_pack import commons
+from lib.infer_pack.commons import init_weights, get_padding
+from torch.nn import Conv1d, ConvTranspose1d, AvgPool1d, Conv2d
+from torch.nn.utils import weight_norm, remove_weight_norm, spectral_norm
+from lib.infer_pack.commons import init_weights
+import numpy as np
+from lib.infer_pack import commons
+
+
+class TextEncoder256(nn.Module):
+    def __init__(
+        self,
+        out_channels,
+        hidden_channels,
+        filter_channels,
+        n_heads,
+        n_layers,
+        kernel_size,
+        p_dropout,
+        f0=True,
+    ):
+        super().__init__()
+        self.out_channels = out_channels
+        self.hidden_channels = hidden_channels
+        self.filter_channels = filter_channels
+        self.n_heads = n_heads
+        self.n_layers = n_layers
+        self.kernel_size = kernel_size
+        self.p_dropout = p_dropout
+        self.emb_phone = nn.Linear(256, hidden_channels)
+        self.lrelu = nn.LeakyReLU(0.1, inplace=True)
+        if f0 == True:
+            self.emb_pitch = nn.Embedding(256, hidden_channels)  # pitch 256
+        self.encoder = attentions.Encoder(
+            hidden_channels, filter_channels, n_heads, n_layers, kernel_size, p_dropout
+        )
+        self.proj = nn.Conv1d(hidden_channels, out_channels * 2, 1)
+
+    def forward(self, phone, pitch, lengths):
+        if pitch == None:
+            x = self.emb_phone(phone)
+        else:
+            x = self.emb_phone(phone) + self.emb_pitch(pitch)
+        x = x * math.sqrt(self.hidden_channels)  # [b, t, h]
+        x = self.lrelu(x)
+        x = torch.transpose(x, 1, -1)  # [b, h, t]
+        x_mask = torch.unsqueeze(commons.sequence_mask(lengths, x.size(2)), 1).to(
+            x.dtype
+        )
+        x = self.encoder(x * x_mask, x_mask)
+        stats = self.proj(x) * x_mask
+
+        m, logs = torch.split(stats, self.out_channels, dim=1)
+        return m, logs, x_mask
+
+
+class TextEncoder768(nn.Module):
+    def __init__(
+        self,
+        out_channels,
+        hidden_channels,
+        filter_channels,
+        n_heads,
+        n_layers,
+        kernel_size,
+        p_dropout,
+        f0=True,
+    ):
+        super().__init__()
+        self.out_channels = out_channels
+        self.hidden_channels = hidden_channels
+        self.filter_channels = filter_channels
+        self.n_heads = n_heads
+        self.n_layers = n_layers
+        self.kernel_size = kernel_size
+        self.p_dropout = p_dropout
+        self.emb_phone = nn.Linear(768, hidden_channels)
+        self.lrelu = nn.LeakyReLU(0.1, inplace=True)
+        if f0 == True:
+            self.emb_pitch = nn.Embedding(256, hidden_channels)  # pitch 256
+        self.encoder = attentions.Encoder(
+            hidden_channels, filter_channels, n_heads, n_layers, kernel_size, p_dropout
+        )
+        self.proj = nn.Conv1d(hidden_channels, out_channels * 2, 1)
+
+    def forward(self, phone, pitch, lengths):
+        if pitch == None:
+            x = self.emb_phone(phone)
+        else:
+            x = self.emb_phone(phone) + self.emb_pitch(pitch)
+        x = x * math.sqrt(self.hidden_channels)  # [b, t, h]
+        x = self.lrelu(x)
+        x = torch.transpose(x, 1, -1)  # [b, h, t]
+        x_mask = torch.unsqueeze(commons.sequence_mask(lengths, x.size(2)), 1).to(
+            x.dtype
+        )
+        x = self.encoder(x * x_mask, x_mask)
+        stats = self.proj(x) * x_mask
+
+        m, logs = torch.split(stats, self.out_channels, dim=1)
+        return m, logs, x_mask
+
+
+class ResidualCouplingBlock(nn.Module):
+    def __init__(
+        self,
+        channels,
+        hidden_channels,
+        kernel_size,
+        dilation_rate,
+        n_layers,
+        n_flows=4,
+        gin_channels=0,
+    ):
+        super().__init__()
+        self.channels = channels
+        self.hidden_channels = hidden_channels
+        self.kernel_size = kernel_size
+        self.dilation_rate = dilation_rate
+        self.n_layers = n_layers
+        self.n_flows = n_flows
+        self.gin_channels = gin_channels
+
+        self.flows = nn.ModuleList()
+        for i in range(n_flows):
+            self.flows.append(
+                modules.ResidualCouplingLayer(
+                    channels,
+                    hidden_channels,
+                    kernel_size,
+                    dilation_rate,
+                    n_layers,
+                    gin_channels=gin_channels,
+                    mean_only=True,
+                )
+            )
+            self.flows.append(modules.Flip())
+
+    def forward(self, x, x_mask, g=None, reverse=False):
+        if not reverse:
+            for flow in self.flows:
+                x, _ = flow(x, x_mask, g=g, reverse=reverse)
+        else:
+            for flow in reversed(self.flows):
+                x = flow(x, x_mask, g=g, reverse=reverse)
+        return x
+
+    def remove_weight_norm(self):
+        for i in range(self.n_flows):
+            self.flows[i * 2].remove_weight_norm()
+
+
+class PosteriorEncoder(nn.Module):
+    def __init__(
+        self,
+        in_channels,
+        out_channels,
+        hidden_channels,
+        kernel_size,
+        dilation_rate,
+        n_layers,
+        gin_channels=0,
+    ):
+        super().__init__()
+        self.in_channels = in_channels
+        self.out_channels = out_channels
+        self.hidden_channels = hidden_channels
+        self.kernel_size = kernel_size
+        self.dilation_rate = dilation_rate
+        self.n_layers = n_layers
+        self.gin_channels = gin_channels
+
+        self.pre = nn.Conv1d(in_channels, hidden_channels, 1)
+        self.enc = modules.WN(
+            hidden_channels,
+            kernel_size,
+            dilation_rate,
+            n_layers,
+            gin_channels=gin_channels,
+        )
+        self.proj = nn.Conv1d(hidden_channels, out_channels * 2, 1)
+
+    def forward(self, x, x_lengths, g=None):
+        x_mask = torch.unsqueeze(commons.sequence_mask(x_lengths, x.size(2)), 1).to(
+            x.dtype
+        )
+        x = self.pre(x) * x_mask
+        x = self.enc(x, x_mask, g=g)
+        stats = self.proj(x) * x_mask
+        m, logs = torch.split(stats, self.out_channels, dim=1)
+        z = (m + torch.randn_like(m) * torch.exp(logs)) * x_mask
+        return z, m, logs, x_mask
+
+    def remove_weight_norm(self):
+        self.enc.remove_weight_norm()
+
+
+class Generator(torch.nn.Module):
+    def __init__(
+        self,
+        initial_channel,
+        resblock,
+        resblock_kernel_sizes,
+        resblock_dilation_sizes,
+        upsample_rates,
+        upsample_initial_channel,
+        upsample_kernel_sizes,
+        gin_channels=0,
+    ):
+        super(Generator, self).__init__()
+        self.num_kernels = len(resblock_kernel_sizes)
+        self.num_upsamples = len(upsample_rates)
+        self.conv_pre = Conv1d(
+            initial_channel, upsample_initial_channel, 7, 1, padding=3
+        )
+        resblock = modules.ResBlock1 if resblock == "1" else modules.ResBlock2
+
+        self.ups = nn.ModuleList()
+        for i, (u, k) in enumerate(zip(upsample_rates, upsample_kernel_sizes)):
+            self.ups.append(
+                weight_norm(
+                    ConvTranspose1d(
+                        upsample_initial_channel // (2**i),
+                        upsample_initial_channel // (2 ** (i + 1)),
+                        k,
+                        u,
+                        padding=(k - u) // 2,
+                    )
+                )
+            )
+
+        self.resblocks = nn.ModuleList()
+        for i in range(len(self.ups)):
+            ch = upsample_initial_channel // (2 ** (i + 1))
+            for j, (k, d) in enumerate(
+                zip(resblock_kernel_sizes, resblock_dilation_sizes)
+            ):
+                self.resblocks.append(resblock(ch, k, d))
+
+        self.conv_post = Conv1d(ch, 1, 7, 1, padding=3, bias=False)
+        self.ups.apply(init_weights)
+
+        if gin_channels != 0:
+            self.cond = nn.Conv1d(gin_channels, upsample_initial_channel, 1)
+
+    def forward(self, x, g=None):
+        x = self.conv_pre(x)
+        if g is not None:
+            x = x + self.cond(g)
+
+        for i in range(self.num_upsamples):
+            x = F.leaky_relu(x, modules.LRELU_SLOPE)
+            x = self.ups[i](x)
+            xs = None
+            for j in range(self.num_kernels):
+                if xs is None:
+                    xs = self.resblocks[i * self.num_kernels + j](x)
+                else:
+                    xs += self.resblocks[i * self.num_kernels + j](x)
+            x = xs / self.num_kernels
+        x = F.leaky_relu(x)
+        x = self.conv_post(x)
+        x = torch.tanh(x)
+
+        return x
+
+    def remove_weight_norm(self):
+        for l in self.ups:
+            remove_weight_norm(l)
+        for l in self.resblocks:
+            l.remove_weight_norm()
+
+
+class SineGen(torch.nn.Module):
+    """Definition of sine generator
+    SineGen(samp_rate, harmonic_num = 0,
+            sine_amp = 0.1, noise_std = 0.003,
+            voiced_threshold = 0,
+            flag_for_pulse=False)
+    samp_rate: sampling rate in Hz
+    harmonic_num: number of harmonic overtones (default 0)
+    sine_amp: amplitude of sine-wavefrom (default 0.1)
+    noise_std: std of Gaussian noise (default 0.003)
+    voiced_thoreshold: F0 threshold for U/V classification (default 0)
+    flag_for_pulse: this SinGen is used inside PulseGen (default False)
+    Note: when flag_for_pulse is True, the first time step of a voiced
+        segment is always sin(np.pi) or cos(0)
+    """
+
+    def __init__(
+        self,
+        samp_rate,
+        harmonic_num=0,
+        sine_amp=0.1,
+        noise_std=0.003,
+        voiced_threshold=0,
+        flag_for_pulse=False,
+    ):
+        super(SineGen, self).__init__()
+        self.sine_amp = sine_amp
+        self.noise_std = noise_std
+        self.harmonic_num = harmonic_num
+        self.dim = self.harmonic_num + 1
+        self.sampling_rate = samp_rate
+        self.voiced_threshold = voiced_threshold
+
+    def _f02uv(self, f0):
+        # generate uv signal
+        uv = torch.ones_like(f0)
+        uv = uv * (f0 > self.voiced_threshold)
+        return uv.float()
+
+    def forward(self, f0, upp):
+        """sine_tensor, uv = forward(f0)
+        input F0: tensor(batchsize=1, length, dim=1)
+                  f0 for unvoiced steps should be 0
+        output sine_tensor: tensor(batchsize=1, length, dim)
+        output uv: tensor(batchsize=1, length, 1)
+        """
+        with torch.no_grad():
+            f0 = f0[:, None].transpose(1, 2)
+            f0_buf = torch.zeros(f0.shape[0], f0.shape[1], self.dim, device=f0.device)
+            # fundamental component
+            f0_buf[:, :, 0] = f0[:, :, 0]
+            for idx in np.arange(self.harmonic_num):
+                f0_buf[:, :, idx + 1] = f0_buf[:, :, 0] * (
+                    idx + 2
+                )  # idx + 2: the (idx+1)-th overtone, (idx+2)-th harmonic
+            rad_values = (f0_buf / self.sampling_rate) % 1  ###%1意味着n_har的乘积无法后处理优化
+            rand_ini = torch.rand(
+                f0_buf.shape[0], f0_buf.shape[2], device=f0_buf.device
+            )
+            rand_ini[:, 0] = 0
+            rad_values[:, 0, :] = rad_values[:, 0, :] + rand_ini
+            tmp_over_one = torch.cumsum(rad_values, 1)  # % 1  #####%1意味着后面的cumsum无法再优化
+            tmp_over_one *= upp
+            tmp_over_one = F.interpolate(
+                tmp_over_one.transpose(2, 1),
+                scale_factor=upp,
+                mode="linear",
+                align_corners=True,
+            ).transpose(2, 1)
+            rad_values = F.interpolate(
+                rad_values.transpose(2, 1), scale_factor=upp, mode="nearest"
+            ).transpose(
+                2, 1
+            )  #######
+            tmp_over_one %= 1
+            tmp_over_one_idx = (tmp_over_one[:, 1:, :] - tmp_over_one[:, :-1, :]) < 0
+            cumsum_shift = torch.zeros_like(rad_values)
+            cumsum_shift[:, 1:, :] = tmp_over_one_idx * -1.0
+            sine_waves = torch.sin(
+                torch.cumsum(rad_values + cumsum_shift, dim=1) * 2 * np.pi
+            )
+            sine_waves = sine_waves * self.sine_amp
+            uv = self._f02uv(f0)
+            uv = F.interpolate(
+                uv.transpose(2, 1), scale_factor=upp, mode="nearest"
+            ).transpose(2, 1)
+            noise_amp = uv * self.noise_std + (1 - uv) * self.sine_amp / 3
+            noise = noise_amp * torch.randn_like(sine_waves)
+            sine_waves = sine_waves * uv + noise
+        return sine_waves, uv, noise
+
+
+class SourceModuleHnNSF(torch.nn.Module):
+    """SourceModule for hn-nsf
+    SourceModule(sampling_rate, harmonic_num=0, sine_amp=0.1,
+                 add_noise_std=0.003, voiced_threshod=0)
+    sampling_rate: sampling_rate in Hz
+    harmonic_num: number of harmonic above F0 (default: 0)
+    sine_amp: amplitude of sine source signal (default: 0.1)
+    add_noise_std: std of additive Gaussian noise (default: 0.003)
+        note that amplitude of noise in unvoiced is decided
+        by sine_amp
+    voiced_threshold: threhold to set U/V given F0 (default: 0)
+    Sine_source, noise_source = SourceModuleHnNSF(F0_sampled)
+    F0_sampled (batchsize, length, 1)
+    Sine_source (batchsize, length, 1)
+    noise_source (batchsize, length 1)
+    uv (batchsize, length, 1)
+    """
+
+    def __init__(
+        self,
+        sampling_rate,
+        harmonic_num=0,
+        sine_amp=0.1,
+        add_noise_std=0.003,
+        voiced_threshod=0,
+        is_half=True,
+    ):
+        super(SourceModuleHnNSF, self).__init__()
+
+        self.sine_amp = sine_amp
+        self.noise_std = add_noise_std
+        self.is_half = is_half
+        # to produce sine waveforms
+        self.l_sin_gen = SineGen(
+            sampling_rate, harmonic_num, sine_amp, add_noise_std, voiced_threshod
+        )
+
+        # to merge source harmonics into a single excitation
+        self.l_linear = torch.nn.Linear(harmonic_num + 1, 1)
+        self.l_tanh = torch.nn.Tanh()
+
+    def forward(self, x, upp=None):
+        sine_wavs, uv, _ = self.l_sin_gen(x, upp)
+        if self.is_half:
+            sine_wavs = sine_wavs.half()
+        sine_merge = self.l_tanh(self.l_linear(sine_wavs))
+        return sine_merge, None, None  # noise, uv
+
+
+class GeneratorNSF(torch.nn.Module):
+    def __init__(
+        self,
+        initial_channel,
+        resblock,
+        resblock_kernel_sizes,
+        resblock_dilation_sizes,
+        upsample_rates,
+        upsample_initial_channel,
+        upsample_kernel_sizes,
+        gin_channels,
+        sr,
+        is_half=False,
+    ):
+        super(GeneratorNSF, self).__init__()
+        self.num_kernels = len(resblock_kernel_sizes)
+        self.num_upsamples = len(upsample_rates)
+
+        self.f0_upsamp = torch.nn.Upsample(scale_factor=np.prod(upsample_rates))
+        self.m_source = SourceModuleHnNSF(
+            sampling_rate=sr, harmonic_num=0, is_half=is_half
+        )
+        self.noise_convs = nn.ModuleList()
+        self.conv_pre = Conv1d(
+            initial_channel, upsample_initial_channel, 7, 1, padding=3
+        )
+        resblock = modules.ResBlock1 if resblock == "1" else modules.ResBlock2
+
+        self.ups = nn.ModuleList()
+        for i, (u, k) in enumerate(zip(upsample_rates, upsample_kernel_sizes)):
+            c_cur = upsample_initial_channel // (2 ** (i + 1))
+            self.ups.append(
+                weight_norm(
+                    ConvTranspose1d(
+                        upsample_initial_channel // (2**i),
+                        upsample_initial_channel // (2 ** (i + 1)),
+                        k,
+                        u,
+                        padding=(k - u) // 2,
+                    )
+                )
+            )
+            if i + 1 < len(upsample_rates):
+                stride_f0 = np.prod(upsample_rates[i + 1 :])
+                self.noise_convs.append(
+                    Conv1d(
+                        1,
+                        c_cur,
+                        kernel_size=stride_f0 * 2,
+                        stride=stride_f0,
+                        padding=stride_f0 // 2,
+                    )
+                )
+            else:
+                self.noise_convs.append(Conv1d(1, c_cur, kernel_size=1))
+
+        self.resblocks = nn.ModuleList()
+        for i in range(len(self.ups)):
+            ch = upsample_initial_channel // (2 ** (i + 1))
+            for j, (k, d) in enumerate(
+                zip(resblock_kernel_sizes, resblock_dilation_sizes)
+            ):
+                self.resblocks.append(resblock(ch, k, d))
+
+        self.conv_post = Conv1d(ch, 1, 7, 1, padding=3, bias=False)
+        self.ups.apply(init_weights)
+
+        if gin_channels != 0:
+            self.cond = nn.Conv1d(gin_channels, upsample_initial_channel, 1)
+
+        self.upp = np.prod(upsample_rates)
+
+    def forward(self, x, f0, g=None):
+        har_source, noi_source, uv = self.m_source(f0, self.upp)
+        har_source = har_source.transpose(1, 2)
+        x = self.conv_pre(x)
+        if g is not None:
+            x = x + self.cond(g)
+
+        for i in range(self.num_upsamples):
+            x = F.leaky_relu(x, modules.LRELU_SLOPE)
+            x = self.ups[i](x)
+            x_source = self.noise_convs[i](har_source)
+            x = x + x_source
+            xs = None
+            for j in range(self.num_kernels):
+                if xs is None:
+                    xs = self.resblocks[i * self.num_kernels + j](x)
+                else:
+                    xs += self.resblocks[i * self.num_kernels + j](x)
+            x = xs / self.num_kernels
+        x = F.leaky_relu(x)
+        x = self.conv_post(x)
+        x = torch.tanh(x)
+        return x
+
+    def remove_weight_norm(self):
+        for l in self.ups:
+            remove_weight_norm(l)
+        for l in self.resblocks:
+            l.remove_weight_norm()
+
+
+sr2sr = {
+    "32k": 32000,
+    "40k": 40000,
+    "48k": 48000,
+}
+
+
+class SynthesizerTrnMs256NSFsid(nn.Module):
+    def __init__(
+        self,
+        spec_channels,
+        segment_size,
+        inter_channels,
+        hidden_channels,
+        filter_channels,
+        n_heads,
+        n_layers,
+        kernel_size,
+        p_dropout,
+        resblock,
+        resblock_kernel_sizes,
+        resblock_dilation_sizes,
+        upsample_rates,
+        upsample_initial_channel,
+        upsample_kernel_sizes,
+        spk_embed_dim,
+        gin_channels,
+        sr,
+        **kwargs
+    ):
+        super().__init__()
+        if type(sr) == type("strr"):
+            sr = sr2sr[sr]
+        self.spec_channels = spec_channels
+        self.inter_channels = inter_channels
+        self.hidden_channels = hidden_channels
+        self.filter_channels = filter_channels
+        self.n_heads = n_heads
+        self.n_layers = n_layers
+        self.kernel_size = kernel_size
+        self.p_dropout = p_dropout
+        self.resblock = resblock
+        self.resblock_kernel_sizes = resblock_kernel_sizes
+        self.resblock_dilation_sizes = resblock_dilation_sizes
+        self.upsample_rates = upsample_rates
+        self.upsample_initial_channel = upsample_initial_channel
+        self.upsample_kernel_sizes = upsample_kernel_sizes
+        self.segment_size = segment_size
+        self.gin_channels = gin_channels
+        # self.hop_length = hop_length#
+        self.spk_embed_dim = spk_embed_dim
+        self.enc_p = TextEncoder256(
+            inter_channels,
+            hidden_channels,
+            filter_channels,
+            n_heads,
+            n_layers,
+            kernel_size,
+            p_dropout,
+        )
+        self.dec = GeneratorNSF(
+            inter_channels,
+            resblock,
+            resblock_kernel_sizes,
+            resblock_dilation_sizes,
+            upsample_rates,
+            upsample_initial_channel,
+            upsample_kernel_sizes,
+            gin_channels=gin_channels,
+            sr=sr,
+            is_half=kwargs["is_half"],
+        )
+        self.enc_q = PosteriorEncoder(
+            spec_channels,
+            inter_channels,
+            hidden_channels,
+            5,
+            1,
+            16,
+            gin_channels=gin_channels,
+        )
+        self.flow = ResidualCouplingBlock(
+            inter_channels, hidden_channels, 5, 1, 3, gin_channels=gin_channels
+        )
+        self.emb_g = nn.Embedding(self.spk_embed_dim, gin_channels)
+        print("gin_channels:", gin_channels, "self.spk_embed_dim:", self.spk_embed_dim)
+
+    def remove_weight_norm(self):
+        self.dec.remove_weight_norm()
+        self.flow.remove_weight_norm()
+        self.enc_q.remove_weight_norm()
+
+    def forward(
+        self, phone, phone_lengths, pitch, pitchf, y, y_lengths, ds
+    ):  # 这里ds是id，[bs,1]
+        # print(1,pitch.shape)#[bs,t]
+        g = self.emb_g(ds).unsqueeze(-1)  # [b, 256, 1]##1是t，广播的
+        m_p, logs_p, x_mask = self.enc_p(phone, pitch, phone_lengths)
+        z, m_q, logs_q, y_mask = self.enc_q(y, y_lengths, g=g)
+        z_p = self.flow(z, y_mask, g=g)
+        z_slice, ids_slice = commons.rand_slice_segments(
+            z, y_lengths, self.segment_size
+        )
+        # print(-1,pitchf.shape,ids_slice,self.segment_size,self.hop_length,self.segment_size//self.hop_length)
+        pitchf = commons.slice_segments2(pitchf, ids_slice, self.segment_size)
+        # print(-2,pitchf.shape,z_slice.shape)
+        o = self.dec(z_slice, pitchf, g=g)
+        return o, ids_slice, x_mask, y_mask, (z, z_p, m_p, logs_p, m_q, logs_q)
+
+    def infer(self, phone, phone_lengths, pitch, nsff0, sid, max_len=None):
+        g = self.emb_g(sid).unsqueeze(-1)
+        m_p, logs_p, x_mask = self.enc_p(phone, pitch, phone_lengths)
+        z_p = (m_p + torch.exp(logs_p) * torch.randn_like(m_p) * 0.66666) * x_mask
+        z = self.flow(z_p, x_mask, g=g, reverse=True)
+        o = self.dec((z * x_mask)[:, :, :max_len], nsff0, g=g)
+        return o, x_mask, (z, z_p, m_p, logs_p)
+
+
+class SynthesizerTrnMs768NSFsid(nn.Module):
+    def __init__(
+        self,
+        spec_channels,
+        segment_size,
+        inter_channels,
+        hidden_channels,
+        filter_channels,
+        n_heads,
+        n_layers,
+        kernel_size,
+        p_dropout,
+        resblock,
+        resblock_kernel_sizes,
+        resblock_dilation_sizes,
+        upsample_rates,
+        upsample_initial_channel,
+        upsample_kernel_sizes,
+        spk_embed_dim,
+        gin_channels,
+        sr,
+        **kwargs
+    ):
+        super().__init__()
+        if type(sr) == type("strr"):
+            sr = sr2sr[sr]
+        self.spec_channels = spec_channels
+        self.inter_channels = inter_channels
+        self.hidden_channels = hidden_channels
+        self.filter_channels = filter_channels
+        self.n_heads = n_heads
+        self.n_layers = n_layers
+        self.kernel_size = kernel_size
+        self.p_dropout = p_dropout
+        self.resblock = resblock
+        self.resblock_kernel_sizes = resblock_kernel_sizes
+        self.resblock_dilation_sizes = resblock_dilation_sizes
+        self.upsample_rates = upsample_rates
+        self.upsample_initial_channel = upsample_initial_channel
+        self.upsample_kernel_sizes = upsample_kernel_sizes
+        self.segment_size = segment_size
+        self.gin_channels = gin_channels
+        # self.hop_length = hop_length#
+        self.spk_embed_dim = spk_embed_dim
+        self.enc_p = TextEncoder768(
+            inter_channels,
+            hidden_channels,
+            filter_channels,
+            n_heads,
+            n_layers,
+            kernel_size,
+            p_dropout,
+        )
+        self.dec = GeneratorNSF(
+            inter_channels,
+            resblock,
+            resblock_kernel_sizes,
+            resblock_dilation_sizes,
+            upsample_rates,
+            upsample_initial_channel,
+            upsample_kernel_sizes,
+            gin_channels=gin_channels,
+            sr=sr,
+            is_half=kwargs["is_half"],
+        )
+        self.enc_q = PosteriorEncoder(
+            spec_channels,
+            inter_channels,
+            hidden_channels,
+            5,
+            1,
+            16,
+            gin_channels=gin_channels,
+        )
+        self.flow = ResidualCouplingBlock(
+            inter_channels, hidden_channels, 5, 1, 3, gin_channels=gin_channels
+        )
+        self.emb_g = nn.Embedding(self.spk_embed_dim, gin_channels)
+        print("gin_channels:", gin_channels, "self.spk_embed_dim:", self.spk_embed_dim)
+
+    def remove_weight_norm(self):
+        self.dec.remove_weight_norm()
+        self.flow.remove_weight_norm()
+        self.enc_q.remove_weight_norm()
+
+    def forward(
+        self, phone, phone_lengths, pitch, pitchf, y, y_lengths, ds
+    ):  # 这里ds是id，[bs,1]
+        # print(1,pitch.shape)#[bs,t]
+        g = self.emb_g(ds).unsqueeze(-1)  # [b, 256, 1]##1是t，广播的
+        m_p, logs_p, x_mask = self.enc_p(phone, pitch, phone_lengths)
+        z, m_q, logs_q, y_mask = self.enc_q(y, y_lengths, g=g)
+        z_p = self.flow(z, y_mask, g=g)
+        z_slice, ids_slice = commons.rand_slice_segments(
+            z, y_lengths, self.segment_size
+        )
+        # print(-1,pitchf.shape,ids_slice,self.segment_size,self.hop_length,self.segment_size//self.hop_length)
+        pitchf = commons.slice_segments2(pitchf, ids_slice, self.segment_size)
+        # print(-2,pitchf.shape,z_slice.shape)
+        o = self.dec(z_slice, pitchf, g=g)
+        return o, ids_slice, x_mask, y_mask, (z, z_p, m_p, logs_p, m_q, logs_q)
+
+    def infer(self, phone, phone_lengths, pitch, nsff0, sid, max_len=None):
+        g = self.emb_g(sid).unsqueeze(-1)
+        m_p, logs_p, x_mask = self.enc_p(phone, pitch, phone_lengths)
+        z_p = (m_p + torch.exp(logs_p) * torch.randn_like(m_p) * 0.66666) * x_mask
+        z = self.flow(z_p, x_mask, g=g, reverse=True)
+        o = self.dec((z * x_mask)[:, :, :max_len], nsff0, g=g)
+        return o, x_mask, (z, z_p, m_p, logs_p)
+
+
+class SynthesizerTrnMs256NSFsid_nono(nn.Module):
+    def __init__(
+        self,
+        spec_channels,
+        segment_size,
+        inter_channels,
+        hidden_channels,
+        filter_channels,
+        n_heads,
+        n_layers,
+        kernel_size,
+        p_dropout,
+        resblock,
+        resblock_kernel_sizes,
+        resblock_dilation_sizes,
+        upsample_rates,
+        upsample_initial_channel,
+        upsample_kernel_sizes,
+        spk_embed_dim,
+        gin_channels,
+        sr=None,
+        **kwargs
+    ):
+        super().__init__()
+        self.spec_channels = spec_channels
+        self.inter_channels = inter_channels
+        self.hidden_channels = hidden_channels
+        self.filter_channels = filter_channels
+        self.n_heads = n_heads
+        self.n_layers = n_layers
+        self.kernel_size = kernel_size
+        self.p_dropout = p_dropout
+        self.resblock = resblock
+        self.resblock_kernel_sizes = resblock_kernel_sizes
+        self.resblock_dilation_sizes = resblock_dilation_sizes
+        self.upsample_rates = upsample_rates
+        self.upsample_initial_channel = upsample_initial_channel
+        self.upsample_kernel_sizes = upsample_kernel_sizes
+        self.segment_size = segment_size
+        self.gin_channels = gin_channels
+        # self.hop_length = hop_length#
+        self.spk_embed_dim = spk_embed_dim
+        self.enc_p = TextEncoder256(
+            inter_channels,
+            hidden_channels,
+            filter_channels,
+            n_heads,
+            n_layers,
+            kernel_size,
+            p_dropout,
+            f0=False,
+        )
+        self.dec = Generator(
+            inter_channels,
+            resblock,
+            resblock_kernel_sizes,
+            resblock_dilation_sizes,
+            upsample_rates,
+            upsample_initial_channel,
+            upsample_kernel_sizes,
+            gin_channels=gin_channels,
+        )
+        self.enc_q = PosteriorEncoder(
+            spec_channels,
+            inter_channels,
+            hidden_channels,
+            5,
+            1,
+            16,
+            gin_channels=gin_channels,
+        )
+        self.flow = ResidualCouplingBlock(
+            inter_channels, hidden_channels, 5, 1, 3, gin_channels=gin_channels
+        )
+        self.emb_g = nn.Embedding(self.spk_embed_dim, gin_channels)
+        print("gin_channels:", gin_channels, "self.spk_embed_dim:", self.spk_embed_dim)
+
+    def remove_weight_norm(self):
+        self.dec.remove_weight_norm()
+        self.flow.remove_weight_norm()
+        self.enc_q.remove_weight_norm()
+
+    def forward(self, phone, phone_lengths, y, y_lengths, ds):  # 这里ds是id，[bs,1]
+        g = self.emb_g(ds).unsqueeze(-1)  # [b, 256, 1]##1是t，广播的
+        m_p, logs_p, x_mask = self.enc_p(phone, None, phone_lengths)
+        z, m_q, logs_q, y_mask = self.enc_q(y, y_lengths, g=g)
+        z_p = self.flow(z, y_mask, g=g)
+        z_slice, ids_slice = commons.rand_slice_segments(
+            z, y_lengths, self.segment_size
+        )
+        o = self.dec(z_slice, g=g)
+        return o, ids_slice, x_mask, y_mask, (z, z_p, m_p, logs_p, m_q, logs_q)
+
+    def infer(self, phone, phone_lengths, sid, max_len=None):
+        g = self.emb_g(sid).unsqueeze(-1)
+        m_p, logs_p, x_mask = self.enc_p(phone, None, phone_lengths)
+        z_p = (m_p + torch.exp(logs_p) * torch.randn_like(m_p) * 0.66666) * x_mask
+        z = self.flow(z_p, x_mask, g=g, reverse=True)
+        o = self.dec((z * x_mask)[:, :, :max_len], g=g)
+        return o, x_mask, (z, z_p, m_p, logs_p)
+
+
+class SynthesizerTrnMs768NSFsid_nono(nn.Module):
+    def __init__(
+        self,
+        spec_channels,
+        segment_size,
+        inter_channels,
+        hidden_channels,
+        filter_channels,
+        n_heads,
+        n_layers,
+        kernel_size,
+        p_dropout,
+        resblock,
+        resblock_kernel_sizes,
+        resblock_dilation_sizes,
+        upsample_rates,
+        upsample_initial_channel,
+        upsample_kernel_sizes,
+        spk_embed_dim,
+        gin_channels,
+        sr=None,
+        **kwargs
+    ):
+        super().__init__()
+        self.spec_channels = spec_channels
+        self.inter_channels = inter_channels
+        self.hidden_channels = hidden_channels
+        self.filter_channels = filter_channels
+        self.n_heads = n_heads
+        self.n_layers = n_layers
+        self.kernel_size = kernel_size
+        self.p_dropout = p_dropout
+        self.resblock = resblock
+        self.resblock_kernel_sizes = resblock_kernel_sizes
+        self.resblock_dilation_sizes = resblock_dilation_sizes
+        self.upsample_rates = upsample_rates
+        self.upsample_initial_channel = upsample_initial_channel
+        self.upsample_kernel_sizes = upsample_kernel_sizes
+        self.segment_size = segment_size
+        self.gin_channels = gin_channels
+        # self.hop_length = hop_length#
+        self.spk_embed_dim = spk_embed_dim
+        self.enc_p = TextEncoder768(
+            inter_channels,
+            hidden_channels,
+            filter_channels,
+            n_heads,
+            n_layers,
+            kernel_size,
+            p_dropout,
+            f0=False,
+        )
+        self.dec = Generator(
+            inter_channels,
+            resblock,
+            resblock_kernel_sizes,
+            resblock_dilation_sizes,
+            upsample_rates,
+            upsample_initial_channel,
+            upsample_kernel_sizes,
+            gin_channels=gin_channels,
+        )
+        self.enc_q = PosteriorEncoder(
+            spec_channels,
+            inter_channels,
+            hidden_channels,
+            5,
+            1,
+            16,
+            gin_channels=gin_channels,
+        )
+        self.flow = ResidualCouplingBlock(
+            inter_channels, hidden_channels, 5, 1, 3, gin_channels=gin_channels
+        )
+        self.emb_g = nn.Embedding(self.spk_embed_dim, gin_channels)
+        print("gin_channels:", gin_channels, "self.spk_embed_dim:", self.spk_embed_dim)
+
+    def remove_weight_norm(self):
+        self.dec.remove_weight_norm()
+        self.flow.remove_weight_norm()
+        self.enc_q.remove_weight_norm()
+
+    def forward(self, phone, phone_lengths, y, y_lengths, ds):  # 这里ds是id，[bs,1]
+        g = self.emb_g(ds).unsqueeze(-1)  # [b, 256, 1]##1是t，广播的
+        m_p, logs_p, x_mask = self.enc_p(phone, None, phone_lengths)
+        z, m_q, logs_q, y_mask = self.enc_q(y, y_lengths, g=g)
+        z_p = self.flow(z, y_mask, g=g)
+        z_slice, ids_slice = commons.rand_slice_segments(
+            z, y_lengths, self.segment_size
+        )
+        o = self.dec(z_slice, g=g)
+        return o, ids_slice, x_mask, y_mask, (z, z_p, m_p, logs_p, m_q, logs_q)
+
+    def infer(self, phone, phone_lengths, sid, max_len=None):
+        g = self.emb_g(sid).unsqueeze(-1)
+        m_p, logs_p, x_mask = self.enc_p(phone, None, phone_lengths)
+        z_p = (m_p + torch.exp(logs_p) * torch.randn_like(m_p) * 0.66666) * x_mask
+        z = self.flow(z_p, x_mask, g=g, reverse=True)
+        o = self.dec((z * x_mask)[:, :, :max_len], g=g)
+        return o, x_mask, (z, z_p, m_p, logs_p)
+
+
+class MultiPeriodDiscriminator(torch.nn.Module):
+    def __init__(self, use_spectral_norm=False):
+        super(MultiPeriodDiscriminator, self).__init__()
+        periods = [2, 3, 5, 7, 11, 17]
+        # periods = [3, 5, 7, 11, 17, 23, 37]
+
+        discs = [DiscriminatorS(use_spectral_norm=use_spectral_norm)]
+        discs = discs + [
+            DiscriminatorP(i, use_spectral_norm=use_spectral_norm) for i in periods
+        ]
+        self.discriminators = nn.ModuleList(discs)
+
+    def forward(self, y, y_hat):
+        y_d_rs = []  #
+        y_d_gs = []
+        fmap_rs = []
+        fmap_gs = []
+        for i, d in enumerate(self.discriminators):
+            y_d_r, fmap_r = d(y)
+            y_d_g, fmap_g = d(y_hat)
+            # for j in range(len(fmap_r)):
+            #     print(i,j,y.shape,y_hat.shape,fmap_r[j].shape,fmap_g[j].shape)
+            y_d_rs.append(y_d_r)
+            y_d_gs.append(y_d_g)
+            fmap_rs.append(fmap_r)
+            fmap_gs.append(fmap_g)
+
+        return y_d_rs, y_d_gs, fmap_rs, fmap_gs
+
+
+class MultiPeriodDiscriminatorV2(torch.nn.Module):
+    def __init__(self, use_spectral_norm=False):
+        super(MultiPeriodDiscriminatorV2, self).__init__()
+        # periods = [2, 3, 5, 7, 11, 17]
+        periods = [2, 3, 5, 7, 11, 17, 23, 37]
+
+        discs = [DiscriminatorS(use_spectral_norm=use_spectral_norm)]
+        discs = discs + [
+            DiscriminatorP(i, use_spectral_norm=use_spectral_norm) for i in periods
+        ]
+        self.discriminators = nn.ModuleList(discs)
+
+    def forward(self, y, y_hat):
+        y_d_rs = []  #
+        y_d_gs = []
+        fmap_rs = []
+        fmap_gs = []
+        for i, d in enumerate(self.discriminators):
+            y_d_r, fmap_r = d(y)
+            y_d_g, fmap_g = d(y_hat)
+            # for j in range(len(fmap_r)):
+            #     print(i,j,y.shape,y_hat.shape,fmap_r[j].shape,fmap_g[j].shape)
+            y_d_rs.append(y_d_r)
+            y_d_gs.append(y_d_g)
+            fmap_rs.append(fmap_r)
+            fmap_gs.append(fmap_g)
+
+        return y_d_rs, y_d_gs, fmap_rs, fmap_gs
+
+
+class DiscriminatorS(torch.nn.Module):
+    def __init__(self, use_spectral_norm=False):
+        super(DiscriminatorS, self).__init__()
+        norm_f = weight_norm if use_spectral_norm == False else spectral_norm
+        self.convs = nn.ModuleList(
+            [
+                norm_f(Conv1d(1, 16, 15, 1, padding=7)),
+                norm_f(Conv1d(16, 64, 41, 4, groups=4, padding=20)),
+                norm_f(Conv1d(64, 256, 41, 4, groups=16, padding=20)),
+                norm_f(Conv1d(256, 1024, 41, 4, groups=64, padding=20)),
+                norm_f(Conv1d(1024, 1024, 41, 4, groups=256, padding=20)),
+                norm_f(Conv1d(1024, 1024, 5, 1, padding=2)),
+            ]
+        )
+        self.conv_post = norm_f(Conv1d(1024, 1, 3, 1, padding=1))
+
+    def forward(self, x):
+        fmap = []
+
+        for l in self.convs:
+            x = l(x)
+            x = F.leaky_relu(x, modules.LRELU_SLOPE)
+            fmap.append(x)
+        x = self.conv_post(x)
+        fmap.append(x)
+        x = torch.flatten(x, 1, -1)
+
+        return x, fmap
+
+
+class DiscriminatorP(torch.nn.Module):
+    def __init__(self, period, kernel_size=5, stride=3, use_spectral_norm=False):
+        super(DiscriminatorP, self).__init__()
+        self.period = period
+        self.use_spectral_norm = use_spectral_norm
+        norm_f = weight_norm if use_spectral_norm == False else spectral_norm
+        self.convs = nn.ModuleList(
+            [
+                norm_f(
+                    Conv2d(
+                        1,
+                        32,
+                        (kernel_size, 1),
+                        (stride, 1),
+                        padding=(get_padding(kernel_size, 1), 0),
+                    )
+                ),
+                norm_f(
+                    Conv2d(
+                        32,
+                        128,
+                        (kernel_size, 1),
+                        (stride, 1),
+                        padding=(get_padding(kernel_size, 1), 0),
+                    )
+                ),
+                norm_f(
+                    Conv2d(
+                        128,
+                        512,
+                        (kernel_size, 1),
+                        (stride, 1),
+                        padding=(get_padding(kernel_size, 1), 0),
+                    )
+                ),
+                norm_f(
+                    Conv2d(
+                        512,
+                        1024,
+                        (kernel_size, 1),
+                        (stride, 1),
+                        padding=(get_padding(kernel_size, 1), 0),
+                    )
+                ),
+                norm_f(
+                    Conv2d(
+                        1024,
+                        1024,
+                        (kernel_size, 1),
+                        1,
+                        padding=(get_padding(kernel_size, 1), 0),
+                    )
+                ),
+            ]
+        )
+        self.conv_post = norm_f(Conv2d(1024, 1, (3, 1), 1, padding=(1, 0)))
+
+    def forward(self, x):
+        fmap = []
+
+        # 1d to 2d
+        b, c, t = x.shape
+        if t % self.period != 0:  # pad first
+            n_pad = self.period - (t % self.period)
+            x = F.pad(x, (0, n_pad), "reflect")
+            t = t + n_pad
+        x = x.view(b, c, t // self.period, self.period)
+
+        for l in self.convs:
+            x = l(x)
+            x = F.leaky_relu(x, modules.LRELU_SLOPE)
+            fmap.append(x)
+        x = self.conv_post(x)
+        fmap.append(x)
+        x = torch.flatten(x, 1, -1)
+
+        return x, fmap
diff --git a/lib/infer_pack/models_onnx.py b/lib/infer_pack/models_onnx.py
new file mode 100644
index 0000000000000000000000000000000000000000..963e67b29f828e9fdd096397952054fe77cf3d10
--- /dev/null
+++ b/lib/infer_pack/models_onnx.py
@@ -0,0 +1,819 @@
+import math, pdb, os
+from time import time as ttime
+import torch
+from torch import nn
+from torch.nn import functional as F
+from lib.infer_pack import modules
+from lib.infer_pack import attentions
+from lib.infer_pack import commons
+from lib.infer_pack.commons import init_weights, get_padding
+from torch.nn import Conv1d, ConvTranspose1d, AvgPool1d, Conv2d
+from torch.nn.utils import weight_norm, remove_weight_norm, spectral_norm
+from lib.infer_pack.commons import init_weights
+import numpy as np
+from lib.infer_pack import commons
+
+
+class TextEncoder256(nn.Module):
+    def __init__(
+        self,
+        out_channels,
+        hidden_channels,
+        filter_channels,
+        n_heads,
+        n_layers,
+        kernel_size,
+        p_dropout,
+        f0=True,
+    ):
+        super().__init__()
+        self.out_channels = out_channels
+        self.hidden_channels = hidden_channels
+        self.filter_channels = filter_channels
+        self.n_heads = n_heads
+        self.n_layers = n_layers
+        self.kernel_size = kernel_size
+        self.p_dropout = p_dropout
+        self.emb_phone = nn.Linear(256, hidden_channels)
+        self.lrelu = nn.LeakyReLU(0.1, inplace=True)
+        if f0 == True:
+            self.emb_pitch = nn.Embedding(256, hidden_channels)  # pitch 256
+        self.encoder = attentions.Encoder(
+            hidden_channels, filter_channels, n_heads, n_layers, kernel_size, p_dropout
+        )
+        self.proj = nn.Conv1d(hidden_channels, out_channels * 2, 1)
+
+    def forward(self, phone, pitch, lengths):
+        if pitch == None:
+            x = self.emb_phone(phone)
+        else:
+            x = self.emb_phone(phone) + self.emb_pitch(pitch)
+        x = x * math.sqrt(self.hidden_channels)  # [b, t, h]
+        x = self.lrelu(x)
+        x = torch.transpose(x, 1, -1)  # [b, h, t]
+        x_mask = torch.unsqueeze(commons.sequence_mask(lengths, x.size(2)), 1).to(
+            x.dtype
+        )
+        x = self.encoder(x * x_mask, x_mask)
+        stats = self.proj(x) * x_mask
+
+        m, logs = torch.split(stats, self.out_channels, dim=1)
+        return m, logs, x_mask
+
+
+class TextEncoder768(nn.Module):
+    def __init__(
+        self,
+        out_channels,
+        hidden_channels,
+        filter_channels,
+        n_heads,
+        n_layers,
+        kernel_size,
+        p_dropout,
+        f0=True,
+    ):
+        super().__init__()
+        self.out_channels = out_channels
+        self.hidden_channels = hidden_channels
+        self.filter_channels = filter_channels
+        self.n_heads = n_heads
+        self.n_layers = n_layers
+        self.kernel_size = kernel_size
+        self.p_dropout = p_dropout
+        self.emb_phone = nn.Linear(768, hidden_channels)
+        self.lrelu = nn.LeakyReLU(0.1, inplace=True)
+        if f0 == True:
+            self.emb_pitch = nn.Embedding(256, hidden_channels)  # pitch 256
+        self.encoder = attentions.Encoder(
+            hidden_channels, filter_channels, n_heads, n_layers, kernel_size, p_dropout
+        )
+        self.proj = nn.Conv1d(hidden_channels, out_channels * 2, 1)
+
+    def forward(self, phone, pitch, lengths):
+        if pitch == None:
+            x = self.emb_phone(phone)
+        else:
+            x = self.emb_phone(phone) + self.emb_pitch(pitch)
+        x = x * math.sqrt(self.hidden_channels)  # [b, t, h]
+        x = self.lrelu(x)
+        x = torch.transpose(x, 1, -1)  # [b, h, t]
+        x_mask = torch.unsqueeze(commons.sequence_mask(lengths, x.size(2)), 1).to(
+            x.dtype
+        )
+        x = self.encoder(x * x_mask, x_mask)
+        stats = self.proj(x) * x_mask
+
+        m, logs = torch.split(stats, self.out_channels, dim=1)
+        return m, logs, x_mask
+
+
+class ResidualCouplingBlock(nn.Module):
+    def __init__(
+        self,
+        channels,
+        hidden_channels,
+        kernel_size,
+        dilation_rate,
+        n_layers,
+        n_flows=4,
+        gin_channels=0,
+    ):
+        super().__init__()
+        self.channels = channels
+        self.hidden_channels = hidden_channels
+        self.kernel_size = kernel_size
+        self.dilation_rate = dilation_rate
+        self.n_layers = n_layers
+        self.n_flows = n_flows
+        self.gin_channels = gin_channels
+
+        self.flows = nn.ModuleList()
+        for i in range(n_flows):
+            self.flows.append(
+                modules.ResidualCouplingLayer(
+                    channels,
+                    hidden_channels,
+                    kernel_size,
+                    dilation_rate,
+                    n_layers,
+                    gin_channels=gin_channels,
+                    mean_only=True,
+                )
+            )
+            self.flows.append(modules.Flip())
+
+    def forward(self, x, x_mask, g=None, reverse=False):
+        if not reverse:
+            for flow in self.flows:
+                x, _ = flow(x, x_mask, g=g, reverse=reverse)
+        else:
+            for flow in reversed(self.flows):
+                x = flow(x, x_mask, g=g, reverse=reverse)
+        return x
+
+    def remove_weight_norm(self):
+        for i in range(self.n_flows):
+            self.flows[i * 2].remove_weight_norm()
+
+
+class PosteriorEncoder(nn.Module):
+    def __init__(
+        self,
+        in_channels,
+        out_channels,
+        hidden_channels,
+        kernel_size,
+        dilation_rate,
+        n_layers,
+        gin_channels=0,
+    ):
+        super().__init__()
+        self.in_channels = in_channels
+        self.out_channels = out_channels
+        self.hidden_channels = hidden_channels
+        self.kernel_size = kernel_size
+        self.dilation_rate = dilation_rate
+        self.n_layers = n_layers
+        self.gin_channels = gin_channels
+
+        self.pre = nn.Conv1d(in_channels, hidden_channels, 1)
+        self.enc = modules.WN(
+            hidden_channels,
+            kernel_size,
+            dilation_rate,
+            n_layers,
+            gin_channels=gin_channels,
+        )
+        self.proj = nn.Conv1d(hidden_channels, out_channels * 2, 1)
+
+    def forward(self, x, x_lengths, g=None):
+        x_mask = torch.unsqueeze(commons.sequence_mask(x_lengths, x.size(2)), 1).to(
+            x.dtype
+        )
+        x = self.pre(x) * x_mask
+        x = self.enc(x, x_mask, g=g)
+        stats = self.proj(x) * x_mask
+        m, logs = torch.split(stats, self.out_channels, dim=1)
+        z = (m + torch.randn_like(m) * torch.exp(logs)) * x_mask
+        return z, m, logs, x_mask
+
+    def remove_weight_norm(self):
+        self.enc.remove_weight_norm()
+
+
+class Generator(torch.nn.Module):
+    def __init__(
+        self,
+        initial_channel,
+        resblock,
+        resblock_kernel_sizes,
+        resblock_dilation_sizes,
+        upsample_rates,
+        upsample_initial_channel,
+        upsample_kernel_sizes,
+        gin_channels=0,
+    ):
+        super(Generator, self).__init__()
+        self.num_kernels = len(resblock_kernel_sizes)
+        self.num_upsamples = len(upsample_rates)
+        self.conv_pre = Conv1d(
+            initial_channel, upsample_initial_channel, 7, 1, padding=3
+        )
+        resblock = modules.ResBlock1 if resblock == "1" else modules.ResBlock2
+
+        self.ups = nn.ModuleList()
+        for i, (u, k) in enumerate(zip(upsample_rates, upsample_kernel_sizes)):
+            self.ups.append(
+                weight_norm(
+                    ConvTranspose1d(
+                        upsample_initial_channel // (2**i),
+                        upsample_initial_channel // (2 ** (i + 1)),
+                        k,
+                        u,
+                        padding=(k - u) // 2,
+                    )
+                )
+            )
+
+        self.resblocks = nn.ModuleList()
+        for i in range(len(self.ups)):
+            ch = upsample_initial_channel // (2 ** (i + 1))
+            for j, (k, d) in enumerate(
+                zip(resblock_kernel_sizes, resblock_dilation_sizes)
+            ):
+                self.resblocks.append(resblock(ch, k, d))
+
+        self.conv_post = Conv1d(ch, 1, 7, 1, padding=3, bias=False)
+        self.ups.apply(init_weights)
+
+        if gin_channels != 0:
+            self.cond = nn.Conv1d(gin_channels, upsample_initial_channel, 1)
+
+    def forward(self, x, g=None):
+        x = self.conv_pre(x)
+        if g is not None:
+            x = x + self.cond(g)
+
+        for i in range(self.num_upsamples):
+            x = F.leaky_relu(x, modules.LRELU_SLOPE)
+            x = self.ups[i](x)
+            xs = None
+            for j in range(self.num_kernels):
+                if xs is None:
+                    xs = self.resblocks[i * self.num_kernels + j](x)
+                else:
+                    xs += self.resblocks[i * self.num_kernels + j](x)
+            x = xs / self.num_kernels
+        x = F.leaky_relu(x)
+        x = self.conv_post(x)
+        x = torch.tanh(x)
+
+        return x
+
+    def remove_weight_norm(self):
+        for l in self.ups:
+            remove_weight_norm(l)
+        for l in self.resblocks:
+            l.remove_weight_norm()
+
+
+class SineGen(torch.nn.Module):
+    """Definition of sine generator
+    SineGen(samp_rate, harmonic_num = 0,
+            sine_amp = 0.1, noise_std = 0.003,
+            voiced_threshold = 0,
+            flag_for_pulse=False)
+    samp_rate: sampling rate in Hz
+    harmonic_num: number of harmonic overtones (default 0)
+    sine_amp: amplitude of sine-wavefrom (default 0.1)
+    noise_std: std of Gaussian noise (default 0.003)
+    voiced_thoreshold: F0 threshold for U/V classification (default 0)
+    flag_for_pulse: this SinGen is used inside PulseGen (default False)
+    Note: when flag_for_pulse is True, the first time step of a voiced
+        segment is always sin(np.pi) or cos(0)
+    """
+
+    def __init__(
+        self,
+        samp_rate,
+        harmonic_num=0,
+        sine_amp=0.1,
+        noise_std=0.003,
+        voiced_threshold=0,
+        flag_for_pulse=False,
+    ):
+        super(SineGen, self).__init__()
+        self.sine_amp = sine_amp
+        self.noise_std = noise_std
+        self.harmonic_num = harmonic_num
+        self.dim = self.harmonic_num + 1
+        self.sampling_rate = samp_rate
+        self.voiced_threshold = voiced_threshold
+
+    def _f02uv(self, f0):
+        # generate uv signal
+        uv = torch.ones_like(f0)
+        uv = uv * (f0 > self.voiced_threshold)
+        return uv
+
+    def forward(self, f0, upp):
+        """sine_tensor, uv = forward(f0)
+        input F0: tensor(batchsize=1, length, dim=1)
+                  f0 for unvoiced steps should be 0
+        output sine_tensor: tensor(batchsize=1, length, dim)
+        output uv: tensor(batchsize=1, length, 1)
+        """
+        with torch.no_grad():
+            f0 = f0[:, None].transpose(1, 2)
+            f0_buf = torch.zeros(f0.shape[0], f0.shape[1], self.dim, device=f0.device)
+            # fundamental component
+            f0_buf[:, :, 0] = f0[:, :, 0]
+            for idx in np.arange(self.harmonic_num):
+                f0_buf[:, :, idx + 1] = f0_buf[:, :, 0] * (
+                    idx + 2
+                )  # idx + 2: the (idx+1)-th overtone, (idx+2)-th harmonic
+            rad_values = (f0_buf / self.sampling_rate) % 1  ###%1意味着n_har的乘积无法后处理优化
+            rand_ini = torch.rand(
+                f0_buf.shape[0], f0_buf.shape[2], device=f0_buf.device
+            )
+            rand_ini[:, 0] = 0
+            rad_values[:, 0, :] = rad_values[:, 0, :] + rand_ini
+            tmp_over_one = torch.cumsum(rad_values, 1)  # % 1  #####%1意味着后面的cumsum无法再优化
+            tmp_over_one *= upp
+            tmp_over_one = F.interpolate(
+                tmp_over_one.transpose(2, 1),
+                scale_factor=upp,
+                mode="linear",
+                align_corners=True,
+            ).transpose(2, 1)
+            rad_values = F.interpolate(
+                rad_values.transpose(2, 1), scale_factor=upp, mode="nearest"
+            ).transpose(
+                2, 1
+            )  #######
+            tmp_over_one %= 1
+            tmp_over_one_idx = (tmp_over_one[:, 1:, :] - tmp_over_one[:, :-1, :]) < 0
+            cumsum_shift = torch.zeros_like(rad_values)
+            cumsum_shift[:, 1:, :] = tmp_over_one_idx * -1.0
+            sine_waves = torch.sin(
+                torch.cumsum(rad_values + cumsum_shift, dim=1) * 2 * np.pi
+            )
+            sine_waves = sine_waves * self.sine_amp
+            uv = self._f02uv(f0)
+            uv = F.interpolate(
+                uv.transpose(2, 1), scale_factor=upp, mode="nearest"
+            ).transpose(2, 1)
+            noise_amp = uv * self.noise_std + (1 - uv) * self.sine_amp / 3
+            noise = noise_amp * torch.randn_like(sine_waves)
+            sine_waves = sine_waves * uv + noise
+        return sine_waves, uv, noise
+
+
+class SourceModuleHnNSF(torch.nn.Module):
+    """SourceModule for hn-nsf
+    SourceModule(sampling_rate, harmonic_num=0, sine_amp=0.1,
+                 add_noise_std=0.003, voiced_threshod=0)
+    sampling_rate: sampling_rate in Hz
+    harmonic_num: number of harmonic above F0 (default: 0)
+    sine_amp: amplitude of sine source signal (default: 0.1)
+    add_noise_std: std of additive Gaussian noise (default: 0.003)
+        note that amplitude of noise in unvoiced is decided
+        by sine_amp
+    voiced_threshold: threhold to set U/V given F0 (default: 0)
+    Sine_source, noise_source = SourceModuleHnNSF(F0_sampled)
+    F0_sampled (batchsize, length, 1)
+    Sine_source (batchsize, length, 1)
+    noise_source (batchsize, length 1)
+    uv (batchsize, length, 1)
+    """
+
+    def __init__(
+        self,
+        sampling_rate,
+        harmonic_num=0,
+        sine_amp=0.1,
+        add_noise_std=0.003,
+        voiced_threshod=0,
+        is_half=True,
+    ):
+        super(SourceModuleHnNSF, self).__init__()
+
+        self.sine_amp = sine_amp
+        self.noise_std = add_noise_std
+        self.is_half = is_half
+        # to produce sine waveforms
+        self.l_sin_gen = SineGen(
+            sampling_rate, harmonic_num, sine_amp, add_noise_std, voiced_threshod
+        )
+
+        # to merge source harmonics into a single excitation
+        self.l_linear = torch.nn.Linear(harmonic_num + 1, 1)
+        self.l_tanh = torch.nn.Tanh()
+
+    def forward(self, x, upp=None):
+        sine_wavs, uv, _ = self.l_sin_gen(x, upp)
+        if self.is_half:
+            sine_wavs = sine_wavs.half()
+        sine_merge = self.l_tanh(self.l_linear(sine_wavs))
+        return sine_merge, None, None  # noise, uv
+
+
+class GeneratorNSF(torch.nn.Module):
+    def __init__(
+        self,
+        initial_channel,
+        resblock,
+        resblock_kernel_sizes,
+        resblock_dilation_sizes,
+        upsample_rates,
+        upsample_initial_channel,
+        upsample_kernel_sizes,
+        gin_channels,
+        sr,
+        is_half=False,
+    ):
+        super(GeneratorNSF, self).__init__()
+        self.num_kernels = len(resblock_kernel_sizes)
+        self.num_upsamples = len(upsample_rates)
+
+        self.f0_upsamp = torch.nn.Upsample(scale_factor=np.prod(upsample_rates))
+        self.m_source = SourceModuleHnNSF(
+            sampling_rate=sr, harmonic_num=0, is_half=is_half
+        )
+        self.noise_convs = nn.ModuleList()
+        self.conv_pre = Conv1d(
+            initial_channel, upsample_initial_channel, 7, 1, padding=3
+        )
+        resblock = modules.ResBlock1 if resblock == "1" else modules.ResBlock2
+
+        self.ups = nn.ModuleList()
+        for i, (u, k) in enumerate(zip(upsample_rates, upsample_kernel_sizes)):
+            c_cur = upsample_initial_channel // (2 ** (i + 1))
+            self.ups.append(
+                weight_norm(
+                    ConvTranspose1d(
+                        upsample_initial_channel // (2**i),
+                        upsample_initial_channel // (2 ** (i + 1)),
+                        k,
+                        u,
+                        padding=(k - u) // 2,
+                    )
+                )
+            )
+            if i + 1 < len(upsample_rates):
+                stride_f0 = np.prod(upsample_rates[i + 1 :])
+                self.noise_convs.append(
+                    Conv1d(
+                        1,
+                        c_cur,
+                        kernel_size=stride_f0 * 2,
+                        stride=stride_f0,
+                        padding=stride_f0 // 2,
+                    )
+                )
+            else:
+                self.noise_convs.append(Conv1d(1, c_cur, kernel_size=1))
+
+        self.resblocks = nn.ModuleList()
+        for i in range(len(self.ups)):
+            ch = upsample_initial_channel // (2 ** (i + 1))
+            for j, (k, d) in enumerate(
+                zip(resblock_kernel_sizes, resblock_dilation_sizes)
+            ):
+                self.resblocks.append(resblock(ch, k, d))
+
+        self.conv_post = Conv1d(ch, 1, 7, 1, padding=3, bias=False)
+        self.ups.apply(init_weights)
+
+        if gin_channels != 0:
+            self.cond = nn.Conv1d(gin_channels, upsample_initial_channel, 1)
+
+        self.upp = np.prod(upsample_rates)
+
+    def forward(self, x, f0, g=None):
+        har_source, noi_source, uv = self.m_source(f0, self.upp)
+        har_source = har_source.transpose(1, 2)
+        x = self.conv_pre(x)
+        if g is not None:
+            x = x + self.cond(g)
+
+        for i in range(self.num_upsamples):
+            x = F.leaky_relu(x, modules.LRELU_SLOPE)
+            x = self.ups[i](x)
+            x_source = self.noise_convs[i](har_source)
+            x = x + x_source
+            xs = None
+            for j in range(self.num_kernels):
+                if xs is None:
+                    xs = self.resblocks[i * self.num_kernels + j](x)
+                else:
+                    xs += self.resblocks[i * self.num_kernels + j](x)
+            x = xs / self.num_kernels
+        x = F.leaky_relu(x)
+        x = self.conv_post(x)
+        x = torch.tanh(x)
+        return x
+
+    def remove_weight_norm(self):
+        for l in self.ups:
+            remove_weight_norm(l)
+        for l in self.resblocks:
+            l.remove_weight_norm()
+
+
+sr2sr = {
+    "32k": 32000,
+    "40k": 40000,
+    "48k": 48000,
+}
+
+
+class SynthesizerTrnMsNSFsidM(nn.Module):
+    def __init__(
+        self,
+        spec_channels,
+        segment_size,
+        inter_channels,
+        hidden_channels,
+        filter_channels,
+        n_heads,
+        n_layers,
+        kernel_size,
+        p_dropout,
+        resblock,
+        resblock_kernel_sizes,
+        resblock_dilation_sizes,
+        upsample_rates,
+        upsample_initial_channel,
+        upsample_kernel_sizes,
+        spk_embed_dim,
+        gin_channels,
+        sr,
+        version,
+        **kwargs
+    ):
+        super().__init__()
+        if type(sr) == type("strr"):
+            sr = sr2sr[sr]
+        self.spec_channels = spec_channels
+        self.inter_channels = inter_channels
+        self.hidden_channels = hidden_channels
+        self.filter_channels = filter_channels
+        self.n_heads = n_heads
+        self.n_layers = n_layers
+        self.kernel_size = kernel_size
+        self.p_dropout = p_dropout
+        self.resblock = resblock
+        self.resblock_kernel_sizes = resblock_kernel_sizes
+        self.resblock_dilation_sizes = resblock_dilation_sizes
+        self.upsample_rates = upsample_rates
+        self.upsample_initial_channel = upsample_initial_channel
+        self.upsample_kernel_sizes = upsample_kernel_sizes
+        self.segment_size = segment_size
+        self.gin_channels = gin_channels
+        # self.hop_length = hop_length#
+        self.spk_embed_dim = spk_embed_dim
+        if version == "v1":
+            self.enc_p = TextEncoder256(
+                inter_channels,
+                hidden_channels,
+                filter_channels,
+                n_heads,
+                n_layers,
+                kernel_size,
+                p_dropout,
+            )
+        else:
+            self.enc_p = TextEncoder768(
+                inter_channels,
+                hidden_channels,
+                filter_channels,
+                n_heads,
+                n_layers,
+                kernel_size,
+                p_dropout,
+            )
+        self.dec = GeneratorNSF(
+            inter_channels,
+            resblock,
+            resblock_kernel_sizes,
+            resblock_dilation_sizes,
+            upsample_rates,
+            upsample_initial_channel,
+            upsample_kernel_sizes,
+            gin_channels=gin_channels,
+            sr=sr,
+            is_half=kwargs["is_half"],
+        )
+        self.enc_q = PosteriorEncoder(
+            spec_channels,
+            inter_channels,
+            hidden_channels,
+            5,
+            1,
+            16,
+            gin_channels=gin_channels,
+        )
+        self.flow = ResidualCouplingBlock(
+            inter_channels, hidden_channels, 5, 1, 3, gin_channels=gin_channels
+        )
+        self.emb_g = nn.Embedding(self.spk_embed_dim, gin_channels)
+        self.speaker_map = None
+        print("gin_channels:", gin_channels, "self.spk_embed_dim:", self.spk_embed_dim)
+
+    def remove_weight_norm(self):
+        self.dec.remove_weight_norm()
+        self.flow.remove_weight_norm()
+        self.enc_q.remove_weight_norm()
+
+    def construct_spkmixmap(self, n_speaker):
+        self.speaker_map = torch.zeros((n_speaker, 1, 1, self.gin_channels))
+        for i in range(n_speaker):
+            self.speaker_map[i] = self.emb_g(torch.LongTensor([[i]]))
+        self.speaker_map = self.speaker_map.unsqueeze(0)
+
+    def forward(self, phone, phone_lengths, pitch, nsff0, g, rnd, max_len=None):
+        if self.speaker_map is not None:  # [N, S]  *  [S, B, 1, H]
+            g = g.reshape((g.shape[0], g.shape[1], 1, 1, 1))  # [N, S, B, 1, 1]
+            g = g * self.speaker_map  # [N, S, B, 1, H]
+            g = torch.sum(g, dim=1)  # [N, 1, B, 1, H]
+            g = g.transpose(0, -1).transpose(0, -2).squeeze(0)  # [B, H, N]
+        else:
+            g = g.unsqueeze(0)
+            g = self.emb_g(g).transpose(1, 2)
+
+        m_p, logs_p, x_mask = self.enc_p(phone, pitch, phone_lengths)
+        z_p = (m_p + torch.exp(logs_p) * rnd) * x_mask
+        z = self.flow(z_p, x_mask, g=g, reverse=True)
+        o = self.dec((z * x_mask)[:, :, :max_len], nsff0, g=g)
+        return o
+
+
+class MultiPeriodDiscriminator(torch.nn.Module):
+    def __init__(self, use_spectral_norm=False):
+        super(MultiPeriodDiscriminator, self).__init__()
+        periods = [2, 3, 5, 7, 11, 17]
+        # periods = [3, 5, 7, 11, 17, 23, 37]
+
+        discs = [DiscriminatorS(use_spectral_norm=use_spectral_norm)]
+        discs = discs + [
+            DiscriminatorP(i, use_spectral_norm=use_spectral_norm) for i in periods
+        ]
+        self.discriminators = nn.ModuleList(discs)
+
+    def forward(self, y, y_hat):
+        y_d_rs = []  #
+        y_d_gs = []
+        fmap_rs = []
+        fmap_gs = []
+        for i, d in enumerate(self.discriminators):
+            y_d_r, fmap_r = d(y)
+            y_d_g, fmap_g = d(y_hat)
+            # for j in range(len(fmap_r)):
+            #     print(i,j,y.shape,y_hat.shape,fmap_r[j].shape,fmap_g[j].shape)
+            y_d_rs.append(y_d_r)
+            y_d_gs.append(y_d_g)
+            fmap_rs.append(fmap_r)
+            fmap_gs.append(fmap_g)
+
+        return y_d_rs, y_d_gs, fmap_rs, fmap_gs
+
+
+class MultiPeriodDiscriminatorV2(torch.nn.Module):
+    def __init__(self, use_spectral_norm=False):
+        super(MultiPeriodDiscriminatorV2, self).__init__()
+        # periods = [2, 3, 5, 7, 11, 17]
+        periods = [2, 3, 5, 7, 11, 17, 23, 37]
+
+        discs = [DiscriminatorS(use_spectral_norm=use_spectral_norm)]
+        discs = discs + [
+            DiscriminatorP(i, use_spectral_norm=use_spectral_norm) for i in periods
+        ]
+        self.discriminators = nn.ModuleList(discs)
+
+    def forward(self, y, y_hat):
+        y_d_rs = []  #
+        y_d_gs = []
+        fmap_rs = []
+        fmap_gs = []
+        for i, d in enumerate(self.discriminators):
+            y_d_r, fmap_r = d(y)
+            y_d_g, fmap_g = d(y_hat)
+            # for j in range(len(fmap_r)):
+            #     print(i,j,y.shape,y_hat.shape,fmap_r[j].shape,fmap_g[j].shape)
+            y_d_rs.append(y_d_r)
+            y_d_gs.append(y_d_g)
+            fmap_rs.append(fmap_r)
+            fmap_gs.append(fmap_g)
+
+        return y_d_rs, y_d_gs, fmap_rs, fmap_gs
+
+
+class DiscriminatorS(torch.nn.Module):
+    def __init__(self, use_spectral_norm=False):
+        super(DiscriminatorS, self).__init__()
+        norm_f = weight_norm if use_spectral_norm == False else spectral_norm
+        self.convs = nn.ModuleList(
+            [
+                norm_f(Conv1d(1, 16, 15, 1, padding=7)),
+                norm_f(Conv1d(16, 64, 41, 4, groups=4, padding=20)),
+                norm_f(Conv1d(64, 256, 41, 4, groups=16, padding=20)),
+                norm_f(Conv1d(256, 1024, 41, 4, groups=64, padding=20)),
+                norm_f(Conv1d(1024, 1024, 41, 4, groups=256, padding=20)),
+                norm_f(Conv1d(1024, 1024, 5, 1, padding=2)),
+            ]
+        )
+        self.conv_post = norm_f(Conv1d(1024, 1, 3, 1, padding=1))
+
+    def forward(self, x):
+        fmap = []
+
+        for l in self.convs:
+            x = l(x)
+            x = F.leaky_relu(x, modules.LRELU_SLOPE)
+            fmap.append(x)
+        x = self.conv_post(x)
+        fmap.append(x)
+        x = torch.flatten(x, 1, -1)
+
+        return x, fmap
+
+
+class DiscriminatorP(torch.nn.Module):
+    def __init__(self, period, kernel_size=5, stride=3, use_spectral_norm=False):
+        super(DiscriminatorP, self).__init__()
+        self.period = period
+        self.use_spectral_norm = use_spectral_norm
+        norm_f = weight_norm if use_spectral_norm == False else spectral_norm
+        self.convs = nn.ModuleList(
+            [
+                norm_f(
+                    Conv2d(
+                        1,
+                        32,
+                        (kernel_size, 1),
+                        (stride, 1),
+                        padding=(get_padding(kernel_size, 1), 0),
+                    )
+                ),
+                norm_f(
+                    Conv2d(
+                        32,
+                        128,
+                        (kernel_size, 1),
+                        (stride, 1),
+                        padding=(get_padding(kernel_size, 1), 0),
+                    )
+                ),
+                norm_f(
+                    Conv2d(
+                        128,
+                        512,
+                        (kernel_size, 1),
+                        (stride, 1),
+                        padding=(get_padding(kernel_size, 1), 0),
+                    )
+                ),
+                norm_f(
+                    Conv2d(
+                        512,
+                        1024,
+                        (kernel_size, 1),
+                        (stride, 1),
+                        padding=(get_padding(kernel_size, 1), 0),
+                    )
+                ),
+                norm_f(
+                    Conv2d(
+                        1024,
+                        1024,
+                        (kernel_size, 1),
+                        1,
+                        padding=(get_padding(kernel_size, 1), 0),
+                    )
+                ),
+            ]
+        )
+        self.conv_post = norm_f(Conv2d(1024, 1, (3, 1), 1, padding=(1, 0)))
+
+    def forward(self, x):
+        fmap = []
+
+        # 1d to 2d
+        b, c, t = x.shape
+        if t % self.period != 0:  # pad first
+            n_pad = self.period - (t % self.period)
+            x = F.pad(x, (0, n_pad), "reflect")
+            t = t + n_pad
+        x = x.view(b, c, t // self.period, self.period)
+
+        for l in self.convs:
+            x = l(x)
+            x = F.leaky_relu(x, modules.LRELU_SLOPE)
+            fmap.append(x)
+        x = self.conv_post(x)
+        fmap.append(x)
+        x = torch.flatten(x, 1, -1)
+
+        return x, fmap
diff --git a/lib/infer_pack/modules.py b/lib/infer_pack/modules.py
new file mode 100644
index 0000000000000000000000000000000000000000..c83289df7c79a4810dacd15c050148544ba0b6a9
--- /dev/null
+++ b/lib/infer_pack/modules.py
@@ -0,0 +1,522 @@
+import copy
+import math
+import numpy as np
+import scipy
+import torch
+from torch import nn
+from torch.nn import functional as F
+
+from torch.nn import Conv1d, ConvTranspose1d, AvgPool1d, Conv2d
+from torch.nn.utils import weight_norm, remove_weight_norm
+
+from lib.infer_pack import commons
+from lib.infer_pack.commons import init_weights, get_padding
+from lib.infer_pack.transforms import piecewise_rational_quadratic_transform
+
+
+LRELU_SLOPE = 0.1
+
+
+class LayerNorm(nn.Module):
+    def __init__(self, channels, eps=1e-5):
+        super().__init__()
+        self.channels = channels
+        self.eps = eps
+
+        self.gamma = nn.Parameter(torch.ones(channels))
+        self.beta = nn.Parameter(torch.zeros(channels))
+
+    def forward(self, x):
+        x = x.transpose(1, -1)
+        x = F.layer_norm(x, (self.channels,), self.gamma, self.beta, self.eps)
+        return x.transpose(1, -1)
+
+
+class ConvReluNorm(nn.Module):
+    def __init__(
+        self,
+        in_channels,
+        hidden_channels,
+        out_channels,
+        kernel_size,
+        n_layers,
+        p_dropout,
+    ):
+        super().__init__()
+        self.in_channels = in_channels
+        self.hidden_channels = hidden_channels
+        self.out_channels = out_channels
+        self.kernel_size = kernel_size
+        self.n_layers = n_layers
+        self.p_dropout = p_dropout
+        assert n_layers > 1, "Number of layers should be larger than 0."
+
+        self.conv_layers = nn.ModuleList()
+        self.norm_layers = nn.ModuleList()
+        self.conv_layers.append(
+            nn.Conv1d(
+                in_channels, hidden_channels, kernel_size, padding=kernel_size // 2
+            )
+        )
+        self.norm_layers.append(LayerNorm(hidden_channels))
+        self.relu_drop = nn.Sequential(nn.ReLU(), nn.Dropout(p_dropout))
+        for _ in range(n_layers - 1):
+            self.conv_layers.append(
+                nn.Conv1d(
+                    hidden_channels,
+                    hidden_channels,
+                    kernel_size,
+                    padding=kernel_size // 2,
+                )
+            )
+            self.norm_layers.append(LayerNorm(hidden_channels))
+        self.proj = nn.Conv1d(hidden_channels, out_channels, 1)
+        self.proj.weight.data.zero_()
+        self.proj.bias.data.zero_()
+
+    def forward(self, x, x_mask):
+        x_org = x
+        for i in range(self.n_layers):
+            x = self.conv_layers[i](x * x_mask)
+            x = self.norm_layers[i](x)
+            x = self.relu_drop(x)
+        x = x_org + self.proj(x)
+        return x * x_mask
+
+
+class DDSConv(nn.Module):
+    """
+    Dialted and Depth-Separable Convolution
+    """
+
+    def __init__(self, channels, kernel_size, n_layers, p_dropout=0.0):
+        super().__init__()
+        self.channels = channels
+        self.kernel_size = kernel_size
+        self.n_layers = n_layers
+        self.p_dropout = p_dropout
+
+        self.drop = nn.Dropout(p_dropout)
+        self.convs_sep = nn.ModuleList()
+        self.convs_1x1 = nn.ModuleList()
+        self.norms_1 = nn.ModuleList()
+        self.norms_2 = nn.ModuleList()
+        for i in range(n_layers):
+            dilation = kernel_size**i
+            padding = (kernel_size * dilation - dilation) // 2
+            self.convs_sep.append(
+                nn.Conv1d(
+                    channels,
+                    channels,
+                    kernel_size,
+                    groups=channels,
+                    dilation=dilation,
+                    padding=padding,
+                )
+            )
+            self.convs_1x1.append(nn.Conv1d(channels, channels, 1))
+            self.norms_1.append(LayerNorm(channels))
+            self.norms_2.append(LayerNorm(channels))
+
+    def forward(self, x, x_mask, g=None):
+        if g is not None:
+            x = x + g
+        for i in range(self.n_layers):
+            y = self.convs_sep[i](x * x_mask)
+            y = self.norms_1[i](y)
+            y = F.gelu(y)
+            y = self.convs_1x1[i](y)
+            y = self.norms_2[i](y)
+            y = F.gelu(y)
+            y = self.drop(y)
+            x = x + y
+        return x * x_mask
+
+
+class WN(torch.nn.Module):
+    def __init__(
+        self,
+        hidden_channels,
+        kernel_size,
+        dilation_rate,
+        n_layers,
+        gin_channels=0,
+        p_dropout=0,
+    ):
+        super(WN, self).__init__()
+        assert kernel_size % 2 == 1
+        self.hidden_channels = hidden_channels
+        self.kernel_size = (kernel_size,)
+        self.dilation_rate = dilation_rate
+        self.n_layers = n_layers
+        self.gin_channels = gin_channels
+        self.p_dropout = p_dropout
+
+        self.in_layers = torch.nn.ModuleList()
+        self.res_skip_layers = torch.nn.ModuleList()
+        self.drop = nn.Dropout(p_dropout)
+
+        if gin_channels != 0:
+            cond_layer = torch.nn.Conv1d(
+                gin_channels, 2 * hidden_channels * n_layers, 1
+            )
+            self.cond_layer = torch.nn.utils.weight_norm(cond_layer, name="weight")
+
+        for i in range(n_layers):
+            dilation = dilation_rate**i
+            padding = int((kernel_size * dilation - dilation) / 2)
+            in_layer = torch.nn.Conv1d(
+                hidden_channels,
+                2 * hidden_channels,
+                kernel_size,
+                dilation=dilation,
+                padding=padding,
+            )
+            in_layer = torch.nn.utils.weight_norm(in_layer, name="weight")
+            self.in_layers.append(in_layer)
+
+            # last one is not necessary
+            if i < n_layers - 1:
+                res_skip_channels = 2 * hidden_channels
+            else:
+                res_skip_channels = hidden_channels
+
+            res_skip_layer = torch.nn.Conv1d(hidden_channels, res_skip_channels, 1)
+            res_skip_layer = torch.nn.utils.weight_norm(res_skip_layer, name="weight")
+            self.res_skip_layers.append(res_skip_layer)
+
+    def forward(self, x, x_mask, g=None, **kwargs):
+        output = torch.zeros_like(x)
+        n_channels_tensor = torch.IntTensor([self.hidden_channels])
+
+        if g is not None:
+            g = self.cond_layer(g)
+
+        for i in range(self.n_layers):
+            x_in = self.in_layers[i](x)
+            if g is not None:
+                cond_offset = i * 2 * self.hidden_channels
+                g_l = g[:, cond_offset : cond_offset + 2 * self.hidden_channels, :]
+            else:
+                g_l = torch.zeros_like(x_in)
+
+            acts = commons.fused_add_tanh_sigmoid_multiply(x_in, g_l, n_channels_tensor)
+            acts = self.drop(acts)
+
+            res_skip_acts = self.res_skip_layers[i](acts)
+            if i < self.n_layers - 1:
+                res_acts = res_skip_acts[:, : self.hidden_channels, :]
+                x = (x + res_acts) * x_mask
+                output = output + res_skip_acts[:, self.hidden_channels :, :]
+            else:
+                output = output + res_skip_acts
+        return output * x_mask
+
+    def remove_weight_norm(self):
+        if self.gin_channels != 0:
+            torch.nn.utils.remove_weight_norm(self.cond_layer)
+        for l in self.in_layers:
+            torch.nn.utils.remove_weight_norm(l)
+        for l in self.res_skip_layers:
+            torch.nn.utils.remove_weight_norm(l)
+
+
+class ResBlock1(torch.nn.Module):
+    def __init__(self, channels, kernel_size=3, dilation=(1, 3, 5)):
+        super(ResBlock1, self).__init__()
+        self.convs1 = nn.ModuleList(
+            [
+                weight_norm(
+                    Conv1d(
+                        channels,
+                        channels,
+                        kernel_size,
+                        1,
+                        dilation=dilation[0],
+                        padding=get_padding(kernel_size, dilation[0]),
+                    )
+                ),
+                weight_norm(
+                    Conv1d(
+                        channels,
+                        channels,
+                        kernel_size,
+                        1,
+                        dilation=dilation[1],
+                        padding=get_padding(kernel_size, dilation[1]),
+                    )
+                ),
+                weight_norm(
+                    Conv1d(
+                        channels,
+                        channels,
+                        kernel_size,
+                        1,
+                        dilation=dilation[2],
+                        padding=get_padding(kernel_size, dilation[2]),
+                    )
+                ),
+            ]
+        )
+        self.convs1.apply(init_weights)
+
+        self.convs2 = nn.ModuleList(
+            [
+                weight_norm(
+                    Conv1d(
+                        channels,
+                        channels,
+                        kernel_size,
+                        1,
+                        dilation=1,
+                        padding=get_padding(kernel_size, 1),
+                    )
+                ),
+                weight_norm(
+                    Conv1d(
+                        channels,
+                        channels,
+                        kernel_size,
+                        1,
+                        dilation=1,
+                        padding=get_padding(kernel_size, 1),
+                    )
+                ),
+                weight_norm(
+                    Conv1d(
+                        channels,
+                        channels,
+                        kernel_size,
+                        1,
+                        dilation=1,
+                        padding=get_padding(kernel_size, 1),
+                    )
+                ),
+            ]
+        )
+        self.convs2.apply(init_weights)
+
+    def forward(self, x, x_mask=None):
+        for c1, c2 in zip(self.convs1, self.convs2):
+            xt = F.leaky_relu(x, LRELU_SLOPE)
+            if x_mask is not None:
+                xt = xt * x_mask
+            xt = c1(xt)
+            xt = F.leaky_relu(xt, LRELU_SLOPE)
+            if x_mask is not None:
+                xt = xt * x_mask
+            xt = c2(xt)
+            x = xt + x
+        if x_mask is not None:
+            x = x * x_mask
+        return x
+
+    def remove_weight_norm(self):
+        for l in self.convs1:
+            remove_weight_norm(l)
+        for l in self.convs2:
+            remove_weight_norm(l)
+
+
+class ResBlock2(torch.nn.Module):
+    def __init__(self, channels, kernel_size=3, dilation=(1, 3)):
+        super(ResBlock2, self).__init__()
+        self.convs = nn.ModuleList(
+            [
+                weight_norm(
+                    Conv1d(
+                        channels,
+                        channels,
+                        kernel_size,
+                        1,
+                        dilation=dilation[0],
+                        padding=get_padding(kernel_size, dilation[0]),
+                    )
+                ),
+                weight_norm(
+                    Conv1d(
+                        channels,
+                        channels,
+                        kernel_size,
+                        1,
+                        dilation=dilation[1],
+                        padding=get_padding(kernel_size, dilation[1]),
+                    )
+                ),
+            ]
+        )
+        self.convs.apply(init_weights)
+
+    def forward(self, x, x_mask=None):
+        for c in self.convs:
+            xt = F.leaky_relu(x, LRELU_SLOPE)
+            if x_mask is not None:
+                xt = xt * x_mask
+            xt = c(xt)
+            x = xt + x
+        if x_mask is not None:
+            x = x * x_mask
+        return x
+
+    def remove_weight_norm(self):
+        for l in self.convs:
+            remove_weight_norm(l)
+
+
+class Log(nn.Module):
+    def forward(self, x, x_mask, reverse=False, **kwargs):
+        if not reverse:
+            y = torch.log(torch.clamp_min(x, 1e-5)) * x_mask
+            logdet = torch.sum(-y, [1, 2])
+            return y, logdet
+        else:
+            x = torch.exp(x) * x_mask
+            return x
+
+
+class Flip(nn.Module):
+    def forward(self, x, *args, reverse=False, **kwargs):
+        x = torch.flip(x, [1])
+        if not reverse:
+            logdet = torch.zeros(x.size(0)).to(dtype=x.dtype, device=x.device)
+            return x, logdet
+        else:
+            return x
+
+
+class ElementwiseAffine(nn.Module):
+    def __init__(self, channels):
+        super().__init__()
+        self.channels = channels
+        self.m = nn.Parameter(torch.zeros(channels, 1))
+        self.logs = nn.Parameter(torch.zeros(channels, 1))
+
+    def forward(self, x, x_mask, reverse=False, **kwargs):
+        if not reverse:
+            y = self.m + torch.exp(self.logs) * x
+            y = y * x_mask
+            logdet = torch.sum(self.logs * x_mask, [1, 2])
+            return y, logdet
+        else:
+            x = (x - self.m) * torch.exp(-self.logs) * x_mask
+            return x
+
+
+class ResidualCouplingLayer(nn.Module):
+    def __init__(
+        self,
+        channels,
+        hidden_channels,
+        kernel_size,
+        dilation_rate,
+        n_layers,
+        p_dropout=0,
+        gin_channels=0,
+        mean_only=False,
+    ):
+        assert channels % 2 == 0, "channels should be divisible by 2"
+        super().__init__()
+        self.channels = channels
+        self.hidden_channels = hidden_channels
+        self.kernel_size = kernel_size
+        self.dilation_rate = dilation_rate
+        self.n_layers = n_layers
+        self.half_channels = channels // 2
+        self.mean_only = mean_only
+
+        self.pre = nn.Conv1d(self.half_channels, hidden_channels, 1)
+        self.enc = WN(
+            hidden_channels,
+            kernel_size,
+            dilation_rate,
+            n_layers,
+            p_dropout=p_dropout,
+            gin_channels=gin_channels,
+        )
+        self.post = nn.Conv1d(hidden_channels, self.half_channels * (2 - mean_only), 1)
+        self.post.weight.data.zero_()
+        self.post.bias.data.zero_()
+
+    def forward(self, x, x_mask, g=None, reverse=False):
+        x0, x1 = torch.split(x, [self.half_channels] * 2, 1)
+        h = self.pre(x0) * x_mask
+        h = self.enc(h, x_mask, g=g)
+        stats = self.post(h) * x_mask
+        if not self.mean_only:
+            m, logs = torch.split(stats, [self.half_channels] * 2, 1)
+        else:
+            m = stats
+            logs = torch.zeros_like(m)
+
+        if not reverse:
+            x1 = m + x1 * torch.exp(logs) * x_mask
+            x = torch.cat([x0, x1], 1)
+            logdet = torch.sum(logs, [1, 2])
+            return x, logdet
+        else:
+            x1 = (x1 - m) * torch.exp(-logs) * x_mask
+            x = torch.cat([x0, x1], 1)
+            return x
+
+    def remove_weight_norm(self):
+        self.enc.remove_weight_norm()
+
+
+class ConvFlow(nn.Module):
+    def __init__(
+        self,
+        in_channels,
+        filter_channels,
+        kernel_size,
+        n_layers,
+        num_bins=10,
+        tail_bound=5.0,
+    ):
+        super().__init__()
+        self.in_channels = in_channels
+        self.filter_channels = filter_channels
+        self.kernel_size = kernel_size
+        self.n_layers = n_layers
+        self.num_bins = num_bins
+        self.tail_bound = tail_bound
+        self.half_channels = in_channels // 2
+
+        self.pre = nn.Conv1d(self.half_channels, filter_channels, 1)
+        self.convs = DDSConv(filter_channels, kernel_size, n_layers, p_dropout=0.0)
+        self.proj = nn.Conv1d(
+            filter_channels, self.half_channels * (num_bins * 3 - 1), 1
+        )
+        self.proj.weight.data.zero_()
+        self.proj.bias.data.zero_()
+
+    def forward(self, x, x_mask, g=None, reverse=False):
+        x0, x1 = torch.split(x, [self.half_channels] * 2, 1)
+        h = self.pre(x0)
+        h = self.convs(h, x_mask, g=g)
+        h = self.proj(h) * x_mask
+
+        b, c, t = x0.shape
+        h = h.reshape(b, c, -1, t).permute(0, 1, 3, 2)  # [b, cx?, t] -> [b, c, t, ?]
+
+        unnormalized_widths = h[..., : self.num_bins] / math.sqrt(self.filter_channels)
+        unnormalized_heights = h[..., self.num_bins : 2 * self.num_bins] / math.sqrt(
+            self.filter_channels
+        )
+        unnormalized_derivatives = h[..., 2 * self.num_bins :]
+
+        x1, logabsdet = piecewise_rational_quadratic_transform(
+            x1,
+            unnormalized_widths,
+            unnormalized_heights,
+            unnormalized_derivatives,
+            inverse=reverse,
+            tails="linear",
+            tail_bound=self.tail_bound,
+        )
+
+        x = torch.cat([x0, x1], 1) * x_mask
+        logdet = torch.sum(logabsdet * x_mask, [1, 2])
+        if not reverse:
+            return x, logdet
+        else:
+            return x
diff --git a/lib/infer_pack/modules/F0Predictor/DioF0Predictor.py b/lib/infer_pack/modules/F0Predictor/DioF0Predictor.py
new file mode 100644
index 0000000000000000000000000000000000000000..ee3171bcb7c4a5066560723108b56e055f18be45
--- /dev/null
+++ b/lib/infer_pack/modules/F0Predictor/DioF0Predictor.py
@@ -0,0 +1,90 @@
+from lib.infer_pack.modules.F0Predictor.F0Predictor import F0Predictor
+import pyworld
+import numpy as np
+
+
+class DioF0Predictor(F0Predictor):
+    def __init__(self, hop_length=512, f0_min=50, f0_max=1100, sampling_rate=44100):
+        self.hop_length = hop_length
+        self.f0_min = f0_min
+        self.f0_max = f0_max
+        self.sampling_rate = sampling_rate
+
+    def interpolate_f0(self, f0):
+        """
+        对F0进行插值处理
+        """
+
+        data = np.reshape(f0, (f0.size, 1))
+
+        vuv_vector = np.zeros((data.size, 1), dtype=np.float32)
+        vuv_vector[data > 0.0] = 1.0
+        vuv_vector[data <= 0.0] = 0.0
+
+        ip_data = data
+
+        frame_number = data.size
+        last_value = 0.0
+        for i in range(frame_number):
+            if data[i] <= 0.0:
+                j = i + 1
+                for j in range(i + 1, frame_number):
+                    if data[j] > 0.0:
+                        break
+                if j < frame_number - 1:
+                    if last_value > 0.0:
+                        step = (data[j] - data[i - 1]) / float(j - i)
+                        for k in range(i, j):
+                            ip_data[k] = data[i - 1] + step * (k - i + 1)
+                    else:
+                        for k in range(i, j):
+                            ip_data[k] = data[j]
+                else:
+                    for k in range(i, frame_number):
+                        ip_data[k] = last_value
+            else:
+                ip_data[i] = data[i]  # 这里可能存在一个没有必要的拷贝
+                last_value = data[i]
+
+        return ip_data[:, 0], vuv_vector[:, 0]
+
+    def resize_f0(self, x, target_len):
+        source = np.array(x)
+        source[source < 0.001] = np.nan
+        target = np.interp(
+            np.arange(0, len(source) * target_len, len(source)) / target_len,
+            np.arange(0, len(source)),
+            source,
+        )
+        res = np.nan_to_num(target)
+        return res
+
+    def compute_f0(self, wav, p_len=None):
+        if p_len is None:
+            p_len = wav.shape[0] // self.hop_length
+        f0, t = pyworld.dio(
+            wav.astype(np.double),
+            fs=self.sampling_rate,
+            f0_floor=self.f0_min,
+            f0_ceil=self.f0_max,
+            frame_period=1000 * self.hop_length / self.sampling_rate,
+        )
+        f0 = pyworld.stonemask(wav.astype(np.double), f0, t, self.sampling_rate)
+        for index, pitch in enumerate(f0):
+            f0[index] = round(pitch, 1)
+        return self.interpolate_f0(self.resize_f0(f0, p_len))[0]
+
+    def compute_f0_uv(self, wav, p_len=None):
+        if p_len is None:
+            p_len = wav.shape[0] // self.hop_length
+        f0, t = pyworld.dio(
+            wav.astype(np.double),
+            fs=self.sampling_rate,
+            f0_floor=self.f0_min,
+            f0_ceil=self.f0_max,
+            frame_period=1000 * self.hop_length / self.sampling_rate,
+        )
+        f0 = pyworld.stonemask(wav.astype(np.double), f0, t, self.sampling_rate)
+        for index, pitch in enumerate(f0):
+            f0[index] = round(pitch, 1)
+        return self.interpolate_f0(self.resize_f0(f0, p_len))
diff --git a/lib/infer_pack/modules/F0Predictor/F0Predictor.py b/lib/infer_pack/modules/F0Predictor/F0Predictor.py
new file mode 100644
index 0000000000000000000000000000000000000000..f56e49e7f0e6eab3babf0711cae2933371b9f9cc
--- /dev/null
+++ b/lib/infer_pack/modules/F0Predictor/F0Predictor.py
@@ -0,0 +1,16 @@
+class F0Predictor(object):
+    def compute_f0(self, wav, p_len):
+        """
+        input: wav:[signal_length]
+               p_len:int
+        output: f0:[signal_length//hop_length]
+        """
+        pass
+
+    def compute_f0_uv(self, wav, p_len):
+        """
+        input: wav:[signal_length]
+               p_len:int
+        output: f0:[signal_length//hop_length],uv:[signal_length//hop_length]
+        """
+        pass
diff --git a/lib/infer_pack/modules/F0Predictor/HarvestF0Predictor.py b/lib/infer_pack/modules/F0Predictor/HarvestF0Predictor.py
new file mode 100644
index 0000000000000000000000000000000000000000..b412ba2814e114ca7bb00b6fd6ef217f63d788a3
--- /dev/null
+++ b/lib/infer_pack/modules/F0Predictor/HarvestF0Predictor.py
@@ -0,0 +1,86 @@
+from lib.infer_pack.modules.F0Predictor.F0Predictor import F0Predictor
+import pyworld
+import numpy as np
+
+
+class HarvestF0Predictor(F0Predictor):
+    def __init__(self, hop_length=512, f0_min=50, f0_max=1100, sampling_rate=44100):
+        self.hop_length = hop_length
+        self.f0_min = f0_min
+        self.f0_max = f0_max
+        self.sampling_rate = sampling_rate
+
+    def interpolate_f0(self, f0):
+        """
+        对F0进行插值处理
+        """
+
+        data = np.reshape(f0, (f0.size, 1))
+
+        vuv_vector = np.zeros((data.size, 1), dtype=np.float32)
+        vuv_vector[data > 0.0] = 1.0
+        vuv_vector[data <= 0.0] = 0.0
+
+        ip_data = data
+
+        frame_number = data.size
+        last_value = 0.0
+        for i in range(frame_number):
+            if data[i] <= 0.0:
+                j = i + 1
+                for j in range(i + 1, frame_number):
+                    if data[j] > 0.0:
+                        break
+                if j < frame_number - 1:
+                    if last_value > 0.0:
+                        step = (data[j] - data[i - 1]) / float(j - i)
+                        for k in range(i, j):
+                            ip_data[k] = data[i - 1] + step * (k - i + 1)
+                    else:
+                        for k in range(i, j):
+                            ip_data[k] = data[j]
+                else:
+                    for k in range(i, frame_number):
+                        ip_data[k] = last_value
+            else:
+                ip_data[i] = data[i]  # 这里可能存在一个没有必要的拷贝
+                last_value = data[i]
+
+        return ip_data[:, 0], vuv_vector[:, 0]
+
+    def resize_f0(self, x, target_len):
+        source = np.array(x)
+        source[source < 0.001] = np.nan
+        target = np.interp(
+            np.arange(0, len(source) * target_len, len(source)) / target_len,
+            np.arange(0, len(source)),
+            source,
+        )
+        res = np.nan_to_num(target)
+        return res
+
+    def compute_f0(self, wav, p_len=None):
+        if p_len is None:
+            p_len = wav.shape[0] // self.hop_length
+        f0, t = pyworld.harvest(
+            wav.astype(np.double),
+            fs=self.hop_length,
+            f0_ceil=self.f0_max,
+            f0_floor=self.f0_min,
+            frame_period=1000 * self.hop_length / self.sampling_rate,
+        )
+        f0 = pyworld.stonemask(wav.astype(np.double), f0, t, self.fs)
+        return self.interpolate_f0(self.resize_f0(f0, p_len))[0]
+
+    def compute_f0_uv(self, wav, p_len=None):
+        if p_len is None:
+            p_len = wav.shape[0] // self.hop_length
+        f0, t = pyworld.harvest(
+            wav.astype(np.double),
+            fs=self.sampling_rate,
+            f0_floor=self.f0_min,
+            f0_ceil=self.f0_max,
+            frame_period=1000 * self.hop_length / self.sampling_rate,
+        )
+        f0 = pyworld.stonemask(wav.astype(np.double), f0, t, self.sampling_rate)
+        return self.interpolate_f0(self.resize_f0(f0, p_len))
diff --git a/lib/infer_pack/modules/F0Predictor/PMF0Predictor.py b/lib/infer_pack/modules/F0Predictor/PMF0Predictor.py
new file mode 100644
index 0000000000000000000000000000000000000000..b2c592527a5966e6f8e79e8c52dc5b414246dcc6
--- /dev/null
+++ b/lib/infer_pack/modules/F0Predictor/PMF0Predictor.py
@@ -0,0 +1,97 @@
+from lib.infer_pack.modules.F0Predictor.F0Predictor import F0Predictor
+import parselmouth
+import numpy as np
+
+
+class PMF0Predictor(F0Predictor):
+    def __init__(self, hop_length=512, f0_min=50, f0_max=1100, sampling_rate=44100):
+        self.hop_length = hop_length
+        self.f0_min = f0_min
+        self.f0_max = f0_max
+        self.sampling_rate = sampling_rate
+
+    def interpolate_f0(self, f0):
+        """
+        对F0进行插值处理
+        """
+
+        data = np.reshape(f0, (f0.size, 1))
+
+        vuv_vector = np.zeros((data.size, 1), dtype=np.float32)
+        vuv_vector[data > 0.0] = 1.0
+        vuv_vector[data <= 0.0] = 0.0
+
+        ip_data = data
+
+        frame_number = data.size
+        last_value = 0.0
+        for i in range(frame_number):
+            if data[i] <= 0.0:
+                j = i + 1
+                for j in range(i + 1, frame_number):
+                    if data[j] > 0.0:
+                        break
+                if j < frame_number - 1:
+                    if last_value > 0.0:
+                        step = (data[j] - data[i - 1]) / float(j - i)
+                        for k in range(i, j):
+                            ip_data[k] = data[i - 1] + step * (k - i + 1)
+                    else:
+                        for k in range(i, j):
+                            ip_data[k] = data[j]
+                else:
+                    for k in range(i, frame_number):
+                        ip_data[k] = last_value
+            else:
+                ip_data[i] = data[i]  # 这里可能存在一个没有必要的拷贝
+                last_value = data[i]
+
+        return ip_data[:, 0], vuv_vector[:, 0]
+
+    def compute_f0(self, wav, p_len=None):
+        x = wav
+        if p_len is None:
+            p_len = x.shape[0] // self.hop_length
+        else:
+            assert abs(p_len - x.shape[0] // self.hop_length) < 4, "pad length error"
+        time_step = self.hop_length / self.sampling_rate * 1000
+        f0 = (
+            parselmouth.Sound(x, self.sampling_rate)
+            .to_pitch_ac(
+                time_step=time_step / 1000,
+                voicing_threshold=0.6,
+                pitch_floor=self.f0_min,
+                pitch_ceiling=self.f0_max,
+            )
+            .selected_array["frequency"]
+        )
+
+        pad_size = (p_len - len(f0) + 1) // 2
+        if pad_size > 0 or p_len - len(f0) - pad_size > 0:
+            f0 = np.pad(f0, [[pad_size, p_len - len(f0) - pad_size]], mode="constant")
+        f0, uv = self.interpolate_f0(f0)
+        return f0
+
+    def compute_f0_uv(self, wav, p_len=None):
+        x = wav
+        if p_len is None:
+            p_len = x.shape[0] // self.hop_length
+        else:
+            assert abs(p_len - x.shape[0] // self.hop_length) < 4, "pad length error"
+        time_step = self.hop_length / self.sampling_rate * 1000
+        f0 = (
+            parselmouth.Sound(x, self.sampling_rate)
+            .to_pitch_ac(
+                time_step=time_step / 1000,
+                voicing_threshold=0.6,
+                pitch_floor=self.f0_min,
+                pitch_ceiling=self.f0_max,
+            )
+            .selected_array["frequency"]
+        )
+
+        pad_size = (p_len - len(f0) + 1) // 2
+        if pad_size > 0 or p_len - len(f0) - pad_size > 0:
+            f0 = np.pad(f0, [[pad_size, p_len - len(f0) - pad_size]], mode="constant")
+        f0, uv = self.interpolate_f0(f0)
+        return f0, uv
diff --git a/lib/infer_pack/modules/F0Predictor/__init__.py b/lib/infer_pack/modules/F0Predictor/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/lib/infer_pack/onnx_inference.py b/lib/infer_pack/onnx_inference.py
new file mode 100644
index 0000000000000000000000000000000000000000..6517853be49e61c427cf7cd9b5ed203f6d5f367e
--- /dev/null
+++ b/lib/infer_pack/onnx_inference.py
@@ -0,0 +1,145 @@
+import onnxruntime
+import librosa
+import numpy as np
+import soundfile
+
+
+class ContentVec:
+    def __init__(self, vec_path="pretrained/vec-768-layer-12.onnx", device=None):
+        print("load model(s) from {}".format(vec_path))
+        if device == "cpu" or device is None:
+            providers = ["CPUExecutionProvider"]
+        elif device == "cuda":
+            providers = ["CUDAExecutionProvider", "CPUExecutionProvider"]
+        elif device == "dml":
+            providers = ["DmlExecutionProvider"]
+        else:
+            raise RuntimeError("Unsportted Device")
+        self.model = onnxruntime.InferenceSession(vec_path, providers=providers)
+
+    def __call__(self, wav):
+        return self.forward(wav)
+
+    def forward(self, wav):
+        feats = wav
+        if feats.ndim == 2:  # double channels
+            feats = feats.mean(-1)
+        assert feats.ndim == 1, feats.ndim
+        feats = np.expand_dims(np.expand_dims(feats, 0), 0)
+        onnx_input = {self.model.get_inputs()[0].name: feats}
+        logits = self.model.run(None, onnx_input)[0]
+        return logits.transpose(0, 2, 1)
+
+
+def get_f0_predictor(f0_predictor, hop_length, sampling_rate, **kargs):
+    if f0_predictor == "pm":
+        from lib.infer_pack.modules.F0Predictor.PMF0Predictor import PMF0Predictor
+
+        f0_predictor_object = PMF0Predictor(
+            hop_length=hop_length, sampling_rate=sampling_rate
+        )
+    elif f0_predictor == "harvest":
+        from lib.infer_pack.modules.F0Predictor.HarvestF0Predictor import (
+            HarvestF0Predictor,
+        )
+
+        f0_predictor_object = HarvestF0Predictor(
+            hop_length=hop_length, sampling_rate=sampling_rate
+        )
+    elif f0_predictor == "dio":
+        from lib.infer_pack.modules.F0Predictor.DioF0Predictor import DioF0Predictor
+
+        f0_predictor_object = DioF0Predictor(
+            hop_length=hop_length, sampling_rate=sampling_rate
+        )
+    else:
+        raise Exception("Unknown f0 predictor")
+    return f0_predictor_object
+
+
+class OnnxRVC:
+    def __init__(
+        self,
+        model_path,
+        sr=40000,
+        hop_size=512,
+        vec_path="vec-768-layer-12",
+        device="cpu",
+    ):
+        vec_path = f"pretrained/{vec_path}.onnx"
+        self.vec_model = ContentVec(vec_path, device)
+        if device == "cpu" or device is None:
+            providers = ["CPUExecutionProvider"]
+        elif device == "cuda":
+            providers = ["CUDAExecutionProvider", "CPUExecutionProvider"]
+        elif device == "dml":
+            providers = ["DmlExecutionProvider"]
+        else:
+            raise RuntimeError("Unsportted Device")
+        self.model = onnxruntime.InferenceSession(model_path, providers=providers)
+        self.sampling_rate = sr
+        self.hop_size = hop_size
+
+    def forward(self, hubert, hubert_length, pitch, pitchf, ds, rnd):
+        onnx_input = {
+            self.model.get_inputs()[0].name: hubert,
+            self.model.get_inputs()[1].name: hubert_length,
+            self.model.get_inputs()[2].name: pitch,
+            self.model.get_inputs()[3].name: pitchf,
+            self.model.get_inputs()[4].name: ds,
+            self.model.get_inputs()[5].name: rnd,
+        }
+        return (self.model.run(None, onnx_input)[0] * 32767).astype(np.int16)
+
+    def inference(
+        self,
+        raw_path,
+        sid,
+        f0_method="dio",
+        f0_up_key=0,
+        pad_time=0.5,
+        cr_threshold=0.02,
+    ):
+        f0_min = 50
+        f0_max = 1100
+        f0_mel_min = 1127 * np.log(1 + f0_min / 700)
+        f0_mel_max = 1127 * np.log(1 + f0_max / 700)
+        f0_predictor = get_f0_predictor(
+            f0_method,
+            hop_length=self.hop_size,
+            sampling_rate=self.sampling_rate,
+            threshold=cr_threshold,
+        )
+        wav, sr = librosa.load(raw_path, sr=self.sampling_rate)
+        org_length = len(wav)
+        if org_length / sr > 50.0:
+            raise RuntimeError("Reached Max Length")
+
+        wav16k = librosa.resample(wav, orig_sr=self.sampling_rate, target_sr=16000)
+        wav16k = wav16k
+
+        hubert = self.vec_model(wav16k)
+        hubert = np.repeat(hubert, 2, axis=2).transpose(0, 2, 1).astype(np.float32)
+        hubert_length = hubert.shape[1]
+
+        pitchf = f0_predictor.compute_f0(wav, hubert_length)
+        pitchf = pitchf * 2 ** (f0_up_key / 12)
+        pitch = pitchf.copy()
+        f0_mel = 1127 * np.log(1 + pitch / 700)
+        f0_mel[f0_mel > 0] = (f0_mel[f0_mel > 0] - f0_mel_min) * 254 / (
+            f0_mel_max - f0_mel_min
+        ) + 1
+        f0_mel[f0_mel <= 1] = 1
+        f0_mel[f0_mel > 255] = 255
+        pitch = np.rint(f0_mel).astype(np.int64)
+
+        pitchf = pitchf.reshape(1, len(pitchf)).astype(np.float32)
+        pitch = pitch.reshape(1, len(pitch))
+        ds = np.array([sid]).astype(np.int64)
+
+        rnd = np.random.randn(1, 192, hubert_length).astype(np.float32)
+        hubert_length = np.array([hubert_length]).astype(np.int64)
+
+        out_wav = self.forward(hubert, hubert_length, pitch, pitchf, ds, rnd).squeeze()
+        out_wav = np.pad(out_wav, (0, 2 * self.hop_size), "constant")
+        return out_wav[0:org_length]
diff --git a/lib/infer_pack/transforms.py b/lib/infer_pack/transforms.py
new file mode 100644
index 0000000000000000000000000000000000000000..a11f799e023864ff7082c1f49c0cc18351a13b47
--- /dev/null
+++ b/lib/infer_pack/transforms.py
@@ -0,0 +1,209 @@
+import torch
+from torch.nn import functional as F
+
+import numpy as np
+
+
+DEFAULT_MIN_BIN_WIDTH = 1e-3
+DEFAULT_MIN_BIN_HEIGHT = 1e-3
+DEFAULT_MIN_DERIVATIVE = 1e-3
+
+
+def piecewise_rational_quadratic_transform(
+    inputs,
+    unnormalized_widths,
+    unnormalized_heights,
+    unnormalized_derivatives,
+    inverse=False,
+    tails=None,
+    tail_bound=1.0,
+    min_bin_width=DEFAULT_MIN_BIN_WIDTH,
+    min_bin_height=DEFAULT_MIN_BIN_HEIGHT,
+    min_derivative=DEFAULT_MIN_DERIVATIVE,
+):
+    if tails is None:
+        spline_fn = rational_quadratic_spline
+        spline_kwargs = {}
+    else:
+        spline_fn = unconstrained_rational_quadratic_spline
+        spline_kwargs = {"tails": tails, "tail_bound": tail_bound}
+
+    outputs, logabsdet = spline_fn(
+        inputs=inputs,
+        unnormalized_widths=unnormalized_widths,
+        unnormalized_heights=unnormalized_heights,
+        unnormalized_derivatives=unnormalized_derivatives,
+        inverse=inverse,
+        min_bin_width=min_bin_width,
+        min_bin_height=min_bin_height,
+        min_derivative=min_derivative,
+        **spline_kwargs
+    )
+    return outputs, logabsdet
+
+
+def searchsorted(bin_locations, inputs, eps=1e-6):
+    bin_locations[..., -1] += eps
+    return torch.sum(inputs[..., None] >= bin_locations, dim=-1) - 1
+
+
+def unconstrained_rational_quadratic_spline(
+    inputs,
+    unnormalized_widths,
+    unnormalized_heights,
+    unnormalized_derivatives,
+    inverse=False,
+    tails="linear",
+    tail_bound=1.0,
+    min_bin_width=DEFAULT_MIN_BIN_WIDTH,
+    min_bin_height=DEFAULT_MIN_BIN_HEIGHT,
+    min_derivative=DEFAULT_MIN_DERIVATIVE,
+):
+    inside_interval_mask = (inputs >= -tail_bound) & (inputs <= tail_bound)
+    outside_interval_mask = ~inside_interval_mask
+
+    outputs = torch.zeros_like(inputs)
+    logabsdet = torch.zeros_like(inputs)
+
+    if tails == "linear":
+        unnormalized_derivatives = F.pad(unnormalized_derivatives, pad=(1, 1))
+        constant = np.log(np.exp(1 - min_derivative) - 1)
+        unnormalized_derivatives[..., 0] = constant
+        unnormalized_derivatives[..., -1] = constant
+
+        outputs[outside_interval_mask] = inputs[outside_interval_mask]
+        logabsdet[outside_interval_mask] = 0
+    else:
+        raise RuntimeError("{} tails are not implemented.".format(tails))
+
+    (
+        outputs[inside_interval_mask],
+        logabsdet[inside_interval_mask],
+    ) = rational_quadratic_spline(
+        inputs=inputs[inside_interval_mask],
+        unnormalized_widths=unnormalized_widths[inside_interval_mask, :],
+        unnormalized_heights=unnormalized_heights[inside_interval_mask, :],
+        unnormalized_derivatives=unnormalized_derivatives[inside_interval_mask, :],
+        inverse=inverse,
+        left=-tail_bound,
+        right=tail_bound,
+        bottom=-tail_bound,
+        top=tail_bound,
+        min_bin_width=min_bin_width,
+        min_bin_height=min_bin_height,
+        min_derivative=min_derivative,
+    )
+
+    return outputs, logabsdet
+
+
+def rational_quadratic_spline(
+    inputs,
+    unnormalized_widths,
+    unnormalized_heights,
+    unnormalized_derivatives,
+    inverse=False,
+    left=0.0,
+    right=1.0,
+    bottom=0.0,
+    top=1.0,
+    min_bin_width=DEFAULT_MIN_BIN_WIDTH,
+    min_bin_height=DEFAULT_MIN_BIN_HEIGHT,
+    min_derivative=DEFAULT_MIN_DERIVATIVE,
+):
+    if torch.min(inputs) < left or torch.max(inputs) > right:
+        raise ValueError("Input to a transform is not within its domain")
+
+    num_bins = unnormalized_widths.shape[-1]
+
+    if min_bin_width * num_bins > 1.0:
+        raise ValueError("Minimal bin width too large for the number of bins")
+    if min_bin_height * num_bins > 1.0:
+        raise ValueError("Minimal bin height too large for the number of bins")
+
+    widths = F.softmax(unnormalized_widths, dim=-1)
+    widths = min_bin_width + (1 - min_bin_width * num_bins) * widths
+    cumwidths = torch.cumsum(widths, dim=-1)
+    cumwidths = F.pad(cumwidths, pad=(1, 0), mode="constant", value=0.0)
+    cumwidths = (right - left) * cumwidths + left
+    cumwidths[..., 0] = left
+    cumwidths[..., -1] = right
+    widths = cumwidths[..., 1:] - cumwidths[..., :-1]
+
+    derivatives = min_derivative + F.softplus(unnormalized_derivatives)
+
+    heights = F.softmax(unnormalized_heights, dim=-1)
+    heights = min_bin_height + (1 - min_bin_height * num_bins) * heights
+    cumheights = torch.cumsum(heights, dim=-1)
+    cumheights = F.pad(cumheights, pad=(1, 0), mode="constant", value=0.0)
+    cumheights = (top - bottom) * cumheights + bottom
+    cumheights[..., 0] = bottom
+    cumheights[..., -1] = top
+    heights = cumheights[..., 1:] - cumheights[..., :-1]
+
+    if inverse:
+        bin_idx = searchsorted(cumheights, inputs)[..., None]
+    else:
+        bin_idx = searchsorted(cumwidths, inputs)[..., None]
+
+    input_cumwidths = cumwidths.gather(-1, bin_idx)[..., 0]
+    input_bin_widths = widths.gather(-1, bin_idx)[..., 0]
+
+    input_cumheights = cumheights.gather(-1, bin_idx)[..., 0]
+    delta = heights / widths
+    input_delta = delta.gather(-1, bin_idx)[..., 0]
+
+    input_derivatives = derivatives.gather(-1, bin_idx)[..., 0]
+    input_derivatives_plus_one = derivatives[..., 1:].gather(-1, bin_idx)[..., 0]
+
+    input_heights = heights.gather(-1, bin_idx)[..., 0]
+
+    if inverse:
+        a = (inputs - input_cumheights) * (
+            input_derivatives + input_derivatives_plus_one - 2 * input_delta
+        ) + input_heights * (input_delta - input_derivatives)
+        b = input_heights * input_derivatives - (inputs - input_cumheights) * (
+            input_derivatives + input_derivatives_plus_one - 2 * input_delta
+        )
+        c = -input_delta * (inputs - input_cumheights)
+
+        discriminant = b.pow(2) - 4 * a * c
+        assert (discriminant >= 0).all()
+
+        root = (2 * c) / (-b - torch.sqrt(discriminant))
+        outputs = root * input_bin_widths + input_cumwidths
+
+        theta_one_minus_theta = root * (1 - root)
+        denominator = input_delta + (
+            (input_derivatives + input_derivatives_plus_one - 2 * input_delta)
+            * theta_one_minus_theta
+        )
+        derivative_numerator = input_delta.pow(2) * (
+            input_derivatives_plus_one * root.pow(2)
+            + 2 * input_delta * theta_one_minus_theta
+            + input_derivatives * (1 - root).pow(2)
+        )
+        logabsdet = torch.log(derivative_numerator) - 2 * torch.log(denominator)
+
+        return outputs, -logabsdet
+    else:
+        theta = (inputs - input_cumwidths) / input_bin_widths
+        theta_one_minus_theta = theta * (1 - theta)
+
+        numerator = input_heights * (
+            input_delta * theta.pow(2) + input_derivatives * theta_one_minus_theta
+        )
+        denominator = input_delta + (
+            (input_derivatives + input_derivatives_plus_one - 2 * input_delta)
+            * theta_one_minus_theta
+        )
+        outputs = input_cumheights + numerator / denominator
+
+        derivative_numerator = input_delta.pow(2) * (
+            input_derivatives_plus_one * theta.pow(2)
+            + 2 * input_delta * theta_one_minus_theta
+            + input_derivatives * (1 - theta).pow(2)
+        )
+        logabsdet = torch.log(derivative_numerator) - 2 * torch.log(denominator)
+
+        return outputs, logabsdet
diff --git a/lib/uvr5_pack/lib_v5/dataset.py b/lib/uvr5_pack/lib_v5/dataset.py
new file mode 100644
index 0000000000000000000000000000000000000000..cfd01a174978d97180a897e40cb59ecadec1d12e
--- /dev/null
+++ b/lib/uvr5_pack/lib_v5/dataset.py
@@ -0,0 +1,183 @@
+import os
+import random
+
+import numpy as np
+import torch
+import torch.utils.data
+from tqdm import tqdm
+
+from . import spec_utils
+
+
+class VocalRemoverValidationSet(torch.utils.data.Dataset):
+    def __init__(self, patch_list):
+        self.patch_list = patch_list
+
+    def __len__(self):
+        return len(self.patch_list)
+
+    def __getitem__(self, idx):
+        path = self.patch_list[idx]
+        data = np.load(path)
+
+        X, y = data["X"], data["y"]
+
+        X_mag = np.abs(X)
+        y_mag = np.abs(y)
+
+        return X_mag, y_mag
+
+
+def make_pair(mix_dir, inst_dir):
+    input_exts = [".wav", ".m4a", ".mp3", ".mp4", ".flac"]
+
+    X_list = sorted(
+        [
+            os.path.join(mix_dir, fname)
+            for fname in os.listdir(mix_dir)
+            if os.path.splitext(fname)[1] in input_exts
+        ]
+    )
+    y_list = sorted(
+        [
+            os.path.join(inst_dir, fname)
+            for fname in os.listdir(inst_dir)
+            if os.path.splitext(fname)[1] in input_exts
+        ]
+    )
+
+    filelist = list(zip(X_list, y_list))
+
+    return filelist
+
+
+def train_val_split(dataset_dir, split_mode, val_rate, val_filelist):
+    if split_mode == "random":
+        filelist = make_pair(
+            os.path.join(dataset_dir, "mixtures"),
+            os.path.join(dataset_dir, "instruments"),
+        )
+
+        random.shuffle(filelist)
+
+        if len(val_filelist) == 0:
+            val_size = int(len(filelist) * val_rate)
+            train_filelist = filelist[:-val_size]
+            val_filelist = filelist[-val_size:]
+        else:
+            train_filelist = [
+                pair for pair in filelist if list(pair) not in val_filelist
+            ]
+    elif split_mode == "subdirs":
+        if len(val_filelist) != 0:
+            raise ValueError(
+                "The `val_filelist` option is not available in `subdirs` mode"
+            )
+
+        train_filelist = make_pair(
+            os.path.join(dataset_dir, "training/mixtures"),
+            os.path.join(dataset_dir, "training/instruments"),
+        )
+
+        val_filelist = make_pair(
+            os.path.join(dataset_dir, "validation/mixtures"),
+            os.path.join(dataset_dir, "validation/instruments"),
+        )
+
+    return train_filelist, val_filelist
+
+
+def augment(X, y, reduction_rate, reduction_mask, mixup_rate, mixup_alpha):
+    perm = np.random.permutation(len(X))
+    for i, idx in enumerate(tqdm(perm)):
+        if np.random.uniform() < reduction_rate:
+            y[idx] = spec_utils.reduce_vocal_aggressively(
+                X[idx], y[idx], reduction_mask
+            )
+
+        if np.random.uniform() < 0.5:
+            # swap channel
+            X[idx] = X[idx, ::-1]
+            y[idx] = y[idx, ::-1]
+        if np.random.uniform() < 0.02:
+            # mono
+            X[idx] = X[idx].mean(axis=0, keepdims=True)
+            y[idx] = y[idx].mean(axis=0, keepdims=True)
+        if np.random.uniform() < 0.02:
+            # inst
+            X[idx] = y[idx]
+
+        if np.random.uniform() < mixup_rate and i < len(perm) - 1:
+            lam = np.random.beta(mixup_alpha, mixup_alpha)
+            X[idx] = lam * X[idx] + (1 - lam) * X[perm[i + 1]]
+            y[idx] = lam * y[idx] + (1 - lam) * y[perm[i + 1]]
+
+    return X, y
+
+
+def make_padding(width, cropsize, offset):
+    left = offset
+    roi_size = cropsize - left * 2
+    if roi_size == 0:
+        roi_size = cropsize
+    right = roi_size - (width % roi_size) + left
+
+    return left, right, roi_size
+
+
+def make_training_set(filelist, cropsize, patches, sr, hop_length, n_fft, offset):
+    len_dataset = patches * len(filelist)
+
+    X_dataset = np.zeros((len_dataset, 2, n_fft // 2 + 1, cropsize), dtype=np.complex64)
+    y_dataset = np.zeros((len_dataset, 2, n_fft // 2 + 1, cropsize), dtype=np.complex64)
+
+    for i, (X_path, y_path) in enumerate(tqdm(filelist)):
+        X, y = spec_utils.cache_or_load(X_path, y_path, sr, hop_length, n_fft)
+        coef = np.max([np.abs(X).max(), np.abs(y).max()])
+        X, y = X / coef, y / coef
+
+        l, r, roi_size = make_padding(X.shape[2], cropsize, offset)
+        X_pad = np.pad(X, ((0, 0), (0, 0), (l, r)), mode="constant")
+        y_pad = np.pad(y, ((0, 0), (0, 0), (l, r)), mode="constant")
+
+        starts = np.random.randint(0, X_pad.shape[2] - cropsize, patches)
+        ends = starts + cropsize
+        for j in range(patches):
+            idx = i * patches + j
+            X_dataset[idx] = X_pad[:, :, starts[j] : ends[j]]
+            y_dataset[idx] = y_pad[:, :, starts[j] : ends[j]]
+
+    return X_dataset, y_dataset
+
+
+def make_validation_set(filelist, cropsize, sr, hop_length, n_fft, offset):
+    patch_list = []
+    patch_dir = "cs{}_sr{}_hl{}_nf{}_of{}".format(
+        cropsize, sr, hop_length, n_fft, offset
+    )
+    os.makedirs(patch_dir, exist_ok=True)
+
+    for i, (X_path, y_path) in enumerate(tqdm(filelist)):
+        basename = os.path.splitext(os.path.basename(X_path))[0]
+
+        X, y = spec_utils.cache_or_load(X_path, y_path, sr, hop_length, n_fft)
+        coef = np.max([np.abs(X).max(), np.abs(y).max()])
+        X, y = X / coef, y / coef
+
+        l, r, roi_size = make_padding(X.shape[2], cropsize, offset)
+        X_pad = np.pad(X, ((0, 0), (0, 0), (l, r)), mode="constant")
+        y_pad = np.pad(y, ((0, 0), (0, 0), (l, r)), mode="constant")
+
+        len_dataset = int(np.ceil(X.shape[2] / roi_size))
+        for j in range(len_dataset):
+            outpath = os.path.join(patch_dir, "{}_p{}.npz".format(basename, j))
+            start = j * roi_size
+            if not os.path.exists(outpath):
+                np.savez(
+                    outpath,
+                    X=X_pad[:, :, start : start + cropsize],
+                    y=y_pad[:, :, start : start + cropsize],
+                )
+            patch_list.append(outpath)
+
+    return VocalRemoverValidationSet(patch_list)
diff --git a/lib/uvr5_pack/lib_v5/layers.py b/lib/uvr5_pack/lib_v5/layers.py
new file mode 100644
index 0000000000000000000000000000000000000000..b82f06bb4993cd63f076e68d7e24185269b1bc42
--- /dev/null
+++ b/lib/uvr5_pack/lib_v5/layers.py
@@ -0,0 +1,118 @@
+import torch
+from torch import nn
+import torch.nn.functional as F
+
+from . import spec_utils
+
+
+class Conv2DBNActiv(nn.Module):
+    def __init__(self, nin, nout, ksize=3, stride=1, pad=1, dilation=1, activ=nn.ReLU):
+        super(Conv2DBNActiv, self).__init__()
+        self.conv = nn.Sequential(
+            nn.Conv2d(
+                nin,
+                nout,
+                kernel_size=ksize,
+                stride=stride,
+                padding=pad,
+                dilation=dilation,
+                bias=False,
+            ),
+            nn.BatchNorm2d(nout),
+            activ(),
+        )
+
+    def __call__(self, x):
+        return self.conv(x)
+
+
+class SeperableConv2DBNActiv(nn.Module):
+    def __init__(self, nin, nout, ksize=3, stride=1, pad=1, dilation=1, activ=nn.ReLU):
+        super(SeperableConv2DBNActiv, self).__init__()
+        self.conv = nn.Sequential(
+            nn.Conv2d(
+                nin,
+                nin,
+                kernel_size=ksize,
+                stride=stride,
+                padding=pad,
+                dilation=dilation,
+                groups=nin,
+                bias=False,
+            ),
+            nn.Conv2d(nin, nout, kernel_size=1, bias=False),
+            nn.BatchNorm2d(nout),
+            activ(),
+        )
+
+    def __call__(self, x):
+        return self.conv(x)
+
+
+class Encoder(nn.Module):
+    def __init__(self, nin, nout, ksize=3, stride=1, pad=1, activ=nn.LeakyReLU):
+        super(Encoder, self).__init__()
+        self.conv1 = Conv2DBNActiv(nin, nout, ksize, 1, pad, activ=activ)
+        self.conv2 = Conv2DBNActiv(nout, nout, ksize, stride, pad, activ=activ)
+
+    def __call__(self, x):
+        skip = self.conv1(x)
+        h = self.conv2(skip)
+
+        return h, skip
+
+
+class Decoder(nn.Module):
+    def __init__(
+        self, nin, nout, ksize=3, stride=1, pad=1, activ=nn.ReLU, dropout=False
+    ):
+        super(Decoder, self).__init__()
+        self.conv = Conv2DBNActiv(nin, nout, ksize, 1, pad, activ=activ)
+        self.dropout = nn.Dropout2d(0.1) if dropout else None
+
+    def __call__(self, x, skip=None):
+        x = F.interpolate(x, scale_factor=2, mode="bilinear", align_corners=True)
+        if skip is not None:
+            skip = spec_utils.crop_center(skip, x)
+            x = torch.cat([x, skip], dim=1)
+        h = self.conv(x)
+
+        if self.dropout is not None:
+            h = self.dropout(h)
+
+        return h
+
+
+class ASPPModule(nn.Module):
+    def __init__(self, nin, nout, dilations=(4, 8, 16), activ=nn.ReLU):
+        super(ASPPModule, self).__init__()
+        self.conv1 = nn.Sequential(
+            nn.AdaptiveAvgPool2d((1, None)),
+            Conv2DBNActiv(nin, nin, 1, 1, 0, activ=activ),
+        )
+        self.conv2 = Conv2DBNActiv(nin, nin, 1, 1, 0, activ=activ)
+        self.conv3 = SeperableConv2DBNActiv(
+            nin, nin, 3, 1, dilations[0], dilations[0], activ=activ
+        )
+        self.conv4 = SeperableConv2DBNActiv(
+            nin, nin, 3, 1, dilations[1], dilations[1], activ=activ
+        )
+        self.conv5 = SeperableConv2DBNActiv(
+            nin, nin, 3, 1, dilations[2], dilations[2], activ=activ
+        )
+        self.bottleneck = nn.Sequential(
+            Conv2DBNActiv(nin * 5, nout, 1, 1, 0, activ=activ), nn.Dropout2d(0.1)
+        )
+
+    def forward(self, x):
+        _, _, h, w = x.size()
+        feat1 = F.interpolate(
+            self.conv1(x), size=(h, w), mode="bilinear", align_corners=True
+        )
+        feat2 = self.conv2(x)
+        feat3 = self.conv3(x)
+        feat4 = self.conv4(x)
+        feat5 = self.conv5(x)
+        out = torch.cat((feat1, feat2, feat3, feat4, feat5), dim=1)
+        bottle = self.bottleneck(out)
+        return bottle
diff --git a/lib/uvr5_pack/lib_v5/layers_123812KB .py b/lib/uvr5_pack/lib_v5/layers_123812KB .py
new file mode 100644
index 0000000000000000000000000000000000000000..b82f06bb4993cd63f076e68d7e24185269b1bc42
--- /dev/null
+++ b/lib/uvr5_pack/lib_v5/layers_123812KB .py	
@@ -0,0 +1,118 @@
+import torch
+from torch import nn
+import torch.nn.functional as F
+
+from . import spec_utils
+
+
+class Conv2DBNActiv(nn.Module):
+    def __init__(self, nin, nout, ksize=3, stride=1, pad=1, dilation=1, activ=nn.ReLU):
+        super(Conv2DBNActiv, self).__init__()
+        self.conv = nn.Sequential(
+            nn.Conv2d(
+                nin,
+                nout,
+                kernel_size=ksize,
+                stride=stride,
+                padding=pad,
+                dilation=dilation,
+                bias=False,
+            ),
+            nn.BatchNorm2d(nout),
+            activ(),
+        )
+
+    def __call__(self, x):
+        return self.conv(x)
+
+
+class SeperableConv2DBNActiv(nn.Module):
+    def __init__(self, nin, nout, ksize=3, stride=1, pad=1, dilation=1, activ=nn.ReLU):
+        super(SeperableConv2DBNActiv, self).__init__()
+        self.conv = nn.Sequential(
+            nn.Conv2d(
+                nin,
+                nin,
+                kernel_size=ksize,
+                stride=stride,
+                padding=pad,
+                dilation=dilation,
+                groups=nin,
+                bias=False,
+            ),
+            nn.Conv2d(nin, nout, kernel_size=1, bias=False),
+            nn.BatchNorm2d(nout),
+            activ(),
+        )
+
+    def __call__(self, x):
+        return self.conv(x)
+
+
+class Encoder(nn.Module):
+    def __init__(self, nin, nout, ksize=3, stride=1, pad=1, activ=nn.LeakyReLU):
+        super(Encoder, self).__init__()
+        self.conv1 = Conv2DBNActiv(nin, nout, ksize, 1, pad, activ=activ)
+        self.conv2 = Conv2DBNActiv(nout, nout, ksize, stride, pad, activ=activ)
+
+    def __call__(self, x):
+        skip = self.conv1(x)
+        h = self.conv2(skip)
+
+        return h, skip
+
+
+class Decoder(nn.Module):
+    def __init__(
+        self, nin, nout, ksize=3, stride=1, pad=1, activ=nn.ReLU, dropout=False
+    ):
+        super(Decoder, self).__init__()
+        self.conv = Conv2DBNActiv(nin, nout, ksize, 1, pad, activ=activ)
+        self.dropout = nn.Dropout2d(0.1) if dropout else None
+
+    def __call__(self, x, skip=None):
+        x = F.interpolate(x, scale_factor=2, mode="bilinear", align_corners=True)
+        if skip is not None:
+            skip = spec_utils.crop_center(skip, x)
+            x = torch.cat([x, skip], dim=1)
+        h = self.conv(x)
+
+        if self.dropout is not None:
+            h = self.dropout(h)
+
+        return h
+
+
+class ASPPModule(nn.Module):
+    def __init__(self, nin, nout, dilations=(4, 8, 16), activ=nn.ReLU):
+        super(ASPPModule, self).__init__()
+        self.conv1 = nn.Sequential(
+            nn.AdaptiveAvgPool2d((1, None)),
+            Conv2DBNActiv(nin, nin, 1, 1, 0, activ=activ),
+        )
+        self.conv2 = Conv2DBNActiv(nin, nin, 1, 1, 0, activ=activ)
+        self.conv3 = SeperableConv2DBNActiv(
+            nin, nin, 3, 1, dilations[0], dilations[0], activ=activ
+        )
+        self.conv4 = SeperableConv2DBNActiv(
+            nin, nin, 3, 1, dilations[1], dilations[1], activ=activ
+        )
+        self.conv5 = SeperableConv2DBNActiv(
+            nin, nin, 3, 1, dilations[2], dilations[2], activ=activ
+        )
+        self.bottleneck = nn.Sequential(
+            Conv2DBNActiv(nin * 5, nout, 1, 1, 0, activ=activ), nn.Dropout2d(0.1)
+        )
+
+    def forward(self, x):
+        _, _, h, w = x.size()
+        feat1 = F.interpolate(
+            self.conv1(x), size=(h, w), mode="bilinear", align_corners=True
+        )
+        feat2 = self.conv2(x)
+        feat3 = self.conv3(x)
+        feat4 = self.conv4(x)
+        feat5 = self.conv5(x)
+        out = torch.cat((feat1, feat2, feat3, feat4, feat5), dim=1)
+        bottle = self.bottleneck(out)
+        return bottle
diff --git a/lib/uvr5_pack/lib_v5/layers_123821KB.py b/lib/uvr5_pack/lib_v5/layers_123821KB.py
new file mode 100644
index 0000000000000000000000000000000000000000..b82f06bb4993cd63f076e68d7e24185269b1bc42
--- /dev/null
+++ b/lib/uvr5_pack/lib_v5/layers_123821KB.py
@@ -0,0 +1,118 @@
+import torch
+from torch import nn
+import torch.nn.functional as F
+
+from . import spec_utils
+
+
+class Conv2DBNActiv(nn.Module):
+    def __init__(self, nin, nout, ksize=3, stride=1, pad=1, dilation=1, activ=nn.ReLU):
+        super(Conv2DBNActiv, self).__init__()
+        self.conv = nn.Sequential(
+            nn.Conv2d(
+                nin,
+                nout,
+                kernel_size=ksize,
+                stride=stride,
+                padding=pad,
+                dilation=dilation,
+                bias=False,
+            ),
+            nn.BatchNorm2d(nout),
+            activ(),
+        )
+
+    def __call__(self, x):
+        return self.conv(x)
+
+
+class SeperableConv2DBNActiv(nn.Module):
+    def __init__(self, nin, nout, ksize=3, stride=1, pad=1, dilation=1, activ=nn.ReLU):
+        super(SeperableConv2DBNActiv, self).__init__()
+        self.conv = nn.Sequential(
+            nn.Conv2d(
+                nin,
+                nin,
+                kernel_size=ksize,
+                stride=stride,
+                padding=pad,
+                dilation=dilation,
+                groups=nin,
+                bias=False,
+            ),
+            nn.Conv2d(nin, nout, kernel_size=1, bias=False),
+            nn.BatchNorm2d(nout),
+            activ(),
+        )
+
+    def __call__(self, x):
+        return self.conv(x)
+
+
+class Encoder(nn.Module):
+    def __init__(self, nin, nout, ksize=3, stride=1, pad=1, activ=nn.LeakyReLU):
+        super(Encoder, self).__init__()
+        self.conv1 = Conv2DBNActiv(nin, nout, ksize, 1, pad, activ=activ)
+        self.conv2 = Conv2DBNActiv(nout, nout, ksize, stride, pad, activ=activ)
+
+    def __call__(self, x):
+        skip = self.conv1(x)
+        h = self.conv2(skip)
+
+        return h, skip
+
+
+class Decoder(nn.Module):
+    def __init__(
+        self, nin, nout, ksize=3, stride=1, pad=1, activ=nn.ReLU, dropout=False
+    ):
+        super(Decoder, self).__init__()
+        self.conv = Conv2DBNActiv(nin, nout, ksize, 1, pad, activ=activ)
+        self.dropout = nn.Dropout2d(0.1) if dropout else None
+
+    def __call__(self, x, skip=None):
+        x = F.interpolate(x, scale_factor=2, mode="bilinear", align_corners=True)
+        if skip is not None:
+            skip = spec_utils.crop_center(skip, x)
+            x = torch.cat([x, skip], dim=1)
+        h = self.conv(x)
+
+        if self.dropout is not None:
+            h = self.dropout(h)
+
+        return h
+
+
+class ASPPModule(nn.Module):
+    def __init__(self, nin, nout, dilations=(4, 8, 16), activ=nn.ReLU):
+        super(ASPPModule, self).__init__()
+        self.conv1 = nn.Sequential(
+            nn.AdaptiveAvgPool2d((1, None)),
+            Conv2DBNActiv(nin, nin, 1, 1, 0, activ=activ),
+        )
+        self.conv2 = Conv2DBNActiv(nin, nin, 1, 1, 0, activ=activ)
+        self.conv3 = SeperableConv2DBNActiv(
+            nin, nin, 3, 1, dilations[0], dilations[0], activ=activ
+        )
+        self.conv4 = SeperableConv2DBNActiv(
+            nin, nin, 3, 1, dilations[1], dilations[1], activ=activ
+        )
+        self.conv5 = SeperableConv2DBNActiv(
+            nin, nin, 3, 1, dilations[2], dilations[2], activ=activ
+        )
+        self.bottleneck = nn.Sequential(
+            Conv2DBNActiv(nin * 5, nout, 1, 1, 0, activ=activ), nn.Dropout2d(0.1)
+        )
+
+    def forward(self, x):
+        _, _, h, w = x.size()
+        feat1 = F.interpolate(
+            self.conv1(x), size=(h, w), mode="bilinear", align_corners=True
+        )
+        feat2 = self.conv2(x)
+        feat3 = self.conv3(x)
+        feat4 = self.conv4(x)
+        feat5 = self.conv5(x)
+        out = torch.cat((feat1, feat2, feat3, feat4, feat5), dim=1)
+        bottle = self.bottleneck(out)
+        return bottle
diff --git a/lib/uvr5_pack/lib_v5/layers_33966KB.py b/lib/uvr5_pack/lib_v5/layers_33966KB.py
new file mode 100644
index 0000000000000000000000000000000000000000..a38b7bb3ae3136b07eadfc2db445fef4c2de186b
--- /dev/null
+++ b/lib/uvr5_pack/lib_v5/layers_33966KB.py
@@ -0,0 +1,126 @@
+import torch
+from torch import nn
+import torch.nn.functional as F
+
+from . import spec_utils
+
+
+class Conv2DBNActiv(nn.Module):
+    def __init__(self, nin, nout, ksize=3, stride=1, pad=1, dilation=1, activ=nn.ReLU):
+        super(Conv2DBNActiv, self).__init__()
+        self.conv = nn.Sequential(
+            nn.Conv2d(
+                nin,
+                nout,
+                kernel_size=ksize,
+                stride=stride,
+                padding=pad,
+                dilation=dilation,
+                bias=False,
+            ),
+            nn.BatchNorm2d(nout),
+            activ(),
+        )
+
+    def __call__(self, x):
+        return self.conv(x)
+
+
+class SeperableConv2DBNActiv(nn.Module):
+    def __init__(self, nin, nout, ksize=3, stride=1, pad=1, dilation=1, activ=nn.ReLU):
+        super(SeperableConv2DBNActiv, self).__init__()
+        self.conv = nn.Sequential(
+            nn.Conv2d(
+                nin,
+                nin,
+                kernel_size=ksize,
+                stride=stride,
+                padding=pad,
+                dilation=dilation,
+                groups=nin,
+                bias=False,
+            ),
+            nn.Conv2d(nin, nout, kernel_size=1, bias=False),
+            nn.BatchNorm2d(nout),
+            activ(),
+        )
+
+    def __call__(self, x):
+        return self.conv(x)
+
+
+class Encoder(nn.Module):
+    def __init__(self, nin, nout, ksize=3, stride=1, pad=1, activ=nn.LeakyReLU):
+        super(Encoder, self).__init__()
+        self.conv1 = Conv2DBNActiv(nin, nout, ksize, 1, pad, activ=activ)
+        self.conv2 = Conv2DBNActiv(nout, nout, ksize, stride, pad, activ=activ)
+
+    def __call__(self, x):
+        skip = self.conv1(x)
+        h = self.conv2(skip)
+
+        return h, skip
+
+
+class Decoder(nn.Module):
+    def __init__(
+        self, nin, nout, ksize=3, stride=1, pad=1, activ=nn.ReLU, dropout=False
+    ):
+        super(Decoder, self).__init__()
+        self.conv = Conv2DBNActiv(nin, nout, ksize, 1, pad, activ=activ)
+        self.dropout = nn.Dropout2d(0.1) if dropout else None
+
+    def __call__(self, x, skip=None):
+        x = F.interpolate(x, scale_factor=2, mode="bilinear", align_corners=True)
+        if skip is not None:
+            skip = spec_utils.crop_center(skip, x)
+            x = torch.cat([x, skip], dim=1)
+        h = self.conv(x)
+
+        if self.dropout is not None:
+            h = self.dropout(h)
+
+        return h
+
+
+class ASPPModule(nn.Module):
+    def __init__(self, nin, nout, dilations=(4, 8, 16, 32, 64), activ=nn.ReLU):
+        super(ASPPModule, self).__init__()
+        self.conv1 = nn.Sequential(
+            nn.AdaptiveAvgPool2d((1, None)),
+            Conv2DBNActiv(nin, nin, 1, 1, 0, activ=activ),
+        )
+        self.conv2 = Conv2DBNActiv(nin, nin, 1, 1, 0, activ=activ)
+        self.conv3 = SeperableConv2DBNActiv(
+            nin, nin, 3, 1, dilations[0], dilations[0], activ=activ
+        )
+        self.conv4 = SeperableConv2DBNActiv(
+            nin, nin, 3, 1, dilations[1], dilations[1], activ=activ
+        )
+        self.conv5 = SeperableConv2DBNActiv(
+            nin, nin, 3, 1, dilations[2], dilations[2], activ=activ
+        )
+        self.conv6 = SeperableConv2DBNActiv(
+            nin, nin, 3, 1, dilations[2], dilations[2], activ=activ
+        )
+        self.conv7 = SeperableConv2DBNActiv(
+            nin, nin, 3, 1, dilations[2], dilations[2], activ=activ
+        )
+        self.bottleneck = nn.Sequential(
+            Conv2DBNActiv(nin * 7, nout, 1, 1, 0, activ=activ), nn.Dropout2d(0.1)
+        )
+
+    def forward(self, x):
+        _, _, h, w = x.size()
+        feat1 = F.interpolate(
+            self.conv1(x), size=(h, w), mode="bilinear", align_corners=True
+        )
+        feat2 = self.conv2(x)
+        feat3 = self.conv3(x)
+        feat4 = self.conv4(x)
+        feat5 = self.conv5(x)
+        feat6 = self.conv6(x)
+        feat7 = self.conv7(x)
+        out = torch.cat((feat1, feat2, feat3, feat4, feat5, feat6, feat7), dim=1)
+        bottle = self.bottleneck(out)
+        return bottle
diff --git a/lib/uvr5_pack/lib_v5/layers_537227KB.py b/lib/uvr5_pack/lib_v5/layers_537227KB.py
new file mode 100644
index 0000000000000000000000000000000000000000..a38b7bb3ae3136b07eadfc2db445fef4c2de186b
--- /dev/null
+++ b/lib/uvr5_pack/lib_v5/layers_537227KB.py
@@ -0,0 +1,126 @@
+import torch
+from torch import nn
+import torch.nn.functional as F
+
+from . import spec_utils
+
+
+class Conv2DBNActiv(nn.Module):
+    def __init__(self, nin, nout, ksize=3, stride=1, pad=1, dilation=1, activ=nn.ReLU):
+        super(Conv2DBNActiv, self).__init__()
+        self.conv = nn.Sequential(
+            nn.Conv2d(
+                nin,
+                nout,
+                kernel_size=ksize,
+                stride=stride,
+                padding=pad,
+                dilation=dilation,
+                bias=False,
+            ),
+            nn.BatchNorm2d(nout),
+            activ(),
+        )
+
+    def __call__(self, x):
+        return self.conv(x)
+
+
+class SeperableConv2DBNActiv(nn.Module):
+    def __init__(self, nin, nout, ksize=3, stride=1, pad=1, dilation=1, activ=nn.ReLU):
+        super(SeperableConv2DBNActiv, self).__init__()
+        self.conv = nn.Sequential(
+            nn.Conv2d(
+                nin,
+                nin,
+                kernel_size=ksize,
+                stride=stride,
+                padding=pad,
+                dilation=dilation,
+                groups=nin,
+                bias=False,
+            ),
+            nn.Conv2d(nin, nout, kernel_size=1, bias=False),
+            nn.BatchNorm2d(nout),
+            activ(),
+        )
+
+    def __call__(self, x):
+        return self.conv(x)
+
+
+class Encoder(nn.Module):
+    def __init__(self, nin, nout, ksize=3, stride=1, pad=1, activ=nn.LeakyReLU):
+        super(Encoder, self).__init__()
+        self.conv1 = Conv2DBNActiv(nin, nout, ksize, 1, pad, activ=activ)
+        self.conv2 = Conv2DBNActiv(nout, nout, ksize, stride, pad, activ=activ)
+
+    def __call__(self, x):
+        skip = self.conv1(x)
+        h = self.conv2(skip)
+
+        return h, skip
+
+
+class Decoder(nn.Module):
+    def __init__(
+        self, nin, nout, ksize=3, stride=1, pad=1, activ=nn.ReLU, dropout=False
+    ):
+        super(Decoder, self).__init__()
+        self.conv = Conv2DBNActiv(nin, nout, ksize, 1, pad, activ=activ)
+        self.dropout = nn.Dropout2d(0.1) if dropout else None
+
+    def __call__(self, x, skip=None):
+        x = F.interpolate(x, scale_factor=2, mode="bilinear", align_corners=True)
+        if skip is not None:
+            skip = spec_utils.crop_center(skip, x)
+            x = torch.cat([x, skip], dim=1)
+        h = self.conv(x)
+
+        if self.dropout is not None:
+            h = self.dropout(h)
+
+        return h
+
+
+class ASPPModule(nn.Module):
+    def __init__(self, nin, nout, dilations=(4, 8, 16, 32, 64), activ=nn.ReLU):
+        super(ASPPModule, self).__init__()
+        self.conv1 = nn.Sequential(
+            nn.AdaptiveAvgPool2d((1, None)),
+            Conv2DBNActiv(nin, nin, 1, 1, 0, activ=activ),
+        )
+        self.conv2 = Conv2DBNActiv(nin, nin, 1, 1, 0, activ=activ)
+        self.conv3 = SeperableConv2DBNActiv(
+            nin, nin, 3, 1, dilations[0], dilations[0], activ=activ
+        )
+        self.conv4 = SeperableConv2DBNActiv(
+            nin, nin, 3, 1, dilations[1], dilations[1], activ=activ
+        )
+        self.conv5 = SeperableConv2DBNActiv(
+            nin, nin, 3, 1, dilations[2], dilations[2], activ=activ
+        )
+        self.conv6 = SeperableConv2DBNActiv(
+            nin, nin, 3, 1, dilations[2], dilations[2], activ=activ
+        )
+        self.conv7 = SeperableConv2DBNActiv(
+            nin, nin, 3, 1, dilations[2], dilations[2], activ=activ
+        )
+        self.bottleneck = nn.Sequential(
+            Conv2DBNActiv(nin * 7, nout, 1, 1, 0, activ=activ), nn.Dropout2d(0.1)
+        )
+
+    def forward(self, x):
+        _, _, h, w = x.size()
+        feat1 = F.interpolate(
+            self.conv1(x), size=(h, w), mode="bilinear", align_corners=True
+        )
+        feat2 = self.conv2(x)
+        feat3 = self.conv3(x)
+        feat4 = self.conv4(x)
+        feat5 = self.conv5(x)
+        feat6 = self.conv6(x)
+        feat7 = self.conv7(x)
+        out = torch.cat((feat1, feat2, feat3, feat4, feat5, feat6, feat7), dim=1)
+        bottle = self.bottleneck(out)
+        return bottle
diff --git a/lib/uvr5_pack/lib_v5/layers_537238KB.py b/lib/uvr5_pack/lib_v5/layers_537238KB.py
new file mode 100644
index 0000000000000000000000000000000000000000..a38b7bb3ae3136b07eadfc2db445fef4c2de186b
--- /dev/null
+++ b/lib/uvr5_pack/lib_v5/layers_537238KB.py
@@ -0,0 +1,126 @@
+import torch
+from torch import nn
+import torch.nn.functional as F
+
+from . import spec_utils
+
+
+class Conv2DBNActiv(nn.Module):
+    def __init__(self, nin, nout, ksize=3, stride=1, pad=1, dilation=1, activ=nn.ReLU):
+        super(Conv2DBNActiv, self).__init__()
+        self.conv = nn.Sequential(
+            nn.Conv2d(
+                nin,
+                nout,
+                kernel_size=ksize,
+                stride=stride,
+                padding=pad,
+                dilation=dilation,
+                bias=False,
+            ),
+            nn.BatchNorm2d(nout),
+            activ(),
+        )
+
+    def __call__(self, x):
+        return self.conv(x)
+
+
+class SeperableConv2DBNActiv(nn.Module):
+    def __init__(self, nin, nout, ksize=3, stride=1, pad=1, dilation=1, activ=nn.ReLU):
+        super(SeperableConv2DBNActiv, self).__init__()
+        self.conv = nn.Sequential(
+            nn.Conv2d(
+                nin,
+                nin,
+                kernel_size=ksize,
+                stride=stride,
+                padding=pad,
+                dilation=dilation,
+                groups=nin,
+                bias=False,
+            ),
+            nn.Conv2d(nin, nout, kernel_size=1, bias=False),
+            nn.BatchNorm2d(nout),
+            activ(),
+        )
+
+    def __call__(self, x):
+        return self.conv(x)
+
+
+class Encoder(nn.Module):
+    def __init__(self, nin, nout, ksize=3, stride=1, pad=1, activ=nn.LeakyReLU):
+        super(Encoder, self).__init__()
+        self.conv1 = Conv2DBNActiv(nin, nout, ksize, 1, pad, activ=activ)
+        self.conv2 = Conv2DBNActiv(nout, nout, ksize, stride, pad, activ=activ)
+
+    def __call__(self, x):
+        skip = self.conv1(x)
+        h = self.conv2(skip)
+
+        return h, skip
+
+
+class Decoder(nn.Module):
+    def __init__(
+        self, nin, nout, ksize=3, stride=1, pad=1, activ=nn.ReLU, dropout=False
+    ):
+        super(Decoder, self).__init__()
+        self.conv = Conv2DBNActiv(nin, nout, ksize, 1, pad, activ=activ)
+        self.dropout = nn.Dropout2d(0.1) if dropout else None
+
+    def __call__(self, x, skip=None):
+        x = F.interpolate(x, scale_factor=2, mode="bilinear", align_corners=True)
+        if skip is not None:
+            skip = spec_utils.crop_center(skip, x)
+            x = torch.cat([x, skip], dim=1)
+        h = self.conv(x)
+
+        if self.dropout is not None:
+            h = self.dropout(h)
+
+        return h
+
+
+class ASPPModule(nn.Module):
+    def __init__(self, nin, nout, dilations=(4, 8, 16, 32, 64), activ=nn.ReLU):
+        super(ASPPModule, self).__init__()
+        self.conv1 = nn.Sequential(
+            nn.AdaptiveAvgPool2d((1, None)),
+            Conv2DBNActiv(nin, nin, 1, 1, 0, activ=activ),
+        )
+        self.conv2 = Conv2DBNActiv(nin, nin, 1, 1, 0, activ=activ)
+        self.conv3 = SeperableConv2DBNActiv(
+            nin, nin, 3, 1, dilations[0], dilations[0], activ=activ
+        )
+        self.conv4 = SeperableConv2DBNActiv(
+            nin, nin, 3, 1, dilations[1], dilations[1], activ=activ
+        )
+        self.conv5 = SeperableConv2DBNActiv(
+            nin, nin, 3, 1, dilations[2], dilations[2], activ=activ
+        )
+        self.conv6 = SeperableConv2DBNActiv(
+            nin, nin, 3, 1, dilations[2], dilations[2], activ=activ
+        )
+        self.conv7 = SeperableConv2DBNActiv(
+            nin, nin, 3, 1, dilations[2], dilations[2], activ=activ
+        )
+        self.bottleneck = nn.Sequential(
+            Conv2DBNActiv(nin * 7, nout, 1, 1, 0, activ=activ), nn.Dropout2d(0.1)
+        )
+
+    def forward(self, x):
+        _, _, h, w = x.size()
+        feat1 = F.interpolate(
+            self.conv1(x), size=(h, w), mode="bilinear", align_corners=True
+        )
+        feat2 = self.conv2(x)
+        feat3 = self.conv3(x)
+        feat4 = self.conv4(x)
+        feat5 = self.conv5(x)
+        feat6 = self.conv6(x)
+        feat7 = self.conv7(x)
+        out = torch.cat((feat1, feat2, feat3, feat4, feat5, feat6, feat7), dim=1)
+        bottle = self.bottleneck(out)
+        return bottle
diff --git a/lib/uvr5_pack/lib_v5/layers_new.py b/lib/uvr5_pack/lib_v5/layers_new.py
new file mode 100644
index 0000000000000000000000000000000000000000..0c13e60b0dd136d9115a535101c6dbb2a25c6833
--- /dev/null
+++ b/lib/uvr5_pack/lib_v5/layers_new.py
@@ -0,0 +1,125 @@
+import torch
+from torch import nn
+import torch.nn.functional as F
+
+from . import spec_utils
+
+
+class Conv2DBNActiv(nn.Module):
+    def __init__(self, nin, nout, ksize=3, stride=1, pad=1, dilation=1, activ=nn.ReLU):
+        super(Conv2DBNActiv, self).__init__()
+        self.conv = nn.Sequential(
+            nn.Conv2d(
+                nin,
+                nout,
+                kernel_size=ksize,
+                stride=stride,
+                padding=pad,
+                dilation=dilation,
+                bias=False,
+            ),
+            nn.BatchNorm2d(nout),
+            activ(),
+        )
+
+    def __call__(self, x):
+        return self.conv(x)
+
+
+class Encoder(nn.Module):
+    def __init__(self, nin, nout, ksize=3, stride=1, pad=1, activ=nn.LeakyReLU):
+        super(Encoder, self).__init__()
+        self.conv1 = Conv2DBNActiv(nin, nout, ksize, stride, pad, activ=activ)
+        self.conv2 = Conv2DBNActiv(nout, nout, ksize, 1, pad, activ=activ)
+
+    def __call__(self, x):
+        h = self.conv1(x)
+        h = self.conv2(h)
+
+        return h
+
+
+class Decoder(nn.Module):
+    def __init__(
+        self, nin, nout, ksize=3, stride=1, pad=1, activ=nn.ReLU, dropout=False
+    ):
+        super(Decoder, self).__init__()
+        self.conv1 = Conv2DBNActiv(nin, nout, ksize, 1, pad, activ=activ)
+        # self.conv2 = Conv2DBNActiv(nout, nout, ksize, 1, pad, activ=activ)
+        self.dropout = nn.Dropout2d(0.1) if dropout else None
+
+    def __call__(self, x, skip=None):
+        x = F.interpolate(x, scale_factor=2, mode="bilinear", align_corners=True)
+
+        if skip is not None:
+            skip = spec_utils.crop_center(skip, x)
+            x = torch.cat([x, skip], dim=1)
+
+        h = self.conv1(x)
+        # h = self.conv2(h)
+
+        if self.dropout is not None:
+            h = self.dropout(h)
+
+        return h
+
+
+class ASPPModule(nn.Module):
+    def __init__(self, nin, nout, dilations=(4, 8, 12), activ=nn.ReLU, dropout=False):
+        super(ASPPModule, self).__init__()
+        self.conv1 = nn.Sequential(
+            nn.AdaptiveAvgPool2d((1, None)),
+            Conv2DBNActiv(nin, nout, 1, 1, 0, activ=activ),
+        )
+        self.conv2 = Conv2DBNActiv(nin, nout, 1, 1, 0, activ=activ)
+        self.conv3 = Conv2DBNActiv(
+            nin, nout, 3, 1, dilations[0], dilations[0], activ=activ
+        )
+        self.conv4 = Conv2DBNActiv(
+            nin, nout, 3, 1, dilations[1], dilations[1], activ=activ
+        )
+        self.conv5 = Conv2DBNActiv(
+            nin, nout, 3, 1, dilations[2], dilations[2], activ=activ
+        )
+        self.bottleneck = Conv2DBNActiv(nout * 5, nout, 1, 1, 0, activ=activ)
+        self.dropout = nn.Dropout2d(0.1) if dropout else None
+
+    def forward(self, x):
+        _, _, h, w = x.size()
+        feat1 = F.interpolate(
+            self.conv1(x), size=(h, w), mode="bilinear", align_corners=True
+        )
+        feat2 = self.conv2(x)
+        feat3 = self.conv3(x)
+        feat4 = self.conv4(x)
+        feat5 = self.conv5(x)
+        out = torch.cat((feat1, feat2, feat3, feat4, feat5), dim=1)
+        out = self.bottleneck(out)
+
+        if self.dropout is not None:
+            out = self.dropout(out)
+
+        return out
+
+
+class LSTMModule(nn.Module):
+    def __init__(self, nin_conv, nin_lstm, nout_lstm):
+        super(LSTMModule, self).__init__()
+        self.conv = Conv2DBNActiv(nin_conv, 1, 1, 1, 0)
+        self.lstm = nn.LSTM(
+            input_size=nin_lstm, hidden_size=nout_lstm // 2, bidirectional=True
+        )
+        self.dense = nn.Sequential(
+            nn.Linear(nout_lstm, nin_lstm), nn.BatchNorm1d(nin_lstm), nn.ReLU()
+        )
+
+    def forward(self, x):
+        N, _, nbins, nframes = x.size()
+        h = self.conv(x)[:, 0]  # N, nbins, nframes
+        h = h.permute(2, 0, 1)  # nframes, N, nbins
+        h, _ = self.lstm(h)
+        h = self.dense(h.reshape(-1, h.size()[-1]))  # nframes * N, nbins
+        h = h.reshape(nframes, N, 1, nbins)
+        h = h.permute(1, 2, 3, 0)
+
+        return h
diff --git a/lib/uvr5_pack/lib_v5/model_param_init.py b/lib/uvr5_pack/lib_v5/model_param_init.py
new file mode 100644
index 0000000000000000000000000000000000000000..b995c0bfb1194746187692e2ab1c2a6dbaaaec6c
--- /dev/null
+++ b/lib/uvr5_pack/lib_v5/model_param_init.py
@@ -0,0 +1,69 @@
+import json
+import os
+import pathlib
+
+default_param = {}
+default_param["bins"] = 768
+default_param["unstable_bins"] = 9  # training only
+default_param["reduction_bins"] = 762  # training only
+default_param["sr"] = 44100
+default_param["pre_filter_start"] = 757
+default_param["pre_filter_stop"] = 768
+default_param["band"] = {}
+
+
+default_param["band"][1] = {
+    "sr": 11025,
+    "hl": 128,
+    "n_fft": 960,
+    "crop_start": 0,
+    "crop_stop": 245,
+    "lpf_start": 61,  # inference only
+    "res_type": "polyphase",
+}
+
+default_param["band"][2] = {
+    "sr": 44100,
+    "hl": 512,
+    "n_fft": 1536,
+    "crop_start": 24,
+    "crop_stop": 547,
+    "hpf_start": 81,  # inference only
+    "res_type": "sinc_best",
+}
+
+
+def int_keys(d):
+    r = {}
+    for k, v in d:
+        if k.isdigit():
+            k = int(k)
+        r[k] = v
+    return r
+
+
+class ModelParameters(object):
+    def __init__(self, config_path=""):
+        if ".pth" == pathlib.Path(config_path).suffix:
+            import zipfile
+
+            with zipfile.ZipFile(config_path, "r") as zip:
+                self.param = json.loads(
+                    zip.read("param.json"), object_pairs_hook=int_keys
+                )
+        elif ".json" == pathlib.Path(config_path).suffix:
+            with open(config_path, "r") as f:
+                self.param = json.loads(f.read(), object_pairs_hook=int_keys)
+        else:
+            self.param = default_param
+
+        for k in [
+            "mid_side",
+            "mid_side_b",
+            "mid_side_b2",
+            "stereo_w",
+            "stereo_n",
+            "reverse",
+        ]:
+            if not k in self.param:
+                self.param[k] = False
diff --git a/lib/uvr5_pack/lib_v5/modelparams/1band_sr16000_hl512.json b/lib/uvr5_pack/lib_v5/modelparams/1band_sr16000_hl512.json
new file mode 100644
index 0000000000000000000000000000000000000000..05b4e26892e8aa94c6865b7a8e7008337e69c4bc
--- /dev/null
+++ b/lib/uvr5_pack/lib_v5/modelparams/1band_sr16000_hl512.json
@@ -0,0 +1,19 @@
+{
+  "bins": 1024,
+  "unstable_bins": 0,
+  "reduction_bins": 0,
+  "band": {
+    "1": {
+      "sr": 16000,
+      "hl": 512,
+      "n_fft": 2048,
+      "crop_start": 0,
+      "crop_stop": 1024,
+      "hpf_start": -1,
+      "res_type": "sinc_best"
+    }
+  },
+  "sr": 16000,
+  "pre_filter_start": 1023,
+  "pre_filter_stop": 1024
+}
diff --git a/lib/uvr5_pack/lib_v5/modelparams/1band_sr32000_hl512.json b/lib/uvr5_pack/lib_v5/modelparams/1band_sr32000_hl512.json
new file mode 100644
index 0000000000000000000000000000000000000000..5c8ca23dd7ac6a8800ae5fce5d5fda718ea262ac
--- /dev/null
+++ b/lib/uvr5_pack/lib_v5/modelparams/1band_sr32000_hl512.json
@@ -0,0 +1,19 @@
+{
+  "bins": 1024,
+  "unstable_bins": 0,
+  "reduction_bins": 0,
+  "band": {
+    "1": {
+      "sr": 32000,
+      "hl": 512,
+      "n_fft": 2048,
+      "crop_start": 0,
+      "crop_stop": 1024,
+      "hpf_start": -1,
+      "res_type": "kaiser_fast"
+    }
+  },
+  "sr": 32000,
+  "pre_filter_start": 1000,
+  "pre_filter_stop": 1021
+}
diff --git a/lib/uvr5_pack/lib_v5/modelparams/1band_sr33075_hl384.json b/lib/uvr5_pack/lib_v5/modelparams/1band_sr33075_hl384.json
new file mode 100644
index 0000000000000000000000000000000000000000..7e7ca5d96f65e3b8cf12c3e21a60cc63375cdced
--- /dev/null
+++ b/lib/uvr5_pack/lib_v5/modelparams/1band_sr33075_hl384.json
@@ -0,0 +1,19 @@
+{
+  "bins": 1024,
+  "unstable_bins": 0,
+  "reduction_bins": 0,
+  "band": {
+    "1": {
+      "sr": 33075,
+      "hl": 384,
+      "n_fft": 2048,
+      "crop_start": 0,
+      "crop_stop": 1024,
+      "hpf_start": -1,
+      "res_type": "sinc_best"
+    }
+  },
+  "sr": 33075,
+  "pre_filter_start": 1000,
+  "pre_filter_stop": 1021
+}
diff --git a/lib/uvr5_pack/lib_v5/modelparams/1band_sr44100_hl1024.json b/lib/uvr5_pack/lib_v5/modelparams/1band_sr44100_hl1024.json
new file mode 100644
index 0000000000000000000000000000000000000000..ae9b45f8e1ca4639c93ae705c92e32fac84b9be4
--- /dev/null
+++ b/lib/uvr5_pack/lib_v5/modelparams/1band_sr44100_hl1024.json
@@ -0,0 +1,19 @@
+{
+  "bins": 1024,
+  "unstable_bins": 0,
+  "reduction_bins": 0,
+  "band": {
+    "1": {
+      "sr": 44100,
+      "hl": 1024,
+      "n_fft": 2048,
+      "crop_start": 0,
+      "crop_stop": 1024,
+      "hpf_start": -1,
+      "res_type": "sinc_best"
+    }
+  },
+  "sr": 44100,
+  "pre_filter_start": 1023,
+  "pre_filter_stop": 1024
+}
diff --git a/lib/uvr5_pack/lib_v5/modelparams/1band_sr44100_hl256.json b/lib/uvr5_pack/lib_v5/modelparams/1band_sr44100_hl256.json
new file mode 100644
index 0000000000000000000000000000000000000000..7c439e2a97257f3fd09f85d8a0362192aba7a5f2
--- /dev/null
+++ b/lib/uvr5_pack/lib_v5/modelparams/1band_sr44100_hl256.json
@@ -0,0 +1,19 @@
+{
+  "bins": 256,
+  "unstable_bins": 0,
+  "reduction_bins": 0,
+  "band": {
+    "1": {
+      "sr": 44100,
+      "hl": 256,
+      "n_fft": 512,
+      "crop_start": 0,
+      "crop_stop": 256,
+      "hpf_start": -1,
+      "res_type": "sinc_best"
+    }
+  },
+  "sr": 44100,
+  "pre_filter_start": 256,
+  "pre_filter_stop": 256
+}
diff --git a/lib/uvr5_pack/lib_v5/modelparams/1band_sr44100_hl512.json b/lib/uvr5_pack/lib_v5/modelparams/1band_sr44100_hl512.json
new file mode 100644
index 0000000000000000000000000000000000000000..a33e4f6d06bc576b8d14581d981f486b78c8c351
--- /dev/null
+++ b/lib/uvr5_pack/lib_v5/modelparams/1band_sr44100_hl512.json
@@ -0,0 +1,19 @@
+{
+  "bins": 1024,
+  "unstable_bins": 0,
+  "reduction_bins": 0,
+  "band": {
+    "1": {
+      "sr": 44100,
+      "hl": 512,
+      "n_fft": 2048,
+      "crop_start": 0,
+      "crop_stop": 1024,
+      "hpf_start": -1,
+      "res_type": "sinc_best"
+    }
+  },
+  "sr": 44100,
+  "pre_filter_start": 1023,
+  "pre_filter_stop": 1024
+}
diff --git a/lib/uvr5_pack/lib_v5/modelparams/1band_sr44100_hl512_cut.json b/lib/uvr5_pack/lib_v5/modelparams/1band_sr44100_hl512_cut.json
new file mode 100644
index 0000000000000000000000000000000000000000..25005120395e1e8467b9cf5a377228e8725a62e6
--- /dev/null
+++ b/lib/uvr5_pack/lib_v5/modelparams/1band_sr44100_hl512_cut.json
@@ -0,0 +1,19 @@
+{
+  "bins": 1024,
+  "unstable_bins": 0,
+  "reduction_bins": 0,
+  "band": {
+    "1": {
+      "sr": 44100,
+      "hl": 512,
+      "n_fft": 2048,
+      "crop_start": 0,
+      "crop_stop": 700,
+      "hpf_start": -1,
+      "res_type": "sinc_best"
+    }
+  },
+  "sr": 44100,
+  "pre_filter_start": 1023,
+  "pre_filter_stop": 700
+}
diff --git a/lib/uvr5_pack/lib_v5/modelparams/2band_32000.json b/lib/uvr5_pack/lib_v5/modelparams/2band_32000.json
new file mode 100644
index 0000000000000000000000000000000000000000..479497105f523194f585e5fc6c4292ff2a70b8aa
--- /dev/null
+++ b/lib/uvr5_pack/lib_v5/modelparams/2band_32000.json
@@ -0,0 +1,30 @@
+{
+  "bins": 768,
+  "unstable_bins": 7,
+  "reduction_bins": 705,
+  "band": {
+    "1": {
+      "sr": 6000,
+      "hl": 66,
+      "n_fft": 512,
+      "crop_start": 0,
+      "crop_stop": 240,
+      "lpf_start": 60,
+      "lpf_stop": 118,
+      "res_type": "sinc_fastest"
+    },
+    "2": {
+      "sr": 32000,
+      "hl": 352,
+      "n_fft": 1024,
+      "crop_start": 22,
+      "crop_stop": 505,
+      "hpf_start": 44,
+      "hpf_stop": 23,
+      "res_type": "sinc_medium"
+    }
+  },
+  "sr": 32000,
+  "pre_filter_start": 710,
+  "pre_filter_stop": 731
+}
diff --git a/lib/uvr5_pack/lib_v5/modelparams/2band_44100_lofi.json b/lib/uvr5_pack/lib_v5/modelparams/2band_44100_lofi.json
new file mode 100644
index 0000000000000000000000000000000000000000..ae2ad32fd3632fb9c3c3b6a15e99f6ffc5ff9400
--- /dev/null
+++ b/lib/uvr5_pack/lib_v5/modelparams/2band_44100_lofi.json
@@ -0,0 +1,30 @@
+{
+  "bins": 512,
+  "unstable_bins": 7,
+  "reduction_bins": 510,
+  "band": {
+    "1": {
+      "sr": 11025,
+      "hl": 160,
+      "n_fft": 768,
+      "crop_start": 0,
+      "crop_stop": 192,
+      "lpf_start": 41,
+      "lpf_stop": 139,
+      "res_type": "sinc_fastest"
+    },
+    "2": {
+      "sr": 44100,
+      "hl": 640,
+      "n_fft": 1024,
+      "crop_start": 10,
+      "crop_stop": 320,
+      "hpf_start": 47,
+      "hpf_stop": 15,
+      "res_type": "sinc_medium"
+    }
+  },
+  "sr": 44100,
+  "pre_filter_start": 510,
+  "pre_filter_stop": 512
+}
diff --git a/lib/uvr5_pack/lib_v5/modelparams/2band_48000.json b/lib/uvr5_pack/lib_v5/modelparams/2band_48000.json
new file mode 100644
index 0000000000000000000000000000000000000000..370eab704b7f1b635ff7dbaf819101f5ddee7fa0
--- /dev/null
+++ b/lib/uvr5_pack/lib_v5/modelparams/2band_48000.json
@@ -0,0 +1,30 @@
+{
+  "bins": 768,
+  "unstable_bins": 7,
+  "reduction_bins": 705,
+  "band": {
+    "1": {
+      "sr": 6000,
+      "hl": 66,
+      "n_fft": 512,
+      "crop_start": 0,
+      "crop_stop": 240,
+      "lpf_start": 60,
+      "lpf_stop": 240,
+      "res_type": "sinc_fastest"
+    },
+    "2": {
+      "sr": 48000,
+      "hl": 528,
+      "n_fft": 1536,
+      "crop_start": 22,
+      "crop_stop": 505,
+      "hpf_start": 82,
+      "hpf_stop": 22,
+      "res_type": "sinc_medium"
+    }
+  },
+  "sr": 48000,
+  "pre_filter_start": 710,
+  "pre_filter_stop": 731
+}
diff --git a/lib/uvr5_pack/lib_v5/modelparams/3band_44100.json b/lib/uvr5_pack/lib_v5/modelparams/3band_44100.json
new file mode 100644
index 0000000000000000000000000000000000000000..cc7a51f2b4ad0ab4909cbead55d139442ffeac2c
--- /dev/null
+++ b/lib/uvr5_pack/lib_v5/modelparams/3band_44100.json
@@ -0,0 +1,42 @@
+{
+  "bins": 768,
+  "unstable_bins": 5,
+  "reduction_bins": 733,
+  "band": {
+    "1": {
+      "sr": 11025,
+      "hl": 128,
+      "n_fft": 768,
+      "crop_start": 0,
+      "crop_stop": 278,
+      "lpf_start": 28,
+      "lpf_stop": 140,
+      "res_type": "polyphase"
+    },
+    "2": {
+      "sr": 22050,
+      "hl": 256,
+      "n_fft": 768,
+      "crop_start": 14,
+      "crop_stop": 322,
+      "hpf_start": 70,
+      "hpf_stop": 14,
+      "lpf_start": 283,
+      "lpf_stop": 314,
+      "res_type": "polyphase"
+    },
+    "3": {
+      "sr": 44100,
+      "hl": 512,
+      "n_fft": 768,
+      "crop_start": 131,
+      "crop_stop": 313,
+      "hpf_start": 154,
+      "hpf_stop": 141,
+      "res_type": "sinc_medium"
+    }
+  },
+  "sr": 44100,
+  "pre_filter_start": 757,
+  "pre_filter_stop": 768
+}
diff --git a/lib/uvr5_pack/lib_v5/modelparams/3band_44100_mid.json b/lib/uvr5_pack/lib_v5/modelparams/3band_44100_mid.json
new file mode 100644
index 0000000000000000000000000000000000000000..47623acf6d315779a25412ba18daedb0c3928fa9
--- /dev/null
+++ b/lib/uvr5_pack/lib_v5/modelparams/3band_44100_mid.json
@@ -0,0 +1,43 @@
+{
+  "mid_side": true,
+  "bins": 768,
+  "unstable_bins": 5,
+  "reduction_bins": 733,
+  "band": {
+    "1": {
+      "sr": 11025,
+      "hl": 128,
+      "n_fft": 768,
+      "crop_start": 0,
+      "crop_stop": 278,
+      "lpf_start": 28,
+      "lpf_stop": 140,
+      "res_type": "polyphase"
+    },
+    "2": {
+      "sr": 22050,
+      "hl": 256,
+      "n_fft": 768,
+      "crop_start": 14,
+      "crop_stop": 322,
+      "hpf_start": 70,
+      "hpf_stop": 14,
+      "lpf_start": 283,
+      "lpf_stop": 314,
+      "res_type": "polyphase"
+    },
+    "3": {
+      "sr": 44100,
+      "hl": 512,
+      "n_fft": 768,
+      "crop_start": 131,
+      "crop_stop": 313,
+      "hpf_start": 154,
+      "hpf_stop": 141,
+      "res_type": "sinc_medium"
+    }
+  },
+  "sr": 44100,
+  "pre_filter_start": 757,
+  "pre_filter_stop": 768
+}
diff --git a/lib/uvr5_pack/lib_v5/modelparams/3band_44100_msb2.json b/lib/uvr5_pack/lib_v5/modelparams/3band_44100_msb2.json
new file mode 100644
index 0000000000000000000000000000000000000000..9f9db459d1ab013cac859e0edf5c986881cfd14b
--- /dev/null
+++ b/lib/uvr5_pack/lib_v5/modelparams/3band_44100_msb2.json
@@ -0,0 +1,43 @@
+{
+  "mid_side_b2": true,
+  "bins": 640,
+  "unstable_bins": 7,
+  "reduction_bins": 565,
+  "band": {
+    "1": {
+      "sr": 11025,
+      "hl": 108,
+      "n_fft": 1024,
+      "crop_start": 0,
+      "crop_stop": 187,
+      "lpf_start": 92,
+      "lpf_stop": 186,
+      "res_type": "polyphase"
+    },
+    "2": {
+      "sr": 22050,
+      "hl": 216,
+      "n_fft": 768,
+      "crop_start": 0,
+      "crop_stop": 212,
+      "hpf_start": 68,
+      "hpf_stop": 34,
+      "lpf_start": 174,
+      "lpf_stop": 209,
+      "res_type": "polyphase"
+    },
+    "3": {
+      "sr": 44100,
+      "hl": 432,
+      "n_fft": 640,
+      "crop_start": 66,
+      "crop_stop": 307,
+      "hpf_start": 86,
+      "hpf_stop": 72,
+      "res_type": "kaiser_fast"
+    }
+  },
+  "sr": 44100,
+  "pre_filter_start": 639,
+  "pre_filter_stop": 640
+}
diff --git a/lib/uvr5_pack/lib_v5/modelparams/4band_44100.json b/lib/uvr5_pack/lib_v5/modelparams/4band_44100.json
new file mode 100644
index 0000000000000000000000000000000000000000..68b809af4a5fb1d2580be04d70e054768c0cfe77
--- /dev/null
+++ b/lib/uvr5_pack/lib_v5/modelparams/4band_44100.json
@@ -0,0 +1,54 @@
+{
+  "bins": 768,
+  "unstable_bins": 7,
+  "reduction_bins": 668,
+  "band": {
+    "1": {
+      "sr": 11025,
+      "hl": 128,
+      "n_fft": 1024,
+      "crop_start": 0,
+      "crop_stop": 186,
+      "lpf_start": 37,
+      "lpf_stop": 73,
+      "res_type": "polyphase"
+    },
+    "2": {
+      "sr": 11025,
+      "hl": 128,
+      "n_fft": 512,
+      "crop_start": 4,
+      "crop_stop": 185,
+      "hpf_start": 36,
+      "hpf_stop": 18,
+      "lpf_start": 93,
+      "lpf_stop": 185,
+      "res_type": "polyphase"
+    },
+    "3": {
+      "sr": 22050,
+      "hl": 256,
+      "n_fft": 512,
+      "crop_start": 46,
+      "crop_stop": 186,
+      "hpf_start": 93,
+      "hpf_stop": 46,
+      "lpf_start": 164,
+      "lpf_stop": 186,
+      "res_type": "polyphase"
+    },
+    "4": {
+      "sr": 44100,
+      "hl": 512,
+      "n_fft": 768,
+      "crop_start": 121,
+      "crop_stop": 382,
+      "hpf_start": 138,
+      "hpf_stop": 123,
+      "res_type": "sinc_medium"
+    }
+  },
+  "sr": 44100,
+  "pre_filter_start": 740,
+  "pre_filter_stop": 768
+}
diff --git a/lib/uvr5_pack/lib_v5/modelparams/4band_44100_mid.json b/lib/uvr5_pack/lib_v5/modelparams/4band_44100_mid.json
new file mode 100644
index 0000000000000000000000000000000000000000..82d558887873e406a1038a259b91982f44bfd12a
--- /dev/null
+++ b/lib/uvr5_pack/lib_v5/modelparams/4band_44100_mid.json
@@ -0,0 +1,55 @@
+{
+  "bins": 768,
+  "unstable_bins": 7,
+  "mid_side": true,
+  "reduction_bins": 668,
+  "band": {
+    "1": {
+      "sr": 11025,
+      "hl": 128,
+      "n_fft": 1024,
+      "crop_start": 0,
+      "crop_stop": 186,
+      "lpf_start": 37,
+      "lpf_stop": 73,
+      "res_type": "polyphase"
+    },
+    "2": {
+      "sr": 11025,
+      "hl": 128,
+      "n_fft": 512,
+      "crop_start": 4,
+      "crop_stop": 185,
+      "hpf_start": 36,
+      "hpf_stop": 18,
+      "lpf_start": 93,
+      "lpf_stop": 185,
+      "res_type": "polyphase"
+    },
+    "3": {
+      "sr": 22050,
+      "hl": 256,
+      "n_fft": 512,
+      "crop_start": 46,
+      "crop_stop": 186,
+      "hpf_start": 93,
+      "hpf_stop": 46,
+      "lpf_start": 164,
+      "lpf_stop": 186,
+      "res_type": "polyphase"
+    },
+    "4": {
+      "sr": 44100,
+      "hl": 512,
+      "n_fft": 768,
+      "crop_start": 121,
+      "crop_stop": 382,
+      "hpf_start": 138,
+      "hpf_stop": 123,
+      "res_type": "sinc_medium"
+    }
+  },
+  "sr": 44100,
+  "pre_filter_start": 740,
+  "pre_filter_stop": 768
+}
diff --git a/lib/uvr5_pack/lib_v5/modelparams/4band_44100_msb.json b/lib/uvr5_pack/lib_v5/modelparams/4band_44100_msb.json
new file mode 100644
index 0000000000000000000000000000000000000000..8568d9a89d6c21ca5e640e29cc4cfa85f1c3179f
--- /dev/null
+++ b/lib/uvr5_pack/lib_v5/modelparams/4band_44100_msb.json
@@ -0,0 +1,55 @@
+{
+  "mid_side_b": true,
+  "bins": 768,
+  "unstable_bins": 7,
+  "reduction_bins": 668,
+  "band": {
+    "1": {
+      "sr": 11025,
+      "hl": 128,
+      "n_fft": 1024,
+      "crop_start": 0,
+      "crop_stop": 186,
+      "lpf_start": 37,
+      "lpf_stop": 73,
+      "res_type": "polyphase"
+    },
+    "2": {
+      "sr": 11025,
+      "hl": 128,
+      "n_fft": 512,
+      "crop_start": 4,
+      "crop_stop": 185,
+      "hpf_start": 36,
+      "hpf_stop": 18,
+      "lpf_start": 93,
+      "lpf_stop": 185,
+      "res_type": "polyphase"
+    },
+    "3": {
+      "sr": 22050,
+      "hl": 256,
+      "n_fft": 512,
+      "crop_start": 46,
+      "crop_stop": 186,
+      "hpf_start": 93,
+      "hpf_stop": 46,
+      "lpf_start": 164,
+      "lpf_stop": 186,
+      "res_type": "polyphase"
+    },
+    "4": {
+      "sr": 44100,
+      "hl": 512,
+      "n_fft": 768,
+      "crop_start": 121,
+      "crop_stop": 382,
+      "hpf_start": 138,
+      "hpf_stop": 123,
+      "res_type": "sinc_medium"
+    }
+  },
+  "sr": 44100,
+  "pre_filter_start": 740,
+  "pre_filter_stop": 768
+}
diff --git a/lib/uvr5_pack/lib_v5/modelparams/4band_44100_msb2.json b/lib/uvr5_pack/lib_v5/modelparams/4band_44100_msb2.json
new file mode 100644
index 0000000000000000000000000000000000000000..8568d9a89d6c21ca5e640e29cc4cfa85f1c3179f
--- /dev/null
+++ b/lib/uvr5_pack/lib_v5/modelparams/4band_44100_msb2.json
@@ -0,0 +1,55 @@
+{
+  "mid_side_b": true,
+  "bins": 768,
+  "unstable_bins": 7,
+  "reduction_bins": 668,
+  "band": {
+    "1": {
+      "sr": 11025,
+      "hl": 128,
+      "n_fft": 1024,
+      "crop_start": 0,
+      "crop_stop": 186,
+      "lpf_start": 37,
+      "lpf_stop": 73,
+      "res_type": "polyphase"
+    },
+    "2": {
+      "sr": 11025,
+      "hl": 128,
+      "n_fft": 512,
+      "crop_start": 4,
+      "crop_stop": 185,
+      "hpf_start": 36,
+      "hpf_stop": 18,
+      "lpf_start": 93,
+      "lpf_stop": 185,
+      "res_type": "polyphase"
+    },
+    "3": {
+      "sr": 22050,
+      "hl": 256,
+      "n_fft": 512,
+      "crop_start": 46,
+      "crop_stop": 186,
+      "hpf_start": 93,
+      "hpf_stop": 46,
+      "lpf_start": 164,
+      "lpf_stop": 186,
+      "res_type": "polyphase"
+    },
+    "4": {
+      "sr": 44100,
+      "hl": 512,
+      "n_fft": 768,
+      "crop_start": 121,
+      "crop_stop": 382,
+      "hpf_start": 138,
+      "hpf_stop": 123,
+      "res_type": "sinc_medium"
+    }
+  },
+  "sr": 44100,
+  "pre_filter_start": 740,
+  "pre_filter_stop": 768
+}
diff --git a/lib/uvr5_pack/lib_v5/modelparams/4band_44100_reverse.json b/lib/uvr5_pack/lib_v5/modelparams/4band_44100_reverse.json
new file mode 100644
index 0000000000000000000000000000000000000000..52bf7e91f2c853b7d261b237224c1f2b284cef91
--- /dev/null
+++ b/lib/uvr5_pack/lib_v5/modelparams/4band_44100_reverse.json
@@ -0,0 +1,55 @@
+{
+  "reverse": true,
+  "bins": 768,
+  "unstable_bins": 7,
+  "reduction_bins": 668,
+  "band": {
+    "1": {
+      "sr": 11025,
+      "hl": 128,
+      "n_fft": 1024,
+      "crop_start": 0,
+      "crop_stop": 186,
+      "lpf_start": 37,
+      "lpf_stop": 73,
+      "res_type": "polyphase"
+    },
+    "2": {
+      "sr": 11025,
+      "hl": 128,
+      "n_fft": 512,
+      "crop_start": 4,
+      "crop_stop": 185,
+      "hpf_start": 36,
+      "hpf_stop": 18,
+      "lpf_start": 93,
+      "lpf_stop": 185,
+      "res_type": "polyphase"
+    },
+    "3": {
+      "sr": 22050,
+      "hl": 256,
+      "n_fft": 512,
+      "crop_start": 46,
+      "crop_stop": 186,
+      "hpf_start": 93,
+      "hpf_stop": 46,
+      "lpf_start": 164,
+      "lpf_stop": 186,
+      "res_type": "polyphase"
+    },
+    "4": {
+      "sr": 44100,
+      "hl": 512,
+      "n_fft": 768,
+      "crop_start": 121,
+      "crop_stop": 382,
+      "hpf_start": 138,
+      "hpf_stop": 123,
+      "res_type": "sinc_medium"
+    }
+  },
+  "sr": 44100,
+  "pre_filter_start": 740,
+  "pre_filter_stop": 768
+}
diff --git a/lib/uvr5_pack/lib_v5/modelparams/4band_44100_sw.json b/lib/uvr5_pack/lib_v5/modelparams/4band_44100_sw.json
new file mode 100644
index 0000000000000000000000000000000000000000..0efb1bcab2f2a23a1bb9d81de6ae5bcc90b2daf8
--- /dev/null
+++ b/lib/uvr5_pack/lib_v5/modelparams/4band_44100_sw.json
@@ -0,0 +1,55 @@
+{
+  "stereo_w": true,
+  "bins": 768,
+  "unstable_bins": 7,
+  "reduction_bins": 668,
+  "band": {
+    "1": {
+      "sr": 11025,
+      "hl": 128,
+      "n_fft": 1024,
+      "crop_start": 0,
+      "crop_stop": 186,
+      "lpf_start": 37,
+      "lpf_stop": 73,
+      "res_type": "polyphase"
+    },
+    "2": {
+      "sr": 11025,
+      "hl": 128,
+      "n_fft": 512,
+      "crop_start": 4,
+      "crop_stop": 185,
+      "hpf_start": 36,
+      "hpf_stop": 18,
+      "lpf_start": 93,
+      "lpf_stop": 185,
+      "res_type": "polyphase"
+    },
+    "3": {
+      "sr": 22050,
+      "hl": 256,
+      "n_fft": 512,
+      "crop_start": 46,
+      "crop_stop": 186,
+      "hpf_start": 93,
+      "hpf_stop": 46,
+      "lpf_start": 164,
+      "lpf_stop": 186,
+      "res_type": "polyphase"
+    },
+    "4": {
+      "sr": 44100,
+      "hl": 512,
+      "n_fft": 768,
+      "crop_start": 121,
+      "crop_stop": 382,
+      "hpf_start": 138,
+      "hpf_stop": 123,
+      "res_type": "sinc_medium"
+    }
+  },
+  "sr": 44100,
+  "pre_filter_start": 740,
+  "pre_filter_stop": 768
+}
diff --git a/lib/uvr5_pack/lib_v5/modelparams/4band_v2.json b/lib/uvr5_pack/lib_v5/modelparams/4band_v2.json
new file mode 100644
index 0000000000000000000000000000000000000000..ec8f8c60236c937de4ea46352c69cff3a7776168
--- /dev/null
+++ b/lib/uvr5_pack/lib_v5/modelparams/4band_v2.json
@@ -0,0 +1,54 @@
+{
+  "bins": 672,
+  "unstable_bins": 8,
+  "reduction_bins": 637,
+  "band": {
+    "1": {
+      "sr": 7350,
+      "hl": 80,
+      "n_fft": 640,
+      "crop_start": 0,
+      "crop_stop": 85,
+      "lpf_start": 25,
+      "lpf_stop": 53,
+      "res_type": "polyphase"
+    },
+    "2": {
+      "sr": 7350,
+      "hl": 80,
+      "n_fft": 320,
+      "crop_start": 4,
+      "crop_stop": 87,
+      "hpf_start": 25,
+      "hpf_stop": 12,
+      "lpf_start": 31,
+      "lpf_stop": 62,
+      "res_type": "polyphase"
+    },
+    "3": {
+      "sr": 14700,
+      "hl": 160,
+      "n_fft": 512,
+      "crop_start": 17,
+      "crop_stop": 216,
+      "hpf_start": 48,
+      "hpf_stop": 24,
+      "lpf_start": 139,
+      "lpf_stop": 210,
+      "res_type": "polyphase"
+    },
+    "4": {
+      "sr": 44100,
+      "hl": 480,
+      "n_fft": 960,
+      "crop_start": 78,
+      "crop_stop": 383,
+      "hpf_start": 130,
+      "hpf_stop": 86,
+      "res_type": "kaiser_fast"
+    }
+  },
+  "sr": 44100,
+  "pre_filter_start": 668,
+  "pre_filter_stop": 672
+}
diff --git a/lib/uvr5_pack/lib_v5/modelparams/4band_v2_sn.json b/lib/uvr5_pack/lib_v5/modelparams/4band_v2_sn.json
new file mode 100644
index 0000000000000000000000000000000000000000..3fa4298b4b5325e90e179f9d8843bf42d2f41204
--- /dev/null
+++ b/lib/uvr5_pack/lib_v5/modelparams/4band_v2_sn.json
@@ -0,0 +1,55 @@
+{
+  "bins": 672,
+  "unstable_bins": 8,
+  "reduction_bins": 637,
+  "band": {
+    "1": {
+      "sr": 7350,
+      "hl": 80,
+      "n_fft": 640,
+      "crop_start": 0,
+      "crop_stop": 85,
+      "lpf_start": 25,
+      "lpf_stop": 53,
+      "res_type": "polyphase"
+    },
+    "2": {
+      "sr": 7350,
+      "hl": 80,
+      "n_fft": 320,
+      "crop_start": 4,
+      "crop_stop": 87,
+      "hpf_start": 25,
+      "hpf_stop": 12,
+      "lpf_start": 31,
+      "lpf_stop": 62,
+      "res_type": "polyphase"
+    },
+    "3": {
+      "sr": 14700,
+      "hl": 160,
+      "n_fft": 512,
+      "crop_start": 17,
+      "crop_stop": 216,
+      "hpf_start": 48,
+      "hpf_stop": 24,
+      "lpf_start": 139,
+      "lpf_stop": 210,
+      "res_type": "polyphase"
+    },
+    "4": {
+      "sr": 44100,
+      "hl": 480,
+      "n_fft": 960,
+      "crop_start": 78,
+      "crop_stop": 383,
+      "hpf_start": 130,
+      "hpf_stop": 86,
+      "convert_channels": "stereo_n",
+      "res_type": "kaiser_fast"
+    }
+  },
+  "sr": 44100,
+  "pre_filter_start": 668,
+  "pre_filter_stop": 672
+}
diff --git a/lib/uvr5_pack/lib_v5/modelparams/4band_v3.json b/lib/uvr5_pack/lib_v5/modelparams/4band_v3.json
new file mode 100644
index 0000000000000000000000000000000000000000..f0f5d4a55adf1cc7d8cf0bb79a1c98a588c6c726
--- /dev/null
+++ b/lib/uvr5_pack/lib_v5/modelparams/4band_v3.json
@@ -0,0 +1,54 @@
+{
+  "bins": 672,
+  "unstable_bins": 8,
+  "reduction_bins": 530,
+  "band": {
+    "1": {
+      "sr": 7350,
+      "hl": 80,
+      "n_fft": 640,
+      "crop_start": 0,
+      "crop_stop": 85,
+      "lpf_start": 25,
+      "lpf_stop": 53,
+      "res_type": "polyphase"
+    },
+    "2": {
+      "sr": 7350,
+      "hl": 80,
+      "n_fft": 320,
+      "crop_start": 4,
+      "crop_stop": 87,
+      "hpf_start": 25,
+      "hpf_stop": 12,
+      "lpf_start": 31,
+      "lpf_stop": 62,
+      "res_type": "polyphase"
+    },
+    "3": {
+      "sr": 14700,
+      "hl": 160,
+      "n_fft": 512,
+      "crop_start": 17,
+      "crop_stop": 216,
+      "hpf_start": 48,
+      "hpf_stop": 24,
+      "lpf_start": 139,
+      "lpf_stop": 210,
+      "res_type": "polyphase"
+    },
+    "4": {
+      "sr": 44100,
+      "hl": 480,
+      "n_fft": 960,
+      "crop_start": 78,
+      "crop_stop": 383,
+      "hpf_start": 130,
+      "hpf_stop": 86,
+      "res_type": "kaiser_fast"
+    }
+  },
+  "sr": 44100,
+  "pre_filter_start": 668,
+  "pre_filter_stop": 672
+}
diff --git a/lib/uvr5_pack/lib_v5/modelparams/ensemble.json b/lib/uvr5_pack/lib_v5/modelparams/ensemble.json
new file mode 100644
index 0000000000000000000000000000000000000000..c7bd04ba7060e9fae4f827a39624d483f9cd7317
--- /dev/null
+++ b/lib/uvr5_pack/lib_v5/modelparams/ensemble.json
@@ -0,0 +1,43 @@
+{
+  "mid_side_b2": true,
+  "bins": 1280,
+  "unstable_bins": 7,
+  "reduction_bins": 565,
+  "band": {
+    "1": {
+      "sr": 11025,
+      "hl": 108,
+      "n_fft": 2048,
+      "crop_start": 0,
+      "crop_stop": 374,
+      "lpf_start": 92,
+      "lpf_stop": 186,
+      "res_type": "polyphase"
+    },
+    "2": {
+      "sr": 22050,
+      "hl": 216,
+      "n_fft": 1536,
+      "crop_start": 0,
+      "crop_stop": 424,
+      "hpf_start": 68,
+      "hpf_stop": 34,
+      "lpf_start": 348,
+      "lpf_stop": 418,
+      "res_type": "polyphase"
+    },
+    "3": {
+      "sr": 44100,
+      "hl": 432,
+      "n_fft": 1280,
+      "crop_start": 132,
+      "crop_stop": 614,
+      "hpf_start": 172,
+      "hpf_stop": 144,
+      "res_type": "polyphase"
+    }
+  },
+  "sr": 44100,
+  "pre_filter_start": 1280,
+  "pre_filter_stop": 1280
+}
diff --git a/lib/uvr5_pack/lib_v5/nets.py b/lib/uvr5_pack/lib_v5/nets.py
new file mode 100644
index 0000000000000000000000000000000000000000..db4c5e339f7a96cd24ed1cbbf88c4f35d5031309
--- /dev/null
+++ b/lib/uvr5_pack/lib_v5/nets.py
@@ -0,0 +1,123 @@
+import torch
+from torch import nn
+import torch.nn.functional as F
+
+import layers
+from . import spec_utils
+
+
+class BaseASPPNet(nn.Module):
+    def __init__(self, nin, ch, dilations=(4, 8, 16)):
+        super(BaseASPPNet, self).__init__()
+        self.enc1 = layers.Encoder(nin, ch, 3, 2, 1)
+        self.enc2 = layers.Encoder(ch, ch * 2, 3, 2, 1)
+        self.enc3 = layers.Encoder(ch * 2, ch * 4, 3, 2, 1)
+        self.enc4 = layers.Encoder(ch * 4, ch * 8, 3, 2, 1)
+
+        self.aspp = layers.ASPPModule(ch * 8, ch * 16, dilations)
+
+        self.dec4 = layers.Decoder(ch * (8 + 16), ch * 8, 3, 1, 1)
+        self.dec3 = layers.Decoder(ch * (4 + 8), ch * 4, 3, 1, 1)
+        self.dec2 = layers.Decoder(ch * (2 + 4), ch * 2, 3, 1, 1)
+        self.dec1 = layers.Decoder(ch * (1 + 2), ch, 3, 1, 1)
+
+    def __call__(self, x):
+        h, e1 = self.enc1(x)
+        h, e2 = self.enc2(h)
+        h, e3 = self.enc3(h)
+        h, e4 = self.enc4(h)
+
+        h = self.aspp(h)
+
+        h = self.dec4(h, e4)
+        h = self.dec3(h, e3)
+        h = self.dec2(h, e2)
+        h = self.dec1(h, e1)
+
+        return h
+
+
+class CascadedASPPNet(nn.Module):
+    def __init__(self, n_fft):
+        super(CascadedASPPNet, self).__init__()
+        self.stg1_low_band_net = BaseASPPNet(2, 16)
+        self.stg1_high_band_net = BaseASPPNet(2, 16)
+
+        self.stg2_bridge = layers.Conv2DBNActiv(18, 8, 1, 1, 0)
+        self.stg2_full_band_net = BaseASPPNet(8, 16)
+
+        self.stg3_bridge = layers.Conv2DBNActiv(34, 16, 1, 1, 0)
+        self.stg3_full_band_net = BaseASPPNet(16, 32)
+
+        self.out = nn.Conv2d(32, 2, 1, bias=False)
+        self.aux1_out = nn.Conv2d(16, 2, 1, bias=False)
+        self.aux2_out = nn.Conv2d(16, 2, 1, bias=False)
+
+        self.max_bin = n_fft // 2
+        self.output_bin = n_fft // 2 + 1
+
+        self.offset = 128
+
+    def forward(self, x, aggressiveness=None):
+        mix = x.detach()
+        x = x.clone()
+
+        x = x[:, :, : self.max_bin]
+
+        bandw = x.size()[2] // 2
+        aux1 = torch.cat(
+            [
+                self.stg1_low_band_net(x[:, :, :bandw]),
+                self.stg1_high_band_net(x[:, :, bandw:]),
+            ],
+            dim=2,
+        )
+
+        h = torch.cat([x, aux1], dim=1)
+        aux2 = self.stg2_full_band_net(self.stg2_bridge(h))
+
+        h = torch.cat([x, aux1, aux2], dim=1)
+        h = self.stg3_full_band_net(self.stg3_bridge(h))
+
+        mask = torch.sigmoid(self.out(h))
+        mask = F.pad(
+            input=mask,
+            pad=(0, 0, 0, self.output_bin - mask.size()[2]),
+            mode="replicate",
+        )
+
+        if self.training:
+            aux1 = torch.sigmoid(self.aux1_out(aux1))
+            aux1 = F.pad(
+                input=aux1,
+                pad=(0, 0, 0, self.output_bin - aux1.size()[2]),
+                mode="replicate",
+            )
+            aux2 = torch.sigmoid(self.aux2_out(aux2))
+            aux2 = F.pad(
+                input=aux2,
+                pad=(0, 0, 0, self.output_bin - aux2.size()[2]),
+                mode="replicate",
+            )
+            return mask * mix, aux1 * mix, aux2 * mix
+        else:
+            if aggressiveness:
+                mask[:, :, : aggressiveness["split_bin"]] = torch.pow(
+                    mask[:, :, : aggressiveness["split_bin"]],
+                    1 + aggressiveness["value"] / 3,
+                )
+                mask[:, :, aggressiveness["split_bin"] :] = torch.pow(
+                    mask[:, :, aggressiveness["split_bin"] :],
+                    1 + aggressiveness["value"],
+                )
+
+            return mask * mix
+
+    def predict(self, x_mag, aggressiveness=None):
+        h = self.forward(x_mag, aggressiveness)
+
+        if self.offset > 0:
+            h = h[:, :, :, self.offset : -self.offset]
+            assert h.size()[3] > 0
+
+        return h
diff --git a/lib/uvr5_pack/lib_v5/nets_123812KB.py b/lib/uvr5_pack/lib_v5/nets_123812KB.py
new file mode 100644
index 0000000000000000000000000000000000000000..becbfae85683a13bbb19d3ea6c840da24e61e01e
--- /dev/null
+++ b/lib/uvr5_pack/lib_v5/nets_123812KB.py
@@ -0,0 +1,122 @@
+import torch
+from torch import nn
+import torch.nn.functional as F
+
+from . import layers_123821KB as layers
+
+
+class BaseASPPNet(nn.Module):
+    def __init__(self, nin, ch, dilations=(4, 8, 16)):
+        super(BaseASPPNet, self).__init__()
+        self.enc1 = layers.Encoder(nin, ch, 3, 2, 1)
+        self.enc2 = layers.Encoder(ch, ch * 2, 3, 2, 1)
+        self.enc3 = layers.Encoder(ch * 2, ch * 4, 3, 2, 1)
+        self.enc4 = layers.Encoder(ch * 4, ch * 8, 3, 2, 1)
+
+        self.aspp = layers.ASPPModule(ch * 8, ch * 16, dilations)
+
+        self.dec4 = layers.Decoder(ch * (8 + 16), ch * 8, 3, 1, 1)
+        self.dec3 = layers.Decoder(ch * (4 + 8), ch * 4, 3, 1, 1)
+        self.dec2 = layers.Decoder(ch * (2 + 4), ch * 2, 3, 1, 1)
+        self.dec1 = layers.Decoder(ch * (1 + 2), ch, 3, 1, 1)
+
+    def __call__(self, x):
+        h, e1 = self.enc1(x)
+        h, e2 = self.enc2(h)
+        h, e3 = self.enc3(h)
+        h, e4 = self.enc4(h)
+
+        h = self.aspp(h)
+
+        h = self.dec4(h, e4)
+        h = self.dec3(h, e3)
+        h = self.dec2(h, e2)
+        h = self.dec1(h, e1)
+
+        return h
+
+
+class CascadedASPPNet(nn.Module):
+    def __init__(self, n_fft):
+        super(CascadedASPPNet, self).__init__()
+        self.stg1_low_band_net = BaseASPPNet(2, 32)
+        self.stg1_high_band_net = BaseASPPNet(2, 32)
+
+        self.stg2_bridge = layers.Conv2DBNActiv(34, 16, 1, 1, 0)
+        self.stg2_full_band_net = BaseASPPNet(16, 32)
+
+        self.stg3_bridge = layers.Conv2DBNActiv(66, 32, 1, 1, 0)
+        self.stg3_full_band_net = BaseASPPNet(32, 64)
+
+        self.out = nn.Conv2d(64, 2, 1, bias=False)
+        self.aux1_out = nn.Conv2d(32, 2, 1, bias=False)
+        self.aux2_out = nn.Conv2d(32, 2, 1, bias=False)
+
+        self.max_bin = n_fft // 2
+        self.output_bin = n_fft // 2 + 1
+
+        self.offset = 128
+
+    def forward(self, x, aggressiveness=None):
+        mix = x.detach()
+        x = x.clone()
+
+        x = x[:, :, : self.max_bin]
+
+        bandw = x.size()[2] // 2
+        aux1 = torch.cat(
+            [
+                self.stg1_low_band_net(x[:, :, :bandw]),
+                self.stg1_high_band_net(x[:, :, bandw:]),
+            ],
+            dim=2,
+        )
+
+        h = torch.cat([x, aux1], dim=1)
+        aux2 = self.stg2_full_band_net(self.stg2_bridge(h))
+
+        h = torch.cat([x, aux1, aux2], dim=1)
+        h = self.stg3_full_band_net(self.stg3_bridge(h))
+
+        mask = torch.sigmoid(self.out(h))
+        mask = F.pad(
+            input=mask,
+            pad=(0, 0, 0, self.output_bin - mask.size()[2]),
+            mode="replicate",
+        )
+
+        if self.training:
+            aux1 = torch.sigmoid(self.aux1_out(aux1))
+            aux1 = F.pad(
+                input=aux1,
+                pad=(0, 0, 0, self.output_bin - aux1.size()[2]),
+                mode="replicate",
+            )
+            aux2 = torch.sigmoid(self.aux2_out(aux2))
+            aux2 = F.pad(
+                input=aux2,
+                pad=(0, 0, 0, self.output_bin - aux2.size()[2]),
+                mode="replicate",
+            )
+            return mask * mix, aux1 * mix, aux2 * mix
+        else:
+            if aggressiveness:
+                mask[:, :, : aggressiveness["split_bin"]] = torch.pow(
+                    mask[:, :, : aggressiveness["split_bin"]],
+                    1 + aggressiveness["value"] / 3,
+                )
+                mask[:, :, aggressiveness["split_bin"] :] = torch.pow(
+                    mask[:, :, aggressiveness["split_bin"] :],
+                    1 + aggressiveness["value"],
+                )
+
+            return mask * mix
+
+    def predict(self, x_mag, aggressiveness=None):
+        h = self.forward(x_mag, aggressiveness)
+
+        if self.offset > 0:
+            h = h[:, :, :, self.offset : -self.offset]
+            assert h.size()[3] > 0
+
+        return h
diff --git a/lib/uvr5_pack/lib_v5/nets_123821KB.py b/lib/uvr5_pack/lib_v5/nets_123821KB.py
new file mode 100644
index 0000000000000000000000000000000000000000..becbfae85683a13bbb19d3ea6c840da24e61e01e
--- /dev/null
+++ b/lib/uvr5_pack/lib_v5/nets_123821KB.py
@@ -0,0 +1,122 @@
+import torch
+from torch import nn
+import torch.nn.functional as F
+
+from . import layers_123821KB as layers
+
+
+class BaseASPPNet(nn.Module):
+    def __init__(self, nin, ch, dilations=(4, 8, 16)):
+        super(BaseASPPNet, self).__init__()
+        self.enc1 = layers.Encoder(nin, ch, 3, 2, 1)
+        self.enc2 = layers.Encoder(ch, ch * 2, 3, 2, 1)
+        self.enc3 = layers.Encoder(ch * 2, ch * 4, 3, 2, 1)
+        self.enc4 = layers.Encoder(ch * 4, ch * 8, 3, 2, 1)
+
+        self.aspp = layers.ASPPModule(ch * 8, ch * 16, dilations)
+
+        self.dec4 = layers.Decoder(ch * (8 + 16), ch * 8, 3, 1, 1)
+        self.dec3 = layers.Decoder(ch * (4 + 8), ch * 4, 3, 1, 1)
+        self.dec2 = layers.Decoder(ch * (2 + 4), ch * 2, 3, 1, 1)
+        self.dec1 = layers.Decoder(ch * (1 + 2), ch, 3, 1, 1)
+
+    def __call__(self, x):
+        h, e1 = self.enc1(x)
+        h, e2 = self.enc2(h)
+        h, e3 = self.enc3(h)
+        h, e4 = self.enc4(h)
+
+        h = self.aspp(h)
+
+        h = self.dec4(h, e4)
+        h = self.dec3(h, e3)
+        h = self.dec2(h, e2)
+        h = self.dec1(h, e1)
+
+        return h
+
+
+class CascadedASPPNet(nn.Module):
+    def __init__(self, n_fft):
+        super(CascadedASPPNet, self).__init__()
+        self.stg1_low_band_net = BaseASPPNet(2, 32)
+        self.stg1_high_band_net = BaseASPPNet(2, 32)
+
+        self.stg2_bridge = layers.Conv2DBNActiv(34, 16, 1, 1, 0)
+        self.stg2_full_band_net = BaseASPPNet(16, 32)
+
+        self.stg3_bridge = layers.Conv2DBNActiv(66, 32, 1, 1, 0)
+        self.stg3_full_band_net = BaseASPPNet(32, 64)
+
+        self.out = nn.Conv2d(64, 2, 1, bias=False)
+        self.aux1_out = nn.Conv2d(32, 2, 1, bias=False)
+        self.aux2_out = nn.Conv2d(32, 2, 1, bias=False)
+
+        self.max_bin = n_fft // 2
+        self.output_bin = n_fft // 2 + 1
+
+        self.offset = 128
+
+    def forward(self, x, aggressiveness=None):
+        mix = x.detach()
+        x = x.clone()
+
+        x = x[:, :, : self.max_bin]
+
+        bandw = x.size()[2] // 2
+        aux1 = torch.cat(
+            [
+                self.stg1_low_band_net(x[:, :, :bandw]),
+                self.stg1_high_band_net(x[:, :, bandw:]),
+            ],
+            dim=2,
+        )
+
+        h = torch.cat([x, aux1], dim=1)
+        aux2 = self.stg2_full_band_net(self.stg2_bridge(h))
+
+        h = torch.cat([x, aux1, aux2], dim=1)
+        h = self.stg3_full_band_net(self.stg3_bridge(h))
+
+        mask = torch.sigmoid(self.out(h))
+        mask = F.pad(
+            input=mask,
+            pad=(0, 0, 0, self.output_bin - mask.size()[2]),
+            mode="replicate",
+        )
+
+        if self.training:
+            aux1 = torch.sigmoid(self.aux1_out(aux1))
+            aux1 = F.pad(
+                input=aux1,
+                pad=(0, 0, 0, self.output_bin - aux1.size()[2]),
+                mode="replicate",
+            )
+            aux2 = torch.sigmoid(self.aux2_out(aux2))
+            aux2 = F.pad(
+                input=aux2,
+                pad=(0, 0, 0, self.output_bin - aux2.size()[2]),
+                mode="replicate",
+            )
+            return mask * mix, aux1 * mix, aux2 * mix
+        else:
+            if aggressiveness:
+                mask[:, :, : aggressiveness["split_bin"]] = torch.pow(
+                    mask[:, :, : aggressiveness["split_bin"]],
+                    1 + aggressiveness["value"] / 3,
+                )
+                mask[:, :, aggressiveness["split_bin"] :] = torch.pow(
+                    mask[:, :, aggressiveness["split_bin"] :],
+                    1 + aggressiveness["value"],
+                )
+
+            return mask * mix
+
+    def predict(self, x_mag, aggressiveness=None):
+        h = self.forward(x_mag, aggressiveness)
+
+        if self.offset > 0:
+            h = h[:, :, :, self.offset : -self.offset]
+            assert h.size()[3] > 0
+
+        return h
diff --git a/lib/uvr5_pack/lib_v5/nets_33966KB.py b/lib/uvr5_pack/lib_v5/nets_33966KB.py
new file mode 100644
index 0000000000000000000000000000000000000000..b8986f968dc5383e65d35aac6e4367299de3378b
--- /dev/null
+++ b/lib/uvr5_pack/lib_v5/nets_33966KB.py
@@ -0,0 +1,122 @@
+import torch
+from torch import nn
+import torch.nn.functional as F
+
+from . import layers_33966KB as layers
+
+
+class BaseASPPNet(nn.Module):
+    def __init__(self, nin, ch, dilations=(4, 8, 16, 32)):
+        super(BaseASPPNet, self).__init__()
+        self.enc1 = layers.Encoder(nin, ch, 3, 2, 1)
+        self.enc2 = layers.Encoder(ch, ch * 2, 3, 2, 1)
+        self.enc3 = layers.Encoder(ch * 2, ch * 4, 3, 2, 1)
+        self.enc4 = layers.Encoder(ch * 4, ch * 8, 3, 2, 1)
+
+        self.aspp = layers.ASPPModule(ch * 8, ch * 16, dilations)
+
+        self.dec4 = layers.Decoder(ch * (8 + 16), ch * 8, 3, 1, 1)
+        self.dec3 = layers.Decoder(ch * (4 + 8), ch * 4, 3, 1, 1)
+        self.dec2 = layers.Decoder(ch * (2 + 4), ch * 2, 3, 1, 1)
+        self.dec1 = layers.Decoder(ch * (1 + 2), ch, 3, 1, 1)
+
+    def __call__(self, x):
+        h, e1 = self.enc1(x)
+        h, e2 = self.enc2(h)
+        h, e3 = self.enc3(h)
+        h, e4 = self.enc4(h)
+
+        h = self.aspp(h)
+
+        h = self.dec4(h, e4)
+        h = self.dec3(h, e3)
+        h = self.dec2(h, e2)
+        h = self.dec1(h, e1)
+
+        return h
+
+
+class CascadedASPPNet(nn.Module):
+    def __init__(self, n_fft):
+        super(CascadedASPPNet, self).__init__()
+        self.stg1_low_band_net = BaseASPPNet(2, 16)
+        self.stg1_high_band_net = BaseASPPNet(2, 16)
+
+        self.stg2_bridge = layers.Conv2DBNActiv(18, 8, 1, 1, 0)
+        self.stg2_full_band_net = BaseASPPNet(8, 16)
+
+        self.stg3_bridge = layers.Conv2DBNActiv(34, 16, 1, 1, 0)
+        self.stg3_full_band_net = BaseASPPNet(16, 32)
+
+        self.out = nn.Conv2d(32, 2, 1, bias=False)
+        self.aux1_out = nn.Conv2d(16, 2, 1, bias=False)
+        self.aux2_out = nn.Conv2d(16, 2, 1, bias=False)
+
+        self.max_bin = n_fft // 2
+        self.output_bin = n_fft // 2 + 1
+
+        self.offset = 128
+
+    def forward(self, x, aggressiveness=None):
+        mix = x.detach()
+        x = x.clone()
+
+        x = x[:, :, : self.max_bin]
+
+        bandw = x.size()[2] // 2
+        aux1 = torch.cat(
+            [
+                self.stg1_low_band_net(x[:, :, :bandw]),
+                self.stg1_high_band_net(x[:, :, bandw:]),
+            ],
+            dim=2,
+        )
+
+        h = torch.cat([x, aux1], dim=1)
+        aux2 = self.stg2_full_band_net(self.stg2_bridge(h))
+
+        h = torch.cat([x, aux1, aux2], dim=1)
+        h = self.stg3_full_band_net(self.stg3_bridge(h))
+
+        mask = torch.sigmoid(self.out(h))
+        mask = F.pad(
+            input=mask,
+            pad=(0, 0, 0, self.output_bin - mask.size()[2]),
+            mode="replicate",
+        )
+
+        if self.training:
+            aux1 = torch.sigmoid(self.aux1_out(aux1))
+            aux1 = F.pad(
+                input=aux1,
+                pad=(0, 0, 0, self.output_bin - aux1.size()[2]),
+                mode="replicate",
+            )
+            aux2 = torch.sigmoid(self.aux2_out(aux2))
+            aux2 = F.pad(
+                input=aux2,
+                pad=(0, 0, 0, self.output_bin - aux2.size()[2]),
+                mode="replicate",
+            )
+            return mask * mix, aux1 * mix, aux2 * mix
+        else:
+            if aggressiveness:
+                mask[:, :, : aggressiveness["split_bin"]] = torch.pow(
+                    mask[:, :, : aggressiveness["split_bin"]],
+                    1 + aggressiveness["value"] / 3,
+                )
+                mask[:, :, aggressiveness["split_bin"] :] = torch.pow(
+                    mask[:, :, aggressiveness["split_bin"] :],
+                    1 + aggressiveness["value"],
+                )
+
+            return mask * mix
+
+    def predict(self, x_mag, aggressiveness=None):
+        h = self.forward(x_mag, aggressiveness)
+
+        if self.offset > 0:
+            h = h[:, :, :, self.offset : -self.offset]
+            assert h.size()[3] > 0
+
+        return h
diff --git a/lib/uvr5_pack/lib_v5/nets_537227KB.py b/lib/uvr5_pack/lib_v5/nets_537227KB.py
new file mode 100644
index 0000000000000000000000000000000000000000..a1bb530e006482704f234c2e739a695174142941
--- /dev/null
+++ b/lib/uvr5_pack/lib_v5/nets_537227KB.py
@@ -0,0 +1,123 @@
+import torch
+import numpy as np
+from torch import nn
+import torch.nn.functional as F
+
+from . import layers_537238KB as layers
+
+
+class BaseASPPNet(nn.Module):
+    def __init__(self, nin, ch, dilations=(4, 8, 16)):
+        super(BaseASPPNet, self).__init__()
+        self.enc1 = layers.Encoder(nin, ch, 3, 2, 1)
+        self.enc2 = layers.Encoder(ch, ch * 2, 3, 2, 1)
+        self.enc3 = layers.Encoder(ch * 2, ch * 4, 3, 2, 1)
+        self.enc4 = layers.Encoder(ch * 4, ch * 8, 3, 2, 1)
+
+        self.aspp = layers.ASPPModule(ch * 8, ch * 16, dilations)
+
+        self.dec4 = layers.Decoder(ch * (8 + 16), ch * 8, 3, 1, 1)
+        self.dec3 = layers.Decoder(ch * (4 + 8), ch * 4, 3, 1, 1)
+        self.dec2 = layers.Decoder(ch * (2 + 4), ch * 2, 3, 1, 1)
+        self.dec1 = layers.Decoder(ch * (1 + 2), ch, 3, 1, 1)
+
+    def __call__(self, x):
+        h, e1 = self.enc1(x)
+        h, e2 = self.enc2(h)
+        h, e3 = self.enc3(h)
+        h, e4 = self.enc4(h)
+
+        h = self.aspp(h)
+
+        h = self.dec4(h, e4)
+        h = self.dec3(h, e3)
+        h = self.dec2(h, e2)
+        h = self.dec1(h, e1)
+
+        return h
+
+
+class CascadedASPPNet(nn.Module):
+    def __init__(self, n_fft):
+        super(CascadedASPPNet, self).__init__()
+        self.stg1_low_band_net = BaseASPPNet(2, 64)
+        self.stg1_high_band_net = BaseASPPNet(2, 64)
+
+        self.stg2_bridge = layers.Conv2DBNActiv(66, 32, 1, 1, 0)
+        self.stg2_full_band_net = BaseASPPNet(32, 64)
+
+        self.stg3_bridge = layers.Conv2DBNActiv(130, 64, 1, 1, 0)
+        self.stg3_full_band_net = BaseASPPNet(64, 128)
+
+        self.out = nn.Conv2d(128, 2, 1, bias=False)
+        self.aux1_out = nn.Conv2d(64, 2, 1, bias=False)
+        self.aux2_out = nn.Conv2d(64, 2, 1, bias=False)
+
+        self.max_bin = n_fft // 2
+        self.output_bin = n_fft // 2 + 1
+
+        self.offset = 128
+
+    def forward(self, x, aggressiveness=None):
+        mix = x.detach()
+        x = x.clone()
+
+        x = x[:, :, : self.max_bin]
+
+        bandw = x.size()[2] // 2
+        aux1 = torch.cat(
+            [
+                self.stg1_low_band_net(x[:, :, :bandw]),
+                self.stg1_high_band_net(x[:, :, bandw:]),
+            ],
+            dim=2,
+        )
+
+        h = torch.cat([x, aux1], dim=1)
+        aux2 = self.stg2_full_band_net(self.stg2_bridge(h))
+
+        h = torch.cat([x, aux1, aux2], dim=1)
+        h = self.stg3_full_band_net(self.stg3_bridge(h))
+
+        mask = torch.sigmoid(self.out(h))
+        mask = F.pad(
+            input=mask,
+            pad=(0, 0, 0, self.output_bin - mask.size()[2]),
+            mode="replicate",
+        )
+
+        if self.training:
+            aux1 = torch.sigmoid(self.aux1_out(aux1))
+            aux1 = F.pad(
+                input=aux1,
+                pad=(0, 0, 0, self.output_bin - aux1.size()[2]),
+                mode="replicate",
+            )
+            aux2 = torch.sigmoid(self.aux2_out(aux2))
+            aux2 = F.pad(
+                input=aux2,
+                pad=(0, 0, 0, self.output_bin - aux2.size()[2]),
+                mode="replicate",
+            )
+            return mask * mix, aux1 * mix, aux2 * mix
+        else:
+            if aggressiveness:
+                mask[:, :, : aggressiveness["split_bin"]] = torch.pow(
+                    mask[:, :, : aggressiveness["split_bin"]],
+                    1 + aggressiveness["value"] / 3,
+                )
+                mask[:, :, aggressiveness["split_bin"] :] = torch.pow(
+                    mask[:, :, aggressiveness["split_bin"] :],
+                    1 + aggressiveness["value"],
+                )
+
+            return mask * mix
+
+    def predict(self, x_mag, aggressiveness=None):
+        h = self.forward(x_mag, aggressiveness)
+
+        if self.offset > 0:
+            h = h[:, :, :, self.offset : -self.offset]
+            assert h.size()[3] > 0
+
+        return h
diff --git a/lib/uvr5_pack/lib_v5/nets_537238KB.py b/lib/uvr5_pack/lib_v5/nets_537238KB.py
new file mode 100644
index 0000000000000000000000000000000000000000..a1bb530e006482704f234c2e739a695174142941
--- /dev/null
+++ b/lib/uvr5_pack/lib_v5/nets_537238KB.py
@@ -0,0 +1,123 @@
+import torch
+import numpy as np
+from torch import nn
+import torch.nn.functional as F
+
+from . import layers_537238KB as layers
+
+
+class BaseASPPNet(nn.Module):
+    def __init__(self, nin, ch, dilations=(4, 8, 16)):
+        super(BaseASPPNet, self).__init__()
+        self.enc1 = layers.Encoder(nin, ch, 3, 2, 1)
+        self.enc2 = layers.Encoder(ch, ch * 2, 3, 2, 1)
+        self.enc3 = layers.Encoder(ch * 2, ch * 4, 3, 2, 1)
+        self.enc4 = layers.Encoder(ch * 4, ch * 8, 3, 2, 1)
+
+        self.aspp = layers.ASPPModule(ch * 8, ch * 16, dilations)
+
+        self.dec4 = layers.Decoder(ch * (8 + 16), ch * 8, 3, 1, 1)
+        self.dec3 = layers.Decoder(ch * (4 + 8), ch * 4, 3, 1, 1)
+        self.dec2 = layers.Decoder(ch * (2 + 4), ch * 2, 3, 1, 1)
+        self.dec1 = layers.Decoder(ch * (1 + 2), ch, 3, 1, 1)
+
+    def __call__(self, x):
+        h, e1 = self.enc1(x)
+        h, e2 = self.enc2(h)
+        h, e3 = self.enc3(h)
+        h, e4 = self.enc4(h)
+
+        h = self.aspp(h)
+
+        h = self.dec4(h, e4)
+        h = self.dec3(h, e3)
+        h = self.dec2(h, e2)
+        h = self.dec1(h, e1)
+
+        return h
+
+
+class CascadedASPPNet(nn.Module):
+    def __init__(self, n_fft):
+        super(CascadedASPPNet, self).__init__()
+        self.stg1_low_band_net = BaseASPPNet(2, 64)
+        self.stg1_high_band_net = BaseASPPNet(2, 64)
+
+        self.stg2_bridge = layers.Conv2DBNActiv(66, 32, 1, 1, 0)
+        self.stg2_full_band_net = BaseASPPNet(32, 64)
+
+        self.stg3_bridge = layers.Conv2DBNActiv(130, 64, 1, 1, 0)
+        self.stg3_full_band_net = BaseASPPNet(64, 128)
+
+        self.out = nn.Conv2d(128, 2, 1, bias=False)
+        self.aux1_out = nn.Conv2d(64, 2, 1, bias=False)
+        self.aux2_out = nn.Conv2d(64, 2, 1, bias=False)
+
+        self.max_bin = n_fft // 2
+        self.output_bin = n_fft // 2 + 1
+
+        self.offset = 128
+
+    def forward(self, x, aggressiveness=None):
+        mix = x.detach()
+        x = x.clone()
+
+        x = x[:, :, : self.max_bin]
+
+        bandw = x.size()[2] // 2
+        aux1 = torch.cat(
+            [
+                self.stg1_low_band_net(x[:, :, :bandw]),
+                self.stg1_high_band_net(x[:, :, bandw:]),
+            ],
+            dim=2,
+        )
+
+        h = torch.cat([x, aux1], dim=1)
+        aux2 = self.stg2_full_band_net(self.stg2_bridge(h))
+
+        h = torch.cat([x, aux1, aux2], dim=1)
+        h = self.stg3_full_band_net(self.stg3_bridge(h))
+
+        mask = torch.sigmoid(self.out(h))
+        mask = F.pad(
+            input=mask,
+            pad=(0, 0, 0, self.output_bin - mask.size()[2]),
+            mode="replicate",
+        )
+
+        if self.training:
+            aux1 = torch.sigmoid(self.aux1_out(aux1))
+            aux1 = F.pad(
+                input=aux1,
+                pad=(0, 0, 0, self.output_bin - aux1.size()[2]),
+                mode="replicate",
+            )
+            aux2 = torch.sigmoid(self.aux2_out(aux2))
+            aux2 = F.pad(
+                input=aux2,
+                pad=(0, 0, 0, self.output_bin - aux2.size()[2]),
+                mode="replicate",
+            )
+            return mask * mix, aux1 * mix, aux2 * mix
+        else:
+            if aggressiveness:
+                mask[:, :, : aggressiveness["split_bin"]] = torch.pow(
+                    mask[:, :, : aggressiveness["split_bin"]],
+                    1 + aggressiveness["value"] / 3,
+                )
+                mask[:, :, aggressiveness["split_bin"] :] = torch.pow(
+                    mask[:, :, aggressiveness["split_bin"] :],
+                    1 + aggressiveness["value"],
+                )
+
+            return mask * mix
+
+    def predict(self, x_mag, aggressiveness=None):
+        h = self.forward(x_mag, aggressiveness)
+
+        if self.offset > 0:
+            h = h[:, :, :, self.offset : -self.offset]
+            assert h.size()[3] > 0
+
+        return h
diff --git a/lib/uvr5_pack/lib_v5/nets_61968KB.py b/lib/uvr5_pack/lib_v5/nets_61968KB.py
new file mode 100644
index 0000000000000000000000000000000000000000..becbfae85683a13bbb19d3ea6c840da24e61e01e
--- /dev/null
+++ b/lib/uvr5_pack/lib_v5/nets_61968KB.py
@@ -0,0 +1,122 @@
+import torch
+from torch import nn
+import torch.nn.functional as F
+
+from . import layers_123821KB as layers
+
+
+class BaseASPPNet(nn.Module):
+    def __init__(self, nin, ch, dilations=(4, 8, 16)):
+        super(BaseASPPNet, self).__init__()
+        self.enc1 = layers.Encoder(nin, ch, 3, 2, 1)
+        self.enc2 = layers.Encoder(ch, ch * 2, 3, 2, 1)
+        self.enc3 = layers.Encoder(ch * 2, ch * 4, 3, 2, 1)
+        self.enc4 = layers.Encoder(ch * 4, ch * 8, 3, 2, 1)
+
+        self.aspp = layers.ASPPModule(ch * 8, ch * 16, dilations)
+
+        self.dec4 = layers.Decoder(ch * (8 + 16), ch * 8, 3, 1, 1)
+        self.dec3 = layers.Decoder(ch * (4 + 8), ch * 4, 3, 1, 1)
+        self.dec2 = layers.Decoder(ch * (2 + 4), ch * 2, 3, 1, 1)
+        self.dec1 = layers.Decoder(ch * (1 + 2), ch, 3, 1, 1)
+
+    def __call__(self, x):
+        h, e1 = self.enc1(x)
+        h, e2 = self.enc2(h)
+        h, e3 = self.enc3(h)
+        h, e4 = self.enc4(h)
+
+        h = self.aspp(h)
+
+        h = self.dec4(h, e4)
+        h = self.dec3(h, e3)
+        h = self.dec2(h, e2)
+        h = self.dec1(h, e1)
+
+        return h
+
+
+class CascadedASPPNet(nn.Module):
+    def __init__(self, n_fft):
+        super(CascadedASPPNet, self).__init__()
+        self.stg1_low_band_net = BaseASPPNet(2, 32)
+        self.stg1_high_band_net = BaseASPPNet(2, 32)
+
+        self.stg2_bridge = layers.Conv2DBNActiv(34, 16, 1, 1, 0)
+        self.stg2_full_band_net = BaseASPPNet(16, 32)
+
+        self.stg3_bridge = layers.Conv2DBNActiv(66, 32, 1, 1, 0)
+        self.stg3_full_band_net = BaseASPPNet(32, 64)
+
+        self.out = nn.Conv2d(64, 2, 1, bias=False)
+        self.aux1_out = nn.Conv2d(32, 2, 1, bias=False)
+        self.aux2_out = nn.Conv2d(32, 2, 1, bias=False)
+
+        self.max_bin = n_fft // 2
+        self.output_bin = n_fft // 2 + 1
+
+        self.offset = 128
+
+    def forward(self, x, aggressiveness=None):
+        mix = x.detach()
+        x = x.clone()
+
+        x = x[:, :, : self.max_bin]
+
+        bandw = x.size()[2] // 2
+        aux1 = torch.cat(
+            [
+                self.stg1_low_band_net(x[:, :, :bandw]),
+                self.stg1_high_band_net(x[:, :, bandw:]),
+            ],
+            dim=2,
+        )
+
+        h = torch.cat([x, aux1], dim=1)
+        aux2 = self.stg2_full_band_net(self.stg2_bridge(h))
+
+        h = torch.cat([x, aux1, aux2], dim=1)
+        h = self.stg3_full_band_net(self.stg3_bridge(h))
+
+        mask = torch.sigmoid(self.out(h))
+        mask = F.pad(
+            input=mask,
+            pad=(0, 0, 0, self.output_bin - mask.size()[2]),
+            mode="replicate",
+        )
+
+        if self.training:
+            aux1 = torch.sigmoid(self.aux1_out(aux1))
+            aux1 = F.pad(
+                input=aux1,
+                pad=(0, 0, 0, self.output_bin - aux1.size()[2]),
+                mode="replicate",
+            )
+            aux2 = torch.sigmoid(self.aux2_out(aux2))
+            aux2 = F.pad(
+                input=aux2,
+                pad=(0, 0, 0, self.output_bin - aux2.size()[2]),
+                mode="replicate",
+            )
+            return mask * mix, aux1 * mix, aux2 * mix
+        else:
+            if aggressiveness:
+                mask[:, :, : aggressiveness["split_bin"]] = torch.pow(
+                    mask[:, :, : aggressiveness["split_bin"]],
+                    1 + aggressiveness["value"] / 3,
+                )
+                mask[:, :, aggressiveness["split_bin"] :] = torch.pow(
+                    mask[:, :, aggressiveness["split_bin"] :],
+                    1 + aggressiveness["value"],
+                )
+
+            return mask * mix
+
+    def predict(self, x_mag, aggressiveness=None):
+        h = self.forward(x_mag, aggressiveness)
+
+        if self.offset > 0:
+            h = h[:, :, :, self.offset : -self.offset]
+            assert h.size()[3] > 0
+
+        return h
diff --git a/lib/uvr5_pack/lib_v5/nets_new.py b/lib/uvr5_pack/lib_v5/nets_new.py
new file mode 100644
index 0000000000000000000000000000000000000000..bfaf72e48b31cc1130f2892b0973c9aa06f195a3
--- /dev/null
+++ b/lib/uvr5_pack/lib_v5/nets_new.py
@@ -0,0 +1,132 @@
+import torch
+from torch import nn
+import torch.nn.functional as F
+from . import layers_new
+
+
+class BaseNet(nn.Module):
+    def __init__(
+        self, nin, nout, nin_lstm, nout_lstm, dilations=((4, 2), (8, 4), (12, 6))
+    ):
+        super(BaseNet, self).__init__()
+        self.enc1 = layers_new.Conv2DBNActiv(nin, nout, 3, 1, 1)
+        self.enc2 = layers_new.Encoder(nout, nout * 2, 3, 2, 1)
+        self.enc3 = layers_new.Encoder(nout * 2, nout * 4, 3, 2, 1)
+        self.enc4 = layers_new.Encoder(nout * 4, nout * 6, 3, 2, 1)
+        self.enc5 = layers_new.Encoder(nout * 6, nout * 8, 3, 2, 1)
+
+        self.aspp = layers_new.ASPPModule(nout * 8, nout * 8, dilations, dropout=True)
+
+        self.dec4 = layers_new.Decoder(nout * (6 + 8), nout * 6, 3, 1, 1)
+        self.dec3 = layers_new.Decoder(nout * (4 + 6), nout * 4, 3, 1, 1)
+        self.dec2 = layers_new.Decoder(nout * (2 + 4), nout * 2, 3, 1, 1)
+        self.lstm_dec2 = layers_new.LSTMModule(nout * 2, nin_lstm, nout_lstm)
+        self.dec1 = layers_new.Decoder(nout * (1 + 2) + 1, nout * 1, 3, 1, 1)
+
+    def __call__(self, x):
+        e1 = self.enc1(x)
+        e2 = self.enc2(e1)
+        e3 = self.enc3(e2)
+        e4 = self.enc4(e3)
+        e5 = self.enc5(e4)
+
+        h = self.aspp(e5)
+
+        h = self.dec4(h, e4)
+        h = self.dec3(h, e3)
+        h = self.dec2(h, e2)
+        h = torch.cat([h, self.lstm_dec2(h)], dim=1)
+        h = self.dec1(h, e1)
+
+        return h
+
+
+class CascadedNet(nn.Module):
+    def __init__(self, n_fft, nout=32, nout_lstm=128):
+        super(CascadedNet, self).__init__()
+
+        self.max_bin = n_fft // 2
+        self.output_bin = n_fft // 2 + 1
+        self.nin_lstm = self.max_bin // 2
+        self.offset = 64
+
+        self.stg1_low_band_net = nn.Sequential(
+            BaseNet(2, nout // 2, self.nin_lstm // 2, nout_lstm),
+            layers_new.Conv2DBNActiv(nout // 2, nout // 4, 1, 1, 0),
+        )
+
+        self.stg1_high_band_net = BaseNet(
+            2, nout // 4, self.nin_lstm // 2, nout_lstm // 2
+        )
+
+        self.stg2_low_band_net = nn.Sequential(
+            BaseNet(nout // 4 + 2, nout, self.nin_lstm // 2, nout_lstm),
+            layers_new.Conv2DBNActiv(nout, nout // 2, 1, 1, 0),
+        )
+        self.stg2_high_band_net = BaseNet(
+            nout // 4 + 2, nout // 2, self.nin_lstm // 2, nout_lstm // 2
+        )
+
+        self.stg3_full_band_net = BaseNet(
+            3 * nout // 4 + 2, nout, self.nin_lstm, nout_lstm
+        )
+
+        self.out = nn.Conv2d(nout, 2, 1, bias=False)
+        self.aux_out = nn.Conv2d(3 * nout // 4, 2, 1, bias=False)
+
+    def forward(self, x):
+        x = x[:, :, : self.max_bin]
+
+        bandw = x.size()[2] // 2
+        l1_in = x[:, :, :bandw]
+        h1_in = x[:, :, bandw:]
+        l1 = self.stg1_low_band_net(l1_in)
+        h1 = self.stg1_high_band_net(h1_in)
+        aux1 = torch.cat([l1, h1], dim=2)
+
+        l2_in = torch.cat([l1_in, l1], dim=1)
+        h2_in = torch.cat([h1_in, h1], dim=1)
+        l2 = self.stg2_low_band_net(l2_in)
+        h2 = self.stg2_high_band_net(h2_in)
+        aux2 = torch.cat([l2, h2], dim=2)
+
+        f3_in = torch.cat([x, aux1, aux2], dim=1)
+        f3 = self.stg3_full_band_net(f3_in)
+
+        mask = torch.sigmoid(self.out(f3))
+        mask = F.pad(
+            input=mask,
+            pad=(0, 0, 0, self.output_bin - mask.size()[2]),
+            mode="replicate",
+        )
+
+        if self.training:
+            aux = torch.cat([aux1, aux2], dim=1)
+            aux = torch.sigmoid(self.aux_out(aux))
+            aux = F.pad(
+                input=aux,
+                pad=(0, 0, 0, self.output_bin - aux.size()[2]),
+                mode="replicate",
+            )
+            return mask, aux
+        else:
+            return mask
+
+    def predict_mask(self, x):
+        mask = self.forward(x)
+
+        if self.offset > 0:
+            mask = mask[:, :, :, self.offset : -self.offset]
+            assert mask.size()[3] > 0
+
+        return mask
+
+    def predict(self, x, aggressiveness=None):
+        mask = self.forward(x)
+        pred_mag = x * mask
+
+        if self.offset > 0:
+            pred_mag = pred_mag[:, :, :, self.offset : -self.offset]
+            assert pred_mag.size()[3] > 0
+
+        return pred_mag
diff --git a/lib/uvr5_pack/lib_v5/spec_utils.py b/lib/uvr5_pack/lib_v5/spec_utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..a3fd46d333da7becc7f09f42c084ac7cde661035
--- /dev/null
+++ b/lib/uvr5_pack/lib_v5/spec_utils.py
@@ -0,0 +1,667 @@
+import os, librosa
+import numpy as np
+import soundfile as sf
+from tqdm import tqdm
+import json, math, hashlib
+
+
+def crop_center(h1, h2):
+    h1_shape = h1.size()
+    h2_shape = h2.size()
+
+    if h1_shape[3] == h2_shape[3]:
+        return h1
+    elif h1_shape[3] < h2_shape[3]:
+        raise ValueError("h1_shape[3] must be greater than h2_shape[3]")
+
+    # s_freq = (h2_shape[2] - h1_shape[2]) // 2
+    # e_freq = s_freq + h1_shape[2]
+    s_time = (h1_shape[3] - h2_shape[3]) // 2
+    e_time = s_time + h2_shape[3]
+    h1 = h1[:, :, :, s_time:e_time]
+
+    return h1
+
+
+def wave_to_spectrogram(
+    wave, hop_length, n_fft, mid_side=False, mid_side_b2=False, reverse=False
+):
+    if reverse:
+        wave_left = np.flip(np.asfortranarray(wave[0]))
+        wave_right = np.flip(np.asfortranarray(wave[1]))
+    elif mid_side:
+        wave_left = np.asfortranarray(np.add(wave[0], wave[1]) / 2)
+        wave_right = np.asfortranarray(np.subtract(wave[0], wave[1]))
+    elif mid_side_b2:
+        wave_left = np.asfortranarray(np.add(wave[1], wave[0] * 0.5))
+        wave_right = np.asfortranarray(np.subtract(wave[0], wave[1] * 0.5))
+    else:
+        wave_left = np.asfortranarray(wave[0])
+        wave_right = np.asfortranarray(wave[1])
+
+    spec_left = librosa.stft(wave_left, n_fft, hop_length=hop_length)
+    spec_right = librosa.stft(wave_right, n_fft, hop_length=hop_length)
+
+    spec = np.asfortranarray([spec_left, spec_right])
+
+    return spec
+
+
+def wave_to_spectrogram_mt(
+    wave, hop_length, n_fft, mid_side=False, mid_side_b2=False, reverse=False
+):
+    import threading
+
+    if reverse:
+        wave_left = np.flip(np.asfortranarray(wave[0]))
+        wave_right = np.flip(np.asfortranarray(wave[1]))
+    elif mid_side:
+        wave_left = np.asfortranarray(np.add(wave[0], wave[1]) / 2)
+        wave_right = np.asfortranarray(np.subtract(wave[0], wave[1]))
+    elif mid_side_b2:
+        wave_left = np.asfortranarray(np.add(wave[1], wave[0] * 0.5))
+        wave_right = np.asfortranarray(np.subtract(wave[0], wave[1] * 0.5))
+    else:
+        wave_left = np.asfortranarray(wave[0])
+        wave_right = np.asfortranarray(wave[1])
+
+    def run_thread(**kwargs):
+        global spec_left
+        spec_left = librosa.stft(**kwargs)
+
+    thread = threading.Thread(
+        target=run_thread,
+        kwargs={"y": wave_left, "n_fft": n_fft, "hop_length": hop_length},
+    )
+    thread.start()
+    spec_right = librosa.stft(wave_right, n_fft, hop_length=hop_length)
+    thread.join()
+
+    spec = np.asfortranarray([spec_left, spec_right])
+
+    return spec
+
+
+def combine_spectrograms(specs, mp):
+    l = min([specs[i].shape[2] for i in specs])
+    spec_c = np.zeros(shape=(2, mp.param["bins"] + 1, l), dtype=np.complex64)
+    offset = 0
+    bands_n = len(mp.param["band"])
+
+    for d in range(1, bands_n + 1):
+        h = mp.param["band"][d]["crop_stop"] - mp.param["band"][d]["crop_start"]
+        spec_c[:, offset : offset + h, :l] = specs[d][
+            :, mp.param["band"][d]["crop_start"] : mp.param["band"][d]["crop_stop"], :l
+        ]
+        offset += h
+
+    if offset > mp.param["bins"]:
+        raise ValueError("Too much bins")
+
+    # lowpass fiter
+    if (
+        mp.param["pre_filter_start"] > 0
+    ):  # and mp.param['band'][bands_n]['res_type'] in ['scipy', 'polyphase']:
+        if bands_n == 1:
+            spec_c = fft_lp_filter(
+                spec_c, mp.param["pre_filter_start"], mp.param["pre_filter_stop"]
+            )
+        else:
+            gp = 1
+            for b in range(
+                mp.param["pre_filter_start"] + 1, mp.param["pre_filter_stop"]
+            ):
+                g = math.pow(
+                    10, -(b - mp.param["pre_filter_start"]) * (3.5 - gp) / 20.0
+                )
+                gp = g
+                spec_c[:, b, :] *= g
+
+    return np.asfortranarray(spec_c)
+
+
+def spectrogram_to_image(spec, mode="magnitude"):
+    if mode == "magnitude":
+        if np.iscomplexobj(spec):
+            y = np.abs(spec)
+        else:
+            y = spec
+        y = np.log10(y**2 + 1e-8)
+    elif mode == "phase":
+        if np.iscomplexobj(spec):
+            y = np.angle(spec)
+        else:
+            y = spec
+
+    y -= y.min()
+    y *= 255 / y.max()
+    img = np.uint8(y)
+
+    if y.ndim == 3:
+        img = img.transpose(1, 2, 0)
+        img = np.concatenate([np.max(img, axis=2, keepdims=True), img], axis=2)
+
+    return img
+
+
+def reduce_vocal_aggressively(X, y, softmask):
+    v = X - y
+    y_mag_tmp = np.abs(y)
+    v_mag_tmp = np.abs(v)
+
+    v_mask = v_mag_tmp > y_mag_tmp
+    y_mag = np.clip(y_mag_tmp - v_mag_tmp * v_mask * softmask, 0, np.inf)
+
+    return y_mag * np.exp(1.0j * np.angle(y))
+
+
+def mask_silence(mag, ref, thres=0.2, min_range=64, fade_size=32):
+    if min_range < fade_size * 2:
+        raise ValueError("min_range must be >= fade_area * 2")
+
+    mag = mag.copy()
+
+    idx = np.where(ref.mean(axis=(0, 1)) < thres)[0]
+    starts = np.insert(idx[np.where(np.diff(idx) != 1)[0] + 1], 0, idx[0])
+    ends = np.append(idx[np.where(np.diff(idx) != 1)[0]], idx[-1])
+    uninformative = np.where(ends - starts > min_range)[0]
+    if len(uninformative) > 0:
+        starts = starts[uninformative]
+        ends = ends[uninformative]
+        old_e = None
+        for s, e in zip(starts, ends):
+            if old_e is not None and s - old_e < fade_size:
+                s = old_e - fade_size * 2
+
+            if s != 0:
+                weight = np.linspace(0, 1, fade_size)
+                mag[:, :, s : s + fade_size] += weight * ref[:, :, s : s + fade_size]
+            else:
+                s -= fade_size
+
+            if e != mag.shape[2]:
+                weight = np.linspace(1, 0, fade_size)
+                mag[:, :, e - fade_size : e] += weight * ref[:, :, e - fade_size : e]
+            else:
+                e += fade_size
+
+            mag[:, :, s + fade_size : e - fade_size] += ref[
+                :, :, s + fade_size : e - fade_size
+            ]
+            old_e = e
+
+    return mag
+
+
+def align_wave_head_and_tail(a, b):
+    l = min([a[0].size, b[0].size])
+
+    return a[:l, :l], b[:l, :l]
+
+
+def cache_or_load(mix_path, inst_path, mp):
+    mix_basename = os.path.splitext(os.path.basename(mix_path))[0]
+    inst_basename = os.path.splitext(os.path.basename(inst_path))[0]
+
+    cache_dir = "mph{}".format(
+        hashlib.sha1(json.dumps(mp.param, sort_keys=True).encode("utf-8")).hexdigest()
+    )
+    mix_cache_dir = os.path.join("cache", cache_dir)
+    inst_cache_dir = os.path.join("cache", cache_dir)
+
+    os.makedirs(mix_cache_dir, exist_ok=True)
+    os.makedirs(inst_cache_dir, exist_ok=True)
+
+    mix_cache_path = os.path.join(mix_cache_dir, mix_basename + ".npy")
+    inst_cache_path = os.path.join(inst_cache_dir, inst_basename + ".npy")
+
+    if os.path.exists(mix_cache_path) and os.path.exists(inst_cache_path):
+        X_spec_m = np.load(mix_cache_path)
+        y_spec_m = np.load(inst_cache_path)
+    else:
+        X_wave, y_wave, X_spec_s, y_spec_s = {}, {}, {}, {}
+
+        for d in range(len(mp.param["band"]), 0, -1):
+            bp = mp.param["band"][d]
+
+            if d == len(mp.param["band"]):  # high-end band
+                X_wave[d], _ = librosa.load(
+                    mix_path, bp["sr"], False, dtype=np.float32, res_type=bp["res_type"]
+                )
+                y_wave[d], _ = librosa.load(
+                    inst_path,
+                    bp["sr"],
+                    False,
+                    dtype=np.float32,
+                    res_type=bp["res_type"],
+                )
+            else:  # lower bands
+                X_wave[d] = librosa.resample(
+                    X_wave[d + 1],
+                    mp.param["band"][d + 1]["sr"],
+                    bp["sr"],
+                    res_type=bp["res_type"],
+                )
+                y_wave[d] = librosa.resample(
+                    y_wave[d + 1],
+                    mp.param["band"][d + 1]["sr"],
+                    bp["sr"],
+                    res_type=bp["res_type"],
+                )
+
+            X_wave[d], y_wave[d] = align_wave_head_and_tail(X_wave[d], y_wave[d])
+
+            X_spec_s[d] = wave_to_spectrogram(
+                X_wave[d],
+                bp["hl"],
+                bp["n_fft"],
+                mp.param["mid_side"],
+                mp.param["mid_side_b2"],
+                mp.param["reverse"],
+            )
+            y_spec_s[d] = wave_to_spectrogram(
+                y_wave[d],
+                bp["hl"],
+                bp["n_fft"],
+                mp.param["mid_side"],
+                mp.param["mid_side_b2"],
+                mp.param["reverse"],
+            )
+
+        del X_wave, y_wave
+
+        X_spec_m = combine_spectrograms(X_spec_s, mp)
+        y_spec_m = combine_spectrograms(y_spec_s, mp)
+
+        if X_spec_m.shape != y_spec_m.shape:
+            raise ValueError("The combined spectrograms are different: " + mix_path)
+
+        _, ext = os.path.splitext(mix_path)
+
+        np.save(mix_cache_path, X_spec_m)
+        np.save(inst_cache_path, y_spec_m)
+
+    return X_spec_m, y_spec_m
+
+
+def spectrogram_to_wave(spec, hop_length, mid_side, mid_side_b2, reverse):
+    spec_left = np.asfortranarray(spec[0])
+    spec_right = np.asfortranarray(spec[1])
+
+    wave_left = librosa.istft(spec_left, hop_length=hop_length)
+    wave_right = librosa.istft(spec_right, hop_length=hop_length)
+
+    if reverse:
+        return np.asfortranarray([np.flip(wave_left), np.flip(wave_right)])
+    elif mid_side:
+        return np.asfortranarray(
+            [np.add(wave_left, wave_right / 2), np.subtract(wave_left, wave_right / 2)]
+        )
+    elif mid_side_b2:
+        return np.asfortranarray(
+            [
+                np.add(wave_right / 1.25, 0.4 * wave_left),
+                np.subtract(wave_left / 1.25, 0.4 * wave_right),
+            ]
+        )
+    else:
+        return np.asfortranarray([wave_left, wave_right])
+
+
+def spectrogram_to_wave_mt(spec, hop_length, mid_side, reverse, mid_side_b2):
+    import threading
+
+    spec_left = np.asfortranarray(spec[0])
+    spec_right = np.asfortranarray(spec[1])
+
+    def run_thread(**kwargs):
+        global wave_left
+        wave_left = librosa.istft(**kwargs)
+
+    thread = threading.Thread(
+        target=run_thread, kwargs={"stft_matrix": spec_left, "hop_length": hop_length}
+    )
+    thread.start()
+    wave_right = librosa.istft(spec_right, hop_length=hop_length)
+    thread.join()
+
+    if reverse:
+        return np.asfortranarray([np.flip(wave_left), np.flip(wave_right)])
+    elif mid_side:
+        return np.asfortranarray(
+            [np.add(wave_left, wave_right / 2), np.subtract(wave_left, wave_right / 2)]
+        )
+    elif mid_side_b2:
+        return np.asfortranarray(
+            [
+                np.add(wave_right / 1.25, 0.4 * wave_left),
+                np.subtract(wave_left / 1.25, 0.4 * wave_right),
+            ]
+        )
+    else:
+        return np.asfortranarray([wave_left, wave_right])
+
+
+def cmb_spectrogram_to_wave(spec_m, mp, extra_bins_h=None, extra_bins=None):
+    wave_band = {}
+    bands_n = len(mp.param["band"])
+    offset = 0
+
+    for d in range(1, bands_n + 1):
+        bp = mp.param["band"][d]
+        spec_s = np.ndarray(
+            shape=(2, bp["n_fft"] // 2 + 1, spec_m.shape[2]), dtype=complex
+        )
+        h = bp["crop_stop"] - bp["crop_start"]
+        spec_s[:, bp["crop_start"] : bp["crop_stop"], :] = spec_m[
+            :, offset : offset + h, :
+        ]
+
+        offset += h
+        if d == bands_n:  # higher
+            if extra_bins_h:  # if --high_end_process bypass
+                max_bin = bp["n_fft"] // 2
+                spec_s[:, max_bin - extra_bins_h : max_bin, :] = extra_bins[
+                    :, :extra_bins_h, :
+                ]
+            if bp["hpf_start"] > 0:
+                spec_s = fft_hp_filter(spec_s, bp["hpf_start"], bp["hpf_stop"] - 1)
+            if bands_n == 1:
+                wave = spectrogram_to_wave(
+                    spec_s,
+                    bp["hl"],
+                    mp.param["mid_side"],
+                    mp.param["mid_side_b2"],
+                    mp.param["reverse"],
+                )
+            else:
+                wave = np.add(
+                    wave,
+                    spectrogram_to_wave(
+                        spec_s,
+                        bp["hl"],
+                        mp.param["mid_side"],
+                        mp.param["mid_side_b2"],
+                        mp.param["reverse"],
+                    ),
+                )
+        else:
+            sr = mp.param["band"][d + 1]["sr"]
+            if d == 1:  # lower
+                spec_s = fft_lp_filter(spec_s, bp["lpf_start"], bp["lpf_stop"])
+                wave = librosa.resample(
+                    spectrogram_to_wave(
+                        spec_s,
+                        bp["hl"],
+                        mp.param["mid_side"],
+                        mp.param["mid_side_b2"],
+                        mp.param["reverse"],
+                    ),
+                    bp["sr"],
+                    sr,
+                    res_type="sinc_fastest",
+                )
+            else:  # mid
+                spec_s = fft_hp_filter(spec_s, bp["hpf_start"], bp["hpf_stop"] - 1)
+                spec_s = fft_lp_filter(spec_s, bp["lpf_start"], bp["lpf_stop"])
+                wave2 = np.add(
+                    wave,
+                    spectrogram_to_wave(
+                        spec_s,
+                        bp["hl"],
+                        mp.param["mid_side"],
+                        mp.param["mid_side_b2"],
+                        mp.param["reverse"],
+                    ),
+                )
+                # wave = librosa.core.resample(wave2, bp['sr'], sr, res_type="sinc_fastest")
+                wave = librosa.core.resample(wave2, bp["sr"], sr, res_type="scipy")
+
+    return wave.T
+
+
+def fft_lp_filter(spec, bin_start, bin_stop):
+    g = 1.0
+    for b in range(bin_start, bin_stop):
+        g -= 1 / (bin_stop - bin_start)
+        spec[:, b, :] = g * spec[:, b, :]
+
+    spec[:, bin_stop:, :] *= 0
+
+    return spec
+
+
+def fft_hp_filter(spec, bin_start, bin_stop):
+    g = 1.0
+    for b in range(bin_start, bin_stop, -1):
+        g -= 1 / (bin_start - bin_stop)
+        spec[:, b, :] = g * spec[:, b, :]
+
+    spec[:, 0 : bin_stop + 1, :] *= 0
+
+    return spec
+
+
+def mirroring(a, spec_m, input_high_end, mp):
+    if "mirroring" == a:
+        mirror = np.flip(
+            np.abs(
+                spec_m[
+                    :,
+                    mp.param["pre_filter_start"]
+                    - 10
+                    - input_high_end.shape[1] : mp.param["pre_filter_start"]
+                    - 10,
+                    :,
+                ]
+            ),
+            1,
+        )
+        mirror = mirror * np.exp(1.0j * np.angle(input_high_end))
+
+        return np.where(
+            np.abs(input_high_end) <= np.abs(mirror), input_high_end, mirror
+        )
+
+    if "mirroring2" == a:
+        mirror = np.flip(
+            np.abs(
+                spec_m[
+                    :,
+                    mp.param["pre_filter_start"]
+                    - 10
+                    - input_high_end.shape[1] : mp.param["pre_filter_start"]
+                    - 10,
+                    :,
+                ]
+            ),
+            1,
+        )
+        mi = np.multiply(mirror, input_high_end * 1.7)
+
+        return np.where(np.abs(input_high_end) <= np.abs(mi), input_high_end, mi)
+
+
+def ensembling(a, specs):
+    for i in range(1, len(specs)):
+        if i == 1:
+            spec = specs[0]
+
+        ln = min([spec.shape[2], specs[i].shape[2]])
+        spec = spec[:, :, :ln]
+        specs[i] = specs[i][:, :, :ln]
+
+        if "min_mag" == a:
+            spec = np.where(np.abs(specs[i]) <= np.abs(spec), specs[i], spec)
+        if "max_mag" == a:
+            spec = np.where(np.abs(specs[i]) >= np.abs(spec), specs[i], spec)
+
+    return spec
+
+
+def stft(wave, nfft, hl):
+    wave_left = np.asfortranarray(wave[0])
+    wave_right = np.asfortranarray(wave[1])
+    spec_left = librosa.stft(wave_left, nfft, hop_length=hl)
+    spec_right = librosa.stft(wave_right, nfft, hop_length=hl)
+    spec = np.asfortranarray([spec_left, spec_right])
+
+    return spec
+
+
+def istft(spec, hl):
+    spec_left = np.asfortranarray(spec[0])
+    spec_right = np.asfortranarray(spec[1])
+
+    wave_left = librosa.istft(spec_left, hop_length=hl)
+    wave_right = librosa.istft(spec_right, hop_length=hl)
+    wave = np.asfortranarray([wave_left, wave_right])
+
+
+if __name__ == "__main__":
+    import cv2
+    import sys
+    import time
+    import argparse
+    from model_param_init import ModelParameters
+
+    p = argparse.ArgumentParser()
+    p.add_argument(
+        "--algorithm",
+        "-a",
+        type=str,
+        choices=["invert", "invert_p", "min_mag", "max_mag", "deep", "align"],
+        default="min_mag",
+    )
+    p.add_argument(
+        "--model_params",
+        "-m",
+        type=str,
+        default=os.path.join("modelparams", "1band_sr44100_hl512.json"),
+    )
+    p.add_argument("--output_name", "-o", type=str, default="output")
+    p.add_argument("--vocals_only", "-v", action="store_true")
+    p.add_argument("input", nargs="+")
+    args = p.parse_args()
+
+    start_time = time.time()
+
+    if args.algorithm.startswith("invert") and len(args.input) != 2:
+        raise ValueError("There should be two input files.")
+
+    if not args.algorithm.startswith("invert") and len(args.input) < 2:
+        raise ValueError("There must be at least two input files.")
+
+    wave, specs = {}, {}
+    mp = ModelParameters(args.model_params)
+
+    for i in range(len(args.input)):
+        spec = {}
+
+        for d in range(len(mp.param["band"]), 0, -1):
+            bp = mp.param["band"][d]
+
+            if d == len(mp.param["band"]):  # high-end band
+                wave[d], _ = librosa.load(
+                    args.input[i],
+                    bp["sr"],
+                    False,
+                    dtype=np.float32,
+                    res_type=bp["res_type"],
+                )
+
+                if len(wave[d].shape) == 1:  # mono to stereo
+                    wave[d] = np.array([wave[d], wave[d]])
+            else:  # lower bands
+                wave[d] = librosa.resample(
+                    wave[d + 1],
+                    mp.param["band"][d + 1]["sr"],
+                    bp["sr"],
+                    res_type=bp["res_type"],
+                )
+
+            spec[d] = wave_to_spectrogram(
+                wave[d],
+                bp["hl"],
+                bp["n_fft"],
+                mp.param["mid_side"],
+                mp.param["mid_side_b2"],
+                mp.param["reverse"],
+            )
+
+        specs[i] = combine_spectrograms(spec, mp)
+
+    del wave
+
+    if args.algorithm == "deep":
+        d_spec = np.where(np.abs(specs[0]) <= np.abs(spec[1]), specs[0], spec[1])
+        v_spec = d_spec - specs[1]
+        sf.write(
+            os.path.join("{}.wav".format(args.output_name)),
+            cmb_spectrogram_to_wave(v_spec, mp),
+            mp.param["sr"],
+        )
+
+    if args.algorithm.startswith("invert"):
+        ln = min([specs[0].shape[2], specs[1].shape[2]])
+        specs[0] = specs[0][:, :, :ln]
+        specs[1] = specs[1][:, :, :ln]
+
+        if "invert_p" == args.algorithm:
+            X_mag = np.abs(specs[0])
+            y_mag = np.abs(specs[1])
+            max_mag = np.where(X_mag >= y_mag, X_mag, y_mag)
+            v_spec = specs[1] - max_mag * np.exp(1.0j * np.angle(specs[0]))
+        else:
+            specs[1] = reduce_vocal_aggressively(specs[0], specs[1], 0.2)
+            v_spec = specs[0] - specs[1]
+
+            if not args.vocals_only:
+                X_mag = np.abs(specs[0])
+                y_mag = np.abs(specs[1])
+                v_mag = np.abs(v_spec)
+
+                X_image = spectrogram_to_image(X_mag)
+                y_image = spectrogram_to_image(y_mag)
+                v_image = spectrogram_to_image(v_mag)
+
+                cv2.imwrite("{}_X.png".format(args.output_name), X_image)
+                cv2.imwrite("{}_y.png".format(args.output_name), y_image)
+                cv2.imwrite("{}_v.png".format(args.output_name), v_image)
+
+                sf.write(
+                    "{}_X.wav".format(args.output_name),
+                    cmb_spectrogram_to_wave(specs[0], mp),
+                    mp.param["sr"],
+                )
+                sf.write(
+                    "{}_y.wav".format(args.output_name),
+                    cmb_spectrogram_to_wave(specs[1], mp),
+                    mp.param["sr"],
+                )
+
+        sf.write(
+            "{}_v.wav".format(args.output_name),
+            cmb_spectrogram_to_wave(v_spec, mp),
+            mp.param["sr"],
+        )
+    else:
+        if not args.algorithm == "deep":
+            sf.write(
+                os.path.join("ensembled", "{}.wav".format(args.output_name)),
+                cmb_spectrogram_to_wave(ensembling(args.algorithm, specs), mp),
+                mp.param["sr"],
+            )
+
+    if args.algorithm == "align":
+        trackalignment = [
+            {
+                "file1": '"{}"'.format(args.input[0]),
+                "file2": '"{}"'.format(args.input[1]),
+            }
+        ]
+
+        for i, e in tqdm(enumerate(trackalignment), desc="Performing Alignment..."):
+            os.system(f"python lib/align_tracks.py {e['file1']} {e['file2']}")
+
+    # print('Total time: {0:.{1}f}s'.format(time.time() - start_time, 1))
diff --git a/lib/uvr5_pack/name_params.json b/lib/uvr5_pack/name_params.json
new file mode 100644
index 0000000000000000000000000000000000000000..f48b0b3f18272615dee33dd5407c126c897c01fc
--- /dev/null
+++ b/lib/uvr5_pack/name_params.json
@@ -0,0 +1,262 @@
+{
+  "equivalent": [
+    {
+      "model_hash_name": [
+        {
+          "hash_name": "47939caf0cfe52a0e81442b85b971dfd",
+          "model_params": "lib/uvr5_pack/lib_v5/modelparams/4band_44100.json",
+          "param_name": "4band_44100"
+        },
+        {
+          "hash_name": "4e4ecb9764c50a8c414fee6e10395bbe",
+          "model_params": "lib/uvr5_pack/lib_v5/modelparams/4band_v2.json",
+          "param_name": "4band_v2"
+        },
+        {
+          "hash_name": "ca106edd563e034bde0bdec4bb7a4b36",
+          "model_params": "lib/uvr5_pack/lib_v5/modelparams/4band_v2.json",
+          "param_name": "4band_v2"
+        },
+        {
+          "hash_name": "e60a1e84803ce4efc0a6551206cc4b71",
+          "model_params": "lib/uvr5_pack/lib_v5/modelparams/4band_44100.json",
+          "param_name": "4band_44100"
+        },
+        {
+          "hash_name": "a82f14e75892e55e994376edbf0c8435",
+          "model_params": "lib/uvr5_pack/lib_v5/modelparams/4band_44100.json",
+          "param_name": "4band_44100"
+        },
+        {
+          "hash_name": "6dd9eaa6f0420af9f1d403aaafa4cc06",
+          "model_params": "lib/uvr5_pack/lib_v5/modelparams/4band_v2_sn.json",
+          "param_name": "4band_v2_sn"
+        },
+        {
+          "hash_name": "08611fb99bd59eaa79ad27c58d137727",
+          "model_params": "lib/uvr5_pack/lib_v5/modelparams/4band_v2_sn.json",
+          "param_name": "4band_v2_sn"
+        },
+        {
+          "hash_name": "5c7bbca45a187e81abbbd351606164e5",
+          "model_params": "lib/uvr5_pack/lib_v5/modelparams/3band_44100_msb2.json",
+          "param_name": "3band_44100_msb2"
+        },
+        {
+          "hash_name": "d6b2cb685a058a091e5e7098192d3233",
+          "model_params": "lib/uvr5_pack/lib_v5/modelparams/3band_44100_msb2.json",
+          "param_name": "3band_44100_msb2"
+        },
+        {
+          "hash_name": "c1b9f38170a7c90e96f027992eb7c62b",
+          "model_params": "lib/uvr5_pack/lib_v5/modelparams/4band_44100.json",
+          "param_name": "4band_44100"
+        },
+        {
+          "hash_name": "c3448ec923fa0edf3d03a19e633faa53",
+          "model_params": "lib/uvr5_pack/lib_v5/modelparams/4band_44100.json",
+          "param_name": "4band_44100"
+        },
+        {
+          "hash_name": "68aa2c8093d0080704b200d140f59e54",
+          "model_params": "lib/uvr5_pack/lib_v5/modelparams/3band_44100.json",
+          "param_name": "3band_44100"
+        },
+        {
+          "hash_name": "fdc83be5b798e4bd29fe00fe6600e147",
+          "model_params": "lib/uvr5_pack/lib_v5/modelparams/3band_44100_mid.json",
+          "param_name": "3band_44100_mid.json"
+        },
+        {
+          "hash_name": "2ce34bc92fd57f55db16b7a4def3d745",
+          "model_params": "lib/uvr5_pack/lib_v5/modelparams/3band_44100_mid.json",
+          "param_name": "3band_44100_mid.json"
+        },
+        {
+          "hash_name": "52fdca89576f06cf4340b74a4730ee5f",
+          "model_params": "lib/uvr5_pack/lib_v5/modelparams/4band_44100.json",
+          "param_name": "4band_44100.json"
+        },
+        {
+          "hash_name": "41191165b05d38fc77f072fa9e8e8a30",
+          "model_params": "lib/uvr5_pack/lib_v5/modelparams/4band_44100.json",
+          "param_name": "4band_44100.json"
+        },
+        {
+          "hash_name": "89e83b511ad474592689e562d5b1f80e",
+          "model_params": "lib/uvr5_pack/lib_v5/modelparams/2band_32000.json",
+          "param_name": "2band_32000.json"
+        },
+        {
+          "hash_name": "0b954da81d453b716b114d6d7c95177f",
+          "model_params": "lib/uvr5_pack/lib_v5/modelparams/2band_32000.json",
+          "param_name": "2band_32000.json"
+        }
+      ],
+      "v4 Models": [
+        {
+          "hash_name": "6a00461c51c2920fd68937d4609ed6c8",
+          "model_params": "lib/uvr5_pack/lib_v5/modelparams/1band_sr16000_hl512.json",
+          "param_name": "1band_sr16000_hl512"
+        },
+        {
+          "hash_name": "0ab504864d20f1bd378fe9c81ef37140",
+          "model_params": "lib/uvr5_pack/lib_v5/modelparams/1band_sr32000_hl512.json",
+          "param_name": "1band_sr32000_hl512"
+        },
+        {
+          "hash_name": "7dd21065bf91c10f7fccb57d7d83b07f",
+          "model_params": "lib/uvr5_pack/lib_v5/modelparams/1band_sr32000_hl512.json",
+          "param_name": "1band_sr32000_hl512"
+        },
+        {
+          "hash_name": "80ab74d65e515caa3622728d2de07d23",
+          "model_params": "lib/uvr5_pack/lib_v5/modelparams/1band_sr32000_hl512.json",
+          "param_name": "1band_sr32000_hl512"
+        },
+        {
+          "hash_name": "edc115e7fc523245062200c00caa847f",
+          "model_params": "lib/uvr5_pack/lib_v5/modelparams/1band_sr33075_hl384.json",
+          "param_name": "1band_sr33075_hl384"
+        },
+        {
+          "hash_name": "28063e9f6ab5b341c5f6d3c67f2045b7",
+          "model_params": "lib/uvr5_pack/lib_v5/modelparams/1band_sr33075_hl384.json",
+          "param_name": "1band_sr33075_hl384"
+        },
+        {
+          "hash_name": "b58090534c52cbc3e9b5104bad666ef2",
+          "model_params": "lib/uvr5_pack/lib_v5/modelparams/1band_sr44100_hl512.json",
+          "param_name": "1band_sr44100_hl512"
+        },
+        {
+          "hash_name": "0cdab9947f1b0928705f518f3c78ea8f",
+          "model_params": "lib/uvr5_pack/lib_v5/modelparams/1band_sr44100_hl512.json",
+          "param_name": "1band_sr44100_hl512"
+        },
+        {
+          "hash_name": "ae702fed0238afb5346db8356fe25f13",
+          "model_params": "lib/uvr5_pack/lib_v5/modelparams/1band_sr44100_hl1024.json",
+          "param_name": "1band_sr44100_hl1024"
+        }
+      ]
+    }
+  ],
+  "User Models": [
+    {
+      "1 Band": [
+        {
+          "hash_name": "1band_sr16000_hl512",
+          "model_params": "lib/uvr5_pack/lib_v5/modelparams/1band_sr16000_hl512.json",
+          "param_name": "1band_sr16000_hl512"
+        },
+        {
+          "hash_name": "1band_sr32000_hl512",
+          "model_params": "lib/uvr5_pack/lib_v5/modelparams/1band_sr32000_hl512.json",
+          "param_name": "1band_sr16000_hl512"
+        },
+        {
+          "hash_name": "1band_sr33075_hl384",
+          "model_params": "lib/uvr5_pack/lib_v5/modelparams/1band_sr33075_hl384.json",
+          "param_name": "1band_sr33075_hl384"
+        },
+        {
+          "hash_name": "1band_sr44100_hl256",
+          "model_params": "lib/uvr5_pack/lib_v5/modelparams/1band_sr44100_hl256.json",
+          "param_name": "1band_sr44100_hl256"
+        },
+        {
+          "hash_name": "1band_sr44100_hl512",
+          "model_params": "lib/uvr5_pack/lib_v5/modelparams/1band_sr44100_hl512.json",
+          "param_name": "1band_sr44100_hl512"
+        },
+        {
+          "hash_name": "1band_sr44100_hl1024",
+          "model_params": "lib/uvr5_pack/lib_v5/modelparams/1band_sr44100_hl1024.json",
+          "param_name": "1band_sr44100_hl1024"
+        }
+      ],
+      "2 Band": [
+        {
+          "hash_name": "2band_44100_lofi",
+          "model_params": "lib/uvr5_pack/lib_v5/modelparams/2band_44100_lofi.json",
+          "param_name": "2band_44100_lofi"
+        },
+        {
+          "hash_name": "2band_32000",
+          "model_params": "lib/uvr5_pack/lib_v5/modelparams/2band_32000.json",
+          "param_name": "2band_32000"
+        },
+        {
+          "hash_name": "2band_48000",
+          "model_params": "lib/uvr5_pack/lib_v5/modelparams/2band_48000.json",
+          "param_name": "2band_48000"
+        }
+      ],
+      "3 Band": [
+        {
+          "hash_name": "3band_44100",
+          "model_params": "lib/uvr5_pack/lib_v5/modelparams/3band_44100.json",
+          "param_name": "3band_44100"
+        },
+        {
+          "hash_name": "3band_44100_mid",
+          "model_params": "lib/uvr5_pack/lib_v5/modelparams/3band_44100_mid.json",
+          "param_name": "3band_44100_mid"
+        },
+        {
+          "hash_name": "3band_44100_msb2",
+          "model_params": "lib/uvr5_pack/lib_v5/modelparams/3band_44100_msb2.json",
+          "param_name": "3band_44100_msb2"
+        }
+      ],
+      "4 Band": [
+        {
+          "hash_name": "4band_44100",
+          "model_params": "lib/uvr5_pack/lib_v5/modelparams/4band_44100.json",
+          "param_name": "4band_44100"
+        },
+        {
+          "hash_name": "4band_44100_mid",
+          "model_params": "lib/uvr5_pack/lib_v5/modelparams/4band_44100_mid.json",
+          "param_name": "4band_44100_mid"
+        },
+        {
+          "hash_name": "4band_44100_msb",
+          "model_params": "lib/uvr5_pack/lib_v5/modelparams/4band_44100_msb.json",
+          "param_name": "4band_44100_msb"
+        },
+        {
+          "hash_name": "4band_44100_msb2",
+          "model_params": "lib/uvr5_pack/lib_v5/modelparams/4band_44100_msb2.json",
+          "param_name": "4band_44100_msb2"
+        },
+        {
+          "hash_name": "4band_44100_reverse",
+          "model_params": "lib/uvr5_pack/lib_v5/modelparams/4band_44100_reverse.json",
+          "param_name": "4band_44100_reverse"
+        },
+        {
+          "hash_name": "4band_44100_sw",
+          "model_params": "lib/uvr5_pack/lib_v5/modelparams/4band_44100_sw.json",
+          "param_name": "4band_44100_sw"
+        },
+        {
+          "hash_name": "4band_v2",
+          "model_params": "lib/uvr5_pack/lib_v5/modelparams/4band_v2.json",
+          "param_name": "4band_v2"
+        },
+        {
+          "hash_name": "4band_v2_sn",
+          "model_params": "lib/uvr5_pack/lib_v5/modelparams/4band_v2_sn.json",
+          "param_name": "4band_v2_sn"
+        },
+        {
+          "hash_name": "tmodelparam",
+          "model_params": "lib/uvr5_pack/lib_v5/modelparams/tmodelparam.json",
+          "param_name": "User Model Param Set"
+        }
+      ]
+    }
+  ]
+}
diff --git a/lib/uvr5_pack/utils.py b/lib/uvr5_pack/utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..0fafe8793b0d539fa58dd024342250b24b6187a9
--- /dev/null
+++ b/lib/uvr5_pack/utils.py
@@ -0,0 +1,120 @@
+import torch
+import numpy as np
+from tqdm import tqdm
+import json
+
+
+def load_data(file_name: str = "./lib/uvr5_pack/name_params.json") -> dict:
+    with open(file_name, "r") as f:
+        data = json.load(f)
+
+    return data
+
+
+def make_padding(width, cropsize, offset):
+    left = offset
+    roi_size = cropsize - left * 2
+    if roi_size == 0:
+        roi_size = cropsize
+    right = roi_size - (width % roi_size) + left
+
+    return left, right, roi_size
+
+
+def inference(X_spec, device, model, aggressiveness, data):
+    """
+    data ： dic configs
+    """
+
+    def _execute(
+        X_mag_pad, roi_size, n_window, device, model, aggressiveness, is_half=True
+    ):
+        model.eval()
+        with torch.no_grad():
+            preds = []
+
+            iterations = [n_window]
+
+            total_iterations = sum(iterations)
+            for i in tqdm(range(n_window)):
+                start = i * roi_size
+                X_mag_window = X_mag_pad[
+                    None, :, :, start : start + data["window_size"]
+                ]
+                X_mag_window = torch.from_numpy(X_mag_window)
+                if is_half:
+                    X_mag_window = X_mag_window.half()
+                X_mag_window = X_mag_window.to(device)
+
+                pred = model.predict(X_mag_window, aggressiveness)
+
+                pred = pred.detach().cpu().numpy()
+                preds.append(pred[0])
+
+            pred = np.concatenate(preds, axis=2)
+        return pred
+
+    def preprocess(X_spec):
+        X_mag = np.abs(X_spec)
+        X_phase = np.angle(X_spec)
+
+        return X_mag, X_phase
+
+    X_mag, X_phase = preprocess(X_spec)
+
+    coef = X_mag.max()
+    X_mag_pre = X_mag / coef
+
+    n_frame = X_mag_pre.shape[2]
+    pad_l, pad_r, roi_size = make_padding(n_frame, data["window_size"], model.offset)
+    n_window = int(np.ceil(n_frame / roi_size))
+
+    X_mag_pad = np.pad(X_mag_pre, ((0, 0), (0, 0), (pad_l, pad_r)), mode="constant")
+
+    if list(model.state_dict().values())[0].dtype == torch.float16:
+        is_half = True
+    else:
+        is_half = False
+    pred = _execute(
+        X_mag_pad, roi_size, n_window, device, model, aggressiveness, is_half
+    )
+    pred = pred[:, :, :n_frame]
+
+    if data["tta"]:
+        pad_l += roi_size // 2
+        pad_r += roi_size // 2
+        n_window += 1
+
+        X_mag_pad = np.pad(X_mag_pre, ((0, 0), (0, 0), (pad_l, pad_r)), mode="constant")
+
+        pred_tta = _execute(
+            X_mag_pad, roi_size, n_window, device, model, aggressiveness, is_half
+        )
+        pred_tta = pred_tta[:, :, roi_size // 2 :]
+        pred_tta = pred_tta[:, :, :n_frame]
+
+        return (pred + pred_tta) * 0.5 * coef, X_mag, np.exp(1.0j * X_phase)
+    else:
+        return pred * coef, X_mag, np.exp(1.0j * X_phase)
+
+
+def _get_name_params(model_path, model_hash):
+    data = load_data()
+    flag = False
+    ModelName = model_path
+    for type in list(data):
+        for model in list(data[type][0]):
+            for i in range(len(data[type][0][model])):
+                if str(data[type][0][model][i]["hash_name"]) == model_hash:
+                    flag = True
+                elif str(data[type][0][model][i]["hash_name"]) in ModelName:
+                    flag = True
+
+                if flag:
+                    model_params_auto = data[type][0][model][i]["model_params"]
+                    param_name_auto = data[type][0][model][i]["param_name"]
+                    if type == "equivalent":
+                        return param_name_auto, model_params_auto
+                    else:
+                        flag = False
+    return param_name_auto, model_params_auto
diff --git a/logs/mute/0_gt_wavs/mute32k.wav b/logs/mute/0_gt_wavs/mute32k.wav
new file mode 100644
index 0000000000000000000000000000000000000000..b4b5029205bf72dee5856bbe0c65c34337dc8dd4
Binary files /dev/null and b/logs/mute/0_gt_wavs/mute32k.wav differ
diff --git a/logs/mute/0_gt_wavs/mute40k.wav b/logs/mute/0_gt_wavs/mute40k.wav
new file mode 100644
index 0000000000000000000000000000000000000000..fcf1281d4d1b01417a4d6738022f4402594a6802
Binary files /dev/null and b/logs/mute/0_gt_wavs/mute40k.wav differ
diff --git a/logs/mute/0_gt_wavs/mute48k.wav b/logs/mute/0_gt_wavs/mute48k.wav
new file mode 100644
index 0000000000000000000000000000000000000000..72822a01251e77d7d2a4a7da9d94805426829083
Binary files /dev/null and b/logs/mute/0_gt_wavs/mute48k.wav differ
diff --git a/logs/mute/1_16k_wavs/mute.wav b/logs/mute/1_16k_wavs/mute.wav
new file mode 100644
index 0000000000000000000000000000000000000000..27a7d638558539c521aacf8c0f34bd0d4816aa9d
Binary files /dev/null and b/logs/mute/1_16k_wavs/mute.wav differ
diff --git a/logs/mute/2a_f0/mute.wav.npy b/logs/mute/2a_f0/mute.wav.npy
new file mode 100644
index 0000000000000000000000000000000000000000..dd7e9afd2e7f2aefaa30bcd4541a23ce96a9e150
--- /dev/null
+++ b/logs/mute/2a_f0/mute.wav.npy
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9b9acf9ab7facdb032e1d687fe35182670b0b94566c4b209ae48c239d19956a6
+size 1332
diff --git a/logs/mute/2b-f0nsf/mute.wav.npy b/logs/mute/2b-f0nsf/mute.wav.npy
new file mode 100644
index 0000000000000000000000000000000000000000..7644e325ddd34bd186153ecf7461aa1593a054f3
--- /dev/null
+++ b/logs/mute/2b-f0nsf/mute.wav.npy
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:30792849c8e72d67e6691754077f2888b101cb741e9c7f193c91dd9692870c87
+size 2536
diff --git a/logs/mute/3_feature256/mute.npy b/logs/mute/3_feature256/mute.npy
new file mode 100644
index 0000000000000000000000000000000000000000..c57ae95d19d969788ef186a81cdc2f4b462ed6df
--- /dev/null
+++ b/logs/mute/3_feature256/mute.npy
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:64d5abbac078e19a3f649c0d78a02cb33a71407ded3ddf2db78e6b803d0c0126
+size 152704
diff --git a/logs/mute/3_feature768/mute.npy b/logs/mute/3_feature768/mute.npy
new file mode 100644
index 0000000000000000000000000000000000000000..ea5f9dddca08ff210791b27e3db3fc5676eabc90
--- /dev/null
+++ b/logs/mute/3_feature768/mute.npy
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:16ef62b957887ac9f0913aa5158f18983afff1ef5a3e4c5fd067ac20fc380d54
+size 457856
diff --git a/mdx.py b/mdx.py
new file mode 100644
index 0000000000000000000000000000000000000000..4cc7c08b37bc371294f2f82b3382424a5455b7c2
--- /dev/null
+++ b/mdx.py
@@ -0,0 +1,228 @@
+import torch
+import onnxruntime as ort
+from tqdm import tqdm
+import warnings
+import numpy as np
+import hashlib
+import queue
+import threading
+
+warnings.filterwarnings("ignore")
+
+class MDX_Model:
+    def __init__(self, device, dim_f, dim_t, n_fft, hop=1024, stem_name=None, compensation=1.000):
+        self.dim_f = dim_f
+        self.dim_t = dim_t
+        self.dim_c = 4
+        self.n_fft = n_fft
+        self.hop = hop
+        self.stem_name = stem_name
+        self.compensation = compensation
+
+        self.n_bins = self.n_fft//2+1
+        self.chunk_size = hop * (self.dim_t-1)
+        self.window = torch.hann_window(window_length=self.n_fft, periodic=True).to(device)
+
+        out_c = self.dim_c
+
+        self.freq_pad = torch.zeros([1, out_c, self.n_bins-self.dim_f, self.dim_t]).to(device)
+
+    def stft(self, x):
+        x = x.reshape([-1, self.chunk_size])
+        x = torch.stft(x, n_fft=self.n_fft, hop_length=self.hop, window=self.window, center=True, return_complex=True)
+        x = torch.view_as_real(x)
+        x = x.permute([0,3,1,2])
+        x = x.reshape([-1,2,2,self.n_bins,self.dim_t]).reshape([-1,4,self.n_bins,self.dim_t])
+        return x[:,:,:self.dim_f]
+
+    def istft(self, x, freq_pad=None):
+        freq_pad = self.freq_pad.repeat([x.shape[0],1,1,1]) if freq_pad is None else freq_pad
+        x = torch.cat([x, freq_pad], -2)
+        # c = 4*2 if self.target_name=='*' else 2
+        x = x.reshape([-1,2,2,self.n_bins,self.dim_t]).reshape([-1,2,self.n_bins,self.dim_t])
+        x = x.permute([0,2,3,1])
+        x = x.contiguous()
+        x = torch.view_as_complex(x)
+        x = torch.istft(x, n_fft=self.n_fft, hop_length=self.hop, window=self.window, center=True)
+        return x.reshape([-1,2,self.chunk_size])
+
+
+class MDX:
+
+    DEFAULT_SR = 44100
+    # Unit: seconds
+    DEFAULT_CHUNK_SIZE = 0 * DEFAULT_SR
+    DEFAULT_MARGIN_SIZE = 1 * DEFAULT_SR
+
+    DEFAULT_PROCESSOR = 0
+
+    def __init__(self, model_path:str, params:MDX_Model, processor=DEFAULT_PROCESSOR):
+
+        # Set the device and the provider (CPU or CUDA)
+        self.device = torch.device(f'cuda:{processor}') if processor >= 0 else torch.device('cpu')
+        self.provider = ['CUDAExecutionProvider'] if processor >= 0 else ['CPUExecutionProvider']
+
+        self.model = params
+
+        # Load the ONNX model using ONNX Runtime
+        self.ort = ort.InferenceSession(model_path, providers=self.provider)
+        # Preload the model for faster performance
+        self.ort.run(None, {'input':torch.rand(1, 4, params.dim_f, params.dim_t).numpy()})
+        self.process = lambda spec:self.ort.run(None, {'input': spec.cpu().numpy()})[0]
+
+        self.prog = None
+
+    @staticmethod
+    def get_hash(model_path):
+        try:
+            with open(model_path, 'rb') as f:
+                f.seek(- 10000 * 1024, 2)
+                model_hash = hashlib.md5(f.read()).hexdigest()
+        except:
+            model_hash = hashlib.md5(open(model_path,'rb').read()).hexdigest()
+            
+        return model_hash
+    
+    @staticmethod
+    def segment(wave, combine=True, chunk_size=DEFAULT_CHUNK_SIZE, margin_size=DEFAULT_MARGIN_SIZE):
+        """
+        Segment or join segmented wave array
+
+        Args:
+            wave: (np.array) Wave array to be segmented or joined
+            combine: (bool) If True, combines segmented wave array. If False, segments wave array.
+            chunk_size: (int) Size of each segment (in samples)
+            margin_size: (int) Size of margin between segments (in samples)
+
+        Returns:
+            numpy array: Segmented or joined wave array
+        """
+        
+        if combine:
+            processed_wave = None  # Initializing as None instead of [] for later numpy array concatenation
+            for segment_count, segment in enumerate(wave):
+                start = 0 if segment_count == 0 else margin_size
+                end = None if segment_count == len(wave)-1 else -margin_size
+                if margin_size == 0:
+                    end = None
+                if processed_wave is None:  # Create array for first segment
+                    processed_wave = segment[:, start:end]
+                else:  # Concatenate to existing array for subsequent segments
+                    processed_wave = np.concatenate((processed_wave, segment[:, start:end]), axis=-1)
+
+        else:
+            processed_wave = []
+            sample_count = wave.shape[-1]
+
+            if chunk_size <= 0 or chunk_size > sample_count:
+                chunk_size = sample_count
+
+            if margin_size > chunk_size:
+                margin_size = chunk_size
+
+            for segment_count, skip in enumerate(range(0, sample_count, chunk_size)):
+
+                margin = 0 if segment_count == 0 else margin_size
+                end = min(skip+chunk_size+margin_size, sample_count)
+                start = skip-margin
+
+                cut = wave[:,start:end].copy()
+                processed_wave.append(cut)
+
+                if end == sample_count:
+                    break
+        
+        return processed_wave
+
+    def pad_wave(self, wave):
+        """
+        Pad the wave array to match the required chunk size
+
+        Args:
+            wave: (np.array) Wave array to be padded
+
+        Returns:
+            tuple: (padded_wave, pad, trim)
+                - padded_wave: Padded wave array
+                - pad: Number of samples that were padded
+                - trim: Number of samples that were trimmed
+        """
+        n_sample = wave.shape[1]
+        trim = self.model.n_fft//2
+        gen_size = self.model.chunk_size-2*trim
+        pad = gen_size - n_sample%gen_size
+
+        # Padded wave
+        wave_p = np.concatenate((np.zeros((2,trim)), wave, np.zeros((2,pad)), np.zeros((2,trim))), 1)
+
+        mix_waves = []
+        for i in range(0, n_sample+pad, gen_size):
+            waves = np.array(wave_p[:, i:i+self.model.chunk_size])
+            mix_waves.append(waves)
+
+        mix_waves = torch.tensor(mix_waves, dtype=torch.float32).to(self.device)
+
+        return mix_waves, pad, trim
+
+    def _process_wave(self, mix_waves, trim, pad, q:queue.Queue, _id:int):
+        """
+        Process each wave segment in a multi-threaded environment
+
+        Args:
+            mix_waves: (torch.Tensor) Wave segments to be processed
+            trim: (int) Number of samples trimmed during padding
+            pad: (int) Number of samples padded during padding
+            q: (queue.Queue) Queue to hold the processed wave segments
+            _id: (int) Identifier of the processed wave segment
+
+        Returns:
+            numpy array: Processed wave segment
+        """
+        mix_waves = mix_waves.split(1)
+        with torch.no_grad():
+            pw = []
+            for mix_wave in mix_waves:
+                self.prog.update()
+                spec = self.model.stft(mix_wave)
+                processed_spec = torch.tensor(self.process(spec))
+                processed_wav = self.model.istft(processed_spec.to(self.device))
+                processed_wav = processed_wav[:,:,trim:-trim].transpose(0,1).reshape(2, -1).cpu().numpy()
+                pw.append(processed_wav)
+        processed_signal = np.concatenate(pw, axis=-1)[:, :-pad]
+        q.put({_id:processed_signal})
+        return processed_signal
+
+    def process_wave(self, wave:np.array, mt_threads=1):
+        """
+        Process the wave array in a multi-threaded environment
+
+        Args:
+            wave: (np.array) Wave array to be processed
+            mt_threads: (int) Number of threads to be used for processing
+
+        Returns:
+            numpy array: Processed wave array
+        """
+        self.prog = tqdm(total=0)
+        chunk = wave.shape[-1]//mt_threads
+        waves = self.segment(wave, False, chunk)
+
+        # Create a queue to hold the processed wave segments
+        q = queue.Queue()
+        threads = []
+        for c, batch in enumerate(waves):
+            mix_waves, pad, trim = self.pad_wave(batch)
+            self.prog.total = len(mix_waves)*mt_threads
+            thread = threading.Thread(target=self._process_wave, args=(mix_waves, trim, pad, q, c))
+            thread.start()
+            threads.append(thread)
+        for thread in threads:
+            thread.join()
+        self.prog.close()
+
+        processed_batches = []
+        while not q.empty():
+            processed_batches.append(q.get())
+        processed_batches = [list(wave.values())[0] for wave in sorted(processed_batches, key=lambda d: list(d.keys())[0])]
+        assert len(processed_batches) == len(waves), 'Incomplete processed batches, please reduce batch size!'
+        return self.segment(processed_batches, True, chunk)
\ No newline at end of file
diff --git a/mdx_processing_script.py b/mdx_processing_script.py
new file mode 100644
index 0000000000000000000000000000000000000000..05616843300aacf46c98ce06f017ba1d0794f313
--- /dev/null
+++ b/mdx_processing_script.py
@@ -0,0 +1,146 @@
+import gc
+import requests
+import subprocess
+import logging
+import sys
+from bs4 import BeautifulSoup
+import torch, pdb, os, warnings, librosa
+import soundfile as sf
+from tqdm import tqdm
+import numpy as np
+import torch
+now_dir = os.getcwd()
+sys.path.append(now_dir)
+import mdx
+branch = "https://github.com/NaJeongMo/Colab-for-MDX_B"
+
+model_params = "https://raw.githubusercontent.com/TRvlvr/application_data/main/mdx_model_data/model_data.json"
+_Models = "https://github.com/TRvlvr/model_repo/releases/download/all_public_uvr_models/"
+# _models = "https://pastebin.com/raw/jBzYB8vz"
+_models = "https://raw.githubusercontent.com/TRvlvr/application_data/main/filelists/download_checks.json"
+stem_naming = "https://pastebin.com/raw/mpH4hRcF"
+
+file_folder = "Colab-for-MDX_B"
+model_ids = requests.get(_models).json()
+model_ids = model_ids["mdx_download_list"].values()
+#print(model_ids)
+model_params = requests.get(model_params).json()
+stem_naming = requests.get(stem_naming).json()
+
+os.makedirs("tmp_models", exist_ok=True)
+
+warnings.filterwarnings("ignore")
+cpu = torch.device("cpu")
+if torch.cuda.is_available():
+    device = torch.device("cuda:0")
+elif torch.backends.mps.is_available():
+    device = torch.device("mps")
+else:
+    device = torch.device("cpu")
+
+
+def get_model_list():
+    return model_ids
+
+def id_to_ptm(mkey):
+    if mkey in model_ids:
+        mpath = f"{now_dir}/tmp_models/{mkey}"
+        if not os.path.exists(f'{now_dir}/tmp_models/{mkey}'):
+            print('Downloading model...',end=' ')
+            subprocess.run(
+                ["wget", _Models+mkey, "-O", mpath]
+            )
+            print(f'saved to {mpath}')
+            # get_ipython().system(f'gdown {model_id} -O /content/tmp_models/{mkey}')
+            return mpath
+        else:
+            return mpath
+    else:
+        mpath = f'models/{mkey}'
+        return mpath
+
+def prepare_mdx(onnx,custom_param=False, dim_f=None, dim_t=None, n_fft=None, stem_name=None, compensation=None):
+    device = torch.device('cuda:0') if torch.cuda.is_available() else torch.device('cpu')
+    if custom_param:
+        assert not (dim_f is None or dim_t is None or n_fft is None or compensation is None), 'Custom parameter selected, but incomplete parameters are provided.'
+        mdx_model = mdx.MDX_Model(
+            device,
+            dim_f = dim_f,
+            dim_t = dim_t,
+            n_fft = n_fft,
+            stem_name=stem_name,
+            compensation=compensation
+        )
+    else:
+        model_hash = mdx.MDX.get_hash(onnx)
+        if model_hash in model_params:
+            mp = model_params.get(model_hash)
+            mdx_model = mdx.MDX_Model(
+                device,
+                dim_f = mp["mdx_dim_f_set"],
+                dim_t = 2**mp["mdx_dim_t_set"],
+                n_fft = mp["mdx_n_fft_scale_set"],
+                stem_name=mp["primary_stem"],
+                compensation=compensation if not custom_param and compensation is not None else mp["compensate"]
+            )
+    return mdx_model
+
+def run_mdx(onnx, mdx_model,filename, output_format='wav',diff=False,suffix=None,diff_suffix=None, denoise=False, m_threads=2):
+    mdx_sess = mdx.MDX(onnx,mdx_model)
+    print(f"Processing: {filename}")
+    if filename.lower().endswith('.wav'):
+        wave, sr = librosa.load(filename, mono=False, sr=44100)
+    else:
+        temp_wav = 'temp_audio.wav'
+        subprocess.run(['ffmpeg', '-i', filename, '-ar', '44100', '-ac', '2', temp_wav])  # Convert to WAV format
+        wave, sr = librosa.load(temp_wav, mono=False, sr=44100)
+        os.remove(temp_wav)
+    
+    #wave, sr = librosa.load(filename,mono=False, sr=44100)
+    # normalizing input wave gives better output
+    peak = max(np.max(wave), abs(np.min(wave)))
+    wave /= peak
+    if denoise:
+        wave_processed = -(mdx_sess.process_wave(-wave, m_threads)) + (mdx_sess.process_wave(wave, m_threads))
+        wave_processed *= 0.5
+    else:
+        wave_processed = mdx_sess.process_wave(wave, m_threads)
+    # return to previous peak
+    wave_processed *= peak
+
+    stem_name = mdx_model.stem_name if suffix is None else suffix # use suffix if provided
+    save_path = os.path.basename(os.path.splitext(filename)[0])
+    #vocals_save_path = os.path.join(vocals_folder, f"{save_path}_{stem_name}.{output_format}")
+    #instrumental_save_path = os.path.join(instrumental_folder, f"{save_path}_{stem_name}.{output_format}")
+    save_path = f"{os.path.basename(os.path.splitext(filename)[0])}_{stem_name}.{output_format}"
+    save_path = os.path.join(
+            'audios',
+            save_path
+        )
+    sf.write(
+        save_path,
+        wave_processed.T,
+        sr
+    )
+
+    print(f'done, saved to: {save_path}')
+
+    if diff:
+        diff_stem_name = stem_naming.get(stem_name) if diff_suffix is None else diff_suffix # use suffix if provided
+        stem_name = f"{stem_name}_diff" if diff_stem_name is None else diff_stem_name
+        save_path = f"{os.path.basename(os.path.splitext(filename)[0])}_{stem_name}.{output_format}"
+        save_path = os.path.join(
+                'audio-others',
+                save_path
+            )
+        sf.write(
+            save_path,
+            (-wave_processed.T*mdx_model.compensation)+wave.T,
+            sr
+        )
+        print(f'invert done, saved to: {save_path}')
+    del mdx_sess, wave_processed, wave
+    gc.collect()
+
+if __name__ == "__main__":
+    print()
\ No newline at end of file
diff --git a/model/.gitkeep b/model/.gitkeep
new file mode 100644
index 0000000000000000000000000000000000000000..8b137891791fe96927ad78e64b0aad7bded08bdc
--- /dev/null
+++ b/model/.gitkeep
@@ -0,0 +1 @@
+
diff --git a/poetry.lock b/poetry.lock
new file mode 100644
index 0000000000000000000000000000000000000000..f7aad0a171d64c76d3f404939e2f0cedd0043b8d
--- /dev/null
+++ b/poetry.lock
@@ -0,0 +1,3881 @@
+# This file is automatically @generated by Poetry 1.5.1 and should not be changed by hand.
+
+[[package]]
+name = "absl-py"
+version = "1.4.0"
+description = "Abseil Python Common Libraries, see https://github.com/abseil/abseil-py."
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "absl-py-1.4.0.tar.gz", hash = "sha256:d2c244d01048ba476e7c080bd2c6df5e141d211de80223460d5b3b8a2a58433d"},
+    {file = "absl_py-1.4.0-py3-none-any.whl", hash = "sha256:0d3fe606adfa4f7db64792dd4c7aee4ee0c38ab75dfd353b7a83ed3e957fcb47"},
+]
+
+[[package]]
+name = "aiofiles"
+version = "23.1.0"
+description = "File support for asyncio."
+optional = false
+python-versions = ">=3.7,<4.0"
+files = [
+    {file = "aiofiles-23.1.0-py3-none-any.whl", hash = "sha256:9312414ae06472eb6f1d163f555e466a23aed1c8f60c30cccf7121dba2e53eb2"},
+    {file = "aiofiles-23.1.0.tar.gz", hash = "sha256:edd247df9a19e0db16534d4baaf536d6609a43e1de5401d7a4c1c148753a1635"},
+]
+
+[[package]]
+name = "aiohttp"
+version = "3.8.4"
+description = "Async http client/server framework (asyncio)"
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "aiohttp-3.8.4-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:5ce45967538fb747370308d3145aa68a074bdecb4f3a300869590f725ced69c1"},
+    {file = "aiohttp-3.8.4-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:b744c33b6f14ca26b7544e8d8aadff6b765a80ad6164fb1a430bbadd593dfb1a"},
+    {file = "aiohttp-3.8.4-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:1a45865451439eb320784918617ba54b7a377e3501fb70402ab84d38c2cd891b"},
+    {file = "aiohttp-3.8.4-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a86d42d7cba1cec432d47ab13b6637bee393a10f664c425ea7b305d1301ca1a3"},
+    {file = "aiohttp-3.8.4-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:ee3c36df21b5714d49fc4580247947aa64bcbe2939d1b77b4c8dcb8f6c9faecc"},
+    {file = "aiohttp-3.8.4-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:176a64b24c0935869d5bbc4c96e82f89f643bcdf08ec947701b9dbb3c956b7dd"},
+    {file = "aiohttp-3.8.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c844fd628851c0bc309f3c801b3a3d58ce430b2ce5b359cd918a5a76d0b20cb5"},
+    {file = "aiohttp-3.8.4-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:5393fb786a9e23e4799fec788e7e735de18052f83682ce2dfcabaf1c00c2c08e"},
+    {file = "aiohttp-3.8.4-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:e4b09863aae0dc965c3ef36500d891a3ff495a2ea9ae9171e4519963c12ceefd"},
+    {file = "aiohttp-3.8.4-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:adfbc22e87365a6e564c804c58fc44ff7727deea782d175c33602737b7feadb6"},
+    {file = "aiohttp-3.8.4-cp310-cp310-musllinux_1_1_ppc64le.whl", hash = "sha256:147ae376f14b55f4f3c2b118b95be50a369b89b38a971e80a17c3fd623f280c9"},
+    {file = "aiohttp-3.8.4-cp310-cp310-musllinux_1_1_s390x.whl", hash = "sha256:eafb3e874816ebe2a92f5e155f17260034c8c341dad1df25672fb710627c6949"},
+    {file = "aiohttp-3.8.4-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:c6cc15d58053c76eacac5fa9152d7d84b8d67b3fde92709195cb984cfb3475ea"},
+    {file = "aiohttp-3.8.4-cp310-cp310-win32.whl", hash = "sha256:59f029a5f6e2d679296db7bee982bb3d20c088e52a2977e3175faf31d6fb75d1"},
+    {file = "aiohttp-3.8.4-cp310-cp310-win_amd64.whl", hash = "sha256:fe7ba4a51f33ab275515f66b0a236bcde4fb5561498fe8f898d4e549b2e4509f"},
+    {file = "aiohttp-3.8.4-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:3d8ef1a630519a26d6760bc695842579cb09e373c5f227a21b67dc3eb16cfea4"},
+    {file = "aiohttp-3.8.4-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:5b3f2e06a512e94722886c0827bee9807c86a9f698fac6b3aee841fab49bbfb4"},
+    {file = "aiohttp-3.8.4-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:3a80464982d41b1fbfe3154e440ba4904b71c1a53e9cd584098cd41efdb188ef"},
+    {file = "aiohttp-3.8.4-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:8b631e26df63e52f7cce0cce6507b7a7f1bc9b0c501fcde69742130b32e8782f"},
+    {file = "aiohttp-3.8.4-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:3f43255086fe25e36fd5ed8f2ee47477408a73ef00e804cb2b5cba4bf2ac7f5e"},
+    {file = "aiohttp-3.8.4-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:4d347a172f866cd1d93126d9b239fcbe682acb39b48ee0873c73c933dd23bd0f"},
+    {file = "aiohttp-3.8.4-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a3fec6a4cb5551721cdd70473eb009d90935b4063acc5f40905d40ecfea23e05"},
+    {file = "aiohttp-3.8.4-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:80a37fe8f7c1e6ce8f2d9c411676e4bc633a8462844e38f46156d07a7d401654"},
+    {file = "aiohttp-3.8.4-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:d1e6a862b76f34395a985b3cd39a0d949ca80a70b6ebdea37d3ab39ceea6698a"},
+    {file = "aiohttp-3.8.4-cp311-cp311-musllinux_1_1_i686.whl", hash = "sha256:cd468460eefef601ece4428d3cf4562459157c0f6523db89365202c31b6daebb"},
+    {file = "aiohttp-3.8.4-cp311-cp311-musllinux_1_1_ppc64le.whl", hash = "sha256:618c901dd3aad4ace71dfa0f5e82e88b46ef57e3239fc7027773cb6d4ed53531"},
+    {file = "aiohttp-3.8.4-cp311-cp311-musllinux_1_1_s390x.whl", hash = "sha256:652b1bff4f15f6287550b4670546a2947f2a4575b6c6dff7760eafb22eacbf0b"},
+    {file = "aiohttp-3.8.4-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:80575ba9377c5171407a06d0196b2310b679dc752d02a1fcaa2bc20b235dbf24"},
+    {file = "aiohttp-3.8.4-cp311-cp311-win32.whl", hash = "sha256:bbcf1a76cf6f6dacf2c7f4d2ebd411438c275faa1dc0c68e46eb84eebd05dd7d"},
+    {file = "aiohttp-3.8.4-cp311-cp311-win_amd64.whl", hash = "sha256:6e74dd54f7239fcffe07913ff8b964e28b712f09846e20de78676ce2a3dc0bfc"},
+    {file = "aiohttp-3.8.4-cp36-cp36m-macosx_10_9_x86_64.whl", hash = "sha256:880e15bb6dad90549b43f796b391cfffd7af373f4646784795e20d92606b7a51"},
+    {file = "aiohttp-3.8.4-cp36-cp36m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:bb96fa6b56bb536c42d6a4a87dfca570ff8e52de2d63cabebfd6fb67049c34b6"},
+    {file = "aiohttp-3.8.4-cp36-cp36m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:4a6cadebe132e90cefa77e45f2d2f1a4b2ce5c6b1bfc1656c1ddafcfe4ba8131"},
+    {file = "aiohttp-3.8.4-cp36-cp36m-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:f352b62b45dff37b55ddd7b9c0c8672c4dd2eb9c0f9c11d395075a84e2c40f75"},
+    {file = "aiohttp-3.8.4-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7ab43061a0c81198d88f39aaf90dae9a7744620978f7ef3e3708339b8ed2ef01"},
+    {file = "aiohttp-3.8.4-cp36-cp36m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:c9cb1565a7ad52e096a6988e2ee0397f72fe056dadf75d17fa6b5aebaea05622"},
+    {file = "aiohttp-3.8.4-cp36-cp36m-musllinux_1_1_aarch64.whl", hash = "sha256:1b3ea7edd2d24538959c1c1abf97c744d879d4e541d38305f9bd7d9b10c9ec41"},
+    {file = "aiohttp-3.8.4-cp36-cp36m-musllinux_1_1_i686.whl", hash = "sha256:7c7837fe8037e96b6dd5cfcf47263c1620a9d332a87ec06a6ca4564e56bd0f36"},
+    {file = "aiohttp-3.8.4-cp36-cp36m-musllinux_1_1_ppc64le.whl", hash = "sha256:3b90467ebc3d9fa5b0f9b6489dfb2c304a1db7b9946fa92aa76a831b9d587e99"},
+    {file = "aiohttp-3.8.4-cp36-cp36m-musllinux_1_1_s390x.whl", hash = "sha256:cab9401de3ea52b4b4c6971db5fb5c999bd4260898af972bf23de1c6b5dd9d71"},
+    {file = "aiohttp-3.8.4-cp36-cp36m-musllinux_1_1_x86_64.whl", hash = "sha256:d1f9282c5f2b5e241034a009779e7b2a1aa045f667ff521e7948ea9b56e0c5ff"},
+    {file = "aiohttp-3.8.4-cp36-cp36m-win32.whl", hash = "sha256:5e14f25765a578a0a634d5f0cd1e2c3f53964553a00347998dfdf96b8137f777"},
+    {file = "aiohttp-3.8.4-cp36-cp36m-win_amd64.whl", hash = "sha256:4c745b109057e7e5f1848c689ee4fb3a016c8d4d92da52b312f8a509f83aa05e"},
+    {file = "aiohttp-3.8.4-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:aede4df4eeb926c8fa70de46c340a1bc2c6079e1c40ccf7b0eae1313ffd33519"},
+    {file = "aiohttp-3.8.4-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4ddaae3f3d32fc2cb4c53fab020b69a05c8ab1f02e0e59665c6f7a0d3a5be54f"},
+    {file = "aiohttp-3.8.4-cp37-cp37m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:c4eb3b82ca349cf6fadcdc7abcc8b3a50ab74a62e9113ab7a8ebc268aad35bb9"},
+    {file = "aiohttp-3.8.4-cp37-cp37m-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:9bcb89336efa095ea21b30f9e686763f2be4478f1b0a616969551982c4ee4c3b"},
+    {file = "aiohttp-3.8.4-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6c08e8ed6fa3d477e501ec9db169bfac8140e830aa372d77e4a43084d8dd91ab"},
+    {file = "aiohttp-3.8.4-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:c6cd05ea06daca6ad6a4ca3ba7fe7dc5b5de063ff4daec6170ec0f9979f6c332"},
+    {file = "aiohttp-3.8.4-cp37-cp37m-musllinux_1_1_aarch64.whl", hash = "sha256:b7a00a9ed8d6e725b55ef98b1b35c88013245f35f68b1b12c5cd4100dddac333"},
+    {file = "aiohttp-3.8.4-cp37-cp37m-musllinux_1_1_i686.whl", hash = "sha256:de04b491d0e5007ee1b63a309956eaed959a49f5bb4e84b26c8f5d49de140fa9"},
+    {file = "aiohttp-3.8.4-cp37-cp37m-musllinux_1_1_ppc64le.whl", hash = "sha256:40653609b3bf50611356e6b6554e3a331f6879fa7116f3959b20e3528783e699"},
+    {file = "aiohttp-3.8.4-cp37-cp37m-musllinux_1_1_s390x.whl", hash = "sha256:dbf3a08a06b3f433013c143ebd72c15cac33d2914b8ea4bea7ac2c23578815d6"},
+    {file = "aiohttp-3.8.4-cp37-cp37m-musllinux_1_1_x86_64.whl", hash = "sha256:854f422ac44af92bfe172d8e73229c270dc09b96535e8a548f99c84f82dde241"},
+    {file = "aiohttp-3.8.4-cp37-cp37m-win32.whl", hash = "sha256:aeb29c84bb53a84b1a81c6c09d24cf33bb8432cc5c39979021cc0f98c1292a1a"},
+    {file = "aiohttp-3.8.4-cp37-cp37m-win_amd64.whl", hash = "sha256:db3fc6120bce9f446d13b1b834ea5b15341ca9ff3f335e4a951a6ead31105480"},
+    {file = "aiohttp-3.8.4-cp38-cp38-macosx_10_9_universal2.whl", hash = "sha256:fabb87dd8850ef0f7fe2b366d44b77d7e6fa2ea87861ab3844da99291e81e60f"},
+    {file = "aiohttp-3.8.4-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:91f6d540163f90bbaef9387e65f18f73ffd7c79f5225ac3d3f61df7b0d01ad15"},
+    {file = "aiohttp-3.8.4-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:d265f09a75a79a788237d7f9054f929ced2e69eb0bb79de3798c468d8a90f945"},
+    {file = "aiohttp-3.8.4-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:3d89efa095ca7d442a6d0cbc755f9e08190ba40069b235c9886a8763b03785da"},
+    {file = "aiohttp-3.8.4-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:4dac314662f4e2aa5009977b652d9b8db7121b46c38f2073bfeed9f4049732cd"},
+    {file = "aiohttp-3.8.4-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:fe11310ae1e4cd560035598c3f29d86cef39a83d244c7466f95c27ae04850f10"},
+    {file = "aiohttp-3.8.4-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6ddb2a2026c3f6a68c3998a6c47ab6795e4127315d2e35a09997da21865757f8"},
+    {file = "aiohttp-3.8.4-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:e75b89ac3bd27d2d043b234aa7b734c38ba1b0e43f07787130a0ecac1e12228a"},
+    {file = "aiohttp-3.8.4-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:6e601588f2b502c93c30cd5a45bfc665faaf37bbe835b7cfd461753068232074"},
+    {file = "aiohttp-3.8.4-cp38-cp38-musllinux_1_1_i686.whl", hash = "sha256:a5d794d1ae64e7753e405ba58e08fcfa73e3fad93ef9b7e31112ef3c9a0efb52"},
+    {file = "aiohttp-3.8.4-cp38-cp38-musllinux_1_1_ppc64le.whl", hash = "sha256:a1f4689c9a1462f3df0a1f7e797791cd6b124ddbee2b570d34e7f38ade0e2c71"},
+    {file = "aiohttp-3.8.4-cp38-cp38-musllinux_1_1_s390x.whl", hash = "sha256:3032dcb1c35bc330134a5b8a5d4f68c1a87252dfc6e1262c65a7e30e62298275"},
+    {file = "aiohttp-3.8.4-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:8189c56eb0ddbb95bfadb8f60ea1b22fcfa659396ea36f6adcc521213cd7b44d"},
+    {file = "aiohttp-3.8.4-cp38-cp38-win32.whl", hash = "sha256:33587f26dcee66efb2fff3c177547bd0449ab7edf1b73a7f5dea1e38609a0c54"},
+    {file = "aiohttp-3.8.4-cp38-cp38-win_amd64.whl", hash = "sha256:e595432ac259af2d4630008bf638873d69346372d38255774c0e286951e8b79f"},
+    {file = "aiohttp-3.8.4-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:5a7bdf9e57126dc345b683c3632e8ba317c31d2a41acd5800c10640387d193ed"},
+    {file = "aiohttp-3.8.4-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:22f6eab15b6db242499a16de87939a342f5a950ad0abaf1532038e2ce7d31567"},
+    {file = "aiohttp-3.8.4-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:7235604476a76ef249bd64cb8274ed24ccf6995c4a8b51a237005ee7a57e8643"},
+    {file = "aiohttp-3.8.4-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ea9eb976ffdd79d0e893869cfe179a8f60f152d42cb64622fca418cd9b18dc2a"},
+    {file = "aiohttp-3.8.4-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:92c0cea74a2a81c4c76b62ea1cac163ecb20fb3ba3a75c909b9fa71b4ad493cf"},
+    {file = "aiohttp-3.8.4-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:493f5bc2f8307286b7799c6d899d388bbaa7dfa6c4caf4f97ef7521b9cb13719"},
+    {file = "aiohttp-3.8.4-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0a63f03189a6fa7c900226e3ef5ba4d3bd047e18f445e69adbd65af433add5a2"},
+    {file = "aiohttp-3.8.4-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:10c8cefcff98fd9168cdd86c4da8b84baaa90bf2da2269c6161984e6737bf23e"},
+    {file = "aiohttp-3.8.4-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:bca5f24726e2919de94f047739d0a4fc01372801a3672708260546aa2601bf57"},
+    {file = "aiohttp-3.8.4-cp39-cp39-musllinux_1_1_i686.whl", hash = "sha256:03baa76b730e4e15a45f81dfe29a8d910314143414e528737f8589ec60cf7391"},
+    {file = "aiohttp-3.8.4-cp39-cp39-musllinux_1_1_ppc64le.whl", hash = "sha256:8c29c77cc57e40f84acef9bfb904373a4e89a4e8b74e71aa8075c021ec9078c2"},
+    {file = "aiohttp-3.8.4-cp39-cp39-musllinux_1_1_s390x.whl", hash = "sha256:03543dcf98a6619254b409be2d22b51f21ec66272be4ebda7b04e6412e4b2e14"},
+    {file = "aiohttp-3.8.4-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:17b79c2963db82086229012cff93ea55196ed31f6493bb1ccd2c62f1724324e4"},
+    {file = "aiohttp-3.8.4-cp39-cp39-win32.whl", hash = "sha256:34ce9f93a4a68d1272d26030655dd1b58ff727b3ed2a33d80ec433561b03d67a"},
+    {file = "aiohttp-3.8.4-cp39-cp39-win_amd64.whl", hash = "sha256:41a86a69bb63bb2fc3dc9ad5ea9f10f1c9c8e282b471931be0268ddd09430b04"},
+    {file = "aiohttp-3.8.4.tar.gz", hash = "sha256:bf2e1a9162c1e441bf805a1fd166e249d574ca04e03b34f97e2928769e91ab5c"},
+]
+
+[package.dependencies]
+aiosignal = ">=1.1.2"
+async-timeout = ">=4.0.0a3,<5.0"
+attrs = ">=17.3.0"
+charset-normalizer = ">=2.0,<4.0"
+frozenlist = ">=1.1.1"
+multidict = ">=4.5,<7.0"
+yarl = ">=1.0,<2.0"
+
+[package.extras]
+speedups = ["Brotli", "aiodns", "cchardet"]
+
+[[package]]
+name = "aiosignal"
+version = "1.3.1"
+description = "aiosignal: a list of registered asynchronous callbacks"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "aiosignal-1.3.1-py3-none-any.whl", hash = "sha256:f8376fb07dd1e86a584e4fcdec80b36b7f81aac666ebc724e2c090300dd83b17"},
+    {file = "aiosignal-1.3.1.tar.gz", hash = "sha256:54cd96e15e1649b75d6c87526a6ff0b6c1b0dd3459f43d9ca11d48c339b68cfc"},
+]
+
+[package.dependencies]
+frozenlist = ">=1.1.0"
+
+[[package]]
+name = "altair"
+version = "4.2.2"
+description = "Altair: A declarative statistical visualization library for Python."
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "altair-4.2.2-py3-none-any.whl", hash = "sha256:8b45ebeaf8557f2d760c5c77b79f02ae12aee7c46c27c06014febab6f849bc87"},
+    {file = "altair-4.2.2.tar.gz", hash = "sha256:39399a267c49b30d102c10411e67ab26374156a84b1aeb9fcd15140429ba49c5"},
+]
+
+[package.dependencies]
+entrypoints = "*"
+jinja2 = "*"
+jsonschema = ">=3.0"
+numpy = "*"
+pandas = ">=0.18"
+toolz = "*"
+
+[package.extras]
+dev = ["black", "docutils", "flake8", "ipython", "m2r", "mistune (<2.0.0)", "pytest", "recommonmark", "sphinx", "vega-datasets"]
+
+[[package]]
+name = "antlr4-python3-runtime"
+version = "4.8"
+description = "ANTLR 4.8 runtime for Python 3.7"
+optional = false
+python-versions = "*"
+files = [
+    {file = "antlr4-python3-runtime-4.8.tar.gz", hash = "sha256:15793f5d0512a372b4e7d2284058ad32ce7dd27126b105fb0b2245130445db33"},
+]
+
+[[package]]
+name = "anyio"
+version = "3.6.2"
+description = "High level compatibility layer for multiple asynchronous event loop implementations"
+optional = false
+python-versions = ">=3.6.2"
+files = [
+    {file = "anyio-3.6.2-py3-none-any.whl", hash = "sha256:fbbe32bd270d2a2ef3ed1c5d45041250284e31fc0a4df4a5a6071842051a51e3"},
+    {file = "anyio-3.6.2.tar.gz", hash = "sha256:25ea0d673ae30af41a0c442f81cf3b38c7e79fdc7b60335a4c14e05eb0947421"},
+]
+
+[package.dependencies]
+idna = ">=2.8"
+sniffio = ">=1.1"
+
+[package.extras]
+doc = ["packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"]
+test = ["contextlib2", "coverage[toml] (>=4.5)", "hypothesis (>=4.0)", "mock (>=4)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (<0.15)", "uvloop (>=0.15)"]
+trio = ["trio (>=0.16,<0.22)"]
+
+[[package]]
+name = "async-timeout"
+version = "4.0.2"
+description = "Timeout context manager for asyncio programs"
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "async-timeout-4.0.2.tar.gz", hash = "sha256:2163e1640ddb52b7a8c80d0a67a08587e5d245cc9c553a74a847056bc2976b15"},
+    {file = "async_timeout-4.0.2-py3-none-any.whl", hash = "sha256:8ca1e4fcf50d07413d66d1a5e416e42cfdf5851c981d679a09851a6853383b3c"},
+]
+
+[[package]]
+name = "attrs"
+version = "22.2.0"
+description = "Classes Without Boilerplate"
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "attrs-22.2.0-py3-none-any.whl", hash = "sha256:29e95c7f6778868dbd49170f98f8818f78f3dc5e0e37c0b1f474e3561b240836"},
+    {file = "attrs-22.2.0.tar.gz", hash = "sha256:c9227bfc2f01993c03f68db37d1d15c9690188323c067c641f1a35ca58185f99"},
+]
+
+[package.extras]
+cov = ["attrs[tests]", "coverage-enable-subprocess", "coverage[toml] (>=5.3)"]
+dev = ["attrs[docs,tests]"]
+docs = ["furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-towncrier", "towncrier", "zope.interface"]
+tests = ["attrs[tests-no-zope]", "zope.interface"]
+tests-no-zope = ["cloudpickle", "cloudpickle", "hypothesis", "hypothesis", "mypy (>=0.971,<0.990)", "mypy (>=0.971,<0.990)", "pympler", "pympler", "pytest (>=4.3.0)", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-mypy-plugins", "pytest-xdist[psutil]", "pytest-xdist[psutil]"]
+
+[[package]]
+name = "audioread"
+version = "3.0.0"
+description = "multi-library, cross-platform audio decoding"
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "audioread-3.0.0.tar.gz", hash = "sha256:121995bd207eb1fda3d566beb851d3534275925bc35a4fb6da0cb11de0f7251a"},
+]
+
+[[package]]
+name = "bitarray"
+version = "2.7.3"
+description = "efficient arrays of booleans -- C extension"
+optional = false
+python-versions = "*"
+files = [
+    {file = "bitarray-2.7.3-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:979d42e0b2c3113526f9716a461e08671788a23ce7e3b5cd090ce3e6a6762641"},
+    {file = "bitarray-2.7.3-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:860edf8533223d82bd6201894bcaf540f828f49075f363390eecf04b12fb94cb"},
+    {file = "bitarray-2.7.3-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:78378d8dacbe1f4f263347f42ec0a41cc2097cd671c6ac30a65a838284a5e141"},
+    {file = "bitarray-2.7.3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:888df211aafe5fad41c0792a686d95c8ba37345d5037f437aa3c09608f9c3b56"},
+    {file = "bitarray-2.7.3-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:fb3f003dee96dbf24a6df71443557f249b17b20083c189995302b14eb01530bf"},
+    {file = "bitarray-2.7.3-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:c531532c21bc1063e65957a1a85a2d13601ec21801f70821c89d9339b16ebc78"},
+    {file = "bitarray-2.7.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:8b8fd92c8026e4ba6874e94f538890e35bef2a3a18ea54e3663c578b7916ade1"},
+    {file = "bitarray-2.7.3-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:6d19c34a2121eccfeb642d4ad71163bd3342a8f3a99e6724fe824bdfbc0a5b65"},
+    {file = "bitarray-2.7.3-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:102db74ee82ec5774aba01481e73eedaebd27ba167344a81d3b42e6fbf9ffb77"},
+    {file = "bitarray-2.7.3-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:7f6540b45b2230442f7a0614745131e0a6f28251f5d33ac19d0ed61d80db7153"},
+    {file = "bitarray-2.7.3-cp310-cp310-musllinux_1_1_ppc64le.whl", hash = "sha256:99c9345c417a9cff98f9f6e59b0350dcc10c2e0e1ea66acf7946de1cd60541fa"},
+    {file = "bitarray-2.7.3-cp310-cp310-musllinux_1_1_s390x.whl", hash = "sha256:a1d439c98e65ab8e5fbcc2b242a16e7a3f076974bff78185ff42ba2d4c220032"},
+    {file = "bitarray-2.7.3-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:87897ec0e4876c9f2c1ae313519de0ed2ad8041a4d2210a083f9b4a239add2e3"},
+    {file = "bitarray-2.7.3-cp310-cp310-win32.whl", hash = "sha256:cb46c3a4002c8322dd0e1b4b53f8a647dcb0f199f5c7a1fc03d3880c3eabbd2c"},
+    {file = "bitarray-2.7.3-cp310-cp310-win_amd64.whl", hash = "sha256:5df10eb9b794932b0cf806f412d1c6d04fb7655ca7ae5caf6354b9edc380a5f7"},
+    {file = "bitarray-2.7.3-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:27524bc92fdeb464a5057a4677a35f482cf30be2e920bd1d11c46de533cafda6"},
+    {file = "bitarray-2.7.3-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:3cf37431de779b29e5c0d8e36868f77f6df53c3c19c20e8404137e257dc80040"},
+    {file = "bitarray-2.7.3-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:8abd23f94cdcce971d932a5f0a066d40fbc61901fd087aa70d32cccd1793bd20"},
+    {file = "bitarray-2.7.3-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7659bdfe7716b14a39007e31e957fa64d7f0d9e40a1dbd024bd81b972d76bffb"},
+    {file = "bitarray-2.7.3-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:da1570f301abdfda68f4fdb40c4d3f09af4bb6e4550b4fa5395db0d142b680bc"},
+    {file = "bitarray-2.7.3-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:8becbb9649fd29ee577f9f0405ce2fba5cf9fa2c290c9b044bc235c04473f213"},
+    {file = "bitarray-2.7.3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:72fd7f6f940bc42914c86700591ccfd1daeff0e414cefcbd7843117df2fac4e9"},
+    {file = "bitarray-2.7.3-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:23b7bada6d6b62cba08f4a1b8a95da2d8592aae1db3c167dcb52abcba0a7bef5"},
+    {file = "bitarray-2.7.3-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:4b2d150a81a981537801ac7d4f4f5d082c48343612a21f4e2c4cd2e887973bd5"},
+    {file = "bitarray-2.7.3-cp311-cp311-musllinux_1_1_i686.whl", hash = "sha256:1502660ab489b1f18c3493c766252cd5d24bc1cbf4bdf3594e0a30de142ed453"},
+    {file = "bitarray-2.7.3-cp311-cp311-musllinux_1_1_ppc64le.whl", hash = "sha256:91f43f6b6c9129a56d3e2dccb8b88ffce0e4f4893dd9d69d285676bdf5b9ca14"},
+    {file = "bitarray-2.7.3-cp311-cp311-musllinux_1_1_s390x.whl", hash = "sha256:a69c99274aee2ffdc7f1cfd34044ccb7155790d6f5217d677ea46a6ddead6dd2"},
+    {file = "bitarray-2.7.3-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:d63f20299441e32171f08fc62f7ea7e401cc12a96f67a36ab2d76439ecfcb118"},
+    {file = "bitarray-2.7.3-cp311-cp311-win32.whl", hash = "sha256:0b84fd9dbf999cbca1090a7703aa1404cd01af4035c6ba3adf69d41280611fb6"},
+    {file = "bitarray-2.7.3-cp311-cp311-win_amd64.whl", hash = "sha256:76bbbb9ceebb9cbb2b14369b3681fecab226792b339f612e79f6575ca31fed45"},
+    {file = "bitarray-2.7.3-cp36-cp36m-macosx_10_9_x86_64.whl", hash = "sha256:50d5e2c026b3e3d145f64c457338ea99edcbdd302fdcbd96418251ac51a98a59"},
+    {file = "bitarray-2.7.3-cp36-cp36m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7d571056115bbdc18f199a9ee4c2a1b5884f5e63a3c05fe43d2fc7fc67320515"},
+    {file = "bitarray-2.7.3-cp36-cp36m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:e2a0313657e6656efca2148cfc91c50fdafca6f811b6c7d0906e6ba57134e560"},
+    {file = "bitarray-2.7.3-cp36-cp36m-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:d3b5abb73c45d40d27f9795dac9d6eb1515729c13f93dd67df2be07be6549990"},
+    {file = "bitarray-2.7.3-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7776c070943f45cd8303543a6625cf82f2e000ef9c885d52d7828be099e52f42"},
+    {file = "bitarray-2.7.3-cp36-cp36m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:057f9c53a34e42deed6e8813a82b9c85924f4728be28e3b9b65144569ac5a387"},
+    {file = "bitarray-2.7.3-cp36-cp36m-musllinux_1_1_aarch64.whl", hash = "sha256:8591ad5768860ad186dc94fd58b2932604a7639b57eefbbff2b4865af3407691"},
+    {file = "bitarray-2.7.3-cp36-cp36m-musllinux_1_1_i686.whl", hash = "sha256:bd7f4b2df89bf4e298756c0be0be67fb84d6aa49bda60d46805d43f0e643abd5"},
+    {file = "bitarray-2.7.3-cp36-cp36m-musllinux_1_1_ppc64le.whl", hash = "sha256:433f91c8ab8338662aaa86b0677e6c15c35f8f7b65d4c43d7d1647a8198bc0b0"},
+    {file = "bitarray-2.7.3-cp36-cp36m-musllinux_1_1_s390x.whl", hash = "sha256:31e60d8341c3189aa156ca8cb2f6370b29d79cf132e3d091714b0a5a9097eb69"},
+    {file = "bitarray-2.7.3-cp36-cp36m-musllinux_1_1_x86_64.whl", hash = "sha256:ea33ed09157e032f0a7a2627ef87f156e9927697f59b55961439d34bf45af23a"},
+    {file = "bitarray-2.7.3-cp36-cp36m-win32.whl", hash = "sha256:302149aaff75939beb8af7f32ac9bf922480033a24fb54f4ebc0c9dc175247c4"},
+    {file = "bitarray-2.7.3-cp36-cp36m-win_amd64.whl", hash = "sha256:7a8995737fae8de03b31ed83acf4f4326a55b217022009d18be19ff87fc9010e"},
+    {file = "bitarray-2.7.3-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:8b2f31a4cc28aef27355ab896e4b4cc2da2204b2b7adb674d8be7fefa0c93868"},
+    {file = "bitarray-2.7.3-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:b5df624ee8a4098c3b1149f4817f2a4a0121c4920e1c114af324bc52d6659e2b"},
+    {file = "bitarray-2.7.3-cp37-cp37m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:cb1d60ed709989e34e7158d97fdb077a2f2dfc505998a84161a70f81a6101172"},
+    {file = "bitarray-2.7.3-cp37-cp37m-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:748847e58c45a37f23db1f53a6dc16ae32aa80ee504653d79336830de1a79ed7"},
+    {file = "bitarray-2.7.3-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e4b7fdb9772e087174f446655bbc497a1600b5758f279c6d44fcf344c13d5c8a"},
+    {file = "bitarray-2.7.3-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:86e9c48ffeddb0f943e87ab65e1e95dccc9b44ef3761af3bf9642973ab7646d2"},
+    {file = "bitarray-2.7.3-cp37-cp37m-musllinux_1_1_aarch64.whl", hash = "sha256:0d1f49cc51919d6fa0f7eebd073d2c620b80079aa537d084a7fafb46a35c7a4d"},
+    {file = "bitarray-2.7.3-cp37-cp37m-musllinux_1_1_i686.whl", hash = "sha256:b43d56c7c96f5a055f4051be426496db2a616840645d0ab3733d5ceacb2f701b"},
+    {file = "bitarray-2.7.3-cp37-cp37m-musllinux_1_1_ppc64le.whl", hash = "sha256:01f8d02c3eae82c98d4259777cb2f042a0b3989d7dceeb37c643cb94b91d5a42"},
+    {file = "bitarray-2.7.3-cp37-cp37m-musllinux_1_1_s390x.whl", hash = "sha256:d089b1d0b157c9a484f8f7475eecea813d0dc3818adc5bf352903da14fe88fc3"},
+    {file = "bitarray-2.7.3-cp37-cp37m-musllinux_1_1_x86_64.whl", hash = "sha256:1362e9fb78ca72aa52ec1f1fbd62872801302001b0156ed2a1e707850cd30ffd"},
+    {file = "bitarray-2.7.3-cp37-cp37m-win32.whl", hash = "sha256:2cdf5700537e5aa4ec9f4a0b498b8d5b03b9859d503e01ea17a6a134a838aa30"},
+    {file = "bitarray-2.7.3-cp37-cp37m-win_amd64.whl", hash = "sha256:1e1553933f4533040491f4e4499bcbbfcee42c4056f56d7e18010e779daab33d"},
+    {file = "bitarray-2.7.3-cp38-cp38-macosx_10_9_universal2.whl", hash = "sha256:1048a29b3d72b1821a3ae9e8d64e71ed96c53a1a36b1da6db02091a424a8f795"},
+    {file = "bitarray-2.7.3-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:10dc358fe29d7a4c5be78ab2fb5aa50cb8066babd23e0b5589eb68e26afe58d8"},
+    {file = "bitarray-2.7.3-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:8ab6770833976448a9a973bc0df63adedc4c30de4774cec5a9928fc496423ebb"},
+    {file = "bitarray-2.7.3-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4abe2f829f6f2d330bccf1bcde2192264ab9a15d6d00e507265f46dc66557014"},
+    {file = "bitarray-2.7.3-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:87851a82bdf849e3c40ff6d8af5f734634e17f52a8f7f7e74486c2f8ce717578"},
+    {file = "bitarray-2.7.3-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:a5fc2512bdf5289a1412c936c65d17881d2b46edb0036c63a8d5605dc8d398a3"},
+    {file = "bitarray-2.7.3-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:1289f408a8b5c87cdb4fd7975d4021c6e61209ccb956d0411e72bf43c7f78463"},
+    {file = "bitarray-2.7.3-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:9ee181cc00aaba38d9812f4df4e7d828105b6dde3b068cd2c43f1d8f395e0046"},
+    {file = "bitarray-2.7.3-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:00e93f70cbcbeabd1e79accf1b6f5b2424cd40556e7877f618549523d0031c98"},
+    {file = "bitarray-2.7.3-cp38-cp38-musllinux_1_1_i686.whl", hash = "sha256:3fb6a952796d16c3a309d866eef56a8f4e5591d112c22446e67d33ecb096b44b"},
+    {file = "bitarray-2.7.3-cp38-cp38-musllinux_1_1_ppc64le.whl", hash = "sha256:0fe747a134f7f5bc0877eee58090ae7e7f23628eeb459f681ade65719c3f246a"},
+    {file = "bitarray-2.7.3-cp38-cp38-musllinux_1_1_s390x.whl", hash = "sha256:2c1b2c91bf991b5c641faee78dd5a751dff6155ec51c7a6c7f922dc85431898e"},
+    {file = "bitarray-2.7.3-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:c3956ae54285ab30d802756144887e30e013f81c9f03e5ffff9daa46d8ca0154"},
+    {file = "bitarray-2.7.3-cp38-cp38-win32.whl", hash = "sha256:00a6fc4355bd4e6ead54d05187dc4ea39f0af439b336ae113f0194673ed730ae"},
+    {file = "bitarray-2.7.3-cp38-cp38-win_amd64.whl", hash = "sha256:305e6f7441c007f296644ba3899c0306ce9fd7a482dbbc06b6e7b7bd6e0ddabc"},
+    {file = "bitarray-2.7.3-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:fe80c23409efb41b86efb5e45f334420a9b5b7828f5b3d08b5ff28f03a024d9e"},
+    {file = "bitarray-2.7.3-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:16345146b61e93ca20679c83537ccf7245f78b17035f5b1a436fd2b75da04c5e"},
+    {file = "bitarray-2.7.3-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:1af9b720a048c69e999094e2310138b7cfca5471a9d2c1dbe4b53dd10e516720"},
+    {file = "bitarray-2.7.3-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:088e6e9ea7f0eaf8b672679a68096dbc0a7a7b7a4ed567860f7362e1588370a6"},
+    {file = "bitarray-2.7.3-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:122cd70ee0de2cc9d94da8b8ebcb7dca12b9f4d3beefb94c11e110e1d87503bb"},
+    {file = "bitarray-2.7.3-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:cb9a8ee23416bd0cfd457118978bc2f6f02c20b95336db486887f670bf92c2b7"},
+    {file = "bitarray-2.7.3-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9a544f99c24b6f658907eb9edf290a9c54f4106738b2ab84cd19dc6013cc3abf"},
+    {file = "bitarray-2.7.3-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:980f6564218f853a9341fb045446539d4153338926ed2fb222e86dc9b2ae9b8f"},
+    {file = "bitarray-2.7.3-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:f64abe9301b918d2c352e42198cea0196f3639bc1ad23a4a9d8ae97f66068901"},
+    {file = "bitarray-2.7.3-cp39-cp39-musllinux_1_1_i686.whl", hash = "sha256:029c724bf38c6616b90b1c423b846b63f8d607ed5a23d270e3862696d88a5392"},
+    {file = "bitarray-2.7.3-cp39-cp39-musllinux_1_1_ppc64le.whl", hash = "sha256:16cb00911584a6e9ca0f42c305714898120dc6bfbbec90dacedeed4690331a47"},
+    {file = "bitarray-2.7.3-cp39-cp39-musllinux_1_1_s390x.whl", hash = "sha256:699b0134e87c0c4e3b224d879d218c4385a06e6b72df73b4c9c9d549155fb837"},
+    {file = "bitarray-2.7.3-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:b508e1bba4ec68fd0ef28505e2dad2f56de7df710c8334c97036705a562cb908"},
+    {file = "bitarray-2.7.3-cp39-cp39-win32.whl", hash = "sha256:4b84230624d15868e407ba8b66df54fc69ee6a9e9cb6d51eb264b8f2614596f1"},
+    {file = "bitarray-2.7.3-cp39-cp39-win_amd64.whl", hash = "sha256:757a08bf0aed5a650a399f8c66bcba00c210bce34408b6d7b09b4837bee8f4da"},
+    {file = "bitarray-2.7.3.tar.gz", hash = "sha256:f71256a32609b036adad932e1228b66a6b4e2cae6be397e588ddc0babd9a78b9"},
+]
+
+[[package]]
+name = "cachetools"
+version = "5.3.0"
+description = "Extensible memoizing collections and decorators"
+optional = false
+python-versions = "~=3.7"
+files = [
+    {file = "cachetools-5.3.0-py3-none-any.whl", hash = "sha256:429e1a1e845c008ea6c85aa35d4b98b65d6a9763eeef3e37e92728a12d1de9d4"},
+    {file = "cachetools-5.3.0.tar.gz", hash = "sha256:13dfddc7b8df938c21a940dfa6557ce6e94a2f1cdfa58eb90c805721d58f2c14"},
+]
+
+[[package]]
+name = "certifi"
+version = "2022.12.7"
+description = "Python package for providing Mozilla's CA Bundle."
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "certifi-2022.12.7-py3-none-any.whl", hash = "sha256:4ad3232f5e926d6718ec31cfc1fcadfde020920e278684144551c91769c7bc18"},
+    {file = "certifi-2022.12.7.tar.gz", hash = "sha256:35824b4c3a97115964b408844d64aa14db1cc518f6562e8d7261699d1350a9e3"},
+]
+
+[[package]]
+name = "cffi"
+version = "1.15.1"
+description = "Foreign Function Interface for Python calling C code."
+optional = false
+python-versions = "*"
+files = [
+    {file = "cffi-1.15.1-cp27-cp27m-macosx_10_9_x86_64.whl", hash = "sha256:a66d3508133af6e8548451b25058d5812812ec3798c886bf38ed24a98216fab2"},
+    {file = "cffi-1.15.1-cp27-cp27m-manylinux1_i686.whl", hash = "sha256:470c103ae716238bbe698d67ad020e1db9d9dba34fa5a899b5e21577e6d52ed2"},
+    {file = "cffi-1.15.1-cp27-cp27m-manylinux1_x86_64.whl", hash = "sha256:9ad5db27f9cabae298d151c85cf2bad1d359a1b9c686a275df03385758e2f914"},
+    {file = "cffi-1.15.1-cp27-cp27m-win32.whl", hash = "sha256:b3bbeb01c2b273cca1e1e0c5df57f12dce9a4dd331b4fa1635b8bec26350bde3"},
+    {file = "cffi-1.15.1-cp27-cp27m-win_amd64.whl", hash = "sha256:e00b098126fd45523dd056d2efba6c5a63b71ffe9f2bbe1a4fe1716e1d0c331e"},
+    {file = "cffi-1.15.1-cp27-cp27mu-manylinux1_i686.whl", hash = "sha256:d61f4695e6c866a23a21acab0509af1cdfd2c013cf256bbf5b6b5e2695827162"},
+    {file = "cffi-1.15.1-cp27-cp27mu-manylinux1_x86_64.whl", hash = "sha256:ed9cb427ba5504c1dc15ede7d516b84757c3e3d7868ccc85121d9310d27eed0b"},
+    {file = "cffi-1.15.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:39d39875251ca8f612b6f33e6b1195af86d1b3e60086068be9cc053aa4376e21"},
+    {file = "cffi-1.15.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:285d29981935eb726a4399badae8f0ffdff4f5050eaa6d0cfc3f64b857b77185"},
+    {file = "cffi-1.15.1-cp310-cp310-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:3eb6971dcff08619f8d91607cfc726518b6fa2a9eba42856be181c6d0d9515fd"},
+    {file = "cffi-1.15.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:21157295583fe8943475029ed5abdcf71eb3911894724e360acff1d61c1d54bc"},
+    {file = "cffi-1.15.1-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:5635bd9cb9731e6d4a1132a498dd34f764034a8ce60cef4f5319c0541159392f"},
+    {file = "cffi-1.15.1-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:2012c72d854c2d03e45d06ae57f40d78e5770d252f195b93f581acf3ba44496e"},
+    {file = "cffi-1.15.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:dd86c085fae2efd48ac91dd7ccffcfc0571387fe1193d33b6394db7ef31fe2a4"},
+    {file = "cffi-1.15.1-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:fa6693661a4c91757f4412306191b6dc88c1703f780c8234035eac011922bc01"},
+    {file = "cffi-1.15.1-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:59c0b02d0a6c384d453fece7566d1c7e6b7bae4fc5874ef2ef46d56776d61c9e"},
+    {file = "cffi-1.15.1-cp310-cp310-win32.whl", hash = "sha256:cba9d6b9a7d64d4bd46167096fc9d2f835e25d7e4c121fb2ddfc6528fb0413b2"},
+    {file = "cffi-1.15.1-cp310-cp310-win_amd64.whl", hash = "sha256:ce4bcc037df4fc5e3d184794f27bdaab018943698f4ca31630bc7f84a7b69c6d"},
+    {file = "cffi-1.15.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:3d08afd128ddaa624a48cf2b859afef385b720bb4b43df214f85616922e6a5ac"},
+    {file = "cffi-1.15.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:3799aecf2e17cf585d977b780ce79ff0dc9b78d799fc694221ce814c2c19db83"},
+    {file = "cffi-1.15.1-cp311-cp311-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:a591fe9e525846e4d154205572a029f653ada1a78b93697f3b5a8f1f2bc055b9"},
+    {file = "cffi-1.15.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:3548db281cd7d2561c9ad9984681c95f7b0e38881201e157833a2342c30d5e8c"},
+    {file = "cffi-1.15.1-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:91fc98adde3d7881af9b59ed0294046f3806221863722ba7d8d120c575314325"},
+    {file = "cffi-1.15.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:94411f22c3985acaec6f83c6df553f2dbe17b698cc7f8ae751ff2237d96b9e3c"},
+    {file = "cffi-1.15.1-cp311-cp311-musllinux_1_1_i686.whl", hash = "sha256:03425bdae262c76aad70202debd780501fabeaca237cdfddc008987c0e0f59ef"},
+    {file = "cffi-1.15.1-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:cc4d65aeeaa04136a12677d3dd0b1c0c94dc43abac5860ab33cceb42b801c1e8"},
+    {file = "cffi-1.15.1-cp311-cp311-win32.whl", hash = "sha256:a0f100c8912c114ff53e1202d0078b425bee3649ae34d7b070e9697f93c5d52d"},
+    {file = "cffi-1.15.1-cp311-cp311-win_amd64.whl", hash = "sha256:04ed324bda3cda42b9b695d51bb7d54b680b9719cfab04227cdd1e04e5de3104"},
+    {file = "cffi-1.15.1-cp36-cp36m-macosx_10_9_x86_64.whl", hash = "sha256:50a74364d85fd319352182ef59c5c790484a336f6db772c1a9231f1c3ed0cbd7"},
+    {file = "cffi-1.15.1-cp36-cp36m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e263d77ee3dd201c3a142934a086a4450861778baaeeb45db4591ef65550b0a6"},
+    {file = "cffi-1.15.1-cp36-cp36m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:cec7d9412a9102bdc577382c3929b337320c4c4c4849f2c5cdd14d7368c5562d"},
+    {file = "cffi-1.15.1-cp36-cp36m-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:4289fc34b2f5316fbb762d75362931e351941fa95fa18789191b33fc4cf9504a"},
+    {file = "cffi-1.15.1-cp36-cp36m-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:173379135477dc8cac4bc58f45db08ab45d228b3363adb7af79436135d028405"},
+    {file = "cffi-1.15.1-cp36-cp36m-manylinux_2_5_x86_64.manylinux1_x86_64.whl", hash = "sha256:6975a3fac6bc83c4a65c9f9fcab9e47019a11d3d2cf7f3c0d03431bf145a941e"},
+    {file = "cffi-1.15.1-cp36-cp36m-win32.whl", hash = "sha256:2470043b93ff09bf8fb1d46d1cb756ce6132c54826661a32d4e4d132e1977adf"},
+    {file = "cffi-1.15.1-cp36-cp36m-win_amd64.whl", hash = "sha256:30d78fbc8ebf9c92c9b7823ee18eb92f2e6ef79b45ac84db507f52fbe3ec4497"},
+    {file = "cffi-1.15.1-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:198caafb44239b60e252492445da556afafc7d1e3ab7a1fb3f0584ef6d742375"},
+    {file = "cffi-1.15.1-cp37-cp37m-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:5ef34d190326c3b1f822a5b7a45f6c4535e2f47ed06fec77d3d799c450b2651e"},
+    {file = "cffi-1.15.1-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:8102eaf27e1e448db915d08afa8b41d6c7ca7a04b7d73af6514df10a3e74bd82"},
+    {file = "cffi-1.15.1-cp37-cp37m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:5df2768244d19ab7f60546d0c7c63ce1581f7af8b5de3eb3004b9b6fc8a9f84b"},
+    {file = "cffi-1.15.1-cp37-cp37m-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:a8c4917bd7ad33e8eb21e9a5bbba979b49d9a97acb3a803092cbc1133e20343c"},
+    {file = "cffi-1.15.1-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0e2642fe3142e4cc4af0799748233ad6da94c62a8bec3a6648bf8ee68b1c7426"},
+    {file = "cffi-1.15.1-cp37-cp37m-win32.whl", hash = "sha256:e229a521186c75c8ad9490854fd8bbdd9a0c9aa3a524326b55be83b54d4e0ad9"},
+    {file = "cffi-1.15.1-cp37-cp37m-win_amd64.whl", hash = "sha256:a0b71b1b8fbf2b96e41c4d990244165e2c9be83d54962a9a1d118fd8657d2045"},
+    {file = "cffi-1.15.1-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:320dab6e7cb2eacdf0e658569d2575c4dad258c0fcc794f46215e1e39f90f2c3"},
+    {file = "cffi-1.15.1-cp38-cp38-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:1e74c6b51a9ed6589199c787bf5f9875612ca4a8a0785fb2d4a84429badaf22a"},
+    {file = "cffi-1.15.1-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a5c84c68147988265e60416b57fc83425a78058853509c1b0629c180094904a5"},
+    {file = "cffi-1.15.1-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:3b926aa83d1edb5aa5b427b4053dc420ec295a08e40911296b9eb1b6170f6cca"},
+    {file = "cffi-1.15.1-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:87c450779d0914f2861b8526e035c5e6da0a3199d8f1add1a665e1cbc6fc6d02"},
+    {file = "cffi-1.15.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4f2c9f67e9821cad2e5f480bc8d83b8742896f1242dba247911072d4fa94c192"},
+    {file = "cffi-1.15.1-cp38-cp38-win32.whl", hash = "sha256:8b7ee99e510d7b66cdb6c593f21c043c248537a32e0bedf02e01e9553a172314"},
+    {file = "cffi-1.15.1-cp38-cp38-win_amd64.whl", hash = "sha256:00a9ed42e88df81ffae7a8ab6d9356b371399b91dbdf0c3cb1e84c03a13aceb5"},
+    {file = "cffi-1.15.1-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:54a2db7b78338edd780e7ef7f9f6c442500fb0d41a5a4ea24fff1c929d5af585"},
+    {file = "cffi-1.15.1-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:fcd131dd944808b5bdb38e6f5b53013c5aa4f334c5cad0c72742f6eba4b73db0"},
+    {file = "cffi-1.15.1-cp39-cp39-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:7473e861101c9e72452f9bf8acb984947aa1661a7704553a9f6e4baa5ba64415"},
+    {file = "cffi-1.15.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6c9a799e985904922a4d207a94eae35c78ebae90e128f0c4e521ce339396be9d"},
+    {file = "cffi-1.15.1-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:3bcde07039e586f91b45c88f8583ea7cf7a0770df3a1649627bf598332cb6984"},
+    {file = "cffi-1.15.1-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:33ab79603146aace82c2427da5ca6e58f2b3f2fb5da893ceac0c42218a40be35"},
+    {file = "cffi-1.15.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:5d598b938678ebf3c67377cdd45e09d431369c3b1a5b331058c338e201f12b27"},
+    {file = "cffi-1.15.1-cp39-cp39-musllinux_1_1_i686.whl", hash = "sha256:db0fbb9c62743ce59a9ff687eb5f4afbe77e5e8403d6697f7446e5f609976f76"},
+    {file = "cffi-1.15.1-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:98d85c6a2bef81588d9227dde12db8a7f47f639f4a17c9ae08e773aa9c697bf3"},
+    {file = "cffi-1.15.1-cp39-cp39-win32.whl", hash = "sha256:40f4774f5a9d4f5e344f31a32b5096977b5d48560c5592e2f3d2c4374bd543ee"},
+    {file = "cffi-1.15.1-cp39-cp39-win_amd64.whl", hash = "sha256:70df4e3b545a17496c9b3f41f5115e69a4f2e77e94e1d2a8e1070bc0c38c8a3c"},
+    {file = "cffi-1.15.1.tar.gz", hash = "sha256:d400bfb9a37b1351253cb402671cea7e89bdecc294e8016a707f6d1d8ac934f9"},
+]
+
+[package.dependencies]
+pycparser = "*"
+
+[[package]]
+name = "charset-normalizer"
+version = "3.1.0"
+description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet."
+optional = false
+python-versions = ">=3.7.0"
+files = [
+    {file = "charset-normalizer-3.1.0.tar.gz", hash = "sha256:34e0a2f9c370eb95597aae63bf85eb5e96826d81e3dcf88b8886012906f509b5"},
+    {file = "charset_normalizer-3.1.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:e0ac8959c929593fee38da1c2b64ee9778733cdf03c482c9ff1d508b6b593b2b"},
+    {file = "charset_normalizer-3.1.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:d7fc3fca01da18fbabe4625d64bb612b533533ed10045a2ac3dd194bfa656b60"},
+    {file = "charset_normalizer-3.1.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:04eefcee095f58eaabe6dc3cc2262f3bcd776d2c67005880894f447b3f2cb9c1"},
+    {file = "charset_normalizer-3.1.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:20064ead0717cf9a73a6d1e779b23d149b53daf971169289ed2ed43a71e8d3b0"},
+    {file = "charset_normalizer-3.1.0-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:1435ae15108b1cb6fffbcea2af3d468683b7afed0169ad718451f8db5d1aff6f"},
+    {file = "charset_normalizer-3.1.0-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:c84132a54c750fda57729d1e2599bb598f5fa0344085dbde5003ba429a4798c0"},
+    {file = "charset_normalizer-3.1.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:75f2568b4189dda1c567339b48cba4ac7384accb9c2a7ed655cd86b04055c795"},
+    {file = "charset_normalizer-3.1.0-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:11d3bcb7be35e7b1bba2c23beedac81ee893ac9871d0ba79effc7fc01167db6c"},
+    {file = "charset_normalizer-3.1.0-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:891cf9b48776b5c61c700b55a598621fdb7b1e301a550365571e9624f270c203"},
+    {file = "charset_normalizer-3.1.0-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:5f008525e02908b20e04707a4f704cd286d94718f48bb33edddc7d7b584dddc1"},
+    {file = "charset_normalizer-3.1.0-cp310-cp310-musllinux_1_1_ppc64le.whl", hash = "sha256:b06f0d3bf045158d2fb8837c5785fe9ff9b8c93358be64461a1089f5da983137"},
+    {file = "charset_normalizer-3.1.0-cp310-cp310-musllinux_1_1_s390x.whl", hash = "sha256:49919f8400b5e49e961f320c735388ee686a62327e773fa5b3ce6721f7e785ce"},
+    {file = "charset_normalizer-3.1.0-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:22908891a380d50738e1f978667536f6c6b526a2064156203d418f4856d6e86a"},
+    {file = "charset_normalizer-3.1.0-cp310-cp310-win32.whl", hash = "sha256:12d1a39aa6b8c6f6248bb54550efcc1c38ce0d8096a146638fd4738e42284448"},
+    {file = "charset_normalizer-3.1.0-cp310-cp310-win_amd64.whl", hash = "sha256:65ed923f84a6844de5fd29726b888e58c62820e0769b76565480e1fdc3d062f8"},
+    {file = "charset_normalizer-3.1.0-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:9a3267620866c9d17b959a84dd0bd2d45719b817245e49371ead79ed4f710d19"},
+    {file = "charset_normalizer-3.1.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:6734e606355834f13445b6adc38b53c0fd45f1a56a9ba06c2058f86893ae8017"},
+    {file = "charset_normalizer-3.1.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:f8303414c7b03f794347ad062c0516cee0e15f7a612abd0ce1e25caf6ceb47df"},
+    {file = "charset_normalizer-3.1.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:aaf53a6cebad0eae578f062c7d462155eada9c172bd8c4d250b8c1d8eb7f916a"},
+    {file = "charset_normalizer-3.1.0-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:3dc5b6a8ecfdc5748a7e429782598e4f17ef378e3e272eeb1340ea57c9109f41"},
+    {file = "charset_normalizer-3.1.0-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:e1b25e3ad6c909f398df8921780d6a3d120d8c09466720226fc621605b6f92b1"},
+    {file = "charset_normalizer-3.1.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0ca564606d2caafb0abe6d1b5311c2649e8071eb241b2d64e75a0d0065107e62"},
+    {file = "charset_normalizer-3.1.0-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:b82fab78e0b1329e183a65260581de4375f619167478dddab510c6c6fb04d9b6"},
+    {file = "charset_normalizer-3.1.0-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:bd7163182133c0c7701b25e604cf1611c0d87712e56e88e7ee5d72deab3e76b5"},
+    {file = "charset_normalizer-3.1.0-cp311-cp311-musllinux_1_1_i686.whl", hash = "sha256:11d117e6c63e8f495412d37e7dc2e2fff09c34b2d09dbe2bee3c6229577818be"},
+    {file = "charset_normalizer-3.1.0-cp311-cp311-musllinux_1_1_ppc64le.whl", hash = "sha256:cf6511efa4801b9b38dc5546d7547d5b5c6ef4b081c60b23e4d941d0eba9cbeb"},
+    {file = "charset_normalizer-3.1.0-cp311-cp311-musllinux_1_1_s390x.whl", hash = "sha256:abc1185d79f47c0a7aaf7e2412a0eb2c03b724581139193d2d82b3ad8cbb00ac"},
+    {file = "charset_normalizer-3.1.0-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:cb7b2ab0188829593b9de646545175547a70d9a6e2b63bf2cd87a0a391599324"},
+    {file = "charset_normalizer-3.1.0-cp311-cp311-win32.whl", hash = "sha256:c36bcbc0d5174a80d6cccf43a0ecaca44e81d25be4b7f90f0ed7bcfbb5a00909"},
+    {file = "charset_normalizer-3.1.0-cp311-cp311-win_amd64.whl", hash = "sha256:cca4def576f47a09a943666b8f829606bcb17e2bc2d5911a46c8f8da45f56755"},
+    {file = "charset_normalizer-3.1.0-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:0c95f12b74681e9ae127728f7e5409cbbef9cd914d5896ef238cc779b8152373"},
+    {file = "charset_normalizer-3.1.0-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:fca62a8301b605b954ad2e9c3666f9d97f63872aa4efcae5492baca2056b74ab"},
+    {file = "charset_normalizer-3.1.0-cp37-cp37m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:ac0aa6cd53ab9a31d397f8303f92c42f534693528fafbdb997c82bae6e477ad9"},
+    {file = "charset_normalizer-3.1.0-cp37-cp37m-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:c3af8e0f07399d3176b179f2e2634c3ce9c1301379a6b8c9c9aeecd481da494f"},
+    {file = "charset_normalizer-3.1.0-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3a5fc78f9e3f501a1614a98f7c54d3969f3ad9bba8ba3d9b438c3bc5d047dd28"},
+    {file = "charset_normalizer-3.1.0-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:628c985afb2c7d27a4800bfb609e03985aaecb42f955049957814e0491d4006d"},
+    {file = "charset_normalizer-3.1.0-cp37-cp37m-musllinux_1_1_aarch64.whl", hash = "sha256:74db0052d985cf37fa111828d0dd230776ac99c740e1a758ad99094be4f1803d"},
+    {file = "charset_normalizer-3.1.0-cp37-cp37m-musllinux_1_1_i686.whl", hash = "sha256:1e8fcdd8f672a1c4fc8d0bd3a2b576b152d2a349782d1eb0f6b8e52e9954731d"},
+    {file = "charset_normalizer-3.1.0-cp37-cp37m-musllinux_1_1_ppc64le.whl", hash = "sha256:04afa6387e2b282cf78ff3dbce20f0cc071c12dc8f685bd40960cc68644cfea6"},
+    {file = "charset_normalizer-3.1.0-cp37-cp37m-musllinux_1_1_s390x.whl", hash = "sha256:dd5653e67b149503c68c4018bf07e42eeed6b4e956b24c00ccdf93ac79cdff84"},
+    {file = "charset_normalizer-3.1.0-cp37-cp37m-musllinux_1_1_x86_64.whl", hash = "sha256:d2686f91611f9e17f4548dbf050e75b079bbc2a82be565832bc8ea9047b61c8c"},
+    {file = "charset_normalizer-3.1.0-cp37-cp37m-win32.whl", hash = "sha256:4155b51ae05ed47199dc5b2a4e62abccb274cee6b01da5b895099b61b1982974"},
+    {file = "charset_normalizer-3.1.0-cp37-cp37m-win_amd64.whl", hash = "sha256:322102cdf1ab682ecc7d9b1c5eed4ec59657a65e1c146a0da342b78f4112db23"},
+    {file = "charset_normalizer-3.1.0-cp38-cp38-macosx_10_9_universal2.whl", hash = "sha256:e633940f28c1e913615fd624fcdd72fdba807bf53ea6925d6a588e84e1151531"},
+    {file = "charset_normalizer-3.1.0-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:3a06f32c9634a8705f4ca9946d667609f52cf130d5548881401f1eb2c39b1e2c"},
+    {file = "charset_normalizer-3.1.0-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:7381c66e0561c5757ffe616af869b916c8b4e42b367ab29fedc98481d1e74e14"},
+    {file = "charset_normalizer-3.1.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:3573d376454d956553c356df45bb824262c397c6e26ce43e8203c4c540ee0acb"},
+    {file = "charset_normalizer-3.1.0-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:e89df2958e5159b811af9ff0f92614dabf4ff617c03a4c1c6ff53bf1c399e0e1"},
+    {file = "charset_normalizer-3.1.0-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:78cacd03e79d009d95635e7d6ff12c21eb89b894c354bd2b2ed0b4763373693b"},
+    {file = "charset_normalizer-3.1.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:de5695a6f1d8340b12a5d6d4484290ee74d61e467c39ff03b39e30df62cf83a0"},
+    {file = "charset_normalizer-3.1.0-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:1c60b9c202d00052183c9be85e5eaf18a4ada0a47d188a83c8f5c5b23252f649"},
+    {file = "charset_normalizer-3.1.0-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:f645caaf0008bacf349875a974220f1f1da349c5dbe7c4ec93048cdc785a3326"},
+    {file = "charset_normalizer-3.1.0-cp38-cp38-musllinux_1_1_i686.whl", hash = "sha256:ea9f9c6034ea2d93d9147818f17c2a0860d41b71c38b9ce4d55f21b6f9165a11"},
+    {file = "charset_normalizer-3.1.0-cp38-cp38-musllinux_1_1_ppc64le.whl", hash = "sha256:80d1543d58bd3d6c271b66abf454d437a438dff01c3e62fdbcd68f2a11310d4b"},
+    {file = "charset_normalizer-3.1.0-cp38-cp38-musllinux_1_1_s390x.whl", hash = "sha256:73dc03a6a7e30b7edc5b01b601e53e7fc924b04e1835e8e407c12c037e81adbd"},
+    {file = "charset_normalizer-3.1.0-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:6f5c2e7bc8a4bf7c426599765b1bd33217ec84023033672c1e9a8b35eaeaaaf8"},
+    {file = "charset_normalizer-3.1.0-cp38-cp38-win32.whl", hash = "sha256:12a2b561af122e3d94cdb97fe6fb2bb2b82cef0cdca131646fdb940a1eda04f0"},
+    {file = "charset_normalizer-3.1.0-cp38-cp38-win_amd64.whl", hash = "sha256:3160a0fd9754aab7d47f95a6b63ab355388d890163eb03b2d2b87ab0a30cfa59"},
+    {file = "charset_normalizer-3.1.0-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:38e812a197bf8e71a59fe55b757a84c1f946d0ac114acafaafaf21667a7e169e"},
+    {file = "charset_normalizer-3.1.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:6baf0baf0d5d265fa7944feb9f7451cc316bfe30e8df1a61b1bb08577c554f31"},
+    {file = "charset_normalizer-3.1.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:8f25e17ab3039b05f762b0a55ae0b3632b2e073d9c8fc88e89aca31a6198e88f"},
+    {file = "charset_normalizer-3.1.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:3747443b6a904001473370d7810aa19c3a180ccd52a7157aacc264a5ac79265e"},
+    {file = "charset_normalizer-3.1.0-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:b116502087ce8a6b7a5f1814568ccbd0e9f6cfd99948aa59b0e241dc57cf739f"},
+    {file = "charset_normalizer-3.1.0-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:d16fd5252f883eb074ca55cb622bc0bee49b979ae4e8639fff6ca3ff44f9f854"},
+    {file = "charset_normalizer-3.1.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:21fa558996782fc226b529fdd2ed7866c2c6ec91cee82735c98a197fae39f706"},
+    {file = "charset_normalizer-3.1.0-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:6f6c7a8a57e9405cad7485f4c9d3172ae486cfef1344b5ddd8e5239582d7355e"},
+    {file = "charset_normalizer-3.1.0-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:ac3775e3311661d4adace3697a52ac0bab17edd166087d493b52d4f4f553f9f0"},
+    {file = "charset_normalizer-3.1.0-cp39-cp39-musllinux_1_1_i686.whl", hash = "sha256:10c93628d7497c81686e8e5e557aafa78f230cd9e77dd0c40032ef90c18f2230"},
+    {file = "charset_normalizer-3.1.0-cp39-cp39-musllinux_1_1_ppc64le.whl", hash = "sha256:6f4f4668e1831850ebcc2fd0b1cd11721947b6dc7c00bf1c6bd3c929ae14f2c7"},
+    {file = "charset_normalizer-3.1.0-cp39-cp39-musllinux_1_1_s390x.whl", hash = "sha256:0be65ccf618c1e7ac9b849c315cc2e8a8751d9cfdaa43027d4f6624bd587ab7e"},
+    {file = "charset_normalizer-3.1.0-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:53d0a3fa5f8af98a1e261de6a3943ca631c526635eb5817a87a59d9a57ebf48f"},
+    {file = "charset_normalizer-3.1.0-cp39-cp39-win32.whl", hash = "sha256:a04f86f41a8916fe45ac5024ec477f41f886b3c435da2d4e3d2709b22ab02af1"},
+    {file = "charset_normalizer-3.1.0-cp39-cp39-win_amd64.whl", hash = "sha256:830d2948a5ec37c386d3170c483063798d7879037492540f10a475e3fd6f244b"},
+    {file = "charset_normalizer-3.1.0-py3-none-any.whl", hash = "sha256:3d9098b479e78c85080c98e1e35ff40b4a31d8953102bb0fd7d1b6f8a2111a3d"},
+]
+
+[[package]]
+name = "click"
+version = "8.1.3"
+description = "Composable command line interface toolkit"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "click-8.1.3-py3-none-any.whl", hash = "sha256:bb4d8133cb15a609f44e8213d9b391b0809795062913b383c62be0ee95b1db48"},
+    {file = "click-8.1.3.tar.gz", hash = "sha256:7682dc8afb30297001674575ea00d1814d808d6a36af415a82bd481d37ba7b8e"},
+]
+
+[package.dependencies]
+colorama = {version = "*", markers = "platform_system == \"Windows\""}
+
+[[package]]
+name = "cmake"
+version = "3.26.1"
+description = "CMake is an open-source, cross-platform family of tools designed to build, test and package software"
+optional = false
+python-versions = "*"
+files = [
+    {file = "cmake-3.26.1-py2.py3-none-macosx_10_10_universal2.macosx_10_10_x86_64.macosx_11_0_arm64.macosx_11_0_universal2.whl", hash = "sha256:d8a7e0cc8677677a732aff3e3fd0ad64eeff43cac772614b03c436912247d0d8"},
+    {file = "cmake-3.26.1-py2.py3-none-manylinux2010_i686.manylinux_2_12_i686.whl", hash = "sha256:f2f721f5aebe304c281ee4b1d2dfbf7f4a52fca003834b2b4a3ba838aeded63c"},
+    {file = "cmake-3.26.1-py2.py3-none-manylinux2010_x86_64.manylinux_2_12_x86_64.whl", hash = "sha256:63a012b72836702eadfe4fba9642aeb17337f26861f4768e837053f40e98cb46"},
+    {file = "cmake-3.26.1-py2.py3-none-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:2b72be88b7bfaa6ae59566cbb9d6a5553f19b2a8d14efa6ac0cf019a29860a1b"},
+    {file = "cmake-3.26.1-py2.py3-none-manylinux2014_i686.manylinux_2_17_i686.whl", hash = "sha256:1278354f7210e22458aa9137d46a56da1f115a7b76ad2733f0bf6041fb40f1dc"},
+    {file = "cmake-3.26.1-py2.py3-none-manylinux2014_ppc64le.manylinux_2_17_ppc64le.whl", hash = "sha256:de96a5522917fba0ab0da2d01d9dd9462fa80f365218bf27162d539c2335758f"},
+    {file = "cmake-3.26.1-py2.py3-none-manylinux2014_s390x.manylinux_2_17_s390x.whl", hash = "sha256:449928ad7dfcd41e4dcff64c7d44f86557883c70577666a19e79e22d783bbbd0"},
+    {file = "cmake-3.26.1-py2.py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:19fa3e457afecf2803265f71652ef17c3f1d317173c330ba46767a0853d38fa0"},
+    {file = "cmake-3.26.1-py2.py3-none-musllinux_1_1_aarch64.whl", hash = "sha256:43360650d60d177d979e4ad0a5f31afa286e6d88f5350f7a38c29d94514900eb"},
+    {file = "cmake-3.26.1-py2.py3-none-musllinux_1_1_i686.whl", hash = "sha256:16aac10363bc926da5109a59ef8fe46ddcd7e3d421de61f871b35524eef2f1ae"},
+    {file = "cmake-3.26.1-py2.py3-none-musllinux_1_1_ppc64le.whl", hash = "sha256:e460ba5070be4dcac9613cb526a46db4e5fa19d8b909a8d8d5244c6cc3c777e1"},
+    {file = "cmake-3.26.1-py2.py3-none-musllinux_1_1_s390x.whl", hash = "sha256:fd2ecc0899f7939a014bd906df85e8681bd63ce457de3ab0b5d9e369fa3bdf79"},
+    {file = "cmake-3.26.1-py2.py3-none-musllinux_1_1_x86_64.whl", hash = "sha256:22781a23e274ba9bf380b970649654851c1b4b9d83b65fec12ee2e2e03b6ffc4"},
+    {file = "cmake-3.26.1-py2.py3-none-win32.whl", hash = "sha256:7b4e81de30ac1fb2f1eb5287063e140b53f376fd9ed7e2060c1c7b5917bd5f83"},
+    {file = "cmake-3.26.1-py2.py3-none-win_amd64.whl", hash = "sha256:90845b6c87a25be07e9220f67dd7f6c891c6ec14d764d37335218d97f9ea4520"},
+    {file = "cmake-3.26.1-py2.py3-none-win_arm64.whl", hash = "sha256:43bd96327e2631183bb4829ba20cb810e20b4b0c68f852fcd7082fbb5359d57c"},
+    {file = "cmake-3.26.1.tar.gz", hash = "sha256:4e0eb3c03dcf2d459f78d96cc85f7482476aeb1ae5ada65150b1db35c0f70cc7"},
+]
+
+[package.extras]
+test = ["codecov (>=2.0.5)", "coverage (>=4.2)", "flake8 (>=3.0.4)", "path.py (>=11.5.0)", "pytest (>=3.0.3)", "pytest-cov (>=2.4.0)", "pytest-runner (>=2.9)", "pytest-virtualenv (>=1.7.0)", "scikit-build (>=0.10.0)", "setuptools (>=28.0.0)", "virtualenv (>=15.0.3)", "wheel"]
+
+[[package]]
+name = "colorama"
+version = "0.4.6"
+description = "Cross-platform colored terminal text."
+optional = false
+python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,>=2.7"
+files = [
+    {file = "colorama-0.4.6-py2.py3-none-any.whl", hash = "sha256:4f1d9991f5acc0ca119f9d443620b77f9d6b33703e51011c16baf57afb285fc6"},
+    {file = "colorama-0.4.6.tar.gz", hash = "sha256:08695f5cb7ed6e0531a20572697297273c47b8cae5a63ffc6d6ed5c201be6e44"},
+]
+
+[[package]]
+name = "contourpy"
+version = "1.0.7"
+description = "Python library for calculating contours of 2D quadrilateral grids"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "contourpy-1.0.7-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:95c3acddf921944f241b6773b767f1cbce71d03307270e2d769fd584d5d1092d"},
+    {file = "contourpy-1.0.7-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:fc1464c97579da9f3ab16763c32e5c5d5bb5fa1ec7ce509a4ca6108b61b84fab"},
+    {file = "contourpy-1.0.7-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:8acf74b5d383414401926c1598ed77825cd530ac7b463ebc2e4f46638f56cce6"},
+    {file = "contourpy-1.0.7-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:1c71fdd8f1c0f84ffd58fca37d00ca4ebaa9e502fb49825484da075ac0b0b803"},
+    {file = "contourpy-1.0.7-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:f99e9486bf1bb979d95d5cffed40689cb595abb2b841f2991fc894b3452290e8"},
+    {file = "contourpy-1.0.7-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:87f4d8941a9564cda3f7fa6a6cd9b32ec575830780677932abdec7bcb61717b0"},
+    {file = "contourpy-1.0.7-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:9e20e5a1908e18aaa60d9077a6d8753090e3f85ca25da6e25d30dc0a9e84c2c6"},
+    {file = "contourpy-1.0.7-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:a877ada905f7d69b2a31796c4b66e31a8068b37aa9b78832d41c82fc3e056ddd"},
+    {file = "contourpy-1.0.7-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:6381fa66866b0ea35e15d197fc06ac3840a9b2643a6475c8fff267db8b9f1e69"},
+    {file = "contourpy-1.0.7-cp310-cp310-win32.whl", hash = "sha256:3c184ad2433635f216645fdf0493011a4667e8d46b34082f5a3de702b6ec42e3"},
+    {file = "contourpy-1.0.7-cp310-cp310-win_amd64.whl", hash = "sha256:3caea6365b13119626ee996711ab63e0c9d7496f65641f4459c60a009a1f3e80"},
+    {file = "contourpy-1.0.7-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:ed33433fc3820263a6368e532f19ddb4c5990855e4886088ad84fd7c4e561c71"},
+    {file = "contourpy-1.0.7-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:38e2e577f0f092b8e6774459317c05a69935a1755ecfb621c0a98f0e3c09c9a5"},
+    {file = "contourpy-1.0.7-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:ae90d5a8590e5310c32a7630b4b8618cef7563cebf649011da80874d0aa8f414"},
+    {file = "contourpy-1.0.7-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:130230b7e49825c98edf0b428b7aa1125503d91732735ef897786fe5452b1ec2"},
+    {file = "contourpy-1.0.7-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:58569c491e7f7e874f11519ef46737cea1d6eda1b514e4eb5ac7dab6aa864d02"},
+    {file = "contourpy-1.0.7-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:54d43960d809c4c12508a60b66cb936e7ed57d51fb5e30b513934a4a23874fae"},
+    {file = "contourpy-1.0.7-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:152fd8f730c31fd67fe0ffebe1df38ab6a669403da93df218801a893645c6ccc"},
+    {file = "contourpy-1.0.7-cp311-cp311-musllinux_1_1_i686.whl", hash = "sha256:9056c5310eb1daa33fc234ef39ebfb8c8e2533f088bbf0bc7350f70a29bde1ac"},
+    {file = "contourpy-1.0.7-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:a9d7587d2fdc820cc9177139b56795c39fb8560f540bba9ceea215f1f66e1566"},
+    {file = "contourpy-1.0.7-cp311-cp311-win32.whl", hash = "sha256:4ee3ee247f795a69e53cd91d927146fb16c4e803c7ac86c84104940c7d2cabf0"},
+    {file = "contourpy-1.0.7-cp311-cp311-win_amd64.whl", hash = "sha256:5caeacc68642e5f19d707471890f037a13007feba8427eb7f2a60811a1fc1350"},
+    {file = "contourpy-1.0.7-cp38-cp38-macosx_10_9_universal2.whl", hash = "sha256:fd7dc0e6812b799a34f6d12fcb1000539098c249c8da54f3566c6a6461d0dbad"},
+    {file = "contourpy-1.0.7-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:0f9d350b639db6c2c233d92c7f213d94d2e444d8e8fc5ca44c9706cf72193772"},
+    {file = "contourpy-1.0.7-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:e96a08b62bb8de960d3a6afbc5ed8421bf1a2d9c85cc4ea73f4bc81b4910500f"},
+    {file = "contourpy-1.0.7-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:031154ed61f7328ad7f97662e48660a150ef84ee1bc8876b6472af88bf5a9b98"},
+    {file = "contourpy-1.0.7-cp38-cp38-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:2e9ebb4425fc1b658e13bace354c48a933b842d53c458f02c86f371cecbedecc"},
+    {file = "contourpy-1.0.7-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:efb8f6d08ca7998cf59eaf50c9d60717f29a1a0a09caa46460d33b2924839dbd"},
+    {file = "contourpy-1.0.7-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:6c180d89a28787e4b73b07e9b0e2dac7741261dbdca95f2b489c4f8f887dd810"},
+    {file = "contourpy-1.0.7-cp38-cp38-musllinux_1_1_i686.whl", hash = "sha256:b8d587cc39057d0afd4166083d289bdeff221ac6d3ee5046aef2d480dc4b503c"},
+    {file = "contourpy-1.0.7-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:769eef00437edf115e24d87f8926955f00f7704bede656ce605097584f9966dc"},
+    {file = "contourpy-1.0.7-cp38-cp38-win32.whl", hash = "sha256:62398c80ef57589bdbe1eb8537127321c1abcfdf8c5f14f479dbbe27d0322e66"},
+    {file = "contourpy-1.0.7-cp38-cp38-win_amd64.whl", hash = "sha256:57119b0116e3f408acbdccf9eb6ef19d7fe7baf0d1e9aaa5381489bc1aa56556"},
+    {file = "contourpy-1.0.7-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:30676ca45084ee61e9c3da589042c24a57592e375d4b138bd84d8709893a1ba4"},
+    {file = "contourpy-1.0.7-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:3e927b3868bd1e12acee7cc8f3747d815b4ab3e445a28d2e5373a7f4a6e76ba1"},
+    {file = "contourpy-1.0.7-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:366a0cf0fc079af5204801786ad7a1c007714ee3909e364dbac1729f5b0849e5"},
+    {file = "contourpy-1.0.7-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:89ba9bb365446a22411f0673abf6ee1fea3b2cf47b37533b970904880ceb72f3"},
+    {file = "contourpy-1.0.7-cp39-cp39-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:71b0bf0c30d432278793d2141362ac853859e87de0a7dee24a1cea35231f0d50"},
+    {file = "contourpy-1.0.7-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e7281244c99fd7c6f27c1c6bfafba878517b0b62925a09b586d88ce750a016d2"},
+    {file = "contourpy-1.0.7-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:b6d0f9e1d39dbfb3977f9dd79f156c86eb03e57a7face96f199e02b18e58d32a"},
+    {file = "contourpy-1.0.7-cp39-cp39-musllinux_1_1_i686.whl", hash = "sha256:7f6979d20ee5693a1057ab53e043adffa1e7418d734c1532e2d9e915b08d8ec2"},
+    {file = "contourpy-1.0.7-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:5dd34c1ae752515318224cba7fc62b53130c45ac6a1040c8b7c1a223c46e8967"},
+    {file = "contourpy-1.0.7-cp39-cp39-win32.whl", hash = "sha256:c5210e5d5117e9aec8c47d9156d1d3835570dd909a899171b9535cb4a3f32693"},
+    {file = "contourpy-1.0.7-cp39-cp39-win_amd64.whl", hash = "sha256:60835badb5ed5f4e194a6f21c09283dd6e007664a86101431bf870d9e86266c4"},
+    {file = "contourpy-1.0.7-pp38-pypy38_pp73-macosx_10_9_x86_64.whl", hash = "sha256:ce41676b3d0dd16dbcfabcc1dc46090aaf4688fd6e819ef343dbda5a57ef0161"},
+    {file = "contourpy-1.0.7-pp38-pypy38_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:5a011cf354107b47c58ea932d13b04d93c6d1d69b8b6dce885e642531f847566"},
+    {file = "contourpy-1.0.7-pp38-pypy38_pp73-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:31a55dccc8426e71817e3fe09b37d6d48ae40aae4ecbc8c7ad59d6893569c436"},
+    {file = "contourpy-1.0.7-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:69f8ff4db108815addd900a74df665e135dbbd6547a8a69333a68e1f6e368ac2"},
+    {file = "contourpy-1.0.7-pp38-pypy38_pp73-win_amd64.whl", hash = "sha256:efe99298ba37e37787f6a2ea868265465410822f7bea163edcc1bd3903354ea9"},
+    {file = "contourpy-1.0.7-pp39-pypy39_pp73-macosx_10_9_x86_64.whl", hash = "sha256:a1e97b86f73715e8670ef45292d7cc033548266f07d54e2183ecb3c87598888f"},
+    {file = "contourpy-1.0.7-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:cc331c13902d0f50845099434cd936d49d7a2ca76cb654b39691974cb1e4812d"},
+    {file = "contourpy-1.0.7-pp39-pypy39_pp73-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:24847601071f740837aefb730e01bd169fbcaa610209779a78db7ebb6e6a7051"},
+    {file = "contourpy-1.0.7-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:abf298af1e7ad44eeb93501e40eb5a67abbf93b5d90e468d01fc0c4451971afa"},
+    {file = "contourpy-1.0.7-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:64757f6460fc55d7e16ed4f1de193f362104285c667c112b50a804d482777edd"},
+    {file = "contourpy-1.0.7.tar.gz", hash = "sha256:d8165a088d31798b59e91117d1f5fc3df8168d8b48c4acc10fc0df0d0bdbcc5e"},
+]
+
+[package.dependencies]
+numpy = ">=1.16"
+
+[package.extras]
+bokeh = ["bokeh", "chromedriver", "selenium"]
+docs = ["furo", "sphinx-copybutton"]
+mypy = ["contourpy[bokeh]", "docutils-stubs", "mypy (==0.991)", "types-Pillow"]
+test = ["Pillow", "matplotlib", "pytest"]
+test-no-images = ["pytest"]
+
+[[package]]
+name = "cycler"
+version = "0.11.0"
+description = "Composable style cycles"
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "cycler-0.11.0-py3-none-any.whl", hash = "sha256:3a27e95f763a428a739d2add979fa7494c912a32c17c4c38c4d5f082cad165a3"},
+    {file = "cycler-0.11.0.tar.gz", hash = "sha256:9c87405839a19696e837b3b818fed3f5f69f16f1eec1a1ad77e043dcea9c772f"},
+]
+
+[[package]]
+name = "cython"
+version = "0.29.34"
+description = "The Cython compiler for writing C extensions for the Python language."
+optional = false
+python-versions = ">=2.6, !=3.0.*, !=3.1.*, !=3.2.*"
+files = [
+    {file = "Cython-0.29.34-cp27-cp27m-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:742544024ddb74314e2d597accdb747ed76bd126e61fcf49940a5b5be0a8f381"},
+    {file = "Cython-0.29.34-cp27-cp27m-manylinux_2_5_x86_64.manylinux1_x86_64.whl", hash = "sha256:03daae07f8cbf797506446adae512c3dd86e7f27a62a541fa1ee254baf43e32c"},
+    {file = "Cython-0.29.34-cp27-cp27mu-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:5a8de3e793a576e40ca9b4f5518610cd416273c7dc5e254115656b6e4ec70663"},
+    {file = "Cython-0.29.34-cp27-cp27mu-manylinux_2_5_x86_64.manylinux1_x86_64.whl", hash = "sha256:60969d38e6a456a67e7ef8ae20668eff54e32ba439d4068ccf2854a44275a30f"},
+    {file = "Cython-0.29.34-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.manylinux_2_24_aarch64.whl", hash = "sha256:21b88200620d80cfe193d199b259cdad2b9af56f916f0f7f474b5a3631ca0caa"},
+    {file = "Cython-0.29.34-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_24_x86_64.whl", hash = "sha256:308c8f1e58bf5e6e8a1c4dcf8abbd2d13d0f9b1e582f4d9ae8b89857342d8bb5"},
+    {file = "Cython-0.29.34-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_24_i686.whl", hash = "sha256:d8f822fb6ecd5d88c42136561f82960612421154fc5bf23c57103a367bb91356"},
+    {file = "Cython-0.29.34-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:56866323f1660cecb4d5ff3a1fba92a56b91b7cfae0a8253777aa4bdb3bdf9a8"},
+    {file = "Cython-0.29.34-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.manylinux_2_24_aarch64.whl", hash = "sha256:e971db8aeb12e7c0697cefafe65eefcc33ff1224ae3d8c7f83346cbc42c6c270"},
+    {file = "Cython-0.29.34-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_24_x86_64.whl", hash = "sha256:e4401270b0dc464c23671e2e9d52a60985f988318febaf51b047190e855bbe7d"},
+    {file = "Cython-0.29.34-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_24_i686.whl", hash = "sha256:dce0a36d163c05ae8b21200059511217d79b47baf2b7b0f926e8367bd7a3cc24"},
+    {file = "Cython-0.29.34-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:dbd79221869ee9a6ccc4953b2c8838bb6ae08ab4d50ea4b60d7894f03739417b"},
+    {file = "Cython-0.29.34-cp35-cp35m-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:a0f4229df10bc4545ebbeaaf96ebb706011d8b333e54ed202beb03f2bee0a50e"},
+    {file = "Cython-0.29.34-cp35-cp35m-manylinux_2_5_x86_64.manylinux1_x86_64.whl", hash = "sha256:fd1ea21f1cebf33ae288caa0f3e9b5563a709f4df8925d53bad99be693fc0d9b"},
+    {file = "Cython-0.29.34-cp36-cp36m-manylinux_2_17_aarch64.manylinux2014_aarch64.manylinux_2_24_aarch64.whl", hash = "sha256:d7ef5f68f4c5baa93349ea54a352f8716d18bee9a37f3e93eff38a5d4e9b7262"},
+    {file = "Cython-0.29.34-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_24_x86_64.whl", hash = "sha256:459994d1de0f99bb18fad9f2325f760c4b392b1324aef37bcc1cd94922dfce41"},
+    {file = "Cython-0.29.34-cp36-cp36m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_24_i686.whl", hash = "sha256:1d6c809e2f9ce5950bbc52a1d2352ef3d4fc56186b64cb0d50c8c5a3c1d17661"},
+    {file = "Cython-0.29.34-cp36-cp36m-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:f674ceb5f722d364395f180fbac273072fc1a266aab924acc9cfd5afc645aae1"},
+    {file = "Cython-0.29.34-cp36-cp36m-manylinux_2_5_x86_64.manylinux1_x86_64.whl", hash = "sha256:9489de5b2044dcdfd9d6ca8242a02d560137b3c41b1f5ae1c4f6707d66d6e44d"},
+    {file = "Cython-0.29.34-cp36-cp36m-musllinux_1_1_x86_64.whl", hash = "sha256:5c121dc185040f4333bfded68963b4529698e1b6d994da56be32c97a90c896b6"},
+    {file = "Cython-0.29.34-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.manylinux_2_24_aarch64.whl", hash = "sha256:b6149f7cc5b31bccb158c5b968e5a8d374fdc629792e7b928a9b66e08b03fca5"},
+    {file = "Cython-0.29.34-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_24_x86_64.whl", hash = "sha256:0ab3cbf3d62b0354631a45dc93cfcdf79098663b1c65a6033af4a452b52217a7"},
+    {file = "Cython-0.29.34-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_24_i686.whl", hash = "sha256:4a2723447d1334484681d5aede34184f2da66317891f94b80e693a2f96a8f1a7"},
+    {file = "Cython-0.29.34-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:e40cf86aadc29ecd1cb6de67b0d9488705865deea4fc185c7ad56d7a6fc78703"},
+    {file = "Cython-0.29.34-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.whl", hash = "sha256:8c3cd8bb8e880a3346f5685601004d96e0a2221e73edcaeea57ea848618b4ac6"},
+    {file = "Cython-0.29.34-cp37-cp37m-musllinux_1_1_x86_64.whl", hash = "sha256:0e9032cd650b0cb1d2c2ef2623f5714c14d14c28d7647d589c3eeed0baf7428e"},
+    {file = "Cython-0.29.34-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.manylinux_2_24_aarch64.whl", hash = "sha256:bdb3285660e3068438791ace7dd7b1efd6b442a10b5c8d7a4f0c9d184d08c8ed"},
+    {file = "Cython-0.29.34-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_24_x86_64.whl", hash = "sha256:a8ad755f9364e720f10a36734a1c7a5ced5c679446718b589259261438a517c9"},
+    {file = "Cython-0.29.34-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_24_i686.whl", hash = "sha256:7595d29eaee95633dd8060f50f0e54b27472d01587659557ebcfe39da3ea946b"},
+    {file = "Cython-0.29.34-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:e6ef7879668214d80ea3914c17e7d4e1ebf4242e0dd4dabe95ca5ccbe75589a5"},
+    {file = "Cython-0.29.34-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.whl", hash = "sha256:ccb223b5f0fd95d8d27561efc0c14502c0945f1a32274835831efa5d5baddfc1"},
+    {file = "Cython-0.29.34-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:11b1b278b8edef215caaa5250ad65a10023bfa0b5a93c776552248fc6f60098d"},
+    {file = "Cython-0.29.34-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.manylinux_2_24_aarch64.whl", hash = "sha256:5718319a01489688fdd22ddebb8e2fcbbd60be5f30de4336ea7063c3ae29fbe5"},
+    {file = "Cython-0.29.34-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_24_x86_64.whl", hash = "sha256:cfb2302ef617d647ee590a4c0a00ba3c2da05f301dcefe7721125565d2e51351"},
+    {file = "Cython-0.29.34-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_24_i686.whl", hash = "sha256:67b850cf46b861bc27226d31e1d87c0e69869a02f8d3cc5d5bef549764029879"},
+    {file = "Cython-0.29.34-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:0963266dad685812c1dbb758fcd4de78290e3adc7db271c8664dcde27380b13e"},
+    {file = "Cython-0.29.34-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.whl", hash = "sha256:7879992487d9060a61393eeefe00d299210256928dce44d887b6be313d342bac"},
+    {file = "Cython-0.29.34-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:44733366f1604b0c327613b6918469284878d2f5084297d10d26072fc6948d51"},
+    {file = "Cython-0.29.34-py2.py3-none-any.whl", hash = "sha256:be4f6b7be75a201c290c8611c0978549c60353890204573078e865423dbe3c83"},
+    {file = "Cython-0.29.34.tar.gz", hash = "sha256:1909688f5d7b521a60c396d20bba9e47a1b2d2784bfb085401e1e1e7d29a29a8"},
+]
+
+[[package]]
+name = "decorator"
+version = "5.1.1"
+description = "Decorators for Humans"
+optional = false
+python-versions = ">=3.5"
+files = [
+    {file = "decorator-5.1.1-py3-none-any.whl", hash = "sha256:b8c3f85900b9dc423225913c5aace94729fe1fa9763b38939a95226f02d37186"},
+    {file = "decorator-5.1.1.tar.gz", hash = "sha256:637996211036b6385ef91435e4fae22989472f9d571faba8927ba8253acbc330"},
+]
+
+[[package]]
+name = "entrypoints"
+version = "0.4"
+description = "Discover and load entry points from installed packages."
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "entrypoints-0.4-py3-none-any.whl", hash = "sha256:f174b5ff827504fd3cd97cc3f8649f3693f51538c7e4bdf3ef002c8429d42f9f"},
+    {file = "entrypoints-0.4.tar.gz", hash = "sha256:b706eddaa9218a19ebcd67b56818f05bb27589b1ca9e8d797b74affad4ccacd4"},
+]
+
+[[package]]
+name = "fairseq"
+version = "0.12.2"
+description = "Facebook AI Research Sequence-to-Sequence Toolkit"
+optional = false
+python-versions = "*"
+files = [
+    {file = "fairseq-0.12.2-cp36-cp36m-macosx_10_9_x86_64.whl", hash = "sha256:fe65b07c5121b7cda0c7a17166994a6b0059259ce37881b6daa117b8c209b662"},
+    {file = "fairseq-0.12.2-cp36-cp36m-manylinux_2_5_x86_64.manylinux1_x86_64.whl", hash = "sha256:0543905012e39f00bd8c3f3781d9f49e76ab309801eb2eb7de250f5984df0de3"},
+    {file = "fairseq-0.12.2-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:c4877d65346797fc580a3a7e6e2364d2331a0026ef099c22eb8311441e49c2c6"},
+    {file = "fairseq-0.12.2-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.whl", hash = "sha256:26454f334ca705c67f898846dff34e14c148fcdaf53b4f52d64209773b509347"},
+    {file = "fairseq-0.12.2-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:3b8c8b6dc368d2fd23a06ff613a2af05959eee275fe90846d7cffef4a43c522a"},
+    {file = "fairseq-0.12.2-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.whl", hash = "sha256:08fa308c760f995cdc13d9c385e2b9d923a78b48275d8b4d78f3a854c71a8f29"},
+    {file = "fairseq-0.12.2.tar.gz", hash = "sha256:34f1b18426bf3844714534162f065ab733e049597476daa35fffb4d06a92b524"},
+]
+
+[package.dependencies]
+bitarray = "*"
+cffi = "*"
+cython = "*"
+hydra-core = ">=1.0.7,<1.1"
+numpy = {version = "*", markers = "python_version >= \"3.7\""}
+omegaconf = "<2.1"
+regex = "*"
+sacrebleu = ">=1.4.12"
+torch = "*"
+torchaudio = ">=0.8.0"
+tqdm = "*"
+
+[[package]]
+name = "faiss-cpu"
+version = "1.7.3"
+description = "A library for efficient similarity search and clustering of dense vectors."
+optional = false
+python-versions = "*"
+files = [
+    {file = "faiss-cpu-1.7.3.tar.gz", hash = "sha256:cb71fe3f2934732d157d9d8cfb6ed2dd4020a0065571c84842ff6a3f0beab310"},
+    {file = "faiss_cpu-1.7.3-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:343f025e0846239d987d0c719772387ad685b74e5ef62b2e5616cabef9062729"},
+    {file = "faiss_cpu-1.7.3-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:8b7b1cf693d7c24b5a633ff024717bd715fec501af4854357da0805b4899bcec"},
+    {file = "faiss_cpu-1.7.3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:1c37e5fc0a266839844798a53dd42dd6afbee0c5905611f3f278297053fccbd7"},
+    {file = "faiss_cpu-1.7.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0628f7b0c6263ef4431995bb4f5f39833f999e96e6663935cbf0a1f2243dc4ac"},
+    {file = "faiss_cpu-1.7.3-cp310-cp310-win_amd64.whl", hash = "sha256:e22d1887c617156a673665c913ee82a30bfc1a3bc939ba8500b61328bce5a625"},
+    {file = "faiss_cpu-1.7.3-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:6d411449a5f3c3abfcafadaac3190ab1ab206023fc9110da86649506dcbe8a27"},
+    {file = "faiss_cpu-1.7.3-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:a10ea8622908f9f9ca4003e66da809dfad4af5c7d9fb7f582722d703bbc6c8bd"},
+    {file = "faiss_cpu-1.7.3-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7c5ced43ae058a62f63b12194ec9aa4c34066b0ea813ecbd936c65b7d52848c8"},
+    {file = "faiss_cpu-1.7.3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3df6371012248dea8e9509949e2d2c6d73dea7c1bdaa4ba4563eb1c3cd8021a6"},
+    {file = "faiss_cpu-1.7.3-cp311-cp311-win_amd64.whl", hash = "sha256:8b6ff7854c3f46104718c6b34e81cd48c156d970dd87703c5122ca90217bb8dc"},
+    {file = "faiss_cpu-1.7.3-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:ab6314a8fbcce11dc3ecb6f48dda8c4ec274ed11c1f336f599f480bf0561442c"},
+    {file = "faiss_cpu-1.7.3-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:877c0bbf4c4a1806d88e091aba4c91ff3fa35c3ede5663b7fafc5b39247a369e"},
+    {file = "faiss_cpu-1.7.3-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f6f199be10d30ecc6ed65350931006eca01b7bb8faa27d63069318eea0f6a0c1"},
+    {file = "faiss_cpu-1.7.3-cp37-cp37m-win_amd64.whl", hash = "sha256:1ca2b7cdbfdcc6a2e8fa75a09594916b50ec8260913ca48334dc3ce797179b5f"},
+    {file = "faiss_cpu-1.7.3-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:7b3f91856c19cfb8464178bab7e8ea94a391f6947b556be6754f9fc10b3c25fb"},
+    {file = "faiss_cpu-1.7.3-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:7a238a0ef4d36c614d6f60e1ea308288b3920091638a3687f708de6071d007c1"},
+    {file = "faiss_cpu-1.7.3-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:af53bee502c629eaaaf8b5ec648484a726be0fd2768ad4ef2bd4b829384b2682"},
+    {file = "faiss_cpu-1.7.3-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:441d1c305595d925138f2cde63dabe8c10ee05fc8ad66bf750e278a7e8c409bd"},
+    {file = "faiss_cpu-1.7.3-cp38-cp38-win_amd64.whl", hash = "sha256:2766cc14b9004c1aae3b3943e693c3a9566eb1a25168b681981f9048276fe1e7"},
+    {file = "faiss_cpu-1.7.3-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:20ef191bb6164c8e794b11d20427568a75d15980b6d66732071e9aa57ea06e2d"},
+    {file = "faiss_cpu-1.7.3-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:c57c293c4682066955626c2a2956be9a3b92594f69ed1a33abd72260a6911b69"},
+    {file = "faiss_cpu-1.7.3-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:bd128170446ff3c3e28d89e813d32cd04f17fa3025794778a01a0d81524275dc"},
+    {file = "faiss_cpu-1.7.3-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a14d832b5361ce9af21977eb1dcdebe23b9edcc12aad40316df7ca1bd86bc6b5"},
+    {file = "faiss_cpu-1.7.3-cp39-cp39-win_amd64.whl", hash = "sha256:52df8895c5e59d1c9eda368a63790381a6f7fceddb22bed08f9c90a706d8a148"},
+]
+
+[[package]]
+name = "fastapi"
+version = "0.95.2"
+description = "FastAPI framework, high performance, easy to learn, fast to code, ready for production"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "fastapi-0.95.2-py3-none-any.whl", hash = "sha256:d374dbc4ef2ad9b803899bd3360d34c534adc574546e25314ab72c0c4411749f"},
+    {file = "fastapi-0.95.2.tar.gz", hash = "sha256:4d9d3e8c71c73f11874bcf5e33626258d143252e329a01002f767306c64fb982"},
+]
+
+[package.dependencies]
+pydantic = ">=1.6.2,<1.7 || >1.7,<1.7.1 || >1.7.1,<1.7.2 || >1.7.2,<1.7.3 || >1.7.3,<1.8 || >1.8,<1.8.1 || >1.8.1,<2.0.0"
+starlette = ">=0.27.0,<0.28.0"
+
+[package.extras]
+all = ["email-validator (>=1.1.1)", "httpx (>=0.23.0)", "itsdangerous (>=1.1.0)", "jinja2 (>=2.11.2)", "orjson (>=3.2.1)", "python-multipart (>=0.0.5)", "pyyaml (>=5.3.1)", "ujson (>=4.0.1,!=4.0.2,!=4.1.0,!=4.2.0,!=4.3.0,!=5.0.0,!=5.1.0)", "uvicorn[standard] (>=0.12.0)"]
+dev = ["pre-commit (>=2.17.0,<3.0.0)", "ruff (==0.0.138)", "uvicorn[standard] (>=0.12.0,<0.21.0)"]
+doc = ["mdx-include (>=1.4.1,<2.0.0)", "mkdocs (>=1.1.2,<2.0.0)", "mkdocs-markdownextradata-plugin (>=0.1.7,<0.3.0)", "mkdocs-material (>=8.1.4,<9.0.0)", "pyyaml (>=5.3.1,<7.0.0)", "typer-cli (>=0.0.13,<0.0.14)", "typer[all] (>=0.6.1,<0.8.0)"]
+test = ["anyio[trio] (>=3.2.1,<4.0.0)", "black (==23.1.0)", "coverage[toml] (>=6.5.0,<8.0)", "databases[sqlite] (>=0.3.2,<0.7.0)", "email-validator (>=1.1.1,<2.0.0)", "flask (>=1.1.2,<3.0.0)", "httpx (>=0.23.0,<0.24.0)", "isort (>=5.0.6,<6.0.0)", "mypy (==0.982)", "orjson (>=3.2.1,<4.0.0)", "passlib[bcrypt] (>=1.7.2,<2.0.0)", "peewee (>=3.13.3,<4.0.0)", "pytest (>=7.1.3,<8.0.0)", "python-jose[cryptography] (>=3.3.0,<4.0.0)", "python-multipart (>=0.0.5,<0.0.7)", "pyyaml (>=5.3.1,<7.0.0)", "ruff (==0.0.138)", "sqlalchemy (>=1.3.18,<1.4.43)", "types-orjson (==3.6.2)", "types-ujson (==5.7.0.1)", "ujson (>=4.0.1,!=4.0.2,!=4.1.0,!=4.2.0,!=4.3.0,!=5.0.0,!=5.1.0,<6.0.0)"]
+
+[[package]]
+name = "ffmpeg-python"
+version = "0.2.0"
+description = "Python bindings for FFmpeg - with complex filtering support"
+optional = false
+python-versions = "*"
+files = [
+    {file = "ffmpeg-python-0.2.0.tar.gz", hash = "sha256:65225db34627c578ef0e11c8b1eb528bb35e024752f6f10b78c011f6f64c4127"},
+    {file = "ffmpeg_python-0.2.0-py3-none-any.whl", hash = "sha256:ac441a0404e053f8b6a1113a77c0f452f1cfc62f6344a769475ffdc0f56c23c5"},
+]
+
+[package.dependencies]
+future = "*"
+
+[package.extras]
+dev = ["Sphinx (==2.1.0)", "future (==0.17.1)", "numpy (==1.16.4)", "pytest (==4.6.1)", "pytest-mock (==1.10.4)", "tox (==3.12.1)"]
+
+[[package]]
+name = "ffmpy"
+version = "0.3.0"
+description = "A simple Python wrapper for ffmpeg"
+optional = false
+python-versions = "*"
+files = [
+    {file = "ffmpy-0.3.0.tar.gz", hash = "sha256:757591581eee25b4a50ac9ffb9b58035a2794533db47e0512f53fb2d7b6f9adc"},
+]
+
+[[package]]
+name = "filelock"
+version = "3.10.7"
+description = "A platform independent file lock."
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "filelock-3.10.7-py3-none-any.whl", hash = "sha256:bde48477b15fde2c7e5a0713cbe72721cb5a5ad32ee0b8f419907960b9d75536"},
+    {file = "filelock-3.10.7.tar.gz", hash = "sha256:892be14aa8efc01673b5ed6589dbccb95f9a8596f0507e232626155495c18105"},
+]
+
+[package.extras]
+docs = ["furo (>=2022.12.7)", "sphinx (>=6.1.3)", "sphinx-autodoc-typehints (>=1.22,!=1.23.4)"]
+testing = ["covdefaults (>=2.3)", "coverage (>=7.2.2)", "diff-cover (>=7.5)", "pytest (>=7.2.2)", "pytest-cov (>=4)", "pytest-mock (>=3.10)", "pytest-timeout (>=2.1)"]
+
+[[package]]
+name = "fonttools"
+version = "4.39.3"
+description = "Tools to manipulate font files"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "fonttools-4.39.3-py3-none-any.whl", hash = "sha256:64c0c05c337f826183637570ac5ab49ee220eec66cf50248e8df527edfa95aeb"},
+    {file = "fonttools-4.39.3.zip", hash = "sha256:9234b9f57b74e31b192c3fc32ef1a40750a8fbc1cd9837a7b7bfc4ca4a5c51d7"},
+]
+
+[package.extras]
+all = ["brotli (>=1.0.1)", "brotlicffi (>=0.8.0)", "fs (>=2.2.0,<3)", "lxml (>=4.0,<5)", "lz4 (>=1.7.4.2)", "matplotlib", "munkres", "scipy", "skia-pathops (>=0.5.0)", "sympy", "uharfbuzz (>=0.23.0)", "unicodedata2 (>=15.0.0)", "xattr", "zopfli (>=0.1.4)"]
+graphite = ["lz4 (>=1.7.4.2)"]
+interpolatable = ["munkres", "scipy"]
+lxml = ["lxml (>=4.0,<5)"]
+pathops = ["skia-pathops (>=0.5.0)"]
+plot = ["matplotlib"]
+repacker = ["uharfbuzz (>=0.23.0)"]
+symfont = ["sympy"]
+type1 = ["xattr"]
+ufo = ["fs (>=2.2.0,<3)"]
+unicode = ["unicodedata2 (>=15.0.0)"]
+woff = ["brotli (>=1.0.1)", "brotlicffi (>=0.8.0)", "zopfli (>=0.1.4)"]
+
+[[package]]
+name = "frozenlist"
+version = "1.3.3"
+description = "A list-like structure which implements collections.abc.MutableSequence"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "frozenlist-1.3.3-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:ff8bf625fe85e119553b5383ba0fb6aa3d0ec2ae980295aaefa552374926b3f4"},
+    {file = "frozenlist-1.3.3-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:dfbac4c2dfcc082fcf8d942d1e49b6aa0766c19d3358bd86e2000bf0fa4a9cf0"},
+    {file = "frozenlist-1.3.3-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:b1c63e8d377d039ac769cd0926558bb7068a1f7abb0f003e3717ee003ad85530"},
+    {file = "frozenlist-1.3.3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7fdfc24dcfce5b48109867c13b4cb15e4660e7bd7661741a391f821f23dfdca7"},
+    {file = "frozenlist-1.3.3-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:2c926450857408e42f0bbc295e84395722ce74bae69a3b2aa2a65fe22cb14b99"},
+    {file = "frozenlist-1.3.3-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:1841e200fdafc3d51f974d9d377c079a0694a8f06de2e67b48150328d66d5483"},
+    {file = "frozenlist-1.3.3-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:f470c92737afa7d4c3aacc001e335062d582053d4dbe73cda126f2d7031068dd"},
+    {file = "frozenlist-1.3.3-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:783263a4eaad7c49983fe4b2e7b53fa9770c136c270d2d4bbb6d2192bf4d9caf"},
+    {file = "frozenlist-1.3.3-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:924620eef691990dfb56dc4709f280f40baee568c794b5c1885800c3ecc69816"},
+    {file = "frozenlist-1.3.3-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:ae4dc05c465a08a866b7a1baf360747078b362e6a6dbeb0c57f234db0ef88ae0"},
+    {file = "frozenlist-1.3.3-cp310-cp310-musllinux_1_1_ppc64le.whl", hash = "sha256:bed331fe18f58d844d39ceb398b77d6ac0b010d571cba8267c2e7165806b00ce"},
+    {file = "frozenlist-1.3.3-cp310-cp310-musllinux_1_1_s390x.whl", hash = "sha256:02c9ac843e3390826a265e331105efeab489ffaf4dd86384595ee8ce6d35ae7f"},
+    {file = "frozenlist-1.3.3-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:9545a33965d0d377b0bc823dcabf26980e77f1b6a7caa368a365a9497fb09420"},
+    {file = "frozenlist-1.3.3-cp310-cp310-win32.whl", hash = "sha256:d5cd3ab21acbdb414bb6c31958d7b06b85eeb40f66463c264a9b343a4e238642"},
+    {file = "frozenlist-1.3.3-cp310-cp310-win_amd64.whl", hash = "sha256:b756072364347cb6aa5b60f9bc18e94b2f79632de3b0190253ad770c5df17db1"},
+    {file = "frozenlist-1.3.3-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:b4395e2f8d83fbe0c627b2b696acce67868793d7d9750e90e39592b3626691b7"},
+    {file = "frozenlist-1.3.3-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:14143ae966a6229350021384870458e4777d1eae4c28d1a7aa47f24d030e6678"},
+    {file = "frozenlist-1.3.3-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:5d8860749e813a6f65bad8285a0520607c9500caa23fea6ee407e63debcdbef6"},
+    {file = "frozenlist-1.3.3-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:23d16d9f477bb55b6154654e0e74557040575d9d19fe78a161bd33d7d76808e8"},
+    {file = "frozenlist-1.3.3-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:eb82dbba47a8318e75f679690190c10a5e1f447fbf9df41cbc4c3afd726d88cb"},
+    {file = "frozenlist-1.3.3-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:9309869032abb23d196cb4e4db574232abe8b8be1339026f489eeb34a4acfd91"},
+    {file = "frozenlist-1.3.3-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:a97b4fe50b5890d36300820abd305694cb865ddb7885049587a5678215782a6b"},
+    {file = "frozenlist-1.3.3-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c188512b43542b1e91cadc3c6c915a82a5eb95929134faf7fd109f14f9892ce4"},
+    {file = "frozenlist-1.3.3-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:303e04d422e9b911a09ad499b0368dc551e8c3cd15293c99160c7f1f07b59a48"},
+    {file = "frozenlist-1.3.3-cp311-cp311-musllinux_1_1_i686.whl", hash = "sha256:0771aed7f596c7d73444c847a1c16288937ef988dc04fb9f7be4b2aa91db609d"},
+    {file = "frozenlist-1.3.3-cp311-cp311-musllinux_1_1_ppc64le.whl", hash = "sha256:66080ec69883597e4d026f2f71a231a1ee9887835902dbe6b6467d5a89216cf6"},
+    {file = "frozenlist-1.3.3-cp311-cp311-musllinux_1_1_s390x.whl", hash = "sha256:41fe21dc74ad3a779c3d73a2786bdf622ea81234bdd4faf90b8b03cad0c2c0b4"},
+    {file = "frozenlist-1.3.3-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:f20380df709d91525e4bee04746ba612a4df0972c1b8f8e1e8af997e678c7b81"},
+    {file = "frozenlist-1.3.3-cp311-cp311-win32.whl", hash = "sha256:f30f1928162e189091cf4d9da2eac617bfe78ef907a761614ff577ef4edfb3c8"},
+    {file = "frozenlist-1.3.3-cp311-cp311-win_amd64.whl", hash = "sha256:a6394d7dadd3cfe3f4b3b186e54d5d8504d44f2d58dcc89d693698e8b7132b32"},
+    {file = "frozenlist-1.3.3-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:8df3de3a9ab8325f94f646609a66cbeeede263910c5c0de0101079ad541af332"},
+    {file = "frozenlist-1.3.3-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0693c609e9742c66ba4870bcee1ad5ff35462d5ffec18710b4ac89337ff16e27"},
+    {file = "frozenlist-1.3.3-cp37-cp37m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:cd4210baef299717db0a600d7a3cac81d46ef0e007f88c9335db79f8979c0d3d"},
+    {file = "frozenlist-1.3.3-cp37-cp37m-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:394c9c242113bfb4b9aa36e2b80a05ffa163a30691c7b5a29eba82e937895d5e"},
+    {file = "frozenlist-1.3.3-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:6327eb8e419f7d9c38f333cde41b9ae348bec26d840927332f17e887a8dcb70d"},
+    {file = "frozenlist-1.3.3-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:2e24900aa13212e75e5b366cb9065e78bbf3893d4baab6052d1aca10d46d944c"},
+    {file = "frozenlist-1.3.3-cp37-cp37m-musllinux_1_1_aarch64.whl", hash = "sha256:3843f84a6c465a36559161e6c59dce2f2ac10943040c2fd021cfb70d58c4ad56"},
+    {file = "frozenlist-1.3.3-cp37-cp37m-musllinux_1_1_i686.whl", hash = "sha256:84610c1502b2461255b4c9b7d5e9c48052601a8957cd0aea6ec7a7a1e1fb9420"},
+    {file = "frozenlist-1.3.3-cp37-cp37m-musllinux_1_1_ppc64le.whl", hash = "sha256:c21b9aa40e08e4f63a2f92ff3748e6b6c84d717d033c7b3438dd3123ee18f70e"},
+    {file = "frozenlist-1.3.3-cp37-cp37m-musllinux_1_1_s390x.whl", hash = "sha256:efce6ae830831ab6a22b9b4091d411698145cb9b8fc869e1397ccf4b4b6455cb"},
+    {file = "frozenlist-1.3.3-cp37-cp37m-musllinux_1_1_x86_64.whl", hash = "sha256:40de71985e9042ca00b7953c4f41eabc3dc514a2d1ff534027f091bc74416401"},
+    {file = "frozenlist-1.3.3-cp37-cp37m-win32.whl", hash = "sha256:180c00c66bde6146a860cbb81b54ee0df350d2daf13ca85b275123bbf85de18a"},
+    {file = "frozenlist-1.3.3-cp37-cp37m-win_amd64.whl", hash = "sha256:9bbbcedd75acdfecf2159663b87f1bb5cfc80e7cd99f7ddd9d66eb98b14a8411"},
+    {file = "frozenlist-1.3.3-cp38-cp38-macosx_10_9_universal2.whl", hash = "sha256:034a5c08d36649591be1cbb10e09da9f531034acfe29275fc5454a3b101ce41a"},
+    {file = "frozenlist-1.3.3-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:ba64dc2b3b7b158c6660d49cdb1d872d1d0bf4e42043ad8d5006099479a194e5"},
+    {file = "frozenlist-1.3.3-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:47df36a9fe24054b950bbc2db630d508cca3aa27ed0566c0baf661225e52c18e"},
+    {file = "frozenlist-1.3.3-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:008a054b75d77c995ea26629ab3a0c0d7281341f2fa7e1e85fa6153ae29ae99c"},
+    {file = "frozenlist-1.3.3-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:841ea19b43d438a80b4de62ac6ab21cfe6827bb8a9dc62b896acc88eaf9cecba"},
+    {file = "frozenlist-1.3.3-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:e235688f42b36be2b6b06fc37ac2126a73b75fb8d6bc66dd632aa35286238703"},
+    {file = "frozenlist-1.3.3-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:ca713d4af15bae6e5d79b15c10c8522859a9a89d3b361a50b817c98c2fb402a2"},
+    {file = "frozenlist-1.3.3-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9ac5995f2b408017b0be26d4a1d7c61bce106ff3d9e3324374d66b5964325448"},
+    {file = "frozenlist-1.3.3-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:a4ae8135b11652b08a8baf07631d3ebfe65a4c87909dbef5fa0cdde440444ee4"},
+    {file = "frozenlist-1.3.3-cp38-cp38-musllinux_1_1_i686.whl", hash = "sha256:4ea42116ceb6bb16dbb7d526e242cb6747b08b7710d9782aa3d6732bd8d27649"},
+    {file = "frozenlist-1.3.3-cp38-cp38-musllinux_1_1_ppc64le.whl", hash = "sha256:810860bb4bdce7557bc0febb84bbd88198b9dbc2022d8eebe5b3590b2ad6c842"},
+    {file = "frozenlist-1.3.3-cp38-cp38-musllinux_1_1_s390x.whl", hash = "sha256:ee78feb9d293c323b59a6f2dd441b63339a30edf35abcb51187d2fc26e696d13"},
+    {file = "frozenlist-1.3.3-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:0af2e7c87d35b38732e810befb9d797a99279cbb85374d42ea61c1e9d23094b3"},
+    {file = "frozenlist-1.3.3-cp38-cp38-win32.whl", hash = "sha256:899c5e1928eec13fd6f6d8dc51be23f0d09c5281e40d9cf4273d188d9feeaf9b"},
+    {file = "frozenlist-1.3.3-cp38-cp38-win_amd64.whl", hash = "sha256:7f44e24fa70f6fbc74aeec3e971f60a14dde85da364aa87f15d1be94ae75aeef"},
+    {file = "frozenlist-1.3.3-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:2b07ae0c1edaa0a36339ec6cce700f51b14a3fc6545fdd32930d2c83917332cf"},
+    {file = "frozenlist-1.3.3-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:ebb86518203e12e96af765ee89034a1dbb0c3c65052d1b0c19bbbd6af8a145e1"},
+    {file = "frozenlist-1.3.3-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:5cf820485f1b4c91e0417ea0afd41ce5cf5965011b3c22c400f6d144296ccbc0"},
+    {file = "frozenlist-1.3.3-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:5c11e43016b9024240212d2a65043b70ed8dfd3b52678a1271972702d990ac6d"},
+    {file = "frozenlist-1.3.3-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:8fa3c6e3305aa1146b59a09b32b2e04074945ffcfb2f0931836d103a2c38f936"},
+    {file = "frozenlist-1.3.3-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:352bd4c8c72d508778cf05ab491f6ef36149f4d0cb3c56b1b4302852255d05d5"},
+    {file = "frozenlist-1.3.3-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:65a5e4d3aa679610ac6e3569e865425b23b372277f89b5ef06cf2cdaf1ebf22b"},
+    {file = "frozenlist-1.3.3-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b1e2c1185858d7e10ff045c496bbf90ae752c28b365fef2c09cf0fa309291669"},
+    {file = "frozenlist-1.3.3-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:f163d2fd041c630fed01bc48d28c3ed4a3b003c00acd396900e11ee5316b56bb"},
+    {file = "frozenlist-1.3.3-cp39-cp39-musllinux_1_1_i686.whl", hash = "sha256:05cdb16d09a0832eedf770cb7bd1fe57d8cf4eaf5aced29c4e41e3f20b30a784"},
+    {file = "frozenlist-1.3.3-cp39-cp39-musllinux_1_1_ppc64le.whl", hash = "sha256:8bae29d60768bfa8fb92244b74502b18fae55a80eac13c88eb0b496d4268fd2d"},
+    {file = "frozenlist-1.3.3-cp39-cp39-musllinux_1_1_s390x.whl", hash = "sha256:eedab4c310c0299961ac285591acd53dc6723a1ebd90a57207c71f6e0c2153ab"},
+    {file = "frozenlist-1.3.3-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:3bbdf44855ed8f0fbcd102ef05ec3012d6a4fd7c7562403f76ce6a52aeffb2b1"},
+    {file = "frozenlist-1.3.3-cp39-cp39-win32.whl", hash = "sha256:efa568b885bca461f7c7b9e032655c0c143d305bf01c30caf6db2854a4532b38"},
+    {file = "frozenlist-1.3.3-cp39-cp39-win_amd64.whl", hash = "sha256:cfe33efc9cb900a4c46f91a5ceba26d6df370ffddd9ca386eb1d4f0ad97b9ea9"},
+    {file = "frozenlist-1.3.3.tar.gz", hash = "sha256:58bcc55721e8a90b88332d6cd441261ebb22342e238296bb330968952fbb3a6a"},
+]
+
+[[package]]
+name = "fsspec"
+version = "2023.3.0"
+description = "File-system specification"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "fsspec-2023.3.0-py3-none-any.whl", hash = "sha256:bf57215e19dbfa4fe7edae53040cc1deef825e3b1605cca9a8d2c2fadd2328a0"},
+    {file = "fsspec-2023.3.0.tar.gz", hash = "sha256:24e635549a590d74c6c18274ddd3ffab4753341753e923408b1904eaabafe04d"},
+]
+
+[package.extras]
+abfs = ["adlfs"]
+adl = ["adlfs"]
+arrow = ["pyarrow (>=1)"]
+dask = ["dask", "distributed"]
+dropbox = ["dropbox", "dropboxdrivefs", "requests"]
+fuse = ["fusepy"]
+gcs = ["gcsfs"]
+git = ["pygit2"]
+github = ["requests"]
+gs = ["gcsfs"]
+gui = ["panel"]
+hdfs = ["pyarrow (>=1)"]
+http = ["aiohttp (!=4.0.0a0,!=4.0.0a1)", "requests"]
+libarchive = ["libarchive-c"]
+oci = ["ocifs"]
+s3 = ["s3fs"]
+sftp = ["paramiko"]
+smb = ["smbprotocol"]
+ssh = ["paramiko"]
+tqdm = ["tqdm"]
+
+[[package]]
+name = "functorch"
+version = "2.0.0"
+description = "JAX-like composable function transforms for PyTorch"
+optional = false
+python-versions = "*"
+files = [
+    {file = "functorch-2.0.0-py2.py3-none-any.whl", hash = "sha256:ca21ace6b9048e2ec6d132fa0fd18c776eb165ca1c91ef7e3584fdc668eaa4ea"},
+]
+
+[package.dependencies]
+torch = ">=2.0,<2.1"
+
+[package.extras]
+aot = ["networkx"]
+
+[[package]]
+name = "future"
+version = "0.18.3"
+description = "Clean single-source support for Python 3 and 2"
+optional = false
+python-versions = ">=2.6, !=3.0.*, !=3.1.*, !=3.2.*"
+files = [
+    {file = "future-0.18.3.tar.gz", hash = "sha256:34a17436ed1e96697a86f9de3d15a3b0be01d8bc8de9c1dffd59fb8234ed5307"},
+]
+
+[[package]]
+name = "google-auth"
+version = "2.17.1"
+description = "Google Authentication Library"
+optional = false
+python-versions = ">=2.7,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*"
+files = [
+    {file = "google-auth-2.17.1.tar.gz", hash = "sha256:8f379b46bad381ad2a0b989dfb0c13ad28d3c2a79f27348213f8946a1d15d55a"},
+    {file = "google_auth-2.17.1-py2.py3-none-any.whl", hash = "sha256:357ff22a75b4c0f6093470f21816a825d2adee398177569824e37b6c10069e19"},
+]
+
+[package.dependencies]
+cachetools = ">=2.0.0,<6.0"
+pyasn1-modules = ">=0.2.1"
+rsa = {version = ">=3.1.4,<5", markers = "python_version >= \"3.6\""}
+six = ">=1.9.0"
+
+[package.extras]
+aiohttp = ["aiohttp (>=3.6.2,<4.0.0dev)", "requests (>=2.20.0,<3.0.0dev)"]
+enterprise-cert = ["cryptography (==36.0.2)", "pyopenssl (==22.0.0)"]
+pyopenssl = ["cryptography (>=38.0.3)", "pyopenssl (>=20.0.0)"]
+reauth = ["pyu2f (>=0.1.5)"]
+requests = ["requests (>=2.20.0,<3.0.0dev)"]
+
+[[package]]
+name = "google-auth-oauthlib"
+version = "1.0.0"
+description = "Google Authentication Library"
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "google-auth-oauthlib-1.0.0.tar.gz", hash = "sha256:e375064964820b47221a7e1b7ee1fd77051b6323c3f9e3e19785f78ab67ecfc5"},
+    {file = "google_auth_oauthlib-1.0.0-py2.py3-none-any.whl", hash = "sha256:95880ca704928c300f48194d1770cf5b1462835b6e49db61445a520f793fd5fb"},
+]
+
+[package.dependencies]
+google-auth = ">=2.15.0"
+requests-oauthlib = ">=0.7.0"
+
+[package.extras]
+tool = ["click (>=6.0.0)"]
+
+[[package]]
+name = "gradio"
+version = "3.34.0"
+description = "Python library for easily interacting with trained machine learning models"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "gradio-3.34.0-py3-none-any.whl", hash = "sha256:1cd8b25b598d983561d64f0a039af819382f1376c676aa9f84972c46b6875741"},
+    {file = "gradio-3.34.0.tar.gz", hash = "sha256:fd7fa7257ffc749f9dc7c297eba554eaa1e5acd1a5f9c973250b2080932d6a41"},
+]
+
+[package.dependencies]
+aiofiles = "*"
+aiohttp = "*"
+altair = ">=4.2.0"
+fastapi = "*"
+ffmpy = "*"
+gradio-client = ">=0.2.6"
+httpx = "*"
+huggingface-hub = ">=0.14.0"
+jinja2 = "*"
+markdown-it-py = {version = ">=2.0.0", extras = ["linkify"]}
+markupsafe = "*"
+matplotlib = "*"
+mdit-py-plugins = "<=0.3.3"
+numpy = "*"
+orjson = "*"
+pandas = "*"
+pillow = "*"
+pydantic = "*"
+pydub = "*"
+pygments = ">=2.12.0"
+python-multipart = "*"
+pyyaml = "*"
+requests = "*"
+semantic-version = "*"
+typing-extensions = "*"
+uvicorn = ">=0.14.0"
+websockets = ">=10.0"
+
+[[package]]
+name = "gradio-client"
+version = "0.2.7"
+description = "Python library for easily interacting with trained machine learning models"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "gradio_client-0.2.7-py3-none-any.whl", hash = "sha256:4a7ec6bb1341c626051f1ed24d50cb960ff1a4cd1a5db031dd4caaf1ee7d2d0a"},
+    {file = "gradio_client-0.2.7.tar.gz", hash = "sha256:c83008df8a1dd3f81a290c0a24c03d0ab70317741991b60f713620ed39ad8f12"},
+]
+
+[package.dependencies]
+fsspec = "*"
+httpx = "*"
+huggingface-hub = ">=0.13.0"
+packaging = "*"
+requests = "*"
+typing-extensions = "*"
+websockets = "*"
+
+[[package]]
+name = "grpcio"
+version = "1.53.0"
+description = "HTTP/2-based RPC framework"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "grpcio-1.53.0-cp310-cp310-linux_armv7l.whl", hash = "sha256:752d2949b40e12e6ad3ed8cc552a65b54d226504f6b1fb67cab2ccee502cc06f"},
+    {file = "grpcio-1.53.0-cp310-cp310-macosx_12_0_universal2.whl", hash = "sha256:8a48fd3a7222be226bb86b7b413ad248f17f3101a524018cdc4562eeae1eb2a3"},
+    {file = "grpcio-1.53.0-cp310-cp310-manylinux_2_17_aarch64.whl", hash = "sha256:f3e837d29f0e1b9d6e7b29d569e2e9b0da61889e41879832ea15569c251c303a"},
+    {file = "grpcio-1.53.0-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:aef7d30242409c3aa5839b501e877e453a2c8d3759ca8230dd5a21cda029f046"},
+    {file = "grpcio-1.53.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e6f90698b5d1c5dd7b3236cd1fa959d7b80e17923f918d5be020b65f1c78b173"},
+    {file = "grpcio-1.53.0-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:a96c3c7f564b263c5d7c0e49a337166c8611e89c4c919f66dba7b9a84abad137"},
+    {file = "grpcio-1.53.0-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:ee81349411648d1abc94095c68cd25e3c2812e4e0367f9a9355be1e804a5135c"},
+    {file = "grpcio-1.53.0-cp310-cp310-win32.whl", hash = "sha256:fdc6191587de410a184550d4143e2b24a14df495c86ca15e59508710681690ac"},
+    {file = "grpcio-1.53.0-cp310-cp310-win_amd64.whl", hash = "sha256:658ffe1e39171be00490db5bd3b966f79634ac4215a1eb9a85c6cd6783bf7f6e"},
+    {file = "grpcio-1.53.0-cp311-cp311-linux_armv7l.whl", hash = "sha256:1b172e6d497191940c4b8d75b53de82dc252e15b61de2951d577ec5b43316b29"},
+    {file = "grpcio-1.53.0-cp311-cp311-macosx_10_10_universal2.whl", hash = "sha256:82434ba3a5935e47908bc861ce1ebc43c2edfc1001d235d6e31e5d3ed55815f7"},
+    {file = "grpcio-1.53.0-cp311-cp311-manylinux_2_17_aarch64.whl", hash = "sha256:1c734a2d4843e4e14ececf5600c3c4750990ec319e1299db7e4f0d02c25c1467"},
+    {file = "grpcio-1.53.0-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:b6a2ead3de3b2d53119d473aa2f224030257ef33af1e4ddabd4afee1dea5f04c"},
+    {file = "grpcio-1.53.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a34d6e905f071f9b945cabbcc776e2055de1fdb59cd13683d9aa0a8f265b5bf9"},
+    {file = "grpcio-1.53.0-cp311-cp311-musllinux_1_1_i686.whl", hash = "sha256:eaf8e3b97caaf9415227a3c6ca5aa8d800fecadd526538d2bf8f11af783f1550"},
+    {file = "grpcio-1.53.0-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:da95778d37be8e4e9afca771a83424f892296f5dfb2a100eda2571a1d8bbc0dc"},
+    {file = "grpcio-1.53.0-cp311-cp311-win32.whl", hash = "sha256:e4f513d63df6336fd84b74b701f17d1bb3b64e9d78a6ed5b5e8a198bbbe8bbfa"},
+    {file = "grpcio-1.53.0-cp311-cp311-win_amd64.whl", hash = "sha256:ddb2511fbbb440ed9e5c9a4b9b870f2ed649b7715859fd6f2ebc585ee85c0364"},
+    {file = "grpcio-1.53.0-cp37-cp37m-linux_armv7l.whl", hash = "sha256:2a912397eb8d23c177d6d64e3c8bc46b8a1c7680b090d9f13a640b104aaec77c"},
+    {file = "grpcio-1.53.0-cp37-cp37m-macosx_10_10_universal2.whl", hash = "sha256:55930c56b8f5b347d6c8c609cc341949a97e176c90f5cbb01d148d778f3bbd23"},
+    {file = "grpcio-1.53.0-cp37-cp37m-manylinux_2_17_aarch64.whl", hash = "sha256:6601d812105583948ab9c6e403a7e2dba6e387cc678c010e74f2d6d589d1d1b3"},
+    {file = "grpcio-1.53.0-cp37-cp37m-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:c705e0c21acb0e8478a00e7e773ad0ecdb34bd0e4adc282d3d2f51ba3961aac7"},
+    {file = "grpcio-1.53.0-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ba074af9ca268ad7b05d3fc2b920b5fb3c083da94ab63637aaf67f4f71ecb755"},
+    {file = "grpcio-1.53.0-cp37-cp37m-musllinux_1_1_i686.whl", hash = "sha256:14817de09317dd7d3fbc8272864288320739973ef0f4b56bf2c0032349da8cdf"},
+    {file = "grpcio-1.53.0-cp37-cp37m-musllinux_1_1_x86_64.whl", hash = "sha256:c7ad9fbedb93f331c2e9054e202e95cf825b885811f1bcbbdfdc301e451442db"},
+    {file = "grpcio-1.53.0-cp37-cp37m-win_amd64.whl", hash = "sha256:dad5b302a4c21c604d88a5d441973f320134e6ff6a84ecef9c1139e5ffd466f6"},
+    {file = "grpcio-1.53.0-cp38-cp38-linux_armv7l.whl", hash = "sha256:fa8eaac75d3107e3f5465f2c9e3bbd13db21790c6e45b7de1756eba16b050aca"},
+    {file = "grpcio-1.53.0-cp38-cp38-macosx_10_10_universal2.whl", hash = "sha256:104a2210edd3776c38448b4f76c2f16e527adafbde171fc72a8a32976c20abc7"},
+    {file = "grpcio-1.53.0-cp38-cp38-manylinux_2_17_aarch64.whl", hash = "sha256:dbc1ba968639c1d23476f75c356e549e7bbf2d8d6688717dcab5290e88e8482b"},
+    {file = "grpcio-1.53.0-cp38-cp38-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:95952d3fe795b06af29bb8ec7bbf3342cdd867fc17b77cc25e6733d23fa6c519"},
+    {file = "grpcio-1.53.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f144a790f14c51b8a8e591eb5af40507ffee45ea6b818c2482f0457fec2e1a2e"},
+    {file = "grpcio-1.53.0-cp38-cp38-musllinux_1_1_i686.whl", hash = "sha256:0698c094688a2dd4c7c2f2c0e3e142cac439a64d1cef6904c97f6cde38ba422f"},
+    {file = "grpcio-1.53.0-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:6b6d60b0958be711bab047e9f4df5dbbc40367955f8651232bfdcdd21450b9ab"},
+    {file = "grpcio-1.53.0-cp38-cp38-win32.whl", hash = "sha256:1948539ce78805d4e6256ab0e048ec793956d54787dc9d6777df71c1d19c7f81"},
+    {file = "grpcio-1.53.0-cp38-cp38-win_amd64.whl", hash = "sha256:df9ba1183b3f649210788cf80c239041dddcb375d6142d8bccafcfdf549522cd"},
+    {file = "grpcio-1.53.0-cp39-cp39-linux_armv7l.whl", hash = "sha256:19caa5b7282a89b799e63776ff602bb39604f7ca98db6df27e2de06756ae86c3"},
+    {file = "grpcio-1.53.0-cp39-cp39-macosx_10_10_universal2.whl", hash = "sha256:b5bd026ac928c96cc23149e6ef79183125542062eb6d1ccec34c0a37e02255e7"},
+    {file = "grpcio-1.53.0-cp39-cp39-manylinux_2_17_aarch64.whl", hash = "sha256:7dc8584ca6c015ad82e186e82f4c0fe977394588f66b8ecfc4ec873285314619"},
+    {file = "grpcio-1.53.0-cp39-cp39-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:2eddaae8af625e45b5c8500dcca1043264d751a6872cde2eda5022df8a336959"},
+    {file = "grpcio-1.53.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c5fb6f3d7824696c1c9f2ad36ddb080ba5a86f2d929ef712d511b4d9972d3d27"},
+    {file = "grpcio-1.53.0-cp39-cp39-musllinux_1_1_i686.whl", hash = "sha256:8270d1dc2c98ab57e6dbf36fa187db8df4c036f04a398e5d5e25b4e01a766d70"},
+    {file = "grpcio-1.53.0-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:976a7f24eb213e8429cab78d5e120500dfcdeb01041f1f5a77b17b9101902615"},
+    {file = "grpcio-1.53.0-cp39-cp39-win32.whl", hash = "sha256:9c84a481451e7174f3a764a44150f93b041ab51045aa33d7b5b68b6979114e48"},
+    {file = "grpcio-1.53.0-cp39-cp39-win_amd64.whl", hash = "sha256:6beb84f83360ff29a3654f43f251ec11b809dcb5524b698d711550243debd289"},
+    {file = "grpcio-1.53.0.tar.gz", hash = "sha256:a4952899b4931a6ba12951f9a141ef3e74ff8a6ec9aa2dc602afa40f63595e33"},
+]
+
+[package.extras]
+protobuf = ["grpcio-tools (>=1.53.0)"]
+
+[[package]]
+name = "h11"
+version = "0.14.0"
+description = "A pure-Python, bring-your-own-I/O implementation of HTTP/1.1"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "h11-0.14.0-py3-none-any.whl", hash = "sha256:e3fe4ac4b851c468cc8363d500db52c2ead036020723024a109d37346efaa761"},
+    {file = "h11-0.14.0.tar.gz", hash = "sha256:8f19fbbe99e72420ff35c00b27a34cb9937e902a8b810e2c88300c6f0a3b699d"},
+]
+
+[[package]]
+name = "httpcore"
+version = "0.16.3"
+description = "A minimal low-level HTTP client."
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "httpcore-0.16.3-py3-none-any.whl", hash = "sha256:da1fb708784a938aa084bde4feb8317056c55037247c787bd7e19eb2c2949dc0"},
+    {file = "httpcore-0.16.3.tar.gz", hash = "sha256:c5d6f04e2fc530f39e0c077e6a30caa53f1451096120f1f38b954afd0b17c0cb"},
+]
+
+[package.dependencies]
+anyio = ">=3.0,<5.0"
+certifi = "*"
+h11 = ">=0.13,<0.15"
+sniffio = "==1.*"
+
+[package.extras]
+http2 = ["h2 (>=3,<5)"]
+socks = ["socksio (==1.*)"]
+
+[[package]]
+name = "httpx"
+version = "0.23.3"
+description = "The next generation HTTP client."
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "httpx-0.23.3-py3-none-any.whl", hash = "sha256:a211fcce9b1254ea24f0cd6af9869b3d29aba40154e947d2a07bb499b3e310d6"},
+    {file = "httpx-0.23.3.tar.gz", hash = "sha256:9818458eb565bb54898ccb9b8b251a28785dd4a55afbc23d0eb410754fe7d0f9"},
+]
+
+[package.dependencies]
+certifi = "*"
+httpcore = ">=0.15.0,<0.17.0"
+rfc3986 = {version = ">=1.3,<2", extras = ["idna2008"]}
+sniffio = "*"
+
+[package.extras]
+brotli = ["brotli", "brotlicffi"]
+cli = ["click (==8.*)", "pygments (==2.*)", "rich (>=10,<13)"]
+http2 = ["h2 (>=3,<5)"]
+socks = ["socksio (==1.*)"]
+
+[[package]]
+name = "huggingface-hub"
+version = "0.15.1"
+description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
+optional = false
+python-versions = ">=3.7.0"
+files = [
+    {file = "huggingface_hub-0.15.1-py3-none-any.whl", hash = "sha256:05b0fb0abbf1f625dfee864648ac3049fe225ac4371c7bafaca0c2d3a2f83445"},
+    {file = "huggingface_hub-0.15.1.tar.gz", hash = "sha256:a61b7d1a7769fe10119e730277c72ab99d95c48d86a3d6da3e9f3d0f632a4081"},
+]
+
+[package.dependencies]
+filelock = "*"
+fsspec = "*"
+packaging = ">=20.9"
+pyyaml = ">=5.1"
+requests = "*"
+tqdm = ">=4.42.1"
+typing-extensions = ">=3.7.4.3"
+
+[package.extras]
+all = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "black (>=23.1,<24.0)", "gradio", "jedi", "mypy (==0.982)", "numpy", "pytest", "pytest-cov", "pytest-env", "pytest-vcr", "pytest-xdist", "ruff (>=0.0.241)", "soundfile", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "urllib3 (<2.0)"]
+cli = ["InquirerPy (==0.3.4)"]
+dev = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "black (>=23.1,<24.0)", "gradio", "jedi", "mypy (==0.982)", "numpy", "pytest", "pytest-cov", "pytest-env", "pytest-vcr", "pytest-xdist", "ruff (>=0.0.241)", "soundfile", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "urllib3 (<2.0)"]
+fastai = ["fastai (>=2.4)", "fastcore (>=1.3.27)", "toml"]
+quality = ["black (>=23.1,<24.0)", "mypy (==0.982)", "ruff (>=0.0.241)"]
+tensorflow = ["graphviz", "pydot", "tensorflow"]
+testing = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "gradio", "jedi", "numpy", "pytest", "pytest-cov", "pytest-env", "pytest-vcr", "pytest-xdist", "soundfile", "urllib3 (<2.0)"]
+torch = ["torch"]
+typing = ["types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3"]
+
+[[package]]
+name = "hydra-core"
+version = "1.0.7"
+description = "A framework for elegantly configuring complex applications"
+optional = false
+python-versions = "*"
+files = [
+    {file = "hydra-core-1.0.7.tar.gz", hash = "sha256:58cc3f7531995b6d8de162ca21f936e17bdaebd4d1e8614d63c32e17c2e41e45"},
+    {file = "hydra_core-1.0.7-py3-none-any.whl", hash = "sha256:e800c6deb8309395508094851fa93bc13408f2285261eb97e626d37193b58a9f"},
+]
+
+[package.dependencies]
+antlr4-python3-runtime = "4.8"
+importlib-resources = {version = "*", markers = "python_version < \"3.9\""}
+omegaconf = ">=2.0.5,<2.1"
+
+[[package]]
+name = "idna"
+version = "3.4"
+description = "Internationalized Domain Names in Applications (IDNA)"
+optional = false
+python-versions = ">=3.5"
+files = [
+    {file = "idna-3.4-py3-none-any.whl", hash = "sha256:90b77e79eaa3eba6de819a0c442c0b4ceefc341a7a2ab77d7562bf49f425c5c2"},
+    {file = "idna-3.4.tar.gz", hash = "sha256:814f528e8dead7d329833b91c5faa87d60bf71824cd12a7530b5526063d02cb4"},
+]
+
+[[package]]
+name = "importlib-metadata"
+version = "6.1.0"
+description = "Read metadata from Python packages"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "importlib_metadata-6.1.0-py3-none-any.whl", hash = "sha256:ff80f3b5394912eb1b108fcfd444dc78b7f1f3e16b16188054bd01cb9cb86f09"},
+    {file = "importlib_metadata-6.1.0.tar.gz", hash = "sha256:43ce9281e097583d758c2c708c4376371261a02c34682491a8e98352365aad20"},
+]
+
+[package.dependencies]
+zipp = ">=0.5"
+
+[package.extras]
+docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
+perf = ["ipython"]
+testing = ["flake8 (<5)", "flufl.flake8", "importlib-resources (>=1.3)", "packaging", "pyfakefs", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)", "pytest-perf (>=0.9.2)"]
+
+[[package]]
+name = "importlib-resources"
+version = "5.12.0"
+description = "Read resources from Python packages"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "importlib_resources-5.12.0-py3-none-any.whl", hash = "sha256:7b1deeebbf351c7578e09bf2f63fa2ce8b5ffec296e0d349139d43cca061a81a"},
+    {file = "importlib_resources-5.12.0.tar.gz", hash = "sha256:4be82589bf5c1d7999aedf2a45159d10cb3ca4f19b2271f8792bc8e6da7b22f6"},
+]
+
+[package.dependencies]
+zipp = {version = ">=3.1.0", markers = "python_version < \"3.10\""}
+
+[package.extras]
+docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
+testing = ["flake8 (<5)", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)"]
+
+[[package]]
+name = "jinja2"
+version = "3.1.2"
+description = "A very fast and expressive template engine."
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "Jinja2-3.1.2-py3-none-any.whl", hash = "sha256:6088930bfe239f0e6710546ab9c19c9ef35e29792895fed6e6e31a023a182a61"},
+    {file = "Jinja2-3.1.2.tar.gz", hash = "sha256:31351a702a408a9e7595a8fc6150fc3f43bb6bf7e319770cbc0db9df9437e852"},
+]
+
+[package.dependencies]
+MarkupSafe = ">=2.0"
+
+[package.extras]
+i18n = ["Babel (>=2.7)"]
+
+[[package]]
+name = "joblib"
+version = "1.2.0"
+description = "Lightweight pipelining with Python functions"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "joblib-1.2.0-py3-none-any.whl", hash = "sha256:091138ed78f800342968c523bdde947e7a305b8594b910a0fea2ab83c3c6d385"},
+    {file = "joblib-1.2.0.tar.gz", hash = "sha256:e1cee4a79e4af22881164f218d4311f60074197fb707e082e803b61f6d137018"},
+]
+
+[[package]]
+name = "json5"
+version = "0.9.11"
+description = "A Python implementation of the JSON5 data format."
+optional = false
+python-versions = "*"
+files = [
+    {file = "json5-0.9.11-py2.py3-none-any.whl", hash = "sha256:1aa54b80b5e507dfe31d12b7743a642e2ffa6f70bf73b8e3d7d1d5fba83d99bd"},
+    {file = "json5-0.9.11.tar.gz", hash = "sha256:4f1e196acc55b83985a51318489f345963c7ba84aa37607e49073066c562e99b"},
+]
+
+[package.extras]
+dev = ["hypothesis"]
+
+[[package]]
+name = "jsonschema"
+version = "4.17.3"
+description = "An implementation of JSON Schema validation for Python"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "jsonschema-4.17.3-py3-none-any.whl", hash = "sha256:a870ad254da1a8ca84b6a2905cac29d265f805acc57af304784962a2aa6508f6"},
+    {file = "jsonschema-4.17.3.tar.gz", hash = "sha256:0f864437ab8b6076ba6707453ef8f98a6a0d512a80e93f8abdb676f737ecb60d"},
+]
+
+[package.dependencies]
+attrs = ">=17.4.0"
+importlib-resources = {version = ">=1.4.0", markers = "python_version < \"3.9\""}
+pkgutil-resolve-name = {version = ">=1.3.10", markers = "python_version < \"3.9\""}
+pyrsistent = ">=0.14.0,<0.17.0 || >0.17.0,<0.17.1 || >0.17.1,<0.17.2 || >0.17.2"
+
+[package.extras]
+format = ["fqdn", "idna", "isoduration", "jsonpointer (>1.13)", "rfc3339-validator", "rfc3987", "uri-template", "webcolors (>=1.11)"]
+format-nongpl = ["fqdn", "idna", "isoduration", "jsonpointer (>1.13)", "rfc3339-validator", "rfc3986-validator (>0.1.0)", "uri-template", "webcolors (>=1.11)"]
+
+[[package]]
+name = "kiwisolver"
+version = "1.4.4"
+description = "A fast implementation of the Cassowary constraint solver"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "kiwisolver-1.4.4-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:2f5e60fabb7343a836360c4f0919b8cd0d6dbf08ad2ca6b9cf90bf0c76a3c4f6"},
+    {file = "kiwisolver-1.4.4-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:10ee06759482c78bdb864f4109886dff7b8a56529bc1609d4f1112b93fe6423c"},
+    {file = "kiwisolver-1.4.4-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:c79ebe8f3676a4c6630fd3f777f3cfecf9289666c84e775a67d1d358578dc2e3"},
+    {file = "kiwisolver-1.4.4-cp310-cp310-manylinux_2_12_i686.manylinux2010_i686.whl", hash = "sha256:abbe9fa13da955feb8202e215c4018f4bb57469b1b78c7a4c5c7b93001699938"},
+    {file = "kiwisolver-1.4.4-cp310-cp310-manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:7577c1987baa3adc4b3c62c33bd1118c3ef5c8ddef36f0f2c950ae0b199e100d"},
+    {file = "kiwisolver-1.4.4-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f8ad8285b01b0d4695102546b342b493b3ccc6781fc28c8c6a1bb63e95d22f09"},
+    {file = "kiwisolver-1.4.4-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:8ed58b8acf29798b036d347791141767ccf65eee7f26bde03a71c944449e53de"},
+    {file = "kiwisolver-1.4.4-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:a68b62a02953b9841730db7797422f983935aeefceb1679f0fc85cbfbd311c32"},
+    {file = "kiwisolver-1.4.4-cp310-cp310-win32.whl", hash = "sha256:e92a513161077b53447160b9bd8f522edfbed4bd9759e4c18ab05d7ef7e49408"},
+    {file = "kiwisolver-1.4.4-cp310-cp310-win_amd64.whl", hash = "sha256:3fe20f63c9ecee44560d0e7f116b3a747a5d7203376abeea292ab3152334d004"},
+    {file = "kiwisolver-1.4.4-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:e0ea21f66820452a3f5d1655f8704a60d66ba1191359b96541eaf457710a5fc6"},
+    {file = "kiwisolver-1.4.4-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:bc9db8a3efb3e403e4ecc6cd9489ea2bac94244f80c78e27c31dcc00d2790ac2"},
+    {file = "kiwisolver-1.4.4-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:d5b61785a9ce44e5a4b880272baa7cf6c8f48a5180c3e81c59553ba0cb0821ca"},
+    {file = "kiwisolver-1.4.4-cp311-cp311-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:c2dbb44c3f7e6c4d3487b31037b1bdbf424d97687c1747ce4ff2895795c9bf69"},
+    {file = "kiwisolver-1.4.4-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6295ecd49304dcf3bfbfa45d9a081c96509e95f4b9d0eb7ee4ec0530c4a96514"},
+    {file = "kiwisolver-1.4.4-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:4bd472dbe5e136f96a4b18f295d159d7f26fd399136f5b17b08c4e5f498cd494"},
+    {file = "kiwisolver-1.4.4-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:bf7d9fce9bcc4752ca4a1b80aabd38f6d19009ea5cbda0e0856983cf6d0023f5"},
+    {file = "kiwisolver-1.4.4-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:78d6601aed50c74e0ef02f4204da1816147a6d3fbdc8b3872d263338a9052c51"},
+    {file = "kiwisolver-1.4.4-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:877272cf6b4b7e94c9614f9b10140e198d2186363728ed0f701c6eee1baec1da"},
+    {file = "kiwisolver-1.4.4-cp311-cp311-musllinux_1_1_i686.whl", hash = "sha256:db608a6757adabb32f1cfe6066e39b3706d8c3aa69bbc353a5b61edad36a5cb4"},
+    {file = "kiwisolver-1.4.4-cp311-cp311-musllinux_1_1_ppc64le.whl", hash = "sha256:5853eb494c71e267912275e5586fe281444eb5e722de4e131cddf9d442615626"},
+    {file = "kiwisolver-1.4.4-cp311-cp311-musllinux_1_1_s390x.whl", hash = "sha256:f0a1dbdb5ecbef0d34eb77e56fcb3e95bbd7e50835d9782a45df81cc46949750"},
+    {file = "kiwisolver-1.4.4-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:283dffbf061a4ec60391d51e6155e372a1f7a4f5b15d59c8505339454f8989e4"},
+    {file = "kiwisolver-1.4.4-cp311-cp311-win32.whl", hash = "sha256:d06adcfa62a4431d404c31216f0f8ac97397d799cd53800e9d3efc2fbb3cf14e"},
+    {file = "kiwisolver-1.4.4-cp311-cp311-win_amd64.whl", hash = "sha256:e7da3fec7408813a7cebc9e4ec55afed2d0fd65c4754bc376bf03498d4e92686"},
+    {file = "kiwisolver-1.4.4-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:62ac9cc684da4cf1778d07a89bf5f81b35834cb96ca523d3a7fb32509380cbf6"},
+    {file = "kiwisolver-1.4.4-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:41dae968a94b1ef1897cb322b39360a0812661dba7c682aa45098eb8e193dbdf"},
+    {file = "kiwisolver-1.4.4-cp37-cp37m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:02f79693ec433cb4b5f51694e8477ae83b3205768a6fb48ffba60549080e295b"},
+    {file = "kiwisolver-1.4.4-cp37-cp37m-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:d0611a0a2a518464c05ddd5a3a1a0e856ccc10e67079bb17f265ad19ab3c7597"},
+    {file = "kiwisolver-1.4.4-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:db5283d90da4174865d520e7366801a93777201e91e79bacbac6e6927cbceede"},
+    {file = "kiwisolver-1.4.4-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.whl", hash = "sha256:1041feb4cda8708ce73bb4dcb9ce1ccf49d553bf87c3954bdfa46f0c3f77252c"},
+    {file = "kiwisolver-1.4.4-cp37-cp37m-win32.whl", hash = "sha256:a553dadda40fef6bfa1456dc4be49b113aa92c2a9a9e8711e955618cd69622e3"},
+    {file = "kiwisolver-1.4.4-cp37-cp37m-win_amd64.whl", hash = "sha256:03baab2d6b4a54ddbb43bba1a3a2d1627e82d205c5cf8f4c924dc49284b87166"},
+    {file = "kiwisolver-1.4.4-cp38-cp38-macosx_10_9_universal2.whl", hash = "sha256:841293b17ad704d70c578f1f0013c890e219952169ce8a24ebc063eecf775454"},
+    {file = "kiwisolver-1.4.4-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:f4f270de01dd3e129a72efad823da90cc4d6aafb64c410c9033aba70db9f1ff0"},
+    {file = "kiwisolver-1.4.4-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:f9f39e2f049db33a908319cf46624a569b36983c7c78318e9726a4cb8923b26c"},
+    {file = "kiwisolver-1.4.4-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c97528e64cb9ebeff9701e7938653a9951922f2a38bd847787d4a8e498cc83ae"},
+    {file = "kiwisolver-1.4.4-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:1d1573129aa0fd901076e2bfb4275a35f5b7aa60fbfb984499d661ec950320b0"},
+    {file = "kiwisolver-1.4.4-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:ad881edc7ccb9d65b0224f4e4d05a1e85cf62d73aab798943df6d48ab0cd79a1"},
+    {file = "kiwisolver-1.4.4-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:b428ef021242344340460fa4c9185d0b1f66fbdbfecc6c63eff4b7c29fad429d"},
+    {file = "kiwisolver-1.4.4-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.whl", hash = "sha256:2e407cb4bd5a13984a6c2c0fe1845e4e41e96f183e5e5cd4d77a857d9693494c"},
+    {file = "kiwisolver-1.4.4-cp38-cp38-win32.whl", hash = "sha256:75facbe9606748f43428fc91a43edb46c7ff68889b91fa31f53b58894503a191"},
+    {file = "kiwisolver-1.4.4-cp38-cp38-win_amd64.whl", hash = "sha256:5bce61af018b0cb2055e0e72e7d65290d822d3feee430b7b8203d8a855e78766"},
+    {file = "kiwisolver-1.4.4-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:8c808594c88a025d4e322d5bb549282c93c8e1ba71b790f539567932722d7bd8"},
+    {file = "kiwisolver-1.4.4-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:f0a71d85ecdd570ded8ac3d1c0f480842f49a40beb423bb8014539a9f32a5897"},
+    {file = "kiwisolver-1.4.4-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:b533558eae785e33e8c148a8d9921692a9fe5aa516efbdff8606e7d87b9d5824"},
+    {file = "kiwisolver-1.4.4-cp39-cp39-manylinux_2_12_i686.manylinux2010_i686.whl", hash = "sha256:efda5fc8cc1c61e4f639b8067d118e742b812c930f708e6667a5ce0d13499e29"},
+    {file = "kiwisolver-1.4.4-cp39-cp39-manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:7c43e1e1206cd421cd92e6b3280d4385d41d7166b3ed577ac20444b6995a445f"},
+    {file = "kiwisolver-1.4.4-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:bc8d3bd6c72b2dd9decf16ce70e20abcb3274ba01b4e1c96031e0c4067d1e7cd"},
+    {file = "kiwisolver-1.4.4-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:4ea39b0ccc4f5d803e3337dd46bcce60b702be4d86fd0b3d7531ef10fd99a1ac"},
+    {file = "kiwisolver-1.4.4-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:968f44fdbf6dd757d12920d63b566eeb4d5b395fd2d00d29d7ef00a00582aac9"},
+    {file = "kiwisolver-1.4.4-cp39-cp39-win32.whl", hash = "sha256:da7e547706e69e45d95e116e6939488d62174e033b763ab1496b4c29b76fabea"},
+    {file = "kiwisolver-1.4.4-cp39-cp39-win_amd64.whl", hash = "sha256:ba59c92039ec0a66103b1d5fe588fa546373587a7d68f5c96f743c3396afc04b"},
+    {file = "kiwisolver-1.4.4-pp37-pypy37_pp73-manylinux_2_12_i686.manylinux2010_i686.whl", hash = "sha256:91672bacaa030f92fc2f43b620d7b337fd9a5af28b0d6ed3f77afc43c4a64b5a"},
+    {file = "kiwisolver-1.4.4-pp37-pypy37_pp73-manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:787518a6789009c159453da4d6b683f468ef7a65bbde796bcea803ccf191058d"},
+    {file = "kiwisolver-1.4.4-pp37-pypy37_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:da152d8cdcab0e56e4f45eb08b9aea6455845ec83172092f09b0e077ece2cf7a"},
+    {file = "kiwisolver-1.4.4-pp37-pypy37_pp73-win_amd64.whl", hash = "sha256:ecb1fa0db7bf4cff9dac752abb19505a233c7f16684c5826d1f11ebd9472b871"},
+    {file = "kiwisolver-1.4.4-pp38-pypy38_pp73-macosx_10_9_x86_64.whl", hash = "sha256:28bc5b299f48150b5f822ce68624e445040595a4ac3d59251703779836eceff9"},
+    {file = "kiwisolver-1.4.4-pp38-pypy38_pp73-manylinux_2_12_i686.manylinux2010_i686.whl", hash = "sha256:81e38381b782cc7e1e46c4e14cd997ee6040768101aefc8fa3c24a4cc58e98f8"},
+    {file = "kiwisolver-1.4.4-pp38-pypy38_pp73-manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:2a66fdfb34e05b705620dd567f5a03f239a088d5a3f321e7b6ac3239d22aa286"},
+    {file = "kiwisolver-1.4.4-pp38-pypy38_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:872b8ca05c40d309ed13eb2e582cab0c5a05e81e987ab9c521bf05ad1d5cf5cb"},
+    {file = "kiwisolver-1.4.4-pp38-pypy38_pp73-win_amd64.whl", hash = "sha256:70e7c2e7b750585569564e2e5ca9845acfaa5da56ac46df68414f29fea97be9f"},
+    {file = "kiwisolver-1.4.4-pp39-pypy39_pp73-macosx_10_9_x86_64.whl", hash = "sha256:9f85003f5dfa867e86d53fac6f7e6f30c045673fa27b603c397753bebadc3008"},
+    {file = "kiwisolver-1.4.4-pp39-pypy39_pp73-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:2e307eb9bd99801f82789b44bb45e9f541961831c7311521b13a6c85afc09767"},
+    {file = "kiwisolver-1.4.4-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:b1792d939ec70abe76f5054d3f36ed5656021dcad1322d1cc996d4e54165cef9"},
+    {file = "kiwisolver-1.4.4-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f6cb459eea32a4e2cf18ba5fcece2dbdf496384413bc1bae15583f19e567f3b2"},
+    {file = "kiwisolver-1.4.4-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:36dafec3d6d6088d34e2de6b85f9d8e2324eb734162fba59d2ba9ed7a2043d5b"},
+    {file = "kiwisolver-1.4.4.tar.gz", hash = "sha256:d41997519fcba4a1e46eb4a2fe31bc12f0ff957b2b81bac28db24744f333e955"},
+]
+
+[[package]]
+name = "librosa"
+version = "0.9.2"
+description = "Python module for audio and music processing"
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "librosa-0.9.2-py3-none-any.whl", hash = "sha256:322a813e6d37af9fbc369e6a637dcf5fdc5c6925ce806a0d27c68de61a81350f"},
+    {file = "librosa-0.9.2.tar.gz", hash = "sha256:5b576b5efdce428e90bc988bdd5a953d12a727e5f931f30d74c53b63abbe3c89"},
+]
+
+[package.dependencies]
+audioread = ">=2.1.9"
+decorator = ">=4.0.10"
+joblib = ">=0.14"
+numba = ">=0.45.1"
+numpy = ">=1.17.0"
+packaging = ">=20.0"
+pooch = ">=1.0"
+resampy = ">=0.2.2"
+scikit-learn = ">=0.19.1"
+scipy = ">=1.2.0"
+soundfile = ">=0.10.2"
+
+[package.extras]
+display = ["matplotlib (>=3.3.0)"]
+docs = ["ipython (>=7.0)", "matplotlib (>=3.3.0)", "mir-eval (>=0.5)", "numba (<0.50)", "numpydoc", "presets", "sphinx (!=1.3.1)", "sphinx-gallery (>=0.7)", "sphinx-multiversion (>=0.2.3)", "sphinx-rtd-theme (==1.*)", "sphinxcontrib-svg2pdfconverter"]
+tests = ["contextlib2", "matplotlib (>=3.3.0)", "pytest", "pytest-cov", "pytest-mpl", "samplerate", "soxr"]
+
+[[package]]
+name = "linkify-it-py"
+version = "2.0.0"
+description = "Links recognition library with FULL unicode support."
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "linkify-it-py-2.0.0.tar.gz", hash = "sha256:476464480906bed8b2fa3813bf55566282e55214ad7e41b7d1c2b564666caf2f"},
+    {file = "linkify_it_py-2.0.0-py3-none-any.whl", hash = "sha256:1bff43823e24e507a099e328fc54696124423dd6320c75a9da45b4b754b748ad"},
+]
+
+[package.dependencies]
+uc-micro-py = "*"
+
+[package.extras]
+benchmark = ["pytest", "pytest-benchmark"]
+dev = ["black", "flake8", "isort", "pre-commit"]
+doc = ["myst-parser", "sphinx", "sphinx-book-theme"]
+test = ["coverage", "pytest", "pytest-cov"]
+
+[[package]]
+name = "lit"
+version = "16.0.0"
+description = "A Software Testing Tool"
+optional = false
+python-versions = "*"
+files = [
+    {file = "lit-16.0.0.tar.gz", hash = "sha256:3c4ac372122a1de4a88deb277b956f91b7209420a0bef683b1ab2d2b16dabe11"},
+]
+
+[[package]]
+name = "llvmlite"
+version = "0.39.0"
+description = "lightweight wrapper around basic LLVM functionality"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "llvmlite-0.39.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:589f08a1b1920e6004735819ce9aafdd85d030d4a231c1e7adaca9360724b1ed"},
+    {file = "llvmlite-0.39.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:44a9a5cbe76db8ba01a5f6fa21649d91aa8a2634cc6f3a60291797e42e67d79e"},
+    {file = "llvmlite-0.39.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:74d89f2ec4734d3e200fb90ea0b3ca5e9be40f3b3e50eb368ca9002ed5b3e4f8"},
+    {file = "llvmlite-0.39.0-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:8b4cb4f433b48792f02ec4ab619b86b145689302a3088a3f3853f50df6c2559d"},
+    {file = "llvmlite-0.39.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:35db4122182cc5112912a3ec94a3c18eab9a990bd588bfda8445087c1b748563"},
+    {file = "llvmlite-0.39.0-cp310-cp310-win32.whl", hash = "sha256:c00bf7a8dc56b4b3618c65b67e75046410f751512871d9e23919cf1feb1007b2"},
+    {file = "llvmlite-0.39.0-cp310-cp310-win_amd64.whl", hash = "sha256:72bd2e5db9790344ec39cef77098486635853829ecb0e66e6fa516488ff6dd9e"},
+    {file = "llvmlite-0.39.0-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:53c7c608baffdcdc2213926f4e3600036d4048aed08d6209b9f76a5439e529d6"},
+    {file = "llvmlite-0.39.0-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c3bbd23e42593f85a842614d8ddb2b2943630e4c4c8418ea0d8cf1dce9f2fa7a"},
+    {file = "llvmlite-0.39.0-cp37-cp37m-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:d733eb9c02bb8b01373228a1339901b1e50be4581105239c6052b9573ddb9298"},
+    {file = "llvmlite-0.39.0-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f575fcb9bebe5bcbe20373c56ad3ebf63bae0e27d3c22c1a4dc27fa4666d0324"},
+    {file = "llvmlite-0.39.0-cp37-cp37m-win32.whl", hash = "sha256:5ca4ea962da6ec3b007bedab17065781803d71159b03435f24ce6845cf3d1c66"},
+    {file = "llvmlite-0.39.0-cp37-cp37m-win_amd64.whl", hash = "sha256:8e461608135859ac40e39211d9c63a1ce35176513f6b8be87efb554d4af3a388"},
+    {file = "llvmlite-0.39.0-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:62a11b8e9e5fc4783d94da45d94c5a047ce6ccc4c112ae5f764109e9405fcc2c"},
+    {file = "llvmlite-0.39.0-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:9272b7e344d12b36dafeb6911054eff32d2a9be7256a2866f0c09d08f945e17f"},
+    {file = "llvmlite-0.39.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:3df59a7c2b60764fb9eeaf9c442d757eca1f3e87298d4f88849203667528581e"},
+    {file = "llvmlite-0.39.0-cp38-cp38-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:4cfd6688efd0f551168dd8626f386464aef25663268a2400c0f6a089b97a73dc"},
+    {file = "llvmlite-0.39.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c7292b394956749e51ae3d51a2085932a0e3261108b35eda61d702c1b977102c"},
+    {file = "llvmlite-0.39.0-cp38-cp38-win32.whl", hash = "sha256:f8e9463a7d0152994b6f7d630012297bb160db237ad9ca8e75c8dceef7a747cf"},
+    {file = "llvmlite-0.39.0-cp38-cp38-win_amd64.whl", hash = "sha256:8d8149fdaab40ae48ea4ec816ae2ae5d36d664795e1b1dfb911fc2c62bc73184"},
+    {file = "llvmlite-0.39.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:0929e3c26bcafb53545c77bcf7020b943dcefcf8d7d3010f414384458f805cc1"},
+    {file = "llvmlite-0.39.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:56ea23c6bbcd25a7c050a26b6effe836a575a33183744cbc28fb21358b3801f8"},
+    {file = "llvmlite-0.39.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:2f82d605c5d6c8df96fe19bc3a61c934580e24cafa694cbf79cb227cdc0e426a"},
+    {file = "llvmlite-0.39.0-cp39-cp39-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:e7f7a7278ba6d75533be46abc3d9e242030ab017f0016dd081b55f821cc03be9"},
+    {file = "llvmlite-0.39.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:56ccfe736a12aef2e39450a22e4c027eee4f488c5786c81d0b18ff8a6cf52531"},
+    {file = "llvmlite-0.39.0-cp39-cp39-win32.whl", hash = "sha256:0706abf522dc510ddc818f5c9e1cdae521a1416d3c399bbfc4827813379f0164"},
+    {file = "llvmlite-0.39.0-cp39-cp39-win_amd64.whl", hash = "sha256:d4a8199263859b97f174035e39297e770617d3497fac44fe738f74ce9c51d22b"},
+    {file = "llvmlite-0.39.0.tar.gz", hash = "sha256:01098be54f1aa25e391cebba8ea71cd1533f8cd1f50e34c7dd7540c2560a93af"},
+]
+
+[[package]]
+name = "lxml"
+version = "4.9.2"
+description = "Powerful and Pythonic XML processing library combining libxml2/libxslt with the ElementTree API."
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, != 3.4.*"
+files = [
+    {file = "lxml-4.9.2-cp27-cp27m-macosx_10_15_x86_64.whl", hash = "sha256:76cf573e5a365e790396a5cc2b909812633409306c6531a6877c59061e42c4f2"},
+    {file = "lxml-4.9.2-cp27-cp27m-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:b1f42b6921d0e81b1bcb5e395bc091a70f41c4d4e55ba99c6da2b31626c44892"},
+    {file = "lxml-4.9.2-cp27-cp27m-manylinux_2_5_x86_64.manylinux1_x86_64.whl", hash = "sha256:9f102706d0ca011de571de32c3247c6476b55bb6bc65a20f682f000b07a4852a"},
+    {file = "lxml-4.9.2-cp27-cp27m-win32.whl", hash = "sha256:8d0b4612b66ff5d62d03bcaa043bb018f74dfea51184e53f067e6fdcba4bd8de"},
+    {file = "lxml-4.9.2-cp27-cp27m-win_amd64.whl", hash = "sha256:4c8f293f14abc8fd3e8e01c5bd86e6ed0b6ef71936ded5bf10fe7a5efefbaca3"},
+    {file = "lxml-4.9.2-cp27-cp27mu-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:2899456259589aa38bfb018c364d6ae7b53c5c22d8e27d0ec7609c2a1ff78b50"},
+    {file = "lxml-4.9.2-cp27-cp27mu-manylinux_2_5_x86_64.manylinux1_x86_64.whl", hash = "sha256:6749649eecd6a9871cae297bffa4ee76f90b4504a2a2ab528d9ebe912b101975"},
+    {file = "lxml-4.9.2-cp310-cp310-macosx_10_15_x86_64.whl", hash = "sha256:a08cff61517ee26cb56f1e949cca38caabe9ea9fbb4b1e10a805dc39844b7d5c"},
+    {file = "lxml-4.9.2-cp310-cp310-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_24_i686.whl", hash = "sha256:85cabf64adec449132e55616e7ca3e1000ab449d1d0f9d7f83146ed5bdcb6d8a"},
+    {file = "lxml-4.9.2-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.manylinux_2_24_aarch64.whl", hash = "sha256:8340225bd5e7a701c0fa98284c849c9b9fc9238abf53a0ebd90900f25d39a4e4"},
+    {file = "lxml-4.9.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_24_x86_64.whl", hash = "sha256:1ab8f1f932e8f82355e75dda5413a57612c6ea448069d4fb2e217e9a4bed13d4"},
+    {file = "lxml-4.9.2-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:699a9af7dffaf67deeae27b2112aa06b41c370d5e7633e0ee0aea2e0b6c211f7"},
+    {file = "lxml-4.9.2-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:b9cc34af337a97d470040f99ba4282f6e6bac88407d021688a5d585e44a23184"},
+    {file = "lxml-4.9.2-cp310-cp310-win32.whl", hash = "sha256:d02a5399126a53492415d4906ab0ad0375a5456cc05c3fc0fc4ca11771745cda"},
+    {file = "lxml-4.9.2-cp310-cp310-win_amd64.whl", hash = "sha256:a38486985ca49cfa574a507e7a2215c0c780fd1778bb6290c21193b7211702ab"},
+    {file = "lxml-4.9.2-cp311-cp311-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_24_i686.whl", hash = "sha256:c83203addf554215463b59f6399835201999b5e48019dc17f182ed5ad87205c9"},
+    {file = "lxml-4.9.2-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.manylinux_2_24_aarch64.whl", hash = "sha256:2a87fa548561d2f4643c99cd13131acb607ddabb70682dcf1dff5f71f781a4bf"},
+    {file = "lxml-4.9.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_24_x86_64.whl", hash = "sha256:d6b430a9938a5a5d85fc107d852262ddcd48602c120e3dbb02137c83d212b380"},
+    {file = "lxml-4.9.2-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:3efea981d956a6f7173b4659849f55081867cf897e719f57383698af6f618a92"},
+    {file = "lxml-4.9.2-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:df0623dcf9668ad0445e0558a21211d4e9a149ea8f5666917c8eeec515f0a6d1"},
+    {file = "lxml-4.9.2-cp311-cp311-win32.whl", hash = "sha256:da248f93f0418a9e9d94b0080d7ebc407a9a5e6d0b57bb30db9b5cc28de1ad33"},
+    {file = "lxml-4.9.2-cp311-cp311-win_amd64.whl", hash = "sha256:3818b8e2c4b5148567e1b09ce739006acfaa44ce3156f8cbbc11062994b8e8dd"},
+    {file = "lxml-4.9.2-cp35-cp35m-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:ca989b91cf3a3ba28930a9fc1e9aeafc2a395448641df1f387a2d394638943b0"},
+    {file = "lxml-4.9.2-cp35-cp35m-manylinux_2_5_x86_64.manylinux1_x86_64.whl", hash = "sha256:822068f85e12a6e292803e112ab876bc03ed1f03dddb80154c395f891ca6b31e"},
+    {file = "lxml-4.9.2-cp35-cp35m-win32.whl", hash = "sha256:be7292c55101e22f2a3d4d8913944cbea71eea90792bf914add27454a13905df"},
+    {file = "lxml-4.9.2-cp35-cp35m-win_amd64.whl", hash = "sha256:998c7c41910666d2976928c38ea96a70d1aa43be6fe502f21a651e17483a43c5"},
+    {file = "lxml-4.9.2-cp36-cp36m-macosx_10_15_x86_64.whl", hash = "sha256:b26a29f0b7fc6f0897f043ca366142d2b609dc60756ee6e4e90b5f762c6adc53"},
+    {file = "lxml-4.9.2-cp36-cp36m-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_24_i686.whl", hash = "sha256:ab323679b8b3030000f2be63e22cdeea5b47ee0abd2d6a1dc0c8103ddaa56cd7"},
+    {file = "lxml-4.9.2-cp36-cp36m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:689bb688a1db722485e4610a503e3e9210dcc20c520b45ac8f7533c837be76fe"},
+    {file = "lxml-4.9.2-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_24_x86_64.whl", hash = "sha256:f49e52d174375a7def9915c9f06ec4e569d235ad428f70751765f48d5926678c"},
+    {file = "lxml-4.9.2-cp36-cp36m-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:36c3c175d34652a35475a73762b545f4527aec044910a651d2bf50de9c3352b1"},
+    {file = "lxml-4.9.2-cp36-cp36m-manylinux_2_5_x86_64.manylinux1_x86_64.whl", hash = "sha256:a35f8b7fa99f90dd2f5dc5a9fa12332642f087a7641289ca6c40d6e1a2637d8e"},
+    {file = "lxml-4.9.2-cp36-cp36m-musllinux_1_1_aarch64.whl", hash = "sha256:58bfa3aa19ca4c0f28c5dde0ff56c520fbac6f0daf4fac66ed4c8d2fb7f22e74"},
+    {file = "lxml-4.9.2-cp36-cp36m-musllinux_1_1_x86_64.whl", hash = "sha256:bc718cd47b765e790eecb74d044cc8d37d58562f6c314ee9484df26276d36a38"},
+    {file = "lxml-4.9.2-cp36-cp36m-win32.whl", hash = "sha256:d5bf6545cd27aaa8a13033ce56354ed9e25ab0e4ac3b5392b763d8d04b08e0c5"},
+    {file = "lxml-4.9.2-cp36-cp36m-win_amd64.whl", hash = "sha256:3ab9fa9d6dc2a7f29d7affdf3edebf6ece6fb28a6d80b14c3b2fb9d39b9322c3"},
+    {file = "lxml-4.9.2-cp37-cp37m-macosx_10_15_x86_64.whl", hash = "sha256:05ca3f6abf5cf78fe053da9b1166e062ade3fa5d4f92b4ed688127ea7d7b1d03"},
+    {file = "lxml-4.9.2-cp37-cp37m-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_24_i686.whl", hash = "sha256:a5da296eb617d18e497bcf0a5c528f5d3b18dadb3619fbdadf4ed2356ef8d941"},
+    {file = "lxml-4.9.2-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.manylinux_2_24_aarch64.whl", hash = "sha256:04876580c050a8c5341d706dd464ff04fd597095cc8c023252566a8826505726"},
+    {file = "lxml-4.9.2-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_24_x86_64.whl", hash = "sha256:c9ec3eaf616d67db0764b3bb983962b4f385a1f08304fd30c7283954e6a7869b"},
+    {file = "lxml-4.9.2-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:2a29ba94d065945944016b6b74e538bdb1751a1db6ffb80c9d3c2e40d6fa9894"},
+    {file = "lxml-4.9.2-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.whl", hash = "sha256:a82d05da00a58b8e4c0008edbc8a4b6ec5a4bc1e2ee0fb6ed157cf634ed7fa45"},
+    {file = "lxml-4.9.2-cp37-cp37m-musllinux_1_1_aarch64.whl", hash = "sha256:223f4232855ade399bd409331e6ca70fb5578efef22cf4069a6090acc0f53c0e"},
+    {file = "lxml-4.9.2-cp37-cp37m-musllinux_1_1_x86_64.whl", hash = "sha256:d17bc7c2ccf49c478c5bdd447594e82692c74222698cfc9b5daae7ae7e90743b"},
+    {file = "lxml-4.9.2-cp37-cp37m-win32.whl", hash = "sha256:b64d891da92e232c36976c80ed7ebb383e3f148489796d8d31a5b6a677825efe"},
+    {file = "lxml-4.9.2-cp37-cp37m-win_amd64.whl", hash = "sha256:a0a336d6d3e8b234a3aae3c674873d8f0e720b76bc1d9416866c41cd9500ffb9"},
+    {file = "lxml-4.9.2-cp38-cp38-macosx_10_15_x86_64.whl", hash = "sha256:da4dd7c9c50c059aba52b3524f84d7de956f7fef88f0bafcf4ad7dde94a064e8"},
+    {file = "lxml-4.9.2-cp38-cp38-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_24_i686.whl", hash = "sha256:821b7f59b99551c69c85a6039c65b75f5683bdc63270fec660f75da67469ca24"},
+    {file = "lxml-4.9.2-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.manylinux_2_24_aarch64.whl", hash = "sha256:e5168986b90a8d1f2f9dc1b841467c74221bd752537b99761a93d2d981e04889"},
+    {file = "lxml-4.9.2-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_24_x86_64.whl", hash = "sha256:8e20cb5a47247e383cf4ff523205060991021233ebd6f924bca927fcf25cf86f"},
+    {file = "lxml-4.9.2-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:13598ecfbd2e86ea7ae45ec28a2a54fb87ee9b9fdb0f6d343297d8e548392c03"},
+    {file = "lxml-4.9.2-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.whl", hash = "sha256:880bbbcbe2fca64e2f4d8e04db47bcdf504936fa2b33933efd945e1b429bea8c"},
+    {file = "lxml-4.9.2-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:7d2278d59425777cfcb19735018d897ca8303abe67cc735f9f97177ceff8027f"},
+    {file = "lxml-4.9.2-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:5344a43228767f53a9df6e5b253f8cdca7dfc7b7aeae52551958192f56d98457"},
+    {file = "lxml-4.9.2-cp38-cp38-win32.whl", hash = "sha256:925073b2fe14ab9b87e73f9a5fde6ce6392da430f3004d8b72cc86f746f5163b"},
+    {file = "lxml-4.9.2-cp38-cp38-win_amd64.whl", hash = "sha256:9b22c5c66f67ae00c0199f6055705bc3eb3fcb08d03d2ec4059a2b1b25ed48d7"},
+    {file = "lxml-4.9.2-cp39-cp39-macosx_10_15_x86_64.whl", hash = "sha256:5f50a1c177e2fa3ee0667a5ab79fdc6b23086bc8b589d90b93b4bd17eb0e64d1"},
+    {file = "lxml-4.9.2-cp39-cp39-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_24_i686.whl", hash = "sha256:090c6543d3696cbe15b4ac6e175e576bcc3f1ccfbba970061b7300b0c15a2140"},
+    {file = "lxml-4.9.2-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.manylinux_2_24_aarch64.whl", hash = "sha256:63da2ccc0857c311d764e7d3d90f429c252e83b52d1f8f1d1fe55be26827d1f4"},
+    {file = "lxml-4.9.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_24_x86_64.whl", hash = "sha256:5b4545b8a40478183ac06c073e81a5ce4cf01bf1734962577cf2bb569a5b3bbf"},
+    {file = "lxml-4.9.2-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:2e430cd2824f05f2d4f687701144556646bae8f249fd60aa1e4c768ba7018947"},
+    {file = "lxml-4.9.2-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.whl", hash = "sha256:6804daeb7ef69e7b36f76caddb85cccd63d0c56dedb47555d2fc969e2af6a1a5"},
+    {file = "lxml-4.9.2-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:a6e441a86553c310258aca15d1c05903aaf4965b23f3bc2d55f200804e005ee5"},
+    {file = "lxml-4.9.2-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:ca34efc80a29351897e18888c71c6aca4a359247c87e0b1c7ada14f0ab0c0fb2"},
+    {file = "lxml-4.9.2-cp39-cp39-win32.whl", hash = "sha256:6b418afe5df18233fc6b6093deb82a32895b6bb0b1155c2cdb05203f583053f1"},
+    {file = "lxml-4.9.2-cp39-cp39-win_amd64.whl", hash = "sha256:f1496ea22ca2c830cbcbd473de8f114a320da308438ae65abad6bab7867fe38f"},
+    {file = "lxml-4.9.2-pp37-pypy37_pp73-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_24_i686.whl", hash = "sha256:b264171e3143d842ded311b7dccd46ff9ef34247129ff5bf5066123c55c2431c"},
+    {file = "lxml-4.9.2-pp37-pypy37_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_24_x86_64.whl", hash = "sha256:0dc313ef231edf866912e9d8f5a042ddab56c752619e92dfd3a2c277e6a7299a"},
+    {file = "lxml-4.9.2-pp38-pypy38_pp73-macosx_10_15_x86_64.whl", hash = "sha256:16efd54337136e8cd72fb9485c368d91d77a47ee2d42b057564aae201257d419"},
+    {file = "lxml-4.9.2-pp38-pypy38_pp73-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_24_i686.whl", hash = "sha256:0f2b1e0d79180f344ff9f321327b005ca043a50ece8713de61d1cb383fb8ac05"},
+    {file = "lxml-4.9.2-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_24_x86_64.whl", hash = "sha256:7b770ed79542ed52c519119473898198761d78beb24b107acf3ad65deae61f1f"},
+    {file = "lxml-4.9.2-pp38-pypy38_pp73-win_amd64.whl", hash = "sha256:efa29c2fe6b4fdd32e8ef81c1528506895eca86e1d8c4657fda04c9b3786ddf9"},
+    {file = "lxml-4.9.2-pp39-pypy39_pp73-macosx_10_15_x86_64.whl", hash = "sha256:7e91ee82f4199af8c43d8158024cbdff3d931df350252288f0d4ce656df7f3b5"},
+    {file = "lxml-4.9.2-pp39-pypy39_pp73-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_24_i686.whl", hash = "sha256:b23e19989c355ca854276178a0463951a653309fb8e57ce674497f2d9f208746"},
+    {file = "lxml-4.9.2-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_24_x86_64.whl", hash = "sha256:01d36c05f4afb8f7c20fd9ed5badca32a2029b93b1750f571ccc0b142531caf7"},
+    {file = "lxml-4.9.2-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:7b515674acfdcadb0eb5d00d8a709868173acece5cb0be3dd165950cbfdf5409"},
+    {file = "lxml-4.9.2.tar.gz", hash = "sha256:2455cfaeb7ac70338b3257f41e21f0724f4b5b0c0e7702da67ee6c3640835b67"},
+]
+
+[package.extras]
+cssselect = ["cssselect (>=0.7)"]
+html5 = ["html5lib"]
+htmlsoup = ["BeautifulSoup4"]
+source = ["Cython (>=0.29.7)"]
+
+[[package]]
+name = "markdown"
+version = "3.4.3"
+description = "Python implementation of John Gruber's Markdown."
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "Markdown-3.4.3-py3-none-any.whl", hash = "sha256:065fd4df22da73a625f14890dd77eb8040edcbd68794bcd35943be14490608b2"},
+    {file = "Markdown-3.4.3.tar.gz", hash = "sha256:8bf101198e004dc93e84a12a7395e31aac6a9c9942848ae1d99b9d72cf9b3520"},
+]
+
+[package.dependencies]
+importlib-metadata = {version = ">=4.4", markers = "python_version < \"3.10\""}
+
+[package.extras]
+testing = ["coverage", "pyyaml"]
+
+[[package]]
+name = "markdown-it-py"
+version = "2.2.0"
+description = "Python port of markdown-it. Markdown parsing, done right!"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "markdown-it-py-2.2.0.tar.gz", hash = "sha256:7c9a5e412688bc771c67432cbfebcdd686c93ce6484913dccf06cb5a0bea35a1"},
+    {file = "markdown_it_py-2.2.0-py3-none-any.whl", hash = "sha256:5a35f8d1870171d9acc47b99612dc146129b631baf04970128b568f190d0cc30"},
+]
+
+[package.dependencies]
+linkify-it-py = {version = ">=1,<3", optional = true, markers = "extra == \"linkify\""}
+mdurl = ">=0.1,<1.0"
+
+[package.extras]
+benchmarking = ["psutil", "pytest", "pytest-benchmark"]
+code-style = ["pre-commit (>=3.0,<4.0)"]
+compare = ["commonmark (>=0.9,<1.0)", "markdown (>=3.4,<4.0)", "mistletoe (>=1.0,<2.0)", "mistune (>=2.0,<3.0)", "panflute (>=2.3,<3.0)"]
+linkify = ["linkify-it-py (>=1,<3)"]
+plugins = ["mdit-py-plugins"]
+profiling = ["gprof2dot"]
+rtd = ["attrs", "myst-parser", "pyyaml", "sphinx", "sphinx-copybutton", "sphinx-design", "sphinx_book_theme"]
+testing = ["coverage", "pytest", "pytest-cov", "pytest-regressions"]
+
+[[package]]
+name = "markupsafe"
+version = "2.1.2"
+description = "Safely add untrusted strings to HTML/XML markup."
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "MarkupSafe-2.1.2-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:665a36ae6f8f20a4676b53224e33d456a6f5a72657d9c83c2aa00765072f31f7"},
+    {file = "MarkupSafe-2.1.2-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:340bea174e9761308703ae988e982005aedf427de816d1afe98147668cc03036"},
+    {file = "MarkupSafe-2.1.2-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:22152d00bf4a9c7c83960521fc558f55a1adbc0631fbb00a9471e097b19d72e1"},
+    {file = "MarkupSafe-2.1.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:28057e985dace2f478e042eaa15606c7efccb700797660629da387eb289b9323"},
+    {file = "MarkupSafe-2.1.2-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:ca244fa73f50a800cf8c3ebf7fd93149ec37f5cb9596aa8873ae2c1d23498601"},
+    {file = "MarkupSafe-2.1.2-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:d9d971ec1e79906046aa3ca266de79eac42f1dbf3612a05dc9368125952bd1a1"},
+    {file = "MarkupSafe-2.1.2-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:7e007132af78ea9df29495dbf7b5824cb71648d7133cf7848a2a5dd00d36f9ff"},
+    {file = "MarkupSafe-2.1.2-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:7313ce6a199651c4ed9d7e4cfb4aa56fe923b1adf9af3b420ee14e6d9a73df65"},
+    {file = "MarkupSafe-2.1.2-cp310-cp310-win32.whl", hash = "sha256:c4a549890a45f57f1ebf99c067a4ad0cb423a05544accaf2b065246827ed9603"},
+    {file = "MarkupSafe-2.1.2-cp310-cp310-win_amd64.whl", hash = "sha256:835fb5e38fd89328e9c81067fd642b3593c33e1e17e2fdbf77f5676abb14a156"},
+    {file = "MarkupSafe-2.1.2-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:2ec4f2d48ae59bbb9d1f9d7efb9236ab81429a764dedca114f5fdabbc3788013"},
+    {file = "MarkupSafe-2.1.2-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:608e7073dfa9e38a85d38474c082d4281f4ce276ac0010224eaba11e929dd53a"},
+    {file = "MarkupSafe-2.1.2-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:65608c35bfb8a76763f37036547f7adfd09270fbdbf96608be2bead319728fcd"},
+    {file = "MarkupSafe-2.1.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f2bfb563d0211ce16b63c7cb9395d2c682a23187f54c3d79bfec33e6705473c6"},
+    {file = "MarkupSafe-2.1.2-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:da25303d91526aac3672ee6d49a2f3db2d9502a4a60b55519feb1a4c7714e07d"},
+    {file = "MarkupSafe-2.1.2-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:9cad97ab29dfc3f0249b483412c85c8ef4766d96cdf9dcf5a1e3caa3f3661cf1"},
+    {file = "MarkupSafe-2.1.2-cp311-cp311-musllinux_1_1_i686.whl", hash = "sha256:085fd3201e7b12809f9e6e9bc1e5c96a368c8523fad5afb02afe3c051ae4afcc"},
+    {file = "MarkupSafe-2.1.2-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:1bea30e9bf331f3fef67e0a3877b2288593c98a21ccb2cf29b74c581a4eb3af0"},
+    {file = "MarkupSafe-2.1.2-cp311-cp311-win32.whl", hash = "sha256:7df70907e00c970c60b9ef2938d894a9381f38e6b9db73c5be35e59d92e06625"},
+    {file = "MarkupSafe-2.1.2-cp311-cp311-win_amd64.whl", hash = "sha256:e55e40ff0cc8cc5c07996915ad367fa47da6b3fc091fdadca7f5403239c5fec3"},
+    {file = "MarkupSafe-2.1.2-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:a6e40afa7f45939ca356f348c8e23048e02cb109ced1eb8420961b2f40fb373a"},
+    {file = "MarkupSafe-2.1.2-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:cf877ab4ed6e302ec1d04952ca358b381a882fbd9d1b07cccbfd61783561f98a"},
+    {file = "MarkupSafe-2.1.2-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:63ba06c9941e46fa389d389644e2d8225e0e3e5ebcc4ff1ea8506dce646f8c8a"},
+    {file = "MarkupSafe-2.1.2-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:f1cd098434e83e656abf198f103a8207a8187c0fc110306691a2e94a78d0abb2"},
+    {file = "MarkupSafe-2.1.2-cp37-cp37m-musllinux_1_1_aarch64.whl", hash = "sha256:55f44b440d491028addb3b88f72207d71eeebfb7b5dbf0643f7c023ae1fba619"},
+    {file = "MarkupSafe-2.1.2-cp37-cp37m-musllinux_1_1_i686.whl", hash = "sha256:a6f2fcca746e8d5910e18782f976489939d54a91f9411c32051b4aab2bd7c513"},
+    {file = "MarkupSafe-2.1.2-cp37-cp37m-musllinux_1_1_x86_64.whl", hash = "sha256:0b462104ba25f1ac006fdab8b6a01ebbfbce9ed37fd37fd4acd70c67c973e460"},
+    {file = "MarkupSafe-2.1.2-cp37-cp37m-win32.whl", hash = "sha256:7668b52e102d0ed87cb082380a7e2e1e78737ddecdde129acadb0eccc5423859"},
+    {file = "MarkupSafe-2.1.2-cp37-cp37m-win_amd64.whl", hash = "sha256:6d6607f98fcf17e534162f0709aaad3ab7a96032723d8ac8750ffe17ae5a0666"},
+    {file = "MarkupSafe-2.1.2-cp38-cp38-macosx_10_9_universal2.whl", hash = "sha256:a806db027852538d2ad7555b203300173dd1b77ba116de92da9afbc3a3be3eed"},
+    {file = "MarkupSafe-2.1.2-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:a4abaec6ca3ad8660690236d11bfe28dfd707778e2442b45addd2f086d6ef094"},
+    {file = "MarkupSafe-2.1.2-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f03a532d7dee1bed20bc4884194a16160a2de9ffc6354b3878ec9682bb623c54"},
+    {file = "MarkupSafe-2.1.2-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4cf06cdc1dda95223e9d2d3c58d3b178aa5dacb35ee7e3bbac10e4e1faacb419"},
+    {file = "MarkupSafe-2.1.2-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:22731d79ed2eb25059ae3df1dfc9cb1546691cc41f4e3130fe6bfbc3ecbbecfa"},
+    {file = "MarkupSafe-2.1.2-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:f8ffb705ffcf5ddd0e80b65ddf7bed7ee4f5a441ea7d3419e861a12eaf41af58"},
+    {file = "MarkupSafe-2.1.2-cp38-cp38-musllinux_1_1_i686.whl", hash = "sha256:8db032bf0ce9022a8e41a22598eefc802314e81b879ae093f36ce9ddf39ab1ba"},
+    {file = "MarkupSafe-2.1.2-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:2298c859cfc5463f1b64bd55cb3e602528db6fa0f3cfd568d3605c50678f8f03"},
+    {file = "MarkupSafe-2.1.2-cp38-cp38-win32.whl", hash = "sha256:50c42830a633fa0cf9e7d27664637532791bfc31c731a87b202d2d8ac40c3ea2"},
+    {file = "MarkupSafe-2.1.2-cp38-cp38-win_amd64.whl", hash = "sha256:bb06feb762bade6bf3c8b844462274db0c76acc95c52abe8dbed28ae3d44a147"},
+    {file = "MarkupSafe-2.1.2-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:99625a92da8229df6d44335e6fcc558a5037dd0a760e11d84be2260e6f37002f"},
+    {file = "MarkupSafe-2.1.2-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:8bca7e26c1dd751236cfb0c6c72d4ad61d986e9a41bbf76cb445f69488b2a2bd"},
+    {file = "MarkupSafe-2.1.2-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:40627dcf047dadb22cd25ea7ecfe9cbf3bbbad0482ee5920b582f3809c97654f"},
+    {file = "MarkupSafe-2.1.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:40dfd3fefbef579ee058f139733ac336312663c6706d1163b82b3003fb1925c4"},
+    {file = "MarkupSafe-2.1.2-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:090376d812fb6ac5f171e5938e82e7f2d7adc2b629101cec0db8b267815c85e2"},
+    {file = "MarkupSafe-2.1.2-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:2e7821bffe00aa6bd07a23913b7f4e01328c3d5cc0b40b36c0bd81d362faeb65"},
+    {file = "MarkupSafe-2.1.2-cp39-cp39-musllinux_1_1_i686.whl", hash = "sha256:c0a33bc9f02c2b17c3ea382f91b4db0e6cde90b63b296422a939886a7a80de1c"},
+    {file = "MarkupSafe-2.1.2-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:b8526c6d437855442cdd3d87eede9c425c4445ea011ca38d937db299382e6fa3"},
+    {file = "MarkupSafe-2.1.2-cp39-cp39-win32.whl", hash = "sha256:137678c63c977754abe9086a3ec011e8fd985ab90631145dfb9294ad09c102a7"},
+    {file = "MarkupSafe-2.1.2-cp39-cp39-win_amd64.whl", hash = "sha256:0576fe974b40a400449768941d5d0858cc624e3249dfd1e0c33674e5c7ca7aed"},
+    {file = "MarkupSafe-2.1.2.tar.gz", hash = "sha256:abcabc8c2b26036d62d4c746381a6f7cf60aafcc653198ad678306986b09450d"},
+]
+
+[[package]]
+name = "matplotlib"
+version = "3.7.1"
+description = "Python plotting package"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "matplotlib-3.7.1-cp310-cp310-macosx_10_12_universal2.whl", hash = "sha256:95cbc13c1fc6844ab8812a525bbc237fa1470863ff3dace7352e910519e194b1"},
+    {file = "matplotlib-3.7.1-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:08308bae9e91aca1ec6fd6dda66237eef9f6294ddb17f0d0b3c863169bf82353"},
+    {file = "matplotlib-3.7.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:544764ba51900da4639c0f983b323d288f94f65f4024dc40ecb1542d74dc0500"},
+    {file = "matplotlib-3.7.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:56d94989191de3fcc4e002f93f7f1be5da476385dde410ddafbb70686acf00ea"},
+    {file = "matplotlib-3.7.1-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:e99bc9e65901bb9a7ce5e7bb24af03675cbd7c70b30ac670aa263240635999a4"},
+    {file = "matplotlib-3.7.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:eb7d248c34a341cd4c31a06fd34d64306624c8cd8d0def7abb08792a5abfd556"},
+    {file = "matplotlib-3.7.1-cp310-cp310-win32.whl", hash = "sha256:ce463ce590f3825b52e9fe5c19a3c6a69fd7675a39d589e8b5fbe772272b3a24"},
+    {file = "matplotlib-3.7.1-cp310-cp310-win_amd64.whl", hash = "sha256:3d7bc90727351fb841e4d8ae620d2d86d8ed92b50473cd2b42ce9186104ecbba"},
+    {file = "matplotlib-3.7.1-cp311-cp311-macosx_10_12_universal2.whl", hash = "sha256:770a205966d641627fd5cf9d3cb4b6280a716522cd36b8b284a8eb1581310f61"},
+    {file = "matplotlib-3.7.1-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:f67bfdb83a8232cb7a92b869f9355d677bce24485c460b19d01970b64b2ed476"},
+    {file = "matplotlib-3.7.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:2bf092f9210e105f414a043b92af583c98f50050559616930d884387d0772aba"},
+    {file = "matplotlib-3.7.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:89768d84187f31717349c6bfadc0e0d8c321e8eb34522acec8a67b1236a66332"},
+    {file = "matplotlib-3.7.1-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:83111e6388dec67822e2534e13b243cc644c7494a4bb60584edbff91585a83c6"},
+    {file = "matplotlib-3.7.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a867bf73a7eb808ef2afbca03bcdb785dae09595fbe550e1bab0cd023eba3de0"},
+    {file = "matplotlib-3.7.1-cp311-cp311-win32.whl", hash = "sha256:fbdeeb58c0cf0595efe89c05c224e0a502d1aa6a8696e68a73c3efc6bc354304"},
+    {file = "matplotlib-3.7.1-cp311-cp311-win_amd64.whl", hash = "sha256:c0bd19c72ae53e6ab979f0ac6a3fafceb02d2ecafa023c5cca47acd934d10be7"},
+    {file = "matplotlib-3.7.1-cp38-cp38-macosx_10_12_universal2.whl", hash = "sha256:6eb88d87cb2c49af00d3bbc33a003f89fd9f78d318848da029383bfc08ecfbfb"},
+    {file = "matplotlib-3.7.1-cp38-cp38-macosx_10_12_x86_64.whl", hash = "sha256:cf0e4f727534b7b1457898c4f4ae838af1ef87c359b76dcd5330fa31893a3ac7"},
+    {file = "matplotlib-3.7.1-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:46a561d23b91f30bccfd25429c3c706afe7d73a5cc64ef2dfaf2b2ac47c1a5dc"},
+    {file = "matplotlib-3.7.1-cp38-cp38-manylinux_2_12_i686.manylinux2010_i686.whl", hash = "sha256:8704726d33e9aa8a6d5215044b8d00804561971163563e6e6591f9dcf64340cc"},
+    {file = "matplotlib-3.7.1-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:4cf327e98ecf08fcbb82685acaf1939d3338548620ab8dfa02828706402c34de"},
+    {file = "matplotlib-3.7.1-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:617f14ae9d53292ece33f45cba8503494ee199a75b44de7717964f70637a36aa"},
+    {file = "matplotlib-3.7.1-cp38-cp38-win32.whl", hash = "sha256:7c9a4b2da6fac77bcc41b1ea95fadb314e92508bf5493ceff058e727e7ecf5b0"},
+    {file = "matplotlib-3.7.1-cp38-cp38-win_amd64.whl", hash = "sha256:14645aad967684e92fc349493fa10c08a6da514b3d03a5931a1bac26e6792bd1"},
+    {file = "matplotlib-3.7.1-cp39-cp39-macosx_10_12_universal2.whl", hash = "sha256:81a6b377ea444336538638d31fdb39af6be1a043ca5e343fe18d0f17e098770b"},
+    {file = "matplotlib-3.7.1-cp39-cp39-macosx_10_12_x86_64.whl", hash = "sha256:28506a03bd7f3fe59cd3cd4ceb2a8d8a2b1db41afede01f66c42561b9be7b4b7"},
+    {file = "matplotlib-3.7.1-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:8c587963b85ce41e0a8af53b9b2de8dddbf5ece4c34553f7bd9d066148dc719c"},
+    {file = "matplotlib-3.7.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:8bf26ade3ff0f27668989d98c8435ce9327d24cffb7f07d24ef609e33d582439"},
+    {file = "matplotlib-3.7.1-cp39-cp39-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:def58098f96a05f90af7e92fd127d21a287068202aa43b2a93476170ebd99e87"},
+    {file = "matplotlib-3.7.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f883a22a56a84dba3b588696a2b8a1ab0d2c3d41be53264115c71b0a942d8fdb"},
+    {file = "matplotlib-3.7.1-cp39-cp39-win32.whl", hash = "sha256:4f99e1b234c30c1e9714610eb0c6d2f11809c9c78c984a613ae539ea2ad2eb4b"},
+    {file = "matplotlib-3.7.1-cp39-cp39-win_amd64.whl", hash = "sha256:3ba2af245e36990facf67fde840a760128ddd71210b2ab6406e640188d69d136"},
+    {file = "matplotlib-3.7.1-pp38-pypy38_pp73-macosx_10_12_x86_64.whl", hash = "sha256:3032884084f541163f295db8a6536e0abb0db464008fadca6c98aaf84ccf4717"},
+    {file = "matplotlib-3.7.1-pp38-pypy38_pp73-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:3a2cb34336110e0ed8bb4f650e817eed61fa064acbefeb3591f1b33e3a84fd96"},
+    {file = "matplotlib-3.7.1-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b867e2f952ed592237a1828f027d332d8ee219ad722345b79a001f49df0936eb"},
+    {file = "matplotlib-3.7.1-pp38-pypy38_pp73-win_amd64.whl", hash = "sha256:57bfb8c8ea253be947ccb2bc2d1bb3862c2bccc662ad1b4626e1f5e004557042"},
+    {file = "matplotlib-3.7.1-pp39-pypy39_pp73-macosx_10_12_x86_64.whl", hash = "sha256:438196cdf5dc8d39b50a45cb6e3f6274edbcf2254f85fa9b895bf85851c3a613"},
+    {file = "matplotlib-3.7.1-pp39-pypy39_pp73-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:21e9cff1a58d42e74d01153360de92b326708fb205250150018a52c70f43c290"},
+    {file = "matplotlib-3.7.1-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:75d4725d70b7c03e082bbb8a34639ede17f333d7247f56caceb3801cb6ff703d"},
+    {file = "matplotlib-3.7.1-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:97cc368a7268141afb5690760921765ed34867ffb9655dd325ed207af85c7529"},
+    {file = "matplotlib-3.7.1.tar.gz", hash = "sha256:7b73305f25eab4541bd7ee0b96d87e53ae9c9f1823be5659b806cd85786fe882"},
+]
+
+[package.dependencies]
+contourpy = ">=1.0.1"
+cycler = ">=0.10"
+fonttools = ">=4.22.0"
+importlib-resources = {version = ">=3.2.0", markers = "python_version < \"3.10\""}
+kiwisolver = ">=1.0.1"
+numpy = ">=1.20"
+packaging = ">=20.0"
+pillow = ">=6.2.0"
+pyparsing = ">=2.3.1"
+python-dateutil = ">=2.7"
+
+[[package]]
+name = "matplotlib-inline"
+version = "0.1.6"
+description = "Inline Matplotlib backend for Jupyter"
+optional = false
+python-versions = ">=3.5"
+files = [
+    {file = "matplotlib-inline-0.1.6.tar.gz", hash = "sha256:f887e5f10ba98e8d2b150ddcf4702c1e5f8b3a20005eb0f74bfdbd360ee6f304"},
+    {file = "matplotlib_inline-0.1.6-py3-none-any.whl", hash = "sha256:f1f41aab5328aa5aaea9b16d083b128102f8712542f819fe7e6a420ff581b311"},
+]
+
+[package.dependencies]
+traitlets = "*"
+
+[[package]]
+name = "mdit-py-plugins"
+version = "0.3.3"
+description = "Collection of plugins for markdown-it-py"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "mdit-py-plugins-0.3.3.tar.gz", hash = "sha256:5cfd7e7ac582a594e23ba6546a2f406e94e42eb33ae596d0734781261c251260"},
+    {file = "mdit_py_plugins-0.3.3-py3-none-any.whl", hash = "sha256:36d08a29def19ec43acdcd8ba471d3ebab132e7879d442760d963f19913e04b9"},
+]
+
+[package.dependencies]
+markdown-it-py = ">=1.0.0,<3.0.0"
+
+[package.extras]
+code-style = ["pre-commit"]
+rtd = ["attrs", "myst-parser (>=0.16.1,<0.17.0)", "sphinx-book-theme (>=0.1.0,<0.2.0)"]
+testing = ["coverage", "pytest", "pytest-cov", "pytest-regressions"]
+
+[[package]]
+name = "mdurl"
+version = "0.1.2"
+description = "Markdown URL utilities"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "mdurl-0.1.2-py3-none-any.whl", hash = "sha256:84008a41e51615a49fc9966191ff91509e3c40b939176e643fd50a5c2196b8f8"},
+    {file = "mdurl-0.1.2.tar.gz", hash = "sha256:bb413d29f5eea38f31dd4754dd7377d4465116fb207585f97bf925588687c1ba"},
+]
+
+[[package]]
+name = "mpmath"
+version = "1.3.0"
+description = "Python library for arbitrary-precision floating-point arithmetic"
+optional = false
+python-versions = "*"
+files = [
+    {file = "mpmath-1.3.0-py3-none-any.whl", hash = "sha256:a0b2b9fe80bbcd81a6647ff13108738cfb482d481d826cc0e02f5b35e5c88d2c"},
+    {file = "mpmath-1.3.0.tar.gz", hash = "sha256:7a28eb2a9774d00c7bc92411c19a89209d5da7c4c9a9e227be8330a23a25b91f"},
+]
+
+[package.extras]
+develop = ["codecov", "pycodestyle", "pytest (>=4.6)", "pytest-cov", "wheel"]
+docs = ["sphinx"]
+gmpy = ["gmpy2 (>=2.1.0a4)"]
+tests = ["pytest (>=4.6)"]
+
+[[package]]
+name = "multidict"
+version = "6.0.4"
+description = "multidict implementation"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "multidict-6.0.4-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:0b1a97283e0c85772d613878028fec909f003993e1007eafa715b24b377cb9b8"},
+    {file = "multidict-6.0.4-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:eeb6dcc05e911516ae3d1f207d4b0520d07f54484c49dfc294d6e7d63b734171"},
+    {file = "multidict-6.0.4-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:d6d635d5209b82a3492508cf5b365f3446afb65ae7ebd755e70e18f287b0adf7"},
+    {file = "multidict-6.0.4-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c048099e4c9e9d615545e2001d3d8a4380bd403e1a0578734e0d31703d1b0c0b"},
+    {file = "multidict-6.0.4-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:ea20853c6dbbb53ed34cb4d080382169b6f4554d394015f1bef35e881bf83547"},
+    {file = "multidict-6.0.4-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:16d232d4e5396c2efbbf4f6d4df89bfa905eb0d4dc5b3549d872ab898451f569"},
+    {file = "multidict-6.0.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:36c63aaa167f6c6b04ef2c85704e93af16c11d20de1d133e39de6a0e84582a93"},
+    {file = "multidict-6.0.4-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:64bdf1086b6043bf519869678f5f2757f473dee970d7abf6da91ec00acb9cb98"},
+    {file = "multidict-6.0.4-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:43644e38f42e3af682690876cff722d301ac585c5b9e1eacc013b7a3f7b696a0"},
+    {file = "multidict-6.0.4-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:7582a1d1030e15422262de9f58711774e02fa80df0d1578995c76214f6954988"},
+    {file = "multidict-6.0.4-cp310-cp310-musllinux_1_1_ppc64le.whl", hash = "sha256:ddff9c4e225a63a5afab9dd15590432c22e8057e1a9a13d28ed128ecf047bbdc"},
+    {file = "multidict-6.0.4-cp310-cp310-musllinux_1_1_s390x.whl", hash = "sha256:ee2a1ece51b9b9e7752e742cfb661d2a29e7bcdba2d27e66e28a99f1890e4fa0"},
+    {file = "multidict-6.0.4-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:a2e4369eb3d47d2034032a26c7a80fcb21a2cb22e1173d761a162f11e562caa5"},
+    {file = "multidict-6.0.4-cp310-cp310-win32.whl", hash = "sha256:574b7eae1ab267e5f8285f0fe881f17efe4b98c39a40858247720935b893bba8"},
+    {file = "multidict-6.0.4-cp310-cp310-win_amd64.whl", hash = "sha256:4dcbb0906e38440fa3e325df2359ac6cb043df8e58c965bb45f4e406ecb162cc"},
+    {file = "multidict-6.0.4-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:0dfad7a5a1e39c53ed00d2dd0c2e36aed4650936dc18fd9a1826a5ae1cad6f03"},
+    {file = "multidict-6.0.4-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:64da238a09d6039e3bd39bb3aee9c21a5e34f28bfa5aa22518581f910ff94af3"},
+    {file = "multidict-6.0.4-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:ff959bee35038c4624250473988b24f846cbeb2c6639de3602c073f10410ceba"},
+    {file = "multidict-6.0.4-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:01a3a55bd90018c9c080fbb0b9f4891db37d148a0a18722b42f94694f8b6d4c9"},
+    {file = "multidict-6.0.4-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:c5cb09abb18c1ea940fb99360ea0396f34d46566f157122c92dfa069d3e0e982"},
+    {file = "multidict-6.0.4-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:666daae833559deb2d609afa4490b85830ab0dfca811a98b70a205621a6109fe"},
+    {file = "multidict-6.0.4-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:11bdf3f5e1518b24530b8241529d2050014c884cf18b6fc69c0c2b30ca248710"},
+    {file = "multidict-6.0.4-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:7d18748f2d30f94f498e852c67d61261c643b349b9d2a581131725595c45ec6c"},
+    {file = "multidict-6.0.4-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:458f37be2d9e4c95e2d8866a851663cbc76e865b78395090786f6cd9b3bbf4f4"},
+    {file = "multidict-6.0.4-cp311-cp311-musllinux_1_1_i686.whl", hash = "sha256:b1a2eeedcead3a41694130495593a559a668f382eee0727352b9a41e1c45759a"},
+    {file = "multidict-6.0.4-cp311-cp311-musllinux_1_1_ppc64le.whl", hash = "sha256:7d6ae9d593ef8641544d6263c7fa6408cc90370c8cb2bbb65f8d43e5b0351d9c"},
+    {file = "multidict-6.0.4-cp311-cp311-musllinux_1_1_s390x.whl", hash = "sha256:5979b5632c3e3534e42ca6ff856bb24b2e3071b37861c2c727ce220d80eee9ed"},
+    {file = "multidict-6.0.4-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:dcfe792765fab89c365123c81046ad4103fcabbc4f56d1c1997e6715e8015461"},
+    {file = "multidict-6.0.4-cp311-cp311-win32.whl", hash = "sha256:3601a3cece3819534b11d4efc1eb76047488fddd0c85a3948099d5da4d504636"},
+    {file = "multidict-6.0.4-cp311-cp311-win_amd64.whl", hash = "sha256:81a4f0b34bd92df3da93315c6a59034df95866014ac08535fc819f043bfd51f0"},
+    {file = "multidict-6.0.4-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:67040058f37a2a51ed8ea8f6b0e6ee5bd78ca67f169ce6122f3e2ec80dfe9b78"},
+    {file = "multidict-6.0.4-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:853888594621e6604c978ce2a0444a1e6e70c8d253ab65ba11657659dcc9100f"},
+    {file = "multidict-6.0.4-cp37-cp37m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:39ff62e7d0f26c248b15e364517a72932a611a9b75f35b45be078d81bdb86603"},
+    {file = "multidict-6.0.4-cp37-cp37m-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:af048912e045a2dc732847d33821a9d84ba553f5c5f028adbd364dd4765092ac"},
+    {file = "multidict-6.0.4-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b1e8b901e607795ec06c9e42530788c45ac21ef3aaa11dbd0c69de543bfb79a9"},
+    {file = "multidict-6.0.4-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:62501642008a8b9871ddfccbf83e4222cf8ac0d5aeedf73da36153ef2ec222d2"},
+    {file = "multidict-6.0.4-cp37-cp37m-musllinux_1_1_aarch64.whl", hash = "sha256:99b76c052e9f1bc0721f7541e5e8c05db3941eb9ebe7b8553c625ef88d6eefde"},
+    {file = "multidict-6.0.4-cp37-cp37m-musllinux_1_1_i686.whl", hash = "sha256:509eac6cf09c794aa27bcacfd4d62c885cce62bef7b2c3e8b2e49d365b5003fe"},
+    {file = "multidict-6.0.4-cp37-cp37m-musllinux_1_1_ppc64le.whl", hash = "sha256:21a12c4eb6ddc9952c415f24eef97e3e55ba3af61f67c7bc388dcdec1404a067"},
+    {file = "multidict-6.0.4-cp37-cp37m-musllinux_1_1_s390x.whl", hash = "sha256:5cad9430ab3e2e4fa4a2ef4450f548768400a2ac635841bc2a56a2052cdbeb87"},
+    {file = "multidict-6.0.4-cp37-cp37m-musllinux_1_1_x86_64.whl", hash = "sha256:ab55edc2e84460694295f401215f4a58597f8f7c9466faec545093045476327d"},
+    {file = "multidict-6.0.4-cp37-cp37m-win32.whl", hash = "sha256:5a4dcf02b908c3b8b17a45fb0f15b695bf117a67b76b7ad18b73cf8e92608775"},
+    {file = "multidict-6.0.4-cp37-cp37m-win_amd64.whl", hash = "sha256:6ed5f161328b7df384d71b07317f4d8656434e34591f20552c7bcef27b0ab88e"},
+    {file = "multidict-6.0.4-cp38-cp38-macosx_10_9_universal2.whl", hash = "sha256:5fc1b16f586f049820c5c5b17bb4ee7583092fa0d1c4e28b5239181ff9532e0c"},
+    {file = "multidict-6.0.4-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:1502e24330eb681bdaa3eb70d6358e818e8e8f908a22a1851dfd4e15bc2f8161"},
+    {file = "multidict-6.0.4-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:b692f419760c0e65d060959df05f2a531945af31fda0c8a3b3195d4efd06de11"},
+    {file = "multidict-6.0.4-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:45e1ecb0379bfaab5eef059f50115b54571acfbe422a14f668fc8c27ba410e7e"},
+    {file = "multidict-6.0.4-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:ddd3915998d93fbcd2566ddf9cf62cdb35c9e093075f862935573d265cf8f65d"},
+    {file = "multidict-6.0.4-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:59d43b61c59d82f2effb39a93c48b845efe23a3852d201ed2d24ba830d0b4cf2"},
+    {file = "multidict-6.0.4-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:cc8e1d0c705233c5dd0c5e6460fbad7827d5d36f310a0fadfd45cc3029762258"},
+    {file = "multidict-6.0.4-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:d6aa0418fcc838522256761b3415822626f866758ee0bc6632c9486b179d0b52"},
+    {file = "multidict-6.0.4-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:6748717bb10339c4760c1e63da040f5f29f5ed6e59d76daee30305894069a660"},
+    {file = "multidict-6.0.4-cp38-cp38-musllinux_1_1_i686.whl", hash = "sha256:4d1a3d7ef5e96b1c9e92f973e43aa5e5b96c659c9bc3124acbbd81b0b9c8a951"},
+    {file = "multidict-6.0.4-cp38-cp38-musllinux_1_1_ppc64le.whl", hash = "sha256:4372381634485bec7e46718edc71528024fcdc6f835baefe517b34a33c731d60"},
+    {file = "multidict-6.0.4-cp38-cp38-musllinux_1_1_s390x.whl", hash = "sha256:fc35cb4676846ef752816d5be2193a1e8367b4c1397b74a565a9d0389c433a1d"},
+    {file = "multidict-6.0.4-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:4b9d9e4e2b37daddb5c23ea33a3417901fa7c7b3dee2d855f63ee67a0b21e5b1"},
+    {file = "multidict-6.0.4-cp38-cp38-win32.whl", hash = "sha256:e41b7e2b59679edfa309e8db64fdf22399eec4b0b24694e1b2104fb789207779"},
+    {file = "multidict-6.0.4-cp38-cp38-win_amd64.whl", hash = "sha256:d6c254ba6e45d8e72739281ebc46ea5eb5f101234f3ce171f0e9f5cc86991480"},
+    {file = "multidict-6.0.4-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:16ab77bbeb596e14212e7bab8429f24c1579234a3a462105cda4a66904998664"},
+    {file = "multidict-6.0.4-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:bc779e9e6f7fda81b3f9aa58e3a6091d49ad528b11ed19f6621408806204ad35"},
+    {file = "multidict-6.0.4-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:4ceef517eca3e03c1cceb22030a3e39cb399ac86bff4e426d4fc6ae49052cc60"},
+    {file = "multidict-6.0.4-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:281af09f488903fde97923c7744bb001a9b23b039a909460d0f14edc7bf59706"},
+    {file = "multidict-6.0.4-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:52f2dffc8acaba9a2f27174c41c9e57f60b907bb9f096b36b1a1f3be71c6284d"},
+    {file = "multidict-6.0.4-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:b41156839806aecb3641f3208c0dafd3ac7775b9c4c422d82ee2a45c34ba81ca"},
+    {file = "multidict-6.0.4-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d5e3fc56f88cc98ef8139255cf8cd63eb2c586531e43310ff859d6bb3a6b51f1"},
+    {file = "multidict-6.0.4-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:8316a77808c501004802f9beebde51c9f857054a0c871bd6da8280e718444449"},
+    {file = "multidict-6.0.4-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:f70b98cd94886b49d91170ef23ec5c0e8ebb6f242d734ed7ed677b24d50c82cf"},
+    {file = "multidict-6.0.4-cp39-cp39-musllinux_1_1_i686.whl", hash = "sha256:bf6774e60d67a9efe02b3616fee22441d86fab4c6d335f9d2051d19d90a40063"},
+    {file = "multidict-6.0.4-cp39-cp39-musllinux_1_1_ppc64le.whl", hash = "sha256:e69924bfcdda39b722ef4d9aa762b2dd38e4632b3641b1d9a57ca9cd18f2f83a"},
+    {file = "multidict-6.0.4-cp39-cp39-musllinux_1_1_s390x.whl", hash = "sha256:6b181d8c23da913d4ff585afd1155a0e1194c0b50c54fcfe286f70cdaf2b7176"},
+    {file = "multidict-6.0.4-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:52509b5be062d9eafc8170e53026fbc54cf3b32759a23d07fd935fb04fc22d95"},
+    {file = "multidict-6.0.4-cp39-cp39-win32.whl", hash = "sha256:27c523fbfbdfd19c6867af7346332b62b586eed663887392cff78d614f9ec313"},
+    {file = "multidict-6.0.4-cp39-cp39-win_amd64.whl", hash = "sha256:33029f5734336aa0d4c0384525da0387ef89148dc7191aae00ca5fb23d7aafc2"},
+    {file = "multidict-6.0.4.tar.gz", hash = "sha256:3666906492efb76453c0e7b97f2cf459b0682e7402c0489a95484965dbc1da49"},
+]
+
+[[package]]
+name = "networkx"
+version = "3.1"
+description = "Python package for creating and manipulating graphs and networks"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "networkx-3.1-py3-none-any.whl", hash = "sha256:4f33f68cb2afcf86f28a45f43efc27a9386b535d567d2127f8f61d51dec58d36"},
+    {file = "networkx-3.1.tar.gz", hash = "sha256:de346335408f84de0eada6ff9fafafff9bcda11f0a0dfaa931133debb146ab61"},
+]
+
+[package.extras]
+default = ["matplotlib (>=3.4)", "numpy (>=1.20)", "pandas (>=1.3)", "scipy (>=1.8)"]
+developer = ["mypy (>=1.1)", "pre-commit (>=3.2)"]
+doc = ["nb2plots (>=0.6)", "numpydoc (>=1.5)", "pillow (>=9.4)", "pydata-sphinx-theme (>=0.13)", "sphinx (>=6.1)", "sphinx-gallery (>=0.12)", "texext (>=0.6.7)"]
+extra = ["lxml (>=4.6)", "pydot (>=1.4.2)", "pygraphviz (>=1.10)", "sympy (>=1.10)"]
+test = ["codecov (>=2.1)", "pytest (>=7.2)", "pytest-cov (>=4.0)"]
+
+[[package]]
+name = "numba"
+version = "0.56.4"
+description = "compiling Python code using LLVM"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "numba-0.56.4-cp310-cp310-macosx_10_14_x86_64.whl", hash = "sha256:9f62672145f8669ec08762895fe85f4cf0ead08ce3164667f2b94b2f62ab23c3"},
+    {file = "numba-0.56.4-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:c602d015478b7958408d788ba00a50272649c5186ea8baa6cf71d4a1c761bba1"},
+    {file = "numba-0.56.4-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:85dbaed7a05ff96492b69a8900c5ba605551afb9b27774f7f10511095451137c"},
+    {file = "numba-0.56.4-cp310-cp310-manylinux2014_i686.manylinux_2_17_i686.whl", hash = "sha256:f4cfc3a19d1e26448032049c79fc60331b104f694cf570a9e94f4e2c9d0932bb"},
+    {file = "numba-0.56.4-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:4e08e203b163ace08bad500b0c16f6092b1eb34fd1fce4feaf31a67a3a5ecf3b"},
+    {file = "numba-0.56.4-cp310-cp310-win32.whl", hash = "sha256:0611e6d3eebe4cb903f1a836ffdb2bda8d18482bcd0a0dcc56e79e2aa3fefef5"},
+    {file = "numba-0.56.4-cp310-cp310-win_amd64.whl", hash = "sha256:fbfb45e7b297749029cb28694abf437a78695a100e7c2033983d69f0ba2698d4"},
+    {file = "numba-0.56.4-cp37-cp37m-macosx_10_14_x86_64.whl", hash = "sha256:3cb1a07a082a61df80a468f232e452d818f5ae254b40c26390054e4e868556e0"},
+    {file = "numba-0.56.4-cp37-cp37m-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:d69ad934e13c15684e7887100a8f5f0f61d7a8e57e0fd29d9993210089a5b531"},
+    {file = "numba-0.56.4-cp37-cp37m-manylinux2014_i686.manylinux_2_17_i686.whl", hash = "sha256:dbcc847bac2d225265d054993a7f910fda66e73d6662fe7156452cac0325b073"},
+    {file = "numba-0.56.4-cp37-cp37m-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:8a95ca9cc77ea4571081f6594e08bd272b66060634b8324e99cd1843020364f9"},
+    {file = "numba-0.56.4-cp37-cp37m-win32.whl", hash = "sha256:fcdf84ba3ed8124eb7234adfbb8792f311991cbf8aed1cad4b1b1a7ee08380c1"},
+    {file = "numba-0.56.4-cp37-cp37m-win_amd64.whl", hash = "sha256:42f9e1be942b215df7e6cc9948cf9c15bb8170acc8286c063a9e57994ef82fd1"},
+    {file = "numba-0.56.4-cp38-cp38-macosx_10_14_x86_64.whl", hash = "sha256:553da2ce74e8862e18a72a209ed3b6d2924403bdd0fb341fa891c6455545ba7c"},
+    {file = "numba-0.56.4-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:4373da9757049db7c90591e9ec55a2e97b2b36ba7ae3bf9c956a513374077470"},
+    {file = "numba-0.56.4-cp38-cp38-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:3a993349b90569518739009d8f4b523dfedd7e0049e6838c0e17435c3e70dcc4"},
+    {file = "numba-0.56.4-cp38-cp38-manylinux2014_i686.manylinux_2_17_i686.whl", hash = "sha256:720886b852a2d62619ae3900fe71f1852c62db4f287d0c275a60219e1643fc04"},
+    {file = "numba-0.56.4-cp38-cp38-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:e64d338b504c9394a4a34942df4627e1e6cb07396ee3b49fe7b8d6420aa5104f"},
+    {file = "numba-0.56.4-cp38-cp38-win32.whl", hash = "sha256:03fe94cd31e96185cce2fae005334a8cc712fc2ba7756e52dff8c9400718173f"},
+    {file = "numba-0.56.4-cp38-cp38-win_amd64.whl", hash = "sha256:91f021145a8081f881996818474ef737800bcc613ffb1e618a655725a0f9e246"},
+    {file = "numba-0.56.4-cp39-cp39-macosx_10_14_x86_64.whl", hash = "sha256:d0ae9270a7a5cc0ede63cd234b4ff1ce166c7a749b91dbbf45e0000c56d3eade"},
+    {file = "numba-0.56.4-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:c75e8a5f810ce80a0cfad6e74ee94f9fde9b40c81312949bf356b7304ef20740"},
+    {file = "numba-0.56.4-cp39-cp39-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:a12ef323c0f2101529d455cfde7f4135eaa147bad17afe10b48634f796d96abd"},
+    {file = "numba-0.56.4-cp39-cp39-manylinux2014_i686.manylinux_2_17_i686.whl", hash = "sha256:03634579d10a6129181129de293dd6b5eaabee86881369d24d63f8fe352dd6cb"},
+    {file = "numba-0.56.4-cp39-cp39-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:0240f9026b015e336069329839208ebd70ec34ae5bfbf402e4fcc8e06197528e"},
+    {file = "numba-0.56.4-cp39-cp39-win32.whl", hash = "sha256:14dbbabf6ffcd96ee2ac827389afa59a70ffa9f089576500434c34abf9b054a4"},
+    {file = "numba-0.56.4-cp39-cp39-win_amd64.whl", hash = "sha256:0da583c532cd72feefd8e551435747e0e0fbb3c0530357e6845fcc11e38d6aea"},
+    {file = "numba-0.56.4.tar.gz", hash = "sha256:32d9fef412c81483d7efe0ceb6cf4d3310fde8b624a9cecca00f790573ac96ee"},
+]
+
+[package.dependencies]
+importlib-metadata = {version = "*", markers = "python_version < \"3.9\""}
+llvmlite = "==0.39.*"
+numpy = ">=1.18,<1.24"
+setuptools = "*"
+
+[[package]]
+name = "numpy"
+version = "1.23.5"
+description = "NumPy is the fundamental package for array computing with Python."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "numpy-1.23.5-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:9c88793f78fca17da0145455f0d7826bcb9f37da4764af27ac945488116efe63"},
+    {file = "numpy-1.23.5-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:e9f4c4e51567b616be64e05d517c79a8a22f3606499941d97bb76f2ca59f982d"},
+    {file = "numpy-1.23.5-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7903ba8ab592b82014713c491f6c5d3a1cde5b4a3bf116404e08f5b52f6daf43"},
+    {file = "numpy-1.23.5-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:5e05b1c973a9f858c74367553e236f287e749465f773328c8ef31abe18f691e1"},
+    {file = "numpy-1.23.5-cp310-cp310-win32.whl", hash = "sha256:522e26bbf6377e4d76403826ed689c295b0b238f46c28a7251ab94716da0b280"},
+    {file = "numpy-1.23.5-cp310-cp310-win_amd64.whl", hash = "sha256:dbee87b469018961d1ad79b1a5d50c0ae850000b639bcb1b694e9981083243b6"},
+    {file = "numpy-1.23.5-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:ce571367b6dfe60af04e04a1834ca2dc5f46004ac1cc756fb95319f64c095a96"},
+    {file = "numpy-1.23.5-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:56e454c7833e94ec9769fa0f86e6ff8e42ee38ce0ce1fa4cbb747ea7e06d56aa"},
+    {file = "numpy-1.23.5-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:5039f55555e1eab31124a5768898c9e22c25a65c1e0037f4d7c495a45778c9f2"},
+    {file = "numpy-1.23.5-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:58f545efd1108e647604a1b5aa809591ccd2540f468a880bedb97247e72db387"},
+    {file = "numpy-1.23.5-cp311-cp311-win32.whl", hash = "sha256:b2a9ab7c279c91974f756c84c365a669a887efa287365a8e2c418f8b3ba73fb0"},
+    {file = "numpy-1.23.5-cp311-cp311-win_amd64.whl", hash = "sha256:0cbe9848fad08baf71de1a39e12d1b6310f1d5b2d0ea4de051058e6e1076852d"},
+    {file = "numpy-1.23.5-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:f063b69b090c9d918f9df0a12116029e274daf0181df392839661c4c7ec9018a"},
+    {file = "numpy-1.23.5-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:0aaee12d8883552fadfc41e96b4c82ee7d794949e2a7c3b3a7201e968c7ecab9"},
+    {file = "numpy-1.23.5-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:92c8c1e89a1f5028a4c6d9e3ccbe311b6ba53694811269b992c0b224269e2398"},
+    {file = "numpy-1.23.5-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d208a0f8729f3fb790ed18a003f3a57895b989b40ea4dce4717e9cf4af62c6bb"},
+    {file = "numpy-1.23.5-cp38-cp38-win32.whl", hash = "sha256:06005a2ef6014e9956c09ba07654f9837d9e26696a0470e42beedadb78c11b07"},
+    {file = "numpy-1.23.5-cp38-cp38-win_amd64.whl", hash = "sha256:ca51fcfcc5f9354c45f400059e88bc09215fb71a48d3768fb80e357f3b457e1e"},
+    {file = "numpy-1.23.5-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:8969bfd28e85c81f3f94eb4a66bc2cf1dbdc5c18efc320af34bffc54d6b1e38f"},
+    {file = "numpy-1.23.5-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:a7ac231a08bb37f852849bbb387a20a57574a97cfc7b6cabb488a4fc8be176de"},
+    {file = "numpy-1.23.5-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:bf837dc63ba5c06dc8797c398db1e223a466c7ece27a1f7b5232ba3466aafe3d"},
+    {file = "numpy-1.23.5-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:33161613d2269025873025b33e879825ec7b1d831317e68f4f2f0f84ed14c719"},
+    {file = "numpy-1.23.5-cp39-cp39-win32.whl", hash = "sha256:af1da88f6bc3d2338ebbf0e22fe487821ea4d8e89053e25fa59d1d79786e7481"},
+    {file = "numpy-1.23.5-cp39-cp39-win_amd64.whl", hash = "sha256:09b7847f7e83ca37c6e627682f145856de331049013853f344f37b0c9690e3df"},
+    {file = "numpy-1.23.5-pp38-pypy38_pp73-macosx_10_9_x86_64.whl", hash = "sha256:abdde9f795cf292fb9651ed48185503a2ff29be87770c3b8e2a14b0cd7aa16f8"},
+    {file = "numpy-1.23.5-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f9a909a8bae284d46bbfdefbdd4a262ba19d3bc9921b1e76126b1d21c3c34135"},
+    {file = "numpy-1.23.5-pp38-pypy38_pp73-win_amd64.whl", hash = "sha256:01dd17cbb340bf0fc23981e52e1d18a9d4050792e8fb8363cecbf066a84b827d"},
+    {file = "numpy-1.23.5.tar.gz", hash = "sha256:1b1766d6f397c18153d40015ddfc79ddb715cabadc04d2d228d4e5a8bc4ded1a"},
+]
+
+[[package]]
+name = "nvidia-cublas-cu11"
+version = "11.10.3.66"
+description = "CUBLAS native runtime libraries"
+optional = false
+python-versions = ">=3"
+files = [
+    {file = "nvidia_cublas_cu11-11.10.3.66-py3-none-manylinux1_x86_64.whl", hash = "sha256:d32e4d75f94ddfb93ea0a5dda08389bcc65d8916a25cb9f37ac89edaeed3bded"},
+    {file = "nvidia_cublas_cu11-11.10.3.66-py3-none-win_amd64.whl", hash = "sha256:8ac17ba6ade3ed56ab898a036f9ae0756f1e81052a317bf98f8c6d18dc3ae49e"},
+]
+
+[package.dependencies]
+setuptools = "*"
+wheel = "*"
+
+[[package]]
+name = "nvidia-cuda-cupti-cu11"
+version = "11.7.101"
+description = "CUDA profiling tools runtime libs."
+optional = false
+python-versions = ">=3"
+files = [
+    {file = "nvidia_cuda_cupti_cu11-11.7.101-py3-none-manylinux1_x86_64.whl", hash = "sha256:e0cfd9854e1f2edaa36ca20d21cd0bdd5dcfca4e3b9e130a082e05b33b6c5895"},
+    {file = "nvidia_cuda_cupti_cu11-11.7.101-py3-none-win_amd64.whl", hash = "sha256:7cc5b8f91ae5e1389c3c0ad8866b3b016a175e827ea8f162a672990a402ab2b0"},
+]
+
+[package.dependencies]
+setuptools = "*"
+wheel = "*"
+
+[[package]]
+name = "nvidia-cuda-nvrtc-cu11"
+version = "11.7.99"
+description = "NVRTC native runtime libraries"
+optional = false
+python-versions = ">=3"
+files = [
+    {file = "nvidia_cuda_nvrtc_cu11-11.7.99-2-py3-none-manylinux1_x86_64.whl", hash = "sha256:9f1562822ea264b7e34ed5930567e89242d266448e936b85bc97a3370feabb03"},
+    {file = "nvidia_cuda_nvrtc_cu11-11.7.99-py3-none-manylinux1_x86_64.whl", hash = "sha256:f7d9610d9b7c331fa0da2d1b2858a4a8315e6d49765091d28711c8946e7425e7"},
+    {file = "nvidia_cuda_nvrtc_cu11-11.7.99-py3-none-win_amd64.whl", hash = "sha256:f2effeb1309bdd1b3854fc9b17eaf997808f8b25968ce0c7070945c4265d64a3"},
+]
+
+[package.dependencies]
+setuptools = "*"
+wheel = "*"
+
+[[package]]
+name = "nvidia-cuda-runtime-cu11"
+version = "11.7.99"
+description = "CUDA Runtime native Libraries"
+optional = false
+python-versions = ">=3"
+files = [
+    {file = "nvidia_cuda_runtime_cu11-11.7.99-py3-none-manylinux1_x86_64.whl", hash = "sha256:cc768314ae58d2641f07eac350f40f99dcb35719c4faff4bc458a7cd2b119e31"},
+    {file = "nvidia_cuda_runtime_cu11-11.7.99-py3-none-win_amd64.whl", hash = "sha256:bc77fa59a7679310df9d5c70ab13c4e34c64ae2124dd1efd7e5474b71be125c7"},
+]
+
+[package.dependencies]
+setuptools = "*"
+wheel = "*"
+
+[[package]]
+name = "nvidia-cudnn-cu11"
+version = "8.5.0.96"
+description = "cuDNN runtime libraries"
+optional = false
+python-versions = ">=3"
+files = [
+    {file = "nvidia_cudnn_cu11-8.5.0.96-2-py3-none-manylinux1_x86_64.whl", hash = "sha256:402f40adfc6f418f9dae9ab402e773cfed9beae52333f6d86ae3107a1b9527e7"},
+    {file = "nvidia_cudnn_cu11-8.5.0.96-py3-none-manylinux1_x86_64.whl", hash = "sha256:71f8111eb830879ff2836db3cccf03bbd735df9b0d17cd93761732ac50a8a108"},
+]
+
+[package.dependencies]
+setuptools = "*"
+wheel = "*"
+
+[[package]]
+name = "nvidia-cufft-cu11"
+version = "10.9.0.58"
+description = "CUFFT native runtime libraries"
+optional = false
+python-versions = ">=3"
+files = [
+    {file = "nvidia_cufft_cu11-10.9.0.58-py3-none-manylinux1_x86_64.whl", hash = "sha256:222f9da70c80384632fd6035e4c3f16762d64ea7a843829cb278f98b3cb7dd81"},
+    {file = "nvidia_cufft_cu11-10.9.0.58-py3-none-win_amd64.whl", hash = "sha256:c4d316f17c745ec9c728e30409612eaf77a8404c3733cdf6c9c1569634d1ca03"},
+]
+
+[[package]]
+name = "nvidia-curand-cu11"
+version = "10.2.10.91"
+description = "CURAND native runtime libraries"
+optional = false
+python-versions = ">=3"
+files = [
+    {file = "nvidia_curand_cu11-10.2.10.91-py3-none-manylinux1_x86_64.whl", hash = "sha256:eecb269c970fa599a2660c9232fa46aaccbf90d9170b96c462e13bcb4d129e2c"},
+    {file = "nvidia_curand_cu11-10.2.10.91-py3-none-win_amd64.whl", hash = "sha256:f742052af0e1e75523bde18895a9ed016ecf1e5aa0ecddfcc3658fd11a1ff417"},
+]
+
+[package.dependencies]
+setuptools = "*"
+wheel = "*"
+
+[[package]]
+name = "nvidia-cusolver-cu11"
+version = "11.4.0.1"
+description = "CUDA solver native runtime libraries"
+optional = false
+python-versions = ">=3"
+files = [
+    {file = "nvidia_cusolver_cu11-11.4.0.1-2-py3-none-manylinux1_x86_64.whl", hash = "sha256:72fa7261d755ed55c0074960df5904b65e2326f7adce364cbe4945063c1be412"},
+    {file = "nvidia_cusolver_cu11-11.4.0.1-py3-none-manylinux1_x86_64.whl", hash = "sha256:700b781bfefd57d161443aff9ace1878584b93e0b2cfef3d6e9296d96febbf99"},
+    {file = "nvidia_cusolver_cu11-11.4.0.1-py3-none-win_amd64.whl", hash = "sha256:00f70b256add65f8c1eb3b6a65308795a93e7740f6df9e273eccbba770d370c4"},
+]
+
+[package.dependencies]
+setuptools = "*"
+wheel = "*"
+
+[[package]]
+name = "nvidia-cusparse-cu11"
+version = "11.7.4.91"
+description = "CUSPARSE native runtime libraries"
+optional = false
+python-versions = ">=3"
+files = [
+    {file = "nvidia_cusparse_cu11-11.7.4.91-py3-none-manylinux1_x86_64.whl", hash = "sha256:a3389de714db63321aa11fbec3919271f415ef19fda58aed7f2ede488c32733d"},
+    {file = "nvidia_cusparse_cu11-11.7.4.91-py3-none-win_amd64.whl", hash = "sha256:304a01599534f5186a8ed1c3756879282c72c118bc77dd890dc1ff868cad25b9"},
+]
+
+[package.dependencies]
+setuptools = "*"
+wheel = "*"
+
+[[package]]
+name = "nvidia-nccl-cu11"
+version = "2.14.3"
+description = "NVIDIA Collective Communication Library (NCCL) Runtime"
+optional = false
+python-versions = ">=3"
+files = [
+    {file = "nvidia_nccl_cu11-2.14.3-py3-none-manylinux1_x86_64.whl", hash = "sha256:5e5534257d1284b8e825bc3a182c6f06acd6eb405e9f89d49340e98cd8f136eb"},
+]
+
+[[package]]
+name = "nvidia-nvtx-cu11"
+version = "11.7.91"
+description = "NVIDIA Tools Extension"
+optional = false
+python-versions = ">=3"
+files = [
+    {file = "nvidia_nvtx_cu11-11.7.91-py3-none-manylinux1_x86_64.whl", hash = "sha256:b22c64eee426a62fc00952b507d6d29cf62b4c9df7a480fcc417e540e05fd5ac"},
+    {file = "nvidia_nvtx_cu11-11.7.91-py3-none-win_amd64.whl", hash = "sha256:dfd7fcb2a91742513027d63a26b757f38dd8b07fecac282c4d132a9d373ff064"},
+]
+
+[package.dependencies]
+setuptools = "*"
+wheel = "*"
+
+[[package]]
+name = "oauthlib"
+version = "3.2.2"
+description = "A generic, spec-compliant, thorough implementation of the OAuth request-signing logic"
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "oauthlib-3.2.2-py3-none-any.whl", hash = "sha256:8139f29aac13e25d502680e9e19963e83f16838d48a0d71c287fe40e7067fbca"},
+    {file = "oauthlib-3.2.2.tar.gz", hash = "sha256:9859c40929662bec5d64f34d01c99e093149682a3f38915dc0655d5a633dd918"},
+]
+
+[package.extras]
+rsa = ["cryptography (>=3.0.0)"]
+signals = ["blinker (>=1.4.0)"]
+signedtoken = ["cryptography (>=3.0.0)", "pyjwt (>=2.0.0,<3)"]
+
+[[package]]
+name = "omegaconf"
+version = "2.0.6"
+description = "A flexible configuration library"
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "omegaconf-2.0.6-py3-none-any.whl", hash = "sha256:9e349fd76819b95b47aa628edea1ff83fed5b25108608abdd6c7fdca188e302a"},
+    {file = "omegaconf-2.0.6.tar.gz", hash = "sha256:92ca535a788d21651bf4c2eaf5c1ca4c7a8003b2dab4a87cbb09109784268806"},
+]
+
+[package.dependencies]
+PyYAML = ">=5.1"
+typing-extensions = "*"
+
+[[package]]
+name = "orjson"
+version = "3.8.9"
+description = "Fast, correct Python JSON library supporting dataclasses, datetimes, and numpy"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "orjson-3.8.9-cp310-cp310-macosx_10_7_x86_64.whl", hash = "sha256:5d029843eae7b6cbd6468b63517b8b61471afed6572162171d8b6471b6dbf41f"},
+    {file = "orjson-3.8.9-cp310-cp310-macosx_10_9_x86_64.macosx_11_0_arm64.macosx_10_9_universal2.whl", hash = "sha256:405933c05490efb209d0f940d8ef1403d2932a97e47010a26d2694e9dd49f84d"},
+    {file = "orjson-3.8.9-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:183de66eff4d41c330a3006f210ab0bce7affe398da6f6eda9579b67245a34ff"},
+    {file = "orjson-3.8.9-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:bb4081fe340ed1df42dddfd055e1d50479cb0ccb976d13e6b5e8667a07fec6f4"},
+    {file = "orjson-3.8.9-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d11593a2e736055dd7b9587dbf89cd1cbe4a42a70e70f186e51aee7e1b38902e"},
+    {file = "orjson-3.8.9-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e20649359e28f34d01b2570e4650a076f439a959bae3a8bbe7f5923ad80f54e8"},
+    {file = "orjson-3.8.9-cp310-cp310-manylinux_2_28_x86_64.whl", hash = "sha256:c02ece4f36a160c83efe74adfba5f189c7c7702361f02b809ab73744923ee139"},
+    {file = "orjson-3.8.9-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:f0e19801836cf1b30f333d475b05d79051b8ae8639a8e2422fb5f64e82676ae7"},
+    {file = "orjson-3.8.9-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:d4850fe5650cead3c0f8822192e381cee9d4c3b8162eb082c86c927124572dc6"},
+    {file = "orjson-3.8.9-cp310-none-win_amd64.whl", hash = "sha256:5fd4193f260d9d30112b5e379d0870b54dc88040807c93cbe8d67bfea148ba5a"},
+    {file = "orjson-3.8.9-cp311-cp311-macosx_10_7_x86_64.whl", hash = "sha256:70eae063ad8d7405dc63873760567b600fc10728ba0da24a69d49c1a5d318d6d"},
+    {file = "orjson-3.8.9-cp311-cp311-macosx_10_9_x86_64.macosx_11_0_arm64.macosx_10_9_universal2.whl", hash = "sha256:251653437632583d02203e6b118b72b99c04425175853f35340f4bac7034a36e"},
+    {file = "orjson-3.8.9-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6ea833751f017ba321c277e7425b51c0b1a18a2c60f8c9c0f4c6c4d7e16cbd6c"},
+    {file = "orjson-3.8.9-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:8563c2cdeb923b82a5cc5bfc76c28c786777428263ee39292d928e9687165fb4"},
+    {file = "orjson-3.8.9-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:6f33e9ea45b4c9457eedca0c40f38cf5732c91b0fb68f091ac59e6ea68e03eb2"},
+    {file = "orjson-3.8.9-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:855dee152daecb7de7b4cd7069d7854e11aa291687bffe8433156af0a224417e"},
+    {file = "orjson-3.8.9-cp311-cp311-manylinux_2_28_x86_64.whl", hash = "sha256:74fa9e02589339defc9d3662de9e7eef51d8f9f3a7f6304b43b18b39d7bbf10f"},
+    {file = "orjson-3.8.9-cp311-none-win_amd64.whl", hash = "sha256:6c5b10ba1e62df8f96cbc37f6d5ae9acb3f6475926dea8b1b6a1a60f201a64f7"},
+    {file = "orjson-3.8.9-cp37-cp37m-macosx_10_7_x86_64.whl", hash = "sha256:a651123d01bc399fcd866e56acc2d76512e62aae3673652b13b470ea69faf1f4"},
+    {file = "orjson-3.8.9-cp37-cp37m-macosx_10_9_x86_64.macosx_11_0_arm64.macosx_10_9_universal2.whl", hash = "sha256:73019b6d2cc998c99556020c6bd8f8bc28420c69583186ca290c66a27916a3b7"},
+    {file = "orjson-3.8.9-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:8f5c3daa8b02786ad5f0e14ae16a59bbb4e02cbae3a41989a25188e5a6c962ff"},
+    {file = "orjson-3.8.9-cp37-cp37m-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:598598b7f81f8fda7c3e09c88165f844152b7be223bc4ea929ec8ad59b00ea17"},
+    {file = "orjson-3.8.9-cp37-cp37m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:090b10bdb06baae6d5cd3550d772ecbabd833bfceed7592ff167c0a82f5b4c20"},
+    {file = "orjson-3.8.9-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bd46f688ddf9c2ea10367446fe9bf3ceba0f7490c15b4f96420491c7f00bb283"},
+    {file = "orjson-3.8.9-cp37-cp37m-manylinux_2_28_x86_64.whl", hash = "sha256:b8ed8d780e9fab01bc404a70d755a8b2b34ea6c0b6604b65de135daaaadaf9a9"},
+    {file = "orjson-3.8.9-cp37-cp37m-musllinux_1_1_aarch64.whl", hash = "sha256:8a32c9fb742868a34346f3c52e12d893a9d27f8e0c0bf3c480db7e6903d8be28"},
+    {file = "orjson-3.8.9-cp37-cp37m-musllinux_1_1_x86_64.whl", hash = "sha256:2ba366009b98ac8899e935eff6fef7672d3ea43d3ce9deb3ee33452134b6cc3a"},
+    {file = "orjson-3.8.9-cp37-none-win_amd64.whl", hash = "sha256:236b9313425cb2570626c64dd5cb6caff13882d1717d491da542cff228b96e97"},
+    {file = "orjson-3.8.9-cp38-cp38-macosx_10_7_x86_64.whl", hash = "sha256:e8efc7e9ec35336f7cc98b6692536b1262046ff1d2a545295a4d89b8a2495903"},
+    {file = "orjson-3.8.9-cp38-cp38-macosx_10_9_x86_64.macosx_11_0_arm64.macosx_10_9_universal2.whl", hash = "sha256:8c7eba3610ae69f4aba4032ecb61b0a6fbd1e4537283d1553eb8c1cb136e9118"},
+    {file = "orjson-3.8.9-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7742649e4c357d4e7ad483a35ff5f55d519e895de56772cc486913614ee7d23b"},
+    {file = "orjson-3.8.9-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:b6566fb8daa538c7848fd6822e2409a7e1c41dae8e65e6536598d505f641a318"},
+    {file = "orjson-3.8.9-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:0ce8a2a667221e2e5160021e26b09e9c13eeedafb5cda1981340c8c0c0bc8f9d"},
+    {file = "orjson-3.8.9-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4c0399631b88fa4868956badef2561fba07dffcaf050bf53959ee50d26edf6f6"},
+    {file = "orjson-3.8.9-cp38-cp38-manylinux_2_28_x86_64.whl", hash = "sha256:189ccb16ed140a824d133fa1c55175cf0d2207edaade54f1db0456a526cb5fd8"},
+    {file = "orjson-3.8.9-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:b707fa4481e1af19b3052ec9352c688bad3f539d7bdd8aa4a451f6dd7e4bae73"},
+    {file = "orjson-3.8.9-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:c3d988eb562da1dda7d49e9abd8a64b3cabc632b4299d177fb9e0c0ca9f06b8c"},
+    {file = "orjson-3.8.9-cp38-none-win_amd64.whl", hash = "sha256:b30240eb6b22daab604f1595f6aacf92bcdac0d29e2d7ad507dfac68d2b39182"},
+    {file = "orjson-3.8.9-cp39-cp39-macosx_10_7_x86_64.whl", hash = "sha256:81869a6de00bc676d10056fa8bb28cbe805b1cf498a45c14cb7b1765eee33fcb"},
+    {file = "orjson-3.8.9-cp39-cp39-macosx_10_9_x86_64.macosx_11_0_arm64.macosx_10_9_universal2.whl", hash = "sha256:a25a5a215b19d414de8d416a3c5414f29165843a06f704cc0345ded9eac34ac1"},
+    {file = "orjson-3.8.9-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:dec0f2bea52e30ea98ce095f1f42da04535791f9a31b2aab2499caa88307bc49"},
+    {file = "orjson-3.8.9-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:7b91d88fe96b698b28bb1b95b1fce226f72757ab3ab7d8d97551e23bc629c84f"},
+    {file = "orjson-3.8.9-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:7629841ccdcccd3c43ebc6a4165abe9844909fcedb2041994c0153470f610801"},
+    {file = "orjson-3.8.9-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d875b304e19f4b2758d233bbf2b9d627c66fac50b3150b8d31a35ba6cda3db67"},
+    {file = "orjson-3.8.9-cp39-cp39-manylinux_2_28_x86_64.whl", hash = "sha256:723ec880c5290fe4de330febb8030e57c1978fbd624fc5b9399969e7d7d74984"},
+    {file = "orjson-3.8.9-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:b11f8a71c82d19fce11ce487efeec2ca0dc3bcf5b4564445fecfc68d9c268744"},
+    {file = "orjson-3.8.9-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:b2079bf86dec62731c1b90fdfea3211f993f0c894d9261e0ce9b68ed9c9dfbec"},
+    {file = "orjson-3.8.9-cp39-none-win_amd64.whl", hash = "sha256:97d94322a2eaab767ba8d52f6bf9d0ec0f35313fe36287be6e6085dd65d55d37"},
+    {file = "orjson-3.8.9.tar.gz", hash = "sha256:c40bece58c11cb09aff17424d21b41f6f767d2b1252b2f745ec3ff29cce6a240"},
+]
+
+[[package]]
+name = "packaging"
+version = "23.0"
+description = "Core utilities for Python packages"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "packaging-23.0-py3-none-any.whl", hash = "sha256:714ac14496c3e68c99c29b00845f7a2b85f3bb6f1078fd9f72fd20f0570002b2"},
+    {file = "packaging-23.0.tar.gz", hash = "sha256:b6ad297f8907de0fa2fe1ccbd26fdaf387f5f47c7275fedf8cce89f99446cf97"},
+]
+
+[[package]]
+name = "pandas"
+version = "2.0.0"
+description = "Powerful data structures for data analysis, time series, and statistics"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "pandas-2.0.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:bbb2c5e94d6aa4e632646a3bacd05c2a871c3aa3e85c9bec9be99cb1267279f2"},
+    {file = "pandas-2.0.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:b5337c87c4e963f97becb1217965b6b75c6fe5f54c4cf09b9a5ac52fc0bd03d3"},
+    {file = "pandas-2.0.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6ded51f7e3dd9b4f8b87f2ceb7bd1a8df2491f7ee72f7074c6927a512607199e"},
+    {file = "pandas-2.0.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:52c858de9e9fc422d25e67e1592a6e6135d7bcf9a19fcaf4d0831a0be496bf21"},
+    {file = "pandas-2.0.0-cp310-cp310-win32.whl", hash = "sha256:2d1d138848dd71b37e3cbe7cd952ff84e2ab04d8988972166e18567dcc811245"},
+    {file = "pandas-2.0.0-cp310-cp310-win_amd64.whl", hash = "sha256:d08e41d96bc4de6f500afe80936c68fce6099d5a434e2af7c7fd8e7c72a3265d"},
+    {file = "pandas-2.0.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:24472cfc7ced511ac90608728b88312be56edc8f19b9ed885a7d2e47ffaf69c0"},
+    {file = "pandas-2.0.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:4ffb14f50c74ee541610668137830bb93e9dfa319b1bef2cedf2814cd5ac9c70"},
+    {file = "pandas-2.0.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c24c7d12d033a372a9daf9ff2c80f8b0af6f98d14664dbb0a4f6a029094928a7"},
+    {file = "pandas-2.0.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:8318de0f886e4dcb8f9f36e45a3d6a6c3d1cfdc508354da85e739090f0222991"},
+    {file = "pandas-2.0.0-cp311-cp311-win32.whl", hash = "sha256:57c34b79c13249505e850d0377b722961b99140f81dafbe6f19ef10239f6284a"},
+    {file = "pandas-2.0.0-cp311-cp311-win_amd64.whl", hash = "sha256:8f987ec26e96a8490909bc5d98c514147236e49830cba7df8690f6087c12bbae"},
+    {file = "pandas-2.0.0-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:b3ba8f5dd470d8bfbc4259829589f4a32881151c49e36384d9eb982b35a12020"},
+    {file = "pandas-2.0.0-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:fcd471c9d9f60926ab2f15c6c29164112f458acb42280365fbefa542d0c2fc74"},
+    {file = "pandas-2.0.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:9253edfd015520ce77a9343eb7097429479c039cd3ebe81d7810ea11b4b24695"},
+    {file = "pandas-2.0.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:977326039bd1ded620001a1889e2ed4798460a6bc5a24fbaebb5f07a41c32a55"},
+    {file = "pandas-2.0.0-cp38-cp38-win32.whl", hash = "sha256:78425ca12314b23356c28b16765639db10ebb7d8983f705d6759ff7fe41357fa"},
+    {file = "pandas-2.0.0-cp38-cp38-win_amd64.whl", hash = "sha256:d93b7fcfd9f3328072b250d6d001dcfeec5d3bb66c1b9c8941e109a46c0c01a8"},
+    {file = "pandas-2.0.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:425705cee8be54db2504e8dd2a730684790b15e5904b750c367611ede49098ab"},
+    {file = "pandas-2.0.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:a4f789b7c012a608c08cda4ff0872fd979cb18907a37982abe884e6f529b8793"},
+    {file = "pandas-2.0.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:3bb9d840bf15656805f6a3d87eea9dcb7efdf1314a82adcf7f00b820427c5570"},
+    {file = "pandas-2.0.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0778ab54c8f399d83d98ffb674d11ec716449956bc6f6821891ab835848687f2"},
+    {file = "pandas-2.0.0-cp39-cp39-win32.whl", hash = "sha256:70db5c278bbec0306d32bf78751ff56b9594c05a5098386f6c8a563659124f91"},
+    {file = "pandas-2.0.0-cp39-cp39-win_amd64.whl", hash = "sha256:4f3320bb55f34af4193020158ef8118ee0fb9aec7cc47d2084dbfdd868a0a24f"},
+    {file = "pandas-2.0.0.tar.gz", hash = "sha256:cda9789e61b44463c1c4fe17ef755de77bcd13b09ba31c940d20f193d63a5dc8"},
+]
+
+[package.dependencies]
+numpy = [
+    {version = ">=1.20.3", markers = "python_version < \"3.10\""},
+    {version = ">=1.21.0", markers = "python_version >= \"3.10\""},
+    {version = ">=1.23.2", markers = "python_version >= \"3.11\""},
+]
+python-dateutil = ">=2.8.2"
+pytz = ">=2020.1"
+tzdata = ">=2022.1"
+
+[package.extras]
+all = ["PyQt5 (>=5.15.1)", "SQLAlchemy (>=1.4.16)", "beautifulsoup4 (>=4.9.3)", "bottleneck (>=1.3.2)", "brotlipy (>=0.7.0)", "fastparquet (>=0.6.3)", "fsspec (>=2021.07.0)", "gcsfs (>=2021.07.0)", "html5lib (>=1.1)", "hypothesis (>=6.34.2)", "jinja2 (>=3.0.0)", "lxml (>=4.6.3)", "matplotlib (>=3.6.1)", "numba (>=0.53.1)", "numexpr (>=2.7.3)", "odfpy (>=1.4.1)", "openpyxl (>=3.0.7)", "pandas-gbq (>=0.15.0)", "psycopg2 (>=2.8.6)", "pyarrow (>=7.0.0)", "pymysql (>=1.0.2)", "pyreadstat (>=1.1.2)", "pytest (>=7.0.0)", "pytest-asyncio (>=0.17.0)", "pytest-xdist (>=2.2.0)", "python-snappy (>=0.6.0)", "pyxlsb (>=1.0.8)", "qtpy (>=2.2.0)", "s3fs (>=2021.08.0)", "scipy (>=1.7.1)", "tables (>=3.6.1)", "tabulate (>=0.8.9)", "xarray (>=0.21.0)", "xlrd (>=2.0.1)", "xlsxwriter (>=1.4.3)", "zstandard (>=0.15.2)"]
+aws = ["s3fs (>=2021.08.0)"]
+clipboard = ["PyQt5 (>=5.15.1)", "qtpy (>=2.2.0)"]
+compression = ["brotlipy (>=0.7.0)", "python-snappy (>=0.6.0)", "zstandard (>=0.15.2)"]
+computation = ["scipy (>=1.7.1)", "xarray (>=0.21.0)"]
+excel = ["odfpy (>=1.4.1)", "openpyxl (>=3.0.7)", "pyxlsb (>=1.0.8)", "xlrd (>=2.0.1)", "xlsxwriter (>=1.4.3)"]
+feather = ["pyarrow (>=7.0.0)"]
+fss = ["fsspec (>=2021.07.0)"]
+gcp = ["gcsfs (>=2021.07.0)", "pandas-gbq (>=0.15.0)"]
+hdf5 = ["tables (>=3.6.1)"]
+html = ["beautifulsoup4 (>=4.9.3)", "html5lib (>=1.1)", "lxml (>=4.6.3)"]
+mysql = ["SQLAlchemy (>=1.4.16)", "pymysql (>=1.0.2)"]
+output-formatting = ["jinja2 (>=3.0.0)", "tabulate (>=0.8.9)"]
+parquet = ["pyarrow (>=7.0.0)"]
+performance = ["bottleneck (>=1.3.2)", "numba (>=0.53.1)", "numexpr (>=2.7.1)"]
+plot = ["matplotlib (>=3.6.1)"]
+postgresql = ["SQLAlchemy (>=1.4.16)", "psycopg2 (>=2.8.6)"]
+spss = ["pyreadstat (>=1.1.2)"]
+sql-other = ["SQLAlchemy (>=1.4.16)"]
+test = ["hypothesis (>=6.34.2)", "pytest (>=7.0.0)", "pytest-asyncio (>=0.17.0)", "pytest-xdist (>=2.2.0)"]
+xml = ["lxml (>=4.6.3)"]
+
+[[package]]
+name = "pillow"
+version = "9.3.0"
+description = "Python Imaging Library (Fork)"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "Pillow-9.3.0-1-cp37-cp37m-win32.whl", hash = "sha256:e6ea6b856a74d560d9326c0f5895ef8050126acfdc7ca08ad703eb0081e82b74"},
+    {file = "Pillow-9.3.0-1-cp37-cp37m-win_amd64.whl", hash = "sha256:32a44128c4bdca7f31de5be641187367fe2a450ad83b833ef78910397db491aa"},
+    {file = "Pillow-9.3.0-cp310-cp310-macosx_10_10_x86_64.whl", hash = "sha256:0b7257127d646ff8676ec8a15520013a698d1fdc48bc2a79ba4e53df792526f2"},
+    {file = "Pillow-9.3.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:b90f7616ea170e92820775ed47e136208e04c967271c9ef615b6fbd08d9af0e3"},
+    {file = "Pillow-9.3.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:68943d632f1f9e3dce98908e873b3a090f6cba1cbb1b892a9e8d97c938871fbe"},
+    {file = "Pillow-9.3.0-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:be55f8457cd1eac957af0c3f5ece7bc3f033f89b114ef30f710882717670b2a8"},
+    {file = "Pillow-9.3.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:5d77adcd56a42d00cc1be30843d3426aa4e660cab4a61021dc84467123f7a00c"},
+    {file = "Pillow-9.3.0-cp310-cp310-manylinux_2_28_aarch64.whl", hash = "sha256:829f97c8e258593b9daa80638aee3789b7df9da5cf1336035016d76f03b8860c"},
+    {file = "Pillow-9.3.0-cp310-cp310-manylinux_2_28_x86_64.whl", hash = "sha256:801ec82e4188e935c7f5e22e006d01611d6b41661bba9fe45b60e7ac1a8f84de"},
+    {file = "Pillow-9.3.0-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:871b72c3643e516db4ecf20efe735deb27fe30ca17800e661d769faab45a18d7"},
+    {file = "Pillow-9.3.0-cp310-cp310-win32.whl", hash = "sha256:655a83b0058ba47c7c52e4e2df5ecf484c1b0b0349805896dd350cbc416bdd91"},
+    {file = "Pillow-9.3.0-cp310-cp310-win_amd64.whl", hash = "sha256:9f47eabcd2ded7698106b05c2c338672d16a6f2a485e74481f524e2a23c2794b"},
+    {file = "Pillow-9.3.0-cp311-cp311-macosx_10_10_x86_64.whl", hash = "sha256:57751894f6618fd4308ed8e0c36c333e2f5469744c34729a27532b3db106ee20"},
+    {file = "Pillow-9.3.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:7db8b751ad307d7cf238f02101e8e36a128a6cb199326e867d1398067381bff4"},
+    {file = "Pillow-9.3.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:3033fbe1feb1b59394615a1cafaee85e49d01b51d54de0cbf6aa8e64182518a1"},
+    {file = "Pillow-9.3.0-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:22b012ea2d065fd163ca096f4e37e47cd8b59cf4b0fd47bfca6abb93df70b34c"},
+    {file = "Pillow-9.3.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b9a65733d103311331875c1dca05cb4606997fd33d6acfed695b1232ba1df193"},
+    {file = "Pillow-9.3.0-cp311-cp311-manylinux_2_28_aarch64.whl", hash = "sha256:502526a2cbfa431d9fc2a079bdd9061a2397b842bb6bc4239bb176da00993812"},
+    {file = "Pillow-9.3.0-cp311-cp311-manylinux_2_28_x86_64.whl", hash = "sha256:90fb88843d3902fe7c9586d439d1e8c05258f41da473952aa8b328d8b907498c"},
+    {file = "Pillow-9.3.0-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:89dca0ce00a2b49024df6325925555d406b14aa3efc2f752dbb5940c52c56b11"},
+    {file = "Pillow-9.3.0-cp311-cp311-win32.whl", hash = "sha256:3168434d303babf495d4ba58fc22d6604f6e2afb97adc6a423e917dab828939c"},
+    {file = "Pillow-9.3.0-cp311-cp311-win_amd64.whl", hash = "sha256:18498994b29e1cf86d505edcb7edbe814d133d2232d256db8c7a8ceb34d18cef"},
+    {file = "Pillow-9.3.0-cp37-cp37m-macosx_10_10_x86_64.whl", hash = "sha256:772a91fc0e03eaf922c63badeca75e91baa80fe2f5f87bdaed4280662aad25c9"},
+    {file = "Pillow-9.3.0-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:afa4107d1b306cdf8953edde0534562607fe8811b6c4d9a486298ad31de733b2"},
+    {file = "Pillow-9.3.0-cp37-cp37m-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:b4012d06c846dc2b80651b120e2cdd787b013deb39c09f407727ba90015c684f"},
+    {file = "Pillow-9.3.0-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:77ec3e7be99629898c9a6d24a09de089fa5356ee408cdffffe62d67bb75fdd72"},
+    {file = "Pillow-9.3.0-cp37-cp37m-manylinux_2_28_aarch64.whl", hash = "sha256:6c738585d7a9961d8c2821a1eb3dcb978d14e238be3d70f0a706f7fa9316946b"},
+    {file = "Pillow-9.3.0-cp37-cp37m-manylinux_2_28_x86_64.whl", hash = "sha256:828989c45c245518065a110434246c44a56a8b2b2f6347d1409c787e6e4651ee"},
+    {file = "Pillow-9.3.0-cp37-cp37m-win32.whl", hash = "sha256:82409ffe29d70fd733ff3c1025a602abb3e67405d41b9403b00b01debc4c9a29"},
+    {file = "Pillow-9.3.0-cp37-cp37m-win_amd64.whl", hash = "sha256:41e0051336807468be450d52b8edd12ac60bebaa97fe10c8b660f116e50b30e4"},
+    {file = "Pillow-9.3.0-cp38-cp38-macosx_10_10_x86_64.whl", hash = "sha256:b03ae6f1a1878233ac620c98f3459f79fd77c7e3c2b20d460284e1fb370557d4"},
+    {file = "Pillow-9.3.0-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:4390e9ce199fc1951fcfa65795f239a8a4944117b5935a9317fb320e7767b40f"},
+    {file = "Pillow-9.3.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:40e1ce476a7804b0fb74bcfa80b0a2206ea6a882938eaba917f7a0f004b42502"},
+    {file = "Pillow-9.3.0-cp38-cp38-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:a0a06a052c5f37b4ed81c613a455a81f9a3a69429b4fd7bb913c3fa98abefc20"},
+    {file = "Pillow-9.3.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:03150abd92771742d4a8cd6f2fa6246d847dcd2e332a18d0c15cc75bf6703040"},
+    {file = "Pillow-9.3.0-cp38-cp38-manylinux_2_28_aarch64.whl", hash = "sha256:15c42fb9dea42465dfd902fb0ecf584b8848ceb28b41ee2b58f866411be33f07"},
+    {file = "Pillow-9.3.0-cp38-cp38-manylinux_2_28_x86_64.whl", hash = "sha256:51e0e543a33ed92db9f5ef69a0356e0b1a7a6b6a71b80df99f1d181ae5875636"},
+    {file = "Pillow-9.3.0-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:3dd6caf940756101205dffc5367babf288a30043d35f80936f9bfb37f8355b32"},
+    {file = "Pillow-9.3.0-cp38-cp38-win32.whl", hash = "sha256:f1ff2ee69f10f13a9596480335f406dd1f70c3650349e2be67ca3139280cade0"},
+    {file = "Pillow-9.3.0-cp38-cp38-win_amd64.whl", hash = "sha256:276a5ca930c913f714e372b2591a22c4bd3b81a418c0f6635ba832daec1cbcfc"},
+    {file = "Pillow-9.3.0-cp39-cp39-macosx_10_10_x86_64.whl", hash = "sha256:73bd195e43f3fadecfc50c682f5055ec32ee2c933243cafbfdec69ab1aa87cad"},
+    {file = "Pillow-9.3.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:1c7c8ae3864846fc95f4611c78129301e203aaa2af813b703c55d10cc1628535"},
+    {file = "Pillow-9.3.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:2e0918e03aa0c72ea56edbb00d4d664294815aa11291a11504a377ea018330d3"},
+    {file = "Pillow-9.3.0-cp39-cp39-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:b0915e734b33a474d76c28e07292f196cdf2a590a0d25bcc06e64e545f2d146c"},
+    {file = "Pillow-9.3.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:af0372acb5d3598f36ec0914deed2a63f6bcdb7b606da04dc19a88d31bf0c05b"},
+    {file = "Pillow-9.3.0-cp39-cp39-manylinux_2_28_aarch64.whl", hash = "sha256:ad58d27a5b0262c0c19b47d54c5802db9b34d38bbf886665b626aff83c74bacd"},
+    {file = "Pillow-9.3.0-cp39-cp39-manylinux_2_28_x86_64.whl", hash = "sha256:97aabc5c50312afa5e0a2b07c17d4ac5e865b250986f8afe2b02d772567a380c"},
+    {file = "Pillow-9.3.0-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:9aaa107275d8527e9d6e7670b64aabaaa36e5b6bd71a1015ddd21da0d4e06448"},
+    {file = "Pillow-9.3.0-cp39-cp39-win32.whl", hash = "sha256:bac18ab8d2d1e6b4ce25e3424f709aceef668347db8637c2296bcf41acb7cf48"},
+    {file = "Pillow-9.3.0-cp39-cp39-win_amd64.whl", hash = "sha256:b472b5ea442148d1c3e2209f20f1e0bb0eb556538690fa70b5e1f79fa0ba8dc2"},
+    {file = "Pillow-9.3.0-pp37-pypy37_pp73-macosx_10_10_x86_64.whl", hash = "sha256:ab388aaa3f6ce52ac1cb8e122c4bd46657c15905904b3120a6248b5b8b0bc228"},
+    {file = "Pillow-9.3.0-pp37-pypy37_pp73-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:dbb8e7f2abee51cef77673be97760abff1674ed32847ce04b4af90f610144c7b"},
+    {file = "Pillow-9.3.0-pp37-pypy37_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bca31dd6014cb8b0b2db1e46081b0ca7d936f856da3b39744aef499db5d84d02"},
+    {file = "Pillow-9.3.0-pp37-pypy37_pp73-manylinux_2_28_x86_64.whl", hash = "sha256:c7025dce65566eb6e89f56c9509d4f628fddcedb131d9465cacd3d8bac337e7e"},
+    {file = "Pillow-9.3.0-pp37-pypy37_pp73-win_amd64.whl", hash = "sha256:ebf2029c1f464c59b8bdbe5143c79fa2045a581ac53679733d3a91d400ff9efb"},
+    {file = "Pillow-9.3.0-pp38-pypy38_pp73-macosx_10_10_x86_64.whl", hash = "sha256:b59430236b8e58840a0dfb4099a0e8717ffb779c952426a69ae435ca1f57210c"},
+    {file = "Pillow-9.3.0-pp38-pypy38_pp73-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:12ce4932caf2ddf3e41d17fc9c02d67126935a44b86df6a206cf0d7161548627"},
+    {file = "Pillow-9.3.0-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ae5331c23ce118c53b172fa64a4c037eb83c9165aba3a7ba9ddd3ec9fa64a699"},
+    {file = "Pillow-9.3.0-pp38-pypy38_pp73-manylinux_2_28_x86_64.whl", hash = "sha256:0b07fffc13f474264c336298d1b4ce01d9c5a011415b79d4ee5527bb69ae6f65"},
+    {file = "Pillow-9.3.0-pp38-pypy38_pp73-win_amd64.whl", hash = "sha256:073adb2ae23431d3b9bcbcff3fe698b62ed47211d0716b067385538a1b0f28b8"},
+    {file = "Pillow-9.3.0.tar.gz", hash = "sha256:c935a22a557a560108d780f9a0fc426dd7459940dc54faa49d83249c8d3e760f"},
+]
+
+[package.extras]
+docs = ["furo", "olefile", "sphinx (>=2.4)", "sphinx-copybutton", "sphinx-issues (>=3.0.1)", "sphinx-removed-in", "sphinxext-opengraph"]
+tests = ["check-manifest", "coverage", "defusedxml", "markdown2", "olefile", "packaging", "pyroma", "pytest", "pytest-cov", "pytest-timeout"]
+
+[[package]]
+name = "pkgutil-resolve-name"
+version = "1.3.10"
+description = "Resolve a name to an object."
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "pkgutil_resolve_name-1.3.10-py3-none-any.whl", hash = "sha256:ca27cc078d25c5ad71a9de0a7a330146c4e014c2462d9af19c6b828280649c5e"},
+    {file = "pkgutil_resolve_name-1.3.10.tar.gz", hash = "sha256:357d6c9e6a755653cfd78893817c0853af365dd51ec97f3d358a819373bbd174"},
+]
+
+[[package]]
+name = "platformdirs"
+version = "3.2.0"
+description = "A small Python package for determining appropriate platform-specific dirs, e.g. a \"user data dir\"."
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "platformdirs-3.2.0-py3-none-any.whl", hash = "sha256:ebe11c0d7a805086e99506aa331612429a72ca7cd52a1f0d277dc4adc20cb10e"},
+    {file = "platformdirs-3.2.0.tar.gz", hash = "sha256:d5b638ca397f25f979350ff789db335903d7ea010ab28903f57b27e1b16c2b08"},
+]
+
+[package.extras]
+docs = ["furo (>=2022.12.7)", "proselint (>=0.13)", "sphinx (>=6.1.3)", "sphinx-autodoc-typehints (>=1.22,!=1.23.4)"]
+test = ["appdirs (==1.4.4)", "covdefaults (>=2.3)", "pytest (>=7.2.2)", "pytest-cov (>=4)", "pytest-mock (>=3.10)"]
+
+[[package]]
+name = "pooch"
+version = "1.7.0"
+description = "\"Pooch manages your Python library's sample data files: it automatically downloads and stores them in a local directory, with support for versioning and corruption checks.\""
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "pooch-1.7.0-py3-none-any.whl", hash = "sha256:74258224fc33d58f53113cf955e8d51bf01386b91492927d0d1b6b341a765ad7"},
+    {file = "pooch-1.7.0.tar.gz", hash = "sha256:f174a1041b6447f0eef8860f76d17f60ed2f857dc0efa387a7f08228af05d998"},
+]
+
+[package.dependencies]
+packaging = ">=20.0"
+platformdirs = ">=2.5.0"
+requests = ">=2.19.0"
+
+[package.extras]
+progress = ["tqdm (>=4.41.0,<5.0.0)"]
+sftp = ["paramiko (>=2.7.0)"]
+xxhash = ["xxhash (>=1.4.3)"]
+
+[[package]]
+name = "portalocker"
+version = "2.7.0"
+description = "Wraps the portalocker recipe for easy usage"
+optional = false
+python-versions = ">=3.5"
+files = [
+    {file = "portalocker-2.7.0-py2.py3-none-any.whl", hash = "sha256:a07c5b4f3985c3cf4798369631fb7011adb498e2a46d8440efc75a8f29a0f983"},
+    {file = "portalocker-2.7.0.tar.gz", hash = "sha256:032e81d534a88ec1736d03f780ba073f047a06c478b06e2937486f334e955c51"},
+]
+
+[package.dependencies]
+pywin32 = {version = ">=226", markers = "platform_system == \"Windows\""}
+
+[package.extras]
+docs = ["sphinx (>=1.7.1)"]
+redis = ["redis"]
+tests = ["pytest (>=5.4.1)", "pytest-cov (>=2.8.1)", "pytest-mypy (>=0.8.0)", "pytest-timeout (>=2.1.0)", "redis", "sphinx (>=6.0.0)"]
+
+[[package]]
+name = "praat-parselmouth"
+version = "0.4.3"
+description = "Praat in Python, the Pythonic way"
+optional = false
+python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,>=2.7"
+files = [
+    {file = "praat-parselmouth-0.4.3.tar.gz", hash = "sha256:93538d0ba06444b68d18b793efb436b0d645c62c0397c4977c1d27b679aee168"},
+    {file = "praat_parselmouth-0.4.3-cp27-cp27m-macosx_10_9_x86_64.whl", hash = "sha256:124925f3e40a6d626d65789d449bdabe43078528efbee6f3a1df6e67db60c971"},
+    {file = "praat_parselmouth-0.4.3-cp27-cp27m-manylinux2010_i686.whl", hash = "sha256:0d3023d9b625c6b0a3cbe8a4f09cc23f666f9b9df40c59e33c4c9ca5b8ea1dac"},
+    {file = "praat_parselmouth-0.4.3-cp27-cp27m-manylinux2010_x86_64.whl", hash = "sha256:6841b9d9d2a614382cf186311610d663f0170ba20824296878eb98905b04899a"},
+    {file = "praat_parselmouth-0.4.3-cp27-cp27m-win32.whl", hash = "sha256:4fee56603cb57326457c6af779b89f96e7b2745114baa996659e1d52e5f245a3"},
+    {file = "praat_parselmouth-0.4.3-cp27-cp27m-win_amd64.whl", hash = "sha256:dc688749a0db4144936d3ed5180996500eb927bbf321192019ddee535fb97f3d"},
+    {file = "praat_parselmouth-0.4.3-cp27-cp27mu-manylinux2010_i686.whl", hash = "sha256:c0ccf73de16c0f69162952b0d1865d4dbc929de0f9b88a9d7aea57f454de3cb8"},
+    {file = "praat_parselmouth-0.4.3-cp27-cp27mu-manylinux2010_x86_64.whl", hash = "sha256:87fa2dd7f8b5dd5e3127af82e97b229ae2db8e1656525329224df4c0bffa024c"},
+    {file = "praat_parselmouth-0.4.3-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:2bc111055efccf2bb25039a7891ec9ef106b13ddc5680293659ff0b4c5f4353f"},
+    {file = "praat_parselmouth-0.4.3-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:cd38542210b1f381086b4a9424832b2330c42712e0fb7ea6c28c9200119c294b"},
+    {file = "praat_parselmouth-0.4.3-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:a536b37411c52171500984c97bfd66dc000701a7dc0807e11061b85a653a600a"},
+    {file = "praat_parselmouth-0.4.3-cp310-cp310-manylinux_2_12_i686.manylinux2010_i686.whl", hash = "sha256:6ea1ab0632eff129516f147041aaf7874e50770561a2e9b9c81913b6de243f2a"},
+    {file = "praat_parselmouth-0.4.3-cp310-cp310-manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:543ba3deb32502e93074b76b1cfb3f09e598e5d9f74a0345fa5b3928fedb5a51"},
+    {file = "praat_parselmouth-0.4.3-cp310-cp310-win32.whl", hash = "sha256:e0addf774a57d57a54df2b06de04ad0de34e81a3abfda03f744c732776c779ec"},
+    {file = "praat_parselmouth-0.4.3-cp310-cp310-win_amd64.whl", hash = "sha256:fc497357aeea2e3cbca2fb308d66b9de9739dc6b320ca2661ca6250f7a7489bd"},
+    {file = "praat_parselmouth-0.4.3-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:afac52cb7a72cda7fe2ec1d9573d8f402786abcb06bd7a22f2ca240f95e33263"},
+    {file = "praat_parselmouth-0.4.3-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:b2261a79c2dc5387a7a678ec304ef8dd00ed93d9e028148bbb064fd0ac222a3a"},
+    {file = "praat_parselmouth-0.4.3-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:de31b458d3c1ca7ee45506871a38fdc3aec44526c065552adf8bec2876e816bd"},
+    {file = "praat_parselmouth-0.4.3-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:63ff24e045bed7c44f140fb7bab910d89fd3a45b7e8afe5b5e936aa2eea62904"},
+    {file = "praat_parselmouth-0.4.3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a40c51c628235c54c8956306fc58fd14cd04127d85359134ef73ef35ff19d651"},
+    {file = "praat_parselmouth-0.4.3-cp311-cp311-win32.whl", hash = "sha256:f8ad9ee3be60d33f1ad593ec5f99466b1c266e00d29a5ec5787f969c618a7a9a"},
+    {file = "praat_parselmouth-0.4.3-cp311-cp311-win_amd64.whl", hash = "sha256:c32b1f3632e69ed67f501c635fff37ad72e1eae4ddd1c2c0827c4690c06ee990"},
+    {file = "praat_parselmouth-0.4.3-cp35-cp35m-macosx_10_9_x86_64.whl", hash = "sha256:1dcb6f55376f193c83d123953a55de471bcadd756af3b157c13d455b0c052999"},
+    {file = "praat_parselmouth-0.4.3-cp35-cp35m-manylinux2010_i686.whl", hash = "sha256:0970facd26b771f5799a396a0e54d12a69fbf8904a4f6ae0442f3831175e4508"},
+    {file = "praat_parselmouth-0.4.3-cp35-cp35m-manylinux2010_x86_64.whl", hash = "sha256:5c1104f41d9fef48cd44247738b9c8735e10a12ba0a1860e478e0bd69201813e"},
+    {file = "praat_parselmouth-0.4.3-cp35-cp35m-win32.whl", hash = "sha256:3d12469e301d9a25f29f6cb5427aa9a1276e7f2f1edf1a3caede69a84c46170f"},
+    {file = "praat_parselmouth-0.4.3-cp35-cp35m-win_amd64.whl", hash = "sha256:c4142faf664dd6c7f1773d04331b278d92e17064eaaef09132954f72a9041ea0"},
+    {file = "praat_parselmouth-0.4.3-cp36-cp36m-macosx_10_9_x86_64.whl", hash = "sha256:5ea2079d519e8d42ed8d2de3c4f68803110060a8ae5d1c56df795c600aa1c3be"},
+    {file = "praat_parselmouth-0.4.3-cp36-cp36m-manylinux_2_12_i686.manylinux2010_i686.whl", hash = "sha256:2e88f00b740548cf3de5768b2d06e296e525164ea71ccc991920f41f2e277ad2"},
+    {file = "praat_parselmouth-0.4.3-cp36-cp36m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:2da226bccd52fd81223eb94a7ea43a1a7588e4384ea65ce0818329b73ef8df6d"},
+    {file = "praat_parselmouth-0.4.3-cp36-cp36m-win32.whl", hash = "sha256:0f3af0413992398ac613b0eefdfbcb8cad064c36a28b972300a2bb760523c109"},
+    {file = "praat_parselmouth-0.4.3-cp36-cp36m-win_amd64.whl", hash = "sha256:e0ed79941b6e37a440860511767eedd85ec003060870d10ff1f98773b2a268ae"},
+    {file = "praat_parselmouth-0.4.3-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:10f3113ad4f5f6df5fe81d4080ca3ad46de2fe0fdb8ebbcad1ba884b1cae3b9d"},
+    {file = "praat_parselmouth-0.4.3-cp37-cp37m-manylinux_2_12_i686.manylinux2010_i686.whl", hash = "sha256:6e9338f7a1b304390014bb2eec619e5a306527a4df438e68439c92aa968627dc"},
+    {file = "praat_parselmouth-0.4.3-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:cb3798b2ca8163444662b6ae84a74b1add38b2c04e5af8d07bde55cf0335300a"},
+    {file = "praat_parselmouth-0.4.3-cp37-cp37m-win32.whl", hash = "sha256:d947f9d1fb092b91acca1259ce4dd62ff4f456338958fd1fd41ee65efc53ca2c"},
+    {file = "praat_parselmouth-0.4.3-cp37-cp37m-win_amd64.whl", hash = "sha256:2f3e026f590aeec8f68921359f56a42efa43076942f271244bee57fd22db8eef"},
+    {file = "praat_parselmouth-0.4.3-cp38-cp38-macosx_10_9_universal2.whl", hash = "sha256:28844229dab2a9335629b4526188b9540d02208856f48b1a46776279c022f937"},
+    {file = "praat_parselmouth-0.4.3-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:410748af84eb8c2eb69e408e300694a45090ed7c4f31375c4ec75a8c18f87169"},
+    {file = "praat_parselmouth-0.4.3-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:30ff6f17babad25b9d6ab086465a54494eef9d1b4368b0722230c5282be2bf94"},
+    {file = "praat_parselmouth-0.4.3-cp38-cp38-manylinux_2_12_i686.manylinux2010_i686.whl", hash = "sha256:ff7096bc3e87a8f719e66f5e16a90e2f6de445612abd234f86837d390b947421"},
+    {file = "praat_parselmouth-0.4.3-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:f41d121c4d2322ff12808bb2c4490609f750f89064170e327dfd74fca13cc212"},
+    {file = "praat_parselmouth-0.4.3-cp38-cp38-win32.whl", hash = "sha256:9af9945db11fab0e1ed29ad20f7c97a3e7a8d016328ad6d7237a0d7819db075e"},
+    {file = "praat_parselmouth-0.4.3-cp38-cp38-win_amd64.whl", hash = "sha256:ae0c63c432e8216d7c70da44131f51c845fb81d48ac04eb5f39ebcfae34624be"},
+    {file = "praat_parselmouth-0.4.3-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:8e25658af5a87ed502753de6924c51bf3400d4078e67a611b5874ab08b478fdb"},
+    {file = "praat_parselmouth-0.4.3-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:7aa2ffd0c6e47feda35343a9d6722b2558f3677a4a51bf5ec864f27ab80e2f42"},
+    {file = "praat_parselmouth-0.4.3-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:3b245d9457ab39f12142da160cda12c4c2a58d9b916e5bb33e6b3ac267882d46"},
+    {file = "praat_parselmouth-0.4.3-cp39-cp39-manylinux_2_12_i686.manylinux2010_i686.whl", hash = "sha256:da9779a694941074bc5b199dd3cb41ad4af3306552f06af8dbfdea6ab0a87dec"},
+    {file = "praat_parselmouth-0.4.3-cp39-cp39-manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:cfa141c04fd8a0477f91c168878112098a25cbac7ac4a20de627bc9293ee4667"},
+    {file = "praat_parselmouth-0.4.3-cp39-cp39-win32.whl", hash = "sha256:6941fe602802fd57ecbedecd612b41493b7d1c6bf722ac0cbf3f47f805fbbd43"},
+    {file = "praat_parselmouth-0.4.3-cp39-cp39-win_amd64.whl", hash = "sha256:5252496e0391754a642973837670c56ecd39c8e0a1f7ec6e6b60b0cd2cc9f51d"},
+    {file = "praat_parselmouth-0.4.3-pp27-pypy_73-macosx_10_9_x86_64.whl", hash = "sha256:fd7c143c6511807b67c92b3ab94733746c0ae3a7b4ba52d6763585c4d459061d"},
+    {file = "praat_parselmouth-0.4.3-pp27-pypy_73-manylinux2010_x86_64.whl", hash = "sha256:7ad0739ad6c102817c7d43b67b7270f78cb431eb72b6ecd9a17e354d1b379deb"},
+    {file = "praat_parselmouth-0.4.3-pp27-pypy_73-win32.whl", hash = "sha256:f5e98ec1f41efba90bedab358cff8e6a3c6473978e1f42b55d0977e580efe673"},
+    {file = "praat_parselmouth-0.4.3-pp36-pypy36_pp73-macosx_10_9_x86_64.whl", hash = "sha256:7b58c1c8fd967446f6d74775b5d9bceadfe35a928fa5f192d4d03d80cb005d92"},
+    {file = "praat_parselmouth-0.4.3-pp36-pypy36_pp73-manylinux2010_x86_64.whl", hash = "sha256:d217df07c770156fa284aff3e7a5c11eb43e37f0226730d729d6b45be8a7c4d7"},
+    {file = "praat_parselmouth-0.4.3-pp36-pypy36_pp73-win32.whl", hash = "sha256:29cb47438989f8155c3b3dca987afd48999dec71e4b79564aa7e922c3c5c1f9a"},
+    {file = "praat_parselmouth-0.4.3-pp37-pypy37_pp73-macosx_10_9_x86_64.whl", hash = "sha256:5f772b4a097654883f4bba41efae419f9ebdd5e83ef7a857e547100d26663e2c"},
+    {file = "praat_parselmouth-0.4.3-pp37-pypy37_pp73-manylinux_2_12_i686.manylinux2010_i686.whl", hash = "sha256:bf9634a6986732dc43a88b3a16a0000cff903da1db6556b7959a6a4897f25570"},
+    {file = "praat_parselmouth-0.4.3-pp37-pypy37_pp73-manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:fab1bbb6a88f47cb5d0db07a4fd6d88b9294d2775a7556aeb459e96ac372e29f"},
+    {file = "praat_parselmouth-0.4.3-pp37-pypy37_pp73-win32.whl", hash = "sha256:261f03f95f25943da2cf746599e47acfcf79b7fc823c871571901d6c97bad948"},
+    {file = "praat_parselmouth-0.4.3-pp37-pypy37_pp73-win_amd64.whl", hash = "sha256:199b8df2659a1e6f30e9ae3064b0a28a661d834d2bccb56d22051c40cc348817"},
+    {file = "praat_parselmouth-0.4.3-pp38-pypy38_pp73-macosx_10_9_x86_64.whl", hash = "sha256:ef1f3f6bd08cc410d0d595f6a9c7dd72558e30ad3bd7949c94ea4e07a2de2605"},
+    {file = "praat_parselmouth-0.4.3-pp38-pypy38_pp73-manylinux_2_12_i686.manylinux2010_i686.whl", hash = "sha256:28a61b7a3cf95a53554dd3ebb4f48e991d4b913ae2d2fbc3868a4e864d69794f"},
+    {file = "praat_parselmouth-0.4.3-pp38-pypy38_pp73-manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:488833ee33690fa1a57a3c429d286e42e6882748f5c3d28dc50889abec12b8c2"},
+    {file = "praat_parselmouth-0.4.3-pp38-pypy38_pp73-win_amd64.whl", hash = "sha256:10f181e199c47fa90fe7cad065275f7f3ccda2de6febf86394cf96aa48531079"},
+    {file = "praat_parselmouth-0.4.3-pp39-pypy39_pp73-macosx_10_9_x86_64.whl", hash = "sha256:52702bc5cdf59b2b4db87448fe9042307e5ebce6b67ee5ea55c2b8627ce803e0"},
+    {file = "praat_parselmouth-0.4.3-pp39-pypy39_pp73-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:a7d4f5d7c701517986654365f0a41b8b4a610a2ddc0365da60e48c098774259b"},
+    {file = "praat_parselmouth-0.4.3-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4dc013608a536ad74efdc3242421cabfcb8cb2e9cd1259ec9de9aeaa141c2d14"},
+    {file = "praat_parselmouth-0.4.3-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:d593065ed1500d305d9cf3d20f5ac7e3671061c3c073ef6e94e97817a664d399"},
+]
+
+[package.dependencies]
+numpy = ">=1.7.0"
+
+[[package]]
+name = "protobuf"
+version = "3.20.3"
+description = "Protocol Buffers"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "protobuf-3.20.3-cp310-cp310-manylinux2014_aarch64.whl", hash = "sha256:f4bd856d702e5b0d96a00ec6b307b0f51c1982c2bf9c0052cf9019e9a544ba99"},
+    {file = "protobuf-3.20.3-cp310-cp310-manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:9aae4406ea63d825636cc11ffb34ad3379335803216ee3a856787bcf5ccc751e"},
+    {file = "protobuf-3.20.3-cp310-cp310-win32.whl", hash = "sha256:28545383d61f55b57cf4df63eebd9827754fd2dc25f80c5253f9184235db242c"},
+    {file = "protobuf-3.20.3-cp310-cp310-win_amd64.whl", hash = "sha256:67a3598f0a2dcbc58d02dd1928544e7d88f764b47d4a286202913f0b2801c2e7"},
+    {file = "protobuf-3.20.3-cp36-cp36m-manylinux_2_5_x86_64.manylinux1_x86_64.whl", hash = "sha256:899dc660cd599d7352d6f10d83c95df430a38b410c1b66b407a6b29265d66469"},
+    {file = "protobuf-3.20.3-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:e64857f395505ebf3d2569935506ae0dfc4a15cb80dc25261176c784662cdcc4"},
+    {file = "protobuf-3.20.3-cp37-cp37m-manylinux2014_aarch64.whl", hash = "sha256:d9e4432ff660d67d775c66ac42a67cf2453c27cb4d738fc22cb53b5d84c135d4"},
+    {file = "protobuf-3.20.3-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.whl", hash = "sha256:74480f79a023f90dc6e18febbf7b8bac7508420f2006fabd512013c0c238f454"},
+    {file = "protobuf-3.20.3-cp37-cp37m-win32.whl", hash = "sha256:b6cc7ba72a8850621bfec987cb72623e703b7fe2b9127a161ce61e61558ad905"},
+    {file = "protobuf-3.20.3-cp37-cp37m-win_amd64.whl", hash = "sha256:8c0c984a1b8fef4086329ff8dd19ac77576b384079247c770f29cc8ce3afa06c"},
+    {file = "protobuf-3.20.3-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:de78575669dddf6099a8a0f46a27e82a1783c557ccc38ee620ed8cc96d3be7d7"},
+    {file = "protobuf-3.20.3-cp38-cp38-manylinux2014_aarch64.whl", hash = "sha256:f4c42102bc82a51108e449cbb32b19b180022941c727bac0cfd50170341f16ee"},
+    {file = "protobuf-3.20.3-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.whl", hash = "sha256:44246bab5dd4b7fbd3c0c80b6f16686808fab0e4aca819ade6e8d294a29c7050"},
+    {file = "protobuf-3.20.3-cp38-cp38-win32.whl", hash = "sha256:c02ce36ec760252242a33967d51c289fd0e1c0e6e5cc9397e2279177716add86"},
+    {file = "protobuf-3.20.3-cp38-cp38-win_amd64.whl", hash = "sha256:447d43819997825d4e71bf5769d869b968ce96848b6479397e29fc24c4a5dfe9"},
+    {file = "protobuf-3.20.3-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:398a9e0c3eaceb34ec1aee71894ca3299605fa8e761544934378bbc6c97de23b"},
+    {file = "protobuf-3.20.3-cp39-cp39-manylinux2014_aarch64.whl", hash = "sha256:bf01b5720be110540be4286e791db73f84a2b721072a3711efff6c324cdf074b"},
+    {file = "protobuf-3.20.3-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.whl", hash = "sha256:daa564862dd0d39c00f8086f88700fdbe8bc717e993a21e90711acfed02f2402"},
+    {file = "protobuf-3.20.3-cp39-cp39-win32.whl", hash = "sha256:819559cafa1a373b7096a482b504ae8a857c89593cf3a25af743ac9ecbd23480"},
+    {file = "protobuf-3.20.3-cp39-cp39-win_amd64.whl", hash = "sha256:03038ac1cfbc41aa21f6afcbcd357281d7521b4157926f30ebecc8d4ea59dcb7"},
+    {file = "protobuf-3.20.3-py2.py3-none-any.whl", hash = "sha256:a7ca6d488aa8ff7f329d4c545b2dbad8ac31464f1d8b1c87ad1346717731e4db"},
+    {file = "protobuf-3.20.3.tar.gz", hash = "sha256:2e3427429c9cffebf259491be0af70189607f365c2f41c7c3764af6f337105f2"},
+]
+
+[[package]]
+name = "pyasn1"
+version = "0.4.8"
+description = "ASN.1 types and codecs"
+optional = false
+python-versions = "*"
+files = [
+    {file = "pyasn1-0.4.8-py2.py3-none-any.whl", hash = "sha256:39c7e2ec30515947ff4e87fb6f456dfc6e84857d34be479c9d4a4ba4bf46aa5d"},
+    {file = "pyasn1-0.4.8.tar.gz", hash = "sha256:aef77c9fb94a3ac588e87841208bdec464471d9871bd5050a287cc9a475cd0ba"},
+]
+
+[[package]]
+name = "pyasn1-modules"
+version = "0.2.8"
+description = "A collection of ASN.1-based protocols modules."
+optional = false
+python-versions = "*"
+files = [
+    {file = "pyasn1-modules-0.2.8.tar.gz", hash = "sha256:905f84c712230b2c592c19470d3ca8d552de726050d1d1716282a1f6146be65e"},
+    {file = "pyasn1_modules-0.2.8-py2.py3-none-any.whl", hash = "sha256:a50b808ffeb97cb3601dd25981f6b016cbb3d31fbf57a8b8a87428e6158d0c74"},
+]
+
+[package.dependencies]
+pyasn1 = ">=0.4.6,<0.5.0"
+
+[[package]]
+name = "pycparser"
+version = "2.21"
+description = "C parser in Python"
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
+files = [
+    {file = "pycparser-2.21-py2.py3-none-any.whl", hash = "sha256:8ee45429555515e1f6b185e78100aea234072576aa43ab53aefcae078162fca9"},
+    {file = "pycparser-2.21.tar.gz", hash = "sha256:e644fdec12f7872f86c58ff790da456218b10f863970249516d60a5eaca77206"},
+]
+
+[[package]]
+name = "pydantic"
+version = "1.10.7"
+description = "Data validation and settings management using python type hints"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "pydantic-1.10.7-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:e79e999e539872e903767c417c897e729e015872040e56b96e67968c3b918b2d"},
+    {file = "pydantic-1.10.7-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:01aea3a42c13f2602b7ecbbea484a98169fb568ebd9e247593ea05f01b884b2e"},
+    {file = "pydantic-1.10.7-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:516f1ed9bc2406a0467dd777afc636c7091d71f214d5e413d64fef45174cfc7a"},
+    {file = "pydantic-1.10.7-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:ae150a63564929c675d7f2303008d88426a0add46efd76c3fc797cd71cb1b46f"},
+    {file = "pydantic-1.10.7-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:ecbbc51391248116c0a055899e6c3e7ffbb11fb5e2a4cd6f2d0b93272118a209"},
+    {file = "pydantic-1.10.7-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:f4a2b50e2b03d5776e7f21af73e2070e1b5c0d0df255a827e7c632962f8315af"},
+    {file = "pydantic-1.10.7-cp310-cp310-win_amd64.whl", hash = "sha256:a7cd2251439988b413cb0a985c4ed82b6c6aac382dbaff53ae03c4b23a70e80a"},
+    {file = "pydantic-1.10.7-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:68792151e174a4aa9e9fc1b4e653e65a354a2fa0fed169f7b3d09902ad2cb6f1"},
+    {file = "pydantic-1.10.7-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:dfe2507b8ef209da71b6fb5f4e597b50c5a34b78d7e857c4f8f3115effaef5fe"},
+    {file = "pydantic-1.10.7-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:10a86d8c8db68086f1e30a530f7d5f83eb0685e632e411dbbcf2d5c0150e8dcd"},
+    {file = "pydantic-1.10.7-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:d75ae19d2a3dbb146b6f324031c24f8a3f52ff5d6a9f22f0683694b3afcb16fb"},
+    {file = "pydantic-1.10.7-cp311-cp311-musllinux_1_1_i686.whl", hash = "sha256:464855a7ff7f2cc2cf537ecc421291b9132aa9c79aef44e917ad711b4a93163b"},
+    {file = "pydantic-1.10.7-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:193924c563fae6ddcb71d3f06fa153866423ac1b793a47936656e806b64e24ca"},
+    {file = "pydantic-1.10.7-cp311-cp311-win_amd64.whl", hash = "sha256:b4a849d10f211389502059c33332e91327bc154acc1845f375a99eca3afa802d"},
+    {file = "pydantic-1.10.7-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:cc1dde4e50a5fc1336ee0581c1612215bc64ed6d28d2c7c6f25d2fe3e7c3e918"},
+    {file = "pydantic-1.10.7-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e0cfe895a504c060e5d36b287ee696e2fdad02d89e0d895f83037245218a87fe"},
+    {file = "pydantic-1.10.7-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:670bb4683ad1e48b0ecb06f0cfe2178dcf74ff27921cdf1606e527d2617a81ee"},
+    {file = "pydantic-1.10.7-cp37-cp37m-musllinux_1_1_i686.whl", hash = "sha256:950ce33857841f9a337ce07ddf46bc84e1c4946d2a3bba18f8280297157a3fd1"},
+    {file = "pydantic-1.10.7-cp37-cp37m-musllinux_1_1_x86_64.whl", hash = "sha256:c15582f9055fbc1bfe50266a19771bbbef33dd28c45e78afbe1996fd70966c2a"},
+    {file = "pydantic-1.10.7-cp37-cp37m-win_amd64.whl", hash = "sha256:82dffb306dd20bd5268fd6379bc4bfe75242a9c2b79fec58e1041fbbdb1f7914"},
+    {file = "pydantic-1.10.7-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:8c7f51861d73e8b9ddcb9916ae7ac39fb52761d9ea0df41128e81e2ba42886cd"},
+    {file = "pydantic-1.10.7-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:6434b49c0b03a51021ade5c4daa7d70c98f7a79e95b551201fff682fc1661245"},
+    {file = "pydantic-1.10.7-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:64d34ab766fa056df49013bb6e79921a0265204c071984e75a09cbceacbbdd5d"},
+    {file = "pydantic-1.10.7-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:701daea9ffe9d26f97b52f1d157e0d4121644f0fcf80b443248434958fd03dc3"},
+    {file = "pydantic-1.10.7-cp38-cp38-musllinux_1_1_i686.whl", hash = "sha256:cf135c46099ff3f919d2150a948ce94b9ce545598ef2c6c7bf55dca98a304b52"},
+    {file = "pydantic-1.10.7-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:b0f85904f73161817b80781cc150f8b906d521fa11e3cdabae19a581c3606209"},
+    {file = "pydantic-1.10.7-cp38-cp38-win_amd64.whl", hash = "sha256:9f6f0fd68d73257ad6685419478c5aece46432f4bdd8d32c7345f1986496171e"},
+    {file = "pydantic-1.10.7-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:c230c0d8a322276d6e7b88c3f7ce885f9ed16e0910354510e0bae84d54991143"},
+    {file = "pydantic-1.10.7-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:976cae77ba6a49d80f461fd8bba183ff7ba79f44aa5cfa82f1346b5626542f8e"},
+    {file = "pydantic-1.10.7-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7d45fc99d64af9aaf7e308054a0067fdcd87ffe974f2442312372dfa66e1001d"},
+    {file = "pydantic-1.10.7-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:d2a5ebb48958754d386195fe9e9c5106f11275867051bf017a8059410e9abf1f"},
+    {file = "pydantic-1.10.7-cp39-cp39-musllinux_1_1_i686.whl", hash = "sha256:abfb7d4a7cd5cc4e1d1887c43503a7c5dd608eadf8bc615413fc498d3e4645cd"},
+    {file = "pydantic-1.10.7-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:80b1fab4deb08a8292d15e43a6edccdffa5377a36a4597bb545b93e79c5ff0a5"},
+    {file = "pydantic-1.10.7-cp39-cp39-win_amd64.whl", hash = "sha256:d71e69699498b020ea198468e2480a2f1e7433e32a3a99760058c6520e2bea7e"},
+    {file = "pydantic-1.10.7-py3-none-any.whl", hash = "sha256:0cd181f1d0b1d00e2b705f1bf1ac7799a2d938cce3376b8007df62b29be3c2c6"},
+    {file = "pydantic-1.10.7.tar.gz", hash = "sha256:cfc83c0678b6ba51b0532bea66860617c4cd4251ecf76e9846fa5a9f3454e97e"},
+]
+
+[package.dependencies]
+typing-extensions = ">=4.2.0"
+
+[package.extras]
+dotenv = ["python-dotenv (>=0.10.4)"]
+email = ["email-validator (>=1.0.3)"]
+
+[[package]]
+name = "pydub"
+version = "0.25.1"
+description = "Manipulate audio with an simple and easy high level interface"
+optional = false
+python-versions = "*"
+files = [
+    {file = "pydub-0.25.1-py2.py3-none-any.whl", hash = "sha256:65617e33033874b59d87db603aa1ed450633288aefead953b30bded59cb599a6"},
+    {file = "pydub-0.25.1.tar.gz", hash = "sha256:980a33ce9949cab2a569606b65674d748ecbca4f0796887fd6f46173a7b0d30f"},
+]
+
+[[package]]
+name = "pygments"
+version = "2.15.1"
+description = "Pygments is a syntax highlighting package written in Python."
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "Pygments-2.15.1-py3-none-any.whl", hash = "sha256:db2db3deb4b4179f399a09054b023b6a586b76499d36965813c71aa8ed7b5fd1"},
+    {file = "Pygments-2.15.1.tar.gz", hash = "sha256:8ace4d3c1dd481894b2005f560ead0f9f19ee64fe983366be1a21e171d12775c"},
+]
+
+[package.extras]
+plugins = ["importlib-metadata"]
+
+[[package]]
+name = "pyparsing"
+version = "3.0.9"
+description = "pyparsing module - Classes and methods to define and execute parsing grammars"
+optional = false
+python-versions = ">=3.6.8"
+files = [
+    {file = "pyparsing-3.0.9-py3-none-any.whl", hash = "sha256:5026bae9a10eeaefb61dab2f09052b9f4307d44aee4eda64b309723d8d206bbc"},
+    {file = "pyparsing-3.0.9.tar.gz", hash = "sha256:2b020ecf7d21b687f219b71ecad3631f644a47f01403fa1d1036b0c6416d70fb"},
+]
+
+[package.extras]
+diagrams = ["jinja2", "railroad-diagrams"]
+
+[[package]]
+name = "pyrsistent"
+version = "0.19.3"
+description = "Persistent/Functional/Immutable data structures"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "pyrsistent-0.19.3-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:20460ac0ea439a3e79caa1dbd560344b64ed75e85d8703943e0b66c2a6150e4a"},
+    {file = "pyrsistent-0.19.3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4c18264cb84b5e68e7085a43723f9e4c1fd1d935ab240ce02c0324a8e01ccb64"},
+    {file = "pyrsistent-0.19.3-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:4b774f9288dda8d425adb6544e5903f1fb6c273ab3128a355c6b972b7df39dcf"},
+    {file = "pyrsistent-0.19.3-cp310-cp310-win32.whl", hash = "sha256:5a474fb80f5e0d6c9394d8db0fc19e90fa540b82ee52dba7d246a7791712f74a"},
+    {file = "pyrsistent-0.19.3-cp310-cp310-win_amd64.whl", hash = "sha256:49c32f216c17148695ca0e02a5c521e28a4ee6c5089f97e34fe24163113722da"},
+    {file = "pyrsistent-0.19.3-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:f0774bf48631f3a20471dd7c5989657b639fd2d285b861237ea9e82c36a415a9"},
+    {file = "pyrsistent-0.19.3-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:3ab2204234c0ecd8b9368dbd6a53e83c3d4f3cab10ecaf6d0e772f456c442393"},
+    {file = "pyrsistent-0.19.3-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:e42296a09e83028b3476f7073fcb69ffebac0e66dbbfd1bd847d61f74db30f19"},
+    {file = "pyrsistent-0.19.3-cp311-cp311-win32.whl", hash = "sha256:64220c429e42a7150f4bfd280f6f4bb2850f95956bde93c6fda1b70507af6ef3"},
+    {file = "pyrsistent-0.19.3-cp311-cp311-win_amd64.whl", hash = "sha256:016ad1afadf318eb7911baa24b049909f7f3bb2c5b1ed7b6a8f21db21ea3faa8"},
+    {file = "pyrsistent-0.19.3-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:c4db1bd596fefd66b296a3d5d943c94f4fac5bcd13e99bffe2ba6a759d959a28"},
+    {file = "pyrsistent-0.19.3-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:aeda827381f5e5d65cced3024126529ddc4289d944f75e090572c77ceb19adbf"},
+    {file = "pyrsistent-0.19.3-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:42ac0b2f44607eb92ae88609eda931a4f0dfa03038c44c772e07f43e738bcac9"},
+    {file = "pyrsistent-0.19.3-cp37-cp37m-win32.whl", hash = "sha256:e8f2b814a3dc6225964fa03d8582c6e0b6650d68a232df41e3cc1b66a5d2f8d1"},
+    {file = "pyrsistent-0.19.3-cp37-cp37m-win_amd64.whl", hash = "sha256:c9bb60a40a0ab9aba40a59f68214eed5a29c6274c83b2cc206a359c4a89fa41b"},
+    {file = "pyrsistent-0.19.3-cp38-cp38-macosx_10_9_universal2.whl", hash = "sha256:a2471f3f8693101975b1ff85ffd19bb7ca7dd7c38f8a81701f67d6b4f97b87d8"},
+    {file = "pyrsistent-0.19.3-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:cc5d149f31706762c1f8bda2e8c4f8fead6e80312e3692619a75301d3dbb819a"},
+    {file = "pyrsistent-0.19.3-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:3311cb4237a341aa52ab8448c27e3a9931e2ee09561ad150ba94e4cfd3fc888c"},
+    {file = "pyrsistent-0.19.3-cp38-cp38-win32.whl", hash = "sha256:f0e7c4b2f77593871e918be000b96c8107da48444d57005b6a6bc61fb4331b2c"},
+    {file = "pyrsistent-0.19.3-cp38-cp38-win_amd64.whl", hash = "sha256:c147257a92374fde8498491f53ffa8f4822cd70c0d85037e09028e478cababb7"},
+    {file = "pyrsistent-0.19.3-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:b735e538f74ec31378f5a1e3886a26d2ca6351106b4dfde376a26fc32a044edc"},
+    {file = "pyrsistent-0.19.3-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:99abb85579e2165bd8522f0c0138864da97847875ecbd45f3e7e2af569bfc6f2"},
+    {file = "pyrsistent-0.19.3-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:3a8cb235fa6d3fd7aae6a4f1429bbb1fec1577d978098da1252f0489937786f3"},
+    {file = "pyrsistent-0.19.3-cp39-cp39-win32.whl", hash = "sha256:c74bed51f9b41c48366a286395c67f4e894374306b197e62810e0fdaf2364da2"},
+    {file = "pyrsistent-0.19.3-cp39-cp39-win_amd64.whl", hash = "sha256:878433581fc23e906d947a6814336eee031a00e6defba224234169ae3d3d6a98"},
+    {file = "pyrsistent-0.19.3-py3-none-any.whl", hash = "sha256:ccf0d6bd208f8111179f0c26fdf84ed7c3891982f2edaeae7422575f47e66b64"},
+    {file = "pyrsistent-0.19.3.tar.gz", hash = "sha256:1a2994773706bbb4995c31a97bc94f1418314923bd1048c6d964837040376440"},
+]
+
+[[package]]
+name = "python-dateutil"
+version = "2.8.2"
+description = "Extensions to the standard Python datetime module"
+optional = false
+python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,>=2.7"
+files = [
+    {file = "python-dateutil-2.8.2.tar.gz", hash = "sha256:0123cacc1627ae19ddf3c27a5de5bd67ee4586fbdd6440d9748f8abb483d3e86"},
+    {file = "python_dateutil-2.8.2-py2.py3-none-any.whl", hash = "sha256:961d03dc3453ebbc59dbdea9e4e11c5651520a876d0f4db161e8674aae935da9"},
+]
+
+[package.dependencies]
+six = ">=1.5"
+
+[[package]]
+name = "python-multipart"
+version = "0.0.6"
+description = "A streaming multipart parser for Python"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "python_multipart-0.0.6-py3-none-any.whl", hash = "sha256:ee698bab5ef148b0a760751c261902cd096e57e10558e11aca17646b74ee1c18"},
+    {file = "python_multipart-0.0.6.tar.gz", hash = "sha256:e9925a80bb668529f1b67c7fdb0a5dacdd7cbfc6fb0bff3ea443fe22bdd62132"},
+]
+
+[package.extras]
+dev = ["atomicwrites (==1.2.1)", "attrs (==19.2.0)", "coverage (==6.5.0)", "hatch", "invoke (==1.7.3)", "more-itertools (==4.3.0)", "pbr (==4.3.0)", "pluggy (==1.0.0)", "py (==1.11.0)", "pytest (==7.2.0)", "pytest-cov (==4.0.0)", "pytest-timeout (==2.1.0)", "pyyaml (==5.1)"]
+
+[[package]]
+name = "pytz"
+version = "2023.3"
+description = "World timezone definitions, modern and historical"
+optional = false
+python-versions = "*"
+files = [
+    {file = "pytz-2023.3-py2.py3-none-any.whl", hash = "sha256:a151b3abb88eda1d4e34a9814df37de2a80e301e68ba0fd856fb9b46bfbbbffb"},
+    {file = "pytz-2023.3.tar.gz", hash = "sha256:1d8ce29db189191fb55338ee6d0387d82ab59f3d00eac103412d64e0ebd0c588"},
+]
+
+[[package]]
+name = "pywin32"
+version = "306"
+description = "Python for Window Extensions"
+optional = false
+python-versions = "*"
+files = [
+    {file = "pywin32-306-cp310-cp310-win32.whl", hash = "sha256:06d3420a5155ba65f0b72f2699b5bacf3109f36acbe8923765c22938a69dfc8d"},
+    {file = "pywin32-306-cp310-cp310-win_amd64.whl", hash = "sha256:84f4471dbca1887ea3803d8848a1616429ac94a4a8d05f4bc9c5dcfd42ca99c8"},
+    {file = "pywin32-306-cp311-cp311-win32.whl", hash = "sha256:e65028133d15b64d2ed8f06dd9fbc268352478d4f9289e69c190ecd6818b6407"},
+    {file = "pywin32-306-cp311-cp311-win_amd64.whl", hash = "sha256:a7639f51c184c0272e93f244eb24dafca9b1855707d94c192d4a0b4c01e1100e"},
+    {file = "pywin32-306-cp311-cp311-win_arm64.whl", hash = "sha256:70dba0c913d19f942a2db25217d9a1b726c278f483a919f1abfed79c9cf64d3a"},
+    {file = "pywin32-306-cp312-cp312-win32.whl", hash = "sha256:383229d515657f4e3ed1343da8be101000562bf514591ff383ae940cad65458b"},
+    {file = "pywin32-306-cp312-cp312-win_amd64.whl", hash = "sha256:37257794c1ad39ee9be652da0462dc2e394c8159dfd913a8a4e8eb6fd346da0e"},
+    {file = "pywin32-306-cp312-cp312-win_arm64.whl", hash = "sha256:5821ec52f6d321aa59e2db7e0a35b997de60c201943557d108af9d4ae1ec7040"},
+    {file = "pywin32-306-cp37-cp37m-win32.whl", hash = "sha256:1c73ea9a0d2283d889001998059f5eaaba3b6238f767c9cf2833b13e6a685f65"},
+    {file = "pywin32-306-cp37-cp37m-win_amd64.whl", hash = "sha256:72c5f621542d7bdd4fdb716227be0dd3f8565c11b280be6315b06ace35487d36"},
+    {file = "pywin32-306-cp38-cp38-win32.whl", hash = "sha256:e4c092e2589b5cf0d365849e73e02c391c1349958c5ac3e9d5ccb9a28e017b3a"},
+    {file = "pywin32-306-cp38-cp38-win_amd64.whl", hash = "sha256:e8ac1ae3601bee6ca9f7cb4b5363bf1c0badb935ef243c4733ff9a393b1690c0"},
+    {file = "pywin32-306-cp39-cp39-win32.whl", hash = "sha256:e25fd5b485b55ac9c057f67d94bc203f3f6595078d1fb3b458c9c28b7153a802"},
+    {file = "pywin32-306-cp39-cp39-win_amd64.whl", hash = "sha256:39b61c15272833b5c329a2989999dcae836b1eed650252ab1b7bfbe1d59f30f4"},
+]
+
+[[package]]
+name = "pyworld"
+version = "0.3.2"
+description = "PyWorld is a Python wrapper for WORLD vocoder."
+optional = false
+python-versions = "*"
+files = [
+    {file = "pyworld-0.3.2-cp310-cp310-win_amd64.whl", hash = "sha256:688730fa5394709a185061e5a58e7a614b4548d814eeecc1dc825f73af53a9aa"},
+    {file = "pyworld-0.3.2-cp36-cp36m-win32.whl", hash = "sha256:1e110e2f95d45b0765f4ba4e49b389f9b931c9c438cd69774dce20699cc6dc7d"},
+    {file = "pyworld-0.3.2-cp36-cp36m-win_amd64.whl", hash = "sha256:e858668185a177e9e30c0ff12de3e166b39124c14b424ba3be31418694dcb2b7"},
+    {file = "pyworld-0.3.2-cp37-cp37m-win32.whl", hash = "sha256:b5325e7a08f104a9bf533d54423546bd3ef05953b80b79a8ced34efbb892862b"},
+    {file = "pyworld-0.3.2-cp37-cp37m-win_amd64.whl", hash = "sha256:fddd503ac264810221d9460bfdc1454c5c1313214e1c58a4ddd9417699f99bc8"},
+    {file = "pyworld-0.3.2-cp38-cp38-win_amd64.whl", hash = "sha256:502fbf577f4e56a497b3ad8c29434ec423eabc4674b93fa11046837d297c97be"},
+    {file = "pyworld-0.3.2-cp39-cp39-win_amd64.whl", hash = "sha256:a8ea62219b9bce0e514ff05ee80cfbc1248b165d8d802f00b9b8754510701f3e"},
+    {file = "pyworld-0.3.2.tar.gz", hash = "sha256:668d09842c3cfa74b1f6edabdb0058a64c04f9cf17b93883e6da811e1204ad4d"},
+]
+
+[package.dependencies]
+cython = "*"
+numpy = "*"
+
+[package.extras]
+sdist = ["cython", "numpy"]
+test = ["nose"]
+
+[[package]]
+name = "pyyaml"
+version = "6.0"
+description = "YAML parser and emitter for Python"
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "PyYAML-6.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:d4db7c7aef085872ef65a8fd7d6d09a14ae91f691dec3e87ee5ee0539d516f53"},
+    {file = "PyYAML-6.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:9df7ed3b3d2e0ecfe09e14741b857df43adb5a3ddadc919a2d94fbdf78fea53c"},
+    {file = "PyYAML-6.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:77f396e6ef4c73fdc33a9157446466f1cff553d979bd00ecb64385760c6babdc"},
+    {file = "PyYAML-6.0-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:a80a78046a72361de73f8f395f1f1e49f956c6be882eed58505a15f3e430962b"},
+    {file = "PyYAML-6.0-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:f84fbc98b019fef2ee9a1cb3ce93e3187a6df0b2538a651bfb890254ba9f90b5"},
+    {file = "PyYAML-6.0-cp310-cp310-win32.whl", hash = "sha256:2cd5df3de48857ed0544b34e2d40e9fac445930039f3cfe4bcc592a1f836d513"},
+    {file = "PyYAML-6.0-cp310-cp310-win_amd64.whl", hash = "sha256:daf496c58a8c52083df09b80c860005194014c3698698d1a57cbcfa182142a3a"},
+    {file = "PyYAML-6.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:d4b0ba9512519522b118090257be113b9468d804b19d63c71dbcf4a48fa32358"},
+    {file = "PyYAML-6.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:81957921f441d50af23654aa6c5e5eaf9b06aba7f0a19c18a538dc7ef291c5a1"},
+    {file = "PyYAML-6.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:afa17f5bc4d1b10afd4466fd3a44dc0e245382deca5b3c353d8b757f9e3ecb8d"},
+    {file = "PyYAML-6.0-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:dbad0e9d368bb989f4515da330b88a057617d16b6a8245084f1b05400f24609f"},
+    {file = "PyYAML-6.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:432557aa2c09802be39460360ddffd48156e30721f5e8d917f01d31694216782"},
+    {file = "PyYAML-6.0-cp311-cp311-win32.whl", hash = "sha256:bfaef573a63ba8923503d27530362590ff4f576c626d86a9fed95822a8255fd7"},
+    {file = "PyYAML-6.0-cp311-cp311-win_amd64.whl", hash = "sha256:01b45c0191e6d66c470b6cf1b9531a771a83c1c4208272ead47a3ae4f2f603bf"},
+    {file = "PyYAML-6.0-cp36-cp36m-macosx_10_9_x86_64.whl", hash = "sha256:897b80890765f037df3403d22bab41627ca8811ae55e9a722fd0392850ec4d86"},
+    {file = "PyYAML-6.0-cp36-cp36m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:50602afada6d6cbfad699b0c7bb50d5ccffa7e46a3d738092afddc1f9758427f"},
+    {file = "PyYAML-6.0-cp36-cp36m-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:48c346915c114f5fdb3ead70312bd042a953a8ce5c7106d5bfb1a5254e47da92"},
+    {file = "PyYAML-6.0-cp36-cp36m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:98c4d36e99714e55cfbaaee6dd5badbc9a1ec339ebfc3b1f52e293aee6bb71a4"},
+    {file = "PyYAML-6.0-cp36-cp36m-win32.whl", hash = "sha256:0283c35a6a9fbf047493e3a0ce8d79ef5030852c51e9d911a27badfde0605293"},
+    {file = "PyYAML-6.0-cp36-cp36m-win_amd64.whl", hash = "sha256:07751360502caac1c067a8132d150cf3d61339af5691fe9e87803040dbc5db57"},
+    {file = "PyYAML-6.0-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:819b3830a1543db06c4d4b865e70ded25be52a2e0631ccd2f6a47a2822f2fd7c"},
+    {file = "PyYAML-6.0-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:473f9edb243cb1935ab5a084eb238d842fb8f404ed2193a915d1784b5a6b5fc0"},
+    {file = "PyYAML-6.0-cp37-cp37m-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:0ce82d761c532fe4ec3f87fc45688bdd3a4c1dc5e0b4a19814b9009a29baefd4"},
+    {file = "PyYAML-6.0-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:231710d57adfd809ef5d34183b8ed1eeae3f76459c18fb4a0b373ad56bedcdd9"},
+    {file = "PyYAML-6.0-cp37-cp37m-win32.whl", hash = "sha256:c5687b8d43cf58545ade1fe3e055f70eac7a5a1a0bf42824308d868289a95737"},
+    {file = "PyYAML-6.0-cp37-cp37m-win_amd64.whl", hash = "sha256:d15a181d1ecd0d4270dc32edb46f7cb7733c7c508857278d3d378d14d606db2d"},
+    {file = "PyYAML-6.0-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:0b4624f379dab24d3725ffde76559cff63d9ec94e1736b556dacdfebe5ab6d4b"},
+    {file = "PyYAML-6.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:213c60cd50106436cc818accf5baa1aba61c0189ff610f64f4a3e8c6726218ba"},
+    {file = "PyYAML-6.0-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:9fa600030013c4de8165339db93d182b9431076eb98eb40ee068700c9c813e34"},
+    {file = "PyYAML-6.0-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:277a0ef2981ca40581a47093e9e2d13b3f1fbbeffae064c1d21bfceba2030287"},
+    {file = "PyYAML-6.0-cp38-cp38-win32.whl", hash = "sha256:d4eccecf9adf6fbcc6861a38015c2a64f38b9d94838ac1810a9023a0609e1b78"},
+    {file = "PyYAML-6.0-cp38-cp38-win_amd64.whl", hash = "sha256:1e4747bc279b4f613a09eb64bba2ba602d8a6664c6ce6396a4d0cd413a50ce07"},
+    {file = "PyYAML-6.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:055d937d65826939cb044fc8c9b08889e8c743fdc6a32b33e2390f66013e449b"},
+    {file = "PyYAML-6.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:e61ceaab6f49fb8bdfaa0f92c4b57bcfbea54c09277b1b4f7ac376bfb7a7c174"},
+    {file = "PyYAML-6.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d67d839ede4ed1b28a4e8909735fc992a923cdb84e618544973d7dfc71540803"},
+    {file = "PyYAML-6.0-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:cba8c411ef271aa037d7357a2bc8f9ee8b58b9965831d9e51baf703280dc73d3"},
+    {file = "PyYAML-6.0-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:40527857252b61eacd1d9af500c3337ba8deb8fc298940291486c465c8b46ec0"},
+    {file = "PyYAML-6.0-cp39-cp39-win32.whl", hash = "sha256:b5b9eccad747aabaaffbc6064800670f0c297e52c12754eb1d976c57e4f74dcb"},
+    {file = "PyYAML-6.0-cp39-cp39-win_amd64.whl", hash = "sha256:b3d267842bf12586ba6c734f89d1f5b871df0273157918b0ccefa29deb05c21c"},
+    {file = "PyYAML-6.0.tar.gz", hash = "sha256:68fb519c14306fec9720a2a5b45bc9f0c8d1b9c72adf45c37baedfcd949c35a2"},
+]
+
+[[package]]
+name = "regex"
+version = "2023.3.23"
+description = "Alternative regular expression module, to replace re."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "regex-2023.3.23-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:845a5e2d84389c4ddada1a9b95c055320070f18bb76512608374aca00d22eca8"},
+    {file = "regex-2023.3.23-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:87d9951f5a538dd1d016bdc0dcae59241d15fa94860964833a54d18197fcd134"},
+    {file = "regex-2023.3.23-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:37ae17d3be44c0b3f782c28ae9edd8b47c1f1776d4cabe87edc0b98e1f12b021"},
+    {file = "regex-2023.3.23-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:0b8eb1e3bca6b48dc721818a60ae83b8264d4089a4a41d62be6d05316ec38e15"},
+    {file = "regex-2023.3.23-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:df45fac182ebc3c494460c644e853515cc24f5ad9da05f8ffb91da891bfee879"},
+    {file = "regex-2023.3.23-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b7006105b10b59971d3b248ad75acc3651c7e4cf54d81694df5a5130a3c3f7ea"},
+    {file = "regex-2023.3.23-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:93f3f1aa608380fe294aa4cb82e2afda07a7598e828d0341e124b8fd9327c715"},
+    {file = "regex-2023.3.23-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:787954f541ab95d8195d97b0b8cf1dc304424adb1e07365967e656b92b38a699"},
+    {file = "regex-2023.3.23-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:20abe0bdf03630fe92ccafc45a599bca8b3501f48d1de4f7d121153350a2f77d"},
+    {file = "regex-2023.3.23-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:11d00c31aeab9a6e0503bc77e73ed9f4527b3984279d997eb145d7c7be6268fd"},
+    {file = "regex-2023.3.23-cp310-cp310-musllinux_1_1_ppc64le.whl", hash = "sha256:d5bbe0e1511b844794a3be43d6c145001626ba9a6c1db8f84bdc724e91131d9d"},
+    {file = "regex-2023.3.23-cp310-cp310-musllinux_1_1_s390x.whl", hash = "sha256:ea3c0cb56eadbf4ab2277e7a095676370b3e46dbfc74d5c383bd87b0d6317910"},
+    {file = "regex-2023.3.23-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:d895b4c863059a4934d3e874b90998df774644a41b349ebb330f85f11b4ef2c0"},
+    {file = "regex-2023.3.23-cp310-cp310-win32.whl", hash = "sha256:9d764514d19b4edcc75fd8cb1423448ef393e8b6cbd94f38cab983ab1b75855d"},
+    {file = "regex-2023.3.23-cp310-cp310-win_amd64.whl", hash = "sha256:11d1f2b7a0696dc0310de0efb51b1f4d813ad4401fe368e83c0c62f344429f98"},
+    {file = "regex-2023.3.23-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:8a9c63cde0eaa345795c0fdeb19dc62d22e378c50b0bc67bf4667cd5b482d98b"},
+    {file = "regex-2023.3.23-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:dd7200b4c27b68cf9c9646da01647141c6db09f48cc5b51bc588deaf8e98a797"},
+    {file = "regex-2023.3.23-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:22720024b90a6ba673a725dcc62e10fb1111b889305d7c6b887ac7466b74bedb"},
+    {file = "regex-2023.3.23-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:6b190a339090e6af25f4a5fd9e77591f6d911cc7b96ecbb2114890b061be0ac1"},
+    {file = "regex-2023.3.23-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:e76b6fc0d8e9efa39100369a9b3379ce35e20f6c75365653cf58d282ad290f6f"},
+    {file = "regex-2023.3.23-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7868b8f218bf69a2a15402fde08b08712213a1f4b85a156d90473a6fb6b12b09"},
+    {file = "regex-2023.3.23-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:2472428efc4127374f494e570e36b30bb5e6b37d9a754f7667f7073e43b0abdd"},
+    {file = "regex-2023.3.23-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:c37df2a060cb476d94c047b18572ee2b37c31f831df126c0da3cd9227b39253d"},
+    {file = "regex-2023.3.23-cp311-cp311-musllinux_1_1_i686.whl", hash = "sha256:4479f9e2abc03362df4045b1332d4a2b7885b245a30d4f4b051c4083b97d95d8"},
+    {file = "regex-2023.3.23-cp311-cp311-musllinux_1_1_ppc64le.whl", hash = "sha256:e2396e0678167f2d0c197da942b0b3fb48fee2f0b5915a0feb84d11b6686afe6"},
+    {file = "regex-2023.3.23-cp311-cp311-musllinux_1_1_s390x.whl", hash = "sha256:75f288c60232a5339e0ff2fa05779a5e9c74e9fc085c81e931d4a264501e745b"},
+    {file = "regex-2023.3.23-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:c869260aa62cee21c5eb171a466c0572b5e809213612ef8d495268cd2e34f20d"},
+    {file = "regex-2023.3.23-cp311-cp311-win32.whl", hash = "sha256:25f0532fd0c53e96bad84664171969de9673b4131f2297f1db850d3918d58858"},
+    {file = "regex-2023.3.23-cp311-cp311-win_amd64.whl", hash = "sha256:5ccfafd98473e007cebf7da10c1411035b7844f0f204015efd050601906dbb53"},
+    {file = "regex-2023.3.23-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:6572ff287176c0fb96568adb292674b421fa762153ed074d94b1d939ed92c253"},
+    {file = "regex-2023.3.23-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:a610e0adfcb0fc84ea25f6ea685e39e74cbcd9245a72a9a7aab85ff755a5ed27"},
+    {file = "regex-2023.3.23-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:086afe222d58b88b62847bdbd92079b4699350b4acab892f88a935db5707c790"},
+    {file = "regex-2023.3.23-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:79e29fd62fa2f597a6754b247356bda14b866131a22444d67f907d6d341e10f3"},
+    {file = "regex-2023.3.23-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:c07ce8e9eee878a48ebeb32ee661b49504b85e164b05bebf25420705709fdd31"},
+    {file = "regex-2023.3.23-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:86b036f401895e854de9fefe061518e78d506d8a919cc250dc3416bca03f6f9a"},
+    {file = "regex-2023.3.23-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:78ac8dd8e18800bb1f97aad0d73f68916592dddf233b99d2b5cabc562088503a"},
+    {file = "regex-2023.3.23-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:539dd010dc35af935b32f248099e38447bbffc10b59c2b542bceead2bed5c325"},
+    {file = "regex-2023.3.23-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:9bf4a5626f2a0ea006bf81e8963f498a57a47d58907eaa58f4b3e13be68759d8"},
+    {file = "regex-2023.3.23-cp38-cp38-musllinux_1_1_i686.whl", hash = "sha256:cf86b4328c204c3f315074a61bc1c06f8a75a8e102359f18ce99fbcbbf1951f0"},
+    {file = "regex-2023.3.23-cp38-cp38-musllinux_1_1_ppc64le.whl", hash = "sha256:2848bf76673c83314068241c8d5b7fa9ad9bed866c979875a0e84039349e8fa7"},
+    {file = "regex-2023.3.23-cp38-cp38-musllinux_1_1_s390x.whl", hash = "sha256:c125a02d22c555e68f7433bac8449992fa1cead525399f14e47c2d98f2f0e467"},
+    {file = "regex-2023.3.23-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:cd1671e9d5ac05ce6aa86874dd8dfa048824d1dbe73060851b310c6c1a201a96"},
+    {file = "regex-2023.3.23-cp38-cp38-win32.whl", hash = "sha256:fffe57312a358be6ec6baeb43d253c36e5790e436b7bf5b7a38df360363e88e9"},
+    {file = "regex-2023.3.23-cp38-cp38-win_amd64.whl", hash = "sha256:dbb3f87e15d3dd76996d604af8678316ad2d7d20faa394e92d9394dfd621fd0c"},
+    {file = "regex-2023.3.23-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:c88e8c226473b5549fe9616980ea7ca09289246cfbdf469241edf4741a620004"},
+    {file = "regex-2023.3.23-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:6560776ec19c83f3645bbc5db64a7a5816c9d8fb7ed7201c5bcd269323d88072"},
+    {file = "regex-2023.3.23-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:1b1fc2632c01f42e06173d8dd9bb2e74ab9b0afa1d698058c867288d2c7a31f3"},
+    {file = "regex-2023.3.23-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:fdf7ad455f1916b8ea5cdbc482d379f6daf93f3867b4232d14699867a5a13af7"},
+    {file = "regex-2023.3.23-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:5fc33b27b1d800fc5b78d7f7d0f287e35079ecabe68e83d46930cf45690e1c8c"},
+    {file = "regex-2023.3.23-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4c49552dc938e3588f63f8a78c86f3c9c75301e813bca0bef13bdb4b87ccf364"},
+    {file = "regex-2023.3.23-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:e152461e9a0aedec7d37fc66ec0fa635eca984777d3d3c3e36f53bf3d3ceb16e"},
+    {file = "regex-2023.3.23-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:db034255e72d2995cf581b14bb3fc9c00bdbe6822b49fcd4eef79e1d5f232618"},
+    {file = "regex-2023.3.23-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:55ae114da21b7a790b90255ea52d2aa3a0d121a646deb2d3c6a3194e722fc762"},
+    {file = "regex-2023.3.23-cp39-cp39-musllinux_1_1_i686.whl", hash = "sha256:ef3f528fe1cc3d139508fe1b22523745aa77b9d6cb5b0bf277f48788ee0b993f"},
+    {file = "regex-2023.3.23-cp39-cp39-musllinux_1_1_ppc64le.whl", hash = "sha256:a81c9ec59ca2303acd1ccd7b9ac409f1e478e40e96f8f79b943be476c5fdb8bb"},
+    {file = "regex-2023.3.23-cp39-cp39-musllinux_1_1_s390x.whl", hash = "sha256:cde09c4fdd070772aa2596d97e942eb775a478b32459e042e1be71b739d08b77"},
+    {file = "regex-2023.3.23-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:3cd9f5dd7b821f141d3a6ca0d5d9359b9221e4f051ca3139320adea9f1679691"},
+    {file = "regex-2023.3.23-cp39-cp39-win32.whl", hash = "sha256:7304863f3a652dab5e68e6fb1725d05ebab36ec0390676d1736e0571ebb713ef"},
+    {file = "regex-2023.3.23-cp39-cp39-win_amd64.whl", hash = "sha256:54c3fa855a3f7438149de3211738dd9b5f0c733f48b54ae05aa7fce83d48d858"},
+    {file = "regex-2023.3.23.tar.gz", hash = "sha256:dc80df325b43ffea5cdea2e3eaa97a44f3dd298262b1c7fe9dbb2a9522b956a7"},
+]
+
+[[package]]
+name = "requests"
+version = "2.31.0"
+description = "Python HTTP for Humans."
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "requests-2.31.0-py3-none-any.whl", hash = "sha256:58cd2187c01e70e6e26505bca751777aa9f2ee0b7f4300988b709f44e013003f"},
+    {file = "requests-2.31.0.tar.gz", hash = "sha256:942c5a758f98d790eaed1a29cb6eefc7ffb0d1cf7af05c3d2791656dbd6ad1e1"},
+]
+
+[package.dependencies]
+certifi = ">=2017.4.17"
+charset-normalizer = ">=2,<4"
+idna = ">=2.5,<4"
+urllib3 = ">=1.21.1,<3"
+
+[package.extras]
+socks = ["PySocks (>=1.5.6,!=1.5.7)"]
+use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"]
+
+[[package]]
+name = "requests-oauthlib"
+version = "1.3.1"
+description = "OAuthlib authentication support for Requests."
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
+files = [
+    {file = "requests-oauthlib-1.3.1.tar.gz", hash = "sha256:75beac4a47881eeb94d5ea5d6ad31ef88856affe2332b9aafb52c6452ccf0d7a"},
+    {file = "requests_oauthlib-1.3.1-py2.py3-none-any.whl", hash = "sha256:2577c501a2fb8d05a304c09d090d6e47c306fef15809d102b327cf8364bddab5"},
+]
+
+[package.dependencies]
+oauthlib = ">=3.0.0"
+requests = ">=2.0.0"
+
+[package.extras]
+rsa = ["oauthlib[signedtoken] (>=3.0.0)"]
+
+[[package]]
+name = "resampy"
+version = "0.4.2"
+description = "Efficient signal resampling"
+optional = false
+python-versions = "*"
+files = [
+    {file = "resampy-0.4.2-py3-none-any.whl", hash = "sha256:4340b6c4e685a865621dfcf016e2a3dd49d865446b6025e30fe88567f22e052e"},
+    {file = "resampy-0.4.2.tar.gz", hash = "sha256:0a469e6ddb89956f4fd6c88728300e4bbd186fae569dd4fd17dae51a91cbaa15"},
+]
+
+[package.dependencies]
+numba = ">=0.53"
+numpy = ">=1.17"
+
+[package.extras]
+design = ["optuna (>=2.10.0)"]
+docs = ["numpydoc", "sphinx (!=1.3.1)"]
+tests = ["pytest (<8)", "pytest-cov", "scipy (>=1.0)"]
+
+[[package]]
+name = "rfc3986"
+version = "1.5.0"
+description = "Validating URI References per RFC 3986"
+optional = false
+python-versions = "*"
+files = [
+    {file = "rfc3986-1.5.0-py2.py3-none-any.whl", hash = "sha256:a86d6e1f5b1dc238b218b012df0aa79409667bb209e58da56d0b94704e712a97"},
+    {file = "rfc3986-1.5.0.tar.gz", hash = "sha256:270aaf10d87d0d4e095063c65bf3ddbc6ee3d0b226328ce21e036f946e421835"},
+]
+
+[package.dependencies]
+idna = {version = "*", optional = true, markers = "extra == \"idna2008\""}
+
+[package.extras]
+idna2008 = ["idna"]
+
+[[package]]
+name = "rsa"
+version = "4.9"
+description = "Pure-Python RSA implementation"
+optional = false
+python-versions = ">=3.6,<4"
+files = [
+    {file = "rsa-4.9-py3-none-any.whl", hash = "sha256:90260d9058e514786967344d0ef75fa8727eed8a7d2e43ce9f4bcf1b536174f7"},
+    {file = "rsa-4.9.tar.gz", hash = "sha256:e38464a49c6c85d7f1351b0126661487a7e0a14a50f1675ec50eb34d4f20ef21"},
+]
+
+[package.dependencies]
+pyasn1 = ">=0.1.3"
+
+[[package]]
+name = "sacrebleu"
+version = "2.3.1"
+description = "Hassle-free computation of shareable, comparable, and reproducible BLEU, chrF, and TER scores"
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "sacrebleu-2.3.1-py3-none-any.whl", hash = "sha256:352227b8ca9e04ed509266d1fee6c8cff0ea1417c429f8c684645ad2db8b02e7"},
+    {file = "sacrebleu-2.3.1.tar.gz", hash = "sha256:7969b294f15dae84d80fb2b76d30c83b245f49f4ecb1cac79acb553eb93cb537"},
+]
+
+[package.dependencies]
+colorama = "*"
+lxml = "*"
+numpy = ">=1.17"
+portalocker = "*"
+regex = "*"
+tabulate = ">=0.8.9"
+
+[package.extras]
+ja = ["ipadic (>=1.0,<2.0)", "mecab-python3 (==1.0.5)"]
+ko = ["mecab-ko (==1.0.0)", "mecab-ko-dic (>=1.0,<2.0)"]
+
+[[package]]
+name = "scikit-learn"
+version = "1.2.2"
+description = "A set of python modules for machine learning and data mining"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "scikit-learn-1.2.2.tar.gz", hash = "sha256:8429aea30ec24e7a8c7ed8a3fa6213adf3814a6efbea09e16e0a0c71e1a1a3d7"},
+    {file = "scikit_learn-1.2.2-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:99cc01184e347de485bf253d19fcb3b1a3fb0ee4cea5ee3c43ec0cc429b6d29f"},
+    {file = "scikit_learn-1.2.2-cp310-cp310-macosx_12_0_arm64.whl", hash = "sha256:e6e574db9914afcb4e11ade84fab084536a895ca60aadea3041e85b8ac963edb"},
+    {file = "scikit_learn-1.2.2-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6fe83b676f407f00afa388dd1fdd49e5c6612e551ed84f3b1b182858f09e987d"},
+    {file = "scikit_learn-1.2.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:2e2642baa0ad1e8f8188917423dd73994bf25429f8893ddbe115be3ca3183584"},
+    {file = "scikit_learn-1.2.2-cp310-cp310-win_amd64.whl", hash = "sha256:ad66c3848c0a1ec13464b2a95d0a484fd5b02ce74268eaa7e0c697b904f31d6c"},
+    {file = "scikit_learn-1.2.2-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:dfeaf8be72117eb61a164ea6fc8afb6dfe08c6f90365bde2dc16456e4bc8e45f"},
+    {file = "scikit_learn-1.2.2-cp311-cp311-macosx_12_0_arm64.whl", hash = "sha256:fe0aa1a7029ed3e1dcbf4a5bc675aa3b1bc468d9012ecf6c6f081251ca47f590"},
+    {file = "scikit_learn-1.2.2-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:065e9673e24e0dc5113e2dd2b4ca30c9d8aa2fa90f4c0597241c93b63130d233"},
+    {file = "scikit_learn-1.2.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bf036ea7ef66115e0d49655f16febfa547886deba20149555a41d28f56fd6d3c"},
+    {file = "scikit_learn-1.2.2-cp311-cp311-win_amd64.whl", hash = "sha256:8b0670d4224a3c2d596fd572fb4fa673b2a0ccfb07152688ebd2ea0b8c61025c"},
+    {file = "scikit_learn-1.2.2-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:9c710ff9f9936ba8a3b74a455ccf0dcf59b230caa1e9ba0223773c490cab1e51"},
+    {file = "scikit_learn-1.2.2-cp38-cp38-macosx_12_0_arm64.whl", hash = "sha256:2dd3ffd3950e3d6c0c0ef9033a9b9b32d910c61bd06cb8206303fb4514b88a49"},
+    {file = "scikit_learn-1.2.2-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:44b47a305190c28dd8dd73fc9445f802b6ea716669cfc22ab1eb97b335d238b1"},
+    {file = "scikit_learn-1.2.2-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:953236889928d104c2ef14027539f5f2609a47ebf716b8cbe4437e85dce42744"},
+    {file = "scikit_learn-1.2.2-cp38-cp38-win_amd64.whl", hash = "sha256:7f69313884e8eb311460cc2f28676d5e400bd929841a2c8eb8742ae78ebf7c20"},
+    {file = "scikit_learn-1.2.2-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:8156db41e1c39c69aa2d8599ab7577af53e9e5e7a57b0504e116cc73c39138dd"},
+    {file = "scikit_learn-1.2.2-cp39-cp39-macosx_12_0_arm64.whl", hash = "sha256:fe175ee1dab589d2e1033657c5b6bec92a8a3b69103e3dd361b58014729975c3"},
+    {file = "scikit_learn-1.2.2-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7d5312d9674bed14f73773d2acf15a3272639b981e60b72c9b190a0cffed5bad"},
+    {file = "scikit_learn-1.2.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ea061bf0283bf9a9f36ea3c5d3231ba2176221bbd430abd2603b1c3b2ed85c89"},
+    {file = "scikit_learn-1.2.2-cp39-cp39-win_amd64.whl", hash = "sha256:6477eed40dbce190f9f9e9d0d37e020815825b300121307942ec2110302b66a3"},
+]
+
+[package.dependencies]
+joblib = ">=1.1.1"
+numpy = ">=1.17.3"
+scipy = ">=1.3.2"
+threadpoolctl = ">=2.0.0"
+
+[package.extras]
+benchmark = ["matplotlib (>=3.1.3)", "memory-profiler (>=0.57.0)", "pandas (>=1.0.5)"]
+docs = ["Pillow (>=7.1.2)", "matplotlib (>=3.1.3)", "memory-profiler (>=0.57.0)", "numpydoc (>=1.2.0)", "pandas (>=1.0.5)", "plotly (>=5.10.0)", "pooch (>=1.6.0)", "scikit-image (>=0.16.2)", "seaborn (>=0.9.0)", "sphinx (>=4.0.1)", "sphinx-gallery (>=0.7.0)", "sphinx-prompt (>=1.3.0)", "sphinxext-opengraph (>=0.4.2)"]
+examples = ["matplotlib (>=3.1.3)", "pandas (>=1.0.5)", "plotly (>=5.10.0)", "pooch (>=1.6.0)", "scikit-image (>=0.16.2)", "seaborn (>=0.9.0)"]
+tests = ["black (>=22.3.0)", "flake8 (>=3.8.2)", "matplotlib (>=3.1.3)", "mypy (>=0.961)", "numpydoc (>=1.2.0)", "pandas (>=1.0.5)", "pooch (>=1.6.0)", "pyamg (>=4.0.0)", "pytest (>=5.3.1)", "pytest-cov (>=2.9.0)", "scikit-image (>=0.16.2)"]
+
+[[package]]
+name = "scipy"
+version = "1.9.3"
+description = "Fundamental algorithms for scientific computing in Python"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "scipy-1.9.3-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:1884b66a54887e21addf9c16fb588720a8309a57b2e258ae1c7986d4444d3bc0"},
+    {file = "scipy-1.9.3-cp310-cp310-macosx_12_0_arm64.whl", hash = "sha256:83b89e9586c62e787f5012e8475fbb12185bafb996a03257e9675cd73d3736dd"},
+    {file = "scipy-1.9.3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:1a72d885fa44247f92743fc20732ae55564ff2a519e8302fb7e18717c5355a8b"},
+    {file = "scipy-1.9.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d01e1dd7b15bd2449c8bfc6b7cc67d630700ed655654f0dfcf121600bad205c9"},
+    {file = "scipy-1.9.3-cp310-cp310-win_amd64.whl", hash = "sha256:68239b6aa6f9c593da8be1509a05cb7f9efe98b80f43a5861cd24c7557e98523"},
+    {file = "scipy-1.9.3-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:b41bc822679ad1c9a5f023bc93f6d0543129ca0f37c1ce294dd9d386f0a21096"},
+    {file = "scipy-1.9.3-cp311-cp311-macosx_12_0_arm64.whl", hash = "sha256:90453d2b93ea82a9f434e4e1cba043e779ff67b92f7a0e85d05d286a3625df3c"},
+    {file = "scipy-1.9.3-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:83c06e62a390a9167da60bedd4575a14c1f58ca9dfde59830fc42e5197283dab"},
+    {file = "scipy-1.9.3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:abaf921531b5aeaafced90157db505e10345e45038c39e5d9b6c7922d68085cb"},
+    {file = "scipy-1.9.3-cp311-cp311-win_amd64.whl", hash = "sha256:06d2e1b4c491dc7d8eacea139a1b0b295f74e1a1a0f704c375028f8320d16e31"},
+    {file = "scipy-1.9.3-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:5a04cd7d0d3eff6ea4719371cbc44df31411862b9646db617c99718ff68d4840"},
+    {file = "scipy-1.9.3-cp38-cp38-macosx_12_0_arm64.whl", hash = "sha256:545c83ffb518094d8c9d83cce216c0c32f8c04aaf28b92cc8283eda0685162d5"},
+    {file = "scipy-1.9.3-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0d54222d7a3ba6022fdf5773931b5d7c56efe41ede7f7128c7b1637700409108"},
+    {file = "scipy-1.9.3-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:cff3a5295234037e39500d35316a4c5794739433528310e117b8a9a0c76d20fc"},
+    {file = "scipy-1.9.3-cp38-cp38-win_amd64.whl", hash = "sha256:2318bef588acc7a574f5bfdff9c172d0b1bf2c8143d9582e05f878e580a3781e"},
+    {file = "scipy-1.9.3-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:d644a64e174c16cb4b2e41dfea6af722053e83d066da7343f333a54dae9bc31c"},
+    {file = "scipy-1.9.3-cp39-cp39-macosx_12_0_arm64.whl", hash = "sha256:da8245491d73ed0a994ed9c2e380fd058ce2fa8a18da204681f2fe1f57f98f95"},
+    {file = "scipy-1.9.3-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4db5b30849606a95dcf519763dd3ab6fe9bd91df49eba517359e450a7d80ce2e"},
+    {file = "scipy-1.9.3-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c68db6b290cbd4049012990d7fe71a2abd9ffbe82c0056ebe0f01df8be5436b0"},
+    {file = "scipy-1.9.3-cp39-cp39-win_amd64.whl", hash = "sha256:5b88e6d91ad9d59478fafe92a7c757d00c59e3bdc3331be8ada76a4f8d683f58"},
+    {file = "scipy-1.9.3.tar.gz", hash = "sha256:fbc5c05c85c1a02be77b1ff591087c83bc44579c6d2bd9fb798bb64ea5e1a027"},
+]
+
+[package.dependencies]
+numpy = ">=1.18.5,<1.26.0"
+
+[package.extras]
+dev = ["flake8", "mypy", "pycodestyle", "typing_extensions"]
+doc = ["matplotlib (>2)", "numpydoc", "pydata-sphinx-theme (==0.9.0)", "sphinx (!=4.1.0)", "sphinx-panels (>=0.5.2)", "sphinx-tabs"]
+test = ["asv", "gmpy2", "mpmath", "pytest", "pytest-cov", "pytest-xdist", "scikit-umfpack", "threadpoolctl"]
+
+[[package]]
+name = "semantic-version"
+version = "2.10.0"
+description = "A library implementing the 'SemVer' scheme."
+optional = false
+python-versions = ">=2.7"
+files = [
+    {file = "semantic_version-2.10.0-py2.py3-none-any.whl", hash = "sha256:de78a3b8e0feda74cabc54aab2da702113e33ac9d9eb9d2389bcf1f58b7d9177"},
+    {file = "semantic_version-2.10.0.tar.gz", hash = "sha256:bdabb6d336998cbb378d4b9db3a4b56a1e3235701dc05ea2690d9a997ed5041c"},
+]
+
+[package.extras]
+dev = ["Django (>=1.11)", "check-manifest", "colorama (<=0.4.1)", "coverage", "flake8", "nose2", "readme-renderer (<25.0)", "tox", "wheel", "zest.releaser[recommended]"]
+doc = ["Sphinx", "sphinx-rtd-theme"]
+
+[[package]]
+name = "setuptools"
+version = "67.7.2"
+description = "Easily download, build, install, upgrade, and uninstall Python packages"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "setuptools-67.7.2-py3-none-any.whl", hash = "sha256:23aaf86b85ca52ceb801d32703f12d77517b2556af839621c641fca11287952b"},
+    {file = "setuptools-67.7.2.tar.gz", hash = "sha256:f104fa03692a2602fa0fec6c6a9e63b6c8a968de13e17c026957dd1f53d80990"},
+]
+
+[package.extras]
+docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "pygments-github-lexers (==0.0.5)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-favicon", "sphinx-hoverxref (<2)", "sphinx-inline-tabs", "sphinx-lint", "sphinx-notfound-page (==0.8.3)", "sphinx-reredirects", "sphinxcontrib-towncrier"]
+testing = ["build[virtualenv]", "filelock (>=3.4.0)", "flake8 (<5)", "flake8-2020", "ini2toml[lite] (>=0.9)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "pip (>=19.1)", "pip-run (>=8.8)", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)", "pytest-perf", "pytest-timeout", "pytest-xdist", "tomli-w (>=1.0.0)", "virtualenv (>=13.0.0)", "wheel"]
+testing-integration = ["build[virtualenv]", "filelock (>=3.4.0)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "pytest", "pytest-enabler", "pytest-xdist", "tomli", "virtualenv (>=13.0.0)", "wheel"]
+
+[[package]]
+name = "six"
+version = "1.16.0"
+description = "Python 2 and 3 compatibility utilities"
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*"
+files = [
+    {file = "six-1.16.0-py2.py3-none-any.whl", hash = "sha256:8abb2f1d86890a2dfb989f9a77cfcfd3e47c2a354b01111771326f8aa26e0254"},
+    {file = "six-1.16.0.tar.gz", hash = "sha256:1e61c37477a1626458e36f7b1d82aa5c9b094fa4802892072e49de9c60c4c926"},
+]
+
+[[package]]
+name = "sniffio"
+version = "1.3.0"
+description = "Sniff out which async library your code is running under"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "sniffio-1.3.0-py3-none-any.whl", hash = "sha256:eecefdce1e5bbfb7ad2eeaabf7c1eeb404d7757c379bd1f7e5cce9d8bf425384"},
+    {file = "sniffio-1.3.0.tar.gz", hash = "sha256:e60305c5e5d314f5389259b7f22aaa33d8f7dee49763119234af3755c55b9101"},
+]
+
+[[package]]
+name = "soundfile"
+version = "0.12.1"
+description = "An audio library based on libsndfile, CFFI and NumPy"
+optional = false
+python-versions = "*"
+files = [
+    {file = "soundfile-0.12.1-py2.py3-none-any.whl", hash = "sha256:828a79c2e75abab5359f780c81dccd4953c45a2c4cd4f05ba3e233ddf984b882"},
+    {file = "soundfile-0.12.1-py2.py3-none-macosx_10_9_x86_64.whl", hash = "sha256:d922be1563ce17a69582a352a86f28ed8c9f6a8bc951df63476ffc310c064bfa"},
+    {file = "soundfile-0.12.1-py2.py3-none-macosx_11_0_arm64.whl", hash = "sha256:bceaab5c4febb11ea0554566784bcf4bc2e3977b53946dda2b12804b4fe524a8"},
+    {file = "soundfile-0.12.1-py2.py3-none-manylinux_2_17_x86_64.whl", hash = "sha256:2dc3685bed7187c072a46ab4ffddd38cef7de9ae5eb05c03df2ad569cf4dacbc"},
+    {file = "soundfile-0.12.1-py2.py3-none-manylinux_2_31_x86_64.whl", hash = "sha256:074247b771a181859d2bc1f98b5ebf6d5153d2c397b86ee9e29ba602a8dfe2a6"},
+    {file = "soundfile-0.12.1-py2.py3-none-win32.whl", hash = "sha256:59dfd88c79b48f441bbf6994142a19ab1de3b9bb7c12863402c2bc621e49091a"},
+    {file = "soundfile-0.12.1-py2.py3-none-win_amd64.whl", hash = "sha256:0d86924c00b62552b650ddd28af426e3ff2d4dc2e9047dae5b3d8452e0a49a77"},
+    {file = "soundfile-0.12.1.tar.gz", hash = "sha256:e8e1017b2cf1dda767aef19d2fd9ee5ebe07e050d430f77a0a7c66ba08b8cdae"},
+]
+
+[package.dependencies]
+cffi = ">=1.0"
+
+[package.extras]
+numpy = ["numpy"]
+
+[[package]]
+name = "starlette"
+version = "0.27.0"
+description = "The little ASGI library that shines."
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "starlette-0.27.0-py3-none-any.whl", hash = "sha256:918416370e846586541235ccd38a474c08b80443ed31c578a418e2209b3eef91"},
+    {file = "starlette-0.27.0.tar.gz", hash = "sha256:6a6b0d042acb8d469a01eba54e9cda6cbd24ac602c4cd016723117d6a7e73b75"},
+]
+
+[package.dependencies]
+anyio = ">=3.4.0,<5"
+typing-extensions = {version = ">=3.10.0", markers = "python_version < \"3.10\""}
+
+[package.extras]
+full = ["httpx (>=0.22.0)", "itsdangerous", "jinja2", "python-multipart", "pyyaml"]
+
+[[package]]
+name = "sympy"
+version = "1.11.1"
+description = "Computer algebra system (CAS) in Python"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "sympy-1.11.1-py3-none-any.whl", hash = "sha256:938f984ee2b1e8eae8a07b884c8b7a1146010040fccddc6539c54f401c8f6fcf"},
+    {file = "sympy-1.11.1.tar.gz", hash = "sha256:e32380dce63cb7c0108ed525570092fd45168bdae2faa17e528221ef72e88658"},
+]
+
+[package.dependencies]
+mpmath = ">=0.19"
+
+[[package]]
+name = "tabulate"
+version = "0.9.0"
+description = "Pretty-print tabular data"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "tabulate-0.9.0-py3-none-any.whl", hash = "sha256:024ca478df22e9340661486f85298cff5f6dcdba14f3813e8830015b9ed1948f"},
+    {file = "tabulate-0.9.0.tar.gz", hash = "sha256:0095b12bf5966de529c0feb1fa08671671b3368eec77d7ef7ab114be2c068b3c"},
+]
+
+[package.extras]
+widechars = ["wcwidth"]
+
+[[package]]
+name = "tensorboard"
+version = "2.12.1"
+description = "TensorBoard lets you watch Tensors Flow"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "tensorboard-2.12.1-py3-none-any.whl", hash = "sha256:58f1c2a25b4829b9c48d2b1ec951dedc9325dcd1ea4b0f601d241d2887d0ed65"},
+]
+
+[package.dependencies]
+absl-py = ">=0.4"
+google-auth = ">=1.6.3,<3"
+google-auth-oauthlib = ">=0.5,<1.1"
+grpcio = ">=1.48.2"
+markdown = ">=2.6.8"
+numpy = ">=1.12.0"
+protobuf = ">=3.19.6"
+requests = ">=2.21.0,<3"
+setuptools = ">=41.0.0"
+tensorboard-data-server = ">=0.7.0,<0.8.0"
+tensorboard-plugin-wit = ">=1.6.0"
+werkzeug = ">=1.0.1"
+wheel = ">=0.26"
+
+[[package]]
+name = "tensorboard-data-server"
+version = "0.7.0"
+description = "Fast data loading for TensorBoard"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "tensorboard_data_server-0.7.0-py3-none-any.whl", hash = "sha256:753d4214799b31da7b6d93837959abebbc6afa86e69eacf1e9a317a48daa31eb"},
+    {file = "tensorboard_data_server-0.7.0-py3-none-macosx_10_9_x86_64.whl", hash = "sha256:eb7fa518737944dbf4f0cf83c2e40a7ac346bf91be2e6a0215de98be74e85454"},
+    {file = "tensorboard_data_server-0.7.0-py3-none-manylinux2014_x86_64.whl", hash = "sha256:64aa1be7c23e80b1a42c13b686eb0875bb70f5e755f4d2b8de5c1d880cf2267f"},
+]
+
+[[package]]
+name = "tensorboard-plugin-wit"
+version = "1.8.1"
+description = "What-If Tool TensorBoard plugin."
+optional = false
+python-versions = "*"
+files = [
+    {file = "tensorboard_plugin_wit-1.8.1-py3-none-any.whl", hash = "sha256:ff26bdd583d155aa951ee3b152b3d0cffae8005dc697f72b44a8e8c2a77a8cbe"},
+]
+
+[[package]]
+name = "tensorboardx"
+version = "2.6"
+description = "TensorBoardX lets you watch Tensors Flow without Tensorflow"
+optional = false
+python-versions = "*"
+files = [
+    {file = "tensorboardX-2.6-py2.py3-none-any.whl", hash = "sha256:24a7cd076488de1e9d15ef25371b8ebf90c4f8f622af2477c611198f03f4a606"},
+    {file = "tensorboardX-2.6.tar.gz", hash = "sha256:d4c036964dd2deb075a1909832b276daa383eab3f9db519ad90b99f5aea06b0c"},
+]
+
+[package.dependencies]
+numpy = "*"
+packaging = "*"
+protobuf = ">=3.8.0,<4"
+
+[[package]]
+name = "threadpoolctl"
+version = "3.1.0"
+description = "threadpoolctl"
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "threadpoolctl-3.1.0-py3-none-any.whl", hash = "sha256:8b99adda265feb6773280df41eece7b2e6561b772d21ffd52e372f999024907b"},
+    {file = "threadpoolctl-3.1.0.tar.gz", hash = "sha256:a335baacfaa4400ae1f0d8e3a58d6674d2f8828e3716bb2802c44955ad391380"},
+]
+
+[[package]]
+name = "toolz"
+version = "0.12.0"
+description = "List processing tools and functional utilities"
+optional = false
+python-versions = ">=3.5"
+files = [
+    {file = "toolz-0.12.0-py3-none-any.whl", hash = "sha256:2059bd4148deb1884bb0eb770a3cde70e7f954cfbbdc2285f1f2de01fd21eb6f"},
+    {file = "toolz-0.12.0.tar.gz", hash = "sha256:88c570861c440ee3f2f6037c4654613228ff40c93a6c25e0eba70d17282c6194"},
+]
+
+[[package]]
+name = "torch"
+version = "2.0.0"
+description = "Tensors and Dynamic neural networks in Python with strong GPU acceleration"
+optional = false
+python-versions = ">=3.8.0"
+files = [
+    {file = "torch-2.0.0-1-cp310-cp310-manylinux2014_aarch64.whl", hash = "sha256:c9090bda7d2eeeecd74f51b721420dbeb44f838d4536cc1b284e879417e3064a"},
+    {file = "torch-2.0.0-1-cp311-cp311-manylinux2014_aarch64.whl", hash = "sha256:bd42db2a48a20574d2c33489e120e9f32789c4dc13c514b0c44272972d14a2d7"},
+    {file = "torch-2.0.0-1-cp38-cp38-manylinux2014_aarch64.whl", hash = "sha256:8969aa8375bcbc0c2993e7ede0a7f889df9515f18b9b548433f412affed478d9"},
+    {file = "torch-2.0.0-1-cp39-cp39-manylinux2014_aarch64.whl", hash = "sha256:ab2da16567cb55b67ae39e32d520d68ec736191d88ac79526ca5874754c32203"},
+    {file = "torch-2.0.0-cp310-cp310-manylinux1_x86_64.whl", hash = "sha256:7a9319a67294ef02459a19738bbfa8727bb5307b822dadd708bc2ccf6c901aca"},
+    {file = "torch-2.0.0-cp310-cp310-manylinux2014_aarch64.whl", hash = "sha256:9f01fe1f6263f31bd04e1757946fd63ad531ae37f28bb2dbf66f5c826ee089f4"},
+    {file = "torch-2.0.0-cp310-cp310-win_amd64.whl", hash = "sha256:527f4ae68df7b8301ee6b1158ca56350282ea633686537b30dbb5d7b4a52622a"},
+    {file = "torch-2.0.0-cp310-none-macosx_10_9_x86_64.whl", hash = "sha256:ce9b5a49bd513dff7950a5a07d6e26594dd51989cee05ba388b03e8e366fd5d5"},
+    {file = "torch-2.0.0-cp310-none-macosx_11_0_arm64.whl", hash = "sha256:53e1c33c6896583cdb9a583693e22e99266444c4a43392dddc562640d39e542b"},
+    {file = "torch-2.0.0-cp311-cp311-manylinux1_x86_64.whl", hash = "sha256:09651bff72e439d004c991f15add0c397c66f98ab36fe60d5514b44e4da722e8"},
+    {file = "torch-2.0.0-cp311-cp311-manylinux2014_aarch64.whl", hash = "sha256:d439aec349c98f12819e8564b8c54008e4613dd4428582af0e6e14c24ca85870"},
+    {file = "torch-2.0.0-cp311-cp311-win_amd64.whl", hash = "sha256:2802f84f021907deee7e9470ed10c0e78af7457ac9a08a6cd7d55adef835fede"},
+    {file = "torch-2.0.0-cp311-none-macosx_10_9_x86_64.whl", hash = "sha256:01858620f25f25e7a9ec4b547ff38e5e27c92d38ec4ccba9cfbfb31d7071ed9c"},
+    {file = "torch-2.0.0-cp311-none-macosx_11_0_arm64.whl", hash = "sha256:9a2e53b5783ef5896a6af338b36d782f28e83c8ddfc2ac44b67b066d9d76f498"},
+    {file = "torch-2.0.0-cp38-cp38-manylinux1_x86_64.whl", hash = "sha256:ec5fff2447663e369682838ff0f82187b4d846057ef4d119a8dea7772a0b17dd"},
+    {file = "torch-2.0.0-cp38-cp38-manylinux2014_aarch64.whl", hash = "sha256:11b0384fe3c18c01b8fc5992e70fc519cde65e44c51cc87be1838c1803daf42f"},
+    {file = "torch-2.0.0-cp38-cp38-win_amd64.whl", hash = "sha256:e54846aa63855298cfb1195487f032e413e7ac9cbfa978fda32354cc39551475"},
+    {file = "torch-2.0.0-cp38-none-macosx_10_9_x86_64.whl", hash = "sha256:cc788cbbbbc6eb4c90e52c550efd067586c2693092cf367c135b34893a64ae78"},
+    {file = "torch-2.0.0-cp38-none-macosx_11_0_arm64.whl", hash = "sha256:d292640f0fd72b7a31b2a6e3b635eb5065fcbedd4478f9cad1a1e7a9ec861d35"},
+    {file = "torch-2.0.0-cp39-cp39-manylinux1_x86_64.whl", hash = "sha256:6befaad784004b7af357e3d87fa0863c1f642866291f12a4c2af2de435e8ac5c"},
+    {file = "torch-2.0.0-cp39-cp39-manylinux2014_aarch64.whl", hash = "sha256:a83b26bd6ae36fbf5fee3d56973d9816e2002e8a3b7d9205531167c28aaa38a7"},
+    {file = "torch-2.0.0-cp39-cp39-win_amd64.whl", hash = "sha256:c7e67195e1c3e33da53954b026e89a8e1ff3bc1aeb9eb32b677172d4a9b5dcbf"},
+    {file = "torch-2.0.0-cp39-none-macosx_10_9_x86_64.whl", hash = "sha256:6e0b97beb037a165669c312591f242382e9109a240e20054d5a5782d9236cad0"},
+    {file = "torch-2.0.0-cp39-none-macosx_11_0_arm64.whl", hash = "sha256:297a4919aff1c0f98a58ebe969200f71350a1d4d4f986dbfd60c02ffce780e99"},
+]
+
+[package.dependencies]
+filelock = "*"
+jinja2 = "*"
+networkx = "*"
+nvidia-cublas-cu11 = {version = "11.10.3.66", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
+nvidia-cuda-cupti-cu11 = {version = "11.7.101", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
+nvidia-cuda-nvrtc-cu11 = {version = "11.7.99", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
+nvidia-cuda-runtime-cu11 = {version = "11.7.99", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
+nvidia-cudnn-cu11 = {version = "8.5.0.96", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
+nvidia-cufft-cu11 = {version = "10.9.0.58", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
+nvidia-curand-cu11 = {version = "10.2.10.91", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
+nvidia-cusolver-cu11 = {version = "11.4.0.1", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
+nvidia-cusparse-cu11 = {version = "11.7.4.91", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
+nvidia-nccl-cu11 = {version = "2.14.3", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
+nvidia-nvtx-cu11 = {version = "11.7.91", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
+sympy = "*"
+triton = {version = "2.0.0", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
+typing-extensions = "*"
+
+[package.extras]
+opt-einsum = ["opt-einsum (>=3.3)"]
+
+[[package]]
+name = "torchaudio"
+version = "2.0.1"
+description = "An audio package for PyTorch"
+optional = false
+python-versions = "*"
+files = [
+    {file = "torchaudio-2.0.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:b5d21ebbb55e7040d418d5062b0e882f9660d68b477b38fd436fa6c92ccbb52a"},
+    {file = "torchaudio-2.0.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:6dbcd93b29d71a2f500f36a34ea5e467f510f773da85322098e6bdd8c9dc9948"},
+    {file = "torchaudio-2.0.1-cp310-cp310-manylinux1_x86_64.whl", hash = "sha256:5fdaba10ff06d098d603d9eb8d2ff541c3f3fe28ba178a78787190cec0d5187f"},
+    {file = "torchaudio-2.0.1-cp310-cp310-manylinux2014_aarch64.whl", hash = "sha256:6419199c773c5045c594ff950d5e5dbbfa6c830892ec09721d4ed8704b702bfd"},
+    {file = "torchaudio-2.0.1-cp310-cp310-win_amd64.whl", hash = "sha256:a5c81e480e5dcdcba065af1e3e31678ac29518991f00260094d37a39e63d76e5"},
+    {file = "torchaudio-2.0.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:e2a047675493c0aa258fec621ef40e8b01abe3d8dbc872152e4b5998418aa3c5"},
+    {file = "torchaudio-2.0.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:91a28e587f708a03320eddbcc4a7dd1ad7150b3d4846b6c1557d85cc89a8d06c"},
+    {file = "torchaudio-2.0.1-cp311-cp311-manylinux1_x86_64.whl", hash = "sha256:ba7740d98f601218ff667598ab3d9dab5f326878374fcb52d656f4ff033b9e96"},
+    {file = "torchaudio-2.0.1-cp311-cp311-manylinux2014_aarch64.whl", hash = "sha256:f401b192921c8b77cc5e478ede589b256dba463f1cee91172ecb376fea45a288"},
+    {file = "torchaudio-2.0.1-cp311-cp311-win_amd64.whl", hash = "sha256:0ef6754cf75ca5fd5117cb6243a6cf33552d67e9af0075aa6954b2c34bbf1036"},
+    {file = "torchaudio-2.0.1-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:022ca1baa4bb819b78343bd47b57ff6dc6f9fc19fa4ef269946aadf7e62db3c0"},
+    {file = "torchaudio-2.0.1-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:a153ad5cdb62de8ec9fd1360a0d080bbaf39d578ae04e788db211571e675b7e0"},
+    {file = "torchaudio-2.0.1-cp38-cp38-manylinux1_x86_64.whl", hash = "sha256:aa7897774ab4156d0b72f7078b823ebc1371ee24c50df965447782889552367a"},
+    {file = "torchaudio-2.0.1-cp38-cp38-manylinux2014_aarch64.whl", hash = "sha256:48d133593cddfe0424a350b566d54065bf6fe7469654de7add2f11b3ef03c5d9"},
+    {file = "torchaudio-2.0.1-cp38-cp38-win_amd64.whl", hash = "sha256:ac65eb067feee435debba81adfe8337fa007a06de6508c0d80261c5562b6d098"},
+    {file = "torchaudio-2.0.1-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:e3c6c8f9ea9f0e2df7a0b9375b0dcf955906e38fc12fab542b72a861564af8e7"},
+    {file = "torchaudio-2.0.1-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:1d0cf0779a334ec1861e9fa28bceb66a633c42e8f6b3322e2e37ff9f20d0ae81"},
+    {file = "torchaudio-2.0.1-cp39-cp39-manylinux1_x86_64.whl", hash = "sha256:ab7acd2b5d351a2c65e4d935bb90b9256382bed93df57ee177bdbbe31c3cc984"},
+    {file = "torchaudio-2.0.1-cp39-cp39-manylinux2014_aarch64.whl", hash = "sha256:77b953fd7278773269a9477315b8998ae7e5011cc4b2907e0df18162327482f1"},
+    {file = "torchaudio-2.0.1-cp39-cp39-win_amd64.whl", hash = "sha256:c01bcea9d4c4a6616452e6cbd44d55913d8e6dee58191b925f35d46a2bf6e71b"},
+]
+
+[package.dependencies]
+torch = "2.0.0"
+
+[[package]]
+name = "torchgen"
+version = "0.0.1"
+description = "Ready to use implementations of state-of-the-art generative models in PyTorch"
+optional = false
+python-versions = ">=3.7, <4"
+files = [
+    {file = "torchgen-0.0.1-py3-none-any.whl", hash = "sha256:78d02b5e4ea0231ce46b4262564a05a9cb2047fcfcdcf4a4ab56230a0f21be66"},
+]
+
+[[package]]
+name = "tornado"
+version = "6.3.2"
+description = "Tornado is a Python web framework and asynchronous networking library, originally developed at FriendFeed."
+optional = false
+python-versions = ">= 3.8"
+files = [
+    {file = "tornado-6.3.2-cp38-abi3-macosx_10_9_universal2.whl", hash = "sha256:c367ab6c0393d71171123ca5515c61ff62fe09024fa6bf299cd1339dc9456829"},
+    {file = "tornado-6.3.2-cp38-abi3-macosx_10_9_x86_64.whl", hash = "sha256:b46a6ab20f5c7c1cb949c72c1994a4585d2eaa0be4853f50a03b5031e964fc7c"},
+    {file = "tornado-6.3.2-cp38-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c2de14066c4a38b4ecbbcd55c5cc4b5340eb04f1c5e81da7451ef555859c833f"},
+    {file = "tornado-6.3.2-cp38-abi3-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:05615096845cf50a895026f749195bf0b10b8909f9be672f50b0fe69cba368e4"},
+    {file = "tornado-6.3.2-cp38-abi3-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:5b17b1cf5f8354efa3d37c6e28fdfd9c1c1e5122f2cb56dac121ac61baa47cbe"},
+    {file = "tornado-6.3.2-cp38-abi3-musllinux_1_1_aarch64.whl", hash = "sha256:29e71c847a35f6e10ca3b5c2990a52ce38b233019d8e858b755ea6ce4dcdd19d"},
+    {file = "tornado-6.3.2-cp38-abi3-musllinux_1_1_i686.whl", hash = "sha256:834ae7540ad3a83199a8da8f9f2d383e3c3d5130a328889e4cc991acc81e87a0"},
+    {file = "tornado-6.3.2-cp38-abi3-musllinux_1_1_x86_64.whl", hash = "sha256:6a0848f1aea0d196a7c4f6772197cbe2abc4266f836b0aac76947872cd29b411"},
+    {file = "tornado-6.3.2-cp38-abi3-win32.whl", hash = "sha256:7efcbcc30b7c654eb6a8c9c9da787a851c18f8ccd4a5a3a95b05c7accfa068d2"},
+    {file = "tornado-6.3.2-cp38-abi3-win_amd64.whl", hash = "sha256:0c325e66c8123c606eea33084976c832aa4e766b7dff8aedd7587ea44a604cdf"},
+    {file = "tornado-6.3.2.tar.gz", hash = "sha256:4b927c4f19b71e627b13f3db2324e4ae660527143f9e1f2e2fb404f3a187e2ba"},
+]
+
+[[package]]
+name = "tqdm"
+version = "4.65.0"
+description = "Fast, Extensible Progress Meter"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "tqdm-4.65.0-py3-none-any.whl", hash = "sha256:c4f53a17fe37e132815abceec022631be8ffe1b9381c2e6e30aa70edc99e9671"},
+    {file = "tqdm-4.65.0.tar.gz", hash = "sha256:1871fb68a86b8fb3b59ca4cdd3dcccbc7e6d613eeed31f4c332531977b89beb5"},
+]
+
+[package.dependencies]
+colorama = {version = "*", markers = "platform_system == \"Windows\""}
+
+[package.extras]
+dev = ["py-make (>=0.1.0)", "twine", "wheel"]
+notebook = ["ipywidgets (>=6)"]
+slack = ["slack-sdk"]
+telegram = ["requests"]
+
+[[package]]
+name = "traitlets"
+version = "5.9.0"
+description = "Traitlets Python configuration system"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "traitlets-5.9.0-py3-none-any.whl", hash = "sha256:9e6ec080259b9a5940c797d58b613b5e31441c2257b87c2e795c5228ae80d2d8"},
+    {file = "traitlets-5.9.0.tar.gz", hash = "sha256:f6cde21a9c68cf756af02035f72d5a723bf607e862e7be33ece505abf4a3bad9"},
+]
+
+[package.extras]
+docs = ["myst-parser", "pydata-sphinx-theme", "sphinx"]
+test = ["argcomplete (>=2.0)", "pre-commit", "pytest", "pytest-mock"]
+
+[[package]]
+name = "triton"
+version = "2.0.0"
+description = "A language and compiler for custom Deep Learning operations"
+optional = false
+python-versions = "*"
+files = [
+    {file = "triton-2.0.0-1-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:38806ee9663f4b0f7cd64790e96c579374089e58f49aac4a6608121aa55e2505"},
+    {file = "triton-2.0.0-1-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:226941c7b8595219ddef59a1fdb821e8c744289a132415ddd584facedeb475b1"},
+    {file = "triton-2.0.0-1-cp36-cp36m-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:4c9fc8c89874bc48eb7e7b2107a9b8d2c0bf139778637be5bfccb09191685cfd"},
+    {file = "triton-2.0.0-1-cp37-cp37m-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:d2684b6a60b9f174f447f36f933e9a45f31db96cb723723ecd2dcfd1c57b778b"},
+    {file = "triton-2.0.0-1-cp38-cp38-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:9d4978298b74fcf59a75fe71e535c092b023088933b2f1df933ec32615e4beef"},
+    {file = "triton-2.0.0-1-cp39-cp39-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:74f118c12b437fb2ca25e1a04759173b517582fcf4c7be11913316c764213656"},
+    {file = "triton-2.0.0-1-pp37-pypy37_pp73-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:9618815a8da1d9157514f08f855d9e9ff92e329cd81c0305003eb9ec25cc5add"},
+    {file = "triton-2.0.0-1-pp38-pypy38_pp73-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:1aca3303629cd3136375b82cb9921727f804e47ebee27b2677fef23005c3851a"},
+    {file = "triton-2.0.0-1-pp39-pypy39_pp73-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:e3e13aa8b527c9b642e3a9defcc0fbd8ffbe1c80d8ac8c15a01692478dc64d8a"},
+    {file = "triton-2.0.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:8f05a7e64e4ca0565535e3d5d3405d7e49f9d308505bb7773d21fb26a4c008c2"},
+    {file = "triton-2.0.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bb4b99ca3c6844066e516658541d876c28a5f6e3a852286bbc97ad57134827fd"},
+    {file = "triton-2.0.0-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:47b4d70dc92fb40af553b4460492c31dc7d3a114a979ffb7a5cdedb7eb546c08"},
+    {file = "triton-2.0.0-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:fedce6a381901b1547e0e7e1f2546e4f65dca6d91e2d8a7305a2d1f5551895be"},
+    {file = "triton-2.0.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:75834f27926eab6c7f00ce73aaf1ab5bfb9bec6eb57ab7c0bfc0a23fac803b4c"},
+    {file = "triton-2.0.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0117722f8c2b579cd429e0bee80f7731ae05f63fe8e9414acd9a679885fcbf42"},
+    {file = "triton-2.0.0-pp37-pypy37_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bcd9be5d0c2e45d2b7e6ddc6da20112b6862d69741576f9c3dbaf941d745ecae"},
+    {file = "triton-2.0.0-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:42a0d2c3fc2eab4ba71384f2e785fbfd47aa41ae05fa58bf12cb31dcbd0aeceb"},
+    {file = "triton-2.0.0-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:52c47b72c72693198163ece9d90a721299e4fb3b8e24fd13141e384ad952724f"},
+]
+
+[package.dependencies]
+cmake = "*"
+filelock = "*"
+lit = "*"
+torch = "*"
+
+[package.extras]
+tests = ["autopep8", "flake8", "isort", "numpy", "pytest", "scipy (>=1.7.1)"]
+tutorials = ["matplotlib", "pandas", "tabulate"]
+
+[[package]]
+name = "typing-extensions"
+version = "4.5.0"
+description = "Backported and Experimental Type Hints for Python 3.7+"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "typing_extensions-4.5.0-py3-none-any.whl", hash = "sha256:fb33085c39dd998ac16d1431ebc293a8b3eedd00fd4a32de0ff79002c19511b4"},
+    {file = "typing_extensions-4.5.0.tar.gz", hash = "sha256:5cb5f4a79139d699607b3ef622a1dedafa84e115ab0024e0d9c044a9479ca7cb"},
+]
+
+[[package]]
+name = "tzdata"
+version = "2023.3"
+description = "Provider of IANA time zone data"
+optional = false
+python-versions = ">=2"
+files = [
+    {file = "tzdata-2023.3-py2.py3-none-any.whl", hash = "sha256:7e65763eef3120314099b6939b5546db7adce1e7d6f2e179e3df563c70511eda"},
+    {file = "tzdata-2023.3.tar.gz", hash = "sha256:11ef1e08e54acb0d4f95bdb1be05da659673de4acbd21bf9c69e94cc5e907a3a"},
+]
+
+[[package]]
+name = "uc-micro-py"
+version = "1.0.1"
+description = "Micro subset of unicode data files for linkify-it-py projects."
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "uc-micro-py-1.0.1.tar.gz", hash = "sha256:b7cdf4ea79433043ddfe2c82210208f26f7962c0cfbe3bacb05ee879a7fdb596"},
+    {file = "uc_micro_py-1.0.1-py3-none-any.whl", hash = "sha256:316cfb8b6862a0f1d03540f0ae6e7b033ff1fa0ddbe60c12cbe0d4cec846a69f"},
+]
+
+[package.extras]
+test = ["coverage", "pytest", "pytest-cov"]
+
+[[package]]
+name = "urllib3"
+version = "1.26.15"
+description = "HTTP library with thread-safe connection pooling, file post, and more."
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*"
+files = [
+    {file = "urllib3-1.26.15-py2.py3-none-any.whl", hash = "sha256:aa751d169e23c7479ce47a0cb0da579e3ede798f994f5816a74e4f4500dcea42"},
+    {file = "urllib3-1.26.15.tar.gz", hash = "sha256:8a388717b9476f934a21484e8c8e61875ab60644d29b9b39e11e4b9dc1c6b305"},
+]
+
+[package.extras]
+brotli = ["brotli (>=1.0.9)", "brotlicffi (>=0.8.0)", "brotlipy (>=0.6.0)"]
+secure = ["certifi", "cryptography (>=1.3.4)", "idna (>=2.0.0)", "ipaddress", "pyOpenSSL (>=0.14)", "urllib3-secure-extra"]
+socks = ["PySocks (>=1.5.6,!=1.5.7,<2.0)"]
+
+[[package]]
+name = "uvicorn"
+version = "0.21.1"
+description = "The lightning-fast ASGI server."
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "uvicorn-0.21.1-py3-none-any.whl", hash = "sha256:e47cac98a6da10cd41e6fd036d472c6f58ede6c5dbee3dbee3ef7a100ed97742"},
+    {file = "uvicorn-0.21.1.tar.gz", hash = "sha256:0fac9cb342ba099e0d582966005f3fdba5b0290579fed4a6266dc702ca7bb032"},
+]
+
+[package.dependencies]
+click = ">=7.0"
+h11 = ">=0.8"
+
+[package.extras]
+standard = ["colorama (>=0.4)", "httptools (>=0.5.0)", "python-dotenv (>=0.13)", "pyyaml (>=5.1)", "uvloop (>=0.14.0,!=0.15.0,!=0.15.1)", "watchfiles (>=0.13)", "websockets (>=10.4)"]
+
+[[package]]
+name = "websockets"
+version = "11.0"
+description = "An implementation of the WebSocket Protocol (RFC 6455 & 7692)"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "websockets-11.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:269e3547877a6ca55f62acdf291b256b01bc3469535e892af36afd3e17de284a"},
+    {file = "websockets-11.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:70a4e03d2416c1dad16ccfab97c975192337c6481b07167c90221f1926893e1e"},
+    {file = "websockets-11.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:4100dc8566ea3b9c0528dee73284be524ab053aebd77e3fc7439a90e0d57745b"},
+    {file = "websockets-11.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a8e0505c556b2b48078291b300d930f2fb8ba81d1e36379b637c060cfa561ae4"},
+    {file = "websockets-11.0-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:1d5bc68cec8269b4b52ab6d1d8690f56dba35f7bcb83a5487518406300f81cf1"},
+    {file = "websockets-11.0-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:067ac1f6153fc5218afc4563491dcbdb7384895cfc588a0afee962ca77fe0b58"},
+    {file = "websockets-11.0-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:910c84c0cfe4f872905b6ebe1866c579582070331abcb7a58621935eca95c18a"},
+    {file = "websockets-11.0-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:df0f7769450ca67a53182f917910e2b0b6dd3f8268f88cbfe54ee6be96812889"},
+    {file = "websockets-11.0-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:fe23605f5c351773b6fb82fcf680549980d63e126fab5213ed875686c0cec25d"},
+    {file = "websockets-11.0-cp310-cp310-win32.whl", hash = "sha256:eb2e7cd654a05c36fccf726385c64a0e1027997d05ba0859f4d84c3d87db1623"},
+    {file = "websockets-11.0-cp310-cp310-win_amd64.whl", hash = "sha256:fb26c333751a1e3805ecc416a85dcfa3657676b185acd515fd6992f0cea898ef"},
+    {file = "websockets-11.0-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:b4a939963bae1055f14976ef2cf53e797c1997f8835ca9cf23060afc3e7d6718"},
+    {file = "websockets-11.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:d7fc189fb632f8b31af8a5b32105919662a1bbaac20912320482415b7fed9c96"},
+    {file = "websockets-11.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:6e3cfc890f1326c95fd7d4cc50f2bd496d3f014fb2da36b4525a10f226be565d"},
+    {file = "websockets-11.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:9093f4c72c23ed5e475970c6a37e77c4f3a8856223421b9eb405b9fb2170629f"},
+    {file = "websockets-11.0-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:5c56547f97bc76293522ccfcfbdde12442420f1a2c0218ff45d733a0030046df"},
+    {file = "websockets-11.0-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ffb406b4449d4fa41ebc47faa3b9153a082f6fe0e4a0891f596a5ddb69fdeccd"},
+    {file = "websockets-11.0-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:8fad76be2c5e36fb3620ad507ac8004e9f358f5c4a9a1b756dbe7918d58884a0"},
+    {file = "websockets-11.0-cp311-cp311-musllinux_1_1_i686.whl", hash = "sha256:17eb1988d320e2f1f20e4a3523f1068a0bb08318ab123962fc99fd90c90ab0d6"},
+    {file = "websockets-11.0-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:9873288db9c673a2ba9c0f7b59a130576c50fc75f3336a706fff686009c41631"},
+    {file = "websockets-11.0-cp311-cp311-win32.whl", hash = "sha256:cf4ef6343478bf63098d3060fe06baf54d9c011b4b1b05e65e7957091cc87ef4"},
+    {file = "websockets-11.0-cp311-cp311-win_amd64.whl", hash = "sha256:713cd5fc1fd40436495c90a259274e1a4a39416c65447a256434941ddaf2f424"},
+    {file = "websockets-11.0-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:649ddddcbafd318d427b843425c92b1c035660c32507645c472c77356226cf07"},
+    {file = "websockets-11.0-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:564c53d84b95da527e96778f2cc873ef186038924abee601f9e8f12ebda9ad46"},
+    {file = "websockets-11.0-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:66d8df2db9801063e4093efe01458b1705c9f76382ad32617c005eeeb201a730"},
+    {file = "websockets-11.0-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bbcd876ed166a82d250fcf012b729315489e9d653cb659c2e013c19daba2eb8f"},
+    {file = "websockets-11.0-cp37-cp37m-musllinux_1_1_aarch64.whl", hash = "sha256:cb00963b49d343210ebbdbe69a35004fbecad73da2158e83d481cd2a6716cf19"},
+    {file = "websockets-11.0-cp37-cp37m-musllinux_1_1_i686.whl", hash = "sha256:3d6f7c2f822e439f47f3492ee3e48c87c7d134d619a42c6dba1a318504501bfb"},
+    {file = "websockets-11.0-cp37-cp37m-musllinux_1_1_x86_64.whl", hash = "sha256:c4b2ae9c0f1acec5d2f8000eb496eebb9db19055a63716ee166cf0694b945982"},
+    {file = "websockets-11.0-cp37-cp37m-win32.whl", hash = "sha256:2b363e0f9b4247a0c7482e22c70ef39fb3259a14f7c0791c9200b93145f60b4b"},
+    {file = "websockets-11.0-cp37-cp37m-win_amd64.whl", hash = "sha256:3d372c3426f165a0a22be9250526b1cd12e3556e80b4b2afaa6fd6649c99b086"},
+    {file = "websockets-11.0-cp38-cp38-macosx_10_9_universal2.whl", hash = "sha256:7eb914d37e0574246c63b995f9ca8d7bb7c2f2d53a8d4e9b00200ea856aa43c4"},
+    {file = "websockets-11.0-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:a8717a5f3a00cde308e2971064bd5fcb14e0cc08f8234b97f4eb92b505ea95d4"},
+    {file = "websockets-11.0-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:a17151722349c4af221616cca2f28e79237738bfbc53e7155240e2a8a7cc02f4"},
+    {file = "websockets-11.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a4b60686d9b2ba500847c045595eb5887f4cca7102b4615773b6f490aa611107"},
+    {file = "websockets-11.0-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:eededf25ef6b838e650eeeb1511804b82e9ece566fe6cdc11aa909d2992dcdaf"},
+    {file = "websockets-11.0-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7587f339f016f0e1b0b6f013e98c83e382c5929774f2b8234c1b2d3f01dd1339"},
+    {file = "websockets-11.0-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:26369646078e16e7364729ed3e3b1a4315ab1a22ca3c48b4e25dea48fcc1a881"},
+    {file = "websockets-11.0-cp38-cp38-musllinux_1_1_i686.whl", hash = "sha256:92f51fbe87381ff76c1791dd44d599152b400f1adfa8453613f1ff6857200ee7"},
+    {file = "websockets-11.0-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:b5bb04a77c326d727c0b986c37a76147916d79db95629267307d1be47788a020"},
+    {file = "websockets-11.0-cp38-cp38-win32.whl", hash = "sha256:50ac95111009178e58b9a25aa51702cdaad4ed843b98eb9b58d69b323ccb224e"},
+    {file = "websockets-11.0-cp38-cp38-win_amd64.whl", hash = "sha256:7a4076cd6a3678def988668fc4b1779da598e1e5c9fa26319af5499f00c23e1c"},
+    {file = "websockets-11.0-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:26559e8a385f71ce2a58f3bb1d005ddd3db7d3328ddbfbff1034f4039d46c4ec"},
+    {file = "websockets-11.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:f10d283697dec8d91fa983eb8e217c9cac27bc1032057768129b89780009318e"},
+    {file = "websockets-11.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:f74efe229e078bf5595e207e9a7b135ff37a10858263ed86be66003c4c98d47b"},
+    {file = "websockets-11.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f048c88bfcc5bf0e038630cfb970b2c479f913819fd9653db920eef3b105a2b1"},
+    {file = "websockets-11.0-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:ceab6c1827fa14ad10c6b0806941d577b21d17012a3648787ac2b946182285b4"},
+    {file = "websockets-11.0-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:817227e23897808c4bb621da7f57b1f83ee18345bdc44f5c9c1bbd3a094a73f6"},
+    {file = "websockets-11.0-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:6fdcc17348d8697c1f88bba38680cca94131f2a9db727a61fe067284e1e59e8d"},
+    {file = "websockets-11.0-cp39-cp39-musllinux_1_1_i686.whl", hash = "sha256:8b21ad915b747075f29fe2fa5590111d98988d6730d2cd212acfe52bbe6a2545"},
+    {file = "websockets-11.0-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:9ae401ad881d5329062b9b2d8160f0b2a147430974f2a3f32e6cedadddc2d634"},
+    {file = "websockets-11.0-cp39-cp39-win32.whl", hash = "sha256:ee84660927293f449760badfe010e06409edb99d72e1910e2e404d2eeff6990f"},
+    {file = "websockets-11.0-cp39-cp39-win_amd64.whl", hash = "sha256:2b4e704a9dac1faf4994e63dceae9e2f504913ff0f865bd3e5a097cbd5874a8f"},
+    {file = "websockets-11.0-pp37-pypy37_pp73-macosx_10_9_x86_64.whl", hash = "sha256:c2d6429c9bcd70ed8126a1f9ca6069e4ab95c96a3cc141fc84ce02917f7b45ec"},
+    {file = "websockets-11.0-pp37-pypy37_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ff3f67567862a853af2c0db362ede8249be50c576cd9eaf380736c6fce840414"},
+    {file = "websockets-11.0-pp37-pypy37_pp73-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:b86ce3d17bcc4b6556b2a2e1277beed74ff6b1de23f002f9763e9875e8ba361d"},
+    {file = "websockets-11.0-pp37-pypy37_pp73-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:59c4b458cc09ea6470a5eee98b06ccaa84f2a193b92e337a879612614df0f8eb"},
+    {file = "websockets-11.0-pp37-pypy37_pp73-win_amd64.whl", hash = "sha256:e5e21aeb350906dfcff321bfa6c60541a1d05cadb6d431ecf9d6376365be60d4"},
+    {file = "websockets-11.0-pp38-pypy38_pp73-macosx_10_9_x86_64.whl", hash = "sha256:8731189f6985b239a6c34a353c36b45cb3c9fed1c287fbcf7f61df9e4a7ac392"},
+    {file = "websockets-11.0-pp38-pypy38_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ee3aa7660ae0d3a4e47517bb5a545b9a02ff7b9632a640f617e755990ef65f66"},
+    {file = "websockets-11.0-pp38-pypy38_pp73-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:027aabfd053715ce0f5f6fc5107e5093e05b3c94fa555fb65375aa09cb845a66"},
+    {file = "websockets-11.0-pp38-pypy38_pp73-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:1e8c729aa179ef105f096cad12070aef230be9e2ae509eb47c3cdd9257213c14"},
+    {file = "websockets-11.0-pp38-pypy38_pp73-win_amd64.whl", hash = "sha256:ff607c6e16409ac83f1ae59cc96167fead577bc652e8dff48f7458ce082372ff"},
+    {file = "websockets-11.0-pp39-pypy39_pp73-macosx_10_9_x86_64.whl", hash = "sha256:ca3d7c08f472c40f28bb9fb99610d28dc97137612ab5308f80dac7ce79f87fe1"},
+    {file = "websockets-11.0-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:3f179deef8288dd8ec227d644ba5b711609093b634008643561f6d9c74938c3c"},
+    {file = "websockets-11.0-pp39-pypy39_pp73-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:269d33f1573a31130da9afd63a2558f60131522d3fe86d0aa2d1612ad065d27c"},
+    {file = "websockets-11.0-pp39-pypy39_pp73-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:eb0b306c1180d0268341447982b415aca7c072c84b4a59688dbc1d7d2ec25df9"},
+    {file = "websockets-11.0-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:6ae209f11e433575e17d5d6e61a2f77ceda53b4bce07df55af614aa1d618e2e7"},
+    {file = "websockets-11.0-py3-none-any.whl", hash = "sha256:6ebd971b9b2c0aaa2188c472016e4dad93108b3db425a33ad584bdc41b22026d"},
+    {file = "websockets-11.0.tar.gz", hash = "sha256:19d638549c470f5fd3b67b52b2a08f2edba5a04e05323a706937e35f5f19d056"},
+]
+
+[[package]]
+name = "werkzeug"
+version = "2.2.3"
+description = "The comprehensive WSGI web application library."
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "Werkzeug-2.2.3-py3-none-any.whl", hash = "sha256:56433961bc1f12533306c624f3be5e744389ac61d722175d543e1751285da612"},
+    {file = "Werkzeug-2.2.3.tar.gz", hash = "sha256:2e1ccc9417d4da358b9de6f174e3ac094391ea1d4fbef2d667865d819dfd0afe"},
+]
+
+[package.dependencies]
+MarkupSafe = ">=2.1.1"
+
+[package.extras]
+watchdog = ["watchdog"]
+
+[[package]]
+name = "wheel"
+version = "0.40.0"
+description = "A built-package format for Python"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "wheel-0.40.0-py3-none-any.whl", hash = "sha256:d236b20e7cb522daf2390fa84c55eea81c5c30190f90f29ae2ca1ad8355bf247"},
+    {file = "wheel-0.40.0.tar.gz", hash = "sha256:cd1196f3faee2b31968d626e1731c94f99cbdb67cf5a46e4f5656cbee7738873"},
+]
+
+[package.extras]
+test = ["pytest (>=6.0.0)"]
+
+[[package]]
+name = "yarl"
+version = "1.8.2"
+description = "Yet another URL library"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "yarl-1.8.2-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:bb81f753c815f6b8e2ddd2eef3c855cf7da193b82396ac013c661aaa6cc6b0a5"},
+    {file = "yarl-1.8.2-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:47d49ac96156f0928f002e2424299b2c91d9db73e08c4cd6742923a086f1c863"},
+    {file = "yarl-1.8.2-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:3fc056e35fa6fba63248d93ff6e672c096f95f7836938241ebc8260e062832fe"},
+    {file = "yarl-1.8.2-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:58a3c13d1c3005dbbac5c9f0d3210b60220a65a999b1833aa46bd6677c69b08e"},
+    {file = "yarl-1.8.2-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:10b08293cda921157f1e7c2790999d903b3fd28cd5c208cf8826b3b508026996"},
+    {file = "yarl-1.8.2-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:de986979bbd87272fe557e0a8fcb66fd40ae2ddfe28a8b1ce4eae22681728fef"},
+    {file = "yarl-1.8.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6c4fcfa71e2c6a3cb568cf81aadc12768b9995323186a10827beccf5fa23d4f8"},
+    {file = "yarl-1.8.2-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:ae4d7ff1049f36accde9e1ef7301912a751e5bae0a9d142459646114c70ecba6"},
+    {file = "yarl-1.8.2-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:bf071f797aec5b96abfc735ab97da9fd8f8768b43ce2abd85356a3127909d146"},
+    {file = "yarl-1.8.2-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:74dece2bfc60f0f70907c34b857ee98f2c6dd0f75185db133770cd67300d505f"},
+    {file = "yarl-1.8.2-cp310-cp310-musllinux_1_1_ppc64le.whl", hash = "sha256:df60a94d332158b444301c7f569659c926168e4d4aad2cfbf4bce0e8fb8be826"},
+    {file = "yarl-1.8.2-cp310-cp310-musllinux_1_1_s390x.whl", hash = "sha256:63243b21c6e28ec2375f932a10ce7eda65139b5b854c0f6b82ed945ba526bff3"},
+    {file = "yarl-1.8.2-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:cfa2bbca929aa742b5084fd4663dd4b87c191c844326fcb21c3afd2d11497f80"},
+    {file = "yarl-1.8.2-cp310-cp310-win32.whl", hash = "sha256:b05df9ea7496df11b710081bd90ecc3a3db6adb4fee36f6a411e7bc91a18aa42"},
+    {file = "yarl-1.8.2-cp310-cp310-win_amd64.whl", hash = "sha256:24ad1d10c9db1953291f56b5fe76203977f1ed05f82d09ec97acb623a7976574"},
+    {file = "yarl-1.8.2-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:2a1fca9588f360036242f379bfea2b8b44cae2721859b1c56d033adfd5893634"},
+    {file = "yarl-1.8.2-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:f37db05c6051eff17bc832914fe46869f8849de5b92dc4a3466cd63095d23dfd"},
+    {file = "yarl-1.8.2-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:77e913b846a6b9c5f767b14dc1e759e5aff05502fe73079f6f4176359d832581"},
+    {file = "yarl-1.8.2-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0978f29222e649c351b173da2b9b4665ad1feb8d1daa9d971eb90df08702668a"},
+    {file = "yarl-1.8.2-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:388a45dc77198b2460eac0aca1efd6a7c09e976ee768b0d5109173e521a19daf"},
+    {file = "yarl-1.8.2-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:2305517e332a862ef75be8fad3606ea10108662bc6fe08509d5ca99503ac2aee"},
+    {file = "yarl-1.8.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:42430ff511571940d51e75cf42f1e4dbdded477e71c1b7a17f4da76c1da8ea76"},
+    {file = "yarl-1.8.2-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:3150078118f62371375e1e69b13b48288e44f6691c1069340081c3fd12c94d5b"},
+    {file = "yarl-1.8.2-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:c15163b6125db87c8f53c98baa5e785782078fbd2dbeaa04c6141935eb6dab7a"},
+    {file = "yarl-1.8.2-cp311-cp311-musllinux_1_1_i686.whl", hash = "sha256:4d04acba75c72e6eb90745447d69f84e6c9056390f7a9724605ca9c56b4afcc6"},
+    {file = "yarl-1.8.2-cp311-cp311-musllinux_1_1_ppc64le.whl", hash = "sha256:e7fd20d6576c10306dea2d6a5765f46f0ac5d6f53436217913e952d19237efc4"},
+    {file = "yarl-1.8.2-cp311-cp311-musllinux_1_1_s390x.whl", hash = "sha256:75c16b2a900b3536dfc7014905a128a2bea8fb01f9ee26d2d7d8db0a08e7cb2c"},
+    {file = "yarl-1.8.2-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:6d88056a04860a98341a0cf53e950e3ac9f4e51d1b6f61a53b0609df342cc8b2"},
+    {file = "yarl-1.8.2-cp311-cp311-win32.whl", hash = "sha256:fb742dcdd5eec9f26b61224c23baea46c9055cf16f62475e11b9b15dfd5c117b"},
+    {file = "yarl-1.8.2-cp311-cp311-win_amd64.whl", hash = "sha256:8c46d3d89902c393a1d1e243ac847e0442d0196bbd81aecc94fcebbc2fd5857c"},
+    {file = "yarl-1.8.2-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:ceff9722e0df2e0a9e8a79c610842004fa54e5b309fe6d218e47cd52f791d7ef"},
+    {file = "yarl-1.8.2-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:3f6b4aca43b602ba0f1459de647af954769919c4714706be36af670a5f44c9c1"},
+    {file = "yarl-1.8.2-cp37-cp37m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:1684a9bd9077e922300ecd48003ddae7a7474e0412bea38d4631443a91d61077"},
+    {file = "yarl-1.8.2-cp37-cp37m-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:ebb78745273e51b9832ef90c0898501006670d6e059f2cdb0e999494eb1450c2"},
+    {file = "yarl-1.8.2-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3adeef150d528ded2a8e734ebf9ae2e658f4c49bf413f5f157a470e17a4a2e89"},
+    {file = "yarl-1.8.2-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:57a7c87927a468e5a1dc60c17caf9597161d66457a34273ab1760219953f7f4c"},
+    {file = "yarl-1.8.2-cp37-cp37m-musllinux_1_1_aarch64.whl", hash = "sha256:efff27bd8cbe1f9bd127e7894942ccc20c857aa8b5a0327874f30201e5ce83d0"},
+    {file = "yarl-1.8.2-cp37-cp37m-musllinux_1_1_i686.whl", hash = "sha256:a783cd344113cb88c5ff7ca32f1f16532a6f2142185147822187913eb989f739"},
+    {file = "yarl-1.8.2-cp37-cp37m-musllinux_1_1_ppc64le.whl", hash = "sha256:705227dccbe96ab02c7cb2c43e1228e2826e7ead880bb19ec94ef279e9555b5b"},
+    {file = "yarl-1.8.2-cp37-cp37m-musllinux_1_1_s390x.whl", hash = "sha256:34c09b43bd538bf6c4b891ecce94b6fa4f1f10663a8d4ca589a079a5018f6ed7"},
+    {file = "yarl-1.8.2-cp37-cp37m-musllinux_1_1_x86_64.whl", hash = "sha256:a48f4f7fea9a51098b02209d90297ac324241bf37ff6be6d2b0149ab2bd51b37"},
+    {file = "yarl-1.8.2-cp37-cp37m-win32.whl", hash = "sha256:0414fd91ce0b763d4eadb4456795b307a71524dbacd015c657bb2a39db2eab89"},
+    {file = "yarl-1.8.2-cp37-cp37m-win_amd64.whl", hash = "sha256:d881d152ae0007809c2c02e22aa534e702f12071e6b285e90945aa3c376463c5"},
+    {file = "yarl-1.8.2-cp38-cp38-macosx_10_9_universal2.whl", hash = "sha256:5df5e3d04101c1e5c3b1d69710b0574171cc02fddc4b23d1b2813e75f35a30b1"},
+    {file = "yarl-1.8.2-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:7a66c506ec67eb3159eea5096acd05f5e788ceec7b96087d30c7d2865a243918"},
+    {file = "yarl-1.8.2-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:2b4fa2606adf392051d990c3b3877d768771adc3faf2e117b9de7eb977741229"},
+    {file = "yarl-1.8.2-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:1e21fb44e1eff06dd6ef971d4bdc611807d6bd3691223d9c01a18cec3677939e"},
+    {file = "yarl-1.8.2-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:93202666046d9edadfe9f2e7bf5e0782ea0d497b6d63da322e541665d65a044e"},
+    {file = "yarl-1.8.2-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:fc77086ce244453e074e445104f0ecb27530d6fd3a46698e33f6c38951d5a0f1"},
+    {file = "yarl-1.8.2-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:64dd68a92cab699a233641f5929a40f02a4ede8c009068ca8aa1fe87b8c20ae3"},
+    {file = "yarl-1.8.2-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:1b372aad2b5f81db66ee7ec085cbad72c4da660d994e8e590c997e9b01e44901"},
+    {file = "yarl-1.8.2-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:e6f3515aafe0209dd17fb9bdd3b4e892963370b3de781f53e1746a521fb39fc0"},
+    {file = "yarl-1.8.2-cp38-cp38-musllinux_1_1_i686.whl", hash = "sha256:dfef7350ee369197106805e193d420b75467b6cceac646ea5ed3049fcc950a05"},
+    {file = "yarl-1.8.2-cp38-cp38-musllinux_1_1_ppc64le.whl", hash = "sha256:728be34f70a190566d20aa13dc1f01dc44b6aa74580e10a3fb159691bc76909d"},
+    {file = "yarl-1.8.2-cp38-cp38-musllinux_1_1_s390x.whl", hash = "sha256:ff205b58dc2929191f68162633d5e10e8044398d7a45265f90a0f1d51f85f72c"},
+    {file = "yarl-1.8.2-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:baf211dcad448a87a0d9047dc8282d7de59473ade7d7fdf22150b1d23859f946"},
+    {file = "yarl-1.8.2-cp38-cp38-win32.whl", hash = "sha256:272b4f1599f1b621bf2aabe4e5b54f39a933971f4e7c9aa311d6d7dc06965165"},
+    {file = "yarl-1.8.2-cp38-cp38-win_amd64.whl", hash = "sha256:326dd1d3caf910cd26a26ccbfb84c03b608ba32499b5d6eeb09252c920bcbe4f"},
+    {file = "yarl-1.8.2-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:f8ca8ad414c85bbc50f49c0a106f951613dfa5f948ab69c10ce9b128d368baf8"},
+    {file = "yarl-1.8.2-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:418857f837347e8aaef682679f41e36c24250097f9e2f315d39bae3a99a34cbf"},
+    {file = "yarl-1.8.2-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:ae0eec05ab49e91a78700761777f284c2df119376e391db42c38ab46fd662b77"},
+    {file = "yarl-1.8.2-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:009a028127e0a1755c38b03244c0bea9d5565630db9c4cf9572496e947137a87"},
+    {file = "yarl-1.8.2-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:3edac5d74bb3209c418805bda77f973117836e1de7c000e9755e572c1f7850d0"},
+    {file = "yarl-1.8.2-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:da65c3f263729e47351261351b8679c6429151ef9649bba08ef2528ff2c423b2"},
+    {file = "yarl-1.8.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0ef8fb25e52663a1c85d608f6dd72e19bd390e2ecaf29c17fb08f730226e3a08"},
+    {file = "yarl-1.8.2-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:bcd7bb1e5c45274af9a1dd7494d3c52b2be5e6bd8d7e49c612705fd45420b12d"},
+    {file = "yarl-1.8.2-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:44ceac0450e648de86da8e42674f9b7077d763ea80c8ceb9d1c3e41f0f0a9951"},
+    {file = "yarl-1.8.2-cp39-cp39-musllinux_1_1_i686.whl", hash = "sha256:97209cc91189b48e7cfe777237c04af8e7cc51eb369004e061809bcdf4e55220"},
+    {file = "yarl-1.8.2-cp39-cp39-musllinux_1_1_ppc64le.whl", hash = "sha256:48dd18adcf98ea9cd721a25313aef49d70d413a999d7d89df44f469edfb38a06"},
+    {file = "yarl-1.8.2-cp39-cp39-musllinux_1_1_s390x.whl", hash = "sha256:e59399dda559688461762800d7fb34d9e8a6a7444fd76ec33220a926c8be1516"},
+    {file = "yarl-1.8.2-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:d617c241c8c3ad5c4e78a08429fa49e4b04bedfc507b34b4d8dceb83b4af3588"},
+    {file = "yarl-1.8.2-cp39-cp39-win32.whl", hash = "sha256:cb6d48d80a41f68de41212f3dfd1a9d9898d7841c8f7ce6696cf2fd9cb57ef83"},
+    {file = "yarl-1.8.2-cp39-cp39-win_amd64.whl", hash = "sha256:6604711362f2dbf7160df21c416f81fac0de6dbcf0b5445a2ef25478ecc4c778"},
+    {file = "yarl-1.8.2.tar.gz", hash = "sha256:49d43402c6e3013ad0978602bf6bf5328535c48d192304b91b97a3c6790b1562"},
+]
+
+[package.dependencies]
+idna = ">=2.0"
+multidict = ">=4.0"
+
+[[package]]
+name = "zipp"
+version = "3.15.0"
+description = "Backport of pathlib-compatible object wrapper for zip files"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "zipp-3.15.0-py3-none-any.whl", hash = "sha256:48904fc76a60e542af151aded95726c1a5c34ed43ab4134b597665c86d7ad556"},
+    {file = "zipp-3.15.0.tar.gz", hash = "sha256:112929ad649da941c23de50f356a2b5570c954b65150642bccdd66bf194d224b"},
+]
+
+[package.extras]
+docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
+testing = ["big-O", "flake8 (<5)", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)"]
+
+[metadata]
+lock-version = "2.0"
+python-versions = "^3.8"
+content-hash = "400ac506bf8f14333fa2e073fd39cc765a1941aab895d5ed6f9dd264146fc726"
diff --git a/pretrained/.gitignore b/pretrained/.gitignore
new file mode 100644
index 0000000000000000000000000000000000000000..d6b7ef32c8478a48c3994dcadc86837f4371184d
--- /dev/null
+++ b/pretrained/.gitignore
@@ -0,0 +1,2 @@
+*
+!.gitignore
diff --git a/pretrained_v2/.gitignore b/pretrained_v2/.gitignore
new file mode 100644
index 0000000000000000000000000000000000000000..d6b7ef32c8478a48c3994dcadc86837f4371184d
--- /dev/null
+++ b/pretrained_v2/.gitignore
@@ -0,0 +1,2 @@
+*
+!.gitignore
diff --git a/pyproject.toml b/pyproject.toml
new file mode 100644
index 0000000000000000000000000000000000000000..5b152583542f7129fe688c2eccd7285ac37f1714
--- /dev/null
+++ b/pyproject.toml
@@ -0,0 +1,62 @@
+[tool.poetry]
+name = "rvc-beta"
+version = "0.1.0"
+description = ""
+authors = ["lj1995"]
+license = "MIT"
+
+[tool.poetry.dependencies]
+python = "^3.8"
+torch = "^2.0.0"
+torchaudio = "^2.0.1"
+Cython = "^0.29.34"
+gradio = "^3.34.0"
+future = "^0.18.3"
+pydub = "^0.25.1"
+soundfile = "^0.12.1"
+ffmpeg-python = "^0.2.0"
+tensorboardX = "^2.6"
+functorch = "^2.0.0"
+fairseq = "^0.12.2"
+faiss-cpu = "^1.7.2"
+Jinja2 = "^3.1.2"
+json5 = "^0.9.11"
+librosa = "0.9.2"
+llvmlite = "0.39.0"
+Markdown = "^3.4.3"
+matplotlib = "^3.7.1"
+matplotlib-inline = "^0.1.6"
+numba = "0.56.4"
+numpy = "1.23.5"
+scipy = "1.9.3"
+praat-parselmouth = "^0.4.3"
+Pillow = "9.3.0"
+pyworld = "^0.3.2"
+resampy = "^0.4.2"
+scikit-learn = "^1.2.2"
+starlette = "^0.27.0"
+tensorboard = "^2.12.1"
+tensorboard-data-server = "^0.7.0"
+tensorboard-plugin-wit = "^1.8.1"
+torchgen = "^0.0.1"
+tqdm = "^4.65.0"
+tornado = "^6.3"
+Werkzeug = "^2.2.3"
+uc-micro-py = "^1.0.1"
+sympy = "^1.11.1"
+tabulate = "^0.9.0"
+PyYAML = "^6.0"
+pyasn1 = "^0.4.8"
+pyasn1-modules = "^0.2.8"
+fsspec = "^2023.3.0"
+absl-py = "^1.4.0"
+audioread = "^3.0.0"
+uvicorn = "^0.21.1"
+colorama = "^0.4.6"
+torchcrepe = "0.0.20"
+
+[tool.poetry.dev-dependencies]
+
+[build-system]
+requires = ["poetry-core>=1.0.0"]
+build-backend = "poetry.core.masonry.api"
diff --git a/requirements-dml.txt b/requirements-dml.txt
new file mode 100644
index 0000000000000000000000000000000000000000..445fb1e6e3691ea78275d75b0c146c1c2da321e7
--- /dev/null
+++ b/requirements-dml.txt
@@ -0,0 +1,48 @@
+joblib>=1.1.0
+numba==0.56.4
+numpy==1.23.5
+scipy
+librosa==0.9.1
+llvmlite==0.39.0
+fairseq==0.12.2
+faiss-cpu==1.7.3
+gradio==3.34.0
+Cython
+pydub>=0.25.1
+soundfile>=0.12.1
+ffmpeg-python>=0.2.0
+tensorboardX
+Jinja2>=3.1.2
+json5
+Markdown
+matplotlib>=3.7.0
+matplotlib-inline>=0.1.3
+praat-parselmouth>=0.4.2
+Pillow>=9.1.1
+resampy>=0.4.2
+scikit-learn
+tensorboard
+tqdm>=4.63.1
+tornado>=6.1
+Werkzeug>=2.2.3
+uc-micro-py>=1.0.1
+sympy>=1.11.1
+tabulate>=0.8.10
+PyYAML>=6.0
+pyasn1>=0.4.8
+pyasn1-modules>=0.2.8
+fsspec>=2022.11.0
+absl-py>=1.2.0
+audioread
+uvicorn>=0.21.1
+colorama>=0.4.5
+pyworld==0.3.2
+httpx
+onnxruntime-directml
+torchcrepe==0.0.20
+fastapi==0.88
+ffmpy==0.3.1
+python-dotenv>=1.0.0
+av
+edge-tts
+git+https://github.com/suno-ai/bark.git
diff --git a/requirements-ipex.txt b/requirements-ipex.txt
new file mode 100644
index 0000000000000000000000000000000000000000..afcc738df901cd1e24b3ce9be1b5ef441de54aca
--- /dev/null
+++ b/requirements-ipex.txt
@@ -0,0 +1,56 @@
+torch==2.0.1a0
+intel_extension_for_pytorch==2.0.110+xpu
+torchvision==0.15.2a0
+https://github.com/Disty0/Retrieval-based-Voice-Conversion-WebUI/releases/download/torchaudio_wheels_for_ipex/torchaudio-2.0.2+31de77d-cp310-cp310-linux_x86_64.whl
+-f https://developer.intel.com/ipex-whl-stable-xpu
+joblib>=1.1.0
+numba==0.56.4
+numpy==1.23.5
+scipy
+librosa==0.9.1
+llvmlite==0.39.0
+fairseq==0.12.2
+faiss-cpu==1.7.3
+gradio==3.34.0
+Cython
+pydub>=0.25.1
+soundfile>=0.12.1
+ffmpeg-python>=0.2.0
+tensorboardX
+Jinja2>=3.1.2
+json5
+Markdown
+matplotlib>=3.7.0
+matplotlib-inline>=0.1.3
+praat-parselmouth>=0.4.2
+Pillow>=9.1.1
+resampy>=0.4.2
+scikit-learn
+tensorboard
+tqdm>=4.63.1
+tornado>=6.1
+Werkzeug>=2.2.3
+uc-micro-py>=1.0.1
+sympy>=1.11.1
+tabulate>=0.8.10
+PyYAML>=6.0
+pyasn1>=0.4.8
+pyasn1-modules>=0.2.8
+fsspec>=2022.11.0
+absl-py>=1.2.0
+audioread
+uvicorn>=0.21.1
+colorama>=0.4.5
+pyworld==0.3.2
+httpx
+onnxruntime; sys_platform == 'darwin'
+onnxruntime-gpu; sys_platform != 'darwin'
+torchcrepe==0.0.20
+fastapi==0.88
+ffmpy==0.3.1
+python-dotenv>=1.0.0
+av
+PySimpleGUI
+sounddevice
+edge-tts
+git+https://github.com/suno-ai/bark.git
diff --git a/requirements-realtime-vc.txt b/requirements-realtime-vc.txt
new file mode 100644
index 0000000000000000000000000000000000000000..9d6935bfebd2df6533e8fafe2aa116d8ccf92085
--- /dev/null
+++ b/requirements-realtime-vc.txt
@@ -0,0 +1,29 @@
+#1.Install torch from pytorch.org:
+#torch 2.0 with cuda 11.8
+#pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118
+#torch 1.11.0 with cuda 11.3
+#pip install torch==1.11.0+cu113 torchvision==0.12.0+cu113 torchaudio==0.11.0 --extra-index-url https://download.pytorch.org/whl/cu113
+einops
+fairseq
+flask
+flask_cors
+gin
+gin_config
+librosa
+local_attention
+matplotlib
+praat-parselmouth
+pyworld
+PyYAML
+resampy
+scikit_learn
+scipy
+SoundFile
+tensorboard
+tqdm
+wave
+PySimpleGUI
+sounddevice
+gradio
+noisereduce
+torchcrepe==0.0.20
diff --git a/requirements-win-for-realtime_vc_gui-dml.txt b/requirements-win-for-realtime_vc_gui-dml.txt
new file mode 100644
index 0000000000000000000000000000000000000000..651498960713e42c8a843c2507f0413141794807
--- /dev/null
+++ b/requirements-win-for-realtime_vc_gui-dml.txt
@@ -0,0 +1,29 @@
+#1.Install torch from pytorch.org:
+#torch 2.0 with cuda 11.8
+#pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118
+#torch 1.11.0 with cuda 11.3
+#pip install torch==1.11.0+cu113 torchvision==0.12.0+cu113 torchaudio==0.11.0 --extra-index-url https://download.pytorch.org/whl/cu113
+einops
+fairseq
+flask
+flask_cors
+gin
+gin_config
+librosa
+local_attention
+matplotlib
+praat-parselmouth
+pyworld
+PyYAML
+resampy
+scikit_learn
+scipy
+SoundFile
+tensorboard
+tqdm
+wave
+PySimpleGUI
+sounddevice
+gradio
+noisereduce
+onnxruntime-directml
\ No newline at end of file
diff --git a/requirements-win-for-realtime_vc_gui.txt b/requirements-win-for-realtime_vc_gui.txt
new file mode 100644
index 0000000000000000000000000000000000000000..37ca23823fb800612369078bbb8908204442937a
--- /dev/null
+++ b/requirements-win-for-realtime_vc_gui.txt
@@ -0,0 +1,28 @@
+#1.Install torch from pytorch.org:
+#torch 2.0 with cuda 11.8
+#pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118
+#torch 1.11.0 with cuda 11.3
+#pip install torch==1.11.0+cu113 torchvision==0.12.0+cu113 torchaudio==0.11.0 --extra-index-url https://download.pytorch.org/whl/cu113
+einops
+fairseq
+flask
+flask_cors
+gin
+gin_config
+librosa
+local_attention
+matplotlib
+praat-parselmouth
+pyworld
+PyYAML
+resampy
+scikit_learn
+scipy
+SoundFile
+tensorboard
+tqdm
+wave
+PySimpleGUI
+sounddevice
+gradio
+noisereduce
diff --git a/requirements.txt b/requirements.txt
index a735a02a5b33773a5c605f28a347d99f8af88601..e48c9aa538e34a30845262538d3ad8dd53f81c93 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1 +1,57 @@
-ipython
\ No newline at end of file
+tornado>=6.1
+setuptools
+pydantic
+fairseq==0.12.2
+wheel
+google-auth-oauthlib
+pedalboard
+pydub==0.25.1
+httpx==0.23.0
+tensorboardX
+faiss_cpu==1.7.3
+ffmpeg_python==0.2.0
+ffmpy==0.3.1
+websockets>=10.0
+gradio==3.34.0
+librosa==0.9.1
+elevenlabs
+gTTS==2.3.2
+wget
+psutil
+matplotlib==3.7.2
+mega.py==1.0.8
+gdown
+edge-tts
+git+https://github.com/suno-ai/bark.git
+nltk
+noisereduce==2.0.1
+unidecode
+numba==0.57.1
+numpy==1.23.5
+onnxruntime
+onnxruntime_gpu==1.15.1
+opencv_python==4.8.0.74
+opencv_python_headless==4.8.0.74
+pandas==2.0.3
+praat-parselmouth==0.4.2
+PySimpleGUI==4.60.5
+pyworld==0.3.3
+requests==2.31.0
+resampy==0.4.2
+scikit_learn==1.3.0
+scipy==1.11.1
+yt_dlp==2023.7.6
+pyngrok==4.1.12
+sounddevice==0.4.6
+soundfile==0.12.1
+tensorboard==2.13.0
+tb_nightly==2.14.0a20230803
+torch==2.0.0
+torchcrepe==0.0.21
+torch_directml==0.2.0.dev230426
+torchaudio==2.0.1
+torchvision==0.15.1
+torchgen>=0.0.1
+tqdm==4.65.0
+python-dotenv>=1.0.0
+av
diff --git a/run.sh b/run.sh
new file mode 100644
index 0000000000000000000000000000000000000000..704c9fff20b42b8659f7b4c797cd2928af9dec7a
--- /dev/null
+++ b/run.sh
@@ -0,0 +1,61 @@
+#!/bin/bash
+
+if [[ "$(uname)" == "Darwin" ]]; then
+  # macOS specific env:
+  export PYTORCH_ENABLE_MPS_FALLBACK=1
+  export PYTORCH_MPS_HIGH_WATERMARK_RATIO=0.0
+elif [[ "$(uname)" != "Linux" ]]; then
+  echo "Unsupported operating system."
+  exit 1
+fi
+
+if [ -d ".venv" ]; then
+  echo "Activate venv..."
+  source .venv/bin/activate
+else
+  echo "Create venv..."
+  requirements_file="requirements.txt"
+
+  # Check if Python 3.8 is installed
+  if ! command -v python3 &> /dev/null; then
+    echo "Python 3 not found. Attempting to install 3.8..."
+    if [[ "$(uname)" == "Darwin" ]] && command -v brew &> /dev/null; then
+      brew install python@3.8
+    elif [[ "$(uname)" == "Linux" ]] && command -v apt-get &> /dev/null; then
+      sudo apt-get update
+      sudo apt-get install python3.8
+    else
+      echo "Please install Python 3.8 manually."
+      exit 1
+    fi
+  fi
+
+  python3 -m venv .venv
+  source .venv/bin/activate
+
+  # Check if required packages are installed and install them if not
+  if [ -f "${requirements_file}" ]; then
+    installed_packages=$(python3 -m pip freeze)
+    while IFS= read -r package; do
+      [[ "${package}" =~ ^#.* ]] && continue
+      package_name=$(echo "${package}" | sed 's/[<>=!].*//')
+      if ! echo "${installed_packages}" | grep -q "${package_name}"; then
+        echo "${package_name} not found. Attempting to install..."
+        python3 -m pip install --upgrade "${package}"
+      fi
+    done < "${requirements_file}"
+  else
+    echo "${requirements_file} not found. Please ensure the requirements file with required packages exists."
+    exit 1
+  fi
+fi
+
+# Download models
+./tools/dlmodels.sh
+
+if [[ $? -ne 0 ]]; then
+  exit 1
+fi
+
+# Run the main script
+python3 infer-web.py --pycmd python3
diff --git a/rvc_for_realtime.py b/rvc_for_realtime.py
new file mode 100644
index 0000000000000000000000000000000000000000..55070f668c385ba0a9ba50989b282448cd75e59b
--- /dev/null
+++ b/rvc_for_realtime.py
@@ -0,0 +1,297 @@
+import faiss, torch, traceback, parselmouth, numpy as np, torchcrepe, torch.nn as nn, pyworld
+from fairseq import checkpoint_utils
+from lib.infer_pack.models import (
+    SynthesizerTrnMs256NSFsid,
+    SynthesizerTrnMs256NSFsid_nono,
+    SynthesizerTrnMs768NSFsid,
+    SynthesizerTrnMs768NSFsid_nono,
+)
+import os, sys
+from time import time as ttime
+import torch.nn.functional as F
+import scipy.signal as signal
+
+now_dir = os.getcwd()
+sys.path.append(now_dir)
+from configs.config import Config
+from multiprocessing import Manager as M
+
+mm = M()
+config = Config()
+
+
+class RVC:
+    def __init__(
+        self, key, pth_path, index_path, index_rate, n_cpu, inp_q, opt_q, device
+    ) -> None:
+        """
+        初始化
+        """
+        try:
+            global config
+            self.inp_q = inp_q
+            self.opt_q = opt_q
+            self.device = device
+            self.f0_up_key = key
+            self.time_step = 160 / 16000 * 1000
+            self.f0_min = 50
+            self.f0_max = 1100
+            self.f0_mel_min = 1127 * np.log(1 + self.f0_min / 700)
+            self.f0_mel_max = 1127 * np.log(1 + self.f0_max / 700)
+            self.sr = 16000
+            self.window = 160
+            self.n_cpu = n_cpu
+            if index_rate != 0:
+                self.index = faiss.read_index(index_path)
+                self.big_npy = self.index.reconstruct_n(0, self.index.ntotal)
+                print("index search enabled")
+            self.index_rate = index_rate
+            models, _, _ = checkpoint_utils.load_model_ensemble_and_task(
+                ["hubert_base.pt"],
+                suffix="",
+            )
+            hubert_model = models[0]
+            hubert_model = hubert_model.to(config.device)
+            if config.is_half:
+                hubert_model = hubert_model.half()
+            else:
+                hubert_model = hubert_model.float()
+            hubert_model.eval()
+            self.model = hubert_model
+            cpt = torch.load(pth_path, map_location="cpu")
+            self.tgt_sr = cpt["config"][-1]
+            cpt["config"][-3] = cpt["weight"]["emb_g.weight"].shape[0]
+            self.if_f0 = cpt.get("f0", 1)
+            self.version = cpt.get("version", "v1")
+            if self.version == "v1":
+                if self.if_f0 == 1:
+                    self.net_g = SynthesizerTrnMs256NSFsid(
+                        *cpt["config"], is_half=config.is_half
+                    )
+                else:
+                    self.net_g = SynthesizerTrnMs256NSFsid_nono(*cpt["config"])
+            elif self.version == "v2":
+                if self.if_f0 == 1:
+                    self.net_g = SynthesizerTrnMs768NSFsid(
+                        *cpt["config"], is_half=config.is_half
+                    )
+                else:
+                    self.net_g = SynthesizerTrnMs768NSFsid_nono(*cpt["config"])
+            del self.net_g.enc_q
+            print(self.net_g.load_state_dict(cpt["weight"], strict=False))
+            self.net_g.eval().to(device)
+            if config.is_half:
+                self.net_g = self.net_g.half()
+            else:
+                self.net_g = self.net_g.float()
+            self.is_half = config.is_half
+        except:
+            print(traceback.format_exc())
+
+    def get_f0_post(self, f0):
+        f0_min = self.f0_min
+        f0_max = self.f0_max
+        f0_mel_min = 1127 * np.log(1 + f0_min / 700)
+        f0_mel_max = 1127 * np.log(1 + f0_max / 700)
+        f0bak = f0.copy()
+        f0_mel = 1127 * np.log(1 + f0 / 700)
+        f0_mel[f0_mel > 0] = (f0_mel[f0_mel > 0] - f0_mel_min) * 254 / (
+            f0_mel_max - f0_mel_min
+        ) + 1
+        f0_mel[f0_mel <= 1] = 1
+        f0_mel[f0_mel > 255] = 255
+        f0_coarse = np.rint(f0_mel).astype(np.int_)
+        return f0_coarse, f0bak
+
+    def get_f0(self, x, f0_up_key, n_cpu, method="harvest"):
+        n_cpu = int(n_cpu)
+        if method == "crepe":
+            return self.get_f0_crepe(x, f0_up_key)
+        if method == "rmvpe":
+            return self.get_f0_rmvpe(x, f0_up_key)
+        if method == "pm":
+            p_len = x.shape[0] // 160
+            f0 = (
+                parselmouth.Sound(x, 16000)
+                .to_pitch_ac(
+                    time_step=0.01,
+                    voicing_threshold=0.6,
+                    pitch_floor=50,
+                    pitch_ceiling=1100,
+                )
+                .selected_array["frequency"]
+            )
+
+            pad_size = (p_len - len(f0) + 1) // 2
+            if pad_size > 0 or p_len - len(f0) - pad_size > 0:
+                print(pad_size, p_len - len(f0) - pad_size)
+                f0 = np.pad(
+                    f0, [[pad_size, p_len - len(f0) - pad_size]], mode="constant"
+                )
+
+            f0 *= pow(2, f0_up_key / 12)
+            return self.get_f0_post(f0)
+        if n_cpu == 1:
+            f0, t = pyworld.harvest(
+                x.astype(np.double),
+                fs=16000,
+                f0_ceil=1100,
+                f0_floor=50,
+                frame_period=10,
+            )
+            f0 = signal.medfilt(f0, 3)
+            f0 *= pow(2, f0_up_key / 12)
+            return self.get_f0_post(f0)
+        f0bak = np.zeros(x.shape[0] // 160, dtype=np.float64)
+        length = len(x)
+        part_length = int(length / n_cpu / 160) * 160
+        ts = ttime()
+        res_f0 = mm.dict()
+        for idx in range(n_cpu):
+            tail = part_length * (idx + 1) + 320
+            if idx == 0:
+                self.inp_q.put((idx, x[:tail], res_f0, n_cpu, ts))
+            else:
+                self.inp_q.put(
+                    (idx, x[part_length * idx - 320 : tail], res_f0, n_cpu, ts)
+                )
+        while 1:
+            res_ts = self.opt_q.get()
+            if res_ts == ts:
+                break
+        f0s = [i[1] for i in sorted(res_f0.items(), key=lambda x: x[0])]
+        for idx, f0 in enumerate(f0s):
+            if idx == 0:
+                f0 = f0[:-3]
+            elif idx != n_cpu - 1:
+                f0 = f0[2:-3]
+            else:
+                f0 = f0[2:-1]
+            f0bak[
+                part_length * idx // 160 : part_length * idx // 160 + f0.shape[0]
+            ] = f0
+        f0bak = signal.medfilt(f0bak, 3)
+        f0bak *= pow(2, f0_up_key / 12)
+        return self.get_f0_post(f0bak)
+
+    def get_f0_crepe(self, x, f0_up_key):
+        audio = torch.tensor(np.copy(x))[None].float()
+        f0, pd = torchcrepe.predict(
+            audio,
+            self.sr,
+            160,
+            self.f0_min,
+            self.f0_max,
+            "full",
+            batch_size=512,
+            device=self.device,
+            return_periodicity=True,
+        )
+        pd = torchcrepe.filter.median(pd, 3)
+        f0 = torchcrepe.filter.mean(f0, 3)
+        f0[pd < 0.1] = 0
+        f0 = f0[0].cpu().numpy()
+        f0 *= pow(2, f0_up_key / 12)
+        return self.get_f0_post(f0)
+
+    def get_f0_rmvpe(self, x, f0_up_key):
+        if hasattr(self, "model_rmvpe") == False:
+            from infer.lib.rmvpe import RMVPE
+
+            print("loading rmvpe model")
+            self.model_rmvpe = RMVPE(
+                "rmvpe.pt", is_half=self.is_half, device=self.device
+            )
+            # self.model_rmvpe = RMVPE("aug2_58000_half.pt", is_half=self.is_half, device=self.device)
+        f0 = self.model_rmvpe.infer_from_audio(x, thred=0.03)
+        f0 *= pow(2, f0_up_key / 12)
+        return self.get_f0_post(f0)
+
+    def infer(
+        self,
+        feats: torch.Tensor,
+        indata: np.ndarray,
+        rate1,
+        rate2,
+        cache_pitch,
+        cache_pitchf,
+        f0method,
+    ) -> np.ndarray:
+        feats = feats.view(1, -1)
+        if config.is_half:
+            feats = feats.half()
+        else:
+            feats = feats.float()
+        feats = feats.to(self.device)
+        t1 = ttime()
+        with torch.no_grad():
+            padding_mask = torch.BoolTensor(feats.shape).to(self.device).fill_(False)
+            inputs = {
+                "source": feats,
+                "padding_mask": padding_mask,
+                "output_layer": 9 if self.version == "v1" else 12,
+            }
+            logits = self.model.extract_features(**inputs)
+            feats = (
+                self.model.final_proj(logits[0]) if self.version == "v1" else logits[0]
+            )
+        t2 = ttime()
+        try:
+            if hasattr(self, "index") and self.index_rate != 0:
+                leng_replace_head = int(rate1 * feats[0].shape[0])
+                npy = feats[0][-leng_replace_head:].cpu().numpy().astype("float32")
+                score, ix = self.index.search(npy, k=8)
+                weight = np.square(1 / score)
+                weight /= weight.sum(axis=1, keepdims=True)
+                npy = np.sum(self.big_npy[ix] * np.expand_dims(weight, axis=2), axis=1)
+                if config.is_half:
+                    npy = npy.astype("float16")
+                feats[0][-leng_replace_head:] = (
+                    torch.from_numpy(npy).unsqueeze(0).to(self.device) * self.index_rate
+                    + (1 - self.index_rate) * feats[0][-leng_replace_head:]
+                )
+            else:
+                print("index search FAIL or disabled")
+        except:
+            traceback.print_exc()
+            print("index search FAIL")
+        feats = F.interpolate(feats.permute(0, 2, 1), scale_factor=2).permute(0, 2, 1)
+        t3 = ttime()
+        if self.if_f0 == 1:
+            pitch, pitchf = self.get_f0(indata, self.f0_up_key, self.n_cpu, f0method)
+            cache_pitch[:] = np.append(cache_pitch[pitch[:-1].shape[0] :], pitch[:-1])
+            cache_pitchf[:] = np.append(
+                cache_pitchf[pitchf[:-1].shape[0] :], pitchf[:-1]
+            )
+            p_len = min(feats.shape[1], 13000, cache_pitch.shape[0])
+        else:
+            cache_pitch, cache_pitchf = None, None
+            p_len = min(feats.shape[1], 13000)
+        t4 = ttime()
+        feats = feats[:, :p_len, :]
+        if self.if_f0 == 1:
+            cache_pitch = cache_pitch[:p_len]
+            cache_pitchf = cache_pitchf[:p_len]
+            cache_pitch = torch.LongTensor(cache_pitch).unsqueeze(0).to(self.device)
+            cache_pitchf = torch.FloatTensor(cache_pitchf).unsqueeze(0).to(self.device)
+        p_len = torch.LongTensor([p_len]).to(self.device)
+        ii = 0  # sid
+        sid = torch.LongTensor([ii]).to(self.device)
+        with torch.no_grad():
+            if self.if_f0 == 1:
+                infered_audio = (
+                    self.net_g.infer(
+                        feats, p_len, cache_pitch, cache_pitchf, sid, rate2
+                    )[0][0, 0]
+                    .data.cpu()
+                    .float()
+                )
+            else:
+                infered_audio = (
+                    self.net_g.infer(feats, p_len, sid, rate2)[0][0, 0]
+                    .data.cpu()
+                    .float()
+                )
+        t5 = ttime()
+        print("time->fea-index-f0-model:", t2 - t1, t3 - t2, t4 - t3, t5 - t4)
+        return infered_audio
diff --git a/separated/.gitkeep b/separated/.gitkeep
new file mode 100644
index 0000000000000000000000000000000000000000..8b137891791fe96927ad78e64b0aad7bded08bdc
--- /dev/null
+++ b/separated/.gitkeep
@@ -0,0 +1 @@
+
diff --git a/slicer2.py b/slicer2.py
new file mode 100644
index 0000000000000000000000000000000000000000..5b29ee262aa54045e807be2cffeb41687499ba58
--- /dev/null
+++ b/slicer2.py
@@ -0,0 +1,260 @@
+import numpy as np
+
+
+# This function is obtained from librosa.
+def get_rms(
+    y,
+    frame_length=2048,
+    hop_length=512,
+    pad_mode="constant",
+):
+    padding = (int(frame_length // 2), int(frame_length // 2))
+    y = np.pad(y, padding, mode=pad_mode)
+
+    axis = -1
+    # put our new within-frame axis at the end for now
+    out_strides = y.strides + tuple([y.strides[axis]])
+    # Reduce the shape on the framing axis
+    x_shape_trimmed = list(y.shape)
+    x_shape_trimmed[axis] -= frame_length - 1
+    out_shape = tuple(x_shape_trimmed) + tuple([frame_length])
+    xw = np.lib.stride_tricks.as_strided(y, shape=out_shape, strides=out_strides)
+    if axis < 0:
+        target_axis = axis - 1
+    else:
+        target_axis = axis + 1
+    xw = np.moveaxis(xw, -1, target_axis)
+    # Downsample along the target axis
+    slices = [slice(None)] * xw.ndim
+    slices[axis] = slice(0, None, hop_length)
+    x = xw[tuple(slices)]
+
+    # Calculate power
+    power = np.mean(np.abs(x) ** 2, axis=-2, keepdims=True)
+
+    return np.sqrt(power)
+
+
+class Slicer:
+    def __init__(
+        self,
+        sr: int,
+        threshold: float = -40.0,
+        min_length: int = 5000,
+        min_interval: int = 300,
+        hop_size: int = 20,
+        max_sil_kept: int = 5000,
+    ):
+        if not min_length >= min_interval >= hop_size:
+            raise ValueError(
+                "The following condition must be satisfied: min_length >= min_interval >= hop_size"
+            )
+        if not max_sil_kept >= hop_size:
+            raise ValueError(
+                "The following condition must be satisfied: max_sil_kept >= hop_size"
+            )
+        min_interval = sr * min_interval / 1000
+        self.threshold = 10 ** (threshold / 20.0)
+        self.hop_size = round(sr * hop_size / 1000)
+        self.win_size = min(round(min_interval), 4 * self.hop_size)
+        self.min_length = round(sr * min_length / 1000 / self.hop_size)
+        self.min_interval = round(min_interval / self.hop_size)
+        self.max_sil_kept = round(sr * max_sil_kept / 1000 / self.hop_size)
+
+    def _apply_slice(self, waveform, begin, end):
+        if len(waveform.shape) > 1:
+            return waveform[
+                :, begin * self.hop_size : min(waveform.shape[1], end * self.hop_size)
+            ]
+        else:
+            return waveform[
+                begin * self.hop_size : min(waveform.shape[0], end * self.hop_size)
+            ]
+
+    # @timeit
+    def slice(self, waveform):
+        if len(waveform.shape) > 1:
+            samples = waveform.mean(axis=0)
+        else:
+            samples = waveform
+        if samples.shape[0] <= self.min_length:
+            return [waveform]
+        rms_list = get_rms(
+            y=samples, frame_length=self.win_size, hop_length=self.hop_size
+        ).squeeze(0)
+        sil_tags = []
+        silence_start = None
+        clip_start = 0
+        for i, rms in enumerate(rms_list):
+            # Keep looping while frame is silent.
+            if rms < self.threshold:
+                # Record start of silent frames.
+                if silence_start is None:
+                    silence_start = i
+                continue
+            # Keep looping while frame is not silent and silence start has not been recorded.
+            if silence_start is None:
+                continue
+            # Clear recorded silence start if interval is not enough or clip is too short
+            is_leading_silence = silence_start == 0 and i > self.max_sil_kept
+            need_slice_middle = (
+                i - silence_start >= self.min_interval
+                and i - clip_start >= self.min_length
+            )
+            if not is_leading_silence and not need_slice_middle:
+                silence_start = None
+                continue
+            # Need slicing. Record the range of silent frames to be removed.
+            if i - silence_start <= self.max_sil_kept:
+                pos = rms_list[silence_start : i + 1].argmin() + silence_start
+                if silence_start == 0:
+                    sil_tags.append((0, pos))
+                else:
+                    sil_tags.append((pos, pos))
+                clip_start = pos
+            elif i - silence_start <= self.max_sil_kept * 2:
+                pos = rms_list[
+                    i - self.max_sil_kept : silence_start + self.max_sil_kept + 1
+                ].argmin()
+                pos += i - self.max_sil_kept
+                pos_l = (
+                    rms_list[
+                        silence_start : silence_start + self.max_sil_kept + 1
+                    ].argmin()
+                    + silence_start
+                )
+                pos_r = (
+                    rms_list[i - self.max_sil_kept : i + 1].argmin()
+                    + i
+                    - self.max_sil_kept
+                )
+                if silence_start == 0:
+                    sil_tags.append((0, pos_r))
+                    clip_start = pos_r
+                else:
+                    sil_tags.append((min(pos_l, pos), max(pos_r, pos)))
+                    clip_start = max(pos_r, pos)
+            else:
+                pos_l = (
+                    rms_list[
+                        silence_start : silence_start + self.max_sil_kept + 1
+                    ].argmin()
+                    + silence_start
+                )
+                pos_r = (
+                    rms_list[i - self.max_sil_kept : i + 1].argmin()
+                    + i
+                    - self.max_sil_kept
+                )
+                if silence_start == 0:
+                    sil_tags.append((0, pos_r))
+                else:
+                    sil_tags.append((pos_l, pos_r))
+                clip_start = pos_r
+            silence_start = None
+        # Deal with trailing silence.
+        total_frames = rms_list.shape[0]
+        if (
+            silence_start is not None
+            and total_frames - silence_start >= self.min_interval
+        ):
+            silence_end = min(total_frames, silence_start + self.max_sil_kept)
+            pos = rms_list[silence_start : silence_end + 1].argmin() + silence_start
+            sil_tags.append((pos, total_frames + 1))
+        # Apply and return slices.
+        if len(sil_tags) == 0:
+            return [waveform]
+        else:
+            chunks = []
+            if sil_tags[0][0] > 0:
+                chunks.append(self._apply_slice(waveform, 0, sil_tags[0][0]))
+            for i in range(len(sil_tags) - 1):
+                chunks.append(
+                    self._apply_slice(waveform, sil_tags[i][1], sil_tags[i + 1][0])
+                )
+            if sil_tags[-1][1] < total_frames:
+                chunks.append(
+                    self._apply_slice(waveform, sil_tags[-1][1], total_frames)
+                )
+            return chunks
+
+
+def main():
+    import os.path
+    from argparse import ArgumentParser
+
+    import librosa
+    import soundfile
+
+    parser = ArgumentParser()
+    parser.add_argument("audio", type=str, help="The audio to be sliced")
+    parser.add_argument(
+        "--out", type=str, help="Output directory of the sliced audio clips"
+    )
+    parser.add_argument(
+        "--db_thresh",
+        type=float,
+        required=False,
+        default=-40,
+        help="The dB threshold for silence detection",
+    )
+    parser.add_argument(
+        "--min_length",
+        type=int,
+        required=False,
+        default=5000,
+        help="The minimum milliseconds required for each sliced audio clip",
+    )
+    parser.add_argument(
+        "--min_interval",
+        type=int,
+        required=False,
+        default=300,
+        help="The minimum milliseconds for a silence part to be sliced",
+    )
+    parser.add_argument(
+        "--hop_size",
+        type=int,
+        required=False,
+        default=10,
+        help="Frame length in milliseconds",
+    )
+    parser.add_argument(
+        "--max_sil_kept",
+        type=int,
+        required=False,
+        default=500,
+        help="The maximum silence length kept around the sliced clip, presented in milliseconds",
+    )
+    args = parser.parse_args()
+    out = args.out
+    if out is None:
+        out = os.path.dirname(os.path.abspath(args.audio))
+    audio, sr = librosa.load(args.audio, sr=None, mono=False)
+    slicer = Slicer(
+        sr=sr,
+        threshold=args.db_thresh,
+        min_length=args.min_length,
+        min_interval=args.min_interval,
+        hop_size=args.hop_size,
+        max_sil_kept=args.max_sil_kept,
+    )
+    chunks = slicer.slice(audio)
+    if not os.path.exists(out):
+        os.makedirs(out)
+    for i, chunk in enumerate(chunks):
+        if len(chunk.shape) > 1:
+            chunk = chunk.T
+        soundfile.write(
+            os.path.join(
+                out,
+                f"%s_%d.wav"
+                % (os.path.basename(args.audio).rsplit(".", maxsplit=1)[0], i),
+            ),
+            chunk,
+            sr,
+        )
+
+
+if __name__ == "__main__":
+    main()
diff --git a/stftpitchshift b/stftpitchshift
new file mode 100644
index 0000000000000000000000000000000000000000..4f62e31529b9aafede1b7c08de1f41b980fdf132
--- /dev/null
+++ b/stftpitchshift
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:eb2f50ea8e5ca1a11a587f11f25ba9182f9b24e2367ac480f430b3f04062782e
+size 1822104
diff --git a/stftpitchshift.exe b/stftpitchshift.exe
new file mode 100644
index 0000000000000000000000000000000000000000..39c73ad888644657dc44dd7df62e1a77859355f9
Binary files /dev/null and b/stftpitchshift.exe differ
diff --git a/tensorlowest.py b/tensorlowest.py
new file mode 100644
index 0000000000000000000000000000000000000000..eccd4dbf3494434e59f7defaae6ab91797263b90
--- /dev/null
+++ b/tensorlowest.py
@@ -0,0 +1,123 @@
+from tensorboard.backend.event_processing import event_accumulator
+
+import os
+from shutil import copy2
+from re import search as RSearch
+import pandas as pd
+from ast import literal_eval as LEval
+
+weights_dir = 'weights/'
+
+def find_biggest_tensorboard(tensordir):
+    try:
+        files = [f for f in os.listdir(tensordir) if f.endswith('.0')]
+        if not files:
+            print("No files with the '.0' extension found!")
+            return
+
+        max_size = 0
+        biggest_file = ""
+
+        for file in files:
+            file_path = os.path.join(tensordir, file)
+            if os.path.isfile(file_path):
+                file_size = os.path.getsize(file_path)
+                if file_size > max_size:
+                    max_size = file_size
+                    biggest_file = file
+
+        return biggest_file
+
+    except FileNotFoundError:
+        print("Couldn't find your model!")
+        return
+
+def main(model_name, save_freq, lastmdls):
+    global lowestval_weight_dir, scl
+
+    tensordir = os.path.join('logs', model_name)
+    lowestval_weight_dir = os.path.join(tensordir, "lowestvals")
+    
+    latest_file = find_biggest_tensorboard(tensordir)
+    
+    if latest_file is None:
+        print("Couldn't find a valid tensorboard file!")
+        return
+    
+    tfile = os.path.join(tensordir, latest_file)
+    
+    ea = event_accumulator.EventAccumulator(tfile,
+        size_guidance={
+        event_accumulator.COMPRESSED_HISTOGRAMS: 500,
+        event_accumulator.IMAGES: 4,
+        event_accumulator.AUDIO: 4,
+        event_accumulator.SCALARS: 0,
+        event_accumulator.HISTOGRAMS: 1,
+    })
+
+    ea.Reload()
+    ea.Tags()
+
+    scl = ea.Scalars('loss/g/total')
+
+    listwstep = {}
+    
+    for val in scl:
+        if (val.step // save_freq) * save_freq in [val.step for val in scl]:
+            listwstep[float(val.value)] = (val.step // save_freq) * save_freq
+
+    lowest_vals = sorted(listwstep.keys())[:lastmdls]
+
+    sorted_dict = {value: step for value, step in listwstep.items() if value in lowest_vals}
+    
+    return sorted_dict
+
+def selectweights(model_name, file_dict, weights_dir, lowestval_weight_dir):
+    os.makedirs(lowestval_weight_dir, exist_ok=True)
+    logdir = []
+    files = []
+    lbldict = {
+        'Values': {},
+        'Names': {}
+    }
+    weights_dir_path = os.path.join(weights_dir, "")
+    low_val_path = os.path.join(os.getcwd(), os.path.join(lowestval_weight_dir, ""))
+    
+    try:
+        file_dict = LEval(file_dict)
+    except Exception as e: 
+        print(f"Error! {e}")
+        return f"Couldn't load tensorboard file! {e}"
+    
+    weights = [f for f in os.scandir(weights_dir)]
+    for key, value in file_dict.items():
+        pattern = fr"^{model_name}_.*_s{value}\.pth$"
+        matching_weights = [f.name for f in weights if f.is_file() and RSearch(pattern, f.name)]
+        for weight in matching_weights:
+            source_path = weights_dir_path + weight
+            destination_path = os.path.join(lowestval_weight_dir, weight)
+            
+            copy2(source_path, destination_path)
+
+            logdir.append(f"File = {weight} Value: {key}, Step: {value}")
+
+            lbldict['Names'][weight] = weight
+            lbldict['Values'][weight] = key
+
+            files.append(low_val_path + weight)
+
+            print(f"File = {weight} Value: {key}, Step: {value}")
+
+            yield ('\n'.join(logdir), files, pd.DataFrame(lbldict))
+            
+
+    return ''.join(logdir), files, pd.DataFrame(lbldict)
+    
+
+if __name__ == "__main__":
+    model = str(input("Enter the name of the model: "))
+    sav_freq = int(input("Enter save frequency of the model: "))
+    ds = main(model, sav_freq)
+    
+    if ds: selectweights(model, ds, weights_dir, lowestval_weight_dir)
+    
\ No newline at end of file
diff --git a/tools/app.py b/tools/app.py
new file mode 100644
index 0000000000000000000000000000000000000000..602fbb71a49f2537295337cdcecf501abdd74153
--- /dev/null
+++ b/tools/app.py
@@ -0,0 +1,148 @@
+import logging
+import os
+
+# os.system("wget -P cvec/ https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/hubert_base.pt")
+import gradio as gr
+from dotenv import load_dotenv
+
+from configs.config import Config
+from i18n import I18nAuto
+from infer.modules.vc.pipeline import Pipeline
+VC = Pipeline
+
+logging.getLogger("numba").setLevel(logging.WARNING)
+logging.getLogger("markdown_it").setLevel(logging.WARNING)
+logging.getLogger("urllib3").setLevel(logging.WARNING)
+logging.getLogger("matplotlib").setLevel(logging.WARNING)
+logger = logging.getLogger(__name__)
+
+i18n = I18nAuto()
+#(i18n)
+
+load_dotenv()
+config = Config()
+vc = VC(config)
+
+weight_root = os.getenv("weight_root")
+weight_uvr5_root = os.getenv("weight_uvr5_root")
+index_root = os.getenv("index_root")
+names = []
+hubert_model = None
+for name in os.listdir(weight_root):
+    if name.endswith(".pth"):
+        names.append(name)
+index_paths = []
+for root, dirs, files in os.walk(index_root, topdown=False):
+    for name in files:
+        if name.endswith(".index") and "trained" not in name:
+            index_paths.append("%s/%s" % (root, name))
+
+
+app = gr.Blocks()
+with app:
+    with gr.Tabs():
+        with gr.TabItem("在线demo"):
+            gr.Markdown(
+                value="""
+                RVC 在线demo
+                """
+            )
+            sid = gr.Dropdown(label=i18n("推理音色"), choices=sorted(names))
+            with gr.Column():
+                spk_item = gr.Slider(
+                    minimum=0,
+                    maximum=2333,
+                    step=1,
+                    label=i18n("请选择说话人id"),
+                    value=0,
+                    visible=False,
+                    interactive=True,
+                )
+            sid.change(fn=vc.get_vc, inputs=[sid], outputs=[spk_item])
+            gr.Markdown(
+                value=i18n("男转女推荐+12key, 女转男推荐-12key, 如果音域爆炸导致音色失真也可以自己调整到合适音域. ")
+            )
+            vc_input3 = gr.Audio(label="上传音频（长度小于90秒）")
+            vc_transform0 = gr.Number(label=i18n("变调(整数, 半音数量, 升八度12降八度-12)"), value=0)
+            f0method0 = gr.Radio(
+                label=i18n("选择音高提取算法,输入歌声可用pm提速,harvest低音好但巨慢无比,crepe效果好但吃GPU"),
+                choices=["pm", "harvest", "crepe", "rmvpe"],
+                value="pm",
+                interactive=True,
+            )
+            filter_radius0 = gr.Slider(
+                minimum=0,
+                maximum=7,
+                label=i18n(">=3则使用对harvest音高识别的结果使用中值滤波，数值为滤波半径，使用可以削弱哑音"),
+                value=3,
+                step=1,
+                interactive=True,
+            )
+            with gr.Column():
+                file_index1 = gr.Textbox(
+                    label=i18n("特征检索库文件路径,为空则使用下拉的选择结果"),
+                    value="",
+                    interactive=False,
+                    visible=False,
+                )
+            file_index2 = gr.Dropdown(
+                label=i18n("自动检测index路径,下拉式选择(dropdown)"),
+                choices=sorted(index_paths),
+                interactive=True,
+            )
+            index_rate1 = gr.Slider(
+                minimum=0,
+                maximum=1,
+                label=i18n("检索特征占比"),
+                value=0.88,
+                interactive=True,
+            )
+            resample_sr0 = gr.Slider(
+                minimum=0,
+                maximum=48000,
+                label=i18n("后处理重采样至最终采样率，0为不进行重采样"),
+                value=0,
+                step=1,
+                interactive=True,
+            )
+            rms_mix_rate0 = gr.Slider(
+                minimum=0,
+                maximum=1,
+                label=i18n("输入源音量包络替换输出音量包络融合比例，越靠近1越使用输出包络"),
+                value=1,
+                interactive=True,
+            )
+            protect0 = gr.Slider(
+                minimum=0,
+                maximum=0.5,
+                label=i18n("保护清辅音和呼吸声，防止电音撕裂等artifact，拉满0.5不开启，调低加大保护力度但可能降低索引效果"),
+                value=0.33,
+                step=0.01,
+                interactive=True,
+            )
+            f0_file = gr.File(label=i18n("F0曲线文件, 可选, 一行一个音高, 代替默认F0及升降调"))
+            but0 = gr.Button(i18n("转换"), variant="primary")
+            vc_output1 = gr.Textbox(label=i18n("输出信息"))
+            vc_output2 = gr.Audio(label=i18n("输出音频(右下角三个点,点了可以下载)"))
+            but0.click(
+                vc.vc_single,
+                [
+                    spk_item,
+                    vc_input3,
+                    vc_transform0,
+                    f0_file,
+                    f0method0,
+                    file_index1,
+                    file_index2,
+                    # file_big_npy1,
+                    index_rate1,
+                    filter_radius0,
+                    resample_sr0,
+                    rms_mix_rate0,
+                    protect0,
+                ],
+                [vc_output1, vc_output2],
+            )
+
+
+app.launch()
diff --git a/tools/calc_rvc_model_similarity.py b/tools/calc_rvc_model_similarity.py
new file mode 100644
index 0000000000000000000000000000000000000000..42496e088e51dc5162d0714470c2226f696e260c
--- /dev/null
+++ b/tools/calc_rvc_model_similarity.py
@@ -0,0 +1,96 @@
+# This code references https://huggingface.co/JosephusCheung/ASimilarityCalculatior/blob/main/qwerty.py
+# Fill in the path of the model to be queried and the root directory of the reference models, and this script will return the similarity between the model to be queried and all reference models.
+import os
+import logging
+
+logger = logging.getLogger(__name__)
+
+import torch
+import torch.nn as nn
+import torch.nn.functional as F
+
+
+def cal_cross_attn(to_q, to_k, to_v, rand_input):
+    hidden_dim, embed_dim = to_q.shape
+    attn_to_q = nn.Linear(hidden_dim, embed_dim, bias=False)
+    attn_to_k = nn.Linear(hidden_dim, embed_dim, bias=False)
+    attn_to_v = nn.Linear(hidden_dim, embed_dim, bias=False)
+    attn_to_q.load_state_dict({"weight": to_q})
+    attn_to_k.load_state_dict({"weight": to_k})
+    attn_to_v.load_state_dict({"weight": to_v})
+
+    return torch.einsum(
+        "ik, jk -> ik",
+        F.softmax(
+            torch.einsum("ij, kj -> ik", attn_to_q(rand_input), attn_to_k(rand_input)),
+            dim=-1,
+        ),
+        attn_to_v(rand_input),
+    )
+
+
+def model_hash(filename):
+    try:
+        with open(filename, "rb") as file:
+            import hashlib
+
+            m = hashlib.sha256()
+
+            file.seek(0x100000)
+            m.update(file.read(0x10000))
+            return m.hexdigest()[0:8]
+    except FileNotFoundError:
+        return "NOFILE"
+
+
+def eval(model, n, input):
+    qk = f"enc_p.encoder.attn_layers.{n}.conv_q.weight"
+    uk = f"enc_p.encoder.attn_layers.{n}.conv_k.weight"
+    vk = f"enc_p.encoder.attn_layers.{n}.conv_v.weight"
+    atoq, atok, atov = model[qk][:, :, 0], model[uk][:, :, 0], model[vk][:, :, 0]
+
+    attn = cal_cross_attn(atoq, atok, atov, input)
+    return attn
+
+
+def main(path, root):
+    torch.manual_seed(114514)
+    model_a = torch.load(path, map_location="cpu")["weight"]
+
+    logger.info("Query:\t\t%s\t%s" % (path, model_hash(path)))
+
+    map_attn_a = {}
+    map_rand_input = {}
+    for n in range(6):
+        hidden_dim, embed_dim, _ = model_a[
+            f"enc_p.encoder.attn_layers.{n}.conv_v.weight"
+        ].shape
+        rand_input = torch.randn([embed_dim, hidden_dim])
+
+        map_attn_a[n] = eval(model_a, n, rand_input)
+        map_rand_input[n] = rand_input
+
+    del model_a
+
+    for name in sorted(list(os.listdir(root))):
+        path = "%s/%s" % (root, name)
+        model_b = torch.load(path, map_location="cpu")["weight"]
+
+        sims = []
+        for n in range(6):
+            attn_a = map_attn_a[n]
+            attn_b = eval(model_b, n, map_rand_input[n])
+
+            sim = torch.mean(torch.cosine_similarity(attn_a, attn_b))
+            sims.append(sim)
+
+        logger.info(
+            "Reference:\t%s\t%s\t%s"
+            % (path, model_hash(path), f"{torch.mean(torch.stack(sims)) * 1e2:.2f}%")
+        )
+
+
+if __name__ == "__main__":
+    query_path = r"assets\weights\mi v3.pth"
+    reference_root = r"assets\weights"
+    main(query_path, reference_root)
diff --git a/tools/dlmodels.bat b/tools/dlmodels.bat
new file mode 100644
index 0000000000000000000000000000000000000000..5d80f50369b1f3ed37c045d07a9e2ce8954f09d4
--- /dev/null
+++ b/tools/dlmodels.bat
@@ -0,0 +1,348 @@
+@echo off && chcp 65001
+
+echo working dir is %cd%
+echo downloading requirement aria2 check.
+echo=
+dir /a:d/b | findstr "aria2" > flag.txt
+findstr "aria2" flag.txt >nul
+if %errorlevel% ==0 (
+    echo aria2 checked.
+    echo=
+) else (
+    echo failed. please downloading aria2 from webpage!
+    echo unzip it and put in this directory!
+    timeout /T 5
+    start https://github.com/aria2/aria2/releases/tag/release-1.36.0
+    echo=
+    goto end
+)
+
+echo envfiles checking start.
+echo=
+
+for /f %%x in ('findstr /i /c:"aria2" "flag.txt"') do (set aria2=%%x)&goto endSch
+:endSch
+
+set d32=f0D32k.pth
+set d40=f0D40k.pth
+set d48=f0D48k.pth
+set g32=f0G32k.pth
+set g40=f0G40k.pth
+set g48=f0G48k.pth
+
+set d40v2=f0D40k.pth
+set g40v2=f0G40k.pth
+
+set dld32=https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/f0D32k.pth
+set dld40=https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/f0D40k.pth
+set dld48=https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/f0D48k.pth
+set dlg32=https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/f0G32k.pth
+set dlg40=https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/f0G40k.pth
+set dlg48=https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/f0G48k.pth
+
+set dld40v2=https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained_v2/f0D40k.pth
+set dlg40v2=https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained_v2/f0G40k.pth
+
+set hp2_all=HP2_all_vocals.pth
+set hp3_all=HP3_all_vocals.pth
+set hp5_only=HP5_only_main_vocal.pth
+set VR_DeEchoAggressive=VR-DeEchoAggressive.pth
+set VR_DeEchoDeReverb=VR-DeEchoDeReverb.pth
+set VR_DeEchoNormal=VR-DeEchoNormal.pth
+set onnx_dereverb=vocals.onnx
+
+set dlhp2_all=https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/uvr5_weights/HP2_all_vocals.pth
+set dlhp3_all=https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/uvr5_weights/HP3_all_vocals.pth
+set dlhp5_only=https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/uvr5_weights/HP5_only_main_vocal.pth
+set dlVR_DeEchoAggressive=https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/uvr5_weights/VR-DeEchoAggressive.pth
+set dlVR_DeEchoDeReverb=https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/uvr5_weights/VR-DeEchoDeReverb.pth
+set dlVR_DeEchoNormal=https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/uvr5_weights/VR-DeEchoNormal.pth
+set dlonnx_dereverb=https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/uvr5_weights/onnx_dereverb_By_FoxJoy/vocals.onnx
+
+set hb=hubert_base.pt
+
+set dlhb=https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/hubert_base.pt
+
+echo dir check start.
+echo=
+
+if exist "%~dp0assets\pretrained" (
+        echo dir .\assets\pretrained checked.
+    ) else (
+        echo failed. generating dir .\assets\pretrained.
+        mkdir pretrained
+    )
+if exist "%~dp0assets\pretrained_v2" (
+        echo dir .\assets\pretrained_v2 checked.
+    ) else (
+        echo failed. generating dir .\assets\pretrained_v2.
+        mkdir pretrained_v2
+    )    
+if exist "%~dp0assets\uvr5_weights" (
+        echo dir .\assets\uvr5_weights checked.
+    ) else (
+        echo failed. generating dir .\assets\uvr5_weights.
+        mkdir uvr5_weights
+    )
+if exist "%~dp0assets\uvr5_weights\onnx_dereverb_By_FoxJoy" (
+        echo dir .\assets\uvr5_weights\onnx_dereverb_By_FoxJoy checked.
+    ) else (
+        echo failed. generating dir .\assets\uvr5_weights\onnx_dereverb_By_FoxJoy.
+        mkdir uvr5_weights\onnx_dereverb_By_FoxJoy
+    )    
+
+echo=
+echo dir check finished.
+
+echo=
+echo required files check start.
+
+echo checking D32k.pth
+if exist "%~dp0assets\pretrained\D32k.pth" (
+        echo D32k.pth in .\assets\pretrained checked.
+        echo=
+    ) else (
+        echo failed. starting download from huggingface.
+        %~dp0%aria2%\aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/D32k.pth -d %~dp0assets\pretrained -o D32k.pth
+        if exist "%~dp0assets\pretrained\D32k.pth" (echo download successful.) else (echo please try again!
+        echo=)
+    )
+echo checking D40k.pth
+if exist "%~dp0assets\pretrained\D40k.pth" (
+        echo D40k.pth in .\assets\pretrained checked.
+        echo=
+    ) else (
+        echo failed. starting download from huggingface.
+        %~dp0%aria2%\aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/D40k.pth -d %~dp0assets\pretrained -o D40k.pth
+        if exist "%~dp0assets\pretrained\D40k.pth" (echo download successful.) else (echo please try again!
+        echo=)
+    )
+echo checking D40k.pth
+if exist "%~dp0assets\pretrained_v2\D40k.pth" (
+        echo D40k.pth in .\assets\pretrained_v2 checked.
+        echo=
+    ) else (
+        echo failed. starting download from huggingface.
+        %~dp0%aria2%\aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained_v2/D40k.pth -d %~dp0assets\pretrained_v2 -o D40k.pth
+        if exist "%~dp0assets\pretrained_v2\D40k.pth" (echo download successful.) else (echo please try again!
+        echo=)
+    )    
+echo checking D48k.pth
+if exist "%~dp0assets\pretrained\D48k.pth" (
+        echo D48k.pth in .\assets\pretrained checked.
+        echo=
+    ) else (
+        echo failed. starting download from huggingface.
+        %~dp0%aria2%\aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/D48k.pth -d %~dp0assets\pretrained -o D48k.pth
+        if exist "%~dp0assets\pretrained\D48k.pth" (echo download successful.) else (echo please try again!
+        echo=)
+    )
+echo checking G32k.pth
+if exist "%~dp0assets\pretrained\G32k.pth" (
+        echo G32k.pth in .\assets\pretrained checked.
+        echo=
+    ) else (
+        echo failed. starting download from huggingface.
+        %~dp0%aria2%\aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/G32k.pth -d %~dp0assets\pretrained -o G32k.pth
+        if exist "%~dp0assets\pretrained\G32k.pth" (echo download successful.) else (echo please try again!
+        echo=)
+    )
+echo checking G40k.pth
+if exist "%~dp0assets\pretrained\G40k.pth" (
+        echo G40k.pth in .\assets\pretrained checked.
+        echo=
+    ) else (
+        echo failed. starting download from huggingface.
+        %~dp0%aria2%\aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/G40k.pth -d %~dp0assets\pretrained -o G40k.pth
+        if exist "%~dp0assets\pretrained\G40k.pth" (echo download successful.) else (echo please try again!
+        echo=)
+    )
+echo checking G40k.pth
+if exist "%~dp0assets\pretrained_v2\G40k.pth" (
+        echo G40k.pth in .\assets\pretrained_v2 checked.
+        echo=
+    ) else (
+        echo failed. starting download from huggingface.
+        %~dp0%aria2%\aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained_v2/G40k.pth -d %~dp0assets\pretrained_v2 -o G40k.pth
+        if exist "%~dp0assets\pretrained_v2\G40k.pth" (echo download successful.) else (echo please try again!
+        echo=)
+    )    
+echo checking G48k.pth
+if exist "%~dp0assets\pretrained\G48k.pth" (
+        echo G48k.pth in .\assets\pretrained checked.
+        echo=
+    ) else (
+        echo failed. starting download from huggingface.
+        %~dp0%aria2%\aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/G48k.pth -d %~dp0assets\pretrained -o G48k.pth
+        if exist "%~dp0assets\pretrained\G48k.pth" (echo download successful.) else (echo please try again!
+        echo=)
+    )
+
+echo checking %d32%
+if exist "%~dp0assets\pretrained\%d32%" (
+        echo %d32% in .\assets\pretrained checked.
+        echo=
+    ) else (
+        echo failed. starting download from huggingface.
+        %~dp0%aria2%\aria2c --console-log-level=error -c -x 16 -s 16 -k 1M %dld32% -d %~dp0assets\pretrained -o %d32%
+        if exist "%~dp0assets\pretrained\%d32%" (echo download successful.) else (echo please try again!
+        echo=)
+    )
+echo checking %d40%
+if exist "%~dp0assets\pretrained\%d40%" (
+        echo %d40% in .\assets\pretrained checked.
+        echo=
+    ) else (
+        echo failed. starting download from huggingface.
+        %~dp0%aria2%\aria2c --console-log-level=error -c -x 16 -s 16 -k 1M %dld40% -d %~dp0assets\pretrained -o %d40%
+        if exist "%~dp0assets\pretrained\%d40%" (echo download successful.) else (echo please try again!
+        echo=)
+    )
+echo checking %d40v2%
+if exist "%~dp0assets\pretrained_v2\%d40v2%" (
+        echo %d40v2% in .\assets\pretrained_v2 checked.
+        echo=
+    ) else (
+        echo failed. starting download from huggingface.
+        %~dp0%aria2%\aria2c --console-log-level=error -c -x 16 -s 16 -k 1M %dld40v2% -d %~dp0assets\pretrained_v2 -o %d40v2%
+        if exist "%~dp0assets\pretrained_v2\%d40v2%" (echo download successful.) else (echo please try again!
+        echo=)
+    )    
+echo checking %d48%
+if exist "%~dp0assets\pretrained\%d48%" (
+        echo %d48% in .\assets\pretrained checked.
+        echo=
+    ) else (
+        echo failed. starting download from huggingface.
+        %~dp0%aria2%\aria2c --console-log-level=error -c -x 16 -s 16 -k 1M %dld48% -d %~dp0assets\pretrained -o %d48%
+        if exist "%~dp0assets\pretrained\%d48%" (echo download successful.) else (echo please try again!
+        echo=)
+    )
+echo checking %g32%
+if exist "%~dp0assets\pretrained\%g32%" (
+        echo %g32% in .\assets\pretrained checked.
+        echo=
+    ) else (
+        echo failed. starting download from huggingface.
+        %~dp0%aria2%\aria2c --console-log-level=error -c -x 16 -s 16 -k 1M %dlg32% -d %~dp0assets\pretrained -o %g32%
+        if exist "%~dp0assets\pretrained\%g32%" (echo download successful.) else (echo please try again!
+        echo=)
+    )
+echo checking %g40%
+if exist "%~dp0assets\pretrained\%g40%" (
+        echo %g40% in .\assets\pretrained checked.
+        echo=
+    ) else (
+        echo failed. starting download from huggingface.
+        %~dp0%aria2%\aria2c --console-log-level=error -c -x 16 -s 16 -k 1M %dlg40% -d %~dp0assets\pretrained -o %g40%
+        if exist "%~dp0assets\pretrained\%g40%" (echo download successful.) else (echo please try again!
+        echo=)
+    )
+echo checking %g40v2%
+if exist "%~dp0assets\pretrained_v2\%g40v2%" (
+        echo %g40v2% in .\assets\pretrained_v2 checked.
+        echo=
+    ) else (
+        echo failed. starting download from huggingface.
+        %~dp0%aria2%\aria2c --console-log-level=error -c -x 16 -s 16 -k 1M %dlg40v2% -d %~dp0assets\pretrained_v2 -o %g40v2%
+        if exist "%~dp0assets\pretrained_v2\%g40v2%" (echo download successful.) else (echo please try again!
+        echo=)
+    )    
+echo checking %g48%
+if exist "%~dp0assets\pretrained\%g48%" (
+        echo %g48% in .\assets\pretrained checked.
+        echo=
+    ) else (
+        echo failed. starting download from huggingface.
+        %~dp0%aria2%\aria2c --console-log-level=error -c -x 16 -s 16 -k 1M %dlg48% -d %~dp0assets\pretrained -o %g48%
+        if exist "%~dp0assets\pretrained\%g48%" (echo download successful.) else (echo please try again!
+        echo=)
+    )
+
+echo checking %hp2_all%
+if exist "%~dp0assets\uvr5_weights\%hp2_all%" (
+        echo %hp2_all% in .\assets\uvr5_weights checked.
+        echo=
+    ) else (
+        echo failed. starting download from huggingface.
+        %~dp0%aria2%\aria2c --console-log-level=error -c -x 16 -s 16 -k 1M %dlhp2_all% -d %~dp0assets\uvr5_weights -o %hp2_all%
+        if exist "%~dp0assets\uvr5_weights\%hp2_all%" (echo download successful.) else (echo please try again!
+        echo=)
+    )
+echo checking %hp3_all%
+if exist "%~dp0assets\uvr5_weights\%hp3_all%" (
+        echo %hp3_all% in .\assets\uvr5_weights checked.
+        echo=
+    ) else (
+        echo failed. starting download from huggingface.
+        %~dp0%aria2%\aria2c --console-log-level=error -c -x 16 -s 16 -k 1M %dlhp3_all% -d %~dp0assets\uvr5_weights -o %hp3_all%
+        if exist "%~dp0assets\uvr5_weights\%hp3_all%" (echo download successful.) else (echo please try again!
+        echo=)
+    )
+echo checking %hp5_only%
+if exist "%~dp0assets\uvr5_weights\%hp5_only%" (
+        echo %hp5_only% in .\assets\uvr5_weights checked.
+        echo=
+    ) else (
+        echo failed. starting download from huggingface.
+        %~dp0%aria2%\aria2c --console-log-level=error -c -x 16 -s 16 -k 1M %dlhp5_only% -d %~dp0assets\uvr5_weights -o %hp5_only%
+        if exist "%~dp0assets\uvr5_weights\%hp5_only%" (echo download successful.) else (echo please try again!
+        echo=)
+    )
+echo checking %VR_DeEchoAggressive%
+if exist "%~dp0assets\uvr5_weights\%VR_DeEchoAggressive%" (
+        echo %VR_DeEchoAggressive% in .\assets\uvr5_weights checked.
+        echo=
+    ) else (
+        echo failed. starting download from huggingface.
+        %~dp0%aria2%\aria2c --console-log-level=error -c -x 16 -s 16 -k 1M %dlVR_DeEchoAggressive% -d %~dp0assets\uvr5_weights -o %VR_DeEchoAggressive%
+        if exist "%~dp0assets\uvr5_weights\%VR_DeEchoAggressive%" (echo download successful.) else (echo please try again!
+        echo=)
+    )
+echo checking %VR_DeEchoDeReverb%
+if exist "%~dp0assets\uvr5_weights\%VR_DeEchoDeReverb%" (
+        echo %VR_DeEchoDeReverb% in .\assets\uvr5_weights checked.
+        echo=
+    ) else (
+        echo failed. starting download from huggingface.
+        %~dp0%aria2%\aria2c --console-log-level=error -c -x 16 -s 16 -k 1M %dlVR_DeEchoDeReverb% -d %~dp0assets\uvr5_weights -o %VR_DeEchoDeReverb%
+        if exist "%~dp0assets\uvr5_weights\%VR_DeEchoDeReverb%" (echo download successful.) else (echo please try again!
+        echo=)
+    )
+echo checking %VR_DeEchoNormal%
+if exist "%~dp0assets\uvr5_weights\%VR_DeEchoNormal%" (
+        echo %VR_DeEchoNormal% in .\assets\uvr5_weights checked.
+        echo=
+    ) else (
+        echo failed. starting download from huggingface.
+        %~dp0%aria2%\aria2c --console-log-level=error -c -x 16 -s 16 -k 1M %dlVR_DeEchoNormal% -d %~dp0assets\uvr5_weights -o %VR_DeEchoNormal%
+        if exist "%~dp0assets\uvr5_weights\%VR_DeEchoNormal%" (echo download successful.) else (echo please try again!
+        echo=)
+    )
+echo checking %onnx_dereverb%
+if exist "%~dp0assets\uvr5_weights\onnx_dereverb_By_FoxJoy\%onnx_dereverb%" (
+        echo %onnx_dereverb% in .\assets\uvr5_weights\onnx_dereverb_By_FoxJoy checked.
+        echo=
+    ) else (
+        echo failed. starting download from huggingface.
+        %~dp0%aria2%\aria2c --console-log-level=error -c -x 16 -s 16 -k 1M %dlonnx_dereverb% -d %~dp0assets\uvr5_weights\onnx_dereverb_By_FoxJoy -o %onnx_dereverb%
+        if exist "%~dp0assets\uvr5_weights\onnx_dereverb_By_FoxJoy\%onnx_dereverb%" (echo download successful.) else (echo please try again!
+        echo=)
+    )    
+
+echo checking %hb%
+if exist "%~dp0assets\hubert\%hb%" (
+        echo %hb% in .\assets\hubert\pretrained checked.
+        echo=
+    ) else (
+        echo failed. starting download from huggingface.
+        %~dp0%aria2%\aria2c --console-log-level=error -c -x 16 -s 16 -k 1M %dlhb% -d %~dp0assets\hubert\ -o %hb%
+        if exist "%~dp0assets\hubert\%hb%" (echo download successful.) else (echo please try again!
+        echo=)
+    )
+
+echo required files check finished.
+echo envfiles check complete.
+pause
+:end
+del flag.txt
diff --git a/tools/dlmodels.sh b/tools/dlmodels.sh
new file mode 100644
index 0000000000000000000000000000000000000000..5fba0edef345c0a4384aa9402cfd5e93e29efdc3
--- /dev/null
+++ b/tools/dlmodels.sh
@@ -0,0 +1,566 @@
+#!/bin/bash
+
+echo working dir is $(pwd)
+echo downloading requirement aria2 check.
+
+if command -v aria2c &> /dev/null
+then
+    echo "aria2c command found"
+else
+    echo failed. please install aria2
+    sleep 5
+    exit 1
+fi
+
+d32="f0D32k.pth"
+d40="f0D40k.pth"
+d48="f0D48k.pth"
+g32="f0G32k.pth"
+g40="f0G40k.pth"
+g48="f0G48k.pth"
+
+d40v2="f0D40k.pth"
+g40v2="f0G40k.pth"
+
+dld32="https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/f0D32k.pth"
+dld40="https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/f0D40k.pth"
+dld48="https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/f0D48k.pth"
+dlg32="https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/f0G32k.pth"
+dlg40="https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/f0G40k.pth"
+dlg48="https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/f0G48k.pth"
+
+dld40v2="https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained_v2/f0D40k.pth"
+dlg40v2="https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained_v2/f0G40k.pth"
+
+hp2_all="HP2_all_vocals.pth"
+hp3_all="HP3_all_vocals.pth"
+hp5_only="HP5_only_main_vocal.pth"
+VR_DeEchoAggressive="VR-DeEchoAggressive.pth"
+VR_DeEchoDeReverb="VR-DeEchoDeReverb.pth"
+VR_DeEchoNormal="VR-DeEchoNormal.pth"
+onnx_dereverb="vocals.onnx"
+rmvpe="rmvpe.pt"
+
+dlhp2_all="https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/uvr5_weights/HP2_all_vocals.pth"
+dlhp3_all="https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/uvr5_weights/HP3_all_vocals.pth"
+dlhp5_only="https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/uvr5_weights/HP5_only_main_vocal.pth"
+dlVR_DeEchoAggressive="https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/uvr5_weights/VR-DeEchoAggressive.pth"
+dlVR_DeEchoDeReverb="https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/uvr5_weights/VR-DeEchoDeReverb.pth"
+dlVR_DeEchoNormal="https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/uvr5_weights/VR-DeEchoNormal.pth"
+dlonnx_dereverb="https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/uvr5_weights/onnx_dereverb_By_FoxJoy/vocals.onnx"
+dlrmvpe="https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/rmvpe.pt"
+
+hb="hubert_base.pt"
+
+dlhb="https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/hubert_base.pt"
+
+echo dir check start.
+
+if [ -d "./assets/pretrained" ]; then
+    echo dir ./assets/pretrained checked.
+else
+    echo failed. generating dir ./assets/pretrained.
+    mkdir pretrained
+fi
+
+if [ -d "./assets/pretrained_v2" ]; then
+    echo dir ./assets/pretrained_v2 checked.
+else
+    echo failed. generating dir ./assets/pretrained_v2.
+    mkdir pretrained_v2
+fi
+
+if [ -d "./assets/uvr5_weights" ]; then
+    echo dir ./assets/uvr5_weights checked.
+else
+    echo failed. generating dir ./assets/uvr5_weights.
+    mkdir uvr5_weights
+fi
+
+if [ -d "./assets/uvr5_weights/onnx_dereverb_By_FoxJoy" ]; then
+    echo dir ./assets/uvr5_weights/onnx_dereverb_By_FoxJoy checked.
+else
+    echo failed. generating dir ./assets/uvr5_weights/onnx_dereverb_By_FoxJoy.
+    mkdir uvr5_weights/onnx_dereverb_By_FoxJoy
+fi
+
+echo dir check finished.
+
+echo required files check start.
+
+echo checking D32k.pth
+if [ -f "./assets/pretrained/D32k.pth" ]; then
+    echo D32k.pth in ./assets/pretrained checked.
+else
+    echo failed. starting download from huggingface.
+    if command -v aria2c &> /dev/null; then
+        aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/D32k.pth -d ./assets/pretrained -o D32k.pth
+        if [ -f "./assets/pretrained/D32k.pth" ]; then
+            echo download successful.
+        else
+            echo please try again!
+            exit 1
+        fi
+    else
+        echo aria2c command not found. Please install aria2c and try again.
+        exit 1
+    fi
+fi
+
+echo checking D40k.pth
+if [ -f "./assets/pretrained/D40k.pth" ]; then
+    echo D40k.pth in ./assets/pretrained checked.
+else
+    echo failed. starting download from huggingface.
+    if command -v aria2c &> /dev/null; then
+        aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/D40k.pth -d ./assets/pretrained -o D40k.pth
+        if [ -f "./assets/pretrained/D40k.pth" ]; then
+            echo download successful.
+        else
+            echo please try again!
+            exit 1
+        fi
+    else
+        echo aria2c command not found. Please install aria2c and try again.
+        exit 1
+    fi
+fi
+
+echo checking D40k.pth
+if [ -f "./assets/pretrained_v2/D40k.pth" ]; then
+    echo D40k.pth in ./assets/pretrained_v2 checked.
+else
+    echo failed. starting download from huggingface.
+    if command -v aria2c &> /dev/null; then
+        aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained_v2/D40k.pth -d ./assets/pretrained_v2 -o D40k.pth
+        if [ -f "./assets/pretrained_v2/D40k.pth" ]; then
+            echo download successful.
+        else
+            echo please try again!
+            exit 1
+        fi
+    else
+        echo aria2c command not found. Please install aria2c and try again.
+        exit 1
+    fi
+fi
+
+echo checking D48k.pth
+if [ -f "./assets/pretrained/D48k.pth" ]; then
+    echo D48k.pth in ./assets/pretrained checked.
+else
+    echo failed. starting download from huggingface.
+    if command -v aria2c &> /dev/null; then
+        aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/D48k.pth -d ./assets/pretrained -o D48k.pth
+        if [ -f "./assets/pretrained/D48k.pth" ]; then
+            echo download successful.
+        else
+            echo please try again!
+            exit 1
+        fi
+    else
+        echo aria2c command not found. Please install aria2c and try again.
+        exit 1
+    fi
+fi
+
+echo checking G32k.pth
+if [ -f "./assets/pretrained/G32k.pth" ]; then
+    echo G32k.pth in ./assets/pretrained checked.
+else
+    echo failed. starting download from huggingface.
+    if command -v aria2c &> /dev/null; then
+        aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/G32k.pth -d ./assets/pretrained -o G32k.pth
+        if [ -f "./assets/pretrained/G32k.pth" ]; then
+            echo download successful.
+        else
+            echo please try again!
+            exit 1
+        fi
+    else
+        echo aria2c command not found. Please install aria2c and try again.
+        exit 1
+    fi
+fi
+
+echo checking G40k.pth
+if [ -f "./assets/pretrained/G40k.pth" ]; then
+    echo G40k.pth in ./assets/pretrained checked.
+else
+    echo failed. starting download from huggingface.
+    if command -v aria2c &> /dev/null; then
+        aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/G40k.pth -d ./assets/pretrained -o G40k.pth
+        if [ -f "./assets/pretrained/G40k.pth" ]; then
+            echo download successful.
+        else
+            echo please try again!
+            exit 1
+        fi
+    else
+        echo aria2c command not found. Please install aria2c and try again.
+        exit 1
+    fi
+fi
+
+echo checking G40k.pth
+if [ -f "./assets/pretrained_v2/G40k.pth" ]; then
+    echo G40k.pth in ./assets/pretrained_v2 checked.
+else
+    echo failed. starting download from huggingface.
+    if command -v aria2c &> /dev/null; then
+        aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained_v2/G40k.pth -d ./assets/pretrained_v2 -o G40k.pth
+        if [ -f "./assets/pretrained_v2/G40k.pth" ]; then
+            echo download successful.
+        else
+            echo please try again!
+            exit 1
+        fi
+    else
+        echo aria2c command not found. Please install aria2c and try again.
+        exit 1
+    fi
+fi
+
+echo checking G48k.pth
+if [ -f "./assets/pretrained/G48k.pth" ]; then
+    echo G48k.pth in ./assets/pretrained checked.
+else
+    echo failed. starting download from huggingface.
+    if command -v aria2c &> /dev/null; then
+        aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/G48k.pth -d ./assets/pretrained -o G48k.pth
+        if [ -f "./assets/pretrained/G48k.pth" ]; then
+            echo download successful.
+        else
+            echo please try again!
+            exit 1
+        fi
+    else
+        echo aria2c command not found. Please install aria2c and try again.
+        exit 1
+    fi
+fi
+
+echo checking $d32
+if [ -f "./assets/pretrained/$d32" ]; then
+    echo $d32 in ./assets/pretrained checked.
+else
+    echo failed. starting download from huggingface.
+    if command -v aria2c &> /dev/null; then
+        aria2c --console-log-level=error -c -x 16 -s 16 -k 1M $dld32 -d ./assets/pretrained -o $d32
+        if [ -f "./assets/pretrained/$d32" ]; then
+            echo download successful.
+        else
+            echo please try again!
+            exit 1
+        fi
+    else
+        echo aria2c command not found. Please install aria2c and try again.
+        exit 1
+    fi
+fi
+
+echo checking $d40
+if [ -f "./assets/pretrained/$d40" ]; then
+    echo $d40 in ./assets/pretrained checked.
+else
+    echo failed. starting download from huggingface.
+    if command -v aria2c &> /dev/null; then
+        aria2c --console-log-level=error -c -x 16 -s 16 -k 1M $dld40 -d ./assets/pretrained -o $d40
+        if [ -f "./assets/pretrained/$d40" ]; then
+            echo download successful.
+        else
+            echo please try again!
+            exit 1
+        fi
+    else
+        echo aria2c command not found. Please install aria2c and try again.
+        exit 1
+    fi
+fi
+
+echo checking $d40v2
+if [ -f "./assets/pretrained_v2/$d40v2" ]; then
+    echo $d40v2 in ./assets/pretrained_v2 checked.
+else
+    echo failed. starting download from huggingface.
+    if command -v aria2c &> /dev/null; then
+        aria2c --console-log-level=error -c -x 16 -s 16 -k 1M $dld40v2 -d ./assets/pretrained_v2 -o $d40v2
+        if [ -f "./assets/pretrained_v2/$d40v2" ]; then
+            echo download successful.
+        else
+            echo please try again!
+            exit 1
+        fi
+    else
+        echo aria2c command not found. Please install aria2c and try again.
+        exit 1
+    fi
+fi
+
+echo checking $d48
+if [ -f "./assets/pretrained/$d48" ]; then
+    echo $d48 in ./assets/pretrained checked.
+else
+    echo failed. starting download from huggingface.
+    if command -v aria2c &> /dev/null; then
+        aria2c --console-log-level=error -c -x 16 -s 16 -k 1M $dld48 -d ./assets/pretrained -o $d48
+        if [ -f "./assets/pretrained/$d48" ]; then
+            echo download successful.
+        else
+            echo please try again!
+            exit 1
+        fi
+    else
+        echo aria2c command not found. Please install aria2c and try again.
+        exit 1
+    fi
+fi
+
+echo checking $g32
+if [ -f "./assets/pretrained/$g32" ]; then
+    echo $g32 in ./assets/pretrained checked.
+else
+    echo failed. starting download from huggingface.
+    if command -v aria2c &> /dev/null; then
+        aria2c --console-log-level=error -c -x 16 -s 16 -k 1M $dlg32 -d ./assets/pretrained -o $g32
+        if [ -f "./assets/pretrained/$g32" ]; then
+            echo download successful.
+        else
+            echo please try again!
+            exit 1
+        fi
+    else
+        echo aria2c command not found. Please install aria2c and try again.
+        exit 1
+    fi
+fi
+
+echo checking $g40
+if [ -f "./assets/pretrained/$g40" ]; then
+    echo $g40 in ./assets/pretrained checked.
+else
+    echo failed. starting download from huggingface.
+    if command -v aria2c &> /dev/null; then
+        aria2c --console-log-level=error -c -x 16 -s 16 -k 1M $dlg40 -d ./assets/pretrained -o $g40
+        if [ -f "./assets/pretrained/$g40" ]; then
+            echo download successful.
+        else
+            echo please try again!
+            exit 1
+        fi
+    else
+        echo aria2c command not found. Please install aria2c and try again.
+        exit 1
+    fi
+fi
+
+echo checking $g40v2
+if [ -f "./assets/pretrained_v2/$g40v2" ]; then
+    echo $g40v2 in ./assets/pretrained_v2 checked.
+else
+    echo failed. starting download from huggingface.
+    if command -v aria2c &> /dev/null; then
+        aria2c --console-log-level=error -c -x 16 -s 16 -k 1M $dlg40v2 -d ./assets/pretrained_v2 -o $g40v2
+        if [ -f "./assets/pretrained_v2/$g40v2" ]; then
+            echo download successful.
+        else
+            echo please try again!
+            exit 1
+        fi
+    else
+        echo aria2c command not found. Please install aria2c and try again.
+        exit 1
+    fi
+fi
+
+echo checking $g48
+if [ -f "./assets/pretrained/$g48" ]; then
+    echo $g48 in ./assets/pretrained checked.
+else
+    echo failed. starting download from huggingface.
+    if command -v aria2c &> /dev/null; then
+        aria2c --console-log-level=error -c -x 16 -s 16 -k 1M $dlg48 -d ./assets/pretrained -o $g48
+        if [ -f "./assets/pretrained/$g48" ]; then
+            echo download successful.
+        else
+            echo please try again!
+            exit 1
+        fi
+    else
+        echo aria2c command not found. Please install aria2c and try again.
+        exit 1
+    fi
+fi
+
+echo checking $hp2_all
+if [ -f "./assets/uvr5_weights/$hp2_all" ]; then
+    echo $hp2_all in ./assets/uvr5_weights checked.
+else
+    echo failed. starting download from huggingface.
+    if command -v aria2c &> /dev/null; then
+        aria2c --console-log-level=error -c -x 16 -s 16 -k 1M $dlhp2_all -d ./assets/uvr5_weights -o $hp2_all
+        if [ -f "./assets/uvr5_weights/$hp2_all" ]; then
+            echo download successful.
+        else
+            echo please try again!
+            exit 1
+        fi
+    else
+        echo aria2c command not found. Please install aria2c and try again.
+        exit 1
+    fi
+fi
+
+echo checking $hp3_all
+if [ -f "./assets/uvr5_weights/$hp3_all" ]; then
+    echo $hp3_all in ./assets/uvr5_weights checked.
+else
+    echo failed. starting download from huggingface.
+    if command -v aria2c &> /dev/null; then
+        aria2c --console-log-level=error -c -x 16 -s 16 -k 1M $dlhp3_all -d ./assets/uvr5_weights -o $hp3_all
+        if [ -f "./assets/uvr5_weights/$hp3_all" ]; then
+            echo download successful.
+        else
+            echo please try again!
+            exit 1
+        fi
+    else
+        echo aria2c command not found. Please install aria2c and try again.
+        exit 1
+    fi
+fi
+
+echo checking $hp5_only
+if [ -f "./assets/uvr5_weights/$hp5_only" ]; then
+    echo $hp5_only in ./assets/uvr5_weights checked.
+else
+    echo failed. starting download from huggingface.
+    if command -v aria2c &> /dev/null; then
+        aria2c --console-log-level=error -c -x 16 -s 16 -k 1M $dlhp5_only -d ./assets/uvr5_weights -o $hp5_only
+        if [ -f "./assets/uvr5_weights/$hp5_only" ]; then
+            echo download successful.
+        else
+            echo please try again!
+            exit 1
+        fi
+    else
+        echo aria2c command not found. Please install aria2c and try again.
+        exit 1
+    fi
+fi
+
+echo checking $VR_DeEchoAggressive
+if [ -f "./assets/uvr5_weights/$VR_DeEchoAggressive" ]; then
+    echo $VR_DeEchoAggressive in ./assets/uvr5_weights checked.
+else
+    echo failed. starting download from huggingface.
+    if command -v aria2c &> /dev/null; then
+        aria2c --console-log-level=error -c -x 16 -s 16 -k 1M $dlVR_DeEchoAggressive -d ./assets/uvr5_weights -o $VR_DeEchoAggressive
+        if [ -f "./assets/uvr5_weights/$VR_DeEchoAggressive" ]; then
+            echo download successful.
+        else
+            echo please try again!
+            exit 1
+        fi
+    else
+        echo aria2c command not found. Please install aria2c and try again.
+        exit 1
+    fi
+fi
+
+echo checking $VR_DeEchoDeReverb
+if [ -f "./assets/uvr5_weights/$VR_DeEchoDeReverb" ]; then
+    echo $VR_DeEchoDeReverb in ./assets/uvr5_weights checked.
+else
+    echo failed. starting download from huggingface.
+    if command -v aria2c &> /dev/null; then
+        aria2c --console-log-level=error -c -x 16 -s 16 -k 1M $dlVR_DeEchoDeReverb -d ./assets/uvr5_weights -o $VR_DeEchoDeReverb
+        if [ -f "./assets/uvr5_weights/$VR_DeEchoDeReverb" ]; then
+            echo download successful.
+        else
+            echo please try again!
+            exit 1
+        fi
+    else
+        echo aria2c command not found. Please install aria2c and try again.
+        exit 1
+    fi
+fi
+
+echo checking $VR_DeEchoNormal
+if [ -f "./assets/uvr5_weights/$VR_DeEchoNormal" ]; then
+    echo $VR_DeEchoNormal in ./assets/uvr5_weights checked.
+else
+    echo failed. starting download from huggingface.
+    if command -v aria2c &> /dev/null; then
+        aria2c --console-log-level=error -c -x 16 -s 16 -k 1M $dlVR_DeEchoNormal -d ./assets/uvr5_weights -o $VR_DeEchoNormal
+        if [ -f "./assets/uvr5_weights/$VR_DeEchoNormal" ]; then
+            echo download successful.
+        else
+            echo please try again!
+            exit 1
+        fi
+    else
+        echo aria2c command not found. Please install aria2c and try again.
+        exit 1
+    fi
+fi
+
+echo checking $onnx_dereverb
+if [ -f "./assets/uvr5_weights/onnx_dereverb_By_FoxJoy/$onnx_dereverb" ]; then
+    echo $onnx_dereverb in ./assets/uvr5_weights/onnx_dereverb_By_FoxJoy checked.
+else
+    echo failed. starting download from huggingface.
+    if command -v aria2c &> /dev/null; then
+        aria2c --console-log-level=error -c -x 16 -s 16 -k 1M $dlonnx_dereverb -d ./assets/uvr5_weights/onnx_dereverb_By_FoxJoy -o $onnx_dereverb
+        if [ -f "./assets/uvr5_weights/onnx_dereverb_By_FoxJoy/$onnx_dereverb" ]; then
+            echo download successful.
+        else
+            echo please try again!
+            exit 1
+        fi
+    else
+        echo aria2c command not found. Please install aria2c and try again.
+        exit 1
+    fi
+fi
+
+echo checking $rmvpe
+if [ -f "./assets/rmvpe/$rmvpe" ]; then
+    echo $rmvpe in ./assets/rmvpe checked.
+else
+    echo failed. starting download from huggingface.
+    if command -v aria2c &> /dev/null; then
+        aria2c --console-log-level=error -c -x 16 -s 16 -k 1M $dlrmvpe -d ./assets/rmvpe -o $rmvpe
+        if [ -f "./assets/rmvpe/$rmvpe" ]; then
+            echo download successful.
+        else
+            echo please try again!
+            exit 1
+        fi
+    else
+        echo aria2c command not found. Please install aria2c and try again.
+        exit 1
+    fi
+fi
+
+echo checking $hb
+if [ -f "./assets/hubert/$hb" ]; then
+    echo $hb in ./assets/hubert/pretrained checked.
+else
+    echo failed. starting download from huggingface.
+    if command -v aria2c &> /dev/null; then
+        aria2c --console-log-level=error -c -x 16 -s 16 -k 1M $dlhb -d ./assets/hubert/ -o $hb
+        if [ -f "./assets/hubert/$hb" ]; then
+            echo download successful.
+        else
+            echo please try again!
+            exit 1
+        fi
+    else
+        echo aria2c command not found. Please install aria2c and try again.
+        exit 1
+    fi
+fi
+
+echo required files check finished.
diff --git a/tools/infer/infer-pm-index256.py b/tools/infer/infer-pm-index256.py
new file mode 100644
index 0000000000000000000000000000000000000000..da5430421f1de17a57379aefbe7919dd555b2f50
--- /dev/null
+++ b/tools/infer/infer-pm-index256.py
@@ -0,0 +1,202 @@
+"""
+
+对源特征进行检索
+"""
+import os
+import logging
+
+logger = logging.getLogger(__name__)
+
+import parselmouth
+import torch
+
+os.environ["CUDA_VISIBLE_DEVICES"] = "0"
+# import torchcrepe
+from time import time as ttime
+
+# import pyworld
+import librosa
+import numpy as np
+import soundfile as sf
+import torch.nn.functional as F
+from fairseq import checkpoint_utils
+
+# from models import SynthesizerTrn256#hifigan_nonsf
+# from lib.infer_pack.models import SynthesizerTrn256NSF as SynthesizerTrn256#hifigan_nsf
+from infer.lib.infer_pack.models import (
+    SynthesizerTrnMs256NSFsid as SynthesizerTrn256,
+)  # hifigan_nsf
+from scipy.io import wavfile
+
+# from lib.infer_pack.models import SynthesizerTrnMs256NSFsid_sim as SynthesizerTrn256#hifigan_nsf
+# from models import SynthesizerTrn256NSFsim as SynthesizerTrn256#hifigan_nsf
+# from models import SynthesizerTrn256NSFsimFlow as SynthesizerTrn256#hifigan_nsf
+
+
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+model_path = r"E:\codes\py39\vits_vc_gpu_train\assets\hubert\hubert_base.pt"  #
+logger.info("Load model(s) from {}".format(model_path))
+models, saved_cfg, task = checkpoint_utils.load_model_ensemble_and_task(
+    [model_path],
+    suffix="",
+)
+model = models[0]
+model = model.to(device)
+model = model.half()
+model.eval()
+
+# net_g = SynthesizerTrn256(1025,32,192,192,768,2,6,3,0.1,"1", [3,7,11],[[1,3,5], [1,3,5], [1,3,5]],[10,10,2,2],512,[16,16,4,4],183,256,is_half=True)#hifigan#512#256
+# net_g = SynthesizerTrn256(1025,32,192,192,768,2,6,3,0.1,"1", [3,7,11],[[1,3,5], [1,3,5], [1,3,5]],[10,10,2,2],512,[16,16,4,4],109,256,is_half=True)#hifigan#512#256
+net_g = SynthesizerTrn256(
+    1025,
+    32,
+    192,
+    192,
+    768,
+    2,
+    6,
+    3,
+    0,
+    "1",
+    [3, 7, 11],
+    [[1, 3, 5], [1, 3, 5], [1, 3, 5]],
+    [10, 10, 2, 2],
+    512,
+    [16, 16, 4, 4],
+    183,
+    256,
+    is_half=True,
+)  # hifigan#512#256#no_dropout
+# net_g = SynthesizerTrn256(1025,32,192,192,768,2,3,3,0.1,"1", [3,7,11],[[1,3,5], [1,3,5], [1,3,5]],[10,10,2,2],512,[16,16,4,4],0)#ts3
+# net_g = SynthesizerTrn256(1025,32,192,192,768,2,6,3,0.1,"1", [3,7,11],[[1,3,5], [1,3,5], [1,3,5]],[10,10,2],512,[16,16,4],0)#hifigan-ps-sr
+#
+# net_g = SynthesizerTrn(1025, 32, 192, 192, 768, 2, 6, 3, 0.1, "1", [3, 7, 11], [[1, 3, 5], [1, 3, 5], [1, 3, 5]], [5,5], 512, [15,15], 0)#ms
+# net_g = SynthesizerTrn(1025, 32, 192, 192, 768, 2, 6, 3, 0.1, "1", [3, 7, 11], [[1, 3, 5], [1, 3, 5], [1, 3, 5]], [10,10], 512, [16,16], 0)#idwt2
+
+# weights=torch.load("infer/ft-mi_1k-noD.pt")
+# weights=torch.load("infer/ft-mi-freeze-vocoder-flow-enc_q_1k.pt")
+# weights=torch.load("infer/ft-mi-freeze-vocoder_true_1k.pt")
+# weights=torch.load("infer/ft-mi-sim1k.pt")
+weights = torch.load("infer/ft-mi-no_opt-no_dropout.pt")
+logger.debug(net_g.load_state_dict(weights, strict=True))
+
+net_g.eval().to(device)
+net_g.half()
+
+
+def get_f0(x, p_len, f0_up_key=0):
+    time_step = 160 / 16000 * 1000
+    f0_min = 50
+    f0_max = 1100
+    f0_mel_min = 1127 * np.log(1 + f0_min / 700)
+    f0_mel_max = 1127 * np.log(1 + f0_max / 700)
+
+    f0 = (
+        parselmouth.Sound(x, 16000)
+        .to_pitch_ac(
+            time_step=time_step / 1000,
+            voicing_threshold=0.6,
+            pitch_floor=f0_min,
+            pitch_ceiling=f0_max,
+        )
+        .selected_array["frequency"]
+    )
+
+    pad_size = (p_len - len(f0) + 1) // 2
+    if pad_size > 0 or p_len - len(f0) - pad_size > 0:
+        f0 = np.pad(f0, [[pad_size, p_len - len(f0) - pad_size]], mode="constant")
+    f0 *= pow(2, f0_up_key / 12)
+    f0bak = f0.copy()
+
+    f0_mel = 1127 * np.log(1 + f0 / 700)
+    f0_mel[f0_mel > 0] = (f0_mel[f0_mel > 0] - f0_mel_min) * 254 / (
+        f0_mel_max - f0_mel_min
+    ) + 1
+    f0_mel[f0_mel <= 1] = 1
+    f0_mel[f0_mel > 255] = 255
+    # f0_mel[f0_mel > 188] = 188
+    f0_coarse = np.rint(f0_mel).astype(np.int32)
+    return f0_coarse, f0bak
+
+
+import faiss
+
+index = faiss.read_index("infer/added_IVF512_Flat_mi_baseline_src_feat.index")
+big_npy = np.load("infer/big_src_feature_mi.npy")
+ta0 = ta1 = ta2 = 0
+for idx, name in enumerate(
+    [
+        "冬之花clip1.wav",
+    ]
+):  ##
+    wav_path = "todo-songs/%s" % name  #
+    f0_up_key = -2  #
+    audio, sampling_rate = sf.read(wav_path)
+    if len(audio.shape) > 1:
+        audio = librosa.to_mono(audio.transpose(1, 0))
+    if sampling_rate != 16000:
+        audio = librosa.resample(audio, orig_sr=sampling_rate, target_sr=16000)
+
+    feats = torch.from_numpy(audio).float()
+    if feats.dim() == 2:  # double channels
+        feats = feats.mean(-1)
+    assert feats.dim() == 1, feats.dim()
+    feats = feats.view(1, -1)
+    padding_mask = torch.BoolTensor(feats.shape).fill_(False)
+    inputs = {
+        "source": feats.half().to(device),
+        "padding_mask": padding_mask.to(device),
+        "output_layer": 9,  # layer 9
+    }
+    if torch.cuda.is_available():
+        torch.cuda.synchronize()
+    t0 = ttime()
+    with torch.no_grad():
+        logits = model.extract_features(**inputs)
+        feats = model.final_proj(logits[0])
+
+    ####索引优化
+    npy = feats[0].cpu().numpy().astype("float32")
+    D, I = index.search(npy, 1)
+    feats = (
+        torch.from_numpy(big_npy[I.squeeze()].astype("float16")).unsqueeze(0).to(device)
+    )
+
+    feats = F.interpolate(feats.permute(0, 2, 1), scale_factor=2).permute(0, 2, 1)
+    if torch.cuda.is_available():
+        torch.cuda.synchronize()
+    t1 = ttime()
+    # p_len = min(feats.shape[1],10000,pitch.shape[0])#太大了爆显存
+    p_len = min(feats.shape[1], 10000)  #
+    pitch, pitchf = get_f0(audio, p_len, f0_up_key)
+    p_len = min(feats.shape[1], 10000, pitch.shape[0])  # 太大了爆显存
+    if torch.cuda.is_available():
+        torch.cuda.synchronize()
+    t2 = ttime()
+    feats = feats[:, :p_len, :]
+    pitch = pitch[:p_len]
+    pitchf = pitchf[:p_len]
+    p_len = torch.LongTensor([p_len]).to(device)
+    pitch = torch.LongTensor(pitch).unsqueeze(0).to(device)
+    sid = torch.LongTensor([0]).to(device)
+    pitchf = torch.FloatTensor(pitchf).unsqueeze(0).to(device)
+    with torch.no_grad():
+        audio = (
+            net_g.infer(feats, p_len, pitch, pitchf, sid)[0][0, 0]
+            .data.cpu()
+            .float()
+            .numpy()
+        )  # nsf
+    if torch.cuda.is_available():
+        torch.cuda.synchronize()
+    t3 = ttime()
+    ta0 += t1 - t0
+    ta1 += t2 - t1
+    ta2 += t3 - t2
+    # wavfile.write("ft-mi_1k-index256-noD-%s.wav"%name, 40000, audio)##
+    # wavfile.write("ft-mi-freeze-vocoder-flow-enc_q_1k-%s.wav"%name, 40000, audio)##
+    # wavfile.write("ft-mi-sim1k-%s.wav"%name, 40000, audio)##
+    wavfile.write("ft-mi-no_opt-no_dropout-%s.wav" % name, 40000, audio)  ##
+
+
+logger.debug("%.2fs %.2fs %.2fs", ta0, ta1, ta2)  #
diff --git a/tools/infer/train-index-v2.py b/tools/infer/train-index-v2.py
new file mode 100644
index 0000000000000000000000000000000000000000..cbeed5d4fbf65fcb9a697a99d5f7b41c844e95d6
--- /dev/null
+++ b/tools/infer/train-index-v2.py
@@ -0,0 +1,79 @@
+"""
+格式：直接cid为自带的index位；aid放不下了，通过字典来查，反正就5w个
+"""
+import os
+import traceback
+import logging
+
+logger = logging.getLogger(__name__)
+
+from multiprocessing import cpu_count
+
+import faiss
+import numpy as np
+from sklearn.cluster import MiniBatchKMeans
+
+# ###########如果是原始特征要先写save
+n_cpu = 0
+if n_cpu == 0:
+    n_cpu = cpu_count()
+inp_root = r"./logs/anz/3_feature768"
+npys = []
+listdir_res = list(os.listdir(inp_root))
+for name in sorted(listdir_res):
+    phone = np.load("%s/%s" % (inp_root, name))
+    npys.append(phone)
+big_npy = np.concatenate(npys, 0)
+big_npy_idx = np.arange(big_npy.shape[0])
+np.random.shuffle(big_npy_idx)
+big_npy = big_npy[big_npy_idx]
+logger.debug(big_npy.shape)  # (6196072, 192)#fp32#4.43G
+if big_npy.shape[0] > 2e5:
+    # if(1):
+    info = "Trying doing kmeans %s shape to 10k centers." % big_npy.shape[0]
+    logger.info(info)
+    try:
+        big_npy = (
+            MiniBatchKMeans(
+                n_clusters=10000,
+                verbose=True,
+                batch_size=256 * n_cpu,
+                compute_labels=False,
+                init="random",
+            )
+            .fit(big_npy)
+            .cluster_centers_
+        )
+    except:
+        info = traceback.format_exc()
+        logger.warn(info)
+
+np.save("tools/infer/big_src_feature_mi.npy", big_npy)
+
+##################train+add
+# big_npy=np.load("/bili-coeus/jupyter/jupyterhub-liujing04/vits_ch/inference_f0/big_src_feature_mi.npy")
+n_ivf = min(int(16 * np.sqrt(big_npy.shape[0])), big_npy.shape[0] // 39)
+index = faiss.index_factory(768, "IVF%s,Flat" % n_ivf)  # mi
+logger.info("Training...")
+index_ivf = faiss.extract_index_ivf(index)  #
+index_ivf.nprobe = 1
+index.train(big_npy)
+faiss.write_index(
+    index, "tools/infer/trained_IVF%s_Flat_baseline_src_feat_v2.index" % (n_ivf)
+)
+logger.info("Adding...")
+batch_size_add = 8192
+for i in range(0, big_npy.shape[0], batch_size_add):
+    index.add(big_npy[i : i + batch_size_add])
+faiss.write_index(
+    index, "tools/infer/added_IVF%s_Flat_mi_baseline_src_feat.index" % (n_ivf)
+)
+"""
+大小（都是FP32）
+big_src_feature 2.95G
+    (3098036, 256)
+big_emb         4.43G
+    (6196072, 192)
+big_emb双倍是因为求特征要repeat后再加pitch
+
+"""
diff --git a/tools/infer/train-index.py b/tools/infer/train-index.py
new file mode 100644
index 0000000000000000000000000000000000000000..44b447ef32148c181eb4bcd9013a22a82371b82c
--- /dev/null
+++ b/tools/infer/train-index.py
@@ -0,0 +1,42 @@
+"""
+格式：直接cid为自带的index位；aid放不下了，通过字典来查，反正就5w个
+"""
+import os
+import logging
+
+logger = logging.getLogger(__name__)
+
+import faiss
+import numpy as np
+
+# ###########如果是原始特征要先写save
+inp_root = r"E:\codes\py39\dataset\mi\2-co256"
+npys = []
+for name in sorted(list(os.listdir(inp_root))):
+    phone = np.load("%s/%s" % (inp_root, name))
+    npys.append(phone)
+big_npy = np.concatenate(npys, 0)
+logger.debug(big_npy.shape)  # (6196072, 192)#fp32#4.43G
+np.save("infer/big_src_feature_mi.npy", big_npy)
+
+##################train+add
+# big_npy=np.load("/bili-coeus/jupyter/jupyterhub-liujing04/vits_ch/inference_f0/big_src_feature_mi.npy")
+logger.debug(big_npy.shape)
+index = faiss.index_factory(256, "IVF512,Flat")  # mi
+logger.info("Training...")
+index_ivf = faiss.extract_index_ivf(index)  #
+index_ivf.nprobe = 9
+index.train(big_npy)
+faiss.write_index(index, "infer/trained_IVF512_Flat_mi_baseline_src_feat.index")
+logger.info("Adding...")
+index.add(big_npy)
+faiss.write_index(index, "infer/added_IVF512_Flat_mi_baseline_src_feat.index")
+"""
+大小（都是FP32）
+big_src_feature 2.95G
+    (3098036, 256)
+big_emb         4.43G
+    (6196072, 192)
+big_emb双倍是因为求特征要repeat后再加pitch
+
+"""
diff --git a/tools/infer/trans_weights.py b/tools/infer/trans_weights.py
new file mode 100644
index 0000000000000000000000000000000000000000..1c54eefd6e7c678238d31e251a2e15479bf35d5b
--- /dev/null
+++ b/tools/infer/trans_weights.py
@@ -0,0 +1,18 @@
+import pdb
+
+import torch
+
+# a=torch.load(r"E:\codes\py39\vits_vc_gpu_train\logs\ft-mi-suc\G_1000.pth")["model"]#sim_nsf#
+# a=torch.load(r"E:\codes\py39\vits_vc_gpu_train\logs\ft-mi-freeze-vocoder-flow-enc_q\G_1000.pth")["model"]#sim_nsf#
+# a=torch.load(r"E:\codes\py39\vits_vc_gpu_train\logs\ft-mi-freeze-vocoder\G_1000.pth")["model"]#sim_nsf#
+# a=torch.load(r"E:\codes\py39\vits_vc_gpu_train\logs\ft-mi-test\G_1000.pth")["model"]#sim_nsf#
+a = torch.load(
+    r"E:\codes\py39\vits_vc_gpu_train\logs\ft-mi-no_opt-no_dropout\G_1000.pth"
+)[
+    "model"
+]  # sim_nsf#
+for key in a.keys():
+    a[key] = a[key].half()
+# torch.save(a,"ft-mi-freeze-vocoder_true_1k.pt")#
+# torch.save(a,"ft-mi-sim1k.pt")#
+torch.save(a, "ft-mi-no_opt-no_dropout.pt")  #
diff --git a/tools/infer_batch_rvc.py b/tools/infer_batch_rvc.py
new file mode 100644
index 0000000000000000000000000000000000000000..763d17f14877a2ce35f750202e91356c1f24270f
--- /dev/null
+++ b/tools/infer_batch_rvc.py
@@ -0,0 +1,72 @@
+import argparse
+import os
+import sys
+
+print("Command-line arguments:", sys.argv)
+
+now_dir = os.getcwd()
+sys.path.append(now_dir)
+import sys
+
+import tqdm as tq
+from dotenv import load_dotenv
+from scipy.io import wavfile
+
+from configs.config import Config
+from infer.modules.vc.modules import VC
+
+
+def arg_parse() -> tuple:
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--f0up_key", type=int, default=0)
+    parser.add_argument("--input_path", type=str, help="input path")
+    parser.add_argument("--index_path", type=str, help="index path")
+    parser.add_argument("--f0method", type=str, default="harvest", help="harvest or pm")
+    parser.add_argument("--opt_path", type=str, help="opt path")
+    parser.add_argument("--model_name", type=str, help="store in assets/weight_root")
+    parser.add_argument("--index_rate", type=float, default=0.66, help="index rate")
+    parser.add_argument("--device", type=str, help="device")
+    parser.add_argument("--is_half", type=bool, help="use half -> True")
+    parser.add_argument("--filter_radius", type=int, default=3, help="filter radius")
+    parser.add_argument("--resample_sr", type=int, default=0, help="resample sr")
+    parser.add_argument("--rms_mix_rate", type=float, default=1, help="rms mix rate")
+    parser.add_argument("--protect", type=float, default=0.33, help="protect")
+
+    args = parser.parse_args()
+    sys.argv = sys.argv[:1]
+
+    return args
+
+
+def main():
+    load_dotenv()
+    args = arg_parse()
+    config = Config()
+    config.device = args.device if args.device else config.device
+    config.is_half = args.is_half if args.is_half else config.is_half
+    vc = VC(config)
+    vc.get_vc(args.model_name)
+    audios = os.listdir(args.input_path)
+    for file in tq.tqdm(audios):
+        if file.endswith(".wav"):
+            file_path = os.path.join(args.input_path, file)
+            _, wav_opt = vc.vc_single(
+                0,
+                file_path,
+                args.f0up_key,
+                None,
+                args.f0method,
+                args.index_path,
+                None,
+                args.index_rate,
+                args.filter_radius,
+                args.resample_sr,
+                args.rms_mix_rate,
+                args.protect,
+            )
+            out_path = os.path.join(args.opt_path, file)
+            wavfile.write(out_path, wav_opt[0], wav_opt[1])
+
+
+if __name__ == "__main__":
+    main()
diff --git a/tools/infer_cli.py b/tools/infer_cli.py
new file mode 100644
index 0000000000000000000000000000000000000000..bbe0a53c1aac6a8f2d42613d554b2bdd07abea2d
--- /dev/null
+++ b/tools/infer_cli.py
@@ -0,0 +1,67 @@
+import argparse
+import os
+import sys
+
+now_dir = os.getcwd()
+sys.path.append(now_dir)
+from dotenv import load_dotenv
+from scipy.io import wavfile
+
+from configs.config import Config
+from infer.modules.vc.modules import VC
+
+####
+# USAGE
+#
+# In your Terminal or CMD or whatever
+
+
+def arg_parse() -> tuple:
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--f0up_key", type=int, default=0)
+    parser.add_argument("--input_path", type=str, help="input path")
+    parser.add_argument("--index_path", type=str, help="index path")
+    parser.add_argument("--f0method", type=str, default="harvest", help="harvest or pm")
+    parser.add_argument("--opt_path", type=str, help="opt path")
+    parser.add_argument("--model_name", type=str, help="store in assets/weight_root")
+    parser.add_argument("--index_rate", type=float, default=0.66, help="index rate")
+    parser.add_argument("--device", type=str, help="device")
+    parser.add_argument("--is_half", type=bool, help="use half -> True")
+    parser.add_argument("--filter_radius", type=int, default=3, help="filter radius")
+    parser.add_argument("--resample_sr", type=int, default=0, help="resample sr")
+    parser.add_argument("--rms_mix_rate", type=float, default=1, help="rms mix rate")
+    parser.add_argument("--protect", type=float, default=0.33, help="protect")
+
+    args = parser.parse_args()
+    sys.argv = sys.argv[:1]
+
+    return args
+
+
+def main():
+    load_dotenv()
+    args = arg_parse()
+    config = Config()
+    config.device = args.device if args.device else config.device
+    config.is_half = args.is_half if args.is_half else config.is_half
+    vc = VC(config)
+    vc.get_vc(args.model_name)
+    _, wav_opt = vc.vc_single(
+        0,
+        args.input_path,
+        args.f0up_key,
+        None,
+        args.f0method,
+        args.index_path,
+        None,
+        args.index_rate,
+        args.filter_radius,
+        args.resample_sr,
+        args.rms_mix_rate,
+        args.protect,
+    )
+    wavfile.write(args.opt_path, wav_opt[0], wav_opt[1])
+
+
+if __name__ == "__main__":
+    main()
diff --git a/tools/rvc_for_realtime.py b/tools/rvc_for_realtime.py
new file mode 100644
index 0000000000000000000000000000000000000000..f746cde4dfd9c3b87fe844304aa3a975d68b3433
--- /dev/null
+++ b/tools/rvc_for_realtime.py
@@ -0,0 +1,381 @@
+import os
+import sys
+import traceback
+import logging
+
+logger = logging.getLogger(__name__)
+
+from time import time as ttime
+
+import fairseq
+import faiss
+import numpy as np
+import parselmouth
+import pyworld
+import scipy.signal as signal
+import torch
+import torch.nn as nn
+import torch.nn.functional as F
+import torchcrepe
+
+from infer.lib.infer_pack.models import (
+    SynthesizerTrnMs256NSFsid,
+    SynthesizerTrnMs256NSFsid_nono,
+    SynthesizerTrnMs768NSFsid,
+    SynthesizerTrnMs768NSFsid_nono,
+)
+
+now_dir = os.getcwd()
+sys.path.append(now_dir)
+from multiprocessing import Manager as M
+
+from configs.config import Config
+
+config = Config()
+
+mm = M()
+if config.dml == True:
+
+    def forward_dml(ctx, x, scale):
+        ctx.scale = scale
+        res = x.clone().detach()
+        return res
+
+    fairseq.modules.grad_multiply.GradMultiply.forward = forward_dml
+
+
+# config.device=torch.device("cpu")########强制cpu测试
+# config.is_half=False########强制cpu测试
+class RVC:
+    def __init__(
+        self,
+        key,
+        pth_path,
+        index_path,
+        index_rate,
+        n_cpu,
+        inp_q,
+        opt_q,
+        device,
+        last_rvc=None,
+    ) -> None:
+        """
+        初始化
+        """
+        try:
+            global config
+            self.inp_q = inp_q
+            self.opt_q = opt_q
+            # device="cpu"########强制cpu测试
+            self.device = device
+            self.f0_up_key = key
+            self.time_step = 160 / 16000 * 1000
+            self.f0_min = 50
+            self.f0_max = 1100
+            self.f0_mel_min = 1127 * np.log(1 + self.f0_min / 700)
+            self.f0_mel_max = 1127 * np.log(1 + self.f0_max / 700)
+            self.sr = 16000
+            self.window = 160
+            self.n_cpu = n_cpu
+            if index_rate != 0:
+                self.index = faiss.read_index(index_path)
+                self.big_npy = self.index.reconstruct_n(0, self.index.ntotal)
+                logger.info("Index search enabled")
+            self.pth_path = pth_path
+            self.index_path = index_path
+            self.index_rate = index_rate
+
+            if last_rvc is None:
+                models, _, _ = fairseq.checkpoint_utils.load_model_ensemble_and_task(
+                    ["assets/hubert/hubert_base.pt"],
+                    suffix="",
+                )
+                hubert_model = models[0]
+                hubert_model = hubert_model.to(device)
+                if config.is_half:
+                    hubert_model = hubert_model.half()
+                else:
+                    hubert_model = hubert_model.float()
+                hubert_model.eval()
+                self.model = hubert_model
+            else:
+                self.model = last_rvc.model
+
+            if last_rvc is None or last_rvc.pth_path != self.pth_path:
+                cpt = torch.load(self.pth_path, map_location="cpu")
+                self.tgt_sr = cpt["config"][-1]
+                cpt["config"][-3] = cpt["weight"]["emb_g.weight"].shape[0]
+                self.if_f0 = cpt.get("f0", 1)
+                self.version = cpt.get("version", "v1")
+                if self.version == "v1":
+                    if self.if_f0 == 1:
+                        self.net_g = SynthesizerTrnMs256NSFsid(
+                            *cpt["config"], is_half=config.is_half
+                        )
+                    else:
+                        self.net_g = SynthesizerTrnMs256NSFsid_nono(*cpt["config"])
+                elif self.version == "v2":
+                    if self.if_f0 == 1:
+                        self.net_g = SynthesizerTrnMs768NSFsid(
+                            *cpt["config"], is_half=config.is_half
+                        )
+                    else:
+                        self.net_g = SynthesizerTrnMs768NSFsid_nono(*cpt["config"])
+                del self.net_g.enc_q
+                logger.debug(self.net_g.load_state_dict(cpt["weight"], strict=False))
+                self.net_g.eval().to(device)
+                # print(2333333333,device,config.device,self.device)#net_g是device，hubert是config.device
+                if config.is_half:
+                    self.net_g = self.net_g.half()
+                else:
+                    self.net_g = self.net_g.float()
+                self.is_half = config.is_half
+            else:
+                self.tgt_sr = last_rvc.tgt_sr
+                self.if_f0 = last_rvc.if_f0
+                self.version = last_rvc.version
+                self.net_g = last_rvc.net_g
+                self.is_half = last_rvc.is_half
+
+            if last_rvc is not None and hasattr(last_rvc, "model_rmvpe"):
+                self.model_rmvpe = last_rvc.model_rmvpe
+        except:
+            logger.warn(traceback.format_exc())
+
+    def change_key(self, new_key):
+        self.f0_up_key = new_key
+
+    def change_index_rate(self, new_index_rate):
+        if new_index_rate != 0 and self.index_rate == 0:
+            self.index = faiss.read_index(self.index_path)
+            self.big_npy = self.index.reconstruct_n(0, self.index.ntotal)
+            logger.info("Index search enabled")
+        self.index_rate = new_index_rate
+
+    def get_f0_post(self, f0):
+        f0_min = self.f0_min
+        f0_max = self.f0_max
+        f0_mel_min = 1127 * np.log(1 + f0_min / 700)
+        f0_mel_max = 1127 * np.log(1 + f0_max / 700)
+        f0bak = f0.copy()
+        f0_mel = 1127 * np.log(1 + f0 / 700)
+        f0_mel[f0_mel > 0] = (f0_mel[f0_mel > 0] - f0_mel_min) * 254 / (
+            f0_mel_max - f0_mel_min
+        ) + 1
+        f0_mel[f0_mel <= 1] = 1
+        f0_mel[f0_mel > 255] = 255
+        f0_coarse = np.rint(f0_mel).astype(np.int32)
+        return f0_coarse, f0bak
+
+    def get_f0(self, x, f0_up_key, n_cpu, method="harvest"):
+        n_cpu = int(n_cpu)
+        if method == "crepe":
+            return self.get_f0_crepe(x, f0_up_key)
+        if method == "rmvpe":
+            return self.get_f0_rmvpe(x, f0_up_key)
+        if method == "pm":
+            p_len = x.shape[0] // 160 + 1
+            f0 = (
+                parselmouth.Sound(x, 16000)
+                .to_pitch_ac(
+                    time_step=0.01,
+                    voicing_threshold=0.6,
+                    pitch_floor=50,
+                    pitch_ceiling=1100,
+                )
+                .selected_array["frequency"]
+            )
+
+            pad_size = (p_len - len(f0) + 1) // 2
+            if pad_size > 0 or p_len - len(f0) - pad_size > 0:
+                # print(pad_size, p_len - len(f0) - pad_size)
+                f0 = np.pad(
+                    f0, [[pad_size, p_len - len(f0) - pad_size]], mode="constant"
+                )
+
+            f0 *= pow(2, f0_up_key / 12)
+            return self.get_f0_post(f0)
+        if n_cpu == 1:
+            f0, t = pyworld.harvest(
+                x.astype(np.double),
+                fs=16000,
+                f0_ceil=1100,
+                f0_floor=50,
+                frame_period=10,
+            )
+            f0 = signal.medfilt(f0, 3)
+            f0 *= pow(2, f0_up_key / 12)
+            return self.get_f0_post(f0)
+        f0bak = np.zeros(x.shape[0] // 160 + 1, dtype=np.float64)
+        length = len(x)
+        part_length = 160 * ((length // 160 - 1) // n_cpu + 1)
+        n_cpu = (length // 160 - 1) // (part_length // 160) + 1
+        ts = ttime()
+        res_f0 = mm.dict()
+        for idx in range(n_cpu):
+            tail = part_length * (idx + 1) + 320
+            if idx == 0:
+                self.inp_q.put((idx, x[:tail], res_f0, n_cpu, ts))
+            else:
+                self.inp_q.put(
+                    (idx, x[part_length * idx - 320 : tail], res_f0, n_cpu, ts)
+                )
+        while 1:
+            res_ts = self.opt_q.get()
+            if res_ts == ts:
+                break
+        f0s = [i[1] for i in sorted(res_f0.items(), key=lambda x: x[0])]
+        for idx, f0 in enumerate(f0s):
+            if idx == 0:
+                f0 = f0[:-3]
+            elif idx != n_cpu - 1:
+                f0 = f0[2:-3]
+            else:
+                f0 = f0[2:]
+            f0bak[
+                part_length * idx // 160 : part_length * idx // 160 + f0.shape[0]
+            ] = f0
+        f0bak = signal.medfilt(f0bak, 3)
+        f0bak *= pow(2, f0_up_key / 12)
+        return self.get_f0_post(f0bak)
+
+    def get_f0_crepe(self, x, f0_up_key):
+        if "privateuseone" in str(self.device):  ###不支持dml，cpu又太慢用不成，拿pm顶替
+            return self.get_f0(x, f0_up_key, 1, "pm")
+        audio = torch.tensor(np.copy(x))[None].float()
+        # print("using crepe,device:%s"%self.device)
+        f0, pd = torchcrepe.predict(
+            audio,
+            self.sr,
+            160,
+            self.f0_min,
+            self.f0_max,
+            "full",
+            batch_size=512,
+            # device=self.device if self.device.type!="privateuseone" else "cpu",###crepe不用半精度全部是全精度所以不愁###cpu延迟高到没法用
+            device=self.device,
+            return_periodicity=True,
+        )
+        pd = torchcrepe.filter.median(pd, 3)
+        f0 = torchcrepe.filter.mean(f0, 3)
+        f0[pd < 0.1] = 0
+        f0 = f0[0].cpu().numpy()
+        f0 *= pow(2, f0_up_key / 12)
+        return self.get_f0_post(f0)
+
+    def get_f0_rmvpe(self, x, f0_up_key):
+        if hasattr(self, "model_rmvpe") == False:
+            from infer.lib.rmvpe import RMVPE
+
+            logger.info("Loading rmvpe model")
+            self.model_rmvpe = RMVPE(
+                # "rmvpe.pt", is_half=self.is_half if self.device.type!="privateuseone" else False, device=self.device if self.device.type!="privateuseone"else "cpu"####dml时强制对rmvpe用cpu跑
+                #  "rmvpe.pt", is_half=False, device=self.device####dml配置
+                # "rmvpe.pt", is_half=False, device="cpu"####锁定cpu配置
+                "assets/rmvpe/rmvpe.pt",
+                is_half=self.is_half,
+                device=self.device,  ####正常逻辑
+            )
+            # self.model_rmvpe = RMVPE("aug2_58000_half.pt", is_half=self.is_half, device=self.device)
+        f0 = self.model_rmvpe.infer_from_audio(x, thred=0.03)
+        f0 *= pow(2, f0_up_key / 12)
+        return self.get_f0_post(f0)
+
+    def infer(
+        self,
+        feats: torch.Tensor,
+        indata: np.ndarray,
+        block_frame_16k,
+        rate,
+        cache_pitch,
+        cache_pitchf,
+        f0method,
+    ) -> np.ndarray:
+        feats = feats.view(1, -1)
+        if config.is_half:
+            feats = feats.half()
+        else:
+            feats = feats.float()
+        feats = feats.to(self.device)
+        t1 = ttime()
+        with torch.no_grad():
+            padding_mask = torch.BoolTensor(feats.shape).to(self.device).fill_(False)
+            inputs = {
+                "source": feats,
+                "padding_mask": padding_mask,
+                "output_layer": 9 if self.version == "v1" else 12,
+            }
+            logits = self.model.extract_features(**inputs)
+            feats = (
+                self.model.final_proj(logits[0]) if self.version == "v1" else logits[0]
+            )
+            feats = F.pad(feats, (0, 0, 1, 0))
+        t2 = ttime()
+        try:
+            if hasattr(self, "index") and self.index_rate != 0:
+                leng_replace_head = int(rate * feats[0].shape[0])
+                npy = feats[0][-leng_replace_head:].cpu().numpy().astype("float32")
+                score, ix = self.index.search(npy, k=8)
+                weight = np.square(1 / score)
+                weight /= weight.sum(axis=1, keepdims=True)
+                npy = np.sum(self.big_npy[ix] * np.expand_dims(weight, axis=2), axis=1)
+                if config.is_half:
+                    npy = npy.astype("float16")
+                feats[0][-leng_replace_head:] = (
+                    torch.from_numpy(npy).unsqueeze(0).to(self.device) * self.index_rate
+                    + (1 - self.index_rate) * feats[0][-leng_replace_head:]
+                )
+            else:
+                logger.warn("Index search FAILED or disabled")
+        except:
+            traceback.print_exc()
+            logger.warn("Index search FAILED")
+        feats = F.interpolate(feats.permute(0, 2, 1), scale_factor=2).permute(0, 2, 1)
+        t3 = ttime()
+        if self.if_f0 == 1:
+            pitch, pitchf = self.get_f0(indata, self.f0_up_key, self.n_cpu, f0method)
+            start_frame = block_frame_16k // 160
+            end_frame = len(cache_pitch) - (pitch.shape[0] - 4) + start_frame
+            cache_pitch[:] = np.append(cache_pitch[start_frame:end_frame], pitch[3:-1])
+            cache_pitchf[:] = np.append(
+                cache_pitchf[start_frame:end_frame], pitchf[3:-1]
+            )
+            p_len = min(feats.shape[1], 13000, cache_pitch.shape[0])
+        else:
+            cache_pitch, cache_pitchf = None, None
+            p_len = min(feats.shape[1], 13000)
+        t4 = ttime()
+        feats = feats[:, :p_len, :]
+        if self.if_f0 == 1:
+            cache_pitch = cache_pitch[:p_len]
+            cache_pitchf = cache_pitchf[:p_len]
+            cache_pitch = torch.LongTensor(cache_pitch).unsqueeze(0).to(self.device)
+            cache_pitchf = torch.FloatTensor(cache_pitchf).unsqueeze(0).to(self.device)
+        p_len = torch.LongTensor([p_len]).to(self.device)
+        ii = 0  # sid
+        sid = torch.LongTensor([ii]).to(self.device)
+        with torch.no_grad():
+            if self.if_f0 == 1:
+                # print(12222222222,feats.device,p_len.device,cache_pitch.device,cache_pitchf.device,sid.device,rate2)
+                infered_audio = (
+                    self.net_g.infer(
+                        feats, p_len, cache_pitch, cache_pitchf, sid, rate
+                    )[0][0, 0]
+                    .data
+                    .float()
+                )
+            else:
+                infered_audio = (
+                    self.net_g.infer(feats, p_len, sid, rate)[0][0, 0]
+                    .data
+                    .float()
+                )
+        t5 = ttime()
+        logger.info(
+            "Spent time: fea = %.2fs, index = %.2fs, f0 = %.2fs, model = %.2fs",
+            t2 - t1,
+            t3 - t2,
+            t4 - t3,
+            t5 - t4,
+        )
+        return infered_audio
\ No newline at end of file
diff --git a/tools/torchgate/__init__.py b/tools/torchgate/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..b4a12675828dceb6e6270f9439cdf98ea28ea96d
--- /dev/null
+++ b/tools/torchgate/__init__.py
@@ -0,0 +1,12 @@
+"""
+TorchGating is a PyTorch-based implementation of Spectral Gating
+================================================
+Author: Asaf Zorea
+
+Contents
+--------
+torchgate imports all the functions from PyTorch, and in addition provides:
+ TorchGating       --- A PyTorch module that applies a spectral gate to an input signal
+
+"""
+from .torchgate import TorchGate
diff --git a/tools/torchgate/torchgate.py b/tools/torchgate/torchgate.py
new file mode 100644
index 0000000000000000000000000000000000000000..086f2ab38e4ad79e432a51c38ed7e59defae0acd
--- /dev/null
+++ b/tools/torchgate/torchgate.py
@@ -0,0 +1,264 @@
+import torch
+from torch.nn.functional import conv1d, conv2d
+from typing import Union, Optional
+from .utils import linspace, temperature_sigmoid, amp_to_db
+
+
+class TorchGate(torch.nn.Module):
+    """
+    A PyTorch module that applies a spectral gate to an input signal.
+
+    Arguments:
+        sr {int} -- Sample rate of the input signal.
+        nonstationary {bool} -- Whether to use non-stationary or stationary masking (default: {False}).
+        n_std_thresh_stationary {float} -- Number of standard deviations above mean to threshold noise for
+                                           stationary masking (default: {1.5}).
+        n_thresh_nonstationary {float} -- Number of multiplies above smoothed magnitude spectrogram. for
+                                        non-stationary masking (default: {1.3}).
+        temp_coeff_nonstationary {float} -- Temperature coefficient for non-stationary masking (default: {0.1}).
+        n_movemean_nonstationary {int} -- Number of samples for moving average smoothing in non-stationary masking
+                                          (default: {20}).
+        prop_decrease {float} -- Proportion to decrease signal by where the mask is zero (default: {1.0}).
+        n_fft {int} -- Size of FFT for STFT (default: {1024}).
+        win_length {[int]} -- Window length for STFT. If None, defaults to `n_fft` (default: {None}).
+        hop_length {[int]} -- Hop length for STFT. If None, defaults to `win_length` // 4 (default: {None}).
+        freq_mask_smooth_hz {float} -- Frequency smoothing width for mask (in Hz). If None, no smoothing is applied
+                                     (default: {500}).
+        time_mask_smooth_ms {float} -- Time smoothing width for mask (in ms). If None, no smoothing is applied
+                                     (default: {50}).
+    """
+
+    @torch.no_grad()
+    def __init__(
+        self,
+        sr: int,
+        nonstationary: bool = False,
+        n_std_thresh_stationary: float = 1.5,
+        n_thresh_nonstationary: float = 1.3,
+        temp_coeff_nonstationary: float = 0.1,
+        n_movemean_nonstationary: int = 20,
+        prop_decrease: float = 1.0,
+        n_fft: int = 1024,
+        win_length: bool = None,
+        hop_length: int = None,
+        freq_mask_smooth_hz: float = 500,
+        time_mask_smooth_ms: float = 50,
+    ):
+        super().__init__()
+
+        # General Params
+        self.sr = sr
+        self.nonstationary = nonstationary
+        assert 0.0 <= prop_decrease <= 1.0
+        self.prop_decrease = prop_decrease
+
+        # STFT Params
+        self.n_fft = n_fft
+        self.win_length = self.n_fft if win_length is None else win_length
+        self.hop_length = self.win_length // 4 if hop_length is None else hop_length
+
+        # Stationary Params
+        self.n_std_thresh_stationary = n_std_thresh_stationary
+
+        # Non-Stationary Params
+        self.temp_coeff_nonstationary = temp_coeff_nonstationary
+        self.n_movemean_nonstationary = n_movemean_nonstationary
+        self.n_thresh_nonstationary = n_thresh_nonstationary
+
+        # Smooth Mask Params
+        self.freq_mask_smooth_hz = freq_mask_smooth_hz
+        self.time_mask_smooth_ms = time_mask_smooth_ms
+        self.register_buffer("smoothing_filter", self._generate_mask_smoothing_filter())
+
+    @torch.no_grad()
+    def _generate_mask_smoothing_filter(self) -> Union[torch.Tensor, None]:
+        """
+        A PyTorch module that applies a spectral gate to an input signal using the STFT.
+
+        Returns:
+            smoothing_filter (torch.Tensor): a 2D tensor representing the smoothing filter,
+            with shape (n_grad_freq, n_grad_time), where n_grad_freq is the number of frequency
+            bins to smooth and n_grad_time is the number of time frames to smooth.
+            If both self.freq_mask_smooth_hz and self.time_mask_smooth_ms are None, returns None.
+        """
+        if self.freq_mask_smooth_hz is None and self.time_mask_smooth_ms is None:
+            return None
+
+        n_grad_freq = (
+            1
+            if self.freq_mask_smooth_hz is None
+            else int(self.freq_mask_smooth_hz / (self.sr / (self.n_fft / 2)))
+        )
+        if n_grad_freq < 1:
+            raise ValueError(
+                f"freq_mask_smooth_hz needs to be at least {int((self.sr / (self._n_fft / 2)))} Hz"
+            )
+
+        n_grad_time = (
+            1
+            if self.time_mask_smooth_ms is None
+            else int(self.time_mask_smooth_ms / ((self.hop_length / self.sr) * 1000))
+        )
+        if n_grad_time < 1:
+            raise ValueError(
+                f"time_mask_smooth_ms needs to be at least {int((self.hop_length / self.sr) * 1000)} ms"
+            )
+
+        if n_grad_time == 1 and n_grad_freq == 1:
+            return None
+
+        v_f = torch.cat(
+            [
+                linspace(0, 1, n_grad_freq + 1, endpoint=False),
+                linspace(1, 0, n_grad_freq + 2),
+            ]
+        )[1:-1]
+        v_t = torch.cat(
+            [
+                linspace(0, 1, n_grad_time + 1, endpoint=False),
+                linspace(1, 0, n_grad_time + 2),
+            ]
+        )[1:-1]
+        smoothing_filter = torch.outer(v_f, v_t).unsqueeze(0).unsqueeze(0)
+
+        return smoothing_filter / smoothing_filter.sum()
+
+    @torch.no_grad()
+    def _stationary_mask(
+        self, X_db: torch.Tensor, xn: Optional[torch.Tensor] = None
+    ) -> torch.Tensor:
+        """
+        Computes a stationary binary mask to filter out noise in a log-magnitude spectrogram.
+
+        Arguments:
+            X_db (torch.Tensor): 2D tensor of shape (frames, freq_bins) containing the log-magnitude spectrogram.
+            xn (torch.Tensor): 1D tensor containing the audio signal corresponding to X_db.
+
+        Returns:
+            sig_mask (torch.Tensor): Binary mask of the same shape as X_db, where values greater than the threshold
+            are set to 1, and the rest are set to 0.
+        """
+        if xn is not None:
+            XN = torch.stft(
+                xn,
+                n_fft=self.n_fft,
+                hop_length=self.hop_length,
+                win_length=self.win_length,
+                return_complex=True,
+                pad_mode="constant",
+                center=True,
+                window=torch.hann_window(self.win_length).to(xn.device),
+            )
+
+            XN_db = amp_to_db(XN).to(dtype=X_db.dtype)
+        else:
+            XN_db = X_db
+
+        # calculate mean and standard deviation along the frequency axis
+        std_freq_noise, mean_freq_noise = torch.std_mean(XN_db, dim=-1)
+
+        # compute noise threshold
+        noise_thresh = mean_freq_noise + std_freq_noise * self.n_std_thresh_stationary
+
+        # create binary mask by thresholding the spectrogram
+        sig_mask = X_db > noise_thresh.unsqueeze(2)
+        return sig_mask
+
+    @torch.no_grad()
+    def _nonstationary_mask(self, X_abs: torch.Tensor) -> torch.Tensor:
+        """
+        Computes a non-stationary binary mask to filter out noise in a log-magnitude spectrogram.
+
+        Arguments:
+            X_abs (torch.Tensor): 2D tensor of shape (frames, freq_bins) containing the magnitude spectrogram.
+
+        Returns:
+            sig_mask (torch.Tensor): Binary mask of the same shape as X_abs, where values greater than the threshold
+            are set to 1, and the rest are set to 0.
+        """
+        X_smoothed = (
+            conv1d(
+                X_abs.reshape(-1, 1, X_abs.shape[-1]),
+                torch.ones(
+                    self.n_movemean_nonstationary,
+                    dtype=X_abs.dtype,
+                    device=X_abs.device,
+                ).view(1, 1, -1),
+                padding="same",
+            ).view(X_abs.shape)
+            / self.n_movemean_nonstationary
+        )
+
+        # Compute slowness ratio and apply temperature sigmoid
+        slowness_ratio = (X_abs - X_smoothed) / (X_smoothed + 1e-6)
+        sig_mask = temperature_sigmoid(
+            slowness_ratio, self.n_thresh_nonstationary, self.temp_coeff_nonstationary
+        )
+
+        return sig_mask
+
+    def forward(
+        self, x: torch.Tensor, xn: Optional[torch.Tensor] = None
+    ) -> torch.Tensor:
+        """
+        Apply the proposed algorithm to the input signal.
+
+        Arguments:
+            x (torch.Tensor): The input audio signal, with shape (batch_size, signal_length).
+            xn (Optional[torch.Tensor]): The noise signal used for stationary noise reduction. If `None`, the input
+                                         signal is used as the noise signal. Default: `None`.
+
+        Returns:
+            torch.Tensor: The denoised audio signal, with the same shape as the input signal.
+        """
+        assert x.ndim == 2
+        if x.shape[-1] < self.win_length * 2:
+            raise Exception(f"x must be bigger than {self.win_length * 2}")
+
+        assert xn is None or xn.ndim == 1 or xn.ndim == 2
+        if xn is not None and xn.shape[-1] < self.win_length * 2:
+            raise Exception(f"xn must be bigger than {self.win_length * 2}")
+
+        # Compute short-time Fourier transform (STFT)
+        X = torch.stft(
+            x,
+            n_fft=self.n_fft,
+            hop_length=self.hop_length,
+            win_length=self.win_length,
+            return_complex=True,
+            pad_mode="constant",
+            center=True,
+            window=torch.hann_window(self.win_length).to(x.device),
+        )
+
+        # Compute signal mask based on stationary or nonstationary assumptions
+        if self.nonstationary:
+            sig_mask = self._nonstationary_mask(X.abs())
+        else:
+            sig_mask = self._stationary_mask(amp_to_db(X), xn)
+
+        # Propagate decrease in signal power
+        sig_mask = self.prop_decrease * (sig_mask * 1.0 - 1.0) + 1.0
+
+        # Smooth signal mask with 2D convolution
+        if self.smoothing_filter is not None:
+            sig_mask = conv2d(
+                sig_mask.unsqueeze(1),
+                self.smoothing_filter.to(sig_mask.dtype),
+                padding="same",
+            )
+
+        # Apply signal mask to STFT magnitude and phase components
+        Y = X * sig_mask.squeeze(1)
+
+        # Inverse STFT to obtain time-domain signal
+        y = torch.istft(
+            Y,
+            n_fft=self.n_fft,
+            hop_length=self.hop_length,
+            win_length=self.win_length,
+            center=True,
+            window=torch.hann_window(self.win_length).to(Y.device),
+        )
+
+        return y.to(dtype=x.dtype)
diff --git a/tools/torchgate/utils.py b/tools/torchgate/utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..dc97d45a399c112c76e80cdd8c73cfebaf3ef6ad
--- /dev/null
+++ b/tools/torchgate/utils.py
@@ -0,0 +1,66 @@
+import torch
+from torch.types import Number
+
+
+@torch.no_grad()
+def amp_to_db(x: torch.Tensor, eps=torch.finfo(torch.float64).eps, top_db=40) -> torch.Tensor:
+    """
+    Convert the input tensor from amplitude to decibel scale.
+
+    Arguments:
+        x {[torch.Tensor]} -- [Input tensor.]
+
+    Keyword Arguments:
+        eps {[float]} -- [Small value to avoid numerical instability.]
+                          (default: {torch.finfo(torch.float64).eps})
+        top_db {[float]} -- [threshold the output at ``top_db`` below the peak]
+            `             (default: {40})
+
+    Returns:
+        [torch.Tensor] -- [Output tensor in decibel scale.]
+    """
+    x_db = 20 * torch.log10(x.abs() + eps)
+    return torch.max(x_db, (x_db.max(-1).values - top_db).unsqueeze(-1))
+
+
+@torch.no_grad()
+def temperature_sigmoid(x: torch.Tensor, x0: float, temp_coeff: float) -> torch.Tensor:
+    """
+    Apply a sigmoid function with temperature scaling.
+
+    Arguments:
+        x {[torch.Tensor]} -- [Input tensor.]
+        x0 {[float]} -- [Parameter that controls the threshold of the sigmoid.]
+        temp_coeff {[float]} -- [Parameter that controls the slope of the sigmoid.]
+
+    Returns:
+        [torch.Tensor] -- [Output tensor after applying the sigmoid with temperature scaling.]
+    """
+    return torch.sigmoid((x - x0) / temp_coeff)
+
+
+@torch.no_grad()
+def linspace(start: Number, stop: Number, num: int = 50, endpoint: bool = True, **kwargs) -> torch.Tensor:
+    """
+    Generate a linearly spaced 1-D tensor.
+
+    Arguments:
+        start {[Number]} -- [The starting value of the sequence.]
+        stop {[Number]} -- [The end value of the sequence, unless `endpoint` is set to False.
+                            In that case, the sequence consists of all but the last of ``num + 1``
+                            evenly spaced samples, so that `stop` is excluded. Note that the step
+                            size changes when `endpoint` is False.]
+
+    Keyword Arguments:
+        num {[int]} -- [Number of samples to generate. Default is 50. Must be non-negative.]
+        endpoint {[bool]} -- [If True, `stop` is the last sample. Otherwise, it is not included.
+                              Default is True.]
+        **kwargs -- [Additional arguments to be passed to the underlying PyTorch `linspace` function.]
+
+    Returns:
+        [torch.Tensor] -- [1-D tensor of `num` equally spaced samples from `start` to `stop`.]
+    """
+    if endpoint:
+        return torch.linspace(start, stop, num, **kwargs)
+    else:
+        return torch.linspace(start, stop, num + 1, **kwargs)[:-1]
diff --git a/tracks/.gitkeep b/tracks/.gitkeep
new file mode 100644
index 0000000000000000000000000000000000000000..8b137891791fe96927ad78e64b0aad7bded08bdc
--- /dev/null
+++ b/tracks/.gitkeep
@@ -0,0 +1 @@
+
diff --git a/train/cmd.txt b/train/cmd.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e4b895e54fbcd4ffa5ba4ded7d0f37f04f67392f
--- /dev/null
+++ b/train/cmd.txt
@@ -0,0 +1 @@
+python train_nsf_sim_cache_sid.py -c configs/mi_mix40k_nsf_co256_cs1sid_ms2048.json -m ft-mi
\ No newline at end of file
diff --git a/train/data_utils.py b/train/data_utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..71c0eff1815469a52399dc90a093a2f8a29223eb
--- /dev/null
+++ b/train/data_utils.py
@@ -0,0 +1,512 @@
+import os, traceback
+import numpy as np
+import torch
+import torch.utils.data
+
+from mel_processing import spectrogram_torch
+from utils import load_wav_to_torch, load_filepaths_and_text
+
+
+class TextAudioLoaderMultiNSFsid(torch.utils.data.Dataset):
+    """
+    1) loads audio, text pairs
+    2) normalizes text and converts them to sequences of integers
+    3) computes spectrograms from audio files.
+    """
+
+    def __init__(self, audiopaths_and_text, hparams):
+        self.audiopaths_and_text = load_filepaths_and_text(audiopaths_and_text)
+        self.max_wav_value = hparams.max_wav_value
+        self.sampling_rate = hparams.sampling_rate
+        self.filter_length = hparams.filter_length
+        self.hop_length = hparams.hop_length
+        self.win_length = hparams.win_length
+        self.sampling_rate = hparams.sampling_rate
+        self.min_text_len = getattr(hparams, "min_text_len", 1)
+        self.max_text_len = getattr(hparams, "max_text_len", 5000)
+        self._filter()
+
+    def _filter(self):
+        """
+        Filter text & store spec lengths
+        """
+        # Store spectrogram lengths for Bucketing
+        # wav_length ~= file_size / (wav_channels * Bytes per dim) = file_size / (1 * 2)
+        # spec_length = wav_length // hop_length
+        audiopaths_and_text_new = []
+        lengths = []
+        for audiopath, text, pitch, pitchf, dv in self.audiopaths_and_text:
+            if self.min_text_len <= len(text) and len(text) <= self.max_text_len:
+                audiopaths_and_text_new.append([audiopath, text, pitch, pitchf, dv])
+                lengths.append(os.path.getsize(audiopath) // (3 * self.hop_length))
+        self.audiopaths_and_text = audiopaths_and_text_new
+        self.lengths = lengths
+
+    def get_sid(self, sid):
+        sid = torch.LongTensor([int(sid)])
+        return sid
+
+    def get_audio_text_pair(self, audiopath_and_text):
+        # separate filename and text
+        file = audiopath_and_text[0]
+        phone = audiopath_and_text[1]
+        pitch = audiopath_and_text[2]
+        pitchf = audiopath_and_text[3]
+        dv = audiopath_and_text[4]
+
+        phone, pitch, pitchf = self.get_labels(phone, pitch, pitchf)
+        spec, wav = self.get_audio(file)
+        dv = self.get_sid(dv)
+
+        len_phone = phone.size()[0]
+        len_spec = spec.size()[-1]
+        # print(123,phone.shape,pitch.shape,spec.shape)
+        if len_phone != len_spec:
+            len_min = min(len_phone, len_spec)
+            # amor
+            len_wav = len_min * self.hop_length
+
+            spec = spec[:, :len_min]
+            wav = wav[:, :len_wav]
+
+            phone = phone[:len_min, :]
+            pitch = pitch[:len_min]
+            pitchf = pitchf[:len_min]
+
+        return (spec, wav, phone, pitch, pitchf, dv)
+
+    def get_labels(self, phone, pitch, pitchf):
+        phone = np.load(phone)
+        phone = np.repeat(phone, 2, axis=0)
+        pitch = np.load(pitch)
+        pitchf = np.load(pitchf)
+        n_num = min(phone.shape[0], 900)  # DistributedBucketSampler
+        # print(234,phone.shape,pitch.shape)
+        phone = phone[:n_num, :]
+        pitch = pitch[:n_num]
+        pitchf = pitchf[:n_num]
+        phone = torch.FloatTensor(phone)
+        pitch = torch.LongTensor(pitch)
+        pitchf = torch.FloatTensor(pitchf)
+        return phone, pitch, pitchf
+
+    def get_audio(self, filename):
+        audio, sampling_rate = load_wav_to_torch(filename)
+        if sampling_rate != self.sampling_rate:
+            raise ValueError(
+                "{} SR doesn't match target {} SR".format(
+                    sampling_rate, self.sampling_rate
+                )
+            )
+        audio_norm = audio
+        #        audio_norm = audio / self.max_wav_value
+        #        audio_norm = audio / np.abs(audio).max()
+
+        audio_norm = audio_norm.unsqueeze(0)
+        spec_filename = filename.replace(".wav", ".spec.pt")
+        if os.path.exists(spec_filename):
+            try:
+                spec = torch.load(spec_filename)
+            except:
+                print(spec_filename, traceback.format_exc())
+                spec = spectrogram_torch(
+                    audio_norm,
+                    self.filter_length,
+                    self.sampling_rate,
+                    self.hop_length,
+                    self.win_length,
+                    center=False,
+                )
+                spec = torch.squeeze(spec, 0)
+                torch.save(spec, spec_filename, _use_new_zipfile_serialization=False)
+        else:
+            spec = spectrogram_torch(
+                audio_norm,
+                self.filter_length,
+                self.sampling_rate,
+                self.hop_length,
+                self.win_length,
+                center=False,
+            )
+            spec = torch.squeeze(spec, 0)
+            torch.save(spec, spec_filename, _use_new_zipfile_serialization=False)
+        return spec, audio_norm
+
+    def __getitem__(self, index):
+        return self.get_audio_text_pair(self.audiopaths_and_text[index])
+
+    def __len__(self):
+        return len(self.audiopaths_and_text)
+
+
+class TextAudioCollateMultiNSFsid:
+    """Zero-pads model inputs and targets"""
+
+    def __init__(self, return_ids=False):
+        self.return_ids = return_ids
+
+    def __call__(self, batch):
+        """Collate's training batch from normalized text and aduio
+        PARAMS
+        ------
+        batch: [text_normalized, spec_normalized, wav_normalized]
+        """
+        # Right zero-pad all one-hot text sequences to max input length
+        _, ids_sorted_decreasing = torch.sort(
+            torch.LongTensor([x[0].size(1) for x in batch]), dim=0, descending=True
+        )
+
+        max_spec_len = max([x[0].size(1) for x in batch])
+        max_wave_len = max([x[1].size(1) for x in batch])
+        spec_lengths = torch.LongTensor(len(batch))
+        wave_lengths = torch.LongTensor(len(batch))
+        spec_padded = torch.FloatTensor(len(batch), batch[0][0].size(0), max_spec_len)
+        wave_padded = torch.FloatTensor(len(batch), 1, max_wave_len)
+        spec_padded.zero_()
+        wave_padded.zero_()
+
+        max_phone_len = max([x[2].size(0) for x in batch])
+        phone_lengths = torch.LongTensor(len(batch))
+        phone_padded = torch.FloatTensor(
+            len(batch), max_phone_len, batch[0][2].shape[1]
+        )  # (spec, wav, phone, pitch)
+        pitch_padded = torch.LongTensor(len(batch), max_phone_len)
+        pitchf_padded = torch.FloatTensor(len(batch), max_phone_len)
+        phone_padded.zero_()
+        pitch_padded.zero_()
+        pitchf_padded.zero_()
+        # dv = torch.FloatTensor(len(batch), 256)#gin=256
+        sid = torch.LongTensor(len(batch))
+
+        for i in range(len(ids_sorted_decreasing)):
+            row = batch[ids_sorted_decreasing[i]]
+
+            spec = row[0]
+            spec_padded[i, :, : spec.size(1)] = spec
+            spec_lengths[i] = spec.size(1)
+
+            wave = row[1]
+            wave_padded[i, :, : wave.size(1)] = wave
+            wave_lengths[i] = wave.size(1)
+
+            phone = row[2]
+            phone_padded[i, : phone.size(0), :] = phone
+            phone_lengths[i] = phone.size(0)
+
+            pitch = row[3]
+            pitch_padded[i, : pitch.size(0)] = pitch
+            pitchf = row[4]
+            pitchf_padded[i, : pitchf.size(0)] = pitchf
+
+            # dv[i] = row[5]
+            sid[i] = row[5]
+
+        return (
+            phone_padded,
+            phone_lengths,
+            pitch_padded,
+            pitchf_padded,
+            spec_padded,
+            spec_lengths,
+            wave_padded,
+            wave_lengths,
+            # dv
+            sid,
+        )
+
+
+class TextAudioLoader(torch.utils.data.Dataset):
+    """
+    1) loads audio, text pairs
+    2) normalizes text and converts them to sequences of integers
+    3) computes spectrograms from audio files.
+    """
+
+    def __init__(self, audiopaths_and_text, hparams):
+        self.audiopaths_and_text = load_filepaths_and_text(audiopaths_and_text)
+        self.max_wav_value = hparams.max_wav_value
+        self.sampling_rate = hparams.sampling_rate
+        self.filter_length = hparams.filter_length
+        self.hop_length = hparams.hop_length
+        self.win_length = hparams.win_length
+        self.sampling_rate = hparams.sampling_rate
+        self.min_text_len = getattr(hparams, "min_text_len", 1)
+        self.max_text_len = getattr(hparams, "max_text_len", 5000)
+        self._filter()
+
+    def _filter(self):
+        """
+        Filter text & store spec lengths
+        """
+        # Store spectrogram lengths for Bucketing
+        # wav_length ~= file_size / (wav_channels * Bytes per dim) = file_size / (1 * 2)
+        # spec_length = wav_length // hop_length
+        audiopaths_and_text_new = []
+        lengths = []
+        for audiopath, text, dv in self.audiopaths_and_text:
+            if self.min_text_len <= len(text) and len(text) <= self.max_text_len:
+                audiopaths_and_text_new.append([audiopath, text, dv])
+                lengths.append(os.path.getsize(audiopath) // (3 * self.hop_length))
+        self.audiopaths_and_text = audiopaths_and_text_new
+        self.lengths = lengths
+
+    def get_sid(self, sid):
+        sid = torch.LongTensor([int(sid)])
+        return sid
+
+    def get_audio_text_pair(self, audiopath_and_text):
+        # separate filename and text
+        file = audiopath_and_text[0]
+        phone = audiopath_and_text[1]
+        dv = audiopath_and_text[2]
+
+        phone = self.get_labels(phone)
+        spec, wav = self.get_audio(file)
+        dv = self.get_sid(dv)
+
+        len_phone = phone.size()[0]
+        len_spec = spec.size()[-1]
+        if len_phone != len_spec:
+            len_min = min(len_phone, len_spec)
+            len_wav = len_min * self.hop_length
+            spec = spec[:, :len_min]
+            wav = wav[:, :len_wav]
+            phone = phone[:len_min, :]
+        return (spec, wav, phone, dv)
+
+    def get_labels(self, phone):
+        phone = np.load(phone)
+        phone = np.repeat(phone, 2, axis=0)
+        n_num = min(phone.shape[0], 900)  # DistributedBucketSampler
+        phone = phone[:n_num, :]
+        phone = torch.FloatTensor(phone)
+        return phone
+
+    def get_audio(self, filename):
+        audio, sampling_rate = load_wav_to_torch(filename)
+        if sampling_rate != self.sampling_rate:
+            raise ValueError(
+                "{} SR doesn't match target {} SR".format(
+                    sampling_rate, self.sampling_rate
+                )
+            )
+        audio_norm = audio
+        #        audio_norm = audio / self.max_wav_value
+        #        audio_norm = audio / np.abs(audio).max()
+
+        audio_norm = audio_norm.unsqueeze(0)
+        spec_filename = filename.replace(".wav", ".spec.pt")
+        if os.path.exists(spec_filename):
+            try:
+                spec = torch.load(spec_filename)
+            except:
+                print(spec_filename, traceback.format_exc())
+                spec = spectrogram_torch(
+                    audio_norm,
+                    self.filter_length,
+                    self.sampling_rate,
+                    self.hop_length,
+                    self.win_length,
+                    center=False,
+                )
+                spec = torch.squeeze(spec, 0)
+                torch.save(spec, spec_filename, _use_new_zipfile_serialization=False)
+        else:
+            spec = spectrogram_torch(
+                audio_norm,
+                self.filter_length,
+                self.sampling_rate,
+                self.hop_length,
+                self.win_length,
+                center=False,
+            )
+            spec = torch.squeeze(spec, 0)
+            torch.save(spec, spec_filename, _use_new_zipfile_serialization=False)
+        return spec, audio_norm
+
+    def __getitem__(self, index):
+        return self.get_audio_text_pair(self.audiopaths_and_text[index])
+
+    def __len__(self):
+        return len(self.audiopaths_and_text)
+
+
+class TextAudioCollate:
+    """Zero-pads model inputs and targets"""
+
+    def __init__(self, return_ids=False):
+        self.return_ids = return_ids
+
+    def __call__(self, batch):
+        """Collate's training batch from normalized text and aduio
+        PARAMS
+        ------
+        batch: [text_normalized, spec_normalized, wav_normalized]
+        """
+        # Right zero-pad all one-hot text sequences to max input length
+        _, ids_sorted_decreasing = torch.sort(
+            torch.LongTensor([x[0].size(1) for x in batch]), dim=0, descending=True
+        )
+
+        max_spec_len = max([x[0].size(1) for x in batch])
+        max_wave_len = max([x[1].size(1) for x in batch])
+        spec_lengths = torch.LongTensor(len(batch))
+        wave_lengths = torch.LongTensor(len(batch))
+        spec_padded = torch.FloatTensor(len(batch), batch[0][0].size(0), max_spec_len)
+        wave_padded = torch.FloatTensor(len(batch), 1, max_wave_len)
+        spec_padded.zero_()
+        wave_padded.zero_()
+
+        max_phone_len = max([x[2].size(0) for x in batch])
+        phone_lengths = torch.LongTensor(len(batch))
+        phone_padded = torch.FloatTensor(
+            len(batch), max_phone_len, batch[0][2].shape[1]
+        )
+        phone_padded.zero_()
+        sid = torch.LongTensor(len(batch))
+
+        for i in range(len(ids_sorted_decreasing)):
+            row = batch[ids_sorted_decreasing[i]]
+
+            spec = row[0]
+            spec_padded[i, :, : spec.size(1)] = spec
+            spec_lengths[i] = spec.size(1)
+
+            wave = row[1]
+            wave_padded[i, :, : wave.size(1)] = wave
+            wave_lengths[i] = wave.size(1)
+
+            phone = row[2]
+            phone_padded[i, : phone.size(0), :] = phone
+            phone_lengths[i] = phone.size(0)
+
+            sid[i] = row[3]
+
+        return (
+            phone_padded,
+            phone_lengths,
+            spec_padded,
+            spec_lengths,
+            wave_padded,
+            wave_lengths,
+            sid,
+        )
+
+
+class DistributedBucketSampler(torch.utils.data.distributed.DistributedSampler):
+    """
+    Maintain similar input lengths in a batch.
+    Length groups are specified by boundaries.
+    Ex) boundaries = [b1, b2, b3] -> any batch is included either {x | b1 < length(x) <=b2} or {x | b2 < length(x) <= b3}.
+
+    It removes samples which are not included in the boundaries.
+    Ex) boundaries = [b1, b2, b3] -> any x s.t. length(x) <= b1 or length(x) > b3 are discarded.
+    """
+
+    def __init__(
+        self,
+        dataset,
+        batch_size,
+        boundaries,
+        num_replicas=None,
+        rank=None,
+        shuffle=True,
+    ):
+        super().__init__(dataset, num_replicas=num_replicas, rank=rank, shuffle=shuffle)
+        self.lengths = dataset.lengths
+        self.batch_size = batch_size
+        self.boundaries = boundaries
+
+        self.buckets, self.num_samples_per_bucket = self._create_buckets()
+        self.total_size = sum(self.num_samples_per_bucket)
+        self.num_samples = self.total_size // self.num_replicas
+
+    def _create_buckets(self):
+        buckets = [[] for _ in range(len(self.boundaries) - 1)]
+        for i in range(len(self.lengths)):
+            length = self.lengths[i]
+            idx_bucket = self._bisect(length)
+            if idx_bucket != -1:
+                buckets[idx_bucket].append(i)
+
+        for i in range(len(buckets) - 1, -1, -1):  #
+            if len(buckets[i]) == 0:
+                buckets.pop(i)
+                self.boundaries.pop(i + 1)
+
+        num_samples_per_bucket = []
+        for i in range(len(buckets)):
+            len_bucket = len(buckets[i])
+            total_batch_size = self.num_replicas * self.batch_size
+            rem = (
+                total_batch_size - (len_bucket % total_batch_size)
+            ) % total_batch_size
+            num_samples_per_bucket.append(len_bucket + rem)
+        return buckets, num_samples_per_bucket
+
+    def __iter__(self):
+        # deterministically shuffle based on epoch
+        g = torch.Generator()
+        g.manual_seed(self.epoch)
+
+        indices = []
+        if self.shuffle:
+            for bucket in self.buckets:
+                indices.append(torch.randperm(len(bucket), generator=g).tolist())
+        else:
+            for bucket in self.buckets:
+                indices.append(list(range(len(bucket))))
+
+        batches = []
+        for i in range(len(self.buckets)):
+            bucket = self.buckets[i]
+            len_bucket = len(bucket)
+            ids_bucket = indices[i]
+            num_samples_bucket = self.num_samples_per_bucket[i]
+
+            # add extra samples to make it evenly divisible
+            rem = num_samples_bucket - len_bucket
+            ids_bucket = (
+                ids_bucket
+                + ids_bucket * (rem // len_bucket)
+                + ids_bucket[: (rem % len_bucket)]
+            )
+
+            # subsample
+            ids_bucket = ids_bucket[self.rank :: self.num_replicas]
+
+            # batching
+            for j in range(len(ids_bucket) // self.batch_size):
+                batch = [
+                    bucket[idx]
+                    for idx in ids_bucket[
+                        j * self.batch_size : (j + 1) * self.batch_size
+                    ]
+                ]
+                batches.append(batch)
+
+        if self.shuffle:
+            batch_ids = torch.randperm(len(batches), generator=g).tolist()
+            batches = [batches[i] for i in batch_ids]
+        self.batches = batches
+
+        assert len(self.batches) * self.batch_size == self.num_samples
+        return iter(self.batches)
+
+    def _bisect(self, x, lo=0, hi=None):
+        if hi is None:
+            hi = len(self.boundaries) - 1
+
+        if hi > lo:
+            mid = (hi + lo) // 2
+            if self.boundaries[mid] < x and x <= self.boundaries[mid + 1]:
+                return mid
+            elif x <= self.boundaries[mid]:
+                return self._bisect(x, lo, mid)
+            else:
+                return self._bisect(x, mid + 1, hi)
+        else:
+            return -1
+
+    def __len__(self):
+        return self.num_samples // self.batch_size
diff --git a/train/losses.py b/train/losses.py
new file mode 100644
index 0000000000000000000000000000000000000000..b89038f14d06d7fae43628183e9ffb465e4edafd
--- /dev/null
+++ b/train/losses.py
@@ -0,0 +1,59 @@
+import torch
+from torch.nn import functional as F
+
+
+def feature_loss(fmap_r, fmap_g):
+    loss = 0
+    for dr, dg in zip(fmap_r, fmap_g):
+        for rl, gl in zip(dr, dg):
+            rl = rl.float().detach()
+            gl = gl.float()
+            loss += torch.mean(torch.abs(rl - gl))
+
+    return loss * 2
+
+
+def discriminator_loss(disc_real_outputs, disc_generated_outputs):
+    loss = 0
+    r_losses = []
+    g_losses = []
+    for dr, dg in zip(disc_real_outputs, disc_generated_outputs):
+        dr = dr.float()
+        dg = dg.float()
+        r_loss = torch.mean((1 - dr) ** 2)
+        g_loss = torch.mean(dg**2)
+        loss += r_loss + g_loss
+        r_losses.append(r_loss.item())
+        g_losses.append(g_loss.item())
+
+    return loss, r_losses, g_losses
+
+
+def generator_loss(disc_outputs):
+    loss = 0
+    gen_losses = []
+    for dg in disc_outputs:
+        dg = dg.float()
+        l = torch.mean((1 - dg) ** 2)
+        gen_losses.append(l)
+        loss += l
+
+    return loss, gen_losses
+
+
+def kl_loss(z_p, logs_q, m_p, logs_p, z_mask):
+    """
+    z_p, logs_q: [b, h, t_t]
+    m_p, logs_p: [b, h, t_t]
+    """
+    z_p = z_p.float()
+    logs_q = logs_q.float()
+    m_p = m_p.float()
+    logs_p = logs_p.float()
+    z_mask = z_mask.float()
+
+    kl = logs_p - logs_q - 0.5
+    kl += 0.5 * ((z_p - m_p) ** 2) * torch.exp(-2.0 * logs_p)
+    kl = torch.sum(kl * z_mask)
+    l = kl / torch.sum(z_mask)
+    return l
diff --git a/train/mel_processing.py b/train/mel_processing.py
new file mode 100644
index 0000000000000000000000000000000000000000..1c871ab6b838b174407d163c201df899cc3e2b14
--- /dev/null
+++ b/train/mel_processing.py
@@ -0,0 +1,130 @@
+import torch
+import torch.utils.data
+from librosa.filters import mel as librosa_mel_fn
+
+
+MAX_WAV_VALUE = 32768.0
+
+
+def dynamic_range_compression_torch(x, C=1, clip_val=1e-5):
+    """
+    PARAMS
+    ------
+    C: compression factor
+    """
+    return torch.log(torch.clamp(x, min=clip_val) * C)
+
+
+def dynamic_range_decompression_torch(x, C=1):
+    """
+    PARAMS
+    ------
+    C: compression factor used to compress
+    """
+    return torch.exp(x) / C
+
+
+def spectral_normalize_torch(magnitudes):
+    return dynamic_range_compression_torch(magnitudes)
+
+
+def spectral_de_normalize_torch(magnitudes):
+    return dynamic_range_decompression_torch(magnitudes)
+
+
+# Reusable banks
+mel_basis = {}
+hann_window = {}
+
+
+def spectrogram_torch(y, n_fft, sampling_rate, hop_size, win_size, center=False):
+    """Convert waveform into Linear-frequency Linear-amplitude spectrogram.
+
+    Args:
+        y             :: (B, T) - Audio waveforms
+        n_fft
+        sampling_rate
+        hop_size
+        win_size
+        center
+    Returns:
+        :: (B, Freq, Frame) - Linear-frequency Linear-amplitude spectrogram
+    """
+    # Validation
+    if torch.min(y) < -1.07:
+        print("min value is ", torch.min(y))
+    if torch.max(y) > 1.07:
+        print("max value is ", torch.max(y))
+
+    # Window - Cache if needed
+    global hann_window
+    dtype_device = str(y.dtype) + "_" + str(y.device)
+    wnsize_dtype_device = str(win_size) + "_" + dtype_device
+    if wnsize_dtype_device not in hann_window:
+        hann_window[wnsize_dtype_device] = torch.hann_window(win_size).to(
+            dtype=y.dtype, device=y.device
+        )
+
+    # Padding
+    y = torch.nn.functional.pad(
+        y.unsqueeze(1),
+        (int((n_fft - hop_size) / 2), int((n_fft - hop_size) / 2)),
+        mode="reflect",
+    )
+    y = y.squeeze(1)
+
+    # Complex Spectrogram :: (B, T) -> (B, Freq, Frame, RealComplex=2)
+    spec = torch.stft(
+        y,
+        n_fft,
+        hop_length=hop_size,
+        win_length=win_size,
+        window=hann_window[wnsize_dtype_device],
+        center=center,
+        pad_mode="reflect",
+        normalized=False,
+        onesided=True,
+        return_complex=False,
+    )
+
+    # Linear-frequency Linear-amplitude spectrogram :: (B, Freq, Frame, RealComplex=2) -> (B, Freq, Frame)
+    spec = torch.sqrt(spec.pow(2).sum(-1) + 1e-6)
+    return spec
+
+
+def spec_to_mel_torch(spec, n_fft, num_mels, sampling_rate, fmin, fmax):
+    # MelBasis - Cache if needed
+    global mel_basis
+    dtype_device = str(spec.dtype) + "_" + str(spec.device)
+    fmax_dtype_device = str(fmax) + "_" + dtype_device
+    if fmax_dtype_device not in mel_basis:
+        mel = librosa_mel_fn(
+            sr=sampling_rate, n_fft=n_fft, n_mels=num_mels, fmin=fmin, fmax=fmax
+        )
+        mel_basis[fmax_dtype_device] = torch.from_numpy(mel).to(
+            dtype=spec.dtype, device=spec.device
+        )
+
+    # Mel-frequency Log-amplitude spectrogram :: (B, Freq=num_mels, Frame)
+    melspec = torch.matmul(mel_basis[fmax_dtype_device], spec)
+    melspec = spectral_normalize_torch(melspec)
+    return melspec
+
+
+def mel_spectrogram_torch(
+    y, n_fft, num_mels, sampling_rate, hop_size, win_size, fmin, fmax, center=False
+):
+    """Convert waveform into Mel-frequency Log-amplitude spectrogram.
+
+    Args:
+        y       :: (B, T)           - Waveforms
+    Returns:
+        melspec :: (B, Freq, Frame) - Mel-frequency Log-amplitude spectrogram
+    """
+    # Linear-frequency Linear-amplitude spectrogram :: (B, T) -> (B, Freq, Frame)
+    spec = spectrogram_torch(y, n_fft, sampling_rate, hop_size, win_size, center)
+
+    # Mel-frequency Log-amplitude spectrogram :: (B, Freq, Frame) -> (B, Freq=num_mels, Frame)
+    melspec = spec_to_mel_torch(spec, n_fft, num_mels, sampling_rate, fmin, fmax)
+
+    return melspec
diff --git a/train/process_ckpt.py b/train/process_ckpt.py
new file mode 100644
index 0000000000000000000000000000000000000000..e3c3dba6df4b4f71a4d0865cdc96241d17da8781
--- /dev/null
+++ b/train/process_ckpt.py
@@ -0,0 +1,259 @@
+import torch, traceback, os, pdb, sys
+
+now_dir = os.getcwd()
+sys.path.append(now_dir)
+from collections import OrderedDict
+from i18n import I18nAuto
+
+i18n = I18nAuto()
+
+
+def savee(ckpt, sr, if_f0, name, epoch, version, hps):
+    try:
+        opt = OrderedDict()
+        opt["weight"] = {}
+        for key in ckpt.keys():
+            if "enc_q" in key:
+                continue
+            opt["weight"][key] = ckpt[key].half()
+        opt["config"] = [
+            hps.data.filter_length // 2 + 1,
+            32,
+            hps.model.inter_channels,
+            hps.model.hidden_channels,
+            hps.model.filter_channels,
+            hps.model.n_heads,
+            hps.model.n_layers,
+            hps.model.kernel_size,
+            hps.model.p_dropout,
+            hps.model.resblock,
+            hps.model.resblock_kernel_sizes,
+            hps.model.resblock_dilation_sizes,
+            hps.model.upsample_rates,
+            hps.model.upsample_initial_channel,
+            hps.model.upsample_kernel_sizes,
+            hps.model.spk_embed_dim,
+            hps.model.gin_channels,
+            hps.data.sampling_rate,
+        ]
+        opt["info"] = "%sepoch" % epoch
+        opt["sr"] = sr
+        opt["f0"] = if_f0
+        opt["version"] = version
+        torch.save(opt, "weights/%s.pth" % name)
+        return "Success."
+    except:
+        return traceback.format_exc()
+
+
+def show_info(path):
+    try:
+        a = torch.load(path, map_location="cpu")
+        return "Epochs: %s\nSample rate: %s\nPitch guidance: %s\nRVC Version: %s" % (
+            a.get("info", "None"),
+            a.get("sr", "None"),
+            a.get("f0", "None"),
+            a.get("version", "None"),
+        )
+    except:
+        return traceback.format_exc()
+
+
+def extract_small_model(path, name, sr, if_f0, info, version):
+    try:
+        ckpt = torch.load(path, map_location="cpu")
+        if "model" in ckpt:
+            ckpt = ckpt["model"]
+        opt = OrderedDict()
+        opt["weight"] = {}
+        for key in ckpt.keys():
+            if "enc_q" in key:
+                continue
+            opt["weight"][key] = ckpt[key].half()
+        if sr == "40k":
+            opt["config"] = [
+                1025,
+                32,
+                192,
+                192,
+                768,
+                2,
+                6,
+                3,
+                0,
+                "1",
+                [3, 7, 11],
+                [[1, 3, 5], [1, 3, 5], [1, 3, 5]],
+                [10, 10, 2, 2],
+                512,
+                [16, 16, 4, 4],
+                109,
+                256,
+                40000,
+            ]
+        elif sr == "48k":
+            if version == "v1":
+                opt["config"] = [
+                    1025,
+                    32,
+                    192,
+                    192,
+                    768,
+                    2,
+                    6,
+                    3,
+                    0,
+                    "1",
+                    [3, 7, 11],
+                    [[1, 3, 5], [1, 3, 5], [1, 3, 5]],
+                    [10, 6, 2, 2, 2],
+                    512,
+                    [16, 16, 4, 4, 4],
+                    109,
+                    256,
+                    48000,
+                ]
+            else:
+                opt["config"] = [
+                    1025,
+                    32,
+                    192,
+                    192,
+                    768,
+                    2,
+                    6,
+                    3,
+                    0,
+                    "1",
+                    [3, 7, 11],
+                    [[1, 3, 5], [1, 3, 5], [1, 3, 5]],
+                    [12, 10, 2, 2],
+                    512,
+                    [24, 20, 4, 4],
+                    109,
+                    256,
+                    48000,
+                ]
+        elif sr == "32k":
+            if version == "v1":
+                opt["config"] = [
+                    513,
+                    32,
+                    192,
+                    192,
+                    768,
+                    2,
+                    6,
+                    3,
+                    0,
+                    "1",
+                    [3, 7, 11],
+                    [[1, 3, 5], [1, 3, 5], [1, 3, 5]],
+                    [10, 4, 2, 2, 2],
+                    512,
+                    [16, 16, 4, 4, 4],
+                    109,
+                    256,
+                    32000,
+                ]
+            else:
+                opt["config"] = [
+                    513,
+                    32,
+                    192,
+                    192,
+                    768,
+                    2,
+                    6,
+                    3,
+                    0,
+                    "1",
+                    [3, 7, 11],
+                    [[1, 3, 5], [1, 3, 5], [1, 3, 5]],
+                    [10, 8, 2, 2],
+                    512,
+                    [20, 16, 4, 4],
+                    109,
+                    256,
+                    32000,
+                ]
+        if info == "":
+            info = "Extracted model."
+        opt["info"] = info
+        opt["version"] = version
+        opt["sr"] = sr
+        opt["f0"] = int(if_f0)
+        torch.save(opt, "weights/%s.pth" % name)
+        return "Success."
+    except:
+        return traceback.format_exc()
+
+
+def change_info(path, info, name):
+    try:
+        ckpt = torch.load(path, map_location="cpu")
+        ckpt["info"] = info
+        if name == "":
+            name = os.path.basename(path)
+        torch.save(ckpt, "weights/%s" % name)
+        return "Success."
+    except:
+        return traceback.format_exc()
+
+
+def merge(path1, path2, alpha1, sr, f0, info, name, version):
+    try:
+
+        def extract(ckpt):
+            a = ckpt["model"]
+            opt = OrderedDict()
+            opt["weight"] = {}
+            for key in a.keys():
+                if "enc_q" in key:
+                    continue
+                opt["weight"][key] = a[key]
+            return opt
+
+        ckpt1 = torch.load(path1, map_location="cpu")
+        ckpt2 = torch.load(path2, map_location="cpu")
+        cfg = ckpt1["config"]
+        if "model" in ckpt1:
+            ckpt1 = extract(ckpt1)
+        else:
+            ckpt1 = ckpt1["weight"]
+        if "model" in ckpt2:
+            ckpt2 = extract(ckpt2)
+        else:
+            ckpt2 = ckpt2["weight"]
+        if sorted(list(ckpt1.keys())) != sorted(list(ckpt2.keys())):
+            return "Fail to merge the models. The model architectures are not the same."
+        opt = OrderedDict()
+        opt["weight"] = {}
+        for key in ckpt1.keys():
+            # try:
+            if key == "emb_g.weight" and ckpt1[key].shape != ckpt2[key].shape:
+                min_shape0 = min(ckpt1[key].shape[0], ckpt2[key].shape[0])
+                opt["weight"][key] = (
+                    alpha1 * (ckpt1[key][:min_shape0].float())
+                    + (1 - alpha1) * (ckpt2[key][:min_shape0].float())
+                ).half()
+            else:
+                opt["weight"][key] = (
+                    alpha1 * (ckpt1[key].float()) + (1 - alpha1) * (ckpt2[key].float())
+                ).half()
+        # except:
+        #     pdb.set_trace()
+        opt["config"] = cfg
+        """
+        if(sr=="40k"):opt["config"] = [1025, 32, 192, 192, 768, 2, 6, 3, 0, "1", [3, 7, 11], [[1, 3, 5], [1, 3, 5], [1, 3, 5]], [10, 10, 2, 2], 512, [16, 16, 4, 4,4], 109, 256, 40000]
+        elif(sr=="48k"):opt["config"] = [1025, 32, 192, 192, 768, 2, 6, 3, 0, "1", [3, 7, 11], [[1, 3, 5], [1, 3, 5], [1, 3, 5]], [10,6,2,2,2], 512, [16, 16, 4, 4], 109, 256, 48000]
+        elif(sr=="32k"):opt["config"] = [513, 32, 192, 192, 768, 2, 6, 3, 0, "1", [3, 7, 11], [[1, 3, 5], [1, 3, 5], [1, 3, 5]], [10, 4, 2, 2, 2], 512, [16, 16, 4, 4,4], 109, 256, 32000]
+        """
+        opt["sr"] = sr
+        opt["f0"] = 1 if f0 else 0
+        opt["version"] = version
+        opt["info"] = info
+        torch.save(opt, "weights/%s.pth" % name)
+        return "Success."
+    except:
+        return traceback.format_exc()
diff --git a/train/utils.py b/train/utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..aae833b08acc24b848aa70114fd9b7aad8b1a6ad
--- /dev/null
+++ b/train/utils.py
@@ -0,0 +1,500 @@
+import os, traceback
+import glob
+import sys
+import argparse
+import logging
+import json
+import subprocess
+import numpy as np
+from scipy.io.wavfile import read
+import torch
+
+MATPLOTLIB_FLAG = False
+
+logging.basicConfig(stream=sys.stdout, level=logging.DEBUG)
+logger = logging
+
+
+def load_checkpoint_d(checkpoint_path, combd, sbd, optimizer=None, load_opt=1):
+    assert os.path.isfile(checkpoint_path)
+    checkpoint_dict = torch.load(checkpoint_path, map_location="cpu")
+
+    ##################
+    def go(model, bkey):
+        saved_state_dict = checkpoint_dict[bkey]
+        if hasattr(model, "module"):
+            state_dict = model.module.state_dict()
+        else:
+            state_dict = model.state_dict()
+        new_state_dict = {}
+        for k, v in state_dict.items():  # 模型需要的shape
+            try:
+                new_state_dict[k] = saved_state_dict[k]
+                if saved_state_dict[k].shape != state_dict[k].shape:
+                    print(
+                        "shape-%s-mismatch|need-%s|get-%s"
+                        % (k, state_dict[k].shape, saved_state_dict[k].shape)
+                    )  #
+                    raise KeyError
+            except:
+                # logger.info(traceback.format_exc())
+                logger.info("%s is not in the checkpoint" % k)  # pretrain缺失的
+                new_state_dict[k] = v  # 模型自带的随机值
+        if hasattr(model, "module"):
+            model.module.load_state_dict(new_state_dict, strict=False)
+        else:
+            model.load_state_dict(new_state_dict, strict=False)
+
+    go(combd, "combd")
+    go(sbd, "sbd")
+    #############
+    logger.info("Loaded model weights")
+
+    iteration = checkpoint_dict["iteration"]
+    learning_rate = checkpoint_dict["learning_rate"]
+    if (
+        optimizer is not None and load_opt == 1
+    ):  ###加载不了，如果是空的的话，重新初始化，可能还会影响lr时间表的更新，因此在train文件最外围catch
+        #   try:
+        optimizer.load_state_dict(checkpoint_dict["optimizer"])
+    #   except:
+    #     traceback.print_exc()
+    logger.info("Loaded checkpoint '{}' (epoch {})".format(checkpoint_path, iteration))
+    return model, optimizer, learning_rate, iteration
+
+
+# def load_checkpoint(checkpoint_path, model, optimizer=None):
+#   assert os.path.isfile(checkpoint_path)
+#   checkpoint_dict = torch.load(checkpoint_path, map_location='cpu')
+#   iteration = checkpoint_dict['iteration']
+#   learning_rate = checkpoint_dict['learning_rate']
+#   if optimizer is not None:
+#     optimizer.load_state_dict(checkpoint_dict['optimizer'])
+#   # print(1111)
+#   saved_state_dict = checkpoint_dict['model']
+#   # print(1111)
+#
+#   if hasattr(model, 'module'):
+#     state_dict = model.module.state_dict()
+#   else:
+#     state_dict = model.state_dict()
+#   new_state_dict= {}
+#   for k, v in state_dict.items():
+#     try:
+#       new_state_dict[k] = saved_state_dict[k]
+#     except:
+#       logger.info("%s is not in the checkpoint" % k)
+#       new_state_dict[k] = v
+#   if hasattr(model, 'module'):
+#     model.module.load_state_dict(new_state_dict)
+#   else:
+#     model.load_state_dict(new_state_dict)
+#   logger.info("Loaded checkpoint '{}' (epoch {})" .format(
+#     checkpoint_path, iteration))
+#   return model, optimizer, learning_rate, iteration
+def load_checkpoint(checkpoint_path, model, optimizer=None, load_opt=1):
+    assert os.path.isfile(checkpoint_path)
+    checkpoint_dict = torch.load(checkpoint_path, map_location="cpu")
+
+    saved_state_dict = checkpoint_dict["model"]
+    if hasattr(model, "module"):
+        state_dict = model.module.state_dict()
+    else:
+        state_dict = model.state_dict()
+    new_state_dict = {}
+    for k, v in state_dict.items():  # 模型需要的shape
+        try:
+            new_state_dict[k] = saved_state_dict[k]
+            if saved_state_dict[k].shape != state_dict[k].shape:
+                print(
+                    "shape-%s-mismatch|need-%s|get-%s"
+                    % (k, state_dict[k].shape, saved_state_dict[k].shape)
+                )  #
+                raise KeyError
+        except:
+            # logger.info(traceback.format_exc())
+            logger.info("%s is not in the checkpoint" % k)  # pretrain缺失的
+            new_state_dict[k] = v  # 模型自带的随机值
+    if hasattr(model, "module"):
+        model.module.load_state_dict(new_state_dict, strict=False)
+    else:
+        model.load_state_dict(new_state_dict, strict=False)
+    logger.info("Loaded model weights")
+
+    iteration = checkpoint_dict["iteration"]
+    learning_rate = checkpoint_dict["learning_rate"]
+    if (
+        optimizer is not None and load_opt == 1
+    ):  ###加载不了，如果是空的的话，重新初始化，可能还会影响lr时间表的更新，因此在train文件最外围catch
+        #   try:
+        optimizer.load_state_dict(checkpoint_dict["optimizer"])
+    #   except:
+    #     traceback.print_exc()
+    logger.info("Loaded checkpoint '{}' (epoch {})".format(checkpoint_path, iteration))
+    return model, optimizer, learning_rate, iteration
+
+
+def save_checkpoint(model, optimizer, learning_rate, iteration, checkpoint_path):
+    logger.info(
+        "Saving model and optimizer state at epoch {} to {}".format(
+            iteration, checkpoint_path
+        )
+    )
+    if hasattr(model, "module"):
+        state_dict = model.module.state_dict()
+    else:
+        state_dict = model.state_dict()
+    torch.save(
+        {
+            "model": state_dict,
+            "iteration": iteration,
+            "optimizer": optimizer.state_dict(),
+            "learning_rate": learning_rate,
+        },
+        checkpoint_path,
+    )
+
+
+def save_checkpoint_d(combd, sbd, optimizer, learning_rate, iteration, checkpoint_path):
+    logger.info(
+        "Saving model and optimizer state at epoch {} to {}".format(
+            iteration, checkpoint_path
+        )
+    )
+    if hasattr(combd, "module"):
+        state_dict_combd = combd.module.state_dict()
+    else:
+        state_dict_combd = combd.state_dict()
+    if hasattr(sbd, "module"):
+        state_dict_sbd = sbd.module.state_dict()
+    else:
+        state_dict_sbd = sbd.state_dict()
+    torch.save(
+        {
+            "combd": state_dict_combd,
+            "sbd": state_dict_sbd,
+            "iteration": iteration,
+            "optimizer": optimizer.state_dict(),
+            "learning_rate": learning_rate,
+        },
+        checkpoint_path,
+    )
+
+
+def summarize(
+    writer,
+    global_step,
+    scalars={},
+    histograms={},
+    images={},
+    audios={},
+    audio_sampling_rate=22050,
+):
+    for k, v in scalars.items():
+        writer.add_scalar(k, v, global_step)
+    for k, v in histograms.items():
+        writer.add_histogram(k, v, global_step)
+    for k, v in images.items():
+        writer.add_image(k, v, global_step, dataformats="HWC")
+    for k, v in audios.items():
+        writer.add_audio(k, v, global_step, audio_sampling_rate)
+
+
+def latest_checkpoint_path(dir_path, regex="G_*.pth"):
+    f_list = glob.glob(os.path.join(dir_path, regex))
+    f_list.sort(key=lambda f: int("".join(filter(str.isdigit, f))))
+    x = f_list[-1]
+    print(x)
+    return x
+
+
+def plot_spectrogram_to_numpy(spectrogram):
+    global MATPLOTLIB_FLAG
+    if not MATPLOTLIB_FLAG:
+        import matplotlib
+
+        matplotlib.use("Agg")
+        MATPLOTLIB_FLAG = True
+        mpl_logger = logging.getLogger("matplotlib")
+        mpl_logger.setLevel(logging.WARNING)
+    import matplotlib.pylab as plt
+    import numpy as np
+
+    fig, ax = plt.subplots(figsize=(10, 2))
+    im = ax.imshow(spectrogram, aspect="auto", origin="lower", interpolation="none")
+    plt.colorbar(im, ax=ax)
+    plt.xlabel("Frames")
+    plt.ylabel("Channels")
+    plt.tight_layout()
+
+    fig.canvas.draw()
+    data = np.fromstring(fig.canvas.tostring_rgb(), dtype=np.uint8, sep="")
+    data = data.reshape(fig.canvas.get_width_height()[::-1] + (3,))
+    plt.close()
+    return data
+
+
+def plot_alignment_to_numpy(alignment, info=None):
+    global MATPLOTLIB_FLAG
+    if not MATPLOTLIB_FLAG:
+        import matplotlib
+
+        matplotlib.use("Agg")
+        MATPLOTLIB_FLAG = True
+        mpl_logger = logging.getLogger("matplotlib")
+        mpl_logger.setLevel(logging.WARNING)
+    import matplotlib.pylab as plt
+    import numpy as np
+
+    fig, ax = plt.subplots(figsize=(6, 4))
+    im = ax.imshow(
+        alignment.transpose(), aspect="auto", origin="lower", interpolation="none"
+    )
+    fig.colorbar(im, ax=ax)
+    xlabel = "Decoder timestep"
+    if info is not None:
+        xlabel += "\n\n" + info
+    plt.xlabel(xlabel)
+    plt.ylabel("Encoder timestep")
+    plt.tight_layout()
+
+    fig.canvas.draw()
+    data = np.fromstring(fig.canvas.tostring_rgb(), dtype=np.uint8, sep="")
+    data = data.reshape(fig.canvas.get_width_height()[::-1] + (3,))
+    plt.close()
+    return data
+
+
+def load_wav_to_torch(full_path):
+    sampling_rate, data = read(full_path)
+    return torch.FloatTensor(data.astype(np.float32)), sampling_rate
+
+
+def load_filepaths_and_text(filename, split="|"):
+    with open(filename, encoding='utf-8') as f:
+        filepaths_and_text = [line.strip().split(split) for line in f]
+        filepaths_and_text = [item for item in filepaths_and_text if len(item) == 5]  # ensure there are 5 items.
+    return filepaths_and_text
+
+
+def get_hparams(init=True):
+    """
+    todo:
+      结尾七人组：
+        保存频率、总epoch                     done
+        bs                                    done
+        pretrainG、pretrainD                  done
+        卡号：os.en["CUDA_VISIBLE_DEVICES"]   done
+        if_latest                             done
+      模型：if_f0                             done
+      采样率：自动选择config                  done
+      是否缓存数据集进GPU:if_cache_data_in_gpu done
+
+      -m:
+        自动决定training_files路径,改掉train_nsf_load_pretrain.py里的hps.data.training_files    done
+      -c不要了
+    """
+    parser = argparse.ArgumentParser()
+    # parser.add_argument('-c', '--config', type=str, default="configs/40k.json",help='JSON file for configuration')
+    parser.add_argument(
+        "-se",
+        "--save_every_epoch",
+        type=int,
+        required=True,
+        help="checkpoint save frequency (epoch)",
+    )
+    parser.add_argument(
+        "-te", "--total_epoch", type=int, required=True, help="total_epoch"
+    )
+    parser.add_argument(
+        "-pg", "--pretrainG", type=str, default="", help="Pretrained Discriminator path"
+    )
+    parser.add_argument(
+        "-pd", "--pretrainD", type=str, default="", help="Pretrained Generator path"
+    )
+    parser.add_argument("-g", "--gpus", type=str, default="0", help="split by -")
+    parser.add_argument(
+        "-bs", "--batch_size", type=int, required=True, help="batch size"
+    )
+    parser.add_argument(
+        "-e", "--experiment_dir", type=str, required=True, help="experiment dir"
+    )  # -m
+    parser.add_argument(
+        "-sr", "--sample_rate", type=str, required=True, help="sample rate, 32k/40k/48k"
+    )
+    parser.add_argument(
+        "-sw",
+        "--save_every_weights",
+        type=str,
+        default="0",
+        help="save the extracted model in weights directory when saving checkpoints",
+    )
+    parser.add_argument(
+        "-v", "--version", type=str, required=True, help="model version"
+    )
+    parser.add_argument(
+        "-f0",
+        "--if_f0",
+        type=int,
+        required=True,
+        help="use f0 as one of the inputs of the model, 1 or 0",
+    )
+    parser.add_argument(
+        "-l",
+        "--if_latest",
+        type=int,
+        required=True,
+        help="if only save the latest G/D pth file, 1 or 0",
+    )
+    parser.add_argument(
+        "-c",
+        "--if_cache_data_in_gpu",
+        type=int,
+        required=True,
+        help="if caching the dataset in GPU memory, 1 or 0",
+    )
+    parser.add_argument(
+        "-li", "--log_interval", type=int, required=True, help="log interval"
+    )
+
+    args = parser.parse_args()
+    name = args.experiment_dir
+    experiment_dir = os.path.join("./logs", args.experiment_dir)
+
+    if not os.path.exists(experiment_dir):
+        os.makedirs(experiment_dir)
+
+    if args.version == "v1" or args.sample_rate == "40k":
+        config_path = "configs/%s.json" % args.sample_rate
+    else:
+        config_path = "configs/%s_v2.json" % args.sample_rate
+    config_save_path = os.path.join(experiment_dir, "config.json")
+    if init:
+        with open(config_path, "r") as f:
+            data = f.read()
+        with open(config_save_path, "w") as f:
+            f.write(data)
+    else:
+        with open(config_save_path, "r") as f:
+            data = f.read()
+    config = json.loads(data)
+
+    hparams = HParams(**config)
+    hparams.model_dir = hparams.experiment_dir = experiment_dir
+    hparams.save_every_epoch = args.save_every_epoch
+    hparams.name = name
+    hparams.total_epoch = args.total_epoch
+    hparams.pretrainG = args.pretrainG
+    hparams.pretrainD = args.pretrainD
+    hparams.version = args.version
+    hparams.gpus = args.gpus
+    hparams.train.batch_size = args.batch_size
+    hparams.sample_rate = args.sample_rate
+    hparams.if_f0 = args.if_f0
+    hparams.if_latest = args.if_latest
+    hparams.save_every_weights = args.save_every_weights
+    hparams.if_cache_data_in_gpu = args.if_cache_data_in_gpu
+    hparams.data.training_files = "%s/filelist.txt" % experiment_dir
+
+    hparams.train.log_interval = args.log_interval
+
+    # Update log_interval in the 'train' section of the config dictionary
+    config["train"]["log_interval"] = args.log_interval
+
+    # Save the updated config back to the config_save_path
+    with open(config_save_path, "w") as f:
+        json.dump(config, f, indent=4)
+
+    return hparams
+
+
+def get_hparams_from_dir(model_dir):
+    config_save_path = os.path.join(model_dir, "config.json")
+    with open(config_save_path, "r") as f:
+        data = f.read()
+    config = json.loads(data)
+
+    hparams = HParams(**config)
+    hparams.model_dir = model_dir
+    return hparams
+
+
+def get_hparams_from_file(config_path):
+    with open(config_path, "r") as f:
+        data = f.read()
+    config = json.loads(data)
+
+    hparams = HParams(**config)
+    return hparams
+
+
+def check_git_hash(model_dir):
+    source_dir = os.path.dirname(os.path.realpath(__file__))
+    if not os.path.exists(os.path.join(source_dir, ".git")):
+        logger.warn(
+            "{} is not a git repository, therefore hash value comparison will be ignored.".format(
+                source_dir
+            )
+        )
+        return
+
+    cur_hash = subprocess.getoutput("git rev-parse HEAD")
+
+    path = os.path.join(model_dir, "githash")
+    if os.path.exists(path):
+        saved_hash = open(path).read()
+        if saved_hash != cur_hash:
+            logger.warn(
+                "git hash values are different. {}(saved) != {}(current)".format(
+                    saved_hash[:8], cur_hash[:8]
+                )
+            )
+    else:
+        open(path, "w").write(cur_hash)
+
+
+def get_logger(model_dir, filename="train.log"):
+    global logger
+    logger = logging.getLogger(os.path.basename(model_dir))
+    logger.setLevel(logging.DEBUG)
+
+    formatter = logging.Formatter("%(asctime)s\t%(name)s\t%(levelname)s\t%(message)s")
+    if not os.path.exists(model_dir):
+        os.makedirs(model_dir)
+    h = logging.FileHandler(os.path.join(model_dir, filename))
+    h.setLevel(logging.DEBUG)
+    h.setFormatter(formatter)
+    logger.addHandler(h)
+    return logger
+
+
+class HParams:
+    def __init__(self, **kwargs):
+        for k, v in kwargs.items():
+            if type(v) == dict:
+                v = HParams(**v)
+            self[k] = v
+
+    def keys(self):
+        return self.__dict__.keys()
+
+    def items(self):
+        return self.__dict__.items()
+
+    def values(self):
+        return self.__dict__.values()
+
+    def __len__(self):
+        return len(self.__dict__)
+
+    def __getitem__(self, key):
+        return getattr(self, key)
+
+    def __setitem__(self, key, value):
+        return setattr(self, key, value)
+
+    def __contains__(self, key):
+        return key in self.__dict__
+
+    def __repr__(self):
+        return self.__dict__.__repr__()
diff --git a/uvr5_weights/.gitignore b/uvr5_weights/.gitignore
new file mode 100644
index 0000000000000000000000000000000000000000..d6b7ef32c8478a48c3994dcadc86837f4371184d
--- /dev/null
+++ b/uvr5_weights/.gitignore
@@ -0,0 +1,2 @@
+*
+!.gitignore
diff --git a/venv.sh b/venv.sh
new file mode 100644
index 0000000000000000000000000000000000000000..aa230992e892292cb8aa5924ecdafc5758f14e95
--- /dev/null
+++ b/venv.sh
@@ -0,0 +1 @@
+python3.8 -m venv .venv
diff --git a/weights/.gitignore b/weights/.gitignore
new file mode 100644
index 0000000000000000000000000000000000000000..d6b7ef32c8478a48c3994dcadc86837f4371184d
--- /dev/null
+++ b/weights/.gitignore
@@ -0,0 +1,2 @@
+*
+!.gitignore